python-igraph-0.8.0/0000755000076500000240000000000013617375001014543 5ustar tamasstaff00000000000000python-igraph-0.8.0/PKG-INFO0000644000076500000240000000360413617375001015643 0ustar tamasstaff00000000000000Metadata-Version: 1.1 Name: python-igraph Version: 0.8.0 Summary: High performance graph data structures and algorithms Home-page: http://pypi.python.org/pypi/python-igraph Author: Tamas Nepusz Author-email: ntamas@gmail.com License: GNU General Public License (GPL) Description: Python interface to the igraph high performance graph library, primarily aimed at complex network research and analysis. Graph plotting functionality is provided by the Cairo library, so make sure you install the Python bindings of Cairo if you want to generate publication-quality graph plots. You can try either `pycairo `_ or `cairocffi `_, ``cairocffi`` is recommended, in particular if you are on Python 3.x because there were bug reports affecting igraph graph plots in Jupyter notebooks when using ``pycairo`` (but not with ``cairocffi``). Unofficial installers for 64-bit Windows machines and/or different Python versions can also be found `here `_. Many thanks to the maintainers of this page! Keywords: graph,network,mathematics,math,graph theory,discrete mathematics Platform: ALL Classifier: Development Status :: 4 - Beta Classifier: Intended Audience :: Developers Classifier: Intended Audience :: Science/Research Classifier: Operating System :: OS Independent Classifier: Programming Language :: C Classifier: Programming Language :: Python Classifier: Topic :: Scientific/Engineering Classifier: Topic :: Scientific/Engineering :: Information Analysis Classifier: Topic :: Scientific/Engineering :: Mathematics Classifier: Topic :: Scientific/Engineering :: Physics Classifier: Topic :: Scientific/Engineering :: Bio-Informatics Classifier: Topic :: Software Development :: Libraries :: Python Modules python-igraph-0.8.0/tests/0000755000076500000240000000000013617375000015704 5ustar tamasstaff00000000000000python-igraph-0.8.0/tests/test_rng.py0000644000076500000240000000233013606025206020077 0ustar tamasstaff00000000000000import random import unittest from igraph import * class FakeRNG(object): @staticmethod def random(): return 0.1 @staticmethod def randint(a, b): return a @staticmethod def gauss(mu, sigma): return 0.3 class InvalidRNG(object): pass class RandomNumberGeneratorTests(unittest.TestCase): def tearDown(self): set_random_number_generator(random) def testSetRandomNumberGenerator(self): set_random_number_generator(FakeRNG) graph = Graph.GRG(10, 0.2) self.assertEqual(graph.vs["x"], [0.1] * 10) self.assertEqual(graph.vs["y"], [0.1] * 10) self.assertRaises(AttributeError, set_random_number_generator, InvalidRNG) def testSeeding(self): state = random.getstate() g1 = Graph.Erdos_Renyi(n=1000, m=5000) random.setstate(state) g2 = Graph.Erdos_Renyi(n=1000, m=5000) self.assertTrue(g1.get_edgelist() == g2.get_edgelist()) def suite(): random_suite = unittest.makeSuite(RandomNumberGeneratorTests) return unittest.TestSuite([random_suite]) def test(): runner = unittest.TextTestRunner() runner.run(suite()) if __name__ == "__main__": test() python-igraph-0.8.0/tests/test_basic.py0000644000076500000240000006051013606025206020376 0ustar tamasstaff00000000000000import unittest from igraph import ( ALL, Graph, IN, InternalError, is_degree_sequence, is_graphical_degree_sequence, Matrix ) try: import numpy as np except ImportError: np = None class BasicTests(unittest.TestCase): def testGraphCreation(self): g = Graph() self.assertTrue(isinstance(g, Graph)) self.assertTrue( g.vcount() == 0 and g.ecount() == 0 and not g.is_directed() ) g = Graph(3, [(0, 1), (1, 2), (2, 0)]) self.assertTrue( g.vcount() == 3 and g.ecount() == 3 and not g.is_directed() and g.is_simple() ) g = Graph(2, [(0, 1), (1, 2), (2, 3)], True) self.assertTrue( g.vcount() == 4 and g.ecount() == 3 and g.is_directed() and g.is_simple() ) g = Graph([(0, 1), (1, 2), (2, 1)]) self.assertTrue( g.vcount() == 3 and g.ecount() == 3 and not g.is_directed() and not g.is_simple() ) g = Graph(((0, 1), (0, 0), (1, 2))) self.assertTrue( g.vcount() == 3 and g.ecount() == 3 and not g.is_directed() and not g.is_simple() ) g = Graph(8, None) self.assertEqual(8, g.vcount()) self.assertEqual(0, g.ecount()) self.assertFalse(g.is_directed()) g = Graph(edges=None) self.assertEqual(0, g.vcount()) self.assertEqual(0, g.ecount()) self.assertFalse(g.is_directed()) self.assertRaises(TypeError, Graph, edgelist=[(1, 2)]) @unittest.skipIf(np is None, "test case depends on NumPy") def testGraphCreationWithNumPy(self): # NumPy array with integers arr = np.array([(0, 1), (1, 2), (2, 3)]) g = Graph(arr, directed=True) self.assertTrue( g.vcount() == 4 and g.ecount() == 3 and g.is_directed() and g.is_simple() ) # Sliced NumPy array -- the sliced array is non-contiguous but we # automatically make it so arr = np.array([(0, 1), (10, 11), (1, 2), (11, 12), (2, 3), (12, 13)]) g = Graph(arr[::2, :], directed=True) self.assertTrue( g.vcount() == 4 and g.ecount() == 3 and g.is_directed() and g.is_simple() ) # 1D NumPy array -- should raise a TypeError because we need a 2D array arr = np.array([0, 1, 1, 2, 2, 3]) self.assertRaises(TypeError, Graph, arr) # 3D NumPy array -- should raise a TypeError because we need a 2D array arr = np.array( [([0, 1], [10, 11]), ([1, 2], [11, 12]), ([2, 3], [12, 13])] ) self.assertRaises(TypeError, Graph, arr) # NumPy array with strings -- should be a casting error arr = np.array([("a", "b"), ("c", "d"), ("e", "f")]) self.assertRaises(ValueError, Graph, arr) def testAddVertex(self): g = Graph() vertex = g.add_vertex() self.assertTrue(g.vcount() == 1 and g.ecount() == 0) self.assertEqual(0, vertex.index) self.assertFalse("name" in g.vertex_attributes()) vertex = g.add_vertex("foo") self.assertTrue(g.vcount() == 2 and g.ecount() == 0) self.assertEqual(1, vertex.index) self.assertTrue("name" in g.vertex_attributes()) self.assertEqual(g.vs["name"], [None, "foo"]) vertex = g.add_vertex(3) self.assertTrue(g.vcount() == 3 and g.ecount() == 0) self.assertEqual(2, vertex.index) self.assertTrue("name" in g.vertex_attributes()) self.assertEqual(g.vs["name"], [None, "foo", 3]) vertex = g.add_vertex(name="bar") self.assertTrue(g.vcount() == 4 and g.ecount() == 0) self.assertEqual(3, vertex.index) self.assertTrue("name" in g.vertex_attributes()) self.assertEqual(g.vs["name"], [None, "foo", 3, "bar"]) vertex = g.add_vertex(name="frob", spam="cheese", ham=42) self.assertTrue(g.vcount() == 5 and g.ecount() == 0) self.assertEqual(4, vertex.index) self.assertEqual( sorted(g.vertex_attributes()), ["ham", "name", "spam"] ) self.assertEqual(g.vs["spam"], [None]*4 + ["cheese"]) self.assertEqual(g.vs["ham"], [None]*4 + [42]) def testAddVertices(self): g = Graph() g.add_vertices(2) self.assertTrue(g.vcount() == 2 and g.ecount() == 0) g.add_vertices("spam") self.assertTrue(g.vcount() == 3 and g.ecount() == 0) self.assertEqual(g.vs[2]["name"], "spam") g.add_vertices(["bacon", "eggs"]) self.assertTrue(g.vcount() == 5 and g.ecount() == 0) self.assertEqual(g.vs[2:]["name"], ["spam", "bacon", "eggs"]) def testDeleteVertices(self): g = Graph([(0, 1), (1, 2), (2, 3), (0, 2), (3, 4), (4, 5)]) self.assertEqual(6, g.vcount()) self.assertEqual(6, g.ecount()) # Delete a single vertex g.delete_vertices(4) self.assertEqual(5, g.vcount()) self.assertEqual(4, g.ecount()) # Delete multiple vertices g.delete_vertices([1, 3]) self.assertEqual(3, g.vcount()) self.assertEqual(1, g.ecount()) # Delete a vertex sequence g.delete_vertices(g.vs[:2]) self.assertEqual(1, g.vcount()) self.assertEqual(0, g.ecount()) # Delete a single vertex object g.vs[0].delete() self.assertEqual(0, g.vcount()) self.assertEqual(0, g.ecount()) # Delete vertices by name g = Graph.Full(4) g.vs["name"] = ["spam", "bacon", "eggs", "ham"] self.assertEqual(4, g.vcount()) g.delete_vertices("spam") self.assertEqual(3, g.vcount()) g.delete_vertices(["bacon", "ham"]) self.assertEqual(1, g.vcount()) # Deleting a nonexistent vertex self.assertRaises(ValueError, g.delete_vertices, "no-such-vertex") self.assertRaises(InternalError, g.delete_vertices, 2) def testAddEdge(self): g = Graph() g.add_vertices(["spam", "bacon", "eggs", "ham"]) edge = g.add_edge(0, 1) self.assertEqual(g.vcount(), 4) self.assertEqual(g.get_edgelist(), [(0, 1)]) self.assertEqual(0, edge.index) self.assertEqual((0, 1), edge.tuple) edge = g.add_edge(1, 2, foo="bar") self.assertEqual(g.vcount(), 4) self.assertEqual(g.get_edgelist(), [(0, 1), (1, 2)]) self.assertEqual(1, edge.index) self.assertEqual((1, 2), edge.tuple) self.assertEqual("bar", edge["foo"]) self.assertEqual([None, "bar"], g.es["foo"]) def testAddEdges(self): g = Graph() g.add_vertices(["spam", "bacon", "eggs", "ham"]) g.add_edges([(0, 1)]) self.assertEqual(g.vcount(), 4) self.assertEqual(g.get_edgelist(), [(0, 1)]) g.add_edges([(1, 2), (2, 3), (1, 3)]) self.assertEqual(g.vcount(), 4) self.assertEqual(g.get_edgelist(), [(0, 1), (1, 2), (2, 3), (1, 3)]) g.add_edges([("spam", "eggs"), ("spam", "ham")]) self.assertEqual(g.vcount(), 4) self.assertEqual(g.get_edgelist(), [ (0, 1), (1, 2), (2, 3), (1, 3), (0, 2), (0, 3) ]) def testDeleteEdges(self): g = Graph.Famous("petersen") g.vs["name"] = list("ABCDEFGHIJ") el = g.get_edgelist() self.assertEqual(15, g.ecount()) # Deleting single edge g.delete_edges(14) el[14:] = [] self.assertEqual(14, g.ecount()) self.assertEqual(el, g.get_edgelist()) # Deleting multiple edges g.delete_edges([2, 5, 7]) el[7:8] = [] el[5:6] = [] el[2:3] = [] self.assertEqual(11, g.ecount()) self.assertEqual(el, g.get_edgelist()) # Deleting edge object g.es[6].delete() el[6:7] = [] self.assertEqual(10, g.ecount()) self.assertEqual(el, g.get_edgelist()) # Deleting edge sequence object g.es[1:4].delete() el[1:4] = [] self.assertEqual(7, g.ecount()) self.assertEqual(el, g.get_edgelist()) # Deleting edges by IDs g.delete_edges([(2, 7), (5, 8)]) el[4:5] = [] el[1:2] = [] self.assertEqual(5, g.ecount()) self.assertEqual(el, g.get_edgelist()) # Deleting edges by names g.delete_edges([("D", "I"), ("G", "I")]) el[3:4] = [] el[1:2] = [] self.assertEqual(3, g.ecount()) self.assertEqual(el, g.get_edgelist()) # Deleting nonexistent edges self.assertRaises(ValueError, g.delete_edges, [(0, 2)]) self.assertRaises(ValueError, g.delete_edges, [("A", "C")]) self.assertRaises(ValueError, g.delete_edges, [(0, 15)]) def testGraphGetEid(self): g = Graph.Famous("petersen") g.vs["name"] = list("ABCDEFGHIJ") edges_to_ids = dict((v, k) for k, v in enumerate(g.get_edgelist())) for (source, target), edge_id in edges_to_ids.items(): source_name, target_name = g.vs[(source, target)]["name"] self.assertEqual(edge_id, g.get_eid(source, target)) self.assertEqual(edge_id, g.get_eid(source_name, target_name)) self.assertRaises(InternalError, g.get_eid, 0, 11) self.assertRaises(ValueError, g.get_eid, "A", "K") def testGraphGetEids(self): g = Graph.Famous("petersen") eids = g.get_eids(pairs=[(0, 1), (0, 5), (1, 6), (4, 9), (8, 6)]) self.assertTrue(eids == [0, 2, 4, 9, 12]) eids = g.get_eids(path=[0, 1, 2, 3, 4]) self.assertTrue(eids == [0, 3, 5, 7]) eids = g.get_eids(pairs=[(7, 9), (9, 6)], path=[7, 9, 6]) self.assertTrue(eids == [14, 13, 14, 13]) self.assertRaises(InternalError, g.get_eids, pairs=[(0, 1), (0, 2)]) def testAdjacency(self): g = Graph(4, [(0, 1), (1, 2), (2, 0), (2, 3)], directed=True) self.assertTrue(g.neighbors(2) == [0, 1, 3]) self.assertTrue(g.predecessors(2) == [1]) self.assertTrue(g.successors(2) == [0, 3]) self.assertTrue(g.get_adjlist() == [[1], [2], [0, 3], []]) self.assertTrue(g.get_adjlist(IN) == [[2], [0], [1], [2]]) self.assertTrue(g.get_adjlist(ALL) == [[1, 2], [0, 2], [0, 1, 3], [2]]) def testEdgeIncidency(self): g = Graph(4, [(0, 1), (1, 2), (2, 0), (2, 3)], directed=True) self.assertTrue(g.incident(2) == [2, 3]) self.assertTrue(g.incident(2, IN) == [1]) self.assertTrue(g.incident(2, ALL) == [2, 3, 1]) self.assertTrue(g.get_inclist() == [[0], [1], [2, 3], []]) self.assertTrue(g.get_inclist(IN) == [[2], [0], [1], [3]]) self.assertTrue(g.get_inclist(ALL) == [[0, 2], [1, 0], [2, 3, 1], [3]]) def testMultiplesLoops(self): g = Graph.Tree(7, 2) # has_multiple self.assertFalse(g.has_multiple()) g.add_vertices(1) g.add_edges([(0, 1), (7, 7), (6, 6), (6, 6), (6, 6)]) # is_loop self.assertTrue(g.is_loop() == [ False, False, False, False, False, False, False, True, True, True, True ]) self.assertTrue(g.is_loop(g.ecount()-2)) self.assertTrue(g.is_loop(range(6, 8)) == [False, True]) # is_multiple self.assertTrue(g.is_multiple() == [ False, False, False, False, False, False, True, False, False, True, True ]) # has_multiple self.assertTrue(g.has_multiple()) # count_multiple self.assertTrue( g.count_multiple() == [2, 1, 1, 1, 1, 1, 2, 1, 3, 3, 3] ) self.assertTrue(g.count_multiple(g.ecount()-1) == 3) self.assertTrue(g.count_multiple(range(2, 5)) == [1, 1, 1]) # check if a mutual directed edge pair is reported as multiple g = Graph(2, [(0, 1), (1, 0)], directed=True) self.assertTrue(g.is_multiple() == [False, False]) def testPickling(self): import pickle g = Graph([(0, 1), (1, 2)]) g["data"] = "abcdef" g.vs["data"] = [3, 4, 5] g.es["data"] = ["A", "B"] g.custom_data = None pickled = pickle.dumps(g) g2 = pickle.loads(pickled) self.assertTrue(g["data"] == g2["data"]) self.assertTrue(g.vs["data"] == g2.vs["data"]) self.assertTrue(g.es["data"] == g2.es["data"]) self.assertTrue(g.vcount() == g2.vcount()) self.assertTrue(g.ecount() == g2.ecount()) self.assertTrue(g.is_directed() == g2.is_directed()) self.assertTrue(g2.custom_data == g.custom_data) def testHashing(self): g = Graph([(0, 1), (1, 2)]) self.assertRaises(TypeError, hash, g) def testIteration(self): g = Graph() self.assertRaises(TypeError, iter, g) class DatatypeTests(unittest.TestCase): def testMatrix(self): m = Matrix([[1, 2, 3], [4, 5], [6, 7, 8]]) self.assertTrue(m.shape == (3, 3)) # Reading data self.assertTrue(m.data == [[1, 2, 3], [4, 5, 0], [6, 7, 8]]) self.assertTrue(m[1, 1] == 5) self.assertTrue(m[0] == [1, 2, 3]) self.assertTrue(m[0, :] == [1, 2, 3]) self.assertTrue(m[:, 0] == [1, 4, 6]) self.assertTrue(m[2, 0:2] == [6, 7]) self.assertTrue(m[:, :].data == [[1, 2, 3], [4, 5, 0], [6, 7, 8]]) self.assertTrue(m[:, 1:3].data == [[2, 3], [5, 0], [7, 8]]) # Writing data m[1, 1] = 10 self.assertTrue(m[1, 1] == 10) m[1] = (6, 5, 4) self.assertTrue(m[1] == [6, 5, 4]) m[1:3] = [[4, 5, 6], (7, 8, 9)] self.assertTrue(m[1:3].data == [[4, 5, 6], [7, 8, 9]]) # Minimums and maximums self.assertTrue(m.min() == 1) self.assertTrue(m.max() == 9) self.assertTrue(m.min(0) == [1, 2, 3]) self.assertTrue(m.max(0) == [7, 8, 9]) self.assertTrue(m.min(1) == [1, 4, 7]) self.assertTrue(m.max(1) == [3, 6, 9]) # Special constructors m = Matrix.Fill(2, (3, 3)) self.assertTrue(m.min() == 2 and m.max() == 2 and m.shape == (3, 3)) m = Matrix.Zero(5, 4) self.assertTrue(m.min() == 0 and m.max() == 0 and m.shape == (5, 4)) m = Matrix.Identity(3) self.assertTrue(m.data == [[1, 0, 0], [0, 1, 0], [0, 0, 1]]) m = Matrix.Identity(3, 2) self.assertTrue(m.data == [[1, 0], [0, 1], [0, 0]]) # Conversion to string m = Matrix.Identity(3) self.assertTrue(str(m) == "[[1, 0, 0]\n [0, 1, 0]\n [0, 0, 1]]") self.assertTrue(repr(m) == "Matrix([[1, 0, 0], [0, 1, 0], [0, 0, 1]])") class GraphDictListTests(unittest.TestCase): def setUp(self): self.vertices = [ {"name": "Alice", "age": 48, "gender": "F"}, {"name": "Bob", "age": 33, "gender": "M"}, {"name": "Cecil", "age": 45, "gender": "F"}, {"name": "David", "age": 34, "gender": "M"} ] self.edges = [ {"source": "Alice", "target": "Bob", "friendship": 4, "advice": 4}, {"source": "Cecil", "target": "Bob", "friendship": 5, "advice": 5}, { "source": "Cecil", "target": "Alice", "friendship": 5, "advice": 5 }, { "source": "David", "target": "Alice", "friendship": 2, "advice": 4 }, {"source": "David", "target": "Bob", "friendship": 1, "advice": 2} ] def testGraphFromDictList(self): g = Graph.DictList(self.vertices, self.edges) self.checkIfOK(g, "name") g = Graph.DictList(self.vertices, self.edges, iterative=True) self.checkIfOK(g, "name") def testGraphFromDictIterator(self): g = Graph.DictList(iter(self.vertices), iter(self.edges)) self.checkIfOK(g, "name") g = Graph.DictList( iter(self.vertices), iter(self.edges), iterative=True ) self.checkIfOK(g, "name") def testGraphFromDictIteratorNoVertices(self): g = Graph.DictList(None, iter(self.edges)) self.checkIfOK(g, "name", check_vertex_attrs=False) g = Graph.DictList(None, iter(self.edges), iterative=True) self.checkIfOK(g, "name", check_vertex_attrs=False) def testGraphFromDictListExtraVertexName(self): del self.vertices[2:] # No data for "Cecil" and "David" g = Graph.DictList(self.vertices, self.edges) self.assertTrue( g.vcount() == 4 and g.ecount() == 5 and not g.is_directed() ) self.assertTrue(g.vs["name"] == ["Alice", "Bob", "Cecil", "David"]) self.assertTrue(g.vs["age"] == [48, 33, None, None]) self.assertTrue(g.vs["gender"] == ["F", "M", None, None]) self.assertTrue(g.es["friendship"] == [4, 5, 5, 2, 1]) self.assertTrue(g.es["advice"] == [4, 5, 5, 4, 2]) self.assertTrue(g.get_edgelist() == [ (0, 1), (1, 2), (0, 2), (0, 3), (1, 3) ]) def testGraphFromDictListAlternativeName(self): for vdata in self.vertices: vdata["name_alternative"] = vdata["name"] del vdata["name"] g = Graph.DictList( self.vertices, self.edges, vertex_name_attr="name_alternative" ) self.checkIfOK(g, "name_alternative") g = Graph.DictList( self.vertices, self.edges, vertex_name_attr="name_alternative", iterative=True ) self.checkIfOK(g, "name_alternative") def checkIfOK(self, g, name_attr, check_vertex_attrs=True): self.assertTrue( g.vcount() == 4 and g.ecount() == 5 and not g.is_directed() ) self.assertTrue(g.get_edgelist() == [ (0, 1), (1, 2), (0, 2), (0, 3), (1, 3) ]) self.assertTrue(g.vs[name_attr] == ["Alice", "Bob", "Cecil", "David"]) if check_vertex_attrs: self.assertTrue(g.vs["age"] == [48, 33, 45, 34]) self.assertTrue(g.vs["gender"] == ["F", "M", "F", "M"]) self.assertTrue(g.es["friendship"] == [4, 5, 5, 2, 1]) self.assertTrue(g.es["advice"] == [4, 5, 5, 4, 2]) class GraphTupleListTests(unittest.TestCase): def setUp(self): self.edges = [ ("Alice", "Bob", 4, 4), ("Cecil", "Bob", 5, 5), ("Cecil", "Alice", 5, 5), ("David", "Alice", 2, 4), ("David", "Bob", 1, 2) ] def testGraphFromTupleList(self): g = Graph.TupleList(self.edges) self.checkIfOK(g, "name", ()) def testGraphFromTupleListWithEdgeAttributes(self): g = Graph.TupleList(self.edges, edge_attrs=("friendship", "advice")) self.checkIfOK(g, "name", ("friendship", "advice")) g = Graph.TupleList(self.edges, edge_attrs=("friendship", )) self.checkIfOK(g, "name", ("friendship", )) g = Graph.TupleList(self.edges, edge_attrs="friendship") self.checkIfOK(g, "name", ("friendship", )) def testGraphFromTupleListWithDifferentNameAttribute(self): g = Graph.TupleList(self.edges, vertex_name_attr="spam") self.checkIfOK(g, "spam", ()) def testGraphFromTupleListWithWeights(self): g = Graph.TupleList(self.edges, weights=True) self.checkIfOK(g, "name", ("weight", )) g = Graph.TupleList(self.edges, weights="friendship") self.checkIfOK(g, "name", ("friendship", )) g = Graph.TupleList(self.edges, weights=False) self.checkIfOK(g, "name", ()) self.assertRaises( ValueError, Graph.TupleList, [self.edges], weights=True, edge_attrs="friendship" ) def testNoneForMissingAttributes(self): g = Graph.TupleList( self.edges, edge_attrs=("friendship", "advice", "spam") ) self.checkIfOK(g, "name", ("friendship", "advice", "spam")) def checkIfOK(self, g, name_attr, edge_attrs): self.assertTrue( g.vcount() == 4 and g.ecount() == 5 and not g.is_directed() ) self.assertTrue(g.get_edgelist() == [ (0, 1), (1, 2), (0, 2), (0, 3), (1, 3) ]) self.assertTrue(g.attributes() == []) self.assertTrue(g.vertex_attributes() == [name_attr]) self.assertTrue(g.vs[name_attr] == ["Alice", "Bob", "Cecil", "David"]) if edge_attrs: self.assertTrue(sorted(g.edge_attributes()) == sorted(edge_attrs)) self.assertTrue(g.es[edge_attrs[0]] == [4, 5, 5, 2, 1]) if len(edge_attrs) > 1: self.assertTrue(g.es[edge_attrs[1]] == [4, 5, 5, 4, 2]) if len(edge_attrs) > 2: self.assertTrue(g.es[edge_attrs[2]] == [None] * 5) else: self.assertTrue(g.edge_attributes() == []) class DegreeSequenceTests(unittest.TestCase): def testIsDegreeSequence(self): self.assertTrue(is_degree_sequence([])) self.assertTrue(is_degree_sequence([], [])) self.assertTrue(is_degree_sequence([0])) self.assertTrue(is_degree_sequence([0], [0])) self.assertFalse(is_degree_sequence([1])) self.assertTrue(is_degree_sequence([1], [1])) self.assertTrue(is_degree_sequence([2])) self.assertFalse(is_degree_sequence([2, 1, 1, 1])) self.assertTrue(is_degree_sequence([2, 1, 1, 1], [1, 1, 1, 2])) self.assertFalse(is_degree_sequence([2, 1, -2])) self.assertFalse(is_degree_sequence([2, 1, 1, 1], [1, 1, 1, -2])) self.assertTrue(is_degree_sequence([3, 3, 3, 3, 3, 3, 3, 3, 3, 3])) self.assertTrue(is_degree_sequence( [3, 3, 3, 3, 3, 3, 3, 3, 3, 3], None )) self.assertFalse(is_degree_sequence([3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3])) self.assertTrue(is_degree_sequence( [3, 3, 3, 3, 3, 3, 3, 3, 3, 3], [4, 3, 2, 3, 4, 4, 2, 2, 4, 2] )) def testIsGraphicalSequence(self): self.assertTrue(is_graphical_degree_sequence([])) self.assertTrue(is_graphical_degree_sequence([], [])) self.assertTrue(is_graphical_degree_sequence([0])) self.assertTrue(is_graphical_degree_sequence([0], [0])) self.assertFalse(is_graphical_degree_sequence([1])) self.assertFalse(is_graphical_degree_sequence([1], [1])) self.assertFalse(is_graphical_degree_sequence([2])) self.assertFalse(is_graphical_degree_sequence([2, 1, 1, 1])) self.assertTrue(is_graphical_degree_sequence( [2, 1, 1, 1], [1, 1, 1, 2] )) self.assertFalse(is_graphical_degree_sequence([2, 1, -2])) self.assertFalse(is_graphical_degree_sequence( [2, 1, 1, 1], [1, 1, 1, -2] )) self.assertTrue(is_graphical_degree_sequence( [3, 3, 3, 3, 3, 3, 3, 3, 3, 3] )) self.assertTrue(is_graphical_degree_sequence( [3, 3, 3, 3, 3, 3, 3, 3, 3, 3], None )) self.assertFalse(is_graphical_degree_sequence( [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3] )) self.assertTrue(is_graphical_degree_sequence( [3, 3, 3, 3, 3, 3, 3, 3, 3, 3], [4, 3, 2, 3, 4, 4, 2, 2, 4, 2] )) self.assertTrue(is_graphical_degree_sequence([3, 3, 3, 3, 4])) class InheritedGraph(Graph): def __init__(self, *args, **kwds): super(InheritedGraph, self).__init__(*args, **kwds) self.init_called = True def __new__(cls, *args, **kwds): result = Graph.__new__(cls, *args, **kwds) result.new_called = True return result class InheritanceTests(unittest.TestCase): def testInitCalledProperly(self): g = InheritedGraph() self.assertTrue(getattr(g, "init_called", False)) def testNewCalledProperly(self): g = InheritedGraph() self.assertTrue(getattr(g, "new_called", False)) def testInitCalledProperlyWithClassMethod(self): g = InheritedGraph.Tree(3, 2) self.assertTrue(getattr(g, "init_called", False)) def testNewCalledProperlyWithClassMethod(self): g = InheritedGraph.Tree(3, 2) self.assertTrue(getattr(g, "new_called", False)) def suite(): basic_suite = unittest.makeSuite(BasicTests) datatype_suite = unittest.makeSuite(DatatypeTests) graph_dict_list_suite = unittest.makeSuite(GraphDictListTests) graph_tuple_list_suite = unittest.makeSuite(GraphTupleListTests) degree_sequence_suite = unittest.makeSuite(DegreeSequenceTests) inheritance_suite = unittest.makeSuite(InheritanceTests) return unittest.TestSuite([ basic_suite, datatype_suite, graph_dict_list_suite, graph_tuple_list_suite, degree_sequence_suite, inheritance_suite ]) def test(): runner = unittest.TextTestRunner() runner.run(suite()) if __name__ == "__main__": test() python-igraph-0.8.0/tests/test_iterators.py0000644000076500000240000000133713606025206021333 0ustar tamasstaff00000000000000import unittest from igraph import * class IteratorTests(unittest.TestCase): def testBFS(self): g=Graph.Tree(10, 2) vs=[v.index for v in g.bfsiter(0)] self.assertEqual(vs, [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]) vs=[(v.index,dist,parent) for v,dist,parent in g.bfsiter(0, advanced=True)] vs=[(v,d,p.index) for v,d,p in vs if p != None] self.assertEqual(vs, [(1,1,0), (2,1,0), (3,2,1), (4,2,1), \ (5,2,2), (6,2,2), (7,3,3), (8,3,3), (9,3,4)]) def suite(): iterator_suite = unittest.makeSuite(IteratorTests) return unittest.TestSuite([iterator_suite]) def test(): runner = unittest.TextTestRunner() runner.run(suite()) if __name__ == "__main__": test() python-igraph-0.8.0/tests/test_atlas.py0000644000076500000240000001100613606025335020420 0ustar tamasstaff00000000000000from __future__ import division import warnings import unittest from igraph import * class AtlasTestBase(object): def testPageRank(self): for idx, g in enumerate(self.__class__.graphs): try: pr = g.pagerank() except Exception as ex: self.assertTrue(False, msg="PageRank calculation threw exception for graph #%d: %s" % (idx, ex)) raise if g.vcount() == 0: self.assertEqual([], pr) continue self.assertAlmostEqual(1.0, sum(pr), places=5, \ msg="PageRank sum is not 1.0 for graph #%d (%r)" % (idx, pr)) self.assertTrue(min(pr) >= 0, \ msg="Minimum PageRank is less than 0 for graph #%d (%r)" % (idx, pr)) def testEigenvectorCentrality(self): # Temporarily turn off the warning handler because g.evcent() will print # a warning for DAGs warnings.simplefilter("ignore") try: for idx, g in enumerate(self.__class__.graphs): if idx in self.__class__.skip_graphs: # Skip this graph; it causes lots of problems and I don't know why continue try: ec, eval = g.evcent(return_eigenvalue=True) except Exception as ex: self.assertTrue(False, msg="Eigenvector centrality threw exception for graph #%d: %s" % (idx, ex)) raise if g.vcount() == 0: self.assertEqual([], ec) continue if not g.is_connected(): # Skip disconnected graphs; this will be fixed in igraph 0.7 continue n = g.vcount() if abs(eval) < 1e-4: self.assertTrue(min(ec) >= -1e-10, msg="Minimum eigenvector centrality is smaller than 0 for graph #%d" % idx) self.assertTrue(max(ec) <= 1, msg="Maximum eigenvector centrality is greater than 1 for graph #%d" % idx) continue self.assertAlmostEqual(max(ec), 1, places=7, \ msg="Maximum eigenvector centrality is %r (not 1) for graph #%d (%r)" % \ (max(ec), idx, ec)) self.assertTrue(min(ec) >= 0, \ msg="Minimum eigenvector centrality is less than 0 for graph #%d" % idx) ec2 = [sum(ec[u.index] for u in v.predecessors()) for v in g.vs] for i in range(n): self.assertAlmostEqual(ec[i] * eval, ec2[i], places=7, \ msg="Eigenvector centrality in graph #%d seems to be invalid "\ "for vertex %d" % (idx, i)) finally: # Reset the warning handler warnings.resetwarnings() def testHubScore(self): for idx, g in enumerate(self.__class__.graphs): sc = g.hub_score() if g.vcount() == 0: self.assertEqual([], sc) continue self.assertAlmostEqual(max(sc), 1, places=7, \ msg="Maximum authority score is not 1 for graph #%d" % idx) self.assertTrue(min(sc) >= 0, \ msg="Minimum hub score is less than 0 for graph #%d" % idx) def testAuthorityScore(self): for idx, g in enumerate(self.__class__.graphs): sc = g.authority_score() if g.vcount() == 0: self.assertEqual([], sc) continue self.assertAlmostEqual(max(sc), 1, places=7, \ msg="Maximum authority score is not 1 for graph #%d" % idx) self.assertTrue(min(sc) >= 0, \ msg="Minimum authority score is less than 0 for graph #%d" % idx) class GraphAtlasTests(unittest.TestCase, AtlasTestBase): graphs = [Graph.Atlas(i) for i in range(1253)] skip_graphs = set([180]) class IsoclassTests(unittest.TestCase, AtlasTestBase): graphs = [Graph.Isoclass(3, i, directed=True) for i in range(16)] + \ [Graph.Isoclass(4, i, directed=True) for i in range(218)] skip_graphs = set([136]) def suite(): atlas_suite = unittest.makeSuite(GraphAtlasTests) isoclass_suite = unittest.makeSuite(IsoclassTests) return unittest.TestSuite([atlas_suite, isoclass_suite]) def test(): runner = unittest.TextTestRunner() runner.run(suite()) if __name__ == "__main__": test() python-igraph-0.8.0/tests/test_walks.py0000644000076500000240000000426113606025206020437 0ustar tamasstaff00000000000000import random import unittest from igraph import Graph, InternalError class RandomWalkTests(unittest.TestCase): def validate_walk(self, g, walk, start, length, mode="out"): prev = None for vertex in walk: if prev is not None: self.assertTrue(vertex in g.neighbors(prev, mode=mode)) else: self.assertEqual(start, vertex) prev = vertex def testRandomWalkUndirected(self): g = Graph.GRG(100, 0.2) for i in range(100): start = random.randint(0, g.vcount()-1) length = random.randint(0, 10) walk = g.random_walk(start, length) self.validate_walk(g, walk, start, length) def testRandomWalkDirectedOut(self): g = Graph.Tree(121, 3, mode="out") mode = "out" for i in range(100): start = 0 length = random.randint(0, 4) walk = g.random_walk(start, length, mode) self.validate_walk(g, walk, start, length, mode) def testRandomWalkDirectedIn(self): g = Graph.Tree(121, 3, mode="out") mode = "in" for i in range(100): start = random.randint(40, g.vcount()-1) length = random.randint(0, 4) walk = g.random_walk(start, length, mode) self.validate_walk(g, walk, start, length, mode) def testRandomWalkDirectedAll(self): g = Graph.Tree(121, 3, mode="out") mode = "all" for i in range(100): start = random.randint(0, g.vcount()-1) length = random.randint(0, 10) walk = g.random_walk(start, length, mode) self.validate_walk(g, walk, start, length, mode) def testRandomWalkStuck(self): g = Graph.Ring(10, circular=False, directed=True) walk = g.random_walk(5, 20) self.assertEqual([5, 6, 7, 8, 9], walk) self.assertRaises(InternalError, g.random_walk, 5, 20, stuck="error") def suite(): random_walk_suite = unittest.makeSuite(RandomWalkTests) return unittest.TestSuite([random_walk_suite]) def test(): runner = unittest.TextTestRunner() runner.run(suite()) if __name__ == "__main__": test() python-igraph-0.8.0/tests/test_unicode_issues.py0000644000076500000240000000131513606025376022344 0ustar tamasstaff00000000000000from __future__ import unicode_literals import unittest from igraph import Graph class UnicodeTests(unittest.TestCase): def testBug128(self): y = [1, 4, 9] g = Graph(n=len(y), directed=True, vertex_attrs={'y': y}) self.assertEqual(3, g.vcount()) g.add_vertices(1) # Bug #128 would prevent us from reaching the next statement # because an exception would have been thrown here self.assertEqual(4, g.vcount()) def suite(): generator_suite = unittest.makeSuite(UnicodeTests) return unittest.TestSuite([generator_suite]) def test(): runner = unittest.TextTestRunner() runner.run(suite()) if __name__ == "__main__": test() python-igraph-0.8.0/tests/test_bipartite.py0000644000076500000240000001333613606025206021304 0ustar tamasstaff00000000000000import unittest from igraph import * class BipartiteTests(unittest.TestCase): def testCreateBipartite(self): g = Graph.Bipartite([0, 1]*5, [(0,1),(2,3),(4,5),(6,7),(8,9)]) self.assertTrue(g.vcount() == 10 and g.ecount() == 5 and g.is_directed() == False) self.assertTrue(g.is_bipartite()) self.assertTrue(g.vs["type"] == [False, True]*5) def testFullBipartite(self): g = Graph.Full_Bipartite(10, 5) self.assertTrue(g.vcount() == 15 and g.ecount() == 50 and g.is_directed() == False) expected = sorted([(i, j) for i in range(10) for j in range(10, 15)]) self.assertTrue(sorted(g.get_edgelist()) == expected) self.assertTrue(g.vs["type"] == [False]*10 + [True]*5) g = Graph.Full_Bipartite(10, 5, directed=True, mode=OUT) self.assertTrue(g.vcount() == 15 and g.ecount() == 50 and g.is_directed() == True) self.assertTrue(sorted(g.get_edgelist()) == expected) self.assertTrue(g.vs["type"] == [False]*10 + [True]*5) g = Graph.Full_Bipartite(10, 5, directed=True, mode=IN) self.assertTrue(g.vcount() == 15 and g.ecount() == 50 and g.is_directed() == True) self.assertTrue(sorted(g.get_edgelist()) == sorted([(i,j) for j, i in expected])) self.assertTrue(g.vs["type"] == [False]*10 + [True]*5) g = Graph.Full_Bipartite(10, 5, directed=True) self.assertTrue(g.vcount() == 15 and g.ecount() == 100 and g.is_directed() == True) expected.extend([(j, i) for i, j in expected]) expected.sort() self.assertTrue(sorted(g.get_edgelist()) == expected) self.assertTrue(g.vs["type"] == [False]*10 + [True]*5) def testIncidence(self): g = Graph.Incidence([[0, 1, 1], [1, 2, 0]]) self.assertTrue(g.vcount() == 5 and g.ecount() == 4 and g.is_directed() == False) self.assertTrue(g.vs["type"] == [False]*2 + [True]*3) self.assertTrue(sorted(g.get_edgelist()) == [(0,3),(0,4),(1,2),(1,3)]) g = Graph.Incidence([[0, 1, 1], [1, 2, 0]], multiple=True) self.assertTrue(g.vcount() == 5 and g.ecount() == 5 and g.is_directed() == False) self.assertTrue(g.vs["type"] == [False]*2 + [True]*3) self.assertTrue(sorted(g.get_edgelist()) == [(0,3),(0,4),(1,2),(1,3),(1,3)]) g = Graph.Incidence([[0, 1, 1], [1, 2, 0]], directed=True) self.assertTrue(g.vcount() == 5 and g.ecount() == 4 and g.is_directed() == True) self.assertTrue(g.vs["type"] == [False]*2 + [True]*3) self.assertTrue(sorted(g.get_edgelist()) == [(0,3),(0,4),(1,2),(1,3)]) g = Graph.Incidence([[0, 1, 1], [1, 2, 0]], directed=True, mode="in") self.assertTrue(g.vcount() == 5 and g.ecount() == 4 and g.is_directed() == True) self.assertTrue(g.vs["type"] == [False]*2 + [True]*3) self.assertTrue(sorted(g.get_edgelist()) == [(2,1),(3,0),(3,1),(4,0)]) def testGetIncidence(self): mat = [[0, 1, 1], [1, 1, 0]] v1, v2 = [0, 1], [2, 3, 4] g = Graph.Incidence(mat) self.assertTrue(g.get_incidence() == (mat, v1, v2)) g.vs["type2"] = g.vs["type"] self.assertTrue(g.get_incidence("type2") == (mat, v1, v2)) self.assertTrue(g.get_incidence(g.vs["type2"]) == (mat, v1, v2)) def testBipartiteProjection(self): g = Graph.Full_Bipartite(10, 5) g1, g2 = g.bipartite_projection() self.assertTrue(g1.isomorphic(Graph.Full(10))) self.assertTrue(g2.isomorphic(Graph.Full(5))) self.assertTrue(g.bipartite_projection(which=0).isomorphic(g1)) self.assertTrue(g.bipartite_projection(which=1).isomorphic(g2)) self.assertTrue(g.bipartite_projection(which=False).isomorphic(g1)) self.assertTrue(g.bipartite_projection(which=True).isomorphic(g2)) self.assertTrue(g1.es["weight"] == [5] * 45) self.assertTrue(g2.es["weight"] == [10] * 10) self.assertTrue(g.bipartite_projection_size() == (10, 45, 5, 10)) g1, g2 = g.bipartite_projection(probe1=10) self.assertTrue(g1.isomorphic(Graph.Full(5))) self.assertTrue(g2.isomorphic(Graph.Full(10))) self.assertTrue(g.bipartite_projection(which=0).isomorphic(g2)) self.assertTrue(g.bipartite_projection(which=1).isomorphic(g1)) self.assertTrue(g.bipartite_projection(which=False).isomorphic(g2)) self.assertTrue(g.bipartite_projection(which=True).isomorphic(g1)) g1, g2 = g.bipartite_projection(multiplicity=False) self.assertTrue(g1.isomorphic(Graph.Full(10))) self.assertTrue(g2.isomorphic(Graph.Full(5))) self.assertTrue(g.bipartite_projection(which=0).isomorphic(g1)) self.assertTrue(g.bipartite_projection(which=1).isomorphic(g2)) self.assertTrue(g.bipartite_projection(which=False).isomorphic(g1)) self.assertTrue(g.bipartite_projection(which=True).isomorphic(g2)) self.assertTrue("weight" not in g1.edge_attributes()) self.assertTrue("weight" not in g2.edge_attributes()) def testIsBipartite(self): g = Graph.Star(10) self.assertTrue(g.is_bipartite() == True) self.assertTrue(g.is_bipartite(True) == (True, [False] + [True]*9)) g = Graph.Tree(100, 3) self.assertTrue(g.is_bipartite() == True) g = Graph.Ring(9) self.assertTrue(g.is_bipartite() == False) self.assertTrue(g.is_bipartite(True) == (False, None)) g = Graph.Ring(10) self.assertTrue(g.is_bipartite() == True) g += (2, 0) self.assertTrue(g.is_bipartite(True) == (False, None)) def suite(): bipartite_suite = unittest.makeSuite(BipartiteTests) return unittest.TestSuite([bipartite_suite]) def test(): runner = unittest.TextTestRunner() runner.run(suite()) if __name__ == "__main__": test() python-igraph-0.8.0/tests/test_flow.py0000644000076500000240000002303213606025206020262 0ustar tamasstaff00000000000000import unittest from igraph import * from itertools import combinations from random import randint class MaxFlowTests(unittest.TestCase): def setUp(self): self.g = Graph(4, [(0, 1), (0, 2), (1, 2), (1, 3), (2, 3)]) self.capacities = [4, 2, 10, 2, 2] self.g.es["capacity"] = self.capacities def testCapacities(self): self.assertTrue(self.capacities == \ self.g.es.get_attribute_values("capacity")) def testEdgeConnectivity(self): self.assertTrue(self.g.edge_connectivity(0, 3) == 2) self.assertTrue(Graph.Barabasi(50).edge_connectivity() == 1) self.assertTrue(self.g.adhesion() == 2) self.assertTrue(Graph.Tree(10, 3).adhesion() == 1) self.assertTrue(Graph.Tree(10, 3, TREE_OUT).adhesion() == 0) self.assertRaises(ValueError, self.g.edge_connectivity, 0) def testVertexConnectivity(self): self.assertTrue(self.g.vertex_connectivity(0, 3) == 2) self.assertTrue(Graph.Barabasi(50).vertex_connectivity() == 1) self.assertTrue(self.g.cohesion() == 2) self.assertTrue(Graph.Tree(10, 3).cohesion() == 1) self.assertTrue(Graph.Tree(10, 3, TREE_OUT).cohesion() == 0) self.assertRaises(ValueError, self.g.vertex_connectivity, 0) self.assertRaises(InternalError, self.g.vertex_connectivity, 0, 1) self.assertTrue(self.g.vertex_connectivity(0, 1, neighbors="nodes") == 4) self.assertTrue(self.g.vertex_connectivity(0, 1, neighbors="negative") == -1) def testMaxFlowValue(self): self.assertTrue(self.g.maxflow_value(0, 3) == 2) self.assertTrue(self.g.maxflow_value(0, 3, self.capacities) == 4) self.assertTrue(self.g.maxflow_value(0, 3, "capacity") == 4) self.assertRaises(KeyError, self.g.maxflow_value, 0, 3, "unknown") def testMaxFlow(self): flow = self.g.maxflow(0, 3) self.assertEqual(flow.value, 2) self.assertEqual(flow.flow, [1, 1, 0, 1, 1]) flow = self.g.maxflow(0, 3, "capacity") self.assertEqual(flow.value, 4) self.assertEqual(flow.cut, [3, 4]) self.assertEqual([e.index for e in flow.es], [3, 4]) self.assertTrue(set(flow.partition[0]).union(flow.partition[1]) == \ set(range(self.g.vcount()))) self.assertRaises(KeyError, self.g.maxflow, 0, 3, "unknown") class CutTests(unittest.TestCase): def constructSimpleGraph(self, directed=False): g = Graph(4, [(0, 1), (0, 2), (1, 2), (1, 3), (2, 3)], directed) g.es["capacity"] = [4, 2, 10, 2, 2] return g def constructLadderGraph(self, directed=False): el = list(zip(range(0, 5), range(1, 6))) el += list(zip(range(6, 11), range(7, 12))) el += list(zip(range(0, 6), range(6, 12))) g = Graph(el, directed=directed) return g def testMinCutValue(self): g = self.constructSimpleGraph() self.assertTrue(g.mincut_value(0, 3) == 2) self.assertTrue(g.mincut_value(0, 3, g.es["capacity"]) == 4) self.assertTrue(g.mincut_value(0, 3, "capacity") == 4) self.assertRaises(KeyError, g.mincut_value, 0, 3, "unknown") self.assertTrue(g.mincut_value() == 2) self.assertTrue(g.mincut_value(source=0) == 2) self.assertTrue(g.mincut_value(target=2) == 2) def testMinCut(self): g = self.constructSimpleGraph() mc = g.mincut() self.assertTrue(isinstance(mc, Cut)) self.assertTrue(mc.value == 2) self.assertTrue(set(mc.partition[0]).union(mc.partition[1]) == \ set(range(g.vcount()))) self.assertTrue(isinstance(str(mc), str)) self.assertTrue(isinstance(repr(mc), str)) self.assertTrue(isinstance(mc.es, EdgeSeq)) self.assertTrue(len(mc.es) == 2) mc = g.mincut(capacity="capacity") self.assertTrue(mc.value == 4) self.assertRaises(KeyError, g.mincut, capacity="unknown") def testMinCutWithSourceAndTarget(self): g = self.constructSimpleGraph() mc = g.mincut(0, 3, "capacity") self.assertTrue(isinstance(mc, Cut)) self.assertTrue(mc.cut == [3, 4]) self.assertTrue(mc.value == 4) self.assertTrue(set(mc.partition[0]).union(mc.partition[1]) == \ set(range(g.vcount()))) mc = g.mincut(0, 3) self.assertTrue(isinstance(mc, Cut)) self.assertTrue(mc.cut == [3, 4]) self.assertTrue(mc.value == 2) mc = g.mincut(2, 0, "capacity") self.assertTrue(isinstance(mc, Cut)) self.assertTrue(mc.cut == [0, 1]) self.assertTrue(mc.value == 6) self.assertRaises(ValueError, g.mincut, 2, capacity="capacity") def testStMinCut(self): g = self.constructSimpleGraph() mc = g.st_mincut(0, 3, "capacity") self.assertTrue(isinstance(mc, Cut)) self.assertTrue(mc.cut == [3, 4]) self.assertTrue(mc.value == 4) self.assertTrue(set(mc.partition[0]).union(mc.partition[1]) == \ set(range(g.vcount()))) mc = g.st_mincut(0, 3) self.assertTrue(isinstance(mc, Cut)) self.assertTrue(mc.cut == [3, 4]) self.assertTrue(mc.value == 2) mc = g.st_mincut(2, 0, "capacity") self.assertTrue(isinstance(mc, Cut)) self.assertTrue(mc.cut == [0, 1]) self.assertTrue(mc.value == 6) self.assertRaises(KeyError, g.st_mincut, 2, 0, capacity="unknown") def testAllSTCuts1(self): # Simple graph with four vertices g = self.constructSimpleGraph(directed=True) partitions = [((0, 1, 1, 1), 2), ((0, 0, 1, 1), 3), ((0, 1, 0, 1), 2), ((0, 0, 0, 1), 2)] values = dict(partitions) partitions = [partition for partition, _ in partitions] for cut in g.all_st_cuts(0,3): membership = tuple(cut.membership) self.assertTrue(membership in partitions, "%r not found among expected partitions" % (membership,)) self.assertEqual(cut.value, values[membership]) self.assertEqual(len(cut.es), values[membership]) partitions.remove(membership) self.assertTrue(partitions == [], "expected partitions not seen: %r" % (partitions, )) def testAllSTCuts2(self): # "Ladder graph" g = self.constructLadderGraph(directed=True) cuts = g.all_st_cuts(0, 11) self.assertEqual(len(cuts), 36) self.assertEqual(len(set(tuple(cut.membership) for cut in cuts)), 36) for cut in cuts: g2 = g.copy() g2.delete_edges(cut.es) self.assertFalse(g2.is_connected(), "%r is not a real cut" % (cut.membership,)) self.assertFalse(cut.value < 2 or cut.value > 6) def testAllSTMinCuts2(self): # "Ladder graph" g = self.constructLadderGraph() g.to_directed("mutual") cuts = g.all_st_mincuts(0, 11) self.assertEqual(len(cuts), 7) self.assertEqual(len(set(tuple(cut.membership) for cut in cuts)), 7) for cut in cuts: self.assertEqual(cut.value, 2) g2 = g.copy() g2.delete_edges(cut.es) self.assertFalse(g2.is_connected(), "%r is not a real cut" % (cut.membership,)) g.es["capacity"] = [2, 1, 2, 1, 2, 2, 1, 2, 1, 2, 1, 1, 1, 1, 1] cuts = g.all_st_mincuts(0, 11, "capacity") self.assertEqual(len(cuts), 2) self.assertEqual(cuts[0].membership, [0,0,1,1,1,1,0,0,1,1,1,1]) self.assertEqual(cuts[1].membership, [0,0,0,0,1,1,0,0,0,0,1,1]) self.assertEqual(cuts[0].value, 2) self.assertEqual(cuts[1].value, 2) class GomoryHuTests(unittest.TestCase): def testEmpty(self): g = Graph() t = g.gomory_hu_tree() self.assertEqual(0, t.vcount()) self.assertEqual(0, t.ecount()) def testSimpleExample(self): g = Graph(6, [(0,1),(0,2),(1,2),(1,3),(1,4),(2,4),(3,4),(3,5),(4,5)], \ directed=False) g.es["capacity"] = [1,7,1,3,2,4,1,6,2] t = g.gomory_hu_tree("capacity") self.validate_gomory_hu_tree(g, t) def testDirected(self): g = Graph(6, [(0,1),(0,2),(1,2),(1,3),(1,4),(2,4),(3,4),(3,5),(4,5)], \ directed=True) g.es["capacity"] = [1,7,1,3,2,4,1,6,2] self.assertRaises(InternalError, g.gomory_hu_tree, "capacity") def testRandomGRG(self): g = Graph.GRG(25, 0.4) self.validate_gomory_hu_tree(g, g.gomory_hu_tree()) g.es["capacity"] = [randint(0, 10) for _ in range(g.ecount())] self.validate_gomory_hu_tree(g, g.gomory_hu_tree("capacity")) def validate_gomory_hu_tree(self, g, t): n = g.vcount() self.assertEqual(n, t.vcount()) self.assertEqual(n-1, t.ecount()) self.assertFalse(t.is_directed()) if "capacity" in g.edge_attributes(): capacities = g.es["capacity"] else: capacities = None for i, j in combinations(range(n), 2): path = t.get_shortest_paths(i, j, output="epath") if path: path = path[0] expected_flow = min(t.es[path]["flow"]) observed_flow = g.maxflow_value(i, j, capacities) self.assertEqual(observed_flow, expected_flow) def suite(): flow_suite = unittest.makeSuite(MaxFlowTests) cut_suite = unittest.makeSuite(CutTests) gomory_hu_suite = unittest.makeSuite(GomoryHuTests) return unittest.TestSuite([flow_suite, cut_suite, gomory_hu_suite]) def test(): runner = unittest.TextTestRunner() runner.run(suite()) if __name__ == "__main__": test() python-igraph-0.8.0/tests/test_generators.py0000644000076500000240000001553113606025206021471 0ustar tamasstaff00000000000000import unittest from igraph import * class GeneratorTests(unittest.TestCase): def testStar(self): g=Graph.Star(5, "in") el=[(1,0),(2,0),(3,0),(4,0)] self.assertTrue(g.is_directed()) self.assertTrue(g.get_edgelist() == el) g=Graph.Star(5, "out", center=2) el=[(2,0),(2,1),(2,3),(2,4)] self.assertTrue(g.is_directed()) self.assertTrue(g.get_edgelist() == el) g=Graph.Star(5, "mutual", center=2) el=[(0,2),(1,2),(2,0),(2,1),(2,3),(2,4),(3,2),(4,2)] self.assertTrue(g.is_directed()) self.assertTrue(sorted(g.get_edgelist()) == el) g=Graph.Star(5, center=3) el=[(0,3),(1,3),(2,3),(3,4)] self.assertTrue(not g.is_directed()) self.assertTrue(sorted(g.get_edgelist()) == el) def testFamous(self): g=Graph.Famous("tutte") self.assertTrue(g.vcount() == 46 and g.ecount() == 69) self.assertRaises(InternalError, Graph.Famous, "unknown") def testFormula(self): tests = [ (None, [], []), ("", [""], []), ("A", ["A"], []), ("A-B", ["A", "B"], [(0, 1)]), ("A --- B", ["A", "B"], [(0, 1)]), ("A--B, C--D, E--F, G--H, I, J, K", ["A", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K"], [(0,1), (2,3), (4,5), (6,7)] ), ("A:B:C:D -- A:B:C:D", ["A", "B", "C", "D"], [(0,1), (0,2), (0,3), (1,2), (1,3), (2,3)] ), ("A -> B -> C", ["A", "B", "C"], [(0,1), (1,2)]), ("A <- B -> C", ["A", "B", "C"], [(1,0), (1,2)]), ("A <- B -- C", ["A", "B", "C"], [(1,0)]), ("A <-> B <---> C <> D", ["A", "B", "C", "D"], [(0,1), (1,0), (1,2), (2,1), (2,3), (3,2)]), ("'this is' <- 'a silly' -> 'graph here'", ["this is", "a silly", "graph here"], [(1,0), (1,2)]), ("Alice-Bob-Cecil-Alice, Daniel-Cecil-Eugene, Cecil-Gordon", ["Alice", "Bob", "Cecil", "Daniel", "Eugene", "Gordon"], [(0,1),(1,2),(0,2),(2,3),(2,4),(2,5)] ), ("Alice-Bob:Cecil:Daniel, Cecil:Daniel-Eugene:Gordon", ["Alice", "Bob", "Cecil", "Daniel", "Eugene", "Gordon"], [(0,1),(0,2),(0,3),(2,4),(2,5),(3,4),(3,5)] ), ("Alice <-> Bob --> Cecil <-- Daniel, Eugene --> Gordon:Helen", ["Alice", "Bob", "Cecil", "Daniel", "Eugene", "Gordon", "Helen"], [(0,1),(1,0),(1,2),(3,2),(4,5),(4,6)] ), ("Alice -- Bob -- Daniel, Cecil:Gordon, Helen", ["Alice", "Bob", "Daniel", "Cecil", "Gordon", "Helen"], [(0,1),(1,2)] ), ('"+" -- "-", "*" -- "/", "%%" -- "%/%"', ["+", "-", "*", "/", "%%", "%/%"], [(0,1),(2,3),(4,5)] ), ("A-B-C\nC-D", ["A", "B", "C", "D"], [(0,1),(1,2),(2,3)]), ("A-B-C\n C-D", ["A", "B", "C", "D"], [(0,1),(1,2),(2,3)]) ] for formula, names, edges in tests: g = Graph.Formula(formula) self.assertEqual(g.vs["name"], names) self.assertEqual(g.get_edgelist(), sorted(edges)) def testFull(self): g=Graph.Full(20, directed=True) el=g.get_edgelist() el.sort() self.assertTrue(g.get_edgelist() == [(x, y) for x in range(20) for y in range(20) if x!=y]) def testFullCitation(self): g=Graph.Full_Citation(20) el=g.get_edgelist() el.sort() self.assertTrue(not g.is_directed()) self.assertTrue(el == [(x, y) for x in range(19) for y in range(x+1, 20)]) g=Graph.Full_Citation(20, True) el=g.get_edgelist() el.sort() self.assertTrue(g.is_directed()) self.assertTrue(el == [(x, y) for x in range(1, 20) for y in range(x)]) self.assertRaises(InternalError, Graph.Full_Citation, -2) def testLCF(self): g1=Graph.LCF(12, (5, -5), 6) g2=Graph.Famous("Franklin") self.assertTrue(g1.isomorphic(g2)) self.assertRaises(InternalError, Graph.LCF, 12, (5, -5), -3) def testKautz(self): g=Graph.Kautz(2, 2) deg_in=g.degree(mode=IN) deg_out=g.degree(mode=OUT) # This is not a proper test, but should spot most errors self.assertTrue(g.is_directed() and deg_in==[2]*12 and deg_out==[2]*12) def testDeBruijn(self): g=Graph.De_Bruijn(2, 3) deg_in=g.degree(mode=IN, loops=True) deg_out=g.degree(mode=OUT, loops=True) # This is not a proper test, but should spot most errors self.assertTrue(g.is_directed() and deg_in==[2]*8 and deg_out==[2]*8) def testSBM(self): pref_matrix = [[0.5, 0, 0], [0, 0, 0.5], [0, 0.5, 0]] n = 60 types = [20, 20, 20] g = Graph.SBM(n, pref_matrix, types) # Simple smoke tests for the expected structure of the graph self.assertTrue(g.is_simple()) self.assertFalse(g.is_directed()) self.assertEqual([0]*20 + [1]*40, g.clusters().membership) g2 = g.subgraph(range(20, 60)) self.assertTrue(not any(e.source // 20 == e.target // 20 for e in g2.es)) # Check loops argument g = Graph.SBM(n, pref_matrix, types, loops=True) self.assertFalse(g.is_simple()) self.assertTrue(sum(g.is_loop()) > 0) # Check directedness g = Graph.SBM(n, pref_matrix, types, directed=True) self.assertTrue(g.is_directed()) self.assertTrue(sum(g.is_mutual()) < g.ecount()) self.assertTrue(sum(g.is_loop()) == 0) # Check error conditions self.assertRaises(InternalError, Graph.SBM, -1, pref_matrix, types) self.assertRaises(InternalError, Graph.SBM, 61, pref_matrix, types) pref_matrix[0][1] = 0.7 self.assertRaises(InternalError, Graph.SBM, 60, pref_matrix, types) def testWeightedAdjacency(self): mat = [[0, 1, 2, 0], [2, 0, 0, 0], [0, 0, 2.5, 0], [0, 1, 0, 0]] g = Graph.Weighted_Adjacency(mat, attr="w0") el = g.get_edgelist() self.assertTrue(el == [(0,1), (0,2), (1,0), (2,2), (3,1)]) self.assertTrue(g.es["w0"] == [1, 2, 2, 2.5, 1]) g = Graph.Weighted_Adjacency(mat, mode="plus") el = g.get_edgelist() self.assertTrue(el == [(0,1), (0,2), (1,3), (2,2)]) self.assertTrue(g.es["weight"] == [3, 2, 1, 2.5]) g = Graph.Weighted_Adjacency(mat, attr="w0", loops=False) el = g.get_edgelist() self.assertTrue(el == [(0,1), (0,2), (1,0), (3,1)]) self.assertTrue(g.es["w0"] == [1, 2, 2, 1]) def suite(): generator_suite = unittest.makeSuite(GeneratorTests) return unittest.TestSuite([generator_suite]) def test(): runner = unittest.TextTestRunner() runner.run(suite()) if __name__ == "__main__": test() python-igraph-0.8.0/tests/test_separators.py0000644000076500000240000000504113606025206021476 0ustar tamasstaff00000000000000import unittest from igraph import * def powerset(iterable): items_powers = [(item, 1 << i) for i, item in enumerate(iterable)] for i in range(1 << len(items_powers)): for item, power in items_powers: if i & power: yield item class IsSeparatorTests(unittest.TestCase): def testIsSeparator(self): g = Graph.Lattice([8, 4], circular=False) self.assertTrue(g.is_separator([3, 11, 19, 27])) self.assertFalse(g.is_separator([10, 11, 18, 19])) self.assertTrue(g.is_separator([29, 20, 11, 2])) self.assertTrue(g.is_separator([16, 25, 17])) g = Graph.Lattice([8, 4], circular=True) self.assertFalse(g.is_separator([3, 11, 19, 27])) self.assertFalse(g.is_separator([29, 20, 11, 2])) self.assertFalse(g.is_separator(range(32))) self.assertRaises(InternalError, g.is_separator, range(33)) def testIsMinimalSeparator(self): g = Graph.Lattice([8, 4], circular=False) self.assertTrue(g.is_minimal_separator([3, 11, 19, 27])) self.assertFalse(g.is_minimal_separator([3, 11, 19, 27, 28])) self.assertFalse(g.is_minimal_separator([16, 25, 17])) self.assertTrue(g.is_minimal_separator([16, 25])) self.assertFalse(g.is_minimal_separator(range(32))) self.assertRaises(InternalError, g.is_minimal_separator, range(33)) def testAllMinimalSTSeparators(self): g = Graph.Famous("petersen") min_st_seps = set(tuple(x) for x in g.all_minimal_st_separators()) for vs in powerset(range(g.vcount())): if vs in min_st_seps: self.assertTrue(g.is_minimal_separator(vs)) else: self.assertFalse(g.is_minimal_separator(vs)) def testMinimumSizeSeparators(self): g = Graph.Famous("zachary") min_st_seps = set(tuple(x) for x in g.all_minimal_st_separators()) min_size_seps = [tuple(x) for x in g.minimum_size_separators()] self.assertTrue(set(min_size_seps).issubset(min_st_seps)) self.assertTrue(len(set(min_size_seps)) == len(min_size_seps)) size = len(min_size_seps[0]) self.assertTrue(len(s) != size for s in min_size_seps) self.assertTrue(sum(1 for s in min_st_seps if len(s) == size) == len(min_size_seps)) def suite(): is_separator_suite = unittest.makeSuite(IsSeparatorTests) return unittest.TestSuite([is_separator_suite]) def test(): runner = unittest.TextTestRunner() runner.run(suite()) if __name__ == "__main__": test() python-igraph-0.8.0/tests/test_operators.py0000644000076500000240000001620613606025206021336 0ustar tamasstaff00000000000000import unittest from igraph import * from .utils import skipIf try: import numpy as np except ImportError: np = None class OperatorTests(unittest.TestCase): def testMultiplication(self): g = Graph.Full(3)*3 self.assertTrue(g.vcount() == 9 and g.ecount() == 9 and g.clusters().membership == [0,0,0,1,1,1,2,2,2]) def testIntersection(self): g = Graph.Tree(7, 2) & Graph.Lattice([7]) self.assertTrue(g.get_edgelist() == [(0, 1)]) def testUnion(self): g = Graph.Tree(7, 2) | Graph.Lattice([7]) self.assertTrue(g.vcount() == 7 and g.ecount() == 12) def testInPlaceAddition(self): g = Graph.Full(3) orig = g # Adding vertices g += 2 self.assertTrue(g.vcount() == 5 and g.ecount() == 3 and g.clusters().membership == [0,0,0,1,2]) # Adding a vertex by name g += "spam" self.assertTrue(g.vcount() == 6 and g.ecount() == 3 and g.clusters().membership == [0,0,0,1,2,3]) # Adding a single edge g += (2, 3) self.assertTrue(g.vcount() == 6 and g.ecount() == 4 and g.clusters().membership == [0,0,0,0,1,2]) # Adding two edges g += [(3, 4), (2, 4), (4, 5)] self.assertTrue(g.vcount() == 6 and g.ecount() == 7 and g.clusters().membership == [0]*6) # Adding two more vertices g += ["eggs", "bacon"] self.assertEqual(g.vs["name"], [None, None, None, None, None, "spam", "eggs", "bacon"]) # Did we really use the original graph so far? # TODO: disjoint union should be modified so that this assertion # could be moved to the end self.assertTrue(id(g) == id(orig)) # Adding another graph g += Graph.Full(3) self.assertTrue(g.vcount() == 11 and g.ecount() == 10 and g.clusters().membership == [0,0,0,0,0,0,1,2,3,3,3]) # Adding two graphs g += [Graph.Full(3), Graph.Full(2)] self.assertTrue(g.vcount() == 16 and g.ecount() == 14 and g.clusters().membership == [0,0,0,0,0,0,1,2,3,3,3,4,4,4,5,5]) def testAddition(self): g0 = Graph.Full(3) # Adding vertices g = g0+2 self.assertTrue(g.vcount() == 5 and g.ecount() == 3 and g.clusters().membership == [0,0,0,1,2]) g0 = g # Adding vertices by name g = g0+"spam" self.assertTrue(g.vcount() == 6 and g.ecount() == 3 and g.clusters().membership == [0,0,0,1,2,3]) g0 = g # Adding a single edge g = g0+(2,3) self.assertTrue(g.vcount() == 6 and g.ecount() == 4 and g.clusters().membership == [0,0,0,0,1,2]) g0 = g # Adding two edges g = g0+[(3, 4), (2, 4), (4, 5)] self.assertTrue(g.vcount() == 6 and g.ecount() == 7 and g.clusters().membership == [0]*6) g0 = g # Adding another graph g = g0+Graph.Full(3) self.assertTrue(g.vcount() == 9 and g.ecount() == 10 and g.clusters().membership == [0,0,0,0,0,0,1,1,1]) def testInPlaceSubtraction(self): g = Graph.Full(8) orig = g # Deleting a vertex by vertex selector g -= 7 self.assertTrue(g.vcount() == 7 and g.ecount() == 21 and g.clusters().membership == [0,0,0,0,0,0,0]) # Deleting a vertex g -= g.vs[6] self.assertTrue(g.vcount() == 6 and g.ecount() == 15 and g.clusters().membership == [0,0,0,0,0,0]) # Deleting two vertices g -= [4, 5] self.assertTrue(g.vcount() == 4 and g.ecount() == 6 and g.clusters().membership == [0,0,0,0]) # Deleting an edge g -= (1, 2) self.assertTrue(g.vcount() == 4 and g.ecount() == 5 and g.clusters().membership == [0,0,0,0]) # Deleting three more edges g -= [(1, 3), (0, 2), (0, 3)] self.assertTrue(g.vcount() == 4 and g.ecount() == 2 and g.clusters().membership == [0,0,1,1]) # Did we really use the original graph so far? self.assertTrue(id(g) == id(orig)) # Subtracting a graph g2 = Graph.Tree(3, 2) g -= g2 self.assertTrue(g.vcount() == 4 and g.ecount() == 1 and g.clusters().membership == [0,1,2,2]) def testNonzero(self): self.assertTrue(Graph(1)) self.assertFalse(Graph(0)) def testLength(self): self.assertRaises(TypeError, len, Graph(15)) self.assertTrue(len(Graph(15).vs) == 15) self.assertTrue(len(Graph.Full(5).es) == 10) def testSimplify(self): el = [(0,1), (1,0), (1,2), (2,3), (2,3), (2,3), (3,3)] g = Graph(el) g.es["weight"] = [1, 2, 3, 4, 5, 6, 7] g2 = g.copy() g2.simplify() self.assertTrue(g2.vcount() == g.vcount()) self.assertTrue(g2.ecount() == 3) g2 = g.copy() g2.simplify(loops=False) self.assertTrue(g2.vcount() == g.vcount()) self.assertTrue(g2.ecount() == 4) g2 = g.copy() g2.simplify(multiple=False) self.assertTrue(g2.vcount() == g.vcount()) self.assertTrue(g2.ecount() == g.ecount() - 1) def testContractVertices(self): g = Graph.Full(4) + Graph.Full(4) + [(0, 5), (1, 4)] g2 = g.copy() g2.contract_vertices([0, 1, 2, 3, 1, 0, 4, 5]) self.assertEqual(g2.vcount(), 6) self.assertEqual(g2.ecount(), g.ecount()) self.assertEqual(sorted(g2.get_edgelist()), [(0, 0), (0, 1), (0, 1), (0, 2), (0, 3), (0, 4), (0, 5), (1, 1), (1, 2), (1, 3), (1, 4), (1, 5), (2, 3), (4, 5)]) g2 = g.copy() g2.contract_vertices([0, 1, 2, 3, 1, 0, 6, 7]) self.assertEqual(g2.vcount(), 8) self.assertEqual(g2.ecount(), g.ecount()) self.assertEqual(sorted(g2.get_edgelist()), [(0, 0), (0, 1), (0, 1), (0, 2), (0, 3), (0, 6), (0, 7), (1, 1), (1, 2), (1, 3), (1, 6), (1, 7), (2, 3), (6, 7)]) g2 = Graph(10) g2.contract_vertices([0, 0, 1, 1, 2, 2, 3, 3, 4, 4]) self.assertEqual(g2.vcount(), 5) self.assertEqual(g2.ecount(), 0) @skipIf(np is None, "test case depends on NumPy") def testContractVerticesWithNumPyIntegers(self): g = Graph.Full(4) + Graph.Full(4) + [(0, 5), (1, 4)] g2 = g.copy() g2.contract_vertices([np.int32(x) for x in [0, 1, 2, 3, 1, 0, 6, 7]]) self.assertEqual(g2.vcount(), 8) self.assertEqual(g2.ecount(), g.ecount()) self.assertEqual(sorted(g2.get_edgelist()), [(0, 0), (0, 1), (0, 1), (0, 2), (0, 3), (0, 6), (0, 7), (1, 1), (1, 2), (1, 3), (1, 6), (1, 7), (2, 3), (6, 7)]) def suite(): operator_suite = unittest.makeSuite(OperatorTests) return unittest.TestSuite([operator_suite]) def test(): runner = unittest.TextTestRunner() runner.run(suite()) if __name__ == "__main__": test() python-igraph-0.8.0/tests/__init__.py0000644000076500000240000000000013606023505020001 0ustar tamasstaff00000000000000python-igraph-0.8.0/tests/test_conversion.py0000644000076500000240000000704113606025206021502 0ustar tamasstaff00000000000000import unittest from igraph import * class DirectedUndirectedTests(unittest.TestCase): def testToUndirected(self): graph = Graph([(0,1), (0,2), (1,0)], directed=True) graph2 = graph.copy() graph2.to_undirected(mode=False) self.assertTrue(graph2.vcount() == graph.vcount()) self.assertTrue(graph2.is_directed() == False) self.assertTrue(sorted(graph2.get_edgelist()) == [(0,1), (0,1), (0,2)]) graph2 = graph.copy() graph2.to_undirected() self.assertTrue(graph2.vcount() == graph.vcount()) self.assertTrue(graph2.is_directed() == False) self.assertTrue(sorted(graph2.get_edgelist()) == [(0,1), (0,2)]) graph2 = graph.copy() graph2.es["weight"] = [1,2,3] graph2.to_undirected(mode="collapse", combine_edges="sum") self.assertTrue(graph2.vcount() == graph.vcount()) self.assertTrue(graph2.is_directed() == False) self.assertTrue(sorted(graph2.get_edgelist()) == [(0,1), (0,2)]) self.assertTrue(graph2.es["weight"] == [4,2]) graph = Graph([(0,1),(1,0),(0,1),(1,0),(2,1),(1,2)], directed=True) graph2 = graph.copy() graph2.es["weight"] = [1,2,3,4,5,6] graph2.to_undirected(mode="mutual", combine_edges="sum") self.assertTrue(graph2.vcount() == graph.vcount()) self.assertTrue(graph2.is_directed() == False) self.assertTrue(sorted(graph2.get_edgelist()) == [(0,1), (0,1), (1,2)]) self.assertTrue(graph2.es["weight"] == [7,3,11] or graph2.es["weight"] == [3,7,11]) def testToDirected(self): graph = Graph([(0,1), (0,2), (2,3), (2,4)], directed=False) graph.to_directed() self.assertTrue(graph.is_directed()) self.assertTrue(graph.vcount() == 5) self.assertTrue(sorted(graph.get_edgelist()) == \ [(0,1), (0,2), (1,0), (2,0), (2,3), (2,4), (3,2), (4,2)] ) class GraphRepresentationTests(unittest.TestCase): def testGetAdjacency(self): # Undirected case g = Graph.Tree(6, 3) g.es["weight"] = range(5) self.assertTrue(g.get_adjacency() == Matrix([ [0, 1, 1, 1, 0, 0], [1, 0, 0, 0, 1, 1], [1, 0, 0, 0, 0, 0], [1, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0] ])) self.assertTrue(g.get_adjacency(attribute="weight") == Matrix([ [0, 0, 1, 2, 0, 0], [0, 0, 0, 0, 3, 4], [1, 0, 0, 0, 0, 0], [2, 0, 0, 0, 0, 0], [0, 3, 0, 0, 0, 0], [0, 4, 0, 0, 0, 0] ])) self.assertTrue(g.get_adjacency(eids=True) == Matrix([ [0, 1, 2, 3, 0, 0], [1, 0, 0, 0, 4, 5], [2, 0, 0, 0, 0, 0], [3, 0, 0, 0, 0, 0], [0, 4, 0, 0, 0, 0], [0, 5, 0, 0, 0, 0] ])-1) # Directed case g = Graph.Tree(6, 3, "tree_out") g.add_edges([(0,1), (1,0)]) self.assertTrue(g.get_adjacency() == Matrix([ [0, 2, 1, 1, 0, 0], [1, 0, 0, 0, 1, 1], [0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0] ])) def suite(): direction_suite = unittest.makeSuite(DirectedUndirectedTests) representation_suite = unittest.makeSuite(GraphRepresentationTests) return unittest.TestSuite([direction_suite, representation_suite]) def test(): runner = unittest.TextTestRunner() runner.run(suite()) if __name__ == "__main__": test() python-igraph-0.8.0/tests/test_indexing.py0000644000076500000240000000352113606025206021121 0ustar tamasstaff00000000000000# vim:ts=4 sw=4 sts=4: import unittest from igraph import * class GraphAdjacencyMatrixLikeIndexingTests(unittest.TestCase): def testSingleEdgeRetrieval(self): g = Graph.Famous("krackhardt_kite") for v1, v2 in g.get_edgelist(): self.assertEqual(g[v1, v2], 1) self.assertEqual(g[v2, v1], 1) for v1 in range(g.vcount()): for v2 in set(range(g.vcount())) - set(g.neighbors(v1)): self.assertEqual(g[v1, v2], 0) self.assertEqual(g[v2, v1], 0) g.add_edge(1, 1) self.assertEqual(g[1, 1], 1) def testSingleEdgeRetrievalWeights(self): g = Graph.Famous("krackhardt_kite") g.es["weight"] = range(g.ecount()) for idx, (v1, v2) in enumerate(g.get_edgelist()): self.assertEqual(g[v1, v2], idx) self.assertEqual(g[v2, v1], idx) for v1 in range(g.vcount()): for v2 in set(range(g.vcount())) - set(g.neighbors(v1)): self.assertEqual(g[v1, v2], 0) self.assertEqual(g[v2, v1], 0) def testSingleEdgeRetrievalAttrName(self): g = Graph.Famous("krackhardt_kite") g.es["value"] = range(20, g.ecount()+20) for idx, (v1, v2) in enumerate(g.get_edgelist()): self.assertEqual(g[v1, v2, "value"], idx+20) self.assertEqual(g[v2, v1, "value"], idx+20) for v1 in range(g.vcount()): for v2 in set(range(g.vcount())) - set(g.neighbors(v1)): self.assertEqual(g[v1, v2, "value"], 0) self.assertEqual(g[v2, v1, "value"], 0) def suite(): adjacency_suite = unittest.makeSuite(GraphAdjacencyMatrixLikeIndexingTests) return unittest.TestSuite([adjacency_suite]) def test(): runner = unittest.TextTestRunner() runner.run(suite()) if __name__ == "__main__": test() python-igraph-0.8.0/tests/test_homepage.py0000644000076500000240000000273513606025206021107 0ustar tamasstaff00000000000000import unittest from igraph import * class HomepageExampleTests(unittest.TestCase): """Smoke tests for the Python examples found on the homepage to ensure that they do not break.""" def testErdosRenyiComponents(self): g = Graph.Erdos_Renyi(n=300, m=250) colors = ["lightgray", "cyan", "magenta", "yellow", "blue", "green", "red"] components = g.components() for component in components: color = colors[min(6, len(components)-1)] g.vs[component]["color"] = color # No plotting here, but we calculate the FR layout fr = g.layout("fr") def testKautz(self): g = Graph.Kautz(m=3, n=2) adj = g.get_adjacency() # Plotting omitted def testMSTofGRG(self): def distance(p1, p2): return ((p1[0]-p2[0]) ** 2 + (p1[1]-p2[1]) ** 2) ** 0.5 g = Graph.GRG(100, 0.2) layout = Layout(zip(g.vs["x"], g.vs["y"])) weights = [distance(layout[edge.source], layout[edge.target]) \ for edge in g.es] max_weight = max(weights) g.es["width"] = [6 - 5*weight / max_weight for weight in weights] mst = g.spanning_tree(weights) # Plotting omitted def suite(): homepage_example_suite = unittest.makeSuite(HomepageExampleTests) return unittest.TestSuite([homepage_example_suite]) def test(): runner = unittest.TextTestRunner() runner.run(suite()) if __name__ == "__main__": test() python-igraph-0.8.0/tests/test_edgeseq.py0000644000076500000240000003635713616232333020750 0ustar tamasstaff00000000000000# vim:ts=4 sw=4 sts=4: import unittest from igraph import * from .utils import is_pypy, skipIf try: import numpy as np except ImportError: np = None class EdgeTests(unittest.TestCase): def setUp(self): self.g = Graph.Full(10) def testHash(self): data = {} n = self.g.ecount() for i in range(n): code1 = hash(self.g.es[i]) code2 = hash(self.g.es[i]) self.assertEqual(code1, code2) data[self.g.es[i]] = i for i in range(n): self.assertEqual(i, data[self.g.es[i]]) def testRichCompare(self): idxs = [2,5,9,13,42] g2 = Graph.Full(10) for i in idxs: for j in idxs: self.assertEqual(i == j, self.g.es[i] == self.g.es[j]) self.assertEqual(i != j, self.g.es[i] != self.g.es[j]) self.assertEqual(i < j, self.g.es[i] < self.g.es[j]) self.assertEqual(i > j, self.g.es[i] > self.g.es[j]) self.assertEqual(i <= j, self.g.es[i] <= self.g.es[j]) self.assertEqual(i >= j, self.g.es[i] >= self.g.es[j]) self.assertFalse(self.g.es[i] == g2.es[j]) self.assertFalse(self.g.es[i] != g2.es[j]) self.assertFalse(self.g.es[i] < g2.es[j]) self.assertFalse(self.g.es[i] > g2.es[j]) self.assertFalse(self.g.es[i] <= g2.es[j]) self.assertFalse(self.g.es[i] >= g2.es[j]) self.assertFalse(self.g.es[2] == self.g.vs[2]) def testRepr(self): output = repr(self.g.es[0]) self.assertEqual(output, "igraph.Edge(%r, 0, {})" % self.g) self.g.es["weight"] = range(10, 0, -1) output = repr(self.g.es[3]) self.assertEqual(output, "igraph.Edge(%r, 3, {'weight': 7})" % self.g) def testUpdateAttributes(self): e = self.g.es[0] e.update_attributes(a=2) self.assertEqual(e["a"], 2) e.update_attributes([("a", 3), ("b", 4)], c=5, d=6) self.assertEqual(e.attributes(), dict(a=3, b=4, c=5, d=6)) e.update_attributes(dict(b=44, c=55)) self.assertEqual(e.attributes(), dict(a=3, b=44, c=55, d=6)) def testPhantomEdge(self): e = self.g.es[self.g.ecount()-1] e.delete() # v is now a phantom edge; try to freak igraph out now :) self.assertRaises(ValueError, e.update_attributes, a=2) self.assertRaises(ValueError, e.__getitem__, "a") self.assertRaises(ValueError, e.__setitem__, "a", 4) self.assertRaises(ValueError, e.__delitem__, "a") self.assertRaises(ValueError, e.attributes) self.assertRaises(ValueError, getattr, e, "source") self.assertRaises(ValueError, getattr, e, "source_vertex") self.assertRaises(ValueError, getattr, e, "target") self.assertRaises(ValueError, getattr, e, "target_vertex") self.assertRaises(ValueError, getattr, e, "tuple") self.assertRaises(ValueError, getattr, e, "vertex_tuple") @skipIf(is_pypy, "skipped on PyPy because we do not have access to docstrings") def testProxyMethods(self): g = Graph.GRG(10, 0.5) e = g.es[0] # - delete() is ignored because it mutates the graph ignore = "delete" ignore = set(ignore.split()) # Methods not listed here are expected to return an int or a float return_types = { } for name in Edge.__dict__: if name in ignore: continue func = getattr(e, name) docstr = func.__doc__ if not docstr.startswith("Proxy method"): continue result = func() self.assertEqual(getattr(g, name)(e.index), result, msg=("Edge.%s proxy method misbehaved" % name)) return_type = return_types.get(name, (int, float)) self.assertTrue(isinstance(result, return_type), msg=("Edge.%s proxy method did not return %s" % (name, return_type)) ) class EdgeSeqTests(unittest.TestCase): def assert_edges_unique_in(self, es): pairs = sorted(e.tuple for e in es) self.assertEqual(pairs, sorted(set(pairs))) def setUp(self): self.g = Graph.Full(10) self.g.es["test"] = range(45) def testCreation(self): self.assertTrue(len(EdgeSeq(self.g)) == 45) self.assertTrue(len(EdgeSeq(self.g, 2)) == 1) self.assertTrue(len(EdgeSeq(self.g, [1,2,3])) == 3) self.assertTrue(EdgeSeq(self.g, [1,2,3]).indices == [1,2,3]) self.assertRaises(ValueError, EdgeSeq, self.g, 112) self.assertRaises(ValueError, EdgeSeq, self.g, [112]) self.assertTrue(self.g.es.graph == self.g) def testIndexing(self): n = self.g.ecount() for i in range(n): self.assertEqual(i, self.g.es[i].index) self.assertEqual(n-i-1, self.g.es[-i-1].index) self.assertRaises(IndexError, self.g.es.__getitem__, n) self.assertRaises(IndexError, self.g.es.__getitem__, -n-1) self.assertRaises(TypeError, self.g.es.__getitem__, 1.5) @skipIf(np is None, "test case depends on NumPy") def testNumPyIndexing(self): n = self.g.ecount() for i in range(n): arr = np.array([i]) self.assertEqual(i, self.g.es[arr[0]].index) arr = np.array([n]) self.assertRaises(IndexError, self.g.es.__getitem__, arr[0]) arr = np.array([-n-1]) self.assertRaises(IndexError, self.g.es.__getitem__, arr[0]) arr = np.array([1.5]) self.assertRaises(TypeError, self.g.es.__getitem__, arr[0]) def testPartialAttributeAssignment(self): only_even = self.g.es.select(lambda e: (e.index % 2 == 0)) only_even["test"] = [0]*len(only_even) expected = [[0,i][i % 2] for i in range(self.g.ecount())] self.assertTrue(self.g.es["test"] == expected) only_even["test2"] = range(23) expected = [[i//2, None][i % 2] for i in range(self.g.ecount())] self.assertTrue(self.g.es["test2"] == expected) def testSequenceReusing(self): if "test" in self.g.edge_attributes(): del self.g.es["test"] self.g.es["test"] = ["A", "B", "C"] self.assertTrue(self.g.es["test"] == ["A", "B", "C"]*15) self.g.es["test"] = "ABC" self.assertTrue(self.g.es["test"] == ["ABC"] * 45) only_even = self.g.es.select(lambda e: (e.index % 2 == 0)) only_even["test"] = ["D", "E"] expected = ["D", "ABC", "E", "ABC"] * 12 expected = expected[0:45] self.assertTrue(self.g.es["test"] == expected) del self.g.es["test"] only_even["test"] = ["D", "E"] expected = ["D", None, "E", None] * 12 expected = expected[0:45] self.assertTrue(self.g.es["test"] == expected) def testAllSequence(self): self.assertTrue(len(self.g.es) == 45) self.assertTrue(self.g.es["test"] == list(range(45))) def testEmptySequence(self): empty_es = self.g.es.select(None) self.assertTrue(len(empty_es) == 0) self.assertRaises(IndexError, empty_es.__getitem__, 0) self.assertRaises(KeyError, empty_es.__getitem__, "nonexistent") self.assertTrue(empty_es["test"] == []) empty_es = self.g.es[[]] self.assertTrue(len(empty_es) == 0) empty_es = self.g.es[()] self.assertTrue(len(empty_es) == 0) def testCallableFilteringFind(self): edge = self.g.es.find(lambda e: (e.index % 2 == 1)) self.assertTrue(edge.index == 1) self.assertRaises(IndexError, self.g.es.find, lambda e: (e.index % 2 == 3)) def testCallableFilteringSelect(self): only_even = self.g.es.select(lambda e: (e.index % 2 == 0)) self.assertTrue(len(only_even) == 23) self.assertRaises(KeyError, only_even.__getitem__, "nonexistent") self.assertTrue(only_even["test"] == [i*2 for i in range(23)]) def testChainedCallableFilteringSelect(self): only_div_six = self.g.es.select(lambda e: (e.index % 2 == 0), lambda e: (e.index % 3 == 0)) self.assertTrue(len(only_div_six) == 8) self.assertTrue(only_div_six["test"] == [0, 6, 12, 18, 24, 30, 36, 42]) only_div_six = self.g.es.select(lambda e: (e.index % 2 == 0)).select(\ lambda e: (e.index % 3 == 0)) self.assertTrue(len(only_div_six) == 8) self.assertTrue(only_div_six["test"] == [0, 6, 12, 18, 24, 30, 36, 42]) def testIntegerFilteringFind(self): self.assertEqual(self.g.es.find(3).index, 3) self.assertEqual(self.g.es.select(2,3,4,2).find(3).index, 2) self.assertRaises(IndexError, self.g.es.find, 178) def testIntegerFilteringSelect(self): subset = self.g.es.select(2,3,4,2) self.assertTrue(len(subset) == 4) self.assertTrue(subset["test"] == [2,3,4,2]) self.assertRaises(TypeError, self.g.es.select, 2, 3, 4, 2, None) subset = self.g.es[2,3,4,2] self.assertTrue(len(subset) == 4) self.assertTrue(subset["test"] == [2,3,4,2]) def testIterableFilteringSelect(self): subset = self.g.es.select(range(5,8)) self.assertTrue(len(subset) == 3) self.assertTrue(subset["test"] == [5,6,7]) def testSliceFilteringSelect(self): subset = self.g.es.select(slice(5, 8)) self.assertTrue(len(subset) == 3) self.assertTrue(subset["test"] == [5,6,7]) subset = self.g.es[40:56:2] self.assertTrue(len(subset) == 3) self.assertTrue(subset["test"] == [40,42,44]) def testKeywordFilteringSelect(self): g = Graph.Barabasi(1000, 2) g.es["betweenness"] = g.edge_betweenness() g.es["parity"] = [i % 2 for i in range(g.ecount())] self.assertTrue(len(g.es(betweenness_gt=10)) < 2000) self.assertTrue(len(g.es(betweenness_gt=10, parity=0)) < 2000) def testSourceTargetFiltering(self): g = Graph.Barabasi(1000, 2, directed=True) es1 = set(e.source for e in g.es.select(_target_in = [2, 4])) es2 = set(v1 for v1, v2 in g.get_edgelist() if v2 in [2, 4]) self.assertTrue(es1 == es2) def testWithinFiltering(self): g = Graph.Lattice([10, 10]) vs = [0, 1, 2, 10, 11, 12, 20, 21, 22] vs2 = (0, 1, 10, 11) es1 = g.es.select(_within = vs) es2 = g.es.select(_within = VertexSeq(g, vs)) for es in [es1, es2]: self.assertTrue(len(es) == 12) self.assertTrue(all(e.source in vs and e.target in vs for e in es)) self.assert_edges_unique_in(es) es_filtered = es.select(_within = vs2) self.assertTrue(len(es_filtered) == 4) self.assertTrue(all(e.source in vs2 and e.target in vs2 for e in es_filtered)) self.assert_edges_unique_in(es_filtered) def testBetweenFiltering(self): g = Graph.Lattice([10, 10]) vs1, vs2 = [10, 11, 12], [20, 21, 22] es1 = g.es.select(_between = (vs1, vs2)) es2 = g.es.select(_between = (VertexSeq(g, vs1), VertexSeq(g, vs2))) for es in [es1, es2]: self.assertTrue(len(es) == 3) self.assertTrue(all((e.source in vs1 and e.target in vs2) or \ (e.target in vs1 and e.source in vs2) for e in es)) self.assert_edges_unique_in(es) def testIncidentFiltering(self): g = Graph.Lattice([10, 10], circular=False) vs = (0, 1, 10, 11) vs2 = (11, 0, 24) vs3 = sorted(set(vs).intersection(set(vs2))) es = g.es.select(_incident = vs) self.assertEqual(8, len(es)) self.assertTrue(all((e.source in vs or e.target in vs) for e in es)) self.assert_edges_unique_in(es) es_filtered = es.select(_incident = vs2) self.assertEqual(6, len(es_filtered)) self.assertTrue(all((e.source in vs3 or e.target in vs3) for e in es_filtered)) self.assert_edges_unique_in(es_filtered) def testIncidentFilteringByNames(self): g = Graph.Lattice([10, 10], circular=False) vs = (0, 1, 10, 11) g.vs[vs]["name"] = ["A", "B", "C", "D"] vs2 = (11, 0, 24) g.vs[24]["name"] = "X" vs3 = sorted(set(vs).intersection(set(vs2))) es = g.es.select(_incident = ("A", "B", "C", "D")) self.assertEqual(8, len(es)) self.assertTrue(all((e.source in vs or e.target in vs) for e in es)) self.assert_edges_unique_in(es) es_filtered = es.select(_incident = ("D", "A", "X")) self.assertEqual(6, len(es_filtered)) self.assertTrue(all((e.source in vs3 or e.target in vs3) for e in es_filtered)) self.assert_edges_unique_in(es_filtered) es_filtered = es_filtered.select(_from="A") self.assertEqual(2, len(es_filtered)) self.assertTrue(all((e.source == 0 or e.target == 0) for e in es_filtered)) self.assert_edges_unique_in(es_filtered) def testSourceAndTargetFilteringForUndirectedGraphs(self): g = Graph.Lattice([10, 10], circular=False) vs = (0, 1, 10, 11) vs2 = (11, 0, 24) vs3 = sorted(set(vs).intersection(set(vs2))) es = g.es.select(_from = vs) self.assertEqual(8, len(es)) self.assertTrue(all((e.source in vs or e.target in vs) for e in es)) self.assert_edges_unique_in(es) es_filtered = es.select(_to_in = vs2) self.assertEqual(6, len(es_filtered)) self.assertTrue(all((e.source in vs3 or e.target in vs3) for e in es_filtered)) self.assert_edges_unique_in(es_filtered) es_filtered = es_filtered.select(_from_eq = 0) self.assertEqual(2, len(es_filtered)) self.assertTrue(all((e.source == 0 or e.target == 0) for e in es_filtered)) self.assert_edges_unique_in(es_filtered) def testIndexOutOfBoundsSelect(self): g = Graph.Full(3) self.assertRaises(ValueError, g.es.select, 4) self.assertRaises(ValueError, g.es.select, 4, 5) self.assertRaises(ValueError, g.es.select, (4, 5)) self.assertRaises(ValueError, g.es.select, 2, -1) self.assertRaises(ValueError, g.es.select, (2, -1)) self.assertRaises(ValueError, g.es.__getitem__, (0, 1000000)) def testIndexAndKeywordFilteringFind(self): self.assertRaises(ValueError, self.g.es.find, 2, test=4) self.assertTrue(self.g.es.find(2, test=2) == self.g.es[2]) def testGraphMethodProxying(self): idxs = [1, 3, 5, 7, 9] g = Graph.Barabasi(100) es = g.es(*idxs) ebs = g.edge_betweenness() self.assertEqual([ebs[i] for i in idxs], es.edge_betweenness()) idxs = [1, 3] g = Graph([(0, 1), (1, 2), (2, 0), (1, 0)], directed=True) es = g.es(*idxs) mutual = g.is_mutual(es) self.assertEqual(mutual, es.is_mutual()) for e, m in zip(es, mutual): self.assertEqual(e.is_mutual(), m) def testIsAll(self): g = Graph.Full(5) self.assertTrue(g.es.is_all()) self.assertFalse(g.es.select(1,2,3).is_all()) self.assertFalse(g.es.select(_within=[1,2,3]).is_all()) def suite(): edge_suite = unittest.makeSuite(EdgeTests) es_suite = unittest.makeSuite(EdgeSeqTests) return unittest.TestSuite([edge_suite, es_suite]) def test(): runner = unittest.TextTestRunner() runner.run(suite()) if __name__ == "__main__": test() python-igraph-0.8.0/tests/utils.py0000644000076500000240000000334313606025206017417 0ustar tamasstaff00000000000000"""Utility functions for unit testing.""" import functools import os import platform import sys import tempfile import types from contextlib import contextmanager from textwrap import dedent __all__ = ["skip", "skipIf", "temporary_file"] def _id(obj): return obj try: from unittest import skip except ImportError: # Provide basic replacement for unittest.skip def skip(reason): """Unconditionally skip a test.""" def decorator(test_item): if not isinstance(test_item, (type, types.ClassType)): @functools.wraps(test_item) def skip_wrapper(*args, **kwds): if reason: sys.stderr.write("skipped, %s ... " % reason) else: sys.stderr.write("skipped, ") return test_item = skip_wrapper return test_item return decorator try: from unittest import skipIf except ImportError: # Provide basic replacement for unittest.skipIf def skipIf(condition, reason): """Skip a test if the condition is true.""" if condition: return skip(reason) return _id @contextmanager def temporary_file(content=None, mode=None): tmpf, tmpfname = tempfile.mkstemp() os.close(tmpf) if mode is None: if content is None: mode = "rb" else: mode = "wb" tmpf = open(tmpfname, mode) if content is not None: if hasattr(content, "encode"): tmpf.write(dedent(content).encode("utf8")) else: tmpf.write(content) tmpf.close() yield tmpfname os.unlink(tmpfname) is_pypy = (platform.python_implementation() == "PyPy") python-igraph-0.8.0/tests/test_decomposition.py0000644000076500000240000004466013616774160022214 0ustar tamasstaff00000000000000import random import unittest import math from igraph import * try: set, frozenset except NameError: import sets set, frozenset = sets.Set, sets.ImmutableSet class SubgraphTests(unittest.TestCase): def testSubgraph(self): g = Graph.Lattice([10, 10], circular=False, mutual=False) g.vs["id"] = range(g.vcount()) vs = [0, 1, 2, 10, 11, 12, 20, 21, 22] sg = g.subgraph(vs) self.assertTrue(sg.isomorphic(Graph.Lattice([3, 3], circular=False, mutual=False))) self.assertTrue(sg.vs["id"] == vs) def testSubgraphEdges(self): g = Graph.Lattice([10, 10], circular=False, mutual=False) g.es["id"] = range(g.ecount()) es = [0, 1, 2, 5, 20, 21, 22, 24, 38, 40] sg = g.subgraph_edges(es) exp = Graph.Lattice([3, 3], circular=False, mutual=False) exp.delete_edges([7, 8]) self.assertTrue(sg.isomorphic(exp)) self.assertTrue(sg.es["id"] == es) class DecompositionTests(unittest.TestCase): def testKCores(self): g = Graph(11, [(0,1), (0,2), (0,3), (1,2), (1,3), (2,3), (2,4), (2,5), (3,6), (3,7), (1,7), (7,8), (1,9), (1,10), (9,10)]) self.assertTrue(g.coreness() == [3,3,3,3,1,1,1,2,1,2,2]) self.assertTrue(g.shell_index() == g.coreness()) l=g.k_core(3).get_edgelist() l.sort() self.assertTrue(l == [(0,1), (0,2), (0,3), (1,2), (1,3), (2,3)]) class ClusteringTests(unittest.TestCase): def setUp(self): self.cl = Clustering([0,0,0,1,1,2,1,1,4,4]) def testClusteringIndex(self): self.assertTrue(self.cl[0] == [0, 1, 2]) self.assertTrue(self.cl[1] == [3, 4, 6, 7]) self.assertTrue(self.cl[2] == [5]) self.assertTrue(self.cl[3] == []) self.assertTrue(self.cl[4] == [8, 9]) def testClusteringLength(self): self.assertTrue(len(self.cl) == 5) def testClusteringMembership(self): self.assertTrue(self.cl.membership == [0,0,0,1,1,2,1,1,4,4]) def testClusteringSizes(self): self.assertTrue(self.cl.sizes() == [3, 4, 1, 0, 2]) self.assertTrue(self.cl.sizes(2, 4, 1) == [1, 2, 4]) self.assertTrue(self.cl.size(2) == 1) def testClusteringHistogram(self): self.assertTrue(isinstance(self.cl.size_histogram(), Histogram)) class VertexClusteringTests(unittest.TestCase): def setUp(self): self.graph = Graph.Full(10) self.graph.vs["string"] = list("aaabbcccab") self.graph.vs["int"] = [17, 41, 23, 25, 64, 33, 3, 24, 47, 15] def testFromStringAttribute(self): cl = VertexClustering.FromAttribute(self.graph, "string") self.assertTrue(cl.membership == [0,0,0,1,1,2,2,2,0,1]) def testFromIntAttribute(self): cl = VertexClustering.FromAttribute(self.graph, "int") self.assertTrue(cl.membership == list(range(10))) cl = VertexClustering.FromAttribute(self.graph, "int", 15) self.assertTrue(cl.membership == [0, 1, 0, 0, 2, 1, 3, 0, 4, 0]) cl = VertexClustering.FromAttribute(self.graph, "int", [10, 20, 30]) self.assertTrue(cl.membership == [0, 1, 2, 2, 1, 1, 3, 2, 1, 0]) def testClusterGraph(self): cl = VertexClustering(self.graph, [0, 0, 0, 1, 1, 1, 2, 2, 2, 2]) self.graph.delete_edges(self.graph.es.select(_between=([0,1,2], [3,4,5]))) clg = cl.cluster_graph(dict(string="concat", int=max)) self.assertTrue(sorted(clg.get_edgelist()) == [(0, 2), (1, 2)]) self.assertTrue(not clg.is_directed()) self.assertTrue(clg.vs["string"] == ["aaa", "bbc", "ccab"]) self.assertTrue(clg.vs["int"] == [41, 64, 47]) clg = cl.cluster_graph(dict(string="concat", int=max), False) self.assertTrue(sorted(clg.get_edgelist()) == \ [(0, 0)]*3 + [(0, 2)]*12 + [(1, 1)]*3 + [(1, 2)]*12 + [(2, 2)]*6) self.assertTrue(not clg.is_directed()) self.assertTrue(clg.vs["string"] == ["aaa", "bbc", "ccab"]) self.assertTrue(clg.vs["int"] == [41, 64, 47]) class CoverTests(unittest.TestCase): def setUp(self): self.cl = Cover([(0,1,2,3), (3,4,5,6,9), (), (8,9)]) def testCoverIndex(self): self.assertTrue(self.cl[0] == [0, 1, 2, 3]) self.assertTrue(self.cl[1] == [3, 4, 5, 6, 9]) self.assertTrue(self.cl[2] == []) self.assertTrue(self.cl[3] == [8, 9]) def testCoverLength(self): self.assertTrue(len(self.cl) == 4) def testCoverSizes(self): self.assertTrue(self.cl.sizes() == [4, 5, 0, 2]) self.assertTrue(self.cl.sizes(1, 3, 0) == [5, 2, 4]) self.assertTrue(self.cl.size(1) == 5) self.assertTrue(self.cl.size(2) == 0) def testCoverHistogram(self): self.assertTrue(isinstance(self.cl.size_histogram(), Histogram)) def testCoverConstructorWithN(self): self.assertTrue(self.cl.n == 10) cl = Cover(self.cl, n = 15) self.assertTrue(cl.n == 15) cl = Cover(self.cl, n = 1) self.assertTrue(cl.n == 10) class CommunityTests(unittest.TestCase): def reindexMembership(self, cl): if hasattr(cl, "membership"): cl = cl.membership idgen = UniqueIdGenerator() return [idgen[i] for i in cl] def assertMembershipsEqual(self, observed, expected): if hasattr(observed, "membership"): observed = observed.membership if hasattr(expected, "membership"): expected = expected.membership self.assertEqual(self.reindexMembership(expected), \ self.reindexMembership(observed)) def testClauset(self): # Two cliques of size 5 with one connecting edge g = Graph.Full(5) + Graph.Full(5) g.add_edges([(0, 5)]) cl = g.community_fastgreedy().as_clustering() self.assertMembershipsEqual(cl, [0,0,0,0,0,1,1,1,1,1]) self.assertAlmostEqual(cl.q, 0.4523, places=3) # Lollipop, weighted g = Graph.Full(4) + Graph.Full(2) g.add_edges([(3,4)]) weights = [1, 1, 1, 1, 1, 1, 10, 10] cl = g.community_fastgreedy(weights).as_clustering() self.assertMembershipsEqual(cl, [0,0,0,1,1,1]) self.assertAlmostEqual(cl.q, 0.1708, places=3) # Same graph, different weights g.es["weight"] = [3] * g.ecount() cl = g.community_fastgreedy("weight").as_clustering() self.assertMembershipsEqual(cl, [0,0,0,0,1,1]) self.assertAlmostEqual(cl.q, 0.1796, places=3) # Disconnected graph g = Graph.Full(4) + Graph.Full(4) + Graph.Full(3) + Graph.Full(2) cl = g.community_fastgreedy().as_clustering() self.assertMembershipsEqual(cl, [0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 3, 3]) # Empty graph g = Graph(20) cl = g.community_fastgreedy().as_clustering() self.assertMembershipsEqual(cl, range(g.vcount())) def testEdgeBetweenness(self): # Full graph, no weights g = Graph.Full(5) cl = g.community_edge_betweenness().as_clustering() self.assertMembershipsEqual(cl, [0]*5) # Full graph with weights g.es["weight"] = 1 g[0,1] = g[1,2] = g[2,0] = g[3,4] = 10 # We need to specify the desired cluster count explicitly; this is # because edge betweenness-based detection does not play well with # modularity-based cluster count selection (the edge weights have # different semantics) so we need to give igraph a hint cl = g.community_edge_betweenness(weights="weight").as_clustering(n=2) self.assertMembershipsEqual(cl, [0,0,0,1,1]) self.assertAlmostEqual(cl.q, 0.2750, places=3) def testEigenvector(self): g = Graph.Full(5) + Graph.Full(5) g.add_edges([(0, 5)]) cl = g.community_leading_eigenvector() self.assertMembershipsEqual(cl, [0,0,0,0,0,1,1,1,1,1]) self.assertAlmostEqual(cl.q, 0.4523, places=3) cl = g.community_leading_eigenvector(2) self.assertMembershipsEqual(cl, [0,0,0,0,0,1,1,1,1,1]) self.assertAlmostEqual(cl.q, 0.4523, places=3) def testInfomap(self): g = Graph.Famous("zachary") cl = g.community_infomap() self.assertAlmostEqual(cl.codelength, 4.60605, places=3) self.assertAlmostEqual(cl.q, 0.40203, places=3) self.assertMembershipsEqual(cl, [1,1,1,1,2,2,2,1,0,1,2,1,1,1,0,0,2,1,0,1,0,1] + [0]*12) # Smoke testing with vertex and edge weights v_weights = [random.randint(1, 5) for _ in range(g.vcount())] e_weights = [random.randint(1, 5) for _ in range(g.ecount())] cl = g.community_infomap(edge_weights=e_weights) cl = g.community_infomap(vertex_weights=v_weights) cl = g.community_infomap(edge_weights=e_weights, vertex_weights=v_weights) def testLabelPropagation(self): # Nothing to test there really, since the algorithm # is pretty nondeterministic. We just do a quick smoke # test. g = Graph.GRG(100, 0.2) cl = g.community_label_propagation() g = Graph([(0,1),(1,2),(2,3)]) g.es["weight"] = [2, 1, 2] g.vs["initial"] = [0, -1, -1, 1] cl = g.community_label_propagation("weight", "initial", [1,0,0,1]) self.assertMembershipsEqual(cl, [0,0,1,1]) cl = g.community_label_propagation(initial="initial", fixed=[1,0,0,1]) self.assertTrue(cl.membership == [0, 0, 1, 1] or \ cl.membership == [0, 1, 1, 1] or \ cl.membership == [0, 0, 0, 1]) def testMultilevel(self): # Example graph from the paper g = Graph(16) g += [(0,2), (0,3), (0,4), (0,5), (1,2), (1,4), (1,7), (2,4), (2,5), (2,6), (3,7), (4,10), (5,7), (5,11), (6,7), (6,11), (8,9), (8,10), (8,11), (8,14), (8,15), (9,12), (9,14), (10,11), (10,12), (10,13), (10,14), (11,13)] cls = g.community_multilevel(return_levels=True) self.assertTrue(len(cls) == 2) self.assertMembershipsEqual(cls[0], [1,1,1,0,1,1,0,0,2,2,2,3,2,3,2,2]) self.assertMembershipsEqual(cls[1], [0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1]) self.assertAlmostEqual(cls[0].q, 0.346301, places=5) self.assertAlmostEqual(cls[1].q, 0.392219, places=5) def testOptimalModularity(self): try: g = Graph.Famous("bull") cl = g.community_optimal_modularity() self.assertTrue(len(cl) == 2) self.assertMembershipsEqual(cl, [0, 0, 1, 0, 1]) self.assertAlmostEqual(cl.q, 0.08, places=7) ws = [i % 5 for i in range(g.ecount())] cl = g.community_optimal_modularity(weights=ws) self.assertAlmostEqual(cl.q, g.modularity(cl.membership, weights=ws), places=7) g = Graph.Famous("zachary") cl = g.community_optimal_modularity() self.assertTrue(len(cl) == 4) self.assertMembershipsEqual(cl, [0, 0, 0, 0, 1, 1, 1, 0, 2, 2, 1, \ 0, 0, 0, 2, 2, 1, 0, 2, 0, 2, 0, 2, 3, 3, 3, 2, 3, 3, \ 2, 2, 3, 2, 2]) self.assertAlmostEqual(cl.q, 0.4197896, places=7) ws = [2+(i % 3) for i in range(g.ecount())] cl = g.community_optimal_modularity(weights=ws) self.assertAlmostEqual(cl.q, g.modularity(cl.membership, weights=ws), places=7) except NotImplementedError: # Well, meh pass def testSpinglass(self): g = Graph.Full(5) + Graph.Full(5) + Graph.Full(5) g += [(0,5), (5,10), (10, 0)] # Spinglass community detection is a bit unstable, so run it three times ok = False for i in range(3): cl = g.community_spinglass() if self.reindexMembership(cl) == [0,0,0,0,0,1,1,1,1,1,2,2,2,2,2]: ok = True break self.assertTrue(ok) def testWalktrap(self): g = Graph.Full(5) + Graph.Full(5) + Graph.Full(5) g += [(0,5), (5,10), (10, 0)] cl = g.community_walktrap().as_clustering() self.assertMembershipsEqual(cl, [0,0,0,0,0,1,1,1,1,1,2,2,2,2,2]) cl = g.community_walktrap(steps=3).as_clustering() self.assertMembershipsEqual(cl, [0,0,0,0,0,1,1,1,1,1,2,2,2,2,2]) def testLeiden(self): # Example from paper (Fig. C.1) high_weight = 3.0 low_weight = 3.0/2.0 edges = [(0, 1, high_weight), (2, 3, high_weight), (4, 2, high_weight), (3, 4, high_weight), (5, 6, high_weight), (7, 5, high_weight), (6, 7, high_weight), (0, 2, low_weight), (0, 3, low_weight), (0, 4, low_weight), (1, 5, low_weight), (1, 6, low_weight), (1, 7, low_weight)] G = Graph.TupleList(edges, weights=True) import random random.seed(0) set_random_number_generator(random) # We don't find the optimal partition if we are greedy cl = G.community_leiden("CPM", resolution_parameter=1, weights='weight', beta=0, n_iterations=-1) self.assertMembershipsEqual(cl, [0, 0, 1, 1, 1, 2, 2, 2]) random.seed(0) set_random_number_generator(random) # We can find the optimal partition if we allow for non-decreasing moves # (The randomness is only present in the refinement, which is why we # start from all nodes in the same community: this should then be # refined). cl = G.community_leiden("CPM", resolution_parameter=1, weights='weight', beta=5, n_iterations=-1, initial_membership=[0]*G.vcount()) self.assertMembershipsEqual(cl, [0, 1, 0, 0, 0, 1, 1, 1]) class CohesiveBlocksTests(unittest.TestCase): def genericTests(self, cbs): self.assertTrue(isinstance(cbs, CohesiveBlocks)) self.assertTrue(all(cbs.cohesion(i) == c for i, c in enumerate(cbs.cohesions()))) self.assertTrue(all(cbs.parent(i) == c for i, c in enumerate(cbs.parents()))) self.assertTrue(all(cbs.max_cohesion(i) == c for i, c in enumerate(cbs.max_cohesions()))) def testCohesiveBlocks1(self): # Taken from the igraph R manual g = Graph.Full(4) + Graph(2) + [(3, 4), (4, 5), (4, 2)] g *= 3 g += [(0, 6), (1, 7), (0, 12), (4, 0), (4, 1)] cbs = g.cohesive_blocks() self.genericTests(cbs) self.assertEqual(sorted(list(cbs)), [list(range(0, 5)), list(range(18)), [0, 1, 2, 3, 4, 6, 7, 8, 9, 10], list(range(6, 10)), list(range(12, 16)), list(range(12, 17))]) self.assertEqual(cbs.cohesions(), [1, 2, 2, 4, 3, 3]) self.assertEqual(cbs.max_cohesions(), [4, 4, 4, 4, 4, 1, 3, 3, 3, 3, 2, 1, 3, 3, 3, 3, 2, 1]) self.assertEqual(cbs.parents(), [None, 0, 0, 1, 2, 1]) def testCohesiveBlocks2(self): # Taken from the Moody-White paper g = Graph.Formula("1-2:3:4:5:6, 2-3:4:5:7, 3-4:6:7, 4-5:6:7, " "5-6:7:21, 6-7, 7-8:11:14:19, 8-9:11:14, 9-10, " "10-12:13, 11-12:14, 12-16, 13-16, 14-15, 15-16, " "17-18:19:20, 18-20:21, 19-20:22:23, 20-21, " "21-22:23, 22-23") cbs = g.cohesive_blocks() self.genericTests(cbs) expected_blocks = [list(range(7)), list(range(23)), list(range(7))+list(range(16, 23)), list(range(6, 16)), [6, 7, 10, 13]] observed_blocks = sorted(sorted(int(x)-1 for x in g.vs[bl]["name"]) for bl in cbs) self.assertEqual(expected_blocks, observed_blocks) self.assertTrue(cbs.cohesions() == [1, 2, 2, 5, 3]) self.assertTrue(cbs.parents() == [None, 0, 0, 1, 2]) self.assertTrue(sorted(cbs.hierarchy().get_edgelist()) == [(0, 1), (0, 2), (1, 3), (2, 4)]) def testCohesiveBlockingErrors(self): g = Graph.GRG(100, 0.2) g.to_directed() self.assertRaises(InternalError, g.cohesive_blocks) class ComparisonTests(unittest.TestCase): def setUp(self): self.clusterings = [ ([0, 0, 0, 1, 1, 1], [1, 1, 1, 0, 0, 0]), ([0, 0, 0, 1, 1, 1], [0, 0, 1, 1, 2, 2]), ([0, 0, 0, 0, 0, 0], [0, 1, 2, 3, 4, 5]), ([0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 2, 2], [2, 0, 1, 0, 2, 0, 2, 0, 1, 0, 3, 1]) ] def _testMethod(self, method, expected): for clusters, result in zip(self.clusterings, expected): self.assertAlmostEqual(compare_communities(method=method, *clusters), result, places=3) def testCompareVI(self): expected = [0, 0.8675, math.log(6)] self._testMethod(None, expected) self._testMethod("vi", expected) def testCompareNMI(self): expected = [1, 0.5158, 0] self._testMethod("nmi", expected) def testCompareSplitJoin(self): expected = [0, 3, 5, 11] self._testMethod("split", expected) l1 = [1, 1, 1, 1, 2, 2, 2, 3, 3, 3, 3, 3] l2 = [3, 1, 2, 1, 3, 1, 3, 1, 2, 1, 4, 2] self.assertEqual(split_join_distance(l1, l2), (6, 5)) def testCompareRand(self): expected = [1, 2/3., 0, 0.590909] self._testMethod("rand", expected) def testCompareAdjustedRand(self): expected = [1, 0.242424, 0, -0.04700353] self._testMethod("adjusted_rand", expected) def testRemoveNone(self): l1 = Clustering([1, 1, 1, None, None, 2, 2, 2, 2]) l2 = Clustering([1, 1, 2, 2, None, 2, 3, 3, None]) self.assertAlmostEqual(compare_communities(l1, l2, "nmi", remove_none=True), \ 0.5158, places=3) def suite(): decomposition_suite = unittest.makeSuite(DecompositionTests) clustering_suite = unittest.makeSuite(ClusteringTests) vertex_clustering_suite = unittest.makeSuite(VertexClusteringTests) cover_suite = unittest.makeSuite(CoverTests) community_suite = unittest.makeSuite(CommunityTests) cohesive_blocks_suite = unittest.makeSuite(CohesiveBlocksTests) comparison_suite = unittest.makeSuite(ComparisonTests) return unittest.TestSuite([decomposition_suite, clustering_suite, \ vertex_clustering_suite, cover_suite, community_suite, \ cohesive_blocks_suite, comparison_suite]) def test(): runner = unittest.TextTestRunner() runner.run(suite()) if __name__ == "__main__": test() python-igraph-0.8.0/tests/test_cliques.py0000644000076500000240000002006713606025206020765 0ustar tamasstaff00000000000000from __future__ import print_function import unittest from igraph import * from .utils import is_pypy, skipIf, temporary_file class CliqueTests(unittest.TestCase): def setUp(self): self.g=Graph.Full(6) self.g.delete_edges([(0, 1), (0, 2), (3, 5)]) def testCliques(self): tests = {(4, -1): [[1, 2, 3, 4], [1, 2, 4, 5]], (2, 2): [[0, 3], [0, 4], [0, 5], [1, 2], [1, 3], [1, 4], [1, 5], [2, 3], [2, 4], [2, 5], [3, 4], [4, 5]], (-1, -1): [[0], [1], [2], [3], [4], [5], [0, 3], [0, 4], [0, 5], [1, 2], [1, 3], [1, 4], [1, 5], [2, 3], [2, 4], [2, 5], [3, 4], [4, 5], [0, 3, 4], [0, 4, 5], [1, 2, 3], [1, 2, 4], [1, 2, 5], [1, 3, 4], [1, 4, 5], [2, 3, 4], [2, 4, 5], [1, 2, 3, 4], [1, 2, 4, 5]]} for (lo, hi), exp in tests.items(): self.assertEqual(sorted(exp), sorted(map(sorted, self.g.cliques(lo, hi)))) def testLargestCliques(self): self.assertEqual(sorted(map(sorted, self.g.largest_cliques())), [[1, 2, 3, 4], [1, 2, 4, 5]]) def testMaximalCliques(self): self.assertEqual(sorted(map(sorted, self.g.maximal_cliques())), [[0, 3, 4], [0, 4, 5], [1, 2, 3, 4], [1, 2, 4, 5]]) self.assertEqual(sorted(map(sorted, self.g.maximal_cliques(min=4))), [[1, 2, 3, 4], [1, 2, 4, 5]]) self.assertEqual(sorted(map(sorted, self.g.maximal_cliques(max=3))), [[0, 3, 4], [0, 4, 5]]) def testMaximalCliquesFile(self): def read_cliques(fname): with open(fname) as fp: return sorted(sorted(int(item) for item in line.split()) for line in fp) with temporary_file() as fname: self.g.maximal_cliques(file=fname) self.assertEqual([[0, 3, 4], [0, 4, 5], [1, 2, 3, 4], [1, 2, 4, 5]], read_cliques(fname)) with temporary_file() as fname: self.g.maximal_cliques(min=4, file=fname) self.assertEqual([[1, 2, 3, 4], [1, 2, 4, 5]], read_cliques(fname)) with temporary_file() as fname: self.g.maximal_cliques(max=3, file=fname) self.assertEqual([[0, 3, 4], [0, 4, 5]], read_cliques(fname)) def testCliqueNumber(self): self.assertEqual(self.g.clique_number(), 4) self.assertEqual(self.g.omega(), 4) class IndependentVertexSetTests(unittest.TestCase): def setUp(self): self.g1=Graph.Tree(5, 2, TREE_UNDIRECTED) self.g2=Graph.Tree(10, 2, TREE_UNDIRECTED) def testIndependentVertexSets(self): tests = {(4, -1): [], (2, 2): [(0, 3), (0, 4), (1, 2), (2, 3), (2, 4), (3, 4)], (-1, -1): [(0,), (1,), (2,), (3,), (4,), (0, 3), (0, 4), (1, 2), (2, 3), (2, 4), (3, 4), (0, 3, 4), (2, 3, 4)]} for (lo, hi), exp in tests.items(): self.assertEqual(exp, self.g1.independent_vertex_sets(lo, hi)) def testLargestIndependentVertexSets(self): self.assertEqual(self.g1.largest_independent_vertex_sets(), [(0, 3, 4), (2, 3, 4)]) def testMaximalIndependentVertexSets(self): self.assertEqual(self.g2.maximal_independent_vertex_sets(), [(0, 3, 4, 5, 6), (0, 3, 5, 6, 9), (0, 4, 5, 6, 7, 8), (0, 5, 6, 7, 8, 9), (1, 2, 7, 8, 9), (1, 5, 6, 7, 8, 9), (2, 3, 4), (2, 3, 9), (2, 4, 7, 8)]) def testIndependenceNumber(self): self.assertEqual(self.g2.independence_number(), 6) self.assertEqual(self.g2.alpha(), 6) class MotifTests(unittest.TestCase): def setUp(self): self.g = Graph.Erdos_Renyi(100, 0.2, directed=True) def testDyads(self): """ @note: this test is not exhaustive, it only checks whether the L{DyadCensus} objects "understand" attribute and item accessors """ dc = self.g.dyad_census() accessors = ["mut", "mutual", "asym", "asymm", "asymmetric", "null"] for a in accessors: self.assertTrue(isinstance(getattr(dc, a), int)) self.assertTrue(isinstance(dc[a], int)) self.assertTrue(isinstance(list(dc), list)) self.assertTrue(isinstance(tuple(dc), tuple)) self.assertTrue(len(list(dc)) == 3) self.assertTrue(len(tuple(dc)) == 3) def testTriads(self): """ @note: this test is not exhaustive, it only checks whether the L{TriadCensus} objects "understand" attribute and item accessors """ tc = self.g.triad_census() accessors = ["003", "012", "021d", "030C"] for a in accessors: self.assertTrue(isinstance(getattr(tc, "t"+a), int)) self.assertTrue(isinstance(tc[a], int)) self.assertTrue(isinstance(list(tc), list)) self.assertTrue(isinstance(tuple(tc), tuple)) self.assertTrue(len(list(tc)) == 16) self.assertTrue(len(tuple(tc)) == 16) class CliqueBenchmark(object): """This is a benchmark, not a real test case. You can run it using: >>> from igraph.test.cliques import CliqueBenchmark >>> CliqueBenchmark().run() """ def __init__(self): from time import time import gc self.time = time self.gc_collect = gc.collect def run(self): self.printIntro() self.testRandom() self.testMoonMoser() self.testGRG() def printIntro(self): print("n = number of vertices") print("#cliques = number of maximal cliques found") print("t1 = time required to determine the clique number") print("t2 = time required to determine and save all maximal cliques") print() def timeit(self, g): start = self.time() omega = g.clique_number() mid = self.time() cl = g.maximal_cliques() end = self.time() self.gc_collect() return len(cl), mid-start, end-mid def testRandom(self): np = {100: [0.6, 0.7], 300: [0.1, 0.2, 0.3, 0.4], 500: [0.1, 0.2, 0.3], 700: [0.1, 0.2], 1000:[0.1, 0.2], 10000: [0.001, 0.003, 0.005, 0.01, 0.02]} print() print("Erdos-Renyi random graphs") print(" n p #cliques t1 t2") for n in sorted(np.keys()): for p in np[n]: g = Graph.Erdos_Renyi(n, p) result = self.timeit(g) print("%8d %8.3f %8d %8.4fs %8.4fs" % tuple([n, p] + list(result))) def testMoonMoser(self): ns = [15, 27, 33] print() print("Moon-Moser graphs") print(" n exp_clqs #cliques t1 t2") for n in ns: n3 = n/3 types = range(n3) * 3 el = [(i, j) for i in range(n) for j in range(i+1,n) if types[i] != types[j]] g = Graph(n, el) result = self.timeit(g) print("%8d %8d %8d %8.4fs %8.4fs" % tuple([n, (3**(n/3))] + list(result))) def testGRG(self): ns = [100, 1000, 5000, 10000, 25000, 50000] print() print("Geometric random graphs") print(" n d #cliques t1 t2") for n in ns: d = 2. / (n ** 0.5) g = Graph.GRG(n, d) result = self.timeit(g) print("%8d %8.3f %8d %8.4fs %8.4fs" % tuple([n, d] + list(result))) def suite(): clique_suite = unittest.makeSuite(CliqueTests) indvset_suite = unittest.makeSuite(IndependentVertexSetTests) motif_suite = unittest.makeSuite(MotifTests) return unittest.TestSuite([clique_suite, indvset_suite, motif_suite]) def test(): runner = unittest.TextTestRunner() runner.run(suite()) if __name__ == "__main__": test() python-igraph-0.8.0/tests/test_matching.py0000644000076500000240000000523013606025206021105 0ustar tamasstaff00000000000000import unittest from igraph import * def powerset(iterable): items_powers = [(item, 1 << i) for i, item in enumerate(iterable)] for i in range(1 << len(items_powers)): for item, power in items_powers: if i & power: yield item leda_graph = Graph([ (0,8),(0,12),(0,14),(1,9),(1,10),(1,13), (2,8),(2,9),(3,10),(3,11),(3,13),(4,9),(4,14), (5,14),(6,9),(6,14),(7,8),(7,12),(7,14)]) leda_graph.vs["type"] = [0]*8+[1]*7 class MatchingTests(unittest.TestCase): def setUp(self): self.matching = Matching(leda_graph, [12, 10, 8, 13, -1, 14, 9, -1, 2, 6, 1, -1, 0, 3, 5], "type") def testIsMaximal(self): self.assertTrue(self.matching.is_maximal()) self.matching.matching[0] = -1 self.matching.matching[12] = -1 self.assertFalse(self.matching.is_maximal()) def testMatchingRetrieval(self): m = [12, 10, 8, 13, -1, 14, 9, -1, 2, 6, 1, -1, 0, 3, 5] self.assertEqual(self.matching.matching, m) for i, mate in enumerate(m): if mate == -1: self.assertFalse(self.matching.is_matched(i)) self.assertEqual(self.matching.match_of(i), None) else: self.assertTrue(self.matching.is_matched(i)) self.assertEqual(self.matching.match_of(i), mate) self.assertEqual(self.matching.match_of( leda_graph.vs[i]).index, leda_graph.vs[mate].index) class MaximumBipartiteMatchingTests(unittest.TestCase): def testBipartiteMatchingSimple(self): # Specifying the "type" attribute explicitly matching = leda_graph.maximum_bipartite_matching("type") self.assertEqual(len(matching), 6) self.assertTrue(matching.is_maximal()) # Using the default attribute matching = leda_graph.maximum_bipartite_matching() self.assertEqual(len(matching), 6) self.assertTrue(matching.is_maximal()) def testBipartiteMatchingErrors(self): # Type vector too short g = Graph([(0, 1), (1, 2), (2, 3)]) self.assertRaises(InternalError, g.maximum_bipartite_matching, types=[0,1,0]) # Graph not bipartite self.assertRaises(InternalError, g.maximum_bipartite_matching, types=[0,1,1,1]) def suite(): matching_suite = unittest.makeSuite(MatchingTests) bipartite_unweighted_suite = unittest.makeSuite(MaximumBipartiteMatchingTests) return unittest.TestSuite([matching_suite, bipartite_unweighted_suite]) def test(): runner = unittest.TextTestRunner() runner.run(suite()) if __name__ == "__main__": test() python-igraph-0.8.0/tests/test_isomorphism.py0000644000076500000240000003103113606025422021662 0ustar tamasstaff00000000000000import unittest from igraph import * from itertools import permutations from random import shuffle def node_compat(g1, g2, v1, v2): """Node compatibility function for isomorphism tests""" return g1.vs[v1]["color"] == g2.vs[v2]["color"] def edge_compat(g1, g2, e1, e2): """Edge compatibility function for isomorphism tests""" return g1.es[e1]["color"] == g2.es[e2]["color"] class IsomorphismTests(unittest.TestCase): def testIsomorphic(self): g1 = Graph(8, [(0, 4), (0, 5), (0, 6), \ (1, 4), (1, 5), (1, 7), \ (2, 4), (2, 6), (2, 7), \ (3, 5), (3, 6), (3, 7)]) g2 = Graph(8, [(0, 1), (0, 3), (0, 4), \ (2, 3), (2, 1), (2, 6), \ (5, 1), (5, 4), (5, 6), \ (7, 3), (7, 6), (7, 4)]) # Test the isomorphy of g1 and g2 self.assertTrue(g1.isomorphic(g2)) self.assertTrue(g2.isomorphic_vf2(g1, return_mapping_21=True) \ == (True, None, [0, 2, 5, 7, 1, 3, 4, 6])) self.assertTrue(g2.isomorphic_bliss(g1, return_mapping_21=True, sh1="fl")\ == (True, None, [0, 2, 5, 7, 1, 3, 4, 6])) self.assertRaises(ValueError, g2.isomorphic_bliss, g1, sh2="nonexistent") # Test the automorphy of g1 self.assertTrue(g1.isomorphic()) self.assertTrue(g1.isomorphic_vf2(return_mapping_21=True) \ == (True, None, [0, 1, 2, 3, 4, 5, 6, 7])) # Test VF2 with colors self.assertTrue(g1.isomorphic_vf2(g2, color1=[0,1,0,1,0,1,0,1], color2=[0,0,1,1,0,0,1,1])) g1.vs["color"] = [0,1,0,1,0,1,0,1] g2.vs["color"] = [0,0,1,1,0,1,1,0] self.assertTrue(not g1.isomorphic_vf2(g2, "color", "color")) # Test bliss with colors self.assertTrue(g1.isomorphic_bliss(g2, color1=[0,0,0,0,0,0,0,0], color2=[0,0,0,0,0,0,0,0])) self.assertTrue(g1.isomorphic_bliss(g2, color1=[1,0,2,0,0,0,0,0], color2=[1,0,2,0,0,0,0,0])) self.assertTrue(g1.isomorphic_bliss(g2, color1=[0,1,0,1,0,1,0,1], color2=[0,0,1,1,0,0,1,1])) # Test VF2 with vertex and edge colors self.assertTrue(g1.isomorphic_vf2(g2, color1=[0,1,0,1,0,1,0,1], color2=[0,0,1,1,0,0,1,1])) g1.es["color"] = range(12) g2.es["color"] = [0]*6 + [1]*6 self.assertTrue(not g1.isomorphic_vf2(g2, "color", "color", "color", "color")) # Test VF2 with node compatibility function g2.vs["color"] = [0,0,1,1,0,0,1,1] self.assertTrue(g1.isomorphic_vf2(g2, node_compat_fn=node_compat)) g2.vs["color"] = [0,0,1,1,0,1,1,0] self.assertTrue(not g1.isomorphic_vf2(g2, node_compat_fn=node_compat)) # Test VF2 with node edge compatibility function g2.vs["color"] = [0,0,1,1,0,0,1,1] g1.es["color"] = range(12) g2.es["color"] = [0]*6 + [1]*6 self.assertTrue(not g1.isomorphic_vf2(g2, node_compat_fn=node_compat, edge_compat_fn=edge_compat)) def testIsomorphicCallback(self): maps = [] def callback(g1, g2, map1, map2): maps.append(map1) return True # Test VF2 callback g = Graph(6, [(0,1), (2,3), (4,5), (0,2), (2,4), (1,3), (3,5)]) g.isomorphic_vf2(g, callback=callback) expected_maps = [[0,1,2,3,4,5], [1,0,3,2,5,4], [4,5,2,3,0,1], [5,4,3,2,1,0]] self.assertTrue(sorted(maps) == expected_maps) maps[:] = [] g3 = Graph.Full(4) g3.vs["color"] = [0,1,1,0] g3.isomorphic_vf2(callback=callback, color1="color", color2="color") expected_maps = [[0,1,2,3], [0,2,1,3], [3,1,2,0], [3,2,1,0]] self.assertTrue(sorted(maps) == expected_maps) def testCountIsomorphisms(self): g = Graph.Full(4) self.assertTrue(g.count_automorphisms_vf2() == 24) g = Graph(6, [(0,1), (2,3), (4,5), (0,2), (2,4), (1,3), (3,5)]) self.assertTrue(g.count_automorphisms_vf2() == 4) # Some more tests with colors g3 = Graph.Full(4) g3.vs["color"] = [0,1,1,0] self.assertTrue(g3.count_isomorphisms_vf2() == 24) self.assertTrue(g3.count_isomorphisms_vf2(color1="color", color2="color") == 4) self.assertTrue(g3.count_isomorphisms_vf2(color1=[0,1,2,0], color2=(0,1,2,0)) == 2) self.assertTrue(g3.count_isomorphisms_vf2(edge_color1=[0,1,0,0,0,1], edge_color2=[0,1,0,0,0,1]) == 2) # Test VF2 with node/edge compatibility function g3.vs["color"] = [0,1,1,0] self.assertTrue(g3.count_isomorphisms_vf2(node_compat_fn=node_compat) == 4) g3.vs["color"] = [0,1,2,0] self.assertTrue(g3.count_isomorphisms_vf2(node_compat_fn=node_compat) == 2) g3.es["color"] = [0,1,0,0,0,1] self.assertTrue(g3.count_isomorphisms_vf2(edge_compat_fn=edge_compat) == 2) def testGetIsomorphisms(self): g = Graph(6, [(0,1), (2,3), (4,5), (0,2), (2,4), (1,3), (3,5)]) maps = g.get_automorphisms_vf2() expected_maps = [[0,1,2,3,4,5], [1,0,3,2,5,4], [4,5,2,3,0,1], [5,4,3,2,1,0]] self.assertTrue(maps == expected_maps) g3 = Graph.Full(4) g3.vs["color"] = [0,1,1,0] expected_maps = [[0,1,2,3], [0,2,1,3], [3,1,2,0], [3,2,1,0]] self.assertTrue(sorted(g3.get_automorphisms_vf2(color="color")) == expected_maps) class SubisomorphismTests(unittest.TestCase): def testSubisomorphicLAD(self): g = Graph.Lattice([3,3], circular=False) g2 = Graph([(0,1), (1,2), (1,3)]) g3 = g + [(0,4), (2,4), (6,4), (8,4), (3,1), (1,5), (5,7), (7,3)] self.assertTrue(g.subisomorphic_lad(g2)) self.assertFalse(g2.subisomorphic_lad(g)) # Test 'induced' self.assertFalse(g3.subisomorphic_lad(g, induced=True)) self.assertTrue(g3.subisomorphic_lad(g, induced=False)) self.assertTrue(g3.subisomorphic_lad(g)) self.assertTrue(g3.subisomorphic_lad(g2, induced=True)) self.assertTrue(g3.subisomorphic_lad(g2, induced=False)) self.assertTrue(g3.subisomorphic_lad(g2)) # Test with limited vertex matching domains = [[4], [0,1,2,3,5,6,7,8], [0,1,2,3,5,6,7,8], [0,1,2,3,5,6,7,8]] self.assertTrue(g.subisomorphic_lad(g2, domains=domains)) domains = [[], [0,1,2,3,5,6,7,8], [0,1,2,3,5,6,7,8], [0,1,2,3,5,6,7,8]] self.assertTrue(not g.subisomorphic_lad(g2, domains=domains)) # Corner cases empty = Graph() self.assertTrue(g.subisomorphic_lad(empty)) self.assertTrue(empty.subisomorphic_lad(empty)) def testGetSubisomorphismsLAD(self): g = Graph.Lattice([3,3], circular=False) g2 = Graph([(0,1), (1,2), (2,3), (3,0)]) g3 = g + [(0,4), (2,4), (6,4), (8,4), (3,1), (1,5), (5,7), (7,3)] all_subiso = "0143 0341 1034 1254 1430 1452 2145 2541 3014 3410 3476 \ 3674 4103 4125 4301 4367 4521 4587 4763 4785 5214 5412 5478 5874 6347 \ 6743 7436 7458 7634 7854 8547 8745" all_subiso = sorted([int(x) for x in item] for item in all_subiso.split()) self.assertEqual(all_subiso, sorted(g.get_subisomorphisms_lad(g2))) self.assertEqual([], sorted(g2.get_subisomorphisms_lad(g))) # Test 'induced' induced_subiso = "1375 1573 3751 5731 7513 7315 5137 3157" induced_subiso = sorted([int(x) for x in item] for item in induced_subiso.split()) all_subiso_extra = sorted(all_subiso + induced_subiso) self.assertEqual(induced_subiso, sorted(g3.get_subisomorphisms_lad(g2, induced=True))) self.assertEqual([], g3.get_subisomorphisms_lad(g, induced=True)) # Test with limited vertex matching limited_subiso = [iso for iso in all_subiso if iso[0] == 4] domains = [[4], [0,1,2,3,5,6,7,8], [0,1,2,3,5,6,7,8], [0,1,2,3,5,6,7,8]] self.assertEqual(limited_subiso, sorted(g.get_subisomorphisms_lad(g2, domains=domains))) domains = [[], [0,1,2,3,5,6,7,8], [0,1,2,3,5,6,7,8], [0,1,2,3,5,6,7,8]] self.assertEqual([], sorted(g.get_subisomorphisms_lad(g2, domains=domains))) # Corner cases empty = Graph() self.assertEqual([], g.get_subisomorphisms_lad(empty)) self.assertEqual([], empty.get_subisomorphisms_lad(empty)) def testSubisomorphicVF2(self): g = Graph.Lattice([3,3], circular=False) g2 = Graph([(0,1), (1,2), (1,3)]) self.assertTrue(g.subisomorphic_vf2(g2)) self.assertTrue(not g2.subisomorphic_vf2(g)) # Test with vertex colors g.vs["color"] = [0,0,0,0,1,0,0,0,0] g2.vs["color"] = [1,0,0,0] self.assertTrue(g.subisomorphic_vf2(g2, node_compat_fn=node_compat)) g2.vs["color"] = [2,0,0,0] self.assertTrue(not g.subisomorphic_vf2(g2, node_compat_fn=node_compat)) # Test with edge colors g.es["color"] = [1] + [0]*(g.ecount()-1) g2.es["color"] = [1] + [0]*(g2.ecount()-1) self.assertTrue(g.subisomorphic_vf2(g2, edge_compat_fn=edge_compat)) g2.es[0]["color"] = [2] self.assertTrue(not g.subisomorphic_vf2(g2, node_compat_fn=node_compat)) def testCountSubisomorphisms(self): g = Graph.Lattice([3,3], circular=False) g2 = Graph.Lattice([2,2], circular=False) self.assertTrue(g.count_subisomorphisms_vf2(g2) == 4*4*2) self.assertTrue(g2.count_subisomorphisms_vf2(g) == 0) # Test with vertex colors g.vs["color"] = [0,0,0,0,1,0,0,0,0] g2.vs["color"] = [1,0,0,0] self.assertTrue(g.count_subisomorphisms_vf2(g2, "color", "color") == 4*2) self.assertTrue(g.count_subisomorphisms_vf2(g2, node_compat_fn=node_compat) == 4*2) # Test with edge colors g.es["color"] = [1] + [0]*(g.ecount()-1) g2.es["color"] = [1] + [0]*(g2.ecount()-1) self.assertTrue(g.count_subisomorphisms_vf2(g2, edge_color1="color", edge_color2="color") == 2) self.assertTrue(g.count_subisomorphisms_vf2(g2, edge_compat_fn=edge_compat) == 2) class PermutationTests(unittest.TestCase): def testCanonicalPermutation(self): # Simple case: two ring graphs g1 = Graph(4, [(0, 1), (1, 2), (2, 3), (3, 0)]) g2 = Graph(4, [(0, 1), (1, 3), (3, 2), (2, 0)]) cp = g1.canonical_permutation() g3 = g1.permute_vertices(cp) cp = g2.canonical_permutation() g4 = g2.permute_vertices(cp) self.assertTrue(g3.vcount() == g4.vcount()) self.assertTrue(sorted(g3.get_edgelist()) == sorted(g4.get_edgelist())) # Simple case with coloring cp = g1.canonical_permutation(color = [0, 0, 1, 1]) g3 = g1.permute_vertices(cp) cp = g2.canonical_permutation(color = [0, 0, 1, 1]) g4 = g2.permute_vertices(cp) self.assertTrue(g3.vcount() == g4.vcount()) self.assertTrue(sorted(g3.get_edgelist()) == sorted(g4.get_edgelist())) # More complicated one: small GRG, random permutation g = Graph.GRG(10, 0.5) perm = list(range(10)) shuffle(perm) g2 = g.permute_vertices(perm) g3 = g.permute_vertices(g.canonical_permutation()) g4 = g2.permute_vertices(g2.canonical_permutation()) self.assertTrue(g3.vcount() == g4.vcount()) self.assertTrue(sorted(g3.get_edgelist()) == sorted(g4.get_edgelist())) def testPermuteVertices(self): g1 = Graph(8, [(0, 4), (0, 5), (0, 6), \ (1, 4), (1, 5), (1, 7), \ (2, 4), (2, 6), (2, 7), \ (3, 5), (3, 6), (3, 7)]) g2 = Graph(8, [(0, 1), (0, 3), (0, 4), \ (2, 3), (2, 1), (2, 6), \ (5, 1), (5, 4), (5, 6), \ (7, 3), (7, 6), (7, 4)]) _, _, mapping = g1.isomorphic_vf2(g2, return_mapping_21=True) g3 = g2.permute_vertices(mapping) self.assertTrue(g3.vcount() == g2.vcount() and g3.ecount() == g2.ecount()) self.assertTrue(set(g3.get_edgelist()) == set(g1.get_edgelist())) def suite(): isomorphism_suite = unittest.makeSuite(IsomorphismTests) subisomorphism_suite = unittest.makeSuite(SubisomorphismTests) permutation_suite = unittest.makeSuite(PermutationTests) return unittest.TestSuite([isomorphism_suite, subisomorphism_suite, \ permutation_suite]) def test(): runner = unittest.TextTestRunner() runner.run(suite()) if __name__ == "__main__": test() python-igraph-0.8.0/tests/test_vertexseq.py0000644000076500000240000003200713614530423021344 0ustar tamasstaff00000000000000# vim:ts=4 sw=4 sts=4: import unittest from igraph import * from .utils import is_pypy, skipIf try: import numpy as np except ImportError: np = None class VertexTests(unittest.TestCase): def setUp(self): self.g = Graph.Full(10) def testHash(self): data = {} n = self.g.vcount() for i in range(n): code1 = hash(self.g.vs[i]) code2 = hash(self.g.vs[i]) self.assertEqual(code1, code2) data[self.g.vs[i]] = i for i in range(n): self.assertEqual(i, data[self.g.vs[i]]) def testRichCompare(self): g2 = Graph.Full(10) for i in range(self.g.vcount()): for j in range(self.g.vcount()): self.assertEqual(i == j, self.g.vs[i] == self.g.vs[j]) self.assertEqual(i != j, self.g.vs[i] != self.g.vs[j]) self.assertEqual(i < j, self.g.vs[i] < self.g.vs[j]) self.assertEqual(i > j, self.g.vs[i] > self.g.vs[j]) self.assertEqual(i <= j, self.g.vs[i] <= self.g.vs[j]) self.assertEqual(i >= j, self.g.vs[i] >= self.g.vs[j]) self.assertFalse(self.g.vs[i] == g2.vs[j]) self.assertFalse(self.g.vs[i] != g2.vs[j]) self.assertFalse(self.g.vs[i] < g2.vs[j]) self.assertFalse(self.g.vs[i] > g2.vs[j]) self.assertFalse(self.g.vs[i] <= g2.vs[j]) self.assertFalse(self.g.vs[i] >= g2.vs[j]) self.assertFalse(self.g.es[i] == self.g.vs[j]) def testUpdateAttributes(self): v = self.g.vs[0] v.update_attributes(a=2) self.assertEqual(v["a"], 2) v.update_attributes([("a", 3), ("b", 4)], c=5, d=6) self.assertEqual(v.attributes(), dict(a=3, b=4, c=5, d=6)) v.update_attributes(dict(b=44, c=55)) self.assertEqual(v.attributes(), dict(a=3, b=44, c=55, d=6)) def testPhantomVertex(self): v = self.g.vs[9] v.delete() # v is now a phantom vertex; try to freak igraph out now :) self.assertRaises(ValueError, v.update_attributes, a=2) self.assertRaises(ValueError, v.__getitem__, "a") self.assertRaises(ValueError, v.__setitem__, "a", 4) self.assertRaises(ValueError, v.__delitem__, "a") self.assertRaises(ValueError, v.attributes) def testIncident(self): g = Graph.Famous("petersen") g.to_directed() method_table = { "all": "all_edges", "in": "in_edges", "out": "out_edges" } for i in range(g.vcount()): vertex = g.vs[i] for mode, method_name in method_table.items(): method = getattr(vertex, method_name) self.assertEqual( g.incident(i, mode=mode), [edge.index for edge in vertex.incident(mode=mode)] ) self.assertEqual( g.incident(i, mode=mode), [edge.index for edge in method()] ) def testNeighbors(self): g = Graph.Famous("petersen") g.to_directed() for i in range(g.vcount()): vertex = g.vs[i] for mode in "all in out".split(): self.assertEqual( g.neighbors(i, mode=mode), [edge.index for edge in vertex.neighbors(mode=mode)] ) @skipIf(is_pypy, "skipped on PyPy because we do not have access to docstrings") def testProxyMethods(self): # We only test with connected graphs because disconnected graphs might # print a warning when shortest_paths() is invoked on them and we want # to avoid that in the test output. while True: g = Graph.GRG(10, 0.6) if g.is_connected(): break v = g.vs[0] # - neighbors(), predecessors() and succesors() are ignored because they # return vertex lists while the methods in Graph return vertex index # lists. # - incident(), all_edges(), in_edges() and out_edges() are ignored # because it returns an edge list while the methods in Graph return # edge indices. # - pagerank() and personalized_pagerank() are ignored because of numerical # inaccuracies # - delete() is ignored because it mutates the graph ignore = "neighbors predecessors successors pagerank personalized_pagerank"\ " delete incident all_edges in_edges out_edges" ignore = set(ignore.split()) # Methods not listed here are expected to return an int or a float return_types = { "get_shortest_paths": list, "shortest_paths": list } for name in Vertex.__dict__: if name in ignore: continue func = getattr(v, name) docstr = func.__doc__ if not docstr.startswith("Proxy method"): continue result = func() self.assertEqual(getattr(g, name)(v.index), result, msg=("Vertex.%s proxy method misbehaved" % name)) return_type = return_types.get(name, (int, float)) self.assertTrue(isinstance(result, return_type), msg=("Vertex.%s proxy method did not return %s" % (name, return_type)) ) class VertexSeqTests(unittest.TestCase): def setUp(self): self.g = Graph.Full(10) self.g.vs["test"] = range(10) self.g.vs["name"] = list("ABCDEFGHIJ") def testCreation(self): self.assertTrue(len(VertexSeq(self.g)) == 10) self.assertTrue(len(VertexSeq(self.g, 2)) == 1) self.assertTrue(len(VertexSeq(self.g, [1,2,3])) == 3) self.assertTrue(VertexSeq(self.g, [1,2,3]).indices == [1,2,3]) self.assertRaises(ValueError, VertexSeq, self.g, 12) self.assertRaises(ValueError, VertexSeq, self.g, [12]) self.assertTrue(self.g.vs.graph == self.g) def testIndexing(self): n = self.g.vcount() for i in range(n): self.assertEqual(i, self.g.vs[i].index) self.assertEqual(n-i-1, self.g.vs[-i-1].index) self.assertRaises(IndexError, self.g.vs.__getitem__, n) self.assertRaises(IndexError, self.g.vs.__getitem__, -n-1) self.assertRaises(TypeError, self.g.vs.__getitem__, 1.5) @skipIf(np is None, "test case depends on NumPy") def testNumPyIndexing(self): n = self.g.vcount() for i in range(self.g.vcount()): arr = np.array([i]) self.assertEqual(i, self.g.vs[arr[0]].index) arr = np.array([-i-1]) self.assertEqual(n-i-1, self.g.vs[arr[0]].index) arr = np.array([n]) self.assertRaises(IndexError, self.g.vs.__getitem__, arr[0]) arr = np.array([-n-1]) self.assertRaises(IndexError, self.g.vs.__getitem__, arr[0]) arr = np.array([1.5]) self.assertRaises(TypeError, self.g.vs.__getitem__, arr[0]) def testPartialAttributeAssignment(self): only_even = self.g.vs.select(lambda v: (v.index % 2 == 0)) only_even["test"] = [0]*len(only_even) self.assertTrue(self.g.vs["test"] == [0,1,0,3,0,5,0,7,0,9]) only_even["test2"] = range(5) self.assertTrue(self.g.vs["test2"] == [0,None,1,None,2,None,3,None,4,None]) def testSequenceReusing(self): if "test" in self.g.vertex_attributes(): del self.g.vs["test"] self.g.vs["test"] = ["A", "B", "C"] self.assertTrue(self.g.vs["test"] == ["A", "B", "C", "A", "B", "C", "A", "B", "C", "A"]) self.g.vs["test"] = "ABC" self.assertTrue(self.g.vs["test"] == ["ABC"] * 10) only_even = self.g.vs.select(lambda v: (v.index % 2 == 0)) only_even["test"] = ["D", "E"] self.assertTrue(self.g.vs["test"] == ["D", "ABC", "E", "ABC", "D", "ABC", "E", "ABC", "D", "ABC"]) del self.g.vs["test"] only_even["test"] = ["D", "E"] self.assertTrue(self.g.vs["test"] == ["D", None, "E", None, "D", None, "E", None, "D", None]) def testAllSequence(self): self.assertTrue(len(self.g.vs) == 10) self.assertTrue(self.g.vs["test"] == list(range(10))) def testEmptySequence(self): empty_vs = self.g.vs.select(None) self.assertTrue(len(empty_vs) == 0) self.assertRaises(IndexError, empty_vs.__getitem__, 0) self.assertRaises(KeyError, empty_vs.__getitem__, "nonexistent") self.assertTrue(empty_vs["test"] == []) empty_vs = self.g.vs[[]] self.assertTrue(len(empty_vs) == 0) empty_vs = self.g.vs[()] self.assertTrue(len(empty_vs) == 0) def testCallableFilteringFind(self): vertex = self.g.vs.find(lambda v: (v.index % 2 == 1)) self.assertTrue(vertex.index == 1) self.assertRaises(IndexError, self.g.vs.find, lambda v: (v.index % 2 == 3)) def testCallableFilteringSelect(self): only_even = self.g.vs.select(lambda v: (v.index % 2 == 0)) self.assertTrue(len(only_even) == 5) self.assertRaises(KeyError, only_even.__getitem__, "nonexistent") self.assertTrue(only_even["test"] == [0, 2, 4, 6, 8]) def testChainedCallableFilteringSelect(self): only_div_six = self.g.vs.select(lambda v: (v.index % 2 == 0), lambda v: (v.index % 3 == 0)) self.assertTrue(len(only_div_six) == 2) self.assertTrue(only_div_six["test"] == [0, 6]) only_div_six = self.g.vs.select(lambda v: (v.index % 2 == 0)).select(\ lambda v: (v.index % 3 == 0)) self.assertTrue(len(only_div_six) == 2) self.assertTrue(only_div_six["test"] == [0, 6]) def testIntegerFilteringFind(self): self.assertEqual(self.g.vs.find(3).index, 3) self.assertEqual(self.g.vs.select(2,3,4,2).find(3).index, 2) self.assertRaises(IndexError, self.g.vs.find, 17) def testIntegerFilteringSelect(self): subset = self.g.vs.select(2,3,4,2) self.assertEqual(len(subset), 4) self.assertEqual(subset["test"], [2,3,4,2]) self.assertRaises(TypeError, self.g.vs.select, 2, 3, 4, 2, None) subset = self.g.vs[2,3,4,2] self.assertTrue(len(subset) == 4) self.assertTrue(subset["test"] == [2,3,4,2]) def testStringFilteringFind(self): self.assertEqual(self.g.vs.find("D").index, 3) self.assertEqual(self.g.vs.select(2,3,4,2).find("C").index, 2) self.assertRaises(ValueError, self.g.vs.select(2,3,4,2).find, "F") self.assertRaises(ValueError, self.g.vs.find, "NoSuchName") def testIterableFilteringSelect(self): subset = self.g.vs.select(range(5,8)) self.assertTrue(len(subset) == 3) self.assertTrue(subset["test"] == [5,6,7]) def testSliceFilteringSelect(self): subset = self.g.vs.select(slice(5, 8)) self.assertTrue(len(subset) == 3) self.assertTrue(subset["test"] == [5,6,7]) subset = self.g.vs[5:16:2] self.assertTrue(len(subset) == 3) self.assertTrue(subset["test"] == [5,7,9]) def testKeywordFilteringSelect(self): g = Graph.Barabasi(10000) g.vs["degree"] = g.degree() g.vs["parity"] = [i % 2 for i in range(g.vcount())] l = len(g.vs(degree_gt=30)) self.assertTrue(l < 1000) self.assertTrue(len(g.vs(degree_gt=30, parity=0)) <= 500) del g.vs["degree"] self.assertTrue(len(g.vs(_degree_gt=30)) == l) def testIndexAndKeywordFilteringFind(self): self.assertRaises(ValueError, self.g.vs.find, 2, name="G") self.assertRaises(ValueError, self.g.vs.find, 2, test=4) self.assertTrue(self.g.vs.find(2, name="C") == self.g.vs[2]) self.assertTrue(self.g.vs.find(2, test=2) == self.g.vs[2]) def testIndexOutOfBoundsSelect(self): g = Graph.Full(3) self.assertRaises(ValueError, g.vs.select, 4) self.assertRaises(ValueError, g.vs.select, 4, 5) self.assertRaises(ValueError, g.vs.select, (4, 5)) self.assertRaises(ValueError, g.vs.select, 2, -1) self.assertRaises(ValueError, g.vs.select, (2, -1)) self.assertRaises(ValueError, g.vs.__getitem__, (0, 1000000)) def testGraphMethodProxying(self): g = Graph.Barabasi(100) vs = g.vs(1,3,5,7,9) self.assertEqual(vs.degree(), g.degree(vs)) self.assertEqual(g.degree(vs), g.degree(vs.indices)) for v, d in zip(vs, vs.degree()): self.assertEqual(v.degree(), d) def testBug73(self): # This is a regression test for igraph/python-igraph#73 g = Graph() g.add_vertices(2) g.vs[0]["name"] = 1 g.vs[1]["name"] = "h" self.assertEqual(1, g.vs.find("h").index) self.assertEqual(1, g.vs.find(1).index) self.assertEqual(0, g.vs.find(name=1).index) def suite(): vertex_suite = unittest.makeSuite(VertexTests) vs_suite = unittest.makeSuite(VertexSeqTests) return unittest.TestSuite([vertex_suite, vs_suite]) def test(): runner = unittest.TextTestRunner() runner.run(suite()) if __name__ == "__main__": test() python-igraph-0.8.0/tests/test_foreign.py0000644000076500000240000001701713606025206020752 0ustar tamasstaff00000000000000from __future__ import with_statement import io import unittest import warnings from igraph import * from .utils import temporary_file class ForeignTests(unittest.TestCase): def testDIMACS(self): with temporary_file(u"""\ c c This is a simple example file to demonstrate the c DIMACS input file format for minimum-cost flow problems. c c problem line : p max 4 5 c c node descriptor lines : n 1 s n 4 t c c arc descriptor lines : a 1 2 4 a 1 3 2 a 2 3 2 a 2 4 3 a 3 4 5 """) as tmpfname: graph = Graph.Read_DIMACS(tmpfname, False) self.assertTrue(isinstance(graph, Graph)) self.assertTrue(graph.vcount() == 4 and graph.ecount() == 5) self.assertTrue(graph["source"] == 0 and graph["target"] == 3) self.assertTrue(graph.es["capacity"] == [4,2,2,3,5]) graph.write_dimacs(tmpfname) def testDL(self): with temporary_file(u"""\ dl n=5 format = fullmatrix labels embedded data: larry david lin pat russ Larry 0 1 1 1 0 david 1 0 0 0 1 Lin 1 0 0 1 0 Pat 1 0 1 0 1 russ 0 1 0 1 0 """) as tmpfname: g = Graph.Read_DL(tmpfname) self.assertTrue(isinstance(g, Graph)) self.assertTrue(g.vcount() == 5 and g.ecount() == 12) self.assertTrue(g.is_directed()) self.assertTrue(sorted(g.get_edgelist()) == \ [(0,1),(0,2),(0,3),(1,0),(1,4),(2,0),(2,3),(3,0),\ (3,2),(3,4),(4,1),(4,3)]) with temporary_file(u"""\ dl n=5 format = fullmatrix labels: barry,david lin,pat russ data: 0 1 1 1 0 1 0 0 0 1 1 0 0 1 0 1 0 1 0 1 0 1 0 1 0 """) as tmpfname: g = Graph.Read_DL(tmpfname) self.assertTrue(isinstance(g, Graph)) self.assertTrue(g.vcount() == 5 and g.ecount() == 12) self.assertTrue(g.is_directed()) self.assertTrue(sorted(g.get_edgelist()) == \ [(0,1),(0,2),(0,3),(1,0),(1,4),(2,0),(2,3),(3,0),\ (3,2),(3,4),(4,1),(4,3)]) with temporary_file(u"""\ DL n=5 format = edgelist1 labels: george, sally, jim, billy, jane labels embedded: data: george sally 2 george jim 3 sally jim 4 billy george 5 jane jim 6 """) as tmpfname: g = Graph.Read_DL(tmpfname, False) self.assertTrue(isinstance(g, Graph)) self.assertTrue(g.vcount() == 5 and g.ecount() == 5) self.assertTrue(not g.is_directed()) self.assertTrue(sorted(g.get_edgelist()) == \ [(0,1),(0,2),(0,3),(1,2),(2,4)]) def _testNCOLOrLGL(self, func, fname, can_be_reopened=True): g = func(fname, names=False, weights=False, \ directed=False) self.assertTrue(isinstance(g, Graph)) self.assertTrue(g.vcount() == 4 and g.ecount() == 5) self.assertTrue(not g.is_directed()) self.assertTrue(sorted(g.get_edgelist()) == \ [(0,1),(0,2),(1,1),(1,3),(2,3)]) self.assertTrue("name" not in g.vertex_attributes() and \ "weight" not in g.edge_attributes()) if not can_be_reopened: return g = func(fname, names=False, \ directed=False) self.assertTrue("name" not in g.vertex_attributes() and \ "weight" in g.edge_attributes()) self.assertTrue(g.es["weight"] == [1, 2, 0, 3, 0]) g = func(fname, directed=False) self.assertTrue("name" in g.vertex_attributes() and \ "weight" in g.edge_attributes()) self.assertTrue(g.vs["name"] == ["eggs", "spam", "ham", "bacon"]) self.assertTrue(g.es["weight"] == [1, 2, 0, 3, 0]) def testNCOL(self): with temporary_file(u"""\ eggs spam 1 ham eggs 2 ham bacon bacon spam 3 spam spam""") as tmpfname: self._testNCOLOrLGL(func=Graph.Read_Ncol, fname=tmpfname) with temporary_file(u"""\ eggs spam ham eggs ham bacon bacon spam spam spam""") as tmpfname: g = Graph.Read_Ncol(tmpfname) self.assertTrue("name" in g.vertex_attributes() and \ "weight" not in g.edge_attributes()) def testLGL(self): with temporary_file(u"""\ # eggs spam 1 # ham eggs 2 bacon # bacon spam 3 # spam spam""") as tmpfname: self._testNCOLOrLGL(func=Graph.Read_Lgl, fname=tmpfname) with temporary_file(u"""\ # eggs spam # ham eggs bacon # bacon spam # spam spam""") as tmpfname: with warnings.catch_warnings(): warnings.simplefilter("ignore") g = Graph.Read_Lgl(tmpfname) self.assertTrue("name" in g.vertex_attributes() and \ "weight" not in g.edge_attributes()) # This is not an LGL file; we are testing error handling here with temporary_file(u"""\ 1 2 1 3 """) as tmpfname: with self.assertRaises(InternalError): Graph.Read_Lgl(tmpfname) def testLGLWithIOModule(self): with temporary_file(u"""\ # eggs spam 1 # ham eggs 2 bacon # bacon spam 3 # spam spam""") as tmpfname: with io.open(tmpfname, "r") as fp: self._testNCOLOrLGL(func=Graph.Read_Lgl, fname=fp, can_be_reopened=False) def testAdjacency(self): with temporary_file(u"""\ # Test comment line 0 1 1 0 0 0 1 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 2 2 0 0 0 2 0 2 0 0 0 2 2 0 """) as tmpfname: g = Graph.Read_Adjacency(tmpfname) self.assertTrue(isinstance(g, Graph)) self.assertTrue(g.vcount() == 6 and g.ecount() == 18 and g.is_directed() and "weight" not in g.edge_attributes()) g = Graph.Read_Adjacency(tmpfname, attribute="weight") self.assertTrue(isinstance(g, Graph)) self.assertTrue(g.vcount() == 6 and g.ecount() == 12 and g.is_directed() and g.es["weight"] == [1,1,1,1,1,1,2,2,2,2,2,2]) g.write_adjacency(tmpfname) def testPickle(self): pickle = [128, 2, 99, 105, 103, 114, 97, 112, 104, 10, 71, 114, 97, 112, 104, 10, 113, 1, 40, 75, 3, 93, 113, 2, 75, 1, 75, 2, 134, 113, 3, 97, 137, 125, 125, 125, 116, 82, 113, 4, 125, 98, 46] if sys.version_info > (3, 0): pickle = bytes(pickle) else: pickle = "".join(map(chr, pickle)) with temporary_file(pickle, "wb") as tmpfname: g = Graph.Read_Pickle(pickle) self.assertTrue(isinstance(g, Graph)) self.assertTrue(g.vcount() == 3 and g.ecount() == 1 and not g.is_directed()) g.write_pickle(tmpfname) def suite(): foreign_suite = unittest.makeSuite(ForeignTests) return unittest.TestSuite([foreign_suite]) def test(): runner = unittest.TextTestRunner() runner.run(suite()) if __name__ == "__main__": test() python-igraph-0.8.0/tests/test_structural.py0000644000076500000240000006302013606025206021524 0ustar tamasstaff00000000000000from __future__ import division import math import unittest import warnings from igraph import * from igraph.compat import isnan class SimplePropertiesTests(unittest.TestCase): gfull = Graph.Full(10) gempty = Graph(10) g = Graph(4, [(0, 1), (0, 2), (1, 2), (0, 3), (1, 3)]) gdir = Graph(4, [(0, 1), (0, 2), (1, 2), (2, 1), (0, 3), (1, 3), (3, 0)], directed=True) tree = Graph.Tree(14, 3) def testDensity(self): self.assertAlmostEqual(1.0, self.gfull.density(), places=5) self.assertAlmostEqual(0.0, self.gempty.density(), places=5) self.assertAlmostEqual(5/6, self.g.density(), places=5) self.assertAlmostEqual(1/2, self.g.density(True), places=5) self.assertAlmostEqual(7/12, self.gdir.density(), places=5) self.assertAlmostEqual(7/16, self.gdir.density(True), places=5) self.assertAlmostEqual(1/7, self.tree.density(), places=5) def testDiameter(self): self.assertTrue(self.gfull.diameter() == 1) self.assertTrue(self.gempty.diameter(unconn=False) == 10) self.assertTrue(self.gempty.diameter(unconn=False, weights=[]) \ == float('inf')) self.assertTrue(self.g.diameter() == 2) self.assertTrue(self.gdir.diameter(False) == 2) self.assertTrue(self.gdir.diameter() == 3) self.assertTrue(self.tree.diameter() == 5) s, t, d = self.tree.farthest_points() self.assertTrue((s == 13 or t == 13) and d == 5) self.assertTrue(self.gempty.farthest_points(unconn=False) == (None, None, 10)) d = self.tree.get_diameter() self.assertTrue(d[0] == 13 or d[-1] == 13) weights = [1, 1, 1, 5, 1, 5, 1, 1, 1, 1, 1, 1, 5] self.assertTrue(self.tree.diameter(weights=weights) == 15) d = self.tree.farthest_points(weights=weights) self.assertTrue(d == (13, 6, 15) or d == (6, 13, 15)) def testEccentricity(self): self.assertEqual(self.gfull.eccentricity(), [1] * self.gfull.vcount()) self.assertEqual(self.gempty.eccentricity(), [0] * self.gempty.vcount()) self.assertEqual(self.g.eccentricity(), [1, 1, 2, 2]) self.assertEqual(self.gdir.eccentricity(), [1, 2, 3, 2]) self.assertEqual(self.tree.eccentricity(), [3, 3, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 5]) self.assertEqual(Graph().eccentricity(), []) def testRadius(self): self.assertEqual(self.gfull.radius(), 1) self.assertEqual(self.gempty.radius(), 0) self.assertEqual(self.g.radius(), 1) self.assertEqual(self.gdir.radius(), 1) self.assertEqual(self.tree.radius(), 3) self.assertTrue(isnan(Graph().radius())) def testTransitivity(self): self.assertTrue(self.gfull.transitivity_undirected() == 1.0) self.assertTrue(self.tree.transitivity_undirected() == 0.0) self.assertTrue(self.g.transitivity_undirected() == 0.75) def testLocalTransitivity(self): self.assertTrue(self.gfull.transitivity_local_undirected() == [1.0] * self.gfull.vcount()) self.assertTrue(self.tree.transitivity_local_undirected(mode="zero") == [0.0] * self.tree.vcount()) l = self.g.transitivity_local_undirected(mode="zero") self.assertAlmostEqual(2/3, l[0], places=4) self.assertAlmostEqual(2/3, l[1], places=4) self.assertEqual(1, l[2]) self.assertEqual(1, l[3]) g = Graph.Full(4) + 1 + [(0, 4)] g.es["weight"] = [1, 1, 1, 1, 1, 1, 5] self.assertAlmostEqual( g.transitivity_local_undirected(0, weights="weight"), 0.25, places=4) def testAvgLocalTransitivity(self): self.assertTrue(self.gfull.transitivity_avglocal_undirected() == 1.0) self.assertTrue(self.tree.transitivity_avglocal_undirected() == 0.0) self.assertAlmostEqual(self.g.transitivity_avglocal_undirected(), 5/6., places=4) def testModularity(self): g = Graph.Full(5)+Graph.Full(5) g.add_edges([(0,5)]) cl = [0]*5+[1]*5 self.assertAlmostEqual(g.modularity(cl), 0.4523, places=3) ws = [1]*21 self.assertAlmostEqual(g.modularity(cl, ws), 0.4523, places=3) ws = [2]*21 self.assertAlmostEqual(g.modularity(cl, ws), 0.4523, places=3) ws = [2]*10+[1]*11 self.assertAlmostEqual(g.modularity(cl, ws), 0.4157, places=3) self.assertRaises(InternalError, g.modularity, cl, ws[0:20]) class DegreeTests(unittest.TestCase): gfull = Graph.Full(10) gempty = Graph(10) g = Graph(4, [(0, 1), (0, 2), (1, 2), (0, 3), (1, 3), (0, 0)]) gdir = Graph(4, [(0, 1), (0, 2), (1, 2), (2, 1), (0, 3), (1, 3), (3, 0)], directed=True) tree = Graph.Tree(10, 3) def testKnn(self): knn, knnk = self.gfull.knn() self.assertTrue(knn == [9.] * 10) self.assertAlmostEqual(knnk[8], 9.0, places=6) # knn works for simple graphs only -- self.g is not simple self.assertRaises(InternalError, self.g.knn) # Okay, simplify it and then go on g = self.g.copy() g.simplify() knn, knnk = g.knn() diff = max(abs(a-b) for a, b in zip(knn, [7/3., 7/3., 3, 3])) self.assertAlmostEqual(diff, 0., places=6) self.assertEqual(len(knnk), 3) self.assertAlmostEqual(knnk[1], 3, places=6) self.assertAlmostEqual(knnk[2], 7/3., places=6) def testDegree(self): self.assertTrue(self.gfull.degree() == [9] * 10) self.assertTrue(self.gempty.degree() == [0] * 10) self.assertTrue(self.g.degree(loops=False) == [3, 3, 2, 2]) self.assertTrue(self.g.degree() == [5, 3, 2, 2]) self.assertTrue(self.gdir.degree(mode=IN) == [1, 2, 2, 2]) self.assertTrue(self.gdir.degree(mode=OUT) == [3, 2, 1, 1]) self.assertTrue(self.gdir.degree(mode=ALL) == [4, 4, 3, 3]) vs = self.gdir.vs.select(0, 2) self.assertTrue(self.gdir.degree(vs, mode=ALL) == [4, 3]) self.assertTrue(self.gdir.degree(self.gdir.vs[1], mode=ALL) == 4) def testMaxDegree(self): self.assertTrue(self.gfull.maxdegree() == 9) self.assertTrue(self.gempty.maxdegree() == 0) self.assertTrue(self.g.maxdegree() == 3) self.assertTrue(self.g.maxdegree(loops=True) == 5) self.assertTrue(self.g.maxdegree([1, 2], loops=True) == 3) self.assertTrue(self.gdir.maxdegree(mode=IN) == 2) self.assertTrue(self.gdir.maxdegree(mode=OUT) == 3) self.assertTrue(self.gdir.maxdegree(mode=ALL) == 4) def testStrength(self): # Turn off warnings about calling strength without weights import warnings warnings.filterwarnings("ignore", "No edge weights for strength calculation", \ RuntimeWarning) # No weights self.assertTrue(self.gfull.strength() == [9] * 10) self.assertTrue(self.gempty.strength() == [0] * 10) self.assertTrue(self.g.degree(loops=False) == [3, 3, 2, 2]) self.assertTrue(self.g.degree() == [5, 3, 2, 2]) # With weights ws = [1, 2, 3, 4, 5, 6] self.assertTrue(self.g.strength(weights=ws, loops=False) == \ [7, 9, 5, 9]) self.assertTrue(self.g.strength(weights=ws) == [19, 9, 5, 9]) ws = [1, 2, 3, 4, 5, 6, 7] self.assertTrue(self.gdir.strength(mode=IN, weights=ws) == \ [7, 5, 5, 11]) self.assertTrue(self.gdir.strength(mode=OUT, weights=ws) == \ [8, 9, 4, 7]) self.assertTrue(self.gdir.strength(mode=ALL, weights=ws) == \ [15, 14, 9, 18]) vs = self.gdir.vs.select(0, 2) self.assertTrue(self.gdir.strength(vs, mode=ALL, weights=ws) == \ [15, 9]) self.assertTrue(self.gdir.strength(self.gdir.vs[1], \ mode=ALL, weights=ws) == 14) class LocalTransitivityTests(unittest.TestCase): def testLocalTransitivityFull(self): trans = Graph.Full(10).transitivity_local_undirected() self.assertTrue(trans == [1.0]*10) def testLocalTransitivityTree(self): trans = Graph.Tree(10, 3).transitivity_local_undirected() self.assertTrue(trans[0:3] == [0.0, 0.0, 0.0]) def testLocalTransitivityHalf(self): g = Graph(4, [(0, 1), (0, 2), (1, 2), (0, 3), (1, 3)]) trans = g.transitivity_local_undirected() trans = [round(x, 3) for x in trans] self.assertTrue(trans == [0.667, 0.667, 1.0, 1.0]) def testLocalTransitivityPartial(self): g = Graph(4, [(0, 1), (0, 2), (1, 2), (0, 3), (1, 3)]) trans = g.transitivity_local_undirected([1,2]) trans = [round(x, 3) for x in trans] self.assertTrue(trans == [0.667, 1.0]) class BiconnectedComponentTests(unittest.TestCase): g1 = Graph.Full(10) g2 = Graph(5, [(0,1),(1,2),(2,3),(3,4)]) g3 = Graph(6, [(0,1),(1,2),(2,3),(3,0),(2,4),(2,5),(4,5)]) def testBiconnectedComponents(self): s = self.g1.biconnected_components() self.assertTrue(len(s) == 1 and s[0]==list(range(10))) s, ap = self.g1.biconnected_components(True) self.assertTrue(len(s) == 1 and s[0]==list(range(10))) s = self.g3.biconnected_components() self.assertTrue(len(s) == 2 and s[0]==[2,4,5] and s[1]==[0,1,2,3]) s, ap = self.g3.biconnected_components(True) self.assertTrue(len(s) == 2 and s[0]==[2,4,5] and \ s[1]==[0,1,2,3] and ap == [2]) def testArticulationPoints(self): self.assertTrue(self.g1.articulation_points() == []) self.assertTrue(self.g2.cut_vertices() == [1,2,3]) self.assertTrue(self.g3.articulation_points() == [2]) class CentralityTests(unittest.TestCase): def testBetweennessCentrality(self): g = Graph.Star(5) self.assertTrue(g.betweenness() == [6., 0., 0., 0., 0.]) g = Graph(5, [(0, 1), (0, 2), (0, 3), (1, 4)]) self.assertTrue(g.betweenness() == [5., 3., 0., 0., 0.]) self.assertTrue(g.betweenness(cutoff=2) == [3., 1., 0., 0., 0.]) self.assertTrue(g.betweenness(cutoff=1) == [0., 0., 0., 0., 0.]) g = Graph.Lattice([3, 3], circular=False) self.assertTrue(g.betweenness(cutoff=2) == [0.5, 2.0, 0.5, 2.0, 4.0, 2.0, 0.5, 2.0, 0.5]) def testEdgeBetweennessCentrality(self): g = Graph.Star(5) self.assertTrue(g.edge_betweenness() == [4., 4., 4., 4.]) g = Graph(5, [(0, 1), (0, 2), (0, 3), (1, 4)]) self.assertTrue(g.edge_betweenness() == [6., 4., 4., 4.]) self.assertTrue(g.edge_betweenness(cutoff=2) == [4., 3., 3., 2.]) self.assertTrue(g.edge_betweenness(cutoff=1) == [1., 1., 1., 1.]) g = Graph.Ring(5) self.assertTrue(g.edge_betweenness() == [3., 3., 3., 3., 3.]) self.assertTrue(g.edge_betweenness(weights=[4, 1, 1, 1, 1]) == \ [0.5, 3.5, 5.5, 5.5, 3.5]) def testClosenessCentrality(self): g = Graph.Star(5) cl = g.closeness() cl2 = [1., 0.57142, 0.57142, 0.57142, 0.57142] for idx in range(g.vcount()): self.assertAlmostEqual(cl[idx], cl2[idx], places=3) g = Graph.Star(5) with warnings.catch_warnings(): warnings.simplefilter("ignore") cl = g.closeness(cutoff=1) cl2 = [1., 0.25, 0.25, 0.25, 0.25] for idx in range(g.vcount()): self.assertAlmostEqual(cl[idx], cl2[idx], places=3) weights = [1] * 4 g = Graph.Star(5) cl = g.closeness(weights=weights) cl2 = [1., 0.57142, 0.57142, 0.57142, 0.57142] for idx in range(g.vcount()): self.assertAlmostEqual(cl[idx], cl2[idx], places=3) g = Graph.Star(5) with warnings.catch_warnings(): warnings.simplefilter("ignore") cl = g.closeness(cutoff=1, weights=weights) cl2 = [1., 0.25, 0.25, 0.25, 0.25] for idx in range(g.vcount()): self.assertAlmostEqual(cl[idx], cl2[idx], places=3) # Test for igraph/igraph:#1078 g = Graph([ (0, 1), (0, 2), (0, 5), (0, 6), (0, 9), (1, 6), (1, 8), (2, 4), (2, 6), (2, 7), (2, 8), (3, 6), (4, 8), (5, 6), (5, 9), (6, 7), (6, 8), (7, 8), (7, 9), (8, 9) ]) weights = [0.69452, 0.329886, 0.131649, 0.503269, 0.472738, 0.370933, 0.23857, 0.0354043, 0.189015, 0.355118, 0.768335, 0.893289, 0.891709, 0.494896, 0.924684, 0.432001, 0.858159, 0.246798, 0.881304, 0.64685] with warnings.catch_warnings(): warnings.simplefilter("ignore") cl = g.closeness(weights=weights) expected_cl = [1.63318, 1.52014, 2.03724, 0.760158, 1.91449, 1.43224, 1.91761, 1.60198, 1.3891, 1.12829] for obs, exp in zip(cl, expected_cl): self.assertAlmostEqual(obs, exp, places=4) def testPageRank(self): g = Graph.Star(11) cent = g.pagerank() self.assertTrue(cent.index(max(cent)) == 0) self.assertAlmostEqual(max(cent), 0.4668, places=3) def testPersonalizedPageRank(self): g = Graph.Star(11) self.assertRaises(InternalError, g.personalized_pagerank, reset=[0]*11) cent = g.personalized_pagerank(reset=[0,10]+[0]*9, damping=0.5) self.assertTrue(cent.index(max(cent)) == 1) self.assertAlmostEqual(cent[0], 0.3333, places=3) self.assertAlmostEqual(cent[1], 0.5166, places=3) self.assertAlmostEqual(cent[2], 0.0166, places=3) cent2 = g.personalized_pagerank(reset_vertices=g.vs[1], damping=0.5) self.assertTrue(max(abs(x-y) for x, y in zip(cent, cent2)) < 0.001) def testEigenvectorCentrality(self): g = Graph.Star(11) cent = g.evcent() self.assertTrue(cent.index(max(cent)) == 0) self.assertAlmostEqual(max(cent), 1.0, places=3) self.assertTrue(min(cent) >= 0) cent, ev = g.evcent(scale=False, return_eigenvalue=True) if cent[0]<0: cent = [-x for x in cent] self.assertTrue(cent.index(max(cent)) == 0) self.assertAlmostEqual(cent[1]/cent[0], 0.3162, places=3) self.assertAlmostEqual(ev, 3.162, places=3) def testAuthorityScore(self): g = Graph.Tree(15, 2, TREE_IN) asc = g.authority_score() self.assertAlmostEqual(max(asc), 1.0, places=3) asc, ev = g.hub_score(scale=False, return_eigenvalue=True) if asc[0]<0: hs = [-x for x in asc] def testHubScore(self): g = Graph.Tree(15, 2, TREE_IN) hsc = g.hub_score() self.assertAlmostEqual(max(hsc), 1.0, places=3) hsc, ev = g.hub_score(scale=False, return_eigenvalue=True) if hsc[0]<0: hsc = [-x for x in hsc] def testCoreness(self): g = Graph.Full(4) + Graph(4) + [(0,4), (1,5), (2,6), (3,7)] self.assertEqual(g.coreness("A"), [3,3,3,3,1,1,1,1]) class NeighborhoodTests(unittest.TestCase): def testNeighborhood(self): g = Graph.Ring(10, circular=False) self.assertTrue(list(map(sorted, g.neighborhood())) == \ [[0,1], [0,1,2], [1,2,3], [2,3,4], [3,4,5], [4,5,6], \ [5,6,7], [6,7,8], [7,8,9], [8,9]]) self.assertTrue(list(map(sorted, g.neighborhood(order=3))) == \ [[0,1,2,3], [0,1,2,3,4], [0,1,2,3,4,5], [0,1,2,3,4,5,6], \ [1,2,3,4,5,6,7], [2,3,4,5,6,7,8], [3,4,5,6,7,8,9], \ [4,5,6,7,8,9], [5,6,7,8,9], [6,7,8,9]]) self.assertTrue(list(map(sorted, g.neighborhood(order=3, mindist=2))) == \ [[2,3], [3,4], [0,4,5], [0,1,5,6], \ [1,2,6,7], [2,3,7,8], [3,4,8,9], \ [4,5,9], [5,6], [6,7]]) def testNeighborhoodSize(self): g = Graph.Ring(10, circular=False) self.assertTrue(g.neighborhood_size() == [2,3,3,3,3,3,3,3,3,2]) self.assertTrue(g.neighborhood_size(order=3) == [4,5,6,7,7,7,7,6,5,4]) self.assertTrue(g.neighborhood_size(order=3, mindist=2) == \ [2,2,3,4,4,4,4,3,2,2]) class MiscTests(unittest.TestCase): def testConstraint(self): g = Graph(4, [(0, 1), (0, 2), (1, 2), (0, 3), (1, 3)]) self.assertTrue(isinstance(g.constraint(), list)) # TODO check more def testTopologicalSorting(self): g = Graph(5, [(0, 1), (0, 2), (1, 2), (1, 3), (2, 3)], directed=True) self.assertTrue(g.topological_sorting() == [0, 4, 1, 2, 3]) self.assertTrue(g.topological_sorting(IN) == [3, 4, 2, 1, 0]) g.to_undirected() self.assertRaises(InternalError, g.topological_sorting) def testIsDAG(self): g = Graph(5, [(0, 1), (0, 2), (1, 2), (1, 3), (2, 3)], directed=True) self.assertTrue(g.is_dag()) g.to_undirected() self.assertFalse(g.is_dag()) g = Graph.Barabasi(1000, 2, directed=True) self.assertTrue(g.is_dag()) g = Graph.GRG(100, 0.2) self.assertFalse(g.is_dag()) g = Graph.Ring(10, directed=True, mutual=False) self.assertFalse(g.is_dag()) def testLineGraph(self): g = Graph(4, [(0, 1), (0, 2), (1, 2), (0, 3), (1, 3)]) el = g.linegraph().get_edgelist() el.sort() self.assertTrue(el == [(0, 1), (0, 2), (0, 3), (0, 4), (1, 2), (1, 3), (2, 4), (3, 4)]) g = Graph(4, [(0, 1), (0, 2), (1, 2), (0, 3), (1, 3)], directed=True) el = g.linegraph().get_edgelist() el.sort() self.assertTrue(el == [(0, 2), (0, 4)]) class PathTests(unittest.TestCase): def testShortestPaths(self): g = Graph(10, [(0,1), (0,2), (0,3), (1,2), (1,4), (1,5), (2,3), (2,6), \ (3,2), (3,6), (4,5), (4,7), (5,6), (5,8), (5,9), (7,5), (7,8), \ (8,9), (5,2), (2,1)], directed=True) ws = [0,2,1,0,5,2,1,1,0,2,2,8,1,1,3,1,1,4,2,1] g.es["weight"] = ws inf = float('inf') expected = [ [0, 0, 0, 1, 5, 2, 1, 13, 3, 5], [inf, 0, 0, 1, 5, 2, 1, 13, 3, 5], [inf, 1, 0, 1, 6, 3, 1, 14, 4, 6], [inf, 1, 0, 0, 6, 3, 1, 14, 4, 6], [inf, 5, 4, 5, 0, 2, 3, 8, 3, 5], [inf, 3, 2, 3, 8, 0, 1, 16, 1, 3], [inf, inf, inf, inf, inf, inf, 0, inf, inf, inf], [inf, 4, 3, 4, 9, 1, 2, 0, 1, 4], [inf, inf, inf, inf, inf, inf, inf, inf, 0, 4], [inf, inf, inf, inf, inf, inf, inf, inf, inf, 0] ] self.assertTrue(g.shortest_paths(weights=ws) == expected) self.assertTrue(g.shortest_paths(weights="weight") == expected) self.assertTrue(g.shortest_paths(weights="weight", target=[2,3]) == [row[2:4] for row in expected]) def testGetShortestPaths(self): g = Graph(4, [(0,1), (0,2), (1,3), (3,2), (2,1)], directed=True) sps = g.get_shortest_paths(0) expected = [[0], [0, 1], [0, 2], [0, 1, 3]] self.assertTrue(sps == expected) sps = g.get_shortest_paths(0, output="vpath") expected = [[0], [0, 1], [0, 2], [0, 1, 3]] self.assertTrue(sps == expected) sps = g.get_shortest_paths(0, output="epath") expected = [[], [0], [1], [0, 2]] self.assertTrue(sps == expected) self.assertRaises(ValueError, g.get_shortest_paths, 0, output="x") def testGetAllShortestPaths(self): g = Graph(4, [(0,1), (1, 2), (1, 3), (2, 4), (3, 4), (4, 5)], directed=True) sps = sorted(g.get_all_shortest_paths(0, 0)) expected = [[0]] self.assertEqual(expected, sps) sps = sorted(g.get_all_shortest_paths(0, 5)) expected = [[0, 1, 2, 4, 5], [0, 1, 3, 4, 5]] self.assertEqual(expected, sps) sps = sorted(g.get_all_shortest_paths(1, 4)) expected = [[1, 2, 4], [1, 3, 4]] self.assertEqual(expected, sps) g = Graph.Lattice([5, 5], circular=False) sps = sorted(g.get_all_shortest_paths(0, 12)) expected = [[0, 1, 2, 7, 12], [0, 1, 6, 7, 12], [0, 1, 6, 11, 12], \ [0, 5, 6, 7, 12], [0, 5, 6, 11, 12], [0, 5, 10, 11, 12]] self.assertEqual(expected, sps) g = Graph.Lattice([100, 100], circular=False) sps = sorted(g.get_all_shortest_paths(0, 202)) expected = [[0, 1, 2, 102, 202], [0, 1, 101, 102, 202], [0, 1, 101, 201, 202], \ [0, 100, 101, 102, 202], [0, 100, 101, 201, 202], [0, 100, 200, 201, 202]] self.assertEqual(expected, sps) g = Graph.Lattice([100, 100], circular=False) sps = sorted(g.get_all_shortest_paths(0, [0, 202])) self.assertEqual([[0]] + expected, sps) g = Graph([(0,1), (1,2), (0,2)]) g.es["weight"] = [0.5, 0.5, 1] sps = sorted(g.get_all_shortest_paths(0, weights="weight")) self.assertEqual([[0], [0,1], [0,1,2], [0,2]], sps) g = Graph.Lattice([4, 4], circular=False) g.es["weight"] = 1 g.es[2,8]["weight"] = 100 sps = sorted(g.get_all_shortest_paths(0, [3, 12, 15], weights="weight")) self.assertEqual(20, len(sps)) self.assertEqual(4, sum(1 for path in sps if path[-1] == 3)) self.assertEqual(4, sum(1 for path in sps if path[-1] == 12)) self.assertEqual(12, sum(1 for path in sps if path[-1] == 15)) def testGetAllSimplePaths(self): g = Graph.Ring(20) sps = sorted(g.get_all_simple_paths(0, 10)) self.assertEqual([ [0,1,2,3,4,5,6,7,8,9,10], [0,19,18,17,16,15,14,13,12,11,10] ], sps) g = Graph.Ring(20, directed=True) sps = sorted(g.get_all_simple_paths(0, 10)) self.assertEqual([ [0,1,2,3,4,5,6,7,8,9,10] ], sps) sps = sorted(g.get_all_simple_paths(0, 10, mode="in")) self.assertEqual([ [0,19,18,17,16,15,14,13,12,11,10] ], sps) sps = sorted(g.get_all_simple_paths(0, 10, mode="all")) self.assertEqual([ [0,1,2,3,4,5,6,7,8,9,10], [0,19,18,17,16,15,14,13,12,11,10] ], sps) g = Graph.Lattice([4, 4], circular=False) g = Graph([(min(u, v), max(u, v)) for u, v in g.get_edgelist()], directed=True) sps = sorted(g.get_all_simple_paths(0, 15)) self.assertEqual(20, len(sps)) for path in sps: self.assertEqual(0, path[0]) self.assertEqual(15, path[-1]) curr = path[0] for next in path[1:]: self.assertTrue(g.are_connected(curr, next)) curr = next def testPathLengthHist(self): g = Graph.Tree(15, 2) h = g.path_length_hist() self.assertTrue(h.unconnected == 0) self.assertTrue([(int(l),x) for l,_,x in h.bins()] == \ [(1,14),(2,19),(3,20),(4,20),(5,16),(6,16)]) g = Graph.Full(5)+Graph.Full(4) h = g.path_length_hist() self.assertTrue(h.unconnected == 20) g.to_directed() h = g.path_length_hist() self.assertTrue(h.unconnected == 40) h = g.path_length_hist(False) self.assertTrue(h.unconnected == 20) class DominatorTests(unittest.TestCase): def compareDomTrees(self, alist, blist): ''' Required due to NaN use for isolated nodes ''' if len(alist) != len(blist): return False for i, (a, b) in enumerate(zip(alist, blist)): if math.isnan(a) and math.isnan(b): continue elif a == b: continue else: return False return True def testDominators(self): # examples taken from igraph's examples/simple/dominator_tree.out # initial g = Graph(13, [(0,1), (0,7), (0,10), (1,2), (1,5), (2,3), (3,4), (4,3), (4,0), (5,3), (5,6), (6,3), (7,8), (7,10), (7,11), (8,9), (9,4), (9,8), (10,11), (11,12), (12,9) ], directed=True) s = [-1, 0, 1, 0, 0, 1, 5, 0, 0, 0, 0, 0, 11 ] r = g.dominator(0) self.assertTrue(self.compareDomTrees(s, r)) # flipped edges g = Graph(13, [(1,0), (2,0), (3,0), (4,1), (1,2), (4,2), (5,2), (6,3), (7,3), (12,4), (8,5), (9,6), (9,7), (10,7), (5,8), (11,8), (11,9), (9,10), (9,11), (0,11), (8,12)], directed=True) s = [-1, 0, 0, 0, 0, 0, 3, 3, 0, 0, 7, 0, 4] r = g.dominator(0, mode=IN) self.assertTrue(self.compareDomTrees(s, r)) # disconnected components g = Graph(20, [(0,1), (0,2), (0,3), (1,4), (2,1), (2,4), (2,8), (3,9), (3,10), (4,15), (8,11), (9,12), (10,12), (10,13), (11,8), (11,14), (12,14), (13,12), (14,12), (14,0), (15,11)], directed=True) s = [-1, 0, 0, 0, 0, float("nan"), float("nan"), float("nan"), 0, 3, 3, 0, 0, 10, 0, 4, float("nan"), float("nan"), float("nan"), float("nan")] r = g.dominator(0, mode=OUT) self.assertTrue(self.compareDomTrees(s, r)) def suite(): simple_suite = unittest.makeSuite(SimplePropertiesTests) degree_suite = unittest.makeSuite(DegreeTests) local_transitivity_suite = unittest.makeSuite(LocalTransitivityTests) biconnected_suite = unittest.makeSuite(BiconnectedComponentTests) centrality_suite = unittest.makeSuite(CentralityTests) neighborhood_suite = unittest.makeSuite(NeighborhoodTests) path_suite = unittest.makeSuite(PathTests) misc_suite = unittest.makeSuite(MiscTests) dominator_suite = unittest.makeSuite(DominatorTests) return unittest.TestSuite([simple_suite, degree_suite, local_transitivity_suite, biconnected_suite, centrality_suite, neighborhood_suite, path_suite, misc_suite, dominator_suite]) def test(): runner = unittest.TextTestRunner() runner.run(suite()) if __name__ == "__main__": test() python-igraph-0.8.0/tests/test_attributes.py0000644000076500000240000002467213616232155021520 0ustar tamasstaff00000000000000# vim:ts=4 sw=4 sts=4: import unittest from igraph import * class AttributeTests(unittest.TestCase): def testGraphAttributes(self): g = Graph.Full(5) g["date"] = "2005-12-17" self.assertTrue(g["date"] == "2005-12-17") del g["date"] self.assertRaises(KeyError, g.__getitem__, "date") def testVertexAttributes(self): g = Graph.Full(5) g.vs[0]["name"] = "first" self.assertTrue(g.vs[0]["name"] == "first") del g.vs["name"] self.assertRaises(KeyError, g.vs.__getitem__, "name") g.vs[0]["name"] = "second" g.vs[0]["date"] = "2007-12-17" ans = g.vs[0].attribute_names() ans.sort() self.assertTrue(ans == ["date", "name"]) attrs = g.vs[0].attributes() self.assertTrue(attrs == {"name": "second", "date": "2007-12-17"}) def testEdgeAttributes(self): g = Graph.Full(5) g.es[0]["name"] = "first" self.assertTrue(g.es[0]["name"] == "first") del g.es["name"] self.assertRaises(KeyError, g.es.__getitem__, "name") g.es[0]["name"] = "second" g.es[0]["date"] = "2007-12-17" ans = g.es[0].attribute_names() ans.sort() self.assertTrue(ans == ["date", "name"]) attrs = g.es[0].attributes() self.assertTrue(attrs == {"name": "second", "date": "2007-12-17"}) def testMassVertexAttributeAssignment(self): g = Graph.Full(5) g.vs.set_attribute_values("name", list(range(5))) self.assertTrue(g.vs.get_attribute_values("name") == list(range(5))) g.vs["name"] = list(range(5,10)) self.assertTrue(g.vs["name"] == list(range(5,10))) g.vs["name2"] = (1,2,3,4,6) self.assertTrue(g.vs["name2"] == [1,2,3,4,6]) g.vs.set_attribute_values("name", [2]) self.assertTrue(g.vs["name"] == [2]*5) def testMassEdgeAttributeAssignment(self): g = Graph.Full(5) g.es.set_attribute_values("name", list(range(10))) self.assertTrue(g.es.get_attribute_values("name") == list(range(10))) g.es["name"] = list(range(10,20)) self.assertTrue(g.es["name"] == list(range(10,20))) g.es["name2"] = (1,2,3,4,6,1,2,3,4,6) self.assertTrue(g.es["name2"] == [1,2,3,4,6,1,2,3,4,6]) g.es.set_attribute_values("name", [2]) self.assertTrue(g.es["name"] == [2]*10) def testVertexNameIndexing(self): g = Graph.Famous("bull") g.vs["name"] = ["foo", "bar", "baz", "fred", "thud"] self.assertTrue(g.degree("bar") == 3) self.assertTrue(g.degree(["bar", "fred", 0]) == [3, 1, 2]) g.vs[2]["name"] = "quack" self.assertRaises(ValueError, g.degree, "baz") self.assertTrue(g.degree("quack") == 3) self.assertTrue(g.degree(u"quack") == 3) self.assertTrue(g.degree([u"bar", u"thud", 0]) == [3, 1, 2]) del g.vs["name"] self.assertRaises(ValueError, g.degree, [u"bar", u"thud", 0]) def testVertexNameIndexingBytes(self): g = Graph.Famous("bull") g.vs["name"] = [b"foo", b"bar", b"baz", b"fred", b"thud"] self.assertTrue(g.degree(b"bar") == 3) self.assertTrue(g.degree([b"bar", b"fred", 0]) == [3, 1, 2]) g.vs[2]["name"] = b"quack" self.assertRaises(ValueError, g.degree, b"baz") self.assertTrue(g.degree(b"quack") == 3) del g.vs["name"] self.assertRaises(ValueError, g.degree, [b"bar", b"thud", 0]) def testUnhashableVertexNames(self): g = Graph.Famous("bull") g.vs["name"] = [str(x) for x in range(4)] value = "this is not hashable".split() g.vs[2]["name"] = value # Trigger an indexing by doing a lookup by name try: g.vs.find("3") err = None except Exception as ex: err = ex # Check the exception self.assertTrue(isinstance(err, RuntimeError)) self.assertTrue(repr(value) in str(err)) def testVertexNameIndexingBug196(self): g = Graph() a, b = b'a', b'b' g.add_vertices([a, b]) g.add_edges([(a, b)]) self.assertEqual(g.ecount(), 1) self.assertTrue(g.are_connected(a, b)) def testInvalidAttributeNames(self): g = Graph.Famous("bull") for attr_name in [None, 2.654, unittest, str]: self.assertRaises(TypeError, g.vs.__setitem__, attr_name, "foo") self.assertRaises(TypeError, g.vs.__getitem__, attr_name, "foo") self.assertRaises(TypeError, g.vs[0].__setitem__, attr_name, "foo") self.assertRaises(TypeError, g.vs[0].__getitem__, attr_name, "foo") self.assertRaises(TypeError, g.es.__setitem__, attr_name, "foo") self.assertRaises(TypeError, g.es.__getitem__, attr_name, "foo") self.assertRaises(TypeError, g.es[0].__setitem__, attr_name, "foo") self.assertRaises(TypeError, g.es[0].__getitem__, attr_name, "foo") class AttributeCombinationTests(unittest.TestCase): def setUp(self): el = [(0,1), (1,0), (1,2), (2,3), (2,3), (2,3), (3,3)] self.g = Graph(el) self.g.es["weight"] = [1, 2, 3, 4, 5, 6, 7] self.g.es["weight2"] = [1, 2, 3, 4, 5, 6, 7] def testCombinationMax(self): g = self.g g.simplify(combine_edges="max") self.assertTrue(g.es["weight"] == [2, 3, 6]) self.assertTrue(g.es["weight2"] == [2, 3, 6]) def testCombinationMin(self): g = self.g g.simplify(combine_edges="min") self.assertTrue(g.es["weight"] == [1, 3, 4]) self.assertTrue(g.es["weight2"] == [1, 3, 4]) def testCombinationRandom(self): g = self.g g.simplify(combine_edges="random") del g.es["weight2"] for i in range(100): self.assertTrue(g.es[0]["weight"] in (1, 2)) self.assertTrue(g.es[1]["weight"] == 3) self.assertTrue(g.es[2]["weight"] in (4, 5, 6)) def testCombinationMean(self): g = self.g g.simplify(combine_edges="mean") self.assertTrue(g.es["weight"] == [1.5, 3, 5]) self.assertTrue(g.es["weight2"] == [1.5, 3, 5]) def testCombinationMedian(self): g = self.g g.es["weight2"] = [1, 0, 2, 4, 8, 6, 7] g.simplify(combine_edges="median") self.assertTrue(g.es["weight"] == [1.5, 3, 5]) self.assertTrue(g.es["weight2"] == [0.5, 2, 6]) def testCombinationSum(self): g = self.g g.simplify(combine_edges="sum") self.assertTrue(g.es["weight"] == [3, 3, 15]) self.assertTrue(g.es["weight2"] == [3, 3, 15]) def testCombinationProd(self): g = self.g g.simplify(combine_edges="prod") self.assertTrue(g.es["weight"] == [2, 3, 120]) self.assertTrue(g.es["weight2"] == [2, 3, 120]) def testCombinationMedian(self): g = self.g g.es["weight2"] = [1, 0, 2, 4, 8, 6, 7] g.simplify(combine_edges="median") self.assertTrue(g.es["weight"] == [1.5, 3, 5]) self.assertTrue(g.es["weight2"] == [0.5, 2, 6]) def testCombinationFirst(self): g = self.g g.es["weight2"] = [1, 0, 2, 6, 8, 4, 7] g.simplify(combine_edges="first") self.assertTrue(g.es["weight"] == [1, 3, 4]) self.assertTrue(g.es["weight2"] == [1, 2, 6]) def testCombinationLast(self): g = self.g g.es["weight2"] = [1, 0, 2, 6, 8, 4, 7] g.simplify(combine_edges="last") self.assertTrue(g.es["weight"] == [2, 3, 6]) self.assertTrue(g.es["weight2"] == [0, 2, 4]) def testCombinationConcat(self): g = self.g g.es["name"] = list("ABCDEFG") g.simplify(combine_edges=dict(name="concat")) self.assertFalse("weight" in g.edge_attributes()) self.assertFalse("weight2" in g.edge_attributes()) self.assertTrue(g.es["name"] == ["AB", "C", "DEF"]) def testCombinationMaxMinIgnore(self): g = self.g g.es["name"] = list("ABCDEFG") g.simplify(combine_edges={"weight": "min", "weight2": "max", "name": "ignore"}) self.assertTrue(g.es["weight"] == [1, 3, 4]) self.assertTrue(g.es["weight2"] == [2, 3, 6]) self.assertFalse("name" in g.edge_attributes()) def testCombinationIgnoreAsNone(self): g = self.g g.es["name"] = list("ABCDEFG") g.simplify(combine_edges={"weight": "min", "name": None}) self.assertTrue(g.es["weight"] == [1, 3, 4]) self.assertFalse("weight2" in g.edge_attributes()) self.assertFalse("name" in g.edge_attributes()) def testCombinationFunction(self): g = self.g def join_dash(l): return "-".join(l) g.es["name"] = list("ABCDEFG") g.simplify(combine_edges={"weight": max, "name": join_dash}) self.assertTrue(g.es["weight"] == [2, 3, 6]) self.assertFalse("weight2" in g.edge_attributes()) self.assertTrue(g.es["name"] == ["A-B", "C", "D-E-F"]) def testCombinationDefault(self): g = self.g g.simplify(combine_edges={None: "max"}) self.assertTrue(g.es["weight"] == [2, 3, 6]) self.assertTrue(g.es["weight2"] == [2, 3, 6]) def testCombinationDefaultOverride(self): g = self.g g.simplify(combine_edges={None: "max", "weight": "sum"}) self.assertTrue(g.es["weight"] == [3, 3, 15]) self.assertTrue(g.es["weight2"] == [2, 3, 6]) def testCombinationTypeMismatch(self): g = self.g g.es["weight"] = list("ABCDEFG") self.assertRaises(TypeError, g.simplify, combine_edges={"weight": "mean"}) def testCombinationNonexistentAttribute(self): g = self.g g.simplify(combine_edges={"nonexistent": max}) self.assertTrue(g.edge_attributes() == []) def testCombinationNone(self): g = self.g g.simplify() self.assertTrue(sorted(g.edge_attributes()) == []) class UnicodeAttributeTests(unittest.TestCase): def testUnicodeAttributeNameCombination(self): g = Graph.Erdos_Renyi(n=9, m=20) g.es[u"test"] = 1 g.contract_vertices([0,0,0,1,1,1,2,2,2]) def suite(): attribute_suite = unittest.makeSuite(AttributeTests) attribute_combination_suite = unittest.makeSuite(AttributeCombinationTests) unicode_attributes_suite = unittest.makeSuite(UnicodeAttributeTests) return unittest.TestSuite([attribute_suite, attribute_combination_suite, unicode_attributes_suite]) def test(): runner = unittest.TextTestRunner() runner.run(suite()) if __name__ == "__main__": test() python-igraph-0.8.0/tests/test_colortests.py0000644000076500000240000000742613606025206021525 0ustar tamasstaff00000000000000import unittest try: from itertools import izip except ImportError: izip = zip # Python 3.x from igraph import * class ColorTests(unittest.TestCase): def assertAlmostEqualMany(self, items1, items2, eps): for idx, (item1, item2) in enumerate(izip(items1, items2)): self.assertAlmostEqual(item1, item2, places=eps, msg="mismatch at index %d, %r != %r with %d digits" % (idx, items1, items2, eps)) def setUp(self): columns = ["r", "g", "b", "h", "v", "l", "s_hsv", "s_hsl", "alpha"] # Examples taken from http://en.wikipedia.org/wiki/HSL_and_HSV values = [ (1, 1, 1, 0, 1, 1, 0, 0, 1), (0.5, 0.5, 0.5, 0, 0.5, 0.5, 0, 0, 0.5), (0, 0, 0, 0, 0, 0, 0, 0, 1), (1, 0, 0, 0, 1, 0.5, 1, 1, 0.5), (0.75, 0.75, 0, 60, 0.75, 0.375, 1, 1, 0.25), (0, 0.5, 0, 120, 0.5, 0.25, 1, 1, 0.75), (0.5, 1, 1, 180, 1, 0.75, 0.5, 1, 1), (0.5, 0.5, 1, 240, 1, 0.75, 0.5, 1, 1), (0.75, 0.25, 0.75, 300, 0.75, 0.5, 0.666666667, 0.5, 0.25), (0.211, 0.149, 0.597, 248.3, 0.597, 0.373, 0.750, 0.601, 1), (0.495, 0.493, 0.721, 240.5, 0.721, 0.607, 0.316, 0.290, 0.75), ] self.data = [dict(zip(columns, value)) for value in values] for row in self.data: row["h"] /= 360. def _testGeneric(self, method, args1, args2=("r", "g", "b")): if len(args1) == len(args2)+1: args2 += ("alpha", ) for data in self.data: vals1 = [data.get(arg, 0.0) for arg in args1] vals2 = [data.get(arg, 0.0) for arg in args2] self.assertAlmostEqualMany(method(*vals1), vals2, 2) def testHSVtoRGB(self): self._testGeneric(hsv_to_rgb, "h s_hsv v".split()) def testHSVAtoRGBA(self): self._testGeneric(hsva_to_rgba, "h s_hsv v alpha".split()) def testHSLtoRGB(self): self._testGeneric(hsl_to_rgb, "h s_hsl l".split()) def testHSLAtoRGBA(self): self._testGeneric(hsla_to_rgba, "h s_hsl l alpha".split()) def testRGBtoHSL(self): self._testGeneric(rgb_to_hsl, "r g b".split(), "h s_hsl l".split()) def testRGBAtoHSLA(self): self._testGeneric(rgba_to_hsla, "r g b alpha".split(), "h s_hsl l alpha".split()) def testRGBtoHSV(self): self._testGeneric(rgb_to_hsv, "r g b".split(), "h s_hsv v".split()) def testRGBAtoHSVA(self): self._testGeneric(rgba_to_hsva, "r g b alpha".split(), "h s_hsv v alpha".split()) class PaletteTests(unittest.TestCase): def testGradientPalette(self): gp = GradientPalette("red", "blue", 3) self.assertTrue(gp.get(0) == (1., 0., 0., 1.)) self.assertTrue(gp.get(1) == (0.5, 0., 0.5, 1.)) self.assertTrue(gp.get(2) == (0., 0., 1., 1.)) def testAdvancedGradientPalette(self): agp = AdvancedGradientPalette(["red", "black", "blue"], n=9) self.assertTrue(agp.get(0) == (1., 0., 0., 1.)) self.assertTrue(agp.get(2) == (0.5, 0., 0., 1.)) self.assertTrue(agp.get(4) == (0., 0., 0., 1.)) self.assertTrue(agp.get(5) == (0., 0., 0.25, 1.)) self.assertTrue(agp.get(8) == (0., 0., 1., 1.)) agp = AdvancedGradientPalette(["red", "black", "blue"], [0, 8, 2], 9) self.assertTrue(agp.get(0) == (1., 0., 0., 1.)) self.assertTrue(agp.get(1) == (0.5, 0., 0.5, 1.)) self.assertTrue(agp.get(5) == (0., 0., 0.5, 1.)) def suite(): color_suite = unittest.makeSuite(ColorTests) palette_suite = unittest.makeSuite(PaletteTests) return unittest.TestSuite([color_suite, palette_suite]) def test(): runner = unittest.TextTestRunner() runner.run(suite()) if __name__ == "__main__": test() python-igraph-0.8.0/tests/test_games.py0000644000076500000240000001434613606025206020417 0ustar tamasstaff00000000000000import unittest from igraph import * class GameTests(unittest.TestCase): def testGRG(self): g = Graph.GRG(50, 0.2) self.assertTrue(isinstance(g, Graph)) g = Graph.GRG(50, 0.2, True) self.assertTrue(isinstance(g, Graph)) self.assertTrue("x" in g.vertex_attributes()) self.assertTrue("y" in g.vertex_attributes()) self.assertTrue(isinstance(Layout(zip(g.vs["x"], g.vs["y"])), Layout)) def testForestFire(self): g=Graph.Forest_Fire(100, 0.1) self.assertTrue(isinstance(g, Graph) and g.is_directed() == False) g=Graph.Forest_Fire(100, 0.1, directed=True) self.assertTrue(isinstance(g, Graph) and g.is_directed() == True) def testRecentDegree(self): g=Graph.Recent_Degree(100, 5, 10) self.assertTrue(isinstance(g, Graph)) def testPreference(self): g=Graph.Preference(100, [1, 1], [[1, 0], [0, 1]]) self.assertTrue(isinstance(g, Graph) and len(g.clusters()) == 2) g=Graph.Preference(100, [1, 1], [[1, 0], [0, 1]], attribute="type") l=g.vs.get_attribute_values("type") self.assertTrue(min(l) == 0 and max(l) == 1) def testAsymmetricPreference(self): g=Graph.Asymmetric_Preference(100, [[0, 1], [1, 0]], [[0, 1], [1, 0]]) self.assertTrue(isinstance(g, Graph) and len(g.clusters()) == 2) g=Graph.Asymmetric_Preference(100, [[0, 1], [1, 0]], [[1, 0], [0, 1]],\ attribute="type") l=g.vs.get_attribute_values("type") l1=[i[0] for i in l] l2=[i[1] for i in l] self.assertTrue(min(l1) == 0 and max(l1) == 1 and min(l2) == 0 and max(l2) == 1) g=Graph.Asymmetric_Preference(100, [[0, 1], [1, 0]], [[1, 0], [0, 1]]) self.assertTrue(isinstance(g, Graph) and len(g.clusters()) == 1) def testWattsStrogatz(self): g=Graph.Watts_Strogatz(1, 20, 1, 0.2) self.assertTrue(isinstance(g, Graph) and g.vcount()==20 and g.ecount()==20) def testRandomBipartiteNP(self): # Test np mode, undirected g = Graph.Random_Bipartite(10, 20, p=0.25) self.assertTrue(g.is_simple()) self.assertTrue(g.is_bipartite()) self.assertFalse(g.is_directed()) self.assertEqual([False]*10 + [True]*20, g.vs["type"]) # Test np mode, directed, "out" g = Graph.Random_Bipartite(10, 20, p=0.25, directed=True, neimode="out") self.assertTrue(g.is_simple()) self.assertTrue(g.is_bipartite()) self.assertTrue(g.is_directed()) self.assertEqual([False]*10 + [True]*20, g.vs["type"]) self.assertTrue(all(g.vs[e.tuple]["type"] == [False, True] for e in g.es)) # Test np mode, directed, "in" g = Graph.Random_Bipartite(10, 20, p=0.25, directed=True, neimode="in") self.assertTrue(g.is_simple()) self.assertTrue(g.is_bipartite()) self.assertTrue(g.is_directed()) self.assertEqual([False]*10 + [True]*20, g.vs["type"]) self.assertTrue(all(g.vs[e.tuple]["type"] == [True, False] for e in g.es)) # Test np mode, directed, "all" g = Graph.Random_Bipartite(10, 20, p=0.25, directed=True, neimode="all") self.assertTrue(g.is_simple()) self.assertTrue(g.is_bipartite()) self.assertTrue(g.is_directed()) self.assertEqual([False]*10 + [True]*20, g.vs["type"]) def testRandomBipartiteNM(self): # Test np mode, undirected g = Graph.Random_Bipartite(10, 20, m=50) self.assertTrue(g.is_simple()) self.assertTrue(g.is_bipartite()) self.assertFalse(g.is_directed()) self.assertEqual(50, g.ecount()) self.assertEqual([False]*10 + [True]*20, g.vs["type"]) # Test np mode, directed, "out" g = Graph.Random_Bipartite(10, 20, m=50, directed=True, neimode="out") self.assertTrue(g.is_simple()) self.assertTrue(g.is_bipartite()) self.assertTrue(g.is_directed()) self.assertEqual(50, g.ecount()) self.assertEqual([False]*10 + [True]*20, g.vs["type"]) self.assertTrue(all(g.vs[e.tuple]["type"] == [False, True] for e in g.es)) # Test np mode, directed, "in" g = Graph.Random_Bipartite(10, 20, m=50, directed=True, neimode="in") self.assertTrue(g.is_simple()) self.assertTrue(g.is_bipartite()) self.assertTrue(g.is_directed()) self.assertEqual(50, g.ecount()) self.assertEqual([False]*10 + [True]*20, g.vs["type"]) self.assertTrue(all(g.vs[e.tuple]["type"] == [True, False] for e in g.es)) # Test np mode, directed, "all" g = Graph.Random_Bipartite(10, 20, m=50, directed=True, neimode="all") self.assertTrue(g.is_simple()) self.assertTrue(g.is_bipartite()) self.assertTrue(g.is_directed()) self.assertEqual(50, g.ecount()) self.assertEqual([False]*10 + [True]*20, g.vs["type"]) def testRewire(self): # Undirected graph g=Graph.GRG(25, 0.4) degrees=g.degree() # Rewiring without loops g.rewire(10000) self.assertEqual(degrees, g.degree()) self.assertTrue(g.is_simple()) # Rewiring with loops (1) g.rewire(10000, mode="loops") self.assertEqual(degrees, g.degree()) self.assertFalse(any(g.is_multiple())) # Rewiring with loops (2) g = Graph.Full(4) g[1,3] = 0 degrees = g.degree() g.rewire(100, mode="loops") self.assertEqual(degrees, g.degree()) self.assertFalse(any(g.is_multiple())) # Directed graph g=Graph.GRG(25, 0.4) g.to_directed("mutual") indeg, outdeg = g.indegree(), g.outdegree() g.rewire(10000) self.assertEqual(indeg, g.indegree()) self.assertEqual(outdeg, g.outdegree()) self.assertTrue(g.is_simple()) # Directed graph with loops g.rewire(10000, mode="loops") self.assertEqual(indeg, g.indegree()) self.assertEqual(outdeg, g.outdegree()) self.assertFalse(any(g.is_multiple())) def suite(): game_suite = unittest.makeSuite(GameTests) return unittest.TestSuite([game_suite]) def test(): runner = unittest.TextTestRunner() runner.run(suite()) if __name__ == "__main__": test() python-igraph-0.8.0/tests/test_layouts.py0000644000076500000240000002520413606025356021024 0ustar tamasstaff00000000000000import unittest from igraph import Graph, Layout, BoundingBox class LayoutTests(unittest.TestCase): def testConstructor(self): layout = Layout([(0,0,1), (0,1,0), (1,0,0)]) self.assertEqual(layout.dim, 3) layout = Layout([(0,0,1), (0,1,0), (1,0,0)], 3) self.assertEqual(layout.dim, 3) self.assertRaises(ValueError, Layout, [(0,1), (1,0)], 3) def testIndexing(self): layout = Layout([(0,0,1), (0,1,0), (1,0,0), (2,1,3)]) self.assertEqual(len(layout), 4) self.assertEqual(layout[1], [0, 1, 0]) self.assertEqual(layout[3], [2, 1, 3]) row = layout[2] row[2] = 1 self.assertEqual(layout[2], [1, 0, 1]) del layout[1] self.assertEqual(len(layout), 3) def testScaling(self): layout = Layout([(0,0,1), (0,1,0), (1,0,0), (2,1,3)]) layout.scale(1.5) self.assertEqual(layout.coords, [[0., 0., 1.5], \ [0., 1.5, 0.], \ [1.5, 0., 0.], \ [3., 1.5, 4.5]]) layout = Layout([(0,0,1), (0,1,0), (1,0,0), (2,1,3)]) layout.scale(1, 1, 3) self.assertEqual(layout.coords, [[0, 0, 3], \ [0, 1, 0], \ [1, 0, 0], \ [2, 1, 9]]) layout = Layout([(0,0,1), (0,1,0), (1,0,0), (2,1,3)]) layout.scale((2, 2, 1)) self.assertEqual(layout.coords, [[0, 0, 1], \ [0, 2, 0], \ [2, 0, 0], \ [4, 2, 3]]) self.assertRaises(ValueError, layout.scale, 2, 3) def testTranslation(self): layout = Layout([(0,0,1), (0,1,0), (1,0,0), (2,1,3)]) layout2 = layout.copy() layout.translate(1,3,2) self.assertEqual(layout.coords, [[1, 3, 3], \ [1, 4, 2], \ [2, 3, 2], \ [3, 4, 5]]) layout.translate((-1,-3,-2)) self.assertEqual(layout.coords, layout2.coords) self.assertRaises(ValueError, layout.translate, v=[3]) def testCentroid(self): layout = Layout([(0,0,1), (0,1,0), (1,0,0), (2,1,3)]) centroid = layout.centroid() self.assertEqual(len(centroid), 3) self.assertAlmostEqual(centroid[0], 0.75) self.assertAlmostEqual(centroid[1], 0.5) self.assertAlmostEqual(centroid[2], 1.) def testBoundaries(self): layout = Layout([(0,0,1), (0,1,0), (1,0,0), (2,1,3)]) self.assertEqual(layout.boundaries(), ([0,0,0],[2,1,3])) self.assertEqual(layout.boundaries(1), ([-1,-1,-1],[3,2,4])) layout = Layout([]) self.assertRaises(ValueError, layout.boundaries) layout = Layout([], dim=3) self.assertRaises(ValueError, layout.boundaries) def testBoundingBox(self): layout = Layout([(0,1), (2,7)]) self.assertEqual(layout.bounding_box(), BoundingBox(0,1,2,7)) self.assertEqual(layout.bounding_box(1), BoundingBox(-1,0,3,8)) layout = Layout([]) self.assertEqual(layout.bounding_box(), BoundingBox(0,0,0,0)) def testCenter(self): layout = Layout([(-2,0), (-2,-2), (0,-2), (0,0)]) layout.center() self.assertEqual(layout.coords, [[-1,1], [-1,-1], [1,-1], [1,1]]) layout.center(5,5) self.assertEqual(layout.coords, [[4,6], [4,4], [6,4], [6,6]]) self.assertRaises(ValueError, layout.center, 3) self.assertRaises(TypeError, layout.center, p=6) def testFitInto(self): layout = Layout([(-2,0), (-2,-2), (0,-2), (0,0)]) layout.fit_into(BoundingBox(5,5,8,10), keep_aspect_ratio=False) self.assertEqual(layout.coords, [[5, 10], [5, 5], [8, 5], [8, 10]]) layout = Layout([(-2,0), (-2,-2), (0,-2), (0,0)]) layout.fit_into(BoundingBox(5,5,8,10)) self.assertEqual(layout.coords, [[5, 9], [5, 6], [8, 6], [8, 9]]) layout = Layout([(-1,-1,-1), (0,0,0), (1,1,1), (2,2,0), (3,3,-1)]) layout.fit_into((0,0,0,8,8,4)) self.assertEqual(layout.coords, \ [[0, 0, 0], [2, 2, 2], [4, 4, 4], [6, 6, 2], [8, 8, 0]] ) layout = Layout([]) layout.fit_into((6,7,8,11)) self.assertEqual(layout.coords, []) def testToPolar(self): layout = Layout([(0, 0), (-1, 1), (0, 1), (1, 1)]) layout.to_radial(min_angle=180, max_angle=0, max_radius=2) exp = [[0., 0.], [-2., 0.], [0., 2.], [2, 0.]] for idx in range(4): self.assertAlmostEqual(layout.coords[idx][0], exp[idx][0], places=3) self.assertAlmostEqual(layout.coords[idx][1], exp[idx][1], places=3) def testTransform(self): def tr(coord, dx, dy): return coord[0]+dx, coord[1]+dy layout = Layout([(1, 2), (3, 4)]) layout.transform(tr, 2, -1) self.assertEqual(layout.coords, [[3, 1], [5, 3]]) class LayoutAlgorithmTests(unittest.TestCase): def testAuto(self): def layout_test(graph, test_with_dims=(2, 3)): lo = graph.layout("auto") self.assertTrue(isinstance(lo, Layout)) self.assertEqual(len(lo[0]), 2) for dim in test_with_dims: lo = graph.layout("auto", dim=dim) self.assertTrue(isinstance(lo, Layout)) self.assertEqual(len(lo[0]), dim) return lo g = Graph.Barabasi(10) layout_test(g) g = Graph.GRG(101, 0.2) del g.vs["x"] del g.vs["y"] layout_test(g) g = Graph.Full(10) * 2 layout_test(g) g["layout"] = "graphopt" layout_test(g, test_with_dims=()) g.vs["x"] = range(20) g.vs["y"] = range(20, 40) layout_test(g, test_with_dims=()) del g["layout"] lo = layout_test(g, test_with_dims=(2,)) self.assertEqual([tuple(item) for item in lo], list(zip(range(20), range(20, 40)))) g.vs["z"] = range(40, 60) lo = layout_test(g) self.assertEqual([tuple(item) for item in lo], list(zip(range(20), range(20, 40), range(40, 60)))) def testCircle(self): def test_is_proper_circular_layout(graph, layout): xs, ys = zip(*layout) n = graph.vcount() self.assertEqual(n, len(xs)) self.assertEqual(n, len(ys)) self.assertAlmostEqual(0, sum(xs)) self.assertAlmostEqual(0, sum(ys)) for x, y in zip(xs, ys): self.assertAlmostEqual(1, x**2+y**2) g = Graph.Ring(8) layout = g.layout("circle") test_is_proper_circular_layout(g, g.layout("circle")) order = [0, 2, 4, 6, 1, 3, 5, 7] ordered_layout = g.layout("circle", order=order) test_is_proper_circular_layout(g, g.layout("circle")) for v, w in enumerate(order): self.assertAlmostEqual(layout[v][0], ordered_layout[w][0]) self.assertAlmostEqual(layout[v][1], ordered_layout[w][1]) def testDavidsonHarel(self): # Quick smoke testing only g = Graph.Barabasi(100) lo = g.layout("dh") self.assertTrue(isinstance(lo, Layout)) def testFruchtermanReingold(self): g = Graph.Barabasi(100) lo = g.layout("fr") self.assertTrue(isinstance(lo, Layout)) lo = g.layout("fr", miny=range(100)) self.assertTrue(isinstance(lo, Layout)) self.assertTrue(all(lo[i][1] >= i for i in range(100))) lo = g.layout("fr", miny=range(100), maxy=range(100)) self.assertTrue(isinstance(lo, Layout)) self.assertTrue(all(lo[i][1] == i for i in range(100))) lo = g.layout("fr", miny=[2]*100, maxy=[3]*100, minx=[4]*100, maxx=[6]*100) self.assertTrue(isinstance(lo, Layout)) bbox = lo.bounding_box() self.assertTrue(bbox.top >= 2) self.assertTrue(bbox.bottom <= 3) self.assertTrue(bbox.left >= 4) self.assertTrue(bbox.right <= 6) def testFruchtermanReingoldGrid(self): g = Graph.Barabasi(100) for grid_opt in ["grid", "nogrid", "auto", True, False]: lo = g.layout("fr", miny=range(100), grid=grid_opt) self.assertTrue(isinstance(lo, Layout)) self.assertTrue(all(lo[i][1] >= i for i in range(100))) def testKamadaKawai(self): g = Graph.Barabasi(100) lo = g.layout("kk", miny=[2]*100, maxy=[3]*100, minx=[4]*100, maxx=[6]*100) self.assertTrue(isinstance(lo, Layout)) bbox = lo.bounding_box() self.assertTrue(bbox.top >= 2) self.assertTrue(bbox.bottom <= 3) self.assertTrue(bbox.left >= 4) self.assertTrue(bbox.right <= 6) def testMDS(self): g = Graph.Tree(10, 2) lo = g.layout("mds") self.assertTrue(isinstance(lo, Layout)) dists = g.shortest_paths() lo = g.layout("mds", dists) self.assertTrue(isinstance(lo, Layout)) g += Graph.Tree(10, 2) lo = g.layout("mds") self.assertTrue(isinstance(lo, Layout)) def testReingoldTilford(self): g = Graph.Barabasi(100) lo = g.layout("rt") ys = [coord[1] for coord in lo] root = ys.index(0.0) self.assertEqual(ys, g.shortest_paths(root)[0]) g = Graph.Barabasi(100) + Graph.Barabasi(50) lo = g.layout("rt", root=[0, 100]) self.assertEqual(lo[100][1]-lo[0][1], 0) lo = g.layout("rt", root=[0, 100], rootlevel=[2, 10]) self.assertEqual(lo[100][1]-lo[0][1], 8) def testBipartite(self): g = Graph.Full_Bipartite(3, 2) lo = g.layout("bipartite") ys = [coord[1] for coord in lo] self.assertEqual([1, 1, 1, 0, 0], ys) lo = g.layout("bipartite", vgap=3) ys = [coord[1] for coord in lo] self.assertEqual([3, 3, 3, 0, 0], ys) lo = g.layout("bipartite", hgap=5) self.assertEqual(set([0, 5, 10]), set(coord[0] for coord in lo if coord[1] == 1)) self.assertEqual(set([2.5, 7.5]), set(coord[0] for coord in lo if coord[1] == 0)) def testDRL(self): # Regression test for bug #1091891 g = Graph.Ring(10, circular=False) + 1 lo = g.layout("drl") self.assertTrue(isinstance(lo, Layout)) def suite(): layout_suite = unittest.makeSuite(LayoutTests) layout_algorithm_suite = unittest.makeSuite(LayoutAlgorithmTests) return unittest.TestSuite([layout_suite, layout_algorithm_suite]) def test(): runner = unittest.TextTestRunner() runner.run(suite()) if __name__ == "__main__": test() python-igraph-0.8.0/tests/test_spectral.py0000644000076500000240000000313013606025206021125 0ustar tamasstaff00000000000000# vim:set ts=4 sw=4 sts=4 et: import unittest from igraph import * class SpectralTests(unittest.TestCase): def assertAlmostEqualMatrix(self, mat1, mat2, eps = 1e-7): self.assertTrue(all( abs(obs-exp) < eps for obs, exp in zip(sum(mat1, []), sum(mat2, [])) )) def testLaplacian(self): g=Graph.Full(3) g.es["weight"] = [1, 2, 3] self.assertTrue(g.laplacian() == [[ 2, -1, -1],\ [-1, 2, -1],\ [-1, -1, 2]]) self.assertAlmostEqualMatrix(g.laplacian(normalized=True), [[1, -0.5, -0.5], [-0.5, 1, -0.5], [-0.5, -0.5, 1]]) mx0 = [[1., -1/(12**0.5), -2/(15**0.5)], [-1/(12**0.5), 1., -3/(20**0.5)], [-2/(15**0.5), -3/(20**0.5), 1.]] self.assertAlmostEqualMatrix(g.laplacian("weight", True), mx0) g=Graph.Tree(5, 2) g.add_vertices(1) self.assertTrue(g.laplacian() == [[ 2, -1, -1, 0, 0, 0],\ [-1, 3, 0, -1, -1, 0],\ [-1, 0, 1, 0, 0, 0],\ [ 0, -1, 0, 1, 0, 0],\ [ 0, -1, 0, 0, 1, 0],\ [ 0, 0, 0, 0, 0, 0]]) def suite(): spectral_suite = unittest.makeSuite(SpectralTests) return unittest.TestSuite([spectral_suite]) def test(): runner = unittest.TextTestRunner() runner.run(suite()) if __name__ == "__main__": test() python-igraph-0.8.0/MANIFEST.in0000644000076500000240000000107213614767471016316 0ustar tamasstaff00000000000000include setup.cfg include src/_igraph/*.h include MANIFEST.in include COPYING include scripts/mkdoc.sh include scripts/epydoc-patched include scripts/epydoc.cfg include tests/*.py graft vendor/source/igraph prune vendor/source/igraph/doc/abstracts prune vendor/source/igraph/doc/papers prune vendor/source/igraph/doc/presentations prune vendor/source/igraph/interfaces prune vendor/source/igraph/msvc prune vendor/source/igraph/nexus prune vendor/source/igraph/tools/virtual prune vendor/source/igraph/optional/simpleraytracer prune vendor/source/igraph/tools/virtual python-igraph-0.8.0/README.md0000644000076500000240000001256213614764153016037 0ustar tamasstaff00000000000000 [![](https://travis-ci.org/igraph/python-igraph.svg?branch=master)](https://travis-ci.org/igraph/python-igraph) Python interface for the igraph library --------------------------------------- igraph is a library for creating and manipulating graphs. It is intended to be as powerful (ie. fast) as possible to enable the analysis of large graphs. This repository contains the source code to the Python interface of igraph. You can learn more about python-igraph [on our website](http://igraph.org/python/). ## Installation from PyPI We aim to provide wheels on PyPI for most of the stock Python versions; typically the three most recent minor releases from Python 3.x. Therefore, running the following command should work without having to compile anything during installation: ``` $ pip install python-igraph ``` See details in [Installing Python Modules](https://docs.python.org/3/installing/). ### Installation from source with pip on Debian / Ubuntu and derivatives If you need to compile python-igraph from source for some reason, you need to install some dependencies first: ``` $ sudo apt install build-essential python-dev libxml2 libxml2-dev zlib1g-dev bison flex ``` and then run ``` $ pip install python-igraph ``` This should compile the C core of igraph as well as the Python extension automatically. ### Linking to an existing igraph installation The source code of the Python package includes the source code of the matching igraph version that the Python interface should compile against. However, if you want to link the Python interface to a custom installation of the C core that has already been compiled and installed on your system, you can ask `setup.py` to use the pre-compiled version. This option requires that your custom installation of igraph is discoverable with `pkg-config`. First, check whether `pkg-config` can tell you the required compiler and linker flags for igraph: ``` $ pkg-config --cflags --libs igraph ``` If `pkg-config` responds with a set of compiler and linker flags and not an error message, you are probably okay. You can then proceed with the installation using pip: ``` $ pip install python-igraph --install-option="--use-pkg-config" ``` Alternatively, if you have already downloaded and extracted the source code of igraph, you can run `setup.py` directly: ``` $ python setup.py build --use-pkg-config ``` This option is primarily intended for package maintainers in Linux distributions so they can ensure that the packaged Python interface links to the packaged igraph library instead of bringing its own copy. It is also useful on macOS if you want to link to the igraph library installed from Homebrew. ## Compiling the development version If you have downloaded the source code from Github and not PyPI, chances are that you have the latest development version, which contains a matching version of the C core of igraph as a git submodule. Therefore, to install the bleeding edge version, you need to instruct git to check out the submodules first: ``` git submodule update --init ``` Then, running the setup script should work if you have a C compiler and the necessary build dependencies (see the previous section): ``` $ sudo python setup.py build ``` ## Running unit tests Unit tests can be executed from the project directory with `tox` or with the built-in unittest module: ``` $ python -m unittest ``` ## Contributing Contributions to `python-igraph` are welcome! If you want to add a feature, fix a bug, or suggest an improvement, open an issue on this repository and we'll try to answer. If you have a piece of code that you would like to see included in the main tree, open a PR on this repo. To start developing `python-igraph`, follow the steps below (these are for Linux, Windows users should change the system commands a little). First, clone this repo (e.g. via https) and enter the folder: ```bash git clone https://github.com/igraph/python-igraph.git cd python-igraph ``` Second, check out the necessary git submodules: ```bash git submodule update --init ``` and install igraph in development mode so your changes in the Python source code are picked up automatically by Python: ```bash python setup.py develop ``` **NOTE**: Building requires `autotools`, a C compiler, and a few more dependencies. Changes that you make to the Python code do not need any extra action. However, if you adjust the source code of the C extension, you need to rebuild it by running `python setup.py develop` again. However, compilation of igraph's C core is cached in ``vendor/build`` and ``vendor/install`` so subsequent builds are much faster than the first one as the C core does not need to be recompiled. ## Notes ### Pypy This version of python-igraph is compatible with [PyPy](http://pypy.org/) and is regularly tested on [PyPy](http://pypy.org/) with ``tox``. However, the PyPy version falls behind the CPython version in terms of performance; for instance, running all the tests takes ~5 seconds on my machine with CPython and ~15 seconds with PyPy. This can probably be attributed to the need for emulating CPython reference counting, and does not seem to be alleviated by the JIT. There are also some subtle differences between the CPython and PyPy versions: - Docstrings defined in the C source code are not visible from PyPy. - ``GraphBase`` is hashable and iterable in PyPy but not in CPython. Since ``GraphBase`` is internal anyway, this is likely to stay this way. python-igraph-0.8.0/COPYING0000644000076500000240000004313313104627150015576 0ustar tamasstaff00000000000000 GNU GENERAL PUBLIC LICENSE Version 2, June 1991 Copyright (C) 1989, 1991 Free Software Foundation, Inc. 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed. Preamble The licenses for most software are designed to take away your freedom to share and change it. By contrast, the GNU General Public License is intended to guarantee your freedom to share and change free software--to make sure the software is free for all its users. This General Public License applies to most of the Free Software Foundation's software and to any other program whose authors commit to using it. (Some other Free Software Foundation software is covered by the GNU Library General Public License instead.) You can apply it to your programs, too. When we speak of free software, we are referring to freedom, not price. Our General Public Licenses are designed to make sure that you have the freedom to distribute copies of free software (and charge for this service if you wish), that you receive source code or can get it if you want it, that you can change the software or use pieces of it in new free programs; and that you know you can do these things. To protect your rights, we need to make restrictions that forbid anyone to deny you these rights or to ask you to surrender the rights. These restrictions translate to certain responsibilities for you if you distribute copies of the software, or if you modify it. For example, if you distribute copies of such a program, whether gratis or for a fee, you must give the recipients all the rights that you have. You must make sure that they, too, receive or can get the source code. And you must show them these terms so they know their rights. We protect your rights with two steps: (1) copyright the software, and (2) offer you this license which gives you legal permission to copy, distribute and/or modify the software. Also, for each author's protection and ours, we want to make certain that everyone understands that there is no warranty for this free software. If the software is modified by someone else and passed on, we want its recipients to know that what they have is not the original, so that any problems introduced by others will not reflect on the original authors' reputations. Finally, any free program is threatened constantly by software patents. We wish to avoid the danger that redistributors of a free program will individually obtain patent licenses, in effect making the program proprietary. To prevent this, we have made it clear that any patent must be licensed for everyone's free use or not licensed at all. The precise terms and conditions for copying, distribution and modification follow. 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It is safest to attach them to the start of each source file to most effectively convey the exclusion of warranty; and each file should have at least the "copyright" line and a pointer to where the full notice is found. Copyright (C) This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA Also add information on how to contact you by electronic and paper mail. If the program is interactive, make it output a short notice like this when it starts in an interactive mode: Gnomovision version 69, Copyright (C) year name of author Gnomovision comes with ABSOLUTELY NO WARRANTY; for details type `show w'. This is free software, and you are welcome to redistribute it under certain conditions; type `show c' for details. The hypothetical commands `show w' and `show c' should show the appropriate parts of the General Public License. Of course, the commands you use may be called something other than `show w' and `show c'; they could even be mouse-clicks or menu items--whatever suits your program. You should also get your employer (if you work as a programmer) or your school, if any, to sign a "copyright disclaimer" for the program, if necessary. Here is a sample; alter the names: Yoyodyne, Inc., hereby disclaims all copyright interest in the program `Gnomovision' (which makes passes at compilers) written by James Hacker. , 1 April 1989 Ty Coon, President of Vice This General Public License does not permit incorporating your program into proprietary programs. If your program is a subroutine library, you may consider it more useful to permit linking proprietary applications with the library. If this is what you want to do, use the GNU Library General Public License instead of this License. python-igraph-0.8.0/setup.py0000644000076500000240000007523013616240402016257 0ustar tamasstaff00000000000000#usr/bin/env python import os import platform import sys ########################################################################### # Global version number. Keep the format of the next line intact. VERSION = "0.7.1.post6" # Check Python's version info and exit early if it is too old if sys.version_info < (2, 7): print("This module requires Python >= 2.7") sys.exit(0) # Check whether we are compiling for PyPy. Headers will not be installed # for PyPy. SKIP_HEADER_INSTALL = (platform.python_implementation() == "PyPy") or ( "SKIP_HEADER_INSTALL" in os.environ ) ########################################################################### from setuptools import setup, Command, Extension import distutils.ccompiler import glob import shutil import subprocess import sys from select import select ########################################################################### LIBIGRAPH_FALLBACK_INCLUDE_DIRS = ["/usr/include/igraph", "/usr/local/include/igraph"] LIBIGRAPH_FALLBACK_LIBRARIES = ["igraph"] LIBIGRAPH_FALLBACK_LIBRARY_DIRS = [] ########################################################################### def create_dir_unless_exists(*args): """Creates a directory unless it exists already.""" path = os.path.join(*args) if not os.path.isdir(path): os.makedirs(path) def ensure_dir_does_not_exist(*args): """Ensures that the given directory does not exist.""" path = os.path.join(*args) if os.path.isdir(path): shutil.rmtree(path) def exclude_from_list(items, items_to_exclude): """Excludes certain items from a list, keeping the original order of the remaining items.""" itemset = set(items_to_exclude) return [item for item in items if item not in itemset] def find_static_library(library_name, library_path): """Given the raw name of a library in `library_name`, tries to find a static library with this name in the given `library_path`. `library_path` is automatically extended with common library directories on Linux and Mac OS X.""" variants = ["lib{0}.a", "{0}.a", "{0}.lib", "lib{0}.lib"] if is_unix_like(): extra_libdirs = [ "/usr/local/lib64", "/usr/local/lib", "/usr/lib64", "/usr/lib", "/lib64", "/lib", ] else: extra_libdirs = [] for path in extra_libdirs: if path not in library_path and os.path.isdir(path): library_path.append(path) for path in library_path: for variant in variants: full_path = os.path.join(path, variant.format(library_name)) if os.path.isfile(full_path): return full_path def first(iterable): """Returns the first element from the given iterable.""" for item in iterable: return item raise ValueError("iterable is empty") def get_output(args, encoding="utf-8"): """Returns the output of a command returning a single line of output.""" PIPE = subprocess.PIPE try: p = subprocess.Popen(args, shell=False, stdin=PIPE, stdout=PIPE, stderr=PIPE) stdout, stderr = p.communicate() returncode = p.returncode except OSError: stdout, stderr = None, None returncode = 77 if encoding and type(stdout).__name__ == "bytes": stdout = str(stdout, encoding=encoding) if encoding and type(stderr).__name__ == "bytes": stderr = str(stderr, encoding=encoding) return stdout, returncode def get_output_single_line(args, encoding="utf-8"): """Returns the output of a command returning a single line of output, stripped from any trailing newlines.""" stdout, returncode = get_output(args, encoding=encoding) if stdout is not None: line, _, _ = stdout.partition("\n") else: line = None return line, returncode def is_unix_like(platform=None): """Returns whether the given platform is a Unix-like platform with the usual Unix filesystem. When the parameter is omitted, it defaults to ``sys.platform`` """ platform = platform or sys.platform platform = platform.lower() return ( platform.startswith("linux") or platform.startswith("darwin") or platform.startswith("cygwin") ) def find_msvc_source_folder(folder = ".", requires_built=False): """Finds the folder that contains the MSVC-specific source of igraph if there is any. Returns `None` if no such folder is found. Prints a warning if the choice is ambiguous. """ all_msvc_dirs = glob.glob(os.path.join(folder, "igraph-*-msvc")) if len(all_msvc_dirs) > 0: if len(all_msvc_dirs) > 1: print( "More than one MSVC build directory (..\\..\\igraph-*-msvc) found!" ) print( "It could happen that setup.py uses the wrong one! Please remove all but the right one!\n\n" ) msvc_builddir = all_msvc_dirs[-1] if requires_built and not os.path.exists(os.path.join(msvc_builddir, "Release")): print( "There is no 'Release' dir in the MSVC build directory\n(%s)" % msvc_builddir ) print("Please build the MSVC build first!\n") return None return msvc_builddir else: return None def preprocess_fallback_config(): """Preprocesses the fallback include and library paths depending on the platform.""" global LIBIGRAPH_FALLBACK_INCLUDE_DIRS global LIBIGRAPH_FALLBACK_LIBRARY_DIRS global LIBIGRAPH_FALLBACK_LIBRARIES if platform.system() == "Windows" and distutils.ccompiler.get_default_compiler() == "msvc": # if this setup is run in the source checkout *and* the igraph msvc was build, # this code adds the right library and include dir msvc_builddir = find_msvc_source_folder(os.path.join("..", ".."), requires_built=True) if msvc_builddir is not None: print("Using MSVC build dir: %s\n\n" % msvc_builddir) LIBIGRAPH_FALLBACK_INCLUDE_DIRS = [ os.path.join(msvc_builddir, "include") ] LIBIGRAPH_FALLBACK_LIBRARY_DIRS = [ os.path.join(msvc_builddir, "Release") ] return True else: return False else: return True def quote_path_for_shell(s): # On MinGW / MSYS, we need to use forward slash style and remove unsafe # characters in order not to trip up the configure script if "MSYSTEM" in os.environ: s = s.replace("\\", "/") if s[1:3] == ":/": s = "/" + s[0] + s[2:] # Now the proper quoting return "'" + s.replace("'", "'\\''") + "'" def wait_for_keypress(seconds): """Wait for a keypress or until the given number of seconds have passed, whichever happens first. """ is_windows = platform.system() == "windows" while seconds > 0: if seconds > 1: plural = "s" else: plural = "" sys.stdout.write( "\rContinuing in %2d second%s; press Enter to continue " "immediately. " % (seconds, plural) ) sys.stdout.flush() if is_windows: from msvcrt import kbhit for i in range(10): if kbhit(): seconds = 0 break sleep(0.1) else: rlist, _, _ = select([sys.stdin], [], [], 1) if rlist: sys.stdin.readline() seconds = 0 break seconds -= 1 sys.stdout.write("\r" + " " * 65 + "\r") ########################################################################### class IgraphCCoreBuilder(object): """Class responsible for downloading and building the C core of igraph if it is not installed yet.""" def compile_in(self, build_folder, source_folder=None): """Compiles igraph from its source code in the given folder. source_folder is the name of the folder that contains igraph's source files. If it is `None`, it is assumed that it is the same as the build folder. """ if source_folder is None: source_folder = build_folder source_folder = os.path.abspath(source_folder) build_folder = os.path.abspath(build_folder) cwd = os.getcwd() try: os.chdir(source_folder) # Run the bootstrap script if we have downloaded a tarball from # Github if os.path.isfile("bootstrap.sh") and not os.path.isfile("configure"): print("Bootstrapping igraph...") retcode = subprocess.call("sh bootstrap.sh", shell=True) if retcode: return False # Patch ltmain.sh so it does not freak out when the build directory # contains spaces with open("ltmain.sh") as infp: with open("ltmain.sh.new", "w") as outfp: for line in infp: if line.endswith("cd $darwin_orig_dir\n"): line = line.replace( "cd $darwin_orig_dir\n", 'cd "$darwin_orig_dir"\n' ) outfp.write(line) shutil.move("ltmain.sh.new", "ltmain.sh") create_dir_unless_exists(build_folder) os.chdir(build_folder) print("Configuring igraph...") configure_args = ["--disable-tls"] if "IGRAPH_EXTRA_CONFIGURE_ARGS" in os.environ: configure_args.extend(os.environ["IGRAPH_EXTRA_CONFIGURE_ARGS"].split(" ")) retcode = subprocess.call( "sh {0} {1}".format( quote_path_for_shell(os.path.join(source_folder, "configure")), " ".join(configure_args) ), env=self.enhanced_env(CFLAGS="-fPIC", CXXFLAGS="-fPIC"), shell=True ) if retcode: return False building_on_windows = platform.system() == "Windows" if building_on_windows: print("Creating Microsoft Visual Studio project...") retcode = subprocess.call("make msvc", shell=True) if retcode: return False print("Building igraph...") if building_on_windows: msvc_source = find_msvc_source_folder() if not msvc_source: return False devenv = os.environ.get("DEVENV_EXECUTABLE") os.chdir(msvc_source) if devenv is None: retcode = subprocess.call("devenv /upgrade igraph.vcproj", shell=True) else: retcode = subprocess.call([devenv, "/upgrade", "igraph.vcproj"]) if retcode: return False retcode = subprocess.call("msbuild.exe igraph.vcxproj /p:configuration=Release") else: retcode = subprocess.call("make", shell=True) if retcode: return False if building_on_windows: libraries = ["igraph"] else: libraries = [] for line in open("igraph.pc"): if line.startswith("Libs: ") or line.startswith("Libs.private: "): words = line.strip().split() libraries.extend( word[2:] for word in words if word.startswith("-l") ) if not libraries: # Educated guess libraries = ["igraph"] return libraries finally: os.chdir(cwd) def copy_build_artifacts( self, source_folder, build_folder, install_folder, libraries ): building_on_windows = platform.system() == "Windows" create_dir_unless_exists(install_folder) ensure_dir_does_not_exist(install_folder, "include") ensure_dir_does_not_exist(install_folder, "lib") shutil.copytree( os.path.join(source_folder, "include"), os.path.join(install_folder, "include"), ) create_dir_unless_exists(install_folder, "lib") for fname in glob.glob(os.path.join(build_folder, "include", "*.h")): shutil.copy(fname, os.path.join(install_folder, "include")) if building_on_windows: msvc_builddir = find_msvc_source_folder(build_folder, requires_built=True) if msvc_builddir is not None: print("Using MSVC build dir: %s\n\n" % msvc_builddir) for fname in glob.glob( os.path.join(msvc_builddir, "Release", "*.lib") ): shutil.copy(fname, os.path.join(install_folder, "lib")) else: print("Cannot find MSVC build dir in %s\n\n" % build_folder) return False else: for fname in glob.glob( os.path.join(build_folder, "src", ".libs", "libigraph.*") ): shutil.copy(fname, os.path.join(install_folder, "lib")) with open(os.path.join(install_folder, "build.cfg"), "w") as f: f.write(repr(libraries)) return True @staticmethod def enhanced_env(**kwargs): env = os.environ.copy() for k, v in kwargs.items(): prev = os.environ.get(k) env[k] = "{0} {1}".format(prev, v) if prev else v return env class BuildConfiguration(object): def __init__(self): self.include_dirs = [] self.library_dirs = [] self.runtime_library_dirs = [] self.libraries = [] self.extra_compile_args = [] self.extra_link_args = [] self.define_macros = [] self.extra_objects = [] self.static_extension = False self.use_pkgconfig = False self._has_pkgconfig = None self.excluded_include_dirs = [] self.excluded_library_dirs = [] self.wait = platform.system() != "Windows" @property def has_pkgconfig(self): """Returns whether ``pkg-config`` is available on the current system and it knows about igraph or not.""" if self._has_pkgconfig is None: if self.use_pkgconfig: line, exit_code = get_output_single_line(["pkg-config", "igraph"]) self._has_pkgconfig = exit_code == 0 else: self._has_pkgconfig = False return self._has_pkgconfig @property def build_c_core(self): """Returns a class representing a custom setup.py command that builds the C core of igraph. This is used in CI environments where we want to build the C core of igraph once and then build the Python interface for various Python versions without having to recompile the C core all the time. If is also used as a custom building block of `build_ext`. """ buildcfg = self class build_c_core(Command): description = "Compile the C core of igraph only" user_options = [] def initialize_options(self): pass def finalize_options(self): pass def run(self): buildcfg.c_core_built = buildcfg.compile_igraph_from_vendor_source() return build_c_core @property def build_ext(self): """Returns a class that can be used as a replacement for the ``build_ext`` command in ``setuptools`` and that will compile the C core of igraph before compiling the Python extension. """ from setuptools.command.build_ext import build_ext from distutils.sysconfig import get_python_inc buildcfg = self class custom_build_ext(build_ext): def run(self): # Bail out if we don't have the Python include files include_dir = get_python_inc() if not os.path.isfile(os.path.join(include_dir, "Python.h")): print("You will need the Python headers to compile this extension.") sys.exit(1) # Check whether the user asked us to discover a pre-built igraph # with pkg-config if buildcfg.use_pkgconfig: detected = buildcfg.detect_from_pkgconfig() if not detected: print("Cannot find the C core of igraph on this system using pkg-config.") sys.exit(1) else: # Build the C core from the vendored igraph source self.run_command("build_c_core") if not buildcfg.c_core_built: # Fall back to an educated guess if everything else failed if not detected: buildcfg.use_educated_guess() # Add any extra library paths if needed; this is needed for the # Appveyor CI build if "IGRAPH_EXTRA_LIBRARY_PATH" in os.environ: buildcfg.library_dirs = list( os.environ["IGRAPH_EXTRA_LIBRARY_PATH"].split(os.pathsep) ) + buildcfg.library_dirs # Replaces library names with full paths to static libraries # where possible. libm.a is excluded because it caused problems # on Sabayon Linux where libm.a is probably not compiled with # -fPIC if buildcfg.static_extension: if buildcfg.static_extension == "only_igraph": buildcfg.replace_static_libraries(only=["igraph"]) else: buildcfg.replace_static_libraries(exclusions=["m"]) # Prints basic build information buildcfg.print_build_info() # Find the igraph extension and configure it with the settings # of this build configuration ext = first( extension for extension in self.extensions if extension.name == "igraph._igraph" ) buildcfg.configure(ext) # Run the original build_ext command build_ext.run(self) return custom_build_ext @property def sdist(self): """Returns a class that can be used as a replacement for the ``sdist`` command in ``setuptools`` and that will clean up ``vendor/source/igraph`` before running the original ``sdist`` command. """ from setuptools.command.sdist import sdist from distutils.sysconfig import get_python_inc buildcfg = self class custom_sdist(sdist): def run(self): # Clean up vendor/source/igraph with git cwd = os.getcwd() try: os.chdir(os.path.join("vendor", "source", "igraph")) if os.path.exists(".git"): retcode = subprocess.call("git clean -dfx", shell=True) if retcode: print("Failed to clean vendor/source/igraph with git") print("") return False finally: os.chdir(cwd) # Run the original sdist command sdist.run(self) return custom_sdist def compile_igraph_from_vendor_source(self): """Compiles igraph from the vendored source code inside `vendor/igraph/source`. This folder typically comes from a git submodule. """ if os.path.exists(os.path.join("vendor", "install", "igraph")): # Vendored igraph already compiled and installed, just use it self.use_vendored_igraph() return True vendor_source_path = os.path.join("vendor", "source", "igraph") if not os.path.isfile(os.path.join(vendor_source_path, "configure.ac")): # No git submodule present with vendored source print("Cannot find vendored igraph source in " + vendor_source_path) print("") return False source_folder = os.path.join("vendor", "source", "igraph") build_folder = os.path.join("vendor", "build", "igraph") install_folder = os.path.join("vendor", "install", "igraph") print("We are going to build the C core of igraph.") print(" Source folder: %s" % source_folder) print(" Build folder: %s" % build_folder) print(" Install folder: %s" % install_folder) print("") igraph_builder = IgraphCCoreBuilder() libraries = igraph_builder.compile_in(build_folder, source_folder=source_folder) if not libraries or not igraph_builder.copy_build_artifacts( source_folder=source_folder, build_folder=build_folder, install_folder=install_folder, libraries=libraries, ): print("Could not compile the C core of igraph.") print("") sys.exit(1) self.use_vendored_igraph() return True def configure(self, ext): """Configures the given Extension object using this build configuration.""" ext.include_dirs = exclude_from_list( self.include_dirs, self.excluded_include_dirs ) ext.library_dirs = exclude_from_list( self.library_dirs, self.excluded_library_dirs ) ext.runtime_library_dirs = self.runtime_library_dirs ext.libraries = self.libraries ext.extra_compile_args = self.extra_compile_args ext.extra_link_args = self.extra_link_args ext.extra_objects = self.extra_objects ext.define_macros = self.define_macros def detect_from_pkgconfig(self): """Detects the igraph include directory, library directory and the list of libraries to link to using ``pkg-config``.""" if not buildcfg.has_pkgconfig: return False cmd = ["pkg-config", "igraph", "--cflags", "--libs"] if self.static_extension: cmd += ["--static"] line, exit_code = get_output_single_line(cmd) if exit_code > 0 or len(line) == 0: return False opts = line.strip().split() self.libraries = [opt[2:] for opt in opts if opt.startswith("-l")] self.library_dirs = [opt[2:] for opt in opts if opt.startswith("-L")] self.include_dirs = [opt[2:] for opt in opts if opt.startswith("-I")] return True def print_build_info(self): """Prints the include and library path being used for debugging purposes.""" if self.static_extension == "only_igraph": build_type = "dynamic extension with vendored igraph source" elif self.static_extension: build_type = "static extension" else: build_type = "dynamic extension" print("Build type: %s" % build_type) print("Include path: %s" % " ".join(self.include_dirs)) if self.excluded_include_dirs: print(" - excluding: %s" % " ".join(self.excluded_include_dirs)) print("Library path: %s" % " ".join(self.library_dirs)) if self.excluded_library_dirs: print(" - excluding: %s" % " ".join(self.excluded_library_dirs)) print("Runtime library path: %s" % " ".join(self.runtime_library_dirs)) print("Linked dynamic libraries: %s" % " ".join(self.libraries)) print("Linked static libraries: %s" % " ".join(self.extra_objects)) print("Extra compiler options: %s" % " ".join(self.extra_compile_args)) print("Extra linker options: %s" % " ".join(self.extra_link_args)) def process_args_from_command_line(self): """Preprocesses the command line options before they are passed to setup.py and sets up the build configuration.""" # Yes, this is ugly, but we don't want to interfere with setup.py's own # option handling opts_to_remove = [] for idx, option in enumerate(sys.argv): if not option.startswith("--"): continue if option == "--static": opts_to_remove.append(idx) self.static_extension = True elif option == "--no-pkg-config": opts_to_remove.append(idx) self.use_pkgconfig = False elif option == "--no-wait": opts_to_remove.append(idx) self.wait = False elif option == "--use-pkg-config": opts_to_remove.append(idx) self.use_pkgconfig = True for idx in reversed(opts_to_remove): sys.argv[idx : (idx + 1)] = [] def replace_static_libraries(self, only=None, exclusions=None): """Replaces references to libraries with full paths to their static versions if the static version is to be found on the library path.""" building_on_windows = platform.system() == "Windows" if not building_on_windows and "stdc++" not in self.libraries: self.libraries.append("stdc++") if exclusions is None: exclusions = [] for library_name in set(self.libraries) - set(exclusions): if only is not None and library_name not in only: continue static_lib = find_static_library(library_name, self.library_dirs) if static_lib: self.libraries.remove(library_name) self.extra_objects.append(static_lib) def use_vendored_igraph(self): """Assumes that igraph is installed already in ``vendor/install/igraph`` and sets up the include and library paths and the library names accordingly.""" building_on_windows = platform.system() == "Windows" buildcfg.include_dirs = [os.path.join("vendor", "install", "igraph", "include")] buildcfg.library_dirs = [os.path.join("vendor", "install", "igraph", "lib")] if not buildcfg.static_extension: buildcfg.static_extension = "only_igraph" if building_on_windows: buildcfg.define_macros.append(("IGRAPH_STATIC", "1")) buildcfg_file = os.path.join("vendor", "install", "igraph", "build.cfg") if os.path.exists(buildcfg_file): buildcfg.libraries = eval(open(buildcfg_file).read()) def use_educated_guess(self): """Tries to guess the proper library names, include and library paths if everything else failed.""" preprocess_fallback_config() global LIBIGRAPH_FALLBACK_LIBRARIES global LIBIGRAPH_FALLBACK_INCLUDE_DIRS global LIBIGRAPH_FALLBACK_LIBRARY_DIRS print("WARNING: we were not able to detect where igraph is installed on") print("your machine (if it is installed at all). We will use the fallback") print("library and include paths hardcoded in setup.py and hope that the") print("C core of igraph is installed there.") print("") print("If the compilation fails and you are sure that igraph is installed") print("on your machine, adjust the following two variables in setup.py") print("accordingly and try again:") print("") print("- LIBIGRAPH_FALLBACK_INCLUDE_DIRS") print("- LIBIGRAPH_FALLBACK_LIBRARY_DIRS") print("") if self.wait: wait_for_keypress(seconds=10) self.libraries = LIBIGRAPH_FALLBACK_LIBRARIES[:] if self.static_extension: self.libraries.extend(["xml2", "z", "m", "stdc++"]) self.include_dirs = LIBIGRAPH_FALLBACK_INCLUDE_DIRS[:] self.library_dirs = LIBIGRAPH_FALLBACK_LIBRARY_DIRS[:] ########################################################################### # Import version number from version.py so we only need to change it in # one place when a new release is created __version__ = None exec(open("src/igraph/version.py").read()) # Process command line options buildcfg = BuildConfiguration() buildcfg.process_args_from_command_line() # Define the extension sources = glob.glob(os.path.join("src", "_igraph", "*.c")) igraph_extension = Extension("igraph._igraph", sources) description = """Python interface to the igraph high performance graph library, primarily aimed at complex network research and analysis. Graph plotting functionality is provided by the Cairo library, so make sure you install the Python bindings of Cairo if you want to generate publication-quality graph plots. You can try either `pycairo `_ or `cairocffi `_, ``cairocffi`` is recommended, in particular if you are on Python 3.x because there were bug reports affecting igraph graph plots in Jupyter notebooks when using ``pycairo`` (but not with ``cairocffi``). Unofficial installers for 64-bit Windows machines and/or different Python versions can also be found `here `_. Many thanks to the maintainers of this page! """ headers = ["src/_igraph/igraphmodule_api.h"] if not SKIP_HEADER_INSTALL else [] options = dict( name="python-igraph", version=__version__, url="http://pypi.python.org/pypi/python-igraph", description="High performance graph data structures and algorithms", long_description=description, license="GNU General Public License (GPL)", author="Tamas Nepusz", author_email="ntamas@gmail.com", ext_modules=[igraph_extension], package_dir={"igraph": "src/igraph"}, packages=[ "igraph", "igraph.app", "igraph.drawing", "igraph.remote" ], scripts=["scripts/igraph"], install_requires=["texttable>=1.6.2"], headers=headers, platforms="ALL", keywords=[ "graph", "network", "mathematics", "math", "graph theory", "discrete mathematics", ], classifiers=[ "Development Status :: 4 - Beta", "Intended Audience :: Developers", "Intended Audience :: Science/Research", "Operating System :: OS Independent", "Programming Language :: C", "Programming Language :: Python", "Topic :: Scientific/Engineering", "Topic :: Scientific/Engineering :: Information Analysis", "Topic :: Scientific/Engineering :: Mathematics", "Topic :: Scientific/Engineering :: Physics", "Topic :: Scientific/Engineering :: Bio-Informatics", "Topic :: Software Development :: Libraries :: Python Modules", ], cmdclass={ "build_c_core": buildcfg.build_c_core, # used by CI "build_ext": buildcfg.build_ext, "sdist": buildcfg.sdist }, ) if sys.version_info > (3, 0): options["use_2to3"] = True setup(**options) python-igraph-0.8.0/scripts/0000755000076500000240000000000013617375000016231 5ustar tamasstaff00000000000000python-igraph-0.8.0/scripts/igraph0000755000076500000240000000017713104627150017433 0ustar tamasstaff00000000000000#!/usr/bin/env python """Small script to execute the igraph command line interface""" from igraph.app.shell import main main() python-igraph-0.8.0/scripts/epydoc.cfg0000644000076500000240000000031113104627150020165 0ustar tamasstaff00000000000000[epydoc] name: igraph library url: http://igraph.org modules: igraph, igraph.app, igraph.app.shell, igraph.statistics exclude: igraph.compat, igraph.formula, igraph.test, igraph.vendor imports: yes python-igraph-0.8.0/scripts/mkdoc.sh0000755000076500000240000000226113610155006017661 0ustar tamasstaff00000000000000#!/bin/sh # # Creates documentation for igraph's Python interface using epydoc # # Usage: ./mkdoc.sh [--sync] [directory] SCRIPTS_FOLDER=`dirname $0` cd ${SCRIPTS_FOLDER}/.. ROOT_FOLDER=`pwd` DOC_API_FOLDER=${ROOT_FOLDER}/doc/api CONFIG=${ROOT_FOLDER}/scripts/epydoc.cfg cd ${ROOT_FOLDER} mkdir -p ${DOC_API_FOLDER}/pdf mkdir -p ${DOC_API_FOLDER}/html EPYDOC="${ROOT_FOLDER}/scripts/epydoc-patched" python -m epydoc.__init__ if [ $? -gt 0 ]; then echo "Epydoc not installed, exiting..." exit 1 fi PWD=`pwd` echo "Checking symlinked _igraph.so in ${ROOT_FOLDER}/src/igraph..." if [ ! -e ${ROOT_FOLDER}/src/igraph/_igraph.so -o ! -L ${ROOT_FOLDER}/src/igraph/_igraph.so ]; then rm -f ${ROOT_FOLDER}/src/igraph/_igraph.so cd ${ROOT_FOLDER}/src/igraph ln -s ../../build/lib*/igraph/_igraph.so . cd ${ROOT_FOLDER} fi echo "Removing existing documentation..." rm -rf html echo "Generating HTML documentation..." PYTHONPATH=src ${EPYDOC} --html -v -o ${DOC_API_FOLDER}/html --config ${CONFIG} PDF=0 which latex >/dev/null && PDF=1 if [ $PDF -eq 1 ]; then echo "Generating PDF documentation..." PYTHONPATH=src ${EPYDOC} --pdf -v -o ${DOC_API_FOLDER}/pdf --config ${CONFIG} fi cd "$PWD" python-igraph-0.8.0/scripts/epydoc-patched0000755000076500000240000000112613104627150021045 0ustar tamasstaff00000000000000#!/usr/bin/env python """Patched version of Epydoc that does not blow up with `docutils` newer than 0.6 when reST is used as a markup language""" from epydoc.cli import cli from epydoc.markup.restructuredtext import parse_docstring from epydoc.docwriter.latex import LatexWriter # Check whether Epydoc needs patching doc = parse_docstring("aaa", []) try: doc.summary() except AttributeError: # Monkey-patching docutils so that Text nodes have a "data" property, # which is always empty from docutils.nodes import Text Text.data="" LatexWriter.PREAMBLE += [r'\usepackage[T1]{fontenc}'] cli()python-igraph-0.8.0/setup.cfg0000644000076500000240000000004613617375001016364 0ustar tamasstaff00000000000000[egg_info] tag_build = tag_date = 0 python-igraph-0.8.0/python_igraph.egg-info/0000755000076500000240000000000013617375000021107 5ustar tamasstaff00000000000000python-igraph-0.8.0/python_igraph.egg-info/PKG-INFO0000644000076500000240000000360413617375000022207 0ustar tamasstaff00000000000000Metadata-Version: 1.1 Name: python-igraph Version: 0.8.0 Summary: High performance graph data structures and algorithms Home-page: http://pypi.python.org/pypi/python-igraph Author: Tamas Nepusz Author-email: ntamas@gmail.com License: GNU General Public License (GPL) Description: Python interface to the igraph high performance graph library, primarily aimed at complex network research and analysis. Graph plotting functionality is provided by the Cairo library, so make sure you install the Python bindings of Cairo if you want to generate publication-quality graph plots. You can try either `pycairo `_ or `cairocffi `_, ``cairocffi`` is recommended, in particular if you are on Python 3.x because there were bug reports affecting igraph graph plots in Jupyter notebooks when using ``pycairo`` (but not with ``cairocffi``). Unofficial installers for 64-bit Windows machines and/or different Python versions can also be found `here `_. Many thanks to the maintainers of this page! Keywords: graph,network,mathematics,math,graph theory,discrete mathematics Platform: ALL Classifier: Development Status :: 4 - Beta Classifier: Intended Audience :: Developers Classifier: Intended Audience :: Science/Research Classifier: Operating System :: OS Independent Classifier: Programming Language :: C Classifier: Programming Language :: Python Classifier: Topic :: Scientific/Engineering Classifier: Topic :: Scientific/Engineering :: Information Analysis Classifier: Topic :: Scientific/Engineering :: Mathematics Classifier: Topic :: Scientific/Engineering :: Physics Classifier: Topic :: Scientific/Engineering :: Bio-Informatics Classifier: Topic :: Software Development :: Libraries :: Python Modules python-igraph-0.8.0/python_igraph.egg-info/SOURCES.txt0000644000076500000240000024134313617375000023002 0ustar tamasstaff00000000000000COPYING MANIFEST.in README.md setup.py python_igraph.egg-info/PKG-INFO python_igraph.egg-info/SOURCES.txt python_igraph.egg-info/dependency_links.txt python_igraph.egg-info/requires.txt python_igraph.egg-info/top_level.txt scripts/epydoc-patched scripts/epydoc.cfg scripts/igraph scripts/mkdoc.sh src/_igraph/arpackobject.c src/_igraph/arpackobject.h src/_igraph/attributes.c src/_igraph/attributes.h src/_igraph/bfsiter.c src/_igraph/bfsiter.h src/_igraph/common.c src/_igraph/common.h src/_igraph/convert.c src/_igraph/convert.h src/_igraph/edgeobject.c src/_igraph/edgeobject.h src/_igraph/edgeseqobject.c src/_igraph/edgeseqobject.h src/_igraph/error.c src/_igraph/error.h src/_igraph/filehandle.c src/_igraph/filehandle.h src/_igraph/graphobject.c src/_igraph/graphobject.h src/_igraph/igraphmodule.c src/_igraph/igraphmodule_api.h src/_igraph/indexing.c src/_igraph/indexing.h src/_igraph/platform.h src/_igraph/py2compat.c src/_igraph/py2compat.h src/_igraph/pyhelpers.c src/_igraph/pyhelpers.h src/_igraph/random.c src/_igraph/random.h src/_igraph/vertexobject.c src/_igraph/vertexobject.h src/_igraph/vertexseqobject.c 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tamasstaff00000000000000python-igraph-0.8.0/vendor/source/0000755000076500000240000000000013617375000017337 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/0000755000076500000240000000000013617375000020611 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/igraph.pc.in0000644000076500000240000000045213524616144023021 0ustar tamasstaff00000000000000prefix=@prefix@ exec_prefix=@exec_prefix@ libdir=@libdir@ includedir=@includedir@ Name: libigraph Description: A library for creating and manipulating graphs Version: @VERSION@ URL: http://igraph.org Libs: -L${libdir} -ligraph Libs.private: @PKGCONFIG_LIBS_PRIVATE@ Cflags: -I${includedir}/igraph python-igraph-0.8.0/vendor/source/igraph/configure.ac0000644000076500000240000003124513614300625023102 0ustar tamasstaff00000000000000AC_INIT(igraph, esyscmd([tr -d '\n' < IGRAPH_VERSION]), igraph@igraph.org) AC_CONFIG_MACRO_DIR([m4]) AC_CONFIG_SRCDIR(src/games.c) AM_INIT_AUTOMAKE([foreign subdir-objects]) 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then CFLAGS="${CFLAGS} -ggdb -O0" CPPFLAGS="${CPPFLAGS} -DRC_DEBUG" CXXFLAGS="${CXXFLAGS} -ggdb -O0" fi if test "$use_gprof" = "yes"; then CFLAGS="${CFLAGS} -pg" CXXFLAGS="${CXXFLAGS} -pg" fi if test "$use_asan" = "yes"; then CFLAGS="${CFLAGS} -g -fsanitize=address -fno-omit-frame-pointer" CXXFLAGS="${CXXFLAGS} -g -fsanitize=address -fno-omit-frame-pointer" fi if test "$use_asan" != "yes" -a "$use_gprof" != "yes" -a "$debug" != "yes"; then CFLAGS="${CFLAGS} -O3" CPPFLAGS="${CPPFLAGS} -O3" CXXFLAGS="${CXXFLAGS} -O3" fi AC_CONFIG_FILES([Makefile src/Makefile igraph.pc igraph_Info.plist doc/Makefile include/igraph_version.h include/igraph_threading.h]) AC_OUTPUT AC_MSG_RESULT([igraph successfully configured.]) AC_MSG_RESULT([ GraphML format support -- $graphml_support]) AC_MSG_RESULT([ GMP library support -- $gmp_support]) AC_MSG_RESULT([ GLPK library support -- $glpk_support]) AC_MSG_RESULT([ Thread-local storage -- $tls_support]) AC_MSG_RESULT([ Use internal ARPACK -- $internal_arpack]) AC_MSG_RESULT([ Use internal LAPACK -- $internal_lapack]) AC_MSG_RESULT([ Use internal BLAS -- $internal_blas]) if test "$needs_f2c" != "yes"; then AC_MSG_RESULT([ Use internal F2C -- f2c not needed]) else AC_MSG_RESULT([ Use internal F2C -- $internal_f2c]) fi if test "$glpk_support" != "no"; then AC_MSG_RESULT([ Use internal GLPK -- $internal_glpk]) fi AC_MSG_RESULT([ Debug build -- $debug]) AC_MSG_RESULT([ Clang AddressSanitizer -- $use_asan]) AC_MSG_RESULT([ Profiling -- $use_gprof]) python-igraph-0.8.0/vendor/source/igraph/tools/0000755000076500000240000000000013617375001021752 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/tools/seqdict/0000755000076500000240000000000013617375001023406 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/tools/seqdict/mdict.py0000644000076500000240000001437413524616145025075 0ustar tamasstaff00000000000000################################################################################ # Sequential Dictionary Class # # # # by Wolfgang Grafen # # # # Version 0.2 11. February 2004 # # # email to: WolfgangGrafen@gmx.de # # # ################################################################################ from ndict import seqdict #Sequential Single Value Dictionary from UserList import UserList class MyUserList(UserList): from UserList import UserList def __init__(self,parent,liste=None): UserList.__init__(self,liste) self.parent = parent #remember parent for call-back def __delitem__(self, i): del self.data[i] if self.data==[]: #call-back, deletes item of parent index = self.parent.values().index([]) del self.parent[index:index+1] class mseqdict(seqdict): #Sequential Multiple Value Dictionary def __init__(self,List=[],Dict={}): self.list = [] self.dict = {} if not List: pass elif type(List)==type({}): for key,value in List.items(): self.__setitem__(key,value) elif List and not Dict: #dict.items() for key,value in List: if isinstance(value,MyUserList): for v in value: self.__setitem__(key,v) else: self.__setitem__(key,value) elif type(List)==type(Dict)==type([]): for key,value in map(None,List,Dict): self.__setitem__(key,value) else: if isinstance(Dict.values()[0],MyUserList): self.dict = Dict self.list = List else: for key in List: value = Dict[key] if type(value)==type([]): for v in value: self.__setitem__(key,v) else: self.__setitem__(key,value) self_list = self.list self_dict = self.dict for k in self_list: assert self_dict.has_key(k),"key %r not in self.dict" % k for k in self_dict.keys(): if k not in self_list: self_list.append(k) def __setitem__(self,key,value): if not self.dict.has_key(key): self.list.append(key) if isinstance(value,MyUserList): self.dict[key] = value else: self.dict[key]=MyUserList(self,[value]) else: values = self.dict[key] if isinstance(value,MyUserList): for v in value: if not v in values: values.extend(MyUserList(self,[v])) else: #if not value in values: for v in values: if v is value: break values.extend(MyUserList(self,[value])) def __delitem__(self, key): del self.dict[key] self.list.remove(key) def append(self,key,value): self.__setitem__(key,value) def __setslice__(self,start,stop,newdict): start = max(start,0); stop = max(stop,0) delindexes = [] for key in newdict.keys(): if self.dict.has_key(key): index = self.list.index(key) delindexes.append(index) if index < start: start = start - 1 stop = stop - 1 elif index >= stop: pass else: stop = stop - 1 else: self.dict[key]=UserList(self) delindexes.sort() delindexes.reverse() for index in delindexes: key = self.list[index] #del self.dict[key] del self.list[index] self.list[start:stop] = newdict.list[:] self.dict.update(newdict.dict) def copy(self): values = map(lambda x:x[:],self.values()) return self.__class__(self.list,values) def count(self,value): vallist = self.dict.values() return map(lambda x,y=value:x.count(y),vallist).count(1) def filter(self,function,filtervalues=0): if filtervalues == 1: #consider key and all keyvalues at once dict = self.__class__() for key,values in self.items(): if function(key,values): dict[key]=values return dict elif filtervalues == 2: #consider key and every keyvalue for itself dict = self.__class__() for key,values in self.items(): for value in values: if function(key,value): dict[key]=value return dict else: #consider key only liste=filter(function,self.list) dict = {} for i in liste: dict[i]=self.dict[i] return self.__class__(liste,dict) def map(self,function,mapvalues=2): if mapvalues == 1: #consider key and all keyvalues at once dict = self.__class__() for key,values in self.items(): k,v = function(key,values) dict[k]=v return dict else: #if mapvalues!=1: #consider key and every keyvalue for itself dict = self.__class__() for key,values in self.items(): for value in values: k,v = function(key,value) dict[k]=v return dict def pop(self,key='...None',value='...None'): if value=='...None': if key=='...None': pos = -1 key = self.list[pos] else: pos = self.list.index(key) tmp = self.dict[key] del self.dict[key] return {self.list.pop(pos):tmp} else: val = self.dict[key] index = val.index(value) tmp = val[index] del val[index] return {key:tmp} def remove(self,key,value='...None'): if value=='...None': del self[key] else: index = self[key].index(value) del self[key][index] def sort(self,func1=None,func2=None): if not func1: self.list.sort() else: apply(self.list.sort,[func1]) if func2: for value in self.values(): apply(value.sort,[func2]) def swap(self): tmp = self.__class__() for key,values in self.items(): for value in values: tmp[value]=key self.list,self.dict = tmp.list,tmp.dict del tmp def __repr__(self):return 'mseqdict(\n%s,\n%s)'%(self.list,self.dict) python-igraph-0.8.0/vendor/source/igraph/tools/seqdict/__init__.py0000644000076500000240000000006513524616145025524 0ustar tamasstaff00000000000000from ndict import seqdict from mdict import mseqdict python-igraph-0.8.0/vendor/source/igraph/tools/seqdict/ndict.py0000644000076500000240000001660713524616145025077 0ustar tamasstaff00000000000000################################################################################ # Sequential Dictionary Class # # # # by Wolfgang Grafen # # # # Version 0.2 11. February 2004 # # # email to: WolfgangGrafen@gmx.de # # # ################################################################################ # History # Version 0.2 11. February 2004 # # - Fixed slicing problem: # #>>> s = seqdict.seqdict(['b'], {'b': 'b'}) #>>> s[0:0] = seqdict.seqdict(['a'], {'a': 'a'}) # >>> s #seqdict( #['a', 'b'], #was ['a', 'b', 'a'], #{'a': 'a', 'b': 'b'}) # # - Initialisation is now correct for: # a) Not all keys of dict given in list: #>>> seqdict(["a","b","c","d","b","a",],{"a":1,"b":2,"d":4,"c":3,"h":66,"j":77}) #seqdict( #['c', 'd', 'b', 'a', 'h', 'j'], #{'a': 1, 'c': 3, 'b': 2, 'd': 4, 'h': 66, 'j': 77}) # # b) exceeding key "p" in list: #>>> seqdict(["a","b","c","d","b","a","p"],{"a":1,"b":2,"d":4,"c":3}) #Traceback (most recent call last): # File "", line 1, in ? # File "seqdict/hide/ndict.py", line 53, in __init__ # assert self.dict.has_key(k),"key %r not in self.dict" % k #AssertionError: key 'p' not in self.dict # # Version 0.1 24. Oct 2002 # - Bugfix seqdict(["a","b","c"],[1,2,3]) evaluated into # seqdict( ['a', 'b', 'd', 'c', 'd'], {'d': 4, 'b': 2, 'c': 3, 'a': 1}) # # Version 0.0 29. June 1999 def is_dict(whatever): try: whatever.keys() return 1 except: return 0 class seqdict: def __init__(self,List=[],Dict={}): if is_dict(List): self.list = List.keys() self.dict = List.copy() elif List and not Dict: self.list=[] self.dict={} for i,j in List: self.list.append(i) self.dict[i]=j elif type(List)==type(Dict)==type([]): self.list = List self.dict = {} for key,value in map(None,List,Dict): self.dict[key] = value else: lcopy = List[:] lcopy.reverse() lnew = [] for l in lcopy: if not l in lnew: lnew.append(l) lnew.reverse() self.list,self.dict = lnew,Dict.copy() self_list = self.list self_dict = self.dict for k in self_list: assert self_dict.has_key(k),"key %r not in self.dict" % k for k in self_dict.keys(): if k not in self_list: self_list.append(k) def append(self,key,value): if self.dict.has_key(key): self.list.remove(key) self.list.append(key) self.dict[key]=value def check(self): if len(self.dict)==len(self.list): l1=self.list[:];l1.sort() l2=self.dict.keys();l2.sort() return l1==l2 return -1 def clear(self): self.list=[];self.dict={} def copy(self): if self.__class__ is seqdict: return self.__class__(self.list,self.dict) import copy return copy.copy(self) def __cmp__(self,other): return cmp(self.dict,other.dict) or cmp(self.list,other.list) def __getitem__(self,key): if type(key)==type([]): newdict={} for i in key: newdict[i]=self.dict[i] return self.__class__(key,newdict) return self.dict[key] def __setitem__(self,key,value): if not self.dict.has_key(key): self.list.append(key) self.dict[key]=value def __delitem__(self, key): del self.dict[key] self.list.remove(key) def __getslice__(self,start,stop): start = max(start,0); stop = max(stop,0) newdict = self.__class__() for key in self.list[start:stop]: newdict.dict[key]=self.dict[key] newdict.list[:]=self.list[start:stop] return newdict def __setslice__(self,start,stop,newdict): start = max(start,0); stop = max(stop,0) delindexes = [] for key in newdict.keys(): if self.dict.has_key(key): index = self.list.index(key) delindexes.append(index) if index < start: start = start - 1 stop = stop - 1 elif index >= stop: pass else: stop = stop - 1 delindexes.sort() delindexes.reverse() for index in delindexes: key = self.list[index] del self.dict[key] del self.list[index] for key in self.list[start:stop]: del self.dict[key] self.list[start:stop] = newdict.list[:] self.dict.update(newdict.dict) def __delslice__(self, start, stop): start = max(start, 0); stop = max(stop, 0) for key in self.list[start:stop]: del self.dict[key] del self.list[start:stop] def __add__(self,other): newdict = self.__class__() for key,value in self.items()+other.items(): newdict.append(key,value) return newdict def __radd__(self,other): newdict = self.__class__() for key,value in other.items()+self.items(): newdict.append(key,value) return newdict def count(self,value): vallist = self.dict.values() return vallist.count(value) def extend(self,other): self.update(other) def filter(self,function): liste=filter(function,self.list) dict = {} for i in liste: dict[i]=self.dict[i] return self.__class__(liste,dict) def get(self, key, failobj=None): return self.dict.get(key, failobj) def index(self,key):return self.list.index(key) def insert(self,i,x):self.__setslice__(i,i,x) def items(self):return map(None,self.list,self.values()) def has_key(self,key):return self.dict.has_key(key) def keys(self):return self.list def map(self,function): return self.__class__(map(function,self.items())) def values(self): nlist = [] for key in self.list: nlist.append(self.dict[key]) return nlist def __len__(self):return len(self.list) def pop(self,key=None): if key==None: pos = -1 key = self.list[pos] else: pos = self.list.index(key) tmp = self.dict[key] del self.dict[key] return {self.list.pop(pos):tmp} def push(self,key,value): self.append(key,value) def reduce(self,function,start=None): return reduce(function,self.items(),start) def remove(self,key): del self.dict[key] self.list.remove(key) def reverse(self):self.list.reverse() def sort(self,*args):apply(self.list.sort,args) def split(self,function,Ignore=None): splitdict = seqdict() #self.__class__() for key in self.list: skey = function(key) if skey != Ignore: if not splitdict.has_key(skey): splitdict[skey] = self.__class__() splitdict[skey][key] = self.dict[key] return splitdict def swap(self): tmp = self.__class__(map(lambda (x,y):(y,x),self.items())) self.list,self.dict = tmp.list,tmp.dict def update(self,newdict): for key,value in newdict.items(): self.__setitem__(key,value) def slice(self,From,To=None,Step=1): From = self.list.index(From) if To:To = self.list.index(To) else : To = From + 1 List = range(From,To,Step) def getitem(pos,self=self):return self.list[pos] return self.__getitem__(map(getitem,List)) def __repr__(self):return 'seqdict(\n%s,\n%s)'%(self.list,self.dict) python-igraph-0.8.0/vendor/source/igraph/tools/bump_version.sh0000755000076500000240000000372113524616145025030 0ustar tamasstaff00000000000000#!/bin/sh # # Script that should be run whenever we bump the version number of # igraph. # # This script adjusts the version numbers in the following files: # # - configure.in # - interfaces/java/build.xml # - interfaces/R/configure.in # - examples/simple/gml.out # - examples/simple/cattributes2.out # - msvc/igraphtest/igraphtest.vcproj # - tools/launchpad_nightly.recipe # - debian/changelog set -e set -u if [ $# -lt 1 ]; then echo "Usage: $0 version" exit 1 fi VERSION="$1" # Step to the root of the source tree cd `dirname $0`/.. # Adjust configure.in sed -e "s/AC_INIT(igraph, [^,]*,/AC_INIT(igraph, ${VERSION},/" \ -e "s/AM_INIT_AUTOMAKE(igraph, [^)]*)/AM_INIT_AUTOMAKE(igraph, ${VERSION})/" \ -i configure.in # Adjust interfaces/java/build.xml sed -e "s/property name=\"package\.version\" value=\"[^\"]*\"/property name=\"package.version\" value=\"${VERSION}\"/" \ -i interfaces/java/build.xml # Adjust interfaces/R/configure.in sed -e "s/AC_INIT(igraph, [^,]*,/AC_INIT(igraph, ${VERSION},/" \ -i configure.in # Adjust examples/simple/gml.out sed -e "s/igraph version [^ ]*/igraph version ${VERSION}/" \ -i examples/simple/gml.out # Adjust examples/simple/cattributes2.out sed -e "s/igraph version [^ ]*/igraph version ${VERSION}/" \ -i examples/simple/cattributes2.out # Adjust msvc/igraphtest/igraphtest.vcproj sed -e "s/igraph-[^-]*-msvc/igraph-${VERSION}-msvc/g" \ -i msvc/igraphtest/igraphtest.vcproj # Adjust tools/launchpad_nightly.recipe sed -e "s/deb-version [^~]*/deb-version ${VERSION}/" \ -e "s|lp:igraph/[^-]*-main|lp:igraph/${VERSION}-main|" \ -i tools/launchpad_nightly.recipe # Adjust debian/changelog DATE="`date -R`" cat >debian/changelog.new < ${DATE} EOF cat debian/changelog >>debian/changelog.new mv debian/changelog.new debian/changelog # Done. echo "Successfully bumped version number to ${VERSION}." python-igraph-0.8.0/vendor/source/igraph/tools/NEXT_VERSION0000644000076500000240000000000613524616145023660 0ustar tamasstaff000000000000000.8.0 python-igraph-0.8.0/vendor/source/igraph/tools/lapack/0000755000076500000240000000000013617375001023205 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/tools/lapack/getlapack.sh0000755000076500000240000001016213524616145025503 0ustar tamasstaff00000000000000#! /bin/sh # # ./getlapack.sh dgeev dsyevr dnaupd dneupd dsaupd dseupd dgemv dgeevx \ # dgetrf dgetrs dgesv dlapy2 dpotrf dsyrk dtrsv # make origdir=`pwd` destdir=lapack-new cd /tmp rm -rf $destdir mkdir $destdir ## Download and unpack BLAS if test ! -f blas.tgz; then curl -O http://www.netlib.org/blas/blas.tgz fi blasdir=`tar tzf blas.tgz | head -1 | cut -f1 -d"/"` rm -rf ${blasdir} tar xzf blas.tgz ## Download, unpack and patch LAPACK if test ! -f lapack.tgz; then curl -O http://www.netlib.org/lapack/lapack.tgz fi lapackdir=`tar tzf lapack.tgz | head -1 | cut -f1 -d"/"` rm -rf ${lapackdir} tar xzf lapack.tgz cd /tmp/${lapackdir} patch -p 1 <${origdir}/lapack.patch cd /tmp ## Download and unpack ARPACK if test ! -f arpack96.tar.gz; then curl -O http://www.caam.rice.edu/software/ARPACK/SRC/arpack96.tar.gz fi arpackdir=`tar tzf arpack96.tar.gz | head -1 | cut -f1 -d"/"` rm -rf ${arpackdir} tar xzf arpack96.tar.gz alreadydone=() lapack=() arpack=() blas=() known() { needle=$1 res=0 for i in ${alreadydone[@]}; do if [[ $i == ${needle} ]]; then return 0 fi done return 1 } getdeps() { name=$1; f2c -a ${name}.f >/dev/null 2>/dev/null && gcc -c ${name}.c >/dev/null && nm ${name}.o | grep " U " | awk ' { print $2 }' | sed 's/_$//g' | sed 's/^_//g' } dofunction() { name=$1; if known $name; then return 0; fi if test -f /tmp/${arpackdir}/SRC/${name}.f; then cd /tmp/${arpackdir}/SRC arpack[$[${#arpack[@]}+1]]=$name elif test -f /tmp/${lapackdir}/SRC/${name}.f; then cd /tmp/${lapackdir}/SRC lapack[$[${#lapack[@]}+1]]=$name elif test -f /tmp/${blasdir}/${name}.f; then cd /tmp/${blasdir} blas[$[${#blas[@]}+1]]=$name elif test -f /tmp/${arpackdir}/UTIL/${name}.f; then cd /tmp/${arpackdir}/UTIL arpack[$[${#arpack[@]}+1]]=$name elif test -f /tmp/${lapackdir}/INSTALL/${name}.f; then cd /tmp/${lapackdir}/INSTALL lapack[$[${#lapack[@]}+1]]=$name elif test -f ${origdir}/extra/${name}.f; then cd ${origdir}/extra lapack[$[${#lapack[@]}+1]]=$name else return fi cp ${name}.f /tmp/${destdir} alreadydone[$[${#alreadydone[@]}+1]]=$name deps=`getdeps $name` for i in $deps; do dofunction $i done } if test "$#" -eq "0"; then exit 0 fi ## Collect and copy the needed files for i in "$@"; do dofunction $i done ## Some more required files dofunction second dofunction dvout dofunction ivout dofunction dmout dofunction dlamch dofunction len_trim ## Polish them cd /tmp/${destdir} touch debug.h touch stat.h trans_dir=${origdir} ${origdir}/CompletePolish *.f ## Remove the .f files. cd /tmp/${destdir} rm -f *.f ## Prefix the function calls with 'igraph', this is needed ## if the user wants to link igraph including internal BLAS/LAPACK/ARPACK ## and BLAS/LAPACK/ARPACK for some reason extrafunctions=(dlamc1 dlamc2 dlamc3 dlamc4 dlamc5) for name in ${alreadydone[@]} ${extrafunctions[@]}; do echo "s/${name}_/igraph${name}_/g" done > /tmp/lapack-sed.txt for name in ${alreadydone[@]}; do sed -f /tmp/lapack-sed.txt < ${name}.c >/tmp/arpackfun.c cp /tmp/arpackfun.c ${name}.c done ## Update the file that is included into the main Makefile, ## this contains the ARPACK/LAPACK/BLAS source files blasinc=/tmp/${destdir}/blas.inc /bin/echo -n "BLAS = " > ${blasinc} for name in ${blas[@]}; do /bin/echo -n "lapack/${name}.c " done >> ${blasinc} /bin/echo >> ${blasinc} lapackinc=/tmp/${destdir}/lapack.inc /bin/echo -n "LAPACK = " > ${lapackinc} for name in ${lapack[@]}; do /bin/echo -n "lapack/${name}.c " done | sed 's/lapack\/dlamch\.c//' >> ${lapackinc} /bin/echo >> ${lapackinc} arpackinc=/tmp/${destdir}/arpack.inc /bin/echo -n "ARPACK = " > ${arpackinc} for name in ${arpack[@]}; do /bin/echo -n "lapack/${name}.c " done >> ${arpackinc} /bin/echo >> ${arpackinc} ## This is a patch to make ARPACK thread-safe cd /tmp/${destdir} patch -p2 < ${origdir}/mt.patch ## We are done echo "Sources are ready, to update your tree please run: bzr rm ${origdir}/../../src/lapack mv /tmp/${destdir} ${origdir}/../../src/lapack bzr add ${origdir}/../../src/lapack " python-igraph-0.8.0/vendor/source/igraph/tools/lapack/Makefile0000644000076500000240000000045713524616145024657 0ustar tamasstaff00000000000000LOADLIBS = -ly -lfl -lm LIBS = -lfl -lm CFLAGS = -O all: lenscrub comment lenscrub: lenscrub.l lex lenscrub.l mv -f lex.yy.c lex_for_lenscrub.c cc -o lenscrub -O lex_for_lenscrub.c -ll comment: comment.l lex comment.l mv -f lex.yy.c lex_for_comment.c cc -o comment -O lex_for_comment.c -ll python-igraph-0.8.0/vendor/source/igraph/tools/lapack/lenscrub.l0000644000076500000240000000253613524616145025211 0ustar tamasstaff00000000000000/* {definitions} */ iofun "("[^;\{]*[;\{] decl "("[^)]*")"[,;] any [.]* S [ \t\n]* cS ","{S} len [a-z][a-z0-9]*_len %% "s_stop"{decl} | "do_fio"{decl} | "s_cat"{iofun} | "s_copy"{iofun} | "s_stop"{iofun} | "s_cmp"{iofun} | "i_len"{iofun} | "len_trim__"{iofun} | "do_fio"{iofun} | "do_lio"{iofun} { printf("%s", yytext); /* unchanged */ } {any}"ilaenv_(" | "dvout_(" | "dmout_(" | "ivout_(" | "xerbla_(" | [a-z]"tim"[a-z0-9]*"_(" | [a-z]"prtb"[a-z0-9]"_(" { register int c, paran_count = 1; printf("%s", yytext); /* unchanged */ /* Loop until the correct closing paranthesis */ while (paran_count != 0) { c = input(); if (c == '(') ++paran_count; else if (c == ')') --paran_count; putchar(c); } } {cS}"("{S}ftnlen{S}")"{S}[1-9][0-9]* { ; /* omit -- f2c -A */ } {cS}[1-9]([0-9])*L { ; /* omit */ } {cS}ftnlen({S}{len})? { ; /* omit -- f2c -A */ } ^ftnlen" "{len}";\n" { ; /* omit -- f2c without -A or -C++ */ } {cS}{len} { ; } . { printf("%s", yytext); /* unchanged */ } python-igraph-0.8.0/vendor/source/igraph/tools/lapack/delete.sed0000644000076500000240000000012013524616145025141 0ustar tamasstaff00000000000000# delete the line of the form .. Scalar arguments .. /\/\* *\.\. .*\*\//{ d } python-igraph-0.8.0/vendor/source/igraph/tools/lapack/CompletePolish0000755000076500000240000000220213524616145026062 0ustar tamasstaff00000000000000#!/bin/sh - # call this Unix script "MagicScript" # To use: MagicScript *.f # that translates *.f to *.c and polish the resulting C code from f2c. # # Note: define trans_dir as the directory that contains this file. # # trans_dir=/home/barad-dur/jwd/users/mercedes-tmp/LAPACK_v2.0/LAPACK_Final_Release2.0/NEW_CLAPACK/CLAPACK/Translate rm -f -r temp mkdir temp for file do base=`echo $file | sed -e 's/\.f//g'` # run_stripper f2c -a < ${base}.f | ${trans_dir}/lenscrub > ${base}.c # run_macro (better vector and array indexing; from NAG) # ${trans_dir}/substitute_locals.exe < ${base}.c > ${base}.u # ${trans_dir}/test_tool.exe ${base}.u > ${base}.c # rm -f ${base}.u # run_comment sed -f ${trans_dir}/delete.sed ${base}.c > ${base}.t mv -f ${base}.t ${base}.c ${trans_dir}/comment < ${base}.c > ${base}.t mv -f ${base}.t ${base}.c # run_splitter # sed -n -f ${trans_dir}/split.sed ${base}.c # mv -f ${base}.c ${base}.t # cat temp/header1 temp/header3 temp/comment temp/header2 temp/prologue \ # temp/code > ${base}.c # rm -f ${base}.t done rm -f -r temp python-igraph-0.8.0/vendor/source/igraph/tools/lapack/extra/0000755000076500000240000000000013617375001024330 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/tools/lapack/extra/len_trim.f0000644000076500000240000000041613524616145026315 0ustar tamasstaff00000000000000* * -- LEN_TRIM is Fortran 95, so we use a replacement here * FUNCTION LEN_TRIM(S) * CHARACTER*(*) S INTEGER LEN_TRIM * INTRINSIC LEN * DO LEN_TRIM = LEN(S), 1, -1 IF (s(LEN_TRIM:LEN_TRIM) .NE. ' ') RETURN END DO END python-igraph-0.8.0/vendor/source/igraph/tools/lapack/mt.patch0000644000076500000240000004443113524616145024660 0ustar tamasstaff00000000000000=== modified file 'src/lapack/dgetv0.c' --- src/lapack/dgetv0.c 2011-11-02 20:55:12 +0000 +++ src/lapack/dgetv0.c 2011-11-03 13:12:52 +0000 @@ -144,7 +144,7 @@ { /* Initialized data */ - static logical inits = TRUE_; + IGRAPH_F77_SAVE logical inits = TRUE_; /* System generated locals */ integer v_dim1, v_offset, i__1; @@ -157,29 +157,29 @@ integer jj, nbx; extern doublereal igraphddot_(integer *, doublereal *, integer *, doublereal *, integer *); - static integer iter; - static logical orth; + IGRAPH_F77_SAVE integer iter; + IGRAPH_F77_SAVE logical orth; integer nopx; extern doublereal igraphdnrm2_(integer *, doublereal *, integer *); - static integer iseed[4]; + IGRAPH_F77_SAVE integer iseed[4]; extern /* Subroutine */ int igraphdgemv_(char *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *); integer idist; extern /* Subroutine */ int igraphdcopy_(integer *, doublereal *, integer *, doublereal *, integer *); - static logical first; + IGRAPH_F77_SAVE logical first; real tmvbx; extern /* Subroutine */ int igraphdvout_(integer *, integer *, doublereal *, integer *, char *, ftnlen); integer mgetv0=0; real tgetv0; - static doublereal rnorm0; + IGRAPH_F77_SAVE doublereal rnorm0; extern /* Subroutine */ int igraphsecond_(real *); integer logfil=0, ndigit; extern /* Subroutine */ int igraphdlarnv_(integer *, integer *, integer *, doublereal *); - static integer msglvl; + IGRAPH_F77_SAVE integer msglvl; real tmvopx; === modified file 'src/lapack/dlaln2.c' --- src/lapack/dlaln2.c 2011-11-02 20:55:12 +0000 +++ src/lapack/dlaln2.c 2011-11-03 13:47:19 +0000 @@ -28,7 +28,7 @@ /* System generated locals */ integer a_dim1, a_offset, b_dim1, b_offset, x_dim1, x_offset; doublereal d__1, d__2, d__3, d__4, d__5, d__6; - static doublereal equiv_0[4], equiv_1[4]; + IGRAPH_F77_SAVE doublereal equiv_0[4], equiv_1[4]; /* Local variables */ integer j; === modified file 'src/lapack/dnaitr.c' --- src/lapack/dnaitr.c 2011-11-02 20:55:12 +0000 +++ src/lapack/dnaitr.c 2011-11-03 13:12:52 +0000 @@ -236,7 +236,7 @@ { /* Initialized data */ - static logical first = TRUE_; + IGRAPH_F77_SAVE logical first = TRUE_; /* System generated locals */ integer h_dim1, h_offset, v_dim1, v_offset, i__1, i__2; @@ -247,24 +247,24 @@ /* Local variables */ integer i__; - static integer j; + IGRAPH_F77_SAVE integer j; real t0, t1, t2, t3, t4, t5; integer jj; - static integer ipj, irj; + IGRAPH_F77_SAVE integer ipj, irj; integer nbx; - static integer ivj; - static doublereal ulp; + IGRAPH_F77_SAVE integer ivj; + IGRAPH_F77_SAVE doublereal ulp; doublereal tst1; extern doublereal igraphddot_(integer *, doublereal *, integer *, doublereal *, integer *); - static integer ierr, iter; - static doublereal unfl, ovfl; + IGRAPH_F77_SAVE integer ierr, iter; + IGRAPH_F77_SAVE doublereal unfl, ovfl; integer nopx; - static integer itry; + IGRAPH_F77_SAVE integer itry; extern doublereal igraphdnrm2_(integer *, doublereal *, integer *); doublereal temp1; - static logical orth1, orth2, step3, step4; - static doublereal betaj; + IGRAPH_F77_SAVE logical orth1, orth2, step3, step4; + IGRAPH_F77_SAVE doublereal betaj; extern /* Subroutine */ int igraphdscal_(integer *, doublereal *, doublereal *, integer *), igraphdgemv_(char *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, @@ -279,12 +279,12 @@ real tmvbx; extern /* Subroutine */ int igraphdvout_(integer *, integer *, doublereal *, integer *, char *, ftnlen); - static doublereal wnorm; + IGRAPH_F77_SAVE doublereal wnorm; extern /* Subroutine */ int igraphivout_(integer *, integer *, integer *, integer *, char *, ftnlen), igraphdgetv0_(integer *, char *, integer *, logical *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *), igraphdlabad_(doublereal *, doublereal *); - static doublereal rnorm1; + IGRAPH_F77_SAVE doublereal rnorm1; extern doublereal igraphdlamch_(char *); extern /* Subroutine */ int igraphdlascl_(char *, integer *, integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, @@ -294,10 +294,10 @@ extern /* Subroutine */ int igraphsecond_(real *); integer logfil=0, ndigit, nitref, mnaitr=0; real titref, tnaitr; - static integer msglvl; - static doublereal smlnum; + IGRAPH_F77_SAVE integer msglvl; + IGRAPH_F77_SAVE doublereal smlnum; integer nrorth; - static logical rstart; + IGRAPH_F77_SAVE logical rstart; integer nrstrt; real tmvopx; === modified file 'src/lapack/dnapps.c' --- src/lapack/dnapps.c 2011-11-02 20:55:12 +0000 +++ src/lapack/dnapps.c 2011-11-03 13:12:52 +0000 @@ -168,7 +168,7 @@ { /* Initialized data */ - static logical first = TRUE_; + IGRAPH_F77_SAVE logical first = TRUE_; /* System generated locals */ integer h_dim1, h_offset, v_dim1, v_offset, q_dim1, q_offset, i__1, i__2, @@ -183,10 +183,10 @@ doublereal h11, h12, h21, h22, h32; integer jj, ir, nr; doublereal tau; - static doublereal ulp; + IGRAPH_F77_SAVE doublereal ulp; doublereal tst1; integer iend; - static doublereal unfl, ovfl; + IGRAPH_F77_SAVE doublereal unfl, ovfl; extern /* Subroutine */ int igraphdscal_(integer *, doublereal *, doublereal *, integer *), igraphdlarf_(char *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *); @@ -218,7 +218,7 @@ integer mnapps=0, msglvl; real tnapps; integer istart; - static doublereal smlnum; + IGRAPH_F77_SAVE doublereal smlnum; integer kplusp; === modified file 'src/lapack/dnaup2.c' --- src/lapack/dnaup2.c 2011-11-02 20:55:12 +0000 +++ src/lapack/dnaup2.c 2011-11-03 13:12:52 +0000 @@ -213,44 +213,44 @@ double sqrt(doublereal); /* Local variables */ - static integer j; - static real t0, t1, t2, t3; - static integer kp[4], np0, nbx, nev0; + IGRAPH_F77_SAVE integer j; + IGRAPH_F77_SAVE real t0, t1, t2, t3; + IGRAPH_F77_SAVE integer kp[4], np0, nbx, nev0; extern doublereal igraphddot_(integer *, doublereal *, integer *, doublereal *, integer *); - static doublereal eps23; - static integer ierr, iter; - static doublereal temp; + IGRAPH_F77_SAVE doublereal eps23; + IGRAPH_F77_SAVE integer ierr, iter; + IGRAPH_F77_SAVE doublereal temp; extern doublereal igraphdnrm2_(integer *, doublereal *, integer *); - static logical getv0, cnorm; + IGRAPH_F77_SAVE logical getv0, cnorm; extern /* Subroutine */ int igraphdcopy_(integer *, doublereal *, integer *, doublereal *, integer *); - static integer nconv; + IGRAPH_F77_SAVE integer nconv; extern /* Subroutine */ int igraphdmout_(integer *, integer *, integer *, doublereal *, integer *, integer *, char *, ftnlen); - static logical initv; - static doublereal rnorm; - static real tmvbx; + IGRAPH_F77_SAVE logical initv; + IGRAPH_F77_SAVE doublereal rnorm; + IGRAPH_F77_SAVE real tmvbx; extern /* Subroutine */ int igraphdvout_(integer *, integer *, doublereal *, integer *, char *, ftnlen), igraphivout_(integer *, integer *, integer * , integer *, char *, ftnlen), igraphdgetv0_(integer *, char *, integer * , logical *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *); extern doublereal igraphdlapy2_(doublereal *, doublereal *); - static integer mnaup2=0; - static real tnaup2; + IGRAPH_F77_SAVE integer mnaup2=0; + IGRAPH_F77_SAVE real tnaup2; extern doublereal igraphdlamch_(char *); extern /* Subroutine */ int igraphdneigh_(doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, doublereal * , integer *, doublereal *, integer *); - static integer nevbef; + IGRAPH_F77_SAVE integer nevbef; extern /* Subroutine */ int igraphsecond_(real *); - static integer logfil=0, ndigit; + IGRAPH_F77_SAVE integer logfil=0, ndigit; extern /* Subroutine */ int igraphdnaitr_(integer *, char *, integer *, integer *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *, doublereal *, integer *, integer *, doublereal *, integer *); - static logical update; + IGRAPH_F77_SAVE logical update; extern /* Subroutine */ int igraphdngets_(integer *, char *, integer *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *), igraphdnapps_(integer *, integer *, integer *, @@ -259,9 +259,9 @@ doublereal *), igraphdnconv_(integer *, doublereal *, doublereal *, doublereal *, doublereal *, integer *), igraphdsortc_(char *, logical *, integer *, doublereal *, doublereal *, doublereal *); - static logical ushift; - static char wprime[2]; - static integer msglvl, nptemp, numcnv, kplusp; + IGRAPH_F77_SAVE logical ushift; + IGRAPH_F77_SAVE char wprime[2]; + IGRAPH_F77_SAVE integer msglvl, nptemp, numcnv, kplusp; /* %----------------------------------------------------% === modified file 'src/lapack/dnaupd.c' --- src/lapack/dnaupd.c 2011-11-02 20:55:12 +0000 +++ src/lapack/dnaupd.c 2011-11-03 13:12:52 +0000 @@ -464,19 +464,19 @@ /* Local variables */ integer j; real t0, t1; - static integer nb, ih, iq, np, iw, ldh, ldq; + IGRAPH_F77_SAVE integer nb, ih, iq, np, iw, ldh, ldq; integer nbx; - static integer nev0, mode; + IGRAPH_F77_SAVE integer nev0, mode; integer ierr; - static integer iupd, next; + IGRAPH_F77_SAVE integer iupd, next; integer nopx; - static integer levec; + IGRAPH_F77_SAVE integer levec; real trvec, tmvbx; - static integer ritzi; + IGRAPH_F77_SAVE integer ritzi; extern /* Subroutine */ int igraphdvout_(integer *, integer *, doublereal *, integer *, char *, ftnlen), igraphivout_(integer *, integer *, integer * , integer *, char *, ftnlen); - static integer ritzr; + IGRAPH_F77_SAVE integer ritzr; extern /* Subroutine */ int igraphdnaup2_(integer *, char *, integer *, char *, integer *, integer *, doublereal *, doublereal *, integer *, integer *, integer *, integer *, doublereal *, integer *, @@ -489,15 +489,15 @@ integer logfil=0, ndigit; real tneigh; integer mnaupd=0; - static integer ishift; + IGRAPH_F77_SAVE integer ishift; integer nitref; - static integer bounds; + IGRAPH_F77_SAVE integer bounds; real tnaupd; extern /* Subroutine */ int igraphdstatn_(void); real titref, tnaitr; - static integer msglvl; + IGRAPH_F77_SAVE integer msglvl; real tngets, tnapps, tnconv; - static integer mxiter; + IGRAPH_F77_SAVE integer mxiter; integer nrorth, nrstrt; real tmvopx; === modified file 'src/lapack/dsaitr.c' --- src/lapack/dsaitr.c 2011-11-02 20:55:12 +0000 +++ src/lapack/dsaitr.c 2011-11-03 13:12:53 +0000 @@ -231,7 +231,7 @@ { /* Initialized data */ - static logical first = TRUE_; + IGRAPH_F77_SAVE logical first = TRUE_; /* System generated locals */ integer h_dim1, h_offset, v_dim1, v_offset, i__1; @@ -241,20 +241,20 @@ /* Local variables */ integer i__; - static integer j; + IGRAPH_F77_SAVE integer j; real t0, t1, t2, t3, t4, t5; integer jj; - static integer ipj, irj; + IGRAPH_F77_SAVE integer ipj, irj; integer nbx; - static integer ivj; + IGRAPH_F77_SAVE integer ivj; extern doublereal igraphddot_(integer *, doublereal *, integer *, doublereal *, integer *); - static integer ierr, iter; + IGRAPH_F77_SAVE integer ierr, iter; integer nopx; - static integer itry; + IGRAPH_F77_SAVE integer itry; extern doublereal igraphdnrm2_(integer *, doublereal *, integer *); doublereal temp1; - static logical orth1, orth2, step3, step4; + IGRAPH_F77_SAVE logical orth1, orth2, step3, step4; extern /* Subroutine */ int igraphdscal_(integer *, doublereal *, doublereal *, integer *), igraphdgemv_(char *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, @@ -266,25 +266,25 @@ real tmvbx; extern /* Subroutine */ int igraphdvout_(integer *, integer *, doublereal *, integer *, char *, ftnlen); - static doublereal wnorm; + IGRAPH_F77_SAVE doublereal wnorm; extern /* Subroutine */ int igraphivout_(integer *, integer *, integer *, integer *, char *, ftnlen), igraphdgetv0_(integer *, char *, integer *, logical *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *); - static doublereal rnorm1; + IGRAPH_F77_SAVE doublereal rnorm1; extern doublereal igraphdlamch_(char *); extern /* Subroutine */ int igraphdlascl_(char *, integer *, integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, integer *, integer *), igraphsecond_(real *); integer logfil=0; - static doublereal safmin; + IGRAPH_F77_SAVE doublereal safmin; integer ndigit, nitref; real titref; integer msaitr=0; - static integer msglvl; + IGRAPH_F77_SAVE integer msglvl; real tsaitr; integer nrorth; - static logical rstart; + IGRAPH_F77_SAVE logical rstart; integer nrstrt; real tmvopx; === modified file 'src/lapack/dsapps.c' --- src/lapack/dsapps.c 2011-11-02 20:55:12 +0000 +++ src/lapack/dsapps.c 2011-11-03 13:12:53 +0000 @@ -156,7 +156,7 @@ { /* Initialized data */ - static logical first = TRUE_; + IGRAPH_F77_SAVE logical first = TRUE_; /* System generated locals */ integer h_dim1, h_offset, q_dim1, q_offset, v_dim1, v_offset, i__1, i__2, @@ -185,7 +185,7 @@ integer *, doublereal *, integer *, doublereal *, integer *), igraphdlartg_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *), igraphdlaset_(char *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *); - static doublereal epsmch; + IGRAPH_F77_SAVE doublereal epsmch; integer logfil=0, ndigit, msapps=0, msglvl, istart; real tsapps; integer kplusp; === modified file 'src/lapack/dsaup2.c' --- src/lapack/dsaup2.c 2011-11-02 20:55:12 +0000 +++ src/lapack/dsaup2.c 2011-11-03 13:12:53 +0000 @@ -221,26 +221,26 @@ integer j; real t0, t1, t2, t3; integer kp[3]; - static integer np0; + IGRAPH_F77_SAVE integer np0; integer nbx; - static integer nev0; + IGRAPH_F77_SAVE integer nev0; extern doublereal igraphddot_(integer *, doublereal *, integer *, doublereal *, integer *); - static doublereal eps23; + IGRAPH_F77_SAVE doublereal eps23; integer ierr; - static integer iter; + IGRAPH_F77_SAVE integer iter; doublereal temp; integer nevd2; extern doublereal igraphdnrm2_(integer *, doublereal *, integer *); - static logical getv0; + IGRAPH_F77_SAVE logical getv0; integer nevm2; - static logical cnorm; + IGRAPH_F77_SAVE logical cnorm; extern /* Subroutine */ int igraphdcopy_(integer *, doublereal *, integer *, doublereal *, integer *), igraphdswap_(integer *, doublereal *, integer *, doublereal *, integer *); - static integer nconv; - static logical initv; - static doublereal rnorm; + IGRAPH_F77_SAVE integer nconv; + IGRAPH_F77_SAVE logical initv; + IGRAPH_F77_SAVE doublereal rnorm; real tmvbx; extern /* Subroutine */ int igraphdvout_(integer *, integer *, doublereal *, integer *, char *, ftnlen), igraphivout_(integer *, integer *, integer * @@ -255,7 +255,7 @@ integer logfil=0, ndigit; extern /* Subroutine */ int igraphdseigt_(doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, integer *); - static logical update; + IGRAPH_F77_SAVE logical update; extern /* Subroutine */ int igraphdsaitr_(integer *, char *, integer *, integer *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *, doublereal *, integer *, integer *, doublereal *, @@ -265,13 +265,13 @@ integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *), igraphdsconv_(integer *, doublereal *, doublereal *, doublereal *, integer *); - static logical ushift; + IGRAPH_F77_SAVE logical ushift; char wprime[2]; - static integer msglvl; + IGRAPH_F77_SAVE integer msglvl; integer nptemp; extern /* Subroutine */ int igraphdsortr_(char *, logical *, integer *, doublereal *, doublereal *); - static integer kplusp; + IGRAPH_F77_SAVE integer kplusp; /* %----------------------------------------------------% === modified file 'src/lapack/dsaupd.c' --- src/lapack/dsaupd.c 2011-11-02 20:55:12 +0000 +++ src/lapack/dsaupd.c 2011-11-03 13:12:53 +0000 @@ -465,11 +465,11 @@ /* Local variables */ integer j; real t0, t1; - static integer nb, ih, iq, np, iw, ldh, ldq; + IGRAPH_F77_SAVE integer nb, ih, iq, np, iw, ldh, ldq; integer nbx; - static integer nev0, mode, ierr, iupd, next; + IGRAPH_F77_SAVE integer nev0, mode, ierr, iupd, next; integer nopx; - static integer ritz; + IGRAPH_F77_SAVE integer ritz; real tmvbx; extern /* Subroutine */ int igraphdvout_(integer *, integer *, doublereal *, integer *, char *, ftnlen), igraphivout_(integer *, integer *, integer * @@ -483,14 +483,14 @@ extern doublereal igraphdlamch_(char *); extern /* Subroutine */ int igraphsecond_(real *); integer logfil=0, ndigit; - static integer ishift; + IGRAPH_F77_SAVE integer ishift; integer nitref, msaupd=0; - static integer bounds; + IGRAPH_F77_SAVE integer bounds; real titref, tseigt, tsaupd; extern /* Subroutine */ int igraphdstats_(void); - static integer msglvl; + IGRAPH_F77_SAVE integer msglvl; real tsaitr; - static integer mxiter; + IGRAPH_F77_SAVE integer mxiter; real tsgets, tsapps; integer nrorth; real tsconv; python-igraph-0.8.0/vendor/source/igraph/tools/lapack/lapack.patch0000644000076500000240000001305513524616145025471 0ustar tamasstaff00000000000000diff -ru lapack-3.2.2/SRC/dlarft.f lapack-3.2.2-new/SRC/dlarft.f --- lapack-3.2.2/SRC/dlarft.f 2009-04-16 20:10:16.000000000 +0200 +++ lapack-3.2.2-new/SRC/dlarft.f 2010-10-06 21:47:53.000000000 +0200 @@ -145,9 +145,15 @@ V( I, I ) = ONE IF( LSAME( STOREV, 'C' ) ) THEN ! Skip any trailing zeros. - DO LASTV = N, I+1, -1 - IF( V( LASTV, I ).NE.ZERO ) EXIT - END DO + LASTV = N + 14 IF (V(LASTV, I ) .NE. ZERO) GOTO 15 + IF (LASTV .EQ. I+1) GOTO 15 + LASTV = LASTV - 1 + GOTO 14 + 15 CONTINUE +* DO LASTV = N, I+1, -1 +* IF( V( LASTV, I ).NE.ZERO ) EXIT +* END DO J = MIN( LASTV, PREVLASTV ) * * T(1:i-1,i) := - tau(i) * V(i:j,1:i-1)' * V(i:j,i) @@ -157,9 +163,16 @@ $ T( 1, I ), 1 ) ELSE ! Skip any trailing zeros. - DO LASTV = N, I+1, -1 - IF( V( I, LASTV ).NE.ZERO ) EXIT - END DO + LASTV = N + 16 IF (V(I, LASTV) .NE. ZERO) GOTO 17 + IF (LASTV .EQ. I+1) GOTO 17 + LASTV = LASTV - 1 + GOTO 16 + 17 CONTINUE +* DO LASTV = N, I+1, -1 +* IF( V( I, LASTV ).NE.ZERO ) EXIT +* END DO + J = MIN( LASTV, PREVLASTV ) * * T(1:i-1,i) := - tau(i) * V(1:i-1,i:j) * V(i,i:j)' @@ -201,9 +214,16 @@ VII = V( N-K+I, I ) V( N-K+I, I ) = ONE ! Skip any leading zeros. - DO LASTV = 1, I-1 - IF( V( LASTV, I ).NE.ZERO ) EXIT - END DO + LASTV = 1 + 34 IF (V(LASTV, I) .NE. ZERO) GOTO 35 + IF (LASTV .EQ. I-1) GOTO 35 + LASTV = LASTV + 1 + GOTO 34 + 35 CONTINUE +* DO LASTV = 1, I-1 +* IF( V( LASTV, I ).NE.ZERO ) EXIT +* END DO + J = MAX( LASTV, PREVLASTV ) * * T(i+1:k,i) := @@ -217,9 +237,14 @@ VII = V( I, N-K+I ) V( I, N-K+I ) = ONE ! Skip any leading zeros. - DO LASTV = 1, I-1 - IF( V( I, LASTV ).NE.ZERO ) EXIT - END DO + LASTV = 1 + 36 IF (V(I, LASTV) .NE. ZERO) GOTO 37 + IF (LASTV .EQ. I-1) GOTO 37 + LASTV = LASTV + 1 + 37 CONTINUE +* DO LASTV = 1, I-1 +* IF( V( I, LASTV ).NE.ZERO ) EXIT +* END DO J = MAX( LASTV, PREVLASTV ) * * T(i+1:k,i) := diff -ru lapack-3.2.2/SRC/xerbla.f lapack-3.2.2-new/SRC/xerbla.f --- lapack-3.2.2/SRC/xerbla.f 2009-04-16 20:10:16.000000000 +0200 +++ lapack-3.2.2-new/SRC/xerbla.f 2010-10-08 17:53:21.000000000 +0200 @@ -33,7 +33,7 @@ * ===================================================================== * * .. Intrinsic Functions .. - INTRINSIC LEN_TRIM + EXTERNAL LEN_TRIM * .. * .. Executable Statements .. * diff -ru lapack-3.3.1/INSTALL/dlamch.f lapack-3.3.1-new/INSTALL/dlamch.f --- lapack-3.3.1/INSTALL/dlamch.f 2011-04-26 12:41:18.000000000 -0400 +++ lapack-3.3.1-new/INSTALL/dlamch.f 2011-04-26 12:41:22.000000000 -0400 @@ -60,8 +60,8 @@ EXTERNAL LSAME * .. * .. Intrinsic Functions .. - INTRINSIC DIGITS, EPSILON, HUGE, MAXEXPONENT, - $ MINEXPONENT, RADIX, TINY + EXTERNAL DIGITSDBL, EPSILONDBL, HUGEDBL, MAXEXPONENTDBL, + $ MINEXPONENTDBL, RADIXDBL, TINYDBL * .. * .. Executable Statements .. * @@ -71,16 +71,16 @@ RND = ONE * IF( ONE.EQ.RND ) THEN - EPS = EPSILON(ZERO) * 0.5 + EPS = EPSILONDBL(ZERO) * 0.5 ELSE - EPS = EPSILON(ZERO) + EPS = EPSILONDBL(ZERO) END IF * IF( LSAME( CMACH, 'E' ) ) THEN RMACH = EPS ELSE IF( LSAME( CMACH, 'S' ) ) THEN - SFMIN = TINY(ZERO) - SMALL = ONE / HUGE(ZERO) + SFMIN = TINYDBL(ZERO) + SMALL = ONE / HUGEDBL(ZERO) IF( SMALL.GE.SFMIN ) THEN * * Use SMALL plus a bit, to avoid the possibility of rounding @@ -90,21 +90,21 @@ END IF RMACH = SFMIN ELSE IF( LSAME( CMACH, 'B' ) ) THEN - RMACH = RADIX(ZERO) + RMACH = RADIXDBL(ZERO) ELSE IF( LSAME( CMACH, 'P' ) ) THEN - RMACH = EPS * RADIX(ZERO) + RMACH = EPS * RADIXDBL(ZERO) ELSE IF( LSAME( CMACH, 'N' ) ) THEN - RMACH = DIGITS(ZERO) + RMACH = DIGITSDBL(ZERO) ELSE IF( LSAME( CMACH, 'R' ) ) THEN RMACH = RND ELSE IF( LSAME( CMACH, 'M' ) ) THEN - RMACH = MINEXPONENT(ZERO) + RMACH = MINEXPONENTDBL(ZERO) ELSE IF( LSAME( CMACH, 'U' ) ) THEN - RMACH = tiny(zero) + RMACH = TINYDBL(zero) ELSE IF( LSAME( CMACH, 'L' ) ) THEN - RMACH = MAXEXPONENT(ZERO) + RMACH = MAXEXPONENTDBL(ZERO) ELSE IF( LSAME( CMACH, 'O' ) ) THEN - RMACH = HUGE(ZERO) + RMACH = HUGEDBL(ZERO) ELSE RMACH = ZERO END IF python-igraph-0.8.0/vendor/source/igraph/tools/lapack/comment.l0000644000076500000240000000052013524616145025025 0ustar tamasstaff00000000000000%{ #include /* extern FILE *commentFile, *localVarFile, *codeFile; */ %} whitespace [\n\t ]* any .* %% "*/"{whitespace}"/*" {yytext[0]=yytext[1]=yytext[yyleng-1]=yytext[yyleng-2]=' ';printf("%s",yytext);} "\n" {printf("%s", yytext);} . {printf("%s", yytext);} python-igraph-0.8.0/vendor/source/igraph/tools/lapack/split.sed0000644000076500000240000000117713524616145025047 0ustar tamasstaff00000000000000# delete the header produced by f2c /\/\* -- trans.*/,/\*\//{ d } # extract the first line of including f2c.h /#include/,/^$/{ w temp/header1 d } # possible local constants produced by f2c /\/\* Table of constant values \*\//{ s/^/ / w temp/header2 d } /^static.*=.*/,/^$/{ s/^/ / w temp/header2 d } # matches /* Subroutine */..._( or /* Complex */..._( /^\/\* .*_(/,/^\{/{ w temp/header3 /^\{/!{ d } } # matches any function declaration line /^[a-zA-Z].*_(/,/^\{/{ w temp/header3 /^\{/!{ d } } /^\{/,/\/\*.*LAPACK/{ /\/\*.*LAPACK/!{ /^$/d /^\{/d w temp/prologue d } } /\/\*.*LAPACK/,/\*\//{ w temp/comment d } w temp/code python-igraph-0.8.0/vendor/source/igraph/tools/leakcheck.supp0000644000076500000240000000010613524616145024576 0ustar tamasstaff00000000000000{ malloc/glp_init_env Memcheck:Leak fun:malloc fun:glp_init_env } python-igraph-0.8.0/vendor/source/igraph/tools/removeexamples.py0000755000076500000240000000102213524616145025362 0ustar tamasstaff00000000000000#! /usr/bin/env python import sys from xml.etree.ElementTree import ElementTree def usage(): print sys.argv[0], " " def main(): if len(sys.argv) != 3: usage() sys.exit(2) # Read in tree=ElementTree() tree.parse(sys.argv[1]) # Remove examples examples=tree.findall(".//example") for ex in examples: prog=ex.find("programlisting") ex.remove(prog) # Write result tree.write(sys.argv[2]) if __name__ == "__main__": main() python-igraph-0.8.0/vendor/source/igraph/tools/protect_braces.sh0000755000076500000240000000006713524616145025317 0ustar tamasstaff00000000000000#!/bin/sh echo '{% raw %}' cat - echo '{% endraw %}' python-igraph-0.8.0/vendor/source/igraph/tools/ltmain.patch0000644000076500000240000000151113524616145024261 0ustar tamasstaff00000000000000--- ltmain.sh.old 2017-09-12 11:03:05.000000000 +0200 +++ ltmain.sh 2017-09-12 11:04:08.000000000 +0200 @@ -7273,9 +7273,11 @@ # --sysroot=* for sysroot support # -O*, -g*, -flto*, -fwhopr*, -fuse-linker-plugin GCC link-time optimization # -stdlib=* select c++ std lib with clang + # -fsanitize=* memory and address sanitizers -64|-mips[0-9]|-r[0-9][0-9]*|-xarch=*|-xtarget=*|+DA*|+DD*|-q*|-m*| \ -t[45]*|-txscale*|-p|-pg|--coverage|-fprofile-*|-F*|@*|-tp=*|--sysroot=*| \ - -O*|-g*|-flto*|-fwhopr*|-fuse-linker-plugin|-fstack-protector*|-stdlib=*) + -O*|-g*|-flto*|-fwhopr*|-fuse-linker-plugin|-fstack-protector*|-stdlib=*| \ + -fsanitize=*) func_quote_for_eval "$arg" arg=$func_quote_for_eval_result func_append compile_command " $arg" python-igraph-0.8.0/vendor/source/igraph/tools/test-icc-compiler.sh0000755000076500000240000000056013524616145025641 0ustar tamasstaff00000000000000#!/bin/sh # Test igraph compilation with Intel's C compiler set -e ICC_DIR=/opt/intel source ${ICC_DIR}/bin/compilervars.sh intel64 CC=icc CXX=icpc LD=xild AR=xiar LANG=en LANGUAGE=en LC_ALL=C export CC CXX LD AR LANG LANGUAGE LC_ALL IGRAPH_ROOT=`dirname $0`/.. cd ${IGRAPH_ROOT} rm -rf build-icc mkdir build-icc cd build-icc ../configure make 2>stderr.log cd ..python-igraph-0.8.0/vendor/source/igraph/tools/stimulus.py0000755000076500000240000015627213524616145024235 0ustar tamasstaff00000000000000#! /usr/bin/env python import re import seqdict import sys import getopt import os version="0.1" date="Jul 29 2007" def usage(): print "Stimulus version", version, date print sys.argv[0], "-f -t -l language " print ' ' * len(sys.argv[0]), "-i -o " print ' ' * len(sys.argv[0]), "-h --help -v" ################################################################################ class StimulusError(Exception): def __init__(self, message): self.msg = message def __str__(self): return str(self.msg) ################################################################################ class PLexer: def __init__(self, stream): self.stream=stream self.ws_stack=[0] self.tokens=[] self.lineno=0 def lineno(self): return self.lineno def token(self): keys=[] if (len(self.tokens)>0): return self.tokens.pop(0) # Read a line, skip empty lines and comments while True: line=self.stream.readline(); self.lineno = self.lineno+1 if line=="": for k in keys: self.tokens.append( ("key", k) ) keys=[] while len(self.ws_stack)>0: self.tokens.append( ("dedent", "") ) self.ws_stack.pop() self.tokens.append( ("eof", "") ) return self.tokens.pop(0) if re.match("^[ \t]*$", line): continue if re.match("^[ \t]*#", line): continue break if line[-1]=="\n": line=line[:(len(line)-1)] ws=re.match(r"^[ \t]*", line).span()[1] line=line.strip() if ws > self.ws_stack[-1]: self.tokens.append( ("indent", "") ) self.ws_stack.append(ws) else: for k in keys: self.tokens.append( ("key", k) ) keys=[] while ws < self.ws_stack[-1]: self.ws_stack.pop() self.tokens.append( ("dedent", "") ) if ws != self.ws_stack[-1]: print "Bad indentation in line", self.lineno exit # Ok, we're done with the white space, now let's see # whether this line is continued while line[-1]=="\\": line=line[:(len(line)-1)] line=line+"\n " + self.stream.readline().strip() ; self.lineno=self.lineno+1 # We have the line now, check whether there is a ':' in it line=line.split(":", 1) if len(line)>1: line[0]=line[0].strip() line[1]=line[1].strip() if line[0]=="": print "Missing keyword in line", self.lineno exit keys=line[0].split(",") keys=[ k.strip() for k in keys ] if line[1] == "": self.tokens.append( ("key", keys.pop(0)) ) else: for k in keys: self.tokens.append( ("key", k)) self.tokens.append( ("indent", "") ) self.tokens.append( ("text", line[1]) ) self.tokens.append( ("dedent", "") ) else: self.tokens.append( ("text", line[0].strip()) ) for k in keys: self.tokens.append( ("dedent", "") ) self.tokens.append( ("key", k) ) self.tokens.append( ("indent", "") ) keys=[] if self.tokens: return self.tokens.pop(0) ################################################################################ class PParser: def parse(self, stream): lex=PLexer(stream) val=seqdict.seqdict() val_stack=[val, None] nam_stack=[None, None] tok=lex.token() while not tok[0]=="eof": if tok[0]=="indent": val_stack.append(None) nam_stack.append(None) elif tok[0]=="dedent": v=val_stack.pop() n=nam_stack.pop() if n is None: val_stack[-1]=v else: val_stack[-1][n]=v elif tok[0]=="key": if not nam_stack[-1] is None: val_stack[-2][nam_stack[-1]]=val_stack[-1] if tok[1][-5:]=="-list": val_stack[-1]=seqdict.seqdict() nam_stack[-1]=tok[1][:-5] else: val_stack[-1]={} nam_stack[-1]=tok[1] elif tok[0]=="text": val_stack[-1]=tok[1] tok=lex.token() return val ################################################################################ def main(): # Command line arguments try: optlist, args = getopt.getopt(sys.argv[1:], 't:f:l:i:o:hv', ['help']) except getopt.GetoptError: usage() sys.exit(2) types=[]; functions=[]; inputs=[]; languages=[]; outputs=[]; verbose=False for o,a in optlist: if o in ("-h", "--help"): usage() sys.exit() elif o == "-o": outputs.append(a) elif o == "-t": types.append(a) elif o == "-f": functions.append(a) elif o == "-l": languages.append(a) elif o == "-i": inputs.append(a) elif o =="-v": verbose=True # Parameter checks # Note: the lists might be empty, but languages and outputs must # have the same length. if len(languages) != len(outputs): print "Error: number of languages and output files must match" sys.exit(4) for l in languages: if not l+"CodeGenerator" in globals(): print "Error: unknown language:", l sys.exit(6) for f in types: if not os.access(f, os.R_OK): print "Error: cannot open type file:", f sys.exit(5) for f in functions: if not os.access(f, os.R_OK): print "Error: cannot open function file:", f sys.exit(5) for f in inputs: if not os.access(f, os.R_OK): print "Error: cannot open input file:", f sys.exit(5) # TODO: output files are not checked now # OK, do the trick: for l in range(len(languages)): cl=globals()[languages[l]+"CodeGenerator"] cg=cl(functions, types) cg.generate(inputs, outputs[l]) ################################################################################ class CodeGenerator: def __init__(self, func, types): # Set name self.name=str(self.__class__).split(".")[-1] self.name=self.name[0:len(self.name)-len("CodeGenerator")] # Parse function and type files parser=PParser() self.func=seqdict.seqdict() for f in func: ff=open(f) newfunc=parser.parse(ff) self.func.extend(newfunc) ff.close() self.types=seqdict.seqdict() for t in types: ff=open(t) newtypes=parser.parse(ff) self.types.extend(newtypes) ff.close() # The default return type is 'ERROR' for f in self.func.keys(): if 'RETURN' not in self.func[f]: self.func[f]['RETURN']='ERROR' def generate(self, inputs, output): out=open(output, "w") self.append_inputs(inputs, out) for f in self.func.keys(): if 'FLAGS' in self.func[f]: flags=self.func[f]['FLAGS'] flags=flags.split(",") flags=[ flag.strip() for flag in flags ] else: self.func[f]['FLAGS']=[] self.generate_function(f, out) out.close() def generate_function(self, f, out): print "Error: invalid code generator, this method should be overridden" sys.exit(1) def parse_params(self, function): if "PARAMS" not in self.func[function]: return seqdict.seqdict() params=self.func[function]["PARAMS"] params=params.split(",") params=[ p.strip() for p in params ] params=[ p.split(" ", 1) for p in params ] for p in range(len(params)): if params[p][0] in ['OUT', 'IN', 'INOUT']: params[p]=[params[p][0]] + params[p][1].split(" ", 1) else: params[p]=['IN', params[p][0]]+ params[p][1].split(" ", 1) if '=' in params[p][2]: params[p]=params[p][:2] + params[p][2].split("=", 1) params=[ [ p.strip() for p in pp ] for pp in params ] res=seqdict.seqdict() for p in params: if len(p)==3: res[ p[2] ] = { 'mode': p[0], 'type': p[1] } else: res[ p[2] ] = { 'mode': p[0], 'type': p[1], 'default': p[3] } return res def parse_deps(self, function): if 'DEPS' not in self.func[function]: return seqdict.seqdict() deps=self.func[function]["DEPS"] deps=deps.split(",") deps=[ d.strip() for d in deps ] deps=[ d.split("ON", 1) for d in deps ] deps=[ [ dd.strip() for dd in d ] for d in deps ] deps=[ [d[0]] + d[1].split(" ",1) for d in deps ] deps=[ [ dd.strip() for dd in d ] for d in deps ] res=seqdict.seqdict() for d in deps: res[ d[0] ] = d[1:] return res def append_inputs(self, inputs, output): for i in inputs: ii=open(i) str=ii.read() while str != "": output.write(str) str=ii.read() ii.close() pass def ignore(self, function): if 'IGNORE' in self.func[function]: ign=self.func[function]['IGNORE'] ign=ign.split(",") ign=[i.strip() for i in ign] if self.name in ign: return True return False ################################################################################ # GNU R, see http://www.r-project.org # TODO: free memory when CTRL+C pressed, even on windows ################################################################################ class RNamespaceCodeGenerator(CodeGenerator): def __init__(self, func, types): CodeGenerator.__init__(self, func, types) def generate(self, inputs, output): """This is very simple, we include an 'export' line for every function which it not to be ignored by the RNamespace language. Function names are taken from NAME-R if present, otherwise underscores are converted to dots and the leading 'i' (from 'igraph') is stripped to create the function name, ie. igraph_clusters is mapped to graph.clusters.""" out=open(output, "w") self.append_inputs(inputs, out) for f in self.func.keys(): if (self.ignore(f)): continue name=self.func[f].get("NAME-R", f[1:].replace("_", ".")) out.write("export(" + name + ")\n") out.close() class RRCodeGenerator(CodeGenerator): def __init__(self, func, types): CodeGenerator.__init__(self, func, types) def generate_function(self, function, out): # Ignore? if self.ignore(function): return name=self.func[function].get("NAME-R", function[1:].replace("_", ".")) params=self.parse_params(function) self.deps=self.parse_deps(function) # Check types for p in params.keys(): tname=params[p]['type'] if not tname in self.types.keys(): print "Error: Unknown type encountered:", tname sys.exit(7) params[p].setdefault('mode', 'IN') ## Roxygen to export the function internal = self.func[function].get("INTERNAL") print internal if internal is None or internal == 'False': out.write("#' @export\n") ## Header ## do_par handles the translation of a single argument in the ## header. Pretty simple, the only difficulty is that we ## might need to add default values. Default values are taken ## from a language specific dictionary, this is compiled from ## the type file(s). ## So we take all arguments with mode 'IN' or 'INOUT' and ## check whether they have a default value. If yes then we ## check if the default value is given in the type file. If ## yes then we use the value given there, otherwise the ## default value is ignored silently. (Not very nice.) out.write(name) out.write(" <- function(") def do_par(pname): tname=params[pname]['type'] t=self.types[tname] default="" header=pname.replace("_", ".") if 'HEADER' in t: header=t['HEADER'] if header: header=header.replace("%I%", pname.replace("_", ".")) else: header="" if 'default' in params[pname]: if 'DEFAULT' in t and params[pname]['default'] in t['DEFAULT']: default="=" + t['DEFAULT'][ params[pname]['default'] ] else: default="=" + params[pname]['default'] header = header + default if pname in self.deps.keys(): deps = self.deps[pname] for i in range(len(deps)): header=header.replace("%I"+str(i+1)+"%", deps[i]) return header head=[ do_par(n) for n,p in params.items() if p['mode'] in ['IN','INOUT'] ] head=[ h for h in head if h != "" ] out.write(", ".join(head)) out.write(") {\n") ## Argument checks, INCONV ## We take 'IN' and 'INOUT' mode arguments and if they have an ## INCONV field then we use that. This is typically for ## argument checks, like we check here that the argument ## supplied for a graph is indeed an igraph graph object. We ## also covert numeric vectors to 'double' here. ## The INCONV fields are simply concatenated by newline ## characters. out.write(" # Argument checks\n") def do_par(pname): t=self.types[params[pname]['type']] m=params[pname]['mode'] if m in ['IN', 'INOUT'] and 'INCONV' in t: if m in t['INCONV']: res= " " + t['INCONV'][m] else: res=" " + t['INCONV'] else: res="" res=res.replace("%I%", pname.replace("_", ".")) if pname in self.deps.keys(): deps = self.deps[pname] for i in range(len(deps)): res=res.replace("%I"+str(i+1)+"%", deps[i]) return res inconv=[ do_par(n) for n in params.keys() ] inconv=[ i for i in inconv if i != "" ] out.write("\n".join(inconv)+"\n\n") ## Function call ## This is a bit more difficult than INCONV. Here we supply ## each argument to the .Call function, if the argument has a ## 'CALL' field then it is used, otherwise we simply use its ## name. ## argument. Note that arguments with empty CALL fields are ## completely ignored, so giving an empty CALL field is ## different than not giving it at all. ## Function call def do_par(pname): t=self.types[params[pname]['type']] call=pname.replace("_", ".") if 'CALL' in t: call=t['CALL'] if call: call=call.replace('%I%', pname.replace("_", ".")) else: call="" return call out.write(" on.exit( .Call(C_R_igraph_finalizer) )\n") out.write(" # Function call\n") out.write(" res <- .Call(C_R_" + function + ", ") call=[ do_par(n) for n,p in params.items() if p['mode'] in ['IN', 'INOUT'] ] call=[ c for c in call if c != "" ] out.write(", ".join(call)) out.write(")\n") ## Output conversions def do_opar(pname, realname=None, iprefix=""): if realname is None: realname=pname t=self.types[params[pname]['type']] mode=params[pname]['mode'] if 'OUTCONV' in t and mode in t['OUTCONV']: outconv=" " + t['OUTCONV'][mode] else: outconv="" outconv=outconv.replace("%I%", iprefix+realname) if pname in self.deps.keys(): deps = self.deps[pname] for i in range(len(deps)): outconv=outconv.replace("%I"+str(i+1)+"%", deps[i]) return re.sub("%I[0-9]+%", "", outconv) retpars=[ n for n,p in params.items() if p['mode'] in ['OUT', 'INOUT'] ] if len(retpars) <= 1: outconv=[ do_opar(n, "res") for n in params.keys() ] else: outconv=[ do_opar(n, iprefix="res$") for n in params.keys() ] outconv=[ o for o in outconv if o != "" ] if len(retpars)==0: # returning the return value of the function rt=self.types[self.func[function]['RETURN']] if 'OUTCONV' in rt: retconv=" " + rt['OUTCONV']['OUT'] else: retconv="" retconv=retconv.replace("%I%", "res") # TODO: %I1% etc, is not handled here! ret="\n".join(outconv) + "\n" + retconv + "\n" elif len(retpars)==1: # returning a single output value ret="\n".join(outconv) + "\n" else: # returning a list of output values None ret="\n".join(outconv) + "\n" out.write(ret) ## Some graph attributes to add if 'GATTR-R' in self.func[function].keys(): gattrs=self.func[function]['GATTR-R'].split(',') gattrs=[ ga.split(' IS ', 1) for ga in gattrs ] sstr=" res <- set.graph.attribute(res, '%s', '%s')\n" for ga in gattrs: aname=ga[0].strip() aval=ga[1].strip().replace("'", "\\'") out.write(sstr % (aname, aval)) ## Add some parameters as graph attributes if 'GATTR-PARAM-R' in self.func[function].keys(): pars=self.func[function]['GATTR-PARAM-R'].split(',') pars=[ p.strip().replace("_", ".") for p in pars ] sstr=" res <- set.graph.attribute(res, '%s', %s)\n" for p in pars: out.write(sstr % (p, p)) ## Set the class if requested if 'CLASS-R' in self.func[function].keys(): myclass=self.func[function]['CLASS-R'] out.write(" class(res) <- \"" + myclass + "\"\n") ## See if there is a postprocessor if 'PP-R' in self.func[function].keys(): pp=self.func[function]['PP-R'] out.write(" res <- " + pp + "(res)\n") out.write(" res\n}\n\n") class RCCodeGenerator(CodeGenerator): def __init__(self, func, types): CodeGenerator.__init__(self, func, types) def generate_function(self, function, out): # Ignore? if self.ignore(function): return params=self.parse_params(function) self.deps = self.parse_deps(function) # Check types for p in params.keys(): tname=params[p]['type'] if not tname in self.types.keys(): print "Error: Unknown type encountered:", tname sys.exit(7) params[p].setdefault('mode', 'IN') ## Compile the output ## This code generator is quite difficult, so we use different ## functions to generate the approprite chunks and then ## compile them together using a simple template. ## See the documentation of each chunk below. res={} res['func']=function res['header']=self.chunk_header(function, params) res['decl']=self.chunk_declaration(function, params) res['inconv']=self.chunk_inconv(function, params) res['call']=self.chunk_call(function, params) res['outconv']=self.chunk_outconv(function, params) # Replace into the template text=""" /*-------------------------------------------/ / %(func)-42s / /-------------------------------------------*/ %(header)s { /* Declarations */ %(decl)s /* Convert input */ %(inconv)s /* Call igraph */ %(call)s /* Convert output */ %(outconv)s UNPROTECT(1); return(result); }\n""" % res out.write(text) def chunk_header(self, function, params): """The header. All functions return with a 'SEXP', so this is easy. We just take the 'IN' and 'INOUT' arguments, all will have type SEXP, and concatenate them by commas. The function name is created by prefixing the original name with 'R_'.""" def do_par(pname): t=self.types[params[pname]['type']] if 'HEADER' in t: if t['HEADER']: return t['HEADER'].replace("%I%", pname) else: return "" else: return pname inout=[ do_par(n) for n,p in params.items() if p['mode'] in ['IN','INOUT'] ] inout=[ "SEXP " + n for n in inout if n != "" ] return "SEXP R_" + function + "(" + ", ".join(inout) + ")" def chunk_declaration(self, function, params): """There are a couple of things to declare. First a C type is needed for every argument, these will be supplied in the C igraph call. Then, all 'OUT' arguments need a SEXP variable as well, the result will be stored here. The return type of the C function also needs to be declared, that comes next. The result and names SEXP variables will contain the final result, these are last. ('names' is not always used, but it is easier to always declare it.) """ def do_par(pname): cname="c_"+pname t=self.types[params[pname]['type']] if 'DECL' in t: decl=" " + t['DECL'] elif 'CTYPE' in t: ctype = t['CTYPE'] if type(ctype)==dict: mode=params[pname]['mode'] decl=" " + ctype[mode] + " " + cname + ";" else: decl=" " + ctype + " " + cname + ";" else: decl="" return decl.replace("%C%", cname).replace("%I%", pname) inout=[ do_par(n) for n in params.keys() ] out=[ " SEXP "+n+";" for n,p in params.items() if p['mode']=='OUT' ] retpars=[ n for n,p in params.items() if p['mode'] in ['OUT', 'INOUT'] ] rt=self.types[self.func[function]['RETURN']] if 'DECL' in rt: retdecl=" " + rt['DECL'] elif 'CTYPE' in rt and len(retpars)==0: ctype=rt['CTYPE'] if type(ctype)==dict: mode=params[pname]['mode'] retdecl=" " + ctype[mode] + " " + "c_result;" else: retdecl=" " + rt['CTYPE'] + " c_result;" else: retdecl="" if len(retpars)<=1: res = "\n".join(inout + out + [retdecl] + [" SEXP result;"]) else: res = "\n".join(inout + out + [retdecl] + [" SEXP result, names;"]) return res def chunk_inconv(self, function, params): """Input conversions. Not only for types with mode 'IN' and 'INOUT', eg. for 'OUT' vector types we need to allocate the required memory here, do all the initializations, etc. Types without INCONV fields are ignored. The usual %C%, %I% is performed at the end. """ def do_par(pname): cname="c_"+pname t=self.types[params[pname]['type']] mode=params[pname]['mode'] if 'INCONV' in t and mode in t['INCONV']: inconv=" " + t['INCONV'][mode] else: inconv="" if pname in self.deps.keys(): deps = self.deps[pname] for i in range(len(deps)): inconv=inconv.replace("%C"+str(i+1)+"%", "c_"+deps[i]) return inconv.replace("%C%", cname).replace("%I%", pname) inconv=[ do_par(n) for n in params.keys() ] inconv=[ i for i in inconv if i != "" ] return "\n".join(inconv) def chunk_call(self, function, params): """Every single argument is included, independently of their mode. If a type has a 'CALL' field then that is used after the usual %C% and %I% substitutions, otherwise the standard 'c_' prefixed C argument name is used. """ def docall(t, n): if type(t)==dict: mode=params[n]['mode'] if mode in t: return t[mode] else: return "" else: return t types=[ self.types[params[n]['type']] for n in params.keys() ] call=map( lambda t, n: docall(t.get('CALL', "c_"+n), n), types, params.keys() ) call=map( lambda c, n: c.replace("%C%", "c_"+n).replace("%I%", n), call, params.keys() ) retpars=[ n for n,p in params.items() if p['mode'] in ['OUT', 'INOUT'] ] call=[ c for c in call if c != "" ] res=" " + function + "(" + ", ".join(call) + ");\n" if len(retpars)==0: res=" c_result=" + res return res def chunk_outconv(self, function, params): """The output conversions, this is quite difficult. A function may report its results in two ways: by returning it directly or by setting a variable to which a pointer was passed. igraph usually uses the latter and returns error codes, except for some simple functions like 'igraph_vcount()' which cannot fail. First we add the output conversion for all types. This is easy. Note that even 'IN' arguments may have output conversion, eg. this is the place to free memory allocated to them in the 'INCONV' part. Then we check how many 'OUT' or 'INOUT' arguments we have. There are three cases. If there is a single such argument then that is already converted and we need to return that. If there is no such argument then the output of the function was returned, so we perform the output conversion for the returned type and this will be the result. If there are more than one 'OUT' and 'INOUT' arguments then they are collected in a named list. The names come from the argument names. """ def do_par(pname): cname="c_"+pname t=self.types[params[pname]['type']] mode=params[pname]['mode'] if 'OUTCONV' in t and mode in t['OUTCONV']: outconv=" " + t['OUTCONV'][mode] else: outconv="" if pname in self.deps.keys(): deps = self.deps[pname] for i in range(len(deps)): outconv=outconv.replace("%C"+str(i+1)+"%", "c_"+deps[i]) return outconv.replace("%C%", cname).replace("%I%", pname) outconv=[ do_par(n) for n in params.keys() ] outconv=[ o for o in outconv if o != "" ] retpars=[ n for n,p in params.items() if p['mode'] in ['OUT', 'INOUT'] ] if len(retpars)==0: # return the return value of the function rt=self.types[self.func[function]['RETURN']] if 'OUTCONV' in rt: retconv=" " + rt['OUTCONV']['OUT'] else: retconv="" retconv=retconv.replace("%C%", "c_result").replace("%I%", "result") ret="\n".join(outconv) + "\n" + retconv elif len(retpars)==1: # return the single output value retconv=" result=" + retpars[0] + ";" ret="\n".join(outconv) + "\n" + retconv else: # create a list of output values sets=map ( lambda c, n: " SET_VECTOR_ELT(result, "+str(c)+", "+n+");", range(len(retpars)), retpars ) names=map ( lambda c, n: " SET_STRING_ELT(names, "+str(c)+ ", CREATE_STRING_VECTOR(\""+n+"\"));", range(len(retpars)), retpars ) ret="\n".join([" PROTECT(result=NEW_LIST(" + str(len(retpars)) + "));", " PROTECT(names=NEW_CHARACTER(" + str(len(retpars)) + "));"]+ outconv + sets + names + [" SET_NAMES(result, names);" ] + [" UNPROTECT("+str(len(sets)+1)+");" ]) return ret ################################################################################ # Java interface, experimental version using JNI (Java Native Interface) # TODO: - everything :) This is just a PoC implementation. ################################################################################ class JavaCodeGenerator(CodeGenerator): """Class containing the common parts of JavaJavaCodeGenerator and JavaCCodeGenerator""" package = "net.sf.igraph" def __init__(self, func, types): CodeGenerator.__init__(self, func, types) def camelcase(s): """Returns a camelCase version of the given string (as used in Java libraries""" parts = s.split("_") result = [parts.pop(0)] for part in parts: result.append(part.capitalize()) return "".join(result) camelcase=staticmethod(camelcase) def get_function_metadata(self, f, type_param="JAVATYPE"): """Returns metadata for the given function based on the parameters. f is the name of the function. The result is a dict with the following keys: - java_modifiers: Java modifiers to be used in the .java file - return_type: return type of the function - name: name of the function - argument_types: list of argument types - self_name: name of the "self" argument - is_static: whether the function is static - is_constructor: whether the function is a constructor """ params = self.parse_params(f) is_static, is_constructor = False, False # We will collect data related to the current function in a dict data = {} data["name"]=self.func[f].get("NAME-JAVA", \ JavaCodeGenerator.camelcase(f[7:])) data["java_modifiers"]=["public"] # Check parameter types to determine Java calling semantics types = {"IN": [], "OUT": [], "INOUT": []} for p in params.keys(): types[params[p]["mode"]].append(params[p]) if len(types["OUT"])+len(types["INOUT"]) == 1: # If a single one is OUT or INOUT and all others are # INs, then this is our lucky day - the method fits the Java # semantics if len(types["OUT"]) > 0: return_type_name = types["OUT"][0]["type"] else: return_type_name = types["INOUT"][0]["type"] elif len(types["OUT"])+len(types["INOUT"]) == 0 and \ self.func[f].has_key("RETURN"): # There are only input parameters and the return type is specified, # this also fits the Java semantics return_type_name = self.func[f]["RETURN"] else: raise StimulusError, "%s: calling convention unsupported yet" % \ data["name"] # Loop through the input parameters method_arguments = [] found_self = False for p in params.keys(): if params[p]["mode"] != "IN": continue type_name = params[p]["type"] if not found_self and type_name == "GRAPH": # this will be the 'self' argument found_self = True data["self_name"] = p continue tdesc = self.types.get(type_name, {}) if not tdesc.has_key(type_param): raise StimulusError, "%s: unknown input type %s (needs %s), skipping" % \ (data["name"], type_name, type_param) method_arguments.append(" ".join([tdesc[type_param], p])) data["argument_types"] = method_arguments if not found_self: # Loop through INOUT arguments if we found no "self" yet for p in params.keys(): if params[p]["mode"] == "INOUT" and params[p]["type"] == "GRAPH": found_self = True data["self_name"] = p break tdesc = self.types.get(return_type_name, {}) if not tdesc.has_key(type_param): raise StimulusError, "%s: unknown return type %s, skipping" % \ (data["name"], return_type_name) data["return_type"] = tdesc[type_param] if not found_self: data["java_modifiers"].append("static") data["name"] = data["name"][0].upper()+data["name"][1:] data["java_modifiers"] = " ".join(data["java_modifiers"]) data["is_static"] = not found_self data["is_constructor"] = is_constructor return data class JavaJavaCodeGenerator(JavaCodeGenerator): def __init__(self, func, types): JavaCodeGenerator.__init__(self, func, types) def generate(self, inputs, output): out=open(output, "w") if len(inputs)>1: raise StimulusError, "Java code generator supports only a single input" input = open(inputs[0]) for line in input: if "%STIMULUS%" not in line: out.write(line) continue for f in self.func.keys(): if (self.ignore(f)): continue try: func_metadata = self.get_function_metadata(f) func_metadata["arguments"] = ", ".join(func_metadata["argument_types"]) out.write(" %(java_modifiers)s native %(return_type)s %(name)s(%(arguments)s);\n" % func_metadata) except StimulusError, e: out.write(" // %s\n" % str(e)) out.close() class JavaCCodeGenerator(JavaCodeGenerator): def __init__(self, func, types): JavaCodeGenerator.__init__(self, func, types) def generate_function(self, function, out): # Ignore? if self.ignore(function): return try: self.metadata=self.get_function_metadata(function, "CTYPE") except StimulusError, e: out.write("/* %s */\n" % str(e)) return params=self.parse_params(function) self.deps = self.parse_deps(function) # Check types for p in params.keys(): tname=params[p]['type'] if not tname in self.types.keys(): print "W: Unknown type encountered:", tname return params[p].setdefault('mode', 'IN') ## Compile the output ## This code generator is quite difficult, so we use different ## functions to generate the approprite chunks and then ## compile them together using a simple template. ## See the documentation of each chunk below. try: res={} res['func']=function res['header']=self.chunk_header(function, params) res['decl']=self.chunk_declaration(function, params) res['before']=self.chunk_before(function, params) res['inconv']=self.chunk_inconv(function, params) res['call']=self.chunk_call(function, params) res['outconv']=self.chunk_outconv(function, params) res['after']=self.chunk_after(function, params) except StimulusError, e: out.write("/* %s */\n" % str(e)) return # Replace into the template text=""" /*-------------------------------------------/ / %(func)-42s / /-------------------------------------------*/ %(header)s { /* Declarations */ %(decl)s %(before)s /* Convert input */ %(inconv)s /* Call igraph */ %(call)s /* Convert output */ %(outconv)s %(after)s return result; }\n""" % res out.write(text) def chunk_header(self, function, params): """The header. The name of the function is the igraph function name minus the igraph_ prefix, camelcased and prefixed with the underscored Java classname: net_sf_igraph_Graph_. The arguments are mapped from the JAVATYPE key of the type dict. Static methods also need a 'jclass cls' argument, ordinary methods need 'jobject jobj'. Besides that, the Java environment pointer is also passed. """ data = self.get_function_metadata(function, "JAVATYPE") types = [] data["funcname"] = "Java_%s_Graph_%s" % \ (self.package.replace(".", "_"), data["name"]) if data["is_static"]: data["argument_types"].insert(0, "jclass cls") else: data["argument_types"].insert(0, "jobject "+data["self_name"]) data["argument_types"].insert(0, "JNIEnv *env") data["types"] = ", ".join(data["argument_types"]) res="JNIEXPORT %(return_type)s JNICALL %(funcname)s(%(types)s)" % data return res def chunk_declaration(self, function, params): """The declaration part of the function body There are a couple of things to declare. First a C type is needed for every argument, these will be supplied in the C igraph call. Then, all 'OUT' arguments need an appropriate variable as well, the result will be stored here. The return type of the C function also needs to be declared, that comes next. The result variable will contain the final result. Finally, if the method is not static but we are returning a new Graph object (e.g. in the case of igraph_linegraph), we need a jclass variable to store the Java class object.""" def do_cpar(pname): cname="c_"+pname t=self.types[params[pname]['type']] if 'CDECL' in t: decl=" " + t['CDECL'] elif 'CTYPE' in t: decl=" " + t['CTYPE'] + " " + cname + ";" else: decl="" return decl.replace("%C%", cname).replace("%I%", pname) def do_jpar(pname): jname="j_"+pname t=self.types[params[pname]['type']] if 'JAVADECL' in t: decl=" " + t['JAVADECL'] elif 'JAVATYPE' in t: decl=" " + t['JAVATYPE'] + " " + jname + ";" else: decl="" return decl.replace("%J%", jname).replace("%I%", pname) inout=[ do_cpar(n) for n in params.keys() ] out=[ do_jpar(n) for n,p in params.items() if p['mode']=='OUT'] rt=self.types[self.func[function]['RETURN']] if 'CDECL' in rt: retdecl=" " + rt['CDECL'] elif 'CTYPE' in rt: retdecl=" " + rt['CTYPE'] + " c__result;" else: retdecl="" rnames = [n for n,p in params.items() if p['mode'] in ['OUT','INOUT']] jretdecl = "" if len(rnames)>0: n = rnames[0] rtname = params[n]['type'] else: rtname = self.func[function]["RETURN"] rt = self.types[rtname] if 'JAVADECL' in rt: jretdecl=" " + rt['JAVADECL'] elif 'JAVATYPE' in rt: jretdecl=" " + rt['JAVATYPE'] + " result;" decls = inout + out + [retdecl, jretdecl] if not self.metadata["is_static"] and rtname == "GRAPH": self.metadata["need_class_decl"] = True decls.append(" jclass cls = (*env)->GetObjectClass(env, %s);" % self.metadata["self_name"]) else: self.metadata["need_class_decl"] = False return "\n".join([i for i in decls if i!=""]) def chunk_before(self, function, params): """We simply call Java_igraph_before""" return ' Java_igraph_before();' def chunk_inconv(self, function, params): """Input conversions. Not only for types with mode 'IN' and 'INOUT', eg. for 'OUT' vector types we need to allocate the required memory here, do all the initializations, etc. Types without INCONV fields are ignored. The usual %C%, %I% is performed at the end. """ def do_par(pname): cname="c_"+pname t=self.types[params[pname]['type']] mode=params[pname]['mode'] if 'INCONV' in t and mode in t['INCONV']: inconv=" " + t['INCONV'][mode] else: inconv="" if pname in self.deps.keys(): deps = self.deps[pname] for i in range(len(deps)): inconv=inconv.replace("%C"+str(i+1)+"%", "c_"+deps[i]) return inconv.replace("%C%", cname).replace("%I%", pname) inconv=[ do_par(n) for n in params.keys() ] inconv=[ i for i in inconv if i != "" ] return "\n".join(inconv) def chunk_call(self, function, params): """Every single argument is included, independently of their mode. If a type has a 'CALL' field then that is used after the usual %C% and %I% substitutions, otherwise the standard 'c_' prefixed C argument name is used. """ types=[ self.types[params[n]['type']] for n in params.keys() ] call=map( lambda t, n: t.get('CALL', "c_"+n), types, params.keys() ) call=map( lambda c, n: c.replace("%C%", "c_"+n).replace("%I%", n), call, params.keys() ) lines = [" if ((*env)->ExceptionCheck(env)) {", \ " c__result = IGRAPH_EINVAL;", \ " } else {", \ " c__result = " + function + "(" + ", ".join(call) + ");", \ " }"] return "\n".join(lines) def chunk_outconv(self, function, params): """The output conversions, this is quite difficult. A function may report its results in two ways: by returning it directly or by setting a variable to which a pointer was passed. igraph usually uses the latter and returns error codes, except for some simple functions like 'igraph_vcount()' which cannot fail. First we add the output conversion for all types. This is easy. Note that even 'IN' arguments may have output conversion, eg. this is the place to free memory allocated to them in the 'INCONV' part. Then we check how many 'OUT' or 'INOUT' arguments we have. There are three cases. If there is a single such argument then that is already converted and we need to return that. If there is no such argument then the output of the function was returned, so we perform the output conversion for the returned type and this will be the result. The case of more than one 'OUT' and 'INOUT' arguments is not yet supported by the Java interface. """ def do_par(pname): cname="c_"+pname jname="j_"+pname t=self.types[params[pname]['type']] mode=params[pname]['mode'] if 'OUTCONV' in t and mode in t['OUTCONV']: outconv=" " + t['OUTCONV'][mode] else: outconv="" return outconv.replace("%C%", cname).replace("%I%", jname) outconv=[ do_par(n) for n in params.keys() ] outconv=[ o for o in outconv if o != "" ] retpars=[ (n,p) for n,p in params.items() if p['mode'] in ['OUT', 'INOUT'] ] if len(retpars)==0: # return the return value of the function rt=self.types[self.func[function]['RETURN']] if 'OUTCONV' in rt: retconv=" " + rt['OUTCONV']['OUT'] else: retconv="" retconv=retconv.replace("%C%", "c__result").replace("%I%", "result") if len(retconv)>0: outconv.append(retconv) ret="\n".join(outconv) elif len(retpars)==1: # return the single output value if retpars[0][1]['mode'] == "OUT": # OUT parameter retconv=" result = j_" + retpars[0][0] + ";" else: # INOUT parameter retconv=" result = " + retpars[0][0] + ";" outconv.append(retconv) outconv.insert(0, "if (c__result == 0) {") outconv.extend(["} else {", " result = 0;", "}"]) outconv = [" %s" % line for line in outconv] ret="\n".join(outconv) else: raise StimulusError, "%s: the case of multiple outputs not supported yet" % function return ret def chunk_after(self, function, params): """We simply call Java_igraph_after""" return ' Java_igraph_after();' ################################################################################ # Shell interface, igraph functions directly from the command line # TODO: - read/write default input/output from/to stdin/stdout # - short options # - prefixed output (?) # - default values depending on other parameters # - other input/output graph formats, to be controlled by # environment variables (?): IGRAPH_INGRAPH, IGRAPH_OUTGRAPH ################################################################################ class ShellLnCodeGenerator(CodeGenerator): def __init__(self, func, types): CodeGenerator.__init__(self, func, types) def generate(self, inputs, output): out=open(output, "w") self.append_inputs(inputs, out) for f in self.func.keys(): if (self.ignore(f)): continue out.write(f+"\n") out.close() class ShellCodeGenerator(CodeGenerator): def __init__(self, func, types): CodeGenerator.__init__(self, func, types) def generate(self, inputs, output): out=open(output, "w") self.append_inputs(inputs, out) out.write("\n/* Function prototypes first */\n\n") for f in self.func.keys(): if self.ignore(f): continue if 'FLAGS' in self.func[f]: flags=self.func[f]['FLAGS'] flags=flags.split(",") flags=[ flag.strip() for flag in flags ] else: self.func[f]['FLAGS']=[] self.generate_prototype(f, out) out.write("\n/* The main function */\n\n") out.write("int main(int argc, char **argv) {\n\n") out.write(" const char *base=basename(argv[0]);\n\n ") for f in self.func.keys(): if self.ignore(f): continue out.write("if (!strcasecmp(base, \""+f+ "\")) {\n return shell_"+f+"(argc, argv);\n } else ") out.write("{\n printf(\"Unknown function, exiting\\n\");\n") out.write(" }\n\n shell_igraph_usage(argc, argv);\n return 0;\n\n}\n"); out.write("\n/* The functions themselves at last */\n") for f in self.func.keys(): if self.ignore(f): continue self.generate_function(f, out) out.close() def generate_prototype(self, function, out): out.write("int shell_"+function+"(int argc, char **argv);\n") def generate_function(self, function, out): params=self.parse_params(function) # Check types, also enumerate them args=seqdict.seqdict() for p in params.keys(): tname=params[p]['type'] if not tname in self.types.keys(): print "Error: Unknown type encountered:", tname sys.exit(7) params[p].setdefault('mode', 'IN') t=self.types[tname] mode=params[p]['mode'] if 'INCONV' in t or 'OUTCONV' in t: args[p]=params[p].copy() args[p]['shell_no']=len(args)-1 if mode=="INOUT": args[p]['mode']='IN' args[p+'-out']=params[p].copy() args[p+'-out']['mode']='OUT' args[p+'-out']['shell_no']=len(args)-1 if 'INCONV' not in t or 'IN' not in t['INCONV']: print "Warning: no INCONV for type", tname, ", mode IN" if 'OUTCONV' not in t or 'OUT' not in t['OUTCONV']: print "Warning: no OUTCONV for type", tname, ", mode OUT" if mode =='IN' and ('INCONV' not in t or mode not in t['INCONV']): print "Warning: no INCONV for type", tname, ", mode", mode if mode == 'OUT' and ('OUTCONV' not in t or mode not in t['OUTCONV']): print "Warning: no OUTCONV for type", tname, ", mode", mode res={'nargs': len(args)} res['func']=function res['args']=self.chunk_args(function, args) res['decl']=self.chunk_decl(function, params) res['inconv']=self.chunk_inconv(function, args) res['call']=self.chunk_call(function, params) res['outconv']=self.chunk_outconv(function, args) res['default']=self.chunk_default(function, args) res['usage']=self.chunk_usage(function, args) text=""" /*-------------------------------------------/ / %(func)-42s / /-------------------------------------------*/ void shell_%(func)s_usage(char **argv) { %(usage)s exit(1); } int shell_%(func)s(int argc, char **argv) { %(decl)s int shell_seen[%(nargs)s]; int shell_index=-1; struct option shell_options[]= { %(args)s { "help",no_argument,0,%(nargs)s }, { 0,0,0,0 } }; /* 0 - not seen, 1 - seen as argument, 2 - seen as default */ memset(shell_seen, 0, %(nargs)s*sizeof(int)); %(default)s /* Parse arguments and read input */ while (getopt_long(argc, argv, "", shell_options, &shell_index) != -1) { if (shell_index==-1) { exit(1); } if (shell_seen[shell_index]==1) { fprintf(stderr, "Error, `--%%s' argument given twice.\\n", shell_options[shell_index].name); exit(1); } shell_seen[shell_index]=1; %(inconv)s shell_index=-1; } /* Check that we have all arguments */ for (shell_index=0; shell_index<%(nargs)s; shell_index++) { if (!shell_seen[shell_index]) { fprintf(stderr, "Error, argument missing: `--%%s'.\\n", shell_options[shell_index].name); exit(1); } } /* Do the operation */ %(call)s /* Write the result */ %(outconv)s return 0; }\n""" % res out.write(text) def chunk_args(self, function, params): res=[ ['"'+n+'"',"required_argument","0", str(p['shell_no']) ] for n,p in params.items() ] res=[ "{ "+",".join(e)+" }," for e in res ] return "\n ".join(res) def chunk_decl(self, function, params): def do_par(pname): t=self.types[params[pname]['type']] if 'DECL' in t: decl=" " + t['DECL'].replace("%C%", pname) elif 'CTYPE' in t: decl=" " + t['CTYPE'] + " " + pname else: decl="" if 'default' in params[pname]: if 'DEFAULT' in t and params[pname]['default'] in t['DEFAULT']: default="="+t['DEFAULT'][params[pname]['default']] else: default="="+params[pname]['default'] else: default="" if decl: return decl+default+";" else: return "" decl=[ do_par(n) for n in params.keys() ] inout=[ " char* shell_arg_"+n+"=0;" for n,p in params.items() if p['mode'] in ['INOUT','OUT'] ] rt=self.types[self.func[function]['RETURN']] if 'DECL' in rt: retdecl=" " + rt['DECL'] elif 'CTYPE' in rt: retdecl=" " + rt['CTYPE'] + " shell_result;" else: retdecl="" if self.func[function]['RETURN'] != 'ERROR': retchar=" char *shell_arg_shell_result=\"-\";" else: retchar="" return "\n".join(decl+inout+[retdecl, retchar]) def chunk_default(self, function, params): def do_par(pname): t=self.types[params[pname]['type']] if 'default' in params[pname]: res=" shell_seen["+str(params[pname]['shell_no'])+"]=2;" else: res="" return res res= [ do_par(n) for n in params.keys() ] res= [ n for n in res if n != "" ] return "\n".join(res) def chunk_inconv(self, function, params): def do_par(pname): t=self.types[params[pname]['type']] mode=params[pname]['mode'] if 'INCONV' in t and mode in t['INCONV']: inconv="" + t['INCONV'][mode] else: inconv="" if pname.endswith('-out'): pname=pname[0:-4] return inconv.replace("%C%", pname) inconv=[ " case "+str(p['shell_no'])+": /* "+n+" */\n "+ do_par(n) for n,p in params.items() ] inconv=[ n+"\n break;" for n in inconv ] inconv=[ "".join(n) for n in inconv ] text="\n switch (shell_index) {\n"+"\n".join(inconv)+ \ "\n case "+str(len(inconv))+":\n shell_"+function+"_usage(argv);\n break;"+ \ "\n default:\n break;\n }\n" return text def chunk_call(self, function, params): types=[ self.types[params[n]['type']] for n in params.keys() ] call=map( lambda t,n: t.get('CALL', n), types, params.keys() ) call=map( lambda c,n: c.replace("%C%", n), call, params.keys() ) return " shell_result=" + function + "(" + ", ".join(call) + ");" def chunk_outconv(self, function, params): def do_par(pname): t=self.types[params[pname]['type']] mode=params[pname]['mode'] if 'OUTCONV' in t and mode in t['OUTCONV']: outconv=" " + t['OUTCONV'][mode] else: outconv="" if pname.endswith('-out'): pname=pname[0:-4] return outconv.replace("%C%", pname) outconv=[ do_par(n) for n in params.keys() ] rt=self.types[self.func[function]['RETURN']] if 'OUTCONV' in rt and 'OUT' in rt['OUTCONV']: rtout=" " + rt['OUTCONV']['OUT'] else: rtout="" outconv.append(rtout.replace("%C%", "shell_result")) outconv=[ o for o in outconv if o != "" ] return "\n".join(outconv) def chunk_usage(self, function, params): res=[ "--"+n+"=<"+n+">" for n in params.keys() ] return " printf(\"%s "+" ".join(res)+"\\n\", basename(argv[0]));" ################################################################################ if __name__ == "__main__": main() python-igraph-0.8.0/vendor/source/igraph/tools/leakcheck0000755000076500000240000000610513524616145023620 0ustar tamasstaff00000000000000#!/bin/bash # # Valgrind leak check for the given subdirectory. # The given subdirectory must be an igraph root subdir function usage { echo Usage: $0 [directory] echo directory must be the root of an igraph tree. echo If omitted, assumes that the script itself is in the igraph tree } VALGRIND=`which valgrind` if [ x$VALGRIND == x ]; then echo Error: Valgrind is not installed exit 3 fi if [ x$1 == -h -o x$1 == --help ]; then usage exit 1 fi ORIGDIR=`pwd` DIR=$1 if [ x$DIR == x ]; then # No directory was given, start backtracking from the current OK=0 PREVDIR="/" DIR=`pwd` while [ $OK -eq 0 -a ${PREVDIR} != ${DIR} ]; do if [ -f include/igraph.h ]; then OK=1 else cd .. DIR=`pwd` fi done cd ${ORIGDIR} if [ $OK -eq 0 ]; then echo Error: no igraph tree was given and not in an igraph tree usage exit 4 fi fi if [ ! -d $DIR -o ! -f $DIR/include/igraph.h ]; then echo $DIR is not an igraph root subdirectory exit 2 fi TESTBED="valgrind-testbed" FULLDIR=`cd $DIR && pwd && cd ..` TESTBEDDIR=${FULLDIR}/${TESTBED} if [ ! -f $DIR/configure ]; then cd $DIR ./bootstrap.sh cd $ORIGDIR fi if [ ! -d $TESTBED ]; then mkdir $TESTBED fi # run make distclean on the original tree if necessary if [ -f ${FULLDIR}/Makefile ]; then cd ${FULLDIR} && make distclean && cd ${ORIGDIR} fi cd $TESTBED || exit 3 ${FULLDIR}/configure --enable-debug || ( cd $ORIGDIR; exit 4 ) make || (cd $ORIGDIR; exit 5 ) rm -f a.out if [ `grep -c "HAVE_TLS 1" config.h` -gt 0 ]; then PTHREADS_LIBS=-lpthread else PTHREADS_LIBS= fi mkdir -p examples/simple rm -rf examples/simple/* cp ${FULLDIR}/examples/simple/* examples/simple mkdir -p valgrind-logs rm -rf valgrind-logs/* cd examples/simple SKIPS="igraph_layout_merge.c igraph_es_adj.c igraph_es_fromto.c" for i in *.c; do current=$i OK=1 for skip in $SKIPS; do if [ $skip == $current ]; then OK=0; fi done echo -n "${current}... " if [ $OK -eq 0 ]; then echo "skipped." else gcc -g -o a.out $i -I${ORIGDIR}/include -I${TESTBEDDIR}/include -I${ORIGDIR}/src -I${TESTBEDDIR} -L../../src/.libs -ligraph ${PTHREADS_LIBS} if [ -x a.out ]; then echo -n "compiled... " LOG=../../valgrind-logs/`basename ${current} .c`.log LD_LIBRARY_PATH=../../src/.libs valgrind --tool=memcheck --error-exitcode=63 --leak-check=yes --show-reachable=yes --log-file=${LOG} --suppressions=${ORIGDIR}/tools/leakcheck.supp ./a.out >/dev/null ERRCODE=$? if [ $ERRCODE -eq 63 ]; then echo "executed, memory access problems found!" elif [ $ERRCODE -eq 77 ]; then echo "skipped, OK" rm ${LOG} elif [ $ERRCODE -ne 0 ]; then echo "test case failed, error code: $ERRCODE!" elif [ `cat $LOG | grep -c 'no leaks are possible'` -ne 1 ]; then if [ `cat $LOG | grep -c 'lost: 0 bytes'` -lt 2 ]; then echo "executed, leaks found!" else echo "executed, OK" rm ${LOG} fi else echo "executed, OK" rm ${LOG} fi else echo "compilation FAILED!" fi rm -f a.out fi done cd ../.. cd $ORIGDIR python-igraph-0.8.0/vendor/source/igraph/tools/extract_body.sh0000755000076500000240000000010313524616145024776 0ustar tamasstaff00000000000000#!/bin/sh sed -n '1,/^]/!{ /<\/body>/,/^]/!p; }' python-igraph-0.8.0/vendor/source/igraph/tools/exclude.txt0000644000076500000240000000002413524616145024144 0ustar tamasstaff00000000000000toc.html toc-*.html python-igraph-0.8.0/vendor/source/igraph/tools/arpack-sed.txt0000644000076500000240000000422613524616145024535 0ustar tamasstaff00000000000000s/dsaupd_/igraphdsaupd_/g s/dseupd_/igraphdseupd_/g s/dsaup2_/igraphdsaup2_/g s/dstats_/igraphdstats_/g s/dsesrt_/igraphdsesrt_/g s/dsortr_/igraphdsortr_/g s/dgetv0_/igraphdgetv0_/g s/dsaitr_/igraphdsaitr_/g s/dsapps_/igraphdsapps_/g s/dsconv_/igraphdsconv_/g s/dseigt_/igraphdseigt_/g s/dsgets_/igraphdsgets_/g s/dstqrb_/igraphdstqrb_/g s/dmout_/igraphdmout_/g s/ivout_/igraphivout_/g s/second_/igraphsecond_/g s/dvout_/igraphdvout_/g s/dlarnv_/igraphdlarnv_/g s/dlascl_/igraphdlascl_/g s/dlartg_/igraphdlartg_/g s/dlaset_/igraphdlaset_/g s/dlaev2_/igraphdlaev2_/g s/dlasr_/igraphdlasr_/g s/dlasrt_/igraphdlasrt_/g s/dgeqr2_/igraphdgeqr2_/g s/dlacpy_/igraphdlacpy_/g s/dorm2r_/igraphdorm2r_/g s/dsteqr_/igraphdsteqr_/g s/dlanst_/igraphdlanst_/g s/dlapy2_/igraphdlapy2_/g s/dlamch_/igraphdlamch_/g s/dlaruv_/igraphdlaruv_/g s/dlarfg_/igraphdlarfg_/g s/dlarf_/igraphdlarf_/g s/dlae2_/igraphdlae2_/g s/dlassq_/igraphdlassq_/g s/dlamc1_/igraphdlamc1_/g s/dlamc2_/igraphdlamc2_/g s/dlamc3_/igraphdlamc3_/g s/dlamc4_/igraphdlamc4_/g s/dlamc5_/igraphdlamc5_/g s/xerbla_/igraphxerbla_/g s/daxpy_/igraphdaxpy_/g s/dger_/igraphdger_/g s/dcopy_/igraphdcopy_/g s/dscal_/igraphdscal_/g s/dswap_/igraphdswap_/g s/dgemv_/igraphdgemv_/g s/ddot_/igraphddot_/g s/dnrm2_/igraphdnrm2_/g s/lsame_/igraphlsame_/g s/d_sign/igraphd_sign/g s/etime_/igraphetime_/g s/pow_dd/igraphpow_dd/g s/pow_di/igraphpow_di/g s/s_cmp/igraphs_cmp/g s/s_copy/igraphs_copy/g s/dnaitr/igraphdnaitr/g s/dnapps/igraphdnapps/g s/dnaup2/igraphdnaup2/g s/dnaupd/igraphdnaupd/g s/dnconv/igraphdnconv/g s/dlabad/igraphdlabad/g s/dlanhs/igraphdlanhs/g s/dsortc/igraphdsortc/g s/dneigh/igraphdneigh/g s/dngets/igraphdngets/g s/dstatn/igraphdstatn/g s/dtrevc/igraphdtrevc/g s/dlaqrb/igraphdlaqrb/g s/d_lg10/igraphd_lg10/g s/dlanv2/igraphdlanv2/g s/drot/igraphdrot/g s/idamax/igraphidamax/g s/dlaln2/igraphdlaln2/g s/dladiv/igraphdladiv/g s/dneupd/igraphdneupd/g s/dtrmm/igraphdtrmm/g s/dtrsen/igraphdtrsen/g s/dlahqr/igraphdlahqr/g s/dlacon/igraphdlacon/g s/dtrsyl/igraphdtrsyl/g s/dtrexc/igraphdtrexc/g s/dlange/igraphdlange/g s/dlaexc/igraphdlaexc/g s/dlasy2/igraphdlasy2/g s/dasum/igraphdasum/g s/i_dnnt/igraphi_dnnt/g s/dlarfx/igraphdlarfx/g python-igraph-0.8.0/vendor/source/igraph/tools/autoconf/0000755000076500000240000000000013617375001023570 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/tools/autoconf/as-version.m40000644000076500000240000000431213524616145026124 0ustar tamasstaff00000000000000dnl as-version.m4 0.2.1 dnl autostars m4 macro for versioning dnl Thomas Vander Stichele dnl Gabor Csardi dnl $Id: as-version.m4,v 1.4 2004/06/01 09:40:05 thomasvs Exp $ dnl AS_VERSION dnl example dnl AS_VERSION dnl this macro dnl - AC_SUBST's PACKAGE_VERSION_MAJOR, _MINOR, _PATCH, _PRERELEASE dnl - AC_SUBST's PACKAGE_VERSION_RELEASE, dnl which can be used for rpm release fields dnl - doesn't call AM_INIT_AUTOMAKE anymore because it prevents dnl maintainer mode from running correctly dnl dnl don't forget to put #undef PACKAGE_VERSION_RELEASE in acconfig.h dnl if you use acconfig.h AC_DEFUN([AS_VERSION], [ PACKAGE_VERSION_MAJOR=$(echo AC_PACKAGE_VERSION | cut -d'.' -f1) PACKAGE_VERSION_MINOR=$(echo AC_PACKAGE_VERSION | cut -d'.' -f2) PACKAGE_VERSION_PATCH=$(echo AC_PACKAGE_VERSION | cut -d'.' -f3 | cut -d'-' -f1) PACKAGE_VERSION_PRERELEASE=$(echo AC_PACKAGE_VERSION | cut -d'.' -f3- | cut -s -d'-' -f2-) AC_SUBST(PACKAGE_VERSION_MAJOR) AC_SUBST(PACKAGE_VERSION_MINOR) AC_SUBST(PACKAGE_VERSION_PATCH) AC_SUBST(PACKAGE_VERSION_PRERELEASE) ]) dnl AS_NANO(ACTION-IF-NO-NANO, [ACTION-IF-NANO]) dnl requires AC_INIT to be called before dnl For projects using a fourth or nano number in your versioning to indicate dnl development or prerelease snapshots, this macro allows the build to be dnl set up differently accordingly. dnl this macro: dnl - parses AC_PACKAGE_VERSION, set by AC_INIT, and extracts the nano number dnl - sets the variable PACKAGE_VERSION_NANO dnl - sets the variable PACKAGE_VERSION_RELEASE, which can be used dnl for rpm release fields dnl - executes ACTION-IF-NO-NANO or ACTION-IF-NANO dnl example: dnl AS_NANO(RELEASE="yes", RELEASE="no") AC_DEFUN([AS_NANO], [ AC_MSG_CHECKING(nano version) NANO=$(echo AC_PACKAGE_VERSION | cut -d'.' -f4) if test x"$NANO" = x || test "x$NANO" = "x0" ; then AC_MSG_RESULT([0 (release)]) NANO=0 PACKAGE_VERSION_RELEASE=1 ifelse([$1], , :, [$1]) else AC_MSG_RESULT($NANO) PACKAGE_VERSION_RELEASE=0.`date +%Y%m%d.%H%M%S` ifelse([$2], , :, [$2]) fi PACKAGE_VERSION_NANO=$NANO AC_SUBST(PACKAGE_VERSION_NANO) AC_SUBST(PACKAGE_VERSION_RELEASE) ]) python-igraph-0.8.0/vendor/source/igraph/tools/autoconf/ax_tls.m40000644000076500000240000000575513524616145025344 0ustar tamasstaff00000000000000# =========================================================================== # http://www.gnu.org/software/autoconf-archive/ax_tls.html # =========================================================================== # # SYNOPSIS # # AX_TLS([action-if-found], [action-if-not-found]) # # DESCRIPTION # # Provides a test for the compiler support of thread local storage (TLS) # extensions. Defines TLS if it is found. Currently knows about GCC/ICC # and MSVC. I think SunPro uses the same as GCC, and Borland apparently # supports either. # # LICENSE # # Copyright (c) 2008 Alan Woodland # Copyright (c) 2010 Diego Elio Petteno` # # This program is free software: you can redistribute it and/or modify it # under the terms of the GNU General Public License as published by the # Free Software Foundation, either version 3 of the License, or (at your # option) any later version. # # This program is distributed in the hope that it will be useful, but # WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General # Public License for more details. # # You should have received a copy of the GNU General Public License along # with this program. If not, see . # # As a special exception, the respective Autoconf Macro's copyright owner # gives unlimited permission to copy, distribute and modify the configure # scripts that are the output of Autoconf when processing the Macro. You # need not follow the terms of the GNU General Public License when using # or distributing such scripts, even though portions of the text of the # Macro appear in them. The GNU General Public License (GPL) does govern # all other use of the material that constitutes the Autoconf Macro. # # This special exception to the GPL applies to versions of the Autoconf # Macro released by the Autoconf Archive. When you make and distribute a # modified version of the Autoconf Macro, you may extend this special # exception to the GPL to apply to your modified version as well. #serial 10 AC_DEFUN([AX_TLS], [ AC_MSG_CHECKING(for thread local storage (TLS) class) AC_CACHE_VAL(ac_cv_tls, [ ax_tls_keywords="__thread __declspec(thread) none" for ax_tls_keyword in $ax_tls_keywords; do AS_CASE([$ax_tls_keyword], [none], [ac_cv_tls=none ; break], [AC_TRY_COMPILE( [#include static void foo(void) { static ] $ax_tls_keyword [ int bar; exit(1); }], [], [ac_cv_tls=$ax_tls_keyword ; break], ac_cv_tls=none )]) done ]) AC_MSG_RESULT($ac_cv_tls) AS_IF([test "$ac_cv_tls" != "none"], AC_DEFINE_UNQUOTED([TLS], $ac_cv_tls, [If the compiler supports a TLS storage class define it to that here]) m4_ifval([$1], [$1], [true]), m4_ifval([$2], [$2], [true]) ) ]) python-igraph-0.8.0/vendor/source/igraph/tools/getversion.sh0000755000076500000240000000062313524616145024503 0ustar tamasstaff00000000000000#! /bin/bash thistag=$(git describe --exact-match --tags HEAD 2>/dev/null || true) if [ -z "${thistag}" ]; then # taghash=$(git rev-list --tags --max-count=1) # tag=$(git describe --tags "$taghash") next_version=$( cd "$( dirname "${BASH_SOURCE[0]}" )" && cat NEXT_VERSION ) current=$(git rev-parse --short HEAD) echo "${next_version}-pre+${current}" else echo "${thistag}" fi python-igraph-0.8.0/vendor/source/igraph/tools/jekyll_header.sh0000755000076500000240000000024113524616145025114 0ustar tamasstaff00000000000000#!/bin/sh cat < """ headtext = """ """ headptext = """ """ def runmake(makefile, target): out = check_output("make -q -C " + os.path.dirname(makefile) + " -f " + os.path.basename(makefile) + " " + target, shell=True) out = out.decode(sys.stdout.encoding or "utf8") out = out.replace("/", "\\") out = re.sub("make.*'.*'", "", out) # msys2 make adds "make[x]: entering ''"" return out def rreplace(s, old, new, occurrence): li = s.rsplit(old, occurrence) return new.join(li) def main(): if len(sys.argv) != 4: print( "Error: need three arguments") sys.exit(1) package = sys.argv[1] projectfile = sys.argv[2] makefile = sys.argv[3] proj = open(projectfile).read() sources = runmake(makefile, "echosources").split() headers = runmake(makefile, "echoheaders").split() headersprivate = runmake(makefile, "echoheadersprivate").split() # lex and bison stuff headers2 = [ rreplace(s, ".y", ".h",1) for s in sources if s[-2:]==".y" ] sources = [ rreplace(s, ".l", ".c", 1) for s in sources ] sources = [ rreplace(s, ".y", ".c", 1) for s in sources ] stext = "\n".join([ srctext % s for s in sources ]) htext = "\n".join([ headtext % s for s in headers ]) hptext = "\n".join([ headptext % s for s in headersprivate + headers2 ]) proj = proj.replace("", stext) proj = proj.replace("", htext + "\n" + hptext) out_file = open(package + "/igraph.vcproj", "w") out_file.write(proj) out_file.close() if __name__ == "__main__": main() python-igraph-0.8.0/vendor/source/igraph/tools/getglpk.sh0000755000076500000240000002174113524616145023757 0ustar tamasstaff00000000000000#! /bin/sh if [ -d ../optional/glpk ]; then echo "GLPK directory '../optional/glpk' already exists, remove it first" # exit 1 fi THIS=`pwd` IDIR=${THIS}/../optional/glpk/ mkdir $IDIR GLPK="http://ftp.gnu.org/gnu/glpk/glpk-4.45.tar.gz" TARGZ=`echo $GLPK | sed 's/^.*\///'` DIR=`echo $TARGZ | sed 's/\.tar\.gz$//'` cd /tmp if [ ! -f $TARGZ ]; then curl -O $GLPK; fi tar xzf $TARGZ #cp -R $DIR/include/*.h $DIR/src/*.{c,h} $DIR/src/amd $DIR/src/colamd \ # $DIR/{README,COPYING} $IDIR cd $THIS SRC=`ls ../optional/glpk/*.h ../optional/glpk/*.c` SRC2=`ls ../optional/glpk/amd/*.h ../optional/glpk/amd/*.c` SRC3=`ls ../optional/glpk/colamd/*.h ../optional/glpk/colamd/*.c` INC=$IDIR/glpk.inc /bin/echo -n "GLPK = " > $INC for i in $SRC; do /bin/echo -n "$i " >>$INC; done for i in $SRC2; do /bin/echo -n "$i " >>$INC; done for i in $SRC3; do /bin/echo -n "$i " >>$INC; done # Need a patch to get rid of an abort() call. We call igraph_error() # instead. patch -p1 -d ../optional/glpk <<-EOF diff -ru glpk.old/glpenv01.c glpk/glpenv01.c --- glpk.old/glpenv01.c 2012-03-30 11:30:58.000000000 -0400 +++ glpk/glpenv01.c 2012-03-30 12:03:54.000000000 -0400 @@ -23,6 +23,7 @@ ***********************************************************************/ #include "glpapi.h" +#include "igraph_error.h" /*********************************************************************** * NAME @@ -126,19 +127,15 @@ { /* not initialized yet; perform initialization */ if (glp_init_env() != 0) { /* initialization failed; display an error message */ - fprintf(stderr, "GLPK initialization failed\n"); - fflush(stderr); - /* and abnormally terminate the program */ - abort(); + IGRAPH_ERROR("GLPK initialization failed", IGRAPH_EGLP); } /* initialization successful; retrieve the pointer */ env = tls_get_ptr(); } /* check if the environment block is valid */ if (env->magic != ENV_MAGIC) - { fprintf(stderr, "Invalid GLPK environment\n"); - fflush(stderr); - abort(); + { + IGRAPH_ERROR("Invalid GLPK environment", IGRAPH_EGLP); } return env; } @@ -200,9 +197,8 @@ if (env == NULL) return 1; /* check if the environment block is valid */ if (env->magic != ENV_MAGIC) - { fprintf(stderr, "Invalid GLPK environment\n"); - fflush(stderr); - abort(); + { + IGRAPH_ERROR("Invalid GLPK environment", IGRAPH_EGLP); } /* close handles to shared libraries */ if (env->h_odbc != NULL) diff -ru glpk.old/glpenv03.c glpk/glpenv03.c --- glpk.old/glpenv03.c 2012-03-30 11:30:58.000000000 -0400 +++ glpk/glpenv03.c 2012-04-02 11:18:42.000000000 -0400 @@ -40,9 +40,9 @@ void glp_printf(const char *fmt, ...) { va_list arg; - va_start(arg, fmt); - xvprintf(fmt, arg); - va_end(arg); + /* va_start(arg, fmt); */ + /* xvprintf(fmt, arg); */ + /* va_end(arg); */ return; } @@ -64,22 +64,22 @@ void glp_vprintf(const char *fmt, va_list arg) { ENV *env = get_env_ptr(); /* if terminal output is disabled, do nothing */ - if (!env->term_out) goto skip; - /* format the output */ - vsprintf(env->term_buf, fmt, arg); - /* pass the output to the user-defined routine */ - if (env->term_hook != NULL) - { if (env->term_hook(env->term_info, env->term_buf) != 0) - goto skip; - } - /* send the output to the terminal */ - fputs(env->term_buf, stdout); - fflush(stdout); - /* copy the output to the text file */ - if (env->tee_file != NULL) - { fputs(env->term_buf, env->tee_file); - fflush(env->tee_file); - } + /* if (!env->term_out) goto skip; */ + /* /\* format the output *\/ */ + /* vsprintf(env->term_buf, fmt, arg); */ + /* /\* pass the output to the user-defined routine *\/ */ + /* if (env->term_hook != NULL) */ + /* { if (env->term_hook(env->term_info, env->term_buf) != 0) */ + /* goto skip; */ + /* } */ + /* /\* send the output to the terminal *\/ */ + /* fputs(env->term_buf, stdout); */ + /* fflush(stdout); */ + /* /\* copy the output to the text file *\/ */ + /* if (env->tee_file != NULL) */ + /* { fputs(env->term_buf, env->tee_file); */ + /* fflush(env->tee_file); */ + /* } */ skip: return; } diff -ru glpk.old/glpenv04.c glpk/glpenv04.c --- glpk.old/glpenv04.c 2012-03-30 11:30:58.000000000 -0400 +++ glpk/glpenv04.c 2012-03-30 11:56:41.000000000 -0400 @@ -23,6 +23,7 @@ ***********************************************************************/ #include "glpapi.h" +#include "igraph_error.h" /*********************************************************************** * NAME @@ -44,14 +45,7 @@ va_list arg; env->term_out = GLP_ON; va_start(arg, fmt); - xvprintf(fmt, arg); - va_end(arg); - xprintf("Error detected in file %s at line %d\n", env->err_file, - env->err_line); - if (env->err_hook != NULL) - env->err_hook(env->err_info); - abort(); - exit(EXIT_FAILURE); + igraph_errorvf(fmt, env->err_file, env->err_line, IGRAPH_EGLP, arg); /* no return */ } diff -ru glpk.old/glpenv07.c glpk/glpenv07.c --- glpk.old/glpenv07.c 2012-03-30 11:30:58.000000000 -0400 +++ glpk/glpenv07.c 2012-03-31 13:21:03.000000000 -0400 @@ -413,13 +413,13 @@ static void *c_fopen(const char *fname, const char *mode) { FILE *fh; - if (strcmp(fname, "/dev/stdin") == 0) - fh = stdin; - else if (strcmp(fname, "/dev/stdout") == 0) - fh = stdout; - else if (strcmp(fname, "/dev/stderr") == 0) - fh = stderr; - else + /* if (strcmp(fname, "/dev/stdin") == 0) */ + /* fh = stdin; */ + /* else if (strcmp(fname, "/dev/stdout") == 0) */ + /* fh = stdout; */ + /* else if (strcmp(fname, "/dev/stderr") == 0) */ + /* fh = stderr; */ + /* else */ fh = fopen(fname, mode); if (fh == NULL) lib_err_msg(strerror(errno)); @@ -484,11 +484,11 @@ static int c_fclose(void *_fh) { FILE *fh = _fh; int ret; - if (fh == stdin) - ret = 0; - else if (fh == stdout || fh == stderr) - fflush(fh), ret = 0; - else + /* if (fh == stdin) */ + /* ret = 0; */ + /* else if (fh == stdout || fh == stderr) */ + /* fflush(fh), ret = 0; */ + /* else */ ret = fclose(fh); if (ret != 0) { lib_err_msg(strerror(errno)); diff -ru glpk.old/glpgmp.c glpk/glpgmp.c --- glpk.old/glpgmp.c 2012-03-30 11:30:58.000000000 -0400 +++ glpk/glpgmp.c 2012-04-01 00:05:13.000000000 -0400 @@ -860,7 +860,7 @@ d[j] = (unsigned char)r->val; } /* output the integer to the stream */ - if (fp == NULL) fp = stdout; + /* if (fp == NULL) fp = stdout; */ if (mpz_sgn(x) < 0) fputc('-', fp), nwr++; for (j = n-1; j >= 0; j--) @@ -1091,7 +1091,7 @@ int nwr; if (!(2 <= base && base <= 36)) xfault("mpq_out_str: base = %d; invalid base\n", base); - if (fp == NULL) fp = stdout; + /* if (fp == NULL) fp = stdout; */ nwr = mpz_out_str(fp, base, &x->p); if (x->q.val == 1 && x->q.ptr == NULL) ; diff -ru glpk.old/glpmpl04.c glpk/glpmpl04.c --- glpk.old/glpmpl04.c 2012-03-30 11:30:58.000000000 -0400 +++ glpk/glpmpl04.c 2012-04-01 00:07:09.000000000 -0400 @@ -341,11 +341,11 @@ void open_output(MPL *mpl, char *file) { xassert(mpl->out_fp == NULL); - if (file == NULL) - { file = ""; - mpl->out_fp = (void *)stdout; - } - else + /* if (file == NULL) */ + /* { file = ""; */ + /* mpl->out_fp = (void *)stdout; */ + /* } */ + /* else */ { mpl->out_fp = xfopen(file, "w"); if (mpl->out_fp == NULL) error(mpl, "unable to create %s - %s", file, xerrmsg()); @@ -362,9 +362,9 @@ void write_char(MPL *mpl, int c) { xassert(mpl->out_fp != NULL); - if (mpl->out_fp == (void *)stdout) - xprintf("%c", c); - else + /* if (mpl->out_fp == (void *)stdout) */ + /* xprintf("%c", c); */ + /* else */ xfprintf(mpl->out_fp, "%c", c); return; } @@ -393,7 +393,7 @@ void flush_output(MPL *mpl) { xassert(mpl->out_fp != NULL); - if (mpl->out_fp != (void *)stdout) + /* if (mpl->out_fp != (void *)stdout) */ { xfflush(mpl->out_fp); if (xferror(mpl->out_fp)) error(mpl, "write error on %s - %s", mpl->out_file, @@ -1410,7 +1410,7 @@ if (mpl->row != NULL) xfree(mpl->row); if (mpl->col != NULL) xfree(mpl->col); if (mpl->in_fp != NULL) xfclose(mpl->in_fp); - if (mpl->out_fp != NULL && mpl->out_fp != (void *)stdout) + if (mpl->out_fp != NULL /* && mpl->out_fp != (void *)stdout */) xfclose(mpl->out_fp); if (mpl->out_file != NULL) xfree(mpl->out_file); if (mpl->prt_fp != NULL) xfclose(mpl->prt_fp); EOF python-igraph-0.8.0/vendor/source/igraph/tools/insert-banner.sh0000755000076500000240000000147313524616145025071 0ustar tamasstaff00000000000000#!/bin/bash ## Insert a banner into a html file, right at the start of if [ $# != "2" -a $# != "3" ] || [ ! -d $1 ] || [ ! -f $2 ]; then printf "Usage: $0 []\n" exit 1 fi banner=$2 exclude=/dev/null if [ -n "$3" ]; then exclude=$3; fi tmpfile=`mktemp -t XXXXXX` function insert { printf "%b" "Doing $1..." if [ -n "$exclude" ] && (echo $1 | grep -q -f $exclude); then printf "%b" " excluded\n" else insert2 $1 > "$tmpfile" cp $tmpfile $1 printf "%b" " DONE\n" fi } function insert2 { cat $1 | sed -n '1h;1!H;${;g;s/\(]*>\)/\1\n/g;p;}' | sed "// { r $banner N }" } find $1 -name "*.html" | while read; do insert $REPLY done rm "$tmpfile" python-igraph-0.8.0/vendor/source/igraph/INSTALL0000644000076500000240000000010313614300625021632 0ustar tamasstaff00000000000000Instructions for installation are provided at https://igraph.org/c/python-igraph-0.8.0/vendor/source/igraph/CHANGELOG.md0000644000076500000240000000745713614300625022435 0ustar tamasstaff00000000000000# igraph C library changelog ## [0.8.0] - 2020-01-29 ### Added #### Trees - `igraph_to_prufer()` and `igraph_from_prufer()` convert labelled trees to/from Prüfer sequences - `igraph_tree_game()` samples uniformly from the set of labelled trees - `igraph_is_tree()` checks if a graph is a tree - `igraph_random_spanning_tree()` picks a spanning tree of a graph uniformly at random - `igraph_random_edge_walk()` returns the indices of edges traversed by a random walk; useful for multigraphs #### Community detection - `igraph_community_fluid_communities()` detects communities based on interacting fluids - `igraph_community_leiden()` detects communities with the Leiden method #### Cliques - `igraph_maximal_cliques_hist()` counts maximal cliques of each size - `igraph_maximal_cliques_callback()` calls a function for each maximal clique - `igraph_clique_size_hist()` counts cliques of each size - `igraph_cliques_callback()` calls a function for each clique - `igraph_weighted_cliques()` finds weighted cliques in graphs with integer vertex weights - `igraph_weighted_clique_number()` computes the weighted clique number - `igraph_largest_weighted_cliques()` finds the largest weighted cliques #### Graph generators - `igraph_hsbm_game()` for a hierarchical stochastic block model - `igraph_hsbm_list_game()` for a more general hierarchical stochastic block model - `igraph_correlated_game()` generates pairs of correlated random graphs by perturbing existing adjacency matrix - `igraph_correlated_pair_game()` generates pairs of correlated random graphs - `igraph_tree_game()` samples uniformly from the set of labelled trees - `igraph_dot_product_game()` generates a random dot product graph - `igraph_realize_degree_sequence()` creates a single graph with a given degree sequence (Havel-Hakimi algorithm) #### Graph embeddings - `igraph_adjacency_spectral_embedding()` and `igraph_laplacian_spectral_embedding()` provide graph embedddings - `igraph_dim_select()` provides dimensionality selection for singular values using profile likelihood #### Other - `igraph_simplify_and_colorize()` encodes edge and self-loop multiplicities into edge and vertex colors - `igraph_bridges()` finds edges whose removal would disconnect a graph - `igraph_vertex_coloring_greedy()` computes a vertex coloring using a greedy algorithm - `igraph_rewire_directed_edges()` randomly rewires only the starting points or only the endpoints of directed edges - Various `igraph_local_scan_*` functions provide local counts and statistics of neighborhoods - `igraph_sample_sphere_surface()` samples points uniformly from the surface of a sphere - `igraph_sample_sphere_volume()` samples points uniformly from the volume of a sphere - `igraph_sample_dirichlet()` samples points from a Dirichlet distribution - `igraph_malloc()`, to be paired with the existing `igraph_free()` ### Changed - `igraph_degree_sequence_game()`: new method added for uniform sampling: `IGRAPH_DEGSEQ_SIMPLE_NO_MULTIPLE_UNIFORM` - `igraph_modularity_matrix()`: removed `membership` argument (PR #1194) - `igraph_avg_nearest_neighbor_degree()`: added `mode` and `neighbor_degree_mode` arguments (PR #1214). - `igraph_get_all_simple_paths()`: added `cutoff` argument (PR #1232). - `igraph_unfold_tree()`: no longer preserves edge ordering of original graph - `igraph_decompose()`: support strongly connected components ### Other - The [Bliss library](http://www.tcs.hut.fi/Software/bliss/) was updated to version 0.73 - igraph now uses the high-performance [Cliquer library](https://users.aalto.fi/~pat/cliquer.html) to find (non-maximal) cliques - Provide proper support for Windows, using `__declspec(dllexport)` and `__declspec(dllimport)` for `DLL`s and static usage by using `#define IGRAPH_STATIC 1`. - Provided integer versions of `dqueue` and `stack` data types. python-igraph-0.8.0/vendor/source/igraph/ChangeLog0000644000076500000240000000007013614300625022356 0ustar tamasstaff00000000000000See CHANGELOG.md for a list of changes between versions.python-igraph-0.8.0/vendor/source/igraph/AUTHORS0000644000076500000240000000023013614300625021652 0ustar tamasstaff00000000000000Gabor Csardi Tamas Nepusz Szabolcs Horvat Vincent Traag python-igraph-0.8.0/vendor/source/igraph/include/0000755000076500000240000000000013617375001022235 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/include/igraph_conversion.h0000644000076500000240000000470513614300625026130 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_CONVERSION_H #define IGRAPH_CONVERSION_H #include "igraph_decls.h" #include "igraph_constants.h" #include "igraph_types.h" #include "igraph_datatype.h" #include "igraph_spmatrix.h" #include "igraph_matrix.h" #include "igraph_sparsemat.h" #include "igraph_attributes.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* Conversion */ /* -------------------------------------------------- */ DECLDIR int igraph_get_adjacency(const igraph_t *graph, igraph_matrix_t *res, igraph_get_adjacency_t type, igraph_bool_t eids); DECLDIR int igraph_get_adjacency_sparse(const igraph_t *graph, igraph_spmatrix_t *res, igraph_get_adjacency_t type); DECLDIR int igraph_get_stochastic(const igraph_t *graph, igraph_matrix_t *matrix, igraph_bool_t column_wise); DECLDIR int igraph_get_stochastic_sparsemat(const igraph_t *graph, igraph_sparsemat_t *sparsemat, igraph_bool_t column_wise); DECLDIR int igraph_get_edgelist(const igraph_t *graph, igraph_vector_t *res, igraph_bool_t bycol); DECLDIR int igraph_to_directed(igraph_t *graph, igraph_to_directed_t flags); DECLDIR int igraph_to_undirected(igraph_t *graph, igraph_to_undirected_t flags, const igraph_attribute_combination_t *edge_comb); DECLDIR int igraph_to_prufer(const igraph_t *graph, igraph_vector_int_t *prufer); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_attributes.h0000644000076500000240000010611013614300625026122 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2005-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef REST_ATTRIBUTES_H #define REST_ATTRIBUTES_H #include "igraph_decls.h" #include "igraph_datatype.h" #include "igraph_types.h" #include "igraph_vector.h" #include "igraph_strvector.h" #include "igraph_vector_ptr.h" #include "igraph_iterators.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* Attributes */ /* -------------------------------------------------- */ /** * \section about_attributes * * Attributes are numbers or strings (or basically any kind * of data) associated with the vertices or edges of a graph, or * with the graph itself. Eg. you may label vertices with symbolic names * or attach numeric weights to the edges of a graph. * * igraph attributes are designed to be flexible and extensible. * In igraph attributes are implemented via an interface abstraction: * any type implementing the functions in the interface, can be used * for storing vertex, edge and graph attributes. This means that * different attribute implementations can be used together with * igraph. This is reasonable: if igraph is used from Python attributes can be * of any Python type, from GNU R all R types are allowed. There is an * experimental attribute implementation to be used when programming * in C, but by default it is currently turned off. * * First we briefly look over how attribute handlers can be * implemented. This is not something a user does every day. It is * rather typically the job of the high level interface writers. (But * it is possible to write an interface without implementing * attributes.) Then we show the experimental C attribute handler. */ /** * \section about_attribute_table * It is possible to attach an attribute handling * interface to \a igraph. This is simply a table of functions, of * type \ref igraph_attribute_table_t. These functions are invoked to * notify the attribute handling code about the structural changes in * a graph. See the documentation of this type for details. * * By default there is no attribute interface attached to \a igraph, * to attach one, call \ref igraph_i_set_attribute_table with your new * table. * */ /** * \typedef igraph_attribute_type_t * The possible types of the attributes. * * Note that this is only the * type communicated by the attribute interface towards igraph * functions. Eg. in the GNU R attribute handler, it is safe to say * that all complex R object attributes are strings, as long as this * interface is able to serialize them into strings. See also \ref * igraph_attribute_table_t. * \enumval IGRAPH_ATTRIBUTE_DEFAULT Currently not used for anything. * \enumval IGRAPH_ATTRIBUTE_NUMERIC Numeric attribute. * \enumval IGRAPH_ATTRIBUTE_BOOLEAN Logical values, true or false. * \enumval IGRAPH_ATTRIBUTE_STRING Attribute that can be converted to * a string. * \enumval IGRAPH_ATTRIBUTE_R_OBJECT An R object. This is usually * ignored by the igraph functions. * \enumval IGRAPH_ATTRIBUTE_PY_OBJECT A Python object. Usually * ignored by the igraph functions. * */ typedef enum { IGRAPH_ATTRIBUTE_DEFAULT = 0, IGRAPH_ATTRIBUTE_NUMERIC = 1, IGRAPH_ATTRIBUTE_BOOLEAN = 5, IGRAPH_ATTRIBUTE_STRING = 2, IGRAPH_ATTRIBUTE_R_OBJECT = 3, IGRAPH_ATTRIBUTE_PY_OBJECT = 4 } igraph_attribute_type_t; typedef struct igraph_attribute_record_t { const char *name; igraph_attribute_type_t type; const void *value; } igraph_attribute_record_t; typedef enum { IGRAPH_ATTRIBUTE_GRAPH = 0, IGRAPH_ATTRIBUTE_VERTEX, IGRAPH_ATTRIBUTE_EDGE } igraph_attribute_elemtype_t; typedef enum { IGRAPH_ATTRIBUTE_COMBINE_IGNORE = 0, IGRAPH_ATTRIBUTE_COMBINE_DEFAULT = 1, IGRAPH_ATTRIBUTE_COMBINE_FUNCTION = 2, IGRAPH_ATTRIBUTE_COMBINE_SUM = 3, IGRAPH_ATTRIBUTE_COMBINE_PROD = 4, IGRAPH_ATTRIBUTE_COMBINE_MIN = 5, IGRAPH_ATTRIBUTE_COMBINE_MAX = 6, IGRAPH_ATTRIBUTE_COMBINE_RANDOM = 7, IGRAPH_ATTRIBUTE_COMBINE_FIRST = 8, IGRAPH_ATTRIBUTE_COMBINE_LAST = 9, IGRAPH_ATTRIBUTE_COMBINE_MEAN = 10, IGRAPH_ATTRIBUTE_COMBINE_MEDIAN = 11, IGRAPH_ATTRIBUTE_COMBINE_CONCAT = 12 } igraph_attribute_combination_type_t; typedef void (*igraph_function_pointer_t)(void); typedef struct igraph_attribute_combination_record_t { const char *name; /* can be NULL, meaning: the rest */ igraph_attribute_combination_type_t type; igraph_function_pointer_t func; } igraph_attribute_combination_record_t; typedef struct igraph_attribute_combination_t { igraph_vector_ptr_t list; } igraph_attribute_combination_t; #define IGRAPH_NO_MORE_ATTRIBUTES ((const char*)0) DECLDIR int igraph_attribute_combination_init(igraph_attribute_combination_t *comb); DECLDIR int igraph_attribute_combination(igraph_attribute_combination_t *comb, ...); DECLDIR void igraph_attribute_combination_destroy(igraph_attribute_combination_t *comb); DECLDIR int igraph_attribute_combination_add(igraph_attribute_combination_t *comb, const char *name, igraph_attribute_combination_type_t type, igraph_function_pointer_t func); DECLDIR int igraph_attribute_combination_remove(igraph_attribute_combination_t *comb, const char *name); DECLDIR int igraph_attribute_combination_query(const igraph_attribute_combination_t *comb, const char *name, igraph_attribute_combination_type_t *type, igraph_function_pointer_t *func); /** * \struct igraph_attribute_table_t * \brief Table of functions to perform operations on attributes * * This type collects the functions defining an attribute handler. * It has the following members: * \member init This function is called whenever a new graph object is * created, right after it is created but before any vertices or * edges are added. It is supposed to set the \c attr member of the \c * igraph_t object. It is expected to return an error code. * \member destroy This function is called whenever the graph object * is destroyed, right before freeing the allocated memory. * \member copy This function is called when copying a graph with \ref * igraph_copy, after the structure of the graph has been already * copied. It is expected to return an error code. * \member add_vertices Called when vertices are added to a * graph, before adding the vertices themselves. * The number of vertices to add is supplied as an * argument. Expected to return an error code. * \member permute_vertices Typically called when a new graph is * created based on an existing one, e.g. if vertices are removed * from a graph. The supplied index vector defines which old vertex * a new vertex corresponds to. Its length must be the same as the * number of vertices in the new graph. * \member combine_vertices This function is called when the creation * of a new graph involves a merge (contraction, etc.) of vertices * from another graph. The function is after the new graph was created. * An argument specifies how several vertices from the old graph map to a * single vertex in the new graph. * \member add_edges Called when new edges have been added. The number * of new edges are supplied as well. It is expected to return an * error code. * \member permute_edges Typically called when a new graph is created and * some of the new edges should carry the attributes of some of the * old edges. The idx vector shows the mapping between the old edges and * the new ones. Its length is the same as the number of edges in the new * graph, and for each edge it gives the id of the old edge (the edge in * the old graph). * \member combine_edges This function is called when the creation * of a new graph involves a merge (contraction, etc.) of edges * from another graph. The function is after the new graph was created. * An argument specifies how several edges from the old graph map to a * single edge in the new graph. * \member get_info Query the attributes of a graph, the names and * types should be returned. * \member has_attr Check whether a graph has the named * graph/vertex/edge attribute. * \member gettype Query the type of a graph/vertex/edge attribute. * \member get_numeric_graph_attr Query a numeric graph attribute. The * value should be placed as the first element of the \p value * vector. * \member get_string_graph_attr Query a string graph attribute. The * value should be placed as the first element of the \p value * string vector. * \member get_bool_graph_attr Query a boolean graph attribute. The * value should be placed as the first element of the \p value * boolean vector. * \member get_numeric_vertex_attr Query a numeric vertex attribute, * for the vertices included in \p vs. * \member get_string_vertex_attr Query a string vertex attribute, * for the vertices included in \p vs. * \member get_bool_vertex_attr Query a boolean vertex attribute, * for the vertices included in \p vs. * \member get_numeric_edge_attr Query a numeric edge attribute, for * the edges included in \p es. * \member get_string_edge_attr Query a string edge attribute, for the * edges included in \p es. * \member get_bool_edge_attr Query a boolean edge attribute, for the * edges included in \p es. * * Note that the get_*_*_attr are allowed to * convert the attributes to numeric or string. E.g. if a vertex attribute * is a GNU R complex data type, then * get_string_vertex_attribute may serialize it * into a string, but this probably makes sense only if * add_vertices is able to deserialize it. */ typedef struct igraph_attribute_table_t { int (*init)(igraph_t *graph, igraph_vector_ptr_t *attr); void (*destroy)(igraph_t *graph); int (*copy)(igraph_t *to, const igraph_t *from, igraph_bool_t ga, igraph_bool_t va, igraph_bool_t ea); int (*add_vertices)(igraph_t *graph, long int nv, igraph_vector_ptr_t *attr); int (*permute_vertices)(const igraph_t *graph, igraph_t *newgraph, const igraph_vector_t *idx); int (*combine_vertices)(const igraph_t *graph, igraph_t *newgraph, const igraph_vector_ptr_t *merges, const igraph_attribute_combination_t *comb); int (*add_edges)(igraph_t *graph, const igraph_vector_t *edges, igraph_vector_ptr_t *attr); int (*permute_edges)(const igraph_t *graph, igraph_t *newgraph, const igraph_vector_t *idx); int (*combine_edges)(const igraph_t *graph, igraph_t *newgraph, const igraph_vector_ptr_t *merges, const igraph_attribute_combination_t *comb); int (*get_info)(const igraph_t *graph, igraph_strvector_t *gnames, igraph_vector_t *gtypes, igraph_strvector_t *vnames, igraph_vector_t *vtypes, igraph_strvector_t *enames, igraph_vector_t *etypes); igraph_bool_t (*has_attr)(const igraph_t *graph, igraph_attribute_elemtype_t type, const char *name); int (*gettype)(const igraph_t *graph, igraph_attribute_type_t *type, igraph_attribute_elemtype_t elemtype, const char *name); int (*get_numeric_graph_attr)(const igraph_t *graph, const char *name, igraph_vector_t *value); int (*get_string_graph_attr)(const igraph_t *graph, const char *name, igraph_strvector_t *value); int (*get_bool_graph_attr)(const igraph_t *igraph, const char *name, igraph_vector_bool_t *value); int (*get_numeric_vertex_attr)(const igraph_t *graph, const char *name, igraph_vs_t vs, igraph_vector_t *value); int (*get_string_vertex_attr)(const igraph_t *graph, const char *name, igraph_vs_t vs, igraph_strvector_t *value); int (*get_bool_vertex_attr)(const igraph_t *graph, const char *name, igraph_vs_t vs, igraph_vector_bool_t *value); int (*get_numeric_edge_attr)(const igraph_t *graph, const char *name, igraph_es_t es, igraph_vector_t *value); int (*get_string_edge_attr)(const igraph_t *graph, const char *name, igraph_es_t es, igraph_strvector_t *value); int (*get_bool_edge_attr)(const igraph_t *graph, const char *name, igraph_es_t es, igraph_vector_bool_t *value); } igraph_attribute_table_t; DECLDIR igraph_attribute_table_t * igraph_i_set_attribute_table(const igraph_attribute_table_t * table); DECLDIR igraph_bool_t igraph_has_attribute_table(void); #define IGRAPH_I_ATTRIBUTE_DESTROY(graph) \ do {if ((graph)->attr) igraph_i_attribute_destroy(graph);} while(0) #define IGRAPH_I_ATTRIBUTE_COPY(to,from,ga,va,ea) do { \ int igraph_i_ret2=0; \ if ((from)->attr) { \ IGRAPH_CHECK(igraph_i_ret2=igraph_i_attribute_copy((to),(from),(ga),(va),(ea))); \ } else { \ (to)->attr = 0; \ } \ if (igraph_i_ret2 != 0) { \ IGRAPH_ERROR("", igraph_i_ret2); \ } \ } while(0) int igraph_i_attribute_init(igraph_t *graph, void *attr); void igraph_i_attribute_destroy(igraph_t *graph); int igraph_i_attribute_copy(igraph_t *to, const igraph_t *from, igraph_bool_t ga, igraph_bool_t va, igraph_bool_t ea); int igraph_i_attribute_add_vertices(igraph_t *graph, long int nv, void *attr); int igraph_i_attribute_permute_vertices(const igraph_t *graph, igraph_t *newgraph, const igraph_vector_t *idx); int igraph_i_attribute_combine_vertices(const igraph_t *graph, igraph_t *newgraph, const igraph_vector_ptr_t *merges, const igraph_attribute_combination_t *comb); int igraph_i_attribute_add_edges(igraph_t *graph, const igraph_vector_t *edges, void *attr); int igraph_i_attribute_permute_edges(const igraph_t *graph, igraph_t *newgraph, const igraph_vector_t *idx); int igraph_i_attribute_combine_edges(const igraph_t *graph, igraph_t *newgraph, const igraph_vector_ptr_t *merges, const igraph_attribute_combination_t *comb); int igraph_i_attribute_get_info(const igraph_t *graph, igraph_strvector_t *gnames, igraph_vector_t *gtypes, igraph_strvector_t *vnames, igraph_vector_t *vtypes, igraph_strvector_t *enames, igraph_vector_t *etypes); igraph_bool_t igraph_i_attribute_has_attr(const igraph_t *graph, igraph_attribute_elemtype_t type, const char *name); int igraph_i_attribute_gettype(const igraph_t *graph, igraph_attribute_type_t *type, igraph_attribute_elemtype_t elemtype, const char *name); int igraph_i_attribute_get_numeric_graph_attr(const igraph_t *graph, const char *name, igraph_vector_t *value); int igraph_i_attribute_get_numeric_vertex_attr(const igraph_t *graph, const char *name, igraph_vs_t vs, igraph_vector_t *value); int igraph_i_attribute_get_numeric_edge_attr(const igraph_t *graph, const char *name, igraph_es_t es, igraph_vector_t *value); int igraph_i_attribute_get_string_graph_attr(const igraph_t *graph, const char *name, igraph_strvector_t *value); int igraph_i_attribute_get_string_vertex_attr(const igraph_t *graph, const char *name, igraph_vs_t vs, igraph_strvector_t *value); int igraph_i_attribute_get_string_edge_attr(const igraph_t *graph, const char *name, igraph_es_t es, igraph_strvector_t *value); int igraph_i_attribute_get_bool_graph_attr(const igraph_t *graph, const char *name, igraph_vector_bool_t *value); int igraph_i_attribute_get_bool_vertex_attr(const igraph_t *graph, const char *name, igraph_vs_t vs, igraph_vector_bool_t *value); int igraph_i_attribute_get_bool_edge_attr(const igraph_t *graph, const char *name, igraph_es_t es, igraph_vector_bool_t *value); /* Experimental attribute handler in C */ extern const igraph_attribute_table_t igraph_cattribute_table; DECLDIR igraph_real_t igraph_cattribute_GAN(const igraph_t *graph, const char *name); DECLDIR igraph_bool_t igraph_cattribute_GAB(const igraph_t *graph, const char *name); DECLDIR const char* igraph_cattribute_GAS(const igraph_t *graph, const char *name); DECLDIR igraph_real_t igraph_cattribute_VAN(const igraph_t *graph, const char *name, igraph_integer_t vid); DECLDIR igraph_bool_t igraph_cattribute_VAB(const igraph_t *graph, const char *name, igraph_integer_t vid); DECLDIR const char* igraph_cattribute_VAS(const igraph_t *graph, const char *name, igraph_integer_t vid); DECLDIR igraph_real_t igraph_cattribute_EAN(const igraph_t *graph, const char *name, igraph_integer_t eid); DECLDIR igraph_bool_t igraph_cattribute_EAB(const igraph_t *graph, const char *name, igraph_integer_t eid); DECLDIR const char* igraph_cattribute_EAS(const igraph_t *graph, const char *name, igraph_integer_t eid); DECLDIR int igraph_cattribute_VANV(const igraph_t *graph, const char *name, igraph_vs_t vids, igraph_vector_t *result); DECLDIR int igraph_cattribute_EANV(const igraph_t *graph, const char *name, igraph_es_t eids, igraph_vector_t *result); DECLDIR int igraph_cattribute_VASV(const igraph_t *graph, const char *name, igraph_vs_t vids, igraph_strvector_t *result); DECLDIR int igraph_cattribute_EASV(const igraph_t *graph, const char *name, igraph_es_t eids, igraph_strvector_t *result); DECLDIR int igraph_cattribute_VABV(const igraph_t *graph, const char *name, igraph_vs_t vids, igraph_vector_bool_t *result); DECLDIR int igraph_cattribute_EABV(const igraph_t *graph, const char *name, igraph_es_t eids, igraph_vector_bool_t *result); DECLDIR int igraph_cattribute_list(const igraph_t *graph, igraph_strvector_t *gnames, igraph_vector_t *gtypes, igraph_strvector_t *vnames, igraph_vector_t *vtypes, igraph_strvector_t *enames, igraph_vector_t *etypes); DECLDIR igraph_bool_t igraph_cattribute_has_attr(const igraph_t *graph, igraph_attribute_elemtype_t type, const char *name); DECLDIR int igraph_cattribute_GAN_set(igraph_t *graph, const char *name, igraph_real_t value); DECLDIR int igraph_cattribute_GAB_set(igraph_t *graph, const char *name, igraph_bool_t value); DECLDIR int igraph_cattribute_GAS_set(igraph_t *graph, const char *name, const char *value); DECLDIR int igraph_cattribute_VAN_set(igraph_t *graph, const char *name, igraph_integer_t vid, igraph_real_t value); DECLDIR int igraph_cattribute_VAB_set(igraph_t *graph, const char *name, igraph_integer_t vid, igraph_bool_t value); DECLDIR int igraph_cattribute_VAS_set(igraph_t *graph, const char *name, igraph_integer_t vid, const char *value); DECLDIR int igraph_cattribute_EAN_set(igraph_t *graph, const char *name, igraph_integer_t eid, igraph_real_t value); DECLDIR int igraph_cattribute_EAB_set(igraph_t *graph, const char *name, igraph_integer_t eid, igraph_bool_t value); DECLDIR int igraph_cattribute_EAS_set(igraph_t *graph, const char *name, igraph_integer_t eid, const char *value); DECLDIR int igraph_cattribute_VAN_setv(igraph_t *graph, const char *name, const igraph_vector_t *v); DECLDIR int igraph_cattribute_VAB_setv(igraph_t *graph, const char *name, const igraph_vector_bool_t *v); DECLDIR int igraph_cattribute_VAS_setv(igraph_t *graph, const char *name, const igraph_strvector_t *sv); DECLDIR int igraph_cattribute_EAN_setv(igraph_t *graph, const char *name, const igraph_vector_t *v); DECLDIR int igraph_cattribute_EAB_setv(igraph_t *graph, const char *name, const igraph_vector_bool_t *v); DECLDIR int igraph_cattribute_EAS_setv(igraph_t *graph, const char *name, const igraph_strvector_t *sv); DECLDIR void igraph_cattribute_remove_g(igraph_t *graph, const char *name); DECLDIR void igraph_cattribute_remove_v(igraph_t *graph, const char *name); DECLDIR void igraph_cattribute_remove_e(igraph_t *graph, const char *name); DECLDIR void igraph_cattribute_remove_all(igraph_t *graph, igraph_bool_t g, igraph_bool_t v, igraph_bool_t e); /** * \define GAN * Query a numeric graph attribute. * * This is shorthand for \ref igraph_cattribute_GAN(). * \param graph The graph. * \param n The name of the attribute. * \return The value of the attribute. */ #define GAN(graph,n) (igraph_cattribute_GAN((graph), (n))) /** * \define GAB * Query a boolean graph attribute. * * This is shorthand for \ref igraph_cattribute_GAB(). * \param graph The graph. * \param n The name of the attribute. * \return The value of the attribute. */ #define GAB(graph,n) (igraph_cattribute_GAB((graph), (n))) /** * \define GAS * Query a string graph attribute. * * This is shorthand for \ref igraph_cattribute_GAS(). * \param graph The graph. * \param n The name of the attribute. * \return The value of the attribute. */ #define GAS(graph,n) (igraph_cattribute_GAS((graph), (n))) /** * \define VAN * Query a numeric vertex attribute. * * This is shorthand for \ref igraph_cattribute_VAN(). * \param graph The graph. * \param n The name of the attribute. * \param v The id of the vertex. * \return The value of the attribute. */ #define VAN(graph,n,v) (igraph_cattribute_VAN((graph), (n), (v))) /** * \define VAB * Query a boolean vertex attribute. * * This is shorthand for \ref igraph_cattribute_VAB(). * \param graph The graph. * \param n The name of the attribute. * \param v The id of the vertex. * \return The value of the attribute. */ #define VAB(graph,n,v) (igraph_cattribute_VAB((graph), (n), (v))) /** * \define VAS * Query a string vertex attribute. * * This is shorthand for \ref igraph_cattribute_VAS(). * \param graph The graph. * \param n The name of the attribute. * \param v The id of the vertex. * \return The value of the attribute. */ #define VAS(graph,n,v) (igraph_cattribute_VAS((graph), (n), (v))) /** * \define VANV * Query a numeric vertex attribute for all vertices. * * This is a shorthand for \ref igraph_cattribute_VANV(). * \param graph The graph. * \param n The name of the attribute. * \param vec Pointer to an initialized vector, the result is * stored here. It will be resized, if needed. * \return Error code. */ #define VANV(graph,n,vec) (igraph_cattribute_VANV((graph),(n), \ igraph_vss_all(), (vec))) /** * \define VABV * Query a boolean vertex attribute for all vertices. * * This is a shorthand for \ref igraph_cattribute_VABV(). * \param graph The graph. * \param n The name of the attribute. * \param vec Pointer to an initialized boolean vector, the result is * stored here. It will be resized, if needed. * \return Error code. */ #define VABV(graph,n,vec) (igraph_cattribute_VABV((graph),(n), \ igraph_vss_all(), (vec))) /** * \define VASV * Query a string vertex attribute for all vertices. * * This is a shorthand for \ref igraph_cattribute_VASV(). * \param graph The graph. * \param n The name of the attribute. * \param vec Pointer to an initialized string vector, the result is * stored here. It will be resized, if needed. * \return Error code. */ #define VASV(graph,n,vec) (igraph_cattribute_VASV((graph),(n), \ igraph_vss_all(), (vec))) /** * \define EAN * Query a numeric edge attribute. * * This is shorthand for \ref igraph_cattribute_EAN(). * \param graph The graph. * \param n The name of the attribute. * \param e The id of the edge. * \return The value of the attribute. */ #define EAN(graph,n,e) (igraph_cattribute_EAN((graph), (n), (e))) /** * \define EAB * Query a boolean edge attribute. * * This is shorthand for \ref igraph_cattribute_EAB(). * \param graph The graph. * \param n The name of the attribute. * \param e The id of the edge. * \return The value of the attribute. */ #define EAB(graph,n,e) (igraph_cattribute_EAB((graph), (n), (e))) /** * \define EAS * Query a string edge attribute. * * This is shorthand for \ref igraph_cattribute_EAS(). * \param graph The graph. * \param n The name of the attribute. * \param e The id of the edge. * \return The value of the attribute. */ #define EAS(graph,n,e) (igraph_cattribute_EAS((graph), (n), (e))) /** * \define EANV * Query a numeric edge attribute for all edges. * * This is a shorthand for \ref igraph_cattribute_EANV(). * \param graph The graph. * \param n The name of the attribute. * \param vec Pointer to an initialized vector, the result is * stored here. It will be resized, if needed. * \return Error code. */ #define EANV(graph,n,vec) (igraph_cattribute_EANV((graph),(n), \ igraph_ess_all(IGRAPH_EDGEORDER_ID), (vec))) /** * \define EABV * Query a boolean edge attribute for all edges. * * This is a shorthand for \ref igraph_cattribute_EABV(). * \param graph The graph. * \param n The name of the attribute. * \param vec Pointer to an initialized vector, the result is * stored here. It will be resized, if needed. * \return Error code. */ #define EABV(graph,n,vec) (igraph_cattribute_EABV((graph),(n), \ igraph_ess_all(IGRAPH_EDGEORDER_ID), (vec))) /** * \define EASV * Query a string edge attribute for all edges. * * This is a shorthand for \ref igraph_cattribute_EASV(). * \param graph The graph. * \param n The name of the attribute. * \param vec Pointer to an initialized string vector, the result is * stored here. It will be resized, if needed. * \return Error code. */ #define EASV(graph,n,vec) (igraph_cattribute_EASV((graph),(n), \ igraph_ess_all(IGRAPH_EDGEORDER_ID), (vec))) /** * \define SETGAN * Set a numeric graph attribute * * This is a shorthand for \ref igraph_cattribute_GAN_set(). * \param graph The graph. * \param n The name of the attribute. * \param value The new value of the attribute. * \return Error code. */ #define SETGAN(graph,n,value) (igraph_cattribute_GAN_set((graph),(n),(value))) /** * \define SETGAB * Set a boolean graph attribute * * This is a shorthand for \ref igraph_cattribute_GAB_set(). * \param graph The graph. * \param n The name of the attribute. * \param value The new value of the attribute. * \return Error code. */ #define SETGAB(graph,n,value) (igraph_cattribute_GAB_set((graph),(n),(value))) /** * \define SETGAS * Set a string graph attribute * * This is a shorthand for \ref igraph_cattribute_GAS_set(). * \param graph The graph. * \param n The name of the attribute. * \param value The new value of the attribute. * \return Error code. */ #define SETGAS(graph,n,value) (igraph_cattribute_GAS_set((graph),(n),(value))) /** * \define SETVAN * Set a numeric vertex attribute * * This is a shorthand for \ref igraph_cattribute_VAN_set(). * \param graph The graph. * \param n The name of the attribute. * \param vid Ids of the vertices to set. * \param value The new value of the attribute. * \return Error code. */ #define SETVAN(graph,n,vid,value) (igraph_cattribute_VAN_set((graph),(n),(vid),(value))) /** * \define SETVAB * Set a boolean vertex attribute * * This is a shorthand for \ref igraph_cattribute_VAB_set(). * \param graph The graph. * \param n The name of the attribute. * \param vid Ids of the vertices to set. * \param value The new value of the attribute. * \return Error code. */ #define SETVAB(graph,n,vid,value) (igraph_cattribute_VAB_set((graph),(n),(vid),(value))) /** * \define SETVAS * Set a string vertex attribute * * This is a shorthand for \ref igraph_cattribute_VAS_set(). * \param graph The graph. * \param n The name of the attribute. * \param vid Ids of the vertices to set. * \param value The new value of the attribute. * \return Error code. */ #define SETVAS(graph,n,vid,value) (igraph_cattribute_VAS_set((graph),(n),(vid),(value))) /** * \define SETEAN * Set a numeric edge attribute * * This is a shorthand for \ref igraph_cattribute_EAN_set(). * \param graph The graph. * \param n The name of the attribute. * \param eid Ids of the edges to set. * \param value The new value of the attribute. * \return Error code. */ #define SETEAN(graph,n,eid,value) (igraph_cattribute_EAN_set((graph),(n),(eid),(value))) /** * \define SETEAB * Set a boolean edge attribute * * This is a shorthand for \ref igraph_cattribute_EAB_set(). * \param graph The graph. * \param n The name of the attribute. * \param eid Ids of the edges to set. * \param value The new value of the attribute. * \return Error code. */ #define SETEAB(graph,n,eid,value) (igraph_cattribute_EAB_set((graph),(n),(eid),(value))) /** * \define SETEAS * Set a string edge attribute * * This is a shorthand for \ref igraph_cattribute_EAS_set(). * \param graph The graph. * \param n The name of the attribute. * \param eid Ids of the edges to set. * \param value The new value of the attribute. * \return Error code. */ #define SETEAS(graph,n,eid,value) (igraph_cattribute_EAS_set((graph),(n),(eid),(value))) /** * \define SETVANV * Set a numeric vertex attribute for all vertices * * This is a shorthand for \ref igraph_cattribute_VAN_setv(). * \param graph The graph. * \param n The name of the attribute. * \param v Vector containing the new values of the attributes. * \return Error code. */ #define SETVANV(graph,n,v) (igraph_cattribute_VAN_setv((graph),(n),(v))) /** * \define SETVABV * Set a boolean vertex attribute for all vertices * * This is a shorthand for \ref igraph_cattribute_VAB_setv(). * \param graph The graph. * \param n The name of the attribute. * \param v Vector containing the new values of the attributes. * \return Error code. */ #define SETVABV(graph,n,v) (igraph_cattribute_VAB_setv((graph),(n),(v))) /** * \define SETVASV * Set a string vertex attribute for all vertices * * This is a shorthand for \ref igraph_cattribute_VAS_setv(). * \param graph The graph. * \param n The name of the attribute. * \param v Vector containing the new values of the attributes. * \return Error code. */ #define SETVASV(graph,n,v) (igraph_cattribute_VAS_setv((graph),(n),(v))) /** * \define SETEANV * Set a numeric edge attribute for all vertices * * This is a shorthand for \ref igraph_cattribute_EAN_setv(). * \param graph The graph. * \param n The name of the attribute. * \param v Vector containing the new values of the attributes. */ #define SETEANV(graph,n,v) (igraph_cattribute_EAN_setv((graph),(n),(v))) /** * \define SETEABV * Set a boolean edge attribute for all vertices * * This is a shorthand for \ref igraph_cattribute_EAB_setv(). * \param graph The graph. * \param n The name of the attribute. * \param v Vector containing the new values of the attributes. */ #define SETEABV(graph,n,v) (igraph_cattribute_EAB_setv((graph),(n),(v))) /** * \define SETEASV * Set a string edge attribute for all vertices * * This is a shorthand for \ref igraph_cattribute_EAS_setv(). * \param graph The graph. * \param n The name of the attribute. * \param v Vector containing the new values of the attributes. */ #define SETEASV(graph,n,v) (igraph_cattribute_EAS_setv((graph),(n),(v))) /** * \define DELGA * Remove a graph attribute. * * A shorthand for \ref igraph_cattribute_remove_g(). * \param graph The graph. * \param n The name of the attribute to remove. */ #define DELGA(graph,n) (igraph_cattribute_remove_g((graph),(n))) /** * \define DELVA * Remove a vertex attribute. * * A shorthand for \ref igraph_cattribute_remove_v(). * \param graph The graph. * \param n The name of the attribute to remove. */ #define DELVA(graph,n) (igraph_cattribute_remove_v((graph),(n))) /** * \define DELEA * Remove an edge attribute. * * A shorthand for \ref igraph_cattribute_remove_e(). * \param graph The graph. * \param n The name of the attribute to remove. */ #define DELEA(graph,n) (igraph_cattribute_remove_e((graph),(n))) /** * \define DELGAS * Remove all graph attributes. * * Calls \ref igraph_cattribute_remove_all(). * \param graph The graph. */ #define DELGAS(graph) (igraph_cattribute_remove_all((graph),1,0,0)) /** * \define DELVAS * Remove all vertex attributes. * * Calls \ref igraph_cattribute_remove_all(). * \param graph The graph. */ #define DELVAS(graph) (igraph_cattribute_remove_all((graph),0,1,0)) /** * \define DELEAS * Remove all edge attributes. * * Calls \ref igraph_cattribute_remove_all(). * \param graph The graph. */ #define DELEAS(graph) (igraph_cattribute_remove_all((graph),0,0,1)) /** * \define DELALL * Remove all attributes. * * All graph, vertex and edges attributes will be removed. * Calls \ref igraph_cattribute_remove_all(). * \param graph The graph. */ #define DELALL(graph) (igraph_cattribute_remove_all((graph),1,1,1)) __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_coloring.h0000644000076500000240000000112113524616144025552 0ustar tamasstaff00000000000000#ifndef IGRAPH_COLORING_H #define IGRAPH_COLORING_H #include "igraph_datatype.h" __BEGIN_DECLS /** * \typedef igraph_coloring_greedy_t * Ordering heuristics for igraph_vertex_coloring_greedy * * \enumval IGRAPH_COLORING_GREEDY_COLORED_NEIGHBORS Choose vertex with largest number of already colored neighbors. * */ typedef enum { IGRAPH_COLORING_GREEDY_COLORED_NEIGHBORS = 0 } igraph_coloring_greedy_t; DECLDIR int igraph_vertex_coloring_greedy(const igraph_t *graph, igraph_vector_int_t *colors, igraph_coloring_greedy_t heuristic); __END_DECLS #endif /* IGRAPH_COLORING_H */ python-igraph-0.8.0/vendor/source/igraph/include/igraph_scg.h0000644000076500000240000001357413614300625024523 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_SCG_H #define IGRAPH_SCG_H #include "igraph_types.h" #include "igraph_vector.h" #include "igraph_matrix.h" #include "igraph_sparsemat.h" __BEGIN_DECLS typedef enum { IGRAPH_SCG_SYMMETRIC = 1, IGRAPH_SCG_LAPLACIAN = 2, IGRAPH_SCG_STOCHASTIC = 3 } igraph_scg_matrix_t; typedef enum { IGRAPH_SCG_OPTIMUM = 1, IGRAPH_SCG_INTERV_KM = 2, IGRAPH_SCG_INTERV = 3, IGRAPH_SCG_EXACT = 4 } igraph_scg_algorithm_t; typedef enum { IGRAPH_SCG_NORM_ROW = 1, IGRAPH_SCG_NORM_COL = 2 } igraph_scg_norm_t; typedef enum { IGRAPH_SCG_DIRECTION_DEFAULT = 1, IGRAPH_SCG_DIRECTION_LEFT = 2, IGRAPH_SCG_DIRECTION_RIGHT = 3 } igraph_scg_direction_t; int igraph_scg_grouping(const igraph_matrix_t *V, igraph_vector_t *groups, igraph_integer_t nt, const igraph_vector_t *nt_vec, igraph_scg_matrix_t mtype, igraph_scg_algorithm_t algo, const igraph_vector_t *p, igraph_integer_t maxiter); int igraph_scg_semiprojectors(const igraph_vector_t *groups, igraph_scg_matrix_t mtype, igraph_matrix_t *L, igraph_matrix_t *R, igraph_sparsemat_t *Lsparse, igraph_sparsemat_t *Rsparse, const igraph_vector_t *p, igraph_scg_norm_t norm); int igraph_scg_norm_eps(const igraph_matrix_t *V, const igraph_vector_t *groups, igraph_vector_t *eps, igraph_scg_matrix_t mtype, const igraph_vector_t *p, igraph_scg_norm_t norm); int igraph_scg_adjacency(const igraph_t *graph, const igraph_matrix_t *matrix, const igraph_sparsemat_t *sparsemat, const igraph_vector_t *ev, igraph_integer_t nt, const igraph_vector_t *nt_vec, igraph_scg_algorithm_t algo, igraph_vector_t *values, igraph_matrix_t *vectors, igraph_vector_t *groups, igraph_bool_t use_arpack, igraph_integer_t maxiter, igraph_t *scg_graph, igraph_matrix_t *scg_matrix, igraph_sparsemat_t *scg_sparsemat, igraph_matrix_t *L, igraph_matrix_t *R, igraph_sparsemat_t *Lsparse, igraph_sparsemat_t *Rsparse); int igraph_scg_stochastic(const igraph_t *graph, const igraph_matrix_t *matrix, const igraph_sparsemat_t *sparsemat, const igraph_vector_t *ev, igraph_integer_t nt, const igraph_vector_t *nt_vec, igraph_scg_algorithm_t algo, igraph_scg_norm_t norm, igraph_vector_complex_t *values, igraph_matrix_complex_t *vectors, igraph_vector_t *groups, igraph_vector_t *p, igraph_bool_t use_arpack, igraph_integer_t maxiter, igraph_t *scg_graph, igraph_matrix_t *scg_matrix, igraph_sparsemat_t *scg_sparsemat, igraph_matrix_t *L, igraph_matrix_t *R, igraph_sparsemat_t *Lsparse, igraph_sparsemat_t *Rsparse); int igraph_scg_laplacian(const igraph_t *graph, const igraph_matrix_t *matrix, const igraph_sparsemat_t *sparsemat, const igraph_vector_t *ev, igraph_integer_t nt, const igraph_vector_t *nt_vec, igraph_scg_algorithm_t algo, igraph_scg_norm_t norm, igraph_scg_direction_t direction, igraph_vector_complex_t *values, igraph_matrix_complex_t *vectors, igraph_vector_t *groups, igraph_bool_t use_arpack, igraph_integer_t maxiter, igraph_t *scg_graph, igraph_matrix_t *scg_matrix, igraph_sparsemat_t *scg_sparsemat, igraph_matrix_t *L, igraph_matrix_t *R, igraph_sparsemat_t *Lsparse, igraph_sparsemat_t *Rsparse); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_decls.h0000644000076500000240000000124713614300625025033 0ustar tamasstaff00000000000000#undef __BEGIN_DECLS #undef __END_DECLS #ifdef __cplusplus #define __BEGIN_DECLS extern "C" { #define __END_DECLS } #else #define __BEGIN_DECLS /* empty */ #define __END_DECLS /* empty */ #endif #undef DECLDIR #if defined (_WIN32) || defined (WIN32) || defined (_WIN64) || defined (WIN64) #if defined (__MINGW32__) || defined (__CYGWIN32__) #define DECLDIR /**/ #else #ifdef IGRAPH_EXPORTS #define DECLDIR __declspec(dllexport) #elif defined(IGRAPH_STATIC) #define DECLDIR /**/ #else #define DECLDIR __declspec(dllimport) #endif #endif #else #define DECLDIR /**/ #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_centrality.h0000644000076500000240000002150413614300625026115 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_CENTRALITY_H #define IGRAPH_CENTRALITY_H #include "igraph_decls.h" #include "igraph_constants.h" #include "igraph_types.h" #include "igraph_datatype.h" #include "igraph_iterators.h" #include "igraph_arpack.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* Centrality */ /* -------------------------------------------------- */ DECLDIR int igraph_closeness(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, igraph_neimode_t mode, const igraph_vector_t *weights, igraph_bool_t normalized); DECLDIR int igraph_closeness_estimate(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, igraph_neimode_t mode, igraph_real_t cutoff, const igraph_vector_t *weights, igraph_bool_t normalized); DECLDIR int igraph_betweenness(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, igraph_bool_t directed, const igraph_vector_t *weights, igraph_bool_t nobigint); DECLDIR int igraph_betweenness_estimate(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, igraph_bool_t directed, igraph_real_t cutoff, const igraph_vector_t *weights, igraph_bool_t nobigint); DECLDIR int igraph_edge_betweenness(const igraph_t *graph, igraph_vector_t *result, igraph_bool_t directed, const igraph_vector_t *weigths); DECLDIR int igraph_edge_betweenness_estimate(const igraph_t *graph, igraph_vector_t *result, igraph_bool_t directed, igraph_real_t cutoff, const igraph_vector_t *weights); DECLDIR int igraph_pagerank_old(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, igraph_bool_t directed, igraph_integer_t niter, igraph_real_t eps, igraph_real_t damping, igraph_bool_t old); /** * \typedef igraph_pagerank_algo_t * \brief PageRank algorithm implementation * * Algorithms to calculate PageRank. * \enumval IGRAPH_PAGERANK_ALGO_POWER Use a simple power iteration, * as it was implemented before igraph version 0.5. * \enumval IGRAPH_PAGERANK_ALGO_ARPACK Use the ARPACK library, this * was the PageRank implementation in igraph from version 0.5, until * version 0.7. * \enumval IGRAPH_PAGERANK_ALGO_PRPACK Use the PRPACK * library. Currently this implementation is recommended. */ typedef enum { IGRAPH_PAGERANK_ALGO_POWER = 0, IGRAPH_PAGERANK_ALGO_ARPACK = 1, IGRAPH_PAGERANK_ALGO_PRPACK = 2 } igraph_pagerank_algo_t; /** * \struct igraph_pagerank_power_options_t * \brief Options for the power method * * \member niter The number of iterations to perform, integer. * \member eps The algorithm will consider the calculation as complete * if the difference of values between iterations change * less than this value for every vertex. */ typedef struct igraph_pagerank_power_options_t { igraph_integer_t niter; igraph_real_t eps; } igraph_pagerank_power_options_t; DECLDIR int igraph_pagerank(const igraph_t *graph, igraph_pagerank_algo_t algo, igraph_vector_t *vector, igraph_real_t *value, const igraph_vs_t vids, igraph_bool_t directed, igraph_real_t damping, const igraph_vector_t *weights, void *options); DECLDIR int igraph_personalized_pagerank(const igraph_t *graph, igraph_pagerank_algo_t algo, igraph_vector_t *vector, igraph_real_t *value, const igraph_vs_t vids, igraph_bool_t directed, igraph_real_t damping, igraph_vector_t *reset, const igraph_vector_t *weights, void *options); DECLDIR int igraph_personalized_pagerank_vs(const igraph_t *graph, igraph_pagerank_algo_t algo, igraph_vector_t *vector, igraph_real_t *value, const igraph_vs_t vids, igraph_bool_t directed, igraph_real_t damping, igraph_vs_t reset_vids, const igraph_vector_t *weights, void *options); DECLDIR int igraph_eigenvector_centrality(const igraph_t *graph, igraph_vector_t *vector, igraph_real_t *value, igraph_bool_t directed, igraph_bool_t scale, const igraph_vector_t *weights, igraph_arpack_options_t *options); DECLDIR int igraph_hub_score(const igraph_t *graph, igraph_vector_t *vector, igraph_real_t *value, igraph_bool_t scale, const igraph_vector_t *weights, igraph_arpack_options_t *options); DECLDIR int igraph_authority_score(const igraph_t *graph, igraph_vector_t *vector, igraph_real_t *value, igraph_bool_t scale, const igraph_vector_t *weights, igraph_arpack_options_t *options); DECLDIR int igraph_constraint(const igraph_t *graph, igraph_vector_t *res, igraph_vs_t vids, const igraph_vector_t *weights); DECLDIR int igraph_strength(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, igraph_neimode_t mode, igraph_bool_t loops, const igraph_vector_t *weights); DECLDIR int igraph_convergence_degree(const igraph_t *graph, igraph_vector_t *result, igraph_vector_t *ins, igraph_vector_t *outs); DECLDIR int igraph_sort_vertex_ids_by_degree(const igraph_t *graph, igraph_vector_t *outvids, igraph_vs_t vids, igraph_neimode_t mode, igraph_bool_t loops, igraph_order_t order, igraph_bool_t only_indices); DECLDIR igraph_real_t igraph_centralization(const igraph_vector_t *scores, igraph_real_t theoretical_max, igraph_bool_t normalized); DECLDIR int igraph_centralization_degree(const igraph_t *graph, igraph_vector_t *res, igraph_neimode_t mode, igraph_bool_t loops, igraph_real_t *centralization, igraph_real_t *theoretical_max, igraph_bool_t normalized); DECLDIR int igraph_centralization_degree_tmax(const igraph_t *graph, igraph_integer_t nodes, igraph_neimode_t mode, igraph_bool_t loops, igraph_real_t *res); DECLDIR int igraph_centralization_betweenness(const igraph_t *graph, igraph_vector_t *res, igraph_bool_t directed, igraph_bool_t nobigint, igraph_real_t *centralization, igraph_real_t *theoretical_max, igraph_bool_t normalized); DECLDIR int igraph_centralization_betweenness_tmax(const igraph_t *graph, igraph_integer_t nodes, igraph_bool_t directed, igraph_real_t *res); DECLDIR int igraph_centralization_closeness(const igraph_t *graph, igraph_vector_t *res, igraph_neimode_t mode, igraph_real_t *centralization, igraph_real_t *theoretical_max, igraph_bool_t normalized); DECLDIR int igraph_centralization_closeness_tmax(const igraph_t *graph, igraph_integer_t nodes, igraph_neimode_t mode, igraph_real_t *res); DECLDIR int igraph_centralization_eigenvector_centrality( const igraph_t *graph, igraph_vector_t *vector, igraph_real_t *value, igraph_bool_t directed, igraph_bool_t scale, igraph_arpack_options_t *options, igraph_real_t *centralization, igraph_real_t *theoretical_max, igraph_bool_t normalized); DECLDIR int igraph_centralization_eigenvector_centrality_tmax( const igraph_t *graph, igraph_integer_t nodes, igraph_bool_t directed, igraph_bool_t scale, igraph_real_t *res); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_vector_type.h0000644000076500000240000000205013614300625026275 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2013 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ /** * Vector, dealing with arrays efficiently. * \ingroup types */ typedef struct TYPE(igraph_vector) { BASE* stor_begin; BASE* stor_end; BASE* end; } TYPE(igraph_vector); python-igraph-0.8.0/vendor/source/igraph/include/igraph_paths.h0000644000076500000240000001455413614300625025065 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_PATHS_H #define IGRAPH_PATHS_H #include "igraph_decls.h" #include "igraph_constants.h" #include "igraph_types.h" #include "igraph_vector.h" #include "igraph_vector_ptr.h" #include "igraph_matrix.h" #include "igraph_iterators.h" __BEGIN_DECLS DECLDIR int igraph_diameter(const igraph_t *graph, igraph_integer_t *res, igraph_integer_t *from, igraph_integer_t *to, igraph_vector_t *path, igraph_bool_t directed, igraph_bool_t unconn); DECLDIR int igraph_diameter_dijkstra(const igraph_t *graph, const igraph_vector_t *weights, igraph_real_t *pres, igraph_integer_t *pfrom, igraph_integer_t *pto, igraph_vector_t *path, igraph_bool_t directed, igraph_bool_t unconn); DECLDIR int igraph_shortest_paths(const igraph_t *graph, igraph_matrix_t *res, const igraph_vs_t from, const igraph_vs_t to, igraph_neimode_t mode); DECLDIR int igraph_get_shortest_paths(const igraph_t *graph, igraph_vector_ptr_t *vertices, igraph_vector_ptr_t *edges, igraph_integer_t from, const igraph_vs_t to, igraph_neimode_t mode, igraph_vector_long_t *predecessors, igraph_vector_long_t *inbound_edges); DECLDIR int igraph_get_shortest_path(const igraph_t *graph, igraph_vector_t *vertices, igraph_vector_t *edges, igraph_integer_t from, igraph_integer_t to, igraph_neimode_t mode); DECLDIR int igraph_get_all_shortest_paths(const igraph_t *graph, igraph_vector_ptr_t *res, igraph_vector_t *nrgeo, igraph_integer_t from, const igraph_vs_t to, igraph_neimode_t mode); DECLDIR int igraph_shortest_paths_dijkstra(const igraph_t *graph, igraph_matrix_t *res, const igraph_vs_t from, const igraph_vs_t to, const igraph_vector_t *weights, igraph_neimode_t mode); DECLDIR int igraph_shortest_paths_bellman_ford(const igraph_t *graph, igraph_matrix_t *res, const igraph_vs_t from, const igraph_vs_t to, const igraph_vector_t *weights, igraph_neimode_t mode); DECLDIR int igraph_get_shortest_paths_dijkstra(const igraph_t *graph, igraph_vector_ptr_t *vertices, igraph_vector_ptr_t *edges, igraph_integer_t from, igraph_vs_t to, const igraph_vector_t *weights, igraph_neimode_t mode, igraph_vector_long_t *predecessors, igraph_vector_long_t *inbound_edges); DECLDIR int igraph_get_shortest_path_dijkstra(const igraph_t *graph, igraph_vector_t *vertices, igraph_vector_t *edges, igraph_integer_t from, igraph_integer_t to, const igraph_vector_t *weights, igraph_neimode_t mode); DECLDIR int igraph_get_all_shortest_paths_dijkstra(const igraph_t *graph, igraph_vector_ptr_t *res, igraph_vector_t *nrgeo, igraph_integer_t from, igraph_vs_t to, const igraph_vector_t *weights, igraph_neimode_t mode); DECLDIR int igraph_shortest_paths_johnson(const igraph_t *graph, igraph_matrix_t *res, const igraph_vs_t from, const igraph_vs_t to, const igraph_vector_t *weights); DECLDIR int igraph_average_path_length(const igraph_t *graph, igraph_real_t *res, igraph_bool_t directed, igraph_bool_t unconn); DECLDIR int igraph_path_length_hist(const igraph_t *graph, igraph_vector_t *res, igraph_real_t *unconnected, igraph_bool_t directed); DECLDIR int igraph_eccentricity(const igraph_t *graph, igraph_vector_t *res, igraph_vs_t vids, igraph_neimode_t mode); DECLDIR int igraph_radius(const igraph_t *graph, igraph_real_t *radius, igraph_neimode_t mode); DECLDIR int igraph_get_all_simple_paths(const igraph_t *graph, igraph_vector_int_t *res, igraph_integer_t from, const igraph_vs_t to, igraph_integer_t cutoff, igraph_neimode_t mode); DECLDIR int igraph_random_walk(const igraph_t *graph, igraph_vector_t *walk, igraph_integer_t start, igraph_neimode_t mode, igraph_integer_t steps, igraph_random_walk_stuck_t stuck); DECLDIR int igraph_random_edge_walk(const igraph_t *graph, const igraph_vector_t *weights, igraph_vector_t *edgewalk, igraph_integer_t start, igraph_neimode_t mode, igraph_integer_t steps, igraph_random_walk_stuck_t stuck); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_stack.h0000644000076500000240000000401013614300625025035 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_STACK_H #define IGRAPH_STACK_H #include "igraph_decls.h" #include "igraph_types.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* Plain stack */ /* -------------------------------------------------- */ #define BASE_IGRAPH_REAL #include "igraph_pmt.h" #include "igraph_stack_pmt.h" #include "igraph_pmt_off.h" #undef BASE_IGRAPH_REAL #define BASE_LONG #include "igraph_pmt.h" #include "igraph_stack_pmt.h" #include "igraph_pmt_off.h" #undef BASE_LONG #define BASE_INT #include "igraph_pmt.h" #include "igraph_stack_pmt.h" #include "igraph_pmt_off.h" #undef BASE_INT #define BASE_CHAR #include "igraph_pmt.h" #include "igraph_stack_pmt.h" #include "igraph_pmt_off.h" #undef BASE_CHAR #define BASE_BOOL #include "igraph_pmt.h" #include "igraph_stack_pmt.h" #include "igraph_pmt_off.h" #undef BASE_BOOL #define BASE_PTR #include "igraph_pmt.h" #include "igraph_stack_pmt.h" #include "igraph_pmt_off.h" #undef BASE_PTR #define IGRAPH_STACK_NULL { 0,0,0 } void igraph_stack_ptr_free_all(igraph_stack_ptr_t* s); void igraph_stack_ptr_destroy_all(igraph_stack_ptr_t* s); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_scan.h0000644000076500000240000000506013614300625024662 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2013 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_SCAN_H #define IGRAPH_SCAN_H #include "igraph_decls.h" #include "igraph_datatype.h" #include "igraph_arpack.h" #include "igraph_constants.h" #include "igraph_vector_ptr.h" __BEGIN_DECLS DECLDIR int igraph_local_scan_0(const igraph_t *graph, igraph_vector_t *res, const igraph_vector_t *weights, igraph_neimode_t mode); DECLDIR int igraph_local_scan_0_them(const igraph_t *us, const igraph_t *them, igraph_vector_t *res, const igraph_vector_t *weigths_them, igraph_neimode_t mode); DECLDIR int igraph_local_scan_1_ecount(const igraph_t *graph, igraph_vector_t *res, const igraph_vector_t *weights, igraph_neimode_t mode); DECLDIR int igraph_local_scan_1_ecount_them(const igraph_t *us, const igraph_t *them, igraph_vector_t *res, const igraph_vector_t *weights, igraph_neimode_t mode); DECLDIR int igraph_local_scan_k_ecount(const igraph_t *graph, int k, igraph_vector_t *res, const igraph_vector_t *weights, igraph_neimode_t mode); DECLDIR int igraph_local_scan_k_ecount_them(const igraph_t *us, const igraph_t *them, int k, igraph_vector_t *res, const igraph_vector_t *weights_them, igraph_neimode_t mode); DECLDIR int igraph_local_scan_neighborhood_ecount(const igraph_t *graph, igraph_vector_t *res, const igraph_vector_t *weights, const igraph_vector_ptr_t *neighborhoods); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_array.h0000644000076500000240000000315713614300625025061 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_ARRAY_H #define IGRAPH_ARRAY_H #include "igraph_decls.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* 3D array */ /* -------------------------------------------------- */ #define BASE_IGRAPH_REAL #include "igraph_pmt.h" #include "igraph_array_pmt.h" #include "igraph_pmt_off.h" #undef BASE_IGRAPH_REAL #define BASE_LONG #include "igraph_pmt.h" #include "igraph_array_pmt.h" #include "igraph_pmt_off.h" #undef BASE_LONG #define BASE_CHAR #include "igraph_pmt.h" #include "igraph_array_pmt.h" #include "igraph_pmt_off.h" #undef BASE_CHAR #define BASE_BOOL #include "igraph_pmt.h" #include "igraph_array_pmt.h" #include "igraph_pmt_off.h" #undef BASE_BOOL __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_separators.h0000644000076500000240000000333413614300625026123 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_SEPARATORS_H #define IGRAPH_SEPARATORS_H #include "igraph_decls.h" #include "igraph_constants.h" #include "igraph_types.h" #include "igraph_vector.h" #include "igraph_vector_ptr.h" #include "igraph_datatype.h" #include "igraph_iterators.h" __BEGIN_DECLS DECLDIR int igraph_is_separator(const igraph_t *graph, const igraph_vs_t candidate, igraph_bool_t *res); DECLDIR int igraph_all_minimal_st_separators(const igraph_t *graph, igraph_vector_ptr_t *separators); DECLDIR int igraph_is_minimal_separator(const igraph_t *graph, const igraph_vs_t candidate, igraph_bool_t *res); DECLDIR int igraph_minimum_size_separators(const igraph_t *graph, igraph_vector_ptr_t *separators); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_vector_ptr.h0000644000076500000240000001066313614300625026132 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_VECTOR_PTR_H #define IGRAPH_VECTOR_PTR_H #include "igraph_decls.h" #include "igraph_vector.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* Flexible vector, storing pointers */ /* -------------------------------------------------- */ /** * Vector, storing pointers efficiently * \ingroup internal * */ typedef struct s_vector_ptr { void** stor_begin; void** stor_end; void** end; igraph_finally_func_t* item_destructor; } igraph_vector_ptr_t; #define IGRAPH_VECTOR_PTR_NULL { 0,0,0,0 } #define IGRAPH_VECTOR_PTR_INIT_FINALLY(v, size) \ do { IGRAPH_CHECK(igraph_vector_ptr_init(v, size)); \ IGRAPH_FINALLY(igraph_vector_ptr_destroy, v); } while (0) DECLDIR int igraph_vector_ptr_init (igraph_vector_ptr_t* v, long int size); DECLDIR int igraph_vector_ptr_init_copy (igraph_vector_ptr_t* v, void** data, long int length); DECLDIR const igraph_vector_ptr_t *igraph_vector_ptr_view (const igraph_vector_ptr_t *v, void *const *data, long int length); DECLDIR void igraph_vector_ptr_destroy (igraph_vector_ptr_t* v); DECLDIR void igraph_vector_ptr_free_all (igraph_vector_ptr_t* v); DECLDIR void igraph_vector_ptr_destroy_all (igraph_vector_ptr_t* v); DECLDIR int igraph_vector_ptr_reserve (igraph_vector_ptr_t* v, long int size); DECLDIR igraph_bool_t igraph_vector_ptr_empty (const igraph_vector_ptr_t* v); DECLDIR long int igraph_vector_ptr_size (const igraph_vector_ptr_t* v); DECLDIR void igraph_vector_ptr_clear (igraph_vector_ptr_t* v); DECLDIR void igraph_vector_ptr_null (igraph_vector_ptr_t* v); DECLDIR int igraph_vector_ptr_push_back (igraph_vector_ptr_t* v, void* e); DECLDIR int igraph_vector_ptr_append (igraph_vector_ptr_t *to, const igraph_vector_ptr_t *from); DECLDIR void *igraph_vector_ptr_pop_back (igraph_vector_ptr_t *v); DECLDIR int igraph_vector_ptr_insert(igraph_vector_ptr_t *v, long int pos, void* e); DECLDIR void* igraph_vector_ptr_e (const igraph_vector_ptr_t* v, long int pos); DECLDIR void igraph_vector_ptr_set (igraph_vector_ptr_t* v, long int pos, void* value); DECLDIR int igraph_vector_ptr_resize(igraph_vector_ptr_t* v, long int newsize); DECLDIR void igraph_vector_ptr_copy_to(const igraph_vector_ptr_t *v, void** to); DECLDIR int igraph_vector_ptr_copy(igraph_vector_ptr_t *to, const igraph_vector_ptr_t *from); DECLDIR void igraph_vector_ptr_remove(igraph_vector_ptr_t *v, long int pos); DECLDIR void igraph_vector_ptr_sort(igraph_vector_ptr_t *v, int(*compar)(const void*, const void*)); DECLDIR int igraph_vector_ptr_index_int(igraph_vector_ptr_t *v, const igraph_vector_int_t *idx); DECLDIR igraph_finally_func_t* igraph_vector_ptr_get_item_destructor(const igraph_vector_ptr_t *v); DECLDIR igraph_finally_func_t* igraph_vector_ptr_set_item_destructor(igraph_vector_ptr_t *v, igraph_finally_func_t *func); /** * \define IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR * \brief Sets the item destructor for this pointer vector (macro version). * * This macro is expanded to \ref igraph_vector_ptr_set_item_destructor(), the * only difference is that the second argument is automatically cast to an * \c igraph_finally_func_t*. The cast is necessary in most cases as the * destructor functions we use (such as \ref igraph_vector_destroy()) take a * pointer to some concrete igraph data type, while \c igraph_finally_func_t * expects \c void* */ #define IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(v, func) \ igraph_vector_ptr_set_item_destructor((v), (igraph_finally_func_t*)(func)) __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_datatype.h0000644000076500000240000000556313614300625025561 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_DATATYPE_H #define IGRAPH_DATATYPE_H #include "igraph_decls.h" #include "igraph_types.h" #include "igraph_vector.h" __BEGIN_DECLS /** * \ingroup internal * \struct igraph_t * \brief The internal data structure for storing graphs. * * It is simple and efficient. It has the following members: * - n The number of vertices, reduntant. * - directed Whether the graph is directed. * - from The first column of the edge list. * - to The second column of the edge list. * - oi The index of the edge list by the first column. Thus * the first edge according to this order goes from * \c from[oi[0]] to \c to[oi[0]]. The length of * this vector is the same as the number of edges in the graph. * - ii The index of the edge list by the second column. * The length of this vector is the same as the number of edges. * - os Contains pointers to the edgelist (\c from * and \c to for every vertex. The first edge \em from * vertex \c v is edge no. \c from[oi[os[v]]] if * \c os[v]is This is basically the same as os, but this time * for the incoming edges. * * For undirected graph, the same edge list is stored, ie. an * undirected edge is stored only once, and for checking whether there * is an undirected edge from \c v1 to \c v2 one * should search for both \c from=v1, \c to=v2 and * \c from=v2, \c to=v1. * * The storage requirements for a graph with \c |V| vertices * and \c |E| edges is \c O(|E|+|V|). */ typedef struct igraph_s { igraph_integer_t n; igraph_bool_t directed; igraph_vector_t from; igraph_vector_t to; igraph_vector_t oi; igraph_vector_t ii; igraph_vector_t os; igraph_vector_t is; void *attr; } igraph_t; __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_iterators.h0000644000076500000240000003137013614300625025755 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_ITERATORS_H #define IGRAPH_ITERATORS_H #include "igraph_decls.h" #include "igraph_constants.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* Vertex selectors */ /* -------------------------------------------------- */ #define IGRAPH_VS_ALL 0 #define IGRAPH_VS_ADJ 1 #define IGRAPH_VS_NONE 2 #define IGRAPH_VS_1 3 #define IGRAPH_VS_VECTORPTR 4 #define IGRAPH_VS_VECTOR 5 #define IGRAPH_VS_SEQ 6 #define IGRAPH_VS_NONADJ 7 typedef struct igraph_vs_t { int type; union { igraph_integer_t vid; /* single vertex */ const igraph_vector_t *vecptr; /* vector of vertices */ struct { igraph_integer_t vid; igraph_neimode_t mode; } adj; /* adjacent vertices */ struct { igraph_integer_t from; igraph_integer_t to; } seq; /* sequence of vertices from:to */ } data; } igraph_vs_t; DECLDIR int igraph_vs_all(igraph_vs_t *vs); DECLDIR igraph_vs_t igraph_vss_all(void); DECLDIR int igraph_vs_adj(igraph_vs_t *vs, igraph_integer_t vid, igraph_neimode_t mode); DECLDIR igraph_vs_t igraph_vss_adj(igraph_integer_t vid, igraph_neimode_t mode); DECLDIR int igraph_vs_nonadj(igraph_vs_t *vs, igraph_integer_t vid, igraph_neimode_t mode); DECLDIR int igraph_vs_none(igraph_vs_t *vs); DECLDIR igraph_vs_t igraph_vss_none(void); DECLDIR int igraph_vs_1(igraph_vs_t *vs, igraph_integer_t vid); DECLDIR igraph_vs_t igraph_vss_1(igraph_integer_t vid); DECLDIR int igraph_vs_vector(igraph_vs_t *vs, const igraph_vector_t *v); DECLDIR igraph_vs_t igraph_vss_vector(const igraph_vector_t *v); DECLDIR int igraph_vs_vector_small(igraph_vs_t *vs, ...); DECLDIR int igraph_vs_vector_copy(igraph_vs_t *vs, const igraph_vector_t *v); DECLDIR int igraph_vs_seq(igraph_vs_t *vs, igraph_integer_t from, igraph_integer_t to); DECLDIR igraph_vs_t igraph_vss_seq(igraph_integer_t from, igraph_integer_t to); DECLDIR void igraph_vs_destroy(igraph_vs_t *vs); DECLDIR igraph_bool_t igraph_vs_is_all(const igraph_vs_t *vs); DECLDIR int igraph_vs_copy(igraph_vs_t* dest, const igraph_vs_t* src); DECLDIR int igraph_vs_as_vector(const igraph_t *graph, igraph_vs_t vs, igraph_vector_t *v); DECLDIR int igraph_vs_size(const igraph_t *graph, const igraph_vs_t *vs, igraph_integer_t *result); DECLDIR int igraph_vs_type(const igraph_vs_t *vs); /* -------------------------------------------------- */ /* Vertex iterators */ /* -------------------------------------------------- */ #define IGRAPH_VIT_SEQ 0 #define IGRAPH_VIT_VECTOR 1 #define IGRAPH_VIT_VECTORPTR 2 typedef struct igraph_vit_t { int type; long int pos; long int start; long int end; const igraph_vector_t *vec; } igraph_vit_t; /** * \section IGRAPH_VIT Stepping over the vertices * * After creating an iterator with \ref igraph_vit_create(), it * points to the first vertex in the vertex determined by the vertex * selector (if there is any). The \ref IGRAPH_VIT_NEXT() macro steps * to the next vertex, \ref IGRAPH_VIT_END() checks whether there are * more vertices to visit, \ref IGRAPH_VIT_SIZE() gives the total size * of the vertices visited so far and to be visited. \ref * IGRAPH_VIT_RESET() resets the iterator, it will point to the first * vertex again. Finally \ref IGRAPH_VIT_GET() gives the current vertex * pointed to by the iterator (call this only if \ref IGRAPH_VIT_END() * is false). * * * Here is an example on how to step over the neighbors of vertex 0: * * igraph_vs_t vs; * igraph_vit_t vit; * ... * igraph_vs_adj(&vs, 0, IGRAPH_ALL); * igraph_vit_create(&graph, vs, &vit); * while (!IGRAPH_VIT_END(vit)) { * printf(" %li", (long int) IGRAPH_VIT_GET(vit)); * IGRAPH_VIT_NEXT(vit); * } * printf("\n"); * ... * igraph_vit_destroy(&vit); * igraph_vs_destroy(&vs); * * */ /** * \define IGRAPH_VIT_NEXT * \brief Next vertex. * * Steps the iterator to the next vertex. Only call this function if * \ref IGRAPH_VIT_END() returns false. * \param vit The vertex iterator to step. * * Time complexity: O(1). */ #define IGRAPH_VIT_NEXT(vit) (++((vit).pos)) /** * \define IGRAPH_VIT_END * \brief Are we at the end? * * Checks whether there are more vertices to step to. * \param vit The vertex iterator to check. * \return Logical value, if true there are no more vertices to step * to. * * Time complexity: O(1). */ #define IGRAPH_VIT_END(vit) ((vit).pos >= (vit).end) /** * \define IGRAPH_VIT_SIZE * \brief Size of a vertex iterator. * * Gives the number of vertices in a vertex iterator. * \param vit The vertex iterator. * \return The number of vertices. * * Time complexity: O(1). */ #define IGRAPH_VIT_SIZE(vit) ((vit).end - (vit).start) /** * \define IGRAPH_VIT_RESET * \brief Reset a vertex iterator. * * Resets a vertex iterator. After calling this macro the iterator * will point to the first vertex. * \param vit The vertex iterator. * * Time complexity: O(1). */ #define IGRAPH_VIT_RESET(vit) ((vit).pos = (vit).start) /** * \define IGRAPH_VIT_GET * \brief Query the current position. * * Gives the vertex id of the current vertex pointed to by the * iterator. * \param vit The vertex iterator. * \return The vertex id of the current vertex. * * Time complexity: O(1). */ #define IGRAPH_VIT_GET(vit) \ ((igraph_integer_t)(((vit).type == IGRAPH_VIT_SEQ) ? (vit).pos : \ VECTOR(*(vit).vec)[(vit).pos])) DECLDIR int igraph_vit_create(const igraph_t *graph, igraph_vs_t vs, igraph_vit_t *vit); DECLDIR void igraph_vit_destroy(const igraph_vit_t *vit); DECLDIR int igraph_vit_as_vector(const igraph_vit_t *vit, igraph_vector_t *v); /* -------------------------------------------------- */ /* Edge Selectors */ /* -------------------------------------------------- */ #define IGRAPH_ES_ALL 0 #define IGRAPH_ES_ALLFROM 1 #define IGRAPH_ES_ALLTO 2 #define IGRAPH_ES_INCIDENT 3 #define IGRAPH_ES_NONE 4 #define IGRAPH_ES_1 5 #define IGRAPH_ES_VECTORPTR 6 #define IGRAPH_ES_VECTOR 7 #define IGRAPH_ES_SEQ 8 #define IGRAPH_ES_PAIRS 9 #define IGRAPH_ES_PATH 10 #define IGRAPH_ES_MULTIPAIRS 11 typedef struct igraph_es_t { int type; union { igraph_integer_t vid; igraph_integer_t eid; const igraph_vector_t *vecptr; struct { igraph_integer_t vid; igraph_neimode_t mode; } incident; struct { igraph_integer_t from; igraph_integer_t to; } seq; struct { const igraph_vector_t *ptr; igraph_bool_t mode; } path; } data; } igraph_es_t; DECLDIR int igraph_es_all(igraph_es_t *es, igraph_edgeorder_type_t order); DECLDIR igraph_es_t igraph_ess_all(igraph_edgeorder_type_t order); DECLDIR int igraph_es_adj(igraph_es_t *es, igraph_integer_t vid, igraph_neimode_t mode); /* deprecated */ DECLDIR int igraph_es_incident(igraph_es_t *es, igraph_integer_t vid, igraph_neimode_t mode); DECLDIR int igraph_es_none(igraph_es_t *es); DECLDIR igraph_es_t igraph_ess_none(void); DECLDIR int igraph_es_1(igraph_es_t *es, igraph_integer_t eid); DECLDIR igraph_es_t igraph_ess_1(igraph_integer_t eid); DECLDIR int igraph_es_vector(igraph_es_t *es, const igraph_vector_t *v); DECLDIR igraph_es_t igraph_ess_vector(const igraph_vector_t *v); DECLDIR int igraph_es_fromto(igraph_es_t *es, igraph_vs_t from, igraph_vs_t to); DECLDIR int igraph_es_seq(igraph_es_t *es, igraph_integer_t from, igraph_integer_t to); DECLDIR igraph_es_t igraph_ess_seq(igraph_integer_t from, igraph_integer_t to); DECLDIR int igraph_es_vector_copy(igraph_es_t *es, const igraph_vector_t *v); DECLDIR int igraph_es_pairs(igraph_es_t *es, const igraph_vector_t *v, igraph_bool_t directed); DECLDIR int igraph_es_pairs_small(igraph_es_t *es, igraph_bool_t directed, ...); DECLDIR int igraph_es_multipairs(igraph_es_t *es, const igraph_vector_t *v, igraph_bool_t directed); DECLDIR int igraph_es_path(igraph_es_t *es, const igraph_vector_t *v, igraph_bool_t directed); DECLDIR int igraph_es_path_small(igraph_es_t *es, igraph_bool_t directed, ...); DECLDIR void igraph_es_destroy(igraph_es_t *es); DECLDIR igraph_bool_t igraph_es_is_all(const igraph_es_t *es); DECLDIR int igraph_es_copy(igraph_es_t* dest, const igraph_es_t* src); DECLDIR int igraph_es_as_vector(const igraph_t *graph, igraph_es_t es, igraph_vector_t *v); DECLDIR int igraph_es_size(const igraph_t *graph, const igraph_es_t *es, igraph_integer_t *result); DECLDIR int igraph_es_type(const igraph_es_t *es); /* -------------------------------------------------- */ /* Edge Iterators */ /* -------------------------------------------------- */ #define IGRAPH_EIT_SEQ 0 #define IGRAPH_EIT_VECTOR 1 #define IGRAPH_EIT_VECTORPTR 2 typedef struct igraph_eit_t { int type; long int pos; long int start; long int end; const igraph_vector_t *vec; } igraph_eit_t; /** * \section IGRAPH_EIT Stepping over the edges * * Just like for vertex iterators, macros are provided for * stepping over a sequence of edges: \ref IGRAPH_EIT_NEXT() goes to * the next edge, \ref IGRAPH_EIT_END() checks whether there are more * edges to visit, \ref IGRAPH_EIT_SIZE() gives the number of edges in * the edge sequence, \ref IGRAPH_EIT_RESET() resets the iterator to * the first edge and \ref IGRAPH_EIT_GET() returns the id of the * current edge. */ /** * \define IGRAPH_EIT_NEXT * \brief Next edge. * * Steps the iterator to the next edge. Call this function only if * \ref IGRAPH_EIT_END() returns false. * \param eit The edge iterator to step. * * Time complexity: O(1). */ #define IGRAPH_EIT_NEXT(eit) (++((eit).pos)) /** * \define IGRAPH_EIT_END * \brief Are we at the end? * * Checks whether there are more edges to step to. * \param wit The edge iterator to check. * \return Logical value, if true there are no more edges * to step to. * * Time complexity: O(1). */ #define IGRAPH_EIT_END(eit) ((eit).pos >= (eit).end) /** * \define IGRAPH_EIT_SIZE * \brief Number of edges in the iterator. * * Gives the number of edges in an edge iterator. * \param eit The edge iterator. * \return The number of edges. * * Time complexity: O(1). */ #define IGRAPH_EIT_SIZE(eit) ((eit).end - (eit).start) /** * \define IGRAPH_EIT_RESET * \brief Reset an edge iterator. * * Resets an edge iterator. After calling this macro the iterator will * point to the first edge. * \param eit The edge iterator. * * Time complexity: O(1). */ #define IGRAPH_EIT_RESET(eit) ((eit).pos = (eit).start) /** * \define IGRAPH_EIT_GET * \brief Query an edge iterator. * * Gives the edge id of the current edge pointed to by an iterator. * \param eit The edge iterator. * \return The id of the current edge. * * Time complexity: O(1). */ #define IGRAPH_EIT_GET(eit) \ (igraph_integer_t)((((eit).type == IGRAPH_EIT_SEQ) ? (eit).pos : \ VECTOR(*(eit).vec)[(eit).pos])) DECLDIR int igraph_eit_create(const igraph_t *graph, igraph_es_t es, igraph_eit_t *eit); DECLDIR void igraph_eit_destroy(const igraph_eit_t *eit); DECLDIR int igraph_eit_as_vector(const igraph_eit_t *eit, igraph_vector_t *v); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_eigen.h0000644000076500000240000001042013614300625025021 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_arpack.h" #include "igraph_lapack.h" #include "igraph_sparsemat.h" #ifndef IGRAPH_EIGEN_H #define IGRAPH_EIGEN_H #include "igraph_decls.h" __BEGIN_DECLS typedef enum { IGRAPH_EIGEN_AUTO = 0, IGRAPH_EIGEN_LAPACK, IGRAPH_EIGEN_ARPACK, IGRAPH_EIGEN_COMP_AUTO, IGRAPH_EIGEN_COMP_LAPACK, IGRAPH_EIGEN_COMP_ARPACK } igraph_eigen_algorithm_t; typedef enum { IGRAPH_EIGEN_LM = 0, IGRAPH_EIGEN_SM, /* 1 */ IGRAPH_EIGEN_LA, /* 2 */ IGRAPH_EIGEN_SA, /* 3 */ IGRAPH_EIGEN_BE, /* 4 */ IGRAPH_EIGEN_LR, /* 5 */ IGRAPH_EIGEN_SR, /* 6 */ IGRAPH_EIGEN_LI, /* 7 */ IGRAPH_EIGEN_SI, /* 8 */ IGRAPH_EIGEN_ALL, /* 9 */ IGRAPH_EIGEN_INTERVAL, /* 10 */ IGRAPH_EIGEN_SELECT } /* 11 */ igraph_eigen_which_position_t; typedef struct igraph_eigen_which_t { igraph_eigen_which_position_t pos; int howmany; int il, iu; igraph_real_t vl, vu; int vestimate; igraph_lapack_dgeevx_balance_t balance; } igraph_eigen_which_t; DECLDIR int igraph_eigen_matrix_symmetric(const igraph_matrix_t *A, const igraph_sparsemat_t *sA, igraph_arpack_function_t *fun, int n, void *extra, igraph_eigen_algorithm_t algorithm, const igraph_eigen_which_t *which, igraph_arpack_options_t *options, igraph_arpack_storage_t *storage, igraph_vector_t *values, igraph_matrix_t *vectors); DECLDIR int igraph_eigen_matrix(const igraph_matrix_t *A, const igraph_sparsemat_t *sA, igraph_arpack_function_t *fun, int n, void *extra, igraph_eigen_algorithm_t algorithm, const igraph_eigen_which_t *which, igraph_arpack_options_t *options, igraph_arpack_storage_t *storage, igraph_vector_complex_t *values, igraph_matrix_complex_t *vectors); DECLDIR int igraph_eigen_adjacency(const igraph_t *graph, igraph_eigen_algorithm_t algorithm, const igraph_eigen_which_t *which, igraph_arpack_options_t *options, igraph_arpack_storage_t *storage, igraph_vector_t *values, igraph_matrix_t *vectors, igraph_vector_complex_t *cmplxvalues, igraph_matrix_complex_t *cmplxvectors); DECLDIR int igraph_eigen_laplacian(const igraph_t *graph, igraph_eigen_algorithm_t algorithm, const igraph_eigen_which_t *which, igraph_arpack_options_t *options, igraph_arpack_storage_t *storage, igraph_vector_t *values, igraph_matrix_t *vectors, igraph_vector_complex_t *cmplxvalues, igraph_matrix_complex_t *cmplxvectors); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_foreign.h0000644000076500000240000001012113614300625025361 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_FOREIGN_H #define IGRAPH_FOREIGN_H #include "igraph_decls.h" #include "igraph_constants.h" #include "igraph_datatype.h" #include "igraph_types.h" #include "igraph_strvector.h" #include __BEGIN_DECLS /* -------------------------------------------------- */ /* Read and write foreign formats */ /* -------------------------------------------------- */ DECLDIR int igraph_read_graph_edgelist(igraph_t *graph, FILE *instream, igraph_integer_t n, igraph_bool_t directed); DECLDIR int igraph_read_graph_ncol(igraph_t *graph, FILE *instream, igraph_strvector_t *predefnames, igraph_bool_t names, igraph_add_weights_t weights, igraph_bool_t directed); DECLDIR int igraph_read_graph_lgl(igraph_t *graph, FILE *instream, igraph_bool_t names, igraph_add_weights_t weights, igraph_bool_t directed); DECLDIR int igraph_read_graph_pajek(igraph_t *graph, FILE *instream); DECLDIR int igraph_read_graph_graphml(igraph_t *graph, FILE *instream, int index); DECLDIR int igraph_read_graph_dimacs(igraph_t *graph, FILE *instream, igraph_strvector_t *problem, igraph_vector_t *label, igraph_integer_t *source, igraph_integer_t *target, igraph_vector_t *capacity, igraph_bool_t directed); DECLDIR int igraph_read_graph_graphdb(igraph_t *graph, FILE *instream, igraph_bool_t directed); DECLDIR int igraph_read_graph_gml(igraph_t *graph, FILE *instream); DECLDIR int igraph_read_graph_dl(igraph_t *graph, FILE *instream, igraph_bool_t directed); DECLDIR int igraph_write_graph_edgelist(const igraph_t *graph, FILE *outstream); DECLDIR int igraph_write_graph_ncol(const igraph_t *graph, FILE *outstream, const char *names, const char *weights); DECLDIR int igraph_write_graph_lgl(const igraph_t *graph, FILE *outstream, const char *names, const char *weights, igraph_bool_t isolates); DECLDIR int igraph_write_graph_graphml(const igraph_t *graph, FILE *outstream, igraph_bool_t prefixattr); DECLDIR int igraph_write_graph_pajek(const igraph_t *graph, FILE *outstream); DECLDIR int igraph_write_graph_dimacs(const igraph_t *graph, FILE *outstream, long int source, long int target, const igraph_vector_t *capacity); DECLDIR int igraph_write_graph_gml(const igraph_t *graph, FILE *outstream, const igraph_vector_t *id, const char *creator); DECLDIR int igraph_write_graph_dot(const igraph_t *graph, FILE *outstream); DECLDIR int igraph_write_graph_leda(const igraph_t *graph, FILE *outstream, const char* vertex_attr_name, const char* edge_attr_name); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_strvector.h0000644000076500000240000000732613614300625026000 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_STRVECTOR_H #define IGRAPH_STRVECTOR_H #include "igraph_decls.h" #include "igraph_vector.h" __BEGIN_DECLS /** * Vector of strings * \ingroup internal */ typedef struct s_igraph_strvector { char **data; long int len; } igraph_strvector_t; /** * \define STR * Indexing string vectors * * This is a macro which allows to query the elements of a string vector in * simpler way than \ref igraph_strvector_get(). Note this macro cannot be * used to set an element, for that use \ref igraph_strvector_set(). * \param sv The string vector * \param i The the index of the element. * \return The element at position \p i. * * Time complexity: O(1). */ #define STR(sv,i) ((const char *)((sv).data[(i)])) #define IGRAPH_STRVECTOR_NULL { 0,0 } #define IGRAPH_STRVECTOR_INIT_FINALLY(v, size) \ do { IGRAPH_CHECK(igraph_strvector_init(v, size)); \ IGRAPH_FINALLY( (igraph_finally_func_t*) igraph_strvector_destroy, v); } while (0) DECLDIR int igraph_strvector_init(igraph_strvector_t *sv, long int len); DECLDIR void igraph_strvector_destroy(igraph_strvector_t *sv); DECLDIR long int igraph_strvector_size(const igraph_strvector_t *sv); DECLDIR void igraph_strvector_get(const igraph_strvector_t *sv, long int idx, char **value); DECLDIR int igraph_strvector_set(igraph_strvector_t *sv, long int idx, const char *value); DECLDIR int igraph_strvector_set2(igraph_strvector_t *sv, long int idx, const char *value, int len); DECLDIR void igraph_strvector_clear(igraph_strvector_t *sv); DECLDIR void igraph_strvector_remove_section(igraph_strvector_t *v, long int from, long int to); DECLDIR void igraph_strvector_remove(igraph_strvector_t *v, long int elem); DECLDIR void igraph_strvector_move_interval(igraph_strvector_t *v, long int begin, long int end, long int to); DECLDIR int igraph_strvector_copy(igraph_strvector_t *to, const igraph_strvector_t *from); DECLDIR int igraph_strvector_append(igraph_strvector_t *to, const igraph_strvector_t *from); DECLDIR int igraph_strvector_resize(igraph_strvector_t* v, long int newsize); DECLDIR int igraph_strvector_add(igraph_strvector_t *v, const char *value); DECLDIR void igraph_strvector_permdelete(igraph_strvector_t *v, const igraph_vector_t *index, long int nremove); DECLDIR void igraph_strvector_remove_negidx(igraph_strvector_t *v, const igraph_vector_t *neg, long int nremove); DECLDIR int igraph_strvector_print(const igraph_strvector_t *v, FILE *file, const char *sep); DECLDIR int igraph_strvector_index(const igraph_strvector_t *v, igraph_strvector_t *newv, const igraph_vector_t *idx); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_hrg.h0000644000076500000240000001045313614300625024520 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_HRG_H #define IGRAPH_HRG_H #include "igraph_decls.h" #include "igraph_vector.h" #include "igraph_vector_ptr.h" #include "igraph_datatype.h" __BEGIN_DECLS /** * \struct igraph_hrg_t * Data structure to store a hierarchical random graph * * A hierarchical random graph (HRG) can be given as a binary tree, * where the internal vertices are labeled with real numbers. * * Note that you don't necessarily have to know this * internal representation for using the HRG functions, just pass the * HRG objects created by one igraph function, to another igraph * function. * * * It has the following members: * \member left Vector that contains the left children of the internal * tree vertices. The first vertex is always the root vertex, so * the first element of the vector is the left child of the root * vertex. Internal vertices are denoted with negative numbers, * starting from -1 and going down, i.e. the root vertex is * -1. Leaf vertices are denoted by non-negative number, starting * from zero and up. * \member right Vector that contains the right children of the * vertices, with the same encoding as the \c left vector. * \member prob The connection probabilities attached to the internal * vertices, the first number belongs to the root vertex * (i.e. internal vertex -1), the second to internal vertex -2, * etc. * \member edges The number of edges in the subtree below the given * internal vertex. * \member vertices The number of vertices in the subtree below the * given internal vertex, including itself. */ typedef struct igraph_hrg_t { igraph_vector_t left, right, prob, edges, vertices; } igraph_hrg_t; DECLDIR int igraph_hrg_init(igraph_hrg_t *hrg, int n); DECLDIR void igraph_hrg_destroy(igraph_hrg_t *hrg); DECLDIR int igraph_hrg_size(const igraph_hrg_t *hrg); DECLDIR int igraph_hrg_resize(igraph_hrg_t *hrg, int newsize); DECLDIR int igraph_hrg_fit(const igraph_t *graph, igraph_hrg_t *hrg, igraph_bool_t start, int steps); DECLDIR int igraph_hrg_sample(const igraph_t *graph, igraph_t *sample, igraph_vector_ptr_t *samples, igraph_hrg_t *hrg, igraph_bool_t start); DECLDIR int igraph_hrg_game(igraph_t *graph, const igraph_hrg_t *hrg); DECLDIR int igraph_hrg_dendrogram(igraph_t *graph, const igraph_hrg_t *hrg); DECLDIR int igraph_hrg_consensus(const igraph_t *graph, igraph_vector_t *parents, igraph_vector_t *weights, igraph_hrg_t *hrg, igraph_bool_t start, int num_samples); DECLDIR int igraph_hrg_predict(const igraph_t *graph, igraph_vector_t *edges, igraph_vector_t *prob, igraph_hrg_t *hrg, igraph_bool_t start, int num_samples, int num_bins); DECLDIR int igraph_hrg_create(igraph_hrg_t *hrg, const igraph_t *graph, const igraph_vector_t *prob); __END_DECLS #endif /* IGRAPH_HRG_H */ python-igraph-0.8.0/vendor/source/igraph/include/igraph_threading.h.in0000644000076500000240000000225213614300625026310 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_THREADING_H #define IGRAPH_THREADING_H #include "igraph_decls.h" __BEGIN_DECLS /** * \define IGRAPH_THREAD_SAFE * * Macro that is defined to be 1 if the current build of the * igraph library is thread-safe, and 0 if it is not. */ #define IGRAPH_THREAD_SAFE @HAVE_TLS@ __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_embedding.h0000644000076500000240000000417313614300625025660 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2013 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_EMBEDDING_H #define IGRAPH_EMBEDDING_H #include "igraph_decls.h" #include "igraph_datatype.h" #include "igraph_arpack.h" #include "igraph_eigen.h" #include "igraph_constants.h" __BEGIN_DECLS DECLDIR int igraph_adjacency_spectral_embedding(const igraph_t *graph, igraph_integer_t no, const igraph_vector_t *weights, igraph_eigen_which_position_t which, igraph_bool_t scaled, igraph_matrix_t *X, igraph_matrix_t *Y, igraph_vector_t *D, const igraph_vector_t *cvec, igraph_arpack_options_t *options); typedef enum { IGRAPH_EMBEDDING_D_A = 0, IGRAPH_EMBEDDING_I_DAD, IGRAPH_EMBEDDING_DAD, IGRAPH_EMBEDDING_OAP } igraph_laplacian_spectral_embedding_type_t; DECLDIR int igraph_laplacian_spectral_embedding(const igraph_t *graph, igraph_integer_t no, const igraph_vector_t *weights, igraph_eigen_which_position_t which, igraph_neimode_t degmode, igraph_laplacian_spectral_embedding_type_t type, igraph_bool_t scaled, igraph_matrix_t *X, igraph_matrix_t *Y, igraph_vector_t *D, igraph_arpack_options_t *options); DECLDIR int igraph_dim_select(const igraph_vector_t *sv, igraph_integer_t *dim); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_neighborhood.h0000644000076500000240000000352413614300625026410 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_NEIGHBORHOOD_H #define IGRAPH_NEIGHBORHOOD_H #include "igraph_decls.h" #include "igraph_datatype.h" #include "igraph_iterators.h" #include "igraph_vector_ptr.h" __BEGIN_DECLS DECLDIR int igraph_neighborhood_size(const igraph_t *graph, igraph_vector_t *res, igraph_vs_t vids, igraph_integer_t order, igraph_neimode_t mode, igraph_integer_t mindist); DECLDIR int igraph_neighborhood(const igraph_t *graph, igraph_vector_ptr_t *res, igraph_vs_t vids, igraph_integer_t order, igraph_neimode_t mode, igraph_integer_t mindist); DECLDIR int igraph_neighborhood_graphs(const igraph_t *graph, igraph_vector_ptr_t *res, igraph_vs_t vids, igraph_integer_t order, igraph_neimode_t mode, igraph_integer_t mindist); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_bipartite.h0000644000076500000240000001021613614300625025720 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_BIPARTITE_H #define IGRAPH_BIPARTITE_H #include "igraph_decls.h" #include "igraph_constants.h" #include "igraph_types.h" #include "igraph_vector.h" #include "igraph_matrix.h" #include "igraph_datatype.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* Bipartite networks */ /* -------------------------------------------------- */ DECLDIR int igraph_full_bipartite(igraph_t *graph, igraph_vector_bool_t *types, igraph_integer_t n1, igraph_integer_t n2, igraph_bool_t directed, igraph_neimode_t mode); DECLDIR int igraph_create_bipartite(igraph_t *g, const igraph_vector_bool_t *types, const igraph_vector_t *edges, igraph_bool_t directed); DECLDIR int igraph_bipartite_projection_size(const igraph_t *graph, const igraph_vector_bool_t *types, igraph_integer_t *vcount1, igraph_integer_t *ecount1, igraph_integer_t *vcount2, igraph_integer_t *ecount2); DECLDIR int igraph_bipartite_projection(const igraph_t *graph, const igraph_vector_bool_t *types, igraph_t *proj1, igraph_t *proj2, igraph_vector_t *multiplicity1, igraph_vector_t *multiplicity2, igraph_integer_t probe1); DECLDIR int igraph_incidence(igraph_t *graph, igraph_vector_bool_t *types, const igraph_matrix_t *incidence, igraph_bool_t directed, igraph_neimode_t mode, igraph_bool_t multiple); DECLDIR int igraph_get_incidence(const igraph_t *graph, const igraph_vector_bool_t *types, igraph_matrix_t *res, igraph_vector_t *row_ids, igraph_vector_t *col_ids); DECLDIR int igraph_is_bipartite(const igraph_t *graph, igraph_bool_t *res, igraph_vector_bool_t *type); DECLDIR int igraph_bipartite_game(igraph_t *graph, igraph_vector_bool_t *types, igraph_erdos_renyi_t type, igraph_integer_t n1, igraph_integer_t n2, igraph_real_t p, igraph_integer_t m, igraph_bool_t directed, igraph_neimode_t mode); DECLDIR int igraph_bipartite_game_gnp(igraph_t *graph, igraph_vector_bool_t *types, igraph_integer_t n1, igraph_integer_t n2, igraph_real_t p, igraph_bool_t directed, igraph_neimode_t mode); DECLDIR int igraph_bipartite_game_gnm(igraph_t *graph, igraph_vector_bool_t *types, igraph_integer_t n1, igraph_integer_t n2, igraph_integer_t m, igraph_bool_t directed, igraph_neimode_t mode); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_nongraph.h0000644000076500000240000000775413614300625025566 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_NONGRAPH_H #define IGRAPH_NONGRAPH_H #include "igraph_decls.h" #include "igraph_constants.h" #include "igraph_matrix.h" #include "igraph_types.h" #include "igraph_vector.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* Other, not graph related */ /* -------------------------------------------------- */ /** * \struct igraph_plfit_result_t * \brief Result of fitting a power-law distribution to a vector * * This data structure contains the result of \ref igraph_power_law_fit(), * which tries to fit a power-law distribution to a vector of numbers. The * structure contains the following members: * * \member continuous Whether the fitted power-law distribution was continuous * or discrete. * \member alpha The exponent of the fitted power-law distribution. * \member xmin The minimum value from which the power-law distribution was * fitted. In other words, only the values larger than \c xmin * were used from the input vector. * \member L The log-likelihood of the fitted parameters; in other words, * the probability of observing the input vector given the * parameters. * \member D The test statistic of a Kolmogorov-Smirnov test that compares * the fitted distribution with the input vector. Smaller scores * denote better fit. * \member p The p-value of the Kolmogorov-Smirnov test. Small p-values * (less than 0.05) indicate that the test rejected the hypothesis * that the original data could have been drawn from the fitted * power-law distribution. */ typedef struct igraph_plfit_result_t { igraph_bool_t continuous; double alpha; double xmin; double L; double D; double p; } igraph_plfit_result_t; DECLDIR int igraph_running_mean(const igraph_vector_t *data, igraph_vector_t *res, igraph_integer_t binwidth); DECLDIR int igraph_fisher_yates_shuffle(igraph_vector_t *seq); DECLDIR int igraph_random_sample(igraph_vector_t *res, igraph_real_t l, igraph_real_t h, igraph_integer_t length); DECLDIR int igraph_convex_hull(const igraph_matrix_t *data, igraph_vector_t *resverts, igraph_matrix_t *rescoords); DECLDIR int igraph_zeroin(igraph_real_t *ax, igraph_real_t *bx, igraph_real_t (*f)(igraph_real_t x, void *info), void *info, igraph_real_t *Tol, int *Maxit, igraph_real_t *res); DECLDIR int igraph_bfgs(igraph_vector_t *b, igraph_real_t *Fmin, igraph_scalar_function_t fminfn, igraph_vector_function_t fmingr, int maxit, int trace, igraph_real_t abstol, igraph_real_t reltol, int nREPORT, void *ex, igraph_integer_t *fncount, igraph_integer_t *grcount); DECLDIR int igraph_power_law_fit(const igraph_vector_t* vector, igraph_plfit_result_t* result, igraph_real_t xmin, igraph_bool_t force_continuous); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_interrupt.h0000644000076500000240000001142313614300625025772 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2003-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_INTERRUPT_H #define IGRAPH_INTERRUPT_H #include "igraph_error.h" #include "igraph_decls.h" __BEGIN_DECLS /* This file contains the igraph interruption handling. */ /** * \section interrupthandlers Interruption handlers * * * \a igraph is designed to be embeddable into several higher level * languages (R and Python interfaces are included in the original * package). Since most higher level languages consider internal \a igraph * calls as atomic, interruption requests (like Ctrl-C in Python) must * be handled differently depending on the environment \a igraph embeds * into. * * An \emb interruption handler \eme is a function which is called regularly * by \a igraph during long calculations. A typical usage of the interruption * handler is to check whether the user tried to interrupt the calculation * and return an appropriate value to signal this condition. For example, * in R, one must call an internal R function regularly to check for * interruption requests, and the \a igraph interruption handler is the * perfect place to do that. * * If you are using the plain C interface of \a igraph or if you are * allowed to replace the operating system's interruption handler (like * SIGINT in Un*x systems), these calls are not of much use to you. * * The default interruption handler is empty. * The \ref igraph_set_interruption_handler() function can be used to set a * new interruption handler function of type * \ref igraph_interruption_handler_t, see the * documentation of this type for details. * */ /** * \section writing_interruption_handlers Writing interruption handlers * * * You can write and install interruption handlers simply by defining a * function of type \ref igraph_interruption_handler_t and calling * \ref igraph_set_interruption_handler(). This feature is useful for * interface writers, because usually this is the only way to allow handling * of Ctrl-C and similar keypresses properly. * * * Your interruption handler will be called regularly during long operations * (so it is not guaranteed to be called during operations which tend to be * short, like adding single edges). An interruption handler accepts no * parameters and must return \c IGRAPH_SUCCESS if the calculation should go on. All * other return values are considered to be a request for interruption, * and the caller function would return a special error code, \c IGRAPH_INTERRUPTED. * It is up to your error handler function to handle this error properly. * */ /** * \section writing_functions_interruption_handling Writing \a igraph functions with * proper interruption handling * * * There is practically a simple rule that should be obeyed when writing * \a igraph functions. If the calculation is expected to take a long time * in large graphs (a simple rule of thumb is to assume this for every * function with a time complexity of at least O(n^2)), call * \ref IGRAPH_ALLOW_INTERRUPTION in regular intervals like every 10th * iteration or so. * */ /** * \typedef igraph_interruption_handler_t * * This is the type of the interruption handler functions. * * \param data reserved for possible future use * \return \c IGRAPH_SUCCESS if the calculation should go on, anything else otherwise. */ typedef int igraph_interruption_handler_t (void* data); /** * \function igraph_allow_interruption * * This is the function which is called (usually via the * \ref IGRAPH_INTERRUPTION macro) if \a igraph is checking for interruption * requests. * * \param data reserved for possible future use, now it is always \c NULL * \return \c IGRAPH_SUCCESS if the calculation should go on, anything else otherwise. */ DECLDIR int igraph_allow_interruption(void* data); DECLDIR igraph_interruption_handler_t * igraph_set_interruption_handler (igraph_interruption_handler_t * new_handler); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_complex.h0000644000076500000240000001005213614300625025402 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_COMPLEX_H #define IGRAPH_COMPLEX_H #include "igraph_decls.h" #include "igraph_types.h" __BEGIN_DECLS typedef struct igraph_complex_t { igraph_real_t dat[2]; } igraph_complex_t; #define IGRAPH_REAL(x) ((x).dat[0]) #define IGRAPH_IMAG(x) ((x).dat[1]) #define IGRAPH_COMPLEX_EQ(x,y) ((x).dat[0]==(y).dat[0] && (x).dat[1]==(y).dat[1]) DECLDIR igraph_complex_t igraph_complex(igraph_real_t x, igraph_real_t y); DECLDIR igraph_complex_t igraph_complex_polar(igraph_real_t r, igraph_real_t theta); DECLDIR igraph_bool_t igraph_complex_eq_tol(igraph_complex_t z1, igraph_complex_t z2, igraph_real_t tol); DECLDIR igraph_real_t igraph_complex_mod(igraph_complex_t z); DECLDIR igraph_real_t igraph_complex_arg(igraph_complex_t z); DECLDIR igraph_real_t igraph_complex_abs(igraph_complex_t z); DECLDIR igraph_real_t igraph_complex_logabs(igraph_complex_t z); DECLDIR igraph_complex_t igraph_complex_add(igraph_complex_t z1, igraph_complex_t z2); DECLDIR igraph_complex_t igraph_complex_sub(igraph_complex_t z1, igraph_complex_t z2); DECLDIR igraph_complex_t igraph_complex_mul(igraph_complex_t z1, igraph_complex_t z2); DECLDIR igraph_complex_t igraph_complex_div(igraph_complex_t z1, igraph_complex_t z2); DECLDIR igraph_complex_t igraph_complex_add_real(igraph_complex_t z, igraph_real_t x); DECLDIR igraph_complex_t igraph_complex_add_imag(igraph_complex_t z, igraph_real_t y); DECLDIR igraph_complex_t igraph_complex_sub_real(igraph_complex_t z, igraph_real_t x); DECLDIR igraph_complex_t igraph_complex_sub_imag(igraph_complex_t z, igraph_real_t y); DECLDIR igraph_complex_t igraph_complex_mul_real(igraph_complex_t z, igraph_real_t x); DECLDIR igraph_complex_t igraph_complex_mul_imag(igraph_complex_t z, igraph_real_t y); DECLDIR igraph_complex_t igraph_complex_div_real(igraph_complex_t z, igraph_real_t x); DECLDIR igraph_complex_t igraph_complex_div_imag(igraph_complex_t z, igraph_real_t y); DECLDIR igraph_complex_t igraph_complex_conj(igraph_complex_t z); DECLDIR igraph_complex_t igraph_complex_neg(igraph_complex_t z); DECLDIR igraph_complex_t igraph_complex_inv(igraph_complex_t z); DECLDIR igraph_complex_t igraph_complex_sqrt(igraph_complex_t z); DECLDIR igraph_complex_t igraph_complex_sqrt_real(igraph_real_t x); DECLDIR igraph_complex_t igraph_complex_exp(igraph_complex_t z); DECLDIR igraph_complex_t igraph_complex_pow(igraph_complex_t z1, igraph_complex_t z2); DECLDIR igraph_complex_t igraph_complex_pow_real(igraph_complex_t z, igraph_real_t x); DECLDIR igraph_complex_t igraph_complex_log(igraph_complex_t z); DECLDIR igraph_complex_t igraph_complex_log10(igraph_complex_t z); DECLDIR igraph_complex_t igraph_complex_log_b(igraph_complex_t z, igraph_complex_t b); DECLDIR igraph_complex_t igraph_complex_sin(igraph_complex_t z); DECLDIR igraph_complex_t igraph_complex_cos(igraph_complex_t z); DECLDIR igraph_complex_t igraph_complex_tan(igraph_complex_t z); DECLDIR igraph_complex_t igraph_complex_sec(igraph_complex_t z); DECLDIR igraph_complex_t igraph_complex_csc(igraph_complex_t z); DECLDIR igraph_complex_t igraph_complex_cot(igraph_complex_t z); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_version.h.in0000644000076500000240000000260113614300625026026 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_VERSION_H #define IGRAPH_VERSION_H #include "igraph_decls.h" __BEGIN_DECLS #define IGRAPH_VERSION "@PACKAGE_VERSION@" #define IGRAPH_VERSION_MAJOR @PACKAGE_VERSION_MAJOR@ #define IGRAPH_VERSION_MINOR @PACKAGE_VERSION_MINOR@ #define IGRAPH_VERSION_PATCH @PACKAGE_VERSION_PATCH@ #define IGRAPH_VERSION_PRERELEASE "@PACKAGE_VERSION_PRERELEASE@" int igraph_version(const char **version_string, int *major, int *minor, int *subminor); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_matching.h0000644000076500000240000000424413614300625025533 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_MATCHING_H #define IGRAPH_MATCHING_H #include "igraph_decls.h" #include "igraph_constants.h" #include "igraph_datatype.h" #include "igraph_types.h" #include "igraph_vector.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* Matchings in graphs */ /* -------------------------------------------------- */ DECLDIR int igraph_is_matching(const igraph_t* graph, const igraph_vector_bool_t* types, const igraph_vector_long_t* matching, igraph_bool_t* result); DECLDIR int igraph_is_maximal_matching(const igraph_t* graph, const igraph_vector_bool_t* types, const igraph_vector_long_t* matching, igraph_bool_t* result); DECLDIR int igraph_maximum_bipartite_matching(const igraph_t* graph, const igraph_vector_bool_t* types, igraph_integer_t* matching_size, igraph_real_t* matching_weight, igraph_vector_long_t* matching, const igraph_vector_t* weights, igraph_real_t eps); DECLDIR int igraph_maximum_matching(const igraph_t* graph, igraph_integer_t* matching_size, igraph_real_t* matching_weight, igraph_vector_long_t* matching, const igraph_vector_t* weights); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_heap.h0000644000076500000240000000407613614300625024661 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_HEAP_H #define IGRAPH_HEAP_H #include "igraph_decls.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* Heap */ /* -------------------------------------------------- */ /** * Heap data type. * \ingroup internal */ #define BASE_IGRAPH_REAL #define HEAP_TYPE_MAX #include "igraph_pmt.h" #include "igraph_heap_pmt.h" #include "igraph_pmt_off.h" #undef HEAP_TYPE_MAX #define HEAP_TYPE_MIN #include "igraph_pmt.h" #include "igraph_heap_pmt.h" #include "igraph_pmt_off.h" #undef HEAP_TYPE_MIN #undef BASE_IGRAPH_REAL #define BASE_LONG #define HEAP_TYPE_MAX #include "igraph_pmt.h" #include "igraph_heap_pmt.h" #include "igraph_pmt_off.h" #undef HEAP_TYPE_MAX #define HEAP_TYPE_MIN #include "igraph_pmt.h" #include "igraph_heap_pmt.h" #include "igraph_pmt_off.h" #undef HEAP_TYPE_MIN #undef BASE_LONG #define BASE_CHAR #define HEAP_TYPE_MAX #include "igraph_pmt.h" #include "igraph_heap_pmt.h" #include "igraph_pmt_off.h" #undef HEAP_TYPE_MAX #define HEAP_TYPE_MIN #include "igraph_pmt.h" #include "igraph_heap_pmt.h" #include "igraph_pmt_off.h" #undef HEAP_TYPE_MIN #undef BASE_CHAR #define IGRAPH_HEAP_NULL { 0,0,0 } __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_matrix.h0000644000076500000240000000544113614300625025245 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_MATRIX_H #define IGRAPH_MATRIX_H #include "igraph_decls.h" #include "igraph_vector.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* Matrix, very similar to vector */ /* -------------------------------------------------- */ #define BASE_IGRAPH_REAL #include "igraph_pmt.h" #include "igraph_matrix_pmt.h" #include "igraph_pmt_off.h" #undef BASE_IGRAPH_REAL #define BASE_INT #include "igraph_pmt.h" #include "igraph_matrix_pmt.h" #include "igraph_pmt_off.h" #undef BASE_INT #define BASE_LONG #include "igraph_pmt.h" #include "igraph_matrix_pmt.h" #include "igraph_pmt_off.h" #undef BASE_LONG #define BASE_CHAR #include "igraph_pmt.h" #include "igraph_matrix_pmt.h" #include "igraph_pmt_off.h" #undef BASE_CHAR #define BASE_BOOL #include "igraph_pmt.h" #include "igraph_matrix_pmt.h" #include "igraph_pmt_off.h" #undef BASE_BOOL #define BASE_COMPLEX #include "igraph_pmt.h" #include "igraph_matrix_pmt.h" #include "igraph_pmt_off.h" #undef BASE_COMPLEX #define IGRAPH_MATRIX_NULL { IGRAPH_VECTOR_NULL, 0, 0 } #define IGRAPH_MATRIX_INIT_FINALLY(m, nr, nc) \ do { IGRAPH_CHECK(igraph_matrix_init(m, nr, nc)); \ IGRAPH_FINALLY(igraph_matrix_destroy, m); } while (0) /** * \ingroup matrix * \define MATRIX * \brief Accessing an element of a matrix. * * Note that there are no range checks right now. * This functionality might be redefined as a proper function later. * \param m The matrix object. * \param i The index of the row, starting with zero. * \param j The index of the column, starting with zero. * * Time complexity: O(1). */ #define MATRIX(m,i,j) ((m).data.stor_begin[(m).nrow*(j)+(i)]) igraph_bool_t igraph_matrix_all_e_tol(const igraph_matrix_t *lhs, const igraph_matrix_t *rhs, igraph_real_t tol); int igraph_matrix_zapsmall(igraph_matrix_t *m, igraph_real_t tol); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_qsort.h0000644000076500000240000000242413614300625025107 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard st, Cambridge, MA 02139, USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_QSORT_H #define IGRAPH_QSORT_H #include "igraph_decls.h" #include __BEGIN_DECLS DECLDIR void igraph_qsort(void *base, size_t nel, size_t width, int (*compar)(const void *, const void *)); DECLDIR void igraph_qsort_r(void *base, size_t nel, size_t width, void *thunk, int (*compar)(void *, const void *, const void *)); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_constants.h0000644000076500000240000001457613614300625025766 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_CONSTANTS_H #define IGRAPH_CONSTANTS_H #include "igraph_decls.h" #include "igraph_types.h" #include "igraph_datatype.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* Constants */ /* -------------------------------------------------- */ typedef enum { IGRAPH_UNDIRECTED = 0, IGRAPH_DIRECTED = 1 } igraph_i_directed_t; typedef enum { IGRAPH_NO_LOOPS = 0, IGRAPH_LOOPS = 1 } igraph_i_loops_t; typedef enum { IGRAPH_NO_MULTIPLE = 0, IGRAPH_MULTIPLE = 1 } igraph_i_multiple_t; typedef enum { IGRAPH_ASCENDING = 0, IGRAPH_DESCENDING = 1 } igraph_order_t; typedef enum { IGRAPH_MINIMUM = 0, IGRAPH_MAXIMUM = 1 } igraph_optimal_t; typedef enum { IGRAPH_OUT = 1, IGRAPH_IN = 2, IGRAPH_ALL = 3, IGRAPH_TOTAL = 3 } igraph_neimode_t; typedef enum { IGRAPH_WEAK = 1, IGRAPH_STRONG = 2 } igraph_connectedness_t; typedef enum { IGRAPH_RECIPROCITY_DEFAULT = 0, IGRAPH_RECIPROCITY_RATIO = 1 } igraph_reciprocity_t; typedef enum { IGRAPH_ADJ_DIRECTED = 0, IGRAPH_ADJ_UNDIRECTED = 1, IGRAPH_ADJ_MAX = 1, IGRAPH_ADJ_UPPER, IGRAPH_ADJ_LOWER, IGRAPH_ADJ_MIN, IGRAPH_ADJ_PLUS } igraph_adjacency_t; typedef enum { IGRAPH_STAR_OUT = 0, IGRAPH_STAR_IN, IGRAPH_STAR_UNDIRECTED, IGRAPH_STAR_MUTUAL } igraph_star_mode_t; typedef enum { IGRAPH_TREE_OUT = 0, IGRAPH_TREE_IN, IGRAPH_TREE_UNDIRECTED } igraph_tree_mode_t; typedef enum { IGRAPH_ERDOS_RENYI_GNP = 0, IGRAPH_ERDOS_RENYI_GNM } igraph_erdos_renyi_t; typedef enum { IGRAPH_GET_ADJACENCY_UPPER = 0, IGRAPH_GET_ADJACENCY_LOWER, IGRAPH_GET_ADJACENCY_BOTH } igraph_get_adjacency_t; typedef enum { IGRAPH_DEGSEQ_SIMPLE = 0, IGRAPH_DEGSEQ_VL, IGRAPH_DEGSEQ_SIMPLE_NO_MULTIPLE, IGRAPH_DEGSEQ_SIMPLE_NO_MULTIPLE_UNIFORM } igraph_degseq_t; typedef enum { IGRAPH_REALIZE_DEGSEQ_SMALLEST = 0, IGRAPH_REALIZE_DEGSEQ_LARGEST, IGRAPH_REALIZE_DEGSEQ_INDEX } igraph_realize_degseq_t; typedef enum { IGRAPH_RANDOM_TREE_PRUFER = 0, IGRAPH_RANDOM_TREE_LERW } igraph_random_tree_t; typedef enum { IGRAPH_FILEFORMAT_EDGELIST = 0, IGRAPH_FILEFORMAT_NCOL, IGRAPH_FILEFORMAT_PAJEK, IGRAPH_FILEFORMAT_LGL, IGRAPH_FILEFORMAT_GRAPHML } igraph_fileformat_type_t; typedef enum { IGRAPH_REWIRING_SIMPLE = 0, IGRAPH_REWIRING_SIMPLE_LOOPS } igraph_rewiring_t; typedef enum { IGRAPH_EDGEORDER_ID = 0, IGRAPH_EDGEORDER_FROM, IGRAPH_EDGEORDER_TO } igraph_edgeorder_type_t; typedef enum { IGRAPH_TO_DIRECTED_ARBITRARY = 0, IGRAPH_TO_DIRECTED_MUTUAL } igraph_to_directed_t; typedef enum { IGRAPH_TO_UNDIRECTED_EACH = 0, IGRAPH_TO_UNDIRECTED_COLLAPSE, IGRAPH_TO_UNDIRECTED_MUTUAL } igraph_to_undirected_t; typedef enum { IGRAPH_VCONN_NEI_ERROR = 0, IGRAPH_VCONN_NEI_NUMBER_OF_NODES, IGRAPH_VCONN_NEI_IGNORE, IGRAPH_VCONN_NEI_NEGATIVE } igraph_vconn_nei_t; typedef enum { IGRAPH_SPINCOMM_UPDATE_SIMPLE = 0, IGRAPH_SPINCOMM_UPDATE_CONFIG } igraph_spincomm_update_t; typedef enum { IGRAPH_DONT_SIMPLIFY = 0, IGRAPH_SIMPLIFY } igraph_lazy_adlist_simplify_t; typedef enum { IGRAPH_TRANSITIVITY_NAN = 0, IGRAPH_TRANSITIVITY_ZERO } igraph_transitivity_mode_t; typedef enum { IGRAPH_SPINCOMM_IMP_ORIG = 0, IGRAPH_SPINCOMM_IMP_NEG } igraph_spinglass_implementation_t; typedef enum { IGRAPH_COMMCMP_VI = 0, IGRAPH_COMMCMP_NMI, IGRAPH_COMMCMP_SPLIT_JOIN, IGRAPH_COMMCMP_RAND, IGRAPH_COMMCMP_ADJUSTED_RAND } igraph_community_comparison_t; typedef enum { IGRAPH_ADD_WEIGHTS_NO = 0, IGRAPH_ADD_WEIGHTS_YES, IGRAPH_ADD_WEIGHTS_IF_PRESENT } igraph_add_weights_t; typedef enum { IGRAPH_BARABASI_BAG = 0, IGRAPH_BARABASI_PSUMTREE, IGRAPH_BARABASI_PSUMTREE_MULTIPLE } igraph_barabasi_algorithm_t; typedef enum { IGRAPH_FAS_EXACT_IP = 0, IGRAPH_FAS_APPROX_EADES } igraph_fas_algorithm_t; typedef enum { IGRAPH_SUBGRAPH_AUTO = 0, IGRAPH_SUBGRAPH_COPY_AND_DELETE, IGRAPH_SUBGRAPH_CREATE_FROM_SCRATCH } igraph_subgraph_implementation_t; typedef enum { IGRAPH_IMITATE_AUGMENTED = 0, IGRAPH_IMITATE_BLIND, IGRAPH_IMITATE_CONTRACTED } igraph_imitate_algorithm_t; typedef igraph_real_t igraph_scalar_function_t(const igraph_vector_t *var, const igraph_vector_t *par, void* extra); typedef void igraph_vector_function_t(const igraph_vector_t *var, const igraph_vector_t *par, igraph_vector_t* res, void* extra); typedef enum { IGRAPH_LAYOUT_GRID = 0, IGRAPH_LAYOUT_NOGRID, IGRAPH_LAYOUT_AUTOGRID } igraph_layout_grid_t; typedef enum { IGRAPH_RANDOM_WALK_STUCK_ERROR = 0, IGRAPH_RANDOM_WALK_STUCK_RETURN } igraph_random_walk_stuck_t; __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_interface.h0000644000076500000240000001032413614300625025675 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_INTERFACE_H #define IGRAPH_INTERFACE_H #include "igraph_decls.h" #include "igraph_types.h" #include "igraph_datatype.h" #include "igraph_iterators.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* Interface */ /* -------------------------------------------------- */ DECLDIR int igraph_empty(igraph_t *graph, igraph_integer_t n, igraph_bool_t directed); DECLDIR int igraph_empty_attrs(igraph_t *graph, igraph_integer_t n, igraph_bool_t directed, void *attr); DECLDIR void igraph_destroy(igraph_t *graph); DECLDIR int igraph_copy(igraph_t *to, const igraph_t *from); DECLDIR int igraph_add_edges(igraph_t *graph, const igraph_vector_t *edges, void *attr); DECLDIR int igraph_add_vertices(igraph_t *graph, igraph_integer_t nv, void *attr); DECLDIR int igraph_delete_edges(igraph_t *graph, igraph_es_t edges); DECLDIR int igraph_delete_vertices(igraph_t *graph, const igraph_vs_t vertices); DECLDIR int igraph_delete_vertices_idx(igraph_t *graph, const igraph_vs_t vertices, igraph_vector_t *idx, igraph_vector_t *invidx); DECLDIR igraph_integer_t igraph_vcount(const igraph_t *graph); DECLDIR igraph_integer_t igraph_ecount(const igraph_t *graph); DECLDIR int igraph_neighbors(const igraph_t *graph, igraph_vector_t *neis, igraph_integer_t vid, igraph_neimode_t mode); DECLDIR igraph_bool_t igraph_is_directed(const igraph_t *graph); DECLDIR int igraph_degree(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, igraph_neimode_t mode, igraph_bool_t loops); DECLDIR int igraph_edge(const igraph_t *graph, igraph_integer_t eid, igraph_integer_t *from, igraph_integer_t *to); DECLDIR int igraph_edges(const igraph_t *graph, igraph_es_t eids, igraph_vector_t *edges); DECLDIR int igraph_get_eid(const igraph_t *graph, igraph_integer_t *eid, igraph_integer_t from, igraph_integer_t to, igraph_bool_t directed, igraph_bool_t error); DECLDIR int igraph_get_eids(const igraph_t *graph, igraph_vector_t *eids, const igraph_vector_t *pairs, const igraph_vector_t *path, igraph_bool_t directed, igraph_bool_t error); DECLDIR int igraph_get_eids_multi(const igraph_t *graph, igraph_vector_t *eids, const igraph_vector_t *pairs, const igraph_vector_t *path, igraph_bool_t directed, igraph_bool_t error); DECLDIR int igraph_adjacent(const igraph_t *graph, igraph_vector_t *eids, igraph_integer_t vid, igraph_neimode_t mode); /* deprecated */ DECLDIR int igraph_incident(const igraph_t *graph, igraph_vector_t *eids, igraph_integer_t vid, igraph_neimode_t mode); #define IGRAPH_FROM(g,e) ((igraph_integer_t)(VECTOR((g)->from)[(long int)(e)])) #define IGRAPH_TO(g,e) ((igraph_integer_t)(VECTOR((g)->to) [(long int)(e)])) #define IGRAPH_OTHER(g,e,v) \ ((igraph_integer_t)(IGRAPH_TO(g,(e))==(v) ? IGRAPH_FROM((g),(e)) : IGRAPH_TO((g),(e)))) __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_cocitation.h0000644000076500000240000000543613614300625026101 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_COCITATION_H #define IGRAPH_COCITATION_H #include "igraph_decls.h" #include "igraph_types.h" #include "igraph_matrix.h" #include "igraph_datatype.h" #include "igraph_iterators.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* Cocitation and other similarity measures */ /* -------------------------------------------------- */ DECLDIR int igraph_cocitation(const igraph_t *graph, igraph_matrix_t *res, const igraph_vs_t vids); DECLDIR int igraph_bibcoupling(const igraph_t *graph, igraph_matrix_t *res, const igraph_vs_t vids); DECLDIR int igraph_similarity_jaccard(const igraph_t *graph, igraph_matrix_t *res, const igraph_vs_t vids, igraph_neimode_t mode, igraph_bool_t loops); DECLDIR int igraph_similarity_jaccard_pairs(const igraph_t *graph, igraph_vector_t *res, const igraph_vector_t *pairs, igraph_neimode_t mode, igraph_bool_t loops); DECLDIR int igraph_similarity_jaccard_es(const igraph_t *graph, igraph_vector_t *res, const igraph_es_t es, igraph_neimode_t mode, igraph_bool_t loops); DECLDIR int igraph_similarity_dice(const igraph_t *graph, igraph_matrix_t *res, const igraph_vs_t vids, igraph_neimode_t mode, igraph_bool_t loops); DECLDIR int igraph_similarity_dice_pairs(const igraph_t *graph, igraph_vector_t *res, const igraph_vector_t *pairs, igraph_neimode_t mode, igraph_bool_t loops); DECLDIR int igraph_similarity_dice_es(const igraph_t *graph, igraph_vector_t *res, const igraph_es_t es, igraph_neimode_t mode, igraph_bool_t loops); DECLDIR int igraph_similarity_inverse_log_weighted(const igraph_t *graph, igraph_matrix_t *res, const igraph_vs_t vids, igraph_neimode_t mode); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_progress.h0000644000076500000240000001535213614300625025607 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_PROGRESS_H #define IGRAPH_PROGRESS_H #include "igraph_decls.h" #include "igraph_types.h" __BEGIN_DECLS /** * \section about_progress_handlers About progress handlers * * It is often useful to report the progress of some long * calculation, to allow the user to follow the computation and * guess the total running time. A couple of igraph functions * support this at the time of writing, hopefully more will support it * in the future. * * * * To see the progress of a computation, the user has to install a * progress handler, as there is none installed by default. * If an igraph function supports progress reporting, then it * calls the installed progress handler periodically, and passes a * percentage value to it, the percentage of computation already * performed. To install a progress handler, you need to call * \ref igraph_set_progress_handler(). Currently there is a single * pre-defined progress handler, called \ref * igraph_progress_handler_stderr(). * */ /** * \section writing_progress_handlers Writing progress handlers * * * To write a new progress handler, one needs to create a function of * type \ref igraph_progress_handler_t. The new progress handler * can then be installed with the \ref igraph_set_progress_handler() * function. * * * * One can assume that the first progress handler call from a * calculation will be call with zero as the \p percentage argument, * and the last call from a function will have 100 as the \p * percentage argument. Note, however, that if an error happens in the * middle of a computation, then the 100 percent call might be * omitted. * */ /** * \section igraph_functions_with_progress Writing igraph functions with progress reporting * * * If you want to write a function that uses igraph and supports * progress reporting, you need to include \ref igraph_progress() * calls in your function, usually via the \ref IGRAPH_PROGRESS() * macro. * * * * It is good practice to always include a call to \ref * igraph_progress() with a zero \p percentage argument, before the * computation; and another call with 100 \p percentage value * after the computation is completed. * * * * It is also good practice \em not to call \ref igraph_progress() too * often, as this would slow down the computation. It might not be * worth to support progress reporting in functions with linear or * log-linear time complexity, as these are fast, even with a large * amount of data. For functions with quadratic or higher time * complexity make sure that the time complexity of the progress * reporting is constant or at least linear. In practice this means * having at most O(n) progress checks and at most 100 \reg * igraph_progress() calls. * */ /** * \section progress_and_threads Multi-threaded programs * * * In multi-threaded programs, each thread has its own progress * handler, if thread-local storage is supported and igraph is * thread-safe. See the \ref IGRAPH_THREAD_SAFE macro for checking * whether an igraph build is thread-safe. * */ /* -------------------------------------------------- */ /* Progress handlers */ /* -------------------------------------------------- */ /** * \typedef igraph_progress_handler_t * \brief Type of progress handler functions * * This is the type of the igraph progress handler functions. * There is currently one such predefined function, * \ref igraph_progress_handler_stderr(), but the user can * write and set up more sophisticated ones. * \param message A string describing the function or algorithm * that is reporting the progress. Current igraph functions * always use the name \p message argument if reporting from the * same function. * \param percent Numeric, the percentage that was completed by the * algorithm or function. * \param data User-defined data. Current igraph functions that * report progress pass a null pointer here. Users can * write their own progress handlers and functions with progress * reporting, and then pass some meaningfull context here. * \return If the return value of the progress handler is not * IGRAPH_SUCCESS (=0), then \ref igraph_progress() returns the * error code \c IGRAPH_INTERRUPTED. The \ref IGRAPH_PROGRESS() * macro frees all memory and finishes the igraph function with * error code \c IGRAPH_INTERRUPTED in this case. */ typedef int igraph_progress_handler_t(const char *message, igraph_real_t percent, void *data); extern igraph_progress_handler_t igraph_progress_handler_stderr; DECLDIR igraph_progress_handler_t * igraph_set_progress_handler(igraph_progress_handler_t new_handler); DECLDIR int igraph_progress(const char *message, igraph_real_t percent, void *data); DECLDIR int igraph_progressf(const char *message, igraph_real_t percent, void *data, ...); /** * \define IGRAPH_PROGRESS * \brief Report progress. * * The standard way to report progress from an igraph function * \param message A string, a textual message that references the * calculation under progress. * \param percent Numeric scalar, the percentage that is complete. * \param data User-defined data, this can be used in user-defined * progress handler functions, from user-written igraph functions. * \return If the progress handler returns with \c IGRAPH_INTERRUPTED, * then this macro frees up the igraph allocated memory for * temporary data and returns to the caller with \c * IGRAPH_INTERRUPTED. */ #define IGRAPH_PROGRESS(message, percent, data) \ do { \ if (igraph_progress((message), (percent), (data)) != IGRAPH_SUCCESS) { \ IGRAPH_FINALLY_FREE(); \ return IGRAPH_INTERRUPTED; \ } \ } while (0) __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_flow.h0000644000076500000240000001702713614300625024713 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2003-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_FLOW_H #define IGRAPH_FLOW_H #include "igraph_decls.h" #include "igraph_constants.h" #include "igraph_types.h" #include "igraph_datatype.h" #include "igraph_vector_ptr.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* MAximum flows, minimum cuts & such */ /* -------------------------------------------------- */ /** * \typedef igraph_maxflow_stats_t * A simple data type to return some statistics from the * push-relabel maximum flow solver. * * \param nopush The number of push operations performed. * \param norelabel The number of relabel operarions performed. * \param nogap The number of times the gap heuristics was used. * \param nogapnodes The total number of vertices that were * omitted form further calculations because of the gap * heuristics. * \param nobfs The number of times the reverse BFS was run to * assign good values to the height function. This includes * an initial run before the whole algorithm, so it is always * at least one. */ typedef struct { int nopush, norelabel, nogap, nogapnodes, nobfs; } igraph_maxflow_stats_t; DECLDIR int igraph_maxflow(const igraph_t *graph, igraph_real_t *value, igraph_vector_t *flow, igraph_vector_t *cut, igraph_vector_t *partition, igraph_vector_t *partition2, igraph_integer_t source, igraph_integer_t target, const igraph_vector_t *capacity, igraph_maxflow_stats_t *stats); DECLDIR int igraph_maxflow_value(const igraph_t *graph, igraph_real_t *value, igraph_integer_t source, igraph_integer_t target, const igraph_vector_t *capacity, igraph_maxflow_stats_t *stats); DECLDIR int igraph_st_mincut(const igraph_t *graph, igraph_real_t *value, igraph_vector_t *cut, igraph_vector_t *partition, igraph_vector_t *partition2, igraph_integer_t source, igraph_integer_t target, const igraph_vector_t *capacity); DECLDIR int igraph_st_mincut_value(const igraph_t *graph, igraph_real_t *res, igraph_integer_t source, igraph_integer_t target, const igraph_vector_t *capacity); DECLDIR int igraph_mincut_value(const igraph_t *graph, igraph_real_t *res, const igraph_vector_t *capacity); DECLDIR int igraph_mincut(const igraph_t *graph, igraph_real_t *value, igraph_vector_t *partition, igraph_vector_t *partition2, igraph_vector_t *cut, const igraph_vector_t *capacity); DECLDIR int igraph_st_vertex_connectivity(const igraph_t *graph, igraph_integer_t *res, igraph_integer_t source, igraph_integer_t target, igraph_vconn_nei_t neighbors); DECLDIR int igraph_vertex_connectivity(const igraph_t *graph, igraph_integer_t *res, igraph_bool_t checks); DECLDIR int igraph_st_edge_connectivity(const igraph_t *graph, igraph_integer_t *res, igraph_integer_t source, igraph_integer_t target); DECLDIR int igraph_edge_connectivity(const igraph_t *graph, igraph_integer_t *res, igraph_bool_t checks); DECLDIR int igraph_edge_disjoint_paths(const igraph_t *graph, igraph_integer_t *res, igraph_integer_t source, igraph_integer_t target); DECLDIR int igraph_vertex_disjoint_paths(const igraph_t *graph, igraph_integer_t *res, igraph_integer_t source, igraph_integer_t target); DECLDIR int igraph_adhesion(const igraph_t *graph, igraph_integer_t *res, igraph_bool_t checks); DECLDIR int igraph_cohesion(const igraph_t *graph, igraph_integer_t *res, igraph_bool_t checks); /* s-t cut listing related stuff */ DECLDIR int igraph_even_tarjan_reduction(const igraph_t *graph, igraph_t *graphbar, igraph_vector_t *capacity); DECLDIR int igraph_residual_graph(const igraph_t *graph, const igraph_vector_t *capacity, igraph_t *residual, igraph_vector_t *residual_capacity, const igraph_vector_t *flow); int igraph_i_residual_graph(const igraph_t *graph, const igraph_vector_t *capacity, igraph_t *residual, igraph_vector_t *residual_capacity, const igraph_vector_t *flow, igraph_vector_t *tmp); int igraph_i_reverse_residual_graph(const igraph_t *graph, const igraph_vector_t *capacity, igraph_t *residual, const igraph_vector_t *flow, igraph_vector_t *tmp); DECLDIR int igraph_reverse_residual_graph(const igraph_t *graph, const igraph_vector_t *capacity, igraph_t *residual, const igraph_vector_t *flow); DECLDIR int igraph_dominator_tree(const igraph_t *graph, igraph_integer_t root, igraph_vector_t *dom, igraph_t *domtree, igraph_vector_t *leftout, igraph_neimode_t mode); DECLDIR int igraph_all_st_cuts(const igraph_t *graph, igraph_vector_ptr_t *cuts, igraph_vector_ptr_t *partition1s, igraph_integer_t source, igraph_integer_t target); DECLDIR int igraph_all_st_mincuts(const igraph_t *graph, igraph_real_t *value, igraph_vector_ptr_t *cuts, igraph_vector_ptr_t *partition1s, igraph_integer_t source, igraph_integer_t target, const igraph_vector_t *capacity); DECLDIR int igraph_gomory_hu_tree(const igraph_t *graph, igraph_t *tree, igraph_vector_t *flows, const igraph_vector_t *capacity); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_error.h0000644000076500000240000006617013614300625025100 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2003-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_ERROR_H #define IGRAPH_ERROR_H #include #include "igraph_decls.h" __BEGIN_DECLS /* This file contains the igraph error handling. * Most bits are taken literally from the GSL library (with the GSL_ * prefix renamed to IGRAPH_), as I couldn't find a better way to do * them. */ /** * \section errorhandlingbasics Error handling basics * * \a igraph functions can run into various problems preventing them * from normal operation. The user might have supplied invalid arguments, * e.g. a non-square matrix when a square-matrix was expected, or the program * has run out of memory while some more memory allocation is required, etc. * * * By default \a igraph aborts the program when it runs into an * error. While this behavior might be good enough for smaller programs, * it is without doubt avoidable in larger projects. Please read further * if your project requires more sophisticated error handling. You can * safely skip the rest of this chapter otherwise. * */ /** * \section errorhandlers Error handlers * * * If \a igraph runs into an error - an invalid argument was supplied * to a function, or we've ran out of memory - the control is * transferred to the \emb error handler \eme function. * * The default error handler is \ref igraph_error_handler_abort which * prints an error message and aborts the program. * * * The \ref igraph_set_error_handler() function can be used to set a new * error handler function of type \ref igraph_error_handler_t; see the * documentation of this type for details. * * * There are two other predefined error handler functions, * \ref igraph_error_handler_ignore and \ref igraph_error_handler_printignore. * These deallocate the temporarily allocated memory (more about this * later) and return with the error code. The latter also prints an * error message. If you use these error handlers you need to take * care about possible errors yourself by checking the return value of * (almost) every non-void \a igraph function. * * Independently of the error handler installed, all functions in the * library do their best to leave their arguments * \em semantically unchanged if an error * happens. By semantically we mean that the implementation of an * object supplied as an argument might change, but its * \quote meaning \endquote in most cases does not. The rare occasions * when this rule is violated are documented in this manual. * */ /** * \section errorcodes Error codes * * Every \a igraph function which can fail return a * single integer error code. Some functions are very simple and * cannot run into any error, these may return other types, or * \type void as well. The error codes are defined by the * \ref igraph_error_type_t enumeration. * */ /** * \section writing_error_handlers Writing error handlers * * * The contents of the rest of this chapter might be useful only * for those who want to create an interface to \a igraph from another * language. Most readers can safely skip to the next chapter. * * * * You can write and install error handlers simply by defining a * function of type \ref igraph_error_handler_t and calling * \ref igraph_set_error_handler(). This feature is useful for interface * writers, as \a igraph will have the chance to * signal errors the appropriate way, eg. the R interface defines an * error handler which calls the error() * function, as required by R, while the Python interface has an error * handler which raises an exception according to the Python way. * * * If you want to write an error handler, your error handler should * call \ref IGRAPH_FINALLY_FREE() to deallocate all temporary memory to * prevent memory leaks. * */ /** * \section error_handling_internals Error handling internals * * * If an error happens, the functions in the library call the * \ref IGRAPH_ERROR macro with a textual description of the error and an * \a igraph error code. This macro calls (through the \ref * igraph_error() function) the installed error handler. Another useful * macro is \ref IGRAPH_CHECK(). This checks the return value of its * argument, which is normally a function call, and calls \ref * IGRAPH_ERROR if it is not \c IGRAPH_SUCCESS. * */ /** * \section deallocating_memory Deallocating memory * * * If a function runs into an error (and the program is not aborted) * the error handler should deallocate all temporary memory. This is * done by storing the address and the destroy function of all temporary * objects in a stack. The \ref IGRAPH_FINALLY function declares an object as * temporary by placing its address in the stack. If an \a igraph function returns * with success it calls \ref IGRAPH_FINALLY_CLEAN() with the * number of objects to remove from the stack. If an error happens * however, the error handler should call \ref IGRAPH_FINALLY_FREE() to * deallocate each object added to the stack. This means that the * temporary objects allocated in the calling function (and etc.) will * be freed as well. * */ /** * \section writing_functions_error_handling Writing \a igraph functions with * proper error handling * * * There are some simple rules to keep in order to have functions * behaving well in erroneous situations. First, check the arguments * of the functions and call \ref IGRAPH_ERROR if they are invalid. Second, * call \ref IGRAPH_FINALLY on each dynamically allocated object and call * \ref IGRAPH_FINALLY_CLEAN() with the proper argument before returning. Third, use * \ref IGRAPH_CHECK on all \a igraph function calls which can generate errors. * * * The size of the stack used for this bookkeeping is fixed, and * small. If you want to allocate several objects, write a destroy * function which can deallocate all of these. See the * adjlist.c file in the * \a igraph source for an example. * * * For some functions these mechanisms are simply not flexible * enough. These functions should define their own error handlers and * restore the error handler before they return. * */ /** * \section error_handling_threads Error handling and threads * * * It is likely that the \a igraph error handling * method is \em not thread-safe, mainly because of * the static global stack which is used to store the address of the * temporarily allocated objects. This issue might be addressed in a * later version of \a igraph. * */ /** * \typedef igraph_error_handler_t * \brief Type of error handler functions. * * This is the type of the error handler functions. * \param reason Textual description of the error. * \param file The source file in which the error is noticed. * \param line The number of the line in the source file which triggered * the error * \param igraph_errno The \a igraph error code. */ typedef void igraph_error_handler_t (const char * reason, const char * file, int line, int igraph_errno); /** * \var igraph_error_handler_abort * \brief Abort program in case of error. * * The default error handler, prints an error message and aborts the * program. */ extern igraph_error_handler_t igraph_error_handler_abort; /** * \var igraph_error_handler_ignore * \brief Ignore errors. * * This error handler frees the temporarily allocated memory and returns * with the error code. */ extern igraph_error_handler_t igraph_error_handler_ignore; /** * \var igraph_error_handler_printignore * \brief Print and ignore errors. * * Frees temporarily allocated memory, prints an error message to the * standard error and returns with the error code. */ extern igraph_error_handler_t igraph_error_handler_printignore; /** * \function igraph_set_error_handler * \brief Set a new error handler. * * Installs a new error handler. If called with 0, it installs the * default error handler (which is currently * \ref igraph_error_handler_abort). * \param new_handler The error handler function to install. * \return The old error handler function. This should be saved and * restored if \p new_handler is not needed any * more. */ DECLDIR igraph_error_handler_t* igraph_set_error_handler(igraph_error_handler_t* new_handler); /** * \typedef igraph_error_type_t * \brief Error code type. * These are the possible values returned by \a igraph functions. * Note that these are interesting only if you defined an error handler * with \ref igraph_set_error_handler(). Otherwise the program is aborted * and the function causing the error never returns. * * \enumval IGRAPH_SUCCESS The function successfully completed its task. * \enumval IGRAPH_FAILURE Something went wrong. You'll almost never * meet this error as normally more specific error codes are used. * \enumval IGRAPH_ENOMEM There wasn't enough memory to allocate * on the heap. * \enumval IGRAPH_PARSEERROR A parse error was found in a file. * \enumval IGRAPH_EINVAL A parameter's value is invalid. Eg. negative * number was specified as the number of vertices. * \enumval IGRAPH_EXISTS A graph/vertex/edge attribute is already * installed with the given name. * \enumval IGRAPH_EINVEVECTOR Invalid vector of vertex ids. A vertex id * is either negative or bigger than the number of vertices minus one. * \enumval IGRAPH_EINVVID Invalid vertex id, negative or too big. * \enumval IGRAPH_NONSQUARE A non-square matrix was received while a * square matrix was expected. * \enumval IGRAPH_EINVMODE Invalid mode parameter. * \enumval IGRAPH_EFILE A file operation failed. Eg. a file doesn't exist, * or the user has no rights to open it. * \enumval IGRAPH_UNIMPLEMENTED Attempted to call an unimplemented or * disabled (at compile-time) function. * \enumval IGRAPH_DIVERGED A numeric algorithm failed to converge. * \enumval IGRAPH_ARPACK_PROD Matrix-vector product failed. * \enumval IGRAPH_ARPACK_NPOS N must be positive. * \enumval IGRAPH_ARPACK_NEVNPOS NEV must be positive. * \enumval IGRAPH_ARPACK_NCVSMALL NCV must be bigger. * \enumval IGRAPH_ARPACK_NONPOSI Maximum number of iterations should be positive. * \enumval IGRAPH_ARPACK_WHICHINV Invalid WHICH parameter. * \enumval IGRAPH_ARPACK_BMATINV Invalid BMAT parameter. * \enumval IGRAPH_ARPACK_WORKLSMALL WORKL is too small. * \enumval IGRAPH_ARPACK_TRIDERR LAPACK error in tridiagonal eigenvalue calculation. * \enumval IGRAPH_ARPACK_ZEROSTART Starting vector is zero. * \enumval IGRAPH_ARPACK_MODEINV MODE is invalid. * \enumval IGRAPH_ARPACK_MODEBMAT MODE and BMAT are not compatible. * \enumval IGRAPH_ARPACK_ISHIFT ISHIFT must be 0 or 1. * \enumval IGRAPH_ARPACK_NEVBE NEV and WHICH='BE' are incompatible. * \enumval IGRAPH_ARPACK_NOFACT Could not build an Arnoldi factorization. * \enumval IGRAPH_ARPACK_FAILED No eigenvalues to sufficient accuracy. * \enumval IGRAPH_ARPACK_HOWMNY HOWMNY is invalid. * \enumval IGRAPH_ARPACK_HOWMNYS HOWMNY='S' is not implemented. * \enumval IGRAPH_ARPACK_EVDIFF Different number of converged Ritz values. * \enumval IGRAPH_ARPACK_SHUR Error from calculation of a real Schur form. * \enumval IGRAPH_ARPACK_LAPACK LAPACK (dtrevc) error for calculating eigenvectors. * \enumval IGRAPH_ARPACK_UNKNOWN Unknown ARPACK error. * \enumval IGRAPH_ENEGLOOP Negative loop detected while calculating shortest paths. * \enumval IGRAPH_EINTERNAL Internal error, likely a bug in igraph. * \enumval IGRAPH_EDIVZERO Big integer division by zero. * \enumval IGARPH_GLP_EBOUND GLPK error (GLP_EBOUND). * \enumval IGARPH_GLP_EROOT GLPK error (GLP_EROOT). * \enumval IGARPH_GLP_ENOPFS GLPK error (GLP_ENOPFS). * \enumval IGARPH_GLP_ENODFS GLPK error (GLP_ENODFS). * \enumval IGARPH_GLP_EFAIL GLPK error (GLP_EFAIL). * \enumval IGARPH_GLP_EMIPGAP GLPK error (GLP_EMIPGAP). * \enumval IGARPH_GLP_ETMLIM GLPK error (GLP_ETMLIM). * \enumval IGARPH_GLP_ESTOP GLPK error (GLP_ESTOP). * \enumval IGRAPH_EATTRIBUTES Attribute handler error. The user is not * expected to find this; it is signalled if some igraph function is * not using the attribute handler interface properly. * \enumval IGRAPH_EATTRCOMBINE Unimplemented attribute combination * method for the given attribute type. * \enumval IGRAPH_ELAPACK A LAPACK call resulted an error. * \enumval IGRAPH_EDRL Internal error in the DrL layout generator. * \enumval IGRAPH_EOVERFLOW Integer or double overflow. * \enumval IGRAPH_EGLP Internal GLPK error. * \enumval IGRAPH_CPUTIME CPU time exceeded. * \enumval IGRAPH_EUNDERFLOW Integer or double underflow. * \enumval IGRAPH_ERWSTUCK Random walk got stuck. */ /* Each enum value below must have a corresponding error string in * igraph_i_error_strings[] in igraph_error.c */ typedef enum { IGRAPH_SUCCESS = 0, IGRAPH_FAILURE = 1, IGRAPH_ENOMEM = 2, IGRAPH_PARSEERROR = 3, IGRAPH_EINVAL = 4, IGRAPH_EXISTS = 5, IGRAPH_EINVEVECTOR = 6, IGRAPH_EINVVID = 7, IGRAPH_NONSQUARE = 8, IGRAPH_EINVMODE = 9, IGRAPH_EFILE = 10, IGRAPH_UNIMPLEMENTED = 12, IGRAPH_INTERRUPTED = 13, IGRAPH_DIVERGED = 14, IGRAPH_ARPACK_PROD = 15, IGRAPH_ARPACK_NPOS = 16, IGRAPH_ARPACK_NEVNPOS = 17, IGRAPH_ARPACK_NCVSMALL = 18, IGRAPH_ARPACK_NONPOSI = 19, IGRAPH_ARPACK_WHICHINV = 20, IGRAPH_ARPACK_BMATINV = 21, IGRAPH_ARPACK_WORKLSMALL = 22, IGRAPH_ARPACK_TRIDERR = 23, IGRAPH_ARPACK_ZEROSTART = 24, IGRAPH_ARPACK_MODEINV = 25, IGRAPH_ARPACK_MODEBMAT = 26, IGRAPH_ARPACK_ISHIFT = 27, IGRAPH_ARPACK_NEVBE = 28, IGRAPH_ARPACK_NOFACT = 29, IGRAPH_ARPACK_FAILED = 30, IGRAPH_ARPACK_HOWMNY = 31, IGRAPH_ARPACK_HOWMNYS = 32, IGRAPH_ARPACK_EVDIFF = 33, IGRAPH_ARPACK_SHUR = 34, IGRAPH_ARPACK_LAPACK = 35, IGRAPH_ARPACK_UNKNOWN = 36, IGRAPH_ENEGLOOP = 37, IGRAPH_EINTERNAL = 38, IGRAPH_ARPACK_MAXIT = 39, IGRAPH_ARPACK_NOSHIFT = 40, IGRAPH_ARPACK_REORDER = 41, IGRAPH_EDIVZERO = 42, IGRAPH_GLP_EBOUND = 43, IGRAPH_GLP_EROOT = 44, IGRAPH_GLP_ENOPFS = 45, IGRAPH_GLP_ENODFS = 46, IGRAPH_GLP_EFAIL = 47, IGRAPH_GLP_EMIPGAP = 48, IGRAPH_GLP_ETMLIM = 49, IGRAPH_GLP_ESTOP = 50, IGRAPH_EATTRIBUTES = 51, IGRAPH_EATTRCOMBINE = 52, IGRAPH_ELAPACK = 53, IGRAPH_EDRL = 54, IGRAPH_EOVERFLOW = 55, IGRAPH_EGLP = 56, IGRAPH_CPUTIME = 57, IGRAPH_EUNDERFLOW = 58, IGRAPH_ERWSTUCK = 59, IGRAPH_STOP = 60, /* undocumented, used internally; signals a request to stop in functions like igraph_i_maximal_cliques_bk */ } igraph_error_type_t; /** * \define IGRAPH_ERROR * \brief Trigger an error. * * \a igraph functions usually use this macro when they notice an error. * It calls * \ref igraph_error() with the proper parameters and if that returns * the macro returns the "calling" function as well, with the error * code. If for some (suspicious) reason you want to call the error * handler without returning from the current function, call * \ref igraph_error() directly. * \param reason Textual description of the error. This should be * something more descriptive than the text associated with the error * code. Eg. if the error code is \c IGRAPH_EINVAL, * its associated text (see \ref igraph_strerror()) is "Invalid * value" and this string should explain which parameter was invalid * and maybe why. * \param igraph_errno The \a igraph error code. */ #define IGRAPH_ERROR(reason,igraph_errno) \ do { \ igraph_error (reason, __FILE__, __LINE__, igraph_errno) ; \ return igraph_errno ; \ } while (0) /** * \function igraph_error * \brief Trigger an error. * * \a igraph functions usually call this function (most often via the * \ref IGRAPH_ERROR macro) if they notice an error. * It calls the currently installed error handler function with the * supplied arguments. * * \param reason Textual description of the error. * \param file The source file in which the error was noticed. * \param line The number of line in the source file which triggered the * error. * \param igraph_errno The \a igraph error code. * \return the error code (if it returns) * * \sa igraph_errorf(). */ DECLDIR int igraph_error(const char *reason, const char *file, int line, int igraph_errno); /** * \function igraph_errorf * \brief Trigger an error, printf-like version. * * \param reason Textual description of the error, interpreted as * a printf format string. * \param file The source file in which the error was noticed. * \param line The line in the source file which triggered the error. * \param igraph_errno The \a igraph error code. * \param ... Additional parameters, the values to substitute into the * format string. * * \sa igraph_error(). */ DECLDIR int igraph_errorf(const char *reason, const char *file, int line, int igraph_errno, ...); DECLDIR int igraph_errorvf(const char *reason, const char *file, int line, int igraph_errno, va_list ap); /** * \function igraph_strerror * \brief Textual description of an error. * * This is a simple utility function, it gives a short general textual * description for an \a igraph error code. * * \param igraph_errno The \a igraph error code. * \return pointer to the textual description of the error code. */ DECLDIR const char* igraph_strerror(const int igraph_errno); #define IGRAPH_ERROR_SELECT_2(a,b) ((a) != IGRAPH_SUCCESS ? (a) : ((b) != IGRAPH_SUCCESS ? (b) : IGRAPH_SUCCESS)) #define IGRAPH_ERROR_SELECT_3(a,b,c) ((a) != IGRAPH_SUCCESS ? (a) : IGRAPH_ERROR_SELECT_2(b,c)) #define IGRAPH_ERROR_SELECT_4(a,b,c,d) ((a) != IGRAPH_SUCCESS ? (a) : IGRAPH_ERROR_SELECT_3(b,c,d)) #define IGRAPH_ERROR_SELECT_5(a,b,c,d,e) ((a) != IGRAPH_SUCCESS ? (a) : IGRAPH_ERROR_SELECT_4(b,c,d,e)) /* Now comes the more convenient error handling macro arsenal. * Ideas taken from exception.{h,c} by Laurent Deniau see * http://cern.ch/Laurent.Deniau/html/oopc/oopc.html#Exceptions for more * information. We don't use the exception handling code though. */ struct igraph_i_protectedPtr { int all; void *ptr; void (*func)(void*); }; typedef void igraph_finally_func_t (void*); DECLDIR void IGRAPH_FINALLY_REAL(void (*func)(void*), void* ptr); /** * \function IGRAPH_FINALLY_CLEAN * \brief Signal clean deallocation of objects. * * Removes the specified number of objects from the stack of * temporarily allocated objects. Most often this is called just * before returning from a function. * \param num The number of objects to remove from the bookkeeping * stack. */ DECLDIR void IGRAPH_FINALLY_CLEAN(int num); /** * \function IGRAPH_FINALLY_FREE * \brief Deallocate all registered objects. * * Calls the destroy function for all objects in the stack of * temporarily allocated objects. This is usually called only from an * error handler. It is \em not appropriate to use it * instead of destroying each unneeded object of a function, as it * destroys the temporary objects of the caller function (and so on) * as well. */ DECLDIR void IGRAPH_FINALLY_FREE(void); /** * \function IGRAPH_FINALLY_STACK_SIZE * \brief Returns the number of registered objects. * * Returns the number of objects in the stack of temporarily allocated * objects. This function is handy if you write an own igraph routine and * you want to make sure it handles errors properly. A properly written * igraph routine should not leave pointers to temporarily allocated objects * in the finally stack, because otherwise an \ref IGRAPH_FINALLY_FREE call * in another igraph function would result in freeing these objects as well * (and this is really hard to debug, since the error will be not in that * function that shows erroneous behaviour). Therefore, it is advised to * write your own test cases and examine \ref IGRAPH_FINALLY_STACK_SIZE * before and after your test cases - the numbers should be equal. */ DECLDIR int IGRAPH_FINALLY_STACK_SIZE(void); /** * \define IGRAPH_FINALLY_STACK_EMPTY * \brief Returns true if there are no registered objects, false otherwise. * * This is just a shorthand notation for checking that * \ref IGRAPH_FINALLY_STACK_SIZE is zero. */ #define IGRAPH_FINALLY_STACK_EMPTY (IGRAPH_FINALLY_STACK_SIZE() == 0) /** * \define IGRAPH_FINALLY * \brief Register an object for deallocation. * \param func The address of the function which is normally called to * destroy the object. * \param ptr Pointer to the object itself. * * This macro places the address of an object, together with the * address of its destructor in a stack. This stack is used if an * error happens to deallocate temporarily allocated objects to * prevent memory leaks. */ #define IGRAPH_FINALLY(func,ptr) \ IGRAPH_FINALLY_REAL((igraph_finally_func_t*)(func), (ptr)) #if !defined(GCC_VERSION_MAJOR) && defined(__GNUC__) #define GCC_VERSION_MAJOR __GNUC__ #endif #if defined(GCC_VERSION_MAJOR) && (GCC_VERSION_MAJOR >= 3) #define IGRAPH_UNLIKELY(a) __builtin_expect((a), 0) #define IGRAPH_LIKELY(a) __builtin_expect((a), 1) #else #define IGRAPH_UNLIKELY(a) a #define IGRAPH_LIKELY(a) a #endif /** * \define IGRAPH_CHECK * \brief Check the return value of a function call. * * \param a An expression, usually a function call. * * Executes the expression and checks its value. If this is not * \c IGRAPH_SUCCESS, it calls \ref IGRAPH_ERROR with * the value as the error code. Here is an example usage: * \verbatim IGRAPH_CHECK(vector_push_back(&v, 100)); \endverbatim * * There is only one reason to use this macro when writing * \a igraph functions. If the user installs an error handler which * returns to the auxiliary calling code (like \ref * igraph_error_handler_ignore and \ref * igraph_error_handler_printignore), and the \a igraph function * signalling the error is called from another \a igraph function * then we need to make sure that the error is propagated back to * the auxiliary (ie. non-igraph) calling function. This is achieved * by using IGRAPH_CHECK on every \a igraph * call which can return an error code. */ #define IGRAPH_CHECK(a) do { \ int igraph_i_ret=(a); \ if (IGRAPH_UNLIKELY(igraph_i_ret != 0)) {\ IGRAPH_ERROR("", igraph_i_ret); \ } } while (0) /** * \section about_igraph_warnings Warning messages * * * Igraph also supports warning messages in addition to error * messages. Warning messages typically do not terminate the * program, but they are usually crucial to the user. * * * * Igraph warning are handled similarly to errors. There is a * separate warning handler function that is called whenever * an igraph function triggers a warning. This handler can be * set by the \ref igraph_set_warning_handler() function. There are * two predefined simple warning handlers, * \ref igraph_warning_handler_ignore() and * \ref igraph_warning_handler_print(), the latter being the default. * * * * To trigger a warning, igraph functions typically use the * \ref IGRAPH_WARNING() macro, the \ref igraph_warning() function, * or if more flexibility is needed, \ref igraph_warningf(). * */ /** * \typedef igraph_warning_handler_t * Type of igraph warning handler functions * * Currently it is defined to have the same type as * \ref igraph_error_handler_t, although the last (error code) * argument is not used. */ typedef igraph_error_handler_t igraph_warning_handler_t; /** * \function igraph_set_warning_handler * Install a warning handler * * Install the supplied warning handler function. * \param new_handler The new warning handler function to install. * Supply a null pointer here to uninstall the current * warning handler, without installing a new one. * \return The current warning handler function. */ DECLDIR igraph_warning_handler_t* igraph_set_warning_handler(igraph_warning_handler_t* new_handler); extern igraph_warning_handler_t igraph_warning_handler_ignore; extern igraph_warning_handler_t igraph_warning_handler_print; /** * \function igraph_warning * Trigger a warning * * Call this function if you want to trigger a warning from within * a function that uses igraph. * \param reason Textual description of the warning. * \param file The source file in which the warning was noticed. * \param line The number of line in the source file which triggered the * warning. * \param igraph_errno Warnings could have potentially error codes as well, * but this is currently not used in igraph. * \return The supplied error code. */ DECLDIR int igraph_warning(const char *reason, const char *file, int line, int igraph_errno); /** * \function igraph_warningf * Trigger a warning, more flexible printf-like syntax * * This function is similar to \ref igraph_warning(), but * uses a printf-like syntax. It substitutes the additional arguments * into the \p reason template string and calls \ref igraph_warning(). * \param reason Textual description of the warning, a template string * with the same syntax as the standard printf C library function. * \param file The source file in which the warning was noticed. * \param line The number of line in the source file which triggered the * warning. * \param igraph_errno Warnings could have potentially error codes as well, * but this is currently not used in igraph. * \param ... The additional arguments to be substituted into the * template string. * \return The supplied error code. */ DECLDIR int igraph_warningf(const char *reason, const char *file, int line, int igraph_errno, ...); /** * \define IGRAPH_WARNING * Trigger a warning. * * This is the usual way of triggering a warning from an igraph * function. It calls \ref igraph_warning(). * \param reason The warning message. */ #define IGRAPH_WARNING(reason) \ do { \ igraph_warning(reason, __FILE__, __LINE__, -1); \ } while (0) __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_psumtree.h0000644000076500000240000000405513614300625025605 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_PSUMTREE_H #define IGRAPH_PSUMTREE_H #include "igraph_decls.h" #include "igraph_vector.h" __BEGIN_DECLS /* * Defines a partial prefix sum tree which is handy for drawing random numbers * from a dynamic discrete distribution. The first part (0,...,offset - 1) of * the vector v contains the prefixes of the values contained in the latter part * (offset, offset + size - 1) of vector v. */ typedef struct { igraph_vector_t v; long int size; long int offset; } igraph_psumtree_t; DECLDIR int igraph_psumtree_init(igraph_psumtree_t *t, long int size); DECLDIR void igraph_psumtree_reset(igraph_psumtree_t *t); DECLDIR void igraph_psumtree_destroy(igraph_psumtree_t *t); DECLDIR igraph_real_t igraph_psumtree_get(const igraph_psumtree_t *t, long int idx); DECLDIR long int igraph_psumtree_size(const igraph_psumtree_t *t); DECLDIR int igraph_psumtree_search(const igraph_psumtree_t *t, long int *idx, igraph_real_t elem); DECLDIR int igraph_psumtree_update(igraph_psumtree_t *t, long int idx, igraph_real_t new_value); DECLDIR igraph_real_t igraph_psumtree_sum(const igraph_psumtree_t *t); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_sparsemat.h0000644000076500000240000003016613614300625025742 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_SPARSEMAT_H #define IGRAPH_SPARSEMAT_H #include "igraph_types.h" #include "igraph_vector.h" #include "igraph_datatype.h" #include "igraph_arpack.h" #include __BEGIN_DECLS struct cs_di_sparse; struct cs_di_symbolic; struct cs_di_numeric; typedef struct { struct cs_di_sparse *cs; } igraph_sparsemat_t; typedef struct { struct cs_di_symbolic *symbolic; } igraph_sparsemat_symbolic_t; typedef struct { struct cs_di_numeric *numeric; } igraph_sparsemat_numeric_t; typedef enum { IGRAPH_SPARSEMAT_TRIPLET, IGRAPH_SPARSEMAT_CC } igraph_sparsemat_type_t; typedef struct { igraph_sparsemat_t *mat; int pos; int col; } igraph_sparsemat_iterator_t; int igraph_sparsemat_init(igraph_sparsemat_t *A, int rows, int cols, int nzmax); int igraph_sparsemat_copy(igraph_sparsemat_t *to, const igraph_sparsemat_t *from); void igraph_sparsemat_destroy(igraph_sparsemat_t *A); int igraph_sparsemat_realloc(igraph_sparsemat_t *A, int nzmax); long int igraph_sparsemat_nrow(const igraph_sparsemat_t *A); long int igraph_sparsemat_ncol(const igraph_sparsemat_t *B); igraph_sparsemat_type_t igraph_sparsemat_type(const igraph_sparsemat_t *A); igraph_bool_t igraph_sparsemat_is_triplet(const igraph_sparsemat_t *A); igraph_bool_t igraph_sparsemat_is_cc(const igraph_sparsemat_t *A); int igraph_sparsemat_permute(const igraph_sparsemat_t *A, const igraph_vector_int_t *p, const igraph_vector_int_t *q, igraph_sparsemat_t *res); int igraph_sparsemat_index(const igraph_sparsemat_t *A, const igraph_vector_int_t *p, const igraph_vector_int_t *q, igraph_sparsemat_t *res, igraph_real_t *constres); int igraph_sparsemat_entry(igraph_sparsemat_t *A, int row, int col, igraph_real_t elem); int igraph_sparsemat_compress(const igraph_sparsemat_t *A, igraph_sparsemat_t *res); int igraph_sparsemat_transpose(const igraph_sparsemat_t *A, igraph_sparsemat_t *res, int values); igraph_bool_t igraph_sparsemat_is_symmetric(const igraph_sparsemat_t *A); int igraph_sparsemat_dupl(igraph_sparsemat_t *A); int igraph_sparsemat_fkeep(igraph_sparsemat_t *A, int (*fkeep)(int, int, igraph_real_t, void*), void *other); int igraph_sparsemat_dropzeros(igraph_sparsemat_t *A); int igraph_sparsemat_droptol(igraph_sparsemat_t *A, igraph_real_t tol); int igraph_sparsemat_multiply(const igraph_sparsemat_t *A, const igraph_sparsemat_t *B, igraph_sparsemat_t *res); int igraph_sparsemat_add(const igraph_sparsemat_t *A, const igraph_sparsemat_t *B, igraph_real_t alpha, igraph_real_t beta, igraph_sparsemat_t *res); int igraph_sparsemat_gaxpy(const igraph_sparsemat_t *A, const igraph_vector_t *x, igraph_vector_t *res); int igraph_sparsemat_lsolve(const igraph_sparsemat_t *A, const igraph_vector_t *b, igraph_vector_t *res); int igraph_sparsemat_ltsolve(const igraph_sparsemat_t *A, const igraph_vector_t *b, igraph_vector_t *res); int igraph_sparsemat_usolve(const igraph_sparsemat_t *A, const igraph_vector_t *b, igraph_vector_t *res); int igraph_sparsemat_utsolve(const igraph_sparsemat_t *A, const igraph_vector_t *b, igraph_vector_t *res); int igraph_sparsemat_cholsol(const igraph_sparsemat_t *A, const igraph_vector_t *b, igraph_vector_t *res, int order); int igraph_sparsemat_lusol(const igraph_sparsemat_t *A, const igraph_vector_t *b, igraph_vector_t *res, int order, igraph_real_t tol); int igraph_sparsemat_print(const igraph_sparsemat_t *A, FILE *outstream); int igraph_sparsemat_eye(igraph_sparsemat_t *A, int n, int nzmax, igraph_real_t value, igraph_bool_t compress); int igraph_sparsemat_diag(igraph_sparsemat_t *A, int nzmax, const igraph_vector_t *values, igraph_bool_t compress); int igraph_sparsemat(igraph_t *graph, const igraph_sparsemat_t *A, igraph_bool_t directed); int igraph_weighted_sparsemat(igraph_t *graph, const igraph_sparsemat_t *A, igraph_bool_t directed, const char *attr, igraph_bool_t loops); int igraph_get_sparsemat(const igraph_t *graph, igraph_sparsemat_t *res); int igraph_matrix_as_sparsemat(igraph_sparsemat_t *res, const igraph_matrix_t *mat, igraph_real_t tol); int igraph_sparsemat_as_matrix(igraph_matrix_t *res, const igraph_sparsemat_t *spmat); typedef enum { IGRAPH_SPARSEMAT_SOLVE_LU, IGRAPH_SPARSEMAT_SOLVE_QR } igraph_sparsemat_solve_t; int igraph_sparsemat_arpack_rssolve(const igraph_sparsemat_t *A, igraph_arpack_options_t *options, igraph_arpack_storage_t *storage, igraph_vector_t *values, igraph_matrix_t *vectors, igraph_sparsemat_solve_t solvemethod); int igraph_sparsemat_arpack_rnsolve(const igraph_sparsemat_t *A, igraph_arpack_options_t *options, igraph_arpack_storage_t *storage, igraph_matrix_t *values, igraph_matrix_t *vectors); int igraph_sparsemat_lu(const igraph_sparsemat_t *A, const igraph_sparsemat_symbolic_t *dis, igraph_sparsemat_numeric_t *din, double tol); int igraph_sparsemat_qr(const igraph_sparsemat_t *A, const igraph_sparsemat_symbolic_t *dis, igraph_sparsemat_numeric_t *din); int igraph_sparsemat_luresol(const igraph_sparsemat_symbolic_t *dis, const igraph_sparsemat_numeric_t *din, const igraph_vector_t *b, igraph_vector_t *res); int igraph_sparsemat_qrresol(const igraph_sparsemat_symbolic_t *dis, const igraph_sparsemat_numeric_t *din, const igraph_vector_t *b, igraph_vector_t *res); int igraph_sparsemat_symbqr(long int order, const igraph_sparsemat_t *A, igraph_sparsemat_symbolic_t *dis); int igraph_sparsemat_symblu(long int order, const igraph_sparsemat_t *A, igraph_sparsemat_symbolic_t *dis); void igraph_sparsemat_symbolic_destroy(igraph_sparsemat_symbolic_t *dis); void igraph_sparsemat_numeric_destroy(igraph_sparsemat_numeric_t *din); igraph_real_t igraph_sparsemat_max(igraph_sparsemat_t *A); igraph_real_t igraph_sparsemat_min(igraph_sparsemat_t *A); int igraph_sparsemat_minmax(igraph_sparsemat_t *A, igraph_real_t *min, igraph_real_t *max); long int igraph_sparsemat_count_nonzero(igraph_sparsemat_t *A); long int igraph_sparsemat_count_nonzerotol(igraph_sparsemat_t *A, igraph_real_t tol); int igraph_sparsemat_rowsums(const igraph_sparsemat_t *A, igraph_vector_t *res); int igraph_sparsemat_colsums(const igraph_sparsemat_t *A, igraph_vector_t *res); int igraph_sparsemat_rowmins(igraph_sparsemat_t *A, igraph_vector_t *res); int igraph_sparsemat_colmins(igraph_sparsemat_t *A, igraph_vector_t *res); int igraph_sparsemat_rowmaxs(igraph_sparsemat_t *A, igraph_vector_t *res); int igraph_sparsemat_colmaxs(igraph_sparsemat_t *A, igraph_vector_t *res); int igraph_sparsemat_which_min_rows(igraph_sparsemat_t *A, igraph_vector_t *res, igraph_vector_int_t *pos); int igraph_sparsemat_which_min_cols(igraph_sparsemat_t *A, igraph_vector_t *res, igraph_vector_int_t *pos); int igraph_sparsemat_scale(igraph_sparsemat_t *A, igraph_real_t by); int igraph_sparsemat_add_rows(igraph_sparsemat_t *A, long int n); int igraph_sparsemat_add_cols(igraph_sparsemat_t *A, long int n); int igraph_sparsemat_resize(igraph_sparsemat_t *A, long int nrow, long int ncol, int nzmax); int igraph_sparsemat_nonzero_storage(const igraph_sparsemat_t *A); int igraph_sparsemat_getelements(const igraph_sparsemat_t *A, igraph_vector_int_t *i, igraph_vector_int_t *j, igraph_vector_t *x); int igraph_sparsemat_getelements_sorted(const igraph_sparsemat_t *A, igraph_vector_int_t *i, igraph_vector_int_t *j, igraph_vector_t *x); int igraph_sparsemat_scale_rows(igraph_sparsemat_t *A, const igraph_vector_t *fact); int igraph_sparsemat_scale_cols(igraph_sparsemat_t *A, const igraph_vector_t *fact); int igraph_sparsemat_multiply_by_dense(const igraph_sparsemat_t *A, const igraph_matrix_t *B, igraph_matrix_t *res); int igraph_sparsemat_dense_multiply(const igraph_matrix_t *A, const igraph_sparsemat_t *B, igraph_matrix_t *res); int igraph_i_sparsemat_view(igraph_sparsemat_t *A, int nzmax, int m, int n, int *p, int *i, double *x, int nz); int igraph_sparsemat_sort(const igraph_sparsemat_t *A, igraph_sparsemat_t *sorted); int igraph_sparsemat_nzmax(const igraph_sparsemat_t *A); int igraph_sparsemat_neg(igraph_sparsemat_t *A); int igraph_sparsemat_iterator_init(igraph_sparsemat_iterator_t *it, igraph_sparsemat_t *sparsemat); int igraph_sparsemat_iterator_reset(igraph_sparsemat_iterator_t *it); igraph_bool_t igraph_sparsemat_iterator_end(const igraph_sparsemat_iterator_t *it); int igraph_sparsemat_iterator_row(const igraph_sparsemat_iterator_t *it); int igraph_sparsemat_iterator_col(const igraph_sparsemat_iterator_t *it); int igraph_sparsemat_iterator_idx(const igraph_sparsemat_iterator_t *it); igraph_real_t igraph_sparsemat_iterator_get(const igraph_sparsemat_iterator_t *it); int igraph_sparsemat_iterator_next(igraph_sparsemat_iterator_t *it); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_layout.h0000644000076500000240000002764313614300625025266 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_LAYOUT_H #define IGRAPH_LAYOUT_H #include "igraph_decls.h" #include "igraph_constants.h" #include "igraph_types.h" #include "igraph_vector.h" #include "igraph_vector_ptr.h" #include "igraph_matrix.h" #include "igraph_datatype.h" #include "igraph_arpack.h" #include "igraph_iterators.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* Layouts */ /* -------------------------------------------------- */ DECLDIR int igraph_layout_random(const igraph_t *graph, igraph_matrix_t *res); DECLDIR int igraph_layout_circle(const igraph_t *graph, igraph_matrix_t *res, igraph_vs_t order); DECLDIR int igraph_layout_star(const igraph_t *graph, igraph_matrix_t *res, igraph_integer_t center, const igraph_vector_t *order); DECLDIR int igraph_layout_grid(const igraph_t *graph, igraph_matrix_t *res, long int width); DECLDIR int igraph_layout_fruchterman_reingold(const igraph_t *graph, igraph_matrix_t *res, igraph_bool_t use_seed, igraph_integer_t niter, igraph_real_t start_temp, igraph_layout_grid_t grid, const igraph_vector_t *weight, const igraph_vector_t *minx, const igraph_vector_t *maxx, const igraph_vector_t *miny, const igraph_vector_t *maxy); DECLDIR int igraph_layout_kamada_kawai(const igraph_t *graph, igraph_matrix_t *res, igraph_bool_t use_seed, igraph_integer_t maxiter, igraph_real_t epsilon, igraph_real_t kkconst, const igraph_vector_t *weights, const igraph_vector_t *minx, const igraph_vector_t *maxx, const igraph_vector_t *miny, const igraph_vector_t *maxy); DECLDIR int igraph_layout_springs(const igraph_t *graph, igraph_matrix_t *res, igraph_real_t mass, igraph_real_t equil, igraph_real_t k, igraph_real_t repeqdis, igraph_real_t kfr, igraph_bool_t repulse); DECLDIR int igraph_layout_lgl(const igraph_t *graph, igraph_matrix_t *res, igraph_integer_t maxiter, igraph_real_t maxdelta, igraph_real_t area, igraph_real_t coolexp, igraph_real_t repulserad, igraph_real_t cellsize, igraph_integer_t root); DECLDIR int igraph_layout_reingold_tilford(const igraph_t *graph, igraph_matrix_t *res, igraph_neimode_t mode, const igraph_vector_t *roots, const igraph_vector_t *rootlevel); DECLDIR int igraph_layout_reingold_tilford_circular(const igraph_t *graph, igraph_matrix_t *res, igraph_neimode_t mode, const igraph_vector_t *roots, const igraph_vector_t *rootlevel); DECLDIR int igraph_layout_sugiyama(const igraph_t *graph, igraph_matrix_t *res, igraph_t *extd_graph, igraph_vector_t *extd_to_orig_eids, const igraph_vector_t* layers, igraph_real_t hgap, igraph_real_t vgap, long int maxiter, const igraph_vector_t *weights); DECLDIR int igraph_layout_random_3d(const igraph_t *graph, igraph_matrix_t *res); DECLDIR int igraph_layout_sphere(const igraph_t *graph, igraph_matrix_t *res); DECLDIR int igraph_layout_grid_3d(const igraph_t *graph, igraph_matrix_t *res, long int width, long int height); DECLDIR int igraph_layout_fruchterman_reingold_3d(const igraph_t *graph, igraph_matrix_t *res, igraph_bool_t use_seed, igraph_integer_t niter, igraph_real_t start_temp, const igraph_vector_t *weight, const igraph_vector_t *minx, const igraph_vector_t *maxx, const igraph_vector_t *miny, const igraph_vector_t *maxy, const igraph_vector_t *minz, const igraph_vector_t *maxz); DECLDIR int igraph_layout_kamada_kawai_3d(const igraph_t *graph, igraph_matrix_t *res, igraph_bool_t use_seed, igraph_integer_t maxiter, igraph_real_t epsilon, igraph_real_t kkconst, const igraph_vector_t *weights, const igraph_vector_t *minx, const igraph_vector_t *maxx, const igraph_vector_t *miny, const igraph_vector_t *maxy, const igraph_vector_t *minz, const igraph_vector_t *maxz); DECLDIR int igraph_layout_graphopt(const igraph_t *graph, igraph_matrix_t *res, igraph_integer_t niter, igraph_real_t node_charge, igraph_real_t node_mass, igraph_real_t spring_length, igraph_real_t spring_constant, igraph_real_t max_sa_movement, igraph_bool_t use_seed); DECLDIR int igraph_layout_mds(const igraph_t *graph, igraph_matrix_t *res, const igraph_matrix_t *dist, long int dim, igraph_arpack_options_t *options); DECLDIR int igraph_layout_bipartite(const igraph_t *graph, const igraph_vector_bool_t *types, igraph_matrix_t *res, igraph_real_t hgap, igraph_real_t vgap, long int maxiter); /** * \struct igraph_layout_drl_options_t * Parameters for the DrL layout generator * * \member edge_cut The edge cutting parameter. * Edge cutting is done in the late stages of the * algorithm in order to achieve less dense layouts. Edges are cut * if there is a lot of stress on them (a large value in the * objective function sum). The edge cutting parameter is a value * between 0 and 1 with 0 representing no edge cutting and 1 * representing maximal edge cutting. The default value is 32/40. * \member init_iterations Number of iterations, initial phase. * \member init_temperature Start temperature, initial phase. * \member init_attraction Attraction, initial phase. * \member init_damping_mult Damping factor, initial phase. * \member liquid_iterations Number of iterations in the liquid phase. * \member liquid_temperature Start temperature in the liquid phase. * \member liquid_attraction Attraction in the liquid phase. * \member liquid_damping_mult Multiplicatie damping factor, liquid phase. * \member expansion_iterations Number of iterations in the expansion phase. * \member expansion_temperature Start temperature in the expansion phase. * \member expansion_attraction Attraction, expansion phase. * \member expansion_damping_mult Damping factor, expansion phase. * \member cooldown_iterations Number of iterations in the cooldown phase. * \member cooldown_temperature Start temperature in the cooldown phase. * \member cooldown_attraction Attraction in the cooldown phase. * \member cooldown_damping_mult Damping fact int the cooldown phase. * \member crunch_iterations Number of iterations in the crunch phase. * \member crunch_temperature Start temperature in the crunch phase. * \member crunch_attraction Attraction in the crunch phase. * \member crunch_damping_mult Damping factor in the crunch phase. * \member simmer_iterations Number of iterations in the simmer phase. * \member simmer_temperature Start temperature in te simmer phase. * \member simmer_attraction Attraction in the simmer phase. * \member simmer_damping_mult Multiplicative damping factor in the simmer phase. */ typedef struct igraph_layout_drl_options_t { igraph_real_t edge_cut; igraph_integer_t init_iterations; igraph_real_t init_temperature; igraph_real_t init_attraction; igraph_real_t init_damping_mult; igraph_integer_t liquid_iterations; igraph_real_t liquid_temperature; igraph_real_t liquid_attraction; igraph_real_t liquid_damping_mult; igraph_integer_t expansion_iterations; igraph_real_t expansion_temperature; igraph_real_t expansion_attraction; igraph_real_t expansion_damping_mult; igraph_integer_t cooldown_iterations; igraph_real_t cooldown_temperature; igraph_real_t cooldown_attraction; igraph_real_t cooldown_damping_mult; igraph_integer_t crunch_iterations; igraph_real_t crunch_temperature; igraph_real_t crunch_attraction; igraph_real_t crunch_damping_mult; igraph_integer_t simmer_iterations; igraph_real_t simmer_temperature; igraph_real_t simmer_attraction; igraph_real_t simmer_damping_mult; } igraph_layout_drl_options_t; /** * \typedef igraph_layout_drl_default_t * Predefined parameter templates for the DrL layout generator * * These constants can be used to initialize a set of DrL parameters. * These can then be modified according to the user's needs. * \enumval IGRAPH_LAYOUT_DRL_DEFAULT The deafult parameters. * \enumval IGRAPH_LAYOUT_DRL_COARSEN Slightly modified parameters to * get a coarser layout. * \enumval IGRAPH_LAYOUT_DRL_COARSEST An even coarser layout. * \enumval IGRAPH_LAYOUT_DRL_REFINE Refine an already calculated layout. * \enumval IGRAPH_LAYOUT_DRL_FINAL Finalize an already refined layout. */ typedef enum { IGRAPH_LAYOUT_DRL_DEFAULT = 0, IGRAPH_LAYOUT_DRL_COARSEN, IGRAPH_LAYOUT_DRL_COARSEST, IGRAPH_LAYOUT_DRL_REFINE, IGRAPH_LAYOUT_DRL_FINAL } igraph_layout_drl_default_t; DECLDIR int igraph_layout_drl_options_init(igraph_layout_drl_options_t *options, igraph_layout_drl_default_t templ); DECLDIR int igraph_layout_drl(const igraph_t *graph, igraph_matrix_t *res, igraph_bool_t use_seed, igraph_layout_drl_options_t *options, const igraph_vector_t *weights, const igraph_vector_bool_t *fixed); DECLDIR int igraph_layout_drl_3d(const igraph_t *graph, igraph_matrix_t *res, igraph_bool_t use_seed, igraph_layout_drl_options_t *options, const igraph_vector_t *weights, const igraph_vector_bool_t *fixed); DECLDIR int igraph_layout_merge_dla(igraph_vector_ptr_t *graphs, igraph_vector_ptr_t *coords, igraph_matrix_t *res); DECLDIR int igraph_layout_gem(const igraph_t *graph, igraph_matrix_t *res, igraph_bool_t use_seed, igraph_integer_t maxiter, igraph_real_t temp_max, igraph_real_t temp_min, igraph_real_t temp_init); DECLDIR int igraph_layout_davidson_harel(const igraph_t *graph, igraph_matrix_t *res, igraph_bool_t use_seed, igraph_integer_t maxiter, igraph_integer_t fineiter, igraph_real_t cool_fact, igraph_real_t weight_node_dist, igraph_real_t weight_border, igraph_real_t weight_edge_lengths, igraph_real_t weight_edge_crossings, igraph_real_t weight_node_edge_dist); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_games.h0000644000076500000240000002622313614300625025036 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_GAMES_H #define IGRAPH_GAMES_H #include "igraph_decls.h" #include "igraph_constants.h" #include "igraph_types.h" #include "igraph_matrix.h" #include "igraph_vector.h" #include "igraph_datatype.h" #include "igraph_vector_ptr.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* Constructors, games (=stochastic) */ /* -------------------------------------------------- */ DECLDIR int igraph_barabasi_game(igraph_t *graph, igraph_integer_t n, igraph_real_t power, igraph_integer_t m, const igraph_vector_t *outseq, igraph_bool_t outpref, igraph_real_t A, igraph_bool_t directed, igraph_barabasi_algorithm_t algo, const igraph_t *start_from); DECLDIR int igraph_nonlinear_barabasi_game(igraph_t *graph, igraph_integer_t n, igraph_real_t power, igraph_integer_t m, const igraph_vector_t *outseq, igraph_bool_t outpref, igraph_real_t zeroappeal, igraph_bool_t directed); DECLDIR int igraph_erdos_renyi_game(igraph_t *graph, igraph_erdos_renyi_t type, igraph_integer_t n, igraph_real_t p, igraph_bool_t directed, igraph_bool_t loops); DECLDIR int igraph_erdos_renyi_game_gnp(igraph_t *graph, igraph_integer_t n, igraph_real_t p, igraph_bool_t directed, igraph_bool_t loops); DECLDIR int igraph_erdos_renyi_game_gnm(igraph_t *graph, igraph_integer_t n, igraph_real_t m, igraph_bool_t directed, igraph_bool_t loops); DECLDIR int igraph_degree_sequence_game(igraph_t *graph, const igraph_vector_t *out_deg, const igraph_vector_t *in_deg, igraph_degseq_t method); DECLDIR int igraph_growing_random_game(igraph_t *graph, igraph_integer_t n, igraph_integer_t m, igraph_bool_t directed, igraph_bool_t citation); DECLDIR int igraph_barabasi_aging_game(igraph_t *graph, igraph_integer_t nodes, igraph_integer_t m, const igraph_vector_t *outseq, igraph_bool_t outpref, igraph_real_t pa_exp, igraph_real_t aging_exp, igraph_integer_t aging_bin, igraph_real_t zero_deg_appeal, igraph_real_t zero_age_appeal, igraph_real_t deg_coef, igraph_real_t age_coef, igraph_bool_t directed); DECLDIR int igraph_recent_degree_game(igraph_t *graph, igraph_integer_t n, igraph_real_t power, igraph_integer_t window, igraph_integer_t m, const igraph_vector_t *outseq, igraph_bool_t outpref, igraph_real_t zero_appeal, igraph_bool_t directed); DECLDIR int igraph_recent_degree_aging_game(igraph_t *graph, igraph_integer_t nodes, igraph_integer_t m, const igraph_vector_t *outseq, igraph_bool_t outpref, igraph_real_t pa_exp, igraph_real_t aging_exp, igraph_integer_t aging_bin, igraph_integer_t window, igraph_real_t zero_appeal, igraph_bool_t directed); DECLDIR int igraph_callaway_traits_game (igraph_t *graph, igraph_integer_t nodes, igraph_integer_t types, igraph_integer_t edges_per_step, igraph_vector_t *type_dist, igraph_matrix_t *pref_matrix, igraph_bool_t directed); DECLDIR int igraph_establishment_game(igraph_t *graph, igraph_integer_t nodes, igraph_integer_t types, igraph_integer_t k, igraph_vector_t *type_dist, igraph_matrix_t *pref_matrix, igraph_bool_t directed); DECLDIR int igraph_grg_game(igraph_t *graph, igraph_integer_t nodes, igraph_real_t radius, igraph_bool_t torus, igraph_vector_t *x, igraph_vector_t *y); DECLDIR int igraph_preference_game(igraph_t *graph, igraph_integer_t nodes, igraph_integer_t types, const igraph_vector_t *type_dist, igraph_bool_t fixed_sizes, const igraph_matrix_t *pref_matrix, igraph_vector_t *node_type_vec, igraph_bool_t directed, igraph_bool_t loops); DECLDIR int igraph_asymmetric_preference_game(igraph_t *graph, igraph_integer_t nodes, igraph_integer_t types, igraph_matrix_t *type_dist_matrix, igraph_matrix_t *pref_matrix, igraph_vector_t *node_type_in_vec, igraph_vector_t *node_type_out_vec, igraph_bool_t loops); DECLDIR int igraph_rewire_edges(igraph_t *graph, igraph_real_t prob, igraph_bool_t loops, igraph_bool_t multiple); DECLDIR int igraph_rewire_directed_edges(igraph_t *graph, igraph_real_t prob, igraph_bool_t loops, igraph_neimode_t mode); DECLDIR int igraph_watts_strogatz_game(igraph_t *graph, igraph_integer_t dim, igraph_integer_t size, igraph_integer_t nei, igraph_real_t p, igraph_bool_t loops, igraph_bool_t multiple); DECLDIR int igraph_lastcit_game(igraph_t *graph, igraph_integer_t nodes, igraph_integer_t edges_per_node, igraph_integer_t agebins, const igraph_vector_t *preference, igraph_bool_t directed); DECLDIR int igraph_cited_type_game(igraph_t *graph, igraph_integer_t nodes, const igraph_vector_t *types, const igraph_vector_t *pref, igraph_integer_t edges_per_step, igraph_bool_t directed); DECLDIR int igraph_citing_cited_type_game(igraph_t *graph, igraph_integer_t nodes, const igraph_vector_t *types, const igraph_matrix_t *pref, igraph_integer_t edges_per_step, igraph_bool_t directed); DECLDIR int igraph_forest_fire_game(igraph_t *graph, igraph_integer_t nodes, igraph_real_t fw_prob, igraph_real_t bw_factor, igraph_integer_t ambs, igraph_bool_t directed); DECLDIR int igraph_simple_interconnected_islands_game( igraph_t *graph, igraph_integer_t islands_n, igraph_integer_t islands_size, igraph_real_t islands_pin, igraph_integer_t n_inter); DECLDIR int igraph_static_fitness_game(igraph_t *graph, igraph_integer_t no_of_edges, igraph_vector_t* fitness_out, igraph_vector_t* fitness_in, igraph_bool_t loops, igraph_bool_t multiple); DECLDIR int igraph_static_power_law_game(igraph_t *graph, igraph_integer_t no_of_nodes, igraph_integer_t no_of_edges, igraph_real_t exponent_out, igraph_real_t exponent_in, igraph_bool_t loops, igraph_bool_t multiple, igraph_bool_t finite_size_correction); DECLDIR int igraph_k_regular_game(igraph_t *graph, igraph_integer_t no_of_nodes, igraph_integer_t k, igraph_bool_t directed, igraph_bool_t multiple); DECLDIR int igraph_sbm_game(igraph_t *graph, igraph_integer_t n, const igraph_matrix_t *pref_matrix, const igraph_vector_int_t *block_sizes, igraph_bool_t directed, igraph_bool_t loops); DECLDIR int igraph_hsbm_game(igraph_t *graph, igraph_integer_t n, igraph_integer_t m, const igraph_vector_t *rho, const igraph_matrix_t *C, igraph_real_t p); DECLDIR int igraph_hsbm_list_game(igraph_t *graph, igraph_integer_t n, const igraph_vector_int_t *mlist, const igraph_vector_ptr_t *rholist, const igraph_vector_ptr_t *Clist, igraph_real_t p); DECLDIR int igraph_correlated_game(const igraph_t *old_graph, igraph_t *new_graph, igraph_real_t corr, igraph_real_t p, const igraph_vector_t *permutation); DECLDIR int igraph_correlated_pair_game(igraph_t *graph1, igraph_t *graph2, int n, igraph_real_t corr, igraph_real_t p, igraph_bool_t directed, const igraph_vector_t *permutation); DECLDIR int igraph_tree_game(igraph_t *graph, igraph_integer_t n, igraph_bool_t directed, igraph_random_tree_t method); DECLDIR int igraph_dot_product_game(igraph_t *graph, const igraph_matrix_t *vecs, igraph_bool_t directed); DECLDIR int igraph_sample_sphere_surface(igraph_integer_t dim, igraph_integer_t n, igraph_real_t radius, igraph_bool_t positive, igraph_matrix_t *res); DECLDIR int igraph_sample_sphere_volume(igraph_integer_t dim, igraph_integer_t n, igraph_real_t radius, igraph_bool_t positive, igraph_matrix_t *res); DECLDIR int igraph_sample_dirichlet(igraph_integer_t n, const igraph_vector_t *alpha, igraph_matrix_t *res); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_pmt_off.h0000644000076500000240000000436013614300625025372 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifdef ATOMIC #undef ATOMIC #endif #ifdef ATOMIC_IO #undef ATOMIC_IO #endif #ifdef BASE #undef BASE #endif #ifdef BASE_EPSILON #undef BASE_EPSILON #endif #ifdef CONCAT2 #undef CONCAT2 #endif #ifdef CONCAT2x #undef CONCAT2x #endif #ifdef CONCAT3 #undef CONCAT3 #endif #ifdef CONCAT3x #undef CONCAT3x #endif #ifdef CONCAT4 #undef CONCAT4 #endif #ifdef CONCAT4x #undef CONCAT4x #endif #ifdef FP #undef FP #endif #ifdef FUNCTION #undef FUNCTION #endif #ifdef IN_FORMAT #undef IN_FORMAT #endif #ifdef MULTIPLICITY #undef MULTIPLICITY #endif #ifdef ONE #undef ONE #endif #ifdef OUT_FORMAT #undef OUT_FORMAT #endif #ifdef SHORT #undef SHORT #endif #ifdef TYPE #undef TYPE #endif #ifdef ZERO #undef ZERO #endif #ifdef HEAPMORE #undef HEAPMORE #endif #ifdef HEAPLESS #undef HEAPLESS #endif #ifdef HEAPMOREEQ #undef HEAPMOREEQ #endif #ifdef HEAPLESSEQ #undef HEAPLESSEQ #endif #ifdef SUM #undef SUM #endif #ifdef SQ #undef SQ #endif #ifdef PROD #undef PROD #endif #ifdef NOTORDERED #undef NOTORDERED #endif #ifdef EQ #undef EQ #endif #ifdef DIFF #undef DIFF #endif #ifdef DIV #undef DIV #endif #ifdef NOABS #undef NOABS #endif #ifdef PRINTFUNC #undef PRINTFUNC #endif #ifdef FPRINTFUNC #undef PRINTFUNC #endif #ifdef UNSIGNED #undef UNSIGNED #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_vector_pmt.h0000644000076500000240000002652613614300625026132 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ /*--------------------*/ /* Allocation */ /*--------------------*/ DECLDIR int FUNCTION(igraph_vector, init)(TYPE(igraph_vector)* v, long int size); DECLDIR int FUNCTION(igraph_vector, init_copy)(TYPE(igraph_vector)* v, const BASE* data, long int length); DECLDIR int FUNCTION(igraph_vector, init_seq)(TYPE(igraph_vector)*v, BASE from, BASE to); DECLDIR int FUNCTION(igraph_vector, copy)(TYPE(igraph_vector) *to, const TYPE(igraph_vector) *from); DECLDIR void FUNCTION(igraph_vector, destroy)(TYPE(igraph_vector)* v); DECLDIR long int FUNCTION(igraph_vector, capacity)(const TYPE(igraph_vector)*v); /*--------------------*/ /* Accessing elements */ /*--------------------*/ #ifndef VECTOR /** * \ingroup vector * \define VECTOR * \brief Accessing an element of a vector. * * Usage: * \verbatim VECTOR(v)[0] \endverbatim * to access the first element of the vector, you can also use this in * assignments, like: * \verbatim VECTOR(v)[10]=5; \endverbatim * * Note that there are no range checks right now. * This functionality might be redefined later as a real function * instead of a #define. * \param v The vector object. * * Time complexity: O(1). */ #define VECTOR(v) ((v).stor_begin) #endif DECLDIR BASE FUNCTION(igraph_vector, e)(const TYPE(igraph_vector)* v, long int pos); BASE* FUNCTION(igraph_vector, e_ptr)(const TYPE(igraph_vector)* v, long int pos); DECLDIR void FUNCTION(igraph_vector, set)(TYPE(igraph_vector)* v, long int pos, BASE value); DECLDIR BASE FUNCTION(igraph_vector, tail)(const TYPE(igraph_vector) *v); /*-----------------------*/ /* Initializing elements */ /*-----------------------*/ DECLDIR void FUNCTION(igraph_vector, null)(TYPE(igraph_vector)* v); DECLDIR void FUNCTION(igraph_vector, fill)(TYPE(igraph_vector)* v, BASE e); /*-----------------------*/ /* Vector views */ /*-----------------------*/ DECLDIR const TYPE(igraph_vector) *FUNCTION(igraph_vector, view)(const TYPE(igraph_vector) *v, const BASE *data, long int length); /*-----------------------*/ /* Copying vectors */ /*-----------------------*/ DECLDIR void FUNCTION(igraph_vector, copy_to)(const TYPE(igraph_vector) *v, BASE* to); DECLDIR int FUNCTION(igraph_vector, update)(TYPE(igraph_vector) *to, const TYPE(igraph_vector) *from); DECLDIR int FUNCTION(igraph_vector, append)(TYPE(igraph_vector) *to, const TYPE(igraph_vector) *from); DECLDIR int FUNCTION(igraph_vector, swap)(TYPE(igraph_vector) *v1, TYPE(igraph_vector) *v2); /*-----------------------*/ /* Exchanging elements */ /*-----------------------*/ DECLDIR int FUNCTION(igraph_vector, swap_elements)(TYPE(igraph_vector) *v, long int i, long int j); DECLDIR int FUNCTION(igraph_vector, reverse)(TYPE(igraph_vector) *v); DECLDIR int FUNCTION(igraph_vector, shuffle)(TYPE(igraph_vector) *v); /*-----------------------*/ /* Vector operations */ /*-----------------------*/ DECLDIR void FUNCTION(igraph_vector, add_constant)(TYPE(igraph_vector) *v, BASE plus); DECLDIR void FUNCTION(igraph_vector, scale)(TYPE(igraph_vector) *v, BASE by); DECLDIR int FUNCTION(igraph_vector, add)(TYPE(igraph_vector) *v1, const TYPE(igraph_vector) *v2); DECLDIR int FUNCTION(igraph_vector, sub)(TYPE(igraph_vector) *v1, const TYPE(igraph_vector) *v2); DECLDIR int FUNCTION(igraph_vector, mul)(TYPE(igraph_vector) *v1, const TYPE(igraph_vector) *v2); DECLDIR int FUNCTION(igraph_vector, div)(TYPE(igraph_vector) *v1, const TYPE(igraph_vector) *v2); DECLDIR int FUNCTION(igraph_vector, cumsum)(TYPE(igraph_vector) *to, const TYPE(igraph_vector) *from); #ifndef NOABS DECLDIR int FUNCTION(igraph_vector, abs)(TYPE(igraph_vector) *v); #endif /*------------------------------*/ /* Comparison */ /*------------------------------*/ DECLDIR igraph_bool_t FUNCTION(igraph_vector, all_e)(const TYPE(igraph_vector) *lhs, const TYPE(igraph_vector) *rhs); DECLDIR igraph_bool_t FUNCTION(igraph_vector, all_l)(const TYPE(igraph_vector) *lhs, const TYPE(igraph_vector) *rhs); DECLDIR igraph_bool_t FUNCTION(igraph_vector, all_g)(const TYPE(igraph_vector) *lhs, const TYPE(igraph_vector) *rhs); DECLDIR igraph_bool_t FUNCTION(igraph_vector, all_le)(const TYPE(igraph_vector) *lhs, const TYPE(igraph_vector) *rhs); DECLDIR igraph_bool_t FUNCTION(igraph_vector, all_ge)(const TYPE(igraph_vector) *lhs, const TYPE(igraph_vector) *rhs); /*------------------------------*/ /* Finding minimum and maximum */ /*------------------------------*/ DECLDIR BASE FUNCTION(igraph_vector, min)(const TYPE(igraph_vector)* v); DECLDIR BASE FUNCTION(igraph_vector, max)(const TYPE(igraph_vector)* v); DECLDIR long int FUNCTION(igraph_vector, which_min)(const TYPE(igraph_vector)* v); DECLDIR long int FUNCTION(igraph_vector, which_max)(const TYPE(igraph_vector)* v); DECLDIR int FUNCTION(igraph_vector, minmax)(const TYPE(igraph_vector) *v, BASE *min, BASE *max); DECLDIR int FUNCTION(igraph_vector, which_minmax)(const TYPE(igraph_vector) *v, long int *which_min, long int *which_max); /*-------------------*/ /* Vector properties */ /*-------------------*/ DECLDIR igraph_bool_t FUNCTION(igraph_vector, empty) (const TYPE(igraph_vector)* v); DECLDIR long int FUNCTION(igraph_vector, size) (const TYPE(igraph_vector)* v); DECLDIR igraph_bool_t FUNCTION(igraph_vector, isnull)(const TYPE(igraph_vector) *v); DECLDIR BASE FUNCTION(igraph_vector, sum)(const TYPE(igraph_vector) *v); DECLDIR igraph_real_t FUNCTION(igraph_vector, sumsq)(const TYPE(igraph_vector) *v); DECLDIR BASE FUNCTION(igraph_vector, prod)(const TYPE(igraph_vector) *v); DECLDIR igraph_bool_t FUNCTION(igraph_vector, isininterval)(const TYPE(igraph_vector) *v, BASE low, BASE high); DECLDIR igraph_bool_t FUNCTION(igraph_vector, any_smaller)(const TYPE(igraph_vector) *v, BASE limit); DECLDIR igraph_bool_t FUNCTION(igraph_vector, is_equal)(const TYPE(igraph_vector) *lhs, const TYPE(igraph_vector) *rhs); DECLDIR igraph_real_t FUNCTION(igraph_vector, maxdifference)(const TYPE(igraph_vector) *m1, const TYPE(igraph_vector) *m2); /*------------------------*/ /* Searching for elements */ /*------------------------*/ DECLDIR igraph_bool_t FUNCTION(igraph_vector, contains)(const TYPE(igraph_vector) *v, BASE e); DECLDIR igraph_bool_t FUNCTION(igraph_vector, search)(const TYPE(igraph_vector) *v, long int from, BASE what, long int *pos); DECLDIR igraph_bool_t FUNCTION(igraph_vector, binsearch)(const TYPE(igraph_vector) *v, BASE what, long int *pos); DECLDIR igraph_bool_t FUNCTION(igraph_vector, binsearch2)(const TYPE(igraph_vector) *v, BASE what); /*------------------------*/ /* Resizing operations */ /*------------------------*/ DECLDIR void FUNCTION(igraph_vector, clear)(TYPE(igraph_vector)* v); DECLDIR int FUNCTION(igraph_vector, resize)(TYPE(igraph_vector)* v, long int newsize); DECLDIR int FUNCTION(igraph_vector, resize_min)(TYPE(igraph_vector)*v); DECLDIR int FUNCTION(igraph_vector, reserve)(TYPE(igraph_vector)* v, long int size); DECLDIR int FUNCTION(igraph_vector, push_back)(TYPE(igraph_vector)* v, BASE e); DECLDIR BASE FUNCTION(igraph_vector, pop_back)(TYPE(igraph_vector)* v); DECLDIR int FUNCTION(igraph_vector, insert)(TYPE(igraph_vector) *v, long int pos, BASE value); DECLDIR void FUNCTION(igraph_vector, remove)(TYPE(igraph_vector) *v, long int elem); DECLDIR void FUNCTION(igraph_vector, remove_section)(TYPE(igraph_vector) *v, long int from, long int to); /*-----------*/ /* Sorting */ /*-----------*/ DECLDIR void FUNCTION(igraph_vector, sort)(TYPE(igraph_vector) *v); DECLDIR long int FUNCTION(igraph_vector, qsort_ind)(TYPE(igraph_vector) *v, igraph_vector_t *inds, igraph_bool_t descending); /*-----------*/ /* Printing */ /*-----------*/ int FUNCTION(igraph_vector, print)(const TYPE(igraph_vector) *v); int FUNCTION(igraph_vector, printf)(const TYPE(igraph_vector) *v, const char *format); int FUNCTION(igraph_vector, fprint)(const TYPE(igraph_vector) *v, FILE *file); #ifdef BASE_COMPLEX DECLDIR int igraph_vector_complex_real(const igraph_vector_complex_t *v, igraph_vector_t *real); DECLDIR int igraph_vector_complex_imag(const igraph_vector_complex_t *v, igraph_vector_t *imag); DECLDIR int igraph_vector_complex_realimag(const igraph_vector_complex_t *v, igraph_vector_t *real, igraph_vector_t *imag); DECLDIR int igraph_vector_complex_create(igraph_vector_complex_t *v, const igraph_vector_t *real, const igraph_vector_t *imag); DECLDIR int igraph_vector_complex_create_polar(igraph_vector_complex_t *v, const igraph_vector_t *r, const igraph_vector_t *theta); #endif /* ----------------------------------------------------------------------------*/ /* For internal use only, may be removed, rewritten ... */ /* ----------------------------------------------------------------------------*/ int FUNCTION(igraph_vector, init_real)(TYPE(igraph_vector)*v, int no, ...); int FUNCTION(igraph_vector, init_int)(TYPE(igraph_vector)*v, int no, ...); int FUNCTION(igraph_vector, init_real_end)(TYPE(igraph_vector)*v, BASE endmark, ...); int FUNCTION(igraph_vector, init_int_end)(TYPE(igraph_vector)*v, int endmark, ...); int FUNCTION(igraph_vector, move_interval)(TYPE(igraph_vector) *v, long int begin, long int end, long int to); int FUNCTION(igraph_vector, move_interval2)(TYPE(igraph_vector) *v, long int begin, long int end, long int to); void FUNCTION(igraph_vector, permdelete)(TYPE(igraph_vector) *v, const igraph_vector_t *index, long int nremove); int FUNCTION(igraph_vector, filter_smaller)(TYPE(igraph_vector) *v, BASE elem); int FUNCTION(igraph_vector, get_interval)(const TYPE(igraph_vector) *v, TYPE(igraph_vector) *res, long int from, long int to); int FUNCTION(igraph_vector, difference_sorted)(const TYPE(igraph_vector) *v1, const TYPE(igraph_vector) *v2, TYPE(igraph_vector) *result); int FUNCTION(igraph_vector, intersect_sorted)(const TYPE(igraph_vector) *v1, const TYPE(igraph_vector) *v2, TYPE(igraph_vector) *result); int FUNCTION(igraph_vector, index)(const TYPE(igraph_vector) *v, TYPE(igraph_vector) *newv, const igraph_vector_t *idx); int FUNCTION(igraph_vector, index_int)(TYPE(igraph_vector) *v, const igraph_vector_int_t *idx); python-igraph-0.8.0/vendor/source/igraph/include/igraph_constructors.h0000644000076500000240000000751613614300625026516 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_CONSTRUCTORS_H #define IGRAPH_CONSTRUCTORS_H #include "igraph_decls.h" #include "igraph_constants.h" #include "igraph_types.h" #include "igraph_matrix.h" #include "igraph_datatype.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* Constructors, deterministic */ /* -------------------------------------------------- */ DECLDIR int igraph_create(igraph_t *graph, const igraph_vector_t *edges, igraph_integer_t n, igraph_bool_t directed); DECLDIR int igraph_small(igraph_t *graph, igraph_integer_t n, igraph_bool_t directed, ...); DECLDIR int igraph_adjacency(igraph_t *graph, igraph_matrix_t *adjmatrix, igraph_adjacency_t mode); DECLDIR int igraph_weighted_adjacency(igraph_t *graph, igraph_matrix_t *adjmatrix, igraph_adjacency_t mode, const char* attr, igraph_bool_t loops); DECLDIR int igraph_star(igraph_t *graph, igraph_integer_t n, igraph_star_mode_t mode, igraph_integer_t center); DECLDIR int igraph_lattice(igraph_t *graph, const igraph_vector_t *dimvector, igraph_integer_t nei, igraph_bool_t directed, igraph_bool_t mutual, igraph_bool_t circular); DECLDIR int igraph_ring(igraph_t *graph, igraph_integer_t n, igraph_bool_t directed, igraph_bool_t mutual, igraph_bool_t circular); DECLDIR int igraph_tree(igraph_t *graph, igraph_integer_t n, igraph_integer_t children, igraph_tree_mode_t type); DECLDIR int igraph_from_prufer(igraph_t *graph, const igraph_vector_int_t *prufer); DECLDIR int igraph_full(igraph_t *graph, igraph_integer_t n, igraph_bool_t directed, igraph_bool_t loops); DECLDIR int igraph_full_citation(igraph_t *graph, igraph_integer_t n, igraph_bool_t directed); DECLDIR int igraph_atlas(igraph_t *graph, int number); DECLDIR int igraph_extended_chordal_ring(igraph_t *graph, igraph_integer_t nodes, const igraph_matrix_t *W, igraph_bool_t directed); DECLDIR int igraph_connect_neighborhood(igraph_t *graph, igraph_integer_t order, igraph_neimode_t mode); DECLDIR int igraph_linegraph(const igraph_t *graph, igraph_t *linegraph); DECLDIR int igraph_de_bruijn(igraph_t *graph, igraph_integer_t m, igraph_integer_t n); DECLDIR int igraph_kautz(igraph_t *graph, igraph_integer_t m, igraph_integer_t n); DECLDIR int igraph_famous(igraph_t *graph, const char *name); DECLDIR int igraph_lcf_vector(igraph_t *graph, igraph_integer_t n, const igraph_vector_t *shifts, igraph_integer_t repeats); DECLDIR int igraph_lcf(igraph_t *graph, igraph_integer_t n, ...); DECLDIR int igraph_realize_degree_sequence(igraph_t *graph, const igraph_vector_t *outdeg, const igraph_vector_t *indeg, igraph_realize_degseq_t method); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_statusbar.h0000644000076500000240000001023113614300625025742 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_STATUSBAR #define IGRAPH_STATUSBAR #include "igraph_decls.h" __BEGIN_DECLS /** * \section about_status_handlers Status reporting * * * In addition to the possibility of reporting the progress of an * igraph computation via \ref igraph_progress(), it is also possible * to report simple status messages from within igraph functions, * without having to judge how much of the computation was performed * already. For this one needs to install a status handler function. * * * * Status handler functions must be of type \ref igraph_status_handler_t * and they can be install by a call to \ref igraph_set_status_handler(). * Currently there is a simple predefined status handler function, * called \ref igraph_status_handler_stderr(), but the user can define * new ones. * * * * Igraph functions report their status via a call to the * \ref IGRAPH_STATUS() or the \ref IGRAPH_STATUSF() macro. * */ /** * \typedef igraph_status_handler_t * * The type of the igraph status handler functions * \param message The status message. * \param data Additional context, with user-defined semantics. * Existing igraph functions pass a null pointer here. */ typedef int igraph_status_handler_t(const char *message, void *data); extern igraph_status_handler_t igraph_status_handler_stderr; DECLDIR igraph_status_handler_t * igraph_set_status_handler(igraph_status_handler_t new_handler); DECLDIR int igraph_status(const char *message, void *data); /** * \define IGRAPH_STATUS * Report the status of an igraph function. * * Typically this function is called only a handful of times from * an igraph function. E.g. if an algorithm has three major * steps, then it is logical to call it three times, to * signal the three major steps. * \param message The status message. * \param data Additional context, with user-defined semantics. * Existing igraph functions pass a null pointer here. * \return If the status handler returns with a value other than * \c IGRAPH_SUCCESS, then the function that called this * macro returns as well, with error code * \c IGRAPH_INTERRUPTED. */ #define IGRAPH_STATUS(message, data) \ do { \ if (igraph_status((message), (data)) != IGRAPH_SUCCESS) { \ IGRAPH_FINALLY_FREE(); \ return IGRAPH_INTERRUPTED; \ } \ } while (0) DECLDIR int igraph_statusf(const char *message, void *data, ...); /** * \define IGRAPH_STATUSF * Report the status from an igraph function * * This is the more flexible version of \ref IGRAPH_STATUS(), * having a printf-like syntax. As this macro takes variable * number of arguments, they must be all supplied as a single * argument, enclosed in parentheses. Then \ref igraph_statusf() * is called with the given arguments. * \param args The arguments to pass to \ref igraph_statusf(). * \return If the status handler returns with a value other than * \c IGRAPH_SUCCESS, then the function that called this * macro returns as well, with error code * \c IGRAPH_INTERRUPTED. */ #define IGRAPH_STATUSF(args) \ do { \ if (igraph_statusf args != IGRAPH_SUCCESS) { \ IGRAPH_FINALLY_FREE(); \ return IGRAPH_INTERRUPTED; \ } \ } while (0) __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_cohesive_blocks.h0000644000076500000240000000247413614300625027106 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_COHESIVE_BLOCKS_H #define IGRAPH_COHESIVE_BLOCKS_H #include "igraph_datatype.h" #include "igraph_vector.h" #include "igraph_vector_ptr.h" __BEGIN_DECLS DECLDIR int igraph_cohesive_blocks(const igraph_t *graph, igraph_vector_ptr_t *blocks, igraph_vector_t *cohesion, igraph_vector_t *parent, igraph_t *block_tree); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_blas.h0000644000076500000240000000477513614300625024673 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef BLAS_H #define BLAS_H #include "igraph_types.h" #include "igraph_vector.h" #include "igraph_matrix.h" #include "igraph_decls.h" __BEGIN_DECLS /** * \section about_blas BLAS interface in igraph * * * BLAS is a highly optimized library for basic linear algebra operations * such as vector-vector, matrix-vector and matrix-matrix product. * Please see http://www.netlib.org/blas/ for details and a reference * implementation in Fortran. igraph contains some wrapper functions * that can be used to call BLAS routines in a somewhat more * user-friendly way. Not all BLAS routines are included in igraph, * and even those which are included might not have wrappers; * the extension of the set of wrapped functions will probably be driven * by igraph's internal requirements. The wrapper functions usually * substitute double-precision floating point arrays used by BLAS with * \type igraph_vector_t and \type igraph_matrix_t instances and also * remove those parameters (such as the number of rows/columns) that * can be inferred from the passed arguments directly. * */ DECLDIR void igraph_blas_dgemv(igraph_bool_t transpose, igraph_real_t alpha, const igraph_matrix_t* a, const igraph_vector_t* x, igraph_real_t beta, igraph_vector_t* y); DECLDIR void igraph_blas_dgemv_array(igraph_bool_t transpose, igraph_real_t alpha, const igraph_matrix_t* a, const igraph_real_t* x, igraph_real_t beta, igraph_real_t* y); DECLDIR igraph_real_t igraph_blas_dnrm2(const igraph_vector_t *v); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_arpack.h0000644000076500000240000003354113614300625025204 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_types.h" #include "igraph_vector.h" #include "igraph_matrix.h" #ifndef ARPACK_H #define ARPACK_H #include "igraph_decls.h" __BEGIN_DECLS /** * \section about_arpack ARPACK interface in igraph * * * ARPACK is a library for solving large scale eigenvalue problems. * The package is designed to compute a few eigenvalues and corresponding * eigenvectors of a general \c n by \c n matrix \c A. It is * most appropriate for large sparse or structured matrices \c A where * structured means that a matrix-vector product w <- Av requires * order \c n rather than the usual order n^2 floating point * operations. Please see * http://www.caam.rice.edu/software/ARPACK/ for details. * * * * The eigenvalue calculation in ARPACK (in the simplest * case) involves the calculation of the \c Av product where \c A * is the matrix we work with and \c v is an arbitrary vector. A * user-defined function of type \ref igraph_arpack_function_t * is expected to perform this product. If the product can be done * efficiently, e.g. if the matrix is sparse, then ARPACK is usually * able to calculate the eigenvalues very quickly. * * * In igraph, eigenvalue/eigenvector calculations usually * involve the following steps: * \olist * \oli Initialization of an \ref igraph_arpack_options_t data * structure using \ref igraph_arpack_options_init. * \oli Setting some options in the initialized \ref * igraph_arpack_options_t object. * \oli Defining a function of type \ref igraph_arpack_function_t. * The input of this function is a vector, and the output * should be the output matrix multiplied by the input vector. * \oli Calling \ref igraph_arpack_rssolve() (is the matrix is * symmetric), or \ref igraph_arpack_rnsolve(). * \endolist * The \ref igraph_arpack_options_t object can be used multiple * times. * * * * If we have many eigenvalue problems to solve, then it might worth * to create an \ref igraph_arpack_storage_t object, and initialize it * via \ref igraph_arpack_storage_init(). This structure contains all * memory needed for ARPACK (with the given upper limit regerding to * the size of the eigenvalue problem). Then many problems can be * solved using the same \ref igraph_arpack_storage_t object, without * always reallocating the required memory. * The \ref igraph_arpack_storage_t object needs to be destroyed by * calling \ref igraph_arpack_storage_destroy() on it, when it is not * needed any more. * * * * igraph does not contain all * ARPACK routines, only the ones dealing with symmetric and * non-symmetric eigenvalue problems using double precision real * numbers. * * */ /** * \struct igraph_arpack_options_t * \brief Options for ARPACK * * This data structure contains the options of thee ARPACK eigenvalue * solver routines. It must be initialized by calling \ref * igraph_arpack_options_init() on it. Then it can be used for * multiple ARPACK calls, as the ARPACK solvers do not modify it. * * Input options: * \member bmat Character. Whether to solve a standard ('I') ot a * generalized problem ('B'). * \member n Dimension of the eigenproblem. * \member which Specifies which eigenvalues/vectors to * compute. Possible values for symmetric matrices: * \clist \cli LA * Compute \c nev largest (algebraic) eigenvalues. * \cli SA * Compute \c nev smallest (algebraic) eigenvalues. * \cli LM * Compute \c nev largest (in magnitude) eigenvalues. * \cli SM * Compute \c nev smallest (in magnitude) eigenvalues. * \cli BE * Compute \c nev eigenvalues, half from each end of * the spectrum. When \c nev is odd, compute one * more from the high en than from the low * end. \endclist * Possible values for non-symmetric matrices: * \clist \cli LM * Compute \c nev largest (in magnitude) eigenvalues. * \cli SM * Compute \c nev smallest (in magnitude) eigenvalues. * \cli LR * Compute \c nev eigenvalues of largest real part. * \cli SR * Compute \c nev eigenvalues of smallest real part. * \cli LI * Compute \c nev eigenvalues of largest imaginary part. * \cli SI * Compute \c nev eigenvalues of smallest imaginary * part. \endclist * \member nev The number of eigenvalues to be computed. * \member tol Stopping criterion: the relative accuracy * of the Ritz value is considered acceptable if its error is less * than \c tol times its estimated value. If this is set to zero * then machine precision is used. * \member ncv Number of Lanczos vectors to be generated. Setting this * to zero means that \ref igraph_arpack_rssolve and \ref igraph_arpack_rnsolve * will determine a suitable value for \c ncv automatically. * \member ldv Numberic scalar. It should be set to * zero in the current igraph implementation. * \member ishift Either zero or one. If zero then the shifts are * provided by the user via reverse communication. If one then exact * shifts with respect to the reduced tridiagonal matrix \c T. * Please always set this to one. * \member mxiter Maximum number of Arnoldi update iterations allowed. * \member nb Blocksize to be used in the recurrence. Please always * leave this on the default value, one. * \member mode The type of the eigenproblem to be solved. * Possible values if the input matrix is symmetric: * \olist * \oli A*x=lambda*x, A is symmetric. * \oli A*x=lambda*M*x, A is * symmetric, M is symmetric positive definite. * \oli K*x=lambda*M*x, K is * symmetric, M is symmetric positive semi-definite. * \oli K*x=lambda*KG*x, K is * symmetric positive semi-definite, KG is symmetric * indefinite. * \oli A*x=lambda*M*x, A is * symmetric, M is symmetric positive * semi-definite. (Cayley transformed mode.) \endolist * Please note that only \c mode ==1 was tested and other values * might not work properly. * Possible values if the input matrix is not symmetric: * \olist * \oli A*x=lambda*x. * \oli A*x=lambda*M*x, M is * symmetric positive definite. * \oli A*x=lambda*M*x, M is * symmetric semi-definite. * \oli A*x=lambda*M*x, M is * symmetric semi-definite. \endolist * Please note that only \c mode == 1 was tested and other values * might not work properly. * \member start Whether to use the supplied starting vector (1), or * use a random starting vector (0). The starting vector must be * supplied in the first column of the \c vectors argument of the * \ref igraph_arpack_rssolve() of \ref igraph_arpack_rnsolve() call. * * Output options: * \member info Error flag of ARPACK. Possible values: * \clist \cli 0 * Normal exit. * \cli 1 * Maximum number of iterations taken. * \cli 3 * No shifts could be applied during a cycle of the * Implicitly restarted Arnoldi iteration. One possibility * is to increase the size of \c ncv relative to \c * nev. \endclist * ARPACK can return other error flags as well, but these are * converted to igraph errors, see \ref igraph_error_type_t. * \member ierr Error flag of the second ARPACK call (one eigenvalue * computation usually involves two calls to ARPACK). This is * always zero, as other error codes are converted to igraph errors. * \member noiter Number of Arnoldi iterations taken. * \member nconv Number of converged Ritz values. This * represents the number of Ritz values that satisfy the * convergence critetion. * \member numop Total number of matrix-vector multiplications. * \member numopb Not used currently. * \member numreo Total number of steps of re-orthogonalization. * * Internal options: * \member lworkl Do not modify this option. * \member sigma The shift for the shift-invert mode. * \member sigmai The imaginary part of the shift, for the * non-symmetric or complex shift-invert mode. * \member iparam Do not modify this option. * \member ipntr Do not modify this option. * */ typedef struct igraph_arpack_options_t { /* INPUT */ char bmat[1]; /* I-standard problem, G-generalized */ int n; /* Dimension of the eigenproblem */ char which[2]; /* LA, SA, LM, SM, BE */ int nev; /* Number of eigenvalues to be computed */ igraph_real_t tol; /* Stopping criterion */ int ncv; /* Number of columns in V */ int ldv; /* Leading dimension of V */ int ishift; /* 0-reverse comm., 1-exact with tridiagonal */ int mxiter; /* Maximum number of update iterations to take */ int nb; /* Block size on the recurrence, only 1 works */ int mode; /* The kind of problem to be solved (1-5) 1: A*x=l*x, A symmetric 2: A*x=l*M*x, A symm. M pos. def. 3: K*x = l*M*x, K symm., M pos. semidef. 4: K*x = l*KG*x, K s. pos. semidef. KG s. indef. 5: A*x = l*M*x, A symm., M symm. pos. semidef. */ int start; /* 0: random, 1: use the supplied vector */ int lworkl; /* Size of temporary storage, default is fine */ igraph_real_t sigma; /* The shift for modes 3,4,5 */ igraph_real_t sigmai; /* The imaginary part of shift for rnsolve */ /* OUTPUT */ int info; /* What happened, see docs */ int ierr; /* What happened in the dseupd call */ int noiter; /* The number of iterations taken */ int nconv; int numop; /* Number of OP*x operations */ int numopb; /* Number of B*x operations if BMAT='G' */ int numreo; /* Number of steps of re-orthogonalizations */ /* INTERNAL */ int iparam[11]; int ipntr[14]; } igraph_arpack_options_t; /** * \struct igraph_arpack_storage_t * \brief Storage for ARPACK * * Public members, do not modify them directly, these are considered * to be read-only. * \member maxn Maximum rank of matrix. * \member maxncv Maximum NCV. * \member maxldv Maximum LDV. * * These members are considered to be private: * \member workl Working memory. * \member workd Working memory. * \member d Memory for eigenvalues. * \member resid Memory for residuals. * \member ax Working memory. * \member select Working memory. * \member di Memory for eigenvalues, non-symmetric case only. * \member workev Working memory, non-symmetric case only. */ typedef struct igraph_arpack_storage_t { int maxn, maxncv, maxldv; igraph_real_t *v; igraph_real_t *workl; igraph_real_t *workd; igraph_real_t *d; igraph_real_t *resid; igraph_real_t *ax; int *select; igraph_real_t *di; /* These two only for non-symmetric problems */ igraph_real_t *workev; } igraph_arpack_storage_t; DECLDIR void igraph_arpack_options_init(igraph_arpack_options_t *o); DECLDIR int igraph_arpack_storage_init(igraph_arpack_storage_t *s, long int maxn, long int maxncv, long int maxldv, igraph_bool_t symm); DECLDIR void igraph_arpack_storage_destroy(igraph_arpack_storage_t *s); /** * \typedef igraph_arpack_function_t * Type of the ARPACK callback function * * \param to Pointer to an \c igraph_real_t, the result of the * matrix-vector product is expected to be stored here. * \param from Pointer to an \c igraph_real_t, the input matrix should * be multiplied by the vector stored here. * \param n The length of the vector (which is the same as the order * of the input matrix). * \param extra Extra argument to the matrix-vector calculation * function. This is coming from the \ref igraph_arpack_rssolve() * or \ref igraph_arpack_rnsolve() function. * \return Error code, if not zero, then the ARPACK solver considers * this as an error, stops and calls the igraph error handler. */ typedef int igraph_arpack_function_t(igraph_real_t *to, const igraph_real_t *from, int n, void *extra); DECLDIR int igraph_arpack_rssolve(igraph_arpack_function_t *fun, void *extra, igraph_arpack_options_t *options, igraph_arpack_storage_t *storage, igraph_vector_t *values, igraph_matrix_t *vectors); DECLDIR int igraph_arpack_rnsolve(igraph_arpack_function_t *fun, void *extra, igraph_arpack_options_t *options, igraph_arpack_storage_t *storage, igraph_matrix_t *values, igraph_matrix_t *vectors); DECLDIR int igraph_arpack_unpack_complex(igraph_matrix_t *vectors, igraph_matrix_t *values, long int nev); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_matrix_pmt.h0000644000076500000240000002463113614300625026127 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ typedef struct TYPE(igraph_matrix) { TYPE(igraph_vector) data; long int nrow, ncol; } TYPE(igraph_matrix); /*---------------*/ /* Allocation */ /*---------------*/ DECLDIR int FUNCTION(igraph_matrix, init)(TYPE(igraph_matrix) *m, long int nrow, long int ncol); DECLDIR int FUNCTION(igraph_matrix, copy)(TYPE(igraph_matrix) *to, const TYPE(igraph_matrix) *from); DECLDIR void FUNCTION(igraph_matrix, destroy)(TYPE(igraph_matrix) *m); DECLDIR long int FUNCTION(igraph_matrix, capacity)(const TYPE(igraph_matrix) *m); /*--------------------*/ /* Accessing elements */ /*--------------------*/ /* MATRIX */ DECLDIR BASE FUNCTION(igraph_matrix, e)(const TYPE(igraph_matrix) *m, long int row, long int col); BASE* FUNCTION(igraph_matrix, e_ptr)(const TYPE(igraph_matrix) *m, long int row, long int col); DECLDIR void FUNCTION(igraph_matrix, set)(TYPE(igraph_matrix)* m, long int row, long int col, BASE value); /*------------------------------*/ /* Initializing matrix elements */ /*------------------------------*/ DECLDIR void FUNCTION(igraph_matrix, null)(TYPE(igraph_matrix) *m); DECLDIR void FUNCTION(igraph_matrix, fill)(TYPE(igraph_matrix) *m, BASE e); /*-----------------------*/ /* Matrix views */ /*-----------------------*/ const TYPE(igraph_matrix) *FUNCTION(igraph_matrix, view)(const TYPE(igraph_matrix) *m, const BASE *data, long int nrow, long int ncol); /*------------------*/ /* Copying matrices */ /*------------------*/ DECLDIR void FUNCTION(igraph_matrix, copy_to)(const TYPE(igraph_matrix) *m, BASE *to); DECLDIR int FUNCTION(igraph_matrix, update)(TYPE(igraph_matrix) *to, const TYPE(igraph_matrix) *from); DECLDIR int FUNCTION(igraph_matrix, rbind)(TYPE(igraph_matrix) *to, const TYPE(igraph_matrix) *from); DECLDIR int FUNCTION(igraph_matrix, cbind)(TYPE(igraph_matrix) *to, const TYPE(igraph_matrix) *from); DECLDIR int FUNCTION(igraph_matrix, swap)(TYPE(igraph_matrix) *m1, TYPE(igraph_matrix) *m2); /*--------------------------*/ /* Copying rows and columns */ /*--------------------------*/ DECLDIR int FUNCTION(igraph_matrix, get_row)(const TYPE(igraph_matrix) *m, TYPE(igraph_vector) *res, long int index); DECLDIR int FUNCTION(igraph_matrix, get_col)(const TYPE(igraph_matrix) *m, TYPE(igraph_vector) *res, long int index); DECLDIR int FUNCTION(igraph_matrix, set_row)(TYPE(igraph_matrix) *m, const TYPE(igraph_vector) *v, long int index); DECLDIR int FUNCTION(igraph_matrix, set_col)(TYPE(igraph_matrix) *m, const TYPE(igraph_vector) *v, long int index); DECLDIR int FUNCTION(igraph_matrix, select_rows)(const TYPE(igraph_matrix) *m, TYPE(igraph_matrix) *res, const igraph_vector_t *rows); DECLDIR int FUNCTION(igraph_matrix, select_cols)(const TYPE(igraph_matrix) *m, TYPE(igraph_matrix) *res, const igraph_vector_t *cols); DECLDIR int FUNCTION(igraph_matrix, select_rows_cols)(const TYPE(igraph_matrix) *m, TYPE(igraph_matrix) *res, const igraph_vector_t *rows, const igraph_vector_t *cols); /*-----------------------------*/ /* Exchanging rows and columns */ /*-----------------------------*/ DECLDIR int FUNCTION(igraph_matrix, swap_rows)(TYPE(igraph_matrix) *m, long int i, long int j); DECLDIR int FUNCTION(igraph_matrix, swap_cols)(TYPE(igraph_matrix) *m, long int i, long int j); DECLDIR int FUNCTION(igraph_matrix, swap_rowcol)(TYPE(igraph_matrix) *m, long int i, long int j); DECLDIR int FUNCTION(igraph_matrix, transpose)(TYPE(igraph_matrix) *m); /*-----------------------------*/ /* Matrix operations */ /*-----------------------------*/ DECLDIR int FUNCTION(igraph_matrix, add)(TYPE(igraph_matrix) *m1, const TYPE(igraph_matrix) *m2); DECLDIR int FUNCTION(igraph_matrix, sub)(TYPE(igraph_matrix) *m1, const TYPE(igraph_matrix) *m2); DECLDIR int FUNCTION(igraph_matrix, mul_elements)(TYPE(igraph_matrix) *m1, const TYPE(igraph_matrix) *m2); DECLDIR int FUNCTION(igraph_matrix, div_elements)(TYPE(igraph_matrix) *m1, const TYPE(igraph_matrix) *m2); DECLDIR void FUNCTION(igraph_matrix, scale)(TYPE(igraph_matrix) *m, BASE by); DECLDIR void FUNCTION(igraph_matrix, add_constant)(TYPE(igraph_matrix) *m, BASE plus); /*-----------------------------*/ /* Finding minimum and maximum */ /*-----------------------------*/ DECLDIR igraph_real_t FUNCTION(igraph_matrix, min)(const TYPE(igraph_matrix) *m); DECLDIR igraph_real_t FUNCTION(igraph_matrix, max)(const TYPE(igraph_matrix) *m); DECLDIR int FUNCTION(igraph_matrix, which_min)(const TYPE(igraph_matrix) *m, long int *i, long int *j); DECLDIR int FUNCTION(igraph_matrix, which_max)(const TYPE(igraph_matrix) *m, long int *i, long int *j); DECLDIR int FUNCTION(igraph_matrix, minmax)(const TYPE(igraph_matrix) *m, BASE *min, BASE *max); DECLDIR int FUNCTION(igraph_matrix, which_minmax)(const TYPE(igraph_matrix) *m, long int *imin, long int *jmin, long int *imax, long int *jmax); /*------------------------------*/ /* Comparison */ /*------------------------------*/ DECLDIR igraph_bool_t FUNCTION(igraph_matrix, all_e)(const TYPE(igraph_matrix) *lhs, const TYPE(igraph_matrix) *rhs); DECLDIR igraph_bool_t FUNCTION(igraph_matrix, all_l)(const TYPE(igraph_matrix) *lhs, const TYPE(igraph_matrix) *rhs); DECLDIR igraph_bool_t FUNCTION(igraph_matrix, all_g)(const TYPE(igraph_matrix) *lhs, const TYPE(igraph_matrix) *rhs); DECLDIR igraph_bool_t FUNCTION(igraph_matrix, all_le)(const TYPE(igraph_matrix) *lhs, const TYPE(igraph_matrix) *rhs); DECLDIR igraph_bool_t FUNCTION(igraph_matrix, all_ge)(const TYPE(igraph_matrix) *lhs, const TYPE(igraph_matrix) *rhs); /*-------------------*/ /* Matrix properties */ /*-------------------*/ DECLDIR igraph_bool_t FUNCTION(igraph_matrix, isnull)(const TYPE(igraph_matrix) *m); DECLDIR igraph_bool_t FUNCTION(igraph_matrix, empty)(const TYPE(igraph_matrix) *m); DECLDIR long int FUNCTION(igraph_matrix, size)(const TYPE(igraph_matrix) *m); DECLDIR long int FUNCTION(igraph_matrix, nrow)(const TYPE(igraph_matrix) *m); DECLDIR long int FUNCTION(igraph_matrix, ncol)(const TYPE(igraph_matrix) *m); DECLDIR igraph_bool_t FUNCTION(igraph_matrix, is_symmetric)(const TYPE(igraph_matrix) *m); DECLDIR BASE FUNCTION(igraph_matrix, sum)(const TYPE(igraph_matrix) *m); DECLDIR BASE FUNCTION(igraph_matrix, prod)(const TYPE(igraph_matrix) *m); DECLDIR int FUNCTION(igraph_matrix, rowsum)(const TYPE(igraph_matrix) *m, TYPE(igraph_vector) *res); DECLDIR int FUNCTION(igraph_matrix, colsum)(const TYPE(igraph_matrix) *m, TYPE(igraph_vector) *res); DECLDIR igraph_bool_t FUNCTION(igraph_matrix, is_equal)(const TYPE(igraph_matrix) *m1, const TYPE(igraph_matrix) *m2); DECLDIR igraph_real_t FUNCTION(igraph_matrix, maxdifference)(const TYPE(igraph_matrix) *m1, const TYPE(igraph_matrix) *m2); /*------------------------*/ /* Searching for elements */ /*------------------------*/ DECLDIR igraph_bool_t FUNCTION(igraph_matrix, contains)(const TYPE(igraph_matrix) *m, BASE e); DECLDIR igraph_bool_t FUNCTION(igraph_matrix, search)(const TYPE(igraph_matrix) *m, long int from, BASE what, long int *pos, long int *row, long int *col); /*------------------------*/ /* Resizing operations */ /*------------------------*/ DECLDIR int FUNCTION(igraph_matrix, resize)(TYPE(igraph_matrix) *m, long int nrow, long int ncol); DECLDIR int FUNCTION(igraph_matrix, resize_min)(TYPE(igraph_matrix) *m); DECLDIR int FUNCTION(igraph_matrix, add_cols)(TYPE(igraph_matrix) *m, long int n); DECLDIR int FUNCTION(igraph_matrix, add_rows)(TYPE(igraph_matrix) *m, long int n); DECLDIR int FUNCTION(igraph_matrix, remove_col)(TYPE(igraph_matrix) *m, long int col); DECLDIR int FUNCTION(igraph_matrix, remove_row)(TYPE(igraph_matrix) *m, long int row); /*------------------------*/ /* Print as text */ /*------------------------*/ int FUNCTION(igraph_matrix, print)(const TYPE(igraph_matrix) *m); int FUNCTION(igraph_matrix, printf)(const TYPE(igraph_matrix) *m, const char *format); int FUNCTION(igraph_matrix, fprint)(const TYPE(igraph_matrix) *m, FILE *file); #ifdef BASE_COMPLEX int igraph_matrix_complex_real(const igraph_matrix_complex_t *v, igraph_matrix_t *real); int igraph_matrix_complex_imag(const igraph_matrix_complex_t *v, igraph_matrix_t *imag); int igraph_matrix_complex_realimag(const igraph_matrix_complex_t *v, igraph_matrix_t *real, igraph_matrix_t *imag); int igraph_matrix_complex_create(igraph_matrix_complex_t *v, const igraph_matrix_t *real, const igraph_matrix_t *imag); int igraph_matrix_complex_create_polar(igraph_matrix_complex_t *v, const igraph_matrix_t *r, const igraph_matrix_t *theta); #endif /* ----------------------------------------------------------------------------*/ /* For internal use only, may be removed, rewritten ... */ /* ----------------------------------------------------------------------------*/ int FUNCTION(igraph_matrix, permdelete_rows)(TYPE(igraph_matrix) *m, long int *index, long int nremove); int FUNCTION(igraph_matrix, delete_rows_neg)(TYPE(igraph_matrix) *m, const igraph_vector_t *neg, long int nremove); python-igraph-0.8.0/vendor/source/igraph/include/igraph_stack_pmt.h0000644000076500000240000000353613614300625025731 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include /** * Stack data type. * \ingroup internal */ typedef struct TYPE(igraph_stack) { BASE* stor_begin; BASE* stor_end; BASE* end; } TYPE(igraph_stack); DECLDIR int FUNCTION(igraph_stack, init)(TYPE(igraph_stack)* s, long int size); DECLDIR void FUNCTION(igraph_stack, destroy)(TYPE(igraph_stack)* s); DECLDIR int FUNCTION(igraph_stack, reserve)(TYPE(igraph_stack)* s, long int size); DECLDIR igraph_bool_t FUNCTION(igraph_stack, empty)(TYPE(igraph_stack)* s); DECLDIR long int FUNCTION(igraph_stack, size)(const TYPE(igraph_stack)* s); DECLDIR void FUNCTION(igraph_stack, clear)(TYPE(igraph_stack)* s); DECLDIR int FUNCTION(igraph_stack, push)(TYPE(igraph_stack)* s, BASE elem); DECLDIR BASE FUNCTION(igraph_stack, pop)(TYPE(igraph_stack)* s); DECLDIR BASE FUNCTION(igraph_stack, top)(const TYPE(igraph_stack)* s); DECLDIR int FUNCTION(igraph_stack, print)(const TYPE(igraph_stack)* s); DECLDIR int FUNCTION(igraph_stack, fprint)(const TYPE(igraph_stack)* s, FILE *file); python-igraph-0.8.0/vendor/source/igraph/include/igraph_types.h0000644000076500000240000000547613614300625025115 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2003-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef REST_TYPES_H #define REST_TYPES_H #include "igraph_decls.h" __BEGIN_DECLS #ifndef _GNU_SOURCE #define _GNU_SOURCE 1 #endif #include "igraph_error.h" #include #include #include /* This is to eliminate gcc warnings about unused parameters */ #define IGRAPH_UNUSED(x) (void)(x) typedef int igraph_integer_t; typedef double igraph_real_t; typedef int igraph_bool_t; /* Replacements for printf that print doubles in the same way on all platforms * (even for NaN and infinities) */ DECLDIR int igraph_real_printf(igraph_real_t val); DECLDIR int igraph_real_fprintf(FILE *file, igraph_real_t val); DECLDIR int igraph_real_snprintf(char* str, size_t size, igraph_real_t val); /* Replacements for printf that print doubles in the same way on all platforms * (even for NaN and infinities) with the largest possible precision */ DECLDIR int igraph_real_printf_precise(igraph_real_t val); DECLDIR int igraph_real_fprintf_precise(FILE *file, igraph_real_t val); DECLDIR int igraph_real_snprintf_precise(char* str, size_t size, igraph_real_t val); /* igraph_i_fdiv is needed here instead of in igraph_math.h because * some constants use it */ double igraph_i_fdiv(const double a, const double b); #if defined(INFINITY) #define IGRAPH_INFINITY INFINITY #define IGRAPH_POSINFINITY INFINITY #define IGRAPH_NEGINFINITY (-INFINITY) #else #define IGRAPH_INFINITY (igraph_i_fdiv(1.0, 0.0)) #define IGRAPH_POSINFINITY (igraph_i_fdiv(1.0, 0.0)) #define IGRAPH_NEGINFINITY (igraph_i_fdiv(-1.0, 0.0)) #endif DECLDIR int igraph_finite(double x); #define IGRAPH_FINITE(x) igraph_finite(x) DECLDIR int igraph_is_nan(double x); DECLDIR int igraph_is_inf(double x); DECLDIR int igraph_is_posinf(double x); DECLDIR int igraph_is_neginf(double x); #if defined(NAN) #define IGRAPH_NAN NAN #elif defined(INFINITY) #define IGRAPH_NAN (INFINITY/INFINITY) #else #define IGRAPH_NAN (igraph_i_fdiv(0.0, 0.0)) #endif __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_topology.h0000644000076500000240000003202513614300625025613 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_TOPOLOGY_H #define IGRAPH_TOPOLOGY_H #include "igraph_decls.h" #include "igraph_constants.h" #include "igraph_datatype.h" #include "igraph_types.h" #include "igraph_vector_ptr.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* Degree sequences */ /* -------------------------------------------------- */ DECLDIR int igraph_is_degree_sequence(const igraph_vector_t *out_degrees, const igraph_vector_t *in_degrees, igraph_bool_t *res); DECLDIR int igraph_is_graphical_degree_sequence(const igraph_vector_t *out_degrees, const igraph_vector_t *in_degrees, igraph_bool_t *res); /* -------------------------------------------------- */ /* Directed acyclic graphs */ /* -------------------------------------------------- */ DECLDIR int igraph_topological_sorting(const igraph_t *graph, igraph_vector_t *res, igraph_neimode_t mode); DECLDIR int igraph_is_dag(const igraph_t *graph, igraph_bool_t *res); DECLDIR int igraph_transitive_closure_dag(const igraph_t *graph, igraph_t *closure); /* -------------------------------------------------- */ /* Graph isomorphisms */ /* -------------------------------------------------- */ /* Common functions */ DECLDIR int igraph_permute_vertices(const igraph_t *graph, igraph_t *res, const igraph_vector_t *permutation); DECLDIR int igraph_simplify_and_colorize( const igraph_t *graph, igraph_t *res, igraph_vector_int_t *vertex_color, igraph_vector_int_t *edge_color); /* Generic interface */ DECLDIR int igraph_isomorphic(const igraph_t *graph1, const igraph_t *graph2, igraph_bool_t *iso); DECLDIR int igraph_subisomorphic(const igraph_t *graph1, const igraph_t *graph2, igraph_bool_t *iso); /* LAD */ DECLDIR int igraph_subisomorphic_lad(const igraph_t *pattern, const igraph_t *target, igraph_vector_ptr_t *domains, igraph_bool_t *iso, igraph_vector_t *map, igraph_vector_ptr_t *maps, igraph_bool_t induced, int time_limit); /* VF2 family*/ /** * \typedef igraph_isohandler_t * Callback type, called when an isomorphism was found * * See the details at the documentation of \ref * igraph_isomorphic_function_vf2(). * \param map12 The mapping from the first graph to the second. * \param map21 The mapping from the second graph to the first, the * inverse of \p map12 basically. * \param arg This extra argument was passed to \ref * igraph_isomorphic_function_vf2() when it was called. * \return Boolean, whether to continue with the isomorphism search. */ typedef igraph_bool_t igraph_isohandler_t(const igraph_vector_t *map12, const igraph_vector_t *map21, void *arg); /** * \typedef igraph_isocompat_t * Callback type, called to check whether two vertices or edges are compatible * * VF2 (subgraph) isomorphism functions can be restricted by defining * relations on the vertices and/or edges of the graphs, and then checking * whether the vertices (edges) match according to these relations. * * This feature is implemented by two callbacks, one for * vertices, one for edges. Every time igraph tries to match a vertex (edge) * of the first (sub)graph to a vertex of the second graph, the vertex * (edge) compatibility callback is called. The callback returns a * logical value, giving whether the two vertices match. * * Both callback functions are of type \c igraph_isocompat_t. * \param graph1 The first graph. * \param graph2 The second graph. * \param g1_num The id of a vertex or edge in the first graph. * \param g2_num The id of a vertex or edge in the second graph. * \param arg Extra argument to pass to the callback functions. * \return Logical scalar, whether vertex (or edge) \p g1_num in \p graph1 * is compatible with vertex (or edge) \p g2_num in \p graph2. */ typedef igraph_bool_t igraph_isocompat_t(const igraph_t *graph1, const igraph_t *graph2, const igraph_integer_t g1_num, const igraph_integer_t g2_num, void *arg); DECLDIR int igraph_isomorphic_vf2(const igraph_t *graph1, const igraph_t *graph2, const igraph_vector_int_t *vertex_color1, const igraph_vector_int_t *vertex_color2, const igraph_vector_int_t *edge_color1, const igraph_vector_int_t *edge_color2, igraph_bool_t *iso, igraph_vector_t *map12, igraph_vector_t *map21, igraph_isocompat_t *node_compat_fn, igraph_isocompat_t *edge_compat_fn, void *arg); DECLDIR int igraph_isomorphic_function_vf2(const igraph_t *graph1, const igraph_t *graph2, const igraph_vector_int_t *vertex_color1, const igraph_vector_int_t *vertex_color2, const igraph_vector_int_t *edge_color1, const igraph_vector_int_t *edge_color2, igraph_vector_t *map12, igraph_vector_t *map21, igraph_isohandler_t *isohandler_fn, igraph_isocompat_t *node_compat_fn, igraph_isocompat_t *edge_compat_fn, void *arg); DECLDIR int igraph_count_isomorphisms_vf2(const igraph_t *graph1, const igraph_t *graph2, const igraph_vector_int_t *vertex_color1, const igraph_vector_int_t *vertex_color2, const igraph_vector_int_t *edge_color1, const igraph_vector_int_t *edge_color2, igraph_integer_t *count, igraph_isocompat_t *node_compat_fn, igraph_isocompat_t *edge_compat_fn, void *arg); DECLDIR int igraph_get_isomorphisms_vf2(const igraph_t *graph1, const igraph_t *graph2, const igraph_vector_int_t *vertex_color1, const igraph_vector_int_t *vertex_color2, const igraph_vector_int_t *edge_color1, const igraph_vector_int_t *edge_color2, igraph_vector_ptr_t *maps, igraph_isocompat_t *node_compat_fn, igraph_isocompat_t *edge_compat_fn, void *arg); DECLDIR int igraph_subisomorphic_vf2(const igraph_t *graph1, const igraph_t *graph2, const igraph_vector_int_t *vertex_color1, const igraph_vector_int_t *vertex_color2, const igraph_vector_int_t *edge_color1, const igraph_vector_int_t *edge_color2, igraph_bool_t *iso, igraph_vector_t *map12, igraph_vector_t *map21, igraph_isocompat_t *node_compat_fn, igraph_isocompat_t *edge_compat_fn, void *arg); DECLDIR int igraph_subisomorphic_function_vf2(const igraph_t *graph1, const igraph_t *graph2, const igraph_vector_int_t *vertex_color1, const igraph_vector_int_t *vertex_color2, const igraph_vector_int_t *edge_color1, const igraph_vector_int_t *edge_color2, igraph_vector_t *map12, igraph_vector_t *map21, igraph_isohandler_t *isohandler_fn, igraph_isocompat_t *node_compat_fn, igraph_isocompat_t *edge_compat_fn, void *arg); DECLDIR int igraph_count_subisomorphisms_vf2(const igraph_t *graph1, const igraph_t *graph2, const igraph_vector_int_t *vertex_color1, const igraph_vector_int_t *vertex_color2, const igraph_vector_int_t *edge_color1, const igraph_vector_int_t *edge_color2, igraph_integer_t *count, igraph_isocompat_t *node_compat_fn, igraph_isocompat_t *edge_compat_fn, void *arg); DECLDIR int igraph_get_subisomorphisms_vf2(const igraph_t *graph1, const igraph_t *graph2, const igraph_vector_int_t *vertex_color1, const igraph_vector_int_t *vertex_color2, const igraph_vector_int_t *edge_color1, const igraph_vector_int_t *edge_color2, igraph_vector_ptr_t *maps, igraph_isocompat_t *node_compat_fn, igraph_isocompat_t *edge_compat_fn, void *arg); /* BLISS family */ /** * \struct igraph_bliss_info_t * Information about a BLISS run * * Some secondary information found by the BLISS algorithm is stored * here. It is useful if you wany to study the internal working of the * algorithm. * \member nof_nodes The number of nodes in the search tree. * \member nof_leaf_nodes The number of leaf nodes in the search tree. * \member nof_bad_nodes Number of bad nodes. * \member nof_canupdates Number of canrep updates. * \member nof_generators Number of generators of the automorphism group. * \member max_level Maximum level. * \member group_size The size of the automorphism group of the graph, * given as a string. It should be deallocated via * \ref igraph_free() if not needed any more. * * See http://www.tcs.hut.fi/Software/bliss/index.html * for details about the algorithm and these parameters. */ typedef struct igraph_bliss_info_t { unsigned long nof_nodes; unsigned long nof_leaf_nodes; unsigned long nof_bad_nodes; unsigned long nof_canupdates; unsigned long nof_generators; unsigned long max_level; char *group_size; } igraph_bliss_info_t; /** * \typedef igraph_bliss_sh_t * Splitting heuristics for BLISS * * \enumval IGRAPH_BLISS_F First non-singleton cell. * \enumval IGRAPH_BLISS_FL First largest non-singleton cell. * \enumval IGRAPH_BLISS_FS First smallest non-singleton cell. * \enumval IGRAPH_BLISS_FM First maximally non-trivially connected * non-singleton cell. * \enumval IGRAPH_BLISS_FLM Largest maximally non-trivially connected * non-singleton cell. * \enumval IGRAPH_BLISS_FSM Smallest maximally non-trivially * connected non-singletion cell. */ typedef enum { IGRAPH_BLISS_F = 0, IGRAPH_BLISS_FL, IGRAPH_BLISS_FS, IGRAPH_BLISS_FM, IGRAPH_BLISS_FLM, IGRAPH_BLISS_FSM } igraph_bliss_sh_t; DECLDIR int igraph_canonical_permutation(const igraph_t *graph, const igraph_vector_int_t *colors, igraph_vector_t *labeling, igraph_bliss_sh_t sh, igraph_bliss_info_t *info); DECLDIR int igraph_isomorphic_bliss(const igraph_t *graph1, const igraph_t *graph2, const igraph_vector_int_t *colors1, const igraph_vector_int_t *colors2, igraph_bool_t *iso, igraph_vector_t *map12, igraph_vector_t *map21, igraph_bliss_sh_t sh, igraph_bliss_info_t *info1, igraph_bliss_info_t *info2); DECLDIR int igraph_automorphisms(const igraph_t *graph, const igraph_vector_int_t *colors, igraph_bliss_sh_t sh, igraph_bliss_info_t *info); DECLDIR int igraph_automorphism_group(const igraph_t *graph, const igraph_vector_int_t *colors, igraph_vector_ptr_t *generators, igraph_bliss_sh_t sh, igraph_bliss_info_t *info); /* Functions for 3-4 graphs */ DECLDIR int igraph_isomorphic_34(const igraph_t *graph1, const igraph_t *graph2, igraph_bool_t *iso); DECLDIR int igraph_isoclass(const igraph_t *graph, igraph_integer_t *isoclass); DECLDIR int igraph_isoclass_subgraph(const igraph_t *graph, igraph_vector_t *vids, igraph_integer_t *isoclass); DECLDIR int igraph_isoclass_create(igraph_t *graph, igraph_integer_t size, igraph_integer_t number, igraph_bool_t directed); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_pmt.h0000644000076500000240000001012113614300625024530 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #define CONCAT2x(a,b) a ## _ ## b #define CONCAT2(a,b) CONCAT2x(a,b) #define CONCAT3x(a,b,c) a ## _ ## b ## _ ## c #define CONCAT3(a,b,c) CONCAT3x(a,b,c) #define CONCAT4x(a,b,c,d) a ## _ ## b ## _ ## c ## _ ## d #define CONCAT4(a,b,c,d) CONCAT4x(a,b,c,d) #if defined(BASE_IGRAPH_REAL) #define BASE igraph_real_t #define SHORT #define OUT_FORMAT "%G" #define PRINTFUNC(val) igraph_real_printf(val) #define FPRINTFUNC(file, val) igraph_real_fprintf(file, val) #define ZERO 0.0 #define ONE 1.0 #define MULTIPLICITY 1 #elif defined(BASE_FLOAT) #define BASE float #define SHORT float #define OUT_FORMAT "%f" #define ZERO 0.0F #define ONE 1.0F #define MULTIPLICITY 1 #elif defined(BASE_LONG) #define BASE long #define SHORT long #define OUT_FORMAT "%ld" #define ZERO 0L #define ONE 1L #define MULTIPLICITY 1 #elif defined(BASE_CHAR) #define BASE char #define SHORT char #define OUT_FORMAT "%d" #define ZERO 0 #define ONE 1 #define MULTIPLICITY 1 #elif defined(BASE_BOOL) #define BASE igraph_bool_t #define SHORT bool #define OUT_FORMAT "%d" #define ZERO 0 #define ONE 1 #define MULTIPLICITY 1 #elif defined(BASE_INT) #define BASE int #define SHORT int #define OUT_FORMAT "%d" #define ZERO 0 #define ONE 1 #define MULTIPLICITY 1 #elif defined(BASE_LIMB) #define BASE limb_t #define SHORT limb #define ZERO 0 #define ONE 1 #define MULTIPLICITY 1 #define UNSIGNED 1 #elif defined(BASE_PTR) #define BASE void* #define SHORT ptr #define ZERO 0 #define MULTIPLICITY 1 #elif defined(BASE_COMPLEX) #undef complex #define BASE igraph_complex_t #define SHORT complex #define ZERO igraph_complex(0,0) #define ONE {{1.0,0.0}} #define MULTIPLICITY 2 #define NOTORDERED 1 #define NOABS 1 #define SUM(a,b,c) ((a) = igraph_complex_add((b),(c))) #define DIFF(a,b,c) ((a) = igraph_complex_sub((b),(c))) #define PROD(a,b,c) ((a) = igraph_complex_mul((b),(c))) #define DIV(a,b,c) ((a) = igraph_complex_div((b),(c))) #define EQ(a,b) IGRAPH_COMPLEX_EQ((a),(b)) #define SQ(a) IGRAPH_REAL(igraph_complex_mul((a),(a))) #else #error unknown BASE_ directive #endif #if defined(BASE_IGRAPH_REAL) #define FUNCTION(dir,name) CONCAT2(dir,name) #define TYPE(dir) CONCAT2(dir,t) #elif defined(BASE_BOOL) /* Special case because stdbool.h defines bool as a macro to _Bool which would * screw things up */ #define FUNCTION(a,c) CONCAT3x(a,bool,c) #define TYPE(dir) CONCAT3x(dir,bool,t) #else #define FUNCTION(a,c) CONCAT3(a,SHORT,c) #define TYPE(dir) CONCAT3(dir,SHORT,t) #endif #if defined(HEAP_TYPE_MIN) #define HEAPMORE < #define HEAPMOREEQ <= #define HEAPLESS > #define HEAPLESSEQ >= #undef FUNCTION #undef TYPE #if defined(BASE_IGRAPH_REAL) #define FUNCTION(dir,name) CONCAT3(dir,min,name) #define TYPE(dir) CONCAT3(dir,min,t) #else #define FUNCTION(a,c) CONCAT4(a,min,SHORT,c) #define TYPE(dir) CONCAT4(dir,min,SHORT,t) #endif #endif #if defined(HEAP_TYPE_MAX) #define HEAPMORE > #define HEAPMOREEQ >= #define HEAPLESS < #define HEAPLESSEQ <= #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_array_pmt.h0000644000076500000240000000422513614300625025736 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ typedef struct TYPE(igraph_array3) { TYPE(igraph_vector) data; long int n1, n2, n3, n1n2; } TYPE(igraph_array3); #ifndef IGRAPH_ARRAY3_INIT_FINALLY #define IGRAPH_ARRAY3_INIT_FINALLY(a, n1, n2, n3) \ do { IGRAPH_CHECK(igraph_array3_init(a, n1, n2, n3)); \ IGRAPH_FINALLY(igraph_array3_destroy, a); } while (0) #endif #ifndef ARRAY3 #define ARRAY3(m,i,j,k) ((m).data.stor_begin[(m).n1n2*(k)+(m).n1*(j)+(i)]) #endif int FUNCTION(igraph_array3, init)(TYPE(igraph_array3) *a, long int n1, long int n2, long int n3); void FUNCTION(igraph_array3, destroy)(TYPE(igraph_array3) *a); long int FUNCTION(igraph_array3, size)(const TYPE(igraph_array3) *a); long int FUNCTION(igraph_array3, n)(const TYPE(igraph_array3) *a, long int idx); int FUNCTION(igraph_array3, resize)(TYPE(igraph_array3) *a, long int n1, long int n2, long int n3); void FUNCTION(igraph_array3, null)(TYPE(igraph_array3) *a); BASE FUNCTION(igraph_array3, sum)(const TYPE(igraph_array3) *a); void FUNCTION(igraph_array3, scale)(TYPE(igraph_array3) *a, BASE by); void FUNCTION(igraph_array3, fill)(TYPE(igraph_array3) *a, BASE e); int FUNCTION(igraph_array3, update)(TYPE(igraph_array3) *to, const TYPE(igraph_array3) *from); python-igraph-0.8.0/vendor/source/igraph/include/igraph_memory.h0000644000076500000240000000265013614300625025250 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2003-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef REST_MEMORY_H #define REST_MEMORY_H #include #include "igraph_decls.h" __BEGIN_DECLS #define igraph_Calloc(n,t) (t*) calloc( (size_t)(n), sizeof(t) ) #define igraph_Realloc(p,n,t) (t*) realloc((void*)(p), (size_t)((n)*sizeof(t))) #define igraph_Free(p) (free( (void *)(p) ), (p) = NULL) /* #ifndef IGRAPH_NO_CALLOC */ /* # define Calloc igraph_Calloc */ /* # define Realloc igraph_Realloc */ /* # define Free igraph_Free */ /* #endif */ DECLDIR int igraph_free(void *p); DECLDIR void *igraph_malloc(size_t n); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_epidemics.h0000644000076500000240000000420313614300625025676 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2014 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_EPIDEMICS_H #define IGRAPH_EPIDEMICS_H #include "igraph_decls.h" #include "igraph_datatype.h" #include "igraph_vector.h" #include "igraph_vector_ptr.h" __BEGIN_DECLS /** * \struct igraph_sir_t * * Data structure to store the results of one simulation * of the SIR (susceptible-infected-recovered) model on a graph. * * It has the following members. They are all (real or integer) * vectors, and they are of the same length. * * \member times A vector, the times of the events are stored here. * \member no_s An integer vector, the number of susceptibles in * each time step is stored here. * \member no_i An integer vector, the number of infected individuals * at each time step, is stored here. * \member no_r An integer vector, the number of recovered individuals * is stored here at each time step. */ typedef struct igraph_sir_t { igraph_vector_t times; igraph_vector_int_t no_s, no_i, no_r; } igraph_sir_t; DECLDIR int igraph_sir_init(igraph_sir_t *sir); DECLDIR void igraph_sir_destroy(igraph_sir_t *sir); DECLDIR int igraph_sir(const igraph_t *graph, igraph_real_t beta, igraph_real_t gamma, igraph_integer_t no_sim, igraph_vector_ptr_t *result); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_operators.h0000644000076500000240000000521413614300625025755 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_OPERATORS_H #define IGRAPH_OPERATORS_H #include "igraph_decls.h" #include "igraph_constants.h" #include "igraph_types.h" #include "igraph_datatype.h" #include "igraph_vector_ptr.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* Graph operators */ /* -------------------------------------------------- */ DECLDIR int igraph_disjoint_union(igraph_t *res, const igraph_t *left, const igraph_t *right); DECLDIR int igraph_disjoint_union_many(igraph_t *res, const igraph_vector_ptr_t *graphs); DECLDIR int igraph_union(igraph_t *res, const igraph_t *left, const igraph_t *right, igraph_vector_t *edge_map1, igraph_vector_t *edge_map2); DECLDIR int igraph_union_many(igraph_t *res, const igraph_vector_ptr_t *graphs, igraph_vector_ptr_t *edgemaps); DECLDIR int igraph_intersection(igraph_t *res, const igraph_t *left, const igraph_t *right, igraph_vector_t *edge_map1, igraph_vector_t *edge_map2); DECLDIR int igraph_intersection_many(igraph_t *res, const igraph_vector_ptr_t *graphs, igraph_vector_ptr_t *edgemaps); DECLDIR int igraph_difference(igraph_t *res, const igraph_t *orig, const igraph_t *sub); DECLDIR int igraph_complementer(igraph_t *res, const igraph_t *graph, igraph_bool_t loops); DECLDIR int igraph_compose(igraph_t *res, const igraph_t *g1, const igraph_t *g2, igraph_vector_t *edge_map1, igraph_vector_t *edge_map2); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_adjlist.h0000644000076500000240000002173313614300625025375 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_ADJLIST_H #define IGRAPH_ADJLIST_H #include "igraph_decls.h" #include "igraph_constants.h" #include "igraph_types.h" #include "igraph_datatype.h" __BEGIN_DECLS typedef struct igraph_adjlist_t { igraph_integer_t length; igraph_vector_int_t *adjs; } igraph_adjlist_t; DECLDIR int igraph_adjlist_init(const igraph_t *graph, igraph_adjlist_t *al, igraph_neimode_t mode); DECLDIR int igraph_adjlist_init_empty(igraph_adjlist_t *al, igraph_integer_t no_of_nodes); DECLDIR igraph_integer_t igraph_adjlist_size(const igraph_adjlist_t *al); DECLDIR int igraph_adjlist_init_complementer(const igraph_t *graph, igraph_adjlist_t *al, igraph_neimode_t mode, igraph_bool_t loops); DECLDIR void igraph_adjlist_destroy(igraph_adjlist_t *al); DECLDIR void igraph_adjlist_clear(igraph_adjlist_t *al); DECLDIR void igraph_adjlist_sort(igraph_adjlist_t *al); DECLDIR int igraph_adjlist_simplify(igraph_adjlist_t *al); DECLDIR int igraph_adjlist_remove_duplicate(const igraph_t *graph, igraph_adjlist_t *al); DECLDIR int igraph_adjlist_print(const igraph_adjlist_t *al); DECLDIR int igraph_adjlist_fprint(const igraph_adjlist_t *al, FILE *outfile); DECLDIR igraph_bool_t igraph_adjlist_has_edge(igraph_adjlist_t* al, igraph_integer_t from, igraph_integer_t to, igraph_bool_t directed); DECLDIR int igraph_adjlist_replace_edge(igraph_adjlist_t* al, igraph_integer_t from, igraph_integer_t oldto, igraph_integer_t newto, igraph_bool_t directed); /* igraph_vector_int_t *igraph_adjlist_get(const igraph_adjlist_t *al, */ /* igraph_integer_t no); */ /** * \define igraph_adjlist_get * Query a vector in an adjlist * * Returns a pointer to an igraph_vector_int_t object from an * adjacency list. The vector can be modified as desired. * \param al The adjacency list object. * \param no The vertex of which the vertex of adjacent vertices are * returned. * \return Pointer to the igraph_vector_int_t object. * * Time complexity: O(1). */ #define igraph_adjlist_get(al,no) (&(al)->adjs[(long int)(no)]) DECLDIR int igraph_adjlist(igraph_t *graph, const igraph_adjlist_t *adjlist, igraph_neimode_t mode, igraph_bool_t duplicate); typedef struct igraph_inclist_t { igraph_integer_t length; igraph_vector_int_t *incs; } igraph_inclist_t; DECLDIR int igraph_inclist_init(const igraph_t *graph, igraph_inclist_t *il, igraph_neimode_t mode); DECLDIR int igraph_inclist_init_empty(igraph_inclist_t *il, igraph_integer_t n); DECLDIR void igraph_inclist_destroy(igraph_inclist_t *il); DECLDIR void igraph_inclist_clear(igraph_inclist_t *il); DECLDIR int igraph_inclist_remove_duplicate(const igraph_t *graph, igraph_inclist_t *il); DECLDIR int igraph_inclist_print(const igraph_inclist_t *il); DECLDIR int igraph_inclist_fprint(const igraph_inclist_t *il, FILE *outfile); /** * \define igraph_inclist_get * Query a vector in an incidence list * * Returns a pointer to an igraph_vector_int_t object from an * incidence list containing edge ids. The vector can be modified, * resized, etc. as desired. * \param il Pointer to the incidence list. * \param no The vertex for which the incident edges are returned. * \return Pointer to an igraph_vector_int_t object. * * Time complexity: O(1). */ #define igraph_inclist_get(il,no) (&(il)->incs[(long int)(no)]) typedef struct igraph_lazy_adjlist_t { const igraph_t *graph; igraph_integer_t length; igraph_vector_t **adjs; igraph_neimode_t mode; igraph_lazy_adlist_simplify_t simplify; } igraph_lazy_adjlist_t; DECLDIR int igraph_lazy_adjlist_init(const igraph_t *graph, igraph_lazy_adjlist_t *al, igraph_neimode_t mode, igraph_lazy_adlist_simplify_t simplify); DECLDIR void igraph_lazy_adjlist_destroy(igraph_lazy_adjlist_t *al); DECLDIR void igraph_lazy_adjlist_clear(igraph_lazy_adjlist_t *al); /* igraph_vector_t *igraph_lazy_adjlist_get(igraph_lazy_adjlist_t *al, */ /* igraph_integer_t no); */ /** * \define igraph_lazy_adjlist_get * Query neighbor vertices * * If the function is called for the first time for a vertex then the * result is stored in the adjacency list and no further query * operations are needed when the neighbors of the same vertex are * queried again. * \param al The lazy adjacency list. * \param no The vertex id to query. * \return Pointer to a vector. It is allowed to modify it and * modification does not affect the original graph. * * Time complexity: O(d), the number of neighbor vertices for the * first time, O(1) for subsequent calls. */ #define igraph_lazy_adjlist_get(al,no) \ ((al)->adjs[(long int)(no)] != 0 ? ((al)->adjs[(long int)(no)]) : \ (igraph_lazy_adjlist_get_real(al, no))) DECLDIR igraph_vector_t *igraph_lazy_adjlist_get_real(igraph_lazy_adjlist_t *al, igraph_integer_t no); typedef struct igraph_lazy_inclist_t { const igraph_t *graph; igraph_integer_t length; igraph_vector_t **incs; igraph_neimode_t mode; } igraph_lazy_inclist_t; DECLDIR int igraph_lazy_inclist_init(const igraph_t *graph, igraph_lazy_inclist_t *il, igraph_neimode_t mode); DECLDIR void igraph_lazy_inclist_destroy(igraph_lazy_inclist_t *il); DECLDIR void igraph_lazy_inclist_clear(igraph_lazy_inclist_t *il); /** * \define igraph_lazy_inclist_get * Query incident edges * * If the function is called for the first time for a vertex, then the * result is stored in the incidence list and no further query * operations are needed when the incident edges of the same vertex are * queried again. * \param al The lazy incidence list object. * \param no The vertex id to query. * \return Pointer to a vector. It is allowed to modify it and * modification does not affect the original graph. * * Time complexity: O(d), the number of incident edges for the first * time, O(1) for subsequent calls with the same \p no argument. */ #define igraph_lazy_inclist_get(al,no) \ ((al)->incs[(long int)(no)] != 0 ? ((al)->incs[(long int)(no)]) : \ (igraph_lazy_inclist_get_real(al, no))) DECLDIR igraph_vector_t *igraph_lazy_inclist_get_real(igraph_lazy_inclist_t *al, igraph_integer_t no); /************************************************************************* * DEPRECATED TYPES AND FUNCTIONS */ typedef igraph_inclist_t igraph_adjedgelist_t; DECLDIR int igraph_adjedgelist_init(const igraph_t *graph, igraph_inclist_t *il, igraph_neimode_t mode); DECLDIR void igraph_adjedgelist_destroy(igraph_inclist_t *il); DECLDIR int igraph_adjedgelist_remove_duplicate(const igraph_t *graph, igraph_inclist_t *il); DECLDIR int igraph_adjedgelist_print(const igraph_inclist_t *il, FILE *outfile); /** * \define igraph_adjedgelist_get * Query a vector in an incidence list * * This macro was superseded by \ref igraph_inclist_get() in igraph 0.6. * Please use \ref igraph_inclist_get() instead of this macro. * * * Deprecated in version 0.6. */ #define igraph_adjedgelist_get(ael,no) (&(ael)->incs[(long int)(no)]) typedef igraph_lazy_inclist_t igraph_lazy_adjedgelist_t; DECLDIR int igraph_lazy_adjedgelist_init(const igraph_t *graph, igraph_lazy_inclist_t *il, igraph_neimode_t mode); DECLDIR void igraph_lazy_adjedgelist_destroy(igraph_lazy_inclist_t *il); /** * \define igraph_lazy_adjedgelist_get * Query a vector in a lazy incidence list * * This macro was superseded by \ref igraph_lazy_inclist_get() in igraph 0.6. * Please use \ref igraph_lazy_inclist_get() instead of this macro. * * * Deprecated in version 0.6. */ #define igraph_lazy_adjedgelist_get(al,no) \ ((al)->incs[(long int)(no)] != 0 ? ((al)->incs[(long int)(no)]) : \ (igraph_lazy_adjedgelist_get_real(al, no))) DECLDIR igraph_vector_t *igraph_lazy_adjedgelist_get_real(igraph_lazy_inclist_t *al, igraph_integer_t no); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_dqueue.h0000644000076500000240000000371613614300625025234 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_DQUEUE_H #define IGRAPH_DQUEUE_H #include "igraph_types.h" #include "igraph_decls.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* double ended queue, very useful */ /* -------------------------------------------------- */ #define BASE_IGRAPH_REAL #include "igraph_pmt.h" #include "igraph_dqueue_pmt.h" #include "igraph_pmt_off.h" #undef BASE_IGRAPH_REAL #define BASE_LONG #include "igraph_pmt.h" #include "igraph_dqueue_pmt.h" #include "igraph_pmt_off.h" #undef BASE_LONG #define BASE_CHAR #include "igraph_pmt.h" #include "igraph_dqueue_pmt.h" #include "igraph_pmt_off.h" #undef BASE_CHAR #define BASE_BOOL #include "igraph_pmt.h" #include "igraph_dqueue_pmt.h" #include "igraph_pmt_off.h" #undef BASE_BOOL #define BASE_INT #include "igraph_pmt.h" #include "igraph_dqueue_pmt.h" #include "igraph_pmt_off.h" #undef BASE_INT #define IGRAPH_DQUEUE_NULL { 0,0,0,0 } #define IGRAPH_DQUEUE_INIT_FINALLY(v, size) \ do { IGRAPH_CHECK(igraph_dqueue_init(v, size)); \ IGRAPH_FINALLY(igraph_dqueue_destroy, v); } while (0) __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_mixing.h0000644000076500000240000000327213614300625025234 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_MIXING_H #define IGRAPH_MIXING_H #include "igraph_decls.h" #include "igraph_types.h" #include "igraph_datatype.h" #include "igraph_vector.h" __BEGIN_DECLS DECLDIR int igraph_assortativity_nominal(const igraph_t *graph, const igraph_vector_t *types, igraph_real_t *res, igraph_bool_t directed); DECLDIR int igraph_assortativity(const igraph_t *graph, const igraph_vector_t *types1, const igraph_vector_t *types2, igraph_real_t *res, igraph_bool_t directed); DECLDIR int igraph_assortativity_degree(const igraph_t *graph, igraph_real_t *res, igraph_bool_t directed); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_visitor.h0000644000076500000240000001204713614300625025440 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_VISITOR_H #define IGRAPH_VISITOR_H #include "igraph_decls.h" #include "igraph_constants.h" #include "igraph_types.h" #include "igraph_datatype.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* Visitor-like functions */ /* -------------------------------------------------- */ /** * \typedef igraph_bfshandler_t * Callback type for BFS function * * \ref igraph_bfs() is able to call a callback function, whenever a * new vertex is found, while doing the breadth-first search. This * callback function must be of type \c igraph_bfshandler_t. It has * the following arguments: * \param graph The graph that that algorithm is working on. Of course * this must not be modified. * \param vid The id of the vertex just found by the breadth-first * search. * \param pred The id of the previous vertex visited. It is -1 if * there is no previous vertex, because the current vertex is the root * is a search tree. * \param succ The id of the next vertex that will be visited. It is * -1 if there is no next vertex, because the current vertex is the * last one in a search tree. * \param rank The rank of the current vertex, it starts with zero. * \param dist The distance (number of hops) of the current vertex * from the root of the current search tree. * \param extra The extra argument that was passed to \ref * igraph_bfs(). * \return A logical value, if TRUE (=non-zero), that is interpreted * as a request to stop the BFS and return to the caller. If a BFS * is terminated like this, then all elements of the result vectors * that were not yet calculated at the point of the termination * contain \c IGRAPH_NAN. * * \sa \ref igraph_bfs() */ typedef igraph_bool_t igraph_bfshandler_t(const igraph_t *graph, igraph_integer_t vid, igraph_integer_t pred, igraph_integer_t succ, igraph_integer_t rank, igraph_integer_t dist, void *extra); DECLDIR int igraph_bfs(const igraph_t *graph, igraph_integer_t root, const igraph_vector_t *roots, igraph_neimode_t mode, igraph_bool_t unreachable, const igraph_vector_t *restricted, igraph_vector_t *order, igraph_vector_t *rank, igraph_vector_t *father, igraph_vector_t *pred, igraph_vector_t *succ, igraph_vector_t *dist, igraph_bfshandler_t *callback, void *extra); int igraph_i_bfs(igraph_t *graph, igraph_integer_t vid, igraph_neimode_t mode, igraph_vector_t *vids, igraph_vector_t *layers, igraph_vector_t *parents); /** * \function igraph_dfshandler_t * Callback type for the DFS function * * \ref igraph_dfs() is able to call a callback function, whenever a * new vertex is discovered, and/or whenever a subtree is * completed. These callbacks must be of type \c * igraph_dfshandler_t. They have the following arguments: * \param graph The graph that that algorithm is working on. Of course * this must not be modified. * \param vid The id of the vertex just found by the depth-first * search. * \param dist The distance (number of hops) of the current vertex * from the root of the current search tree. * \param extra The extra argument that was passed to \ref * igraph_dfs(). * \return A logical value, if TRUE (=non-zero), that is interpreted * as a request to stop the DFS and return to the caller. If a DFS * is terminated like this, then all elements of the result vectors * that were not yet calculated at the point of the termination * contain \c IGRAPH_NAN. * * \sa \ref igraph_dfs() */ typedef igraph_bool_t igraph_dfshandler_t(const igraph_t *graph, igraph_integer_t vid, igraph_integer_t dist, void *extra); DECLDIR int igraph_dfs(const igraph_t *graph, igraph_integer_t root, igraph_neimode_t mode, igraph_bool_t unreachable, igraph_vector_t *order, igraph_vector_t *order_out, igraph_vector_t *father, igraph_vector_t *dist, igraph_dfshandler_t *in_callback, igraph_dfshandler_t *out_callback, void *extra); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_motifs.h0000644000076500000240000000755113614300625025246 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_MOTIFS_H #define IGRAPH_MOTIFS_H #include "igraph_decls.h" #include "igraph_types.h" #include "igraph_datatype.h" #include "igraph_iterators.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* Graph motifs */ /* -------------------------------------------------- */ /** * \typedef igraph_motifs_handler_t * Callback type for \c igraph_motifs_randesu_callback * * \ref igraph_motifs_randesu_callback() calls a specified callback * function whenever a new motif is found during a motif search. This * callback function must be of type \c igraph_motifs_handler_t. It has * the following arguments: * \param graph The graph that that algorithm is working on. Of course * this must not be modified. * \param vids The IDs of the vertices in the motif that has just been * found. This vector is owned by the motif search algorithm, so do not * modify or destroy it; make a copy of it if you need it later. * \param isoclass The isomorphism class of the motif that has just been * found. Use \ref igraph_isoclass or \ref igraph_isoclass_subgraph to find * out which isomorphism class belongs to a given motif. * \param extra The extra argument that was passed to \ref * igraph_motifs_randesu_callback(). * \return A logical value, if TRUE (=non-zero), that is interpreted * as a request to stop the motif search and return to the caller. * * \sa \ref igraph_motifs_randesu_callback() */ typedef igraph_bool_t igraph_motifs_handler_t(const igraph_t *graph, igraph_vector_t *vids, int isoclass, void* extra); DECLDIR int igraph_motifs_randesu(const igraph_t *graph, igraph_vector_t *hist, int size, const igraph_vector_t *cut_prob); DECLDIR int igraph_motifs_randesu_callback(const igraph_t *graph, int size, const igraph_vector_t *cut_prob, igraph_motifs_handler_t *callback, void* extra); DECLDIR int igraph_motifs_randesu_estimate(const igraph_t *graph, igraph_integer_t *est, int size, const igraph_vector_t *cut_prob, igraph_integer_t sample_size, const igraph_vector_t *sample); DECLDIR int igraph_motifs_randesu_no(const igraph_t *graph, igraph_integer_t *no, int size, const igraph_vector_t *cut_prob); DECLDIR int igraph_dyad_census(const igraph_t *graph, igraph_integer_t *mut, igraph_integer_t *asym, igraph_integer_t *null); DECLDIR int igraph_triad_census(const igraph_t *igraph, igraph_vector_t *res); DECLDIR int igraph_triad_census_24(const igraph_t *graph, igraph_real_t *res2, igraph_real_t *res4); DECLDIR int igraph_adjacent_triangles(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids); DECLDIR int igraph_list_triangles(const igraph_t *graph, igraph_vector_int_t *res); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_heap_pmt.h0000644000076500000240000000371213614300625025535 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ typedef struct TYPE(igraph_heap) { BASE* stor_begin; BASE* stor_end; BASE* end; int destroy; } TYPE(igraph_heap); DECLDIR int FUNCTION(igraph_heap, init)(TYPE(igraph_heap)* h, long int size); DECLDIR int FUNCTION(igraph_heap, init_array)(TYPE(igraph_heap) *t, BASE* data, long int len); DECLDIR void FUNCTION(igraph_heap, destroy)(TYPE(igraph_heap)* h); DECLDIR igraph_bool_t FUNCTION(igraph_heap, empty)(TYPE(igraph_heap)* h); DECLDIR int FUNCTION(igraph_heap, push)(TYPE(igraph_heap)* h, BASE elem); DECLDIR BASE FUNCTION(igraph_heap, top)(TYPE(igraph_heap)* h); DECLDIR BASE FUNCTION(igraph_heap, delete_top)(TYPE(igraph_heap)* h); DECLDIR long int FUNCTION(igraph_heap, size)(TYPE(igraph_heap)* h); DECLDIR int FUNCTION(igraph_heap, reserve)(TYPE(igraph_heap)* h, long int size); void FUNCTION(igraph_heap, i_build)(BASE* arr, long int size, long int head); void FUNCTION(igraph_heap, i_shift_up)(BASE* arr, long int size, long int elem); void FUNCTION(igraph_heap, i_sink)(BASE* arr, long int size, long int head); void FUNCTION(igraph_heap, i_switch)(BASE* arr, long int e1, long int e2); python-igraph-0.8.0/vendor/source/igraph/include/igraph_graphlets.h0000644000076500000240000000345213614300625025732 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2013 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_GRAPHLETS_H #define IGRAPH_GRAPHLETS_H #include "igraph_decls.h" #include "igraph_datatype.h" #include "igraph_vector_ptr.h" #include "igraph_interface.h" __BEGIN_DECLS DECLDIR int igraph_graphlets_candidate_basis(const igraph_t *graph, const igraph_vector_t *weights, igraph_vector_ptr_t *cliques, igraph_vector_t *thresholds); DECLDIR int igraph_graphlets_project(const igraph_t *graph, const igraph_vector_t *weights, const igraph_vector_ptr_t *cliques, igraph_vector_t *Mu, igraph_bool_t startMu, int niter); DECLDIR int igraph_graphlets(const igraph_t *graph, const igraph_vector_t *weights, igraph_vector_ptr_t *cliques, igraph_vector_t *Mu, int niter); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_cliques.h0000644000076500000240000001162013614300625025402 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_CLIQUES_H #define IGRAPH_CLIQUES_H #include "igraph_decls.h" #include "igraph_types.h" #include "igraph_datatype.h" #include "igraph_vector_ptr.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* Cliques, maximal independent vertex sets */ /* -------------------------------------------------- */ DECLDIR int igraph_maximal_cliques(const igraph_t *graph, igraph_vector_ptr_t *res, igraph_integer_t min_size, igraph_integer_t max_size); DECLDIR int igraph_maximal_cliques_file(const igraph_t *graph, FILE *outfile, igraph_integer_t min_size, igraph_integer_t max_size); DECLDIR int igraph_maximal_cliques_count(const igraph_t *graph, igraph_integer_t *res, igraph_integer_t min_size, igraph_integer_t max_size); DECLDIR int igraph_maximal_cliques_subset(const igraph_t *graph, igraph_vector_int_t *subset, igraph_vector_ptr_t *res, igraph_integer_t *no, FILE *outfile, igraph_integer_t min_size, igraph_integer_t max_size); DECLDIR int igraph_maximal_cliques_hist(const igraph_t *graph, igraph_vector_t *hist, igraph_integer_t min_size, igraph_integer_t max_size); DECLDIR int igraph_cliques(const igraph_t *graph, igraph_vector_ptr_t *res, igraph_integer_t min_size, igraph_integer_t max_size); DECLDIR int igraph_clique_size_hist(const igraph_t *graph, igraph_vector_t *hist, igraph_integer_t min_size, igraph_integer_t max_size); DECLDIR int igraph_largest_cliques(const igraph_t *graph, igraph_vector_ptr_t *cliques); DECLDIR int igraph_clique_number(const igraph_t *graph, igraph_integer_t *no); DECLDIR int igraph_weighted_cliques(const igraph_t *graph, const igraph_vector_t *vertex_weights, igraph_vector_ptr_t *res, igraph_real_t min_weight, igraph_real_t max_weight, igraph_bool_t maximal); DECLDIR int igraph_largest_weighted_cliques(const igraph_t *graph, const igraph_vector_t *vertex_weights, igraph_vector_ptr_t *res); DECLDIR int igraph_weighted_clique_number(const igraph_t *graph, const igraph_vector_t *vertex_weights, igraph_real_t *res); DECLDIR int igraph_independent_vertex_sets(const igraph_t *graph, igraph_vector_ptr_t *res, igraph_integer_t min_size, igraph_integer_t max_size); DECLDIR int igraph_largest_independent_vertex_sets(const igraph_t *graph, igraph_vector_ptr_t *res); DECLDIR int igraph_maximal_independent_vertex_sets(const igraph_t *graph, igraph_vector_ptr_t *res); DECLDIR int igraph_independence_number(const igraph_t *graph, igraph_integer_t *no); /** * \typedef igraph_clique_handler_t * \brief Type of clique handler functions * * Callback type, called when a clique was found. * * See the details at the documentation of \ref * igraph_cliques_callback(). * * \param clique The current clique. Destroying and freeing * this vector is left to the user. * Use \ref igraph_vector_destroy() and \ref igraph_free() * to do this. * \param arg This extra argument was passed to \ref * igraph_cliques_callback() when it was called. * \return Boolean, whether to continue with the clique search. */ typedef igraph_bool_t igraph_clique_handler_t(igraph_vector_t *clique, void *arg); DECLDIR int igraph_cliques_callback(const igraph_t *graph, igraph_integer_t min_size, igraph_integer_t max_size, igraph_clique_handler_t *cliquehandler_fn, void *arg); DECLDIR int igraph_maximal_cliques_callback(const igraph_t *graph, igraph_clique_handler_t *cliquehandler_fn, void *arg, igraph_integer_t min_size, igraph_integer_t max_size); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_vector.h0000644000076500000240000001242313614300625025241 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_VECTOR_H #define IGRAPH_VECTOR_H #include "igraph_decls.h" #include "igraph_types.h" #include "igraph_complex.h" #ifdef HAVE_STDINT_H #include #else #if defined(HAVE_SYS_INT_TYPES_H) && HAVE_SYS_INT_TYPES_H #include /* for Solaris */ #endif #endif __BEGIN_DECLS /* -------------------------------------------------- */ /* Flexible vector */ /* -------------------------------------------------- */ #define BASE_IGRAPH_REAL #include "igraph_pmt.h" #include "igraph_vector_type.h" #include "igraph_pmt_off.h" #undef BASE_IGRAPH_REAL #define BASE_FLOAT #include "igraph_pmt.h" #include "igraph_vector_type.h" #include "igraph_pmt_off.h" #undef BASE_FLOAT #define BASE_LONG #include "igraph_pmt.h" #include "igraph_vector_type.h" #include "igraph_pmt_off.h" #undef BASE_LONG #define BASE_CHAR #include "igraph_pmt.h" #include "igraph_vector_type.h" #include "igraph_pmt_off.h" #undef BASE_CHAR #define BASE_BOOL #include "igraph_pmt.h" #include "igraph_vector_type.h" #include "igraph_pmt_off.h" #undef BASE_BOOL #define BASE_INT #include "igraph_pmt.h" #include "igraph_vector_type.h" #include "igraph_pmt_off.h" #undef BASE_INT #define BASE_COMPLEX #include "igraph_pmt.h" #include "igraph_vector_type.h" #include "igraph_pmt_off.h" #undef BASE_COMPLEX #define BASE_IGRAPH_REAL #include "igraph_pmt.h" #include "igraph_vector_pmt.h" #include "igraph_pmt_off.h" #undef BASE_IGRAPH_REAL #define BASE_FLOAT #include "igraph_pmt.h" #include "igraph_vector_pmt.h" #include "igraph_pmt_off.h" #undef BASE_FLOAT #define BASE_LONG #include "igraph_pmt.h" #include "igraph_vector_pmt.h" #include "igraph_pmt_off.h" #undef BASE_LONG #define BASE_CHAR #include "igraph_pmt.h" #include "igraph_vector_pmt.h" #include "igraph_pmt_off.h" #undef BASE_CHAR #define BASE_BOOL #include "igraph_pmt.h" #include "igraph_vector_pmt.h" #include "igraph_pmt_off.h" #undef BASE_BOOL #define BASE_INT #include "igraph_pmt.h" #include "igraph_vector_pmt.h" #include "igraph_pmt_off.h" #undef BASE_INT #define BASE_COMPLEX #include "igraph_pmt.h" #include "igraph_vector_pmt.h" #include "igraph_pmt_off.h" #undef BASE_COMPLEX /* -------------------------------------------------- */ /* Helper macros */ /* -------------------------------------------------- */ #ifndef IGRAPH_VECTOR_NULL #define IGRAPH_VECTOR_NULL { 0,0,0 } #endif #ifndef IGRAPH_VECTOR_INIT_FINALLY #define IGRAPH_VECTOR_INIT_FINALLY(v, size) \ do { IGRAPH_CHECK(igraph_vector_init(v, size)); \ IGRAPH_FINALLY(igraph_vector_destroy, v); } while (0) #endif #ifndef IGRAPH_VECTOR_BOOL_INIT_FINALLY #define IGRAPH_VECTOR_BOOL_INIT_FINALLY(v, size) \ do { IGRAPH_CHECK(igraph_vector_bool_init(v, size)); \ IGRAPH_FINALLY(igraph_vector_bool_destroy, v); } while (0) #endif #ifndef IGRAPH_VECTOR_INT_INIT_FINALLY #define IGRAPH_VECTOR_INT_INIT_FINALLY(v, size) \ do { IGRAPH_CHECK(igraph_vector_int_init(v, size)); \ IGRAPH_FINALLY(igraph_vector_int_destroy, v); } while (0) #endif #ifndef IGRAPH_VECTOR_LONG_INIT_FINALLY #define IGRAPH_VECTOR_LONG_INIT_FINALLY(v, size) \ do { IGRAPH_CHECK(igraph_vector_long_init(v, size)); \ IGRAPH_FINALLY(igraph_vector_long_destroy, v); } while (0) #endif /* -------------------------------------------------- */ /* Type-specific vector functions */ /* -------------------------------------------------- */ DECLDIR int igraph_vector_floor(const igraph_vector_t *from, igraph_vector_long_t *to); DECLDIR int igraph_vector_round(const igraph_vector_t *from, igraph_vector_long_t *to); DECLDIR igraph_bool_t igraph_vector_e_tol(const igraph_vector_t *lhs, const igraph_vector_t *rhs, igraph_real_t tol); DECLDIR int igraph_vector_zapsmall(igraph_vector_t *v, igraph_real_t tol); /* These are for internal use only */ int igraph_vector_order(const igraph_vector_t* v, const igraph_vector_t *v2, igraph_vector_t* res, igraph_real_t maxval); int igraph_vector_order1(const igraph_vector_t* v, igraph_vector_t* res, igraph_real_t maxval); int igraph_vector_order1_int(const igraph_vector_t* v, igraph_vector_int_t* res, igraph_real_t maxval); int igraph_vector_order2(igraph_vector_t *v); int igraph_vector_rank(const igraph_vector_t *v, igraph_vector_t *res, long int nodes); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph.h0000644000076500000240000000547013614300625023663 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2003-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_H #define IGRAPH_H #ifndef _GNU_SOURCE #define _GNU_SOURCE 1 #endif #include "igraph_version.h" #include "igraph_memory.h" #include "igraph_error.h" #include "igraph_random.h" #include "igraph_progress.h" #include "igraph_statusbar.h" #include "igraph_types.h" #include "igraph_complex.h" #include "igraph_vector.h" #include "igraph_matrix.h" #include "igraph_array.h" #include "igraph_dqueue.h" #include "igraph_stack.h" #include "igraph_heap.h" #include "igraph_psumtree.h" #include "igraph_strvector.h" #include "igraph_vector_ptr.h" #include "igraph_spmatrix.h" #include "igraph_sparsemat.h" #include "igraph_qsort.h" #include "igraph_constants.h" #include "igraph_datatype.h" #include "igraph_iterators.h" #include "igraph_interface.h" #include "igraph_constructors.h" #include "igraph_games.h" #include "igraph_microscopic_update.h" #include "igraph_centrality.h" #include "igraph_paths.h" #include "igraph_components.h" #include "igraph_structural.h" #include "igraph_transitivity.h" #include "igraph_neighborhood.h" #include "igraph_topology.h" #include "igraph_bipartite.h" #include "igraph_cliques.h" #include "igraph_layout.h" #include "igraph_visitor.h" #include "igraph_community.h" #include "igraph_conversion.h" #include "igraph_foreign.h" #include "igraph_motifs.h" #include "igraph_operators.h" #include "igraph_flow.h" #include "igraph_nongraph.h" #include "igraph_cocitation.h" #include "igraph_adjlist.h" #include "igraph_attributes.h" #include "igraph_blas.h" #include "igraph_lapack.h" #include "igraph_arpack.h" #include "igraph_mixing.h" #include "igraph_separators.h" #include "igraph_cohesive_blocks.h" #include "igraph_eigen.h" #include "igraph_hrg.h" #include "igraph_threading.h" #include "igraph_interrupt.h" #include "igraph_scg.h" #include "igraph_matching.h" #include "igraph_embedding.h" #include "igraph_scan.h" #include "igraph_graphlets.h" #include "igraph_epidemics.h" #include "igraph_lsap.h" #include "igraph_coloring.h" #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_spmatrix.h0000644000076500000240000001257413614300625025615 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_SPMATRIX_H #define IGRAPH_SPMATRIX_H #include "igraph_decls.h" #include "igraph_vector.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* Sparse matrix */ /* -------------------------------------------------- */ /** * \section about_igraph_spmatrix_t_objects About \type igraph_spmatrix_t objects * * The \type igraph_spmatrix_t type stores a sparse matrix with the * assumption that the number of nonzero elements in the matrix scales * linearly with the row or column count of the matrix (so most of the * elements are zero). Of course it can store an arbitrary real matrix, * but if most of the elements are nonzero, one should use \type igraph_matrix_t * instead. * * The elements are stored in column compressed format, so the elements * in the same column are stored adjacent in the computer's memory. The storage * requirement for a sparse matrix is O(n) where n is the number of nonzero * elements. Actually it can be a bit larger, see the documentation of * the vector type for an explanation. */ typedef struct s_spmatrix { igraph_vector_t ridx, cidx, data; long int nrow, ncol; } igraph_spmatrix_t; #define IGRAPH_SPMATRIX_INIT_FINALLY(m, nr, nc) \ do { IGRAPH_CHECK(igraph_spmatrix_init(m, nr, nc)); \ IGRAPH_FINALLY(igraph_spmatrix_destroy, m); } while (0) DECLDIR int igraph_spmatrix_init(igraph_spmatrix_t *m, long int nrow, long int ncol); DECLDIR void igraph_spmatrix_destroy(igraph_spmatrix_t *m); DECLDIR int igraph_spmatrix_resize(igraph_spmatrix_t *m, long int nrow, long int ncol); DECLDIR igraph_real_t igraph_spmatrix_e(const igraph_spmatrix_t *m, long int row, long int col); DECLDIR int igraph_spmatrix_set(igraph_spmatrix_t *m, long int row, long int col, igraph_real_t value); DECLDIR int igraph_spmatrix_add_e(igraph_spmatrix_t *m, long int row, long int col, igraph_real_t value); DECLDIR int igraph_spmatrix_add_col_values(igraph_spmatrix_t *m, long int to, long int from); DECLDIR long int igraph_spmatrix_count_nonzero(const igraph_spmatrix_t *m); DECLDIR long int igraph_spmatrix_size(const igraph_spmatrix_t *m); DECLDIR long int igraph_spmatrix_nrow(const igraph_spmatrix_t *m); DECLDIR long int igraph_spmatrix_ncol(const igraph_spmatrix_t *m); DECLDIR int igraph_spmatrix_copy_to(const igraph_spmatrix_t *m, igraph_real_t *to); DECLDIR int igraph_spmatrix_null(igraph_spmatrix_t *m); DECLDIR int igraph_spmatrix_add_cols(igraph_spmatrix_t *m, long int n); DECLDIR int igraph_spmatrix_add_rows(igraph_spmatrix_t *m, long int n); DECLDIR int igraph_spmatrix_clear_col(igraph_spmatrix_t *m, long int col); DECLDIR int igraph_spmatrix_clear_row(igraph_spmatrix_t *m, long int row); DECLDIR int igraph_spmatrix_copy(igraph_spmatrix_t *to, const igraph_spmatrix_t *from); DECLDIR igraph_real_t igraph_spmatrix_max_nonzero(const igraph_spmatrix_t *m, igraph_real_t *ridx, igraph_real_t *cidx); DECLDIR igraph_real_t igraph_spmatrix_max(const igraph_spmatrix_t *m, igraph_real_t *ridx, igraph_real_t *cidx); DECLDIR void igraph_spmatrix_scale(igraph_spmatrix_t *m, igraph_real_t by); DECLDIR int igraph_spmatrix_colsums(const igraph_spmatrix_t *m, igraph_vector_t *res); DECLDIR int igraph_spmatrix_rowsums(const igraph_spmatrix_t *m, igraph_vector_t *res); DECLDIR int igraph_spmatrix_print(const igraph_spmatrix_t *matrix); DECLDIR int igraph_spmatrix_fprint(const igraph_spmatrix_t *matrix, FILE* file); DECLDIR int igraph_i_spmatrix_get_col_nonzero_indices(const igraph_spmatrix_t *m, igraph_vector_t *res, long int col); DECLDIR int igraph_i_spmatrix_clear_row_fast(igraph_spmatrix_t *m, long int row); DECLDIR int igraph_i_spmatrix_cleanup(igraph_spmatrix_t *m); typedef struct s_spmatrix_iter { const igraph_spmatrix_t *m; /* pointer to the matrix we are iterating over */ long int pos; /* internal index into the data vector */ long int ri; /* row index */ long int ci; /* column index */ igraph_real_t value; /* value at the given cell */ } igraph_spmatrix_iter_t; DECLDIR int igraph_spmatrix_iter_create(igraph_spmatrix_iter_t *mit, const igraph_spmatrix_t *m); DECLDIR int igraph_spmatrix_iter_reset(igraph_spmatrix_iter_t *mit); DECLDIR int igraph_spmatrix_iter_next(igraph_spmatrix_iter_t *mit); DECLDIR igraph_bool_t igraph_spmatrix_iter_end(igraph_spmatrix_iter_t *mit); DECLDIR void igraph_spmatrix_iter_destroy(igraph_spmatrix_iter_t *mit); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_microscopic_update.h0000644000076500000240000000445613614300625027622 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* Microscopic update rules for dealing with agent-level strategy revision. Copyright (C) 2011 Minh Van Nguyen This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_MICROSCOPIC_UPDATE_H #define IGRAPH_MICROSCOPIC_UPDATE_H #include "igraph_decls.h" #include "igraph_constants.h" #include "igraph_datatype.h" #include "igraph_iterators.h" #include "igraph_types.h" #include "igraph_vector.h" __BEGIN_DECLS DECLDIR int igraph_deterministic_optimal_imitation(const igraph_t *graph, igraph_integer_t vid, igraph_optimal_t optimality, const igraph_vector_t *quantities, igraph_vector_t *strategies, igraph_neimode_t mode); DECLDIR int igraph_moran_process(const igraph_t *graph, const igraph_vector_t *weights, igraph_vector_t *quantities, igraph_vector_t *strategies, igraph_neimode_t mode); DECLDIR int igraph_roulette_wheel_imitation(const igraph_t *graph, igraph_integer_t vid, igraph_bool_t islocal, const igraph_vector_t *quantities, igraph_vector_t *strategies, igraph_neimode_t mode); DECLDIR int igraph_stochastic_imitation(const igraph_t *graph, igraph_integer_t vid, igraph_imitate_algorithm_t algo, const igraph_vector_t *quantities, igraph_vector_t *strategies, igraph_neimode_t mode); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_components.h0000644000076500000240000000456413614300625026133 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_COMPONENTS_H #define IGRAPH_COMPONENTS_H #include "igraph_decls.h" #include "igraph_constants.h" #include "igraph_types.h" #include "igraph_vector.h" #include "igraph_vector_ptr.h" #include "igraph_datatype.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* Components */ /* -------------------------------------------------- */ DECLDIR int igraph_clusters(const igraph_t *graph, igraph_vector_t *membership, igraph_vector_t *csize, igraph_integer_t *no, igraph_connectedness_t mode); DECLDIR int igraph_is_connected(const igraph_t *graph, igraph_bool_t *res, igraph_connectedness_t mode); DECLDIR void igraph_decompose_destroy(igraph_vector_ptr_t *complist); DECLDIR int igraph_decompose(const igraph_t *graph, igraph_vector_ptr_t *components, igraph_connectedness_t mode, long int maxcompno, long int minelements); DECLDIR int igraph_articulation_points(const igraph_t *graph, igraph_vector_t *res); DECLDIR int igraph_biconnected_components(const igraph_t *graph, igraph_integer_t *no, igraph_vector_ptr_t *tree_edges, igraph_vector_ptr_t *component_edges, igraph_vector_ptr_t *components, igraph_vector_t *articulation_points); DECLDIR int igraph_bridges(const igraph_t *graph, igraph_vector_t *bridges); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_lsap.h0000644000076500000240000000041413614300625024673 0ustar tamasstaff00000000000000 #ifndef IGRAPH_LSAP #define IGRAPH_LSAP #include "igraph_types.h" #include "igraph_vector.h" #include "igraph_matrix.h" __BEGIN_DECLS int igraph_solve_lsap(igraph_matrix_t *c, igraph_integer_t n, igraph_vector_int_t *p); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_random.h0000644000076500000240000001136513614300625025223 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2003-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef REST_RANDOM_H #define REST_RANDOM_H #include "igraph_decls.h" __BEGIN_DECLS #include #include #include "igraph_types.h" #include "igraph_vector.h" /* The new RNG interface is (somewhat) modelled based on the GSL */ typedef struct igraph_rng_type_t { const char *name; unsigned long int min; unsigned long int max; int (*init)(void **state); void (*destroy)(void *state); int (*seed)(void *state, unsigned long int seed); unsigned long int (*get)(void *state); igraph_real_t (*get_real)(void *state); igraph_real_t (*get_norm)(void *state); igraph_real_t (*get_geom)(void *state, igraph_real_t p); igraph_real_t (*get_binom)(void *state, long int n, igraph_real_t p); igraph_real_t (*get_exp)(void *state, igraph_real_t rate); igraph_real_t (*get_gamma)(void *state, igraph_real_t shape, igraph_real_t scale); } igraph_rng_type_t; typedef struct igraph_rng_t { const igraph_rng_type_t *type; void *state; int def; } igraph_rng_t; /* --------------------------------- */ DECLDIR int igraph_rng_init(igraph_rng_t *rng, const igraph_rng_type_t *type); DECLDIR void igraph_rng_destroy(igraph_rng_t *rng); DECLDIR int igraph_rng_seed(igraph_rng_t *rng, unsigned long int seed); DECLDIR unsigned long int igraph_rng_max(igraph_rng_t *rng); DECLDIR unsigned long int igraph_rng_min(igraph_rng_t *rng); DECLDIR const char *igraph_rng_name(igraph_rng_t *rng); DECLDIR long int igraph_rng_get_integer(igraph_rng_t *rng, long int l, long int h); DECLDIR igraph_real_t igraph_rng_get_normal(igraph_rng_t *rng, igraph_real_t m, igraph_real_t s); DECLDIR igraph_real_t igraph_rng_get_unif(igraph_rng_t *rng, igraph_real_t l, igraph_real_t h); DECLDIR igraph_real_t igraph_rng_get_unif01(igraph_rng_t *rng); DECLDIR igraph_real_t igraph_rng_get_geom(igraph_rng_t *rng, igraph_real_t p); DECLDIR igraph_real_t igraph_rng_get_binom(igraph_rng_t *rng, long int n, igraph_real_t p); DECLDIR igraph_real_t igraph_rng_get_exp(igraph_rng_t *rng, igraph_real_t rate); DECLDIR unsigned long int igraph_rng_get_int31(igraph_rng_t *rng); DECLDIR igraph_real_t igraph_rng_get_gamma(igraph_rng_t *rng, igraph_real_t shape, igraph_real_t scale); DECLDIR int igraph_rng_get_dirichlet(igraph_rng_t *rng, const igraph_vector_t *alpha, igraph_vector_t *result); /* --------------------------------- */ extern const igraph_rng_type_t igraph_rngtype_glibc2; extern const igraph_rng_type_t igraph_rngtype_rand; extern const igraph_rng_type_t igraph_rngtype_mt19937; DECLDIR igraph_rng_t *igraph_rng_default(void); DECLDIR void igraph_rng_set_default(igraph_rng_t *rng); /* --------------------------------- */ #ifdef USING_R void GetRNGstate(void); void PutRNGstate(void); #define RNG_BEGIN() GetRNGstate() #define RNG_END() PutRNGstate() double Rf_dnorm4(double x, double mu, double sigma, int give_log); #define igraph_dnorm Rf_dnorm4 #else #define RNG_BEGIN() if (igraph_rng_default()->def==1) { \ igraph_rng_seed(igraph_rng_default(), time(0)); \ igraph_rng_default()->def=2; \ } #define RNG_END() /* do nothing */ DECLDIR double igraph_dnorm(double x, double mu, double sigma, int give_log); #endif #define RNG_INTEGER(l,h) (igraph_rng_get_integer(igraph_rng_default(),(l),(h))) #define RNG_NORMAL(m,s) (igraph_rng_get_normal(igraph_rng_default(),(m),(s))) #define RNG_UNIF(l,h) (igraph_rng_get_unif(igraph_rng_default(),(l),(h))) #define RNG_UNIF01() (igraph_rng_get_unif01(igraph_rng_default())) #define RNG_GEOM(p) (igraph_rng_get_geom(igraph_rng_default(),(p))) #define RNG_BINOM(n,p) (igraph_rng_get_binom(igraph_rng_default(),(n),(p))) #define RNG_INT31() (igraph_rng_get_int31(igraph_rng_default())) __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_structural.h0000644000076500000240000001637313614300625026157 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_STRUCTURAL_H #define IGRAPH_STRUCTURAL_H #include "igraph_decls.h" #include "igraph_constants.h" #include "igraph_types.h" #include "igraph_vector.h" #include "igraph_matrix.h" #include "igraph_datatype.h" #include "igraph_iterators.h" #include "igraph_attributes.h" #include "igraph_sparsemat.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* Basic query functions */ /* -------------------------------------------------- */ DECLDIR int igraph_are_connected(const igraph_t *graph, igraph_integer_t v1, igraph_integer_t v2, igraph_bool_t *res); /* -------------------------------------------------- */ /* Structural properties */ /* -------------------------------------------------- */ DECLDIR int igraph_minimum_spanning_tree(const igraph_t *graph, igraph_vector_t *res, const igraph_vector_t *weights); DECLDIR int igraph_minimum_spanning_tree_unweighted(const igraph_t *graph, igraph_t *mst); DECLDIR int igraph_minimum_spanning_tree_prim(const igraph_t *graph, igraph_t *mst, const igraph_vector_t *weights); DECLDIR int igraph_random_spanning_tree(const igraph_t *graph, igraph_vector_t *res, igraph_integer_t vid); DECLDIR int igraph_subcomponent(const igraph_t *graph, igraph_vector_t *res, igraph_real_t vid, igraph_neimode_t mode); DECLDIR int igraph_rewire(igraph_t *graph, igraph_integer_t n, igraph_rewiring_t mode); DECLDIR int igraph_subgraph(const igraph_t *graph, igraph_t *res, const igraph_vs_t vids); DECLDIR int igraph_induced_subgraph_map(const igraph_t *graph, igraph_t *res, const igraph_vs_t vids, igraph_subgraph_implementation_t impl, igraph_vector_t *map, igraph_vector_t *invmap); DECLDIR int igraph_induced_subgraph(const igraph_t *graph, igraph_t *res, const igraph_vs_t vids, igraph_subgraph_implementation_t impl); DECLDIR int igraph_subgraph_edges(const igraph_t *graph, igraph_t *res, const igraph_es_t eids, igraph_bool_t delete_vertices); DECLDIR int igraph_simplify(igraph_t *graph, igraph_bool_t multiple, igraph_bool_t loops, const igraph_attribute_combination_t *edge_comb); DECLDIR int igraph_reciprocity(const igraph_t *graph, igraph_real_t *res, igraph_bool_t ignore_loops, igraph_reciprocity_t mode); DECLDIR int igraph_maxdegree(const igraph_t *graph, igraph_integer_t *res, igraph_vs_t vids, igraph_neimode_t mode, igraph_bool_t loops); DECLDIR int igraph_density(const igraph_t *graph, igraph_real_t *res, igraph_bool_t loops); DECLDIR int igraph_has_loop(const igraph_t *graph, igraph_bool_t *res); DECLDIR int igraph_is_loop(const igraph_t *graph, igraph_vector_bool_t *res, igraph_es_t es); DECLDIR int igraph_is_simple(const igraph_t *graph, igraph_bool_t *res); DECLDIR int igraph_has_multiple(const igraph_t *graph, igraph_bool_t *res); DECLDIR int igraph_is_multiple(const igraph_t *graph, igraph_vector_bool_t *res, igraph_es_t es); DECLDIR int igraph_count_multiple(const igraph_t *graph, igraph_vector_t *res, igraph_es_t es); DECLDIR int igraph_is_tree(const igraph_t *graph, igraph_bool_t *res, igraph_integer_t *root, igraph_neimode_t mode); DECLDIR int igraph_girth(const igraph_t *graph, igraph_integer_t *girth, igraph_vector_t *circle); DECLDIR int igraph_add_edge(igraph_t *graph, igraph_integer_t from, igraph_integer_t to); DECLDIR int igraph_unfold_tree(const igraph_t *graph, igraph_t *tree, igraph_neimode_t mode, const igraph_vector_t *roots, igraph_vector_t *vertex_index); DECLDIR int igraph_is_mutual(igraph_t *graph, igraph_vector_bool_t *res, igraph_es_t es); DECLDIR int igraph_maximum_cardinality_search(const igraph_t *graph, igraph_vector_t *alpha, igraph_vector_t *alpham1); DECLDIR int igraph_is_chordal(const igraph_t *graph, const igraph_vector_t *alpha, const igraph_vector_t *alpham1, igraph_bool_t *chordal, igraph_vector_t *fill_in, igraph_t *newgraph); DECLDIR int igraph_avg_nearest_neighbor_degree(const igraph_t *graph, igraph_vs_t vids, igraph_neimode_t mode, igraph_neimode_t neighbor_degree_mode, igraph_vector_t *knn, igraph_vector_t *knnk, const igraph_vector_t *weights); DECLDIR int igraph_contract_vertices(igraph_t *graph, const igraph_vector_t *mapping, const igraph_attribute_combination_t *vertex_comb); DECLDIR int igraph_feedback_arc_set(const igraph_t *graph, igraph_vector_t *result, const igraph_vector_t *weights, igraph_fas_algorithm_t algo); DECLDIR int igraph_diversity(igraph_t *graph, const igraph_vector_t *weights, igraph_vector_t *res, const igraph_vs_t vs); /* -------------------------------------------------- */ /* Spectral Properties */ /* -------------------------------------------------- */ DECLDIR int igraph_laplacian(const igraph_t *graph, igraph_matrix_t *res, igraph_sparsemat_t *sparseres, igraph_bool_t normalized, const igraph_vector_t *weights); /* -------------------------------------------------- */ /* Internal functions, may change any time */ /* -------------------------------------------------- */ int igraph_i_feedback_arc_set_undirected(const igraph_t *graph, igraph_vector_t *result, const igraph_vector_t *weights, igraph_vector_t *layering); int igraph_i_feedback_arc_set_eades(const igraph_t *graph, igraph_vector_t *result, const igraph_vector_t *weights, igraph_vector_t *layering); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_lapack.h0000644000076500000240000001104613614300625025172 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_LAPACK_H #define IGRAPH_LAPACK_H #include "igraph_vector.h" #include "igraph_matrix.h" #include "igraph_decls.h" __BEGIN_DECLS /** * \section about_lapack LAPACK interface in igraph * * * LAPACK is written in Fortran90 and provides routines for solving * systems of simultaneous linear equations, least-squares solutions * of linear systems of equations, eigenvalue problems, and singular * value problems. The associated matrix factorizations (LU, Cholesky, * QR, SVD, Schur, generalized Schur) are also provided, as are * related computations such as reordering of the Schur factorizations * and estimating condition numbers. Dense and banded matrices are * handled, but not general sparse matrices. In all areas, similar * functionality is provided for real and complex matrices, in both * single and double precision. * * * * igraph provides an interface to a very limited set of LAPACK * functions, using the regular igraph data structures. * * * * See more about LAPACK at http://www.netlib.org/lapack/ * */ DECLDIR int igraph_lapack_dgetrf(igraph_matrix_t *a, igraph_vector_int_t *ipiv, int *info); DECLDIR int igraph_lapack_dgetrs(igraph_bool_t transpose, const igraph_matrix_t *a, igraph_vector_int_t *ipiv, igraph_matrix_t *b); DECLDIR int igraph_lapack_dgesv(igraph_matrix_t *a, igraph_vector_int_t *ipiv, igraph_matrix_t *b, int *info); typedef enum { IGRAPH_LAPACK_DSYEV_ALL, IGRAPH_LAPACK_DSYEV_INTERVAL, IGRAPH_LAPACK_DSYEV_SELECT } igraph_lapack_dsyev_which_t; DECLDIR int igraph_lapack_dsyevr(const igraph_matrix_t *A, igraph_lapack_dsyev_which_t which, igraph_real_t vl, igraph_real_t vu, int vestimate, int il, int iu, igraph_real_t abstol, igraph_vector_t *values, igraph_matrix_t *vectors, igraph_vector_int_t *support); /* TODO: should we use complex vectors/matrices? */ DECLDIR int igraph_lapack_dgeev(const igraph_matrix_t *A, igraph_vector_t *valuesreal, igraph_vector_t *valuesimag, igraph_matrix_t *vectorsleft, igraph_matrix_t *vectorsright, int *info); typedef enum { IGRAPH_LAPACK_DGEEVX_BALANCE_NONE = 0, IGRAPH_LAPACK_DGEEVX_BALANCE_PERM, IGRAPH_LAPACK_DGEEVX_BALANCE_SCALE, IGRAPH_LAPACK_DGEEVX_BALANCE_BOTH } igraph_lapack_dgeevx_balance_t; DECLDIR int igraph_lapack_dgeevx(igraph_lapack_dgeevx_balance_t balance, const igraph_matrix_t *A, igraph_vector_t *valuesreal, igraph_vector_t *valuesimag, igraph_matrix_t *vectorsleft, igraph_matrix_t *vectorsright, int *ilo, int *ihi, igraph_vector_t *scale, igraph_real_t *abnrm, igraph_vector_t *rconde, igraph_vector_t *rcondv, int *info); DECLDIR int igraph_lapack_dgehrd(const igraph_matrix_t *A, int ilo, int ihi, igraph_matrix_t *result); DECLDIR int igraph_lapack_ddot(const igraph_vector_t *v1, const igraph_vector_t *v2, igraph_real_t *res); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_dqueue_pmt.h0000644000076500000240000000417213614300625026111 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ /** * Double ended queue data type. * \ingroup internal */ typedef struct TYPE(igraph_dqueue) { BASE *begin; BASE *end; BASE *stor_begin; BASE *stor_end; } TYPE(igraph_dqueue); DECLDIR int FUNCTION(igraph_dqueue, init) (TYPE(igraph_dqueue)* q, long int size); DECLDIR void FUNCTION(igraph_dqueue, destroy) (TYPE(igraph_dqueue)* q); DECLDIR igraph_bool_t FUNCTION(igraph_dqueue, empty) (const TYPE(igraph_dqueue)* q); DECLDIR void FUNCTION(igraph_dqueue, clear) (TYPE(igraph_dqueue)* q); DECLDIR igraph_bool_t FUNCTION(igraph_dqueue, full) (TYPE(igraph_dqueue)* q); DECLDIR long int FUNCTION(igraph_dqueue, size) (const TYPE(igraph_dqueue)* q); DECLDIR BASE FUNCTION(igraph_dqueue, pop) (TYPE(igraph_dqueue)* q); DECLDIR BASE FUNCTION(igraph_dqueue, pop_back)(TYPE(igraph_dqueue)* q); DECLDIR BASE FUNCTION(igraph_dqueue, head) (const TYPE(igraph_dqueue)* q); DECLDIR BASE FUNCTION(igraph_dqueue, back) (const TYPE(igraph_dqueue)* q); DECLDIR int FUNCTION(igraph_dqueue, push) (TYPE(igraph_dqueue)* q, BASE elem); int FUNCTION(igraph_dqueue, print)(const TYPE(igraph_dqueue)* q); int FUNCTION(igraph_dqueue, fprint)(const TYPE(igraph_dqueue)* q, FILE *file); DECLDIR BASE FUNCTION(igraph_dqueue, e)(const TYPE(igraph_dqueue) *q, long int idx); python-igraph-0.8.0/vendor/source/igraph/include/igraph_community.h0000644000076500000240000002530113614300625025762 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_COMMUNITY_H #define IGRAPH_COMMUNITY_H #include "igraph_decls.h" #include "igraph_constants.h" #include "igraph_datatype.h" #include "igraph_types.h" #include "igraph_arpack.h" #include "igraph_vector_ptr.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* K-Cores */ /* -------------------------------------------------- */ DECLDIR int igraph_coreness(const igraph_t *graph, igraph_vector_t *cores, igraph_neimode_t mode); /* -------------------------------------------------- */ /* Community Structure */ /* -------------------------------------------------- */ /* TODO: cut.community */ /* TODO: edge.type.matrix */ /* TODO: */ DECLDIR int igraph_community_optimal_modularity(const igraph_t *graph, igraph_real_t *modularity, igraph_vector_t *membership, const igraph_vector_t *weights); DECLDIR int igraph_community_spinglass(const igraph_t *graph, const igraph_vector_t *weights, igraph_real_t *modularity, igraph_real_t *temperature, igraph_vector_t *membership, igraph_vector_t *csize, igraph_integer_t spins, igraph_bool_t parupdate, igraph_real_t starttemp, igraph_real_t stoptemp, igraph_real_t coolfact, igraph_spincomm_update_t update_rule, igraph_real_t gamma, /* the rest is for the NegSpin implementation */ igraph_spinglass_implementation_t implementation, /* igraph_matrix_t *adhesion, */ /* igraph_matrix_t *normalised_adhesion, */ /* igraph_real_t *polarization, */ igraph_real_t lambda); DECLDIR int igraph_community_spinglass_single(const igraph_t *graph, const igraph_vector_t *weights, igraph_integer_t vertex, igraph_vector_t *community, igraph_real_t *cohesion, igraph_real_t *adhesion, igraph_integer_t *inner_links, igraph_integer_t *outer_links, igraph_integer_t spins, igraph_spincomm_update_t update_rule, igraph_real_t gamma); DECLDIR int igraph_community_walktrap(const igraph_t *graph, const igraph_vector_t *weights, int steps, igraph_matrix_t *merges, igraph_vector_t *modularity, igraph_vector_t *membership); DECLDIR int igraph_community_infomap(const igraph_t * graph, const igraph_vector_t *e_weights, const igraph_vector_t *v_weights, int nb_trials, igraph_vector_t *membership, igraph_real_t *codelength); DECLDIR int igraph_community_edge_betweenness(const igraph_t *graph, igraph_vector_t *result, igraph_vector_t *edge_betweenness, igraph_matrix_t *merges, igraph_vector_t *bridges, igraph_vector_t *modularity, igraph_vector_t *membership, igraph_bool_t directed, const igraph_vector_t *weights); DECLDIR int igraph_community_eb_get_merges(const igraph_t *graph, const igraph_vector_t *edges, const igraph_vector_t *weights, igraph_matrix_t *merges, igraph_vector_t *bridges, igraph_vector_t *modularity, igraph_vector_t *membership); DECLDIR int igraph_community_fastgreedy(const igraph_t *graph, const igraph_vector_t *weights, igraph_matrix_t *merges, igraph_vector_t *modularity, igraph_vector_t *membership); DECLDIR int igraph_community_to_membership(const igraph_matrix_t *merges, igraph_integer_t nodes, igraph_integer_t steps, igraph_vector_t *membership, igraph_vector_t *csize); DECLDIR int igraph_le_community_to_membership(const igraph_matrix_t *merges, igraph_integer_t steps, igraph_vector_t *membership, igraph_vector_t *csize); DECLDIR int igraph_modularity(const igraph_t *graph, const igraph_vector_t *membership, igraph_real_t *modularity, const igraph_vector_t *weights); DECLDIR int igraph_modularity_matrix(const igraph_t *graph, igraph_matrix_t *modmat, const igraph_vector_t *weights); DECLDIR int igraph_reindex_membership(igraph_vector_t *membership, igraph_vector_t *new_to_old, igraph_integer_t *nb_clusters); typedef enum { IGRAPH_LEVC_HIST_SPLIT = 1, IGRAPH_LEVC_HIST_FAILED, IGRAPH_LEVC_HIST_START_FULL, IGRAPH_LEVC_HIST_START_GIVEN } igraph_leading_eigenvector_community_history_t; /** * \typedef igraph_community_leading_eigenvector_callback_t * Callback for the leading eigenvector community finding method. * * The leading eigenvector community finding implementation in igraph * is able to call a callback function, after each eigenvalue * calculation. This callback function must be of \c * igraph_community_leading_eigenvector_callback_t type. * The following arguments are passed to the callback: * \param membership The actual membership vector, before recording * the potential change implied by the newly found eigenvalue. * \param comm The id of the community that the algorithm tried to * split in the last iteration. The community ids are indexed from * zero here! * \param eigenvalue The eigenvalue the algorithm has just found. * \param eigenvector The eigenvector corresponding to the eigenvalue * the algorithm just found. * \param arpack_multiplier A function that was passed to \ref * igraph_arpack_rssolve() to solve the last eigenproblem. * \param arpack_extra The extra argument that was passed to the * ARPACK solver. * \param extra Extra argument that as passed to \ref * igraph_community_leading_eigenvector(). * * \sa \ref igraph_community_leading_eigenvector(), \ref * igraph_arpack_function_t, \ref igraph_arpack_rssolve(). */ typedef int igraph_community_leading_eigenvector_callback_t( const igraph_vector_t *membership, long int comm, igraph_real_t eigenvalue, const igraph_vector_t *eigenvector, igraph_arpack_function_t *arpack_multiplier, void *arpack_extra, void *extra); DECLDIR int igraph_community_leading_eigenvector(const igraph_t *graph, const igraph_vector_t *weights, igraph_matrix_t *merges, igraph_vector_t *membership, igraph_integer_t steps, igraph_arpack_options_t *options, igraph_real_t *modularity, igraph_bool_t start, igraph_vector_t *eigenvalues, igraph_vector_ptr_t *eigenvectors, igraph_vector_t *history, igraph_community_leading_eigenvector_callback_t *callback, void *callback_extra); DECLDIR int igraph_community_fluid_communities(const igraph_t *graph, igraph_integer_t no_of_communities, igraph_vector_t *membership, igraph_real_t *modularity); DECLDIR int igraph_community_label_propagation(const igraph_t *graph, igraph_vector_t *membership, const igraph_vector_t *weights, const igraph_vector_t *initial, igraph_vector_bool_t *fixed, igraph_real_t *modularity); DECLDIR int igraph_community_multilevel(const igraph_t *graph, const igraph_vector_t *weights, igraph_vector_t *membership, igraph_matrix_t *memberships, igraph_vector_t *modularity); DECLDIR int igraph_community_leiden(const igraph_t *graph, const igraph_vector_t *edge_weights, const igraph_vector_t *node_weights, const igraph_real_t resolution_parameter, const igraph_real_t beta, const igraph_bool_t start, igraph_vector_t *membership, igraph_integer_t *nb_clusters, igraph_real_t *quality); /* -------------------------------------------------- */ /* Community Structure Comparison */ /* -------------------------------------------------- */ DECLDIR int igraph_compare_communities(const igraph_vector_t *comm1, const igraph_vector_t *comm2, igraph_real_t* result, igraph_community_comparison_t method); DECLDIR int igraph_split_join_distance(const igraph_vector_t *comm1, const igraph_vector_t *comm2, igraph_integer_t* distance12, igraph_integer_t* distance21); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/include/igraph_transitivity.h0000644000076500000240000000456113614300625026514 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_TRANSITIVITY_H #define IGRAPH_TRANSITIVITY_H #include "igraph_decls.h" #include "igraph_datatype.h" #include "igraph_constants.h" #include "igraph_iterators.h" __BEGIN_DECLS DECLDIR int igraph_transitivity_undirected(const igraph_t *graph, igraph_real_t *res, igraph_transitivity_mode_t mode); DECLDIR int igraph_transitivity_local_undirected(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, igraph_transitivity_mode_t mode); DECLDIR int igraph_transitivity_local_undirected1(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, igraph_transitivity_mode_t mode); DECLDIR int igraph_transitivity_local_undirected2(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, igraph_transitivity_mode_t mode); DECLDIR int igraph_transitivity_local_undirected4(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, igraph_transitivity_mode_t mode); DECLDIR int igraph_transitivity_avglocal_undirected(const igraph_t *graph, igraph_real_t *res, igraph_transitivity_mode_t mode); DECLDIR int igraph_transitivity_barrat(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, const igraph_vector_t *weights, const igraph_transitivity_mode_t mode); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/tests/0000755000076500000240000000000013617375001021754 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/tests/iterators.at0000644000076500000240000000424313524616145024325 0ustar tamasstaff00000000000000# Check vertex and edge sequences (=iterators) # Test suite for the IGraph library. # Copyright (C) 2005-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([[Iterators aka vertex and edge sequences]]) AT_SETUP([Vertices in a vector (igraph_vs_vector): ]) AT_KEYWORDS([iterator vector igraph_vs_vector igraph_vs_vectorview]) AT_COMPILE_CHECK([simple/igraph_vs_vector.c], [simple/igraph_vs_vector.out]) AT_CLEANUP AT_SETUP([Non-adjacent vertices (igraph_vs_nonadj): ]) AT_KEYWORDS([iterator igraph_vs_nonadj]) AT_COMPILE_CHECK([simple/igraph_vs_nonadj.c], [simple/igraph_vs_nonadj.out]) AT_CLEANUP AT_SETUP([Sequence (igraph_vs_seq): ]) AT_KEYWORDS([iterator igraph_vs_seq seq sequence]) AT_COMPILE_CHECK([simple/igraph_vs_seq.c], [simple/igraph_vs_seq.out]) AT_CLEANUP #AT_SETUP([Adjacent edges (igraph_es_adj): ]) #AT_KEYWORDS([iterator adjacent igraph_es_adj]) #AT_COMPILE_CHECK([simple/igraph_es_adj.c], [simple/igraph_es_adj.out]) #AT_CLEANUP #AT_SETUP([Edges connecting two vertex sets (igraph_es_fromto): ]) #AT_KEYWORDS([iterator igraph_es_fromto]) #AT_COMPILE_CHECK([simple/igraph_es_fromto.c], [simple/igraph_es_fromto.out]) #AT_CLEANUP AT_SETUP([Edges given by end points (igraph_es_pairs): ]) AT_KEYWORDS([iterator igraph_es_pairs]) AT_COMPILE_CHECK([simple/igraph_es_pairs.c]) AT_CLEANUP AT_SETUP([Edges in a path (igraph_es_path): ]) AT_KEYWORDS([iterator, igraph_es_path]) AT_COMPILE_CHECK([simple/igraph_es_path.c]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/structure_generators.at0000644000076500000240000001170413524616145026602 0ustar tamasstaff00000000000000# Check graph generators # Test suite for the IGraph library. # Copyright (C) 2005-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([[Structure generators]]) AT_SETUP([Simple graph creation (igraph_create): ]) AT_KEYWORDS([igraph_create]) AT_COMPILE_CHECK([simple/igraph_create.c]) AT_CLEANUP AT_SETUP([Barabasi-Albert model (igraph_barabasi_game):]) AT_KEYWORDS([barabasi barabasi-albert igraph_barabasi_game]) AT_COMPILE_CHECK([simple/igraph_barabasi_game.c]) AT_CLEANUP AT_SETUP([More Barabasi-Albert model (igraph_barabasi_game):]) AT_KEYWORDS([barabasi barabasi-albert igraph_barabasi_game]) AT_COMPILE_CHECK([simple/igraph_barabasi_game2.c]) AT_CLEANUP AT_SETUP([Erdos-Renyi model (igraph_erdos_renyi_game):]) AT_KEYWORDS([erdos renyi erdos-renyi igraph_erdos_renyi_game]) AT_COMPILE_CHECK([simple/igraph_erdos_renyi_game.c]) AT_CLEANUP AT_SETUP([Degree sequence (igraph_degree_sequence_game):]) AT_KEYWORDS([degree sequence igraph_degree_sequence_game]) AT_COMPILE_CHECK([simple/igraph_degree_sequence_game.c], [simple/igraph_degree_sequence_game.out]) AT_CLEANUP AT_SETUP([k-regular graphs (igraph_k_regular_game):]) AT_KEYWORDS([regular k-regular igraph_k_regular_game]) AT_COMPILE_CHECK([simple/igraph_k_regular_game.c], [simple/igraph_k_regular_game.out]) AT_CLEANUP AT_SETUP([Growing random (igraph_growing_random_game):]) AT_KEYWORDS([growing random game igraph_growing_random_game]) AT_COMPILE_CHECK([simple/igraph_growing_random_game.c]) AT_CLEANUP AT_SETUP([Preference model (igraph_preference_game):]) AT_KEYWORDS([preference game igraph_preference_game igraph_asymmetric_preference_game]) AT_COMPILE_CHECK([simple/igraph_preference_game.c]) AT_CLEANUP AT_SETUP([From adjacency matrix (igraph_adjacency):]) AT_KEYWORDS([adjacency matrix igraph_adjacency]) AT_COMPILE_CHECK([simple/igraph_adjacency.c]) AT_CLEANUP AT_SETUP([From weighted adjacency matrix (igraph_weighted_adjacency):]) AT_KEYWORDS([weighted adjacency matrix igraph_weighted_adjacency]) AT_COMPILE_CHECK([simple/igraph_weighted_adjacency.c], [simple/igraph_weighted_adjacency.out]) AT_CLEANUP AT_SETUP([Star graph (igraph_star):]) AT_KEYWORDS([star igraph_star]) AT_COMPILE_CHECK([simple/igraph_star.c]) AT_CLEANUP AT_SETUP([Lattice graph (igraph_lattice):]) AT_KEYWORDS([lattice igraph_lattice]) AT_COMPILE_CHECK([simple/igraph_lattice.c]) AT_CLEANUP AT_SETUP([Ring graph (igraph_ring):]) AT_KEYWORDS([ring igraph_ring]) AT_COMPILE_CHECK([simple/igraph_ring.c]) AT_CLEANUP AT_SETUP([Tree graph (igraph_tree):]) AT_KEYWORDS([tree igraph_tree]) AT_COMPILE_CHECK([simple/igraph_tree.c], [simple/igraph_tree.out]) AT_CLEANUP AT_SETUP([Tree graph 2 (igraph_tree):]) AT_KEYWORDS([tree igraph_tree]) AT_COMPILE_CHECK([tests/tree.c], [tests/tree.out]) AT_CLEANUP AT_SETUP([Tree graph from Prufer sequence (igraph_from_prufer):]) AT_KEYWORDS([tree igraph_from_prufer]) AT_COMPILE_CHECK([simple/igraph_from_prufer.c], [simple/igraph_from_prufer.out]) AT_CLEANUP AT_SETUP([Full graph (igraph_full):]) AT_KEYWORDS([full igraph_full]) AT_COMPILE_CHECK([simple/igraph_full.c]) AT_CLEANUP AT_SETUP([Graph atlas (igraph_atlas):]) AT_KEYWORDS([atlas igraph_atlas]) AT_COMPILE_CHECK([simple/igraph_atlas.c], [simple/igraph_atlas.out]) AT_CLEANUP AT_SETUP([Small graph (igraph_small):]) AT_KEYWORDS([graph constructor small igraph_small]) AT_COMPILE_CHECK([simple/igraph_small.c], [simple/igraph_small.out]) AT_CLEANUP AT_SETUP([Geomeric random graphs (igraph_grg_game):]) AT_KEYWORDS([graph GRG grg geometric random graph igraph_grg_game]) AT_COMPILE_CHECK([simple/igraph_grg_game.c]) AT_CLEANUP AT_SETUP([Graphs in LCF notation (igraph_lcf{,_vector}):]) AT_KEYWORDS([LCF graph constructor]) AT_COMPILE_CHECK([simple/igraph_lcf.c]) AT_CLEANUP AT_SETUP([Watts-Strogatz graphs (igraph_watts_strogatz_game):]) AT_KEYWORDS([small world small-world Watts Strogratz]) AT_COMPILE_CHECK([simple/watts_strogatz_game.c]) AT_CLEANUP AT_SETUP([Correlated random graphs (igraph_correlated_game):]) AT_KEYWORDS([correlated random graph]) AT_COMPILE_CHECK([simple/igraph_correlated_game.c]) AT_CLEANUP AT_SETUP([Realize a degree sequence (igraph_realize_degree_sequence):]) AT_KEYWORDS([degree sequence]) AT_COMPILE_CHECK([simple/igraph_realize_degree_sequence.c], [simple/igraph_realize_degree_sequence.out]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/topology.at0000644000076500000240000000442113524616145024163 0ustar tamasstaff00000000000000# Check graph topology related functions # Test suite for the IGraph library. # Copyright (C) 2005-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([[Graph topology]]) AT_SETUP([The isomorphism class of a subgraph (igraph_isolass_subgraph)]) AT_KEYWORDS([isomorph isomorphism class motif]) AT_COMPILE_CHECK([simple/topology.c], [simple/topology.out]) AT_CLEANUP AT_SETUP([The VF2 isomorphism algorithm]) AT_KEYWORDS([isomorph isomorphic VF2]) AT_COMPILE_CHECK([simple/igraph_isomorphic_vf2.c]) AT_CLEANUP AT_SETUP([The BLISS isomorphism algorithm]) AT_KEYWORDS([isomorph isomorphic BLISS]) AT_COMPILE_CHECK([simple/igraph_isomorphic_bliss.c]) AT_CLEANUP AT_SETUP([VF algorithm with compatibility functions]) AT_KEYWORDS([isomorph isomorphic VF2 compatibility]) AT_COMPILE_CHECK([simple/VF2-compat.c]) AT_CLEANUP AT_SETUP([LAD subgraph isomorphism algorithm]) AT_KEYWORDS([isomorph isomorphic subgraph isomorphism LAD]) AT_COMPILE_CHECK([simple/igraph_subisomorphic_lad.c], [simple/igraph_subisomorphic_lad.out]) AT_CLEANUP AT_SETUP([Additional isomorphism tests]) AT_KEYWORDS([isomorph isomorphic isomorphism BLISS VF2]) AT_COMPILE_CHECK([simple/isomorphism_test.c], [simple/isomorphism_test.out]) AT_CLEANUP AT_SETUP([Simplify and colorize]) AT_KEYWORDS([simplify multigraph colorize isomorphism]) AT_COMPILE_CHECK([tests/simplify_and_colorize.c], [tests/simplify_and_colorize.out]) AT_CLEANUP AT_SETUP([Graphical degree sequences]) AT_KEYWORDS([degree sequence graphical]) AT_COMPILE_CHECK([simple/igraph_is_degree_sequence.c]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/separators.at0000644000076500000240000000377513524616145024505 0ustar tamasstaff00000000000000# Minimal separators # Test suite for the IGraph library. # Copyright (C) 2010-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([[Minimal separators]]) AT_SETUP([Decision problem (igraph_is_separator): ]) AT_KEYWORDS([vertex separator]) AT_COMPILE_CHECK([simple/igraph_is_separator.c]) AT_CLEANUP AT_SETUP([Decision problem, minimal separator (igraph_is_minimal separator): ]) AT_KEYWORDS([minimal vertex separator]) AT_COMPILE_CHECK([simple/igraph_is_minimal_separator.c]) AT_CLEANUP AT_SETUP([Minimal separators (igraph_all_minimal_ab_separators): ]) AT_KEYWORDS([minimal separator]) AT_COMPILE_CHECK([simple/igraph_minimal_separators.c]) AT_CLEANUP AT_SETUP([Minimal separators, bug 1033045 (igraph_all_minimal_st_separators): ]) AT_KEYWORDS([minimal separator]) AT_COMPILE_CHECK([simple/bug-1033045.c], [simple/bug-1033045.out]) AT_CLEANUP AT_SETUP([Minimum size separators (igraph_minimum_size_separators): ]) AT_KEYWORDS([minimum size separators]) AT_COMPILE_CHECK([simple/igraph_minimum_size_separators.c], [simple/igraph_minimum_size_separators.out]) AT_CLEANUP AT_SETUP([Cohesive blocking (igraph_cohesive_blocks): ]) AT_KEYWORDS([structurally cohesive blocks]) AT_COMPILE_CHECK([simple/cohesive_blocks.c], [simple/cohesive_blocks.out]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/matching.at0000644000076500000240000000206013524616145024076 0ustar tamasstaff00000000000000# Maximum bipartite and non-bipartite matchings # Test suite for the IGraph library. # Copyright (C) 2012 Tamas Nepusz # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([[Maximum matchings]]) AT_SETUP([Maximum bipartite matching (igraph_maximum_bipartite_matching): ]) AT_KEYWORDS([bipartite matching]) AT_COMPILE_CHECK([simple/igraph_maximum_bipartite_matching.c]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/scg.at0000644000076500000240000000610513524616145023064 0ustar tamasstaff00000000000000# Spectral coarse graining # Test suite for the IGraph library. # Copyright (C) 2011-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([[Spectral coarse graining]]) AT_SETUP([Solving the SCG problem (igraph_scg_grouping) :]) AT_KEYWORDS([SCG spectral coarse graining grouping]) AT_COMPILE_CHECK([simple/igraph_scg_grouping.c], [simple/igraph_scg_grouping.out]) AT_CLEANUP AT_SETUP([Solving the SCG problem, adjacency matrix (igraph_scg_grouping) :]) AT_KEYWORDS([SCG spectral coarse graining grouping adjacency]) AT_COMPILE_CHECK([simple/igraph_scg_grouping2.c], [simple/igraph_scg_grouping2.out]) AT_CLEANUP AT_SETUP([Solving the SCG problem, stochastic matrix (igraph_scg_grouping) :]) AT_KEYWORDS([SCG spectral coarse graining grouping stochastic]) AT_COMPILE_CHECK([simple/igraph_scg_grouping3.c], [simple/igraph_scg_grouping3.out]) AT_CLEANUP AT_SETUP([Solving the SCG problem, laplacian matrix (igraph_scg_grouping) :]) AT_KEYWORDS([SCG spectral coarse graining grouping laplacian]) AT_COMPILE_CHECK([simple/igraph_scg_grouping4.c], [simple/igraph_scg_grouping4.out]) AT_CLEANUP AT_SETUP([SCG semi-projectors, symmetric (igraph_scg_semiprojectors) :]) AT_KEYWORDS([SCG spectral coarse graining semi-projectors adjancency]) AT_COMPILE_CHECK([simple/igraph_scg_semiprojectors.c], [simple/igraph_scg_semiprojectors.out]) AT_CLEANUP AT_SETUP([SCG semi-projectors, stochastic (igraph_scg_semiprojectors) :]) AT_KEYWORDS([SCG spectral coarse graining semi-projectors stochastic]) AT_COMPILE_CHECK([simple/igraph_scg_semiprojectors2.c], [simple/igraph_scg_semiprojectors2.out]) AT_CLEANUP AT_SETUP([SCG semi-projectors, laplacian (igraph_scg_semiprojectors) :]) AT_KEYWORDS([SCG spectral coarse graining semi-projectors laplacian]) AT_COMPILE_CHECK([simple/igraph_scg_semiprojectors3.c], [simple/igraph_scg_semiprojectors3.out]) AT_CLEANUP AT_SETUP([SCG of a graph, adjacency matrix (igraph_scg) :]) AT_KEYWORDS([SCG spectral coarse graining]) AT_COMPILE_CHECK([simple/scg.c], [simple/scg.out]) AT_CLEANUP AT_SETUP([SCG of a graph, stochastic matrix (igraph_scg) :]) AT_KEYWORDS([SCG spectral coarse graining]) AT_COMPILE_CHECK([simple/scg2.c], [simple/scg2.out]) AT_CLEANUP AT_SETUP([SCG of a graph, laplacian matrix (igraph_scg) :]) AT_KEYWORDS([SCG spectral coarse graining]) AT_COMPILE_CHECK([simple/scg3.c], [simple/scg3.out]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/mt.at0000644000076500000240000000232413524616145022727 0ustar tamasstaff00000000000000# Thread-safety tests # Test suite for the IGraph library. # Copyright (C) 2011-2012 Gabor Csardi # 334 Harvard street, Cambridge MA, 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([[Thread-safety tests]]) AT_SETUP([Simple error handling test :]) AT_KEYWORDS([thread-safe]) AT_COMPILE_CHECK([simple/tls1.c], [], [], [], [-lpthread]) AT_CLEANUP AT_SETUP([Thread-safe ARPACK:]) AT_KEYWORDS([thread-safe ARPACK]) AT_COMPILE_CHECK([simple/tls2.c], [simple/tls2.out], [], [internal], [-lpthread]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/basic.at0000644000076500000240000000524713524616145023377 0ustar tamasstaff00000000000000# Check the basic (interface) functions and implicitly also compilation # Test suite for the IGraph library. # Copyright (C) 2005-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA # Macros AT_BANNER([[Basic (interface) functions.]]) AT_SETUP([Creating an empty graph (igraph_empty): ]) AT_KEYWORDS([igraph_empty]) AT_COMPILE_CHECK([simple/igraph_empty.c]) AT_CLEANUP AT_SETUP([Copying a graph (igraph_copy): ]) AT_KEYWORDS([igraph_copy igraph_create]) AT_COMPILE_CHECK([simple/igraph_copy.c]) AT_CLEANUP AT_SETUP([Adding edges to a graph (igraph_add_edges): ]) AT_KEYWORDS([igraph_add_edges]) AT_COMPILE_CHECK([simple/igraph_add_edges.c], [simple/igraph_add_edges.out]) AT_CLEANUP AT_SETUP([Adding vertices (igraph_add_vertices): ]) AT_KEYWORDS([igraph_add_vertices]) AT_COMPILE_CHECK([simple/igraph_add_vertices.c]) AT_CLEANUP AT_SETUP([Deleting edges (igraph_delete_edges): ]) AT_KEYWORDS([igraph_delete_vertices]) AT_COMPILE_CHECK([simple/igraph_delete_edges.c]) AT_CLEANUP AT_SETUP([Deleting vertices (igraph_delete_vertices): ]) AT_KEYWORDS([igraph_delete_vertices]) AT_COMPILE_CHECK([simple/igraph_delete_vertices.c]) AT_CLEANUP AT_SETUP([Neighbors (igraph_neighbors): ]) AT_KEYWORDS([igraph_neighbors]) AT_COMPILE_CHECK([simple/igraph_neighbors.c], [simple/igraph_neighbors.out]) AT_CLEANUP AT_SETUP([Is the graph directed? (igraph_is_directed): ]) AT_KEYWORDS([igraph_is_directed]) AT_COMPILE_CHECK([simple/igraph_is_directed.c]) AT_CLEANUP AT_SETUP([Degree of the vertices (igraph_degree): ]) AT_KEYWORDS([igraph_degree]) AT_COMPILE_CHECK([simple/igraph_degree.c], [simple/igraph_degree.out]) AT_CLEANUP AT_SETUP([Query edge ids (igraph_get_eid): ]) AT_KEYWORDS([igraph_get_eid edge id]) AT_COMPILE_CHECK([simple/igraph_get_eid.c], [simple/igraph_get_eid.out]) AT_CLEANUP AT_SETUP([Query many edge ids (igraph_get_eids): ]) AT_KEYWORDS([igraph_get_eids edge id]) AT_COMPILE_CHECK([simple/igraph_get_eids.c], [simple/igraph_get_eids.out]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/microscopic.at0000644000076500000240000000307213524616145024622 0ustar tamasstaff00000000000000# Check functions for microscopic updates at the agent level # Test suite for the IGraph library. # Copyright (C) 2011 Minh Van Nguyen # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([[Microscopic updates]]) AT_SETUP([Deterministic optimal imitation:]) AT_KEYWORDS([deterministic imitation strategy]) AT_COMPILE_CHECK([simple/igraph_deterministic_optimal_imitation.c]) AT_CLEANUP AT_SETUP([Stochastic imitation via uniform selection:]) AT_KEYWORDS([stochastic imitation strategy uniform selection]) AT_COMPILE_CHECK([simple/igraph_stochastic_imitation.c]) AT_CLEANUP AT_SETUP([Stochastic imitation via roulette selection:]) AT_KEYWORDS([stochastic imitation strategy roulette wheel]) AT_COMPILE_CHECK([simple/igraph_roulette_wheel_imitation.c]) AT_CLEANUP AT_SETUP([Moran process:]) AT_KEYWORDS([Moran process haploid reproduction]) AT_COMPILE_CHECK([simple/igraph_moran_process.c]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/centralization.at0000644000076500000240000000205513524616145025336 0ustar tamasstaff00000000000000# Check functions for centralization # Test suite for the IGraph library. # Copyright (C) 2005-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([[Centralization]]) AT_SETUP([Centralization (igraph_centralization_*):]) AT_KEYWORDS([centralization]) AT_COMPILE_CHECK([simple/centralization.c]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/community.at0000644000076500000240000001076413576365615024354 0ustar tamasstaff00000000000000# Community structure # Test suite for the IGraph library. # Copyright (C) 2005-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([[Community structure]]) AT_SETUP([Spinglass clustering (igraph_spinglass_community): ]) AT_KEYWORDS([spin glass spinglass community clustering]) AT_COMPILE_CHECK([simple/spinglass.c]) AT_CLEANUP AT_SETUP([Walktrap community structure (igraph_walktrap_community): ]) AT_KEYWORDS([random walk community structure clustering walktrap]) AT_COMPILE_CHECK([simple/walktrap.c], [simple/walktrap.out]) AT_CLEANUP AT_SETUP([Edge betweenness community structure (igraph_community_edge_betweenness): ]) AT_KEYWORDS([community structure edge betweenness Newman Girvan]) AT_COMPILE_CHECK([simple/igraph_community_edge_betweenness.c], [simple/igraph_community_edge_betweenness.out]) AT_CLEANUP AT_SETUP([Modularity optimization (igraph_community_fastgreedy): ]) AT_KEYWORDS([community structure Clauset Newman Moore modularity greedy]) AT_COMPILE_CHECK([simple/igraph_community_fastgreedy.c], [simple/igraph_community_fastgreedy.out]) AT_CLEANUP AT_SETUP([Leading eigenvector community structure (igraph_community_leading_eigenvector) :]) AT_KEYWORDS([community structure leading eigenvector Newman]) AT_COMPILE_CHECK([simple/igraph_community_leading_eigenvector.c], [simple/igraph_community_leading_eigenvector.out]) AT_CLEANUP AT_SETUP([Weighted leading eigenvector community structure (igraph_community_leading_eigenvector) :]) AT_KEYWORDS([community structure leading eigenvector Newman weighted]) AT_COMPILE_CHECK([simple/igraph_community_leading_eigenvector2.c], [simple/igraph_community_leading_eigenvector2.out]) AT_CLEANUP AT_SETUP([Leading eigenvector bug 1002140 test (igraph_community_leading_eigenvector) :]) AT_KEYWORDS([community structure leading eigenvector Newman]) AT_COMPILE_CHECK([simple/levc-stress.c], [], [simple/input.dl]) AT_CLEANUP AT_SETUP([Fluid communities algorithm (igraph_community_fluid_communities) :]) AT_KEYWORDS([community structure fluidc fluid communities Pares Garcia-Gasulla]) AT_COMPILE_CHECK([tests/igraph_community_fluid_communities.c], [tests/igraph_community_fluid_communities.out]) AT_CLEANUP AT_SETUP([Label propagation algorithm (igraph_community_label_propagation) :]) AT_KEYWORDS([community structure label propagation Raghavan Albert Kumara]) AT_COMPILE_CHECK([simple/igraph_community_label_propagation.c], [simple/igraph_community_label_propagation.out]) AT_CLEANUP AT_SETUP([Multilevel community detection (igraph_community_multilevel) :]) AT_KEYWORDS([community structure multilevel Blondel Guillaume Lambiotte Lefebvre]) AT_COMPILE_CHECK([simple/igraph_community_multilevel.c], [simple/igraph_community_multilevel.out]) AT_CLEANUP AT_SETUP([Multilevel community detection, isolates (igraph_community_multilevel) :]) AT_KEYWORDS([community structure multilevel Blondel Guillaume Lambiotte Lefebvre]) AT_COMPILE_CHECK([simple/bug-1149658.c]) AT_CLEANUP AT_SETUP([Leiden community detection (igraph_community_leiden) :]) AT_KEYWORDS([community structure using Leiden algorithm]) AT_COMPILE_CHECK([tests/igraph_community_leiden.c], [tests/igraph_community_leiden.out]) AT_CLEANUP AT_SETUP([Modularity optimization, integer programming (igraph_community_optimal_modularity) :]) AT_KEYWORDS([community structure optimal modularity integer programming]) AT_COMPILE_CHECK([simple/igraph_community_optimal_modularity.c]) AT_CLEANUP AT_SETUP([Infomap community structure (igraph_community_infomap) :]) AT_KEYWORDS([community structure infomap Rosvall Bergstrom]) AT_COMPILE_CHECK([simple/igraph_community_infomap.c], [simple/igraph_community_infomap.out], [simple/wikti_en_V_syn.elist]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/qsort.at0000644000076500000240000000234613524616145023463 0ustar tamasstaff00000000000000# qsort test # Test suite for the IGraph library. # Copyright (C) 2011-2012 Gabor Csardi # 334 Harvard st, Cambridge, MA 02139, USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([[Quick sort]]) AT_SETUP([Regular qsort (igraph_qsort):]) AT_KEYWORDS([qsort quick sort igraph_qsort]) AT_COMPILE_CHECK([simple/igraph_qsort.c], [simple/igraph_qsort.out]) AT_CLEANUP AT_SETUP([qsort with extra argument (igraph_qsort_r):]) AT_KEYWORDS([qsort quick sort igraph_qsort_r]) AT_COMPILE_CHECK([simple/igraph_qsort_r.c], [simple/igraph_qsort_r.out]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/arpack.at0000644000076500000240000000523013524616145023547 0ustar tamasstaff00000000000000# Check ARPACK based functins # Test suite for the IGraph library. # Copyright (C) 2005-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([[BLAS, LAPACK and ARPACK based functions]]) AT_SETUP([Basic BLAS functions (igraph_blas_*):]) AT_KEYWORDS([blas BLAS matrix vector dgemv igraph_blas_dgemv]) AT_COMPILE_CHECK([simple/blas.c], [simple/blas.out]) AT_CLEANUP AT_SETUP([Dense symmetric eigenvalues and eigenvectors (igraph_lapack_dsyevr):]) AT_KEYWORDS([lapack LAPACK dsyevr eigenvalue eigenvector dense]) AT_COMPILE_CHECK([simple/igraph_lapack_dsyevr.c]) AT_CLEANUP AT_SETUP([Dense non-symmetric eigenvalues and eigenvectors (igraph_lapack_dgeev):]) AT_KEYWORDS([lapack LAPACK dgeev eigenvalue eigenvector dense]) AT_COMPILE_CHECK([simple/igraph_lapack_dgeev.c]) AT_CLEANUP AT_SETUP([Dense non-symmetric eigenvalues and eigenvectors (igraph_lapack_dgeevx):]) AT_KEYWORDS([lapack LAPACK dgeevx eigenvalue eigenvector dense]) AT_COMPILE_CHECK([simple/igraph_lapack_dgeevx.c]) AT_CLEANUP AT_SETUP([Solving linear systems with LU factorization (igraph_lapack_dgesv):]) AT_KEYWORDS([lapack LAPACK dgesv solve LU factorization]) AT_COMPILE_CHECK([simple/igraph_lapack_dgesv.c], [simple/igraph_lapack_dgesv.out]) AT_CLEANUP AT_SETUP([Upper Hessenberg transformation (igraph_lapack_dgehrd):]) AT_KEYWORDS([lapack dgehrd Hessenberg]) AT_COMPILE_CHECK([simple/igraph_lapack_dgehrd.c], [simple/igraph_lapack_dgehrd.out]) AT_CLEANUP AT_SETUP([Eigenvector centrality (igraph_eigenvector_centrality):]) AT_KEYWORDS([eigenvector centrality arpack ARPACK]) AT_COMPILE_CHECK([simple/eigenvector_centrality.c], [simple/eigenvector_centrality.out]) AT_CLEANUP AT_SETUP([Non-symmetric ARPACK solver (igraph_arpack_rnsolve):]) AT_KEYWORDS([ARPACK eigenvalue eigenvector eigen eigenproblem non-symmetric]) AT_COMPILE_CHECK([simple/igraph_arpack_rnsolve.c], [simple/igraph_arpack_rnsolve.out]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/eigen.at0000644000076500000240000000426013524616145023377 0ustar tamasstaff00000000000000# Eigenvalues, eigenvectors # Test suite for the IGraph library. # Copyright (C) 2005-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([[Eigenvalues, eigenvectors]]) AT_SETUP([Symmetric matrix, LAPACK (igraph_eigen_matrix_symmetric):]) AT_KEYWORDS([eigenvalue lapack LAPACK]) AT_COMPILE_CHECK([simple/igraph_eigen_matrix_symmetric.c], [simple/igraph_eigen_matrix_symmetric.out]) AT_CLEANUP AT_SETUP([Symmetric matrix, ARPACK (igraph_eigen_matrix_symmetric):]) AT_KEYWORDS([eigenvalue lapack LAPACK]) AT_COMPILE_CHECK([simple/igraph_eigen_matrix_symmetric_arpack.c], [simple/igraph_eigen_matrix_symmetric_arpack.out]) AT_CLEANUP AT_SETUP([General matrix, LAPACK, LM, SM (igraph_eigen_matrix):]) AT_KEYWORDS([eigenvalue lapack LAPACK]) AT_COMPILE_CHECK([simple/igraph_eigen_matrix.c], [simple/igraph_eigen_matrix.out]) AT_CLEANUP AT_SETUP([General matrix, LAPACK, LR, SR (igraph_eigen_matrix):]) AT_KEYWORDS([eigenvalue lapack LAPACK]) AT_COMPILE_CHECK([simple/igraph_eigen_matrix2.c], [simple/igraph_eigen_matrix2.out]) AT_CLEANUP AT_SETUP([General matrix, LAPACK, LI, SI (igraph_eigen_matrix):]) AT_KEYWORDS([eigenvalue lapack LAPACK]) AT_COMPILE_CHECK([simple/igraph_eigen_matrix4.c], [simple/igraph_eigen_matrix4.out]) AT_CLEANUP AT_SETUP([General matrix, LAPACK, SELECT (igraph_eigen_matrix):]) AT_KEYWORDS([eigenvalue lapack LAPACK]) AT_COMPILE_CHECK([simple/igraph_eigen_matrix3.c], [simple/igraph_eigen_matrix3.out]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/cliques.at0000644000076500000240000000607013612122634023747 0ustar tamasstaff00000000000000# Check the functions related to clique and independent set calculations # Test suite for the IGraph library. # Copyright (C) 2005-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA # Macros AT_BANNER([[Cliques and independent vertex sets.]]) AT_SETUP([Calculating cliques (igraph_cliques): ]) AT_KEYWORDS([igraph_cliques, igraph_maximal_cliques, igraph_clique_number]) AT_COMPILE_CHECK([simple/igraph_cliques.c], [simple/igraph_cliques.out]) AT_CLEANUP AT_SETUP([Additional test for maximal cliques (igraph_maximal_cliques):]) AT_KEYWORDS([igraph_maximal_cliques cliques maximal cliques]) AT_COMPILE_CHECK([simple/igraph_maximal_cliques.c], [simple/igraph_maximal_cliques.out]) AT_CLEANUP AT_SETUP([More maximal cliques (igraph_maximal_cliques):]) AT_KEYWORDS([igraph_maximal_cliques cliques maximal cliques]) AT_COMPILE_CHECK([simple/igraph_maximal_cliques2.c], [simple/igraph_maximal_cliques2.out]) AT_CLEANUP AT_SETUP([Maximal cliques 3 (igraph_maximal_cliques):]) AT_KEYWORDS([igraph_maximal_cliques cliques maximal cliques]) AT_COMPILE_CHECK([simple/igraph_maximal_cliques3.c], [simple/igraph_maximal_cliques3.out]) AT_CLEANUP AT_SETUP([Maximal cliques for a subset (igraph_maximal_cliques):]) AT_KEYWORDS([igraph_maximal_cliques cliques maximal cliques]) AT_COMPILE_CHECK([simple/igraph_maximal_cliques4.c], [simple/igraph_maximal_cliques4.out]) AT_CLEANUP AT_SETUP([Maximal cliques callback (igraph_maximal_cliques_callback):]) AT_KEYWORDS([igraph_maximal_cliques cliques maximal cliques]) AT_COMPILE_CHECK([tests/maximal_cliques_callback.c]) AT_CLEANUP AT_SETUP([Maximal cliques histogram (igraph_maximal_cliques_hist):]) AT_KEYWORDS([igraph_maximal_cliques cliques maximal cliques]) AT_COMPILE_CHECK([tests/maximal_cliques_hist.c], [tests/maximal_cliques_hist.out]) AT_CLEANUP AT_SETUP([Weighted cliques (igraph_weighted_cliques):]) AT_KEYWORDS([igraph_weighted_cliques cliques]) AT_COMPILE_CHECK([simple/igraph_weighted_cliques.c], [simple/igraph_weighted_cliques.out]) AT_CLEANUP AT_SETUP([Calculating independent vertex sets (igraph_independent_vertex_sets): ]) AT_KEYWORDS([igraph_independent_vertex_sets, igraph_maximal_independent_vertex_sets, igraph_independence_number]) AT_COMPILE_CHECK([simple/igraph_independent_sets.c], [simple/igraph_independent_sets.out]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/foreign.at0000644000076500000240000001133513524616145023742 0ustar tamasstaff00000000000000# Check functions for importing and exporting various formats # Test suite for the IGraph library. # Copyright (C) 2005-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([[Foreign formats]]) AT_SETUP([Reading Pajek (igraph_read_graph_pajek):]) AT_KEYWORDS([igraph_read_graph_pajek foreign pajek]) AT_COMPILE_CHECK([simple/foreign.c], [simple/foreign.out], [simple/LINKS.NET]) AT_CLEANUP AT_SETUP([GraphML (igraph_{read,write}_graph_graphml):]) AT_KEYWORDS([igraph_read_graph_graphml igraph_write_graph_graphml foreign graphml]) AT_COMPILE_CHECK([simple/graphml.c], [simple/graphml.out], [simple/{test.gxl,graphml-hsa05010.xml,graphml-default-attrs.xml,graphml-namespace.xml,graphml-lenient.xml,graphml-malformed.xml}]) AT_CLEANUP AT_SETUP([Writing Pajek (igraph_write_graph_pajek):]) AT_KEYWORDS([igraph_write_graph_pajek foreign pajek]) AT_COMPILE_CHECK([simple/igraph_write_graph_pajek.c], [simple/igraph_write_graph_pajek.out]) AT_CLEANUP AT_SETUP([Pajek with number of edges present (igraph_read_graph_pajek):]) AT_KEYWORDS([igraph_read_graph_pajek pajek foreign]) AT_COMPILE_CHECK([simple/pajek.c], [], [simple/pajek{5,6}.net]) AT_CLEANUP AT_SETUP([Pajek, bipartite (igraph_read_graph_pajek):]) AT_KEYWORDS([igraph_read_graph_pajek pajek foreign bipartite]) AT_COMPILE_CHECK([simple/pajek2.c], [simple/pajek2.out], [simple/bipartite.net]) AT_CLEANUP AT_SETUP([Pajek, bipartite incidence matrix (igraph_read_graph_pajek):]) AT_KEYWORDS([igraph_read_graph_pajek pajek foreign bipartite incidence]) AT_COMPILE_CHECK([simple/pajek_bipartite2.c], [simple/pajek_bipartite2.out], [simple/pajek_{bip,bip2}.net]) AT_CLEANUP AT_SETUP([Pajek, signed (igraph_read_graph_pajek):]) AT_KEYWORDS([igraph_read_graph_pajek pajek foreign signed]) AT_COMPILE_CHECK([simple/pajek_signed.c], [simple/pajek_signed.out], [simple/pajek_signed.net]) AT_CLEANUP AT_SETUP([Pajek, writing bipartite graph (igraph_write_graph_pajek):]) AT_KEYWORDS([igraph_write_graph_pajek pajek foreign bipartite]) AT_COMPILE_CHECK([simple/pajek_bipartite.c], [simple/pajek_bipartite.out]) AT_CLEANUP AT_SETUP([Reading an LGL file (igraph_read_graph_lgl):]) AT_KEYWORDS([igraph_read_graph_lgl LGL foreign]) AT_COMPILE_CHECK([simple/igraph_read_graph_lgl.c], [simple/igraph_read_graph_lgl.out], [{simple/igraph_read_graph_lgl-1.lgl,simple/igraph_read_graph_lgl-2.lgl,simple/igraph_read_graph_lgl-3.lgl}]) AT_CLEANUP AT_SETUP([Writing LGL (igraph_write_graph_lgl):]) AT_KEYWORDS([igraph_write_graph_lgl foreign LGL]) AT_COMPILE_CHECK([simple/igraph_write_graph_lgl.c]) AT_CLEANUP AT_SETUP([Reading a graph from the graph database (igraph_read_graph_graphdb):]) AT_KEYWORDS([igraph_read_graph_graphdb foreign graphdb database isomorphism]) AT_COMPILE_CHECK([simple/igraph_read_graph_graphdb.c], [simple/igraph_read_graph_graphdb.out], [simple/iso_b03_m1000.A00]) AT_CLEANUP AT_SETUP([Reading a GML file (igraph_read_graph_gml):]) AT_KEYWORDS([igraph_read_graph_gml foreign GML]) AT_COMPILE_CHECK([simple/gml.c], [simple/gml.out], [simple/karate.gml]) AT_CLEANUP AT_SETUP([Writing a DOT file (igraph_write_graph_dot):]) AT_KEYWORDS([igraph_write_graph_dot foreign DOT GraphViz]) AT_COMPILE_CHECK([simple/dot.c], [simple/dot.out], [simple/karate.gml]) AT_CLEANUP AT_SETUP([Different line endings:]) AT_KEYWORDS([igraph_read_graph_pajek igraph_write_graph_pajek foreign line ending lineending]) AT_COMPILE_CHECK([simple/lineendings.c], [simple/lineendings.out], [{simple/pajek1.net,simple/pajek2.net,simple/pajek3.net,simple/pajek4.net}]) AT_CLEANUP AT_SETUP([UNICET DL format:]) AT_KEYWORDS([igraph_read_graph_dl DL UCINET]) AT_COMPILE_CHECK([simple/igraph_read_graph_dl.c], [simple/igraph_read_graph_dl.out], [simple/{edgelist1,edgelist2,edgelist3,edgelist4,edgelist5,edgelist6,edgelist7,fullmatrix1,fullmatrix2,fullmatrix3,fullmatrix4,nodelist1,nodelist2}.dl]) AT_CLEANUP AT_SETUP([LEDA format:]) AT_KEYWORDS([igraph_write_graph_leda LEDA]) AT_COMPILE_CHECK([simple/igraph_write_graph_leda.c], [simple/igraph_write_graph_leda.out], []) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/testsuite.at0000644000076500000240000000520413524616145024340 0ustar tamasstaff00000000000000# Process this file with autom4te to create testsuite. -*- Autotest -*- # Test suite for the IGraph library. # Copyright (C) 2005-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_INIT([igraph]) m4_define([AT_COMPILE_CHECK], [ AT_CHECK([m4_if([[$4]],[[]], [[${CC} ${CFLAGS} ${abs_top_srcdir}/examples/$1 -I${abs_top_srcdir}/include -I${abs_top_builddir}/include -L${abs_top_builddir}/src/.libs -ligraph -lm $5 -o itest]], [[${CC} ${CFLAGS} ${abs_top_srcdir}/examples/$1 -I${abs_top_srcdir}/include -I${abs_top_srcdir}/src -I${abs_top_builddir}/include -I${abs_top_builddir} -L${abs_top_builddir}/src/.libs -ligraph -lm $5 -o itest]])]) AT_CHECK([m4_if([[$2]],[[]],[[>expout]],[[cat ${abs_top_srcdir}/examples/'$2' | sed "s/@VERSION@/$(cat ${abs_top_srcdir}/IGRAPH_VERSION)/g" > expout]])]) AT_CHECK([m4_if([[$3]],[[]],[[]],[[cp ${abs_top_srcdir}/examples/$3 .]])]) AT_CHECK([DYLD_LIBRARY_PATH=${abs_top_builddir}/src/.libs${DYLD_LIBRARY_PATH+:$DYLD_LIBRARY_PATH} LD_LIBRARY_PATH=${abs_top_builddir}/src/.libs${LD_LIBRARY_PATH+:$LD_LIBRARY_PATH} ./itest], [], [expout])]) m4_include([version.at]) m4_include([types.at]) m4_include([basic.at]) m4_include([iterators.at]) m4_include([structure_generators.at]) m4_include([structural_properties.at]) m4_include([components.at]) m4_include([layout.at]) m4_include([visitors.at]) m4_include([topology.at]) m4_include([coloring.at]) m4_include([motifs.at]) m4_include([foreign.at]) m4_include([other.at]) m4_include([operators.at]) m4_include([conversion.at]) m4_include([flow.at]) m4_include([community.at]) m4_include([cliques.at]) m4_include([eigen.at]) m4_include([attributes.at]) m4_include([arpack.at]) m4_include([bipartite.at]) m4_include([centralization.at]) m4_include([separators.at]) m4_include([hrg.at]) m4_include([microscopic.at]) m4_include([mt.at]) m4_include([scg.at]) m4_include([random.at]) m4_include([qsort.at]) m4_include([matching.at]) m4_include([embedding.at]) python-igraph-0.8.0/vendor/source/igraph/tests/bipartite.at0000644000076500000240000000255613524616145024301 0ustar tamasstaff00000000000000# Check functions for bipartite graphs # Test suite for the IGraph library. # Copyright (C) 2005-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([[Bipartite graphs]]) AT_SETUP([Create bipartite graphs (igraph_create_bipartite):]) AT_KEYWORDS([bipartite two mode igraph_create_bipartite]) AT_COMPILE_CHECK([simple/igraph_bipartite_create.c], [simple/igraph_bipartite_create.out]) AT_CLEANUP AT_SETUP([Projection of bipartite graphs (igraph_bipartite_projection):]) AT_KEYWORDS([bipartite two mode projection igraph_bipartite_projection]) AT_COMPILE_CHECK([simple/igraph_bipartite_projection.c]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/structural_properties.at0000644000076500000240000002072113532467671027003 0ustar tamasstaff00000000000000# Check functions calculating structural properties # Test suite for the IGraph library. # Copyright (C) 2005-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([[Structural properties]]) AT_SETUP([Two vertices connected by an edge:]) AT_KEYWORDS([igraph_are_connected]) AT_COMPILE_CHECK([simple/igraph_are_connected.c]) AT_CLEANUP AT_SETUP([Density of a graph (igraph_density):]) AT_KEYWORDS([igraph_density density]) AT_COMPILE_CHECK([simple/igraph_density.c], [simple/igraph_density.out]) AT_CLEANUP AT_SETUP([Diameter of a graph (igraph_diameter):]) AT_KEYWORDS([igraph_diameter]) AT_COMPILE_CHECK([simple/igraph_diameter.c], [simple/igraph_diameter.out]) AT_CLEANUP AT_SETUP([Average geodesic length (igraph_average_path_length): ]) AT_KEYWORDS([igraph_average_path_length]) AT_COMPILE_CHECK([simple/igraph_average_path_length.c]) AT_CLEANUP AT_SETUP([Google PageRank (igraph_pagerank): ]) AT_KEYWORDS([igraph_pagerank]) AT_COMPILE_CHECK([simple/igraph_pagerank.c], [simple/igraph_pagerank.out]) AT_CLEANUP AT_SETUP([Random rewiring (igraph_rewire): ]) AT_KEYWORDS([igraph_rewire]) AT_COMPILE_CHECK([simple/igraph_rewire.c]) AT_CLEANUP AT_SETUP([Get the shortest paths (igraph_get_shortest_paths): ]) AT_KEYWORDS([igraph_get_shortest_paths shortest paths geodesic]) AT_COMPILE_CHECK([simple/igraph_get_shortest_paths.c], [simple/igraph_get_shortest_paths.out]) AT_CLEANUP AT_SETUP([Get the shortest paths 2 (igraph_get_shortest_paths): ]) AT_KEYWORDS([igraph_get_shortest_paths shortest paths geodesic]) AT_COMPILE_CHECK([simple/igraph_get_shortest_paths2.c], [simple/igraph_get_shortest_paths2.out]) AT_CLEANUP AT_SETUP([Weighted shortest paths (Dijkstra): ]) AT_KEYWORDS([igraph_shortest_paths_dijkstra Dijkstra shortest paths geodesic]) AT_COMPILE_CHECK([simple/dijkstra.c], [simple/dijkstra.out]) AT_CLEANUP AT_SETUP([Weighted shortest paths (Bellman-Ford): ]) AT_KEYWORDS([igraph_shortest_paths_bellman_ford Bellman-Ford shortest paths geodesic]) AT_COMPILE_CHECK([simple/bellman_ford.c], [simple/bellman_ford.out]) AT_CLEANUP AT_SETUP([Get the weighted shortest paths (Dijkstra): ]) AT_KEYWORDS([igraph_get_shortest_paths_dijkstra Dijkstra shortest paths geodesic]) AT_COMPILE_CHECK([simple/igraph_get_shortest_paths_dijkstra.c], [simple/igraph_get_shortest_paths_dijkstra.out]) AT_CLEANUP AT_SETUP([Get all weighted shortest paths (Dijkstra): ]) AT_KEYWORDS([igraph_get_all_shortest_paths_dijkstra Dijkstra shortest paths geodesic]) AT_COMPILE_CHECK([simple/igraph_get_all_shortest_paths_dijkstra.c], [simple/igraph_get_all_shortest_paths_dijkstra.out]) AT_CLEANUP AT_SETUP([Get all simple paths: ]) AT_KEYWORDS([igraph_get_all_simple_paths simple paths]) AT_COMPILE_CHECK([simple/igraph_get_all_simple_paths.c], [simple/igraph_get_all_simple_paths.out]) AT_CLEANUP AT_SETUP([Shortest path wrappers for single target node: ]) AT_KEYWORDS([igraph_get_shortest_path igraph_get_shortest_path_dijkstra]) AT_COMPILE_CHECK([simple/single_target_shortest_path.c], [simple/single_target_shortest_path.out]) AT_CLEANUP AT_SETUP([Betweenness (igraph_betweenness): ]) AT_KEYWORDS([igraph_betweenness betweenness]) AT_COMPILE_CHECK([simple/igraph_betweenness.c]) AT_CLEANUP AT_SETUP([Betweenness, big integers (igraph_betweenness): ]) AT_KEYWORDS([igraph_betweenness betweenness arbitrarily large integers biguint bigint]) AT_COMPILE_CHECK([simple/biguint_betweenness.c]) AT_CLEANUP AT_SETUP([Edge betweenness (igraph_edge_betweenness): ]) AT_KEYWORDS([igraph_edge_betweenness betwenness]) AT_COMPILE_CHECK([simple/igraph_edge_betweenness.c], [simple/igraph_edge_betweenness.out]) AT_CLEANUP AT_SETUP([Transitivity (igraph_transitivity): ]) AT_KEYWORDS([igraph_transitivity transitivity igraph_transitivity_undirected]) AT_COMPILE_CHECK([simple/igraph_transitivity.c]) AT_CLEANUP AT_SETUP([Local transitivity (igraph_local_transitivity): ]) AT_KEYWORDS([transitivity igraph_transitivity_local_undirected]) AT_COMPILE_CHECK([simple/igraph_local_transitivity.c]) AT_CLEANUP AT_SETUP([Reciprocity (igraph_reciprocity): ]) AT_KEYWORDS([igraph_reciprocity reciprocity]) AT_COMPILE_CHECK([simple/igraph_reciprocity.c]) AT_CLEANUP AT_SETUP([Minimum spanning tree (igraph_minimum_spanning_tree_*): ]) AT_KEYWORDS([igraph_minimum_spanning_tree_prim Prim minimum spanning tree]) AT_COMPILE_CHECK([simple/igraph_minimum_spanning_tree.c], [simple/igraph_minimum_spanning_tree.out]) AT_CLEANUP AT_SETUP([Cocitation and bibcoupling (igraph_cocitation,igraph_bibcoupling):]) AT_KEYWORDS([cocitation bibliographic coupling]) AT_COMPILE_CHECK([simple/igraph_cocitation.c], [simple/igraph_cocitation.out]) AT_CLEANUP AT_SETUP([Similarity coefficients (igraph_similarity_*):]) AT_KEYWORDS([similarity jaccard dice]) AT_COMPILE_CHECK([simple/igraph_similarity.c], [simple/igraph_similarity.out]) AT_CLEANUP AT_SETUP([Simplification of non-simple graphs (igraph_simplify): ]) AT_KEYWORDS([simplify multiple edge loop edges non-simple graphs simple graphs]) AT_COMPILE_CHECK([simple/igraph_simplify.c], [simple/igraph_simplify.out]) AT_CLEANUP AT_SETUP([Topological sorting (igraph_topological_sorting, igraph_is_dag): ]) AT_KEYWORDS([topological sorting directed acyclic graphs]) AT_COMPILE_CHECK([simple/igraph_topological_sorting.c], [simple/igraph_topological_sorting.out]) AT_CLEANUP AT_SETUP([Feedback arc sets, Eades heuristics (igraph_feedback_arc_set): ]) AT_KEYWORDS([feedback arc set directed graphs]) AT_COMPILE_CHECK([simple/igraph_feedback_arc_set.c], [simple/igraph_feedback_arc_set.out]) AT_CLEANUP AT_SETUP([Feedback arc sets, integer programming (igraph_feedback_arc_set): ]) AT_KEYWORDS([feedback arc set directed graphs]) AT_COMPILE_CHECK([simple/igraph_feedback_arc_set_ip.c], [simple/igraph_feedback_arc_set_ip.out]) AT_CLEANUP AT_SETUP([Loop edges test (igraph_is_loop): ]) AT_KEYWORDS([loop edge igraph_is_loop]) AT_COMPILE_CHECK([simple/igraph_is_loop.c], [simple/igraph_is_loop.out]) AT_CLEANUP AT_SETUP([Multiple edges test (igraph_is_multiple): ]) AT_KEYWORDS([multiple edge parallel edge igraph_is_multiple]) AT_COMPILE_CHECK([simple/igraph_is_multiple.c], [simple/igraph_is_multiple.out]) AT_CLEANUP AT_SETUP([Multiple edges test (igraph_has_multiple): ]) AT_KEYWORDS([multiple edge parallel edge igraph_has_multiple]) AT_COMPILE_CHECK([simple/igraph_has_multiple.c]) AT_CLEANUP AT_SETUP([Tree test (igraph_is_tree): ]) AT_KEYWORDS([tree igraph_is_tree]) AT_COMPILE_CHECK([simple/igraph_is_tree.c]) AT_CLEANUP AT_SETUP([Girth (igraph_girth): ]) AT_KEYWORDS([girth igraph_girth]) AT_COMPILE_CHECK([simple/igraph_girth.c]) AT_CLEANUP AT_SETUP([Convergence degree (igraph_convergence_degree): ]) AT_KEYWORDS([edge convergence degree igraph_convergence_degree]) AT_COMPILE_CHECK([simple/igraph_convergence_degree.c], [simple/igraph_convergence_degree.out]) AT_CLEANUP AT_SETUP([Assortativity coefficient (igraph_assortativity): ]) AT_KEYWORDS([assortativity mixing igraph_assortativity]) AT_COMPILE_CHECK([simple/assortativity.c], [simple/assortativity.out], [simple/{karate,celegansneural}.gml]) AT_CLEANUP AT_SETUP([Average nearest neighbor degree (igraph_avg_nearest_neighbor_degree): ]) AT_KEYWORDS([nearest neighbor degree degree correlations]) AT_COMPILE_CHECK([simple/igraph_knn.c]) AT_CLEANUP AT_SETUP([Transitive closure of a DAG (igraph_transitive_closure_dag): ]) AT_KEYWORDS([transitive closure DAG]) AT_COMPILE_CHECK([simple/igraph_transitive_closure_dag.c], [simple/igraph_transitive_closure_dag.out]) AT_CLEANUP AT_SETUP([Eccentricity (igraph_eccentricity): ]) AT_KEYWORDS([eccentricity]) AT_COMPILE_CHECK([simple/igraph_eccentricity.c], [simple/igraph_eccentricity.out]) AT_CLEANUP AT_SETUP([Radius (igraph_radius): ]) AT_KEYWORDS([radius eccentricity]) AT_COMPILE_CHECK([simple/igraph_radius.c]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/components.at0000644000076500000240000000342713524616145024501 0ustar tamasstaff00000000000000# Check functions for working with connected components # Test suite for the IGraph library. # Copyright (C) 2005-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([[Components]]) AT_SETUP([Decompose a graph (igraph_decompose):]) AT_KEYWORDS([igraph_decompose decompose component]) AT_COMPILE_CHECK([simple/igraph_decompose.c], [simple/igraph_decompose.out]) AT_CLEANUP AT_SETUP([Decompose a graph into strongly connected components (igraph_decompose_strong):]) AT_KEYWORDS([igraph_decompose_strong decompose_strong component_strong]) AT_COMPILE_CHECK([tests/igraph_decompose_strong.c], [tests/igraph_decompose_strong.out]) AT_CLEANUP AT_SETUP([Biconnected components (igraph_biconnected_components):]) AT_KEYWORDS([igraph_biconnected_components biconnected component]) AT_COMPILE_CHECK([simple/igraph_biconnected_components.c], [simple/igraph_biconnected_components.out]) AT_CLEANUP AT_SETUP([Bridges (igraph_bridges):]) AT_KEYWORDS([igraph_bridges bridges]) AT_COMPILE_CHECK([simple/igraph_bridges.c], [simple/igraph_bridges.out]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/operators.at0000644000076500000240000000462113524616145024327 0ustar tamasstaff00000000000000# Check functions for graph operators # Test suite for the IGraph library. # Copyright (C) 2005-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([[Graphs operators]]) AT_SETUP([Disjoint union (igraph_disjoint_union, igraph_dosjoint_union_many):]) AT_KEYWORDS([igraph_disjoint_union, igraph_disjoint_union_many, disjoint_union, union]) AT_COMPILE_CHECK([simple/igraph_disjoint_union.c], [simple/igraph_disjoint_union.out]) AT_CLEANUP AT_SETUP([Union (igraph_union, igraph_union_many):]) AT_KEYWORDS([igraph_union, igraph_union_many, union]) AT_COMPILE_CHECK([simple/igraph_union.c], [simple/igraph_union.out]) AT_CLEANUP AT_SETUP([Intersection (igraph_intersection, igraph_intersection_many):]) AT_KEYWORDS([igraph_intersection, igraph_intersection_many, intersection]) AT_COMPILE_CHECK([simple/igraph_intersection.c], [simple/igraph_intersection.out]) AT_CLEANUP AT_SETUP([Intersection 2 (igraph_intersection, igraph_intersection_many):]) AT_KEYWORDS([igraph_intersection, igraph_intersection_many, intersection]) AT_COMPILE_CHECK([simple/igraph_intersection2.c], [simple/igraph_intersection2.out]) AT_CLEANUP AT_SETUP([Difference (igraph_difference):]) AT_KEYWORDS([igraph_difference, difference]) AT_COMPILE_CHECK([simple/igraph_difference.c], [simple/igraph_difference.out]) AT_CLEANUP AT_SETUP([Complementer (igraph_complementer):]) AT_KEYWORDS([igraph_complementer, complementer]) AT_COMPILE_CHECK([simple/igraph_complementer.c], [simple/igraph_complementer.out]) AT_CLEANUP AT_SETUP([Composition (igraph_compose):]) AT_KEYWORDS([igraph_composition, composition, compose]) AT_COMPILE_CHECK([simple/igraph_compose.c], [simple/igraph_compose.out]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/atlocal.in0000644000076500000240000000046713524616145023736 0ustar tamasstaff00000000000000# @configure_input@ # Configurable variable values for igraph test suite. Taken from bison source. # Copyright 2000, 2001, 2002 Free Software Foundation, Inc. # We need a C compiler. CC='@CC@' CFLAGS='@CFLAGS@ @WARNING_CFLAGS@ @WERROR_CFLAGS@' # We need `config.h'. CPPFLAGS="-I$abs_top_builddir @CPPFLAGS@" python-igraph-0.8.0/vendor/source/igraph/tests/Makefile.am0000644000076500000240000000312313532467671024022 0ustar tamasstaff00000000000000 EXTRA_DIST = $(TESTSUITE_AT) $(top_builddir)/tests/testsuite MAINTAINERCLEANFILES = Makefile.in $(TESTSUITE) package.m4 atconfig $(srcdir)/package.m4: $(top_srcdir)/configure.ac { \ echo '# Signature of the current package.'; \ echo 'm4_define([AT_PACKAGE_NAME], [@PACKAGE_NAME@])'; \ echo 'm4_define([AT_PACKAGE_TARNAME], [@PACKAGE_TARNAME@])'; \ echo 'm4_define([AT_PACKAGE_VERSION], [@PACKAGE_VERSION@])'; \ echo 'm4_define([AT_PACKAGE_STRING], [@PACKAGE_STRING@])'; \ echo 'm4_define([AT_PACKAGE_BUGREPORT], [@PACKAGE_BUGREPORT@])'; \ } >$(srcdir)/package.m4 EXTRA_DIST += package.m4 TESTSUITE_AT = \ testsuite.at \ types.at basic.at structure_generators.at \ structural_properties.at iterators.at components.at \ visitors.at layout.at motifs.at topology.at foreign.at operators.at \ other.at foreign.at conversion.at flow.at community.at eigen.at \ cliques.at attributes.at arpack.at bipartite.at centralization.at \ version.at separators.at hrg.at microscopic.at mt.at random.at scg.at \ matching.at qsort.at coloring.at embedding.at TESTSUITE = testsuite AUTOTEST = $(AUTOM4TE) --language=autotest $(TESTSUITE): $(srcdir)/package.m4 $(TESTSUITE_AT) $(AUTOTEST) -I $(top_srcdir)/tests $(top_srcdir)/tests/testsuite.at -o $@.tmp mv $@.tmp $@ clean-local: $(TESTSUITE) $(SHELL) $(TESTSUITE) --clean check-local: atconfig atlocal $(TESTSUITE) if [ ! -f $(TESTSUITE) ]; then cp $(top_srcdir)/tests/testsuite .; fi $(SHELL) $(TESTSUITE) # Run the test suite on the *installed* tree. installcheck-local: $(SHELL) $(TESTSUITE) AUTOTEST_PATH=$(exec_prefix)/bin python-igraph-0.8.0/vendor/source/igraph/tests/version.at0000644000076500000240000000206713524616145024000 0ustar tamasstaff00000000000000# Query version number # Test suite for the IGraph library. # Copyright (C) 2010-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA # Macros AT_BANNER([[igraph version number.]]) AT_SETUP([Simple version query (igraph_version): ]) AT_KEYWORDS([version igraph_version]) AT_COMPILE_CHECK([simple/igraph_version.c]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/attributes.at0000644000076500000240000000430313524616145024474 0ustar tamasstaff00000000000000# Check functions for graph, vertex and edge attributes # Test suite for the IGraph library. # Copyright (C) 2007-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([[Attributes from C]]) AT_SETUP([Reading a Pajek file with attributes:]) AT_KEYWORDS([pajek attributes]) AT_COMPILE_CHECK([simple/cattributes.c], [simple/cattributes.out], [simple/LINKS.NET]) AT_CLEANUP AT_SETUP([Writing an attributed graph in GML and GraphML:]) AT_KEYWORDS([gml GML graphml GraphML attributes]) AT_COMPILE_CHECK([simple/cattributes2.c], [simple/cattributes2.out]) AT_CLEANUP AT_SETUP([Combining numeric attributes:]) AT_KEYWORDS([attributes combination combining]) AT_COMPILE_CHECK([simple/cattributes3.c], [simple/cattributes3.out]) AT_CLEANUP AT_SETUP([Combining string attributes:]) AT_KEYWORDS([attributes combination combining]) AT_COMPILE_CHECK([simple/cattributes4.c], [simple/cattributes4.out]) AT_CLEANUP AT_SETUP([Combining Boolean attributes:]) AT_KEYWORDS([attributes combination combining]) AT_COMPILE_CHECK([simple/cattributes5.c], [simple/cattributes5.out]) AT_CLEANUP AT_SETUP([Boolean graph attribute bug:]) AT_KEYWORDS([attributes bool boolean logical bug]) AT_COMPILE_CHECK([simple/cattr_bool_bug.c], [], [simple/cattr_bool_bug.graphml]) AT_CLEANUP AT_SETUP([Boolean graph attribute bug 2:]) AT_KEYWORDS([attributes bool boolean logical bug]) AT_COMPILE_CHECK([tests/cattr_bool_bug2.c], [tests/cattr_bool_bug2.out], [tests/cattr_bool_bug2.graphml]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/embedding.at0000644000076500000240000000213713524616145024227 0ustar tamasstaff00000000000000# Embeddings # Test suite for the igraph library. # Copyright (C) 2013 Gabor Csardi # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([[Embeddings]]) AT_SETUP([Adjacency spectral embedding (igraph_adjacency_spectral_embedding): ]) AT_KEYWORDS([adjacency spectral embedding]) AT_COMPILE_CHECK([simple/igraph_adjacency_spectral_embedding.c], [simple/igraph_adjacency_spectral_embedding.out]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/coloring.at0000644000076500000240000000217513524616145024127 0ustar tamasstaff00000000000000# Check the functions related to graph coloring # Test suite for the IGraph library. # Copyright (C) 2005-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA # Macros AT_BANNER([[Graph coloring]]) AT_SETUP([Greedy vertex coloring (igraph_vertex_coloring_greedy): ]) #AT_KEYWORDS([igraph_cliques, igraph_maximal_cliques, igraph_clique_number]) AT_COMPILE_CHECK([simple/igraph_coloring.c]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/flow.at0000644000076500000240000000456213524616145023264 0ustar tamasstaff00000000000000# Check maximum flow and related functions # Test suite for the IGraph library. # Copyright (C) 2005-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([[Maximum flows and such]]) AT_SETUP([Maximum flow value (igraph_maxflow_value): ]) AT_KEYWORDS([maximum flow maxflow minimum cut]) AT_COMPILE_CHECK([simple/flow.c], [], [simple/ak-4102.max]) AT_CLEANUP AT_SETUP([Maximum flow (igraph_maxflow): ]) AT_KEYWORDS([maximum flow maxflow minimum cut]) AT_COMPILE_CHECK([simple/flow2.c], [simple/flow2.out], [simple/ak-4102.max]) AT_CLEANUP AT_SETUP([Minimum cut (igraph_mincut): ]) AT_KEYWORDS([minimum cut Stoer-Wagner]) AT_COMPILE_CHECK([simple/igraph_mincut.c], [simple/igraph_mincut.out]) AT_CLEANUP AT_SETUP([Even-Tarjan reduction (igraph_even_tarjan_reduction): ]) AT_KEYWORDS([Even Tarjan reduction vertex cut separator]) AT_COMPILE_CHECK([simple/even_tarjan.c]) AT_CLEANUP AT_SETUP([Dominator tree of a flow graph (igraph_dominator_tree): ]) AT_KEYWORDS([dominator tree]) AT_COMPILE_CHECK([simple/dominator_tree.c], [simple/dominator_tree.out]) AT_CLEANUP AT_SETUP([All s-t cuts of a graph (igraph_all_st_cuts): ]) AT_KEYWORDS([s-t cut]) AT_COMPILE_CHECK([simple/igraph_all_st_cuts.c], [simple/igraph_all_st_cuts.out], [], [INTERNAL]) AT_CLEANUP AT_SETUP([All minimal s-t cuts of a graph (igraph_all_st_mincuts): ]) AT_KEYWORDS([minimal s-t cut]) AT_COMPILE_CHECK([simple/igraph_all_st_mincuts.c], [simple/igraph_all_st_mincuts.out]) AT_CLEANUP AT_SETUP([Gomory-Hu tree (igraph_gomory_hu_tree): ]) AT_KEYWORDS([Gomory-Hu tree]) AT_COMPILE_CHECK([simple/igraph_gomory_hu_tree.c]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/other.at0000644000076500000240000000252513524616145023433 0ustar tamasstaff00000000000000# Check functions for other miscellaneous functions # Test suite for the IGraph library. # Copyright (C) 2005-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([[Miscellaneous functions]]) AT_SETUP([Convex hull calculation (igraph_convex_hull):]) AT_KEYWORDS([igraph_convex_hull other]) AT_COMPILE_CHECK([simple/igraph_convex_hull.c], [simple/igraph_convex_hull.out]) AT_CLEANUP AT_SETUP([Fitting power-law distributions (igraph_power_law_fit):]) AT_KEYWORDS([igraph_power_law_fit other power law fitting]) AT_COMPILE_CHECK([simple/igraph_power_law_fit.c], [simple/igraph_power_law_fit.out]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/hrg.at0000644000076500000240000000270413524616145023071 0ustar tamasstaff00000000000000# Hierarchical random graphs # Test suite for the IGraph library. # Copyright (C) 2011-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([[Hierarchical random graphs]]) AT_SETUP([Fitting a hierarchical model (igraph_hrg_fit) :]) AT_KEYWORDS([hierarchical random graph]) AT_COMPILE_CHECK([simple/igraph_hrg.c]) AT_CLEANUP AT_SETUP([Consensus tree (igraph_hrg_consensus) :]) AT_KEYWORDS([hierarchical random graph consensus tree]) AT_COMPILE_CHECK([simple/igraph_hrg2.c], [simple/igraph_hrg2.out]) AT_CLEANUP AT_SETUP([Missing edge prediction (igraph_hrg_predict) :]) AT_KEYWORDS([hierarchical random graph missing edge prediction]) AT_COMPILE_CHECK([simple/igraph_hrg3.c], [simple/igraph_hrg3.out]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/types.at0000644000076500000240000001616013524616145023456 0ustar tamasstaff00000000000000# Check the utility types (vector_t, etc.) # Test suite for the IGraph library. # Copyright (C) 2005-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([[Utility types (vector_t, etc.)]]) AT_SETUP([Vector (vector_t): ]) AT_KEYWORDS([vector vector_t]) AT_COMPILE_CHECK([simple/vector.c], [simple/vector.out]) AT_CLEANUP AT_SETUP([Vector (more) (vector_t): ]) AT_KEYWORDS([vector vector_t]) AT_COMPILE_CHECK([simple/vector2.c], [simple/vector2.out]) AT_CLEANUP AT_SETUP([Vector (even more) (vector_t): ]) AT_KEYWORDS([vector vector_t]) AT_COMPILE_CHECK([simple/vector3.c]) AT_CLEANUP AT_SETUP([Matrix (matrix_t): ]) AT_KEYWORDS([matrix matrix_t]) AT_COMPILE_CHECK([simple/matrix.c], [simple/matrix.out]) AT_CLEANUP AT_SETUP([Matrix (more) (matrix_t): ]) AT_KEYWORDS([matrix matrix_t]) AT_COMPILE_CHECK([simple/matrix2.c], [simple/matrix2.out]) AT_CLEANUP AT_SETUP([Matrix (even more) (matrix_t): ]) AT_KEYWORDS([matrix matrix_t]) AT_COMPILE_CHECK([simple/matrix3.c]) AT_CLEANUP AT_SETUP([Double ended queue (dqueue_t): ]) AT_KEYWORDS([dqueue double queue dqueue_t]) AT_COMPILE_CHECK([simple/dqueue.c], [simple/dqueue.out]) AT_CLEANUP AT_SETUP([Vector of pointers (vector_ptr_t): ]) AT_KEYWORDS([vector pointers vector_ptr_t]) AT_COMPILE_CHECK([simple/vector_ptr.c]) AT_CLEANUP AT_SETUP([Stack (stack_t): ]) AT_KEYWORDS([stack stack_t]) AT_COMPILE_CHECK([simple/stack.c]) AT_CLEANUP AT_SETUP([Heap (heap_t): ]) AT_KEYWORDS([heap heap_t]) AT_COMPILE_CHECK([simple/heap.c]) AT_CLEANUP AT_SETUP([Indexed heap (indheap_t): ]) AT_KEYWORDS([indexed heap indheap_t]) AT_COMPILE_CHECK([simple/indheap.c], [], [], [INTERNAL]) AT_CLEANUP AT_SETUP([Doubly indexed heap (d_indheap_t): ]) AT_KEYWORDS([doubly indexed heap d_indheap_t]) AT_COMPILE_CHECK([simple/d_indheap.c], [simple/d_indheap.out], [], [INTERNAL]) AT_CLEANUP AT_SETUP([String vector (igraph_strvector_t): ]) AT_KEYWORDS([string vector igraph_strvector_t]) AT_COMPILE_CHECK([simple/igraph_strvector.c], [simple/igraph_strvector.out]) AT_CLEANUP AT_SETUP([Trie (igraph_trie_t): ]) AT_KEYWORDS([trie igraph_trie_t]) AT_COMPILE_CHECK([simple/igraph_trie.c], [simple/igraph_trie.out], [], [INTERNAL]) AT_CLEANUP AT_SETUP([Partial Sum-Tree (igraph_psumtree_t): ]) AT_KEYWORDS([partial sumtree igraph_psumtree_t]) AT_COMPILE_CHECK([simple/igraph_psumtree.c]) AT_CLEANUP AT_SETUP([Three dimensional array (igraph_array3_t): ]) AT_KEYWORDS([array array3 three dimensional array]) AT_COMPILE_CHECK([simple/igraph_array.c], [simple/igraph_array.out]) AT_CLEANUP AT_SETUP([Hash table (string->string) (igraph_hashtable_t): ]) AT_KEYWORDS([igraph_hashtable_t hash table]) AT_COMPILE_CHECK([simple/igraph_hashtable.c], [simple/igraph_hashtable.out], [], [INTERNAL]) AT_CLEANUP AT_SETUP([Special heap for minimum cuts (igraph_i_cutheap_t): ]) AT_KEYWORDS([heap minimum cut]) AT_COMPILE_CHECK([simple/igraph_i_cutheap.c], [simple/igraph_i_cutheap.out], [], [INTERNAL]) AT_CLEANUP AT_SETUP([Set (igraph_set_t): ]) AT_KEYWORDS([set igraph_set_t]) AT_COMPILE_CHECK([simple/igraph_set.c], [simple/igraph_set.out], [], [INTERNAL]) AT_CLEANUP AT_SETUP([2-way heap (igraph_2wheap_t): ]) AT_KEYWORDS([heap two-way 2-way igraph_2wheap_t]) AT_COMPILE_CHECK([simple/2wheap.c], [], [], [INTERNAL]) AT_CLEANUP AT_SETUP([Sparse matrix (igraph_sparsemat_t): ]) AT_KEYWORDS([sparse matrix igraph_sparsemat_t]) AT_COMPILE_CHECK([simple/igraph_sparsemat.c], [simple/igraph_sparsemat.out]) AT_CLEANUP AT_SETUP([Sparse matrix, multiplications (igraph_sparsemat_t): ]) AT_KEYWORDS([sparse matrix igraph_sparsemat_t]) AT_COMPILE_CHECK([simple/igraph_sparsemat2.c], [simple/igraph_sparsemat2.out], [], [INTERNAL], [-lblas]) AT_CLEANUP AT_SETUP([Sparse matrix, indexing (igraph_sparsemat_t): ]) AT_KEYWORDS([sparse matrix igraph_sparsemat_t]) AT_COMPILE_CHECK([simple/igraph_sparsemat3.c], [simple/igraph_sparsemat3.out], [], [INTERNAL]) AT_CLEANUP AT_SETUP([Sparse matrix, solvers (igraph_sparsemat_t): ]) AT_KEYWORDS([sparse matrix igraph_sparsemat_t]) AT_COMPILE_CHECK([simple/igraph_sparsemat4.c], [simple/igraph_sparsemat4.out], [], [INTERNAL]) AT_CLEANUP AT_SETUP([Sparse matrix, ARPACK eigensolver (igraph_sparsemat_t): ]) AT_KEYWORDS([sparse matrix igraph_sparsemat_t ARPACK]) AT_COMPILE_CHECK([simple/igraph_sparsemat5.c], [simple/igraph_sparsemat5.out]) AT_CLEANUP AT_SETUP([Sparse matrix, conversion to dense (igraph_sparsemat_t): ]) AT_KEYWORDS([sparse matrix igraph_sparsemat_t]) AT_COMPILE_CHECK([simple/igraph_sparsemat6.c]) AT_CLEANUP AT_SETUP([Sparse matrix, min & max (igraph_sparsemat_t): ]) AT_KEYWORDS([sparse matrix igraph_sparsemat_t]) AT_COMPILE_CHECK([simple/igraph_sparsemat7.c]) AT_CLEANUP AT_SETUP([Sparse matrix, other operations (igraph_sparsemat_t): ]) AT_KEYWORDS([sparse matrix igraph_sparsemat_t]) AT_COMPILE_CHECK([simple/igraph_sparsemat8.c]) AT_CLEANUP AT_SETUP([Sparse matrix, multiplications with dense (igraph_sparsemat_t): ]) AT_KEYWORDS([sparse matrix igraph_sparsemat_t sparse-dense dense-sparse]) AT_COMPILE_CHECK([simple/igraph_sparsemat9.c]) AT_CLEANUP AT_SETUP([Sparse matrix, is symmetric? (igraph_sparsemat_t): ]) AT_KEYWORDS([sparse matrix igraph_sparsemat_t symmetric is_symmetric]) AT_COMPILE_CHECK([simple/igraph_sparsemat_is_symmetric.c]) AT_CLEANUP AT_SETUP([Sparse matrix col/row min/max (igraph_sparsemat_t): ]) AT_KEYWORDS([sparse matrix igraph_sparsemat_t]) AT_COMPILE_CHECK([simple/igraph_sparsemat_minmax.c], [simple/igraph_sparsemat_minmax.out]) AT_CLEANUP AT_SETUP([Sparse matrix which col/row min/max (igraph_sparsemat_t): ]) AT_KEYWORDS([sparse matrix igraph_sparsemat_t minimum maximum]) AT_COMPILE_CHECK([simple/igraph_sparsemat_which_minmax.c], [simple/igraph_sparsemat_which_minmax.out]) AT_CLEANUP AT_SETUP([Another sparse matrix (igraph_spmatrix_t): ]) AT_KEYWORDS([sparse matrix igraph_spmatrix_t]) AT_COMPILE_CHECK([simple/spmatrix.c], [simple/spmatrix.out]) AT_CLEANUP AT_SETUP([Arbitrarily big integers (igraph_biguint_t): ]) AT_KEYWORDS([bignum bigint big integer arbitrarily]) AT_COMPILE_CHECK([simple/biguint.c],[simple/biguint.out],[],[INTERNAL]) AT_CLEANUP AT_SETUP([Marked double ended queue (igraph_marked_queue_t): ]) AT_KEYWORDS([dqueue queue igraph_marked_queue_t]) AT_COMPILE_CHECK([simple/igraph_marked_queue.c], [], [], [INTERNAL]) AT_CLEANUP AT_SETUP([Complex numbers (igraph_complex_t): ]) AT_KEYWORDS([complex]) AT_COMPILE_CHECK([simple/igraph_complex.c]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/motifs.at0000644000076500000240000000236113524616145023611 0ustar tamasstaff00000000000000# Check functions for motif detectors # Test suite for the IGraph library. # Copyright (C) 2005-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([[Motifs]]) AT_SETUP([RAND-ESU algorithm (igraph_motifs_randesu)]) AT_KEYWORDS([motif RAND-ESU]) AT_COMPILE_CHECK([simple/igraph_motifs_randesu.c], [simple/igraph_motifs_randesu.out]) AT_CLEANUP AT_SETUP([Triad counts (igraph_triad_census):]) AT_KEYWORDS([motif RAND-ESU]) AT_COMPILE_CHECK([simple/triad_census.c], [simple/triad_census.out]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/random.at0000644000076500000240000000345113524616145023571 0ustar tamasstaff00000000000000# Check functions for other miscellaneous functions # Test suite for the IGraph library. # Copyright (C) 2011-2012 Gabor Csardi # 334 Harvard st, Cambridge MA, 02139, USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([Random number generators]) AT_SETUP([Random seed:]) AT_KEYWORDS([RNG seed random]) AT_COMPILE_CHECK([simple/random_seed.c]) AT_CLEANUP AT_SETUP([RNG reproducibility:]) AT_KEYWORDS([RNG seed random]) AT_COMPILE_CHECK([tests/rng_reproducibility.c], [tests/rng_reproducibility.out]) AT_CLEANUP AT_SETUP([MT19937 RNG on 64 bit machines:]) AT_KEYWORDS([RNG MT19937]) AT_COMPILE_CHECK([simple/mt.c]) AT_CLEANUP AT_SETUP([Exponentially distributed random numbers:]) AT_KEYWORDS([exponential random numbers]) AT_COMPILE_CHECK([simple/igraph_rng_get_exp.c], [simple/igraph_rng_get_exp.out]) AT_CLEANUP AT_SETUP([Random sampling from consecutive sequence:]) AT_KEYWORDS([random sampling]) AT_COMPILE_CHECK([simple/igraph_random_sample.c]) AT_CLEANUP AT_SETUP([Fisher-Yates shuffle:]) AT_KEYWORDS([Fisher-Yates shuffle random permutation]) AT_COMPILE_CHECK([simple/igraph_fisher_yates_shuffle.c]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/visitors.at0000644000076500000240000000267513524616145024202 0ustar tamasstaff00000000000000# Check functions for different visitor-like functions # Test suite for the IGraph library. # Copyright (C) 2005-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([[Visitors]]) AT_SETUP([Internal breadth-first search (igraph_i_bfs):]) AT_KEYWORDS([igraph_i_bfs bfs breadth-first visitor]) AT_COMPILE_CHECK([simple/igraph_bfs.c], [simple/igraph_bfs.out]) AT_CLEANUP AT_SETUP([Breadth-first search (igraph_bfs):]) AT_KEYWORDS([igraph_bfs bfs breadth-first visitor]) AT_COMPILE_CHECK([simple/igraph_bfs2.c], [simple/igraph_bfs2.out]) AT_CLEANUP AT_SETUP([Random walk (igraph_random_edge_walk):]) AT_KEYWORDS([igraph_random_edge_walk random_walk]) AT_COMPILE_CHECK([simple/igraph_random_walk.c]) AT_CLEANUPpython-igraph-0.8.0/vendor/source/igraph/tests/layout.at0000644000076500000240000000612113532467671023632 0ustar tamasstaff00000000000000# Check functions for generating layouts # Test suite for the IGraph library. # Copyright (C) 2005-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([[Layouts]]) AT_SETUP([Grid layout (igraph_layout_grid, igraph_layout_grid_3d):]) AT_KEYWORDS([igraph_layout_grid igraph_layout_grid_3d grid layout]) AT_COMPILE_CHECK([simple/igraph_layout_grid.c], [simple/igraph_layout_grid.out]) AT_CLEANUP AT_SETUP([Large Graph Layout (igraph_layout_lgl):]) AT_KEYWORDS([igraph_layout_lgl LGL]) AT_COMPILE_CHECK([simple/igraph_layout_lgl.c]) AT_CLEANUP AT_SETUP([Reingold-Tilford tree layout (igraph_layout_reingold_tilford):]) AT_KEYWORDS([reingold tilford tree layout igraph_layout_reingold_tilford]) AT_COMPILE_CHECK([simple/igraph_layout_reingold_tilford.c], [], [simple/igraph_layout_reingold_tilford.in]) AT_CLEANUP AT_SETUP([Reingold-Tilford tree layout extended (igraph_layout_reingold_tilford):]) AT_KEYWORDS([reingold tilford tree layout igraph_layout_reingold_tilford]) AT_COMPILE_CHECK([tests/igraph_layout_reingold_tilford_extended.c], [], [tests/igraph_layout_reingold_tilford_extended.in]) AT_CLEANUP AT_SETUP([Sugiyama layout (igraph_layout_sugiyama):]) AT_KEYWORDS([sugiyama layout igraph_layout_sugiyama]) AT_COMPILE_CHECK([simple/igraph_layout_sugiyama.c], [simple/igraph_layout_sugiyama.out]) AT_CLEANUP AT_SETUP([Multidimensional scaling (igraph_layout_mds):]) AT_KEYWORDS([multidimensional scaling layout igraph_layout_mds]) AT_COMPILE_CHECK([simple/igraph_layout_mds.c], [simple/igraph_layout_mds.out]) AT_CLEANUP AT_SETUP([Covering circle and sphere (igraph_i_layout_sphere_{2,3}d):]) AT_KEYWORDS([covering circle sphere layout]) AT_COMPILE_CHECK([simple/igraph_i_layout_sphere.c]) AT_CLEANUP AT_SETUP([Merging layouts (igraph_i_layout_merge):]) AT_KEYWORDS([layout merge dla]) AT_COMPILE_CHECK([simple/igraph_layout_merge.c], [], [], [INTERNAL]) AT_CLEANUP AT_SETUP([Merging layouts 2 (igraph_i_layout_merge):]) AT_KEYWORDS([layout merge dla]) AT_COMPILE_CHECK([simple/igraph_layout_merge2.c], [simple/igraph_layout_merge2.out]) AT_CLEANUP AT_SETUP([Merging layouts 3 (igraph_i_layout_merge):]) AT_KEYWORDS([layout merge dla]) AT_COMPILE_CHECK([simple/igraph_layout_merge3.c]) AT_CLEANUP AT_SETUP([Davidson-Harel layout (igraph_layout_davidson_harel):]) AT_KEYWORDS([layout Davidson-Harel]) AT_COMPILE_CHECK([simple/igraph_layout_davidson_harel.c]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/tests/conversion.at0000644000076500000240000000323113524616145024472 0ustar tamasstaff00000000000000# Check various conversion functions # Test suite for the IGraph library. # Copyright (C) 2006-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA AT_BANNER([[Conversion functions]]) AT_SETUP([Directed to undirected (igraph_to_undirected):]) AT_KEYWORDS([igraph_to_undirected directedness undirected directed]) AT_COMPILE_CHECK([simple/igraph_to_undirected.c], [simple/igraph_to_undirected.out]) AT_CLEANUP AT_SETUP([Graphs from adjacency list (igraph_adjlist):]) AT_KEYWORDS([igraph_adjlist adjacency list adjlist]) AT_COMPILE_CHECK([simple/adjlist.c]) AT_CLEANUP AT_SETUP([Graph to Laplacian matrix (igraph_laplacian):]) AT_KEYWORDS([igraph_laplacian laplacian matrix]) AT_COMPILE_CHECK([simple/igraph_laplacian.c], [simple/igraph_laplacian.out]) AT_CLEANUP AT_SETUP([Tree to prufer sequence (igraph_to_prufer):]) AT_KEYWORDS([igraph_to_prufer]) AT_COMPILE_CHECK([simple/igraph_to_prufer.c]) AT_CLEANUP python-igraph-0.8.0/vendor/source/igraph/.editorconfig0000644000076500000240000000031713614300625023265 0ustar tamasstaff00000000000000root = true [*] charset = utf-8 end_of_line = lf insert_final_newline = true trim_trailing_whitespace = true [*.{c,cc,cpp,h,hh,hpp,pmt}] indent_style = space indent_size = 4 [Makefile] indent_style = tab python-igraph-0.8.0/vendor/source/igraph/Makefile.am0000644000076500000240000000764413614300625022656 0ustar tamasstaff00000000000000ACLOCAL_AMFLAGS = -I m4 SUBDIRS=src tests DOC_FILES = $(top_srcdir)/doc/Makefile.in \ $(top_srcdir)/doc/igraph.3 pkgconfigdir = @libdir@/pkgconfig pkgconfig_DATA = igraph.pc EXTRA_DIST = igraph.pc IGRAPH_VERSION $(top_srcdir)/include/* $(DOC_FILES) examples \ $(wildcard $(top_srcdir)/optional/glpk/*.{inc,c,h}) \ $(wildcard $(top_srcdir)/optional/glpk/{README,COPYING}) \ $(wildcard $(top_srcdir)/optional/glpk/amd/*.{c,h}) \ $(wildcard $(top_srcdir)/optional/glpk/amd/{README,COPYING}) \ $(wildcard $(top_srcdir)/optional/glpk/colamd/*.{c,h}) \ $(wildcard $(top_srcdir)/optional/glpk/colamd/{README,COPYING}) \ tests/testsuite tests/testsuite: cd tests && make testsuite install-exec-hook: if test -f $(top_builddir)/src/.libs/cygigraph-0.dll ; \ then cp $(top_builddir)/src/.libs/cygigraph-0.dll \ $(DESTDIR)$(libdir) ; fi install-info: if test -f doc/igraph.info; then d="doc"; \ else d=$(srcdir); fi; \ $(INSTALL_DATA) $$d/igraph.info $(infodir); \ if $(SHELL) -c 'install-info --version' \ >/dev/null 2>&1; then \ install-info --infodir=$(infodir) $$d/igraph.info; \ else true; fi dist-hook: rm -rf `find $(distdir)/examples -type d -name .arch-ids` MAINTAINERCLEANFILES = Makefile.in ## to make sure make deb will generate Debian packages .PHONY: framework msvc parsersources framework: all rm -rf $(top_builddir)/igraph.framework mkdir -p $(top_builddir)/igraph.framework/Versions/$(VERSION)/Headers mkdir -p $(top_builddir)/igraph.framework/Versions/$(VERSION)/Resources ln -s $(VERSION) $(top_builddir)/igraph.framework/Versions/Current ln -s Versions/Current/Headers $(top_builddir)/igraph.framework/Headers ln -s Versions/Current/Resources $(top_builddir)/igraph.framework/Resources cp $(top_srcdir)/include/* $(top_builddir)/igraph.framework/Headers/ if [ $(top_builddir) != $(top_srcdir) ]; then cp $(top_builddir)/include/* $(top_builddir)/igraph.framework/Headers/; fi cp $(top_builddir)/src/.libs/libigraph.dylib $(top_builddir)/igraph.framework/Versions/Current/igraph ln -s Versions/Current/igraph $(top_builddir)/igraph.framework/igraph cp $(top_builddir)/igraph_Info.plist $(top_builddir)/igraph.framework/Versions/Current/Resources/Info.plist parsersources: cd src; make parsersources msvc: parsersources rm -rf $(top_builddir)/igraph-$(VERSION)-msvc mkdir $(top_builddir)/igraph-$(VERSION)-msvc mkdir $(top_builddir)/igraph-$(VERSION)-msvc/include cp -r $(top_srcdir)/src $(top_builddir)/igraph-$(VERSION)-msvc/ cp -r $(top_srcdir)/include/*.h $(top_builddir)/igraph-$(VERSION)-msvc/include if [ "x$(top_srcdir)" != "x$(top_builddir)" ]; then cp -r $(top_builddir)/include $(top_builddir)/src $(top_builddir)/igraph-$(VERSION)-msvc; fi cp -r $(top_srcdir)/msvc/include $(top_builddir)/igraph-$(VERSION)-msvc/winclude cp -r $(top_srcdir)/msvc/src/f2c/arith.h $(top_builddir)/igraph-$(VERSION)-msvc/src/f2c find $(top_builddir)/igraph-$(VERSION)-msvc/src -type d \( -name .deps -o -name .libs \) | xargs -r rm -rf find $(top_builddir)/igraph-$(VERSION)-msvc/src -type f \( -name '*.o' -o -name '*.lo' -o -name '*.la' \) | xargs -r rm find $(top_builddir)/igraph-$(VERSION)-msvc/src -type f \( -name 'Makefile*' -o -name '.dirstamp' \) | xargs -r rm rm -rf $(top_builddir)/igraph-$(VERSION)-msvc/src/f2c/arith rm -rf $(top_builddir)/igraph-$(VERSION)-msvc/src/config.h rm -rf $(top_builddir)/igraph-$(VERSION)-msvc/src/*~ rm -rf $(top_builddir)/igraph-$(VERSION)-msvc/include/*~ mkdir $(top_builddir)/igraph-$(VERSION)-msvc/winlib $(top_srcdir)/tools/create-msvc-projectfile.py \ $(top_builddir)/igraph-$(VERSION)-msvc \ $(top_srcdir)/msvc/igraph.vcproj \ $(top_builddir)/src/Makefile cp $(top_srcdir)/msvc/igraph.sln $(top_builddir)/igraph-$(VERSION)-msvc cp -r $(top_srcdir)/msvc/igraphtest $(top_builddir)/igraph-$(VERSION)-msvc/test rm -rf igraph-$(VERSION)-msvc.zip zip -q -r igraph-$(VERSION)-msvc.zip igraph-$(VERSION)-msvc CLEANFILES= python-igraph-0.8.0/vendor/source/igraph/README.md0000644000076500000240000000135113614300630022062 0ustar tamasstaff00000000000000 [![Build status Linux](https://travis-ci.org/igraph/igraph.svg?branch=master)](https://travis-ci.org/igraph/igraph) [![Build status Windows](https://ci.appveyor.com/api/projects/status/github/igraph/igraph?branch=master&svg=true)](https://ci.appveyor.com/project/ntamas/igraph/branch/master) The igraph library ------------------ igraph is a library for creating and manipulating graphs. It is intended to be as powerful (ie. fast) as possible to enable the analysis of large graphs. See http://igraph.org for installation instructions, and documentation. Igraph can also be used from: - R — https://github.com/igraph/rigraph - Python — https://github.com/igraph/python-igraph - Mathematica — https://github.com/szhorvat/IGraphM python-igraph-0.8.0/vendor/source/igraph/optional/0000755000076500000240000000000013617375000022436 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/optional/glpk/0000755000076500000240000000000013617375001023374 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpapi11.c0000644000076500000240000012710313524616144025165 0ustar tamasstaff00000000000000/* glpapi11.c (utility routines) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wlogical-op-parentheses" #endif #include "glpapi.h" int glp_print_sol(glp_prob *P, const char *fname) { /* write basic solution in printable format */ XFILE *fp; GLPROW *row; GLPCOL *col; int i, j, t, ae_ind, re_ind, ret; double ae_max, re_max; xprintf("Writing basic solution to `%s'...\n", fname); fp = xfopen(fname, "w"); if (fp == NULL) { xprintf("Unable to create `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } xfprintf(fp, "%-12s%s\n", "Problem:", P->name == NULL ? "" : P->name); xfprintf(fp, "%-12s%d\n", "Rows:", P->m); xfprintf(fp, "%-12s%d\n", "Columns:", P->n); xfprintf(fp, "%-12s%d\n", "Non-zeros:", P->nnz); t = glp_get_status(P); xfprintf(fp, "%-12s%s\n", "Status:", t == GLP_OPT ? "OPTIMAL" : t == GLP_FEAS ? "FEASIBLE" : t == GLP_INFEAS ? "INFEASIBLE (INTERMEDIATE)" : t == GLP_NOFEAS ? "INFEASIBLE (FINAL)" : t == GLP_UNBND ? "UNBOUNDED" : t == GLP_UNDEF ? "UNDEFINED" : "???"); xfprintf(fp, "%-12s%s%s%.10g (%s)\n", "Objective:", P->obj == NULL ? "" : P->obj, P->obj == NULL ? "" : " = ", P->obj_val, P->dir == GLP_MIN ? "MINimum" : P->dir == GLP_MAX ? "MAXimum" : "???"); xfprintf(fp, "\n"); xfprintf(fp, " No. Row name St Activity Lower bound " " Upper bound Marginal\n"); xfprintf(fp, "------ ------------ -- ------------- ------------- " "------------- -------------\n"); for (i = 1; i <= P->m; i++) { row = P->row[i]; xfprintf(fp, "%6d ", i); if (row->name == NULL || strlen(row->name) <= 12) xfprintf(fp, "%-12s ", row->name == NULL ? "" : row->name); else xfprintf(fp, "%s\n%20s", row->name, ""); xfprintf(fp, "%s ", row->stat == GLP_BS ? "B " : row->stat == GLP_NL ? "NL" : row->stat == GLP_NU ? "NU" : row->stat == GLP_NF ? "NF" : row->stat == GLP_NS ? "NS" : "??"); xfprintf(fp, "%13.6g ", fabs(row->prim) <= 1e-9 ? 0.0 : row->prim); if (row->type == GLP_LO || row->type == GLP_DB || row->type == GLP_FX) xfprintf(fp, "%13.6g ", row->lb); else xfprintf(fp, "%13s ", ""); if (row->type == GLP_UP || row->type == GLP_DB) xfprintf(fp, "%13.6g ", row->ub); else xfprintf(fp, "%13s ", row->type == GLP_FX ? "=" : ""); if (row->stat != GLP_BS) { if (fabs(row->dual) <= 1e-9) xfprintf(fp, "%13s", "< eps"); else xfprintf(fp, "%13.6g ", row->dual); } xfprintf(fp, "\n"); } xfprintf(fp, "\n"); xfprintf(fp, " No. Column name St Activity Lower bound " " Upper bound Marginal\n"); xfprintf(fp, "------ ------------ -- ------------- ------------- " "------------- -------------\n"); for (j = 1; j <= P->n; j++) { col = P->col[j]; xfprintf(fp, "%6d ", j); if (col->name == NULL || strlen(col->name) <= 12) xfprintf(fp, "%-12s ", col->name == NULL ? "" : col->name); else xfprintf(fp, "%s\n%20s", col->name, ""); xfprintf(fp, "%s ", col->stat == GLP_BS ? "B " : col->stat == GLP_NL ? "NL" : col->stat == GLP_NU ? "NU" : col->stat == GLP_NF ? "NF" : col->stat == GLP_NS ? "NS" : "??"); xfprintf(fp, "%13.6g ", fabs(col->prim) <= 1e-9 ? 0.0 : col->prim); if (col->type == GLP_LO || col->type == GLP_DB || col->type == GLP_FX) xfprintf(fp, "%13.6g ", col->lb); else xfprintf(fp, "%13s ", ""); if (col->type == GLP_UP || col->type == GLP_DB) xfprintf(fp, "%13.6g ", col->ub); else xfprintf(fp, "%13s ", col->type == GLP_FX ? "=" : ""); if (col->stat != GLP_BS) { if (fabs(col->dual) <= 1e-9) xfprintf(fp, "%13s", "< eps"); else xfprintf(fp, "%13.6g ", col->dual); } xfprintf(fp, "\n"); } xfprintf(fp, "\n"); xfprintf(fp, "Karush-Kuhn-Tucker optimality conditions:\n"); xfprintf(fp, "\n"); _glp_check_kkt(P, GLP_SOL, GLP_KKT_PE, &ae_max, &ae_ind, &re_max, &re_ind); xfprintf(fp, "KKT.PE: max.abs.err = %.2e on row %d\n", ae_max, ae_ind); xfprintf(fp, " max.rel.err = %.2e on row %d\n", re_max, re_ind); xfprintf(fp, "%8s%s\n", "", re_max <= 1e-9 ? "High quality" : re_max <= 1e-6 ? "Medium quality" : re_max <= 1e-3 ? "Low quality" : "PRIMAL SOLUTION IS WRONG"); xfprintf(fp, "\n"); _glp_check_kkt(P, GLP_SOL, GLP_KKT_PB, &ae_max, &ae_ind, &re_max, &re_ind); xfprintf(fp, "KKT.PB: max.abs.err = %.2e on %s %d\n", ae_max, ae_ind <= P->m ? "row" : "column", ae_ind <= P->m ? ae_ind : ae_ind - P->m); xfprintf(fp, " max.rel.err = %.2e on %s %d\n", re_max, re_ind <= P->m ? "row" : "column", re_ind <= P->m ? re_ind : re_ind - P->m); xfprintf(fp, "%8s%s\n", "", re_max <= 1e-9 ? "High quality" : re_max <= 1e-6 ? "Medium quality" : re_max <= 1e-3 ? "Low quality" : "PRIMAL SOLUTION IS INFEASIBL" "E"); xfprintf(fp, "\n"); _glp_check_kkt(P, GLP_SOL, GLP_KKT_DE, &ae_max, &ae_ind, &re_max, &re_ind); xfprintf(fp, "KKT.DE: max.abs.err = %.2e on column %d\n", ae_max, ae_ind == 0 ? 0 : ae_ind - P->m); xfprintf(fp, " max.rel.err = %.2e on column %d\n", re_max, re_ind == 0 ? 0 : re_ind - P->m); xfprintf(fp, "%8s%s\n", "", re_max <= 1e-9 ? "High quality" : re_max <= 1e-6 ? "Medium quality" : re_max <= 1e-3 ? "Low quality" : "DUAL SOLUTION IS WRONG"); xfprintf(fp, "\n"); _glp_check_kkt(P, GLP_SOL, GLP_KKT_DB, &ae_max, &ae_ind, &re_max, &re_ind); xfprintf(fp, "KKT.DB: max.abs.err = %.2e on %s %d\n", ae_max, ae_ind <= P->m ? "row" : "column", ae_ind <= P->m ? ae_ind : ae_ind - P->m); xfprintf(fp, " max.rel.err = %.2e on %s %d\n", re_max, re_ind <= P->m ? "row" : "column", re_ind <= P->m ? re_ind : re_ind - P->m); xfprintf(fp, "%8s%s\n", "", re_max <= 1e-9 ? "High quality" : re_max <= 1e-6 ? "Medium quality" : re_max <= 1e-3 ? "Low quality" : "DUAL SOLUTION IS INFEASIBLE") ; xfprintf(fp, "\n"); xfprintf(fp, "End of output\n"); xfflush(fp); if (xferror(fp)) { xprintf("Write error on `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } ret = 0; done: if (fp != NULL) xfclose(fp); return ret; } /*********************************************************************** * NAME * * glp_read_sol - read basic solution from text file * * SYNOPSIS * * int glp_read_sol(glp_prob *lp, const char *fname); * * DESCRIPTION * * The routine glp_read_sol reads basic solution from a text file whose * name is specified by the parameter fname into the problem object. * * For the file format see description of the routine glp_write_sol. * * RETURNS * * On success the routine returns zero, otherwise non-zero. */ int glp_read_sol(glp_prob *lp, const char *fname) { glp_data *data; jmp_buf jump; int i, j, k, ret = 0; xprintf("Reading basic solution from `%s'...\n", fname); data = glp_sdf_open_file(fname); if (data == NULL) { ret = 1; goto done; } if (setjmp(jump)) { ret = 1; goto done; } glp_sdf_set_jump(data, jump); /* number of rows, number of columns */ k = glp_sdf_read_int(data); if (k != lp->m) glp_sdf_error(data, "wrong number of rows\n"); k = glp_sdf_read_int(data); if (k != lp->n) glp_sdf_error(data, "wrong number of columns\n"); /* primal status, dual status, objective value */ k = glp_sdf_read_int(data); if (!(k == GLP_UNDEF || k == GLP_FEAS || k == GLP_INFEAS || k == GLP_NOFEAS)) glp_sdf_error(data, "invalid primal status\n"); lp->pbs_stat = k; k = glp_sdf_read_int(data); if (!(k == GLP_UNDEF || k == GLP_FEAS || k == GLP_INFEAS || k == GLP_NOFEAS)) glp_sdf_error(data, "invalid dual status\n"); lp->dbs_stat = k; lp->obj_val = glp_sdf_read_num(data); /* rows (auxiliary variables) */ for (i = 1; i <= lp->m; i++) { GLPROW *row = lp->row[i]; /* status, primal value, dual value */ k = glp_sdf_read_int(data); if (!(k == GLP_BS || k == GLP_NL || k == GLP_NU || k == GLP_NF || k == GLP_NS)) glp_sdf_error(data, "invalid row status\n"); glp_set_row_stat(lp, i, k); row->prim = glp_sdf_read_num(data); row->dual = glp_sdf_read_num(data); } /* columns (structural variables) */ for (j = 1; j <= lp->n; j++) { GLPCOL *col = lp->col[j]; /* status, primal value, dual value */ k = glp_sdf_read_int(data); if (!(k == GLP_BS || k == GLP_NL || k == GLP_NU || k == GLP_NF || k == GLP_NS)) glp_sdf_error(data, "invalid column status\n"); glp_set_col_stat(lp, j, k); col->prim = glp_sdf_read_num(data); col->dual = glp_sdf_read_num(data); } xprintf("%d lines were read\n", glp_sdf_line(data)); done: if (ret) lp->pbs_stat = lp->dbs_stat = GLP_UNDEF; if (data != NULL) glp_sdf_close_file(data); return ret; } /*********************************************************************** * NAME * * glp_write_sol - write basic solution to text file * * SYNOPSIS * * int glp_write_sol(glp_prob *lp, const char *fname); * * DESCRIPTION * * The routine glp_write_sol writes the current basic solution to a * text file whose name is specified by the parameter fname. This file * can be read back with the routine glp_read_sol. * * RETURNS * * On success the routine returns zero, otherwise non-zero. * * FILE FORMAT * * The file created by the routine glp_write_sol is a plain text file, * which contains the following information: * * m n * p_stat d_stat obj_val * r_stat[1] r_prim[1] r_dual[1] * . . . * r_stat[m] r_prim[m] r_dual[m] * c_stat[1] c_prim[1] c_dual[1] * . . . * c_stat[n] c_prim[n] c_dual[n] * * where: * m is the number of rows (auxiliary variables); * n is the number of columns (structural variables); * p_stat is the primal status of the basic solution (GLP_UNDEF = 1, * GLP_FEAS = 2, GLP_INFEAS = 3, or GLP_NOFEAS = 4); * d_stat is the dual status of the basic solution (GLP_UNDEF = 1, * GLP_FEAS = 2, GLP_INFEAS = 3, or GLP_NOFEAS = 4); * obj_val is the objective value; * r_stat[i], i = 1,...,m, is the status of i-th row (GLP_BS = 1, * GLP_NL = 2, GLP_NU = 3, GLP_NF = 4, or GLP_NS = 5); * r_prim[i], i = 1,...,m, is the primal value of i-th row; * r_dual[i], i = 1,...,m, is the dual value of i-th row; * c_stat[j], j = 1,...,n, is the status of j-th column (GLP_BS = 1, * GLP_NL = 2, GLP_NU = 3, GLP_NF = 4, or GLP_NS = 5); * c_prim[j], j = 1,...,n, is the primal value of j-th column; * c_dual[j], j = 1,...,n, is the dual value of j-th column. */ int glp_write_sol(glp_prob *lp, const char *fname) { XFILE *fp; int i, j, ret = 0; xprintf("Writing basic solution to `%s'...\n", fname); fp = xfopen(fname, "w"); if (fp == NULL) { xprintf("Unable to create `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } /* number of rows, number of columns */ xfprintf(fp, "%d %d\n", lp->m, lp->n); /* primal status, dual status, objective value */ xfprintf(fp, "%d %d %.*g\n", lp->pbs_stat, lp->dbs_stat, DBL_DIG, lp->obj_val); /* rows (auxiliary variables) */ for (i = 1; i <= lp->m; i++) { GLPROW *row = lp->row[i]; /* status, primal value, dual value */ xfprintf(fp, "%d %.*g %.*g\n", row->stat, DBL_DIG, row->prim, DBL_DIG, row->dual); } /* columns (structural variables) */ for (j = 1; j <= lp->n; j++) { GLPCOL *col = lp->col[j]; /* status, primal value, dual value */ xfprintf(fp, "%d %.*g %.*g\n", col->stat, DBL_DIG, col->prim, DBL_DIG, col->dual); } xfflush(fp); if (xferror(fp)) { xprintf("Write error on `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } xprintf("%d lines were written\n", 2 + lp->m + lp->n); done: if (fp != NULL) xfclose(fp); return ret; } /**********************************************************************/ static char *format(char buf[13+1], double x) { /* format floating-point number in MPS/360-like style */ if (x == -DBL_MAX) strcpy(buf, " -Inf"); else if (x == +DBL_MAX) strcpy(buf, " +Inf"); else if (fabs(x) <= 999999.99998) { sprintf(buf, "%13.5f", x); #if 1 if (strcmp(buf, " 0.00000") == 0 || strcmp(buf, " -0.00000") == 0) strcpy(buf, " . "); else if (memcmp(buf, " 0.", 8) == 0) memcpy(buf, " .", 8); else if (memcmp(buf, " -0.", 8) == 0) memcpy(buf, " -.", 8); #endif } else sprintf(buf, "%13.6g", x); return buf; } int glp_print_ranges(glp_prob *P, int len, const int list[], int flags, const char *fname) { /* print sensitivity analysis report */ XFILE *fp = NULL; GLPROW *row; GLPCOL *col; int m, n, pass, k, t, numb, type, stat, var1, var2, count, page, ret; double lb, ub, slack, coef, prim, dual, value1, value2, coef1, coef2, obj1, obj2; const char *name, *limit; char buf[13+1]; /* sanity checks */ if (P == NULL || P->magic != GLP_PROB_MAGIC) xerror("glp_print_ranges: P = %p; invalid problem object\n", P); m = P->m, n = P->n; if (len < 0) xerror("glp_print_ranges: len = %d; invalid list length\n", len); if (len > 0) { if (list == NULL) xerror("glp_print_ranges: list = %p: invalid parameter\n", list); for (t = 1; t <= len; t++) { k = list[t]; if (!(1 <= k && k <= m+n)) xerror("glp_print_ranges: list[%d] = %d; row/column numb" "er out of range\n", t, k); } } if (flags != 0) xerror("glp_print_ranges: flags = %d; invalid parameter\n", flags); if (fname == NULL) xerror("glp_print_ranges: fname = %p; invalid parameter\n", fname); if (glp_get_status(P) != GLP_OPT) { xprintf("glp_print_ranges: optimal basic solution required\n"); ret = 1; goto done; } if (!glp_bf_exists(P)) { xprintf("glp_print_ranges: basis factorization required\n"); ret = 2; goto done; } /* start reporting */ xprintf("Write sensitivity analysis report to `%s'...\n", fname); fp = xfopen(fname, "w"); if (fp == NULL) { xprintf("Unable to create `%s' - %s\n", fname, xerrmsg()); ret = 3; goto done; } page = count = 0; for (pass = 1; pass <= 2; pass++) for (t = 1; t <= (len == 0 ? m+n : len); t++) { if (t == 1) count = 0; k = (len == 0 ? t : list[t]); if (pass == 1 && k > m || pass == 2 && k <= m) continue; if (count == 0) { xfprintf(fp, "GLPK %-4s - SENSITIVITY ANALYSIS REPORT%73sPa" "ge%4d\n", glp_version(), "", ++page); xfprintf(fp, "\n"); xfprintf(fp, "%-12s%s\n", "Problem:", P->name == NULL ? "" : P->name); xfprintf(fp, "%-12s%s%s%.10g (%s)\n", "Objective:", P->obj == NULL ? "" : P->obj, P->obj == NULL ? "" : " = ", P->obj_val, P->dir == GLP_MIN ? "MINimum" : P->dir == GLP_MAX ? "MAXimum" : "???"); xfprintf(fp, "\n"); xfprintf(fp, "%6s %-12s %2s %13s %13s %13s %13s %13s %13s " "%s\n", "No.", pass == 1 ? "Row name" : "Column name", "St", "Activity", pass == 1 ? "Slack" : "Obj coef", "Lower bound", "Activity", "Obj coef", "Obj value at", "Limiting"); xfprintf(fp, "%6s %-12s %2s %13s %13s %13s %13s %13s %13s " "%s\n", "", "", "", "", "Marginal", "Upper bound", "range", "range", "break point", "variable"); xfprintf(fp, "------ ------------ -- ------------- --------" "----- ------------- ------------- ------------- ------" "------- ------------\n"); } if (pass == 1) { numb = k; xassert(1 <= numb && numb <= m); row = P->row[numb]; name = row->name; type = row->type; lb = glp_get_row_lb(P, numb); ub = glp_get_row_ub(P, numb); coef = 0.0; stat = row->stat; prim = row->prim; if (type == GLP_FR) slack = - prim; else if (type == GLP_LO) slack = lb - prim; else if (type == GLP_UP || type == GLP_DB || type == GLP_FX) slack = ub - prim; dual = row->dual; } else { numb = k - m; xassert(1 <= numb && numb <= n); col = P->col[numb]; name = col->name; lb = glp_get_col_lb(P, numb); ub = glp_get_col_ub(P, numb); coef = col->coef; stat = col->stat; prim = col->prim; slack = 0.0; dual = col->dual; } if (stat != GLP_BS) { glp_analyze_bound(P, k, &value1, &var1, &value2, &var2); if (stat == GLP_NF) coef1 = coef2 = coef; else if (stat == GLP_NS) coef1 = -DBL_MAX, coef2 = +DBL_MAX; else if (stat == GLP_NL && P->dir == GLP_MIN || stat == GLP_NU && P->dir == GLP_MAX) coef1 = coef - dual, coef2 = +DBL_MAX; else coef1 = -DBL_MAX, coef2 = coef - dual; if (value1 == -DBL_MAX) { if (dual < -1e-9) obj1 = +DBL_MAX; else if (dual > +1e-9) obj1 = -DBL_MAX; else obj1 = P->obj_val; } else obj1 = P->obj_val + dual * (value1 - prim); if (value2 == +DBL_MAX) { if (dual < -1e-9) obj2 = -DBL_MAX; else if (dual > +1e-9) obj2 = +DBL_MAX; else obj2 = P->obj_val; } else obj2 = P->obj_val + dual * (value2 - prim); } else { glp_analyze_coef(P, k, &coef1, &var1, &value1, &coef2, &var2, &value2); if (coef1 == -DBL_MAX) { if (prim < -1e-9) obj1 = +DBL_MAX; else if (prim > +1e-9) obj1 = -DBL_MAX; else obj1 = P->obj_val; } else obj1 = P->obj_val + (coef1 - coef) * prim; if (coef2 == +DBL_MAX) { if (prim < -1e-9) obj2 = -DBL_MAX; else if (prim > +1e-9) obj2 = +DBL_MAX; else obj2 = P->obj_val; } else obj2 = P->obj_val + (coef2 - coef) * prim; } /*** first line ***/ /* row/column number */ xfprintf(fp, "%6d", numb); /* row/column name */ xfprintf(fp, " %-12.12s", name == NULL ? "" : name); if (name != NULL && strlen(name) > 12) xfprintf(fp, "%s\n%6s %12s", name+12, "", ""); /* row/column status */ xfprintf(fp, " %2s", stat == GLP_BS ? "BS" : stat == GLP_NL ? "NL" : stat == GLP_NU ? "NU" : stat == GLP_NF ? "NF" : stat == GLP_NS ? "NS" : "??"); /* row/column activity */ xfprintf(fp, " %s", format(buf, prim)); /* row slack, column objective coefficient */ xfprintf(fp, " %s", format(buf, k <= m ? slack : coef)); /* row/column lower bound */ xfprintf(fp, " %s", format(buf, lb)); /* row/column activity range */ xfprintf(fp, " %s", format(buf, value1)); /* row/column objective coefficient range */ xfprintf(fp, " %s", format(buf, coef1)); /* objective value at break point */ xfprintf(fp, " %s", format(buf, obj1)); /* limiting variable name */ if (var1 != 0) { if (var1 <= m) limit = glp_get_row_name(P, var1); else limit = glp_get_col_name(P, var1 - m); if (limit != NULL) xfprintf(fp, " %s", limit); } xfprintf(fp, "\n"); /*** second line ***/ xfprintf(fp, "%6s %-12s %2s %13s", "", "", "", ""); /* row/column reduced cost */ xfprintf(fp, " %s", format(buf, dual)); /* row/column upper bound */ xfprintf(fp, " %s", format(buf, ub)); /* row/column activity range */ xfprintf(fp, " %s", format(buf, value2)); /* row/column objective coefficient range */ xfprintf(fp, " %s", format(buf, coef2)); /* objective value at break point */ xfprintf(fp, " %s", format(buf, obj2)); /* limiting variable name */ if (var2 != 0) { if (var2 <= m) limit = glp_get_row_name(P, var2); else limit = glp_get_col_name(P, var2 - m); if (limit != NULL) xfprintf(fp, " %s", limit); } xfprintf(fp, "\n"); xfprintf(fp, "\n"); /* print 10 items per page */ count = (count + 1) % 10; } xfprintf(fp, "End of report\n"); xfflush(fp); if (xferror(fp)) { xprintf("Write error on `%s' - %s\n", fname, xerrmsg()); ret = 4; goto done; } ret = 0; done: if (fp != NULL) xfclose(fp); return ret; } /**********************************************************************/ int glp_print_ipt(glp_prob *P, const char *fname) { /* write interior-point solution in printable format */ XFILE *fp; GLPROW *row; GLPCOL *col; int i, j, t, ae_ind, re_ind, ret; double ae_max, re_max; xprintf("Writing interior-point solution to `%s'...\n", fname); fp = xfopen(fname, "w"); if (fp == NULL) { xprintf("Unable to create `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } xfprintf(fp, "%-12s%s\n", "Problem:", P->name == NULL ? "" : P->name); xfprintf(fp, "%-12s%d\n", "Rows:", P->m); xfprintf(fp, "%-12s%d\n", "Columns:", P->n); xfprintf(fp, "%-12s%d\n", "Non-zeros:", P->nnz); t = glp_ipt_status(P); xfprintf(fp, "%-12s%s\n", "Status:", t == GLP_OPT ? "OPTIMAL" : t == GLP_UNDEF ? "UNDEFINED" : t == GLP_INFEAS ? "INFEASIBLE (INTERMEDIATE)" : t == GLP_NOFEAS ? "INFEASIBLE (FINAL)" : "???"); xfprintf(fp, "%-12s%s%s%.10g (%s)\n", "Objective:", P->obj == NULL ? "" : P->obj, P->obj == NULL ? "" : " = ", P->ipt_obj, P->dir == GLP_MIN ? "MINimum" : P->dir == GLP_MAX ? "MAXimum" : "???"); xfprintf(fp, "\n"); xfprintf(fp, " No. Row name Activity Lower bound " " Upper bound Marginal\n"); xfprintf(fp, "------ ------------ ------------- ------------- " "------------- -------------\n"); for (i = 1; i <= P->m; i++) { row = P->row[i]; xfprintf(fp, "%6d ", i); if (row->name == NULL || strlen(row->name) <= 12) xfprintf(fp, "%-12s ", row->name == NULL ? "" : row->name); else xfprintf(fp, "%s\n%20s", row->name, ""); xfprintf(fp, "%3s", ""); xfprintf(fp, "%13.6g ", fabs(row->pval) <= 1e-9 ? 0.0 : row->pval); if (row->type == GLP_LO || row->type == GLP_DB || row->type == GLP_FX) xfprintf(fp, "%13.6g ", row->lb); else xfprintf(fp, "%13s ", ""); if (row->type == GLP_UP || row->type == GLP_DB) xfprintf(fp, "%13.6g ", row->ub); else xfprintf(fp, "%13s ", row->type == GLP_FX ? "=" : ""); if (fabs(row->dval) <= 1e-9) xfprintf(fp, "%13s", "< eps"); else xfprintf(fp, "%13.6g ", row->dval); xfprintf(fp, "\n"); } xfprintf(fp, "\n"); xfprintf(fp, " No. Column name Activity Lower bound " " Upper bound Marginal\n"); xfprintf(fp, "------ ------------ ------------- ------------- " "------------- -------------\n"); for (j = 1; j <= P->n; j++) { col = P->col[j]; xfprintf(fp, "%6d ", j); if (col->name == NULL || strlen(col->name) <= 12) xfprintf(fp, "%-12s ", col->name == NULL ? "" : col->name); else xfprintf(fp, "%s\n%20s", col->name, ""); xfprintf(fp, "%3s", ""); xfprintf(fp, "%13.6g ", fabs(col->pval) <= 1e-9 ? 0.0 : col->pval); if (col->type == GLP_LO || col->type == GLP_DB || col->type == GLP_FX) xfprintf(fp, "%13.6g ", col->lb); else xfprintf(fp, "%13s ", ""); if (col->type == GLP_UP || col->type == GLP_DB) xfprintf(fp, "%13.6g ", col->ub); else xfprintf(fp, "%13s ", col->type == GLP_FX ? "=" : ""); if (fabs(col->dval) <= 1e-9) xfprintf(fp, "%13s", "< eps"); else xfprintf(fp, "%13.6g ", col->dval); xfprintf(fp, "\n"); } xfprintf(fp, "\n"); xfprintf(fp, "Karush-Kuhn-Tucker optimality conditions:\n"); xfprintf(fp, "\n"); _glp_check_kkt(P, GLP_IPT, GLP_KKT_PE, &ae_max, &ae_ind, &re_max, &re_ind); xfprintf(fp, "KKT.PE: max.abs.err = %.2e on row %d\n", ae_max, ae_ind); xfprintf(fp, " max.rel.err = %.2e on row %d\n", re_max, re_ind); xfprintf(fp, "%8s%s\n", "", re_max <= 1e-9 ? "High quality" : re_max <= 1e-6 ? "Medium quality" : re_max <= 1e-3 ? "Low quality" : "PRIMAL SOLUTION IS WRONG"); xfprintf(fp, "\n"); _glp_check_kkt(P, GLP_IPT, GLP_KKT_PB, &ae_max, &ae_ind, &re_max, &re_ind); xfprintf(fp, "KKT.PB: max.abs.err = %.2e on %s %d\n", ae_max, ae_ind <= P->m ? "row" : "column", ae_ind <= P->m ? ae_ind : ae_ind - P->m); xfprintf(fp, " max.rel.err = %.2e on %s %d\n", re_max, re_ind <= P->m ? "row" : "column", re_ind <= P->m ? re_ind : re_ind - P->m); xfprintf(fp, "%8s%s\n", "", re_max <= 1e-9 ? "High quality" : re_max <= 1e-6 ? "Medium quality" : re_max <= 1e-3 ? "Low quality" : "PRIMAL SOLUTION IS INFEASIBL" "E"); xfprintf(fp, "\n"); _glp_check_kkt(P, GLP_IPT, GLP_KKT_DE, &ae_max, &ae_ind, &re_max, &re_ind); xfprintf(fp, "KKT.DE: max.abs.err = %.2e on column %d\n", ae_max, ae_ind == 0 ? 0 : ae_ind - P->m); xfprintf(fp, " max.rel.err = %.2e on column %d\n", re_max, re_ind == 0 ? 0 : re_ind - P->m); xfprintf(fp, "%8s%s\n", "", re_max <= 1e-9 ? "High quality" : re_max <= 1e-6 ? "Medium quality" : re_max <= 1e-3 ? "Low quality" : "DUAL SOLUTION IS WRONG"); xfprintf(fp, "\n"); _glp_check_kkt(P, GLP_IPT, GLP_KKT_DB, &ae_max, &ae_ind, &re_max, &re_ind); xfprintf(fp, "KKT.DB: max.abs.err = %.2e on %s %d\n", ae_max, ae_ind <= P->m ? "row" : "column", ae_ind <= P->m ? ae_ind : ae_ind - P->m); xfprintf(fp, " max.rel.err = %.2e on %s %d\n", re_max, re_ind <= P->m ? "row" : "column", re_ind <= P->m ? re_ind : re_ind - P->m); xfprintf(fp, "%8s%s\n", "", re_max <= 1e-9 ? "High quality" : re_max <= 1e-6 ? "Medium quality" : re_max <= 1e-3 ? "Low quality" : "DUAL SOLUTION IS INFEASIBLE") ; xfprintf(fp, "\n"); xfprintf(fp, "End of output\n"); xfflush(fp); if (xferror(fp)) { xprintf("Write error on `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } ret = 0; done: if (fp != NULL) xfclose(fp); return ret; } /*********************************************************************** * NAME * * glp_read_ipt - read interior-point solution from text file * * SYNOPSIS * * int glp_read_ipt(glp_prob *lp, const char *fname); * * DESCRIPTION * * The routine glp_read_ipt reads interior-point solution from a text * file whose name is specified by the parameter fname into the problem * object. * * For the file format see description of the routine glp_write_ipt. * * RETURNS * * On success the routine returns zero, otherwise non-zero. */ int glp_read_ipt(glp_prob *lp, const char *fname) { glp_data *data; jmp_buf jump; int i, j, k, ret = 0; xprintf("Reading interior-point solution from `%s'...\n", fname); data = glp_sdf_open_file(fname); if (data == NULL) { ret = 1; goto done; } if (setjmp(jump)) { ret = 1; goto done; } glp_sdf_set_jump(data, jump); /* number of rows, number of columns */ k = glp_sdf_read_int(data); if (k != lp->m) glp_sdf_error(data, "wrong number of rows\n"); k = glp_sdf_read_int(data); if (k != lp->n) glp_sdf_error(data, "wrong number of columns\n"); /* solution status, objective value */ k = glp_sdf_read_int(data); if (!(k == GLP_UNDEF || k == GLP_OPT)) glp_sdf_error(data, "invalid solution status\n"); lp->ipt_stat = k; lp->ipt_obj = glp_sdf_read_num(data); /* rows (auxiliary variables) */ for (i = 1; i <= lp->m; i++) { GLPROW *row = lp->row[i]; /* primal value, dual value */ row->pval = glp_sdf_read_num(data); row->dval = glp_sdf_read_num(data); } /* columns (structural variables) */ for (j = 1; j <= lp->n; j++) { GLPCOL *col = lp->col[j]; /* primal value, dual value */ col->pval = glp_sdf_read_num(data); col->dval = glp_sdf_read_num(data); } xprintf("%d lines were read\n", glp_sdf_line(data)); done: if (ret) lp->ipt_stat = GLP_UNDEF; if (data != NULL) glp_sdf_close_file(data); return ret; } /*********************************************************************** * NAME * * glp_write_ipt - write interior-point solution to text file * * SYNOPSIS * * int glp_write_ipt(glp_prob *lp, const char *fname); * * DESCRIPTION * * The routine glp_write_ipt writes the current interior-point solution * to a text file whose name is specified by the parameter fname. This * file can be read back with the routine glp_read_ipt. * * RETURNS * * On success the routine returns zero, otherwise non-zero. * * FILE FORMAT * * The file created by the routine glp_write_ipt is a plain text file, * which contains the following information: * * m n * stat obj_val * r_prim[1] r_dual[1] * . . . * r_prim[m] r_dual[m] * c_prim[1] c_dual[1] * . . . * c_prim[n] c_dual[n] * * where: * m is the number of rows (auxiliary variables); * n is the number of columns (structural variables); * stat is the solution status (GLP_UNDEF = 1 or GLP_OPT = 5); * obj_val is the objective value; * r_prim[i], i = 1,...,m, is the primal value of i-th row; * r_dual[i], i = 1,...,m, is the dual value of i-th row; * c_prim[j], j = 1,...,n, is the primal value of j-th column; * c_dual[j], j = 1,...,n, is the dual value of j-th column. */ int glp_write_ipt(glp_prob *lp, const char *fname) { XFILE *fp; int i, j, ret = 0; xprintf("Writing interior-point solution to `%s'...\n", fname); fp = xfopen(fname, "w"); if (fp == NULL) { xprintf("Unable to create `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } /* number of rows, number of columns */ xfprintf(fp, "%d %d\n", lp->m, lp->n); /* solution status, objective value */ xfprintf(fp, "%d %.*g\n", lp->ipt_stat, DBL_DIG, lp->ipt_obj); /* rows (auxiliary variables) */ for (i = 1; i <= lp->m; i++) { GLPROW *row = lp->row[i]; /* primal value, dual value */ xfprintf(fp, "%.*g %.*g\n", DBL_DIG, row->pval, DBL_DIG, row->dval); } /* columns (structural variables) */ for (j = 1; j <= lp->n; j++) { GLPCOL *col = lp->col[j]; /* primal value, dual value */ xfprintf(fp, "%.*g %.*g\n", DBL_DIG, col->pval, DBL_DIG, col->dval); } xfflush(fp); if (xferror(fp)) { xprintf("Write error on `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } xprintf("%d lines were written\n", 2 + lp->m + lp->n); done: if (fp != NULL) xfclose(fp); return ret; } /**********************************************************************/ int glp_print_mip(glp_prob *P, const char *fname) { /* write MIP solution in printable format */ XFILE *fp; GLPROW *row; GLPCOL *col; int i, j, t, ae_ind, re_ind, ret; double ae_max, re_max; xprintf("Writing MIP solution to `%s'...\n", fname); fp = xfopen(fname, "w"); if (fp == NULL) { xprintf("Unable to create `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } xfprintf(fp, "%-12s%s\n", "Problem:", P->name == NULL ? "" : P->name); xfprintf(fp, "%-12s%d\n", "Rows:", P->m); xfprintf(fp, "%-12s%d (%d integer, %d binary)\n", "Columns:", P->n, glp_get_num_int(P), glp_get_num_bin(P)); xfprintf(fp, "%-12s%d\n", "Non-zeros:", P->nnz); t = glp_mip_status(P); xfprintf(fp, "%-12s%s\n", "Status:", t == GLP_OPT ? "INTEGER OPTIMAL" : t == GLP_FEAS ? "INTEGER NON-OPTIMAL" : t == GLP_NOFEAS ? "INTEGER EMPTY" : t == GLP_UNDEF ? "INTEGER UNDEFINED" : "???"); xfprintf(fp, "%-12s%s%s%.10g (%s)\n", "Objective:", P->obj == NULL ? "" : P->obj, P->obj == NULL ? "" : " = ", P->mip_obj, P->dir == GLP_MIN ? "MINimum" : P->dir == GLP_MAX ? "MAXimum" : "???"); xfprintf(fp, "\n"); xfprintf(fp, " No. Row name Activity Lower bound " " Upper bound\n"); xfprintf(fp, "------ ------------ ------------- ------------- " "-------------\n"); for (i = 1; i <= P->m; i++) { row = P->row[i]; xfprintf(fp, "%6d ", i); if (row->name == NULL || strlen(row->name) <= 12) xfprintf(fp, "%-12s ", row->name == NULL ? "" : row->name); else xfprintf(fp, "%s\n%20s", row->name, ""); xfprintf(fp, "%3s", ""); xfprintf(fp, "%13.6g ", fabs(row->mipx) <= 1e-9 ? 0.0 : row->mipx); if (row->type == GLP_LO || row->type == GLP_DB || row->type == GLP_FX) xfprintf(fp, "%13.6g ", row->lb); else xfprintf(fp, "%13s ", ""); if (row->type == GLP_UP || row->type == GLP_DB) xfprintf(fp, "%13.6g ", row->ub); else xfprintf(fp, "%13s ", row->type == GLP_FX ? "=" : ""); xfprintf(fp, "\n"); } xfprintf(fp, "\n"); xfprintf(fp, " No. Column name Activity Lower bound " " Upper bound\n"); xfprintf(fp, "------ ------------ ------------- ------------- " "-------------\n"); for (j = 1; j <= P->n; j++) { col = P->col[j]; xfprintf(fp, "%6d ", j); if (col->name == NULL || strlen(col->name) <= 12) xfprintf(fp, "%-12s ", col->name == NULL ? "" : col->name); else xfprintf(fp, "%s\n%20s", col->name, ""); xfprintf(fp, "%s ", col->kind == GLP_CV ? " " : col->kind == GLP_IV ? "*" : "?"); xfprintf(fp, "%13.6g ", fabs(col->mipx) <= 1e-9 ? 0.0 : col->mipx); if (col->type == GLP_LO || col->type == GLP_DB || col->type == GLP_FX) xfprintf(fp, "%13.6g ", col->lb); else xfprintf(fp, "%13s ", ""); if (col->type == GLP_UP || col->type == GLP_DB) xfprintf(fp, "%13.6g ", col->ub); else xfprintf(fp, "%13s ", col->type == GLP_FX ? "=" : ""); xfprintf(fp, "\n"); } xfprintf(fp, "\n"); xfprintf(fp, "Integer feasibility conditions:\n"); xfprintf(fp, "\n"); _glp_check_kkt(P, GLP_MIP, GLP_KKT_PE, &ae_max, &ae_ind, &re_max, &re_ind); xfprintf(fp, "KKT.PE: max.abs.err = %.2e on row %d\n", ae_max, ae_ind); xfprintf(fp, " max.rel.err = %.2e on row %d\n", re_max, re_ind); xfprintf(fp, "%8s%s\n", "", re_max <= 1e-9 ? "High quality" : re_max <= 1e-6 ? "Medium quality" : re_max <= 1e-3 ? "Low quality" : "SOLUTION IS WRONG"); xfprintf(fp, "\n"); _glp_check_kkt(P, GLP_MIP, GLP_KKT_PB, &ae_max, &ae_ind, &re_max, &re_ind); xfprintf(fp, "KKT.PB: max.abs.err = %.2e on %s %d\n", ae_max, ae_ind <= P->m ? "row" : "column", ae_ind <= P->m ? ae_ind : ae_ind - P->m); xfprintf(fp, " max.rel.err = %.2e on %s %d\n", re_max, re_ind <= P->m ? "row" : "column", re_ind <= P->m ? re_ind : re_ind - P->m); xfprintf(fp, "%8s%s\n", "", re_max <= 1e-9 ? "High quality" : re_max <= 1e-6 ? "Medium quality" : re_max <= 1e-3 ? "Low quality" : "SOLUTION IS INFEASIBLE"); xfprintf(fp, "\n"); xfprintf(fp, "End of output\n"); xfflush(fp); if (xferror(fp)) { xprintf("Write error on `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } ret = 0; done: if (fp != NULL) xfclose(fp); return ret; } /*********************************************************************** * NAME * * glp_read_mip - read MIP solution from text file * * SYNOPSIS * * int glp_read_mip(glp_prob *mip, const char *fname); * * DESCRIPTION * * The routine glp_read_mip reads MIP solution from a text file whose * name is specified by the parameter fname into the problem object. * * For the file format see description of the routine glp_write_mip. * * RETURNS * * On success the routine returns zero, otherwise non-zero. */ int glp_read_mip(glp_prob *mip, const char *fname) { glp_data *data; jmp_buf jump; int i, j, k, ret = 0; xprintf("Reading MIP solution from `%s'...\n", fname); data = glp_sdf_open_file(fname); if (data == NULL) { ret = 1; goto done; } if (setjmp(jump)) { ret = 1; goto done; } glp_sdf_set_jump(data, jump); /* number of rows, number of columns */ k = glp_sdf_read_int(data); if (k != mip->m) glp_sdf_error(data, "wrong number of rows\n"); k = glp_sdf_read_int(data); if (k != mip->n) glp_sdf_error(data, "wrong number of columns\n"); /* solution status, objective value */ k = glp_sdf_read_int(data); if (!(k == GLP_UNDEF || k == GLP_OPT || k == GLP_FEAS || k == GLP_NOFEAS)) glp_sdf_error(data, "invalid solution status\n"); mip->mip_stat = k; mip->mip_obj = glp_sdf_read_num(data); /* rows (auxiliary variables) */ for (i = 1; i <= mip->m; i++) { GLPROW *row = mip->row[i]; row->mipx = glp_sdf_read_num(data); } /* columns (structural variables) */ for (j = 1; j <= mip->n; j++) { GLPCOL *col = mip->col[j]; col->mipx = glp_sdf_read_num(data); if (col->kind == GLP_IV && col->mipx != floor(col->mipx)) glp_sdf_error(data, "non-integer column value"); } xprintf("%d lines were read\n", glp_sdf_line(data)); done: if (ret) mip->mip_stat = GLP_UNDEF; if (data != NULL) glp_sdf_close_file(data); return ret; } /*********************************************************************** * NAME * * glp_write_mip - write MIP solution to text file * * SYNOPSIS * * int glp_write_mip(glp_prob *mip, const char *fname); * * DESCRIPTION * * The routine glp_write_mip writes the current MIP solution to a text * file whose name is specified by the parameter fname. This file can * be read back with the routine glp_read_mip. * * RETURNS * * On success the routine returns zero, otherwise non-zero. * * FILE FORMAT * * The file created by the routine glp_write_sol is a plain text file, * which contains the following information: * * m n * stat obj_val * r_val[1] * . . . * r_val[m] * c_val[1] * . . . * c_val[n] * * where: * m is the number of rows (auxiliary variables); * n is the number of columns (structural variables); * stat is the solution status (GLP_UNDEF = 1, GLP_FEAS = 2, * GLP_NOFEAS = 4, or GLP_OPT = 5); * obj_val is the objective value; * r_val[i], i = 1,...,m, is the value of i-th row; * c_val[j], j = 1,...,n, is the value of j-th column. */ int glp_write_mip(glp_prob *mip, const char *fname) { XFILE *fp; int i, j, ret = 0; xprintf("Writing MIP solution to `%s'...\n", fname); fp = xfopen(fname, "w"); if (fp == NULL) { xprintf("Unable to create `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } /* number of rows, number of columns */ xfprintf(fp, "%d %d\n", mip->m, mip->n); /* solution status, objective value */ xfprintf(fp, "%d %.*g\n", mip->mip_stat, DBL_DIG, mip->mip_obj); /* rows (auxiliary variables) */ for (i = 1; i <= mip->m; i++) xfprintf(fp, "%.*g\n", DBL_DIG, mip->row[i]->mipx); /* columns (structural variables) */ for (j = 1; j <= mip->n; j++) xfprintf(fp, "%.*g\n", DBL_DIG, mip->col[j]->mipx); xfflush(fp); if (xferror(fp)) { xprintf("Write error on `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } xprintf("%d lines were written\n", 2 + mip->m + mip->n); done: if (fp != NULL) xfclose(fp); return ret; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpdmp.c0000644000076500000240000001712713524616144025036 0ustar tamasstaff00000000000000/* glpdmp.c (dynamic memory pool) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glpdmp.h" #if 1 /* 29/VIII-2008 */ /* some processors need data to be properly aligned; the macro align_datasize enlarges the specified size of a data item to provide a proper alignment of immediately following data */ #define align_datasize(size) ((((size) + 7) / 8) * 8) /* 8 bytes is sufficient in both 32- and 64-bit environments */ #endif #ifdef GLP_DEBUG struct info { DMP *pool; int size; }; #endif /*********************************************************************** * NAME * * dmp_create_pool - create dynamic memory pool * * SYNOPSIS * * #include "glpdmp.h" * DMP *dmp_create_pool(void); * * DESCRIPTION * * The routine dmp_create_pool creates a dynamic memory pool. * * RETURNS * * The routine returns a pointer to the memory pool created. */ DMP *dmp_create_pool(void) { DMP *pool; int k; #ifdef GLP_DEBUG xprintf("dmp_create_pool: warning: debug mode enabled\n"); #endif pool = xmalloc(sizeof(DMP)); #if 0 pool->size = 0; #endif for (k = 0; k <= 31; k++) pool->avail[k] = NULL; pool->block = NULL; pool->used = DMP_BLK_SIZE; pool->count.lo = pool->count.hi = 0; return pool; } /*********************************************************************** * NAME * * dmp_get_atom - get free atom from dynamic memory pool * * SYNOPSIS * * #include "glpdmp.h" * void *dmp_get_atom(DMP *pool, int size); * * DESCRIPTION * * The routine dmp_get_atom obtains a free atom (memory block) from the * specified memory pool. * * The parameter size is the atom size, in bytes, 1 <= size <= 256. * * Note that the free atom contains arbitrary data, not binary zeros. * * RETURNS * * The routine returns a pointer to the free atom obtained. */ void *dmp_get_atom(DMP *pool, int size) { void *atom; int k; #ifdef GLP_DEBUG int orig_size = size; #endif if (!(1 <= size && size <= 256)) xerror("dmp_get_atom: size = %d; invalid atom size\n", size); #if 0 if (!(pool->size == 0 || pool->size == size)) xerror("dmp_get_atom: size = %d; wrong atom size\n", size); #endif /* adjust the size to provide the proper data alignment */ size = align_datasize(size); #ifdef GLP_DEBUG size += align_datasize(sizeof(struct info)); #endif /* adjust the size to make it multiple of 8 bytes, if needed */ size = ((size + 7) / 8) * 8; /* determine the corresponding list of free cells */ k = size / 8 - 1; xassert(0 <= k && k <= 31); /* obtain a free atom */ if (pool->avail[k] == NULL) { /* the list of free cells is empty */ if (pool->used + size > DMP_BLK_SIZE) { /* allocate a new memory block */ void *block = xmalloc(DMP_BLK_SIZE); *(void **)block = pool->block; pool->block = block; pool->used = align_datasize(sizeof(void *)); } /* place the atom in the current memory block */ atom = (char *)pool->block + pool->used; pool->used += size; } else { /* obtain the atom from the list of free cells */ atom = pool->avail[k]; pool->avail[k] = *(void **)atom; } memset(atom, '?', size); /* increase the number of atoms which are currently in use */ pool->count.lo++; if (pool->count.lo == 0) pool->count.hi++; #ifdef GLP_DEBUG ((struct info *)atom)->pool = pool; ((struct info *)atom)->size = orig_size; atom = (char *)atom + align_datasize(sizeof(struct info)); #endif return atom; } /*********************************************************************** * NAME * * dmp_free_atom - return atom to dynamic memory pool * * SYNOPSIS * * #include "glpdmp.h" * void dmp_free_atom(DMP *pool, void *atom, int size); * * DESCRIPTION * * The routine dmp_free_atom returns the specified atom (memory block) * to the specified memory pool, making it free. * * The parameter size is the atom size, in bytes, 1 <= size <= 256. * * Note that the atom can be returned only to the pool, from which it * was obtained, and its size must be exactly the same as on obtaining * it from the pool. */ void dmp_free_atom(DMP *pool, void *atom, int size) { int k; if (!(1 <= size && size <= 256)) xerror("dmp_free_atom: size = %d; invalid atom size\n", size); #if 0 if (!(pool->size == 0 || pool->size == size)) xerror("dmp_free_atom: size = %d; wrong atom size\n", size); #endif if (pool->count.lo == 0 && pool->count.hi == 0) xerror("dmp_free_atom: pool allocation error\n"); #ifdef GLP_DEBUG atom = (char *)atom - align_datasize(sizeof(struct info)); xassert(((struct info *)atom)->pool == pool); xassert(((struct info *)atom)->size == size); #endif /* adjust the size to provide the proper data alignment */ size = align_datasize(size); #ifdef GLP_DEBUG size += align_datasize(sizeof(struct info)); #endif /* adjust the size to make it multiple of 8 bytes, if needed */ size = ((size + 7) / 8) * 8; /* determine the corresponding list of free cells */ k = size / 8 - 1; xassert(0 <= k && k <= 31); /* return the atom to the list of free cells */ *(void **)atom = pool->avail[k]; pool->avail[k] = atom; /* decrease the number of atoms which are currently in use */ pool->count.lo--; if (pool->count.lo == 0xFFFFFFFF) pool->count.hi--; return; } /*********************************************************************** * NAME * * dmp_in_use - determine how many atoms are still in use * * SYNOPSIS * * #include "glpdmp.h" * glp_long dmp_in_use(DMP *pool); * * DESCRIPTION * * The routine dmp_in_use determines how many atoms allocated from the * specified memory pool with the routine dmp_get_atom are still in use, * i.e. not returned to the pool with the routine dmp_free_atom. * * RETURNS * * The routine returns the number of atoms which are still in use. */ glp_long dmp_in_use(DMP *pool) { return pool->count; } /*********************************************************************** * NAME * * dmp_delete_pool - delete dynamic memory pool * * SYNOPSIS * * #include "glpdmp.h" * void dmp_delete_pool(DMP *pool); * * DESCRIPTION * * The routine dmp_delete_pool deletes the specified dynamic memory * pool and frees all the memory allocated to this object. */ void dmp_delete_pool(DMP *pool) { while (pool->block != NULL) { void *block = pool->block; pool->block = *(void **)block; xfree(block); } xfree(pool); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpios08.c0000644000076500000240000006741613524616144025226 0ustar tamasstaff00000000000000/* glpios08.c (clique cut generator) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wsometimes-uninitialized" #pragma clang diagnostic ignored "-Wshorten-64-to-32" #endif #include "glpios.h" static double get_row_lb(LPX *lp, int i) { /* this routine returns lower bound of row i or -DBL_MAX if the row has no lower bound */ double lb; switch (lpx_get_row_type(lp, i)) { case LPX_FR: case LPX_UP: lb = -DBL_MAX; break; case LPX_LO: case LPX_DB: case LPX_FX: lb = lpx_get_row_lb(lp, i); break; default: xassert(lp != lp); } return lb; } static double get_row_ub(LPX *lp, int i) { /* this routine returns upper bound of row i or +DBL_MAX if the row has no upper bound */ double ub; switch (lpx_get_row_type(lp, i)) { case LPX_FR: case LPX_LO: ub = +DBL_MAX; break; case LPX_UP: case LPX_DB: case LPX_FX: ub = lpx_get_row_ub(lp, i); break; default: xassert(lp != lp); } return ub; } static double get_col_lb(LPX *lp, int j) { /* this routine returns lower bound of column j or -DBL_MAX if the column has no lower bound */ double lb; switch (lpx_get_col_type(lp, j)) { case LPX_FR: case LPX_UP: lb = -DBL_MAX; break; case LPX_LO: case LPX_DB: case LPX_FX: lb = lpx_get_col_lb(lp, j); break; default: xassert(lp != lp); } return lb; } static double get_col_ub(LPX *lp, int j) { /* this routine returns upper bound of column j or +DBL_MAX if the column has no upper bound */ double ub; switch (lpx_get_col_type(lp, j)) { case LPX_FR: case LPX_LO: ub = +DBL_MAX; break; case LPX_UP: case LPX_DB: case LPX_FX: ub = lpx_get_col_ub(lp, j); break; default: xassert(lp != lp); } return ub; } static int is_binary(LPX *lp, int j) { /* this routine checks if variable x[j] is binary */ return lpx_get_col_kind(lp, j) == LPX_IV && lpx_get_col_type(lp, j) == LPX_DB && lpx_get_col_lb(lp, j) == 0.0 && lpx_get_col_ub(lp, j) == 1.0; } static double eval_lf_min(LPX *lp, int len, int ind[], double val[]) { /* this routine computes the minimum of a specified linear form sum a[j]*x[j] j using the formula: min = sum a[j]*lb[j] + sum a[j]*ub[j], j in J+ j in J- where J+ = {j: a[j] > 0}, J- = {j: a[j] < 0}, lb[j] and ub[j] are lower and upper bound of variable x[j], resp. */ int j, t; double lb, ub, sum; sum = 0.0; for (t = 1; t <= len; t++) { j = ind[t]; if (val[t] > 0.0) { lb = get_col_lb(lp, j); if (lb == -DBL_MAX) { sum = -DBL_MAX; break; } sum += val[t] * lb; } else if (val[t] < 0.0) { ub = get_col_ub(lp, j); if (ub == +DBL_MAX) { sum = -DBL_MAX; break; } sum += val[t] * ub; } else xassert(val != val); } return sum; } static double eval_lf_max(LPX *lp, int len, int ind[], double val[]) { /* this routine computes the maximum of a specified linear form sum a[j]*x[j] j using the formula: max = sum a[j]*ub[j] + sum a[j]*lb[j], j in J+ j in J- where J+ = {j: a[j] > 0}, J- = {j: a[j] < 0}, lb[j] and ub[j] are lower and upper bound of variable x[j], resp. */ int j, t; double lb, ub, sum; sum = 0.0; for (t = 1; t <= len; t++) { j = ind[t]; if (val[t] > 0.0) { ub = get_col_ub(lp, j); if (ub == +DBL_MAX) { sum = +DBL_MAX; break; } sum += val[t] * ub; } else if (val[t] < 0.0) { lb = get_col_lb(lp, j); if (lb == -DBL_MAX) { sum = +DBL_MAX; break; } sum += val[t] * lb; } else xassert(val != val); } return sum; } /*---------------------------------------------------------------------- -- probing - determine logical relation between binary variables. -- -- This routine tentatively sets a binary variable to 0 and then to 1 -- and examines whether another binary variable is caused to be fixed. -- -- The examination is based only on one row (constraint), which is the -- following: -- -- L <= sum a[j]*x[j] <= U. (1) -- j -- -- Let x[p] be a probing variable, x[q] be an examined variable. Then -- (1) can be written as: -- -- L <= sum a[j]*x[j] + a[p]*x[p] + a[q]*x[q] <= U, (2) -- j in J' -- -- where J' = {j: j != p and j != q}. -- -- Let -- -- L' = L - a[p]*x[p], (3) -- -- U' = U - a[p]*x[p], (4) -- -- where x[p] is assumed to be fixed at 0 or 1. So (2) can be rewritten -- as follows: -- -- L' <= sum a[j]*x[j] + a[q]*x[q] <= U', (5) -- j in J' -- -- from where we have: -- -- L' - sum a[j]*x[j] <= a[q]*x[q] <= U' - sum a[j]*x[j]. (6) -- j in J' j in J' -- -- Thus, -- -- min a[q]*x[q] = L' - MAX, (7) -- -- max a[q]*x[q] = U' - MIN, (8) -- -- where -- -- MIN = min sum a[j]*x[j], (9) -- j in J' -- -- MAX = max sum a[j]*x[j]. (10) -- j in J' -- -- Formulae (7) and (8) allows determining implied lower and upper -- bounds of x[q]. -- -- Parameters len, val, L and U specify the constraint (1). -- -- Parameters lf_min and lf_max specify implied lower and upper bounds -- of the linear form (1). It is assumed that these bounds are computed -- with the routines eval_lf_min and eval_lf_max (see above). -- -- Parameter p specifies the probing variable x[p], which is set to 0 -- (if set is 0) or to 1 (if set is 1). -- -- Parameter q specifies the examined variable x[q]. -- -- On exit the routine returns one of the following codes: -- -- 0 - there is no logical relation between x[p] and x[q]; -- 1 - x[q] can take only on value 0; -- 2 - x[q] can take only on value 1. */ static int probing(int len, double val[], double L, double U, double lf_min, double lf_max, int p, int set, int q) { double temp; xassert(1 <= p && p < q && q <= len); /* compute L' (3) */ if (L != -DBL_MAX && set) L -= val[p]; /* compute U' (4) */ if (U != +DBL_MAX && set) U -= val[p]; /* compute MIN (9) */ if (lf_min != -DBL_MAX) { if (val[p] < 0.0) lf_min -= val[p]; if (val[q] < 0.0) lf_min -= val[q]; } /* compute MAX (10) */ if (lf_max != +DBL_MAX) { if (val[p] > 0.0) lf_max -= val[p]; if (val[q] > 0.0) lf_max -= val[q]; } /* compute implied lower bound of x[q]; see (7), (8) */ if (val[q] > 0.0) { if (L == -DBL_MAX || lf_max == +DBL_MAX) temp = -DBL_MAX; else temp = (L - lf_max) / val[q]; } else { if (U == +DBL_MAX || lf_min == -DBL_MAX) temp = -DBL_MAX; else temp = (U - lf_min) / val[q]; } if (temp > 0.001) return 2; /* compute implied upper bound of x[q]; see (7), (8) */ if (val[q] > 0.0) { if (U == +DBL_MAX || lf_min == -DBL_MAX) temp = +DBL_MAX; else temp = (U - lf_min) / val[q]; } else { if (L == -DBL_MAX || lf_max == +DBL_MAX) temp = +DBL_MAX; else temp = (L - lf_max) / val[q]; } if (temp < 0.999) return 1; /* there is no logical relation between x[p] and x[q] */ return 0; } struct COG { /* conflict graph; it represents logical relations between binary variables and has a vertex for each binary variable and its complement, and an edge between two vertices when at most one of the variables represented by the vertices can equal one in an optimal solution */ int n; /* number of variables */ int nb; /* number of binary variables represented in the graph (note that not all binary variables can be represented); vertices which correspond to binary variables have numbers 1, ..., nb while vertices which correspond to complements of binary variables have numbers nb+1, ..., nb+nb */ int ne; /* number of edges in the graph */ int *vert; /* int vert[1+n]; */ /* if x[j] is a binary variable represented in the graph, vert[j] is the vertex number corresponding to x[j]; otherwise vert[j] is zero */ int *orig; /* int list[1:nb]; */ /* if vert[j] = k > 0, then orig[k] = j */ unsigned char *a; /* adjacency matrix of the graph having 2*nb rows and columns; only strict lower triangle is stored in dense packed form */ }; /*---------------------------------------------------------------------- -- lpx_create_cog - create the conflict graph. -- -- SYNOPSIS -- -- #include "glplpx.h" -- void *lpx_create_cog(LPX *lp); -- -- DESCRIPTION -- -- The routine lpx_create_cog creates the conflict graph for a given -- problem instance. -- -- RETURNS -- -- If the graph has been created, the routine returns a pointer to it. -- Otherwise the routine returns NULL. */ #define MAX_NB 4000 #define MAX_ROW_LEN 500 static void lpx_add_cog_edge(void *_cog, int i, int j); static void *lpx_create_cog(LPX *lp) { struct COG *cog = NULL; int m, n, nb, i, j, p, q, len, *ind, *vert, *orig; double L, U, lf_min, lf_max, *val; xprintf("Creating the conflict graph...\n"); m = lpx_get_num_rows(lp); n = lpx_get_num_cols(lp); /* determine which binary variables should be included in the conflict graph */ nb = 0; vert = xcalloc(1+n, sizeof(int)); for (j = 1; j <= n; j++) vert[j] = 0; orig = xcalloc(1+n, sizeof(int)); ind = xcalloc(1+n, sizeof(int)); val = xcalloc(1+n, sizeof(double)); for (i = 1; i <= m; i++) { L = get_row_lb(lp, i); U = get_row_ub(lp, i); if (L == -DBL_MAX && U == +DBL_MAX) continue; len = lpx_get_mat_row(lp, i, ind, val); if (len > MAX_ROW_LEN) continue; lf_min = eval_lf_min(lp, len, ind, val); lf_max = eval_lf_max(lp, len, ind, val); for (p = 1; p <= len; p++) { if (!is_binary(lp, ind[p])) continue; for (q = p+1; q <= len; q++) { if (!is_binary(lp, ind[q])) continue; if (probing(len, val, L, U, lf_min, lf_max, p, 0, q) || probing(len, val, L, U, lf_min, lf_max, p, 1, q)) { /* there is a logical relation */ /* include the first variable in the graph */ j = ind[p]; if (vert[j] == 0) nb++, vert[j] = nb, orig[nb] = j; /* incude the second variable in the graph */ j = ind[q]; if (vert[j] == 0) nb++, vert[j] = nb, orig[nb] = j; } } } } /* if the graph is either empty or has too many vertices, do not create it */ if (nb == 0 || nb > MAX_NB) { xprintf("The conflict graph is either empty or too big\n"); xfree(vert); xfree(orig); goto done; } /* create the conflict graph */ cog = xmalloc(sizeof(struct COG)); cog->n = n; cog->nb = nb; cog->ne = 0; cog->vert = vert; cog->orig = orig; len = nb + nb; /* number of vertices */ len = (len * (len - 1)) / 2; /* number of entries in triangle */ len = (len + (CHAR_BIT - 1)) / CHAR_BIT; /* bytes needed */ cog->a = xmalloc(len); memset(cog->a, 0, len); for (j = 1; j <= nb; j++) { /* add edge between variable and its complement */ lpx_add_cog_edge(cog, +orig[j], -orig[j]); } for (i = 1; i <= m; i++) { L = get_row_lb(lp, i); U = get_row_ub(lp, i); if (L == -DBL_MAX && U == +DBL_MAX) continue; len = lpx_get_mat_row(lp, i, ind, val); if (len > MAX_ROW_LEN) continue; lf_min = eval_lf_min(lp, len, ind, val); lf_max = eval_lf_max(lp, len, ind, val); for (p = 1; p <= len; p++) { if (!is_binary(lp, ind[p])) continue; for (q = p+1; q <= len; q++) { if (!is_binary(lp, ind[q])) continue; /* set x[p] to 0 and examine x[q] */ switch (probing(len, val, L, U, lf_min, lf_max, p, 0, q)) { case 0: /* no logical relation */ break; case 1: /* x[p] = 0 implies x[q] = 0 */ lpx_add_cog_edge(cog, -ind[p], +ind[q]); break; case 2: /* x[p] = 0 implies x[q] = 1 */ lpx_add_cog_edge(cog, -ind[p], -ind[q]); break; default: xassert(lp != lp); } /* set x[p] to 1 and examine x[q] */ switch (probing(len, val, L, U, lf_min, lf_max, p, 1, q)) { case 0: /* no logical relation */ break; case 1: /* x[p] = 1 implies x[q] = 0 */ lpx_add_cog_edge(cog, +ind[p], +ind[q]); break; case 2: /* x[p] = 1 implies x[q] = 1 */ lpx_add_cog_edge(cog, +ind[p], -ind[q]); break; default: xassert(lp != lp); } } } } xprintf("The conflict graph has 2*%d vertices and %d edges\n", cog->nb, cog->ne); done: xfree(ind); xfree(val); return cog; } /*---------------------------------------------------------------------- -- lpx_add_cog_edge - add edge to the conflict graph. -- -- SYNOPSIS -- -- #include "glplpx.h" -- void lpx_add_cog_edge(void *cog, int i, int j); -- -- DESCRIPTION -- -- The routine lpx_add_cog_edge adds an edge to the conflict graph. -- The edge connects x[i] (if i > 0) or its complement (if i < 0) and -- x[j] (if j > 0) or its complement (if j < 0), where i and j are -- original ordinal numbers of corresponding variables. */ static void lpx_add_cog_edge(void *_cog, int i, int j) { struct COG *cog = _cog; int k; xassert(i != j); /* determine indices of corresponding vertices */ if (i > 0) { xassert(1 <= i && i <= cog->n); i = cog->vert[i]; xassert(i != 0); } else { i = -i; xassert(1 <= i && i <= cog->n); i = cog->vert[i]; xassert(i != 0); i += cog->nb; } if (j > 0) { xassert(1 <= j && j <= cog->n); j = cog->vert[j]; xassert(j != 0); } else { j = -j; xassert(1 <= j && j <= cog->n); j = cog->vert[j]; xassert(j != 0); j += cog->nb; } /* only lower triangle is stored, so we need i > j */ if (i < j) k = i, i = j, j = k; k = ((i - 1) * (i - 2)) / 2 + (j - 1); cog->a[k / CHAR_BIT] |= (unsigned char)(1 << ((CHAR_BIT - 1) - k % CHAR_BIT)); cog->ne++; return; } /*---------------------------------------------------------------------- -- MAXIMUM WEIGHT CLIQUE -- -- Two subroutines sub() and wclique() below are intended to find a -- maximum weight clique in a given undirected graph. These subroutines -- are slightly modified version of the program WCLIQUE developed by -- Patric Ostergard and based -- on ideas from the article "P. R. J. Ostergard, A new algorithm for -- the maximum-weight clique problem, submitted for publication", which -- in turn is a generalization of the algorithm for unweighted graphs -- presented in "P. R. J. Ostergard, A fast algorithm for the maximum -- clique problem, submitted for publication". -- -- USED WITH PERMISSION OF THE AUTHOR OF THE ORIGINAL CODE. */ struct dsa { /* dynamic storage area */ int n; /* number of vertices */ int *wt; /* int wt[0:n-1]; */ /* weights */ unsigned char *a; /* adjacency matrix (packed lower triangle without main diag.) */ int record; /* weight of best clique */ int rec_level; /* number of vertices in best clique */ int *rec; /* int rec[0:n-1]; */ /* best clique so far */ int *clique; /* int clique[0:n-1]; */ /* table for pruning */ int *set; /* int set[0:n-1]; */ /* current clique */ }; #define n (dsa->n) #define wt (dsa->wt) #define a (dsa->a) #define record (dsa->record) #define rec_level (dsa->rec_level) #define rec (dsa->rec) #define clique (dsa->clique) #define set (dsa->set) #if 0 static int is_edge(struct dsa *dsa, int i, int j) { /* if there is arc (i,j), the routine returns true; otherwise false; 0 <= i, j < n */ int k; xassert(0 <= i && i < n); xassert(0 <= j && j < n); if (i == j) return 0; if (i < j) k = i, i = j, j = k; k = (i * (i - 1)) / 2 + j; return a[k / CHAR_BIT] & (unsigned char)(1 << ((CHAR_BIT - 1) - k % CHAR_BIT)); } #else #define is_edge(dsa, i, j) ((i) == (j) ? 0 : \ (i) > (j) ? is_edge1(i, j) : is_edge1(j, i)) #define is_edge1(i, j) is_edge2(((i) * ((i) - 1)) / 2 + (j)) #define is_edge2(k) (a[(k) / CHAR_BIT] & \ (unsigned char)(1 << ((CHAR_BIT - 1) - (k) % CHAR_BIT))) #endif static void sub(struct dsa *dsa, int ct, int table[], int level, int weight, int l_weight) { int i, j, k, curr_weight, left_weight, *p1, *p2, *newtable; newtable = xcalloc(n, sizeof(int)); if (ct <= 0) { /* 0 or 1 elements left; include these */ if (ct == 0) { set[level++] = table[0]; weight += l_weight; } if (weight > record) { record = weight; rec_level = level; for (i = 0; i < level; i++) rec[i] = set[i]; } goto done; } for (i = ct; i >= 0; i--) { if ((level == 0) && (i < ct)) goto done; k = table[i]; if ((level > 0) && (clique[k] <= (record - weight))) goto done; /* prune */ set[level] = k; curr_weight = weight + wt[k]; l_weight -= wt[k]; if (l_weight <= (record - curr_weight)) goto done; /* prune */ p1 = newtable; p2 = table; left_weight = 0; while (p2 < table + i) { j = *p2++; if (is_edge(dsa, j, k)) { *p1++ = j; left_weight += wt[j]; } } if (left_weight <= (record - curr_weight)) continue; sub(dsa, p1 - newtable - 1, newtable, level + 1, curr_weight, left_weight); } done: xfree(newtable); return; } static int wclique(int _n, int w[], unsigned char _a[], int sol[]) { struct dsa _dsa, *dsa = &_dsa; int i, j, p, max_wt, max_nwt, wth, *used, *nwt, *pos; glp_long timer; n = _n; wt = &w[1]; a = _a; record = 0; rec_level = 0; rec = &sol[1]; clique = xcalloc(n, sizeof(int)); set = xcalloc(n, sizeof(int)); used = xcalloc(n, sizeof(int)); nwt = xcalloc(n, sizeof(int)); pos = xcalloc(n, sizeof(int)); /* start timer */ timer = xtime(); /* order vertices */ for (i = 0; i < n; i++) { nwt[i] = 0; for (j = 0; j < n; j++) if (is_edge(dsa, i, j)) nwt[i] += wt[j]; } for (i = 0; i < n; i++) used[i] = 0; for (i = n-1; i >= 0; i--) { max_wt = -1; max_nwt = -1; for (j = 0; j < n; j++) { if ((!used[j]) && ((wt[j] > max_wt) || (wt[j] == max_wt && nwt[j] > max_nwt))) { max_wt = wt[j]; max_nwt = nwt[j]; p = j; } } pos[i] = p; used[p] = 1; for (j = 0; j < n; j++) if ((!used[j]) && (j != p) && (is_edge(dsa, p, j))) nwt[j] -= wt[p]; } /* main routine */ wth = 0; for (i = 0; i < n; i++) { wth += wt[pos[i]]; sub(dsa, i, pos, 0, 0, wth); clique[pos[i]] = record; #if 0 if (utime() >= timer + 5.0) #else if (xdifftime(xtime(), timer) >= 5.0 - 0.001) #endif { /* print current record and reset timer */ xprintf("level = %d (%d); best = %d\n", i+1, n, record); #if 0 timer = utime(); #else timer = xtime(); #endif } } xfree(clique); xfree(set); xfree(used); xfree(nwt); xfree(pos); /* return the solution found */ for (i = 1; i <= rec_level; i++) sol[i]++; return rec_level; } #undef n #undef wt #undef a #undef record #undef rec_level #undef rec #undef clique #undef set /*---------------------------------------------------------------------- -- lpx_clique_cut - generate cluque cut. -- -- SYNOPSIS -- -- #include "glplpx.h" -- int lpx_clique_cut(LPX *lp, void *cog, int ind[], double val[]); -- -- DESCRIPTION -- -- The routine lpx_clique_cut generates a clique cut using the conflict -- graph specified by the parameter cog. -- -- If a violated clique cut has been found, it has the following form: -- -- sum{j in J} a[j]*x[j] <= b. -- -- Variable indices j in J are stored in elements ind[1], ..., ind[len] -- while corresponding constraint coefficients are stored in elements -- val[1], ..., val[len], where len is returned on exit. The right-hand -- side b is stored in element val[0]. -- -- RETURNS -- -- If the cutting plane has been successfully generated, the routine -- returns 1 <= len <= n, which is the number of non-zero coefficients -- in the inequality constraint. Otherwise, the routine returns zero. */ static int lpx_clique_cut(LPX *lp, void *_cog, int ind[], double val[]) { struct COG *cog = _cog; int n = lpx_get_num_cols(lp); int j, t, v, card, temp, len = 0, *w, *sol; double x, sum, b, *vec; /* allocate working arrays */ w = xcalloc(1 + 2 * cog->nb, sizeof(int)); sol = xcalloc(1 + 2 * cog->nb, sizeof(int)); vec = xcalloc(1+n, sizeof(double)); /* assign weights to vertices of the conflict graph */ for (t = 1; t <= cog->nb; t++) { j = cog->orig[t]; x = lpx_get_col_prim(lp, j); temp = (int)(100.0 * x + 0.5); if (temp < 0) temp = 0; if (temp > 100) temp = 100; w[t] = temp; w[cog->nb + t] = 100 - temp; } /* find a clique of maximum weight */ card = wclique(2 * cog->nb, w, cog->a, sol); /* compute the clique weight for unscaled values */ sum = 0.0; for ( t = 1; t <= card; t++) { v = sol[t]; xassert(1 <= v && v <= 2 * cog->nb); if (v <= cog->nb) { /* vertex v corresponds to binary variable x[j] */ j = cog->orig[v]; x = lpx_get_col_prim(lp, j); sum += x; } else { /* vertex v corresponds to the complement of x[j] */ j = cog->orig[v - cog->nb]; x = lpx_get_col_prim(lp, j); sum += 1.0 - x; } } /* if the sum of binary variables and their complements in the clique greater than 1, the clique cut is violated */ if (sum >= 1.01) { /* construct the inquality */ for (j = 1; j <= n; j++) vec[j] = 0; b = 1.0; for (t = 1; t <= card; t++) { v = sol[t]; if (v <= cog->nb) { /* vertex v corresponds to binary variable x[j] */ j = cog->orig[v]; xassert(1 <= j && j <= n); vec[j] += 1.0; } else { /* vertex v corresponds to the complement of x[j] */ j = cog->orig[v - cog->nb]; xassert(1 <= j && j <= n); vec[j] -= 1.0; b -= 1.0; } } xassert(len == 0); for (j = 1; j <= n; j++) { if (vec[j] != 0.0) { len++; ind[len] = j, val[len] = vec[j]; } } ind[0] = 0, val[0] = b; } /* free working arrays */ xfree(w); xfree(sol); xfree(vec); /* return to the calling program */ return len; } /*---------------------------------------------------------------------- -- lpx_delete_cog - delete the conflict graph. -- -- SYNOPSIS -- -- #include "glplpx.h" -- void lpx_delete_cog(void *cog); -- -- DESCRIPTION -- -- The routine lpx_delete_cog deletes the conflict graph, which the -- parameter cog points to, freeing all the memory allocated to this -- object. */ static void lpx_delete_cog(void *_cog) { struct COG *cog = _cog; xfree(cog->vert); xfree(cog->orig); xfree(cog->a); xfree(cog); } /**********************************************************************/ void *ios_clq_init(glp_tree *tree) { /* initialize clique cut generator */ glp_prob *mip = tree->mip; xassert(mip != NULL); return lpx_create_cog(mip); } /*********************************************************************** * NAME * * ios_clq_gen - generate clique cuts * * SYNOPSIS * * #include "glpios.h" * void ios_clq_gen(glp_tree *tree, void *gen); * * DESCRIPTION * * The routine ios_clq_gen generates clique cuts for the current point * and adds them to the clique pool. */ void ios_clq_gen(glp_tree *tree, void *gen) { int n = lpx_get_num_cols(tree->mip); int len, *ind; double *val; xassert(gen != NULL); ind = xcalloc(1+n, sizeof(int)); val = xcalloc(1+n, sizeof(double)); len = lpx_clique_cut(tree->mip, gen, ind, val); if (len > 0) { /* xprintf("len = %d\n", len); */ glp_ios_add_row(tree, NULL, GLP_RF_CLQ, 0, len, ind, val, GLP_UP, val[0]); } xfree(ind); xfree(val); return; } /**********************************************************************/ void ios_clq_term(void *gen) { /* terminate clique cut generator */ xassert(gen != NULL); lpx_delete_cog(gen); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpios02.c0000644000076500000240000006463513524616144025220 0ustar tamasstaff00000000000000/* glpios02.c (preprocess current subproblem) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wsign-conversion" #endif #include "glpios.h" /*********************************************************************** * prepare_row_info - prepare row info to determine implied bounds * * Given a row (linear form) * * n * sum a[j] * x[j] (1) * j=1 * * and bounds of columns (variables) * * l[j] <= x[j] <= u[j] (2) * * this routine computes f_min, j_min, f_max, j_max needed to determine * implied bounds. * * ALGORITHM * * Let J+ = {j : a[j] > 0} and J- = {j : a[j] < 0}. * * Parameters f_min and j_min are computed as follows: * * 1) if there is no x[k] such that k in J+ and l[k] = -inf or k in J- * and u[k] = +inf, then * * f_min := sum a[j] * l[j] + sum a[j] * u[j] * j in J+ j in J- * (3) * j_min := 0 * * 2) if there is exactly one x[k] such that k in J+ and l[k] = -inf * or k in J- and u[k] = +inf, then * * f_min := sum a[j] * l[j] + sum a[j] * u[j] * j in J+\{k} j in J-\{k} * (4) * j_min := k * * 3) if there are two or more x[k] such that k in J+ and l[k] = -inf * or k in J- and u[k] = +inf, then * * f_min := -inf * (5) * j_min := 0 * * Parameters f_max and j_max are computed in a similar way as follows: * * 1) if there is no x[k] such that k in J+ and u[k] = +inf or k in J- * and l[k] = -inf, then * * f_max := sum a[j] * u[j] + sum a[j] * l[j] * j in J+ j in J- * (6) * j_max := 0 * * 2) if there is exactly one x[k] such that k in J+ and u[k] = +inf * or k in J- and l[k] = -inf, then * * f_max := sum a[j] * u[j] + sum a[j] * l[j] * j in J+\{k} j in J-\{k} * (7) * j_max := k * * 3) if there are two or more x[k] such that k in J+ and u[k] = +inf * or k in J- and l[k] = -inf, then * * f_max := +inf * (8) * j_max := 0 */ struct f_info { int j_min, j_max; double f_min, f_max; }; static void prepare_row_info(int n, const double a[], const double l[], const double u[], struct f_info *f) { int j, j_min, j_max; double f_min, f_max; xassert(n >= 0); /* determine f_min and j_min */ f_min = 0.0, j_min = 0; for (j = 1; j <= n; j++) { if (a[j] > 0.0) { if (l[j] == -DBL_MAX) { if (j_min == 0) j_min = j; else { f_min = -DBL_MAX, j_min = 0; break; } } else f_min += a[j] * l[j]; } else if (a[j] < 0.0) { if (u[j] == +DBL_MAX) { if (j_min == 0) j_min = j; else { f_min = -DBL_MAX, j_min = 0; break; } } else f_min += a[j] * u[j]; } else xassert(a != a); } f->f_min = f_min, f->j_min = j_min; /* determine f_max and j_max */ f_max = 0.0, j_max = 0; for (j = 1; j <= n; j++) { if (a[j] > 0.0) { if (u[j] == +DBL_MAX) { if (j_max == 0) j_max = j; else { f_max = +DBL_MAX, j_max = 0; break; } } else f_max += a[j] * u[j]; } else if (a[j] < 0.0) { if (l[j] == -DBL_MAX) { if (j_max == 0) j_max = j; else { f_max = +DBL_MAX, j_max = 0; break; } } else f_max += a[j] * l[j]; } else xassert(a != a); } f->f_max = f_max, f->j_max = j_max; return; } /*********************************************************************** * row_implied_bounds - determine row implied bounds * * Given a row (linear form) * * n * sum a[j] * x[j] * j=1 * * and bounds of columns (variables) * * l[j] <= x[j] <= u[j] * * this routine determines implied bounds of the row. * * ALGORITHM * * Let J+ = {j : a[j] > 0} and J- = {j : a[j] < 0}. * * The implied lower bound of the row is computed as follows: * * L' := sum a[j] * l[j] + sum a[j] * u[j] (9) * j in J+ j in J- * * and as it follows from (3), (4), and (5): * * L' := if j_min = 0 then f_min else -inf (10) * * The implied upper bound of the row is computed as follows: * * U' := sum a[j] * u[j] + sum a[j] * l[j] (11) * j in J+ j in J- * * and as it follows from (6), (7), and (8): * * U' := if j_max = 0 then f_max else +inf (12) * * The implied bounds are stored in locations LL and UU. */ static void row_implied_bounds(const struct f_info *f, double *LL, double *UU) { *LL = (f->j_min == 0 ? f->f_min : -DBL_MAX); *UU = (f->j_max == 0 ? f->f_max : +DBL_MAX); return; } /*********************************************************************** * col_implied_bounds - determine column implied bounds * * Given a row (constraint) * * n * L <= sum a[j] * x[j] <= U (13) * j=1 * * and bounds of columns (variables) * * l[j] <= x[j] <= u[j] * * this routine determines implied bounds of variable x[k]. * * It is assumed that if L != -inf, the lower bound of the row can be * active, and if U != +inf, the upper bound of the row can be active. * * ALGORITHM * * From (13) it follows that * * L <= sum a[j] * x[j] + a[k] * x[k] <= U * j!=k * or * * L - sum a[j] * x[j] <= a[k] * x[k] <= U - sum a[j] * x[j] * j!=k j!=k * * Thus, if the row lower bound L can be active, implied lower bound of * term a[k] * x[k] can be determined as follows: * * ilb(a[k] * x[k]) = min(L - sum a[j] * x[j]) = * j!=k * (14) * = L - max sum a[j] * x[j] * j!=k * * where, as it follows from (6), (7), and (8) * * / f_max - a[k] * u[k], j_max = 0, a[k] > 0 * | * | f_max - a[k] * l[k], j_max = 0, a[k] < 0 * max sum a[j] * x[j] = { * j!=k | f_max, j_max = k * | * \ +inf, j_max != 0 * * and if the upper bound U can be active, implied upper bound of term * a[k] * x[k] can be determined as follows: * * iub(a[k] * x[k]) = max(U - sum a[j] * x[j]) = * j!=k * (15) * = U - min sum a[j] * x[j] * j!=k * * where, as it follows from (3), (4), and (5) * * / f_min - a[k] * l[k], j_min = 0, a[k] > 0 * | * | f_min - a[k] * u[k], j_min = 0, a[k] < 0 * min sum a[j] * x[j] = { * j!=k | f_min, j_min = k * | * \ -inf, j_min != 0 * * Since * * ilb(a[k] * x[k]) <= a[k] * x[k] <= iub(a[k] * x[k]) * * implied lower and upper bounds of x[k] are determined as follows: * * l'[k] := if a[k] > 0 then ilb / a[k] else ulb / a[k] (16) * * u'[k] := if a[k] > 0 then ulb / a[k] else ilb / a[k] (17) * * The implied bounds are stored in locations ll and uu. */ static void col_implied_bounds(const struct f_info *f, int n, const double a[], double L, double U, const double l[], const double u[], int k, double *ll, double *uu) { double ilb, iub; xassert(n >= 0); xassert(1 <= k && k <= n); /* determine implied lower bound of term a[k] * x[k] (14) */ if (L == -DBL_MAX || f->f_max == +DBL_MAX) ilb = -DBL_MAX; else if (f->j_max == 0) { if (a[k] > 0.0) { xassert(u[k] != +DBL_MAX); ilb = L - (f->f_max - a[k] * u[k]); } else if (a[k] < 0.0) { xassert(l[k] != -DBL_MAX); ilb = L - (f->f_max - a[k] * l[k]); } else xassert(a != a); } else if (f->j_max == k) ilb = L - f->f_max; else ilb = -DBL_MAX; /* determine implied upper bound of term a[k] * x[k] (15) */ if (U == +DBL_MAX || f->f_min == -DBL_MAX) iub = +DBL_MAX; else if (f->j_min == 0) { if (a[k] > 0.0) { xassert(l[k] != -DBL_MAX); iub = U - (f->f_min - a[k] * l[k]); } else if (a[k] < 0.0) { xassert(u[k] != +DBL_MAX); iub = U - (f->f_min - a[k] * u[k]); } else xassert(a != a); } else if (f->j_min == k) iub = U - f->f_min; else iub = +DBL_MAX; /* determine implied bounds of x[k] (16) and (17) */ #if 1 /* do not use a[k] if it has small magnitude to prevent wrong implied bounds; for example, 1e-15 * x1 >= x2 + x3, where x1 >= -10, x2, x3 >= 0, would lead to wrong conclusion that x1 >= 0 */ if (fabs(a[k]) < 1e-6) *ll = -DBL_MAX, *uu = +DBL_MAX; else #endif if (a[k] > 0.0) { *ll = (ilb == -DBL_MAX ? -DBL_MAX : ilb / a[k]); *uu = (iub == +DBL_MAX ? +DBL_MAX : iub / a[k]); } else if (a[k] < 0.0) { *ll = (iub == +DBL_MAX ? -DBL_MAX : iub / a[k]); *uu = (ilb == -DBL_MAX ? +DBL_MAX : ilb / a[k]); } else xassert(a != a); return; } /*********************************************************************** * check_row_bounds - check and relax original row bounds * * Given a row (constraint) * * n * L <= sum a[j] * x[j] <= U * j=1 * * and bounds of columns (variables) * * l[j] <= x[j] <= u[j] * * this routine checks the original row bounds L and U for feasibility * and redundancy. If the original lower bound L or/and upper bound U * cannot be active due to bounds of variables, the routine remove them * replacing by -inf or/and +inf, respectively. * * If no primal infeasibility is detected, the routine returns zero, * otherwise non-zero. */ static int check_row_bounds(const struct f_info *f, double *L_, double *U_) { int ret = 0; double L = *L_, U = *U_, LL, UU; /* determine implied bounds of the row */ row_implied_bounds(f, &LL, &UU); /* check if the original lower bound is infeasible */ if (L != -DBL_MAX) { double eps = 1e-3 * (1.0 + fabs(L)); if (UU < L - eps) { ret = 1; goto done; } } /* check if the original upper bound is infeasible */ if (U != +DBL_MAX) { double eps = 1e-3 * (1.0 + fabs(U)); if (LL > U + eps) { ret = 1; goto done; } } /* check if the original lower bound is redundant */ if (L != -DBL_MAX) { double eps = 1e-12 * (1.0 + fabs(L)); if (LL > L - eps) { /* it cannot be active, so remove it */ *L_ = -DBL_MAX; } } /* check if the original upper bound is redundant */ if (U != +DBL_MAX) { double eps = 1e-12 * (1.0 + fabs(U)); if (UU < U + eps) { /* it cannot be active, so remove it */ *U_ = +DBL_MAX; } } done: return ret; } /*********************************************************************** * check_col_bounds - check and tighten original column bounds * * Given a row (constraint) * * n * L <= sum a[j] * x[j] <= U * j=1 * * and bounds of columns (variables) * * l[j] <= x[j] <= u[j] * * for column (variable) x[j] this routine checks the original column * bounds l[j] and u[j] for feasibility and redundancy. If the original * lower bound l[j] or/and upper bound u[j] cannot be active due to * bounds of the constraint and other variables, the routine tighten * them replacing by corresponding implied bounds, if possible. * * NOTE: It is assumed that if L != -inf, the row lower bound can be * active, and if U != +inf, the row upper bound can be active. * * The flag means that variable x[j] is required to be integer. * * New actual bounds for x[j] are stored in locations lj and uj. * * If no primal infeasibility is detected, the routine returns zero, * otherwise non-zero. */ static int check_col_bounds(const struct f_info *f, int n, const double a[], double L, double U, const double l[], const double u[], int flag, int j, double *_lj, double *_uj) { int ret = 0; double lj, uj, ll, uu; xassert(n >= 0); xassert(1 <= j && j <= n); lj = l[j], uj = u[j]; /* determine implied bounds of the column */ col_implied_bounds(f, n, a, L, U, l, u, j, &ll, &uu); /* if x[j] is integral, round its implied bounds */ if (flag) { if (ll != -DBL_MAX) ll = (ll - floor(ll) < 1e-3 ? floor(ll) : ceil(ll)); if (uu != +DBL_MAX) uu = (ceil(uu) - uu < 1e-3 ? ceil(uu) : floor(uu)); } /* check if the original lower bound is infeasible */ if (lj != -DBL_MAX) { double eps = 1e-3 * (1.0 + fabs(lj)); if (uu < lj - eps) { ret = 1; goto done; } } /* check if the original upper bound is infeasible */ if (uj != +DBL_MAX) { double eps = 1e-3 * (1.0 + fabs(uj)); if (ll > uj + eps) { ret = 1; goto done; } } /* check if the original lower bound is redundant */ if (ll != -DBL_MAX) { double eps = 1e-3 * (1.0 + fabs(ll)); if (lj < ll - eps) { /* it cannot be active, so tighten it */ lj = ll; } } /* check if the original upper bound is redundant */ if (uu != +DBL_MAX) { double eps = 1e-3 * (1.0 + fabs(uu)); if (uj > uu + eps) { /* it cannot be active, so tighten it */ uj = uu; } } /* due to round-off errors it may happen that lj > uj (although lj < uj + eps, since no primal infeasibility is detected), so adjuct the new actual bounds to provide lj <= uj */ if (!(lj == -DBL_MAX || uj == +DBL_MAX)) { double t1 = fabs(lj), t2 = fabs(uj); double eps = 1e-10 * (1.0 + (t1 <= t2 ? t1 : t2)); if (lj > uj - eps) { if (lj == l[j]) uj = lj; else if (uj == u[j]) lj = uj; else if (t1 <= t2) uj = lj; else lj = uj; } } *_lj = lj, *_uj = uj; done: return ret; } /*********************************************************************** * check_efficiency - check if change in column bounds is efficient * * Given the original bounds of a column l and u and its new actual * bounds l' and u' (possibly tighten by the routine check_col_bounds) * this routine checks if the change in the column bounds is efficient * enough. If so, the routine returns non-zero, otherwise zero. * * The flag means that the variable is required to be integer. */ static int check_efficiency(int flag, double l, double u, double ll, double uu) { int eff = 0; /* check efficiency for lower bound */ if (l < ll) { if (flag || l == -DBL_MAX) eff++; else { double r; if (u == +DBL_MAX) r = 1.0 + fabs(l); else r = 1.0 + (u - l); if (ll - l >= 0.25 * r) eff++; } } /* check efficiency for upper bound */ if (u > uu) { if (flag || u == +DBL_MAX) eff++; else { double r; if (l == -DBL_MAX) r = 1.0 + fabs(u); else r = 1.0 + (u - l); if (u - uu >= 0.25 * r) eff++; } } return eff; } /*********************************************************************** * basic_preprocessing - perform basic preprocessing * * This routine performs basic preprocessing of the specified MIP that * includes relaxing some row bounds and tightening some column bounds. * * On entry the arrays L and U contains original row bounds, and the * arrays l and u contains original column bounds: * * L[0] is the lower bound of the objective row; * L[i], i = 1,...,m, is the lower bound of i-th row; * U[0] is the upper bound of the objective row; * U[i], i = 1,...,m, is the upper bound of i-th row; * l[0] is not used; * l[j], j = 1,...,n, is the lower bound of j-th column; * u[0] is not used; * u[j], j = 1,...,n, is the upper bound of j-th column. * * On exit the arrays L, U, l, and u contain new actual bounds of rows * and column in the same locations. * * The parameters nrs and num specify an initial list of rows to be * processed: * * nrs is the number of rows in the initial list, 0 <= nrs <= m+1; * num[0] is not used; * num[1,...,nrs] are row numbers (0 means the objective row). * * The parameter max_pass specifies the maximal number of times that * each row can be processed, max_pass > 0. * * If no primal infeasibility is detected, the routine returns zero, * otherwise non-zero. */ static int basic_preprocessing(glp_prob *mip, double L[], double U[], double l[], double u[], int nrs, const int num[], int max_pass) { int m = mip->m; int n = mip->n; struct f_info f; int i, j, k, len, size, ret = 0; int *ind, *list, *mark, *pass; double *val, *lb, *ub; xassert(0 <= nrs && nrs <= m+1); xassert(max_pass > 0); /* allocate working arrays */ ind = xcalloc(1+n, sizeof(int)); list = xcalloc(1+m+1, sizeof(int)); mark = xcalloc(1+m+1, sizeof(int)); memset(&mark[0], 0, (m+1) * sizeof(int)); pass = xcalloc(1+m+1, sizeof(int)); memset(&pass[0], 0, (m+1) * sizeof(int)); val = xcalloc(1+n, sizeof(double)); lb = xcalloc(1+n, sizeof(double)); ub = xcalloc(1+n, sizeof(double)); /* initialize the list of rows to be processed */ size = 0; for (k = 1; k <= nrs; k++) { i = num[k]; xassert(0 <= i && i <= m); /* duplicate row numbers are not allowed */ xassert(!mark[i]); list[++size] = i, mark[i] = 1; } xassert(size == nrs); /* process rows in the list until it becomes empty */ while (size > 0) { /* get a next row from the list */ i = list[size--], mark[i] = 0; /* increase the row processing count */ pass[i]++; /* if the row is free, skip it */ if (L[i] == -DBL_MAX && U[i] == +DBL_MAX) continue; /* obtain coefficients of the row */ len = 0; if (i == 0) { for (j = 1; j <= n; j++) { GLPCOL *col = mip->col[j]; if (col->coef != 0.0) len++, ind[len] = j, val[len] = col->coef; } } else { GLPROW *row = mip->row[i]; GLPAIJ *aij; for (aij = row->ptr; aij != NULL; aij = aij->r_next) len++, ind[len] = aij->col->j, val[len] = aij->val; } /* determine lower and upper bounds of columns corresponding to non-zero row coefficients */ for (k = 1; k <= len; k++) j = ind[k], lb[k] = l[j], ub[k] = u[j]; /* prepare the row info to determine implied bounds */ prepare_row_info(len, val, lb, ub, &f); /* check and relax bounds of the row */ if (check_row_bounds(&f, &L[i], &U[i])) { /* the feasible region is empty */ ret = 1; goto done; } /* if the row became free, drop it */ if (L[i] == -DBL_MAX && U[i] == +DBL_MAX) continue; /* process columns having non-zero coefficients in the row */ for (k = 1; k <= len; k++) { GLPCOL *col; int flag, eff; double ll, uu; /* take a next column in the row */ j = ind[k], col = mip->col[j]; flag = col->kind != GLP_CV; /* check and tighten bounds of the column */ if (check_col_bounds(&f, len, val, L[i], U[i], lb, ub, flag, k, &ll, &uu)) { /* the feasible region is empty */ ret = 1; goto done; } /* check if change in the column bounds is efficient */ eff = check_efficiency(flag, l[j], u[j], ll, uu); /* set new actual bounds of the column */ l[j] = ll, u[j] = uu; /* if the change is efficient, add all rows affected by the corresponding column, to the list */ if (eff > 0) { GLPAIJ *aij; for (aij = col->ptr; aij != NULL; aij = aij->c_next) { int ii = aij->row->i; /* if the row was processed maximal number of times, skip it */ if (pass[ii] >= max_pass) continue; /* if the row is free, skip it */ if (L[ii] == -DBL_MAX && U[ii] == +DBL_MAX) continue; /* put the row into the list */ if (mark[ii] == 0) { xassert(size <= m); list[++size] = ii, mark[ii] = 1; } } } } } done: /* free working arrays */ xfree(ind); xfree(list); xfree(mark); xfree(pass); xfree(val); xfree(lb); xfree(ub); return ret; } /*********************************************************************** * NAME * * ios_preprocess_node - preprocess current subproblem * * SYNOPSIS * * #include "glpios.h" * int ios_preprocess_node(glp_tree *tree, int max_pass); * * DESCRIPTION * * The routine ios_preprocess_node performs basic preprocessing of the * current subproblem. * * RETURNS * * If no primal infeasibility is detected, the routine returns zero, * otherwise non-zero. */ int ios_preprocess_node(glp_tree *tree, int max_pass) { glp_prob *mip = tree->mip; int m = mip->m; int n = mip->n; int i, j, nrs, *num, ret = 0; double *L, *U, *l, *u; /* the current subproblem must exist */ xassert(tree->curr != NULL); /* determine original row bounds */ L = xcalloc(1+m, sizeof(double)); U = xcalloc(1+m, sizeof(double)); switch (mip->mip_stat) { case GLP_UNDEF: L[0] = -DBL_MAX, U[0] = +DBL_MAX; break; case GLP_FEAS: switch (mip->dir) { case GLP_MIN: L[0] = -DBL_MAX, U[0] = mip->mip_obj - mip->c0; break; case GLP_MAX: L[0] = mip->mip_obj - mip->c0, U[0] = +DBL_MAX; break; default: xassert(mip != mip); } break; default: xassert(mip != mip); } for (i = 1; i <= m; i++) { L[i] = glp_get_row_lb(mip, i); U[i] = glp_get_row_ub(mip, i); } /* determine original column bounds */ l = xcalloc(1+n, sizeof(double)); u = xcalloc(1+n, sizeof(double)); for (j = 1; j <= n; j++) { l[j] = glp_get_col_lb(mip, j); u[j] = glp_get_col_ub(mip, j); } /* build the initial list of rows to be analyzed */ nrs = m + 1; num = xcalloc(1+nrs, sizeof(int)); for (i = 1; i <= nrs; i++) num[i] = i - 1; /* perform basic preprocessing */ if (basic_preprocessing(mip , L, U, l, u, nrs, num, max_pass)) { ret = 1; goto done; } /* set new actual (relaxed) row bounds */ for (i = 1; i <= m; i++) { /* consider only non-active rows to keep dual feasibility */ if (glp_get_row_stat(mip, i) == GLP_BS) { if (L[i] == -DBL_MAX && U[i] == +DBL_MAX) glp_set_row_bnds(mip, i, GLP_FR, 0.0, 0.0); else if (U[i] == +DBL_MAX) glp_set_row_bnds(mip, i, GLP_LO, L[i], 0.0); else if (L[i] == -DBL_MAX) glp_set_row_bnds(mip, i, GLP_UP, 0.0, U[i]); } } /* set new actual (tightened) column bounds */ for (j = 1; j <= n; j++) { int type; if (l[j] == -DBL_MAX && u[j] == +DBL_MAX) type = GLP_FR; else if (u[j] == +DBL_MAX) type = GLP_LO; else if (l[j] == -DBL_MAX) type = GLP_UP; else if (l[j] != u[j]) type = GLP_DB; else type = GLP_FX; glp_set_col_bnds(mip, j, type, l[j], u[j]); } done: /* free working arrays and return */ xfree(L); xfree(U); xfree(l); xfree(u); xfree(num); return ret; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpnet06.c0000644000076500000240000003073313524616144025210 0ustar tamasstaff00000000000000/* glpnet06.c (out-of-kilter algorithm) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wlogical-op-parentheses" #endif #include "glpenv.h" #include "glpnet.h" /*********************************************************************** * NAME * * okalg - out-of-kilter algorithm * * SYNOPSIS * * #include "glpnet.h" * int okalg(int nv, int na, const int tail[], const int head[], * const int low[], const int cap[], const int cost[], int x[], * int pi[]); * * DESCRIPTION * * The routine okalg implements the out-of-kilter algorithm to find a * minimal-cost circulation in the specified flow network. * * INPUT PARAMETERS * * nv is the number of nodes, nv >= 0. * * na is the number of arcs, na >= 0. * * tail[a], a = 1,...,na, is the index of tail node of arc a. * * head[a], a = 1,...,na, is the index of head node of arc a. * * low[a], a = 1,...,na, is an lower bound to the flow through arc a. * * cap[a], a = 1,...,na, is an upper bound to the flow through arc a, * which is the capacity of the arc. * * cost[a], a = 1,...,na, is a per-unit cost of the flow through arc a. * * NOTES * * 1. Multiple arcs are allowed, but self-loops are not allowed. * * 2. It is required that 0 <= low[a] <= cap[a] for all arcs. * * 3. Arc costs may have any sign. * * OUTPUT PARAMETERS * * x[a], a = 1,...,na, is optimal value of the flow through arc a. * * pi[i], i = 1,...,nv, is Lagrange multiplier for flow conservation * equality constraint corresponding to node i (the node potential). * * RETURNS * * 0 optimal circulation found; * * 1 there is no feasible circulation; * * 2 integer overflow occured; * * 3 optimality test failed (logic error). * * REFERENCES * * L.R.Ford, Jr., and D.R.Fulkerson, "Flows in Networks," The RAND * Corp., Report R-375-PR (August 1962), Chap. III "Minimal Cost Flow * Problems," pp.113-26. */ static int overflow(int u, int v) { /* check for integer overflow on computing u + v */ if (u > 0 && v > 0 && u + v < 0) return 1; if (u < 0 && v < 0 && u + v > 0) return 1; return 0; } int okalg(int nv, int na, const int tail[], const int head[], const int low[], const int cap[], const int cost[], int x[], int pi[]) { int a, aok, delta, i, j, k, lambda, pos1, pos2, s, t, temp, ret, *ptr, *arc, *link, *list; /* sanity checks */ xassert(nv >= 0); xassert(na >= 0); for (a = 1; a <= na; a++) { i = tail[a], j = head[a]; xassert(1 <= i && i <= nv); xassert(1 <= j && j <= nv); xassert(i != j); xassert(0 <= low[a] && low[a] <= cap[a]); } /* allocate working arrays */ ptr = xcalloc(1+nv+1, sizeof(int)); arc = xcalloc(1+na+na, sizeof(int)); link = xcalloc(1+nv, sizeof(int)); list = xcalloc(1+nv, sizeof(int)); /* ptr[i] := (degree of node i) */ for (i = 1; i <= nv; i++) ptr[i] = 0; for (a = 1; a <= na; a++) { ptr[tail[a]]++; ptr[head[a]]++; } /* initialize arc pointers */ ptr[1]++; for (i = 1; i < nv; i++) ptr[i+1] += ptr[i]; ptr[nv+1] = ptr[nv]; /* build arc lists */ for (a = 1; a <= na; a++) { arc[--ptr[tail[a]]] = a; arc[--ptr[head[a]]] = a; } xassert(ptr[1] == 1); xassert(ptr[nv+1] == na+na+1); /* now the indices of arcs incident to node i are stored in locations arc[ptr[i]], arc[ptr[i]+1], ..., arc[ptr[i+1]-1] */ /* initialize arc flows and node potentials */ for (a = 1; a <= na; a++) x[a] = 0; for (i = 1; i <= nv; i++) pi[i] = 0; loop: /* main loop starts here */ /* find out-of-kilter arc */ aok = 0; for (a = 1; a <= na; a++) { i = tail[a], j = head[a]; if (overflow(cost[a], pi[i] - pi[j])) { ret = 2; goto done; } lambda = cost[a] + (pi[i] - pi[j]); if (x[a] < low[a] || lambda < 0 && x[a] < cap[a]) { /* arc a = i->j is out of kilter, and we need to increase the flow through this arc */ aok = a, s = j, t = i; break; } if (x[a] > cap[a] || lambda > 0 && x[a] > low[a]) { /* arc a = i->j is out of kilter, and we need to decrease the flow through this arc */ aok = a, s = i, t = j; break; } } if (aok == 0) { /* all arcs are in kilter */ /* check for feasibility */ for (a = 1; a <= na; a++) { if (!(low[a] <= x[a] && x[a] <= cap[a])) { ret = 3; goto done; } } for (i = 1; i <= nv; i++) { temp = 0; for (k = ptr[i]; k < ptr[i+1]; k++) { a = arc[k]; if (tail[a] == i) { /* a is outgoing arc */ temp += x[a]; } else if (head[a] == i) { /* a is incoming arc */ temp -= x[a]; } else xassert(a != a); } if (temp != 0) { ret = 3; goto done; } } /* check for optimality */ for (a = 1; a <= na; a++) { i = tail[a], j = head[a]; lambda = cost[a] + (pi[i] - pi[j]); if (lambda > 0 && x[a] != low[a] || lambda < 0 && x[a] != cap[a]) { ret = 3; goto done; } } /* current circulation is optimal */ ret = 0; goto done; } /* now we need to find a cycle (t, a, s, ..., t), which allows increasing the flow along it, where a is the out-of-kilter arc just found */ /* link[i] = 0 means that node i is not labelled yet; link[i] = a means that arc a immediately precedes node i */ /* initially only node s is labelled */ for (i = 1; i <= nv; i++) link[i] = 0; link[s] = aok, list[1] = s, pos1 = pos2 = 1; /* breadth first search */ while (pos1 <= pos2) { /* dequeue node i */ i = list[pos1++]; /* consider all arcs incident to node i */ for (k = ptr[i]; k < ptr[i+1]; k++) { a = arc[k]; if (tail[a] == i) { /* a = i->j is a forward arc from s to t */ j = head[a]; /* if node j has been labelled, skip the arc */ if (link[j] != 0) continue; /* if the arc does not allow increasing the flow through it, skip the arc */ if (x[a] >= cap[a]) continue; if (overflow(cost[a], pi[i] - pi[j])) { ret = 2; goto done; } lambda = cost[a] + (pi[i] - pi[j]); if (lambda > 0 && x[a] >= low[a]) continue; } else if (head[a] == i) { /* a = i<-j is a backward arc from s to t */ j = tail[a]; /* if node j has been labelled, skip the arc */ if (link[j] != 0) continue; /* if the arc does not allow decreasing the flow through it, skip the arc */ if (x[a] <= low[a]) continue; if (overflow(cost[a], pi[j] - pi[i])) { ret = 2; goto done; } lambda = cost[a] + (pi[j] - pi[i]); if (lambda < 0 && x[a] <= cap[a]) continue; } else xassert(a != a); /* label node j and enqueue it */ link[j] = a, list[++pos2] = j; /* check for breakthrough */ if (j == t) goto brkt; } } /* NONBREAKTHROUGH */ /* consider all arcs, whose one endpoint is labelled and other is not, and determine maximal change of node potentials */ delta = 0; for (a = 1; a <= na; a++) { i = tail[a], j = head[a]; if (link[i] != 0 && link[j] == 0) { /* a = i->j, where node i is labelled, node j is not */ if (overflow(cost[a], pi[i] - pi[j])) { ret = 2; goto done; } lambda = cost[a] + (pi[i] - pi[j]); if (x[a] <= cap[a] && lambda > 0) if (delta == 0 || delta > + lambda) delta = + lambda; } else if (link[i] == 0 && link[j] != 0) { /* a = j<-i, where node j is labelled, node i is not */ if (overflow(cost[a], pi[i] - pi[j])) { ret = 2; goto done; } lambda = cost[a] + (pi[i] - pi[j]); if (x[a] >= low[a] && lambda < 0) if (delta == 0 || delta > - lambda) delta = - lambda; } } if (delta == 0) { /* there is no feasible circulation */ ret = 1; goto done; } /* increase potentials of all unlabelled nodes */ for (i = 1; i <= nv; i++) { if (link[i] == 0) { if (overflow(pi[i], delta)) { ret = 2; goto done; } pi[i] += delta; } } goto loop; brkt: /* BREAKTHROUGH */ /* walk through arcs of the cycle (t, a, s, ..., t) found in the reverse order and determine maximal change of the flow */ delta = 0; for (j = t;; j = i) { /* arc a immediately precedes node j in the cycle */ a = link[j]; if (head[a] == j) { /* a = i->j is a forward arc of the cycle */ i = tail[a]; lambda = cost[a] + (pi[i] - pi[j]); if (lambda > 0 && x[a] < low[a]) { /* x[a] may be increased until its lower bound */ temp = low[a] - x[a]; } else if (lambda <= 0 && x[a] < cap[a]) { /* x[a] may be increased until its upper bound */ temp = cap[a] - x[a]; } else xassert(a != a); } else if (tail[a] == j) { /* a = i<-j is a backward arc of the cycle */ i = head[a]; lambda = cost[a] + (pi[j] - pi[i]); if (lambda < 0 && x[a] > cap[a]) { /* x[a] may be decreased until its upper bound */ temp = x[a] - cap[a]; } else if (lambda >= 0 && x[a] > low[a]) { /* x[a] may be decreased until its lower bound */ temp = x[a] - low[a]; } else xassert(a != a); } else xassert(a != a); if (delta == 0 || delta > temp) delta = temp; /* check for end of the cycle */ if (i == t) break; } xassert(delta > 0); /* increase the flow along the cycle */ for (j = t;; j = i) { /* arc a immediately precedes node j in the cycle */ a = link[j]; if (head[a] == j) { /* a = i->j is a forward arc of the cycle */ i = tail[a]; /* overflow cannot occur */ x[a] += delta; } else if (tail[a] == j) { /* a = i<-j is a backward arc of the cycle */ i = head[a]; /* overflow cannot occur */ x[a] -= delta; } else xassert(a != a); /* check for end of the cycle */ if (i == t) break; } goto loop; done: /* free working arrays */ xfree(ptr); xfree(arc); xfree(link); xfree(list); return ret; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpios06.c0000644000076500000240000014000713524616144025210 0ustar tamasstaff00000000000000/* glpios06.c (MIR cut generator) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wlogical-op-parentheses" #pragma clang diagnostic ignored "-Wsign-conversion" #pragma clang diagnostic ignored "-Wsometimes-uninitialized" #endif #include "glpios.h" #define _MIR_DEBUG 0 #define MAXAGGR 5 /* maximal number of rows which can be aggregated */ struct MIR { /* MIR cut generator working area */ /*--------------------------------------------------------------*/ /* global information valid for the root subproblem */ int m; /* number of rows (in the root subproblem) */ int n; /* number of columns */ char *skip; /* char skip[1+m]; */ /* skip[i], 1 <= i <= m, is a flag that means that row i should not be used because (1) it is not suitable, or (2) because it has been used in the aggregated constraint */ char *isint; /* char isint[1+m+n]; */ /* isint[k], 1 <= k <= m+n, is a flag that means that variable x[k] is integer (otherwise, continuous) */ double *lb; /* double lb[1+m+n]; */ /* lb[k], 1 <= k <= m+n, is lower bound of x[k]; -DBL_MAX means that x[k] has no lower bound */ int *vlb; /* int vlb[1+m+n]; */ /* vlb[k] = k', 1 <= k <= m+n, is the number of integer variable, which defines variable lower bound x[k] >= lb[k] * x[k']; zero means that x[k] has simple lower bound */ double *ub; /* double ub[1+m+n]; */ /* ub[k], 1 <= k <= m+n, is upper bound of x[k]; +DBL_MAX means that x[k] has no upper bound */ int *vub; /* int vub[1+m+n]; */ /* vub[k] = k', 1 <= k <= m+n, is the number of integer variable, which defines variable upper bound x[k] <= ub[k] * x[k']; zero means that x[k] has simple upper bound */ /*--------------------------------------------------------------*/ /* current (fractional) point to be separated */ double *x; /* double x[1+m+n]; */ /* x[k] is current value of auxiliary (1 <= k <= m) or structural (m+1 <= k <= m+n) variable */ /*--------------------------------------------------------------*/ /* aggregated constraint sum a[k] * x[k] = b, which is a linear combination of original constraints transformed to equalities by introducing auxiliary variables */ int agg_cnt; /* number of rows (original constraints) used to build aggregated constraint, 1 <= agg_cnt <= MAXAGGR */ int *agg_row; /* int agg_row[1+MAXAGGR]; */ /* agg_row[k], 1 <= k <= agg_cnt, is the row number used to build aggregated constraint */ IOSVEC *agg_vec; /* IOSVEC agg_vec[1:m+n]; */ /* sparse vector of aggregated constraint coefficients, a[k] */ double agg_rhs; /* right-hand side of the aggregated constraint, b */ /*--------------------------------------------------------------*/ /* bound substitution flags for modified constraint */ char *subst; /* char subst[1+m+n]; */ /* subst[k], 1 <= k <= m+n, is a bound substitution flag used for variable x[k]: '?' - x[k] is missing in modified constraint 'L' - x[k] = (lower bound) + x'[k] 'U' - x[k] = (upper bound) - x'[k] */ /*--------------------------------------------------------------*/ /* modified constraint sum a'[k] * x'[k] = b', where x'[k] >= 0, derived from aggregated constraint by substituting bounds; note that due to substitution of variable bounds there may be additional terms in the modified constraint */ IOSVEC *mod_vec; /* IOSVEC mod_vec[1:m+n]; */ /* sparse vector of modified constraint coefficients, a'[k] */ double mod_rhs; /* right-hand side of the modified constraint, b' */ /*--------------------------------------------------------------*/ /* cutting plane sum alpha[k] * x[k] <= beta */ IOSVEC *cut_vec; /* IOSVEC cut_vec[1:m+n]; */ /* sparse vector of cutting plane coefficients, alpha[k] */ double cut_rhs; /* right-hand size of the cutting plane, beta */ }; /*********************************************************************** * NAME * * ios_mir_init - initialize MIR cut generator * * SYNOPSIS * * #include "glpios.h" * void *ios_mir_init(glp_tree *tree); * * DESCRIPTION * * The routine ios_mir_init initializes the MIR cut generator assuming * that the current subproblem is the root subproblem. * * RETURNS * * The routine ios_mir_init returns a pointer to the MIR cut generator * working area. */ static void set_row_attrib(glp_tree *tree, struct MIR *mir) { /* set global row attributes */ glp_prob *mip = tree->mip; int m = mir->m; int k; for (k = 1; k <= m; k++) { GLPROW *row = mip->row[k]; mir->skip[k] = 0; mir->isint[k] = 0; switch (row->type) { case GLP_FR: mir->lb[k] = -DBL_MAX, mir->ub[k] = +DBL_MAX; break; case GLP_LO: mir->lb[k] = row->lb, mir->ub[k] = +DBL_MAX; break; case GLP_UP: mir->lb[k] = -DBL_MAX, mir->ub[k] = row->ub; break; case GLP_DB: mir->lb[k] = row->lb, mir->ub[k] = row->ub; break; case GLP_FX: mir->lb[k] = mir->ub[k] = row->lb; break; default: xassert(row != row); } mir->vlb[k] = mir->vub[k] = 0; } return; } static void set_col_attrib(glp_tree *tree, struct MIR *mir) { /* set global column attributes */ glp_prob *mip = tree->mip; int m = mir->m; int n = mir->n; int k; for (k = m+1; k <= m+n; k++) { GLPCOL *col = mip->col[k-m]; switch (col->kind) { case GLP_CV: mir->isint[k] = 0; break; case GLP_IV: mir->isint[k] = 1; break; default: xassert(col != col); } switch (col->type) { case GLP_FR: mir->lb[k] = -DBL_MAX, mir->ub[k] = +DBL_MAX; break; case GLP_LO: mir->lb[k] = col->lb, mir->ub[k] = +DBL_MAX; break; case GLP_UP: mir->lb[k] = -DBL_MAX, mir->ub[k] = col->ub; break; case GLP_DB: mir->lb[k] = col->lb, mir->ub[k] = col->ub; break; case GLP_FX: mir->lb[k] = mir->ub[k] = col->lb; break; default: xassert(col != col); } mir->vlb[k] = mir->vub[k] = 0; } return; } static void set_var_bounds(glp_tree *tree, struct MIR *mir) { /* set variable bounds */ glp_prob *mip = tree->mip; int m = mir->m; GLPAIJ *aij; int i, k1, k2; double a1, a2; for (i = 1; i <= m; i++) { /* we need the row to be '>= 0' or '<= 0' */ if (!(mir->lb[i] == 0.0 && mir->ub[i] == +DBL_MAX || mir->lb[i] == -DBL_MAX && mir->ub[i] == 0.0)) continue; /* take first term */ aij = mip->row[i]->ptr; if (aij == NULL) continue; k1 = m + aij->col->j, a1 = aij->val; /* take second term */ aij = aij->r_next; if (aij == NULL) continue; k2 = m + aij->col->j, a2 = aij->val; /* there must be only two terms */ if (aij->r_next != NULL) continue; /* interchange terms, if needed */ if (!mir->isint[k1] && mir->isint[k2]) ; else if (mir->isint[k1] && !mir->isint[k2]) { k2 = k1, a2 = a1; k1 = m + aij->col->j, a1 = aij->val; } else { /* both terms are either continuous or integer */ continue; } /* x[k2] should be double-bounded */ if (mir->lb[k2] == -DBL_MAX || mir->ub[k2] == +DBL_MAX || mir->lb[k2] == mir->ub[k2]) continue; /* change signs, if necessary */ if (mir->ub[i] == 0.0) a1 = - a1, a2 = - a2; /* now the row has the form a1 * x1 + a2 * x2 >= 0, where x1 is continuous, x2 is integer */ if (a1 > 0.0) { /* x1 >= - (a2 / a1) * x2 */ if (mir->vlb[k1] == 0) { /* set variable lower bound for x1 */ mir->lb[k1] = - a2 / a1; mir->vlb[k1] = k2; /* the row should not be used */ mir->skip[i] = 1; } } else /* a1 < 0.0 */ { /* x1 <= - (a2 / a1) * x2 */ if (mir->vub[k1] == 0) { /* set variable upper bound for x1 */ mir->ub[k1] = - a2 / a1; mir->vub[k1] = k2; /* the row should not be used */ mir->skip[i] = 1; } } } return; } static void mark_useless_rows(glp_tree *tree, struct MIR *mir) { /* mark rows which should not be used */ glp_prob *mip = tree->mip; int m = mir->m; GLPAIJ *aij; int i, k, nv; for (i = 1; i <= m; i++) { /* free rows should not be used */ if (mir->lb[i] == -DBL_MAX && mir->ub[i] == +DBL_MAX) { mir->skip[i] = 1; continue; } nv = 0; for (aij = mip->row[i]->ptr; aij != NULL; aij = aij->r_next) { k = m + aij->col->j; /* rows with free variables should not be used */ if (mir->lb[k] == -DBL_MAX && mir->ub[k] == +DBL_MAX) { mir->skip[i] = 1; break; } /* rows with integer variables having infinite (lower or upper) bound should not be used */ if (mir->isint[k] && mir->lb[k] == -DBL_MAX || mir->isint[k] && mir->ub[k] == +DBL_MAX) { mir->skip[i] = 1; break; } /* count non-fixed variables */ if (!(mir->vlb[k] == 0 && mir->vub[k] == 0 && mir->lb[k] == mir->ub[k])) nv++; } /* rows with all variables fixed should not be used */ if (nv == 0) { mir->skip[i] = 1; continue; } } return; } void *ios_mir_init(glp_tree *tree) { /* initialize MIR cut generator */ glp_prob *mip = tree->mip; int m = mip->m; int n = mip->n; struct MIR *mir; #if _MIR_DEBUG xprintf("ios_mir_init: warning: debug mode enabled\n"); #endif /* allocate working area */ mir = xmalloc(sizeof(struct MIR)); mir->m = m; mir->n = n; mir->skip = xcalloc(1+m, sizeof(char)); mir->isint = xcalloc(1+m+n, sizeof(char)); mir->lb = xcalloc(1+m+n, sizeof(double)); mir->vlb = xcalloc(1+m+n, sizeof(int)); mir->ub = xcalloc(1+m+n, sizeof(double)); mir->vub = xcalloc(1+m+n, sizeof(int)); mir->x = xcalloc(1+m+n, sizeof(double)); mir->agg_row = xcalloc(1+MAXAGGR, sizeof(int)); mir->agg_vec = ios_create_vec(m+n); mir->subst = xcalloc(1+m+n, sizeof(char)); mir->mod_vec = ios_create_vec(m+n); mir->cut_vec = ios_create_vec(m+n); /* set global row attributes */ set_row_attrib(tree, mir); /* set global column attributes */ set_col_attrib(tree, mir); /* set variable bounds */ set_var_bounds(tree, mir); /* mark rows which should not be used */ mark_useless_rows(tree, mir); return mir; } /*********************************************************************** * NAME * * ios_mir_gen - generate MIR cuts * * SYNOPSIS * * #include "glpios.h" * void ios_mir_gen(glp_tree *tree, void *gen, IOSPOOL *pool); * * DESCRIPTION * * The routine ios_mir_gen generates MIR cuts for the current point and * adds them to the cut pool. */ static void get_current_point(glp_tree *tree, struct MIR *mir) { /* obtain current point */ glp_prob *mip = tree->mip; int m = mir->m; int n = mir->n; int k; for (k = 1; k <= m; k++) mir->x[k] = mip->row[k]->prim; for (k = m+1; k <= m+n; k++) mir->x[k] = mip->col[k-m]->prim; return; } #if _MIR_DEBUG static void check_current_point(struct MIR *mir) { /* check current point */ int m = mir->m; int n = mir->n; int k, kk; double lb, ub, eps; for (k = 1; k <= m+n; k++) { /* determine lower bound */ lb = mir->lb[k]; kk = mir->vlb[k]; if (kk != 0) { xassert(lb != -DBL_MAX); xassert(!mir->isint[k]); xassert(mir->isint[kk]); lb *= mir->x[kk]; } /* check lower bound */ if (lb != -DBL_MAX) { eps = 1e-6 * (1.0 + fabs(lb)); xassert(mir->x[k] >= lb - eps); } /* determine upper bound */ ub = mir->ub[k]; kk = mir->vub[k]; if (kk != 0) { xassert(ub != +DBL_MAX); xassert(!mir->isint[k]); xassert(mir->isint[kk]); ub *= mir->x[kk]; } /* check upper bound */ if (ub != +DBL_MAX) { eps = 1e-6 * (1.0 + fabs(ub)); xassert(mir->x[k] <= ub + eps); } } return; } #endif static void initial_agg_row(glp_tree *tree, struct MIR *mir, int i) { /* use original i-th row as initial aggregated constraint */ glp_prob *mip = tree->mip; int m = mir->m; GLPAIJ *aij; xassert(1 <= i && i <= m); xassert(!mir->skip[i]); /* mark i-th row in order not to use it in the same aggregated constraint */ mir->skip[i] = 2; mir->agg_cnt = 1; mir->agg_row[1] = i; /* use x[i] - sum a[i,j] * x[m+j] = 0, where x[i] is auxiliary variable of row i, x[m+j] are structural variables */ ios_clear_vec(mir->agg_vec); ios_set_vj(mir->agg_vec, i, 1.0); for (aij = mip->row[i]->ptr; aij != NULL; aij = aij->r_next) ios_set_vj(mir->agg_vec, m + aij->col->j, - aij->val); mir->agg_rhs = 0.0; #if _MIR_DEBUG ios_check_vec(mir->agg_vec); #endif return; } #if _MIR_DEBUG static void check_agg_row(struct MIR *mir) { /* check aggregated constraint */ int m = mir->m; int n = mir->n; int j, k; double r, big; /* compute the residual r = sum a[k] * x[k] - b and determine big = max(1, |a[k]|, |b|) */ r = 0.0, big = 1.0; for (j = 1; j <= mir->agg_vec->nnz; j++) { k = mir->agg_vec->ind[j]; xassert(1 <= k && k <= m+n); r += mir->agg_vec->val[j] * mir->x[k]; if (big < fabs(mir->agg_vec->val[j])) big = fabs(mir->agg_vec->val[j]); } r -= mir->agg_rhs; if (big < fabs(mir->agg_rhs)) big = fabs(mir->agg_rhs); /* the residual must be close to zero */ xassert(fabs(r) <= 1e-6 * big); return; } #endif static void subst_fixed_vars(struct MIR *mir) { /* substitute fixed variables into aggregated constraint */ int m = mir->m; int n = mir->n; int j, k; for (j = 1; j <= mir->agg_vec->nnz; j++) { k = mir->agg_vec->ind[j]; xassert(1 <= k && k <= m+n); if (mir->vlb[k] == 0 && mir->vub[k] == 0 && mir->lb[k] == mir->ub[k]) { /* x[k] is fixed */ mir->agg_rhs -= mir->agg_vec->val[j] * mir->lb[k]; mir->agg_vec->val[j] = 0.0; } } /* remove terms corresponding to fixed variables */ ios_clean_vec(mir->agg_vec, DBL_EPSILON); #if _MIR_DEBUG ios_check_vec(mir->agg_vec); #endif return; } static void bound_subst_heur(struct MIR *mir) { /* bound substitution heuristic */ int m = mir->m; int n = mir->n; int j, k, kk; double d1, d2; for (j = 1; j <= mir->agg_vec->nnz; j++) { k = mir->agg_vec->ind[j]; xassert(1 <= k && k <= m+n); if (mir->isint[k]) continue; /* skip integer variable */ /* compute distance from x[k] to its lower bound */ kk = mir->vlb[k]; if (kk == 0) { if (mir->lb[k] == -DBL_MAX) d1 = DBL_MAX; else d1 = mir->x[k] - mir->lb[k]; } else { xassert(1 <= kk && kk <= m+n); xassert(mir->isint[kk]); xassert(mir->lb[k] != -DBL_MAX); d1 = mir->x[k] - mir->lb[k] * mir->x[kk]; } /* compute distance from x[k] to its upper bound */ kk = mir->vub[k]; if (kk == 0) { if (mir->vub[k] == +DBL_MAX) d2 = DBL_MAX; else d2 = mir->ub[k] - mir->x[k]; } else { xassert(1 <= kk && kk <= m+n); xassert(mir->isint[kk]); xassert(mir->ub[k] != +DBL_MAX); d2 = mir->ub[k] * mir->x[kk] - mir->x[k]; } /* x[k] cannot be free */ xassert(d1 != DBL_MAX || d2 != DBL_MAX); /* choose the bound which is closer to x[k] */ xassert(mir->subst[k] == '?'); if (d1 <= d2) mir->subst[k] = 'L'; else mir->subst[k] = 'U'; } return; } static void build_mod_row(struct MIR *mir) { /* substitute bounds and build modified constraint */ int m = mir->m; int n = mir->n; int j, jj, k, kk; /* initially modified constraint is aggregated constraint */ ios_copy_vec(mir->mod_vec, mir->agg_vec); mir->mod_rhs = mir->agg_rhs; #if _MIR_DEBUG ios_check_vec(mir->mod_vec); #endif /* substitute bounds for continuous variables; note that due to substitution of variable bounds additional terms may appear in modified constraint */ for (j = mir->mod_vec->nnz; j >= 1; j--) { k = mir->mod_vec->ind[j]; xassert(1 <= k && k <= m+n); if (mir->isint[k]) continue; /* skip integer variable */ if (mir->subst[k] == 'L') { /* x[k] = (lower bound) + x'[k] */ xassert(mir->lb[k] != -DBL_MAX); kk = mir->vlb[k]; if (kk == 0) { /* x[k] = lb[k] + x'[k] */ mir->mod_rhs -= mir->mod_vec->val[j] * mir->lb[k]; } else { /* x[k] = lb[k] * x[kk] + x'[k] */ xassert(mir->isint[kk]); jj = mir->mod_vec->pos[kk]; if (jj == 0) { ios_set_vj(mir->mod_vec, kk, 1.0); jj = mir->mod_vec->pos[kk]; mir->mod_vec->val[jj] = 0.0; } mir->mod_vec->val[jj] += mir->mod_vec->val[j] * mir->lb[k]; } } else if (mir->subst[k] == 'U') { /* x[k] = (upper bound) - x'[k] */ xassert(mir->ub[k] != +DBL_MAX); kk = mir->vub[k]; if (kk == 0) { /* x[k] = ub[k] - x'[k] */ mir->mod_rhs -= mir->mod_vec->val[j] * mir->ub[k]; } else { /* x[k] = ub[k] * x[kk] - x'[k] */ xassert(mir->isint[kk]); jj = mir->mod_vec->pos[kk]; if (jj == 0) { ios_set_vj(mir->mod_vec, kk, 1.0); jj = mir->mod_vec->pos[kk]; mir->mod_vec->val[jj] = 0.0; } mir->mod_vec->val[jj] += mir->mod_vec->val[j] * mir->ub[k]; } mir->mod_vec->val[j] = - mir->mod_vec->val[j]; } else xassert(k != k); } #if _MIR_DEBUG ios_check_vec(mir->mod_vec); #endif /* substitute bounds for integer variables */ for (j = 1; j <= mir->mod_vec->nnz; j++) { k = mir->mod_vec->ind[j]; xassert(1 <= k && k <= m+n); if (!mir->isint[k]) continue; /* skip continuous variable */ xassert(mir->subst[k] == '?'); xassert(mir->vlb[k] == 0 && mir->vub[k] == 0); xassert(mir->lb[k] != -DBL_MAX && mir->ub[k] != +DBL_MAX); if (fabs(mir->lb[k]) <= fabs(mir->ub[k])) { /* x[k] = lb[k] + x'[k] */ mir->subst[k] = 'L'; mir->mod_rhs -= mir->mod_vec->val[j] * mir->lb[k]; } else { /* x[k] = ub[k] - x'[k] */ mir->subst[k] = 'U'; mir->mod_rhs -= mir->mod_vec->val[j] * mir->ub[k]; mir->mod_vec->val[j] = - mir->mod_vec->val[j]; } } #if _MIR_DEBUG ios_check_vec(mir->mod_vec); #endif return; } #if _MIR_DEBUG static void check_mod_row(struct MIR *mir) { /* check modified constraint */ int m = mir->m; int n = mir->n; int j, k, kk; double r, big, x; /* compute the residual r = sum a'[k] * x'[k] - b' and determine big = max(1, |a[k]|, |b|) */ r = 0.0, big = 1.0; for (j = 1; j <= mir->mod_vec->nnz; j++) { k = mir->mod_vec->ind[j]; xassert(1 <= k && k <= m+n); if (mir->subst[k] == 'L') { /* x'[k] = x[k] - (lower bound) */ xassert(mir->lb[k] != -DBL_MAX); kk = mir->vlb[k]; if (kk == 0) x = mir->x[k] - mir->lb[k]; else x = mir->x[k] - mir->lb[k] * mir->x[kk]; } else if (mir->subst[k] == 'U') { /* x'[k] = (upper bound) - x[k] */ xassert(mir->ub[k] != +DBL_MAX); kk = mir->vub[k]; if (kk == 0) x = mir->ub[k] - mir->x[k]; else x = mir->ub[k] * mir->x[kk] - mir->x[k]; } else xassert(k != k); r += mir->mod_vec->val[j] * x; if (big < fabs(mir->mod_vec->val[j])) big = fabs(mir->mod_vec->val[j]); } r -= mir->mod_rhs; if (big < fabs(mir->mod_rhs)) big = fabs(mir->mod_rhs); /* the residual must be close to zero */ xassert(fabs(r) <= 1e-6 * big); return; } #endif /*********************************************************************** * mir_ineq - construct MIR inequality * * Given the single constraint mixed integer set * * |N| * X = {(x,s) in Z x R : sum a[j] * x[j] <= b + s}, * + + j in N * * this routine constructs the mixed integer rounding (MIR) inequality * * sum alpha[j] * x[j] <= beta + gamma * s, * j in N * * which is valid for X. * * If the MIR inequality has been successfully constructed, the routine * returns zero. Otherwise, if b is close to nearest integer, there may * be numeric difficulties due to big coefficients; so in this case the * routine returns non-zero. */ static int mir_ineq(const int n, const double a[], const double b, double alpha[], double *beta, double *gamma) { int j; double f, t; if (fabs(b - floor(b + .5)) < 0.01) return 1; f = b - floor(b); for (j = 1; j <= n; j++) { t = (a[j] - floor(a[j])) - f; if (t <= 0.0) alpha[j] = floor(a[j]); else alpha[j] = floor(a[j]) + t / (1.0 - f); } *beta = floor(b); *gamma = 1.0 / (1.0 - f); return 0; } /*********************************************************************** * cmir_ineq - construct c-MIR inequality * * Given the mixed knapsack set * * MK |N| * X = {(x,s) in Z x R : sum a[j] * x[j] <= b + s, * + + j in N * * x[j] <= u[j]}, * * a subset C of variables to be complemented, and a divisor delta > 0, * this routine constructs the complemented MIR (c-MIR) inequality * * sum alpha[j] * x[j] <= beta + gamma * s, * j in N * MK * which is valid for X . * * If the c-MIR inequality has been successfully constructed, the * routine returns zero. Otherwise, if there is a risk of numerical * difficulties due to big coefficients (see comments to the routine * mir_ineq), the routine cmir_ineq returns non-zero. */ static int cmir_ineq(const int n, const double a[], const double b, const double u[], const char cset[], const double delta, double alpha[], double *beta, double *gamma) { int j; double *aa, bb; aa = alpha, bb = b; for (j = 1; j <= n; j++) { aa[j] = a[j] / delta; if (cset[j]) aa[j] = - aa[j], bb -= a[j] * u[j]; } bb /= delta; if (mir_ineq(n, aa, bb, alpha, beta, gamma)) return 1; for (j = 1; j <= n; j++) { if (cset[j]) alpha[j] = - alpha[j], *beta += alpha[j] * u[j]; } *gamma /= delta; return 0; } /*********************************************************************** * cmir_sep - c-MIR separation heuristic * * Given the mixed knapsack set * * MK |N| * X = {(x,s) in Z x R : sum a[j] * x[j] <= b + s, * + + j in N * * x[j] <= u[j]} * * * * * and a fractional point (x , s ), this routine tries to construct * c-MIR inequality * * sum alpha[j] * x[j] <= beta + gamma * s, * j in N * MK * which is valid for X and has (desirably maximal) violation at the * fractional point given. This is attained by choosing an appropriate * set C of variables to be complemented and a divisor delta > 0, which * together define corresponding c-MIR inequality. * * If a violated c-MIR inequality has been successfully constructed, * the routine returns its violation: * * * * * sum alpha[j] * x [j] - beta - gamma * s , * j in N * * which is positive. In case of failure the routine returns zero. */ struct vset { int j; double v; }; static int cmir_cmp(const void *p1, const void *p2) { const struct vset *v1 = p1, *v2 = p2; if (v1->v < v2->v) return -1; if (v1->v > v2->v) return +1; return 0; } static double cmir_sep(const int n, const double a[], const double b, const double u[], const double x[], const double s, double alpha[], double *beta, double *gamma) { int fail, j, k, nv, v; double delta, eps, d_try[1+3], r, r_best; char *cset; struct vset *vset; /* allocate working arrays */ cset = xcalloc(1+n, sizeof(char)); vset = xcalloc(1+n, sizeof(struct vset)); /* choose initial C */ for (j = 1; j <= n; j++) cset[j] = (char)(x[j] >= 0.5 * u[j]); /* choose initial delta */ r_best = delta = 0.0; for (j = 1; j <= n; j++) { xassert(a[j] != 0.0); /* if x[j] is close to its bounds, skip it */ eps = 1e-9 * (1.0 + fabs(u[j])); if (x[j] < eps || x[j] > u[j] - eps) continue; /* try delta = |a[j]| to construct c-MIR inequality */ fail = cmir_ineq(n, a, b, u, cset, fabs(a[j]), alpha, beta, gamma); if (fail) continue; /* compute violation */ r = - (*beta) - (*gamma) * s; for (k = 1; k <= n; k++) r += alpha[k] * x[k]; if (r_best < r) r_best = r, delta = fabs(a[j]); } if (r_best < 0.001) r_best = 0.0; if (r_best == 0.0) goto done; xassert(delta > 0.0); /* try to increase violation by dividing delta by 2, 4, and 8, respectively */ d_try[1] = delta / 2.0; d_try[2] = delta / 4.0; d_try[3] = delta / 8.0; for (j = 1; j <= 3; j++) { /* construct c-MIR inequality */ fail = cmir_ineq(n, a, b, u, cset, d_try[j], alpha, beta, gamma); if (fail) continue; /* compute violation */ r = - (*beta) - (*gamma) * s; for (k = 1; k <= n; k++) r += alpha[k] * x[k]; if (r_best < r) r_best = r, delta = d_try[j]; } /* build subset of variables lying strictly between their bounds and order it by nondecreasing values of |x[j] - u[j]/2| */ nv = 0; for (j = 1; j <= n; j++) { /* if x[j] is close to its bounds, skip it */ eps = 1e-9 * (1.0 + fabs(u[j])); if (x[j] < eps || x[j] > u[j] - eps) continue; /* add x[j] to the subset */ nv++; vset[nv].j = j; vset[nv].v = fabs(x[j] - 0.5 * u[j]); } qsort(&vset[1], nv, sizeof(struct vset), cmir_cmp); /* try to increase violation by successively complementing each variable in the subset */ for (v = 1; v <= nv; v++) { j = vset[v].j; /* replace x[j] by its complement or vice versa */ cset[j] = (char)!cset[j]; /* construct c-MIR inequality */ fail = cmir_ineq(n, a, b, u, cset, delta, alpha, beta, gamma); /* restore the variable */ cset[j] = (char)!cset[j]; /* do not replace the variable in case of failure */ if (fail) continue; /* compute violation */ r = - (*beta) - (*gamma) * s; for (k = 1; k <= n; k++) r += alpha[k] * x[k]; if (r_best < r) r_best = r, cset[j] = (char)!cset[j]; } /* construct the best c-MIR inequality chosen */ fail = cmir_ineq(n, a, b, u, cset, delta, alpha, beta, gamma); xassert(!fail); done: /* free working arrays */ xfree(cset); xfree(vset); /* return to the calling routine */ return r_best; } static double generate(struct MIR *mir) { /* try to generate violated c-MIR cut for modified constraint */ int m = mir->m; int n = mir->n; int j, k, kk, nint; double s, *u, *x, *alpha, r_best = 0.0, b, beta, gamma; ios_copy_vec(mir->cut_vec, mir->mod_vec); mir->cut_rhs = mir->mod_rhs; /* remove small terms, which can appear due to substitution of variable bounds */ ios_clean_vec(mir->cut_vec, DBL_EPSILON); #if _MIR_DEBUG ios_check_vec(mir->cut_vec); #endif /* remove positive continuous terms to obtain MK relaxation */ for (j = 1; j <= mir->cut_vec->nnz; j++) { k = mir->cut_vec->ind[j]; xassert(1 <= k && k <= m+n); if (!mir->isint[k] && mir->cut_vec->val[j] > 0.0) mir->cut_vec->val[j] = 0.0; } ios_clean_vec(mir->cut_vec, 0.0); #if _MIR_DEBUG ios_check_vec(mir->cut_vec); #endif /* move integer terms to the beginning of the sparse vector and determine the number of integer variables */ nint = 0; for (j = 1; j <= mir->cut_vec->nnz; j++) { k = mir->cut_vec->ind[j]; xassert(1 <= k && k <= m+n); if (mir->isint[k]) { double temp; nint++; /* interchange elements [nint] and [j] */ kk = mir->cut_vec->ind[nint]; mir->cut_vec->pos[k] = nint; mir->cut_vec->pos[kk] = j; mir->cut_vec->ind[nint] = k; mir->cut_vec->ind[j] = kk; temp = mir->cut_vec->val[nint]; mir->cut_vec->val[nint] = mir->cut_vec->val[j]; mir->cut_vec->val[j] = temp; } } #if _MIR_DEBUG ios_check_vec(mir->cut_vec); #endif /* if there is no integer variable, nothing to generate */ if (nint == 0) goto done; /* allocate working arrays */ u = xcalloc(1+nint, sizeof(double)); x = xcalloc(1+nint, sizeof(double)); alpha = xcalloc(1+nint, sizeof(double)); /* determine u and x */ for (j = 1; j <= nint; j++) { k = mir->cut_vec->ind[j]; xassert(m+1 <= k && k <= m+n); xassert(mir->isint[k]); u[j] = mir->ub[k] - mir->lb[k]; xassert(u[j] >= 1.0); if (mir->subst[k] == 'L') x[j] = mir->x[k] - mir->lb[k]; else if (mir->subst[k] == 'U') x[j] = mir->ub[k] - mir->x[k]; else xassert(k != k); xassert(x[j] >= -0.001); if (x[j] < 0.0) x[j] = 0.0; } /* compute s = - sum of continuous terms */ s = 0.0; for (j = nint+1; j <= mir->cut_vec->nnz; j++) { double x; k = mir->cut_vec->ind[j]; xassert(1 <= k && k <= m+n); /* must be continuous */ xassert(!mir->isint[k]); if (mir->subst[k] == 'L') { xassert(mir->lb[k] != -DBL_MAX); kk = mir->vlb[k]; if (kk == 0) x = mir->x[k] - mir->lb[k]; else x = mir->x[k] - mir->lb[k] * mir->x[kk]; } else if (mir->subst[k] == 'U') { xassert(mir->ub[k] != +DBL_MAX); kk = mir->vub[k]; if (kk == 0) x = mir->ub[k] - mir->x[k]; else x = mir->ub[k] * mir->x[kk] - mir->x[k]; } else xassert(k != k); xassert(x >= -0.001); if (x < 0.0) x = 0.0; s -= mir->cut_vec->val[j] * x; } xassert(s >= 0.0); /* apply heuristic to obtain most violated c-MIR inequality */ b = mir->cut_rhs; r_best = cmir_sep(nint, mir->cut_vec->val, b, u, x, s, alpha, &beta, &gamma); if (r_best == 0.0) goto skip; xassert(r_best > 0.0); /* convert to raw cut */ /* sum alpha[j] * x[j] <= beta + gamma * s */ for (j = 1; j <= nint; j++) mir->cut_vec->val[j] = alpha[j]; for (j = nint+1; j <= mir->cut_vec->nnz; j++) { k = mir->cut_vec->ind[j]; if (k <= m+n) mir->cut_vec->val[j] *= gamma; } mir->cut_rhs = beta; #if _MIR_DEBUG ios_check_vec(mir->cut_vec); #endif skip: /* free working arrays */ xfree(u); xfree(x); xfree(alpha); done: return r_best; } #if _MIR_DEBUG static void check_raw_cut(struct MIR *mir, double r_best) { /* check raw cut before back bound substitution */ int m = mir->m; int n = mir->n; int j, k, kk; double r, big, x; /* compute the residual r = sum a[k] * x[k] - b and determine big = max(1, |a[k]|, |b|) */ r = 0.0, big = 1.0; for (j = 1; j <= mir->cut_vec->nnz; j++) { k = mir->cut_vec->ind[j]; xassert(1 <= k && k <= m+n); if (mir->subst[k] == 'L') { xassert(mir->lb[k] != -DBL_MAX); kk = mir->vlb[k]; if (kk == 0) x = mir->x[k] - mir->lb[k]; else x = mir->x[k] - mir->lb[k] * mir->x[kk]; } else if (mir->subst[k] == 'U') { xassert(mir->ub[k] != +DBL_MAX); kk = mir->vub[k]; if (kk == 0) x = mir->ub[k] - mir->x[k]; else x = mir->ub[k] * mir->x[kk] - mir->x[k]; } else xassert(k != k); r += mir->cut_vec->val[j] * x; if (big < fabs(mir->cut_vec->val[j])) big = fabs(mir->cut_vec->val[j]); } r -= mir->cut_rhs; if (big < fabs(mir->cut_rhs)) big = fabs(mir->cut_rhs); /* the residual must be close to r_best */ xassert(fabs(r - r_best) <= 1e-6 * big); return; } #endif static void back_subst(struct MIR *mir) { /* back substitution of original bounds */ int m = mir->m; int n = mir->n; int j, jj, k, kk; /* at first, restore bounds of integer variables (because on restoring variable bounds of continuous variables we need original, not shifted, bounds of integer variables) */ for (j = 1; j <= mir->cut_vec->nnz; j++) { k = mir->cut_vec->ind[j]; xassert(1 <= k && k <= m+n); if (!mir->isint[k]) continue; /* skip continuous */ if (mir->subst[k] == 'L') { /* x'[k] = x[k] - lb[k] */ xassert(mir->lb[k] != -DBL_MAX); xassert(mir->vlb[k] == 0); mir->cut_rhs += mir->cut_vec->val[j] * mir->lb[k]; } else if (mir->subst[k] == 'U') { /* x'[k] = ub[k] - x[k] */ xassert(mir->ub[k] != +DBL_MAX); xassert(mir->vub[k] == 0); mir->cut_rhs -= mir->cut_vec->val[j] * mir->ub[k]; mir->cut_vec->val[j] = - mir->cut_vec->val[j]; } else xassert(k != k); } /* now restore bounds of continuous variables */ for (j = 1; j <= mir->cut_vec->nnz; j++) { k = mir->cut_vec->ind[j]; xassert(1 <= k && k <= m+n); if (mir->isint[k]) continue; /* skip integer */ if (mir->subst[k] == 'L') { /* x'[k] = x[k] - (lower bound) */ xassert(mir->lb[k] != -DBL_MAX); kk = mir->vlb[k]; if (kk == 0) { /* x'[k] = x[k] - lb[k] */ mir->cut_rhs += mir->cut_vec->val[j] * mir->lb[k]; } else { /* x'[k] = x[k] - lb[k] * x[kk] */ jj = mir->cut_vec->pos[kk]; #if 0 xassert(jj != 0); #else if (jj == 0) { ios_set_vj(mir->cut_vec, kk, 1.0); jj = mir->cut_vec->pos[kk]; xassert(jj != 0); mir->cut_vec->val[jj] = 0.0; } #endif mir->cut_vec->val[jj] -= mir->cut_vec->val[j] * mir->lb[k]; } } else if (mir->subst[k] == 'U') { /* x'[k] = (upper bound) - x[k] */ xassert(mir->ub[k] != +DBL_MAX); kk = mir->vub[k]; if (kk == 0) { /* x'[k] = ub[k] - x[k] */ mir->cut_rhs -= mir->cut_vec->val[j] * mir->ub[k]; } else { /* x'[k] = ub[k] * x[kk] - x[k] */ jj = mir->cut_vec->pos[kk]; if (jj == 0) { ios_set_vj(mir->cut_vec, kk, 1.0); jj = mir->cut_vec->pos[kk]; xassert(jj != 0); mir->cut_vec->val[jj] = 0.0; } mir->cut_vec->val[jj] += mir->cut_vec->val[j] * mir->ub[k]; } mir->cut_vec->val[j] = - mir->cut_vec->val[j]; } else xassert(k != k); } #if _MIR_DEBUG ios_check_vec(mir->cut_vec); #endif return; } #if _MIR_DEBUG static void check_cut_row(struct MIR *mir, double r_best) { /* check the cut after back bound substitution or elimination of auxiliary variables */ int m = mir->m; int n = mir->n; int j, k; double r, big; /* compute the residual r = sum a[k] * x[k] - b and determine big = max(1, |a[k]|, |b|) */ r = 0.0, big = 1.0; for (j = 1; j <= mir->cut_vec->nnz; j++) { k = mir->cut_vec->ind[j]; xassert(1 <= k && k <= m+n); r += mir->cut_vec->val[j] * mir->x[k]; if (big < fabs(mir->cut_vec->val[j])) big = fabs(mir->cut_vec->val[j]); } r -= mir->cut_rhs; if (big < fabs(mir->cut_rhs)) big = fabs(mir->cut_rhs); /* the residual must be close to r_best */ xassert(fabs(r - r_best) <= 1e-6 * big); return; } #endif static void subst_aux_vars(glp_tree *tree, struct MIR *mir) { /* final substitution to eliminate auxiliary variables */ glp_prob *mip = tree->mip; int m = mir->m; int n = mir->n; GLPAIJ *aij; int j, k, kk, jj; for (j = mir->cut_vec->nnz; j >= 1; j--) { k = mir->cut_vec->ind[j]; xassert(1 <= k && k <= m+n); if (k > m) continue; /* skip structurals */ for (aij = mip->row[k]->ptr; aij != NULL; aij = aij->r_next) { kk = m + aij->col->j; /* structural */ jj = mir->cut_vec->pos[kk]; if (jj == 0) { ios_set_vj(mir->cut_vec, kk, 1.0); jj = mir->cut_vec->pos[kk]; mir->cut_vec->val[jj] = 0.0; } mir->cut_vec->val[jj] += mir->cut_vec->val[j] * aij->val; } mir->cut_vec->val[j] = 0.0; } ios_clean_vec(mir->cut_vec, 0.0); return; } static void add_cut(glp_tree *tree, struct MIR *mir) { /* add constructed cut inequality to the cut pool */ int m = mir->m; int n = mir->n; int j, k, len; int *ind = xcalloc(1+n, sizeof(int)); double *val = xcalloc(1+n, sizeof(double)); len = 0; for (j = mir->cut_vec->nnz; j >= 1; j--) { k = mir->cut_vec->ind[j]; xassert(m+1 <= k && k <= m+n); len++, ind[len] = k - m, val[len] = mir->cut_vec->val[j]; } #if 0 ios_add_cut_row(tree, pool, GLP_RF_MIR, len, ind, val, GLP_UP, mir->cut_rhs); #else glp_ios_add_row(tree, NULL, GLP_RF_MIR, 0, len, ind, val, GLP_UP, mir->cut_rhs); #endif xfree(ind); xfree(val); return; } static int aggregate_row(glp_tree *tree, struct MIR *mir) { /* try to aggregate another row */ glp_prob *mip = tree->mip; int m = mir->m; int n = mir->n; GLPAIJ *aij; IOSVEC *v; int ii, j, jj, k, kk, kappa = 0, ret = 0; double d1, d2, d, d_max = 0.0; /* choose appropriate structural variable in the aggregated row to be substituted */ for (j = 1; j <= mir->agg_vec->nnz; j++) { k = mir->agg_vec->ind[j]; xassert(1 <= k && k <= m+n); if (k <= m) continue; /* skip auxiliary var */ if (mir->isint[k]) continue; /* skip integer var */ if (fabs(mir->agg_vec->val[j]) < 0.001) continue; /* compute distance from x[k] to its lower bound */ kk = mir->vlb[k]; if (kk == 0) { if (mir->lb[k] == -DBL_MAX) d1 = DBL_MAX; else d1 = mir->x[k] - mir->lb[k]; } else { xassert(1 <= kk && kk <= m+n); xassert(mir->isint[kk]); xassert(mir->lb[k] != -DBL_MAX); d1 = mir->x[k] - mir->lb[k] * mir->x[kk]; } /* compute distance from x[k] to its upper bound */ kk = mir->vub[k]; if (kk == 0) { if (mir->vub[k] == +DBL_MAX) d2 = DBL_MAX; else d2 = mir->ub[k] - mir->x[k]; } else { xassert(1 <= kk && kk <= m+n); xassert(mir->isint[kk]); xassert(mir->ub[k] != +DBL_MAX); d2 = mir->ub[k] * mir->x[kk] - mir->x[k]; } /* x[k] cannot be free */ xassert(d1 != DBL_MAX || d2 != DBL_MAX); /* d = min(d1, d2) */ d = (d1 <= d2 ? d1 : d2); xassert(d != DBL_MAX); /* should not be close to corresponding bound */ if (d < 0.001) continue; if (d_max < d) d_max = d, kappa = k; } if (kappa == 0) { /* nothing chosen */ ret = 1; goto done; } /* x[kappa] has been chosen */ xassert(m+1 <= kappa && kappa <= m+n); xassert(!mir->isint[kappa]); /* find another row, which have not been used yet, to eliminate x[kappa] from the aggregated row */ for (ii = 1; ii <= m; ii++) { if (mir->skip[ii]) continue; for (aij = mip->row[ii]->ptr; aij != NULL; aij = aij->r_next) if (aij->col->j == kappa - m) break; if (aij != NULL && fabs(aij->val) >= 0.001) break; } if (ii > m) { /* nothing found */ ret = 2; goto done; } /* row ii has been found; include it in the aggregated list */ mir->agg_cnt++; xassert(mir->agg_cnt <= MAXAGGR); mir->agg_row[mir->agg_cnt] = ii; mir->skip[ii] = 2; /* v := new row */ v = ios_create_vec(m+n); ios_set_vj(v, ii, 1.0); for (aij = mip->row[ii]->ptr; aij != NULL; aij = aij->r_next) ios_set_vj(v, m + aij->col->j, - aij->val); #if _MIR_DEBUG ios_check_vec(v); #endif /* perform gaussian elimination to remove x[kappa] */ j = mir->agg_vec->pos[kappa]; xassert(j != 0); jj = v->pos[kappa]; xassert(jj != 0); ios_linear_comb(mir->agg_vec, - mir->agg_vec->val[j] / v->val[jj], v); ios_delete_vec(v); ios_set_vj(mir->agg_vec, kappa, 0.0); #if _MIR_DEBUG ios_check_vec(mir->agg_vec); #endif done: return ret; } void ios_mir_gen(glp_tree *tree, void *gen) { /* main routine to generate MIR cuts */ glp_prob *mip = tree->mip; struct MIR *mir = gen; int m = mir->m; int n = mir->n; int i; double r_best; xassert(mip->m >= m); xassert(mip->n == n); /* obtain current point */ get_current_point(tree, mir); #if _MIR_DEBUG /* check current point */ check_current_point(mir); #endif /* reset bound substitution flags */ memset(&mir->subst[1], '?', m+n); /* try to generate a set of violated MIR cuts */ for (i = 1; i <= m; i++) { if (mir->skip[i]) continue; /* use original i-th row as initial aggregated constraint */ initial_agg_row(tree, mir, i); loop: ; #if _MIR_DEBUG /* check aggregated row */ check_agg_row(mir); #endif /* substitute fixed variables into aggregated constraint */ subst_fixed_vars(mir); #if _MIR_DEBUG /* check aggregated row */ check_agg_row(mir); #endif #if _MIR_DEBUG /* check bound substitution flags */ { int k; for (k = 1; k <= m+n; k++) xassert(mir->subst[k] == '?'); } #endif /* apply bound substitution heuristic */ bound_subst_heur(mir); /* substitute bounds and build modified constraint */ build_mod_row(mir); #if _MIR_DEBUG /* check modified row */ check_mod_row(mir); #endif /* try to generate violated c-MIR cut for modified row */ r_best = generate(mir); if (r_best > 0.0) { /* success */ #if _MIR_DEBUG /* check raw cut before back bound substitution */ check_raw_cut(mir, r_best); #endif /* back substitution of original bounds */ back_subst(mir); #if _MIR_DEBUG /* check the cut after back bound substitution */ check_cut_row(mir, r_best); #endif /* final substitution to eliminate auxiliary variables */ subst_aux_vars(tree, mir); #if _MIR_DEBUG /* check the cut after elimination of auxiliaries */ check_cut_row(mir, r_best); #endif /* add constructed cut inequality to the cut pool */ add_cut(tree, mir); } /* reset bound substitution flags */ { int j, k; for (j = 1; j <= mir->mod_vec->nnz; j++) { k = mir->mod_vec->ind[j]; xassert(1 <= k && k <= m+n); xassert(mir->subst[k] != '?'); mir->subst[k] = '?'; } } if (r_best == 0.0) { /* failure */ if (mir->agg_cnt < MAXAGGR) { /* try to aggregate another row */ if (aggregate_row(tree, mir) == 0) goto loop; } } /* unmark rows used in the aggregated constraint */ { int k, ii; for (k = 1; k <= mir->agg_cnt; k++) { ii = mir->agg_row[k]; xassert(1 <= ii && ii <= m); xassert(mir->skip[ii] == 2); mir->skip[ii] = 0; } } } return; } /*********************************************************************** * NAME * * ios_mir_term - terminate MIR cut generator * * SYNOPSIS * * #include "glpios.h" * void ios_mir_term(void *gen); * * DESCRIPTION * * The routine ios_mir_term deletes the MIR cut generator working area * freeing all the memory allocated to it. */ void ios_mir_term(void *gen) { struct MIR *mir = gen; xfree(mir->skip); xfree(mir->isint); xfree(mir->lb); xfree(mir->vlb); xfree(mir->ub); xfree(mir->vub); xfree(mir->x); xfree(mir->agg_row); ios_delete_vec(mir->agg_vec); xfree(mir->subst); ios_delete_vec(mir->mod_vec); ios_delete_vec(mir->cut_vec); xfree(mir); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glplib02.c0000644000076500000240000002124313524616144025160 0ustar tamasstaff00000000000000/* glplib02.c (64-bit arithmetic) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wsign-conversion" #pragma clang diagnostic ignored "-Wsometimes-uninitialized" #endif #include "glpenv.h" #include "glplib.h" /*********************************************************************** * NAME * * xlset - expand integer to long integer * * SYNOPSIS * * #include "glplib.h" * glp_long xlset(int x); * * RETURNS * * The routine xlset returns x expanded to long integer. */ glp_long xlset(int x) { glp_long t; t.lo = x, t.hi = (x >= 0 ? 0 : -1); return t; } /*********************************************************************** * NAME * * xlneg - negate long integer * * SYNOPSIS * * #include "glplib.h" * glp_long xlneg(glp_long x); * * RETURNS * * The routine xlneg returns the difference 0 - x. */ glp_long xlneg(glp_long x) { if (x.lo) x.lo = - x.lo, x.hi = ~x.hi; else x.hi = - x.hi; return x; } /*********************************************************************** * NAME * * xladd - add long integers * * SYNOPSIS * * #include "glplib.h" * glp_long xladd(glp_long x, glp_long y); * * RETURNS * * The routine xladd returns the sum x + y. */ glp_long xladd(glp_long x, glp_long y) { if ((unsigned int)x.lo <= 0xFFFFFFFF - (unsigned int)y.lo) x.lo += y.lo, x.hi += y.hi; else x.lo += y.lo, x.hi += y.hi + 1; return x; } /*********************************************************************** * NAME * * xlsub - subtract long integers * * SYNOPSIS * * #include "glplib.h" * glp_long xlsub(glp_long x, glp_long y); * * RETURNS * * The routine xlsub returns the difference x - y. */ glp_long xlsub(glp_long x, glp_long y) { return xladd(x, xlneg(y)); } /*********************************************************************** * NAME * * xlcmp - compare long integers * * SYNOPSIS * * #include "glplib.h" * int xlcmp(glp_long x, glp_long y); * * RETURNS * * The routine xlcmp returns the sign of the difference x - y. */ int xlcmp(glp_long x, glp_long y) { if (x.hi >= 0 && y.hi < 0) return +1; if (x.hi < 0 && y.hi >= 0) return -1; if ((unsigned int)x.hi < (unsigned int)y.hi) return -1; if ((unsigned int)x.hi > (unsigned int)y.hi) return +1; if ((unsigned int)x.lo < (unsigned int)y.lo) return -1; if ((unsigned int)x.lo > (unsigned int)y.lo) return +1; return 0; } /*********************************************************************** * NAME * * xlmul - multiply long integers * * SYNOPSIS * * #include "glplib.h" * glp_long xlmul(glp_long x, glp_long y); * * RETURNS * * The routine xlmul returns the product x * y. */ glp_long xlmul(glp_long x, glp_long y) { unsigned short xx[8], yy[4]; xx[4] = (unsigned short)x.lo; xx[5] = (unsigned short)(x.lo >> 16); xx[6] = (unsigned short)x.hi; xx[7] = (unsigned short)(x.hi >> 16); yy[0] = (unsigned short)y.lo; yy[1] = (unsigned short)(y.lo >> 16); yy[2] = (unsigned short)y.hi; yy[3] = (unsigned short)(y.hi >> 16); bigmul(4, 4, xx, yy); x.lo = (unsigned int)xx[0] | ((unsigned int)xx[1] << 16); x.hi = (unsigned int)xx[2] | ((unsigned int)xx[3] << 16); return x; } /*********************************************************************** * NAME * * xldiv - divide long integers * * SYNOPSIS * * #include "glplib.h" * glp_ldiv xldiv(glp_long x, glp_long y); * * RETURNS * * The routine xldiv returns a structure of type glp_ldiv containing * members quot (the quotient) and rem (the remainder), both of type * glp_long. */ glp_ldiv xldiv(glp_long x, glp_long y) { glp_ldiv t; int m, sx, sy; unsigned short xx[8], yy[4]; /* sx := sign(x) */ sx = (x.hi < 0); /* sy := sign(y) */ sy = (y.hi < 0); /* x := |x| */ if (sx) x = xlneg(x); /* y := |y| */ if (sy) y = xlneg(y); /* compute x div y and x mod y */ xx[0] = (unsigned short)x.lo; xx[1] = (unsigned short)(x.lo >> 16); xx[2] = (unsigned short)x.hi; xx[3] = (unsigned short)(x.hi >> 16); yy[0] = (unsigned short)y.lo; yy[1] = (unsigned short)(y.lo >> 16); yy[2] = (unsigned short)y.hi; yy[3] = (unsigned short)(y.hi >> 16); if (yy[3]) m = 4; else if (yy[2]) m = 3; else if (yy[1]) m = 2; else if (yy[0]) m = 1; else xerror("xldiv: divide by zero\n"); bigdiv(4 - m, m, xx, yy); /* remainder in x[0], x[1], ..., x[m-1] */ t.rem.lo = (unsigned int)xx[0], t.rem.hi = 0; if (m >= 2) t.rem.lo |= (unsigned int)xx[1] << 16; if (m >= 3) t.rem.hi = (unsigned int)xx[2]; if (m >= 4) t.rem.hi |= (unsigned int)xx[3] << 16; if (sx) t.rem = xlneg(t.rem); /* quotient in x[m], x[m+1], ..., x[4] */ t.quot.lo = (unsigned int)xx[m], t.quot.hi = 0; if (m <= 3) t.quot.lo |= (unsigned int)xx[m+1] << 16; if (m <= 2) t.quot.hi = (unsigned int)xx[m+2]; if (m <= 1) t.quot.hi |= (unsigned int)xx[m+3] << 16; if (sx ^ sy) t.quot = xlneg(t.quot); return t; } /*********************************************************************** * NAME * * xltod - convert long integer to double * * SYNOPSIS * * #include "glplib.h" * double xltod(glp_long x); * * RETURNS * * The routine xltod returns x converted to double. */ double xltod(glp_long x) { double s, z; if (x.hi >= 0) s = +1.0; else s = -1.0, x = xlneg(x); if (x.hi >= 0) z = 4294967296.0 * (double)x.hi + (double)(unsigned int)x.lo; else { xassert(x.hi == 0x80000000 && x.lo == 0x00000000); z = 9223372036854775808.0; /* 2^63 */ } return s * z; } char *xltoa(glp_long x, char *s) { /* convert long integer to character string */ static const char *d = "0123456789"; glp_ldiv t; int neg, len; if (x.hi >= 0) neg = 0; else neg = 1, x = xlneg(x); if (x.hi >= 0) { len = 0; while (!(x.hi == 0 && x.lo == 0)) { t = xldiv(x, xlset(10)); xassert(0 <= t.rem.lo && t.rem.lo <= 9); s[len++] = d[t.rem.lo]; x = t.quot; } if (len == 0) s[len++] = d[0]; if (neg) s[len++] = '-'; s[len] = '\0'; strrev(s); } else strcpy(s, "-9223372036854775808"); /* -2^63 */ return s; } /**********************************************************************/ #if 0 #include "glprng.h" #define N_TEST 1000000 /* number of tests */ static glp_long myrand(RNG *rand) { glp_long x; int k; k = rng_unif_rand(rand, 4); xassert(0 <= k && k <= 3); x.lo = rng_unif_rand(rand, 65536); if (k == 1 || k == 3) { x.lo <<= 16; x.lo += rng_unif_rand(rand, 65536); } if (k <= 1) x.hi = 0; else x.hi = rng_unif_rand(rand, 65536); if (k == 3) { x.hi <<= 16; x.hi += rng_unif_rand(rand, 65536); } if (rng_unif_rand(rand, 2)) x = xlneg(x); return x; } int main(void) { RNG *rand; glp_long x, y; glp_ldiv z; int test; rand = rng_create_rand(); for (test = 1; test <= N_TEST; test++) { x = myrand(rand); y = myrand(rand); if (y.lo == 0 && y.hi == 0) y.lo = 1; /* z.quot := x div y, z.rem := x mod y */ z = xldiv(x, y); /* x must be equal to y * z.quot + z.rem */ xassert(xlcmp(x, xladd(xlmul(y, z.quot), z.rem)) == 0); } xprintf("%d tests successfully passed\n", N_TEST); rng_delete_rand(rand); return 0; } #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpnet02.c0000644000076500000240000002443613524616144025207 0ustar tamasstaff00000000000000/* glpnet02.c (permutations to block triangular form) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * This code is the result of translation of the Fortran subroutines * MC13D and MC13E associated with the following paper: * * I.S.Duff, J.K.Reid, Algorithm 529: Permutations to block triangular * form, ACM Trans. on Math. Softw. 4 (1978), 189-192. * * Use of ACM Algorithms is subject to the ACM Software Copyright and * License Agreement. See . * * The translation was made by Andrew Makhorin . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glpnet.h" /*********************************************************************** * NAME * * mc13d - permutations to block triangular form * * SYNOPSIS * * #include "glpnet.h" * int mc13d(int n, const int icn[], const int ip[], const int lenr[], * int ior[], int ib[], int lowl[], int numb[], int prev[]); * * DESCRIPTION * * Given the column numbers of the nonzeros in each row of the sparse * matrix, the routine mc13d finds a symmetric permutation that makes * the matrix block lower triangular. * * INPUT PARAMETERS * * n order of the matrix. * * icn array containing the column indices of the non-zeros. Those * belonging to a single row must be contiguous but the ordering * of column indices within each row is unimportant and wasted * space between rows is permitted. * * ip ip[i], i = 1,2,...,n, is the position in array icn of the * first column index of a non-zero in row i. * * lenr lenr[i], i = 1,2,...,n, is the number of non-zeros in row i. * * OUTPUT PARAMETERS * * ior ior[i], i = 1,2,...,n, gives the position on the original * ordering of the row or column which is in position i in the * permuted form. * * ib ib[i], i = 1,2,...,num, is the row number in the permuted * matrix of the beginning of block i, 1 <= num <= n. * * WORKING ARRAYS * * arp working array of length [1+n], where arp[0] is not used. * arp[i] is one less than the number of unsearched edges leaving * node i. At the end of the algorithm it is set to a permutation * which puts the matrix in block lower triangular form. * * ib working array of length [1+n], where ib[0] is not used. * ib[i] is the position in the ordering of the start of the ith * block. ib[n+1-i] holds the node number of the ith node on the * stack. * * lowl working array of length [1+n], where lowl[0] is not used. * lowl[i] is the smallest stack position of any node to which a * path from node i has been found. It is set to n+1 when node i * is removed from the stack. * * numb working array of length [1+n], where numb[0] is not used. * numb[i] is the position of node i in the stack if it is on it, * is the permuted order of node i for those nodes whose final * position has been found and is otherwise zero. * * prev working array of length [1+n], where prev[0] is not used. * prev[i] is the node at the end of the path when node i was * placed on the stack. * * RETURNS * * The routine mc13d returns num, the number of blocks found. */ int mc13d(int n, const int icn[], const int ip[], const int lenr[], int ior[], int ib[], int lowl[], int numb[], int prev[]) { int *arp = ior; int dummy, i, i1, i2, icnt, ii, isn, ist, ist1, iv, iw, j, lcnt, nnm1, num, stp; /* icnt is the number of nodes whose positions in final ordering have been found. */ icnt = 0; /* num is the number of blocks that have been found. */ num = 0; nnm1 = n + n - 1; /* Initialization of arrays. */ for (j = 1; j <= n; j++) { numb[j] = 0; arp[j] = lenr[j] - 1; } for (isn = 1; isn <= n; isn++) { /* Look for a starting node. */ if (numb[isn] != 0) continue; iv = isn; /* ist is the number of nodes on the stack ... it is the stack pointer. */ ist = 1; /* Put node iv at beginning of stack. */ lowl[iv] = numb[iv] = 1; ib[n] = iv; /* The body of this loop puts a new node on the stack or backtracks. */ for (dummy = 1; dummy <= nnm1; dummy++) { i1 = arp[iv]; /* Have all edges leaving node iv been searched? */ if (i1 >= 0) { i2 = ip[iv] + lenr[iv] - 1; i1 = i2 - i1; /* Look at edges leaving node iv until one enters a new node or all edges are exhausted. */ for (ii = i1; ii <= i2; ii++) { iw = icn[ii]; /* Has node iw been on stack already? */ if (numb[iw] == 0) goto L70; /* Update value of lowl[iv] if necessary. */ if (lowl[iw] < lowl[iv]) lowl[iv] = lowl[iw]; } /* There are no more edges leaving node iv. */ arp[iv] = -1; } /* Is node iv the root of a block? */ if (lowl[iv] < numb[iv]) goto L60; /* Order nodes in a block. */ num++; ist1 = n + 1 - ist; lcnt = icnt + 1; /* Peel block off the top of the stack starting at the top and working down to the root of the block. */ for (stp = ist1; stp <= n; stp++) { iw = ib[stp]; lowl[iw] = n + 1; numb[iw] = ++icnt; if (iw == iv) break; } ist = n - stp; ib[num] = lcnt; /* Are there any nodes left on the stack? */ if (ist != 0) goto L60; /* Have all the nodes been ordered? */ if (icnt < n) break; goto L100; L60: /* Backtrack to previous node on path. */ iw = iv; iv = prev[iv]; /* Update value of lowl[iv] if necessary. */ if (lowl[iw] < lowl[iv]) lowl[iv] = lowl[iw]; continue; L70: /* Put new node on the stack. */ arp[iv] = i2 - ii - 1; prev[iw] = iv; iv = iw; lowl[iv] = numb[iv] = ++ist; ib[n+1-ist] = iv; } } L100: /* Put permutation in the required form. */ for (i = 1; i <= n; i++) arp[numb[i]] = i; return num; } /**********************************************************************/ #if 0 #include "glplib.h" void test(int n, int ipp); int main(void) { /* test program for routine mc13d */ test( 1, 0); test( 2, 1); test( 2, 2); test( 3, 3); test( 4, 4); test( 5, 10); test(10, 10); test(10, 20); test(20, 20); test(20, 50); test(50, 50); test(50, 200); return 0; } void fa01bs(int max, int *nrand); void setup(int n, char a[1+50][1+50], int ip[], int icn[], int lenr[]); void test(int n, int ipp) { int ip[1+50], icn[1+1000], ior[1+50], ib[1+51], iw[1+150], lenr[1+50]; char a[1+50][1+50], hold[1+100]; int i, ii, iblock, ij, index, j, jblock, jj, k9, num; xprintf("\n\n\nMatrix is of order %d and has %d off-diagonal non-" "zeros\n", n, ipp); for (j = 1; j <= n; j++) { for (i = 1; i <= n; i++) a[i][j] = 0; a[j][j] = 1; } for (k9 = 1; k9 <= ipp; k9++) { /* these statements should be replaced by calls to your favorite random number generator to place two pseudo-random numbers between 1 and n in the variables i and j */ for (;;) { fa01bs(n, &i); fa01bs(n, &j); if (!a[i][j]) break; } a[i][j] = 1; } /* setup converts matrix a[i,j] to required sparsity-oriented storage format */ setup(n, a, ip, icn, lenr); num = mc13d(n, icn, ip, lenr, ior, ib, &iw[0], &iw[n], &iw[n+n]); /* output reordered matrix with blocking to improve clarity */ xprintf("\nThe reordered matrix which has %d block%s is of the fo" "rm\n", num, num == 1 ? "" : "s"); ib[num+1] = n + 1; index = 100; iblock = 1; for (i = 1; i <= n; i++) { for (ij = 1; ij <= index; ij++) hold[ij] = ' '; if (i == ib[iblock]) { xprintf("\n"); iblock++; } jblock = 1; index = 0; for (j = 1; j <= n; j++) { if (j == ib[jblock]) { hold[++index] = ' '; jblock++; } ii = ior[i]; jj = ior[j]; hold[++index] = (char)(a[ii][jj] ? 'X' : '0'); } xprintf("%.*s\n", index, &hold[1]); } xprintf("\nThe starting point for each block is given by\n"); for (i = 1; i <= num; i++) { if ((i - 1) % 12 == 0) xprintf("\n"); xprintf(" %4d", ib[i]); } xprintf("\n"); return; } void setup(int n, char a[1+50][1+50], int ip[], int icn[], int lenr[]) { int i, j, ind; for (i = 1; i <= n; i++) lenr[i] = 0; ind = 1; for (i = 1; i <= n; i++) { ip[i] = ind; for (j = 1; j <= n; j++) { if (a[i][j]) { lenr[i]++; icn[ind++] = j; } } } return; } double g = 1431655765.0; double fa01as(int i) { /* random number generator */ g = fmod(g * 9228907.0, 4294967296.0); if (i >= 0) return g / 4294967296.0; else return 2.0 * g / 4294967296.0 - 1.0; } void fa01bs(int max, int *nrand) { *nrand = (int)(fa01as(1) * (double)max) + 1; return; } #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpnet08.c0000644000076500000240000001654513524616144025217 0ustar tamasstaff00000000000000/* glpnet08.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Two subroutines sub() and wclique() below are intended to find a * maximum weight clique in a given undirected graph. These subroutines * are slightly modified version of the program WCLIQUE developed by * Patric Ostergard and based * on ideas from the article "P. R. J. Ostergard, A new algorithm for * the maximum-weight clique problem, submitted for publication", which * in turn is a generalization of the algorithm for unweighted graphs * presented in "P. R. J. Ostergard, A fast algorithm for the maximum * clique problem, submitted for publication". * * USED WITH PERMISSION OF THE AUTHOR OF THE ORIGINAL CODE. * * Changes were made by Andrew Makhorin . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wshorten-64-to-32" #endif #include "glpenv.h" #include "glpnet.h" /*********************************************************************** * NAME * * wclique - find maximum weight clique with Ostergard's algorithm * * SYNOPSIS * * int wclique(int n, const int w[], const unsigned char a[], * int ind[]); * * DESCRIPTION * * The routine wclique finds a maximum weight clique in an undirected * graph with Ostergard's algorithm. * * INPUT PARAMETERS * * n is the number of vertices, n > 0. * * w[i], i = 1,...,n, is a weight of vertex i. * * a[*] is the strict (without main diagonal) lower triangle of the * graph adjacency matrix in packed format. * * OUTPUT PARAMETER * * ind[k], k = 1,...,size, is the number of a vertex included in the * clique found, 1 <= ind[k] <= n, where size is the number of vertices * in the clique returned on exit. * * RETURNS * * The routine returns the clique size, i.e. the number of vertices in * the clique. */ struct csa { /* common storage area */ int n; /* number of vertices */ const int *wt; /* int wt[0:n-1]; */ /* weights */ const unsigned char *a; /* adjacency matrix (packed lower triangle without main diag.) */ int record; /* weight of best clique */ int rec_level; /* number of vertices in best clique */ int *rec; /* int rec[0:n-1]; */ /* best clique so far */ int *clique; /* int clique[0:n-1]; */ /* table for pruning */ int *set; /* int set[0:n-1]; */ /* current clique */ }; #define n (csa->n) #define wt (csa->wt) #define a (csa->a) #define record (csa->record) #define rec_level (csa->rec_level) #define rec (csa->rec) #define clique (csa->clique) #define set (csa->set) #if 0 static int is_edge(struct csa *csa, int i, int j) { /* if there is arc (i,j), the routine returns true; otherwise false; 0 <= i, j < n */ int k; xassert(0 <= i && i < n); xassert(0 <= j && j < n); if (i == j) return 0; if (i < j) k = i, i = j, j = k; k = (i * (i - 1)) / 2 + j; return a[k / CHAR_BIT] & (unsigned char)(1 << ((CHAR_BIT - 1) - k % CHAR_BIT)); } #else #define is_edge(csa, i, j) ((i) == (j) ? 0 : \ (i) > (j) ? is_edge1(i, j) : is_edge1(j, i)) #define is_edge1(i, j) is_edge2(((i) * ((i) - 1)) / 2 + (j)) #define is_edge2(k) (a[(k) / CHAR_BIT] & \ (unsigned char)(1 << ((CHAR_BIT - 1) - (k) % CHAR_BIT))) #endif static void sub(struct csa *csa, int ct, int table[], int level, int weight, int l_weight) { int i, j, k, curr_weight, left_weight, *p1, *p2, *newtable; newtable = xcalloc(n, sizeof(int)); if (ct <= 0) { /* 0 or 1 elements left; include these */ if (ct == 0) { set[level++] = table[0]; weight += l_weight; } if (weight > record) { record = weight; rec_level = level; for (i = 0; i < level; i++) rec[i] = set[i]; } goto done; } for (i = ct; i >= 0; i--) { if ((level == 0) && (i < ct)) goto done; k = table[i]; if ((level > 0) && (clique[k] <= (record - weight))) goto done; /* prune */ set[level] = k; curr_weight = weight + wt[k]; l_weight -= wt[k]; if (l_weight <= (record - curr_weight)) goto done; /* prune */ p1 = newtable; p2 = table; left_weight = 0; while (p2 < table + i) { j = *p2++; if (is_edge(csa, j, k)) { *p1++ = j; left_weight += wt[j]; } } if (left_weight <= (record - curr_weight)) continue; sub(csa, p1 - newtable - 1, newtable, level + 1, curr_weight, left_weight); } done: xfree(newtable); return; } int wclique(int _n, const int w[], const unsigned char _a[], int ind[]) { struct csa _csa, *csa = &_csa; int i, j, p, max_wt, max_nwt, wth, *used, *nwt, *pos; glp_long timer; n = _n; xassert(n > 0); wt = &w[1]; a = _a; record = 0; rec_level = 0; rec = &ind[1]; clique = xcalloc(n, sizeof(int)); set = xcalloc(n, sizeof(int)); used = xcalloc(n, sizeof(int)); nwt = xcalloc(n, sizeof(int)); pos = xcalloc(n, sizeof(int)); /* start timer */ timer = xtime(); /* order vertices */ for (i = 0; i < n; i++) { nwt[i] = 0; for (j = 0; j < n; j++) if (is_edge(csa, i, j)) nwt[i] += wt[j]; } for (i = 0; i < n; i++) used[i] = 0; for (i = n-1; i >= 0; i--) { max_wt = -1; max_nwt = -1; for (j = 0; j < n; j++) { if ((!used[j]) && ((wt[j] > max_wt) || (wt[j] == max_wt && nwt[j] > max_nwt))) { max_wt = wt[j]; max_nwt = nwt[j]; p = j; } } pos[i] = p; used[p] = 1; for (j = 0; j < n; j++) if ((!used[j]) && (j != p) && (is_edge(csa, p, j))) nwt[j] -= wt[p]; } /* main routine */ wth = 0; for (i = 0; i < n; i++) { wth += wt[pos[i]]; sub(csa, i, pos, 0, 0, wth); clique[pos[i]] = record; if (xdifftime(xtime(), timer) >= 5.0 - 0.001) { /* print current record and reset timer */ xprintf("level = %d (%d); best = %d\n", i+1, n, record); timer = xtime(); } } xfree(clique); xfree(set); xfree(used); xfree(nwt); xfree(pos); /* return the solution found */ for (i = 1; i <= rec_level; i++) ind[i]++; return rec_level; } #undef n #undef wt #undef a #undef record #undef rec_level #undef rec #undef clique #undef set /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpgmp.c0000644000076500000240000007603113524616144025040 0ustar tamasstaff00000000000000/* glpgmp.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wlogical-op-parentheses" #pragma clang diagnostic ignored "-Wsign-conversion" #endif #define _GLPSTD_STDIO #include "glpdmp.h" #include "glpgmp.h" #define xfault xerror #ifdef HAVE_GMP /* use GNU MP bignum library */ int gmp_pool_count(void) { return 0; } void gmp_free_mem(void) { return; } #else /* use GLPK bignum module */ static DMP *gmp_pool = NULL; static int gmp_size = 0; static unsigned short *gmp_work = NULL; void *gmp_get_atom(int size) { if (gmp_pool == NULL) gmp_pool = dmp_create_pool(); return dmp_get_atom(gmp_pool, size); } void gmp_free_atom(void *ptr, int size) { xassert(gmp_pool != NULL); dmp_free_atom(gmp_pool, ptr, size); return; } int gmp_pool_count(void) { if (gmp_pool == NULL) return 0; else return dmp_in_use(gmp_pool).lo; } unsigned short *gmp_get_work(int size) { xassert(size > 0); if (gmp_size < size) { if (gmp_size == 0) { xassert(gmp_work == NULL); gmp_size = 100; } else { xassert(gmp_work != NULL); xfree(gmp_work); } while (gmp_size < size) gmp_size += gmp_size; gmp_work = xcalloc(gmp_size, sizeof(unsigned short)); } return gmp_work; } void gmp_free_mem(void) { if (gmp_pool != NULL) dmp_delete_pool(gmp_pool); if (gmp_work != NULL) xfree(gmp_work); gmp_pool = NULL; gmp_size = 0; gmp_work = NULL; return; } /*====================================================================*/ mpz_t _mpz_init(void) { /* initialize x, and set its value to 0 */ mpz_t x; x = gmp_get_atom(sizeof(struct mpz)); x->val = 0; x->ptr = NULL; return x; } void mpz_clear(mpz_t x) { /* free the space occupied by x */ mpz_set_si(x, 0); xassert(x->ptr == NULL); /* free the number descriptor */ gmp_free_atom(x, sizeof(struct mpz)); return; } void mpz_set(mpz_t z, mpz_t x) { /* set the value of z from x */ struct mpz_seg *e, *ee, *es; if (z != x) { mpz_set_si(z, 0); z->val = x->val; xassert(z->ptr == NULL); for (e = x->ptr, es = NULL; e != NULL; e = e->next) { ee = gmp_get_atom(sizeof(struct mpz_seg)); memcpy(ee->d, e->d, 12); ee->next = NULL; if (z->ptr == NULL) z->ptr = ee; else es->next = ee; es = ee; } } return; } void mpz_set_si(mpz_t x, int val) { /* set the value of x to val */ struct mpz_seg *e; /* free existing segments, if any */ while (x->ptr != NULL) { e = x->ptr; x->ptr = e->next; gmp_free_atom(e, sizeof(struct mpz_seg)); } /* assign new value */ if (val == 0x80000000) { /* long format is needed */ x->val = -1; x->ptr = e = gmp_get_atom(sizeof(struct mpz_seg)); memset(e->d, 0, 12); e->d[1] = 0x8000; e->next = NULL; } else { /* short format is enough */ x->val = val; } return; } double mpz_get_d(mpz_t x) { /* convert x to a double, truncating if necessary */ struct mpz_seg *e; int j; double val, deg; if (x->ptr == NULL) val = (double)x->val; else { xassert(x->val != 0); val = 0.0; deg = 1.0; for (e = x->ptr; e != NULL; e = e->next) { for (j = 0; j <= 5; j++) { val += deg * (double)((int)e->d[j]); deg *= 65536.0; } } if (x->val < 0) val = - val; } return val; } double mpz_get_d_2exp(int *exp, mpz_t x) { /* convert x to a double, truncating if necessary (i.e. rounding towards zero), and returning the exponent separately; the return value is in the range 0.5 <= |d| < 1 and the exponent is stored to *exp; d*2^exp is the (truncated) x value; if x is zero, the return is 0.0 and 0 is stored to *exp; this is similar to the standard C frexp function */ struct mpz_seg *e; int j, n, n1; double val; if (x->ptr == NULL) val = (double)x->val, n = 0; else { xassert(x->val != 0); val = 0.0, n = 0; for (e = x->ptr; e != NULL; e = e->next) { for (j = 0; j <= 5; j++) { val += (double)((int)e->d[j]); val /= 65536.0, n += 16; } } if (x->val < 0) val = - val; } val = frexp(val, &n1); *exp = n + n1; return val; } void mpz_swap(mpz_t x, mpz_t y) { /* swap the values x and y efficiently */ int val; void *ptr; val = x->val, ptr = x->ptr; x->val = y->val, x->ptr = y->ptr; y->val = val, y->ptr = ptr; return; } static void normalize(mpz_t x) { /* normalize integer x that includes removing non-significant (leading) zeros and converting to short format, if possible */ struct mpz_seg *es, *e; /* if the integer is in short format, it remains unchanged */ if (x->ptr == NULL) { xassert(x->val != 0x80000000); goto done; } xassert(x->val == +1 || x->val == -1); /* find the last (most significant) non-zero segment */ es = NULL; for (e = x->ptr; e != NULL; e = e->next) { if (e->d[0] || e->d[1] || e->d[2] || e->d[3] || e->d[4] || e->d[5]) es = e; } /* if all segments contain zeros, the integer is zero */ if (es == NULL) { mpz_set_si(x, 0); goto done; } /* remove non-significant (leading) zero segments */ while (es->next != NULL) { e = es->next; es->next = e->next; gmp_free_atom(e, sizeof(struct mpz_seg)); } /* convert the integer to short format, if possible */ e = x->ptr; if (e->next == NULL && e->d[1] <= 0x7FFF && !e->d[2] && !e->d[3] && !e->d[4] && !e->d[5]) { int val; val = (int)e->d[0] + ((int)e->d[1] << 16); if (x->val < 0) val = - val; mpz_set_si(x, val); } done: return; } void mpz_add(mpz_t z, mpz_t x, mpz_t y) { /* set z to x + y */ static struct mpz_seg zero = { { 0, 0, 0, 0, 0, 0 }, NULL }; struct mpz_seg dumx, dumy, *ex, *ey, *ez, *es, *ee; int k, sx, sy, sz; unsigned int t; /* if [x] = 0 then [z] = [y] */ if (x->val == 0) { xassert(x->ptr == NULL); mpz_set(z, y); goto done; } /* if [y] = 0 then [z] = [x] */ if (y->val == 0) { xassert(y->ptr == NULL); mpz_set(z, x); goto done; } /* special case when both [x] and [y] are in short format */ if (x->ptr == NULL && y->ptr == NULL) { int xval = x->val, yval = y->val, zval = x->val + y->val; xassert(xval != 0x80000000 && yval != 0x80000000); if (!(xval > 0 && yval > 0 && zval <= 0 || xval < 0 && yval < 0 && zval >= 0)) { mpz_set_si(z, zval); goto done; } } /* convert [x] to long format, if necessary */ if (x->ptr == NULL) { xassert(x->val != 0x80000000); if (x->val >= 0) { sx = +1; t = (unsigned int)(+ x->val); } else { sx = -1; t = (unsigned int)(- x->val); } ex = &dumx; ex->d[0] = (unsigned short)t; ex->d[1] = (unsigned short)(t >> 16); ex->d[2] = ex->d[3] = ex->d[4] = ex->d[5] = 0; ex->next = NULL; } else { sx = x->val; xassert(sx == +1 || sx == -1); ex = x->ptr; } /* convert [y] to long format, if necessary */ if (y->ptr == NULL) { xassert(y->val != 0x80000000); if (y->val >= 0) { sy = +1; t = (unsigned int)(+ y->val); } else { sy = -1; t = (unsigned int)(- y->val); } ey = &dumy; ey->d[0] = (unsigned short)t; ey->d[1] = (unsigned short)(t >> 16); ey->d[2] = ey->d[3] = ey->d[4] = ey->d[5] = 0; ey->next = NULL; } else { sy = y->val; xassert(sy == +1 || sy == -1); ey = y->ptr; } /* main fragment */ sz = sx; ez = es = NULL; if (sx > 0 && sy > 0 || sx < 0 && sy < 0) { /* [x] and [y] have identical signs -- addition */ t = 0; for (; ex || ey; ex = ex->next, ey = ey->next) { if (ex == NULL) ex = &zero; if (ey == NULL) ey = &zero; ee = gmp_get_atom(sizeof(struct mpz_seg)); for (k = 0; k <= 5; k++) { t += (unsigned int)ex->d[k]; t += (unsigned int)ey->d[k]; ee->d[k] = (unsigned short)t; t >>= 16; } ee->next = NULL; if (ez == NULL) ez = ee; else es->next = ee; es = ee; } if (t) { /* overflow -- one extra digit is needed */ ee = gmp_get_atom(sizeof(struct mpz_seg)); ee->d[0] = 1; ee->d[1] = ee->d[2] = ee->d[3] = ee->d[4] = ee->d[5] = 0; ee->next = NULL; xassert(es != NULL); es->next = ee; } } else { /* [x] and [y] have different signs -- subtraction */ t = 1; for (; ex || ey; ex = ex->next, ey = ey->next) { if (ex == NULL) ex = &zero; if (ey == NULL) ey = &zero; ee = gmp_get_atom(sizeof(struct mpz_seg)); for (k = 0; k <= 5; k++) { t += (unsigned int)ex->d[k]; t += (0xFFFF - (unsigned int)ey->d[k]); ee->d[k] = (unsigned short)t; t >>= 16; } ee->next = NULL; if (ez == NULL) ez = ee; else es->next = ee; es = ee; } if (!t) { /* |[x]| < |[y]| -- result in complement coding */ sz = - sz; t = 1; for (ee = ez; ee != NULL; ee = ee->next) for (k = 0; k <= 5; k++) { t += (0xFFFF - (unsigned int)ee->d[k]); ee->d[k] = (unsigned short)t; t >>= 16; } } } /* contruct and normalize result */ mpz_set_si(z, 0); z->val = sz; z->ptr = ez; normalize(z); done: return; } void mpz_sub(mpz_t z, mpz_t x, mpz_t y) { /* set z to x - y */ if (x == y) mpz_set_si(z, 0); else { y->val = - y->val; mpz_add(z, x, y); if (y != z) y->val = - y->val; } return; } void mpz_mul(mpz_t z, mpz_t x, mpz_t y) { /* set z to x * y */ struct mpz_seg dumx, dumy, *ex, *ey, *es, *e; int sx, sy, k, nx, ny, n; unsigned int t; unsigned short *work, *wx, *wy; /* if [x] = 0 then [z] = 0 */ if (x->val == 0) { xassert(x->ptr == NULL); mpz_set_si(z, 0); goto done; } /* if [y] = 0 then [z] = 0 */ if (y->val == 0) { xassert(y->ptr == NULL); mpz_set_si(z, 0); goto done; } /* special case when both [x] and [y] are in short format */ if (x->ptr == NULL && y->ptr == NULL) { int xval = x->val, yval = y->val, sz = +1; xassert(xval != 0x80000000 && yval != 0x80000000); if (xval < 0) xval = - xval, sz = - sz; if (yval < 0) yval = - yval, sz = - sz; if (xval <= 0x7FFFFFFF / yval) { mpz_set_si(z, sz * (xval * yval)); goto done; } } /* convert [x] to long format, if necessary */ if (x->ptr == NULL) { xassert(x->val != 0x80000000); if (x->val >= 0) { sx = +1; t = (unsigned int)(+ x->val); } else { sx = -1; t = (unsigned int)(- x->val); } ex = &dumx; ex->d[0] = (unsigned short)t; ex->d[1] = (unsigned short)(t >> 16); ex->d[2] = ex->d[3] = ex->d[4] = ex->d[5] = 0; ex->next = NULL; } else { sx = x->val; xassert(sx == +1 || sx == -1); ex = x->ptr; } /* convert [y] to long format, if necessary */ if (y->ptr == NULL) { xassert(y->val != 0x80000000); if (y->val >= 0) { sy = +1; t = (unsigned int)(+ y->val); } else { sy = -1; t = (unsigned int)(- y->val); } ey = &dumy; ey->d[0] = (unsigned short)t; ey->d[1] = (unsigned short)(t >> 16); ey->d[2] = ey->d[3] = ey->d[4] = ey->d[5] = 0; ey->next = NULL; } else { sy = y->val; xassert(sy == +1 || sy == -1); ey = y->ptr; } /* determine the number of digits of [x] */ nx = n = 0; for (e = ex; e != NULL; e = e->next) for (k = 0; k <= 5; k++) { n++; if (e->d[k]) nx = n; } xassert(nx > 0); /* determine the number of digits of [y] */ ny = n = 0; for (e = ey; e != NULL; e = e->next) for (k = 0; k <= 5; k++) { n++; if (e->d[k]) ny = n; } xassert(ny > 0); /* we need working array containing at least nx+ny+ny places */ work = gmp_get_work(nx+ny+ny); /* load digits of [x] */ wx = &work[0]; for (n = 0; n < nx; n++) wx[ny+n] = 0; for (n = 0, e = ex; e != NULL; e = e->next) for (k = 0; k <= 5; k++, n++) if (e->d[k]) wx[ny+n] = e->d[k]; /* load digits of [y] */ wy = &work[nx+ny]; for (n = 0; n < ny; n++) wy[n] = 0; for (n = 0, e = ey; e != NULL; e = e->next) for (k = 0; k <= 5; k++, n++) if (e->d[k]) wy[n] = e->d[k]; /* compute [x] * [y] */ bigmul(nx, ny, wx, wy); /* construct and normalize result */ mpz_set_si(z, 0); z->val = sx * sy; es = NULL; k = 6; for (n = 0; n < nx+ny; n++) { if (k > 5) { e = gmp_get_atom(sizeof(struct mpz_seg)); e->d[0] = e->d[1] = e->d[2] = 0; e->d[3] = e->d[4] = e->d[5] = 0; e->next = NULL; if (z->ptr == NULL) z->ptr = e; else es->next = e; es = e; k = 0; } es->d[k++] = wx[n]; } normalize(z); done: return; } void mpz_neg(mpz_t z, mpz_t x) { /* set z to 0 - x */ mpz_set(z, x); z->val = - z->val; return; } void mpz_abs(mpz_t z, mpz_t x) { /* set z to the absolute value of x */ mpz_set(z, x); if (z->val < 0) z->val = - z->val; return; } void mpz_div(mpz_t q, mpz_t r, mpz_t x, mpz_t y) { /* divide x by y, forming quotient q and/or remainder r if q = NULL then quotient is not stored; if r = NULL then remainder is not stored the sign of quotient is determined as in algebra while the sign of remainder is the same as the sign of dividend: +26 : +7 = +3, remainder is +5 -26 : +7 = -3, remainder is -5 +26 : -7 = -3, remainder is +5 -26 : -7 = +3, remainder is -5 */ struct mpz_seg dumx, dumy, *ex, *ey, *es, *e; int sx, sy, k, nx, ny, n; unsigned int t; unsigned short *work, *wx, *wy; /* divide by zero is not allowed */ if (y->val == 0) { xassert(y->ptr == NULL); xfault("mpz_div: divide by zero not allowed\n"); } /* if [x] = 0 then [q] = [r] = 0 */ if (x->val == 0) { xassert(x->ptr == NULL); if (q != NULL) mpz_set_si(q, 0); if (r != NULL) mpz_set_si(r, 0); goto done; } /* special case when both [x] and [y] are in short format */ if (x->ptr == NULL && y->ptr == NULL) { int xval = x->val, yval = y->val; xassert(xval != 0x80000000 && yval != 0x80000000); if (q != NULL) mpz_set_si(q, xval / yval); if (r != NULL) mpz_set_si(r, xval % yval); goto done; } /* convert [x] to long format, if necessary */ if (x->ptr == NULL) { xassert(x->val != 0x80000000); if (x->val >= 0) { sx = +1; t = (unsigned int)(+ x->val); } else { sx = -1; t = (unsigned int)(- x->val); } ex = &dumx; ex->d[0] = (unsigned short)t; ex->d[1] = (unsigned short)(t >> 16); ex->d[2] = ex->d[3] = ex->d[4] = ex->d[5] = 0; ex->next = NULL; } else { sx = x->val; xassert(sx == +1 || sx == -1); ex = x->ptr; } /* convert [y] to long format, if necessary */ if (y->ptr == NULL) { xassert(y->val != 0x80000000); if (y->val >= 0) { sy = +1; t = (unsigned int)(+ y->val); } else { sy = -1; t = (unsigned int)(- y->val); } ey = &dumy; ey->d[0] = (unsigned short)t; ey->d[1] = (unsigned short)(t >> 16); ey->d[2] = ey->d[3] = ey->d[4] = ey->d[5] = 0; ey->next = NULL; } else { sy = y->val; xassert(sy == +1 || sy == -1); ey = y->ptr; } /* determine the number of digits of [x] */ nx = n = 0; for (e = ex; e != NULL; e = e->next) for (k = 0; k <= 5; k++) { n++; if (e->d[k]) nx = n; } xassert(nx > 0); /* determine the number of digits of [y] */ ny = n = 0; for (e = ey; e != NULL; e = e->next) for (k = 0; k <= 5; k++) { n++; if (e->d[k]) ny = n; } xassert(ny > 0); /* if nx < ny then [q] = 0 and [r] = [x] */ if (nx < ny) { if (r != NULL) mpz_set(r, x); if (q != NULL) mpz_set_si(q, 0); goto done; } /* we need working array containing at least nx+ny+1 places */ work = gmp_get_work(nx+ny+1); /* load digits of [x] */ wx = &work[0]; for (n = 0; n < nx; n++) wx[n] = 0; for (n = 0, e = ex; e != NULL; e = e->next) for (k = 0; k <= 5; k++, n++) if (e->d[k]) wx[n] = e->d[k]; /* load digits of [y] */ wy = &work[nx+1]; for (n = 0; n < ny; n++) wy[n] = 0; for (n = 0, e = ey; e != NULL; e = e->next) for (k = 0; k <= 5; k++, n++) if (e->d[k]) wy[n] = e->d[k]; /* compute quotient and remainder */ xassert(wy[ny-1] != 0); bigdiv(nx-ny, ny, wx, wy); /* construct and normalize quotient */ if (q != NULL) { mpz_set_si(q, 0); q->val = sx * sy; es = NULL; k = 6; for (n = ny; n <= nx; n++) { if (k > 5) { e = gmp_get_atom(sizeof(struct mpz_seg)); e->d[0] = e->d[1] = e->d[2] = 0; e->d[3] = e->d[4] = e->d[5] = 0; e->next = NULL; if (q->ptr == NULL) q->ptr = e; else es->next = e; es = e; k = 0; } es->d[k++] = wx[n]; } normalize(q); } /* construct and normalize remainder */ if (r != NULL) { mpz_set_si(r, 0); r->val = sx; es = NULL; k = 6; for (n = 0; n < ny; n++) { if (k > 5) { e = gmp_get_atom(sizeof(struct mpz_seg)); e->d[0] = e->d[1] = e->d[2] = 0; e->d[3] = e->d[4] = e->d[5] = 0; e->next = NULL; if (r->ptr == NULL) r->ptr = e; else es->next = e; es = e; k = 0; } es->d[k++] = wx[n]; } normalize(r); } done: return; } void mpz_gcd(mpz_t z, mpz_t x, mpz_t y) { /* set z to the greatest common divisor of x and y */ /* in case of arbitrary integers GCD(x, y) = GCD(|x|, |y|), and, in particular, GCD(0, 0) = 0 */ mpz_t u, v, r; mpz_init(u); mpz_init(v); mpz_init(r); mpz_abs(u, x); mpz_abs(v, y); while (mpz_sgn(v)) { mpz_div(NULL, r, u, v); mpz_set(u, v); mpz_set(v, r); } mpz_set(z, u); mpz_clear(u); mpz_clear(v); mpz_clear(r); return; } int mpz_cmp(mpz_t x, mpz_t y) { /* compare x and y; return a positive value if x > y, zero if x = y, or a nefative value if x < y */ static struct mpz_seg zero = { { 0, 0, 0, 0, 0, 0 }, NULL }; struct mpz_seg dumx, dumy, *ex, *ey; int cc, sx, sy, k; unsigned int t; if (x == y) { cc = 0; goto done; } /* special case when both [x] and [y] are in short format */ if (x->ptr == NULL && y->ptr == NULL) { int xval = x->val, yval = y->val; xassert(xval != 0x80000000 && yval != 0x80000000); cc = (xval > yval ? +1 : xval < yval ? -1 : 0); goto done; } /* special case when [x] and [y] have different signs */ if (x->val > 0 && y->val <= 0 || x->val == 0 && y->val < 0) { cc = +1; goto done; } if (x->val < 0 && y->val >= 0 || x->val == 0 && y->val > 0) { cc = -1; goto done; } /* convert [x] to long format, if necessary */ if (x->ptr == NULL) { xassert(x->val != 0x80000000); if (x->val >= 0) { sx = +1; t = (unsigned int)(+ x->val); } else { sx = -1; t = (unsigned int)(- x->val); } ex = &dumx; ex->d[0] = (unsigned short)t; ex->d[1] = (unsigned short)(t >> 16); ex->d[2] = ex->d[3] = ex->d[4] = ex->d[5] = 0; ex->next = NULL; } else { sx = x->val; xassert(sx == +1 || sx == -1); ex = x->ptr; } /* convert [y] to long format, if necessary */ if (y->ptr == NULL) { xassert(y->val != 0x80000000); if (y->val >= 0) { sy = +1; t = (unsigned int)(+ y->val); } else { sy = -1; t = (unsigned int)(- y->val); } ey = &dumy; ey->d[0] = (unsigned short)t; ey->d[1] = (unsigned short)(t >> 16); ey->d[2] = ey->d[3] = ey->d[4] = ey->d[5] = 0; ey->next = NULL; } else { sy = y->val; xassert(sy == +1 || sy == -1); ey = y->ptr; } /* main fragment */ xassert(sx > 0 && sy > 0 || sx < 0 && sy < 0); cc = 0; for (; ex || ey; ex = ex->next, ey = ey->next) { if (ex == NULL) ex = &zero; if (ey == NULL) ey = &zero; for (k = 0; k <= 5; k++) { if (ex->d[k] > ey->d[k]) cc = +1; if (ex->d[k] < ey->d[k]) cc = -1; } } if (sx < 0) cc = - cc; done: return cc; } int mpz_sgn(mpz_t x) { /* return +1 if x > 0, 0 if x = 0, and -1 if x < 0 */ int s; s = (x->val > 0 ? +1 : x->val < 0 ? -1 : 0); return s; } int mpz_out_str(void *_fp, int base, mpz_t x) { /* output x on stream fp, as a string in given base; the base may vary from 2 to 36; return the number of bytes written, or if an error occurred, return 0 */ FILE *fp = _fp; mpz_t b, y, r; int n, j, nwr = 0; unsigned char *d; static char *set = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ"; if (!(2 <= base && base <= 36)) xfault("mpz_out_str: base = %d; invalid base\n", base); mpz_init(b); mpz_set_si(b, base); mpz_init(y); mpz_init(r); /* determine the number of digits */ mpz_abs(y, x); for (n = 0; mpz_sgn(y) != 0; n++) mpz_div(y, NULL, y, b); if (n == 0) n = 1; /* compute the digits */ d = xmalloc(n); mpz_abs(y, x); for (j = 0; j < n; j++) { mpz_div(y, r, y, b); xassert(0 <= r->val && r->val < base && r->ptr == NULL); d[j] = (unsigned char)r->val; } /* output the integer to the stream */ /* if (fp == NULL) fp = stdout; */ if (mpz_sgn(x) < 0) fputc('-', fp), nwr++; for (j = n-1; j >= 0; j--) fputc(set[d[j]], fp), nwr++; if (ferror(fp)) nwr = 0; mpz_clear(b); mpz_clear(y); mpz_clear(r); xfree(d); return nwr; } /*====================================================================*/ mpq_t _mpq_init(void) { /* initialize x, and set its value to 0/1 */ mpq_t x; x = gmp_get_atom(sizeof(struct mpq)); x->p.val = 0; x->p.ptr = NULL; x->q.val = 1; x->q.ptr = NULL; return x; } void mpq_clear(mpq_t x) { /* free the space occupied by x */ mpz_set_si(&x->p, 0); xassert(x->p.ptr == NULL); mpz_set_si(&x->q, 0); xassert(x->q.ptr == NULL); /* free the number descriptor */ gmp_free_atom(x, sizeof(struct mpq)); return; } void mpq_canonicalize(mpq_t x) { /* remove any factors that are common to the numerator and denominator of x, and make the denominator positive */ mpz_t f; xassert(x->q.val != 0); if (x->q.val < 0) { mpz_neg(&x->p, &x->p); mpz_neg(&x->q, &x->q); } mpz_init(f); mpz_gcd(f, &x->p, &x->q); if (!(f->val == 1 && f->ptr == NULL)) { mpz_div(&x->p, NULL, &x->p, f); mpz_div(&x->q, NULL, &x->q, f); } mpz_clear(f); return; } void mpq_set(mpq_t z, mpq_t x) { /* set the value of z from x */ if (z != x) { mpz_set(&z->p, &x->p); mpz_set(&z->q, &x->q); } return; } void mpq_set_si(mpq_t x, int p, unsigned int q) { /* set the value of x to p/q */ if (q == 0) xfault("mpq_set_si: zero denominator not allowed\n"); mpz_set_si(&x->p, p); xassert(q <= 0x7FFFFFFF); mpz_set_si(&x->q, q); return; } double mpq_get_d(mpq_t x) { /* convert x to a double, truncating if necessary */ int np, nq; double p, q; p = mpz_get_d_2exp(&np, &x->p); q = mpz_get_d_2exp(&nq, &x->q); return ldexp(p / q, np - nq); } void mpq_set_d(mpq_t x, double val) { /* set x to val; there is no rounding, the conversion is exact */ int s, n, d, j; double f; mpz_t temp; xassert(-DBL_MAX <= val && val <= +DBL_MAX); mpq_set_si(x, 0, 1); if (val > 0.0) s = +1; else if (val < 0.0) s = -1; else goto done; f = frexp(fabs(val), &n); /* |val| = f * 2^n, where 0.5 <= f < 1.0 */ mpz_init(temp); while (f != 0.0) { f *= 16.0, n -= 4; d = (int)f; xassert(0 <= d && d <= 15); f -= (double)d; /* x := 16 * x + d */ mpz_set_si(temp, 16); mpz_mul(&x->p, &x->p, temp); mpz_set_si(temp, d); mpz_add(&x->p, &x->p, temp); } mpz_clear(temp); /* x := x * 2^n */ if (n > 0) { for (j = 1; j <= n; j++) mpz_add(&x->p, &x->p, &x->p); } else if (n < 0) { for (j = 1; j <= -n; j++) mpz_add(&x->q, &x->q, &x->q); mpq_canonicalize(x); } if (s < 0) mpq_neg(x, x); done: return; } void mpq_add(mpq_t z, mpq_t x, mpq_t y) { /* set z to x + y */ mpz_t p, q; mpz_init(p); mpz_init(q); mpz_mul(p, &x->p, &y->q); mpz_mul(q, &x->q, &y->p); mpz_add(p, p, q); mpz_mul(q, &x->q, &y->q); mpz_set(&z->p, p); mpz_set(&z->q, q); mpz_clear(p); mpz_clear(q); mpq_canonicalize(z); return; } void mpq_sub(mpq_t z, mpq_t x, mpq_t y) { /* set z to x - y */ mpz_t p, q; mpz_init(p); mpz_init(q); mpz_mul(p, &x->p, &y->q); mpz_mul(q, &x->q, &y->p); mpz_sub(p, p, q); mpz_mul(q, &x->q, &y->q); mpz_set(&z->p, p); mpz_set(&z->q, q); mpz_clear(p); mpz_clear(q); mpq_canonicalize(z); return; } void mpq_mul(mpq_t z, mpq_t x, mpq_t y) { /* set z to x * y */ mpz_mul(&z->p, &x->p, &y->p); mpz_mul(&z->q, &x->q, &y->q); mpq_canonicalize(z); return; } void mpq_div(mpq_t z, mpq_t x, mpq_t y) { /* set z to x / y */ mpz_t p, q; if (mpq_sgn(y) == 0) xfault("mpq_div: zero divisor not allowed\n"); mpz_init(p); mpz_init(q); mpz_mul(p, &x->p, &y->q); mpz_mul(q, &x->q, &y->p); mpz_set(&z->p, p); mpz_set(&z->q, q); mpz_clear(p); mpz_clear(q); mpq_canonicalize(z); return; } void mpq_neg(mpq_t z, mpq_t x) { /* set z to 0 - x */ mpq_set(z, x); mpz_neg(&z->p, &z->p); return; } void mpq_abs(mpq_t z, mpq_t x) { /* set z to the absolute value of x */ mpq_set(z, x); mpz_abs(&z->p, &z->p); xassert(mpz_sgn(&x->q) > 0); return; } int mpq_cmp(mpq_t x, mpq_t y) { /* compare x and y; return a positive value if x > y, zero if x = y, or a nefative value if x < y */ mpq_t temp; int s; mpq_init(temp); mpq_sub(temp, x, y); s = mpq_sgn(temp); mpq_clear(temp); return s; } int mpq_sgn(mpq_t x) { /* return +1 if x > 0, 0 if x = 0, and -1 if x < 0 */ int s; s = mpz_sgn(&x->p); xassert(mpz_sgn(&x->q) > 0); return s; } int mpq_out_str(void *_fp, int base, mpq_t x) { /* output x on stream fp, as a string in given base; the base may vary from 2 to 36; output is in the form 'num/den' or if the denominator is 1 then just 'num'; if the parameter fp is a null pointer, stdout is assumed; return the number of bytes written, or if an error occurred, return 0 */ FILE *fp = _fp; int nwr; if (!(2 <= base && base <= 36)) xfault("mpq_out_str: base = %d; invalid base\n", base); /* if (fp == NULL) fp = stdout; */ nwr = mpz_out_str(fp, base, &x->p); if (x->q.val == 1 && x->q.ptr == NULL) ; else { fputc('/', fp), nwr++; nwr += mpz_out_str(fp, base, &x->q); } if (ferror(fp)) nwr = 0; return nwr; } #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpstd.h0000644000076500000240000000254613524616144025054 0ustar tamasstaff00000000000000/* glpstd.h (standard C headers) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPSTD_H #define GLPSTD_H #include #include #include #include #include #include #include #include #include #include #include #include #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpapi15.c0000644000076500000240000004470313524616144025175 0ustar tamasstaff00000000000000/* glpapi15.c (basic graph and network routines) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wshorten-64-to-32" #pragma clang diagnostic ignored "-Wsign-conversion" #endif #include "glpapi.h" /* CAUTION: DO NOT CHANGE THE LIMITS BELOW */ #define NV_MAX 100000000 /* = 100*10^6 */ /* maximal number of vertices in the graph */ #define NA_MAX 500000000 /* = 500*10^6 */ /* maximal number of arcs in the graph */ /*********************************************************************** * NAME * * glp_create_graph - create graph * * SYNOPSIS * * glp_graph *glp_create_graph(int v_size, int a_size); * * DESCRIPTION * * The routine creates a new graph, which initially is empty, i.e. has * no vertices and arcs. * * The parameter v_size specifies the size of data associated with each * vertex of the graph (0 to 256 bytes). * * The parameter a_size specifies the size of data associated with each * arc of the graph (0 to 256 bytes). * * RETURNS * * The routine returns a pointer to the graph created. */ static void create_graph(glp_graph *G, int v_size, int a_size) { G->pool = dmp_create_pool(); G->name = NULL; G->nv_max = 50; G->nv = G->na = 0; G->v = xcalloc(1+G->nv_max, sizeof(glp_vertex *)); G->index = NULL; G->v_size = v_size; G->a_size = a_size; return; } glp_graph *glp_create_graph(int v_size, int a_size) { glp_graph *G; if (!(0 <= v_size && v_size <= 256)) xerror("glp_create_graph: v_size = %d; invalid size of vertex " "data\n", v_size); if (!(0 <= a_size && a_size <= 256)) xerror("glp_create_graph: a_size = %d; invalid size of arc dat" "a\n", a_size); G = xmalloc(sizeof(glp_graph)); create_graph(G, v_size, a_size); return G; } /*********************************************************************** * NAME * * glp_set_graph_name - assign (change) graph name * * SYNOPSIS * * void glp_set_graph_name(glp_graph *G, const char *name); * * DESCRIPTION * * The routine glp_set_graph_name assigns a symbolic name specified by * the character string name (1 to 255 chars) to the graph. * * If the parameter name is NULL or an empty string, the routine erases * the existing symbolic name of the graph. */ void glp_set_graph_name(glp_graph *G, const char *name) { if (G->name != NULL) { dmp_free_atom(G->pool, G->name, strlen(G->name)+1); G->name = NULL; } if (!(name == NULL || name[0] == '\0')) { int j; for (j = 0; name[j] != '\0'; j++) { if (j == 256) xerror("glp_set_graph_name: graph name too long\n"); if (iscntrl((unsigned char)name[j])) xerror("glp_set_graph_name: graph name contains invalid " "character(s)\n"); } G->name = dmp_get_atom(G->pool, strlen(name)+1); strcpy(G->name, name); } return; } /*********************************************************************** * NAME * * glp_add_vertices - add new vertices to graph * * SYNOPSIS * * int glp_add_vertices(glp_graph *G, int nadd); * * DESCRIPTION * * The routine glp_add_vertices adds nadd vertices to the specified * graph. New vertices are always added to the end of the vertex list, * so ordinal numbers of existing vertices remain unchanged. * * Being added each new vertex is isolated (has no incident arcs). * * RETURNS * * The routine glp_add_vertices returns an ordinal number of the first * new vertex added to the graph. */ int glp_add_vertices(glp_graph *G, int nadd) { int i, nv_new; if (nadd < 1) xerror("glp_add_vertices: nadd = %d; invalid number of vertice" "s\n", nadd); if (nadd > NV_MAX - G->nv) xerror("glp_add_vertices: nadd = %d; too many vertices\n", nadd); /* determine new number of vertices */ nv_new = G->nv + nadd; /* increase the room, if necessary */ if (G->nv_max < nv_new) { glp_vertex **save = G->v; while (G->nv_max < nv_new) { G->nv_max += G->nv_max; xassert(G->nv_max > 0); } G->v = xcalloc(1+G->nv_max, sizeof(glp_vertex *)); memcpy(&G->v[1], &save[1], G->nv * sizeof(glp_vertex *)); xfree(save); } /* add new vertices to the end of the vertex list */ for (i = G->nv+1; i <= nv_new; i++) { glp_vertex *v; G->v[i] = v = dmp_get_atom(G->pool, sizeof(glp_vertex)); v->i = i; v->name = NULL; v->entry = NULL; if (G->v_size == 0) v->data = NULL; else { v->data = dmp_get_atom(G->pool, G->v_size); memset(v->data, 0, G->v_size); } v->temp = NULL; v->in = v->out = NULL; } /* set new number of vertices */ G->nv = nv_new; /* return the ordinal number of the first vertex added */ return nv_new - nadd + 1; } /**********************************************************************/ void glp_set_vertex_name(glp_graph *G, int i, const char *name) { /* assign (change) vertex name */ glp_vertex *v; if (!(1 <= i && i <= G->nv)) xerror("glp_set_vertex_name: i = %d; vertex number out of rang" "e\n", i); v = G->v[i]; if (v->name != NULL) { if (v->entry != NULL) { xassert(G->index != NULL); avl_delete_node(G->index, v->entry); v->entry = NULL; } dmp_free_atom(G->pool, v->name, strlen(v->name)+1); v->name = NULL; } if (!(name == NULL || name[0] == '\0')) { int k; for (k = 0; name[k] != '\0'; k++) { if (k == 256) xerror("glp_set_vertex_name: i = %d; vertex name too lon" "g\n", i); if (iscntrl((unsigned char)name[k])) xerror("glp_set_vertex_name: i = %d; vertex name contain" "s invalid character(s)\n", i); } v->name = dmp_get_atom(G->pool, strlen(name)+1); strcpy(v->name, name); if (G->index != NULL) { xassert(v->entry == NULL); v->entry = avl_insert_node(G->index, v->name); avl_set_node_link(v->entry, v); } } return; } /*********************************************************************** * NAME * * glp_add_arc - add new arc to graph * * SYNOPSIS * * glp_arc *glp_add_arc(glp_graph *G, int i, int j); * * DESCRIPTION * * The routine glp_add_arc adds a new arc to the specified graph. * * The parameters i and j specify the ordinal numbers of, resp., tail * and head vertices of the arc. Note that self-loops and multiple arcs * are allowed. * * RETURNS * * The routine glp_add_arc returns a pointer to the arc added. */ glp_arc *glp_add_arc(glp_graph *G, int i, int j) { glp_arc *a; if (!(1 <= i && i <= G->nv)) xerror("glp_add_arc: i = %d; tail vertex number out of range\n" , i); if (!(1 <= j && j <= G->nv)) xerror("glp_add_arc: j = %d; head vertex number out of range\n" , j); if (G->na == NA_MAX) xerror("glp_add_arc: too many arcs\n"); a = dmp_get_atom(G->pool, sizeof(glp_arc)); a->tail = G->v[i]; a->head = G->v[j]; if (G->a_size == 0) a->data = NULL; else { a->data = dmp_get_atom(G->pool, G->a_size); memset(a->data, 0, G->a_size); } a->temp = NULL; a->t_prev = NULL; a->t_next = G->v[i]->out; if (a->t_next != NULL) a->t_next->t_prev = a; a->h_prev = NULL; a->h_next = G->v[j]->in; if (a->h_next != NULL) a->h_next->h_prev = a; G->v[i]->out = G->v[j]->in = a; G->na++; return a; } /*********************************************************************** * NAME * * glp_del_vertices - delete vertices from graph * * SYNOPSIS * * void glp_del_vertices(glp_graph *G, int ndel, const int num[]); * * DESCRIPTION * * The routine glp_del_vertices deletes vertices along with all * incident arcs from the specified graph. Ordinal numbers of vertices * to be deleted should be placed in locations num[1], ..., num[ndel], * ndel > 0. * * Note that deleting vertices involves changing ordinal numbers of * other vertices remaining in the graph. New ordinal numbers of the * remaining vertices are assigned under the assumption that the * original order of vertices is not changed. */ void glp_del_vertices(glp_graph *G, int ndel, const int num[]) { glp_vertex *v; int i, k, nv_new; /* scan the list of vertices to be deleted */ if (!(1 <= ndel && ndel <= G->nv)) xerror("glp_del_vertices: ndel = %d; invalid number of vertice" "s\n", ndel); for (k = 1; k <= ndel; k++) { /* take the number of vertex to be deleted */ i = num[k]; /* obtain pointer to i-th vertex */ if (!(1 <= i && i <= G->nv)) xerror("glp_del_vertices: num[%d] = %d; vertex number out o" "f range\n", k, i); v = G->v[i]; /* check that the vertex is not marked yet */ if (v->i == 0) xerror("glp_del_vertices: num[%d] = %d; duplicate vertex nu" "mbers not allowed\n", k, i); /* erase symbolic name assigned to the vertex */ glp_set_vertex_name(G, i, NULL); xassert(v->name == NULL); xassert(v->entry == NULL); /* free vertex data, if allocated */ if (v->data != NULL) dmp_free_atom(G->pool, v->data, G->v_size); /* delete all incoming arcs */ while (v->in != NULL) glp_del_arc(G, v->in); /* delete all outgoing arcs */ while (v->out != NULL) glp_del_arc(G, v->out); /* mark the vertex to be deleted */ v->i = 0; } /* delete all marked vertices from the vertex list */ nv_new = 0; for (i = 1; i <= G->nv; i++) { /* obtain pointer to i-th vertex */ v = G->v[i]; /* check if the vertex is marked */ if (v->i == 0) { /* it is marked, delete it */ dmp_free_atom(G->pool, v, sizeof(glp_vertex)); } else { /* it is not marked, keep it */ v->i = ++nv_new; G->v[v->i] = v; } } /* set new number of vertices in the graph */ G->nv = nv_new; return; } /*********************************************************************** * NAME * * glp_del_arc - delete arc from graph * * SYNOPSIS * * void glp_del_arc(glp_graph *G, glp_arc *a); * * DESCRIPTION * * The routine glp_del_arc deletes an arc from the specified graph. * The arc to be deleted must exist. */ void glp_del_arc(glp_graph *G, glp_arc *a) { /* some sanity checks */ xassert(G->na > 0); xassert(1 <= a->tail->i && a->tail->i <= G->nv); xassert(a->tail == G->v[a->tail->i]); xassert(1 <= a->head->i && a->head->i <= G->nv); xassert(a->head == G->v[a->head->i]); /* remove the arc from the list of incoming arcs */ if (a->h_prev == NULL) a->head->in = a->h_next; else a->h_prev->h_next = a->h_next; if (a->h_next == NULL) ; else a->h_next->h_prev = a->h_prev; /* remove the arc from the list of outgoing arcs */ if (a->t_prev == NULL) a->tail->out = a->t_next; else a->t_prev->t_next = a->t_next; if (a->t_next == NULL) ; else a->t_next->t_prev = a->t_prev; /* free arc data, if allocated */ if (a->data != NULL) dmp_free_atom(G->pool, a->data, G->a_size); /* delete the arc from the graph */ dmp_free_atom(G->pool, a, sizeof(glp_arc)); G->na--; return; } /*********************************************************************** * NAME * * glp_erase_graph - erase graph content * * SYNOPSIS * * void glp_erase_graph(glp_graph *G, int v_size, int a_size); * * DESCRIPTION * * The routine glp_erase_graph erases the content of the specified * graph. The effect of this operation is the same as if the graph * would be deleted with the routine glp_delete_graph and then created * anew with the routine glp_create_graph, with exception that the * handle (pointer) to the graph remains valid. */ static void delete_graph(glp_graph *G) { dmp_delete_pool(G->pool); xfree(G->v); if (G->index != NULL) avl_delete_tree(G->index); return; } void glp_erase_graph(glp_graph *G, int v_size, int a_size) { if (!(0 <= v_size && v_size <= 256)) xerror("glp_erase_graph: v_size = %d; invalid size of vertex d" "ata\n", v_size); if (!(0 <= a_size && a_size <= 256)) xerror("glp_erase_graph: a_size = %d; invalid size of arc data" "\n", a_size); delete_graph(G); create_graph(G, v_size, a_size); return; } /*********************************************************************** * NAME * * glp_delete_graph - delete graph * * SYNOPSIS * * void glp_delete_graph(glp_graph *G); * * DESCRIPTION * * The routine glp_delete_graph deletes the specified graph and frees * all the memory allocated to this program object. */ void glp_delete_graph(glp_graph *G) { delete_graph(G); xfree(G); return; } /**********************************************************************/ void glp_create_v_index(glp_graph *G) { /* create vertex name index */ glp_vertex *v; int i; if (G->index == NULL) { G->index = avl_create_tree(avl_strcmp, NULL); for (i = 1; i <= G->nv; i++) { v = G->v[i]; xassert(v->entry == NULL); if (v->name != NULL) { v->entry = avl_insert_node(G->index, v->name); avl_set_node_link(v->entry, v); } } } return; } int glp_find_vertex(glp_graph *G, const char *name) { /* find vertex by its name */ AVLNODE *node; int i = 0; if (G->index == NULL) xerror("glp_find_vertex: vertex name index does not exist\n"); if (!(name == NULL || name[0] == '\0' || strlen(name) > 255)) { node = avl_find_node(G->index, name); if (node != NULL) i = ((glp_vertex *)avl_get_node_link(node))->i; } return i; } void glp_delete_v_index(glp_graph *G) { /* delete vertex name index */ int i; if (G->index != NULL) { avl_delete_tree(G->index), G->index = NULL; for (i = 1; i <= G->nv; i++) G->v[i]->entry = NULL; } return; } /*********************************************************************** * NAME * * glp_read_graph - read graph from plain text file * * SYNOPSIS * * int glp_read_graph(glp_graph *G, const char *fname); * * DESCRIPTION * * The routine glp_read_graph reads a graph from a plain text file. * * RETURNS * * If the operation was successful, the routine returns zero. Otherwise * it prints an error message and returns non-zero. */ int glp_read_graph(glp_graph *G, const char *fname) { glp_data *data; jmp_buf jump; int nv, na, i, j, k, ret; glp_erase_graph(G, G->v_size, G->a_size); xprintf("Reading graph from `%s'...\n", fname); data = glp_sdf_open_file(fname); if (data == NULL) { ret = 1; goto done; } if (setjmp(jump)) { ret = 1; goto done; } glp_sdf_set_jump(data, jump); nv = glp_sdf_read_int(data); if (nv < 0) glp_sdf_error(data, "invalid number of vertices\n"); na = glp_sdf_read_int(data); if (na < 0) glp_sdf_error(data, "invalid number of arcs\n"); xprintf("Graph has %d vert%s and %d arc%s\n", nv, nv == 1 ? "ex" : "ices", na, na == 1 ? "" : "s"); if (nv > 0) glp_add_vertices(G, nv); for (k = 1; k <= na; k++) { i = glp_sdf_read_int(data); if (!(1 <= i && i <= nv)) glp_sdf_error(data, "tail vertex number out of range\n"); j = glp_sdf_read_int(data); if (!(1 <= j && j <= nv)) glp_sdf_error(data, "head vertex number out of range\n"); glp_add_arc(G, i, j); } xprintf("%d lines were read\n", glp_sdf_line(data)); ret = 0; done: if (data != NULL) glp_sdf_close_file(data); return ret; } /*********************************************************************** * NAME * * glp_write_graph - write graph to plain text file * * SYNOPSIS * * int glp_write_graph(glp_graph *G, const char *fname). * * DESCRIPTION * * The routine glp_write_graph writes the specified graph to a plain * text file. * * RETURNS * * If the operation was successful, the routine returns zero. Otherwise * it prints an error message and returns non-zero. */ int glp_write_graph(glp_graph *G, const char *fname) { XFILE *fp; glp_vertex *v; glp_arc *a; int i, count, ret; xprintf("Writing graph to `%s'...\n", fname); fp = xfopen(fname, "w"), count = 0; if (fp == NULL) { xprintf("Unable to create `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } xfprintf(fp, "%d %d\n", G->nv, G->na), count++; for (i = 1; i <= G->nv; i++) { v = G->v[i]; for (a = v->out; a != NULL; a = a->t_next) xfprintf(fp, "%d %d\n", a->tail->i, a->head->i), count++; } xfflush(fp); if (xferror(fp)) { xprintf("Write error on `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } xprintf("%d lines were written\n", count); ret = 0; done: if (fp != NULL) xfclose(fp); return ret; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpnpp02.c0000644000076500000240000012623413524616144025215 0ustar tamasstaff00000000000000/* glpnpp02.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glpnpp.h" /*********************************************************************** * NAME * * npp_free_row - process free (unbounded) row * * SYNOPSIS * * #include "glpnpp.h" * void npp_free_row(NPP *npp, NPPROW *p); * * DESCRIPTION * * The routine npp_free_row processes row p, which is free (i.e. has * no finite bounds): * * -inf < sum a[p,j] x[j] < +inf. (1) * j * * PROBLEM TRANSFORMATION * * Constraint (1) cannot be active, so it is redundant and can be * removed from the original problem. * * Removing row p leads to removing a column of multiplier pi[p] for * this row in the dual system. Since row p has no bounds, pi[p] = 0, * so removing the column does not affect the dual solution. * * RECOVERING BASIC SOLUTION * * In solution to the original problem row p is inactive constraint, * so it is assigned status GLP_BS, and multiplier pi[p] is assigned * zero value. * * RECOVERING INTERIOR-POINT SOLUTION * * In solution to the original problem row p is inactive constraint, * so its multiplier pi[p] is assigned zero value. * * RECOVERING MIP SOLUTION * * None needed. */ struct free_row { /* free (unbounded) row */ int p; /* row reference number */ }; static int rcv_free_row(NPP *npp, void *info); void npp_free_row(NPP *npp, NPPROW *p) { /* process free (unbounded) row */ struct free_row *info; /* the row must be free */ xassert(p->lb == -DBL_MAX && p->ub == +DBL_MAX); /* create transformation stack entry */ info = npp_push_tse(npp, rcv_free_row, sizeof(struct free_row)); info->p = p->i; /* remove the row from the problem */ npp_del_row(npp, p); return; } static int rcv_free_row(NPP *npp, void *_info) { /* recover free (unbounded) row */ struct free_row *info = _info; if (npp->sol == GLP_SOL) npp->r_stat[info->p] = GLP_BS; if (npp->sol != GLP_MIP) npp->r_pi[info->p] = 0.0; return 0; } /*********************************************************************** * NAME * * npp_geq_row - process row of 'not less than' type * * SYNOPSIS * * #include "glpnpp.h" * void npp_geq_row(NPP *npp, NPPROW *p); * * DESCRIPTION * * The routine npp_geq_row processes row p, which is 'not less than' * inequality constraint: * * L[p] <= sum a[p,j] x[j] (<= U[p]), (1) * j * * where L[p] < U[p], and upper bound may not exist (U[p] = +oo). * * PROBLEM TRANSFORMATION * * Constraint (1) can be replaced by equality constraint: * * sum a[p,j] x[j] - s = L[p], (2) * j * * where * * 0 <= s (<= U[p] - L[p]) (3) * * is a non-negative surplus variable. * * Since in the primal system there appears column s having the only * non-zero coefficient in row p, in the dual system there appears a * new row: * * (-1) pi[p] + lambda = 0, (4) * * where (-1) is coefficient of column s in row p, pi[p] is multiplier * of row p, lambda is multiplier of column q, 0 is coefficient of * column s in the objective row. * * RECOVERING BASIC SOLUTION * * Status of row p in solution to the original problem is determined * by its status and status of column q in solution to the transformed * problem as follows: * * +--------------------------------------+------------------+ * | Transformed problem | Original problem | * +-----------------+--------------------+------------------+ * | Status of row p | Status of column s | Status of row p | * +-----------------+--------------------+------------------+ * | GLP_BS | GLP_BS | N/A | * | GLP_BS | GLP_NL | GLP_BS | * | GLP_BS | GLP_NU | GLP_BS | * | GLP_NS | GLP_BS | GLP_BS | * | GLP_NS | GLP_NL | GLP_NL | * | GLP_NS | GLP_NU | GLP_NU | * +-----------------+--------------------+------------------+ * * Value of row multiplier pi[p] in solution to the original problem * is the same as in solution to the transformed problem. * * 1. In solution to the transformed problem row p and column q cannot * be basic at the same time; otherwise the basis matrix would have * two linear dependent columns: unity column of auxiliary variable * of row p and unity column of variable s. * * 2. Though in the transformed problem row p is equality constraint, * it may be basic due to primal degenerate solution. * * RECOVERING INTERIOR-POINT SOLUTION * * Value of row multiplier pi[p] in solution to the original problem * is the same as in solution to the transformed problem. * * RECOVERING MIP SOLUTION * * None needed. */ struct ineq_row { /* inequality constraint row */ int p; /* row reference number */ int s; /* column reference number for slack/surplus variable */ }; static int rcv_geq_row(NPP *npp, void *info); void npp_geq_row(NPP *npp, NPPROW *p) { /* process row of 'not less than' type */ struct ineq_row *info; NPPCOL *s; /* the row must have lower bound */ xassert(p->lb != -DBL_MAX); xassert(p->lb < p->ub); /* create column for surplus variable */ s = npp_add_col(npp); s->lb = 0.0; s->ub = (p->ub == +DBL_MAX ? +DBL_MAX : p->ub - p->lb); /* and add it to the transformed problem */ npp_add_aij(npp, p, s, -1.0); /* create transformation stack entry */ info = npp_push_tse(npp, rcv_geq_row, sizeof(struct ineq_row)); info->p = p->i; info->s = s->j; /* replace the row by equality constraint */ p->ub = p->lb; return; } static int rcv_geq_row(NPP *npp, void *_info) { /* recover row of 'not less than' type */ struct ineq_row *info = _info; if (npp->sol == GLP_SOL) { if (npp->r_stat[info->p] == GLP_BS) { if (npp->c_stat[info->s] == GLP_BS) { npp_error(); return 1; } else if (npp->c_stat[info->s] == GLP_NL || npp->c_stat[info->s] == GLP_NU) npp->r_stat[info->p] = GLP_BS; else { npp_error(); return 1; } } else if (npp->r_stat[info->p] == GLP_NS) { if (npp->c_stat[info->s] == GLP_BS) npp->r_stat[info->p] = GLP_BS; else if (npp->c_stat[info->s] == GLP_NL) npp->r_stat[info->p] = GLP_NL; else if (npp->c_stat[info->s] == GLP_NU) npp->r_stat[info->p] = GLP_NU; else { npp_error(); return 1; } } else { npp_error(); return 1; } } return 0; } /*********************************************************************** * NAME * * npp_leq_row - process row of 'not greater than' type * * SYNOPSIS * * #include "glpnpp.h" * void npp_leq_row(NPP *npp, NPPROW *p); * * DESCRIPTION * * The routine npp_leq_row processes row p, which is 'not greater than' * inequality constraint: * * (L[p] <=) sum a[p,j] x[j] <= U[p], (1) * j * * where L[p] < U[p], and lower bound may not exist (L[p] = +oo). * * PROBLEM TRANSFORMATION * * Constraint (1) can be replaced by equality constraint: * * sum a[p,j] x[j] + s = L[p], (2) * j * * where * * 0 <= s (<= U[p] - L[p]) (3) * * is a non-negative slack variable. * * Since in the primal system there appears column s having the only * non-zero coefficient in row p, in the dual system there appears a * new row: * * (+1) pi[p] + lambda = 0, (4) * * where (+1) is coefficient of column s in row p, pi[p] is multiplier * of row p, lambda is multiplier of column q, 0 is coefficient of * column s in the objective row. * * RECOVERING BASIC SOLUTION * * Status of row p in solution to the original problem is determined * by its status and status of column q in solution to the transformed * problem as follows: * * +--------------------------------------+------------------+ * | Transformed problem | Original problem | * +-----------------+--------------------+------------------+ * | Status of row p | Status of column s | Status of row p | * +-----------------+--------------------+------------------+ * | GLP_BS | GLP_BS | N/A | * | GLP_BS | GLP_NL | GLP_BS | * | GLP_BS | GLP_NU | GLP_BS | * | GLP_NS | GLP_BS | GLP_BS | * | GLP_NS | GLP_NL | GLP_NU | * | GLP_NS | GLP_NU | GLP_NL | * +-----------------+--------------------+------------------+ * * Value of row multiplier pi[p] in solution to the original problem * is the same as in solution to the transformed problem. * * 1. In solution to the transformed problem row p and column q cannot * be basic at the same time; otherwise the basis matrix would have * two linear dependent columns: unity column of auxiliary variable * of row p and unity column of variable s. * * 2. Though in the transformed problem row p is equality constraint, * it may be basic due to primal degeneracy. * * RECOVERING INTERIOR-POINT SOLUTION * * Value of row multiplier pi[p] in solution to the original problem * is the same as in solution to the transformed problem. * * RECOVERING MIP SOLUTION * * None needed. */ static int rcv_leq_row(NPP *npp, void *info); void npp_leq_row(NPP *npp, NPPROW *p) { /* process row of 'not greater than' type */ struct ineq_row *info; NPPCOL *s; /* the row must have upper bound */ xassert(p->ub != +DBL_MAX); xassert(p->lb < p->ub); /* create column for slack variable */ s = npp_add_col(npp); s->lb = 0.0; s->ub = (p->lb == -DBL_MAX ? +DBL_MAX : p->ub - p->lb); /* and add it to the transformed problem */ npp_add_aij(npp, p, s, +1.0); /* create transformation stack entry */ info = npp_push_tse(npp, rcv_leq_row, sizeof(struct ineq_row)); info->p = p->i; info->s = s->j; /* replace the row by equality constraint */ p->lb = p->ub; return; } static int rcv_leq_row(NPP *npp, void *_info) { /* recover row of 'not greater than' type */ struct ineq_row *info = _info; if (npp->sol == GLP_SOL) { if (npp->r_stat[info->p] == GLP_BS) { if (npp->c_stat[info->s] == GLP_BS) { npp_error(); return 1; } else if (npp->c_stat[info->s] == GLP_NL || npp->c_stat[info->s] == GLP_NU) npp->r_stat[info->p] = GLP_BS; else { npp_error(); return 1; } } else if (npp->r_stat[info->p] == GLP_NS) { if (npp->c_stat[info->s] == GLP_BS) npp->r_stat[info->p] = GLP_BS; else if (npp->c_stat[info->s] == GLP_NL) npp->r_stat[info->p] = GLP_NU; else if (npp->c_stat[info->s] == GLP_NU) npp->r_stat[info->p] = GLP_NL; else { npp_error(); return 1; } } else { npp_error(); return 1; } } return 0; } /*********************************************************************** * NAME * * npp_free_col - process free (unbounded) column * * SYNOPSIS * * #include "glpnpp.h" * void npp_free_col(NPP *npp, NPPCOL *q); * * DESCRIPTION * * The routine npp_free_col processes column q, which is free (i.e. has * no finite bounds): * * -oo < x[q] < +oo. (1) * * PROBLEM TRANSFORMATION * * Free (unbounded) variable can be replaced by the difference of two * non-negative variables: * * x[q] = s' - s'', s', s'' >= 0. (2) * * Assuming that in the transformed problem x[q] becomes s', * transformation (2) causes new column s'' to appear, which differs * from column s' only in the sign of coefficients in constraint and * objective rows. Thus, if in the dual system the following row * corresponds to column s': * * sum a[i,q] pi[i] + lambda' = c[q], (3) * i * * the row which corresponds to column s'' is the following: * * sum (-a[i,q]) pi[i] + lambda'' = -c[q]. (4) * i * * Then from (3) and (4) it follows that: * * lambda' + lambda'' = 0 => lambda' = lmabda'' = 0, (5) * * where lambda' and lambda'' are multipliers for columns s' and s'', * resp. * * RECOVERING BASIC SOLUTION * * With respect to (5) status of column q in solution to the original * problem is determined by statuses of columns s' and s'' in solution * to the transformed problem as follows: * * +--------------------------------------+------------------+ * | Transformed problem | Original problem | * +------------------+-------------------+------------------+ * | Status of col s' | Status of col s'' | Status of col q | * +------------------+-------------------+------------------+ * | GLP_BS | GLP_BS | N/A | * | GLP_BS | GLP_NL | GLP_BS | * | GLP_NL | GLP_BS | GLP_BS | * | GLP_NL | GLP_NL | GLP_NF | * +------------------+-------------------+------------------+ * * Value of column q is computed with formula (2). * * 1. In solution to the transformed problem columns s' and s'' cannot * be basic at the same time, because they differ only in the sign, * hence, are linear dependent. * * 2. Though column q is free, it can be non-basic due to dual * degeneracy. * * 3. If column q is integral, columns s' and s'' are also integral. * * RECOVERING INTERIOR-POINT SOLUTION * * Value of column q is computed with formula (2). * * RECOVERING MIP SOLUTION * * Value of column q is computed with formula (2). */ struct free_col { /* free (unbounded) column */ int q; /* column reference number for variables x[q] and s' */ int s; /* column reference number for variable s'' */ }; static int rcv_free_col(NPP *npp, void *info); void npp_free_col(NPP *npp, NPPCOL *q) { /* process free (unbounded) column */ struct free_col *info; NPPCOL *s; NPPAIJ *aij; /* the column must be free */ xassert(q->lb == -DBL_MAX && q->ub == +DBL_MAX); /* variable x[q] becomes s' */ q->lb = 0.0, q->ub = +DBL_MAX; /* create variable s'' */ s = npp_add_col(npp); s->is_int = q->is_int; s->lb = 0.0, s->ub = +DBL_MAX; /* duplicate objective coefficient */ s->coef = -q->coef; /* duplicate column of the constraint matrix */ for (aij = q->ptr; aij != NULL; aij = aij->c_next) npp_add_aij(npp, aij->row, s, -aij->val); /* create transformation stack entry */ info = npp_push_tse(npp, rcv_free_col, sizeof(struct free_col)); info->q = q->j; info->s = s->j; return; } static int rcv_free_col(NPP *npp, void *_info) { /* recover free (unbounded) column */ struct free_col *info = _info; if (npp->sol == GLP_SOL) { if (npp->c_stat[info->q] == GLP_BS) { if (npp->c_stat[info->s] == GLP_BS) { npp_error(); return 1; } else if (npp->c_stat[info->s] == GLP_NL) npp->c_stat[info->q] = GLP_BS; else { npp_error(); return -1; } } else if (npp->c_stat[info->q] == GLP_NL) { if (npp->c_stat[info->s] == GLP_BS) npp->c_stat[info->q] = GLP_BS; else if (npp->c_stat[info->s] == GLP_NL) npp->c_stat[info->q] = GLP_NF; else { npp_error(); return -1; } } else { npp_error(); return -1; } } /* compute value of x[q] with formula (2) */ npp->c_value[info->q] -= npp->c_value[info->s]; return 0; } /*********************************************************************** * NAME * * npp_lbnd_col - process column with (non-zero) lower bound * * SYNOPSIS * * #include "glpnpp.h" * void npp_lbnd_col(NPP *npp, NPPCOL *q); * * DESCRIPTION * * The routine npp_lbnd_col processes column q, which has (non-zero) * lower bound: * * l[q] <= x[q] (<= u[q]), (1) * * where l[q] < u[q], and upper bound may not exist (u[q] = +oo). * * PROBLEM TRANSFORMATION * * Column q can be replaced as follows: * * x[q] = l[q] + s, (2) * * where * * 0 <= s (<= u[q] - l[q]) (3) * * is a non-negative variable. * * Substituting x[q] from (2) into the objective row, we have: * * z = sum c[j] x[j] + c0 = * j * * = sum c[j] x[j] + c[q] x[q] + c0 = * j!=q * * = sum c[j] x[j] + c[q] (l[q] + s) + c0 = * j!=q * * = sum c[j] x[j] + c[q] s + c~0, * * where * * c~0 = c0 + c[q] l[q] (4) * * is the constant term of the objective in the transformed problem. * Similarly, substituting x[q] into constraint row i, we have: * * L[i] <= sum a[i,j] x[j] <= U[i] ==> * j * * L[i] <= sum a[i,j] x[j] + a[i,q] x[q] <= U[i] ==> * j!=q * * L[i] <= sum a[i,j] x[j] + a[i,q] (l[q] + s) <= U[i] ==> * j!=q * * L~[i] <= sum a[i,j] x[j] + a[i,q] s <= U~[i], * j!=q * * where * * L~[i] = L[i] - a[i,q] l[q], U~[i] = U[i] - a[i,q] l[q] (5) * * are lower and upper bounds of row i in the transformed problem, * resp. * * Transformation (2) does not affect the dual system. * * RECOVERING BASIC SOLUTION * * Status of column q in solution to the original problem is the same * as in solution to the transformed problem (GLP_BS, GLP_NL or GLP_NU). * Value of column q is computed with formula (2). * * RECOVERING INTERIOR-POINT SOLUTION * * Value of column q is computed with formula (2). * * RECOVERING MIP SOLUTION * * Value of column q is computed with formula (2). */ struct bnd_col { /* bounded column */ int q; /* column reference number for variables x[q] and s */ double bnd; /* lower/upper bound l[q] or u[q] */ }; static int rcv_lbnd_col(NPP *npp, void *info); void npp_lbnd_col(NPP *npp, NPPCOL *q) { /* process column with (non-zero) lower bound */ struct bnd_col *info; NPPROW *i; NPPAIJ *aij; /* the column must have non-zero lower bound */ xassert(q->lb != 0.0); xassert(q->lb != -DBL_MAX); xassert(q->lb < q->ub); /* create transformation stack entry */ info = npp_push_tse(npp, rcv_lbnd_col, sizeof(struct bnd_col)); info->q = q->j; info->bnd = q->lb; /* substitute x[q] into objective row */ npp->c0 += q->coef * q->lb; /* substitute x[q] into constraint rows */ for (aij = q->ptr; aij != NULL; aij = aij->c_next) { i = aij->row; if (i->lb == i->ub) i->ub = (i->lb -= aij->val * q->lb); else { if (i->lb != -DBL_MAX) i->lb -= aij->val * q->lb; if (i->ub != +DBL_MAX) i->ub -= aij->val * q->lb; } } /* column x[q] becomes column s */ if (q->ub != +DBL_MAX) q->ub -= q->lb; q->lb = 0.0; return; } static int rcv_lbnd_col(NPP *npp, void *_info) { /* recover column with (non-zero) lower bound */ struct bnd_col *info = _info; if (npp->sol == GLP_SOL) { if (npp->c_stat[info->q] == GLP_BS || npp->c_stat[info->q] == GLP_NL || npp->c_stat[info->q] == GLP_NU) npp->c_stat[info->q] = npp->c_stat[info->q]; else { npp_error(); return 1; } } /* compute value of x[q] with formula (2) */ npp->c_value[info->q] = info->bnd + npp->c_value[info->q]; return 0; } /*********************************************************************** * NAME * * npp_ubnd_col - process column with upper bound * * SYNOPSIS * * #include "glpnpp.h" * void npp_ubnd_col(NPP *npp, NPPCOL *q); * * DESCRIPTION * * The routine npp_ubnd_col processes column q, which has upper bound: * * (l[q] <=) x[q] <= u[q], (1) * * where l[q] < u[q], and lower bound may not exist (l[q] = -oo). * * PROBLEM TRANSFORMATION * * Column q can be replaced as follows: * * x[q] = u[q] - s, (2) * * where * * 0 <= s (<= u[q] - l[q]) (3) * * is a non-negative variable. * * Substituting x[q] from (2) into the objective row, we have: * * z = sum c[j] x[j] + c0 = * j * * = sum c[j] x[j] + c[q] x[q] + c0 = * j!=q * * = sum c[j] x[j] + c[q] (u[q] - s) + c0 = * j!=q * * = sum c[j] x[j] - c[q] s + c~0, * * where * * c~0 = c0 + c[q] u[q] (4) * * is the constant term of the objective in the transformed problem. * Similarly, substituting x[q] into constraint row i, we have: * * L[i] <= sum a[i,j] x[j] <= U[i] ==> * j * * L[i] <= sum a[i,j] x[j] + a[i,q] x[q] <= U[i] ==> * j!=q * * L[i] <= sum a[i,j] x[j] + a[i,q] (u[q] - s) <= U[i] ==> * j!=q * * L~[i] <= sum a[i,j] x[j] - a[i,q] s <= U~[i], * j!=q * * where * * L~[i] = L[i] - a[i,q] u[q], U~[i] = U[i] - a[i,q] u[q] (5) * * are lower and upper bounds of row i in the transformed problem, * resp. * * Note that in the transformed problem coefficients c[q] and a[i,q] * change their sign. Thus, the row of the dual system corresponding to * column q: * * sum a[i,q] pi[i] + lambda[q] = c[q] (6) * i * * in the transformed problem becomes the following: * * sum (-a[i,q]) pi[i] + lambda[s] = -c[q]. (7) * i * * Therefore: * * lambda[q] = - lambda[s], (8) * * where lambda[q] is multiplier for column q, lambda[s] is multiplier * for column s. * * RECOVERING BASIC SOLUTION * * With respect to (8) status of column q in solution to the original * problem is determined by status of column s in solution to the * transformed problem as follows: * * +-----------------------+--------------------+ * | Status of column s | Status of column q | * | (transformed problem) | (original problem) | * +-----------------------+--------------------+ * | GLP_BS | GLP_BS | * | GLP_NL | GLP_NU | * | GLP_NU | GLP_NL | * +-----------------------+--------------------+ * * Value of column q is computed with formula (2). * * RECOVERING INTERIOR-POINT SOLUTION * * Value of column q is computed with formula (2). * * RECOVERING MIP SOLUTION * * Value of column q is computed with formula (2). */ static int rcv_ubnd_col(NPP *npp, void *info); void npp_ubnd_col(NPP *npp, NPPCOL *q) { /* process column with upper bound */ struct bnd_col *info; NPPROW *i; NPPAIJ *aij; /* the column must have upper bound */ xassert(q->ub != +DBL_MAX); xassert(q->lb < q->ub); /* create transformation stack entry */ info = npp_push_tse(npp, rcv_ubnd_col, sizeof(struct bnd_col)); info->q = q->j; info->bnd = q->ub; /* substitute x[q] into objective row */ npp->c0 += q->coef * q->ub; q->coef = -q->coef; /* substitute x[q] into constraint rows */ for (aij = q->ptr; aij != NULL; aij = aij->c_next) { i = aij->row; if (i->lb == i->ub) i->ub = (i->lb -= aij->val * q->ub); else { if (i->lb != -DBL_MAX) i->lb -= aij->val * q->ub; if (i->ub != +DBL_MAX) i->ub -= aij->val * q->ub; } aij->val = -aij->val; } /* column x[q] becomes column s */ if (q->lb != -DBL_MAX) q->ub -= q->lb; else q->ub = +DBL_MAX; q->lb = 0.0; return; } static int rcv_ubnd_col(NPP *npp, void *_info) { /* recover column with upper bound */ struct bnd_col *info = _info; if (npp->sol == GLP_BS) { if (npp->c_stat[info->q] == GLP_BS) npp->c_stat[info->q] = GLP_BS; else if (npp->c_stat[info->q] == GLP_NL) npp->c_stat[info->q] = GLP_NU; else if (npp->c_stat[info->q] == GLP_NU) npp->c_stat[info->q] = GLP_NL; else { npp_error(); return 1; } } /* compute value of x[q] with formula (2) */ npp->c_value[info->q] = info->bnd - npp->c_value[info->q]; return 0; } /*********************************************************************** * NAME * * npp_dbnd_col - process non-negative column with upper bound * * SYNOPSIS * * #include "glpnpp.h" * void npp_dbnd_col(NPP *npp, NPPCOL *q); * * DESCRIPTION * * The routine npp_dbnd_col processes column q, which is non-negative * and has upper bound: * * 0 <= x[q] <= u[q], (1) * * where u[q] > 0. * * PROBLEM TRANSFORMATION * * Upper bound of column q can be replaced by the following equality * constraint: * * x[q] + s = u[q], (2) * * where s >= 0 is a non-negative complement variable. * * Since in the primal system along with new row (2) there appears a * new column s having the only non-zero coefficient in this row, in * the dual system there appears a new row: * * (+1)pi + lambda[s] = 0, (3) * * where (+1) is coefficient at column s in row (2), pi is multiplier * for row (2), lambda[s] is multiplier for column s, 0 is coefficient * at column s in the objective row. * * RECOVERING BASIC SOLUTION * * Status of column q in solution to the original problem is determined * by its status and status of column s in solution to the transformed * problem as follows: * * +-----------------------------------+------------------+ * | Transformed problem | Original problem | * +-----------------+-----------------+------------------+ * | Status of col q | Status of col s | Status of col q | * +-----------------+-----------------+------------------+ * | GLP_BS | GLP_BS | GLP_BS | * | GLP_BS | GLP_NL | GLP_NU | * | GLP_NL | GLP_BS | GLP_NL | * | GLP_NL | GLP_NL | GLP_NL (*) | * +-----------------+-----------------+------------------+ * * Value of column q in solution to the original problem is the same as * in solution to the transformed problem. * * 1. Formally, in solution to the transformed problem columns q and s * cannot be non-basic at the same time, since the constraint (2) * would be violated. However, if u[q] is close to zero, violation * may be less than a working precision even if both columns q and s * are non-basic. In this degenerate case row (2) can be only basic, * i.e. non-active constraint (otherwise corresponding row of the * basis matrix would be zero). This allows to pivot out auxiliary * variable and pivot in column s, in which case the row becomes * active while column s becomes basic. * * 2. If column q is integral, column s is also integral. * * RECOVERING INTERIOR-POINT SOLUTION * * Value of column q in solution to the original problem is the same as * in solution to the transformed problem. * * RECOVERING MIP SOLUTION * * Value of column q in solution to the original problem is the same as * in solution to the transformed problem. */ struct dbnd_col { /* double-bounded column */ int q; /* column reference number for variable x[q] */ int s; /* column reference number for complement variable s */ }; static int rcv_dbnd_col(NPP *npp, void *info); void npp_dbnd_col(NPP *npp, NPPCOL *q) { /* process non-negative column with upper bound */ struct dbnd_col *info; NPPROW *p; NPPCOL *s; /* the column must be non-negative with upper bound */ xassert(q->lb == 0.0); xassert(q->ub > 0.0); xassert(q->ub != +DBL_MAX); /* create variable s */ s = npp_add_col(npp); s->is_int = q->is_int; s->lb = 0.0, s->ub = +DBL_MAX; /* create equality constraint (2) */ p = npp_add_row(npp); p->lb = p->ub = q->ub; npp_add_aij(npp, p, q, +1.0); npp_add_aij(npp, p, s, +1.0); /* create transformation stack entry */ info = npp_push_tse(npp, rcv_dbnd_col, sizeof(struct dbnd_col)); info->q = q->j; info->s = s->j; /* remove upper bound of x[q] */ q->ub = +DBL_MAX; return; } static int rcv_dbnd_col(NPP *npp, void *_info) { /* recover non-negative column with upper bound */ struct dbnd_col *info = _info; if (npp->sol == GLP_BS) { if (npp->c_stat[info->q] == GLP_BS) { if (npp->c_stat[info->s] == GLP_BS) npp->c_stat[info->q] = GLP_BS; else if (npp->c_stat[info->s] == GLP_NL) npp->c_stat[info->q] = GLP_NU; else { npp_error(); return 1; } } else if (npp->c_stat[info->q] == GLP_NL) { if (npp->c_stat[info->s] == GLP_BS || npp->c_stat[info->s] == GLP_NL) npp->c_stat[info->q] = GLP_NL; else { npp_error(); return 1; } } else { npp_error(); return 1; } } return 0; } /*********************************************************************** * NAME * * npp_fixed_col - process fixed column * * SYNOPSIS * * #include "glpnpp.h" * void npp_fixed_col(NPP *npp, NPPCOL *q); * * DESCRIPTION * * The routine npp_fixed_col processes column q, which is fixed: * * x[q] = s[q], (1) * * where s[q] is a fixed column value. * * PROBLEM TRANSFORMATION * * The value of a fixed column can be substituted into the objective * and constraint rows that allows removing the column from the problem. * * Substituting x[q] = s[q] into the objective row, we have: * * z = sum c[j] x[j] + c0 = * j * * = sum c[j] x[j] + c[q] x[q] + c0 = * j!=q * * = sum c[j] x[j] + c[q] s[q] + c0 = * j!=q * * = sum c[j] x[j] + c~0, * j!=q * * where * * c~0 = c0 + c[q] s[q] (2) * * is the constant term of the objective in the transformed problem. * Similarly, substituting x[q] = s[q] into constraint row i, we have: * * L[i] <= sum a[i,j] x[j] <= U[i] ==> * j * * L[i] <= sum a[i,j] x[j] + a[i,q] x[q] <= U[i] ==> * j!=q * * L[i] <= sum a[i,j] x[j] + a[i,q] s[q] <= U[i] ==> * j!=q * * L~[i] <= sum a[i,j] x[j] + a[i,q] s <= U~[i], * j!=q * * where * * L~[i] = L[i] - a[i,q] s[q], U~[i] = U[i] - a[i,q] s[q] (3) * * are lower and upper bounds of row i in the transformed problem, * resp. * * RECOVERING BASIC SOLUTION * * Column q is assigned status GLP_NS and its value is assigned s[q]. * * RECOVERING INTERIOR-POINT SOLUTION * * Value of column q is assigned s[q]. * * RECOVERING MIP SOLUTION * * Value of column q is assigned s[q]. */ struct fixed_col { /* fixed column */ int q; /* column reference number for variable x[q] */ double s; /* value, at which x[q] is fixed */ }; static int rcv_fixed_col(NPP *npp, void *info); void npp_fixed_col(NPP *npp, NPPCOL *q) { /* process fixed column */ struct fixed_col *info; NPPROW *i; NPPAIJ *aij; /* the column must be fixed */ xassert(q->lb == q->ub); /* create transformation stack entry */ info = npp_push_tse(npp, rcv_fixed_col, sizeof(struct fixed_col)); info->q = q->j; info->s = q->lb; /* substitute x[q] = s[q] into objective row */ npp->c0 += q->coef * q->lb; /* substitute x[q] = s[q] into constraint rows */ for (aij = q->ptr; aij != NULL; aij = aij->c_next) { i = aij->row; if (i->lb == i->ub) i->ub = (i->lb -= aij->val * q->lb); else { if (i->lb != -DBL_MAX) i->lb -= aij->val * q->lb; if (i->ub != +DBL_MAX) i->ub -= aij->val * q->lb; } } /* remove the column from the problem */ npp_del_col(npp, q); return; } static int rcv_fixed_col(NPP *npp, void *_info) { /* recover fixed column */ struct fixed_col *info = _info; if (npp->sol == GLP_SOL) npp->c_stat[info->q] = GLP_NS; npp->c_value[info->q] = info->s; return 0; } /*********************************************************************** * NAME * * npp_make_equality - process row with almost identical bounds * * SYNOPSIS * * #include "glpnpp.h" * int npp_make_equality(NPP *npp, NPPROW *p); * * DESCRIPTION * * The routine npp_make_equality processes row p: * * L[p] <= sum a[p,j] x[j] <= U[p], (1) * j * * where -oo < L[p] < U[p] < +oo, i.e. which is double-sided inequality * constraint. * * RETURNS * * 0 - row bounds have not been changed; * * 1 - row has been replaced by equality constraint. * * PROBLEM TRANSFORMATION * * If bounds of row (1) are very close to each other: * * U[p] - L[p] <= eps, (2) * * where eps is an absolute tolerance for row value, the row can be * replaced by the following almost equivalent equiality constraint: * * sum a[p,j] x[j] = b, (3) * j * * where b = (L[p] + U[p]) / 2. If the right-hand side in (3) happens * to be very close to its nearest integer: * * |b - floor(b + 0.5)| <= eps, (4) * * it is reasonable to use this nearest integer as the right-hand side. * * RECOVERING BASIC SOLUTION * * Status of row p in solution to the original problem is determined * by its status and the sign of its multiplier pi[p] in solution to * the transformed problem as follows: * * +-----------------------+---------+--------------------+ * | Status of row p | Sign of | Status of row p | * | (transformed problem) | pi[p] | (original problem) | * +-----------------------+---------+--------------------+ * | GLP_BS | + / - | GLP_BS | * | GLP_NS | + | GLP_NL | * | GLP_NS | - | GLP_NU | * +-----------------------+---------+--------------------+ * * Value of row multiplier pi[p] in solution to the original problem is * the same as in solution to the transformed problem. * * RECOVERING INTERIOR POINT SOLUTION * * Value of row multiplier pi[p] in solution to the original problem is * the same as in solution to the transformed problem. * * RECOVERING MIP SOLUTION * * None needed. */ struct make_equality { /* row with almost identical bounds */ int p; /* row reference number */ }; static int rcv_make_equality(NPP *npp, void *info); int npp_make_equality(NPP *npp, NPPROW *p) { /* process row with almost identical bounds */ struct make_equality *info; double b, eps, nint; /* the row must be double-sided inequality */ xassert(p->lb != -DBL_MAX); xassert(p->ub != +DBL_MAX); xassert(p->lb < p->ub); /* check row bounds */ eps = 1e-9 + 1e-12 * fabs(p->lb); if (p->ub - p->lb > eps) return 0; /* row bounds are very close to each other */ /* create transformation stack entry */ info = npp_push_tse(npp, rcv_make_equality, sizeof(struct make_equality)); info->p = p->i; /* compute right-hand side */ b = 0.5 * (p->ub + p->lb); nint = floor(b + 0.5); if (fabs(b - nint) <= eps) b = nint; /* replace row p by almost equivalent equality constraint */ p->lb = p->ub = b; return 1; } int rcv_make_equality(NPP *npp, void *_info) { /* recover row with almost identical bounds */ struct make_equality *info = _info; if (npp->sol == GLP_SOL) { if (npp->r_stat[info->p] == GLP_BS) npp->r_stat[info->p] = GLP_BS; else if (npp->r_stat[info->p] == GLP_NS) { if (npp->r_pi[info->p] >= 0.0) npp->r_stat[info->p] = GLP_NL; else npp->r_stat[info->p] = GLP_NU; } else { npp_error(); return 1; } } return 0; } /*********************************************************************** * NAME * * npp_make_fixed - process column with almost identical bounds * * SYNOPSIS * * #include "glpnpp.h" * int npp_make_fixed(NPP *npp, NPPCOL *q); * * DESCRIPTION * * The routine npp_make_fixed processes column q: * * l[q] <= x[q] <= u[q], (1) * * where -oo < l[q] < u[q] < +oo, i.e. which has both lower and upper * bounds. * * RETURNS * * 0 - column bounds have not been changed; * * 1 - column has been fixed. * * PROBLEM TRANSFORMATION * * If bounds of column (1) are very close to each other: * * u[q] - l[q] <= eps, (2) * * where eps is an absolute tolerance for column value, the column can * be fixed: * * x[q] = s[q], (3) * * where s[q] = (l[q] + u[q]) / 2. And if the fixed column value s[q] * happens to be very close to its nearest integer: * * |s[q] - floor(s[q] + 0.5)| <= eps, (4) * * it is reasonable to use this nearest integer as the fixed value. * * RECOVERING BASIC SOLUTION * * In the dual system of the original (as well as transformed) problem * column q corresponds to the following row: * * sum a[i,q] pi[i] + lambda[q] = c[q]. (5) * i * * Since multipliers pi[i] are known for all rows from solution to the * transformed problem, formula (5) allows computing value of multiplier * (reduced cost) for column q: * * lambda[q] = c[q] - sum a[i,q] pi[i]. (6) * i * * Status of column q in solution to the original problem is determined * by its status and the sign of its multiplier lambda[q] in solution to * the transformed problem as follows: * * +-----------------------+-----------+--------------------+ * | Status of column q | Sign of | Status of column q | * | (transformed problem) | lambda[q] | (original problem) | * +-----------------------+-----------+--------------------+ * | GLP_BS | + / - | GLP_BS | * | GLP_NS | + | GLP_NL | * | GLP_NS | - | GLP_NU | * +-----------------------+-----------+--------------------+ * * Value of column q in solution to the original problem is the same as * in solution to the transformed problem. * * RECOVERING INTERIOR POINT SOLUTION * * Value of column q in solution to the original problem is the same as * in solution to the transformed problem. * * RECOVERING MIP SOLUTION * * None needed. */ struct make_fixed { /* column with almost identical bounds */ int q; /* column reference number */ double c; /* objective coefficient at x[q] */ NPPLFE *ptr; /* list of non-zero coefficients a[i,q] */ }; static int rcv_make_fixed(NPP *npp, void *info); int npp_make_fixed(NPP *npp, NPPCOL *q) { /* process column with almost identical bounds */ struct make_fixed *info; NPPAIJ *aij; NPPLFE *lfe; double s, eps, nint; /* the column must be double-bounded */ xassert(q->lb != -DBL_MAX); xassert(q->ub != +DBL_MAX); xassert(q->lb < q->ub); /* check column bounds */ eps = 1e-9 + 1e-12 * fabs(q->lb); if (q->ub - q->lb > eps) return 0; /* column bounds are very close to each other */ /* create transformation stack entry */ info = npp_push_tse(npp, rcv_make_fixed, sizeof(struct make_fixed)); info->q = q->j; info->c = q->coef; info->ptr = NULL; /* save column coefficients a[i,q] (needed for basic solution only) */ if (npp->sol == GLP_SOL) { for (aij = q->ptr; aij != NULL; aij = aij->c_next) { lfe = dmp_get_atom(npp->stack, sizeof(NPPLFE)); lfe->ref = aij->row->i; lfe->val = aij->val; lfe->next = info->ptr; info->ptr = lfe; } } /* compute column fixed value */ s = 0.5 * (q->ub + q->lb); nint = floor(s + 0.5); if (fabs(s - nint) <= eps) s = nint; /* make column q fixed */ q->lb = q->ub = s; return 1; } static int rcv_make_fixed(NPP *npp, void *_info) { /* recover column with almost identical bounds */ struct make_fixed *info = _info; NPPLFE *lfe; double lambda; if (npp->sol == GLP_SOL) { if (npp->c_stat[info->q] == GLP_BS) npp->c_stat[info->q] = GLP_BS; else if (npp->c_stat[info->q] == GLP_NS) { /* compute multiplier for column q with formula (6) */ lambda = info->c; for (lfe = info->ptr; lfe != NULL; lfe = lfe->next) lambda -= lfe->val * npp->r_pi[lfe->ref]; /* assign status to non-basic column */ if (lambda >= 0.0) npp->c_stat[info->q] = GLP_NL; else npp->c_stat[info->q] = GLP_NU; } else { npp_error(); return 1; } } return 0; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpipm.c0000644000076500000240000011423513524616144025041 0ustar tamasstaff00000000000000/* glpipm.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wsometimes-uninitialized" #endif #include "glpipm.h" #include "glpmat.h" #define ITER_MAX 100 /* maximal number of iterations */ struct csa { /* common storage area */ /*--------------------------------------------------------------*/ /* LP data */ int m; /* number of rows (equality constraints) */ int n; /* number of columns (structural variables) */ int *A_ptr; /* int A_ptr[1+m+1]; */ int *A_ind; /* int A_ind[A_ptr[m+1]]; */ double *A_val; /* double A_val[A_ptr[m+1]]; */ /* mxn-matrix A in storage-by-rows format */ double *b; /* double b[1+m]; */ /* m-vector b of right-hand sides */ double *c; /* double c[1+n]; */ /* n-vector c of objective coefficients; c[0] is constant term of the objective function */ /*--------------------------------------------------------------*/ /* LP solution */ double *x; /* double x[1+n]; */ double *y; /* double y[1+m]; */ double *z; /* double z[1+n]; */ /* current point in primal-dual space; the best point on exit */ /*--------------------------------------------------------------*/ /* control parameters */ const glp_iptcp *parm; /*--------------------------------------------------------------*/ /* working arrays and variables */ double *D; /* double D[1+n]; */ /* diagonal nxn-matrix D = X*inv(Z), where X = diag(x[j]) and Z = diag(z[j]) */ int *P; /* int P[1+m+m]; */ /* permutation mxm-matrix P used to minimize fill-in in Cholesky factorization */ int *S_ptr; /* int S_ptr[1+m+1]; */ int *S_ind; /* int S_ind[S_ptr[m+1]]; */ double *S_val; /* double S_val[S_ptr[m+1]]; */ double *S_diag; /* double S_diag[1+m]; */ /* symmetric mxm-matrix S = P*A*D*A'*P' whose upper triangular part without diagonal elements is stored in S_ptr, S_ind, and S_val in storage-by-rows format, diagonal elements are stored in S_diag */ int *U_ptr; /* int U_ptr[1+m+1]; */ int *U_ind; /* int U_ind[U_ptr[m+1]]; */ double *U_val; /* double U_val[U_ptr[m+1]]; */ double *U_diag; /* double U_diag[1+m]; */ /* upper triangular mxm-matrix U defining Cholesky factorization S = U'*U; its non-diagonal elements are stored in U_ptr, U_ind, U_val in storage-by-rows format, diagonal elements are stored in U_diag */ int iter; /* iteration number (0, 1, 2, ...); iter = 0 corresponds to the initial point */ double obj; /* current value of the objective function */ double rpi; /* relative primal infeasibility rpi = ||A*x-b||/(1+||b||) */ double rdi; /* relative dual infeasibility rdi = ||A'*y+z-c||/(1+||c||) */ double gap; /* primal-dual gap = |c'*x-b'*y|/(1+|c'*x|) which is a relative difference between primal and dual objective functions */ double phi; /* merit function phi = ||A*x-b||/max(1,||b||) + + ||A'*y+z-c||/max(1,||c||) + + |c'*x-b'*y|/max(1,||b||,||c||) */ double mu; /* duality measure mu = x'*z/n (used as barrier parameter) */ double rmu; /* rmu = max(||A*x-b||,||A'*y+z-c||)/mu */ double rmu0; /* the initial value of rmu on iteration 0 */ double *phi_min; /* double phi_min[1+ITER_MAX]; */ /* phi_min[k] = min(phi[k]), where phi[k] is the value of phi on k-th iteration, 0 <= k <= iter */ int best_iter; /* iteration number, on which the value of phi reached its best (minimal) value */ double *best_x; /* double best_x[1+n]; */ double *best_y; /* double best_y[1+m]; */ double *best_z; /* double best_z[1+n]; */ /* best point (in the sense of the merit function phi) which has been reached on iteration iter_best */ double best_obj; /* objective value at the best point */ double *dx_aff; /* double dx_aff[1+n]; */ double *dy_aff; /* double dy_aff[1+m]; */ double *dz_aff; /* double dz_aff[1+n]; */ /* affine scaling direction */ double alfa_aff_p, alfa_aff_d; /* maximal primal and dual stepsizes in affine scaling direction, on which x and z are still non-negative */ double mu_aff; /* duality measure mu_aff = x_aff'*z_aff/n in the boundary point x_aff' = x+alfa_aff_p*dx_aff, z_aff' = z+alfa_aff_d*dz_aff */ double sigma; /* Mehrotra's heuristic parameter (0 <= sigma <= 1) */ double *dx_cc; /* double dx_cc[1+n]; */ double *dy_cc; /* double dy_cc[1+m]; */ double *dz_cc; /* double dz_cc[1+n]; */ /* centering corrector direction */ double *dx; /* double dx[1+n]; */ double *dy; /* double dy[1+m]; */ double *dz; /* double dz[1+n]; */ /* final combined direction dx = dx_aff+dx_cc, dy = dy_aff+dy_cc, dz = dz_aff+dz_cc */ double alfa_max_p; double alfa_max_d; /* maximal primal and dual stepsizes in combined direction, on which x and z are still non-negative */ }; /*********************************************************************** * initialize - allocate and initialize common storage area * * This routine allocates and initializes the common storage area (CSA) * used by interior-point method routines. */ static void initialize(struct csa *csa) { int m = csa->m; int n = csa->n; int i; if (csa->parm->msg_lev >= GLP_MSG_ALL) xprintf("Matrix A has %d non-zeros\n", csa->A_ptr[m+1]-1); csa->D = xcalloc(1+n, sizeof(double)); /* P := I */ csa->P = xcalloc(1+m+m, sizeof(int)); for (i = 1; i <= m; i++) csa->P[i] = csa->P[m+i] = i; /* S := A*A', symbolically */ csa->S_ptr = xcalloc(1+m+1, sizeof(int)); csa->S_ind = adat_symbolic(m, n, csa->P, csa->A_ptr, csa->A_ind, csa->S_ptr); if (csa->parm->msg_lev >= GLP_MSG_ALL) xprintf("Matrix S = A*A' has %d non-zeros (upper triangle)\n", csa->S_ptr[m+1]-1 + m); /* determine P using specified ordering algorithm */ if (csa->parm->ord_alg == GLP_ORD_NONE) { if (csa->parm->msg_lev >= GLP_MSG_ALL) xprintf("Original ordering is being used\n"); for (i = 1; i <= m; i++) csa->P[i] = csa->P[m+i] = i; } else if (csa->parm->ord_alg == GLP_ORD_QMD) { if (csa->parm->msg_lev >= GLP_MSG_ALL) xprintf("Minimum degree ordering (QMD)...\n"); min_degree(m, csa->S_ptr, csa->S_ind, csa->P); } else if (csa->parm->ord_alg == GLP_ORD_AMD) { if (csa->parm->msg_lev >= GLP_MSG_ALL) xprintf("Approximate minimum degree ordering (AMD)...\n"); amd_order1(m, csa->S_ptr, csa->S_ind, csa->P); } else if (csa->parm->ord_alg == GLP_ORD_SYMAMD) { if (csa->parm->msg_lev >= GLP_MSG_ALL) xprintf("Approximate minimum degree ordering (SYMAMD)...\n") ; symamd_ord(m, csa->S_ptr, csa->S_ind, csa->P); } else xassert(csa != csa); /* S := P*A*A'*P', symbolically */ xfree(csa->S_ind); csa->S_ind = adat_symbolic(m, n, csa->P, csa->A_ptr, csa->A_ind, csa->S_ptr); csa->S_val = xcalloc(csa->S_ptr[m+1], sizeof(double)); csa->S_diag = xcalloc(1+m, sizeof(double)); /* compute Cholesky factorization S = U'*U, symbolically */ if (csa->parm->msg_lev >= GLP_MSG_ALL) xprintf("Computing Cholesky factorization S = L*L'...\n"); csa->U_ptr = xcalloc(1+m+1, sizeof(int)); csa->U_ind = chol_symbolic(m, csa->S_ptr, csa->S_ind, csa->U_ptr); if (csa->parm->msg_lev >= GLP_MSG_ALL) xprintf("Matrix L has %d non-zeros\n", csa->U_ptr[m+1]-1 + m); csa->U_val = xcalloc(csa->U_ptr[m+1], sizeof(double)); csa->U_diag = xcalloc(1+m, sizeof(double)); csa->iter = 0; csa->obj = 0.0; csa->rpi = 0.0; csa->rdi = 0.0; csa->gap = 0.0; csa->phi = 0.0; csa->mu = 0.0; csa->rmu = 0.0; csa->rmu0 = 0.0; csa->phi_min = xcalloc(1+ITER_MAX, sizeof(double)); csa->best_iter = 0; csa->best_x = xcalloc(1+n, sizeof(double)); csa->best_y = xcalloc(1+m, sizeof(double)); csa->best_z = xcalloc(1+n, sizeof(double)); csa->best_obj = 0.0; csa->dx_aff = xcalloc(1+n, sizeof(double)); csa->dy_aff = xcalloc(1+m, sizeof(double)); csa->dz_aff = xcalloc(1+n, sizeof(double)); csa->alfa_aff_p = 0.0; csa->alfa_aff_d = 0.0; csa->mu_aff = 0.0; csa->sigma = 0.0; csa->dx_cc = xcalloc(1+n, sizeof(double)); csa->dy_cc = xcalloc(1+m, sizeof(double)); csa->dz_cc = xcalloc(1+n, sizeof(double)); csa->dx = csa->dx_aff; csa->dy = csa->dy_aff; csa->dz = csa->dz_aff; csa->alfa_max_p = 0.0; csa->alfa_max_d = 0.0; return; } /*********************************************************************** * A_by_vec - compute y = A*x * * This routine computes matrix-vector product y = A*x, where A is the * constraint matrix. */ static void A_by_vec(struct csa *csa, double x[], double y[]) { /* compute y = A*x */ int m = csa->m; int *A_ptr = csa->A_ptr; int *A_ind = csa->A_ind; double *A_val = csa->A_val; int i, t, beg, end; double temp; for (i = 1; i <= m; i++) { temp = 0.0; beg = A_ptr[i], end = A_ptr[i+1]; for (t = beg; t < end; t++) temp += A_val[t] * x[A_ind[t]]; y[i] = temp; } return; } /*********************************************************************** * AT_by_vec - compute y = A'*x * * This routine computes matrix-vector product y = A'*x, where A' is a * matrix transposed to the constraint matrix A. */ static void AT_by_vec(struct csa *csa, double x[], double y[]) { /* compute y = A'*x, where A' is transposed to A */ int m = csa->m; int n = csa->n; int *A_ptr = csa->A_ptr; int *A_ind = csa->A_ind; double *A_val = csa->A_val; int i, j, t, beg, end; double temp; for (j = 1; j <= n; j++) y[j] = 0.0; for (i = 1; i <= m; i++) { temp = x[i]; if (temp == 0.0) continue; beg = A_ptr[i], end = A_ptr[i+1]; for (t = beg; t < end; t++) y[A_ind[t]] += A_val[t] * temp; } return; } /*********************************************************************** * decomp_NE - numeric factorization of matrix S = P*A*D*A'*P' * * This routine implements numeric phase of Cholesky factorization of * the matrix S = P*A*D*A'*P', which is a permuted matrix of the normal * equation system. Matrix D is assumed to be already computed. */ static void decomp_NE(struct csa *csa) { adat_numeric(csa->m, csa->n, csa->P, csa->A_ptr, csa->A_ind, csa->A_val, csa->D, csa->S_ptr, csa->S_ind, csa->S_val, csa->S_diag); chol_numeric(csa->m, csa->S_ptr, csa->S_ind, csa->S_val, csa->S_diag, csa->U_ptr, csa->U_ind, csa->U_val, csa->U_diag); return; } /*********************************************************************** * solve_NE - solve normal equation system * * This routine solves the normal equation system: * * A*D*A'*y = h. * * It is assumed that the matrix A*D*A' has been previously factorized * by the routine decomp_NE. * * On entry the array y contains the vector of right-hand sides h. On * exit this array contains the computed vector of unknowns y. * * Once the vector y has been computed the routine checks for numeric * stability. If the residual vector: * * r = A*D*A'*y - h * * is relatively small, the routine returns zero, otherwise non-zero is * returned. */ static int solve_NE(struct csa *csa, double y[]) { int m = csa->m; int n = csa->n; int *P = csa->P; int i, j, ret = 0; double *h, *r, *w; /* save vector of right-hand sides h */ h = xcalloc(1+m, sizeof(double)); for (i = 1; i <= m; i++) h[i] = y[i]; /* solve normal equation system (A*D*A')*y = h */ /* since S = P*A*D*A'*P' = U'*U, then A*D*A' = P'*U'*U*P, so we have inv(A*D*A') = P'*inv(U)*inv(U')*P */ /* w := P*h */ w = xcalloc(1+m, sizeof(double)); for (i = 1; i <= m; i++) w[i] = y[P[i]]; /* w := inv(U')*w */ ut_solve(m, csa->U_ptr, csa->U_ind, csa->U_val, csa->U_diag, w); /* w := inv(U)*w */ u_solve(m, csa->U_ptr, csa->U_ind, csa->U_val, csa->U_diag, w); /* y := P'*w */ for (i = 1; i <= m; i++) y[i] = w[P[m+i]]; xfree(w); /* compute residual vector r = A*D*A'*y - h */ r = xcalloc(1+m, sizeof(double)); /* w := A'*y */ w = xcalloc(1+n, sizeof(double)); AT_by_vec(csa, y, w); /* w := D*w */ for (j = 1; j <= n; j++) w[j] *= csa->D[j]; /* r := A*w */ A_by_vec(csa, w, r); xfree(w); /* r := r - h */ for (i = 1; i <= m; i++) r[i] -= h[i]; /* check for numeric stability */ for (i = 1; i <= m; i++) { if (fabs(r[i]) / (1.0 + fabs(h[i])) > 1e-4) { ret = 1; break; } } xfree(h); xfree(r); return ret; } /*********************************************************************** * solve_NS - solve Newtonian system * * This routine solves the Newtonian system: * * A*dx = p * * A'*dy + dz = q * * Z*dx + X*dz = r * * where X = diag(x[j]), Z = diag(z[j]), by reducing it to the normal * equation system: * * (A*inv(Z)*X*A')*dy = A*inv(Z)*(X*q-r)+p * * (it is assumed that the matrix A*inv(Z)*X*A' has been factorized by * the routine decomp_NE). * * Once vector dy has been computed the routine computes vectors dx and * dz as follows: * * dx = inv(Z)*(X*(A'*dy-q)+r) * * dz = inv(X)*(r-Z*dx) * * The routine solve_NS returns the same code which was reported by the * routine solve_NE (see above). */ static int solve_NS(struct csa *csa, double p[], double q[], double r[], double dx[], double dy[], double dz[]) { int m = csa->m; int n = csa->n; double *x = csa->x; double *z = csa->z; int i, j, ret; double *w = dx; /* compute the vector of right-hand sides A*inv(Z)*(X*q-r)+p for the normal equation system */ for (j = 1; j <= n; j++) w[j] = (x[j] * q[j] - r[j]) / z[j]; A_by_vec(csa, w, dy); for (i = 1; i <= m; i++) dy[i] += p[i]; /* solve the normal equation system to compute vector dy */ ret = solve_NE(csa, dy); /* compute vectors dx and dz */ AT_by_vec(csa, dy, dx); for (j = 1; j <= n; j++) { dx[j] = (x[j] * (dx[j] - q[j]) + r[j]) / z[j]; dz[j] = (r[j] - z[j] * dx[j]) / x[j]; } return ret; } /*********************************************************************** * initial_point - choose initial point using Mehrotra's heuristic * * This routine chooses a starting point using a heuristic proposed in * the paper: * * S. Mehrotra. On the implementation of a primal-dual interior point * method. SIAM J. on Optim., 2(4), pp. 575-601, 1992. * * The starting point x in the primal space is chosen as a solution of * the following least squares problem: * * minimize ||x|| * * subject to A*x = b * * which can be computed explicitly as follows: * * x = A'*inv(A*A')*b * * Similarly, the starting point (y, z) in the dual space is chosen as * a solution of the following least squares problem: * * minimize ||z|| * * subject to A'*y + z = c * * which can be computed explicitly as follows: * * y = inv(A*A')*A*c * * z = c - A'*y * * However, some components of the vectors x and z may be non-positive * or close to zero, so the routine uses a Mehrotra's heuristic to find * a more appropriate starting point. */ static void initial_point(struct csa *csa) { int m = csa->m; int n = csa->n; double *b = csa->b; double *c = csa->c; double *x = csa->x; double *y = csa->y; double *z = csa->z; double *D = csa->D; int i, j; double dp, dd, ex, ez, xz; /* factorize A*A' */ for (j = 1; j <= n; j++) D[j] = 1.0; decomp_NE(csa); /* x~ = A'*inv(A*A')*b */ for (i = 1; i <= m; i++) y[i] = b[i]; solve_NE(csa, y); AT_by_vec(csa, y, x); /* y~ = inv(A*A')*A*c */ A_by_vec(csa, c, y); solve_NE(csa, y); /* z~ = c - A'*y~ */ AT_by_vec(csa, y,z); for (j = 1; j <= n; j++) z[j] = c[j] - z[j]; /* use Mehrotra's heuristic in order to choose more appropriate starting point with positive components of vectors x and z */ dp = dd = 0.0; for (j = 1; j <= n; j++) { if (dp < -1.5 * x[j]) dp = -1.5 * x[j]; if (dd < -1.5 * z[j]) dd = -1.5 * z[j]; } /* note that b = 0 involves x = 0, and c = 0 involves y = 0 and z = 0, so we need to be careful */ if (dp == 0.0) dp = 1.5; if (dd == 0.0) dd = 1.5; ex = ez = xz = 0.0; for (j = 1; j <= n; j++) { ex += (x[j] + dp); ez += (z[j] + dd); xz += (x[j] + dp) * (z[j] + dd); } dp += 0.5 * (xz / ez); dd += 0.5 * (xz / ex); for (j = 1; j <= n; j++) { x[j] += dp; z[j] += dd; xassert(x[j] > 0.0 && z[j] > 0.0); } return; } /*********************************************************************** * basic_info - perform basic computations at the current point * * This routine computes the following quantities at the current point: * * 1) value of the objective function: * * F = c'*x + c[0] * * 2) relative primal infeasibility: * * rpi = ||A*x-b|| / (1+||b||) * * 3) relative dual infeasibility: * * rdi = ||A'*y+z-c|| / (1+||c||) * * 4) primal-dual gap (relative difference between the primal and the * dual objective function values): * * gap = |c'*x-b'*y| / (1+|c'*x|) * * 5) merit function: * * phi = ||A*x-b|| / max(1,||b||) + ||A'*y+z-c|| / max(1,||c||) + * * + |c'*x-b'*y| / max(1,||b||,||c||) * * 6) duality measure: * * mu = x'*z / n * * 7) the ratio of infeasibility to mu: * * rmu = max(||A*x-b||,||A'*y+z-c||) / mu * * where ||*|| denotes euclidian norm, *' denotes transposition. */ static void basic_info(struct csa *csa) { int m = csa->m; int n = csa->n; double *b = csa->b; double *c = csa->c; double *x = csa->x; double *y = csa->y; double *z = csa->z; int i, j; double norm1, bnorm, norm2, cnorm, cx, by, *work, temp; /* compute value of the objective function */ temp = c[0]; for (j = 1; j <= n; j++) temp += c[j] * x[j]; csa->obj = temp; /* norm1 = ||A*x-b|| */ work = xcalloc(1+m, sizeof(double)); A_by_vec(csa, x, work); norm1 = 0.0; for (i = 1; i <= m; i++) norm1 += (work[i] - b[i]) * (work[i] - b[i]); norm1 = sqrt(norm1); xfree(work); /* bnorm = ||b|| */ bnorm = 0.0; for (i = 1; i <= m; i++) bnorm += b[i] * b[i]; bnorm = sqrt(bnorm); /* compute relative primal infeasibility */ csa->rpi = norm1 / (1.0 + bnorm); /* norm2 = ||A'*y+z-c|| */ work = xcalloc(1+n, sizeof(double)); AT_by_vec(csa, y, work); norm2 = 0.0; for (j = 1; j <= n; j++) norm2 += (work[j] + z[j] - c[j]) * (work[j] + z[j] - c[j]); norm2 = sqrt(norm2); xfree(work); /* cnorm = ||c|| */ cnorm = 0.0; for (j = 1; j <= n; j++) cnorm += c[j] * c[j]; cnorm = sqrt(cnorm); /* compute relative dual infeasibility */ csa->rdi = norm2 / (1.0 + cnorm); /* by = b'*y */ by = 0.0; for (i = 1; i <= m; i++) by += b[i] * y[i]; /* cx = c'*x */ cx = 0.0; for (j = 1; j <= n; j++) cx += c[j] * x[j]; /* compute primal-dual gap */ csa->gap = fabs(cx - by) / (1.0 + fabs(cx)); /* compute merit function */ csa->phi = 0.0; csa->phi += norm1 / (bnorm > 1.0 ? bnorm : 1.0); csa->phi += norm2 / (cnorm > 1.0 ? cnorm : 1.0); temp = 1.0; if (temp < bnorm) temp = bnorm; if (temp < cnorm) temp = cnorm; csa->phi += fabs(cx - by) / temp; /* compute duality measure */ temp = 0.0; for (j = 1; j <= n; j++) temp += x[j] * z[j]; csa->mu = temp / (double)n; /* compute the ratio of infeasibility to mu */ csa->rmu = (norm1 > norm2 ? norm1 : norm2) / csa->mu; return; } /*********************************************************************** * make_step - compute next point using Mehrotra's technique * * This routine computes the next point using the predictor-corrector * technique proposed in the paper: * * S. Mehrotra. On the implementation of a primal-dual interior point * method. SIAM J. on Optim., 2(4), pp. 575-601, 1992. * * At first, the routine computes so called affine scaling (predictor) * direction (dx_aff,dy_aff,dz_aff) which is a solution of the system: * * A*dx_aff = b - A*x * * A'*dy_aff + dz_aff = c - A'*y - z * * Z*dx_aff + X*dz_aff = - X*Z*e * * where (x,y,z) is the current point, X = diag(x[j]), Z = diag(z[j]), * e = (1,...,1)'. * * Then, the routine computes the centering parameter sigma, using the * following Mehrotra's heuristic: * * alfa_aff_p = inf{0 <= alfa <= 1 | x+alfa*dx_aff >= 0} * * alfa_aff_d = inf{0 <= alfa <= 1 | z+alfa*dz_aff >= 0} * * mu_aff = (x+alfa_aff_p*dx_aff)'*(z+alfa_aff_d*dz_aff)/n * * sigma = (mu_aff/mu)^3 * * where alfa_aff_p is the maximal stepsize along the affine scaling * direction in the primal space, alfa_aff_d is the maximal stepsize * along the same direction in the dual space. * * After determining sigma the routine computes so called centering * (corrector) direction (dx_cc,dy_cc,dz_cc) which is the solution of * the system: * * A*dx_cc = 0 * * A'*dy_cc + dz_cc = 0 * * Z*dx_cc + X*dz_cc = sigma*mu*e - X*Z*e * * Finally, the routine computes the combined direction * * (dx,dy,dz) = (dx_aff,dy_aff,dz_aff) + (dx_cc,dy_cc,dz_cc) * * and determines maximal primal and dual stepsizes along the combined * direction: * * alfa_max_p = inf{0 <= alfa <= 1 | x+alfa*dx >= 0} * * alfa_max_d = inf{0 <= alfa <= 1 | z+alfa*dz >= 0} * * In order to prevent the next point to be too close to the boundary * of the positive ortant, the routine decreases maximal stepsizes: * * alfa_p = gamma_p * alfa_max_p * * alfa_d = gamma_d * alfa_max_d * * where gamma_p and gamma_d are scaling factors, and computes the next * point: * * x_new = x + alfa_p * dx * * y_new = y + alfa_d * dy * * z_new = z + alfa_d * dz * * which becomes the current point on the next iteration. */ static int make_step(struct csa *csa) { int m = csa->m; int n = csa->n; double *b = csa->b; double *c = csa->c; double *x = csa->x; double *y = csa->y; double *z = csa->z; double *dx_aff = csa->dx_aff; double *dy_aff = csa->dy_aff; double *dz_aff = csa->dz_aff; double *dx_cc = csa->dx_cc; double *dy_cc = csa->dy_cc; double *dz_cc = csa->dz_cc; double *dx = csa->dx; double *dy = csa->dy; double *dz = csa->dz; int i, j, ret = 0; double temp, gamma_p, gamma_d, *p, *q, *r; /* allocate working arrays */ p = xcalloc(1+m, sizeof(double)); q = xcalloc(1+n, sizeof(double)); r = xcalloc(1+n, sizeof(double)); /* p = b - A*x */ A_by_vec(csa, x, p); for (i = 1; i <= m; i++) p[i] = b[i] - p[i]; /* q = c - A'*y - z */ AT_by_vec(csa, y,q); for (j = 1; j <= n; j++) q[j] = c[j] - q[j] - z[j]; /* r = - X * Z * e */ for (j = 1; j <= n; j++) r[j] = - x[j] * z[j]; /* solve the first Newtonian system */ if (solve_NS(csa, p, q, r, dx_aff, dy_aff, dz_aff)) { ret = 1; goto done; } /* alfa_aff_p = inf{0 <= alfa <= 1 | x + alfa*dx_aff >= 0} */ /* alfa_aff_d = inf{0 <= alfa <= 1 | z + alfa*dz_aff >= 0} */ csa->alfa_aff_p = csa->alfa_aff_d = 1.0; for (j = 1; j <= n; j++) { if (dx_aff[j] < 0.0) { temp = - x[j] / dx_aff[j]; if (csa->alfa_aff_p > temp) csa->alfa_aff_p = temp; } if (dz_aff[j] < 0.0) { temp = - z[j] / dz_aff[j]; if (csa->alfa_aff_d > temp) csa->alfa_aff_d = temp; } } /* mu_aff = (x+alfa_aff_p*dx_aff)' * (z+alfa_aff_d*dz_aff) / n */ temp = 0.0; for (j = 1; j <= n; j++) temp += (x[j] + csa->alfa_aff_p * dx_aff[j]) * (z[j] + csa->alfa_aff_d * dz_aff[j]); csa->mu_aff = temp / (double)n; /* sigma = (mu_aff/mu)^3 */ temp = csa->mu_aff / csa->mu; csa->sigma = temp * temp * temp; /* p = 0 */ for (i = 1; i <= m; i++) p[i] = 0.0; /* q = 0 */ for (j = 1; j <= n; j++) q[j] = 0.0; /* r = sigma * mu * e - X * Z * e */ for (j = 1; j <= n; j++) r[j] = csa->sigma * csa->mu - dx_aff[j] * dz_aff[j]; /* solve the second Newtonian system with the same coefficients but with altered right-hand sides */ if (solve_NS(csa, p, q, r, dx_cc, dy_cc, dz_cc)) { ret = 1; goto done; } /* (dx,dy,dz) = (dx_aff,dy_aff,dz_aff) + (dx_cc,dy_cc,dz_cc) */ for (j = 1; j <= n; j++) dx[j] = dx_aff[j] + dx_cc[j]; for (i = 1; i <= m; i++) dy[i] = dy_aff[i] + dy_cc[i]; for (j = 1; j <= n; j++) dz[j] = dz_aff[j] + dz_cc[j]; /* alfa_max_p = inf{0 <= alfa <= 1 | x + alfa*dx >= 0} */ /* alfa_max_d = inf{0 <= alfa <= 1 | z + alfa*dz >= 0} */ csa->alfa_max_p = csa->alfa_max_d = 1.0; for (j = 1; j <= n; j++) { if (dx[j] < 0.0) { temp = - x[j] / dx[j]; if (csa->alfa_max_p > temp) csa->alfa_max_p = temp; } if (dz[j] < 0.0) { temp = - z[j] / dz[j]; if (csa->alfa_max_d > temp) csa->alfa_max_d = temp; } } /* determine scale factors (not implemented yet) */ gamma_p = 0.90; gamma_d = 0.90; /* compute the next point */ for (j = 1; j <= n; j++) { x[j] += gamma_p * csa->alfa_max_p * dx[j]; xassert(x[j] > 0.0); } for (i = 1; i <= m; i++) y[i] += gamma_d * csa->alfa_max_d * dy[i]; for (j = 1; j <= n; j++) { z[j] += gamma_d * csa->alfa_max_d * dz[j]; xassert(z[j] > 0.0); } done: /* free working arrays */ xfree(p); xfree(q); xfree(r); return ret; } /*********************************************************************** * terminate - deallocate common storage area * * This routine frees all memory allocated to the common storage area * used by interior-point method routines. */ static void terminate(struct csa *csa) { xfree(csa->D); xfree(csa->P); xfree(csa->S_ptr); xfree(csa->S_ind); xfree(csa->S_val); xfree(csa->S_diag); xfree(csa->U_ptr); xfree(csa->U_ind); xfree(csa->U_val); xfree(csa->U_diag); xfree(csa->phi_min); xfree(csa->best_x); xfree(csa->best_y); xfree(csa->best_z); xfree(csa->dx_aff); xfree(csa->dy_aff); xfree(csa->dz_aff); xfree(csa->dx_cc); xfree(csa->dy_cc); xfree(csa->dz_cc); return; } /*********************************************************************** * ipm_main - main interior-point method routine * * This is a main routine of the primal-dual interior-point method. * * The routine ipm_main returns one of the following codes: * * 0 - optimal solution found; * 1 - problem has no feasible (primal or dual) solution; * 2 - no convergence; * 3 - iteration limit exceeded; * 4 - numeric instability on solving Newtonian system. * * In case of non-zero return code the routine returns the best point, * which has been reached during optimization. */ static int ipm_main(struct csa *csa) { int m = csa->m; int n = csa->n; int i, j, status; double temp; /* choose initial point using Mehrotra's heuristic */ if (csa->parm->msg_lev >= GLP_MSG_ALL) xprintf("Guessing initial point...\n"); initial_point(csa); /* main loop starts here */ if (csa->parm->msg_lev >= GLP_MSG_ALL) xprintf("Optimization begins...\n"); for (;;) { /* perform basic computations at the current point */ basic_info(csa); /* save initial value of rmu */ if (csa->iter == 0) csa->rmu0 = csa->rmu; /* accumulate values of min(phi[k]) and save the best point */ xassert(csa->iter <= ITER_MAX); if (csa->iter == 0 || csa->phi_min[csa->iter-1] > csa->phi) { csa->phi_min[csa->iter] = csa->phi; csa->best_iter = csa->iter; for (j = 1; j <= n; j++) csa->best_x[j] = csa->x[j]; for (i = 1; i <= m; i++) csa->best_y[i] = csa->y[i]; for (j = 1; j <= n; j++) csa->best_z[j] = csa->z[j]; csa->best_obj = csa->obj; } else csa->phi_min[csa->iter] = csa->phi_min[csa->iter-1]; /* display information at the current point */ if (csa->parm->msg_lev >= GLP_MSG_ON) xprintf("%3d: obj = %17.9e; rpi = %8.1e; rdi = %8.1e; gap =" " %8.1e\n", csa->iter, csa->obj, csa->rpi, csa->rdi, csa->gap); /* check if the current point is optimal */ if (csa->rpi < 1e-8 && csa->rdi < 1e-8 && csa->gap < 1e-8) { if (csa->parm->msg_lev >= GLP_MSG_ALL) xprintf("OPTIMAL SOLUTION FOUND\n"); status = 0; break; } /* check if the problem has no feasible solution */ temp = 1e5 * csa->phi_min[csa->iter]; if (temp < 1e-8) temp = 1e-8; if (csa->phi >= temp) { if (csa->parm->msg_lev >= GLP_MSG_ALL) xprintf("PROBLEM HAS NO FEASIBLE PRIMAL/DUAL SOLUTION\n") ; status = 1; break; } /* check for very slow convergence or divergence */ if (((csa->rpi >= 1e-8 || csa->rdi >= 1e-8) && csa->rmu / csa->rmu0 >= 1e6) || (csa->iter >= 30 && csa->phi_min[csa->iter] >= 0.5 * csa->phi_min[csa->iter - 30])) { if (csa->parm->msg_lev >= GLP_MSG_ALL) xprintf("NO CONVERGENCE; SEARCH TERMINATED\n"); status = 2; break; } /* check for maximal number of iterations */ if (csa->iter == ITER_MAX) { if (csa->parm->msg_lev >= GLP_MSG_ALL) xprintf("ITERATION LIMIT EXCEEDED; SEARCH TERMINATED\n"); status = 3; break; } /* start the next iteration */ csa->iter++; /* factorize normal equation system */ for (j = 1; j <= n; j++) csa->D[j] = csa->x[j] / csa->z[j]; decomp_NE(csa); /* compute the next point using Mehrotra's predictor-corrector technique */ if (make_step(csa)) { if (csa->parm->msg_lev >= GLP_MSG_ALL) xprintf("NUMERIC INSTABILITY; SEARCH TERMINATED\n"); status = 4; break; } } /* restore the best point */ if (status != 0) { for (j = 1; j <= n; j++) csa->x[j] = csa->best_x[j]; for (i = 1; i <= m; i++) csa->y[i] = csa->best_y[i]; for (j = 1; j <= n; j++) csa->z[j] = csa->best_z[j]; if (csa->parm->msg_lev >= GLP_MSG_ALL) xprintf("Best point %17.9e was reached on iteration %d\n", csa->best_obj, csa->best_iter); } /* return to the calling program */ return status; } /*********************************************************************** * NAME * * ipm_solve - core LP solver based on the interior-point method * * SYNOPSIS * * #include "glpipm.h" * int ipm_solve(glp_prob *P, const glp_iptcp *parm); * * DESCRIPTION * * The routine ipm_solve is a core LP solver based on the primal-dual * interior-point method. * * The routine assumes the following standard formulation of LP problem * to be solved: * * minimize * * F = c[0] + c[1]*x[1] + c[2]*x[2] + ... + c[n]*x[n] * * subject to linear constraints * * a[1,1]*x[1] + a[1,2]*x[2] + ... + a[1,n]*x[n] = b[1] * * a[2,1]*x[1] + a[2,2]*x[2] + ... + a[2,n]*x[n] = b[2] * * . . . . . . * * a[m,1]*x[1] + a[m,2]*x[2] + ... + a[m,n]*x[n] = b[m] * * and non-negative variables * * x[1] >= 0, x[2] >= 0, ..., x[n] >= 0 * * where: * F is the objective function; * x[1], ..., x[n] are (structural) variables; * c[0] is a constant term of the objective function; * c[1], ..., c[n] are objective coefficients; * a[1,1], ..., a[m,n] are constraint coefficients; * b[1], ..., b[n] are right-hand sides. * * The solution is three vectors x, y, and z, which are stored by the * routine in the arrays x, y, and z, respectively. These vectors * correspond to the best primal-dual point found during optimization. * They are approximate solution of the following system (which is the * Karush-Kuhn-Tucker optimality conditions): * * A*x = b (primal feasibility condition) * * A'*y + z = c (dual feasibility condition) * * x'*z = 0 (primal-dual complementarity condition) * * x >= 0, z >= 0 (non-negativity condition) * * where: * x[1], ..., x[n] are primal (structural) variables; * y[1], ..., y[m] are dual variables (Lagrange multipliers) for * equality constraints; * z[1], ..., z[n] are dual variables (Lagrange multipliers) for * non-negativity constraints. * * RETURNS * * 0 LP has been successfully solved. * * GLP_ENOCVG * No convergence. * * GLP_EITLIM * Iteration limit exceeded. * * GLP_EINSTAB * Numeric instability on solving Newtonian system. * * In case of non-zero return code the routine returns the best point, * which has been reached during optimization. */ int ipm_solve(glp_prob *P, const glp_iptcp *parm) { struct csa _dsa, *csa = &_dsa; int m = P->m; int n = P->n; int nnz = P->nnz; GLPROW *row; GLPCOL *col; GLPAIJ *aij; int i, j, loc, ret, *A_ind, *A_ptr; double dir, *A_val, *b, *c, *x, *y, *z; xassert(m > 0); xassert(n > 0); /* allocate working arrays */ A_ptr = xcalloc(1+m+1, sizeof(int)); A_ind = xcalloc(1+nnz, sizeof(int)); A_val = xcalloc(1+nnz, sizeof(double)); b = xcalloc(1+m, sizeof(double)); c = xcalloc(1+n, sizeof(double)); x = xcalloc(1+n, sizeof(double)); y = xcalloc(1+m, sizeof(double)); z = xcalloc(1+n, sizeof(double)); /* prepare rows and constraint coefficients */ loc = 1; for (i = 1; i <= m; i++) { row = P->row[i]; xassert(row->type == GLP_FX); b[i] = row->lb * row->rii; A_ptr[i] = loc; for (aij = row->ptr; aij != NULL; aij = aij->r_next) { A_ind[loc] = aij->col->j; A_val[loc] = row->rii * aij->val * aij->col->sjj; loc++; } } A_ptr[m+1] = loc; xassert(loc-1 == nnz); /* prepare columns and objective coefficients */ if (P->dir == GLP_MIN) dir = +1.0; else if (P->dir == GLP_MAX) dir = -1.0; else xassert(P != P); c[0] = dir * P->c0; for (j = 1; j <= n; j++) { col = P->col[j]; xassert(col->type == GLP_LO && col->lb == 0.0); c[j] = dir * col->coef * col->sjj; } /* allocate and initialize the common storage area */ csa->m = m; csa->n = n; csa->A_ptr = A_ptr; csa->A_ind = A_ind; csa->A_val = A_val; csa->b = b; csa->c = c; csa->x = x; csa->y = y; csa->z = z; csa->parm = parm; initialize(csa); /* solve LP with the interior-point method */ ret = ipm_main(csa); /* deallocate the common storage area */ terminate(csa); /* determine solution status */ if (ret == 0) { /* optimal solution found */ P->ipt_stat = GLP_OPT; ret = 0; } else if (ret == 1) { /* problem has no feasible (primal or dual) solution */ P->ipt_stat = GLP_NOFEAS; ret = 0; } else if (ret == 2) { /* no convergence */ P->ipt_stat = GLP_INFEAS; ret = GLP_ENOCVG; } else if (ret == 3) { /* iteration limit exceeded */ P->ipt_stat = GLP_INFEAS; ret = GLP_EITLIM; } else if (ret == 4) { /* numeric instability on solving Newtonian system */ P->ipt_stat = GLP_INFEAS; ret = GLP_EINSTAB; } else xassert(ret != ret); /* store row solution components */ for (i = 1; i <= m; i++) { row = P->row[i]; row->pval = row->lb; row->dval = dir * y[i] * row->rii; } /* store column solution components */ P->ipt_obj = P->c0; for (j = 1; j <= n; j++) { col = P->col[j]; col->pval = x[j] * col->sjj; col->dval = dir * z[j] / col->sjj; P->ipt_obj += col->coef * col->pval; } /* free working arrays */ xfree(A_ptr); xfree(A_ind); xfree(A_val); xfree(b); xfree(c); xfree(x); xfree(y); xfree(z); return ret; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glprng02.c0000644000076500000240000000440713524616144025203 0ustar tamasstaff00000000000000/* glprng02.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glpenv.h" #include "glprng.h" #define xfault xerror /*********************************************************************** * NAME * * rng_unif_01 - obtain pseudo-random number in the range [0, 1] * * SYNOPSIS * * #include "glprng.h" * double rng_unif_01(RNG *rand); * * RETURNS * * The routine rng_unif_01 returns a next pseudo-random number which is * uniformly distributed in the range [0, 1]. */ double rng_unif_01(RNG *rand) { double x; x = (double)rng_next_rand(rand) / 2147483647.0; xassert(0.0 <= x && x <= 1.0); return x; } /*********************************************************************** * NAME * * rng_uniform - obtain pseudo-random number in the range [a, b] * * SYNOPSIS * * #include "glprng.h" * double rng_uniform(RNG *rand, double a, double b); * * RETURNS * * The routine rng_uniform returns a next pseudo-random number which is * uniformly distributed in the range [a, b]. */ double rng_uniform(RNG *rand, double a, double b) { double x; if (a >= b) xfault("rng_uniform: a = %g, b = %g; invalid range\n", a, b); x = rng_unif_01(rand); x = a * (1.0 - x) + b * x; xassert(a <= x && x <= b); return x; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpenv07.c0000644000076500000240000003735113524616144025216 0ustar tamasstaff00000000000000/* glpenv07.c (stream input/output) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wshorten-64-to-32" #pragma clang diagnostic ignored "-Wsometimes-uninitialized" #endif #ifdef HAVE_CONFIG_H #include #endif #include "glpenv.h" /*********************************************************************** * NAME * * lib_err_msg - save error message string * * SYNOPSIS * * #include "glpenv.h" * void lib_err_msg(const char *msg); * * DESCRIPTION * * The routine lib_err_msg saves an error message string specified by * the parameter msg. The message is obtained by some library routines * with a call to strerror(errno). */ void lib_err_msg(const char *msg) { ENV *env = get_env_ptr(); int len = strlen(msg); if (len >= IOERR_MSG_SIZE) len = IOERR_MSG_SIZE - 1; memcpy(env->ioerr_msg, msg, len); if (len > 0 && env->ioerr_msg[len-1] == '\n') len--; env->ioerr_msg[len] = '\0'; return; } /*********************************************************************** * NAME * * xerrmsg - retrieve error message string * * SYNOPSIS * * #include "glpenv.h" * const char *xerrmsg(void); * * RETURNS * * The routine xerrmsg returns a pointer to an error message string * previously set by some library routine to indicate an error. */ const char *xerrmsg(void) { ENV *env = get_env_ptr(); return env->ioerr_msg; } /*********************************************************************** * NAME * * xfopen - open a stream * * SYNOPSIS * * #include "glpenv.h" * XFILE *xfopen(const char *fname, const char *mode); * * DESCRIPTION * * The routine xfopen opens the file whose name is a string pointed to * by fname and associates a stream with it. * * The parameter mode points to a string, which indicates the open mode * and should be one of the following: * * "r" open text file for reading; * "w" truncate to zero length or create text file for writing; * "rb" open binary file for reading; * "wb" truncate to zero length or create binary file for writing. * * RETURNS * * The routine xfopen returns a pointer to the object controlling the * stream. If the open operation fails, xfopen returns NULL. */ static void *c_fopen(const char *fname, const char *mode); static void *z_fopen(const char *fname, const char *mode); static int is_gz_file(const char *fname) { char *ext = strrchr(fname, '.'); return ext != NULL && strcmp(ext, ".gz") == 0; } XFILE *xfopen(const char *fname, const char *mode) { ENV *env = get_env_ptr(); XFILE *fp; int type; void *fh; if (!is_gz_file(fname)) { type = FH_FILE; fh = c_fopen(fname, mode); } else { type = FH_ZLIB; fh = z_fopen(fname, mode); } if (fh == NULL) { fp = NULL; goto done; } fp = xmalloc(sizeof(XFILE)); fp->type = type; fp->fh = fh; fp->prev = NULL; fp->next = env->file_ptr; if (fp->next != NULL) fp->next->prev = fp; env->file_ptr = fp; done: return fp; } /*********************************************************************** * NAME * * xfgetc - read character from the stream * * SYNOPSIS * * #include "glpenv.h" * int xfgetc(XFILE *fp); * * DESCRIPTION * * If the end-of-file indicator for the input stream pointed to by fp * is not set and a next character is present, the routine xfgetc * obtains that character as an unsigned char converted to an int and * advances the associated file position indicator for the stream (if * defined). * * RETURNS * * If the end-of-file indicator for the stream is set, or if the * stream is at end-of-file, the end-of-file indicator for the stream * is set and the routine xfgetc returns XEOF. Otherwise, the routine * xfgetc returns the next character from the input stream pointed to * by fp. If a read error occurs, the error indicator for the stream is * set and the xfgetc routine returns XEOF. * * Note: An end-of-file and a read error can be distinguished by use of * the routines xfeof and xferror. */ static int c_fgetc(void *fh); static int z_fgetc(void *fh); int xfgetc(XFILE *fp) { int c; switch (fp->type) { case FH_FILE: c = c_fgetc(fp->fh); break; case FH_ZLIB: c = z_fgetc(fp->fh); break; default: xassert(fp != fp); } return c; } /*********************************************************************** * NAME * * xfputc - write character to the stream * * SYNOPSIS * * #include "glpenv.h" * int xfputc(int c, XFILE *fp); * * DESCRIPTION * * The routine xfputc writes the character specified by c (converted * to an unsigned char) to the output stream pointed to by fp, at the * position indicated by the associated file position indicator (if * defined), and advances the indicator appropriately. * * RETURNS * * The routine xfputc returns the character written. If a write error * occurs, the error indicator for the stream is set and xfputc returns * XEOF. */ static int c_fputc(int c, void *fh); static int z_fputc(int c, void *fh); int xfputc(int c, XFILE *fp) { switch (fp->type) { case FH_FILE: c = c_fputc(c, fp->fh); break; case FH_ZLIB: c = z_fputc(c, fp->fh); break; default: xassert(fp != fp); } return c; } /*********************************************************************** * NAME * * xferror - test error indicator for the stream * * SYNOPSIS * * #include "glpenv.h" * int xferror(XFILE *fp); * * DESCRIPTION * * The routine xferror tests the error indicator for the stream * pointed to by fp. * * RETURNS * * The routine xferror returns non-zero if and only if the error * indicator is set for the stream. */ static int c_ferror(void *fh); static int z_ferror(void *fh); int xferror(XFILE *fp) { int ret; switch (fp->type) { case FH_FILE: ret = c_ferror(fp->fh); break; case FH_ZLIB: ret = z_ferror(fp->fh); break; default: xassert(fp != fp); } return ret; } /*********************************************************************** * NAME * * xfeof - test end-of-file indicator for the stream * * SYNOPSIS * * #include "glpenv.h" * int xfeof(XFILE *fp); * * DESCRIPTION * * The routine xfeof tests the end-of-file indicator for the stream * pointed to by fp. * * RETURNS * * The routine xfeof returns non-zero if and only if the end-of-file * indicator is set for the stream. */ static int c_feof(void *fh); static int z_feof(void *fh); int xfeof(XFILE *fp) { int ret; switch (fp->type) { case FH_FILE: ret = c_feof(fp->fh); break; case FH_ZLIB: ret = z_feof(fp->fh); break; default: xassert(fp != fp); } return ret; } int xfprintf(XFILE *file, const char *fmt, ...) { ENV *env = get_env_ptr(); int cnt, j; va_list arg; va_start(arg, fmt); cnt = vsprintf(env->term_buf, fmt, arg); va_end(arg); for (j = 0; j < cnt; j++) { if (xfputc(env->term_buf[j], file) < 0) { cnt = -1; break; } } return cnt; } /*********************************************************************** * NAME * * xfflush - flush the stream * * SYNOPSIS * * #include "glpenv.h" * int xfflush(XFILE *fp); * * DESCRIPTION * * The routine xfflush causes any unwritten data for the output stream * pointed to by fp to be written to the associated file. * * RETURNS * * The routine xfflush returns zero if the stream was successfully * flushed. Otherwise, xfflush sets the error indicator for the stream * and returns XEOF. */ static int c_fflush(void *fh); static int z_fflush(void *fh); int xfflush(XFILE *fp) { int ret; switch (fp->type) { case FH_FILE: ret = c_fflush(fp->fh); break; case FH_ZLIB: ret = z_fflush(fp->fh); break; default: xassert(fp != fp); } return ret; } /*********************************************************************** * NAME * * xfclose - close the stream * * SYNOPSIS * * #include "glpenv.h" * int xfclose(XFILE *fp); * * DESCRIPTION * * A successful call to the routine xfclose causes the stream pointed * to by fp to be flushed and the associated file to be closed. Whether * or not the call succeeds, the stream is disassociated from the file. * * RETURNS * * The routine xfclose returns zero if the stream was successfully * closed, or XEOF if any errors were detected. */ static int c_fclose(void *fh); static int z_fclose(void *fh); int xfclose(XFILE *fp) { ENV *env = get_env_ptr(); int ret; switch (fp->type) { case FH_FILE: ret = c_fclose(fp->fh); break; case FH_ZLIB: ret = z_fclose(fp->fh); break; default: xassert(fp != fp); } fp->type = 0xF00BAD; if (fp->prev == NULL) env->file_ptr = fp->next; else fp->prev->next = fp->next; if (fp->next == NULL) ; else fp->next->prev = fp->prev; xfree(fp); return ret; } /*********************************************************************** * The following routines implement stream input/output based on the * standard C streams. */ static void *c_fopen(const char *fname, const char *mode) { FILE *fh; /* if (strcmp(fname, "/dev/stdin") == 0) */ /* fh = stdin; */ /* else if (strcmp(fname, "/dev/stdout") == 0) */ /* fh = stdout; */ /* else if (strcmp(fname, "/dev/stderr") == 0) */ /* fh = stderr; */ /* else */ fh = fopen(fname, mode); if (fh == NULL) lib_err_msg(strerror(errno)); return fh; } static int c_fgetc(void *_fh) { FILE *fh = _fh; int c; if (ferror(fh) || feof(fh)) { c = XEOF; goto done; } c = fgetc(fh); if (ferror(fh)) { lib_err_msg(strerror(errno)); c = XEOF; } else if (feof(fh)) c = XEOF; else xassert(0x00 <= c && c <= 0xFF); done: return c; } static int c_fputc(int c, void *_fh) { FILE *fh = _fh; if (ferror(fh)) { c = XEOF; goto done; } c = (unsigned char)c; fputc(c, fh); if (ferror(fh)) { lib_err_msg(strerror(errno)); c = XEOF; } done: return c; } static int c_ferror(void *_fh) { FILE *fh = _fh; return ferror(fh); } static int c_feof(void *_fh) { FILE *fh = _fh; return feof(fh); } static int c_fflush(void *_fh) { FILE *fh = _fh; int ret; ret = fflush(fh); if (ret != 0) { lib_err_msg(strerror(errno)); ret = XEOF; } return ret; } static int c_fclose(void *_fh) { FILE *fh = _fh; int ret; /* if (fh == stdin) */ /* ret = 0; */ /* else if (fh == stdout || fh == stderr) */ /* fflush(fh), ret = 0; */ /* else */ ret = fclose(fh); if (ret != 0) { lib_err_msg(strerror(errno)); ret = XEOF; } return ret; } /*********************************************************************** * The following routines implement stream input/output based on the * zlib library, which provides processing .gz files "on the fly". */ #ifndef HAVE_ZLIB static void *z_fopen(const char *fname, const char *mode) { xassert(fname == fname); xassert(mode == mode); lib_err_msg("Compressed files not supported"); return NULL; } static int z_fgetc(void *fh) { xassert(fh != fh); return 0; } static int z_fputc(int c, void *fh) { xassert(c != c); xassert(fh != fh); return 0; } static int z_ferror(void *fh) { xassert(fh != fh); return 0; } static int z_feof(void *fh) { xassert(fh != fh); return 0; } static int z_fflush(void *fh) { xassert(fh != fh); return 0; } static int z_fclose(void *fh) { xassert(fh != fh); return 0; } #else #include struct z_file { /* .gz file handle */ gzFile file; /* pointer to .gz stream */ int err; /* i/o error indicator */ int eof; /* end-of-file indicator */ }; static void *z_fopen(const char *fname, const char *mode) { struct z_file *fh; gzFile file; if (strcmp(mode, "r") == 0 || strcmp(mode, "rb") == 0) mode = "rb"; else if (strcmp(mode, "w") == 0 || strcmp(mode, "wb") == 0) mode = "wb"; else { lib_err_msg("Invalid open mode"); fh = NULL; goto done; } file = gzopen(fname, mode); if (file == NULL) { lib_err_msg(strerror(errno)); fh = NULL; goto done; } fh = xmalloc(sizeof(struct z_file)); fh->file = file; fh->err = fh->eof = 0; done: return fh; } static int z_fgetc(void *_fh) { struct z_file *fh = _fh; int c; if (fh->err || fh->eof) { c = XEOF; goto done; } c = gzgetc(fh->file); if (c < 0) { int errnum; const char *msg; msg = gzerror(fh->file, &errnum); if (errnum == Z_STREAM_END) fh->eof = 1; else if (errnum == Z_ERRNO) { fh->err = 1; lib_err_msg(strerror(errno)); } else { fh->err = 1; lib_err_msg(msg); } c = XEOF; } else xassert(0x00 <= c && c <= 0xFF); done: return c; } static int z_fputc(int c, void *_fh) { struct z_file *fh = _fh; if (fh->err) { c = XEOF; goto done; } c = (unsigned char)c; if (gzputc(fh->file, c) < 0) { int errnum; const char *msg; fh->err = 1; msg = gzerror(fh->file, &errnum); if (errnum == Z_ERRNO) lib_err_msg(strerror(errno)); else lib_err_msg(msg); c = XEOF; } done: return c; } static int z_ferror(void *_fh) { struct z_file *fh = _fh; return fh->err; } static int z_feof(void *_fh) { struct z_file *fh = _fh; return fh->eof; } static int z_fflush(void *_fh) { struct z_file *fh = _fh; int ret; ret = gzflush(fh->file, Z_FINISH); if (ret == Z_OK) ret = 0; else { int errnum; const char *msg; fh->err = 1; msg = gzerror(fh->file, &errnum); if (errnum == Z_ERRNO) lib_err_msg(strerror(errno)); else lib_err_msg(msg); ret = XEOF; } return ret; } static int z_fclose(void *_fh) { struct z_file *fh = _fh; gzclose(fh->file); xfree(fh); return 0; } #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpmpl04.c0000644000076500000240000013445113524616144025212 0ustar tamasstaff00000000000000/* glpmpl04.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wshorten-64-to-32" #pragma clang diagnostic ignored "-Wsometimes-uninitialized" #endif #define _GLPSTD_ERRNO #define _GLPSTD_STDIO #include "glpmpl.h" #define xfault xerror #define dmp_create_poolx(size) dmp_create_pool() /**********************************************************************/ /* * * GENERATING AND POSTSOLVING MODEL * * */ /**********************************************************************/ /*---------------------------------------------------------------------- -- alloc_content - allocate content arrays for all model objects. -- -- This routine allocates content arrays for all existing model objects -- and thereby finalizes creating model. -- -- This routine must be called immediately after reading model section, -- i.e. before reading data section or generating model. */ void alloc_content(MPL *mpl) { STATEMENT *stmt; /* walk through all model statements */ for (stmt = mpl->model; stmt != NULL; stmt = stmt->next) { switch (stmt->type) { case A_SET: /* model set */ xassert(stmt->u.set->array == NULL); stmt->u.set->array = create_array(mpl, A_ELEMSET, stmt->u.set->dim); break; case A_PARAMETER: /* model parameter */ xassert(stmt->u.par->array == NULL); switch (stmt->u.par->type) { case A_NUMERIC: case A_INTEGER: case A_BINARY: stmt->u.par->array = create_array(mpl, A_NUMERIC, stmt->u.par->dim); break; case A_SYMBOLIC: stmt->u.par->array = create_array(mpl, A_SYMBOLIC, stmt->u.par->dim); break; default: xassert(stmt != stmt); } break; case A_VARIABLE: /* model variable */ xassert(stmt->u.var->array == NULL); stmt->u.var->array = create_array(mpl, A_ELEMVAR, stmt->u.var->dim); break; case A_CONSTRAINT: /* model constraint/objective */ xassert(stmt->u.con->array == NULL); stmt->u.con->array = create_array(mpl, A_ELEMCON, stmt->u.con->dim); break; #if 1 /* 11/II-2008 */ case A_TABLE: #endif case A_SOLVE: case A_CHECK: case A_DISPLAY: case A_PRINTF: case A_FOR: /* functional statements have no content array */ break; default: xassert(stmt != stmt); } } return; } /*---------------------------------------------------------------------- -- generate_model - generate model. -- -- This routine executes the model statements which precede the solve -- statement. */ void generate_model(MPL *mpl) { STATEMENT *stmt; xassert(!mpl->flag_p); for (stmt = mpl->model; stmt != NULL; stmt = stmt->next) { execute_statement(mpl, stmt); if (mpl->stmt->type == A_SOLVE) break; } mpl->stmt = stmt; return; } /*---------------------------------------------------------------------- -- build_problem - build problem instance. -- -- This routine builds lists of rows and columns for problem instance, -- which corresponds to the generated model. */ void build_problem(MPL *mpl) { STATEMENT *stmt; MEMBER *memb; VARIABLE *v; CONSTRAINT *c; FORMULA *t; int i, j; xassert(mpl->m == 0); xassert(mpl->n == 0); xassert(mpl->row == NULL); xassert(mpl->col == NULL); /* check that all elemental variables has zero column numbers */ for (stmt = mpl->model; stmt != NULL; stmt = stmt->next) { if (stmt->type == A_VARIABLE) { v = stmt->u.var; for (memb = v->array->head; memb != NULL; memb = memb->next) xassert(memb->value.var->j == 0); } } /* assign row numbers to elemental constraints and objectives */ for (stmt = mpl->model; stmt != NULL; stmt = stmt->next) { if (stmt->type == A_CONSTRAINT) { c = stmt->u.con; for (memb = c->array->head; memb != NULL; memb = memb->next) { xassert(memb->value.con->i == 0); memb->value.con->i = ++mpl->m; /* walk through linear form and mark elemental variables, which are referenced at least once */ for (t = memb->value.con->form; t != NULL; t = t->next) { xassert(t->var != NULL); t->var->memb->value.var->j = -1; } } } } /* assign column numbers to marked elemental variables */ for (stmt = mpl->model; stmt != NULL; stmt = stmt->next) { if (stmt->type == A_VARIABLE) { v = stmt->u.var; for (memb = v->array->head; memb != NULL; memb = memb->next) if (memb->value.var->j != 0) memb->value.var->j = ++mpl->n; } } /* build list of rows */ mpl->row = xcalloc(1+mpl->m, sizeof(ELEMCON *)); for (i = 1; i <= mpl->m; i++) mpl->row[i] = NULL; for (stmt = mpl->model; stmt != NULL; stmt = stmt->next) { if (stmt->type == A_CONSTRAINT) { c = stmt->u.con; for (memb = c->array->head; memb != NULL; memb = memb->next) { i = memb->value.con->i; xassert(1 <= i && i <= mpl->m); xassert(mpl->row[i] == NULL); mpl->row[i] = memb->value.con; } } } for (i = 1; i <= mpl->m; i++) xassert(mpl->row[i] != NULL); /* build list of columns */ mpl->col = xcalloc(1+mpl->n, sizeof(ELEMVAR *)); for (j = 1; j <= mpl->n; j++) mpl->col[j] = NULL; for (stmt = mpl->model; stmt != NULL; stmt = stmt->next) { if (stmt->type == A_VARIABLE) { v = stmt->u.var; for (memb = v->array->head; memb != NULL; memb = memb->next) { j = memb->value.var->j; if (j == 0) continue; xassert(1 <= j && j <= mpl->n); xassert(mpl->col[j] == NULL); mpl->col[j] = memb->value.var; } } } for (j = 1; j <= mpl->n; j++) xassert(mpl->col[j] != NULL); return; } /*---------------------------------------------------------------------- -- postsolve_model - postsolve model. -- -- This routine executes the model statements which follow the solve -- statement. */ void postsolve_model(MPL *mpl) { STATEMENT *stmt; xassert(!mpl->flag_p); mpl->flag_p = 1; for (stmt = mpl->stmt; stmt != NULL; stmt = stmt->next) execute_statement(mpl, stmt); mpl->stmt = NULL; return; } /*---------------------------------------------------------------------- -- clean_model - clean model content. -- -- This routine cleans the model content that assumes deleting all stuff -- dynamically allocated on generating/postsolving phase. -- -- Actually cleaning model content is not needed. This function is used -- mainly to be sure that there were no logical errors on using dynamic -- memory pools during the generation phase. -- -- NOTE: This routine must not be called if any errors were detected on -- the generation phase. */ void clean_model(MPL *mpl) { STATEMENT *stmt; for (stmt = mpl->model; stmt != NULL; stmt = stmt->next) clean_statement(mpl, stmt); /* check that all atoms have been returned to their pools */ if (dmp_in_use(mpl->strings).lo != 0) error(mpl, "internal logic error: %d string segment(s) were lo" "st", dmp_in_use(mpl->strings).lo); if (dmp_in_use(mpl->symbols).lo != 0) error(mpl, "internal logic error: %d symbol(s) were lost", dmp_in_use(mpl->symbols).lo); if (dmp_in_use(mpl->tuples).lo != 0) error(mpl, "internal logic error: %d n-tuple component(s) were" " lost", dmp_in_use(mpl->tuples).lo); if (dmp_in_use(mpl->arrays).lo != 0) error(mpl, "internal logic error: %d array(s) were lost", dmp_in_use(mpl->arrays).lo); if (dmp_in_use(mpl->members).lo != 0) error(mpl, "internal logic error: %d array member(s) were lost" , dmp_in_use(mpl->members).lo); if (dmp_in_use(mpl->elemvars).lo != 0) error(mpl, "internal logic error: %d elemental variable(s) wer" "e lost", dmp_in_use(mpl->elemvars).lo); if (dmp_in_use(mpl->formulae).lo != 0) error(mpl, "internal logic error: %d linear term(s) were lost", dmp_in_use(mpl->formulae).lo); if (dmp_in_use(mpl->elemcons).lo != 0) error(mpl, "internal logic error: %d elemental constraint(s) w" "ere lost", dmp_in_use(mpl->elemcons).lo); return; } /**********************************************************************/ /* * * INPUT/OUTPUT * * */ /**********************************************************************/ /*---------------------------------------------------------------------- -- open_input - open input text file. -- -- This routine opens the input text file for scanning. */ void open_input(MPL *mpl, char *file) { mpl->line = 0; mpl->c = '\n'; mpl->token = 0; mpl->imlen = 0; mpl->image[0] = '\0'; mpl->value = 0.0; mpl->b_token = T_EOF; mpl->b_imlen = 0; mpl->b_image[0] = '\0'; mpl->b_value = 0.0; mpl->f_dots = 0; mpl->f_scan = 0; mpl->f_token = 0; mpl->f_imlen = 0; mpl->f_image[0] = '\0'; mpl->f_value = 0.0; memset(mpl->context, ' ', CONTEXT_SIZE); mpl->c_ptr = 0; xassert(mpl->in_fp == NULL); mpl->in_fp = xfopen(file, "r"); if (mpl->in_fp == NULL) error(mpl, "unable to open %s - %s", file, xerrmsg()); mpl->in_file = file; /* scan the very first character */ get_char(mpl); /* scan the very first token */ get_token(mpl); return; } /*---------------------------------------------------------------------- -- read_char - read next character from input text file. -- -- This routine returns a next ASCII character read from the input text -- file. If the end of file has been reached, EOF is returned. */ int read_char(MPL *mpl) { int c; xassert(mpl->in_fp != NULL); c = xfgetc(mpl->in_fp); if (c < 0) { if (xferror(mpl->in_fp)) error(mpl, "read error on %s - %s", mpl->in_file, xerrmsg()); c = EOF; } return c; } /*---------------------------------------------------------------------- -- close_input - close input text file. -- -- This routine closes the input text file. */ void close_input(MPL *mpl) { xassert(mpl->in_fp != NULL); xfclose(mpl->in_fp); mpl->in_fp = NULL; mpl->in_file = NULL; return; } /*---------------------------------------------------------------------- -- open_output - open output text file. -- -- This routine opens the output text file for writing data produced by -- display and printf statements. */ void open_output(MPL *mpl, char *file) { xassert(mpl->out_fp == NULL); /* if (file == NULL) */ /* { file = ""; */ /* mpl->out_fp = (void *)stdout; */ /* } */ /* else */ { mpl->out_fp = xfopen(file, "w"); if (mpl->out_fp == NULL) error(mpl, "unable to create %s - %s", file, xerrmsg()); } mpl->out_file = xmalloc(strlen(file)+1); strcpy(mpl->out_file, file); return; } /*---------------------------------------------------------------------- -- write_char - write next character to output text file. -- -- This routine writes an ASCII character to the output text file. */ void write_char(MPL *mpl, int c) { xassert(mpl->out_fp != NULL); /* if (mpl->out_fp == (void *)stdout) */ /* xprintf("%c", c); */ /* else */ xfprintf(mpl->out_fp, "%c", c); return; } /*---------------------------------------------------------------------- -- write_text - format and write text to output text file. -- -- This routine formats a text using the format control string and then -- writes this text to the output text file. */ void write_text(MPL *mpl, char *fmt, ...) { va_list arg; char buf[OUTBUF_SIZE], *c; va_start(arg, fmt); vsprintf(buf, fmt, arg); xassert(strlen(buf) < sizeof(buf)); va_end(arg); for (c = buf; *c != '\0'; c++) write_char(mpl, *c); return; } /*---------------------------------------------------------------------- -- flush_output - finalize writing data to output text file. -- -- This routine finalizes writing data to the output text file. */ void flush_output(MPL *mpl) { xassert(mpl->out_fp != NULL); /* if (mpl->out_fp != (void *)stdout) */ { xfflush(mpl->out_fp); if (xferror(mpl->out_fp)) error(mpl, "write error on %s - %s", mpl->out_file, xerrmsg()); } return; } /**********************************************************************/ /* * * SOLVER INTERFACE * * */ /**********************************************************************/ /*---------------------------------------------------------------------- -- error - print error message and terminate model processing. -- -- This routine formats and prints an error message and then terminates -- model processing. */ void error(MPL *mpl, char *fmt, ...) { va_list arg; char msg[4095+1]; va_start(arg, fmt); vsprintf(msg, fmt, arg); xassert(strlen(msg) < sizeof(msg)); va_end(arg); switch (mpl->phase) { case 1: case 2: /* translation phase */ xprintf("%s:%d: %s\n", mpl->in_file == NULL ? "(unknown)" : mpl->in_file, mpl->line, msg); print_context(mpl); break; case 3: /* generation/postsolve phase */ xprintf("%s:%d: %s\n", mpl->mod_file == NULL ? "(unknown)" : mpl->mod_file, mpl->stmt == NULL ? 0 : mpl->stmt->line, msg); break; default: xassert(mpl != mpl); } mpl->phase = 4; longjmp(mpl->jump, 1); /* no return */ } /*---------------------------------------------------------------------- -- warning - print warning message and continue model processing. -- -- This routine formats and prints a warning message and returns to the -- calling program. */ void warning(MPL *mpl, char *fmt, ...) { va_list arg; char msg[4095+1]; va_start(arg, fmt); vsprintf(msg, fmt, arg); xassert(strlen(msg) < sizeof(msg)); va_end(arg); switch (mpl->phase) { case 1: case 2: /* translation phase */ xprintf("%s:%d: warning: %s\n", mpl->in_file == NULL ? "(unknown)" : mpl->in_file, mpl->line, msg); break; case 3: /* generation/postsolve phase */ xprintf("%s:%d: warning: %s\n", mpl->mod_file == NULL ? "(unknown)" : mpl->mod_file, mpl->stmt == NULL ? 0 : mpl->stmt->line, msg); break; default: xassert(mpl != mpl); } return; } /*---------------------------------------------------------------------- -- mpl_initialize - create and initialize translator database. -- -- *Synopsis* -- -- #include "glpmpl.h" -- MPL *mpl_initialize(void); -- -- *Description* -- -- The routine mpl_initialize creates and initializes the database used -- by the GNU MathProg translator. -- -- *Returns* -- -- The routine returns a pointer to the database created. */ MPL *mpl_initialize(void) { MPL *mpl; mpl = xmalloc(sizeof(MPL)); /* scanning segment */ mpl->line = 0; mpl->c = 0; mpl->token = 0; mpl->imlen = 0; mpl->image = xcalloc(MAX_LENGTH+1, sizeof(char)); mpl->image[0] = '\0'; mpl->value = 0.0; mpl->b_token = 0; mpl->b_imlen = 0; mpl->b_image = xcalloc(MAX_LENGTH+1, sizeof(char)); mpl->b_image[0] = '\0'; mpl->b_value = 0.0; mpl->f_dots = 0; mpl->f_scan = 0; mpl->f_token = 0; mpl->f_imlen = 0; mpl->f_image = xcalloc(MAX_LENGTH+1, sizeof(char)); mpl->f_image[0] = '\0'; mpl->f_value = 0.0; mpl->context = xcalloc(CONTEXT_SIZE, sizeof(char)); memset(mpl->context, ' ', CONTEXT_SIZE); mpl->c_ptr = 0; mpl->flag_d = 0; /* translating segment */ mpl->pool = dmp_create_poolx(0); mpl->tree = avl_create_tree(avl_strcmp, NULL); mpl->model = NULL; mpl->flag_x = 0; mpl->as_within = 0; mpl->as_in = 0; mpl->as_binary = 0; mpl->flag_s = 0; /* common segment */ mpl->strings = dmp_create_poolx(sizeof(STRING)); mpl->symbols = dmp_create_poolx(sizeof(SYMBOL)); mpl->tuples = dmp_create_poolx(sizeof(TUPLE)); mpl->arrays = dmp_create_poolx(sizeof(ARRAY)); mpl->members = dmp_create_poolx(sizeof(MEMBER)); mpl->elemvars = dmp_create_poolx(sizeof(ELEMVAR)); mpl->formulae = dmp_create_poolx(sizeof(FORMULA)); mpl->elemcons = dmp_create_poolx(sizeof(ELEMCON)); mpl->a_list = NULL; mpl->sym_buf = xcalloc(255+1, sizeof(char)); mpl->sym_buf[0] = '\0'; mpl->tup_buf = xcalloc(255+1, sizeof(char)); mpl->tup_buf[0] = '\0'; /* generating/postsolving segment */ mpl->rand = rng_create_rand(); mpl->flag_p = 0; mpl->stmt = NULL; #if 1 /* 11/II-2008 */ mpl->dca = NULL; #endif mpl->m = 0; mpl->n = 0; mpl->row = NULL; mpl->col = NULL; /* input/output segment */ mpl->in_fp = NULL; mpl->in_file = NULL; mpl->out_fp = NULL; mpl->out_file = NULL; mpl->prt_fp = NULL; mpl->prt_file = NULL; /* solver interface segment */ if (setjmp(mpl->jump)) xassert(mpl != mpl); mpl->phase = 0; mpl->mod_file = NULL; mpl->mpl_buf = xcalloc(255+1, sizeof(char)); mpl->mpl_buf[0] = '\0'; return mpl; } /*---------------------------------------------------------------------- -- mpl_read_model - read model section and optional data section. -- -- *Synopsis* -- -- #include "glpmpl.h" -- int mpl_read_model(MPL *mpl, char *file, int skip_data); -- -- *Description* -- -- The routine mpl_read_model reads model section and optionally data -- section, which may follow the model section, from the text file, -- whose name is the character string file, performs translating model -- statements and data blocks, and stores all the information in the -- translator database. -- -- The parameter skip_data is a flag. If the input file contains the -- data section and this flag is set, the data section is not read as -- if there were no data section and a warning message is issued. This -- allows reading the data section from another input file. -- -- This routine should be called once after the routine mpl_initialize -- and before other API routines. -- -- *Returns* -- -- The routine mpl_read_model returns one the following codes: -- -- 1 - translation successful. The input text file contains only model -- section. In this case the calling program may call the routine -- mpl_read_data to read data section from another file. -- 2 - translation successful. The input text file contains both model -- and data section. -- 4 - processing failed due to some errors. In this case the calling -- program should call the routine mpl_terminate to terminate model -- processing. */ int mpl_read_model(MPL *mpl, char *file, int skip_data) { if (mpl->phase != 0) xfault("mpl_read_model: invalid call sequence\n"); if (file == NULL) xfault("mpl_read_model: no input filename specified\n"); /* set up error handler */ if (setjmp(mpl->jump)) goto done; /* translate model section */ mpl->phase = 1; xprintf("Reading model section from %s...\n", file); open_input(mpl, file); model_section(mpl); if (mpl->model == NULL) error(mpl, "empty model section not allowed"); /* save name of the input text file containing model section for error diagnostics during the generation phase */ mpl->mod_file = xcalloc(strlen(file)+1, sizeof(char)); strcpy(mpl->mod_file, mpl->in_file); /* allocate content arrays for all model objects */ alloc_content(mpl); /* optional data section may begin with the keyword 'data' */ if (is_keyword(mpl, "data")) { if (skip_data) { warning(mpl, "data section ignored"); goto skip; } mpl->flag_d = 1; get_token(mpl /* data */); if (mpl->token != T_SEMICOLON) error(mpl, "semicolon missing where expected"); get_token(mpl /* ; */); /* translate data section */ mpl->phase = 2; xprintf("Reading data section from %s...\n", file); data_section(mpl); } /* process end statement */ end_statement(mpl); skip: xprintf("%d line%s were read\n", mpl->line, mpl->line == 1 ? "" : "s"); close_input(mpl); done: /* return to the calling program */ return mpl->phase; } /*---------------------------------------------------------------------- -- mpl_read_data - read data section. -- -- *Synopsis* -- -- #include "glpmpl.h" -- int mpl_read_data(MPL *mpl, char *file); -- -- *Description* -- -- The routine mpl_read_data reads data section from the text file, -- whose name is the character string file, performs translating data -- blocks, and stores the data read in the translator database. -- -- If this routine is used, it should be called once after the routine -- mpl_read_model and if the latter returned the code 1. -- -- *Returns* -- -- The routine mpl_read_data returns one of the following codes: -- -- 2 - data section has been successfully processed. -- 4 - processing failed due to some errors. In this case the calling -- program should call the routine mpl_terminate to terminate model -- processing. */ int mpl_read_data(MPL *mpl, char *file) #if 0 /* 02/X-2008 */ { if (mpl->phase != 1) #else { if (!(mpl->phase == 1 || mpl->phase == 2)) #endif xfault("mpl_read_data: invalid call sequence\n"); if (file == NULL) xfault("mpl_read_data: no input filename specified\n"); /* set up error handler */ if (setjmp(mpl->jump)) goto done; /* process data section */ mpl->phase = 2; xprintf("Reading data section from %s...\n", file); mpl->flag_d = 1; open_input(mpl, file); /* in this case the keyword 'data' is optional */ if (is_literal(mpl, "data")) { get_token(mpl /* data */); if (mpl->token != T_SEMICOLON) error(mpl, "semicolon missing where expected"); get_token(mpl /* ; */); } data_section(mpl); /* process end statement */ end_statement(mpl); xprintf("%d line%s were read\n", mpl->line, mpl->line == 1 ? "" : "s"); close_input(mpl); done: /* return to the calling program */ return mpl->phase; } /*---------------------------------------------------------------------- -- mpl_generate - generate model. -- -- *Synopsis* -- -- #include "glpmpl.h" -- int mpl_generate(MPL *mpl, char *file); -- -- *Description* -- -- The routine mpl_generate generates the model using its description -- stored in the translator database. This phase means generating all -- variables, constraints, and objectives, executing check and display -- statements, which precede the solve statement (if it is presented), -- and building the problem instance. -- -- The character string file specifies the name of output text file, to -- which output produced by display statements should be written. It is -- allowed to specify NULL, in which case the output goes to stdout via -- the routine print. -- -- This routine should be called once after the routine mpl_read_model -- or mpl_read_data and if one of the latters returned the code 2. -- -- *Returns* -- -- The routine mpl_generate returns one of the following codes: -- -- 3 - model has been successfully generated. In this case the calling -- program may call other api routines to obtain components of the -- problem instance from the translator database. -- 4 - processing failed due to some errors. In this case the calling -- program should call the routine mpl_terminate to terminate model -- processing. */ int mpl_generate(MPL *mpl, char *file) { if (!(mpl->phase == 1 || mpl->phase == 2)) xfault("mpl_generate: invalid call sequence\n"); /* set up error handler */ if (setjmp(mpl->jump)) goto done; /* generate model */ mpl->phase = 3; open_output(mpl, file); generate_model(mpl); flush_output(mpl); /* build problem instance */ build_problem(mpl); /* generation phase has been finished */ xprintf("Model has been successfully generated\n"); done: /* return to the calling program */ return mpl->phase; } /*---------------------------------------------------------------------- -- mpl_get_prob_name - obtain problem (model) name. -- -- *Synopsis* -- -- #include "glpmpl.h" -- char *mpl_get_prob_name(MPL *mpl); -- -- *Returns* -- -- The routine mpl_get_prob_name returns a pointer to internal buffer, -- which contains symbolic name of the problem (model). -- -- *Note* -- -- Currently MathProg has no feature to assign a symbolic name to the -- model. Therefore the routine mpl_get_prob_name tries to construct -- such name using the name of input text file containing model section, -- although this is not a good idea (due to portability problems). */ char *mpl_get_prob_name(MPL *mpl) { char *name = mpl->mpl_buf; char *file = mpl->mod_file; int k; if (mpl->phase != 3) xfault("mpl_get_prob_name: invalid call sequence\n"); for (;;) { if (strchr(file, '/') != NULL) file = strchr(file, '/') + 1; else if (strchr(file, '\\') != NULL) file = strchr(file, '\\') + 1; else if (strchr(file, ':') != NULL) file = strchr(file, ':') + 1; else break; } for (k = 0; ; k++) { if (k == 255) break; if (!(isalnum((unsigned char)*file) || *file == '_')) break; name[k] = *file++; } if (k == 0) strcpy(name, "Unknown"); else name[k] = '\0'; xassert(strlen(name) <= 255); return name; } /*---------------------------------------------------------------------- -- mpl_get_num_rows - determine number of rows. -- -- *Synopsis* -- -- #include "glpmpl.h" -- int mpl_get_num_rows(MPL *mpl); -- -- *Returns* -- -- The routine mpl_get_num_rows returns total number of rows in the -- problem, where each row is an individual constraint or objective. */ int mpl_get_num_rows(MPL *mpl) { if (mpl->phase != 3) xfault("mpl_get_num_rows: invalid call sequence\n"); return mpl->m; } /*---------------------------------------------------------------------- -- mpl_get_num_cols - determine number of columns. -- -- *Synopsis* -- -- #include "glpmpl.h" -- int mpl_get_num_cols(MPL *mpl); -- -- *Returns* -- -- The routine mpl_get_num_cols returns total number of columns in the -- problem, where each column is an individual variable. */ int mpl_get_num_cols(MPL *mpl) { if (mpl->phase != 3) xfault("mpl_get_num_cols: invalid call sequence\n"); return mpl->n; } /*---------------------------------------------------------------------- -- mpl_get_row_name - obtain row name. -- -- *Synopsis* -- -- #include "glpmpl.h" -- char *mpl_get_row_name(MPL *mpl, int i); -- -- *Returns* -- -- The routine mpl_get_row_name returns a pointer to internal buffer, -- which contains symbolic name of i-th row of the problem. */ char *mpl_get_row_name(MPL *mpl, int i) { char *name = mpl->mpl_buf, *t; int len; if (mpl->phase != 3) xfault("mpl_get_row_name: invalid call sequence\n"); if (!(1 <= i && i <= mpl->m)) xfault("mpl_get_row_name: i = %d; row number out of range\n", i); strcpy(name, mpl->row[i]->con->name); len = strlen(name); xassert(len <= 255); t = format_tuple(mpl, '[', mpl->row[i]->memb->tuple); while (*t) { if (len == 255) break; name[len++] = *t++; } name[len] = '\0'; if (len == 255) strcpy(name+252, "..."); xassert(strlen(name) <= 255); return name; } /*---------------------------------------------------------------------- -- mpl_get_row_kind - determine row kind. -- -- *Synopsis* -- -- #include "glpmpl.h" -- int mpl_get_row_kind(MPL *mpl, int i); -- -- *Returns* -- -- The routine mpl_get_row_kind returns the kind of i-th row, which can -- be one of the following: -- -- MPL_ST - non-free (constraint) row; -- MPL_MIN - free (objective) row to be minimized; -- MPL_MAX - free (objective) row to be maximized. */ int mpl_get_row_kind(MPL *mpl, int i) { int kind; if (mpl->phase != 3) xfault("mpl_get_row_kind: invalid call sequence\n"); if (!(1 <= i && i <= mpl->m)) xfault("mpl_get_row_kind: i = %d; row number out of range\n", i); switch (mpl->row[i]->con->type) { case A_CONSTRAINT: kind = MPL_ST; break; case A_MINIMIZE: kind = MPL_MIN; break; case A_MAXIMIZE: kind = MPL_MAX; break; default: xassert(mpl != mpl); } return kind; } /*---------------------------------------------------------------------- -- mpl_get_row_bnds - obtain row bounds. -- -- *Synopsis* -- -- #include "glpmpl.h" -- int mpl_get_row_bnds(MPL *mpl, int i, double *lb, double *ub); -- -- *Description* -- -- The routine mpl_get_row_bnds stores lower and upper bounds of i-th -- row of the problem to the locations, which the parameters lb and ub -- point to, respectively. Besides the routine returns the type of the -- i-th row. -- -- If some of the parameters lb and ub is NULL, the corresponding bound -- value is not stored. -- -- Types and bounds have the following meaning: -- -- Type Bounds Note -- ----------------------------------------------------------- -- MPL_FR -inf < f(x) < +inf Free linear form -- MPL_LO lb <= f(x) < +inf Inequality f(x) >= lb -- MPL_UP -inf < f(x) <= ub Inequality f(x) <= ub -- MPL_DB lb <= f(x) <= ub Inequality lb <= f(x) <= ub -- MPL_FX f(x) = lb Equality f(x) = lb -- -- where f(x) is the corresponding linear form of the i-th row. -- -- If the row has no lower bound, *lb is set to zero; if the row has -- no upper bound, *ub is set to zero; and if the row is of fixed type, -- both *lb and *ub are set to the same value. -- -- *Returns* -- -- The routine returns the type of the i-th row as it is stated in the -- table above. */ int mpl_get_row_bnds(MPL *mpl, int i, double *_lb, double *_ub) { ELEMCON *con; int type; double lb, ub; if (mpl->phase != 3) xfault("mpl_get_row_bnds: invalid call sequence\n"); if (!(1 <= i && i <= mpl->m)) xfault("mpl_get_row_bnds: i = %d; row number out of range\n", i); con = mpl->row[i]; #if 0 /* 21/VII-2006 */ if (con->con->lbnd == NULL && con->con->ubnd == NULL) type = MPL_FR, lb = ub = 0.0; else if (con->con->ubnd == NULL) type = MPL_LO, lb = con->lbnd, ub = 0.0; else if (con->con->lbnd == NULL) type = MPL_UP, lb = 0.0, ub = con->ubnd; else if (con->con->lbnd != con->con->ubnd) type = MPL_DB, lb = con->lbnd, ub = con->ubnd; else type = MPL_FX, lb = ub = con->lbnd; #else lb = (con->con->lbnd == NULL ? -DBL_MAX : con->lbnd); ub = (con->con->ubnd == NULL ? +DBL_MAX : con->ubnd); if (lb == -DBL_MAX && ub == +DBL_MAX) type = MPL_FR, lb = ub = 0.0; else if (ub == +DBL_MAX) type = MPL_LO, ub = 0.0; else if (lb == -DBL_MAX) type = MPL_UP, lb = 0.0; else if (con->con->lbnd != con->con->ubnd) type = MPL_DB; else type = MPL_FX; #endif if (_lb != NULL) *_lb = lb; if (_ub != NULL) *_ub = ub; return type; } /*---------------------------------------------------------------------- -- mpl_get_mat_row - obtain row of the constraint matrix. -- -- *Synopsis* -- -- #include "glpmpl.h" -- int mpl_get_mat_row(MPL *mpl, int i, int ndx[], double val[]); -- -- *Description* -- -- The routine mpl_get_mat_row stores column indices and numeric values -- of constraint coefficients for the i-th row to locations ndx[1], ..., -- ndx[len] and val[1], ..., val[len], respectively, where 0 <= len <= n -- is number of (structural) non-zero constraint coefficients, and n is -- number of columns in the problem. -- -- If the parameter ndx is NULL, column indices are not stored. If the -- parameter val is NULL, numeric values are not stored. -- -- Note that free rows may have constant terms, which are not part of -- the constraint matrix and therefore not reported by this routine. The -- constant term of a particular row can be obtained, if necessary, via -- the routine mpl_get_row_c0. -- -- *Returns* -- -- The routine mpl_get_mat_row returns len, which is length of i-th row -- of the constraint matrix (i.e. number of non-zero coefficients). */ int mpl_get_mat_row(MPL *mpl, int i, int ndx[], double val[]) { FORMULA *term; int len = 0; if (mpl->phase != 3) xfault("mpl_get_mat_row: invalid call sequence\n"); if (!(1 <= i && i <= mpl->m)) xfault("mpl_get_mat_row: i = %d; row number out of range\n", i); for (term = mpl->row[i]->form; term != NULL; term = term->next) { xassert(term->var != NULL); len++; xassert(len <= mpl->n); if (ndx != NULL) ndx[len] = term->var->j; if (val != NULL) val[len] = term->coef; } return len; } /*---------------------------------------------------------------------- -- mpl_get_row_c0 - obtain constant term of free row. -- -- *Synopsis* -- -- #include "glpmpl.h" -- double mpl_get_row_c0(MPL *mpl, int i); -- -- *Returns* -- -- The routine mpl_get_row_c0 returns numeric value of constant term of -- i-th row. -- -- Note that only free rows may have non-zero constant terms. Therefore -- if i-th row is not free, the routine returns zero. */ double mpl_get_row_c0(MPL *mpl, int i) { ELEMCON *con; double c0; if (mpl->phase != 3) xfault("mpl_get_row_c0: invalid call sequence\n"); if (!(1 <= i && i <= mpl->m)) xfault("mpl_get_row_c0: i = %d; row number out of range\n", i); con = mpl->row[i]; if (con->con->lbnd == NULL && con->con->ubnd == NULL) c0 = - con->lbnd; else c0 = 0.0; return c0; } /*---------------------------------------------------------------------- -- mpl_get_col_name - obtain column name. -- -- *Synopsis* -- -- #include "glpmpl.h" -- char *mpl_get_col_name(MPL *mpl, int j); -- -- *Returns* -- -- The routine mpl_get_col_name returns a pointer to internal buffer, -- which contains symbolic name of j-th column of the problem. */ char *mpl_get_col_name(MPL *mpl, int j) { char *name = mpl->mpl_buf, *t; int len; if (mpl->phase != 3) xfault("mpl_get_col_name: invalid call sequence\n"); if (!(1 <= j && j <= mpl->n)) xfault("mpl_get_col_name: j = %d; column number out of range\n" , j); strcpy(name, mpl->col[j]->var->name); len = strlen(name); xassert(len <= 255); t = format_tuple(mpl, '[', mpl->col[j]->memb->tuple); while (*t) { if (len == 255) break; name[len++] = *t++; } name[len] = '\0'; if (len == 255) strcpy(name+252, "..."); xassert(strlen(name) <= 255); return name; } /*---------------------------------------------------------------------- -- mpl_get_col_kind - determine column kind. -- -- *Synopsis* -- -- #include "glpmpl.h" -- int mpl_get_col_kind(MPL *mpl, int j); -- -- *Returns* -- -- The routine mpl_get_col_kind returns the kind of j-th column, which -- can be one of the following: -- -- MPL_NUM - continuous variable; -- MPL_INT - integer variable; -- MPL_BIN - binary variable. -- -- Note that column kinds are defined independently on type and bounds -- (reported by the routine mpl_get_col_bnds) of corresponding columns. -- This means, in particular, that bounds of an integer column may be -- fractional, or a binary column may have lower and upper bounds that -- are not 0 and 1 (or it may have no lower/upper bound at all). */ int mpl_get_col_kind(MPL *mpl, int j) { int kind; if (mpl->phase != 3) xfault("mpl_get_col_kind: invalid call sequence\n"); if (!(1 <= j && j <= mpl->n)) xfault("mpl_get_col_kind: j = %d; column number out of range\n" , j); switch (mpl->col[j]->var->type) { case A_NUMERIC: kind = MPL_NUM; break; case A_INTEGER: kind = MPL_INT; break; case A_BINARY: kind = MPL_BIN; break; default: xassert(mpl != mpl); } return kind; } /*---------------------------------------------------------------------- -- mpl_get_col_bnds - obtain column bounds. -- -- *Synopsis* -- -- #include "glpmpl.h" -- int mpl_get_col_bnds(MPL *mpl, int j, double *lb, double *ub); -- -- *Description* -- -- The routine mpl_get_col_bnds stores lower and upper bound of j-th -- column of the problem to the locations, which the parameters lb and -- ub point to, respectively. Besides the routine returns the type of -- the j-th column. -- -- If some of the parameters lb and ub is NULL, the corresponding bound -- value is not stored. -- -- Types and bounds have the following meaning: -- -- Type Bounds Note -- ------------------------------------------------------ -- MPL_FR -inf < x < +inf Free (unbounded) variable -- MPL_LO lb <= x < +inf Variable with lower bound -- MPL_UP -inf < x <= ub Variable with upper bound -- MPL_DB lb <= x <= ub Double-bounded variable -- MPL_FX x = lb Fixed variable -- -- where x is individual variable corresponding to the j-th column. -- -- If the column has no lower bound, *lb is set to zero; if the column -- has no upper bound, *ub is set to zero; and if the column is of fixed -- type, both *lb and *ub are set to the same value. -- -- *Returns* -- -- The routine returns the type of the j-th column as it is stated in -- the table above. */ int mpl_get_col_bnds(MPL *mpl, int j, double *_lb, double *_ub) { ELEMVAR *var; int type; double lb, ub; if (mpl->phase != 3) xfault("mpl_get_col_bnds: invalid call sequence\n"); if (!(1 <= j && j <= mpl->n)) xfault("mpl_get_col_bnds: j = %d; column number out of range\n" , j); var = mpl->col[j]; #if 0 /* 21/VII-2006 */ if (var->var->lbnd == NULL && var->var->ubnd == NULL) type = MPL_FR, lb = ub = 0.0; else if (var->var->ubnd == NULL) type = MPL_LO, lb = var->lbnd, ub = 0.0; else if (var->var->lbnd == NULL) type = MPL_UP, lb = 0.0, ub = var->ubnd; else if (var->var->lbnd != var->var->ubnd) type = MPL_DB, lb = var->lbnd, ub = var->ubnd; else type = MPL_FX, lb = ub = var->lbnd; #else lb = (var->var->lbnd == NULL ? -DBL_MAX : var->lbnd); ub = (var->var->ubnd == NULL ? +DBL_MAX : var->ubnd); if (lb == -DBL_MAX && ub == +DBL_MAX) type = MPL_FR, lb = ub = 0.0; else if (ub == +DBL_MAX) type = MPL_LO, ub = 0.0; else if (lb == -DBL_MAX) type = MPL_UP, lb = 0.0; else if (var->var->lbnd != var->var->ubnd) type = MPL_DB; else type = MPL_FX; #endif if (_lb != NULL) *_lb = lb; if (_ub != NULL) *_ub = ub; return type; } /*---------------------------------------------------------------------- -- mpl_has_solve_stmt - check if model has solve statement. -- -- *Synopsis* -- -- #include "glpmpl.h" -- int mpl_has_solve_stmt(MPL *mpl); -- -- *Returns* -- -- If the model has the solve statement, the routine returns non-zero, -- otherwise zero is returned. */ int mpl_has_solve_stmt(MPL *mpl) { if (mpl->phase != 3) xfault("mpl_has_solve_stmt: invalid call sequence\n"); return mpl->flag_s; } #if 1 /* 15/V-2010 */ void mpl_put_row_soln(MPL *mpl, int i, int stat, double prim, double dual) { /* store row (constraint/objective) solution components */ xassert(mpl->phase == 3); xassert(1 <= i && i <= mpl->m); mpl->row[i]->stat = stat; mpl->row[i]->prim = prim; mpl->row[i]->dual = dual; return; } #endif #if 1 /* 15/V-2010 */ void mpl_put_col_soln(MPL *mpl, int j, int stat, double prim, double dual) { /* store column (variable) solution components */ xassert(mpl->phase == 3); xassert(1 <= j && j <= mpl->n); mpl->col[j]->stat = stat; mpl->col[j]->prim = prim; mpl->col[j]->dual = dual; return; } #endif #if 0 /* 15/V-2010 */ /*---------------------------------------------------------------------- -- mpl_put_col_value - store column value. -- -- *Synopsis* -- -- #include "glpmpl.h" -- void mpl_put_col_value(MPL *mpl, int j, double val); -- -- *Description* -- -- The routine mpl_put_col_value stores numeric value of j-th column -- into the translator database. It is assumed that the column value is -- provided by the solver. */ void mpl_put_col_value(MPL *mpl, int j, double val) { if (mpl->phase != 3) xfault("mpl_put_col_value: invalid call sequence\n"); if (!(1 <= j && j <= mpl->n)) xfault( "mpl_put_col_value: j = %d; column number out of range\n", j); mpl->col[j]->prim = val; return; } #endif /*---------------------------------------------------------------------- -- mpl_postsolve - postsolve model. -- -- *Synopsis* -- -- #include "glpmpl.h" -- int mpl_postsolve(MPL *mpl); -- -- *Description* -- -- The routine mpl_postsolve performs postsolving of the model using -- its description stored in the translator database. This phase means -- executing statements, which follow the solve statement. -- -- If this routine is used, it should be called once after the routine -- mpl_generate and if the latter returned the code 3. -- -- *Returns* -- -- The routine mpl_postsolve returns one of the following codes: -- -- 3 - model has been successfully postsolved. -- 4 - processing failed due to some errors. In this case the calling -- program should call the routine mpl_terminate to terminate model -- processing. */ int mpl_postsolve(MPL *mpl) { if (!(mpl->phase == 3 && !mpl->flag_p)) xfault("mpl_postsolve: invalid call sequence\n"); /* set up error handler */ if (setjmp(mpl->jump)) goto done; /* perform postsolving */ postsolve_model(mpl); flush_output(mpl); /* postsolving phase has been finished */ xprintf("Model has been successfully processed\n"); done: /* return to the calling program */ return mpl->phase; } /*---------------------------------------------------------------------- -- mpl_terminate - free all resources used by translator. -- -- *Synopsis* -- -- #include "glpmpl.h" -- void mpl_terminate(MPL *mpl); -- -- *Description* -- -- The routine mpl_terminate frees all the resources used by the GNU -- MathProg translator. */ void mpl_terminate(MPL *mpl) { if (setjmp(mpl->jump)) xassert(mpl != mpl); switch (mpl->phase) { case 0: case 1: case 2: case 3: /* there were no errors; clean the model content */ clean_model(mpl); xassert(mpl->a_list == NULL); #if 1 /* 11/II-2008 */ xassert(mpl->dca == NULL); #endif break; case 4: /* model processing has been finished due to error; delete search trees, which may be created for some arrays */ { ARRAY *a; for (a = mpl->a_list; a != NULL; a = a->next) if (a->tree != NULL) avl_delete_tree(a->tree); } #if 1 /* 11/II-2008 */ free_dca(mpl); #endif break; default: xassert(mpl != mpl); } /* delete the translator database */ xfree(mpl->image); xfree(mpl->b_image); xfree(mpl->f_image); xfree(mpl->context); dmp_delete_pool(mpl->pool); avl_delete_tree(mpl->tree); dmp_delete_pool(mpl->strings); dmp_delete_pool(mpl->symbols); dmp_delete_pool(mpl->tuples); dmp_delete_pool(mpl->arrays); dmp_delete_pool(mpl->members); dmp_delete_pool(mpl->elemvars); dmp_delete_pool(mpl->formulae); dmp_delete_pool(mpl->elemcons); xfree(mpl->sym_buf); xfree(mpl->tup_buf); rng_delete_rand(mpl->rand); if (mpl->row != NULL) xfree(mpl->row); if (mpl->col != NULL) xfree(mpl->col); if (mpl->in_fp != NULL) xfclose(mpl->in_fp); if (mpl->out_fp != NULL /* && mpl->out_fp != (void *)stdout */) xfclose(mpl->out_fp); if (mpl->out_file != NULL) xfree(mpl->out_file); if (mpl->prt_fp != NULL) xfclose(mpl->prt_fp); if (mpl->prt_file != NULL) xfree(mpl->prt_file); if (mpl->mod_file != NULL) xfree(mpl->mod_file); xfree(mpl->mpl_buf); xfree(mpl); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpsql.c0000644000076500000240000013165313524616144025056 0ustar tamasstaff00000000000000/* glpsql.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Author: Heinrich Schuchardt . * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wunused-function" #endif #ifdef HAVE_CONFIG_H #include #endif #include "glpmpl.h" #include "glpsql.h" #ifdef ODBC_DLNAME #define HAVE_ODBC #define libodbc ODBC_DLNAME #define h_odbc (get_env_ptr()->h_odbc) #endif #ifdef MYSQL_DLNAME #define HAVE_MYSQL #define libmysql MYSQL_DLNAME #define h_mysql (get_env_ptr()->h_mysql) #endif static void *db_iodbc_open_int(TABDCA *dca, int mode, const char **sqllines); static void *db_mysql_open_int(TABDCA *dca, int mode, const char **sqllines); /**********************************************************************/ #if defined(HAVE_ODBC) || defined(HAVE_MYSQL) #define SQL_FIELD_MAX 100 /* maximal field count */ #define SQL_FDLEN_MAX 255 /* maximal field length */ /*********************************************************************** * NAME * * args_concat - concatenate arguments * * SYNOPSIS * * static char **args_concat(TABDCA *dca); * * DESCRIPTION * * The arguments passed in dca are SQL statements. A SQL statement may * be split over multiple arguments. The last argument of a SQL * statement will be terminated with a semilocon. Each SQL statement is * merged into a single zero terminated string. Boundaries between * arguments are replaced by space. * * RETURNS * * Buffer with SQL statements */ static char **args_concat(TABDCA *dca) { const char *arg; int i; int j; int j0; int j1; int len; int lentot; int narg; int nline = 0; void *ret; char **sqllines = NULL; narg = mpl_tab_num_args(dca); /* The SQL statements start with argument 3. */ if (narg < 3) return NULL; /* Count the SQL statements */ for (j = 3; j <= narg; j++) { arg = mpl_tab_get_arg(dca, j); len = strlen(arg); if (arg[len-1] == ';' || j == narg) nline ++; } /* Allocate string buffer. */ sqllines = (char **) xmalloc((nline+1) * sizeof(char **)); /* Join arguments */ sqllines[0] = NULL; j0 = 3; i = 0; lentot = 0; for (j = 3; j <= narg; j++) { arg = mpl_tab_get_arg(dca, j); len = strlen(arg); lentot += len; if (arg[len-1] == ';' || j == narg) { /* Join arguments for a single SQL statement */ sqllines[i] = xmalloc(lentot+1); sqllines[i+1] = NULL; sqllines[i][0] = 0x00; for (j1 = j0; j1 <= j; j1++) { if(j1>j0) strcat(sqllines[i], " "); strcat(sqllines[i], mpl_tab_get_arg(dca, j1)); } len = strlen(sqllines[i]); if (sqllines[i][len-1] == ';') sqllines[i][len-1] = 0x00; j0 = j+1; i++; lentot = 0; } } return sqllines; } /*********************************************************************** * NAME * * free_buffer - free multiline string buffer * * SYNOPSIS * * static void free_buffer(char **buf); * * DESCRIPTION * * buf is a list of strings terminated by NULL. * The memory for the strings and for the list is released. */ static void free_buffer(char **buf) { int i; for(i = 0; buf[i] != NULL; i++) xfree(buf[i]); xfree(buf); } static int db_escaped_string_length(const char* from) /* length of escaped string */ { int count; const char *pointer; for (pointer = from, count = 0; *pointer != (char) '\0'; pointer++, count++) { switch (*pointer) { case '\'': count++; break; } } return count; } static int db_escape_string (char *to, const char *from) /* escape string*/ { const char *source = from; char *target = to; unsigned int remaining; remaining = strlen(from); if (to == NULL) to = (char *) (from + remaining); while (remaining > 0) { switch (*source) { case '\'': *target = '\''; target++; *target = '\''; break; default: *target = *source; } source++; target++; remaining--; } /* Write the terminating NUL character. */ *target = '\0'; return target - to; } static char *db_generate_select_stmt(TABDCA *dca) /* generate select statement */ { char *arg; char const *field; char *query; int j; int narg; int nf; int total; total = 50; nf = mpl_tab_num_flds(dca); narg = mpl_tab_num_args(dca); for (j=1; j <= nf && j <= SQL_FIELD_MAX; j++) { field = mpl_tab_get_name(dca, j); total += strlen(field); total += 2; } arg = (char *) mpl_tab_get_arg(dca, narg); total += strlen(arg); query = xmalloc( total * sizeof(char)); strcpy (query, "SELECT "); for (j=1; j <= nf && j <= SQL_FIELD_MAX; j++) { field = mpl_tab_get_name(dca, j); strcat(query, field); if ( j < nf ) strcat(query, ", "); } strcat(query, " FROM "); strcat(query, arg); return query; } static char *db_generate_insert_stmt(TABDCA *dca) /* generate insert statement */ { char *arg; char const *field; char *query; int j; int narg; int nf; int total; total = 50; nf = mpl_tab_num_flds(dca); narg = mpl_tab_num_args(dca); for (j=1; j <= nf && j <= SQL_FIELD_MAX; j++) { field = mpl_tab_get_name(dca, j); total += strlen(field); total += 5; } arg = (char *) mpl_tab_get_arg(dca, narg); total += strlen(arg); query = xmalloc( (total+1) * sizeof(char)); strcpy (query, "INSERT INTO "); strcat(query, arg); strcat(query, " ( "); for (j=1; j <= nf && j <= SQL_FIELD_MAX; j++) { field = mpl_tab_get_name(dca, j); strcat(query, field); if ( j < nf ) strcat(query, ", "); } strcat(query, " ) VALUES ( "); for (j=1; j <= nf && j <= SQL_FIELD_MAX; j++) { strcat(query, "?"); if ( j < nf ) strcat(query, ", "); } strcat(query, " )"); return query; } #endif /**********************************************************************/ #ifndef HAVE_ODBC void *db_iodbc_open(TABDCA *dca, int mode) { xassert(dca == dca); xassert(mode == mode); xprintf("iODBC table driver not supported\n"); return NULL; } int db_iodbc_read(TABDCA *dca, void *link) { xassert(dca != dca); xassert(link != link); return 0; } int db_iodbc_write(TABDCA *dca, void *link) { xassert(dca != dca); xassert(link != link); return 0; } int db_iodbc_close(TABDCA *dca, void *link) { xassert(dca != dca); xassert(link != link); return 0; } #else #if defined(__CYGWIN__) || defined(__MINGW32__) || defined(__WOE__) #include #endif #include #include struct db_odbc { int mode; /*'R' = Read, 'W' = Write*/ SQLHDBC hdbc; /*connection handle*/ SQLHENV henv; /*environment handle*/ SQLHSTMT hstmt; /*statement handle*/ SQLSMALLINT nresultcols; /* columns in result*/ SQLULEN collen[SQL_FIELD_MAX+1]; SQLLEN outlen[SQL_FIELD_MAX+1]; SQLSMALLINT coltype[SQL_FIELD_MAX+1]; SQLCHAR data[SQL_FIELD_MAX+1][SQL_FDLEN_MAX+1]; SQLCHAR colname[SQL_FIELD_MAX+1][SQL_FDLEN_MAX+1]; int isnumeric[SQL_FIELD_MAX+1]; int nf; /* number of fields in the csv file */ int ref[1+SQL_FIELD_MAX]; /* ref[k] = k', if k-th field of the csv file corresponds to k'-th field in the table statement; if ref[k] = 0, k-th field of the csv file is ignored */ SQLCHAR *query; /* query generated by db_iodbc_open */ }; SQLRETURN SQL_API dl_SQLAllocHandle ( SQLSMALLINT HandleType, SQLHANDLE InputHandle, SQLHANDLE *OutputHandle) { typedef SQLRETURN SQL_API ep_SQLAllocHandle( SQLSMALLINT HandleType, SQLHANDLE InputHandle, SQLHANDLE *OutputHandle); ep_SQLAllocHandle *fn; fn = (ep_SQLAllocHandle *) xdlsym(h_odbc, "SQLAllocHandle"); xassert(fn != NULL); return (*fn)(HandleType, InputHandle, OutputHandle); } SQLRETURN SQL_API dl_SQLBindCol ( SQLHSTMT StatementHandle, SQLUSMALLINT ColumnNumber, SQLSMALLINT TargetType, SQLPOINTER TargetValue, SQLLEN BufferLength, SQLLEN *StrLen_or_Ind) { typedef SQLRETURN SQL_API ep_SQLBindCol( SQLHSTMT StatementHandle, SQLUSMALLINT ColumnNumber, SQLSMALLINT TargetType, SQLPOINTER TargetValue, SQLLEN BufferLength, SQLLEN *StrLen_or_Ind); ep_SQLBindCol *fn; fn = (ep_SQLBindCol *) xdlsym(h_odbc, "SQLBindCol"); xassert(fn != NULL); return (*fn)(StatementHandle, ColumnNumber, TargetType, TargetValue, BufferLength, StrLen_or_Ind); } SQLRETURN SQL_API dl_SQLCloseCursor ( SQLHSTMT StatementHandle) { typedef SQLRETURN SQL_API ep_SQLCloseCursor ( SQLHSTMT StatementHandle); ep_SQLCloseCursor *fn; fn = (ep_SQLCloseCursor *) xdlsym(h_odbc, "SQLCloseCursor"); xassert(fn != NULL); return (*fn)(StatementHandle); } SQLRETURN SQL_API dl_SQLDisconnect ( SQLHDBC ConnectionHandle) { typedef SQLRETURN SQL_API ep_SQLDisconnect( SQLHDBC ConnectionHandle); ep_SQLDisconnect *fn; fn = (ep_SQLDisconnect *) xdlsym(h_odbc, "SQLDisconnect"); xassert(fn != NULL); return (*fn)(ConnectionHandle); } SQLRETURN SQL_API dl_SQLDriverConnect ( SQLHDBC hdbc, SQLHWND hwnd, SQLCHAR *szConnStrIn, SQLSMALLINT cbConnStrIn, SQLCHAR *szConnStrOut, SQLSMALLINT cbConnStrOutMax, SQLSMALLINT *pcbConnStrOut, SQLUSMALLINT fDriverCompletion) { typedef SQLRETURN SQL_API ep_SQLDriverConnect( SQLHDBC hdbc, SQLHWND hwnd, SQLCHAR * szConnStrIn, SQLSMALLINT cbConnStrIn, SQLCHAR * szConnStrOut, SQLSMALLINT cbConnStrOutMax, SQLSMALLINT * pcbConnStrOut, SQLUSMALLINT fDriverCompletion); ep_SQLDriverConnect *fn; fn = (ep_SQLDriverConnect *) xdlsym(h_odbc, "SQLDriverConnect"); xassert(fn != NULL); return (*fn)(hdbc, hwnd, szConnStrIn, cbConnStrIn, szConnStrOut, cbConnStrOutMax, pcbConnStrOut, fDriverCompletion); } SQLRETURN SQL_API dl_SQLEndTran ( SQLSMALLINT HandleType, SQLHANDLE Handle, SQLSMALLINT CompletionType) { typedef SQLRETURN SQL_API ep_SQLEndTran ( SQLSMALLINT HandleType, SQLHANDLE Handle, SQLSMALLINT CompletionType); ep_SQLEndTran *fn; fn = (ep_SQLEndTran *) xdlsym(h_odbc, "SQLEndTran"); xassert(fn != NULL); return (*fn)(HandleType, Handle, CompletionType); } SQLRETURN SQL_API dl_SQLExecDirect ( SQLHSTMT StatementHandle, SQLCHAR * StatementText, SQLINTEGER TextLength) { typedef SQLRETURN SQL_API ep_SQLExecDirect ( SQLHSTMT StatementHandle, SQLCHAR * StatementText, SQLINTEGER TextLength); ep_SQLExecDirect *fn; fn = (ep_SQLExecDirect *) xdlsym(h_odbc, "SQLExecDirect"); xassert(fn != NULL); return (*fn)(StatementHandle, StatementText, TextLength); } SQLRETURN SQL_API dl_SQLFetch ( SQLHSTMT StatementHandle) { typedef SQLRETURN SQL_API ep_SQLFetch ( SQLHSTMT StatementHandle); ep_SQLFetch *fn; fn = (ep_SQLFetch*) xdlsym(h_odbc, "SQLFetch"); xassert(fn != NULL); return (*fn)(StatementHandle); } SQLRETURN SQL_API dl_SQLFreeHandle ( SQLSMALLINT HandleType, SQLHANDLE Handle) { typedef SQLRETURN SQL_API ep_SQLFreeHandle ( SQLSMALLINT HandleType, SQLHANDLE Handle); ep_SQLFreeHandle *fn; fn = (ep_SQLFreeHandle *) xdlsym(h_odbc, "SQLFreeHandle"); xassert(fn != NULL); return (*fn)(HandleType, Handle); } SQLRETURN SQL_API dl_SQLDescribeCol ( SQLHSTMT StatementHandle, SQLUSMALLINT ColumnNumber, SQLCHAR * ColumnName, SQLSMALLINT BufferLength, SQLSMALLINT * NameLength, SQLSMALLINT * DataType, SQLULEN * ColumnSize, SQLSMALLINT * DecimalDigits, SQLSMALLINT * Nullable) { typedef SQLRETURN SQL_API ep_SQLDescribeCol ( SQLHSTMT StatementHandle, SQLUSMALLINT ColumnNumber, SQLCHAR *ColumnName, SQLSMALLINT BufferLength, SQLSMALLINT *NameLength, SQLSMALLINT *DataType, SQLULEN *ColumnSize, SQLSMALLINT *DecimalDigits, SQLSMALLINT *Nullable); ep_SQLDescribeCol *fn; fn = (ep_SQLDescribeCol *) xdlsym(h_odbc, "SQLDescribeCol"); xassert(fn != NULL); return (*fn)(StatementHandle, ColumnNumber, ColumnName, BufferLength, NameLength, DataType, ColumnSize, DecimalDigits, Nullable); } SQLRETURN SQL_API dl_SQLGetDiagRec ( SQLSMALLINT HandleType, SQLHANDLE Handle, SQLSMALLINT RecNumber, SQLCHAR *Sqlstate, SQLINTEGER *NativeError, SQLCHAR *MessageText, SQLSMALLINT BufferLength, SQLSMALLINT *TextLength) { typedef SQLRETURN SQL_API ep_SQLGetDiagRec ( SQLSMALLINT HandleType, SQLHANDLE Handle, SQLSMALLINT RecNumber, SQLCHAR *Sqlstate, SQLINTEGER *NativeError, SQLCHAR *MessageText, SQLSMALLINT BufferLength, SQLSMALLINT *TextLength); ep_SQLGetDiagRec *fn; fn = (ep_SQLGetDiagRec *) xdlsym(h_odbc, "SQLGetDiagRec"); xassert(fn != NULL); return (*fn)(HandleType, Handle, RecNumber, Sqlstate, NativeError, MessageText, BufferLength, TextLength); } SQLRETURN SQL_API dl_SQLGetInfo ( SQLHDBC ConnectionHandle, SQLUSMALLINT InfoType, SQLPOINTER InfoValue, SQLSMALLINT BufferLength, SQLSMALLINT *StringLength) { typedef SQLRETURN SQL_API ep_SQLGetInfo ( SQLHDBC ConnectionHandle, SQLUSMALLINT InfoType, SQLPOINTER InfoValue, SQLSMALLINT BufferLength, SQLSMALLINT *StringLength); ep_SQLGetInfo *fn; fn = (ep_SQLGetInfo *) xdlsym(h_odbc, "SQLGetInfo"); xassert(fn != NULL); return (*fn)(ConnectionHandle, InfoType, InfoValue, BufferLength, StringLength); } SQLRETURN SQL_API dl_SQLNumResultCols ( SQLHSTMT StatementHandle, SQLSMALLINT *ColumnCount) { typedef SQLRETURN SQL_API ep_SQLNumResultCols ( SQLHSTMT StatementHandle, SQLSMALLINT *ColumnCount); ep_SQLNumResultCols *fn; fn = (ep_SQLNumResultCols *) xdlsym(h_odbc, "SQLNumResultCols"); xassert(fn != NULL); return (*fn)(StatementHandle, ColumnCount); } SQLRETURN SQL_API dl_SQLSetConnectAttr ( SQLHDBC ConnectionHandle, SQLINTEGER Attribute, SQLPOINTER Value, SQLINTEGER StringLength) { typedef SQLRETURN SQL_API ep_SQLSetConnectAttr ( SQLHDBC ConnectionHandle, SQLINTEGER Attribute, SQLPOINTER Value, SQLINTEGER StringLength); ep_SQLSetConnectAttr *fn; fn = (ep_SQLSetConnectAttr *) xdlsym(h_odbc, "SQLSetConnectAttr"); xassert(fn != NULL); return (*fn)(ConnectionHandle, Attribute, Value, StringLength); } SQLRETURN SQL_API dl_SQLSetEnvAttr ( SQLHENV EnvironmentHandle, SQLINTEGER Attribute, SQLPOINTER Value, SQLINTEGER StringLength) { typedef SQLRETURN SQL_API ep_SQLSetEnvAttr ( SQLHENV EnvironmentHandle, SQLINTEGER Attribute, SQLPOINTER Value, SQLINTEGER StringLength); ep_SQLSetEnvAttr *fn; fn = (ep_SQLSetEnvAttr *) xdlsym(h_odbc, "SQLSetEnvAttr"); xassert(fn != NULL); return (*fn)(EnvironmentHandle, Attribute, Value, StringLength); } static void extract_error( char *fn, SQLHANDLE handle, SQLSMALLINT type); static int is_numeric( SQLSMALLINT coltype); /*********************************************************************** * NAME * * db_iodbc_open - open connection to ODBC data base * * SYNOPSIS * * #include "glpsql.h" * void *db_iodbc_open(TABDCA *dca, int mode); * * DESCRIPTION * * The routine db_iodbc_open opens a connection to an ODBC data base. * It then executes the sql statements passed. * * In the case of table read the SELECT statement is executed. * * In the case of table write the INSERT statement is prepared. * RETURNS * * The routine returns a pointer to data storage area created. */ void *db_iodbc_open(TABDCA *dca, int mode) { void *ret; char **sqllines; sqllines = args_concat(dca); if (sqllines == NULL) { xprintf("Missing arguments in table statement.\n" "Please, supply table driver, dsn, and query.\n"); return NULL; } ret = db_iodbc_open_int(dca, mode, (const char **) sqllines); free_buffer(sqllines); return ret; } static void *db_iodbc_open_int(TABDCA *dca, int mode, const char **sqllines) { struct db_odbc *sql; SQLRETURN ret; SQLCHAR FAR *dsn; SQLCHAR info[256]; SQLSMALLINT colnamelen; SQLSMALLINT nullable; SQLSMALLINT scale; const char *arg; int narg; int i, j; int total; if (libodbc == NULL) { xprintf("No loader for shared ODBC library available\n"); return NULL; } if (h_odbc == NULL) { h_odbc = xdlopen(libodbc); if (h_odbc == NULL) { xprintf("unable to open library %s\n", libodbc); xprintf("%s\n", xerrmsg()); return NULL; } } sql = (struct db_odbc *) xmalloc(sizeof(struct db_odbc)); if (sql == NULL) return NULL; sql->mode = mode; sql->hdbc = NULL; sql->henv = NULL; sql->hstmt = NULL; sql->query = NULL; narg = mpl_tab_num_args(dca); dsn = (SQLCHAR FAR *) mpl_tab_get_arg(dca, 2); /* allocate an environment handle */ ret = dl_SQLAllocHandle(SQL_HANDLE_ENV, SQL_NULL_HANDLE, &(sql->henv)); /* set attribute to enable application to run as ODBC 3.0 application */ ret = dl_SQLSetEnvAttr(sql->henv, SQL_ATTR_ODBC_VERSION, (void *) SQL_OV_ODBC3, 0); /* allocate a connection handle */ ret = dl_SQLAllocHandle(SQL_HANDLE_DBC, sql->henv, &(sql->hdbc)); /* connect */ ret = dl_SQLDriverConnect(sql->hdbc, NULL, dsn, SQL_NTS, NULL, 0, NULL, SQL_DRIVER_COMPLETE); if (SQL_SUCCEEDED(ret)) { /* output information about data base connection */ xprintf("Connected to "); dl_SQLGetInfo(sql->hdbc, SQL_DBMS_NAME, (SQLPOINTER)info, sizeof(info), NULL); xprintf("%s ", info); dl_SQLGetInfo(sql->hdbc, SQL_DBMS_VER, (SQLPOINTER)info, sizeof(info), NULL); xprintf("%s - ", info); dl_SQLGetInfo(sql->hdbc, SQL_DATABASE_NAME, (SQLPOINTER)info, sizeof(info), NULL); xprintf("%s\n", info); } else { /* describe error */ xprintf("Failed to connect\n"); extract_error("SQLDriverConnect", sql->hdbc, SQL_HANDLE_DBC); dl_SQLFreeHandle(SQL_HANDLE_DBC, sql->hdbc); dl_SQLFreeHandle(SQL_HANDLE_ENV, sql->henv); xfree(sql); return NULL; } /* set AUTOCOMMIT on*/ ret = dl_SQLSetConnectAttr(sql->hdbc, SQL_ATTR_AUTOCOMMIT, (SQLPOINTER)SQL_AUTOCOMMIT_ON, 0); /* allocate a statement handle */ ret = dl_SQLAllocHandle(SQL_HANDLE_STMT, sql->hdbc, &(sql->hstmt)); /* initialization queries */ for(j = 0; sqllines[j+1] != NULL; j++) { sql->query = (SQLCHAR *) sqllines[j]; xprintf("%s\n", sql->query); ret = dl_SQLExecDirect(sql->hstmt, sql->query, SQL_NTS); switch (ret) { case SQL_SUCCESS: case SQL_SUCCESS_WITH_INFO: case SQL_NO_DATA_FOUND: break; default: xprintf("db_iodbc_open: Query\n\"%s\"\nfailed.\n", sql->query); extract_error("SQLExecDirect", sql->hstmt, SQL_HANDLE_STMT); dl_SQLFreeHandle(SQL_HANDLE_STMT, sql->hstmt); dl_SQLDisconnect(sql->hdbc); dl_SQLFreeHandle(SQL_HANDLE_DBC, sql->hdbc); dl_SQLFreeHandle(SQL_HANDLE_ENV, sql->henv); xfree(sql); return NULL; } /* commit statement */ dl_SQLEndTran(SQL_HANDLE_ENV, sql->henv, SQL_COMMIT); } if ( sql->mode == 'R' ) { sql->nf = mpl_tab_num_flds(dca); for(j = 0; sqllines[j] != NULL; j++) arg = sqllines[j]; total = strlen(arg); if (total > 7 && 0 == strncmp(arg, "SELECT ", 7)) { total = strlen(arg); sql->query = xmalloc( (total+1) * sizeof(char)); strcpy (sql->query, arg); } else { sql->query = db_generate_select_stmt(dca); } xprintf("%s\n", sql->query); if (dl_SQLExecDirect(sql->hstmt, sql->query, SQL_NTS) != SQL_SUCCESS) { xprintf("db_iodbc_open: Query\n\"%s\"\nfailed.\n", sql->query); extract_error("SQLExecDirect", sql->hstmt, SQL_HANDLE_STMT); dl_SQLFreeHandle(SQL_HANDLE_STMT, sql->hstmt); dl_SQLDisconnect(sql->hdbc); dl_SQLFreeHandle(SQL_HANDLE_DBC, sql->hdbc); dl_SQLFreeHandle(SQL_HANDLE_ENV, sql->henv); xfree(sql->query); xfree(sql); return NULL; } xfree(sql->query); /* determine number of result columns */ ret = dl_SQLNumResultCols(sql->hstmt, &sql->nresultcols); total = sql->nresultcols; if (total > SQL_FIELD_MAX) { xprintf("db_iodbc_open: Too many fields (> %d) in query.\n" "\"%s\"\n", SQL_FIELD_MAX, sql->query); dl_SQLFreeHandle(SQL_HANDLE_STMT, sql->hstmt); dl_SQLDisconnect(sql->hdbc); dl_SQLFreeHandle(SQL_HANDLE_DBC, sql->hdbc); dl_SQLFreeHandle(SQL_HANDLE_ENV, sql->henv); xfree(sql->query); return NULL; } for (i = 1; i <= total; i++) { /* return a set of attributes for a column */ ret = dl_SQLDescribeCol(sql->hstmt, (SQLSMALLINT) i, sql->colname[i], SQL_FDLEN_MAX, &colnamelen, &(sql->coltype[i]), &(sql->collen[i]), &scale, &nullable); sql->isnumeric[i] = is_numeric(sql->coltype[i]); /* bind columns to program vars, converting all types to CHAR*/ dl_SQLBindCol(sql->hstmt, i, SQL_CHAR, sql->data[i], SQL_FDLEN_MAX, &(sql->outlen[i])); for (j = sql->nf; j >= 1; j--) { if (strcmp(mpl_tab_get_name(dca, j), sql->colname[i]) == 0) break; } sql->ref[i] = j; } } else if ( sql->mode == 'W' ) { for(j = 0; sqllines[j] != NULL; j++) arg = sqllines[j]; if ( NULL != strchr(arg, '?') ) { total = strlen(arg); sql->query = xmalloc( (total+1) * sizeof(char)); strcpy (sql->query, arg); } else { sql->query = db_generate_insert_stmt(dca); } xprintf("%s\n", sql->query); } return sql; } int db_iodbc_read(TABDCA *dca, void *link) { struct db_odbc *sql; SQLRETURN ret; char buf[SQL_FDLEN_MAX+1]; int i; int len; double num; sql = (struct db_odbc *) link; xassert(sql != NULL); xassert(sql->mode == 'R'); ret=dl_SQLFetch(sql->hstmt); if (ret== SQL_ERROR) return -1; if (ret== SQL_NO_DATA_FOUND) return -1; /*EOF*/ for (i=1; i <= sql->nresultcols; i++) { if (sql->ref[i] > 0) { len = sql->outlen[i]; if (len != SQL_NULL_DATA) { if (len > SQL_FDLEN_MAX) len = SQL_FDLEN_MAX; else if (len < 0) len = 0; strncpy(buf, (const char *) sql->data[i], len); buf[len] = 0x00; if (0 != (sql->isnumeric[i])) { strspx(buf); /* remove spaces*/ if (str2num(buf, &num) != 0) { xprintf("'%s' cannot be converted to a number.\n", buf); return 1; } mpl_tab_set_num(dca, sql->ref[i], num); } else { mpl_tab_set_str(dca, sql->ref[i], strtrim(buf)); } } } } return 0; } int db_iodbc_write(TABDCA *dca, void *link) { struct db_odbc *sql; char *part; char *query; char *template; char num[50]; int k; int len; int nf; sql = (struct db_odbc *) link; xassert(sql != NULL); xassert(sql->mode == 'W'); len = strlen(sql->query); template = (char *) xmalloc( (len + 1) * sizeof(char) ); strcpy(template, sql->query); nf = mpl_tab_num_flds(dca); for (k = 1; k <= nf; k++) { switch (mpl_tab_get_type(dca, k)) { case 'N': len += 20; break; case 'S': len += db_escaped_string_length(mpl_tab_get_str(dca, k)); len += 2; break; default: xassert(dca != dca); } } query = xmalloc( (len + 1 ) * sizeof(char) ); query[0] = 0x00; for (k = 1, part = strtok (template, "?"); (part != NULL); part = strtok (NULL, "?"), k++) { if (k > nf) break; strcat( query, part ); switch (mpl_tab_get_type(dca, k)) { case 'N': #if 0 /* 02/XI-2010 by xypron */ sprintf(num, "%-18g",mpl_tab_get_num(dca, k)); #else sprintf(num, "%.*g", DBL_DIG, mpl_tab_get_num(dca, k)); #endif strcat( query, num ); break; case 'S': strcat( query, "'"); db_escape_string( query + strlen(query), mpl_tab_get_str(dca, k) ); strcat( query, "'"); break; default: xassert(dca != dca); } } if (part != NULL) strcat(query, part); if (dl_SQLExecDirect(sql->hstmt, (SQLCHAR *) query, SQL_NTS) != SQL_SUCCESS) { xprintf("db_iodbc_write: Query\n\"%s\"\nfailed.\n", query); extract_error("SQLExecDirect", sql->hdbc, SQL_HANDLE_DBC); xfree(query); xfree(template); return 1; } xfree(query); xfree(template); return 0; } int db_iodbc_close(TABDCA *dca, void *link) { struct db_odbc *sql; sql = (struct db_odbc *) link; xassert(sql != NULL); /* Commit */ if ( sql->mode == 'W' ) dl_SQLEndTran(SQL_HANDLE_ENV, sql->henv, SQL_COMMIT); if ( sql->mode == 'R' ) dl_SQLCloseCursor(sql->hstmt); dl_SQLFreeHandle(SQL_HANDLE_STMT, sql->hstmt); dl_SQLDisconnect(sql->hdbc); dl_SQLFreeHandle(SQL_HANDLE_DBC, sql->hdbc); dl_SQLFreeHandle(SQL_HANDLE_ENV, sql->henv); if ( sql->mode == 'W' ) xfree(sql->query); xfree(sql); dca->link = NULL; return 0; } static void extract_error( char *fn, SQLHANDLE handle, SQLSMALLINT type) { SQLINTEGER i = 0; SQLINTEGER native; SQLCHAR state[ 7 ]; SQLCHAR text[256]; SQLSMALLINT len; SQLRETURN ret; xprintf("\nThe driver reported the following diagnostics whilst " "running %s\n", fn); do { ret = dl_SQLGetDiagRec(type, handle, ++i, state, &native, text, sizeof(text), &len ); if (SQL_SUCCEEDED(ret)) xprintf("%s:%ld:%ld:%s\n", state, i, native, text); } while( ret == SQL_SUCCESS ); } static int is_numeric(SQLSMALLINT coltype) { int ret = 0; switch (coltype) { case SQL_DECIMAL: case SQL_NUMERIC: case SQL_SMALLINT: case SQL_INTEGER: case SQL_REAL: case SQL_FLOAT: case SQL_DOUBLE: case SQL_TINYINT: case SQL_BIGINT: ret = 1; break; } return ret; } #endif /**********************************************************************/ #ifndef HAVE_MYSQL void *db_mysql_open(TABDCA *dca, int mode) { xassert(dca == dca); xassert(mode == mode); xprintf("MySQL table driver not supported\n"); return NULL; } int db_mysql_read(TABDCA *dca, void *link) { xassert(dca != dca); xassert(link != link); return 0; } int db_mysql_write(TABDCA *dca, void *link) { xassert(dca != dca); xassert(link != link); return 0; } int db_mysql_close(TABDCA *dca, void *link) { xassert(dca != dca); xassert(link != link); return 0; } #else #if defined(__CYGWIN__) || defined(__MINGW32__) || defined(__WOE__) #include #endif #ifdef __CYGWIN__ #define byte_defined 1 #endif #include #include #include struct db_mysql { int mode; /*'R' = Read, 'W' = Write*/ MYSQL *con; /*connection*/ MYSQL_RES *res; /*result*/ int nf; /* number of fields in the csv file */ int ref[1+SQL_FIELD_MAX]; /* ref[k] = k', if k-th field of the csv file corresponds to k'-th field in the table statement; if ref[k] = 0, k-th field of the csv file is ignored */ char *query; /* query generated by db_mysql_open */ }; void STDCALL dl_mysql_close(MYSQL *sock) { typedef void STDCALL ep_mysql_close(MYSQL *sock); ep_mysql_close *fn; fn = (ep_mysql_close *) xdlsym(h_mysql, "mysql_close"); xassert(fn != NULL); return (*fn)(sock); } const char * STDCALL dl_mysql_error(MYSQL *mysql) { typedef const char * STDCALL ep_mysql_error(MYSQL *mysql); ep_mysql_error *fn; fn = (ep_mysql_error *) xdlsym(h_mysql, "mysql_error"); xassert(fn != NULL); return (*fn)(mysql); } MYSQL_FIELD * STDCALL dl_mysql_fetch_fields(MYSQL_RES *res) { typedef MYSQL_FIELD * STDCALL ep_mysql_fetch_fields(MYSQL_RES *res); ep_mysql_fetch_fields *fn; fn = (ep_mysql_fetch_fields *) xdlsym(h_mysql, "mysql_fetch_fields"); xassert(fn != NULL); return (*fn)(res); } unsigned long * STDCALL dl_mysql_fetch_lengths(MYSQL_RES *result) { typedef unsigned long * STDCALL ep_mysql_fetch_lengths(MYSQL_RES *result); ep_mysql_fetch_lengths *fn; fn = (ep_mysql_fetch_lengths *) xdlsym(h_mysql, "mysql_fetch_lengths"); xassert(fn != NULL); return (*fn)(result); } MYSQL_ROW STDCALL dl_mysql_fetch_row(MYSQL_RES *result) { typedef MYSQL_ROW STDCALL ep_mysql_fetch_row(MYSQL_RES *result); ep_mysql_fetch_row *fn; fn = (ep_mysql_fetch_row *) xdlsym(h_mysql, "mysql_fetch_row"); xassert(fn != NULL); return (*fn)(result); } unsigned int STDCALL dl_mysql_field_count(MYSQL *mysql) { typedef unsigned int STDCALL ep_mysql_field_count(MYSQL *mysql); ep_mysql_field_count *fn; fn = (ep_mysql_field_count *) xdlsym(h_mysql, "mysql_field_count"); xassert(fn != NULL); return (*fn)(mysql); } MYSQL * STDCALL dl_mysql_init(MYSQL *mysql) { typedef MYSQL * STDCALL ep_mysql_init(MYSQL *mysql); ep_mysql_init *fn; fn = (ep_mysql_init *) xdlsym(h_mysql, "mysql_init"); xassert(fn != NULL); return (*fn)(mysql); } unsigned int STDCALL dl_mysql_num_fields(MYSQL_RES *res) { typedef unsigned int STDCALL ep_mysql_num_fields(MYSQL_RES *res); ep_mysql_num_fields *fn; fn = (ep_mysql_num_fields *) xdlsym(h_mysql, "mysql_num_fields"); xassert(fn != NULL); return (*fn)(res); } int STDCALL dl_mysql_query(MYSQL *mysql, const char *q) { typedef int STDCALL ep_mysql_query(MYSQL *mysql, const char *q); ep_mysql_query *fn; fn = (ep_mysql_query *) xdlsym(h_mysql, "mysql_query"); xassert(fn != NULL); return (*fn)(mysql, q); } MYSQL * STDCALL dl_mysql_real_connect(MYSQL *mysql, const char *host, const char *user, const char *passwd, const char *db, unsigned int port, const char *unix_socket, unsigned long clientflag) { typedef MYSQL * STDCALL ep_mysql_real_connect(MYSQL *mysql, const char *host, const char *user, const char *passwd, const char *db, unsigned int port, const char *unix_socket, unsigned long clientflag); ep_mysql_real_connect *fn; fn = (ep_mysql_real_connect *) xdlsym(h_mysql, "mysql_real_connect"); xassert(fn != NULL); return (*fn)(mysql, host, user, passwd, db, port, unix_socket, clientflag); } MYSQL_RES * STDCALL dl_mysql_use_result(MYSQL *mysql) { typedef MYSQL_RES * STDCALL ep_mysql_use_result(MYSQL *mysql); ep_mysql_use_result *fn; fn = (ep_mysql_use_result *) xdlsym(h_mysql, "mysql_use_result"); xassert(fn != NULL); return (*fn)(mysql); } /*********************************************************************** * NAME * * db_mysql_open - open connection to ODBC data base * * SYNOPSIS * * #include "glpsql.h" * void *db_mysql_open(TABDCA *dca, int mode); * * DESCRIPTION * * The routine db_mysql_open opens a connection to a MySQL data base. * It then executes the sql statements passed. * * In the case of table read the SELECT statement is executed. * * In the case of table write the INSERT statement is prepared. * RETURNS * * The routine returns a pointer to data storage area created. */ void *db_mysql_open(TABDCA *dca, int mode) { void *ret; char **sqllines; sqllines = args_concat(dca); if (sqllines == NULL) { xprintf("Missing arguments in table statement.\n" "Please, supply table driver, dsn, and query.\n"); return NULL; } ret = db_mysql_open_int(dca, mode, (const char **) sqllines); free_buffer(sqllines); return ret; } static void *db_mysql_open_int(TABDCA *dca, int mode, const char **sqllines) { struct db_mysql *sql = NULL; char *arg = NULL; const char *field; MYSQL_FIELD *fields; char *keyword; char *value; char *query; char *dsn; /* "Server=[server_name];Database=[database_name];UID=[username];*/ /* PWD=[password];Port=[port]"*/ char *server = NULL; /* Server */ char *user = NULL; /* UID */ char *password = NULL; /* PWD */ char *database = NULL; /* Database */ unsigned int port = 0; /* Port */ int narg; int i, j, total; if (libmysql == NULL) { xprintf("No loader for shared MySQL library available\n"); return NULL; } if (h_mysql == NULL) { h_mysql = xdlopen(libmysql); if (h_mysql == NULL) { xprintf("unable to open library %s\n", libmysql); xprintf("%s\n", xerrmsg()); return NULL; } } sql = (struct db_mysql *) xmalloc(sizeof(struct db_mysql)); if (sql == NULL) return NULL; sql->mode = mode; sql->res = NULL; sql->query = NULL; sql->nf = mpl_tab_num_flds(dca); narg = mpl_tab_num_args(dca); if (narg < 3 ) xprintf("MySQL driver: string list too short \n"); /* get connection string*/ dsn = (char *) mpl_tab_get_arg(dca, 2); /* copy connection string*/ i = strlen(dsn); i++; arg = xmalloc(i * sizeof(char)); strcpy(arg, dsn); /*tokenize connection string*/ for (i = 1, keyword = strtok (arg, "="); (keyword != NULL); keyword = strtok (NULL, "="), i++) { value = strtok (NULL, ";"); if (value==NULL) { xprintf("db_mysql_open: Missing value for keyword %s\n", keyword); xfree(arg); xfree(sql); return NULL; } if (0 == strcmp(keyword, "Server")) server = value; else if (0 == strcmp(keyword, "Database")) database = value; else if (0 == strcmp(keyword, "UID")) user = value; else if (0 == strcmp(keyword, "PWD")) password = value; else if (0 == strcmp(keyword, "Port")) port = (unsigned int) atol(value); } /* Connect to database */ sql->con = dl_mysql_init(NULL); if (!dl_mysql_real_connect(sql->con, server, user, password, database, port, NULL, 0)) { xprintf("db_mysql_open: Connect failed\n"); xprintf("%s\n", dl_mysql_error(sql->con)); xfree(arg); xfree(sql); return NULL; } xfree(arg); for(j = 0; sqllines[j+1] != NULL; j++) { query = (char *) sqllines[j]; xprintf("%s\n", query); if (dl_mysql_query(sql->con, query)) { xprintf("db_mysql_open: Query\n\"%s\"\nfailed.\n", query); xprintf("%s\n",dl_mysql_error(sql->con)); dl_mysql_close(sql->con); xfree(sql); return NULL; } } if ( sql->mode == 'R' ) { sql->nf = mpl_tab_num_flds(dca); for(j = 0; sqllines[j] != NULL; j++) arg = (char *) sqllines[j]; total = strlen(arg); if (total > 7 && 0 == strncmp(arg, "SELECT ", 7)) { total = strlen(arg); query = xmalloc( (total+1) * sizeof(char)); strcpy (query, arg); } else { query = db_generate_select_stmt(dca); } xprintf("%s\n", query); if (dl_mysql_query(sql->con, query)) { xprintf("db_mysql_open: Query\n\"%s\"\nfailed.\n", query); xprintf("%s\n",dl_mysql_error(sql->con)); dl_mysql_close(sql->con); xfree(query); xfree(sql); return NULL; } xfree(query); sql->res = dl_mysql_use_result(sql->con); if (sql->res) { /* create references between query results and table fields*/ total = dl_mysql_num_fields(sql->res); if (total > SQL_FIELD_MAX) { xprintf("db_mysql_open: Too many fields (> %d) in query.\n" "\"%s\"\n", SQL_FIELD_MAX, query); xprintf("%s\n",dl_mysql_error(sql->con)); dl_mysql_close(sql->con); xfree(query); xfree(sql); return NULL; } fields = dl_mysql_fetch_fields(sql->res); for (i = 1; i <= total; i++) { for (j = sql->nf; j >= 1; j--) { if (strcmp(mpl_tab_get_name(dca, j), fields[i-1].name) == 0) break; } sql->ref[i] = j; } } else { if(dl_mysql_field_count(sql->con) == 0) { xprintf("db_mysql_open: Query was not a SELECT\n\"%s\"\n", query); xprintf("%s\n",dl_mysql_error(sql->con)); xfree(query); xfree(sql); return NULL; } else { xprintf("db_mysql_open: Query\n\"%s\"\nfailed.\n", query); xprintf("%s\n",dl_mysql_error(sql->con)); xfree(query); xfree(sql); return NULL; } } } else if ( sql->mode == 'W' ) { for(j = 0; sqllines[j] != NULL; j++) arg = (char *) sqllines[j]; if ( NULL != strchr(arg, '?') ) { total = strlen(arg); query = xmalloc( (total+1) * sizeof(char)); strcpy (query, arg); } else query = db_generate_insert_stmt(dca); sql->query = query; xprintf("%s\n", query); } return sql; } int db_mysql_read(TABDCA *dca, void *link) { struct db_mysql *sql; char buf[255+1]; char **row; unsigned long *lengths; MYSQL_FIELD *fields; double num; int len; unsigned long num_fields; int i; sql = (struct db_mysql *) link; xassert(sql != NULL); xassert(sql->mode == 'R'); if (NULL == sql->res) { xprintf("db_mysql_read: no result set available"); return 1; } if (NULL==(row = (char **)dl_mysql_fetch_row(sql->res))) { return -1; /*EOF*/ } lengths = dl_mysql_fetch_lengths(sql->res); fields = dl_mysql_fetch_fields(sql->res); num_fields = dl_mysql_num_fields(sql->res); for (i=1; i <= num_fields; i++) { if (row[i-1] != NULL) { len = (size_t) lengths[i-1]; if (len > 255) len = 255; strncpy(buf, (const char *) row[i-1], len); buf[len] = 0x00; if (0 != (fields[i-1].flags & NUM_FLAG)) { strspx(buf); /* remove spaces*/ if (str2num(buf, &num) != 0) { xprintf("'%s' cannot be converted to a number.\n", buf); return 1; } if (sql->ref[i] > 0) mpl_tab_set_num(dca, sql->ref[i], num); } else { if (sql->ref[i] > 0) mpl_tab_set_str(dca, sql->ref[i], strtrim(buf)); } } } return 0; } int db_mysql_write(TABDCA *dca, void *link) { struct db_mysql *sql; char *part; char *query; char *template; char num[50]; int k; int len; int nf; sql = (struct db_mysql *) link; xassert(sql != NULL); xassert(sql->mode == 'W'); len = strlen(sql->query); template = (char *) xmalloc( (len + 1) * sizeof(char) ); strcpy(template, sql->query); nf = mpl_tab_num_flds(dca); for (k = 1; k <= nf; k++) { switch (mpl_tab_get_type(dca, k)) { case 'N': len += 20; break; case 'S': len += db_escaped_string_length(mpl_tab_get_str(dca, k)); len += 2; break; default: xassert(dca != dca); } } query = xmalloc( (len + 1 ) * sizeof(char) ); query[0] = 0x00; for (k = 1, part = strtok (template, "?"); (part != NULL); part = strtok (NULL, "?"), k++) { if (k > nf) break; strcat( query, part ); switch (mpl_tab_get_type(dca, k)) { case 'N': #if 0 /* 02/XI-2010 by xypron */ sprintf(num, "%-18g",mpl_tab_get_num(dca, k)); #else sprintf(num, "%.*g", DBL_DIG, mpl_tab_get_num(dca, k)); #endif strcat( query, num ); break; case 'S': strcat( query, "'"); db_escape_string( query + strlen(query), mpl_tab_get_str(dca, k) ); strcat( query, "'"); break; default: xassert(dca != dca); } } if (part != NULL) strcat(query, part); if (dl_mysql_query(sql->con, query)) { xprintf("db_mysql_write: Query\n\"%s\"\nfailed.\n", query); xprintf("%s\n",dl_mysql_error(sql->con)); xfree(query); xfree(template); return 1; } xfree(query); xfree(template); return 0; } int db_mysql_close(TABDCA *dca, void *link) { struct db_mysql *sql; sql = (struct db_mysql *) link; xassert(sql != NULL); dl_mysql_close(sql->con); if ( sql->mode == 'W' ) xfree(sql->query); xfree(sql); dca->link = NULL; return 0; } #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpapi05.c0000644000076500000240000001325613524616144025173 0ustar tamasstaff00000000000000/* glpapi05.c (LP basis constructing routines) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wlogical-op-parentheses" #endif #include "glpapi.h" /*********************************************************************** * NAME * * glp_set_row_stat - set (change) row status * * SYNOPSIS * * void glp_set_row_stat(glp_prob *lp, int i, int stat); * * DESCRIPTION * * The routine glp_set_row_stat sets (changes) status of the auxiliary * variable associated with i-th row. * * The new status of the auxiliary variable should be specified by the * parameter stat as follows: * * GLP_BS - basic variable; * GLP_NL - non-basic variable; * GLP_NU - non-basic variable on its upper bound; if the variable is * not double-bounded, this means the same as GLP_NL (only in * case of this routine); * GLP_NF - the same as GLP_NL (only in case of this routine); * GLP_NS - the same as GLP_NL (only in case of this routine). */ void glp_set_row_stat(glp_prob *lp, int i, int stat) { GLPROW *row; if (!(1 <= i && i <= lp->m)) xerror("glp_set_row_stat: i = %d; row number out of range\n", i); if (!(stat == GLP_BS || stat == GLP_NL || stat == GLP_NU || stat == GLP_NF || stat == GLP_NS)) xerror("glp_set_row_stat: i = %d; stat = %d; invalid status\n", i, stat); row = lp->row[i]; if (stat != GLP_BS) { switch (row->type) { case GLP_FR: stat = GLP_NF; break; case GLP_LO: stat = GLP_NL; break; case GLP_UP: stat = GLP_NU; break; case GLP_DB: if (stat != GLP_NU) stat = GLP_NL; break; case GLP_FX: stat = GLP_NS; break; default: xassert(row != row); } } if (row->stat == GLP_BS && stat != GLP_BS || row->stat != GLP_BS && stat == GLP_BS) { /* invalidate the basis factorization */ lp->valid = 0; } row->stat = stat; return; } /*********************************************************************** * NAME * * glp_set_col_stat - set (change) column status * * SYNOPSIS * * void glp_set_col_stat(glp_prob *lp, int j, int stat); * * DESCRIPTION * * The routine glp_set_col_stat sets (changes) status of the structural * variable associated with j-th column. * * The new status of the structural variable should be specified by the * parameter stat as follows: * * GLP_BS - basic variable; * GLP_NL - non-basic variable; * GLP_NU - non-basic variable on its upper bound; if the variable is * not double-bounded, this means the same as GLP_NL (only in * case of this routine); * GLP_NF - the same as GLP_NL (only in case of this routine); * GLP_NS - the same as GLP_NL (only in case of this routine). */ void glp_set_col_stat(glp_prob *lp, int j, int stat) { GLPCOL *col; if (!(1 <= j && j <= lp->n)) xerror("glp_set_col_stat: j = %d; column number out of range\n" , j); if (!(stat == GLP_BS || stat == GLP_NL || stat == GLP_NU || stat == GLP_NF || stat == GLP_NS)) xerror("glp_set_col_stat: j = %d; stat = %d; invalid status\n", j, stat); col = lp->col[j]; if (stat != GLP_BS) { switch (col->type) { case GLP_FR: stat = GLP_NF; break; case GLP_LO: stat = GLP_NL; break; case GLP_UP: stat = GLP_NU; break; case GLP_DB: if (stat != GLP_NU) stat = GLP_NL; break; case GLP_FX: stat = GLP_NS; break; default: xassert(col != col); } } if (col->stat == GLP_BS && stat != GLP_BS || col->stat != GLP_BS && stat == GLP_BS) { /* invalidate the basis factorization */ lp->valid = 0; } col->stat = stat; return; } /*********************************************************************** * NAME * * glp_std_basis - construct standard initial LP basis * * SYNOPSIS * * void glp_std_basis(glp_prob *lp); * * DESCRIPTION * * The routine glp_std_basis builds the "standard" (trivial) initial * basis for the specified problem object. * * In the "standard" basis all auxiliary variables are basic, and all * structural variables are non-basic. */ void glp_std_basis(glp_prob *lp) { int i, j; /* make all auxiliary variables basic */ for (i = 1; i <= lp->m; i++) glp_set_row_stat(lp, i, GLP_BS); /* make all structural variables non-basic */ for (j = 1; j <= lp->n; j++) { GLPCOL *col = lp->col[j]; if (col->type == GLP_DB && fabs(col->lb) > fabs(col->ub)) glp_set_col_stat(lp, j, GLP_NU); else glp_set_col_stat(lp, j, GLP_NL); } return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpapi01.c0000644000076500000240000014745113524616144025174 0ustar tamasstaff00000000000000/* glpapi01.c (problem creating and modifying routines) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wshorten-64-to-32" #pragma clang diagnostic ignored "-Wsign-conversion" #endif #include "glpios.h" /* CAUTION: DO NOT CHANGE THE LIMITS BELOW */ #define M_MAX 100000000 /* = 100*10^6 */ /* maximal number of rows in the problem object */ #define N_MAX 100000000 /* = 100*10^6 */ /* maximal number of columns in the problem object */ #define NNZ_MAX 500000000 /* = 500*10^6 */ /* maximal number of constraint coefficients in the problem object */ /*********************************************************************** * NAME * * glp_create_prob - create problem object * * SYNOPSIS * * glp_prob *glp_create_prob(void); * * DESCRIPTION * * The routine glp_create_prob creates a new problem object, which is * initially "empty", i.e. has no rows and columns. * * RETURNS * * The routine returns a pointer to the object created, which should be * used in any subsequent operations on this object. */ static void create_prob(glp_prob *lp) { lp->magic = GLP_PROB_MAGIC; lp->pool = dmp_create_pool(); #if 0 /* 17/XI-2009 */ lp->cps = xmalloc(sizeof(struct LPXCPS)); lpx_reset_parms(lp); #else lp->parms = NULL; #endif lp->tree = NULL; #if 0 lp->lwa = 0; lp->cwa = NULL; #endif /* LP/MIP data */ lp->name = NULL; lp->obj = NULL; lp->dir = GLP_MIN; lp->c0 = 0.0; lp->m_max = 100; lp->n_max = 200; lp->m = lp->n = 0; lp->nnz = 0; lp->row = xcalloc(1+lp->m_max, sizeof(GLPROW *)); lp->col = xcalloc(1+lp->n_max, sizeof(GLPCOL *)); lp->r_tree = lp->c_tree = NULL; /* basis factorization */ lp->valid = 0; lp->head = xcalloc(1+lp->m_max, sizeof(int)); lp->bfcp = NULL; lp->bfd = NULL; /* basic solution (LP) */ lp->pbs_stat = lp->dbs_stat = GLP_UNDEF; lp->obj_val = 0.0; lp->it_cnt = 0; lp->some = 0; /* interior-point solution (LP) */ lp->ipt_stat = GLP_UNDEF; lp->ipt_obj = 0.0; /* integer solution (MIP) */ lp->mip_stat = GLP_UNDEF; lp->mip_obj = 0.0; return; } glp_prob *glp_create_prob(void) { glp_prob *lp; lp = xmalloc(sizeof(glp_prob)); create_prob(lp); return lp; } /*********************************************************************** * NAME * * glp_set_prob_name - assign (change) problem name * * SYNOPSIS * * void glp_set_prob_name(glp_prob *lp, const char *name); * * DESCRIPTION * * The routine glp_set_prob_name assigns a given symbolic name (1 up to * 255 characters) to the specified problem object. * * If the parameter name is NULL or empty string, the routine erases an * existing symbolic name of the problem object. */ void glp_set_prob_name(glp_prob *lp, const char *name) { glp_tree *tree = lp->tree; if (tree != NULL && tree->reason != 0) xerror("glp_set_prob_name: operation not allowed\n"); if (lp->name != NULL) { dmp_free_atom(lp->pool, lp->name, strlen(lp->name)+1); lp->name = NULL; } if (!(name == NULL || name[0] == '\0')) { int k; for (k = 0; name[k] != '\0'; k++) { if (k == 256) xerror("glp_set_prob_name: problem name too long\n"); if (iscntrl((unsigned char)name[k])) xerror("glp_set_prob_name: problem name contains invalid" " character(s)\n"); } lp->name = dmp_get_atom(lp->pool, strlen(name)+1); strcpy(lp->name, name); } return; } /*********************************************************************** * NAME * * glp_set_obj_name - assign (change) objective function name * * SYNOPSIS * * void glp_set_obj_name(glp_prob *lp, const char *name); * * DESCRIPTION * * The routine glp_set_obj_name assigns a given symbolic name (1 up to * 255 characters) to the objective function of the specified problem * object. * * If the parameter name is NULL or empty string, the routine erases an * existing name of the objective function. */ void glp_set_obj_name(glp_prob *lp, const char *name) { glp_tree *tree = lp->tree; if (tree != NULL && tree->reason != 0) xerror("glp_set_obj_name: operation not allowed\n"); if (lp->obj != NULL) { dmp_free_atom(lp->pool, lp->obj, strlen(lp->obj)+1); lp->obj = NULL; } if (!(name == NULL || name[0] == '\0')) { int k; for (k = 0; name[k] != '\0'; k++) { if (k == 256) xerror("glp_set_obj_name: objective name too long\n"); if (iscntrl((unsigned char)name[k])) xerror("glp_set_obj_name: objective name contains invali" "d character(s)\n"); } lp->obj = dmp_get_atom(lp->pool, strlen(name)+1); strcpy(lp->obj, name); } return; } /*********************************************************************** * NAME * * glp_set_obj_dir - set (change) optimization direction flag * * SYNOPSIS * * void glp_set_obj_dir(glp_prob *lp, int dir); * * DESCRIPTION * * The routine glp_set_obj_dir sets (changes) optimization direction * flag (i.e. "sense" of the objective function) as specified by the * parameter dir: * * GLP_MIN - minimization; * GLP_MAX - maximization. */ void glp_set_obj_dir(glp_prob *lp, int dir) { glp_tree *tree = lp->tree; if (tree != NULL && tree->reason != 0) xerror("glp_set_obj_dir: operation not allowed\n"); if (!(dir == GLP_MIN || dir == GLP_MAX)) xerror("glp_set_obj_dir: dir = %d; invalid direction flag\n", dir); lp->dir = dir; return; } /*********************************************************************** * NAME * * glp_add_rows - add new rows to problem object * * SYNOPSIS * * int glp_add_rows(glp_prob *lp, int nrs); * * DESCRIPTION * * The routine glp_add_rows adds nrs rows (constraints) to the specified * problem object. New rows are always added to the end of the row list, * so the ordinal numbers of existing rows remain unchanged. * * Being added each new row is initially free (unbounded) and has empty * list of the constraint coefficients. * * RETURNS * * The routine glp_add_rows returns the ordinal number of the first new * row added to the problem object. */ int glp_add_rows(glp_prob *lp, int nrs) { glp_tree *tree = lp->tree; GLPROW *row; int m_new, i; /* determine new number of rows */ if (nrs < 1) xerror("glp_add_rows: nrs = %d; invalid number of rows\n", nrs); if (nrs > M_MAX - lp->m) xerror("glp_add_rows: nrs = %d; too many rows\n", nrs); m_new = lp->m + nrs; /* increase the room, if necessary */ if (lp->m_max < m_new) { GLPROW **save = lp->row; while (lp->m_max < m_new) { lp->m_max += lp->m_max; xassert(lp->m_max > 0); } lp->row = xcalloc(1+lp->m_max, sizeof(GLPROW *)); memcpy(&lp->row[1], &save[1], lp->m * sizeof(GLPROW *)); xfree(save); /* do not forget about the basis header */ xfree(lp->head); lp->head = xcalloc(1+lp->m_max, sizeof(int)); } /* add new rows to the end of the row list */ for (i = lp->m+1; i <= m_new; i++) { /* create row descriptor */ lp->row[i] = row = dmp_get_atom(lp->pool, sizeof(GLPROW)); row->i = i; row->name = NULL; row->node = NULL; #if 1 /* 20/IX-2008 */ row->level = 0; row->origin = 0; row->klass = 0; if (tree != NULL) { switch (tree->reason) { case 0: break; case GLP_IROWGEN: xassert(tree->curr != NULL); row->level = tree->curr->level; row->origin = GLP_RF_LAZY; break; case GLP_ICUTGEN: xassert(tree->curr != NULL); row->level = tree->curr->level; row->origin = GLP_RF_CUT; break; default: xassert(tree != tree); } } #endif row->type = GLP_FR; row->lb = row->ub = 0.0; row->ptr = NULL; row->rii = 1.0; row->stat = GLP_BS; #if 0 row->bind = -1; #else row->bind = 0; #endif row->prim = row->dual = 0.0; row->pval = row->dval = 0.0; row->mipx = 0.0; } /* set new number of rows */ lp->m = m_new; /* invalidate the basis factorization */ lp->valid = 0; #if 1 if (tree != NULL && tree->reason != 0) tree->reopt = 1; #endif /* return the ordinal number of the first row added */ return m_new - nrs + 1; } /*********************************************************************** * NAME * * glp_add_cols - add new columns to problem object * * SYNOPSIS * * int glp_add_cols(glp_prob *lp, int ncs); * * DESCRIPTION * * The routine glp_add_cols adds ncs columns (structural variables) to * the specified problem object. New columns are always added to the end * of the column list, so the ordinal numbers of existing columns remain * unchanged. * * Being added each new column is initially fixed at zero and has empty * list of the constraint coefficients. * * RETURNS * * The routine glp_add_cols returns the ordinal number of the first new * column added to the problem object. */ int glp_add_cols(glp_prob *lp, int ncs) { glp_tree *tree = lp->tree; GLPCOL *col; int n_new, j; if (tree != NULL && tree->reason != 0) xerror("glp_add_cols: operation not allowed\n"); /* determine new number of columns */ if (ncs < 1) xerror("glp_add_cols: ncs = %d; invalid number of columns\n", ncs); if (ncs > N_MAX - lp->n) xerror("glp_add_cols: ncs = %d; too many columns\n", ncs); n_new = lp->n + ncs; /* increase the room, if necessary */ if (lp->n_max < n_new) { GLPCOL **save = lp->col; while (lp->n_max < n_new) { lp->n_max += lp->n_max; xassert(lp->n_max > 0); } lp->col = xcalloc(1+lp->n_max, sizeof(GLPCOL *)); memcpy(&lp->col[1], &save[1], lp->n * sizeof(GLPCOL *)); xfree(save); } /* add new columns to the end of the column list */ for (j = lp->n+1; j <= n_new; j++) { /* create column descriptor */ lp->col[j] = col = dmp_get_atom(lp->pool, sizeof(GLPCOL)); col->j = j; col->name = NULL; col->node = NULL; col->kind = GLP_CV; col->type = GLP_FX; col->lb = col->ub = 0.0; col->coef = 0.0; col->ptr = NULL; col->sjj = 1.0; col->stat = GLP_NS; #if 0 col->bind = -1; #else col->bind = 0; /* the basis may remain valid */ #endif col->prim = col->dual = 0.0; col->pval = col->dval = 0.0; col->mipx = 0.0; } /* set new number of columns */ lp->n = n_new; /* return the ordinal number of the first column added */ return n_new - ncs + 1; } /*********************************************************************** * NAME * * glp_set_row_name - assign (change) row name * * SYNOPSIS * * void glp_set_row_name(glp_prob *lp, int i, const char *name); * * DESCRIPTION * * The routine glp_set_row_name assigns a given symbolic name (1 up to * 255 characters) to i-th row (auxiliary variable) of the specified * problem object. * * If the parameter name is NULL or empty string, the routine erases an * existing name of i-th row. */ void glp_set_row_name(glp_prob *lp, int i, const char *name) { glp_tree *tree = lp->tree; GLPROW *row; if (!(1 <= i && i <= lp->m)) xerror("glp_set_row_name: i = %d; row number out of range\n", i); row = lp->row[i]; if (tree != NULL && tree->reason != 0) { xassert(tree->curr != NULL); xassert(row->level == tree->curr->level); } if (row->name != NULL) { if (row->node != NULL) { xassert(lp->r_tree != NULL); avl_delete_node(lp->r_tree, row->node); row->node = NULL; } dmp_free_atom(lp->pool, row->name, strlen(row->name)+1); row->name = NULL; } if (!(name == NULL || name[0] == '\0')) { int k; for (k = 0; name[k] != '\0'; k++) { if (k == 256) xerror("glp_set_row_name: i = %d; row name too long\n", i); if (iscntrl((unsigned char)name[k])) xerror("glp_set_row_name: i = %d: row name contains inva" "lid character(s)\n", i); } row->name = dmp_get_atom(lp->pool, strlen(name)+1); strcpy(row->name, name); if (lp->r_tree != NULL) { xassert(row->node == NULL); row->node = avl_insert_node(lp->r_tree, row->name); avl_set_node_link(row->node, row); } } return; } /*********************************************************************** * NAME * * glp_set_col_name - assign (change) column name * * SYNOPSIS * * void glp_set_col_name(glp_prob *lp, int j, const char *name); * * DESCRIPTION * * The routine glp_set_col_name assigns a given symbolic name (1 up to * 255 characters) to j-th column (structural variable) of the specified * problem object. * * If the parameter name is NULL or empty string, the routine erases an * existing name of j-th column. */ void glp_set_col_name(glp_prob *lp, int j, const char *name) { glp_tree *tree = lp->tree; GLPCOL *col; if (tree != NULL && tree->reason != 0) xerror("glp_set_col_name: operation not allowed\n"); if (!(1 <= j && j <= lp->n)) xerror("glp_set_col_name: j = %d; column number out of range\n" , j); col = lp->col[j]; if (col->name != NULL) { if (col->node != NULL) { xassert(lp->c_tree != NULL); avl_delete_node(lp->c_tree, col->node); col->node = NULL; } dmp_free_atom(lp->pool, col->name, strlen(col->name)+1); col->name = NULL; } if (!(name == NULL || name[0] == '\0')) { int k; for (k = 0; name[k] != '\0'; k++) { if (k == 256) xerror("glp_set_col_name: j = %d; column name too long\n" , j); if (iscntrl((unsigned char)name[k])) xerror("glp_set_col_name: j = %d: column name contains i" "nvalid character(s)\n", j); } col->name = dmp_get_atom(lp->pool, strlen(name)+1); strcpy(col->name, name); if (lp->c_tree != NULL && col->name != NULL) { xassert(col->node == NULL); col->node = avl_insert_node(lp->c_tree, col->name); avl_set_node_link(col->node, col); } } return; } /*********************************************************************** * NAME * * glp_set_row_bnds - set (change) row bounds * * SYNOPSIS * * void glp_set_row_bnds(glp_prob *lp, int i, int type, double lb, * double ub); * * DESCRIPTION * * The routine glp_set_row_bnds sets (changes) the type and bounds of * i-th row (auxiliary variable) of the specified problem object. * * Parameters type, lb, and ub specify the type, lower bound, and upper * bound, respectively, as follows: * * Type Bounds Comments * ------------------------------------------------------ * GLP_FR -inf < x < +inf Free variable * GLP_LO lb <= x < +inf Variable with lower bound * GLP_UP -inf < x <= ub Variable with upper bound * GLP_DB lb <= x <= ub Double-bounded variable * GLP_FX x = lb Fixed variable * * where x is the auxiliary variable associated with i-th row. * * If the row has no lower bound, the parameter lb is ignored. If the * row has no upper bound, the parameter ub is ignored. If the row is * an equality constraint (i.e. the corresponding auxiliary variable is * of fixed type), only the parameter lb is used while the parameter ub * is ignored. */ void glp_set_row_bnds(glp_prob *lp, int i, int type, double lb, double ub) { GLPROW *row; if (!(1 <= i && i <= lp->m)) xerror("glp_set_row_bnds: i = %d; row number out of range\n", i); row = lp->row[i]; row->type = type; switch (type) { case GLP_FR: row->lb = row->ub = 0.0; if (row->stat != GLP_BS) row->stat = GLP_NF; break; case GLP_LO: row->lb = lb, row->ub = 0.0; if (row->stat != GLP_BS) row->stat = GLP_NL; break; case GLP_UP: row->lb = 0.0, row->ub = ub; if (row->stat != GLP_BS) row->stat = GLP_NU; break; case GLP_DB: row->lb = lb, row->ub = ub; if (!(row->stat == GLP_BS || row->stat == GLP_NL || row->stat == GLP_NU)) row->stat = (fabs(lb) <= fabs(ub) ? GLP_NL : GLP_NU); break; case GLP_FX: row->lb = row->ub = lb; if (row->stat != GLP_BS) row->stat = GLP_NS; break; default: xerror("glp_set_row_bnds: i = %d; type = %d; invalid row ty" "pe\n", i, type); } return; } /*********************************************************************** * NAME * * glp_set_col_bnds - set (change) column bounds * * SYNOPSIS * * void glp_set_col_bnds(glp_prob *lp, int j, int type, double lb, * double ub); * * DESCRIPTION * * The routine glp_set_col_bnds sets (changes) the type and bounds of * j-th column (structural variable) of the specified problem object. * * Parameters type, lb, and ub specify the type, lower bound, and upper * bound, respectively, as follows: * * Type Bounds Comments * ------------------------------------------------------ * GLP_FR -inf < x < +inf Free variable * GLP_LO lb <= x < +inf Variable with lower bound * GLP_UP -inf < x <= ub Variable with upper bound * GLP_DB lb <= x <= ub Double-bounded variable * GLP_FX x = lb Fixed variable * * where x is the structural variable associated with j-th column. * * If the column has no lower bound, the parameter lb is ignored. If the * column has no upper bound, the parameter ub is ignored. If the column * is of fixed type, only the parameter lb is used while the parameter * ub is ignored. */ void glp_set_col_bnds(glp_prob *lp, int j, int type, double lb, double ub) { GLPCOL *col; if (!(1 <= j && j <= lp->n)) xerror("glp_set_col_bnds: j = %d; column number out of range\n" , j); col = lp->col[j]; col->type = type; switch (type) { case GLP_FR: col->lb = col->ub = 0.0; if (col->stat != GLP_BS) col->stat = GLP_NF; break; case GLP_LO: col->lb = lb, col->ub = 0.0; if (col->stat != GLP_BS) col->stat = GLP_NL; break; case GLP_UP: col->lb = 0.0, col->ub = ub; if (col->stat != GLP_BS) col->stat = GLP_NU; break; case GLP_DB: col->lb = lb, col->ub = ub; if (!(col->stat == GLP_BS || col->stat == GLP_NL || col->stat == GLP_NU)) col->stat = (fabs(lb) <= fabs(ub) ? GLP_NL : GLP_NU); break; case GLP_FX: col->lb = col->ub = lb; if (col->stat != GLP_BS) col->stat = GLP_NS; break; default: xerror("glp_set_col_bnds: j = %d; type = %d; invalid column" " type\n", j, type); } return; } /*********************************************************************** * NAME * * glp_set_obj_coef - set (change) obj. coefficient or constant term * * SYNOPSIS * * void glp_set_obj_coef(glp_prob *lp, int j, double coef); * * DESCRIPTION * * The routine glp_set_obj_coef sets (changes) objective coefficient at * j-th column (structural variable) of the specified problem object. * * If the parameter j is 0, the routine sets (changes) the constant term * ("shift") of the objective function. */ void glp_set_obj_coef(glp_prob *lp, int j, double coef) { glp_tree *tree = lp->tree; if (tree != NULL && tree->reason != 0) xerror("glp_set_obj_coef: operation not allowed\n"); if (!(0 <= j && j <= lp->n)) xerror("glp_set_obj_coef: j = %d; column number out of range\n" , j); if (j == 0) lp->c0 = coef; else lp->col[j]->coef = coef; return; } /*********************************************************************** * NAME * * glp_set_mat_row - set (replace) row of the constraint matrix * * SYNOPSIS * * void glp_set_mat_row(glp_prob *lp, int i, int len, const int ind[], * const double val[]); * * DESCRIPTION * * The routine glp_set_mat_row stores (replaces) the contents of i-th * row of the constraint matrix of the specified problem object. * * Column indices and numeric values of new row elements must be placed * in locations ind[1], ..., ind[len] and val[1], ..., val[len], where * 0 <= len <= n is the new length of i-th row, n is the current number * of columns in the problem object. Elements with identical column * indices are not allowed. Zero elements are allowed, but they are not * stored in the constraint matrix. * * If the parameter len is zero, the parameters ind and/or val can be * specified as NULL. */ void glp_set_mat_row(glp_prob *lp, int i, int len, const int ind[], const double val[]) { glp_tree *tree = lp->tree; GLPROW *row; GLPCOL *col; GLPAIJ *aij, *next; int j, k; /* obtain pointer to i-th row */ if (!(1 <= i && i <= lp->m)) xerror("glp_set_mat_row: i = %d; row number out of range\n", i); row = lp->row[i]; if (tree != NULL && tree->reason != 0) { xassert(tree->curr != NULL); xassert(row->level == tree->curr->level); } /* remove all existing elements from i-th row */ while (row->ptr != NULL) { /* take next element in the row */ aij = row->ptr; /* remove the element from the row list */ row->ptr = aij->r_next; /* obtain pointer to corresponding column */ col = aij->col; /* remove the element from the column list */ if (aij->c_prev == NULL) col->ptr = aij->c_next; else aij->c_prev->c_next = aij->c_next; if (aij->c_next == NULL) ; else aij->c_next->c_prev = aij->c_prev; /* return the element to the memory pool */ dmp_free_atom(lp->pool, aij, sizeof(GLPAIJ)), lp->nnz--; /* if the corresponding column is basic, invalidate the basis factorization */ if (col->stat == GLP_BS) lp->valid = 0; } /* store new contents of i-th row */ if (!(0 <= len && len <= lp->n)) xerror("glp_set_mat_row: i = %d; len = %d; invalid row length " "\n", i, len); if (len > NNZ_MAX - lp->nnz) xerror("glp_set_mat_row: i = %d; len = %d; too many constraint" " coefficients\n", i, len); for (k = 1; k <= len; k++) { /* take number j of corresponding column */ j = ind[k]; /* obtain pointer to j-th column */ if (!(1 <= j && j <= lp->n)) xerror("glp_set_mat_row: i = %d; ind[%d] = %d; column index" " out of range\n", i, k, j); col = lp->col[j]; /* if there is element with the same column index, it can only be found in the beginning of j-th column list */ if (col->ptr != NULL && col->ptr->row->i == i) xerror("glp_set_mat_row: i = %d; ind[%d] = %d; duplicate co" "lumn indices not allowed\n", i, k, j); /* create new element */ aij = dmp_get_atom(lp->pool, sizeof(GLPAIJ)), lp->nnz++; aij->row = row; aij->col = col; aij->val = val[k]; /* add the new element to the beginning of i-th row and j-th column lists */ aij->r_prev = NULL; aij->r_next = row->ptr; aij->c_prev = NULL; aij->c_next = col->ptr; if (aij->r_next != NULL) aij->r_next->r_prev = aij; if (aij->c_next != NULL) aij->c_next->c_prev = aij; row->ptr = col->ptr = aij; /* if the corresponding column is basic, invalidate the basis factorization */ if (col->stat == GLP_BS && aij->val != 0.0) lp->valid = 0; } /* remove zero elements from i-th row */ for (aij = row->ptr; aij != NULL; aij = next) { next = aij->r_next; if (aij->val == 0.0) { /* remove the element from the row list */ if (aij->r_prev == NULL) row->ptr = next; else aij->r_prev->r_next = next; if (next == NULL) ; else next->r_prev = aij->r_prev; /* remove the element from the column list */ xassert(aij->c_prev == NULL); aij->col->ptr = aij->c_next; if (aij->c_next != NULL) aij->c_next->c_prev = NULL; /* return the element to the memory pool */ dmp_free_atom(lp->pool, aij, sizeof(GLPAIJ)), lp->nnz--; } } return; } /*********************************************************************** * NAME * * glp_set_mat_col - set (replace) column of the constraint matrix * * SYNOPSIS * * void glp_set_mat_col(glp_prob *lp, int j, int len, const int ind[], * const double val[]); * * DESCRIPTION * * The routine glp_set_mat_col stores (replaces) the contents of j-th * column of the constraint matrix of the specified problem object. * * Row indices and numeric values of new column elements must be placed * in locations ind[1], ..., ind[len] and val[1], ..., val[len], where * 0 <= len <= m is the new length of j-th column, m is the current * number of rows in the problem object. Elements with identical column * indices are not allowed. Zero elements are allowed, but they are not * stored in the constraint matrix. * * If the parameter len is zero, the parameters ind and/or val can be * specified as NULL. */ void glp_set_mat_col(glp_prob *lp, int j, int len, const int ind[], const double val[]) { glp_tree *tree = lp->tree; GLPROW *row; GLPCOL *col; GLPAIJ *aij, *next; int i, k; if (tree != NULL && tree->reason != 0) xerror("glp_set_mat_col: operation not allowed\n"); /* obtain pointer to j-th column */ if (!(1 <= j && j <= lp->n)) xerror("glp_set_mat_col: j = %d; column number out of range\n", j); col = lp->col[j]; /* remove all existing elements from j-th column */ while (col->ptr != NULL) { /* take next element in the column */ aij = col->ptr; /* remove the element from the column list */ col->ptr = aij->c_next; /* obtain pointer to corresponding row */ row = aij->row; /* remove the element from the row list */ if (aij->r_prev == NULL) row->ptr = aij->r_next; else aij->r_prev->r_next = aij->r_next; if (aij->r_next == NULL) ; else aij->r_next->r_prev = aij->r_prev; /* return the element to the memory pool */ dmp_free_atom(lp->pool, aij, sizeof(GLPAIJ)), lp->nnz--; } /* store new contents of j-th column */ if (!(0 <= len && len <= lp->m)) xerror("glp_set_mat_col: j = %d; len = %d; invalid column leng" "th\n", j, len); if (len > NNZ_MAX - lp->nnz) xerror("glp_set_mat_col: j = %d; len = %d; too many constraint" " coefficients\n", j, len); for (k = 1; k <= len; k++) { /* take number i of corresponding row */ i = ind[k]; /* obtain pointer to i-th row */ if (!(1 <= i && i <= lp->m)) xerror("glp_set_mat_col: j = %d; ind[%d] = %d; row index ou" "t of range\n", j, k, i); row = lp->row[i]; /* if there is element with the same row index, it can only be found in the beginning of i-th row list */ if (row->ptr != NULL && row->ptr->col->j == j) xerror("glp_set_mat_col: j = %d; ind[%d] = %d; duplicate ro" "w indices not allowed\n", j, k, i); /* create new element */ aij = dmp_get_atom(lp->pool, sizeof(GLPAIJ)), lp->nnz++; aij->row = row; aij->col = col; aij->val = val[k]; /* add the new element to the beginning of i-th row and j-th column lists */ aij->r_prev = NULL; aij->r_next = row->ptr; aij->c_prev = NULL; aij->c_next = col->ptr; if (aij->r_next != NULL) aij->r_next->r_prev = aij; if (aij->c_next != NULL) aij->c_next->c_prev = aij; row->ptr = col->ptr = aij; } /* remove zero elements from j-th column */ for (aij = col->ptr; aij != NULL; aij = next) { next = aij->c_next; if (aij->val == 0.0) { /* remove the element from the row list */ xassert(aij->r_prev == NULL); aij->row->ptr = aij->r_next; if (aij->r_next != NULL) aij->r_next->r_prev = NULL; /* remove the element from the column list */ if (aij->c_prev == NULL) col->ptr = next; else aij->c_prev->c_next = next; if (next == NULL) ; else next->c_prev = aij->c_prev; /* return the element to the memory pool */ dmp_free_atom(lp->pool, aij, sizeof(GLPAIJ)), lp->nnz--; } } /* if j-th column is basic, invalidate the basis factorization */ if (col->stat == GLP_BS) lp->valid = 0; return; } /*********************************************************************** * NAME * * glp_load_matrix - load (replace) the whole constraint matrix * * SYNOPSIS * * void glp_load_matrix(glp_prob *lp, int ne, const int ia[], * const int ja[], const double ar[]); * * DESCRIPTION * * The routine glp_load_matrix loads the constraint matrix passed in * the arrays ia, ja, and ar into the specified problem object. Before * loading the current contents of the constraint matrix is destroyed. * * Constraint coefficients (elements of the constraint matrix) must be * specified as triplets (ia[k], ja[k], ar[k]) for k = 1, ..., ne, * where ia[k] is the row index, ja[k] is the column index, ar[k] is a * numeric value of corresponding constraint coefficient. The parameter * ne specifies the total number of (non-zero) elements in the matrix * to be loaded. Coefficients with identical indices are not allowed. * Zero coefficients are allowed, however, they are not stored in the * constraint matrix. * * If the parameter ne is zero, the parameters ia, ja, and ar can be * specified as NULL. */ void glp_load_matrix(glp_prob *lp, int ne, const int ia[], const int ja[], const double ar[]) { glp_tree *tree = lp->tree; GLPROW *row; GLPCOL *col; GLPAIJ *aij, *next; int i, j, k; if (tree != NULL && tree->reason != 0) xerror("glp_load_matrix: operation not allowed\n"); /* clear the constraint matrix */ for (i = 1; i <= lp->m; i++) { row = lp->row[i]; while (row->ptr != NULL) { aij = row->ptr; row->ptr = aij->r_next; dmp_free_atom(lp->pool, aij, sizeof(GLPAIJ)), lp->nnz--; } } xassert(lp->nnz == 0); for (j = 1; j <= lp->n; j++) lp->col[j]->ptr = NULL; /* load the new contents of the constraint matrix and build its row lists */ if (ne < 0) xerror("glp_load_matrix: ne = %d; invalid number of constraint" " coefficients\n", ne); if (ne > NNZ_MAX) xerror("glp_load_matrix: ne = %d; too many constraint coeffici" "ents\n", ne); for (k = 1; k <= ne; k++) { /* take indices of new element */ i = ia[k], j = ja[k]; /* obtain pointer to i-th row */ if (!(1 <= i && i <= lp->m)) xerror("glp_load_matrix: ia[%d] = %d; row index out of rang" "e\n", k, i); row = lp->row[i]; /* obtain pointer to j-th column */ if (!(1 <= j && j <= lp->n)) xerror("glp_load_matrix: ja[%d] = %d; column index out of r" "ange\n", k, j); col = lp->col[j]; /* create new element */ aij = dmp_get_atom(lp->pool, sizeof(GLPAIJ)), lp->nnz++; aij->row = row; aij->col = col; aij->val = ar[k]; /* add the new element to the beginning of i-th row list */ aij->r_prev = NULL; aij->r_next = row->ptr; if (aij->r_next != NULL) aij->r_next->r_prev = aij; row->ptr = aij; } xassert(lp->nnz == ne); /* build column lists of the constraint matrix and check elements with identical indices */ for (i = 1; i <= lp->m; i++) { for (aij = lp->row[i]->ptr; aij != NULL; aij = aij->r_next) { /* obtain pointer to corresponding column */ col = aij->col; /* if there is element with identical indices, it can only be found in the beginning of j-th column list */ if (col->ptr != NULL && col->ptr->row->i == i) { for (k = 1; k <= ne; k++) if (ia[k] == i && ja[k] == col->j) break; xerror("glp_load_mat: ia[%d] = %d; ja[%d] = %d; duplicat" "e indices not allowed\n", k, i, k, col->j); } /* add the element to the beginning of j-th column list */ aij->c_prev = NULL; aij->c_next = col->ptr; if (aij->c_next != NULL) aij->c_next->c_prev = aij; col->ptr = aij; } } /* remove zero elements from the constraint matrix */ for (i = 1; i <= lp->m; i++) { row = lp->row[i]; for (aij = row->ptr; aij != NULL; aij = next) { next = aij->r_next; if (aij->val == 0.0) { /* remove the element from the row list */ if (aij->r_prev == NULL) row->ptr = next; else aij->r_prev->r_next = next; if (next == NULL) ; else next->r_prev = aij->r_prev; /* remove the element from the column list */ if (aij->c_prev == NULL) aij->col->ptr = aij->c_next; else aij->c_prev->c_next = aij->c_next; if (aij->c_next == NULL) ; else aij->c_next->c_prev = aij->c_prev; /* return the element to the memory pool */ dmp_free_atom(lp->pool, aij, sizeof(GLPAIJ)), lp->nnz--; } } } /* invalidate the basis factorization */ lp->valid = 0; return; } /*********************************************************************** * NAME * * glp_check_dup - check for duplicate elements in sparse matrix * * SYNOPSIS * * int glp_check_dup(int m, int n, int ne, const int ia[], * const int ja[]); * * DESCRIPTION * * The routine glp_check_dup checks for duplicate elements (that is, * elements with identical indices) in a sparse matrix specified in the * coordinate format. * * The parameters m and n specifies, respectively, the number of rows * and columns in the matrix, m >= 0, n >= 0. * * The parameter ne specifies the number of (structurally) non-zero * elements in the matrix, ne >= 0. * * Elements of the matrix are specified as doublets (ia[k],ja[k]) for * k = 1,...,ne, where ia[k] is a row index, ja[k] is a column index. * * The routine glp_check_dup can be used prior to a call to the routine * glp_load_matrix to check that the constraint matrix to be loaded has * no duplicate elements. * * RETURNS * * The routine glp_check_dup returns one of the following values: * * 0 - the matrix has no duplicate elements; * * -k - indices ia[k] or/and ja[k] are out of range; * * +k - element (ia[k],ja[k]) is duplicate. */ int glp_check_dup(int m, int n, int ne, const int ia[], const int ja[]) { int i, j, k, *ptr, *next, ret; char *flag; if (m < 0) xerror("glp_check_dup: m = %d; invalid parameter\n"); if (n < 0) xerror("glp_check_dup: n = %d; invalid parameter\n"); if (ne < 0) xerror("glp_check_dup: ne = %d; invalid parameter\n"); if (ne > 0 && ia == NULL) xerror("glp_check_dup: ia = %p; invalid parameter\n", ia); if (ne > 0 && ja == NULL) xerror("glp_check_dup: ja = %p; invalid parameter\n", ja); for (k = 1; k <= ne; k++) { i = ia[k], j = ja[k]; if (!(1 <= i && i <= m && 1 <= j && j <= n)) { ret = -k; goto done; } } if (m == 0 || n == 0) { ret = 0; goto done; } /* allocate working arrays */ ptr = xcalloc(1+m, sizeof(int)); next = xcalloc(1+ne, sizeof(int)); flag = xcalloc(1+n, sizeof(char)); /* build row lists */ for (i = 1; i <= m; i++) ptr[i] = 0; for (k = 1; k <= ne; k++) { i = ia[k]; next[k] = ptr[i]; ptr[i] = k; } /* clear column flags */ for (j = 1; j <= n; j++) flag[j] = 0; /* check for duplicate elements */ for (i = 1; i <= m; i++) { for (k = ptr[i]; k != 0; k = next[k]) { j = ja[k]; if (flag[j]) { /* find first element (i,j) */ for (k = 1; k <= ne; k++) if (ia[k] == i && ja[k] == j) break; xassert(k <= ne); /* find next (duplicate) element (i,j) */ for (k++; k <= ne; k++) if (ia[k] == i && ja[k] == j) break; xassert(k <= ne); ret = +k; goto skip; } flag[j] = 1; } /* clear column flags */ for (k = ptr[i]; k != 0; k = next[k]) flag[ja[k]] = 0; } /* no duplicate element found */ ret = 0; skip: /* free working arrays */ xfree(ptr); xfree(next); xfree(flag); done: return ret; } /*********************************************************************** * NAME * * glp_sort_matrix - sort elements of the constraint matrix * * SYNOPSIS * * void glp_sort_matrix(glp_prob *P); * * DESCRIPTION * * The routine glp_sort_matrix sorts elements of the constraint matrix * rebuilding its row and column linked lists. On exit from the routine * the constraint matrix is not changed, however, elements in the row * linked lists become ordered by ascending column indices, and the * elements in the column linked lists become ordered by ascending row * indices. */ void glp_sort_matrix(glp_prob *P) { GLPAIJ *aij; int i, j; if (P == NULL || P->magic != GLP_PROB_MAGIC) xerror("glp_sort_matrix: P = %p; invalid problem object\n", P); /* rebuild row linked lists */ for (i = P->m; i >= 1; i--) P->row[i]->ptr = NULL; for (j = P->n; j >= 1; j--) { for (aij = P->col[j]->ptr; aij != NULL; aij = aij->c_next) { i = aij->row->i; aij->r_prev = NULL; aij->r_next = P->row[i]->ptr; if (aij->r_next != NULL) aij->r_next->r_prev = aij; P->row[i]->ptr = aij; } } /* rebuild column linked lists */ for (j = P->n; j >= 1; j--) P->col[j]->ptr = NULL; for (i = P->m; i >= 1; i--) { for (aij = P->row[i]->ptr; aij != NULL; aij = aij->r_next) { j = aij->col->j; aij->c_prev = NULL; aij->c_next = P->col[j]->ptr; if (aij->c_next != NULL) aij->c_next->c_prev = aij; P->col[j]->ptr = aij; } } return; } /*********************************************************************** * NAME * * glp_del_rows - delete rows from problem object * * SYNOPSIS * * void glp_del_rows(glp_prob *lp, int nrs, const int num[]); * * DESCRIPTION * * The routine glp_del_rows deletes rows from the specified problem * object. Ordinal numbers of rows to be deleted should be placed in * locations num[1], ..., num[nrs], where nrs > 0. * * Note that deleting rows involves changing ordinal numbers of other * rows remaining in the problem object. New ordinal numbers of the * remaining rows are assigned under the assumption that the original * order of rows is not changed. */ void glp_del_rows(glp_prob *lp, int nrs, const int num[]) { glp_tree *tree = lp->tree; GLPROW *row; int i, k, m_new; /* mark rows to be deleted */ if (!(1 <= nrs && nrs <= lp->m)) xerror("glp_del_rows: nrs = %d; invalid number of rows\n", nrs); for (k = 1; k <= nrs; k++) { /* take the number of row to be deleted */ i = num[k]; /* obtain pointer to i-th row */ if (!(1 <= i && i <= lp->m)) xerror("glp_del_rows: num[%d] = %d; row number out of range" "\n", k, i); row = lp->row[i]; if (tree != NULL && tree->reason != 0) { if (!(tree->reason == GLP_IROWGEN || tree->reason == GLP_ICUTGEN)) xerror("glp_del_rows: operation not allowed\n"); xassert(tree->curr != NULL); if (row->level != tree->curr->level) xerror("glp_del_rows: num[%d] = %d; invalid attempt to d" "elete row created not in current subproblem\n", k,i); if (row->stat != GLP_BS) xerror("glp_del_rows: num[%d] = %d; invalid attempt to d" "elete active row (constraint)\n", k, i); tree->reinv = 1; } /* check that the row is not marked yet */ if (row->i == 0) xerror("glp_del_rows: num[%d] = %d; duplicate row numbers n" "ot allowed\n", k, i); /* erase symbolic name assigned to the row */ glp_set_row_name(lp, i, NULL); xassert(row->node == NULL); /* erase corresponding row of the constraint matrix */ glp_set_mat_row(lp, i, 0, NULL, NULL); xassert(row->ptr == NULL); /* mark the row to be deleted */ row->i = 0; } /* delete all marked rows from the row list */ m_new = 0; for (i = 1; i <= lp->m; i++) { /* obtain pointer to i-th row */ row = lp->row[i]; /* check if the row is marked */ if (row->i == 0) { /* it is marked, delete it */ dmp_free_atom(lp->pool, row, sizeof(GLPROW)); } else { /* it is not marked; keep it */ row->i = ++m_new; lp->row[row->i] = row; } } /* set new number of rows */ lp->m = m_new; /* invalidate the basis factorization */ lp->valid = 0; return; } /*********************************************************************** * NAME * * glp_del_cols - delete columns from problem object * * SYNOPSIS * * void glp_del_cols(glp_prob *lp, int ncs, const int num[]); * * DESCRIPTION * * The routine glp_del_cols deletes columns from the specified problem * object. Ordinal numbers of columns to be deleted should be placed in * locations num[1], ..., num[ncs], where ncs > 0. * * Note that deleting columns involves changing ordinal numbers of * other columns remaining in the problem object. New ordinal numbers * of the remaining columns are assigned under the assumption that the * original order of columns is not changed. */ void glp_del_cols(glp_prob *lp, int ncs, const int num[]) { glp_tree *tree = lp->tree; GLPCOL *col; int j, k, n_new; if (tree != NULL && tree->reason != 0) xerror("glp_del_cols: operation not allowed\n"); /* mark columns to be deleted */ if (!(1 <= ncs && ncs <= lp->n)) xerror("glp_del_cols: ncs = %d; invalid number of columns\n", ncs); for (k = 1; k <= ncs; k++) { /* take the number of column to be deleted */ j = num[k]; /* obtain pointer to j-th column */ if (!(1 <= j && j <= lp->n)) xerror("glp_del_cols: num[%d] = %d; column number out of ra" "nge", k, j); col = lp->col[j]; /* check that the column is not marked yet */ if (col->j == 0) xerror("glp_del_cols: num[%d] = %d; duplicate column number" "s not allowed\n", k, j); /* erase symbolic name assigned to the column */ glp_set_col_name(lp, j, NULL); xassert(col->node == NULL); /* erase corresponding column of the constraint matrix */ glp_set_mat_col(lp, j, 0, NULL, NULL); xassert(col->ptr == NULL); /* mark the column to be deleted */ col->j = 0; /* if it is basic, invalidate the basis factorization */ if (col->stat == GLP_BS) lp->valid = 0; } /* delete all marked columns from the column list */ n_new = 0; for (j = 1; j <= lp->n; j++) { /* obtain pointer to j-th column */ col = lp->col[j]; /* check if the column is marked */ if (col->j == 0) { /* it is marked; delete it */ dmp_free_atom(lp->pool, col, sizeof(GLPCOL)); } else { /* it is not marked; keep it */ col->j = ++n_new; lp->col[col->j] = col; } } /* set new number of columns */ lp->n = n_new; /* if the basis header is still valid, adjust it */ if (lp->valid) { int m = lp->m; int *head = lp->head; for (j = 1; j <= n_new; j++) { k = lp->col[j]->bind; if (k != 0) { xassert(1 <= k && k <= m); head[k] = m + j; } } } return; } /*********************************************************************** * NAME * * glp_copy_prob - copy problem object content * * SYNOPSIS * * void glp_copy_prob(glp_prob *dest, glp_prob *prob, int names); * * DESCRIPTION * * The routine glp_copy_prob copies the content of the problem object * prob to the problem object dest. * * The parameter names is a flag. If it is non-zero, the routine also * copies all symbolic names; otherwise, if it is zero, symbolic names * are not copied. */ void glp_copy_prob(glp_prob *dest, glp_prob *prob, int names) { glp_tree *tree = dest->tree; glp_bfcp bfcp; int i, j, len, *ind; double *val; if (tree != NULL && tree->reason != 0) xerror("glp_copy_prob: operation not allowed\n"); if (dest == prob) xerror("glp_copy_prob: copying problem object to itself not al" "lowed\n"); if (!(names == GLP_ON || names == GLP_OFF)) xerror("glp_copy_prob: names = %d; invalid parameter\n", names); glp_erase_prob(dest); if (names && prob->name != NULL) glp_set_prob_name(dest, prob->name); if (names && prob->obj != NULL) glp_set_obj_name(dest, prob->obj); dest->dir = prob->dir; dest->c0 = prob->c0; if (prob->m > 0) glp_add_rows(dest, prob->m); if (prob->n > 0) glp_add_cols(dest, prob->n); glp_get_bfcp(prob, &bfcp); glp_set_bfcp(dest, &bfcp); dest->pbs_stat = prob->pbs_stat; dest->dbs_stat = prob->dbs_stat; dest->obj_val = prob->obj_val; dest->some = prob->some; dest->ipt_stat = prob->ipt_stat; dest->ipt_obj = prob->ipt_obj; dest->mip_stat = prob->mip_stat; dest->mip_obj = prob->mip_obj; for (i = 1; i <= prob->m; i++) { GLPROW *to = dest->row[i]; GLPROW *from = prob->row[i]; if (names && from->name != NULL) glp_set_row_name(dest, i, from->name); to->type = from->type; to->lb = from->lb; to->ub = from->ub; to->rii = from->rii; to->stat = from->stat; to->prim = from->prim; to->dual = from->dual; to->pval = from->pval; to->dval = from->dval; to->mipx = from->mipx; } ind = xcalloc(1+prob->m, sizeof(int)); val = xcalloc(1+prob->m, sizeof(double)); for (j = 1; j <= prob->n; j++) { GLPCOL *to = dest->col[j]; GLPCOL *from = prob->col[j]; if (names && from->name != NULL) glp_set_col_name(dest, j, from->name); to->kind = from->kind; to->type = from->type; to->lb = from->lb; to->ub = from->ub; to->coef = from->coef; len = glp_get_mat_col(prob, j, ind, val); glp_set_mat_col(dest, j, len, ind, val); to->sjj = from->sjj; to->stat = from->stat; to->prim = from->prim; to->dual = from->dual; to->pval = from->pval; to->dval = from->dval; to->mipx = from->mipx; } xfree(ind); xfree(val); return; } /*********************************************************************** * NAME * * glp_erase_prob - erase problem object content * * SYNOPSIS * * void glp_erase_prob(glp_prob *lp); * * DESCRIPTION * * The routine glp_erase_prob erases the content of the specified * problem object. The effect of this operation is the same as if the * problem object would be deleted with the routine glp_delete_prob and * then created anew with the routine glp_create_prob, with exception * that the handle (pointer) to the problem object remains valid. */ static void delete_prob(glp_prob *lp); void glp_erase_prob(glp_prob *lp) { glp_tree *tree = lp->tree; if (tree != NULL && tree->reason != 0) xerror("glp_erase_prob: operation not allowed\n"); delete_prob(lp); create_prob(lp); return; } /*********************************************************************** * NAME * * glp_delete_prob - delete problem object * * SYNOPSIS * * void glp_delete_prob(glp_prob *lp); * * DESCRIPTION * * The routine glp_delete_prob deletes the specified problem object and * frees all the memory allocated to it. */ static void delete_prob(glp_prob *lp) { lp->magic = 0x3F3F3F3F; dmp_delete_pool(lp->pool); #if 0 /* 17/XI-2009 */ xfree(lp->cps); #else if (lp->parms != NULL) xfree(lp->parms); #endif xassert(lp->tree == NULL); #if 0 if (lp->cwa != NULL) xfree(lp->cwa); #endif xfree(lp->row); xfree(lp->col); if (lp->r_tree != NULL) avl_delete_tree(lp->r_tree); if (lp->c_tree != NULL) avl_delete_tree(lp->c_tree); xfree(lp->head); if (lp->bfcp != NULL) xfree(lp->bfcp); if (lp->bfd != NULL) bfd_delete_it(lp->bfd); return; } void glp_delete_prob(glp_prob *lp) { glp_tree *tree = lp->tree; if (tree != NULL && tree->reason != 0) xerror("glp_delete_prob: operation not allowed\n"); delete_prob(lp); xfree(lp); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpfhv.h0000644000076500000240000001522313524616144025041 0ustar tamasstaff00000000000000/* glpfhv.h (LP basis factorization, FHV eta file version) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPFHV_H #define GLPFHV_H #include "glpluf.h" /*********************************************************************** * The structure FHV defines the factorization of the basis mxm-matrix * B, where m is the number of rows in corresponding problem instance. * * This factorization is the following sextet: * * [B] = (F, H, V, P0, P, Q), (1) * * where F, H, and V are such matrices that * * B = F * H * V, (2) * * and P0, P, and Q are such permutation matrices that the matrix * * L = P0 * F * inv(P0) (3) * * is lower triangular with unity diagonal, and the matrix * * U = P * V * Q (4) * * is upper triangular. All the matrices have the same order m, which * is the order of the basis matrix B. * * The matrices F, V, P, and Q are stored in the structure LUF (see the * module GLPLUF), which is a member of the structure FHV. * * The matrix H is stored in the form of eta file using row-like format * as follows: * * H = H[1] * H[2] * ... * H[nfs], (5) * * where H[k], k = 1, 2, ..., nfs, is a row-like factor, which differs * from the unity matrix only by one row, nfs is current number of row- * like factors. After the factorization has been built for some given * basis matrix B the matrix H has no factors and thus it is the unity * matrix. Then each time when the factorization is recomputed for an * adjacent basis matrix, the next factor H[k], k = 1, 2, ... is built * and added to the end of the eta file H. * * Being sparse vectors non-trivial rows of the factors H[k] are stored * in the right part of the sparse vector area (SVA) in the same manner * as rows and columns of the matrix F. * * For more details see the program documentation. */ typedef struct FHV FHV; struct FHV { /* LP basis factorization */ int m_max; /* maximal value of m (increased automatically, if necessary) */ int m; /* the order of matrices B, F, H, V, P0, P, Q */ int valid; /* the factorization is valid only if this flag is set */ LUF *luf; /* LU-factorization (contains the matrices F, V, P, Q) */ /*--------------------------------------------------------------*/ /* matrix H in the form of eta file */ int hh_max; /* maximal number of row-like factors (which limits the number of updates of the factorization) */ int hh_nfs; /* current number of row-like factors (0 <= hh_nfs <= hh_max) */ int *hh_ind; /* int hh_ind[1+hh_max]; */ /* hh_ind[k], k = 1, ..., nfs, is the number of a non-trivial row of factor H[k] */ int *hh_ptr; /* int hh_ptr[1+hh_max]; */ /* hh_ptr[k], k = 1, ..., nfs, is a pointer to the first element of the non-trivial row of factor H[k] in the SVA */ int *hh_len; /* int hh_len[1+hh_max]; */ /* hh_len[k], k = 1, ..., nfs, is the number of non-zero elements in the non-trivial row of factor H[k] */ /*--------------------------------------------------------------*/ /* matrix P0 */ int *p0_row; /* int p0_row[1+m_max]; */ /* p0_row[i] = j means that p0[i,j] = 1 */ int *p0_col; /* int p0_col[1+m_max]; */ /* p0_col[j] = i means that p0[i,j] = 1 */ /* if i-th row or column of the matrix F corresponds to i'-th row or column of the matrix L = P0*F*inv(P0), then p0_row[i'] = i and p0_col[i] = i' */ /*--------------------------------------------------------------*/ /* working arrays */ int *cc_ind; /* int cc_ind[1+m_max]; */ /* integer working array */ double *cc_val; /* double cc_val[1+m_max]; */ /* floating-point working array */ /*--------------------------------------------------------------*/ /* control parameters */ double upd_tol; /* update tolerance; if after updating the factorization absolute value of some diagonal element u[k,k] of matrix U = P*V*Q is less than upd_tol * max(|u[k,*]|, |u[*,k]|), the factorization is considered as inaccurate */ /*--------------------------------------------------------------*/ /* some statistics */ int nnz_h; /* current number of non-zeros in all factors of matrix H */ }; /* return codes: */ #define FHV_ESING 1 /* singular matrix */ #define FHV_ECOND 2 /* ill-conditioned matrix */ #define FHV_ECHECK 3 /* insufficient accuracy */ #define FHV_ELIMIT 4 /* update limit reached */ #define FHV_EROOM 5 /* SVA overflow */ #define fhv_create_it _glp_fhv_create_it FHV *fhv_create_it(void); /* create LP basis factorization */ #define fhv_factorize _glp_fhv_factorize int fhv_factorize(FHV *fhv, int m, int (*col)(void *info, int j, int ind[], double val[]), void *info); /* compute LP basis factorization */ #define fhv_h_solve _glp_fhv_h_solve void fhv_h_solve(FHV *fhv, int tr, double x[]); /* solve system H*x = b or H'*x = b */ #define fhv_ftran _glp_fhv_ftran void fhv_ftran(FHV *fhv, double x[]); /* perform forward transformation (solve system B*x = b) */ #define fhv_btran _glp_fhv_btran void fhv_btran(FHV *fhv, double x[]); /* perform backward transformation (solve system B'*x = b) */ #define fhv_update_it _glp_fhv_update_it int fhv_update_it(FHV *fhv, int j, int len, const int ind[], const double val[]); /* update LP basis factorization */ #define fhv_delete_it _glp_fhv_delete_it void fhv_delete_it(FHV *fhv); /* delete LP basis factorization */ #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glplpx03.c0000644000076500000240000002127113524616144025217 0ustar tamasstaff00000000000000/* glplpx03.c (OPB format) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Author: Oscar Gustafsson . * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #define _GLPSTD_ERRNO #define _GLPSTD_STDIO #include "glpapi.h" #if 0 /* 24/XII-2009; by mao */ #include "glpipp.h" #endif /*---------------------------------------------------------------------- -- lpx_write_pb - write problem data in (normalized) OPB format. -- -- *Synopsis* -- -- #include "glplpx.h" -- int lpx_write_pb(LPX *lp, const char *fname, int normalized, -- int binarize); -- -- *Description* -- -- The routine lpx_write_pb writes problem data in OPB format -- to an output text file whose name is the character string fname. -- If normalized is non-zero the output will be generated in a -- normalized form with sequentially numbered variables, x1, x2 etc. -- If binarize, any integer variable will be repalzec by binary ones, -- see ipp_binarize -- -- *Returns* -- -- If the operation was successful, the routine returns zero. Otherwise -- the routine prints an error message and returns non-zero. */ #if 1 /* 24/XII-2009; by mao (disabled, because IPP was removed) */ int lpx_write_pb(LPX *lp, const char *fname, int normalized, int binarize) { xassert(lp == lp); xassert(fname == fname); xassert(normalized == normalized); xassert(binarize == binarize); xprintf("lpx_write_pb: sorry, currently this operation is not ava" "ilable\n"); return 1; } #else int lpx_write_pb(LPX *lp, const char *fname, int normalized, int binarize) { FILE* fp; int m,n,i,j,k,o,nonfree=0, obj_dir, dbl, *ndx, row_type, emptylhs=0; double coeff, *val, bound, constant/*=0.0*/; char* objconstname = "dummy_one"; char* emptylhsname = "dummy_zero"; /* Variables needed for possible binarization */ /*LPX* tlp;*/ IPP *ipp = NULL; /*tlp=lp;*/ if(binarize) /* Transform integer variables to binary ones */ { ipp = ipp_create_wksp(); ipp_load_orig(ipp, lp); ipp_binarize(ipp); lp = ipp_build_prob(ipp); } fp = fopen(fname, "w"); if(fp!= NULL) { xprintf( "lpx_write_pb: writing problem in %sOPB format to `%s'...\n", (normalized?"normalized ":""), fname); m = glp_get_num_rows(lp); n = glp_get_num_cols(lp); for(i=1;i<=m;i++) { switch(glp_get_row_type(lp,i)) { case GLP_LO: case GLP_UP: case GLP_FX: { nonfree += 1; break; } case GLP_DB: { nonfree += 2; break; } } } constant=glp_get_obj_coef(lp,0); fprintf(fp,"* #variables = %d #constraints = %d\n", n + (constant == 0?1:0), nonfree + (constant == 0?1:0)); /* Objective function */ obj_dir = glp_get_obj_dir(lp); fprintf(fp,"min: "); for(i=1;i<=n;i++) { coeff = glp_get_obj_coef(lp,i); if(coeff != 0.0) { if(obj_dir == GLP_MAX) coeff=-coeff; if(normalized) fprintf(fp, " %d x%d", (int)coeff, i); else fprintf(fp, " %d*%s", (int)coeff, glp_get_col_name(lp,i)); } } if(constant) { if(normalized) fprintf(fp, " %d x%d", (int)constant, n+1); else fprintf(fp, " %d*%s", (int)constant, objconstname); } fprintf(fp,";\n"); if(normalized && !binarize) /* Name substitution */ { fprintf(fp,"* Variable name substitution:\n"); for(j=1;j<=n;j++) { fprintf(fp, "* x%d = %s\n", j, glp_get_col_name(lp,j)); } if(constant) fprintf(fp, "* x%d = %s\n", n+1, objconstname); } ndx = xcalloc(1+n, sizeof(int)); val = xcalloc(1+n, sizeof(double)); /* Constraints */ for(j=1;j<=m;j++) { row_type=glp_get_row_type(lp,j); if(row_type!=GLP_FR) { if(row_type == GLP_DB) { dbl=2; row_type = GLP_UP; } else { dbl=1; } k=glp_get_mat_row(lp, j, ndx, val); for(o=1;o<=dbl;o++) { if(o==2) { row_type = GLP_LO; } if(k==0) /* Empty LHS */ { emptylhs = 1; if(normalized) { fprintf(fp, "0 x%d ", n+2); } else { fprintf(fp, "0*%s ", emptylhsname); } } for(i=1;i<=k;i++) { if(val[i] != 0.0) { if(normalized) { fprintf(fp, "%d x%d ", (row_type==GLP_UP)?(-(int)val[i]):((int)val[i]), ndx[i]); } else { fprintf(fp, "%d*%s ", (int)val[i], glp_get_col_name(lp,ndx[i])); } } } switch(row_type) { case GLP_LO: { fprintf(fp, ">="); bound = glp_get_row_lb(lp,j); break; } case GLP_UP: { if(normalized) { fprintf(fp, ">="); bound = -glp_get_row_ub(lp,j); } else { fprintf(fp, "<="); bound = glp_get_row_ub(lp,j); } break; } case GLP_FX: { fprintf(fp, "="); bound = glp_get_row_lb(lp,j); break; } } fprintf(fp," %d;\n",(int)bound); } } } xfree(ndx); xfree(val); if(constant) { xprintf( "lpx_write_pb: adding constant objective function variable\n"); if(normalized) fprintf(fp, "1 x%d = 1;\n", n+1); else fprintf(fp, "1*%s = 1;\n", objconstname); } if(emptylhs) { xprintf( "lpx_write_pb: adding dummy variable for empty left-hand si" "de constraint\n"); if(normalized) fprintf(fp, "1 x%d = 0;\n", n+2); else fprintf(fp, "1*%s = 0;\n", emptylhsname); } } else { xprintf("Problems opening file for writing: %s\n", fname); return(1); } fflush(fp); if (ferror(fp)) { xprintf("lpx_write_pb: can't write to `%s' - %s\n", fname, strerror(errno)); goto fail; } fclose(fp); if(binarize) { /* delete the resultant problem object */ if (lp != NULL) lpx_delete_prob(lp); /* delete MIP presolver workspace */ if (ipp != NULL) ipp_delete_wksp(ipp); /*lp=tlp;*/ } return 0; fail: if (fp != NULL) fclose(fp); return 1; } #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpqmd.h0000644000076500000240000000430513524616144025036 0ustar tamasstaff00000000000000/* glpqmd.h (quotient minimum degree algorithm) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPQMD_H #define GLPQMD_H #define genqmd _glp_qmd_genqmd void genqmd(int *neqns, int xadj[], int adjncy[], int perm[], int invp[], int deg[], int marker[], int rchset[], int nbrhd[], int qsize[], int qlink[], int *nofsub); /* GENeral Quotient Minimum Degree algorithm */ #define qmdrch _glp_qmd_qmdrch void qmdrch(int *root, int xadj[], int adjncy[], int deg[], int marker[], int *rchsze, int rchset[], int *nhdsze, int nbrhd[]); /* Quotient MD ReaCHable set */ #define qmdqt _glp_qmd_qmdqt void qmdqt(int *root, int xadj[], int adjncy[], int marker[], int *rchsze, int rchset[], int nbrhd[]); /* Quotient MD Quotient graph Transformation */ #define qmdupd _glp_qmd_qmdupd void qmdupd(int xadj[], int adjncy[], int *nlist, int list[], int deg[], int qsize[], int qlink[], int marker[], int rchset[], int nbrhd[]); /* Quotient MD UPDate */ #define qmdmrg _glp_qmd_qmdmrg void qmdmrg(int xadj[], int adjncy[], int deg[], int qsize[], int qlink[], int marker[], int *deg0, int *nhdsze, int nbrhd[], int rchset[], int ovrlp[]); /* Quotient MD MeRGe */ #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpspx.h0000644000076500000240000000265413524616144025074 0ustar tamasstaff00000000000000/* glpspx.h (core simplex solvers) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPSPX_H #define GLPSPX_H #include "glpapi.h" #define spx_primal _glp_spx_primal int spx_primal(glp_prob *lp, const glp_smcp *parm); /* core LP solver based on the primal simplex method */ #define spx_dual _glp_spx_dual int spx_dual(glp_prob *lp, const glp_smcp *parm); /* core LP solver based on the dual simplex method */ #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpenv03.c0000644000076500000240000001533313524616144025206 0ustar tamasstaff00000000000000/* glpenv03.c (terminal output) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wunused-label" #pragma clang diagnostic ignored "-Wunused-variable" #endif #include "glpapi.h" /*********************************************************************** * NAME * * glp_printf - write formatted output to terminal * * SYNOPSIS * * void glp_printf(const char *fmt, ...); * * DESCRIPTION * * The routine glp_printf uses the format control string fmt to format * its parameters and writes the formatted output to the terminal. */ void glp_printf(const char *fmt, ...) { va_list arg; /* va_start(arg, fmt); */ /* xvprintf(fmt, arg); */ /* va_end(arg); */ return; } /*********************************************************************** * NAME * * glp_vprintf - write formatted output to terminal * * SYNOPSIS * * void glp_vprintf(const char *fmt, va_list arg); * * DESCRIPTION * * The routine glp_vprintf uses the format control string fmt to format * its parameters specified by the list arg and writes the formatted * output to the terminal. */ void glp_vprintf(const char *fmt, va_list arg) { ENV *env = get_env_ptr(); /* if terminal output is disabled, do nothing */ /* if (!env->term_out) goto skip; */ /* /\* format the output *\/ */ /* vsprintf(env->term_buf, fmt, arg); */ /* /\* pass the output to the user-defined routine *\/ */ /* if (env->term_hook != NULL) */ /* { if (env->term_hook(env->term_info, env->term_buf) != 0) */ /* goto skip; */ /* } */ /* /\* send the output to the terminal *\/ */ /* fputs(env->term_buf, stdout); */ /* fflush(stdout); */ /* /\* copy the output to the text file *\/ */ /* if (env->tee_file != NULL) */ /* { fputs(env->term_buf, env->tee_file); */ /* fflush(env->tee_file); */ /* } */ skip: return; } /*********************************************************************** * NAME * * glp_term_out - enable/disable terminal output * * SYNOPSIS * * int glp_term_out(int flag); * * DESCRIPTION * * Depending on the parameter flag the routine glp_term_out enables or * disables terminal output performed by glpk routines: * * GLP_ON - enable terminal output; * GLP_OFF - disable terminal output. * * RETURNS * * The routine glp_term_out returns the previous value of the terminal * output flag. */ int glp_term_out(int flag) { ENV *env = get_env_ptr(); int old = env->term_out; if (!(flag == GLP_ON || flag == GLP_OFF)) xerror("glp_term_out: flag = %d; invalid value\n", flag); env->term_out = flag; return old; } /*********************************************************************** * NAME * * glp_term_hook - install hook to intercept terminal output * * SYNOPSIS * * void glp_term_hook(int (*func)(void *info, const char *s), * void *info); * * DESCRIPTION * * The routine glp_term_hook installs a user-defined hook routine to * intercept all terminal output performed by glpk routines. * * This feature can be used to redirect the terminal output to other * destination, for example to a file or a text window. * * The parameter func specifies the user-defined hook routine. It is * called from an internal printing routine, which passes to it two * parameters: info and s. The parameter info is a transit pointer, * specified in the corresponding call to the routine glp_term_hook; * it may be used to pass some information to the hook routine. The * parameter s is a pointer to the null terminated character string, * which is intended to be written to the terminal. If the hook routine * returns zero, the printing routine writes the string s to the * terminal in a usual way; otherwise, if the hook routine returns * non-zero, no terminal output is performed. * * To uninstall the hook routine the parameters func and info should be * specified as NULL. */ void glp_term_hook(int (*func)(void *info, const char *s), void *info) { ENV *env = get_env_ptr(); if (func == NULL) { env->term_hook = NULL; env->term_info = NULL; } else { env->term_hook = func; env->term_info = info; } return; } /*********************************************************************** * NAME * * glp_open_tee - start copying terminal output to text file * * SYNOPSIS * * int glp_open_tee(const char *fname); * * DESCRIPTION * * The routine glp_open_tee starts copying all the terminal output to * an output text file, whose name is specified by the character string * fname. * * RETURNS * * 0 - operation successful * 1 - copying terminal output is already active * 2 - unable to create output file */ int glp_open_tee(const char *fname) { ENV *env = get_env_ptr(); if (env->tee_file != NULL) { /* copying terminal output is already active */ return 1; } env->tee_file = fopen(fname, "w"); if (env->tee_file == NULL) { /* unable to create output file */ return 2; } return 0; } /*********************************************************************** * NAME * * glp_close_tee - stop copying terminal output to text file * * SYNOPSIS * * int glp_close_tee(void); * * DESCRIPTION * * The routine glp_close_tee stops copying the terminal output to the * output text file previously open by the routine glp_open_tee closing * that file. * * RETURNS * * 0 - operation successful * 1 - copying terminal output was not started */ int glp_close_tee(void) { ENV *env = get_env_ptr(); if (env->tee_file == NULL) { /* copying terminal output was not started */ return 1; } fclose(env->tee_file); env->tee_file = NULL; return 0; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpssx02.c0000644000076500000240000004070313524616144025231 0ustar tamasstaff00000000000000/* glpssx02.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glpenv.h" #include "glpssx.h" static void show_progress(SSX *ssx, int phase) { /* this auxiliary routine displays information about progress of the search */ int i, def = 0; for (i = 1; i <= ssx->m; i++) if (ssx->type[ssx->Q_col[i]] == SSX_FX) def++; xprintf("%s%6d: %s = %22.15g (%d)\n", phase == 1 ? " " : "*", ssx->it_cnt, phase == 1 ? "infsum" : "objval", mpq_get_d(ssx->bbar[0]), def); #if 0 ssx->tm_lag = utime(); #else ssx->tm_lag = xtime(); #endif return; } /*---------------------------------------------------------------------- // ssx_phase_I - find primal feasible solution. // // This routine implements phase I of the primal simplex method. // // On exit the routine returns one of the following codes: // // 0 - feasible solution found; // 1 - problem has no feasible solution; // 2 - iterations limit exceeded; // 3 - time limit exceeded. ----------------------------------------------------------------------*/ int ssx_phase_I(SSX *ssx) { int m = ssx->m; int n = ssx->n; int *type = ssx->type; mpq_t *lb = ssx->lb; mpq_t *ub = ssx->ub; mpq_t *coef = ssx->coef; int *A_ptr = ssx->A_ptr; int *A_ind = ssx->A_ind; mpq_t *A_val = ssx->A_val; int *Q_col = ssx->Q_col; mpq_t *bbar = ssx->bbar; mpq_t *pi = ssx->pi; mpq_t *cbar = ssx->cbar; int *orig_type, orig_dir; mpq_t *orig_lb, *orig_ub, *orig_coef; int i, k, ret; /* save components of the original LP problem, which are changed by the routine */ orig_type = xcalloc(1+m+n, sizeof(int)); orig_lb = xcalloc(1+m+n, sizeof(mpq_t)); orig_ub = xcalloc(1+m+n, sizeof(mpq_t)); orig_coef = xcalloc(1+m+n, sizeof(mpq_t)); for (k = 1; k <= m+n; k++) { orig_type[k] = type[k]; mpq_init(orig_lb[k]); mpq_set(orig_lb[k], lb[k]); mpq_init(orig_ub[k]); mpq_set(orig_ub[k], ub[k]); } orig_dir = ssx->dir; for (k = 0; k <= m+n; k++) { mpq_init(orig_coef[k]); mpq_set(orig_coef[k], coef[k]); } /* build an artificial basic solution, which is primal feasible, and also build an auxiliary objective function to minimize the sum of infeasibilities for the original problem */ ssx->dir = SSX_MIN; for (k = 0; k <= m+n; k++) mpq_set_si(coef[k], 0, 1); mpq_set_si(bbar[0], 0, 1); for (i = 1; i <= m; i++) { int t; k = Q_col[i]; /* x[k] = xB[i] */ t = type[k]; if (t == SSX_LO || t == SSX_DB || t == SSX_FX) { /* in the original problem x[k] has lower bound */ if (mpq_cmp(bbar[i], lb[k]) < 0) { /* which is violated */ type[k] = SSX_UP; mpq_set(ub[k], lb[k]); mpq_set_si(lb[k], 0, 1); mpq_set_si(coef[k], -1, 1); mpq_add(bbar[0], bbar[0], ub[k]); mpq_sub(bbar[0], bbar[0], bbar[i]); } } if (t == SSX_UP || t == SSX_DB || t == SSX_FX) { /* in the original problem x[k] has upper bound */ if (mpq_cmp(bbar[i], ub[k]) > 0) { /* which is violated */ type[k] = SSX_LO; mpq_set(lb[k], ub[k]); mpq_set_si(ub[k], 0, 1); mpq_set_si(coef[k], +1, 1); mpq_add(bbar[0], bbar[0], bbar[i]); mpq_sub(bbar[0], bbar[0], lb[k]); } } } /* now the initial basic solution should be primal feasible due to changes of bounds of some basic variables, which turned to implicit artifical variables */ /* compute simplex multipliers and reduced costs */ ssx_eval_pi(ssx); ssx_eval_cbar(ssx); /* display initial progress of the search */ show_progress(ssx, 1); /* main loop starts here */ for (;;) { /* display current progress of the search */ #if 0 if (utime() - ssx->tm_lag >= ssx->out_frq - 0.001) #else if (xdifftime(xtime(), ssx->tm_lag) >= ssx->out_frq - 0.001) #endif show_progress(ssx, 1); /* we do not need to wait until all artificial variables have left the basis */ if (mpq_sgn(bbar[0]) == 0) { /* the sum of infeasibilities is zero, therefore the current solution is primal feasible for the original problem */ ret = 0; break; } /* check if the iterations limit has been exhausted */ if (ssx->it_lim == 0) { ret = 2; break; } /* check if the time limit has been exhausted */ #if 0 if (ssx->tm_lim >= 0.0 && ssx->tm_lim <= utime() - ssx->tm_beg) #else if (ssx->tm_lim >= 0.0 && ssx->tm_lim <= xdifftime(xtime(), ssx->tm_beg)) #endif { ret = 3; break; } /* choose non-basic variable xN[q] */ ssx_chuzc(ssx); /* if xN[q] cannot be chosen, the sum of infeasibilities is minimal but non-zero; therefore the original problem has no primal feasible solution */ if (ssx->q == 0) { ret = 1; break; } /* compute q-th column of the simplex table */ ssx_eval_col(ssx); /* choose basic variable xB[p] */ ssx_chuzr(ssx); /* the sum of infeasibilities cannot be negative, therefore the auxiliary lp problem cannot have unbounded solution */ xassert(ssx->p != 0); /* update values of basic variables */ ssx_update_bbar(ssx); if (ssx->p > 0) { /* compute p-th row of the inverse inv(B) */ ssx_eval_rho(ssx); /* compute p-th row of the simplex table */ ssx_eval_row(ssx); xassert(mpq_cmp(ssx->aq[ssx->p], ssx->ap[ssx->q]) == 0); /* update simplex multipliers */ ssx_update_pi(ssx); /* update reduced costs of non-basic variables */ ssx_update_cbar(ssx); } /* xB[p] is leaving the basis; if it is implicit artificial variable, the corresponding residual vanishes; therefore bounds of this variable should be restored to the original values */ if (ssx->p > 0) { k = Q_col[ssx->p]; /* x[k] = xB[p] */ if (type[k] != orig_type[k]) { /* x[k] is implicit artificial variable */ type[k] = orig_type[k]; mpq_set(lb[k], orig_lb[k]); mpq_set(ub[k], orig_ub[k]); xassert(ssx->p_stat == SSX_NL || ssx->p_stat == SSX_NU); ssx->p_stat = (ssx->p_stat == SSX_NL ? SSX_NU : SSX_NL); if (type[k] == SSX_FX) ssx->p_stat = SSX_NS; /* nullify the objective coefficient at x[k] */ mpq_set_si(coef[k], 0, 1); /* since coef[k] has been changed, we need to compute new reduced cost of x[k], which it will have in the adjacent basis */ /* the formula d[j] = cN[j] - pi' * N[j] is used (note that the vector pi is not changed, because it depends on objective coefficients at basic variables, but in the adjacent basis, for which the vector pi has been just recomputed, x[k] is non-basic) */ if (k <= m) { /* x[k] is auxiliary variable */ mpq_neg(cbar[ssx->q], pi[k]); } else { /* x[k] is structural variable */ int ptr; mpq_t temp; mpq_init(temp); mpq_set_si(cbar[ssx->q], 0, 1); for (ptr = A_ptr[k-m]; ptr < A_ptr[k-m+1]; ptr++) { mpq_mul(temp, pi[A_ind[ptr]], A_val[ptr]); mpq_add(cbar[ssx->q], cbar[ssx->q], temp); } mpq_clear(temp); } } } /* jump to the adjacent vertex of the polyhedron */ ssx_change_basis(ssx); /* one simplex iteration has been performed */ if (ssx->it_lim > 0) ssx->it_lim--; ssx->it_cnt++; } /* display final progress of the search */ show_progress(ssx, 1); /* restore components of the original problem, which were changed by the routine */ for (k = 1; k <= m+n; k++) { type[k] = orig_type[k]; mpq_set(lb[k], orig_lb[k]); mpq_clear(orig_lb[k]); mpq_set(ub[k], orig_ub[k]); mpq_clear(orig_ub[k]); } ssx->dir = orig_dir; for (k = 0; k <= m+n; k++) { mpq_set(coef[k], orig_coef[k]); mpq_clear(orig_coef[k]); } xfree(orig_type); xfree(orig_lb); xfree(orig_ub); xfree(orig_coef); /* return to the calling program */ return ret; } /*---------------------------------------------------------------------- // ssx_phase_II - find optimal solution. // // This routine implements phase II of the primal simplex method. // // On exit the routine returns one of the following codes: // // 0 - optimal solution found; // 1 - problem has unbounded solution; // 2 - iterations limit exceeded; // 3 - time limit exceeded. ----------------------------------------------------------------------*/ int ssx_phase_II(SSX *ssx) { int ret; /* display initial progress of the search */ show_progress(ssx, 2); /* main loop starts here */ for (;;) { /* display current progress of the search */ #if 0 if (utime() - ssx->tm_lag >= ssx->out_frq - 0.001) #else if (xdifftime(xtime(), ssx->tm_lag) >= ssx->out_frq - 0.001) #endif show_progress(ssx, 2); /* check if the iterations limit has been exhausted */ if (ssx->it_lim == 0) { ret = 2; break; } /* check if the time limit has been exhausted */ #if 0 if (ssx->tm_lim >= 0.0 && ssx->tm_lim <= utime() - ssx->tm_beg) #else if (ssx->tm_lim >= 0.0 && ssx->tm_lim <= xdifftime(xtime(), ssx->tm_beg)) #endif { ret = 3; break; } /* choose non-basic variable xN[q] */ ssx_chuzc(ssx); /* if xN[q] cannot be chosen, the current basic solution is dual feasible and therefore optimal */ if (ssx->q == 0) { ret = 0; break; } /* compute q-th column of the simplex table */ ssx_eval_col(ssx); /* choose basic variable xB[p] */ ssx_chuzr(ssx); /* if xB[p] cannot be chosen, the problem has no dual feasible solution (i.e. unbounded) */ if (ssx->p == 0) { ret = 1; break; } /* update values of basic variables */ ssx_update_bbar(ssx); if (ssx->p > 0) { /* compute p-th row of the inverse inv(B) */ ssx_eval_rho(ssx); /* compute p-th row of the simplex table */ ssx_eval_row(ssx); xassert(mpq_cmp(ssx->aq[ssx->p], ssx->ap[ssx->q]) == 0); #if 0 /* update simplex multipliers */ ssx_update_pi(ssx); #endif /* update reduced costs of non-basic variables */ ssx_update_cbar(ssx); } /* jump to the adjacent vertex of the polyhedron */ ssx_change_basis(ssx); /* one simplex iteration has been performed */ if (ssx->it_lim > 0) ssx->it_lim--; ssx->it_cnt++; } /* display final progress of the search */ show_progress(ssx, 2); /* return to the calling program */ return ret; } /*---------------------------------------------------------------------- // ssx_driver - base driver to exact simplex method. // // This routine is a base driver to a version of the primal simplex // method using exact (bignum) arithmetic. // // On exit the routine returns one of the following codes: // // 0 - optimal solution found; // 1 - problem has no feasible solution; // 2 - problem has unbounded solution; // 3 - iterations limit exceeded (phase I); // 4 - iterations limit exceeded (phase II); // 5 - time limit exceeded (phase I); // 6 - time limit exceeded (phase II); // 7 - initial basis matrix is exactly singular. ----------------------------------------------------------------------*/ int ssx_driver(SSX *ssx) { int m = ssx->m; int *type = ssx->type; mpq_t *lb = ssx->lb; mpq_t *ub = ssx->ub; int *Q_col = ssx->Q_col; mpq_t *bbar = ssx->bbar; int i, k, ret; ssx->tm_beg = xtime(); /* factorize the initial basis matrix */ if (ssx_factorize(ssx)) { xprintf("Initial basis matrix is singular\n"); ret = 7; goto done; } /* compute values of basic variables */ ssx_eval_bbar(ssx); /* check if the initial basic solution is primal feasible */ for (i = 1; i <= m; i++) { int t; k = Q_col[i]; /* x[k] = xB[i] */ t = type[k]; if (t == SSX_LO || t == SSX_DB || t == SSX_FX) { /* x[k] has lower bound */ if (mpq_cmp(bbar[i], lb[k]) < 0) { /* which is violated */ break; } } if (t == SSX_UP || t == SSX_DB || t == SSX_FX) { /* x[k] has upper bound */ if (mpq_cmp(bbar[i], ub[k]) > 0) { /* which is violated */ break; } } } if (i > m) { /* no basic variable violates its bounds */ ret = 0; goto skip; } /* phase I: find primal feasible solution */ ret = ssx_phase_I(ssx); switch (ret) { case 0: ret = 0; break; case 1: xprintf("PROBLEM HAS NO FEASIBLE SOLUTION\n"); ret = 1; break; case 2: xprintf("ITERATIONS LIMIT EXCEEDED; SEARCH TERMINATED\n"); ret = 3; break; case 3: xprintf("TIME LIMIT EXCEEDED; SEARCH TERMINATED\n"); ret = 5; break; default: xassert(ret != ret); } /* compute values of basic variables (actually only the objective value needs to be computed) */ ssx_eval_bbar(ssx); skip: /* compute simplex multipliers */ ssx_eval_pi(ssx); /* compute reduced costs of non-basic variables */ ssx_eval_cbar(ssx); /* if phase I failed, do not start phase II */ if (ret != 0) goto done; /* phase II: find optimal solution */ ret = ssx_phase_II(ssx); switch (ret) { case 0: xprintf("OPTIMAL SOLUTION FOUND\n"); ret = 0; break; case 1: xprintf("PROBLEM HAS UNBOUNDED SOLUTION\n"); ret = 2; break; case 2: xprintf("ITERATIONS LIMIT EXCEEDED; SEARCH TERMINATED\n"); ret = 4; break; case 3: xprintf("TIME LIMIT EXCEEDED; SEARCH TERMINATED\n"); ret = 6; break; default: xassert(ret != ret); } done: /* decrease the time limit by the spent amount of time */ if (ssx->tm_lim >= 0.0) #if 0 { ssx->tm_lim -= utime() - ssx->tm_beg; #else { ssx->tm_lim -= xdifftime(xtime(), ssx->tm_beg); #endif if (ssx->tm_lim < 0.0) ssx->tm_lim = 0.0; } return ret; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpios12.c0000644000076500000240000001340613524616144025207 0ustar tamasstaff00000000000000/* glpios12.c (node selection heuristics) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wsometimes-uninitialized" #endif #include "glpios.h" /*********************************************************************** * NAME * * ios_choose_node - select subproblem to continue the search * * SYNOPSIS * * #include "glpios.h" * int ios_choose_node(glp_tree *T); * * DESCRIPTION * * The routine ios_choose_node selects a subproblem from the active * list to continue the search. The choice depends on the backtracking * technique option. * * RETURNS * * The routine ios_choose_node return the reference number of the * subproblem selected. */ static int most_feas(glp_tree *T); static int best_proj(glp_tree *T); static int best_node(glp_tree *T); int ios_choose_node(glp_tree *T) { int p; if (T->parm->bt_tech == GLP_BT_DFS) { /* depth first search */ xassert(T->tail != NULL); p = T->tail->p; } else if (T->parm->bt_tech == GLP_BT_BFS) { /* breadth first search */ xassert(T->head != NULL); p = T->head->p; } else if (T->parm->bt_tech == GLP_BT_BLB) { /* select node with best local bound */ p = best_node(T); } else if (T->parm->bt_tech == GLP_BT_BPH) { if (T->mip->mip_stat == GLP_UNDEF) { /* "most integer feasible" subproblem */ p = most_feas(T); } else { /* best projection heuristic */ p = best_proj(T); } } else xassert(T != T); return p; } static int most_feas(glp_tree *T) { /* select subproblem whose parent has minimal sum of integer infeasibilities */ IOSNPD *node; int p; double best; p = 0, best = DBL_MAX; for (node = T->head; node != NULL; node = node->next) { xassert(node->up != NULL); if (best > node->up->ii_sum) p = node->p, best = node->up->ii_sum; } return p; } static int best_proj(glp_tree *T) { /* select subproblem using the best projection heuristic */ IOSNPD *root, *node; int p; double best, deg, obj; /* the global bound must exist */ xassert(T->mip->mip_stat == GLP_FEAS); /* obtain pointer to the root node, which must exist */ root = T->slot[1].node; xassert(root != NULL); /* deg estimates degradation of the objective function per unit of the sum of integer infeasibilities */ xassert(root->ii_sum > 0.0); deg = (T->mip->mip_obj - root->bound) / root->ii_sum; /* nothing has been selected so far */ p = 0, best = DBL_MAX; /* walk through the list of active subproblems */ for (node = T->head; node != NULL; node = node->next) { xassert(node->up != NULL); /* obj estimates optimal objective value if the sum of integer infeasibilities were zero */ obj = node->up->bound + deg * node->up->ii_sum; if (T->mip->dir == GLP_MAX) obj = - obj; /* select the subproblem which has the best estimated optimal objective value */ if (best > obj) p = node->p, best = obj; } return p; } static int best_node(glp_tree *T) { /* select subproblem with best local bound */ IOSNPD *node, *best = NULL; double bound, eps; switch (T->mip->dir) { case GLP_MIN: bound = +DBL_MAX; for (node = T->head; node != NULL; node = node->next) if (bound > node->bound) bound = node->bound; xassert(bound != +DBL_MAX); eps = 0.001 * (1.0 + fabs(bound)); for (node = T->head; node != NULL; node = node->next) { if (node->bound <= bound + eps) { xassert(node->up != NULL); if (best == NULL || #if 1 best->up->ii_sum > node->up->ii_sum) best = node; #else best->lp_obj > node->lp_obj) best = node; #endif } } break; case GLP_MAX: bound = -DBL_MAX; for (node = T->head; node != NULL; node = node->next) if (bound < node->bound) bound = node->bound; xassert(bound != -DBL_MAX); eps = 0.001 * (1.0 + fabs(bound)); for (node = T->head; node != NULL; node = node->next) { if (node->bound >= bound - eps) { xassert(node->up != NULL); if (best == NULL || #if 1 best->up->ii_sum > node->up->ii_sum) best = node; #else best->lp_obj < node->lp_obj) best = node; #endif } } break; default: xassert(T != T); } xassert(best != NULL); return best->p; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpbfx.h0000644000076500000240000000455513524616144025043 0ustar tamasstaff00000000000000/* glpbfx.h (basis factorization interface, bignum arithmetic) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPBFX_H #define GLPBFX_H #include "glpgmp.h" #ifndef GLPBFX_DEFINED #define GLPBFX_DEFINED typedef struct { double _opaque_bfx; } BFX; #endif #define bfx_create_binv _glp_bfx_create_binv #define bfx_is_valid _glp_bfx_is_valid #define bfx_invalidate _glp_bfx_invalidate #define bfx_factorize _glp_bfx_factorize #define bfx_ftran _glp_bfx_ftran #define bfx_btran _glp_bfx_btran #define bfx_update _glp_bfx_update #define bfx_delete_binv _glp_bfx_delete_binv BFX *bfx_create_binv(void); /* create factorization of the basis matrix */ int bfx_is_valid(BFX *binv); /* check if factorization is valid */ void bfx_invalidate(BFX *binv); /* invalidate factorization of the basis matrix */ int bfx_factorize(BFX *binv, int m, int (*col)(void *info, int j, int ind[], mpq_t val[]), void *info); /* compute factorization of the basis matrix */ void bfx_ftran(BFX *binv, mpq_t x[], int save); /* perform forward transformation (FTRAN) */ void bfx_btran(BFX *binv, mpq_t x[]); /* perform backward transformation (BTRAN) */ int bfx_update(BFX *binv, int j); /* update factorization of the basis matrix */ void bfx_delete_binv(BFX *binv); /* delete factorization of the basis matrix */ #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpmpl.h0000644000076500000240000025714713524616144025063 0ustar tamasstaff00000000000000/* glpmpl.h (GNU MathProg translator) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPMPL_H #define GLPMPL_H #include "glpavl.h" #include "glprng.h" typedef struct MPL MPL; typedef char STRING; typedef struct SYMBOL SYMBOL; typedef struct TUPLE TUPLE; typedef struct ARRAY ELEMSET; typedef struct ELEMVAR ELEMVAR; typedef struct FORMULA FORMULA; typedef struct ELEMCON ELEMCON; typedef union VALUE VALUE; typedef struct ARRAY ARRAY; typedef struct MEMBER MEMBER; #if 1 /* many C compilers have DOMAIN declared in :( */ #undef DOMAIN #define DOMAIN DOMAIN1 #endif typedef struct DOMAIN DOMAIN; typedef struct DOMAIN_BLOCK DOMAIN_BLOCK; typedef struct DOMAIN_SLOT DOMAIN_SLOT; typedef struct SET SET; typedef struct WITHIN WITHIN; typedef struct GADGET GADGET; typedef struct PARAMETER PARAMETER; typedef struct CONDITION CONDITION; typedef struct VARIABLE VARIABLE; typedef struct CONSTRAINT CONSTRAINT; typedef struct TABLE TABLE; typedef struct TABARG TABARG; typedef struct TABFLD TABFLD; typedef struct TABIN TABIN; typedef struct TABOUT TABOUT; typedef struct TABDCA TABDCA; typedef union OPERANDS OPERANDS; typedef struct ARG_LIST ARG_LIST; typedef struct CODE CODE; typedef struct CHECK CHECK; typedef struct DISPLAY DISPLAY; typedef struct DISPLAY1 DISPLAY1; typedef struct PRINTF PRINTF; typedef struct PRINTF1 PRINTF1; typedef struct FOR FOR; typedef struct STATEMENT STATEMENT; typedef struct TUPLE SLICE; /**********************************************************************/ /* * * TRANSLATOR DATABASE * * */ /**********************************************************************/ #define A_BINARY 101 /* something binary */ #define A_CHECK 102 /* check statement */ #define A_CONSTRAINT 103 /* model constraint */ #define A_DISPLAY 104 /* display statement */ #define A_ELEMCON 105 /* elemental constraint/objective */ #define A_ELEMSET 106 /* elemental set */ #define A_ELEMVAR 107 /* elemental variable */ #define A_EXPRESSION 108 /* expression */ #define A_FOR 109 /* for statement */ #define A_FORMULA 110 /* formula */ #define A_INDEX 111 /* dummy index */ #define A_INPUT 112 /* input table */ #define A_INTEGER 113 /* something integer */ #define A_LOGICAL 114 /* something logical */ #define A_MAXIMIZE 115 /* objective has to be maximized */ #define A_MINIMIZE 116 /* objective has to be minimized */ #define A_NONE 117 /* nothing */ #define A_NUMERIC 118 /* something numeric */ #define A_OUTPUT 119 /* output table */ #define A_PARAMETER 120 /* model parameter */ #define A_PRINTF 121 /* printf statement */ #define A_SET 122 /* model set */ #define A_SOLVE 123 /* solve statement */ #define A_SYMBOLIC 124 /* something symbolic */ #define A_TABLE 125 /* data table */ #define A_TUPLE 126 /* n-tuple */ #define A_VARIABLE 127 /* model variable */ #define MAX_LENGTH 100 /* maximal length of any symbolic value (this includes symbolic names, numeric and string literals, and all symbolic values that may appear during the evaluation phase) */ #define CONTEXT_SIZE 60 /* size of the context queue, in characters */ #define OUTBUF_SIZE 1024 /* size of the output buffer, in characters */ struct MPL { /* translator database */ /*--------------------------------------------------------------*/ /* scanning segment */ int line; /* number of the current text line */ int c; /* the current character or EOF */ int token; /* the current token: */ #define T_EOF 201 /* end of file */ #define T_NAME 202 /* symbolic name (model section only) */ #define T_SYMBOL 203 /* symbol (data section only) */ #define T_NUMBER 204 /* numeric literal */ #define T_STRING 205 /* string literal */ #define T_AND 206 /* and && */ #define T_BY 207 /* by */ #define T_CROSS 208 /* cross */ #define T_DIFF 209 /* diff */ #define T_DIV 210 /* div */ #define T_ELSE 211 /* else */ #define T_IF 212 /* if */ #define T_IN 213 /* in */ #define T_INFINITY 214 /* Infinity */ #define T_INTER 215 /* inter */ #define T_LESS 216 /* less */ #define T_MOD 217 /* mod */ #define T_NOT 218 /* not ! */ #define T_OR 219 /* or || */ #define T_SPTP 220 /* s.t. */ #define T_SYMDIFF 221 /* symdiff */ #define T_THEN 222 /* then */ #define T_UNION 223 /* union */ #define T_WITHIN 224 /* within */ #define T_PLUS 225 /* + */ #define T_MINUS 226 /* - */ #define T_ASTERISK 227 /* * */ #define T_SLASH 228 /* / */ #define T_POWER 229 /* ^ ** */ #define T_LT 230 /* < */ #define T_LE 231 /* <= */ #define T_EQ 232 /* = == */ #define T_GE 233 /* >= */ #define T_GT 234 /* > */ #define T_NE 235 /* <> != */ #define T_CONCAT 236 /* & */ #define T_BAR 237 /* | */ #define T_POINT 238 /* . */ #define T_COMMA 239 /* , */ #define T_COLON 240 /* : */ #define T_SEMICOLON 241 /* ; */ #define T_ASSIGN 242 /* := */ #define T_DOTS 243 /* .. */ #define T_LEFT 244 /* ( */ #define T_RIGHT 245 /* ) */ #define T_LBRACKET 246 /* [ */ #define T_RBRACKET 247 /* ] */ #define T_LBRACE 248 /* { */ #define T_RBRACE 249 /* } */ #define T_APPEND 250 /* >> */ #define T_TILDE 251 /* ~ */ #define T_INPUT 252 /* <- */ int imlen; /* length of the current token */ char *image; /* char image[MAX_LENGTH+1]; */ /* image of the current token */ double value; /* value of the current token (for T_NUMBER only) */ int b_token; /* the previous token */ int b_imlen; /* length of the previous token */ char *b_image; /* char b_image[MAX_LENGTH+1]; */ /* image of the previous token */ double b_value; /* value of the previous token (if token is T_NUMBER) */ int f_dots; /* if this flag is set, the next token should be recognized as T_DOTS, not as T_POINT */ int f_scan; /* if this flag is set, the next token is already scanned */ int f_token; /* the next token */ int f_imlen; /* length of the next token */ char *f_image; /* char f_image[MAX_LENGTH+1]; */ /* image of the next token */ double f_value; /* value of the next token (if token is T_NUMBER) */ char *context; /* char context[CONTEXT_SIZE]; */ /* context circular queue (not null-terminated!) */ int c_ptr; /* pointer to the current position in the context queue */ int flag_d; /* if this flag is set, the data section is being processed */ /*--------------------------------------------------------------*/ /* translating segment */ DMP *pool; /* memory pool used to allocate all data instances created during the translation phase */ AVL *tree; /* symbolic name table: node.type = A_INDEX => node.link -> DOMAIN_SLOT node.type = A_SET => node.link -> SET node.type = A_PARAMETER => node.link -> PARAMETER node.type = A_VARIABLE => node.link -> VARIABLE node.type = A_CONSTRANT => node.link -> CONSTRAINT */ STATEMENT *model; /* linked list of model statements in the original order */ int flag_x; /* if this flag is set, the current token being left parenthesis begins a slice that allows recognizing any undeclared symbolic names as dummy indices; this flag is automatically reset once the next token has been scanned */ int as_within; /* the warning "in understood as within" has been issued */ int as_in; /* the warning "within understood as in" has been issued */ int as_binary; /* the warning "logical understood as binary" has been issued */ int flag_s; /* if this flag is set, the solve statement has been parsed */ /*--------------------------------------------------------------*/ /* common segment */ DMP *strings; /* memory pool to allocate STRING data structures */ DMP *symbols; /* memory pool to allocate SYMBOL data structures */ DMP *tuples; /* memory pool to allocate TUPLE data structures */ DMP *arrays; /* memory pool to allocate ARRAY data structures */ DMP *members; /* memory pool to allocate MEMBER data structures */ DMP *elemvars; /* memory pool to allocate ELEMVAR data structures */ DMP *formulae; /* memory pool to allocate FORMULA data structures */ DMP *elemcons; /* memory pool to allocate ELEMCON data structures */ ARRAY *a_list; /* linked list of all arrays in the database */ char *sym_buf; /* char sym_buf[255+1]; */ /* working buffer used by the routine format_symbol */ char *tup_buf; /* char tup_buf[255+1]; */ /* working buffer used by the routine format_tuple */ /*--------------------------------------------------------------*/ /* generating/postsolving segment */ RNG *rand; /* pseudo-random number generator */ int flag_p; /* if this flag is set, the postsolving phase is in effect */ STATEMENT *stmt; /* model statement being currently executed */ TABDCA *dca; /* pointer to table driver communication area for table statement currently executed */ int m; /* number of rows in the problem, m >= 0 */ int n; /* number of columns in the problem, n >= 0 */ ELEMCON **row; /* ELEMCON *row[1+m]; */ /* row[0] is not used; row[i] is elemental constraint or objective, which corresponds to i-th row of the problem, 1 <= i <= m */ ELEMVAR **col; /* ELEMVAR *col[1+n]; */ /* col[0] is not used; col[j] is elemental variable, which corresponds to j-th column of the problem, 1 <= j <= n */ /*--------------------------------------------------------------*/ /* input/output segment */ XFILE *in_fp; /* stream assigned to the input text file */ char *in_file; /* name of the input text file */ XFILE *out_fp; /* stream assigned to the output text file used to write all data produced by display and printf statements; NULL means the data should be sent to stdout via the routine xprintf */ char *out_file; /* name of the output text file */ #if 0 /* 08/XI-2009 */ char *out_buf; /* char out_buf[OUTBUF_SIZE] */ /* buffer to accumulate output data */ int out_cnt; /* count of data bytes stored in the output buffer */ #endif XFILE *prt_fp; /* stream assigned to the print text file; may be NULL */ char *prt_file; /* name of the output print file */ /*--------------------------------------------------------------*/ /* solver interface segment */ jmp_buf jump; /* jump address for non-local go to in case of error */ int phase; /* phase of processing: 0 - database is being or has been initialized 1 - model section is being or has been read 2 - data section is being or has been read 3 - model is being or has been generated/postsolved 4 - model processing error has occurred */ char *mod_file; /* name of the input text file, which contains model section */ char *mpl_buf; /* char mpl_buf[255+1]; */ /* working buffer used by some interface routines */ }; /**********************************************************************/ /* * * PROCESSING MODEL SECTION * * */ /**********************************************************************/ #define alloc(type) ((type *)dmp_get_atomv(mpl->pool, sizeof(type))) /* allocate atom of given type */ #define enter_context _glp_mpl_enter_context void enter_context(MPL *mpl); /* enter current token into context queue */ #define print_context _glp_mpl_print_context void print_context(MPL *mpl); /* print current content of context queue */ #define get_char _glp_mpl_get_char void get_char(MPL *mpl); /* scan next character from input text file */ #define append_char _glp_mpl_append_char void append_char(MPL *mpl); /* append character to current token */ #define get_token _glp_mpl_get_token void get_token(MPL *mpl); /* scan next token from input text file */ #define unget_token _glp_mpl_unget_token void unget_token(MPL *mpl); /* return current token back to input stream */ #define is_keyword _glp_mpl_is_keyword int is_keyword(MPL *mpl, char *keyword); /* check if current token is given non-reserved keyword */ #define is_reserved _glp_mpl_is_reserved int is_reserved(MPL *mpl); /* check if current token is reserved keyword */ #define make_code _glp_mpl_make_code CODE *make_code(MPL *mpl, int op, OPERANDS *arg, int type, int dim); /* generate pseudo-code (basic routine) */ #define make_unary _glp_mpl_make_unary CODE *make_unary(MPL *mpl, int op, CODE *x, int type, int dim); /* generate pseudo-code for unary operation */ #define make_binary _glp_mpl_make_binary CODE *make_binary(MPL *mpl, int op, CODE *x, CODE *y, int type, int dim); /* generate pseudo-code for binary operation */ #define make_ternary _glp_mpl_make_ternary CODE *make_ternary(MPL *mpl, int op, CODE *x, CODE *y, CODE *z, int type, int dim); /* generate pseudo-code for ternary operation */ #define numeric_literal _glp_mpl_numeric_literal CODE *numeric_literal(MPL *mpl); /* parse reference to numeric literal */ #define string_literal _glp_mpl_string_literal CODE *string_literal(MPL *mpl); /* parse reference to string literal */ #define create_arg_list _glp_mpl_create_arg_list ARG_LIST *create_arg_list(MPL *mpl); /* create empty operands list */ #define expand_arg_list _glp_mpl_expand_arg_list ARG_LIST *expand_arg_list(MPL *mpl, ARG_LIST *list, CODE *x); /* append operand to operands list */ #define arg_list_len _glp_mpl_arg_list_len int arg_list_len(MPL *mpl, ARG_LIST *list); /* determine length of operands list */ #define subscript_list _glp_mpl_subscript_list ARG_LIST *subscript_list(MPL *mpl); /* parse subscript list */ #define object_reference _glp_mpl_object_reference CODE *object_reference(MPL *mpl); /* parse reference to named object */ #define numeric_argument _glp_mpl_numeric_argument CODE *numeric_argument(MPL *mpl, char *func); /* parse argument passed to built-in function */ #define symbolic_argument _glp_mpl_symbolic_argument CODE *symbolic_argument(MPL *mpl, char *func); #define elemset_argument _glp_mpl_elemset_argument CODE *elemset_argument(MPL *mpl, char *func); #define function_reference _glp_mpl_function_reference CODE *function_reference(MPL *mpl); /* parse reference to built-in function */ #define create_domain _glp_mpl_create_domain DOMAIN *create_domain(MPL *mpl); /* create empty domain */ #define create_block _glp_mpl_create_block DOMAIN_BLOCK *create_block(MPL *mpl); /* create empty domain block */ #define append_block _glp_mpl_append_block void append_block(MPL *mpl, DOMAIN *domain, DOMAIN_BLOCK *block); /* append domain block to specified domain */ #define append_slot _glp_mpl_append_slot DOMAIN_SLOT *append_slot(MPL *mpl, DOMAIN_BLOCK *block, char *name, CODE *code); /* create and append new slot to domain block */ #define expression_list _glp_mpl_expression_list CODE *expression_list(MPL *mpl); /* parse expression list */ #define literal_set _glp_mpl_literal_set CODE *literal_set(MPL *mpl, CODE *code); /* parse literal set */ #define indexing_expression _glp_mpl_indexing_expression DOMAIN *indexing_expression(MPL *mpl); /* parse indexing expression */ #define close_scope _glp_mpl_close_scope void close_scope(MPL *mpl, DOMAIN *domain); /* close scope of indexing expression */ #define iterated_expression _glp_mpl_iterated_expression CODE *iterated_expression(MPL *mpl); /* parse iterated expression */ #define domain_arity _glp_mpl_domain_arity int domain_arity(MPL *mpl, DOMAIN *domain); /* determine arity of domain */ #define set_expression _glp_mpl_set_expression CODE *set_expression(MPL *mpl); /* parse set expression */ #define branched_expression _glp_mpl_branched_expression CODE *branched_expression(MPL *mpl); /* parse conditional expression */ #define primary_expression _glp_mpl_primary_expression CODE *primary_expression(MPL *mpl); /* parse primary expression */ #define error_preceding _glp_mpl_error_preceding void error_preceding(MPL *mpl, char *opstr); /* raise error if preceding operand has wrong type */ #define error_following _glp_mpl_error_following void error_following(MPL *mpl, char *opstr); /* raise error if following operand has wrong type */ #define error_dimension _glp_mpl_error_dimension void error_dimension(MPL *mpl, char *opstr, int dim1, int dim2); /* raise error if operands have different dimension */ #define expression_0 _glp_mpl_expression_0 CODE *expression_0(MPL *mpl); /* parse expression of level 0 */ #define expression_1 _glp_mpl_expression_1 CODE *expression_1(MPL *mpl); /* parse expression of level 1 */ #define expression_2 _glp_mpl_expression_2 CODE *expression_2(MPL *mpl); /* parse expression of level 2 */ #define expression_3 _glp_mpl_expression_3 CODE *expression_3(MPL *mpl); /* parse expression of level 3 */ #define expression_4 _glp_mpl_expression_4 CODE *expression_4(MPL *mpl); /* parse expression of level 4 */ #define expression_5 _glp_mpl_expression_5 CODE *expression_5(MPL *mpl); /* parse expression of level 5 */ #define expression_6 _glp_mpl_expression_6 CODE *expression_6(MPL *mpl); /* parse expression of level 6 */ #define expression_7 _glp_mpl_expression_7 CODE *expression_7(MPL *mpl); /* parse expression of level 7 */ #define expression_8 _glp_mpl_expression_8 CODE *expression_8(MPL *mpl); /* parse expression of level 8 */ #define expression_9 _glp_mpl_expression_9 CODE *expression_9(MPL *mpl); /* parse expression of level 9 */ #define expression_10 _glp_mpl_expression_10 CODE *expression_10(MPL *mpl); /* parse expression of level 10 */ #define expression_11 _glp_mpl_expression_11 CODE *expression_11(MPL *mpl); /* parse expression of level 11 */ #define expression_12 _glp_mpl_expression_12 CODE *expression_12(MPL *mpl); /* parse expression of level 12 */ #define expression_13 _glp_mpl_expression_13 CODE *expression_13(MPL *mpl); /* parse expression of level 13 */ #define set_statement _glp_mpl_set_statement SET *set_statement(MPL *mpl); /* parse set statement */ #define parameter_statement _glp_mpl_parameter_statement PARAMETER *parameter_statement(MPL *mpl); /* parse parameter statement */ #define variable_statement _glp_mpl_variable_statement VARIABLE *variable_statement(MPL *mpl); /* parse variable statement */ #define constraint_statement _glp_mpl_constraint_statement CONSTRAINT *constraint_statement(MPL *mpl); /* parse constraint statement */ #define objective_statement _glp_mpl_objective_statement CONSTRAINT *objective_statement(MPL *mpl); /* parse objective statement */ #define table_statement _glp_mpl_table_statement TABLE *table_statement(MPL *mpl); /* parse table statement */ #define solve_statement _glp_mpl_solve_statement void *solve_statement(MPL *mpl); /* parse solve statement */ #define check_statement _glp_mpl_check_statement CHECK *check_statement(MPL *mpl); /* parse check statement */ #define display_statement _glp_mpl_display_statement DISPLAY *display_statement(MPL *mpl); /* parse display statement */ #define printf_statement _glp_mpl_printf_statement PRINTF *printf_statement(MPL *mpl); /* parse printf statement */ #define for_statement _glp_mpl_for_statement FOR *for_statement(MPL *mpl); /* parse for statement */ #define end_statement _glp_mpl_end_statement void end_statement(MPL *mpl); /* parse end statement */ #define simple_statement _glp_mpl_simple_statement STATEMENT *simple_statement(MPL *mpl, int spec); /* parse simple statement */ #define model_section _glp_mpl_model_section void model_section(MPL *mpl); /* parse model section */ /**********************************************************************/ /* * * PROCESSING DATA SECTION * * */ /**********************************************************************/ #if 2 + 2 == 5 struct SLICE /* see TUPLE */ { /* component of slice; the slice itself is associated with its first component; slices are similar to n-tuples with exception that some slice components (which are indicated by asterisks) don't refer to any symbols */ SYMBOL *sym; /* symbol, which this component refers to; can be NULL */ SLICE *next; /* the next component of slice */ }; #endif #define create_slice _glp_mpl_create_slice SLICE *create_slice(MPL *mpl); /* create slice */ #define expand_slice _glp_mpl_expand_slice SLICE *expand_slice ( MPL *mpl, SLICE *slice, /* destroyed */ SYMBOL *sym /* destroyed */ ); /* append new component to slice */ #define slice_dimen _glp_mpl_slice_dimen int slice_dimen ( MPL *mpl, SLICE *slice /* not changed */ ); /* determine dimension of slice */ #define slice_arity _glp_mpl_slice_arity int slice_arity ( MPL *mpl, SLICE *slice /* not changed */ ); /* determine arity of slice */ #define fake_slice _glp_mpl_fake_slice SLICE *fake_slice(MPL *mpl, int dim); /* create fake slice of all asterisks */ #define delete_slice _glp_mpl_delete_slice void delete_slice ( MPL *mpl, SLICE *slice /* destroyed */ ); /* delete slice */ #define is_number _glp_mpl_is_number int is_number(MPL *mpl); /* check if current token is number */ #define is_symbol _glp_mpl_is_symbol int is_symbol(MPL *mpl); /* check if current token is symbol */ #define is_literal _glp_mpl_is_literal int is_literal(MPL *mpl, char *literal); /* check if current token is given symbolic literal */ #define read_number _glp_mpl_read_number double read_number(MPL *mpl); /* read number */ #define read_symbol _glp_mpl_read_symbol SYMBOL *read_symbol(MPL *mpl); /* read symbol */ #define read_slice _glp_mpl_read_slice SLICE *read_slice ( MPL *mpl, char *name, /* not changed */ int dim ); /* read slice */ #define select_set _glp_mpl_select_set SET *select_set ( MPL *mpl, char *name /* not changed */ ); /* select set to saturate it with elemental sets */ #define simple_format _glp_mpl_simple_format void simple_format ( MPL *mpl, SET *set, /* not changed */ MEMBER *memb, /* modified */ SLICE *slice /* not changed */ ); /* read set data block in simple format */ #define matrix_format _glp_mpl_matrix_format void matrix_format ( MPL *mpl, SET *set, /* not changed */ MEMBER *memb, /* modified */ SLICE *slice, /* not changed */ int tr ); /* read set data block in matrix format */ #define set_data _glp_mpl_set_data void set_data(MPL *mpl); /* read set data */ #define select_parameter _glp_mpl_select_parameter PARAMETER *select_parameter ( MPL *mpl, char *name /* not changed */ ); /* select parameter to saturate it with data */ #define set_default _glp_mpl_set_default void set_default ( MPL *mpl, PARAMETER *par, /* not changed */ SYMBOL *altval /* destroyed */ ); /* set default parameter value */ #define read_value _glp_mpl_read_value MEMBER *read_value ( MPL *mpl, PARAMETER *par, /* not changed */ TUPLE *tuple /* destroyed */ ); /* read value and assign it to parameter member */ #define plain_format _glp_mpl_plain_format void plain_format ( MPL *mpl, PARAMETER *par, /* not changed */ SLICE *slice /* not changed */ ); /* read parameter data block in plain format */ #define tabular_format _glp_mpl_tabular_format void tabular_format ( MPL *mpl, PARAMETER *par, /* not changed */ SLICE *slice, /* not changed */ int tr ); /* read parameter data block in tabular format */ #define tabbing_format _glp_mpl_tabbing_format void tabbing_format ( MPL *mpl, SYMBOL *altval /* not changed */ ); /* read parameter data block in tabbing format */ #define parameter_data _glp_mpl_parameter_data void parameter_data(MPL *mpl); /* read parameter data */ #define data_section _glp_mpl_data_section void data_section(MPL *mpl); /* read data section */ /**********************************************************************/ /* * * FLOATING-POINT NUMBERS * * */ /**********************************************************************/ #define fp_add _glp_mpl_fp_add double fp_add(MPL *mpl, double x, double y); /* floating-point addition */ #define fp_sub _glp_mpl_fp_sub double fp_sub(MPL *mpl, double x, double y); /* floating-point subtraction */ #define fp_less _glp_mpl_fp_less double fp_less(MPL *mpl, double x, double y); /* floating-point non-negative subtraction */ #define fp_mul _glp_mpl_fp_mul double fp_mul(MPL *mpl, double x, double y); /* floating-point multiplication */ #define fp_div _glp_mpl_fp_div double fp_div(MPL *mpl, double x, double y); /* floating-point division */ #define fp_idiv _glp_mpl_fp_idiv double fp_idiv(MPL *mpl, double x, double y); /* floating-point quotient of exact division */ #define fp_mod _glp_mpl_fp_mod double fp_mod(MPL *mpl, double x, double y); /* floating-point remainder of exact division */ #define fp_power _glp_mpl_fp_power double fp_power(MPL *mpl, double x, double y); /* floating-point exponentiation (raise to power) */ #define fp_exp _glp_mpl_fp_exp double fp_exp(MPL *mpl, double x); /* floating-point base-e exponential */ #define fp_log _glp_mpl_fp_log double fp_log(MPL *mpl, double x); /* floating-point natural logarithm */ #define fp_log10 _glp_mpl_fp_log10 double fp_log10(MPL *mpl, double x); /* floating-point common (decimal) logarithm */ #define fp_sqrt _glp_mpl_fp_sqrt double fp_sqrt(MPL *mpl, double x); /* floating-point square root */ #define fp_sin _glp_mpl_fp_sin double fp_sin(MPL *mpl, double x); /* floating-point trigonometric sine */ #define fp_cos _glp_mpl_fp_cos double fp_cos(MPL *mpl, double x); /* floating-point trigonometric cosine */ #define fp_atan _glp_mpl_fp_atan double fp_atan(MPL *mpl, double x); /* floating-point trigonometric arctangent */ #define fp_atan2 _glp_mpl_fp_atan2 double fp_atan2(MPL *mpl, double y, double x); /* floating-point trigonometric arctangent */ #define fp_round _glp_mpl_fp_round double fp_round(MPL *mpl, double x, double n); /* round floating-point value to n fractional digits */ #define fp_trunc _glp_mpl_fp_trunc double fp_trunc(MPL *mpl, double x, double n); /* truncate floating-point value to n fractional digits */ /**********************************************************************/ /* * * PSEUDO-RANDOM NUMBER GENERATORS * * */ /**********************************************************************/ #define fp_irand224 _glp_mpl_fp_irand224 double fp_irand224(MPL *mpl); /* pseudo-random integer in the range [0, 2^24) */ #define fp_uniform01 _glp_mpl_fp_uniform01 double fp_uniform01(MPL *mpl); /* pseudo-random number in the range [0, 1) */ #define fp_uniform _glp_mpl_uniform double fp_uniform(MPL *mpl, double a, double b); /* pseudo-random number in the range [a, b) */ #define fp_normal01 _glp_mpl_fp_normal01 double fp_normal01(MPL *mpl); /* Gaussian random variate with mu = 0 and sigma = 1 */ #define fp_normal _glp_mpl_fp_normal double fp_normal(MPL *mpl, double mu, double sigma); /* Gaussian random variate with specified mu and sigma */ /**********************************************************************/ /* * * DATE/TIME * * */ /**********************************************************************/ #define fn_gmtime _glp_mpl_fn_gmtime double fn_gmtime(MPL *mpl); /* obtain the current calendar time (UTC) */ #define fn_str2time _glp_mpl_fn_str2time double fn_str2time(MPL *mpl, const char *str, const char *fmt); /* convert character string to the calendar time */ #define fn_time2str _glp_mpl_fn_time2str void fn_time2str(MPL *mpl, char *str, double t, const char *fmt); /* convert the calendar time to character string */ /**********************************************************************/ /* * * CHARACTER STRINGS * * */ /**********************************************************************/ #define create_string _glp_mpl_create_string STRING *create_string ( MPL *mpl, char buf[MAX_LENGTH+1] /* not changed */ ); /* create character string */ #define copy_string _glp_mpl_copy_string STRING *copy_string ( MPL *mpl, STRING *str /* not changed */ ); /* make copy of character string */ #define compare_strings _glp_mpl_compare_strings int compare_strings ( MPL *mpl, STRING *str1, /* not changed */ STRING *str2 /* not changed */ ); /* compare one character string with another */ #define fetch_string _glp_mpl_fetch_string char *fetch_string ( MPL *mpl, STRING *str, /* not changed */ char buf[MAX_LENGTH+1] /* modified */ ); /* extract content of character string */ #define delete_string _glp_mpl_delete_string void delete_string ( MPL *mpl, STRING *str /* destroyed */ ); /* delete character string */ /**********************************************************************/ /* * * SYMBOLS * * */ /**********************************************************************/ struct SYMBOL { /* symbol (numeric or abstract quantity) */ double num; /* numeric value of symbol (used only if str == NULL) */ STRING *str; /* abstract value of symbol (used only if str != NULL) */ }; #define create_symbol_num _glp_mpl_create_symbol_num SYMBOL *create_symbol_num(MPL *mpl, double num); /* create symbol of numeric type */ #define create_symbol_str _glp_mpl_create_symbol_str SYMBOL *create_symbol_str ( MPL *mpl, STRING *str /* destroyed */ ); /* create symbol of abstract type */ #define copy_symbol _glp_mpl_copy_symbol SYMBOL *copy_symbol ( MPL *mpl, SYMBOL *sym /* not changed */ ); /* make copy of symbol */ #define compare_symbols _glp_mpl_compare_symbols int compare_symbols ( MPL *mpl, SYMBOL *sym1, /* not changed */ SYMBOL *sym2 /* not changed */ ); /* compare one symbol with another */ #define delete_symbol _glp_mpl_delete_symbol void delete_symbol ( MPL *mpl, SYMBOL *sym /* destroyed */ ); /* delete symbol */ #define format_symbol _glp_mpl_format_symbol char *format_symbol ( MPL *mpl, SYMBOL *sym /* not changed */ ); /* format symbol for displaying or printing */ #define concat_symbols _glp_mpl_concat_symbols SYMBOL *concat_symbols ( MPL *mpl, SYMBOL *sym1, /* destroyed */ SYMBOL *sym2 /* destroyed */ ); /* concatenate one symbol with another */ /**********************************************************************/ /* * * N-TUPLES * * */ /**********************************************************************/ struct TUPLE { /* component of n-tuple; the n-tuple itself is associated with its first component; (note that 0-tuple has no components) */ SYMBOL *sym; /* symbol, which the component refers to; cannot be NULL */ TUPLE *next; /* the next component of n-tuple */ }; #define create_tuple _glp_mpl_create_tuple TUPLE *create_tuple(MPL *mpl); /* create n-tuple */ #define expand_tuple _glp_mpl_expand_tuple TUPLE *expand_tuple ( MPL *mpl, TUPLE *tuple, /* destroyed */ SYMBOL *sym /* destroyed */ ); /* append symbol to n-tuple */ #define tuple_dimen _glp_mpl_tuple_dimen int tuple_dimen ( MPL *mpl, TUPLE *tuple /* not changed */ ); /* determine dimension of n-tuple */ #define copy_tuple _glp_mpl_copy_tuple TUPLE *copy_tuple ( MPL *mpl, TUPLE *tuple /* not changed */ ); /* make copy of n-tuple */ #define compare_tuples _glp_mpl_compare_tuples int compare_tuples ( MPL *mpl, TUPLE *tuple1, /* not changed */ TUPLE *tuple2 /* not changed */ ); /* compare one n-tuple with another */ #define build_subtuple _glp_mpl_build_subtuple TUPLE *build_subtuple ( MPL *mpl, TUPLE *tuple, /* not changed */ int dim ); /* build subtuple of given n-tuple */ #define delete_tuple _glp_mpl_delete_tuple void delete_tuple ( MPL *mpl, TUPLE *tuple /* destroyed */ ); /* delete n-tuple */ #define format_tuple _glp_mpl_format_tuple char *format_tuple ( MPL *mpl, int c, TUPLE *tuple /* not changed */ ); /* format n-tuple for displaying or printing */ /**********************************************************************/ /* * * ELEMENTAL SETS * * */ /**********************************************************************/ #if 2 + 2 == 5 struct ELEMSET /* see ARRAY */ { /* elemental set of n-tuples; formally it is a "value" assigned to members of model sets (like numbers and symbols, which are values assigned to members of model parameters); note that a simple model set is not an elemental set, it is 0-dimensional array, the only member of which (if it exists) is assigned an elemental set */ #endif #define create_elemset _glp_mpl_create_elemset ELEMSET *create_elemset(MPL *mpl, int dim); /* create elemental set */ #define find_tuple _glp_mpl_find_tuple MEMBER *find_tuple ( MPL *mpl, ELEMSET *set, /* not changed */ TUPLE *tuple /* not changed */ ); /* check if elemental set contains given n-tuple */ #define add_tuple _glp_mpl_add_tuple MEMBER *add_tuple ( MPL *mpl, ELEMSET *set, /* modified */ TUPLE *tuple /* destroyed */ ); /* add new n-tuple to elemental set */ #define check_then_add _glp_mpl_check_then_add MEMBER *check_then_add ( MPL *mpl, ELEMSET *set, /* modified */ TUPLE *tuple /* destroyed */ ); /* check and add new n-tuple to elemental set */ #define copy_elemset _glp_mpl_copy_elemset ELEMSET *copy_elemset ( MPL *mpl, ELEMSET *set /* not changed */ ); /* make copy of elemental set */ #define delete_elemset _glp_mpl_delete_elemset void delete_elemset ( MPL *mpl, ELEMSET *set /* destroyed */ ); /* delete elemental set */ #define arelset_size _glp_mpl_arelset_size int arelset_size(MPL *mpl, double t0, double tf, double dt); /* compute size of "arithmetic" elemental set */ #define arelset_member _glp_mpl_arelset_member double arelset_member(MPL *mpl, double t0, double tf, double dt, int j); /* compute member of "arithmetic" elemental set */ #define create_arelset _glp_mpl_create_arelset ELEMSET *create_arelset(MPL *mpl, double t0, double tf, double dt); /* create "arithmetic" elemental set */ #define set_union _glp_mpl_set_union ELEMSET *set_union ( MPL *mpl, ELEMSET *X, /* destroyed */ ELEMSET *Y /* destroyed */ ); /* union of two elemental sets */ #define set_diff _glp_mpl_set_diff ELEMSET *set_diff ( MPL *mpl, ELEMSET *X, /* destroyed */ ELEMSET *Y /* destroyed */ ); /* difference between two elemental sets */ #define set_symdiff _glp_mpl_set_symdiff ELEMSET *set_symdiff ( MPL *mpl, ELEMSET *X, /* destroyed */ ELEMSET *Y /* destroyed */ ); /* symmetric difference between two elemental sets */ #define set_inter _glp_mpl_set_inter ELEMSET *set_inter ( MPL *mpl, ELEMSET *X, /* destroyed */ ELEMSET *Y /* destroyed */ ); /* intersection of two elemental sets */ #define set_cross _glp_mpl_set_cross ELEMSET *set_cross ( MPL *mpl, ELEMSET *X, /* destroyed */ ELEMSET *Y /* destroyed */ ); /* cross (Cartesian) product of two elemental sets */ /**********************************************************************/ /* * * ELEMENTAL VARIABLES * * */ /**********************************************************************/ struct ELEMVAR { /* elemental variable; formally it is a "value" assigned to members of model variables (like numbers and symbols, which are values assigned to members of model parameters) */ int j; /* LP column number assigned to this elemental variable */ VARIABLE *var; /* model variable, which contains this elemental variable */ MEMBER *memb; /* array member, which is assigned this elemental variable */ double lbnd; /* lower bound */ double ubnd; /* upper bound */ double temp; /* working quantity used in operations on linear forms; normally it contains floating-point zero */ #if 1 /* 15/V-2010 */ int stat; double prim, dual; /* solution components provided by the solver */ #endif }; /**********************************************************************/ /* * * LINEAR FORMS * * */ /**********************************************************************/ struct FORMULA { /* term of linear form c * x, where c is a coefficient, x is an elemental variable; the linear form itself is the sum of terms and is associated with its first term; (note that the linear form may be empty that means the sum is equal to zero) */ double coef; /* coefficient at elemental variable or constant term */ ELEMVAR *var; /* reference to elemental variable; NULL means constant term */ FORMULA *next; /* the next term of linear form */ }; #define constant_term _glp_mpl_constant_term FORMULA *constant_term(MPL *mpl, double coef); /* create constant term */ #define single_variable _glp_mpl_single_variable FORMULA *single_variable ( MPL *mpl, ELEMVAR *var /* referenced */ ); /* create single variable */ #define copy_formula _glp_mpl_copy_formula FORMULA *copy_formula ( MPL *mpl, FORMULA *form /* not changed */ ); /* make copy of linear form */ #define delete_formula _glp_mpl_delete_formula void delete_formula ( MPL *mpl, FORMULA *form /* destroyed */ ); /* delete linear form */ #define linear_comb _glp_mpl_linear_comb FORMULA *linear_comb ( MPL *mpl, double a, FORMULA *fx, /* destroyed */ double b, FORMULA *fy /* destroyed */ ); /* linear combination of two linear forms */ #define remove_constant _glp_mpl_remove_constant FORMULA *remove_constant ( MPL *mpl, FORMULA *form, /* destroyed */ double *coef /* modified */ ); /* remove constant term from linear form */ #define reduce_terms _glp_mpl_reduce_terms FORMULA *reduce_terms ( MPL *mpl, FORMULA *form /* destroyed */ ); /* reduce identical terms in linear form */ /**********************************************************************/ /* * * ELEMENTAL CONSTRAINTS * * */ /**********************************************************************/ struct ELEMCON { /* elemental constraint; formally it is a "value" assigned to members of model constraints (like numbers or symbols, which are values assigned to members of model parameters) */ int i; /* LP row number assigned to this elemental constraint */ CONSTRAINT *con; /* model constraint, which contains this elemental constraint */ MEMBER *memb; /* array member, which is assigned this elemental constraint */ FORMULA *form; /* linear form */ double lbnd; /* lower bound */ double ubnd; /* upper bound */ #if 1 /* 15/V-2010 */ int stat; double prim, dual; /* solution components provided by the solver */ #endif }; /**********************************************************************/ /* * * GENERIC VALUES * * */ /**********************************************************************/ union VALUE { /* generic value, which can be assigned to object member or be a result of evaluation of expression */ /* indicator that specifies the particular type of generic value is stored in the corresponding array or pseudo-code descriptor and can be one of the following: A_NONE - no value A_NUMERIC - floating-point number A_SYMBOLIC - symbol A_LOGICAL - logical value A_TUPLE - n-tuple A_ELEMSET - elemental set A_ELEMVAR - elemental variable A_FORMULA - linear form A_ELEMCON - elemental constraint */ void *none; /* null */ double num; /* value */ SYMBOL *sym; /* value */ int bit; /* value */ TUPLE *tuple; /* value */ ELEMSET *set; /* value */ ELEMVAR *var; /* reference */ FORMULA *form; /* value */ ELEMCON *con; /* reference */ }; #define delete_value _glp_mpl_delete_value void delete_value ( MPL *mpl, int type, VALUE *value /* content destroyed */ ); /* delete generic value */ /**********************************************************************/ /* * * SYMBOLICALLY INDEXED ARRAYS * * */ /**********************************************************************/ struct ARRAY { /* multi-dimensional array, a set of members indexed over simple or compound sets of symbols; arrays are used to represent the contents of model objects (i.e. sets, parameters, variables, constraints, and objectives); arrays also are used as "values" that are assigned to members of set objects, in which case the array itself represents an elemental set */ int type; /* type of generic values assigned to the array members: A_NONE - none (members have no assigned values) A_NUMERIC - floating-point numbers A_SYMBOLIC - symbols A_ELEMSET - elemental sets A_ELEMVAR - elemental variables A_ELEMCON - elemental constraints */ int dim; /* dimension of the array that determines number of components in n-tuples for all members of the array, dim >= 0; dim = 0 means the array is 0-dimensional */ int size; /* size of the array, i.e. number of its members */ MEMBER *head; /* the first array member; NULL means the array is empty */ MEMBER *tail; /* the last array member; NULL means the array is empty */ AVL *tree; /* the search tree intended to find array members for logarithmic time; NULL means the search tree doesn't exist */ ARRAY *prev; /* the previous array in the translator database */ ARRAY *next; /* the next array in the translator database */ }; struct MEMBER { /* array member */ TUPLE *tuple; /* n-tuple, which identifies the member; number of its components is the same for all members within the array and determined by the array dimension; duplicate members are not allowed */ MEMBER *next; /* the next array member */ VALUE value; /* generic value assigned to the member */ }; #define create_array _glp_mpl_create_array ARRAY *create_array(MPL *mpl, int type, int dim); /* create array */ #define find_member _glp_mpl_find_member MEMBER *find_member ( MPL *mpl, ARRAY *array, /* not changed */ TUPLE *tuple /* not changed */ ); /* find array member with given n-tuple */ #define add_member _glp_mpl_add_member MEMBER *add_member ( MPL *mpl, ARRAY *array, /* modified */ TUPLE *tuple /* destroyed */ ); /* add new member to array */ #define delete_array _glp_mpl_delete_array void delete_array ( MPL *mpl, ARRAY *array /* destroyed */ ); /* delete array */ /**********************************************************************/ /* * * DOMAINS AND DUMMY INDICES * * */ /**********************************************************************/ struct DOMAIN { /* domain (a simple or compound set); syntactically domain looks like '{ i in I, (j,k) in S, t in T : }'; domains are used to define sets, over which model objects are indexed, and also as constituents of iterated operators */ DOMAIN_BLOCK *list; /* linked list of domain blocks (in the example above such blocks are 'i in I', '(j,k) in S', and 't in T'); this list cannot be empty */ CODE *code; /* pseudo-code for computing the logical predicate, which follows the colon; NULL means no predicate is specified */ }; struct DOMAIN_BLOCK { /* domain block; syntactically domain blocks look like 'i in I', '(j,k) in S', and 't in T' in the example above (in the sequel sets like I, S, and T are called basic sets) */ DOMAIN_SLOT *list; /* linked list of domain slots (i.e. indexing positions); number of slots in this list is the same as dimension of n-tuples in the basic set; this list cannot be empty */ CODE *code; /* pseudo-code for computing basic set; cannot be NULL */ TUPLE *backup; /* if this n-tuple is not empty, current values of dummy indices in the domain block are the same as components of this n-tuple (note that this n-tuple may have larger dimension than number of dummy indices in this block, in which case extra components are ignored); this n-tuple is used to restore former values of dummy indices, if they were changed due to recursive calls to the domain block */ DOMAIN_BLOCK *next; /* the next block in the same domain */ }; struct DOMAIN_SLOT { /* domain slot; it specifies an individual indexing position and defines the corresponding dummy index */ char *name; /* symbolic name of the dummy index; null pointer means the dummy index is not explicitly specified */ CODE *code; /* pseudo-code for computing symbolic value, at which the dummy index is bound; NULL means the dummy index is free within the domain scope */ SYMBOL *value; /* current value assigned to the dummy index; NULL means no value is assigned at the moment */ CODE *list; /* linked list of pseudo-codes with operation O_INDEX referring to this slot; this linked list is used to invalidate resultant values of the operation, which depend on this dummy index */ DOMAIN_SLOT *next; /* the next slot in the same domain block */ }; #define assign_dummy_index _glp_mpl_assign_dummy_index void assign_dummy_index ( MPL *mpl, DOMAIN_SLOT *slot, /* modified */ SYMBOL *value /* not changed */ ); /* assign new value to dummy index */ #define update_dummy_indices _glp_mpl_update_dummy_indices void update_dummy_indices ( MPL *mpl, DOMAIN_BLOCK *block /* not changed */ ); /* update current values of dummy indices */ #define enter_domain_block _glp_mpl_enter_domain_block int enter_domain_block ( MPL *mpl, DOMAIN_BLOCK *block, /* not changed */ TUPLE *tuple, /* not changed */ void *info, void (*func)(MPL *mpl, void *info) ); /* enter domain block */ #define eval_within_domain _glp_mpl_eval_within_domain int eval_within_domain ( MPL *mpl, DOMAIN *domain, /* not changed */ TUPLE *tuple, /* not changed */ void *info, void (*func)(MPL *mpl, void *info) ); /* perform evaluation within domain scope */ #define loop_within_domain _glp_mpl_loop_within_domain void loop_within_domain ( MPL *mpl, DOMAIN *domain, /* not changed */ void *info, int (*func)(MPL *mpl, void *info) ); /* perform iterations within domain scope */ #define out_of_domain _glp_mpl_out_of_domain void out_of_domain ( MPL *mpl, char *name, /* not changed */ TUPLE *tuple /* not changed */ ); /* raise domain exception */ #define get_domain_tuple _glp_mpl_get_domain_tuple TUPLE *get_domain_tuple ( MPL *mpl, DOMAIN *domain /* not changed */ ); /* obtain current n-tuple from domain */ #define clean_domain _glp_mpl_clean_domain void clean_domain(MPL *mpl, DOMAIN *domain); /* clean domain */ /**********************************************************************/ /* * * MODEL SETS * * */ /**********************************************************************/ struct SET { /* model set */ char *name; /* symbolic name; cannot be NULL */ char *alias; /* alias; NULL means alias is not specified */ int dim; /* aka arity */ /* dimension (number of subscripts); dim = 0 means 0-dimensional (unsubscripted) set, dim > 0 means set of sets */ DOMAIN *domain; /* subscript domain; NULL for 0-dimensional set */ int dimen; /* dimension of n-tuples, which members of this set consist of (note that the model set itself is an array of elemental sets, which are its members; so, don't confuse this dimension with dimension of the model set); always non-zero */ WITHIN *within; /* list of supersets, which restrict each member of the set to be in every superset from this list; this list can be empty */ CODE *assign; /* pseudo-code for computing assigned value; can be NULL */ CODE *option; /* pseudo-code for computing default value; can be NULL */ GADGET *gadget; /* plain set used to initialize the array of sets; can be NULL */ int data; /* data status flag: 0 - no data are provided in the data section 1 - data are provided, but not checked yet 2 - data are provided and have been checked */ ARRAY *array; /* array of members, which are assigned elemental sets */ }; struct WITHIN { /* restricting superset list entry */ CODE *code; /* pseudo-code for computing the superset; cannot be NULL */ WITHIN *next; /* the next entry for the same set or parameter */ }; struct GADGET { /* plain set used to initialize the array of sets with data */ SET *set; /* pointer to plain set; cannot be NULL */ int ind[20]; /* ind[dim+dimen]; */ /* permutation of integers 1, 2, ..., dim+dimen */ }; #define check_elem_set _glp_mpl_check_elem_set void check_elem_set ( MPL *mpl, SET *set, /* not changed */ TUPLE *tuple, /* not changed */ ELEMSET *refer /* not changed */ ); /* check elemental set assigned to set member */ #define take_member_set _glp_mpl_take_member_set ELEMSET *take_member_set /* returns reference, not value */ ( MPL *mpl, SET *set, /* not changed */ TUPLE *tuple /* not changed */ ); /* obtain elemental set assigned to set member */ #define eval_member_set _glp_mpl_eval_member_set ELEMSET *eval_member_set /* returns reference, not value */ ( MPL *mpl, SET *set, /* not changed */ TUPLE *tuple /* not changed */ ); /* evaluate elemental set assigned to set member */ #define eval_whole_set _glp_mpl_eval_whole_set void eval_whole_set(MPL *mpl, SET *set); /* evaluate model set over entire domain */ #define clean_set _glp_mpl_clean_set void clean_set(MPL *mpl, SET *set); /* clean model set */ /**********************************************************************/ /* * * MODEL PARAMETERS * * */ /**********************************************************************/ struct PARAMETER { /* model parameter */ char *name; /* symbolic name; cannot be NULL */ char *alias; /* alias; NULL means alias is not specified */ int dim; /* aka arity */ /* dimension (number of subscripts); dim = 0 means 0-dimensional (unsubscripted) parameter */ DOMAIN *domain; /* subscript domain; NULL for 0-dimensional parameter */ int type; /* parameter type: A_NUMERIC - numeric A_INTEGER - integer A_BINARY - binary A_SYMBOLIC - symbolic */ CONDITION *cond; /* list of conditions, which restrict each parameter member to satisfy to every condition from this list; this list is used only for numeric parameters and can be empty */ WITHIN *in; /* list of supersets, which restrict each parameter member to be in every superset from this list; this list is used only for symbolic parameters and can be empty */ CODE *assign; /* pseudo-code for computing assigned value; can be NULL */ CODE *option; /* pseudo-code for computing default value; can be NULL */ int data; /* data status flag: 0 - no data are provided in the data section 1 - data are provided, but not checked yet 2 - data are provided and have been checked */ SYMBOL *defval; /* default value provided in the data section; can be NULL */ ARRAY *array; /* array of members, which are assigned numbers or symbols */ }; struct CONDITION { /* restricting condition list entry */ int rho; /* flag that specifies the form of the condition: O_LT - less than O_LE - less than or equal to O_EQ - equal to O_GE - greater than or equal to O_GT - greater than O_NE - not equal to */ CODE *code; /* pseudo-code for computing the reference value */ CONDITION *next; /* the next entry for the same parameter */ }; #define check_value_num _glp_mpl_check_value_num void check_value_num ( MPL *mpl, PARAMETER *par, /* not changed */ TUPLE *tuple, /* not changed */ double value ); /* check numeric value assigned to parameter member */ #define take_member_num _glp_mpl_take_member_num double take_member_num ( MPL *mpl, PARAMETER *par, /* not changed */ TUPLE *tuple /* not changed */ ); /* obtain numeric value assigned to parameter member */ #define eval_member_num _glp_mpl_eval_member_num double eval_member_num ( MPL *mpl, PARAMETER *par, /* not changed */ TUPLE *tuple /* not changed */ ); /* evaluate numeric value assigned to parameter member */ #define check_value_sym _glp_mpl_check_value_sym void check_value_sym ( MPL *mpl, PARAMETER *par, /* not changed */ TUPLE *tuple, /* not changed */ SYMBOL *value /* not changed */ ); /* check symbolic value assigned to parameter member */ #define take_member_sym _glp_mpl_take_member_sym SYMBOL *take_member_sym /* returns value, not reference */ ( MPL *mpl, PARAMETER *par, /* not changed */ TUPLE *tuple /* not changed */ ); /* obtain symbolic value assigned to parameter member */ #define eval_member_sym _glp_mpl_eval_member_sym SYMBOL *eval_member_sym /* returns value, not reference */ ( MPL *mpl, PARAMETER *par, /* not changed */ TUPLE *tuple /* not changed */ ); /* evaluate symbolic value assigned to parameter member */ #define eval_whole_par _glp_mpl_eval_whole_par void eval_whole_par(MPL *mpl, PARAMETER *par); /* evaluate model parameter over entire domain */ #define clean_parameter _glp_mpl_clean_parameter void clean_parameter(MPL *mpl, PARAMETER *par); /* clean model parameter */ /**********************************************************************/ /* * * MODEL VARIABLES * * */ /**********************************************************************/ struct VARIABLE { /* model variable */ char *name; /* symbolic name; cannot be NULL */ char *alias; /* alias; NULL means alias is not specified */ int dim; /* aka arity */ /* dimension (number of subscripts); dim = 0 means 0-dimensional (unsubscripted) variable */ DOMAIN *domain; /* subscript domain; NULL for 0-dimensional variable */ int type; /* variable type: A_NUMERIC - continuous A_INTEGER - integer A_BINARY - binary */ CODE *lbnd; /* pseudo-code for computing lower bound; NULL means lower bound is not specified */ CODE *ubnd; /* pseudo-code for computing upper bound; NULL means upper bound is not specified */ /* if both the pointers lbnd and ubnd refer to the same code, the variable is fixed at the corresponding value */ ARRAY *array; /* array of members, which are assigned elemental variables */ }; #define take_member_var _glp_mpl_take_member_var ELEMVAR *take_member_var /* returns reference */ ( MPL *mpl, VARIABLE *var, /* not changed */ TUPLE *tuple /* not changed */ ); /* obtain reference to elemental variable */ #define eval_member_var _glp_mpl_eval_member_var ELEMVAR *eval_member_var /* returns reference */ ( MPL *mpl, VARIABLE *var, /* not changed */ TUPLE *tuple /* not changed */ ); /* evaluate reference to elemental variable */ #define eval_whole_var _glp_mpl_eval_whole_var void eval_whole_var(MPL *mpl, VARIABLE *var); /* evaluate model variable over entire domain */ #define clean_variable _glp_mpl_clean_variable void clean_variable(MPL *mpl, VARIABLE *var); /* clean model variable */ /**********************************************************************/ /* * * MODEL CONSTRAINTS AND OBJECTIVES * * */ /**********************************************************************/ struct CONSTRAINT { /* model constraint or objective */ char *name; /* symbolic name; cannot be NULL */ char *alias; /* alias; NULL means alias is not specified */ int dim; /* aka arity */ /* dimension (number of subscripts); dim = 0 means 0-dimensional (unsubscripted) constraint */ DOMAIN *domain; /* subscript domain; NULL for 0-dimensional constraint */ int type; /* constraint type: A_CONSTRAINT - constraint A_MINIMIZE - objective (minimization) A_MAXIMIZE - objective (maximization) */ CODE *code; /* pseudo-code for computing main linear form; cannot be NULL */ CODE *lbnd; /* pseudo-code for computing lower bound; NULL means lower bound is not specified */ CODE *ubnd; /* pseudo-code for computing upper bound; NULL means upper bound is not specified */ /* if both the pointers lbnd and ubnd refer to the same code, the constraint has the form of equation */ ARRAY *array; /* array of members, which are assigned elemental constraints */ }; #define take_member_con _glp_mpl_take_member_con ELEMCON *take_member_con /* returns reference */ ( MPL *mpl, CONSTRAINT *con, /* not changed */ TUPLE *tuple /* not changed */ ); /* obtain reference to elemental constraint */ #define eval_member_con _glp_mpl_eval_member_con ELEMCON *eval_member_con /* returns reference */ ( MPL *mpl, CONSTRAINT *con, /* not changed */ TUPLE *tuple /* not changed */ ); /* evaluate reference to elemental constraint */ #define eval_whole_con _glp_mpl_eval_whole_con void eval_whole_con(MPL *mpl, CONSTRAINT *con); /* evaluate model constraint over entire domain */ #define clean_constraint _glp_mpl_clean_constraint void clean_constraint(MPL *mpl, CONSTRAINT *con); /* clean model constraint */ /**********************************************************************/ /* * * DATA TABLES * * */ /**********************************************************************/ struct TABLE { /* data table */ char *name; /* symbolic name; cannot be NULL */ char *alias; /* alias; NULL means alias is not specified */ int type; /* table type: A_INPUT - input table A_OUTPUT - output table */ TABARG *arg; /* argument list; cannot be empty */ union { struct { SET *set; /* input set; NULL means the set is not specified */ TABFLD *fld; /* field list; cannot be empty */ TABIN *list; /* input list; can be empty */ } in; struct { DOMAIN *domain; /* subscript domain; cannot be NULL */ TABOUT *list; /* output list; cannot be empty */ } out; } u; }; struct TABARG { /* table argument list entry */ CODE *code; /* pseudo-code for computing the argument */ TABARG *next; /* next entry for the same table */ }; struct TABFLD { /* table field list entry */ char *name; /* field name; cannot be NULL */ TABFLD *next; /* next entry for the same table */ }; struct TABIN { /* table input list entry */ PARAMETER *par; /* parameter to be read; cannot be NULL */ char *name; /* column name; cannot be NULL */ TABIN *next; /* next entry for the same table */ }; struct TABOUT { /* table output list entry */ CODE *code; /* pseudo-code for computing the value to be written */ char *name; /* column name; cannot be NULL */ TABOUT *next; /* next entry for the same table */ }; struct TABDCA { /* table driver communication area */ int id; /* driver identifier (set by mpl_tab_drv_open) */ void *link; /* driver link pointer (set by mpl_tab_drv_open) */ int na; /* number of arguments */ char **arg; /* char *arg[1+ns]; */ /* arg[k], 1 <= k <= ns, is pointer to k-th argument */ int nf; /* number of fields */ char **name; /* char *name[1+nc]; */ /* name[k], 1 <= k <= nc, is name of k-th field */ int *type; /* int type[1+nc]; */ /* type[k], 1 <= k <= nc, is type of k-th field: '?' - value not assigned 'N' - number 'S' - character string */ double *num; /* double num[1+nc]; */ /* num[k], 1 <= k <= nc, is numeric value of k-th field */ char **str; /* str[k], 1 <= k <= nc, is string value of k-th field */ }; #define mpl_tab_num_args _glp_mpl_tab_num_args int mpl_tab_num_args(TABDCA *dca); #define mpl_tab_get_arg _glp_mpl_tab_get_arg const char *mpl_tab_get_arg(TABDCA *dca, int k); #define mpl_tab_num_flds _glp_mpl_tab_num_flds int mpl_tab_num_flds(TABDCA *dca); #define mpl_tab_get_name _glp_mpl_tab_get_name const char *mpl_tab_get_name(TABDCA *dca, int k); #define mpl_tab_get_type _glp_mpl_tab_get_type int mpl_tab_get_type(TABDCA *dca, int k); #define mpl_tab_get_num _glp_mpl_tab_get_num double mpl_tab_get_num(TABDCA *dca, int k); #define mpl_tab_get_str _glp_mpl_tab_get_str const char *mpl_tab_get_str(TABDCA *dca, int k); #define mpl_tab_set_num _glp_mpl_tab_set_num void mpl_tab_set_num(TABDCA *dca, int k, double num); #define mpl_tab_set_str _glp_mpl_tab_set_str void mpl_tab_set_str(TABDCA *dca, int k, const char *str); #define mpl_tab_drv_open _glp_mpl_tab_drv_open void mpl_tab_drv_open(MPL *mpl, int mode); #define mpl_tab_drv_read _glp_mpl_tab_drv_read int mpl_tab_drv_read(MPL *mpl); #define mpl_tab_drv_write _glp_mpl_tab_drv_write void mpl_tab_drv_write(MPL *mpl); #define mpl_tab_drv_close _glp_mpl_tab_drv_close void mpl_tab_drv_close(MPL *mpl); /**********************************************************************/ /* * * PSEUDO-CODE * * */ /**********************************************************************/ union OPERANDS { /* operands that participate in pseudo-code operation (choice of particular operands depends on the operation code) */ /*--------------------------------------------------------------*/ double num; /* O_NUMBER */ /* floaing-point number to be taken */ /*--------------------------------------------------------------*/ char *str; /* O_STRING */ /* character string to be taken */ /*--------------------------------------------------------------*/ struct /* O_INDEX */ { DOMAIN_SLOT *slot; /* domain slot, which contains dummy index to be taken */ CODE *next; /* the next pseudo-code with op = O_INDEX, which refers to the same slot as this one; pointer to the beginning of this list is stored in the corresponding domain slot */ } index; /*--------------------------------------------------------------*/ struct /* O_MEMNUM, O_MEMSYM */ { PARAMETER *par; /* model parameter, which contains member to be taken */ ARG_LIST *list; /* list of subscripts; NULL for 0-dimensional parameter */ } par; /*--------------------------------------------------------------*/ struct /* O_MEMSET */ { SET *set; /* model set, which contains member to be taken */ ARG_LIST *list; /* list of subscripts; NULL for 0-dimensional set */ } set; /*--------------------------------------------------------------*/ struct /* O_MEMVAR */ { VARIABLE *var; /* model variable, which contains member to be taken */ ARG_LIST *list; /* list of subscripts; NULL for 0-dimensional variable */ #if 1 /* 15/V-2010 */ int suff; /* suffix specified: */ #define DOT_NONE 0x00 /* none (means variable itself) */ #define DOT_LB 0x01 /* .lb (lower bound) */ #define DOT_UB 0x02 /* .ub (upper bound) */ #define DOT_STATUS 0x03 /* .status (status) */ #define DOT_VAL 0x04 /* .val (primal value) */ #define DOT_DUAL 0x05 /* .dual (dual value) */ #endif } var; #if 1 /* 15/V-2010 */ /*--------------------------------------------------------------*/ struct /* O_MEMCON */ { CONSTRAINT *con; /* model constraint, which contains member to be taken */ ARG_LIST *list; /* list of subscripys; NULL for 0-dimensional constraint */ int suff; /* suffix specified (see O_MEMVAR above) */ } con; #endif /*--------------------------------------------------------------*/ ARG_LIST *list; /* O_TUPLE, O_MAKE, n-ary operations */ /* list of operands */ /*--------------------------------------------------------------*/ DOMAIN_BLOCK *slice; /* O_SLICE */ /* domain block, which specifies slice (i.e. n-tuple that contains free dummy indices); this operation is never evaluated */ /*--------------------------------------------------------------*/ struct /* unary, binary, ternary operations */ { CODE *x; /* pseudo-code for computing first operand */ CODE *y; /* pseudo-code for computing second operand */ CODE *z; /* pseudo-code for computing third operand */ } arg; /*--------------------------------------------------------------*/ struct /* iterated operations */ { DOMAIN *domain; /* domain, over which the operation is performed */ CODE *x; /* pseudo-code for computing "integrand" */ } loop; /*--------------------------------------------------------------*/ }; struct ARG_LIST { /* operands list entry */ CODE *x; /* pseudo-code for computing operand */ ARG_LIST *next; /* the next operand of the same operation */ }; struct CODE { /* pseudo-code (internal form of expressions) */ int op; /* operation code: */ #define O_NUMBER 301 /* take floating-point number */ #define O_STRING 302 /* take character string */ #define O_INDEX 303 /* take dummy index */ #define O_MEMNUM 304 /* take member of numeric parameter */ #define O_MEMSYM 305 /* take member of symbolic parameter */ #define O_MEMSET 306 /* take member of set */ #define O_MEMVAR 307 /* take member of variable */ #define O_MEMCON 308 /* take member of constraint */ #define O_TUPLE 309 /* make n-tuple */ #define O_MAKE 310 /* make elemental set of n-tuples */ #define O_SLICE 311 /* define domain block (dummy op) */ /* 0-ary operations --------------------*/ #define O_IRAND224 312 /* pseudo-random in [0, 2^24-1] */ #define O_UNIFORM01 313 /* pseudo-random in [0, 1) */ #define O_NORMAL01 314 /* gaussian random, mu = 0, sigma = 1 */ #define O_GMTIME 315 /* current calendar time (UTC) */ /* unary operations --------------------*/ #define O_CVTNUM 316 /* conversion to numeric */ #define O_CVTSYM 317 /* conversion to symbolic */ #define O_CVTLOG 318 /* conversion to logical */ #define O_CVTTUP 319 /* conversion to 1-tuple */ #define O_CVTLFM 320 /* conversion to linear form */ #define O_PLUS 321 /* unary plus */ #define O_MINUS 322 /* unary minus */ #define O_NOT 323 /* negation (logical "not") */ #define O_ABS 324 /* absolute value */ #define O_CEIL 325 /* round upward ("ceiling of x") */ #define O_FLOOR 326 /* round downward ("floor of x") */ #define O_EXP 327 /* base-e exponential */ #define O_LOG 328 /* natural logarithm */ #define O_LOG10 329 /* common (decimal) logarithm */ #define O_SQRT 330 /* square root */ #define O_SIN 331 /* trigonometric sine */ #define O_COS 332 /* trigonometric cosine */ #define O_ATAN 333 /* trigonometric arctangent */ #define O_ROUND 334 /* round to nearest integer */ #define O_TRUNC 335 /* truncate to nearest integer */ #define O_CARD 336 /* cardinality of set */ #define O_LENGTH 337 /* length of symbolic value */ /* binary operations -------------------*/ #define O_ADD 338 /* addition */ #define O_SUB 339 /* subtraction */ #define O_LESS 340 /* non-negative subtraction */ #define O_MUL 341 /* multiplication */ #define O_DIV 342 /* division */ #define O_IDIV 343 /* quotient of exact division */ #define O_MOD 344 /* remainder of exact division */ #define O_POWER 345 /* exponentiation (raise to power) */ #define O_ATAN2 346 /* trigonometric arctangent */ #define O_ROUND2 347 /* round to n fractional digits */ #define O_TRUNC2 348 /* truncate to n fractional digits */ #define O_UNIFORM 349 /* pseudo-random in [a, b) */ #define O_NORMAL 350 /* gaussian random, given mu and sigma */ #define O_CONCAT 351 /* concatenation */ #define O_LT 352 /* comparison on 'less than' */ #define O_LE 353 /* comparison on 'not greater than' */ #define O_EQ 354 /* comparison on 'equal to' */ #define O_GE 355 /* comparison on 'not less than' */ #define O_GT 356 /* comparison on 'greater than' */ #define O_NE 357 /* comparison on 'not equal to' */ #define O_AND 358 /* conjunction (logical "and") */ #define O_OR 359 /* disjunction (logical "or") */ #define O_UNION 360 /* union */ #define O_DIFF 361 /* difference */ #define O_SYMDIFF 362 /* symmetric difference */ #define O_INTER 363 /* intersection */ #define O_CROSS 364 /* cross (Cartesian) product */ #define O_IN 365 /* test on 'x in Y' */ #define O_NOTIN 366 /* test on 'x not in Y' */ #define O_WITHIN 367 /* test on 'X within Y' */ #define O_NOTWITHIN 368 /* test on 'X not within Y' */ #define O_SUBSTR 369 /* substring */ #define O_STR2TIME 370 /* convert string to time */ #define O_TIME2STR 371 /* convert time to string */ /* ternary operations ------------------*/ #define O_DOTS 372 /* build "arithmetic" set */ #define O_FORK 373 /* if-then-else */ #define O_SUBSTR3 374 /* substring */ /* n-ary operations --------------------*/ #define O_MIN 375 /* minimal value (n-ary) */ #define O_MAX 376 /* maximal value (n-ary) */ /* iterated operations -----------------*/ #define O_SUM 377 /* summation */ #define O_PROD 378 /* multiplication */ #define O_MINIMUM 379 /* minimum */ #define O_MAXIMUM 380 /* maximum */ #define O_FORALL 381 /* conjunction (A-quantification) */ #define O_EXISTS 382 /* disjunction (E-quantification) */ #define O_SETOF 383 /* compute elemental set */ #define O_BUILD 384 /* build elemental set */ OPERANDS arg; /* operands that participate in the operation */ int type; /* type of the resultant value: A_NUMERIC - numeric A_SYMBOLIC - symbolic A_LOGICAL - logical A_TUPLE - n-tuple A_ELEMSET - elemental set A_FORMULA - linear form */ int dim; /* dimension of the resultant value; for A_TUPLE and A_ELEMSET it is the dimension of the corresponding n-tuple(s) and cannot be zero; for other resultant types it is always zero */ CODE *up; /* parent pseudo-code, which refers to this pseudo-code as to its operand; NULL means this pseudo-code has no parent and defines an expression, which is not contained in another expression */ int vflag; /* volatile flag; being set this flag means that this operation has a side effect; for primary expressions this flag is set directly by corresponding parsing routines (for example, if primary expression is a reference to a function that generates pseudo-random numbers); in other cases this flag is inherited from operands */ int valid; /* if this flag is set, the resultant value, which is a temporary result of evaluating this operation on particular values of operands, is valid; if this flag is clear, the resultant value doesn't exist and therefore not valid; having been evaluated the resultant value is stored here and not destroyed until the dummy indices, which this value depends on, have been changed (and if it doesn't depend on dummy indices at all, it is never destroyed); thus, if the resultant value is valid, evaluating routine can immediately take its copy not computing the result from scratch; this mechanism is similar to moving invariants out of loops and allows improving efficiency at the expense of some extra memory needed to keep temporary results */ /* however, if the volatile flag (see above) is set, even if the resultant value is valid, evaluating routine computes it as if it were not valid, i.e. caching is not used in this case */ VALUE value; /* resultant value in generic format */ }; #define eval_numeric _glp_mpl_eval_numeric double eval_numeric(MPL *mpl, CODE *code); /* evaluate pseudo-code to determine numeric value */ #define eval_symbolic _glp_mpl_eval_symbolic SYMBOL *eval_symbolic(MPL *mpl, CODE *code); /* evaluate pseudo-code to determine symbolic value */ #define eval_logical _glp_mpl_eval_logical int eval_logical(MPL *mpl, CODE *code); /* evaluate pseudo-code to determine logical value */ #define eval_tuple _glp_mpl_eval_tuple TUPLE *eval_tuple(MPL *mpl, CODE *code); /* evaluate pseudo-code to construct n-tuple */ #define eval_elemset _glp_mpl_eval_elemset ELEMSET *eval_elemset(MPL *mpl, CODE *code); /* evaluate pseudo-code to construct elemental set */ #define is_member _glp_mpl_is_member int is_member(MPL *mpl, CODE *code, TUPLE *tuple); /* check if n-tuple is in set specified by pseudo-code */ #define eval_formula _glp_mpl_eval_formula FORMULA *eval_formula(MPL *mpl, CODE *code); /* evaluate pseudo-code to construct linear form */ #define clean_code _glp_mpl_clean_code void clean_code(MPL *mpl, CODE *code); /* clean pseudo-code */ /**********************************************************************/ /* * * MODEL STATEMENTS * * */ /**********************************************************************/ struct CHECK { /* check statement */ DOMAIN *domain; /* subscript domain; NULL means domain is not used */ CODE *code; /* code for computing the predicate to be checked */ }; struct DISPLAY { /* display statement */ DOMAIN *domain; /* subscript domain; NULL means domain is not used */ DISPLAY1 *list; /* display list; cannot be empty */ }; struct DISPLAY1 { /* display list entry */ int type; /* item type: A_INDEX - dummy index A_SET - model set A_PARAMETER - model parameter A_VARIABLE - model variable A_CONSTRAINT - model constraint/objective A_EXPRESSION - expression */ union { DOMAIN_SLOT *slot; SET *set; PARAMETER *par; VARIABLE *var; CONSTRAINT *con; CODE *code; } u; /* item to be displayed */ #if 0 /* 15/V-2010 */ ARG_LIST *list; /* optional subscript list (for constraint/objective only) */ #endif DISPLAY1 *next; /* the next entry for the same statement */ }; struct PRINTF { /* printf statement */ DOMAIN *domain; /* subscript domain; NULL means domain is not used */ CODE *fmt; /* pseudo-code for computing format string */ PRINTF1 *list; /* printf list; can be empty */ CODE *fname; /* pseudo-code for computing filename to redirect the output; NULL means the output goes to stdout */ int app; /* if this flag is set, the output is appended */ }; struct PRINTF1 { /* printf list entry */ CODE *code; /* pseudo-code for computing value to be printed */ PRINTF1 *next; /* the next entry for the same statement */ }; struct FOR { /* for statement */ DOMAIN *domain; /* subscript domain; cannot be NULL */ STATEMENT *list; /* linked list of model statements within this for statement in the original order */ }; struct STATEMENT { /* model statement */ int line; /* number of source text line, where statement begins */ int type; /* statement type: A_SET - set statement A_PARAMETER - parameter statement A_VARIABLE - variable statement A_CONSTRAINT - constraint/objective statement A_TABLE - table statement A_SOLVE - solve statement A_CHECK - check statement A_DISPLAY - display statement A_PRINTF - printf statement A_FOR - for statement */ union { SET *set; PARAMETER *par; VARIABLE *var; CONSTRAINT *con; TABLE *tab; void *slv; /* currently not used (set to NULL) */ CHECK *chk; DISPLAY *dpy; PRINTF *prt; FOR *fur; } u; /* specific part of statement */ STATEMENT *next; /* the next statement; in this list statements follow in the same order as they appear in the model section */ }; #define execute_table _glp_mpl_execute_table void execute_table(MPL *mpl, TABLE *tab); /* execute table statement */ #define free_dca _glp_mpl_free_dca void free_dca(MPL *mpl); /* free table driver communucation area */ #define clean_table _glp_mpl_clean_table void clean_table(MPL *mpl, TABLE *tab); /* clean table statement */ #define execute_check _glp_mpl_execute_check void execute_check(MPL *mpl, CHECK *chk); /* execute check statement */ #define clean_check _glp_mpl_clean_check void clean_check(MPL *mpl, CHECK *chk); /* clean check statement */ #define execute_display _glp_mpl_execute_display void execute_display(MPL *mpl, DISPLAY *dpy); /* execute display statement */ #define clean_display _glp_mpl_clean_display void clean_display(MPL *mpl, DISPLAY *dpy); /* clean display statement */ #define execute_printf _glp_mpl_execute_printf void execute_printf(MPL *mpl, PRINTF *prt); /* execute printf statement */ #define clean_printf _glp_mpl_clean_printf void clean_printf(MPL *mpl, PRINTF *prt); /* clean printf statement */ #define execute_for _glp_mpl_execute_for void execute_for(MPL *mpl, FOR *fur); /* execute for statement */ #define clean_for _glp_mpl_clean_for void clean_for(MPL *mpl, FOR *fur); /* clean for statement */ #define execute_statement _glp_mpl_execute_statement void execute_statement(MPL *mpl, STATEMENT *stmt); /* execute specified model statement */ #define clean_statement _glp_mpl_clean_statement void clean_statement(MPL *mpl, STATEMENT *stmt); /* clean specified model statement */ /**********************************************************************/ /* * * GENERATING AND POSTSOLVING MODEL * * */ /**********************************************************************/ #define alloc_content _glp_mpl_alloc_content void alloc_content(MPL *mpl); /* allocate content arrays for all model objects */ #define generate_model _glp_mpl_generate_model void generate_model(MPL *mpl); /* generate model */ #define build_problem _glp_mpl_build_problem void build_problem(MPL *mpl); /* build problem instance */ #define postsolve_model _glp_mpl_postsolve_model void postsolve_model(MPL *mpl); /* postsolve model */ #define clean_model _glp_mpl_clean_model void clean_model(MPL *mpl); /* clean model content */ /**********************************************************************/ /* * * INPUT/OUTPUT * * */ /**********************************************************************/ #define open_input _glp_mpl_open_input void open_input(MPL *mpl, char *file); /* open input text file */ #define read_char _glp_mpl_read_char int read_char(MPL *mpl); /* read next character from input text file */ #define close_input _glp_mpl_close_input void close_input(MPL *mpl); /* close input text file */ #define open_output _glp_mpl_open_output void open_output(MPL *mpl, char *file); /* open output text file */ #define write_char _glp_mpl_write_char void write_char(MPL *mpl, int c); /* write next character to output text file */ #define write_text _glp_mpl_write_text void write_text(MPL *mpl, char *fmt, ...); /* format and write text to output text file */ #define flush_output _glp_mpl_flush_output void flush_output(MPL *mpl); /* finalize writing data to output text file */ /**********************************************************************/ /* * * SOLVER INTERFACE * * */ /**********************************************************************/ #define MPL_FR 401 /* free (unbounded) */ #define MPL_LO 402 /* lower bound */ #define MPL_UP 403 /* upper bound */ #define MPL_DB 404 /* both lower and upper bounds */ #define MPL_FX 405 /* fixed */ #define MPL_ST 411 /* constraint */ #define MPL_MIN 412 /* objective (minimization) */ #define MPL_MAX 413 /* objective (maximization) */ #define MPL_NUM 421 /* continuous */ #define MPL_INT 422 /* integer */ #define MPL_BIN 423 /* binary */ #define error _glp_mpl_error void error(MPL *mpl, char *fmt, ...); /* print error message and terminate model processing */ #define warning _glp_mpl_warning void warning(MPL *mpl, char *fmt, ...); /* print warning message and continue model processing */ #define mpl_initialize _glp_mpl_initialize MPL *mpl_initialize(void); /* create and initialize translator database */ #define mpl_read_model _glp_mpl_read_model int mpl_read_model(MPL *mpl, char *file, int skip_data); /* read model section and optional data section */ #define mpl_read_data _glp_mpl_read_data int mpl_read_data(MPL *mpl, char *file); /* read data section */ #define mpl_generate _glp_mpl_generate int mpl_generate(MPL *mpl, char *file); /* generate model */ #define mpl_get_prob_name _glp_mpl_get_prob_name char *mpl_get_prob_name(MPL *mpl); /* obtain problem (model) name */ #define mpl_get_num_rows _glp_mpl_get_num_rows int mpl_get_num_rows(MPL *mpl); /* determine number of rows */ #define mpl_get_num_cols _glp_mpl_get_num_cols int mpl_get_num_cols(MPL *mpl); /* determine number of columns */ #define mpl_get_row_name _glp_mpl_get_row_name char *mpl_get_row_name(MPL *mpl, int i); /* obtain row name */ #define mpl_get_row_kind _glp_mpl_get_row_kind int mpl_get_row_kind(MPL *mpl, int i); /* determine row kind */ #define mpl_get_row_bnds _glp_mpl_get_row_bnds int mpl_get_row_bnds(MPL *mpl, int i, double *lb, double *ub); /* obtain row bounds */ #define mpl_get_mat_row _glp_mpl_get_mat_row int mpl_get_mat_row(MPL *mpl, int i, int ndx[], double val[]); /* obtain row of the constraint matrix */ #define mpl_get_row_c0 _glp_mpl_get_row_c0 double mpl_get_row_c0(MPL *mpl, int i); /* obtain constant term of free row */ #define mpl_get_col_name _glp_mpl_get_col_name char *mpl_get_col_name(MPL *mpl, int j); /* obtain column name */ #define mpl_get_col_kind _glp_mpl_get_col_kind int mpl_get_col_kind(MPL *mpl, int j); /* determine column kind */ #define mpl_get_col_bnds _glp_mpl_get_col_bnds int mpl_get_col_bnds(MPL *mpl, int j, double *lb, double *ub); /* obtain column bounds */ #define mpl_has_solve_stmt _glp_mpl_has_solve_stmt int mpl_has_solve_stmt(MPL *mpl); /* check if model has solve statement */ #if 1 /* 15/V-2010 */ #define mpl_put_row_soln _glp_mpl_put_row_soln void mpl_put_row_soln(MPL *mpl, int i, int stat, double prim, double dual); /* store row (constraint/objective) solution components */ #endif #if 1 /* 15/V-2010 */ #define mpl_put_col_soln _glp_mpl_put_col_soln void mpl_put_col_soln(MPL *mpl, int j, int stat, double prim, double dual); /* store column (variable) solution components */ #endif #if 0 /* 15/V-2010 */ #define mpl_put_col_value _glp_mpl_put_col_value void mpl_put_col_value(MPL *mpl, int j, double val); /* store column value */ #endif #define mpl_postsolve _glp_mpl_postsolve int mpl_postsolve(MPL *mpl); /* postsolve model */ #define mpl_terminate _glp_mpl_terminate void mpl_terminate(MPL *mpl); /* free all resources used by translator */ #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpspm.h0000644000076500000240000001174013524616144025055 0ustar tamasstaff00000000000000/* glpspm.h (general sparse matrix) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPSPM_H #define GLPSPM_H #include "glpdmp.h" typedef struct SPM SPM; typedef struct SPME SPME; struct SPM { /* general sparse matrix */ int m; /* number of rows, m >= 0 */ int n; /* number of columns, n >= 0 */ DMP *pool; /* memory pool to store matrix elements */ SPME **row; /* SPME *row[1+m]; */ /* row[i], 1 <= i <= m, is a pointer to i-th row list */ SPME **col; /* SPME *col[1+n]; */ /* col[j], 1 <= j <= n, is a pointer to j-th column list */ }; struct SPME { /* sparse matrix element */ int i; /* row number */ int j; /* column number */ double val; /* element value */ SPME *r_prev; /* pointer to previous element in the same row */ SPME *r_next; /* pointer to next element in the same row */ SPME *c_prev; /* pointer to previous element in the same column */ SPME *c_next; /* pointer to next element in the same column */ }; typedef struct PER PER; struct PER { /* permutation matrix */ int n; /* matrix order, n >= 0 */ int *row; /* int row[1+n]; */ /* row[i] = j means p[i,j] = 1 */ int *col; /* int col[1+n]; */ /* col[j] = i means p[i,j] = 1 */ }; #define spm_create_mat _glp_spm_create_mat SPM *spm_create_mat(int m, int n); /* create general sparse matrix */ #define spm_new_elem _glp_spm_new_elem SPME *spm_new_elem(SPM *A, int i, int j, double val); /* add new element to sparse matrix */ #define spm_delete_mat _glp_spm_delete_mat void spm_delete_mat(SPM *A); /* delete general sparse matrix */ #define spm_test_mat_e _glp_spm_test_mat_e SPM *spm_test_mat_e(int n, int c); /* create test sparse matrix of E(n,c) class */ #define spm_test_mat_d _glp_spm_test_mat_d SPM *spm_test_mat_d(int n, int c); /* create test sparse matrix of D(n,c) class */ #define spm_show_mat _glp_spm_show_mat int spm_show_mat(const SPM *A, const char *fname); /* write sparse matrix pattern in BMP file format */ #define spm_read_hbm _glp_spm_read_hbm SPM *spm_read_hbm(const char *fname); /* read sparse matrix in Harwell-Boeing format */ #define spm_count_nnz _glp_spm_count_nnz int spm_count_nnz(const SPM *A); /* determine number of non-zeros in sparse matrix */ #define spm_drop_zeros _glp_spm_drop_zeros int spm_drop_zeros(SPM *A, double eps); /* remove zero elements from sparse matrix */ #define spm_read_mat _glp_spm_read_mat SPM *spm_read_mat(const char *fname); /* read sparse matrix from text file */ #define spm_write_mat _glp_spm_write_mat int spm_write_mat(const SPM *A, const char *fname); /* write sparse matrix to text file */ #define spm_transpose _glp_spm_transpose SPM *spm_transpose(const SPM *A); /* transpose sparse matrix */ #define spm_add_sym _glp_spm_add_sym SPM *spm_add_sym(const SPM *A, const SPM *B); /* add two sparse matrices (symbolic phase) */ #define spm_add_num _glp_spm_add_num void spm_add_num(SPM *C, double alfa, const SPM *A, double beta, const SPM *B); /* add two sparse matrices (numeric phase) */ #define spm_add_mat _glp_spm_add_mat SPM *spm_add_mat(double alfa, const SPM *A, double beta, const SPM *B); /* add two sparse matrices (driver routine) */ #define spm_mul_sym _glp_spm_mul_sym SPM *spm_mul_sym(const SPM *A, const SPM *B); /* multiply two sparse matrices (symbolic phase) */ #define spm_mul_num _glp_spm_mul_num void spm_mul_num(SPM *C, const SPM *A, const SPM *B); /* multiply two sparse matrices (numeric phase) */ #define spm_mul_mat _glp_spm_mul_mat SPM *spm_mul_mat(const SPM *A, const SPM *B); /* multiply two sparse matrices (driver routine) */ #define spm_create_per _glp_spm_create_per PER *spm_create_per(int n); /* create permutation matrix */ #define spm_check_per _glp_spm_check_per void spm_check_per(PER *P); /* check permutation matrix for correctness */ #define spm_delete_per _glp_spm_delete_per void spm_delete_per(PER *P); /* delete permutation matrix */ #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpios01.c0000644000076500000240000015050513524616144025207 0ustar tamasstaff00000000000000/* glpios01.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wsign-conversion" #pragma clang diagnostic ignored "-Wself-assign" #pragma clang diagnostic ignored "-Wshorten-64-to-32" #pragma clang diagnostic ignored "-Wlogical-op-parentheses" #endif #include "glpios.h" /*********************************************************************** * NAME * * ios_create_tree - create branch-and-bound tree * * SYNOPSIS * * #include "glpios.h" * glp_tree *ios_create_tree(glp_prob *mip, const glp_iocp *parm); * * DESCRIPTION * * The routine ios_create_tree creates the branch-and-bound tree. * * Being created the tree consists of the only root subproblem whose * reference number is 1. Note that initially the root subproblem is in * frozen state and therefore needs to be revived. * * RETURNS * * The routine returns a pointer to the tree created. */ static IOSNPD *new_node(glp_tree *tree, IOSNPD *parent); glp_tree *ios_create_tree(glp_prob *mip, const glp_iocp *parm) { int m = mip->m; int n = mip->n; glp_tree *tree; int i, j; xassert(mip->tree == NULL); mip->tree = tree = xmalloc(sizeof(glp_tree)); tree->pool = dmp_create_pool(); tree->n = n; /* save original problem components */ tree->orig_m = m; tree->orig_type = xcalloc(1+m+n, sizeof(char)); tree->orig_lb = xcalloc(1+m+n, sizeof(double)); tree->orig_ub = xcalloc(1+m+n, sizeof(double)); tree->orig_stat = xcalloc(1+m+n, sizeof(char)); tree->orig_prim = xcalloc(1+m+n, sizeof(double)); tree->orig_dual = xcalloc(1+m+n, sizeof(double)); for (i = 1; i <= m; i++) { GLPROW *row = mip->row[i]; tree->orig_type[i] = (char)row->type; tree->orig_lb[i] = row->lb; tree->orig_ub[i] = row->ub; tree->orig_stat[i] = (char)row->stat; tree->orig_prim[i] = row->prim; tree->orig_dual[i] = row->dual; } for (j = 1; j <= n; j++) { GLPCOL *col = mip->col[j]; tree->orig_type[m+j] = (char)col->type; tree->orig_lb[m+j] = col->lb; tree->orig_ub[m+j] = col->ub; tree->orig_stat[m+j] = (char)col->stat; tree->orig_prim[m+j] = col->prim; tree->orig_dual[m+j] = col->dual; } tree->orig_obj = mip->obj_val; /* initialize the branch-and-bound tree */ tree->nslots = 0; tree->avail = 0; tree->slot = NULL; tree->head = tree->tail = NULL; tree->a_cnt = tree->n_cnt = tree->t_cnt = 0; /* the root subproblem is not solved yet, so its final components are unknown so far */ tree->root_m = 0; tree->root_type = NULL; tree->root_lb = tree->root_ub = NULL; tree->root_stat = NULL; /* the current subproblem does not exist yet */ tree->curr = NULL; tree->mip = mip; /*tree->solved = 0;*/ tree->non_int = xcalloc(1+n, sizeof(char)); memset(&tree->non_int[1], 0, n); /* arrays to save parent subproblem components will be allocated later */ tree->pred_m = tree->pred_max = 0; tree->pred_type = NULL; tree->pred_lb = tree->pred_ub = NULL; tree->pred_stat = NULL; /* cut generator */ tree->local = ios_create_pool(tree); /*tree->first_attempt = 1;*/ /*tree->max_added_cuts = 0;*/ /*tree->min_eff = 0.0;*/ /*tree->miss = 0;*/ /*tree->just_selected = 0;*/ tree->mir_gen = NULL; tree->clq_gen = NULL; /*tree->round = 0;*/ #if 0 /* create the conflict graph */ tree->n_ref = xcalloc(1+n, sizeof(int)); memset(&tree->n_ref[1], 0, n * sizeof(int)); tree->c_ref = xcalloc(1+n, sizeof(int)); memset(&tree->c_ref[1], 0, n * sizeof(int)); tree->g = scg_create_graph(0); tree->j_ref = xcalloc(1+tree->g->n_max, sizeof(int)); #endif /* pseudocost branching */ tree->pcost = NULL; tree->iwrk = xcalloc(1+n, sizeof(int)); tree->dwrk = xcalloc(1+n, sizeof(double)); /* initialize control parameters */ tree->parm = parm; tree->tm_beg = xtime(); tree->tm_lag = xlset(0); tree->sol_cnt = 0; /* initialize advanced solver interface */ tree->reason = 0; tree->reopt = 0; tree->reinv = 0; tree->br_var = 0; tree->br_sel = 0; tree->child = 0; tree->next_p = 0; /*tree->btrack = NULL;*/ tree->stop = 0; /* create the root subproblem, which initially is identical to the original MIP */ new_node(tree, NULL); return tree; } /*********************************************************************** * NAME * * ios_revive_node - revive specified subproblem * * SYNOPSIS * * #include "glpios.h" * void ios_revive_node(glp_tree *tree, int p); * * DESCRIPTION * * The routine ios_revive_node revives the specified subproblem, whose * reference number is p, and thereby makes it the current subproblem. * Note that the specified subproblem must be active. Besides, if the * current subproblem already exists, it must be frozen before reviving * another subproblem. */ void ios_revive_node(glp_tree *tree, int p) { glp_prob *mip = tree->mip; IOSNPD *node, *root; /* obtain pointer to the specified subproblem */ xassert(1 <= p && p <= tree->nslots); node = tree->slot[p].node; xassert(node != NULL); /* the specified subproblem must be active */ xassert(node->count == 0); /* the current subproblem must not exist */ xassert(tree->curr == NULL); /* the specified subproblem becomes current */ tree->curr = node; /*tree->solved = 0;*/ /* obtain pointer to the root subproblem */ root = tree->slot[1].node; xassert(root != NULL); /* at this point problem object components correspond to the root subproblem, so if the root subproblem should be revived, there is nothing more to do */ if (node == root) goto done; xassert(mip->m == tree->root_m); /* build path from the root to the current node */ node->temp = NULL; for (node = node; node != NULL; node = node->up) { if (node->up == NULL) xassert(node == root); else node->up->temp = node; } /* go down from the root to the current node and make necessary changes to restore components of the current subproblem */ for (node = root; node != NULL; node = node->temp) { int m = mip->m; int n = mip->n; /* if the current node is reached, the problem object at this point corresponds to its parent, so save attributes of rows and columns for the parent subproblem */ if (node->temp == NULL) { int i, j; tree->pred_m = m; /* allocate/reallocate arrays, if necessary */ if (tree->pred_max < m + n) { int new_size = m + n + 100; if (tree->pred_type != NULL) xfree(tree->pred_type); if (tree->pred_lb != NULL) xfree(tree->pred_lb); if (tree->pred_ub != NULL) xfree(tree->pred_ub); if (tree->pred_stat != NULL) xfree(tree->pred_stat); tree->pred_max = new_size; tree->pred_type = xcalloc(1+new_size, sizeof(char)); tree->pred_lb = xcalloc(1+new_size, sizeof(double)); tree->pred_ub = xcalloc(1+new_size, sizeof(double)); tree->pred_stat = xcalloc(1+new_size, sizeof(char)); } /* save row attributes */ for (i = 1; i <= m; i++) { GLPROW *row = mip->row[i]; tree->pred_type[i] = (char)row->type; tree->pred_lb[i] = row->lb; tree->pred_ub[i] = row->ub; tree->pred_stat[i] = (char)row->stat; } /* save column attributes */ for (j = 1; j <= n; j++) { GLPCOL *col = mip->col[j]; tree->pred_type[mip->m+j] = (char)col->type; tree->pred_lb[mip->m+j] = col->lb; tree->pred_ub[mip->m+j] = col->ub; tree->pred_stat[mip->m+j] = (char)col->stat; } } /* change bounds of rows and columns */ { IOSBND *b; for (b = node->b_ptr; b != NULL; b = b->next) { if (b->k <= m) glp_set_row_bnds(mip, b->k, b->type, b->lb, b->ub); else glp_set_col_bnds(mip, b->k-m, b->type, b->lb, b->ub); } } /* change statuses of rows and columns */ { IOSTAT *s; for (s = node->s_ptr; s != NULL; s = s->next) { if (s->k <= m) glp_set_row_stat(mip, s->k, s->stat); else glp_set_col_stat(mip, s->k-m, s->stat); } } /* add new rows */ if (node->r_ptr != NULL) { IOSROW *r; IOSAIJ *a; int i, len, *ind; double *val; ind = xcalloc(1+n, sizeof(int)); val = xcalloc(1+n, sizeof(double)); for (r = node->r_ptr; r != NULL; r = r->next) { i = glp_add_rows(mip, 1); glp_set_row_name(mip, i, r->name); #if 1 /* 20/IX-2008 */ xassert(mip->row[i]->level == 0); mip->row[i]->level = node->level; mip->row[i]->origin = r->origin; mip->row[i]->klass = r->klass; #endif glp_set_row_bnds(mip, i, r->type, r->lb, r->ub); len = 0; for (a = r->ptr; a != NULL; a = a->next) len++, ind[len] = a->j, val[len] = a->val; glp_set_mat_row(mip, i, len, ind, val); glp_set_rii(mip, i, r->rii); glp_set_row_stat(mip, i, r->stat); } xfree(ind); xfree(val); } #if 0 /* add new edges to the conflict graph */ /* add new cliques to the conflict graph */ /* (not implemented yet) */ xassert(node->own_nn == 0); xassert(node->own_nc == 0); xassert(node->e_ptr == NULL); #endif } /* the specified subproblem has been revived */ node = tree->curr; /* delete its bound change list */ while (node->b_ptr != NULL) { IOSBND *b; b = node->b_ptr; node->b_ptr = b->next; dmp_free_atom(tree->pool, b, sizeof(IOSBND)); } /* delete its status change list */ while (node->s_ptr != NULL) { IOSTAT *s; s = node->s_ptr; node->s_ptr = s->next; dmp_free_atom(tree->pool, s, sizeof(IOSTAT)); } #if 1 /* 20/XI-2009 */ /* delete its row addition list (additional rows may appear, for example, due to branching on GUB constraints */ while (node->r_ptr != NULL) { IOSROW *r; r = node->r_ptr; node->r_ptr = r->next; xassert(r->name == NULL); while (r->ptr != NULL) { IOSAIJ *a; a = r->ptr; r->ptr = a->next; dmp_free_atom(tree->pool, a, sizeof(IOSAIJ)); } dmp_free_atom(tree->pool, r, sizeof(IOSROW)); } #endif done: return; } /*********************************************************************** * NAME * * ios_freeze_node - freeze current subproblem * * SYNOPSIS * * #include "glpios.h" * void ios_freeze_node(glp_tree *tree); * * DESCRIPTION * * The routine ios_freeze_node freezes the current subproblem. */ void ios_freeze_node(glp_tree *tree) { glp_prob *mip = tree->mip; int m = mip->m; int n = mip->n; IOSNPD *node; /* obtain pointer to the current subproblem */ node = tree->curr; xassert(node != NULL); if (node->up == NULL) { /* freeze the root subproblem */ int k; xassert(node->p == 1); xassert(tree->root_m == 0); xassert(tree->root_type == NULL); xassert(tree->root_lb == NULL); xassert(tree->root_ub == NULL); xassert(tree->root_stat == NULL); tree->root_m = m; tree->root_type = xcalloc(1+m+n, sizeof(char)); tree->root_lb = xcalloc(1+m+n, sizeof(double)); tree->root_ub = xcalloc(1+m+n, sizeof(double)); tree->root_stat = xcalloc(1+m+n, sizeof(char)); for (k = 1; k <= m+n; k++) { if (k <= m) { GLPROW *row = mip->row[k]; tree->root_type[k] = (char)row->type; tree->root_lb[k] = row->lb; tree->root_ub[k] = row->ub; tree->root_stat[k] = (char)row->stat; } else { GLPCOL *col = mip->col[k-m]; tree->root_type[k] = (char)col->type; tree->root_lb[k] = col->lb; tree->root_ub[k] = col->ub; tree->root_stat[k] = (char)col->stat; } } } else { /* freeze non-root subproblem */ int root_m = tree->root_m; int pred_m = tree->pred_m; int i, j, k; xassert(pred_m <= m); /* build change lists for rows and columns which exist in the parent subproblem */ xassert(node->b_ptr == NULL); xassert(node->s_ptr == NULL); for (k = 1; k <= pred_m + n; k++) { int pred_type, pred_stat, type, stat; double pred_lb, pred_ub, lb, ub; /* determine attributes in the parent subproblem */ pred_type = tree->pred_type[k]; pred_lb = tree->pred_lb[k]; pred_ub = tree->pred_ub[k]; pred_stat = tree->pred_stat[k]; /* determine attributes in the current subproblem */ if (k <= pred_m) { GLPROW *row = mip->row[k]; type = row->type; lb = row->lb; ub = row->ub; stat = row->stat; } else { GLPCOL *col = mip->col[k - pred_m]; type = col->type; lb = col->lb; ub = col->ub; stat = col->stat; } /* save type and bounds of a row/column, if changed */ if (!(pred_type == type && pred_lb == lb && pred_ub == ub)) { IOSBND *b; b = dmp_get_atom(tree->pool, sizeof(IOSBND)); b->k = k; b->type = (unsigned char)type; b->lb = lb; b->ub = ub; b->next = node->b_ptr; node->b_ptr = b; } /* save status of a row/column, if changed */ if (pred_stat != stat) { IOSTAT *s; s = dmp_get_atom(tree->pool, sizeof(IOSTAT)); s->k = k; s->stat = (unsigned char)stat; s->next = node->s_ptr; node->s_ptr = s; } } /* save new rows added to the current subproblem */ xassert(node->r_ptr == NULL); if (pred_m < m) { int i, len, *ind; double *val; ind = xcalloc(1+n, sizeof(int)); val = xcalloc(1+n, sizeof(double)); for (i = m; i > pred_m; i--) { GLPROW *row = mip->row[i]; IOSROW *r; const char *name; r = dmp_get_atom(tree->pool, sizeof(IOSROW)); name = glp_get_row_name(mip, i); if (name == NULL) r->name = NULL; else { r->name = dmp_get_atom(tree->pool, strlen(name)+1); strcpy(r->name, name); } #if 1 /* 20/IX-2008 */ r->origin = row->origin; r->klass = row->klass; #endif r->type = (unsigned char)row->type; r->lb = row->lb; r->ub = row->ub; r->ptr = NULL; len = glp_get_mat_row(mip, i, ind, val); for (k = 1; k <= len; k++) { IOSAIJ *a; a = dmp_get_atom(tree->pool, sizeof(IOSAIJ)); a->j = ind[k]; a->val = val[k]; a->next = r->ptr; r->ptr = a; } r->rii = row->rii; r->stat = (unsigned char)row->stat; r->next = node->r_ptr; node->r_ptr = r; } xfree(ind); xfree(val); } /* remove all rows missing in the root subproblem */ if (m != root_m) { int nrs, *num; nrs = m - root_m; xassert(nrs > 0); num = xcalloc(1+nrs, sizeof(int)); for (i = 1; i <= nrs; i++) num[i] = root_m + i; glp_del_rows(mip, nrs, num); xfree(num); } m = mip->m; /* and restore attributes of all rows and columns for the root subproblem */ xassert(m == root_m); for (i = 1; i <= m; i++) { glp_set_row_bnds(mip, i, tree->root_type[i], tree->root_lb[i], tree->root_ub[i]); glp_set_row_stat(mip, i, tree->root_stat[i]); } for (j = 1; j <= n; j++) { glp_set_col_bnds(mip, j, tree->root_type[m+j], tree->root_lb[m+j], tree->root_ub[m+j]); glp_set_col_stat(mip, j, tree->root_stat[m+j]); } #if 1 /* remove all edges and cliques missing in the conflict graph for the root subproblem */ /* (not implemented yet) */ #endif } /* the current subproblem has been frozen */ tree->curr = NULL; return; } /*********************************************************************** * NAME * * ios_clone_node - clone specified subproblem * * SYNOPSIS * * #include "glpios.h" * void ios_clone_node(glp_tree *tree, int p, int nnn, int ref[]); * * DESCRIPTION * * The routine ios_clone_node clones the specified subproblem, whose * reference number is p, creating its nnn exact copies. Note that the * specified subproblem must be active and must be in the frozen state * (i.e. it must not be the current subproblem). * * Each clone, an exact copy of the specified subproblem, becomes a new * active subproblem added to the end of the active list. After cloning * the specified subproblem becomes inactive. * * The reference numbers of clone subproblems are stored to locations * ref[1], ..., ref[nnn]. */ static int get_slot(glp_tree *tree) { int p; /* if no free slots are available, increase the room */ if (tree->avail == 0) { int nslots = tree->nslots; IOSLOT *save = tree->slot; if (nslots == 0) tree->nslots = 20; else { tree->nslots = nslots + nslots; xassert(tree->nslots > nslots); } tree->slot = xcalloc(1+tree->nslots, sizeof(IOSLOT)); if (save != NULL) { memcpy(&tree->slot[1], &save[1], nslots * sizeof(IOSLOT)); xfree(save); } /* push more free slots into the stack */ for (p = tree->nslots; p > nslots; p--) { tree->slot[p].node = NULL; tree->slot[p].next = tree->avail; tree->avail = p; } } /* pull a free slot from the stack */ p = tree->avail; tree->avail = tree->slot[p].next; xassert(tree->slot[p].node == NULL); tree->slot[p].next = 0; return p; } static IOSNPD *new_node(glp_tree *tree, IOSNPD *parent) { IOSNPD *node; int p; /* pull a free slot for the new node */ p = get_slot(tree); /* create descriptor of the new subproblem */ node = dmp_get_atom(tree->pool, sizeof(IOSNPD)); tree->slot[p].node = node; node->p = p; node->up = parent; node->level = (parent == NULL ? 0 : parent->level + 1); node->count = 0; node->b_ptr = NULL; node->s_ptr = NULL; node->r_ptr = NULL; node->solved = 0; #if 0 node->own_nn = node->own_nc = 0; node->e_ptr = NULL; #endif #if 1 /* 04/X-2008 */ node->lp_obj = (parent == NULL ? (tree->mip->dir == GLP_MIN ? -DBL_MAX : +DBL_MAX) : parent->lp_obj); #endif node->bound = (parent == NULL ? (tree->mip->dir == GLP_MIN ? -DBL_MAX : +DBL_MAX) : parent->bound); node->br_var = 0; node->br_val = 0.0; node->ii_cnt = 0; node->ii_sum = 0.0; #if 1 /* 30/XI-2009 */ node->changed = 0; #endif if (tree->parm->cb_size == 0) node->data = NULL; else { node->data = dmp_get_atom(tree->pool, tree->parm->cb_size); memset(node->data, 0, tree->parm->cb_size); } node->temp = NULL; node->prev = tree->tail; node->next = NULL; /* add the new subproblem to the end of the active list */ if (tree->head == NULL) tree->head = node; else tree->tail->next = node; tree->tail = node; tree->a_cnt++; tree->n_cnt++; tree->t_cnt++; /* increase the number of child subproblems */ if (parent == NULL) xassert(p == 1); else parent->count++; return node; } void ios_clone_node(glp_tree *tree, int p, int nnn, int ref[]) { IOSNPD *node; int k; /* obtain pointer to the subproblem to be cloned */ xassert(1 <= p && p <= tree->nslots); node = tree->slot[p].node; xassert(node != NULL); /* the specified subproblem must be active */ xassert(node->count == 0); /* and must be in the frozen state */ xassert(tree->curr != node); /* remove the specified subproblem from the active list, because it becomes inactive */ if (node->prev == NULL) tree->head = node->next; else node->prev->next = node->next; if (node->next == NULL) tree->tail = node->prev; else node->next->prev = node->prev; node->prev = node->next = NULL; tree->a_cnt--; /* create clone subproblems */ xassert(nnn > 0); for (k = 1; k <= nnn; k++) ref[k] = new_node(tree, node)->p; return; } /*********************************************************************** * NAME * * ios_delete_node - delete specified subproblem * * SYNOPSIS * * #include "glpios.h" * void ios_delete_node(glp_tree *tree, int p); * * DESCRIPTION * * The routine ios_delete_node deletes the specified subproblem, whose * reference number is p. The subproblem must be active and must be in * the frozen state (i.e. it must not be the current subproblem). * * Note that deletion is performed recursively, i.e. if a subproblem to * be deleted is the only child of its parent, the parent subproblem is * also deleted, etc. */ void ios_delete_node(glp_tree *tree, int p) { IOSNPD *node, *temp; /* obtain pointer to the subproblem to be deleted */ xassert(1 <= p && p <= tree->nslots); node = tree->slot[p].node; xassert(node != NULL); /* the specified subproblem must be active */ xassert(node->count == 0); /* and must be in the frozen state */ xassert(tree->curr != node); /* remove the specified subproblem from the active list, because it is gone from the tree */ if (node->prev == NULL) tree->head = node->next; else node->prev->next = node->next; if (node->next == NULL) tree->tail = node->prev; else node->next->prev = node->prev; node->prev = node->next = NULL; tree->a_cnt--; loop: /* recursive deletion starts here */ /* delete the bound change list */ { IOSBND *b; while (node->b_ptr != NULL) { b = node->b_ptr; node->b_ptr = b->next; dmp_free_atom(tree->pool, b, sizeof(IOSBND)); } } /* delete the status change list */ { IOSTAT *s; while (node->s_ptr != NULL) { s = node->s_ptr; node->s_ptr = s->next; dmp_free_atom(tree->pool, s, sizeof(IOSTAT)); } } /* delete the row addition list */ while (node->r_ptr != NULL) { IOSROW *r; r = node->r_ptr; if (r->name != NULL) dmp_free_atom(tree->pool, r->name, strlen(r->name)+1); while (r->ptr != NULL) { IOSAIJ *a; a = r->ptr; r->ptr = a->next; dmp_free_atom(tree->pool, a, sizeof(IOSAIJ)); } node->r_ptr = r->next; dmp_free_atom(tree->pool, r, sizeof(IOSROW)); } #if 0 /* delete the edge addition list */ /* delete the clique addition list */ /* (not implemented yet) */ xassert(node->own_nn == 0); xassert(node->own_nc == 0); xassert(node->e_ptr == NULL); #endif /* free application-specific data */ if (tree->parm->cb_size == 0) xassert(node->data == NULL); else dmp_free_atom(tree->pool, node->data, tree->parm->cb_size); /* free the corresponding node slot */ p = node->p; xassert(tree->slot[p].node == node); tree->slot[p].node = NULL; tree->slot[p].next = tree->avail; tree->avail = p; /* save pointer to the parent subproblem */ temp = node->up; /* delete the subproblem descriptor */ dmp_free_atom(tree->pool, node, sizeof(IOSNPD)); tree->n_cnt--; /* take pointer to the parent subproblem */ node = temp; if (node != NULL) { /* the parent subproblem exists; decrease the number of its child subproblems */ xassert(node->count > 0); node->count--; /* if now the parent subproblem has no childs, it also must be deleted */ if (node->count == 0) goto loop; } return; } /*********************************************************************** * NAME * * ios_delete_tree - delete branch-and-bound tree * * SYNOPSIS * * #include "glpios.h" * void ios_delete_tree(glp_tree *tree); * * DESCRIPTION * * The routine ios_delete_tree deletes the branch-and-bound tree, which * the parameter tree points to, and frees all the memory allocated to * this program object. * * On exit components of the problem object are restored to correspond * to the original MIP passed to the routine ios_create_tree. */ void ios_delete_tree(glp_tree *tree) { glp_prob *mip = tree->mip; int i, j; int m = mip->m; int n = mip->n; xassert(mip->tree == tree); /* remove all additional rows */ if (m != tree->orig_m) { int nrs, *num; nrs = m - tree->orig_m; xassert(nrs > 0); num = xcalloc(1+nrs, sizeof(int)); for (i = 1; i <= nrs; i++) num[i] = tree->orig_m + i; glp_del_rows(mip, nrs, num); xfree(num); } m = tree->orig_m; /* restore original attributes of rows and columns */ xassert(m == tree->orig_m); xassert(n == tree->n); for (i = 1; i <= m; i++) { glp_set_row_bnds(mip, i, tree->orig_type[i], tree->orig_lb[i], tree->orig_ub[i]); glp_set_row_stat(mip, i, tree->orig_stat[i]); mip->row[i]->prim = tree->orig_prim[i]; mip->row[i]->dual = tree->orig_dual[i]; } for (j = 1; j <= n; j++) { glp_set_col_bnds(mip, j, tree->orig_type[m+j], tree->orig_lb[m+j], tree->orig_ub[m+j]); glp_set_col_stat(mip, j, tree->orig_stat[m+j]); mip->col[j]->prim = tree->orig_prim[m+j]; mip->col[j]->dual = tree->orig_dual[m+j]; } mip->pbs_stat = mip->dbs_stat = GLP_FEAS; mip->obj_val = tree->orig_obj; /* delete the branch-and-bound tree */ xassert(tree->local != NULL); ios_delete_pool(tree, tree->local); dmp_delete_pool(tree->pool); xfree(tree->orig_type); xfree(tree->orig_lb); xfree(tree->orig_ub); xfree(tree->orig_stat); xfree(tree->orig_prim); xfree(tree->orig_dual); xfree(tree->slot); if (tree->root_type != NULL) xfree(tree->root_type); if (tree->root_lb != NULL) xfree(tree->root_lb); if (tree->root_ub != NULL) xfree(tree->root_ub); if (tree->root_stat != NULL) xfree(tree->root_stat); xfree(tree->non_int); #if 0 xfree(tree->n_ref); xfree(tree->c_ref); xfree(tree->j_ref); #endif if (tree->pcost != NULL) ios_pcost_free(tree); xfree(tree->iwrk); xfree(tree->dwrk); #if 0 scg_delete_graph(tree->g); #endif if (tree->pred_type != NULL) xfree(tree->pred_type); if (tree->pred_lb != NULL) xfree(tree->pred_lb); if (tree->pred_ub != NULL) xfree(tree->pred_ub); if (tree->pred_stat != NULL) xfree(tree->pred_stat); #if 0 xassert(tree->cut_gen == NULL); #endif xassert(tree->mir_gen == NULL); xassert(tree->clq_gen == NULL); xfree(tree); mip->tree = NULL; return; } /*********************************************************************** * NAME * * ios_eval_degrad - estimate obj. degrad. for down- and up-branches * * SYNOPSIS * * #include "glpios.h" * void ios_eval_degrad(glp_tree *tree, int j, double *dn, double *up); * * DESCRIPTION * * Given optimal basis to LP relaxation of the current subproblem the * routine ios_eval_degrad performs the dual ratio test to compute the * objective values in the adjacent basis for down- and up-branches, * which are stored in locations *dn and *up, assuming that x[j] is a * variable chosen to branch upon. */ void ios_eval_degrad(glp_tree *tree, int j, double *dn, double *up) { glp_prob *mip = tree->mip; int m = mip->m, n = mip->n; int len, kase, k, t, stat; double alfa, beta, gamma, delta, dz; int *ind = tree->iwrk; double *val = tree->dwrk; /* current basis must be optimal */ xassert(glp_get_status(mip) == GLP_OPT); /* basis factorization must exist */ xassert(glp_bf_exists(mip)); /* obtain (fractional) value of x[j] in optimal basic solution to LP relaxation of the current subproblem */ xassert(1 <= j && j <= n); beta = mip->col[j]->prim; /* since the value of x[j] is fractional, it is basic; compute corresponding row of the simplex table */ len = lpx_eval_tab_row(mip, m+j, ind, val); /* kase < 0 means down-branch; kase > 0 means up-branch */ for (kase = -1; kase <= +1; kase += 2) { /* for down-branch we introduce new upper bound floor(beta) for x[j]; similarly, for up-branch we introduce new lower bound ceil(beta) for x[j]; in the current basis this new upper/lower bound is violated, so in the adjacent basis x[j] will leave the basis and go to its new upper/lower bound; we need to know which non-basic variable x[k] should enter the basis to keep dual feasibility */ #if 0 /* 23/XI-2009 */ k = lpx_dual_ratio_test(mip, len, ind, val, kase, 1e-7); #else k = lpx_dual_ratio_test(mip, len, ind, val, kase, 1e-9); #endif /* if no variable has been chosen, current basis being primal infeasible due to the new upper/lower bound of x[j] is dual unbounded, therefore, LP relaxation to corresponding branch has no primal feasible solution */ if (k == 0) { if (mip->dir == GLP_MIN) { if (kase < 0) *dn = +DBL_MAX; else *up = +DBL_MAX; } else if (mip->dir == GLP_MAX) { if (kase < 0) *dn = -DBL_MAX; else *up = -DBL_MAX; } else xassert(mip != mip); continue; } xassert(1 <= k && k <= m+n); /* row of the simplex table corresponding to specified basic variable x[j] is the following: x[j] = ... + alfa * x[k] + ... ; we need to know influence coefficient, alfa, at non-basic variable x[k] chosen with the dual ratio test */ for (t = 1; t <= len; t++) if (ind[t] == k) break; xassert(1 <= t && t <= len); alfa = val[t]; /* determine status and reduced cost of variable x[k] */ if (k <= m) { stat = mip->row[k]->stat; gamma = mip->row[k]->dual; } else { stat = mip->col[k-m]->stat; gamma = mip->col[k-m]->dual; } /* x[k] cannot be basic or fixed non-basic */ xassert(stat == GLP_NL || stat == GLP_NU || stat == GLP_NF); /* if the current basis is dual degenerative, some reduced costs, which are close to zero, may have wrong sign due to round-off errors, so correct the sign of gamma */ if (mip->dir == GLP_MIN) { if (stat == GLP_NL && gamma < 0.0 || stat == GLP_NU && gamma > 0.0 || stat == GLP_NF) gamma = 0.0; } else if (mip->dir == GLP_MAX) { if (stat == GLP_NL && gamma > 0.0 || stat == GLP_NU && gamma < 0.0 || stat == GLP_NF) gamma = 0.0; } else xassert(mip != mip); /* determine the change of x[j] in the adjacent basis: delta x[j] = new x[j] - old x[j] */ delta = (kase < 0 ? floor(beta) : ceil(beta)) - beta; /* compute the change of x[k] in the adjacent basis: delta x[k] = new x[k] - old x[k] = delta x[j] / alfa */ delta /= alfa; /* compute the change of the objective in the adjacent basis: delta z = new z - old z = gamma * delta x[k] */ dz = gamma * delta; if (mip->dir == GLP_MIN) xassert(dz >= 0.0); else if (mip->dir == GLP_MAX) xassert(dz <= 0.0); else xassert(mip != mip); /* compute the new objective value in the adjacent basis: new z = old z + delta z */ if (kase < 0) *dn = mip->obj_val + dz; else *up = mip->obj_val + dz; } /*xprintf("obj = %g; dn = %g; up = %g\n", mip->obj_val, *dn, *up);*/ return; } /*********************************************************************** * NAME * * ios_round_bound - improve local bound by rounding * * SYNOPSIS * * #include "glpios.h" * double ios_round_bound(glp_tree *tree, double bound); * * RETURNS * * For the given local bound for any integer feasible solution to the * current subproblem the routine ios_round_bound returns an improved * local bound for the same integer feasible solution. * * BACKGROUND * * Let the current subproblem has the following objective function: * * z = sum c[j] * x[j] + s >= b, (1) * j in J * * where J = {j: c[j] is non-zero and integer, x[j] is integer}, s is * the sum of terms corresponding to fixed variables, b is an initial * local bound (minimization). * * From (1) it follows that: * * d * sum (c[j] / d) * x[j] + s >= b, (2) * j in J * * or, equivalently, * * sum (c[j] / d) * x[j] >= (b - s) / d = h, (3) * j in J * * where d = gcd(c[j]). Since the left-hand side of (3) is integer, * h = (b - s) / d can be rounded up to the nearest integer: * * h' = ceil(h) = (b' - s) / d, (4) * * that gives an rounded, improved local bound: * * b' = d * h' + s. (5) * * In case of maximization '>=' in (1) should be replaced by '<=' that * leads to the following formula: * * h' = floor(h) = (b' - s) / d, (6) * * which should used in the same way as (4). * * NOTE: If b is a valid local bound for a child of the current * subproblem, b' is also valid for that child subproblem. */ double ios_round_bound(glp_tree *tree, double bound) { glp_prob *mip = tree->mip; int n = mip->n; int d, j, nn, *c = tree->iwrk; double s, h; /* determine c[j] and compute s */ nn = 0, s = mip->c0, d = 0; for (j = 1; j <= n; j++) { GLPCOL *col = mip->col[j]; if (col->coef == 0.0) continue; if (col->type == GLP_FX) { /* fixed variable */ s += col->coef * col->prim; } else { /* non-fixed variable */ if (col->kind != GLP_IV) goto skip; if (col->coef != floor(col->coef)) goto skip; if (fabs(col->coef) <= (double)INT_MAX) c[++nn] = (int)fabs(col->coef); else d = 1; } } /* compute d = gcd(c[1],...c[nn]) */ if (d == 0) { if (nn == 0) goto skip; d = gcdn(nn, c); } xassert(d > 0); /* compute new local bound */ if (mip->dir == GLP_MIN) { if (bound != +DBL_MAX) { h = (bound - s) / (double)d; if (h >= floor(h) + 0.001) { /* round up */ h = ceil(h); /*xprintf("d = %d; old = %g; ", d, bound);*/ bound = (double)d * h + s; /*xprintf("new = %g\n", bound);*/ } } } else if (mip->dir == GLP_MAX) { if (bound != -DBL_MAX) { h = (bound - s) / (double)d; if (h <= ceil(h) - 0.001) { /* round down */ h = floor(h); bound = (double)d * h + s; } } } else xassert(mip != mip); skip: return bound; } /*********************************************************************** * NAME * * ios_is_hopeful - check if subproblem is hopeful * * SYNOPSIS * * #include "glpios.h" * int ios_is_hopeful(glp_tree *tree, double bound); * * DESCRIPTION * * Given the local bound of a subproblem the routine ios_is_hopeful * checks if the subproblem can have an integer optimal solution which * is better than the best one currently known. * * RETURNS * * If the subproblem can have a better integer optimal solution, the * routine returns non-zero; otherwise, if the corresponding branch can * be pruned, the routine returns zero. */ int ios_is_hopeful(glp_tree *tree, double bound) { glp_prob *mip = tree->mip; int ret = 1; double eps; if (mip->mip_stat == GLP_FEAS) { eps = tree->parm->tol_obj * (1.0 + fabs(mip->mip_obj)); switch (mip->dir) { case GLP_MIN: if (bound >= mip->mip_obj - eps) ret = 0; break; case GLP_MAX: if (bound <= mip->mip_obj + eps) ret = 0; break; default: xassert(mip != mip); } } else { switch (mip->dir) { case GLP_MIN: if (bound == +DBL_MAX) ret = 0; break; case GLP_MAX: if (bound == -DBL_MAX) ret = 0; break; default: xassert(mip != mip); } } return ret; } /*********************************************************************** * NAME * * ios_best_node - find active node with best local bound * * SYNOPSIS * * #include "glpios.h" * int ios_best_node(glp_tree *tree); * * DESCRIPTION * * The routine ios_best_node finds an active node whose local bound is * best among other active nodes. * * It is understood that the integer optimal solution of the original * mip problem cannot be better than the best bound, so the best bound * is an lower (minimization) or upper (maximization) global bound for * the original problem. * * RETURNS * * The routine ios_best_node returns the subproblem reference number * for the best node. However, if the tree is empty, it returns zero. */ int ios_best_node(glp_tree *tree) { IOSNPD *node, *best = NULL; switch (tree->mip->dir) { case GLP_MIN: /* minimization */ for (node = tree->head; node != NULL; node = node->next) if (best == NULL || best->bound > node->bound) best = node; break; case GLP_MAX: /* maximization */ for (node = tree->head; node != NULL; node = node->next) if (best == NULL || best->bound < node->bound) best = node; break; default: xassert(tree != tree); } return best == NULL ? 0 : best->p; } /*********************************************************************** * NAME * * ios_relative_gap - compute relative mip gap * * SYNOPSIS * * #include "glpios.h" * double ios_relative_gap(glp_tree *tree); * * DESCRIPTION * * The routine ios_relative_gap computes the relative mip gap using the * formula: * * gap = |best_mip - best_bnd| / (|best_mip| + DBL_EPSILON), * * where best_mip is the best integer feasible solution found so far, * best_bnd is the best (global) bound. If no integer feasible solution * has been found yet, rel_gap is set to DBL_MAX. * * RETURNS * * The routine ios_relative_gap returns the relative mip gap. */ double ios_relative_gap(glp_tree *tree) { glp_prob *mip = tree->mip; int p; double best_mip, best_bnd, gap; if (mip->mip_stat == GLP_FEAS) { best_mip = mip->mip_obj; p = ios_best_node(tree); if (p == 0) { /* the tree is empty */ gap = 0.0; } else { best_bnd = tree->slot[p].node->bound; gap = fabs(best_mip - best_bnd) / (fabs(best_mip) + DBL_EPSILON); } } else { /* no integer feasible solution has been found yet */ gap = DBL_MAX; } return gap; } /*********************************************************************** * NAME * * ios_solve_node - solve LP relaxation of current subproblem * * SYNOPSIS * * #include "glpios.h" * int ios_solve_node(glp_tree *tree); * * DESCRIPTION * * The routine ios_solve_node re-optimizes LP relaxation of the current * subproblem using the dual simplex method. * * RETURNS * * The routine returns the code which is reported by glp_simplex. */ int ios_solve_node(glp_tree *tree) { glp_prob *mip = tree->mip; glp_smcp parm; int ret; /* the current subproblem must exist */ xassert(tree->curr != NULL); /* set some control parameters */ glp_init_smcp(&parm); switch (tree->parm->msg_lev) { case GLP_MSG_OFF: parm.msg_lev = GLP_MSG_OFF; break; case GLP_MSG_ERR: parm.msg_lev = GLP_MSG_ERR; break; case GLP_MSG_ON: case GLP_MSG_ALL: parm.msg_lev = GLP_MSG_ON; break; case GLP_MSG_DBG: parm.msg_lev = GLP_MSG_ALL; break; default: xassert(tree != tree); } parm.meth = GLP_DUALP; if (tree->parm->msg_lev < GLP_MSG_DBG) parm.out_dly = tree->parm->out_dly; else parm.out_dly = 0; /* if the incumbent objective value is already known, use it to prematurely terminate the dual simplex search */ if (mip->mip_stat == GLP_FEAS) { switch (tree->mip->dir) { case GLP_MIN: parm.obj_ul = mip->mip_obj; break; case GLP_MAX: parm.obj_ll = mip->mip_obj; break; default: xassert(mip != mip); } } /* try to solve/re-optimize the LP relaxation */ ret = glp_simplex(mip, &parm); tree->curr->solved++; #if 0 xprintf("ret = %d; status = %d; pbs = %d; dbs = %d; some = %d\n", ret, glp_get_status(mip), mip->pbs_stat, mip->dbs_stat, mip->some); lpx_print_sol(mip, "sol"); #endif return ret; } /**********************************************************************/ IOSPOOL *ios_create_pool(glp_tree *tree) { /* create cut pool */ IOSPOOL *pool; #if 0 pool = dmp_get_atom(tree->pool, sizeof(IOSPOOL)); #else xassert(tree == tree); pool = xmalloc(sizeof(IOSPOOL)); #endif pool->size = 0; pool->head = pool->tail = NULL; pool->ord = 0, pool->curr = NULL; return pool; } int ios_add_row(glp_tree *tree, IOSPOOL *pool, const char *name, int klass, int flags, int len, const int ind[], const double val[], int type, double rhs) { /* add row (constraint) to the cut pool */ IOSCUT *cut; IOSAIJ *aij; int k; xassert(pool != NULL); cut = dmp_get_atom(tree->pool, sizeof(IOSCUT)); if (name == NULL || name[0] == '\0') cut->name = NULL; else { for (k = 0; name[k] != '\0'; k++) { if (k == 256) xerror("glp_ios_add_row: cut name too long\n"); if (iscntrl((unsigned char)name[k])) xerror("glp_ios_add_row: cut name contains invalid chara" "cter(s)\n"); } cut->name = dmp_get_atom(tree->pool, strlen(name)+1); strcpy(cut->name, name); } if (!(0 <= klass && klass <= 255)) xerror("glp_ios_add_row: klass = %d; invalid cut class\n", klass); cut->klass = (unsigned char)klass; if (flags != 0) xerror("glp_ios_add_row: flags = %d; invalid cut flags\n", flags); cut->ptr = NULL; if (!(0 <= len && len <= tree->n)) xerror("glp_ios_add_row: len = %d; invalid cut length\n", len); for (k = 1; k <= len; k++) { aij = dmp_get_atom(tree->pool, sizeof(IOSAIJ)); if (!(1 <= ind[k] && ind[k] <= tree->n)) xerror("glp_ios_add_row: ind[%d] = %d; column index out of " "range\n", k, ind[k]); aij->j = ind[k]; aij->val = val[k]; aij->next = cut->ptr; cut->ptr = aij; } if (!(type == GLP_LO || type == GLP_UP || type == GLP_FX)) xerror("glp_ios_add_row: type = %d; invalid cut type\n", type); cut->type = (unsigned char)type; cut->rhs = rhs; cut->prev = pool->tail; cut->next = NULL; if (cut->prev == NULL) pool->head = cut; else cut->prev->next = cut; pool->tail = cut; pool->size++; return pool->size; } IOSCUT *ios_find_row(IOSPOOL *pool, int i) { /* find row (constraint) in the cut pool */ /* (smart linear search) */ xassert(pool != NULL); xassert(1 <= i && i <= pool->size); if (pool->ord == 0) { xassert(pool->curr == NULL); pool->ord = 1; pool->curr = pool->head; } xassert(pool->curr != NULL); if (i < pool->ord) { if (i < pool->ord - i) { pool->ord = 1; pool->curr = pool->head; while (pool->ord != i) { pool->ord++; xassert(pool->curr != NULL); pool->curr = pool->curr->next; } } else { while (pool->ord != i) { pool->ord--; xassert(pool->curr != NULL); pool->curr = pool->curr->prev; } } } else if (i > pool->ord) { if (i - pool->ord < pool->size - i) { while (pool->ord != i) { pool->ord++; xassert(pool->curr != NULL); pool->curr = pool->curr->next; } } else { pool->ord = pool->size; pool->curr = pool->tail; while (pool->ord != i) { pool->ord--; xassert(pool->curr != NULL); pool->curr = pool->curr->prev; } } } xassert(pool->ord == i); xassert(pool->curr != NULL); return pool->curr; } void ios_del_row(glp_tree *tree, IOSPOOL *pool, int i) { /* remove row (constraint) from the cut pool */ IOSCUT *cut; IOSAIJ *aij; xassert(pool != NULL); if (!(1 <= i && i <= pool->size)) xerror("glp_ios_del_row: i = %d; cut number out of range\n", i); cut = ios_find_row(pool, i); xassert(pool->curr == cut); if (cut->next != NULL) pool->curr = cut->next; else if (cut->prev != NULL) pool->ord--, pool->curr = cut->prev; else pool->ord = 0, pool->curr = NULL; if (cut->name != NULL) dmp_free_atom(tree->pool, cut->name, strlen(cut->name)+1); if (cut->prev == NULL) { xassert(pool->head == cut); pool->head = cut->next; } else { xassert(cut->prev->next == cut); cut->prev->next = cut->next; } if (cut->next == NULL) { xassert(pool->tail == cut); pool->tail = cut->prev; } else { xassert(cut->next->prev == cut); cut->next->prev = cut->prev; } while (cut->ptr != NULL) { aij = cut->ptr; cut->ptr = aij->next; dmp_free_atom(tree->pool, aij, sizeof(IOSAIJ)); } dmp_free_atom(tree->pool, cut, sizeof(IOSCUT)); pool->size--; return; } void ios_clear_pool(glp_tree *tree, IOSPOOL *pool) { /* remove all rows (constraints) from the cut pool */ xassert(pool != NULL); while (pool->head != NULL) { IOSCUT *cut = pool->head; pool->head = cut->next; if (cut->name != NULL) dmp_free_atom(tree->pool, cut->name, strlen(cut->name)+1); while (cut->ptr != NULL) { IOSAIJ *aij = cut->ptr; cut->ptr = aij->next; dmp_free_atom(tree->pool, aij, sizeof(IOSAIJ)); } dmp_free_atom(tree->pool, cut, sizeof(IOSCUT)); } pool->size = 0; pool->head = pool->tail = NULL; pool->ord = 0, pool->curr = NULL; return; } void ios_delete_pool(glp_tree *tree, IOSPOOL *pool) { /* delete cut pool */ xassert(pool != NULL); ios_clear_pool(tree, pool); xfree(pool); return; } /**********************************************************************/ #if 0 static int refer_to_node(glp_tree *tree, int j) { /* determine node number corresponding to binary variable x[j] or its complement */ glp_prob *mip = tree->mip; int n = mip->n; int *ref; if (j > 0) ref = tree->n_ref; else ref = tree->c_ref, j = - j; xassert(1 <= j && j <= n); if (ref[j] == 0) { /* new node is needed */ SCG *g = tree->g; int n_max = g->n_max; ref[j] = scg_add_nodes(g, 1); if (g->n_max > n_max) { int *save = tree->j_ref; tree->j_ref = xcalloc(1+g->n_max, sizeof(int)); memcpy(&tree->j_ref[1], &save[1], g->n * sizeof(int)); xfree(save); } xassert(ref[j] == g->n); tree->j_ref[ref[j]] = j; xassert(tree->curr != NULL); if (tree->curr->level > 0) tree->curr->own_nn++; } return ref[j]; } #endif #if 0 void ios_add_edge(glp_tree *tree, int j1, int j2) { /* add new edge to the conflict graph */ glp_prob *mip = tree->mip; int n = mip->n; SCGRIB *e; int first, i1, i2; xassert(-n <= j1 && j1 <= +n && j1 != 0); xassert(-n <= j2 && j2 <= +n && j2 != 0); xassert(j1 != j2); /* determine number of the first node, which was added for the current subproblem */ xassert(tree->curr != NULL); first = tree->g->n - tree->curr->own_nn + 1; /* determine node numbers for both endpoints */ i1 = refer_to_node(tree, j1); i2 = refer_to_node(tree, j2); /* add edge (i1,i2) to the conflict graph */ e = scg_add_edge(tree->g, i1, i2); /* if the current subproblem is not the root and both endpoints were created on some previous levels, save the edge */ if (tree->curr->level > 0 && i1 < first && i2 < first) { IOSRIB *rib; rib = dmp_get_atom(tree->pool, sizeof(IOSRIB)); rib->j1 = j1; rib->j2 = j2; rib->e = e; rib->next = tree->curr->e_ptr; tree->curr->e_ptr = rib; } return; } #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/colamd/0000755000076500000240000000000013617375001024633 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/optional/glpk/colamd/colamd.c0000644000076500000240000037022613524616144026253 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === colamd/symamd - a sparse matrix column ordering algorithm ============ */ /* ========================================================================== */ /* COLAMD / SYMAMD colamd: an approximate minimum degree column ordering algorithm, for LU factorization of symmetric or unsymmetric matrices, QR factorization, least squares, interior point methods for linear programming problems, and other related problems. symamd: an approximate minimum degree ordering algorithm for Cholesky factorization of symmetric matrices. Purpose: Colamd computes a permutation Q such that the Cholesky factorization of (AQ)'(AQ) has less fill-in and requires fewer floating point operations than A'A. This also provides a good ordering for sparse partial pivoting methods, P(AQ) = LU, where Q is computed prior to numerical factorization, and P is computed during numerical factorization via conventional partial pivoting with row interchanges. Colamd is the column ordering method used in SuperLU, part of the ScaLAPACK library. It is also available as built-in function in MATLAB Version 6, available from MathWorks, Inc. (http://www.mathworks.com). This routine can be used in place of colmmd in MATLAB. Symamd computes a permutation P of a symmetric matrix A such that the Cholesky factorization of PAP' has less fill-in and requires fewer floating point operations than A. Symamd constructs a matrix M such that M'M has the same nonzero pattern of A, and then orders the columns of M using colmmd. The column ordering of M is then returned as the row and column ordering P of A. Authors: The authors of the code itself are Stefan I. Larimore and Timothy A. Davis (davis at cise.ufl.edu), University of Florida. The algorithm was developed in collaboration with John Gilbert, Xerox PARC, and Esmond Ng, Oak Ridge National Laboratory. Acknowledgements: This work was supported by the National Science Foundation, under grants DMS-9504974 and DMS-9803599. Copyright and License: Copyright (c) 1998-2007, Timothy A. Davis, All Rights Reserved. COLAMD is also available under alternate licenses, contact T. Davis for details. This library is free software; you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation; either version 2.1 of the License, or (at your option) any later version. This library is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with this library; if not, write to the Free Software Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA Permission is hereby granted to use or copy this program under the terms of the GNU LGPL, provided that the Copyright, this License, and the Availability of the original version is retained on all copies. User documentation of any code that uses this code or any modified version of this code must cite the Copyright, this License, the Availability note, and "Used by permission." Permission to modify the code and to distribute modified code is granted, provided the Copyright, this License, and the Availability note are retained, and a notice that the code was modified is included. Availability: The colamd/symamd library is available at http://www.cise.ufl.edu/research/sparse/colamd/ This is the http://www.cise.ufl.edu/research/sparse/colamd/colamd.c file. It requires the colamd.h file. It is required by the colamdmex.c and symamdmex.c files, for the MATLAB interface to colamd and symamd. Appears as ACM Algorithm 836. See the ChangeLog file for changes since Version 1.0. References: T. A. Davis, J. R. Gilbert, S. Larimore, E. Ng, An approximate column minimum degree ordering algorithm, ACM Transactions on Mathematical Software, vol. 30, no. 3., pp. 353-376, 2004. T. A. Davis, J. R. Gilbert, S. Larimore, E. Ng, Algorithm 836: COLAMD, an approximate column minimum degree ordering algorithm, ACM Transactions on Mathematical Software, vol. 30, no. 3., pp. 377-380, 2004. */ /* ========================================================================== */ /* === Description of user-callable routines ================================ */ /* ========================================================================== */ /* COLAMD includes both int and UF_long versions of all its routines. The * description below is for the int version. For UF_long, all int arguments * become UF_long. UF_long is normally defined as long, except for WIN64. ---------------------------------------------------------------------------- colamd_recommended: ---------------------------------------------------------------------------- C syntax: #include "colamd.h" size_t colamd_recommended (int nnz, int n_row, int n_col) ; size_t colamd_l_recommended (UF_long nnz, UF_long n_row, UF_long n_col) ; Purpose: Returns recommended value of Alen for use by colamd. Returns 0 if any input argument is negative. The use of this routine is optional. Not needed for symamd, which dynamically allocates its own memory. Note that in v2.4 and earlier, these routines returned int or long. They now return a value of type size_t. Arguments (all input arguments): int nnz ; Number of nonzeros in the matrix A. This must be the same value as p [n_col] in the call to colamd - otherwise you will get a wrong value of the recommended memory to use. int n_row ; Number of rows in the matrix A. int n_col ; Number of columns in the matrix A. ---------------------------------------------------------------------------- colamd_set_defaults: ---------------------------------------------------------------------------- C syntax: #include "colamd.h" colamd_set_defaults (double knobs [COLAMD_KNOBS]) ; colamd_l_set_defaults (double knobs [COLAMD_KNOBS]) ; Purpose: Sets the default parameters. The use of this routine is optional. Arguments: double knobs [COLAMD_KNOBS] ; Output only. NOTE: the meaning of the dense row/col knobs has changed in v2.4 knobs [0] and knobs [1] control dense row and col detection: Colamd: rows with more than max (16, knobs [COLAMD_DENSE_ROW] * sqrt (n_col)) entries are removed prior to ordering. Columns with more than max (16, knobs [COLAMD_DENSE_COL] * sqrt (MIN (n_row,n_col))) entries are removed prior to ordering, and placed last in the output column ordering. Symamd: uses only knobs [COLAMD_DENSE_ROW], which is knobs [0]. Rows and columns with more than max (16, knobs [COLAMD_DENSE_ROW] * sqrt (n)) entries are removed prior to ordering, and placed last in the output ordering. COLAMD_DENSE_ROW and COLAMD_DENSE_COL are defined as 0 and 1, respectively, in colamd.h. Default values of these two knobs are both 10. Currently, only knobs [0] and knobs [1] are used, but future versions may use more knobs. If so, they will be properly set to their defaults by the future version of colamd_set_defaults, so that the code that calls colamd will not need to change, assuming that you either use colamd_set_defaults, or pass a (double *) NULL pointer as the knobs array to colamd or symamd. knobs [2]: aggressive absorption knobs [COLAMD_AGGRESSIVE] controls whether or not to do aggressive absorption during the ordering. Default is TRUE. ---------------------------------------------------------------------------- colamd: ---------------------------------------------------------------------------- C syntax: #include "colamd.h" int colamd (int n_row, int n_col, int Alen, int *A, int *p, double knobs [COLAMD_KNOBS], int stats [COLAMD_STATS]) ; UF_long colamd_l (UF_long n_row, UF_long n_col, UF_long Alen, UF_long *A, UF_long *p, double knobs [COLAMD_KNOBS], UF_long stats [COLAMD_STATS]) ; Purpose: Computes a column ordering (Q) of A such that P(AQ)=LU or (AQ)'AQ=LL' have less fill-in and require fewer floating point operations than factorizing the unpermuted matrix A or A'A, respectively. Returns: TRUE (1) if successful, FALSE (0) otherwise. Arguments: int n_row ; Input argument. Number of rows in the matrix A. Restriction: n_row >= 0. Colamd returns FALSE if n_row is negative. int n_col ; Input argument. Number of columns in the matrix A. Restriction: n_col >= 0. Colamd returns FALSE if n_col is negative. int Alen ; Input argument. Restriction (see note): Alen >= 2*nnz + 6*(n_col+1) + 4*(n_row+1) + n_col Colamd returns FALSE if these conditions are not met. Note: this restriction makes an modest assumption regarding the size of the two typedef's structures in colamd.h. We do, however, guarantee that Alen >= colamd_recommended (nnz, n_row, n_col) will be sufficient. Note: the macro version does not check for integer overflow, and thus is not recommended. Use the colamd_recommended routine instead. int A [Alen] ; Input argument, undefined on output. A is an integer array of size Alen. Alen must be at least as large as the bare minimum value given above, but this is very low, and can result in excessive run time. For best performance, we recommend that Alen be greater than or equal to colamd_recommended (nnz, n_row, n_col), which adds nnz/5 to the bare minimum value given above. On input, the row indices of the entries in column c of the matrix are held in A [(p [c]) ... (p [c+1]-1)]. The row indices in a given column c need not be in ascending order, and duplicate row indices may be be present. However, colamd will work a little faster if both of these conditions are met (Colamd puts the matrix into this format, if it finds that the the conditions are not met). The matrix is 0-based. That is, rows are in the range 0 to n_row-1, and columns are in the range 0 to n_col-1. Colamd returns FALSE if any row index is out of range. The contents of A are modified during ordering, and are undefined on output. int p [n_col+1] ; Both input and output argument. p is an integer array of size n_col+1. On input, it holds the "pointers" for the column form of the matrix A. Column c of the matrix A is held in A [(p [c]) ... (p [c+1]-1)]. The first entry, p [0], must be zero, and p [c] <= p [c+1] must hold for all c in the range 0 to n_col-1. The value p [n_col] is thus the total number of entries in the pattern of the matrix A. Colamd returns FALSE if these conditions are not met. On output, if colamd returns TRUE, the array p holds the column permutation (Q, for P(AQ)=LU or (AQ)'(AQ)=LL'), where p [0] is the first column index in the new ordering, and p [n_col-1] is the last. That is, p [k] = j means that column j of A is the kth pivot column, in AQ, where k is in the range 0 to n_col-1 (p [0] = j means that column j of A is the first column in AQ). If colamd returns FALSE, then no permutation is returned, and p is undefined on output. double knobs [COLAMD_KNOBS] ; Input argument. See colamd_set_defaults for a description. int stats [COLAMD_STATS] ; Output argument. Statistics on the ordering, and error status. See colamd.h for related definitions. Colamd returns FALSE if stats is not present. stats [0]: number of dense or empty rows ignored. stats [1]: number of dense or empty columns ignored (and ordered last in the output permutation p) Note that a row can become "empty" if it contains only "dense" and/or "empty" columns, and similarly a column can become "empty" if it only contains "dense" and/or "empty" rows. stats [2]: number of garbage collections performed. This can be excessively high if Alen is close to the minimum required value. stats [3]: status code. < 0 is an error code. > 1 is a warning or notice. 0 OK. Each column of the input matrix contained row indices in increasing order, with no duplicates. 1 OK, but columns of input matrix were jumbled (unsorted columns or duplicate entries). Colamd had to do some extra work to sort the matrix first and remove duplicate entries, but it still was able to return a valid permutation (return value of colamd was TRUE). stats [4]: highest numbered column that is unsorted or has duplicate entries. stats [5]: last seen duplicate or unsorted row index. stats [6]: number of duplicate or unsorted row indices. -1 A is a null pointer -2 p is a null pointer -3 n_row is negative stats [4]: n_row -4 n_col is negative stats [4]: n_col -5 number of nonzeros in matrix is negative stats [4]: number of nonzeros, p [n_col] -6 p [0] is nonzero stats [4]: p [0] -7 A is too small stats [4]: required size stats [5]: actual size (Alen) -8 a column has a negative number of entries stats [4]: column with < 0 entries stats [5]: number of entries in col -9 a row index is out of bounds stats [4]: column with bad row index stats [5]: bad row index stats [6]: n_row, # of rows of matrx -10 (unused; see symamd.c) -999 (unused; see symamd.c) Future versions may return more statistics in the stats array. Example: See http://www.cise.ufl.edu/research/sparse/colamd/example.c for a complete example. To order the columns of a 5-by-4 matrix with 11 nonzero entries in the following nonzero pattern x 0 x 0 x 0 x x 0 x x 0 0 0 x x x x 0 0 with default knobs and no output statistics, do the following: #include "colamd.h" #define ALEN 100 int A [ALEN] = {0, 1, 4, 2, 4, 0, 1, 2, 3, 1, 3} ; int p [ ] = {0, 3, 5, 9, 11} ; int stats [COLAMD_STATS] ; colamd (5, 4, ALEN, A, p, (double *) NULL, stats) ; The permutation is returned in the array p, and A is destroyed. ---------------------------------------------------------------------------- symamd: ---------------------------------------------------------------------------- C syntax: #include "colamd.h" int symamd (int n, int *A, int *p, int *perm, double knobs [COLAMD_KNOBS], int stats [COLAMD_STATS], void (*allocate) (size_t, size_t), void (*release) (void *)) ; UF_long symamd_l (UF_long n, UF_long *A, UF_long *p, UF_long *perm, double knobs [COLAMD_KNOBS], UF_long stats [COLAMD_STATS], void (*allocate) (size_t, size_t), void (*release) (void *)) ; Purpose: The symamd routine computes an ordering P of a symmetric sparse matrix A such that the Cholesky factorization PAP' = LL' remains sparse. It is based on a column ordering of a matrix M constructed so that the nonzero pattern of M'M is the same as A. The matrix A is assumed to be symmetric; only the strictly lower triangular part is accessed. You must pass your selected memory allocator (usually calloc/free or mxCalloc/mxFree) to symamd, for it to allocate memory for the temporary matrix M. Returns: TRUE (1) if successful, FALSE (0) otherwise. Arguments: int n ; Input argument. Number of rows and columns in the symmetrix matrix A. Restriction: n >= 0. Symamd returns FALSE if n is negative. int A [nnz] ; Input argument. A is an integer array of size nnz, where nnz = p [n]. The row indices of the entries in column c of the matrix are held in A [(p [c]) ... (p [c+1]-1)]. The row indices in a given column c need not be in ascending order, and duplicate row indices may be present. However, symamd will run faster if the columns are in sorted order with no duplicate entries. The matrix is 0-based. That is, rows are in the range 0 to n-1, and columns are in the range 0 to n-1. Symamd returns FALSE if any row index is out of range. The contents of A are not modified. int p [n+1] ; Input argument. p is an integer array of size n+1. On input, it holds the "pointers" for the column form of the matrix A. Column c of the matrix A is held in A [(p [c]) ... (p [c+1]-1)]. The first entry, p [0], must be zero, and p [c] <= p [c+1] must hold for all c in the range 0 to n-1. The value p [n] is thus the total number of entries in the pattern of the matrix A. Symamd returns FALSE if these conditions are not met. The contents of p are not modified. int perm [n+1] ; Output argument. On output, if symamd returns TRUE, the array perm holds the permutation P, where perm [0] is the first index in the new ordering, and perm [n-1] is the last. That is, perm [k] = j means that row and column j of A is the kth column in PAP', where k is in the range 0 to n-1 (perm [0] = j means that row and column j of A are the first row and column in PAP'). The array is used as a workspace during the ordering, which is why it must be of length n+1, not just n. double knobs [COLAMD_KNOBS] ; Input argument. See colamd_set_defaults for a description. int stats [COLAMD_STATS] ; Output argument. Statistics on the ordering, and error status. See colamd.h for related definitions. Symamd returns FALSE if stats is not present. stats [0]: number of dense or empty row and columns ignored (and ordered last in the output permutation perm). Note that a row/column can become "empty" if it contains only "dense" and/or "empty" columns/rows. stats [1]: (same as stats [0]) stats [2]: number of garbage collections performed. stats [3]: status code. < 0 is an error code. > 1 is a warning or notice. 0 OK. Each column of the input matrix contained row indices in increasing order, with no duplicates. 1 OK, but columns of input matrix were jumbled (unsorted columns or duplicate entries). Symamd had to do some extra work to sort the matrix first and remove duplicate entries, but it still was able to return a valid permutation (return value of symamd was TRUE). stats [4]: highest numbered column that is unsorted or has duplicate entries. stats [5]: last seen duplicate or unsorted row index. stats [6]: number of duplicate or unsorted row indices. -1 A is a null pointer -2 p is a null pointer -3 (unused, see colamd.c) -4 n is negative stats [4]: n -5 number of nonzeros in matrix is negative stats [4]: # of nonzeros (p [n]). -6 p [0] is nonzero stats [4]: p [0] -7 (unused) -8 a column has a negative number of entries stats [4]: column with < 0 entries stats [5]: number of entries in col -9 a row index is out of bounds stats [4]: column with bad row index stats [5]: bad row index stats [6]: n_row, # of rows of matrx -10 out of memory (unable to allocate temporary workspace for M or count arrays using the "allocate" routine passed into symamd). Future versions may return more statistics in the stats array. void * (*allocate) (size_t, size_t) A pointer to a function providing memory allocation. The allocated memory must be returned initialized to zero. For a C application, this argument should normally be a pointer to calloc. For a MATLAB mexFunction, the routine mxCalloc is passed instead. void (*release) (size_t, size_t) A pointer to a function that frees memory allocated by the memory allocation routine above. For a C application, this argument should normally be a pointer to free. For a MATLAB mexFunction, the routine mxFree is passed instead. ---------------------------------------------------------------------------- colamd_report: ---------------------------------------------------------------------------- C syntax: #include "colamd.h" colamd_report (int stats [COLAMD_STATS]) ; colamd_l_report (UF_long stats [COLAMD_STATS]) ; Purpose: Prints the error status and statistics recorded in the stats array on the standard error output (for a standard C routine) or on the MATLAB output (for a mexFunction). Arguments: int stats [COLAMD_STATS] ; Input only. Statistics from colamd. ---------------------------------------------------------------------------- symamd_report: ---------------------------------------------------------------------------- C syntax: #include "colamd.h" symamd_report (int stats [COLAMD_STATS]) ; symamd_l_report (UF_long stats [COLAMD_STATS]) ; Purpose: Prints the error status and statistics recorded in the stats array on the standard error output (for a standard C routine) or on the MATLAB output (for a mexFunction). Arguments: int stats [COLAMD_STATS] ; Input only. Statistics from symamd. */ /* ========================================================================== */ /* === Scaffolding code definitions ======================================== */ /* ========================================================================== */ /* Ensure that debugging is turned off: */ #ifndef NDEBUG #define NDEBUG #endif /* turn on debugging by uncommenting the following line #undef NDEBUG */ /* Our "scaffolding code" philosophy: In our opinion, well-written library code should keep its "debugging" code, and just normally have it turned off by the compiler so as not to interfere with performance. This serves several purposes: (1) assertions act as comments to the reader, telling you what the code expects at that point. All assertions will always be true (unless there really is a bug, of course). (2) leaving in the scaffolding code assists anyone who would like to modify the code, or understand the algorithm (by reading the debugging output, one can get a glimpse into what the code is doing). (3) (gasp!) for actually finding bugs. This code has been heavily tested and "should" be fully functional and bug-free ... but you never know... The code will become outrageously slow when debugging is enabled. To control the level of debugging output, set an environment variable D to 0 (little), 1 (some), 2, 3, or 4 (lots). When debugging, you should see the following message on the standard output: colamd: debug version, D = 1 (THIS WILL BE SLOW!) or a similar message for symamd. If you don't, then debugging has not been enabled. */ /* ========================================================================== */ /* === Include files ======================================================== */ /* ========================================================================== */ #pragma clang diagnostic ignored "-Wsign-conversion" #pragma clang diagnostic ignored "-Wshorten-64-to-32" #include "colamd.h" #if 0 /* by mao */ #include #include #ifdef MATLAB_MEX_FILE #include "mex.h" #include "matrix.h" #endif /* MATLAB_MEX_FILE */ #if !defined (NPRINT) || !defined (NDEBUG) #include #endif #ifndef NULL #define NULL ((void *) 0) #endif #endif /* ========================================================================== */ /* === int or UF_long ======================================================= */ /* ========================================================================== */ #if 0 /* by mao */ /* define UF_long */ #include "UFconfig.h" #endif #ifdef DLONG #define Int UF_long #define ID UF_long_id #define Int_MAX UF_long_max #define COLAMD_recommended colamd_l_recommended #define COLAMD_set_defaults colamd_l_set_defaults #define COLAMD_MAIN colamd_l #define SYMAMD_MAIN symamd_l #define COLAMD_report colamd_l_report #define SYMAMD_report symamd_l_report #else #define Int int #define ID "%d" #define Int_MAX INT_MAX #define COLAMD_recommended colamd_recommended #define COLAMD_set_defaults colamd_set_defaults #define COLAMD_MAIN colamd #define SYMAMD_MAIN symamd #define COLAMD_report colamd_report #define SYMAMD_report symamd_report #endif /* ========================================================================== */ /* === Row and Column structures ============================================ */ /* ========================================================================== */ /* User code that makes use of the colamd/symamd routines need not directly */ /* reference these structures. They are used only for colamd_recommended. */ typedef struct Colamd_Col_struct { Int start ; /* index for A of first row in this column, or DEAD */ /* if column is dead */ Int length ; /* number of rows in this column */ union { Int thickness ; /* number of original columns represented by this */ /* col, if the column is alive */ Int parent ; /* parent in parent tree super-column structure, if */ /* the column is dead */ } shared1 ; union { Int score ; /* the score used to maintain heap, if col is alive */ Int order ; /* pivot ordering of this column, if col is dead */ } shared2 ; union { Int headhash ; /* head of a hash bucket, if col is at the head of */ /* a degree list */ Int hash ; /* hash value, if col is not in a degree list */ Int prev ; /* previous column in degree list, if col is in a */ /* degree list (but not at the head of a degree list) */ } shared3 ; union { Int degree_next ; /* next column, if col is in a degree list */ Int hash_next ; /* next column, if col is in a hash list */ } shared4 ; } Colamd_Col ; typedef struct Colamd_Row_struct { Int start ; /* index for A of first col in this row */ Int length ; /* number of principal columns in this row */ union { Int degree ; /* number of principal & non-principal columns in row */ Int p ; /* used as a row pointer in init_rows_cols () */ } shared1 ; union { Int mark ; /* for computing set differences and marking dead rows*/ Int first_column ;/* first column in row (used in garbage collection) */ } shared2 ; } Colamd_Row ; /* ========================================================================== */ /* === Definitions ========================================================== */ /* ========================================================================== */ /* Routines are either PUBLIC (user-callable) or PRIVATE (not user-callable) */ #define PUBLIC #define PRIVATE static #define DENSE_DEGREE(alpha,n) \ ((Int) MAX (16.0, (alpha) * sqrt ((double) (n)))) #define MAX(a,b) (((a) > (b)) ? (a) : (b)) #define MIN(a,b) (((a) < (b)) ? (a) : (b)) #define ONES_COMPLEMENT(r) (-(r)-1) /* -------------------------------------------------------------------------- */ /* Change for version 2.1: define TRUE and FALSE only if not yet defined */ /* -------------------------------------------------------------------------- */ #ifndef TRUE #define TRUE (1) #endif #ifndef FALSE #define FALSE (0) #endif /* -------------------------------------------------------------------------- */ #define EMPTY (-1) /* Row and column status */ #define ALIVE (0) #define DEAD (-1) /* Column status */ #define DEAD_PRINCIPAL (-1) #define DEAD_NON_PRINCIPAL (-2) /* Macros for row and column status update and checking. */ #define ROW_IS_DEAD(r) ROW_IS_MARKED_DEAD (Row[r].shared2.mark) #define ROW_IS_MARKED_DEAD(row_mark) (row_mark < ALIVE) #define ROW_IS_ALIVE(r) (Row [r].shared2.mark >= ALIVE) #define COL_IS_DEAD(c) (Col [c].start < ALIVE) #define COL_IS_ALIVE(c) (Col [c].start >= ALIVE) #define COL_IS_DEAD_PRINCIPAL(c) (Col [c].start == DEAD_PRINCIPAL) #define KILL_ROW(r) { Row [r].shared2.mark = DEAD ; } #define KILL_PRINCIPAL_COL(c) { Col [c].start = DEAD_PRINCIPAL ; } #define KILL_NON_PRINCIPAL_COL(c) { Col [c].start = DEAD_NON_PRINCIPAL ; } /* ========================================================================== */ /* === Colamd reporting mechanism =========================================== */ /* ========================================================================== */ #if defined (MATLAB_MEX_FILE) || defined (MATHWORKS) /* In MATLAB, matrices are 1-based to the user, but 0-based internally */ #define INDEX(i) ((i)+1) #else /* In C, matrices are 0-based and indices are reported as such in *_report */ #define INDEX(i) (i) #endif /* All output goes through the PRINTF macro. */ #define PRINTF(params) { if (colamd_printf != NULL) (void) colamd_printf params ; } /* ========================================================================== */ /* === Prototypes of PRIVATE routines ======================================= */ /* ========================================================================== */ PRIVATE Int init_rows_cols ( Int n_row, Int n_col, Colamd_Row Row [], Colamd_Col Col [], Int A [], Int p [], Int stats [COLAMD_STATS] ) ; PRIVATE void init_scoring ( Int n_row, Int n_col, Colamd_Row Row [], Colamd_Col Col [], Int A [], Int head [], double knobs [COLAMD_KNOBS], Int *p_n_row2, Int *p_n_col2, Int *p_max_deg ) ; PRIVATE Int find_ordering ( Int n_row, Int n_col, Int Alen, Colamd_Row Row [], Colamd_Col Col [], Int A [], Int head [], Int n_col2, Int max_deg, Int pfree, Int aggressive ) ; PRIVATE void order_children ( Int n_col, Colamd_Col Col [], Int p [] ) ; PRIVATE void detect_super_cols ( #ifndef NDEBUG Int n_col, Colamd_Row Row [], #endif /* NDEBUG */ Colamd_Col Col [], Int A [], Int head [], Int row_start, Int row_length ) ; PRIVATE Int garbage_collection ( Int n_row, Int n_col, Colamd_Row Row [], Colamd_Col Col [], Int A [], Int *pfree ) ; PRIVATE Int clear_mark ( Int tag_mark, Int max_mark, Int n_row, Colamd_Row Row [] ) ; PRIVATE void print_report ( char *method, Int stats [COLAMD_STATS] ) ; /* ========================================================================== */ /* === Debugging prototypes and definitions ================================= */ /* ========================================================================== */ #ifndef NDEBUG #if 0 /* by mao */ #include #endif /* colamd_debug is the *ONLY* global variable, and is only */ /* present when debugging */ PRIVATE Int colamd_debug = 0 ; /* debug print level */ #define DEBUG0(params) { PRINTF (params) ; } #define DEBUG1(params) { if (colamd_debug >= 1) PRINTF (params) ; } #define DEBUG2(params) { if (colamd_debug >= 2) PRINTF (params) ; } #define DEBUG3(params) { if (colamd_debug >= 3) PRINTF (params) ; } #define DEBUG4(params) { if (colamd_debug >= 4) PRINTF (params) ; } #if 0 /* by mao */ #ifdef MATLAB_MEX_FILE #define ASSERT(expression) (mxAssert ((expression), "")) #else #define ASSERT(expression) (assert (expression)) #endif /* MATLAB_MEX_FILE */ #else #define ASSERT xassert #endif PRIVATE void colamd_get_debug /* gets the debug print level from getenv */ ( char *method ) ; PRIVATE void debug_deg_lists ( Int n_row, Int n_col, Colamd_Row Row [], Colamd_Col Col [], Int head [], Int min_score, Int should, Int max_deg ) ; PRIVATE void debug_mark ( Int n_row, Colamd_Row Row [], Int tag_mark, Int max_mark ) ; PRIVATE void debug_matrix ( Int n_row, Int n_col, Colamd_Row Row [], Colamd_Col Col [], Int A [] ) ; PRIVATE void debug_structures ( Int n_row, Int n_col, Colamd_Row Row [], Colamd_Col Col [], Int A [], Int n_col2 ) ; #else /* NDEBUG */ /* === No debugging ========================================================= */ #define DEBUG0(params) ; #define DEBUG1(params) ; #define DEBUG2(params) ; #define DEBUG3(params) ; #define DEBUG4(params) ; #define ASSERT(expression) #endif /* NDEBUG */ /* ========================================================================== */ /* === USER-CALLABLE ROUTINES: ============================================== */ /* ========================================================================== */ /* ========================================================================== */ /* === colamd_recommended =================================================== */ /* ========================================================================== */ /* The colamd_recommended routine returns the suggested size for Alen. This value has been determined to provide good balance between the number of garbage collections and the memory requirements for colamd. If any argument is negative, or if integer overflow occurs, a 0 is returned as an error condition. 2*nnz space is required for the row and column indices of the matrix. COLAMD_C (n_col) + COLAMD_R (n_row) space is required for the Col and Row arrays, respectively, which are internal to colamd (roughly 6*n_col + 4*n_row). An additional n_col space is the minimal amount of "elbow room", and nnz/5 more space is recommended for run time efficiency. Alen is approximately 2.2*nnz + 7*n_col + 4*n_row + 10. This function is not needed when using symamd. */ /* add two values of type size_t, and check for integer overflow */ static size_t t_add (size_t a, size_t b, int *ok) { (*ok) = (*ok) && ((a + b) >= MAX (a,b)) ; return ((*ok) ? (a + b) : 0) ; } /* compute a*k where k is a small integer, and check for integer overflow */ static size_t t_mult (size_t a, size_t k, int *ok) { size_t i, s = 0 ; for (i = 0 ; i < k ; i++) { s = t_add (s, a, ok) ; } return (s) ; } /* size of the Col and Row structures */ #define COLAMD_C(n_col,ok) \ ((t_mult (t_add (n_col, 1, ok), sizeof (Colamd_Col), ok) / sizeof (Int))) #define COLAMD_R(n_row,ok) \ ((t_mult (t_add (n_row, 1, ok), sizeof (Colamd_Row), ok) / sizeof (Int))) PUBLIC size_t COLAMD_recommended /* returns recommended value of Alen. */ ( /* === Parameters ======================================================= */ Int nnz, /* number of nonzeros in A */ Int n_row, /* number of rows in A */ Int n_col /* number of columns in A */ ) { size_t s, c, r ; int ok = TRUE ; if (nnz < 0 || n_row < 0 || n_col < 0) { return (0) ; } s = t_mult (nnz, 2, &ok) ; /* 2*nnz */ c = COLAMD_C (n_col, &ok) ; /* size of column structures */ r = COLAMD_R (n_row, &ok) ; /* size of row structures */ s = t_add (s, c, &ok) ; s = t_add (s, r, &ok) ; s = t_add (s, n_col, &ok) ; /* elbow room */ s = t_add (s, nnz/5, &ok) ; /* elbow room */ ok = ok && (s < Int_MAX) ; return (ok ? s : 0) ; } /* ========================================================================== */ /* === colamd_set_defaults ================================================== */ /* ========================================================================== */ /* The colamd_set_defaults routine sets the default values of the user- controllable parameters for colamd and symamd: Colamd: rows with more than max (16, knobs [0] * sqrt (n_col)) entries are removed prior to ordering. Columns with more than max (16, knobs [1] * sqrt (MIN (n_row,n_col))) entries are removed prior to ordering, and placed last in the output column ordering. Symamd: Rows and columns with more than max (16, knobs [0] * sqrt (n)) entries are removed prior to ordering, and placed last in the output ordering. knobs [0] dense row control knobs [1] dense column control knobs [2] if nonzero, do aggresive absorption knobs [3..19] unused, but future versions might use this */ PUBLIC void COLAMD_set_defaults ( /* === Parameters ======================================================= */ double knobs [COLAMD_KNOBS] /* knob array */ ) { /* === Local variables ================================================== */ Int i ; if (!knobs) { return ; /* no knobs to initialize */ } for (i = 0 ; i < COLAMD_KNOBS ; i++) { knobs [i] = 0 ; } knobs [COLAMD_DENSE_ROW] = 10 ; knobs [COLAMD_DENSE_COL] = 10 ; knobs [COLAMD_AGGRESSIVE] = TRUE ; /* default: do aggressive absorption*/ } /* ========================================================================== */ /* === symamd =============================================================== */ /* ========================================================================== */ PUBLIC Int SYMAMD_MAIN /* return TRUE if OK, FALSE otherwise */ ( /* === Parameters ======================================================= */ Int n, /* number of rows and columns of A */ Int A [], /* row indices of A */ Int p [], /* column pointers of A */ Int perm [], /* output permutation, size n+1 */ double knobs [COLAMD_KNOBS], /* parameters (uses defaults if NULL) */ Int stats [COLAMD_STATS], /* output statistics and error codes */ void * (*allocate) (size_t, size_t), /* pointer to calloc (ANSI C) or */ /* mxCalloc (for MATLAB mexFunction) */ void (*release) (void *) /* pointer to free (ANSI C) or */ /* mxFree (for MATLAB mexFunction) */ ) { /* === Local variables ================================================== */ Int *count ; /* length of each column of M, and col pointer*/ Int *mark ; /* mark array for finding duplicate entries */ Int *M ; /* row indices of matrix M */ size_t Mlen ; /* length of M */ Int n_row ; /* number of rows in M */ Int nnz ; /* number of entries in A */ Int i ; /* row index of A */ Int j ; /* column index of A */ Int k ; /* row index of M */ Int mnz ; /* number of nonzeros in M */ Int pp ; /* index into a column of A */ Int last_row ; /* last row seen in the current column */ Int length ; /* number of nonzeros in a column */ double cknobs [COLAMD_KNOBS] ; /* knobs for colamd */ double default_knobs [COLAMD_KNOBS] ; /* default knobs for colamd */ #ifndef NDEBUG colamd_get_debug ("symamd") ; #endif /* NDEBUG */ /* === Check the input arguments ======================================== */ if (!stats) { DEBUG0 (("symamd: stats not present\n")) ; return (FALSE) ; } for (i = 0 ; i < COLAMD_STATS ; i++) { stats [i] = 0 ; } stats [COLAMD_STATUS] = COLAMD_OK ; stats [COLAMD_INFO1] = -1 ; stats [COLAMD_INFO2] = -1 ; if (!A) { stats [COLAMD_STATUS] = COLAMD_ERROR_A_not_present ; DEBUG0 (("symamd: A not present\n")) ; return (FALSE) ; } if (!p) /* p is not present */ { stats [COLAMD_STATUS] = COLAMD_ERROR_p_not_present ; DEBUG0 (("symamd: p not present\n")) ; return (FALSE) ; } if (n < 0) /* n must be >= 0 */ { stats [COLAMD_STATUS] = COLAMD_ERROR_ncol_negative ; stats [COLAMD_INFO1] = n ; DEBUG0 (("symamd: n negative %d\n", n)) ; return (FALSE) ; } nnz = p [n] ; if (nnz < 0) /* nnz must be >= 0 */ { stats [COLAMD_STATUS] = COLAMD_ERROR_nnz_negative ; stats [COLAMD_INFO1] = nnz ; DEBUG0 (("symamd: number of entries negative %d\n", nnz)) ; return (FALSE) ; } if (p [0] != 0) { stats [COLAMD_STATUS] = COLAMD_ERROR_p0_nonzero ; stats [COLAMD_INFO1] = p [0] ; DEBUG0 (("symamd: p[0] not zero %d\n", p [0])) ; return (FALSE) ; } /* === If no knobs, set default knobs =================================== */ if (!knobs) { COLAMD_set_defaults (default_knobs) ; knobs = default_knobs ; } /* === Allocate count and mark ========================================== */ count = (Int *) ((*allocate) (n+1, sizeof (Int))) ; if (!count) { stats [COLAMD_STATUS] = COLAMD_ERROR_out_of_memory ; DEBUG0 (("symamd: allocate count (size %d) failed\n", n+1)) ; return (FALSE) ; } mark = (Int *) ((*allocate) (n+1, sizeof (Int))) ; if (!mark) { stats [COLAMD_STATUS] = COLAMD_ERROR_out_of_memory ; (*release) ((void *) count) ; DEBUG0 (("symamd: allocate mark (size %d) failed\n", n+1)) ; return (FALSE) ; } /* === Compute column counts of M, check if A is valid ================== */ stats [COLAMD_INFO3] = 0 ; /* number of duplicate or unsorted row indices*/ for (i = 0 ; i < n ; i++) { mark [i] = -1 ; } for (j = 0 ; j < n ; j++) { last_row = -1 ; length = p [j+1] - p [j] ; if (length < 0) { /* column pointers must be non-decreasing */ stats [COLAMD_STATUS] = COLAMD_ERROR_col_length_negative ; stats [COLAMD_INFO1] = j ; stats [COLAMD_INFO2] = length ; (*release) ((void *) count) ; (*release) ((void *) mark) ; DEBUG0 (("symamd: col %d negative length %d\n", j, length)) ; return (FALSE) ; } for (pp = p [j] ; pp < p [j+1] ; pp++) { i = A [pp] ; if (i < 0 || i >= n) { /* row index i, in column j, is out of bounds */ stats [COLAMD_STATUS] = COLAMD_ERROR_row_index_out_of_bounds ; stats [COLAMD_INFO1] = j ; stats [COLAMD_INFO2] = i ; stats [COLAMD_INFO3] = n ; (*release) ((void *) count) ; (*release) ((void *) mark) ; DEBUG0 (("symamd: row %d col %d out of bounds\n", i, j)) ; return (FALSE) ; } if (i <= last_row || mark [i] == j) { /* row index is unsorted or repeated (or both), thus col */ /* is jumbled. This is a notice, not an error condition. */ stats [COLAMD_STATUS] = COLAMD_OK_BUT_JUMBLED ; stats [COLAMD_INFO1] = j ; stats [COLAMD_INFO2] = i ; (stats [COLAMD_INFO3]) ++ ; DEBUG1 (("symamd: row %d col %d unsorted/duplicate\n", i, j)) ; } if (i > j && mark [i] != j) { /* row k of M will contain column indices i and j */ count [i]++ ; count [j]++ ; } /* mark the row as having been seen in this column */ mark [i] = j ; last_row = i ; } } /* v2.4: removed free(mark) */ /* === Compute column pointers of M ===================================== */ /* use output permutation, perm, for column pointers of M */ perm [0] = 0 ; for (j = 1 ; j <= n ; j++) { perm [j] = perm [j-1] + count [j-1] ; } for (j = 0 ; j < n ; j++) { count [j] = perm [j] ; } /* === Construct M ====================================================== */ mnz = perm [n] ; n_row = mnz / 2 ; Mlen = COLAMD_recommended (mnz, n_row, n) ; M = (Int *) ((*allocate) (Mlen, sizeof (Int))) ; DEBUG0 (("symamd: M is %d-by-%d with %d entries, Mlen = %g\n", n_row, n, mnz, (double) Mlen)) ; if (!M) { stats [COLAMD_STATUS] = COLAMD_ERROR_out_of_memory ; (*release) ((void *) count) ; (*release) ((void *) mark) ; DEBUG0 (("symamd: allocate M (size %g) failed\n", (double) Mlen)) ; return (FALSE) ; } k = 0 ; if (stats [COLAMD_STATUS] == COLAMD_OK) { /* Matrix is OK */ for (j = 0 ; j < n ; j++) { ASSERT (p [j+1] - p [j] >= 0) ; for (pp = p [j] ; pp < p [j+1] ; pp++) { i = A [pp] ; ASSERT (i >= 0 && i < n) ; if (i > j) { /* row k of M contains column indices i and j */ M [count [i]++] = k ; M [count [j]++] = k ; k++ ; } } } } else { /* Matrix is jumbled. Do not add duplicates to M. Unsorted cols OK. */ DEBUG0 (("symamd: Duplicates in A.\n")) ; for (i = 0 ; i < n ; i++) { mark [i] = -1 ; } for (j = 0 ; j < n ; j++) { ASSERT (p [j+1] - p [j] >= 0) ; for (pp = p [j] ; pp < p [j+1] ; pp++) { i = A [pp] ; ASSERT (i >= 0 && i < n) ; if (i > j && mark [i] != j) { /* row k of M contains column indices i and j */ M [count [i]++] = k ; M [count [j]++] = k ; k++ ; mark [i] = j ; } } } /* v2.4: free(mark) moved below */ } /* count and mark no longer needed */ (*release) ((void *) count) ; (*release) ((void *) mark) ; /* v2.4: free (mark) moved here */ ASSERT (k == n_row) ; /* === Adjust the knobs for M =========================================== */ for (i = 0 ; i < COLAMD_KNOBS ; i++) { cknobs [i] = knobs [i] ; } /* there are no dense rows in M */ cknobs [COLAMD_DENSE_ROW] = -1 ; cknobs [COLAMD_DENSE_COL] = knobs [COLAMD_DENSE_ROW] ; /* === Order the columns of M =========================================== */ /* v2.4: colamd cannot fail here, so the error check is removed */ (void) COLAMD_MAIN (n_row, n, (Int) Mlen, M, perm, cknobs, stats) ; /* Note that the output permutation is now in perm */ /* === get the statistics for symamd from colamd ======================== */ /* a dense column in colamd means a dense row and col in symamd */ stats [COLAMD_DENSE_ROW] = stats [COLAMD_DENSE_COL] ; /* === Free M =========================================================== */ (*release) ((void *) M) ; DEBUG0 (("symamd: done.\n")) ; return (TRUE) ; } /* ========================================================================== */ /* === colamd =============================================================== */ /* ========================================================================== */ /* The colamd routine computes a column ordering Q of a sparse matrix A such that the LU factorization P(AQ) = LU remains sparse, where P is selected via partial pivoting. The routine can also be viewed as providing a permutation Q such that the Cholesky factorization (AQ)'(AQ) = LL' remains sparse. */ PUBLIC Int COLAMD_MAIN /* returns TRUE if successful, FALSE otherwise*/ ( /* === Parameters ======================================================= */ Int n_row, /* number of rows in A */ Int n_col, /* number of columns in A */ Int Alen, /* length of A */ Int A [], /* row indices of A */ Int p [], /* pointers to columns in A */ double knobs [COLAMD_KNOBS],/* parameters (uses defaults if NULL) */ Int stats [COLAMD_STATS] /* output statistics and error codes */ ) { /* === Local variables ================================================== */ Int i ; /* loop index */ Int nnz ; /* nonzeros in A */ size_t Row_size ; /* size of Row [], in integers */ size_t Col_size ; /* size of Col [], in integers */ size_t need ; /* minimum required length of A */ Colamd_Row *Row ; /* pointer into A of Row [0..n_row] array */ Colamd_Col *Col ; /* pointer into A of Col [0..n_col] array */ Int n_col2 ; /* number of non-dense, non-empty columns */ Int n_row2 ; /* number of non-dense, non-empty rows */ Int ngarbage ; /* number of garbage collections performed */ Int max_deg ; /* maximum row degree */ double default_knobs [COLAMD_KNOBS] ; /* default knobs array */ Int aggressive ; /* do aggressive absorption */ int ok ; #ifndef NDEBUG colamd_get_debug ("colamd") ; #endif /* NDEBUG */ /* === Check the input arguments ======================================== */ if (!stats) { DEBUG0 (("colamd: stats not present\n")) ; return (FALSE) ; } for (i = 0 ; i < COLAMD_STATS ; i++) { stats [i] = 0 ; } stats [COLAMD_STATUS] = COLAMD_OK ; stats [COLAMD_INFO1] = -1 ; stats [COLAMD_INFO2] = -1 ; if (!A) /* A is not present */ { stats [COLAMD_STATUS] = COLAMD_ERROR_A_not_present ; DEBUG0 (("colamd: A not present\n")) ; return (FALSE) ; } if (!p) /* p is not present */ { stats [COLAMD_STATUS] = COLAMD_ERROR_p_not_present ; DEBUG0 (("colamd: p not present\n")) ; return (FALSE) ; } if (n_row < 0) /* n_row must be >= 0 */ { stats [COLAMD_STATUS] = COLAMD_ERROR_nrow_negative ; stats [COLAMD_INFO1] = n_row ; DEBUG0 (("colamd: nrow negative %d\n", n_row)) ; return (FALSE) ; } if (n_col < 0) /* n_col must be >= 0 */ { stats [COLAMD_STATUS] = COLAMD_ERROR_ncol_negative ; stats [COLAMD_INFO1] = n_col ; DEBUG0 (("colamd: ncol negative %d\n", n_col)) ; return (FALSE) ; } nnz = p [n_col] ; if (nnz < 0) /* nnz must be >= 0 */ { stats [COLAMD_STATUS] = COLAMD_ERROR_nnz_negative ; stats [COLAMD_INFO1] = nnz ; DEBUG0 (("colamd: number of entries negative %d\n", nnz)) ; return (FALSE) ; } if (p [0] != 0) { stats [COLAMD_STATUS] = COLAMD_ERROR_p0_nonzero ; stats [COLAMD_INFO1] = p [0] ; DEBUG0 (("colamd: p[0] not zero %d\n", p [0])) ; return (FALSE) ; } /* === If no knobs, set default knobs =================================== */ if (!knobs) { COLAMD_set_defaults (default_knobs) ; knobs = default_knobs ; } aggressive = (knobs [COLAMD_AGGRESSIVE] != FALSE) ; /* === Allocate the Row and Col arrays from array A ===================== */ ok = TRUE ; Col_size = COLAMD_C (n_col, &ok) ; /* size of Col array of structs */ Row_size = COLAMD_R (n_row, &ok) ; /* size of Row array of structs */ /* need = 2*nnz + n_col + Col_size + Row_size ; */ need = t_mult (nnz, 2, &ok) ; need = t_add (need, n_col, &ok) ; need = t_add (need, Col_size, &ok) ; need = t_add (need, Row_size, &ok) ; if (!ok || need > (size_t) Alen || need > Int_MAX) { /* not enough space in array A to perform the ordering */ stats [COLAMD_STATUS] = COLAMD_ERROR_A_too_small ; stats [COLAMD_INFO1] = need ; stats [COLAMD_INFO2] = Alen ; DEBUG0 (("colamd: Need Alen >= %d, given only Alen = %d\n", need,Alen)); return (FALSE) ; } Alen -= Col_size + Row_size ; Col = (Colamd_Col *) &A [Alen] ; Row = (Colamd_Row *) &A [Alen + Col_size] ; /* === Construct the row and column data structures ===================== */ if (!init_rows_cols (n_row, n_col, Row, Col, A, p, stats)) { /* input matrix is invalid */ DEBUG0 (("colamd: Matrix invalid\n")) ; return (FALSE) ; } /* === Initialize scores, kill dense rows/columns ======================= */ init_scoring (n_row, n_col, Row, Col, A, p, knobs, &n_row2, &n_col2, &max_deg) ; /* === Order the supercolumns =========================================== */ ngarbage = find_ordering (n_row, n_col, Alen, Row, Col, A, p, n_col2, max_deg, 2*nnz, aggressive) ; /* === Order the non-principal columns ================================== */ order_children (n_col, Col, p) ; /* === Return statistics in stats ======================================= */ stats [COLAMD_DENSE_ROW] = n_row - n_row2 ; stats [COLAMD_DENSE_COL] = n_col - n_col2 ; stats [COLAMD_DEFRAG_COUNT] = ngarbage ; DEBUG0 (("colamd: done.\n")) ; return (TRUE) ; } /* ========================================================================== */ /* === colamd_report ======================================================== */ /* ========================================================================== */ PUBLIC void COLAMD_report ( Int stats [COLAMD_STATS] ) { print_report ("colamd", stats) ; } /* ========================================================================== */ /* === symamd_report ======================================================== */ /* ========================================================================== */ PUBLIC void SYMAMD_report ( Int stats [COLAMD_STATS] ) { print_report ("symamd", stats) ; } /* ========================================================================== */ /* === NON-USER-CALLABLE ROUTINES: ========================================== */ /* ========================================================================== */ /* There are no user-callable routines beyond this point in the file */ /* ========================================================================== */ /* === init_rows_cols ======================================================= */ /* ========================================================================== */ /* Takes the column form of the matrix in A and creates the row form of the matrix. Also, row and column attributes are stored in the Col and Row structs. If the columns are un-sorted or contain duplicate row indices, this routine will also sort and remove duplicate row indices from the column form of the matrix. Returns FALSE if the matrix is invalid, TRUE otherwise. Not user-callable. */ PRIVATE Int init_rows_cols /* returns TRUE if OK, or FALSE otherwise */ ( /* === Parameters ======================================================= */ Int n_row, /* number of rows of A */ Int n_col, /* number of columns of A */ Colamd_Row Row [], /* of size n_row+1 */ Colamd_Col Col [], /* of size n_col+1 */ Int A [], /* row indices of A, of size Alen */ Int p [], /* pointers to columns in A, of size n_col+1 */ Int stats [COLAMD_STATS] /* colamd statistics */ ) { /* === Local variables ================================================== */ Int col ; /* a column index */ Int row ; /* a row index */ Int *cp ; /* a column pointer */ Int *cp_end ; /* a pointer to the end of a column */ Int *rp ; /* a row pointer */ Int *rp_end ; /* a pointer to the end of a row */ Int last_row ; /* previous row */ /* === Initialize columns, and check column pointers ==================== */ for (col = 0 ; col < n_col ; col++) { Col [col].start = p [col] ; Col [col].length = p [col+1] - p [col] ; if (Col [col].length < 0) { /* column pointers must be non-decreasing */ stats [COLAMD_STATUS] = COLAMD_ERROR_col_length_negative ; stats [COLAMD_INFO1] = col ; stats [COLAMD_INFO2] = Col [col].length ; DEBUG0 (("colamd: col %d length %d < 0\n", col, Col [col].length)) ; return (FALSE) ; } Col [col].shared1.thickness = 1 ; Col [col].shared2.score = 0 ; Col [col].shared3.prev = EMPTY ; Col [col].shared4.degree_next = EMPTY ; } /* p [0..n_col] no longer needed, used as "head" in subsequent routines */ /* === Scan columns, compute row degrees, and check row indices ========= */ stats [COLAMD_INFO3] = 0 ; /* number of duplicate or unsorted row indices*/ for (row = 0 ; row < n_row ; row++) { Row [row].length = 0 ; Row [row].shared2.mark = -1 ; } for (col = 0 ; col < n_col ; col++) { last_row = -1 ; cp = &A [p [col]] ; cp_end = &A [p [col+1]] ; while (cp < cp_end) { row = *cp++ ; /* make sure row indices within range */ if (row < 0 || row >= n_row) { stats [COLAMD_STATUS] = COLAMD_ERROR_row_index_out_of_bounds ; stats [COLAMD_INFO1] = col ; stats [COLAMD_INFO2] = row ; stats [COLAMD_INFO3] = n_row ; DEBUG0 (("colamd: row %d col %d out of bounds\n", row, col)) ; return (FALSE) ; } if (row <= last_row || Row [row].shared2.mark == col) { /* row index are unsorted or repeated (or both), thus col */ /* is jumbled. This is a notice, not an error condition. */ stats [COLAMD_STATUS] = COLAMD_OK_BUT_JUMBLED ; stats [COLAMD_INFO1] = col ; stats [COLAMD_INFO2] = row ; (stats [COLAMD_INFO3]) ++ ; DEBUG1 (("colamd: row %d col %d unsorted/duplicate\n",row,col)); } if (Row [row].shared2.mark != col) { Row [row].length++ ; } else { /* this is a repeated entry in the column, */ /* it will be removed */ Col [col].length-- ; } /* mark the row as having been seen in this column */ Row [row].shared2.mark = col ; last_row = row ; } } /* === Compute row pointers ============================================= */ /* row form of the matrix starts directly after the column */ /* form of matrix in A */ Row [0].start = p [n_col] ; Row [0].shared1.p = Row [0].start ; Row [0].shared2.mark = -1 ; for (row = 1 ; row < n_row ; row++) { Row [row].start = Row [row-1].start + Row [row-1].length ; Row [row].shared1.p = Row [row].start ; Row [row].shared2.mark = -1 ; } /* === Create row form ================================================== */ if (stats [COLAMD_STATUS] == COLAMD_OK_BUT_JUMBLED) { /* if cols jumbled, watch for repeated row indices */ for (col = 0 ; col < n_col ; col++) { cp = &A [p [col]] ; cp_end = &A [p [col+1]] ; while (cp < cp_end) { row = *cp++ ; if (Row [row].shared2.mark != col) { A [(Row [row].shared1.p)++] = col ; Row [row].shared2.mark = col ; } } } } else { /* if cols not jumbled, we don't need the mark (this is faster) */ for (col = 0 ; col < n_col ; col++) { cp = &A [p [col]] ; cp_end = &A [p [col+1]] ; while (cp < cp_end) { A [(Row [*cp++].shared1.p)++] = col ; } } } /* === Clear the row marks and set row degrees ========================== */ for (row = 0 ; row < n_row ; row++) { Row [row].shared2.mark = 0 ; Row [row].shared1.degree = Row [row].length ; } /* === See if we need to re-create columns ============================== */ if (stats [COLAMD_STATUS] == COLAMD_OK_BUT_JUMBLED) { DEBUG0 (("colamd: reconstructing column form, matrix jumbled\n")) ; #ifndef NDEBUG /* make sure column lengths are correct */ for (col = 0 ; col < n_col ; col++) { p [col] = Col [col].length ; } for (row = 0 ; row < n_row ; row++) { rp = &A [Row [row].start] ; rp_end = rp + Row [row].length ; while (rp < rp_end) { p [*rp++]-- ; } } for (col = 0 ; col < n_col ; col++) { ASSERT (p [col] == 0) ; } /* now p is all zero (different than when debugging is turned off) */ #endif /* NDEBUG */ /* === Compute col pointers ========================================= */ /* col form of the matrix starts at A [0]. */ /* Note, we may have a gap between the col form and the row */ /* form if there were duplicate entries, if so, it will be */ /* removed upon the first garbage collection */ Col [0].start = 0 ; p [0] = Col [0].start ; for (col = 1 ; col < n_col ; col++) { /* note that the lengths here are for pruned columns, i.e. */ /* no duplicate row indices will exist for these columns */ Col [col].start = Col [col-1].start + Col [col-1].length ; p [col] = Col [col].start ; } /* === Re-create col form =========================================== */ for (row = 0 ; row < n_row ; row++) { rp = &A [Row [row].start] ; rp_end = rp + Row [row].length ; while (rp < rp_end) { A [(p [*rp++])++] = row ; } } } /* === Done. Matrix is not (or no longer) jumbled ====================== */ return (TRUE) ; } /* ========================================================================== */ /* === init_scoring ========================================================= */ /* ========================================================================== */ /* Kills dense or empty columns and rows, calculates an initial score for each column, and places all columns in the degree lists. Not user-callable. */ PRIVATE void init_scoring ( /* === Parameters ======================================================= */ Int n_row, /* number of rows of A */ Int n_col, /* number of columns of A */ Colamd_Row Row [], /* of size n_row+1 */ Colamd_Col Col [], /* of size n_col+1 */ Int A [], /* column form and row form of A */ Int head [], /* of size n_col+1 */ double knobs [COLAMD_KNOBS],/* parameters */ Int *p_n_row2, /* number of non-dense, non-empty rows */ Int *p_n_col2, /* number of non-dense, non-empty columns */ Int *p_max_deg /* maximum row degree */ ) { /* === Local variables ================================================== */ Int c ; /* a column index */ Int r, row ; /* a row index */ Int *cp ; /* a column pointer */ Int deg ; /* degree of a row or column */ Int *cp_end ; /* a pointer to the end of a column */ Int *new_cp ; /* new column pointer */ Int col_length ; /* length of pruned column */ Int score ; /* current column score */ Int n_col2 ; /* number of non-dense, non-empty columns */ Int n_row2 ; /* number of non-dense, non-empty rows */ Int dense_row_count ; /* remove rows with more entries than this */ Int dense_col_count ; /* remove cols with more entries than this */ Int min_score ; /* smallest column score */ Int max_deg ; /* maximum row degree */ Int next_col ; /* Used to add to degree list.*/ #ifndef NDEBUG Int debug_count ; /* debug only. */ #endif /* NDEBUG */ /* === Extract knobs ==================================================== */ /* Note: if knobs contains a NaN, this is undefined: */ if (knobs [COLAMD_DENSE_ROW] < 0) { /* only remove completely dense rows */ dense_row_count = n_col-1 ; } else { dense_row_count = DENSE_DEGREE (knobs [COLAMD_DENSE_ROW], n_col) ; } if (knobs [COLAMD_DENSE_COL] < 0) { /* only remove completely dense columns */ dense_col_count = n_row-1 ; } else { dense_col_count = DENSE_DEGREE (knobs [COLAMD_DENSE_COL], MIN (n_row, n_col)) ; } DEBUG1 (("colamd: densecount: %d %d\n", dense_row_count, dense_col_count)) ; max_deg = 0 ; n_col2 = n_col ; n_row2 = n_row ; /* === Kill empty columns =============================================== */ /* Put the empty columns at the end in their natural order, so that LU */ /* factorization can proceed as far as possible. */ for (c = n_col-1 ; c >= 0 ; c--) { deg = Col [c].length ; if (deg == 0) { /* this is a empty column, kill and order it last */ Col [c].shared2.order = --n_col2 ; KILL_PRINCIPAL_COL (c) ; } } DEBUG1 (("colamd: null columns killed: %d\n", n_col - n_col2)) ; /* === Kill dense columns =============================================== */ /* Put the dense columns at the end, in their natural order */ for (c = n_col-1 ; c >= 0 ; c--) { /* skip any dead columns */ if (COL_IS_DEAD (c)) { continue ; } deg = Col [c].length ; if (deg > dense_col_count) { /* this is a dense column, kill and order it last */ Col [c].shared2.order = --n_col2 ; /* decrement the row degrees */ cp = &A [Col [c].start] ; cp_end = cp + Col [c].length ; while (cp < cp_end) { Row [*cp++].shared1.degree-- ; } KILL_PRINCIPAL_COL (c) ; } } DEBUG1 (("colamd: Dense and null columns killed: %d\n", n_col - n_col2)) ; /* === Kill dense and empty rows ======================================== */ for (r = 0 ; r < n_row ; r++) { deg = Row [r].shared1.degree ; ASSERT (deg >= 0 && deg <= n_col) ; if (deg > dense_row_count || deg == 0) { /* kill a dense or empty row */ KILL_ROW (r) ; --n_row2 ; } else { /* keep track of max degree of remaining rows */ max_deg = MAX (max_deg, deg) ; } } DEBUG1 (("colamd: Dense and null rows killed: %d\n", n_row - n_row2)) ; /* === Compute initial column scores ==================================== */ /* At this point the row degrees are accurate. They reflect the number */ /* of "live" (non-dense) columns in each row. No empty rows exist. */ /* Some "live" columns may contain only dead rows, however. These are */ /* pruned in the code below. */ /* now find the initial matlab score for each column */ for (c = n_col-1 ; c >= 0 ; c--) { /* skip dead column */ if (COL_IS_DEAD (c)) { continue ; } score = 0 ; cp = &A [Col [c].start] ; new_cp = cp ; cp_end = cp + Col [c].length ; while (cp < cp_end) { /* get a row */ row = *cp++ ; /* skip if dead */ if (ROW_IS_DEAD (row)) { continue ; } /* compact the column */ *new_cp++ = row ; /* add row's external degree */ score += Row [row].shared1.degree - 1 ; /* guard against integer overflow */ score = MIN (score, n_col) ; } /* determine pruned column length */ col_length = (Int) (new_cp - &A [Col [c].start]) ; if (col_length == 0) { /* a newly-made null column (all rows in this col are "dense" */ /* and have already been killed) */ DEBUG2 (("Newly null killed: %d\n", c)) ; Col [c].shared2.order = --n_col2 ; KILL_PRINCIPAL_COL (c) ; } else { /* set column length and set score */ ASSERT (score >= 0) ; ASSERT (score <= n_col) ; Col [c].length = col_length ; Col [c].shared2.score = score ; } } DEBUG1 (("colamd: Dense, null, and newly-null columns killed: %d\n", n_col-n_col2)) ; /* At this point, all empty rows and columns are dead. All live columns */ /* are "clean" (containing no dead rows) and simplicial (no supercolumns */ /* yet). Rows may contain dead columns, but all live rows contain at */ /* least one live column. */ #ifndef NDEBUG debug_structures (n_row, n_col, Row, Col, A, n_col2) ; #endif /* NDEBUG */ /* === Initialize degree lists ========================================== */ #ifndef NDEBUG debug_count = 0 ; #endif /* NDEBUG */ /* clear the hash buckets */ for (c = 0 ; c <= n_col ; c++) { head [c] = EMPTY ; } min_score = n_col ; /* place in reverse order, so low column indices are at the front */ /* of the lists. This is to encourage natural tie-breaking */ for (c = n_col-1 ; c >= 0 ; c--) { /* only add principal columns to degree lists */ if (COL_IS_ALIVE (c)) { DEBUG4 (("place %d score %d minscore %d ncol %d\n", c, Col [c].shared2.score, min_score, n_col)) ; /* === Add columns score to DList =============================== */ score = Col [c].shared2.score ; ASSERT (min_score >= 0) ; ASSERT (min_score <= n_col) ; ASSERT (score >= 0) ; ASSERT (score <= n_col) ; ASSERT (head [score] >= EMPTY) ; /* now add this column to dList at proper score location */ next_col = head [score] ; Col [c].shared3.prev = EMPTY ; Col [c].shared4.degree_next = next_col ; /* if there already was a column with the same score, set its */ /* previous pointer to this new column */ if (next_col != EMPTY) { Col [next_col].shared3.prev = c ; } head [score] = c ; /* see if this score is less than current min */ min_score = MIN (min_score, score) ; #ifndef NDEBUG debug_count++ ; #endif /* NDEBUG */ } } #ifndef NDEBUG DEBUG1 (("colamd: Live cols %d out of %d, non-princ: %d\n", debug_count, n_col, n_col-debug_count)) ; ASSERT (debug_count == n_col2) ; debug_deg_lists (n_row, n_col, Row, Col, head, min_score, n_col2, max_deg) ; #endif /* NDEBUG */ /* === Return number of remaining columns, and max row degree =========== */ *p_n_col2 = n_col2 ; *p_n_row2 = n_row2 ; *p_max_deg = max_deg ; } /* ========================================================================== */ /* === find_ordering ======================================================== */ /* ========================================================================== */ /* Order the principal columns of the supercolumn form of the matrix (no supercolumns on input). Uses a minimum approximate column minimum degree ordering method. Not user-callable. */ PRIVATE Int find_ordering /* return the number of garbage collections */ ( /* === Parameters ======================================================= */ Int n_row, /* number of rows of A */ Int n_col, /* number of columns of A */ Int Alen, /* size of A, 2*nnz + n_col or larger */ Colamd_Row Row [], /* of size n_row+1 */ Colamd_Col Col [], /* of size n_col+1 */ Int A [], /* column form and row form of A */ Int head [], /* of size n_col+1 */ Int n_col2, /* Remaining columns to order */ Int max_deg, /* Maximum row degree */ Int pfree, /* index of first free slot (2*nnz on entry) */ Int aggressive ) { /* === Local variables ================================================== */ Int k ; /* current pivot ordering step */ Int pivot_col ; /* current pivot column */ Int *cp ; /* a column pointer */ Int *rp ; /* a row pointer */ Int pivot_row ; /* current pivot row */ Int *new_cp ; /* modified column pointer */ Int *new_rp ; /* modified row pointer */ Int pivot_row_start ; /* pointer to start of pivot row */ Int pivot_row_degree ; /* number of columns in pivot row */ Int pivot_row_length ; /* number of supercolumns in pivot row */ Int pivot_col_score ; /* score of pivot column */ Int needed_memory ; /* free space needed for pivot row */ Int *cp_end ; /* pointer to the end of a column */ Int *rp_end ; /* pointer to the end of a row */ Int row ; /* a row index */ Int col ; /* a column index */ Int max_score ; /* maximum possible score */ Int cur_score ; /* score of current column */ unsigned Int hash ; /* hash value for supernode detection */ Int head_column ; /* head of hash bucket */ Int first_col ; /* first column in hash bucket */ Int tag_mark ; /* marker value for mark array */ Int row_mark ; /* Row [row].shared2.mark */ Int set_difference ; /* set difference size of row with pivot row */ Int min_score ; /* smallest column score */ Int col_thickness ; /* "thickness" (no. of columns in a supercol) */ Int max_mark ; /* maximum value of tag_mark */ Int pivot_col_thickness ; /* number of columns represented by pivot col */ Int prev_col ; /* Used by Dlist operations. */ Int next_col ; /* Used by Dlist operations. */ Int ngarbage ; /* number of garbage collections performed */ #ifndef NDEBUG Int debug_d ; /* debug loop counter */ Int debug_step = 0 ; /* debug loop counter */ #endif /* NDEBUG */ /* === Initialization and clear mark ==================================== */ max_mark = INT_MAX - n_col ; /* INT_MAX defined in */ tag_mark = clear_mark (0, max_mark, n_row, Row) ; min_score = 0 ; ngarbage = 0 ; DEBUG1 (("colamd: Ordering, n_col2=%d\n", n_col2)) ; /* === Order the columns ================================================ */ for (k = 0 ; k < n_col2 ; /* 'k' is incremented below */) { #ifndef NDEBUG if (debug_step % 100 == 0) { DEBUG2 (("\n... Step k: %d out of n_col2: %d\n", k, n_col2)) ; } else { DEBUG3 (("\n----------Step k: %d out of n_col2: %d\n", k, n_col2)) ; } debug_step++ ; debug_deg_lists (n_row, n_col, Row, Col, head, min_score, n_col2-k, max_deg) ; debug_matrix (n_row, n_col, Row, Col, A) ; #endif /* NDEBUG */ /* === Select pivot column, and order it ============================ */ /* make sure degree list isn't empty */ ASSERT (min_score >= 0) ; ASSERT (min_score <= n_col) ; ASSERT (head [min_score] >= EMPTY) ; #ifndef NDEBUG for (debug_d = 0 ; debug_d < min_score ; debug_d++) { ASSERT (head [debug_d] == EMPTY) ; } #endif /* NDEBUG */ /* get pivot column from head of minimum degree list */ while (head [min_score] == EMPTY && min_score < n_col) { min_score++ ; } pivot_col = head [min_score] ; ASSERT (pivot_col >= 0 && pivot_col <= n_col) ; next_col = Col [pivot_col].shared4.degree_next ; head [min_score] = next_col ; if (next_col != EMPTY) { Col [next_col].shared3.prev = EMPTY ; } ASSERT (COL_IS_ALIVE (pivot_col)) ; /* remember score for defrag check */ pivot_col_score = Col [pivot_col].shared2.score ; /* the pivot column is the kth column in the pivot order */ Col [pivot_col].shared2.order = k ; /* increment order count by column thickness */ pivot_col_thickness = Col [pivot_col].shared1.thickness ; k += pivot_col_thickness ; ASSERT (pivot_col_thickness > 0) ; DEBUG3 (("Pivot col: %d thick %d\n", pivot_col, pivot_col_thickness)) ; /* === Garbage_collection, if necessary ============================= */ needed_memory = MIN (pivot_col_score, n_col - k) ; if (pfree + needed_memory >= Alen) { pfree = garbage_collection (n_row, n_col, Row, Col, A, &A [pfree]) ; ngarbage++ ; /* after garbage collection we will have enough */ ASSERT (pfree + needed_memory < Alen) ; /* garbage collection has wiped out the Row[].shared2.mark array */ tag_mark = clear_mark (0, max_mark, n_row, Row) ; #ifndef NDEBUG debug_matrix (n_row, n_col, Row, Col, A) ; #endif /* NDEBUG */ } /* === Compute pivot row pattern ==================================== */ /* get starting location for this new merged row */ pivot_row_start = pfree ; /* initialize new row counts to zero */ pivot_row_degree = 0 ; /* tag pivot column as having been visited so it isn't included */ /* in merged pivot row */ Col [pivot_col].shared1.thickness = -pivot_col_thickness ; /* pivot row is the union of all rows in the pivot column pattern */ cp = &A [Col [pivot_col].start] ; cp_end = cp + Col [pivot_col].length ; while (cp < cp_end) { /* get a row */ row = *cp++ ; DEBUG4 (("Pivot col pattern %d %d\n", ROW_IS_ALIVE (row), row)) ; /* skip if row is dead */ if (ROW_IS_ALIVE (row)) { rp = &A [Row [row].start] ; rp_end = rp + Row [row].length ; while (rp < rp_end) { /* get a column */ col = *rp++ ; /* add the column, if alive and untagged */ col_thickness = Col [col].shared1.thickness ; if (col_thickness > 0 && COL_IS_ALIVE (col)) { /* tag column in pivot row */ Col [col].shared1.thickness = -col_thickness ; ASSERT (pfree < Alen) ; /* place column in pivot row */ A [pfree++] = col ; pivot_row_degree += col_thickness ; } } } } /* clear tag on pivot column */ Col [pivot_col].shared1.thickness = pivot_col_thickness ; max_deg = MAX (max_deg, pivot_row_degree) ; #ifndef NDEBUG DEBUG3 (("check2\n")) ; debug_mark (n_row, Row, tag_mark, max_mark) ; #endif /* NDEBUG */ /* === Kill all rows used to construct pivot row ==================== */ /* also kill pivot row, temporarily */ cp = &A [Col [pivot_col].start] ; cp_end = cp + Col [pivot_col].length ; while (cp < cp_end) { /* may be killing an already dead row */ row = *cp++ ; DEBUG3 (("Kill row in pivot col: %d\n", row)) ; KILL_ROW (row) ; } /* === Select a row index to use as the new pivot row =============== */ pivot_row_length = pfree - pivot_row_start ; if (pivot_row_length > 0) { /* pick the "pivot" row arbitrarily (first row in col) */ pivot_row = A [Col [pivot_col].start] ; DEBUG3 (("Pivotal row is %d\n", pivot_row)) ; } else { /* there is no pivot row, since it is of zero length */ pivot_row = EMPTY ; ASSERT (pivot_row_length == 0) ; } ASSERT (Col [pivot_col].length > 0 || pivot_row_length == 0) ; /* === Approximate degree computation =============================== */ /* Here begins the computation of the approximate degree. The column */ /* score is the sum of the pivot row "length", plus the size of the */ /* set differences of each row in the column minus the pattern of the */ /* pivot row itself. The column ("thickness") itself is also */ /* excluded from the column score (we thus use an approximate */ /* external degree). */ /* The time taken by the following code (compute set differences, and */ /* add them up) is proportional to the size of the data structure */ /* being scanned - that is, the sum of the sizes of each column in */ /* the pivot row. Thus, the amortized time to compute a column score */ /* is proportional to the size of that column (where size, in this */ /* context, is the column "length", or the number of row indices */ /* in that column). The number of row indices in a column is */ /* monotonically non-decreasing, from the length of the original */ /* column on input to colamd. */ /* === Compute set differences ====================================== */ DEBUG3 (("** Computing set differences phase. **\n")) ; /* pivot row is currently dead - it will be revived later. */ DEBUG3 (("Pivot row: ")) ; /* for each column in pivot row */ rp = &A [pivot_row_start] ; rp_end = rp + pivot_row_length ; while (rp < rp_end) { col = *rp++ ; ASSERT (COL_IS_ALIVE (col) && col != pivot_col) ; DEBUG3 (("Col: %d\n", col)) ; /* clear tags used to construct pivot row pattern */ col_thickness = -Col [col].shared1.thickness ; ASSERT (col_thickness > 0) ; Col [col].shared1.thickness = col_thickness ; /* === Remove column from degree list =========================== */ cur_score = Col [col].shared2.score ; prev_col = Col [col].shared3.prev ; next_col = Col [col].shared4.degree_next ; ASSERT (cur_score >= 0) ; ASSERT (cur_score <= n_col) ; ASSERT (cur_score >= EMPTY) ; if (prev_col == EMPTY) { head [cur_score] = next_col ; } else { Col [prev_col].shared4.degree_next = next_col ; } if (next_col != EMPTY) { Col [next_col].shared3.prev = prev_col ; } /* === Scan the column ========================================== */ cp = &A [Col [col].start] ; cp_end = cp + Col [col].length ; while (cp < cp_end) { /* get a row */ row = *cp++ ; row_mark = Row [row].shared2.mark ; /* skip if dead */ if (ROW_IS_MARKED_DEAD (row_mark)) { continue ; } ASSERT (row != pivot_row) ; set_difference = row_mark - tag_mark ; /* check if the row has been seen yet */ if (set_difference < 0) { ASSERT (Row [row].shared1.degree <= max_deg) ; set_difference = Row [row].shared1.degree ; } /* subtract column thickness from this row's set difference */ set_difference -= col_thickness ; ASSERT (set_difference >= 0) ; /* absorb this row if the set difference becomes zero */ if (set_difference == 0 && aggressive) { DEBUG3 (("aggressive absorption. Row: %d\n", row)) ; KILL_ROW (row) ; } else { /* save the new mark */ Row [row].shared2.mark = set_difference + tag_mark ; } } } #ifndef NDEBUG debug_deg_lists (n_row, n_col, Row, Col, head, min_score, n_col2-k-pivot_row_degree, max_deg) ; #endif /* NDEBUG */ /* === Add up set differences for each column ======================= */ DEBUG3 (("** Adding set differences phase. **\n")) ; /* for each column in pivot row */ rp = &A [pivot_row_start] ; rp_end = rp + pivot_row_length ; while (rp < rp_end) { /* get a column */ col = *rp++ ; ASSERT (COL_IS_ALIVE (col) && col != pivot_col) ; hash = 0 ; cur_score = 0 ; cp = &A [Col [col].start] ; /* compact the column */ new_cp = cp ; cp_end = cp + Col [col].length ; DEBUG4 (("Adding set diffs for Col: %d.\n", col)) ; while (cp < cp_end) { /* get a row */ row = *cp++ ; ASSERT(row >= 0 && row < n_row) ; row_mark = Row [row].shared2.mark ; /* skip if dead */ if (ROW_IS_MARKED_DEAD (row_mark)) { DEBUG4 ((" Row %d, dead\n", row)) ; continue ; } DEBUG4 ((" Row %d, set diff %d\n", row, row_mark-tag_mark)); ASSERT (row_mark >= tag_mark) ; /* compact the column */ *new_cp++ = row ; /* compute hash function */ hash += row ; /* add set difference */ cur_score += row_mark - tag_mark ; /* integer overflow... */ cur_score = MIN (cur_score, n_col) ; } /* recompute the column's length */ Col [col].length = (Int) (new_cp - &A [Col [col].start]) ; /* === Further mass elimination ================================= */ if (Col [col].length == 0) { DEBUG4 (("further mass elimination. Col: %d\n", col)) ; /* nothing left but the pivot row in this column */ KILL_PRINCIPAL_COL (col) ; pivot_row_degree -= Col [col].shared1.thickness ; ASSERT (pivot_row_degree >= 0) ; /* order it */ Col [col].shared2.order = k ; /* increment order count by column thickness */ k += Col [col].shared1.thickness ; } else { /* === Prepare for supercolumn detection ==================== */ DEBUG4 (("Preparing supercol detection for Col: %d.\n", col)) ; /* save score so far */ Col [col].shared2.score = cur_score ; /* add column to hash table, for supercolumn detection */ hash %= n_col + 1 ; DEBUG4 ((" Hash = %d, n_col = %d.\n", hash, n_col)) ; ASSERT (((Int) hash) <= n_col) ; head_column = head [hash] ; if (head_column > EMPTY) { /* degree list "hash" is non-empty, use prev (shared3) of */ /* first column in degree list as head of hash bucket */ first_col = Col [head_column].shared3.headhash ; Col [head_column].shared3.headhash = col ; } else { /* degree list "hash" is empty, use head as hash bucket */ first_col = - (head_column + 2) ; head [hash] = - (col + 2) ; } Col [col].shared4.hash_next = first_col ; /* save hash function in Col [col].shared3.hash */ Col [col].shared3.hash = (Int) hash ; ASSERT (COL_IS_ALIVE (col)) ; } } /* The approximate external column degree is now computed. */ /* === Supercolumn detection ======================================== */ DEBUG3 (("** Supercolumn detection phase. **\n")) ; detect_super_cols ( #ifndef NDEBUG n_col, Row, #endif /* NDEBUG */ Col, A, head, pivot_row_start, pivot_row_length) ; /* === Kill the pivotal column ====================================== */ KILL_PRINCIPAL_COL (pivot_col) ; /* === Clear mark =================================================== */ tag_mark = clear_mark (tag_mark+max_deg+1, max_mark, n_row, Row) ; #ifndef NDEBUG DEBUG3 (("check3\n")) ; debug_mark (n_row, Row, tag_mark, max_mark) ; #endif /* NDEBUG */ /* === Finalize the new pivot row, and column scores ================ */ DEBUG3 (("** Finalize scores phase. **\n")) ; /* for each column in pivot row */ rp = &A [pivot_row_start] ; /* compact the pivot row */ new_rp = rp ; rp_end = rp + pivot_row_length ; while (rp < rp_end) { col = *rp++ ; /* skip dead columns */ if (COL_IS_DEAD (col)) { continue ; } *new_rp++ = col ; /* add new pivot row to column */ A [Col [col].start + (Col [col].length++)] = pivot_row ; /* retrieve score so far and add on pivot row's degree. */ /* (we wait until here for this in case the pivot */ /* row's degree was reduced due to mass elimination). */ cur_score = Col [col].shared2.score + pivot_row_degree ; /* calculate the max possible score as the number of */ /* external columns minus the 'k' value minus the */ /* columns thickness */ max_score = n_col - k - Col [col].shared1.thickness ; /* make the score the external degree of the union-of-rows */ cur_score -= Col [col].shared1.thickness ; /* make sure score is less or equal than the max score */ cur_score = MIN (cur_score, max_score) ; ASSERT (cur_score >= 0) ; /* store updated score */ Col [col].shared2.score = cur_score ; /* === Place column back in degree list ========================= */ ASSERT (min_score >= 0) ; ASSERT (min_score <= n_col) ; ASSERT (cur_score >= 0) ; ASSERT (cur_score <= n_col) ; ASSERT (head [cur_score] >= EMPTY) ; next_col = head [cur_score] ; Col [col].shared4.degree_next = next_col ; Col [col].shared3.prev = EMPTY ; if (next_col != EMPTY) { Col [next_col].shared3.prev = col ; } head [cur_score] = col ; /* see if this score is less than current min */ min_score = MIN (min_score, cur_score) ; } #ifndef NDEBUG debug_deg_lists (n_row, n_col, Row, Col, head, min_score, n_col2-k, max_deg) ; #endif /* NDEBUG */ /* === Resurrect the new pivot row ================================== */ if (pivot_row_degree > 0) { /* update pivot row length to reflect any cols that were killed */ /* during super-col detection and mass elimination */ Row [pivot_row].start = pivot_row_start ; Row [pivot_row].length = (Int) (new_rp - &A[pivot_row_start]) ; ASSERT (Row [pivot_row].length > 0) ; Row [pivot_row].shared1.degree = pivot_row_degree ; Row [pivot_row].shared2.mark = 0 ; /* pivot row is no longer dead */ DEBUG1 (("Resurrect Pivot_row %d deg: %d\n", pivot_row, pivot_row_degree)) ; } } /* === All principal columns have now been ordered ====================== */ return (ngarbage) ; } /* ========================================================================== */ /* === order_children ======================================================= */ /* ========================================================================== */ /* The find_ordering routine has ordered all of the principal columns (the representatives of the supercolumns). The non-principal columns have not yet been ordered. This routine orders those columns by walking up the parent tree (a column is a child of the column which absorbed it). The final permutation vector is then placed in p [0 ... n_col-1], with p [0] being the first column, and p [n_col-1] being the last. It doesn't look like it at first glance, but be assured that this routine takes time linear in the number of columns. Although not immediately obvious, the time taken by this routine is O (n_col), that is, linear in the number of columns. Not user-callable. */ PRIVATE void order_children ( /* === Parameters ======================================================= */ Int n_col, /* number of columns of A */ Colamd_Col Col [], /* of size n_col+1 */ Int p [] /* p [0 ... n_col-1] is the column permutation*/ ) { /* === Local variables ================================================== */ Int i ; /* loop counter for all columns */ Int c ; /* column index */ Int parent ; /* index of column's parent */ Int order ; /* column's order */ /* === Order each non-principal column ================================== */ for (i = 0 ; i < n_col ; i++) { /* find an un-ordered non-principal column */ ASSERT (COL_IS_DEAD (i)) ; if (!COL_IS_DEAD_PRINCIPAL (i) && Col [i].shared2.order == EMPTY) { parent = i ; /* once found, find its principal parent */ do { parent = Col [parent].shared1.parent ; } while (!COL_IS_DEAD_PRINCIPAL (parent)) ; /* now, order all un-ordered non-principal columns along path */ /* to this parent. collapse tree at the same time */ c = i ; /* get order of parent */ order = Col [parent].shared2.order ; do { ASSERT (Col [c].shared2.order == EMPTY) ; /* order this column */ Col [c].shared2.order = order++ ; /* collaps tree */ Col [c].shared1.parent = parent ; /* get immediate parent of this column */ c = Col [c].shared1.parent ; /* continue until we hit an ordered column. There are */ /* guarranteed not to be anymore unordered columns */ /* above an ordered column */ } while (Col [c].shared2.order == EMPTY) ; /* re-order the super_col parent to largest order for this group */ Col [parent].shared2.order = order ; } } /* === Generate the permutation ========================================= */ for (c = 0 ; c < n_col ; c++) { p [Col [c].shared2.order] = c ; } } /* ========================================================================== */ /* === detect_super_cols ==================================================== */ /* ========================================================================== */ /* Detects supercolumns by finding matches between columns in the hash buckets. Check amongst columns in the set A [row_start ... row_start + row_length-1]. The columns under consideration are currently *not* in the degree lists, and have already been placed in the hash buckets. The hash bucket for columns whose hash function is equal to h is stored as follows: if head [h] is >= 0, then head [h] contains a degree list, so: head [h] is the first column in degree bucket h. Col [head [h]].headhash gives the first column in hash bucket h. otherwise, the degree list is empty, and: -(head [h] + 2) is the first column in hash bucket h. For a column c in a hash bucket, Col [c].shared3.prev is NOT a "previous column" pointer. Col [c].shared3.hash is used instead as the hash number for that column. The value of Col [c].shared4.hash_next is the next column in the same hash bucket. Assuming no, or "few" hash collisions, the time taken by this routine is linear in the sum of the sizes (lengths) of each column whose score has just been computed in the approximate degree computation. Not user-callable. */ PRIVATE void detect_super_cols ( /* === Parameters ======================================================= */ #ifndef NDEBUG /* these two parameters are only needed when debugging is enabled: */ Int n_col, /* number of columns of A */ Colamd_Row Row [], /* of size n_row+1 */ #endif /* NDEBUG */ Colamd_Col Col [], /* of size n_col+1 */ Int A [], /* row indices of A */ Int head [], /* head of degree lists and hash buckets */ Int row_start, /* pointer to set of columns to check */ Int row_length /* number of columns to check */ ) { /* === Local variables ================================================== */ Int hash ; /* hash value for a column */ Int *rp ; /* pointer to a row */ Int c ; /* a column index */ Int super_c ; /* column index of the column to absorb into */ Int *cp1 ; /* column pointer for column super_c */ Int *cp2 ; /* column pointer for column c */ Int length ; /* length of column super_c */ Int prev_c ; /* column preceding c in hash bucket */ Int i ; /* loop counter */ Int *rp_end ; /* pointer to the end of the row */ Int col ; /* a column index in the row to check */ Int head_column ; /* first column in hash bucket or degree list */ Int first_col ; /* first column in hash bucket */ /* === Consider each column in the row ================================== */ rp = &A [row_start] ; rp_end = rp + row_length ; while (rp < rp_end) { col = *rp++ ; if (COL_IS_DEAD (col)) { continue ; } /* get hash number for this column */ hash = Col [col].shared3.hash ; ASSERT (hash <= n_col) ; /* === Get the first column in this hash bucket ===================== */ head_column = head [hash] ; if (head_column > EMPTY) { first_col = Col [head_column].shared3.headhash ; } else { first_col = - (head_column + 2) ; } /* === Consider each column in the hash bucket ====================== */ for (super_c = first_col ; super_c != EMPTY ; super_c = Col [super_c].shared4.hash_next) { ASSERT (COL_IS_ALIVE (super_c)) ; ASSERT (Col [super_c].shared3.hash == hash) ; length = Col [super_c].length ; /* prev_c is the column preceding column c in the hash bucket */ prev_c = super_c ; /* === Compare super_c with all columns after it ================ */ for (c = Col [super_c].shared4.hash_next ; c != EMPTY ; c = Col [c].shared4.hash_next) { ASSERT (c != super_c) ; ASSERT (COL_IS_ALIVE (c)) ; ASSERT (Col [c].shared3.hash == hash) ; /* not identical if lengths or scores are different */ if (Col [c].length != length || Col [c].shared2.score != Col [super_c].shared2.score) { prev_c = c ; continue ; } /* compare the two columns */ cp1 = &A [Col [super_c].start] ; cp2 = &A [Col [c].start] ; for (i = 0 ; i < length ; i++) { /* the columns are "clean" (no dead rows) */ ASSERT (ROW_IS_ALIVE (*cp1)) ; ASSERT (ROW_IS_ALIVE (*cp2)) ; /* row indices will same order for both supercols, */ /* no gather scatter nessasary */ if (*cp1++ != *cp2++) { break ; } } /* the two columns are different if the for-loop "broke" */ if (i != length) { prev_c = c ; continue ; } /* === Got it! two columns are identical =================== */ ASSERT (Col [c].shared2.score == Col [super_c].shared2.score) ; Col [super_c].shared1.thickness += Col [c].shared1.thickness ; Col [c].shared1.parent = super_c ; KILL_NON_PRINCIPAL_COL (c) ; /* order c later, in order_children() */ Col [c].shared2.order = EMPTY ; /* remove c from hash bucket */ Col [prev_c].shared4.hash_next = Col [c].shared4.hash_next ; } } /* === Empty this hash bucket ======================================= */ if (head_column > EMPTY) { /* corresponding degree list "hash" is not empty */ Col [head_column].shared3.headhash = EMPTY ; } else { /* corresponding degree list "hash" is empty */ head [hash] = EMPTY ; } } } /* ========================================================================== */ /* === garbage_collection =================================================== */ /* ========================================================================== */ /* Defragments and compacts columns and rows in the workspace A. Used when all avaliable memory has been used while performing row merging. Returns the index of the first free position in A, after garbage collection. The time taken by this routine is linear is the size of the array A, which is itself linear in the number of nonzeros in the input matrix. Not user-callable. */ PRIVATE Int garbage_collection /* returns the new value of pfree */ ( /* === Parameters ======================================================= */ Int n_row, /* number of rows */ Int n_col, /* number of columns */ Colamd_Row Row [], /* row info */ Colamd_Col Col [], /* column info */ Int A [], /* A [0 ... Alen-1] holds the matrix */ Int *pfree /* &A [0] ... pfree is in use */ ) { /* === Local variables ================================================== */ Int *psrc ; /* source pointer */ Int *pdest ; /* destination pointer */ Int j ; /* counter */ Int r ; /* a row index */ Int c ; /* a column index */ Int length ; /* length of a row or column */ #ifndef NDEBUG Int debug_rows ; DEBUG2 (("Defrag..\n")) ; for (psrc = &A[0] ; psrc < pfree ; psrc++) ASSERT (*psrc >= 0) ; debug_rows = 0 ; #endif /* NDEBUG */ /* === Defragment the columns =========================================== */ pdest = &A[0] ; for (c = 0 ; c < n_col ; c++) { if (COL_IS_ALIVE (c)) { psrc = &A [Col [c].start] ; /* move and compact the column */ ASSERT (pdest <= psrc) ; Col [c].start = (Int) (pdest - &A [0]) ; length = Col [c].length ; for (j = 0 ; j < length ; j++) { r = *psrc++ ; if (ROW_IS_ALIVE (r)) { *pdest++ = r ; } } Col [c].length = (Int) (pdest - &A [Col [c].start]) ; } } /* === Prepare to defragment the rows =================================== */ for (r = 0 ; r < n_row ; r++) { if (ROW_IS_DEAD (r) || (Row [r].length == 0)) { /* This row is already dead, or is of zero length. Cannot compact * a row of zero length, so kill it. NOTE: in the current version, * there are no zero-length live rows. Kill the row (for the first * time, or again) just to be safe. */ KILL_ROW (r) ; } else { /* save first column index in Row [r].shared2.first_column */ psrc = &A [Row [r].start] ; Row [r].shared2.first_column = *psrc ; ASSERT (ROW_IS_ALIVE (r)) ; /* flag the start of the row with the one's complement of row */ *psrc = ONES_COMPLEMENT (r) ; #ifndef NDEBUG debug_rows++ ; #endif /* NDEBUG */ } } /* === Defragment the rows ============================================== */ psrc = pdest ; while (psrc < pfree) { /* find a negative number ... the start of a row */ if (*psrc++ < 0) { psrc-- ; /* get the row index */ r = ONES_COMPLEMENT (*psrc) ; ASSERT (r >= 0 && r < n_row) ; /* restore first column index */ *psrc = Row [r].shared2.first_column ; ASSERT (ROW_IS_ALIVE (r)) ; ASSERT (Row [r].length > 0) ; /* move and compact the row */ ASSERT (pdest <= psrc) ; Row [r].start = (Int) (pdest - &A [0]) ; length = Row [r].length ; for (j = 0 ; j < length ; j++) { c = *psrc++ ; if (COL_IS_ALIVE (c)) { *pdest++ = c ; } } Row [r].length = (Int) (pdest - &A [Row [r].start]) ; ASSERT (Row [r].length > 0) ; #ifndef NDEBUG debug_rows-- ; #endif /* NDEBUG */ } } /* ensure we found all the rows */ ASSERT (debug_rows == 0) ; /* === Return the new value of pfree ==================================== */ return ((Int) (pdest - &A [0])) ; } /* ========================================================================== */ /* === clear_mark =========================================================== */ /* ========================================================================== */ /* Clears the Row [].shared2.mark array, and returns the new tag_mark. Return value is the new tag_mark. Not user-callable. */ PRIVATE Int clear_mark /* return the new value for tag_mark */ ( /* === Parameters ======================================================= */ Int tag_mark, /* new value of tag_mark */ Int max_mark, /* max allowed value of tag_mark */ Int n_row, /* number of rows in A */ Colamd_Row Row [] /* Row [0 ... n_row-1].shared2.mark is set to zero */ ) { /* === Local variables ================================================== */ Int r ; if (tag_mark <= 0 || tag_mark >= max_mark) { for (r = 0 ; r < n_row ; r++) { if (ROW_IS_ALIVE (r)) { Row [r].shared2.mark = 0 ; } } tag_mark = 1 ; } return (tag_mark) ; } /* ========================================================================== */ /* === print_report ========================================================= */ /* ========================================================================== */ PRIVATE void print_report ( char *method, Int stats [COLAMD_STATS] ) { Int i1, i2, i3 ; PRINTF (("\n%s version %d.%d, %s: ", method, COLAMD_MAIN_VERSION, COLAMD_SUB_VERSION, COLAMD_DATE)) ; if (!stats) { PRINTF (("No statistics available.\n")) ; return ; } i1 = stats [COLAMD_INFO1] ; i2 = stats [COLAMD_INFO2] ; i3 = stats [COLAMD_INFO3] ; if (stats [COLAMD_STATUS] >= 0) { PRINTF (("OK. ")) ; } else { PRINTF (("ERROR. ")) ; } switch (stats [COLAMD_STATUS]) { case COLAMD_OK_BUT_JUMBLED: PRINTF(("Matrix has unsorted or duplicate row indices.\n")) ; PRINTF(("%s: number of duplicate or out-of-order row indices: %d\n", method, i3)) ; PRINTF(("%s: last seen duplicate or out-of-order row index: %d\n", method, INDEX (i2))) ; PRINTF(("%s: last seen in column: %d", method, INDEX (i1))) ; /* no break - fall through to next case instead */ case COLAMD_OK: PRINTF(("\n")) ; PRINTF(("%s: number of dense or empty rows ignored: %d\n", method, stats [COLAMD_DENSE_ROW])) ; PRINTF(("%s: number of dense or empty columns ignored: %d\n", method, stats [COLAMD_DENSE_COL])) ; PRINTF(("%s: number of garbage collections performed: %d\n", method, stats [COLAMD_DEFRAG_COUNT])) ; break ; case COLAMD_ERROR_A_not_present: PRINTF(("Array A (row indices of matrix) not present.\n")) ; break ; case COLAMD_ERROR_p_not_present: PRINTF(("Array p (column pointers for matrix) not present.\n")) ; break ; case COLAMD_ERROR_nrow_negative: PRINTF(("Invalid number of rows (%d).\n", i1)) ; break ; case COLAMD_ERROR_ncol_negative: PRINTF(("Invalid number of columns (%d).\n", i1)) ; break ; case COLAMD_ERROR_nnz_negative: PRINTF(("Invalid number of nonzero entries (%d).\n", i1)) ; break ; case COLAMD_ERROR_p0_nonzero: PRINTF(("Invalid column pointer, p [0] = %d, must be zero.\n", i1)); break ; case COLAMD_ERROR_A_too_small: PRINTF(("Array A too small.\n")) ; PRINTF((" Need Alen >= %d, but given only Alen = %d.\n", i1, i2)) ; break ; case COLAMD_ERROR_col_length_negative: PRINTF (("Column %d has a negative number of nonzero entries (%d).\n", INDEX (i1), i2)) ; break ; case COLAMD_ERROR_row_index_out_of_bounds: PRINTF (("Row index (row %d) out of bounds (%d to %d) in column %d.\n", INDEX (i2), INDEX (0), INDEX (i3-1), INDEX (i1))) ; break ; case COLAMD_ERROR_out_of_memory: PRINTF(("Out of memory.\n")) ; break ; /* v2.4: internal-error case deleted */ } } /* ========================================================================== */ /* === colamd debugging routines ============================================ */ /* ========================================================================== */ /* When debugging is disabled, the remainder of this file is ignored. */ #ifndef NDEBUG /* ========================================================================== */ /* === debug_structures ===================================================== */ /* ========================================================================== */ /* At this point, all empty rows and columns are dead. All live columns are "clean" (containing no dead rows) and simplicial (no supercolumns yet). Rows may contain dead columns, but all live rows contain at least one live column. */ PRIVATE void debug_structures ( /* === Parameters ======================================================= */ Int n_row, Int n_col, Colamd_Row Row [], Colamd_Col Col [], Int A [], Int n_col2 ) { /* === Local variables ================================================== */ Int i ; Int c ; Int *cp ; Int *cp_end ; Int len ; Int score ; Int r ; Int *rp ; Int *rp_end ; Int deg ; /* === Check A, Row, and Col ============================================ */ for (c = 0 ; c < n_col ; c++) { if (COL_IS_ALIVE (c)) { len = Col [c].length ; score = Col [c].shared2.score ; DEBUG4 (("initial live col %5d %5d %5d\n", c, len, score)) ; ASSERT (len > 0) ; ASSERT (score >= 0) ; ASSERT (Col [c].shared1.thickness == 1) ; cp = &A [Col [c].start] ; cp_end = cp + len ; while (cp < cp_end) { r = *cp++ ; ASSERT (ROW_IS_ALIVE (r)) ; } } else { i = Col [c].shared2.order ; ASSERT (i >= n_col2 && i < n_col) ; } } for (r = 0 ; r < n_row ; r++) { if (ROW_IS_ALIVE (r)) { i = 0 ; len = Row [r].length ; deg = Row [r].shared1.degree ; ASSERT (len > 0) ; ASSERT (deg > 0) ; rp = &A [Row [r].start] ; rp_end = rp + len ; while (rp < rp_end) { c = *rp++ ; if (COL_IS_ALIVE (c)) { i++ ; } } ASSERT (i > 0) ; } } } /* ========================================================================== */ /* === debug_deg_lists ====================================================== */ /* ========================================================================== */ /* Prints the contents of the degree lists. Counts the number of columns in the degree list and compares it to the total it should have. Also checks the row degrees. */ PRIVATE void debug_deg_lists ( /* === Parameters ======================================================= */ Int n_row, Int n_col, Colamd_Row Row [], Colamd_Col Col [], Int head [], Int min_score, Int should, Int max_deg ) { /* === Local variables ================================================== */ Int deg ; Int col ; Int have ; Int row ; /* === Check the degree lists =========================================== */ if (n_col > 10000 && colamd_debug <= 0) { return ; } have = 0 ; DEBUG4 (("Degree lists: %d\n", min_score)) ; for (deg = 0 ; deg <= n_col ; deg++) { col = head [deg] ; if (col == EMPTY) { continue ; } DEBUG4 (("%d:", deg)) ; while (col != EMPTY) { DEBUG4 ((" %d", col)) ; have += Col [col].shared1.thickness ; ASSERT (COL_IS_ALIVE (col)) ; col = Col [col].shared4.degree_next ; } DEBUG4 (("\n")) ; } DEBUG4 (("should %d have %d\n", should, have)) ; ASSERT (should == have) ; /* === Check the row degrees ============================================ */ if (n_row > 10000 && colamd_debug <= 0) { return ; } for (row = 0 ; row < n_row ; row++) { if (ROW_IS_ALIVE (row)) { ASSERT (Row [row].shared1.degree <= max_deg) ; } } } /* ========================================================================== */ /* === debug_mark =========================================================== */ /* ========================================================================== */ /* Ensures that the tag_mark is less that the maximum and also ensures that each entry in the mark array is less than the tag mark. */ PRIVATE void debug_mark ( /* === Parameters ======================================================= */ Int n_row, Colamd_Row Row [], Int tag_mark, Int max_mark ) { /* === Local variables ================================================== */ Int r ; /* === Check the Row marks ============================================== */ ASSERT (tag_mark > 0 && tag_mark <= max_mark) ; if (n_row > 10000 && colamd_debug <= 0) { return ; } for (r = 0 ; r < n_row ; r++) { ASSERT (Row [r].shared2.mark < tag_mark) ; } } /* ========================================================================== */ /* === debug_matrix ========================================================= */ /* ========================================================================== */ /* Prints out the contents of the columns and the rows. */ PRIVATE void debug_matrix ( /* === Parameters ======================================================= */ Int n_row, Int n_col, Colamd_Row Row [], Colamd_Col Col [], Int A [] ) { /* === Local variables ================================================== */ Int r ; Int c ; Int *rp ; Int *rp_end ; Int *cp ; Int *cp_end ; /* === Dump the rows and columns of the matrix ========================== */ if (colamd_debug < 3) { return ; } DEBUG3 (("DUMP MATRIX:\n")) ; for (r = 0 ; r < n_row ; r++) { DEBUG3 (("Row %d alive? %d\n", r, ROW_IS_ALIVE (r))) ; if (ROW_IS_DEAD (r)) { continue ; } DEBUG3 (("start %d length %d degree %d\n", Row [r].start, Row [r].length, Row [r].shared1.degree)) ; rp = &A [Row [r].start] ; rp_end = rp + Row [r].length ; while (rp < rp_end) { c = *rp++ ; DEBUG4 ((" %d col %d\n", COL_IS_ALIVE (c), c)) ; } } for (c = 0 ; c < n_col ; c++) { DEBUG3 (("Col %d alive? %d\n", c, COL_IS_ALIVE (c))) ; if (COL_IS_DEAD (c)) { continue ; } DEBUG3 (("start %d length %d shared1 %d shared2 %d\n", Col [c].start, Col [c].length, Col [c].shared1.thickness, Col [c].shared2.score)) ; cp = &A [Col [c].start] ; cp_end = cp + Col [c].length ; while (cp < cp_end) { r = *cp++ ; DEBUG4 ((" %d row %d\n", ROW_IS_ALIVE (r), r)) ; } } } PRIVATE void colamd_get_debug ( char *method ) { FILE *f ; colamd_debug = 0 ; /* no debug printing */ f = fopen ("debug", "r") ; if (f == (FILE *) NULL) { colamd_debug = 0 ; } else { fscanf (f, "%d", &colamd_debug) ; fclose (f) ; } DEBUG0 (("%s: debug version, D = %d (THIS WILL BE SLOW!)\n", method, colamd_debug)) ; } #endif /* NDEBUG */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/colamd/README0000644000076500000240000001027413524616144025522 0ustar tamasstaff00000000000000NOTE: Files in this subdirectory are NOT part of the GLPK package, but are used with GLPK. The original code was modified according to GLPK requirements by Andrew Makhorin . ************************************************************************ COLAMD/SYMAMD Version 2.7, Copyright (C) 1998-2007, Timothy A. Davis, All Rights Reserved. Description: colamd: an approximate minimum degree column ordering algorithm, for LU factorization of symmetric or unsymmetric matrices, QR factorization, least squares, interior point methods for linear programming problems, and other related problems. symamd: an approximate minimum degree ordering algorithm for Cholesky factorization of symmetric matrices. Purpose: Colamd computes a permutation Q such that the Cholesky factorization of (AQ)'(AQ) has less fill-in and requires fewer floating point operations than A'A. This also provides a good ordering for sparse partial pivoting methods, P(AQ) = LU, where Q is computed prior to numerical factorization, and P is computed during numerical factorization via conventional partial pivoting with row interchanges. Colamd is the column ordering method used in SuperLU, part of the ScaLAPACK library. It is also available as built-in function in MATLAB Version 6, available from MathWorks, Inc. (http://www.mathworks.com). This routine can be used in place of colmmd in MATLAB. Symamd computes a permutation P of a symmetric matrix A such that the Cholesky factorization of PAP' has less fill-in and requires fewer floating point operations than A. Symamd constructs a matrix M such that M'M has the same nonzero pattern of A, and then orders the columns of M using colmmd. The column ordering of M is then returned as the row and column ordering P of A. Authors: The authors of the code itself are Stefan I. Larimore and Timothy A. Davis (davis at cise.ufl.edu), University of Florida. The algorithm was developed in collaboration with John Gilbert, Xerox PARC, and Esmond Ng, Oak Ridge National Laboratory. Acknowledgements: This work was supported by the National Science Foundation, under grants DMS-9504974 and DMS-9803599. License: This library is free software; you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation; either version 2.1 of the License, or (at your option) any later version. This library is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with this library; if not, write to the Free Software Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA. Permission is hereby granted to use or copy this program under the terms of the GNU LGPL, provided that the Copyright, this License, and the Availability of the original version is retained on all copies. User documentation of any code that uses this code or any modified version of this code must cite the Copyright, this License, the Availability note, and "Used by permission." Permission to modify the code and to distribute modified code is granted, provided the Copyright, this License, and the Availability note are retained, and a notice that the code was modified is included. COLAMD is also available under alternate licenses, contact T. Davis for details. Availability: The colamd/symamd library is available at: http://www.cise.ufl.edu/research/sparse/colamd/ References: T. A. Davis, J. R. Gilbert, S. Larimore, E. Ng, An approximate column minimum degree ordering algorithm, ACM Transactions on Mathematical Software, vol. 30, no. 3., pp. 353-376, 2004. T. A. Davis, J. R. Gilbert, S. Larimore, E. Ng, Algorithm 836: COLAMD, an approximate column minimum degree ordering algorithm, ACM Transactions on Mathematical Software, vol. 30, no. 3., pp. 377-380, 2004. python-igraph-0.8.0/vendor/source/igraph/optional/glpk/colamd/colamd.h0000644000076500000240000000411413524616144026246 0ustar tamasstaff00000000000000/* colamd.h */ /* Written by Andrew Makhorin . */ #ifndef COLAMD_H #define COLAMD_H #define _GLPSTD_STDIO #include "glpenv.h" #define COLAMD_DATE "Nov 1, 2007" #define COLAMD_VERSION_CODE(main, sub) ((main) * 1000 + (sub)) #define COLAMD_MAIN_VERSION 2 #define COLAMD_SUB_VERSION 7 #define COLAMD_SUBSUB_VERSION 1 #define COLAMD_VERSION \ COLAMD_VERSION_CODE(COLAMD_MAIN_VERSION, COLAMD_SUB_VERSION) #define COLAMD_KNOBS 20 #define COLAMD_STATS 20 #define COLAMD_DENSE_ROW 0 #define COLAMD_DENSE_COL 1 #define COLAMD_AGGRESSIVE 2 #define COLAMD_DEFRAG_COUNT 2 #define COLAMD_STATUS 3 #define COLAMD_INFO1 4 #define COLAMD_INFO2 5 #define COLAMD_INFO3 6 #define COLAMD_OK (0) #define COLAMD_OK_BUT_JUMBLED (1) #define COLAMD_ERROR_A_not_present (-1) #define COLAMD_ERROR_p_not_present (-2) #define COLAMD_ERROR_nrow_negative (-3) #define COLAMD_ERROR_ncol_negative (-4) #define COLAMD_ERROR_nnz_negative (-5) #define COLAMD_ERROR_p0_nonzero (-6) #define COLAMD_ERROR_A_too_small (-7) #define COLAMD_ERROR_col_length_negative (-8) #define COLAMD_ERROR_row_index_out_of_bounds (-9) #define COLAMD_ERROR_out_of_memory (-10) #define COLAMD_ERROR_internal_error (-999) #define colamd_recommended _glp_colamd_recommended size_t colamd_recommended(int nnz, int n_row, int n_col); #define colamd_set_defaults _glp_colamd_set_defaults void colamd_set_defaults(double knobs [COLAMD_KNOBS]); #define colamd _glp_colamd int colamd(int n_row, int n_col, int Alen, int A[], int p[], double knobs[COLAMD_KNOBS], int stats[COLAMD_STATS]); #define symamd _glp_symamd int symamd(int n, int A[], int p[], int perm[], double knobs[COLAMD_KNOBS], int stats[COLAMD_STATS], void *(*allocate)(size_t, size_t), void(*release)(void *)); #define colamd_report _glp_colamd_report void colamd_report(int stats[COLAMD_STATS]); #define symamd_report _glp_symamd_report void symamd_report(int stats[COLAMD_STATS]); #define colamd_printf xprintf #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/colamd/COPYING0000644000076500000240000006362513524616144025705 0ustar tamasstaff00000000000000 GNU LESSER GENERAL PUBLIC LICENSE Version 2.1, February 1999 Copyright (C) 1991, 1999 Free Software Foundation, Inc. 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed. 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Here is a sample; alter the names: Yoyodyne, Inc., hereby disclaims all copyright interest in the library `Frob' (a library for tweaking knobs) written by James Random Hacker. , 1 April 1990 Ty Coon, President of Vice That's all there is to it! python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpnet05.c0000644000076500000240000002600513524616144025204 0ustar tamasstaff00000000000000/* glpnet05.c (Goldfarb's maximum flow problem generator) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * This code is a modified version of the program RMFGEN, a maxflow * problem generator developed by D.Goldfarb and M.Grigoriadis, and * originally implemented by Tamas Badics . * The original code is publically available on the DIMACS ftp site at: * . * * All changes concern only the program interface, so this modified * version produces exactly the same instances as the original version. * * Changes were made by Andrew Makhorin . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glpapi.h" #include "glprng.h" /*********************************************************************** * NAME * * glp_rmfgen - Goldfarb's maximum flow problem generator * * SYNOPSIS * * int glp_rmfgen(glp_graph *G, int *s, int *t, int a_cap, * const int parm[1+5]); * * DESCRIPTION * * The routine glp_rmfgen is a maximum flow problem generator developed * by D.Goldfarb and M.Grigoriadis. * * The parameter G specifies the graph object, to which the generated * problem data have to be stored. Note that on entry the graph object * is erased with the routine glp_erase_graph. * * The pointer s specifies a location, to which the routine stores the * source node number. If s is NULL, the node number is not stored. * * The pointer t specifies a location, to which the routine stores the * sink node number. If t is NULL, the node number is not stored. * * The parameter a_cap specifies an offset of the field of type double * in the arc data block, to which the routine stores the arc capacity. * If a_cap < 0, the capacity is not stored. * * The array parm contains description of the network to be generated: * * parm[0] not used * parm[1] (seed) random number seed (a positive integer) * parm[2] (a) frame size * parm[3] (b) depth * parm[4] (c1) minimal arc capacity * parm[5] (c2) maximal arc capacity * * RETURNS * * If the instance was successfully generated, the routine glp_netgen * returns zero; otherwise, if specified parameters are inconsistent, * the routine returns a non-zero error code. * * COMMENTS * * The generated network is as follows. It has b pieces of frames of * size a * a. (So alltogether the number of vertices is a * a * b) * * In each frame all the vertices are connected with their neighbours * (forth and back). In addition the vertices of a frame are connected * one to one with the vertices of next frame using a random permutation * of those vertices. * * The source is the lower left vertex of the first frame, the sink is * the upper right vertex of the b'th frame. * * t * +-------+ * | .| * | . | * / | / | * +-------+/ -+ b * | | |/. * a | -v- |/ * | | |/ * +-------+ 1 * s a * * The capacities are randomly chosen integers from the range of [c1,c2] * in the case of interconnecting edges, and c2 * a * a for the in-frame * edges. * * REFERENCES * * D.Goldfarb and M.D.Grigoriadis, "A computational comparison of the * Dinic and network simplex methods for maximum flow." Annals of Op. * Res. 13 (1988), pp. 83-123. * * U.Derigs and W.Meier, "Implementing Goldberg's max-flow algorithm: * A computational investigation." Zeitschrift fuer Operations Research * 33 (1989), pp. 383-403. */ typedef struct VERTEX { struct EDGE **edgelist; /* Pointer to the list of pointers to the adjacent edges. (No matter that to or from edges) */ struct EDGE **current; /* Pointer to the current edge */ int degree; /* Number of adjacent edges (both direction) */ int index; } vertex; typedef struct EDGE { int from; int to; int cap; /* Capacity */ } edge; typedef struct NETWORK { struct NETWORK *next, *prev; int vertnum; int edgenum; vertex *verts; /* Vertex array[1..vertnum] */ edge *edges; /* Edge array[1..edgenum] */ int source; /* Pointer to the source */ int sink; /* Pointer to the sink */ } network; struct csa { /* common storage area */ glp_graph *G; int *s, *t, a_cap; RNG *rand; network *N; int *Parr; int A, AA, C2AA, Ec; }; #define G (csa->G) #define s (csa->s) #define t (csa->t) #define a_cap (csa->a_cap) #define N (csa->N) #define Parr (csa->Parr) #define A (csa->A) #define AA (csa->AA) #define C2AA (csa->C2AA) #define Ec (csa->Ec) #undef random #define random(A) (int)(rng_unif_01(csa->rand) * (double)(A)) #define RANDOM(A, B) (int)(random((B) - (A) + 1) + (A)) #define sgn(A) (((A) > 0) ? 1 : ((A) == 0) ? 0 : -1) static void make_edge(struct csa *csa, int from, int to, int c1, int c2) { Ec++; N->edges[Ec].from = from; N->edges[Ec].to = to; N->edges[Ec].cap = RANDOM(c1, c2); return; } static void permute(struct csa *csa) { int i, j, tmp; for (i = 1; i < AA; i++) { j = RANDOM(i, AA); tmp = Parr[i]; Parr[i] = Parr[j]; Parr[j] = tmp; } return; } static void connect(struct csa *csa, int offset, int cv, int x1, int y1) { int cv1; cv1 = offset + (x1 - 1) * A + y1; Ec++; N->edges[Ec].from = cv; N->edges[Ec].to = cv1; N->edges[Ec].cap = C2AA; return; } static network *gen_rmf(struct csa *csa, int a, int b, int c1, int c2) { /* generates a network with a*a*b nodes and 6a*a*b-4ab-2a*a edges random_frame network: Derigs & Meier, Methods & Models of OR (1989), 33:383-403 */ int x, y, z, offset, cv; A = a; AA = a * a; C2AA = c2 * AA; Ec = 0; N = (network *)xmalloc(sizeof(network)); N->vertnum = AA * b; N->edgenum = 5 * AA * b - 4 * A * b - AA; N->edges = (edge *)xcalloc(N->edgenum + 1, sizeof(edge)); N->source = 1; N->sink = N->vertnum; Parr = (int *)xcalloc(AA + 1, sizeof(int)); for (x = 1; x <= AA; x++) Parr[x] = x; for (z = 1; z <= b; z++) { offset = AA * (z - 1); if (z != b) permute(csa); for (x = 1; x <= A; x++) { for (y = 1; y <= A; y++) { cv = offset + (x - 1) * A + y; if (z != b) make_edge(csa, cv, offset + AA + Parr[cv - offset], c1, c2); /* the intermediate edges */ if (y < A) connect(csa, offset, cv, x, y + 1); if (y > 1) connect(csa, offset, cv, x, y - 1); if (x < A) connect(csa, offset, cv, x + 1, y); if (x > 1) connect(csa, offset, cv, x - 1, y); } } } xfree(Parr); return N; } static void print_max_format(struct csa *csa, network *n, char *comm[], int dim) { /* prints a network heading with dim lines of comments (no \n needs at the ends) */ int i, vnum, e_num; edge *e; vnum = n->vertnum; e_num = n->edgenum; if (G == NULL) { for (i = 0; i < dim; i++) xprintf("c %s\n", comm[i]); xprintf("p max %7d %10d\n", vnum, e_num); xprintf("n %7d s\n", n->source); xprintf("n %7d t\n", n->sink); } else { glp_add_vertices(G, vnum); if (s != NULL) *s = n->source; if (t != NULL) *t = n->sink; } for (i = 1; i <= e_num; i++) { e = &n->edges[i]; if (G == NULL) xprintf("a %7d %7d %10d\n", e->from, e->to, (int)e->cap); else { glp_arc *a = glp_add_arc(G, e->from, e->to); if (a_cap >= 0) { double temp = (double)e->cap; memcpy((char *)a->data + a_cap, &temp, sizeof(double)); } } } return; } static void gen_free_net(network *n) { xfree(n->edges); xfree(n); return; } int glp_rmfgen(glp_graph *G_, int *_s, int *_t, int _a_cap, const int parm[1+5]) { struct csa _csa, *csa = &_csa; network *n; char comm[10][80], *com1[10]; int seed, a, b, c1, c2, ret; G = G_; s = _s; t = _t; a_cap = _a_cap; if (G != NULL) { if (a_cap >= 0 && a_cap > G->a_size - (int)sizeof(double)) xerror("glp_rmfgen: a_cap = %d; invalid offset\n", a_cap); } seed = parm[1]; a = parm[2]; b = parm[3]; c1 = parm[4]; c2 = parm[5]; if (!(seed > 0 && 1 <= a && a <= 1000 && 1 <= b && b <= 1000 && 0 <= c1 && c1 <= c2 && c2 <= 1000)) { ret = 1; goto done; } if (G != NULL) { glp_erase_graph(G, G->v_size, G->a_size); glp_set_graph_name(G, "RMFGEN"); } csa->rand = rng_create_rand(); rng_init_rand(csa->rand, seed); n = gen_rmf(csa, a, b, c1, c2); sprintf(comm[0], "This file was generated by genrmf."); sprintf(comm[1], "The parameters are: a: %d b: %d c1: %d c2: %d", a, b, c1, c2); com1[0] = comm[0]; com1[1] = comm[1]; print_max_format(csa, n, com1, 2); gen_free_net(n); rng_delete_rand(csa->rand); ret = 0; done: return ret; } /**********************************************************************/ #if 0 int main(int argc, char *argv[]) { int seed, a, b, c1, c2, i, parm[1+5]; seed = 123; a = b = c1 = c2 = -1; for (i = 1; i < argc; i++) { if (strcmp(argv[i], "-seed") == 0) seed = atoi(argv[++i]); else if (strcmp(argv[i], "-a") == 0) a = atoi(argv[++i]); else if (strcmp(argv[i], "-b") == 0) b = atoi(argv[++i]); else if (strcmp(argv[i], "-c1") == 0) c1 = atoi(argv[++i]); else if (strcmp(argv[i], "-c2") == 0) c2 = atoi(argv[++i]); } if (a < 0 || b < 0 || c1 < 0 || c2 < 0) { xprintf("Usage:\n"); xprintf("genrmf [-seed seed] -a frame_size -b depth\n"); xprintf(" -c1 cap_range1 -c2 cap_range2\n"); } else { parm[1] = seed; parm[2] = a; parm[3] = b; parm[4] = c1; parm[5] = c2; glp_rmfgen(NULL, NULL, NULL, 0, parm); } return 0; } #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpapi12.c0000644000076500000240000023535413524616144025176 0ustar tamasstaff00000000000000/* glpapi12.c (basis factorization and simplex tableau routines) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wlogical-op-parentheses" #pragma clang diagnostic ignored "-Wsometimes-uninitialized" #endif #include "glpapi.h" /*********************************************************************** * NAME * * glp_bf_exists - check if the basis factorization exists * * SYNOPSIS * * int glp_bf_exists(glp_prob *lp); * * RETURNS * * If the basis factorization for the current basis associated with * the specified problem object exists and therefore is available for * computations, the routine glp_bf_exists returns non-zero. Otherwise * the routine returns zero. */ int glp_bf_exists(glp_prob *lp) { int ret; ret = (lp->m == 0 || lp->valid); return ret; } /*********************************************************************** * NAME * * glp_factorize - compute the basis factorization * * SYNOPSIS * * int glp_factorize(glp_prob *lp); * * DESCRIPTION * * The routine glp_factorize computes the basis factorization for the * current basis associated with the specified problem object. * * RETURNS * * 0 The basis factorization has been successfully computed. * * GLP_EBADB * The basis matrix is invalid, i.e. the number of basic (auxiliary * and structural) variables differs from the number of rows in the * problem object. * * GLP_ESING * The basis matrix is singular within the working precision. * * GLP_ECOND * The basis matrix is ill-conditioned. */ static int b_col(void *info, int j, int ind[], double val[]) { glp_prob *lp = info; int m = lp->m; GLPAIJ *aij; int k, len; xassert(1 <= j && j <= m); /* determine the ordinal number of basic auxiliary or structural variable x[k] corresponding to basic variable xB[j] */ k = lp->head[j]; /* build j-th column of the basic matrix, which is k-th column of the scaled augmented matrix (I | -R*A*S) */ if (k <= m) { /* x[k] is auxiliary variable */ len = 1; ind[1] = k; val[1] = 1.0; } else { /* x[k] is structural variable */ len = 0; for (aij = lp->col[k-m]->ptr; aij != NULL; aij = aij->c_next) { len++; ind[len] = aij->row->i; val[len] = - aij->row->rii * aij->val * aij->col->sjj; } } return len; } static void copy_bfcp(glp_prob *lp); int glp_factorize(glp_prob *lp) { int m = lp->m; int n = lp->n; GLPROW **row = lp->row; GLPCOL **col = lp->col; int *head = lp->head; int j, k, stat, ret; /* invalidate the basis factorization */ lp->valid = 0; /* build the basis header */ j = 0; for (k = 1; k <= m+n; k++) { if (k <= m) { stat = row[k]->stat; row[k]->bind = 0; } else { stat = col[k-m]->stat; col[k-m]->bind = 0; } if (stat == GLP_BS) { j++; if (j > m) { /* too many basic variables */ ret = GLP_EBADB; goto fini; } head[j] = k; if (k <= m) row[k]->bind = j; else col[k-m]->bind = j; } } if (j < m) { /* too few basic variables */ ret = GLP_EBADB; goto fini; } /* try to factorize the basis matrix */ if (m > 0) { if (lp->bfd == NULL) { lp->bfd = bfd_create_it(); copy_bfcp(lp); } switch (bfd_factorize(lp->bfd, m, lp->head, b_col, lp)) { case 0: /* ok */ break; case BFD_ESING: /* singular matrix */ ret = GLP_ESING; goto fini; case BFD_ECOND: /* ill-conditioned matrix */ ret = GLP_ECOND; goto fini; default: xassert(lp != lp); } lp->valid = 1; } /* factorization successful */ ret = 0; fini: /* bring the return code to the calling program */ return ret; } /*********************************************************************** * NAME * * glp_bf_updated - check if the basis factorization has been updated * * SYNOPSIS * * int glp_bf_updated(glp_prob *lp); * * RETURNS * * If the basis factorization has been just computed from scratch, the * routine glp_bf_updated returns zero. Otherwise, if the factorization * has been updated one or more times, the routine returns non-zero. */ int glp_bf_updated(glp_prob *lp) { int cnt; if (!(lp->m == 0 || lp->valid)) xerror("glp_bf_update: basis factorization does not exist\n"); #if 0 /* 15/XI-2009 */ cnt = (lp->m == 0 ? 0 : lp->bfd->upd_cnt); #else cnt = (lp->m == 0 ? 0 : bfd_get_count(lp->bfd)); #endif return cnt; } /*********************************************************************** * NAME * * glp_get_bfcp - retrieve basis factorization control parameters * * SYNOPSIS * * void glp_get_bfcp(glp_prob *lp, glp_bfcp *parm); * * DESCRIPTION * * The routine glp_get_bfcp retrieves control parameters, which are * used on computing and updating the basis factorization associated * with the specified problem object. * * Current values of control parameters are stored by the routine in * a glp_bfcp structure, which the parameter parm points to. */ void glp_get_bfcp(glp_prob *lp, glp_bfcp *parm) { glp_bfcp *bfcp = lp->bfcp; if (bfcp == NULL) { parm->type = GLP_BF_FT; parm->lu_size = 0; parm->piv_tol = 0.10; parm->piv_lim = 4; parm->suhl = GLP_ON; parm->eps_tol = 1e-15; parm->max_gro = 1e+10; parm->nfs_max = 100; parm->upd_tol = 1e-6; parm->nrs_max = 100; parm->rs_size = 0; } else memcpy(parm, bfcp, sizeof(glp_bfcp)); return; } /*********************************************************************** * NAME * * glp_set_bfcp - change basis factorization control parameters * * SYNOPSIS * * void glp_set_bfcp(glp_prob *lp, const glp_bfcp *parm); * * DESCRIPTION * * The routine glp_set_bfcp changes control parameters, which are used * by internal GLPK routines in computing and updating the basis * factorization associated with the specified problem object. * * New values of the control parameters should be passed in a structure * glp_bfcp, which the parameter parm points to. * * The parameter parm can be specified as NULL, in which case all * control parameters are reset to their default values. */ #if 0 /* 15/XI-2009 */ static void copy_bfcp(glp_prob *lp) { glp_bfcp _parm, *parm = &_parm; BFD *bfd = lp->bfd; glp_get_bfcp(lp, parm); xassert(bfd != NULL); bfd->type = parm->type; bfd->lu_size = parm->lu_size; bfd->piv_tol = parm->piv_tol; bfd->piv_lim = parm->piv_lim; bfd->suhl = parm->suhl; bfd->eps_tol = parm->eps_tol; bfd->max_gro = parm->max_gro; bfd->nfs_max = parm->nfs_max; bfd->upd_tol = parm->upd_tol; bfd->nrs_max = parm->nrs_max; bfd->rs_size = parm->rs_size; return; } #else static void copy_bfcp(glp_prob *lp) { glp_bfcp _parm, *parm = &_parm; glp_get_bfcp(lp, parm); bfd_set_parm(lp->bfd, parm); return; } #endif void glp_set_bfcp(glp_prob *lp, const glp_bfcp *parm) { glp_bfcp *bfcp = lp->bfcp; if (parm == NULL) { /* reset to default values */ if (bfcp != NULL) xfree(bfcp), lp->bfcp = NULL; } else { /* set to specified values */ if (bfcp == NULL) bfcp = lp->bfcp = xmalloc(sizeof(glp_bfcp)); memcpy(bfcp, parm, sizeof(glp_bfcp)); if (!(bfcp->type == GLP_BF_FT || bfcp->type == GLP_BF_BG || bfcp->type == GLP_BF_GR)) xerror("glp_set_bfcp: type = %d; invalid parameter\n", bfcp->type); if (bfcp->lu_size < 0) xerror("glp_set_bfcp: lu_size = %d; invalid parameter\n", bfcp->lu_size); if (!(0.0 < bfcp->piv_tol && bfcp->piv_tol < 1.0)) xerror("glp_set_bfcp: piv_tol = %g; invalid parameter\n", bfcp->piv_tol); if (bfcp->piv_lim < 1) xerror("glp_set_bfcp: piv_lim = %d; invalid parameter\n", bfcp->piv_lim); if (!(bfcp->suhl == GLP_ON || bfcp->suhl == GLP_OFF)) xerror("glp_set_bfcp: suhl = %d; invalid parameter\n", bfcp->suhl); if (!(0.0 <= bfcp->eps_tol && bfcp->eps_tol <= 1e-6)) xerror("glp_set_bfcp: eps_tol = %g; invalid parameter\n", bfcp->eps_tol); if (bfcp->max_gro < 1.0) xerror("glp_set_bfcp: max_gro = %g; invalid parameter\n", bfcp->max_gro); if (!(1 <= bfcp->nfs_max && bfcp->nfs_max <= 32767)) xerror("glp_set_bfcp: nfs_max = %d; invalid parameter\n", bfcp->nfs_max); if (!(0.0 < bfcp->upd_tol && bfcp->upd_tol < 1.0)) xerror("glp_set_bfcp: upd_tol = %g; invalid parameter\n", bfcp->upd_tol); if (!(1 <= bfcp->nrs_max && bfcp->nrs_max <= 32767)) xerror("glp_set_bfcp: nrs_max = %d; invalid parameter\n", bfcp->nrs_max); if (bfcp->rs_size < 0) xerror("glp_set_bfcp: rs_size = %d; invalid parameter\n", bfcp->nrs_max); if (bfcp->rs_size == 0) bfcp->rs_size = 20 * bfcp->nrs_max; } if (lp->bfd != NULL) copy_bfcp(lp); return; } /*********************************************************************** * NAME * * glp_get_bhead - retrieve the basis header information * * SYNOPSIS * * int glp_get_bhead(glp_prob *lp, int k); * * DESCRIPTION * * The routine glp_get_bhead returns the basis header information for * the current basis associated with the specified problem object. * * RETURNS * * If xB[k], 1 <= k <= m, is i-th auxiliary variable (1 <= i <= m), the * routine returns i. Otherwise, if xB[k] is j-th structural variable * (1 <= j <= n), the routine returns m+j. Here m is the number of rows * and n is the number of columns in the problem object. */ int glp_get_bhead(glp_prob *lp, int k) { if (!(lp->m == 0 || lp->valid)) xerror("glp_get_bhead: basis factorization does not exist\n"); if (!(1 <= k && k <= lp->m)) xerror("glp_get_bhead: k = %d; index out of range\n", k); return lp->head[k]; } /*********************************************************************** * NAME * * glp_get_row_bind - retrieve row index in the basis header * * SYNOPSIS * * int glp_get_row_bind(glp_prob *lp, int i); * * RETURNS * * The routine glp_get_row_bind returns the index k of basic variable * xB[k], 1 <= k <= m, which is i-th auxiliary variable, 1 <= i <= m, * in the current basis associated with the specified problem object, * where m is the number of rows. However, if i-th auxiliary variable * is non-basic, the routine returns zero. */ int glp_get_row_bind(glp_prob *lp, int i) { if (!(lp->m == 0 || lp->valid)) xerror("glp_get_row_bind: basis factorization does not exist\n" ); if (!(1 <= i && i <= lp->m)) xerror("glp_get_row_bind: i = %d; row number out of range\n", i); return lp->row[i]->bind; } /*********************************************************************** * NAME * * glp_get_col_bind - retrieve column index in the basis header * * SYNOPSIS * * int glp_get_col_bind(glp_prob *lp, int j); * * RETURNS * * The routine glp_get_col_bind returns the index k of basic variable * xB[k], 1 <= k <= m, which is j-th structural variable, 1 <= j <= n, * in the current basis associated with the specified problem object, * where m is the number of rows, n is the number of columns. However, * if j-th structural variable is non-basic, the routine returns zero.*/ int glp_get_col_bind(glp_prob *lp, int j) { if (!(lp->m == 0 || lp->valid)) xerror("glp_get_col_bind: basis factorization does not exist\n" ); if (!(1 <= j && j <= lp->n)) xerror("glp_get_col_bind: j = %d; column number out of range\n" , j); return lp->col[j]->bind; } /*********************************************************************** * NAME * * glp_ftran - perform forward transformation (solve system B*x = b) * * SYNOPSIS * * void glp_ftran(glp_prob *lp, double x[]); * * DESCRIPTION * * The routine glp_ftran performs forward transformation, i.e. solves * the system B*x = b, where B is the basis matrix corresponding to the * current basis for the specified problem object, x is the vector of * unknowns to be computed, b is the vector of right-hand sides. * * On entry elements of the vector b should be stored in dense format * in locations x[1], ..., x[m], where m is the number of rows. On exit * the routine stores elements of the vector x in the same locations. * * SCALING/UNSCALING * * Let A~ = (I | -A) is the augmented constraint matrix of the original * (unscaled) problem. In the scaled LP problem instead the matrix A the * scaled matrix A" = R*A*S is actually used, so * * A~" = (I | A") = (I | R*A*S) = (R*I*inv(R) | R*A*S) = * (1) * = R*(I | A)*S~ = R*A~*S~, * * is the scaled augmented constraint matrix, where R and S are diagonal * scaling matrices used to scale rows and columns of the matrix A, and * * S~ = diag(inv(R) | S) (2) * * is an augmented diagonal scaling matrix. * * By definition: * * A~ = (B | N), (3) * * where B is the basic matrix, which consists of basic columns of the * augmented constraint matrix A~, and N is a matrix, which consists of * non-basic columns of A~. From (1) it follows that: * * A~" = (B" | N") = (R*B*SB | R*N*SN), (4) * * where SB and SN are parts of the augmented scaling matrix S~, which * correspond to basic and non-basic variables, respectively. Therefore * * B" = R*B*SB, (5) * * which is the scaled basis matrix. */ void glp_ftran(glp_prob *lp, double x[]) { int m = lp->m; GLPROW **row = lp->row; GLPCOL **col = lp->col; int i, k; /* B*x = b ===> (R*B*SB)*(inv(SB)*x) = R*b ===> B"*x" = b", where b" = R*b, x = SB*x" */ if (!(m == 0 || lp->valid)) xerror("glp_ftran: basis factorization does not exist\n"); /* b" := R*b */ for (i = 1; i <= m; i++) x[i] *= row[i]->rii; /* x" := inv(B")*b" */ if (m > 0) bfd_ftran(lp->bfd, x); /* x := SB*x" */ for (i = 1; i <= m; i++) { k = lp->head[i]; if (k <= m) x[i] /= row[k]->rii; else x[i] *= col[k-m]->sjj; } return; } /*********************************************************************** * NAME * * glp_btran - perform backward transformation (solve system B'*x = b) * * SYNOPSIS * * void glp_btran(glp_prob *lp, double x[]); * * DESCRIPTION * * The routine glp_btran performs backward transformation, i.e. solves * the system B'*x = b, where B' is a matrix transposed to the basis * matrix corresponding to the current basis for the specified problem * problem object, x is the vector of unknowns to be computed, b is the * vector of right-hand sides. * * On entry elements of the vector b should be stored in dense format * in locations x[1], ..., x[m], where m is the number of rows. On exit * the routine stores elements of the vector x in the same locations. * * SCALING/UNSCALING * * See comments to the routine glp_ftran. */ void glp_btran(glp_prob *lp, double x[]) { int m = lp->m; GLPROW **row = lp->row; GLPCOL **col = lp->col; int i, k; /* B'*x = b ===> (SB*B'*R)*(inv(R)*x) = SB*b ===> (B")'*x" = b", where b" = SB*b, x = R*x" */ if (!(m == 0 || lp->valid)) xerror("glp_btran: basis factorization does not exist\n"); /* b" := SB*b */ for (i = 1; i <= m; i++) { k = lp->head[i]; if (k <= m) x[i] /= row[k]->rii; else x[i] *= col[k-m]->sjj; } /* x" := inv[(B")']*b" */ if (m > 0) bfd_btran(lp->bfd, x); /* x := R*x" */ for (i = 1; i <= m; i++) x[i] *= row[i]->rii; return; } /*********************************************************************** * NAME * * glp_warm_up - "warm up" LP basis * * SYNOPSIS * * int glp_warm_up(glp_prob *P); * * DESCRIPTION * * The routine glp_warm_up "warms up" the LP basis for the specified * problem object using current statuses assigned to rows and columns * (that is, to auxiliary and structural variables). * * This operation includes computing factorization of the basis matrix * (if it does not exist), computing primal and dual components of basic * solution, and determining the solution status. * * RETURNS * * 0 The operation has been successfully performed. * * GLP_EBADB * The basis matrix is invalid, i.e. the number of basic (auxiliary * and structural) variables differs from the number of rows in the * problem object. * * GLP_ESING * The basis matrix is singular within the working precision. * * GLP_ECOND * The basis matrix is ill-conditioned. */ int glp_warm_up(glp_prob *P) { GLPROW *row; GLPCOL *col; GLPAIJ *aij; int i, j, type, ret; double eps, temp, *work; /* invalidate basic solution */ P->pbs_stat = P->dbs_stat = GLP_UNDEF; P->obj_val = 0.0; P->some = 0; for (i = 1; i <= P->m; i++) { row = P->row[i]; row->prim = row->dual = 0.0; } for (j = 1; j <= P->n; j++) { col = P->col[j]; col->prim = col->dual = 0.0; } /* compute the basis factorization, if necessary */ if (!glp_bf_exists(P)) { ret = glp_factorize(P); if (ret != 0) goto done; } /* allocate working array */ work = xcalloc(1+P->m, sizeof(double)); /* determine and store values of non-basic variables, compute vector (- N * xN) */ for (i = 1; i <= P->m; i++) work[i] = 0.0; for (i = 1; i <= P->m; i++) { row = P->row[i]; if (row->stat == GLP_BS) continue; else if (row->stat == GLP_NL) row->prim = row->lb; else if (row->stat == GLP_NU) row->prim = row->ub; else if (row->stat == GLP_NF) row->prim = 0.0; else if (row->stat == GLP_NS) row->prim = row->lb; else xassert(row != row); /* N[j] is i-th column of matrix (I|-A) */ work[i] -= row->prim; } for (j = 1; j <= P->n; j++) { col = P->col[j]; if (col->stat == GLP_BS) continue; else if (col->stat == GLP_NL) col->prim = col->lb; else if (col->stat == GLP_NU) col->prim = col->ub; else if (col->stat == GLP_NF) col->prim = 0.0; else if (col->stat == GLP_NS) col->prim = col->lb; else xassert(col != col); /* N[j] is (m+j)-th column of matrix (I|-A) */ if (col->prim != 0.0) { for (aij = col->ptr; aij != NULL; aij = aij->c_next) work[aij->row->i] += aij->val * col->prim; } } /* compute vector of basic variables xB = - inv(B) * N * xN */ glp_ftran(P, work); /* store values of basic variables, check primal feasibility */ P->pbs_stat = GLP_FEAS; for (i = 1; i <= P->m; i++) { row = P->row[i]; if (row->stat != GLP_BS) continue; row->prim = work[row->bind]; type = row->type; if (type == GLP_LO || type == GLP_DB || type == GLP_FX) { eps = 1e-6 + 1e-9 * fabs(row->lb); if (row->prim < row->lb - eps) P->pbs_stat = GLP_INFEAS; } if (type == GLP_UP || type == GLP_DB || type == GLP_FX) { eps = 1e-6 + 1e-9 * fabs(row->ub); if (row->prim > row->ub + eps) P->pbs_stat = GLP_INFEAS; } } for (j = 1; j <= P->n; j++) { col = P->col[j]; if (col->stat != GLP_BS) continue; col->prim = work[col->bind]; type = col->type; if (type == GLP_LO || type == GLP_DB || type == GLP_FX) { eps = 1e-6 + 1e-9 * fabs(col->lb); if (col->prim < col->lb - eps) P->pbs_stat = GLP_INFEAS; } if (type == GLP_UP || type == GLP_DB || type == GLP_FX) { eps = 1e-6 + 1e-9 * fabs(col->ub); if (col->prim > col->ub + eps) P->pbs_stat = GLP_INFEAS; } } /* compute value of the objective function */ P->obj_val = P->c0; for (j = 1; j <= P->n; j++) { col = P->col[j]; P->obj_val += col->coef * col->prim; } /* build vector cB of objective coefficients at basic variables */ for (i = 1; i <= P->m; i++) work[i] = 0.0; for (j = 1; j <= P->n; j++) { col = P->col[j]; if (col->stat == GLP_BS) work[col->bind] = col->coef; } /* compute vector of simplex multipliers pi = inv(B') * cB */ glp_btran(P, work); /* compute and store reduced costs of non-basic variables d[j] = c[j] - N'[j] * pi, check dual feasibility */ P->dbs_stat = GLP_FEAS; for (i = 1; i <= P->m; i++) { row = P->row[i]; if (row->stat == GLP_BS) { row->dual = 0.0; continue; } /* N[j] is i-th column of matrix (I|-A) */ row->dual = - work[i]; type = row->type; temp = (P->dir == GLP_MIN ? + row->dual : - row->dual); if ((type == GLP_FR || type == GLP_LO) && temp < -1e-5 || (type == GLP_FR || type == GLP_UP) && temp > +1e-5) P->dbs_stat = GLP_INFEAS; } for (j = 1; j <= P->n; j++) { col = P->col[j]; if (col->stat == GLP_BS) { col->dual = 0.0; continue; } /* N[j] is (m+j)-th column of matrix (I|-A) */ col->dual = col->coef; for (aij = col->ptr; aij != NULL; aij = aij->c_next) col->dual += aij->val * work[aij->row->i]; type = col->type; temp = (P->dir == GLP_MIN ? + col->dual : - col->dual); if ((type == GLP_FR || type == GLP_LO) && temp < -1e-5 || (type == GLP_FR || type == GLP_UP) && temp > +1e-5) P->dbs_stat = GLP_INFEAS; } /* free working array */ xfree(work); ret = 0; done: return ret; } /*********************************************************************** * NAME * * glp_eval_tab_row - compute row of the simplex tableau * * SYNOPSIS * * int glp_eval_tab_row(glp_prob *lp, int k, int ind[], double val[]); * * DESCRIPTION * * The routine glp_eval_tab_row computes a row of the current simplex * tableau for the basic variable, which is specified by the number k: * if 1 <= k <= m, x[k] is k-th auxiliary variable; if m+1 <= k <= m+n, * x[k] is (k-m)-th structural variable, where m is number of rows, and * n is number of columns. The current basis must be available. * * The routine stores column indices and numerical values of non-zero * elements of the computed row using sparse format to the locations * ind[1], ..., ind[len] and val[1], ..., val[len], respectively, where * 0 <= len <= n is number of non-zeros returned on exit. * * Element indices stored in the array ind have the same sense as the * index k, i.e. indices 1 to m denote auxiliary variables and indices * m+1 to m+n denote structural ones (all these variables are obviously * non-basic by definition). * * The computed row shows how the specified basic variable x[k] = xB[i] * depends on non-basic variables: * * xB[i] = alfa[i,1]*xN[1] + alfa[i,2]*xN[2] + ... + alfa[i,n]*xN[n], * * where alfa[i,j] are elements of the simplex table row, xN[j] are * non-basic (auxiliary and structural) variables. * * RETURNS * * The routine returns number of non-zero elements in the simplex table * row stored in the arrays ind and val. * * BACKGROUND * * The system of equality constraints of the LP problem is: * * xR = A * xS, (1) * * where xR is the vector of auxliary variables, xS is the vector of * structural variables, A is the matrix of constraint coefficients. * * The system (1) can be written in homogenous form as follows: * * A~ * x = 0, (2) * * where A~ = (I | -A) is the augmented constraint matrix (has m rows * and m+n columns), x = (xR | xS) is the vector of all (auxiliary and * structural) variables. * * By definition for the current basis we have: * * A~ = (B | N), (3) * * where B is the basis matrix. Thus, the system (2) can be written as: * * B * xB + N * xN = 0. (4) * * From (4) it follows that: * * xB = A^ * xN, (5) * * where the matrix * * A^ = - inv(B) * N (6) * * is called the simplex table. * * It is understood that i-th row of the simplex table is: * * e * A^ = - e * inv(B) * N, (7) * * where e is a unity vector with e[i] = 1. * * To compute i-th row of the simplex table the routine first computes * i-th row of the inverse: * * rho = inv(B') * e, (8) * * where B' is a matrix transposed to B, and then computes elements of * i-th row of the simplex table as scalar products: * * alfa[i,j] = - rho * N[j] for all j, (9) * * where N[j] is a column of the augmented constraint matrix A~, which * corresponds to some non-basic auxiliary or structural variable. */ int glp_eval_tab_row(glp_prob *lp, int k, int ind[], double val[]) { int m = lp->m; int n = lp->n; int i, t, len, lll, *iii; double alfa, *rho, *vvv; if (!(m == 0 || lp->valid)) xerror("glp_eval_tab_row: basis factorization does not exist\n" ); if (!(1 <= k && k <= m+n)) xerror("glp_eval_tab_row: k = %d; variable number out of range" , k); /* determine xB[i] which corresponds to x[k] */ if (k <= m) i = glp_get_row_bind(lp, k); else i = glp_get_col_bind(lp, k-m); if (i == 0) xerror("glp_eval_tab_row: k = %d; variable must be basic", k); xassert(1 <= i && i <= m); /* allocate working arrays */ rho = xcalloc(1+m, sizeof(double)); iii = xcalloc(1+m, sizeof(int)); vvv = xcalloc(1+m, sizeof(double)); /* compute i-th row of the inverse; see (8) */ for (t = 1; t <= m; t++) rho[t] = 0.0; rho[i] = 1.0; glp_btran(lp, rho); /* compute i-th row of the simplex table */ len = 0; for (k = 1; k <= m+n; k++) { if (k <= m) { /* x[k] is auxiliary variable, so N[k] is a unity column */ if (glp_get_row_stat(lp, k) == GLP_BS) continue; /* compute alfa[i,j]; see (9) */ alfa = - rho[k]; } else { /* x[k] is structural variable, so N[k] is a column of the original constraint matrix A with negative sign */ if (glp_get_col_stat(lp, k-m) == GLP_BS) continue; /* compute alfa[i,j]; see (9) */ lll = glp_get_mat_col(lp, k-m, iii, vvv); alfa = 0.0; for (t = 1; t <= lll; t++) alfa += rho[iii[t]] * vvv[t]; } /* store alfa[i,j] */ if (alfa != 0.0) len++, ind[len] = k, val[len] = alfa; } xassert(len <= n); /* free working arrays */ xfree(rho); xfree(iii); xfree(vvv); /* return to the calling program */ return len; } /*********************************************************************** * NAME * * glp_eval_tab_col - compute column of the simplex tableau * * SYNOPSIS * * int glp_eval_tab_col(glp_prob *lp, int k, int ind[], double val[]); * * DESCRIPTION * * The routine glp_eval_tab_col computes a column of the current simplex * table for the non-basic variable, which is specified by the number k: * if 1 <= k <= m, x[k] is k-th auxiliary variable; if m+1 <= k <= m+n, * x[k] is (k-m)-th structural variable, where m is number of rows, and * n is number of columns. The current basis must be available. * * The routine stores row indices and numerical values of non-zero * elements of the computed column using sparse format to the locations * ind[1], ..., ind[len] and val[1], ..., val[len] respectively, where * 0 <= len <= m is number of non-zeros returned on exit. * * Element indices stored in the array ind have the same sense as the * index k, i.e. indices 1 to m denote auxiliary variables and indices * m+1 to m+n denote structural ones (all these variables are obviously * basic by the definition). * * The computed column shows how basic variables depend on the specified * non-basic variable x[k] = xN[j]: * * xB[1] = ... + alfa[1,j]*xN[j] + ... * xB[2] = ... + alfa[2,j]*xN[j] + ... * . . . . . . * xB[m] = ... + alfa[m,j]*xN[j] + ... * * where alfa[i,j] are elements of the simplex table column, xB[i] are * basic (auxiliary and structural) variables. * * RETURNS * * The routine returns number of non-zero elements in the simplex table * column stored in the arrays ind and val. * * BACKGROUND * * As it was explained in comments to the routine glp_eval_tab_row (see * above) the simplex table is the following matrix: * * A^ = - inv(B) * N. (1) * * Therefore j-th column of the simplex table is: * * A^ * e = - inv(B) * N * e = - inv(B) * N[j], (2) * * where e is a unity vector with e[j] = 1, B is the basis matrix, N[j] * is a column of the augmented constraint matrix A~, which corresponds * to the given non-basic auxiliary or structural variable. */ int glp_eval_tab_col(glp_prob *lp, int k, int ind[], double val[]) { int m = lp->m; int n = lp->n; int t, len, stat; double *col; if (!(m == 0 || lp->valid)) xerror("glp_eval_tab_col: basis factorization does not exist\n" ); if (!(1 <= k && k <= m+n)) xerror("glp_eval_tab_col: k = %d; variable number out of range" , k); if (k <= m) stat = glp_get_row_stat(lp, k); else stat = glp_get_col_stat(lp, k-m); if (stat == GLP_BS) xerror("glp_eval_tab_col: k = %d; variable must be non-basic", k); /* obtain column N[k] with negative sign */ col = xcalloc(1+m, sizeof(double)); for (t = 1; t <= m; t++) col[t] = 0.0; if (k <= m) { /* x[k] is auxiliary variable, so N[k] is a unity column */ col[k] = -1.0; } else { /* x[k] is structural variable, so N[k] is a column of the original constraint matrix A with negative sign */ len = glp_get_mat_col(lp, k-m, ind, val); for (t = 1; t <= len; t++) col[ind[t]] = val[t]; } /* compute column of the simplex table, which corresponds to the specified non-basic variable x[k] */ glp_ftran(lp, col); len = 0; for (t = 1; t <= m; t++) { if (col[t] != 0.0) { len++; ind[len] = glp_get_bhead(lp, t); val[len] = col[t]; } } xfree(col); /* return to the calling program */ return len; } /*********************************************************************** * NAME * * glp_transform_row - transform explicitly specified row * * SYNOPSIS * * int glp_transform_row(glp_prob *P, int len, int ind[], double val[]); * * DESCRIPTION * * The routine glp_transform_row performs the same operation as the * routine glp_eval_tab_row with exception that the row to be * transformed is specified explicitly as a sparse vector. * * The explicitly specified row may be thought as a linear form: * * x = a[1]*x[m+1] + a[2]*x[m+2] + ... + a[n]*x[m+n], (1) * * where x is an auxiliary variable for this row, a[j] are coefficients * of the linear form, x[m+j] are structural variables. * * On entry column indices and numerical values of non-zero elements of * the row should be stored in locations ind[1], ..., ind[len] and * val[1], ..., val[len], where len is the number of non-zero elements. * * This routine uses the system of equality constraints and the current * basis in order to express the auxiliary variable x in (1) through the * current non-basic variables (as if the transformed row were added to * the problem object and its auxiliary variable were basic), i.e. the * resultant row has the form: * * x = alfa[1]*xN[1] + alfa[2]*xN[2] + ... + alfa[n]*xN[n], (2) * * where xN[j] are non-basic (auxiliary or structural) variables, n is * the number of columns in the LP problem object. * * On exit the routine stores indices and numerical values of non-zero * elements of the resultant row (2) in locations ind[1], ..., ind[len'] * and val[1], ..., val[len'], where 0 <= len' <= n is the number of * non-zero elements in the resultant row returned by the routine. Note * that indices (numbers) of non-basic variables stored in the array ind * correspond to original ordinal numbers of variables: indices 1 to m * mean auxiliary variables and indices m+1 to m+n mean structural ones. * * RETURNS * * The routine returns len', which is the number of non-zero elements in * the resultant row stored in the arrays ind and val. * * BACKGROUND * * The explicitly specified row (1) is transformed in the same way as it * were the objective function row. * * From (1) it follows that: * * x = aB * xB + aN * xN, (3) * * where xB is the vector of basic variables, xN is the vector of * non-basic variables. * * The simplex table, which corresponds to the current basis, is: * * xB = [-inv(B) * N] * xN. (4) * * Therefore substituting xB from (4) to (3) we have: * * x = aB * [-inv(B) * N] * xN + aN * xN = * (5) * = rho * (-N) * xN + aN * xN = alfa * xN, * * where: * * rho = inv(B') * aB, (6) * * and * * alfa = aN + rho * (-N) (7) * * is the resultant row computed by the routine. */ int glp_transform_row(glp_prob *P, int len, int ind[], double val[]) { int i, j, k, m, n, t, lll, *iii; double alfa, *a, *aB, *rho, *vvv; if (!glp_bf_exists(P)) xerror("glp_transform_row: basis factorization does not exist " "\n"); m = glp_get_num_rows(P); n = glp_get_num_cols(P); /* unpack the row to be transformed to the array a */ a = xcalloc(1+n, sizeof(double)); for (j = 1; j <= n; j++) a[j] = 0.0; if (!(0 <= len && len <= n)) xerror("glp_transform_row: len = %d; invalid row length\n", len); for (t = 1; t <= len; t++) { j = ind[t]; if (!(1 <= j && j <= n)) xerror("glp_transform_row: ind[%d] = %d; column index out o" "f range\n", t, j); if (val[t] == 0.0) xerror("glp_transform_row: val[%d] = 0; zero coefficient no" "t allowed\n", t); if (a[j] != 0.0) xerror("glp_transform_row: ind[%d] = %d; duplicate column i" "ndices not allowed\n", t, j); a[j] = val[t]; } /* construct the vector aB */ aB = xcalloc(1+m, sizeof(double)); for (i = 1; i <= m; i++) { k = glp_get_bhead(P, i); /* xB[i] is k-th original variable */ xassert(1 <= k && k <= m+n); aB[i] = (k <= m ? 0.0 : a[k-m]); } /* solve the system B'*rho = aB to compute the vector rho */ rho = aB, glp_btran(P, rho); /* compute coefficients at non-basic auxiliary variables */ len = 0; for (i = 1; i <= m; i++) { if (glp_get_row_stat(P, i) != GLP_BS) { alfa = - rho[i]; if (alfa != 0.0) { len++; ind[len] = i; val[len] = alfa; } } } /* compute coefficients at non-basic structural variables */ iii = xcalloc(1+m, sizeof(int)); vvv = xcalloc(1+m, sizeof(double)); for (j = 1; j <= n; j++) { if (glp_get_col_stat(P, j) != GLP_BS) { alfa = a[j]; lll = glp_get_mat_col(P, j, iii, vvv); for (t = 1; t <= lll; t++) alfa += vvv[t] * rho[iii[t]]; if (alfa != 0.0) { len++; ind[len] = m+j; val[len] = alfa; } } } xassert(len <= n); xfree(iii); xfree(vvv); xfree(aB); xfree(a); return len; } /*********************************************************************** * NAME * * glp_transform_col - transform explicitly specified column * * SYNOPSIS * * int glp_transform_col(glp_prob *P, int len, int ind[], double val[]); * * DESCRIPTION * * The routine glp_transform_col performs the same operation as the * routine glp_eval_tab_col with exception that the column to be * transformed is specified explicitly as a sparse vector. * * The explicitly specified column may be thought as if it were added * to the original system of equality constraints: * * x[1] = a[1,1]*x[m+1] + ... + a[1,n]*x[m+n] + a[1]*x * x[2] = a[2,1]*x[m+1] + ... + a[2,n]*x[m+n] + a[2]*x (1) * . . . . . . . . . . . . . . . * x[m] = a[m,1]*x[m+1] + ... + a[m,n]*x[m+n] + a[m]*x * * where x[i] are auxiliary variables, x[m+j] are structural variables, * x is a structural variable for the explicitly specified column, a[i] * are constraint coefficients for x. * * On entry row indices and numerical values of non-zero elements of * the column should be stored in locations ind[1], ..., ind[len] and * val[1], ..., val[len], where len is the number of non-zero elements. * * This routine uses the system of equality constraints and the current * basis in order to express the current basic variables through the * structural variable x in (1) (as if the transformed column were added * to the problem object and the variable x were non-basic), i.e. the * resultant column has the form: * * xB[1] = ... + alfa[1]*x * xB[2] = ... + alfa[2]*x (2) * . . . . . . * xB[m] = ... + alfa[m]*x * * where xB are basic (auxiliary and structural) variables, m is the * number of rows in the problem object. * * On exit the routine stores indices and numerical values of non-zero * elements of the resultant column (2) in locations ind[1], ..., * ind[len'] and val[1], ..., val[len'], where 0 <= len' <= m is the * number of non-zero element in the resultant column returned by the * routine. Note that indices (numbers) of basic variables stored in * the array ind correspond to original ordinal numbers of variables: * indices 1 to m mean auxiliary variables and indices m+1 to m+n mean * structural ones. * * RETURNS * * The routine returns len', which is the number of non-zero elements * in the resultant column stored in the arrays ind and val. * * BACKGROUND * * The explicitly specified column (1) is transformed in the same way * as any other column of the constraint matrix using the formula: * * alfa = inv(B) * a, (3) * * where alfa is the resultant column computed by the routine. */ int glp_transform_col(glp_prob *P, int len, int ind[], double val[]) { int i, m, t; double *a, *alfa; if (!glp_bf_exists(P)) xerror("glp_transform_col: basis factorization does not exist " "\n"); m = glp_get_num_rows(P); /* unpack the column to be transformed to the array a */ a = xcalloc(1+m, sizeof(double)); for (i = 1; i <= m; i++) a[i] = 0.0; if (!(0 <= len && len <= m)) xerror("glp_transform_col: len = %d; invalid column length\n", len); for (t = 1; t <= len; t++) { i = ind[t]; if (!(1 <= i && i <= m)) xerror("glp_transform_col: ind[%d] = %d; row index out of r" "ange\n", t, i); if (val[t] == 0.0) xerror("glp_transform_col: val[%d] = 0; zero coefficient no" "t allowed\n", t); if (a[i] != 0.0) xerror("glp_transform_col: ind[%d] = %d; duplicate row indi" "ces not allowed\n", t, i); a[i] = val[t]; } /* solve the system B*a = alfa to compute the vector alfa */ alfa = a, glp_ftran(P, alfa); /* store resultant coefficients */ len = 0; for (i = 1; i <= m; i++) { if (alfa[i] != 0.0) { len++; ind[len] = glp_get_bhead(P, i); val[len] = alfa[i]; } } xfree(a); return len; } /*********************************************************************** * NAME * * glp_prim_rtest - perform primal ratio test * * SYNOPSIS * * int glp_prim_rtest(glp_prob *P, int len, const int ind[], * const double val[], int dir, double eps); * * DESCRIPTION * * The routine glp_prim_rtest performs the primal ratio test using an * explicitly specified column of the simplex table. * * The current basic solution associated with the LP problem object * must be primal feasible. * * The explicitly specified column of the simplex table shows how the * basic variables xB depend on some non-basic variable x (which is not * necessarily presented in the problem object): * * xB[1] = ... + alfa[1] * x + ... * xB[2] = ... + alfa[2] * x + ... (*) * . . . . . . . . * xB[m] = ... + alfa[m] * x + ... * * The column (*) is specifed on entry to the routine using the sparse * format. Ordinal numbers of basic variables xB[i] should be placed in * locations ind[1], ..., ind[len], where ordinal number 1 to m denote * auxiliary variables, and ordinal numbers m+1 to m+n denote structural * variables. The corresponding non-zero coefficients alfa[i] should be * placed in locations val[1], ..., val[len]. The arrays ind and val are * not changed on exit. * * The parameter dir specifies direction in which the variable x changes * on entering the basis: +1 means increasing, -1 means decreasing. * * The parameter eps is an absolute tolerance (small positive number) * used by the routine to skip small alfa[j] of the row (*). * * The routine determines which basic variable (among specified in * ind[1], ..., ind[len]) should leave the basis in order to keep primal * feasibility. * * RETURNS * * The routine glp_prim_rtest returns the index piv in the arrays ind * and val corresponding to the pivot element chosen, 1 <= piv <= len. * If the adjacent basic solution is primal unbounded and therefore the * choice cannot be made, the routine returns zero. * * COMMENTS * * If the non-basic variable x is presented in the LP problem object, * the column (*) can be computed with the routine glp_eval_tab_col; * otherwise it can be computed with the routine glp_transform_col. */ int glp_prim_rtest(glp_prob *P, int len, const int ind[], const double val[], int dir, double eps) { int k, m, n, piv, t, type, stat; double alfa, big, beta, lb, ub, temp, teta; if (glp_get_prim_stat(P) != GLP_FEAS) xerror("glp_prim_rtest: basic solution is not primal feasible " "\n"); if (!(dir == +1 || dir == -1)) xerror("glp_prim_rtest: dir = %d; invalid parameter\n", dir); if (!(0.0 < eps && eps < 1.0)) xerror("glp_prim_rtest: eps = %g; invalid parameter\n", eps); m = glp_get_num_rows(P); n = glp_get_num_cols(P); /* initial settings */ piv = 0, teta = DBL_MAX, big = 0.0; /* walk through the entries of the specified column */ for (t = 1; t <= len; t++) { /* get the ordinal number of basic variable */ k = ind[t]; if (!(1 <= k && k <= m+n)) xerror("glp_prim_rtest: ind[%d] = %d; variable number out o" "f range\n", t, k); /* determine type, bounds, status and primal value of basic variable xB[i] = x[k] in the current basic solution */ if (k <= m) { type = glp_get_row_type(P, k); lb = glp_get_row_lb(P, k); ub = glp_get_row_ub(P, k); stat = glp_get_row_stat(P, k); beta = glp_get_row_prim(P, k); } else { type = glp_get_col_type(P, k-m); lb = glp_get_col_lb(P, k-m); ub = glp_get_col_ub(P, k-m); stat = glp_get_col_stat(P, k-m); beta = glp_get_col_prim(P, k-m); } if (stat != GLP_BS) xerror("glp_prim_rtest: ind[%d] = %d; non-basic variable no" "t allowed\n", t, k); /* determine influence coefficient at basic variable xB[i] in the explicitly specified column and turn to the case of increasing the variable x in order to simplify the program logic */ alfa = (dir > 0 ? + val[t] : - val[t]); /* analyze main cases */ if (type == GLP_FR) { /* xB[i] is free variable */ continue; } else if (type == GLP_LO) lo: { /* xB[i] has an lower bound */ if (alfa > - eps) continue; temp = (lb - beta) / alfa; } else if (type == GLP_UP) up: { /* xB[i] has an upper bound */ if (alfa < + eps) continue; temp = (ub - beta) / alfa; } else if (type == GLP_DB) { /* xB[i] has both lower and upper bounds */ if (alfa < 0.0) goto lo; else goto up; } else if (type == GLP_FX) { /* xB[i] is fixed variable */ if (- eps < alfa && alfa < + eps) continue; temp = 0.0; } else xassert(type != type); /* if the value of the variable xB[i] violates its lower or upper bound (slightly, because the current basis is assumed to be primal feasible), temp is negative; we can think this happens due to round-off errors and the value is exactly on the bound; this allows replacing temp by zero */ if (temp < 0.0) temp = 0.0; /* apply the minimal ratio test */ if (teta > temp || teta == temp && big < fabs(alfa)) piv = t, teta = temp, big = fabs(alfa); } /* return index of the pivot element chosen */ return piv; } /*********************************************************************** * NAME * * glp_dual_rtest - perform dual ratio test * * SYNOPSIS * * int glp_dual_rtest(glp_prob *P, int len, const int ind[], * const double val[], int dir, double eps); * * DESCRIPTION * * The routine glp_dual_rtest performs the dual ratio test using an * explicitly specified row of the simplex table. * * The current basic solution associated with the LP problem object * must be dual feasible. * * The explicitly specified row of the simplex table is a linear form * that shows how some basic variable x (which is not necessarily * presented in the problem object) depends on non-basic variables xN: * * x = alfa[1] * xN[1] + alfa[2] * xN[2] + ... + alfa[n] * xN[n]. (*) * * The row (*) is specified on entry to the routine using the sparse * format. Ordinal numbers of non-basic variables xN[j] should be placed * in locations ind[1], ..., ind[len], where ordinal numbers 1 to m * denote auxiliary variables, and ordinal numbers m+1 to m+n denote * structural variables. The corresponding non-zero coefficients alfa[j] * should be placed in locations val[1], ..., val[len]. The arrays ind * and val are not changed on exit. * * The parameter dir specifies direction in which the variable x changes * on leaving the basis: +1 means that x goes to its lower bound, and -1 * means that x goes to its upper bound. * * The parameter eps is an absolute tolerance (small positive number) * used by the routine to skip small alfa[j] of the row (*). * * The routine determines which non-basic variable (among specified in * ind[1], ..., ind[len]) should enter the basis in order to keep dual * feasibility. * * RETURNS * * The routine glp_dual_rtest returns the index piv in the arrays ind * and val corresponding to the pivot element chosen, 1 <= piv <= len. * If the adjacent basic solution is dual unbounded and therefore the * choice cannot be made, the routine returns zero. * * COMMENTS * * If the basic variable x is presented in the LP problem object, the * row (*) can be computed with the routine glp_eval_tab_row; otherwise * it can be computed with the routine glp_transform_row. */ int glp_dual_rtest(glp_prob *P, int len, const int ind[], const double val[], int dir, double eps) { int k, m, n, piv, t, stat; double alfa, big, cost, obj, temp, teta; if (glp_get_dual_stat(P) != GLP_FEAS) xerror("glp_dual_rtest: basic solution is not dual feasible\n") ; if (!(dir == +1 || dir == -1)) xerror("glp_dual_rtest: dir = %d; invalid parameter\n", dir); if (!(0.0 < eps && eps < 1.0)) xerror("glp_dual_rtest: eps = %g; invalid parameter\n", eps); m = glp_get_num_rows(P); n = glp_get_num_cols(P); /* take into account optimization direction */ obj = (glp_get_obj_dir(P) == GLP_MIN ? +1.0 : -1.0); /* initial settings */ piv = 0, teta = DBL_MAX, big = 0.0; /* walk through the entries of the specified row */ for (t = 1; t <= len; t++) { /* get ordinal number of non-basic variable */ k = ind[t]; if (!(1 <= k && k <= m+n)) xerror("glp_dual_rtest: ind[%d] = %d; variable number out o" "f range\n", t, k); /* determine status and reduced cost of non-basic variable x[k] = xN[j] in the current basic solution */ if (k <= m) { stat = glp_get_row_stat(P, k); cost = glp_get_row_dual(P, k); } else { stat = glp_get_col_stat(P, k-m); cost = glp_get_col_dual(P, k-m); } if (stat == GLP_BS) xerror("glp_dual_rtest: ind[%d] = %d; basic variable not al" "lowed\n", t, k); /* determine influence coefficient at non-basic variable xN[j] in the explicitly specified row and turn to the case of increasing the variable x in order to simplify the program logic */ alfa = (dir > 0 ? + val[t] : - val[t]); /* analyze main cases */ if (stat == GLP_NL) { /* xN[j] is on its lower bound */ if (alfa < + eps) continue; temp = (obj * cost) / alfa; } else if (stat == GLP_NU) { /* xN[j] is on its upper bound */ if (alfa > - eps) continue; temp = (obj * cost) / alfa; } else if (stat == GLP_NF) { /* xN[j] is non-basic free variable */ if (- eps < alfa && alfa < + eps) continue; temp = 0.0; } else if (stat == GLP_NS) { /* xN[j] is non-basic fixed variable */ continue; } else xassert(stat != stat); /* if the reduced cost of the variable xN[j] violates its zero bound (slightly, because the current basis is assumed to be dual feasible), temp is negative; we can think this happens due to round-off errors and the reduced cost is exact zero; this allows replacing temp by zero */ if (temp < 0.0) temp = 0.0; /* apply the minimal ratio test */ if (teta > temp || teta == temp && big < fabs(alfa)) piv = t, teta = temp, big = fabs(alfa); } /* return index of the pivot element chosen */ return piv; } /*********************************************************************** * NAME * * glp_analyze_row - simulate one iteration of dual simplex method * * SYNOPSIS * * int glp_analyze_row(glp_prob *P, int len, const int ind[], * const double val[], int type, double rhs, double eps, int *piv, * double *x, double *dx, double *y, double *dy, double *dz); * * DESCRIPTION * * Let the current basis be optimal or dual feasible, and there be * specified a row (constraint), which is violated by the current basic * solution. The routine glp_analyze_row simulates one iteration of the * dual simplex method to determine some information on the adjacent * basis (see below), where the specified row becomes active constraint * (i.e. its auxiliary variable becomes non-basic). * * The current basic solution associated with the problem object passed * to the routine must be dual feasible, and its primal components must * be defined. * * The row to be analyzed must be previously transformed either with * the routine glp_eval_tab_row (if the row is in the problem object) * or with the routine glp_transform_row (if the row is external, i.e. * not in the problem object). This is needed to express the row only * through (auxiliary and structural) variables, which are non-basic in * the current basis: * * y = alfa[1] * xN[1] + alfa[2] * xN[2] + ... + alfa[n] * xN[n], * * where y is an auxiliary variable of the row, alfa[j] is an influence * coefficient, xN[j] is a non-basic variable. * * The row is passed to the routine in sparse format. Ordinal numbers * of non-basic variables are stored in locations ind[1], ..., ind[len], * where numbers 1 to m denote auxiliary variables while numbers m+1 to * m+n denote structural variables. Corresponding non-zero coefficients * alfa[j] are stored in locations val[1], ..., val[len]. The arrays * ind and val are ot changed on exit. * * The parameters type and rhs specify the row type and its right-hand * side as follows: * * type = GLP_LO: y = sum alfa[j] * xN[j] >= rhs * * type = GLP_UP: y = sum alfa[j] * xN[j] <= rhs * * The parameter eps is an absolute tolerance (small positive number) * used by the routine to skip small coefficients alfa[j] on performing * the dual ratio test. * * If the operation was successful, the routine stores the following * information to corresponding location (if some parameter is NULL, * its value is not stored): * * piv index in the array ind and val, 1 <= piv <= len, determining * the non-basic variable, which would enter the adjacent basis; * * x value of the non-basic variable in the current basis; * * dx difference between values of the non-basic variable in the * adjacent and current bases, dx = x.new - x.old; * * y value of the row (i.e. of its auxiliary variable) in the * current basis; * * dy difference between values of the row in the adjacent and * current bases, dy = y.new - y.old; * * dz difference between values of the objective function in the * adjacent and current bases, dz = z.new - z.old. Note that in * case of minimization dz >= 0, and in case of maximization * dz <= 0, i.e. in the adjacent basis the objective function * always gets worse (degrades). */ int _glp_analyze_row(glp_prob *P, int len, const int ind[], const double val[], int type, double rhs, double eps, int *_piv, double *_x, double *_dx, double *_y, double *_dy, double *_dz) { int t, k, dir, piv, ret = 0; double x, dx, y, dy, dz; if (P->pbs_stat == GLP_UNDEF) xerror("glp_analyze_row: primal basic solution components are " "undefined\n"); if (P->dbs_stat != GLP_FEAS) xerror("glp_analyze_row: basic solution is not dual feasible\n" ); /* compute the row value y = sum alfa[j] * xN[j] in the current basis */ if (!(0 <= len && len <= P->n)) xerror("glp_analyze_row: len = %d; invalid row length\n", len); y = 0.0; for (t = 1; t <= len; t++) { /* determine value of x[k] = xN[j] in the current basis */ k = ind[t]; if (!(1 <= k && k <= P->m+P->n)) xerror("glp_analyze_row: ind[%d] = %d; row/column index out" " of range\n", t, k); if (k <= P->m) { /* x[k] is auxiliary variable */ if (P->row[k]->stat == GLP_BS) xerror("glp_analyze_row: ind[%d] = %d; basic auxiliary v" "ariable is not allowed\n", t, k); x = P->row[k]->prim; } else { /* x[k] is structural variable */ if (P->col[k-P->m]->stat == GLP_BS) xerror("glp_analyze_row: ind[%d] = %d; basic structural " "variable is not allowed\n", t, k); x = P->col[k-P->m]->prim; } y += val[t] * x; } /* check if the row is primal infeasible in the current basis, i.e. the constraint is violated at the current point */ if (type == GLP_LO) { if (y >= rhs) { /* the constraint is not violated */ ret = 1; goto done; } /* in the adjacent basis y goes to its lower bound */ dir = +1; } else if (type == GLP_UP) { if (y <= rhs) { /* the constraint is not violated */ ret = 1; goto done; } /* in the adjacent basis y goes to its upper bound */ dir = -1; } else xerror("glp_analyze_row: type = %d; invalid parameter\n", type); /* compute dy = y.new - y.old */ dy = rhs - y; /* perform dual ratio test to determine which non-basic variable should enter the adjacent basis to keep it dual feasible */ piv = glp_dual_rtest(P, len, ind, val, dir, eps); if (piv == 0) { /* no dual feasible adjacent basis exists */ ret = 2; goto done; } /* non-basic variable x[k] = xN[j] should enter the basis */ k = ind[piv]; xassert(1 <= k && k <= P->m+P->n); /* determine its value in the current basis */ if (k <= P->m) x = P->row[k]->prim; else x = P->col[k-P->m]->prim; /* compute dx = x.new - x.old = dy / alfa[j] */ xassert(val[piv] != 0.0); dx = dy / val[piv]; /* compute dz = z.new - z.old = d[j] * dx, where d[j] is reduced cost of xN[j] in the current basis */ if (k <= P->m) dz = P->row[k]->dual * dx; else dz = P->col[k-P->m]->dual * dx; /* store the analysis results */ if (_piv != NULL) *_piv = piv; if (_x != NULL) *_x = x; if (_dx != NULL) *_dx = dx; if (_y != NULL) *_y = y; if (_dy != NULL) *_dy = dy; if (_dz != NULL) *_dz = dz; done: return ret; } #if 0 int main(void) { /* example program for the routine glp_analyze_row */ glp_prob *P; glp_smcp parm; int i, k, len, piv, ret, ind[1+100]; double rhs, x, dx, y, dy, dz, val[1+100]; P = glp_create_prob(); /* read plan.mps (see glpk/examples) */ ret = glp_read_mps(P, GLP_MPS_DECK, NULL, "plan.mps"); glp_assert(ret == 0); /* and solve it to optimality */ ret = glp_simplex(P, NULL); glp_assert(ret == 0); glp_assert(glp_get_status(P) == GLP_OPT); /* the optimal objective value is 296.217 */ /* we would like to know what happens if we would add a new row (constraint) to plan.mps: .01 * bin1 + .01 * bin2 + .02 * bin4 + .02 * bin5 <= 12 */ /* first, we specify this new row */ glp_create_index(P); len = 0; ind[++len] = glp_find_col(P, "BIN1"), val[len] = .01; ind[++len] = glp_find_col(P, "BIN2"), val[len] = .01; ind[++len] = glp_find_col(P, "BIN4"), val[len] = .02; ind[++len] = glp_find_col(P, "BIN5"), val[len] = .02; rhs = 12; /* then we can compute value of the row (i.e. of its auxiliary variable) in the current basis to see if the constraint is violated */ y = 0.0; for (k = 1; k <= len; k++) y += val[k] * glp_get_col_prim(P, ind[k]); glp_printf("y = %g\n", y); /* this prints y = 15.1372, so the constraint is violated, since we require that y <= rhs = 12 */ /* now we transform the row to express it only through non-basic (auxiliary and artificial) variables */ len = glp_transform_row(P, len, ind, val); /* finally, we simulate one step of the dual simplex method to obtain necessary information for the adjacent basis */ ret = _glp_analyze_row(P, len, ind, val, GLP_UP, rhs, 1e-9, &piv, &x, &dx, &y, &dy, &dz); glp_assert(ret == 0); glp_printf("k = %d, x = %g; dx = %g; y = %g; dy = %g; dz = %g\n", ind[piv], x, dx, y, dy, dz); /* this prints dz = 5.64418 and means that in the adjacent basis the objective function would be 296.217 + 5.64418 = 301.861 */ /* now we actually include the row into the problem object; note that the arrays ind and val are clobbered, so we need to build them once again */ len = 0; ind[++len] = glp_find_col(P, "BIN1"), val[len] = .01; ind[++len] = glp_find_col(P, "BIN2"), val[len] = .01; ind[++len] = glp_find_col(P, "BIN4"), val[len] = .02; ind[++len] = glp_find_col(P, "BIN5"), val[len] = .02; rhs = 12; i = glp_add_rows(P, 1); glp_set_row_bnds(P, i, GLP_UP, 0, rhs); glp_set_mat_row(P, i, len, ind, val); /* and perform one dual simplex iteration */ glp_init_smcp(&parm); parm.meth = GLP_DUAL; parm.it_lim = 1; glp_simplex(P, &parm); /* the current objective value is 301.861 */ return 0; } #endif /*********************************************************************** * NAME * * glp_analyze_bound - analyze active bound of non-basic variable * * SYNOPSIS * * void glp_analyze_bound(glp_prob *P, int k, double *limit1, int *var1, * double *limit2, int *var2); * * DESCRIPTION * * The routine glp_analyze_bound analyzes the effect of varying the * active bound of specified non-basic variable. * * The non-basic variable is specified by the parameter k, where * 1 <= k <= m means auxiliary variable of corresponding row while * m+1 <= k <= m+n means structural variable (column). * * Note that the current basic solution must be optimal, and the basis * factorization must exist. * * Results of the analysis have the following meaning. * * value1 is the minimal value of the active bound, at which the basis * still remains primal feasible and thus optimal. -DBL_MAX means that * the active bound has no lower limit. * * var1 is the ordinal number of an auxiliary (1 to m) or structural * (m+1 to n) basic variable, which reaches its bound first and thereby * limits further decreasing the active bound being analyzed. * if value1 = -DBL_MAX, var1 is set to 0. * * value2 is the maximal value of the active bound, at which the basis * still remains primal feasible and thus optimal. +DBL_MAX means that * the active bound has no upper limit. * * var2 is the ordinal number of an auxiliary (1 to m) or structural * (m+1 to n) basic variable, which reaches its bound first and thereby * limits further increasing the active bound being analyzed. * if value2 = +DBL_MAX, var2 is set to 0. */ void glp_analyze_bound(glp_prob *P, int k, double *value1, int *var1, double *value2, int *var2) { GLPROW *row; GLPCOL *col; int m, n, stat, kase, p, len, piv, *ind; double x, new_x, ll, uu, xx, delta, *val; /* sanity checks */ if (P == NULL || P->magic != GLP_PROB_MAGIC) xerror("glp_analyze_bound: P = %p; invalid problem object\n", P); m = P->m, n = P->n; if (!(P->pbs_stat == GLP_FEAS && P->dbs_stat == GLP_FEAS)) xerror("glp_analyze_bound: optimal basic solution required\n"); if (!(m == 0 || P->valid)) xerror("glp_analyze_bound: basis factorization required\n"); if (!(1 <= k && k <= m+n)) xerror("glp_analyze_bound: k = %d; variable number out of rang" "e\n", k); /* retrieve information about the specified non-basic variable x[k] whose active bound is to be analyzed */ if (k <= m) { row = P->row[k]; stat = row->stat; x = row->prim; } else { col = P->col[k-m]; stat = col->stat; x = col->prim; } if (stat == GLP_BS) xerror("glp_analyze_bound: k = %d; basic variable not allowed " "\n", k); /* allocate working arrays */ ind = xcalloc(1+m, sizeof(int)); val = xcalloc(1+m, sizeof(double)); /* compute column of the simplex table corresponding to the non-basic variable x[k] */ len = glp_eval_tab_col(P, k, ind, val); xassert(0 <= len && len <= m); /* perform analysis */ for (kase = -1; kase <= +1; kase += 2) { /* kase < 0 means active bound of x[k] is decreasing; kase > 0 means active bound of x[k] is increasing */ /* use the primal ratio test to determine some basic variable x[p] which reaches its bound first */ piv = glp_prim_rtest(P, len, ind, val, kase, 1e-9); if (piv == 0) { /* nothing limits changing the active bound of x[k] */ p = 0; new_x = (kase < 0 ? -DBL_MAX : +DBL_MAX); goto store; } /* basic variable x[p] limits changing the active bound of x[k]; determine its value in the current basis */ xassert(1 <= piv && piv <= len); p = ind[piv]; if (p <= m) { row = P->row[p]; ll = glp_get_row_lb(P, row->i); uu = glp_get_row_ub(P, row->i); stat = row->stat; xx = row->prim; } else { col = P->col[p-m]; ll = glp_get_col_lb(P, col->j); uu = glp_get_col_ub(P, col->j); stat = col->stat; xx = col->prim; } xassert(stat == GLP_BS); /* determine delta x[p] = bound of x[p] - value of x[p] */ if (kase < 0 && val[piv] > 0.0 || kase > 0 && val[piv] < 0.0) { /* delta x[p] < 0, so x[p] goes toward its lower bound */ xassert(ll != -DBL_MAX); delta = ll - xx; } else { /* delta x[p] > 0, so x[p] goes toward its upper bound */ xassert(uu != +DBL_MAX); delta = uu - xx; } /* delta x[p] = alfa[p,k] * delta x[k], so new x[k] = x[k] + delta x[k] = x[k] + delta x[p] / alfa[p,k] is the value of x[k] in the adjacent basis */ xassert(val[piv] != 0.0); new_x = x + delta / val[piv]; store: /* store analysis results */ if (kase < 0) { if (value1 != NULL) *value1 = new_x; if (var1 != NULL) *var1 = p; } else { if (value2 != NULL) *value2 = new_x; if (var2 != NULL) *var2 = p; } } /* free working arrays */ xfree(ind); xfree(val); return; } /*********************************************************************** * NAME * * glp_analyze_coef - analyze objective coefficient at basic variable * * SYNOPSIS * * void glp_analyze_coef(glp_prob *P, int k, double *coef1, int *var1, * double *value1, double *coef2, int *var2, double *value2); * * DESCRIPTION * * The routine glp_analyze_coef analyzes the effect of varying the * objective coefficient at specified basic variable. * * The basic variable is specified by the parameter k, where * 1 <= k <= m means auxiliary variable of corresponding row while * m+1 <= k <= m+n means structural variable (column). * * Note that the current basic solution must be optimal, and the basis * factorization must exist. * * Results of the analysis have the following meaning. * * coef1 is the minimal value of the objective coefficient, at which * the basis still remains dual feasible and thus optimal. -DBL_MAX * means that the objective coefficient has no lower limit. * * var1 is the ordinal number of an auxiliary (1 to m) or structural * (m+1 to n) non-basic variable, whose reduced cost reaches its zero * bound first and thereby limits further decreasing the objective * coefficient being analyzed. If coef1 = -DBL_MAX, var1 is set to 0. * * value1 is value of the basic variable being analyzed in an adjacent * basis, which is defined as follows. Let the objective coefficient * reaches its minimal value (coef1) and continues decreasing. Then the * reduced cost of the limiting non-basic variable (var1) becomes dual * infeasible and the current basis becomes non-optimal that forces the * limiting non-basic variable to enter the basis replacing there some * basic variable that leaves the basis to keep primal feasibility. * Should note that on determining the adjacent basis current bounds * of the basic variable being analyzed are ignored as if it were free * (unbounded) variable, so it cannot leave the basis. It may happen * that no dual feasible adjacent basis exists, in which case value1 is * set to -DBL_MAX or +DBL_MAX. * * coef2 is the maximal value of the objective coefficient, at which * the basis still remains dual feasible and thus optimal. +DBL_MAX * means that the objective coefficient has no upper limit. * * var2 is the ordinal number of an auxiliary (1 to m) or structural * (m+1 to n) non-basic variable, whose reduced cost reaches its zero * bound first and thereby limits further increasing the objective * coefficient being analyzed. If coef2 = +DBL_MAX, var2 is set to 0. * * value2 is value of the basic variable being analyzed in an adjacent * basis, which is defined exactly in the same way as value1 above with * exception that now the objective coefficient is increasing. */ void glp_analyze_coef(glp_prob *P, int k, double *coef1, int *var1, double *value1, double *coef2, int *var2, double *value2) { GLPROW *row; GLPCOL *col; int m, n, type, stat, kase, p, q, dir, clen, cpiv, rlen, rpiv, *cind, *rind; double lb, ub, coef, x, lim_coef, new_x, d, delta, ll, uu, xx, *rval, *cval; /* sanity checks */ if (P == NULL || P->magic != GLP_PROB_MAGIC) xerror("glp_analyze_coef: P = %p; invalid problem object\n", P); m = P->m, n = P->n; if (!(P->pbs_stat == GLP_FEAS && P->dbs_stat == GLP_FEAS)) xerror("glp_analyze_coef: optimal basic solution required\n"); if (!(m == 0 || P->valid)) xerror("glp_analyze_coef: basis factorization required\n"); if (!(1 <= k && k <= m+n)) xerror("glp_analyze_coef: k = %d; variable number out of range" "\n", k); /* retrieve information about the specified basic variable x[k] whose objective coefficient c[k] is to be analyzed */ if (k <= m) { row = P->row[k]; type = row->type; lb = row->lb; ub = row->ub; coef = 0.0; stat = row->stat; x = row->prim; } else { col = P->col[k-m]; type = col->type; lb = col->lb; ub = col->ub; coef = col->coef; stat = col->stat; x = col->prim; } if (stat != GLP_BS) xerror("glp_analyze_coef: k = %d; non-basic variable not allow" "ed\n", k); /* allocate working arrays */ cind = xcalloc(1+m, sizeof(int)); cval = xcalloc(1+m, sizeof(double)); rind = xcalloc(1+n, sizeof(int)); rval = xcalloc(1+n, sizeof(double)); /* compute row of the simplex table corresponding to the basic variable x[k] */ rlen = glp_eval_tab_row(P, k, rind, rval); xassert(0 <= rlen && rlen <= n); /* perform analysis */ for (kase = -1; kase <= +1; kase += 2) { /* kase < 0 means objective coefficient c[k] is decreasing; kase > 0 means objective coefficient c[k] is increasing */ /* note that decreasing c[k] is equivalent to increasing dual variable lambda[k] and vice versa; we need to correctly set the dir flag as required by the routine glp_dual_rtest */ if (P->dir == GLP_MIN) dir = - kase; else if (P->dir == GLP_MAX) dir = + kase; else xassert(P != P); /* use the dual ratio test to determine non-basic variable x[q] whose reduced cost d[q] reaches zero bound first */ rpiv = glp_dual_rtest(P, rlen, rind, rval, dir, 1e-9); if (rpiv == 0) { /* nothing limits changing c[k] */ lim_coef = (kase < 0 ? -DBL_MAX : +DBL_MAX); q = 0; /* x[k] keeps its current value */ new_x = x; goto store; } /* non-basic variable x[q] limits changing coefficient c[k]; determine its status and reduced cost d[k] in the current basis */ xassert(1 <= rpiv && rpiv <= rlen); q = rind[rpiv]; xassert(1 <= q && q <= m+n); if (q <= m) { row = P->row[q]; stat = row->stat; d = row->dual; } else { col = P->col[q-m]; stat = col->stat; d = col->dual; } /* note that delta d[q] = new d[q] - d[q] = - d[q], because new d[q] = 0; delta d[q] = alfa[k,q] * delta c[k], so delta c[k] = delta d[q] / alfa[k,q] = - d[q] / alfa[k,q] */ xassert(rval[rpiv] != 0.0); delta = - d / rval[rpiv]; /* compute new c[k] = c[k] + delta c[k], which is the limiting value of the objective coefficient c[k] */ lim_coef = coef + delta; /* let c[k] continue decreasing/increasing that makes d[q] dual infeasible and forces x[q] to enter the basis; to perform the primal ratio test we need to know in which direction x[q] changes on entering the basis; we determine that analyzing the sign of delta d[q] (see above), since d[q] may be close to zero having wrong sign */ /* let, for simplicity, the problem is minimization */ if (kase < 0 && rval[rpiv] > 0.0 || kase > 0 && rval[rpiv] < 0.0) { /* delta d[q] < 0, so d[q] being non-negative will become negative, so x[q] will increase */ dir = +1; } else { /* delta d[q] > 0, so d[q] being non-positive will become positive, so x[q] will decrease */ dir = -1; } /* if the problem is maximization, correct the direction */ if (P->dir == GLP_MAX) dir = - dir; /* check that we didn't make a silly mistake */ if (dir > 0) xassert(stat == GLP_NL || stat == GLP_NF); else xassert(stat == GLP_NU || stat == GLP_NF); /* compute column of the simplex table corresponding to the non-basic variable x[q] */ clen = glp_eval_tab_col(P, q, cind, cval); /* make x[k] temporarily free (unbounded) */ if (k <= m) { row = P->row[k]; row->type = GLP_FR; row->lb = row->ub = 0.0; } else { col = P->col[k-m]; col->type = GLP_FR; col->lb = col->ub = 0.0; } /* use the primal ratio test to determine some basic variable which leaves the basis */ cpiv = glp_prim_rtest(P, clen, cind, cval, dir, 1e-9); /* restore original bounds of the basic variable x[k] */ if (k <= m) { row = P->row[k]; row->type = type; row->lb = lb, row->ub = ub; } else { col = P->col[k-m]; col->type = type; col->lb = lb, col->ub = ub; } if (cpiv == 0) { /* non-basic variable x[q] can change unlimitedly */ if (dir < 0 && rval[rpiv] > 0.0 || dir > 0 && rval[rpiv] < 0.0) { /* delta x[k] = alfa[k,q] * delta x[q] < 0 */ new_x = -DBL_MAX; } else { /* delta x[k] = alfa[k,q] * delta x[q] > 0 */ new_x = +DBL_MAX; } goto store; } /* some basic variable x[p] limits changing non-basic variable x[q] in the adjacent basis */ xassert(1 <= cpiv && cpiv <= clen); p = cind[cpiv]; xassert(1 <= p && p <= m+n); xassert(p != k); if (p <= m) { row = P->row[p]; xassert(row->stat == GLP_BS); ll = glp_get_row_lb(P, row->i); uu = glp_get_row_ub(P, row->i); xx = row->prim; } else { col = P->col[p-m]; xassert(col->stat == GLP_BS); ll = glp_get_col_lb(P, col->j); uu = glp_get_col_ub(P, col->j); xx = col->prim; } /* determine delta x[p] = new x[p] - x[p] */ if (dir < 0 && cval[cpiv] > 0.0 || dir > 0 && cval[cpiv] < 0.0) { /* delta x[p] < 0, so x[p] goes toward its lower bound */ xassert(ll != -DBL_MAX); delta = ll - xx; } else { /* delta x[p] > 0, so x[p] goes toward its upper bound */ xassert(uu != +DBL_MAX); delta = uu - xx; } /* compute new x[k] = x[k] + alfa[k,q] * delta x[q], where delta x[q] = delta x[p] / alfa[p,q] */ xassert(cval[cpiv] != 0.0); new_x = x + (rval[rpiv] / cval[cpiv]) * delta; store: /* store analysis results */ if (kase < 0) { if (coef1 != NULL) *coef1 = lim_coef; if (var1 != NULL) *var1 = q; if (value1 != NULL) *value1 = new_x; } else { if (coef2 != NULL) *coef2 = lim_coef; if (var2 != NULL) *var2 = q; if (value2 != NULL) *value2 = new_x; } } /* free working arrays */ xfree(cind); xfree(cval); xfree(rind); xfree(rval); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glplpf.h0000644000076500000240000001712213524616144025037 0ustar tamasstaff00000000000000/* glplpf.h (LP basis factorization, Schur complement version) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPLPF_H #define GLPLPF_H #include "glpscf.h" #include "glpluf.h" /*********************************************************************** * The structure LPF defines the factorization of the basis mxm matrix * B, where m is the number of rows in corresponding problem instance. * * This factorization is the following septet: * * [B] = (L0, U0, R, S, C, P, Q), (1) * * and is based on the following main equality: * * ( B F^) ( B0 F ) ( L0 0 ) ( U0 R ) * ( ) = P ( ) Q = P ( ) ( ) Q, (2) * ( G^ H^) ( G H ) ( S I ) ( 0 C ) * * where: * * B is the current basis matrix (not stored); * * F^, G^, H^ are some additional matrices (not stored); * * B0 is some initial basis matrix (not stored); * * F, G, H are some additional matrices (not stored); * * P, Q are permutation matrices (stored in both row- and column-like * formats); * * L0, U0 are some matrices that defines a factorization of the initial * basis matrix B0 = L0 * U0 (stored in an invertable form); * * R is a matrix defined from L0 * R = F, so R = inv(L0) * F (stored in * a column-wise sparse format); * * S is a matrix defined from S * U0 = G, so S = G * inv(U0) (stored in * a row-wise sparse format); * * C is the Schur complement for matrix (B0 F G H). It is defined from * S * R + C = H, so C = H - S * R = H - G * inv(U0) * inv(L0) * F = * = H - G * inv(B0) * F. Matrix C is stored in an invertable form. * * REFERENCES * * 1. M.A.Saunders, "LUSOL: A basis package for constrained optimiza- * tion," SCCM, Stanford University, 2006. * * 2. M.A.Saunders, "Notes 5: Basis Updates," CME 318, Stanford Univer- * sity, Spring 2006. * * 3. M.A.Saunders, "Notes 6: LUSOL---a Basis Factorization Package," * ibid. */ typedef struct LPF LPF; struct LPF { /* LP basis factorization */ int valid; /* the factorization is valid only if this flag is set */ /*--------------------------------------------------------------*/ /* initial basis matrix B0 */ int m0_max; /* maximal value of m0 (increased automatically, if necessary) */ int m0; /* the order of B0 */ LUF *luf; /* LU-factorization of B0 */ /*--------------------------------------------------------------*/ /* current basis matrix B */ int m; /* the order of B */ double *B; /* double B[1+m*m]; */ /* B in dense format stored by rows and used only for debugging; normally this array is not allocated */ /*--------------------------------------------------------------*/ /* augmented matrix (B0 F G H) of the order m0+n */ int n_max; /* maximal number of additional rows and columns */ int n; /* current number of additional rows and columns */ /*--------------------------------------------------------------*/ /* m0xn matrix R in column-wise format */ int *R_ptr; /* int R_ptr[1+n_max]; */ /* R_ptr[j], 1 <= j <= n, is a pointer to j-th column */ int *R_len; /* int R_len[1+n_max]; */ /* R_len[j], 1 <= j <= n, is the length of j-th column */ /*--------------------------------------------------------------*/ /* nxm0 matrix S in row-wise format */ int *S_ptr; /* int S_ptr[1+n_max]; */ /* S_ptr[i], 1 <= i <= n, is a pointer to i-th row */ int *S_len; /* int S_len[1+n_max]; */ /* S_len[i], 1 <= i <= n, is the length of i-th row */ /*--------------------------------------------------------------*/ /* Schur complement C of the order n */ SCF *scf; /* SCF scf[1:n_max]; */ /* factorization of the Schur complement */ /*--------------------------------------------------------------*/ /* matrix P of the order m0+n */ int *P_row; /* int P_row[1+m0_max+n_max]; */ /* P_row[i] = j means that P[i,j] = 1 */ int *P_col; /* int P_col[1+m0_max+n_max]; */ /* P_col[j] = i means that P[i,j] = 1 */ /*--------------------------------------------------------------*/ /* matrix Q of the order m0+n */ int *Q_row; /* int Q_row[1+m0_max+n_max]; */ /* Q_row[i] = j means that Q[i,j] = 1 */ int *Q_col; /* int Q_col[1+m0_max+n_max]; */ /* Q_col[j] = i means that Q[i,j] = 1 */ /*--------------------------------------------------------------*/ /* Sparse Vector Area (SVA) is a set of locations intended to store sparse vectors which represent columns of matrix R and rows of matrix S; each location is a doublet (ind, val), where ind is an index, val is a numerical value of a sparse vector element; in the whole each sparse vector is a set of adjacent locations defined by a pointer to its first element and its length, i.e. the number of its elements */ int v_size; /* the SVA size, in locations; locations are numbered by integers 1, 2, ..., v_size, and location 0 is not used */ int v_ptr; /* pointer to the first available location */ int *v_ind; /* int v_ind[1+v_size]; */ /* v_ind[k], 1 <= k <= v_size, is the index field of location k */ double *v_val; /* double v_val[1+v_size]; */ /* v_val[k], 1 <= k <= v_size, is the value field of location k */ /*--------------------------------------------------------------*/ double *work1; /* double work1[1+m0+n_max]; */ /* working array */ double *work2; /* double work2[1+m0+n_max]; */ /* working array */ }; /* return codes: */ #define LPF_ESING 1 /* singular matrix */ #define LPF_ECOND 2 /* ill-conditioned matrix */ #define LPF_ELIMIT 3 /* update limit reached */ #define lpf_create_it _glp_lpf_create_it LPF *lpf_create_it(void); /* create LP basis factorization */ #define lpf_factorize _glp_lpf_factorize int lpf_factorize(LPF *lpf, int m, const int bh[], int (*col) (void *info, int j, int ind[], double val[]), void *info); /* compute LP basis factorization */ #define lpf_ftran _glp_lpf_ftran void lpf_ftran(LPF *lpf, double x[]); /* perform forward transformation (solve system B*x = b) */ #define lpf_btran _glp_lpf_btran void lpf_btran(LPF *lpf, double x[]); /* perform backward transformation (solve system B'*x = b) */ #define lpf_update_it _glp_lpf_update_it int lpf_update_it(LPF *lpf, int j, int bh, int len, const int ind[], const double val[]); /* update LP basis factorization */ #define lpf_delete_it _glp_lpf_delete_it void lpf_delete_it(LPF *lpf); /* delete LP basis factorization */ #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpapi18.c0000644000076500000240000001033713524616144025174 0ustar tamasstaff00000000000000/* glpapi18.c (maximum clique problem) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wsign-conversion" #endif #include "glpapi.h" #include "glpnet.h" static void set_edge(int nv, unsigned char a[], int i, int j) { int k; xassert(1 <= j && j < i && i <= nv); k = ((i - 1) * (i - 2)) / 2 + (j - 1); a[k / CHAR_BIT] |= (unsigned char)(1 << ((CHAR_BIT - 1) - k % CHAR_BIT)); return; } int glp_wclique_exact(glp_graph *G, int v_wgt, double *sol, int v_set) { /* find maximum weight clique with exact algorithm */ glp_arc *e; int i, j, k, len, x, *w, *ind, ret = 0; unsigned char *a; double s, t; if (v_wgt >= 0 && v_wgt > G->v_size - (int)sizeof(double)) xerror("glp_wclique_exact: v_wgt = %d; invalid parameter\n", v_wgt); if (v_set >= 0 && v_set > G->v_size - (int)sizeof(int)) xerror("glp_wclique_exact: v_set = %d; invalid parameter\n", v_set); if (G->nv == 0) { /* empty graph has only empty clique */ if (sol != NULL) *sol = 0.0; return 0; } /* allocate working arrays */ w = xcalloc(1+G->nv, sizeof(int)); ind = xcalloc(1+G->nv, sizeof(int)); len = G->nv; /* # vertices */ len = len * (len - 1) / 2; /* # entries in lower triangle */ len = (len + (CHAR_BIT - 1)) / CHAR_BIT; /* # bytes needed */ a = xcalloc(len, sizeof(char)); memset(a, 0, len * sizeof(char)); /* determine vertex weights */ s = 0.0; for (i = 1; i <= G->nv; i++) { if (v_wgt >= 0) { memcpy(&t, (char *)G->v[i]->data + v_wgt, sizeof(double)); if (!(0.0 <= t && t <= (double)INT_MAX && t == floor(t))) { ret = GLP_EDATA; goto done; } w[i] = (int)t; } else w[i] = 1; s += (double)w[i]; } if (s > (double)INT_MAX) { ret = GLP_EDATA; goto done; } /* build the adjacency matrix */ for (i = 1; i <= G->nv; i++) { for (e = G->v[i]->in; e != NULL; e = e->h_next) { j = e->tail->i; /* there exists edge (j,i) in the graph */ if (i > j) set_edge(G->nv, a, i, j); } for (e = G->v[i]->out; e != NULL; e = e->t_next) { j = e->head->i; /* there exists edge (i,j) in the graph */ if (i > j) set_edge(G->nv, a, i, j); } } /* find maximum weight clique in the graph */ len = wclique(G->nv, w, a, ind); /* compute the clique weight */ s = 0.0; for (k = 1; k <= len; k++) { i = ind[k]; xassert(1 <= i && i <= G->nv); s += (double)w[i]; } if (sol != NULL) *sol = s; /* mark vertices included in the clique */ if (v_set >= 0) { x = 0; for (i = 1; i <= G->nv; i++) memcpy((char *)G->v[i]->data + v_set, &x, sizeof(int)); x = 1; for (k = 1; k <= len; k++) { i = ind[k]; memcpy((char *)G->v[i]->data + v_set, &x, sizeof(int)); } } done: /* free working arrays */ xfree(w); xfree(ind); xfree(a); return ret; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glplux.c0000644000076500000240000011400013524616144025052 0ustar tamasstaff00000000000000/* glplux.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glplux.h" #define xfault xerror #define dmp_create_poolx(size) dmp_create_pool() /*---------------------------------------------------------------------- // lux_create - create LU-factorization. // // SYNOPSIS // // #include "glplux.h" // LUX *lux_create(int n); // // DESCRIPTION // // The routine lux_create creates LU-factorization data structure for // a matrix of the order n. Initially the factorization corresponds to // the unity matrix (F = V = P = Q = I, so A = I). // // RETURNS // // The routine returns a pointer to the created LU-factorization data // structure, which represents the unity matrix of the order n. */ LUX *lux_create(int n) { LUX *lux; int k; if (n < 1) xfault("lux_create: n = %d; invalid parameter\n", n); lux = xmalloc(sizeof(LUX)); lux->n = n; lux->pool = dmp_create_poolx(sizeof(LUXELM)); lux->F_row = xcalloc(1+n, sizeof(LUXELM *)); lux->F_col = xcalloc(1+n, sizeof(LUXELM *)); lux->V_piv = xcalloc(1+n, sizeof(mpq_t)); lux->V_row = xcalloc(1+n, sizeof(LUXELM *)); lux->V_col = xcalloc(1+n, sizeof(LUXELM *)); lux->P_row = xcalloc(1+n, sizeof(int)); lux->P_col = xcalloc(1+n, sizeof(int)); lux->Q_row = xcalloc(1+n, sizeof(int)); lux->Q_col = xcalloc(1+n, sizeof(int)); for (k = 1; k <= n; k++) { lux->F_row[k] = lux->F_col[k] = NULL; mpq_init(lux->V_piv[k]); mpq_set_si(lux->V_piv[k], 1, 1); lux->V_row[k] = lux->V_col[k] = NULL; lux->P_row[k] = lux->P_col[k] = k; lux->Q_row[k] = lux->Q_col[k] = k; } lux->rank = n; return lux; } /*---------------------------------------------------------------------- // initialize - initialize LU-factorization data structures. // // This routine initializes data structures for subsequent computing // the LU-factorization of a given matrix A, which is specified by the // formal routine col. On exit V = A and F = P = Q = I, where I is the // unity matrix. */ static void initialize(LUX *lux, int (*col)(void *info, int j, int ind[], mpq_t val[]), void *info, LUXWKA *wka) { int n = lux->n; DMP *pool = lux->pool; LUXELM **F_row = lux->F_row; LUXELM **F_col = lux->F_col; mpq_t *V_piv = lux->V_piv; LUXELM **V_row = lux->V_row; LUXELM **V_col = lux->V_col; int *P_row = lux->P_row; int *P_col = lux->P_col; int *Q_row = lux->Q_row; int *Q_col = lux->Q_col; int *R_len = wka->R_len; int *R_head = wka->R_head; int *R_prev = wka->R_prev; int *R_next = wka->R_next; int *C_len = wka->C_len; int *C_head = wka->C_head; int *C_prev = wka->C_prev; int *C_next = wka->C_next; LUXELM *fij, *vij; int i, j, k, len, *ind; mpq_t *val; /* F := I */ for (i = 1; i <= n; i++) { while (F_row[i] != NULL) { fij = F_row[i], F_row[i] = fij->r_next; mpq_clear(fij->val); dmp_free_atom(pool, fij, sizeof(LUXELM)); } } for (j = 1; j <= n; j++) F_col[j] = NULL; /* V := 0 */ for (k = 1; k <= n; k++) mpq_set_si(V_piv[k], 0, 1); for (i = 1; i <= n; i++) { while (V_row[i] != NULL) { vij = V_row[i], V_row[i] = vij->r_next; mpq_clear(vij->val); dmp_free_atom(pool, vij, sizeof(LUXELM)); } } for (j = 1; j <= n; j++) V_col[j] = NULL; /* V := A */ ind = xcalloc(1+n, sizeof(int)); val = xcalloc(1+n, sizeof(mpq_t)); for (k = 1; k <= n; k++) mpq_init(val[k]); for (j = 1; j <= n; j++) { /* obtain j-th column of matrix A */ len = col(info, j, ind, val); if (!(0 <= len && len <= n)) xfault("lux_decomp: j = %d: len = %d; invalid column length" "\n", j, len); /* copy elements of j-th column to matrix V */ for (k = 1; k <= len; k++) { /* get row index of a[i,j] */ i = ind[k]; if (!(1 <= i && i <= n)) xfault("lux_decomp: j = %d: i = %d; row index out of ran" "ge\n", j, i); /* check for duplicate indices */ if (V_row[i] != NULL && V_row[i]->j == j) xfault("lux_decomp: j = %d: i = %d; duplicate row indice" "s not allowed\n", j, i); /* check for zero value */ if (mpq_sgn(val[k]) == 0) xfault("lux_decomp: j = %d: i = %d; zero elements not al" "lowed\n", j, i); /* add new element v[i,j] = a[i,j] to V */ vij = dmp_get_atom(pool, sizeof(LUXELM)); vij->i = i, vij->j = j; mpq_init(vij->val); mpq_set(vij->val, val[k]); vij->r_prev = NULL; vij->r_next = V_row[i]; vij->c_prev = NULL; vij->c_next = V_col[j]; if (vij->r_next != NULL) vij->r_next->r_prev = vij; if (vij->c_next != NULL) vij->c_next->c_prev = vij; V_row[i] = V_col[j] = vij; } } xfree(ind); for (k = 1; k <= n; k++) mpq_clear(val[k]); xfree(val); /* P := Q := I */ for (k = 1; k <= n; k++) P_row[k] = P_col[k] = Q_row[k] = Q_col[k] = k; /* the rank of A and V is not determined yet */ lux->rank = -1; /* initially the entire matrix V is active */ /* determine its row lengths */ for (i = 1; i <= n; i++) { len = 0; for (vij = V_row[i]; vij != NULL; vij = vij->r_next) len++; R_len[i] = len; } /* build linked lists of active rows */ for (len = 0; len <= n; len++) R_head[len] = 0; for (i = 1; i <= n; i++) { len = R_len[i]; R_prev[i] = 0; R_next[i] = R_head[len]; if (R_next[i] != 0) R_prev[R_next[i]] = i; R_head[len] = i; } /* determine its column lengths */ for (j = 1; j <= n; j++) { len = 0; for (vij = V_col[j]; vij != NULL; vij = vij->c_next) len++; C_len[j] = len; } /* build linked lists of active columns */ for (len = 0; len <= n; len++) C_head[len] = 0; for (j = 1; j <= n; j++) { len = C_len[j]; C_prev[j] = 0; C_next[j] = C_head[len]; if (C_next[j] != 0) C_prev[C_next[j]] = j; C_head[len] = j; } return; } /*---------------------------------------------------------------------- // find_pivot - choose a pivot element. // // This routine chooses a pivot element v[p,q] in the active submatrix // of matrix U = P*V*Q. // // It is assumed that on entry the matrix U has the following partially // triangularized form: // // 1 k n // 1 x x x x x x x x x x // . x x x x x x x x x // . . x x x x x x x x // . . . x x x x x x x // k . . . . * * * * * * // . . . . * * * * * * // . . . . * * * * * * // . . . . * * * * * * // . . . . * * * * * * // n . . . . * * * * * * // // where rows and columns k, k+1, ..., n belong to the active submatrix // (elements of the active submatrix are marked by '*'). // // Since the matrix U = P*V*Q is not stored, the routine works with the // matrix V. It is assumed that the row-wise representation corresponds // to the matrix V, but the column-wise representation corresponds to // the active submatrix of the matrix V, i.e. elements of the matrix V, // which does not belong to the active submatrix, are missing from the // column linked lists. It is also assumed that each active row of the // matrix V is in the set R[len], where len is number of non-zeros in // the row, and each active column of the matrix V is in the set C[len], // where len is number of non-zeros in the column (in the latter case // only elements of the active submatrix are counted; such elements are // marked by '*' on the figure above). // // Due to exact arithmetic any non-zero element of the active submatrix // can be chosen as a pivot. However, to keep sparsity of the matrix V // the routine uses Markowitz strategy, trying to choose such element // v[p,q], which has smallest Markowitz cost (nr[p]-1) * (nc[q]-1), // where nr[p] and nc[q] are the number of non-zero elements, resp., in // p-th row and in q-th column of the active submatrix. // // In order to reduce the search, i.e. not to walk through all elements // of the active submatrix, the routine exploits a technique proposed by // I.Duff. This technique is based on using the sets R[len] and C[len] // of active rows and columns. // // On exit the routine returns a pointer to a pivot v[p,q] chosen, or // NULL, if the active submatrix is empty. */ static LUXELM *find_pivot(LUX *lux, LUXWKA *wka) { int n = lux->n; LUXELM **V_row = lux->V_row; LUXELM **V_col = lux->V_col; int *R_len = wka->R_len; int *R_head = wka->R_head; int *R_next = wka->R_next; int *C_len = wka->C_len; int *C_head = wka->C_head; int *C_next = wka->C_next; LUXELM *piv, *some, *vij; int i, j, len, min_len, ncand, piv_lim = 5; double best, cost; /* nothing is chosen so far */ piv = NULL, best = DBL_MAX, ncand = 0; /* if in the active submatrix there is a column that has the only non-zero (column singleton), choose it as a pivot */ j = C_head[1]; if (j != 0) { xassert(C_len[j] == 1); piv = V_col[j]; xassert(piv != NULL && piv->c_next == NULL); goto done; } /* if in the active submatrix there is a row that has the only non-zero (row singleton), choose it as a pivot */ i = R_head[1]; if (i != 0) { xassert(R_len[i] == 1); piv = V_row[i]; xassert(piv != NULL && piv->r_next == NULL); goto done; } /* there are no singletons in the active submatrix; walk through other non-empty rows and columns */ for (len = 2; len <= n; len++) { /* consider active columns having len non-zeros */ for (j = C_head[len]; j != 0; j = C_next[j]) { /* j-th column has len non-zeros */ /* find an element in the row of minimal length */ some = NULL, min_len = INT_MAX; for (vij = V_col[j]; vij != NULL; vij = vij->c_next) { if (min_len > R_len[vij->i]) some = vij, min_len = R_len[vij->i]; /* if Markowitz cost of this element is not greater than (len-1)**2, it can be chosen right now; this heuristic reduces the search and works well in many cases */ if (min_len <= len) { piv = some; goto done; } } /* j-th column has been scanned */ /* the minimal element found is a next pivot candidate */ xassert(some != NULL); ncand++; /* compute its Markowitz cost */ cost = (double)(min_len - 1) * (double)(len - 1); /* choose between the current candidate and this element */ if (cost < best) piv = some, best = cost; /* if piv_lim candidates have been considered, there is a doubt that a much better candidate exists; therefore it is the time to terminate the search */ if (ncand == piv_lim) goto done; } /* now consider active rows having len non-zeros */ for (i = R_head[len]; i != 0; i = R_next[i]) { /* i-th row has len non-zeros */ /* find an element in the column of minimal length */ some = NULL, min_len = INT_MAX; for (vij = V_row[i]; vij != NULL; vij = vij->r_next) { if (min_len > C_len[vij->j]) some = vij, min_len = C_len[vij->j]; /* if Markowitz cost of this element is not greater than (len-1)**2, it can be chosen right now; this heuristic reduces the search and works well in many cases */ if (min_len <= len) { piv = some; goto done; } } /* i-th row has been scanned */ /* the minimal element found is a next pivot candidate */ xassert(some != NULL); ncand++; /* compute its Markowitz cost */ cost = (double)(len - 1) * (double)(min_len - 1); /* choose between the current candidate and this element */ if (cost < best) piv = some, best = cost; /* if piv_lim candidates have been considered, there is a doubt that a much better candidate exists; therefore it is the time to terminate the search */ if (ncand == piv_lim) goto done; } } done: /* bring the pivot v[p,q] to the factorizing routine */ return piv; } /*---------------------------------------------------------------------- // eliminate - perform gaussian elimination. // // This routine performs elementary gaussian transformations in order // to eliminate subdiagonal elements in the k-th column of the matrix // U = P*V*Q using the pivot element u[k,k], where k is the number of // the current elimination step. // // The parameter piv specifies the pivot element v[p,q] = u[k,k]. // // Each time when the routine applies the elementary transformation to // a non-pivot row of the matrix V, it stores the corresponding element // to the matrix F in order to keep the main equality A = F*V. // // The routine assumes that on entry the matrices L = P*F*inv(P) and // U = P*V*Q are the following: // // 1 k 1 k n // 1 1 . . . . . . . . . 1 x x x x x x x x x x // x 1 . . . . . . . . . x x x x x x x x x // x x 1 . . . . . . . . . x x x x x x x x // x x x 1 . . . . . . . . . x x x x x x x // k x x x x 1 . . . . . k . . . . * * * * * * // x x x x _ 1 . . . . . . . . # * * * * * // x x x x _ . 1 . . . . . . . # * * * * * // x x x x _ . . 1 . . . . . . # * * * * * // x x x x _ . . . 1 . . . . . # * * * * * // n x x x x _ . . . . 1 n . . . . # * * * * * // // matrix L matrix U // // where rows and columns of the matrix U with numbers k, k+1, ..., n // form the active submatrix (eliminated elements are marked by '#' and // other elements of the active submatrix are marked by '*'). Note that // each eliminated non-zero element u[i,k] of the matrix U gives the // corresponding element l[i,k] of the matrix L (marked by '_'). // // Actually all operations are performed on the matrix V. Should note // that the row-wise representation corresponds to the matrix V, but the // column-wise representation corresponds to the active submatrix of the // matrix V, i.e. elements of the matrix V, which doesn't belong to the // active submatrix, are missing from the column linked lists. // // Let u[k,k] = v[p,q] be the pivot. In order to eliminate subdiagonal // elements u[i',k] = v[i,q], i' = k+1, k+2, ..., n, the routine applies // the following elementary gaussian transformations: // // (i-th row of V) := (i-th row of V) - f[i,p] * (p-th row of V), // // where f[i,p] = v[i,q] / v[p,q] is a gaussian multiplier. // // Additionally, in order to keep the main equality A = F*V, each time // when the routine applies the transformation to i-th row of the matrix // V, it also adds f[i,p] as a new element to the matrix F. // // IMPORTANT: On entry the working arrays flag and work should contain // zeros. This status is provided by the routine on exit. */ static void eliminate(LUX *lux, LUXWKA *wka, LUXELM *piv, int flag[], mpq_t work[]) { DMP *pool = lux->pool; LUXELM **F_row = lux->F_row; LUXELM **F_col = lux->F_col; mpq_t *V_piv = lux->V_piv; LUXELM **V_row = lux->V_row; LUXELM **V_col = lux->V_col; int *R_len = wka->R_len; int *R_head = wka->R_head; int *R_prev = wka->R_prev; int *R_next = wka->R_next; int *C_len = wka->C_len; int *C_head = wka->C_head; int *C_prev = wka->C_prev; int *C_next = wka->C_next; LUXELM *fip, *vij, *vpj, *viq, *next; mpq_t temp; int i, j, p, q; mpq_init(temp); /* determine row and column indices of the pivot v[p,q] */ xassert(piv != NULL); p = piv->i, q = piv->j; /* remove p-th (pivot) row from the active set; it will never return there */ if (R_prev[p] == 0) R_head[R_len[p]] = R_next[p]; else R_next[R_prev[p]] = R_next[p]; if (R_next[p] == 0) ; else R_prev[R_next[p]] = R_prev[p]; /* remove q-th (pivot) column from the active set; it will never return there */ if (C_prev[q] == 0) C_head[C_len[q]] = C_next[q]; else C_next[C_prev[q]] = C_next[q]; if (C_next[q] == 0) ; else C_prev[C_next[q]] = C_prev[q]; /* store the pivot value in a separate array */ mpq_set(V_piv[p], piv->val); /* remove the pivot from p-th row */ if (piv->r_prev == NULL) V_row[p] = piv->r_next; else piv->r_prev->r_next = piv->r_next; if (piv->r_next == NULL) ; else piv->r_next->r_prev = piv->r_prev; R_len[p]--; /* remove the pivot from q-th column */ if (piv->c_prev == NULL) V_col[q] = piv->c_next; else piv->c_prev->c_next = piv->c_next; if (piv->c_next == NULL) ; else piv->c_next->c_prev = piv->c_prev; C_len[q]--; /* free the space occupied by the pivot */ mpq_clear(piv->val); dmp_free_atom(pool, piv, sizeof(LUXELM)); /* walk through p-th (pivot) row, which already does not contain the pivot v[p,q], and do the following... */ for (vpj = V_row[p]; vpj != NULL; vpj = vpj->r_next) { /* get column index of v[p,j] */ j = vpj->j; /* store v[p,j] in the working array */ flag[j] = 1; mpq_set(work[j], vpj->val); /* remove j-th column from the active set; it will return there later with a new length */ if (C_prev[j] == 0) C_head[C_len[j]] = C_next[j]; else C_next[C_prev[j]] = C_next[j]; if (C_next[j] == 0) ; else C_prev[C_next[j]] = C_prev[j]; /* v[p,j] leaves the active submatrix, so remove it from j-th column; however, v[p,j] is kept in p-th row */ if (vpj->c_prev == NULL) V_col[j] = vpj->c_next; else vpj->c_prev->c_next = vpj->c_next; if (vpj->c_next == NULL) ; else vpj->c_next->c_prev = vpj->c_prev; C_len[j]--; } /* now walk through q-th (pivot) column, which already does not contain the pivot v[p,q], and perform gaussian elimination */ while (V_col[q] != NULL) { /* element v[i,q] has to be eliminated */ viq = V_col[q]; /* get row index of v[i,q] */ i = viq->i; /* remove i-th row from the active set; later it will return there with a new length */ if (R_prev[i] == 0) R_head[R_len[i]] = R_next[i]; else R_next[R_prev[i]] = R_next[i]; if (R_next[i] == 0) ; else R_prev[R_next[i]] = R_prev[i]; /* compute gaussian multiplier f[i,p] = v[i,q] / v[p,q] and store it in the matrix F */ fip = dmp_get_atom(pool, sizeof(LUXELM)); fip->i = i, fip->j = p; mpq_init(fip->val); mpq_div(fip->val, viq->val, V_piv[p]); fip->r_prev = NULL; fip->r_next = F_row[i]; fip->c_prev = NULL; fip->c_next = F_col[p]; if (fip->r_next != NULL) fip->r_next->r_prev = fip; if (fip->c_next != NULL) fip->c_next->c_prev = fip; F_row[i] = F_col[p] = fip; /* v[i,q] has to be eliminated, so remove it from i-th row */ if (viq->r_prev == NULL) V_row[i] = viq->r_next; else viq->r_prev->r_next = viq->r_next; if (viq->r_next == NULL) ; else viq->r_next->r_prev = viq->r_prev; R_len[i]--; /* and also from q-th column */ V_col[q] = viq->c_next; C_len[q]--; /* free the space occupied by v[i,q] */ mpq_clear(viq->val); dmp_free_atom(pool, viq, sizeof(LUXELM)); /* perform gaussian transformation: (i-th row) := (i-th row) - f[i,p] * (p-th row) note that now p-th row, which is in the working array, does not contain the pivot v[p,q], and i-th row does not contain the element v[i,q] to be eliminated */ /* walk through i-th row and transform existing non-zero elements */ for (vij = V_row[i]; vij != NULL; vij = next) { next = vij->r_next; /* get column index of v[i,j] */ j = vij->j; /* v[i,j] := v[i,j] - f[i,p] * v[p,j] */ if (flag[j]) { /* v[p,j] != 0 */ flag[j] = 0; mpq_mul(temp, fip->val, work[j]); mpq_sub(vij->val, vij->val, temp); if (mpq_sgn(vij->val) == 0) { /* new v[i,j] is zero, so remove it from the active submatrix */ /* remove v[i,j] from i-th row */ if (vij->r_prev == NULL) V_row[i] = vij->r_next; else vij->r_prev->r_next = vij->r_next; if (vij->r_next == NULL) ; else vij->r_next->r_prev = vij->r_prev; R_len[i]--; /* remove v[i,j] from j-th column */ if (vij->c_prev == NULL) V_col[j] = vij->c_next; else vij->c_prev->c_next = vij->c_next; if (vij->c_next == NULL) ; else vij->c_next->c_prev = vij->c_prev; C_len[j]--; /* free the space occupied by v[i,j] */ mpq_clear(vij->val); dmp_free_atom(pool, vij, sizeof(LUXELM)); } } } /* now flag is the pattern of the set v[p,*] \ v[i,*] */ /* walk through p-th (pivot) row and create new elements in i-th row, which appear due to fill-in */ for (vpj = V_row[p]; vpj != NULL; vpj = vpj->r_next) { j = vpj->j; if (flag[j]) { /* create new non-zero v[i,j] = 0 - f[i,p] * v[p,j] and add it to i-th row and j-th column */ vij = dmp_get_atom(pool, sizeof(LUXELM)); vij->i = i, vij->j = j; mpq_init(vij->val); mpq_mul(vij->val, fip->val, work[j]); mpq_neg(vij->val, vij->val); vij->r_prev = NULL; vij->r_next = V_row[i]; vij->c_prev = NULL; vij->c_next = V_col[j]; if (vij->r_next != NULL) vij->r_next->r_prev = vij; if (vij->c_next != NULL) vij->c_next->c_prev = vij; V_row[i] = V_col[j] = vij; R_len[i]++, C_len[j]++; } else { /* there is no fill-in, because v[i,j] already exists in i-th row; restore the flag, which was reset before */ flag[j] = 1; } } /* now i-th row has been completely transformed and can return to the active set with a new length */ R_prev[i] = 0; R_next[i] = R_head[R_len[i]]; if (R_next[i] != 0) R_prev[R_next[i]] = i; R_head[R_len[i]] = i; } /* at this point q-th (pivot) column must be empty */ xassert(C_len[q] == 0); /* walk through p-th (pivot) row again and do the following... */ for (vpj = V_row[p]; vpj != NULL; vpj = vpj->r_next) { /* get column index of v[p,j] */ j = vpj->j; /* erase v[p,j] from the working array */ flag[j] = 0; mpq_set_si(work[j], 0, 1); /* now j-th column has been completely transformed, so it can return to the active list with a new length */ C_prev[j] = 0; C_next[j] = C_head[C_len[j]]; if (C_next[j] != 0) C_prev[C_next[j]] = j; C_head[C_len[j]] = j; } mpq_clear(temp); /* return to the factorizing routine */ return; } /*---------------------------------------------------------------------- // lux_decomp - compute LU-factorization. // // SYNOPSIS // // #include "glplux.h" // int lux_decomp(LUX *lux, int (*col)(void *info, int j, int ind[], // mpq_t val[]), void *info); // // DESCRIPTION // // The routine lux_decomp computes LU-factorization of a given square // matrix A. // // The parameter lux specifies LU-factorization data structure built by // means of the routine lux_create. // // The formal routine col specifies the original matrix A. In order to // obtain j-th column of the matrix A the routine lux_decomp calls the // routine col with the parameter j (1 <= j <= n, where n is the order // of A). In response the routine col should store row indices and // numerical values of non-zero elements of j-th column of A to the // locations ind[1], ..., ind[len] and val[1], ..., val[len], resp., // where len is the number of non-zeros in j-th column, which should be // returned on exit. Neiter zero nor duplicate elements are allowed. // // The parameter info is a transit pointer passed to the formal routine // col; it can be used for various purposes. // // RETURNS // // The routine lux_decomp returns the singularity flag. Zero flag means // that the original matrix A is non-singular while non-zero flag means // that A is (exactly!) singular. // // Note that LU-factorization is valid in both cases, however, in case // of singularity some rows of the matrix V (including pivot elements) // will be empty. // // REPAIRING SINGULAR MATRIX // // If the routine lux_decomp returns non-zero flag, it provides all // necessary information that can be used for "repairing" the matrix A, // where "repairing" means replacing linearly dependent columns of the // matrix A by appropriate columns of the unity matrix. This feature is // needed when the routine lux_decomp is used for reinverting the basis // matrix within the simplex method procedure. // // On exit linearly dependent columns of the matrix U have the numbers // rank+1, rank+2, ..., n, where rank is the exact rank of the matrix A // stored by the routine to the member lux->rank. The correspondence // between columns of A and U is the same as between columns of V and U. // Thus, linearly dependent columns of the matrix A have the numbers // Q_col[rank+1], Q_col[rank+2], ..., Q_col[n], where Q_col is an array // representing the permutation matrix Q in column-like format. It is // understood that each j-th linearly dependent column of the matrix U // should be replaced by the unity vector, where all elements are zero // except the unity diagonal element u[j,j]. On the other hand j-th row // of the matrix U corresponds to the row of the matrix V (and therefore // of the matrix A) with the number P_row[j], where P_row is an array // representing the permutation matrix P in row-like format. Thus, each // j-th linearly dependent column of the matrix U should be replaced by // a column of the unity matrix with the number P_row[j]. // // The code that repairs the matrix A may look like follows: // // for (j = rank+1; j <= n; j++) // { replace column Q_col[j] of the matrix A by column P_row[j] of // the unity matrix; // } // // where rank, P_row, and Q_col are members of the structure LUX. */ int lux_decomp(LUX *lux, int (*col)(void *info, int j, int ind[], mpq_t val[]), void *info) { int n = lux->n; LUXELM **V_row = lux->V_row; LUXELM **V_col = lux->V_col; int *P_row = lux->P_row; int *P_col = lux->P_col; int *Q_row = lux->Q_row; int *Q_col = lux->Q_col; LUXELM *piv, *vij; LUXWKA *wka; int i, j, k, p, q, t, *flag; mpq_t *work; /* allocate working area */ wka = xmalloc(sizeof(LUXWKA)); wka->R_len = xcalloc(1+n, sizeof(int)); wka->R_head = xcalloc(1+n, sizeof(int)); wka->R_prev = xcalloc(1+n, sizeof(int)); wka->R_next = xcalloc(1+n, sizeof(int)); wka->C_len = xcalloc(1+n, sizeof(int)); wka->C_head = xcalloc(1+n, sizeof(int)); wka->C_prev = xcalloc(1+n, sizeof(int)); wka->C_next = xcalloc(1+n, sizeof(int)); /* initialize LU-factorization data structures */ initialize(lux, col, info, wka); /* allocate working arrays */ flag = xcalloc(1+n, sizeof(int)); work = xcalloc(1+n, sizeof(mpq_t)); for (k = 1; k <= n; k++) { flag[k] = 0; mpq_init(work[k]); } /* main elimination loop */ for (k = 1; k <= n; k++) { /* choose a pivot element v[p,q] */ piv = find_pivot(lux, wka); if (piv == NULL) { /* no pivot can be chosen, because the active submatrix is empty */ break; } /* determine row and column indices of the pivot element */ p = piv->i, q = piv->j; /* let v[p,q] correspond to u[i',j']; permute k-th and i'-th rows and k-th and j'-th columns of the matrix U = P*V*Q to move the element u[i',j'] to the position u[k,k] */ i = P_col[p], j = Q_row[q]; xassert(k <= i && i <= n && k <= j && j <= n); /* permute k-th and i-th rows of the matrix U */ t = P_row[k]; P_row[i] = t, P_col[t] = i; P_row[k] = p, P_col[p] = k; /* permute k-th and j-th columns of the matrix U */ t = Q_col[k]; Q_col[j] = t, Q_row[t] = j; Q_col[k] = q, Q_row[q] = k; /* eliminate subdiagonal elements of k-th column of the matrix U = P*V*Q using the pivot element u[k,k] = v[p,q] */ eliminate(lux, wka, piv, flag, work); } /* determine the rank of A (and V) */ lux->rank = k - 1; /* free working arrays */ xfree(flag); for (k = 1; k <= n; k++) mpq_clear(work[k]); xfree(work); /* build column lists of the matrix V using its row lists */ for (j = 1; j <= n; j++) xassert(V_col[j] == NULL); for (i = 1; i <= n; i++) { for (vij = V_row[i]; vij != NULL; vij = vij->r_next) { j = vij->j; vij->c_prev = NULL; vij->c_next = V_col[j]; if (vij->c_next != NULL) vij->c_next->c_prev = vij; V_col[j] = vij; } } /* free working area */ xfree(wka->R_len); xfree(wka->R_head); xfree(wka->R_prev); xfree(wka->R_next); xfree(wka->C_len); xfree(wka->C_head); xfree(wka->C_prev); xfree(wka->C_next); xfree(wka); /* return to the calling program */ return (lux->rank < n); } /*---------------------------------------------------------------------- // lux_f_solve - solve system F*x = b or F'*x = b. // // SYNOPSIS // // #include "glplux.h" // void lux_f_solve(LUX *lux, int tr, mpq_t x[]); // // DESCRIPTION // // The routine lux_f_solve solves either the system F*x = b (if the // flag tr is zero) or the system F'*x = b (if the flag tr is non-zero), // where the matrix F is a component of LU-factorization specified by // the parameter lux, F' is a matrix transposed to F. // // On entry the array x should contain elements of the right-hand side // vector b in locations x[1], ..., x[n], where n is the order of the // matrix F. On exit this array will contain elements of the solution // vector x in the same locations. */ void lux_f_solve(LUX *lux, int tr, mpq_t x[]) { int n = lux->n; LUXELM **F_row = lux->F_row; LUXELM **F_col = lux->F_col; int *P_row = lux->P_row; LUXELM *fik, *fkj; int i, j, k; mpq_t temp; mpq_init(temp); if (!tr) { /* solve the system F*x = b */ for (j = 1; j <= n; j++) { k = P_row[j]; if (mpq_sgn(x[k]) != 0) { for (fik = F_col[k]; fik != NULL; fik = fik->c_next) { mpq_mul(temp, fik->val, x[k]); mpq_sub(x[fik->i], x[fik->i], temp); } } } } else { /* solve the system F'*x = b */ for (i = n; i >= 1; i--) { k = P_row[i]; if (mpq_sgn(x[k]) != 0) { for (fkj = F_row[k]; fkj != NULL; fkj = fkj->r_next) { mpq_mul(temp, fkj->val, x[k]); mpq_sub(x[fkj->j], x[fkj->j], temp); } } } } mpq_clear(temp); return; } /*---------------------------------------------------------------------- // lux_v_solve - solve system V*x = b or V'*x = b. // // SYNOPSIS // // #include "glplux.h" // void lux_v_solve(LUX *lux, int tr, double x[]); // // DESCRIPTION // // The routine lux_v_solve solves either the system V*x = b (if the // flag tr is zero) or the system V'*x = b (if the flag tr is non-zero), // where the matrix V is a component of LU-factorization specified by // the parameter lux, V' is a matrix transposed to V. // // On entry the array x should contain elements of the right-hand side // vector b in locations x[1], ..., x[n], where n is the order of the // matrix V. On exit this array will contain elements of the solution // vector x in the same locations. */ void lux_v_solve(LUX *lux, int tr, mpq_t x[]) { int n = lux->n; mpq_t *V_piv = lux->V_piv; LUXELM **V_row = lux->V_row; LUXELM **V_col = lux->V_col; int *P_row = lux->P_row; int *Q_col = lux->Q_col; LUXELM *vij; int i, j, k; mpq_t *b, temp; b = xcalloc(1+n, sizeof(mpq_t)); for (k = 1; k <= n; k++) mpq_init(b[k]), mpq_set(b[k], x[k]), mpq_set_si(x[k], 0, 1); mpq_init(temp); if (!tr) { /* solve the system V*x = b */ for (k = n; k >= 1; k--) { i = P_row[k], j = Q_col[k]; if (mpq_sgn(b[i]) != 0) { mpq_set(x[j], b[i]); mpq_div(x[j], x[j], V_piv[i]); for (vij = V_col[j]; vij != NULL; vij = vij->c_next) { mpq_mul(temp, vij->val, x[j]); mpq_sub(b[vij->i], b[vij->i], temp); } } } } else { /* solve the system V'*x = b */ for (k = 1; k <= n; k++) { i = P_row[k], j = Q_col[k]; if (mpq_sgn(b[j]) != 0) { mpq_set(x[i], b[j]); mpq_div(x[i], x[i], V_piv[i]); for (vij = V_row[i]; vij != NULL; vij = vij->r_next) { mpq_mul(temp, vij->val, x[i]); mpq_sub(b[vij->j], b[vij->j], temp); } } } } for (k = 1; k <= n; k++) mpq_clear(b[k]); mpq_clear(temp); xfree(b); return; } /*---------------------------------------------------------------------- // lux_solve - solve system A*x = b or A'*x = b. // // SYNOPSIS // // #include "glplux.h" // void lux_solve(LUX *lux, int tr, mpq_t x[]); // // DESCRIPTION // // The routine lux_solve solves either the system A*x = b (if the flag // tr is zero) or the system A'*x = b (if the flag tr is non-zero), // where the parameter lux specifies LU-factorization of the matrix A, // A' is a matrix transposed to A. // // On entry the array x should contain elements of the right-hand side // vector b in locations x[1], ..., x[n], where n is the order of the // matrix A. On exit this array will contain elements of the solution // vector x in the same locations. */ void lux_solve(LUX *lux, int tr, mpq_t x[]) { if (lux->rank < lux->n) xfault("lux_solve: LU-factorization has incomplete rank\n"); if (!tr) { /* A = F*V, therefore inv(A) = inv(V)*inv(F) */ lux_f_solve(lux, 0, x); lux_v_solve(lux, 0, x); } else { /* A' = V'*F', therefore inv(A') = inv(F')*inv(V') */ lux_v_solve(lux, 1, x); lux_f_solve(lux, 1, x); } return; } /*---------------------------------------------------------------------- // lux_delete - delete LU-factorization. // // SYNOPSIS // // #include "glplux.h" // void lux_delete(LUX *lux); // // DESCRIPTION // // The routine lux_delete deletes LU-factorization data structure, // which the parameter lux points to, freeing all the memory allocated // to this object. */ void lux_delete(LUX *lux) { int n = lux->n; LUXELM *fij, *vij; int i; for (i = 1; i <= n; i++) { for (fij = lux->F_row[i]; fij != NULL; fij = fij->r_next) mpq_clear(fij->val); mpq_clear(lux->V_piv[i]); for (vij = lux->V_row[i]; vij != NULL; vij = vij->r_next) mpq_clear(vij->val); } dmp_delete_pool(lux->pool); xfree(lux->F_row); xfree(lux->F_col); xfree(lux->V_piv); xfree(lux->V_row); xfree(lux->V_col); xfree(lux->P_row); xfree(lux->P_col); xfree(lux->Q_row); xfree(lux->Q_col); xfree(lux); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpapi16.c0000644000076500000240000002562113524616144025174 0ustar tamasstaff00000000000000/* glpapi16.c (graph and network analysis routines) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glpapi.h" #include "glpnet.h" /*********************************************************************** * NAME * * glp_weak_comp - find all weakly connected components of graph * * SYNOPSIS * * int glp_weak_comp(glp_graph *G, int v_num); * * DESCRIPTION * * The routine glp_weak_comp finds all weakly connected components of * the specified graph. * * The parameter v_num specifies an offset of the field of type int * in the vertex data block, to which the routine stores the number of * a (weakly) connected component containing that vertex. If v_num < 0, * no component numbers are stored. * * The components are numbered in arbitrary order from 1 to nc, where * nc is the total number of components found, 0 <= nc <= |V|. * * RETURNS * * The routine returns nc, the total number of components found. */ int glp_weak_comp(glp_graph *G, int v_num) { glp_vertex *v; glp_arc *a; int f, i, j, nc, nv, pos1, pos2, *prev, *next, *list; if (v_num >= 0 && v_num > G->v_size - (int)sizeof(int)) xerror("glp_weak_comp: v_num = %d; invalid offset\n", v_num); nv = G->nv; if (nv == 0) { nc = 0; goto done; } /* allocate working arrays */ prev = xcalloc(1+nv, sizeof(int)); next = xcalloc(1+nv, sizeof(int)); list = xcalloc(1+nv, sizeof(int)); /* if vertex i is unlabelled, prev[i] is the index of previous unlabelled vertex, and next[i] is the index of next unlabelled vertex; if vertex i is labelled, then prev[i] < 0, and next[i] is the connected component number */ /* initially all vertices are unlabelled */ f = 1; for (i = 1; i <= nv; i++) prev[i] = i - 1, next[i] = i + 1; next[nv] = 0; /* main loop (until all vertices have been labelled) */ nc = 0; while (f != 0) { /* take an unlabelled vertex */ i = f; /* and remove it from the list of unlabelled vertices */ f = next[i]; if (f != 0) prev[f] = 0; /* label the vertex; it begins a new component */ prev[i] = -1, next[i] = ++nc; /* breadth first search */ list[1] = i, pos1 = pos2 = 1; while (pos1 <= pos2) { /* dequeue vertex i */ i = list[pos1++]; /* consider all arcs incoming to vertex i */ for (a = G->v[i]->in; a != NULL; a = a->h_next) { /* vertex j is adjacent to vertex i */ j = a->tail->i; if (prev[j] >= 0) { /* vertex j is unlabelled */ /* remove it from the list of unlabelled vertices */ if (prev[j] == 0) f = next[j]; else next[prev[j]] = next[j]; if (next[j] == 0) ; else prev[next[j]] = prev[j]; /* label the vertex */ prev[j] = -1, next[j] = nc; /* and enqueue it for further consideration */ list[++pos2] = j; } } /* consider all arcs outgoing from vertex i */ for (a = G->v[i]->out; a != NULL; a = a->t_next) { /* vertex j is adjacent to vertex i */ j = a->head->i; if (prev[j] >= 0) { /* vertex j is unlabelled */ /* remove it from the list of unlabelled vertices */ if (prev[j] == 0) f = next[j]; else next[prev[j]] = next[j]; if (next[j] == 0) ; else prev[next[j]] = prev[j]; /* label the vertex */ prev[j] = -1, next[j] = nc; /* and enqueue it for further consideration */ list[++pos2] = j; } } } } /* store component numbers */ if (v_num >= 0) { for (i = 1; i <= nv; i++) { v = G->v[i]; memcpy((char *)v->data + v_num, &next[i], sizeof(int)); } } /* free working arrays */ xfree(prev); xfree(next); xfree(list); done: return nc; } /*********************************************************************** * NAME * * glp_strong_comp - find all strongly connected components of graph * * SYNOPSIS * * int glp_strong_comp(glp_graph *G, int v_num); * * DESCRIPTION * * The routine glp_strong_comp finds all strongly connected components * of the specified graph. * * The parameter v_num specifies an offset of the field of type int * in the vertex data block, to which the routine stores the number of * a strongly connected component containing that vertex. If v_num < 0, * no component numbers are stored. * * The components are numbered in arbitrary order from 1 to nc, where * nc is the total number of components found, 0 <= nc <= |V|. However, * the component numbering has the property that for every arc (i->j) * in the graph the condition num(i) >= num(j) holds. * * RETURNS * * The routine returns nc, the total number of components found. */ int glp_strong_comp(glp_graph *G, int v_num) { glp_vertex *v; glp_arc *a; int i, k, last, n, na, nc, *icn, *ip, *lenr, *ior, *ib, *lowl, *numb, *prev; if (v_num >= 0 && v_num > G->v_size - (int)sizeof(int)) xerror("glp_strong_comp: v_num = %d; invalid offset\n", v_num); n = G->nv; if (n == 0) { nc = 0; goto done; } na = G->na; icn = xcalloc(1+na, sizeof(int)); ip = xcalloc(1+n, sizeof(int)); lenr = xcalloc(1+n, sizeof(int)); ior = xcalloc(1+n, sizeof(int)); ib = xcalloc(1+n, sizeof(int)); lowl = xcalloc(1+n, sizeof(int)); numb = xcalloc(1+n, sizeof(int)); prev = xcalloc(1+n, sizeof(int)); k = 1; for (i = 1; i <= n; i++) { v = G->v[i]; ip[i] = k; for (a = v->out; a != NULL; a = a->t_next) icn[k++] = a->head->i; lenr[i] = k - ip[i]; } xassert(na == k-1); nc = mc13d(n, icn, ip, lenr, ior, ib, lowl, numb, prev); if (v_num >= 0) { xassert(ib[1] == 1); for (k = 1; k <= nc; k++) { last = (k < nc ? ib[k+1] : n+1); xassert(ib[k] < last); for (i = ib[k]; i < last; i++) { v = G->v[ior[i]]; memcpy((char *)v->data + v_num, &k, sizeof(int)); } } } xfree(icn); xfree(ip); xfree(lenr); xfree(ior); xfree(ib); xfree(lowl); xfree(numb); xfree(prev); done: return nc; } /*********************************************************************** * NAME * * glp_top_sort - topological sorting of acyclic digraph * * SYNOPSIS * * int glp_top_sort(glp_graph *G, int v_num); * * DESCRIPTION * * The routine glp_top_sort performs topological sorting of vertices of * the specified acyclic digraph. * * The parameter v_num specifies an offset of the field of type int in * the vertex data block, to which the routine stores the vertex number * assigned. If v_num < 0, vertex numbers are not stored. * * The vertices are numbered from 1 to n, where n is the total number * of vertices in the graph. The vertex numbering has the property that * for every arc (i->j) in the graph the condition num(i) < num(j) * holds. Special case num(i) = 0 means that vertex i is not assigned a * number, because the graph is *not* acyclic. * * RETURNS * * If the graph is acyclic and therefore all the vertices have been * assigned numbers, the routine glp_top_sort returns zero. Otherwise, * if the graph is not acyclic, the routine returns the number of * vertices which have not been numbered, i.e. for which num(i) = 0. */ static int top_sort(glp_graph *G, int num[]) { glp_arc *a; int i, j, cnt, top, *stack, *indeg; /* allocate working arrays */ indeg = xcalloc(1+G->nv, sizeof(int)); stack = xcalloc(1+G->nv, sizeof(int)); /* determine initial indegree of each vertex; push into the stack the vertices having zero indegree */ top = 0; for (i = 1; i <= G->nv; i++) { num[i] = indeg[i] = 0; for (a = G->v[i]->in; a != NULL; a = a->h_next) indeg[i]++; if (indeg[i] == 0) stack[++top] = i; } /* assign numbers to vertices in the sorted order */ cnt = 0; while (top > 0) { /* pull vertex i from the stack */ i = stack[top--]; /* it has zero indegree in the current graph */ xassert(indeg[i] == 0); /* so assign it a next number */ xassert(num[i] == 0); num[i] = ++cnt; /* remove vertex i from the current graph, update indegree of its adjacent vertices, and push into the stack new vertices whose indegree becomes zero */ for (a = G->v[i]->out; a != NULL; a = a->t_next) { j = a->head->i; /* there exists arc (i->j) in the graph */ xassert(indeg[j] > 0); indeg[j]--; if (indeg[j] == 0) stack[++top] = j; } } /* free working arrays */ xfree(indeg); xfree(stack); return G->nv - cnt; } int glp_top_sort(glp_graph *G, int v_num) { glp_vertex *v; int i, cnt, *num; if (v_num >= 0 && v_num > G->v_size - (int)sizeof(int)) xerror("glp_top_sort: v_num = %d; invalid offset\n", v_num); if (G->nv == 0) { cnt = 0; goto done; } num = xcalloc(1+G->nv, sizeof(int)); cnt = top_sort(G, num); if (v_num >= 0) { for (i = 1; i <= G->nv; i++) { v = G->v[i]; memcpy((char *)v->data + v_num, &num[i], sizeof(int)); } } xfree(num); done: return cnt; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glprgr.h0000644000076500000240000000244513524616144025052 0ustar tamasstaff00000000000000/* glprgr.h (raster graphics) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPRGR_H #define GLPRGR_H #define rgr_write_bmp16 _glp_rgr_write_bmp16 int rgr_write_bmp16(const char *fname, int m, int n, const char map[]); /* write 16-color raster image in BMP file format */ #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glplib01.c0000644000076500000240000002257713524616144025172 0ustar tamasstaff00000000000000/* glplib01.c (bignum arithmetic) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glpenv.h" #include "glplib.h" /*********************************************************************** * Two routines below are intended to multiply and divide unsigned * integer numbers of arbitrary precision. * * The routines assume that an unsigned integer number is represented in * the positional numeral system with the base 2^16 = 65536, i.e. each * "digit" of the number is in the range [0, 65535] and represented as * a 16-bit value of the unsigned short type. In other words, a number x * has the following representation: * * n-1 * x = sum d[j] * 65536^j, * j=0 * * where n is the number of places (positions), and d[j] is j-th "digit" * of x, 0 <= d[j] <= 65535. ***********************************************************************/ /*********************************************************************** * NAME * * bigmul - multiply unsigned integer numbers of arbitrary precision * * SYNOPSIS * * #include "glplib.h" * void bigmul(int n, int m, unsigned short x[], unsigned short y[]); * * DESCRIPTION * * The routine bigmul multiplies unsigned integer numbers of arbitrary * precision. * * n is the number of digits of multiplicand, n >= 1; * * m is the number of digits of multiplier, m >= 1; * * x is an array containing digits of the multiplicand in elements * x[m], x[m+1], ..., x[n+m-1]. Contents of x[0], x[1], ..., x[m-1] are * ignored on entry. * * y is an array containing digits of the multiplier in elements y[0], * y[1], ..., y[m-1]. * * On exit digits of the product are stored in elements x[0], x[1], ..., * x[n+m-1]. The array y is not changed. */ void bigmul(int n, int m, unsigned short x[], unsigned short y[]) { int i, j; unsigned int t; xassert(n >= 1); xassert(m >= 1); for (j = 0; j < m; j++) x[j] = 0; for (i = 0; i < n; i++) { if (x[i+m]) { t = 0; for (j = 0; j < m; j++) { t += (unsigned int)x[i+m] * (unsigned int)y[j] + (unsigned int)x[i+j]; x[i+j] = (unsigned short)t; t >>= 16; } x[i+m] = (unsigned short)t; } } return; } /*********************************************************************** * NAME * * bigdiv - divide unsigned integer numbers of arbitrary precision * * SYNOPSIS * * #include "glplib.h" * void bigdiv(int n, int m, unsigned short x[], unsigned short y[]); * * DESCRIPTION * * The routine bigdiv divides one unsigned integer number of arbitrary * precision by another with the algorithm described in [1]. * * n is the difference between the number of digits of dividend and the * number of digits of divisor, n >= 0. * * m is the number of digits of divisor, m >= 1. * * x is an array containing digits of the dividend in elements x[0], * x[1], ..., x[n+m-1]. * * y is an array containing digits of the divisor in elements y[0], * y[1], ..., y[m-1]. The highest digit y[m-1] must be non-zero. * * On exit n+1 digits of the quotient are stored in elements x[m], * x[m+1], ..., x[n+m], and m digits of the remainder are stored in * elements x[0], x[1], ..., x[m-1]. The array y is changed but then * restored. * * REFERENCES * * 1. D. Knuth. The Art of Computer Programming. Vol. 2: Seminumerical * Algorithms. Stanford University, 1969. */ void bigdiv(int n, int m, unsigned short x[], unsigned short y[]) { int i, j; unsigned int t; unsigned short d, q, r; xassert(n >= 0); xassert(m >= 1); xassert(y[m-1] != 0); /* special case when divisor has the only digit */ if (m == 1) { d = 0; for (i = n; i >= 0; i--) { t = ((unsigned int)d << 16) + (unsigned int)x[i]; x[i+1] = (unsigned short)(t / y[0]); d = (unsigned short)(t % y[0]); } x[0] = d; goto done; } /* multiply dividend and divisor by a normalizing coefficient in order to provide the condition y[m-1] >= base / 2 */ d = (unsigned short)(0x10000 / ((unsigned int)y[m-1] + 1)); if (d == 1) x[n+m] = 0; else { t = 0; for (i = 0; i < n+m; i++) { t += (unsigned int)x[i] * (unsigned int)d; x[i] = (unsigned short)t; t >>= 16; } x[n+m] = (unsigned short)t; t = 0; for (j = 0; j < m; j++) { t += (unsigned int)y[j] * (unsigned int)d; y[j] = (unsigned short)t; t >>= 16; } } /* main loop */ for (i = n; i >= 0; i--) { /* estimate and correct the current digit of quotient */ if (x[i+m] < y[m-1]) { t = ((unsigned int)x[i+m] << 16) + (unsigned int)x[i+m-1]; q = (unsigned short)(t / (unsigned int)y[m-1]); r = (unsigned short)(t % (unsigned int)y[m-1]); if (q == 0) goto putq; else goto test; } q = 0; r = x[i+m-1]; decr: q--; /* if q = 0 then q-- = 0xFFFF */ t = (unsigned int)r + (unsigned int)y[m-1]; r = (unsigned short)t; if (t > 0xFFFF) goto msub; test: t = (unsigned int)y[m-2] * (unsigned int)q; if ((unsigned short)(t >> 16) > r) goto decr; if ((unsigned short)(t >> 16) < r) goto msub; if ((unsigned short)t > x[i+m-2]) goto decr; msub: /* now subtract divisor multiplied by the current digit of quotient from the current dividend */ if (q == 0) goto putq; t = 0; for (j = 0; j < m; j++) { t += (unsigned int)y[j] * (unsigned int)q; if (x[i+j] < (unsigned short)t) t += 0x10000; x[i+j] -= (unsigned short)t; t >>= 16; } if (x[i+m] >= (unsigned short)t) goto putq; /* perform correcting addition, because the current digit of quotient is greater by one than its correct value */ q--; t = 0; for (j = 0; j < m; j++) { t += (unsigned int)x[i+j] + (unsigned int)y[j]; x[i+j] = (unsigned short)t; t >>= 16; } putq: /* store the current digit of quotient */ x[i+m] = q; } /* divide divisor and remainder by the normalizing coefficient in order to restore their original values */ if (d > 1) { t = 0; for (i = m-1; i >= 0; i--) { t = (t << 16) + (unsigned int)x[i]; x[i] = (unsigned short)(t / (unsigned int)d); t %= (unsigned int)d; } t = 0; for (j = m-1; j >= 0; j--) { t = (t << 16) + (unsigned int)y[j]; y[j] = (unsigned short)(t / (unsigned int)d); t %= (unsigned int)d; } } done: return; } /**********************************************************************/ #if 0 #include #include #include #include "glprng.h" #define N_MAX 7 /* maximal number of digits in multiplicand */ #define M_MAX 5 /* maximal number of digits in multiplier */ #define N_TEST 1000000 /* number of tests */ int main(void) { RNG *rand; int d, j, n, m, test; unsigned short x[N_MAX], y[M_MAX], z[N_MAX+M_MAX]; rand = rng_create_rand(); for (test = 1; test <= N_TEST; test++) { /* x[0,...,n-1] := multiplicand */ n = 1 + rng_unif_rand(rand, N_MAX-1); assert(1 <= n && n <= N_MAX); for (j = 0; j < n; j++) { d = rng_unif_rand(rand, 65536); assert(0 <= d && d <= 65535); x[j] = (unsigned short)d; } /* y[0,...,m-1] := multiplier */ m = 1 + rng_unif_rand(rand, M_MAX-1); assert(1 <= m && m <= M_MAX); for (j = 0; j < m; j++) { d = rng_unif_rand(rand, 65536); assert(0 <= d && d <= 65535); y[j] = (unsigned short)d; } if (y[m-1] == 0) y[m-1] = 1; /* z[0,...,n+m-1] := x * y */ for (j = 0; j < n; j++) z[m+j] = x[j]; bigmul(n, m, z, y); /* z[0,...,m-1] := z mod y, z[m,...,n+m-1] := z div y */ bigdiv(n, m, z, y); /* z mod y must be 0 */ for (j = 0; j < m; j++) assert(z[j] == 0); /* z div y must be x */ for (j = 0; j < n; j++) assert(z[m+j] == x[j]); } fprintf(stderr, "%d tests successfully passed\n", N_TEST); rng_delete_rand(rand); return 0; } #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpios05.c0000644000076500000240000002373413524616144025216 0ustar tamasstaff00000000000000/* glpios05.c (Gomory's mixed integer cut generator) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wsign-conversion" #endif #include "glpios.h" /*********************************************************************** * NAME * * ios_gmi_gen - generate Gomory's mixed integer cuts. * * SYNOPSIS * * #include "glpios.h" * void ios_gmi_gen(glp_tree *tree, IOSPOOL *pool); * * DESCRIPTION * * The routine ios_gmi_gen generates Gomory's mixed integer cuts for * the current point and adds them to the cut pool. */ #define MAXCUTS 50 /* maximal number of cuts to be generated for one round */ struct worka { /* Gomory's cut generator working area */ int *ind; /* int ind[1+n]; */ double *val; /* double val[1+n]; */ double *phi; /* double phi[1+m+n]; */ }; #define f(x) ((x) - floor(x)) /* compute fractional part of x */ static void gen_cut(glp_tree *tree, struct worka *worka, int j) { /* this routine tries to generate Gomory's mixed integer cut for specified structural variable x[m+j] of integer kind, which is basic and has fractional value in optimal solution to current LP relaxation */ glp_prob *mip = tree->mip; int m = mip->m; int n = mip->n; int *ind = worka->ind; double *val = worka->val; double *phi = worka->phi; int i, k, len, kind, stat; double lb, ub, alfa, beta, ksi, phi1, rhs; /* compute row of the simplex tableau, which (row) corresponds to specified basic variable xB[i] = x[m+j]; see (23) */ len = glp_eval_tab_row(mip, m+j, ind, val); /* determine beta[i], which a value of xB[i] in optimal solution to current LP relaxation; note that this value is the same as if it would be computed with formula (27); it is assumed that beta[i] is fractional enough */ beta = mip->col[j]->prim; /* compute cut coefficients phi and right-hand side rho, which correspond to formula (30); dense format is used, because rows of the simplex tableau is usually dense */ for (k = 1; k <= m+n; k++) phi[k] = 0.0; rhs = f(beta); /* initial value of rho; see (28), (32) */ for (j = 1; j <= len; j++) { /* determine original number of non-basic variable xN[j] */ k = ind[j]; xassert(1 <= k && k <= m+n); /* determine the kind, bounds and current status of xN[j] in optimal solution to LP relaxation */ if (k <= m) { /* auxiliary variable */ GLPROW *row = mip->row[k]; kind = GLP_CV; lb = row->lb; ub = row->ub; stat = row->stat; } else { /* structural variable */ GLPCOL *col = mip->col[k-m]; kind = col->kind; lb = col->lb; ub = col->ub; stat = col->stat; } /* xN[j] cannot be basic */ xassert(stat != GLP_BS); /* determine row coefficient ksi[i,j] at xN[j]; see (23) */ ksi = val[j]; /* if ksi[i,j] is too large in the magnitude, do not generate the cut */ if (fabs(ksi) > 1e+05) goto fini; /* if ksi[i,j] is too small in the magnitude, skip it */ if (fabs(ksi) < 1e-10) goto skip; /* compute row coefficient alfa[i,j] at y[j]; see (26) */ switch (stat) { case GLP_NF: /* xN[j] is free (unbounded) having non-zero ksi[i,j]; do not generate the cut */ goto fini; case GLP_NL: /* xN[j] has active lower bound */ alfa = - ksi; break; case GLP_NU: /* xN[j] has active upper bound */ alfa = + ksi; break; case GLP_NS: /* xN[j] is fixed; skip it */ goto skip; default: xassert(stat != stat); } /* compute cut coefficient phi'[j] at y[j]; see (21), (28) */ switch (kind) { case GLP_IV: /* y[j] is integer */ if (fabs(alfa - floor(alfa + 0.5)) < 1e-10) { /* alfa[i,j] is close to nearest integer; skip it */ goto skip; } else if (f(alfa) <= f(beta)) phi1 = f(alfa); else phi1 = (f(beta) / (1.0 - f(beta))) * (1.0 - f(alfa)); break; case GLP_CV: /* y[j] is continuous */ if (alfa >= 0.0) phi1 = + alfa; else phi1 = (f(beta) / (1.0 - f(beta))) * (- alfa); break; default: xassert(kind != kind); } /* compute cut coefficient phi[j] at xN[j] and update right- hand side rho; see (31), (32) */ switch (stat) { case GLP_NL: /* xN[j] has active lower bound */ phi[k] = + phi1; rhs += phi1 * lb; break; case GLP_NU: /* xN[j] has active upper bound */ phi[k] = - phi1; rhs -= phi1 * ub; break; default: xassert(stat != stat); } skip: ; } /* now the cut has the form sum_k phi[k] * x[k] >= rho, where cut coefficients are stored in the array phi in dense format; x[1,...,m] are auxiliary variables, x[m+1,...,m+n] are struc- tural variables; see (30) */ /* eliminate auxiliary variables in order to express the cut only through structural variables; see (33) */ for (i = 1; i <= m; i++) { GLPROW *row; GLPAIJ *aij; if (fabs(phi[i]) < 1e-10) continue; /* auxiliary variable x[i] has non-zero cut coefficient */ row = mip->row[i]; /* x[i] cannot be fixed */ xassert(row->type != GLP_FX); /* substitute x[i] = sum_j a[i,j] * x[m+j] */ for (aij = row->ptr; aij != NULL; aij = aij->r_next) phi[m+aij->col->j] += phi[i] * aij->val; } /* convert the final cut to sparse format and substitute fixed (structural) variables */ len = 0; for (j = 1; j <= n; j++) { GLPCOL *col; if (fabs(phi[m+j]) < 1e-10) continue; /* structural variable x[m+j] has non-zero cut coefficient */ col = mip->col[j]; if (col->type == GLP_FX) { /* eliminate x[m+j] */ rhs -= phi[m+j] * col->lb; } else { len++; ind[len] = j; val[len] = phi[m+j]; } } if (fabs(rhs) < 1e-12) rhs = 0.0; /* if the cut inequality seems to be badly scaled, reject it to avoid numeric difficulties */ for (k = 1; k <= len; k++) { if (fabs(val[k]) < 1e-03) goto fini; if (fabs(val[k]) > 1e+03) goto fini; } /* add the cut to the cut pool for further consideration */ #if 0 ios_add_cut_row(tree, pool, GLP_RF_GMI, len, ind, val, GLP_LO, rhs); #else glp_ios_add_row(tree, NULL, GLP_RF_GMI, 0, len, ind, val, GLP_LO, rhs); #endif fini: return; } struct var { int j; double f; }; static int fcmp(const void *p1, const void *p2) { const struct var *v1 = p1, *v2 = p2; if (v1->f > v2->f) return -1; if (v1->f < v2->f) return +1; return 0; } void ios_gmi_gen(glp_tree *tree) { /* main routine to generate Gomory's cuts */ glp_prob *mip = tree->mip; int m = mip->m; int n = mip->n; struct var *var; int k, nv, j, size; struct worka _worka, *worka = &_worka; /* allocate working arrays */ var = xcalloc(1+n, sizeof(struct var)); worka->ind = xcalloc(1+n, sizeof(int)); worka->val = xcalloc(1+n, sizeof(double)); worka->phi = xcalloc(1+m+n, sizeof(double)); /* build the list of integer structural variables, which are basic and have fractional value in optimal solution to current LP relaxation */ nv = 0; for (j = 1; j <= n; j++) { GLPCOL *col = mip->col[j]; double frac; if (col->kind != GLP_IV) continue; if (col->type == GLP_FX) continue; if (col->stat != GLP_BS) continue; frac = f(col->prim); if (!(0.05 <= frac && frac <= 0.95)) continue; /* add variable to the list */ nv++, var[nv].j = j, var[nv].f = frac; } /* order the list by descending fractionality */ qsort(&var[1], nv, sizeof(struct var), fcmp); /* try to generate cuts by one for each variable in the list, but not more than MAXCUTS cuts */ size = glp_ios_pool_size(tree); for (k = 1; k <= nv; k++) { if (glp_ios_pool_size(tree) - size >= MAXCUTS) break; gen_cut(tree, worka, var[k].j); } /* free working arrays */ xfree(var); xfree(worka->ind); xfree(worka->val); xfree(worka->phi); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpnet01.c0000644000076500000240000002335013524616144025200 0ustar tamasstaff00000000000000/* glpnet01.c (permutations for zero-free diagonal) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * This code is the result of translation of the Fortran subroutines * MC21A and MC21B associated with the following paper: * * I.S.Duff, Algorithm 575: Permutations for zero-free diagonal, ACM * Trans. on Math. Softw. 7 (1981), 387-390. * * Use of ACM Algorithms is subject to the ACM Software Copyright and * License Agreement. See . * * The translation was made by Andrew Makhorin . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glpnet.h" /*********************************************************************** * NAME * * mc21a - permutations for zero-free diagonal * * SYNOPSIS * * #include "glpnet.h" * int mc21a(int n, const int icn[], const int ip[], const int lenr[], * int iperm[], int pr[], int arp[], int cv[], int out[]); * * DESCRIPTION * * Given the pattern of nonzeros of a sparse matrix, the routine mc21a * attempts to find a permutation of its rows that makes the matrix have * no zeros on its diagonal. * * INPUT PARAMETERS * * n order of matrix. * * icn array containing the column indices of the non-zeros. Those * belonging to a single row must be contiguous but the ordering * of column indices within each row is unimportant and wasted * space between rows is permitted. * * ip ip[i], i = 1,2,...,n, is the position in array icn of the * first column index of a non-zero in row i. * * lenr lenr[i], i = 1,2,...,n, is the number of non-zeros in row i. * * OUTPUT PARAMETER * * iperm contains permutation to make diagonal have the smallest * number of zeros on it. Elements (iperm[i], i), i = 1,2,...,n, * are non-zero at the end of the algorithm unless the matrix is * structurally singular. In this case, (iperm[i], i) will be * zero for n - numnz entries. * * WORKING ARRAYS * * pr working array of length [1+n], where pr[0] is not used. * pr[i] is the previous row to i in the depth first search. * * arp working array of length [1+n], where arp[0] is not used. * arp[i] is one less than the number of non-zeros in row i which * have not been scanned when looking for a cheap assignment. * * cv working array of length [1+n], where cv[0] is not used. * cv[i] is the most recent row extension at which column i was * visited. * * out working array of length [1+n], where out[0] is not used. * out[i] is one less than the number of non-zeros in row i * which have not been scanned during one pass through the main * loop. * * RETURNS * * The routine mc21a returns numnz, the number of non-zeros on diagonal * of permuted matrix. */ int mc21a(int n, const int icn[], const int ip[], const int lenr[], int iperm[], int pr[], int arp[], int cv[], int out[]) { int i, ii, in1, in2, j, j1, jord, k, kk, numnz; /* Initialization of arrays. */ for (i = 1; i <= n; i++) { arp[i] = lenr[i] - 1; cv[i] = iperm[i] = 0; } numnz = 0; /* Main loop. */ /* Each pass round this loop either results in a new assignment or gives a row with no assignment. */ for (jord = 1; jord <= n; jord++) { j = jord; pr[j] = -1; for (k = 1; k <= jord; k++) { /* Look for a cheap assignment. */ in1 = arp[j]; if (in1 >= 0) { in2 = ip[j] + lenr[j] - 1; in1 = in2 - in1; for (ii = in1; ii <= in2; ii++) { i = icn[ii]; if (iperm[i] == 0) goto L110; } /* No cheap assignment in row. */ arp[j] = -1; } /* Begin looking for assignment chain starting with row j.*/ out[j] = lenr[j] - 1; /* Inner loop. Extends chain by one or backtracks. */ for (kk = 1; kk <= jord; kk++) { in1 = out[j]; if (in1 >= 0) { in2 = ip[j] + lenr[j] - 1; in1 = in2 - in1; /* Forward scan. */ for (ii = in1; ii <= in2; ii++) { i = icn[ii]; if (cv[i] != jord) { /* Column i has not yet been accessed during this pass. */ j1 = j; j = iperm[i]; cv[i] = jord; pr[j] = j1; out[j1] = in2 - ii - 1; goto L100; } } } /* Backtracking step. */ j = pr[j]; if (j == -1) goto L130; } L100: ; } L110: /* New assignment is made. */ iperm[i] = j; arp[j] = in2 - ii - 1; numnz++; for (k = 1; k <= jord; k++) { j = pr[j]; if (j == -1) break; ii = ip[j] + lenr[j] - out[j] - 2; i = icn[ii]; iperm[i] = j; } L130: ; } /* If matrix is structurally singular, we now complete the permutation iperm. */ if (numnz < n) { for (i = 1; i <= n; i++) arp[i] = 0; k = 0; for (i = 1; i <= n; i++) { if (iperm[i] == 0) out[++k] = i; else arp[iperm[i]] = i; } k = 0; for (i = 1; i <= n; i++) { if (arp[i] == 0) iperm[out[++k]] = i; } } return numnz; } /**********************************************************************/ #if 0 #include "glplib.h" int sing; void ranmat(int m, int n, int icn[], int iptr[], int nnnp1, int *knum, int iw[]); void fa01bs(int max, int *nrand); int main(void) { /* test program for the routine mc21a */ /* these runs on random matrices cause all possible statements in mc21a to be executed */ int i, iold, j, j1, j2, jj, knum, l, licn, n, nov4, num, numnz; int ip[1+21], icn[1+1000], iperm[1+20], lenr[1+20], iw1[1+80]; licn = 1000; /* run on random matrices of orders 1 through 20 */ for (n = 1; n <= 20; n++) { nov4 = n / 4; if (nov4 < 1) nov4 = 1; L10: fa01bs(nov4, &l); knum = l * n; /* knum is requested number of non-zeros in random matrix */ if (knum > licn) goto L10; /* if sing is false, matrix is guaranteed structurally non-singular */ sing = ((n / 2) * 2 == n); /* call to subroutine to generate random matrix */ ranmat(n, n, icn, ip, n+1, &knum, iw1); /* knum is now actual number of non-zeros in random matrix */ if (knum > licn) goto L10; xprintf("n = %2d; nz = %4d; sing = %d\n", n, knum, sing); /* set up array of row lengths */ for (i = 1; i <= n; i++) lenr[i] = ip[i+1] - ip[i]; /* call to mc21a */ numnz = mc21a(n, icn, ip, lenr, iperm, &iw1[0], &iw1[n], &iw1[n+n], &iw1[n+n+n]); /* testing to see if there are numnz non-zeros on the diagonal of the permuted matrix. */ num = 0; for (i = 1; i <= n; i++) { iold = iperm[i]; j1 = ip[iold]; j2 = j1 + lenr[iold] - 1; if (j2 < j1) continue; for (jj = j1; jj <= j2; jj++) { j = icn[jj]; if (j == i) { num++; break; } } } if (num != numnz) xprintf("Failure in mc21a, numnz = %d instead of %d\n", numnz, num); } return 0; } void ranmat(int m, int n, int icn[], int iptr[], int nnnp1, int *knum, int iw[]) { /* subroutine to generate random matrix */ int i, ii, inum, j, lrow, matnum; inum = (*knum / n) * 2; if (inum > n-1) inum = n-1; matnum = 1; /* each pass through this loop generates a row of the matrix */ for (j = 1; j <= m; j++) { iptr[j] = matnum; if (!(sing || j > n)) icn[matnum++] = j; if (n == 1) continue; for (i = 1; i <= n; i++) iw[i] = 0; if (!sing) iw[j] = 1; fa01bs(inum, &lrow); lrow--; if (lrow == 0) continue; /* lrow off-diagonal non-zeros in row j of the matrix */ for (ii = 1; ii <= lrow; ii++) { for (;;) { fa01bs(n, &i); if (iw[i] != 1) break; } iw[i] = 1; icn[matnum++] = i; } } for (i = m+1; i <= nnnp1; i++) iptr[i] = matnum; *knum = matnum - 1; return; } double g = 1431655765.0; double fa01as(int i) { /* random number generator */ g = fmod(g * 9228907.0, 4294967296.0); if (i >= 0) return g / 4294967296.0; else return 2.0 * g / 4294967296.0 - 1.0; } void fa01bs(int max, int *nrand) { *nrand = (int)(fa01as(1) * (double)max) + 1; return; } #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpk.h0000644000076500000240000016523213524616144024516 0ustar tamasstaff00000000000000/* glpk.h */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPK_H #define GLPK_H #include #include #ifdef __cplusplus extern "C" { #endif /* library version numbers: */ #define GLP_MAJOR_VERSION 4 #define GLP_MINOR_VERSION 45 #ifndef GLP_PROB_DEFINED #define GLP_PROB_DEFINED typedef struct { double _opaque_prob[100]; } glp_prob; /* LP/MIP problem object */ #endif /* optimization direction flag: */ #define GLP_MIN 1 /* minimization */ #define GLP_MAX 2 /* maximization */ /* kind of structural variable: */ #define GLP_CV 1 /* continuous variable */ #define GLP_IV 2 /* integer variable */ #define GLP_BV 3 /* binary variable */ /* type of auxiliary/structural variable: */ #define GLP_FR 1 /* free variable */ #define GLP_LO 2 /* variable with lower bound */ #define GLP_UP 3 /* variable with upper bound */ #define GLP_DB 4 /* double-bounded variable */ #define GLP_FX 5 /* fixed variable */ /* status of auxiliary/structural variable: */ #define GLP_BS 1 /* basic variable */ #define GLP_NL 2 /* non-basic variable on lower bound */ #define GLP_NU 3 /* non-basic variable on upper bound */ #define GLP_NF 4 /* non-basic free variable */ #define GLP_NS 5 /* non-basic fixed variable */ /* scaling options: */ #define GLP_SF_GM 0x01 /* perform geometric mean scaling */ #define GLP_SF_EQ 0x10 /* perform equilibration scaling */ #define GLP_SF_2N 0x20 /* round scale factors to power of two */ #define GLP_SF_SKIP 0x40 /* skip if problem is well scaled */ #define GLP_SF_AUTO 0x80 /* choose scaling options automatically */ /* solution indicator: */ #define GLP_SOL 1 /* basic solution */ #define GLP_IPT 2 /* interior-point solution */ #define GLP_MIP 3 /* mixed integer solution */ /* solution status: */ #define GLP_UNDEF 1 /* solution is undefined */ #define GLP_FEAS 2 /* solution is feasible */ #define GLP_INFEAS 3 /* solution is infeasible */ #define GLP_NOFEAS 4 /* no feasible solution exists */ #define GLP_OPT 5 /* solution is optimal */ #define GLP_UNBND 6 /* solution is unbounded */ typedef struct { /* basis factorization control parameters */ int msg_lev; /* (reserved) */ int type; /* factorization type: */ #define GLP_BF_FT 1 /* LUF + Forrest-Tomlin */ #define GLP_BF_BG 2 /* LUF + Schur compl. + Bartels-Golub */ #define GLP_BF_GR 3 /* LUF + Schur compl. + Givens rotation */ int lu_size; /* luf.sv_size */ double piv_tol; /* luf.piv_tol */ int piv_lim; /* luf.piv_lim */ int suhl; /* luf.suhl */ double eps_tol; /* luf.eps_tol */ double max_gro; /* luf.max_gro */ int nfs_max; /* fhv.hh_max */ double upd_tol; /* fhv.upd_tol */ int nrs_max; /* lpf.n_max */ int rs_size; /* lpf.v_size */ double foo_bar[38]; /* (reserved) */ } glp_bfcp; typedef struct { /* simplex method control parameters */ int msg_lev; /* message level: */ #define GLP_MSG_OFF 0 /* no output */ #define GLP_MSG_ERR 1 /* warning and error messages only */ #define GLP_MSG_ON 2 /* normal output */ #define GLP_MSG_ALL 3 /* full output */ #define GLP_MSG_DBG 4 /* debug output */ int meth; /* simplex method option: */ #define GLP_PRIMAL 1 /* use primal simplex */ #define GLP_DUALP 2 /* use dual; if it fails, use primal */ #define GLP_DUAL 3 /* use dual simplex */ int pricing; /* pricing technique: */ #define GLP_PT_STD 0x11 /* standard (Dantzig rule) */ #define GLP_PT_PSE 0x22 /* projected steepest edge */ int r_test; /* ratio test technique: */ #define GLP_RT_STD 0x11 /* standard (textbook) */ #define GLP_RT_HAR 0x22 /* two-pass Harris' ratio test */ double tol_bnd; /* spx.tol_bnd */ double tol_dj; /* spx.tol_dj */ double tol_piv; /* spx.tol_piv */ double obj_ll; /* spx.obj_ll */ double obj_ul; /* spx.obj_ul */ int it_lim; /* spx.it_lim */ int tm_lim; /* spx.tm_lim (milliseconds) */ int out_frq; /* spx.out_frq */ int out_dly; /* spx.out_dly (milliseconds) */ int presolve; /* enable/disable using LP presolver */ double foo_bar[36]; /* (reserved) */ } glp_smcp; typedef struct { /* interior-point solver control parameters */ int msg_lev; /* message level (see glp_smcp) */ int ord_alg; /* ordering algorithm: */ #define GLP_ORD_NONE 0 /* natural (original) ordering */ #define GLP_ORD_QMD 1 /* quotient minimum degree (QMD) */ #define GLP_ORD_AMD 2 /* approx. minimum degree (AMD) */ #define GLP_ORD_SYMAMD 3 /* approx. minimum degree (SYMAMD) */ double foo_bar[48]; /* (reserved) */ } glp_iptcp; #ifndef GLP_TREE_DEFINED #define GLP_TREE_DEFINED typedef struct { double _opaque_tree[100]; } glp_tree; /* branch-and-bound tree */ #endif typedef struct { /* integer optimizer control parameters */ int msg_lev; /* message level (see glp_smcp) */ int br_tech; /* branching technique: */ #define GLP_BR_FFV 1 /* first fractional variable */ #define GLP_BR_LFV 2 /* last fractional variable */ #define GLP_BR_MFV 3 /* most fractional variable */ #define GLP_BR_DTH 4 /* heuristic by Driebeck and Tomlin */ #define GLP_BR_PCH 5 /* hybrid pseudocost heuristic */ int bt_tech; /* backtracking technique: */ #define GLP_BT_DFS 1 /* depth first search */ #define GLP_BT_BFS 2 /* breadth first search */ #define GLP_BT_BLB 3 /* best local bound */ #define GLP_BT_BPH 4 /* best projection heuristic */ double tol_int; /* mip.tol_int */ double tol_obj; /* mip.tol_obj */ int tm_lim; /* mip.tm_lim (milliseconds) */ int out_frq; /* mip.out_frq (milliseconds) */ int out_dly; /* mip.out_dly (milliseconds) */ void (*cb_func)(glp_tree *T, void *info); /* mip.cb_func */ void *cb_info; /* mip.cb_info */ int cb_size; /* mip.cb_size */ int pp_tech; /* preprocessing technique: */ #define GLP_PP_NONE 0 /* disable preprocessing */ #define GLP_PP_ROOT 1 /* preprocessing only on root level */ #define GLP_PP_ALL 2 /* preprocessing on all levels */ double mip_gap; /* relative MIP gap tolerance */ int mir_cuts; /* MIR cuts (GLP_ON/GLP_OFF) */ int gmi_cuts; /* Gomory's cuts (GLP_ON/GLP_OFF) */ int cov_cuts; /* cover cuts (GLP_ON/GLP_OFF) */ int clq_cuts; /* clique cuts (GLP_ON/GLP_OFF) */ int presolve; /* enable/disable using MIP presolver */ int binarize; /* try to binarize integer variables */ int fp_heur; /* feasibility pump heuristic */ #if 1 /* 28/V-2010 */ int alien; /* use alien solver */ #endif double foo_bar[29]; /* (reserved) */ } glp_iocp; typedef struct { /* additional row attributes */ int level; /* subproblem level at which the row was added */ int origin; /* row origin flag: */ #define GLP_RF_REG 0 /* regular constraint */ #define GLP_RF_LAZY 1 /* "lazy" constraint */ #define GLP_RF_CUT 2 /* cutting plane constraint */ int klass; /* row class descriptor: */ #define GLP_RF_GMI 1 /* Gomory's mixed integer cut */ #define GLP_RF_MIR 2 /* mixed integer rounding cut */ #define GLP_RF_COV 3 /* mixed cover cut */ #define GLP_RF_CLQ 4 /* clique cut */ double foo_bar[7]; /* (reserved) */ } glp_attr; /* enable/disable flag: */ #define GLP_ON 1 /* enable something */ #define GLP_OFF 0 /* disable something */ /* reason codes: */ #define GLP_IROWGEN 0x01 /* request for row generation */ #define GLP_IBINGO 0x02 /* better integer solution found */ #define GLP_IHEUR 0x03 /* request for heuristic solution */ #define GLP_ICUTGEN 0x04 /* request for cut generation */ #define GLP_IBRANCH 0x05 /* request for branching */ #define GLP_ISELECT 0x06 /* request for subproblem selection */ #define GLP_IPREPRO 0x07 /* request for preprocessing */ /* branch selection indicator: */ #define GLP_NO_BRNCH 0 /* select no branch */ #define GLP_DN_BRNCH 1 /* select down-branch */ #define GLP_UP_BRNCH 2 /* select up-branch */ /* return codes: */ #define GLP_EBADB 0x01 /* invalid basis */ #define GLP_ESING 0x02 /* singular matrix */ #define GLP_ECOND 0x03 /* ill-conditioned matrix */ #define GLP_EBOUND 0x04 /* invalid bounds */ #define GLP_EFAIL 0x05 /* solver failed */ #define GLP_EOBJLL 0x06 /* objective lower limit reached */ #define GLP_EOBJUL 0x07 /* objective upper limit reached */ #define GLP_EITLIM 0x08 /* iteration limit exceeded */ #define GLP_ETMLIM 0x09 /* time limit exceeded */ #define GLP_ENOPFS 0x0A /* no primal feasible solution */ #define GLP_ENODFS 0x0B /* no dual feasible solution */ #define GLP_EROOT 0x0C /* root LP optimum not provided */ #define GLP_ESTOP 0x0D /* search terminated by application */ #define GLP_EMIPGAP 0x0E /* relative mip gap tolerance reached */ #define GLP_ENOFEAS 0x0F /* no primal/dual feasible solution */ #define GLP_ENOCVG 0x10 /* no convergence */ #define GLP_EINSTAB 0x11 /* numerical instability */ #define GLP_EDATA 0x12 /* invalid data */ #define GLP_ERANGE 0x13 /* result out of range */ /* condition indicator: */ #define GLP_KKT_PE 1 /* primal equalities */ #define GLP_KKT_PB 2 /* primal bounds */ #define GLP_KKT_DE 3 /* dual equalities */ #define GLP_KKT_DB 4 /* dual bounds */ #define GLP_KKT_CS 5 /* complementary slackness */ /* MPS file format: */ #define GLP_MPS_DECK 1 /* fixed (ancient) */ #define GLP_MPS_FILE 2 /* free (modern) */ typedef struct { /* MPS format control parameters */ int blank; /* character code to replace blanks in symbolic names */ char *obj_name; /* objective row name */ double tol_mps; /* zero tolerance for MPS data */ double foo_bar[17]; /* (reserved for use in the future) */ } glp_mpscp; typedef struct { /* CPLEX LP format control parameters */ double foo_bar[20]; /* (reserved for use in the future) */ } glp_cpxcp; #ifndef GLP_TRAN_DEFINED #define GLP_TRAN_DEFINED typedef struct { double _opaque_tran[100]; } glp_tran; /* MathProg translator workspace */ #endif glp_prob *glp_create_prob(void); /* create problem object */ void glp_set_prob_name(glp_prob *P, const char *name); /* assign (change) problem name */ void glp_set_obj_name(glp_prob *P, const char *name); /* assign (change) objective function name */ void glp_set_obj_dir(glp_prob *P, int dir); /* set (change) optimization direction flag */ int glp_add_rows(glp_prob *P, int nrs); /* add new rows to problem object */ int glp_add_cols(glp_prob *P, int ncs); /* add new columns to problem object */ void glp_set_row_name(glp_prob *P, int i, const char *name); /* assign (change) row name */ void glp_set_col_name(glp_prob *P, int j, const char *name); /* assign (change) column name */ void glp_set_row_bnds(glp_prob *P, int i, int type, double lb, double ub); /* set (change) row bounds */ void glp_set_col_bnds(glp_prob *P, int j, int type, double lb, double ub); /* set (change) column bounds */ void glp_set_obj_coef(glp_prob *P, int j, double coef); /* set (change) obj. coefficient or constant term */ void glp_set_mat_row(glp_prob *P, int i, int len, const int ind[], const double val[]); /* set (replace) row of the constraint matrix */ void glp_set_mat_col(glp_prob *P, int j, int len, const int ind[], const double val[]); /* set (replace) column of the constraint matrix */ void glp_load_matrix(glp_prob *P, int ne, const int ia[], const int ja[], const double ar[]); /* load (replace) the whole constraint matrix */ int glp_check_dup(int m, int n, int ne, const int ia[], const int ja[]); /* check for duplicate elements in sparse matrix */ void glp_sort_matrix(glp_prob *P); /* sort elements of the constraint matrix */ void glp_del_rows(glp_prob *P, int nrs, const int num[]); /* delete specified rows from problem object */ void glp_del_cols(glp_prob *P, int ncs, const int num[]); /* delete specified columns from problem object */ void glp_copy_prob(glp_prob *dest, glp_prob *prob, int names); /* copy problem object content */ void glp_erase_prob(glp_prob *P); /* erase problem object content */ void glp_delete_prob(glp_prob *P); /* delete problem object */ const char *glp_get_prob_name(glp_prob *P); /* retrieve problem name */ const char *glp_get_obj_name(glp_prob *P); /* retrieve objective function name */ int glp_get_obj_dir(glp_prob *P); /* retrieve optimization direction flag */ int glp_get_num_rows(glp_prob *P); /* retrieve number of rows */ int glp_get_num_cols(glp_prob *P); /* retrieve number of columns */ const char *glp_get_row_name(glp_prob *P, int i); /* retrieve row name */ const char *glp_get_col_name(glp_prob *P, int j); /* retrieve column name */ int glp_get_row_type(glp_prob *P, int i); /* retrieve row type */ double glp_get_row_lb(glp_prob *P, int i); /* retrieve row lower bound */ double glp_get_row_ub(glp_prob *P, int i); /* retrieve row upper bound */ int glp_get_col_type(glp_prob *P, int j); /* retrieve column type */ double glp_get_col_lb(glp_prob *P, int j); /* retrieve column lower bound */ double glp_get_col_ub(glp_prob *P, int j); /* retrieve column upper bound */ double glp_get_obj_coef(glp_prob *P, int j); /* retrieve obj. coefficient or constant term */ int glp_get_num_nz(glp_prob *P); /* retrieve number of constraint coefficients */ int glp_get_mat_row(glp_prob *P, int i, int ind[], double val[]); /* retrieve row of the constraint matrix */ int glp_get_mat_col(glp_prob *P, int j, int ind[], double val[]); /* retrieve column of the constraint matrix */ void glp_create_index(glp_prob *P); /* create the name index */ int glp_find_row(glp_prob *P, const char *name); /* find row by its name */ int glp_find_col(glp_prob *P, const char *name); /* find column by its name */ void glp_delete_index(glp_prob *P); /* delete the name index */ void glp_set_rii(glp_prob *P, int i, double rii); /* set (change) row scale factor */ void glp_set_sjj(glp_prob *P, int j, double sjj); /* set (change) column scale factor */ double glp_get_rii(glp_prob *P, int i); /* retrieve row scale factor */ double glp_get_sjj(glp_prob *P, int j); /* retrieve column scale factor */ void glp_scale_prob(glp_prob *P, int flags); /* scale problem data */ void glp_unscale_prob(glp_prob *P); /* unscale problem data */ void glp_set_row_stat(glp_prob *P, int i, int stat); /* set (change) row status */ void glp_set_col_stat(glp_prob *P, int j, int stat); /* set (change) column status */ void glp_std_basis(glp_prob *P); /* construct standard initial LP basis */ void glp_adv_basis(glp_prob *P, int flags); /* construct advanced initial LP basis */ void glp_cpx_basis(glp_prob *P); /* construct Bixby's initial LP basis */ int glp_simplex(glp_prob *P, const glp_smcp *parm); /* solve LP problem with the simplex method */ int glp_exact(glp_prob *P, const glp_smcp *parm); /* solve LP problem in exact arithmetic */ void glp_init_smcp(glp_smcp *parm); /* initialize simplex method control parameters */ int glp_get_status(glp_prob *P); /* retrieve generic status of basic solution */ int glp_get_prim_stat(glp_prob *P); /* retrieve status of primal basic solution */ int glp_get_dual_stat(glp_prob *P); /* retrieve status of dual basic solution */ double glp_get_obj_val(glp_prob *P); /* retrieve objective value (basic solution) */ int glp_get_row_stat(glp_prob *P, int i); /* retrieve row status */ double glp_get_row_prim(glp_prob *P, int i); /* retrieve row primal value (basic solution) */ double glp_get_row_dual(glp_prob *P, int i); /* retrieve row dual value (basic solution) */ int glp_get_col_stat(glp_prob *P, int j); /* retrieve column status */ double glp_get_col_prim(glp_prob *P, int j); /* retrieve column primal value (basic solution) */ double glp_get_col_dual(glp_prob *P, int j); /* retrieve column dual value (basic solution) */ int glp_get_unbnd_ray(glp_prob *P); /* determine variable causing unboundedness */ int glp_interior(glp_prob *P, const glp_iptcp *parm); /* solve LP problem with the interior-point method */ void glp_init_iptcp(glp_iptcp *parm); /* initialize interior-point solver control parameters */ int glp_ipt_status(glp_prob *P); /* retrieve status of interior-point solution */ double glp_ipt_obj_val(glp_prob *P); /* retrieve objective value (interior point) */ double glp_ipt_row_prim(glp_prob *P, int i); /* retrieve row primal value (interior point) */ double glp_ipt_row_dual(glp_prob *P, int i); /* retrieve row dual value (interior point) */ double glp_ipt_col_prim(glp_prob *P, int j); /* retrieve column primal value (interior point) */ double glp_ipt_col_dual(glp_prob *P, int j); /* retrieve column dual value (interior point) */ void glp_set_col_kind(glp_prob *P, int j, int kind); /* set (change) column kind */ int glp_get_col_kind(glp_prob *P, int j); /* retrieve column kind */ int glp_get_num_int(glp_prob *P); /* retrieve number of integer columns */ int glp_get_num_bin(glp_prob *P); /* retrieve number of binary columns */ int glp_intopt(glp_prob *P, const glp_iocp *parm); /* solve MIP problem with the branch-and-bound method */ void glp_init_iocp(glp_iocp *parm); /* initialize integer optimizer control parameters */ int glp_mip_status(glp_prob *P); /* retrieve status of MIP solution */ double glp_mip_obj_val(glp_prob *P); /* retrieve objective value (MIP solution) */ double glp_mip_row_val(glp_prob *P, int i); /* retrieve row value (MIP solution) */ double glp_mip_col_val(glp_prob *P, int j); /* retrieve column value (MIP solution) */ int glp_print_sol(glp_prob *P, const char *fname); /* write basic solution in printable format */ int glp_read_sol(glp_prob *P, const char *fname); /* read basic solution from text file */ int glp_write_sol(glp_prob *P, const char *fname); /* write basic solution to text file */ int glp_print_ranges(glp_prob *P, int len, const int list[], int flags, const char *fname); /* print sensitivity analysis report */ int glp_print_ipt(glp_prob *P, const char *fname); /* write interior-point solution in printable format */ int glp_read_ipt(glp_prob *P, const char *fname); /* read interior-point solution from text file */ int glp_write_ipt(glp_prob *P, const char *fname); /* write interior-point solution to text file */ int glp_print_mip(glp_prob *P, const char *fname); /* write MIP solution in printable format */ int glp_read_mip(glp_prob *P, const char *fname); /* read MIP solution from text file */ int glp_write_mip(glp_prob *P, const char *fname); /* write MIP solution to text file */ int glp_bf_exists(glp_prob *P); /* check if the basis factorization exists */ int glp_factorize(glp_prob *P); /* compute the basis factorization */ int glp_bf_updated(glp_prob *P); /* check if the basis factorization has been updated */ void glp_get_bfcp(glp_prob *P, glp_bfcp *parm); /* retrieve basis factorization control parameters */ void glp_set_bfcp(glp_prob *P, const glp_bfcp *parm); /* change basis factorization control parameters */ int glp_get_bhead(glp_prob *P, int k); /* retrieve the basis header information */ int glp_get_row_bind(glp_prob *P, int i); /* retrieve row index in the basis header */ int glp_get_col_bind(glp_prob *P, int j); /* retrieve column index in the basis header */ void glp_ftran(glp_prob *P, double x[]); /* perform forward transformation (solve system B*x = b) */ void glp_btran(glp_prob *P, double x[]); /* perform backward transformation (solve system B'*x = b) */ int glp_warm_up(glp_prob *P); /* "warm up" LP basis */ int glp_eval_tab_row(glp_prob *P, int k, int ind[], double val[]); /* compute row of the simplex tableau */ int glp_eval_tab_col(glp_prob *P, int k, int ind[], double val[]); /* compute column of the simplex tableau */ int glp_transform_row(glp_prob *P, int len, int ind[], double val[]); /* transform explicitly specified row */ int glp_transform_col(glp_prob *P, int len, int ind[], double val[]); /* transform explicitly specified column */ int glp_prim_rtest(glp_prob *P, int len, const int ind[], const double val[], int dir, double eps); /* perform primal ratio test */ int glp_dual_rtest(glp_prob *P, int len, const int ind[], const double val[], int dir, double eps); /* perform dual ratio test */ void glp_analyze_bound(glp_prob *P, int k, double *value1, int *var1, double *value2, int *var2); /* analyze active bound of non-basic variable */ void glp_analyze_coef(glp_prob *P, int k, double *coef1, int *var1, double *value1, double *coef2, int *var2, double *value2); /* analyze objective coefficient at basic variable */ int glp_ios_reason(glp_tree *T); /* determine reason for calling the callback routine */ glp_prob *glp_ios_get_prob(glp_tree *T); /* access the problem object */ void glp_ios_tree_size(glp_tree *T, int *a_cnt, int *n_cnt, int *t_cnt); /* determine size of the branch-and-bound tree */ int glp_ios_curr_node(glp_tree *T); /* determine current active subproblem */ int glp_ios_next_node(glp_tree *T, int p); /* determine next active subproblem */ int glp_ios_prev_node(glp_tree *T, int p); /* determine previous active subproblem */ int glp_ios_up_node(glp_tree *T, int p); /* determine parent subproblem */ int glp_ios_node_level(glp_tree *T, int p); /* determine subproblem level */ double glp_ios_node_bound(glp_tree *T, int p); /* determine subproblem local bound */ int glp_ios_best_node(glp_tree *T); /* find active subproblem with best local bound */ double glp_ios_mip_gap(glp_tree *T); /* compute relative MIP gap */ void *glp_ios_node_data(glp_tree *T, int p); /* access subproblem application-specific data */ void glp_ios_row_attr(glp_tree *T, int i, glp_attr *attr); /* retrieve additional row attributes */ int glp_ios_pool_size(glp_tree *T); /* determine current size of the cut pool */ int glp_ios_add_row(glp_tree *T, const char *name, int klass, int flags, int len, const int ind[], const double val[], int type, double rhs); /* add row (constraint) to the cut pool */ void glp_ios_del_row(glp_tree *T, int i); /* remove row (constraint) from the cut pool */ void glp_ios_clear_pool(glp_tree *T); /* remove all rows (constraints) from the cut pool */ int glp_ios_can_branch(glp_tree *T, int j); /* check if can branch upon specified variable */ void glp_ios_branch_upon(glp_tree *T, int j, int sel); /* choose variable to branch upon */ void glp_ios_select_node(glp_tree *T, int p); /* select subproblem to continue the search */ int glp_ios_heur_sol(glp_tree *T, const double x[]); /* provide solution found by heuristic */ void glp_ios_terminate(glp_tree *T); /* terminate the solution process */ void glp_init_mpscp(glp_mpscp *parm); /* initialize MPS format control parameters */ int glp_read_mps(glp_prob *P, int fmt, const glp_mpscp *parm, const char *fname); /* read problem data in MPS format */ int glp_write_mps(glp_prob *P, int fmt, const glp_mpscp *parm, const char *fname); /* write problem data in MPS format */ void glp_init_cpxcp(glp_cpxcp *parm); /* initialize CPLEX LP format control parameters */ int glp_read_lp(glp_prob *P, const glp_cpxcp *parm, const char *fname); /* read problem data in CPLEX LP format */ int glp_write_lp(glp_prob *P, const glp_cpxcp *parm, const char *fname); /* write problem data in CPLEX LP format */ int glp_read_prob(glp_prob *P, int flags, const char *fname); /* read problem data in GLPK format */ int glp_write_prob(glp_prob *P, int flags, const char *fname); /* write problem data in GLPK format */ glp_tran *glp_mpl_alloc_wksp(void); /* allocate the MathProg translator workspace */ int glp_mpl_read_model(glp_tran *tran, const char *fname, int skip); /* read and translate model section */ int glp_mpl_read_data(glp_tran *tran, const char *fname); /* read and translate data section */ int glp_mpl_generate(glp_tran *tran, const char *fname); /* generate the model */ void glp_mpl_build_prob(glp_tran *tran, glp_prob *prob); /* build LP/MIP problem instance from the model */ int glp_mpl_postsolve(glp_tran *tran, glp_prob *prob, int sol); /* postsolve the model */ void glp_mpl_free_wksp(glp_tran *tran); /* free the MathProg translator workspace */ int glp_main(int argc, const char *argv[]); /* stand-alone LP/MIP solver */ /**********************************************************************/ #ifndef GLP_LONG_DEFINED #define GLP_LONG_DEFINED typedef struct { int lo, hi; } glp_long; /* long integer data type */ #endif int glp_init_env(void); /* initialize GLPK environment */ const char *glp_version(void); /* determine library version */ int glp_free_env(void); /* free GLPK environment */ void glp_printf(const char *fmt, ...); /* write formatted output to terminal */ void glp_vprintf(const char *fmt, va_list arg); /* write formatted output to terminal */ int glp_term_out(int flag); /* enable/disable terminal output */ void glp_term_hook(int (*func)(void *info, const char *s), void *info); /* install hook to intercept terminal output */ int glp_open_tee(const char *fname); /* start copying terminal output to text file */ int glp_close_tee(void); /* stop copying terminal output to text file */ #ifndef GLP_ERROR_DEFINED #define GLP_ERROR_DEFINED typedef void (*_glp_error)(const char *fmt, ...); #endif #define glp_error glp_error_(__FILE__, __LINE__) _glp_error glp_error_(const char *file, int line); /* display error message and terminate execution */ #define glp_assert(expr) \ ((void)((expr) || (glp_assert_(#expr, __FILE__, __LINE__), 1))) void glp_assert_(const char *expr, const char *file, int line); /* check for logical condition */ void glp_error_hook(void (*func)(void *info), void *info); /* install hook to intercept abnormal termination */ void *glp_malloc(int size); /* allocate memory block */ void *glp_calloc(int n, int size); /* allocate memory block */ void glp_free(void *ptr); /* free memory block */ void glp_mem_limit(int limit); /* set memory usage limit */ void glp_mem_usage(int *count, int *cpeak, glp_long *total, glp_long *tpeak); /* get memory usage information */ glp_long glp_time(void); /* determine current universal time */ double glp_difftime(glp_long t1, glp_long t0); /* compute difference between two time values */ /**********************************************************************/ #ifndef GLP_DATA_DEFINED #define GLP_DATA_DEFINED typedef struct { double _opaque_data[100]; } glp_data; /* plain data file */ #endif glp_data *glp_sdf_open_file(const char *fname); /* open plain data file */ void glp_sdf_set_jump(glp_data *data, void *jump); /* set up error handling */ void glp_sdf_error(glp_data *data, const char *fmt, ...); /* print error message */ void glp_sdf_warning(glp_data *data, const char *fmt, ...); /* print warning message */ int glp_sdf_read_int(glp_data *data); /* read integer number */ double glp_sdf_read_num(glp_data *data); /* read floating-point number */ const char *glp_sdf_read_item(glp_data *data); /* read data item */ const char *glp_sdf_read_text(glp_data *data); /* read text until end of line */ int glp_sdf_line(glp_data *data); /* determine current line number */ void glp_sdf_close_file(glp_data *data); /* close plain data file */ /**********************************************************************/ typedef struct _glp_graph glp_graph; typedef struct _glp_vertex glp_vertex; typedef struct _glp_arc glp_arc; struct _glp_graph { /* graph descriptor */ void *pool; /* DMP *pool; */ /* memory pool to store graph components */ char *name; /* graph name (1 to 255 chars); NULL means no name is assigned to the graph */ int nv_max; /* length of the vertex list (enlarged automatically) */ int nv; /* number of vertices in the graph, 0 <= nv <= nv_max */ int na; /* number of arcs in the graph, na >= 0 */ glp_vertex **v; /* glp_vertex *v[1+nv_max]; */ /* v[i], 1 <= i <= nv, is a pointer to i-th vertex */ void *index; /* AVL *index; */ /* vertex index to find vertices by their names; NULL means the index does not exist */ int v_size; /* size of data associated with each vertex (0 to 256 bytes) */ int a_size; /* size of data associated with each arc (0 to 256 bytes) */ }; struct _glp_vertex { /* vertex descriptor */ int i; /* vertex ordinal number, 1 <= i <= nv */ char *name; /* vertex name (1 to 255 chars); NULL means no name is assigned to the vertex */ void *entry; /* AVLNODE *entry; */ /* pointer to corresponding entry in the vertex index; NULL means that either the index does not exist or the vertex has no name assigned */ void *data; /* pointer to data associated with the vertex */ void *temp; /* working pointer */ glp_arc *in; /* pointer to the (unordered) list of incoming arcs */ glp_arc *out; /* pointer to the (unordered) list of outgoing arcs */ }; struct _glp_arc { /* arc descriptor */ glp_vertex *tail; /* pointer to the tail endpoint */ glp_vertex *head; /* pointer to the head endpoint */ void *data; /* pointer to data associated with the arc */ void *temp; /* working pointer */ glp_arc *t_prev; /* pointer to previous arc having the same tail endpoint */ glp_arc *t_next; /* pointer to next arc having the same tail endpoint */ glp_arc *h_prev; /* pointer to previous arc having the same head endpoint */ glp_arc *h_next; /* pointer to next arc having the same head endpoint */ }; glp_graph *glp_create_graph(int v_size, int a_size); /* create graph */ void glp_set_graph_name(glp_graph *G, const char *name); /* assign (change) graph name */ int glp_add_vertices(glp_graph *G, int nadd); /* add new vertices to graph */ void glp_set_vertex_name(glp_graph *G, int i, const char *name); /* assign (change) vertex name */ glp_arc *glp_add_arc(glp_graph *G, int i, int j); /* add new arc to graph */ void glp_del_vertices(glp_graph *G, int ndel, const int num[]); /* delete vertices from graph */ void glp_del_arc(glp_graph *G, glp_arc *a); /* delete arc from graph */ void glp_erase_graph(glp_graph *G, int v_size, int a_size); /* erase graph content */ void glp_delete_graph(glp_graph *G); /* delete graph */ void glp_create_v_index(glp_graph *G); /* create vertex name index */ int glp_find_vertex(glp_graph *G, const char *name); /* find vertex by its name */ void glp_delete_v_index(glp_graph *G); /* delete vertex name index */ int glp_read_graph(glp_graph *G, const char *fname); /* read graph from plain text file */ int glp_write_graph(glp_graph *G, const char *fname); /* write graph to plain text file */ void glp_mincost_lp(glp_prob *P, glp_graph *G, int names, int v_rhs, int a_low, int a_cap, int a_cost); /* convert minimum cost flow problem to LP */ int glp_mincost_okalg(glp_graph *G, int v_rhs, int a_low, int a_cap, int a_cost, double *sol, int a_x, int v_pi); /* find minimum-cost flow with out-of-kilter algorithm */ void glp_maxflow_lp(glp_prob *P, glp_graph *G, int names, int s, int t, int a_cap); /* convert maximum flow problem to LP */ int glp_maxflow_ffalg(glp_graph *G, int s, int t, int a_cap, double *sol, int a_x, int v_cut); /* find maximal flow with Ford-Fulkerson algorithm */ int glp_check_asnprob(glp_graph *G, int v_set); /* check correctness of assignment problem data */ /* assignment problem formulation: */ #define GLP_ASN_MIN 1 /* perfect matching (minimization) */ #define GLP_ASN_MAX 2 /* perfect matching (maximization) */ #define GLP_ASN_MMP 3 /* maximum matching */ int glp_asnprob_lp(glp_prob *P, int form, glp_graph *G, int names, int v_set, int a_cost); /* convert assignment problem to LP */ int glp_asnprob_okalg(int form, glp_graph *G, int v_set, int a_cost, double *sol, int a_x); /* solve assignment problem with out-of-kilter algorithm */ int glp_asnprob_hall(glp_graph *G, int v_set, int a_x); /* find bipartite matching of maximum cardinality */ double glp_cpp(glp_graph *G, int v_t, int v_es, int v_ls); /* solve critical path problem */ int glp_read_mincost(glp_graph *G, int v_rhs, int a_low, int a_cap, int a_cost, const char *fname); /* read min-cost flow problem data in DIMACS format */ int glp_write_mincost(glp_graph *G, int v_rhs, int a_low, int a_cap, int a_cost, const char *fname); /* write min-cost flow problem data in DIMACS format */ int glp_read_maxflow(glp_graph *G, int *s, int *t, int a_cap, const char *fname); /* read maximum flow problem data in DIMACS format */ int glp_write_maxflow(glp_graph *G, int s, int t, int a_cap, const char *fname); /* write maximum flow problem data in DIMACS format */ int glp_read_asnprob(glp_graph *G, int v_set, int a_cost, const char *fname); /* read assignment problem data in DIMACS format */ int glp_write_asnprob(glp_graph *G, int v_set, int a_cost, const char *fname); /* write assignment problem data in DIMACS format */ int glp_read_ccdata(glp_graph *G, int v_wgt, const char *fname); /* read graph in DIMACS clique/coloring format */ int glp_write_ccdata(glp_graph *G, int v_wgt, const char *fname); /* write graph in DIMACS clique/coloring format */ int glp_netgen(glp_graph *G, int v_rhs, int a_cap, int a_cost, const int parm[1+15]); /* Klingman's network problem generator */ int glp_gridgen(glp_graph *G, int v_rhs, int a_cap, int a_cost, const int parm[1+14]); /* grid-like network problem generator */ int glp_rmfgen(glp_graph *G, int *s, int *t, int a_cap, const int parm[1+5]); /* Goldfarb's maximum flow problem generator */ int glp_weak_comp(glp_graph *G, int v_num); /* find all weakly connected components of graph */ int glp_strong_comp(glp_graph *G, int v_num); /* find all strongly connected components of graph */ int glp_top_sort(glp_graph *G, int v_num); /* topological sorting of acyclic digraph */ int glp_wclique_exact(glp_graph *G, int v_wgt, double *sol, int v_set); /* find maximum weight clique with exact algorithm */ /*********************************************************************** * NOTE: All symbols defined below are obsolete and kept here only for * backward compatibility. ***********************************************************************/ #define LPX glp_prob /* problem class: */ #define LPX_LP 100 /* linear programming (LP) */ #define LPX_MIP 101 /* mixed integer programming (MIP) */ /* type of auxiliary/structural variable: */ #define LPX_FR 110 /* free variable */ #define LPX_LO 111 /* variable with lower bound */ #define LPX_UP 112 /* variable with upper bound */ #define LPX_DB 113 /* double-bounded variable */ #define LPX_FX 114 /* fixed variable */ /* optimization direction flag: */ #define LPX_MIN 120 /* minimization */ #define LPX_MAX 121 /* maximization */ /* status of primal basic solution: */ #define LPX_P_UNDEF 132 /* primal solution is undefined */ #define LPX_P_FEAS 133 /* solution is primal feasible */ #define LPX_P_INFEAS 134 /* solution is primal infeasible */ #define LPX_P_NOFEAS 135 /* no primal feasible solution exists */ /* status of dual basic solution: */ #define LPX_D_UNDEF 136 /* dual solution is undefined */ #define LPX_D_FEAS 137 /* solution is dual feasible */ #define LPX_D_INFEAS 138 /* solution is dual infeasible */ #define LPX_D_NOFEAS 139 /* no dual feasible solution exists */ /* status of auxiliary/structural variable: */ #define LPX_BS 140 /* basic variable */ #define LPX_NL 141 /* non-basic variable on lower bound */ #define LPX_NU 142 /* non-basic variable on upper bound */ #define LPX_NF 143 /* non-basic free variable */ #define LPX_NS 144 /* non-basic fixed variable */ /* status of interior-point solution: */ #define LPX_T_UNDEF 150 /* interior solution is undefined */ #define LPX_T_OPT 151 /* interior solution is optimal */ /* kind of structural variable: */ #define LPX_CV 160 /* continuous variable */ #define LPX_IV 161 /* integer variable */ /* status of integer solution: */ #define LPX_I_UNDEF 170 /* integer solution is undefined */ #define LPX_I_OPT 171 /* integer solution is optimal */ #define LPX_I_FEAS 172 /* integer solution is feasible */ #define LPX_I_NOFEAS 173 /* no integer solution exists */ /* status codes reported by the routine lpx_get_status: */ #define LPX_OPT 180 /* optimal */ #define LPX_FEAS 181 /* feasible */ #define LPX_INFEAS 182 /* infeasible */ #define LPX_NOFEAS 183 /* no feasible */ #define LPX_UNBND 184 /* unbounded */ #define LPX_UNDEF 185 /* undefined */ /* exit codes returned by solver routines: */ #define LPX_E_OK 200 /* success */ #define LPX_E_EMPTY 201 /* empty problem */ #define LPX_E_BADB 202 /* invalid initial basis */ #define LPX_E_INFEAS 203 /* infeasible initial solution */ #define LPX_E_FAULT 204 /* unable to start the search */ #define LPX_E_OBJLL 205 /* objective lower limit reached */ #define LPX_E_OBJUL 206 /* objective upper limit reached */ #define LPX_E_ITLIM 207 /* iterations limit exhausted */ #define LPX_E_TMLIM 208 /* time limit exhausted */ #define LPX_E_NOFEAS 209 /* no feasible solution */ #define LPX_E_INSTAB 210 /* numerical instability */ #define LPX_E_SING 211 /* problems with basis matrix */ #define LPX_E_NOCONV 212 /* no convergence (interior) */ #define LPX_E_NOPFS 213 /* no primal feas. sol. (LP presolver) */ #define LPX_E_NODFS 214 /* no dual feas. sol. (LP presolver) */ #define LPX_E_MIPGAP 215 /* relative mip gap tolerance reached */ /* control parameter identifiers: */ #define LPX_K_MSGLEV 300 /* lp->msg_lev */ #define LPX_K_SCALE 301 /* lp->scale */ #define LPX_K_DUAL 302 /* lp->dual */ #define LPX_K_PRICE 303 /* lp->price */ #define LPX_K_RELAX 304 /* lp->relax */ #define LPX_K_TOLBND 305 /* lp->tol_bnd */ #define LPX_K_TOLDJ 306 /* lp->tol_dj */ #define LPX_K_TOLPIV 307 /* lp->tol_piv */ #define LPX_K_ROUND 308 /* lp->round */ #define LPX_K_OBJLL 309 /* lp->obj_ll */ #define LPX_K_OBJUL 310 /* lp->obj_ul */ #define LPX_K_ITLIM 311 /* lp->it_lim */ #define LPX_K_ITCNT 312 /* lp->it_cnt */ #define LPX_K_TMLIM 313 /* lp->tm_lim */ #define LPX_K_OUTFRQ 314 /* lp->out_frq */ #define LPX_K_OUTDLY 315 /* lp->out_dly */ #define LPX_K_BRANCH 316 /* lp->branch */ #define LPX_K_BTRACK 317 /* lp->btrack */ #define LPX_K_TOLINT 318 /* lp->tol_int */ #define LPX_K_TOLOBJ 319 /* lp->tol_obj */ #define LPX_K_MPSINFO 320 /* lp->mps_info */ #define LPX_K_MPSOBJ 321 /* lp->mps_obj */ #define LPX_K_MPSORIG 322 /* lp->mps_orig */ #define LPX_K_MPSWIDE 323 /* lp->mps_wide */ #define LPX_K_MPSFREE 324 /* lp->mps_free */ #define LPX_K_MPSSKIP 325 /* lp->mps_skip */ #define LPX_K_LPTORIG 326 /* lp->lpt_orig */ #define LPX_K_PRESOL 327 /* lp->presol */ #define LPX_K_BINARIZE 328 /* lp->binarize */ #define LPX_K_USECUTS 329 /* lp->use_cuts */ #define LPX_K_BFTYPE 330 /* lp->bfcp->type */ #define LPX_K_MIPGAP 331 /* lp->mip_gap */ #define LPX_C_COVER 0x01 /* mixed cover cuts */ #define LPX_C_CLIQUE 0x02 /* clique cuts */ #define LPX_C_GOMORY 0x04 /* Gomory's mixed integer cuts */ #define LPX_C_MIR 0x08 /* mixed integer rounding cuts */ #define LPX_C_ALL 0xFF /* all cuts */ typedef struct { /* this structure contains results reported by the routines which checks Karush-Kuhn-Tucker conditions (for details see comments to those routines) */ /*--------------------------------------------------------------*/ /* xR - A * xS = 0 (KKT.PE) */ double pe_ae_max; /* largest absolute error */ int pe_ae_row; /* number of row with largest absolute error */ double pe_re_max; /* largest relative error */ int pe_re_row; /* number of row with largest relative error */ int pe_quality; /* quality of primal solution: 'H' - high 'M' - medium 'L' - low '?' - primal solution is wrong */ /*--------------------------------------------------------------*/ /* l[k] <= x[k] <= u[k] (KKT.PB) */ double pb_ae_max; /* largest absolute error */ int pb_ae_ind; /* number of variable with largest absolute error */ double pb_re_max; /* largest relative error */ int pb_re_ind; /* number of variable with largest relative error */ int pb_quality; /* quality of primal feasibility: 'H' - high 'M' - medium 'L' - low '?' - primal solution is infeasible */ /*--------------------------------------------------------------*/ /* A' * (dR - cR) + (dS - cS) = 0 (KKT.DE) */ double de_ae_max; /* largest absolute error */ int de_ae_col; /* number of column with largest absolute error */ double de_re_max; /* largest relative error */ int de_re_col; /* number of column with largest relative error */ int de_quality; /* quality of dual solution: 'H' - high 'M' - medium 'L' - low '?' - dual solution is wrong */ /*--------------------------------------------------------------*/ /* d[k] >= 0 or d[k] <= 0 (KKT.DB) */ double db_ae_max; /* largest absolute error */ int db_ae_ind; /* number of variable with largest absolute error */ double db_re_max; /* largest relative error */ int db_re_ind; /* number of variable with largest relative error */ int db_quality; /* quality of dual feasibility: 'H' - high 'M' - medium 'L' - low '?' - dual solution is infeasible */ /*--------------------------------------------------------------*/ /* (x[k] - bound of x[k]) * d[k] = 0 (KKT.CS) */ double cs_ae_max; /* largest absolute error */ int cs_ae_ind; /* number of variable with largest absolute error */ double cs_re_max; /* largest relative error */ int cs_re_ind; /* number of variable with largest relative error */ int cs_quality; /* quality of complementary slackness: 'H' - high 'M' - medium 'L' - low '?' - primal and dual solutions are not complementary */ } LPXKKT; #define lpx_create_prob _glp_lpx_create_prob LPX *lpx_create_prob(void); /* create problem object */ #define lpx_set_prob_name _glp_lpx_set_prob_name void lpx_set_prob_name(LPX *lp, const char *name); /* assign (change) problem name */ #define lpx_set_obj_name _glp_lpx_set_obj_name void lpx_set_obj_name(LPX *lp, const char *name); /* assign (change) objective function name */ #define lpx_set_obj_dir _glp_lpx_set_obj_dir void lpx_set_obj_dir(LPX *lp, int dir); /* set (change) optimization direction flag */ #define lpx_add_rows _glp_lpx_add_rows int lpx_add_rows(LPX *lp, int nrs); /* add new rows to problem object */ #define lpx_add_cols _glp_lpx_add_cols int lpx_add_cols(LPX *lp, int ncs); /* add new columns to problem object */ #define lpx_set_row_name _glp_lpx_set_row_name void lpx_set_row_name(LPX *lp, int i, const char *name); /* assign (change) row name */ #define lpx_set_col_name _glp_lpx_set_col_name void lpx_set_col_name(LPX *lp, int j, const char *name); /* assign (change) column name */ #define lpx_set_row_bnds _glp_lpx_set_row_bnds void lpx_set_row_bnds(LPX *lp, int i, int type, double lb, double ub); /* set (change) row bounds */ #define lpx_set_col_bnds _glp_lpx_set_col_bnds void lpx_set_col_bnds(LPX *lp, int j, int type, double lb, double ub); /* set (change) column bounds */ #define lpx_set_obj_coef _glp_lpx_set_obj_coef void lpx_set_obj_coef(glp_prob *lp, int j, double coef); /* set (change) obj. coefficient or constant term */ #define lpx_set_mat_row _glp_lpx_set_mat_row void lpx_set_mat_row(LPX *lp, int i, int len, const int ind[], const double val[]); /* set (replace) row of the constraint matrix */ #define lpx_set_mat_col _glp_lpx_set_mat_col void lpx_set_mat_col(LPX *lp, int j, int len, const int ind[], const double val[]); /* set (replace) column of the constraint matrix */ #define lpx_load_matrix _glp_lpx_load_matrix void lpx_load_matrix(LPX *lp, int ne, const int ia[], const int ja[], const double ar[]); /* load (replace) the whole constraint matrix */ #define lpx_del_rows _glp_lpx_del_rows void lpx_del_rows(LPX *lp, int nrs, const int num[]); /* delete specified rows from problem object */ #define lpx_del_cols _glp_lpx_del_cols void lpx_del_cols(LPX *lp, int ncs, const int num[]); /* delete specified columns from problem object */ #define lpx_delete_prob _glp_lpx_delete_prob void lpx_delete_prob(LPX *lp); /* delete problem object */ #define lpx_get_prob_name _glp_lpx_get_prob_name const char *lpx_get_prob_name(LPX *lp); /* retrieve problem name */ #define lpx_get_obj_name _glp_lpx_get_obj_name const char *lpx_get_obj_name(LPX *lp); /* retrieve objective function name */ #define lpx_get_obj_dir _glp_lpx_get_obj_dir int lpx_get_obj_dir(LPX *lp); /* retrieve optimization direction flag */ #define lpx_get_num_rows _glp_lpx_get_num_rows int lpx_get_num_rows(LPX *lp); /* retrieve number of rows */ #define lpx_get_num_cols _glp_lpx_get_num_cols int lpx_get_num_cols(LPX *lp); /* retrieve number of columns */ #define lpx_get_row_name _glp_lpx_get_row_name const char *lpx_get_row_name(LPX *lp, int i); /* retrieve row name */ #define lpx_get_col_name _glp_lpx_get_col_name const char *lpx_get_col_name(LPX *lp, int j); /* retrieve column name */ #define lpx_get_row_type _glp_lpx_get_row_type int lpx_get_row_type(LPX *lp, int i); /* retrieve row type */ #define lpx_get_row_lb _glp_lpx_get_row_lb double lpx_get_row_lb(LPX *lp, int i); /* retrieve row lower bound */ #define lpx_get_row_ub _glp_lpx_get_row_ub double lpx_get_row_ub(LPX *lp, int i); /* retrieve row upper bound */ #define lpx_get_row_bnds _glp_lpx_get_row_bnds void lpx_get_row_bnds(LPX *lp, int i, int *typx, double *lb, double *ub); /* retrieve row bounds */ #define lpx_get_col_type _glp_lpx_get_col_type int lpx_get_col_type(LPX *lp, int j); /* retrieve column type */ #define lpx_get_col_lb _glp_lpx_get_col_lb double lpx_get_col_lb(LPX *lp, int j); /* retrieve column lower bound */ #define lpx_get_col_ub _glp_lpx_get_col_ub double lpx_get_col_ub(LPX *lp, int j); /* retrieve column upper bound */ #define lpx_get_col_bnds _glp_lpx_get_col_bnds void lpx_get_col_bnds(LPX *lp, int j, int *typx, double *lb, double *ub); /* retrieve column bounds */ #define lpx_get_obj_coef _glp_lpx_get_obj_coef double lpx_get_obj_coef(LPX *lp, int j); /* retrieve obj. coefficient or constant term */ #define lpx_get_num_nz _glp_lpx_get_num_nz int lpx_get_num_nz(LPX *lp); /* retrieve number of constraint coefficients */ #define lpx_get_mat_row _glp_lpx_get_mat_row int lpx_get_mat_row(LPX *lp, int i, int ind[], double val[]); /* retrieve row of the constraint matrix */ #define lpx_get_mat_col _glp_lpx_get_mat_col int lpx_get_mat_col(LPX *lp, int j, int ind[], double val[]); /* retrieve column of the constraint matrix */ #define lpx_create_index _glp_lpx_create_index void lpx_create_index(LPX *lp); /* create the name index */ #define lpx_find_row _glp_lpx_find_row int lpx_find_row(LPX *lp, const char *name); /* find row by its name */ #define lpx_find_col _glp_lpx_find_col int lpx_find_col(LPX *lp, const char *name); /* find column by its name */ #define lpx_delete_index _glp_lpx_delete_index void lpx_delete_index(LPX *lp); /* delete the name index */ #define lpx_scale_prob _glp_lpx_scale_prob void lpx_scale_prob(LPX *lp); /* scale problem data */ #define lpx_unscale_prob _glp_lpx_unscale_prob void lpx_unscale_prob(LPX *lp); /* unscale problem data */ #define lpx_set_row_stat _glp_lpx_set_row_stat void lpx_set_row_stat(LPX *lp, int i, int stat); /* set (change) row status */ #define lpx_set_col_stat _glp_lpx_set_col_stat void lpx_set_col_stat(LPX *lp, int j, int stat); /* set (change) column status */ #define lpx_std_basis _glp_lpx_std_basis void lpx_std_basis(LPX *lp); /* construct standard initial LP basis */ #define lpx_adv_basis _glp_lpx_adv_basis void lpx_adv_basis(LPX *lp); /* construct advanced initial LP basis */ #define lpx_cpx_basis _glp_lpx_cpx_basis void lpx_cpx_basis(LPX *lp); /* construct Bixby's initial LP basis */ #define lpx_simplex _glp_lpx_simplex int lpx_simplex(LPX *lp); /* easy-to-use driver to the simplex method */ #define lpx_exact _glp_lpx_exact int lpx_exact(LPX *lp); /* easy-to-use driver to the exact simplex method */ #define lpx_get_status _glp_lpx_get_status int lpx_get_status(LPX *lp); /* retrieve generic status of basic solution */ #define lpx_get_prim_stat _glp_lpx_get_prim_stat int lpx_get_prim_stat(LPX *lp); /* retrieve primal status of basic solution */ #define lpx_get_dual_stat _glp_lpx_get_dual_stat int lpx_get_dual_stat(LPX *lp); /* retrieve dual status of basic solution */ #define lpx_get_obj_val _glp_lpx_get_obj_val double lpx_get_obj_val(LPX *lp); /* retrieve objective value (basic solution) */ #define lpx_get_row_stat _glp_lpx_get_row_stat int lpx_get_row_stat(LPX *lp, int i); /* retrieve row status (basic solution) */ #define lpx_get_row_prim _glp_lpx_get_row_prim double lpx_get_row_prim(LPX *lp, int i); /* retrieve row primal value (basic solution) */ #define lpx_get_row_dual _glp_lpx_get_row_dual double lpx_get_row_dual(LPX *lp, int i); /* retrieve row dual value (basic solution) */ #define lpx_get_row_info _glp_lpx_get_row_info void lpx_get_row_info(LPX *lp, int i, int *tagx, double *vx, double *dx); /* obtain row solution information */ #define lpx_get_col_stat _glp_lpx_get_col_stat int lpx_get_col_stat(LPX *lp, int j); /* retrieve column status (basic solution) */ #define lpx_get_col_prim _glp_lpx_get_col_prim double lpx_get_col_prim(LPX *lp, int j); /* retrieve column primal value (basic solution) */ #define lpx_get_col_dual _glp_lpx_get_col_dual double lpx_get_col_dual(glp_prob *lp, int j); /* retrieve column dual value (basic solution) */ #define lpx_get_col_info _glp_lpx_get_col_info void lpx_get_col_info(LPX *lp, int j, int *tagx, double *vx, double *dx); /* obtain column solution information (obsolete) */ #define lpx_get_ray_info _glp_lpx_get_ray_info int lpx_get_ray_info(LPX *lp); /* determine what causes primal unboundness */ #define lpx_check_kkt _glp_lpx_check_kkt void lpx_check_kkt(LPX *lp, int scaled, LPXKKT *kkt); /* check Karush-Kuhn-Tucker conditions */ #define lpx_warm_up _glp_lpx_warm_up int lpx_warm_up(LPX *lp); /* "warm up" LP basis */ #define lpx_eval_tab_row _glp_lpx_eval_tab_row int lpx_eval_tab_row(LPX *lp, int k, int ind[], double val[]); /* compute row of the simplex table */ #define lpx_eval_tab_col _glp_lpx_eval_tab_col int lpx_eval_tab_col(LPX *lp, int k, int ind[], double val[]); /* compute column of the simplex table */ #define lpx_transform_row _glp_lpx_transform_row int lpx_transform_row(LPX *lp, int len, int ind[], double val[]); /* transform explicitly specified row */ #define lpx_transform_col _glp_lpx_transform_col int lpx_transform_col(LPX *lp, int len, int ind[], double val[]); /* transform explicitly specified column */ #define lpx_prim_ratio_test _glp_lpx_prim_ratio_test int lpx_prim_ratio_test(LPX *lp, int len, const int ind[], const double val[], int how, double tol); /* perform primal ratio test */ #define lpx_dual_ratio_test _glp_lpx_dual_ratio_test int lpx_dual_ratio_test(LPX *lp, int len, const int ind[], const double val[], int how, double tol); /* perform dual ratio test */ #define lpx_interior _glp_lpx_interior int lpx_interior(LPX *lp); /* easy-to-use driver to the interior point method */ #define lpx_ipt_status _glp_lpx_ipt_status int lpx_ipt_status(LPX *lp); /* retrieve status of interior-point solution */ #define lpx_ipt_obj_val _glp_lpx_ipt_obj_val double lpx_ipt_obj_val(LPX *lp); /* retrieve objective value (interior point) */ #define lpx_ipt_row_prim _glp_lpx_ipt_row_prim double lpx_ipt_row_prim(LPX *lp, int i); /* retrieve row primal value (interior point) */ #define lpx_ipt_row_dual _glp_lpx_ipt_row_dual double lpx_ipt_row_dual(LPX *lp, int i); /* retrieve row dual value (interior point) */ #define lpx_ipt_col_prim _glp_lpx_ipt_col_prim double lpx_ipt_col_prim(LPX *lp, int j); /* retrieve column primal value (interior point) */ #define lpx_ipt_col_dual _glp_lpx_ipt_col_dual double lpx_ipt_col_dual(LPX *lp, int j); /* retrieve column dual value (interior point) */ #define lpx_set_class _glp_lpx_set_class void lpx_set_class(LPX *lp, int klass); /* set problem class */ #define lpx_get_class _glp_lpx_get_class int lpx_get_class(LPX *lp); /* determine problem klass */ #define lpx_set_col_kind _glp_lpx_set_col_kind void lpx_set_col_kind(LPX *lp, int j, int kind); /* set (change) column kind */ #define lpx_get_col_kind _glp_lpx_get_col_kind int lpx_get_col_kind(LPX *lp, int j); /* retrieve column kind */ #define lpx_get_num_int _glp_lpx_get_num_int int lpx_get_num_int(LPX *lp); /* retrieve number of integer columns */ #define lpx_get_num_bin _glp_lpx_get_num_bin int lpx_get_num_bin(LPX *lp); /* retrieve number of binary columns */ #define lpx_integer _glp_lpx_integer int lpx_integer(LPX *lp); /* easy-to-use driver to the branch-and-bound method */ #define lpx_intopt _glp_lpx_intopt int lpx_intopt(LPX *lp); /* easy-to-use driver to the branch-and-bound method */ #define lpx_mip_status _glp_lpx_mip_status int lpx_mip_status(LPX *lp); /* retrieve status of MIP solution */ #define lpx_mip_obj_val _glp_lpx_mip_obj_val double lpx_mip_obj_val(LPX *lp); /* retrieve objective value (MIP solution) */ #define lpx_mip_row_val _glp_lpx_mip_row_val double lpx_mip_row_val(LPX *lp, int i); /* retrieve row value (MIP solution) */ #define lpx_mip_col_val _glp_lpx_mip_col_val double lpx_mip_col_val(LPX *lp, int j); /* retrieve column value (MIP solution) */ #define lpx_check_int _glp_lpx_check_int void lpx_check_int(LPX *lp, LPXKKT *kkt); /* check integer feasibility conditions */ #define lpx_reset_parms _glp_lpx_reset_parms void lpx_reset_parms(LPX *lp); /* reset control parameters to default values */ #define lpx_set_int_parm _glp_lpx_set_int_parm void lpx_set_int_parm(LPX *lp, int parm, int val); /* set (change) integer control parameter */ #define lpx_get_int_parm _glp_lpx_get_int_parm int lpx_get_int_parm(LPX *lp, int parm); /* query integer control parameter */ #define lpx_set_real_parm _glp_lpx_set_real_parm void lpx_set_real_parm(LPX *lp, int parm, double val); /* set (change) real control parameter */ #define lpx_get_real_parm _glp_lpx_get_real_parm double lpx_get_real_parm(LPX *lp, int parm); /* query real control parameter */ #define lpx_read_mps _glp_lpx_read_mps LPX *lpx_read_mps(const char *fname); /* read problem data in fixed MPS format */ #define lpx_write_mps _glp_lpx_write_mps int lpx_write_mps(LPX *lp, const char *fname); /* write problem data in fixed MPS format */ #define lpx_read_bas _glp_lpx_read_bas int lpx_read_bas(LPX *lp, const char *fname); /* read LP basis in fixed MPS format */ #define lpx_write_bas _glp_lpx_write_bas int lpx_write_bas(LPX *lp, const char *fname); /* write LP basis in fixed MPS format */ #define lpx_read_freemps _glp_lpx_read_freemps LPX *lpx_read_freemps(const char *fname); /* read problem data in free MPS format */ #define lpx_write_freemps _glp_lpx_write_freemps int lpx_write_freemps(LPX *lp, const char *fname); /* write problem data in free MPS format */ #define lpx_read_cpxlp _glp_lpx_read_cpxlp LPX *lpx_read_cpxlp(const char *fname); /* read problem data in CPLEX LP format */ #define lpx_write_cpxlp _glp_lpx_write_cpxlp int lpx_write_cpxlp(LPX *lp, const char *fname); /* write problem data in CPLEX LP format */ #define lpx_read_model _glp_lpx_read_model LPX *lpx_read_model(const char *model, const char *data, const char *output); /* read LP/MIP model written in GNU MathProg language */ #define lpx_print_prob _glp_lpx_print_prob int lpx_print_prob(LPX *lp, const char *fname); /* write problem data in plain text format */ #define lpx_print_sol _glp_lpx_print_sol int lpx_print_sol(LPX *lp, const char *fname); /* write LP problem solution in printable format */ #define lpx_print_sens_bnds _glp_lpx_print_sens_bnds int lpx_print_sens_bnds(LPX *lp, const char *fname); /* write bounds sensitivity information */ #define lpx_print_ips _glp_lpx_print_ips int lpx_print_ips(LPX *lp, const char *fname); /* write interior point solution in printable format */ #define lpx_print_mip _glp_lpx_print_mip int lpx_print_mip(LPX *lp, const char *fname); /* write MIP problem solution in printable format */ #define lpx_is_b_avail _glp_lpx_is_b_avail int lpx_is_b_avail(LPX *lp); /* check if LP basis is available */ #define lpx_write_pb _glp_lpx_write_pb int lpx_write_pb(LPX *lp, const char *fname, int normalized, int binarize); /* write problem data in (normalized) OPB format */ #define lpx_main _glp_lpx_main int lpx_main(int argc, const char *argv[]); /* stand-alone LP/MIP solver */ #ifdef __cplusplus } #endif #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpmat.c0000644000076500000240000010056213524616144025033 0ustar tamasstaff00000000000000/* glpmat.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wsign-conversion" #pragma clang diagnostic ignored "-Wshorten-64-to-32" #endif #include "glpenv.h" #include "glpmat.h" #include "glpqmd.h" #include "amd/amd.h" #include "colamd/colamd.h" /*---------------------------------------------------------------------- -- check_fvs - check sparse vector in full-vector storage format. -- -- SYNOPSIS -- -- #include "glpmat.h" -- int check_fvs(int n, int nnz, int ind[], double vec[]); -- -- DESCRIPTION -- -- The routine check_fvs checks if a given vector of dimension n in -- full-vector storage format has correct representation. -- -- RETURNS -- -- The routine returns one of the following codes: -- -- 0 - the vector is correct; -- 1 - the number of elements (n) is negative; -- 2 - the number of non-zero elements (nnz) is negative; -- 3 - some element index is out of range; -- 4 - some element index is duplicate; -- 5 - some non-zero element is out of pattern. */ int check_fvs(int n, int nnz, int ind[], double vec[]) { int i, t, ret, *flag = NULL; /* check the number of elements */ if (n < 0) { ret = 1; goto done; } /* check the number of non-zero elements */ if (nnz < 0) { ret = 2; goto done; } /* check vector indices */ flag = xcalloc(1+n, sizeof(int)); for (i = 1; i <= n; i++) flag[i] = 0; for (t = 1; t <= nnz; t++) { i = ind[t]; if (!(1 <= i && i <= n)) { ret = 3; goto done; } if (flag[i]) { ret = 4; goto done; } flag[i] = 1; } /* check vector elements */ for (i = 1; i <= n; i++) { if (!flag[i] && vec[i] != 0.0) { ret = 5; goto done; } } /* the vector is ok */ ret = 0; done: if (flag != NULL) xfree(flag); return ret; } /*---------------------------------------------------------------------- -- check_pattern - check pattern of sparse matrix. -- -- SYNOPSIS -- -- #include "glpmat.h" -- int check_pattern(int m, int n, int A_ptr[], int A_ind[]); -- -- DESCRIPTION -- -- The routine check_pattern checks the pattern of a given mxn matrix -- in storage-by-rows format. -- -- RETURNS -- -- The routine returns one of the following codes: -- -- 0 - the pattern is correct; -- 1 - the number of rows (m) is negative; -- 2 - the number of columns (n) is negative; -- 3 - A_ptr[1] is not 1; -- 4 - some column index is out of range; -- 5 - some column indices are duplicate. */ int check_pattern(int m, int n, int A_ptr[], int A_ind[]) { int i, j, ptr, ret, *flag = NULL; /* check the number of rows */ if (m < 0) { ret = 1; goto done; } /* check the number of columns */ if (n < 0) { ret = 2; goto done; } /* check location A_ptr[1] */ if (A_ptr[1] != 1) { ret = 3; goto done; } /* check row patterns */ flag = xcalloc(1+n, sizeof(int)); for (j = 1; j <= n; j++) flag[j] = 0; for (i = 1; i <= m; i++) { /* check pattern of row i */ for (ptr = A_ptr[i]; ptr < A_ptr[i+1]; ptr++) { j = A_ind[ptr]; /* check column index */ if (!(1 <= j && j <= n)) { ret = 4; goto done; } /* check for duplication */ if (flag[j]) { ret = 5; goto done; } flag[j] = 1; } /* clear flags */ for (ptr = A_ptr[i]; ptr < A_ptr[i+1]; ptr++) { j = A_ind[ptr]; flag[j] = 0; } } /* the pattern is ok */ ret = 0; done: if (flag != NULL) xfree(flag); return ret; } /*---------------------------------------------------------------------- -- transpose - transpose sparse matrix. -- -- *Synopsis* -- -- #include "glpmat.h" -- void transpose(int m, int n, int A_ptr[], int A_ind[], -- double A_val[], int AT_ptr[], int AT_ind[], double AT_val[]); -- -- *Description* -- -- For a given mxn sparse matrix A the routine transpose builds a nxm -- sparse matrix A' which is a matrix transposed to A. -- -- The arrays A_ptr, A_ind, and A_val specify a given mxn matrix A to -- be transposed in storage-by-rows format. The parameter A_val can be -- NULL, in which case numeric values are not copied. The arrays A_ptr, -- A_ind, and A_val are not changed on exit. -- -- On entry the arrays AT_ptr, AT_ind, and AT_val must be allocated, -- but their content is ignored. On exit the routine stores a resultant -- nxm matrix A' in these arrays in storage-by-rows format. Note that -- if the parameter A_val is NULL, the array AT_val is not used. -- -- The routine transpose has a side effect that elements in rows of the -- resultant matrix A' follow in ascending their column indices. */ void transpose(int m, int n, int A_ptr[], int A_ind[], double A_val[], int AT_ptr[], int AT_ind[], double AT_val[]) { int i, j, t, beg, end, pos, len; /* determine row lengths of resultant matrix */ for (j = 1; j <= n; j++) AT_ptr[j] = 0; for (i = 1; i <= m; i++) { beg = A_ptr[i], end = A_ptr[i+1]; for (t = beg; t < end; t++) AT_ptr[A_ind[t]]++; } /* set up row pointers of resultant matrix */ pos = 1; for (j = 1; j <= n; j++) len = AT_ptr[j], pos += len, AT_ptr[j] = pos; AT_ptr[n+1] = pos; /* build resultant matrix */ for (i = m; i >= 1; i--) { beg = A_ptr[i], end = A_ptr[i+1]; for (t = beg; t < end; t++) { pos = --AT_ptr[A_ind[t]]; AT_ind[pos] = i; if (A_val != NULL) AT_val[pos] = A_val[t]; } } return; } /*---------------------------------------------------------------------- -- adat_symbolic - compute S = P*A*D*A'*P' (symbolic phase). -- -- *Synopsis* -- -- #include "glpmat.h" -- int *adat_symbolic(int m, int n, int P_per[], int A_ptr[], -- int A_ind[], int S_ptr[]); -- -- *Description* -- -- The routine adat_symbolic implements the symbolic phase to compute -- symmetric matrix S = P*A*D*A'*P', where P is a permutation matrix, -- A is a given sparse matrix, D is a diagonal matrix, A' is a matrix -- transposed to A, P' is an inverse of P. -- -- The parameter m is the number of rows in A and the order of P. -- -- The parameter n is the number of columns in A and the order of D. -- -- The array P_per specifies permutation matrix P. It is not changed on -- exit. -- -- The arrays A_ptr and A_ind specify the pattern of matrix A. They are -- not changed on exit. -- -- On exit the routine stores the pattern of upper triangular part of -- matrix S without diagonal elements in the arrays S_ptr and S_ind in -- storage-by-rows format. The array S_ptr should be allocated on entry, -- however, its content is ignored. The array S_ind is allocated by the -- routine itself which returns a pointer to it. -- -- *Returns* -- -- The routine returns a pointer to the array S_ind. */ int *adat_symbolic(int m, int n, int P_per[], int A_ptr[], int A_ind[], int S_ptr[]) { int i, j, t, ii, jj, tt, k, size, len; int *S_ind, *AT_ptr, *AT_ind, *ind, *map, *temp; /* build the pattern of A', which is a matrix transposed to A, to efficiently access A in column-wise manner */ AT_ptr = xcalloc(1+n+1, sizeof(int)); AT_ind = xcalloc(A_ptr[m+1], sizeof(int)); transpose(m, n, A_ptr, A_ind, NULL, AT_ptr, AT_ind, NULL); /* allocate the array S_ind */ size = A_ptr[m+1] - 1; if (size < m) size = m; S_ind = xcalloc(1+size, sizeof(int)); /* allocate and initialize working arrays */ ind = xcalloc(1+m, sizeof(int)); map = xcalloc(1+m, sizeof(int)); for (jj = 1; jj <= m; jj++) map[jj] = 0; /* compute pattern of S; note that symbolically S = B*B', where B = P*A, B' is matrix transposed to B */ S_ptr[1] = 1; for (ii = 1; ii <= m; ii++) { /* compute pattern of ii-th row of S */ len = 0; i = P_per[ii]; /* i-th row of A = ii-th row of B */ for (t = A_ptr[i]; t < A_ptr[i+1]; t++) { k = A_ind[t]; /* walk through k-th column of A */ for (tt = AT_ptr[k]; tt < AT_ptr[k+1]; tt++) { j = AT_ind[tt]; jj = P_per[m+j]; /* j-th row of A = jj-th row of B */ /* a[i,k] != 0 and a[j,k] != 0 ergo s[ii,jj] != 0 */ if (ii < jj && !map[jj]) ind[++len] = jj, map[jj] = 1; } } /* now (ind) is pattern of ii-th row of S */ S_ptr[ii+1] = S_ptr[ii] + len; /* at least (S_ptr[ii+1] - 1) locations should be available in the array S_ind */ if (S_ptr[ii+1] - 1 > size) { temp = S_ind; size += size; S_ind = xcalloc(1+size, sizeof(int)); memcpy(&S_ind[1], &temp[1], (S_ptr[ii] - 1) * sizeof(int)); xfree(temp); } xassert(S_ptr[ii+1] - 1 <= size); /* (ii-th row of S) := (ind) */ memcpy(&S_ind[S_ptr[ii]], &ind[1], len * sizeof(int)); /* clear the row pattern map */ for (t = 1; t <= len; t++) map[ind[t]] = 0; } /* free working arrays */ xfree(AT_ptr); xfree(AT_ind); xfree(ind); xfree(map); /* reallocate the array S_ind to free unused locations */ temp = S_ind; size = S_ptr[m+1] - 1; S_ind = xcalloc(1+size, sizeof(int)); memcpy(&S_ind[1], &temp[1], size * sizeof(int)); xfree(temp); return S_ind; } /*---------------------------------------------------------------------- -- adat_numeric - compute S = P*A*D*A'*P' (numeric phase). -- -- *Synopsis* -- -- #include "glpmat.h" -- void adat_numeric(int m, int n, int P_per[], -- int A_ptr[], int A_ind[], double A_val[], double D_diag[], -- int S_ptr[], int S_ind[], double S_val[], double S_diag[]); -- -- *Description* -- -- The routine adat_numeric implements the numeric phase to compute -- symmetric matrix S = P*A*D*A'*P', where P is a permutation matrix, -- A is a given sparse matrix, D is a diagonal matrix, A' is a matrix -- transposed to A, P' is an inverse of P. -- -- The parameter m is the number of rows in A and the order of P. -- -- The parameter n is the number of columns in A and the order of D. -- -- The matrix P is specified in the array P_per, which is not changed -- on exit. -- -- The matrix A is specified in the arrays A_ptr, A_ind, and A_val in -- storage-by-rows format. These arrays are not changed on exit. -- -- Diagonal elements of the matrix D are specified in the array D_diag, -- where D_diag[0] is not used, D_diag[i] = d[i,i] for i = 1, ..., n. -- The array D_diag is not changed on exit. -- -- The pattern of the upper triangular part of the matrix S without -- diagonal elements (previously computed by the routine adat_symbolic) -- is specified in the arrays S_ptr and S_ind, which are not changed on -- exit. Numeric values of non-diagonal elements of S are stored in -- corresponding locations of the array S_val, and values of diagonal -- elements of S are stored in locations S_diag[1], ..., S_diag[n]. */ void adat_numeric(int m, int n, int P_per[], int A_ptr[], int A_ind[], double A_val[], double D_diag[], int S_ptr[], int S_ind[], double S_val[], double S_diag[]) { int i, j, t, ii, jj, tt, beg, end, beg1, end1, k; double sum, *work; work = xcalloc(1+n, sizeof(double)); for (j = 1; j <= n; j++) work[j] = 0.0; /* compute S = B*D*B', where B = P*A, B' is a matrix transposed to B */ for (ii = 1; ii <= m; ii++) { i = P_per[ii]; /* i-th row of A = ii-th row of B */ /* (work) := (i-th row of A) */ beg = A_ptr[i], end = A_ptr[i+1]; for (t = beg; t < end; t++) work[A_ind[t]] = A_val[t]; /* compute ii-th row of S */ beg = S_ptr[ii], end = S_ptr[ii+1]; for (t = beg; t < end; t++) { jj = S_ind[t]; j = P_per[jj]; /* j-th row of A = jj-th row of B */ /* s[ii,jj] := sum a[i,k] * d[k,k] * a[j,k] */ sum = 0.0; beg1 = A_ptr[j], end1 = A_ptr[j+1]; for (tt = beg1; tt < end1; tt++) { k = A_ind[tt]; sum += work[k] * D_diag[k] * A_val[tt]; } S_val[t] = sum; } /* s[ii,ii] := sum a[i,k] * d[k,k] * a[i,k] */ sum = 0.0; beg = A_ptr[i], end = A_ptr[i+1]; for (t = beg; t < end; t++) { k = A_ind[t]; sum += A_val[t] * D_diag[k] * A_val[t]; work[k] = 0.0; } S_diag[ii] = sum; } xfree(work); return; } /*---------------------------------------------------------------------- -- min_degree - minimum degree ordering. -- -- *Synopsis* -- -- #include "glpmat.h" -- void min_degree(int n, int A_ptr[], int A_ind[], int P_per[]); -- -- *Description* -- -- The routine min_degree uses the minimum degree ordering algorithm -- to find a permutation matrix P for a given sparse symmetric positive -- matrix A which minimizes the number of non-zeros in upper triangular -- factor U for Cholesky factorization P*A*P' = U'*U. -- -- The parameter n is the order of matrices A and P. -- -- The pattern of the given matrix A is specified on entry in the arrays -- A_ptr and A_ind in storage-by-rows format. Only the upper triangular -- part without diagonal elements (which all are assumed to be non-zero) -- should be specified as if A were upper triangular. The arrays A_ptr -- and A_ind are not changed on exit. -- -- The permutation matrix P is stored by the routine in the array P_per -- on exit. -- -- *Algorithm* -- -- The routine min_degree is based on some subroutines from the package -- SPARSPAK (see comments in the module glpqmd). */ void min_degree(int n, int A_ptr[], int A_ind[], int P_per[]) { int i, j, ne, t, pos, len; int *xadj, *adjncy, *deg, *marker, *rchset, *nbrhd, *qsize, *qlink, nofsub; /* determine number of non-zeros in complete pattern */ ne = A_ptr[n+1] - 1; ne += ne; /* allocate working arrays */ xadj = xcalloc(1+n+1, sizeof(int)); adjncy = xcalloc(1+ne, sizeof(int)); deg = xcalloc(1+n, sizeof(int)); marker = xcalloc(1+n, sizeof(int)); rchset = xcalloc(1+n, sizeof(int)); nbrhd = xcalloc(1+n, sizeof(int)); qsize = xcalloc(1+n, sizeof(int)); qlink = xcalloc(1+n, sizeof(int)); /* determine row lengths in complete pattern */ for (i = 1; i <= n; i++) xadj[i] = 0; for (i = 1; i <= n; i++) { for (t = A_ptr[i]; t < A_ptr[i+1]; t++) { j = A_ind[t]; xassert(i < j && j <= n); xadj[i]++, xadj[j]++; } } /* set up row pointers for complete pattern */ pos = 1; for (i = 1; i <= n; i++) len = xadj[i], pos += len, xadj[i] = pos; xadj[n+1] = pos; xassert(pos - 1 == ne); /* construct complete pattern */ for (i = 1; i <= n; i++) { for (t = A_ptr[i]; t < A_ptr[i+1]; t++) { j = A_ind[t]; adjncy[--xadj[i]] = j, adjncy[--xadj[j]] = i; } } /* call the main minimimum degree ordering routine */ genqmd(&n, xadj, adjncy, P_per, P_per + n, deg, marker, rchset, nbrhd, qsize, qlink, &nofsub); /* make sure that permutation matrix P is correct */ for (i = 1; i <= n; i++) { j = P_per[i]; xassert(1 <= j && j <= n); xassert(P_per[n+j] == i); } /* free working arrays */ xfree(xadj); xfree(adjncy); xfree(deg); xfree(marker); xfree(rchset); xfree(nbrhd); xfree(qsize); xfree(qlink); return; } /**********************************************************************/ void amd_order1(int n, int A_ptr[], int A_ind[], int P_per[]) { /* approximate minimum degree ordering (AMD) */ int k, ret; double Control[AMD_CONTROL], Info[AMD_INFO]; /* get the default parameters */ amd_defaults(Control); #if 0 /* and print them */ amd_control(Control); #endif /* make all indices 0-based */ for (k = 1; k < A_ptr[n+1]; k++) A_ind[k]--; for (k = 1; k <= n+1; k++) A_ptr[k]--; /* call the ordering routine */ ret = amd_order(n, &A_ptr[1], &A_ind[1], &P_per[1], Control, Info) ; #if 0 amd_info(Info); #endif xassert(ret == AMD_OK || ret == AMD_OK_BUT_JUMBLED); /* retsore 1-based indices */ for (k = 1; k <= n+1; k++) A_ptr[k]++; for (k = 1; k < A_ptr[n+1]; k++) A_ind[k]++; /* patch up permutation matrix */ memset(&P_per[n+1], 0, n * sizeof(int)); for (k = 1; k <= n; k++) { P_per[k]++; xassert(1 <= P_per[k] && P_per[k] <= n); xassert(P_per[n+P_per[k]] == 0); P_per[n+P_per[k]] = k; } return; } /**********************************************************************/ static void *allocate(size_t n, size_t size) { void *ptr; ptr = xcalloc(n, size); memset(ptr, 0, n * size); return ptr; } static void release(void *ptr) { xfree(ptr); return; } void symamd_ord(int n, int A_ptr[], int A_ind[], int P_per[]) { /* approximate minimum degree ordering (SYMAMD) */ int k, ok; int stats[COLAMD_STATS]; /* make all indices 0-based */ for (k = 1; k < A_ptr[n+1]; k++) A_ind[k]--; for (k = 1; k <= n+1; k++) A_ptr[k]--; /* call the ordering routine */ ok = symamd(n, &A_ind[1], &A_ptr[1], &P_per[1], NULL, stats, allocate, release); #if 0 symamd_report(stats); #endif xassert(ok); /* restore 1-based indices */ for (k = 1; k <= n+1; k++) A_ptr[k]++; for (k = 1; k < A_ptr[n+1]; k++) A_ind[k]++; /* patch up permutation matrix */ memset(&P_per[n+1], 0, n * sizeof(int)); for (k = 1; k <= n; k++) { P_per[k]++; xassert(1 <= P_per[k] && P_per[k] <= n); xassert(P_per[n+P_per[k]] == 0); P_per[n+P_per[k]] = k; } return; } /*---------------------------------------------------------------------- -- chol_symbolic - compute Cholesky factorization (symbolic phase). -- -- *Synopsis* -- -- #include "glpmat.h" -- int *chol_symbolic(int n, int A_ptr[], int A_ind[], int U_ptr[]); -- -- *Description* -- -- The routine chol_symbolic implements the symbolic phase of Cholesky -- factorization A = U'*U, where A is a given sparse symmetric positive -- definite matrix, U is a resultant upper triangular factor, U' is a -- matrix transposed to U. -- -- The parameter n is the order of matrices A and U. -- -- The pattern of the given matrix A is specified on entry in the arrays -- A_ptr and A_ind in storage-by-rows format. Only the upper triangular -- part without diagonal elements (which all are assumed to be non-zero) -- should be specified as if A were upper triangular. The arrays A_ptr -- and A_ind are not changed on exit. -- -- The pattern of the matrix U without diagonal elements (which all are -- assumed to be non-zero) is stored on exit from the routine in the -- arrays U_ptr and U_ind in storage-by-rows format. The array U_ptr -- should be allocated on entry, however, its content is ignored. The -- array U_ind is allocated by the routine which returns a pointer to it -- on exit. -- -- *Returns* -- -- The routine returns a pointer to the array U_ind. -- -- *Method* -- -- The routine chol_symbolic computes the pattern of the matrix U in a -- row-wise manner. No pivoting is used. -- -- It is known that to compute the pattern of row k of the matrix U we -- need to merge the pattern of row k of the matrix A and the patterns -- of each row i of U, where u[i,k] is non-zero (these rows are already -- computed and placed above row k). -- -- However, to reduce the number of rows to be merged the routine uses -- an advanced algorithm proposed in: -- -- D.J.Rose, R.E.Tarjan, and G.S.Lueker. Algorithmic aspects of vertex -- elimination on graphs. SIAM J. Comput. 5, 1976, 266-83. -- -- The authors of the cited paper show that we have the same result if -- we merge row k of the matrix A and such rows of the matrix U (among -- rows 1, ..., k-1) whose leftmost non-diagonal non-zero element is -- placed in k-th column. This feature signficantly reduces the number -- of rows to be merged, especially on the final steps, where rows of -- the matrix U become quite dense. -- -- To determine rows, which should be merged on k-th step, for a fixed -- time the routine uses linked lists of row numbers of the matrix U. -- Location head[k] contains the number of a first row, whose leftmost -- non-diagonal non-zero element is placed in column k, and location -- next[i] contains the number of a next row with the same property as -- row i. */ int *chol_symbolic(int n, int A_ptr[], int A_ind[], int U_ptr[]) { int i, j, k, t, len, size, beg, end, min_j, *U_ind, *head, *next, *ind, *map, *temp; /* initially we assume that on computing the pattern of U fill-in will double the number of non-zeros in A */ size = A_ptr[n+1] - 1; if (size < n) size = n; size += size; U_ind = xcalloc(1+size, sizeof(int)); /* allocate and initialize working arrays */ head = xcalloc(1+n, sizeof(int)); for (i = 1; i <= n; i++) head[i] = 0; next = xcalloc(1+n, sizeof(int)); ind = xcalloc(1+n, sizeof(int)); map = xcalloc(1+n, sizeof(int)); for (j = 1; j <= n; j++) map[j] = 0; /* compute the pattern of matrix U */ U_ptr[1] = 1; for (k = 1; k <= n; k++) { /* compute the pattern of k-th row of U, which is the union of k-th row of A and those rows of U (among 1, ..., k-1) whose leftmost non-diagonal non-zero is placed in k-th column */ /* (ind) := (k-th row of A) */ len = A_ptr[k+1] - A_ptr[k]; memcpy(&ind[1], &A_ind[A_ptr[k]], len * sizeof(int)); for (t = 1; t <= len; t++) { j = ind[t]; xassert(k < j && j <= n); map[j] = 1; } /* walk through rows of U whose leftmost non-diagonal non-zero is placed in k-th column */ for (i = head[k]; i != 0; i = next[i]) { /* (ind) := (ind) union (i-th row of U) */ beg = U_ptr[i], end = U_ptr[i+1]; for (t = beg; t < end; t++) { j = U_ind[t]; if (j > k && !map[j]) ind[++len] = j, map[j] = 1; } } /* now (ind) is the pattern of k-th row of U */ U_ptr[k+1] = U_ptr[k] + len; /* at least (U_ptr[k+1] - 1) locations should be available in the array U_ind */ if (U_ptr[k+1] - 1 > size) { temp = U_ind; size += size; U_ind = xcalloc(1+size, sizeof(int)); memcpy(&U_ind[1], &temp[1], (U_ptr[k] - 1) * sizeof(int)); xfree(temp); } xassert(U_ptr[k+1] - 1 <= size); /* (k-th row of U) := (ind) */ memcpy(&U_ind[U_ptr[k]], &ind[1], len * sizeof(int)); /* determine column index of leftmost non-diagonal non-zero in k-th row of U and clear the row pattern map */ min_j = n + 1; for (t = 1; t <= len; t++) { j = ind[t], map[j] = 0; if (min_j > j) min_j = j; } /* include k-th row into corresponding linked list */ if (min_j <= n) next[k] = head[min_j], head[min_j] = k; } /* free working arrays */ xfree(head); xfree(next); xfree(ind); xfree(map); /* reallocate the array U_ind to free unused locations */ temp = U_ind; size = U_ptr[n+1] - 1; U_ind = xcalloc(1+size, sizeof(int)); memcpy(&U_ind[1], &temp[1], size * sizeof(int)); xfree(temp); return U_ind; } /*---------------------------------------------------------------------- -- chol_numeric - compute Cholesky factorization (numeric phase). -- -- *Synopsis* -- -- #include "glpmat.h" -- int chol_numeric(int n, -- int A_ptr[], int A_ind[], double A_val[], double A_diag[], -- int U_ptr[], int U_ind[], double U_val[], double U_diag[]); -- -- *Description* -- -- The routine chol_symbolic implements the numeric phase of Cholesky -- factorization A = U'*U, where A is a given sparse symmetric positive -- definite matrix, U is a resultant upper triangular factor, U' is a -- matrix transposed to U. -- -- The parameter n is the order of matrices A and U. -- -- Upper triangular part of the matrix A without diagonal elements is -- specified in the arrays A_ptr, A_ind, and A_val in storage-by-rows -- format. Diagonal elements of A are specified in the array A_diag, -- where A_diag[0] is not used, A_diag[i] = a[i,i] for i = 1, ..., n. -- The arrays A_ptr, A_ind, A_val, and A_diag are not changed on exit. -- -- The pattern of the matrix U without diagonal elements (previously -- computed with the routine chol_symbolic) is specified in the arrays -- U_ptr and U_ind, which are not changed on exit. Numeric values of -- non-diagonal elements of U are stored in corresponding locations of -- the array U_val, and values of diagonal elements of U are stored in -- locations U_diag[1], ..., U_diag[n]. -- -- *Returns* -- -- The routine returns the number of non-positive diagonal elements of -- the matrix U which have been replaced by a huge positive number (see -- the method description below). Zero return code means the matrix A -- has been successfully factorized. -- -- *Method* -- -- The routine chol_numeric computes the matrix U in a row-wise manner -- using standard gaussian elimination technique. No pivoting is used. -- -- Initially the routine sets U = A, and before k-th elimination step -- the matrix U is the following: -- -- 1 k n -- 1 x x x x x x x x x x -- . x x x x x x x x x -- . . x x x x x x x x -- . . . x x x x x x x -- k . . . . * * * * * * -- . . . . * * * * * * -- . . . . * * * * * * -- . . . . * * * * * * -- . . . . * * * * * * -- n . . . . * * * * * * -- -- where 'x' are elements of already computed rows, '*' are elements of -- the active submatrix. (Note that the lower triangular part of the -- active submatrix being symmetric is not stored and diagonal elements -- are stored separately in the array U_diag.) -- -- The matrix A is assumed to be positive definite. However, if it is -- close to semi-definite, on some elimination step a pivot u[k,k] may -- happen to be non-positive due to round-off errors. In this case the -- routine uses a technique proposed in: -- -- S.J.Wright. The Cholesky factorization in interior-point and barrier -- methods. Preprint MCS-P600-0596, Mathematics and Computer Science -- Division, Argonne National Laboratory, Argonne, Ill., May 1996. -- -- The routine just replaces non-positive u[k,k] by a huge positive -- number. This involves non-diagonal elements in k-th row of U to be -- close to zero that, in turn, involves k-th component of a solution -- vector to be close to zero. Note, however, that this technique works -- only if the system A*x = b is consistent. */ int chol_numeric(int n, int A_ptr[], int A_ind[], double A_val[], double A_diag[], int U_ptr[], int U_ind[], double U_val[], double U_diag[]) { int i, j, k, t, t1, beg, end, beg1, end1, count = 0; double ukk, uki, *work; work = xcalloc(1+n, sizeof(double)); for (j = 1; j <= n; j++) work[j] = 0.0; /* U := (upper triangle of A) */ /* note that the upper traingle of A is a subset of U */ for (i = 1; i <= n; i++) { beg = A_ptr[i], end = A_ptr[i+1]; for (t = beg; t < end; t++) j = A_ind[t], work[j] = A_val[t]; beg = U_ptr[i], end = U_ptr[i+1]; for (t = beg; t < end; t++) j = U_ind[t], U_val[t] = work[j], work[j] = 0.0; U_diag[i] = A_diag[i]; } /* main elimination loop */ for (k = 1; k <= n; k++) { /* transform k-th row of U */ ukk = U_diag[k]; if (ukk > 0.0) U_diag[k] = ukk = sqrt(ukk); else U_diag[k] = ukk = DBL_MAX, count++; /* (work) := (transformed k-th row) */ beg = U_ptr[k], end = U_ptr[k+1]; for (t = beg; t < end; t++) work[U_ind[t]] = (U_val[t] /= ukk); /* transform other rows of U */ for (t = beg; t < end; t++) { i = U_ind[t]; xassert(i > k); /* (i-th row) := (i-th row) - u[k,i] * (k-th row) */ uki = work[i]; beg1 = U_ptr[i], end1 = U_ptr[i+1]; for (t1 = beg1; t1 < end1; t1++) U_val[t1] -= uki * work[U_ind[t1]]; U_diag[i] -= uki * uki; } /* (work) := 0 */ for (t = beg; t < end; t++) work[U_ind[t]] = 0.0; } xfree(work); return count; } /*---------------------------------------------------------------------- -- u_solve - solve upper triangular system U*x = b. -- -- *Synopsis* -- -- #include "glpmat.h" -- void u_solve(int n, int U_ptr[], int U_ind[], double U_val[], -- double U_diag[], double x[]); -- -- *Description* -- -- The routine u_solve solves an linear system U*x = b, where U is an -- upper triangular matrix. -- -- The parameter n is the order of matrix U. -- -- The matrix U without diagonal elements is specified in the arrays -- U_ptr, U_ind, and U_val in storage-by-rows format. Diagonal elements -- of U are specified in the array U_diag, where U_diag[0] is not used, -- U_diag[i] = u[i,i] for i = 1, ..., n. All these four arrays are not -- changed on exit. -- -- The right-hand side vector b is specified on entry in the array x, -- where x[0] is not used, and x[i] = b[i] for i = 1, ..., n. On exit -- the routine stores computed components of the vector of unknowns x -- in the array x in the same manner. */ void u_solve(int n, int U_ptr[], int U_ind[], double U_val[], double U_diag[], double x[]) { int i, t, beg, end; double temp; for (i = n; i >= 1; i--) { temp = x[i]; beg = U_ptr[i], end = U_ptr[i+1]; for (t = beg; t < end; t++) temp -= U_val[t] * x[U_ind[t]]; xassert(U_diag[i] != 0.0); x[i] = temp / U_diag[i]; } return; } /*---------------------------------------------------------------------- -- ut_solve - solve lower triangular system U'*x = b. -- -- *Synopsis* -- -- #include "glpmat.h" -- void ut_solve(int n, int U_ptr[], int U_ind[], double U_val[], -- double U_diag[], double x[]); -- -- *Description* -- -- The routine ut_solve solves an linear system U'*x = b, where U is a -- matrix transposed to an upper triangular matrix. -- -- The parameter n is the order of matrix U. -- -- The matrix U without diagonal elements is specified in the arrays -- U_ptr, U_ind, and U_val in storage-by-rows format. Diagonal elements -- of U are specified in the array U_diag, where U_diag[0] is not used, -- U_diag[i] = u[i,i] for i = 1, ..., n. All these four arrays are not -- changed on exit. -- -- The right-hand side vector b is specified on entry in the array x, -- where x[0] is not used, and x[i] = b[i] for i = 1, ..., n. On exit -- the routine stores computed components of the vector of unknowns x -- in the array x in the same manner. */ void ut_solve(int n, int U_ptr[], int U_ind[], double U_val[], double U_diag[], double x[]) { int i, t, beg, end; double temp; for (i = 1; i <= n; i++) { xassert(U_diag[i] != 0.0); temp = (x[i] /= U_diag[i]); if (temp == 0.0) continue; beg = U_ptr[i], end = U_ptr[i+1]; for (t = beg; t < end; t++) x[U_ind[t]] -= U_val[t] * temp; } return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpscl.c0000644000076500000240000003723213524616144025036 0ustar tamasstaff00000000000000/* glpscl.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glpapi.h" /*********************************************************************** * min_row_aij - determine minimal |a[i,j]| in i-th row * * This routine returns minimal magnitude of (non-zero) constraint * coefficients in i-th row of the constraint matrix. * * If the parameter scaled is zero, the original constraint matrix A is * assumed. Otherwise, the scaled constraint matrix R*A*S is assumed. * * If i-th row of the matrix is empty, the routine returns 1. */ static double min_row_aij(glp_prob *lp, int i, int scaled) { GLPAIJ *aij; double min_aij, temp; xassert(1 <= i && i <= lp->m); min_aij = 1.0; for (aij = lp->row[i]->ptr; aij != NULL; aij = aij->r_next) { temp = fabs(aij->val); if (scaled) temp *= (aij->row->rii * aij->col->sjj); if (aij->r_prev == NULL || min_aij > temp) min_aij = temp; } return min_aij; } /*********************************************************************** * max_row_aij - determine maximal |a[i,j]| in i-th row * * This routine returns maximal magnitude of (non-zero) constraint * coefficients in i-th row of the constraint matrix. * * If the parameter scaled is zero, the original constraint matrix A is * assumed. Otherwise, the scaled constraint matrix R*A*S is assumed. * * If i-th row of the matrix is empty, the routine returns 1. */ static double max_row_aij(glp_prob *lp, int i, int scaled) { GLPAIJ *aij; double max_aij, temp; xassert(1 <= i && i <= lp->m); max_aij = 1.0; for (aij = lp->row[i]->ptr; aij != NULL; aij = aij->r_next) { temp = fabs(aij->val); if (scaled) temp *= (aij->row->rii * aij->col->sjj); if (aij->r_prev == NULL || max_aij < temp) max_aij = temp; } return max_aij; } /*********************************************************************** * min_col_aij - determine minimal |a[i,j]| in j-th column * * This routine returns minimal magnitude of (non-zero) constraint * coefficients in j-th column of the constraint matrix. * * If the parameter scaled is zero, the original constraint matrix A is * assumed. Otherwise, the scaled constraint matrix R*A*S is assumed. * * If j-th column of the matrix is empty, the routine returns 1. */ static double min_col_aij(glp_prob *lp, int j, int scaled) { GLPAIJ *aij; double min_aij, temp; xassert(1 <= j && j <= lp->n); min_aij = 1.0; for (aij = lp->col[j]->ptr; aij != NULL; aij = aij->c_next) { temp = fabs(aij->val); if (scaled) temp *= (aij->row->rii * aij->col->sjj); if (aij->c_prev == NULL || min_aij > temp) min_aij = temp; } return min_aij; } /*********************************************************************** * max_col_aij - determine maximal |a[i,j]| in j-th column * * This routine returns maximal magnitude of (non-zero) constraint * coefficients in j-th column of the constraint matrix. * * If the parameter scaled is zero, the original constraint matrix A is * assumed. Otherwise, the scaled constraint matrix R*A*S is assumed. * * If j-th column of the matrix is empty, the routine returns 1. */ static double max_col_aij(glp_prob *lp, int j, int scaled) { GLPAIJ *aij; double max_aij, temp; xassert(1 <= j && j <= lp->n); max_aij = 1.0; for (aij = lp->col[j]->ptr; aij != NULL; aij = aij->c_next) { temp = fabs(aij->val); if (scaled) temp *= (aij->row->rii * aij->col->sjj); if (aij->c_prev == NULL || max_aij < temp) max_aij = temp; } return max_aij; } /*********************************************************************** * min_mat_aij - determine minimal |a[i,j]| in constraint matrix * * This routine returns minimal magnitude of (non-zero) constraint * coefficients in the constraint matrix. * * If the parameter scaled is zero, the original constraint matrix A is * assumed. Otherwise, the scaled constraint matrix R*A*S is assumed. * * If the matrix is empty, the routine returns 1. */ static double min_mat_aij(glp_prob *lp, int scaled) { int i; double min_aij, temp; min_aij = 1.0; for (i = 1; i <= lp->m; i++) { temp = min_row_aij(lp, i, scaled); if (i == 1 || min_aij > temp) min_aij = temp; } return min_aij; } /*********************************************************************** * max_mat_aij - determine maximal |a[i,j]| in constraint matrix * * This routine returns maximal magnitude of (non-zero) constraint * coefficients in the constraint matrix. * * If the parameter scaled is zero, the original constraint matrix A is * assumed. Otherwise, the scaled constraint matrix R*A*S is assumed. * * If the matrix is empty, the routine returns 1. */ static double max_mat_aij(glp_prob *lp, int scaled) { int i; double max_aij, temp; max_aij = 1.0; for (i = 1; i <= lp->m; i++) { temp = max_row_aij(lp, i, scaled); if (i == 1 || max_aij < temp) max_aij = temp; } return max_aij; } /*********************************************************************** * eq_scaling - perform equilibration scaling * * This routine performs equilibration scaling of rows and columns of * the constraint matrix. * * If the parameter flag is zero, the routine scales rows at first and * then columns. Otherwise, the routine scales columns and then rows. * * Rows are scaled as follows: * * n * a'[i,j] = a[i,j] / max |a[i,j]|, i = 1,...,m. * j=1 * * This makes the infinity (maximum) norm of each row of the matrix * equal to 1. * * Columns are scaled as follows: * * n * a'[i,j] = a[i,j] / max |a[i,j]|, j = 1,...,n. * i=1 * * This makes the infinity (maximum) norm of each column of the matrix * equal to 1. */ static void eq_scaling(glp_prob *lp, int flag) { int i, j, pass; double temp; xassert(flag == 0 || flag == 1); for (pass = 0; pass <= 1; pass++) { if (pass == flag) { /* scale rows */ for (i = 1; i <= lp->m; i++) { temp = max_row_aij(lp, i, 1); glp_set_rii(lp, i, glp_get_rii(lp, i) / temp); } } else { /* scale columns */ for (j = 1; j <= lp->n; j++) { temp = max_col_aij(lp, j, 1); glp_set_sjj(lp, j, glp_get_sjj(lp, j) / temp); } } } return; } /*********************************************************************** * gm_scaling - perform geometric mean scaling * * This routine performs geometric mean scaling of rows and columns of * the constraint matrix. * * If the parameter flag is zero, the routine scales rows at first and * then columns. Otherwise, the routine scales columns and then rows. * * Rows are scaled as follows: * * a'[i,j] = a[i,j] / sqrt(alfa[i] * beta[i]), i = 1,...,m, * * where: * n n * alfa[i] = min |a[i,j]|, beta[i] = max |a[i,j]|. * j=1 j=1 * * This allows decreasing the ratio beta[i] / alfa[i] for each row of * the matrix. * * Columns are scaled as follows: * * a'[i,j] = a[i,j] / sqrt(alfa[j] * beta[j]), j = 1,...,n, * * where: * m m * alfa[j] = min |a[i,j]|, beta[j] = max |a[i,j]|. * i=1 i=1 * * This allows decreasing the ratio beta[j] / alfa[j] for each column * of the matrix. */ static void gm_scaling(glp_prob *lp, int flag) { int i, j, pass; double temp; xassert(flag == 0 || flag == 1); for (pass = 0; pass <= 1; pass++) { if (pass == flag) { /* scale rows */ for (i = 1; i <= lp->m; i++) { temp = min_row_aij(lp, i, 1) * max_row_aij(lp, i, 1); glp_set_rii(lp, i, glp_get_rii(lp, i) / sqrt(temp)); } } else { /* scale columns */ for (j = 1; j <= lp->n; j++) { temp = min_col_aij(lp, j, 1) * max_col_aij(lp, j, 1); glp_set_sjj(lp, j, glp_get_sjj(lp, j) / sqrt(temp)); } } } return; } /*********************************************************************** * max_row_ratio - determine worst scaling "quality" for rows * * This routine returns the worst scaling "quality" for rows of the * currently scaled constraint matrix: * * m * ratio = max ratio[i], * i=1 * where: * n n * ratio[i] = max |a[i,j]| / min |a[i,j]|, 1 <= i <= m, * j=1 j=1 * * is the scaling "quality" of i-th row. */ static double max_row_ratio(glp_prob *lp) { int i; double ratio, temp; ratio = 1.0; for (i = 1; i <= lp->m; i++) { temp = max_row_aij(lp, i, 1) / min_row_aij(lp, i, 1); if (i == 1 || ratio < temp) ratio = temp; } return ratio; } /*********************************************************************** * max_col_ratio - determine worst scaling "quality" for columns * * This routine returns the worst scaling "quality" for columns of the * currently scaled constraint matrix: * * n * ratio = max ratio[j], * j=1 * where: * m m * ratio[j] = max |a[i,j]| / min |a[i,j]|, 1 <= j <= n, * i=1 i=1 * * is the scaling "quality" of j-th column. */ static double max_col_ratio(glp_prob *lp) { int j; double ratio, temp; ratio = 1.0; for (j = 1; j <= lp->n; j++) { temp = max_col_aij(lp, j, 1) / min_col_aij(lp, j, 1); if (j == 1 || ratio < temp) ratio = temp; } return ratio; } /*********************************************************************** * gm_iterate - perform iterative geometric mean scaling * * This routine performs iterative geometric mean scaling of rows and * columns of the constraint matrix. * * The parameter it_max specifies the maximal number of iterations. * Recommended value of it_max is 15. * * The parameter tau specifies a minimal improvement of the scaling * "quality" on each iteration, 0 < tau < 1. It means than the scaling * process continues while the following condition is satisfied: * * ratio[k] <= tau * ratio[k-1], * * where ratio = max |a[i,j]| / min |a[i,j]| is the scaling "quality" * to be minimized, k is the iteration number. Recommended value of tau * is 0.90. */ static void gm_iterate(glp_prob *lp, int it_max, double tau) { int k, flag; double ratio = 0.0, r_old; /* if the scaling "quality" for rows is better than for columns, the rows are scaled first; otherwise, the columns are scaled first */ flag = (max_row_ratio(lp) > max_col_ratio(lp)); for (k = 1; k <= it_max; k++) { /* save the scaling "quality" from previous iteration */ r_old = ratio; /* determine the current scaling "quality" */ ratio = max_mat_aij(lp, 1) / min_mat_aij(lp, 1); #if 0 xprintf("k = %d; ratio = %g\n", k, ratio); #endif /* if improvement is not enough, terminate scaling */ if (k > 1 && ratio > tau * r_old) break; /* otherwise, perform another iteration */ gm_scaling(lp, flag); } return; } /*********************************************************************** * NAME * * scale_prob - scale problem data * * SYNOPSIS * * #include "glpscl.h" * void scale_prob(glp_prob *lp, int flags); * * DESCRIPTION * * The routine scale_prob performs automatic scaling of problem data * for the specified problem object. */ static void scale_prob(glp_prob *lp, int flags) { static const char *fmt = "%s: min|aij| = %10.3e max|aij| = %10.3e ratio = %10.3e\n"; double min_aij, max_aij, ratio; xprintf("Scaling...\n"); /* cancel the current scaling effect */ glp_unscale_prob(lp); /* report original scaling "quality" */ min_aij = min_mat_aij(lp, 1); max_aij = max_mat_aij(lp, 1); ratio = max_aij / min_aij; xprintf(fmt, " A", min_aij, max_aij, ratio); /* check if the problem is well scaled */ if (min_aij >= 0.10 && max_aij <= 10.0) { xprintf("Problem data seem to be well scaled\n"); /* skip scaling, if required */ if (flags & GLP_SF_SKIP) goto done; } /* perform iterative geometric mean scaling, if required */ if (flags & GLP_SF_GM) { gm_iterate(lp, 15, 0.90); min_aij = min_mat_aij(lp, 1); max_aij = max_mat_aij(lp, 1); ratio = max_aij / min_aij; xprintf(fmt, "GM", min_aij, max_aij, ratio); } /* perform equilibration scaling, if required */ if (flags & GLP_SF_EQ) { eq_scaling(lp, max_row_ratio(lp) > max_col_ratio(lp)); min_aij = min_mat_aij(lp, 1); max_aij = max_mat_aij(lp, 1); ratio = max_aij / min_aij; xprintf(fmt, "EQ", min_aij, max_aij, ratio); } /* round scale factors to nearest power of two, if required */ if (flags & GLP_SF_2N) { int i, j; for (i = 1; i <= lp->m; i++) glp_set_rii(lp, i, round2n(glp_get_rii(lp, i))); for (j = 1; j <= lp->n; j++) glp_set_sjj(lp, j, round2n(glp_get_sjj(lp, j))); min_aij = min_mat_aij(lp, 1); max_aij = max_mat_aij(lp, 1); ratio = max_aij / min_aij; xprintf(fmt, "2N", min_aij, max_aij, ratio); } done: return; } /*********************************************************************** * NAME * * glp_scale_prob - scale problem data * * SYNOPSIS * * void glp_scale_prob(glp_prob *lp, int flags); * * DESCRIPTION * * The routine glp_scale_prob performs automatic scaling of problem * data for the specified problem object. * * The parameter flags specifies scaling options used by the routine. * Options can be combined with the bitwise OR operator and may be the * following: * * GLP_SF_GM perform geometric mean scaling; * GLP_SF_EQ perform equilibration scaling; * GLP_SF_2N round scale factors to nearest power of two; * GLP_SF_SKIP skip scaling, if the problem is well scaled. * * The parameter flags may be specified as GLP_SF_AUTO, in which case * the routine chooses scaling options automatically. */ void glp_scale_prob(glp_prob *lp, int flags) { if (flags & ~(GLP_SF_GM | GLP_SF_EQ | GLP_SF_2N | GLP_SF_SKIP | GLP_SF_AUTO)) xerror("glp_scale_prob: flags = 0x%02X; invalid scaling option" "s\n", flags); if (flags & GLP_SF_AUTO) flags = (GLP_SF_GM | GLP_SF_EQ | GLP_SF_SKIP); scale_prob(lp, flags); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpnpp.h0000644000076500000240000004331613524616144025057 0ustar tamasstaff00000000000000/* glpnpp.h (LP/MIP preprocessor) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPNPP_H #define GLPNPP_H #include "glpapi.h" typedef struct NPP NPP; typedef struct NPPROW NPPROW; typedef struct NPPCOL NPPCOL; typedef struct NPPAIJ NPPAIJ; typedef struct NPPTSE NPPTSE; typedef struct NPPLFE NPPLFE; struct NPP { /* LP/MIP preprocessor workspace */ /*--------------------------------------------------------------*/ /* original problem segment */ int orig_dir; /* optimization direction flag: GLP_MIN - minimization GLP_MAX - maximization */ int orig_m; /* number of rows */ int orig_n; /* number of columns */ int orig_nnz; /* number of non-zero constraint coefficients */ /*--------------------------------------------------------------*/ /* transformed problem segment (always minimization) */ DMP *pool; /* memory pool to store problem components */ char *name; /* problem name (1 to 255 chars); NULL means no name is assigned to the problem */ char *obj; /* objective function name (1 to 255 chars); NULL means no name is assigned to the objective function */ double c0; /* constant term of the objective function */ int nrows; /* number of rows introduced into the problem; this count increases by one every time a new row is added and never decreases; thus, actual number of rows may be less than nrows due to row deletions */ int ncols; /* number of columns introduced into the problem; this count increases by one every time a new column is added and never decreases; thus, actual number of column may be less than ncols due to column deletions */ NPPROW *r_head; /* pointer to the beginning of the row list */ NPPROW *r_tail; /* pointer to the end of the row list */ NPPCOL *c_head; /* pointer to the beginning of the column list */ NPPCOL *c_tail; /* pointer to the end of the column list */ /*--------------------------------------------------------------*/ /* transformation history */ DMP *stack; /* memory pool to store transformation entries */ NPPTSE *top; /* pointer to most recent transformation entry */ #if 0 /* 16/XII-2009 */ int count[1+25]; /* transformation statistics */ #endif /*--------------------------------------------------------------*/ /* resultant (preprocessed) problem segment */ int m; /* number of rows */ int n; /* number of columns */ int nnz; /* number of non-zero constraint coefficients */ int *row_ref; /* int row_ref[1+m]; */ /* row_ref[i], 1 <= i <= m, is the reference number assigned to a row, which is i-th row of the resultant problem */ int *col_ref; /* int col_ref[1+n]; */ /* col_ref[j], 1 <= j <= n, is the reference number assigned to a column, which is j-th column of the resultant problem */ /*--------------------------------------------------------------*/ /* recovered solution segment */ int sol; /* solution indicator: GLP_SOL - basic solution GLP_IPT - interior-point solution GLP_MIP - mixed integer solution */ int scaling; /* scaling option: GLP_OFF - scaling is disabled GLP_ON - scaling is enabled */ int p_stat; /* status of primal basic solution: GLP_UNDEF - primal solution is undefined GLP_FEAS - primal solution is feasible GLP_INFEAS - primal solution is infeasible GLP_NOFEAS - no primal feasible solution exists */ int d_stat; /* status of dual basic solution: GLP_UNDEF - dual solution is undefined GLP_FEAS - dual solution is feasible GLP_INFEAS - dual solution is infeasible GLP_NOFEAS - no dual feasible solution exists */ int t_stat; /* status of interior-point solution: GLP_UNDEF - interior solution is undefined GLP_OPT - interior solution is optimal */ int i_stat; /* status of mixed integer solution: GLP_UNDEF - integer solution is undefined GLP_OPT - integer solution is optimal GLP_FEAS - integer solution is feasible GLP_NOFEAS - no integer solution exists */ char *r_stat; /* char r_stat[1+nrows]; */ /* r_stat[i], 1 <= i <= nrows, is status of i-th row: GLP_BS - inactive constraint GLP_NL - active constraint on lower bound GLP_NU - active constraint on upper bound GLP_NF - active free row GLP_NS - active equality constraint */ char *c_stat; /* char c_stat[1+nrows]; */ /* c_stat[j], 1 <= j <= nrows, is status of j-th column: GLP_BS - basic variable GLP_NL - non-basic variable on lower bound GLP_NU - non-basic variable on upper bound GLP_NF - non-basic free variable GLP_NS - non-basic fixed variable */ double *r_pi; /* double r_pi[1+nrows]; */ /* r_pi[i], 1 <= i <= nrows, is Lagrange multiplier (dual value) for i-th row (constraint) */ double *c_value; /* double c_value[1+ncols]; */ /* c_value[j], 1 <= j <= ncols, is primal value of j-th column (structural variable) */ }; struct NPPROW { /* row (constraint) */ int i; /* reference number assigned to the row, 1 <= i <= nrows */ char *name; /* row name (1 to 255 chars); NULL means no name is assigned to the row */ double lb; /* lower bound; -DBL_MAX means the row has no lower bound */ double ub; /* upper bound; +DBL_MAX means the row has no upper bound */ NPPAIJ *ptr; /* pointer to the linked list of constraint coefficients */ int temp; /* working field used by preprocessor routines */ NPPROW *prev; /* pointer to previous row in the row list */ NPPROW *next; /* pointer to next row in the row list */ }; struct NPPCOL { /* column (variable) */ int j; /* reference number assigned to the column, 1 <= j <= ncols */ char *name; /* column name (1 to 255 chars); NULL means no name is assigned to the column */ char is_int; /* 0 means continuous variable; 1 means integer variable */ double lb; /* lower bound; -DBL_MAX means the column has no lower bound */ double ub; /* upper bound; +DBL_MAX means the column has no upper bound */ double coef; /* objective coefficient */ NPPAIJ *ptr; /* pointer to the linked list of constraint coefficients */ int temp; /* working field used by preprocessor routines */ #if 1 /* 28/XII-2009 */ union { double ll; /* implied column lower bound */ int pos; /* vertex ordinal number corresponding to this binary column in the conflict graph (0, if the vertex does not exist) */ } ll; union { double uu; /* implied column upper bound */ int neg; /* vertex ordinal number corresponding to complement of this binary column in the conflict graph (0, if the vertex does not exist) */ } uu; #endif NPPCOL *prev; /* pointer to previous column in the column list */ NPPCOL *next; /* pointer to next column in the column list */ }; struct NPPAIJ { /* constraint coefficient */ NPPROW *row; /* pointer to corresponding row */ NPPCOL *col; /* pointer to corresponding column */ double val; /* (non-zero) coefficient value */ NPPAIJ *r_prev; /* pointer to previous coefficient in the same row */ NPPAIJ *r_next; /* pointer to next coefficient in the same row */ NPPAIJ *c_prev; /* pointer to previous coefficient in the same column */ NPPAIJ *c_next; /* pointer to next coefficient in the same column */ }; struct NPPTSE { /* transformation stack entry */ int (*func)(NPP *npp, void *info); /* pointer to routine performing back transformation */ void *info; /* pointer to specific info (depends on the transformation) */ NPPTSE *link; /* pointer to another entry created *before* this entry */ }; struct NPPLFE { /* linear form element */ int ref; /* row/column reference number */ double val; /* (non-zero) coefficient value */ NPPLFE *next; /* pointer to another element */ }; #define npp_create_wksp _glp_npp_create_wksp NPP *npp_create_wksp(void); /* create LP/MIP preprocessor workspace */ #define npp_insert_row _glp_npp_insert_row void npp_insert_row(NPP *npp, NPPROW *row, int where); /* insert row to the row list */ #define npp_remove_row _glp_npp_remove_row void npp_remove_row(NPP *npp, NPPROW *row); /* remove row from the row list */ #define npp_activate_row _glp_npp_activate_row void npp_activate_row(NPP *npp, NPPROW *row); /* make row active */ #define npp_deactivate_row _glp_npp_deactivate_row void npp_deactivate_row(NPP *npp, NPPROW *row); /* make row inactive */ #define npp_insert_col _glp_npp_insert_col void npp_insert_col(NPP *npp, NPPCOL *col, int where); /* insert column to the column list */ #define npp_remove_col _glp_npp_remove_col void npp_remove_col(NPP *npp, NPPCOL *col); /* remove column from the column list */ #define npp_activate_col _glp_npp_activate_col void npp_activate_col(NPP *npp, NPPCOL *col); /* make column active */ #define npp_deactivate_col _glp_npp_deactivate_col void npp_deactivate_col(NPP *npp, NPPCOL *col); /* make column inactive */ #define npp_add_row _glp_npp_add_row NPPROW *npp_add_row(NPP *npp); /* add new row to the current problem */ #define npp_add_col _glp_npp_add_col NPPCOL *npp_add_col(NPP *npp); /* add new column to the current problem */ #define npp_add_aij _glp_npp_add_aij NPPAIJ *npp_add_aij(NPP *npp, NPPROW *row, NPPCOL *col, double val); /* add new element to the constraint matrix */ #define npp_row_nnz _glp_npp_row_nnz int npp_row_nnz(NPP *npp, NPPROW *row); /* count number of non-zero coefficients in row */ #define npp_col_nnz _glp_npp_col_nnz int npp_col_nnz(NPP *npp, NPPCOL *col); /* count number of non-zero coefficients in column */ #define npp_push_tse _glp_npp_push_tse void *npp_push_tse(NPP *npp, int (*func)(NPP *npp, void *info), int size); /* push new entry to the transformation stack */ #define npp_erase_row _glp_npp_erase_row void npp_erase_row(NPP *npp, NPPROW *row); /* erase row content to make it empty */ #define npp_del_row _glp_npp_del_row void npp_del_row(NPP *npp, NPPROW *row); /* remove row from the current problem */ #define npp_del_col _glp_npp_del_col void npp_del_col(NPP *npp, NPPCOL *col); /* remove column from the current problem */ #define npp_del_aij _glp_npp_del_aij void npp_del_aij(NPP *npp, NPPAIJ *aij); /* remove element from the constraint matrix */ #define npp_load_prob _glp_npp_load_prob void npp_load_prob(NPP *npp, glp_prob *orig, int names, int sol, int scaling); /* load original problem into the preprocessor workspace */ #define npp_build_prob _glp_npp_build_prob void npp_build_prob(NPP *npp, glp_prob *prob); /* build resultant (preprocessed) problem */ #define npp_postprocess _glp_npp_postprocess void npp_postprocess(NPP *npp, glp_prob *prob); /* postprocess solution from the resultant problem */ #define npp_unload_sol _glp_npp_unload_sol void npp_unload_sol(NPP *npp, glp_prob *orig); /* store solution to the original problem */ #define npp_delete_wksp _glp_npp_delete_wksp void npp_delete_wksp(NPP *npp); /* delete LP/MIP preprocessor workspace */ #define npp_error() #define npp_free_row _glp_npp_free_row void npp_free_row(NPP *npp, NPPROW *p); /* process free (unbounded) row */ #define npp_geq_row _glp_npp_geq_row void npp_geq_row(NPP *npp, NPPROW *p); /* process row of 'not less than' type */ #define npp_leq_row _glp_npp_leq_row void npp_leq_row(NPP *npp, NPPROW *p); /* process row of 'not greater than' type */ #define npp_free_col _glp_npp_free_col void npp_free_col(NPP *npp, NPPCOL *q); /* process free (unbounded) column */ #define npp_lbnd_col _glp_npp_lbnd_col void npp_lbnd_col(NPP *npp, NPPCOL *q); /* process column with (non-zero) lower bound */ #define npp_ubnd_col _glp_npp_ubnd_col void npp_ubnd_col(NPP *npp, NPPCOL *q); /* process column with upper bound */ #define npp_dbnd_col _glp_npp_dbnd_col void npp_dbnd_col(NPP *npp, NPPCOL *q); /* process non-negative column with upper bound */ #define npp_fixed_col _glp_npp_fixed_col void npp_fixed_col(NPP *npp, NPPCOL *q); /* process fixed column */ #define npp_make_equality _glp_npp_make_equality int npp_make_equality(NPP *npp, NPPROW *p); /* process row with almost identical bounds */ #define npp_make_fixed _glp_npp_make_fixed int npp_make_fixed(NPP *npp, NPPCOL *q); /* process column with almost identical bounds */ #define npp_empty_row _glp_npp_empty_row int npp_empty_row(NPP *npp, NPPROW *p); /* process empty row */ #define npp_empty_col _glp_npp_empty_col int npp_empty_col(NPP *npp, NPPCOL *q); /* process empty column */ #define npp_implied_value _glp_npp_implied_value int npp_implied_value(NPP *npp, NPPCOL *q, double s); /* process implied column value */ #define npp_eq_singlet _glp_npp_eq_singlet int npp_eq_singlet(NPP *npp, NPPROW *p); /* process row singleton (equality constraint) */ #define npp_implied_lower _glp_npp_implied_lower int npp_implied_lower(NPP *npp, NPPCOL *q, double l); /* process implied column lower bound */ #define npp_implied_upper _glp_npp_implied_upper int npp_implied_upper(NPP *npp, NPPCOL *q, double u); /* process implied upper bound of column */ #define npp_ineq_singlet _glp_npp_ineq_singlet int npp_ineq_singlet(NPP *npp, NPPROW *p); /* process row singleton (inequality constraint) */ #define npp_implied_slack _glp_npp_implied_slack void npp_implied_slack(NPP *npp, NPPCOL *q); /* process column singleton (implied slack variable) */ #define npp_implied_free _glp_npp_implied_free int npp_implied_free(NPP *npp, NPPCOL *q); /* process column singleton (implied free variable) */ #define npp_eq_doublet _glp_npp_eq_doublet NPPCOL *npp_eq_doublet(NPP *npp, NPPROW *p); /* process row doubleton (equality constraint) */ #define npp_forcing_row _glp_npp_forcing_row int npp_forcing_row(NPP *npp, NPPROW *p, int at); /* process forcing row */ #define npp_analyze_row _glp_npp_analyze_row int npp_analyze_row(NPP *npp, NPPROW *p); /* perform general row analysis */ #define npp_inactive_bound _glp_npp_inactive_bound void npp_inactive_bound(NPP *npp, NPPROW *p, int which); /* remove row lower/upper inactive bound */ #define npp_implied_bounds _glp_npp_implied_bounds void npp_implied_bounds(NPP *npp, NPPROW *p); /* determine implied column bounds */ #define npp_binarize_prob _glp_npp_binarize_prob int npp_binarize_prob(NPP *npp); /* binarize MIP problem */ #define npp_is_packing _glp_npp_is_packing int npp_is_packing(NPP *npp, NPPROW *row); /* test if constraint is packing inequality */ #define npp_hidden_packing _glp_npp_hidden_packing int npp_hidden_packing(NPP *npp, NPPROW *row); /* identify hidden packing inequality */ #define npp_implied_packing _glp_npp_implied_packing int npp_implied_packing(NPP *npp, NPPROW *row, int which, NPPCOL *var[], char set[]); /* identify implied packing inequality */ #define npp_is_covering _glp_npp_is_covering int npp_is_covering(NPP *npp, NPPROW *row); /* test if constraint is covering inequality */ #define npp_hidden_covering _glp_npp_hidden_covering int npp_hidden_covering(NPP *npp, NPPROW *row); /* identify hidden covering inequality */ #define npp_is_partitioning _glp_npp_is_partitioning int npp_is_partitioning(NPP *npp, NPPROW *row); /* test if constraint is partitioning equality */ #define npp_reduce_ineq_coef _glp_npp_reduce_ineq_coef int npp_reduce_ineq_coef(NPP *npp, NPPROW *row); /* reduce inequality constraint coefficients */ #define npp_clean_prob _glp_npp_clean_prob void npp_clean_prob(NPP *npp); /* perform initial LP/MIP processing */ #define npp_process_row _glp_npp_process_row int npp_process_row(NPP *npp, NPPROW *row, int hard); /* perform basic row processing */ #define npp_improve_bounds _glp_npp_improve_bounds int npp_improve_bounds(NPP *npp, NPPROW *row, int flag); /* improve current column bounds */ #define npp_process_col _glp_npp_process_col int npp_process_col(NPP *npp, NPPCOL *col); /* perform basic column processing */ #define npp_process_prob _glp_npp_process_prob int npp_process_prob(NPP *npp, int hard); /* perform basic LP/MIP processing */ #define npp_simplex _glp_npp_simplex int npp_simplex(NPP *npp, const glp_smcp *parm); /* process LP prior to applying primal/dual simplex method */ #define npp_integer _glp_npp_integer int npp_integer(NPP *npp, const glp_iocp *parm); /* process MIP prior to applying branch-and-bound method */ #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpscf.c0000644000076500000240000004770513524616144025036 0ustar tamasstaff00000000000000/* glpscf.c (Schur complement factorization) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wself-assign" #endif #include "glpenv.h" #include "glpscf.h" #define xfault xerror #define _GLPSCF_DEBUG 0 #define eps 1e-10 /*********************************************************************** * NAME * * scf_create_it - create Schur complement factorization * * SYNOPSIS * * #include "glpscf.h" * SCF *scf_create_it(int n_max); * * DESCRIPTION * * The routine scf_create_it creates the factorization of matrix C, * which initially has no rows and columns. * * The parameter n_max specifies the maximal order of matrix C to be * factorized, 1 <= n_max <= 32767. * * RETURNS * * The routine scf_create_it returns a pointer to the structure SCF, * which defines the factorization. */ SCF *scf_create_it(int n_max) { SCF *scf; #if _GLPSCF_DEBUG xprintf("scf_create_it: warning: debug mode enabled\n"); #endif if (!(1 <= n_max && n_max <= 32767)) xfault("scf_create_it: n_max = %d; invalid parameter\n", n_max); scf = xmalloc(sizeof(SCF)); scf->n_max = n_max; scf->n = 0; scf->f = xcalloc(1 + n_max * n_max, sizeof(double)); scf->u = xcalloc(1 + n_max * (n_max + 1) / 2, sizeof(double)); scf->p = xcalloc(1 + n_max, sizeof(int)); scf->t_opt = SCF_TBG; scf->rank = 0; #if _GLPSCF_DEBUG scf->c = xcalloc(1 + n_max * n_max, sizeof(double)); #else scf->c = NULL; #endif scf->w = xcalloc(1 + n_max, sizeof(double)); return scf; } /*********************************************************************** * The routine f_loc determines location of matrix element F[i,j] in * the one-dimensional array f. */ static int f_loc(SCF *scf, int i, int j) { int n_max = scf->n_max; int n = scf->n; xassert(1 <= i && i <= n); xassert(1 <= j && j <= n); return (i - 1) * n_max + j; } /*********************************************************************** * The routine u_loc determines location of matrix element U[i,j] in * the one-dimensional array u. */ static int u_loc(SCF *scf, int i, int j) { int n_max = scf->n_max; int n = scf->n; xassert(1 <= i && i <= n); xassert(i <= j && j <= n); return (i - 1) * n_max + j - i * (i - 1) / 2; } /*********************************************************************** * The routine bg_transform applies Bartels-Golub version of gaussian * elimination to restore triangular structure of matrix U. * * On entry matrix U has the following structure: * * 1 k n * 1 * * * * * * * * * * * . * * * * * * * * * * . . * * * * * * * * * . . . * * * * * * * * k . . . . * * * * * * * . . . . . * * * * * * . . . . . . * * * * * . . . . . . . * * * * . . . . . . . . * * * n . . . . # # # # # # * * where '#' is a row spike to be eliminated. * * Elements of n-th row are passed separately in locations un[k], ..., * un[n]. On exit the content of the array un is destroyed. * * REFERENCES * * R.H.Bartels, G.H.Golub, "The Simplex Method of Linear Programming * Using LU-decomposition", Comm. ACM, 12, pp. 266-68, 1969. */ static void bg_transform(SCF *scf, int k, double un[]) { int n = scf->n; double *f = scf->f; double *u = scf->u; int j, k1, kj, kk, n1, nj; double t; xassert(1 <= k && k <= n); /* main elimination loop */ for (k = k; k < n; k++) { /* determine location of U[k,k] */ kk = u_loc(scf, k, k); /* determine location of F[k,1] */ k1 = f_loc(scf, k, 1); /* determine location of F[n,1] */ n1 = f_loc(scf, n, 1); /* if |U[k,k]| < |U[n,k]|, interchange k-th and n-th rows to provide |U[k,k]| >= |U[n,k]| */ if (fabs(u[kk]) < fabs(un[k])) { /* interchange k-th and n-th rows of matrix U */ for (j = k, kj = kk; j <= n; j++, kj++) t = u[kj], u[kj] = un[j], un[j] = t; /* interchange k-th and n-th rows of matrix F to keep the main equality F * C = U * P */ for (j = 1, kj = k1, nj = n1; j <= n; j++, kj++, nj++) t = f[kj], f[kj] = f[nj], f[nj] = t; } /* now |U[k,k]| >= |U[n,k]| */ /* if U[k,k] is too small in the magnitude, replace U[k,k] and U[n,k] by exact zero */ if (fabs(u[kk]) < eps) u[kk] = un[k] = 0.0; /* if U[n,k] is already zero, elimination is not needed */ if (un[k] == 0.0) continue; /* compute gaussian multiplier t = U[n,k] / U[k,k] */ t = un[k] / u[kk]; /* apply gaussian elimination to nullify U[n,k] */ /* (n-th row of U) := (n-th row of U) - t * (k-th row of U) */ for (j = k+1, kj = kk+1; j <= n; j++, kj++) un[j] -= t * u[kj]; /* (n-th row of F) := (n-th row of F) - t * (k-th row of F) to keep the main equality F * C = U * P */ for (j = 1, kj = k1, nj = n1; j <= n; j++, kj++, nj++) f[nj] -= t * f[kj]; } /* if U[n,n] is too small in the magnitude, replace it by exact zero */ if (fabs(un[n]) < eps) un[n] = 0.0; /* store U[n,n] in a proper location */ u[u_loc(scf, n, n)] = un[n]; return; } /*********************************************************************** * The routine givens computes the parameters of Givens plane rotation * c = cos(teta) and s = sin(teta) such that: * * ( c -s ) ( a ) ( r ) * ( ) ( ) = ( ) , * ( s c ) ( b ) ( 0 ) * * where a and b are given scalars. * * REFERENCES * * G.H.Golub, C.F.Van Loan, "Matrix Computations", 2nd ed. */ static void givens(double a, double b, double *c, double *s) { double t; if (b == 0.0) (*c) = 1.0, (*s) = 0.0; else if (fabs(a) <= fabs(b)) t = - a / b, (*s) = 1.0 / sqrt(1.0 + t * t), (*c) = (*s) * t; else t = - b / a, (*c) = 1.0 / sqrt(1.0 + t * t), (*s) = (*c) * t; return; } /*---------------------------------------------------------------------- * The routine gr_transform applies Givens plane rotations to restore * triangular structure of matrix U. * * On entry matrix U has the following structure: * * 1 k n * 1 * * * * * * * * * * * . * * * * * * * * * * . . * * * * * * * * * . . . * * * * * * * * k . . . . * * * * * * * . . . . . * * * * * * . . . . . . * * * * * . . . . . . . * * * * . . . . . . . . * * * n . . . . # # # # # # * * where '#' is a row spike to be eliminated. * * Elements of n-th row are passed separately in locations un[k], ..., * un[n]. On exit the content of the array un is destroyed. * * REFERENCES * * R.H.Bartels, G.H.Golub, "The Simplex Method of Linear Programming * Using LU-decomposition", Comm. ACM, 12, pp. 266-68, 1969. */ static void gr_transform(SCF *scf, int k, double un[]) { int n = scf->n; double *f = scf->f; double *u = scf->u; int j, k1, kj, kk, n1, nj; double c, s; xassert(1 <= k && k <= n); /* main elimination loop */ for (k = k; k < n; k++) { /* determine location of U[k,k] */ kk = u_loc(scf, k, k); /* determine location of F[k,1] */ k1 = f_loc(scf, k, 1); /* determine location of F[n,1] */ n1 = f_loc(scf, n, 1); /* if both U[k,k] and U[n,k] are too small in the magnitude, replace them by exact zero */ if (fabs(u[kk]) < eps && fabs(un[k]) < eps) u[kk] = un[k] = 0.0; /* if U[n,k] is already zero, elimination is not needed */ if (un[k] == 0.0) continue; /* compute the parameters of Givens plane rotation */ givens(u[kk], un[k], &c, &s); /* apply Givens rotation to k-th and n-th rows of matrix U */ for (j = k, kj = kk; j <= n; j++, kj++) { double ukj = u[kj], unj = un[j]; u[kj] = c * ukj - s * unj; un[j] = s * ukj + c * unj; } /* apply Givens rotation to k-th and n-th rows of matrix F to keep the main equality F * C = U * P */ for (j = 1, kj = k1, nj = n1; j <= n; j++, kj++, nj++) { double fkj = f[kj], fnj = f[nj]; f[kj] = c * fkj - s * fnj; f[nj] = s * fkj + c * fnj; } } /* if U[n,n] is too small in the magnitude, replace it by exact zero */ if (fabs(un[n]) < eps) un[n] = 0.0; /* store U[n,n] in a proper location */ u[u_loc(scf, n, n)] = un[n]; return; } /*********************************************************************** * The routine transform restores triangular structure of matrix U. * It is a driver to the routines bg_transform and gr_transform (see * comments to these routines above). */ static void transform(SCF *scf, int k, double un[]) { switch (scf->t_opt) { case SCF_TBG: bg_transform(scf, k, un); break; case SCF_TGR: gr_transform(scf, k, un); break; default: xassert(scf != scf); } return; } /*********************************************************************** * The routine estimate_rank estimates the rank of matrix C. * * Since all transformations applied to matrix F are non-singular, * and F is assumed to be well conditioned, from the main equaility * F * C = U * P it follows that rank(C) = rank(U), where rank(U) is * estimated as the number of non-zero diagonal elements of U. */ static int estimate_rank(SCF *scf) { int n_max = scf->n_max; int n = scf->n; double *u = scf->u; int i, ii, inc, rank = 0; for (i = 1, ii = u_loc(scf, i, i), inc = n_max; i <= n; i++, ii += inc, inc--) if (u[ii] != 0.0) rank++; return rank; } #if _GLPSCF_DEBUG /*********************************************************************** * The routine check_error computes the maximal relative error between * left- and right-hand sides of the main equality F * C = U * P. (This * routine is intended only for debugging.) */ static void check_error(SCF *scf, const char *func) { int n = scf->n; double *f = scf->f; double *u = scf->u; int *p = scf->p; double *c = scf->c; int i, j, k; double d, dmax = 0.0, s, t; xassert(c != NULL); for (i = 1; i <= n; i++) { for (j = 1; j <= n; j++) { /* compute element (i,j) of product F * C */ s = 0.0; for (k = 1; k <= n; k++) s += f[f_loc(scf, i, k)] * c[f_loc(scf, k, j)]; /* compute element (i,j) of product U * P */ k = p[j]; t = (i <= k ? u[u_loc(scf, i, k)] : 0.0); /* compute the maximal relative error */ d = fabs(s - t) / (1.0 + fabs(t)); if (dmax < d) dmax = d; } } if (dmax > 1e-8) xprintf("%s: dmax = %g; relative error too large\n", func, dmax); return; } #endif /*********************************************************************** * NAME * * scf_update_exp - update factorization on expanding C * * SYNOPSIS * * #include "glpscf.h" * int scf_update_exp(SCF *scf, const double x[], const double y[], * double z); * * DESCRIPTION * * The routine scf_update_exp updates the factorization of matrix C on * expanding it by adding a new row and column as follows: * * ( C x ) * new C = ( ) * ( y' z ) * * where x[1,...,n] is a new column, y[1,...,n] is a new row, and z is * a new diagonal element. * * If on entry the factorization is empty, the parameters x and y can * be specified as NULL. * * RETURNS * * 0 The factorization has been successfully updated. * * SCF_ESING * The factorization has been successfully updated, however, new * matrix C is singular within working precision. Note that the new * factorization remains valid. * * SCF_ELIMIT * There is not enough room to expand the factorization, because * n = n_max. The factorization remains unchanged. * * ALGORITHM * * We can see that: * * ( F 0 ) ( C x ) ( FC Fx ) ( UP Fx ) * ( ) ( ) = ( ) = ( ) = * ( 0 1 ) ( y' z ) ( y' z ) ( y' z ) * * ( U Fx ) ( P 0 ) * = ( ) ( ), * ( y'P' z ) ( 0 1 ) * * therefore to keep the main equality F * C = U * P we can take: * * ( F 0 ) ( U Fx ) ( P 0 ) * new F = ( ), new U = ( ), new P = ( ), * ( 0 1 ) ( y'P' z ) ( 0 1 ) * * and eliminate the row spike y'P' in the last row of new U to restore * its upper triangular structure. */ int scf_update_exp(SCF *scf, const double x[], const double y[], double z) { int n_max = scf->n_max; int n = scf->n; double *f = scf->f; double *u = scf->u; int *p = scf->p; #if _GLPSCF_DEBUG double *c = scf->c; #endif double *un = scf->w; int i, ij, in, j, k, nj, ret = 0; double t; /* check if the factorization can be expanded */ if (n == n_max) { /* there is not enough room */ ret = SCF_ELIMIT; goto done; } /* increase the order of the factorization */ scf->n = ++n; /* fill new zero column of matrix F */ for (i = 1, in = f_loc(scf, i, n); i < n; i++, in += n_max) f[in] = 0.0; /* fill new zero row of matrix F */ for (j = 1, nj = f_loc(scf, n, j); j < n; j++, nj++) f[nj] = 0.0; /* fill new unity diagonal element of matrix F */ f[f_loc(scf, n, n)] = 1.0; /* compute new column of matrix U, which is (old F) * x */ for (i = 1; i < n; i++) { /* u[i,n] := (i-th row of old F) * x */ t = 0.0; for (j = 1, ij = f_loc(scf, i, 1); j < n; j++, ij++) t += f[ij] * x[j]; u[u_loc(scf, i, n)] = t; } /* compute new (spiked) row of matrix U, which is (old P) * y */ for (j = 1; j < n; j++) un[j] = y[p[j]]; /* store new diagonal element of matrix U, which is z */ un[n] = z; /* expand matrix P */ p[n] = n; #if _GLPSCF_DEBUG /* expand matrix C */ /* fill its new column, which is x */ for (i = 1, in = f_loc(scf, i, n); i < n; i++, in += n_max) c[in] = x[i]; /* fill its new row, which is y */ for (j = 1, nj = f_loc(scf, n, j); j < n; j++, nj++) c[nj] = y[j]; /* fill its new diagonal element, which is z */ c[f_loc(scf, n, n)] = z; #endif /* restore upper triangular structure of matrix U */ for (k = 1; k < n; k++) if (un[k] != 0.0) break; transform(scf, k, un); /* estimate the rank of matrices C and U */ scf->rank = estimate_rank(scf); if (scf->rank != n) ret = SCF_ESING; #if _GLPSCF_DEBUG /* check that the factorization is accurate enough */ check_error(scf, "scf_update_exp"); #endif done: return ret; } /*********************************************************************** * The routine solve solves the system C * x = b. * * From the main equation F * C = U * P it follows that: * * C * x = b => F * C * x = F * b => U * P * x = F * b => * * P * x = inv(U) * F * b => x = P' * inv(U) * F * b. * * On entry the array x contains right-hand side vector b. On exit this * array contains solution vector x. */ static void solve(SCF *scf, double x[]) { int n = scf->n; double *f = scf->f; double *u = scf->u; int *p = scf->p; double *y = scf->w; int i, j, ij; double t; /* y := F * b */ for (i = 1; i <= n; i++) { /* y[i] = (i-th row of F) * b */ t = 0.0; for (j = 1, ij = f_loc(scf, i, 1); j <= n; j++, ij++) t += f[ij] * x[j]; y[i] = t; } /* y := inv(U) * y */ for (i = n; i >= 1; i--) { t = y[i]; for (j = n, ij = u_loc(scf, i, n); j > i; j--, ij--) t -= u[ij] * y[j]; y[i] = t / u[ij]; } /* x := P' * y */ for (i = 1; i <= n; i++) x[p[i]] = y[i]; return; } /*********************************************************************** * The routine tsolve solves the transposed system C' * x = b. * * From the main equation F * C = U * P it follows that: * * C' * F' = P' * U', * * therefore: * * C' * x = b => C' * F' * inv(F') * x = b => * * P' * U' * inv(F') * x = b => U' * inv(F') * x = P * b => * * inv(F') * x = inv(U') * P * b => x = F' * inv(U') * P * b. * * On entry the array x contains right-hand side vector b. On exit this * array contains solution vector x. */ static void tsolve(SCF *scf, double x[]) { int n = scf->n; double *f = scf->f; double *u = scf->u; int *p = scf->p; double *y = scf->w; int i, j, ij; double t; /* y := P * b */ for (i = 1; i <= n; i++) y[i] = x[p[i]]; /* y := inv(U') * y */ for (i = 1; i <= n; i++) { /* compute y[i] */ ij = u_loc(scf, i, i); t = (y[i] /= u[ij]); /* substitute y[i] in other equations */ for (j = i+1, ij++; j <= n; j++, ij++) y[j] -= u[ij] * t; } /* x := F' * y (computed as linear combination of rows of F) */ for (j = 1; j <= n; j++) x[j] = 0.0; for (i = 1; i <= n; i++) { t = y[i]; /* coefficient of linear combination */ for (j = 1, ij = f_loc(scf, i, 1); j <= n; j++, ij++) x[j] += f[ij] * t; } return; } /*********************************************************************** * NAME * * scf_solve_it - solve either system C * x = b or C' * x = b * * SYNOPSIS * * #include "glpscf.h" * void scf_solve_it(SCF *scf, int tr, double x[]); * * DESCRIPTION * * The routine scf_solve_it solves either the system C * x = b (if tr * is zero) or the system C' * x = b, where C' is a matrix transposed * to C (if tr is non-zero). C is assumed to be non-singular. * * On entry the array x should contain the right-hand side vector b in * locations x[1], ..., x[n], where n is the order of matrix C. On exit * the array x contains the solution vector x in the same locations. */ void scf_solve_it(SCF *scf, int tr, double x[]) { if (scf->rank < scf->n) xfault("scf_solve_it: singular matrix\n"); if (!tr) solve(scf, x); else tsolve(scf, x); return; } void scf_reset_it(SCF *scf) { /* reset factorization for empty matrix C */ scf->n = scf->rank = 0; return; } /*********************************************************************** * NAME * * scf_delete_it - delete Schur complement factorization * * SYNOPSIS * * #include "glpscf.h" * void scf_delete_it(SCF *scf); * * DESCRIPTION * * The routine scf_delete_it deletes the specified factorization and * frees all the memory allocated to this object. */ void scf_delete_it(SCF *scf) { xfree(scf->f); xfree(scf->u); xfree(scf->p); #if _GLPSCF_DEBUG xfree(scf->c); #endif xfree(scf->w); xfree(scf); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpapi06.c0000644000076500000240000006405413524616144025176 0ustar tamasstaff00000000000000/* glpapi06.c (simplex method routines) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wself-assign" #endif #include "glpios.h" #include "glpnpp.h" #include "glpspx.h" /*********************************************************************** * NAME * * glp_simplex - solve LP problem with the simplex method * * SYNOPSIS * * int glp_simplex(glp_prob *P, const glp_smcp *parm); * * DESCRIPTION * * The routine glp_simplex is a driver to the LP solver based on the * simplex method. This routine retrieves problem data from the * specified problem object, calls the solver to solve the problem * instance, and stores results of computations back into the problem * object. * * The simplex solver has a set of control parameters. Values of the * control parameters can be passed in a structure glp_smcp, which the * parameter parm points to. * * The parameter parm can be specified as NULL, in which case the LP * solver uses default settings. * * RETURNS * * 0 The LP problem instance has been successfully solved. This code * does not necessarily mean that the solver has found optimal * solution. It only means that the solution process was successful. * * GLP_EBADB * Unable to start the search, because the initial basis specified * in the problem object is invalid--the number of basic (auxiliary * and structural) variables is not the same as the number of rows in * the problem object. * * GLP_ESING * Unable to start the search, because the basis matrix correspodning * to the initial basis is singular within the working precision. * * GLP_ECOND * Unable to start the search, because the basis matrix correspodning * to the initial basis is ill-conditioned, i.e. its condition number * is too large. * * GLP_EBOUND * Unable to start the search, because some double-bounded variables * have incorrect bounds. * * GLP_EFAIL * The search was prematurely terminated due to the solver failure. * * GLP_EOBJLL * The search was prematurely terminated, because the objective * function being maximized has reached its lower limit and continues * decreasing (dual simplex only). * * GLP_EOBJUL * The search was prematurely terminated, because the objective * function being minimized has reached its upper limit and continues * increasing (dual simplex only). * * GLP_EITLIM * The search was prematurely terminated, because the simplex * iteration limit has been exceeded. * * GLP_ETMLIM * The search was prematurely terminated, because the time limit has * been exceeded. * * GLP_ENOPFS * The LP problem instance has no primal feasible solution (only if * the LP presolver is used). * * GLP_ENODFS * The LP problem instance has no dual feasible solution (only if the * LP presolver is used). */ static void trivial_lp(glp_prob *P, const glp_smcp *parm) { /* solve trivial LP which has empty constraint matrix */ GLPROW *row; GLPCOL *col; int i, j; double p_infeas, d_infeas, zeta; P->valid = 0; P->pbs_stat = P->dbs_stat = GLP_FEAS; P->obj_val = P->c0; P->some = 0; p_infeas = d_infeas = 0.0; /* make all auxiliary variables basic */ for (i = 1; i <= P->m; i++) { row = P->row[i]; row->stat = GLP_BS; row->prim = row->dual = 0.0; /* check primal feasibility */ if (row->type == GLP_LO || row->type == GLP_DB || row->type == GLP_FX) { /* row has lower bound */ if (row->lb > + parm->tol_bnd) { P->pbs_stat = GLP_NOFEAS; if (P->some == 0 && parm->meth != GLP_PRIMAL) P->some = i; } if (p_infeas < + row->lb) p_infeas = + row->lb; } if (row->type == GLP_UP || row->type == GLP_DB || row->type == GLP_FX) { /* row has upper bound */ if (row->ub < - parm->tol_bnd) { P->pbs_stat = GLP_NOFEAS; if (P->some == 0 && parm->meth != GLP_PRIMAL) P->some = i; } if (p_infeas < - row->ub) p_infeas = - row->ub; } } /* determine scale factor for the objective row */ zeta = 1.0; for (j = 1; j <= P->n; j++) { col = P->col[j]; if (zeta < fabs(col->coef)) zeta = fabs(col->coef); } zeta = (P->dir == GLP_MIN ? +1.0 : -1.0) / zeta; /* make all structural variables non-basic */ for (j = 1; j <= P->n; j++) { col = P->col[j]; if (col->type == GLP_FR) col->stat = GLP_NF, col->prim = 0.0; else if (col->type == GLP_LO) lo: col->stat = GLP_NL, col->prim = col->lb; else if (col->type == GLP_UP) up: col->stat = GLP_NU, col->prim = col->ub; else if (col->type == GLP_DB) { if (zeta * col->coef > 0.0) goto lo; else if (zeta * col->coef < 0.0) goto up; else if (fabs(col->lb) <= fabs(col->ub)) goto lo; else goto up; } else if (col->type == GLP_FX) col->stat = GLP_NS, col->prim = col->lb; col->dual = col->coef; P->obj_val += col->coef * col->prim; /* check dual feasibility */ if (col->type == GLP_FR || col->type == GLP_LO) { /* column has no upper bound */ if (zeta * col->dual < - parm->tol_dj) { P->dbs_stat = GLP_NOFEAS; if (P->some == 0 && parm->meth == GLP_PRIMAL) P->some = P->m + j; } if (d_infeas < - zeta * col->dual) d_infeas = - zeta * col->dual; } if (col->type == GLP_FR || col->type == GLP_UP) { /* column has no lower bound */ if (zeta * col->dual > + parm->tol_dj) { P->dbs_stat = GLP_NOFEAS; if (P->some == 0 && parm->meth == GLP_PRIMAL) P->some = P->m + j; } if (d_infeas < + zeta * col->dual) d_infeas = + zeta * col->dual; } } /* simulate the simplex solver output */ if (parm->msg_lev >= GLP_MSG_ON && parm->out_dly == 0) { xprintf("~%6d: obj = %17.9e infeas = %10.3e\n", P->it_cnt, P->obj_val, parm->meth == GLP_PRIMAL ? p_infeas : d_infeas); } if (parm->msg_lev >= GLP_MSG_ALL && parm->out_dly == 0) { if (P->pbs_stat == GLP_FEAS && P->dbs_stat == GLP_FEAS) xprintf("OPTIMAL SOLUTION FOUND\n"); else if (P->pbs_stat == GLP_NOFEAS) xprintf("PROBLEM HAS NO FEASIBLE SOLUTION\n"); else if (parm->meth == GLP_PRIMAL) xprintf("PROBLEM HAS UNBOUNDED SOLUTION\n"); else xprintf("PROBLEM HAS NO DUAL FEASIBLE SOLUTION\n"); } return; } static int solve_lp(glp_prob *P, const glp_smcp *parm) { /* solve LP directly without using the preprocessor */ int ret; if (!glp_bf_exists(P)) { ret = glp_factorize(P); if (ret == 0) ; else if (ret == GLP_EBADB) { if (parm->msg_lev >= GLP_MSG_ERR) xprintf("glp_simplex: initial basis is invalid\n"); } else if (ret == GLP_ESING) { if (parm->msg_lev >= GLP_MSG_ERR) xprintf("glp_simplex: initial basis is singular\n"); } else if (ret == GLP_ECOND) { if (parm->msg_lev >= GLP_MSG_ERR) xprintf( "glp_simplex: initial basis is ill-conditioned\n"); } else xassert(ret != ret); if (ret != 0) goto done; } if (parm->meth == GLP_PRIMAL) ret = spx_primal(P, parm); else if (parm->meth == GLP_DUALP) { ret = spx_dual(P, parm); if (ret == GLP_EFAIL && P->valid) ret = spx_primal(P, parm); } else if (parm->meth == GLP_DUAL) ret = spx_dual(P, parm); else xassert(parm != parm); done: return ret; } static int preprocess_and_solve_lp(glp_prob *P, const glp_smcp *parm) { /* solve LP using the preprocessor */ NPP *npp; glp_prob *lp = NULL; glp_bfcp bfcp; int ret; if (parm->msg_lev >= GLP_MSG_ALL) xprintf("Preprocessing...\n"); /* create preprocessor workspace */ npp = npp_create_wksp(); /* load original problem into the preprocessor workspace */ npp_load_prob(npp, P, GLP_OFF, GLP_SOL, GLP_OFF); /* process LP prior to applying primal/dual simplex method */ ret = npp_simplex(npp, parm); if (ret == 0) ; else if (ret == GLP_ENOPFS) { if (parm->msg_lev >= GLP_MSG_ALL) xprintf("PROBLEM HAS NO PRIMAL FEASIBLE SOLUTION\n"); } else if (ret == GLP_ENODFS) { if (parm->msg_lev >= GLP_MSG_ALL) xprintf("PROBLEM HAS NO DUAL FEASIBLE SOLUTION\n"); } else xassert(ret != ret); if (ret != 0) goto done; /* build transformed LP */ lp = glp_create_prob(); npp_build_prob(npp, lp); /* if the transformed LP is empty, it has empty solution, which is optimal */ if (lp->m == 0 && lp->n == 0) { lp->pbs_stat = lp->dbs_stat = GLP_FEAS; lp->obj_val = lp->c0; if (parm->msg_lev >= GLP_MSG_ON && parm->out_dly == 0) { xprintf("~%6d: obj = %17.9e infeas = %10.3e\n", P->it_cnt, lp->obj_val, 0.0); } if (parm->msg_lev >= GLP_MSG_ALL) xprintf("OPTIMAL SOLUTION FOUND BY LP PREPROCESSOR\n"); goto post; } if (parm->msg_lev >= GLP_MSG_ALL) { xprintf("%d row%s, %d column%s, %d non-zero%s\n", lp->m, lp->m == 1 ? "" : "s", lp->n, lp->n == 1 ? "" : "s", lp->nnz, lp->nnz == 1 ? "" : "s"); } /* inherit basis factorization control parameters */ glp_get_bfcp(P, &bfcp); glp_set_bfcp(lp, &bfcp); /* scale the transformed problem */ { ENV *env = get_env_ptr(); int term_out = env->term_out; if (!term_out || parm->msg_lev < GLP_MSG_ALL) env->term_out = GLP_OFF; else env->term_out = GLP_ON; glp_scale_prob(lp, GLP_SF_AUTO); env->term_out = term_out; } /* build advanced initial basis */ { ENV *env = get_env_ptr(); int term_out = env->term_out; if (!term_out || parm->msg_lev < GLP_MSG_ALL) env->term_out = GLP_OFF; else env->term_out = GLP_ON; glp_adv_basis(lp, 0); env->term_out = term_out; } /* solve the transformed LP */ lp->it_cnt = P->it_cnt; ret = solve_lp(lp, parm); P->it_cnt = lp->it_cnt; /* only optimal solution can be postprocessed */ if (!(ret == 0 && lp->pbs_stat == GLP_FEAS && lp->dbs_stat == GLP_FEAS)) { if (parm->msg_lev >= GLP_MSG_ERR) xprintf("glp_simplex: unable to recover undefined or non-op" "timal solution\n"); if (ret == 0) { if (lp->pbs_stat == GLP_NOFEAS) ret = GLP_ENOPFS; else if (lp->dbs_stat == GLP_NOFEAS) ret = GLP_ENODFS; else xassert(lp != lp); } goto done; } post: /* postprocess solution from the transformed LP */ npp_postprocess(npp, lp); /* the transformed LP is no longer needed */ glp_delete_prob(lp), lp = NULL; /* store solution to the original problem */ npp_unload_sol(npp, P); /* the original LP has been successfully solved */ ret = 0; done: /* delete the transformed LP, if it exists */ if (lp != NULL) glp_delete_prob(lp); /* delete preprocessor workspace */ npp_delete_wksp(npp); return ret; } int glp_simplex(glp_prob *P, const glp_smcp *parm) { /* solve LP problem with the simplex method */ glp_smcp _parm; int i, j, ret; /* check problem object */ if (P == NULL || P->magic != GLP_PROB_MAGIC) xerror("glp_simplex: P = %p; invalid problem object\n", P); if (P->tree != NULL && P->tree->reason != 0) xerror("glp_simplex: operation not allowed\n"); /* check control parameters */ if (parm == NULL) parm = &_parm, glp_init_smcp((glp_smcp *)parm); if (!(parm->msg_lev == GLP_MSG_OFF || parm->msg_lev == GLP_MSG_ERR || parm->msg_lev == GLP_MSG_ON || parm->msg_lev == GLP_MSG_ALL || parm->msg_lev == GLP_MSG_DBG)) xerror("glp_simplex: msg_lev = %d; invalid parameter\n", parm->msg_lev); if (!(parm->meth == GLP_PRIMAL || parm->meth == GLP_DUALP || parm->meth == GLP_DUAL)) xerror("glp_simplex: meth = %d; invalid parameter\n", parm->meth); if (!(parm->pricing == GLP_PT_STD || parm->pricing == GLP_PT_PSE)) xerror("glp_simplex: pricing = %d; invalid parameter\n", parm->pricing); if (!(parm->r_test == GLP_RT_STD || parm->r_test == GLP_RT_HAR)) xerror("glp_simplex: r_test = %d; invalid parameter\n", parm->r_test); if (!(0.0 < parm->tol_bnd && parm->tol_bnd < 1.0)) xerror("glp_simplex: tol_bnd = %g; invalid parameter\n", parm->tol_bnd); if (!(0.0 < parm->tol_dj && parm->tol_dj < 1.0)) xerror("glp_simplex: tol_dj = %g; invalid parameter\n", parm->tol_dj); if (!(0.0 < parm->tol_piv && parm->tol_piv < 1.0)) xerror("glp_simplex: tol_piv = %g; invalid parameter\n", parm->tol_piv); if (parm->it_lim < 0) xerror("glp_simplex: it_lim = %d; invalid parameter\n", parm->it_lim); if (parm->tm_lim < 0) xerror("glp_simplex: tm_lim = %d; invalid parameter\n", parm->tm_lim); if (parm->out_frq < 1) xerror("glp_simplex: out_frq = %d; invalid parameter\n", parm->out_frq); if (parm->out_dly < 0) xerror("glp_simplex: out_dly = %d; invalid parameter\n", parm->out_dly); if (!(parm->presolve == GLP_ON || parm->presolve == GLP_OFF)) xerror("glp_simplex: presolve = %d; invalid parameter\n", parm->presolve); /* basic solution is currently undefined */ P->pbs_stat = P->dbs_stat = GLP_UNDEF; P->obj_val = 0.0; P->some = 0; /* check bounds of double-bounded variables */ for (i = 1; i <= P->m; i++) { GLPROW *row = P->row[i]; if (row->type == GLP_DB && row->lb >= row->ub) { if (parm->msg_lev >= GLP_MSG_ERR) xprintf("glp_simplex: row %d: lb = %g, ub = %g; incorrec" "t bounds\n", i, row->lb, row->ub); ret = GLP_EBOUND; goto done; } } for (j = 1; j <= P->n; j++) { GLPCOL *col = P->col[j]; if (col->type == GLP_DB && col->lb >= col->ub) { if (parm->msg_lev >= GLP_MSG_ERR) xprintf("glp_simplex: column %d: lb = %g, ub = %g; incor" "rect bounds\n", j, col->lb, col->ub); ret = GLP_EBOUND; goto done; } } /* solve LP problem */ if (parm->msg_lev >= GLP_MSG_ALL) { xprintf("GLPK Simplex Optimizer, v%s\n", glp_version()); xprintf("%d row%s, %d column%s, %d non-zero%s\n", P->m, P->m == 1 ? "" : "s", P->n, P->n == 1 ? "" : "s", P->nnz, P->nnz == 1 ? "" : "s"); } if (P->nnz == 0) trivial_lp(P, parm), ret = 0; else if (!parm->presolve) ret = solve_lp(P, parm); else ret = preprocess_and_solve_lp(P, parm); done: /* return to the application program */ return ret; } /*********************************************************************** * NAME * * glp_init_smcp - initialize simplex method control parameters * * SYNOPSIS * * void glp_init_smcp(glp_smcp *parm); * * DESCRIPTION * * The routine glp_init_smcp initializes control parameters, which are * used by the simplex solver, with default values. * * Default values of the control parameters are stored in a glp_smcp * structure, which the parameter parm points to. */ void glp_init_smcp(glp_smcp *parm) { parm->msg_lev = GLP_MSG_ALL; parm->meth = GLP_PRIMAL; parm->pricing = GLP_PT_PSE; parm->r_test = GLP_RT_HAR; parm->tol_bnd = 1e-7; parm->tol_dj = 1e-7; parm->tol_piv = 1e-10; parm->obj_ll = -DBL_MAX; parm->obj_ul = +DBL_MAX; parm->it_lim = INT_MAX; parm->tm_lim = INT_MAX; parm->out_frq = 500; parm->out_dly = 0; parm->presolve = GLP_OFF; return; } /*********************************************************************** * NAME * * glp_get_status - retrieve generic status of basic solution * * SYNOPSIS * * int glp_get_status(glp_prob *lp); * * RETURNS * * The routine glp_get_status reports the generic status of the basic * solution for the specified problem object as follows: * * GLP_OPT - solution is optimal; * GLP_FEAS - solution is feasible; * GLP_INFEAS - solution is infeasible; * GLP_NOFEAS - problem has no feasible solution; * GLP_UNBND - problem has unbounded solution; * GLP_UNDEF - solution is undefined. */ int glp_get_status(glp_prob *lp) { int status; status = glp_get_prim_stat(lp); switch (status) { case GLP_FEAS: switch (glp_get_dual_stat(lp)) { case GLP_FEAS: status = GLP_OPT; break; case GLP_NOFEAS: status = GLP_UNBND; break; case GLP_UNDEF: case GLP_INFEAS: status = status; break; default: xassert(lp != lp); } break; case GLP_UNDEF: case GLP_INFEAS: case GLP_NOFEAS: status = status; break; default: xassert(lp != lp); } return status; } /*********************************************************************** * NAME * * glp_get_prim_stat - retrieve status of primal basic solution * * SYNOPSIS * * int glp_get_prim_stat(glp_prob *lp); * * RETURNS * * The routine glp_get_prim_stat reports the status of the primal basic * solution for the specified problem object as follows: * * GLP_UNDEF - primal solution is undefined; * GLP_FEAS - primal solution is feasible; * GLP_INFEAS - primal solution is infeasible; * GLP_NOFEAS - no primal feasible solution exists. */ int glp_get_prim_stat(glp_prob *lp) { int pbs_stat = lp->pbs_stat; return pbs_stat; } /*********************************************************************** * NAME * * glp_get_dual_stat - retrieve status of dual basic solution * * SYNOPSIS * * int glp_get_dual_stat(glp_prob *lp); * * RETURNS * * The routine glp_get_dual_stat reports the status of the dual basic * solution for the specified problem object as follows: * * GLP_UNDEF - dual solution is undefined; * GLP_FEAS - dual solution is feasible; * GLP_INFEAS - dual solution is infeasible; * GLP_NOFEAS - no dual feasible solution exists. */ int glp_get_dual_stat(glp_prob *lp) { int dbs_stat = lp->dbs_stat; return dbs_stat; } /*********************************************************************** * NAME * * glp_get_obj_val - retrieve objective value (basic solution) * * SYNOPSIS * * double glp_get_obj_val(glp_prob *lp); * * RETURNS * * The routine glp_get_obj_val returns value of the objective function * for basic solution. */ double glp_get_obj_val(glp_prob *lp) { /*struct LPXCPS *cps = lp->cps;*/ double z; z = lp->obj_val; /*if (cps->round && fabs(z) < 1e-9) z = 0.0;*/ return z; } /*********************************************************************** * NAME * * glp_get_row_stat - retrieve row status * * SYNOPSIS * * int glp_get_row_stat(glp_prob *lp, int i); * * RETURNS * * The routine glp_get_row_stat returns current status assigned to the * auxiliary variable associated with i-th row as follows: * * GLP_BS - basic variable; * GLP_NL - non-basic variable on its lower bound; * GLP_NU - non-basic variable on its upper bound; * GLP_NF - non-basic free (unbounded) variable; * GLP_NS - non-basic fixed variable. */ int glp_get_row_stat(glp_prob *lp, int i) { if (!(1 <= i && i <= lp->m)) xerror("glp_get_row_stat: i = %d; row number out of range\n", i); return lp->row[i]->stat; } /*********************************************************************** * NAME * * glp_get_row_prim - retrieve row primal value (basic solution) * * SYNOPSIS * * double glp_get_row_prim(glp_prob *lp, int i); * * RETURNS * * The routine glp_get_row_prim returns primal value of the auxiliary * variable associated with i-th row. */ double glp_get_row_prim(glp_prob *lp, int i) { /*struct LPXCPS *cps = lp->cps;*/ double prim; if (!(1 <= i && i <= lp->m)) xerror("glp_get_row_prim: i = %d; row number out of range\n", i); prim = lp->row[i]->prim; /*if (cps->round && fabs(prim) < 1e-9) prim = 0.0;*/ return prim; } /*********************************************************************** * NAME * * glp_get_row_dual - retrieve row dual value (basic solution) * * SYNOPSIS * * double glp_get_row_dual(glp_prob *lp, int i); * * RETURNS * * The routine glp_get_row_dual returns dual value (i.e. reduced cost) * of the auxiliary variable associated with i-th row. */ double glp_get_row_dual(glp_prob *lp, int i) { /*struct LPXCPS *cps = lp->cps;*/ double dual; if (!(1 <= i && i <= lp->m)) xerror("glp_get_row_dual: i = %d; row number out of range\n", i); dual = lp->row[i]->dual; /*if (cps->round && fabs(dual) < 1e-9) dual = 0.0;*/ return dual; } /*********************************************************************** * NAME * * glp_get_col_stat - retrieve column status * * SYNOPSIS * * int glp_get_col_stat(glp_prob *lp, int j); * * RETURNS * * The routine glp_get_col_stat returns current status assigned to the * structural variable associated with j-th column as follows: * * GLP_BS - basic variable; * GLP_NL - non-basic variable on its lower bound; * GLP_NU - non-basic variable on its upper bound; * GLP_NF - non-basic free (unbounded) variable; * GLP_NS - non-basic fixed variable. */ int glp_get_col_stat(glp_prob *lp, int j) { if (!(1 <= j && j <= lp->n)) xerror("glp_get_col_stat: j = %d; column number out of range\n" , j); return lp->col[j]->stat; } /*********************************************************************** * NAME * * glp_get_col_prim - retrieve column primal value (basic solution) * * SYNOPSIS * * double glp_get_col_prim(glp_prob *lp, int j); * * RETURNS * * The routine glp_get_col_prim returns primal value of the structural * variable associated with j-th column. */ double glp_get_col_prim(glp_prob *lp, int j) { /*struct LPXCPS *cps = lp->cps;*/ double prim; if (!(1 <= j && j <= lp->n)) xerror("glp_get_col_prim: j = %d; column number out of range\n" , j); prim = lp->col[j]->prim; /*if (cps->round && fabs(prim) < 1e-9) prim = 0.0;*/ return prim; } /*********************************************************************** * NAME * * glp_get_col_dual - retrieve column dual value (basic solution) * * SYNOPSIS * * double glp_get_col_dual(glp_prob *lp, int j); * * RETURNS * * The routine glp_get_col_dual returns dual value (i.e. reduced cost) * of the structural variable associated with j-th column. */ double glp_get_col_dual(glp_prob *lp, int j) { /*struct LPXCPS *cps = lp->cps;*/ double dual; if (!(1 <= j && j <= lp->n)) xerror("glp_get_col_dual: j = %d; column number out of range\n" , j); dual = lp->col[j]->dual; /*if (cps->round && fabs(dual) < 1e-9) dual = 0.0;*/ return dual; } /*********************************************************************** * NAME * * glp_get_unbnd_ray - determine variable causing unboundedness * * SYNOPSIS * * int glp_get_unbnd_ray(glp_prob *lp); * * RETURNS * * The routine glp_get_unbnd_ray returns the number k of a variable, * which causes primal or dual unboundedness. If 1 <= k <= m, it is * k-th auxiliary variable, and if m+1 <= k <= m+n, it is (k-m)-th * structural variable, where m is the number of rows, n is the number * of columns in the problem object. If such variable is not defined, * the routine returns 0. * * COMMENTS * * If it is not exactly known which version of the simplex solver * detected unboundedness, i.e. whether the unboundedness is primal or * dual, it is sufficient to check the status of the variable reported * with the routine glp_get_row_stat or glp_get_col_stat. If the * variable is non-basic, the unboundedness is primal, otherwise, if * the variable is basic, the unboundedness is dual (the latter case * means that the problem has no primal feasible dolution). */ int glp_get_unbnd_ray(glp_prob *lp) { int k; k = lp->some; xassert(k >= 0); if (k > lp->m + lp->n) k = 0; return k; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glphbm.c0000644000076500000240000004556713524616144025035 0ustar tamasstaff00000000000000/* glphbm.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #define _GLPSTD_ERRNO #define _GLPSTD_STDIO #include "glphbm.h" #include "glpenv.h" /*********************************************************************** * NAME * * hbm_read_mat - read sparse matrix in Harwell-Boeing format * * SYNOPSIS * * #include "glphbm.h" * HBM *hbm_read_mat(const char *fname); * * DESCRIPTION * * The routine hbm_read_mat reads a sparse matrix in the Harwell-Boeing * format from a text file whose name is the character string fname. * * Detailed description of the Harwell-Boeing format recognised by this * routine is given in the following report: * * I.S.Duff, R.G.Grimes, J.G.Lewis. User's Guide for the Harwell-Boeing * Sparse Matrix Collection (Release I), TR/PA/92/86, October 1992. * * RETURNS * * If no error occured, the routine hbm_read_mat returns a pointer to * a data structure containing the matrix. In case of error the routine * prints an appropriate error message and returns NULL. */ struct dsa { /* working area used by routine hbm_read_mat */ const char *fname; /* name of input text file */ FILE *fp; /* stream assigned to input text file */ int seqn; /* card sequential number */ char card[80+1]; /* card image buffer */ int fmt_p; /* scale factor */ int fmt_k; /* iterator */ int fmt_f; /* format code */ int fmt_w; /* field width */ int fmt_d; /* number of decimal places after point */ }; /*********************************************************************** * read_card - read next data card * * This routine reads the next 80-column card from the input text file * and stores its image into the character string card. If the card was * read successfully, the routine returns zero, otherwise non-zero. */ static int read_card(struct dsa *dsa) { int k, c; dsa->seqn++; memset(dsa->card, ' ', 80), dsa->card[80] = '\0'; k = 0; for (;;) { c = fgetc(dsa->fp); if (ferror(dsa->fp)) { xprintf("%s:%d: read error - %s\n", dsa->fname, dsa->seqn, strerror(errno)); return 1; } if (feof(dsa->fp)) { if (k == 0) xprintf("%s:%d: unexpected EOF\n", dsa->fname, dsa->seqn); else xprintf("%s:%d: missing final LF\n", dsa->fname, dsa->seqn); return 1; } if (c == '\r') continue; if (c == '\n') break; if (iscntrl(c)) { xprintf("%s:%d: invalid control character 0x%02X\n", dsa->fname, dsa->seqn, c); return 1; } if (k == 80) { xprintf("%s:%d: card image too long\n", dsa->fname, dsa->seqn); return 1; } dsa->card[k++] = (char)c; } return 0; } /*********************************************************************** * scan_int - scan integer value from the current card * * This routine scans an integer value from the current card, where fld * is the name of the field, pos is the position of the field, width is * the width of the field, val points to a location to which the scanned * value should be stored. If the value was scanned successfully, the * routine returns zero, otherwise non-zero. */ static int scan_int(struct dsa *dsa, char *fld, int pos, int width, int *val) { char str[80+1]; xassert(1 <= width && width <= 80); memcpy(str, dsa->card + pos, width), str[width] = '\0'; if (str2int(strspx(str), val)) { xprintf("%s:%d: field `%s' contains invalid value `%s'\n", dsa->fname, dsa->seqn, fld, str); return 1; } return 0; } /*********************************************************************** * parse_fmt - parse Fortran format specification * * This routine parses the Fortran format specification represented as * character string which fmt points to and stores format elements into * appropriate static locations. Should note that not all valid Fortran * format specifications may be recognised. If the format specification * was recognised, the routine returns zero, otherwise non-zero. */ static int parse_fmt(struct dsa *dsa, char *fmt) { int k, s, val; char str[80+1]; /* first character should be left parenthesis */ if (fmt[0] != '(') fail: { xprintf("hbm_read_mat: format `%s' not recognised\n", fmt); return 1; } k = 1; /* optional scale factor */ dsa->fmt_p = 0; if (isdigit((unsigned char)fmt[k])) { s = 0; while (isdigit((unsigned char)fmt[k])) { if (s == 80) goto fail; str[s++] = fmt[k++]; } str[s] = '\0'; if (str2int(str, &val)) goto fail; if (toupper((unsigned char)fmt[k]) != 'P') goto iter; dsa->fmt_p = val, k++; if (!(0 <= dsa->fmt_p && dsa->fmt_p <= 255)) goto fail; /* optional comma may follow scale factor */ if (fmt[k] == ',') k++; } /* optional iterator */ dsa->fmt_k = 1; if (isdigit((unsigned char)fmt[k])) { s = 0; while (isdigit((unsigned char)fmt[k])) { if (s == 80) goto fail; str[s++] = fmt[k++]; } str[s] = '\0'; if (str2int(str, &val)) goto fail; iter: dsa->fmt_k = val; if (!(1 <= dsa->fmt_k && dsa->fmt_k <= 255)) goto fail; } /* format code */ dsa->fmt_f = toupper((unsigned char)fmt[k++]); if (!(dsa->fmt_f == 'D' || dsa->fmt_f == 'E' || dsa->fmt_f == 'F' || dsa->fmt_f == 'G' || dsa->fmt_f == 'I')) goto fail; /* field width */ if (!isdigit((unsigned char)fmt[k])) goto fail; s = 0; while (isdigit((unsigned char)fmt[k])) { if (s == 80) goto fail; str[s++] = fmt[k++]; } str[s] = '\0'; if (str2int(str, &dsa->fmt_w)) goto fail; if (!(1 <= dsa->fmt_w && dsa->fmt_w <= 255)) goto fail; /* optional number of decimal places after point */ dsa->fmt_d = 0; if (fmt[k] == '.') { k++; if (!isdigit((unsigned char)fmt[k])) goto fail; s = 0; while (isdigit((unsigned char)fmt[k])) { if (s == 80) goto fail; str[s++] = fmt[k++]; } str[s] = '\0'; if (str2int(str, &dsa->fmt_d)) goto fail; if (!(0 <= dsa->fmt_d && dsa->fmt_d <= 255)) goto fail; } /* last character should be right parenthesis */ if (!(fmt[k] == ')' && fmt[k+1] == '\0')) goto fail; return 0; } /*********************************************************************** * read_int_array - read array of integer type * * This routine reads an integer array from the input text file, where * name is array name, fmt is Fortran format specification that controls * reading, n is number of array elements, val is array of integer type. * If the array was read successful, the routine returns zero, otherwise * non-zero. */ static int read_int_array(struct dsa *dsa, char *name, char *fmt, int n, int val[]) { int k, pos; char str[80+1]; if (parse_fmt(dsa, fmt)) return 1; if (!(dsa->fmt_f == 'I' && dsa->fmt_w <= 80 && dsa->fmt_k * dsa->fmt_w <= 80)) { xprintf( "%s:%d: can't read array `%s' - invalid format `%s'\n", dsa->fname, dsa->seqn, name, fmt); return 1; } for (k = 1, pos = INT_MAX; k <= n; k++, pos++) { if (pos >= dsa->fmt_k) { if (read_card(dsa)) return 1; pos = 0; } memcpy(str, dsa->card + dsa->fmt_w * pos, dsa->fmt_w); str[dsa->fmt_w] = '\0'; strspx(str); if (str2int(str, &val[k])) { xprintf( "%s:%d: can't read array `%s' - invalid value `%s'\n", dsa->fname, dsa->seqn, name, str); return 1; } } return 0; } /*********************************************************************** * read_real_array - read array of real type * * This routine reads a real array from the input text file, where name * is array name, fmt is Fortran format specification that controls * reading, n is number of array elements, val is array of real type. * If the array was read successful, the routine returns zero, otherwise * non-zero. */ static int read_real_array(struct dsa *dsa, char *name, char *fmt, int n, double val[]) { int k, pos; char str[80+1], *ptr; if (parse_fmt(dsa, fmt)) return 1; if (!(dsa->fmt_f != 'I' && dsa->fmt_w <= 80 && dsa->fmt_k * dsa->fmt_w <= 80)) { xprintf( "%s:%d: can't read array `%s' - invalid format `%s'\n", dsa->fname, dsa->seqn, name, fmt); return 1; } for (k = 1, pos = INT_MAX; k <= n; k++, pos++) { if (pos >= dsa->fmt_k) { if (read_card(dsa)) return 1; pos = 0; } memcpy(str, dsa->card + dsa->fmt_w * pos, dsa->fmt_w); str[dsa->fmt_w] = '\0'; strspx(str); if (strchr(str, '.') == NULL && strcmp(str, "0")) { xprintf("%s(%d): can't read array `%s' - value `%s' has no " "decimal point\n", dsa->fname, dsa->seqn, name, str); return 1; } /* sometimes lower case letters appear */ for (ptr = str; *ptr; ptr++) *ptr = (char)toupper((unsigned char)*ptr); ptr = strchr(str, 'D'); if (ptr != NULL) *ptr = 'E'; /* value may appear with decimal exponent but without letters E or D (for example, -123.456-012), so missing letter should be inserted */ ptr = strchr(str+1, '+'); if (ptr == NULL) ptr = strchr(str+1, '-'); if (ptr != NULL && *(ptr-1) != 'E') { xassert(strlen(str) < 80); memmove(ptr+1, ptr, strlen(ptr)+1); *ptr = 'E'; } if (str2num(str, &val[k])) { xprintf( "%s:%d: can't read array `%s' - invalid value `%s'\n", dsa->fname, dsa->seqn, name, str); return 1; } } return 0; } HBM *hbm_read_mat(const char *fname) { struct dsa _dsa, *dsa = &_dsa; HBM *hbm = NULL; dsa->fname = fname; xprintf("hbm_read_mat: reading matrix from `%s'...\n", dsa->fname); dsa->fp = fopen(dsa->fname, "r"); if (dsa->fp == NULL) { xprintf("hbm_read_mat: unable to open `%s' - %s\n", dsa->fname, strerror(errno)); goto fail; } dsa->seqn = 0; hbm = xmalloc(sizeof(HBM)); memset(hbm, 0, sizeof(HBM)); /* read the first heading card */ if (read_card(dsa)) goto fail; memcpy(hbm->title, dsa->card, 72), hbm->title[72] = '\0'; strtrim(hbm->title); xprintf("%s\n", hbm->title); memcpy(hbm->key, dsa->card+72, 8), hbm->key[8] = '\0'; strspx(hbm->key); xprintf("key = %s\n", hbm->key); /* read the second heading card */ if (read_card(dsa)) goto fail; if (scan_int(dsa, "totcrd", 0, 14, &hbm->totcrd)) goto fail; if (scan_int(dsa, "ptrcrd", 14, 14, &hbm->ptrcrd)) goto fail; if (scan_int(dsa, "indcrd", 28, 14, &hbm->indcrd)) goto fail; if (scan_int(dsa, "valcrd", 42, 14, &hbm->valcrd)) goto fail; if (scan_int(dsa, "rhscrd", 56, 14, &hbm->rhscrd)) goto fail; xprintf("totcrd = %d; ptrcrd = %d; indcrd = %d; valcrd = %d; rhsc" "rd = %d\n", hbm->totcrd, hbm->ptrcrd, hbm->indcrd, hbm->valcrd, hbm->rhscrd); /* read the third heading card */ if (read_card(dsa)) goto fail; memcpy(hbm->mxtype, dsa->card, 3), hbm->mxtype[3] = '\0'; if (strchr("RCP", hbm->mxtype[0]) == NULL || strchr("SUHZR", hbm->mxtype[1]) == NULL || strchr("AE", hbm->mxtype[2]) == NULL) { xprintf("%s:%d: matrix type `%s' not recognised\n", dsa->fname, dsa->seqn, hbm->mxtype); goto fail; } if (scan_int(dsa, "nrow", 14, 14, &hbm->nrow)) goto fail; if (scan_int(dsa, "ncol", 28, 14, &hbm->ncol)) goto fail; if (scan_int(dsa, "nnzero", 42, 14, &hbm->nnzero)) goto fail; if (scan_int(dsa, "neltvl", 56, 14, &hbm->neltvl)) goto fail; xprintf("mxtype = %s; nrow = %d; ncol = %d; nnzero = %d; neltvl =" " %d\n", hbm->mxtype, hbm->nrow, hbm->ncol, hbm->nnzero, hbm->neltvl); /* read the fourth heading card */ if (read_card(dsa)) goto fail; memcpy(hbm->ptrfmt, dsa->card, 16), hbm->ptrfmt[16] = '\0'; strspx(hbm->ptrfmt); memcpy(hbm->indfmt, dsa->card+16, 16), hbm->indfmt[16] = '\0'; strspx(hbm->indfmt); memcpy(hbm->valfmt, dsa->card+32, 20), hbm->valfmt[20] = '\0'; strspx(hbm->valfmt); memcpy(hbm->rhsfmt, dsa->card+52, 20), hbm->rhsfmt[20] = '\0'; strspx(hbm->rhsfmt); xprintf("ptrfmt = %s; indfmt = %s; valfmt = %s; rhsfmt = %s\n", hbm->ptrfmt, hbm->indfmt, hbm->valfmt, hbm->rhsfmt); /* read the fifth heading card (optional) */ if (hbm->rhscrd <= 0) { strcpy(hbm->rhstyp, "???"); hbm->nrhs = 0; hbm->nrhsix = 0; } else { if (read_card(dsa)) goto fail; memcpy(hbm->rhstyp, dsa->card, 3), hbm->rhstyp[3] = '\0'; if (scan_int(dsa, "nrhs", 14, 14, &hbm->nrhs)) goto fail; if (scan_int(dsa, "nrhsix", 28, 14, &hbm->nrhsix)) goto fail; xprintf("rhstyp = `%s'; nrhs = %d; nrhsix = %d\n", hbm->rhstyp, hbm->nrhs, hbm->nrhsix); } /* read matrix structure */ hbm->colptr = xcalloc(1+hbm->ncol+1, sizeof(int)); if (read_int_array(dsa, "colptr", hbm->ptrfmt, hbm->ncol+1, hbm->colptr)) goto fail; hbm->rowind = xcalloc(1+hbm->nnzero, sizeof(int)); if (read_int_array(dsa, "rowind", hbm->indfmt, hbm->nnzero, hbm->rowind)) goto fail; /* read matrix values */ if (hbm->valcrd <= 0) goto done; if (hbm->mxtype[2] == 'A') { /* assembled matrix */ hbm->values = xcalloc(1+hbm->nnzero, sizeof(double)); if (read_real_array(dsa, "values", hbm->valfmt, hbm->nnzero, hbm->values)) goto fail; } else { /* elemental (unassembled) matrix */ hbm->values = xcalloc(1+hbm->neltvl, sizeof(double)); if (read_real_array(dsa, "values", hbm->valfmt, hbm->neltvl, hbm->values)) goto fail; } /* read right-hand sides */ if (hbm->nrhs <= 0) goto done; if (hbm->rhstyp[0] == 'F') { /* dense format */ hbm->nrhsvl = hbm->nrow * hbm->nrhs; hbm->rhsval = xcalloc(1+hbm->nrhsvl, sizeof(double)); if (read_real_array(dsa, "rhsval", hbm->rhsfmt, hbm->nrhsvl, hbm->rhsval)) goto fail; } else if (hbm->rhstyp[0] == 'M' && hbm->mxtype[2] == 'A') { /* sparse format */ /* read pointers */ hbm->rhsptr = xcalloc(1+hbm->nrhs+1, sizeof(int)); if (read_int_array(dsa, "rhsptr", hbm->ptrfmt, hbm->nrhs+1, hbm->rhsptr)) goto fail; /* read sparsity pattern */ hbm->rhsind = xcalloc(1+hbm->nrhsix, sizeof(int)); if (read_int_array(dsa, "rhsind", hbm->indfmt, hbm->nrhsix, hbm->rhsind)) goto fail; /* read values */ hbm->rhsval = xcalloc(1+hbm->nrhsix, sizeof(double)); if (read_real_array(dsa, "rhsval", hbm->rhsfmt, hbm->nrhsix, hbm->rhsval)) goto fail; } else if (hbm->rhstyp[0] == 'M' && hbm->mxtype[2] == 'E') { /* elemental format */ hbm->rhsval = xcalloc(1+hbm->nrhsvl, sizeof(double)); if (read_real_array(dsa, "rhsval", hbm->rhsfmt, hbm->nrhsvl, hbm->rhsval)) goto fail; } else { xprintf("%s:%d: right-hand side type `%c' not recognised\n", dsa->fname, dsa->seqn, hbm->rhstyp[0]); goto fail; } /* read starting guesses */ if (hbm->rhstyp[1] == 'G') { hbm->nguess = hbm->nrow * hbm->nrhs; hbm->sguess = xcalloc(1+hbm->nguess, sizeof(double)); if (read_real_array(dsa, "sguess", hbm->rhsfmt, hbm->nguess, hbm->sguess)) goto fail; } /* read solution vectors */ if (hbm->rhstyp[2] == 'X') { hbm->nexact = hbm->nrow * hbm->nrhs; hbm->xexact = xcalloc(1+hbm->nexact, sizeof(double)); if (read_real_array(dsa, "xexact", hbm->rhsfmt, hbm->nexact, hbm->xexact)) goto fail; } done: /* reading has been completed */ xprintf("hbm_read_mat: %d cards were read\n", dsa->seqn); fclose(dsa->fp); return hbm; fail: /* something wrong in Danish kingdom */ if (hbm != NULL) { if (hbm->colptr != NULL) xfree(hbm->colptr); if (hbm->rowind != NULL) xfree(hbm->rowind); if (hbm->rhsptr != NULL) xfree(hbm->rhsptr); if (hbm->rhsind != NULL) xfree(hbm->rhsind); if (hbm->values != NULL) xfree(hbm->values); if (hbm->rhsval != NULL) xfree(hbm->rhsval); if (hbm->sguess != NULL) xfree(hbm->sguess); if (hbm->xexact != NULL) xfree(hbm->xexact); xfree(hbm); } if (dsa->fp != NULL) fclose(dsa->fp); return NULL; } /*********************************************************************** * NAME * * hbm_free_mat - free sparse matrix in Harwell-Boeing format * * SYNOPSIS * * #include "glphbm.h" * void hbm_free_mat(HBM *hbm); * * DESCRIPTION * * The hbm_free_mat routine frees all the memory allocated to the data * structure containing a sparse matrix in the Harwell-Boeing format. */ void hbm_free_mat(HBM *hbm) { if (hbm->colptr != NULL) xfree(hbm->colptr); if (hbm->rowind != NULL) xfree(hbm->rowind); if (hbm->rhsptr != NULL) xfree(hbm->rhsptr); if (hbm->rhsind != NULL) xfree(hbm->rhsind); if (hbm->values != NULL) xfree(hbm->values); if (hbm->rhsval != NULL) xfree(hbm->rhsval); if (hbm->sguess != NULL) xfree(hbm->sguess); if (hbm->xexact != NULL) xfree(hbm->xexact); xfree(hbm); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glplib.h0000644000076500000240000000765113524616144025032 0ustar tamasstaff00000000000000/* glplib.h (miscellaneous library routines) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPLIB_H #define GLPLIB_H #define bigmul _glp_lib_bigmul void bigmul(int n, int m, unsigned short x[], unsigned short y[]); /* multiply unsigned integer numbers of arbitrary precision */ #define bigdiv _glp_lib_bigdiv void bigdiv(int n, int m, unsigned short x[], unsigned short y[]); /* divide unsigned integer numbers of arbitrary precision */ #ifndef GLP_LONG_DEFINED #define GLP_LONG_DEFINED typedef struct { int lo, hi; } glp_long; /* long integer data type */ #endif typedef struct { glp_long quot, rem; } glp_ldiv; /* result of long integer division */ #define xlset _glp_lib_xlset glp_long xlset(int x); /* expand integer to long integer */ #define xlneg _glp_lib_xlneg glp_long xlneg(glp_long x); /* negate long integer */ #define xladd _glp_lib_xladd glp_long xladd(glp_long x, glp_long y); /* add long integers */ #define xlsub _glp_lib_xlsub glp_long xlsub(glp_long x, glp_long y); /* subtract long integers */ #define xlcmp _glp_lib_xlcmp int xlcmp(glp_long x, glp_long y); /* compare long integers */ #define xlmul _glp_lib_xlmul glp_long xlmul(glp_long x, glp_long y); /* multiply long integers */ #define xldiv _glp_lib_xldiv glp_ldiv xldiv(glp_long x, glp_long y); /* divide long integers */ #define xltod _glp_lib_xltod double xltod(glp_long x); /* convert long integer to double */ #define xltoa _glp_lib_xltoa char *xltoa(glp_long x, char *s); /* convert long integer to character string */ #define str2int _glp_lib_str2int int str2int(const char *str, int *val); /* convert character string to value of int type */ #define str2num _glp_lib_str2num int str2num(const char *str, double *val); /* convert character string to value of double type */ #define strspx _glp_lib_strspx char *strspx(char *str); /* remove all spaces from character string */ #define strtrim _glp_lib_strtrim char *strtrim(char *str); /* remove trailing spaces from character string */ #define strrev _glp_lib_strrev char *strrev(char *s); /* reverse character string */ #define gcd _glp_lib_gcd int gcd(int x, int y); /* find greatest common divisor of two integers */ #define gcdn _glp_lib_gcdn int gcdn(int n, int x[]); /* find greatest common divisor of n integers */ #define lcm _glp_lib_lcm int lcm(int x, int y); /* find least common multiple of two integers */ #define lcmn _glp_lib_lcmn int lcmn(int n, int x[]); /* find least common multiple of n integers */ #define round2n _glp_lib_round2n double round2n(double x); /* round floating-point number to nearest power of two */ #define fp2rat _glp_lib_fp2rat int fp2rat(double x, double eps, double *p, double *q); /* convert floating-point number to rational number */ #define jday _glp_lib_jday int jday(int d, int m, int y); /* convert calendar date to Julian day number */ #define jdate _glp_lib_jdate int jdate(int j, int *d, int *m, int *y); /* convert Julian day number to calendar date */ #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glprng01.c0000644000076500000240000001425113524616144025200 0ustar tamasstaff00000000000000/* glprng01.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * This code is a modified version of the module GB_FLIP, a portable * pseudo-random number generator. The original version of GB_FLIP is * a part of The Stanford GraphBase developed by Donald E. Knuth (see * http://www-cs-staff.stanford.edu/~knuth/sgb.html). * * Note that all changes concern only external names, so this modified * version produces exactly the same results as the original version. * * Changes were made by Andrew Makhorin . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wsign-conversion" #endif #include "glpenv.h" #include "glprng.h" #if 0 int A[56] = { -1 }; #else #define A (rand->A) #endif /* pseudo-random values */ #if 0 int *fptr = A; #else #define fptr (rand->fptr) #endif /* the next A value to be exported */ #define mod_diff(x, y) (((x) - (y)) & 0x7FFFFFFF) /* difference modulo 2^31 */ static int flip_cycle(RNG *rand) { /* this is an auxiliary routine to do 55 more steps of the basic recurrence, at high speed, and to reset fptr */ int *ii, *jj; for (ii = &A[1], jj = &A[32]; jj <= &A[55]; ii++, jj++) *ii = mod_diff(*ii, *jj); for (jj = &A[1]; ii <= &A[55]; ii++, jj++) *ii = mod_diff(*ii, *jj); fptr = &A[54]; return A[55]; } /*********************************************************************** * NAME * * rng_create_rand - create pseudo-random number generator * * SYNOPSIS * * #include "glprng.h" * RNG *rng_create_rand(void); * * DESCRIPTION * * The routine rng_create_rand creates and initializes a pseudo-random * number generator. * * RETURNS * * The routine returns a pointer to the generator created. */ RNG *rng_create_rand(void) { RNG *rand; int i; rand = xmalloc(sizeof(RNG)); A[0] = -1; for (i = 1; i <= 55; i++) A[i] = 0; fptr = A; rng_init_rand(rand, 1); return rand; } /*********************************************************************** * NAME * * rng_init_rand - initialize pseudo-random number generator * * SYNOPSIS * * #include "glprng.h" * void rng_init_rand(RNG *rand, int seed); * * DESCRIPTION * * The routine rng_init_rand initializes the pseudo-random number * generator. The parameter seed may be any integer number. Note that * on creating the generator this routine is called with the parameter * seed equal to 1. */ void rng_init_rand(RNG *rand, int seed) { int i; int prev = seed, next = 1; seed = prev = mod_diff(prev, 0); A[55] = prev; for (i = 21; i; i = (i + 21) % 55) { A[i] = next; next = mod_diff(prev, next); if (seed & 1) seed = 0x40000000 + (seed >> 1); else seed >>= 1; next = mod_diff(next, seed); prev = A[i]; } flip_cycle(rand); flip_cycle(rand); flip_cycle(rand); flip_cycle(rand); flip_cycle(rand); return; } /*********************************************************************** * NAME * * rng_next_rand - obtain pseudo-random integer in the range [0, 2^31-1] * * SYNOPSIS * * #include "glprng.h" * int rng_next_rand(RNG *rand); * * RETURNS * * The routine rng_next_rand returns a next pseudo-random integer which * is uniformly distributed between 0 and 2^31-1, inclusive. The period * length of the generated numbers is 2^85 - 2^30. The low order bits of * the generated numbers are just as random as the high-order bits. */ int rng_next_rand(RNG *rand) { return *fptr >= 0 ? *fptr-- : flip_cycle(rand); } /*********************************************************************** * NAME * * rng_unif_rand - obtain pseudo-random integer in the range [0, m-1] * * SYNOPSIS * * #include "glprng.h" * int rng_unif_rand(RNG *rand, int m); * * RETURNS * * The routine rng_unif_rand returns a next pseudo-random integer which * is uniformly distributed between 0 and m-1, inclusive, where m is any * positive integer less than 2^31. */ #define two_to_the_31 ((unsigned int)0x80000000) int rng_unif_rand(RNG *rand, int m) { unsigned int t = two_to_the_31 - (two_to_the_31 % m); int r; xassert(m > 0); do { r = rng_next_rand(rand); } while (t <= (unsigned int)r); return r % m; } /*********************************************************************** * NAME * * rng_delete_rand - delete pseudo-random number generator * * SYNOPSIS * * #include "glprng.h" * void rng_delete_rand(RNG *rand); * * DESCRIPTION * * The routine rng_delete_rand frees all the memory allocated to the * specified pseudo-random number generator. */ void rng_delete_rand(RNG *rand) { xfree(rand); return; } /**********************************************************************/ #if 0 /* To be sure that this modified version produces the same results as the original version, run this validation program. */ int main(void) { RNG *rand; int j; rand = rng_create_rand(); rng_init_rand(rand, -314159); if (rng_next_rand(rand) != 119318998) { fprintf(stderr, "Failure on the first try!\n"); return -1; } for (j = 1; j <= 133; j++) rng_next_rand(rand); if (rng_unif_rand(rand, 0x55555555) != 748103812) { fprintf(stderr, "Failure on the second try!\n"); return -2; } fprintf(stderr, "OK, the random-number generator routines seem to" " work!\n"); rng_delete_rand(rand); return 0; } #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpapi.h0000644000076500000240000003030213524616144025022 0ustar tamasstaff00000000000000/* glpapi.h (application program interface) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPAPI_H #define GLPAPI_H #define GLP_PROB_DEFINED typedef struct glp_prob glp_prob; #include "glpk.h" #include "glpavl.h" #include "glpbfd.h" typedef struct GLPROW GLPROW; typedef struct GLPCOL GLPCOL; typedef struct GLPAIJ GLPAIJ; #define GLP_PROB_MAGIC 0xD7D9D6C2 struct glp_prob { /* LP/MIP problem object */ int magic; /* magic value used for debugging */ DMP *pool; /* memory pool to store problem object components */ glp_tree *tree; /* pointer to the search tree; set by the MIP solver when this object is used in the tree as a core MIP object */ void *parms; /* reserved for backward compatibility */ /*--------------------------------------------------------------*/ /* LP/MIP data */ char *name; /* problem name (1 to 255 chars); NULL means no name is assigned to the problem */ char *obj; /* objective function name (1 to 255 chars); NULL means no name is assigned to the objective function */ int dir; /* optimization direction flag (objective "sense"): GLP_MIN - minimization GLP_MAX - maximization */ double c0; /* constant term of the objective function ("shift") */ int m_max; /* length of the array of rows (enlarged automatically) */ int n_max; /* length of the array of columns (enlarged automatically) */ int m; /* number of rows, 0 <= m <= m_max */ int n; /* number of columns, 0 <= n <= n_max */ int nnz; /* number of non-zero constraint coefficients, nnz >= 0 */ GLPROW **row; /* GLPROW *row[1+m_max]; */ /* row[i], 1 <= i <= m, is a pointer to i-th row */ GLPCOL **col; /* GLPCOL *col[1+n_max]; */ /* col[j], 1 <= j <= n, is a pointer to j-th column */ AVL *r_tree; /* row index to find rows by their names; NULL means this index does not exist */ AVL *c_tree; /* column index to find columns by their names; NULL means this index does not exist */ /*--------------------------------------------------------------*/ /* basis factorization (LP) */ int valid; /* the factorization is valid only if this flag is set */ int *head; /* int head[1+m_max]; */ /* basis header (valid only if the factorization is valid); head[i] = k is the ordinal number of auxiliary (1 <= k <= m) or structural (m+1 <= k <= m+n) variable which corresponds to i-th basic variable xB[i], 1 <= i <= m */ glp_bfcp *bfcp; /* basis factorization control parameters; may be NULL */ BFD *bfd; /* BFD bfd[1:m,1:m]; */ /* basis factorization driver; may be NULL */ /*--------------------------------------------------------------*/ /* basic solution (LP) */ int pbs_stat; /* primal basic solution status: GLP_UNDEF - primal solution is undefined GLP_FEAS - primal solution is feasible GLP_INFEAS - primal solution is infeasible GLP_NOFEAS - no primal feasible solution exists */ int dbs_stat; /* dual basic solution status: GLP_UNDEF - dual solution is undefined GLP_FEAS - dual solution is feasible GLP_INFEAS - dual solution is infeasible GLP_NOFEAS - no dual feasible solution exists */ double obj_val; /* objective function value */ int it_cnt; /* simplex method iteration count; increased by one on performing one simplex iteration */ int some; /* ordinal number of some auxiliary or structural variable having certain property, 0 <= some <= m+n */ /*--------------------------------------------------------------*/ /* interior-point solution (LP) */ int ipt_stat; /* interior-point solution status: GLP_UNDEF - interior solution is undefined GLP_OPT - interior solution is optimal GLP_INFEAS - interior solution is infeasible GLP_NOFEAS - no feasible solution exists */ double ipt_obj; /* objective function value */ /*--------------------------------------------------------------*/ /* integer solution (MIP) */ int mip_stat; /* integer solution status: GLP_UNDEF - integer solution is undefined GLP_OPT - integer solution is optimal GLP_FEAS - integer solution is feasible GLP_NOFEAS - no integer solution exists */ double mip_obj; /* objective function value */ }; struct GLPROW { /* LP/MIP row (auxiliary variable) */ int i; /* ordinal number (1 to m) assigned to this row */ char *name; /* row name (1 to 255 chars); NULL means no name is assigned to this row */ AVLNODE *node; /* pointer to corresponding node in the row index; NULL means that either the row index does not exist or this row has no name assigned */ #if 1 /* 20/IX-2008 */ int level; unsigned char origin; unsigned char klass; #endif int type; /* type of the auxiliary variable: GLP_FR - free variable GLP_LO - variable with lower bound GLP_UP - variable with upper bound GLP_DB - double-bounded variable GLP_FX - fixed variable */ double lb; /* non-scaled */ /* lower bound; if the row has no lower bound, lb is zero */ double ub; /* non-scaled */ /* upper bound; if the row has no upper bound, ub is zero */ /* if the row type is GLP_FX, ub is equal to lb */ GLPAIJ *ptr; /* non-scaled */ /* pointer to doubly linked list of constraint coefficients which are placed in this row */ double rii; /* diagonal element r[i,i] of scaling matrix R for this row; if the scaling is not used, r[i,i] is 1 */ int stat; /* status of the auxiliary variable: GLP_BS - basic variable GLP_NL - non-basic variable on lower bound GLP_NU - non-basic variable on upper bound GLP_NF - non-basic free variable GLP_NS - non-basic fixed variable */ int bind; /* if the auxiliary variable is basic, head[bind] refers to this row, otherwise, bind is 0; this attribute is valid only if the basis factorization is valid */ double prim; /* non-scaled */ /* primal value of the auxiliary variable in basic solution */ double dual; /* non-scaled */ /* dual value of the auxiliary variable in basic solution */ double pval; /* non-scaled */ /* primal value of the auxiliary variable in interior solution */ double dval; /* non-scaled */ /* dual value of the auxiliary variable in interior solution */ double mipx; /* non-scaled */ /* primal value of the auxiliary variable in integer solution */ }; struct GLPCOL { /* LP/MIP column (structural variable) */ int j; /* ordinal number (1 to n) assigned to this column */ char *name; /* column name (1 to 255 chars); NULL means no name is assigned to this column */ AVLNODE *node; /* pointer to corresponding node in the column index; NULL means that either the column index does not exist or the column has no name assigned */ int kind; /* kind of the structural variable: GLP_CV - continuous variable GLP_IV - integer or binary variable */ int type; /* type of the structural variable: GLP_FR - free variable GLP_LO - variable with lower bound GLP_UP - variable with upper bound GLP_DB - double-bounded variable GLP_FX - fixed variable */ double lb; /* non-scaled */ /* lower bound; if the column has no lower bound, lb is zero */ double ub; /* non-scaled */ /* upper bound; if the column has no upper bound, ub is zero */ /* if the column type is GLP_FX, ub is equal to lb */ double coef; /* non-scaled */ /* objective coefficient at the structural variable */ GLPAIJ *ptr; /* non-scaled */ /* pointer to doubly linked list of constraint coefficients which are placed in this column */ double sjj; /* diagonal element s[j,j] of scaling matrix S for this column; if the scaling is not used, s[j,j] is 1 */ int stat; /* status of the structural variable: GLP_BS - basic variable GLP_NL - non-basic variable on lower bound GLP_NU - non-basic variable on upper bound GLP_NF - non-basic free variable GLP_NS - non-basic fixed variable */ int bind; /* if the structural variable is basic, head[bind] refers to this column; otherwise, bind is 0; this attribute is valid only if the basis factorization is valid */ double prim; /* non-scaled */ /* primal value of the structural variable in basic solution */ double dual; /* non-scaled */ /* dual value of the structural variable in basic solution */ double pval; /* non-scaled */ /* primal value of the structural variable in interior solution */ double dval; /* non-scaled */ /* dual value of the structural variable in interior solution */ double mipx; /* non-scaled */ /* primal value of the structural variable in integer solution */ }; struct GLPAIJ { /* constraint coefficient a[i,j] */ GLPROW *row; /* pointer to row, where this coefficient is placed */ GLPCOL *col; /* pointer to column, where this coefficient is placed */ double val; /* numeric (non-zero) value of this coefficient */ GLPAIJ *r_prev; /* pointer to previous coefficient in the same row */ GLPAIJ *r_next; /* pointer to next coefficient in the same row */ GLPAIJ *c_prev; /* pointer to previous coefficient in the same column */ GLPAIJ *c_next; /* pointer to next coefficient in the same column */ }; void _glp_check_kkt(glp_prob *P, int sol, int cond, double *ae_max, int *ae_ind, double *re_max, int *re_ind); /* check feasibility and optimality conditions */ #define lpx_put_solution _glp_put_solution void lpx_put_solution(glp_prob *lp, int inval, const int *p_stat, const int *d_stat, const double *obj_val, const int r_stat[], const double r_prim[], const double r_dual[], const int c_stat[], const double c_prim[], const double c_dual[]); /* store basic solution components */ #define lpx_put_mip_soln _glp_put_mip_soln void lpx_put_mip_soln(LPX *lp, int i_stat, double row_mipx[], double col_mipx[]); /* store mixed integer solution components */ #if 1 /* 28/XI-2009 */ int _glp_analyze_row(glp_prob *P, int len, const int ind[], const double val[], int type, double rhs, double eps, int *_piv, double *_x, double *_dx, double *_y, double *_dy, double *_dz); /* simulate one iteration of dual simplex method */ #endif #if 1 /* 08/XII-2009 */ void _glp_mpl_init_rand(glp_tran *tran, int seed); #endif #define glp_skpgen _glp_skpgen void glp_skpgen(int n, int r, int type, int v, int s, int a[], int *b, int c[]); /* Pisinger's 0-1 single knapsack problem generator */ #if 1 /* 28/V-2010 */ int _glp_intopt1(glp_prob *P, const glp_iocp *parm); #endif #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpnpp01.c0000644000076500000240000007106313524616144025213 0ustar tamasstaff00000000000000/* glpnpp01.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wshorten-64-to-32" #pragma clang diagnostic ignored "-Wsometimes-uninitialized" #endif #include "glpnpp.h" NPP *npp_create_wksp(void) { /* create LP/MIP preprocessor workspace */ NPP *npp; npp = xmalloc(sizeof(NPP)); npp->orig_dir = 0; npp->orig_m = npp->orig_n = npp->orig_nnz = 0; npp->pool = dmp_create_pool(); npp->name = npp->obj = NULL; npp->c0 = 0.0; npp->nrows = npp->ncols = 0; npp->r_head = npp->r_tail = NULL; npp->c_head = npp->c_tail = NULL; npp->stack = dmp_create_pool(); npp->top = NULL; #if 0 /* 16/XII-2009 */ memset(&npp->count, 0, sizeof(npp->count)); #endif npp->m = npp->n = npp->nnz = 0; npp->row_ref = npp->col_ref = NULL; npp->sol = npp->scaling = 0; npp->p_stat = npp->d_stat = npp->t_stat = npp->i_stat = 0; npp->r_stat = NULL; /*npp->r_prim =*/ npp->r_pi = NULL; npp->c_stat = NULL; npp->c_value = /*npp->c_dual =*/ NULL; return npp; } void npp_insert_row(NPP *npp, NPPROW *row, int where) { /* insert row to the row list */ if (where == 0) { /* insert row to the beginning of the row list */ row->prev = NULL; row->next = npp->r_head; if (row->next == NULL) npp->r_tail = row; else row->next->prev = row; npp->r_head = row; } else { /* insert row to the end of the row list */ row->prev = npp->r_tail; row->next = NULL; if (row->prev == NULL) npp->r_head = row; else row->prev->next = row; npp->r_tail = row; } return; } void npp_remove_row(NPP *npp, NPPROW *row) { /* remove row from the row list */ if (row->prev == NULL) npp->r_head = row->next; else row->prev->next = row->next; if (row->next == NULL) npp->r_tail = row->prev; else row->next->prev = row->prev; return; } void npp_activate_row(NPP *npp, NPPROW *row) { /* make row active */ if (!row->temp) { row->temp = 1; /* move the row to the beginning of the row list */ npp_remove_row(npp, row); npp_insert_row(npp, row, 0); } return; } void npp_deactivate_row(NPP *npp, NPPROW *row) { /* make row inactive */ if (row->temp) { row->temp = 0; /* move the row to the end of the row list */ npp_remove_row(npp, row); npp_insert_row(npp, row, 1); } return; } void npp_insert_col(NPP *npp, NPPCOL *col, int where) { /* insert column to the column list */ if (where == 0) { /* insert column to the beginning of the column list */ col->prev = NULL; col->next = npp->c_head; if (col->next == NULL) npp->c_tail = col; else col->next->prev = col; npp->c_head = col; } else { /* insert column to the end of the column list */ col->prev = npp->c_tail; col->next = NULL; if (col->prev == NULL) npp->c_head = col; else col->prev->next = col; npp->c_tail = col; } return; } void npp_remove_col(NPP *npp, NPPCOL *col) { /* remove column from the column list */ if (col->prev == NULL) npp->c_head = col->next; else col->prev->next = col->next; if (col->next == NULL) npp->c_tail = col->prev; else col->next->prev = col->prev; return; } void npp_activate_col(NPP *npp, NPPCOL *col) { /* make column active */ if (!col->temp) { col->temp = 1; /* move the column to the beginning of the column list */ npp_remove_col(npp, col); npp_insert_col(npp, col, 0); } return; } void npp_deactivate_col(NPP *npp, NPPCOL *col) { /* make column inactive */ if (col->temp) { col->temp = 0; /* move the column to the end of the column list */ npp_remove_col(npp, col); npp_insert_col(npp, col, 1); } return; } NPPROW *npp_add_row(NPP *npp) { /* add new row to the current problem */ NPPROW *row; row = dmp_get_atom(npp->pool, sizeof(NPPROW)); row->i = ++(npp->nrows); row->name = NULL; row->lb = -DBL_MAX, row->ub = +DBL_MAX; row->ptr = NULL; row->temp = 0; npp_insert_row(npp, row, 1); return row; } NPPCOL *npp_add_col(NPP *npp) { /* add new column to the current problem */ NPPCOL *col; col = dmp_get_atom(npp->pool, sizeof(NPPCOL)); col->j = ++(npp->ncols); col->name = NULL; #if 0 col->kind = GLP_CV; #else col->is_int = 0; #endif col->lb = col->ub = col->coef = 0.0; col->ptr = NULL; col->temp = 0; npp_insert_col(npp, col, 1); return col; } NPPAIJ *npp_add_aij(NPP *npp, NPPROW *row, NPPCOL *col, double val) { /* add new element to the constraint matrix */ NPPAIJ *aij; aij = dmp_get_atom(npp->pool, sizeof(NPPAIJ)); aij->row = row; aij->col = col; aij->val = val; aij->r_prev = NULL; aij->r_next = row->ptr; aij->c_prev = NULL; aij->c_next = col->ptr; if (aij->r_next != NULL) aij->r_next->r_prev = aij; if (aij->c_next != NULL) aij->c_next->c_prev = aij; row->ptr = col->ptr = aij; return aij; } int npp_row_nnz(NPP *npp, NPPROW *row) { /* count number of non-zero coefficients in row */ NPPAIJ *aij; int nnz; xassert(npp == npp); nnz = 0; for (aij = row->ptr; aij != NULL; aij = aij->r_next) nnz++; return nnz; } int npp_col_nnz(NPP *npp, NPPCOL *col) { /* count number of non-zero coefficients in column */ NPPAIJ *aij; int nnz; xassert(npp == npp); nnz = 0; for (aij = col->ptr; aij != NULL; aij = aij->c_next) nnz++; return nnz; } void *npp_push_tse(NPP *npp, int (*func)(NPP *npp, void *info), int size) { /* push new entry to the transformation stack */ NPPTSE *tse; tse = dmp_get_atom(npp->stack, sizeof(NPPTSE)); tse->func = func; tse->info = dmp_get_atom(npp->stack, size); tse->link = npp->top; npp->top = tse; return tse->info; } #if 1 /* 23/XII-2009 */ void npp_erase_row(NPP *npp, NPPROW *row) { /* erase row content to make it empty */ NPPAIJ *aij; while (row->ptr != NULL) { aij = row->ptr; row->ptr = aij->r_next; if (aij->c_prev == NULL) aij->col->ptr = aij->c_next; else aij->c_prev->c_next = aij->c_next; if (aij->c_next == NULL) ; else aij->c_next->c_prev = aij->c_prev; dmp_free_atom(npp->pool, aij, sizeof(NPPAIJ)); } return; } #endif void npp_del_row(NPP *npp, NPPROW *row) { /* remove row from the current problem */ #if 0 /* 23/XII-2009 */ NPPAIJ *aij; #endif if (row->name != NULL) dmp_free_atom(npp->pool, row->name, strlen(row->name)+1); #if 0 /* 23/XII-2009 */ while (row->ptr != NULL) { aij = row->ptr; row->ptr = aij->r_next; if (aij->c_prev == NULL) aij->col->ptr = aij->c_next; else aij->c_prev->c_next = aij->c_next; if (aij->c_next == NULL) ; else aij->c_next->c_prev = aij->c_prev; dmp_free_atom(npp->pool, aij, sizeof(NPPAIJ)); } #else npp_erase_row(npp, row); #endif npp_remove_row(npp, row); dmp_free_atom(npp->pool, row, sizeof(NPPROW)); return; } void npp_del_col(NPP *npp, NPPCOL *col) { /* remove column from the current problem */ NPPAIJ *aij; if (col->name != NULL) dmp_free_atom(npp->pool, col->name, strlen(col->name)+1); while (col->ptr != NULL) { aij = col->ptr; col->ptr = aij->c_next; if (aij->r_prev == NULL) aij->row->ptr = aij->r_next; else aij->r_prev->r_next = aij->r_next; if (aij->r_next == NULL) ; else aij->r_next->r_prev = aij->r_prev; dmp_free_atom(npp->pool, aij, sizeof(NPPAIJ)); } npp_remove_col(npp, col); dmp_free_atom(npp->pool, col, sizeof(NPPCOL)); return; } void npp_del_aij(NPP *npp, NPPAIJ *aij) { /* remove element from the constraint matrix */ if (aij->r_prev == NULL) aij->row->ptr = aij->r_next; else aij->r_prev->r_next = aij->r_next; if (aij->r_next == NULL) ; else aij->r_next->r_prev = aij->r_prev; if (aij->c_prev == NULL) aij->col->ptr = aij->c_next; else aij->c_prev->c_next = aij->c_next; if (aij->c_next == NULL) ; else aij->c_next->c_prev = aij->c_prev; dmp_free_atom(npp->pool, aij, sizeof(NPPAIJ)); return; } void npp_load_prob(NPP *npp, glp_prob *orig, int names, int sol, int scaling) { /* load original problem into the preprocessor workspace */ int m = orig->m; int n = orig->n; NPPROW **link; int i, j; double dir; xassert(names == GLP_OFF || names == GLP_ON); xassert(sol == GLP_SOL || sol == GLP_IPT || sol == GLP_MIP); xassert(scaling == GLP_OFF || scaling == GLP_ON); if (sol == GLP_MIP) xassert(!scaling); npp->orig_dir = orig->dir; if (npp->orig_dir == GLP_MIN) dir = +1.0; else if (npp->orig_dir == GLP_MAX) dir = -1.0; else xassert(npp != npp); npp->orig_m = m; npp->orig_n = n; npp->orig_nnz = orig->nnz; if (names && orig->name != NULL) { npp->name = dmp_get_atom(npp->pool, strlen(orig->name)+1); strcpy(npp->name, orig->name); } if (names && orig->obj != NULL) { npp->obj = dmp_get_atom(npp->pool, strlen(orig->obj)+1); strcpy(npp->obj, orig->obj); } npp->c0 = dir * orig->c0; /* load rows */ link = xcalloc(1+m, sizeof(NPPROW *)); for (i = 1; i <= m; i++) { GLPROW *rrr = orig->row[i]; NPPROW *row; link[i] = row = npp_add_row(npp); xassert(row->i == i); if (names && rrr->name != NULL) { row->name = dmp_get_atom(npp->pool, strlen(rrr->name)+1); strcpy(row->name, rrr->name); } if (!scaling) { if (rrr->type == GLP_FR) row->lb = -DBL_MAX, row->ub = +DBL_MAX; else if (rrr->type == GLP_LO) row->lb = rrr->lb, row->ub = +DBL_MAX; else if (rrr->type == GLP_UP) row->lb = -DBL_MAX, row->ub = rrr->ub; else if (rrr->type == GLP_DB) row->lb = rrr->lb, row->ub = rrr->ub; else if (rrr->type == GLP_FX) row->lb = row->ub = rrr->lb; else xassert(rrr != rrr); } else { double rii = rrr->rii; if (rrr->type == GLP_FR) row->lb = -DBL_MAX, row->ub = +DBL_MAX; else if (rrr->type == GLP_LO) row->lb = rrr->lb * rii, row->ub = +DBL_MAX; else if (rrr->type == GLP_UP) row->lb = -DBL_MAX, row->ub = rrr->ub * rii; else if (rrr->type == GLP_DB) row->lb = rrr->lb * rii, row->ub = rrr->ub * rii; else if (rrr->type == GLP_FX) row->lb = row->ub = rrr->lb * rii; else xassert(rrr != rrr); } } /* load columns and constraint coefficients */ for (j = 1; j <= n; j++) { GLPCOL *ccc = orig->col[j]; GLPAIJ *aaa; NPPCOL *col; col = npp_add_col(npp); xassert(col->j == j); if (names && ccc->name != NULL) { col->name = dmp_get_atom(npp->pool, strlen(ccc->name)+1); strcpy(col->name, ccc->name); } if (sol == GLP_MIP) #if 0 col->kind = ccc->kind; #else col->is_int = (char)(ccc->kind == GLP_IV); #endif if (!scaling) { if (ccc->type == GLP_FR) col->lb = -DBL_MAX, col->ub = +DBL_MAX; else if (ccc->type == GLP_LO) col->lb = ccc->lb, col->ub = +DBL_MAX; else if (ccc->type == GLP_UP) col->lb = -DBL_MAX, col->ub = ccc->ub; else if (ccc->type == GLP_DB) col->lb = ccc->lb, col->ub = ccc->ub; else if (ccc->type == GLP_FX) col->lb = col->ub = ccc->lb; else xassert(ccc != ccc); col->coef = dir * ccc->coef; for (aaa = ccc->ptr; aaa != NULL; aaa = aaa->c_next) npp_add_aij(npp, link[aaa->row->i], col, aaa->val); } else { double sjj = ccc->sjj; if (ccc->type == GLP_FR) col->lb = -DBL_MAX, col->ub = +DBL_MAX; else if (ccc->type == GLP_LO) col->lb = ccc->lb / sjj, col->ub = +DBL_MAX; else if (ccc->type == GLP_UP) col->lb = -DBL_MAX, col->ub = ccc->ub / sjj; else if (ccc->type == GLP_DB) col->lb = ccc->lb / sjj, col->ub = ccc->ub / sjj; else if (ccc->type == GLP_FX) col->lb = col->ub = ccc->lb / sjj; else xassert(ccc != ccc); col->coef = dir * ccc->coef * sjj; for (aaa = ccc->ptr; aaa != NULL; aaa = aaa->c_next) npp_add_aij(npp, link[aaa->row->i], col, aaa->row->rii * aaa->val * sjj); } } xfree(link); /* keep solution indicator and scaling option */ npp->sol = sol; npp->scaling = scaling; return; } void npp_build_prob(NPP *npp, glp_prob *prob) { /* build resultant (preprocessed) problem */ NPPROW *row; NPPCOL *col; NPPAIJ *aij; int i, j, type, len, *ind; double dir, *val; glp_erase_prob(prob); glp_set_prob_name(prob, npp->name); glp_set_obj_name(prob, npp->obj); glp_set_obj_dir(prob, npp->orig_dir); if (npp->orig_dir == GLP_MIN) dir = +1.0; else if (npp->orig_dir == GLP_MAX) dir = -1.0; else xassert(npp != npp); glp_set_obj_coef(prob, 0, dir * npp->c0); /* build rows */ for (row = npp->r_head; row != NULL; row = row->next) { row->temp = i = glp_add_rows(prob, 1); glp_set_row_name(prob, i, row->name); if (row->lb == -DBL_MAX && row->ub == +DBL_MAX) type = GLP_FR; else if (row->ub == +DBL_MAX) type = GLP_LO; else if (row->lb == -DBL_MAX) type = GLP_UP; else if (row->lb != row->ub) type = GLP_DB; else type = GLP_FX; glp_set_row_bnds(prob, i, type, row->lb, row->ub); } /* build columns and the constraint matrix */ ind = xcalloc(1+prob->m, sizeof(int)); val = xcalloc(1+prob->m, sizeof(double)); for (col = npp->c_head; col != NULL; col = col->next) { j = glp_add_cols(prob, 1); glp_set_col_name(prob, j, col->name); #if 0 glp_set_col_kind(prob, j, col->kind); #else glp_set_col_kind(prob, j, col->is_int ? GLP_IV : GLP_CV); #endif if (col->lb == -DBL_MAX && col->ub == +DBL_MAX) type = GLP_FR; else if (col->ub == +DBL_MAX) type = GLP_LO; else if (col->lb == -DBL_MAX) type = GLP_UP; else if (col->lb != col->ub) type = GLP_DB; else type = GLP_FX; glp_set_col_bnds(prob, j, type, col->lb, col->ub); glp_set_obj_coef(prob, j, dir * col->coef); len = 0; for (aij = col->ptr; aij != NULL; aij = aij->c_next) { len++; ind[len] = aij->row->temp; val[len] = aij->val; } glp_set_mat_col(prob, j, len, ind, val); } xfree(ind); xfree(val); /* resultant problem has been built */ npp->m = prob->m; npp->n = prob->n; npp->nnz = prob->nnz; npp->row_ref = xcalloc(1+npp->m, sizeof(int)); npp->col_ref = xcalloc(1+npp->n, sizeof(int)); for (row = npp->r_head, i = 0; row != NULL; row = row->next) npp->row_ref[++i] = row->i; for (col = npp->c_head, j = 0; col != NULL; col = col->next) npp->col_ref[++j] = col->j; /* transformed problem segment is no longer needed */ dmp_delete_pool(npp->pool), npp->pool = NULL; npp->name = npp->obj = NULL; npp->c0 = 0.0; npp->r_head = npp->r_tail = NULL; npp->c_head = npp->c_tail = NULL; return; } void npp_postprocess(NPP *npp, glp_prob *prob) { /* postprocess solution from the resultant problem */ GLPROW *row; GLPCOL *col; NPPTSE *tse; int i, j, k; double dir; xassert(npp->orig_dir == prob->dir); if (npp->orig_dir == GLP_MIN) dir = +1.0; else if (npp->orig_dir == GLP_MAX) dir = -1.0; else xassert(npp != npp); xassert(npp->m == prob->m); xassert(npp->n == prob->n); xassert(npp->nnz == prob->nnz); /* copy solution status */ if (npp->sol == GLP_SOL) { npp->p_stat = prob->pbs_stat; npp->d_stat = prob->dbs_stat; } else if (npp->sol == GLP_IPT) npp->t_stat = prob->ipt_stat; else if (npp->sol == GLP_MIP) npp->i_stat = prob->mip_stat; else xassert(npp != npp); /* allocate solution arrays */ if (npp->sol == GLP_SOL) { if (npp->r_stat == NULL) npp->r_stat = xcalloc(1+npp->nrows, sizeof(char)); for (i = 1; i <= npp->nrows; i++) npp->r_stat[i] = 0; if (npp->c_stat == NULL) npp->c_stat = xcalloc(1+npp->ncols, sizeof(char)); for (j = 1; j <= npp->ncols; j++) npp->c_stat[j] = 0; } #if 0 if (npp->r_prim == NULL) npp->r_prim = xcalloc(1+npp->nrows, sizeof(double)); for (i = 1; i <= npp->nrows; i++) npp->r_prim[i] = DBL_MAX; #endif if (npp->c_value == NULL) npp->c_value = xcalloc(1+npp->ncols, sizeof(double)); for (j = 1; j <= npp->ncols; j++) npp->c_value[j] = DBL_MAX; if (npp->sol != GLP_MIP) { if (npp->r_pi == NULL) npp->r_pi = xcalloc(1+npp->nrows, sizeof(double)); for (i = 1; i <= npp->nrows; i++) npp->r_pi[i] = DBL_MAX; #if 0 if (npp->c_dual == NULL) npp->c_dual = xcalloc(1+npp->ncols, sizeof(double)); for (j = 1; j <= npp->ncols; j++) npp->c_dual[j] = DBL_MAX; #endif } /* copy solution components from the resultant problem */ if (npp->sol == GLP_SOL) { for (i = 1; i <= npp->m; i++) { row = prob->row[i]; k = npp->row_ref[i]; npp->r_stat[k] = (char)row->stat; /*npp->r_prim[k] = row->prim;*/ npp->r_pi[k] = dir * row->dual; } for (j = 1; j <= npp->n; j++) { col = prob->col[j]; k = npp->col_ref[j]; npp->c_stat[k] = (char)col->stat; npp->c_value[k] = col->prim; /*npp->c_dual[k] = dir * col->dual;*/ } } else if (npp->sol == GLP_IPT) { for (i = 1; i <= npp->m; i++) { row = prob->row[i]; k = npp->row_ref[i]; /*npp->r_prim[k] = row->pval;*/ npp->r_pi[k] = dir * row->dval; } for (j = 1; j <= npp->n; j++) { col = prob->col[j]; k = npp->col_ref[j]; npp->c_value[k] = col->pval; /*npp->c_dual[k] = dir * col->dval;*/ } } else if (npp->sol == GLP_MIP) { #if 0 for (i = 1; i <= npp->m; i++) { row = prob->row[i]; k = npp->row_ref[i]; /*npp->r_prim[k] = row->mipx;*/ } #endif for (j = 1; j <= npp->n; j++) { col = prob->col[j]; k = npp->col_ref[j]; npp->c_value[k] = col->mipx; } } else xassert(npp != npp); /* perform postprocessing to construct solution to the original problem */ for (tse = npp->top; tse != NULL; tse = tse->link) { xassert(tse->func != NULL); xassert(tse->func(npp, tse->info) == 0); } return; } void npp_unload_sol(NPP *npp, glp_prob *orig) { /* store solution to the original problem */ GLPROW *row; GLPCOL *col; int i, j; double dir; xassert(npp->orig_dir == orig->dir); if (npp->orig_dir == GLP_MIN) dir = +1.0; else if (npp->orig_dir == GLP_MAX) dir = -1.0; else xassert(npp != npp); xassert(npp->orig_m == orig->m); xassert(npp->orig_n == orig->n); xassert(npp->orig_nnz == orig->nnz); if (npp->sol == GLP_SOL) { /* store basic solution */ orig->valid = 0; orig->pbs_stat = npp->p_stat; orig->dbs_stat = npp->d_stat; orig->obj_val = orig->c0; orig->some = 0; for (i = 1; i <= orig->m; i++) { row = orig->row[i]; row->stat = npp->r_stat[i]; if (!npp->scaling) { /*row->prim = npp->r_prim[i];*/ row->dual = dir * npp->r_pi[i]; } else { /*row->prim = npp->r_prim[i] / row->rii;*/ row->dual = dir * npp->r_pi[i] * row->rii; } if (row->stat == GLP_BS) row->dual = 0.0; else if (row->stat == GLP_NL) { xassert(row->type == GLP_LO || row->type == GLP_DB); row->prim = row->lb; } else if (row->stat == GLP_NU) { xassert(row->type == GLP_UP || row->type == GLP_DB); row->prim = row->ub; } else if (row->stat == GLP_NF) { xassert(row->type == GLP_FR); row->prim = 0.0; } else if (row->stat == GLP_NS) { xassert(row->type == GLP_FX); row->prim = row->lb; } else xassert(row != row); } for (j = 1; j <= orig->n; j++) { col = orig->col[j]; col->stat = npp->c_stat[j]; if (!npp->scaling) { col->prim = npp->c_value[j]; /*col->dual = dir * npp->c_dual[j];*/ } else { col->prim = npp->c_value[j] * col->sjj; /*col->dual = dir * npp->c_dual[j] / col->sjj;*/ } if (col->stat == GLP_BS) col->dual = 0.0; #if 1 else if (col->stat == GLP_NL) { xassert(col->type == GLP_LO || col->type == GLP_DB); col->prim = col->lb; } else if (col->stat == GLP_NU) { xassert(col->type == GLP_UP || col->type == GLP_DB); col->prim = col->ub; } else if (col->stat == GLP_NF) { xassert(col->type == GLP_FR); col->prim = 0.0; } else if (col->stat == GLP_NS) { xassert(col->type == GLP_FX); col->prim = col->lb; } else xassert(col != col); #endif orig->obj_val += col->coef * col->prim; } #if 1 /* compute primal values of inactive rows */ for (i = 1; i <= orig->m; i++) { row = orig->row[i]; if (row->stat == GLP_BS) { GLPAIJ *aij; double temp; temp = 0.0; for (aij = row->ptr; aij != NULL; aij = aij->r_next) temp += aij->val * aij->col->prim; row->prim = temp; } } /* compute reduced costs of active columns */ for (j = 1; j <= orig->n; j++) { col = orig->col[j]; if (col->stat != GLP_BS) { GLPAIJ *aij; double temp; temp = col->coef; for (aij = col->ptr; aij != NULL; aij = aij->c_next) temp -= aij->val * aij->row->dual; col->dual = temp; } } #endif } else if (npp->sol == GLP_IPT) { /* store interior-point solution */ orig->ipt_stat = npp->t_stat; orig->ipt_obj = orig->c0; for (i = 1; i <= orig->m; i++) { row = orig->row[i]; if (!npp->scaling) { /*row->pval = npp->r_prim[i];*/ row->dval = dir * npp->r_pi[i]; } else { /*row->pval = npp->r_prim[i] / row->rii;*/ row->dval = dir * npp->r_pi[i] * row->rii; } } for (j = 1; j <= orig->n; j++) { col = orig->col[j]; if (!npp->scaling) { col->pval = npp->c_value[j]; /*col->dval = dir * npp->c_dual[j];*/ } else { col->pval = npp->c_value[j] * col->sjj; /*col->dval = dir * npp->c_dual[j] / col->sjj;*/ } orig->ipt_obj += col->coef * col->pval; } #if 1 /* compute row primal values */ for (i = 1; i <= orig->m; i++) { row = orig->row[i]; { GLPAIJ *aij; double temp; temp = 0.0; for (aij = row->ptr; aij != NULL; aij = aij->r_next) temp += aij->val * aij->col->pval; row->pval = temp; } } /* compute column dual values */ for (j = 1; j <= orig->n; j++) { col = orig->col[j]; { GLPAIJ *aij; double temp; temp = col->coef; for (aij = col->ptr; aij != NULL; aij = aij->c_next) temp -= aij->val * aij->row->dval; col->dval = temp; } } #endif } else if (npp->sol == GLP_MIP) { /* store MIP solution */ xassert(!npp->scaling); orig->mip_stat = npp->i_stat; orig->mip_obj = orig->c0; #if 0 for (i = 1; i <= orig->m; i++) { row = orig->row[i]; /*row->mipx = npp->r_prim[i];*/ } #endif for (j = 1; j <= orig->n; j++) { col = orig->col[j]; col->mipx = npp->c_value[j]; if (col->kind == GLP_IV) xassert(col->mipx == floor(col->mipx)); orig->mip_obj += col->coef * col->mipx; } #if 1 /* compute row primal values */ for (i = 1; i <= orig->m; i++) { row = orig->row[i]; { GLPAIJ *aij; double temp; temp = 0.0; for (aij = row->ptr; aij != NULL; aij = aij->r_next) temp += aij->val * aij->col->mipx; row->mipx = temp; } } #endif } else xassert(npp != npp); return; } void npp_delete_wksp(NPP *npp) { /* delete LP/MIP preprocessor workspace */ if (npp->pool != NULL) dmp_delete_pool(npp->pool); if (npp->stack != NULL) dmp_delete_pool(npp->stack); if (npp->row_ref != NULL) xfree(npp->row_ref); if (npp->col_ref != NULL) xfree(npp->col_ref); if (npp->r_stat != NULL) xfree(npp->r_stat); #if 0 if (npp->r_prim != NULL) xfree(npp->r_prim); #endif if (npp->r_pi != NULL) xfree(npp->r_pi); if (npp->c_stat != NULL) xfree(npp->c_stat); if (npp->c_value != NULL) xfree(npp->c_value); #if 0 if (npp->c_dual != NULL) xfree(npp->c_dual); #endif xfree(npp); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpluf.h0000644000076500000240000003546213524616144025053 0ustar tamasstaff00000000000000/* glpluf.h (LU-factorization) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPLUF_H #define GLPLUF_H /*********************************************************************** * The structure LUF defines LU-factorization of a square matrix A and * is the following quartet: * * [A] = (F, V, P, Q), (1) * * where F and V are such matrices that * * A = F * V, (2) * * and P and Q are such permutation matrices that the matrix * * L = P * F * inv(P) (3) * * is lower triangular with unity diagonal, and the matrix * * U = P * V * Q (4) * * is upper triangular. All the matrices have the order n. * * Matrices F and V are stored in row- and column-wise sparse format * as row and column linked lists of non-zero elements. Unity elements * on the main diagonal of matrix F are not stored. Pivot elements of * matrix V (which correspond to diagonal elements of matrix U) are * stored separately in an ordinary array. * * Permutation matrices P and Q are stored in ordinary arrays in both * row- and column-like formats. * * Matrices L and U are completely defined by matrices F, V, P, and Q * and therefore not stored explicitly. * * The factorization (1)-(4) is a version of LU-factorization. Indeed, * from (3) and (4) it follows that: * * F = inv(P) * L * P, * * U = inv(P) * U * inv(Q), * * and substitution into (2) leads to: * * A = F * V = inv(P) * L * U * inv(Q). * * For more details see the program documentation. */ typedef struct LUF LUF; struct LUF { /* LU-factorization of a square matrix */ int n_max; /* maximal value of n (increased automatically, if necessary) */ int n; /* the order of matrices A, F, V, P, Q */ int valid; /* the factorization is valid only if this flag is set */ /*--------------------------------------------------------------*/ /* matrix F in row-wise format */ int *fr_ptr; /* int fr_ptr[1+n_max]; */ /* fr_ptr[i], i = 1,...,n, is a pointer to the first element of i-th row in SVA */ int *fr_len; /* int fr_len[1+n_max]; */ /* fr_len[i], i = 1,...,n, is the number of elements in i-th row (except unity diagonal element) */ /*--------------------------------------------------------------*/ /* matrix F in column-wise format */ int *fc_ptr; /* int fc_ptr[1+n_max]; */ /* fc_ptr[j], j = 1,...,n, is a pointer to the first element of j-th column in SVA */ int *fc_len; /* int fc_len[1+n_max]; */ /* fc_len[j], j = 1,...,n, is the number of elements in j-th column (except unity diagonal element) */ /*--------------------------------------------------------------*/ /* matrix V in row-wise format */ int *vr_ptr; /* int vr_ptr[1+n_max]; */ /* vr_ptr[i], i = 1,...,n, is a pointer to the first element of i-th row in SVA */ int *vr_len; /* int vr_len[1+n_max]; */ /* vr_len[i], i = 1,...,n, is the number of elements in i-th row (except pivot element) */ int *vr_cap; /* int vr_cap[1+n_max]; */ /* vr_cap[i], i = 1,...,n, is the capacity of i-th row, i.e. maximal number of elements which can be stored in the row without relocating it, vr_cap[i] >= vr_len[i] */ double *vr_piv; /* double vr_piv[1+n_max]; */ /* vr_piv[p], p = 1,...,n, is the pivot element v[p,q] which corresponds to a diagonal element of matrix U = P*V*Q */ /*--------------------------------------------------------------*/ /* matrix V in column-wise format */ int *vc_ptr; /* int vc_ptr[1+n_max]; */ /* vc_ptr[j], j = 1,...,n, is a pointer to the first element of j-th column in SVA */ int *vc_len; /* int vc_len[1+n_max]; */ /* vc_len[j], j = 1,...,n, is the number of elements in j-th column (except pivot element) */ int *vc_cap; /* int vc_cap[1+n_max]; */ /* vc_cap[j], j = 1,...,n, is the capacity of j-th column, i.e. maximal number of elements which can be stored in the column without relocating it, vc_cap[j] >= vc_len[j] */ /*--------------------------------------------------------------*/ /* matrix P */ int *pp_row; /* int pp_row[1+n_max]; */ /* pp_row[i] = j means that P[i,j] = 1 */ int *pp_col; /* int pp_col[1+n_max]; */ /* pp_col[j] = i means that P[i,j] = 1 */ /* if i-th row or column of matrix F is i'-th row or column of matrix L, or if i-th row of matrix V is i'-th row of matrix U, then pp_row[i'] = i and pp_col[i] = i' */ /*--------------------------------------------------------------*/ /* matrix Q */ int *qq_row; /* int qq_row[1+n_max]; */ /* qq_row[i] = j means that Q[i,j] = 1 */ int *qq_col; /* int qq_col[1+n_max]; */ /* qq_col[j] = i means that Q[i,j] = 1 */ /* if j-th column of matrix V is j'-th column of matrix U, then qq_row[j] = j' and qq_col[j'] = j */ /*--------------------------------------------------------------*/ /* the Sparse Vector Area (SVA) is a set of locations used to store sparse vectors representing rows and columns of matrices F and V; each location is a doublet (ind, val), where ind is an index, and val is a numerical value of a sparse vector element; in the whole each sparse vector is a set of adjacent locations defined by a pointer to the first element and the number of elements; these pointer and number are stored in the corresponding matrix data structure (see above); the left part of SVA is used to store rows and columns of matrix V, and its right part is used to store rows and columns of matrix F; the middle part of SVA contains free (unused) locations */ int sv_size; /* the size of SVA, in locations; all locations are numbered by integers 1, ..., n, and location 0 is not used; if necessary, the SVA size is automatically increased */ int sv_beg, sv_end; /* SVA partitioning pointers: locations from 1 to sv_beg-1 belong to the left part locations from sv_beg to sv_end-1 belong to the middle part locations from sv_end to sv_size belong to the right part the size of the middle part is (sv_end - sv_beg) */ int *sv_ind; /* sv_ind[1+sv_size]; */ /* sv_ind[k], 1 <= k <= sv_size, is the index field of k-th location */ double *sv_val; /* sv_val[1+sv_size]; */ /* sv_val[k], 1 <= k <= sv_size, is the value field of k-th location */ /*--------------------------------------------------------------*/ /* in order to efficiently defragment the left part of SVA there is a doubly linked list of rows and columns of matrix V, where rows are numbered by 1, ..., n, while columns are numbered by n+1, ..., n+n, that allows uniquely identifying each row and column of V by only one integer; in this list rows and columns are ordered by ascending their pointers vr_ptr and vc_ptr */ int sv_head; /* the number of leftmost row/column */ int sv_tail; /* the number of rightmost row/column */ int *sv_prev; /* int sv_prev[1+n_max+n_max]; */ /* sv_prev[k], k = 1,...,n+n, is the number of a row/column which precedes k-th row/column */ int *sv_next; /* int sv_next[1+n_max+n_max]; */ /* sv_next[k], k = 1,...,n+n, is the number of a row/column which succedes k-th row/column */ /*--------------------------------------------------------------*/ /* working segment (used only during factorization) */ double *vr_max; /* int vr_max[1+n_max]; */ /* vr_max[i], 1 <= i <= n, is used only if i-th row of matrix V is active (i.e. belongs to the active submatrix), and is the largest magnitude of elements in i-th row; if vr_max[i] < 0, the largest magnitude is not known yet and should be computed by the pivoting routine */ /*--------------------------------------------------------------*/ /* in order to efficiently implement Markowitz strategy and Duff search technique there are two families {R[0], R[1], ..., R[n]} and {C[0], C[1], ..., C[n]}; member R[k] is the set of active rows of matrix V, which have k non-zeros, and member C[k] is the set of active columns of V, which have k non-zeros in the active submatrix (i.e. in the active rows); each set R[k] and C[k] is implemented as a separate doubly linked list */ int *rs_head; /* int rs_head[1+n_max]; */ /* rs_head[k], 0 <= k <= n, is the number of first active row, which has k non-zeros */ int *rs_prev; /* int rs_prev[1+n_max]; */ /* rs_prev[i], 1 <= i <= n, is the number of previous row, which has the same number of non-zeros as i-th row */ int *rs_next; /* int rs_next[1+n_max]; */ /* rs_next[i], 1 <= i <= n, is the number of next row, which has the same number of non-zeros as i-th row */ int *cs_head; /* int cs_head[1+n_max]; */ /* cs_head[k], 0 <= k <= n, is the number of first active column, which has k non-zeros (in the active rows) */ int *cs_prev; /* int cs_prev[1+n_max]; */ /* cs_prev[j], 1 <= j <= n, is the number of previous column, which has the same number of non-zeros (in the active rows) as j-th column */ int *cs_next; /* int cs_next[1+n_max]; */ /* cs_next[j], 1 <= j <= n, is the number of next column, which has the same number of non-zeros (in the active rows) as j-th column */ /* (end of working segment) */ /*--------------------------------------------------------------*/ /* working arrays */ int *flag; /* int flag[1+n_max]; */ /* integer working array */ double *work; /* double work[1+n_max]; */ /* floating-point working array */ /*--------------------------------------------------------------*/ /* control parameters */ int new_sva; /* new required size of the sparse vector area, in locations; set automatically by the factorizing routine */ double piv_tol; /* threshold pivoting tolerance, 0 < piv_tol < 1; element v[i,j] of the active submatrix fits to be pivot if it satisfies to the stability criterion |v[i,j]| >= piv_tol * max |v[i,*]|, i.e. if it is not very small in the magnitude among other elements in the same row; decreasing this parameter gives better sparsity at the expense of numerical accuracy and vice versa */ int piv_lim; /* maximal allowable number of pivot candidates to be considered; if piv_lim pivot candidates have been considered, the pivoting routine terminates the search with the best candidate found */ int suhl; /* if this flag is set, the pivoting routine applies a heuristic proposed by Uwe Suhl: if a column of the active submatrix has no eligible pivot candidates (i.e. all its elements do not satisfy to the stability criterion), the routine excludes it from futher consideration until it becomes column singleton; in many cases this allows reducing the time needed for pivot searching */ double eps_tol; /* epsilon tolerance; each element of the active submatrix, whose magnitude is less than eps_tol, is replaced by exact zero */ double max_gro; /* maximal allowable growth of elements of matrix V during all the factorization process; if on some eliminaion step the ratio big_v / max_a (see below) becomes greater than max_gro, matrix A is considered as ill-conditioned (assuming that the pivoting tolerance piv_tol has an appropriate value) */ /*--------------------------------------------------------------*/ /* some statistics */ int nnz_a; /* the number of non-zeros in matrix A */ int nnz_f; /* the number of non-zeros in matrix F (except diagonal elements, which are not stored) */ int nnz_v; /* the number of non-zeros in matrix V (except its pivot elements, which are stored in a separate array) */ double max_a; /* the largest magnitude of elements of matrix A */ double big_v; /* the largest magnitude of elements of matrix V appeared in the active submatrix during all the factorization process */ int rank; /* estimated rank of matrix A */ }; /* return codes: */ #define LUF_ESING 1 /* singular matrix */ #define LUF_ECOND 2 /* ill-conditioned matrix */ #define luf_create_it _glp_luf_create_it LUF *luf_create_it(void); /* create LU-factorization */ #define luf_defrag_sva _glp_luf_defrag_sva void luf_defrag_sva(LUF *luf); /* defragment the sparse vector area */ #define luf_enlarge_row _glp_luf_enlarge_row int luf_enlarge_row(LUF *luf, int i, int cap); /* enlarge row capacity */ #define luf_enlarge_col _glp_luf_enlarge_col int luf_enlarge_col(LUF *luf, int j, int cap); /* enlarge column capacity */ #define luf_factorize _glp_luf_factorize int luf_factorize(LUF *luf, int n, int (*col)(void *info, int j, int ind[], double val[]), void *info); /* compute LU-factorization */ #define luf_f_solve _glp_luf_f_solve void luf_f_solve(LUF *luf, int tr, double x[]); /* solve system F*x = b or F'*x = b */ #define luf_v_solve _glp_luf_v_solve void luf_v_solve(LUF *luf, int tr, double x[]); /* solve system V*x = b or V'*x = b */ #define luf_a_solve _glp_luf_a_solve void luf_a_solve(LUF *luf, int tr, double x[]); /* solve system A*x = b or A'*x = b */ #define luf_delete_it _glp_luf_delete_it void luf_delete_it(LUF *luf); /* delete LU-factorization */ #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpenv04.c0000644000076500000240000000725713524616144025215 0ustar tamasstaff00000000000000/* glpenv04.c (error handling) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glpapi.h" #include "igraph_error.h" /*********************************************************************** * NAME * * glp_error - display error message and terminate execution * * SYNOPSIS * * void glp_error(const char *fmt, ...); * * DESCRIPTION * * The routine glp_error (implemented as a macro) formats its * parameters using the format control string fmt, writes the formatted * message to the terminal, and abnormally terminates the program. */ static void error(const char *fmt, ...) { ENV *env = get_env_ptr(); va_list arg; env->term_out = GLP_ON; va_start(arg, fmt); igraph_errorvf(fmt, env->err_file, env->err_line, IGRAPH_EGLP, arg); /* no return */ } _glp_error glp_error_(const char *file, int line) { ENV *env = get_env_ptr(); env->err_file = file; env->err_line = line; return error; } /*********************************************************************** * NAME * * glp_assert - check for logical condition * * SYNOPSIS * * #include "glplib.h" * void glp_assert(int expr); * * DESCRIPTION * * The routine glp_assert (implemented as a macro) checks for a logical * condition specified by the parameter expr. If the condition is false * (i.e. the value of expr is zero), the routine writes a message to * the terminal and abnormally terminates the program. */ void glp_assert_(const char *expr, const char *file, int line) { glp_error_(file, line)("Assertion failed: %s\n", expr); /* no return */ } /*********************************************************************** * NAME * * glp_error_hook - install hook to intercept abnormal termination * * SYNOPSIS * * void glp_error_hook(void (*func)(void *info), void *info); * * DESCRIPTION * * The routine glp_error_hook installs a user-defined hook routine to * intercept abnormal termination. * * The parameter func specifies the user-defined hook routine. It is * called from the routine glp_error before the latter calls the abort * function to abnormally terminate the application program because of * fatal error. The parameter info is a transit pointer, specified in * the corresponding call to the routine glp_error_hook; it may be used * to pass some information to the hook routine. * * To uninstall the hook routine the parameters func and info should be * specified as NULL. */ void glp_error_hook(void (*func)(void *info), void *info) { ENV *env = get_env_ptr(); if (func == NULL) { env->err_hook = NULL; env->err_info = NULL; } else { env->err_hook = func; env->err_info = info; } return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpavl.h0000644000076500000240000001035613524616144025042 0ustar tamasstaff00000000000000/* glpavl.h (binary search tree) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPAVL_H #define GLPAVL_H #include "glpdmp.h" typedef struct AVL AVL; typedef struct AVLNODE AVLNODE; struct AVL { /* AVL tree (Adelson-Velsky & Landis binary search tree) */ DMP *pool; /* memory pool for allocating nodes */ AVLNODE *root; /* pointer to the root node */ int (*fcmp)(void *info, const void *key1, const void *key2); /* application-defined key comparison routine */ void *info; /* transit pointer passed to the routine fcmp */ int size; /* the tree size (the total number of nodes) */ int height; /* the tree height */ }; struct AVLNODE { /* node of AVL tree */ const void *key; /* pointer to the node key (data structure for representing keys is supplied by the application) */ int rank; /* node rank = relative position of the node in its own subtree = the number of nodes in the left subtree plus one */ int type; /* reserved for the application specific information */ void *link; /* reserved for the application specific information */ AVLNODE *up; /* pointer to the parent node */ short int flag; /* node flag: 0 - this node is the left child of its parent (or this node is the root of the tree and has no parent) 1 - this node is the right child of its parent */ short int bal; /* node balance = the difference between heights of the right and left subtrees: -1 - the left subtree is higher than the right one; 0 - the left and right subtrees have the same height; +1 - the left subtree is lower than the right one */ AVLNODE *left; /* pointer to the root of the left subtree */ AVLNODE *right; /* pointer to the root of the right subtree */ }; #define avl_create_tree _glp_avl_create_tree AVL *avl_create_tree(int (*fcmp)(void *info, const void *key1, const void *key2), void *info); /* create AVL tree */ #define avl_strcmp _glp_avl_strcmp int avl_strcmp(void *info, const void *key1, const void *key2); /* compare character string keys */ #define avl_insert_node _glp_avl_insert_node AVLNODE *avl_insert_node(AVL *tree, const void *key); /* insert new node into AVL tree */ #define avl_set_node_type _glp_avl_set_node_type void avl_set_node_type(AVLNODE *node, int type); /* assign the type field of specified node */ #define avl_set_node_link _glp_avl_set_node_link void avl_set_node_link(AVLNODE *node, void *link); /* assign the link field of specified node */ #define avl_find_node _glp_avl_find_node AVLNODE *avl_find_node(AVL *tree, const void *key); /* find node in AVL tree */ #define avl_get_node_type _glp_avl_get_node_type int avl_get_node_type(AVLNODE *node); /* retrieve the type field of specified node */ #define avl_get_node_link _glp_avl_get_node_link void *avl_get_node_link(AVLNODE *node); /* retrieve the link field of specified node */ #define avl_delete_node _glp_avl_delete_node void avl_delete_node(AVL *tree, AVLNODE *node); /* delete specified node from AVL tree */ #define avl_delete_tree _glp_avl_delete_tree void avl_delete_tree(AVL *tree); /* delete AVL tree */ #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpmpl03.c0000644000076500000240000064572213524616144025221 0ustar tamasstaff00000000000000/* glpmpl03.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wlogical-op-parentheses" #pragma clang diagnostic ignored "-Wshorten-64-to-32" #pragma clang diagnostic ignored "-Wsometimes-uninitialized" #endif #define _GLPSTD_ERRNO #define _GLPSTD_STDIO #include "glpenv.h" #include "glpmpl.h" /**********************************************************************/ /* * * FLOATING-POINT NUMBERS * * */ /**********************************************************************/ /*---------------------------------------------------------------------- -- fp_add - floating-point addition. -- -- This routine computes the sum x + y. */ double fp_add(MPL *mpl, double x, double y) { if (x > 0.0 && y > 0.0 && x > + 0.999 * DBL_MAX - y || x < 0.0 && y < 0.0 && x < - 0.999 * DBL_MAX - y) error(mpl, "%.*g + %.*g; floating-point overflow", DBL_DIG, x, DBL_DIG, y); return x + y; } /*---------------------------------------------------------------------- -- fp_sub - floating-point subtraction. -- -- This routine computes the difference x - y. */ double fp_sub(MPL *mpl, double x, double y) { if (x > 0.0 && y < 0.0 && x > + 0.999 * DBL_MAX + y || x < 0.0 && y > 0.0 && x < - 0.999 * DBL_MAX + y) error(mpl, "%.*g - %.*g; floating-point overflow", DBL_DIG, x, DBL_DIG, y); return x - y; } /*---------------------------------------------------------------------- -- fp_less - floating-point non-negative subtraction. -- -- This routine computes the non-negative difference max(0, x - y). */ double fp_less(MPL *mpl, double x, double y) { if (x < y) return 0.0; if (x > 0.0 && y < 0.0 && x > + 0.999 * DBL_MAX + y) error(mpl, "%.*g less %.*g; floating-point overflow", DBL_DIG, x, DBL_DIG, y); return x - y; } /*---------------------------------------------------------------------- -- fp_mul - floating-point multiplication. -- -- This routine computes the product x * y. */ double fp_mul(MPL *mpl, double x, double y) { if (fabs(y) > 1.0 && fabs(x) > (0.999 * DBL_MAX) / fabs(y)) error(mpl, "%.*g * %.*g; floating-point overflow", DBL_DIG, x, DBL_DIG, y); return x * y; } /*---------------------------------------------------------------------- -- fp_div - floating-point division. -- -- This routine computes the quotient x / y. */ double fp_div(MPL *mpl, double x, double y) { if (fabs(y) < DBL_MIN) error(mpl, "%.*g / %.*g; floating-point zero divide", DBL_DIG, x, DBL_DIG, y); if (fabs(y) < 1.0 && fabs(x) > (0.999 * DBL_MAX) * fabs(y)) error(mpl, "%.*g / %.*g; floating-point overflow", DBL_DIG, x, DBL_DIG, y); return x / y; } /*---------------------------------------------------------------------- -- fp_idiv - floating-point quotient of exact division. -- -- This routine computes the quotient of exact division x div y. */ double fp_idiv(MPL *mpl, double x, double y) { if (fabs(y) < DBL_MIN) error(mpl, "%.*g div %.*g; floating-point zero divide", DBL_DIG, x, DBL_DIG, y); if (fabs(y) < 1.0 && fabs(x) > (0.999 * DBL_MAX) * fabs(y)) error(mpl, "%.*g div %.*g; floating-point overflow", DBL_DIG, x, DBL_DIG, y); x /= y; return x > 0.0 ? floor(x) : x < 0.0 ? ceil(x) : 0.0; } /*---------------------------------------------------------------------- -- fp_mod - floating-point remainder of exact division. -- -- This routine computes the remainder of exact division x mod y. -- -- NOTE: By definition x mod y = x - y * floor(x / y). */ double fp_mod(MPL *mpl, double x, double y) { double r; xassert(mpl == mpl); if (x == 0.0) r = 0.0; else if (y == 0.0) r = x; else { r = fmod(fabs(x), fabs(y)); if (r != 0.0) { if (x < 0.0) r = - r; if (x > 0.0 && y < 0.0 || x < 0.0 && y > 0.0) r += y; } } return r; } /*---------------------------------------------------------------------- -- fp_power - floating-point exponentiation (raise to power). -- -- This routine computes the exponentiation x ** y. */ double fp_power(MPL *mpl, double x, double y) { double r; if (x == 0.0 && y <= 0.0 || x < 0.0 && y != floor(y)) error(mpl, "%.*g ** %.*g; result undefined", DBL_DIG, x, DBL_DIG, y); if (x == 0.0) goto eval; if (fabs(x) > 1.0 && y > +1.0 && +log(fabs(x)) > (0.999 * log(DBL_MAX)) / y || fabs(x) < 1.0 && y < -1.0 && +log(fabs(x)) < (0.999 * log(DBL_MAX)) / y) error(mpl, "%.*g ** %.*g; floating-point overflow", DBL_DIG, x, DBL_DIG, y); if (fabs(x) > 1.0 && y < -1.0 && -log(fabs(x)) < (0.999 * log(DBL_MAX)) / y || fabs(x) < 1.0 && y > +1.0 && -log(fabs(x)) > (0.999 * log(DBL_MAX)) / y) r = 0.0; else eval: r = pow(x, y); return r; } /*---------------------------------------------------------------------- -- fp_exp - floating-point base-e exponential. -- -- This routine computes the base-e exponential e ** x. */ double fp_exp(MPL *mpl, double x) { if (x > 0.999 * log(DBL_MAX)) error(mpl, "exp(%.*g); floating-point overflow", DBL_DIG, x); return exp(x); } /*---------------------------------------------------------------------- -- fp_log - floating-point natural logarithm. -- -- This routine computes the natural logarithm log x. */ double fp_log(MPL *mpl, double x) { if (x <= 0.0) error(mpl, "log(%.*g); non-positive argument", DBL_DIG, x); return log(x); } /*---------------------------------------------------------------------- -- fp_log10 - floating-point common (decimal) logarithm. -- -- This routine computes the common (decimal) logarithm lg x. */ double fp_log10(MPL *mpl, double x) { if (x <= 0.0) error(mpl, "log10(%.*g); non-positive argument", DBL_DIG, x); return log10(x); } /*---------------------------------------------------------------------- -- fp_sqrt - floating-point square root. -- -- This routine computes the square root x ** 0.5. */ double fp_sqrt(MPL *mpl, double x) { if (x < 0.0) error(mpl, "sqrt(%.*g); negative argument", DBL_DIG, x); return sqrt(x); } /*---------------------------------------------------------------------- -- fp_sin - floating-point trigonometric sine. -- -- This routine computes the trigonometric sine sin(x). */ double fp_sin(MPL *mpl, double x) { if (!(-1e6 <= x && x <= +1e6)) error(mpl, "sin(%.*g); argument too large", DBL_DIG, x); return sin(x); } /*---------------------------------------------------------------------- -- fp_cos - floating-point trigonometric cosine. -- -- This routine computes the trigonometric cosine cos(x). */ double fp_cos(MPL *mpl, double x) { if (!(-1e6 <= x && x <= +1e6)) error(mpl, "cos(%.*g); argument too large", DBL_DIG, x); return cos(x); } /*---------------------------------------------------------------------- -- fp_atan - floating-point trigonometric arctangent. -- -- This routine computes the trigonometric arctangent atan(x). */ double fp_atan(MPL *mpl, double x) { xassert(mpl == mpl); return atan(x); } /*---------------------------------------------------------------------- -- fp_atan2 - floating-point trigonometric arctangent. -- -- This routine computes the trigonometric arctangent atan(y / x). */ double fp_atan2(MPL *mpl, double y, double x) { xassert(mpl == mpl); return atan2(y, x); } /*---------------------------------------------------------------------- -- fp_round - round floating-point value to n fractional digits. -- -- This routine rounds given floating-point value x to n fractional -- digits with the formula: -- -- round(x, n) = floor(x * 10^n + 0.5) / 10^n. -- -- The parameter n is assumed to be integer. */ double fp_round(MPL *mpl, double x, double n) { double ten_to_n; if (n != floor(n)) error(mpl, "round(%.*g, %.*g); non-integer second argument", DBL_DIG, x, DBL_DIG, n); if (n <= DBL_DIG + 2) { ten_to_n = pow(10.0, n); if (fabs(x) < (0.999 * DBL_MAX) / ten_to_n) { x = floor(x * ten_to_n + 0.5); if (x != 0.0) x /= ten_to_n; } } return x; } /*---------------------------------------------------------------------- -- fp_trunc - truncate floating-point value to n fractional digits. -- -- This routine truncates given floating-point value x to n fractional -- digits with the formula: -- -- ( floor(x * 10^n) / 10^n, if x >= 0 -- trunc(x, n) = < -- ( ceil(x * 10^n) / 10^n, if x < 0 -- -- The parameter n is assumed to be integer. */ double fp_trunc(MPL *mpl, double x, double n) { double ten_to_n; if (n != floor(n)) error(mpl, "trunc(%.*g, %.*g); non-integer second argument", DBL_DIG, x, DBL_DIG, n); if (n <= DBL_DIG + 2) { ten_to_n = pow(10.0, n); if (fabs(x) < (0.999 * DBL_MAX) / ten_to_n) { x = (x >= 0.0 ? floor(x * ten_to_n) : ceil(x * ten_to_n)); if (x != 0.0) x /= ten_to_n; } } return x; } /**********************************************************************/ /* * * PSEUDO-RANDOM NUMBER GENERATORS * * */ /**********************************************************************/ /*---------------------------------------------------------------------- -- fp_irand224 - pseudo-random integer in the range [0, 2^24). -- -- This routine returns a next pseudo-random integer (converted to -- floating-point) which is uniformly distributed between 0 and 2^24-1, -- inclusive. */ #define two_to_the_24 0x1000000 double fp_irand224(MPL *mpl) { return (double)rng_unif_rand(mpl->rand, two_to_the_24); } /*---------------------------------------------------------------------- -- fp_uniform01 - pseudo-random number in the range [0, 1). -- -- This routine returns a next pseudo-random number which is uniformly -- distributed in the range [0, 1). */ #define two_to_the_31 ((unsigned int)0x80000000) double fp_uniform01(MPL *mpl) { return (double)rng_next_rand(mpl->rand) / (double)two_to_the_31; } /*---------------------------------------------------------------------- -- fp_uniform - pseudo-random number in the range [a, b). -- -- This routine returns a next pseudo-random number which is uniformly -- distributed in the range [a, b). */ double fp_uniform(MPL *mpl, double a, double b) { double x; if (a >= b) error(mpl, "Uniform(%.*g, %.*g); invalid range", DBL_DIG, a, DBL_DIG, b); x = fp_uniform01(mpl); #if 0 x = a * (1.0 - x) + b * x; #else x = fp_add(mpl, a * (1.0 - x), b * x); #endif return x; } /*---------------------------------------------------------------------- -- fp_normal01 - Gaussian random variate with mu = 0 and sigma = 1. -- -- This routine returns a Gaussian random variate with zero mean and -- unit standard deviation. The polar (Box-Mueller) method is used. -- -- This code is a modified version of the routine gsl_ran_gaussian from -- the GNU Scientific Library Version 1.0. */ double fp_normal01(MPL *mpl) { double x, y, r2; do { /* choose x, y in uniform square (-1,-1) to (+1,+1) */ x = -1.0 + 2.0 * fp_uniform01(mpl); y = -1.0 + 2.0 * fp_uniform01(mpl); /* see if it is in the unit circle */ r2 = x * x + y * y; } while (r2 > 1.0 || r2 == 0.0); /* Box-Muller transform */ return y * sqrt(-2.0 * log (r2) / r2); } /*---------------------------------------------------------------------- -- fp_normal - Gaussian random variate with specified mu and sigma. -- -- This routine returns a Gaussian random variate with mean mu and -- standard deviation sigma. */ double fp_normal(MPL *mpl, double mu, double sigma) { double x; #if 0 x = mu + sigma * fp_normal01(mpl); #else x = fp_add(mpl, mu, fp_mul(mpl, sigma, fp_normal01(mpl))); #endif return x; } /**********************************************************************/ /* * * SEGMENTED CHARACTER STRINGS * * */ /**********************************************************************/ /*---------------------------------------------------------------------- -- create_string - create character string. -- -- This routine creates a segmented character string, which is exactly -- equivalent to specified character string. */ STRING *create_string ( MPL *mpl, char buf[MAX_LENGTH+1] /* not changed */ ) #if 0 { STRING *head, *tail; int i, j; xassert(buf != NULL); xassert(strlen(buf) <= MAX_LENGTH); head = tail = dmp_get_atom(mpl->strings, sizeof(STRING)); for (i = j = 0; ; i++) { if ((tail->seg[j++] = buf[i]) == '\0') break; if (j == STRSEG_SIZE) tail = (tail->next = dmp_get_atom(mpl->strings, sizeof(STRING))), j = 0; } tail->next = NULL; return head; } #else { STRING *str; xassert(strlen(buf) <= MAX_LENGTH); str = dmp_get_atom(mpl->strings, strlen(buf)+1); strcpy(str, buf); return str; } #endif /*---------------------------------------------------------------------- -- copy_string - make copy of character string. -- -- This routine returns an exact copy of segmented character string. */ STRING *copy_string ( MPL *mpl, STRING *str /* not changed */ ) #if 0 { STRING *head, *tail; xassert(str != NULL); head = tail = dmp_get_atom(mpl->strings, sizeof(STRING)); for (; str != NULL; str = str->next) { memcpy(tail->seg, str->seg, STRSEG_SIZE); if (str->next != NULL) tail = (tail->next = dmp_get_atom(mpl->strings, sizeof(STRING))); } tail->next = NULL; return head; } #else { xassert(mpl == mpl); return create_string(mpl, str); } #endif /*---------------------------------------------------------------------- -- compare_strings - compare one character string with another. -- -- This routine compares one segmented character strings with another -- and returns the result of comparison as follows: -- -- = 0 - both strings are identical; -- < 0 - the first string precedes the second one; -- > 0 - the first string follows the second one. */ int compare_strings ( MPL *mpl, STRING *str1, /* not changed */ STRING *str2 /* not changed */ ) #if 0 { int j, c1, c2; xassert(mpl == mpl); for (;; str1 = str1->next, str2 = str2->next) { xassert(str1 != NULL); xassert(str2 != NULL); for (j = 0; j < STRSEG_SIZE; j++) { c1 = (unsigned char)str1->seg[j]; c2 = (unsigned char)str2->seg[j]; if (c1 < c2) return -1; if (c1 > c2) return +1; if (c1 == '\0') goto done; } } done: return 0; } #else { xassert(mpl == mpl); return strcmp(str1, str2); } #endif /*---------------------------------------------------------------------- -- fetch_string - extract content of character string. -- -- This routine returns a character string, which is exactly equivalent -- to specified segmented character string. */ char *fetch_string ( MPL *mpl, STRING *str, /* not changed */ char buf[MAX_LENGTH+1] /* modified */ ) #if 0 { int i, j; xassert(mpl == mpl); xassert(buf != NULL); for (i = 0; ; str = str->next) { xassert(str != NULL); for (j = 0; j < STRSEG_SIZE; j++) if ((buf[i++] = str->seg[j]) == '\0') goto done; } done: xassert(strlen(buf) <= MAX_LENGTH); return buf; } #else { xassert(mpl == mpl); return strcpy(buf, str); } #endif /*---------------------------------------------------------------------- -- delete_string - delete character string. -- -- This routine deletes specified segmented character string. */ void delete_string ( MPL *mpl, STRING *str /* destroyed */ ) #if 0 { STRING *temp; xassert(str != NULL); while (str != NULL) { temp = str; str = str->next; dmp_free_atom(mpl->strings, temp, sizeof(STRING)); } return; } #else { dmp_free_atom(mpl->strings, str, strlen(str)+1); return; } #endif /**********************************************************************/ /* * * SYMBOLS * * */ /**********************************************************************/ /*---------------------------------------------------------------------- -- create_symbol_num - create symbol of numeric type. -- -- This routine creates a symbol, which has a numeric value specified -- as floating-point number. */ SYMBOL *create_symbol_num(MPL *mpl, double num) { SYMBOL *sym; sym = dmp_get_atom(mpl->symbols, sizeof(SYMBOL)); sym->num = num; sym->str = NULL; return sym; } /*---------------------------------------------------------------------- -- create_symbol_str - create symbol of abstract type. -- -- This routine creates a symbol, which has an abstract value specified -- as segmented character string. */ SYMBOL *create_symbol_str ( MPL *mpl, STRING *str /* destroyed */ ) { SYMBOL *sym; xassert(str != NULL); sym = dmp_get_atom(mpl->symbols, sizeof(SYMBOL)); sym->num = 0.0; sym->str = str; return sym; } /*---------------------------------------------------------------------- -- copy_symbol - make copy of symbol. -- -- This routine returns an exact copy of symbol. */ SYMBOL *copy_symbol ( MPL *mpl, SYMBOL *sym /* not changed */ ) { SYMBOL *copy; xassert(sym != NULL); copy = dmp_get_atom(mpl->symbols, sizeof(SYMBOL)); if (sym->str == NULL) { copy->num = sym->num; copy->str = NULL; } else { copy->num = 0.0; copy->str = copy_string(mpl, sym->str); } return copy; } /*---------------------------------------------------------------------- -- compare_symbols - compare one symbol with another. -- -- This routine compares one symbol with another and returns the result -- of comparison as follows: -- -- = 0 - both symbols are identical; -- < 0 - the first symbol precedes the second one; -- > 0 - the first symbol follows the second one. -- -- Note that the linear order, in which symbols follow each other, is -- implementation-dependent. It may be not an alphabetical order. */ int compare_symbols ( MPL *mpl, SYMBOL *sym1, /* not changed */ SYMBOL *sym2 /* not changed */ ) { xassert(sym1 != NULL); xassert(sym2 != NULL); /* let all numeric quantities precede all symbolic quantities */ if (sym1->str == NULL && sym2->str == NULL) { if (sym1->num < sym2->num) return -1; if (sym1->num > sym2->num) return +1; return 0; } if (sym1->str == NULL) return -1; if (sym2->str == NULL) return +1; return compare_strings(mpl, sym1->str, sym2->str); } /*---------------------------------------------------------------------- -- delete_symbol - delete symbol. -- -- This routine deletes specified symbol. */ void delete_symbol ( MPL *mpl, SYMBOL *sym /* destroyed */ ) { xassert(sym != NULL); if (sym->str != NULL) delete_string(mpl, sym->str); dmp_free_atom(mpl->symbols, sym, sizeof(SYMBOL)); return; } /*---------------------------------------------------------------------- -- format_symbol - format symbol for displaying or printing. -- -- This routine converts specified symbol to a charater string, which -- is suitable for displaying or printing. -- -- The resultant string is never longer than 255 characters. If it gets -- longer, it is truncated from the right and appended by dots. */ char *format_symbol ( MPL *mpl, SYMBOL *sym /* not changed */ ) { char *buf = mpl->sym_buf; xassert(sym != NULL); if (sym->str == NULL) sprintf(buf, "%.*g", DBL_DIG, sym->num); else { char str[MAX_LENGTH+1]; int quoted, j, len; fetch_string(mpl, sym->str, str); if (!(isalpha((unsigned char)str[0]) || str[0] == '_')) quoted = 1; else { quoted = 0; for (j = 1; str[j] != '\0'; j++) { if (!(isalnum((unsigned char)str[j]) || strchr("+-._", (unsigned char)str[j]) != NULL)) { quoted = 1; break; } } } # define safe_append(c) \ (void)(len < 255 ? (buf[len++] = (char)(c)) : 0) buf[0] = '\0', len = 0; if (quoted) safe_append('\''); for (j = 0; str[j] != '\0'; j++) { if (quoted && str[j] == '\'') safe_append('\''); safe_append(str[j]); } if (quoted) safe_append('\''); # undef safe_append buf[len] = '\0'; if (len == 255) strcpy(buf+252, "..."); } xassert(strlen(buf) <= 255); return buf; } /*---------------------------------------------------------------------- -- concat_symbols - concatenate one symbol with another. -- -- This routine concatenates values of two given symbols and assigns -- the resultant character string to a new symbol, which is returned on -- exit. Both original symbols are destroyed. */ SYMBOL *concat_symbols ( MPL *mpl, SYMBOL *sym1, /* destroyed */ SYMBOL *sym2 /* destroyed */ ) { char str1[MAX_LENGTH+1], str2[MAX_LENGTH+1]; xassert(MAX_LENGTH >= DBL_DIG + DBL_DIG); if (sym1->str == NULL) sprintf(str1, "%.*g", DBL_DIG, sym1->num); else fetch_string(mpl, sym1->str, str1); if (sym2->str == NULL) sprintf(str2, "%.*g", DBL_DIG, sym2->num); else fetch_string(mpl, sym2->str, str2); if (strlen(str1) + strlen(str2) > MAX_LENGTH) { char buf[255+1]; strcpy(buf, format_symbol(mpl, sym1)); xassert(strlen(buf) < sizeof(buf)); error(mpl, "%s & %s; resultant symbol exceeds %d characters", buf, format_symbol(mpl, sym2), MAX_LENGTH); } delete_symbol(mpl, sym1); delete_symbol(mpl, sym2); return create_symbol_str(mpl, create_string(mpl, strcat(str1, str2))); } /**********************************************************************/ /* * * N-TUPLES * * */ /**********************************************************************/ /*---------------------------------------------------------------------- -- create_tuple - create n-tuple. -- -- This routine creates a n-tuple, which initially has no components, -- i.e. which is 0-tuple. */ TUPLE *create_tuple(MPL *mpl) { TUPLE *tuple; xassert(mpl == mpl); tuple = NULL; return tuple; } /*---------------------------------------------------------------------- -- expand_tuple - append symbol to n-tuple. -- -- This routine expands n-tuple appending to it a given symbol, which -- becomes its new last component. */ TUPLE *expand_tuple ( MPL *mpl, TUPLE *tuple, /* destroyed */ SYMBOL *sym /* destroyed */ ) { TUPLE *tail, *temp; xassert(sym != NULL); /* create a new component */ tail = dmp_get_atom(mpl->tuples, sizeof(TUPLE)); tail->sym = sym; tail->next = NULL; /* and append it to the component list */ if (tuple == NULL) tuple = tail; else { for (temp = tuple; temp->next != NULL; temp = temp->next); temp->next = tail; } return tuple; } /*---------------------------------------------------------------------- -- tuple_dimen - determine dimension of n-tuple. -- -- This routine returns dimension of n-tuple, i.e. number of components -- in the n-tuple. */ int tuple_dimen ( MPL *mpl, TUPLE *tuple /* not changed */ ) { TUPLE *temp; int dim = 0; xassert(mpl == mpl); for (temp = tuple; temp != NULL; temp = temp->next) dim++; return dim; } /*---------------------------------------------------------------------- -- copy_tuple - make copy of n-tuple. -- -- This routine returns an exact copy of n-tuple. */ TUPLE *copy_tuple ( MPL *mpl, TUPLE *tuple /* not changed */ ) { TUPLE *head, *tail; if (tuple == NULL) head = NULL; else { head = tail = dmp_get_atom(mpl->tuples, sizeof(TUPLE)); for (; tuple != NULL; tuple = tuple->next) { xassert(tuple->sym != NULL); tail->sym = copy_symbol(mpl, tuple->sym); if (tuple->next != NULL) tail = (tail->next = dmp_get_atom(mpl->tuples, sizeof(TUPLE))); } tail->next = NULL; } return head; } /*---------------------------------------------------------------------- -- compare_tuples - compare one n-tuple with another. -- -- This routine compares two given n-tuples, which must have the same -- dimension (not checked for the sake of efficiency), and returns one -- of the following codes: -- -- = 0 - both n-tuples are identical; -- < 0 - the first n-tuple precedes the second one; -- > 0 - the first n-tuple follows the second one. -- -- Note that the linear order, in which n-tuples follow each other, is -- implementation-dependent. It may be not an alphabetical order. */ int compare_tuples ( MPL *mpl, TUPLE *tuple1, /* not changed */ TUPLE *tuple2 /* not changed */ ) { TUPLE *item1, *item2; int ret; xassert(mpl == mpl); for (item1 = tuple1, item2 = tuple2; item1 != NULL; item1 = item1->next, item2 = item2->next) { xassert(item2 != NULL); xassert(item1->sym != NULL); xassert(item2->sym != NULL); ret = compare_symbols(mpl, item1->sym, item2->sym); if (ret != 0) return ret; } xassert(item2 == NULL); return 0; } /*---------------------------------------------------------------------- -- build_subtuple - build subtuple of given n-tuple. -- -- This routine builds subtuple, which consists of first dim components -- of given n-tuple. */ TUPLE *build_subtuple ( MPL *mpl, TUPLE *tuple, /* not changed */ int dim ) { TUPLE *head, *temp; int j; head = create_tuple(mpl); for (j = 1, temp = tuple; j <= dim; j++, temp = temp->next) { xassert(temp != NULL); head = expand_tuple(mpl, head, copy_symbol(mpl, temp->sym)); } return head; } /*---------------------------------------------------------------------- -- delete_tuple - delete n-tuple. -- -- This routine deletes specified n-tuple. */ void delete_tuple ( MPL *mpl, TUPLE *tuple /* destroyed */ ) { TUPLE *temp; while (tuple != NULL) { temp = tuple; tuple = temp->next; xassert(temp->sym != NULL); delete_symbol(mpl, temp->sym); dmp_free_atom(mpl->tuples, temp, sizeof(TUPLE)); } return; } /*---------------------------------------------------------------------- -- format_tuple - format n-tuple for displaying or printing. -- -- This routine converts specified n-tuple to a character string, which -- is suitable for displaying or printing. -- -- The resultant string is never longer than 255 characters. If it gets -- longer, it is truncated from the right and appended by dots. */ char *format_tuple ( MPL *mpl, int c, TUPLE *tuple /* not changed */ ) { TUPLE *temp; int dim, j, len; char *buf = mpl->tup_buf, str[255+1], *save; # define safe_append(c) \ (void)(len < 255 ? (buf[len++] = (char)(c)) : 0) buf[0] = '\0', len = 0; dim = tuple_dimen(mpl, tuple); if (c == '[' && dim > 0) safe_append('['); if (c == '(' && dim > 1) safe_append('('); for (temp = tuple; temp != NULL; temp = temp->next) { if (temp != tuple) safe_append(','); xassert(temp->sym != NULL); save = mpl->sym_buf; mpl->sym_buf = str; format_symbol(mpl, temp->sym); mpl->sym_buf = save; xassert(strlen(str) < sizeof(str)); for (j = 0; str[j] != '\0'; j++) safe_append(str[j]); } if (c == '[' && dim > 0) safe_append(']'); if (c == '(' && dim > 1) safe_append(')'); # undef safe_append buf[len] = '\0'; if (len == 255) strcpy(buf+252, "..."); xassert(strlen(buf) <= 255); return buf; } /**********************************************************************/ /* * * ELEMENTAL SETS * * */ /**********************************************************************/ /*---------------------------------------------------------------------- -- create_elemset - create elemental set. -- -- This routine creates an elemental set, whose members are n-tuples of -- specified dimension. Being created the set is initially empty. */ ELEMSET *create_elemset(MPL *mpl, int dim) { ELEMSET *set; xassert(dim > 0); set = create_array(mpl, A_NONE, dim); return set; } /*---------------------------------------------------------------------- -- find_tuple - check if elemental set contains given n-tuple. -- -- This routine finds given n-tuple in specified elemental set in order -- to check if the set contains that n-tuple. If the n-tuple is found, -- the routine returns pointer to corresponding array member. Otherwise -- null pointer is returned. */ MEMBER *find_tuple ( MPL *mpl, ELEMSET *set, /* not changed */ TUPLE *tuple /* not changed */ ) { xassert(set != NULL); xassert(set->type == A_NONE); xassert(set->dim == tuple_dimen(mpl, tuple)); return find_member(mpl, set, tuple); } /*---------------------------------------------------------------------- -- add_tuple - add new n-tuple to elemental set. -- -- This routine adds given n-tuple to specified elemental set. -- -- For the sake of efficiency this routine doesn't check whether the -- set already contains the same n-tuple or not. Therefore the calling -- program should use the routine find_tuple (if necessary) in order to -- make sure that the given n-tuple is not contained in the set, since -- duplicate n-tuples within the same set are not allowed. */ MEMBER *add_tuple ( MPL *mpl, ELEMSET *set, /* modified */ TUPLE *tuple /* destroyed */ ) { MEMBER *memb; xassert(set != NULL); xassert(set->type == A_NONE); xassert(set->dim == tuple_dimen(mpl, tuple)); memb = add_member(mpl, set, tuple); memb->value.none = NULL; return memb; } /*---------------------------------------------------------------------- -- check_then_add - check and add new n-tuple to elemental set. -- -- This routine is equivalent to the routine add_tuple except that it -- does check for duplicate n-tuples. */ MEMBER *check_then_add ( MPL *mpl, ELEMSET *set, /* modified */ TUPLE *tuple /* destroyed */ ) { if (find_tuple(mpl, set, tuple) != NULL) error(mpl, "duplicate tuple %s detected", format_tuple(mpl, '(', tuple)); return add_tuple(mpl, set, tuple); } /*---------------------------------------------------------------------- -- copy_elemset - make copy of elemental set. -- -- This routine makes an exact copy of elemental set. */ ELEMSET *copy_elemset ( MPL *mpl, ELEMSET *set /* not changed */ ) { ELEMSET *copy; MEMBER *memb; xassert(set != NULL); xassert(set->type == A_NONE); xassert(set->dim > 0); copy = create_elemset(mpl, set->dim); for (memb = set->head; memb != NULL; memb = memb->next) add_tuple(mpl, copy, copy_tuple(mpl, memb->tuple)); return copy; } /*---------------------------------------------------------------------- -- delete_elemset - delete elemental set. -- -- This routine deletes specified elemental set. */ void delete_elemset ( MPL *mpl, ELEMSET *set /* destroyed */ ) { xassert(set != NULL); xassert(set->type == A_NONE); delete_array(mpl, set); return; } /*---------------------------------------------------------------------- -- arelset_size - compute size of "arithmetic" elemental set. -- -- This routine computes the size of "arithmetic" elemental set, which -- is specified in the form of arithmetic progression: -- -- { t0 .. tf by dt }. -- -- The size is computed using the formula: -- -- n = max(0, floor((tf - t0) / dt) + 1). */ int arelset_size(MPL *mpl, double t0, double tf, double dt) { double temp; if (dt == 0.0) error(mpl, "%.*g .. %.*g by %.*g; zero stride not allowed", DBL_DIG, t0, DBL_DIG, tf, DBL_DIG, dt); if (tf > 0.0 && t0 < 0.0 && tf > + 0.999 * DBL_MAX + t0) temp = +DBL_MAX; else if (tf < 0.0 && t0 > 0.0 && tf < - 0.999 * DBL_MAX + t0) temp = -DBL_MAX; else temp = tf - t0; if (fabs(dt) < 1.0 && fabs(temp) > (0.999 * DBL_MAX) * fabs(dt)) { if (temp > 0.0 && dt > 0.0 || temp < 0.0 && dt < 0.0) temp = +DBL_MAX; else temp = 0.0; } else { temp = floor(temp / dt) + 1.0; if (temp < 0.0) temp = 0.0; } xassert(temp >= 0.0); if (temp > (double)(INT_MAX - 1)) error(mpl, "%.*g .. %.*g by %.*g; set too large", DBL_DIG, t0, DBL_DIG, tf, DBL_DIG, dt); return (int)(temp + 0.5); } /*---------------------------------------------------------------------- -- arelset_member - compute member of "arithmetic" elemental set. -- -- This routine returns a numeric value of symbol, which is equivalent -- to j-th member of given "arithmetic" elemental set specified in the -- form of arithmetic progression: -- -- { t0 .. tf by dt }. -- -- The symbol value is computed with the formula: -- -- j-th member = t0 + (j - 1) * dt, -- -- The number j must satisfy to the restriction 1 <= j <= n, where n is -- the set size computed by the routine arelset_size. */ double arelset_member(MPL *mpl, double t0, double tf, double dt, int j) { xassert(1 <= j && j <= arelset_size(mpl, t0, tf, dt)); return t0 + (double)(j - 1) * dt; } /*---------------------------------------------------------------------- -- create_arelset - create "arithmetic" elemental set. -- -- This routine creates "arithmetic" elemental set, which is specified -- in the form of arithmetic progression: -- -- { t0 .. tf by dt }. -- -- Components of this set are 1-tuples. */ ELEMSET *create_arelset(MPL *mpl, double t0, double tf, double dt) { ELEMSET *set; int j, n; set = create_elemset(mpl, 1); n = arelset_size(mpl, t0, tf, dt); for (j = 1; j <= n; j++) { add_tuple ( mpl, set, expand_tuple ( mpl, create_tuple(mpl), create_symbol_num ( mpl, arelset_member(mpl, t0, tf, dt, j) ) ) ); } return set; } /*---------------------------------------------------------------------- -- set_union - union of two elemental sets. -- -- This routine computes the union: -- -- X U Y = { j | (j in X) or (j in Y) }, -- -- where X and Y are given elemental sets (destroyed on exit). */ ELEMSET *set_union ( MPL *mpl, ELEMSET *X, /* destroyed */ ELEMSET *Y /* destroyed */ ) { MEMBER *memb; xassert(X != NULL); xassert(X->type == A_NONE); xassert(X->dim > 0); xassert(Y != NULL); xassert(Y->type == A_NONE); xassert(Y->dim > 0); xassert(X->dim == Y->dim); for (memb = Y->head; memb != NULL; memb = memb->next) { if (find_tuple(mpl, X, memb->tuple) == NULL) add_tuple(mpl, X, copy_tuple(mpl, memb->tuple)); } delete_elemset(mpl, Y); return X; } /*---------------------------------------------------------------------- -- set_diff - difference between two elemental sets. -- -- This routine computes the difference: -- -- X \ Y = { j | (j in X) and (j not in Y) }, -- -- where X and Y are given elemental sets (destroyed on exit). */ ELEMSET *set_diff ( MPL *mpl, ELEMSET *X, /* destroyed */ ELEMSET *Y /* destroyed */ ) { ELEMSET *Z; MEMBER *memb; xassert(X != NULL); xassert(X->type == A_NONE); xassert(X->dim > 0); xassert(Y != NULL); xassert(Y->type == A_NONE); xassert(Y->dim > 0); xassert(X->dim == Y->dim); Z = create_elemset(mpl, X->dim); for (memb = X->head; memb != NULL; memb = memb->next) { if (find_tuple(mpl, Y, memb->tuple) == NULL) add_tuple(mpl, Z, copy_tuple(mpl, memb->tuple)); } delete_elemset(mpl, X); delete_elemset(mpl, Y); return Z; } /*---------------------------------------------------------------------- -- set_symdiff - symmetric difference between two elemental sets. -- -- This routine computes the symmetric difference: -- -- X (+) Y = (X \ Y) U (Y \ X), -- -- where X and Y are given elemental sets (destroyed on exit). */ ELEMSET *set_symdiff ( MPL *mpl, ELEMSET *X, /* destroyed */ ELEMSET *Y /* destroyed */ ) { ELEMSET *Z; MEMBER *memb; xassert(X != NULL); xassert(X->type == A_NONE); xassert(X->dim > 0); xassert(Y != NULL); xassert(Y->type == A_NONE); xassert(Y->dim > 0); xassert(X->dim == Y->dim); /* Z := X \ Y */ Z = create_elemset(mpl, X->dim); for (memb = X->head; memb != NULL; memb = memb->next) { if (find_tuple(mpl, Y, memb->tuple) == NULL) add_tuple(mpl, Z, copy_tuple(mpl, memb->tuple)); } /* Z := Z U (Y \ X) */ for (memb = Y->head; memb != NULL; memb = memb->next) { if (find_tuple(mpl, X, memb->tuple) == NULL) add_tuple(mpl, Z, copy_tuple(mpl, memb->tuple)); } delete_elemset(mpl, X); delete_elemset(mpl, Y); return Z; } /*---------------------------------------------------------------------- -- set_inter - intersection of two elemental sets. -- -- This routine computes the intersection: -- -- X ^ Y = { j | (j in X) and (j in Y) }, -- -- where X and Y are given elemental sets (destroyed on exit). */ ELEMSET *set_inter ( MPL *mpl, ELEMSET *X, /* destroyed */ ELEMSET *Y /* destroyed */ ) { ELEMSET *Z; MEMBER *memb; xassert(X != NULL); xassert(X->type == A_NONE); xassert(X->dim > 0); xassert(Y != NULL); xassert(Y->type == A_NONE); xassert(Y->dim > 0); xassert(X->dim == Y->dim); Z = create_elemset(mpl, X->dim); for (memb = X->head; memb != NULL; memb = memb->next) { if (find_tuple(mpl, Y, memb->tuple) != NULL) add_tuple(mpl, Z, copy_tuple(mpl, memb->tuple)); } delete_elemset(mpl, X); delete_elemset(mpl, Y); return Z; } /*---------------------------------------------------------------------- -- set_cross - cross (Cartesian) product of two elemental sets. -- -- This routine computes the cross (Cartesian) product: -- -- X x Y = { (i,j) | (i in X) and (j in Y) }, -- -- where X and Y are given elemental sets (destroyed on exit). */ ELEMSET *set_cross ( MPL *mpl, ELEMSET *X, /* destroyed */ ELEMSET *Y /* destroyed */ ) { ELEMSET *Z; MEMBER *memx, *memy; TUPLE *tuple, *temp; xassert(X != NULL); xassert(X->type == A_NONE); xassert(X->dim > 0); xassert(Y != NULL); xassert(Y->type == A_NONE); xassert(Y->dim > 0); Z = create_elemset(mpl, X->dim + Y->dim); for (memx = X->head; memx != NULL; memx = memx->next) { for (memy = Y->head; memy != NULL; memy = memy->next) { tuple = copy_tuple(mpl, memx->tuple); for (temp = memy->tuple; temp != NULL; temp = temp->next) tuple = expand_tuple(mpl, tuple, copy_symbol(mpl, temp->sym)); add_tuple(mpl, Z, tuple); } } delete_elemset(mpl, X); delete_elemset(mpl, Y); return Z; } /**********************************************************************/ /* * * ELEMENTAL VARIABLES * * */ /**********************************************************************/ /* (there are no specific routines for elemental variables) */ /**********************************************************************/ /* * * LINEAR FORMS * * */ /**********************************************************************/ /*---------------------------------------------------------------------- -- constant_term - create constant term. -- -- This routine creates the linear form, which is a constant term. */ FORMULA *constant_term(MPL *mpl, double coef) { FORMULA *form; if (coef == 0.0) form = NULL; else { form = dmp_get_atom(mpl->formulae, sizeof(FORMULA)); form->coef = coef; form->var = NULL; form->next = NULL; } return form; } /*---------------------------------------------------------------------- -- single_variable - create single variable. -- -- This routine creates the linear form, which is a single elemental -- variable. */ FORMULA *single_variable ( MPL *mpl, ELEMVAR *var /* referenced */ ) { FORMULA *form; xassert(var != NULL); form = dmp_get_atom(mpl->formulae, sizeof(FORMULA)); form->coef = 1.0; form->var = var; form->next = NULL; return form; } /*---------------------------------------------------------------------- -- copy_formula - make copy of linear form. -- -- This routine returns an exact copy of linear form. */ FORMULA *copy_formula ( MPL *mpl, FORMULA *form /* not changed */ ) { FORMULA *head, *tail; if (form == NULL) head = NULL; else { head = tail = dmp_get_atom(mpl->formulae, sizeof(FORMULA)); for (; form != NULL; form = form->next) { tail->coef = form->coef; tail->var = form->var; if (form->next != NULL) tail = (tail->next = dmp_get_atom(mpl->formulae, sizeof(FORMULA))); } tail->next = NULL; } return head; } /*---------------------------------------------------------------------- -- delete_formula - delete linear form. -- -- This routine deletes specified linear form. */ void delete_formula ( MPL *mpl, FORMULA *form /* destroyed */ ) { FORMULA *temp; while (form != NULL) { temp = form; form = form->next; dmp_free_atom(mpl->formulae, temp, sizeof(FORMULA)); } return; } /*---------------------------------------------------------------------- -- linear_comb - linear combination of two linear forms. -- -- This routine computes the linear combination: -- -- a * fx + b * fy, -- -- where a and b are numeric coefficients, fx and fy are linear forms -- (destroyed on exit). */ FORMULA *linear_comb ( MPL *mpl, double a, FORMULA *fx, /* destroyed */ double b, FORMULA *fy /* destroyed */ ) { FORMULA *form = NULL, *term, *temp; double c0 = 0.0; for (term = fx; term != NULL; term = term->next) { if (term->var == NULL) c0 = fp_add(mpl, c0, fp_mul(mpl, a, term->coef)); else term->var->temp = fp_add(mpl, term->var->temp, fp_mul(mpl, a, term->coef)); } for (term = fy; term != NULL; term = term->next) { if (term->var == NULL) c0 = fp_add(mpl, c0, fp_mul(mpl, b, term->coef)); else term->var->temp = fp_add(mpl, term->var->temp, fp_mul(mpl, b, term->coef)); } for (term = fx; term != NULL; term = term->next) { if (term->var != NULL && term->var->temp != 0.0) { temp = dmp_get_atom(mpl->formulae, sizeof(FORMULA)); temp->coef = term->var->temp, temp->var = term->var; temp->next = form, form = temp; term->var->temp = 0.0; } } for (term = fy; term != NULL; term = term->next) { if (term->var != NULL && term->var->temp != 0.0) { temp = dmp_get_atom(mpl->formulae, sizeof(FORMULA)); temp->coef = term->var->temp, temp->var = term->var; temp->next = form, form = temp; term->var->temp = 0.0; } } if (c0 != 0.0) { temp = dmp_get_atom(mpl->formulae, sizeof(FORMULA)); temp->coef = c0, temp->var = NULL; temp->next = form, form = temp; } delete_formula(mpl, fx); delete_formula(mpl, fy); return form; } /*---------------------------------------------------------------------- -- remove_constant - remove constant term from linear form. -- -- This routine removes constant term from linear form and stores its -- value to given location. */ FORMULA *remove_constant ( MPL *mpl, FORMULA *form, /* destroyed */ double *coef /* modified */ ) { FORMULA *head = NULL, *temp; *coef = 0.0; while (form != NULL) { temp = form; form = form->next; if (temp->var == NULL) { /* constant term */ *coef = fp_add(mpl, *coef, temp->coef); dmp_free_atom(mpl->formulae, temp, sizeof(FORMULA)); } else { /* linear term */ temp->next = head; head = temp; } } return head; } /*---------------------------------------------------------------------- -- reduce_terms - reduce identical terms in linear form. -- -- This routine reduces identical terms in specified linear form. */ FORMULA *reduce_terms ( MPL *mpl, FORMULA *form /* destroyed */ ) { FORMULA *term, *next_term; double c0 = 0.0; for (term = form; term != NULL; term = term->next) { if (term->var == NULL) c0 = fp_add(mpl, c0, term->coef); else term->var->temp = fp_add(mpl, term->var->temp, term->coef); } next_term = form, form = NULL; for (term = next_term; term != NULL; term = next_term) { next_term = term->next; if (term->var == NULL && c0 != 0.0) { term->coef = c0, c0 = 0.0; term->next = form, form = term; } else if (term->var != NULL && term->var->temp != 0.0) { term->coef = term->var->temp, term->var->temp = 0.0; term->next = form, form = term; } else dmp_free_atom(mpl->formulae, term, sizeof(FORMULA)); } return form; } /**********************************************************************/ /* * * ELEMENTAL CONSTRAINTS * * */ /**********************************************************************/ /* (there are no specific routines for elemental constraints) */ /**********************************************************************/ /* * * GENERIC VALUES * * */ /**********************************************************************/ /*---------------------------------------------------------------------- -- delete_value - delete generic value. -- -- This routine deletes specified generic value. -- -- NOTE: The generic value to be deleted must be valid. */ void delete_value ( MPL *mpl, int type, VALUE *value /* content destroyed */ ) { xassert(value != NULL); switch (type) { case A_NONE: value->none = NULL; break; case A_NUMERIC: value->num = 0.0; break; case A_SYMBOLIC: delete_symbol(mpl, value->sym), value->sym = NULL; break; case A_LOGICAL: value->bit = 0; break; case A_TUPLE: delete_tuple(mpl, value->tuple), value->tuple = NULL; break; case A_ELEMSET: delete_elemset(mpl, value->set), value->set = NULL; break; case A_ELEMVAR: value->var = NULL; break; case A_FORMULA: delete_formula(mpl, value->form), value->form = NULL; break; case A_ELEMCON: value->con = NULL; break; default: xassert(type != type); } return; } /**********************************************************************/ /* * * SYMBOLICALLY INDEXED ARRAYS * * */ /**********************************************************************/ /*---------------------------------------------------------------------- -- create_array - create array. -- -- This routine creates an array of specified type and dimension. Being -- created the array is initially empty. -- -- The type indicator determines generic values, which can be assigned -- to the array members: -- -- A_NONE - none (members have no assigned values) -- A_NUMERIC - floating-point numbers -- A_SYMBOLIC - symbols -- A_ELEMSET - elemental sets -- A_ELEMVAR - elemental variables -- A_ELEMCON - elemental constraints -- -- The dimension may be 0, in which case the array consists of the only -- member (such arrays represent 0-dimensional objects). */ ARRAY *create_array(MPL *mpl, int type, int dim) { ARRAY *array; xassert(type == A_NONE || type == A_NUMERIC || type == A_SYMBOLIC || type == A_ELEMSET || type == A_ELEMVAR || type == A_ELEMCON); xassert(dim >= 0); array = dmp_get_atom(mpl->arrays, sizeof(ARRAY)); array->type = type; array->dim = dim; array->size = 0; array->head = NULL; array->tail = NULL; array->tree = NULL; array->prev = NULL; array->next = mpl->a_list; /* include the array in the global array list */ if (array->next != NULL) array->next->prev = array; mpl->a_list = array; return array; } /*---------------------------------------------------------------------- -- find_member - find array member with given n-tuple. -- -- This routine finds an array member, which has given n-tuple. If the -- array is short, the linear search is used. Otherwise the routine -- autimatically creates the search tree (i.e. the array index) to find -- members for logarithmic time. */ static int compare_member_tuples(void *info, const void *key1, const void *key2) { /* this is an auxiliary routine used to compare keys, which are n-tuples assigned to array members */ return compare_tuples((MPL *)info, (TUPLE *)key1, (TUPLE *)key2); } MEMBER *find_member ( MPL *mpl, ARRAY *array, /* not changed */ TUPLE *tuple /* not changed */ ) { MEMBER *memb; xassert(array != NULL); /* the n-tuple must have the same dimension as the array */ xassert(tuple_dimen(mpl, tuple) == array->dim); /* if the array is large enough, create the search tree and index all existing members of the array */ if (array->size > 30 && array->tree == NULL) { array->tree = avl_create_tree(compare_member_tuples, mpl); for (memb = array->head; memb != NULL; memb = memb->next) avl_set_node_link(avl_insert_node(array->tree, memb->tuple), (void *)memb); } /* find a member, which has the given tuple */ if (array->tree == NULL) { /* the search tree doesn't exist; use the linear search */ for (memb = array->head; memb != NULL; memb = memb->next) if (compare_tuples(mpl, memb->tuple, tuple) == 0) break; } else { /* the search tree exists; use the binary search */ AVLNODE *node; node = avl_find_node(array->tree, tuple); memb = (MEMBER *)(node == NULL ? NULL : avl_get_node_link(node)); } return memb; } /*---------------------------------------------------------------------- -- add_member - add new member to array. -- -- This routine creates a new member with given n-tuple and adds it to -- specified array. -- -- For the sake of efficiency this routine doesn't check whether the -- array already contains a member with the given n-tuple or not. Thus, -- if necessary, the calling program should use the routine find_member -- in order to be sure that the array contains no member with the same -- n-tuple, because members with duplicate n-tuples are not allowed. -- -- This routine assigns no generic value to the new member, because the -- calling program must do that. */ MEMBER *add_member ( MPL *mpl, ARRAY *array, /* modified */ TUPLE *tuple /* destroyed */ ) { MEMBER *memb; xassert(array != NULL); /* the n-tuple must have the same dimension as the array */ xassert(tuple_dimen(mpl, tuple) == array->dim); /* create new member */ memb = dmp_get_atom(mpl->members, sizeof(MEMBER)); memb->tuple = tuple; memb->next = NULL; memset(&memb->value, '?', sizeof(VALUE)); /* and append it to the member list */ array->size++; if (array->head == NULL) array->head = memb; else array->tail->next = memb; array->tail = memb; /* if the search tree exists, index the new member */ if (array->tree != NULL) avl_set_node_link(avl_insert_node(array->tree, memb->tuple), (void *)memb); return memb; } /*---------------------------------------------------------------------- -- delete_array - delete array. -- -- This routine deletes specified array. -- -- Generic values assigned to the array members are not deleted by this -- routine. The calling program itself must delete all assigned generic -- values before deleting the array. */ void delete_array ( MPL *mpl, ARRAY *array /* destroyed */ ) { MEMBER *memb; xassert(array != NULL); /* delete all existing array members */ while (array->head != NULL) { memb = array->head; array->head = memb->next; delete_tuple(mpl, memb->tuple); dmp_free_atom(mpl->members, memb, sizeof(MEMBER)); } /* if the search tree exists, also delete it */ if (array->tree != NULL) avl_delete_tree(array->tree); /* remove the array from the global array list */ if (array->prev == NULL) mpl->a_list = array->next; else array->prev->next = array->next; if (array->next == NULL) ; else array->next->prev = array->prev; /* delete the array descriptor */ dmp_free_atom(mpl->arrays, array, sizeof(ARRAY)); return; } /**********************************************************************/ /* * * DOMAINS AND DUMMY INDICES * * */ /**********************************************************************/ /*---------------------------------------------------------------------- -- assign_dummy_index - assign new value to dummy index. -- -- This routine assigns new value to specified dummy index and, that is -- important, invalidates all temporary resultant values, which depends -- on that dummy index. */ void assign_dummy_index ( MPL *mpl, DOMAIN_SLOT *slot, /* modified */ SYMBOL *value /* not changed */ ) { CODE *leaf, *code; xassert(slot != NULL); xassert(value != NULL); /* delete the current value assigned to the dummy index */ if (slot->value != NULL) { /* if the current value and the new one are identical, actual assignment is not needed */ if (compare_symbols(mpl, slot->value, value) == 0) goto done; /* delete a symbol, which is the current value */ delete_symbol(mpl, slot->value), slot->value = NULL; } /* now walk through all the pseudo-codes with op = O_INDEX, which refer to the dummy index to be changed (these pseudo-codes are leaves in the forest of *all* expressions in the database) */ for (leaf = slot->list; leaf != NULL; leaf = leaf->arg.index. next) { xassert(leaf->op == O_INDEX); /* invalidate all resultant values, which depend on the dummy index, walking from the current leaf toward the root of the corresponding expression tree */ for (code = leaf; code != NULL; code = code->up) { if (code->valid) { /* invalidate and delete resultant value */ code->valid = 0; delete_value(mpl, code->type, &code->value); } } } /* assign new value to the dummy index */ slot->value = copy_symbol(mpl, value); done: return; } /*---------------------------------------------------------------------- -- update_dummy_indices - update current values of dummy indices. -- -- This routine assigns components of "backup" n-tuple to dummy indices -- of specified domain block. If no "backup" n-tuple is defined for the -- domain block, values of the dummy indices remain untouched. */ void update_dummy_indices ( MPL *mpl, DOMAIN_BLOCK *block /* not changed */ ) { DOMAIN_SLOT *slot; TUPLE *temp; if (block->backup != NULL) { for (slot = block->list, temp = block->backup; slot != NULL; slot = slot->next, temp = temp->next) { xassert(temp != NULL); xassert(temp->sym != NULL); assign_dummy_index(mpl, slot, temp->sym); } } return; } /*---------------------------------------------------------------------- -- enter_domain_block - enter domain block. -- -- Let specified domain block have the form: -- -- { ..., (j1, j2, ..., jn) in J, ... } -- -- where j1, j2, ..., jn are dummy indices, J is a basic set. -- -- This routine does the following: -- -- 1. Checks if the given n-tuple is a member of the basic set J. Note -- that J being *out of the scope* of the domain block cannot depend -- on the dummy indices in the same and inner domain blocks, so it -- can be computed before the dummy indices are assigned new values. -- If this check fails, the routine returns with non-zero code. -- -- 2. Saves current values of the dummy indices j1, j2, ..., jn. -- -- 3. Assigns new values, which are components of the given n-tuple, to -- the dummy indices j1, j2, ..., jn. If dimension of the n-tuple is -- larger than n, its extra components n+1, n+2, ... are not used. -- -- 4. Calls the formal routine func which either enters the next domain -- block or evaluates some code within the domain scope. -- -- 5. Restores former values of the dummy indices j1, j2, ..., jn. -- -- Since current values assigned to the dummy indices on entry to this -- routine are restored on exit, the formal routine func is allowed to -- call this routine recursively. */ int enter_domain_block ( MPL *mpl, DOMAIN_BLOCK *block, /* not changed */ TUPLE *tuple, /* not changed */ void *info, void (*func)(MPL *mpl, void *info) ) { TUPLE *backup; int ret = 0; /* check if the given n-tuple is a member of the basic set */ xassert(block->code != NULL); if (!is_member(mpl, block->code, tuple)) { ret = 1; goto done; } /* save reference to "backup" n-tuple, which was used to assign current values of the dummy indices (it is sufficient to save reference, not value, because that n-tuple is defined in some outer level of recursion and therefore cannot be changed on this and deeper recursive calls) */ backup = block->backup; /* set up new "backup" n-tuple, which defines new values of the dummy indices */ block->backup = tuple; /* assign new values to the dummy indices */ update_dummy_indices(mpl, block); /* call the formal routine that does the rest part of the job */ func(mpl, info); /* restore reference to the former "backup" n-tuple */ block->backup = backup; /* restore former values of the dummy indices; note that if the domain block just escaped has no other active instances which may exist due to recursion (it is indicated by a null pointer to the former n-tuple), former values of the dummy indices are undefined; therefore in this case the routine keeps currently assigned values of the dummy indices that involves keeping all dependent temporary results and thereby, if this domain block is not used recursively, allows improving efficiency */ update_dummy_indices(mpl, block); done: return ret; } /*---------------------------------------------------------------------- -- eval_within_domain - perform evaluation within domain scope. -- -- This routine assigns new values (symbols) to all dummy indices of -- specified domain and calls the formal routine func, which is used to -- evaluate some code in the domain scope. Each free dummy index in the -- domain is assigned a value specified in the corresponding component -- of given n-tuple. Non-free dummy indices are assigned values, which -- are computed by this routine. -- -- Number of components in the given n-tuple must be the same as number -- of free indices in the domain. -- -- If the given n-tuple is not a member of the domain set, the routine -- func is not called, and non-zero code is returned. -- -- For the sake of convenience it is allowed to specify domain as NULL -- (then n-tuple also must be 0-tuple, i.e. empty), in which case this -- routine just calls the routine func and returns zero. -- -- This routine allows recursive calls from the routine func providing -- correct values of dummy indices for each instance. -- -- NOTE: The n-tuple passed to this routine must not be changed by any -- other routines called from the formal routine func until this -- routine has returned. */ struct eval_domain_info { /* working info used by the routine eval_within_domain */ DOMAIN *domain; /* domain, which has to be entered */ DOMAIN_BLOCK *block; /* domain block, which is currently processed */ TUPLE *tuple; /* tail of original n-tuple, whose components have to be assigned to free dummy indices in the current domain block */ void *info; /* transit pointer passed to the formal routine func */ void (*func)(MPL *mpl, void *info); /* routine, which has to be executed in the domain scope */ int failure; /* this flag indicates that given n-tuple is not a member of the domain set */ }; static void eval_domain_func(MPL *mpl, void *_my_info) { /* this routine recursively enters into the domain scope and then calls the routine func */ struct eval_domain_info *my_info = _my_info; if (my_info->block != NULL) { /* the current domain block to be entered exists */ DOMAIN_BLOCK *block; DOMAIN_SLOT *slot; TUPLE *tuple = NULL, *temp = NULL; /* save pointer to the current domain block */ block = my_info->block; /* and get ready to enter the next block (if it exists) */ my_info->block = block->next; /* construct temporary n-tuple, whose components correspond to dummy indices (slots) of the current domain; components of the temporary n-tuple that correspond to free dummy indices are assigned references (not values!) to symbols specified in the corresponding components of the given n-tuple, while other components that correspond to non-free dummy indices are assigned symbolic values computed here */ for (slot = block->list; slot != NULL; slot = slot->next) { /* create component that corresponds to the current slot */ if (tuple == NULL) tuple = temp = dmp_get_atom(mpl->tuples, sizeof(TUPLE)); else temp = (temp->next = dmp_get_atom(mpl->tuples, sizeof(TUPLE))); if (slot->code == NULL) { /* dummy index is free; take reference to symbol, which is specified in the corresponding component of given n-tuple */ xassert(my_info->tuple != NULL); temp->sym = my_info->tuple->sym; xassert(temp->sym != NULL); my_info->tuple = my_info->tuple->next; } else { /* dummy index is non-free; compute symbolic value to be temporarily assigned to the dummy index */ temp->sym = eval_symbolic(mpl, slot->code); } } temp->next = NULL; /* enter the current domain block */ if (enter_domain_block(mpl, block, tuple, my_info, eval_domain_func)) my_info->failure = 1; /* delete temporary n-tuple as well as symbols that correspond to non-free dummy indices (they were computed here) */ for (slot = block->list; slot != NULL; slot = slot->next) { xassert(tuple != NULL); temp = tuple; tuple = tuple->next; if (slot->code != NULL) { /* dummy index is non-free; delete symbolic value */ delete_symbol(mpl, temp->sym); } /* delete component that corresponds to the current slot */ dmp_free_atom(mpl->tuples, temp, sizeof(TUPLE)); } } else { /* there are no more domain blocks, i.e. we have reached the domain scope */ xassert(my_info->tuple == NULL); /* check optional predicate specified for the domain */ if (my_info->domain->code != NULL && !eval_logical(mpl, my_info->domain->code)) { /* the predicate is false */ my_info->failure = 2; } else { /* the predicate is true; do the job */ my_info->func(mpl, my_info->info); } } return; } int eval_within_domain ( MPL *mpl, DOMAIN *domain, /* not changed */ TUPLE *tuple, /* not changed */ void *info, void (*func)(MPL *mpl, void *info) ) { /* this routine performs evaluation within domain scope */ struct eval_domain_info _my_info, *my_info = &_my_info; if (domain == NULL) { xassert(tuple == NULL); func(mpl, info); my_info->failure = 0; } else { xassert(tuple != NULL); my_info->domain = domain; my_info->block = domain->list; my_info->tuple = tuple; my_info->info = info; my_info->func = func; my_info->failure = 0; /* enter the very first domain block */ eval_domain_func(mpl, my_info); } return my_info->failure; } /*---------------------------------------------------------------------- -- loop_within_domain - perform iterations within domain scope. -- -- This routine iteratively assigns new values (symbols) to the dummy -- indices of specified domain by enumerating all n-tuples, which are -- members of the domain set, and for every n-tuple it calls the formal -- routine func to evaluate some code within the domain scope. -- -- If the routine func returns non-zero, enumeration within the domain -- is prematurely terminated. -- -- For the sake of convenience it is allowed to specify domain as NULL, -- in which case this routine just calls the routine func only once and -- returns zero. -- -- This routine allows recursive calls from the routine func providing -- correct values of dummy indices for each instance. */ struct loop_domain_info { /* working info used by the routine loop_within_domain */ DOMAIN *domain; /* domain, which has to be entered */ DOMAIN_BLOCK *block; /* domain block, which is currently processed */ int looping; /* clearing this flag leads to terminating enumeration */ void *info; /* transit pointer passed to the formal routine func */ int (*func)(MPL *mpl, void *info); /* routine, which needs to be executed in the domain scope */ }; static void loop_domain_func(MPL *mpl, void *_my_info) { /* this routine enumerates all n-tuples in the basic set of the current domain block, enters recursively into the domain scope for every n-tuple, and then calls the routine func */ struct loop_domain_info *my_info = _my_info; if (my_info->block != NULL) { /* the current domain block to be entered exists */ DOMAIN_BLOCK *block; DOMAIN_SLOT *slot; TUPLE *bound; /* save pointer to the current domain block */ block = my_info->block; /* and get ready to enter the next block (if it exists) */ my_info->block = block->next; /* compute symbolic values, at which non-free dummy indices of the current domain block are bound; since that values don't depend on free dummy indices of the current block, they can be computed once out of the enumeration loop */ bound = create_tuple(mpl); for (slot = block->list; slot != NULL; slot = slot->next) { if (slot->code != NULL) bound = expand_tuple(mpl, bound, eval_symbolic(mpl, slot->code)); } /* start enumeration */ xassert(block->code != NULL); if (block->code->op == O_DOTS) { /* the basic set is "arithmetic", in which case it doesn't need to be computed explicitly */ TUPLE *tuple; int n, j; double t0, tf, dt; /* compute "parameters" of the basic set */ t0 = eval_numeric(mpl, block->code->arg.arg.x); tf = eval_numeric(mpl, block->code->arg.arg.y); if (block->code->arg.arg.z == NULL) dt = 1.0; else dt = eval_numeric(mpl, block->code->arg.arg.z); /* determine cardinality of the basic set */ n = arelset_size(mpl, t0, tf, dt); /* create dummy 1-tuple for members of the basic set */ tuple = expand_tuple(mpl, create_tuple(mpl), create_symbol_num(mpl, 0.0)); /* in case of "arithmetic" set there is exactly one dummy index, which cannot be non-free */ xassert(bound == NULL); /* walk through 1-tuples of the basic set */ for (j = 1; j <= n && my_info->looping; j++) { /* construct dummy 1-tuple for the current member */ tuple->sym->num = arelset_member(mpl, t0, tf, dt, j); /* enter the current domain block */ enter_domain_block(mpl, block, tuple, my_info, loop_domain_func); } /* delete dummy 1-tuple */ delete_tuple(mpl, tuple); } else { /* the basic set is of general kind, in which case it needs to be explicitly computed */ ELEMSET *set; MEMBER *memb; TUPLE *temp1, *temp2; /* compute the basic set */ set = eval_elemset(mpl, block->code); /* walk through all n-tuples of the basic set */ for (memb = set->head; memb != NULL && my_info->looping; memb = memb->next) { /* all components of the current n-tuple that correspond to non-free dummy indices must be feasible; otherwise the n-tuple is not in the basic set */ temp1 = memb->tuple; temp2 = bound; for (slot = block->list; slot != NULL; slot = slot->next) { xassert(temp1 != NULL); if (slot->code != NULL) { /* non-free dummy index */ xassert(temp2 != NULL); if (compare_symbols(mpl, temp1->sym, temp2->sym) != 0) { /* the n-tuple is not in the basic set */ goto skip; } temp2 = temp2->next; } temp1 = temp1->next; } xassert(temp1 == NULL); xassert(temp2 == NULL); /* enter the current domain block */ enter_domain_block(mpl, block, memb->tuple, my_info, loop_domain_func); skip: ; } /* delete the basic set */ delete_elemset(mpl, set); } /* delete symbolic values binding non-free dummy indices */ delete_tuple(mpl, bound); /* restore pointer to the current domain block */ my_info->block = block; } else { /* there are no more domain blocks, i.e. we have reached the domain scope */ /* check optional predicate specified for the domain */ if (my_info->domain->code != NULL && !eval_logical(mpl, my_info->domain->code)) { /* the predicate is false */ /* nop */; } else { /* the predicate is true; do the job */ my_info->looping = !my_info->func(mpl, my_info->info); } } return; } void loop_within_domain ( MPL *mpl, DOMAIN *domain, /* not changed */ void *info, int (*func)(MPL *mpl, void *info) ) { /* this routine performs iterations within domain scope */ struct loop_domain_info _my_info, *my_info = &_my_info; if (domain == NULL) func(mpl, info); else { my_info->domain = domain; my_info->block = domain->list; my_info->looping = 1; my_info->info = info; my_info->func = func; /* enter the very first domain block */ loop_domain_func(mpl, my_info); } return; } /*---------------------------------------------------------------------- -- out_of_domain - raise domain exception. -- -- This routine is called when a reference is made to a member of some -- model object, but its n-tuple is out of the object domain. */ void out_of_domain ( MPL *mpl, char *name, /* not changed */ TUPLE *tuple /* not changed */ ) { xassert(name != NULL); xassert(tuple != NULL); error(mpl, "%s%s out of domain", name, format_tuple(mpl, '[', tuple)); /* no return */ } /*---------------------------------------------------------------------- -- get_domain_tuple - obtain current n-tuple from domain. -- -- This routine constructs n-tuple, whose components are current values -- assigned to *free* dummy indices of specified domain. -- -- For the sake of convenience it is allowed to specify domain as NULL, -- in which case this routine returns 0-tuple. -- -- NOTE: This routine must not be called out of domain scope. */ TUPLE *get_domain_tuple ( MPL *mpl, DOMAIN *domain /* not changed */ ) { DOMAIN_BLOCK *block; DOMAIN_SLOT *slot; TUPLE *tuple; tuple = create_tuple(mpl); if (domain != NULL) { for (block = domain->list; block != NULL; block = block->next) { for (slot = block->list; slot != NULL; slot = slot->next) { if (slot->code == NULL) { xassert(slot->value != NULL); tuple = expand_tuple(mpl, tuple, copy_symbol(mpl, slot->value)); } } } } return tuple; } /*---------------------------------------------------------------------- -- clean_domain - clean domain. -- -- This routine cleans specified domain that assumes deleting all stuff -- dynamically allocated during the generation phase. */ void clean_domain(MPL *mpl, DOMAIN *domain) { DOMAIN_BLOCK *block; DOMAIN_SLOT *slot; /* if no domain is specified, do nothing */ if (domain == NULL) goto done; /* clean all domain blocks */ for (block = domain->list; block != NULL; block = block->next) { /* clean all domain slots */ for (slot = block->list; slot != NULL; slot = slot->next) { /* clean pseudo-code for computing bound value */ clean_code(mpl, slot->code); /* delete symbolic value assigned to dummy index */ if (slot->value != NULL) delete_symbol(mpl, slot->value), slot->value = NULL; } /* clean pseudo-code for computing basic set */ clean_code(mpl, block->code); } /* clean pseudo-code for computing domain predicate */ clean_code(mpl, domain->code); done: return; } /**********************************************************************/ /* * * MODEL SETS * * */ /**********************************************************************/ /*---------------------------------------------------------------------- -- check_elem_set - check elemental set assigned to set member. -- -- This routine checks if given elemental set being assigned to member -- of specified model set satisfies to all restrictions. -- -- NOTE: This routine must not be called out of domain scope. */ void check_elem_set ( MPL *mpl, SET *set, /* not changed */ TUPLE *tuple, /* not changed */ ELEMSET *refer /* not changed */ ) { WITHIN *within; MEMBER *memb; int eqno; /* elemental set must be within all specified supersets */ for (within = set->within, eqno = 1; within != NULL; within = within->next, eqno++) { xassert(within->code != NULL); for (memb = refer->head; memb != NULL; memb = memb->next) { if (!is_member(mpl, within->code, memb->tuple)) { char buf[255+1]; strcpy(buf, format_tuple(mpl, '(', memb->tuple)); xassert(strlen(buf) < sizeof(buf)); error(mpl, "%s%s contains %s which not within specified " "set; see (%d)", set->name, format_tuple(mpl, '[', tuple), buf, eqno); } } } return; } /*---------------------------------------------------------------------- -- take_member_set - obtain elemental set assigned to set member. -- -- This routine obtains a reference to elemental set assigned to given -- member of specified model set and returns it on exit. -- -- NOTE: This routine must not be called out of domain scope. */ ELEMSET *take_member_set /* returns reference, not value */ ( MPL *mpl, SET *set, /* not changed */ TUPLE *tuple /* not changed */ ) { MEMBER *memb; ELEMSET *refer; /* find member in the set array */ memb = find_member(mpl, set->array, tuple); if (memb != NULL) { /* member exists, so just take the reference */ refer = memb->value.set; } else if (set->assign != NULL) { /* compute value using assignment expression */ refer = eval_elemset(mpl, set->assign); add: /* check that the elemental set satisfies to all restrictions, assign it to new member, and add the member to the array */ check_elem_set(mpl, set, tuple, refer); memb = add_member(mpl, set->array, copy_tuple(mpl, tuple)); memb->value.set = refer; } else if (set->option != NULL) { /* compute default elemental set */ refer = eval_elemset(mpl, set->option); goto add; } else { /* no value (elemental set) is provided */ error(mpl, "no value for %s%s", set->name, format_tuple(mpl, '[', tuple)); } return refer; } /*---------------------------------------------------------------------- -- eval_member_set - evaluate elemental set assigned to set member. -- -- This routine evaluates a reference to elemental set assigned to given -- member of specified model set and returns it on exit. */ struct eval_set_info { /* working info used by the routine eval_member_set */ SET *set; /* model set */ TUPLE *tuple; /* n-tuple, which defines set member */ MEMBER *memb; /* normally this pointer is NULL; the routine uses this pointer to check data provided in the data section, in which case it points to a member currently checked; this check is performed automatically only once when a reference to any member occurs for the first time */ ELEMSET *refer; /* evaluated reference to elemental set */ }; static void eval_set_func(MPL *mpl, void *_info) { /* this is auxiliary routine to work within domain scope */ struct eval_set_info *info = _info; if (info->memb != NULL) { /* checking call; check elemental set being assigned */ check_elem_set(mpl, info->set, info->memb->tuple, info->memb->value.set); } else { /* normal call; evaluate member, which has given n-tuple */ info->refer = take_member_set(mpl, info->set, info->tuple); } return; } #if 1 /* 12/XII-2008 */ static void saturate_set(MPL *mpl, SET *set) { GADGET *gadget = set->gadget; ELEMSET *data; MEMBER *elem, *memb; TUPLE *tuple, *work[20]; int i; xprintf("Generating %s...\n", set->name); eval_whole_set(mpl, gadget->set); /* gadget set must have exactly one member */ xassert(gadget->set->array != NULL); xassert(gadget->set->array->head != NULL); xassert(gadget->set->array->head == gadget->set->array->tail); data = gadget->set->array->head->value.set; xassert(data->type == A_NONE); xassert(data->dim == gadget->set->dimen); /* walk thru all elements of the plain set */ for (elem = data->head; elem != NULL; elem = elem->next) { /* create a copy of n-tuple */ tuple = copy_tuple(mpl, elem->tuple); /* rearrange component of the n-tuple */ for (i = 0; i < gadget->set->dimen; i++) work[i] = NULL; for (i = 0; tuple != NULL; tuple = tuple->next) work[gadget->ind[i++]-1] = tuple; xassert(i == gadget->set->dimen); for (i = 0; i < gadget->set->dimen; i++) { xassert(work[i] != NULL); work[i]->next = work[i+1]; } /* construct subscript list from first set->dim components */ if (set->dim == 0) tuple = NULL; else tuple = work[0], work[set->dim-1]->next = NULL; /* find corresponding member of the set to be initialized */ memb = find_member(mpl, set->array, tuple); if (memb == NULL) { /* not found; add new member to the set and assign it empty elemental set */ memb = add_member(mpl, set->array, tuple); memb->value.set = create_elemset(mpl, set->dimen); } else { /* found; free subscript list */ delete_tuple(mpl, tuple); } /* construct new n-tuple from rest set->dimen components */ tuple = work[set->dim]; xassert(set->dim + set->dimen == gadget->set->dimen); work[gadget->set->dimen-1]->next = NULL; /* and add it to the elemental set assigned to the member (no check for duplicates is needed) */ add_tuple(mpl, memb->value.set, tuple); } /* the set has been saturated with data */ set->data = 1; return; } #endif ELEMSET *eval_member_set /* returns reference, not value */ ( MPL *mpl, SET *set, /* not changed */ TUPLE *tuple /* not changed */ ) { /* this routine evaluates set member */ struct eval_set_info _info, *info = &_info; xassert(set->dim == tuple_dimen(mpl, tuple)); info->set = set; info->tuple = tuple; #if 1 /* 12/XII-2008 */ if (set->gadget != NULL && set->data == 0) { /* initialize the set with data from a plain set */ saturate_set(mpl, set); } #endif if (set->data == 1) { /* check data, which are provided in the data section, but not checked yet */ /* save pointer to the last array member; note that during the check new members may be added beyond the last member due to references to the same parameter from default expression as well as from expressions that define restricting supersets; however, values assigned to the new members will be checked by other routine, so we don't need to check them here */ MEMBER *tail = set->array->tail; /* change the data status to prevent infinite recursive loop due to references to the same set during the check */ set->data = 2; /* check elemental sets assigned to array members in the data section until the marked member has been reached */ for (info->memb = set->array->head; info->memb != NULL; info->memb = info->memb->next) { if (eval_within_domain(mpl, set->domain, info->memb->tuple, info, eval_set_func)) out_of_domain(mpl, set->name, info->memb->tuple); if (info->memb == tail) break; } /* the check has been finished */ } /* evaluate member, which has given n-tuple */ info->memb = NULL; if (eval_within_domain(mpl, info->set->domain, info->tuple, info, eval_set_func)) out_of_domain(mpl, set->name, info->tuple); /* bring evaluated reference to the calling program */ return info->refer; } /*---------------------------------------------------------------------- -- eval_whole_set - evaluate model set over entire domain. -- -- This routine evaluates all members of specified model set over entire -- domain. */ static int whole_set_func(MPL *mpl, void *info) { /* this is auxiliary routine to work within domain scope */ SET *set = (SET *)info; TUPLE *tuple = get_domain_tuple(mpl, set->domain); eval_member_set(mpl, set, tuple); delete_tuple(mpl, tuple); return 0; } void eval_whole_set(MPL *mpl, SET *set) { loop_within_domain(mpl, set->domain, set, whole_set_func); return; } /*---------------------------------------------------------------------- -- clean set - clean model set. -- -- This routine cleans specified model set that assumes deleting all -- stuff dynamically allocated during the generation phase. */ void clean_set(MPL *mpl, SET *set) { WITHIN *within; MEMBER *memb; /* clean subscript domain */ clean_domain(mpl, set->domain); /* clean pseudo-code for computing supersets */ for (within = set->within; within != NULL; within = within->next) clean_code(mpl, within->code); /* clean pseudo-code for computing assigned value */ clean_code(mpl, set->assign); /* clean pseudo-code for computing default value */ clean_code(mpl, set->option); /* reset data status flag */ set->data = 0; /* delete content array */ for (memb = set->array->head; memb != NULL; memb = memb->next) delete_value(mpl, set->array->type, &memb->value); delete_array(mpl, set->array), set->array = NULL; return; } /**********************************************************************/ /* * * MODEL PARAMETERS * * */ /**********************************************************************/ /*---------------------------------------------------------------------- -- check_value_num - check numeric value assigned to parameter member. -- -- This routine checks if numeric value being assigned to some member -- of specified numeric model parameter satisfies to all restrictions. -- -- NOTE: This routine must not be called out of domain scope. */ void check_value_num ( MPL *mpl, PARAMETER *par, /* not changed */ TUPLE *tuple, /* not changed */ double value ) { CONDITION *cond; WITHIN *in; int eqno; /* the value must satisfy to the parameter type */ switch (par->type) { case A_NUMERIC: break; case A_INTEGER: if (value != floor(value)) error(mpl, "%s%s = %.*g not integer", par->name, format_tuple(mpl, '[', tuple), DBL_DIG, value); break; case A_BINARY: if (!(value == 0.0 || value == 1.0)) error(mpl, "%s%s = %.*g not binary", par->name, format_tuple(mpl, '[', tuple), DBL_DIG, value); break; default: xassert(par != par); } /* the value must satisfy to all specified conditions */ for (cond = par->cond, eqno = 1; cond != NULL; cond = cond->next, eqno++) { double bound; char *rho; xassert(cond->code != NULL); bound = eval_numeric(mpl, cond->code); switch (cond->rho) { case O_LT: if (!(value < bound)) { rho = "<"; err: error(mpl, "%s%s = %.*g not %s %.*g; see (%d)", par->name, format_tuple(mpl, '[', tuple), DBL_DIG, value, rho, DBL_DIG, bound, eqno); } break; case O_LE: if (!(value <= bound)) { rho = "<="; goto err; } break; case O_EQ: if (!(value == bound)) { rho = "="; goto err; } break; case O_GE: if (!(value >= bound)) { rho = ">="; goto err; } break; case O_GT: if (!(value > bound)) { rho = ">"; goto err; } break; case O_NE: if (!(value != bound)) { rho = "<>"; goto err; } break; default: xassert(cond != cond); } } /* the value must be in all specified supersets */ for (in = par->in, eqno = 1; in != NULL; in = in->next, eqno++) { TUPLE *dummy; xassert(in->code != NULL); xassert(in->code->dim == 1); dummy = expand_tuple(mpl, create_tuple(mpl), create_symbol_num(mpl, value)); if (!is_member(mpl, in->code, dummy)) error(mpl, "%s%s = %.*g not in specified set; see (%d)", par->name, format_tuple(mpl, '[', tuple), DBL_DIG, value, eqno); delete_tuple(mpl, dummy); } return; } /*---------------------------------------------------------------------- -- take_member_num - obtain num. value assigned to parameter member. -- -- This routine obtains a numeric value assigned to member of specified -- numeric model parameter and returns it on exit. -- -- NOTE: This routine must not be called out of domain scope. */ double take_member_num ( MPL *mpl, PARAMETER *par, /* not changed */ TUPLE *tuple /* not changed */ ) { MEMBER *memb; double value; /* find member in the parameter array */ memb = find_member(mpl, par->array, tuple); if (memb != NULL) { /* member exists, so just take its value */ value = memb->value.num; } else if (par->assign != NULL) { /* compute value using assignment expression */ value = eval_numeric(mpl, par->assign); add: /* check that the value satisfies to all restrictions, assign it to new member, and add the member to the array */ check_value_num(mpl, par, tuple, value); memb = add_member(mpl, par->array, copy_tuple(mpl, tuple)); memb->value.num = value; } else if (par->option != NULL) { /* compute default value */ value = eval_numeric(mpl, par->option); goto add; } else if (par->defval != NULL) { /* take default value provided in the data section */ if (par->defval->str != NULL) error(mpl, "cannot convert %s to floating-point number", format_symbol(mpl, par->defval)); value = par->defval->num; goto add; } else { /* no value is provided */ error(mpl, "no value for %s%s", par->name, format_tuple(mpl, '[', tuple)); } return value; } /*---------------------------------------------------------------------- -- eval_member_num - evaluate num. value assigned to parameter member. -- -- This routine evaluates a numeric value assigned to given member of -- specified numeric model parameter and returns it on exit. */ struct eval_num_info { /* working info used by the routine eval_member_num */ PARAMETER *par; /* model parameter */ TUPLE *tuple; /* n-tuple, which defines parameter member */ MEMBER *memb; /* normally this pointer is NULL; the routine uses this pointer to check data provided in the data section, in which case it points to a member currently checked; this check is performed automatically only once when a reference to any member occurs for the first time */ double value; /* evaluated numeric value */ }; static void eval_num_func(MPL *mpl, void *_info) { /* this is auxiliary routine to work within domain scope */ struct eval_num_info *info = _info; if (info->memb != NULL) { /* checking call; check numeric value being assigned */ check_value_num(mpl, info->par, info->memb->tuple, info->memb->value.num); } else { /* normal call; evaluate member, which has given n-tuple */ info->value = take_member_num(mpl, info->par, info->tuple); } return; } double eval_member_num ( MPL *mpl, PARAMETER *par, /* not changed */ TUPLE *tuple /* not changed */ ) { /* this routine evaluates numeric parameter member */ struct eval_num_info _info, *info = &_info; xassert(par->type == A_NUMERIC || par->type == A_INTEGER || par->type == A_BINARY); xassert(par->dim == tuple_dimen(mpl, tuple)); info->par = par; info->tuple = tuple; if (par->data == 1) { /* check data, which are provided in the data section, but not checked yet */ /* save pointer to the last array member; note that during the check new members may be added beyond the last member due to references to the same parameter from default expression as well as from expressions that define restricting conditions; however, values assigned to the new members will be checked by other routine, so we don't need to check them here */ MEMBER *tail = par->array->tail; /* change the data status to prevent infinite recursive loop due to references to the same parameter during the check */ par->data = 2; /* check values assigned to array members in the data section until the marked member has been reached */ for (info->memb = par->array->head; info->memb != NULL; info->memb = info->memb->next) { if (eval_within_domain(mpl, par->domain, info->memb->tuple, info, eval_num_func)) out_of_domain(mpl, par->name, info->memb->tuple); if (info->memb == tail) break; } /* the check has been finished */ } /* evaluate member, which has given n-tuple */ info->memb = NULL; if (eval_within_domain(mpl, info->par->domain, info->tuple, info, eval_num_func)) out_of_domain(mpl, par->name, info->tuple); /* bring evaluated value to the calling program */ return info->value; } /*---------------------------------------------------------------------- -- check_value_sym - check symbolic value assigned to parameter member. -- -- This routine checks if symbolic value being assigned to some member -- of specified symbolic model parameter satisfies to all restrictions. -- -- NOTE: This routine must not be called out of domain scope. */ void check_value_sym ( MPL *mpl, PARAMETER *par, /* not changed */ TUPLE *tuple, /* not changed */ SYMBOL *value /* not changed */ ) { CONDITION *cond; WITHIN *in; int eqno; /* the value must satisfy to all specified conditions */ for (cond = par->cond, eqno = 1; cond != NULL; cond = cond->next, eqno++) { SYMBOL *bound; char buf[255+1]; xassert(cond->code != NULL); bound = eval_symbolic(mpl, cond->code); switch (cond->rho) { #if 1 /* 13/VIII-2008 */ case O_LT: if (!(compare_symbols(mpl, value, bound) < 0)) { strcpy(buf, format_symbol(mpl, bound)); xassert(strlen(buf) < sizeof(buf)); error(mpl, "%s%s = %s not < %s", par->name, format_tuple(mpl, '[', tuple), format_symbol(mpl, value), buf, eqno); } break; case O_LE: if (!(compare_symbols(mpl, value, bound) <= 0)) { strcpy(buf, format_symbol(mpl, bound)); xassert(strlen(buf) < sizeof(buf)); error(mpl, "%s%s = %s not <= %s", par->name, format_tuple(mpl, '[', tuple), format_symbol(mpl, value), buf, eqno); } break; #endif case O_EQ: if (!(compare_symbols(mpl, value, bound) == 0)) { strcpy(buf, format_symbol(mpl, bound)); xassert(strlen(buf) < sizeof(buf)); error(mpl, "%s%s = %s not = %s", par->name, format_tuple(mpl, '[', tuple), format_symbol(mpl, value), buf, eqno); } break; #if 1 /* 13/VIII-2008 */ case O_GE: if (!(compare_symbols(mpl, value, bound) >= 0)) { strcpy(buf, format_symbol(mpl, bound)); xassert(strlen(buf) < sizeof(buf)); error(mpl, "%s%s = %s not >= %s", par->name, format_tuple(mpl, '[', tuple), format_symbol(mpl, value), buf, eqno); } break; case O_GT: if (!(compare_symbols(mpl, value, bound) > 0)) { strcpy(buf, format_symbol(mpl, bound)); xassert(strlen(buf) < sizeof(buf)); error(mpl, "%s%s = %s not > %s", par->name, format_tuple(mpl, '[', tuple), format_symbol(mpl, value), buf, eqno); } break; #endif case O_NE: if (!(compare_symbols(mpl, value, bound) != 0)) { strcpy(buf, format_symbol(mpl, bound)); xassert(strlen(buf) < sizeof(buf)); error(mpl, "%s%s = %s not <> %s", par->name, format_tuple(mpl, '[', tuple), format_symbol(mpl, value), buf, eqno); } break; default: xassert(cond != cond); } delete_symbol(mpl, bound); } /* the value must be in all specified supersets */ for (in = par->in, eqno = 1; in != NULL; in = in->next, eqno++) { TUPLE *dummy; xassert(in->code != NULL); xassert(in->code->dim == 1); dummy = expand_tuple(mpl, create_tuple(mpl), copy_symbol(mpl, value)); if (!is_member(mpl, in->code, dummy)) error(mpl, "%s%s = %s not in specified set; see (%d)", par->name, format_tuple(mpl, '[', tuple), format_symbol(mpl, value), eqno); delete_tuple(mpl, dummy); } return; } /*---------------------------------------------------------------------- -- take_member_sym - obtain symb. value assigned to parameter member. -- -- This routine obtains a symbolic value assigned to member of specified -- symbolic model parameter and returns it on exit. -- -- NOTE: This routine must not be called out of domain scope. */ SYMBOL *take_member_sym /* returns value, not reference */ ( MPL *mpl, PARAMETER *par, /* not changed */ TUPLE *tuple /* not changed */ ) { MEMBER *memb; SYMBOL *value; /* find member in the parameter array */ memb = find_member(mpl, par->array, tuple); if (memb != NULL) { /* member exists, so just take its value */ value = copy_symbol(mpl, memb->value.sym); } else if (par->assign != NULL) { /* compute value using assignment expression */ value = eval_symbolic(mpl, par->assign); add: /* check that the value satisfies to all restrictions, assign it to new member, and add the member to the array */ check_value_sym(mpl, par, tuple, value); memb = add_member(mpl, par->array, copy_tuple(mpl, tuple)); memb->value.sym = copy_symbol(mpl, value); } else if (par->option != NULL) { /* compute default value */ value = eval_symbolic(mpl, par->option); goto add; } else if (par->defval != NULL) { /* take default value provided in the data section */ value = copy_symbol(mpl, par->defval); goto add; } else { /* no value is provided */ error(mpl, "no value for %s%s", par->name, format_tuple(mpl, '[', tuple)); } return value; } /*---------------------------------------------------------------------- -- eval_member_sym - evaluate symb. value assigned to parameter member. -- -- This routine evaluates a symbolic value assigned to given member of -- specified symbolic model parameter and returns it on exit. */ struct eval_sym_info { /* working info used by the routine eval_member_sym */ PARAMETER *par; /* model parameter */ TUPLE *tuple; /* n-tuple, which defines parameter member */ MEMBER *memb; /* normally this pointer is NULL; the routine uses this pointer to check data provided in the data section, in which case it points to a member currently checked; this check is performed automatically only once when a reference to any member occurs for the first time */ SYMBOL *value; /* evaluated symbolic value */ }; static void eval_sym_func(MPL *mpl, void *_info) { /* this is auxiliary routine to work within domain scope */ struct eval_sym_info *info = _info; if (info->memb != NULL) { /* checking call; check symbolic value being assigned */ check_value_sym(mpl, info->par, info->memb->tuple, info->memb->value.sym); } else { /* normal call; evaluate member, which has given n-tuple */ info->value = take_member_sym(mpl, info->par, info->tuple); } return; } SYMBOL *eval_member_sym /* returns value, not reference */ ( MPL *mpl, PARAMETER *par, /* not changed */ TUPLE *tuple /* not changed */ ) { /* this routine evaluates symbolic parameter member */ struct eval_sym_info _info, *info = &_info; xassert(par->type == A_SYMBOLIC); xassert(par->dim == tuple_dimen(mpl, tuple)); info->par = par; info->tuple = tuple; if (par->data == 1) { /* check data, which are provided in the data section, but not checked yet */ /* save pointer to the last array member; note that during the check new members may be added beyond the last member due to references to the same parameter from default expression as well as from expressions that define restricting conditions; however, values assigned to the new members will be checked by other routine, so we don't need to check them here */ MEMBER *tail = par->array->tail; /* change the data status to prevent infinite recursive loop due to references to the same parameter during the check */ par->data = 2; /* check values assigned to array members in the data section until the marked member has been reached */ for (info->memb = par->array->head; info->memb != NULL; info->memb = info->memb->next) { if (eval_within_domain(mpl, par->domain, info->memb->tuple, info, eval_sym_func)) out_of_domain(mpl, par->name, info->memb->tuple); if (info->memb == tail) break; } /* the check has been finished */ } /* evaluate member, which has given n-tuple */ info->memb = NULL; if (eval_within_domain(mpl, info->par->domain, info->tuple, info, eval_sym_func)) out_of_domain(mpl, par->name, info->tuple); /* bring evaluated value to the calling program */ return info->value; } /*---------------------------------------------------------------------- -- eval_whole_par - evaluate model parameter over entire domain. -- -- This routine evaluates all members of specified model parameter over -- entire domain. */ static int whole_par_func(MPL *mpl, void *info) { /* this is auxiliary routine to work within domain scope */ PARAMETER *par = (PARAMETER *)info; TUPLE *tuple = get_domain_tuple(mpl, par->domain); switch (par->type) { case A_NUMERIC: case A_INTEGER: case A_BINARY: eval_member_num(mpl, par, tuple); break; case A_SYMBOLIC: delete_symbol(mpl, eval_member_sym(mpl, par, tuple)); break; default: xassert(par != par); } delete_tuple(mpl, tuple); return 0; } void eval_whole_par(MPL *mpl, PARAMETER *par) { loop_within_domain(mpl, par->domain, par, whole_par_func); return; } /*---------------------------------------------------------------------- -- clean_parameter - clean model parameter. -- -- This routine cleans specified model parameter that assumes deleting -- all stuff dynamically allocated during the generation phase. */ void clean_parameter(MPL *mpl, PARAMETER *par) { CONDITION *cond; WITHIN *in; MEMBER *memb; /* clean subscript domain */ clean_domain(mpl, par->domain); /* clean pseudo-code for computing restricting conditions */ for (cond = par->cond; cond != NULL; cond = cond->next) clean_code(mpl, cond->code); /* clean pseudo-code for computing restricting supersets */ for (in = par->in; in != NULL; in = in->next) clean_code(mpl, in->code); /* clean pseudo-code for computing assigned value */ clean_code(mpl, par->assign); /* clean pseudo-code for computing default value */ clean_code(mpl, par->option); /* reset data status flag */ par->data = 0; /* delete default symbolic value */ if (par->defval != NULL) delete_symbol(mpl, par->defval), par->defval = NULL; /* delete content array */ for (memb = par->array->head; memb != NULL; memb = memb->next) delete_value(mpl, par->array->type, &memb->value); delete_array(mpl, par->array), par->array = NULL; return; } /**********************************************************************/ /* * * MODEL VARIABLES * * */ /**********************************************************************/ /*---------------------------------------------------------------------- -- take_member_var - obtain reference to elemental variable. -- -- This routine obtains a reference to elemental variable assigned to -- given member of specified model variable and returns it on exit. If -- necessary, new elemental variable is created. -- -- NOTE: This routine must not be called out of domain scope. */ ELEMVAR *take_member_var /* returns reference */ ( MPL *mpl, VARIABLE *var, /* not changed */ TUPLE *tuple /* not changed */ ) { MEMBER *memb; ELEMVAR *refer; /* find member in the variable array */ memb = find_member(mpl, var->array, tuple); if (memb != NULL) { /* member exists, so just take the reference */ refer = memb->value.var; } else { /* member is referenced for the first time and therefore does not exist; create new elemental variable, assign it to new member, and add the member to the variable array */ memb = add_member(mpl, var->array, copy_tuple(mpl, tuple)); refer = (memb->value.var = dmp_get_atom(mpl->elemvars, sizeof(ELEMVAR))); refer->j = 0; refer->var = var; refer->memb = memb; /* compute lower bound */ if (var->lbnd == NULL) refer->lbnd = 0.0; else refer->lbnd = eval_numeric(mpl, var->lbnd); /* compute upper bound */ if (var->ubnd == NULL) refer->ubnd = 0.0; else if (var->ubnd == var->lbnd) refer->ubnd = refer->lbnd; else refer->ubnd = eval_numeric(mpl, var->ubnd); /* nullify working quantity */ refer->temp = 0.0; #if 1 /* 15/V-2010 */ /* solution has not been obtained by the solver yet */ refer->stat = 0; refer->prim = refer->dual = 0.0; #endif } return refer; } /*---------------------------------------------------------------------- -- eval_member_var - evaluate reference to elemental variable. -- -- This routine evaluates a reference to elemental variable assigned to -- member of specified model variable and returns it on exit. */ struct eval_var_info { /* working info used by the routine eval_member_var */ VARIABLE *var; /* model variable */ TUPLE *tuple; /* n-tuple, which defines variable member */ ELEMVAR *refer; /* evaluated reference to elemental variable */ }; static void eval_var_func(MPL *mpl, void *_info) { /* this is auxiliary routine to work within domain scope */ struct eval_var_info *info = _info; info->refer = take_member_var(mpl, info->var, info->tuple); return; } ELEMVAR *eval_member_var /* returns reference */ ( MPL *mpl, VARIABLE *var, /* not changed */ TUPLE *tuple /* not changed */ ) { /* this routine evaluates variable member */ struct eval_var_info _info, *info = &_info; xassert(var->dim == tuple_dimen(mpl, tuple)); info->var = var; info->tuple = tuple; /* evaluate member, which has given n-tuple */ if (eval_within_domain(mpl, info->var->domain, info->tuple, info, eval_var_func)) out_of_domain(mpl, var->name, info->tuple); /* bring evaluated reference to the calling program */ return info->refer; } /*---------------------------------------------------------------------- -- eval_whole_var - evaluate model variable over entire domain. -- -- This routine evaluates all members of specified model variable over -- entire domain. */ static int whole_var_func(MPL *mpl, void *info) { /* this is auxiliary routine to work within domain scope */ VARIABLE *var = (VARIABLE *)info; TUPLE *tuple = get_domain_tuple(mpl, var->domain); eval_member_var(mpl, var, tuple); delete_tuple(mpl, tuple); return 0; } void eval_whole_var(MPL *mpl, VARIABLE *var) { loop_within_domain(mpl, var->domain, var, whole_var_func); return; } /*---------------------------------------------------------------------- -- clean_variable - clean model variable. -- -- This routine cleans specified model variable that assumes deleting -- all stuff dynamically allocated during the generation phase. */ void clean_variable(MPL *mpl, VARIABLE *var) { MEMBER *memb; /* clean subscript domain */ clean_domain(mpl, var->domain); /* clean code for computing lower bound */ clean_code(mpl, var->lbnd); /* clean code for computing upper bound */ if (var->ubnd != var->lbnd) clean_code(mpl, var->ubnd); /* delete content array */ for (memb = var->array->head; memb != NULL; memb = memb->next) dmp_free_atom(mpl->elemvars, memb->value.var, sizeof(ELEMVAR)); delete_array(mpl, var->array), var->array = NULL; return; } /**********************************************************************/ /* * * MODEL CONSTRAINTS AND OBJECTIVES * * */ /**********************************************************************/ /*---------------------------------------------------------------------- -- take_member_con - obtain reference to elemental constraint. -- -- This routine obtains a reference to elemental constraint assigned -- to given member of specified model constraint and returns it on exit. -- If necessary, new elemental constraint is created. -- -- NOTE: This routine must not be called out of domain scope. */ ELEMCON *take_member_con /* returns reference */ ( MPL *mpl, CONSTRAINT *con, /* not changed */ TUPLE *tuple /* not changed */ ) { MEMBER *memb; ELEMCON *refer; /* find member in the constraint array */ memb = find_member(mpl, con->array, tuple); if (memb != NULL) { /* member exists, so just take the reference */ refer = memb->value.con; } else { /* member is referenced for the first time and therefore does not exist; create new elemental constraint, assign it to new member, and add the member to the constraint array */ memb = add_member(mpl, con->array, copy_tuple(mpl, tuple)); refer = (memb->value.con = dmp_get_atom(mpl->elemcons, sizeof(ELEMCON))); refer->i = 0; refer->con = con; refer->memb = memb; /* compute linear form */ xassert(con->code != NULL); refer->form = eval_formula(mpl, con->code); /* compute lower and upper bounds */ if (con->lbnd == NULL && con->ubnd == NULL) { /* objective has no bounds */ double temp; xassert(con->type == A_MINIMIZE || con->type == A_MAXIMIZE); /* carry the constant term to the right-hand side */ refer->form = remove_constant(mpl, refer->form, &temp); refer->lbnd = refer->ubnd = - temp; } else if (con->lbnd != NULL && con->ubnd == NULL) { /* constraint a * x + b >= c * y + d is transformed to the standard form a * x - c * y >= d - b */ double temp; xassert(con->type == A_CONSTRAINT); refer->form = linear_comb(mpl, +1.0, refer->form, -1.0, eval_formula(mpl, con->lbnd)); refer->form = remove_constant(mpl, refer->form, &temp); refer->lbnd = - temp; refer->ubnd = 0.0; } else if (con->lbnd == NULL && con->ubnd != NULL) { /* constraint a * x + b <= c * y + d is transformed to the standard form a * x - c * y <= d - b */ double temp; xassert(con->type == A_CONSTRAINT); refer->form = linear_comb(mpl, +1.0, refer->form, -1.0, eval_formula(mpl, con->ubnd)); refer->form = remove_constant(mpl, refer->form, &temp); refer->lbnd = 0.0; refer->ubnd = - temp; } else if (con->lbnd == con->ubnd) { /* constraint a * x + b = c * y + d is transformed to the standard form a * x - c * y = d - b */ double temp; xassert(con->type == A_CONSTRAINT); refer->form = linear_comb(mpl, +1.0, refer->form, -1.0, eval_formula(mpl, con->lbnd)); refer->form = remove_constant(mpl, refer->form, &temp); refer->lbnd = refer->ubnd = - temp; } else { /* ranged constraint c <= a * x + b <= d is transformed to the standard form c - b <= a * x <= d - b */ double temp, temp1, temp2; xassert(con->type == A_CONSTRAINT); refer->form = remove_constant(mpl, refer->form, &temp); xassert(remove_constant(mpl, eval_formula(mpl, con->lbnd), &temp1) == NULL); xassert(remove_constant(mpl, eval_formula(mpl, con->ubnd), &temp2) == NULL); refer->lbnd = fp_sub(mpl, temp1, temp); refer->ubnd = fp_sub(mpl, temp2, temp); } #if 1 /* 15/V-2010 */ /* solution has not been obtained by the solver yet */ refer->stat = 0; refer->prim = refer->dual = 0.0; #endif } return refer; } /*---------------------------------------------------------------------- -- eval_member_con - evaluate reference to elemental constraint. -- -- This routine evaluates a reference to elemental constraint assigned -- to member of specified model constraint and returns it on exit. */ struct eval_con_info { /* working info used by the routine eval_member_con */ CONSTRAINT *con; /* model constraint */ TUPLE *tuple; /* n-tuple, which defines constraint member */ ELEMCON *refer; /* evaluated reference to elemental constraint */ }; static void eval_con_func(MPL *mpl, void *_info) { /* this is auxiliary routine to work within domain scope */ struct eval_con_info *info = _info; info->refer = take_member_con(mpl, info->con, info->tuple); return; } ELEMCON *eval_member_con /* returns reference */ ( MPL *mpl, CONSTRAINT *con, /* not changed */ TUPLE *tuple /* not changed */ ) { /* this routine evaluates constraint member */ struct eval_con_info _info, *info = &_info; xassert(con->dim == tuple_dimen(mpl, tuple)); info->con = con; info->tuple = tuple; /* evaluate member, which has given n-tuple */ if (eval_within_domain(mpl, info->con->domain, info->tuple, info, eval_con_func)) out_of_domain(mpl, con->name, info->tuple); /* bring evaluated reference to the calling program */ return info->refer; } /*---------------------------------------------------------------------- -- eval_whole_con - evaluate model constraint over entire domain. -- -- This routine evaluates all members of specified model constraint over -- entire domain. */ static int whole_con_func(MPL *mpl, void *info) { /* this is auxiliary routine to work within domain scope */ CONSTRAINT *con = (CONSTRAINT *)info; TUPLE *tuple = get_domain_tuple(mpl, con->domain); eval_member_con(mpl, con, tuple); delete_tuple(mpl, tuple); return 0; } void eval_whole_con(MPL *mpl, CONSTRAINT *con) { loop_within_domain(mpl, con->domain, con, whole_con_func); return; } /*---------------------------------------------------------------------- -- clean_constraint - clean model constraint. -- -- This routine cleans specified model constraint that assumes deleting -- all stuff dynamically allocated during the generation phase. */ void clean_constraint(MPL *mpl, CONSTRAINT *con) { MEMBER *memb; /* clean subscript domain */ clean_domain(mpl, con->domain); /* clean code for computing main linear form */ clean_code(mpl, con->code); /* clean code for computing lower bound */ clean_code(mpl, con->lbnd); /* clean code for computing upper bound */ if (con->ubnd != con->lbnd) clean_code(mpl, con->ubnd); /* delete content array */ for (memb = con->array->head; memb != NULL; memb = memb->next) { delete_formula(mpl, memb->value.con->form); dmp_free_atom(mpl->elemcons, memb->value.con, sizeof(ELEMCON)); } delete_array(mpl, con->array), con->array = NULL; return; } /**********************************************************************/ /* * * PSEUDO-CODE * * */ /**********************************************************************/ /*---------------------------------------------------------------------- -- eval_numeric - evaluate pseudo-code to determine numeric value. -- -- This routine evaluates specified pseudo-code to determine resultant -- numeric value, which is returned on exit. */ struct iter_num_info { /* working info used by the routine iter_num_func */ CODE *code; /* pseudo-code for iterated operation to be performed */ double value; /* resultant value */ }; static int iter_num_func(MPL *mpl, void *_info) { /* this is auxiliary routine used to perform iterated operation on numeric "integrand" within domain scope */ struct iter_num_info *info = _info; double temp; temp = eval_numeric(mpl, info->code->arg.loop.x); switch (info->code->op) { case O_SUM: /* summation over domain */ info->value = fp_add(mpl, info->value, temp); break; case O_PROD: /* multiplication over domain */ info->value = fp_mul(mpl, info->value, temp); break; case O_MINIMUM: /* minimum over domain */ if (info->value > temp) info->value = temp; break; case O_MAXIMUM: /* maximum over domain */ if (info->value < temp) info->value = temp; break; default: xassert(info != info); } return 0; } double eval_numeric(MPL *mpl, CODE *code) { double value; xassert(code != NULL); xassert(code->type == A_NUMERIC); xassert(code->dim == 0); /* if the operation has a side effect, invalidate and delete the resultant value */ if (code->vflag && code->valid) { code->valid = 0; delete_value(mpl, code->type, &code->value); } /* if resultant value is valid, no evaluation is needed */ if (code->valid) { value = code->value.num; goto done; } /* evaluate pseudo-code recursively */ switch (code->op) { case O_NUMBER: /* take floating-point number */ value = code->arg.num; break; case O_MEMNUM: /* take member of numeric parameter */ { TUPLE *tuple; ARG_LIST *e; tuple = create_tuple(mpl); for (e = code->arg.par.list; e != NULL; e = e->next) tuple = expand_tuple(mpl, tuple, eval_symbolic(mpl, e->x)); value = eval_member_num(mpl, code->arg.par.par, tuple); delete_tuple(mpl, tuple); } break; case O_MEMVAR: /* take computed value of elemental variable */ { TUPLE *tuple; ARG_LIST *e; #if 1 /* 15/V-2010 */ ELEMVAR *var; #endif tuple = create_tuple(mpl); for (e = code->arg.var.list; e != NULL; e = e->next) tuple = expand_tuple(mpl, tuple, eval_symbolic(mpl, e->x)); #if 0 /* 15/V-2010 */ value = eval_member_var(mpl, code->arg.var.var, tuple) ->value; #else var = eval_member_var(mpl, code->arg.var.var, tuple); switch (code->arg.var.suff) { case DOT_LB: if (var->var->lbnd == NULL) value = -DBL_MAX; else value = var->lbnd; break; case DOT_UB: if (var->var->ubnd == NULL) value = +DBL_MAX; else value = var->ubnd; break; case DOT_STATUS: value = var->stat; break; case DOT_VAL: value = var->prim; break; case DOT_DUAL: value = var->dual; break; default: xassert(code != code); } #endif delete_tuple(mpl, tuple); } break; #if 1 /* 15/V-2010 */ case O_MEMCON: /* take computed value of elemental constraint */ { TUPLE *tuple; ARG_LIST *e; ELEMCON *con; tuple = create_tuple(mpl); for (e = code->arg.con.list; e != NULL; e = e->next) tuple = expand_tuple(mpl, tuple, eval_symbolic(mpl, e->x)); con = eval_member_con(mpl, code->arg.con.con, tuple); switch (code->arg.con.suff) { case DOT_LB: if (con->con->lbnd == NULL) value = -DBL_MAX; else value = con->lbnd; break; case DOT_UB: if (con->con->ubnd == NULL) value = +DBL_MAX; else value = con->ubnd; break; case DOT_STATUS: value = con->stat; break; case DOT_VAL: value = con->prim; break; case DOT_DUAL: value = con->dual; break; default: xassert(code != code); } delete_tuple(mpl, tuple); } break; #endif case O_IRAND224: /* pseudo-random in [0, 2^24-1] */ value = fp_irand224(mpl); break; case O_UNIFORM01: /* pseudo-random in [0, 1) */ value = fp_uniform01(mpl); break; case O_NORMAL01: /* gaussian random, mu = 0, sigma = 1 */ value = fp_normal01(mpl); break; case O_GMTIME: /* current calendar time */ value = fn_gmtime(mpl); break; case O_CVTNUM: /* conversion to numeric */ { SYMBOL *sym; sym = eval_symbolic(mpl, code->arg.arg.x); #if 0 /* 23/XI-2008 */ if (sym->str != NULL) error(mpl, "cannot convert %s to floating-point numbe" "r", format_symbol(mpl, sym)); value = sym->num; #else if (sym->str == NULL) value = sym->num; else { if (str2num(sym->str, &value)) error(mpl, "cannot convert %s to floating-point nu" "mber", format_symbol(mpl, sym)); } #endif delete_symbol(mpl, sym); } break; case O_PLUS: /* unary plus */ value = + eval_numeric(mpl, code->arg.arg.x); break; case O_MINUS: /* unary minus */ value = - eval_numeric(mpl, code->arg.arg.x); break; case O_ABS: /* absolute value */ value = fabs(eval_numeric(mpl, code->arg.arg.x)); break; case O_CEIL: /* round upward ("ceiling of x") */ value = ceil(eval_numeric(mpl, code->arg.arg.x)); break; case O_FLOOR: /* round downward ("floor of x") */ value = floor(eval_numeric(mpl, code->arg.arg.x)); break; case O_EXP: /* base-e exponential */ value = fp_exp(mpl, eval_numeric(mpl, code->arg.arg.x)); break; case O_LOG: /* natural logarithm */ value = fp_log(mpl, eval_numeric(mpl, code->arg.arg.x)); break; case O_LOG10: /* common (decimal) logarithm */ value = fp_log10(mpl, eval_numeric(mpl, code->arg.arg.x)); break; case O_SQRT: /* square root */ value = fp_sqrt(mpl, eval_numeric(mpl, code->arg.arg.x)); break; case O_SIN: /* trigonometric sine */ value = fp_sin(mpl, eval_numeric(mpl, code->arg.arg.x)); break; case O_COS: /* trigonometric cosine */ value = fp_cos(mpl, eval_numeric(mpl, code->arg.arg.x)); break; case O_ATAN: /* trigonometric arctangent (one argument) */ value = fp_atan(mpl, eval_numeric(mpl, code->arg.arg.x)); break; case O_ATAN2: /* trigonometric arctangent (two arguments) */ value = fp_atan2(mpl, eval_numeric(mpl, code->arg.arg.x), eval_numeric(mpl, code->arg.arg.y)); break; case O_ROUND: /* round to nearest integer */ value = fp_round(mpl, eval_numeric(mpl, code->arg.arg.x), 0.0); break; case O_ROUND2: /* round to n fractional digits */ value = fp_round(mpl, eval_numeric(mpl, code->arg.arg.x), eval_numeric(mpl, code->arg.arg.y)); break; case O_TRUNC: /* truncate to nearest integer */ value = fp_trunc(mpl, eval_numeric(mpl, code->arg.arg.x), 0.0); break; case O_TRUNC2: /* truncate to n fractional digits */ value = fp_trunc(mpl, eval_numeric(mpl, code->arg.arg.x), eval_numeric(mpl, code->arg.arg.y)); break; case O_ADD: /* addition */ value = fp_add(mpl, eval_numeric(mpl, code->arg.arg.x), eval_numeric(mpl, code->arg.arg.y)); break; case O_SUB: /* subtraction */ value = fp_sub(mpl, eval_numeric(mpl, code->arg.arg.x), eval_numeric(mpl, code->arg.arg.y)); break; case O_LESS: /* non-negative subtraction */ value = fp_less(mpl, eval_numeric(mpl, code->arg.arg.x), eval_numeric(mpl, code->arg.arg.y)); break; case O_MUL: /* multiplication */ value = fp_mul(mpl, eval_numeric(mpl, code->arg.arg.x), eval_numeric(mpl, code->arg.arg.y)); break; case O_DIV: /* division */ value = fp_div(mpl, eval_numeric(mpl, code->arg.arg.x), eval_numeric(mpl, code->arg.arg.y)); break; case O_IDIV: /* quotient of exact division */ value = fp_idiv(mpl, eval_numeric(mpl, code->arg.arg.x), eval_numeric(mpl, code->arg.arg.y)); break; case O_MOD: /* remainder of exact division */ value = fp_mod(mpl, eval_numeric(mpl, code->arg.arg.x), eval_numeric(mpl, code->arg.arg.y)); break; case O_POWER: /* exponentiation (raise to power) */ value = fp_power(mpl, eval_numeric(mpl, code->arg.arg.x), eval_numeric(mpl, code->arg.arg.y)); break; case O_UNIFORM: /* pseudo-random in [a, b) */ value = fp_uniform(mpl, eval_numeric(mpl, code->arg.arg.x), eval_numeric(mpl, code->arg.arg.y)); break; case O_NORMAL: /* gaussian random, given mu and sigma */ value = fp_normal(mpl, eval_numeric(mpl, code->arg.arg.x), eval_numeric(mpl, code->arg.arg.y)); break; case O_CARD: { ELEMSET *set; set = eval_elemset(mpl, code->arg.arg.x); value = set->size; delete_array(mpl, set); } break; case O_LENGTH: { SYMBOL *sym; char str[MAX_LENGTH+1]; sym = eval_symbolic(mpl, code->arg.arg.x); if (sym->str == NULL) sprintf(str, "%.*g", DBL_DIG, sym->num); else fetch_string(mpl, sym->str, str); delete_symbol(mpl, sym); value = strlen(str); } break; case O_STR2TIME: { SYMBOL *sym; char str[MAX_LENGTH+1], fmt[MAX_LENGTH+1]; sym = eval_symbolic(mpl, code->arg.arg.x); if (sym->str == NULL) sprintf(str, "%.*g", DBL_DIG, sym->num); else fetch_string(mpl, sym->str, str); delete_symbol(mpl, sym); sym = eval_symbolic(mpl, code->arg.arg.y); if (sym->str == NULL) sprintf(fmt, "%.*g", DBL_DIG, sym->num); else fetch_string(mpl, sym->str, fmt); delete_symbol(mpl, sym); value = fn_str2time(mpl, str, fmt); } break; case O_FORK: /* if-then-else */ if (eval_logical(mpl, code->arg.arg.x)) value = eval_numeric(mpl, code->arg.arg.y); else if (code->arg.arg.z == NULL) value = 0.0; else value = eval_numeric(mpl, code->arg.arg.z); break; case O_MIN: /* minimal value (n-ary) */ { ARG_LIST *e; double temp; value = +DBL_MAX; for (e = code->arg.list; e != NULL; e = e->next) { temp = eval_numeric(mpl, e->x); if (value > temp) value = temp; } } break; case O_MAX: /* maximal value (n-ary) */ { ARG_LIST *e; double temp; value = -DBL_MAX; for (e = code->arg.list; e != NULL; e = e->next) { temp = eval_numeric(mpl, e->x); if (value < temp) value = temp; } } break; case O_SUM: /* summation over domain */ { struct iter_num_info _info, *info = &_info; info->code = code; info->value = 0.0; loop_within_domain(mpl, code->arg.loop.domain, info, iter_num_func); value = info->value; } break; case O_PROD: /* multiplication over domain */ { struct iter_num_info _info, *info = &_info; info->code = code; info->value = 1.0; loop_within_domain(mpl, code->arg.loop.domain, info, iter_num_func); value = info->value; } break; case O_MINIMUM: /* minimum over domain */ { struct iter_num_info _info, *info = &_info; info->code = code; info->value = +DBL_MAX; loop_within_domain(mpl, code->arg.loop.domain, info, iter_num_func); if (info->value == +DBL_MAX) error(mpl, "min{} over empty set; result undefined"); value = info->value; } break; case O_MAXIMUM: /* maximum over domain */ { struct iter_num_info _info, *info = &_info; info->code = code; info->value = -DBL_MAX; loop_within_domain(mpl, code->arg.loop.domain, info, iter_num_func); if (info->value == -DBL_MAX) error(mpl, "max{} over empty set; result undefined"); value = info->value; } break; default: xassert(code != code); } /* save resultant value */ xassert(!code->valid); code->valid = 1; code->value.num = value; done: return value; } /*---------------------------------------------------------------------- -- eval_symbolic - evaluate pseudo-code to determine symbolic value. -- -- This routine evaluates specified pseudo-code to determine resultant -- symbolic value, which is returned on exit. */ SYMBOL *eval_symbolic(MPL *mpl, CODE *code) { SYMBOL *value; xassert(code != NULL); xassert(code->type == A_SYMBOLIC); xassert(code->dim == 0); /* if the operation has a side effect, invalidate and delete the resultant value */ if (code->vflag && code->valid) { code->valid = 0; delete_value(mpl, code->type, &code->value); } /* if resultant value is valid, no evaluation is needed */ if (code->valid) { value = copy_symbol(mpl, code->value.sym); goto done; } /* evaluate pseudo-code recursively */ switch (code->op) { case O_STRING: /* take character string */ value = create_symbol_str(mpl, create_string(mpl, code->arg.str)); break; case O_INDEX: /* take dummy index */ xassert(code->arg.index.slot->value != NULL); value = copy_symbol(mpl, code->arg.index.slot->value); break; case O_MEMSYM: /* take member of symbolic parameter */ { TUPLE *tuple; ARG_LIST *e; tuple = create_tuple(mpl); for (e = code->arg.par.list; e != NULL; e = e->next) tuple = expand_tuple(mpl, tuple, eval_symbolic(mpl, e->x)); value = eval_member_sym(mpl, code->arg.par.par, tuple); delete_tuple(mpl, tuple); } break; case O_CVTSYM: /* conversion to symbolic */ value = create_symbol_num(mpl, eval_numeric(mpl, code->arg.arg.x)); break; case O_CONCAT: /* concatenation */ value = concat_symbols(mpl, eval_symbolic(mpl, code->arg.arg.x), eval_symbolic(mpl, code->arg.arg.y)); break; case O_FORK: /* if-then-else */ if (eval_logical(mpl, code->arg.arg.x)) value = eval_symbolic(mpl, code->arg.arg.y); else if (code->arg.arg.z == NULL) value = create_symbol_num(mpl, 0.0); else value = eval_symbolic(mpl, code->arg.arg.z); break; case O_SUBSTR: case O_SUBSTR3: { double pos, len; char str[MAX_LENGTH+1]; value = eval_symbolic(mpl, code->arg.arg.x); if (value->str == NULL) sprintf(str, "%.*g", DBL_DIG, value->num); else fetch_string(mpl, value->str, str); delete_symbol(mpl, value); if (code->op == O_SUBSTR) { pos = eval_numeric(mpl, code->arg.arg.y); if (pos != floor(pos)) error(mpl, "substr('...', %.*g); non-integer secon" "d argument", DBL_DIG, pos); if (pos < 1 || pos > strlen(str) + 1) error(mpl, "substr('...', %.*g); substring out of " "range", DBL_DIG, pos); } else { pos = eval_numeric(mpl, code->arg.arg.y); len = eval_numeric(mpl, code->arg.arg.z); if (pos != floor(pos) || len != floor(len)) error(mpl, "substr('...', %.*g, %.*g); non-integer" " second and/or third argument", DBL_DIG, pos, DBL_DIG, len); if (pos < 1 || len < 0 || pos + len > strlen(str) + 1) error(mpl, "substr('...', %.*g, %.*g); substring o" "ut of range", DBL_DIG, pos, DBL_DIG, len); str[(int)pos + (int)len - 1] = '\0'; } value = create_symbol_str(mpl, create_string(mpl, str + (int)pos - 1)); } break; case O_TIME2STR: { double num; SYMBOL *sym; char str[MAX_LENGTH+1], fmt[MAX_LENGTH+1]; num = eval_numeric(mpl, code->arg.arg.x); sym = eval_symbolic(mpl, code->arg.arg.y); if (sym->str == NULL) sprintf(fmt, "%.*g", DBL_DIG, sym->num); else fetch_string(mpl, sym->str, fmt); delete_symbol(mpl, sym); fn_time2str(mpl, str, num, fmt); value = create_symbol_str(mpl, create_string(mpl, str)); } break; default: xassert(code != code); } /* save resultant value */ xassert(!code->valid); code->valid = 1; code->value.sym = copy_symbol(mpl, value); done: return value; } /*---------------------------------------------------------------------- -- eval_logical - evaluate pseudo-code to determine logical value. -- -- This routine evaluates specified pseudo-code to determine resultant -- logical value, which is returned on exit. */ struct iter_log_info { /* working info used by the routine iter_log_func */ CODE *code; /* pseudo-code for iterated operation to be performed */ int value; /* resultant value */ }; static int iter_log_func(MPL *mpl, void *_info) { /* this is auxiliary routine used to perform iterated operation on logical "integrand" within domain scope */ struct iter_log_info *info = _info; int ret = 0; switch (info->code->op) { case O_FORALL: /* conjunction over domain */ info->value &= eval_logical(mpl, info->code->arg.loop.x); if (!info->value) ret = 1; break; case O_EXISTS: /* disjunction over domain */ info->value |= eval_logical(mpl, info->code->arg.loop.x); if (info->value) ret = 1; break; default: xassert(info != info); } return ret; } int eval_logical(MPL *mpl, CODE *code) { int value; xassert(code->type == A_LOGICAL); xassert(code->dim == 0); /* if the operation has a side effect, invalidate and delete the resultant value */ if (code->vflag && code->valid) { code->valid = 0; delete_value(mpl, code->type, &code->value); } /* if resultant value is valid, no evaluation is needed */ if (code->valid) { value = code->value.bit; goto done; } /* evaluate pseudo-code recursively */ switch (code->op) { case O_CVTLOG: /* conversion to logical */ value = (eval_numeric(mpl, code->arg.arg.x) != 0.0); break; case O_NOT: /* negation (logical "not") */ value = !eval_logical(mpl, code->arg.arg.x); break; case O_LT: /* comparison on 'less than' */ #if 0 /* 02/VIII-2008 */ value = (eval_numeric(mpl, code->arg.arg.x) < eval_numeric(mpl, code->arg.arg.y)); #else xassert(code->arg.arg.x != NULL); if (code->arg.arg.x->type == A_NUMERIC) value = (eval_numeric(mpl, code->arg.arg.x) < eval_numeric(mpl, code->arg.arg.y)); else { SYMBOL *sym1 = eval_symbolic(mpl, code->arg.arg.x); SYMBOL *sym2 = eval_symbolic(mpl, code->arg.arg.y); value = (compare_symbols(mpl, sym1, sym2) < 0); delete_symbol(mpl, sym1); delete_symbol(mpl, sym2); } #endif break; case O_LE: /* comparison on 'not greater than' */ #if 0 /* 02/VIII-2008 */ value = (eval_numeric(mpl, code->arg.arg.x) <= eval_numeric(mpl, code->arg.arg.y)); #else xassert(code->arg.arg.x != NULL); if (code->arg.arg.x->type == A_NUMERIC) value = (eval_numeric(mpl, code->arg.arg.x) <= eval_numeric(mpl, code->arg.arg.y)); else { SYMBOL *sym1 = eval_symbolic(mpl, code->arg.arg.x); SYMBOL *sym2 = eval_symbolic(mpl, code->arg.arg.y); value = (compare_symbols(mpl, sym1, sym2) <= 0); delete_symbol(mpl, sym1); delete_symbol(mpl, sym2); } #endif break; case O_EQ: /* comparison on 'equal to' */ xassert(code->arg.arg.x != NULL); if (code->arg.arg.x->type == A_NUMERIC) value = (eval_numeric(mpl, code->arg.arg.x) == eval_numeric(mpl, code->arg.arg.y)); else { SYMBOL *sym1 = eval_symbolic(mpl, code->arg.arg.x); SYMBOL *sym2 = eval_symbolic(mpl, code->arg.arg.y); value = (compare_symbols(mpl, sym1, sym2) == 0); delete_symbol(mpl, sym1); delete_symbol(mpl, sym2); } break; case O_GE: /* comparison on 'not less than' */ #if 0 /* 02/VIII-2008 */ value = (eval_numeric(mpl, code->arg.arg.x) >= eval_numeric(mpl, code->arg.arg.y)); #else xassert(code->arg.arg.x != NULL); if (code->arg.arg.x->type == A_NUMERIC) value = (eval_numeric(mpl, code->arg.arg.x) >= eval_numeric(mpl, code->arg.arg.y)); else { SYMBOL *sym1 = eval_symbolic(mpl, code->arg.arg.x); SYMBOL *sym2 = eval_symbolic(mpl, code->arg.arg.y); value = (compare_symbols(mpl, sym1, sym2) >= 0); delete_symbol(mpl, sym1); delete_symbol(mpl, sym2); } #endif break; case O_GT: /* comparison on 'greater than' */ #if 0 /* 02/VIII-2008 */ value = (eval_numeric(mpl, code->arg.arg.x) > eval_numeric(mpl, code->arg.arg.y)); #else xassert(code->arg.arg.x != NULL); if (code->arg.arg.x->type == A_NUMERIC) value = (eval_numeric(mpl, code->arg.arg.x) > eval_numeric(mpl, code->arg.arg.y)); else { SYMBOL *sym1 = eval_symbolic(mpl, code->arg.arg.x); SYMBOL *sym2 = eval_symbolic(mpl, code->arg.arg.y); value = (compare_symbols(mpl, sym1, sym2) > 0); delete_symbol(mpl, sym1); delete_symbol(mpl, sym2); } #endif break; case O_NE: /* comparison on 'not equal to' */ xassert(code->arg.arg.x != NULL); if (code->arg.arg.x->type == A_NUMERIC) value = (eval_numeric(mpl, code->arg.arg.x) != eval_numeric(mpl, code->arg.arg.y)); else { SYMBOL *sym1 = eval_symbolic(mpl, code->arg.arg.x); SYMBOL *sym2 = eval_symbolic(mpl, code->arg.arg.y); value = (compare_symbols(mpl, sym1, sym2) != 0); delete_symbol(mpl, sym1); delete_symbol(mpl, sym2); } break; case O_AND: /* conjunction (logical "and") */ value = eval_logical(mpl, code->arg.arg.x) && eval_logical(mpl, code->arg.arg.y); break; case O_OR: /* disjunction (logical "or") */ value = eval_logical(mpl, code->arg.arg.x) || eval_logical(mpl, code->arg.arg.y); break; case O_IN: /* test on 'x in Y' */ { TUPLE *tuple; tuple = eval_tuple(mpl, code->arg.arg.x); value = is_member(mpl, code->arg.arg.y, tuple); delete_tuple(mpl, tuple); } break; case O_NOTIN: /* test on 'x not in Y' */ { TUPLE *tuple; tuple = eval_tuple(mpl, code->arg.arg.x); value = !is_member(mpl, code->arg.arg.y, tuple); delete_tuple(mpl, tuple); } break; case O_WITHIN: /* test on 'X within Y' */ { ELEMSET *set; MEMBER *memb; set = eval_elemset(mpl, code->arg.arg.x); value = 1; for (memb = set->head; memb != NULL; memb = memb->next) { if (!is_member(mpl, code->arg.arg.y, memb->tuple)) { value = 0; break; } } delete_elemset(mpl, set); } break; case O_NOTWITHIN: /* test on 'X not within Y' */ { ELEMSET *set; MEMBER *memb; set = eval_elemset(mpl, code->arg.arg.x); value = 1; for (memb = set->head; memb != NULL; memb = memb->next) { if (is_member(mpl, code->arg.arg.y, memb->tuple)) { value = 0; break; } } delete_elemset(mpl, set); } break; case O_FORALL: /* conjunction (A-quantification) */ { struct iter_log_info _info, *info = &_info; info->code = code; info->value = 1; loop_within_domain(mpl, code->arg.loop.domain, info, iter_log_func); value = info->value; } break; case O_EXISTS: /* disjunction (E-quantification) */ { struct iter_log_info _info, *info = &_info; info->code = code; info->value = 0; loop_within_domain(mpl, code->arg.loop.domain, info, iter_log_func); value = info->value; } break; default: xassert(code != code); } /* save resultant value */ xassert(!code->valid); code->valid = 1; code->value.bit = value; done: return value; } /*---------------------------------------------------------------------- -- eval_tuple - evaluate pseudo-code to construct n-tuple. -- -- This routine evaluates specified pseudo-code to construct resultant -- n-tuple, which is returned on exit. */ TUPLE *eval_tuple(MPL *mpl, CODE *code) { TUPLE *value; xassert(code != NULL); xassert(code->type == A_TUPLE); xassert(code->dim > 0); /* if the operation has a side effect, invalidate and delete the resultant value */ if (code->vflag && code->valid) { code->valid = 0; delete_value(mpl, code->type, &code->value); } /* if resultant value is valid, no evaluation is needed */ if (code->valid) { value = copy_tuple(mpl, code->value.tuple); goto done; } /* evaluate pseudo-code recursively */ switch (code->op) { case O_TUPLE: /* make n-tuple */ { ARG_LIST *e; value = create_tuple(mpl); for (e = code->arg.list; e != NULL; e = e->next) value = expand_tuple(mpl, value, eval_symbolic(mpl, e->x)); } break; case O_CVTTUP: /* convert to 1-tuple */ value = expand_tuple(mpl, create_tuple(mpl), eval_symbolic(mpl, code->arg.arg.x)); break; default: xassert(code != code); } /* save resultant value */ xassert(!code->valid); code->valid = 1; code->value.tuple = copy_tuple(mpl, value); done: return value; } /*---------------------------------------------------------------------- -- eval_elemset - evaluate pseudo-code to construct elemental set. -- -- This routine evaluates specified pseudo-code to construct resultant -- elemental set, which is returned on exit. */ struct iter_set_info { /* working info used by the routine iter_set_func */ CODE *code; /* pseudo-code for iterated operation to be performed */ ELEMSET *value; /* resultant value */ }; static int iter_set_func(MPL *mpl, void *_info) { /* this is auxiliary routine used to perform iterated operation on n-tuple "integrand" within domain scope */ struct iter_set_info *info = _info; TUPLE *tuple; switch (info->code->op) { case O_SETOF: /* compute next n-tuple and add it to the set; in this case duplicate n-tuples are silently ignored */ tuple = eval_tuple(mpl, info->code->arg.loop.x); if (find_tuple(mpl, info->value, tuple) == NULL) add_tuple(mpl, info->value, tuple); else delete_tuple(mpl, tuple); break; case O_BUILD: /* construct next n-tuple using current values assigned to *free* dummy indices as its components and add it to the set; in this case duplicate n-tuples cannot appear */ add_tuple(mpl, info->value, get_domain_tuple(mpl, info->code->arg.loop.domain)); break; default: xassert(info != info); } return 0; } ELEMSET *eval_elemset(MPL *mpl, CODE *code) { ELEMSET *value; xassert(code != NULL); xassert(code->type == A_ELEMSET); xassert(code->dim > 0); /* if the operation has a side effect, invalidate and delete the resultant value */ if (code->vflag && code->valid) { code->valid = 0; delete_value(mpl, code->type, &code->value); } /* if resultant value is valid, no evaluation is needed */ if (code->valid) { value = copy_elemset(mpl, code->value.set); goto done; } /* evaluate pseudo-code recursively */ switch (code->op) { case O_MEMSET: /* take member of set */ { TUPLE *tuple; ARG_LIST *e; tuple = create_tuple(mpl); for (e = code->arg.set.list; e != NULL; e = e->next) tuple = expand_tuple(mpl, tuple, eval_symbolic(mpl, e->x)); value = copy_elemset(mpl, eval_member_set(mpl, code->arg.set.set, tuple)); delete_tuple(mpl, tuple); } break; case O_MAKE: /* make elemental set of n-tuples */ { ARG_LIST *e; value = create_elemset(mpl, code->dim); for (e = code->arg.list; e != NULL; e = e->next) check_then_add(mpl, value, eval_tuple(mpl, e->x)); } break; case O_UNION: /* union of two elemental sets */ value = set_union(mpl, eval_elemset(mpl, code->arg.arg.x), eval_elemset(mpl, code->arg.arg.y)); break; case O_DIFF: /* difference between two elemental sets */ value = set_diff(mpl, eval_elemset(mpl, code->arg.arg.x), eval_elemset(mpl, code->arg.arg.y)); break; case O_SYMDIFF: /* symmetric difference between two elemental sets */ value = set_symdiff(mpl, eval_elemset(mpl, code->arg.arg.x), eval_elemset(mpl, code->arg.arg.y)); break; case O_INTER: /* intersection of two elemental sets */ value = set_inter(mpl, eval_elemset(mpl, code->arg.arg.x), eval_elemset(mpl, code->arg.arg.y)); break; case O_CROSS: /* cross (Cartesian) product of two elemental sets */ value = set_cross(mpl, eval_elemset(mpl, code->arg.arg.x), eval_elemset(mpl, code->arg.arg.y)); break; case O_DOTS: /* build "arithmetic" elemental set */ value = create_arelset(mpl, eval_numeric(mpl, code->arg.arg.x), eval_numeric(mpl, code->arg.arg.y), code->arg.arg.z == NULL ? 1.0 : eval_numeric(mpl, code->arg.arg.z)); break; case O_FORK: /* if-then-else */ if (eval_logical(mpl, code->arg.arg.x)) value = eval_elemset(mpl, code->arg.arg.y); else value = eval_elemset(mpl, code->arg.arg.z); break; case O_SETOF: /* compute elemental set */ { struct iter_set_info _info, *info = &_info; info->code = code; info->value = create_elemset(mpl, code->dim); loop_within_domain(mpl, code->arg.loop.domain, info, iter_set_func); value = info->value; } break; case O_BUILD: /* build elemental set identical to domain set */ { struct iter_set_info _info, *info = &_info; info->code = code; info->value = create_elemset(mpl, code->dim); loop_within_domain(mpl, code->arg.loop.domain, info, iter_set_func); value = info->value; } break; default: xassert(code != code); } /* save resultant value */ xassert(!code->valid); code->valid = 1; code->value.set = copy_elemset(mpl, value); done: return value; } /*---------------------------------------------------------------------- -- is_member - check if n-tuple is in set specified by pseudo-code. -- -- This routine checks if given n-tuple is a member of elemental set -- specified in the form of pseudo-code (i.e. by expression). -- -- The n-tuple may have more components that dimension of the elemental -- set, in which case the extra components are ignored. */ static void null_func(MPL *mpl, void *info) { /* this is dummy routine used to enter the domain scope */ xassert(mpl == mpl); xassert(info == NULL); return; } int is_member(MPL *mpl, CODE *code, TUPLE *tuple) { int value; xassert(code != NULL); xassert(code->type == A_ELEMSET); xassert(code->dim > 0); xassert(tuple != NULL); switch (code->op) { case O_MEMSET: /* check if given n-tuple is member of elemental set, which is assigned to member of model set */ { ARG_LIST *e; TUPLE *temp; ELEMSET *set; /* evaluate reference to elemental set */ temp = create_tuple(mpl); for (e = code->arg.set.list; e != NULL; e = e->next) temp = expand_tuple(mpl, temp, eval_symbolic(mpl, e->x)); set = eval_member_set(mpl, code->arg.set.set, temp); delete_tuple(mpl, temp); /* check if the n-tuple is contained in the set array */ temp = build_subtuple(mpl, tuple, set->dim); value = (find_tuple(mpl, set, temp) != NULL); delete_tuple(mpl, temp); } break; case O_MAKE: /* check if given n-tuple is member of literal set */ { ARG_LIST *e; TUPLE *temp, *that; value = 0; temp = build_subtuple(mpl, tuple, code->dim); for (e = code->arg.list; e != NULL; e = e->next) { that = eval_tuple(mpl, e->x); value = (compare_tuples(mpl, temp, that) == 0); delete_tuple(mpl, that); if (value) break; } delete_tuple(mpl, temp); } break; case O_UNION: value = is_member(mpl, code->arg.arg.x, tuple) || is_member(mpl, code->arg.arg.y, tuple); break; case O_DIFF: value = is_member(mpl, code->arg.arg.x, tuple) && !is_member(mpl, code->arg.arg.y, tuple); break; case O_SYMDIFF: { int in1 = is_member(mpl, code->arg.arg.x, tuple); int in2 = is_member(mpl, code->arg.arg.y, tuple); value = (in1 && !in2) || (!in1 && in2); } break; case O_INTER: value = is_member(mpl, code->arg.arg.x, tuple) && is_member(mpl, code->arg.arg.y, tuple); break; case O_CROSS: { int j; value = is_member(mpl, code->arg.arg.x, tuple); if (value) { for (j = 1; j <= code->arg.arg.x->dim; j++) { xassert(tuple != NULL); tuple = tuple->next; } value = is_member(mpl, code->arg.arg.y, tuple); } } break; case O_DOTS: /* check if given 1-tuple is member of "arithmetic" set */ { int j; double x, t0, tf, dt; xassert(code->dim == 1); /* compute "parameters" of the "arithmetic" set */ t0 = eval_numeric(mpl, code->arg.arg.x); tf = eval_numeric(mpl, code->arg.arg.y); if (code->arg.arg.z == NULL) dt = 1.0; else dt = eval_numeric(mpl, code->arg.arg.z); /* make sure the parameters are correct */ arelset_size(mpl, t0, tf, dt); /* if component of 1-tuple is symbolic, not numeric, the 1-tuple cannot be member of "arithmetic" set */ xassert(tuple->sym != NULL); if (tuple->sym->str != NULL) { value = 0; break; } /* determine numeric value of the component */ x = tuple->sym->num; /* if the component value is out of the set range, the 1-tuple is not in the set */ if (dt > 0.0 && !(t0 <= x && x <= tf) || dt < 0.0 && !(tf <= x && x <= t0)) { value = 0; break; } /* estimate ordinal number of the 1-tuple in the set */ j = (int)(((x - t0) / dt) + 0.5) + 1; /* perform the main check */ value = (arelset_member(mpl, t0, tf, dt, j) == x); } break; case O_FORK: /* check if given n-tuple is member of conditional set */ if (eval_logical(mpl, code->arg.arg.x)) value = is_member(mpl, code->arg.arg.y, tuple); else value = is_member(mpl, code->arg.arg.z, tuple); break; case O_SETOF: /* check if given n-tuple is member of computed set */ /* it is not clear how to efficiently perform the check not computing the entire elemental set :+( */ error(mpl, "implementation restriction; in/within setof{} n" "ot allowed"); break; case O_BUILD: /* check if given n-tuple is member of domain set */ { TUPLE *temp; temp = build_subtuple(mpl, tuple, code->dim); /* try to enter the domain scope; if it is successful, the n-tuple is in the domain set */ value = (eval_within_domain(mpl, code->arg.loop.domain, temp, NULL, null_func) == 0); delete_tuple(mpl, temp); } break; default: xassert(code != code); } return value; } /*---------------------------------------------------------------------- -- eval_formula - evaluate pseudo-code to construct linear form. -- -- This routine evaluates specified pseudo-code to construct resultant -- linear form, which is returned on exit. */ struct iter_form_info { /* working info used by the routine iter_form_func */ CODE *code; /* pseudo-code for iterated operation to be performed */ FORMULA *value; /* resultant value */ FORMULA *tail; /* pointer to the last term */ }; static int iter_form_func(MPL *mpl, void *_info) { /* this is auxiliary routine used to perform iterated operation on linear form "integrand" within domain scope */ struct iter_form_info *info = _info; switch (info->code->op) { case O_SUM: /* summation over domain */ #if 0 info->value = linear_comb(mpl, +1.0, info->value, +1.0, eval_formula(mpl, info->code->arg.loop.x)); #else /* the routine linear_comb needs to look through all terms of both linear forms to reduce identical terms, so using it here is not a good idea (for example, evaluation of sum{i in 1..n} x[i] required quadratic time); the better idea is to gather all terms of the integrand in one list and reduce identical terms only once after all terms of the resultant linear form have been evaluated */ { FORMULA *form, *term; form = eval_formula(mpl, info->code->arg.loop.x); if (info->value == NULL) { xassert(info->tail == NULL); info->value = form; } else { xassert(info->tail != NULL); info->tail->next = form; } for (term = form; term != NULL; term = term->next) info->tail = term; } #endif break; default: xassert(info != info); } return 0; } FORMULA *eval_formula(MPL *mpl, CODE *code) { FORMULA *value; xassert(code != NULL); xassert(code->type == A_FORMULA); xassert(code->dim == 0); /* if the operation has a side effect, invalidate and delete the resultant value */ if (code->vflag && code->valid) { code->valid = 0; delete_value(mpl, code->type, &code->value); } /* if resultant value is valid, no evaluation is needed */ if (code->valid) { value = copy_formula(mpl, code->value.form); goto done; } /* evaluate pseudo-code recursively */ switch (code->op) { case O_MEMVAR: /* take member of variable */ { TUPLE *tuple; ARG_LIST *e; tuple = create_tuple(mpl); for (e = code->arg.var.list; e != NULL; e = e->next) tuple = expand_tuple(mpl, tuple, eval_symbolic(mpl, e->x)); #if 1 /* 15/V-2010 */ xassert(code->arg.var.suff == DOT_NONE); #endif value = single_variable(mpl, eval_member_var(mpl, code->arg.var.var, tuple)); delete_tuple(mpl, tuple); } break; case O_CVTLFM: /* convert to linear form */ value = constant_term(mpl, eval_numeric(mpl, code->arg.arg.x)); break; case O_PLUS: /* unary plus */ value = linear_comb(mpl, 0.0, constant_term(mpl, 0.0), +1.0, eval_formula(mpl, code->arg.arg.x)); break; case O_MINUS: /* unary minus */ value = linear_comb(mpl, 0.0, constant_term(mpl, 0.0), -1.0, eval_formula(mpl, code->arg.arg.x)); break; case O_ADD: /* addition */ value = linear_comb(mpl, +1.0, eval_formula(mpl, code->arg.arg.x), +1.0, eval_formula(mpl, code->arg.arg.y)); break; case O_SUB: /* subtraction */ value = linear_comb(mpl, +1.0, eval_formula(mpl, code->arg.arg.x), -1.0, eval_formula(mpl, code->arg.arg.y)); break; case O_MUL: /* multiplication */ xassert(code->arg.arg.x != NULL); xassert(code->arg.arg.y != NULL); if (code->arg.arg.x->type == A_NUMERIC) { xassert(code->arg.arg.y->type == A_FORMULA); value = linear_comb(mpl, eval_numeric(mpl, code->arg.arg.x), eval_formula(mpl, code->arg.arg.y), 0.0, constant_term(mpl, 0.0)); } else { xassert(code->arg.arg.x->type == A_FORMULA); xassert(code->arg.arg.y->type == A_NUMERIC); value = linear_comb(mpl, eval_numeric(mpl, code->arg.arg.y), eval_formula(mpl, code->arg.arg.x), 0.0, constant_term(mpl, 0.0)); } break; case O_DIV: /* division */ value = linear_comb(mpl, fp_div(mpl, 1.0, eval_numeric(mpl, code->arg.arg.y)), eval_formula(mpl, code->arg.arg.x), 0.0, constant_term(mpl, 0.0)); break; case O_FORK: /* if-then-else */ if (eval_logical(mpl, code->arg.arg.x)) value = eval_formula(mpl, code->arg.arg.y); else if (code->arg.arg.z == NULL) value = constant_term(mpl, 0.0); else value = eval_formula(mpl, code->arg.arg.z); break; case O_SUM: /* summation over domain */ { struct iter_form_info _info, *info = &_info; info->code = code; info->value = constant_term(mpl, 0.0); info->tail = NULL; loop_within_domain(mpl, code->arg.loop.domain, info, iter_form_func); value = reduce_terms(mpl, info->value); } break; default: xassert(code != code); } /* save resultant value */ xassert(!code->valid); code->valid = 1; code->value.form = copy_formula(mpl, value); done: return value; } /*---------------------------------------------------------------------- -- clean_code - clean pseudo-code. -- -- This routine recursively cleans specified pseudo-code that assumes -- deleting all temporary resultant values. */ void clean_code(MPL *mpl, CODE *code) { ARG_LIST *e; /* if no pseudo-code is specified, do nothing */ if (code == NULL) goto done; /* if resultant value is valid (exists), delete it */ if (code->valid) { code->valid = 0; delete_value(mpl, code->type, &code->value); } /* recursively clean pseudo-code for operands */ switch (code->op) { case O_NUMBER: case O_STRING: case O_INDEX: break; case O_MEMNUM: case O_MEMSYM: for (e = code->arg.par.list; e != NULL; e = e->next) clean_code(mpl, e->x); break; case O_MEMSET: for (e = code->arg.set.list; e != NULL; e = e->next) clean_code(mpl, e->x); break; case O_MEMVAR: for (e = code->arg.var.list; e != NULL; e = e->next) clean_code(mpl, e->x); break; #if 1 /* 15/V-2010 */ case O_MEMCON: for (e = code->arg.con.list; e != NULL; e = e->next) clean_code(mpl, e->x); break; #endif case O_TUPLE: case O_MAKE: for (e = code->arg.list; e != NULL; e = e->next) clean_code(mpl, e->x); break; case O_SLICE: xassert(code != code); case O_IRAND224: case O_UNIFORM01: case O_NORMAL01: case O_GMTIME: break; case O_CVTNUM: case O_CVTSYM: case O_CVTLOG: case O_CVTTUP: case O_CVTLFM: case O_PLUS: case O_MINUS: case O_NOT: case O_ABS: case O_CEIL: case O_FLOOR: case O_EXP: case O_LOG: case O_LOG10: case O_SQRT: case O_SIN: case O_COS: case O_ATAN: case O_ROUND: case O_TRUNC: case O_CARD: case O_LENGTH: /* unary operation */ clean_code(mpl, code->arg.arg.x); break; case O_ADD: case O_SUB: case O_LESS: case O_MUL: case O_DIV: case O_IDIV: case O_MOD: case O_POWER: case O_ATAN2: case O_ROUND2: case O_TRUNC2: case O_UNIFORM: case O_NORMAL: case O_CONCAT: case O_LT: case O_LE: case O_EQ: case O_GE: case O_GT: case O_NE: case O_AND: case O_OR: case O_UNION: case O_DIFF: case O_SYMDIFF: case O_INTER: case O_CROSS: case O_IN: case O_NOTIN: case O_WITHIN: case O_NOTWITHIN: case O_SUBSTR: case O_STR2TIME: case O_TIME2STR: /* binary operation */ clean_code(mpl, code->arg.arg.x); clean_code(mpl, code->arg.arg.y); break; case O_DOTS: case O_FORK: case O_SUBSTR3: /* ternary operation */ clean_code(mpl, code->arg.arg.x); clean_code(mpl, code->arg.arg.y); clean_code(mpl, code->arg.arg.z); break; case O_MIN: case O_MAX: /* n-ary operation */ for (e = code->arg.list; e != NULL; e = e->next) clean_code(mpl, e->x); break; case O_SUM: case O_PROD: case O_MINIMUM: case O_MAXIMUM: case O_FORALL: case O_EXISTS: case O_SETOF: case O_BUILD: /* iterated operation */ clean_domain(mpl, code->arg.loop.domain); clean_code(mpl, code->arg.loop.x); break; default: xassert(code->op != code->op); } done: return; } #if 1 /* 11/II-2008 */ /**********************************************************************/ /* * * DATA TABLES * * */ /**********************************************************************/ int mpl_tab_num_args(TABDCA *dca) { /* returns the number of arguments */ return dca->na; } const char *mpl_tab_get_arg(TABDCA *dca, int k) { /* returns pointer to k-th argument */ xassert(1 <= k && k <= dca->na); return dca->arg[k]; } int mpl_tab_num_flds(TABDCA *dca) { /* returns the number of fields */ return dca->nf; } const char *mpl_tab_get_name(TABDCA *dca, int k) { /* returns pointer to name of k-th field */ xassert(1 <= k && k <= dca->nf); return dca->name[k]; } int mpl_tab_get_type(TABDCA *dca, int k) { /* returns type of k-th field */ xassert(1 <= k && k <= dca->nf); return dca->type[k]; } double mpl_tab_get_num(TABDCA *dca, int k) { /* returns numeric value of k-th field */ xassert(1 <= k && k <= dca->nf); xassert(dca->type[k] == 'N'); return dca->num[k]; } const char *mpl_tab_get_str(TABDCA *dca, int k) { /* returns pointer to string value of k-th field */ xassert(1 <= k && k <= dca->nf); xassert(dca->type[k] == 'S'); xassert(dca->str[k] != NULL); return dca->str[k]; } void mpl_tab_set_num(TABDCA *dca, int k, double num) { /* assign numeric value to k-th field */ xassert(1 <= k && k <= dca->nf); xassert(dca->type[k] == '?'); dca->type[k] = 'N'; dca->num[k] = num; return; } void mpl_tab_set_str(TABDCA *dca, int k, const char *str) { /* assign string value to k-th field */ xassert(1 <= k && k <= dca->nf); xassert(dca->type[k] == '?'); xassert(strlen(str) <= MAX_LENGTH); xassert(dca->str[k] != NULL); dca->type[k] = 'S'; strcpy(dca->str[k], str); return; } static int write_func(MPL *mpl, void *info) { /* this is auxiliary routine to work within domain scope */ TABLE *tab = info; TABDCA *dca = mpl->dca; TABOUT *out; SYMBOL *sym; int k; char buf[MAX_LENGTH+1]; /* evaluate field values */ k = 0; for (out = tab->u.out.list; out != NULL; out = out->next) { k++; switch (out->code->type) { case A_NUMERIC: dca->type[k] = 'N'; dca->num[k] = eval_numeric(mpl, out->code); dca->str[k][0] = '\0'; break; case A_SYMBOLIC: sym = eval_symbolic(mpl, out->code); if (sym->str == NULL) { dca->type[k] = 'N'; dca->num[k] = sym->num; dca->str[k][0] = '\0'; } else { dca->type[k] = 'S'; dca->num[k] = 0.0; fetch_string(mpl, sym->str, buf); strcpy(dca->str[k], buf); } delete_symbol(mpl, sym); break; default: xassert(out != out); } } /* write record to output table */ mpl_tab_drv_write(mpl); return 0; } void execute_table(MPL *mpl, TABLE *tab) { /* execute table statement */ TABARG *arg; TABFLD *fld; TABIN *in; TABOUT *out; TABDCA *dca; SET *set; int k; char buf[MAX_LENGTH+1]; /* allocate table driver communication area */ xassert(mpl->dca == NULL); mpl->dca = dca = xmalloc(sizeof(TABDCA)); dca->id = 0; dca->link = NULL; dca->na = 0; dca->arg = NULL; dca->nf = 0; dca->name = NULL; dca->type = NULL; dca->num = NULL; dca->str = NULL; /* allocate arguments */ xassert(dca->na == 0); for (arg = tab->arg; arg != NULL; arg = arg->next) dca->na++; dca->arg = xcalloc(1+dca->na, sizeof(char *)); #if 1 /* 28/IX-2008 */ for (k = 1; k <= dca->na; k++) dca->arg[k] = NULL; #endif /* evaluate argument values */ k = 0; for (arg = tab->arg; arg != NULL; arg = arg->next) { SYMBOL *sym; k++; xassert(arg->code->type == A_SYMBOLIC); sym = eval_symbolic(mpl, arg->code); if (sym->str == NULL) sprintf(buf, "%.*g", DBL_DIG, sym->num); else fetch_string(mpl, sym->str, buf); delete_symbol(mpl, sym); dca->arg[k] = xmalloc(strlen(buf)+1); strcpy(dca->arg[k], buf); } /* perform table input/output */ switch (tab->type) { case A_INPUT: goto read_table; case A_OUTPUT: goto write_table; default: xassert(tab != tab); } read_table: /* read data from input table */ /* add the only member to the control set and assign it empty elemental set */ set = tab->u.in.set; if (set != NULL) { if (set->data) error(mpl, "%s already provided with data", set->name); xassert(set->array->head == NULL); add_member(mpl, set->array, NULL)->value.set = create_elemset(mpl, set->dimen); set->data = 1; } /* check parameters specified in the input list */ for (in = tab->u.in.list; in != NULL; in = in->next) { if (in->par->data) error(mpl, "%s already provided with data", in->par->name); in->par->data = 1; } /* allocate and initialize fields */ xassert(dca->nf == 0); for (fld = tab->u.in.fld; fld != NULL; fld = fld->next) dca->nf++; for (in = tab->u.in.list; in != NULL; in = in->next) dca->nf++; dca->name = xcalloc(1+dca->nf, sizeof(char *)); dca->type = xcalloc(1+dca->nf, sizeof(int)); dca->num = xcalloc(1+dca->nf, sizeof(double)); dca->str = xcalloc(1+dca->nf, sizeof(char *)); k = 0; for (fld = tab->u.in.fld; fld != NULL; fld = fld->next) { k++; dca->name[k] = fld->name; dca->type[k] = '?'; dca->num[k] = 0.0; dca->str[k] = xmalloc(MAX_LENGTH+1); dca->str[k][0] = '\0'; } for (in = tab->u.in.list; in != NULL; in = in->next) { k++; dca->name[k] = in->name; dca->type[k] = '?'; dca->num[k] = 0.0; dca->str[k] = xmalloc(MAX_LENGTH+1); dca->str[k][0] = '\0'; } /* open input table */ mpl_tab_drv_open(mpl, 'R'); /* read and process records */ for (;;) { TUPLE *tup; /* reset field types */ for (k = 1; k <= dca->nf; k++) dca->type[k] = '?'; /* read next record */ if (mpl_tab_drv_read(mpl)) break; /* all fields must be set by the driver */ for (k = 1; k <= dca->nf; k++) { if (dca->type[k] == '?') error(mpl, "field %s missing in input table", dca->name[k]); } /* construct n-tuple */ tup = create_tuple(mpl); k = 0; for (fld = tab->u.in.fld; fld != NULL; fld = fld->next) { k++; xassert(k <= dca->nf); switch (dca->type[k]) { case 'N': tup = expand_tuple(mpl, tup, create_symbol_num(mpl, dca->num[k])); break; case 'S': xassert(strlen(dca->str[k]) <= MAX_LENGTH); tup = expand_tuple(mpl, tup, create_symbol_str(mpl, create_string(mpl, dca->str[k]))); break; default: xassert(dca != dca); } } /* add n-tuple just read to the control set */ if (tab->u.in.set != NULL) check_then_add(mpl, tab->u.in.set->array->head->value.set, copy_tuple(mpl, tup)); /* assign values to the parameters in the input list */ for (in = tab->u.in.list; in != NULL; in = in->next) { MEMBER *memb; k++; xassert(k <= dca->nf); /* there must be no member with the same n-tuple */ if (find_member(mpl, in->par->array, tup) != NULL) error(mpl, "%s%s already defined", in->par->name, format_tuple(mpl, '[', tup)); /* create new parameter member with given n-tuple */ memb = add_member(mpl, in->par->array, copy_tuple(mpl, tup)) ; /* assign value to the parameter member */ switch (in->par->type) { case A_NUMERIC: case A_INTEGER: case A_BINARY: if (dca->type[k] != 'N') error(mpl, "%s requires numeric data", in->par->name); memb->value.num = dca->num[k]; break; case A_SYMBOLIC: switch (dca->type[k]) { case 'N': memb->value.sym = create_symbol_num(mpl, dca->num[k]); break; case 'S': xassert(strlen(dca->str[k]) <= MAX_LENGTH); memb->value.sym = create_symbol_str(mpl, create_string(mpl,dca->str[k])); break; default: xassert(dca != dca); } break; default: xassert(in != in); } } /* n-tuple is no more needed */ delete_tuple(mpl, tup); } /* close input table */ mpl_tab_drv_close(mpl); goto done; write_table: /* write data to output table */ /* allocate and initialize fields */ xassert(dca->nf == 0); for (out = tab->u.out.list; out != NULL; out = out->next) dca->nf++; dca->name = xcalloc(1+dca->nf, sizeof(char *)); dca->type = xcalloc(1+dca->nf, sizeof(int)); dca->num = xcalloc(1+dca->nf, sizeof(double)); dca->str = xcalloc(1+dca->nf, sizeof(char *)); k = 0; for (out = tab->u.out.list; out != NULL; out = out->next) { k++; dca->name[k] = out->name; dca->type[k] = '?'; dca->num[k] = 0.0; dca->str[k] = xmalloc(MAX_LENGTH+1); dca->str[k][0] = '\0'; } /* open output table */ mpl_tab_drv_open(mpl, 'W'); /* evaluate fields and write records */ loop_within_domain(mpl, tab->u.out.domain, tab, write_func); /* close output table */ mpl_tab_drv_close(mpl); done: /* free table driver communication area */ free_dca(mpl); return; } void free_dca(MPL *mpl) { /* free table driver communucation area */ TABDCA *dca = mpl->dca; int k; if (dca != NULL) { if (dca->link != NULL) mpl_tab_drv_close(mpl); if (dca->arg != NULL) { for (k = 1; k <= dca->na; k++) #if 1 /* 28/IX-2008 */ if (dca->arg[k] != NULL) #endif xfree(dca->arg[k]); xfree(dca->arg); } if (dca->name != NULL) xfree(dca->name); if (dca->type != NULL) xfree(dca->type); if (dca->num != NULL) xfree(dca->num); if (dca->str != NULL) { for (k = 1; k <= dca->nf; k++) xfree(dca->str[k]); xfree(dca->str); } xfree(dca), mpl->dca = NULL; } return; } void clean_table(MPL *mpl, TABLE *tab) { /* clean table statement */ TABARG *arg; TABOUT *out; /* clean string list */ for (arg = tab->arg; arg != NULL; arg = arg->next) clean_code(mpl, arg->code); switch (tab->type) { case A_INPUT: break; case A_OUTPUT: /* clean subscript domain */ clean_domain(mpl, tab->u.out.domain); /* clean output list */ for (out = tab->u.out.list; out != NULL; out = out->next) clean_code(mpl, out->code); break; default: xassert(tab != tab); } return; } #endif /**********************************************************************/ /* * * MODEL STATEMENTS * * */ /**********************************************************************/ /*---------------------------------------------------------------------- -- execute_check - execute check statement. -- -- This routine executes specified check statement. */ static int check_func(MPL *mpl, void *info) { /* this is auxiliary routine to work within domain scope */ CHECK *chk = (CHECK *)info; if (!eval_logical(mpl, chk->code)) error(mpl, "check%s failed", format_tuple(mpl, '[', get_domain_tuple(mpl, chk->domain))); return 0; } void execute_check(MPL *mpl, CHECK *chk) { loop_within_domain(mpl, chk->domain, chk, check_func); return; } /*---------------------------------------------------------------------- -- clean_check - clean check statement. -- -- This routine cleans specified check statement that assumes deleting -- all stuff dynamically allocated on generating/postsolving phase. */ void clean_check(MPL *mpl, CHECK *chk) { /* clean subscript domain */ clean_domain(mpl, chk->domain); /* clean pseudo-code for computing predicate */ clean_code(mpl, chk->code); return; } /*---------------------------------------------------------------------- -- execute_display - execute display statement. -- -- This routine executes specified display statement. */ static void display_set(MPL *mpl, SET *set, MEMBER *memb) { /* display member of model set */ ELEMSET *s = memb->value.set; MEMBER *m; write_text(mpl, "%s%s%s\n", set->name, format_tuple(mpl, '[', memb->tuple), s->head == NULL ? " is empty" : ":"); for (m = s->head; m != NULL; m = m->next) write_text(mpl, " %s\n", format_tuple(mpl, '(', m->tuple)); return; } static void display_par(MPL *mpl, PARAMETER *par, MEMBER *memb) { /* display member of model parameter */ switch (par->type) { case A_NUMERIC: case A_INTEGER: case A_BINARY: write_text(mpl, "%s%s = %.*g\n", par->name, format_tuple(mpl, '[', memb->tuple), DBL_DIG, memb->value.num); break; case A_SYMBOLIC: write_text(mpl, "%s%s = %s\n", par->name, format_tuple(mpl, '[', memb->tuple), format_symbol(mpl, memb->value.sym)); break; default: xassert(par != par); } return; } #if 1 /* 15/V-2010 */ static void display_var(MPL *mpl, VARIABLE *var, MEMBER *memb, int suff) { /* display member of model variable */ if (suff == DOT_NONE || suff == DOT_VAL) write_text(mpl, "%s%s.val = %.*g\n", var->name, format_tuple(mpl, '[', memb->tuple), DBL_DIG, memb->value.var->prim); else if (suff == DOT_LB) write_text(mpl, "%s%s.lb = %.*g\n", var->name, format_tuple(mpl, '[', memb->tuple), DBL_DIG, memb->value.var->var->lbnd == NULL ? -DBL_MAX : memb->value.var->lbnd); else if (suff == DOT_UB) write_text(mpl, "%s%s.ub = %.*g\n", var->name, format_tuple(mpl, '[', memb->tuple), DBL_DIG, memb->value.var->var->ubnd == NULL ? +DBL_MAX : memb->value.var->ubnd); else if (suff == DOT_STATUS) write_text(mpl, "%s%s.status = %d\n", var->name, format_tuple (mpl, '[', memb->tuple), memb->value.var->stat); else if (suff == DOT_DUAL) write_text(mpl, "%s%s.dual = %.*g\n", var->name, format_tuple(mpl, '[', memb->tuple), DBL_DIG, memb->value.var->dual); else xassert(suff != suff); return; } #endif #if 1 /* 15/V-2010 */ static void display_con(MPL *mpl, CONSTRAINT *con, MEMBER *memb, int suff) { /* display member of model constraint */ if (suff == DOT_NONE || suff == DOT_VAL) write_text(mpl, "%s%s.val = %.*g\n", con->name, format_tuple(mpl, '[', memb->tuple), DBL_DIG, memb->value.con->prim); else if (suff == DOT_LB) write_text(mpl, "%s%s.lb = %.*g\n", con->name, format_tuple(mpl, '[', memb->tuple), DBL_DIG, memb->value.con->con->lbnd == NULL ? -DBL_MAX : memb->value.con->lbnd); else if (suff == DOT_UB) write_text(mpl, "%s%s.ub = %.*g\n", con->name, format_tuple(mpl, '[', memb->tuple), DBL_DIG, memb->value.con->con->ubnd == NULL ? +DBL_MAX : memb->value.con->ubnd); else if (suff == DOT_STATUS) write_text(mpl, "%s%s.status = %d\n", con->name, format_tuple (mpl, '[', memb->tuple), memb->value.con->stat); else if (suff == DOT_DUAL) write_text(mpl, "%s%s.dual = %.*g\n", con->name, format_tuple(mpl, '[', memb->tuple), DBL_DIG, memb->value.con->dual); else xassert(suff != suff); return; } #endif static void display_memb(MPL *mpl, CODE *code) { /* display member specified by pseudo-code */ MEMBER memb; ARG_LIST *e; xassert(code->op == O_MEMNUM || code->op == O_MEMSYM || code->op == O_MEMSET || code->op == O_MEMVAR || code->op == O_MEMCON); memb.tuple = create_tuple(mpl); for (e = code->arg.par.list; e != NULL; e = e->next) memb.tuple = expand_tuple(mpl, memb.tuple, eval_symbolic(mpl, e->x)); switch (code->op) { case O_MEMNUM: memb.value.num = eval_member_num(mpl, code->arg.par.par, memb.tuple); display_par(mpl, code->arg.par.par, &memb); break; case O_MEMSYM: memb.value.sym = eval_member_sym(mpl, code->arg.par.par, memb.tuple); display_par(mpl, code->arg.par.par, &memb); delete_symbol(mpl, memb.value.sym); break; case O_MEMSET: memb.value.set = eval_member_set(mpl, code->arg.set.set, memb.tuple); display_set(mpl, code->arg.set.set, &memb); break; case O_MEMVAR: memb.value.var = eval_member_var(mpl, code->arg.var.var, memb.tuple); display_var (mpl, code->arg.var.var, &memb, code->arg.var.suff); break; case O_MEMCON: memb.value.con = eval_member_con(mpl, code->arg.con.con, memb.tuple); display_con (mpl, code->arg.con.con, &memb, code->arg.con.suff); break; default: xassert(code != code); } delete_tuple(mpl, memb.tuple); return; } static void display_code(MPL *mpl, CODE *code) { /* display value of expression */ switch (code->type) { case A_NUMERIC: /* numeric value */ { double num; num = eval_numeric(mpl, code); write_text(mpl, "%.*g\n", DBL_DIG, num); } break; case A_SYMBOLIC: /* symbolic value */ { SYMBOL *sym; sym = eval_symbolic(mpl, code); write_text(mpl, "%s\n", format_symbol(mpl, sym)); delete_symbol(mpl, sym); } break; case A_LOGICAL: /* logical value */ { int bit; bit = eval_logical(mpl, code); write_text(mpl, "%s\n", bit ? "true" : "false"); } break; case A_TUPLE: /* n-tuple */ { TUPLE *tuple; tuple = eval_tuple(mpl, code); write_text(mpl, "%s\n", format_tuple(mpl, '(', tuple)); delete_tuple(mpl, tuple); } break; case A_ELEMSET: /* elemental set */ { ELEMSET *set; MEMBER *memb; set = eval_elemset(mpl, code); if (set->head == 0) write_text(mpl, "set is empty\n"); for (memb = set->head; memb != NULL; memb = memb->next) write_text(mpl, " %s\n", format_tuple(mpl, '(', memb->tuple)); delete_elemset(mpl, set); } break; case A_FORMULA: /* linear form */ { FORMULA *form, *term; form = eval_formula(mpl, code); if (form == NULL) write_text(mpl, "linear form is empty\n"); for (term = form; term != NULL; term = term->next) { if (term->var == NULL) write_text(mpl, " %.*g\n", term->coef); else write_text(mpl, " %.*g %s%s\n", DBL_DIG, term->coef, term->var->var->name, format_tuple(mpl, '[', term->var->memb->tuple)); } delete_formula(mpl, form); } break; default: xassert(code != code); } return; } static int display_func(MPL *mpl, void *info) { /* this is auxiliary routine to work within domain scope */ DISPLAY *dpy = (DISPLAY *)info; DISPLAY1 *entry; for (entry = dpy->list; entry != NULL; entry = entry->next) { if (entry->type == A_INDEX) { /* dummy index */ DOMAIN_SLOT *slot = entry->u.slot; write_text(mpl, "%s = %s\n", slot->name, format_symbol(mpl, slot->value)); } else if (entry->type == A_SET) { /* model set */ SET *set = entry->u.set; MEMBER *memb; if (set->assign != NULL) { /* the set has assignment expression; evaluate all its members over entire domain */ eval_whole_set(mpl, set); } else { /* the set has no assignment expression; refer to its any existing member ignoring resultant value to check the data provided the data section */ #if 1 /* 12/XII-2008 */ if (set->gadget != NULL && set->data == 0) { /* initialize the set with data from a plain set */ saturate_set(mpl, set); } #endif if (set->array->head != NULL) eval_member_set(mpl, set, set->array->head->tuple); } /* display all members of the set array */ if (set->array->head == NULL) write_text(mpl, "%s has empty content\n", set->name); for (memb = set->array->head; memb != NULL; memb = memb->next) display_set(mpl, set, memb); } else if (entry->type == A_PARAMETER) { /* model parameter */ PARAMETER *par = entry->u.par; MEMBER *memb; if (par->assign != NULL) { /* the parameter has an assignment expression; evaluate all its member over entire domain */ eval_whole_par(mpl, par); } else { /* the parameter has no assignment expression; refer to its any existing member ignoring resultant value to check the data provided in the data section */ if (par->array->head != NULL) { if (par->type != A_SYMBOLIC) eval_member_num(mpl, par, par->array->head->tuple); else delete_symbol(mpl, eval_member_sym(mpl, par, par->array->head->tuple)); } } /* display all members of the parameter array */ if (par->array->head == NULL) write_text(mpl, "%s has empty content\n", par->name); for (memb = par->array->head; memb != NULL; memb = memb->next) display_par(mpl, par, memb); } else if (entry->type == A_VARIABLE) { /* model variable */ VARIABLE *var = entry->u.var; MEMBER *memb; xassert(mpl->flag_p); /* display all members of the variable array */ if (var->array->head == NULL) write_text(mpl, "%s has empty content\n", var->name); for (memb = var->array->head; memb != NULL; memb = memb->next) display_var(mpl, var, memb, DOT_NONE); } else if (entry->type == A_CONSTRAINT) { /* model constraint */ CONSTRAINT *con = entry->u.con; MEMBER *memb; xassert(mpl->flag_p); /* display all members of the constraint array */ if (con->array->head == NULL) write_text(mpl, "%s has empty content\n", con->name); for (memb = con->array->head; memb != NULL; memb = memb->next) display_con(mpl, con, memb, DOT_NONE); } else if (entry->type == A_EXPRESSION) { /* expression */ CODE *code = entry->u.code; if (code->op == O_MEMNUM || code->op == O_MEMSYM || code->op == O_MEMSET || code->op == O_MEMVAR || code->op == O_MEMCON) display_memb(mpl, code); else display_code(mpl, code); } else xassert(entry != entry); } return 0; } void execute_display(MPL *mpl, DISPLAY *dpy) { loop_within_domain(mpl, dpy->domain, dpy, display_func); return; } /*---------------------------------------------------------------------- -- clean_display - clean display statement. -- -- This routine cleans specified display statement that assumes deleting -- all stuff dynamically allocated on generating/postsolving phase. */ void clean_display(MPL *mpl, DISPLAY *dpy) { DISPLAY1 *d; #if 0 /* 15/V-2010 */ ARG_LIST *e; #endif /* clean subscript domain */ clean_domain(mpl, dpy->domain); /* clean display list */ for (d = dpy->list; d != NULL; d = d->next) { /* clean pseudo-code for computing expression */ if (d->type == A_EXPRESSION) clean_code(mpl, d->u.code); #if 0 /* 15/V-2010 */ /* clean pseudo-code for computing subscripts */ for (e = d->list; e != NULL; e = e->next) clean_code(mpl, e->x); #endif } return; } /*---------------------------------------------------------------------- -- execute_printf - execute printf statement. -- -- This routine executes specified printf statement. */ #if 1 /* 14/VII-2006 */ static void print_char(MPL *mpl, int c) { if (mpl->prt_fp == NULL) write_char(mpl, c); else xfputc(c, mpl->prt_fp); return; } static void print_text(MPL *mpl, char *fmt, ...) { va_list arg; char buf[OUTBUF_SIZE], *c; va_start(arg, fmt); vsprintf(buf, fmt, arg); xassert(strlen(buf) < sizeof(buf)); va_end(arg); for (c = buf; *c != '\0'; c++) print_char(mpl, *c); return; } #endif static int printf_func(MPL *mpl, void *info) { /* this is auxiliary routine to work within domain scope */ PRINTF *prt = (PRINTF *)info; PRINTF1 *entry; SYMBOL *sym; char fmt[MAX_LENGTH+1], *c, *from, save; /* evaluate format control string */ sym = eval_symbolic(mpl, prt->fmt); if (sym->str == NULL) sprintf(fmt, "%.*g", DBL_DIG, sym->num); else fetch_string(mpl, sym->str, fmt); delete_symbol(mpl, sym); /* scan format control string and perform formatting output */ entry = prt->list; for (c = fmt; *c != '\0'; c++) { if (*c == '%') { /* scan format specifier */ from = c++; if (*c == '%') { print_char(mpl, '%'); continue; } if (entry == NULL) break; /* scan optional flags */ while (*c == '-' || *c == '+' || *c == ' ' || *c == '#' || *c == '0') c++; /* scan optional minimum field width */ while (isdigit((unsigned char)*c)) c++; /* scan optional precision */ if (*c == '.') { c++; while (isdigit((unsigned char)*c)) c++; } /* scan conversion specifier and perform formatting */ save = *(c+1), *(c+1) = '\0'; if (*c == 'd' || *c == 'i' || *c == 'e' || *c == 'E' || *c == 'f' || *c == 'F' || *c == 'g' || *c == 'G') { /* the specifier requires numeric value */ double value; xassert(entry != NULL); switch (entry->code->type) { case A_NUMERIC: value = eval_numeric(mpl, entry->code); break; case A_SYMBOLIC: sym = eval_symbolic(mpl, entry->code); if (sym->str != NULL) error(mpl, "cannot convert %s to floating-point" " number", format_symbol(mpl, sym)); value = sym->num; delete_symbol(mpl, sym); break; case A_LOGICAL: if (eval_logical(mpl, entry->code)) value = 1.0; else value = 0.0; break; default: xassert(entry != entry); } if (*c == 'd' || *c == 'i') { double int_max = (double)INT_MAX; if (!(-int_max <= value && value <= +int_max)) error(mpl, "cannot convert %.*g to integer", DBL_DIG, value); print_text(mpl, from, (int)floor(value + 0.5)); } else print_text(mpl, from, value); } else if (*c == 's') { /* the specifier requires symbolic value */ char value[MAX_LENGTH+1]; switch (entry->code->type) { case A_NUMERIC: sprintf(value, "%.*g", DBL_DIG, eval_numeric(mpl, entry->code)); break; case A_LOGICAL: if (eval_logical(mpl, entry->code)) strcpy(value, "T"); else strcpy(value, "F"); break; case A_SYMBOLIC: sym = eval_symbolic(mpl, entry->code); if (sym->str == NULL) sprintf(value, "%.*g", DBL_DIG, sym->num); else fetch_string(mpl, sym->str, value); delete_symbol(mpl, sym); break; default: xassert(entry != entry); } print_text(mpl, from, value); } else error(mpl, "format specifier missing or invalid"); *(c+1) = save; entry = entry->next; } else if (*c == '\\') { /* write some control character */ c++; if (*c == 't') print_char(mpl, '\t'); else if (*c == 'n') print_char(mpl, '\n'); #if 1 /* 28/X-2010 */ else if (*c == '\0') { /* format string ends with backslash */ error(mpl, "invalid use of escape character \\ in format" " control string"); } #endif else print_char(mpl, *c); } else { /* write character without formatting */ print_char(mpl, *c); } } return 0; } #if 0 /* 14/VII-2006 */ void execute_printf(MPL *mpl, PRINTF *prt) { loop_within_domain(mpl, prt->domain, prt, printf_func); return; } #else void execute_printf(MPL *mpl, PRINTF *prt) { if (prt->fname == NULL) { /* switch to the standard output */ if (mpl->prt_fp != NULL) { xfclose(mpl->prt_fp), mpl->prt_fp = NULL; xfree(mpl->prt_file), mpl->prt_file = NULL; } } else { /* evaluate file name string */ SYMBOL *sym; char fname[MAX_LENGTH+1]; sym = eval_symbolic(mpl, prt->fname); if (sym->str == NULL) sprintf(fname, "%.*g", DBL_DIG, sym->num); else fetch_string(mpl, sym->str, fname); delete_symbol(mpl, sym); /* close the current print file, if necessary */ if (mpl->prt_fp != NULL && (!prt->app || strcmp(mpl->prt_file, fname) != 0)) { xfclose(mpl->prt_fp), mpl->prt_fp = NULL; xfree(mpl->prt_file), mpl->prt_file = NULL; } /* open the specified print file, if necessary */ if (mpl->prt_fp == NULL) { mpl->prt_fp = xfopen(fname, prt->app ? "a" : "w"); if (mpl->prt_fp == NULL) error(mpl, "unable to open `%s' for writing - %s", fname, xerrmsg()); mpl->prt_file = xmalloc(strlen(fname)+1); strcpy(mpl->prt_file, fname); } } loop_within_domain(mpl, prt->domain, prt, printf_func); if (mpl->prt_fp != NULL) { xfflush(mpl->prt_fp); if (xferror(mpl->prt_fp)) error(mpl, "writing error to `%s' - %s", mpl->prt_file, xerrmsg()); } return; } #endif /*---------------------------------------------------------------------- -- clean_printf - clean printf statement. -- -- This routine cleans specified printf statement that assumes deleting -- all stuff dynamically allocated on generating/postsolving phase. */ void clean_printf(MPL *mpl, PRINTF *prt) { PRINTF1 *p; /* clean subscript domain */ clean_domain(mpl, prt->domain); /* clean pseudo-code for computing format string */ clean_code(mpl, prt->fmt); /* clean printf list */ for (p = prt->list; p != NULL; p = p->next) { /* clean pseudo-code for computing value to be printed */ clean_code(mpl, p->code); } #if 1 /* 14/VII-2006 */ /* clean pseudo-code for computing file name string */ clean_code(mpl, prt->fname); #endif return; } /*---------------------------------------------------------------------- -- execute_for - execute for statement. -- -- This routine executes specified for statement. */ static int for_func(MPL *mpl, void *info) { /* this is auxiliary routine to work within domain scope */ FOR *fur = (FOR *)info; STATEMENT *stmt, *save; save = mpl->stmt; for (stmt = fur->list; stmt != NULL; stmt = stmt->next) execute_statement(mpl, stmt); mpl->stmt = save; return 0; } void execute_for(MPL *mpl, FOR *fur) { loop_within_domain(mpl, fur->domain, fur, for_func); return; } /*---------------------------------------------------------------------- -- clean_for - clean for statement. -- -- This routine cleans specified for statement that assumes deleting all -- stuff dynamically allocated on generating/postsolving phase. */ void clean_for(MPL *mpl, FOR *fur) { STATEMENT *stmt; /* clean subscript domain */ clean_domain(mpl, fur->domain); /* clean all sub-statements */ for (stmt = fur->list; stmt != NULL; stmt = stmt->next) clean_statement(mpl, stmt); return; } /*---------------------------------------------------------------------- -- execute_statement - execute specified model statement. -- -- This routine executes specified model statement. */ void execute_statement(MPL *mpl, STATEMENT *stmt) { mpl->stmt = stmt; switch (stmt->type) { case A_SET: case A_PARAMETER: case A_VARIABLE: break; case A_CONSTRAINT: xprintf("Generating %s...\n", stmt->u.con->name); eval_whole_con(mpl, stmt->u.con); break; case A_TABLE: switch (stmt->u.tab->type) { case A_INPUT: xprintf("Reading %s...\n", stmt->u.tab->name); break; case A_OUTPUT: xprintf("Writing %s...\n", stmt->u.tab->name); break; default: xassert(stmt != stmt); } execute_table(mpl, stmt->u.tab); break; case A_SOLVE: break; case A_CHECK: xprintf("Checking (line %d)...\n", stmt->line); execute_check(mpl, stmt->u.chk); break; case A_DISPLAY: write_text(mpl, "Display statement at line %d\n", stmt->line); execute_display(mpl, stmt->u.dpy); break; case A_PRINTF: execute_printf(mpl, stmt->u.prt); break; case A_FOR: execute_for(mpl, stmt->u.fur); break; default: xassert(stmt != stmt); } return; } /*---------------------------------------------------------------------- -- clean_statement - clean specified model statement. -- -- This routine cleans specified model statement that assumes deleting -- all stuff dynamically allocated on generating/postsolving phase. */ void clean_statement(MPL *mpl, STATEMENT *stmt) { switch(stmt->type) { case A_SET: clean_set(mpl, stmt->u.set); break; case A_PARAMETER: clean_parameter(mpl, stmt->u.par); break; case A_VARIABLE: clean_variable(mpl, stmt->u.var); break; case A_CONSTRAINT: clean_constraint(mpl, stmt->u.con); break; #if 1 /* 11/II-2008 */ case A_TABLE: clean_table(mpl, stmt->u.tab); break; #endif case A_SOLVE: break; case A_CHECK: clean_check(mpl, stmt->u.chk); break; case A_DISPLAY: clean_display(mpl, stmt->u.dpy); break; case A_PRINTF: clean_printf(mpl, stmt->u.prt); break; case A_FOR: clean_for(mpl, stmt->u.fur); break; default: xassert(stmt != stmt); } return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpssx01.c0000644000076500000240000006636313524616144025242 0ustar tamasstaff00000000000000/* glpssx01.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wlogical-op-parentheses" #pragma clang diagnostic ignored "-Wunused-value" #endif #include "glpenv.h" #include "glpssx.h" #define xfault xerror /*---------------------------------------------------------------------- // ssx_create - create simplex solver workspace. // // This routine creates the workspace used by simplex solver routines, // and returns a pointer to it. // // Parameters m, n, and nnz specify, respectively, the number of rows, // columns, and non-zero constraint coefficients. // // This routine only allocates the memory for the workspace components, // so the workspace needs to be saturated by data. */ SSX *ssx_create(int m, int n, int nnz) { SSX *ssx; int i, j, k; if (m < 1) xfault("ssx_create: m = %d; invalid number of rows\n", m); if (n < 1) xfault("ssx_create: n = %d; invalid number of columns\n", n); if (nnz < 0) xfault("ssx_create: nnz = %d; invalid number of non-zero const" "raint coefficients\n", nnz); ssx = xmalloc(sizeof(SSX)); ssx->m = m; ssx->n = n; ssx->type = xcalloc(1+m+n, sizeof(int)); ssx->lb = xcalloc(1+m+n, sizeof(mpq_t)); for (k = 1; k <= m+n; k++) mpq_init(ssx->lb[k]); ssx->ub = xcalloc(1+m+n, sizeof(mpq_t)); for (k = 1; k <= m+n; k++) mpq_init(ssx->ub[k]); ssx->coef = xcalloc(1+m+n, sizeof(mpq_t)); for (k = 0; k <= m+n; k++) mpq_init(ssx->coef[k]); ssx->A_ptr = xcalloc(1+n+1, sizeof(int)); ssx->A_ptr[n+1] = nnz+1; ssx->A_ind = xcalloc(1+nnz, sizeof(int)); ssx->A_val = xcalloc(1+nnz, sizeof(mpq_t)); for (k = 1; k <= nnz; k++) mpq_init(ssx->A_val[k]); ssx->stat = xcalloc(1+m+n, sizeof(int)); ssx->Q_row = xcalloc(1+m+n, sizeof(int)); ssx->Q_col = xcalloc(1+m+n, sizeof(int)); ssx->binv = bfx_create_binv(); ssx->bbar = xcalloc(1+m, sizeof(mpq_t)); for (i = 0; i <= m; i++) mpq_init(ssx->bbar[i]); ssx->pi = xcalloc(1+m, sizeof(mpq_t)); for (i = 1; i <= m; i++) mpq_init(ssx->pi[i]); ssx->cbar = xcalloc(1+n, sizeof(mpq_t)); for (j = 1; j <= n; j++) mpq_init(ssx->cbar[j]); ssx->rho = xcalloc(1+m, sizeof(mpq_t)); for (i = 1; i <= m; i++) mpq_init(ssx->rho[i]); ssx->ap = xcalloc(1+n, sizeof(mpq_t)); for (j = 1; j <= n; j++) mpq_init(ssx->ap[j]); ssx->aq = xcalloc(1+m, sizeof(mpq_t)); for (i = 1; i <= m; i++) mpq_init(ssx->aq[i]); mpq_init(ssx->delta); return ssx; } /*---------------------------------------------------------------------- // ssx_factorize - factorize the current basis matrix. // // This routine computes factorization of the current basis matrix B // and returns the singularity flag. If the matrix B is non-singular, // the flag is zero, otherwise non-zero. */ static int basis_col(void *info, int j, int ind[], mpq_t val[]) { /* this auxiliary routine provides row indices and numeric values of non-zero elements in j-th column of the matrix B */ SSX *ssx = info; int m = ssx->m; int n = ssx->n; int *A_ptr = ssx->A_ptr; int *A_ind = ssx->A_ind; mpq_t *A_val = ssx->A_val; int *Q_col = ssx->Q_col; int k, len, ptr; xassert(1 <= j && j <= m); k = Q_col[j]; /* x[k] = xB[j] */ xassert(1 <= k && k <= m+n); /* j-th column of the matrix B is k-th column of the augmented constraint matrix (I | -A) */ if (k <= m) { /* it is a column of the unity matrix I */ len = 1, ind[1] = k, mpq_set_si(val[1], 1, 1); } else { /* it is a column of the original constraint matrix -A */ len = 0; for (ptr = A_ptr[k-m]; ptr < A_ptr[k-m+1]; ptr++) { len++; ind[len] = A_ind[ptr]; mpq_neg(val[len], A_val[ptr]); } } return len; } int ssx_factorize(SSX *ssx) { int ret; ret = bfx_factorize(ssx->binv, ssx->m, basis_col, ssx); return ret; } /*---------------------------------------------------------------------- // ssx_get_xNj - determine value of non-basic variable. // // This routine determines the value of non-basic variable xN[j] in the // current basic solution defined as follows: // // 0, if xN[j] is free variable // lN[j], if xN[j] is on its lower bound // uN[j], if xN[j] is on its upper bound // lN[j] = uN[j], if xN[j] is fixed variable // // where lN[j] and uN[j] are lower and upper bounds of xN[j]. */ void ssx_get_xNj(SSX *ssx, int j, mpq_t x) { int m = ssx->m; int n = ssx->n; mpq_t *lb = ssx->lb; mpq_t *ub = ssx->ub; int *stat = ssx->stat; int *Q_col = ssx->Q_col; int k; xassert(1 <= j && j <= n); k = Q_col[m+j]; /* x[k] = xN[j] */ xassert(1 <= k && k <= m+n); switch (stat[k]) { case SSX_NL: /* xN[j] is on its lower bound */ mpq_set(x, lb[k]); break; case SSX_NU: /* xN[j] is on its upper bound */ mpq_set(x, ub[k]); break; case SSX_NF: /* xN[j] is free variable */ mpq_set_si(x, 0, 1); break; case SSX_NS: /* xN[j] is fixed variable */ mpq_set(x, lb[k]); break; default: xassert(stat != stat); } return; } /*---------------------------------------------------------------------- // ssx_eval_bbar - compute values of basic variables. // // This routine computes values of basic variables xB in the current // basic solution as follows: // // beta = - inv(B) * N * xN, // // where B is the basis matrix, N is the matrix of non-basic columns, // xN is a vector of current values of non-basic variables. */ void ssx_eval_bbar(SSX *ssx) { int m = ssx->m; int n = ssx->n; mpq_t *coef = ssx->coef; int *A_ptr = ssx->A_ptr; int *A_ind = ssx->A_ind; mpq_t *A_val = ssx->A_val; int *Q_col = ssx->Q_col; mpq_t *bbar = ssx->bbar; int i, j, k, ptr; mpq_t x, temp; mpq_init(x); mpq_init(temp); /* bbar := 0 */ for (i = 1; i <= m; i++) mpq_set_si(bbar[i], 0, 1); /* bbar := - N * xN = - N[1] * xN[1] - ... - N[n] * xN[n] */ for (j = 1; j <= n; j++) { ssx_get_xNj(ssx, j, x); if (mpq_sgn(x) == 0) continue; k = Q_col[m+j]; /* x[k] = xN[j] */ if (k <= m) { /* N[j] is a column of the unity matrix I */ mpq_sub(bbar[k], bbar[k], x); } else { /* N[j] is a column of the original constraint matrix -A */ for (ptr = A_ptr[k-m]; ptr < A_ptr[k-m+1]; ptr++) { mpq_mul(temp, A_val[ptr], x); mpq_add(bbar[A_ind[ptr]], bbar[A_ind[ptr]], temp); } } } /* bbar := inv(B) * bbar */ bfx_ftran(ssx->binv, bbar, 0); #if 1 /* compute value of the objective function */ /* bbar[0] := c[0] */ mpq_set(bbar[0], coef[0]); /* bbar[0] := bbar[0] + sum{i in B} cB[i] * xB[i] */ for (i = 1; i <= m; i++) { k = Q_col[i]; /* x[k] = xB[i] */ if (mpq_sgn(coef[k]) == 0) continue; mpq_mul(temp, coef[k], bbar[i]); mpq_add(bbar[0], bbar[0], temp); } /* bbar[0] := bbar[0] + sum{j in N} cN[j] * xN[j] */ for (j = 1; j <= n; j++) { k = Q_col[m+j]; /* x[k] = xN[j] */ if (mpq_sgn(coef[k]) == 0) continue; ssx_get_xNj(ssx, j, x); mpq_mul(temp, coef[k], x); mpq_add(bbar[0], bbar[0], temp); } #endif mpq_clear(x); mpq_clear(temp); return; } /*---------------------------------------------------------------------- // ssx_eval_pi - compute values of simplex multipliers. // // This routine computes values of simplex multipliers (shadow prices) // pi in the current basic solution as follows: // // pi = inv(B') * cB, // // where B' is a matrix transposed to the basis matrix B, cB is a vector // of objective coefficients at basic variables xB. */ void ssx_eval_pi(SSX *ssx) { int m = ssx->m; mpq_t *coef = ssx->coef; int *Q_col = ssx->Q_col; mpq_t *pi = ssx->pi; int i; /* pi := cB */ for (i = 1; i <= m; i++) mpq_set(pi[i], coef[Q_col[i]]); /* pi := inv(B') * cB */ bfx_btran(ssx->binv, pi); return; } /*---------------------------------------------------------------------- // ssx_eval_dj - compute reduced cost of non-basic variable. // // This routine computes reduced cost d[j] of non-basic variable xN[j] // in the current basic solution as follows: // // d[j] = cN[j] - N[j] * pi, // // where cN[j] is an objective coefficient at xN[j], N[j] is a column // of the augmented constraint matrix (I | -A) corresponding to xN[j], // pi is the vector of simplex multipliers (shadow prices). */ void ssx_eval_dj(SSX *ssx, int j, mpq_t dj) { int m = ssx->m; int n = ssx->n; mpq_t *coef = ssx->coef; int *A_ptr = ssx->A_ptr; int *A_ind = ssx->A_ind; mpq_t *A_val = ssx->A_val; int *Q_col = ssx->Q_col; mpq_t *pi = ssx->pi; int k, ptr, end; mpq_t temp; mpq_init(temp); xassert(1 <= j && j <= n); k = Q_col[m+j]; /* x[k] = xN[j] */ xassert(1 <= k && k <= m+n); /* j-th column of the matrix N is k-th column of the augmented constraint matrix (I | -A) */ if (k <= m) { /* it is a column of the unity matrix I */ mpq_sub(dj, coef[k], pi[k]); } else { /* it is a column of the original constraint matrix -A */ mpq_set(dj, coef[k]); for (ptr = A_ptr[k-m], end = A_ptr[k-m+1]; ptr < end; ptr++) { mpq_mul(temp, A_val[ptr], pi[A_ind[ptr]]); mpq_add(dj, dj, temp); } } mpq_clear(temp); return; } /*---------------------------------------------------------------------- // ssx_eval_cbar - compute reduced costs of all non-basic variables. // // This routine computes the vector of reduced costs pi in the current // basic solution for all non-basic variables, including fixed ones. */ void ssx_eval_cbar(SSX *ssx) { int n = ssx->n; mpq_t *cbar = ssx->cbar; int j; for (j = 1; j <= n; j++) ssx_eval_dj(ssx, j, cbar[j]); return; } /*---------------------------------------------------------------------- // ssx_eval_rho - compute p-th row of the inverse. // // This routine computes p-th row of the matrix inv(B), where B is the // current basis matrix. // // p-th row of the inverse is computed using the following formula: // // rho = inv(B') * e[p], // // where B' is a matrix transposed to B, e[p] is a unity vector, which // contains one in p-th position. */ void ssx_eval_rho(SSX *ssx) { int m = ssx->m; int p = ssx->p; mpq_t *rho = ssx->rho; int i; xassert(1 <= p && p <= m); /* rho := 0 */ for (i = 1; i <= m; i++) mpq_set_si(rho[i], 0, 1); /* rho := e[p] */ mpq_set_si(rho[p], 1, 1); /* rho := inv(B') * rho */ bfx_btran(ssx->binv, rho); return; } /*---------------------------------------------------------------------- // ssx_eval_row - compute pivot row of the simplex table. // // This routine computes p-th (pivot) row of the current simplex table // A~ = - inv(B) * N using the following formula: // // A~[p] = - N' * inv(B') * e[p] = - N' * rho[p], // // where N' is a matrix transposed to the matrix N, rho[p] is p-th row // of the inverse inv(B). */ void ssx_eval_row(SSX *ssx) { int m = ssx->m; int n = ssx->n; int *A_ptr = ssx->A_ptr; int *A_ind = ssx->A_ind; mpq_t *A_val = ssx->A_val; int *Q_col = ssx->Q_col; mpq_t *rho = ssx->rho; mpq_t *ap = ssx->ap; int j, k, ptr; mpq_t temp; mpq_init(temp); for (j = 1; j <= n; j++) { /* ap[j] := - N'[j] * rho (inner product) */ k = Q_col[m+j]; /* x[k] = xN[j] */ if (k <= m) mpq_neg(ap[j], rho[k]); else { mpq_set_si(ap[j], 0, 1); for (ptr = A_ptr[k-m]; ptr < A_ptr[k-m+1]; ptr++) { mpq_mul(temp, A_val[ptr], rho[A_ind[ptr]]); mpq_add(ap[j], ap[j], temp); } } } mpq_clear(temp); return; } /*---------------------------------------------------------------------- // ssx_eval_col - compute pivot column of the simplex table. // // This routine computes q-th (pivot) column of the current simplex // table A~ = - inv(B) * N using the following formula: // // A~[q] = - inv(B) * N[q], // // where N[q] is q-th column of the matrix N corresponding to chosen // non-basic variable xN[q]. */ void ssx_eval_col(SSX *ssx) { int m = ssx->m; int n = ssx->n; int *A_ptr = ssx->A_ptr; int *A_ind = ssx->A_ind; mpq_t *A_val = ssx->A_val; int *Q_col = ssx->Q_col; int q = ssx->q; mpq_t *aq = ssx->aq; int i, k, ptr; xassert(1 <= q && q <= n); /* aq := 0 */ for (i = 1; i <= m; i++) mpq_set_si(aq[i], 0, 1); /* aq := N[q] */ k = Q_col[m+q]; /* x[k] = xN[q] */ if (k <= m) { /* N[q] is a column of the unity matrix I */ mpq_set_si(aq[k], 1, 1); } else { /* N[q] is a column of the original constraint matrix -A */ for (ptr = A_ptr[k-m]; ptr < A_ptr[k-m+1]; ptr++) mpq_neg(aq[A_ind[ptr]], A_val[ptr]); } /* aq := inv(B) * aq */ bfx_ftran(ssx->binv, aq, 1); /* aq := - aq */ for (i = 1; i <= m; i++) mpq_neg(aq[i], aq[i]); return; } /*---------------------------------------------------------------------- // ssx_chuzc - choose pivot column. // // This routine chooses non-basic variable xN[q] whose reduced cost // indicates possible improving of the objective function to enter it // in the basis. // // Currently the standard (textbook) pricing is used, i.e. that // non-basic variable is preferred which has greatest reduced cost (in // magnitude). // // If xN[q] has been chosen, the routine stores its number q and also // sets the flag q_dir that indicates direction in which xN[q] has to // change (+1 means increasing, -1 means decreasing). // // If the choice cannot be made, because the current basic solution is // dual feasible, the routine sets the number q to 0. */ void ssx_chuzc(SSX *ssx) { int m = ssx->m; int n = ssx->n; int dir = (ssx->dir == SSX_MIN ? +1 : -1); int *Q_col = ssx->Q_col; int *stat = ssx->stat; mpq_t *cbar = ssx->cbar; int j, k, s, q, q_dir; double best, temp; /* nothing is chosen so far */ q = 0, q_dir = 0, best = 0.0; /* look through the list of non-basic variables */ for (j = 1; j <= n; j++) { k = Q_col[m+j]; /* x[k] = xN[j] */ s = dir * mpq_sgn(cbar[j]); if ((stat[k] == SSX_NF || stat[k] == SSX_NL) && s < 0 || (stat[k] == SSX_NF || stat[k] == SSX_NU) && s > 0) { /* reduced cost of xN[j] indicates possible improving of the objective function */ temp = fabs(mpq_get_d(cbar[j])); xassert(temp != 0.0); if (q == 0 || best < temp) q = j, q_dir = - s, best = temp; } } ssx->q = q, ssx->q_dir = q_dir; return; } /*---------------------------------------------------------------------- // ssx_chuzr - choose pivot row. // // This routine looks through elements of q-th column of the simplex // table and chooses basic variable xB[p] which should leave the basis. // // The choice is based on the standard (textbook) ratio test. // // If xB[p] has been chosen, the routine stores its number p and also // sets its non-basic status p_stat which should be assigned to xB[p] // when it has left the basis and become xN[q]. // // Special case p < 0 means that xN[q] is double-bounded variable and // it reaches its opposite bound before any basic variable does that, // so the current basis remains unchanged. // // If the choice cannot be made, because xN[q] can infinitely change in // the feasible direction, the routine sets the number p to 0. */ void ssx_chuzr(SSX *ssx) { int m = ssx->m; int n = ssx->n; int *type = ssx->type; mpq_t *lb = ssx->lb; mpq_t *ub = ssx->ub; int *Q_col = ssx->Q_col; mpq_t *bbar = ssx->bbar; int q = ssx->q; mpq_t *aq = ssx->aq; int q_dir = ssx->q_dir; int i, k, s, t, p, p_stat; mpq_t teta, temp; mpq_init(teta); mpq_init(temp); xassert(1 <= q && q <= n); xassert(q_dir == +1 || q_dir == -1); /* nothing is chosen so far */ p = 0, p_stat = 0; /* look through the list of basic variables */ for (i = 1; i <= m; i++) { s = q_dir * mpq_sgn(aq[i]); if (s < 0) { /* xB[i] decreases */ k = Q_col[i]; /* x[k] = xB[i] */ t = type[k]; if (t == SSX_LO || t == SSX_DB || t == SSX_FX) { /* xB[i] has finite lower bound */ mpq_sub(temp, bbar[i], lb[k]); mpq_div(temp, temp, aq[i]); mpq_abs(temp, temp); if (p == 0 || mpq_cmp(teta, temp) > 0) { p = i; p_stat = (t == SSX_FX ? SSX_NS : SSX_NL); mpq_set(teta, temp); } } } else if (s > 0) { /* xB[i] increases */ k = Q_col[i]; /* x[k] = xB[i] */ t = type[k]; if (t == SSX_UP || t == SSX_DB || t == SSX_FX) { /* xB[i] has finite upper bound */ mpq_sub(temp, bbar[i], ub[k]); mpq_div(temp, temp, aq[i]); mpq_abs(temp, temp); if (p == 0 || mpq_cmp(teta, temp) > 0) { p = i; p_stat = (t == SSX_FX ? SSX_NS : SSX_NU); mpq_set(teta, temp); } } } /* if something has been chosen and the ratio test indicates exact degeneracy, the search can be finished */ if (p != 0 && mpq_sgn(teta) == 0) break; } /* if xN[q] is double-bounded, check if it can reach its opposite bound before any basic variable */ k = Q_col[m+q]; /* x[k] = xN[q] */ if (type[k] == SSX_DB) { mpq_sub(temp, ub[k], lb[k]); if (p == 0 || mpq_cmp(teta, temp) > 0) { p = -1; p_stat = -1; mpq_set(teta, temp); } } ssx->p = p; ssx->p_stat = p_stat; /* if xB[p] has been chosen, determine its actual change in the adjacent basis (it has the same sign as q_dir) */ if (p != 0) { xassert(mpq_sgn(teta) >= 0); if (q_dir > 0) mpq_set(ssx->delta, teta); else mpq_neg(ssx->delta, teta); } mpq_clear(teta); mpq_clear(temp); return; } /*---------------------------------------------------------------------- // ssx_update_bbar - update values of basic variables. // // This routine recomputes the current values of basic variables for // the adjacent basis. // // The simplex table for the current basis is the following: // // xB[i] = sum{j in 1..n} alfa[i,j] * xN[q], i = 1,...,m // // therefore // // delta xB[i] = alfa[i,q] * delta xN[q], i = 1,...,m // // where delta xN[q] = xN.new[q] - xN[q] is the change of xN[q] in the // adjacent basis, and delta xB[i] = xB.new[i] - xB[i] is the change of // xB[i]. This gives formulae for recomputing values of xB[i]: // // xB.new[p] = xN[q] + delta xN[q] // // (because xN[q] becomes xB[p] in the adjacent basis), and // // xB.new[i] = xB[i] + alfa[i,q] * delta xN[q], i != p // // for other basic variables. */ void ssx_update_bbar(SSX *ssx) { int m = ssx->m; int n = ssx->n; mpq_t *bbar = ssx->bbar; mpq_t *cbar = ssx->cbar; int p = ssx->p; int q = ssx->q; mpq_t *aq = ssx->aq; int i; mpq_t temp; mpq_init(temp); xassert(1 <= q && q <= n); if (p < 0) { /* xN[q] is double-bounded and goes to its opposite bound */ /* nop */; } else { /* xN[q] becomes xB[p] in the adjacent basis */ /* xB.new[p] = xN[q] + delta xN[q] */ xassert(1 <= p && p <= m); ssx_get_xNj(ssx, q, temp); mpq_add(bbar[p], temp, ssx->delta); } /* update values of other basic variables depending on xN[q] */ for (i = 1; i <= m; i++) { if (i == p) continue; /* xB.new[i] = xB[i] + alfa[i,q] * delta xN[q] */ if (mpq_sgn(aq[i]) == 0) continue; mpq_mul(temp, aq[i], ssx->delta); mpq_add(bbar[i], bbar[i], temp); } #if 1 /* update value of the objective function */ /* z.new = z + d[q] * delta xN[q] */ mpq_mul(temp, cbar[q], ssx->delta); mpq_add(bbar[0], bbar[0], temp); #endif mpq_clear(temp); return; } /*---------------------------------------------------------------------- -- ssx_update_pi - update simplex multipliers. -- -- This routine recomputes the vector of simplex multipliers for the -- adjacent basis. */ void ssx_update_pi(SSX *ssx) { int m = ssx->m; int n = ssx->n; mpq_t *pi = ssx->pi; mpq_t *cbar = ssx->cbar; int p = ssx->p; int q = ssx->q; mpq_t *aq = ssx->aq; mpq_t *rho = ssx->rho; int i; mpq_t new_dq, temp; mpq_init(new_dq); mpq_init(temp); xassert(1 <= p && p <= m); xassert(1 <= q && q <= n); /* compute d[q] in the adjacent basis */ mpq_div(new_dq, cbar[q], aq[p]); /* update the vector of simplex multipliers */ for (i = 1; i <= m; i++) { if (mpq_sgn(rho[i]) == 0) continue; mpq_mul(temp, new_dq, rho[i]); mpq_sub(pi[i], pi[i], temp); } mpq_clear(new_dq); mpq_clear(temp); return; } /*---------------------------------------------------------------------- // ssx_update_cbar - update reduced costs of non-basic variables. // // This routine recomputes the vector of reduced costs of non-basic // variables for the adjacent basis. */ void ssx_update_cbar(SSX *ssx) { int m = ssx->m; int n = ssx->n; mpq_t *cbar = ssx->cbar; int p = ssx->p; int q = ssx->q; mpq_t *ap = ssx->ap; int j; mpq_t temp; mpq_init(temp); xassert(1 <= p && p <= m); xassert(1 <= q && q <= n); /* compute d[q] in the adjacent basis */ /* d.new[q] = d[q] / alfa[p,q] */ mpq_div(cbar[q], cbar[q], ap[q]); /* update reduced costs of other non-basic variables */ for (j = 1; j <= n; j++) { if (j == q) continue; /* d.new[j] = d[j] - (alfa[p,j] / alfa[p,q]) * d[q] */ if (mpq_sgn(ap[j]) == 0) continue; mpq_mul(temp, ap[j], cbar[q]); mpq_sub(cbar[j], cbar[j], temp); } mpq_clear(temp); return; } /*---------------------------------------------------------------------- // ssx_change_basis - change current basis to adjacent one. // // This routine changes the current basis to the adjacent one swapping // basic variable xB[p] and non-basic variable xN[q]. */ void ssx_change_basis(SSX *ssx) { int m = ssx->m; int n = ssx->n; int *type = ssx->type; int *stat = ssx->stat; int *Q_row = ssx->Q_row; int *Q_col = ssx->Q_col; int p = ssx->p; int q = ssx->q; int p_stat = ssx->p_stat; int k, kp, kq; if (p < 0) { /* special case: xN[q] goes to its opposite bound */ xassert(1 <= q && q <= n); k = Q_col[m+q]; /* x[k] = xN[q] */ xassert(type[k] == SSX_DB); switch (stat[k]) { case SSX_NL: stat[k] = SSX_NU; break; case SSX_NU: stat[k] = SSX_NL; break; default: xassert(stat != stat); } } else { /* xB[p] leaves the basis, xN[q] enters the basis */ xassert(1 <= p && p <= m); xassert(1 <= q && q <= n); kp = Q_col[p]; /* x[kp] = xB[p] */ kq = Q_col[m+q]; /* x[kq] = xN[q] */ /* check non-basic status of xB[p] which becomes xN[q] */ switch (type[kp]) { case SSX_FR: xassert(p_stat == SSX_NF); break; case SSX_LO: xassert(p_stat == SSX_NL); break; case SSX_UP: xassert(p_stat == SSX_NU); break; case SSX_DB: xassert(p_stat == SSX_NL || p_stat == SSX_NU); break; case SSX_FX: xassert(p_stat == SSX_NS); break; default: xassert(type != type); } /* swap xB[p] and xN[q] */ stat[kp] = (char)p_stat, stat[kq] = SSX_BS; Q_row[kp] = m+q, Q_row[kq] = p; Q_col[p] = kq, Q_col[m+q] = kp; /* update factorization of the basis matrix */ if (bfx_update(ssx->binv, p)) { if (ssx_factorize(ssx)) xassert(("Internal error: basis matrix is singular", 0)); } } return; } /*---------------------------------------------------------------------- // ssx_delete - delete simplex solver workspace. // // This routine deletes the simplex solver workspace freeing all the // memory allocated to this object. */ void ssx_delete(SSX *ssx) { int m = ssx->m; int n = ssx->n; int nnz = ssx->A_ptr[n+1]-1; int i, j, k; xfree(ssx->type); for (k = 1; k <= m+n; k++) mpq_clear(ssx->lb[k]); xfree(ssx->lb); for (k = 1; k <= m+n; k++) mpq_clear(ssx->ub[k]); xfree(ssx->ub); for (k = 0; k <= m+n; k++) mpq_clear(ssx->coef[k]); xfree(ssx->coef); xfree(ssx->A_ptr); xfree(ssx->A_ind); for (k = 1; k <= nnz; k++) mpq_clear(ssx->A_val[k]); xfree(ssx->A_val); xfree(ssx->stat); xfree(ssx->Q_row); xfree(ssx->Q_col); bfx_delete_binv(ssx->binv); for (i = 0; i <= m; i++) mpq_clear(ssx->bbar[i]); xfree(ssx->bbar); for (i = 1; i <= m; i++) mpq_clear(ssx->pi[i]); xfree(ssx->pi); for (j = 1; j <= n; j++) mpq_clear(ssx->cbar[j]); xfree(ssx->cbar); for (i = 1; i <= m; i++) mpq_clear(ssx->rho[i]); xfree(ssx->rho); for (j = 1; j <= n; j++) mpq_clear(ssx->ap[j]); xfree(ssx->ap); for (i = 1; i <= m; i++) mpq_clear(ssx->aq[i]); xfree(ssx->aq); mpq_clear(ssx->delta); xfree(ssx); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpbfd.h0000644000076500000240000000507413524616144025014 0ustar tamasstaff00000000000000/* glpbfd.h (LP basis factorization driver) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPBFD_H #define GLPBFD_H #ifndef GLPBFD_PRIVATE typedef struct { double _opaque_bfd[100]; } BFD; #endif /* return codes: */ #define BFD_ESING 1 /* singular matrix */ #define BFD_ECOND 2 /* ill-conditioned matrix */ #define BFD_ECHECK 3 /* insufficient accuracy */ #define BFD_ELIMIT 4 /* update limit reached */ #define BFD_EROOM 5 /* SVA overflow */ #define bfd_create_it _glp_bfd_create_it BFD *bfd_create_it(void); /* create LP basis factorization */ #define bfd_set_parm _glp_bfd_set_parm void bfd_set_parm(BFD *bfd, const void *parm); /* change LP basis factorization control parameters */ #define bfd_factorize _glp_bfd_factorize int bfd_factorize(BFD *bfd, int m, const int bh[], int (*col) (void *info, int j, int ind[], double val[]), void *info); /* compute LP basis factorization */ #define bfd_ftran _glp_bfd_ftran void bfd_ftran(BFD *bfd, double x[]); /* perform forward transformation (solve system B*x = b) */ #define bfd_btran _glp_bfd_btran void bfd_btran(BFD *bfd, double x[]); /* perform backward transformation (solve system B'*x = b) */ #define bfd_update_it _glp_bfd_update_it int bfd_update_it(BFD *bfd, int j, int bh, int len, const int ind[], const double val[]); /* update LP basis factorization */ #define bfd_get_count _glp_bfd_get_count int bfd_get_count(BFD *bfd); /* determine factorization update count */ #define bfd_delete_it _glp_bfd_delete_it void bfd_delete_it(BFD *bfd); /* delete LP basis factorization */ #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpnpp05.c0000644000076500000240000006377513524616144025232 0ustar tamasstaff00000000000000/* glpnpp05.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glpnpp.h" /*********************************************************************** * NAME * * npp_clean_prob - perform initial LP/MIP processing * * SYNOPSIS * * #include "glpnpp.h" * void npp_clean_prob(NPP *npp); * * DESCRIPTION * * The routine npp_clean_prob performs initial LP/MIP processing that * currently includes: * * 1) removing free rows; * * 2) replacing double-sided constraint rows with almost identical * bounds, by equality constraint rows; * * 3) removing fixed columns; * * 4) replacing double-bounded columns with almost identical bounds by * fixed columns and removing those columns; * * 5) initial processing constraint coefficients (not implemented); * * 6) initial processing objective coefficients (not implemented). */ void npp_clean_prob(NPP *npp) { /* perform initial LP/MIP processing */ NPPROW *row, *next_row; NPPCOL *col, *next_col; int ret; xassert(npp == npp); /* process rows which originally are free */ for (row = npp->r_head; row != NULL; row = next_row) { next_row = row->next; if (row->lb == -DBL_MAX && row->ub == +DBL_MAX) { /* process free row */ #ifdef GLP_DEBUG xprintf("1"); #endif npp_free_row(npp, row); /* row was deleted */ } } /* process rows which originally are double-sided inequalities */ for (row = npp->r_head; row != NULL; row = next_row) { next_row = row->next; if (row->lb != -DBL_MAX && row->ub != +DBL_MAX && row->lb < row->ub) { ret = npp_make_equality(npp, row); if (ret == 0) ; else if (ret == 1) { /* row was replaced by equality constraint */ #ifdef GLP_DEBUG xprintf("2"); #endif } else xassert(ret != ret); } } /* process columns which are originally fixed */ for (col = npp->c_head; col != NULL; col = next_col) { next_col = col->next; if (col->lb == col->ub) { /* process fixed column */ #ifdef GLP_DEBUG xprintf("3"); #endif npp_fixed_col(npp, col); /* column was deleted */ } } /* process columns which are originally double-bounded */ for (col = npp->c_head; col != NULL; col = next_col) { next_col = col->next; if (col->lb != -DBL_MAX && col->ub != +DBL_MAX && col->lb < col->ub) { ret = npp_make_fixed(npp, col); if (ret == 0) ; else if (ret == 1) { /* column was replaced by fixed column; process it */ #ifdef GLP_DEBUG xprintf("4"); #endif npp_fixed_col(npp, col); /* column was deleted */ } } } return; } /*********************************************************************** * NAME * * npp_process_row - perform basic row processing * * SYNOPSIS * * #include "glpnpp.h" * int npp_process_row(NPP *npp, NPPROW *row, int hard); * * DESCRIPTION * * The routine npp_process_row performs basic row processing that * currently includes: * * 1) removing empty row; * * 2) removing equality constraint row singleton and corresponding * column; * * 3) removing inequality constraint row singleton and corresponding * column if it was fixed; * * 4) performing general row analysis; * * 5) removing redundant row bounds; * * 6) removing forcing row and corresponding columns; * * 7) removing row which becomes free due to redundant bounds; * * 8) computing implied bounds for all columns in the row and using * them to strengthen current column bounds (MIP only, optional, * performed if the flag hard is on). * * Additionally the routine may activate affected rows and/or columns * for further processing. * * RETURNS * * 0 success; * * GLP_ENOPFS primal/integer infeasibility detected; * * GLP_ENODFS dual infeasibility detected. */ int npp_process_row(NPP *npp, NPPROW *row, int hard) { /* perform basic row processing */ NPPCOL *col; NPPAIJ *aij, *next_aij, *aaa; int ret; /* row must not be free */ xassert(!(row->lb == -DBL_MAX && row->ub == +DBL_MAX)); /* start processing row */ if (row->ptr == NULL) { /* empty row */ ret = npp_empty_row(npp, row); if (ret == 0) { /* row was deleted */ #ifdef GLP_DEBUG xprintf("A"); #endif return 0; } else if (ret == 1) { /* primal infeasibility */ return GLP_ENOPFS; } else xassert(ret != ret); } if (row->ptr->r_next == NULL) { /* row singleton */ col = row->ptr->col; if (row->lb == row->ub) { /* equality constraint */ ret = npp_eq_singlet(npp, row); if (ret == 0) { /* column was fixed, row was deleted */ #ifdef GLP_DEBUG xprintf("B"); #endif /* activate rows affected by column */ for (aij = col->ptr; aij != NULL; aij = aij->c_next) npp_activate_row(npp, aij->row); /* process fixed column */ npp_fixed_col(npp, col); /* column was deleted */ return 0; } else if (ret == 1 || ret == 2) { /* primal/integer infeasibility */ return GLP_ENOPFS; } else xassert(ret != ret); } else { /* inequality constraint */ ret = npp_ineq_singlet(npp, row); if (0 <= ret && ret <= 3) { /* row was deleted */ #ifdef GLP_DEBUG xprintf("C"); #endif /* activate column, since its length was changed due to row deletion */ npp_activate_col(npp, col); if (ret >= 2) { /* column bounds changed significantly or column was fixed */ /* activate rows affected by column */ for (aij = col->ptr; aij != NULL; aij = aij->c_next) npp_activate_row(npp, aij->row); } if (ret == 3) { /* column was fixed; process it */ #ifdef GLP_DEBUG xprintf("D"); #endif npp_fixed_col(npp, col); /* column was deleted */ } return 0; } else if (ret == 4) { /* primal infeasibility */ return GLP_ENOPFS; } else xassert(ret != ret); } } #if 0 /* sometimes this causes too large round-off errors; probably pivot coefficient should be chosen more carefully */ if (row->ptr->r_next->r_next == NULL) { /* row doubleton */ if (row->lb == row->ub) { /* equality constraint */ if (!(row->ptr->col->is_int || row->ptr->r_next->col->is_int)) { /* both columns are continuous */ NPPCOL *q; q = npp_eq_doublet(npp, row); if (q != NULL) { /* column q was eliminated */ #ifdef GLP_DEBUG xprintf("E"); #endif /* now column q is singleton of type "implied slack variable"; we process it here to make sure that on recovering basic solution the row is always active equality constraint (as required by the routine rcv_eq_doublet) */ xassert(npp_process_col(npp, q) == 0); /* column q was deleted; note that row p also may be deleted */ return 0; } } } } #endif /* general row analysis */ ret = npp_analyze_row(npp, row); xassert(0x00 <= ret && ret <= 0xFF); if (ret == 0x33) { /* row bounds are inconsistent with column bounds */ return GLP_ENOPFS; } if ((ret & 0x0F) == 0x00) { /* row lower bound does not exist or redundant */ if (row->lb != -DBL_MAX) { /* remove redundant row lower bound */ #ifdef GLP_DEBUG xprintf("F"); #endif npp_inactive_bound(npp, row, 0); } } else if ((ret & 0x0F) == 0x01) { /* row lower bound can be active */ /* see below */ } else if ((ret & 0x0F) == 0x02) { /* row lower bound is a forcing bound */ #ifdef GLP_DEBUG xprintf("G"); #endif /* process forcing row */ if (npp_forcing_row(npp, row, 0) == 0) fixup: { /* columns were fixed, row was made free */ for (aij = row->ptr; aij != NULL; aij = next_aij) { /* process column fixed by forcing row */ #ifdef GLP_DEBUG xprintf("H"); #endif col = aij->col; next_aij = aij->r_next; /* activate rows affected by column */ for (aaa = col->ptr; aaa != NULL; aaa = aaa->c_next) npp_activate_row(npp, aaa->row); /* process fixed column */ npp_fixed_col(npp, col); /* column was deleted */ } /* process free row (which now is empty due to deletion of all its columns) */ npp_free_row(npp, row); /* row was deleted */ return 0; } } else xassert(ret != ret); if ((ret & 0xF0) == 0x00) { /* row upper bound does not exist or redundant */ if (row->ub != +DBL_MAX) { /* remove redundant row upper bound */ #ifdef GLP_DEBUG xprintf("I"); #endif npp_inactive_bound(npp, row, 1); } } else if ((ret & 0xF0) == 0x10) { /* row upper bound can be active */ /* see below */ } else if ((ret & 0xF0) == 0x20) { /* row upper bound is a forcing bound */ #ifdef GLP_DEBUG xprintf("J"); #endif /* process forcing row */ if (npp_forcing_row(npp, row, 1) == 0) goto fixup; } else xassert(ret != ret); if (row->lb == -DBL_MAX && row->ub == +DBL_MAX) { /* row became free due to redundant bounds removal */ #ifdef GLP_DEBUG xprintf("K"); #endif /* activate its columns, since their length will change due to row deletion */ for (aij = row->ptr; aij != NULL; aij = aij->r_next) npp_activate_col(npp, aij->col); /* process free row */ npp_free_row(npp, row); /* row was deleted */ return 0; } #if 1 /* 23/XII-2009 */ /* row lower and/or upper bounds can be active */ if (npp->sol == GLP_MIP && hard) { /* improve current column bounds (optional) */ if (npp_improve_bounds(npp, row, 1) < 0) return GLP_ENOPFS; } #endif return 0; } /*********************************************************************** * NAME * * npp_improve_bounds - improve current column bounds * * SYNOPSIS * * #include "glpnpp.h" * int npp_improve_bounds(NPP *npp, NPPROW *row, int flag); * * DESCRIPTION * * The routine npp_improve_bounds analyzes specified row (inequality * or equality constraint) to determine implied column bounds and then * uses these bounds to improve (strengthen) current column bounds. * * If the flag is on and current column bounds changed significantly * or the column was fixed, the routine activate rows affected by the * column for further processing. (This feature is intended to be used * in the main loop of the routine npp_process_row.) * * NOTE: This operation can be used for MIP problem only. * * RETURNS * * The routine npp_improve_bounds returns the number of significantly * changed bounds plus the number of column having been fixed due to * bound improvements. However, if the routine detects primal/integer * infeasibility, it returns a negative value. */ int npp_improve_bounds(NPP *npp, NPPROW *row, int flag) { /* improve current column bounds */ NPPCOL *col; NPPAIJ *aij, *next_aij, *aaa; int kase, ret, count = 0; double lb, ub; xassert(npp->sol == GLP_MIP); /* row must not be free */ xassert(!(row->lb == -DBL_MAX && row->ub == +DBL_MAX)); /* determine implied column bounds */ npp_implied_bounds(npp, row); /* and use these bounds to strengthen current column bounds */ for (aij = row->ptr; aij != NULL; aij = next_aij) { col = aij->col; next_aij = aij->r_next; for (kase = 0; kase <= 1; kase++) { /* save current column bounds */ lb = col->lb, ub = col->ub; if (kase == 0) { /* process implied column lower bound */ if (col->ll.ll == -DBL_MAX) continue; ret = npp_implied_lower(npp, col, col->ll.ll); } else { /* process implied column upper bound */ if (col->uu.uu == +DBL_MAX) continue; ret = npp_implied_upper(npp, col, col->uu.uu); } if (ret == 0 || ret == 1) { /* current column bounds did not change or changed, but not significantly; restore current column bounds */ col->lb = lb, col->ub = ub; } else if (ret == 2 || ret == 3) { /* current column bounds changed significantly or column was fixed */ #ifdef GLP_DEBUG xprintf("L"); #endif count++; /* activate other rows affected by column, if required */ if (flag) { for (aaa = col->ptr; aaa != NULL; aaa = aaa->c_next) { if (aaa->row != row) npp_activate_row(npp, aaa->row); } } if (ret == 3) { /* process fixed column */ #ifdef GLP_DEBUG xprintf("M"); #endif npp_fixed_col(npp, col); /* column was deleted */ break; /* for kase */ } } else if (ret == 4) { /* primal/integer infeasibility */ return -1; } else xassert(ret != ret); } } return count; } /*********************************************************************** * NAME * * npp_process_col - perform basic column processing * * SYNOPSIS * * #include "glpnpp.h" * int npp_process_col(NPP *npp, NPPCOL *col); * * DESCRIPTION * * The routine npp_process_col performs basic column processing that * currently includes: * * 1) fixing and removing empty column; * * 2) removing column singleton, which is implied slack variable, and * corresponding row if it becomes free; * * 3) removing bounds of column, which is implied free variable, and * replacing corresponding row by equality constraint. * * Additionally the routine may activate affected rows and/or columns * for further processing. * * RETURNS * * 0 success; * * GLP_ENOPFS primal/integer infeasibility detected; * * GLP_ENODFS dual infeasibility detected. */ int npp_process_col(NPP *npp, NPPCOL *col) { /* perform basic column processing */ NPPROW *row; NPPAIJ *aij; int ret; /* column must not be fixed */ xassert(col->lb < col->ub); /* start processing column */ if (col->ptr == NULL) { /* empty column */ ret = npp_empty_col(npp, col); if (ret == 0) { /* column was fixed and deleted */ #ifdef GLP_DEBUG xprintf("N"); #endif return 0; } else if (ret == 1) { /* dual infeasibility */ return GLP_ENODFS; } else xassert(ret != ret); } if (col->ptr->c_next == NULL) { /* column singleton */ row = col->ptr->row; if (row->lb == row->ub) { /* equality constraint */ if (!col->is_int) slack: { /* implied slack variable */ #ifdef GLP_DEBUG xprintf("O"); #endif npp_implied_slack(npp, col); /* column was deleted */ if (row->lb == -DBL_MAX && row->ub == +DBL_MAX) { /* row became free due to implied slack variable */ #ifdef GLP_DEBUG xprintf("P"); #endif /* activate columns affected by row */ for (aij = row->ptr; aij != NULL; aij = aij->r_next) npp_activate_col(npp, aij->col); /* process free row */ npp_free_row(npp, row); /* row was deleted */ } else { /* row became inequality constraint; activate it since its length changed due to column deletion */ npp_activate_row(npp, row); } return 0; } } else { /* inequality constraint */ if (!col->is_int) { ret = npp_implied_free(npp, col); if (ret == 0) { /* implied free variable */ #ifdef GLP_DEBUG xprintf("Q"); #endif /* column bounds were removed, row was replaced by equality constraint */ goto slack; } else if (ret == 1) { /* column is not implied free variable, because its lower and/or upper bounds can be active */ } else if (ret == 2) { /* dual infeasibility */ return GLP_ENODFS; } } } } /* column still exists */ return 0; } /*********************************************************************** * NAME * * npp_process_prob - perform basic LP/MIP processing * * SYNOPSIS * * #include "glpnpp.h" * int npp_process_prob(NPP *npp, int hard); * * DESCRIPTION * * The routine npp_process_prob performs basic LP/MIP processing that * currently includes: * * 1) initial LP/MIP processing (see the routine npp_clean_prob), * * 2) basic row processing (see the routine npp_process_row), and * * 3) basic column processing (see the routine npp_process_col). * * If the flag hard is on, the routine attempts to improve current * column bounds multiple times within the main processing loop, in * which case this feature may take a time. Otherwise, if the flag hard * is off, improving column bounds is performed only once at the end of * the main loop. (Note that this feature is used for MIP only.) * * The routine uses two sets: the set of active rows and the set of * active columns. Rows/columns are marked by a flag (the field temp in * NPPROW/NPPCOL). If the flag is non-zero, the row/column is active, * in which case it is placed in the beginning of the row/column list; * otherwise, if the flag is zero, the row/column is inactive, in which * case it is placed in the end of the row/column list. If a row/column * being currently processed may affect other rows/columns, the latters * are activated for further processing. * * RETURNS * * 0 success; * * GLP_ENOPFS primal/integer infeasibility detected; * * GLP_ENODFS dual infeasibility detected. */ int npp_process_prob(NPP *npp, int hard) { /* perform basic LP/MIP processing */ NPPROW *row; NPPCOL *col; int processing, ret; /* perform initial LP/MIP processing */ npp_clean_prob(npp); /* activate all remaining rows and columns */ for (row = npp->r_head; row != NULL; row = row->next) row->temp = 1; for (col = npp->c_head; col != NULL; col = col->next) col->temp = 1; /* main processing loop */ processing = 1; while (processing) { processing = 0; /* process all active rows */ for (;;) { row = npp->r_head; if (row == NULL || !row->temp) break; npp_deactivate_row(npp, row); ret = npp_process_row(npp, row, hard); if (ret != 0) goto done; processing = 1; } /* process all active columns */ for (;;) { col = npp->c_head; if (col == NULL || !col->temp) break; npp_deactivate_col(npp, col); ret = npp_process_col(npp, col); if (ret != 0) goto done; processing = 1; } } #if 1 /* 23/XII-2009 */ if (npp->sol == GLP_MIP && !hard) { /* improve current column bounds (optional) */ for (row = npp->r_head; row != NULL; row = row->next) { if (npp_improve_bounds(npp, row, 0) < 0) { ret = GLP_ENOPFS; goto done; } } } #endif /* all seems ok */ ret = 0; done: xassert(ret == 0 || ret == GLP_ENOPFS || ret == GLP_ENODFS); #ifdef GLP_DEBUG xprintf("\n"); #endif return ret; } /**********************************************************************/ int npp_simplex(NPP *npp, const glp_smcp *parm) { /* process LP prior to applying primal/dual simplex method */ int ret; xassert(npp->sol == GLP_SOL); xassert(parm == parm); ret = npp_process_prob(npp, 0); return ret; } /**********************************************************************/ int npp_integer(NPP *npp, const glp_iocp *parm) { /* process MIP prior to applying branch-and-bound method */ NPPROW *row, *prev_row; NPPCOL *col; NPPAIJ *aij; int count, ret; xassert(npp->sol == GLP_MIP); xassert(parm == parm); /*==============================================================*/ /* perform basic MIP processing */ ret = npp_process_prob(npp, 1); if (ret != 0) goto done; /*==============================================================*/ /* binarize problem, if required */ if (parm->binarize) npp_binarize_prob(npp); /*==============================================================*/ /* identify hidden packing inequalities */ count = 0; /* new rows will be added to the end of the row list, so we go from the end to beginning of the row list */ for (row = npp->r_tail; row != NULL; row = prev_row) { prev_row = row->prev; /* skip free row */ if (row->lb == -DBL_MAX && row->ub == +DBL_MAX) continue; /* skip equality constraint */ if (row->lb == row->ub) continue; /* skip row having less than two variables */ if (row->ptr == NULL || row->ptr->r_next == NULL) continue; /* skip row having non-binary variables */ for (aij = row->ptr; aij != NULL; aij = aij->r_next) { col = aij->col; if (!(col->is_int && col->lb == 0.0 && col->ub == 1.0)) break; } if (aij != NULL) continue; count += npp_hidden_packing(npp, row); } if (count > 0) xprintf("%d hidden packing inequaliti(es) were detected\n", count); /*==============================================================*/ /* identify hidden covering inequalities */ count = 0; /* new rows will be added to the end of the row list, so we go from the end to beginning of the row list */ for (row = npp->r_tail; row != NULL; row = prev_row) { prev_row = row->prev; /* skip free row */ if (row->lb == -DBL_MAX && row->ub == +DBL_MAX) continue; /* skip equality constraint */ if (row->lb == row->ub) continue; /* skip row having less than three variables */ if (row->ptr == NULL || row->ptr->r_next == NULL || row->ptr->r_next->r_next == NULL) continue; /* skip row having non-binary variables */ for (aij = row->ptr; aij != NULL; aij = aij->r_next) { col = aij->col; if (!(col->is_int && col->lb == 0.0 && col->ub == 1.0)) break; } if (aij != NULL) continue; count += npp_hidden_covering(npp, row); } if (count > 0) xprintf("%d hidden covering inequaliti(es) were detected\n", count); /*==============================================================*/ /* reduce inequality constraint coefficients */ count = 0; /* new rows will be added to the end of the row list, so we go from the end to beginning of the row list */ for (row = npp->r_tail; row != NULL; row = prev_row) { prev_row = row->prev; /* skip equality constraint */ if (row->lb == row->ub) continue; count += npp_reduce_ineq_coef(npp, row); } if (count > 0) xprintf("%d constraint coefficient(s) were reduced\n", count); /*==============================================================*/ #ifdef GLP_DEBUG routine(npp); #endif /*==============================================================*/ /* all seems ok */ ret = 0; done: return ret; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpios11.c0000644000076500000240000002503413524616144025206 0ustar tamasstaff00000000000000/* glpios11.c (process cuts stored in the local cut pool) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wsign-conversion" #endif #include "glpios.h" /*********************************************************************** * NAME * * ios_process_cuts - process cuts stored in the local cut pool * * SYNOPSIS * * #include "glpios.h" * void ios_process_cuts(glp_tree *T); * * DESCRIPTION * * The routine ios_process_cuts analyzes each cut currently stored in * the local cut pool, which must be non-empty, and either adds the cut * to the current subproblem or just discards it. All cuts are assumed * to be locally valid. On exit the local cut pool remains unchanged. * * REFERENCES * * 1. E.Balas, S.Ceria, G.Cornuejols, "Mixed 0-1 Programming by * Lift-and-Project in a Branch-and-Cut Framework", Management Sc., * 42 (1996) 1229-1246. * * 2. G.Andreello, A.Caprara, and M.Fischetti, "Embedding Cuts in * a Branch&Cut Framework: a Computational Study with {0,1/2}-Cuts", * Preliminary Draft, October 28, 2003, pp.6-8. */ struct info { /* estimated cut efficiency */ IOSCUT *cut; /* pointer to cut in the cut pool */ char flag; /* if this flag is set, the cut is included into the current subproblem */ double eff; /* cut efficacy (normalized residual) */ double deg; /* lower bound to objective degradation */ }; static int fcmp(const void *arg1, const void *arg2) { const struct info *info1 = arg1, *info2 = arg2; if (info1->deg == 0.0 && info2->deg == 0.0) { if (info1->eff > info2->eff) return -1; if (info1->eff < info2->eff) return +1; } else { if (info1->deg > info2->deg) return -1; if (info1->deg < info2->deg) return +1; } return 0; } static double parallel(IOSCUT *a, IOSCUT *b, double work[]); void ios_process_cuts(glp_tree *T) { IOSPOOL *pool; IOSCUT *cut; IOSAIJ *aij; struct info *info; int k, kk, max_cuts, len, ret, *ind; double *val, *work; /* the current subproblem must exist */ xassert(T->curr != NULL); /* the pool must exist and be non-empty */ pool = T->local; xassert(pool != NULL); xassert(pool->size > 0); /* allocate working arrays */ info = xcalloc(1+pool->size, sizeof(struct info)); ind = xcalloc(1+T->n, sizeof(int)); val = xcalloc(1+T->n, sizeof(double)); work = xcalloc(1+T->n, sizeof(double)); for (k = 1; k <= T->n; k++) work[k] = 0.0; /* build the list of cuts stored in the cut pool */ for (k = 0, cut = pool->head; cut != NULL; cut = cut->next) k++, info[k].cut = cut, info[k].flag = 0; xassert(k == pool->size); /* estimate efficiency of all cuts in the cut pool */ for (k = 1; k <= pool->size; k++) { double temp, dy, dz; cut = info[k].cut; /* build the vector of cut coefficients and compute its Euclidean norm */ len = 0; temp = 0.0; for (aij = cut->ptr; aij != NULL; aij = aij->next) { xassert(1 <= aij->j && aij->j <= T->n); len++, ind[len] = aij->j, val[len] = aij->val; temp += aij->val * aij->val; } if (temp < DBL_EPSILON * DBL_EPSILON) temp = DBL_EPSILON; /* transform the cut to express it only through non-basic (auxiliary and structural) variables */ len = glp_transform_row(T->mip, len, ind, val); /* determine change in the cut value and in the objective value for the adjacent basis by simulating one step of the dual simplex */ ret = _glp_analyze_row(T->mip, len, ind, val, cut->type, cut->rhs, 1e-9, NULL, NULL, NULL, NULL, &dy, &dz); /* determine normalized residual and lower bound to objective degradation */ if (ret == 0) { info[k].eff = fabs(dy) / sqrt(temp); /* if some reduced costs violates (slightly) their zero bounds (i.e. have wrong signs) due to round-off errors, dz also may have wrong sign being close to zero */ if (T->mip->dir == GLP_MIN) { if (dz < 0.0) dz = 0.0; info[k].deg = + dz; } else /* GLP_MAX */ { if (dz > 0.0) dz = 0.0; info[k].deg = - dz; } } else if (ret == 1) { /* the constraint is not violated at the current point */ info[k].eff = info[k].deg = 0.0; } else if (ret == 2) { /* no dual feasible adjacent basis exists */ info[k].eff = 1.0; info[k].deg = DBL_MAX; } else xassert(ret != ret); /* if the degradation is too small, just ignore it */ if (info[k].deg < 0.01) info[k].deg = 0.0; } /* sort the list of cuts by decreasing objective degradation and then by decreasing efficacy */ qsort(&info[1], pool->size, sizeof(struct info), fcmp); /* only first (most efficient) max_cuts in the list are qualified as candidates to be added to the current subproblem */ max_cuts = (T->curr->level == 0 ? 90 : 10); if (max_cuts > pool->size) max_cuts = pool->size; /* add cuts to the current subproblem */ #if 0 xprintf("*** adding cuts ***\n"); #endif for (k = 1; k <= max_cuts; k++) { int i, len; /* if this cut seems to be inefficient, skip it */ if (info[k].deg < 0.01 && info[k].eff < 0.01) continue; /* if the angle between this cut and every other cut included in the current subproblem is small, skip this cut */ for (kk = 1; kk < k; kk++) { if (info[kk].flag) { if (parallel(info[k].cut, info[kk].cut, work) > 0.90) break; } } if (kk < k) continue; /* add this cut to the current subproblem */ #if 0 xprintf("eff = %g; deg = %g\n", info[k].eff, info[k].deg); #endif cut = info[k].cut, info[k].flag = 1; i = glp_add_rows(T->mip, 1); if (cut->name != NULL) glp_set_row_name(T->mip, i, cut->name); xassert(T->mip->row[i]->origin == GLP_RF_CUT); T->mip->row[i]->klass = cut->klass; len = 0; for (aij = cut->ptr; aij != NULL; aij = aij->next) len++, ind[len] = aij->j, val[len] = aij->val; glp_set_mat_row(T->mip, i, len, ind, val); xassert(cut->type == GLP_LO || cut->type == GLP_UP); glp_set_row_bnds(T->mip, i, cut->type, cut->rhs, cut->rhs); } /* free working arrays */ xfree(info); xfree(ind); xfree(val); xfree(work); return; } #if 0 /*********************************************************************** * Given a cut a * x >= b (<= b) the routine efficacy computes the cut * efficacy as follows: * * eff = d * (a * x~ - b) / ||a||, * * where d is -1 (in case of '>= b') or +1 (in case of '<= b'), x~ is * the vector of values of structural variables in optimal solution to * LP relaxation of the current subproblem, ||a|| is the Euclidean norm * of the vector of cut coefficients. * * If the cut is violated at point x~, the efficacy eff is positive, * and its value is the Euclidean distance between x~ and the cut plane * a * x = b in the space of structural variables. * * Following geometrical intuition, it is quite natural to consider * this distance as a first-order measure of the expected efficacy of * the cut: the larger the distance the better the cut [1]. */ static double efficacy(glp_tree *T, IOSCUT *cut) { glp_prob *mip = T->mip; IOSAIJ *aij; double s = 0.0, t = 0.0, temp; for (aij = cut->ptr; aij != NULL; aij = aij->next) { xassert(1 <= aij->j && aij->j <= mip->n); s += aij->val * mip->col[aij->j]->prim; t += aij->val * aij->val; } temp = sqrt(t); if (temp < DBL_EPSILON) temp = DBL_EPSILON; if (cut->type == GLP_LO) temp = (s >= cut->rhs ? 0.0 : (cut->rhs - s) / temp); else if (cut->type == GLP_UP) temp = (s <= cut->rhs ? 0.0 : (s - cut->rhs) / temp); else xassert(cut != cut); return temp; } #endif /*********************************************************************** * Given two cuts a1 * x >= b1 (<= b1) and a2 * x >= b2 (<= b2) the * routine parallel computes the cosine of angle between the cut planes * a1 * x = b1 and a2 * x = b2 (which is the acute angle between two * normals to these planes) in the space of structural variables as * follows: * * cos phi = (a1' * a2) / (||a1|| * ||a2||), * * where (a1' * a2) is a dot product of vectors of cut coefficients, * ||a1|| and ||a2|| are Euclidean norms of vectors a1 and a2. * * Note that requirement cos phi = 0 forces the cuts to be orthogonal, * i.e. with disjoint support, while requirement cos phi <= 0.999 means * only avoiding duplicate (parallel) cuts [1]. */ static double parallel(IOSCUT *a, IOSCUT *b, double work[]) { IOSAIJ *aij; double s = 0.0, sa = 0.0, sb = 0.0, temp; for (aij = a->ptr; aij != NULL; aij = aij->next) { work[aij->j] = aij->val; sa += aij->val * aij->val; } for (aij = b->ptr; aij != NULL; aij = aij->next) { s += work[aij->j] * aij->val; sb += aij->val * aij->val; } for (aij = a->ptr; aij != NULL; aij = aij->next) work[aij->j] = 0.0; temp = sqrt(sa) * sqrt(sb); if (temp < DBL_EPSILON * DBL_EPSILON) temp = DBL_EPSILON; return s / temp; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpapi02.c0000644000076500000240000003241713524616144025170 0ustar tamasstaff00000000000000/* glpapi02.c (problem retrieving routines) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wsometimes-uninitialized" #endif #include "glpapi.h" /*********************************************************************** * NAME * * glp_get_prob_name - retrieve problem name * * SYNOPSIS * * const char *glp_get_prob_name(glp_prob *lp); * * RETURNS * * The routine glp_get_prob_name returns a pointer to an internal * buffer, which contains symbolic name of the problem. However, if the * problem has no assigned name, the routine returns NULL. */ const char *glp_get_prob_name(glp_prob *lp) { char *name; name = lp->name; return name; } /*********************************************************************** * NAME * * glp_get_obj_name - retrieve objective function name * * SYNOPSIS * * const char *glp_get_obj_name(glp_prob *lp); * * RETURNS * * The routine glp_get_obj_name returns a pointer to an internal * buffer, which contains a symbolic name of the objective function. * However, if the objective function has no assigned name, the routine * returns NULL. */ const char *glp_get_obj_name(glp_prob *lp) { char *name; name = lp->obj; return name; } /*********************************************************************** * NAME * * glp_get_obj_dir - retrieve optimization direction flag * * SYNOPSIS * * int glp_get_obj_dir(glp_prob *lp); * * RETURNS * * The routine glp_get_obj_dir returns the optimization direction flag * (i.e. "sense" of the objective function): * * GLP_MIN - minimization; * GLP_MAX - maximization. */ int glp_get_obj_dir(glp_prob *lp) { int dir = lp->dir; return dir; } /*********************************************************************** * NAME * * glp_get_num_rows - retrieve number of rows * * SYNOPSIS * * int glp_get_num_rows(glp_prob *lp); * * RETURNS * * The routine glp_get_num_rows returns the current number of rows in * the specified problem object. */ int glp_get_num_rows(glp_prob *lp) { int m = lp->m; return m; } /*********************************************************************** * NAME * * glp_get_num_cols - retrieve number of columns * * SYNOPSIS * * int glp_get_num_cols(glp_prob *lp); * * RETURNS * * The routine glp_get_num_cols returns the current number of columns * in the specified problem object. */ int glp_get_num_cols(glp_prob *lp) { int n = lp->n; return n; } /*********************************************************************** * NAME * * glp_get_row_name - retrieve row name * * SYNOPSIS * * const char *glp_get_row_name(glp_prob *lp, int i); * * RETURNS * * The routine glp_get_row_name returns a pointer to an internal * buffer, which contains symbolic name of i-th row. However, if i-th * row has no assigned name, the routine returns NULL. */ const char *glp_get_row_name(glp_prob *lp, int i) { char *name; if (!(1 <= i && i <= lp->m)) xerror("glp_get_row_name: i = %d; row number out of range\n", i); name = lp->row[i]->name; return name; } /*********************************************************************** * NAME * * glp_get_col_name - retrieve column name * * SYNOPSIS * * const char *glp_get_col_name(glp_prob *lp, int j); * * RETURNS * * The routine glp_get_col_name returns a pointer to an internal * buffer, which contains symbolic name of j-th column. However, if j-th * column has no assigned name, the routine returns NULL. */ const char *glp_get_col_name(glp_prob *lp, int j) { char *name; if (!(1 <= j && j <= lp->n)) xerror("glp_get_col_name: j = %d; column number out of range\n" , j); name = lp->col[j]->name; return name; } /*********************************************************************** * NAME * * glp_get_row_type - retrieve row type * * SYNOPSIS * * int glp_get_row_type(glp_prob *lp, int i); * * RETURNS * * The routine glp_get_row_type returns the type of i-th row, i.e. the * type of corresponding auxiliary variable, as follows: * * GLP_FR - free (unbounded) variable; * GLP_LO - variable with lower bound; * GLP_UP - variable with upper bound; * GLP_DB - double-bounded variable; * GLP_FX - fixed variable. */ int glp_get_row_type(glp_prob *lp, int i) { if (!(1 <= i && i <= lp->m)) xerror("glp_get_row_type: i = %d; row number out of range\n", i); return lp->row[i]->type; } /*********************************************************************** * NAME * * glp_get_row_lb - retrieve row lower bound * * SYNOPSIS * * double glp_get_row_lb(glp_prob *lp, int i); * * RETURNS * * The routine glp_get_row_lb returns the lower bound of i-th row, i.e. * the lower bound of corresponding auxiliary variable. However, if the * row has no lower bound, the routine returns -DBL_MAX. */ double glp_get_row_lb(glp_prob *lp, int i) { double lb; if (!(1 <= i && i <= lp->m)) xerror("glp_get_row_lb: i = %d; row number out of range\n", i); switch (lp->row[i]->type) { case GLP_FR: case GLP_UP: lb = -DBL_MAX; break; case GLP_LO: case GLP_DB: case GLP_FX: lb = lp->row[i]->lb; break; default: xassert(lp != lp); } return lb; } /*********************************************************************** * NAME * * glp_get_row_ub - retrieve row upper bound * * SYNOPSIS * * double glp_get_row_ub(glp_prob *lp, int i); * * RETURNS * * The routine glp_get_row_ub returns the upper bound of i-th row, i.e. * the upper bound of corresponding auxiliary variable. However, if the * row has no upper bound, the routine returns +DBL_MAX. */ double glp_get_row_ub(glp_prob *lp, int i) { double ub; if (!(1 <= i && i <= lp->m)) xerror("glp_get_row_ub: i = %d; row number out of range\n", i); switch (lp->row[i]->type) { case GLP_FR: case GLP_LO: ub = +DBL_MAX; break; case GLP_UP: case GLP_DB: case GLP_FX: ub = lp->row[i]->ub; break; default: xassert(lp != lp); } return ub; } /*********************************************************************** * NAME * * glp_get_col_type - retrieve column type * * SYNOPSIS * * int glp_get_col_type(glp_prob *lp, int j); * * RETURNS * * The routine glp_get_col_type returns the type of j-th column, i.e. * the type of corresponding structural variable, as follows: * * GLP_FR - free (unbounded) variable; * GLP_LO - variable with lower bound; * GLP_UP - variable with upper bound; * GLP_DB - double-bounded variable; * GLP_FX - fixed variable. */ int glp_get_col_type(glp_prob *lp, int j) { if (!(1 <= j && j <= lp->n)) xerror("glp_get_col_type: j = %d; column number out of range\n" , j); return lp->col[j]->type; } /*********************************************************************** * NAME * * glp_get_col_lb - retrieve column lower bound * * SYNOPSIS * * double glp_get_col_lb(glp_prob *lp, int j); * * RETURNS * * The routine glp_get_col_lb returns the lower bound of j-th column, * i.e. the lower bound of corresponding structural variable. However, * if the column has no lower bound, the routine returns -DBL_MAX. */ double glp_get_col_lb(glp_prob *lp, int j) { double lb; if (!(1 <= j && j <= lp->n)) xerror("glp_get_col_lb: j = %d; column number out of range\n", j); switch (lp->col[j]->type) { case GLP_FR: case GLP_UP: lb = -DBL_MAX; break; case GLP_LO: case GLP_DB: case GLP_FX: lb = lp->col[j]->lb; break; default: xassert(lp != lp); } return lb; } /*********************************************************************** * NAME * * glp_get_col_ub - retrieve column upper bound * * SYNOPSIS * * double glp_get_col_ub(glp_prob *lp, int j); * * RETURNS * * The routine glp_get_col_ub returns the upper bound of j-th column, * i.e. the upper bound of corresponding structural variable. However, * if the column has no upper bound, the routine returns +DBL_MAX. */ double glp_get_col_ub(glp_prob *lp, int j) { double ub; if (!(1 <= j && j <= lp->n)) xerror("glp_get_col_ub: j = %d; column number out of range\n", j); switch (lp->col[j]->type) { case GLP_FR: case GLP_LO: ub = +DBL_MAX; break; case GLP_UP: case GLP_DB: case GLP_FX: ub = lp->col[j]->ub; break; default: xassert(lp != lp); } return ub; } /*********************************************************************** * NAME * * glp_get_obj_coef - retrieve obj. coefficient or constant term * * SYNOPSIS * * double glp_get_obj_coef(glp_prob *lp, int j); * * RETURNS * * The routine glp_get_obj_coef returns the objective coefficient at * j-th structural variable (column) of the specified problem object. * * If the parameter j is zero, the routine returns the constant term * ("shift") of the objective function. */ double glp_get_obj_coef(glp_prob *lp, int j) { if (!(0 <= j && j <= lp->n)) xerror("glp_get_obj_coef: j = %d; column number out of range\n" , j); return j == 0 ? lp->c0 : lp->col[j]->coef; } /*********************************************************************** * NAME * * glp_get_num_nz - retrieve number of constraint coefficients * * SYNOPSIS * * int glp_get_num_nz(glp_prob *lp); * * RETURNS * * The routine glp_get_num_nz returns the number of (non-zero) elements * in the constraint matrix of the specified problem object. */ int glp_get_num_nz(glp_prob *lp) { int nnz = lp->nnz; return nnz; } /*********************************************************************** * NAME * * glp_get_mat_row - retrieve row of the constraint matrix * * SYNOPSIS * * int glp_get_mat_row(glp_prob *lp, int i, int ind[], double val[]); * * DESCRIPTION * * The routine glp_get_mat_row scans (non-zero) elements of i-th row * of the constraint matrix of the specified problem object and stores * their column indices and numeric values to locations ind[1], ..., * ind[len] and val[1], ..., val[len], respectively, where 0 <= len <= n * is the number of elements in i-th row, n is the number of columns. * * The parameter ind and/or val can be specified as NULL, in which case * corresponding information is not stored. * * RETURNS * * The routine glp_get_mat_row returns the length len, i.e. the number * of (non-zero) elements in i-th row. */ int glp_get_mat_row(glp_prob *lp, int i, int ind[], double val[]) { GLPAIJ *aij; int len; if (!(1 <= i && i <= lp->m)) xerror("glp_get_mat_row: i = %d; row number out of range\n", i); len = 0; for (aij = lp->row[i]->ptr; aij != NULL; aij = aij->r_next) { len++; if (ind != NULL) ind[len] = aij->col->j; if (val != NULL) val[len] = aij->val; } xassert(len <= lp->n); return len; } /*********************************************************************** * NAME * * glp_get_mat_col - retrieve column of the constraint matrix * * SYNOPSIS * * int glp_get_mat_col(glp_prob *lp, int j, int ind[], double val[]); * * DESCRIPTION * * The routine glp_get_mat_col scans (non-zero) elements of j-th column * of the constraint matrix of the specified problem object and stores * their row indices and numeric values to locations ind[1], ..., * ind[len] and val[1], ..., val[len], respectively, where 0 <= len <= m * is the number of elements in j-th column, m is the number of rows. * * The parameter ind or/and val can be specified as NULL, in which case * corresponding information is not stored. * * RETURNS * * The routine glp_get_mat_col returns the length len, i.e. the number * of (non-zero) elements in j-th column. */ int glp_get_mat_col(glp_prob *lp, int j, int ind[], double val[]) { GLPAIJ *aij; int len; if (!(1 <= j && j <= lp->n)) xerror("glp_get_mat_col: j = %d; column number out of range\n", j); len = 0; for (aij = lp->col[j]->ptr; aij != NULL; aij = aij->c_next) { len++; if (ind != NULL) ind[len] = aij->row->i; if (val != NULL) val[len] = aij->val; } xassert(len <= lp->m); return len; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glptsp.h0000644000076500000240000001051713524616144025065 0ustar tamasstaff00000000000000/* glptsp.h (TSP format) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPTSP_H #define GLPTSP_H typedef struct TSP TSP; struct TSP { /* TSP (or related problem) instance in the format described in the report [G.Reinelt, TSPLIB 95] */ /*--------------------------------------------------------------*/ /* the specification part */ char *name; /* identifies the data file */ int type; /* specifies the type of data: */ #define TSP_UNDEF 0 /* undefined */ #define TSP_TSP 1 /* symmetric TSP */ #define TSP_ATSP 2 /* asymmetric TSP */ #define TSP_TOUR 3 /* collection of tours */ char *comment; /* additional comments (usually the name of the contributor or creator of the problem instance is given here) */ int dimension; /* for a TSP or ATSP, the dimension is the number of its nodes for a TOUR it is the dimension of the corresponding problem */ int edge_weight_type; /* specifies how the edge weights (or distances) are given: */ #define TSP_UNDEF 0 /* undefined */ #define TSP_EXPLICIT 1 /* listed explicitly */ #define TSP_EUC_2D 2 /* Eucl. distances in 2-D */ #define TSP_CEIL_2D 3 /* Eucl. distances in 2-D rounded up */ #define TSP_GEO 4 /* geographical distances */ #define TSP_ATT 5 /* special distance function */ int edge_weight_format; /* describes the format of the edge weights if they are given explicitly: */ #define TSP_UNDEF 0 /* undefined */ #define TSP_FUNCTION 1 /* given by a function */ #define TSP_FULL_MATRIX 2 /* given by a full matrix */ #define TSP_UPPER_ROW 3 /* upper triangulat matrix (row-wise without diagonal entries) */ #define TSP_LOWER_DIAG_ROW 4 /* lower triangular matrix (row-wise including diagonal entries) */ int display_data_type; /* specifies how a graphical display of the nodes can be obtained: */ #define TSP_UNDEF 0 /* undefined */ #define TSP_COORD_DISPLAY 1 /* display is generated from the node coordinates */ #define TSP_TWOD_DISPLAY 2 /* explicit coordinates in 2-D are given */ /*--------------------------------------------------------------*/ /* data part */ /* NODE_COORD_SECTION: */ double *node_x_coord; /* double node_x_coord[1+dimension]; */ double *node_y_coord; /* double node_y_coord[1+dimension]; */ /* DISPLAY_DATA_SECTION: */ double *dply_x_coord; /* double dply_x_coord[1+dimension]; */ double *dply_y_coord; /* double dply_y_coord[1+dimension]; */ /* TOUR_SECTION: */ int *tour; /* int tour[1+dimension]; */ /* EDGE_WEIGHT_SECTION: */ int *edge_weight; /* int edge_weight[1+dimension*dimension]; */ }; #define tsp_read_data _glp_tsp_read_data #define tsp_free_data _glp_tsp_free_data #define tsp_distance _glp_tsp_distance TSP *tsp_read_data(char *fname); /* read TSP instance data */ void tsp_free_data(TSP *tsp); /* free TSP instance data */ int tsp_distance(TSP *tsp, int i, int j); /* compute distance between two nodes */ #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpapi08.c0000644000076500000240000003030113524616144025164 0ustar tamasstaff00000000000000/* glpapi08.c (interior-point method routines) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glpapi.h" #include "glpipm.h" #include "glpnpp.h" /*********************************************************************** * NAME * * glp_interior - solve LP problem with the interior-point method * * SYNOPSIS * * int glp_interior(glp_prob *P, const glp_iptcp *parm); * * The routine glp_interior is a driver to the LP solver based on the * interior-point method. * * The interior-point solver has a set of control parameters. Values of * the control parameters can be passed in a structure glp_iptcp, which * the parameter parm points to. * * Currently this routine implements an easy variant of the primal-dual * interior-point method based on Mehrotra's technique. * * This routine transforms the original LP problem to an equivalent LP * problem in the standard formulation (all constraints are equalities, * all variables are non-negative), calls the routine ipm_main to solve * the transformed problem, and then transforms an obtained solution to * the solution of the original problem. * * RETURNS * * 0 The LP problem instance has been successfully solved. This code * does not necessarily mean that the solver has found optimal * solution. It only means that the solution process was successful. * * GLP_EFAIL * The problem has no rows/columns. * * GLP_ENOCVG * Very slow convergence or divergence. * * GLP_EITLIM * Iteration limit exceeded. * * GLP_EINSTAB * Numerical instability on solving Newtonian system. */ static void transform(NPP *npp) { /* transform LP to the standard formulation */ NPPROW *row, *prev_row; NPPCOL *col, *prev_col; for (row = npp->r_tail; row != NULL; row = prev_row) { prev_row = row->prev; if (row->lb == -DBL_MAX && row->ub == +DBL_MAX) npp_free_row(npp, row); else if (row->lb == -DBL_MAX) npp_leq_row(npp, row); else if (row->ub == +DBL_MAX) npp_geq_row(npp, row); else if (row->lb != row->ub) { if (fabs(row->lb) < fabs(row->ub)) npp_geq_row(npp, row); else npp_leq_row(npp, row); } } for (col = npp->c_tail; col != NULL; col = prev_col) { prev_col = col->prev; if (col->lb == -DBL_MAX && col->ub == +DBL_MAX) npp_free_col(npp, col); else if (col->lb == -DBL_MAX) npp_ubnd_col(npp, col); else if (col->ub == +DBL_MAX) { if (col->lb != 0.0) npp_lbnd_col(npp, col); } else if (col->lb != col->ub) { if (fabs(col->lb) < fabs(col->ub)) { if (col->lb != 0.0) npp_lbnd_col(npp, col); } else npp_ubnd_col(npp, col); npp_dbnd_col(npp, col); } else npp_fixed_col(npp, col); } for (row = npp->r_head; row != NULL; row = row->next) xassert(row->lb == row->ub); for (col = npp->c_head; col != NULL; col = col->next) xassert(col->lb == 0.0 && col->ub == +DBL_MAX); return; } int glp_interior(glp_prob *P, const glp_iptcp *parm) { glp_iptcp _parm; GLPROW *row; GLPCOL *col; NPP *npp = NULL; glp_prob *prob = NULL; int i, j, ret; /* check control parameters */ if (parm == NULL) glp_init_iptcp(&_parm), parm = &_parm; if (!(parm->msg_lev == GLP_MSG_OFF || parm->msg_lev == GLP_MSG_ERR || parm->msg_lev == GLP_MSG_ON || parm->msg_lev == GLP_MSG_ALL)) xerror("glp_interior: msg_lev = %d; invalid parameter\n", parm->msg_lev); if (!(parm->ord_alg == GLP_ORD_NONE || parm->ord_alg == GLP_ORD_QMD || parm->ord_alg == GLP_ORD_AMD || parm->ord_alg == GLP_ORD_SYMAMD)) xerror("glp_interior: ord_alg = %d; invalid parameter\n", parm->ord_alg); /* interior-point solution is currently undefined */ P->ipt_stat = GLP_UNDEF; P->ipt_obj = 0.0; /* check bounds of double-bounded variables */ for (i = 1; i <= P->m; i++) { row = P->row[i]; if (row->type == GLP_DB && row->lb >= row->ub) { if (parm->msg_lev >= GLP_MSG_ERR) xprintf("glp_interior: row %d: lb = %g, ub = %g; incorre" "ct bounds\n", i, row->lb, row->ub); ret = GLP_EBOUND; goto done; } } for (j = 1; j <= P->n; j++) { col = P->col[j]; if (col->type == GLP_DB && col->lb >= col->ub) { if (parm->msg_lev >= GLP_MSG_ERR) xprintf("glp_interior: column %d: lb = %g, ub = %g; inco" "rrect bounds\n", j, col->lb, col->ub); ret = GLP_EBOUND; goto done; } } /* transform LP to the standard formulation */ if (parm->msg_lev >= GLP_MSG_ALL) xprintf("Original LP has %d row(s), %d column(s), and %d non-z" "ero(s)\n", P->m, P->n, P->nnz); npp = npp_create_wksp(); npp_load_prob(npp, P, GLP_OFF, GLP_IPT, GLP_ON); transform(npp); prob = glp_create_prob(); npp_build_prob(npp, prob); if (parm->msg_lev >= GLP_MSG_ALL) xprintf("Working LP has %d row(s), %d column(s), and %d non-ze" "ro(s)\n", prob->m, prob->n, prob->nnz); #if 1 /* currently empty problem cannot be solved */ if (!(prob->m > 0 && prob->n > 0)) { if (parm->msg_lev >= GLP_MSG_ERR) xprintf("glp_interior: unable to solve empty problem\n"); ret = GLP_EFAIL; goto done; } #endif /* scale the resultant LP */ { ENV *env = get_env_ptr(); int term_out = env->term_out; env->term_out = GLP_OFF; glp_scale_prob(prob, GLP_SF_EQ); env->term_out = term_out; } /* warn about dense columns */ if (parm->msg_lev >= GLP_MSG_ON && prob->m >= 200) { int len, cnt = 0; for (j = 1; j <= prob->n; j++) { len = glp_get_mat_col(prob, j, NULL, NULL); if ((double)len >= 0.20 * (double)prob->m) cnt++; } if (cnt == 1) xprintf("WARNING: PROBLEM HAS ONE DENSE COLUMN\n"); else if (cnt > 0) xprintf("WARNING: PROBLEM HAS %d DENSE COLUMNS\n", cnt); } /* solve the transformed LP */ ret = ipm_solve(prob, parm); /* postprocess solution from the transformed LP */ npp_postprocess(npp, prob); /* and store solution to the original LP */ npp_unload_sol(npp, P); done: /* free working program objects */ if (npp != NULL) npp_delete_wksp(npp); if (prob != NULL) glp_delete_prob(prob); /* return to the application program */ return ret; } /*********************************************************************** * NAME * * glp_init_iptcp - initialize interior-point solver control parameters * * SYNOPSIS * * void glp_init_iptcp(glp_iptcp *parm); * * DESCRIPTION * * The routine glp_init_iptcp initializes control parameters, which are * used by the interior-point solver, with default values. * * Default values of the control parameters are stored in the glp_iptcp * structure, which the parameter parm points to. */ void glp_init_iptcp(glp_iptcp *parm) { parm->msg_lev = GLP_MSG_ALL; parm->ord_alg = GLP_ORD_AMD; return; } /*********************************************************************** * NAME * * glp_ipt_status - retrieve status of interior-point solution * * SYNOPSIS * * int glp_ipt_status(glp_prob *lp); * * RETURNS * * The routine glp_ipt_status reports the status of solution found by * the interior-point solver as follows: * * GLP_UNDEF - interior-point solution is undefined; * GLP_OPT - interior-point solution is optimal; * GLP_INFEAS - interior-point solution is infeasible; * GLP_NOFEAS - no feasible solution exists. */ int glp_ipt_status(glp_prob *lp) { int ipt_stat = lp->ipt_stat; return ipt_stat; } /*********************************************************************** * NAME * * glp_ipt_obj_val - retrieve objective value (interior point) * * SYNOPSIS * * double glp_ipt_obj_val(glp_prob *lp); * * RETURNS * * The routine glp_ipt_obj_val returns value of the objective function * for interior-point solution. */ double glp_ipt_obj_val(glp_prob *lp) { /*struct LPXCPS *cps = lp->cps;*/ double z; z = lp->ipt_obj; /*if (cps->round && fabs(z) < 1e-9) z = 0.0;*/ return z; } /*********************************************************************** * NAME * * glp_ipt_row_prim - retrieve row primal value (interior point) * * SYNOPSIS * * double glp_ipt_row_prim(glp_prob *lp, int i); * * RETURNS * * The routine glp_ipt_row_prim returns primal value of the auxiliary * variable associated with i-th row. */ double glp_ipt_row_prim(glp_prob *lp, int i) { /*struct LPXCPS *cps = lp->cps;*/ double pval; if (!(1 <= i && i <= lp->m)) xerror("glp_ipt_row_prim: i = %d; row number out of range\n", i); pval = lp->row[i]->pval; /*if (cps->round && fabs(pval) < 1e-9) pval = 0.0;*/ return pval; } /*********************************************************************** * NAME * * glp_ipt_row_dual - retrieve row dual value (interior point) * * SYNOPSIS * * double glp_ipt_row_dual(glp_prob *lp, int i); * * RETURNS * * The routine glp_ipt_row_dual returns dual value (i.e. reduced cost) * of the auxiliary variable associated with i-th row. */ double glp_ipt_row_dual(glp_prob *lp, int i) { /*struct LPXCPS *cps = lp->cps;*/ double dval; if (!(1 <= i && i <= lp->m)) xerror("glp_ipt_row_dual: i = %d; row number out of range\n", i); dval = lp->row[i]->dval; /*if (cps->round && fabs(dval) < 1e-9) dval = 0.0;*/ return dval; } /*********************************************************************** * NAME * * glp_ipt_col_prim - retrieve column primal value (interior point) * * SYNOPSIS * * double glp_ipt_col_prim(glp_prob *lp, int j); * * RETURNS * * The routine glp_ipt_col_prim returns primal value of the structural * variable associated with j-th column. */ double glp_ipt_col_prim(glp_prob *lp, int j) { /*struct LPXCPS *cps = lp->cps;*/ double pval; if (!(1 <= j && j <= lp->n)) xerror("glp_ipt_col_prim: j = %d; column number out of range\n" , j); pval = lp->col[j]->pval; /*if (cps->round && fabs(pval) < 1e-9) pval = 0.0;*/ return pval; } /*********************************************************************** * NAME * * glp_ipt_col_dual - retrieve column dual value (interior point) * * SYNOPSIS * * #include "glplpx.h" * double glp_ipt_col_dual(glp_prob *lp, int j); * * RETURNS * * The routine glp_ipt_col_dual returns dual value (i.e. reduced cost) * of the structural variable associated with j-th column. */ double glp_ipt_col_dual(glp_prob *lp, int j) { /*struct LPXCPS *cps = lp->cps;*/ double dval; if (!(1 <= j && j <= lp->n)) xerror("glp_ipt_col_dual: j = %d; column number out of range\n" , j); dval = lp->col[j]->dval; /*if (cps->round && fabs(dval) < 1e-9) dval = 0.0;*/ return dval; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/README0000644000076500000240000000300513524616144024255 0ustar tamasstaff00000000000000 Olga K. gewidmet GLPK (GNU Linear Programming Kit) Version 4.45 Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010 Andrew Makhorin, Department for Applied Informatics, Moscow Aviation Institute, Moscow, Russia. All rights reserved. E-mail: . GLPK is part of the GNU Project released under the aegis of GNU. GLPK is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. See the file COPYING for the GNU General Public License. See the file INSTALL for compilation and installation instructions. The GLPK package is a set of routines written in ANSI C and organized in the form of a callable library. This package is intended for solving large-scale linear programming (LP), mixed integer linear programming (MIP), and other related problems. The GLPK package includes the following main components: * implementation of the simplex method; * implementation of the exact simplex method based on bignum (rational) arithmetic; * implementation of the primal-dual interior-point method; * implementation of the branch-and-cut method; * application program interface (API); * GNU MathProg modeling language (a subset of AMPL); * GLPSOL, a stand-alone LP/MIP solver. See GLPK webpage . Please report bugs to . python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpnet04.c0000644000076500000240000006226413524616144025212 0ustar tamasstaff00000000000000/* glpnet04.c (grid-like network problem generator) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * This code is a modified version of the program GRIDGEN, a grid-like * network problem generator developed by Yusin Lee and Jim Orlin. * The original code is publically available on the DIMACS ftp site at: * . * * All changes concern only the program interface, so this modified * version produces exactly the same instances as the original version. * * Changes were made by Andrew Makhorin . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wlogical-op-parentheses" #endif #include "glpapi.h" /*********************************************************************** * NAME * * glp_gridgen - grid-like network problem generator * * SYNOPSIS * * int glp_gridgen(glp_graph *G, int v_rhs, int a_cap, int a_cost, * const int parm[1+14]); * * DESCRIPTION * * The routine glp_gridgen is a grid-like network problem generator * developed by Yusin Lee and Jim Orlin. * * The parameter G specifies the graph object, to which the generated * problem data have to be stored. Note that on entry the graph object * is erased with the routine glp_erase_graph. * * The parameter v_rhs specifies an offset of the field of type double * in the vertex data block, to which the routine stores the supply or * demand value. If v_rhs < 0, the value is not stored. * * The parameter a_cap specifies an offset of the field of type double * in the arc data block, to which the routine stores the arc capacity. * If a_cap < 0, the capacity is not stored. * * The parameter a_cost specifies an offset of the field of type double * in the arc data block, to which the routine stores the per-unit cost * if the arc flow. If a_cost < 0, the cost is not stored. * * The array parm contains description of the network to be generated: * * parm[0] not used * parm[1] two-ways arcs indicator: * 1 - if links in both direction should be generated * 0 - otherwise * parm[2] random number seed (a positive integer) * parm[3] number of nodes (the number of nodes generated might be * slightly different to make the network a grid) * parm[4] grid width * parm[5] number of sources * parm[6] number of sinks * parm[7] average degree * parm[8] total flow * parm[9] distribution of arc costs: * 1 - uniform * 2 - exponential * parm[10] lower bound for arc cost (uniform) * 100 * lambda (exponential) * parm[11] upper bound for arc cost (uniform) * not used (exponential) * parm[12] distribution of arc capacities: * 1 - uniform * 2 - exponential * parm[13] lower bound for arc capacity (uniform) * 100 * lambda (exponential) * parm[14] upper bound for arc capacity (uniform) * not used (exponential) * * RETURNS * * If the instance was successfully generated, the routine glp_gridgen * returns zero; otherwise, if specified parameters are inconsistent, * the routine returns a non-zero error code. * * COMMENTS * * This network generator generates a grid-like network plus a super * node. In additional to the arcs connecting the nodes in the grid, * there is an arc from each supply node to the super node and from the * super node to each demand node to guarantee feasiblity. These arcs * have very high costs and very big capacities. * * The idea of this network generator is as follows: First, a grid of * n1 * n2 is generated. For example, 5 * 3. The nodes are numbered as * 1 to 15, and the supernode is numbered as n1*n2+1. Then arcs between * adjacent nodes are generated. For these arcs, the user is allowed to * specify either to generate two-way arcs or one-way arcs. If two-way * arcs are to be generated, two arcs, one in each direction, will be * generated between each adjacent node pairs. Otherwise, only one arc * will be generated. If this is the case, the arcs will be generated * in alterntive directions as shown below. * * 1 ---> 2 ---> 3 ---> 4 ---> 5 * | ^ | ^ | * | | | | | * V | V | V * 6 <--- 7 <--- 8 <--- 9 <--- 10 * | ^ | ^ | * | | | | | * V | V | V * 11 --->12 --->13 --->14 ---> 15 * * Then the arcs between the super node and the source/sink nodes are * added as mentioned before. If the number of arcs still doesn't reach * the requirement, additional arcs will be added by uniformly picking * random node pairs. There is no checking to prevent multiple arcs * between any pair of nodes. However, there will be no self-arcs (arcs * that poins back to its tail node) in the network. * * The source and sink nodes are selected uniformly in the network, and * the imbalances of each source/sink node are also assigned by uniform * distribution. */ struct stat_para { /* structure for statistical distributions */ int distribution; /* the distribution: */ #define UNIFORM 1 /* uniform distribution */ #define EXPONENTIAL 2 /* exponential distribution */ double parameter[5]; /* the parameters of the distribution */ }; struct arcs { int from; /* the FROM node of that arc */ int to; /* the TO node of that arc */ int cost; /* original cost of that arc */ int u; /* capacity of the arc */ }; struct imbalance { int node; /* Node ID */ int supply; /* Supply of that node */ }; struct csa { /* common storage area */ glp_graph *G; int v_rhs, a_cap, a_cost; int seed; /* random number seed */ int seed_original; /* the original seed from input */ int two_way; /* 0: generate arcs in both direction for the basic grid, except for the arcs to/from the super node. 1: o/w */ int n_node; /* total number of nodes in the network, numbered 1 to n_node, including the super node, which is the last one */ int n_arc; /* total number of arcs in the network, counting EVERY arc. */ int n_grid_arc; /* number of arcs in the basic grid, including the arcs to/from the super node */ int n_source, n_sink; /* number of source and sink nodes */ int avg_degree; /* average degree, arcs to and from the super node are counted */ int t_supply; /* total supply in the network */ int n1, n2; /* the two edges of the network grid. n1 >= n2 */ struct imbalance *source_list, *sink_list; /* head of the array of source/sink nodes */ struct stat_para arc_costs; /* the distribution of arc costs */ struct stat_para capacities; /* distribution of the capacities of the arcs */ struct arcs *arc_list; /* head of the arc list array. Arcs in this array are in the order of grid_arcs, arcs to/from super node, and other arcs */ }; #define G (csa->G) #define v_rhs (csa->v_rhs) #define a_cap (csa->a_cap) #define a_cost (csa->a_cost) #define seed (csa->seed) #define seed_original (csa->seed_original) #define two_way (csa->two_way) #define n_node (csa->n_node) #define n_arc (csa->n_arc) #define n_grid_arc (csa->n_grid_arc) #define n_source (csa->n_source) #define n_sink (csa->n_sink) #define avg_degree (csa->avg_degree) #define t_supply (csa->t_supply) #define n1 (csa->n1) #define n2 (csa->n2) #define source_list (csa->source_list) #define sink_list (csa->sink_list) #define arc_costs (csa->arc_costs) #define capacities (csa->capacities) #define arc_list (csa->arc_list) static void assign_capacities(struct csa *csa); static void assign_costs(struct csa *csa); static void assign_imbalance(struct csa *csa); static int exponential(struct csa *csa, double lambda[1]); static struct arcs *gen_additional_arcs(struct csa *csa, struct arcs *arc_ptr); static struct arcs *gen_basic_grid(struct csa *csa, struct arcs *arc_ptr); static void gen_more_arcs(struct csa *csa, struct arcs *arc_ptr); static void generate(struct csa *csa); static void output(struct csa *csa); static double randy(struct csa *csa); static void select_source_sinks(struct csa *csa); static int uniform(struct csa *csa, double a[2]); int glp_gridgen(glp_graph *G_, int _v_rhs, int _a_cap, int _a_cost, const int parm[1+14]) { struct csa _csa, *csa = &_csa; int n, ret; G = G_; v_rhs = _v_rhs; a_cap = _a_cap; a_cost = _a_cost; if (G != NULL) { if (v_rhs >= 0 && v_rhs > G->v_size - (int)sizeof(double)) xerror("glp_gridgen: v_rhs = %d; invalid offset\n", v_rhs); if (a_cap >= 0 && a_cap > G->a_size - (int)sizeof(double)) xerror("glp_gridgen: a_cap = %d; invalid offset\n", a_cap); if (a_cost >= 0 && a_cost > G->a_size - (int)sizeof(double)) xerror("glp_gridgen: a_cost = %d; invalid offset\n", a_cost) ; } /* Check the parameters for consistency. */ if (!(parm[1] == 0 || parm[1] == 1)) { ret = 1; goto done; } if (parm[2] < 1) { ret = 2; goto done; } if (!(10 <= parm[3] && parm[3] <= 40000)) { ret = 3; goto done; } if (!(1 <= parm[4] && parm[4] <= 40000)) { ret = 4; goto done; } if (!(parm[5] >= 0 && parm[6] >= 0 && parm[5] + parm[6] <= parm[3])) { ret = 5; goto done; } if (!(1 <= parm[7] && parm[7] <= parm[3])) { ret = 6; goto done; } if (parm[8] < 0) { ret = 7; goto done; } if (!(parm[9] == 1 || parm[9] == 2)) { ret = 8; goto done; } if (parm[9] == 1 && parm[10] > parm[11] || parm[9] == 2 && parm[10] < 1) { ret = 9; goto done; } if (!(parm[12] == 1 || parm[12] == 2)) { ret = 10; goto done; } if (parm[12] == 1 && !(0 <= parm[13] && parm[13] <= parm[14]) || parm[12] == 2 && parm[13] < 1) { ret = 11; goto done; } /* Initialize the graph object. */ if (G != NULL) { glp_erase_graph(G, G->v_size, G->a_size); glp_set_graph_name(G, "GRIDGEN"); } /* Copy the generator parameters. */ two_way = parm[1]; seed_original = seed = parm[2]; n_node = parm[3]; n = parm[4]; n_source = parm[5]; n_sink = parm[6]; avg_degree = parm[7]; t_supply = parm[8]; arc_costs.distribution = parm[9]; if (parm[9] == 1) { arc_costs.parameter[0] = parm[10]; arc_costs.parameter[1] = parm[11]; } else { arc_costs.parameter[0] = (double)parm[10] / 100.0; arc_costs.parameter[1] = 0.0; } capacities.distribution = parm[12]; if (parm[12] == 1) { capacities.parameter[0] = parm[13]; capacities.parameter[1] = parm[14]; } else { capacities.parameter[0] = (double)parm[13] / 100.0; capacities.parameter[1] = 0.0; } /* Calculate the edge lengths of the grid according to the input. */ if (n * n >= n_node) { n1 = n; n2 = (int)((double)n_node / (double)n + 0.5); } else { n2 = n; n1 = (int)((double)n_node / (double)n + 0.5); } /* Recalculate the total number of nodes and plus 1 for the super node. */ n_node = n1 * n2 + 1; n_arc = n_node * avg_degree; n_grid_arc = (two_way + 1) * ((n1 - 1) * n2 + (n2 - 1) * n1) + n_source + n_sink; if (n_grid_arc > n_arc) n_arc = n_grid_arc; arc_list = xcalloc(n_arc, sizeof(struct arcs)); source_list = xcalloc(n_source, sizeof(struct imbalance)); sink_list = xcalloc(n_sink, sizeof(struct imbalance)); /* Generate a random network. */ generate(csa); /* Output the network. */ output(csa); /* Free all allocated memory. */ xfree(arc_list); xfree(source_list); xfree(sink_list); /* The instance has been successfully generated. */ ret = 0; done: return ret; } #undef random static void assign_capacities(struct csa *csa) { /* Assign a capacity to each arc. */ struct arcs *arc_ptr = arc_list; int (*random)(struct csa *csa, double *); int i; /* Determine the random number generator to use. */ switch (arc_costs.distribution) { case UNIFORM: random = uniform; break; case EXPONENTIAL: random = exponential; break; default: xassert(csa != csa); } /* Assign capacities to grid arcs. */ for (i = n_source + n_sink; i < n_grid_arc; i++, arc_ptr++) arc_ptr->u = random(csa, capacities.parameter); i = i - n_source - n_sink; /* Assign capacities to arcs to/from supernode. */ for (; i < n_grid_arc; i++, arc_ptr++) arc_ptr->u = t_supply; /* Assign capacities to all other arcs. */ for (; i < n_arc; i++, arc_ptr++) arc_ptr->u = random(csa, capacities.parameter); return; } static void assign_costs(struct csa *csa) { /* Assign a cost to each arc. */ struct arcs *arc_ptr = arc_list; int (*random)(struct csa *csa, double *); int i; /* A high cost assigned to arcs to/from the supernode. */ int high_cost; /* The maximum cost assigned to arcs in the base grid. */ int max_cost = 0; /* Determine the random number generator to use. */ switch (arc_costs.distribution) { case UNIFORM: random = uniform; break; case EXPONENTIAL: random = exponential; break; default: xassert(csa != csa); } /* Assign costs to arcs in the base grid. */ for (i = n_source + n_sink; i < n_grid_arc; i++, arc_ptr++) { arc_ptr->cost = random(csa, arc_costs.parameter); if (max_cost < arc_ptr->cost) max_cost = arc_ptr->cost; } i = i - n_source - n_sink; /* Assign costs to arcs to/from the super node. */ high_cost = max_cost * 2; for (; i < n_grid_arc; i++, arc_ptr++) arc_ptr->cost = high_cost; /* Assign costs to all other arcs. */ for (; i < n_arc; i++, arc_ptr++) arc_ptr->cost = random(csa, arc_costs.parameter); return; } static void assign_imbalance(struct csa *csa) { /* Assign an imbalance to each node. */ int total, i; double avg; struct imbalance *ptr; /* assign the supply nodes */ avg = 2.0 * t_supply / n_source; do { for (i = 1, total = t_supply, ptr = source_list + 1; i < n_source; i++, ptr++) { ptr->supply = (int)(randy(csa) * avg + 0.5); total -= ptr->supply; } source_list->supply = total; } /* redo all if the assignment "overshooted" */ while (total <= 0); /* assign the demand nodes */ avg = -2.0 * t_supply / n_sink; do { for (i = 1, total = t_supply, ptr = sink_list + 1; i < n_sink; i++, ptr++) { ptr->supply = (int)(randy(csa) * avg - 0.5); total += ptr->supply; } sink_list->supply = - total; } while (total <= 0); return; } static int exponential(struct csa *csa, double lambda[1]) { /* Returns an "exponentially distributed" integer with parameter lambda. */ return ((int)(- lambda[0] * log((double)randy(csa)) + 0.5)); } static struct arcs *gen_additional_arcs(struct csa *csa, struct arcs *arc_ptr) { /* Generate an arc from each source to the supernode and from supernode to each sink. */ int i; for (i = 0; i < n_source; i++, arc_ptr++) { arc_ptr->from = source_list[i].node; arc_ptr->to = n_node; } for (i = 0; i < n_sink; i++, arc_ptr++) { arc_ptr->to = sink_list[i].node; arc_ptr->from = n_node; } return arc_ptr; } static struct arcs *gen_basic_grid(struct csa *csa, struct arcs *arc_ptr) { /* Generate the basic grid. */ int direction = 1, i, j, k; if (two_way) { /* Generate an arc in each direction. */ for (i = 1; i < n_node; i += n1) { for (j = i, k = j + n1 - 1; j < k; j++) { arc_ptr->from = j; arc_ptr->to = j + 1; arc_ptr++; arc_ptr->from = j + 1; arc_ptr->to = j; arc_ptr++; } } for (i = 1; i <= n1; i++) { for (j = i + n1; j < n_node; j += n1) { arc_ptr->from = j; arc_ptr->to = j - n1; arc_ptr++; arc_ptr->from = j - n1; arc_ptr->to = j; arc_ptr++; } } } else { /* Generate one arc in each direction. */ for (i = 1; i < n_node; i += n1) { if (direction == 1) j = i; else j = i + 1; for (k = j + n1 - 1; j < k; j++) { arc_ptr->from = j; arc_ptr->to = j + direction; arc_ptr++; } direction = - direction; } for (i = 1; i <= n1; i++) { j = i + n1; if (direction == 1) { for (; j < n_node; j += n1) { arc_ptr->from = j - n1; arc_ptr->to = j; arc_ptr++; } } else { for (; j < n_node; j += n1) { arc_ptr->from = j - n1; arc_ptr->to = j; arc_ptr++; } } direction = - direction; } } return arc_ptr; } static void gen_more_arcs(struct csa *csa, struct arcs *arc_ptr) { /* Generate random arcs to meet the specified density. */ int i; double ab[2]; ab[0] = 0.9; ab[1] = n_node - 0.99; /* upper limit is n_node-1 because the supernode cannot be selected */ for (i = n_grid_arc; i < n_arc; i++, arc_ptr++) { arc_ptr->from = uniform(csa, ab); arc_ptr->to = uniform(csa, ab); if (arc_ptr->from == arc_ptr->to) { arc_ptr--; i--; } } return; } static void generate(struct csa *csa) { /* Generate a random network. */ struct arcs *arc_ptr = arc_list; arc_ptr = gen_basic_grid(csa, arc_ptr); select_source_sinks(csa); arc_ptr = gen_additional_arcs(csa, arc_ptr); gen_more_arcs(csa, arc_ptr); assign_costs(csa); assign_capacities(csa); assign_imbalance(csa); return; } static void output(struct csa *csa) { /* Output the network in DIMACS format. */ struct arcs *arc_ptr; struct imbalance *imb_ptr; int i; if (G != NULL) goto skip; /* Output "c", "p" records. */ xprintf("c generated by GRIDGEN\n"); xprintf("c seed %d\n", seed_original); xprintf("c nodes %d\n", n_node); xprintf("c grid size %d X %d\n", n1, n2); xprintf("c sources %d sinks %d\n", n_source, n_sink); xprintf("c avg. degree %d\n", avg_degree); xprintf("c supply %d\n", t_supply); switch (arc_costs.distribution) { case UNIFORM: xprintf("c arc costs: UNIFORM distr. min %d max %d\n", (int)arc_costs.parameter[0], (int)arc_costs.parameter[1]); break; case EXPONENTIAL: xprintf("c arc costs: EXPONENTIAL distr. lambda %d\n", (int)arc_costs.parameter[0]); break; default: xassert(csa != csa); } switch (capacities.distribution) { case UNIFORM: xprintf("c arc caps : UNIFORM distr. min %d max %d\n", (int)capacities.parameter[0], (int)capacities.parameter[1]); break; case EXPONENTIAL: xprintf("c arc caps : EXPONENTIAL distr. %d lambda %d\n", (int)capacities.parameter[0]); break; default: xassert(csa != csa); } skip: if (G == NULL) xprintf("p min %d %d\n", n_node, n_arc); else { glp_add_vertices(G, n_node); if (v_rhs >= 0) { double zero = 0.0; for (i = 1; i <= n_node; i++) { glp_vertex *v = G->v[i]; memcpy((char *)v->data + v_rhs, &zero, sizeof(double)); } } } /* Output "n node supply". */ for (i = 0, imb_ptr = source_list; i < n_source; i++, imb_ptr++) { if (G == NULL) xprintf("n %d %d\n", imb_ptr->node, imb_ptr->supply); else { if (v_rhs >= 0) { double temp = (double)imb_ptr->supply; glp_vertex *v = G->v[imb_ptr->node]; memcpy((char *)v->data + v_rhs, &temp, sizeof(double)); } } } for (i = 0, imb_ptr = sink_list; i < n_sink; i++, imb_ptr++) { if (G == NULL) xprintf("n %d %d\n", imb_ptr->node, imb_ptr->supply); else { if (v_rhs >= 0) { double temp = (double)imb_ptr->supply; glp_vertex *v = G->v[imb_ptr->node]; memcpy((char *)v->data + v_rhs, &temp, sizeof(double)); } } } /* Output "a from to lowcap=0 hicap cost". */ for (i = 0, arc_ptr = arc_list; i < n_arc; i++, arc_ptr++) { if (G == NULL) xprintf("a %d %d 0 %d %d\n", arc_ptr->from, arc_ptr->to, arc_ptr->u, arc_ptr->cost); else { glp_arc *a = glp_add_arc(G, arc_ptr->from, arc_ptr->to); if (a_cap >= 0) { double temp = (double)arc_ptr->u; memcpy((char *)a->data + a_cap, &temp, sizeof(double)); } if (a_cost >= 0) { double temp = (double)arc_ptr->cost; memcpy((char *)a->data + a_cost, &temp, sizeof(double)); } } } return; } static double randy(struct csa *csa) { /* Returns a random number between 0.0 and 1.0. See Ward Cheney & David Kincaid, "Numerical Mathematics and Computing," 2Ed, pp. 335. */ seed = 16807 * seed % 2147483647; if (seed < 0) seed = - seed; return seed * 4.6566128752459e-10; } static void select_source_sinks(struct csa *csa) { /* Randomly select the source nodes and sink nodes. */ int i, *int_ptr; int *temp_list; /* a temporary list of nodes */ struct imbalance *ptr; double ab[2]; /* parameter for random number generator */ ab[0] = 0.9; ab[1] = n_node - 0.99; /* upper limit is n_node-1 because the supernode cannot be selected */ temp_list = xcalloc(n_node, sizeof(int)); for (i = 0, int_ptr = temp_list; i < n_node; i++, int_ptr++) *int_ptr = 0; /* Select the source nodes. */ for (i = 0, ptr = source_list; i < n_source; i++, ptr++) { ptr->node = uniform(csa, ab); if (temp_list[ptr->node] == 1) /* check for duplicates */ { ptr--; i--; } else temp_list[ptr->node] = 1; } /* Select the sink nodes. */ for (i = 0, ptr = sink_list; i < n_sink; i++, ptr++) { ptr->node = uniform(csa, ab); if (temp_list[ptr->node] == 1) { ptr--; i--; } else temp_list[ptr->node] = 1; } xfree(temp_list); return; } int uniform(struct csa *csa, double a[2]) { /* Generates an integer uniformly selected from [a[0],a[1]]. */ return (int)((a[1] - a[0]) * randy(csa) + a[0] + 0.5); } /**********************************************************************/ #if 0 int main(void) { int parm[1+14]; double temp; scanf("%d", &parm[1]); scanf("%d", &parm[2]); scanf("%d", &parm[3]); scanf("%d", &parm[4]); scanf("%d", &parm[5]); scanf("%d", &parm[6]); scanf("%d", &parm[7]); scanf("%d", &parm[8]); scanf("%d", &parm[9]); if (parm[9] == 1) { scanf("%d", &parm[10]); scanf("%d", &parm[11]); } else { scanf("%le", &temp); parm[10] = (int)(100.0 * temp + .5); parm[11] = 0; } scanf("%d", &parm[12]); if (parm[12] == 1) { scanf("%d", &parm[13]); scanf("%d", &parm[14]); } else { scanf("%le", &temp); parm[13] = (int)(100.0 * temp + .5); parm[14] = 0; } glp_gridgen(NULL, 0, 0, 0, parm); return 0; } #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glprng.h0000644000076500000240000000434613524616144025050 0ustar tamasstaff00000000000000/* glprng.h (pseudo-random number generator) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPRNG_H #define GLPRNG_H typedef struct RNG RNG; struct RNG { /* Knuth's portable pseudo-random number generator */ int A[56]; /* pseudo-random values */ int *fptr; /* the next A value to be exported */ }; #define rng_create_rand _glp_rng_create_rand RNG *rng_create_rand(void); /* create pseudo-random number generator */ #define rng_init_rand _glp_rng_init_rand void rng_init_rand(RNG *rand, int seed); /* initialize pseudo-random number generator */ #define rng_next_rand _glp_rng_next_rand int rng_next_rand(RNG *rand); /* obtain pseudo-random integer in the range [0, 2^31-1] */ #define rng_unif_rand _glp_rng_unif_rand int rng_unif_rand(RNG *rand, int m); /* obtain pseudo-random integer in the range [0, m-1] */ #define rng_delete_rand _glp_rng_delete_rand void rng_delete_rand(RNG *rand); /* delete pseudo-random number generator */ #define rng_unif_01 _glp_rng_unif_01 double rng_unif_01(RNG *rand); /* obtain pseudo-random number in the range [0, 1] */ #define rng_uniform _glp_rng_uniform double rng_uniform(RNG *rand, double a, double b); /* obtain pseudo-random number in the range [a, b] */ #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpspx01.c0000644000076500000240000030147413524616144025232 0ustar tamasstaff00000000000000/* glpspx01.c (primal simplex method) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wsign-conversion" #pragma clang diagnostic ignored "-Wsometimes-uninitialized" #pragma clang diagnostic ignored "-Wlogical-op-parentheses" #endif #include "glpspx.h" struct csa { /* common storage area */ /*--------------------------------------------------------------*/ /* LP data */ int m; /* number of rows (auxiliary variables), m > 0 */ int n; /* number of columns (structural variables), n > 0 */ char *type; /* char type[1+m+n]; */ /* type[0] is not used; type[k], 1 <= k <= m+n, is the type of variable x[k]: GLP_FR - free variable GLP_LO - variable with lower bound GLP_UP - variable with upper bound GLP_DB - double-bounded variable GLP_FX - fixed variable */ double *lb; /* double lb[1+m+n]; */ /* lb[0] is not used; lb[k], 1 <= k <= m+n, is an lower bound of variable x[k]; if x[k] has no lower bound, lb[k] is zero */ double *ub; /* double ub[1+m+n]; */ /* ub[0] is not used; ub[k], 1 <= k <= m+n, is an upper bound of variable x[k]; if x[k] has no upper bound, ub[k] is zero; if x[k] is of fixed type, ub[k] is the same as lb[k] */ double *coef; /* double coef[1+m+n]; */ /* coef[0] is not used; coef[k], 1 <= k <= m+n, is an objective coefficient at variable x[k] (note that on phase I auxiliary variables also may have non-zero objective coefficients) */ /*--------------------------------------------------------------*/ /* original objective function */ double *obj; /* double obj[1+n]; */ /* obj[0] is a constant term of the original objective function; obj[j], 1 <= j <= n, is an original objective coefficient at structural variable x[m+j] */ double zeta; /* factor used to scale original objective coefficients; its sign defines original optimization direction: zeta > 0 means minimization, zeta < 0 means maximization */ /*--------------------------------------------------------------*/ /* constraint matrix A; it has m rows and n columns and is stored by columns */ int *A_ptr; /* int A_ptr[1+n+1]; */ /* A_ptr[0] is not used; A_ptr[j], 1 <= j <= n, is starting position of j-th column in arrays A_ind and A_val; note that A_ptr[1] is always 1; A_ptr[n+1] indicates the position after the last element in arrays A_ind and A_val */ int *A_ind; /* int A_ind[A_ptr[n+1]]; */ /* row indices */ double *A_val; /* double A_val[A_ptr[n+1]]; */ /* non-zero element values */ /*--------------------------------------------------------------*/ /* basis header */ int *head; /* int head[1+m+n]; */ /* head[0] is not used; head[i], 1 <= i <= m, is the ordinal number of basic variable xB[i]; head[i] = k means that xB[i] = x[k] and i-th column of matrix B is k-th column of matrix (I|-A); head[m+j], 1 <= j <= n, is the ordinal number of non-basic variable xN[j]; head[m+j] = k means that xN[j] = x[k] and j-th column of matrix N is k-th column of matrix (I|-A) */ char *stat; /* char stat[1+n]; */ /* stat[0] is not used; stat[j], 1 <= j <= n, is the status of non-basic variable xN[j], which defines its active bound: GLP_NL - lower bound is active GLP_NU - upper bound is active GLP_NF - free variable GLP_NS - fixed variable */ /*--------------------------------------------------------------*/ /* matrix B is the basis matrix; it is composed from columns of the augmented constraint matrix (I|-A) corresponding to basic variables and stored in a factorized (invertable) form */ int valid; /* factorization is valid only if this flag is set */ BFD *bfd; /* BFD bfd[1:m,1:m]; */ /* factorized (invertable) form of the basis matrix */ /*--------------------------------------------------------------*/ /* matrix N is a matrix composed from columns of the augmented constraint matrix (I|-A) corresponding to non-basic variables except fixed ones; it is stored by rows and changes every time the basis changes */ int *N_ptr; /* int N_ptr[1+m+1]; */ /* N_ptr[0] is not used; N_ptr[i], 1 <= i <= m, is starting position of i-th row in arrays N_ind and N_val; note that N_ptr[1] is always 1; N_ptr[m+1] indicates the position after the last element in arrays N_ind and N_val */ int *N_len; /* int N_len[1+m]; */ /* N_len[0] is not used; N_len[i], 1 <= i <= m, is length of i-th row (0 to n) */ int *N_ind; /* int N_ind[N_ptr[m+1]]; */ /* column indices */ double *N_val; /* double N_val[N_ptr[m+1]]; */ /* non-zero element values */ /*--------------------------------------------------------------*/ /* working parameters */ int phase; /* search phase: 0 - not determined yet 1 - search for primal feasible solution 2 - search for optimal solution */ glp_long tm_beg; /* time value at the beginning of the search */ int it_beg; /* simplex iteration count at the beginning of the search */ int it_cnt; /* simplex iteration count; it increases by one every time the basis changes (including the case when a non-basic variable jumps to its opposite bound) */ int it_dpy; /* simplex iteration count at the most recent display output */ /*--------------------------------------------------------------*/ /* basic solution components */ double *bbar; /* double bbar[1+m]; */ /* bbar[0] is not used; bbar[i], 1 <= i <= m, is primal value of basic variable xB[i] (if xB[i] is free, its primal value is not updated) */ double *cbar; /* double cbar[1+n]; */ /* cbar[0] is not used; cbar[j], 1 <= j <= n, is reduced cost of non-basic variable xN[j] (if xN[j] is fixed, its reduced cost is not updated) */ /*--------------------------------------------------------------*/ /* the following pricing technique options may be used: GLP_PT_STD - standard ("textbook") pricing; GLP_PT_PSE - projected steepest edge; GLP_PT_DVX - Devex pricing (not implemented yet); in case of GLP_PT_STD the reference space is not used, and all steepest edge coefficients are set to 1 */ int refct; /* this count is set to an initial value when the reference space is defined and decreases by one every time the basis changes; once this count reaches zero, the reference space is redefined again */ char *refsp; /* char refsp[1+m+n]; */ /* refsp[0] is not used; refsp[k], 1 <= k <= m+n, is the flag which means that variable x[k] belongs to the current reference space */ double *gamma; /* double gamma[1+n]; */ /* gamma[0] is not used; gamma[j], 1 <= j <= n, is the steepest edge coefficient for non-basic variable xN[j]; if xN[j] is fixed, gamma[j] is not used and just set to 1 */ /*--------------------------------------------------------------*/ /* non-basic variable xN[q] chosen to enter the basis */ int q; /* index of the non-basic variable xN[q] chosen, 1 <= q <= n; if the set of eligible non-basic variables is empty and thus no variable has been chosen, q is set to 0 */ /*--------------------------------------------------------------*/ /* pivot column of the simplex table corresponding to non-basic variable xN[q] chosen is the following vector: T * e[q] = - inv(B) * N * e[q] = - inv(B) * N[q], where B is the current basis matrix, N[q] is a column of the matrix (I|-A) corresponding to xN[q] */ int tcol_nnz; /* number of non-zero components, 0 <= nnz <= m */ int *tcol_ind; /* int tcol_ind[1+m]; */ /* tcol_ind[0] is not used; tcol_ind[t], 1 <= t <= nnz, is an index of non-zero component, i.e. tcol_ind[t] = i means that tcol_vec[i] != 0 */ double *tcol_vec; /* double tcol_vec[1+m]; */ /* tcol_vec[0] is not used; tcol_vec[i], 1 <= i <= m, is a numeric value of i-th component of the column */ double tcol_max; /* infinity (maximum) norm of the column (max |tcol_vec[i]|) */ int tcol_num; /* number of significant non-zero components, which means that: |tcol_vec[i]| >= eps for i in tcol_ind[1,...,num], |tcol_vec[i]| < eps for i in tcol_ind[num+1,...,nnz], where eps is a pivot tolerance */ /*--------------------------------------------------------------*/ /* basic variable xB[p] chosen to leave the basis */ int p; /* index of the basic variable xB[p] chosen, 1 <= p <= m; p = 0 means that no basic variable reaches its bound; p < 0 means that non-basic variable xN[q] reaches its opposite bound before any basic variable */ int p_stat; /* new status (GLP_NL, GLP_NU, or GLP_NS) to be assigned to xB[p] once it has left the basis */ double teta; /* change of non-basic variable xN[q] (see above), on which xB[p] (or, if p < 0, xN[q] itself) reaches its bound */ /*--------------------------------------------------------------*/ /* pivot row of the simplex table corresponding to basic variable xB[p] chosen is the following vector: T' * e[p] = - N' * inv(B') * e[p] = - N' * rho, where B' is a matrix transposed to the current basis matrix, N' is a matrix, whose rows are columns of the matrix (I|-A) corresponding to non-basic non-fixed variables */ int trow_nnz; /* number of non-zero components, 0 <= nnz <= n */ int *trow_ind; /* int trow_ind[1+n]; */ /* trow_ind[0] is not used; trow_ind[t], 1 <= t <= nnz, is an index of non-zero component, i.e. trow_ind[t] = j means that trow_vec[j] != 0 */ double *trow_vec; /* int trow_vec[1+n]; */ /* trow_vec[0] is not used; trow_vec[j], 1 <= j <= n, is a numeric value of j-th component of the row */ /*--------------------------------------------------------------*/ /* working arrays */ double *work1; /* double work1[1+m]; */ double *work2; /* double work2[1+m]; */ double *work3; /* double work3[1+m]; */ double *work4; /* double work4[1+m]; */ }; static const double kappa = 0.10; /*********************************************************************** * alloc_csa - allocate common storage area * * This routine allocates all arrays in the common storage area (CSA) * and returns a pointer to the CSA. */ static struct csa *alloc_csa(glp_prob *lp) { struct csa *csa; int m = lp->m; int n = lp->n; int nnz = lp->nnz; csa = xmalloc(sizeof(struct csa)); xassert(m > 0 && n > 0); csa->m = m; csa->n = n; csa->type = xcalloc(1+m+n, sizeof(char)); csa->lb = xcalloc(1+m+n, sizeof(double)); csa->ub = xcalloc(1+m+n, sizeof(double)); csa->coef = xcalloc(1+m+n, sizeof(double)); csa->obj = xcalloc(1+n, sizeof(double)); csa->A_ptr = xcalloc(1+n+1, sizeof(int)); csa->A_ind = xcalloc(1+nnz, sizeof(int)); csa->A_val = xcalloc(1+nnz, sizeof(double)); csa->head = xcalloc(1+m+n, sizeof(int)); csa->stat = xcalloc(1+n, sizeof(char)); csa->N_ptr = xcalloc(1+m+1, sizeof(int)); csa->N_len = xcalloc(1+m, sizeof(int)); csa->N_ind = NULL; /* will be allocated later */ csa->N_val = NULL; /* will be allocated later */ csa->bbar = xcalloc(1+m, sizeof(double)); csa->cbar = xcalloc(1+n, sizeof(double)); csa->refsp = xcalloc(1+m+n, sizeof(char)); csa->gamma = xcalloc(1+n, sizeof(double)); csa->tcol_ind = xcalloc(1+m, sizeof(int)); csa->tcol_vec = xcalloc(1+m, sizeof(double)); csa->trow_ind = xcalloc(1+n, sizeof(int)); csa->trow_vec = xcalloc(1+n, sizeof(double)); csa->work1 = xcalloc(1+m, sizeof(double)); csa->work2 = xcalloc(1+m, sizeof(double)); csa->work3 = xcalloc(1+m, sizeof(double)); csa->work4 = xcalloc(1+m, sizeof(double)); return csa; } /*********************************************************************** * init_csa - initialize common storage area * * This routine initializes all data structures in the common storage * area (CSA). */ static void alloc_N(struct csa *csa); static void build_N(struct csa *csa); static void init_csa(struct csa *csa, glp_prob *lp) { int m = csa->m; int n = csa->n; char *type = csa->type; double *lb = csa->lb; double *ub = csa->ub; double *coef = csa->coef; double *obj = csa->obj; int *A_ptr = csa->A_ptr; int *A_ind = csa->A_ind; double *A_val = csa->A_val; int *head = csa->head; char *stat = csa->stat; char *refsp = csa->refsp; double *gamma = csa->gamma; int i, j, k, loc; double cmax; /* auxiliary variables */ for (i = 1; i <= m; i++) { GLPROW *row = lp->row[i]; type[i] = (char)row->type; lb[i] = row->lb * row->rii; ub[i] = row->ub * row->rii; coef[i] = 0.0; } /* structural variables */ for (j = 1; j <= n; j++) { GLPCOL *col = lp->col[j]; type[m+j] = (char)col->type; lb[m+j] = col->lb / col->sjj; ub[m+j] = col->ub / col->sjj; coef[m+j] = col->coef * col->sjj; } /* original objective function */ obj[0] = lp->c0; memcpy(&obj[1], &coef[m+1], n * sizeof(double)); /* factor used to scale original objective coefficients */ cmax = 0.0; for (j = 1; j <= n; j++) if (cmax < fabs(obj[j])) cmax = fabs(obj[j]); if (cmax == 0.0) cmax = 1.0; switch (lp->dir) { case GLP_MIN: csa->zeta = + 1.0 / cmax; break; case GLP_MAX: csa->zeta = - 1.0 / cmax; break; default: xassert(lp != lp); } #if 1 if (fabs(csa->zeta) < 1.0) csa->zeta *= 1000.0; #endif /* matrix A (by columns) */ loc = 1; for (j = 1; j <= n; j++) { GLPAIJ *aij; A_ptr[j] = loc; for (aij = lp->col[j]->ptr; aij != NULL; aij = aij->c_next) { A_ind[loc] = aij->row->i; A_val[loc] = aij->row->rii * aij->val * aij->col->sjj; loc++; } } A_ptr[n+1] = loc; xassert(loc == lp->nnz+1); /* basis header */ xassert(lp->valid); memcpy(&head[1], &lp->head[1], m * sizeof(int)); k = 0; for (i = 1; i <= m; i++) { GLPROW *row = lp->row[i]; if (row->stat != GLP_BS) { k++; xassert(k <= n); head[m+k] = i; stat[k] = (char)row->stat; } } for (j = 1; j <= n; j++) { GLPCOL *col = lp->col[j]; if (col->stat != GLP_BS) { k++; xassert(k <= n); head[m+k] = m + j; stat[k] = (char)col->stat; } } xassert(k == n); /* factorization of matrix B */ csa->valid = 1, lp->valid = 0; csa->bfd = lp->bfd, lp->bfd = NULL; /* matrix N (by rows) */ alloc_N(csa); build_N(csa); /* working parameters */ csa->phase = 0; csa->tm_beg = xtime(); csa->it_beg = csa->it_cnt = lp->it_cnt; csa->it_dpy = -1; /* reference space and steepest edge coefficients */ csa->refct = 0; memset(&refsp[1], 0, (m+n) * sizeof(char)); for (j = 1; j <= n; j++) gamma[j] = 1.0; return; } /*********************************************************************** * invert_B - compute factorization of the basis matrix * * This routine computes factorization of the current basis matrix B. * * If the operation is successful, the routine returns zero, otherwise * non-zero. */ static int inv_col(void *info, int i, int ind[], double val[]) { /* this auxiliary routine returns row indices and numeric values of non-zero elements of i-th column of the basis matrix */ struct csa *csa = info; int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; #endif int *A_ptr = csa->A_ptr; int *A_ind = csa->A_ind; double *A_val = csa->A_val; int *head = csa->head; int k, len, ptr, t; #ifdef GLP_DEBUG xassert(1 <= i && i <= m); #endif k = head[i]; /* B[i] is k-th column of (I|-A) */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif if (k <= m) { /* B[i] is k-th column of submatrix I */ len = 1; ind[1] = k; val[1] = 1.0; } else { /* B[i] is (k-m)-th column of submatrix (-A) */ ptr = A_ptr[k-m]; len = A_ptr[k-m+1] - ptr; memcpy(&ind[1], &A_ind[ptr], len * sizeof(int)); memcpy(&val[1], &A_val[ptr], len * sizeof(double)); for (t = 1; t <= len; t++) val[t] = - val[t]; } return len; } static int invert_B(struct csa *csa) { int ret; ret = bfd_factorize(csa->bfd, csa->m, NULL, inv_col, csa); csa->valid = (ret == 0); return ret; } /*********************************************************************** * update_B - update factorization of the basis matrix * * This routine replaces i-th column of the basis matrix B by k-th * column of the augmented constraint matrix (I|-A) and then updates * the factorization of B. * * If the factorization has been successfully updated, the routine * returns zero, otherwise non-zero. */ static int update_B(struct csa *csa, int i, int k) { int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; #endif int ret; #ifdef GLP_DEBUG xassert(1 <= i && i <= m); xassert(1 <= k && k <= m+n); #endif if (k <= m) { /* new i-th column of B is k-th column of I */ int ind[1+1]; double val[1+1]; ind[1] = k; val[1] = 1.0; xassert(csa->valid); ret = bfd_update_it(csa->bfd, i, 0, 1, ind, val); } else { /* new i-th column of B is (k-m)-th column of (-A) */ int *A_ptr = csa->A_ptr; int *A_ind = csa->A_ind; double *A_val = csa->A_val; double *val = csa->work1; int beg, end, ptr, len; beg = A_ptr[k-m]; end = A_ptr[k-m+1]; len = 0; for (ptr = beg; ptr < end; ptr++) val[++len] = - A_val[ptr]; xassert(csa->valid); ret = bfd_update_it(csa->bfd, i, 0, len, &A_ind[beg-1], val); } csa->valid = (ret == 0); return ret; } /*********************************************************************** * error_ftran - compute residual vector r = h - B * x * * This routine computes the residual vector r = h - B * x, where B is * the current basis matrix, h is the vector of right-hand sides, x is * the solution vector. */ static void error_ftran(struct csa *csa, double h[], double x[], double r[]) { int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; #endif int *A_ptr = csa->A_ptr; int *A_ind = csa->A_ind; double *A_val = csa->A_val; int *head = csa->head; int i, k, beg, end, ptr; double temp; /* compute the residual vector: r = h - B * x = h - B[1] * x[1] - ... - B[m] * x[m], where B[1], ..., B[m] are columns of matrix B */ memcpy(&r[1], &h[1], m * sizeof(double)); for (i = 1; i <= m; i++) { temp = x[i]; if (temp == 0.0) continue; k = head[i]; /* B[i] is k-th column of (I|-A) */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif if (k <= m) { /* B[i] is k-th column of submatrix I */ r[k] -= temp; } else { /* B[i] is (k-m)-th column of submatrix (-A) */ beg = A_ptr[k-m]; end = A_ptr[k-m+1]; for (ptr = beg; ptr < end; ptr++) r[A_ind[ptr]] += A_val[ptr] * temp; } } return; } /*********************************************************************** * refine_ftran - refine solution of B * x = h * * This routine performs one iteration to refine the solution of * the system B * x = h, where B is the current basis matrix, h is the * vector of right-hand sides, x is the solution vector. */ static void refine_ftran(struct csa *csa, double h[], double x[]) { int m = csa->m; double *r = csa->work1; double *d = csa->work1; int i; /* compute the residual vector r = h - B * x */ error_ftran(csa, h, x, r); /* compute the correction vector d = inv(B) * r */ xassert(csa->valid); bfd_ftran(csa->bfd, d); /* refine the solution vector (new x) = (old x) + d */ for (i = 1; i <= m; i++) x[i] += d[i]; return; } /*********************************************************************** * error_btran - compute residual vector r = h - B'* x * * This routine computes the residual vector r = h - B'* x, where B' * is a matrix transposed to the current basis matrix, h is the vector * of right-hand sides, x is the solution vector. */ static void error_btran(struct csa *csa, double h[], double x[], double r[]) { int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; #endif int *A_ptr = csa->A_ptr; int *A_ind = csa->A_ind; double *A_val = csa->A_val; int *head = csa->head; int i, k, beg, end, ptr; double temp; /* compute the residual vector r = b - B'* x */ for (i = 1; i <= m; i++) { /* r[i] := b[i] - (i-th column of B)'* x */ k = head[i]; /* B[i] is k-th column of (I|-A) */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif temp = h[i]; if (k <= m) { /* B[i] is k-th column of submatrix I */ temp -= x[k]; } else { /* B[i] is (k-m)-th column of submatrix (-A) */ beg = A_ptr[k-m]; end = A_ptr[k-m+1]; for (ptr = beg; ptr < end; ptr++) temp += A_val[ptr] * x[A_ind[ptr]]; } r[i] = temp; } return; } /*********************************************************************** * refine_btran - refine solution of B'* x = h * * This routine performs one iteration to refine the solution of the * system B'* x = h, where B' is a matrix transposed to the current * basis matrix, h is the vector of right-hand sides, x is the solution * vector. */ static void refine_btran(struct csa *csa, double h[], double x[]) { int m = csa->m; double *r = csa->work1; double *d = csa->work1; int i; /* compute the residual vector r = h - B'* x */ error_btran(csa, h, x, r); /* compute the correction vector d = inv(B') * r */ xassert(csa->valid); bfd_btran(csa->bfd, d); /* refine the solution vector (new x) = (old x) + d */ for (i = 1; i <= m; i++) x[i] += d[i]; return; } /*********************************************************************** * alloc_N - allocate matrix N * * This routine determines maximal row lengths of matrix N, sets its * row pointers, and then allocates arrays N_ind and N_val. * * Note that some fixed structural variables may temporarily become * double-bounded, so corresponding columns of matrix A should not be * ignored on calculating maximal row lengths of matrix N. */ static void alloc_N(struct csa *csa) { int m = csa->m; int n = csa->n; int *A_ptr = csa->A_ptr; int *A_ind = csa->A_ind; int *N_ptr = csa->N_ptr; int *N_len = csa->N_len; int i, j, beg, end, ptr; /* determine number of non-zeros in each row of the augmented constraint matrix (I|-A) */ for (i = 1; i <= m; i++) N_len[i] = 1; for (j = 1; j <= n; j++) { beg = A_ptr[j]; end = A_ptr[j+1]; for (ptr = beg; ptr < end; ptr++) N_len[A_ind[ptr]]++; } /* determine maximal row lengths of matrix N and set its row pointers */ N_ptr[1] = 1; for (i = 1; i <= m; i++) { /* row of matrix N cannot have more than n non-zeros */ if (N_len[i] > n) N_len[i] = n; N_ptr[i+1] = N_ptr[i] + N_len[i]; } /* now maximal number of non-zeros in matrix N is known */ csa->N_ind = xcalloc(N_ptr[m+1], sizeof(int)); csa->N_val = xcalloc(N_ptr[m+1], sizeof(double)); return; } /*********************************************************************** * add_N_col - add column of matrix (I|-A) to matrix N * * This routine adds j-th column to matrix N which is k-th column of * the augmented constraint matrix (I|-A). (It is assumed that old j-th * column was previously removed from matrix N.) */ static void add_N_col(struct csa *csa, int j, int k) { int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; #endif int *N_ptr = csa->N_ptr; int *N_len = csa->N_len; int *N_ind = csa->N_ind; double *N_val = csa->N_val; int pos; #ifdef GLP_DEBUG xassert(1 <= j && j <= n); xassert(1 <= k && k <= m+n); #endif if (k <= m) { /* N[j] is k-th column of submatrix I */ pos = N_ptr[k] + (N_len[k]++); #ifdef GLP_DEBUG xassert(pos < N_ptr[k+1]); #endif N_ind[pos] = j; N_val[pos] = 1.0; } else { /* N[j] is (k-m)-th column of submatrix (-A) */ int *A_ptr = csa->A_ptr; int *A_ind = csa->A_ind; double *A_val = csa->A_val; int i, beg, end, ptr; beg = A_ptr[k-m]; end = A_ptr[k-m+1]; for (ptr = beg; ptr < end; ptr++) { i = A_ind[ptr]; /* row number */ pos = N_ptr[i] + (N_len[i]++); #ifdef GLP_DEBUG xassert(pos < N_ptr[i+1]); #endif N_ind[pos] = j; N_val[pos] = - A_val[ptr]; } } return; } /*********************************************************************** * del_N_col - remove column of matrix (I|-A) from matrix N * * This routine removes j-th column from matrix N which is k-th column * of the augmented constraint matrix (I|-A). */ static void del_N_col(struct csa *csa, int j, int k) { int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; #endif int *N_ptr = csa->N_ptr; int *N_len = csa->N_len; int *N_ind = csa->N_ind; double *N_val = csa->N_val; int pos, head, tail; #ifdef GLP_DEBUG xassert(1 <= j && j <= n); xassert(1 <= k && k <= m+n); #endif if (k <= m) { /* N[j] is k-th column of submatrix I */ /* find element in k-th row of N */ head = N_ptr[k]; for (pos = head; N_ind[pos] != j; pos++) /* nop */; /* and remove it from the row list */ tail = head + (--N_len[k]); #ifdef GLP_DEBUG xassert(pos <= tail); #endif N_ind[pos] = N_ind[tail]; N_val[pos] = N_val[tail]; } else { /* N[j] is (k-m)-th column of submatrix (-A) */ int *A_ptr = csa->A_ptr; int *A_ind = csa->A_ind; int i, beg, end, ptr; beg = A_ptr[k-m]; end = A_ptr[k-m+1]; for (ptr = beg; ptr < end; ptr++) { i = A_ind[ptr]; /* row number */ /* find element in i-th row of N */ head = N_ptr[i]; for (pos = head; N_ind[pos] != j; pos++) /* nop */; /* and remove it from the row list */ tail = head + (--N_len[i]); #ifdef GLP_DEBUG xassert(pos <= tail); #endif N_ind[pos] = N_ind[tail]; N_val[pos] = N_val[tail]; } } return; } /*********************************************************************** * build_N - build matrix N for current basis * * This routine builds matrix N for the current basis from columns * of the augmented constraint matrix (I|-A) corresponding to non-basic * non-fixed variables. */ static void build_N(struct csa *csa) { int m = csa->m; int n = csa->n; int *head = csa->head; char *stat = csa->stat; int *N_len = csa->N_len; int j, k; /* N := empty matrix */ memset(&N_len[1], 0, m * sizeof(int)); /* go through non-basic columns of matrix (I|-A) */ for (j = 1; j <= n; j++) { if (stat[j] != GLP_NS) { /* xN[j] is non-fixed; add j-th column to matrix N which is k-th column of matrix (I|-A) */ k = head[m+j]; /* x[k] = xN[j] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif add_N_col(csa, j, k); } } return; } /*********************************************************************** * get_xN - determine current value of non-basic variable xN[j] * * This routine returns the current value of non-basic variable xN[j], * which is a value of its active bound. */ static double get_xN(struct csa *csa, int j) { int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; #endif double *lb = csa->lb; double *ub = csa->ub; int *head = csa->head; char *stat = csa->stat; int k; double xN; #ifdef GLP_DEBUG xassert(1 <= j && j <= n); #endif k = head[m+j]; /* x[k] = xN[j] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif switch (stat[j]) { case GLP_NL: /* x[k] is on its lower bound */ xN = lb[k]; break; case GLP_NU: /* x[k] is on its upper bound */ xN = ub[k]; break; case GLP_NF: /* x[k] is free non-basic variable */ xN = 0.0; break; case GLP_NS: /* x[k] is fixed non-basic variable */ xN = lb[k]; break; default: xassert(stat != stat); } return xN; } /*********************************************************************** * eval_beta - compute primal values of basic variables * * This routine computes current primal values of all basic variables: * * beta = - inv(B) * N * xN, * * where B is the current basis matrix, N is a matrix built of columns * of matrix (I|-A) corresponding to non-basic variables, and xN is the * vector of current values of non-basic variables. */ static void eval_beta(struct csa *csa, double beta[]) { int m = csa->m; int n = csa->n; int *A_ptr = csa->A_ptr; int *A_ind = csa->A_ind; double *A_val = csa->A_val; int *head = csa->head; double *h = csa->work2; int i, j, k, beg, end, ptr; double xN; /* compute the right-hand side vector: h := - N * xN = - N[1] * xN[1] - ... - N[n] * xN[n], where N[1], ..., N[n] are columns of matrix N */ for (i = 1; i <= m; i++) h[i] = 0.0; for (j = 1; j <= n; j++) { k = head[m+j]; /* x[k] = xN[j] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif /* determine current value of xN[j] */ xN = get_xN(csa, j); if (xN == 0.0) continue; if (k <= m) { /* N[j] is k-th column of submatrix I */ h[k] -= xN; } else { /* N[j] is (k-m)-th column of submatrix (-A) */ beg = A_ptr[k-m]; end = A_ptr[k-m+1]; for (ptr = beg; ptr < end; ptr++) h[A_ind[ptr]] += xN * A_val[ptr]; } } /* solve system B * beta = h */ memcpy(&beta[1], &h[1], m * sizeof(double)); xassert(csa->valid); bfd_ftran(csa->bfd, beta); /* and refine the solution */ refine_ftran(csa, h, beta); return; } /*********************************************************************** * eval_pi - compute vector of simplex multipliers * * This routine computes the vector of current simplex multipliers: * * pi = inv(B') * cB, * * where B' is a matrix transposed to the current basis matrix, cB is * a subvector of objective coefficients at basic variables. */ static void eval_pi(struct csa *csa, double pi[]) { int m = csa->m; double *c = csa->coef; int *head = csa->head; double *cB = csa->work2; int i; /* construct the right-hand side vector cB */ for (i = 1; i <= m; i++) cB[i] = c[head[i]]; /* solve system B'* pi = cB */ memcpy(&pi[1], &cB[1], m * sizeof(double)); xassert(csa->valid); bfd_btran(csa->bfd, pi); /* and refine the solution */ refine_btran(csa, cB, pi); return; } /*********************************************************************** * eval_cost - compute reduced cost of non-basic variable xN[j] * * This routine computes the current reduced cost of non-basic variable * xN[j]: * * d[j] = cN[j] - N'[j] * pi, * * where cN[j] is the objective coefficient at variable xN[j], N[j] is * a column of the augmented constraint matrix (I|-A) corresponding to * xN[j], pi is the vector of simplex multipliers. */ static double eval_cost(struct csa *csa, double pi[], int j) { int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; #endif double *coef = csa->coef; int *head = csa->head; int k; double dj; #ifdef GLP_DEBUG xassert(1 <= j && j <= n); #endif k = head[m+j]; /* x[k] = xN[j] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif dj = coef[k]; if (k <= m) { /* N[j] is k-th column of submatrix I */ dj -= pi[k]; } else { /* N[j] is (k-m)-th column of submatrix (-A) */ int *A_ptr = csa->A_ptr; int *A_ind = csa->A_ind; double *A_val = csa->A_val; int beg, end, ptr; beg = A_ptr[k-m]; end = A_ptr[k-m+1]; for (ptr = beg; ptr < end; ptr++) dj += A_val[ptr] * pi[A_ind[ptr]]; } return dj; } /*********************************************************************** * eval_bbar - compute and store primal values of basic variables * * This routine computes primal values of all basic variables and then * stores them in the solution array. */ static void eval_bbar(struct csa *csa) { eval_beta(csa, csa->bbar); return; } /*********************************************************************** * eval_cbar - compute and store reduced costs of non-basic variables * * This routine computes reduced costs of all non-basic variables and * then stores them in the solution array. */ static void eval_cbar(struct csa *csa) { #ifdef GLP_DEBUG int m = csa->m; #endif int n = csa->n; #ifdef GLP_DEBUG int *head = csa->head; #endif double *cbar = csa->cbar; double *pi = csa->work3; int j; #ifdef GLP_DEBUG int k; #endif /* compute simplex multipliers */ eval_pi(csa, pi); /* compute and store reduced costs */ for (j = 1; j <= n; j++) { #ifdef GLP_DEBUG k = head[m+j]; /* x[k] = xN[j] */ xassert(1 <= k && k <= m+n); #endif cbar[j] = eval_cost(csa, pi, j); } return; } /*********************************************************************** * reset_refsp - reset the reference space * * This routine resets (redefines) the reference space used in the * projected steepest edge pricing algorithm. */ static void reset_refsp(struct csa *csa) { int m = csa->m; int n = csa->n; int *head = csa->head; char *refsp = csa->refsp; double *gamma = csa->gamma; int j, k; xassert(csa->refct == 0); csa->refct = 1000; memset(&refsp[1], 0, (m+n) * sizeof(char)); for (j = 1; j <= n; j++) { k = head[m+j]; /* x[k] = xN[j] */ refsp[k] = 1; gamma[j] = 1.0; } return; } /*********************************************************************** * eval_gamma - compute steepest edge coefficient * * This routine computes the steepest edge coefficient for non-basic * variable xN[j] using its direct definition: * * gamma[j] = delta[j] + sum alfa[i,j]^2, * i in R * * where delta[j] = 1, if xN[j] is in the current reference space, * and 0 otherwise; R is a set of basic variables xB[i], which are in * the current reference space; alfa[i,j] are elements of the current * simplex table. * * NOTE: The routine is intended only for debugginig purposes. */ static double eval_gamma(struct csa *csa, int j) { int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; #endif int *head = csa->head; char *refsp = csa->refsp; double *alfa = csa->work3; double *h = csa->work3; int i, k; double gamma; #ifdef GLP_DEBUG xassert(1 <= j && j <= n); #endif k = head[m+j]; /* x[k] = xN[j] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif /* construct the right-hand side vector h = - N[j] */ for (i = 1; i <= m; i++) h[i] = 0.0; if (k <= m) { /* N[j] is k-th column of submatrix I */ h[k] = -1.0; } else { /* N[j] is (k-m)-th column of submatrix (-A) */ int *A_ptr = csa->A_ptr; int *A_ind = csa->A_ind; double *A_val = csa->A_val; int beg, end, ptr; beg = A_ptr[k-m]; end = A_ptr[k-m+1]; for (ptr = beg; ptr < end; ptr++) h[A_ind[ptr]] = A_val[ptr]; } /* solve system B * alfa = h */ xassert(csa->valid); bfd_ftran(csa->bfd, alfa); /* compute gamma */ gamma = (refsp[k] ? 1.0 : 0.0); for (i = 1; i <= m; i++) { k = head[i]; #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif if (refsp[k]) gamma += alfa[i] * alfa[i]; } return gamma; } /*********************************************************************** * chuzc - choose non-basic variable (column of the simplex table) * * This routine chooses non-basic variable xN[q], which has largest * weighted reduced cost: * * |d[q]| / sqrt(gamma[q]) = max |d[j]| / sqrt(gamma[j]), * j in J * * where J is a subset of eligible non-basic variables xN[j], d[j] is * reduced cost of xN[j], gamma[j] is the steepest edge coefficient. * * The working objective function is always minimized, so the sign of * d[q] determines direction, in which xN[q] has to change: * * if d[q] < 0, xN[q] has to increase; * * if d[q] > 0, xN[q] has to decrease. * * If |d[j]| <= tol_dj, where tol_dj is a specified tolerance, xN[j] * is not included in J and therefore ignored. (It is assumed that the * working objective row is appropriately scaled, i.e. max|c[k]| = 1.) * * If J is empty and no variable has been chosen, q is set to 0. */ static void chuzc(struct csa *csa, double tol_dj) { int n = csa->n; char *stat = csa->stat; double *cbar = csa->cbar; double *gamma = csa->gamma; int j, q; double dj, best, temp; /* nothing is chosen so far */ q = 0, best = 0.0; /* look through the list of non-basic variables */ for (j = 1; j <= n; j++) { dj = cbar[j]; switch (stat[j]) { case GLP_NL: /* xN[j] can increase */ if (dj >= - tol_dj) continue; break; case GLP_NU: /* xN[j] can decrease */ if (dj <= + tol_dj) continue; break; case GLP_NF: /* xN[j] can change in any direction */ if (- tol_dj <= dj && dj <= + tol_dj) continue; break; case GLP_NS: /* xN[j] cannot change at all */ continue; default: xassert(stat != stat); } /* xN[j] is eligible non-basic variable; choose one which has largest weighted reduced cost */ #ifdef GLP_DEBUG xassert(gamma[j] > 0.0); #endif temp = (dj * dj) / gamma[j]; if (best < temp) q = j, best = temp; } /* store the index of non-basic variable xN[q] chosen */ csa->q = q; return; } /*********************************************************************** * eval_tcol - compute pivot column of the simplex table * * This routine computes the pivot column of the simplex table, which * corresponds to non-basic variable xN[q] chosen. * * The pivot column is the following vector: * * tcol = T * e[q] = - inv(B) * N * e[q] = - inv(B) * N[q], * * where B is the current basis matrix, N[q] is a column of the matrix * (I|-A) corresponding to variable xN[q]. */ static void eval_tcol(struct csa *csa) { int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; #endif int *head = csa->head; int q = csa->q; int *tcol_ind = csa->tcol_ind; double *tcol_vec = csa->tcol_vec; double *h = csa->tcol_vec; int i, k, nnz; #ifdef GLP_DEBUG xassert(1 <= q && q <= n); #endif k = head[m+q]; /* x[k] = xN[q] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif /* construct the right-hand side vector h = - N[q] */ for (i = 1; i <= m; i++) h[i] = 0.0; if (k <= m) { /* N[q] is k-th column of submatrix I */ h[k] = -1.0; } else { /* N[q] is (k-m)-th column of submatrix (-A) */ int *A_ptr = csa->A_ptr; int *A_ind = csa->A_ind; double *A_val = csa->A_val; int beg, end, ptr; beg = A_ptr[k-m]; end = A_ptr[k-m+1]; for (ptr = beg; ptr < end; ptr++) h[A_ind[ptr]] = A_val[ptr]; } /* solve system B * tcol = h */ xassert(csa->valid); bfd_ftran(csa->bfd, tcol_vec); /* construct sparse pattern of the pivot column */ nnz = 0; for (i = 1; i <= m; i++) { if (tcol_vec[i] != 0.0) tcol_ind[++nnz] = i; } csa->tcol_nnz = nnz; return; } /*********************************************************************** * refine_tcol - refine pivot column of the simplex table * * This routine refines the pivot column of the simplex table assuming * that it was previously computed by the routine eval_tcol. */ static void refine_tcol(struct csa *csa) { int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; #endif int *head = csa->head; int q = csa->q; int *tcol_ind = csa->tcol_ind; double *tcol_vec = csa->tcol_vec; double *h = csa->work3; int i, k, nnz; #ifdef GLP_DEBUG xassert(1 <= q && q <= n); #endif k = head[m+q]; /* x[k] = xN[q] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif /* construct the right-hand side vector h = - N[q] */ for (i = 1; i <= m; i++) h[i] = 0.0; if (k <= m) { /* N[q] is k-th column of submatrix I */ h[k] = -1.0; } else { /* N[q] is (k-m)-th column of submatrix (-A) */ int *A_ptr = csa->A_ptr; int *A_ind = csa->A_ind; double *A_val = csa->A_val; int beg, end, ptr; beg = A_ptr[k-m]; end = A_ptr[k-m+1]; for (ptr = beg; ptr < end; ptr++) h[A_ind[ptr]] = A_val[ptr]; } /* refine solution of B * tcol = h */ refine_ftran(csa, h, tcol_vec); /* construct sparse pattern of the pivot column */ nnz = 0; for (i = 1; i <= m; i++) { if (tcol_vec[i] != 0.0) tcol_ind[++nnz] = i; } csa->tcol_nnz = nnz; return; } /*********************************************************************** * sort_tcol - sort pivot column of the simplex table * * This routine reorders the list of non-zero elements of the pivot * column to put significant elements, whose magnitude is not less than * a specified tolerance, in front of the list, and stores the number * of significant elements in tcol_num. */ static void sort_tcol(struct csa *csa, double tol_piv) { #ifdef GLP_DEBUG int m = csa->m; #endif int nnz = csa->tcol_nnz; int *tcol_ind = csa->tcol_ind; double *tcol_vec = csa->tcol_vec; int i, num, pos; double big, eps, temp; /* compute infinity (maximum) norm of the column */ big = 0.0; for (pos = 1; pos <= nnz; pos++) { #ifdef GLP_DEBUG i = tcol_ind[pos]; xassert(1 <= i && i <= m); #endif temp = fabs(tcol_vec[tcol_ind[pos]]); if (big < temp) big = temp; } csa->tcol_max = big; /* determine absolute pivot tolerance */ eps = tol_piv * (1.0 + 0.01 * big); /* move significant column components to front of the list */ for (num = 0; num < nnz; ) { i = tcol_ind[nnz]; if (fabs(tcol_vec[i]) < eps) nnz--; else { num++; tcol_ind[nnz] = tcol_ind[num]; tcol_ind[num] = i; } } csa->tcol_num = num; return; } /*********************************************************************** * chuzr - choose basic variable (row of the simplex table) * * This routine chooses basic variable xB[p], which reaches its bound * first on changing non-basic variable xN[q] in valid direction. * * The parameter rtol is a relative tolerance used to relax bounds of * basic variables. If rtol = 0, the routine implements the standard * ratio test. Otherwise, if rtol > 0, the routine implements Harris' * two-pass ratio test. In the latter case rtol should be about three * times less than a tolerance used to check primal feasibility. */ static void chuzr(struct csa *csa, double rtol) { int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; #endif char *type = csa->type; double *lb = csa->lb; double *ub = csa->ub; double *coef = csa->coef; int *head = csa->head; int phase = csa->phase; double *bbar = csa->bbar; double *cbar = csa->cbar; int q = csa->q; int *tcol_ind = csa->tcol_ind; double *tcol_vec = csa->tcol_vec; int tcol_num = csa->tcol_num; int i, i_stat, k, p, p_stat, pos; double alfa, big, delta, s, t, teta, tmax; #ifdef GLP_DEBUG xassert(1 <= q && q <= n); #endif /* s := - sign(d[q]), where d[q] is reduced cost of xN[q] */ #ifdef GLP_DEBUG xassert(cbar[q] != 0.0); #endif s = (cbar[q] > 0.0 ? -1.0 : +1.0); /*** FIRST PASS ***/ k = head[m+q]; /* x[k] = xN[q] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif if (type[k] == GLP_DB) { /* xN[q] has both lower and upper bounds */ p = -1, p_stat = 0, teta = ub[k] - lb[k], big = 1.0; } else { /* xN[q] has no opposite bound */ p = 0, p_stat = 0, teta = DBL_MAX, big = 0.0; } /* walk through significant elements of the pivot column */ for (pos = 1; pos <= tcol_num; pos++) { i = tcol_ind[pos]; #ifdef GLP_DEBUG xassert(1 <= i && i <= m); #endif k = head[i]; /* x[k] = xB[i] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif alfa = s * tcol_vec[i]; #ifdef GLP_DEBUG xassert(alfa != 0.0); #endif /* xB[i] = ... + alfa * xN[q] + ..., and due to s we need to consider the only case when xN[q] is increasing */ if (alfa > 0.0) { /* xB[i] is increasing */ if (phase == 1 && coef[k] < 0.0) { /* xB[i] violates its lower bound, which plays the role of an upper bound on phase I */ delta = rtol * (1.0 + kappa * fabs(lb[k])); t = ((lb[k] + delta) - bbar[i]) / alfa; i_stat = GLP_NL; } else if (phase == 1 && coef[k] > 0.0) { /* xB[i] violates its upper bound, which plays the role of an lower bound on phase I */ continue; } else if (type[k] == GLP_UP || type[k] == GLP_DB || type[k] == GLP_FX) { /* xB[i] is within its bounds and has an upper bound */ delta = rtol * (1.0 + kappa * fabs(ub[k])); t = ((ub[k] + delta) - bbar[i]) / alfa; i_stat = GLP_NU; } else { /* xB[i] is within its bounds and has no upper bound */ continue; } } else { /* xB[i] is decreasing */ if (phase == 1 && coef[k] > 0.0) { /* xB[i] violates its upper bound, which plays the role of an lower bound on phase I */ delta = rtol * (1.0 + kappa * fabs(ub[k])); t = ((ub[k] - delta) - bbar[i]) / alfa; i_stat = GLP_NU; } else if (phase == 1 && coef[k] < 0.0) { /* xB[i] violates its lower bound, which plays the role of an upper bound on phase I */ continue; } else if (type[k] == GLP_LO || type[k] == GLP_DB || type[k] == GLP_FX) { /* xB[i] is within its bounds and has an lower bound */ delta = rtol * (1.0 + kappa * fabs(lb[k])); t = ((lb[k] - delta) - bbar[i]) / alfa; i_stat = GLP_NL; } else { /* xB[i] is within its bounds and has no lower bound */ continue; } } /* t is a change of xN[q], on which xB[i] reaches its bound (possibly relaxed); since the basic solution is assumed to be primal feasible (or pseudo feasible on phase I), t has to be non-negative by definition; however, it may happen that xB[i] slightly (i.e. within a tolerance) violates its bound, that leads to negative t; in the latter case, if xB[i] is chosen, negative t means that xN[q] changes in wrong direction; if pivot alfa[i,q] is close to zero, even small bound violation of xB[i] may lead to a large change of xN[q] in wrong direction; let, for example, xB[i] >= 0 and in the current basis its value be -5e-9; let also xN[q] be on its zero bound and should increase; from the ratio test rule it follows that the pivot alfa[i,q] < 0; however, if alfa[i,q] is, say, -1e-9, the change of xN[q] in wrong direction is 5e-9 / (-1e-9) = -5, and using it for updating values of other basic variables will give absolutely wrong results; therefore, if t is negative, we should replace it by exact zero assuming that xB[i] is exactly on its bound, and the violation appears due to round-off errors */ if (t < 0.0) t = 0.0; /* apply minimal ratio test */ if (teta > t || teta == t && big < fabs(alfa)) p = i, p_stat = i_stat, teta = t, big = fabs(alfa); } /* the second pass is skipped in the following cases: */ /* if the standard ratio test is used */ if (rtol == 0.0) goto done; /* if xN[q] reaches its opposite bound or if no basic variable has been chosen on the first pass */ if (p <= 0) goto done; /* if xB[p] is a blocking variable, i.e. if it prevents xN[q] from any change */ if (teta == 0.0) goto done; /*** SECOND PASS ***/ /* here tmax is a maximal change of xN[q], on which the solution remains primal feasible (or pseudo feasible on phase I) within a tolerance */ #if 0 tmax = (1.0 + 10.0 * DBL_EPSILON) * teta; #else tmax = teta; #endif /* nothing is chosen so far */ p = 0, p_stat = 0, teta = DBL_MAX, big = 0.0; /* walk through significant elements of the pivot column */ for (pos = 1; pos <= tcol_num; pos++) { i = tcol_ind[pos]; #ifdef GLP_DEBUG xassert(1 <= i && i <= m); #endif k = head[i]; /* x[k] = xB[i] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif alfa = s * tcol_vec[i]; #ifdef GLP_DEBUG xassert(alfa != 0.0); #endif /* xB[i] = ... + alfa * xN[q] + ..., and due to s we need to consider the only case when xN[q] is increasing */ if (alfa > 0.0) { /* xB[i] is increasing */ if (phase == 1 && coef[k] < 0.0) { /* xB[i] violates its lower bound, which plays the role of an upper bound on phase I */ t = (lb[k] - bbar[i]) / alfa; i_stat = GLP_NL; } else if (phase == 1 && coef[k] > 0.0) { /* xB[i] violates its upper bound, which plays the role of an lower bound on phase I */ continue; } else if (type[k] == GLP_UP || type[k] == GLP_DB || type[k] == GLP_FX) { /* xB[i] is within its bounds and has an upper bound */ t = (ub[k] - bbar[i]) / alfa; i_stat = GLP_NU; } else { /* xB[i] is within its bounds and has no upper bound */ continue; } } else { /* xB[i] is decreasing */ if (phase == 1 && coef[k] > 0.0) { /* xB[i] violates its upper bound, which plays the role of an lower bound on phase I */ t = (ub[k] - bbar[i]) / alfa; i_stat = GLP_NU; } else if (phase == 1 && coef[k] < 0.0) { /* xB[i] violates its lower bound, which plays the role of an upper bound on phase I */ continue; } else if (type[k] == GLP_LO || type[k] == GLP_DB || type[k] == GLP_FX) { /* xB[i] is within its bounds and has an lower bound */ t = (lb[k] - bbar[i]) / alfa; i_stat = GLP_NL; } else { /* xB[i] is within its bounds and has no lower bound */ continue; } } /* (see comments for the first pass) */ if (t < 0.0) t = 0.0; /* t is a change of xN[q], on which xB[i] reaches its bound; if t <= tmax, all basic variables can violate their bounds only within relaxation tolerance delta; we can use this freedom and choose basic variable having largest influence coefficient to avoid possible numeric instability */ if (t <= tmax && big < fabs(alfa)) p = i, p_stat = i_stat, teta = t, big = fabs(alfa); } /* something must be chosen on the second pass */ xassert(p != 0); done: /* store the index and status of basic variable xB[p] chosen */ csa->p = p; if (p > 0 && type[head[p]] == GLP_FX) csa->p_stat = GLP_NS; else csa->p_stat = p_stat; /* store corresponding change of non-basic variable xN[q] */ #ifdef GLP_DEBUG xassert(teta >= 0.0); #endif csa->teta = s * teta; return; } /*********************************************************************** * eval_rho - compute pivot row of the inverse * * This routine computes the pivot (p-th) row of the inverse inv(B), * which corresponds to basic variable xB[p] chosen: * * rho = inv(B') * e[p], * * where B' is a matrix transposed to the current basis matrix, e[p] * is unity vector. */ static void eval_rho(struct csa *csa, double rho[]) { int m = csa->m; int p = csa->p; double *e = rho; int i; #ifdef GLP_DEBUG xassert(1 <= p && p <= m); #endif /* construct the right-hand side vector e[p] */ for (i = 1; i <= m; i++) e[i] = 0.0; e[p] = 1.0; /* solve system B'* rho = e[p] */ xassert(csa->valid); bfd_btran(csa->bfd, rho); return; } /*********************************************************************** * refine_rho - refine pivot row of the inverse * * This routine refines the pivot row of the inverse inv(B) assuming * that it was previously computed by the routine eval_rho. */ static void refine_rho(struct csa *csa, double rho[]) { int m = csa->m; int p = csa->p; double *e = csa->work3; int i; #ifdef GLP_DEBUG xassert(1 <= p && p <= m); #endif /* construct the right-hand side vector e[p] */ for (i = 1; i <= m; i++) e[i] = 0.0; e[p] = 1.0; /* refine solution of B'* rho = e[p] */ refine_btran(csa, e, rho); return; } /*********************************************************************** * eval_trow - compute pivot row of the simplex table * * This routine computes the pivot row of the simplex table, which * corresponds to basic variable xB[p] chosen. * * The pivot row is the following vector: * * trow = T'* e[p] = - N'* inv(B') * e[p] = - N' * rho, * * where rho is the pivot row of the inverse inv(B) previously computed * by the routine eval_rho. * * Note that elements of the pivot row corresponding to fixed non-basic * variables are not computed. */ static void eval_trow(struct csa *csa, double rho[]) { int m = csa->m; int n = csa->n; #ifdef GLP_DEBUG char *stat = csa->stat; #endif int *N_ptr = csa->N_ptr; int *N_len = csa->N_len; int *N_ind = csa->N_ind; double *N_val = csa->N_val; int *trow_ind = csa->trow_ind; double *trow_vec = csa->trow_vec; int i, j, beg, end, ptr, nnz; double temp; /* clear the pivot row */ for (j = 1; j <= n; j++) trow_vec[j] = 0.0; /* compute the pivot row as a linear combination of rows of the matrix N: trow = - rho[1] * N'[1] - ... - rho[m] * N'[m] */ for (i = 1; i <= m; i++) { temp = rho[i]; if (temp == 0.0) continue; /* trow := trow - rho[i] * N'[i] */ beg = N_ptr[i]; end = beg + N_len[i]; for (ptr = beg; ptr < end; ptr++) { #ifdef GLP_DEBUG j = N_ind[ptr]; xassert(1 <= j && j <= n); xassert(stat[j] != GLP_NS); #endif trow_vec[N_ind[ptr]] -= temp * N_val[ptr]; } } /* construct sparse pattern of the pivot row */ nnz = 0; for (j = 1; j <= n; j++) { if (trow_vec[j] != 0.0) trow_ind[++nnz] = j; } csa->trow_nnz = nnz; return; } /*********************************************************************** * update_bbar - update values of basic variables * * This routine updates values of all basic variables for the adjacent * basis. */ static void update_bbar(struct csa *csa) { #ifdef GLP_DEBUG int m = csa->m; int n = csa->n; #endif double *bbar = csa->bbar; int q = csa->q; int tcol_nnz = csa->tcol_nnz; int *tcol_ind = csa->tcol_ind; double *tcol_vec = csa->tcol_vec; int p = csa->p; double teta = csa->teta; int i, pos; #ifdef GLP_DEBUG xassert(1 <= q && q <= n); xassert(p < 0 || 1 <= p && p <= m); #endif /* if xN[q] leaves the basis, compute its value in the adjacent basis, where it will replace xB[p] */ if (p > 0) bbar[p] = get_xN(csa, q) + teta; /* update values of other basic variables (except xB[p], because it will be replaced by xN[q]) */ if (teta == 0.0) goto done; for (pos = 1; pos <= tcol_nnz; pos++) { i = tcol_ind[pos]; /* skip xB[p] */ if (i == p) continue; /* (change of xB[i]) = alfa[i,q] * (change of xN[q]) */ bbar[i] += tcol_vec[i] * teta; } done: return; } /*********************************************************************** * reeval_cost - recompute reduced cost of non-basic variable xN[q] * * This routine recomputes reduced cost of non-basic variable xN[q] for * the current basis more accurately using its direct definition: * * d[q] = cN[q] - N'[q] * pi = * * = cN[q] - N'[q] * (inv(B') * cB) = * * = cN[q] - (cB' * inv(B) * N[q]) = * * = cN[q] + cB' * (pivot column). * * It is assumed that the pivot column of the simplex table is already * computed. */ static double reeval_cost(struct csa *csa) { int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; #endif double *coef = csa->coef; int *head = csa->head; int q = csa->q; int tcol_nnz = csa->tcol_nnz; int *tcol_ind = csa->tcol_ind; double *tcol_vec = csa->tcol_vec; int i, pos; double dq; #ifdef GLP_DEBUG xassert(1 <= q && q <= n); #endif dq = coef[head[m+q]]; for (pos = 1; pos <= tcol_nnz; pos++) { i = tcol_ind[pos]; #ifdef GLP_DEBUG xassert(1 <= i && i <= m); #endif dq += coef[head[i]] * tcol_vec[i]; } return dq; } /*********************************************************************** * update_cbar - update reduced costs of non-basic variables * * This routine updates reduced costs of all (except fixed) non-basic * variables for the adjacent basis. */ static void update_cbar(struct csa *csa) { #ifdef GLP_DEBUG int n = csa->n; #endif double *cbar = csa->cbar; int q = csa->q; int trow_nnz = csa->trow_nnz; int *trow_ind = csa->trow_ind; double *trow_vec = csa->trow_vec; int j, pos; double new_dq; #ifdef GLP_DEBUG xassert(1 <= q && q <= n); #endif /* compute reduced cost of xB[p] in the adjacent basis, where it will replace xN[q] */ #ifdef GLP_DEBUG xassert(trow_vec[q] != 0.0); #endif new_dq = (cbar[q] /= trow_vec[q]); /* update reduced costs of other non-basic variables (except xN[q], because it will be replaced by xB[p]) */ for (pos = 1; pos <= trow_nnz; pos++) { j = trow_ind[pos]; /* skip xN[q] */ if (j == q) continue; cbar[j] -= trow_vec[j] * new_dq; } return; } /*********************************************************************** * update_gamma - update steepest edge coefficients * * This routine updates steepest-edge coefficients for the adjacent * basis. */ static void update_gamma(struct csa *csa) { int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; #endif char *type = csa->type; int *A_ptr = csa->A_ptr; int *A_ind = csa->A_ind; double *A_val = csa->A_val; int *head = csa->head; char *refsp = csa->refsp; double *gamma = csa->gamma; int q = csa->q; int tcol_nnz = csa->tcol_nnz; int *tcol_ind = csa->tcol_ind; double *tcol_vec = csa->tcol_vec; int p = csa->p; int trow_nnz = csa->trow_nnz; int *trow_ind = csa->trow_ind; double *trow_vec = csa->trow_vec; double *u = csa->work3; int i, j, k, pos, beg, end, ptr; double gamma_q, delta_q, pivot, s, t, t1, t2; #ifdef GLP_DEBUG xassert(1 <= p && p <= m); xassert(1 <= q && q <= n); #endif /* the basis changes, so decrease the count */ xassert(csa->refct > 0); csa->refct--; /* recompute gamma[q] for the current basis more accurately and compute auxiliary vector u */ gamma_q = delta_q = (refsp[head[m+q]] ? 1.0 : 0.0); for (i = 1; i <= m; i++) u[i] = 0.0; for (pos = 1; pos <= tcol_nnz; pos++) { i = tcol_ind[pos]; if (refsp[head[i]]) { u[i] = t = tcol_vec[i]; gamma_q += t * t; } else u[i] = 0.0; } xassert(csa->valid); bfd_btran(csa->bfd, u); /* update gamma[k] for other non-basic variables (except fixed variables and xN[q], because it will be replaced by xB[p]) */ pivot = trow_vec[q]; #ifdef GLP_DEBUG xassert(pivot != 0.0); #endif for (pos = 1; pos <= trow_nnz; pos++) { j = trow_ind[pos]; /* skip xN[q] */ if (j == q) continue; /* compute t */ t = trow_vec[j] / pivot; /* compute inner product s = N'[j] * u */ k = head[m+j]; /* x[k] = xN[j] */ if (k <= m) s = u[k]; else { s = 0.0; beg = A_ptr[k-m]; end = A_ptr[k-m+1]; for (ptr = beg; ptr < end; ptr++) s -= A_val[ptr] * u[A_ind[ptr]]; } /* compute gamma[k] for the adjacent basis */ t1 = gamma[j] + t * t * gamma_q + 2.0 * t * s; t2 = (refsp[k] ? 1.0 : 0.0) + delta_q * t * t; gamma[j] = (t1 >= t2 ? t1 : t2); if (gamma[j] < DBL_EPSILON) gamma[j] = DBL_EPSILON; } /* compute gamma[q] for the adjacent basis */ if (type[head[p]] == GLP_FX) gamma[q] = 1.0; else { gamma[q] = gamma_q / (pivot * pivot); if (gamma[q] < DBL_EPSILON) gamma[q] = DBL_EPSILON; } return; } /*********************************************************************** * err_in_bbar - compute maximal relative error in primal solution * * This routine returns maximal relative error: * * max |beta[i] - bbar[i]| / (1 + |beta[i]|), * * where beta and bbar are, respectively, directly computed and the * current (updated) values of basic variables. * * NOTE: The routine is intended only for debugginig purposes. */ static double err_in_bbar(struct csa *csa) { int m = csa->m; double *bbar = csa->bbar; int i; double e, emax, *beta; beta = xcalloc(1+m, sizeof(double)); eval_beta(csa, beta); emax = 0.0; for (i = 1; i <= m; i++) { e = fabs(beta[i] - bbar[i]) / (1.0 + fabs(beta[i])); if (emax < e) emax = e; } xfree(beta); return emax; } /*********************************************************************** * err_in_cbar - compute maximal relative error in dual solution * * This routine returns maximal relative error: * * max |cost[j] - cbar[j]| / (1 + |cost[j]|), * * where cost and cbar are, respectively, directly computed and the * current (updated) reduced costs of non-basic non-fixed variables. * * NOTE: The routine is intended only for debugginig purposes. */ static double err_in_cbar(struct csa *csa) { int m = csa->m; int n = csa->n; char *stat = csa->stat; double *cbar = csa->cbar; int j; double e, emax, cost, *pi; pi = xcalloc(1+m, sizeof(double)); eval_pi(csa, pi); emax = 0.0; for (j = 1; j <= n; j++) { if (stat[j] == GLP_NS) continue; cost = eval_cost(csa, pi, j); e = fabs(cost - cbar[j]) / (1.0 + fabs(cost)); if (emax < e) emax = e; } xfree(pi); return emax; } /*********************************************************************** * err_in_gamma - compute maximal relative error in steepest edge cff. * * This routine returns maximal relative error: * * max |gamma'[j] - gamma[j]| / (1 + |gamma'[j]), * * where gamma'[j] and gamma[j] are, respectively, directly computed * and the current (updated) steepest edge coefficients for non-basic * non-fixed variable x[j]. * * NOTE: The routine is intended only for debugginig purposes. */ static double err_in_gamma(struct csa *csa) { int n = csa->n; char *stat = csa->stat; double *gamma = csa->gamma; int j; double e, emax, temp; emax = 0.0; for (j = 1; j <= n; j++) { if (stat[j] == GLP_NS) { xassert(gamma[j] == 1.0); continue; } temp = eval_gamma(csa, j); e = fabs(temp - gamma[j]) / (1.0 + fabs(temp)); if (emax < e) emax = e; } return emax; } /*********************************************************************** * change_basis - change basis header * * This routine changes the basis header to make it corresponding to * the adjacent basis. */ static void change_basis(struct csa *csa) { int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; char *type = csa->type; #endif int *head = csa->head; char *stat = csa->stat; int q = csa->q; int p = csa->p; int p_stat = csa->p_stat; int k; #ifdef GLP_DEBUG xassert(1 <= q && q <= n); #endif if (p < 0) { /* xN[q] goes to its opposite bound */ #ifdef GLP_DEBUG k = head[m+q]; /* x[k] = xN[q] */ xassert(1 <= k && k <= m+n); xassert(type[k] == GLP_DB); #endif switch (stat[q]) { case GLP_NL: /* xN[q] increases */ stat[q] = GLP_NU; break; case GLP_NU: /* xN[q] decreases */ stat[q] = GLP_NL; break; default: xassert(stat != stat); } } else { /* xB[p] leaves the basis, xN[q] enters the basis */ #ifdef GLP_DEBUG xassert(1 <= p && p <= m); k = head[p]; /* x[k] = xB[p] */ switch (p_stat) { case GLP_NL: /* xB[p] goes to its lower bound */ xassert(type[k] == GLP_LO || type[k] == GLP_DB); break; case GLP_NU: /* xB[p] goes to its upper bound */ xassert(type[k] == GLP_UP || type[k] == GLP_DB); break; case GLP_NS: /* xB[p] goes to its fixed value */ xassert(type[k] == GLP_NS); break; default: xassert(p_stat != p_stat); } #endif /* xB[p] <-> xN[q] */ k = head[p], head[p] = head[m+q], head[m+q] = k; stat[q] = (char)p_stat; } return; } /*********************************************************************** * set_aux_obj - construct auxiliary objective function * * The auxiliary objective function is a separable piecewise linear * convex function, which is the sum of primal infeasibilities: * * z = t[1] + ... + t[m+n] -> minimize, * * where: * * / lb[k] - x[k], if x[k] < lb[k] * | * t[k] = < 0, if lb[k] <= x[k] <= ub[k] * | * \ x[k] - ub[k], if x[k] > ub[k] * * This routine computes objective coefficients for the current basis * and returns the number of non-zero terms t[k]. */ static int set_aux_obj(struct csa *csa, double tol_bnd) { int m = csa->m; int n = csa->n; char *type = csa->type; double *lb = csa->lb; double *ub = csa->ub; double *coef = csa->coef; int *head = csa->head; double *bbar = csa->bbar; int i, k, cnt = 0; double eps; /* use a bit more restrictive tolerance */ tol_bnd *= 0.90; /* clear all objective coefficients */ for (k = 1; k <= m+n; k++) coef[k] = 0.0; /* walk through the list of basic variables */ for (i = 1; i <= m; i++) { k = head[i]; /* x[k] = xB[i] */ if (type[k] == GLP_LO || type[k] == GLP_DB || type[k] == GLP_FX) { /* x[k] has lower bound */ eps = tol_bnd * (1.0 + kappa * fabs(lb[k])); if (bbar[i] < lb[k] - eps) { /* and violates it */ coef[k] = -1.0; cnt++; } } if (type[k] == GLP_UP || type[k] == GLP_DB || type[k] == GLP_FX) { /* x[k] has upper bound */ eps = tol_bnd * (1.0 + kappa * fabs(ub[k])); if (bbar[i] > ub[k] + eps) { /* and violates it */ coef[k] = +1.0; cnt++; } } } return cnt; } /*********************************************************************** * set_orig_obj - restore original objective function * * This routine assigns scaled original objective coefficients to the * working objective function. */ static void set_orig_obj(struct csa *csa) { int m = csa->m; int n = csa->n; double *coef = csa->coef; double *obj = csa->obj; double zeta = csa->zeta; int i, j; for (i = 1; i <= m; i++) coef[i] = 0.0; for (j = 1; j <= n; j++) coef[m+j] = zeta * obj[j]; return; } /*********************************************************************** * check_stab - check numerical stability of basic solution * * If the current basic solution is primal feasible (or pseudo feasible * on phase I) within a tolerance, this routine returns zero, otherwise * it returns non-zero. */ static int check_stab(struct csa *csa, double tol_bnd) { int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; #endif char *type = csa->type; double *lb = csa->lb; double *ub = csa->ub; double *coef = csa->coef; int *head = csa->head; int phase = csa->phase; double *bbar = csa->bbar; int i, k; double eps; /* walk through the list of basic variables */ for (i = 1; i <= m; i++) { k = head[i]; /* x[k] = xB[i] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif if (phase == 1 && coef[k] < 0.0) { /* x[k] must not be greater than its lower bound */ #ifdef GLP_DEBUG xassert(type[k] == GLP_LO || type[k] == GLP_DB || type[k] == GLP_FX); #endif eps = tol_bnd * (1.0 + kappa * fabs(lb[k])); if (bbar[i] > lb[k] + eps) return 1; } else if (phase == 1 && coef[k] > 0.0) { /* x[k] must not be less than its upper bound */ #ifdef GLP_DEBUG xassert(type[k] == GLP_UP || type[k] == GLP_DB || type[k] == GLP_FX); #endif eps = tol_bnd * (1.0 + kappa * fabs(ub[k])); if (bbar[i] < ub[k] - eps) return 1; } else { /* either phase = 1 and coef[k] = 0, or phase = 2 */ if (type[k] == GLP_LO || type[k] == GLP_DB || type[k] == GLP_FX) { /* x[k] must not be less than its lower bound */ eps = tol_bnd * (1.0 + kappa * fabs(lb[k])); if (bbar[i] < lb[k] - eps) return 1; } if (type[k] == GLP_UP || type[k] == GLP_DB || type[k] == GLP_FX) { /* x[k] must not be greater then its upper bound */ eps = tol_bnd * (1.0 + kappa * fabs(ub[k])); if (bbar[i] > ub[k] + eps) return 1; } } } /* basic solution is primal feasible within a tolerance */ return 0; } /*********************************************************************** * check_feas - check primal feasibility of basic solution * * If the current basic solution is primal feasible within a tolerance, * this routine returns zero, otherwise it returns non-zero. */ static int check_feas(struct csa *csa, double tol_bnd) { int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; char *type = csa->type; #endif double *lb = csa->lb; double *ub = csa->ub; double *coef = csa->coef; int *head = csa->head; double *bbar = csa->bbar; int i, k; double eps; xassert(csa->phase == 1); /* walk through the list of basic variables */ for (i = 1; i <= m; i++) { k = head[i]; /* x[k] = xB[i] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif if (coef[k] < 0.0) { /* check if x[k] still violates its lower bound */ #ifdef GLP_DEBUG xassert(type[k] == GLP_LO || type[k] == GLP_DB || type[k] == GLP_FX); #endif eps = tol_bnd * (1.0 + kappa * fabs(lb[k])); if (bbar[i] < lb[k] - eps) return 1; } else if (coef[k] > 0.0) { /* check if x[k] still violates its upper bound */ #ifdef GLP_DEBUG xassert(type[k] == GLP_UP || type[k] == GLP_DB || type[k] == GLP_FX); #endif eps = tol_bnd * (1.0 + kappa * fabs(ub[k])); if (bbar[i] > ub[k] + eps) return 1; } } /* basic solution is primal feasible within a tolerance */ return 0; } /*********************************************************************** * eval_obj - compute original objective function * * This routine computes the current value of the original objective * function. */ static double eval_obj(struct csa *csa) { int m = csa->m; int n = csa->n; double *obj = csa->obj; int *head = csa->head; double *bbar = csa->bbar; int i, j, k; double sum; sum = obj[0]; /* walk through the list of basic variables */ for (i = 1; i <= m; i++) { k = head[i]; /* x[k] = xB[i] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif if (k > m) sum += obj[k-m] * bbar[i]; } /* walk through the list of non-basic variables */ for (j = 1; j <= n; j++) { k = head[m+j]; /* x[k] = xN[j] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif if (k > m) sum += obj[k-m] * get_xN(csa, j); } return sum; } /*********************************************************************** * display - display the search progress * * This routine displays some information about the search progress * that includes: * * the search phase; * * the number of simplex iterations performed by the solver; * * the original objective value; * * the sum of (scaled) primal infeasibilities; * * the number of basic fixed variables. */ static void display(struct csa *csa, const glp_smcp *parm, int spec) { int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; #endif char *type = csa->type; double *lb = csa->lb; double *ub = csa->ub; int phase = csa->phase; int *head = csa->head; double *bbar = csa->bbar; int i, k, cnt; double sum; if (parm->msg_lev < GLP_MSG_ON) goto skip; if (parm->out_dly > 0 && 1000.0 * xdifftime(xtime(), csa->tm_beg) < parm->out_dly) goto skip; if (csa->it_cnt == csa->it_dpy) goto skip; if (!spec && csa->it_cnt % parm->out_frq != 0) goto skip; /* compute the sum of primal infeasibilities and determine the number of basic fixed variables */ sum = 0.0, cnt = 0; for (i = 1; i <= m; i++) { k = head[i]; /* x[k] = xB[i] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif if (type[k] == GLP_LO || type[k] == GLP_DB || type[k] == GLP_FX) { /* x[k] has lower bound */ if (bbar[i] < lb[k]) sum += (lb[k] - bbar[i]); } if (type[k] == GLP_UP || type[k] == GLP_DB || type[k] == GLP_FX) { /* x[k] has upper bound */ if (bbar[i] > ub[k]) sum += (bbar[i] - ub[k]); } if (type[k] == GLP_FX) cnt++; } xprintf("%c%6d: obj = %17.9e infeas = %10.3e (%d)\n", phase == 1 ? ' ' : '*', csa->it_cnt, eval_obj(csa), sum, cnt); csa->it_dpy = csa->it_cnt; skip: return; } /*********************************************************************** * store_sol - store basic solution back to the problem object * * This routine stores basic solution components back to the problem * object. */ static void store_sol(struct csa *csa, glp_prob *lp, int p_stat, int d_stat, int ray) { int m = csa->m; int n = csa->n; double zeta = csa->zeta; int *head = csa->head; char *stat = csa->stat; double *bbar = csa->bbar; double *cbar = csa->cbar; int i, j, k; #ifdef GLP_DEBUG xassert(lp->m == m); xassert(lp->n == n); #endif /* basis factorization */ #ifdef GLP_DEBUG xassert(!lp->valid && lp->bfd == NULL); xassert(csa->valid && csa->bfd != NULL); #endif lp->valid = 1, csa->valid = 0; lp->bfd = csa->bfd, csa->bfd = NULL; memcpy(&lp->head[1], &head[1], m * sizeof(int)); /* basic solution status */ lp->pbs_stat = p_stat; lp->dbs_stat = d_stat; /* objective function value */ lp->obj_val = eval_obj(csa); /* simplex iteration count */ lp->it_cnt = csa->it_cnt; /* unbounded ray */ lp->some = ray; /* basic variables */ for (i = 1; i <= m; i++) { k = head[i]; /* x[k] = xB[i] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif if (k <= m) { GLPROW *row = lp->row[k]; row->stat = GLP_BS; row->bind = i; row->prim = bbar[i] / row->rii; row->dual = 0.0; } else { GLPCOL *col = lp->col[k-m]; col->stat = GLP_BS; col->bind = i; col->prim = bbar[i] * col->sjj; col->dual = 0.0; } } /* non-basic variables */ for (j = 1; j <= n; j++) { k = head[m+j]; /* x[k] = xN[j] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif if (k <= m) { GLPROW *row = lp->row[k]; row->stat = stat[j]; row->bind = 0; #if 0 row->prim = get_xN(csa, j) / row->rii; #else switch (stat[j]) { case GLP_NL: row->prim = row->lb; break; case GLP_NU: row->prim = row->ub; break; case GLP_NF: row->prim = 0.0; break; case GLP_NS: row->prim = row->lb; break; default: xassert(stat != stat); } #endif row->dual = (cbar[j] * row->rii) / zeta; } else { GLPCOL *col = lp->col[k-m]; col->stat = stat[j]; col->bind = 0; #if 0 col->prim = get_xN(csa, j) * col->sjj; #else switch (stat[j]) { case GLP_NL: col->prim = col->lb; break; case GLP_NU: col->prim = col->ub; break; case GLP_NF: col->prim = 0.0; break; case GLP_NS: col->prim = col->lb; break; default: xassert(stat != stat); } #endif col->dual = (cbar[j] / col->sjj) / zeta; } } return; } /*********************************************************************** * free_csa - deallocate common storage area * * This routine frees all the memory allocated to arrays in the common * storage area (CSA). */ static void free_csa(struct csa *csa) { xfree(csa->type); xfree(csa->lb); xfree(csa->ub); xfree(csa->coef); xfree(csa->obj); xfree(csa->A_ptr); xfree(csa->A_ind); xfree(csa->A_val); xfree(csa->head); xfree(csa->stat); xfree(csa->N_ptr); xfree(csa->N_len); xfree(csa->N_ind); xfree(csa->N_val); xfree(csa->bbar); xfree(csa->cbar); xfree(csa->refsp); xfree(csa->gamma); xfree(csa->tcol_ind); xfree(csa->tcol_vec); xfree(csa->trow_ind); xfree(csa->trow_vec); xfree(csa->work1); xfree(csa->work2); xfree(csa->work3); xfree(csa->work4); xfree(csa); return; } /*********************************************************************** * spx_primal - core LP solver based on the primal simplex method * * SYNOPSIS * * #include "glpspx.h" * int spx_primal(glp_prob *lp, const glp_smcp *parm); * * DESCRIPTION * * The routine spx_primal is a core LP solver based on the two-phase * primal simplex method. * * RETURNS * * 0 LP instance has been successfully solved. * * GLP_EITLIM * Iteration limit has been exhausted. * * GLP_ETMLIM * Time limit has been exhausted. * * GLP_EFAIL * The solver failed to solve LP instance. */ int spx_primal(glp_prob *lp, const glp_smcp *parm) { struct csa *csa; int binv_st = 2; /* status of basis matrix factorization: 0 - invalid; 1 - just computed; 2 - updated */ int bbar_st = 0; /* status of primal values of basic variables: 0 - invalid; 1 - just computed; 2 - updated */ int cbar_st = 0; /* status of reduced costs of non-basic variables: 0 - invalid; 1 - just computed; 2 - updated */ int rigorous = 0; /* rigorous mode flag; this flag is used to enable iterative refinement on computing pivot rows and columns of the simplex table */ int check = 0; int p_stat, d_stat, ret; /* allocate and initialize the common storage area */ csa = alloc_csa(lp); init_csa(csa, lp); if (parm->msg_lev >= GLP_MSG_DBG) xprintf("Objective scale factor = %g\n", csa->zeta); loop: /* main loop starts here */ /* compute factorization of the basis matrix */ if (binv_st == 0) { ret = invert_B(csa); if (ret != 0) { if (parm->msg_lev >= GLP_MSG_ERR) { xprintf("Error: unable to factorize the basis matrix (%d" ")\n", ret); xprintf("Sorry, basis recovery procedure not implemented" " yet\n"); } xassert(!lp->valid && lp->bfd == NULL); lp->bfd = csa->bfd, csa->bfd = NULL; lp->pbs_stat = lp->dbs_stat = GLP_UNDEF; lp->obj_val = 0.0; lp->it_cnt = csa->it_cnt; lp->some = 0; ret = GLP_EFAIL; goto done; } csa->valid = 1; binv_st = 1; /* just computed */ /* invalidate basic solution components */ bbar_st = cbar_st = 0; } /* compute primal values of basic variables */ if (bbar_st == 0) { eval_bbar(csa); bbar_st = 1; /* just computed */ /* determine the search phase, if not determined yet */ if (csa->phase == 0) { if (set_aux_obj(csa, parm->tol_bnd) > 0) { /* current basic solution is primal infeasible */ /* start to minimize the sum of infeasibilities */ csa->phase = 1; } else { /* current basic solution is primal feasible */ /* start to minimize the original objective function */ set_orig_obj(csa); csa->phase = 2; } xassert(check_stab(csa, parm->tol_bnd) == 0); /* working objective coefficients have been changed, so invalidate reduced costs */ cbar_st = 0; display(csa, parm, 1); } /* make sure that the current basic solution remains primal feasible (or pseudo feasible on phase I) */ if (check_stab(csa, parm->tol_bnd)) { /* there are excessive bound violations due to round-off errors */ if (parm->msg_lev >= GLP_MSG_ERR) xprintf("Warning: numerical instability (primal simplex," " phase %s)\n", csa->phase == 1 ? "I" : "II"); /* restart the search */ csa->phase = 0; binv_st = 0; rigorous = 5; goto loop; } } xassert(csa->phase == 1 || csa->phase == 2); /* on phase I we do not need to wait until the current basic solution becomes dual feasible; it is sufficient to make sure that no basic variable violates its bounds */ if (csa->phase == 1 && !check_feas(csa, parm->tol_bnd)) { /* the current basis is primal feasible; switch to phase II */ csa->phase = 2; set_orig_obj(csa); cbar_st = 0; display(csa, parm, 1); } /* compute reduced costs of non-basic variables */ if (cbar_st == 0) { eval_cbar(csa); cbar_st = 1; /* just computed */ } /* redefine the reference space, if required */ switch (parm->pricing) { case GLP_PT_STD: break; case GLP_PT_PSE: if (csa->refct == 0) reset_refsp(csa); break; default: xassert(parm != parm); } /* at this point the basis factorization and all basic solution components are valid */ xassert(binv_st && bbar_st && cbar_st); /* check accuracy of current basic solution components (only for debugging) */ if (check) { double e_bbar = err_in_bbar(csa); double e_cbar = err_in_cbar(csa); double e_gamma = (parm->pricing == GLP_PT_PSE ? err_in_gamma(csa) : 0.0); xprintf("e_bbar = %10.3e; e_cbar = %10.3e; e_gamma = %10.3e\n", e_bbar, e_cbar, e_gamma); xassert(e_bbar <= 1e-5 && e_cbar <= 1e-5 && e_gamma <= 1e-3); } /* check if the iteration limit has been exhausted */ if (parm->it_lim < INT_MAX && csa->it_cnt - csa->it_beg >= parm->it_lim) { if (bbar_st != 1 || csa->phase == 2 && cbar_st != 1) { if (bbar_st != 1) bbar_st = 0; if (csa->phase == 2 && cbar_st != 1) cbar_st = 0; goto loop; } display(csa, parm, 1); if (parm->msg_lev >= GLP_MSG_ALL) xprintf("ITERATION LIMIT EXCEEDED; SEARCH TERMINATED\n"); switch (csa->phase) { case 1: p_stat = GLP_INFEAS; set_orig_obj(csa); eval_cbar(csa); break; case 2: p_stat = GLP_FEAS; break; default: xassert(csa != csa); } chuzc(csa, parm->tol_dj); d_stat = (csa->q == 0 ? GLP_FEAS : GLP_INFEAS); store_sol(csa, lp, p_stat, d_stat, 0); ret = GLP_EITLIM; goto done; } /* check if the time limit has been exhausted */ if (parm->tm_lim < INT_MAX && 1000.0 * xdifftime(xtime(), csa->tm_beg) >= parm->tm_lim) { if (bbar_st != 1 || csa->phase == 2 && cbar_st != 1) { if (bbar_st != 1) bbar_st = 0; if (csa->phase == 2 && cbar_st != 1) cbar_st = 0; goto loop; } display(csa, parm, 1); if (parm->msg_lev >= GLP_MSG_ALL) xprintf("TIME LIMIT EXCEEDED; SEARCH TERMINATED\n"); switch (csa->phase) { case 1: p_stat = GLP_INFEAS; set_orig_obj(csa); eval_cbar(csa); break; case 2: p_stat = GLP_FEAS; break; default: xassert(csa != csa); } chuzc(csa, parm->tol_dj); d_stat = (csa->q == 0 ? GLP_FEAS : GLP_INFEAS); store_sol(csa, lp, p_stat, d_stat, 0); ret = GLP_ETMLIM; goto done; } /* display the search progress */ display(csa, parm, 0); /* choose non-basic variable xN[q] */ chuzc(csa, parm->tol_dj); if (csa->q == 0) { if (bbar_st != 1 || cbar_st != 1) { if (bbar_st != 1) bbar_st = 0; if (cbar_st != 1) cbar_st = 0; goto loop; } display(csa, parm, 1); switch (csa->phase) { case 1: if (parm->msg_lev >= GLP_MSG_ALL) xprintf("PROBLEM HAS NO FEASIBLE SOLUTION\n"); p_stat = GLP_NOFEAS; set_orig_obj(csa); eval_cbar(csa); chuzc(csa, parm->tol_dj); d_stat = (csa->q == 0 ? GLP_FEAS : GLP_INFEAS); break; case 2: if (parm->msg_lev >= GLP_MSG_ALL) xprintf("OPTIMAL SOLUTION FOUND\n"); p_stat = d_stat = GLP_FEAS; break; default: xassert(csa != csa); } store_sol(csa, lp, p_stat, d_stat, 0); ret = 0; goto done; } /* compute pivot column of the simplex table */ eval_tcol(csa); if (rigorous) refine_tcol(csa); sort_tcol(csa, parm->tol_piv); /* check accuracy of the reduced cost of xN[q] */ { double d1 = csa->cbar[csa->q]; /* less accurate */ double d2 = reeval_cost(csa); /* more accurate */ xassert(d1 != 0.0); if (fabs(d1 - d2) > 1e-5 * (1.0 + fabs(d2)) || !(d1 < 0.0 && d2 < 0.0 || d1 > 0.0 && d2 > 0.0)) { if (parm->msg_lev >= GLP_MSG_DBG) xprintf("d1 = %.12g; d2 = %.12g\n", d1, d2); if (cbar_st != 1 || !rigorous) { if (cbar_st != 1) cbar_st = 0; rigorous = 5; goto loop; } } /* replace cbar[q] by more accurate value keeping its sign */ if (d1 > 0.0) csa->cbar[csa->q] = (d2 > 0.0 ? d2 : +DBL_EPSILON); else csa->cbar[csa->q] = (d2 < 0.0 ? d2 : -DBL_EPSILON); } /* choose basic variable xB[p] */ switch (parm->r_test) { case GLP_RT_STD: chuzr(csa, 0.0); break; case GLP_RT_HAR: chuzr(csa, 0.30 * parm->tol_bnd); break; default: xassert(parm != parm); } if (csa->p == 0) { if (bbar_st != 1 || cbar_st != 1 || !rigorous) { if (bbar_st != 1) bbar_st = 0; if (cbar_st != 1) cbar_st = 0; rigorous = 1; goto loop; } display(csa, parm, 1); switch (csa->phase) { case 1: if (parm->msg_lev >= GLP_MSG_ERR) xprintf("Error: unable to choose basic variable on ph" "ase I\n"); xassert(!lp->valid && lp->bfd == NULL); lp->bfd = csa->bfd, csa->bfd = NULL; lp->pbs_stat = lp->dbs_stat = GLP_UNDEF; lp->obj_val = 0.0; lp->it_cnt = csa->it_cnt; lp->some = 0; ret = GLP_EFAIL; break; case 2: if (parm->msg_lev >= GLP_MSG_ALL) xprintf("PROBLEM HAS UNBOUNDED SOLUTION\n"); store_sol(csa, lp, GLP_FEAS, GLP_NOFEAS, csa->head[csa->m+csa->q]); ret = 0; break; default: xassert(csa != csa); } goto done; } /* check if the pivot element is acceptable */ if (csa->p > 0) { double piv = csa->tcol_vec[csa->p]; double eps = 1e-5 * (1.0 + 0.01 * csa->tcol_max); if (fabs(piv) < eps) { if (parm->msg_lev >= GLP_MSG_DBG) xprintf("piv = %.12g; eps = %g\n", piv, eps); if (!rigorous) { rigorous = 5; goto loop; } } } /* now xN[q] and xB[p] have been chosen anyhow */ /* compute pivot row of the simplex table */ if (csa->p > 0) { double *rho = csa->work4; eval_rho(csa, rho); if (rigorous) refine_rho(csa, rho); eval_trow(csa, rho); } /* accuracy check based on the pivot element */ if (csa->p > 0) { double piv1 = csa->tcol_vec[csa->p]; /* more accurate */ double piv2 = csa->trow_vec[csa->q]; /* less accurate */ xassert(piv1 != 0.0); if (fabs(piv1 - piv2) > 1e-8 * (1.0 + fabs(piv1)) || !(piv1 > 0.0 && piv2 > 0.0 || piv1 < 0.0 && piv2 < 0.0)) { if (parm->msg_lev >= GLP_MSG_DBG) xprintf("piv1 = %.12g; piv2 = %.12g\n", piv1, piv2); if (binv_st != 1 || !rigorous) { if (binv_st != 1) binv_st = 0; rigorous = 5; goto loop; } /* use more accurate version in the pivot row */ if (csa->trow_vec[csa->q] == 0.0) { csa->trow_nnz++; xassert(csa->trow_nnz <= csa->n); csa->trow_ind[csa->trow_nnz] = csa->q; } csa->trow_vec[csa->q] = piv1; } } /* update primal values of basic variables */ update_bbar(csa); bbar_st = 2; /* updated */ /* update reduced costs of non-basic variables */ if (csa->p > 0) { update_cbar(csa); cbar_st = 2; /* updated */ /* on phase I objective coefficient of xB[p] in the adjacent basis becomes zero */ if (csa->phase == 1) { int k = csa->head[csa->p]; /* x[k] = xB[p] -> xN[q] */ csa->cbar[csa->q] -= csa->coef[k]; csa->coef[k] = 0.0; } } /* update steepest edge coefficients */ if (csa->p > 0) { switch (parm->pricing) { case GLP_PT_STD: break; case GLP_PT_PSE: if (csa->refct > 0) update_gamma(csa); break; default: xassert(parm != parm); } } /* update factorization of the basis matrix */ if (csa->p > 0) { ret = update_B(csa, csa->p, csa->head[csa->m+csa->q]); if (ret == 0) binv_st = 2; /* updated */ else { csa->valid = 0; binv_st = 0; /* invalid */ } } /* update matrix N */ if (csa->p > 0) { del_N_col(csa, csa->q, csa->head[csa->m+csa->q]); if (csa->type[csa->head[csa->p]] != GLP_FX) add_N_col(csa, csa->q, csa->head[csa->p]); } /* change the basis header */ change_basis(csa); /* iteration complete */ csa->it_cnt++; if (rigorous > 0) rigorous--; goto loop; done: /* deallocate the common storage area */ free_csa(csa); /* return to the calling program */ return ret; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpini01.c0000644000076500000240000005426313524616144025200 0ustar tamasstaff00000000000000/* glpini01.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wself-assign" #endif #include "glpapi.h" /*---------------------------------------------------------------------- -- triang - find maximal triangular part of a rectangular matrix. -- -- *Synopsis* -- -- int triang(int m, int n, -- void *info, int (*mat)(void *info, int k, int ndx[]), -- int rn[], int cn[]); -- -- *Description* -- -- For a given rectangular (sparse) matrix A with m rows and n columns -- the routine triang tries to find such permutation matrices P and Q -- that the first rows and columns of the matrix B = P*A*Q form a lower -- triangular submatrix of as greatest size as possible: -- -- 1 n -- 1 * . . . . . . x x x x x x -- * * . . . . . x x x x x x -- * * * . . . . x x x x x x -- * * * * . . . x x x x x x -- B = P*A*Q = * * * * * . . x x x x x x -- * * * * * * . x x x x x x -- * * * * * * * x x x x x x -- x x x x x x x x x x x x x -- x x x x x x x x x x x x x -- m x x x x x x x x x x x x x -- -- where: '*' - elements of the lower triangular part, '.' - structural -- zeros, 'x' - other (either non-zero or zero) elements. -- -- The parameter info is a transit pointer passed to the formal routine -- mat (see below). -- -- The formal routine mat specifies the given matrix A in both row- and -- column-wise formats. In order to obtain an i-th row of the matrix A -- the routine triang calls the routine mat with the parameter k = +i, -- 1 <= i <= m. In response the routine mat should store column indices -- of (non-zero) elements of the i-th row to the locations ndx[1], ..., -- ndx[len], where len is number of non-zeros in the i-th row returned -- on exit. Analogously, in order to obtain a j-th column of the matrix -- A, the routine mat is called with the parameter k = -j, 1 <= j <= n, -- and should return pattern of the j-th column in the same way as for -- row patterns. Note that the routine mat may be called more than once -- for the same rows and columns. -- -- On exit the routine computes two resultant arrays rn and cn, which -- define the permutation matrices P and Q, respectively. The array rn -- should have at least 1+m locations, where rn[i] = i' (1 <= i <= m) -- means that i-th row of the original matrix A corresponds to i'-th row -- of the matrix B = P*A*Q. Similarly, the array cn should have at least -- 1+n locations, where cn[j] = j' (1 <= j <= n) means that j-th column -- of the matrix A corresponds to j'-th column of the matrix B. -- -- *Returns* -- -- The routine triang returns the size of the lower tringular part of -- the matrix B = P*A*Q (see the figure above). -- -- *Complexity* -- -- The time complexity of the routine triang is O(nnz), where nnz is -- number of non-zeros in the given matrix A. -- -- *Algorithm* -- -- The routine triang starts from the matrix B = P*Q*A, where P and Q -- are unity matrices, so initially B = A. -- -- Before the next iteration B = (B1 | B2 | B3), where B1 is partially -- built a lower triangular submatrix, B2 is the active submatrix, and -- B3 is a submatrix that contains rejected columns. Thus, the current -- matrix B looks like follows (initially k1 = 1 and k2 = n): -- -- 1 k1 k2 n -- 1 x . . . . . . . . . . . . . # # # -- x x . . . . . . . . . . . . # # # -- x x x . . . . . . . . . . # # # # -- x x x x . . . . . . . . . # # # # -- x x x x x . . . . . . . # # # # # -- k1 x x x x x * * * * * * * # # # # # -- x x x x x * * * * * * * # # # # # -- x x x x x * * * * * * * # # # # # -- x x x x x * * * * * * * # # # # # -- m x x x x x * * * * * * * # # # # # -- <--B1---> <----B2-----> <---B3--> -- -- On each iteartion the routine looks for a singleton row, i.e. some -- row that has the only non-zero in the active submatrix B2. If such -- row exists and the corresponding non-zero is b[i,j], where (by the -- definition) k1 <= i <= m and k1 <= j <= k2, the routine permutes -- k1-th and i-th rows and k1-th and j-th columns of the matrix B (in -- order to place the element in the position b[k1,k1]), removes the -- k1-th column from the active submatrix B2, and adds this column to -- the submatrix B1. If no row singletons exist, but B2 is not empty -- yet, the routine chooses a j-th column, which has maximal number of -- non-zeros among other columns of B2, removes this column from B2 and -- adds it to the submatrix B3 in the hope that new row singletons will -- appear in the active submatrix. */ static int triang(int m, int n, void *info, int (*mat)(void *info, int k, int ndx[]), int rn[], int cn[]) { int *ndx; /* int ndx[1+max(m,n)]; */ /* this array is used for querying row and column patterns of the given matrix A (the third parameter to the routine mat) */ int *rs_len; /* int rs_len[1+m]; */ /* rs_len[0] is not used; rs_len[i], 1 <= i <= m, is number of non-zeros in the i-th row of the matrix A, which (non-zeros) belong to the current active submatrix */ int *rs_head; /* int rs_head[1+n]; */ /* rs_head[len], 0 <= len <= n, is the number i of the first row of the matrix A, for which rs_len[i] = len */ int *rs_prev; /* int rs_prev[1+m]; */ /* rs_prev[0] is not used; rs_prev[i], 1 <= i <= m, is a number i' of the previous row of the matrix A, for which rs_len[i] = rs_len[i'] (zero marks the end of this linked list) */ int *rs_next; /* int rs_next[1+m]; */ /* rs_next[0] is not used; rs_next[i], 1 <= i <= m, is a number i' of the next row of the matrix A, for which rs_len[i] = rs_len[i'] (zero marks the end this linked list) */ int cs_head; /* is a number j of the first column of the matrix A, which has maximal number of non-zeros among other columns */ int *cs_prev; /* cs_prev[1+n]; */ /* cs_prev[0] is not used; cs_prev[j], 1 <= j <= n, is a number of the previous column of the matrix A with the same or greater number of non-zeros than in the j-th column (zero marks the end of this linked list) */ int *cs_next; /* cs_next[1+n]; */ /* cs_next[0] is not used; cs_next[j], 1 <= j <= n, is a number of the next column of the matrix A with the same or lesser number of non-zeros than in the j-th column (zero marks the end of this linked list) */ int i, j, ii, jj, k1, k2, len, t, size = 0; int *head, *rn_inv, *cn_inv; if (!(m > 0 && n > 0)) xerror("triang: m = %d; n = %d; invalid dimension\n", m, n); /* allocate working arrays */ ndx = xcalloc(1+(m >= n ? m : n), sizeof(int)); rs_len = xcalloc(1+m, sizeof(int)); rs_head = xcalloc(1+n, sizeof(int)); rs_prev = xcalloc(1+m, sizeof(int)); rs_next = xcalloc(1+m, sizeof(int)); cs_prev = xcalloc(1+n, sizeof(int)); cs_next = xcalloc(1+n, sizeof(int)); /* build linked lists of columns of the matrix A with the same number of non-zeros */ head = rs_len; /* currently rs_len is used as working array */ for (len = 0; len <= m; len ++) head[len] = 0; for (j = 1; j <= n; j++) { /* obtain length of the j-th column */ len = mat(info, -j, ndx); xassert(0 <= len && len <= m); /* include the j-th column in the corresponding linked list */ cs_prev[j] = head[len]; head[len] = j; } /* merge all linked lists of columns in one linked list, where columns are ordered by descending of their lengths */ cs_head = 0; for (len = 0; len <= m; len++) { for (j = head[len]; j != 0; j = cs_prev[j]) { cs_next[j] = cs_head; cs_head = j; } } jj = 0; for (j = cs_head; j != 0; j = cs_next[j]) { cs_prev[j] = jj; jj = j; } /* build initial doubly linked lists of rows of the matrix A with the same number of non-zeros */ for (len = 0; len <= n; len++) rs_head[len] = 0; for (i = 1; i <= m; i++) { /* obtain length of the i-th row */ rs_len[i] = len = mat(info, +i, ndx); xassert(0 <= len && len <= n); /* include the i-th row in the correspondng linked list */ rs_prev[i] = 0; rs_next[i] = rs_head[len]; if (rs_next[i] != 0) rs_prev[rs_next[i]] = i; rs_head[len] = i; } /* initially all rows and columns of the matrix A are active */ for (i = 1; i <= m; i++) rn[i] = 0; for (j = 1; j <= n; j++) cn[j] = 0; /* set initial bounds of the active submatrix */ k1 = 1, k2 = n; /* main loop starts here */ while (k1 <= k2) { i = rs_head[1]; if (i != 0) { /* the i-th row of the matrix A is a row singleton, since it has the only non-zero in the active submatrix */ xassert(rs_len[i] == 1); /* determine the number j of an active column of the matrix A, in which this non-zero is placed */ j = 0; t = mat(info, +i, ndx); xassert(0 <= t && t <= n); for (t = t; t >= 1; t--) { jj = ndx[t]; xassert(1 <= jj && jj <= n); if (cn[jj] == 0) { xassert(j == 0); j = jj; } } xassert(j != 0); /* the singleton is a[i,j]; move a[i,j] to the position b[k1,k1] of the matrix B */ rn[i] = cn[j] = k1; /* shift the left bound of the active submatrix */ k1++; /* increase the size of the lower triangular part */ size++; } else { /* the current active submatrix has no row singletons */ /* remove an active column with maximal number of non-zeros from the active submatrix */ j = cs_head; xassert(j != 0); cn[j] = k2; /* shift the right bound of the active submatrix */ k2--; } /* the j-th column of the matrix A has been removed from the active submatrix */ /* remove the j-th column from the linked list */ if (cs_prev[j] == 0) cs_head = cs_next[j]; else cs_next[cs_prev[j]] = cs_next[j]; if (cs_next[j] == 0) /* nop */; else cs_prev[cs_next[j]] = cs_prev[j]; /* go through non-zeros of the j-th columns and update active lengths of the corresponding rows */ t = mat(info, -j, ndx); xassert(0 <= t && t <= m); for (t = t; t >= 1; t--) { i = ndx[t]; xassert(1 <= i && i <= m); /* the non-zero a[i,j] has left the active submatrix */ len = rs_len[i]; xassert(len >= 1); /* remove the i-th row from the linked list of rows with active length len */ if (rs_prev[i] == 0) rs_head[len] = rs_next[i]; else rs_next[rs_prev[i]] = rs_next[i]; if (rs_next[i] == 0) /* nop */; else rs_prev[rs_next[i]] = rs_prev[i]; /* decrease the active length of the i-th row */ rs_len[i] = --len; /* return the i-th row to the corresponding linked list */ rs_prev[i] = 0; rs_next[i] = rs_head[len]; if (rs_next[i] != 0) rs_prev[rs_next[i]] = i; rs_head[len] = i; } } /* other rows of the matrix A, which are still active, correspond to rows k1, ..., m of the matrix B (in arbitrary order) */ for (i = 1; i <= m; i++) if (rn[i] == 0) rn[i] = k1++; /* but for columns this is not needed, because now the submatrix B2 has no columns */ for (j = 1; j <= n; j++) xassert(cn[j] != 0); /* perform some optional checks */ /* make sure that rn is a permutation of {1, ..., m} and cn is a permutation of {1, ..., n} */ rn_inv = rs_len; /* used as working array */ for (ii = 1; ii <= m; ii++) rn_inv[ii] = 0; for (i = 1; i <= m; i++) { ii = rn[i]; xassert(1 <= ii && ii <= m); xassert(rn_inv[ii] == 0); rn_inv[ii] = i; } cn_inv = rs_head; /* used as working array */ for (jj = 1; jj <= n; jj++) cn_inv[jj] = 0; for (j = 1; j <= n; j++) { jj = cn[j]; xassert(1 <= jj && jj <= n); xassert(cn_inv[jj] == 0); cn_inv[jj] = j; } /* make sure that the matrix B = P*A*Q really has the form, which was declared */ for (ii = 1; ii <= size; ii++) { int diag = 0; i = rn_inv[ii]; t = mat(info, +i, ndx); xassert(0 <= t && t <= n); for (t = t; t >= 1; t--) { j = ndx[t]; xassert(1 <= j && j <= n); jj = cn[j]; if (jj <= size) xassert(jj <= ii); if (jj == ii) { xassert(!diag); diag = 1; } } xassert(diag); } /* free working arrays */ xfree(ndx); xfree(rs_len); xfree(rs_head); xfree(rs_prev); xfree(rs_next); xfree(cs_prev); xfree(cs_next); /* return to the calling program */ return size; } /*---------------------------------------------------------------------- -- adv_basis - construct advanced initial LP basis. -- -- *Synopsis* -- -- #include "glpini.h" -- void adv_basis(glp_prob *lp); -- -- *Description* -- -- The routine adv_basis constructs an advanced initial basis for an LP -- problem object, which the parameter lp points to. -- -- In order to build the initial basis the routine does the following: -- -- 1) includes in the basis all non-fixed auxiliary variables; -- -- 2) includes in the basis as many as possible non-fixed structural -- variables preserving triangular form of the basis matrix; -- -- 3) includes in the basis appropriate (fixed) auxiliary variables -- in order to complete the basis. -- -- As a result the initial basis has minimum of fixed variables and the -- corresponding basis matrix is triangular. */ static int mat(void *info, int k, int ndx[]) { /* this auxiliary routine returns the pattern of a given row or a given column of the augmented constraint matrix A~ = (I|-A), in which columns of fixed variables are implicitly cleared */ LPX *lp = info; int m = lpx_get_num_rows(lp); int n = lpx_get_num_cols(lp); int typx, i, j, lll, len = 0; if (k > 0) { /* the pattern of the i-th row is required */ i = +k; xassert(1 <= i && i <= m); #if 0 /* 22/XII-2003 */ /* if the auxiliary variable x[i] is non-fixed, include its element (placed in the i-th column) in the pattern */ lpx_get_row_bnds(lp, i, &typx, NULL, NULL); if (typx != LPX_FX) ndx[++len] = i; /* include in the pattern elements placed in columns, which correspond to non-fixed structural varables */ i_beg = aa_ptr[i]; i_end = i_beg + aa_len[i] - 1; for (i_ptr = i_beg; i_ptr <= i_end; i_ptr++) { j = m + sv_ndx[i_ptr]; lpx_get_col_bnds(lp, j-m, &typx, NULL, NULL); if (typx != LPX_FX) ndx[++len] = j; } #else lll = lpx_get_mat_row(lp, i, ndx, NULL); for (k = 1; k <= lll; k++) { lpx_get_col_bnds(lp, ndx[k], &typx, NULL, NULL); if (typx != LPX_FX) ndx[++len] = m + ndx[k]; } lpx_get_row_bnds(lp, i, &typx, NULL, NULL); if (typx != LPX_FX) ndx[++len] = i; #endif } else { /* the pattern of the j-th column is required */ j = -k; xassert(1 <= j && j <= m+n); /* if the (auxiliary or structural) variable x[j] is fixed, the pattern of its column is empty */ if (j <= m) lpx_get_row_bnds(lp, j, &typx, NULL, NULL); else lpx_get_col_bnds(lp, j-m, &typx, NULL, NULL); if (typx != LPX_FX) { if (j <= m) { /* x[j] is non-fixed auxiliary variable */ ndx[++len] = j; } else { /* x[j] is non-fixed structural variables */ #if 0 /* 22/XII-2003 */ j_beg = aa_ptr[j]; j_end = j_beg + aa_len[j] - 1; for (j_ptr = j_beg; j_ptr <= j_end; j_ptr++) ndx[++len] = sv_ndx[j_ptr]; #else len = lpx_get_mat_col(lp, j-m, ndx, NULL); #endif } } } /* return the length of the row/column pattern */ return len; } static void adv_basis(glp_prob *lp) { int m = lpx_get_num_rows(lp); int n = lpx_get_num_cols(lp); int i, j, jj, k, size; int *rn, *cn, *rn_inv, *cn_inv; int typx, *tagx = xcalloc(1+m+n, sizeof(int)); double lb, ub; xprintf("Constructing initial basis...\n"); #if 0 /* 13/V-2009 */ if (m == 0) xerror("glp_adv_basis: problem has no rows\n"); if (n == 0) xerror("glp_adv_basis: problem has no columns\n"); #else if (m == 0 || n == 0) { glp_std_basis(lp); return; } #endif /* use the routine triang (see above) to find maximal triangular part of the augmented constraint matrix A~ = (I|-A); in order to prevent columns of fixed variables to be included in the triangular part, such columns are implictly removed from the matrix A~ by the routine adv_mat */ rn = xcalloc(1+m, sizeof(int)); cn = xcalloc(1+m+n, sizeof(int)); size = triang(m, m+n, lp, mat, rn, cn); if (lpx_get_int_parm(lp, LPX_K_MSGLEV) >= 3) xprintf("Size of triangular part = %d\n", size); /* the first size rows and columns of the matrix P*A~*Q (where P and Q are permutation matrices defined by the arrays rn and cn) form a lower triangular matrix; build the arrays (rn_inv and cn_inv), which define the matrices inv(P) and inv(Q) */ rn_inv = xcalloc(1+m, sizeof(int)); cn_inv = xcalloc(1+m+n, sizeof(int)); for (i = 1; i <= m; i++) rn_inv[rn[i]] = i; for (j = 1; j <= m+n; j++) cn_inv[cn[j]] = j; /* include the columns of the matrix A~, which correspond to the first size columns of the matrix P*A~*Q, in the basis */ for (k = 1; k <= m+n; k++) tagx[k] = -1; for (jj = 1; jj <= size; jj++) { j = cn_inv[jj]; /* the j-th column of A~ is the jj-th column of P*A~*Q */ tagx[j] = LPX_BS; } /* if size < m, we need to add appropriate columns of auxiliary variables to the basis */ for (jj = size + 1; jj <= m; jj++) { /* the jj-th column of P*A~*Q should be replaced by the column of the auxiliary variable, for which the only unity element is placed in the position [jj,jj] */ i = rn_inv[jj]; /* the jj-th row of P*A~*Q is the i-th row of A~, but in the i-th row of A~ the unity element belongs to the i-th column of A~; therefore the disired column corresponds to the i-th auxiliary variable (note that this column doesn't belong to the triangular part found by the routine triang) */ xassert(1 <= i && i <= m); xassert(cn[i] > size); tagx[i] = LPX_BS; } /* free working arrays */ xfree(rn); xfree(cn); xfree(rn_inv); xfree(cn_inv); /* build tags of non-basic variables */ for (k = 1; k <= m+n; k++) { if (tagx[k] != LPX_BS) { if (k <= m) lpx_get_row_bnds(lp, k, &typx, &lb, &ub); else lpx_get_col_bnds(lp, k-m, &typx, &lb, &ub); switch (typx) { case LPX_FR: tagx[k] = LPX_NF; break; case LPX_LO: tagx[k] = LPX_NL; break; case LPX_UP: tagx[k] = LPX_NU; break; case LPX_DB: tagx[k] = (fabs(lb) <= fabs(ub) ? LPX_NL : LPX_NU); break; case LPX_FX: tagx[k] = LPX_NS; break; default: xassert(typx != typx); } } } for (k = 1; k <= m+n; k++) { if (k <= m) lpx_set_row_stat(lp, k, tagx[k]); else lpx_set_col_stat(lp, k-m, tagx[k]); } xfree(tagx); return; } /*********************************************************************** * NAME * * glp_adv_basis - construct advanced initial LP basis * * SYNOPSIS * * void glp_adv_basis(glp_prob *lp, int flags); * * DESCRIPTION * * The routine glp_adv_basis constructs an advanced initial basis for * the specified problem object. * * The parameter flags is reserved for use in the future and must be * specified as zero. */ void glp_adv_basis(glp_prob *lp, int flags) { if (flags != 0) xerror("glp_adv_basis: flags = %d; invalid flags\n", flags); if (lp->m == 0 || lp->n == 0) glp_std_basis(lp); else adv_basis(lp); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/amd/0000755000076500000240000000000013617375001024135 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/optional/glpk/amd/amd_info.c0000644000076500000240000001065613524616144026070 0ustar tamasstaff00000000000000/* ========================================================================= */ /* === AMD_info ============================================================ */ /* ========================================================================= */ /* ------------------------------------------------------------------------- */ /* AMD, Copyright (c) Timothy A. Davis, */ /* Patrick R. Amestoy, and Iain S. Duff. See ../README.txt for License. */ /* email: davis at cise.ufl.edu CISE Department, Univ. of Florida. */ /* web: http://www.cise.ufl.edu/research/sparse/amd */ /* ------------------------------------------------------------------------- */ /* User-callable. Prints the output statistics for AMD. See amd.h * for details. If the Info array is not present, nothing is printed. */ #include "amd_internal.h" #define PRI(format,x) { if (x >= 0) { PRINTF ((format, x)) ; }} GLOBAL void AMD_info ( double Info [ ] ) { double n, ndiv, nmultsubs_ldl, nmultsubs_lu, lnz, lnzd ; PRINTF (("\nAMD version %d.%d.%d, %s, results:\n", AMD_MAIN_VERSION, AMD_SUB_VERSION, AMD_SUBSUB_VERSION, AMD_DATE)) ; if (!Info) { return ; } n = Info [AMD_N] ; ndiv = Info [AMD_NDIV] ; nmultsubs_ldl = Info [AMD_NMULTSUBS_LDL] ; nmultsubs_lu = Info [AMD_NMULTSUBS_LU] ; lnz = Info [AMD_LNZ] ; lnzd = (n >= 0 && lnz >= 0) ? (n + lnz) : (-1) ; /* AMD return status */ PRINTF ((" status: ")) ; if (Info [AMD_STATUS] == AMD_OK) { PRINTF (("OK\n")) ; } else if (Info [AMD_STATUS] == AMD_OUT_OF_MEMORY) { PRINTF (("out of memory\n")) ; } else if (Info [AMD_STATUS] == AMD_INVALID) { PRINTF (("invalid matrix\n")) ; } else if (Info [AMD_STATUS] == AMD_OK_BUT_JUMBLED) { PRINTF (("OK, but jumbled\n")) ; } else { PRINTF (("unknown\n")) ; } /* statistics about the input matrix */ PRI (" n, dimension of A: %.20g\n", n); PRI (" nz, number of nonzeros in A: %.20g\n", Info [AMD_NZ]) ; PRI (" symmetry of A: %.4f\n", Info [AMD_SYMMETRY]) ; PRI (" number of nonzeros on diagonal: %.20g\n", Info [AMD_NZDIAG]) ; PRI (" nonzeros in pattern of A+A' (excl. diagonal): %.20g\n", Info [AMD_NZ_A_PLUS_AT]) ; PRI (" # dense rows/columns of A+A': %.20g\n", Info [AMD_NDENSE]) ; /* statistics about AMD's behavior */ PRI (" memory used, in bytes: %.20g\n", Info [AMD_MEMORY]) ; PRI (" # of memory compactions: %.20g\n", Info [AMD_NCMPA]) ; /* statistics about the ordering quality */ PRINTF (("\n" " The following approximate statistics are for a subsequent\n" " factorization of A(P,P) + A(P,P)'. They are slight upper\n" " bounds if there are no dense rows/columns in A+A', and become\n" " looser if dense rows/columns exist.\n\n")) ; PRI (" nonzeros in L (excluding diagonal): %.20g\n", lnz) ; PRI (" nonzeros in L (including diagonal): %.20g\n", lnzd) ; PRI (" # divide operations for LDL' or LU: %.20g\n", ndiv) ; PRI (" # multiply-subtract operations for LDL': %.20g\n", nmultsubs_ldl) ; PRI (" # multiply-subtract operations for LU: %.20g\n", nmultsubs_lu) ; PRI (" max nz. in any column of L (incl. diagonal): %.20g\n", Info [AMD_DMAX]) ; /* total flop counts for various factorizations */ if (n >= 0 && ndiv >= 0 && nmultsubs_ldl >= 0 && nmultsubs_lu >= 0) { PRINTF (("\n" " chol flop count for real A, sqrt counted as 1 flop: %.20g\n" " LDL' flop count for real A: %.20g\n" " LDL' flop count for complex A: %.20g\n" " LU flop count for real A (with no pivoting): %.20g\n" " LU flop count for complex A (with no pivoting): %.20g\n\n", n + ndiv + 2*nmultsubs_ldl, ndiv + 2*nmultsubs_ldl, 9*ndiv + 8*nmultsubs_ldl, ndiv + 2*nmultsubs_lu, 9*ndiv + 8*nmultsubs_lu)) ; } } python-igraph-0.8.0/vendor/source/igraph/optional/glpk/amd/README0000644000076500000240000000461713524616144025030 0ustar tamasstaff00000000000000NOTE: Files in this subdirectory are NOT part of the GLPK package, but are used with GLPK. The original code was modified according to GLPK requirements by Andrew Makhorin . ************************************************************************ AMD Version 2.2, Copyright (C) 2007 by Timothy A. Davis, Patrick R. Amestoy, and Iain S. Duff. All Rights Reserved. Description: AMD is a set of routines for pre-ordering sparse matrices prior to Cholesky or LU factorization, using the approximate minimum degree ordering algorithm. Written in ANSI/ISO C with a MATLAB interface, and in Fortran 77. Authors: Timothy A. Davis (davis at cise.ufl.edu), University of Florida. Patrick R. Amestoy, ENSEEIHT, Toulouse, France. Iain S. Duff, Rutherford Appleton Laboratory, UK. AMD License: Your use or distribution of AMD or any modified version of AMD implies that you agree to this License. This library is free software; you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation; either version 2.1 of the License, or (at your option) any later version. This library is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with this library; if not, write to the Free Software Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA. Permission is hereby granted to use or copy this program under the terms of the GNU LGPL, provided that the Copyright, this License, and the Availability of the original version is retained on all copies. User documentation of any code that uses this code or any modified version of this code must cite the Copyright, this License, the Availability note, and "Used by permission." Permission to modify the code and to distribute modified code is granted, provided the Copyright, this License, and the Availability note are retained, and a notice that the code was modified is included. AMD is available under alternate licences; contact T. Davis for details. Availability: http://www.cise.ufl.edu/research/sparse/amd python-igraph-0.8.0/vendor/source/igraph/optional/glpk/amd/amd_preprocess.c0000644000076500000240000001017713524616144027320 0ustar tamasstaff00000000000000/* ========================================================================= */ /* === AMD_preprocess ====================================================== */ /* ========================================================================= */ /* ------------------------------------------------------------------------- */ /* AMD, Copyright (c) Timothy A. Davis, */ /* Patrick R. Amestoy, and Iain S. Duff. See ../README.txt for License. */ /* email: davis at cise.ufl.edu CISE Department, Univ. of Florida. */ /* web: http://www.cise.ufl.edu/research/sparse/amd */ /* ------------------------------------------------------------------------- */ /* Sorts, removes duplicate entries, and transposes from the nonzero pattern of * a column-form matrix A, to obtain the matrix R. The input matrix can have * duplicate entries and/or unsorted columns (AMD_valid (n,Ap,Ai) must not be * AMD_INVALID). * * This input condition is NOT checked. This routine is not user-callable. */ #include "amd_internal.h" /* ========================================================================= */ /* === AMD_preprocess ====================================================== */ /* ========================================================================= */ /* AMD_preprocess does not check its input for errors or allocate workspace. * On input, the condition (AMD_valid (n,n,Ap,Ai) != AMD_INVALID) must hold. */ GLOBAL void AMD_preprocess ( Int n, /* input matrix: A is n-by-n */ const Int Ap [ ], /* size n+1 */ const Int Ai [ ], /* size nz = Ap [n] */ /* output matrix R: */ Int Rp [ ], /* size n+1 */ Int Ri [ ], /* size nz (or less, if duplicates present) */ Int W [ ], /* workspace of size n */ Int Flag [ ] /* workspace of size n */ ) { /* --------------------------------------------------------------------- */ /* local variables */ /* --------------------------------------------------------------------- */ Int i, j, p, p2 ; ASSERT (AMD_valid (n, n, Ap, Ai) != AMD_INVALID) ; /* --------------------------------------------------------------------- */ /* count the entries in each row of A (excluding duplicates) */ /* --------------------------------------------------------------------- */ for (i = 0 ; i < n ; i++) { W [i] = 0 ; /* # of nonzeros in row i (excl duplicates) */ Flag [i] = EMPTY ; /* Flag [i] = j if i appears in column j */ } for (j = 0 ; j < n ; j++) { p2 = Ap [j+1] ; for (p = Ap [j] ; p < p2 ; p++) { i = Ai [p] ; if (Flag [i] != j) { /* row index i has not yet appeared in column j */ W [i]++ ; /* one more entry in row i */ Flag [i] = j ; /* flag row index i as appearing in col j*/ } } } /* --------------------------------------------------------------------- */ /* compute the row pointers for R */ /* --------------------------------------------------------------------- */ Rp [0] = 0 ; for (i = 0 ; i < n ; i++) { Rp [i+1] = Rp [i] + W [i] ; } for (i = 0 ; i < n ; i++) { W [i] = Rp [i] ; Flag [i] = EMPTY ; } /* --------------------------------------------------------------------- */ /* construct the row form matrix R */ /* --------------------------------------------------------------------- */ /* R = row form of pattern of A */ for (j = 0 ; j < n ; j++) { p2 = Ap [j+1] ; for (p = Ap [j] ; p < p2 ; p++) { i = Ai [p] ; if (Flag [i] != j) { /* row index i has not yet appeared in column j */ Ri [W [i]++] = j ; /* put col j in row i */ Flag [i] = j ; /* flag row index i as appearing in col j*/ } } } #ifndef NDEBUG ASSERT (AMD_valid (n, n, Rp, Ri) == AMD_OK) ; for (j = 0 ; j < n ; j++) { ASSERT (W [j] == Rp [j+1]) ; } #endif } python-igraph-0.8.0/vendor/source/igraph/optional/glpk/amd/amd_defaults.c0000644000076500000240000000257313524616144026743 0ustar tamasstaff00000000000000/* ========================================================================= */ /* === AMD_defaults ======================================================== */ /* ========================================================================= */ /* ------------------------------------------------------------------------- */ /* AMD, Copyright (c) Timothy A. Davis, */ /* Patrick R. Amestoy, and Iain S. Duff. See ../README.txt for License. */ /* email: davis at cise.ufl.edu CISE Department, Univ. of Florida. */ /* web: http://www.cise.ufl.edu/research/sparse/amd */ /* ------------------------------------------------------------------------- */ /* User-callable. Sets default control parameters for AMD. See amd.h * for details. */ #include "amd_internal.h" /* ========================================================================= */ /* === AMD defaults ======================================================== */ /* ========================================================================= */ GLOBAL void AMD_defaults ( double Control [ ] ) { Int i ; if (Control != (double *) NULL) { for (i = 0 ; i < AMD_CONTROL ; i++) { Control [i] = 0 ; } Control [AMD_DENSE] = AMD_DEFAULT_DENSE ; Control [AMD_AGGRESSIVE] = AMD_DEFAULT_AGGRESSIVE ; } } python-igraph-0.8.0/vendor/source/igraph/optional/glpk/amd/amd_post_tree.c0000644000076500000240000001070513524616144027134 0ustar tamasstaff00000000000000/* ========================================================================= */ /* === AMD_post_tree ======================================================= */ /* ========================================================================= */ /* ------------------------------------------------------------------------- */ /* AMD, Copyright (c) Timothy A. Davis, */ /* Patrick R. Amestoy, and Iain S. Duff. See ../README.txt for License. */ /* email: davis at cise.ufl.edu CISE Department, Univ. of Florida. */ /* web: http://www.cise.ufl.edu/research/sparse/amd */ /* ------------------------------------------------------------------------- */ /* Post-ordering of a supernodal elimination tree. */ #include "amd_internal.h" GLOBAL Int AMD_post_tree ( Int root, /* root of the tree */ Int k, /* start numbering at k */ Int Child [ ], /* input argument of size nn, undefined on * output. Child [i] is the head of a link * list of all nodes that are children of node * i in the tree. */ const Int Sibling [ ], /* input argument of size nn, not modified. * If f is a node in the link list of the * children of node i, then Sibling [f] is the * next child of node i. */ Int Order [ ], /* output order, of size nn. Order [i] = k * if node i is the kth node of the reordered * tree. */ Int Stack [ ] /* workspace of size nn */ #ifndef NDEBUG , Int nn /* nodes are in the range 0..nn-1. */ #endif ) { Int f, head, h, i ; #if 0 /* --------------------------------------------------------------------- */ /* recursive version (Stack [ ] is not used): */ /* --------------------------------------------------------------------- */ /* this is simple, but can caouse stack overflow if nn is large */ i = root ; for (f = Child [i] ; f != EMPTY ; f = Sibling [f]) { k = AMD_post_tree (f, k, Child, Sibling, Order, Stack, nn) ; } Order [i] = k++ ; return (k) ; #endif /* --------------------------------------------------------------------- */ /* non-recursive version, using an explicit stack */ /* --------------------------------------------------------------------- */ /* push root on the stack */ head = 0 ; Stack [0] = root ; while (head >= 0) { /* get head of stack */ ASSERT (head < nn) ; i = Stack [head] ; AMD_DEBUG1 (("head of stack "ID" \n", i)) ; ASSERT (i >= 0 && i < nn) ; if (Child [i] != EMPTY) { /* the children of i are not yet ordered */ /* push each child onto the stack in reverse order */ /* so that small ones at the head of the list get popped first */ /* and the biggest one at the end of the list gets popped last */ for (f = Child [i] ; f != EMPTY ; f = Sibling [f]) { head++ ; ASSERT (head < nn) ; ASSERT (f >= 0 && f < nn) ; } h = head ; ASSERT (head < nn) ; for (f = Child [i] ; f != EMPTY ; f = Sibling [f]) { ASSERT (h > 0) ; Stack [h--] = f ; AMD_DEBUG1 (("push "ID" on stack\n", f)) ; ASSERT (f >= 0 && f < nn) ; } ASSERT (Stack [h] == i) ; /* delete child list so that i gets ordered next time we see it */ Child [i] = EMPTY ; } else { /* the children of i (if there were any) are already ordered */ /* remove i from the stack and order it. Front i is kth front */ head-- ; AMD_DEBUG1 (("pop "ID" order "ID"\n", i, k)) ; Order [i] = k++ ; ASSERT (k <= nn) ; } #ifndef NDEBUG AMD_DEBUG1 (("\nStack:")) ; for (h = head ; h >= 0 ; h--) { Int j = Stack [h] ; AMD_DEBUG1 ((" "ID, j)) ; ASSERT (j >= 0 && j < nn) ; } AMD_DEBUG1 (("\n\n")) ; ASSERT (head < nn) ; #endif } return (k) ; } python-igraph-0.8.0/vendor/source/igraph/optional/glpk/amd/COPYING0000644000076500000240000006362513524616144025207 0ustar tamasstaff00000000000000 GNU LESSER GENERAL PUBLIC LICENSE Version 2.1, February 1999 Copyright (C) 1991, 1999 Free Software Foundation, Inc. 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed. [This is the first released version of the Lesser GPL. It also counts as the successor of the GNU Library Public License, version 2, hence the version number 2.1.] Preamble The licenses for most software are designed to take away your freedom to share and change it. By contrast, the GNU General Public Licenses are intended to guarantee your freedom to share and change free software--to make sure the software is free for all its users. This license, the Lesser General Public License, applies to some specially designated software packages--typically libraries--of the Free Software Foundation and other authors who decide to use it. You can use it too, but we suggest you first think carefully about whether this license or the ordinary General Public License is the better strategy to use in any particular case, based on the explanations below. When we speak of free software, we are referring to freedom of use, not price. 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Here is a sample; alter the names: Yoyodyne, Inc., hereby disclaims all copyright interest in the library `Frob' (a library for tweaking knobs) written by James Random Hacker. , 1 April 1990 Ty Coon, President of Vice That's all there is to it! python-igraph-0.8.0/vendor/source/igraph/optional/glpk/amd/amd_1.c0000644000076500000240000001504313524616144025270 0ustar tamasstaff00000000000000/* ========================================================================= */ /* === AMD_1 =============================================================== */ /* ========================================================================= */ /* ------------------------------------------------------------------------- */ /* AMD, Copyright (c) Timothy A. Davis, */ /* Patrick R. Amestoy, and Iain S. Duff. See ../README.txt for License. */ /* email: davis at cise.ufl.edu CISE Department, Univ. of Florida. */ /* web: http://www.cise.ufl.edu/research/sparse/amd */ /* ------------------------------------------------------------------------- */ /* AMD_1: Construct A+A' for a sparse matrix A and perform the AMD ordering. * * The n-by-n sparse matrix A can be unsymmetric. It is stored in MATLAB-style * compressed-column form, with sorted row indices in each column, and no * duplicate entries. Diagonal entries may be present, but they are ignored. * Row indices of column j of A are stored in Ai [Ap [j] ... Ap [j+1]-1]. * Ap [0] must be zero, and nz = Ap [n] is the number of entries in A. The * size of the matrix, n, must be greater than or equal to zero. * * This routine must be preceded by a call to AMD_aat, which computes the * number of entries in each row/column in A+A', excluding the diagonal. * Len [j], on input, is the number of entries in row/column j of A+A'. This * routine constructs the matrix A+A' and then calls AMD_2. No error checking * is performed (this was done in AMD_valid). */ #include "amd_internal.h" GLOBAL void AMD_1 ( Int n, /* n > 0 */ const Int Ap [ ], /* input of size n+1, not modified */ const Int Ai [ ], /* input of size nz = Ap [n], not modified */ Int P [ ], /* size n output permutation */ Int Pinv [ ], /* size n output inverse permutation */ Int Len [ ], /* size n input, undefined on output */ Int slen, /* slen >= sum (Len [0..n-1]) + 7n, * ideally slen = 1.2 * sum (Len) + 8n */ Int S [ ], /* size slen workspace */ double Control [ ], /* input array of size AMD_CONTROL */ double Info [ ] /* output array of size AMD_INFO */ ) { Int i, j, k, p, pfree, iwlen, pj, p1, p2, pj2, *Iw, *Pe, *Nv, *Head, *Elen, *Degree, *s, *W, *Sp, *Tp ; /* --------------------------------------------------------------------- */ /* construct the matrix for AMD_2 */ /* --------------------------------------------------------------------- */ ASSERT (n > 0) ; iwlen = slen - 6*n ; s = S ; Pe = s ; s += n ; Nv = s ; s += n ; Head = s ; s += n ; Elen = s ; s += n ; Degree = s ; s += n ; W = s ; s += n ; Iw = s ; s += iwlen ; ASSERT (AMD_valid (n, n, Ap, Ai) == AMD_OK) ; /* construct the pointers for A+A' */ Sp = Nv ; /* use Nv and W as workspace for Sp and Tp [ */ Tp = W ; pfree = 0 ; for (j = 0 ; j < n ; j++) { Pe [j] = pfree ; Sp [j] = pfree ; pfree += Len [j] ; } /* Note that this restriction on iwlen is slightly more restrictive than * what is strictly required in AMD_2. AMD_2 can operate with no elbow * room at all, but it will be very slow. For better performance, at * least size-n elbow room is enforced. */ ASSERT (iwlen >= pfree + n) ; #ifndef NDEBUG for (p = 0 ; p < iwlen ; p++) Iw [p] = EMPTY ; #endif for (k = 0 ; k < n ; k++) { AMD_DEBUG1 (("Construct row/column k= "ID" of A+A'\n", k)) ; p1 = Ap [k] ; p2 = Ap [k+1] ; /* construct A+A' */ for (p = p1 ; p < p2 ; ) { /* scan the upper triangular part of A */ j = Ai [p] ; ASSERT (j >= 0 && j < n) ; if (j < k) { /* entry A (j,k) in the strictly upper triangular part */ ASSERT (Sp [j] < (j == n-1 ? pfree : Pe [j+1])) ; ASSERT (Sp [k] < (k == n-1 ? pfree : Pe [k+1])) ; Iw [Sp [j]++] = k ; Iw [Sp [k]++] = j ; p++ ; } else if (j == k) { /* skip the diagonal */ p++ ; break ; } else /* j > k */ { /* first entry below the diagonal */ break ; } /* scan lower triangular part of A, in column j until reaching * row k. Start where last scan left off. */ ASSERT (Ap [j] <= Tp [j] && Tp [j] <= Ap [j+1]) ; pj2 = Ap [j+1] ; for (pj = Tp [j] ; pj < pj2 ; ) { i = Ai [pj] ; ASSERT (i >= 0 && i < n) ; if (i < k) { /* A (i,j) is only in the lower part, not in upper */ ASSERT (Sp [i] < (i == n-1 ? pfree : Pe [i+1])) ; ASSERT (Sp [j] < (j == n-1 ? pfree : Pe [j+1])) ; Iw [Sp [i]++] = j ; Iw [Sp [j]++] = i ; pj++ ; } else if (i == k) { /* entry A (k,j) in lower part and A (j,k) in upper */ pj++ ; break ; } else /* i > k */ { /* consider this entry later, when k advances to i */ break ; } } Tp [j] = pj ; } Tp [k] = p ; } /* clean up, for remaining mismatched entries */ for (j = 0 ; j < n ; j++) { for (pj = Tp [j] ; pj < Ap [j+1] ; pj++) { i = Ai [pj] ; ASSERT (i >= 0 && i < n) ; /* A (i,j) is only in the lower part, not in upper */ ASSERT (Sp [i] < (i == n-1 ? pfree : Pe [i+1])) ; ASSERT (Sp [j] < (j == n-1 ? pfree : Pe [j+1])) ; Iw [Sp [i]++] = j ; Iw [Sp [j]++] = i ; } } #ifndef NDEBUG for (j = 0 ; j < n-1 ; j++) ASSERT (Sp [j] == Pe [j+1]) ; ASSERT (Sp [n-1] == pfree) ; #endif /* Tp and Sp no longer needed ] */ /* --------------------------------------------------------------------- */ /* order the matrix */ /* --------------------------------------------------------------------- */ AMD_2 (n, Pe, Iw, Len, iwlen, pfree, Nv, Pinv, P, Head, Elen, Degree, W, Control, Info) ; } python-igraph-0.8.0/vendor/source/igraph/optional/glpk/amd/amd_postorder.c0000644000076500000240000001543113524616144027152 0ustar tamasstaff00000000000000/* ========================================================================= */ /* === AMD_postorder ======================================================= */ /* ========================================================================= */ /* ------------------------------------------------------------------------- */ /* AMD, Copyright (c) Timothy A. Davis, */ /* Patrick R. Amestoy, and Iain S. Duff. See ../README.txt for License. */ /* email: davis at cise.ufl.edu CISE Department, Univ. of Florida. */ /* web: http://www.cise.ufl.edu/research/sparse/amd */ /* ------------------------------------------------------------------------- */ /* Perform a postordering (via depth-first search) of an assembly tree. */ #include "amd_internal.h" GLOBAL void AMD_postorder ( /* inputs, not modified on output: */ Int nn, /* nodes are in the range 0..nn-1 */ Int Parent [ ], /* Parent [j] is the parent of j, or EMPTY if root */ Int Nv [ ], /* Nv [j] > 0 number of pivots represented by node j, * or zero if j is not a node. */ Int Fsize [ ], /* Fsize [j]: size of node j */ /* output, not defined on input: */ Int Order [ ], /* output post-order */ /* workspaces of size nn: */ Int Child [ ], Int Sibling [ ], Int Stack [ ] ) { Int i, j, k, parent, frsize, f, fprev, maxfrsize, bigfprev, bigf, fnext ; for (j = 0 ; j < nn ; j++) { Child [j] = EMPTY ; Sibling [j] = EMPTY ; } /* --------------------------------------------------------------------- */ /* place the children in link lists - bigger elements tend to be last */ /* --------------------------------------------------------------------- */ for (j = nn-1 ; j >= 0 ; j--) { if (Nv [j] > 0) { /* this is an element */ parent = Parent [j] ; if (parent != EMPTY) { /* place the element in link list of the children its parent */ /* bigger elements will tend to be at the end of the list */ Sibling [j] = Child [parent] ; Child [parent] = j ; } } } #ifndef NDEBUG { Int nels, ff, nchild ; AMD_DEBUG1 (("\n\n================================ AMD_postorder:\n")); nels = 0 ; for (j = 0 ; j < nn ; j++) { if (Nv [j] > 0) { AMD_DEBUG1 (( ""ID" : nels "ID" npiv "ID" size "ID " parent "ID" maxfr "ID"\n", j, nels, Nv [j], Fsize [j], Parent [j], Fsize [j])) ; /* this is an element */ /* dump the link list of children */ nchild = 0 ; AMD_DEBUG1 ((" Children: ")) ; for (ff = Child [j] ; ff != EMPTY ; ff = Sibling [ff]) { AMD_DEBUG1 ((ID" ", ff)) ; ASSERT (Parent [ff] == j) ; nchild++ ; ASSERT (nchild < nn) ; } AMD_DEBUG1 (("\n")) ; parent = Parent [j] ; if (parent != EMPTY) { ASSERT (Nv [parent] > 0) ; } nels++ ; } } } AMD_DEBUG1 (("\n\nGo through the children of each node, and put\n" "the biggest child last in each list:\n")) ; #endif /* --------------------------------------------------------------------- */ /* place the largest child last in the list of children for each node */ /* --------------------------------------------------------------------- */ for (i = 0 ; i < nn ; i++) { if (Nv [i] > 0 && Child [i] != EMPTY) { #ifndef NDEBUG Int nchild ; AMD_DEBUG1 (("Before partial sort, element "ID"\n", i)) ; nchild = 0 ; for (f = Child [i] ; f != EMPTY ; f = Sibling [f]) { ASSERT (f >= 0 && f < nn) ; AMD_DEBUG1 ((" f: "ID" size: "ID"\n", f, Fsize [f])) ; nchild++ ; ASSERT (nchild <= nn) ; } #endif /* find the biggest element in the child list */ fprev = EMPTY ; maxfrsize = EMPTY ; bigfprev = EMPTY ; bigf = EMPTY ; for (f = Child [i] ; f != EMPTY ; f = Sibling [f]) { ASSERT (f >= 0 && f < nn) ; frsize = Fsize [f] ; if (frsize >= maxfrsize) { /* this is the biggest seen so far */ maxfrsize = frsize ; bigfprev = fprev ; bigf = f ; } fprev = f ; } ASSERT (bigf != EMPTY) ; fnext = Sibling [bigf] ; AMD_DEBUG1 (("bigf "ID" maxfrsize "ID" bigfprev "ID" fnext "ID " fprev " ID"\n", bigf, maxfrsize, bigfprev, fnext, fprev)) ; if (fnext != EMPTY) { /* if fnext is EMPTY then bigf is already at the end of list */ if (bigfprev == EMPTY) { /* delete bigf from the element of the list */ Child [i] = fnext ; } else { /* delete bigf from the middle of the list */ Sibling [bigfprev] = fnext ; } /* put bigf at the end of the list */ Sibling [bigf] = EMPTY ; ASSERT (Child [i] != EMPTY) ; ASSERT (fprev != bigf) ; ASSERT (fprev != EMPTY) ; Sibling [fprev] = bigf ; } #ifndef NDEBUG AMD_DEBUG1 (("After partial sort, element "ID"\n", i)) ; for (f = Child [i] ; f != EMPTY ; f = Sibling [f]) { ASSERT (f >= 0 && f < nn) ; AMD_DEBUG1 ((" "ID" "ID"\n", f, Fsize [f])) ; ASSERT (Nv [f] > 0) ; nchild-- ; } ASSERT (nchild == 0) ; #endif } } /* --------------------------------------------------------------------- */ /* postorder the assembly tree */ /* --------------------------------------------------------------------- */ for (i = 0 ; i < nn ; i++) { Order [i] = EMPTY ; } k = 0 ; for (i = 0 ; i < nn ; i++) { if (Parent [i] == EMPTY && Nv [i] > 0) { AMD_DEBUG1 (("Root of assembly tree "ID"\n", i)) ; k = AMD_post_tree (i, k, Child, Sibling, Order, Stack #ifndef NDEBUG , nn #endif ) ; } } } python-igraph-0.8.0/vendor/source/igraph/optional/glpk/amd/amd_internal.h0000644000076500000240000000577713524616144026766 0ustar tamasstaff00000000000000/* amd_internal.h */ /* Written by Andrew Makhorin . */ #ifndef AMD_INTERNAL_H #define AMD_INTERNAL_H /* AMD will be exceedingly slow when running in debug mode. */ #if 1 #ifndef NDEBUG #define NDEBUG #endif #endif #include "amd.h" #define _GLPSTD_STDIO #include "glpenv.h" #define Int int #define ID "%d" #define Int_MAX INT_MAX #ifndef SIZE_T_MAX #define SIZE_T_MAX ((size_t)(-1)) #endif #define EMPTY (-1) #define FLIP(i) (-(i)-2) #define UNFLIP(i) ((i < EMPTY) ? FLIP (i) : (i)) #define MAX(a,b) (((a) > (b)) ? (a) : (b)) #define MIN(a,b) (((a) < (b)) ? (a) : (b)) #define IMPLIES(p, q) (!(p) || (q)) #define GLOBAL #define AMD_order amd_order #define AMD_defaults amd_defaults #define AMD_control amd_control #define AMD_info amd_info #define AMD_1 amd_1 #define AMD_2 amd_2 #define AMD_valid amd_valid #define AMD_aat amd_aat #define AMD_postorder amd_postorder #define AMD_post_tree amd_post_tree #define AMD_dump amd_dump #define AMD_debug amd_debug #define AMD_debug_init amd_debug_init #define AMD_preprocess amd_preprocess #define amd_malloc xmalloc #if 0 /* 24/V-2009 */ #define amd_free xfree #else #define amd_free(ptr) { if ((ptr) != NULL) xfree(ptr); } #endif #define amd_printf xprintf #define PRINTF(params) { amd_printf params; } #ifndef NDEBUG #define ASSERT(expr) xassert(expr) #define AMD_DEBUG0(params) { PRINTF(params); } #define AMD_DEBUG1(params) { if (AMD_debug >= 1) PRINTF(params); } #define AMD_DEBUG2(params) { if (AMD_debug >= 2) PRINTF(params); } #define AMD_DEBUG3(params) { if (AMD_debug >= 3) PRINTF(params); } #define AMD_DEBUG4(params) { if (AMD_debug >= 4) PRINTF(params); } #else #define ASSERT(expression) #define AMD_DEBUG0(params) #define AMD_DEBUG1(params) #define AMD_DEBUG2(params) #define AMD_DEBUG3(params) #define AMD_DEBUG4(params) #endif #define amd_aat _glp_amd_aat size_t AMD_aat(Int n, const Int Ap[], const Int Ai[], Int Len[], Int Tp[], double Info[]); #define amd_1 _glp_amd_1 void AMD_1(Int n, const Int Ap[], const Int Ai[], Int P[], Int Pinv[], Int Len[], Int slen, Int S[], double Control[], double Info[]); #define amd_postorder _glp_amd_postorder void AMD_postorder(Int nn, Int Parent[], Int Npiv[], Int Fsize[], Int Order[], Int Child[], Int Sibling[], Int Stack[]); #define amd_post_tree _glp_amd_post_tree #ifndef NDEBUG Int AMD_post_tree(Int root, Int k, Int Child[], const Int Sibling[], Int Order[], Int Stack[], Int nn); #else Int AMD_post_tree(Int root, Int k, Int Child[], const Int Sibling[], Int Order[], Int Stack[]); #endif #define amd_preprocess _glp_amd_preprocess void AMD_preprocess(Int n, const Int Ap[], const Int Ai[], Int Rp[], Int Ri[], Int W[], Int Flag[]); #define amd_debug _glp_amd_debug extern Int AMD_debug; #define amd_debug_init _glp_amd_debug_init void AMD_debug_init(char *s); #define amd_dump _glp_amd_dump void AMD_dump(Int n, Int Pe[], Int Iw[], Int Len[], Int iwlen, Int pfree, Int Nv[], Int Next[], Int Last[], Int Head[], Int Elen[], Int Degree[], Int W[], Int nel); #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/amd/amd_valid.c0000644000076500000240000000651513524616144026233 0ustar tamasstaff00000000000000/* ========================================================================= */ /* === AMD_valid =========================================================== */ /* ========================================================================= */ /* ------------------------------------------------------------------------- */ /* AMD, Copyright (c) Timothy A. Davis, */ /* Patrick R. Amestoy, and Iain S. Duff. See ../README.txt for License. */ /* email: davis at cise.ufl.edu CISE Department, Univ. of Florida. */ /* web: http://www.cise.ufl.edu/research/sparse/amd */ /* ------------------------------------------------------------------------- */ /* Check if a column-form matrix is valid or not. The matrix A is * n_row-by-n_col. The row indices of entries in column j are in * Ai [Ap [j] ... Ap [j+1]-1]. Required conditions are: * * n_row >= 0 * n_col >= 0 * nz = Ap [n_col] >= 0 number of entries in the matrix * Ap [0] == 0 * Ap [j] <= Ap [j+1] for all j in the range 0 to n_col. * Ai [0 ... nz-1] must be in the range 0 to n_row-1. * * If any of the above conditions hold, AMD_INVALID is returned. If the * following condition holds, AMD_OK_BUT_JUMBLED is returned (a warning, * not an error): * * row indices in Ai [Ap [j] ... Ap [j+1]-1] are not sorted in ascending * order, and/or duplicate entries exist. * * Otherwise, AMD_OK is returned. * * In v1.2 and earlier, this function returned TRUE if the matrix was valid * (now returns AMD_OK), or FALSE otherwise (now returns AMD_INVALID or * AMD_OK_BUT_JUMBLED). */ #include "amd_internal.h" GLOBAL Int AMD_valid ( /* inputs, not modified on output: */ Int n_row, /* A is n_row-by-n_col */ Int n_col, const Int Ap [ ], /* column pointers of A, of size n_col+1 */ const Int Ai [ ] /* row indices of A, of size nz = Ap [n_col] */ ) { Int nz, j, p1, p2, ilast, i, p, result = AMD_OK ; if (n_row < 0 || n_col < 0 || Ap == NULL || Ai == NULL) { return (AMD_INVALID) ; } nz = Ap [n_col] ; if (Ap [0] != 0 || nz < 0) { /* column pointers must start at Ap [0] = 0, and Ap [n] must be >= 0 */ AMD_DEBUG0 (("column 0 pointer bad or nz < 0\n")) ; return (AMD_INVALID) ; } for (j = 0 ; j < n_col ; j++) { p1 = Ap [j] ; p2 = Ap [j+1] ; AMD_DEBUG2 (("\nColumn: "ID" p1: "ID" p2: "ID"\n", j, p1, p2)) ; if (p1 > p2) { /* column pointers must be ascending */ AMD_DEBUG0 (("column "ID" pointer bad\n", j)) ; return (AMD_INVALID) ; } ilast = EMPTY ; for (p = p1 ; p < p2 ; p++) { i = Ai [p] ; AMD_DEBUG3 (("row: "ID"\n", i)) ; if (i < 0 || i >= n_row) { /* row index out of range */ AMD_DEBUG0 (("index out of range, col "ID" row "ID"\n", j, i)); return (AMD_INVALID) ; } if (i <= ilast) { /* row index unsorted, or duplicate entry present */ AMD_DEBUG1 (("index unsorted/dupl col "ID" row "ID"\n", j, i)); result = AMD_OK_BUT_JUMBLED ; } ilast = i ; } } return (result) ; } python-igraph-0.8.0/vendor/source/igraph/optional/glpk/amd/amd_2.c0000644000076500000240000023056213524616144025276 0ustar tamasstaff00000000000000/* ========================================================================= */ /* === AMD_2 =============================================================== */ /* ========================================================================= */ /* ------------------------------------------------------------------------- */ /* AMD, Copyright (c) Timothy A. Davis, */ /* Patrick R. Amestoy, and Iain S. Duff. See ../README.txt for License. */ /* email: davis at cise.ufl.edu CISE Department, Univ. of Florida. */ /* web: http://www.cise.ufl.edu/research/sparse/amd */ /* ------------------------------------------------------------------------- */ /* AMD_2: performs the AMD ordering on a symmetric sparse matrix A, followed * by a postordering (via depth-first search) of the assembly tree using the * AMD_postorder routine. */ #pragma clang diagnostic ignored "-Wconversion" #include "amd_internal.h" /* ========================================================================= */ /* === clear_flag ========================================================== */ /* ========================================================================= */ static Int clear_flag (Int wflg, Int wbig, Int W [ ], Int n) { Int x ; if (wflg < 2 || wflg >= wbig) { for (x = 0 ; x < n ; x++) { if (W [x] != 0) W [x] = 1 ; } wflg = 2 ; } /* at this point, W [0..n-1] < wflg holds */ return (wflg) ; } /* ========================================================================= */ /* === AMD_2 =============================================================== */ /* ========================================================================= */ GLOBAL void AMD_2 ( Int n, /* A is n-by-n, where n > 0 */ Int Pe [ ], /* Pe [0..n-1]: index in Iw of row i on input */ Int Iw [ ], /* workspace of size iwlen. Iw [0..pfree-1] * holds the matrix on input */ Int Len [ ], /* Len [0..n-1]: length for row/column i on input */ Int iwlen, /* length of Iw. iwlen >= pfree + n */ Int pfree, /* Iw [pfree ... iwlen-1] is empty on input */ /* 7 size-n workspaces, not defined on input: */ Int Nv [ ], /* the size of each supernode on output */ Int Next [ ], /* the output inverse permutation */ Int Last [ ], /* the output permutation */ Int Head [ ], Int Elen [ ], /* the size columns of L for each supernode */ Int Degree [ ], Int W [ ], /* control parameters and output statistics */ double Control [ ], /* array of size AMD_CONTROL */ double Info [ ] /* array of size AMD_INFO */ ) { /* * Given a representation of the nonzero pattern of a symmetric matrix, A, * (excluding the diagonal) perform an approximate minimum (UMFPACK/MA38-style) * degree ordering to compute a pivot order such that the introduction of * nonzeros (fill-in) in the Cholesky factors A = LL' is kept low. At each * step, the pivot selected is the one with the minimum UMFAPACK/MA38-style * upper-bound on the external degree. This routine can optionally perform * aggresive absorption (as done by MC47B in the Harwell Subroutine * Library). * * The approximate degree algorithm implemented here is the symmetric analog of * the degree update algorithm in MA38 and UMFPACK (the Unsymmetric-pattern * MultiFrontal PACKage, both by Davis and Duff). The routine is based on the * MA27 minimum degree ordering algorithm by Iain Duff and John Reid. * * This routine is a translation of the original AMDBAR and MC47B routines, * in Fortran, with the following modifications: * * (1) dense rows/columns are removed prior to ordering the matrix, and placed * last in the output order. The presence of a dense row/column can * increase the ordering time by up to O(n^2), unless they are removed * prior to ordering. * * (2) the minimum degree ordering is followed by a postordering (depth-first * search) of the assembly tree. Note that mass elimination (discussed * below) combined with the approximate degree update can lead to the mass * elimination of nodes with lower exact degree than the current pivot * element. No additional fill-in is caused in the representation of the * Schur complement. The mass-eliminated nodes merge with the current * pivot element. They are ordered prior to the current pivot element. * Because they can have lower exact degree than the current element, the * merger of two or more of these nodes in the current pivot element can * lead to a single element that is not a "fundamental supernode". The * diagonal block can have zeros in it. Thus, the assembly tree used here * is not guaranteed to be the precise supernodal elemination tree (with * "funadmental" supernodes), and the postordering performed by this * routine is not guaranteed to be a precise postordering of the * elimination tree. * * (3) input parameters are added, to control aggressive absorption and the * detection of "dense" rows/columns of A. * * (4) additional statistical information is returned, such as the number of * nonzeros in L, and the flop counts for subsequent LDL' and LU * factorizations. These are slight upper bounds, because of the mass * elimination issue discussed above. * * (5) additional routines are added to interface this routine to MATLAB * to provide a simple C-callable user-interface, to check inputs for * errors, compute the symmetry of the pattern of A and the number of * nonzeros in each row/column of A+A', to compute the pattern of A+A', * to perform the assembly tree postordering, and to provide debugging * ouput. Many of these functions are also provided by the Fortran * Harwell Subroutine Library routine MC47A. * * (6) both int and UF_long versions are provided. In the descriptions below * and integer is and int or UF_long depending on which version is * being used. ********************************************************************** ***** CAUTION: ARGUMENTS ARE NOT CHECKED FOR ERRORS ON INPUT. ****** ********************************************************************** ** If you want error checking, a more versatile input format, and a ** ** simpler user interface, use amd_order or amd_l_order instead. ** ** This routine is not meant to be user-callable. ** ********************************************************************** * ---------------------------------------------------------------------------- * References: * ---------------------------------------------------------------------------- * * [1] Timothy A. Davis and Iain Duff, "An unsymmetric-pattern multifrontal * method for sparse LU factorization", SIAM J. Matrix Analysis and * Applications, vol. 18, no. 1, pp. 140-158. Discusses UMFPACK / MA38, * which first introduced the approximate minimum degree used by this * routine. * * [2] Patrick Amestoy, Timothy A. Davis, and Iain S. Duff, "An approximate * minimum degree ordering algorithm," SIAM J. Matrix Analysis and * Applications, vol. 17, no. 4, pp. 886-905, 1996. Discusses AMDBAR and * MC47B, which are the Fortran versions of this routine. * * [3] Alan George and Joseph Liu, "The evolution of the minimum degree * ordering algorithm," SIAM Review, vol. 31, no. 1, pp. 1-19, 1989. * We list below the features mentioned in that paper that this code * includes: * * mass elimination: * Yes. MA27 relied on supervariable detection for mass elimination. * * indistinguishable nodes: * Yes (we call these "supervariables"). This was also in the MA27 * code - although we modified the method of detecting them (the * previous hash was the true degree, which we no longer keep track * of). A supervariable is a set of rows with identical nonzero * pattern. All variables in a supervariable are eliminated together. * Each supervariable has as its numerical name that of one of its * variables (its principal variable). * * quotient graph representation: * Yes. We use the term "element" for the cliques formed during * elimination. This was also in the MA27 code. The algorithm can * operate in place, but it will work more efficiently if given some * "elbow room." * * element absorption: * Yes. This was also in the MA27 code. * * external degree: * Yes. The MA27 code was based on the true degree. * * incomplete degree update and multiple elimination: * No. This was not in MA27, either. Our method of degree update * within MC47B is element-based, not variable-based. It is thus * not well-suited for use with incomplete degree update or multiple * elimination. * * Authors, and Copyright (C) 2004 by: * Timothy A. Davis, Patrick Amestoy, Iain S. Duff, John K. Reid. * * Acknowledgements: This work (and the UMFPACK package) was supported by the * National Science Foundation (ASC-9111263, DMS-9223088, and CCR-0203270). * The UMFPACK/MA38 approximate degree update algorithm, the unsymmetric analog * which forms the basis of AMD, was developed while Tim Davis was supported by * CERFACS (Toulouse, France) in a post-doctoral position. This C version, and * the etree postorder, were written while Tim Davis was on sabbatical at * Stanford University and Lawrence Berkeley National Laboratory. * ---------------------------------------------------------------------------- * INPUT ARGUMENTS (unaltered): * ---------------------------------------------------------------------------- * n: The matrix order. Restriction: n >= 1. * * iwlen: The size of the Iw array. On input, the matrix is stored in * Iw [0..pfree-1]. However, Iw [0..iwlen-1] should be slightly larger * than what is required to hold the matrix, at least iwlen >= pfree + n. * Otherwise, excessive compressions will take place. The recommended * value of iwlen is 1.2 * pfree + n, which is the value used in the * user-callable interface to this routine (amd_order.c). The algorithm * will not run at all if iwlen < pfree. Restriction: iwlen >= pfree + n. * Note that this is slightly more restrictive than the actual minimum * (iwlen >= pfree), but AMD_2 will be very slow with no elbow room. * Thus, this routine enforces a bare minimum elbow room of size n. * * pfree: On input the tail end of the array, Iw [pfree..iwlen-1], is empty, * and the matrix is stored in Iw [0..pfree-1]. During execution, * additional data is placed in Iw, and pfree is modified so that * Iw [pfree..iwlen-1] is always the unused part of Iw. * * Control: A double array of size AMD_CONTROL containing input parameters * that affect how the ordering is computed. If NULL, then default * settings are used. * * Control [AMD_DENSE] is used to determine whether or not a given input * row is "dense". A row is "dense" if the number of entries in the row * exceeds Control [AMD_DENSE] times sqrt (n), except that rows with 16 or * fewer entries are never considered "dense". To turn off the detection * of dense rows, set Control [AMD_DENSE] to a negative number, or to a * number larger than sqrt (n). The default value of Control [AMD_DENSE] * is AMD_DEFAULT_DENSE, which is defined in amd.h as 10. * * Control [AMD_AGGRESSIVE] is used to determine whether or not aggressive * absorption is to be performed. If nonzero, then aggressive absorption * is performed (this is the default). * ---------------------------------------------------------------------------- * INPUT/OUPUT ARGUMENTS: * ---------------------------------------------------------------------------- * * Pe: An integer array of size n. On input, Pe [i] is the index in Iw of * the start of row i. Pe [i] is ignored if row i has no off-diagonal * entries. Thus Pe [i] must be in the range 0 to pfree-1 for non-empty * rows. * * During execution, it is used for both supervariables and elements: * * Principal supervariable i: index into Iw of the description of * supervariable i. A supervariable represents one or more rows of * the matrix with identical nonzero pattern. In this case, * Pe [i] >= 0. * * Non-principal supervariable i: if i has been absorbed into another * supervariable j, then Pe [i] = FLIP (j), where FLIP (j) is defined * as (-(j)-2). Row j has the same pattern as row i. Note that j * might later be absorbed into another supervariable j2, in which * case Pe [i] is still FLIP (j), and Pe [j] = FLIP (j2) which is * < EMPTY, where EMPTY is defined as (-1) in amd_internal.h. * * Unabsorbed element e: the index into Iw of the description of element * e, if e has not yet been absorbed by a subsequent element. Element * e is created when the supervariable of the same name is selected as * the pivot. In this case, Pe [i] >= 0. * * Absorbed element e: if element e is absorbed into element e2, then * Pe [e] = FLIP (e2). This occurs when the pattern of e (which we * refer to as Le) is found to be a subset of the pattern of e2 (that * is, Le2). In this case, Pe [i] < EMPTY. If element e is "null" * (it has no nonzeros outside its pivot block), then Pe [e] = EMPTY, * and e is the root of an assembly subtree (or the whole tree if * there is just one such root). * * Dense variable i: if i is "dense", then Pe [i] = EMPTY. * * On output, Pe holds the assembly tree/forest, which implicitly * represents a pivot order with identical fill-in as the actual order * (via a depth-first search of the tree), as follows. If Nv [i] > 0, * then i represents a node in the assembly tree, and the parent of i is * Pe [i], or EMPTY if i is a root. If Nv [i] = 0, then (i, Pe [i]) * represents an edge in a subtree, the root of which is a node in the * assembly tree. Note that i refers to a row/column in the original * matrix, not the permuted matrix. * * Info: A double array of size AMD_INFO. If present, (that is, not NULL), * then statistics about the ordering are returned in the Info array. * See amd.h for a description. * ---------------------------------------------------------------------------- * INPUT/MODIFIED (undefined on output): * ---------------------------------------------------------------------------- * * Len: An integer array of size n. On input, Len [i] holds the number of * entries in row i of the matrix, excluding the diagonal. The contents * of Len are undefined on output. * * Iw: An integer array of size iwlen. On input, Iw [0..pfree-1] holds the * description of each row i in the matrix. The matrix must be symmetric, * and both upper and lower triangular parts must be present. The * diagonal must not be present. Row i is held as follows: * * Len [i]: the length of the row i data structure in the Iw array. * Iw [Pe [i] ... Pe [i] + Len [i] - 1]: * the list of column indices for nonzeros in row i (simple * supervariables), excluding the diagonal. All supervariables * start with one row/column each (supervariable i is just row i). * If Len [i] is zero on input, then Pe [i] is ignored on input. * * Note that the rows need not be in any particular order, and there * may be empty space between the rows. * * During execution, the supervariable i experiences fill-in. This is * represented by placing in i a list of the elements that cause fill-in * in supervariable i: * * Len [i]: the length of supervariable i in the Iw array. * Iw [Pe [i] ... Pe [i] + Elen [i] - 1]: * the list of elements that contain i. This list is kept short * by removing absorbed elements. * Iw [Pe [i] + Elen [i] ... Pe [i] + Len [i] - 1]: * the list of supervariables in i. This list is kept short by * removing nonprincipal variables, and any entry j that is also * contained in at least one of the elements (j in Le) in the list * for i (e in row i). * * When supervariable i is selected as pivot, we create an element e of * the same name (e=i): * * Len [e]: the length of element e in the Iw array. * Iw [Pe [e] ... Pe [e] + Len [e] - 1]: * the list of supervariables in element e. * * An element represents the fill-in that occurs when supervariable i is * selected as pivot (which represents the selection of row i and all * non-principal variables whose principal variable is i). We use the * term Le to denote the set of all supervariables in element e. Absorbed * supervariables and elements are pruned from these lists when * computationally convenient. * * CAUTION: THE INPUT MATRIX IS OVERWRITTEN DURING COMPUTATION. * The contents of Iw are undefined on output. * ---------------------------------------------------------------------------- * OUTPUT (need not be set on input): * ---------------------------------------------------------------------------- * * Nv: An integer array of size n. During execution, ABS (Nv [i]) is equal to * the number of rows that are represented by the principal supervariable * i. If i is a nonprincipal or dense variable, then Nv [i] = 0. * Initially, Nv [i] = 1 for all i. Nv [i] < 0 signifies that i is a * principal variable in the pattern Lme of the current pivot element me. * After element me is constructed, Nv [i] is set back to a positive * value. * * On output, Nv [i] holds the number of pivots represented by super * row/column i of the original matrix, or Nv [i] = 0 for non-principal * rows/columns. Note that i refers to a row/column in the original * matrix, not the permuted matrix. * * Elen: An integer array of size n. See the description of Iw above. At the * start of execution, Elen [i] is set to zero for all rows i. During * execution, Elen [i] is the number of elements in the list for * supervariable i. When e becomes an element, Elen [e] = FLIP (esize) is * set, where esize is the size of the element (the number of pivots, plus * the number of nonpivotal entries). Thus Elen [e] < EMPTY. * Elen (i) = EMPTY set when variable i becomes nonprincipal. * * For variables, Elen (i) >= EMPTY holds until just before the * postordering and permutation vectors are computed. For elements, * Elen [e] < EMPTY holds. * * On output, Elen [i] is the degree of the row/column in the Cholesky * factorization of the permuted matrix, corresponding to the original row * i, if i is a super row/column. It is equal to EMPTY if i is * non-principal. Note that i refers to a row/column in the original * matrix, not the permuted matrix. * * Note that the contents of Elen on output differ from the Fortran * version (Elen holds the inverse permutation in the Fortran version, * which is instead returned in the Next array in this C version, * described below). * * Last: In a degree list, Last [i] is the supervariable preceding i, or EMPTY * if i is the head of the list. In a hash bucket, Last [i] is the hash * key for i. * * Last [Head [hash]] is also used as the head of a hash bucket if * Head [hash] contains a degree list (see the description of Head, * below). * * On output, Last [0..n-1] holds the permutation. That is, if * i = Last [k], then row i is the kth pivot row (where k ranges from 0 to * n-1). Row Last [k] of A is the kth row in the permuted matrix, PAP'. * * Next: Next [i] is the supervariable following i in a link list, or EMPTY if * i is the last in the list. Used for two kinds of lists: degree lists * and hash buckets (a supervariable can be in only one kind of list at a * time). * * On output Next [0..n-1] holds the inverse permutation. That is, if * k = Next [i], then row i is the kth pivot row. Row i of A appears as * the (Next[i])-th row in the permuted matrix, PAP'. * * Note that the contents of Next on output differ from the Fortran * version (Next is undefined on output in the Fortran version). * ---------------------------------------------------------------------------- * LOCAL WORKSPACE (not input or output - used only during execution): * ---------------------------------------------------------------------------- * * Degree: An integer array of size n. If i is a supervariable, then * Degree [i] holds the current approximation of the external degree of * row i (an upper bound). The external degree is the number of nonzeros * in row i, minus ABS (Nv [i]), the diagonal part. The bound is equal to * the exact external degree if Elen [i] is less than or equal to two. * * We also use the term "external degree" for elements e to refer to * |Le \ Lme|. If e is an element, then Degree [e] is |Le|, which is the * degree of the off-diagonal part of the element e (not including the * diagonal part). * * Head: An integer array of size n. Head is used for degree lists. * Head [deg] is the first supervariable in a degree list. All * supervariables i in a degree list Head [deg] have the same approximate * degree, namely, deg = Degree [i]. If the list Head [deg] is empty then * Head [deg] = EMPTY. * * During supervariable detection Head [hash] also serves as a pointer to * a hash bucket. If Head [hash] >= 0, there is a degree list of degree * hash. The hash bucket head pointer is Last [Head [hash]]. If * Head [hash] = EMPTY, then the degree list and hash bucket are both * empty. If Head [hash] < EMPTY, then the degree list is empty, and * FLIP (Head [hash]) is the head of the hash bucket. After supervariable * detection is complete, all hash buckets are empty, and the * (Last [Head [hash]] = EMPTY) condition is restored for the non-empty * degree lists. * * W: An integer array of size n. The flag array W determines the status of * elements and variables, and the external degree of elements. * * for elements: * if W [e] = 0, then the element e is absorbed. * if W [e] >= wflg, then W [e] - wflg is the size of the set * |Le \ Lme|, in terms of nonzeros (the sum of ABS (Nv [i]) for * each principal variable i that is both in the pattern of * element e and NOT in the pattern of the current pivot element, * me). * if wflg > W [e] > 0, then e is not absorbed and has not yet been * seen in the scan of the element lists in the computation of * |Le\Lme| in Scan 1 below. * * for variables: * during supervariable detection, if W [j] != wflg then j is * not in the pattern of variable i. * * The W array is initialized by setting W [i] = 1 for all i, and by * setting wflg = 2. It is reinitialized if wflg becomes too large (to * ensure that wflg+n does not cause integer overflow). * ---------------------------------------------------------------------------- * LOCAL INTEGERS: * ---------------------------------------------------------------------------- */ Int deg, degme, dext, lemax, e, elenme, eln, i, ilast, inext, j, jlast, jnext, k, knt1, knt2, knt3, lenj, ln, me, mindeg, nel, nleft, nvi, nvj, nvpiv, slenme, wbig, we, wflg, wnvi, ok, ndense, ncmpa, dense, aggressive ; unsigned Int hash ; /* unsigned, so that hash % n is well defined.*/ /* * deg: the degree of a variable or element * degme: size, |Lme|, of the current element, me (= Degree [me]) * dext: external degree, |Le \ Lme|, of some element e * lemax: largest |Le| seen so far (called dmax in Fortran version) * e: an element * elenme: the length, Elen [me], of element list of pivotal variable * eln: the length, Elen [...], of an element list * hash: the computed value of the hash function * i: a supervariable * ilast: the entry in a link list preceding i * inext: the entry in a link list following i * j: a supervariable * jlast: the entry in a link list preceding j * jnext: the entry in a link list, or path, following j * k: the pivot order of an element or variable * knt1: loop counter used during element construction * knt2: loop counter used during element construction * knt3: loop counter used during compression * lenj: Len [j] * ln: length of a supervariable list * me: current supervariable being eliminated, and the current * element created by eliminating that supervariable * mindeg: current minimum degree * nel: number of pivots selected so far * nleft: n - nel, the number of nonpivotal rows/columns remaining * nvi: the number of variables in a supervariable i (= Nv [i]) * nvj: the number of variables in a supervariable j (= Nv [j]) * nvpiv: number of pivots in current element * slenme: number of variables in variable list of pivotal variable * wbig: = INT_MAX - n for the int version, UF_long_max - n for the * UF_long version. wflg is not allowed to be >= wbig. * we: W [e] * wflg: used for flagging the W array. See description of Iw. * wnvi: wflg - Nv [i] * x: either a supervariable or an element * * ok: true if supervariable j can be absorbed into i * ndense: number of "dense" rows/columns * dense: rows/columns with initial degree > dense are considered "dense" * aggressive: true if aggressive absorption is being performed * ncmpa: number of garbage collections * ---------------------------------------------------------------------------- * LOCAL DOUBLES, used for statistical output only (except for alpha): * ---------------------------------------------------------------------------- */ double f, r, ndiv, s, nms_lu, nms_ldl, dmax, alpha, lnz, lnzme ; /* * f: nvpiv * r: degme + nvpiv * ndiv: number of divisions for LU or LDL' factorizations * s: number of multiply-subtract pairs for LU factorization, for the * current element me * nms_lu number of multiply-subtract pairs for LU factorization * nms_ldl number of multiply-subtract pairs for LDL' factorization * dmax: the largest number of entries in any column of L, including the * diagonal * alpha: "dense" degree ratio * lnz: the number of nonzeros in L (excluding the diagonal) * lnzme: the number of nonzeros in L (excl. the diagonal) for the * current element me * ---------------------------------------------------------------------------- * LOCAL "POINTERS" (indices into the Iw array) * ---------------------------------------------------------------------------- */ Int p, p1, p2, p3, p4, pdst, pend, pj, pme, pme1, pme2, pn, psrc ; /* * Any parameter (Pe [...] or pfree) or local variable starting with "p" (for * Pointer) is an index into Iw, and all indices into Iw use variables starting * with "p." The only exception to this rule is the iwlen input argument. * * p: pointer into lots of things * p1: Pe [i] for some variable i (start of element list) * p2: Pe [i] + Elen [i] - 1 for some variable i * p3: index of first supervariable in clean list * p4: * pdst: destination pointer, for compression * pend: end of memory to compress * pj: pointer into an element or variable * pme: pointer into the current element (pme1...pme2) * pme1: the current element, me, is stored in Iw [pme1...pme2] * pme2: the end of the current element * pn: pointer into a "clean" variable, also used to compress * psrc: source pointer, for compression */ /* ========================================================================= */ /* INITIALIZATIONS */ /* ========================================================================= */ /* Note that this restriction on iwlen is slightly more restrictive than * what is actually required in AMD_2. AMD_2 can operate with no elbow * room at all, but it will be slow. For better performance, at least * size-n elbow room is enforced. */ ASSERT (iwlen >= pfree + n) ; ASSERT (n > 0) ; /* initialize output statistics */ lnz = 0 ; ndiv = 0 ; nms_lu = 0 ; nms_ldl = 0 ; dmax = 1 ; me = EMPTY ; mindeg = 0 ; ncmpa = 0 ; nel = 0 ; lemax = 0 ; /* get control parameters */ if (Control != (double *) NULL) { alpha = Control [AMD_DENSE] ; aggressive = (Control [AMD_AGGRESSIVE] != 0) ; } else { alpha = AMD_DEFAULT_DENSE ; aggressive = AMD_DEFAULT_AGGRESSIVE ; } /* Note: if alpha is NaN, this is undefined: */ if (alpha < 0) { /* only remove completely dense rows/columns */ dense = n-2 ; } else { dense = alpha * sqrt ((double) n) ; } dense = MAX (16, dense) ; dense = MIN (n, dense) ; AMD_DEBUG1 (("\n\nAMD (debug), alpha %g, aggr. "ID"\n", alpha, aggressive)) ; for (i = 0 ; i < n ; i++) { Last [i] = EMPTY ; Head [i] = EMPTY ; Next [i] = EMPTY ; /* if separate Hhead array is used for hash buckets: * Hhead [i] = EMPTY ; */ Nv [i] = 1 ; W [i] = 1 ; Elen [i] = 0 ; Degree [i] = Len [i] ; } #ifndef NDEBUG AMD_DEBUG1 (("\n======Nel "ID" initial\n", nel)) ; AMD_dump (n, Pe, Iw, Len, iwlen, pfree, Nv, Next, Last, Head, Elen, Degree, W, -1) ; #endif /* initialize wflg */ wbig = Int_MAX - n ; wflg = clear_flag (0, wbig, W, n) ; /* --------------------------------------------------------------------- */ /* initialize degree lists and eliminate dense and empty rows */ /* --------------------------------------------------------------------- */ ndense = 0 ; for (i = 0 ; i < n ; i++) { deg = Degree [i] ; ASSERT (deg >= 0 && deg < n) ; if (deg == 0) { /* ------------------------------------------------------------- * we have a variable that can be eliminated at once because * there is no off-diagonal non-zero in its row. Note that * Nv [i] = 1 for an empty variable i. It is treated just * the same as an eliminated element i. * ------------------------------------------------------------- */ Elen [i] = FLIP (1) ; nel++ ; Pe [i] = EMPTY ; W [i] = 0 ; } else if (deg > dense) { /* ------------------------------------------------------------- * Dense variables are not treated as elements, but as unordered, * non-principal variables that have no parent. They do not take * part in the postorder, since Nv [i] = 0. Note that the Fortran * version does not have this option. * ------------------------------------------------------------- */ AMD_DEBUG1 (("Dense node "ID" degree "ID"\n", i, deg)) ; ndense++ ; Nv [i] = 0 ; /* do not postorder this node */ Elen [i] = EMPTY ; nel++ ; Pe [i] = EMPTY ; } else { /* ------------------------------------------------------------- * place i in the degree list corresponding to its degree * ------------------------------------------------------------- */ inext = Head [deg] ; ASSERT (inext >= EMPTY && inext < n) ; if (inext != EMPTY) Last [inext] = i ; Next [i] = inext ; Head [deg] = i ; } } /* ========================================================================= */ /* WHILE (selecting pivots) DO */ /* ========================================================================= */ while (nel < n) { #ifndef NDEBUG AMD_DEBUG1 (("\n======Nel "ID"\n", nel)) ; if (AMD_debug >= 2) { AMD_dump (n, Pe, Iw, Len, iwlen, pfree, Nv, Next, Last, Head, Elen, Degree, W, nel) ; } #endif /* ========================================================================= */ /* GET PIVOT OF MINIMUM DEGREE */ /* ========================================================================= */ /* ----------------------------------------------------------------- */ /* find next supervariable for elimination */ /* ----------------------------------------------------------------- */ ASSERT (mindeg >= 0 && mindeg < n) ; for (deg = mindeg ; deg < n ; deg++) { me = Head [deg] ; if (me != EMPTY) break ; } mindeg = deg ; ASSERT (me >= 0 && me < n) ; AMD_DEBUG1 (("=================me: "ID"\n", me)) ; /* ----------------------------------------------------------------- */ /* remove chosen variable from link list */ /* ----------------------------------------------------------------- */ inext = Next [me] ; ASSERT (inext >= EMPTY && inext < n) ; if (inext != EMPTY) Last [inext] = EMPTY ; Head [deg] = inext ; /* ----------------------------------------------------------------- */ /* me represents the elimination of pivots nel to nel+Nv[me]-1. */ /* place me itself as the first in this set. */ /* ----------------------------------------------------------------- */ elenme = Elen [me] ; nvpiv = Nv [me] ; ASSERT (nvpiv > 0) ; nel += nvpiv ; /* ========================================================================= */ /* CONSTRUCT NEW ELEMENT */ /* ========================================================================= */ /* ----------------------------------------------------------------- * At this point, me is the pivotal supervariable. It will be * converted into the current element. Scan list of the pivotal * supervariable, me, setting tree pointers and constructing new list * of supervariables for the new element, me. p is a pointer to the * current position in the old list. * ----------------------------------------------------------------- */ /* flag the variable "me" as being in Lme by negating Nv [me] */ Nv [me] = -nvpiv ; degme = 0 ; ASSERT (Pe [me] >= 0 && Pe [me] < iwlen) ; if (elenme == 0) { /* ------------------------------------------------------------- */ /* construct the new element in place */ /* ------------------------------------------------------------- */ pme1 = Pe [me] ; pme2 = pme1 - 1 ; for (p = pme1 ; p <= pme1 + Len [me] - 1 ; p++) { i = Iw [p] ; ASSERT (i >= 0 && i < n && Nv [i] >= 0) ; nvi = Nv [i] ; if (nvi > 0) { /* ----------------------------------------------------- */ /* i is a principal variable not yet placed in Lme. */ /* store i in new list */ /* ----------------------------------------------------- */ /* flag i as being in Lme by negating Nv [i] */ degme += nvi ; Nv [i] = -nvi ; Iw [++pme2] = i ; /* ----------------------------------------------------- */ /* remove variable i from degree list. */ /* ----------------------------------------------------- */ ilast = Last [i] ; inext = Next [i] ; ASSERT (ilast >= EMPTY && ilast < n) ; ASSERT (inext >= EMPTY && inext < n) ; if (inext != EMPTY) Last [inext] = ilast ; if (ilast != EMPTY) { Next [ilast] = inext ; } else { /* i is at the head of the degree list */ ASSERT (Degree [i] >= 0 && Degree [i] < n) ; Head [Degree [i]] = inext ; } } } } else { /* ------------------------------------------------------------- */ /* construct the new element in empty space, Iw [pfree ...] */ /* ------------------------------------------------------------- */ p = Pe [me] ; pme1 = pfree ; slenme = Len [me] - elenme ; for (knt1 = 1 ; knt1 <= elenme + 1 ; knt1++) { if (knt1 > elenme) { /* search the supervariables in me. */ e = me ; pj = p ; ln = slenme ; AMD_DEBUG2 (("Search sv: "ID" "ID" "ID"\n", me,pj,ln)) ; } else { /* search the elements in me. */ e = Iw [p++] ; ASSERT (e >= 0 && e < n) ; pj = Pe [e] ; ln = Len [e] ; AMD_DEBUG2 (("Search element e "ID" in me "ID"\n", e,me)) ; ASSERT (Elen [e] < EMPTY && W [e] > 0 && pj >= 0) ; } ASSERT (ln >= 0 && (ln == 0 || (pj >= 0 && pj < iwlen))) ; /* --------------------------------------------------------- * search for different supervariables and add them to the * new list, compressing when necessary. this loop is * executed once for each element in the list and once for * all the supervariables in the list. * --------------------------------------------------------- */ for (knt2 = 1 ; knt2 <= ln ; knt2++) { i = Iw [pj++] ; ASSERT (i >= 0 && i < n && (i == me || Elen [i] >= EMPTY)); nvi = Nv [i] ; AMD_DEBUG2 ((": "ID" "ID" "ID" "ID"\n", i, Elen [i], Nv [i], wflg)) ; if (nvi > 0) { /* ------------------------------------------------- */ /* compress Iw, if necessary */ /* ------------------------------------------------- */ if (pfree >= iwlen) { AMD_DEBUG1 (("GARBAGE COLLECTION\n")) ; /* prepare for compressing Iw by adjusting pointers * and lengths so that the lists being searched in * the inner and outer loops contain only the * remaining entries. */ Pe [me] = p ; Len [me] -= knt1 ; /* check if nothing left of supervariable me */ if (Len [me] == 0) Pe [me] = EMPTY ; Pe [e] = pj ; Len [e] = ln - knt2 ; /* nothing left of element e */ if (Len [e] == 0) Pe [e] = EMPTY ; ncmpa++ ; /* one more garbage collection */ /* store first entry of each object in Pe */ /* FLIP the first entry in each object */ for (j = 0 ; j < n ; j++) { pn = Pe [j] ; if (pn >= 0) { ASSERT (pn >= 0 && pn < iwlen) ; Pe [j] = Iw [pn] ; Iw [pn] = FLIP (j) ; } } /* psrc/pdst point to source/destination */ psrc = 0 ; pdst = 0 ; pend = pme1 - 1 ; while (psrc <= pend) { /* search for next FLIP'd entry */ j = FLIP (Iw [psrc++]) ; if (j >= 0) { AMD_DEBUG2 (("Got object j: "ID"\n", j)) ; Iw [pdst] = Pe [j] ; Pe [j] = pdst++ ; lenj = Len [j] ; /* copy from source to destination */ for (knt3 = 0 ; knt3 <= lenj - 2 ; knt3++) { Iw [pdst++] = Iw [psrc++] ; } } } /* move the new partially-constructed element */ p1 = pdst ; for (psrc = pme1 ; psrc <= pfree-1 ; psrc++) { Iw [pdst++] = Iw [psrc] ; } pme1 = p1 ; pfree = pdst ; pj = Pe [e] ; p = Pe [me] ; } /* ------------------------------------------------- */ /* i is a principal variable not yet placed in Lme */ /* store i in new list */ /* ------------------------------------------------- */ /* flag i as being in Lme by negating Nv [i] */ degme += nvi ; Nv [i] = -nvi ; Iw [pfree++] = i ; AMD_DEBUG2 ((" s: "ID" nv "ID"\n", i, Nv [i])); /* ------------------------------------------------- */ /* remove variable i from degree link list */ /* ------------------------------------------------- */ ilast = Last [i] ; inext = Next [i] ; ASSERT (ilast >= EMPTY && ilast < n) ; ASSERT (inext >= EMPTY && inext < n) ; if (inext != EMPTY) Last [inext] = ilast ; if (ilast != EMPTY) { Next [ilast] = inext ; } else { /* i is at the head of the degree list */ ASSERT (Degree [i] >= 0 && Degree [i] < n) ; Head [Degree [i]] = inext ; } } } if (e != me) { /* set tree pointer and flag to indicate element e is * absorbed into new element me (the parent of e is me) */ AMD_DEBUG1 ((" Element "ID" => "ID"\n", e, me)) ; Pe [e] = FLIP (me) ; W [e] = 0 ; } } pme2 = pfree - 1 ; } /* ----------------------------------------------------------------- */ /* me has now been converted into an element in Iw [pme1..pme2] */ /* ----------------------------------------------------------------- */ /* degme holds the external degree of new element */ Degree [me] = degme ; Pe [me] = pme1 ; Len [me] = pme2 - pme1 + 1 ; ASSERT (Pe [me] >= 0 && Pe [me] < iwlen) ; Elen [me] = FLIP (nvpiv + degme) ; /* FLIP (Elen (me)) is now the degree of pivot (including * diagonal part). */ #ifndef NDEBUG AMD_DEBUG2 (("New element structure: length= "ID"\n", pme2-pme1+1)) ; for (pme = pme1 ; pme <= pme2 ; pme++) AMD_DEBUG3 ((" "ID"", Iw[pme])); AMD_DEBUG3 (("\n")) ; #endif /* ----------------------------------------------------------------- */ /* make sure that wflg is not too large. */ /* ----------------------------------------------------------------- */ /* With the current value of wflg, wflg+n must not cause integer * overflow */ wflg = clear_flag (wflg, wbig, W, n) ; /* ========================================================================= */ /* COMPUTE (W [e] - wflg) = |Le\Lme| FOR ALL ELEMENTS */ /* ========================================================================= */ /* ----------------------------------------------------------------- * Scan 1: compute the external degrees of previous elements with * respect to the current element. That is: * (W [e] - wflg) = |Le \ Lme| * for each element e that appears in any supervariable in Lme. The * notation Le refers to the pattern (list of supervariables) of a * previous element e, where e is not yet absorbed, stored in * Iw [Pe [e] + 1 ... Pe [e] + Len [e]]. The notation Lme * refers to the pattern of the current element (stored in * Iw [pme1..pme2]). If aggressive absorption is enabled, and * (W [e] - wflg) becomes zero, then the element e will be absorbed * in Scan 2. * ----------------------------------------------------------------- */ AMD_DEBUG2 (("me: ")) ; for (pme = pme1 ; pme <= pme2 ; pme++) { i = Iw [pme] ; ASSERT (i >= 0 && i < n) ; eln = Elen [i] ; AMD_DEBUG3 ((""ID" Elen "ID": \n", i, eln)) ; if (eln > 0) { /* note that Nv [i] has been negated to denote i in Lme: */ nvi = -Nv [i] ; ASSERT (nvi > 0 && Pe [i] >= 0 && Pe [i] < iwlen) ; wnvi = wflg - nvi ; for (p = Pe [i] ; p <= Pe [i] + eln - 1 ; p++) { e = Iw [p] ; ASSERT (e >= 0 && e < n) ; we = W [e] ; AMD_DEBUG4 ((" e "ID" we "ID" ", e, we)) ; if (we >= wflg) { /* unabsorbed element e has been seen in this loop */ AMD_DEBUG4 ((" unabsorbed, first time seen")) ; we -= nvi ; } else if (we != 0) { /* e is an unabsorbed element */ /* this is the first we have seen e in all of Scan 1 */ AMD_DEBUG4 ((" unabsorbed")) ; we = Degree [e] + wnvi ; } AMD_DEBUG4 (("\n")) ; W [e] = we ; } } } AMD_DEBUG2 (("\n")) ; /* ========================================================================= */ /* DEGREE UPDATE AND ELEMENT ABSORPTION */ /* ========================================================================= */ /* ----------------------------------------------------------------- * Scan 2: for each i in Lme, sum up the degree of Lme (which is * degme), plus the sum of the external degrees of each Le for the * elements e appearing within i, plus the supervariables in i. * Place i in hash list. * ----------------------------------------------------------------- */ for (pme = pme1 ; pme <= pme2 ; pme++) { i = Iw [pme] ; ASSERT (i >= 0 && i < n && Nv [i] < 0 && Elen [i] >= 0) ; AMD_DEBUG2 (("Updating: i "ID" "ID" "ID"\n", i, Elen[i], Len [i])); p1 = Pe [i] ; p2 = p1 + Elen [i] - 1 ; pn = p1 ; hash = 0 ; deg = 0 ; ASSERT (p1 >= 0 && p1 < iwlen && p2 >= -1 && p2 < iwlen) ; /* ------------------------------------------------------------- */ /* scan the element list associated with supervariable i */ /* ------------------------------------------------------------- */ /* UMFPACK/MA38-style approximate degree: */ if (aggressive) { for (p = p1 ; p <= p2 ; p++) { e = Iw [p] ; ASSERT (e >= 0 && e < n) ; we = W [e] ; if (we != 0) { /* e is an unabsorbed element */ /* dext = | Le \ Lme | */ dext = we - wflg ; if (dext > 0) { deg += dext ; Iw [pn++] = e ; hash += e ; AMD_DEBUG4 ((" e: "ID" hash = "ID"\n",e,hash)) ; } else { /* external degree of e is zero, absorb e into me*/ AMD_DEBUG1 ((" Element "ID" =>"ID" (aggressive)\n", e, me)) ; ASSERT (dext == 0) ; Pe [e] = FLIP (me) ; W [e] = 0 ; } } } } else { for (p = p1 ; p <= p2 ; p++) { e = Iw [p] ; ASSERT (e >= 0 && e < n) ; we = W [e] ; if (we != 0) { /* e is an unabsorbed element */ dext = we - wflg ; ASSERT (dext >= 0) ; deg += dext ; Iw [pn++] = e ; hash += e ; AMD_DEBUG4 ((" e: "ID" hash = "ID"\n",e,hash)) ; } } } /* count the number of elements in i (including me): */ Elen [i] = pn - p1 + 1 ; /* ------------------------------------------------------------- */ /* scan the supervariables in the list associated with i */ /* ------------------------------------------------------------- */ /* The bulk of the AMD run time is typically spent in this loop, * particularly if the matrix has many dense rows that are not * removed prior to ordering. */ p3 = pn ; p4 = p1 + Len [i] ; for (p = p2 + 1 ; p < p4 ; p++) { j = Iw [p] ; ASSERT (j >= 0 && j < n) ; nvj = Nv [j] ; if (nvj > 0) { /* j is unabsorbed, and not in Lme. */ /* add to degree and add to new list */ deg += nvj ; Iw [pn++] = j ; hash += j ; AMD_DEBUG4 ((" s: "ID" hash "ID" Nv[j]= "ID"\n", j, hash, nvj)) ; } } /* ------------------------------------------------------------- */ /* update the degree and check for mass elimination */ /* ------------------------------------------------------------- */ /* with aggressive absorption, deg==0 is identical to the * Elen [i] == 1 && p3 == pn test, below. */ ASSERT (IMPLIES (aggressive, (deg==0) == (Elen[i]==1 && p3==pn))) ; if (Elen [i] == 1 && p3 == pn) { /* --------------------------------------------------------- */ /* mass elimination */ /* --------------------------------------------------------- */ /* There is nothing left of this node except for an edge to * the current pivot element. Elen [i] is 1, and there are * no variables adjacent to node i. Absorb i into the * current pivot element, me. Note that if there are two or * more mass eliminations, fillin due to mass elimination is * possible within the nvpiv-by-nvpiv pivot block. It is this * step that causes AMD's analysis to be an upper bound. * * The reason is that the selected pivot has a lower * approximate degree than the true degree of the two mass * eliminated nodes. There is no edge between the two mass * eliminated nodes. They are merged with the current pivot * anyway. * * No fillin occurs in the Schur complement, in any case, * and this effect does not decrease the quality of the * ordering itself, just the quality of the nonzero and * flop count analysis. It also means that the post-ordering * is not an exact elimination tree post-ordering. */ AMD_DEBUG1 ((" MASS i "ID" => parent e "ID"\n", i, me)) ; Pe [i] = FLIP (me) ; nvi = -Nv [i] ; degme -= nvi ; nvpiv += nvi ; nel += nvi ; Nv [i] = 0 ; Elen [i] = EMPTY ; } else { /* --------------------------------------------------------- */ /* update the upper-bound degree of i */ /* --------------------------------------------------------- */ /* the following degree does not yet include the size * of the current element, which is added later: */ Degree [i] = MIN (Degree [i], deg) ; /* --------------------------------------------------------- */ /* add me to the list for i */ /* --------------------------------------------------------- */ /* move first supervariable to end of list */ Iw [pn] = Iw [p3] ; /* move first element to end of element part of list */ Iw [p3] = Iw [p1] ; /* add new element, me, to front of list. */ Iw [p1] = me ; /* store the new length of the list in Len [i] */ Len [i] = pn - p1 + 1 ; /* --------------------------------------------------------- */ /* place in hash bucket. Save hash key of i in Last [i]. */ /* --------------------------------------------------------- */ /* NOTE: this can fail if hash is negative, because the ANSI C * standard does not define a % b when a and/or b are negative. * That's why hash is defined as an unsigned Int, to avoid this * problem. */ hash = hash % n ; ASSERT (((Int) hash) >= 0 && ((Int) hash) < n) ; /* if the Hhead array is not used: */ j = Head [hash] ; if (j <= EMPTY) { /* degree list is empty, hash head is FLIP (j) */ Next [i] = FLIP (j) ; Head [hash] = FLIP (i) ; } else { /* degree list is not empty, use Last [Head [hash]] as * hash head. */ Next [i] = Last [j] ; Last [j] = i ; } /* if a separate Hhead array is used: * Next [i] = Hhead [hash] ; Hhead [hash] = i ; */ Last [i] = hash ; } } Degree [me] = degme ; /* ----------------------------------------------------------------- */ /* Clear the counter array, W [...], by incrementing wflg. */ /* ----------------------------------------------------------------- */ /* make sure that wflg+n does not cause integer overflow */ lemax = MAX (lemax, degme) ; wflg += lemax ; wflg = clear_flag (wflg, wbig, W, n) ; /* at this point, W [0..n-1] < wflg holds */ /* ========================================================================= */ /* SUPERVARIABLE DETECTION */ /* ========================================================================= */ AMD_DEBUG1 (("Detecting supervariables:\n")) ; for (pme = pme1 ; pme <= pme2 ; pme++) { i = Iw [pme] ; ASSERT (i >= 0 && i < n) ; AMD_DEBUG2 (("Consider i "ID" nv "ID"\n", i, Nv [i])) ; if (Nv [i] < 0) { /* i is a principal variable in Lme */ /* --------------------------------------------------------- * examine all hash buckets with 2 or more variables. We do * this by examing all unique hash keys for supervariables in * the pattern Lme of the current element, me * --------------------------------------------------------- */ /* let i = head of hash bucket, and empty the hash bucket */ ASSERT (Last [i] >= 0 && Last [i] < n) ; hash = Last [i] ; /* if Hhead array is not used: */ j = Head [hash] ; if (j == EMPTY) { /* hash bucket and degree list are both empty */ i = EMPTY ; } else if (j < EMPTY) { /* degree list is empty */ i = FLIP (j) ; Head [hash] = EMPTY ; } else { /* degree list is not empty, restore Last [j] of head j */ i = Last [j] ; Last [j] = EMPTY ; } /* if separate Hhead array is used: * i = Hhead [hash] ; Hhead [hash] = EMPTY ; */ ASSERT (i >= EMPTY && i < n) ; AMD_DEBUG2 (("----i "ID" hash "ID"\n", i, hash)) ; while (i != EMPTY && Next [i] != EMPTY) { /* ----------------------------------------------------- * this bucket has one or more variables following i. * scan all of them to see if i can absorb any entries * that follow i in hash bucket. Scatter i into w. * ----------------------------------------------------- */ ln = Len [i] ; eln = Elen [i] ; ASSERT (ln >= 0 && eln >= 0) ; ASSERT (Pe [i] >= 0 && Pe [i] < iwlen) ; /* do not flag the first element in the list (me) */ for (p = Pe [i] + 1 ; p <= Pe [i] + ln - 1 ; p++) { ASSERT (Iw [p] >= 0 && Iw [p] < n) ; W [Iw [p]] = wflg ; } /* ----------------------------------------------------- */ /* scan every other entry j following i in bucket */ /* ----------------------------------------------------- */ jlast = i ; j = Next [i] ; ASSERT (j >= EMPTY && j < n) ; while (j != EMPTY) { /* ------------------------------------------------- */ /* check if j and i have identical nonzero pattern */ /* ------------------------------------------------- */ AMD_DEBUG3 (("compare i "ID" and j "ID"\n", i,j)) ; /* check if i and j have the same Len and Elen */ ASSERT (Len [j] >= 0 && Elen [j] >= 0) ; ASSERT (Pe [j] >= 0 && Pe [j] < iwlen) ; ok = (Len [j] == ln) && (Elen [j] == eln) ; /* skip the first element in the list (me) */ for (p = Pe [j] + 1 ; ok && p <= Pe [j] + ln - 1 ; p++) { ASSERT (Iw [p] >= 0 && Iw [p] < n) ; if (W [Iw [p]] != wflg) ok = 0 ; } if (ok) { /* --------------------------------------------- */ /* found it! j can be absorbed into i */ /* --------------------------------------------- */ AMD_DEBUG1 (("found it! j "ID" => i "ID"\n", j,i)); Pe [j] = FLIP (i) ; /* both Nv [i] and Nv [j] are negated since they */ /* are in Lme, and the absolute values of each */ /* are the number of variables in i and j: */ Nv [i] += Nv [j] ; Nv [j] = 0 ; Elen [j] = EMPTY ; /* delete j from hash bucket */ ASSERT (j != Next [j]) ; j = Next [j] ; Next [jlast] = j ; } else { /* j cannot be absorbed into i */ jlast = j ; ASSERT (j != Next [j]) ; j = Next [j] ; } ASSERT (j >= EMPTY && j < n) ; } /* ----------------------------------------------------- * no more variables can be absorbed into i * go to next i in bucket and clear flag array * ----------------------------------------------------- */ wflg++ ; i = Next [i] ; ASSERT (i >= EMPTY && i < n) ; } } } AMD_DEBUG2 (("detect done\n")) ; /* ========================================================================= */ /* RESTORE DEGREE LISTS AND REMOVE NONPRINCIPAL SUPERVARIABLES FROM ELEMENT */ /* ========================================================================= */ p = pme1 ; nleft = n - nel ; for (pme = pme1 ; pme <= pme2 ; pme++) { i = Iw [pme] ; ASSERT (i >= 0 && i < n) ; nvi = -Nv [i] ; AMD_DEBUG3 (("Restore i "ID" "ID"\n", i, nvi)) ; if (nvi > 0) { /* i is a principal variable in Lme */ /* restore Nv [i] to signify that i is principal */ Nv [i] = nvi ; /* --------------------------------------------------------- */ /* compute the external degree (add size of current element) */ /* --------------------------------------------------------- */ deg = Degree [i] + degme - nvi ; deg = MIN (deg, nleft - nvi) ; ASSERT (IMPLIES (aggressive, deg > 0) && deg >= 0 && deg < n) ; /* --------------------------------------------------------- */ /* place the supervariable at the head of the degree list */ /* --------------------------------------------------------- */ inext = Head [deg] ; ASSERT (inext >= EMPTY && inext < n) ; if (inext != EMPTY) Last [inext] = i ; Next [i] = inext ; Last [i] = EMPTY ; Head [deg] = i ; /* --------------------------------------------------------- */ /* save the new degree, and find the minimum degree */ /* --------------------------------------------------------- */ mindeg = MIN (mindeg, deg) ; Degree [i] = deg ; /* --------------------------------------------------------- */ /* place the supervariable in the element pattern */ /* --------------------------------------------------------- */ Iw [p++] = i ; } } AMD_DEBUG2 (("restore done\n")) ; /* ========================================================================= */ /* FINALIZE THE NEW ELEMENT */ /* ========================================================================= */ AMD_DEBUG2 (("ME = "ID" DONE\n", me)) ; Nv [me] = nvpiv ; /* save the length of the list for the new element me */ Len [me] = p - pme1 ; if (Len [me] == 0) { /* there is nothing left of the current pivot element */ /* it is a root of the assembly tree */ Pe [me] = EMPTY ; W [me] = 0 ; } if (elenme != 0) { /* element was not constructed in place: deallocate part of */ /* it since newly nonprincipal variables may have been removed */ pfree = p ; } /* The new element has nvpiv pivots and the size of the contribution * block for a multifrontal method is degme-by-degme, not including * the "dense" rows/columns. If the "dense" rows/columns are included, * the frontal matrix is no larger than * (degme+ndense)-by-(degme+ndense). */ if (Info != (double *) NULL) { f = nvpiv ; r = degme + ndense ; dmax = MAX (dmax, f + r) ; /* number of nonzeros in L (excluding the diagonal) */ lnzme = f*r + (f-1)*f/2 ; lnz += lnzme ; /* number of divide operations for LDL' and for LU */ ndiv += lnzme ; /* number of multiply-subtract pairs for LU */ s = f*r*r + r*(f-1)*f + (f-1)*f*(2*f-1)/6 ; nms_lu += s ; /* number of multiply-subtract pairs for LDL' */ nms_ldl += (s + lnzme)/2 ; } #ifndef NDEBUG AMD_DEBUG2 (("finalize done nel "ID" n "ID"\n ::::\n", nel, n)) ; for (pme = Pe [me] ; pme <= Pe [me] + Len [me] - 1 ; pme++) { AMD_DEBUG3 ((" "ID"", Iw [pme])) ; } AMD_DEBUG3 (("\n")) ; #endif } /* ========================================================================= */ /* DONE SELECTING PIVOTS */ /* ========================================================================= */ if (Info != (double *) NULL) { /* count the work to factorize the ndense-by-ndense submatrix */ f = ndense ; dmax = MAX (dmax, (double) ndense) ; /* number of nonzeros in L (excluding the diagonal) */ lnzme = (f-1)*f/2 ; lnz += lnzme ; /* number of divide operations for LDL' and for LU */ ndiv += lnzme ; /* number of multiply-subtract pairs for LU */ s = (f-1)*f*(2*f-1)/6 ; nms_lu += s ; /* number of multiply-subtract pairs for LDL' */ nms_ldl += (s + lnzme)/2 ; /* number of nz's in L (excl. diagonal) */ Info [AMD_LNZ] = lnz ; /* number of divide ops for LU and LDL' */ Info [AMD_NDIV] = ndiv ; /* number of multiply-subtract pairs for LDL' */ Info [AMD_NMULTSUBS_LDL] = nms_ldl ; /* number of multiply-subtract pairs for LU */ Info [AMD_NMULTSUBS_LU] = nms_lu ; /* number of "dense" rows/columns */ Info [AMD_NDENSE] = ndense ; /* largest front is dmax-by-dmax */ Info [AMD_DMAX] = dmax ; /* number of garbage collections in AMD */ Info [AMD_NCMPA] = ncmpa ; /* successful ordering */ Info [AMD_STATUS] = AMD_OK ; } /* ========================================================================= */ /* POST-ORDERING */ /* ========================================================================= */ /* ------------------------------------------------------------------------- * Variables at this point: * * Pe: holds the elimination tree. The parent of j is FLIP (Pe [j]), * or EMPTY if j is a root. The tree holds both elements and * non-principal (unordered) variables absorbed into them. * Dense variables are non-principal and unordered. * * Elen: holds the size of each element, including the diagonal part. * FLIP (Elen [e]) > 0 if e is an element. For unordered * variables i, Elen [i] is EMPTY. * * Nv: Nv [e] > 0 is the number of pivots represented by the element e. * For unordered variables i, Nv [i] is zero. * * Contents no longer needed: * W, Iw, Len, Degree, Head, Next, Last. * * The matrix itself has been destroyed. * * n: the size of the matrix. * No other scalars needed (pfree, iwlen, etc.) * ------------------------------------------------------------------------- */ /* restore Pe */ for (i = 0 ; i < n ; i++) { Pe [i] = FLIP (Pe [i]) ; } /* restore Elen, for output information, and for postordering */ for (i = 0 ; i < n ; i++) { Elen [i] = FLIP (Elen [i]) ; } /* Now the parent of j is Pe [j], or EMPTY if j is a root. Elen [e] > 0 * is the size of element e. Elen [i] is EMPTY for unordered variable i. */ #ifndef NDEBUG AMD_DEBUG2 (("\nTree:\n")) ; for (i = 0 ; i < n ; i++) { AMD_DEBUG2 ((" "ID" parent: "ID" ", i, Pe [i])) ; ASSERT (Pe [i] >= EMPTY && Pe [i] < n) ; if (Nv [i] > 0) { /* this is an element */ e = i ; AMD_DEBUG2 ((" element, size is "ID"\n", Elen [i])) ; ASSERT (Elen [e] > 0) ; } AMD_DEBUG2 (("\n")) ; } AMD_DEBUG2 (("\nelements:\n")) ; for (e = 0 ; e < n ; e++) { if (Nv [e] > 0) { AMD_DEBUG3 (("Element e= "ID" size "ID" nv "ID" \n", e, Elen [e], Nv [e])) ; } } AMD_DEBUG2 (("\nvariables:\n")) ; for (i = 0 ; i < n ; i++) { Int cnt ; if (Nv [i] == 0) { AMD_DEBUG3 (("i unordered: "ID"\n", i)) ; j = Pe [i] ; cnt = 0 ; AMD_DEBUG3 ((" j: "ID"\n", j)) ; if (j == EMPTY) { AMD_DEBUG3 ((" i is a dense variable\n")) ; } else { ASSERT (j >= 0 && j < n) ; while (Nv [j] == 0) { AMD_DEBUG3 ((" j : "ID"\n", j)) ; j = Pe [j] ; AMD_DEBUG3 ((" j:: "ID"\n", j)) ; cnt++ ; if (cnt > n) break ; } e = j ; AMD_DEBUG3 ((" got to e: "ID"\n", e)) ; } } } #endif /* ========================================================================= */ /* compress the paths of the variables */ /* ========================================================================= */ for (i = 0 ; i < n ; i++) { if (Nv [i] == 0) { /* ------------------------------------------------------------- * i is an un-ordered row. Traverse the tree from i until * reaching an element, e. The element, e, was the principal * supervariable of i and all nodes in the path from i to when e * was selected as pivot. * ------------------------------------------------------------- */ AMD_DEBUG1 (("Path compression, i unordered: "ID"\n", i)) ; j = Pe [i] ; ASSERT (j >= EMPTY && j < n) ; AMD_DEBUG3 ((" j: "ID"\n", j)) ; if (j == EMPTY) { /* Skip a dense variable. It has no parent. */ AMD_DEBUG3 ((" i is a dense variable\n")) ; continue ; } /* while (j is a variable) */ while (Nv [j] == 0) { AMD_DEBUG3 ((" j : "ID"\n", j)) ; j = Pe [j] ; AMD_DEBUG3 ((" j:: "ID"\n", j)) ; ASSERT (j >= 0 && j < n) ; } /* got to an element e */ e = j ; AMD_DEBUG3 (("got to e: "ID"\n", e)) ; /* ------------------------------------------------------------- * traverse the path again from i to e, and compress the path * (all nodes point to e). Path compression allows this code to * compute in O(n) time. * ------------------------------------------------------------- */ j = i ; /* while (j is a variable) */ while (Nv [j] == 0) { jnext = Pe [j] ; AMD_DEBUG3 (("j "ID" jnext "ID"\n", j, jnext)) ; Pe [j] = e ; j = jnext ; ASSERT (j >= 0 && j < n) ; } } } /* ========================================================================= */ /* postorder the assembly tree */ /* ========================================================================= */ AMD_postorder (n, Pe, Nv, Elen, W, /* output order */ Head, Next, Last) ; /* workspace */ /* ========================================================================= */ /* compute output permutation and inverse permutation */ /* ========================================================================= */ /* W [e] = k means that element e is the kth element in the new * order. e is in the range 0 to n-1, and k is in the range 0 to * the number of elements. Use Head for inverse order. */ for (k = 0 ; k < n ; k++) { Head [k] = EMPTY ; Next [k] = EMPTY ; } for (e = 0 ; e < n ; e++) { k = W [e] ; ASSERT ((k == EMPTY) == (Nv [e] == 0)) ; if (k != EMPTY) { ASSERT (k >= 0 && k < n) ; Head [k] = e ; } } /* construct output inverse permutation in Next, * and permutation in Last */ nel = 0 ; for (k = 0 ; k < n ; k++) { e = Head [k] ; if (e == EMPTY) break ; ASSERT (e >= 0 && e < n && Nv [e] > 0) ; Next [e] = nel ; nel += Nv [e] ; } ASSERT (nel == n - ndense) ; /* order non-principal variables (dense, & those merged into supervar's) */ for (i = 0 ; i < n ; i++) { if (Nv [i] == 0) { e = Pe [i] ; ASSERT (e >= EMPTY && e < n) ; if (e != EMPTY) { /* This is an unordered variable that was merged * into element e via supernode detection or mass * elimination of i when e became the pivot element. * Place i in order just before e. */ ASSERT (Next [i] == EMPTY && Nv [e] > 0) ; Next [i] = Next [e] ; Next [e]++ ; } else { /* This is a dense unordered variable, with no parent. * Place it last in the output order. */ Next [i] = nel++ ; } } } ASSERT (nel == n) ; AMD_DEBUG2 (("\n\nPerm:\n")) ; for (i = 0 ; i < n ; i++) { k = Next [i] ; ASSERT (k >= 0 && k < n) ; Last [k] = i ; AMD_DEBUG2 ((" perm ["ID"] = "ID"\n", k, i)) ; } } python-igraph-0.8.0/vendor/source/igraph/optional/glpk/amd/amd_aat.c0000644000076500000240000001346713524616144025705 0ustar tamasstaff00000000000000/* ========================================================================= */ /* === AMD_aat ============================================================= */ /* ========================================================================= */ /* ------------------------------------------------------------------------- */ /* AMD, Copyright (c) Timothy A. Davis, */ /* Patrick R. Amestoy, and Iain S. Duff. See ../README.txt for License. */ /* email: davis at cise.ufl.edu CISE Department, Univ. of Florida. */ /* web: http://www.cise.ufl.edu/research/sparse/amd */ /* ------------------------------------------------------------------------- */ /* AMD_aat: compute the symmetry of the pattern of A, and count the number of * nonzeros each column of A+A' (excluding the diagonal). Assumes the input * matrix has no errors, with sorted columns and no duplicates * (AMD_valid (n, n, Ap, Ai) must be AMD_OK, but this condition is not * checked). */ #pragma clang diagnostic ignored "-Wsign-conversion" #include "amd_internal.h" GLOBAL size_t AMD_aat /* returns nz in A+A' */ ( Int n, const Int Ap [ ], const Int Ai [ ], Int Len [ ], /* Len [j]: length of column j of A+A', excl diagonal*/ Int Tp [ ], /* workspace of size n */ double Info [ ] ) { Int p1, p2, p, i, j, pj, pj2, k, nzdiag, nzboth, nz ; double sym ; size_t nzaat ; #ifndef NDEBUG AMD_debug_init ("AMD AAT") ; for (k = 0 ; k < n ; k++) Tp [k] = EMPTY ; ASSERT (AMD_valid (n, n, Ap, Ai) == AMD_OK) ; #endif if (Info != (double *) NULL) { /* clear the Info array, if it exists */ for (i = 0 ; i < AMD_INFO ; i++) { Info [i] = EMPTY ; } Info [AMD_STATUS] = AMD_OK ; } for (k = 0 ; k < n ; k++) { Len [k] = 0 ; } nzdiag = 0 ; nzboth = 0 ; nz = Ap [n] ; for (k = 0 ; k < n ; k++) { p1 = Ap [k] ; p2 = Ap [k+1] ; AMD_DEBUG2 (("\nAAT Column: "ID" p1: "ID" p2: "ID"\n", k, p1, p2)) ; /* construct A+A' */ for (p = p1 ; p < p2 ; ) { /* scan the upper triangular part of A */ j = Ai [p] ; if (j < k) { /* entry A (j,k) is in the strictly upper triangular part, * add both A (j,k) and A (k,j) to the matrix A+A' */ Len [j]++ ; Len [k]++ ; AMD_DEBUG3 ((" upper ("ID","ID") ("ID","ID")\n", j,k, k,j)); p++ ; } else if (j == k) { /* skip the diagonal */ p++ ; nzdiag++ ; break ; } else /* j > k */ { /* first entry below the diagonal */ break ; } /* scan lower triangular part of A, in column j until reaching * row k. Start where last scan left off. */ ASSERT (Tp [j] != EMPTY) ; ASSERT (Ap [j] <= Tp [j] && Tp [j] <= Ap [j+1]) ; pj2 = Ap [j+1] ; for (pj = Tp [j] ; pj < pj2 ; ) { i = Ai [pj] ; if (i < k) { /* A (i,j) is only in the lower part, not in upper. * add both A (i,j) and A (j,i) to the matrix A+A' */ Len [i]++ ; Len [j]++ ; AMD_DEBUG3 ((" lower ("ID","ID") ("ID","ID")\n", i,j, j,i)) ; pj++ ; } else if (i == k) { /* entry A (k,j) in lower part and A (j,k) in upper */ pj++ ; nzboth++ ; break ; } else /* i > k */ { /* consider this entry later, when k advances to i */ break ; } } Tp [j] = pj ; } /* Tp [k] points to the entry just below the diagonal in column k */ Tp [k] = p ; } /* clean up, for remaining mismatched entries */ for (j = 0 ; j < n ; j++) { for (pj = Tp [j] ; pj < Ap [j+1] ; pj++) { i = Ai [pj] ; /* A (i,j) is only in the lower part, not in upper. * add both A (i,j) and A (j,i) to the matrix A+A' */ Len [i]++ ; Len [j]++ ; AMD_DEBUG3 ((" lower cleanup ("ID","ID") ("ID","ID")\n", i,j, j,i)) ; } } /* --------------------------------------------------------------------- */ /* compute the symmetry of the nonzero pattern of A */ /* --------------------------------------------------------------------- */ /* Given a matrix A, the symmetry of A is: * B = tril (spones (A), -1) + triu (spones (A), 1) ; * sym = nnz (B & B') / nnz (B) ; * or 1 if nnz (B) is zero. */ if (nz == nzdiag) { sym = 1 ; } else { sym = (2 * (double) nzboth) / ((double) (nz - nzdiag)) ; } nzaat = 0 ; for (k = 0 ; k < n ; k++) { nzaat += Len [k] ; } AMD_DEBUG1 (("AMD nz in A+A', excluding diagonal (nzaat) = %g\n", (double) nzaat)) ; AMD_DEBUG1 ((" nzboth: "ID" nz: "ID" nzdiag: "ID" symmetry: %g\n", nzboth, nz, nzdiag, sym)) ; if (Info != (double *) NULL) { Info [AMD_STATUS] = AMD_OK ; Info [AMD_N] = n ; Info [AMD_NZ] = nz ; Info [AMD_SYMMETRY] = sym ; /* symmetry of pattern of A */ Info [AMD_NZDIAG] = nzdiag ; /* nonzeros on diagonal of A */ Info [AMD_NZ_A_PLUS_AT] = nzaat ; /* nonzeros in A+A' */ } return (nzaat) ; } python-igraph-0.8.0/vendor/source/igraph/optional/glpk/amd/amd_dump.c0000644000076500000240000001400113524616144026066 0ustar tamasstaff00000000000000/* ========================================================================= */ /* === AMD_dump ============================================================ */ /* ========================================================================= */ /* ------------------------------------------------------------------------- */ /* AMD, Copyright (c) Timothy A. Davis, */ /* Patrick R. Amestoy, and Iain S. Duff. See ../README.txt for License. */ /* email: davis at cise.ufl.edu CISE Department, Univ. of Florida. */ /* web: http://www.cise.ufl.edu/research/sparse/amd */ /* ------------------------------------------------------------------------- */ /* Debugging routines for AMD. Not used if NDEBUG is not defined at compile- * time (the default). See comments in amd_internal.h on how to enable * debugging. Not user-callable. */ #include "amd_internal.h" #ifndef NDEBUG /* This global variable is present only when debugging */ GLOBAL Int AMD_debug = -999 ; /* default is no debug printing */ /* ========================================================================= */ /* === AMD_debug_init ====================================================== */ /* ========================================================================= */ /* Sets the debug print level, by reading the file debug.amd (if it exists) */ GLOBAL void AMD_debug_init ( char *s ) { FILE *f ; f = fopen ("debug.amd", "r") ; if (f == (FILE *) NULL) { AMD_debug = -999 ; } else { fscanf (f, ID, &AMD_debug) ; fclose (f) ; } if (AMD_debug >= 0) { printf ("%s: AMD_debug_init, D= "ID"\n", s, AMD_debug) ; } } /* ========================================================================= */ /* === AMD_dump ============================================================ */ /* ========================================================================= */ /* Dump AMD's data structure, except for the hash buckets. This routine * cannot be called when the hash buckets are non-empty. */ GLOBAL void AMD_dump ( Int n, /* A is n-by-n */ Int Pe [ ], /* pe [0..n-1]: index in iw of start of row i */ Int Iw [ ], /* workspace of size iwlen, iwlen [0..pfree-1] * holds the matrix on input */ Int Len [ ], /* len [0..n-1]: length for row i */ Int iwlen, /* length of iw */ Int pfree, /* iw [pfree ... iwlen-1] is empty on input */ Int Nv [ ], /* nv [0..n-1] */ Int Next [ ], /* next [0..n-1] */ Int Last [ ], /* last [0..n-1] */ Int Head [ ], /* head [0..n-1] */ Int Elen [ ], /* size n */ Int Degree [ ], /* size n */ Int W [ ], /* size n */ Int nel ) { Int i, pe, elen, nv, len, e, p, k, j, deg, w, cnt, ilast ; if (AMD_debug < 0) return ; ASSERT (pfree <= iwlen) ; AMD_DEBUG3 (("\nAMD dump, pfree: "ID"\n", pfree)) ; for (i = 0 ; i < n ; i++) { pe = Pe [i] ; elen = Elen [i] ; nv = Nv [i] ; len = Len [i] ; w = W [i] ; if (elen >= EMPTY) { if (nv == 0) { AMD_DEBUG3 (("\nI "ID": nonprincipal: ", i)) ; ASSERT (elen == EMPTY) ; if (pe == EMPTY) { AMD_DEBUG3 ((" dense node\n")) ; ASSERT (w == 1) ; } else { ASSERT (pe < EMPTY) ; AMD_DEBUG3 ((" i "ID" -> parent "ID"\n", i, FLIP (Pe[i]))); } } else { AMD_DEBUG3 (("\nI "ID": active principal supervariable:\n",i)); AMD_DEBUG3 ((" nv(i): "ID" Flag: %d\n", nv, (nv < 0))) ; ASSERT (elen >= 0) ; ASSERT (nv > 0 && pe >= 0) ; p = pe ; AMD_DEBUG3 ((" e/s: ")) ; if (elen == 0) AMD_DEBUG3 ((" : ")) ; ASSERT (pe + len <= pfree) ; for (k = 0 ; k < len ; k++) { j = Iw [p] ; AMD_DEBUG3 ((" "ID"", j)) ; ASSERT (j >= 0 && j < n) ; if (k == elen-1) AMD_DEBUG3 ((" : ")) ; p++ ; } AMD_DEBUG3 (("\n")) ; } } else { e = i ; if (w == 0) { AMD_DEBUG3 (("\nE "ID": absorbed element: w "ID"\n", e, w)) ; ASSERT (nv > 0 && pe < 0) ; AMD_DEBUG3 ((" e "ID" -> parent "ID"\n", e, FLIP (Pe [e]))) ; } else { AMD_DEBUG3 (("\nE "ID": unabsorbed element: w "ID"\n", e, w)) ; ASSERT (nv > 0 && pe >= 0) ; p = pe ; AMD_DEBUG3 ((" : ")) ; ASSERT (pe + len <= pfree) ; for (k = 0 ; k < len ; k++) { j = Iw [p] ; AMD_DEBUG3 ((" "ID"", j)) ; ASSERT (j >= 0 && j < n) ; p++ ; } AMD_DEBUG3 (("\n")) ; } } } /* this routine cannot be called when the hash buckets are non-empty */ AMD_DEBUG3 (("\nDegree lists:\n")) ; if (nel >= 0) { cnt = 0 ; for (deg = 0 ; deg < n ; deg++) { if (Head [deg] == EMPTY) continue ; ilast = EMPTY ; AMD_DEBUG3 ((ID": \n", deg)) ; for (i = Head [deg] ; i != EMPTY ; i = Next [i]) { AMD_DEBUG3 ((" "ID" : next "ID" last "ID" deg "ID"\n", i, Next [i], Last [i], Degree [i])) ; ASSERT (i >= 0 && i < n && ilast == Last [i] && deg == Degree [i]) ; cnt += Nv [i] ; ilast = i ; } AMD_DEBUG3 (("\n")) ; } ASSERT (cnt == n - nel) ; } } #endif python-igraph-0.8.0/vendor/source/igraph/optional/glpk/amd/amd_order.c0000644000076500000240000001467213524616144026252 0ustar tamasstaff00000000000000/* ========================================================================= */ /* === AMD_order =========================================================== */ /* ========================================================================= */ /* ------------------------------------------------------------------------- */ /* AMD, Copyright (c) Timothy A. Davis, */ /* Patrick R. Amestoy, and Iain S. Duff. See ../README.txt for License. */ /* email: davis at cise.ufl.edu CISE Department, Univ. of Florida. */ /* web: http://www.cise.ufl.edu/research/sparse/amd */ /* ------------------------------------------------------------------------- */ /* User-callable AMD minimum degree ordering routine. See amd.h for * documentation. */ #pragma clang diagnostic ignored "-Wsign-conversion" #pragma clang diagnostic ignored "-Wshorten-64-to-32" #include "amd_internal.h" /* ========================================================================= */ /* === AMD_order =========================================================== */ /* ========================================================================= */ GLOBAL Int AMD_order ( Int n, const Int Ap [ ], const Int Ai [ ], Int P [ ], double Control [ ], double Info [ ] ) { Int *Len, *S, nz, i, *Pinv, info, status, *Rp, *Ri, *Cp, *Ci, ok ; size_t nzaat, slen ; double mem = 0 ; #ifndef NDEBUG AMD_debug_init ("amd") ; #endif /* clear the Info array, if it exists */ info = Info != (double *) NULL ; if (info) { for (i = 0 ; i < AMD_INFO ; i++) { Info [i] = EMPTY ; } Info [AMD_N] = n ; Info [AMD_STATUS] = AMD_OK ; } /* make sure inputs exist and n is >= 0 */ if (Ai == (Int *) NULL || Ap == (Int *) NULL || P == (Int *) NULL || n < 0) { if (info) Info [AMD_STATUS] = AMD_INVALID ; return (AMD_INVALID) ; /* arguments are invalid */ } if (n == 0) { return (AMD_OK) ; /* n is 0 so there's nothing to do */ } nz = Ap [n] ; if (info) { Info [AMD_NZ] = nz ; } if (nz < 0) { if (info) Info [AMD_STATUS] = AMD_INVALID ; return (AMD_INVALID) ; } /* check if n or nz will cause size_t overflow */ if (((size_t) n) >= SIZE_T_MAX / sizeof (Int) || ((size_t) nz) >= SIZE_T_MAX / sizeof (Int)) { if (info) Info [AMD_STATUS] = AMD_OUT_OF_MEMORY ; return (AMD_OUT_OF_MEMORY) ; /* problem too large */ } /* check the input matrix: AMD_OK, AMD_INVALID, or AMD_OK_BUT_JUMBLED */ status = AMD_valid (n, n, Ap, Ai) ; if (status == AMD_INVALID) { if (info) Info [AMD_STATUS] = AMD_INVALID ; return (AMD_INVALID) ; /* matrix is invalid */ } /* allocate two size-n integer workspaces */ Len = amd_malloc (n * sizeof (Int)) ; Pinv = amd_malloc (n * sizeof (Int)) ; mem += n ; mem += n ; if (!Len || !Pinv) { /* :: out of memory :: */ amd_free (Len) ; amd_free (Pinv) ; if (info) Info [AMD_STATUS] = AMD_OUT_OF_MEMORY ; return (AMD_OUT_OF_MEMORY) ; } if (status == AMD_OK_BUT_JUMBLED) { /* sort the input matrix and remove duplicate entries */ AMD_DEBUG1 (("Matrix is jumbled\n")) ; Rp = amd_malloc ((n+1) * sizeof (Int)) ; Ri = amd_malloc (MAX (nz,1) * sizeof (Int)) ; mem += (n+1) ; mem += MAX (nz,1) ; if (!Rp || !Ri) { /* :: out of memory :: */ amd_free (Rp) ; amd_free (Ri) ; amd_free (Len) ; amd_free (Pinv) ; if (info) Info [AMD_STATUS] = AMD_OUT_OF_MEMORY ; return (AMD_OUT_OF_MEMORY) ; } /* use Len and Pinv as workspace to create R = A' */ AMD_preprocess (n, Ap, Ai, Rp, Ri, Len, Pinv) ; Cp = Rp ; Ci = Ri ; } else { /* order the input matrix as-is. No need to compute R = A' first */ Rp = NULL ; Ri = NULL ; Cp = (Int *) Ap ; Ci = (Int *) Ai ; } /* --------------------------------------------------------------------- */ /* determine the symmetry and count off-diagonal nonzeros in A+A' */ /* --------------------------------------------------------------------- */ nzaat = AMD_aat (n, Cp, Ci, Len, P, Info) ; AMD_DEBUG1 (("nzaat: %g\n", (double) nzaat)) ; ASSERT ((MAX (nz-n, 0) <= nzaat) && (nzaat <= 2 * (size_t) nz)) ; /* --------------------------------------------------------------------- */ /* allocate workspace for matrix, elbow room, and 6 size-n vectors */ /* --------------------------------------------------------------------- */ S = NULL ; slen = nzaat ; /* space for matrix */ ok = ((slen + nzaat/5) >= slen) ; /* check for size_t overflow */ slen += nzaat/5 ; /* add elbow room */ for (i = 0 ; ok && i < 7 ; i++) { ok = ((slen + n) > slen) ; /* check for size_t overflow */ slen += n ; /* size-n elbow room, 6 size-n work */ } mem += slen ; ok = ok && (slen < SIZE_T_MAX / sizeof (Int)) ; /* check for overflow */ ok = ok && (slen < Int_MAX) ; /* S[i] for Int i must be OK */ if (ok) { S = amd_malloc (slen * sizeof (Int)) ; } AMD_DEBUG1 (("slen %g\n", (double) slen)) ; if (!S) { /* :: out of memory :: (or problem too large) */ amd_free (Rp) ; amd_free (Ri) ; amd_free (Len) ; amd_free (Pinv) ; if (info) Info [AMD_STATUS] = AMD_OUT_OF_MEMORY ; return (AMD_OUT_OF_MEMORY) ; } if (info) { /* memory usage, in bytes. */ Info [AMD_MEMORY] = mem * sizeof (Int) ; } /* --------------------------------------------------------------------- */ /* order the matrix */ /* --------------------------------------------------------------------- */ AMD_1 (n, Cp, Ci, P, Pinv, Len, slen, S, Control, Info) ; /* --------------------------------------------------------------------- */ /* free the workspace */ /* --------------------------------------------------------------------- */ amd_free (Rp) ; amd_free (Ri) ; amd_free (Len) ; amd_free (Pinv) ; amd_free (S) ; if (info) Info [AMD_STATUS] = status ; return (status) ; /* successful ordering */ } python-igraph-0.8.0/vendor/source/igraph/optional/glpk/amd/amd.h0000644000076500000240000000327613524616144025062 0ustar tamasstaff00000000000000/* amd.h */ /* Written by Andrew Makhorin . */ #ifndef GLPAMD_H #define GLPAMD_H #define AMD_DATE "May 31, 2007" #define AMD_VERSION_CODE(main, sub) ((main) * 1000 + (sub)) #define AMD_MAIN_VERSION 2 #define AMD_SUB_VERSION 2 #define AMD_SUBSUB_VERSION 0 #define AMD_VERSION AMD_VERSION_CODE(AMD_MAIN_VERSION, AMD_SUB_VERSION) #define AMD_CONTROL 5 #define AMD_INFO 20 #define AMD_DENSE 0 #define AMD_AGGRESSIVE 1 #define AMD_DEFAULT_DENSE 10.0 #define AMD_DEFAULT_AGGRESSIVE 1 #define AMD_STATUS 0 #define AMD_N 1 #define AMD_NZ 2 #define AMD_SYMMETRY 3 #define AMD_NZDIAG 4 #define AMD_NZ_A_PLUS_AT 5 #define AMD_NDENSE 6 #define AMD_MEMORY 7 #define AMD_NCMPA 8 #define AMD_LNZ 9 #define AMD_NDIV 10 #define AMD_NMULTSUBS_LDL 11 #define AMD_NMULTSUBS_LU 12 #define AMD_DMAX 13 #define AMD_OK 0 #define AMD_OUT_OF_MEMORY (-1) #define AMD_INVALID (-2) #define AMD_OK_BUT_JUMBLED 1 #define amd_order _glp_amd_order int amd_order(int n, const int Ap[], const int Ai[], int P[], double Control[], double Info[]); #define amd_2 _glp_amd_2 void amd_2(int n, int Pe[], int Iw[], int Len[], int iwlen, int pfree, int Nv[], int Next[], int Last[], int Head[], int Elen[], int Degree[], int W[], double Control[], double Info[]); #define amd_valid _glp_amd_valid int amd_valid(int n_row, int n_col, const int Ap[], const int Ai[]); #define amd_defaults _glp_amd_defaults void amd_defaults(double Control[]); #define amd_control _glp_amd_control void amd_control(double Control[]); #define amd_info _glp_amd_info void amd_info(double Info[]); #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/amd/amd_control.c0000644000076500000240000000370113524616144026606 0ustar tamasstaff00000000000000/* ========================================================================= */ /* === AMD_control ========================================================= */ /* ========================================================================= */ /* ------------------------------------------------------------------------- */ /* AMD, Copyright (c) Timothy A. Davis, */ /* Patrick R. Amestoy, and Iain S. Duff. See ../README.txt for License. */ /* email: davis at cise.ufl.edu CISE Department, Univ. of Florida. */ /* web: http://www.cise.ufl.edu/research/sparse/amd */ /* ------------------------------------------------------------------------- */ /* User-callable. Prints the control parameters for AMD. See amd.h * for details. If the Control array is not present, the defaults are * printed instead. */ #include "amd_internal.h" GLOBAL void AMD_control ( double Control [ ] ) { double alpha ; Int aggressive ; if (Control != (double *) NULL) { alpha = Control [AMD_DENSE] ; aggressive = Control [AMD_AGGRESSIVE] != 0 ; } else { alpha = AMD_DEFAULT_DENSE ; aggressive = AMD_DEFAULT_AGGRESSIVE ; } PRINTF (("\nAMD version %d.%d.%d, %s: approximate minimum degree ordering\n" " dense row parameter: %g\n", AMD_MAIN_VERSION, AMD_SUB_VERSION, AMD_SUBSUB_VERSION, AMD_DATE, alpha)) ; if (alpha < 0) { PRINTF ((" no rows treated as dense\n")) ; } else { PRINTF (( " (rows with more than max (%g * sqrt (n), 16) entries are\n" " considered \"dense\", and placed last in output permutation)\n", alpha)) ; } if (aggressive) { PRINTF ((" aggressive absorption: yes\n")) ; } else { PRINTF ((" aggressive absorption: no\n")) ; } PRINTF ((" size of AMD integer: %d\n\n", sizeof (Int))) ; } python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpapi19.c0000644000076500000240000013254113524616144025177 0ustar tamasstaff00000000000000/* glpapi19.c (stand-alone LP/MIP solver) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wlogical-op-parentheses" #pragma clang diagnostic ignored "-Wsign-conversion" #endif #include "glpapi.h" #include "glpgmp.h" struct csa { /* common storage area */ glp_prob *prob; /* LP/MIP problem object */ glp_bfcp bfcp; /* basis factorization control parameters */ glp_smcp smcp; /* simplex method control parameters */ glp_iptcp iptcp; /* interior-point method control parameters */ glp_iocp iocp; /* integer optimizer control parameters */ glp_tran *tran; /* model translator workspace */ glp_graph *graph; /* network problem object */ int format; /* problem file format: */ #define FMT_MPS_DECK 1 /* fixed MPS */ #define FMT_MPS_FILE 2 /* free MPS */ #define FMT_LP 3 /* CPLEX LP */ #define FMT_GLP 4 /* GLPK LP/MIP */ #define FMT_MATHPROG 5 /* MathProg */ #define FMT_MIN_COST 6 /* DIMACS min-cost flow */ #define FMT_MAX_FLOW 7 /* DIMACS maximum flow */ const char *in_file; /* name of input problem file */ #define DATA_MAX 10 /* maximal number of input data files */ int ndf; /* number of input data files specified */ const char *in_data[1+DATA_MAX]; /* name(s) of input data file(s) */ const char *out_dpy; /* name of output file to send display output; NULL means the display output is sent to the terminal */ int seed; /* seed value to be passed to the MathProg translator; initially set to 1; 0x80000000 means the value is omitted */ int solution; /* solution type flag: */ #define SOL_BASIC 1 /* basic */ #define SOL_INTERIOR 2 /* interior-point */ #define SOL_INTEGER 3 /* mixed integer */ const char *in_res; /* name of input solution file in raw format */ int dir; /* optimization direction flag: 0 - not specified GLP_MIN - minimization GLP_MAX - maximization */ int scale; /* automatic problem scaling flag */ const char *out_sol; /* name of output solution file in printable format */ const char *out_res; /* name of output solution file in raw format */ const char *out_ranges; /* name of output file to write sensitivity analysis report */ int check; /* input data checking flag; no solution is performed */ const char *new_name; /* new name to be assigned to the problem */ const char *out_mps; /* name of output problem file in fixed MPS format */ const char *out_freemps; /* name of output problem file in free MPS format */ const char *out_cpxlp; /* name of output problem file in CPLEX LP format */ const char *out_glp; /* name of output problem file in GLPK format */ const char *out_pb; /* name of output problem file in OPB format */ const char *out_npb; /* name of output problem file in normalized OPB format */ const char *log_file; /* name of output file to hardcopy terminal output */ int crash; /* initial basis option: */ #define USE_STD_BASIS 1 /* use standard basis */ #define USE_ADV_BASIS 2 /* use advanced basis */ #define USE_CPX_BASIS 3 /* use Bixby's basis */ #define USE_INI_BASIS 4 /* use initial basis from ini_file */ const char *ini_file; /* name of input file containing initial basis */ int exact; /* flag to use glp_exact rather than glp_simplex */ int xcheck; /* flag to check final basis with glp_exact */ int nomip; /* flag to consider MIP as pure LP */ }; static void print_help(const char *my_name) { /* print help information */ xprintf("Usage: %s [options...] filename\n", my_name); xprintf("\n"); xprintf("General options:\n"); xprintf(" --mps read LP/MIP problem in fixed MPS fo" "rmat\n"); xprintf(" --freemps read LP/MIP problem in free MPS for" "mat (default)\n"); xprintf(" --lp read LP/MIP problem in CPLEX LP for" "mat\n"); xprintf(" --glp read LP/MIP problem in GLPK format " "\n"); xprintf(" --math read LP/MIP model written in GNU Ma" "thProg modeling\n"); xprintf(" language\n"); xprintf(" -m filename, --model filename\n"); xprintf(" read model section and optional dat" "a section from\n"); xprintf(" filename (same as --math)\n"); xprintf(" -d filename, --data filename\n"); xprintf(" read data section from filename (fo" "r --math only);\n"); xprintf(" if model file also has data section" ", it is ignored\n"); xprintf(" -y filename, --display filename\n"); xprintf(" send display output to filename (fo" "r --math only);\n"); xprintf(" by default the output is sent to te" "rminal\n"); xprintf(" --seed value initialize pseudo-random number gen" "erator used in\n"); xprintf(" MathProg model with specified seed " "(any integer);\n"); xprintf(" if seed value is ?, some random see" "d will be used\n"); xprintf(" --mincost read min-cost flow problem in DIMAC" "S format\n"); xprintf(" --maxflow read maximum flow problem in DIMACS" " format\n"); xprintf(" --simplex use simplex method (default)\n"); xprintf(" --interior use interior point method (LP only)" "\n"); xprintf(" -r filename, --read filename\n"); xprintf(" read solution from filename rather " "to find it with\n"); xprintf(" the solver\n"); xprintf(" --min minimization\n"); xprintf(" --max maximization\n"); xprintf(" --scale scale problem (default)\n"); xprintf(" --noscale do not scale problem\n"); xprintf(" -o filename, --output filename\n"); xprintf(" write solution to filename in print" "able format\n"); xprintf(" -w filename, --write filename\n"); xprintf(" write solution to filename in plain" " text format\n"); xprintf(" --ranges filename\n"); xprintf(" write sensitivity analysis report t" "o filename in\n"); xprintf(" printable format (simplex only)\n"); xprintf(" --tmlim nnn limit solution time to nnn seconds " "\n"); xprintf(" --memlim nnn limit available memory to nnn megab" "ytes\n"); xprintf(" --check do not solve problem, check input d" "ata only\n"); xprintf(" --name probname change problem name to probname\n"); xprintf(" --wmps filename write problem to filename in fixed " "MPS format\n"); xprintf(" --wfreemps filename\n"); xprintf(" write problem to filename in free M" "PS format\n"); xprintf(" --wlp filename write problem to filename in CPLEX " "LP format\n"); xprintf(" --wglp filename write problem to filename in GLPK f" "ormat\n"); #if 0 xprintf(" --wpb filename write problem to filename in OPB fo" "rmat\n"); xprintf(" --wnpb filename write problem to filename in normal" "ized OPB format\n"); #endif xprintf(" --log filename write copy of terminal output to fi" "lename\n"); xprintf(" -h, --help display this help information and e" "xit\n"); xprintf(" -v, --version display program version and exit\n") ; xprintf("\n"); xprintf("LP basis factorization options:\n"); xprintf(" --luf LU + Forrest-Tomlin update\n"); xprintf(" (faster, less stable; default)\n"); xprintf(" --cbg LU + Schur complement + Bartels-Gol" "ub update\n"); xprintf(" (slower, more stable)\n"); xprintf(" --cgr LU + Schur complement + Givens rota" "tion update\n"); xprintf(" (slower, more stable)\n"); xprintf("\n"); xprintf("Options specific to simplex solver:\n"); xprintf(" --primal use primal simplex (default)\n"); xprintf(" --dual use dual simplex\n"); xprintf(" --std use standard initial basis of all s" "lacks\n"); xprintf(" --adv use advanced initial basis (default" ")\n"); xprintf(" --bib use Bixby's initial basis\n"); xprintf(" --ini filename use as initial basis previously sav" "ed with -w\n"); xprintf(" (disables LP presolver)\n"); xprintf(" --steep use steepest edge technique (defaul" "t)\n"); xprintf(" --nosteep use standard \"textbook\" pricing\n" ); xprintf(" --relax use Harris' two-pass ratio test (de" "fault)\n"); xprintf(" --norelax use standard \"textbook\" ratio tes" "t\n"); xprintf(" --presol use presolver (default; assumes --s" "cale and --adv)\n"); xprintf(" --nopresol do not use presolver\n"); xprintf(" --exact use simplex method based on exact a" "rithmetic\n"); xprintf(" --xcheck check final basis using exact arith" "metic\n"); xprintf("\n"); xprintf("Options specific to interior-point solver:\n"); xprintf(" --nord use natural (original) ordering\n"); xprintf(" --qmd use quotient minimum degree orderin" "g\n"); xprintf(" --amd use approximate minimum degree orde" "ring (default)\n"); xprintf(" --symamd use approximate minimum degree orde" "ring\n"); xprintf("\n"); xprintf("Options specific to MIP solver:\n"); xprintf(" --nomip consider all integer variables as c" "ontinuous\n"); xprintf(" (allows solving MIP as pure LP)\n"); xprintf(" --first branch on first integer variable\n") ; xprintf(" --last branch on last integer variable\n"); xprintf(" --mostf branch on most fractional variable " "\n"); xprintf(" --drtom branch using heuristic by Driebeck " "and Tomlin\n"); xprintf(" (default)\n"); xprintf(" --pcost branch using hybrid pseudocost heur" "istic (may be\n"); xprintf(" useful for hard instances)\n"); xprintf(" --dfs backtrack using depth first search " "\n"); xprintf(" --bfs backtrack using breadth first searc" "h\n"); xprintf(" --bestp backtrack using the best projection" " heuristic\n"); xprintf(" --bestb backtrack using node with best loca" "l bound\n"); xprintf(" (default)\n"); xprintf(" --intopt use MIP presolver (default)\n"); xprintf(" --nointopt do not use MIP presolver\n"); xprintf(" --binarize replace general integer variables b" "y binary ones\n"); xprintf(" (assumes --intopt)\n"); xprintf(" --fpump apply feasibility pump heuristic\n") ; xprintf(" --gomory generate Gomory's mixed integer cut" "s\n"); xprintf(" --mir generate MIR (mixed integer roundin" "g) cuts\n"); xprintf(" --cover generate mixed cover cuts\n"); xprintf(" --clique generate clique cuts\n"); xprintf(" --cuts generate all cuts above\n"); xprintf(" --mipgap tol set relative mip gap tolerance to t" "ol\n"); xprintf("\n"); xprintf("For description of the MPS and CPLEX LP formats see Refe" "rence Manual.\n"); xprintf("For description of the modeling language see \"GLPK: Mod" "eling Language\n"); xprintf("GNU MathProg\". Both documents are included in the GLPK " "distribution.\n"); xprintf("\n"); xprintf("See GLPK web page at .\n"); xprintf("\n"); xprintf("Please report bugs to .\n"); return; } static void print_version(int briefly) { /* print version information */ xprintf("GLPSOL: GLPK LP/MIP Solver, v%s\n", glp_version()); if (briefly) goto done; xprintf("\n"); xprintf("Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, " "2007, 2008,\n"); xprintf("2009, 2010 Andrew Makhorin, Department for Applied Infor" "matics, Moscow\n"); xprintf("Aviation Institute, Moscow, Russia. All rights reserved." "\n"); xprintf("\n"); xprintf("This program has ABSOLUTELY NO WARRANTY.\n"); xprintf("\n"); xprintf("This program is free software; you may re-distribute it " "under the terms\n"); xprintf("of the GNU General Public License version 3 or later.\n") ; done: return; } static int parse_cmdline(struct csa *csa, int argc, const char *argv[]) { /* parse command-line parameters */ int k; #define p(str) (strcmp(argv[k], str) == 0) for (k = 1; k < argc; k++) { if (p("--mps")) csa->format = FMT_MPS_DECK; else if (p("--freemps")) csa->format = FMT_MPS_FILE; else if (p("--lp") || p("--cpxlp")) csa->format = FMT_LP; else if (p("--glp")) csa->format = FMT_GLP; else if (p("--math") || p("-m") || p("--model")) csa->format = FMT_MATHPROG; else if (p("-d") || p("--data")) { k++; if (k == argc || argv[k][0] == '\0' || argv[k][0] == '-') { xprintf("No input data file specified\n"); return 1; } if (csa->ndf == DATA_MAX) { xprintf("Too many input data files\n"); return 1; } csa->in_data[++(csa->ndf)] = argv[k]; } else if (p("-y") || p("--display")) { k++; if (k == argc || argv[k][0] == '\0' || argv[k][0] == '-') { xprintf("No display output file specified\n"); return 1; } if (csa->out_dpy != NULL) { xprintf("Only one display output file allowed\n"); return 1; } csa->out_dpy = argv[k]; } else if (p("--seed")) { k++; if (k == argc || argv[k][0] == '\0' || argv[k][0] == '-' && !isdigit((unsigned char)argv[k][1])) { xprintf("No seed value specified\n"); return 1; } if (strcmp(argv[k], "?") == 0) csa->seed = 0x80000000; else if (str2int(argv[k], &csa->seed)) { xprintf("Invalid seed value `%s'\n", argv[k]); return 1; } } else if (p("--mincost")) csa->format = FMT_MIN_COST; else if (p("--maxflow")) csa->format = FMT_MAX_FLOW; else if (p("--simplex")) csa->solution = SOL_BASIC; else if (p("--interior")) csa->solution = SOL_INTERIOR; #if 1 /* 28/V-2010 */ else if (p("--alien")) csa->iocp.alien = GLP_ON; #endif else if (p("-r") || p("--read")) { k++; if (k == argc || argv[k][0] == '\0' || argv[k][0] == '-') { xprintf("No input solution file specified\n"); return 1; } if (csa->in_res != NULL) { xprintf("Only one input solution file allowed\n"); return 1; } csa->in_res = argv[k]; } else if (p("--min")) csa->dir = GLP_MIN; else if (p("--max")) csa->dir = GLP_MAX; else if (p("--scale")) csa->scale = 1; else if (p("--noscale")) csa->scale = 0; else if (p("-o") || p("--output")) { k++; if (k == argc || argv[k][0] == '\0' || argv[k][0] == '-') { xprintf("No output solution file specified\n"); return 1; } if (csa->out_sol != NULL) { xprintf("Only one output solution file allowed\n"); return 1; } csa->out_sol = argv[k]; } else if (p("-w") || p("--write")) { k++; if (k == argc || argv[k][0] == '\0' || argv[k][0] == '-') { xprintf("No output solution file specified\n"); return 1; } if (csa->out_res != NULL) { xprintf("Only one output solution file allowed\n"); return 1; } csa->out_res = argv[k]; } else if (p("--ranges") || p("--bounds")) { k++; if (k == argc || argv[k][0] == '\0' || argv[k][0] == '-') { xprintf("No output file specified to write sensitivity a" "nalysis report\n"); return 1; } if (csa->out_ranges != NULL) { xprintf("Only one output file allowed to write sensitivi" "ty analysis report\n"); return 1; } csa->out_ranges = argv[k]; } else if (p("--tmlim")) { int tm_lim; k++; if (k == argc || argv[k][0] == '\0' || argv[k][0] == '-') { xprintf("No time limit specified\n"); return 1; } if (str2int(argv[k], &tm_lim) || tm_lim < 0) { xprintf("Invalid time limit `%s'\n", argv[k]); return 1; } if (tm_lim <= INT_MAX / 1000) csa->smcp.tm_lim = csa->iocp.tm_lim = 1000 * tm_lim; else csa->smcp.tm_lim = csa->iocp.tm_lim = INT_MAX; } else if (p("--memlim")) { int mem_lim; k++; if (k == argc || argv[k][0] == '\0' || argv[k][0] == '-') { xprintf("No memory limit specified\n"); return 1; } if (str2int(argv[k], &mem_lim) || mem_lim < 1) { xprintf("Invalid memory limit `%s'\n", argv[k]); return 1; } glp_mem_limit(mem_lim); } else if (p("--check")) csa->check = 1; else if (p("--name")) { k++; if (k == argc || argv[k][0] == '\0' || argv[k][0] == '-') { xprintf("No problem name specified\n"); return 1; } if (csa->new_name != NULL) { xprintf("Only one problem name allowed\n"); return 1; } csa->new_name = argv[k]; } else if (p("--wmps")) { k++; if (k == argc || argv[k][0] == '\0' || argv[k][0] == '-') { xprintf("No fixed MPS output file specified\n"); return 1; } if (csa->out_mps != NULL) { xprintf("Only one fixed MPS output file allowed\n"); return 1; } csa->out_mps = argv[k]; } else if (p("--wfreemps")) { k++; if (k == argc || argv[k][0] == '\0' || argv[k][0] == '-') { xprintf("No free MPS output file specified\n"); return 1; } if (csa->out_freemps != NULL) { xprintf("Only one free MPS output file allowed\n"); return 1; } csa->out_freemps = argv[k]; } else if (p("--wlp") || p("--wcpxlp") || p("--wlpt")) { k++; if (k == argc || argv[k][0] == '\0' || argv[k][0] == '-') { xprintf("No CPLEX LP output file specified\n"); return 1; } if (csa->out_cpxlp != NULL) { xprintf("Only one CPLEX LP output file allowed\n"); return 1; } csa->out_cpxlp = argv[k]; } else if (p("--wglp")) { k++; if (k == argc || argv[k][0] == '\0' || argv[k][0] == '-') { xprintf("No GLPK LP/MIP output file specified\n"); return 1; } if (csa->out_glp != NULL) { xprintf("Only one GLPK LP/MIP output file allowed\n"); return 1; } csa->out_glp = argv[k]; } else if (p("--wpb")) { k++; if (k == argc || argv[k][0] == '\0' || argv[k][0] == '-') { xprintf("No problem output file specified\n"); return 1; } if (csa->out_pb != NULL) { xprintf("Only one OPB output file allowed\n"); return 1; } csa->out_pb = argv[k]; } else if (p("--wnpb")) { k++; if (k == argc || argv[k][0] == '\0' || argv[k][0] == '-') { xprintf("No problem output file specified\n"); return 1; } if (csa->out_npb != NULL) { xprintf("Only one normalized OPB output file allowed\n"); return 1; } csa->out_npb = argv[k]; } else if (p("--log")) { k++; if (k == argc || argv[k][0] == '\0' || argv[k][0] == '-') { xprintf("No log file specified\n"); return 1; } if (csa->log_file != NULL) { xprintf("Only one log file allowed\n"); return 1; } csa->log_file = argv[k]; } else if (p("-h") || p("--help")) { print_help(argv[0]); return -1; } else if (p("-v") || p("--version")) { print_version(0); return -1; } else if (p("--luf")) csa->bfcp.type = GLP_BF_FT; else if (p("--cbg")) csa->bfcp.type = GLP_BF_BG; else if (p("--cgr")) csa->bfcp.type = GLP_BF_GR; else if (p("--primal")) csa->smcp.meth = GLP_PRIMAL; else if (p("--dual")) csa->smcp.meth = GLP_DUAL; else if (p("--std")) csa->crash = USE_STD_BASIS; else if (p("--adv")) csa->crash = USE_ADV_BASIS; else if (p("--bib")) csa->crash = USE_CPX_BASIS; else if (p("--ini")) { csa->crash = USE_INI_BASIS; csa->smcp.presolve = GLP_OFF; k++; if (k == argc || argv[k][0] == '\0' || argv[k][0] == '-') { xprintf("No initial basis file specified\n"); return 1; } if (csa->ini_file != NULL) { xprintf("Only one initial basis file allowed\n"); return 1; } csa->ini_file = argv[k]; } else if (p("--steep")) csa->smcp.pricing = GLP_PT_PSE; else if (p("--nosteep")) csa->smcp.pricing = GLP_PT_STD; else if (p("--relax")) csa->smcp.r_test = GLP_RT_HAR; else if (p("--norelax")) csa->smcp.r_test = GLP_RT_STD; else if (p("--presol")) csa->smcp.presolve = GLP_ON; else if (p("--nopresol")) csa->smcp.presolve = GLP_OFF; else if (p("--exact")) csa->exact = 1; else if (p("--xcheck")) csa->xcheck = 1; else if (p("--nord")) csa->iptcp.ord_alg = GLP_ORD_NONE; else if (p("--qmd")) csa->iptcp.ord_alg = GLP_ORD_QMD; else if (p("--amd")) csa->iptcp.ord_alg = GLP_ORD_AMD; else if (p("--symamd")) csa->iptcp.ord_alg = GLP_ORD_SYMAMD; else if (p("--nomip")) csa->nomip = 1; else if (p("--first")) csa->iocp.br_tech = GLP_BR_FFV; else if (p("--last")) csa->iocp.br_tech = GLP_BR_LFV; else if (p("--drtom")) csa->iocp.br_tech = GLP_BR_DTH; else if (p("--mostf")) csa->iocp.br_tech = GLP_BR_MFV; else if (p("--pcost")) csa->iocp.br_tech = GLP_BR_PCH; else if (p("--dfs")) csa->iocp.bt_tech = GLP_BT_DFS; else if (p("--bfs")) csa->iocp.bt_tech = GLP_BT_BFS; else if (p("--bestp")) csa->iocp.bt_tech = GLP_BT_BPH; else if (p("--bestb")) csa->iocp.bt_tech = GLP_BT_BLB; else if (p("--intopt")) csa->iocp.presolve = GLP_ON; else if (p("--nointopt")) csa->iocp.presolve = GLP_OFF; else if (p("--binarize")) csa->iocp.presolve = csa->iocp.binarize = GLP_ON; else if (p("--fpump")) csa->iocp.fp_heur = GLP_ON; else if (p("--gomory")) csa->iocp.gmi_cuts = GLP_ON; else if (p("--mir")) csa->iocp.mir_cuts = GLP_ON; else if (p("--cover")) csa->iocp.cov_cuts = GLP_ON; else if (p("--clique")) csa->iocp.clq_cuts = GLP_ON; else if (p("--cuts")) csa->iocp.gmi_cuts = csa->iocp.mir_cuts = csa->iocp.cov_cuts = csa->iocp.clq_cuts = GLP_ON; else if (p("--mipgap")) { double mip_gap; k++; if (k == argc || argv[k][0] == '\0' || argv[k][0] == '-') { xprintf("No relative gap tolerance specified\n"); return 1; } if (str2num(argv[k], &mip_gap) || mip_gap < 0.0) { xprintf("Invalid relative mip gap tolerance `%s'\n", argv[k]); return 1; } csa->iocp.mip_gap = mip_gap; } else if (argv[k][0] == '-' || (argv[k][0] == '-' && argv[k][1] == '-')) { xprintf("Invalid option `%s'; try %s --help\n", argv[k], argv[0]); return 1; } else { if (csa->in_file != NULL) { xprintf("Only one input problem file allowed\n"); return 1; } csa->in_file = argv[k]; } } #undef p return 0; } typedef struct { double rhs, pi; } v_data; typedef struct { double low, cap, cost, x; } a_data; int glp_main(int argc, const char *argv[]) { /* stand-alone LP/MIP solver */ struct csa _csa, *csa = &_csa; int ret; glp_long start; /* perform initialization */ csa->prob = glp_create_prob(); glp_get_bfcp(csa->prob, &csa->bfcp); glp_init_smcp(&csa->smcp); csa->smcp.presolve = GLP_ON; glp_init_iptcp(&csa->iptcp); glp_init_iocp(&csa->iocp); csa->iocp.presolve = GLP_ON; csa->tran = NULL; csa->graph = NULL; csa->format = FMT_MPS_FILE; csa->in_file = NULL; csa->ndf = 0; csa->out_dpy = NULL; csa->seed = 1; csa->solution = SOL_BASIC; csa->in_res = NULL; csa->dir = 0; csa->scale = 1; csa->out_sol = NULL; csa->out_res = NULL; csa->out_ranges = NULL; csa->check = 0; csa->new_name = NULL; csa->out_mps = NULL; csa->out_freemps = NULL; csa->out_cpxlp = NULL; csa->out_glp = NULL; csa->out_pb = NULL; csa->out_npb = NULL; csa->log_file = NULL; csa->crash = USE_ADV_BASIS; csa->ini_file = NULL; csa->exact = 0; csa->xcheck = 0; csa->nomip = 0; /* parse command-line parameters */ ret = parse_cmdline(csa, argc, argv); if (ret < 0) { ret = EXIT_SUCCESS; goto done; } if (ret > 0) { ret = EXIT_FAILURE; goto done; } /*--------------------------------------------------------------*/ /* remove all output files specified in the command line */ if (csa->out_dpy != NULL) remove(csa->out_dpy); if (csa->out_sol != NULL) remove(csa->out_sol); if (csa->out_res != NULL) remove(csa->out_res); if (csa->out_ranges != NULL) remove(csa->out_ranges); if (csa->out_mps != NULL) remove(csa->out_mps); if (csa->out_freemps != NULL) remove(csa->out_freemps); if (csa->out_cpxlp != NULL) remove(csa->out_cpxlp); if (csa->out_glp != NULL) remove(csa->out_glp); if (csa->out_pb != NULL) remove(csa->out_pb); if (csa->out_npb != NULL) remove(csa->out_npb); if (csa->log_file != NULL) remove(csa->log_file); /*--------------------------------------------------------------*/ /* open log file, if required */ if (csa->log_file != NULL) { if (glp_open_tee(csa->log_file)) { xprintf("Unable to create log file\n"); ret = EXIT_FAILURE; goto done; } } /*--------------------------------------------------------------*/ /* print version information */ print_version(1); /*--------------------------------------------------------------*/ /* print parameters specified in the command line */ if (argc > 1) { int k, len = INT_MAX; xprintf("Parameter(s) specified in the command line:"); for (k = 1; k < argc; k++) { if (len > 72) xprintf("\n"), len = 0; xprintf(" %s", argv[k]); len += 1 + strlen(argv[k]); } xprintf("\n"); } /*--------------------------------------------------------------*/ /* read problem data from the input file */ if (csa->in_file == NULL) { xprintf("No input problem file specified; try %s --help\n", argv[0]); ret = EXIT_FAILURE; goto done; } if (csa->format == FMT_MPS_DECK) { ret = glp_read_mps(csa->prob, GLP_MPS_DECK, NULL, csa->in_file); if (ret != 0) err1: { xprintf("MPS file processing error\n"); ret = EXIT_FAILURE; goto done; } } else if (csa->format == FMT_MPS_FILE) { ret = glp_read_mps(csa->prob, GLP_MPS_FILE, NULL, csa->in_file); if (ret != 0) goto err1; } else if (csa->format == FMT_LP) { ret = glp_read_lp(csa->prob, NULL, csa->in_file); if (ret != 0) { xprintf("CPLEX LP file processing error\n"); ret = EXIT_FAILURE; goto done; } } else if (csa->format == FMT_GLP) { ret = glp_read_prob(csa->prob, 0, csa->in_file); if (ret != 0) { xprintf("GLPK LP/MIP file processing error\n"); ret = EXIT_FAILURE; goto done; } } else if (csa->format == FMT_MATHPROG) { int k; /* allocate the translator workspace */ csa->tran = glp_mpl_alloc_wksp(); /* set seed value */ if (csa->seed == 0x80000000) { csa->seed = glp_time().lo; xprintf("Seed value %d will be used\n", csa->seed); } _glp_mpl_init_rand(csa->tran, csa->seed); /* read model section and optional data section */ if (glp_mpl_read_model(csa->tran, csa->in_file, csa->ndf > 0)) err2: { xprintf("MathProg model processing error\n"); ret = EXIT_FAILURE; goto done; } /* read optional data section(s), if necessary */ for (k = 1; k <= csa->ndf; k++) { if (glp_mpl_read_data(csa->tran, csa->in_data[k])) goto err2; } /* generate the model */ if (glp_mpl_generate(csa->tran, csa->out_dpy)) goto err2; /* build the problem instance from the model */ glp_mpl_build_prob(csa->tran, csa->prob); } else if (csa->format == FMT_MIN_COST) { csa->graph = glp_create_graph(sizeof(v_data), sizeof(a_data)); ret = glp_read_mincost(csa->graph, offsetof(v_data, rhs), offsetof(a_data, low), offsetof(a_data, cap), offsetof(a_data, cost), csa->in_file); if (ret != 0) { xprintf("DIMACS file processing error\n"); ret = EXIT_FAILURE; goto done; } glp_mincost_lp(csa->prob, csa->graph, GLP_ON, offsetof(v_data, rhs), offsetof(a_data, low), offsetof(a_data, cap), offsetof(a_data, cost)); glp_set_prob_name(csa->prob, csa->in_file); } else if (csa->format == FMT_MAX_FLOW) { int s, t; csa->graph = glp_create_graph(sizeof(v_data), sizeof(a_data)); ret = glp_read_maxflow(csa->graph, &s, &t, offsetof(a_data, cap), csa->in_file); if (ret != 0) { xprintf("DIMACS file processing error\n"); ret = EXIT_FAILURE; goto done; } glp_maxflow_lp(csa->prob, csa->graph, GLP_ON, s, t, offsetof(a_data, cap)); glp_set_prob_name(csa->prob, csa->in_file); } else xassert(csa != csa); /*--------------------------------------------------------------*/ /* change problem name, if required */ if (csa->new_name != NULL) glp_set_prob_name(csa->prob, csa->new_name); /* change optimization direction, if required */ if (csa->dir != 0) glp_set_obj_dir(csa->prob, csa->dir); /* sort elements of the constraint matrix */ glp_sort_matrix(csa->prob); /*--------------------------------------------------------------*/ /* write problem data in fixed MPS format, if required */ if (csa->out_mps != NULL) { ret = glp_write_mps(csa->prob, GLP_MPS_DECK, NULL, csa->out_mps); if (ret != 0) { xprintf("Unable to write problem in fixed MPS format\n"); ret = EXIT_FAILURE; goto done; } } /* write problem data in free MPS format, if required */ if (csa->out_freemps != NULL) { ret = glp_write_mps(csa->prob, GLP_MPS_FILE, NULL, csa->out_freemps); if (ret != 0) { xprintf("Unable to write problem in free MPS format\n"); ret = EXIT_FAILURE; goto done; } } /* write problem data in CPLEX LP format, if required */ if (csa->out_cpxlp != NULL) { ret = glp_write_lp(csa->prob, NULL, csa->out_cpxlp); if (ret != 0) { xprintf("Unable to write problem in CPLEX LP format\n"); ret = EXIT_FAILURE; goto done; } } /* write problem data in GLPK format, if required */ if (csa->out_glp != NULL) { ret = glp_write_prob(csa->prob, 0, csa->out_glp); if (ret != 0) { xprintf("Unable to write problem in GLPK format\n"); ret = EXIT_FAILURE; goto done; } } /* write problem data in OPB format, if required */ if (csa->out_pb != NULL) { ret = lpx_write_pb(csa->prob, csa->out_pb, 0, 0); if (ret != 0) { xprintf("Unable to write problem in OPB format\n"); ret = EXIT_FAILURE; goto done; } } /* write problem data in normalized OPB format, if required */ if (csa->out_npb != NULL) { ret = lpx_write_pb(csa->prob, csa->out_npb, 1, 1); if (ret != 0) { xprintf( "Unable to write problem in normalized OPB format\n"); ret = EXIT_FAILURE; goto done; } } /*--------------------------------------------------------------*/ /* if only problem data check is required, skip computations */ if (csa->check) { ret = EXIT_SUCCESS; goto done; } /*--------------------------------------------------------------*/ /* determine the solution type */ if (!csa->nomip && glp_get_num_int(csa->prob) + glp_get_num_bin(csa->prob) > 0) { if (csa->solution == SOL_INTERIOR) { xprintf("Interior-point method is not able to solve MIP pro" "blem; use --simplex\n"); ret = EXIT_FAILURE; goto done; } csa->solution = SOL_INTEGER; } /*--------------------------------------------------------------*/ /* if solution is provided, read it and skip computations */ if (csa->in_res != NULL) { if (csa->solution == SOL_BASIC) ret = glp_read_sol(csa->prob, csa->in_res); else if (csa->solution == SOL_INTERIOR) ret = glp_read_ipt(csa->prob, csa->in_res); else if (csa->solution == SOL_INTEGER) ret = glp_read_mip(csa->prob, csa->in_res); else xassert(csa != csa); if (ret != 0) { xprintf("Unable to read problem solution\n"); ret = EXIT_FAILURE; goto done; } goto skip; } /*--------------------------------------------------------------*/ /* scale the problem data, if required */ if (csa->scale) { if (csa->solution == SOL_BASIC && !csa->smcp.presolve || csa->solution == SOL_INTERIOR || csa->solution == SOL_INTEGER && !csa->iocp.presolve) glp_scale_prob(csa->prob, GLP_SF_AUTO); } /*--------------------------------------------------------------*/ /* construct starting LP basis */ if (csa->solution == SOL_BASIC && !csa->smcp.presolve || csa->solution == SOL_INTEGER && !csa->iocp.presolve) { if (csa->crash == USE_STD_BASIS) glp_std_basis(csa->prob); else if (csa->crash == USE_ADV_BASIS) glp_adv_basis(csa->prob, 0); else if (csa->crash == USE_CPX_BASIS) glp_cpx_basis(csa->prob); else if (csa->crash == USE_INI_BASIS) { ret = glp_read_sol(csa->prob, csa->ini_file); if (ret != 0) { xprintf("Unable to read initial basis\n"); ret = EXIT_FAILURE; goto done; } } else xassert(csa != csa); } /*--------------------------------------------------------------*/ /* solve the problem */ start = xtime(); if (csa->solution == SOL_BASIC) { if (!csa->exact) { glp_set_bfcp(csa->prob, &csa->bfcp); glp_simplex(csa->prob, &csa->smcp); if (csa->xcheck) { if (csa->smcp.presolve && glp_get_status(csa->prob) != GLP_OPT) xprintf("If you need to check final basis for non-opt" "imal solution, use --nopresol\n"); else glp_exact(csa->prob, &csa->smcp); } if (csa->out_sol != NULL || csa->out_res != NULL) { if (csa->smcp.presolve && glp_get_status(csa->prob) != GLP_OPT) xprintf("If you need actual output for non-optimal solut" "ion, use --nopresol\n"); } } else glp_exact(csa->prob, &csa->smcp); } else if (csa->solution == SOL_INTERIOR) glp_interior(csa->prob, &csa->iptcp); else if (csa->solution == SOL_INTEGER) { if (!csa->iocp.presolve) { glp_set_bfcp(csa->prob, &csa->bfcp); glp_simplex(csa->prob, &csa->smcp); } #if 0 csa->iocp.msg_lev = GLP_MSG_DBG; csa->iocp.pp_tech = GLP_PP_NONE; #endif glp_intopt(csa->prob, &csa->iocp); } else xassert(csa != csa); /*--------------------------------------------------------------*/ /* display statistics */ xprintf("Time used: %.1f secs\n", xdifftime(xtime(), start)); { glp_long tpeak; char buf[50]; glp_mem_usage(NULL, NULL, NULL, &tpeak); xprintf("Memory used: %.1f Mb (%s bytes)\n", xltod(tpeak) / 1048576.0, xltoa(tpeak, buf)); } /*--------------------------------------------------------------*/ skip: /* postsolve the model, if necessary */ if (csa->tran != NULL) { if (csa->solution == SOL_BASIC) ret = glp_mpl_postsolve(csa->tran, csa->prob, GLP_SOL); else if (csa->solution == SOL_INTERIOR) ret = glp_mpl_postsolve(csa->tran, csa->prob, GLP_IPT); else if (csa->solution == SOL_INTEGER) ret = glp_mpl_postsolve(csa->tran, csa->prob, GLP_MIP); else xassert(csa != csa); if (ret != 0) { xprintf("Model postsolving error\n"); ret = EXIT_FAILURE; goto done; } } /*--------------------------------------------------------------*/ /* write problem solution in printable format, if required */ if (csa->out_sol != NULL) { if (csa->solution == SOL_BASIC) ret = lpx_print_sol(csa->prob, csa->out_sol); else if (csa->solution == SOL_INTERIOR) ret = lpx_print_ips(csa->prob, csa->out_sol); else if (csa->solution == SOL_INTEGER) ret = lpx_print_mip(csa->prob, csa->out_sol); else xassert(csa != csa); if (ret != 0) { xprintf("Unable to write problem solution\n"); ret = EXIT_FAILURE; goto done; } } /* write problem solution in printable format, if required */ if (csa->out_res != NULL) { if (csa->solution == SOL_BASIC) ret = glp_write_sol(csa->prob, csa->out_res); else if (csa->solution == SOL_INTERIOR) ret = glp_write_ipt(csa->prob, csa->out_res); else if (csa->solution == SOL_INTEGER) ret = glp_write_mip(csa->prob, csa->out_res); else xassert(csa != csa); if (ret != 0) { xprintf("Unable to write problem solution\n"); ret = EXIT_FAILURE; goto done; } } /* write sensitivity analysis report, if required */ if (csa->out_ranges != NULL) { if (csa->solution == SOL_BASIC) { if (glp_get_status(csa->prob) == GLP_OPT) { if (glp_bf_exists(csa->prob)) ranges: { ret = glp_print_ranges(csa->prob, 0, NULL, 0, csa->out_ranges); if (ret != 0) { xprintf("Unable to write sensitivity analysis repo" "rt\n"); ret = EXIT_FAILURE; goto done; } } else { ret = glp_factorize(csa->prob); if (ret == 0) goto ranges; xprintf("Cannot produce sensitivity analysis report d" "ue to error in basis factorization (glp_factorize" " returned %d); try --nopresol\n", ret); } } else xprintf("Cannot produce sensitivity analysis report for " "non-optimal basic solution\n"); } else xprintf("Cannot produce sensitivity analysis report for int" "erior-point or MIP solution\n"); } /*--------------------------------------------------------------*/ /* all seems to be ok */ ret = EXIT_SUCCESS; /*--------------------------------------------------------------*/ done: /* delete the LP/MIP problem object */ if (csa->prob != NULL) glp_delete_prob(csa->prob); /* free the translator workspace, if necessary */ if (csa->tran != NULL) glp_mpl_free_wksp(csa->tran); /* delete the network problem object, if necessary */ if (csa->graph != NULL) glp_delete_graph(csa->graph); xassert(gmp_pool_count() == 0); gmp_free_mem(); /* close log file, if necessary */ if (csa->log_file != NULL) glp_close_tee(); /* check that no memory blocks are still allocated */ { int count; glp_long total; glp_mem_usage(&count, NULL, &total, NULL); if (count != 0) xerror("Error: %d memory block(s) were lost\n", count); xassert(count == 0); xassert(total.lo == 0 && total.hi == 0); } /* free the GLPK environment */ glp_free_env(); /* return to the control program */ return ret; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpgmp.h0000644000076500000240000001431513524616144025042 0ustar tamasstaff00000000000000/* glpgmp.h (bignum arithmetic) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPGMP_H #define GLPGMP_H #ifdef HAVE_CONFIG_H #include #endif #ifdef HAVE_GMP /* use GNU MP bignum library */ #include #define gmp_pool_count _glp_gmp_pool_count #define gmp_free_mem _glp_gmp_free_mem int gmp_pool_count(void); void gmp_free_mem(void); #else /* use GLPK bignum module */ /*---------------------------------------------------------------------- // INTEGER NUMBERS // // Depending on its magnitude an integer number of arbitrary precision // is represented either in short format or in long format. // // Short format corresponds to the int type and allows representing // integer numbers in the range [-(2^31-1), +(2^31-1)]. Note that for // the most negative number of int type the short format is not used. // // In long format integer numbers are represented using the positional // system with the base (radix) 2^16 = 65536: // // x = (-1)^s sum{j in 0..n-1} d[j] * 65536^j, // // where x is the integer to be represented, s is its sign (+1 or -1), // d[j] are its digits (0 <= d[j] <= 65535). // // RATIONAL NUMBERS // // A rational number is represented as an irreducible fraction: // // p / q, // // where p (numerator) and q (denominator) are integer numbers (q > 0) // having no common divisors. */ struct mpz { /* integer number */ int val; /* if ptr is a null pointer, the number is in short format, and val is its value; otherwise, the number is in long format, and val is its sign (+1 or -1) */ struct mpz_seg *ptr; /* pointer to the linked list of the number segments ordered in ascending of powers of the base */ }; struct mpz_seg { /* integer number segment */ unsigned short d[6]; /* six digits of the number ordered in ascending of powers of the base */ struct mpz_seg *next; /* pointer to the next number segment */ }; struct mpq { /* rational number (p / q) */ struct mpz p; /* numerator */ struct mpz q; /* denominator */ }; typedef struct mpz *mpz_t; typedef struct mpq *mpq_t; #define gmp_get_atom _glp_gmp_get_atom #define gmp_free_atom _glp_gmp_free_atom #define gmp_pool_count _glp_gmp_pool_count #define gmp_get_work _glp_gmp_get_work #define gmp_free_mem _glp_gmp_free_mem #define _mpz_init _glp_mpz_init #define mpz_clear _glp_mpz_clear #define mpz_set _glp_mpz_set #define mpz_set_si _glp_mpz_set_si #define mpz_get_d _glp_mpz_get_d #define mpz_get_d_2exp _glp_mpz_get_d_2exp #define mpz_swap _glp_mpz_swap #define mpz_add _glp_mpz_add #define mpz_sub _glp_mpz_sub #define mpz_mul _glp_mpz_mul #define mpz_neg _glp_mpz_neg #define mpz_abs _glp_mpz_abs #define mpz_div _glp_mpz_div #define mpz_gcd _glp_mpz_gcd #define mpz_cmp _glp_mpz_cmp #define mpz_sgn _glp_mpz_sgn #define mpz_out_str _glp_mpz_out_str #define _mpq_init _glp_mpq_init #define mpq_clear _glp_mpq_clear #define mpq_canonicalize _glp_mpq_canonicalize #define mpq_set _glp_mpq_set #define mpq_set_si _glp_mpq_set_si #define mpq_get_d _glp_mpq_get_d #define mpq_set_d _glp_mpq_set_d #define mpq_add _glp_mpq_add #define mpq_sub _glp_mpq_sub #define mpq_mul _glp_mpq_mul #define mpq_div _glp_mpq_div #define mpq_neg _glp_mpq_neg #define mpq_abs _glp_mpq_abs #define mpq_cmp _glp_mpq_cmp #define mpq_sgn _glp_mpq_sgn #define mpq_out_str _glp_mpq_out_str void *gmp_get_atom(int size); void gmp_free_atom(void *ptr, int size); int gmp_pool_count(void); unsigned short *gmp_get_work(int size); void gmp_free_mem(void); mpz_t _mpz_init(void); #define mpz_init(x) (void)((x) = _mpz_init()) void mpz_clear(mpz_t x); void mpz_set(mpz_t z, mpz_t x); void mpz_set_si(mpz_t x, int val); double mpz_get_d(mpz_t x); double mpz_get_d_2exp(int *exp, mpz_t x); void mpz_swap(mpz_t x, mpz_t y); void mpz_add(mpz_t, mpz_t, mpz_t); void mpz_sub(mpz_t, mpz_t, mpz_t); void mpz_mul(mpz_t, mpz_t, mpz_t); void mpz_neg(mpz_t z, mpz_t x); void mpz_abs(mpz_t z, mpz_t x); void mpz_div(mpz_t q, mpz_t r, mpz_t x, mpz_t y); void mpz_gcd(mpz_t z, mpz_t x, mpz_t y); int mpz_cmp(mpz_t x, mpz_t y); int mpz_sgn(mpz_t x); int mpz_out_str(void *fp, int base, mpz_t x); mpq_t _mpq_init(void); #define mpq_init(x) (void)((x) = _mpq_init()) void mpq_clear(mpq_t x); void mpq_canonicalize(mpq_t x); void mpq_set(mpq_t z, mpq_t x); void mpq_set_si(mpq_t x, int p, unsigned int q); double mpq_get_d(mpq_t x); void mpq_set_d(mpq_t x, double val); void mpq_add(mpq_t z, mpq_t x, mpq_t y); void mpq_sub(mpq_t z, mpq_t x, mpq_t y); void mpq_mul(mpq_t z, mpq_t x, mpq_t y); void mpq_div(mpq_t z, mpq_t x, mpq_t y); void mpq_neg(mpq_t z, mpq_t x); void mpq_abs(mpq_t z, mpq_t x); int mpq_cmp(mpq_t x, mpq_t y); int mpq_sgn(mpq_t x); int mpq_out_str(void *fp, int base, mpq_t x); #endif #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpdmx.c0000644000076500000240000014314613524616144025047 0ustar tamasstaff00000000000000/* glpdmx.c (reading/writing data in DIMACS format) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wsign-conversion" #endif #define _GLPSTD_STDIO #include "glpapi.h" struct csa { /* common storage area */ jmp_buf jump; /* label for go to in case of error */ const char *fname; /* name of input text file */ XFILE *fp; /* stream assigned to input text file */ int count; /* line count */ int c; /* current character */ char field[255+1]; /* data field */ int empty; /* warning 'empty line ignored' was printed */ int nonint; /* warning 'non-integer data detected' was printed */ }; static void error(struct csa *csa, const char *fmt, ...) { /* print error message and terminate processing */ va_list arg; xprintf("%s:%d: error: ", csa->fname, csa->count); va_start(arg, fmt); xvprintf(fmt, arg); va_end(arg); xprintf("\n"); longjmp(csa->jump, 1); /* no return */ } static void warning(struct csa *csa, const char *fmt, ...) { /* print warning message and continue processing */ va_list arg; xprintf("%s:%d: warning: ", csa->fname, csa->count); va_start(arg, fmt); xvprintf(fmt, arg); va_end(arg); xprintf("\n"); return; } static void read_char(struct csa *csa) { /* read character from input text file */ int c; if (csa->c == '\n') csa->count++; c = xfgetc(csa->fp); if (c < 0) { if (xferror(csa->fp)) error(csa, "read error - %s", xerrmsg()); else if (csa->c == '\n') error(csa, "unexpected end of file"); else { warning(csa, "missing final end of line"); c = '\n'; } } else if (c == '\n') ; else if (isspace(c)) c = ' '; else if (iscntrl(c)) error(csa, "invalid control character 0x%02X", c); csa->c = c; return; } static void read_designator(struct csa *csa) { /* read one-character line designator */ xassert(csa->c == '\n'); read_char(csa); for (;;) { /* skip preceding white-space characters */ while (csa->c == ' ') read_char(csa); if (csa->c == '\n') { /* ignore empty line */ if (!csa->empty) { warning(csa, "empty line ignored"); csa->empty = 1; } read_char(csa); } else if (csa->c == 'c') { /* skip comment line */ while (csa->c != '\n') read_char(csa); read_char(csa); } else { /* hmm... looks like a line designator */ csa->field[0] = (char)csa->c, csa->field[1] = '\0'; /* check that it is followed by a white-space character */ read_char(csa); if (!(csa->c == ' ' || csa->c == '\n')) error(csa, "line designator missing or invalid"); break; } } return; } static void read_field(struct csa *csa) { /* read data field */ int len = 0; /* skip preceding white-space characters */ while (csa->c == ' ') read_char(csa); /* scan data field */ if (csa->c == '\n') error(csa, "unexpected end of line"); while (!(csa->c == ' ' || csa->c == '\n')) { if (len == sizeof(csa->field)-1) error(csa, "data field `%.15s...' too long", csa->field); csa->field[len++] = (char)csa->c; read_char(csa); } csa->field[len] = '\0'; return; } static void end_of_line(struct csa *csa) { /* skip white-space characters until end of line */ while (csa->c == ' ') read_char(csa); if (csa->c != '\n') error(csa, "too many data fields specified"); return; } static void check_int(struct csa *csa, double num) { /* print a warning if non-integer data are detected */ if (!csa->nonint && num != floor(num)) { warning(csa, "non-integer data detected"); csa->nonint = 1; } return; } /*********************************************************************** * NAME * * glp_read_mincost - read min-cost flow problem data in DIMACS format * * SYNOPSIS * * int glp_read_mincost(glp_graph *G, int v_rhs, int a_low, int a_cap, * int a_cost, const char *fname); * * DESCRIPTION * * The routine glp_read_mincost reads minimum cost flow problem data in * DIMACS format from a text file. * * RETURNS * * If the operation was successful, the routine returns zero. Otherwise * it prints an error message and returns non-zero. */ int glp_read_mincost(glp_graph *G, int v_rhs, int a_low, int a_cap, int a_cost, const char *fname) { struct csa _csa, *csa = &_csa; glp_vertex *v; glp_arc *a; int i, j, k, nv, na, ret = 0; double rhs, low, cap, cost; char *flag = NULL; if (v_rhs >= 0 && v_rhs > G->v_size - (int)sizeof(double)) xerror("glp_read_mincost: v_rhs = %d; invalid offset\n", v_rhs); if (a_low >= 0 && a_low > G->a_size - (int)sizeof(double)) xerror("glp_read_mincost: a_low = %d; invalid offset\n", a_low); if (a_cap >= 0 && a_cap > G->a_size - (int)sizeof(double)) xerror("glp_read_mincost: a_cap = %d; invalid offset\n", a_cap); if (a_cost >= 0 && a_cost > G->a_size - (int)sizeof(double)) xerror("glp_read_mincost: a_cost = %d; invalid offset\n", a_cost); glp_erase_graph(G, G->v_size, G->a_size); if (setjmp(csa->jump)) { ret = 1; goto done; } csa->fname = fname; csa->fp = NULL; csa->count = 0; csa->c = '\n'; csa->field[0] = '\0'; csa->empty = csa->nonint = 0; xprintf("Reading min-cost flow problem data from `%s'...\n", fname); csa->fp = xfopen(fname, "r"); if (csa->fp == NULL) { xprintf("Unable to open `%s' - %s\n", fname, xerrmsg()); longjmp(csa->jump, 1); } /* read problem line */ read_designator(csa); if (strcmp(csa->field, "p") != 0) error(csa, "problem line missing or invalid"); read_field(csa); if (strcmp(csa->field, "min") != 0) error(csa, "wrong problem designator; `min' expected"); read_field(csa); if (!(str2int(csa->field, &nv) == 0 && nv >= 0)) error(csa, "number of nodes missing or invalid"); read_field(csa); if (!(str2int(csa->field, &na) == 0 && na >= 0)) error(csa, "number of arcs missing or invalid"); xprintf("Flow network has %d node%s and %d arc%s\n", nv, nv == 1 ? "" : "s", na, na == 1 ? "" : "s"); if (nv > 0) glp_add_vertices(G, nv); end_of_line(csa); /* read node descriptor lines */ flag = xcalloc(1+nv, sizeof(char)); memset(&flag[1], 0, nv * sizeof(char)); if (v_rhs >= 0) { rhs = 0.0; for (i = 1; i <= nv; i++) { v = G->v[i]; memcpy((char *)v->data + v_rhs, &rhs, sizeof(double)); } } for (;;) { read_designator(csa); if (strcmp(csa->field, "n") != 0) break; read_field(csa); if (str2int(csa->field, &i) != 0) error(csa, "node number missing or invalid"); if (!(1 <= i && i <= nv)) error(csa, "node number %d out of range", i); if (flag[i]) error(csa, "duplicate descriptor of node %d", i); read_field(csa); if (str2num(csa->field, &rhs) != 0) error(csa, "node supply/demand missing or invalid"); check_int(csa, rhs); if (v_rhs >= 0) { v = G->v[i]; memcpy((char *)v->data + v_rhs, &rhs, sizeof(double)); } flag[i] = 1; end_of_line(csa); } xfree(flag), flag = NULL; /* read arc descriptor lines */ for (k = 1; k <= na; k++) { if (k > 1) read_designator(csa); if (strcmp(csa->field, "a") != 0) error(csa, "wrong line designator; `a' expected"); read_field(csa); if (str2int(csa->field, &i) != 0) error(csa, "starting node number missing or invalid"); if (!(1 <= i && i <= nv)) error(csa, "starting node number %d out of range", i); read_field(csa); if (str2int(csa->field, &j) != 0) error(csa, "ending node number missing or invalid"); if (!(1 <= j && j <= nv)) error(csa, "ending node number %d out of range", j); read_field(csa); if (!(str2num(csa->field, &low) == 0 && low >= 0.0)) error(csa, "lower bound of arc flow missing or invalid"); check_int(csa, low); read_field(csa); if (!(str2num(csa->field, &cap) == 0 && cap >= low)) error(csa, "upper bound of arc flow missing or invalid"); check_int(csa, cap); read_field(csa); if (str2num(csa->field, &cost) != 0) error(csa, "per-unit cost of arc flow missing or invalid"); check_int(csa, cost); a = glp_add_arc(G, i, j); if (a_low >= 0) memcpy((char *)a->data + a_low, &low, sizeof(double)); if (a_cap >= 0) memcpy((char *)a->data + a_cap, &cap, sizeof(double)); if (a_cost >= 0) memcpy((char *)a->data + a_cost, &cost, sizeof(double)); end_of_line(csa); } xprintf("%d lines were read\n", csa->count); done: if (ret) glp_erase_graph(G, G->v_size, G->a_size); if (csa->fp != NULL) xfclose(csa->fp); if (flag != NULL) xfree(flag); return ret; } /*********************************************************************** * NAME * * glp_write_mincost - write min-cost flow problem data in DIMACS format * * SYNOPSIS * * int glp_write_mincost(glp_graph *G, int v_rhs, int a_low, int a_cap, * int a_cost, const char *fname); * * DESCRIPTION * * The routine glp_write_mincost writes minimum cost flow problem data * in DIMACS format to a text file. * * RETURNS * * If the operation was successful, the routine returns zero. Otherwise * it prints an error message and returns non-zero. */ int glp_write_mincost(glp_graph *G, int v_rhs, int a_low, int a_cap, int a_cost, const char *fname) { XFILE *fp; glp_vertex *v; glp_arc *a; int i, count = 0, ret; double rhs, low, cap, cost; if (v_rhs >= 0 && v_rhs > G->v_size - (int)sizeof(double)) xerror("glp_write_mincost: v_rhs = %d; invalid offset\n", v_rhs); if (a_low >= 0 && a_low > G->a_size - (int)sizeof(double)) xerror("glp_write_mincost: a_low = %d; invalid offset\n", a_low); if (a_cap >= 0 && a_cap > G->a_size - (int)sizeof(double)) xerror("glp_write_mincost: a_cap = %d; invalid offset\n", a_cap); if (a_cost >= 0 && a_cost > G->a_size - (int)sizeof(double)) xerror("glp_write_mincost: a_cost = %d; invalid offset\n", a_cost); xprintf("Writing min-cost flow problem data to `%s'...\n", fname); fp = xfopen(fname, "w"); if (fp == NULL) { xprintf("Unable to create `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } xfprintf(fp, "c %s\n", G->name == NULL ? "unknown" : G->name), count++; xfprintf(fp, "p min %d %d\n", G->nv, G->na), count++; if (v_rhs >= 0) { for (i = 1; i <= G->nv; i++) { v = G->v[i]; memcpy(&rhs, (char *)v->data + v_rhs, sizeof(double)); if (rhs != 0.0) xfprintf(fp, "n %d %.*g\n", i, DBL_DIG, rhs), count++; } } for (i = 1; i <= G->nv; i++) { v = G->v[i]; for (a = v->out; a != NULL; a = a->t_next) { if (a_low >= 0) memcpy(&low, (char *)a->data + a_low, sizeof(double)); else low = 0.0; if (a_cap >= 0) memcpy(&cap, (char *)a->data + a_cap, sizeof(double)); else cap = 1.0; if (a_cost >= 0) memcpy(&cost, (char *)a->data + a_cost, sizeof(double)); else cost = 0.0; xfprintf(fp, "a %d %d %.*g %.*g %.*g\n", a->tail->i, a->head->i, DBL_DIG, low, DBL_DIG, cap, DBL_DIG, cost), count++; } } xfprintf(fp, "c eof\n"), count++; xfflush(fp); if (xferror(fp)) { xprintf("Write error on `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } xprintf("%d lines were written\n", count); ret = 0; done: if (fp != NULL) xfclose(fp); return ret; } /*********************************************************************** * NAME * * glp_read_maxflow - read maximum flow problem data in DIMACS format * * SYNOPSIS * * int glp_read_maxflow(glp_graph *G, int *s, int *t, int a_cap, * const char *fname); * * DESCRIPTION * * The routine glp_read_maxflow reads maximum flow problem data in * DIMACS format from a text file. * * RETURNS * * If the operation was successful, the routine returns zero. Otherwise * it prints an error message and returns non-zero. */ int glp_read_maxflow(glp_graph *G, int *_s, int *_t, int a_cap, const char *fname) { struct csa _csa, *csa = &_csa; glp_arc *a; int i, j, k, s, t, nv, na, ret = 0; double cap; if (a_cap >= 0 && a_cap > G->a_size - (int)sizeof(double)) xerror("glp_read_maxflow: a_cap = %d; invalid offset\n", a_cap); glp_erase_graph(G, G->v_size, G->a_size); if (setjmp(csa->jump)) { ret = 1; goto done; } csa->fname = fname; csa->fp = NULL; csa->count = 0; csa->c = '\n'; csa->field[0] = '\0'; csa->empty = csa->nonint = 0; xprintf("Reading maximum flow problem data from `%s'...\n", fname); csa->fp = xfopen(fname, "r"); if (csa->fp == NULL) { xprintf("Unable to open `%s' - %s\n", fname, xerrmsg()); longjmp(csa->jump, 1); } /* read problem line */ read_designator(csa); if (strcmp(csa->field, "p") != 0) error(csa, "problem line missing or invalid"); read_field(csa); if (strcmp(csa->field, "max") != 0) error(csa, "wrong problem designator; `max' expected"); read_field(csa); if (!(str2int(csa->field, &nv) == 0 && nv >= 2)) error(csa, "number of nodes missing or invalid"); read_field(csa); if (!(str2int(csa->field, &na) == 0 && na >= 0)) error(csa, "number of arcs missing or invalid"); xprintf("Flow network has %d node%s and %d arc%s\n", nv, nv == 1 ? "" : "s", na, na == 1 ? "" : "s"); if (nv > 0) glp_add_vertices(G, nv); end_of_line(csa); /* read node descriptor lines */ s = t = 0; for (;;) { read_designator(csa); if (strcmp(csa->field, "n") != 0) break; read_field(csa); if (str2int(csa->field, &i) != 0) error(csa, "node number missing or invalid"); if (!(1 <= i && i <= nv)) error(csa, "node number %d out of range", i); read_field(csa); if (strcmp(csa->field, "s") == 0) { if (s > 0) error(csa, "only one source node allowed"); s = i; } else if (strcmp(csa->field, "t") == 0) { if (t > 0) error(csa, "only one sink node allowed"); t = i; } else error(csa, "wrong node designator; `s' or `t' expected"); if (s > 0 && s == t) error(csa, "source and sink nodes must be distinct"); end_of_line(csa); } if (s == 0) error(csa, "source node descriptor missing\n"); if (t == 0) error(csa, "sink node descriptor missing\n"); if (_s != NULL) *_s = s; if (_t != NULL) *_t = t; /* read arc descriptor lines */ for (k = 1; k <= na; k++) { if (k > 1) read_designator(csa); if (strcmp(csa->field, "a") != 0) error(csa, "wrong line designator; `a' expected"); read_field(csa); if (str2int(csa->field, &i) != 0) error(csa, "starting node number missing or invalid"); if (!(1 <= i && i <= nv)) error(csa, "starting node number %d out of range", i); read_field(csa); if (str2int(csa->field, &j) != 0) error(csa, "ending node number missing or invalid"); if (!(1 <= j && j <= nv)) error(csa, "ending node number %d out of range", j); read_field(csa); if (!(str2num(csa->field, &cap) == 0 && cap >= 0.0)) error(csa, "arc capacity missing or invalid"); check_int(csa, cap); a = glp_add_arc(G, i, j); if (a_cap >= 0) memcpy((char *)a->data + a_cap, &cap, sizeof(double)); end_of_line(csa); } xprintf("%d lines were read\n", csa->count); done: if (ret) glp_erase_graph(G, G->v_size, G->a_size); if (csa->fp != NULL) xfclose(csa->fp); return ret; } /*********************************************************************** * NAME * * glp_write_maxflow - write maximum flow problem data in DIMACS format * * SYNOPSIS * * int glp_write_maxflow(glp_graph *G, int s, int t, int a_cap, * const char *fname); * * DESCRIPTION * * The routine glp_write_maxflow writes maximum flow problem data in * DIMACS format to a text file. * * RETURNS * * If the operation was successful, the routine returns zero. Otherwise * it prints an error message and returns non-zero. */ int glp_write_maxflow(glp_graph *G, int s, int t, int a_cap, const char *fname) { XFILE *fp; glp_vertex *v; glp_arc *a; int i, count = 0, ret; double cap; if (!(1 <= s && s <= G->nv)) xerror("glp_write_maxflow: s = %d; source node number out of r" "ange\n", s); if (!(1 <= t && t <= G->nv)) xerror("glp_write_maxflow: t = %d: sink node number out of ran" "ge\n", t); if (a_cap >= 0 && a_cap > G->a_size - (int)sizeof(double)) xerror("glp_write_mincost: a_cap = %d; invalid offset\n", a_cap); xprintf("Writing maximum flow problem data to `%s'...\n", fname); fp = xfopen(fname, "w"); if (fp == NULL) { xprintf("Unable to create `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } xfprintf(fp, "c %s\n", G->name == NULL ? "unknown" : G->name), count++; xfprintf(fp, "p max %d %d\n", G->nv, G->na), count++; xfprintf(fp, "n %d s\n", s), count++; xfprintf(fp, "n %d t\n", t), count++; for (i = 1; i <= G->nv; i++) { v = G->v[i]; for (a = v->out; a != NULL; a = a->t_next) { if (a_cap >= 0) memcpy(&cap, (char *)a->data + a_cap, sizeof(double)); else cap = 1.0; xfprintf(fp, "a %d %d %.*g\n", a->tail->i, a->head->i, DBL_DIG, cap), count++; } } xfprintf(fp, "c eof\n"), count++; xfflush(fp); if (xferror(fp)) { xprintf("Write error on `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } xprintf("%d lines were written\n", count); ret = 0; done: if (fp != NULL) xfclose(fp); return ret; } /*********************************************************************** * NAME * * glp_read_asnprob - read assignment problem data in DIMACS format * * SYNOPSIS * * int glp_read_asnprob(glp_graph *G, int v_set, int a_cost, * const char *fname); * * DESCRIPTION * * The routine glp_read_asnprob reads assignment problem data in DIMACS * format from a text file. * * RETURNS * * If the operation was successful, the routine returns zero. Otherwise * it prints an error message and returns non-zero. */ int glp_read_asnprob(glp_graph *G, int v_set, int a_cost, const char *fname) { struct csa _csa, *csa = &_csa; glp_vertex *v; glp_arc *a; int nv, na, n1, i, j, k, ret = 0; double cost; char *flag = NULL; if (v_set >= 0 && v_set > G->v_size - (int)sizeof(int)) xerror("glp_read_asnprob: v_set = %d; invalid offset\n", v_set); if (a_cost >= 0 && a_cost > G->a_size - (int)sizeof(double)) xerror("glp_read_asnprob: a_cost = %d; invalid offset\n", a_cost); glp_erase_graph(G, G->v_size, G->a_size); if (setjmp(csa->jump)) { ret = 1; goto done; } csa->fname = fname; csa->fp = NULL; csa->count = 0; csa->c = '\n'; csa->field[0] = '\0'; csa->empty = csa->nonint = 0; xprintf("Reading assignment problem data from `%s'...\n", fname); csa->fp = xfopen(fname, "r"); if (csa->fp == NULL) { xprintf("Unable to open `%s' - %s\n", fname, xerrmsg()); longjmp(csa->jump, 1); } /* read problem line */ read_designator(csa); if (strcmp(csa->field, "p") != 0) error(csa, "problem line missing or invalid"); read_field(csa); if (strcmp(csa->field, "asn") != 0) error(csa, "wrong problem designator; `asn' expected"); read_field(csa); if (!(str2int(csa->field, &nv) == 0 && nv >= 0)) error(csa, "number of nodes missing or invalid"); read_field(csa); if (!(str2int(csa->field, &na) == 0 && na >= 0)) error(csa, "number of arcs missing or invalid"); if (nv > 0) glp_add_vertices(G, nv); end_of_line(csa); /* read node descriptor lines */ flag = xcalloc(1+nv, sizeof(char)); memset(&flag[1], 0, nv * sizeof(char)); n1 = 0; for (;;) { read_designator(csa); if (strcmp(csa->field, "n") != 0) break; read_field(csa); if (str2int(csa->field, &i) != 0) error(csa, "node number missing or invalid"); if (!(1 <= i && i <= nv)) error(csa, "node number %d out of range", i); if (flag[i]) error(csa, "duplicate descriptor of node %d", i); flag[i] = 1, n1++; end_of_line(csa); } xprintf( "Assignment problem has %d + %d = %d node%s and %d arc%s\n", n1, nv - n1, nv, nv == 1 ? "" : "s", na, na == 1 ? "" : "s"); if (v_set >= 0) { for (i = 1; i <= nv; i++) { v = G->v[i]; k = (flag[i] ? 0 : 1); memcpy((char *)v->data + v_set, &k, sizeof(int)); } } /* read arc descriptor lines */ for (k = 1; k <= na; k++) { if (k > 1) read_designator(csa); if (strcmp(csa->field, "a") != 0) error(csa, "wrong line designator; `a' expected"); read_field(csa); if (str2int(csa->field, &i) != 0) error(csa, "starting node number missing or invalid"); if (!(1 <= i && i <= nv)) error(csa, "starting node number %d out of range", i); if (!flag[i]) error(csa, "node %d cannot be a starting node", i); read_field(csa); if (str2int(csa->field, &j) != 0) error(csa, "ending node number missing or invalid"); if (!(1 <= j && j <= nv)) error(csa, "ending node number %d out of range", j); if (flag[j]) error(csa, "node %d cannot be an ending node", j); read_field(csa); if (str2num(csa->field, &cost) != 0) error(csa, "arc cost missing or invalid"); check_int(csa, cost); a = glp_add_arc(G, i, j); if (a_cost >= 0) memcpy((char *)a->data + a_cost, &cost, sizeof(double)); end_of_line(csa); } xprintf("%d lines were read\n", csa->count); done: if (ret) glp_erase_graph(G, G->v_size, G->a_size); if (csa->fp != NULL) xfclose(csa->fp); if (flag != NULL) xfree(flag); return ret; } /*********************************************************************** * NAME * * glp_write_asnprob - write assignment problem data in DIMACS format * * SYNOPSIS * * int glp_write_asnprob(glp_graph *G, int v_set, int a_cost, * const char *fname); * * DESCRIPTION * * The routine glp_write_asnprob writes assignment problem data in * DIMACS format to a text file. * * RETURNS * * If the operation was successful, the routine returns zero. Otherwise * it prints an error message and returns non-zero. */ int glp_write_asnprob(glp_graph *G, int v_set, int a_cost, const char *fname) { XFILE *fp; glp_vertex *v; glp_arc *a; int i, k, count = 0, ret; double cost; if (v_set >= 0 && v_set > G->v_size - (int)sizeof(int)) xerror("glp_write_asnprob: v_set = %d; invalid offset\n", v_set); if (a_cost >= 0 && a_cost > G->a_size - (int)sizeof(double)) xerror("glp_write_asnprob: a_cost = %d; invalid offset\n", a_cost); xprintf("Writing assignment problem data to `%s'...\n", fname); fp = xfopen(fname, "w"); if (fp == NULL) { xprintf("Unable to create `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } xfprintf(fp, "c %s\n", G->name == NULL ? "unknown" : G->name), count++; xfprintf(fp, "p asn %d %d\n", G->nv, G->na), count++; for (i = 1; i <= G->nv; i++) { v = G->v[i]; if (v_set >= 0) memcpy(&k, (char *)v->data + v_set, sizeof(int)); else k = (v->out != NULL ? 0 : 1); if (k == 0) xfprintf(fp, "n %d\n", i), count++; } for (i = 1; i <= G->nv; i++) { v = G->v[i]; for (a = v->out; a != NULL; a = a->t_next) { if (a_cost >= 0) memcpy(&cost, (char *)a->data + a_cost, sizeof(double)); else cost = 1.0; xfprintf(fp, "a %d %d %.*g\n", a->tail->i, a->head->i, DBL_DIG, cost), count++; } } xfprintf(fp, "c eof\n"), count++; xfflush(fp); if (xferror(fp)) { xprintf("Write error on `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } xprintf("%d lines were written\n", count); ret = 0; done: if (fp != NULL) xfclose(fp); return ret; } /*********************************************************************** * NAME * * glp_read_ccdata - read graph in DIMACS clique/coloring format * * SYNOPSIS * * int glp_read_ccdata(glp_graph *G, int v_wgt, const char *fname); * * DESCRIPTION * * The routine glp_read_ccdata reads an (undirected) graph in DIMACS * clique/coloring format from a text file. * * RETURNS * * If the operation was successful, the routine returns zero. Otherwise * it prints an error message and returns non-zero. */ int glp_read_ccdata(glp_graph *G, int v_wgt, const char *fname) { struct csa _csa, *csa = &_csa; glp_vertex *v; int i, j, k, nv, ne, ret = 0; double w; char *flag = NULL; if (v_wgt >= 0 && v_wgt > G->v_size - (int)sizeof(double)) xerror("glp_read_ccdata: v_wgt = %d; invalid offset\n", v_wgt); glp_erase_graph(G, G->v_size, G->a_size); if (setjmp(csa->jump)) { ret = 1; goto done; } csa->fname = fname; csa->fp = NULL; csa->count = 0; csa->c = '\n'; csa->field[0] = '\0'; csa->empty = csa->nonint = 0; xprintf("Reading graph from `%s'...\n", fname); csa->fp = xfopen(fname, "r"); if (csa->fp == NULL) { xprintf("Unable to open `%s' - %s\n", fname, xerrmsg()); longjmp(csa->jump, 1); } /* read problem line */ read_designator(csa); if (strcmp(csa->field, "p") != 0) error(csa, "problem line missing or invalid"); read_field(csa); if (strcmp(csa->field, "edge") != 0) error(csa, "wrong problem designator; `edge' expected"); read_field(csa); if (!(str2int(csa->field, &nv) == 0 && nv >= 0)) error(csa, "number of vertices missing or invalid"); read_field(csa); if (!(str2int(csa->field, &ne) == 0 && ne >= 0)) error(csa, "number of edges missing or invalid"); xprintf("Graph has %d vert%s and %d edge%s\n", nv, nv == 1 ? "ex" : "ices", ne, ne == 1 ? "" : "s"); if (nv > 0) glp_add_vertices(G, nv); end_of_line(csa); /* read node descriptor lines */ flag = xcalloc(1+nv, sizeof(char)); memset(&flag[1], 0, nv * sizeof(char)); if (v_wgt >= 0) { w = 1.0; for (i = 1; i <= nv; i++) { v = G->v[i]; memcpy((char *)v->data + v_wgt, &w, sizeof(double)); } } for (;;) { read_designator(csa); if (strcmp(csa->field, "n") != 0) break; read_field(csa); if (str2int(csa->field, &i) != 0) error(csa, "vertex number missing or invalid"); if (!(1 <= i && i <= nv)) error(csa, "vertex number %d out of range", i); if (flag[i]) error(csa, "duplicate descriptor of vertex %d", i); read_field(csa); if (str2num(csa->field, &w) != 0) error(csa, "vertex weight missing or invalid"); check_int(csa, w); if (v_wgt >= 0) { v = G->v[i]; memcpy((char *)v->data + v_wgt, &w, sizeof(double)); } flag[i] = 1; end_of_line(csa); } xfree(flag), flag = NULL; /* read edge descriptor lines */ for (k = 1; k <= ne; k++) { if (k > 1) read_designator(csa); if (strcmp(csa->field, "e") != 0) error(csa, "wrong line designator; `e' expected"); read_field(csa); if (str2int(csa->field, &i) != 0) error(csa, "first vertex number missing or invalid"); if (!(1 <= i && i <= nv)) error(csa, "first vertex number %d out of range", i); read_field(csa); if (str2int(csa->field, &j) != 0) error(csa, "second vertex number missing or invalid"); if (!(1 <= j && j <= nv)) error(csa, "second vertex number %d out of range", j); glp_add_arc(G, i, j); end_of_line(csa); } xprintf("%d lines were read\n", csa->count); done: if (ret) glp_erase_graph(G, G->v_size, G->a_size); if (csa->fp != NULL) xfclose(csa->fp); if (flag != NULL) xfree(flag); return ret; } /*********************************************************************** * NAME * * glp_write_ccdata - write graph in DIMACS clique/coloring format * * SYNOPSIS * * int glp_write_ccdata(glp_graph *G, int v_wgt, const char *fname); * * DESCRIPTION * * The routine glp_write_ccdata writes the specified graph in DIMACS * clique/coloring format to a text file. * * RETURNS * * If the operation was successful, the routine returns zero. Otherwise * it prints an error message and returns non-zero. */ int glp_write_ccdata(glp_graph *G, int v_wgt, const char *fname) { XFILE *fp; glp_vertex *v; glp_arc *e; int i, count = 0, ret; double w; if (v_wgt >= 0 && v_wgt > G->v_size - (int)sizeof(double)) xerror("glp_write_ccdata: v_wgt = %d; invalid offset\n", v_wgt); xprintf("Writing graph to `%s'\n", fname); fp = xfopen(fname, "w"); if (fp == NULL) { xprintf("Unable to create `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } xfprintf(fp, "c %s\n", G->name == NULL ? "unknown" : G->name), count++; xfprintf(fp, "p edge %d %d\n", G->nv, G->na), count++; if (v_wgt >= 0) { for (i = 1; i <= G->nv; i++) { v = G->v[i]; memcpy(&w, (char *)v->data + v_wgt, sizeof(double)); if (w != 1.0) xfprintf(fp, "n %d %.*g\n", i, DBL_DIG, w), count++; } } for (i = 1; i <= G->nv; i++) { v = G->v[i]; for (e = v->out; e != NULL; e = e->t_next) xfprintf(fp, "e %d %d\n", e->tail->i, e->head->i), count++; } xfprintf(fp, "c eof\n"), count++; xfflush(fp); if (xferror(fp)) { xprintf("Write error on `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } xprintf("%d lines were written\n", count); ret = 0; done: if (fp != NULL) xfclose(fp); return ret; } /*********************************************************************** * NAME * * glp_read_prob - read problem data in GLPK format * * SYNOPSIS * * int glp_read_prob(glp_prob *P, int flags, const char *fname); * * The routine glp_read_prob reads problem data in GLPK LP/MIP format * from a text file. * * RETURNS * * If the operation was successful, the routine returns zero. Otherwise * it prints an error message and returns non-zero. */ int glp_read_prob(glp_prob *P, int flags, const char *fname) { struct csa _csa, *csa = &_csa; int mip, m, n, nnz, ne, i, j, k, type, kind, ret, *ln = NULL, *ia = NULL, *ja = NULL; double lb, ub, temp, *ar = NULL; char *rf = NULL, *cf = NULL; if (P == NULL || P->magic != GLP_PROB_MAGIC) xerror("glp_read_prob: P = %p; invalid problem object\n", P); if (flags != 0) xerror("glp_read_prob: flags = %d; invalid parameter\n", flags); if (fname == NULL) xerror("glp_read_prob: fname = %d; invalid parameter\n", fname); glp_erase_prob(P); if (setjmp(csa->jump)) { ret = 1; goto done; } csa->fname = fname; csa->fp = NULL; csa->count = 0; csa->c = '\n'; csa->field[0] = '\0'; csa->empty = csa->nonint = 0; xprintf("Reading problem data from `%s'...\n", fname); csa->fp = xfopen(fname, "r"); if (csa->fp == NULL) { xprintf("Unable to open `%s' - %s\n", fname, xerrmsg()); longjmp(csa->jump, 1); } /* read problem line */ read_designator(csa); if (strcmp(csa->field, "p") != 0) error(csa, "problem line missing or invalid"); read_field(csa); if (strcmp(csa->field, "lp") == 0) mip = 0; else if (strcmp(csa->field, "mip") == 0) mip = 1; else error(csa, "wrong problem designator; `lp' or `mip' expected\n" ); read_field(csa); if (strcmp(csa->field, "min") == 0) glp_set_obj_dir(P, GLP_MIN); else if (strcmp(csa->field, "max") == 0) glp_set_obj_dir(P, GLP_MAX); else error(csa, "objective sense missing or invalid"); read_field(csa); if (!(str2int(csa->field, &m) == 0 && m >= 0)) error(csa, "number of rows missing or invalid"); read_field(csa); if (!(str2int(csa->field, &n) == 0 && n >= 0)) error(csa, "number of columns missing or invalid"); read_field(csa); if (!(str2int(csa->field, &nnz) == 0 && nnz >= 0)) error(csa, "number of constraint coefficients missing or inval" "id"); if (m > 0) { glp_add_rows(P, m); for (i = 1; i <= m; i++) glp_set_row_bnds(P, i, GLP_FX, 0.0, 0.0); } if (n > 0) { glp_add_cols(P, n); for (j = 1; j <= n; j++) { if (!mip) glp_set_col_bnds(P, j, GLP_LO, 0.0, 0.0); else glp_set_col_kind(P, j, GLP_BV); } } end_of_line(csa); /* allocate working arrays */ rf = xcalloc(1+m, sizeof(char)); memset(rf, 0, 1+m); cf = xcalloc(1+n, sizeof(char)); memset(cf, 0, 1+n); ln = xcalloc(1+nnz, sizeof(int)); ia = xcalloc(1+nnz, sizeof(int)); ja = xcalloc(1+nnz, sizeof(int)); ar = xcalloc(1+nnz, sizeof(double)); /* read descriptor lines */ ne = 0; for (;;) { read_designator(csa); if (strcmp(csa->field, "i") == 0) { /* row descriptor */ read_field(csa); if (str2int(csa->field, &i) != 0) error(csa, "row number missing or invalid"); if (!(1 <= i && i <= m)) error(csa, "row number out of range"); read_field(csa); if (strcmp(csa->field, "f") == 0) type = GLP_FR; else if (strcmp(csa->field, "l") == 0) type = GLP_LO; else if (strcmp(csa->field, "u") == 0) type = GLP_UP; else if (strcmp(csa->field, "d") == 0) type = GLP_DB; else if (strcmp(csa->field, "s") == 0) type = GLP_FX; else error(csa, "row type missing or invalid"); if (type == GLP_LO || type == GLP_DB || type == GLP_FX) { read_field(csa); if (str2num(csa->field, &lb) != 0) error(csa, "row lower bound/fixed value missing or in" "valid"); } else lb = 0.0; if (type == GLP_UP || type == GLP_DB) { read_field(csa); if (str2num(csa->field, &ub) != 0) error(csa, "row upper bound missing or invalid"); } else ub = 0.0; if (rf[i] & 0x01) error(csa, "duplicate row descriptor"); glp_set_row_bnds(P, i, type, lb, ub), rf[i] |= 0x01; } else if (strcmp(csa->field, "j") == 0) { /* column descriptor */ read_field(csa); if (str2int(csa->field, &j) != 0) error(csa, "column number missing or invalid"); if (!(1 <= j && j <= n)) error(csa, "column number out of range"); if (!mip) kind = GLP_CV; else { read_field(csa); if (strcmp(csa->field, "c") == 0) kind = GLP_CV; else if (strcmp(csa->field, "i") == 0) kind = GLP_IV; else if (strcmp(csa->field, "b") == 0) { kind = GLP_IV; type = GLP_DB, lb = 0.0, ub = 1.0; goto skip; } else error(csa, "column kind missing or invalid"); } read_field(csa); if (strcmp(csa->field, "f") == 0) type = GLP_FR; else if (strcmp(csa->field, "l") == 0) type = GLP_LO; else if (strcmp(csa->field, "u") == 0) type = GLP_UP; else if (strcmp(csa->field, "d") == 0) type = GLP_DB; else if (strcmp(csa->field, "s") == 0) type = GLP_FX; else error(csa, "column type missing or invalid"); if (type == GLP_LO || type == GLP_DB || type == GLP_FX) { read_field(csa); if (str2num(csa->field, &lb) != 0) error(csa, "column lower bound/fixed value missing or" " invalid"); } else lb = 0.0; if (type == GLP_UP || type == GLP_DB) { read_field(csa); if (str2num(csa->field, &ub) != 0) error(csa, "column upper bound missing or invalid"); } else ub = 0.0; skip: if (cf[j] & 0x01) error(csa, "duplicate column descriptor"); glp_set_col_kind(P, j, kind); glp_set_col_bnds(P, j, type, lb, ub), cf[j] |= 0x01; } else if (strcmp(csa->field, "a") == 0) { /* coefficient descriptor */ read_field(csa); if (str2int(csa->field, &i) != 0) error(csa, "row number missing or invalid"); if (!(0 <= i && i <= m)) error(csa, "row number out of range"); read_field(csa); if (str2int(csa->field, &j) != 0) error(csa, "column number missing or invalid"); if (!((i == 0 ? 0 : 1) <= j && j <= n)) error(csa, "column number out of range"); read_field(csa); if (i == 0) { if (str2num(csa->field, &temp) != 0) error(csa, "objective %s missing or invalid", j == 0 ? "constant term" : "coefficient"); if (cf[j] & 0x10) error(csa, "duplicate objective %s", j == 0 ? "constant term" : "coefficient"); glp_set_obj_coef(P, j, temp), cf[j] |= 0x10; } else { if (str2num(csa->field, &temp) != 0) error(csa, "constraint coefficient missing or invalid" ); if (ne == nnz) error(csa, "too many constraint coefficient descripto" "rs"); ln[++ne] = csa->count; ia[ne] = i, ja[ne] = j, ar[ne] = temp; } } else if (strcmp(csa->field, "n") == 0) { /* symbolic name descriptor */ read_field(csa); if (strcmp(csa->field, "p") == 0) { /* problem name */ read_field(csa); if (P->name != NULL) error(csa, "duplicate problem name"); glp_set_prob_name(P, csa->field); } else if (strcmp(csa->field, "z") == 0) { /* objective name */ read_field(csa); if (P->obj != NULL) error(csa, "duplicate objective name"); glp_set_obj_name(P, csa->field); } else if (strcmp(csa->field, "i") == 0) { /* row name */ read_field(csa); if (str2int(csa->field, &i) != 0) error(csa, "row number missing or invalid"); if (!(1 <= i && i <= m)) error(csa, "row number out of range"); read_field(csa); if (P->row[i]->name != NULL) error(csa, "duplicate row name"); glp_set_row_name(P, i, csa->field); } else if (strcmp(csa->field, "j") == 0) { /* column name */ read_field(csa); if (str2int(csa->field, &j) != 0) error(csa, "column number missing or invalid"); if (!(1 <= j && j <= n)) error(csa, "column number out of range"); read_field(csa); if (P->col[j]->name != NULL) error(csa, "duplicate column name"); glp_set_col_name(P, j, csa->field); } else error(csa, "object designator missing or invalid"); } else if (strcmp(csa->field, "e") == 0) break; else error(csa, "line designator missing or invalid"); end_of_line(csa); } if (ne < nnz) error(csa, "too few constraint coefficient descriptors"); xassert(ne == nnz); k = glp_check_dup(m, n, ne, ia, ja); xassert(0 <= k && k <= nnz); if (k > 0) { csa->count = ln[k]; error(csa, "duplicate constraint coefficient"); } glp_load_matrix(P, ne, ia, ja, ar); /* print some statistics */ if (P->name != NULL) xprintf("Problem: %s\n", P->name); if (P->obj != NULL) xprintf("Objective: %s\n", P->obj); xprintf("%d row%s, %d column%s, %d non-zero%s\n", m, m == 1 ? "" : "s", n, n == 1 ? "" : "s", nnz, nnz == 1 ? "" : "s"); if (glp_get_num_int(P) > 0) { int ni = glp_get_num_int(P); int nb = glp_get_num_bin(P); if (ni == 1) { if (nb == 0) xprintf("One variable is integer\n"); else xprintf("One variable is binary\n"); } else { xprintf("%d integer variables, ", ni); if (nb == 0) xprintf("none"); else if (nb == 1) xprintf("one"); else if (nb == ni) xprintf("all"); else xprintf("%d", nb); xprintf(" of which %s binary\n", nb == 1 ? "is" : "are"); } } xprintf("%d lines were read\n", csa->count); /* problem data has been successfully read */ glp_sort_matrix(P); ret = 0; done: if (csa->fp != NULL) xfclose(csa->fp); if (rf != NULL) xfree(rf); if (cf != NULL) xfree(cf); if (ln != NULL) xfree(ln); if (ia != NULL) xfree(ia); if (ja != NULL) xfree(ja); if (ar != NULL) xfree(ar); if (ret) glp_erase_prob(P); return ret; } /*********************************************************************** * NAME * * glp_write_prob - write problem data in GLPK format * * SYNOPSIS * * int glp_write_prob(glp_prob *P, int flags, const char *fname); * * The routine glp_write_prob writes problem data in GLPK LP/MIP format * to a text file. * * RETURNS * * If the operation was successful, the routine returns zero. Otherwise * it prints an error message and returns non-zero. */ int glp_write_prob(glp_prob *P, int flags, const char *fname) { XFILE *fp; GLPROW *row; GLPCOL *col; GLPAIJ *aij; int mip, i, j, count, ret; if (P == NULL || P->magic != GLP_PROB_MAGIC) xerror("glp_write_prob: P = %p; invalid problem object\n", P); if (flags != 0) xerror("glp_write_prob: flags = %d; invalid parameter\n", flags); if (fname == NULL) xerror("glp_write_prob: fname = %d; invalid parameter\n", fname); xprintf("Writing problem data to `%s'...\n", fname); fp = xfopen(fname, "w"), count = 0; if (fp == NULL) { xprintf("Unable to create `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } /* write problem line */ mip = (glp_get_num_int(P) > 0); xfprintf(fp, "p %s %s %d %d %d\n", !mip ? "lp" : "mip", P->dir == GLP_MIN ? "min" : P->dir == GLP_MAX ? "max" : "???", P->m, P->n, P->nnz), count++; if (P->name != NULL) xfprintf(fp, "n p %s\n", P->name), count++; if (P->obj != NULL) xfprintf(fp, "n z %s\n", P->obj), count++; /* write row descriptors */ for (i = 1; i <= P->m; i++) { row = P->row[i]; if (row->type == GLP_FX && row->lb == 0.0) goto skip1; xfprintf(fp, "i %d ", i), count++; if (row->type == GLP_FR) xfprintf(fp, "f\n"); else if (row->type == GLP_LO) xfprintf(fp, "l %.*g\n", DBL_DIG, row->lb); else if (row->type == GLP_UP) xfprintf(fp, "u %.*g\n", DBL_DIG, row->ub); else if (row->type == GLP_DB) xfprintf(fp, "d %.*g %.*g\n", DBL_DIG, row->lb, DBL_DIG, row->ub); else if (row->type == GLP_FX) xfprintf(fp, "s %.*g\n", DBL_DIG, row->lb); else xassert(row != row); skip1: if (row->name != NULL) xfprintf(fp, "n i %d %s\n", i, row->name), count++; } /* write column descriptors */ for (j = 1; j <= P->n; j++) { col = P->col[j]; if (!mip && col->type == GLP_LO && col->lb == 0.0) goto skip2; if (mip && col->kind == GLP_IV && col->type == GLP_DB && col->lb == 0.0 && col->ub == 1.0) goto skip2; xfprintf(fp, "j %d ", j), count++; if (mip) { if (col->kind == GLP_CV) xfprintf(fp, "c "); else if (col->kind == GLP_IV) xfprintf(fp, "i "); else xassert(col != col); } if (col->type == GLP_FR) xfprintf(fp, "f\n"); else if (col->type == GLP_LO) xfprintf(fp, "l %.*g\n", DBL_DIG, col->lb); else if (col->type == GLP_UP) xfprintf(fp, "u %.*g\n", DBL_DIG, col->ub); else if (col->type == GLP_DB) xfprintf(fp, "d %.*g %.*g\n", DBL_DIG, col->lb, DBL_DIG, col->ub); else if (col->type == GLP_FX) xfprintf(fp, "s %.*g\n", DBL_DIG, col->lb); else xassert(col != col); skip2: if (col->name != NULL) xfprintf(fp, "n j %d %s\n", j, col->name), count++; } /* write objective coefficient descriptors */ if (P->c0 != 0.0) xfprintf(fp, "a 0 0 %.*g\n", DBL_DIG, P->c0), count++; for (j = 1; j <= P->n; j++) { col = P->col[j]; if (col->coef != 0.0) xfprintf(fp, "a 0 %d %.*g\n", j, DBL_DIG, col->coef), count++; } /* write constraint coefficient descriptors */ for (i = 1; i <= P->m; i++) { row = P->row[i]; for (aij = row->ptr; aij != NULL; aij = aij->r_next) xfprintf(fp, "a %d %d %.*g\n", i, aij->col->j, DBL_DIG, aij->val), count++; } /* write end line */ xfprintf(fp, "e o f\n"), count++; xfflush(fp); if (xferror(fp)) { xprintf("Write error on `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } xprintf("%d lines were written\n", count); ret = 0; done: if (fp != NULL) xfclose(fp); return ret; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpk.inc0000644000076500000240000000756613524616144025045 0ustar tamasstaff00000000000000GLPK = ../optional/glpk/glpapi.h ../optional/glpk/glpapi01.c ../optional/glpk/glpapi02.c ../optional/glpk/glpapi03.c ../optional/glpk/glpapi04.c ../optional/glpk/glpapi05.c ../optional/glpk/glpapi06.c ../optional/glpk/glpapi07.c ../optional/glpk/glpapi08.c ../optional/glpk/glpapi09.c ../optional/glpk/glpapi10.c ../optional/glpk/glpapi11.c ../optional/glpk/glpapi12.c ../optional/glpk/glpapi13.c ../optional/glpk/glpapi14.c ../optional/glpk/glpapi15.c ../optional/glpk/glpapi16.c ../optional/glpk/glpapi17.c ../optional/glpk/glpapi18.c ../optional/glpk/glpapi19.c ../optional/glpk/glpavl.c ../optional/glpk/glpavl.h ../optional/glpk/glpbfd.c ../optional/glpk/glpbfd.h ../optional/glpk/glpbfx.c ../optional/glpk/glpbfx.h ../optional/glpk/glpcpx.c ../optional/glpk/glpdmp.c ../optional/glpk/glpdmp.h ../optional/glpk/glpdmx.c ../optional/glpk/glpenv.h ../optional/glpk/glpenv01.c ../optional/glpk/glpenv02.c ../optional/glpk/glpenv03.c ../optional/glpk/glpenv04.c ../optional/glpk/glpenv05.c ../optional/glpk/glpenv06.c ../optional/glpk/glpenv07.c ../optional/glpk/glpenv08.c ../optional/glpk/glpfhv.c ../optional/glpk/glpfhv.h ../optional/glpk/glpgmp.c ../optional/glpk/glpgmp.h ../optional/glpk/glphbm.c ../optional/glpk/glphbm.h ../optional/glpk/glpini01.c ../optional/glpk/glpini02.c ../optional/glpk/glpios.h ../optional/glpk/glpios01.c ../optional/glpk/glpios02.c ../optional/glpk/glpios03.c ../optional/glpk/glpios04.c ../optional/glpk/glpios05.c ../optional/glpk/glpios06.c ../optional/glpk/glpios07.c ../optional/glpk/glpios08.c ../optional/glpk/glpios09.c ../optional/glpk/glpios10.c ../optional/glpk/glpios11.c ../optional/glpk/glpios12.c ../optional/glpk/glpipm.c ../optional/glpk/glpipm.h ../optional/glpk/glpk.h ../optional/glpk/glplib.h ../optional/glpk/glplib01.c ../optional/glpk/glplib02.c ../optional/glpk/glplib03.c ../optional/glpk/glplpf.c ../optional/glpk/glplpf.h ../optional/glpk/glplpx01.c ../optional/glpk/glplpx02.c ../optional/glpk/glplpx03.c ../optional/glpk/glpluf.c ../optional/glpk/glpluf.h ../optional/glpk/glplux.c ../optional/glpk/glplux.h ../optional/glpk/glpmat.c ../optional/glpk/glpmat.h ../optional/glpk/glpmpl.h ../optional/glpk/glpmpl01.c ../optional/glpk/glpmpl02.c ../optional/glpk/glpmpl03.c ../optional/glpk/glpmpl04.c ../optional/glpk/glpmpl05.c ../optional/glpk/glpmpl06.c ../optional/glpk/glpmps.c ../optional/glpk/glpnet.h ../optional/glpk/glpnet01.c ../optional/glpk/glpnet02.c ../optional/glpk/glpnet03.c ../optional/glpk/glpnet04.c ../optional/glpk/glpnet05.c ../optional/glpk/glpnet06.c ../optional/glpk/glpnet07.c ../optional/glpk/glpnet08.c ../optional/glpk/glpnet09.c ../optional/glpk/glpnpp.h ../optional/glpk/glpnpp01.c ../optional/glpk/glpnpp02.c ../optional/glpk/glpnpp03.c ../optional/glpk/glpnpp04.c ../optional/glpk/glpnpp05.c ../optional/glpk/glpqmd.c ../optional/glpk/glpqmd.h ../optional/glpk/glprgr.c ../optional/glpk/glprgr.h ../optional/glpk/glprng.h ../optional/glpk/glprng01.c ../optional/glpk/glprng02.c ../optional/glpk/glpscf.c ../optional/glpk/glpscf.h ../optional/glpk/glpscl.c ../optional/glpk/glpsdf.c ../optional/glpk/glpspm.c ../optional/glpk/glpspm.h ../optional/glpk/glpspx.h ../optional/glpk/glpspx01.c ../optional/glpk/glpspx02.c ../optional/glpk/glpsql.c ../optional/glpk/glpsql.h ../optional/glpk/glpssx.h ../optional/glpk/glpssx01.c ../optional/glpk/glpssx02.c ../optional/glpk/glpstd.h ../optional/glpk/glptsp.c ../optional/glpk/glptsp.h ../optional/glpk/amd/amd.h ../optional/glpk/amd/amd_1.c ../optional/glpk/amd/amd_2.c ../optional/glpk/amd/amd_aat.c ../optional/glpk/amd/amd_control.c ../optional/glpk/amd/amd_defaults.c ../optional/glpk/amd/amd_dump.c ../optional/glpk/amd/amd_info.c ../optional/glpk/amd/amd_internal.h ../optional/glpk/amd/amd_order.c ../optional/glpk/amd/amd_post_tree.c ../optional/glpk/amd/amd_postorder.c ../optional/glpk/amd/amd_preprocess.c ../optional/glpk/amd/amd_valid.c ../optional/glpk/colamd/colamd.c ../optional/glpk/colamd/colamd.h python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpcpx.c0000644000076500000240000012517713524616144025055 0ustar tamasstaff00000000000000/* glpcpx.c (CPLEX LP format routines) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wlogical-op-parentheses" #pragma clang diagnostic ignored "-Wsign-conversion" #endif #include "glpapi.h" /*********************************************************************** * NAME * * glp_init_cpxcp - initialize CPLEX LP format control parameters * * SYNOPSIS * * void glp_init_cpxcp(glp_cpxcp *parm): * * The routine glp_init_cpxcp initializes control parameters used by * the CPLEX LP input/output routines glp_read_lp and glp_write_lp with * default values. * * Default values of the control parameters are stored in the glp_cpxcp * structure, which the parameter parm points to. */ void glp_init_cpxcp(glp_cpxcp *parm) { xassert(parm != NULL); return; } static void check_parm(const char *func, const glp_cpxcp *parm) { /* check control parameters */ xassert(func != NULL); xassert(parm != NULL); return; } /*********************************************************************** * NAME * * glp_read_lp - read problem data in CPLEX LP format * * SYNOPSIS * * int glp_read_lp(glp_prob *P, const glp_cpxcp *parm, const char * *fname); * * DESCRIPTION * * The routine glp_read_lp reads problem data in CPLEX LP format from * a text file. * * The parameter parm is a pointer to the structure glp_cpxcp, which * specifies control parameters used by the routine. If parm is NULL, * the routine uses default settings. * * The character string fname specifies a name of the text file to be * read. * * Note that before reading data the current content of the problem * object is completely erased with the routine glp_erase_prob. * * RETURNS * * If the operation was successful, the routine glp_read_lp returns * zero. Otherwise, it prints an error message and returns non-zero. */ struct csa { /* common storage area */ glp_prob *P; /* LP/MIP problem object */ const glp_cpxcp *parm; /* pointer to control parameters */ const char *fname; /* name of input CPLEX LP file */ XFILE *fp; /* stream assigned to input CPLEX LP file */ jmp_buf jump; /* label for go to in case of error */ int count; /* line count */ int c; /* current character or XEOF */ int token; /* current token: */ #define T_EOF 0x00 /* end of file */ #define T_MINIMIZE 0x01 /* keyword 'minimize' */ #define T_MAXIMIZE 0x02 /* keyword 'maximize' */ #define T_SUBJECT_TO 0x03 /* keyword 'subject to' */ #define T_BOUNDS 0x04 /* keyword 'bounds' */ #define T_GENERAL 0x05 /* keyword 'general' */ #define T_INTEGER 0x06 /* keyword 'integer' */ #define T_BINARY 0x07 /* keyword 'binary' */ #define T_END 0x08 /* keyword 'end' */ #define T_NAME 0x09 /* symbolic name */ #define T_NUMBER 0x0A /* numeric constant */ #define T_PLUS 0x0B /* delimiter '+' */ #define T_MINUS 0x0C /* delimiter '-' */ #define T_COLON 0x0D /* delimiter ':' */ #define T_LE 0x0E /* delimiter '<=' */ #define T_GE 0x0F /* delimiter '>=' */ #define T_EQ 0x10 /* delimiter '=' */ char image[255+1]; /* image of current token */ int imlen; /* length of token image */ double value; /* value of numeric constant */ int n_max; /* length of the following five arrays (enlarged automatically, if necessary) */ int *ind; /* int ind[1+n_max]; */ double *val; /* double val[1+n_max]; */ char *flag; /* char flag[1+n_max]; */ /* working arrays used to construct linear forms */ double *lb; /* double lb[1+n_max]; */ double *ub; /* double ub[1+n_max]; */ /* lower and upper bounds of variables (columns) */ }; #define CHAR_SET "!\"#$%&()/,.;?@_`'{}|~" /* characters, which may appear in symbolic names */ static void error(struct csa *csa, const char *fmt, ...) { /* print error message and terminate processing */ va_list arg; xprintf("%s:%d: ", csa->fname, csa->count); va_start(arg, fmt); xvprintf(fmt, arg); va_end(arg); longjmp(csa->jump, 1); /* no return */ } static void warning(struct csa *csa, const char *fmt, ...) { /* print warning message and continue processing */ va_list arg; xprintf("%s:%d: warning: ", csa->fname, csa->count); va_start(arg, fmt); xvprintf(fmt, arg); va_end(arg); return; } static void read_char(struct csa *csa) { /* read next character from input file */ int c; xassert(csa->c != XEOF); if (csa->c == '\n') csa->count++; c = xfgetc(csa->fp); if (c < 0) { if (xferror(csa->fp)) error(csa, "read error - %s\n", xerrmsg()); else if (csa->c == '\n') { csa->count--; c = XEOF; } else { warning(csa, "missing final end of line\n"); c = '\n'; } } else if (c == '\n') ; else if (isspace(c)) c = ' '; else if (iscntrl(c)) error(csa, "invalid control character 0x%02X\n", c); csa->c = c; return; } static void add_char(struct csa *csa) { /* append current character to current token */ if (csa->imlen == sizeof(csa->image)-1) error(csa, "token `%.15s...' too long\n", csa->image); csa->image[csa->imlen++] = (char)csa->c; csa->image[csa->imlen] = '\0'; read_char(csa); return; } static int the_same(char *s1, char *s2) { /* compare two character strings ignoring case sensitivity */ for (; *s1 != '\0'; s1++, s2++) { if (tolower((unsigned char)*s1) != tolower((unsigned char)*s2)) return 0; } return 1; } static void scan_token(struct csa *csa) { /* scan next token */ int flag; csa->token = -1; csa->image[0] = '\0'; csa->imlen = 0; csa->value = 0.0; loop: flag = 0; /* skip non-significant characters */ while (csa->c == ' ') read_char(csa); /* recognize and scan current token */ if (csa->c == XEOF) csa->token = T_EOF; else if (csa->c == '\n') { read_char(csa); /* if the next character is letter, it may begin a keyword */ if (isalpha(csa->c)) { flag = 1; goto name; } goto loop; } else if (csa->c == '\\') { /* comment; ignore everything until end-of-line */ while (csa->c != '\n') read_char(csa); goto loop; } else if (isalpha(csa->c) || csa->c != '.' && strchr(CHAR_SET, csa->c) != NULL) name: { /* symbolic name */ csa->token = T_NAME; while (isalnum(csa->c) || strchr(CHAR_SET, csa->c) != NULL) add_char(csa); if (flag) { /* check for keyword */ if (the_same(csa->image, "minimize")) csa->token = T_MINIMIZE; else if (the_same(csa->image, "minimum")) csa->token = T_MINIMIZE; else if (the_same(csa->image, "min")) csa->token = T_MINIMIZE; else if (the_same(csa->image, "maximize")) csa->token = T_MAXIMIZE; else if (the_same(csa->image, "maximum")) csa->token = T_MAXIMIZE; else if (the_same(csa->image, "max")) csa->token = T_MAXIMIZE; else if (the_same(csa->image, "subject")) { if (csa->c == ' ') { read_char(csa); if (tolower(csa->c) == 't') { csa->token = T_SUBJECT_TO; csa->image[csa->imlen++] = ' '; csa->image[csa->imlen] = '\0'; add_char(csa); if (tolower(csa->c) != 'o') error(csa, "keyword `subject to' incomplete\n"); add_char(csa); if (isalpha(csa->c)) error(csa, "keyword `%s%c...' not recognized\n", csa->image, csa->c); } } } else if (the_same(csa->image, "such")) { if (csa->c == ' ') { read_char(csa); if (tolower(csa->c) == 't') { csa->token = T_SUBJECT_TO; csa->image[csa->imlen++] = ' '; csa->image[csa->imlen] = '\0'; add_char(csa); if (tolower(csa->c) != 'h') err: error(csa, "keyword `such that' incomplete\n"); add_char(csa); if (tolower(csa->c) != 'a') goto err; add_char(csa); if (tolower(csa->c) != 't') goto err; add_char(csa); if (isalpha(csa->c)) error(csa, "keyword `%s%c...' not recognized\n", csa->image, csa->c); } } } else if (the_same(csa->image, "st")) csa->token = T_SUBJECT_TO; else if (the_same(csa->image, "s.t.")) csa->token = T_SUBJECT_TO; else if (the_same(csa->image, "st.")) csa->token = T_SUBJECT_TO; else if (the_same(csa->image, "bounds")) csa->token = T_BOUNDS; else if (the_same(csa->image, "bound")) csa->token = T_BOUNDS; else if (the_same(csa->image, "general")) csa->token = T_GENERAL; else if (the_same(csa->image, "generals")) csa->token = T_GENERAL; else if (the_same(csa->image, "gen")) csa->token = T_GENERAL; else if (the_same(csa->image, "integer")) csa->token = T_INTEGER; else if (the_same(csa->image, "integers")) csa->token = T_INTEGER; else if (the_same(csa->image, "int")) csa->token = T_INTEGER; else if (the_same(csa->image, "binary")) csa->token = T_BINARY; else if (the_same(csa->image, "binaries")) csa->token = T_BINARY; else if (the_same(csa->image, "bin")) csa->token = T_BINARY; else if (the_same(csa->image, "end")) csa->token = T_END; } } else if (isdigit(csa->c) || csa->c == '.') { /* numeric constant */ csa->token = T_NUMBER; /* scan integer part */ while (isdigit(csa->c)) add_char(csa); /* scan optional fractional part (it is mandatory, if there is no integer part) */ if (csa->c == '.') { add_char(csa); if (csa->imlen == 1 && !isdigit(csa->c)) error(csa, "invalid use of decimal point\n"); while (isdigit(csa->c)) add_char(csa); } /* scan optional decimal exponent */ if (csa->c == 'e' || csa->c == 'E') { add_char(csa); if (csa->c == '+' || csa->c == '-') add_char(csa); if (!isdigit(csa->c)) error(csa, "numeric constant `%s' incomplete\n", csa->image); while (isdigit(csa->c)) add_char(csa); } /* convert the numeric constant to floating-point */ if (str2num(csa->image, &csa->value)) error(csa, "numeric constant `%s' out of range\n", csa->image); } else if (csa->c == '+') csa->token = T_PLUS, add_char(csa); else if (csa->c == '-') csa->token = T_MINUS, add_char(csa); else if (csa->c == ':') csa->token = T_COLON, add_char(csa); else if (csa->c == '<') { csa->token = T_LE, add_char(csa); if (csa->c == '=') add_char(csa); } else if (csa->c == '>') { csa->token = T_GE, add_char(csa); if (csa->c == '=') add_char(csa); } else if (csa->c == '=') { csa->token = T_EQ, add_char(csa); if (csa->c == '<') csa->token = T_LE, add_char(csa); else if (csa->c == '>') csa->token = T_GE, add_char(csa); } else error(csa, "character `%c' not recognized\n", csa->c); /* skip non-significant characters */ while (csa->c == ' ') read_char(csa); return; } static int find_col(struct csa *csa, char *name) { /* find column by its symbolic name */ int j; j = glp_find_col(csa->P, name); if (j == 0) { /* not found; create new column */ j = glp_add_cols(csa->P, 1); glp_set_col_name(csa->P, j, name); /* enlarge working arrays, if necessary */ if (csa->n_max < j) { int n_max = csa->n_max; int *ind = csa->ind; double *val = csa->val; char *flag = csa->flag; double *lb = csa->lb; double *ub = csa->ub; csa->n_max += csa->n_max; csa->ind = xcalloc(1+csa->n_max, sizeof(int)); memcpy(&csa->ind[1], &ind[1], n_max * sizeof(int)); xfree(ind); csa->val = xcalloc(1+csa->n_max, sizeof(double)); memcpy(&csa->val[1], &val[1], n_max * sizeof(double)); xfree(val); csa->flag = xcalloc(1+csa->n_max, sizeof(char)); memset(&csa->flag[1], 0, csa->n_max * sizeof(char)); memcpy(&csa->flag[1], &flag[1], n_max * sizeof(char)); xfree(flag); csa->lb = xcalloc(1+csa->n_max, sizeof(double)); memcpy(&csa->lb[1], &lb[1], n_max * sizeof(double)); xfree(lb); csa->ub = xcalloc(1+csa->n_max, sizeof(double)); memcpy(&csa->ub[1], &ub[1], n_max * sizeof(double)); xfree(ub); } csa->lb[j] = +DBL_MAX, csa->ub[j] = -DBL_MAX; } return j; } /*********************************************************************** * parse_linear_form - parse linear form * * This routine parses the linear form using the following syntax: * * ::= * ::= * ::= | * ::= | + | - | * + | - * * The routine returns the number of terms in the linear form. */ static int parse_linear_form(struct csa *csa) { int j, k, len = 0, newlen; double s, coef; loop: /* parse an optional sign */ if (csa->token == T_PLUS) s = +1.0, scan_token(csa); else if (csa->token == T_MINUS) s = -1.0, scan_token(csa); else s = +1.0; /* parse an optional coefficient */ if (csa->token == T_NUMBER) coef = csa->value, scan_token(csa); else coef = 1.0; /* parse a variable name */ if (csa->token != T_NAME) error(csa, "missing variable name\n"); /* find the corresponding column */ j = find_col(csa, csa->image); /* check if the variable is already used in the linear form */ if (csa->flag[j]) error(csa, "multiple use of variable `%s' not allowed\n", csa->image); /* add new term to the linear form */ len++, csa->ind[len] = j, csa->val[len] = s * coef; /* and mark that the variable is used in the linear form */ csa->flag[j] = 1; scan_token(csa); /* if the next token is a sign, there is another term */ if (csa->token == T_PLUS || csa->token == T_MINUS) goto loop; /* clear marks of the variables used in the linear form */ for (k = 1; k <= len; k++) csa->flag[csa->ind[k]] = 0; /* remove zero coefficients */ newlen = 0; for (k = 1; k <= len; k++) { if (csa->val[k] != 0.0) { newlen++; csa->ind[newlen] = csa->ind[k]; csa->val[newlen] = csa->val[k]; } } return newlen; } /*********************************************************************** * parse_objective - parse objective function * * This routine parses definition of the objective function using the * following syntax: * * ::= minimize | minimum | min | maximize | maximum | max * ::= | : * ::= */ static void parse_objective(struct csa *csa) { /* parse objective sense */ int k, len; /* parse the keyword 'minimize' or 'maximize' */ if (csa->token == T_MINIMIZE) glp_set_obj_dir(csa->P, GLP_MIN); else if (csa->token == T_MAXIMIZE) glp_set_obj_dir(csa->P, GLP_MAX); else xassert(csa != csa); scan_token(csa); /* parse objective name */ if (csa->token == T_NAME && csa->c == ':') { /* objective name is followed by a colon */ glp_set_obj_name(csa->P, csa->image); scan_token(csa); xassert(csa->token == T_COLON); scan_token(csa); } else { /* objective name is not specified; use default */ glp_set_obj_name(csa->P, "obj"); } /* parse linear form */ len = parse_linear_form(csa); for (k = 1; k <= len; k++) glp_set_obj_coef(csa->P, csa->ind[k], csa->val[k]); return; } /*********************************************************************** * parse_constraints - parse constraints section * * This routine parses the constraints section using the following * syntax: * * ::= | : * ::= < | <= | =< | > | >= | => | = * ::= | + | * - * ::= * * ::= subject to | such that | st | s.t. | st. * ::= | * */ static void parse_constraints(struct csa *csa) { int i, len, type; double s; /* parse the keyword 'subject to' */ xassert(csa->token == T_SUBJECT_TO); scan_token(csa); loop: /* create new row (constraint) */ i = glp_add_rows(csa->P, 1); /* parse row name */ if (csa->token == T_NAME && csa->c == ':') { /* row name is followed by a colon */ if (glp_find_row(csa->P, csa->image) != 0) error(csa, "constraint `%s' multiply defined\n", csa->image); glp_set_row_name(csa->P, i, csa->image); scan_token(csa); xassert(csa->token == T_COLON); scan_token(csa); } else { /* row name is not specified; use default */ char name[50]; sprintf(name, "r.%d", csa->count); glp_set_row_name(csa->P, i, name); } /* parse linear form */ len = parse_linear_form(csa); glp_set_mat_row(csa->P, i, len, csa->ind, csa->val); /* parse constraint sense */ if (csa->token == T_LE) type = GLP_UP, scan_token(csa); else if (csa->token == T_GE) type = GLP_LO, scan_token(csa); else if (csa->token == T_EQ) type = GLP_FX, scan_token(csa); else error(csa, "missing constraint sense\n"); /* parse right-hand side */ if (csa->token == T_PLUS) s = +1.0, scan_token(csa); else if (csa->token == T_MINUS) s = -1.0, scan_token(csa); else s = +1.0; if (csa->token != T_NUMBER) error(csa, "missing right-hand side\n"); glp_set_row_bnds(csa->P, i, type, s * csa->value, s * csa->value); /* the rest of the current line must be empty */ if (!(csa->c == '\n' || csa->c == XEOF)) error(csa, "invalid symbol(s) beyond right-hand side\n"); scan_token(csa); /* if the next token is a sign, numeric constant, or a symbolic name, here is another constraint */ if (csa->token == T_PLUS || csa->token == T_MINUS || csa->token == T_NUMBER || csa->token == T_NAME) goto loop; return; } static void set_lower_bound(struct csa *csa, int j, double lb) { /* set lower bound of j-th variable */ if (csa->lb[j] != +DBL_MAX) { warning(csa, "lower bound of variable `%s' redefined\n", glp_get_col_name(csa->P, j)); } csa->lb[j] = lb; return; } static void set_upper_bound(struct csa *csa, int j, double ub) { /* set upper bound of j-th variable */ if (csa->ub[j] != -DBL_MAX) { warning(csa, "upper bound of variable `%s' redefined\n", glp_get_col_name(csa->P, j)); } csa->ub[j] = ub; return; } /*********************************************************************** * parse_bounds - parse bounds section * * This routine parses the bounds section using the following syntax: * * ::= * ::= infinity | inf * ::= | + | * - | + | - * ::= < | <= | =< * ::= > | >= | => * ::= | * | | * | = | free * ::= bounds | bound * ::= | * */ static void parse_bounds(struct csa *csa) { int j, lb_flag; double lb, s; /* parse the keyword 'bounds' */ xassert(csa->token == T_BOUNDS); scan_token(csa); loop: /* bound definition can start with a sign, numeric constant, or a symbolic name */ if (!(csa->token == T_PLUS || csa->token == T_MINUS || csa->token == T_NUMBER || csa->token == T_NAME)) goto done; /* parse bound definition */ if (csa->token == T_PLUS || csa->token == T_MINUS) { /* parse signed lower bound */ lb_flag = 1; s = (csa->token == T_PLUS ? +1.0 : -1.0); scan_token(csa); if (csa->token == T_NUMBER) lb = s * csa->value, scan_token(csa); else if (the_same(csa->image, "infinity") || the_same(csa->image, "inf")) { if (s > 0.0) error(csa, "invalid use of `+inf' as lower bound\n"); lb = -DBL_MAX, scan_token(csa); } else error(csa, "missing lower bound\n"); } else if (csa->token == T_NUMBER) { /* parse unsigned lower bound */ lb_flag = 1; lb = csa->value, scan_token(csa); } else { /* lower bound is not specified */ lb_flag = 0; } /* parse the token that should follow the lower bound */ if (lb_flag) { if (csa->token != T_LE) error(csa, "missing `<', `<=', or `=<' after lower bound\n") ; scan_token(csa); } /* parse variable name */ if (csa->token != T_NAME) error(csa, "missing variable name\n"); j = find_col(csa, csa->image); /* set lower bound */ if (lb_flag) set_lower_bound(csa, j, lb); scan_token(csa); /* parse the context that follows the variable name */ if (csa->token == T_LE) { /* parse upper bound */ scan_token(csa); if (csa->token == T_PLUS || csa->token == T_MINUS) { /* parse signed upper bound */ s = (csa->token == T_PLUS ? +1.0 : -1.0); scan_token(csa); if (csa->token == T_NUMBER) { set_upper_bound(csa, j, s * csa->value); scan_token(csa); } else if (the_same(csa->image, "infinity") || the_same(csa->image, "inf")) { if (s < 0.0) error(csa, "invalid use of `-inf' as upper bound\n"); set_upper_bound(csa, j, +DBL_MAX); scan_token(csa); } else error(csa, "missing upper bound\n"); } else if (csa->token == T_NUMBER) { /* parse unsigned upper bound */ set_upper_bound(csa, j, csa->value); scan_token(csa); } else error(csa, "missing upper bound\n"); } else if (csa->token == T_GE) { /* parse lower bound */ if (lb_flag) { /* the context '... <= x >= ...' is invalid */ error(csa, "invalid bound definition\n"); } scan_token(csa); if (csa->token == T_PLUS || csa->token == T_MINUS) { /* parse signed lower bound */ s = (csa->token == T_PLUS ? +1.0 : -1.0); scan_token(csa); if (csa->token == T_NUMBER) { set_lower_bound(csa, j, s * csa->value); scan_token(csa); } else if (the_same(csa->image, "infinity") || the_same(csa->image, "inf") == 0) { if (s > 0.0) error(csa, "invalid use of `+inf' as lower bound\n"); set_lower_bound(csa, j, -DBL_MAX); scan_token(csa); } else error(csa, "missing lower bound\n"); } else if (csa->token == T_NUMBER) { /* parse unsigned lower bound */ set_lower_bound(csa, j, csa->value); scan_token(csa); } else error(csa, "missing lower bound\n"); } else if (csa->token == T_EQ) { /* parse fixed value */ if (lb_flag) { /* the context '... <= x = ...' is invalid */ error(csa, "invalid bound definition\n"); } scan_token(csa); if (csa->token == T_PLUS || csa->token == T_MINUS) { /* parse signed fixed value */ s = (csa->token == T_PLUS ? +1.0 : -1.0); scan_token(csa); if (csa->token == T_NUMBER) { set_lower_bound(csa, j, s * csa->value); set_upper_bound(csa, j, s * csa->value); scan_token(csa); } else error(csa, "missing fixed value\n"); } else if (csa->token == T_NUMBER) { /* parse unsigned fixed value */ set_lower_bound(csa, j, csa->value); set_upper_bound(csa, j, csa->value); scan_token(csa); } else error(csa, "missing fixed value\n"); } else if (the_same(csa->image, "free")) { /* parse the keyword 'free' */ if (lb_flag) { /* the context '... <= x free ...' is invalid */ error(csa, "invalid bound definition\n"); } set_lower_bound(csa, j, -DBL_MAX); set_upper_bound(csa, j, +DBL_MAX); scan_token(csa); } else if (!lb_flag) { /* neither lower nor upper bounds are specified */ error(csa, "invalid bound definition\n"); } goto loop; done: return; } /*********************************************************************** * parse_integer - parse general, integer, or binary section * * ::= * ::= general | generals | gen * ::= integer | integers | int * ::= binary | binaries | bin *
::= * ::=
| * */ static void parse_integer(struct csa *csa) { int j, binary; /* parse the keyword 'general', 'integer', or 'binary' */ if (csa->token == T_GENERAL) binary = 0, scan_token(csa); else if (csa->token == T_INTEGER) binary = 0, scan_token(csa); else if (csa->token == T_BINARY) binary = 1, scan_token(csa); else xassert(csa != csa); /* parse list of variables (may be empty) */ while (csa->token == T_NAME) { /* find the corresponding column */ j = find_col(csa, csa->image); /* change kind of the variable */ glp_set_col_kind(csa->P, j, GLP_IV); /* set 0-1 bounds for the binary variable */ if (binary) { set_lower_bound(csa, j, 0.0); set_upper_bound(csa, j, 1.0); } scan_token(csa); } return; } int glp_read_lp(glp_prob *P, const glp_cpxcp *parm, const char *fname) { /* read problem data in CPLEX LP format */ glp_cpxcp _parm; struct csa _csa, *csa = &_csa; int ret; xprintf("Reading problem data from `%s'...\n", fname); if (parm == NULL) glp_init_cpxcp(&_parm), parm = &_parm; /* check control parameters */ check_parm("glp_read_lp", parm); /* initialize common storage area */ csa->P = P; csa->parm = parm; csa->fname = fname; csa->fp = NULL; if (setjmp(csa->jump)) { ret = 1; goto done; } csa->count = 0; csa->c = '\n'; csa->token = T_EOF; csa->image[0] = '\0'; csa->imlen = 0; csa->value = 0.0; csa->n_max = 100; csa->ind = xcalloc(1+csa->n_max, sizeof(int)); csa->val = xcalloc(1+csa->n_max, sizeof(double)); csa->flag = xcalloc(1+csa->n_max, sizeof(char)); memset(&csa->flag[1], 0, csa->n_max * sizeof(char)); csa->lb = xcalloc(1+csa->n_max, sizeof(double)); csa->ub = xcalloc(1+csa->n_max, sizeof(double)); /* erase problem object */ glp_erase_prob(P); glp_create_index(P); /* open input CPLEX LP file */ csa->fp = xfopen(fname, "r"); if (csa->fp == NULL) { xprintf("Unable to open `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } /* scan very first token */ scan_token(csa); /* parse definition of the objective function */ if (!(csa->token == T_MINIMIZE || csa->token == T_MAXIMIZE)) error(csa, "`minimize' or `maximize' keyword missing\n"); parse_objective(csa); /* parse constraints section */ if (csa->token != T_SUBJECT_TO) error(csa, "constraints section missing\n"); parse_constraints(csa); /* parse optional bounds section */ if (csa->token == T_BOUNDS) parse_bounds(csa); /* parse optional general, integer, and binary sections */ while (csa->token == T_GENERAL || csa->token == T_INTEGER || csa->token == T_BINARY) parse_integer(csa); /* check for the keyword 'end' */ if (csa->token == T_END) scan_token(csa); else if (csa->token == T_EOF) warning(csa, "keyword `end' missing\n"); else error(csa, "symbol `%s' in wrong position\n", csa->image); /* nothing must follow the keyword 'end' (except comments) */ if (csa->token != T_EOF) error(csa, "extra symbol(s) detected beyond `end'\n"); /* set bounds of variables */ { int j, type; double lb, ub; for (j = 1; j <= P->n; j++) { lb = csa->lb[j]; ub = csa->ub[j]; if (lb == +DBL_MAX) lb = 0.0; /* default lb */ if (ub == -DBL_MAX) ub = +DBL_MAX; /* default ub */ if (lb == -DBL_MAX && ub == +DBL_MAX) type = GLP_FR; else if (ub == +DBL_MAX) type = GLP_LO; else if (lb == -DBL_MAX) type = GLP_UP; else if (lb != ub) type = GLP_DB; else type = GLP_FX; glp_set_col_bnds(csa->P, j, type, lb, ub); } } /* print some statistics */ xprintf("%d row%s, %d column%s, %d non-zero%s\n", P->m, P->m == 1 ? "" : "s", P->n, P->n == 1 ? "" : "s", P->nnz, P->nnz == 1 ? "" : "s"); if (glp_get_num_int(P) > 0) { int ni = glp_get_num_int(P); int nb = glp_get_num_bin(P); if (ni == 1) { if (nb == 0) xprintf("One variable is integer\n"); else xprintf("One variable is binary\n"); } else { xprintf("%d integer variables, ", ni); if (nb == 0) xprintf("none"); else if (nb == 1) xprintf("one"); else if (nb == ni) xprintf("all"); else xprintf("%d", nb); xprintf(" of which %s binary\n", nb == 1 ? "is" : "are"); } } xprintf("%d lines were read\n", csa->count); /* problem data has been successfully read */ glp_delete_index(P); glp_sort_matrix(P); ret = 0; done: if (csa->fp != NULL) xfclose(csa->fp); xfree(csa->ind); xfree(csa->val); xfree(csa->flag); xfree(csa->lb); xfree(csa->ub); if (ret != 0) glp_erase_prob(P); return ret; } /*********************************************************************** * NAME * * glp_write_lp - write problem data in CPLEX LP format * * SYNOPSIS * * int glp_write_lp(glp_prob *P, const glp_cpxcp *parm, const char * *fname); * * DESCRIPTION * * The routine glp_write_lp writes problem data in CPLEX LP format to * a text file. * * The parameter parm is a pointer to the structure glp_cpxcp, which * specifies control parameters used by the routine. If parm is NULL, * the routine uses default settings. * * The character string fname specifies a name of the text file to be * written. * * RETURNS * * If the operation was successful, the routine glp_write_lp returns * zero. Otherwise, it prints an error message and returns non-zero. */ #define csa csa1 struct csa { /* common storage area */ glp_prob *P; /* pointer to problem object */ const glp_cpxcp *parm; /* pointer to control parameters */ }; static int check_name(char *name) { /* check if specified name is valid for CPLEX LP format */ if (*name == '.') return 1; if (isdigit((unsigned char)*name)) return 1; for (; *name; name++) { if (!isalnum((unsigned char)*name) && strchr(CHAR_SET, (unsigned char)*name) == NULL) return 1; } return 0; /* name is ok */ } static void adjust_name(char *name) { /* attempt to adjust specified name to make it valid for CPLEX LP format */ for (; *name; name++) { if (*name == ' ') *name = '_'; else if (*name == '-') *name = '~'; else if (*name == '[') *name = '('; else if (*name == ']') *name = ')'; } return; } static char *row_name(struct csa *csa, int i, char rname[255+1]) { /* construct symbolic name of i-th row (constraint) */ const char *name; if (i == 0) name = glp_get_obj_name(csa->P); else name = glp_get_row_name(csa->P, i); if (name == NULL) goto fake; strcpy(rname, name); adjust_name(rname); if (check_name(rname)) goto fake; return rname; fake: if (i == 0) strcpy(rname, "obj"); else sprintf(rname, "r_%d", i); return rname; } static char *col_name(struct csa *csa, int j, char cname[255+1]) { /* construct symbolic name of j-th column (variable) */ const char *name; name = glp_get_col_name(csa->P, j); if (name == NULL) goto fake; strcpy(cname, name); adjust_name(cname); if (check_name(cname)) goto fake; return cname; fake: sprintf(cname, "x_%d", j); return cname; } int glp_write_lp(glp_prob *P, const glp_cpxcp *parm, const char *fname) { /* write problem data in CPLEX LP format */ glp_cpxcp _parm; struct csa _csa, *csa = &_csa; XFILE *fp; GLPROW *row; GLPCOL *col; GLPAIJ *aij; int i, j, len, flag, count, ret; char line[1000+1], term[500+1], name[255+1]; xprintf("Writing problem data to `%s'...\n", fname); if (parm == NULL) glp_init_cpxcp(&_parm), parm = &_parm; /* check control parameters */ check_parm("glp_write_lp", parm); /* initialize common storage area */ csa->P = P; csa->parm = parm; /* create output CPLEX LP file */ fp = xfopen(fname, "w"), count = 0; if (fp == NULL) { xprintf("Unable to create `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } /* write problem name */ xfprintf(fp, "\\* Problem: %s *\\\n", P->name == NULL ? "Unknown" : P->name), count++; xfprintf(fp, "\n"), count++; /* the problem should contain at least one row and one column */ if (!(P->m > 0 && P->n > 0)) { xprintf("Warning: problem has no rows/columns\n"); xfprintf(fp, "\\* WARNING: PROBLEM HAS NO ROWS/COLUMNS *\\\n"), count++; xfprintf(fp, "\n"), count++; goto skip; } /* write the objective function definition */ if (P->dir == GLP_MIN) xfprintf(fp, "Minimize\n"), count++; else if (P->dir == GLP_MAX) xfprintf(fp, "Maximize\n"), count++; else xassert(P != P); row_name(csa, 0, name); sprintf(line, " %s:", name); len = 0; for (j = 1; j <= P->n; j++) { col = P->col[j]; if (col->coef != 0.0 || col->ptr == NULL) { len++; col_name(csa, j, name); if (col->coef == 0.0) sprintf(term, " + 0 %s", name); /* empty column */ else if (col->coef == +1.0) sprintf(term, " + %s", name); else if (col->coef == -1.0) sprintf(term, " - %s", name); else if (col->coef > 0.0) sprintf(term, " + %.*g %s", DBL_DIG, +col->coef, name); else sprintf(term, " - %.*g %s", DBL_DIG, -col->coef, name); if (strlen(line) + strlen(term) > 72) xfprintf(fp, "%s\n", line), line[0] = '\0', count++; strcat(line, term); } } if (len == 0) { /* empty objective */ sprintf(term, " 0 %s", col_name(csa, 1, name)); strcat(line, term); } xfprintf(fp, "%s\n", line), count++; if (P->c0 != 0.0) xfprintf(fp, "\\* constant term = %.*g *\\\n", DBL_DIG, P->c0), count++; xfprintf(fp, "\n"), count++; /* write the constraints section */ xfprintf(fp, "Subject To\n"), count++; for (i = 1; i <= P->m; i++) { row = P->row[i]; if (row->type == GLP_FR) continue; /* skip free row */ row_name(csa, i, name); sprintf(line, " %s:", name); /* linear form */ for (aij = row->ptr; aij != NULL; aij = aij->r_next) { col_name(csa, aij->col->j, name); if (aij->val == +1.0) sprintf(term, " + %s", name); else if (aij->val == -1.0) sprintf(term, " - %s", name); else if (aij->val > 0.0) sprintf(term, " + %.*g %s", DBL_DIG, +aij->val, name); else sprintf(term, " - %.*g %s", DBL_DIG, -aij->val, name); if (strlen(line) + strlen(term) > 72) xfprintf(fp, "%s\n", line), line[0] = '\0', count++; strcat(line, term); } if (row->type == GLP_DB) { /* double-bounded (ranged) constraint */ sprintf(term, " - ~r_%d", i); if (strlen(line) + strlen(term) > 72) xfprintf(fp, "%s\n", line), line[0] = '\0', count++; strcat(line, term); } else if (row->ptr == NULL) { /* empty constraint */ sprintf(term, " 0 %s", col_name(csa, 1, name)); strcat(line, term); } /* right hand-side */ if (row->type == GLP_LO) sprintf(term, " >= %.*g", DBL_DIG, row->lb); else if (row->type == GLP_UP) sprintf(term, " <= %.*g", DBL_DIG, row->ub); else if (row->type == GLP_DB || row->type == GLP_FX) sprintf(term, " = %.*g", DBL_DIG, row->lb); else xassert(row != row); if (strlen(line) + strlen(term) > 72) xfprintf(fp, "%s\n", line), line[0] = '\0', count++; strcat(line, term); xfprintf(fp, "%s\n", line), count++; } xfprintf(fp, "\n"), count++; /* write the bounds section */ flag = 0; for (i = 1; i <= P->m; i++) { row = P->row[i]; if (row->type != GLP_DB) continue; if (!flag) xfprintf(fp, "Bounds\n"), flag = 1, count++; xfprintf(fp, " 0 <= ~r_%d <= %.*g\n", i, DBL_DIG, row->ub - row->lb), count++; } for (j = 1; j <= P->n; j++) { col = P->col[j]; if (col->type == GLP_LO && col->lb == 0.0) continue; if (!flag) xfprintf(fp, "Bounds\n"), flag = 1, count++; col_name(csa, j, name); if (col->type == GLP_FR) xfprintf(fp, " %s free\n", name), count++; else if (col->type == GLP_LO) xfprintf(fp, " %s >= %.*g\n", name, DBL_DIG, col->lb), count++; else if (col->type == GLP_UP) xfprintf(fp, " -Inf <= %s <= %.*g\n", name, DBL_DIG, col->ub), count++; else if (col->type == GLP_DB) xfprintf(fp, " %.*g <= %s <= %.*g\n", DBL_DIG, col->lb, name, DBL_DIG, col->ub), count++; else if (col->type == GLP_FX) xfprintf(fp, " %s = %.*g\n", name, DBL_DIG, col->lb), count++; else xassert(col != col); } if (flag) xfprintf(fp, "\n"), count++; /* write the integer section */ flag = 0; for (j = 1; j <= P->n; j++) { col = P->col[j]; if (col->kind == GLP_CV) continue; xassert(col->kind == GLP_IV); if (!flag) xfprintf(fp, "Generals\n"), flag = 1, count++; xfprintf(fp, " %s\n", col_name(csa, j, name)), count++; } if (flag) xfprintf(fp, "\n"), count++; skip: /* write the end keyword */ xfprintf(fp, "End\n"), count++; xfflush(fp); if (xferror(fp)) { xprintf("Write error on `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } /* problem data has been successfully written */ xprintf("%d lines were written\n", count); ret = 0; done: if (fp != NULL) xfclose(fp); return ret; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpapi13.c0000644000076500000240000005445313524616144025176 0ustar tamasstaff00000000000000/* glpapi13.c (branch-and-bound interface routines) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glpios.h" /*********************************************************************** * NAME * * glp_ios_reason - determine reason for calling the callback routine * * SYNOPSIS * * glp_ios_reason(glp_tree *tree); * * RETURNS * * The routine glp_ios_reason returns a code, which indicates why the * user-defined callback routine is being called. */ int glp_ios_reason(glp_tree *tree) { return tree->reason; } /*********************************************************************** * NAME * * glp_ios_get_prob - access the problem object * * SYNOPSIS * * glp_prob *glp_ios_get_prob(glp_tree *tree); * * DESCRIPTION * * The routine glp_ios_get_prob can be called from the user-defined * callback routine to access the problem object, which is used by the * MIP solver. It is the original problem object passed to the routine * glp_intopt if the MIP presolver is not used; otherwise it is an * internal problem object built by the presolver. If the current * subproblem exists, LP segment of the problem object corresponds to * its LP relaxation. * * RETURNS * * The routine glp_ios_get_prob returns a pointer to the problem object * used by the MIP solver. */ glp_prob *glp_ios_get_prob(glp_tree *tree) { return tree->mip; } /*********************************************************************** * NAME * * glp_ios_tree_size - determine size of the branch-and-bound tree * * SYNOPSIS * * void glp_ios_tree_size(glp_tree *tree, int *a_cnt, int *n_cnt, * int *t_cnt); * * DESCRIPTION * * The routine glp_ios_tree_size stores the following three counts which * characterize the current size of the branch-and-bound tree: * * a_cnt is the current number of active nodes, i.e. the current size of * the active list; * * n_cnt is the current number of all (active and inactive) nodes; * * t_cnt is the total number of nodes including those which have been * already removed from the tree. This count is increased whenever * a new node appears in the tree and never decreased. * * If some of the parameters a_cnt, n_cnt, t_cnt is a null pointer, the * corresponding count is not stored. */ void glp_ios_tree_size(glp_tree *tree, int *a_cnt, int *n_cnt, int *t_cnt) { if (a_cnt != NULL) *a_cnt = tree->a_cnt; if (n_cnt != NULL) *n_cnt = tree->n_cnt; if (t_cnt != NULL) *t_cnt = tree->t_cnt; return; } /*********************************************************************** * NAME * * glp_ios_curr_node - determine current active subproblem * * SYNOPSIS * * int glp_ios_curr_node(glp_tree *tree); * * RETURNS * * The routine glp_ios_curr_node returns the reference number of the * current active subproblem. However, if the current subproblem does * not exist, the routine returns zero. */ int glp_ios_curr_node(glp_tree *tree) { IOSNPD *node; /* obtain pointer to the current subproblem */ node = tree->curr; /* return its reference number */ return node == NULL ? 0 : node->p; } /*********************************************************************** * NAME * * glp_ios_next_node - determine next active subproblem * * SYNOPSIS * * int glp_ios_next_node(glp_tree *tree, int p); * * RETURNS * * If the parameter p is zero, the routine glp_ios_next_node returns * the reference number of the first active subproblem. However, if the * tree is empty, zero is returned. * * If the parameter p is not zero, it must specify the reference number * of some active subproblem, in which case the routine returns the * reference number of the next active subproblem. However, if there is * no next active subproblem in the list, zero is returned. * * All subproblems in the active list are ordered chronologically, i.e. * subproblem A precedes subproblem B if A was created before B. */ int glp_ios_next_node(glp_tree *tree, int p) { IOSNPD *node; if (p == 0) { /* obtain pointer to the first active subproblem */ node = tree->head; } else { /* obtain pointer to the specified subproblem */ if (!(1 <= p && p <= tree->nslots)) err: xerror("glp_ios_next_node: p = %d; invalid subproblem refer" "ence number\n", p); node = tree->slot[p].node; if (node == NULL) goto err; /* the specified subproblem must be active */ if (node->count != 0) xerror("glp_ios_next_node: p = %d; subproblem not in the ac" "tive list\n", p); /* obtain pointer to the next active subproblem */ node = node->next; } /* return the reference number */ return node == NULL ? 0 : node->p; } /*********************************************************************** * NAME * * glp_ios_prev_node - determine previous active subproblem * * SYNOPSIS * * int glp_ios_prev_node(glp_tree *tree, int p); * * RETURNS * * If the parameter p is zero, the routine glp_ios_prev_node returns * the reference number of the last active subproblem. However, if the * tree is empty, zero is returned. * * If the parameter p is not zero, it must specify the reference number * of some active subproblem, in which case the routine returns the * reference number of the previous active subproblem. However, if there * is no previous active subproblem in the list, zero is returned. * * All subproblems in the active list are ordered chronologically, i.e. * subproblem A precedes subproblem B if A was created before B. */ int glp_ios_prev_node(glp_tree *tree, int p) { IOSNPD *node; if (p == 0) { /* obtain pointer to the last active subproblem */ node = tree->tail; } else { /* obtain pointer to the specified subproblem */ if (!(1 <= p && p <= tree->nslots)) err: xerror("glp_ios_prev_node: p = %d; invalid subproblem refer" "ence number\n", p); node = tree->slot[p].node; if (node == NULL) goto err; /* the specified subproblem must be active */ if (node->count != 0) xerror("glp_ios_prev_node: p = %d; subproblem not in the ac" "tive list\n", p); /* obtain pointer to the previous active subproblem */ node = node->prev; } /* return the reference number */ return node == NULL ? 0 : node->p; } /*********************************************************************** * NAME * * glp_ios_up_node - determine parent subproblem * * SYNOPSIS * * int glp_ios_up_node(glp_tree *tree, int p); * * RETURNS * * The parameter p must specify the reference number of some (active or * inactive) subproblem, in which case the routine iet_get_up_node * returns the reference number of its parent subproblem. However, if * the specified subproblem is the root of the tree and, therefore, has * no parent, the routine returns zero. */ int glp_ios_up_node(glp_tree *tree, int p) { IOSNPD *node; /* obtain pointer to the specified subproblem */ if (!(1 <= p && p <= tree->nslots)) err: xerror("glp_ios_up_node: p = %d; invalid subproblem reference " "number\n", p); node = tree->slot[p].node; if (node == NULL) goto err; /* obtain pointer to the parent subproblem */ node = node->up; /* return the reference number */ return node == NULL ? 0 : node->p; } /*********************************************************************** * NAME * * glp_ios_node_level - determine subproblem level * * SYNOPSIS * * int glp_ios_node_level(glp_tree *tree, int p); * * RETURNS * * The routine glp_ios_node_level returns the level of the subproblem, * whose reference number is p, in the branch-and-bound tree. (The root * subproblem has level 0, and the level of any other subproblem is the * level of its parent plus one.) */ int glp_ios_node_level(glp_tree *tree, int p) { IOSNPD *node; /* obtain pointer to the specified subproblem */ if (!(1 <= p && p <= tree->nslots)) err: xerror("glp_ios_node_level: p = %d; invalid subproblem referen" "ce number\n", p); node = tree->slot[p].node; if (node == NULL) goto err; /* return the node level */ return node->level; } /*********************************************************************** * NAME * * glp_ios_node_bound - determine subproblem local bound * * SYNOPSIS * * double glp_ios_node_bound(glp_tree *tree, int p); * * RETURNS * * The routine glp_ios_node_bound returns the local bound for (active or * inactive) subproblem, whose reference number is p. * * COMMENTS * * The local bound for subproblem p is an lower (minimization) or upper * (maximization) bound for integer optimal solution to this subproblem * (not to the original problem). This bound is local in the sense that * only subproblems in the subtree rooted at node p cannot have better * integer feasible solutions. * * On creating a subproblem (due to the branching step) its local bound * is inherited from its parent and then may get only stronger (never * weaker). For the root subproblem its local bound is initially set to * -DBL_MAX (minimization) or +DBL_MAX (maximization) and then improved * as the root LP relaxation has been solved. * * Note that the local bound is not necessarily the optimal objective * value to corresponding LP relaxation; it may be stronger. */ double glp_ios_node_bound(glp_tree *tree, int p) { IOSNPD *node; /* obtain pointer to the specified subproblem */ if (!(1 <= p && p <= tree->nslots)) err: xerror("glp_ios_node_bound: p = %d; invalid subproblem referen" "ce number\n", p); node = tree->slot[p].node; if (node == NULL) goto err; /* return the node local bound */ return node->bound; } /*********************************************************************** * NAME * * glp_ios_best_node - find active subproblem with best local bound * * SYNOPSIS * * int glp_ios_best_node(glp_tree *tree); * * RETURNS * * The routine glp_ios_best_node returns the reference number of the * active subproblem, whose local bound is best (i.e. smallest in case * of minimization or largest in case of maximization). However, if the * tree is empty, the routine returns zero. * * COMMENTS * * The best local bound is an lower (minimization) or upper * (maximization) bound for integer optimal solution to the original * MIP problem. */ int glp_ios_best_node(glp_tree *tree) { return ios_best_node(tree); } /*********************************************************************** * NAME * * glp_ios_mip_gap - compute relative MIP gap * * SYNOPSIS * * double glp_ios_mip_gap(glp_tree *tree); * * DESCRIPTION * * The routine glp_ios_mip_gap computes the relative MIP gap with the * following formula: * * gap = |best_mip - best_bnd| / (|best_mip| + DBL_EPSILON), * * where best_mip is the best integer feasible solution found so far, * best_bnd is the best (global) bound. If no integer feasible solution * has been found yet, gap is set to DBL_MAX. * * RETURNS * * The routine glp_ios_mip_gap returns the relative MIP gap. */ double glp_ios_mip_gap(glp_tree *tree) { return ios_relative_gap(tree); } /*********************************************************************** * NAME * * glp_ios_node_data - access subproblem application-specific data * * SYNOPSIS * * void *glp_ios_node_data(glp_tree *tree, int p); * * DESCRIPTION * * The routine glp_ios_node_data allows the application accessing a * memory block allocated for the subproblem (which may be active or * inactive), whose reference number is p. * * The size of the block is defined by the control parameter cb_size * passed to the routine glp_intopt. The block is initialized by binary * zeros on creating corresponding subproblem, and its contents is kept * until the subproblem will be removed from the tree. * * The application may use these memory blocks to store specific data * for each subproblem. * * RETURNS * * The routine glp_ios_node_data returns a pointer to the memory block * for the specified subproblem. Note that if cb_size = 0, the routine * returns a null pointer. */ void *glp_ios_node_data(glp_tree *tree, int p) { IOSNPD *node; /* obtain pointer to the specified subproblem */ if (!(1 <= p && p <= tree->nslots)) err: xerror("glp_ios_node_level: p = %d; invalid subproblem referen" "ce number\n", p); node = tree->slot[p].node; if (node == NULL) goto err; /* return pointer to the application-specific data */ return node->data; } /*********************************************************************** * NAME * * glp_ios_row_attr - retrieve additional row attributes * * SYNOPSIS * * void glp_ios_row_attr(glp_tree *tree, int i, glp_attr *attr); * * DESCRIPTION * * The routine glp_ios_row_attr retrieves additional attributes of row * i and stores them in the structure glp_attr. */ void glp_ios_row_attr(glp_tree *tree, int i, glp_attr *attr) { GLPROW *row; if (!(1 <= i && i <= tree->mip->m)) xerror("glp_ios_row_attr: i = %d; row number out of range\n", i); row = tree->mip->row[i]; attr->level = row->level; attr->origin = row->origin; attr->klass = row->klass; return; } /**********************************************************************/ int glp_ios_pool_size(glp_tree *tree) { /* determine current size of the cut pool */ if (tree->reason != GLP_ICUTGEN) xerror("glp_ios_pool_size: operation not allowed\n"); xassert(tree->local != NULL); return tree->local->size; } /**********************************************************************/ int glp_ios_add_row(glp_tree *tree, const char *name, int klass, int flags, int len, const int ind[], const double val[], int type, double rhs) { /* add row (constraint) to the cut pool */ int num; if (tree->reason != GLP_ICUTGEN) xerror("glp_ios_add_row: operation not allowed\n"); xassert(tree->local != NULL); num = ios_add_row(tree, tree->local, name, klass, flags, len, ind, val, type, rhs); return num; } /**********************************************************************/ void glp_ios_del_row(glp_tree *tree, int i) { /* remove row (constraint) from the cut pool */ if (tree->reason != GLP_ICUTGEN) xerror("glp_ios_del_row: operation not allowed\n"); ios_del_row(tree, tree->local, i); return; } /**********************************************************************/ void glp_ios_clear_pool(glp_tree *tree) { /* remove all rows (constraints) from the cut pool */ if (tree->reason != GLP_ICUTGEN) xerror("glp_ios_clear_pool: operation not allowed\n"); ios_clear_pool(tree, tree->local); return; } /*********************************************************************** * NAME * * glp_ios_can_branch - check if can branch upon specified variable * * SYNOPSIS * * int glp_ios_can_branch(glp_tree *tree, int j); * * RETURNS * * If j-th variable (column) can be used to branch upon, the routine * glp_ios_can_branch returns non-zero, otherwise zero. */ int glp_ios_can_branch(glp_tree *tree, int j) { if (!(1 <= j && j <= tree->mip->n)) xerror("glp_ios_can_branch: j = %d; column number out of range" "\n", j); return tree->non_int[j]; } /*********************************************************************** * NAME * * glp_ios_branch_upon - choose variable to branch upon * * SYNOPSIS * * void glp_ios_branch_upon(glp_tree *tree, int j, int sel); * * DESCRIPTION * * The routine glp_ios_branch_upon can be called from the user-defined * callback routine in response to the reason GLP_IBRANCH to choose a * branching variable, whose ordinal number is j. Should note that only * variables, for which the routine glp_ios_can_branch returns non-zero, * can be used to branch upon. * * The parameter sel is a flag that indicates which branch (subproblem) * should be selected next to continue the search: * * GLP_DN_BRNCH - select down-branch; * GLP_UP_BRNCH - select up-branch; * GLP_NO_BRNCH - use general selection technique. */ void glp_ios_branch_upon(glp_tree *tree, int j, int sel) { if (!(1 <= j && j <= tree->mip->n)) xerror("glp_ios_branch_upon: j = %d; column number out of rang" "e\n", j); if (!(sel == GLP_DN_BRNCH || sel == GLP_UP_BRNCH || sel == GLP_NO_BRNCH)) xerror("glp_ios_branch_upon: sel = %d: invalid branch selectio" "n flag\n", sel); if (!(tree->non_int[j])) xerror("glp_ios_branch_upon: j = %d; variable cannot be used t" "o branch upon\n", j); if (tree->br_var != 0) xerror("glp_ios_branch_upon: branching variable already chosen" "\n"); tree->br_var = j; tree->br_sel = sel; return; } /*********************************************************************** * NAME * * glp_ios_select_node - select subproblem to continue the search * * SYNOPSIS * * void glp_ios_select_node(glp_tree *tree, int p); * * DESCRIPTION * * The routine glp_ios_select_node can be called from the user-defined * callback routine in response to the reason GLP_ISELECT to select an * active subproblem, whose reference number is p. The search will be * continued from the subproblem selected. */ void glp_ios_select_node(glp_tree *tree, int p) { IOSNPD *node; /* obtain pointer to the specified subproblem */ if (!(1 <= p && p <= tree->nslots)) err: xerror("glp_ios_select_node: p = %d; invalid subproblem refere" "nce number\n", p); node = tree->slot[p].node; if (node == NULL) goto err; /* the specified subproblem must be active */ if (node->count != 0) xerror("glp_ios_select_node: p = %d; subproblem not in the act" "ive list\n", p); /* no subproblem must be selected yet */ if (tree->next_p != 0) xerror("glp_ios_select_node: subproblem already selected\n"); /* select the specified subproblem to continue the search */ tree->next_p = p; return; } /*********************************************************************** * NAME * * glp_ios_heur_sol - provide solution found by heuristic * * SYNOPSIS * * int glp_ios_heur_sol(glp_tree *tree, const double x[]); * * DESCRIPTION * * The routine glp_ios_heur_sol can be called from the user-defined * callback routine in response to the reason GLP_IHEUR to provide an * integer feasible solution found by a primal heuristic. * * Primal values of *all* variables (columns) found by the heuristic * should be placed in locations x[1], ..., x[n], where n is the number * of columns in the original problem object. Note that the routine * glp_ios_heur_sol *does not* check primal feasibility of the solution * provided. * * Using the solution passed in the array x the routine computes value * of the objective function. If the objective value is better than the * best known integer feasible solution, the routine computes values of * auxiliary variables (rows) and stores all solution components in the * problem object. * * RETURNS * * If the provided solution is accepted, the routine glp_ios_heur_sol * returns zero. Otherwise, if the provided solution is rejected, the * routine returns non-zero. */ int glp_ios_heur_sol(glp_tree *tree, const double x[]) { glp_prob *mip = tree->mip; int m = tree->orig_m; int n = tree->n; int i, j; double obj; xassert(mip->m >= m); xassert(mip->n == n); /* check values of integer variables and compute value of the objective function */ obj = mip->c0; for (j = 1; j <= n; j++) { GLPCOL *col = mip->col[j]; if (col->kind == GLP_IV) { /* provided value must be integral */ if (x[j] != floor(x[j])) return 1; } obj += col->coef * x[j]; } /* check if the provided solution is better than the best known integer feasible solution */ if (mip->mip_stat == GLP_FEAS) { switch (mip->dir) { case GLP_MIN: if (obj >= tree->mip->mip_obj) return 1; break; case GLP_MAX: if (obj <= tree->mip->mip_obj) return 1; break; default: xassert(mip != mip); } } /* it is better; store it in the problem object */ if (tree->parm->msg_lev >= GLP_MSG_ON) xprintf("Solution found by heuristic: %.12g\n", obj); mip->mip_stat = GLP_FEAS; mip->mip_obj = obj; for (j = 1; j <= n; j++) mip->col[j]->mipx = x[j]; for (i = 1; i <= m; i++) { GLPROW *row = mip->row[i]; GLPAIJ *aij; row->mipx = 0.0; for (aij = row->ptr; aij != NULL; aij = aij->r_next) row->mipx += aij->val * aij->col->mipx; } return 0; } /*********************************************************************** * NAME * * glp_ios_terminate - terminate the solution process. * * SYNOPSIS * * void glp_ios_terminate(glp_tree *tree); * * DESCRIPTION * * The routine glp_ios_terminate sets a flag indicating that the MIP * solver should prematurely terminate the search. */ void glp_ios_terminate(glp_tree *tree) { if (tree->parm->msg_lev >= GLP_MSG_DBG) xprintf("The search is prematurely terminated due to applicati" "on request\n"); tree->stop = 1; return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpapi17.c0000644000076500000240000010376713524616144025205 0ustar tamasstaff00000000000000/* glpapi17.c (flow network problems) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glpapi.h" #include "glpnet.h" /*********************************************************************** * NAME * * glp_mincost_lp - convert minimum cost flow problem to LP * * SYNOPSIS * * void glp_mincost_lp(glp_prob *lp, glp_graph *G, int names, * int v_rhs, int a_low, int a_cap, int a_cost); * * DESCRIPTION * * The routine glp_mincost_lp builds an LP problem, which corresponds * to the minimum cost flow problem on the specified network G. */ void glp_mincost_lp(glp_prob *lp, glp_graph *G, int names, int v_rhs, int a_low, int a_cap, int a_cost) { glp_vertex *v; glp_arc *a; int i, j, type, ind[1+2]; double rhs, low, cap, cost, val[1+2]; if (!(names == GLP_ON || names == GLP_OFF)) xerror("glp_mincost_lp: names = %d; invalid parameter\n", names); if (v_rhs >= 0 && v_rhs > G->v_size - (int)sizeof(double)) xerror("glp_mincost_lp: v_rhs = %d; invalid offset\n", v_rhs); if (a_low >= 0 && a_low > G->a_size - (int)sizeof(double)) xerror("glp_mincost_lp: a_low = %d; invalid offset\n", a_low); if (a_cap >= 0 && a_cap > G->a_size - (int)sizeof(double)) xerror("glp_mincost_lp: a_cap = %d; invalid offset\n", a_cap); if (a_cost >= 0 && a_cost > G->a_size - (int)sizeof(double)) xerror("glp_mincost_lp: a_cost = %d; invalid offset\n", a_cost) ; glp_erase_prob(lp); if (names) glp_set_prob_name(lp, G->name); if (G->nv > 0) glp_add_rows(lp, G->nv); for (i = 1; i <= G->nv; i++) { v = G->v[i]; if (names) glp_set_row_name(lp, i, v->name); if (v_rhs >= 0) memcpy(&rhs, (char *)v->data + v_rhs, sizeof(double)); else rhs = 0.0; glp_set_row_bnds(lp, i, GLP_FX, rhs, rhs); } if (G->na > 0) glp_add_cols(lp, G->na); for (i = 1, j = 0; i <= G->nv; i++) { v = G->v[i]; for (a = v->out; a != NULL; a = a->t_next) { j++; if (names) { char name[50+1]; sprintf(name, "x[%d,%d]", a->tail->i, a->head->i); xassert(strlen(name) < sizeof(name)); glp_set_col_name(lp, j, name); } if (a->tail->i != a->head->i) { ind[1] = a->tail->i, val[1] = +1.0; ind[2] = a->head->i, val[2] = -1.0; glp_set_mat_col(lp, j, 2, ind, val); } if (a_low >= 0) memcpy(&low, (char *)a->data + a_low, sizeof(double)); else low = 0.0; if (a_cap >= 0) memcpy(&cap, (char *)a->data + a_cap, sizeof(double)); else cap = 1.0; if (cap == DBL_MAX) type = GLP_LO; else if (low != cap) type = GLP_DB; else type = GLP_FX; glp_set_col_bnds(lp, j, type, low, cap); if (a_cost >= 0) memcpy(&cost, (char *)a->data + a_cost, sizeof(double)); else cost = 0.0; glp_set_obj_coef(lp, j, cost); } } xassert(j == G->na); return; } /**********************************************************************/ int glp_mincost_okalg(glp_graph *G, int v_rhs, int a_low, int a_cap, int a_cost, double *sol, int a_x, int v_pi) { /* find minimum-cost flow with out-of-kilter algorithm */ glp_vertex *v; glp_arc *a; int nv, na, i, k, s, t, *tail, *head, *low, *cap, *cost, *x, *pi, ret; double sum, temp; if (v_rhs >= 0 && v_rhs > G->v_size - (int)sizeof(double)) xerror("glp_mincost_okalg: v_rhs = %d; invalid offset\n", v_rhs); if (a_low >= 0 && a_low > G->a_size - (int)sizeof(double)) xerror("glp_mincost_okalg: a_low = %d; invalid offset\n", a_low); if (a_cap >= 0 && a_cap > G->a_size - (int)sizeof(double)) xerror("glp_mincost_okalg: a_cap = %d; invalid offset\n", a_cap); if (a_cost >= 0 && a_cost > G->a_size - (int)sizeof(double)) xerror("glp_mincost_okalg: a_cost = %d; invalid offset\n", a_cost); if (a_x >= 0 && a_x > G->a_size - (int)sizeof(double)) xerror("glp_mincost_okalg: a_x = %d; invalid offset\n", a_x); if (v_pi >= 0 && v_pi > G->v_size - (int)sizeof(double)) xerror("glp_mincost_okalg: v_pi = %d; invalid offset\n", v_pi); /* s is artificial source node */ s = G->nv + 1; /* t is artificial sink node */ t = s + 1; /* nv is the total number of nodes in the resulting network */ nv = t; /* na is the total number of arcs in the resulting network */ na = G->na + 1; for (i = 1; i <= G->nv; i++) { v = G->v[i]; if (v_rhs >= 0) memcpy(&temp, (char *)v->data + v_rhs, sizeof(double)); else temp = 0.0; if (temp != 0.0) na++; } /* allocate working arrays */ tail = xcalloc(1+na, sizeof(int)); head = xcalloc(1+na, sizeof(int)); low = xcalloc(1+na, sizeof(int)); cap = xcalloc(1+na, sizeof(int)); cost = xcalloc(1+na, sizeof(int)); x = xcalloc(1+na, sizeof(int)); pi = xcalloc(1+nv, sizeof(int)); /* construct the resulting network */ k = 0; /* (original arcs) */ for (i = 1; i <= G->nv; i++) { v = G->v[i]; for (a = v->out; a != NULL; a = a->t_next) { k++; tail[k] = a->tail->i; head[k] = a->head->i; if (tail[k] == head[k]) { ret = GLP_EDATA; goto done; } if (a_low >= 0) memcpy(&temp, (char *)a->data + a_low, sizeof(double)); else temp = 0.0; if (!(0.0 <= temp && temp <= (double)INT_MAX && temp == floor(temp))) { ret = GLP_EDATA; goto done; } low[k] = (int)temp; if (a_cap >= 0) memcpy(&temp, (char *)a->data + a_cap, sizeof(double)); else temp = 1.0; if (!((double)low[k] <= temp && temp <= (double)INT_MAX && temp == floor(temp))) { ret = GLP_EDATA; goto done; } cap[k] = (int)temp; if (a_cost >= 0) memcpy(&temp, (char *)a->data + a_cost, sizeof(double)); else temp = 0.0; if (!(fabs(temp) <= (double)INT_MAX && temp == floor(temp))) { ret = GLP_EDATA; goto done; } cost[k] = (int)temp; } } /* (artificial arcs) */ sum = 0.0; for (i = 1; i <= G->nv; i++) { v = G->v[i]; if (v_rhs >= 0) memcpy(&temp, (char *)v->data + v_rhs, sizeof(double)); else temp = 0.0; if (!(fabs(temp) <= (double)INT_MAX && temp == floor(temp))) { ret = GLP_EDATA; goto done; } if (temp > 0.0) { /* artificial arc from s to original source i */ k++; tail[k] = s; head[k] = i; low[k] = cap[k] = (int)(+temp); /* supply */ cost[k] = 0; sum += (double)temp; } else if (temp < 0.0) { /* artificial arc from original sink i to t */ k++; tail[k] = i; head[k] = t; low[k] = cap[k] = (int)(-temp); /* demand */ cost[k] = 0; } } /* (feedback arc from t to s) */ k++; xassert(k == na); tail[k] = t; head[k] = s; if (sum > (double)INT_MAX) { ret = GLP_EDATA; goto done; } low[k] = cap[k] = (int)sum; /* total supply/demand */ cost[k] = 0; /* find minimal-cost circulation in the resulting network */ ret = okalg(nv, na, tail, head, low, cap, cost, x, pi); switch (ret) { case 0: /* optimal circulation found */ ret = 0; break; case 1: /* no feasible circulation exists */ ret = GLP_ENOPFS; break; case 2: /* integer overflow occured */ ret = GLP_ERANGE; goto done; case 3: /* optimality test failed (logic error) */ ret = GLP_EFAIL; goto done; default: xassert(ret != ret); } /* store solution components */ /* (objective function = the total cost) */ if (sol != NULL) { temp = 0.0; for (k = 1; k <= na; k++) temp += (double)cost[k] * (double)x[k]; *sol = temp; } /* (arc flows) */ if (a_x >= 0) { k = 0; for (i = 1; i <= G->nv; i++) { v = G->v[i]; for (a = v->out; a != NULL; a = a->t_next) { temp = (double)x[++k]; memcpy((char *)a->data + a_x, &temp, sizeof(double)); } } } /* (node potentials = Lagrange multipliers) */ if (v_pi >= 0) { for (i = 1; i <= G->nv; i++) { v = G->v[i]; temp = - (double)pi[i]; memcpy((char *)v->data + v_pi, &temp, sizeof(double)); } } done: /* free working arrays */ xfree(tail); xfree(head); xfree(low); xfree(cap); xfree(cost); xfree(x); xfree(pi); return ret; } /*********************************************************************** * NAME * * glp_maxflow_lp - convert maximum flow problem to LP * * SYNOPSIS * * void glp_maxflow_lp(glp_prob *lp, glp_graph *G, int names, int s, * int t, int a_cap); * * DESCRIPTION * * The routine glp_maxflow_lp builds an LP problem, which corresponds * to the maximum flow problem on the specified network G. */ void glp_maxflow_lp(glp_prob *lp, glp_graph *G, int names, int s, int t, int a_cap) { glp_vertex *v; glp_arc *a; int i, j, type, ind[1+2]; double cap, val[1+2]; if (!(names == GLP_ON || names == GLP_OFF)) xerror("glp_maxflow_lp: names = %d; invalid parameter\n", names); if (!(1 <= s && s <= G->nv)) xerror("glp_maxflow_lp: s = %d; source node number out of rang" "e\n", s); if (!(1 <= t && t <= G->nv)) xerror("glp_maxflow_lp: t = %d: sink node number out of range " "\n", t); if (s == t) xerror("glp_maxflow_lp: s = t = %d; source and sink nodes must" " be distinct\n", s); if (a_cap >= 0 && a_cap > G->a_size - (int)sizeof(double)) xerror("glp_maxflow_lp: a_cap = %d; invalid offset\n", a_cap); glp_erase_prob(lp); if (names) glp_set_prob_name(lp, G->name); glp_set_obj_dir(lp, GLP_MAX); glp_add_rows(lp, G->nv); for (i = 1; i <= G->nv; i++) { v = G->v[i]; if (names) glp_set_row_name(lp, i, v->name); if (i == s) type = GLP_LO; else if (i == t) type = GLP_UP; else type = GLP_FX; glp_set_row_bnds(lp, i, type, 0.0, 0.0); } if (G->na > 0) glp_add_cols(lp, G->na); for (i = 1, j = 0; i <= G->nv; i++) { v = G->v[i]; for (a = v->out; a != NULL; a = a->t_next) { j++; if (names) { char name[50+1]; sprintf(name, "x[%d,%d]", a->tail->i, a->head->i); xassert(strlen(name) < sizeof(name)); glp_set_col_name(lp, j, name); } if (a->tail->i != a->head->i) { ind[1] = a->tail->i, val[1] = +1.0; ind[2] = a->head->i, val[2] = -1.0; glp_set_mat_col(lp, j, 2, ind, val); } if (a_cap >= 0) memcpy(&cap, (char *)a->data + a_cap, sizeof(double)); else cap = 1.0; if (cap == DBL_MAX) type = GLP_LO; else if (cap != 0.0) type = GLP_DB; else type = GLP_FX; glp_set_col_bnds(lp, j, type, 0.0, cap); if (a->tail->i == s) glp_set_obj_coef(lp, j, +1.0); else if (a->head->i == s) glp_set_obj_coef(lp, j, -1.0); } } xassert(j == G->na); return; } int glp_maxflow_ffalg(glp_graph *G, int s, int t, int a_cap, double *sol, int a_x, int v_cut) { /* find maximal flow with Ford-Fulkerson algorithm */ glp_vertex *v; glp_arc *a; int nv, na, i, k, flag, *tail, *head, *cap, *x, ret; char *cut; double temp; if (!(1 <= s && s <= G->nv)) xerror("glp_maxflow_ffalg: s = %d; source node number out of r" "ange\n", s); if (!(1 <= t && t <= G->nv)) xerror("glp_maxflow_ffalg: t = %d: sink node number out of ran" "ge\n", t); if (s == t) xerror("glp_maxflow_ffalg: s = t = %d; source and sink nodes m" "ust be distinct\n", s); if (a_cap >= 0 && a_cap > G->a_size - (int)sizeof(double)) xerror("glp_maxflow_ffalg: a_cap = %d; invalid offset\n", a_cap); if (v_cut >= 0 && v_cut > G->v_size - (int)sizeof(int)) xerror("glp_maxflow_ffalg: v_cut = %d; invalid offset\n", v_cut); /* allocate working arrays */ nv = G->nv; na = G->na; tail = xcalloc(1+na, sizeof(int)); head = xcalloc(1+na, sizeof(int)); cap = xcalloc(1+na, sizeof(int)); x = xcalloc(1+na, sizeof(int)); if (v_cut < 0) cut = NULL; else cut = xcalloc(1+nv, sizeof(char)); /* copy the flow network */ k = 0; for (i = 1; i <= G->nv; i++) { v = G->v[i]; for (a = v->out; a != NULL; a = a->t_next) { k++; tail[k] = a->tail->i; head[k] = a->head->i; if (tail[k] == head[k]) { ret = GLP_EDATA; goto done; } if (a_cap >= 0) memcpy(&temp, (char *)a->data + a_cap, sizeof(double)); else temp = 1.0; if (!(0.0 <= temp && temp <= (double)INT_MAX && temp == floor(temp))) { ret = GLP_EDATA; goto done; } cap[k] = (int)temp; } } xassert(k == na); /* find maximal flow in the flow network */ ffalg(nv, na, tail, head, s, t, cap, x, cut); ret = 0; /* store solution components */ /* (objective function = total flow through the network) */ if (sol != NULL) { temp = 0.0; for (k = 1; k <= na; k++) { if (tail[k] == s) temp += (double)x[k]; else if (head[k] == s) temp -= (double)x[k]; } *sol = temp; } /* (arc flows) */ if (a_x >= 0) { k = 0; for (i = 1; i <= G->nv; i++) { v = G->v[i]; for (a = v->out; a != NULL; a = a->t_next) { temp = (double)x[++k]; memcpy((char *)a->data + a_x, &temp, sizeof(double)); } } } /* (node flags) */ if (v_cut >= 0) { for (i = 1; i <= G->nv; i++) { v = G->v[i]; flag = cut[i]; memcpy((char *)v->data + v_cut, &flag, sizeof(int)); } } done: /* free working arrays */ xfree(tail); xfree(head); xfree(cap); xfree(x); if (cut != NULL) xfree(cut); return ret; } /*********************************************************************** * NAME * * glp_check_asnprob - check correctness of assignment problem data * * SYNOPSIS * * int glp_check_asnprob(glp_graph *G, int v_set); * * RETURNS * * If the specified assignment problem data are correct, the routine * glp_check_asnprob returns zero, otherwise, non-zero. */ int glp_check_asnprob(glp_graph *G, int v_set) { glp_vertex *v; int i, k, ret = 0; if (v_set >= 0 && v_set > G->v_size - (int)sizeof(int)) xerror("glp_check_asnprob: v_set = %d; invalid offset\n", v_set); for (i = 1; i <= G->nv; i++) { v = G->v[i]; if (v_set >= 0) { memcpy(&k, (char *)v->data + v_set, sizeof(int)); if (k == 0) { if (v->in != NULL) { ret = 1; break; } } else if (k == 1) { if (v->out != NULL) { ret = 2; break; } } else { ret = 3; break; } } else { if (v->in != NULL && v->out != NULL) { ret = 4; break; } } } return ret; } /*********************************************************************** * NAME * * glp_asnprob_lp - convert assignment problem to LP * * SYNOPSIS * * int glp_asnprob_lp(glp_prob *P, int form, glp_graph *G, int names, * int v_set, int a_cost); * * DESCRIPTION * * The routine glp_asnprob_lp builds an LP problem, which corresponds * to the assignment problem on the specified graph G. * * RETURNS * * If the LP problem has been successfully built, the routine returns * zero, otherwise, non-zero. */ int glp_asnprob_lp(glp_prob *P, int form, glp_graph *G, int names, int v_set, int a_cost) { glp_vertex *v; glp_arc *a; int i, j, ret, ind[1+2]; double cost, val[1+2]; if (!(form == GLP_ASN_MIN || form == GLP_ASN_MAX || form == GLP_ASN_MMP)) xerror("glp_asnprob_lp: form = %d; invalid parameter\n", form); if (!(names == GLP_ON || names == GLP_OFF)) xerror("glp_asnprob_lp: names = %d; invalid parameter\n", names); if (v_set >= 0 && v_set > G->v_size - (int)sizeof(int)) xerror("glp_asnprob_lp: v_set = %d; invalid offset\n", v_set); if (a_cost >= 0 && a_cost > G->a_size - (int)sizeof(double)) xerror("glp_asnprob_lp: a_cost = %d; invalid offset\n", a_cost); ret = glp_check_asnprob(G, v_set); if (ret != 0) goto done; glp_erase_prob(P); if (names) glp_set_prob_name(P, G->name); glp_set_obj_dir(P, form == GLP_ASN_MIN ? GLP_MIN : GLP_MAX); if (G->nv > 0) glp_add_rows(P, G->nv); for (i = 1; i <= G->nv; i++) { v = G->v[i]; if (names) glp_set_row_name(P, i, v->name); glp_set_row_bnds(P, i, form == GLP_ASN_MMP ? GLP_UP : GLP_FX, 1.0, 1.0); } if (G->na > 0) glp_add_cols(P, G->na); for (i = 1, j = 0; i <= G->nv; i++) { v = G->v[i]; for (a = v->out; a != NULL; a = a->t_next) { j++; if (names) { char name[50+1]; sprintf(name, "x[%d,%d]", a->tail->i, a->head->i); xassert(strlen(name) < sizeof(name)); glp_set_col_name(P, j, name); } ind[1] = a->tail->i, val[1] = +1.0; ind[2] = a->head->i, val[2] = +1.0; glp_set_mat_col(P, j, 2, ind, val); glp_set_col_bnds(P, j, GLP_DB, 0.0, 1.0); if (a_cost >= 0) memcpy(&cost, (char *)a->data + a_cost, sizeof(double)); else cost = 1.0; glp_set_obj_coef(P, j, cost); } } xassert(j == G->na); done: return ret; } /**********************************************************************/ int glp_asnprob_okalg(int form, glp_graph *G, int v_set, int a_cost, double *sol, int a_x) { /* solve assignment problem with out-of-kilter algorithm */ glp_vertex *v; glp_arc *a; int nv, na, i, k, *tail, *head, *low, *cap, *cost, *x, *pi, ret; double temp; if (!(form == GLP_ASN_MIN || form == GLP_ASN_MAX || form == GLP_ASN_MMP)) xerror("glp_asnprob_okalg: form = %d; invalid parameter\n", form); if (v_set >= 0 && v_set > G->v_size - (int)sizeof(int)) xerror("glp_asnprob_okalg: v_set = %d; invalid offset\n", v_set); if (a_cost >= 0 && a_cost > G->a_size - (int)sizeof(double)) xerror("glp_asnprob_okalg: a_cost = %d; invalid offset\n", a_cost); if (a_x >= 0 && a_x > G->a_size - (int)sizeof(int)) xerror("glp_asnprob_okalg: a_x = %d; invalid offset\n", a_x); if (glp_check_asnprob(G, v_set)) return GLP_EDATA; /* nv is the total number of nodes in the resulting network */ nv = G->nv + 1; /* na is the total number of arcs in the resulting network */ na = G->na + G->nv; /* allocate working arrays */ tail = xcalloc(1+na, sizeof(int)); head = xcalloc(1+na, sizeof(int)); low = xcalloc(1+na, sizeof(int)); cap = xcalloc(1+na, sizeof(int)); cost = xcalloc(1+na, sizeof(int)); x = xcalloc(1+na, sizeof(int)); pi = xcalloc(1+nv, sizeof(int)); /* construct the resulting network */ k = 0; /* (original arcs) */ for (i = 1; i <= G->nv; i++) { v = G->v[i]; for (a = v->out; a != NULL; a = a->t_next) { k++; tail[k] = a->tail->i; head[k] = a->head->i; low[k] = 0; cap[k] = 1; if (a_cost >= 0) memcpy(&temp, (char *)a->data + a_cost, sizeof(double)); else temp = 1.0; if (!(fabs(temp) <= (double)INT_MAX && temp == floor(temp))) { ret = GLP_EDATA; goto done; } cost[k] = (int)temp; if (form != GLP_ASN_MIN) cost[k] = - cost[k]; } } /* (artificial arcs) */ for (i = 1; i <= G->nv; i++) { v = G->v[i]; k++; if (v->out == NULL) tail[k] = i, head[k] = nv; else if (v->in == NULL) tail[k] = nv, head[k] = i; else xassert(v != v); low[k] = (form == GLP_ASN_MMP ? 0 : 1); cap[k] = 1; cost[k] = 0; } xassert(k == na); /* find minimal-cost circulation in the resulting network */ ret = okalg(nv, na, tail, head, low, cap, cost, x, pi); switch (ret) { case 0: /* optimal circulation found */ ret = 0; break; case 1: /* no feasible circulation exists */ ret = GLP_ENOPFS; break; case 2: /* integer overflow occured */ ret = GLP_ERANGE; goto done; case 3: /* optimality test failed (logic error) */ ret = GLP_EFAIL; goto done; default: xassert(ret != ret); } /* store solution components */ /* (objective function = the total cost) */ if (sol != NULL) { temp = 0.0; for (k = 1; k <= na; k++) temp += (double)cost[k] * (double)x[k]; if (form != GLP_ASN_MIN) temp = - temp; *sol = temp; } /* (arc flows) */ if (a_x >= 0) { k = 0; for (i = 1; i <= G->nv; i++) { v = G->v[i]; for (a = v->out; a != NULL; a = a->t_next) { k++; if (ret == 0) xassert(x[k] == 0 || x[k] == 1); memcpy((char *)a->data + a_x, &x[k], sizeof(int)); } } } done: /* free working arrays */ xfree(tail); xfree(head); xfree(low); xfree(cap); xfree(cost); xfree(x); xfree(pi); return ret; } /*********************************************************************** * NAME * * glp_asnprob_hall - find bipartite matching of maximum cardinality * * SYNOPSIS * * int glp_asnprob_hall(glp_graph *G, int v_set, int a_x); * * DESCRIPTION * * The routine glp_asnprob_hall finds a matching of maximal cardinality * in the specified bipartite graph G. It uses a version of the Fortran * routine MC21A developed by I.S.Duff [1], which implements Hall's * algorithm [2]. * * RETURNS * * The routine glp_asnprob_hall returns the cardinality of the matching * found. However, if the specified graph is incorrect (as detected by * the routine glp_check_asnprob), the routine returns negative value. * * REFERENCES * * 1. I.S.Duff, Algorithm 575: Permutations for zero-free diagonal, ACM * Trans. on Math. Softw. 7 (1981), 387-390. * * 2. M.Hall, "An Algorithm for distinct representatives," Amer. Math. * Monthly 63 (1956), 716-717. */ int glp_asnprob_hall(glp_graph *G, int v_set, int a_x) { glp_vertex *v; glp_arc *a; int card, i, k, loc, n, n1, n2, xij; int *num, *icn, *ip, *lenr, *iperm, *pr, *arp, *cv, *out; if (v_set >= 0 && v_set > G->v_size - (int)sizeof(int)) xerror("glp_asnprob_hall: v_set = %d; invalid offset\n", v_set); if (a_x >= 0 && a_x > G->a_size - (int)sizeof(int)) xerror("glp_asnprob_hall: a_x = %d; invalid offset\n", a_x); if (glp_check_asnprob(G, v_set)) return -1; /* determine the number of vertices in sets R and S and renumber vertices in S which correspond to columns of the matrix; skip all isolated vertices */ num = xcalloc(1+G->nv, sizeof(int)); n1 = n2 = 0; for (i = 1; i <= G->nv; i++) { v = G->v[i]; if (v->in == NULL && v->out != NULL) n1++, num[i] = 0; /* vertex in R */ else if (v->in != NULL && v->out == NULL) n2++, num[i] = n2; /* vertex in S */ else { xassert(v->in == NULL && v->out == NULL); num[i] = -1; /* isolated vertex */ } } /* the matrix must be square, thus, if it has more columns than rows, extra rows will be just empty, and vice versa */ n = (n1 >= n2 ? n1 : n2); /* allocate working arrays */ icn = xcalloc(1+G->na, sizeof(int)); ip = xcalloc(1+n, sizeof(int)); lenr = xcalloc(1+n, sizeof(int)); iperm = xcalloc(1+n, sizeof(int)); pr = xcalloc(1+n, sizeof(int)); arp = xcalloc(1+n, sizeof(int)); cv = xcalloc(1+n, sizeof(int)); out = xcalloc(1+n, sizeof(int)); /* build the adjacency matrix of the bipartite graph in row-wise format (rows are vertices in R, columns are vertices in S) */ k = 0, loc = 1; for (i = 1; i <= G->nv; i++) { if (num[i] != 0) continue; /* vertex i in R */ ip[++k] = loc; v = G->v[i]; for (a = v->out; a != NULL; a = a->t_next) { xassert(num[a->head->i] != 0); icn[loc++] = num[a->head->i]; } lenr[k] = loc - ip[k]; } xassert(loc-1 == G->na); /* make all extra rows empty (all extra columns are empty due to the row-wise format used) */ for (k++; k <= n; k++) ip[k] = loc, lenr[k] = 0; /* find a row permutation that maximizes the number of non-zeros on the main diagonal */ card = mc21a(n, icn, ip, lenr, iperm, pr, arp, cv, out); #if 1 /* 18/II-2010 */ /* FIXED: if card = n, arp remains clobbered on exit */ for (i = 1; i <= n; i++) arp[i] = 0; for (i = 1; i <= card; i++) { k = iperm[i]; xassert(1 <= k && k <= n); xassert(arp[k] == 0); arp[k] = i; } #endif /* store solution, if necessary */ if (a_x < 0) goto skip; k = 0; for (i = 1; i <= G->nv; i++) { if (num[i] != 0) continue; /* vertex i in R */ k++; v = G->v[i]; for (a = v->out; a != NULL; a = a->t_next) { /* arp[k] is the number of matched column or zero */ if (arp[k] == num[a->head->i]) { xassert(arp[k] != 0); xij = 1; } else xij = 0; memcpy((char *)a->data + a_x, &xij, sizeof(int)); } } skip: /* free working arrays */ xfree(num); xfree(icn); xfree(ip); xfree(lenr); xfree(iperm); xfree(pr); xfree(arp); xfree(cv); xfree(out); return card; } /*********************************************************************** * NAME * * glp_cpp - solve critical path problem * * SYNOPSIS * * double glp_cpp(glp_graph *G, int v_t, int v_es, int v_ls); * * DESCRIPTION * * The routine glp_cpp solves the critical path problem represented in * the form of the project network. * * The parameter G is a pointer to the graph object, which specifies * the project network. This graph must be acyclic. Multiple arcs are * allowed being considered as single arcs. * * The parameter v_t specifies an offset of the field of type double * in the vertex data block, which contains time t[i] >= 0 needed to * perform corresponding job j. If v_t < 0, it is assumed that t[i] = 1 * for all jobs. * * The parameter v_es specifies an offset of the field of type double * in the vertex data block, to which the routine stores earliest start * time for corresponding job. If v_es < 0, this time is not stored. * * The parameter v_ls specifies an offset of the field of type double * in the vertex data block, to which the routine stores latest start * time for corresponding job. If v_ls < 0, this time is not stored. * * RETURNS * * The routine glp_cpp returns the minimal project duration, that is, * minimal time needed to perform all jobs in the project. */ static void sorting(glp_graph *G, int list[]); double glp_cpp(glp_graph *G, int v_t, int v_es, int v_ls) { glp_vertex *v; glp_arc *a; int i, j, k, nv, *list; double temp, total, *t, *es, *ls; if (v_t >= 0 && v_t > G->v_size - (int)sizeof(double)) xerror("glp_cpp: v_t = %d; invalid offset\n", v_t); if (v_es >= 0 && v_es > G->v_size - (int)sizeof(double)) xerror("glp_cpp: v_es = %d; invalid offset\n", v_es); if (v_ls >= 0 && v_ls > G->v_size - (int)sizeof(double)) xerror("glp_cpp: v_ls = %d; invalid offset\n", v_ls); nv = G->nv; if (nv == 0) { total = 0.0; goto done; } /* allocate working arrays */ t = xcalloc(1+nv, sizeof(double)); es = xcalloc(1+nv, sizeof(double)); ls = xcalloc(1+nv, sizeof(double)); list = xcalloc(1+nv, sizeof(int)); /* retrieve job times */ for (i = 1; i <= nv; i++) { v = G->v[i]; if (v_t >= 0) { memcpy(&t[i], (char *)v->data + v_t, sizeof(double)); if (t[i] < 0.0) xerror("glp_cpp: t[%d] = %g; invalid time\n", i, t[i]); } else t[i] = 1.0; } /* perform topological sorting to determine the list of nodes (jobs) such that if list[k] = i and list[kk] = j and there exists arc (i->j), then k < kk */ sorting(G, list); /* FORWARD PASS */ /* determine earliest start times */ for (k = 1; k <= nv; k++) { j = list[k]; es[j] = 0.0; for (a = G->v[j]->in; a != NULL; a = a->h_next) { i = a->tail->i; /* there exists arc (i->j) in the project network */ temp = es[i] + t[i]; if (es[j] < temp) es[j] = temp; } } /* determine the minimal project duration */ total = 0.0; for (i = 1; i <= nv; i++) { temp = es[i] + t[i]; if (total < temp) total = temp; } /* BACKWARD PASS */ /* determine latest start times */ for (k = nv; k >= 1; k--) { i = list[k]; ls[i] = total - t[i]; for (a = G->v[i]->out; a != NULL; a = a->t_next) { j = a->head->i; /* there exists arc (i->j) in the project network */ temp = ls[j] - t[i]; if (ls[i] > temp) ls[i] = temp; } /* avoid possible round-off errors */ if (ls[i] < es[i]) ls[i] = es[i]; } /* store results, if necessary */ if (v_es >= 0) { for (i = 1; i <= nv; i++) { v = G->v[i]; memcpy((char *)v->data + v_es, &es[i], sizeof(double)); } } if (v_ls >= 0) { for (i = 1; i <= nv; i++) { v = G->v[i]; memcpy((char *)v->data + v_ls, &ls[i], sizeof(double)); } } /* free working arrays */ xfree(t); xfree(es); xfree(ls); xfree(list); done: return total; } static void sorting(glp_graph *G, int list[]) { /* perform topological sorting to determine the list of nodes (jobs) such that if list[k] = i and list[kk] = j and there exists arc (i->j), then k < kk */ int i, k, nv, v_size, *num; void **save; nv = G->nv; v_size = G->v_size; save = xcalloc(1+nv, sizeof(void *)); num = xcalloc(1+nv, sizeof(int)); G->v_size = sizeof(int); for (i = 1; i <= nv; i++) { save[i] = G->v[i]->data; G->v[i]->data = &num[i]; list[i] = 0; } if (glp_top_sort(G, 0) != 0) xerror("glp_cpp: project network is not acyclic\n"); G->v_size = v_size; for (i = 1; i <= nv; i++) { G->v[i]->data = save[i]; k = num[i]; xassert(1 <= k && k <= nv); xassert(list[k] == 0); list[k] = i; } xfree(save); xfree(num); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/COPYING0000644000076500000240000010451513524616144024440 0ustar tamasstaff00000000000000 GNU GENERAL PUBLIC LICENSE Version 3, 29 June 2007 Copyright (C) 2007 Free Software Foundation, Inc. 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But first, please read . python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpsdf.c0000644000076500000240000001610213524616144025022 0ustar tamasstaff00000000000000/* glpsdf.c (plain data file reading routines) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wshorten-64-to-32" #endif #define GLPSDF_H #define GLP_DATA_DEFINED typedef struct glp_data glp_data; #include "glpapi.h" struct glp_data { /* plain data file */ char *fname; /* name of data file */ XFILE *fp; /* stream assigned to data file */ void *jump; /* jmp_buf jump; */ /* label for go to in case of error */ int count; /* line count */ int c; /* current character of XEOF */ char item[255+1]; /* current data item */ }; static void next_char(glp_data *data); glp_data *glp_sdf_open_file(const char *fname) { /* open plain data file */ glp_data *data = NULL; XFILE *fp; jmp_buf jump; fp = xfopen(fname, "r"); if (fp == NULL) { xprintf("Unable to open `%s' - %s\n", fname, xerrmsg()); goto done; } data = xmalloc(sizeof(glp_data)); data->fname = xmalloc(strlen(fname)+1); strcpy(data->fname, fname); data->fp = fp; data->jump = NULL; data->count = 0; data->c = '\n'; data->item[0] = '\0'; /* read the very first character */ if (setjmp(jump)) { glp_sdf_close_file(data); data = NULL; goto done; } data->jump = jump; next_char(data); data->jump = NULL; done: return data; } void glp_sdf_set_jump(glp_data *data, void *jump) { /* set up error handling */ data->jump = jump; return; } void glp_sdf_error(glp_data *data, const char *fmt, ...) { /* print error message */ va_list arg; xprintf("%s:%d: ", data->fname, data->count); va_start(arg, fmt); xvprintf(fmt, arg); va_end(arg); if (data->jump == NULL) xerror(""); else longjmp(data->jump, 1); /* no return */ } void glp_sdf_warning(glp_data *data, const char *fmt, ...) { /* print warning message */ va_list arg; xprintf("%s:%d: warning: ", data->fname, data->count); va_start(arg, fmt); xvprintf(fmt, arg); va_end(arg); return; } static void next_char(glp_data *data) { /* read next character */ int c; if (data->c == XEOF) glp_sdf_error(data, "unexpected end of file\n"); else if (data->c == '\n') data->count++; c = xfgetc(data->fp); if (c < 0) { if (xferror(data->fp)) glp_sdf_error(data, "read error - %s\n", xerrmsg()); else if (data->c == '\n') c = XEOF; else { glp_sdf_warning(data, "missing final end of line\n"); c = '\n'; } } else if (c == '\n') ; else if (isspace(c)) c = ' '; else if (iscntrl(c)) glp_sdf_error(data, "invalid control character 0x%02X\n", c); data->c = c; return; } static void skip_pad(glp_data *data) { /* skip uninteresting characters and comments */ loop: while (data->c == ' ' || data->c == '\n') next_char(data); if (data->c == '/') { next_char(data); if (data->c != '*') glp_sdf_error(data, "invalid use of slash\n"); next_char(data); for (;;) { if (data->c == '*') { next_char(data); if (data->c == '/') { next_char(data); break; } } next_char(data); } goto loop; } return; } static void next_item(glp_data *data) { /* read next item */ int len; skip_pad(data); len = 0; while (!(data->c == ' ' || data->c == '\n')) { data->item[len++] = (char)data->c; if (len == sizeof(data->item)) glp_sdf_error(data, "data item `%.31s...' too long\n", data->item); next_char(data); } data->item[len] = '\0'; return; } int glp_sdf_read_int(glp_data *data) { /* read integer number */ int x; next_item(data); switch (str2int(data->item, &x)) { case 0: break; case 1: glp_sdf_error(data, "integer `%s' out of range\n", data->item); case 2: glp_sdf_error(data, "cannot convert `%s' to integer\n", data->item); default: xassert(data != data); } return x; } double glp_sdf_read_num(glp_data *data) { /* read floating-point number */ double x; next_item(data); switch (str2num(data->item, &x)) { case 0: break; case 1: glp_sdf_error(data, "number `%s' out of range\n", data->item); case 2: glp_sdf_error(data, "cannot convert `%s' to number\n", data->item); default: xassert(data != data); } return x; } const char *glp_sdf_read_item(glp_data *data) { /* read data item */ next_item(data); return data->item; } const char *glp_sdf_read_text(glp_data *data) { /* read text until end of line */ int c, len = 0; for (;;) { c = data->c; next_char(data); if (c == ' ') { /* ignore initial spaces */ if (len == 0) continue; /* and multiple ones */ if (data->item[len-1] == ' ') continue; } else if (c == '\n') { /* remove trailing space */ if (len > 0 && data->item[len-1] == ' ') len--; /* and stop reading */ break; } /* add current character to the buffer */ data->item[len++] = (char)c; if (len == sizeof(data->item)) glp_sdf_error(data, "line too long\n", data->item); } data->item[len] = '\0'; return data->item; } int glp_sdf_line(glp_data *data) { /* determine current line number */ return data->count; } void glp_sdf_close_file(glp_data *data) { /* close plain data file */ xfclose(data->fp); xfree(data->fname); xfree(data); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpdmp.h0000644000076500000240000000522613524616144025040 0ustar tamasstaff00000000000000/* glpdmp.h (dynamic memory pool) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPDMP_H #define GLPDMP_H #include "glpenv.h" typedef struct DMP DMP; #define DMP_BLK_SIZE 8000 /* size of memory blocks, in bytes, allocated for memory pools */ struct DMP { /* dynamic memory pool */ #if 0 int size; /* size of atoms, in bytes, 1 <= size <= 256; if size = 0, atoms may have different sizes */ #endif void *avail[32]; /* avail[k], 0 <= k <= 31, is a pointer to the first available (free) cell of (k+1)*8 bytes long; in the beginning of each free cell there is a pointer to another free cell of the same length */ void *block; /* pointer to the most recently allocated memory block; in the beginning of each allocated memory block there is a pointer to the previously allocated memory block */ int used; /* number of bytes used in the most recently allocated memory block */ glp_long count; /* number of atoms which are currently in use */ }; #define dmp_create_pool _glp_dmp_create_pool DMP *dmp_create_pool(void); /* create dynamic memory pool */ #define dmp_get_atom _glp_dmp_get_atom void *dmp_get_atom(DMP *pool, int size); /* get free atom from dynamic memory pool */ #define dmp_free_atom _glp_dmp_free_atom void dmp_free_atom(DMP *pool, void *atom, int size); /* return atom to dynamic memory pool */ #define dmp_in_use _glp_dmp_in_use glp_long dmp_in_use(DMP *pool); /* determine how many atoms are still in use */ #define dmp_delete_pool _glp_dmp_delete_pool void dmp_delete_pool(DMP *pool); /* delete dynamic memory pool */ #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpios04.c0000644000076500000240000001675613524616144025223 0ustar tamasstaff00000000000000/* glpios04.c (operations on sparse vectors) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wsign-conversion" #endif #include "glpios.h" /*********************************************************************** * NAME * * ios_create_vec - create sparse vector * * SYNOPSIS * * #include "glpios.h" * IOSVEC *ios_create_vec(int n); * * DESCRIPTION * * The routine ios_create_vec creates a sparse vector of dimension n, * which initially is a null vector. * * RETURNS * * The routine returns a pointer to the vector created. */ IOSVEC *ios_create_vec(int n) { IOSVEC *v; xassert(n >= 0); v = xmalloc(sizeof(IOSVEC)); v->n = n; v->nnz = 0; v->pos = xcalloc(1+n, sizeof(int)); memset(&v->pos[1], 0, n * sizeof(int)); v->ind = xcalloc(1+n, sizeof(int)); v->val = xcalloc(1+n, sizeof(double)); return v; } /*********************************************************************** * NAME * * ios_check_vec - check that sparse vector has correct representation * * SYNOPSIS * * #include "glpios.h" * void ios_check_vec(IOSVEC *v); * * DESCRIPTION * * The routine ios_check_vec checks that a sparse vector specified by * the parameter v has correct representation. * * NOTE * * Complexity of this operation is O(n). */ void ios_check_vec(IOSVEC *v) { int j, k, nnz; xassert(v->n >= 0); nnz = 0; for (j = v->n; j >= 1; j--) { k = v->pos[j]; xassert(0 <= k && k <= v->nnz); if (k != 0) { xassert(v->ind[k] == j); nnz++; } } xassert(v->nnz == nnz); return; } /*********************************************************************** * NAME * * ios_get_vj - retrieve component of sparse vector * * SYNOPSIS * * #include "glpios.h" * double ios_get_vj(IOSVEC *v, int j); * * RETURNS * * The routine ios_get_vj returns j-th component of a sparse vector * specified by the parameter v. */ double ios_get_vj(IOSVEC *v, int j) { int k; xassert(1 <= j && j <= v->n); k = v->pos[j]; xassert(0 <= k && k <= v->nnz); return (k == 0 ? 0.0 : v->val[k]); } /*********************************************************************** * NAME * * ios_set_vj - set/change component of sparse vector * * SYNOPSIS * * #include "glpios.h" * void ios_set_vj(IOSVEC *v, int j, double val); * * DESCRIPTION * * The routine ios_set_vj assigns val to j-th component of a sparse * vector specified by the parameter v. */ void ios_set_vj(IOSVEC *v, int j, double val) { int k; xassert(1 <= j && j <= v->n); k = v->pos[j]; if (val == 0.0) { if (k != 0) { /* remove j-th component */ v->pos[j] = 0; if (k < v->nnz) { v->pos[v->ind[v->nnz]] = k; v->ind[k] = v->ind[v->nnz]; v->val[k] = v->val[v->nnz]; } v->nnz--; } } else { if (k == 0) { /* create j-th component */ k = ++(v->nnz); v->pos[j] = k; v->ind[k] = j; } v->val[k] = val; } return; } /*********************************************************************** * NAME * * ios_clear_vec - set all components of sparse vector to zero * * SYNOPSIS * * #include "glpios.h" * void ios_clear_vec(IOSVEC *v); * * DESCRIPTION * * The routine ios_clear_vec sets all components of a sparse vector * specified by the parameter v to zero. */ void ios_clear_vec(IOSVEC *v) { int k; for (k = 1; k <= v->nnz; k++) v->pos[v->ind[k]] = 0; v->nnz = 0; return; } /*********************************************************************** * NAME * * ios_clean_vec - remove zero or small components from sparse vector * * SYNOPSIS * * #include "glpios.h" * void ios_clean_vec(IOSVEC *v, double eps); * * DESCRIPTION * * The routine ios_clean_vec removes zero components and components * whose magnitude is less than eps from a sparse vector specified by * the parameter v. If eps is 0.0, only zero components are removed. */ void ios_clean_vec(IOSVEC *v, double eps) { int k, nnz; nnz = 0; for (k = 1; k <= v->nnz; k++) { if (fabs(v->val[k]) == 0.0 || fabs(v->val[k]) < eps) { /* remove component */ v->pos[v->ind[k]] = 0; } else { /* keep component */ nnz++; v->pos[v->ind[k]] = nnz; v->ind[nnz] = v->ind[k]; v->val[nnz] = v->val[k]; } } v->nnz = nnz; return; } /*********************************************************************** * NAME * * ios_copy_vec - copy sparse vector (x := y) * * SYNOPSIS * * #include "glpios.h" * void ios_copy_vec(IOSVEC *x, IOSVEC *y); * * DESCRIPTION * * The routine ios_copy_vec copies a sparse vector specified by the * parameter y to a sparse vector specified by the parameter x. */ void ios_copy_vec(IOSVEC *x, IOSVEC *y) { int j; xassert(x != y); xassert(x->n == y->n); ios_clear_vec(x); x->nnz = y->nnz; memcpy(&x->ind[1], &y->ind[1], x->nnz * sizeof(int)); memcpy(&x->val[1], &y->val[1], x->nnz * sizeof(double)); for (j = 1; j <= x->nnz; j++) x->pos[x->ind[j]] = j; return; } /*********************************************************************** * NAME * * ios_linear_comb - compute linear combination (x := x + a * y) * * SYNOPSIS * * #include "glpios.h" * void ios_linear_comb(IOSVEC *x, double a, IOSVEC *y); * * DESCRIPTION * * The routine ios_linear_comb computes the linear combination * * x := x + a * y, * * where x and y are sparse vectors, a is a scalar. */ void ios_linear_comb(IOSVEC *x, double a, IOSVEC *y) { int j, k; double xj, yj; xassert(x != y); xassert(x->n == y->n); for (k = 1; k <= y->nnz; k++) { j = y->ind[k]; xj = ios_get_vj(x, j); yj = y->val[k]; ios_set_vj(x, j, xj + a * yj); } return; } /*********************************************************************** * NAME * * ios_delete_vec - delete sparse vector * * SYNOPSIS * * #include "glpios.h" * void ios_delete_vec(IOSVEC *v); * * DESCRIPTION * * The routine ios_delete_vec deletes a sparse vector specified by the * parameter v freeing all the memory allocated to this object. */ void ios_delete_vec(IOSVEC *v) { /* delete sparse vector */ xfree(v->pos); xfree(v->ind); xfree(v->val); xfree(v); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpmps.c0000644000076500000240000013355213524616144025056 0ustar tamasstaff00000000000000/* glpmps.c (MPS format routines) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wlogical-op-parentheses" #pragma clang diagnostic ignored "-Wself-assign" #pragma clang diagnostic ignored "-Wsometimes-uninitialized" #endif #include "glpapi.h" /*********************************************************************** * NAME * * glp_init_mpscp - initialize MPS format control parameters * * SYNOPSIS * * void glp_init_mpscp(glp_mpscp *parm); * * DESCRIPTION * * The routine glp_init_mpscp initializes control parameters, which are * used by the MPS input/output routines glp_read_mps and glp_write_mps, * with default values. * * Default values of the control parameters are stored in the glp_mpscp * structure, which the parameter parm points to. */ void glp_init_mpscp(glp_mpscp *parm) { parm->blank = '\0'; parm->obj_name = NULL; parm->tol_mps = 1e-12; return; } static void check_parm(const char *func, const glp_mpscp *parm) { /* check control parameters */ if (!(0x00 <= parm->blank && parm->blank <= 0xFF) || !(parm->blank == '\0' || isprint(parm->blank))) xerror("%s: blank = 0x%02X; invalid parameter\n", func, parm->blank); if (!(parm->obj_name == NULL || strlen(parm->obj_name) <= 255)) xerror("%s: obj_name = \"%.12s...\"; parameter too long\n", func, parm->obj_name); if (!(0.0 <= parm->tol_mps && parm->tol_mps < 1.0)) xerror("%s: tol_mps = %g; invalid parameter\n", func, parm->tol_mps); return; } /*********************************************************************** * NAME * * glp_read_mps - read problem data in MPS format * * SYNOPSIS * * int glp_read_mps(glp_prob *P, int fmt, const glp_mpscp *parm, * const char *fname); * * DESCRIPTION * * The routine glp_read_mps reads problem data in MPS format from a * text file. * * The parameter fmt specifies the version of MPS format: * * GLP_MPS_DECK - fixed (ancient) MPS format; * GLP_MPS_FILE - free (modern) MPS format. * * The parameter parm is a pointer to the structure glp_mpscp, which * specifies control parameters used by the routine. If parm is NULL, * the routine uses default settings. * * The character string fname specifies a name of the text file to be * read. * * Note that before reading data the current content of the problem * object is completely erased with the routine glp_erase_prob. * * RETURNS * * If the operation was successful, the routine glp_read_mps returns * zero. Otherwise, it prints an error message and returns non-zero. */ struct csa { /* common storage area */ glp_prob *P; /* pointer to problem object */ int deck; /* MPS format (0 - free, 1 - fixed) */ const glp_mpscp *parm; /* pointer to control parameters */ const char *fname; /* name of input MPS file */ XFILE *fp; /* stream assigned to input MPS file */ jmp_buf jump; /* label for go to in case of error */ int recno; /* current record (card) number */ int recpos; /* current record (card) position */ int c; /* current character */ int fldno; /* current field number */ char field[255+1]; /* current field content */ int w80; /* warning 'record must not be longer than 80 chars' issued */ int wef; /* warning 'extra fields detected beyond field 6' issued */ int obj_row; /* objective row number */ void *work1, *work2, *work3; /* working arrays */ }; static void error(struct csa *csa, const char *fmt, ...) { /* print error message and terminate processing */ va_list arg; xprintf("%s:%d: ", csa->fname, csa->recno); va_start(arg, fmt); xvprintf(fmt, arg); va_end(arg); longjmp(csa->jump, 1); /* no return */ } static void warning(struct csa *csa, const char *fmt, ...) { /* print warning message and continue processing */ va_list arg; xprintf("%s:%d: warning: ", csa->fname, csa->recno); va_start(arg, fmt); xvprintf(fmt, arg); va_end(arg); return; } static void read_char(struct csa *csa) { /* read next character */ int c; if (csa->c == '\n') csa->recno++, csa->recpos = 0; csa->recpos++; read: c = xfgetc(csa->fp); if (c < 0) { if (xferror(csa->fp)) error(csa, "read error - %s\n", xerrmsg()); else if (csa->c == '\n') error(csa, "unexpected end of file\n"); else { warning(csa, "missing final end of line\n"); c = '\n'; } } else if (c == '\n') ; else if (csa->c == '\r') { c = '\r'; goto badc; } else if (csa->deck && c == '\r') { csa->c = '\r'; goto read; } else if (c == ' ') ; else if (isspace(c)) { if (csa->deck) badc: error(csa, "in fixed MPS format white-space character 0x%02" "X is not allowed\n", c); c = ' '; } else if (iscntrl(c)) error(csa, "invalid control character 0x%02X\n", c); if (csa->deck && csa->recpos == 81 && c != '\n' && csa->w80 < 1) { warning(csa, "in fixed MPS format record must not be longer th" "an 80 characters\n"); csa->w80++; } csa->c = c; return; } static int indicator(struct csa *csa, int name) { /* skip comment records and read possible indicator record */ int ret; /* reset current field number */ csa->fldno = 0; loop: /* read the very first character of the next record */ xassert(csa->c == '\n'); read_char(csa); if (csa->c == ' ' || csa->c == '\n') { /* data record */ ret = 0; } else if (csa->c == '*') { /* comment record */ while (csa->c != '\n') read_char(csa); goto loop; } else { /* indicator record */ int len = 0; while (csa->c != ' ' && csa->c != '\n' && len < 12) { csa->field[len++] = (char)csa->c; read_char(csa); } csa->field[len] = '\0'; if (!(strcmp(csa->field, "NAME") == 0 || strcmp(csa->field, "ROWS") == 0 || strcmp(csa->field, "COLUMNS") == 0 || strcmp(csa->field, "RHS") == 0 || strcmp(csa->field, "RANGES") == 0 || strcmp(csa->field, "BOUNDS") == 0 || strcmp(csa->field, "ENDATA") == 0)) error(csa, "invalid indicator record\n"); if (!name) { while (csa->c != '\n') read_char(csa); } ret = 1; } return ret; } static void read_field(struct csa *csa) { /* read next field of the current data record */ csa->fldno++; if (csa->deck) { /* fixed MPS format */ int beg, end, pos; /* determine predefined field positions */ if (csa->fldno == 1) beg = 2, end = 3; else if (csa->fldno == 2) beg = 5, end = 12; else if (csa->fldno == 3) beg = 15, end = 22; else if (csa->fldno == 4) beg = 25, end = 36; else if (csa->fldno == 5) beg = 40, end = 47; else if (csa->fldno == 6) beg = 50, end = 61; else xassert(csa != csa); /* skip blanks preceding the current field */ if (csa->c != '\n') { pos = csa->recpos; while (csa->recpos < beg) { if (csa->c == ' ') ; else if (csa->c == '\n') break; else error(csa, "in fixed MPS format positions %d-%d must " "be blank\n", pos, beg-1); read_char(csa); } } /* skip possible comment beginning in the field 3 or 5 */ if ((csa->fldno == 3 || csa->fldno == 5) && csa->c == '$') { while (csa->c != '\n') read_char(csa); } /* read the current field */ for (pos = beg; pos <= end; pos++) { if (csa->c == '\n') break; csa->field[pos-beg] = (char)csa->c; read_char(csa); } csa->field[pos-beg] = '\0'; strtrim(csa->field); /* skip blanks following the last field */ if (csa->fldno == 6 && csa->c != '\n') { while (csa->recpos <= 72) { if (csa->c == ' ') ; else if (csa->c == '\n') break; else error(csa, "in fixed MPS format positions 62-72 must " "be blank\n"); read_char(csa); } while (csa->c != '\n') read_char(csa); } } else { /* free MPS format */ int len; /* skip blanks preceding the current field */ while (csa->c == ' ') read_char(csa); /* skip possible comment */ if (csa->c == '$') { while (csa->c != '\n') read_char(csa); } /* read the current field */ len = 0; while (!(csa->c == ' ' || csa->c == '\n')) { if (len == 255) error(csa, "length of field %d exceeds 255 characters\n", csa->fldno++); csa->field[len++] = (char)csa->c; read_char(csa); } csa->field[len] = '\0'; /* skip anything following the last field (any extra fields are considered to be comments) */ if (csa->fldno == 6) { while (csa->c == ' ') read_char(csa); if (csa->c != '$' && csa->c != '\n' && csa->wef < 1) { warning(csa, "some extra field(s) detected beyond field " "6; field(s) ignored\n"); csa->wef++; } while (csa->c != '\n') read_char(csa); } } return; } static void patch_name(struct csa *csa, char *name) { /* process embedded blanks in symbolic name */ int blank = csa->parm->blank; if (blank == '\0') { /* remove emedded blanks */ strspx(name); } else { /* replace embedded blanks by specified character */ for (; *name != '\0'; name++) if (*name == ' ') *name = (char)blank; } return; } static double read_number(struct csa *csa) { /* read next field and convert it to floating-point number */ double x; char *s; /* read next field */ read_field(csa); xassert(csa->fldno == 4 || csa->fldno == 6); if (csa->field[0] == '\0') error(csa, "missing numeric value in field %d\n", csa->fldno); /* skip initial spaces of the field */ for (s = csa->field; *s == ' '; s++); /* perform conversion */ if (str2num(s, &x) != 0) error(csa, "cannot convert `%s' to floating-point number\n", s); return x; } static void skip_field(struct csa *csa) { /* read and skip next field (assumed to be blank) */ read_field(csa); if (csa->field[0] != '\0') error(csa, "field %d must be blank\n", csa->fldno); return; } static void read_name(struct csa *csa) { /* read NAME indicator record */ if (!(indicator(csa, 1) && strcmp(csa->field, "NAME") == 0)) error(csa, "missing NAME indicator record\n"); /* this indicator record looks like a data record; simulate that fields 1 and 2 were read */ csa->fldno = 2; /* field 3: model name */ read_field(csa), patch_name(csa, csa->field); if (csa->field[0] == '\0') warning(csa, "missing model name in field 3\n"); else glp_set_prob_name(csa->P, csa->field); /* skip anything following field 3 */ while (csa->c != '\n') read_char(csa); return; } static void read_rows(struct csa *csa) { /* read ROWS section */ int i, type; loop: if (indicator(csa, 0)) goto done; /* field 1: row type */ read_field(csa), strspx(csa->field); if (strcmp(csa->field, "N") == 0) type = GLP_FR; else if (strcmp(csa->field, "G") == 0) type = GLP_LO; else if (strcmp(csa->field, "L") == 0) type = GLP_UP; else if (strcmp(csa->field, "E") == 0) type = GLP_FX; else if (csa->field[0] == '\0') error(csa, "missing row type in field 1\n"); else error(csa, "invalid row type in field 1\n"); /* field 2: row name */ read_field(csa), patch_name(csa, csa->field); if (csa->field[0] == '\0') error(csa, "missing row name in field 2\n"); if (glp_find_row(csa->P, csa->field) != 0) error(csa, "row `%s' multiply specified\n", csa->field); i = glp_add_rows(csa->P, 1); glp_set_row_name(csa->P, i, csa->field); glp_set_row_bnds(csa->P, i, type, 0.0, 0.0); /* fields 3, 4, 5, and 6 must be blank */ skip_field(csa); skip_field(csa); skip_field(csa); skip_field(csa); goto loop; done: return; } static void read_columns(struct csa *csa) { /* read COLUMNS section */ int i, j, f, len, kind = GLP_CV, *ind; double aij, *val; char name[255+1], *flag; /* allocate working arrays */ csa->work1 = ind = xcalloc(1+csa->P->m, sizeof(int)); csa->work2 = val = xcalloc(1+csa->P->m, sizeof(double)); csa->work3 = flag = xcalloc(1+csa->P->m, sizeof(char)); memset(&flag[1], 0, csa->P->m); /* no current column exists */ j = 0, len = 0; loop: if (indicator(csa, 0)) goto done; /* field 1 must be blank */ if (csa->deck) { read_field(csa); if (csa->field[0] != '\0') error(csa, "field 1 must be blank\n"); } else csa->fldno++; /* field 2: column or kind name */ read_field(csa), patch_name(csa, csa->field); strcpy(name, csa->field); /* field 3: row name or keyword 'MARKER' */ read_field(csa), patch_name(csa, csa->field); if (strcmp(csa->field, "'MARKER'") == 0) { /* process kind data record */ /* field 4 must be blank */ if (csa->deck) { read_field(csa); if (csa->field[0] != '\0') error(csa, "field 4 must be blank\n"); } else csa->fldno++; /* field 5: keyword 'INTORG' or 'INTEND' */ read_field(csa), patch_name(csa, csa->field); if (strcmp(csa->field, "'INTORG'") == 0) kind = GLP_IV; else if (strcmp(csa->field, "'INTEND'") == 0) kind = GLP_CV; else if (csa->field[0] == '\0') error(csa, "missing keyword in field 5\n"); else error(csa, "invalid keyword in field 5\n"); /* field 6 must be blank */ skip_field(csa); goto loop; } /* process column name specified in field 2 */ if (name[0] == '\0') { /* the same column as in previous data record */ if (j == 0) error(csa, "missing column name in field 2\n"); } else if (j != 0 && strcmp(name, csa->P->col[j]->name) == 0) { /* the same column as in previous data record */ xassert(j != 0); } else { /* store the current column */ if (j != 0) { glp_set_mat_col(csa->P, j, len, ind, val); while (len > 0) flag[ind[len--]] = 0; } /* create new column */ if (glp_find_col(csa->P, name) != 0) error(csa, "column `%s' multiply specified\n", name); j = glp_add_cols(csa->P, 1); glp_set_col_name(csa->P, j, name); glp_set_col_kind(csa->P, j, kind); if (kind == GLP_CV) glp_set_col_bnds(csa->P, j, GLP_LO, 0.0, 0.0); else if (kind == GLP_IV) glp_set_col_bnds(csa->P, j, GLP_DB, 0.0, 1.0); else xassert(kind != kind); } /* process fields 3-4 and 5-6 */ for (f = 3; f <= 5; f += 2) { /* field 3 or 5: row name */ if (f == 3) { if (csa->field[0] == '\0') error(csa, "missing row name in field 3\n"); } else { read_field(csa), patch_name(csa, csa->field); if (csa->field[0] == '\0') { /* if field 5 is blank, field 6 also must be blank */ skip_field(csa); continue; } } i = glp_find_row(csa->P, csa->field); if (i == 0) error(csa, "row `%s' not found\n", csa->field); if (flag[i]) error(csa, "duplicate coefficient in row `%s'\n", csa->field); /* field 4 or 6: coefficient value */ aij = read_number(csa); if (fabs(aij) < csa->parm->tol_mps) aij = 0.0; len++, ind[len] = i, val[len] = aij, flag[i] = 1; } goto loop; done: /* store the last column */ if (j != 0) glp_set_mat_col(csa->P, j, len, ind, val); /* free working arrays */ xfree(ind); xfree(val); xfree(flag); csa->work1 = csa->work2 = csa->work3 = NULL; return; } static void read_rhs(struct csa *csa) { /* read RHS section */ int i, f, v, type; double rhs; char name[255+1], *flag; /* allocate working array */ csa->work3 = flag = xcalloc(1+csa->P->m, sizeof(char)); memset(&flag[1], 0, csa->P->m); /* no current RHS vector exists */ v = 0; loop: if (indicator(csa, 0)) goto done; /* field 1 must be blank */ if (csa->deck) { read_field(csa); if (csa->field[0] != '\0') error(csa, "field 1 must be blank\n"); } else csa->fldno++; /* field 2: RHS vector name */ read_field(csa), patch_name(csa, csa->field); if (csa->field[0] == '\0') { /* the same RHS vector as in previous data record */ if (v == 0) { warning(csa, "missing RHS vector name in field 2\n"); goto blnk; } } else if (v != 0 && strcmp(csa->field, name) == 0) { /* the same RHS vector as in previous data record */ xassert(v != 0); } else blnk: { /* new RHS vector */ if (v != 0) error(csa, "multiple RHS vectors not supported\n"); v++; strcpy(name, csa->field); } /* process fields 3-4 and 5-6 */ for (f = 3; f <= 5; f += 2) { /* field 3 or 5: row name */ read_field(csa), patch_name(csa, csa->field); if (csa->field[0] == '\0') { if (f == 3) error(csa, "missing row name in field 3\n"); else { /* if field 5 is blank, field 6 also must be blank */ skip_field(csa); continue; } } i = glp_find_row(csa->P, csa->field); if (i == 0) error(csa, "row `%s' not found\n", csa->field); if (flag[i]) error(csa, "duplicate right-hand side for row `%s'\n", csa->field); /* field 4 or 6: right-hand side value */ rhs = read_number(csa); if (fabs(rhs) < csa->parm->tol_mps) rhs = 0.0; type = csa->P->row[i]->type; if (type == GLP_FR) { if (i == csa->obj_row) glp_set_obj_coef(csa->P, 0, rhs); else if (rhs != 0.0) warning(csa, "non-zero right-hand side for free row `%s'" " ignored\n", csa->P->row[i]->name); } else glp_set_row_bnds(csa->P, i, type, rhs, rhs); flag[i] = 1; } goto loop; done: /* free working array */ xfree(flag); csa->work3 = NULL; return; } static void read_ranges(struct csa *csa) { /* read RANGES section */ int i, f, v, type; double rhs, rng; char name[255+1], *flag; /* allocate working array */ csa->work3 = flag = xcalloc(1+csa->P->m, sizeof(char)); memset(&flag[1], 0, csa->P->m); /* no current RANGES vector exists */ v = 0; loop: if (indicator(csa, 0)) goto done; /* field 1 must be blank */ if (csa->deck) { read_field(csa); if (csa->field[0] != '\0') error(csa, "field 1 must be blank\n"); } else csa->fldno++; /* field 2: RANGES vector name */ read_field(csa), patch_name(csa, csa->field); if (csa->field[0] == '\0') { /* the same RANGES vector as in previous data record */ if (v == 0) { warning(csa, "missing RANGES vector name in field 2\n"); goto blnk; } } else if (v != 0 && strcmp(csa->field, name) == 0) { /* the same RANGES vector as in previous data record */ xassert(v != 0); } else blnk: { /* new RANGES vector */ if (v != 0) error(csa, "multiple RANGES vectors not supported\n"); v++; strcpy(name, csa->field); } /* process fields 3-4 and 5-6 */ for (f = 3; f <= 5; f += 2) { /* field 3 or 5: row name */ read_field(csa), patch_name(csa, csa->field); if (csa->field[0] == '\0') { if (f == 3) error(csa, "missing row name in field 3\n"); else { /* if field 5 is blank, field 6 also must be blank */ skip_field(csa); continue; } } i = glp_find_row(csa->P, csa->field); if (i == 0) error(csa, "row `%s' not found\n", csa->field); if (flag[i]) error(csa, "duplicate range for row `%s'\n", csa->field); /* field 4 or 6: range value */ rng = read_number(csa); if (fabs(rng) < csa->parm->tol_mps) rng = 0.0; type = csa->P->row[i]->type; if (type == GLP_FR) warning(csa, "range for free row `%s' ignored\n", csa->P->row[i]->name); else if (type == GLP_LO) { rhs = csa->P->row[i]->lb; glp_set_row_bnds(csa->P, i, rhs == 0.0 ? GLP_FX : GLP_DB, rhs, rhs + fabs(rng)); } else if (type == GLP_UP) { rhs = csa->P->row[i]->ub; glp_set_row_bnds(csa->P, i, rhs == 0.0 ? GLP_FX : GLP_DB, rhs - fabs(rng), rhs); } else if (type == GLP_FX) { rhs = csa->P->row[i]->lb; if (rng > 0.0) glp_set_row_bnds(csa->P, i, GLP_DB, rhs, rhs + rng); else if (rng < 0.0) glp_set_row_bnds(csa->P, i, GLP_DB, rhs + rng, rhs); } else xassert(type != type); flag[i] = 1; } goto loop; done: /* free working array */ xfree(flag); csa->work3 = NULL; return; } static void read_bounds(struct csa *csa) { /* read BOUNDS section */ GLPCOL *col; int j, v, mask, data; double bnd, lb, ub; char type[2+1], name[255+1], *flag; /* allocate working array */ csa->work3 = flag = xcalloc(1+csa->P->n, sizeof(char)); memset(&flag[1], 0, csa->P->n); /* no current BOUNDS vector exists */ v = 0; loop: if (indicator(csa, 0)) goto done; /* field 1: bound type */ read_field(csa); if (strcmp(csa->field, "LO") == 0) mask = 0x01, data = 1; else if (strcmp(csa->field, "UP") == 0) mask = 0x10, data = 1; else if (strcmp(csa->field, "FX") == 0) mask = 0x11, data = 1; else if (strcmp(csa->field, "FR") == 0) mask = 0x11, data = 0; else if (strcmp(csa->field, "MI") == 0) mask = 0x01, data = 0; else if (strcmp(csa->field, "PL") == 0) mask = 0x10, data = 0; else if (strcmp(csa->field, "LI") == 0) mask = 0x01, data = 1; else if (strcmp(csa->field, "UI") == 0) mask = 0x10, data = 1; else if (strcmp(csa->field, "BV") == 0) mask = 0x11, data = 0; else if (csa->field[0] == '\0') error(csa, "missing bound type in field 1\n"); else error(csa, "invalid bound type in field 1\n"); strcpy(type, csa->field); /* field 2: BOUNDS vector name */ read_field(csa), patch_name(csa, csa->field); if (csa->field[0] == '\0') { /* the same BOUNDS vector as in previous data record */ if (v == 0) { warning(csa, "missing BOUNDS vector name in field 2\n"); goto blnk; } } else if (v != 0 && strcmp(csa->field, name) == 0) { /* the same BOUNDS vector as in previous data record */ xassert(v != 0); } else blnk: { /* new BOUNDS vector */ if (v != 0) error(csa, "multiple BOUNDS vectors not supported\n"); v++; strcpy(name, csa->field); } /* field 3: column name */ read_field(csa), patch_name(csa, csa->field); if (csa->field[0] == '\0') error(csa, "missing column name in field 3\n"); j = glp_find_col(csa->P, csa->field); if (j == 0) error(csa, "column `%s' not found\n", csa->field); if ((flag[j] & mask) == 0x01) error(csa, "duplicate lower bound for column `%s'\n", csa->field); if ((flag[j] & mask) == 0x10) error(csa, "duplicate upper bound for column `%s'\n", csa->field); xassert((flag[j] & mask) == 0x00); /* field 4: bound value */ if (data) { bnd = read_number(csa); if (fabs(bnd) < csa->parm->tol_mps) bnd = 0.0; } else read_field(csa), bnd = 0.0; /* get current column bounds */ col = csa->P->col[j]; if (col->type == GLP_FR) lb = -DBL_MAX, ub = +DBL_MAX; else if (col->type == GLP_LO) lb = col->lb, ub = +DBL_MAX; else if (col->type == GLP_UP) lb = -DBL_MAX, ub = col->ub; else if (col->type == GLP_DB) lb = col->lb, ub = col->ub; else if (col->type == GLP_FX) lb = ub = col->lb; else xassert(col != col); /* change column bounds */ if (strcmp(type, "LO") == 0) lb = bnd; else if (strcmp(type, "UP") == 0) ub = bnd; else if (strcmp(type, "FX") == 0) lb = ub = bnd; else if (strcmp(type, "FR") == 0) lb = -DBL_MAX, ub = +DBL_MAX; else if (strcmp(type, "MI") == 0) lb = -DBL_MAX; else if (strcmp(type, "PL") == 0) ub = +DBL_MAX; else if (strcmp(type, "LI") == 0) { glp_set_col_kind(csa->P, j, GLP_IV); lb = ceil(bnd); } else if (strcmp(type, "UI") == 0) { glp_set_col_kind(csa->P, j, GLP_IV); ub = floor(bnd); } else if (strcmp(type, "BV") == 0) { glp_set_col_kind(csa->P, j, GLP_IV); lb = 0.0, ub = 1.0; } else xassert(type != type); /* set new column bounds */ if (lb == -DBL_MAX && ub == +DBL_MAX) glp_set_col_bnds(csa->P, j, GLP_FR, lb, ub); else if (ub == +DBL_MAX) glp_set_col_bnds(csa->P, j, GLP_LO, lb, ub); else if (lb == -DBL_MAX) glp_set_col_bnds(csa->P, j, GLP_UP, lb, ub); else if (lb != ub) glp_set_col_bnds(csa->P, j, GLP_DB, lb, ub); else glp_set_col_bnds(csa->P, j, GLP_FX, lb, ub); flag[j] |= (char)mask; /* fields 5 and 6 must be blank */ skip_field(csa); skip_field(csa); goto loop; done: /* free working array */ xfree(flag); csa->work3 = NULL; return; } int glp_read_mps(glp_prob *P, int fmt, const glp_mpscp *parm, const char *fname) { /* read problem data in MPS format */ glp_mpscp _parm; struct csa _csa, *csa = &_csa; int ret; xprintf("Reading problem data from `%s'...\n", fname); if (!(fmt == GLP_MPS_DECK || fmt == GLP_MPS_FILE)) xerror("glp_read_mps: fmt = %d; invalid parameter\n", fmt); if (parm == NULL) glp_init_mpscp(&_parm), parm = &_parm; /* check control parameters */ check_parm("glp_read_mps", parm); /* initialize common storage area */ csa->P = P; csa->deck = (fmt == GLP_MPS_DECK); csa->parm = parm; csa->fname = fname; csa->fp = NULL; if (setjmp(csa->jump)) { ret = 1; goto done; } csa->recno = csa->recpos = 0; csa->c = '\n'; csa->fldno = 0; csa->field[0] = '\0'; csa->w80 = csa->wef = 0; csa->obj_row = 0; csa->work1 = csa->work2 = csa->work3 = NULL; /* erase problem object */ glp_erase_prob(P); glp_create_index(P); /* open input MPS file */ csa->fp = xfopen(fname, "r"); if (csa->fp == NULL) { xprintf("Unable to open `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } /* read NAME indicator record */ read_name(csa); if (P->name != NULL) xprintf("Problem: %s\n", P->name); /* read ROWS section */ if (!(indicator(csa, 0) && strcmp(csa->field, "ROWS") == 0)) error(csa, "missing ROWS indicator record\n"); read_rows(csa); /* determine objective row */ if (parm->obj_name == NULL || parm->obj_name[0] == '\0') { /* use the first row of N type */ int i; for (i = 1; i <= P->m; i++) { if (P->row[i]->type == GLP_FR) { csa->obj_row = i; break; } } if (csa->obj_row == 0) warning(csa, "unable to determine objective row\n"); } else { /* use a row with specified name */ int i; for (i = 1; i <= P->m; i++) { xassert(P->row[i]->name != NULL); if (strcmp(parm->obj_name, P->row[i]->name) == 0) { csa->obj_row = i; break; } } if (csa->obj_row == 0) error(csa, "objective row `%s' not found\n", parm->obj_name); } if (csa->obj_row != 0) { glp_set_obj_name(P, P->row[csa->obj_row]->name); xprintf("Objective: %s\n", P->obj); } /* read COLUMNS section */ if (strcmp(csa->field, "COLUMNS") != 0) error(csa, "missing COLUMNS indicator record\n"); read_columns(csa); /* set objective coefficients */ if (csa->obj_row != 0) { GLPAIJ *aij; for (aij = P->row[csa->obj_row]->ptr; aij != NULL; aij = aij->r_next) glp_set_obj_coef(P, aij->col->j, aij->val); } /* read optional RHS section */ if (strcmp(csa->field, "RHS") == 0) read_rhs(csa); /* read optional RANGES section */ if (strcmp(csa->field, "RANGES") == 0) read_ranges(csa); /* read optional BOUNDS section */ if (strcmp(csa->field, "BOUNDS") == 0) read_bounds(csa); /* read ENDATA indicator record */ if (strcmp(csa->field, "ENDATA") != 0) error(csa, "invalid use of %s indicator record\n", csa->field); /* print some statistics */ xprintf("%d row%s, %d column%s, %d non-zero%s\n", P->m, P->m == 1 ? "" : "s", P->n, P->n == 1 ? "" : "s", P->nnz, P->nnz == 1 ? "" : "s"); if (glp_get_num_int(P) > 0) { int ni = glp_get_num_int(P); int nb = glp_get_num_bin(P); if (ni == 1) { if (nb == 0) xprintf("One variable is integer\n"); else xprintf("One variable is binary\n"); } else { xprintf("%d integer variables, ", ni); if (nb == 0) xprintf("none"); else if (nb == 1) xprintf("one"); else if (nb == ni) xprintf("all"); else xprintf("%d", nb); xprintf(" of which %s binary\n", nb == 1 ? "is" : "are"); } } xprintf("%d records were read\n", csa->recno); /* problem data has been successfully read */ glp_delete_index(P); glp_sort_matrix(P); ret = 0; done: if (csa->fp != NULL) xfclose(csa->fp); if (csa->work1 != NULL) xfree(csa->work1); if (csa->work2 != NULL) xfree(csa->work2); if (csa->work3 != NULL) xfree(csa->work3); if (ret != 0) glp_erase_prob(P); return ret; } /*********************************************************************** * NAME * * glp_write_mps - write problem data in MPS format * * SYNOPSIS * * int glp_write_mps(glp_prob *P, int fmt, const glp_mpscp *parm, * const char *fname); * * DESCRIPTION * * The routine glp_write_mps writes problem data in MPS format to a * text file. * * The parameter fmt specifies the version of MPS format: * * GLP_MPS_DECK - fixed (ancient) MPS format; * GLP_MPS_FILE - free (modern) MPS format. * * The parameter parm is a pointer to the structure glp_mpscp, which * specifies control parameters used by the routine. If parm is NULL, * the routine uses default settings. * * The character string fname specifies a name of the text file to be * written. * * RETURNS * * If the operation was successful, the routine glp_read_mps returns * zero. Otherwise, it prints an error message and returns non-zero. */ #define csa csa1 struct csa { /* common storage area */ glp_prob *P; /* pointer to problem object */ int deck; /* MPS format (0 - free, 1 - fixed) */ const glp_mpscp *parm; /* pointer to control parameters */ char field[255+1]; /* field buffer */ }; static char *mps_name(struct csa *csa) { /* make problem name */ char *f; if (csa->P->name == NULL) csa->field[0] = '\0'; else if (csa->deck) { strncpy(csa->field, csa->P->name, 8); csa->field[8] = '\0'; } else strcpy(csa->field, csa->P->name); for (f = csa->field; *f != '\0'; f++) if (*f == ' ') *f = '_'; return csa->field; } static char *row_name(struct csa *csa, int i) { /* make i-th row name */ char *f; xassert(0 <= i && i <= csa->P->m); if (i == 0 || csa->P->row[i]->name == NULL || csa->deck && strlen(csa->P->row[i]->name) > 8) sprintf(csa->field, "R%07d", i); else { strcpy(csa->field, csa->P->row[i]->name); for (f = csa->field; *f != '\0'; f++) if (*f == ' ') *f = '_'; } return csa->field; } static char *col_name(struct csa *csa, int j) { /* make j-th column name */ char *f; xassert(1 <= j && j <= csa->P->n); if (csa->P->col[j]->name == NULL || csa->deck && strlen(csa->P->col[j]->name) > 8) sprintf(csa->field, "C%07d", j); else { strcpy(csa->field, csa->P->col[j]->name); for (f = csa->field; *f != '\0'; f++) if (*f == ' ') *f = '_'; } return csa->field; } static char *mps_numb(struct csa *csa, double val) { /* format floating-point number */ int dig; char *exp; for (dig = 12; dig >= 6; dig--) { if (val != 0.0 && fabs(val) < 0.002) sprintf(csa->field, "%.*E", dig-1, val); else sprintf(csa->field, "%.*G", dig, val); exp = strchr(csa->field, 'E'); if (exp != NULL) sprintf(exp+1, "%d", atoi(exp+1)); if (strlen(csa->field) <= 12) break; } xassert(strlen(csa->field) <= 12); return csa->field; } int glp_write_mps(glp_prob *P, int fmt, const glp_mpscp *parm, const char *fname) { /* write problem data in MPS format */ glp_mpscp _parm; struct csa _csa, *csa = &_csa; XFILE *fp; int out_obj, one_col = 0, empty = 0; int i, j, recno, marker, count, gap, ret; xprintf("Writing problem data to `%s'...\n", fname); if (!(fmt == GLP_MPS_DECK || fmt == GLP_MPS_FILE)) xerror("glp_write_mps: fmt = %d; invalid parameter\n", fmt); if (parm == NULL) glp_init_mpscp(&_parm), parm = &_parm; /* check control parameters */ check_parm("glp_write_mps", parm); /* initialize common storage area */ csa->P = P; csa->deck = (fmt == GLP_MPS_DECK); csa->parm = parm; /* create output MPS file */ fp = xfopen(fname, "w"), recno = 0; if (fp == NULL) { xprintf("Unable to create `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } /* write comment records */ xfprintf(fp, "* %-*s%s\n", P->name == NULL ? 1 : 12, "Problem:", P->name == NULL ? "" : P->name), recno++; xfprintf(fp, "* %-12s%s\n", "Class:", glp_get_num_int(P) == 0 ? "LP" : "MIP"), recno++; xfprintf(fp, "* %-12s%d\n", "Rows:", P->m), recno++; if (glp_get_num_int(P) == 0) xfprintf(fp, "* %-12s%d\n", "Columns:", P->n), recno++; else xfprintf(fp, "* %-12s%d (%d integer, %d binary)\n", "Columns:", P->n, glp_get_num_int(P), glp_get_num_bin(P)), recno++; xfprintf(fp, "* %-12s%d\n", "Non-zeros:", P->nnz), recno++; xfprintf(fp, "* %-12s%s\n", "Format:", csa->deck ? "Fixed MPS" : "Free MPS"), recno++; xfprintf(fp, "*\n", recno++); /* write NAME indicator record */ xfprintf(fp, "NAME%*s%s\n", P->name == NULL ? 0 : csa->deck ? 10 : 1, "", mps_name(csa)), recno++; #if 1 /* determine whether to write the objective row */ out_obj = 1; for (i = 1; i <= P->m; i++) { if (P->row[i]->type == GLP_FR) { out_obj = 0; break; } } #endif /* write ROWS section */ xfprintf(fp, "ROWS\n"), recno++; for (i = (out_obj ? 0 : 1); i <= P->m; i++) { int type; type = (i == 0 ? GLP_FR : P->row[i]->type); if (type == GLP_FR) type = 'N'; else if (type == GLP_LO) type = 'G'; else if (type == GLP_UP) type = 'L'; else if (type == GLP_DB || type == GLP_FX) type = 'E'; else xassert(type != type); xfprintf(fp, " %c%*s%s\n", type, csa->deck ? 2 : 1, "", row_name(csa, i)), recno++; } /* write COLUMNS section */ xfprintf(fp, "COLUMNS\n"), recno++; marker = 0; for (j = 1; j <= P->n; j++) { GLPAIJ cj, *aij; int kind; kind = P->col[j]->kind; if (kind == GLP_CV) { if (marker % 2 == 1) { /* close current integer block */ marker++; xfprintf(fp, "%*sM%07d%*s'MARKER'%*s'INTEND'\n", csa->deck ? 4 : 1, "", marker, csa->deck ? 2 : 1, "", csa->deck ? 17 : 1, ""), recno++; } } else if (kind == GLP_IV) { if (marker % 2 == 0) { /* open new integer block */ marker++; xfprintf(fp, "%*sM%07d%*s'MARKER'%*s'INTORG'\n", csa->deck ? 4 : 1, "", marker, csa->deck ? 2 : 1, "", csa->deck ? 17 : 1, ""), recno++; } } else xassert(kind != kind); if (out_obj && P->col[j]->coef != 0.0) { /* make fake objective coefficient */ aij = &cj; aij->row = NULL; aij->val = P->col[j]->coef; aij->c_next = P->col[j]->ptr; } else aij = P->col[j]->ptr; #if 1 /* FIXME */ if (aij == NULL) { /* empty column */ empty++; xfprintf(fp, "%*s%-*s", csa->deck ? 4 : 1, "", csa->deck ? 8 : 1, col_name(csa, j)); /* we need a row */ xassert(P->m > 0); xfprintf(fp, "%*s%-*s", csa->deck ? 2 : 1, "", csa->deck ? 8 : 1, row_name(csa, 1)); xfprintf(fp, "%*s0%*s$ empty column\n", csa->deck ? 13 : 1, "", csa->deck ? 3 : 1, ""), recno++; } #endif count = 0; for (aij = aij; aij != NULL; aij = aij->c_next) { if (one_col || count % 2 == 0) xfprintf(fp, "%*s%-*s", csa->deck ? 4 : 1, "", csa->deck ? 8 : 1, col_name(csa, j)); gap = (one_col || count % 2 == 0 ? 2 : 3); xfprintf(fp, "%*s%-*s", csa->deck ? gap : 1, "", csa->deck ? 8 : 1, row_name(csa, aij->row == NULL ? 0 : aij->row->i)); xfprintf(fp, "%*s%*s", csa->deck ? 2 : 1, "", csa->deck ? 12 : 1, mps_numb(csa, aij->val)), count++; if (one_col || count % 2 == 0) xfprintf(fp, "\n"), recno++; } if (!(one_col || count % 2 == 0)) xfprintf(fp, "\n"), recno++; } if (marker % 2 == 1) { /* close last integer block */ marker++; xfprintf(fp, "%*sM%07d%*s'MARKER'%*s'INTEND'\n", csa->deck ? 4 : 1, "", marker, csa->deck ? 2 : 1, "", csa->deck ? 17 : 1, ""), recno++; } #if 1 if (empty > 0) xprintf("Warning: problem has %d empty column(s)\n", empty); #endif /* write RHS section */ xfprintf(fp, "RHS\n"), recno++; count = 0; for (i = (out_obj ? 0 : 1); i <= P->m; i++) { int type; double rhs; if (i == 0) rhs = P->c0; else { type = P->row[i]->type; if (type == GLP_FR) rhs = 0.0; else if (type == GLP_LO) rhs = P->row[i]->lb; else if (type == GLP_UP) rhs = P->row[i]->ub; else if (type == GLP_DB || type == GLP_FX) rhs = P->row[i]->lb; else xassert(type != type); } if (rhs != 0.0) { if (one_col || count % 2 == 0) xfprintf(fp, "%*s%-*s", csa->deck ? 4 : 1, "", csa->deck ? 8 : 1, "RHS1"); gap = (one_col || count % 2 == 0 ? 2 : 3); xfprintf(fp, "%*s%-*s", csa->deck ? gap : 1, "", csa->deck ? 8 : 1, row_name(csa, i)); xfprintf(fp, "%*s%*s", csa->deck ? 2 : 1, "", csa->deck ? 12 : 1, mps_numb(csa, rhs)), count++; if (one_col || count % 2 == 0) xfprintf(fp, "\n"), recno++; } } if (!(one_col || count % 2 == 0)) xfprintf(fp, "\n"), recno++; /* write RANGES section */ for (i = P->m; i >= 1; i--) if (P->row[i]->type == GLP_DB) break; if (i == 0) goto bnds; xfprintf(fp, "RANGES\n"), recno++; count = 0; for (i = 1; i <= P->m; i++) { if (P->row[i]->type == GLP_DB) { if (one_col || count % 2 == 0) xfprintf(fp, "%*s%-*s", csa->deck ? 4 : 1, "", csa->deck ? 8 : 1, "RNG1"); gap = (one_col || count % 2 == 0 ? 2 : 3); xfprintf(fp, "%*s%-*s", csa->deck ? gap : 1, "", csa->deck ? 8 : 1, row_name(csa, i)); xfprintf(fp, "%*s%*s", csa->deck ? 2 : 1, "", csa->deck ? 12 : 1, mps_numb(csa, P->row[i]->ub - P->row[i]->lb)), count++; if (one_col || count % 2 == 0) xfprintf(fp, "\n"), recno++; } } if (!(one_col || count % 2 == 0)) xfprintf(fp, "\n"), recno++; bnds: /* write BOUNDS section */ for (j = P->n; j >= 1; j--) if (!(P->col[j]->type == GLP_LO && P->col[j]->lb == 0.0)) break; if (j == 0) goto endt; xfprintf(fp, "BOUNDS\n"), recno++; for (j = 1; j <= P->n; j++) { int type, data[2]; double bnd[2]; char *spec[2]; spec[0] = spec[1] = NULL; type = P->col[j]->type; if (type == GLP_FR) spec[0] = "FR", data[0] = 0; else if (type == GLP_LO) { if (P->col[j]->lb != 0.0) spec[0] = "LO", data[0] = 1, bnd[0] = P->col[j]->lb; if (P->col[j]->kind == GLP_IV) spec[1] = "PL", data[1] = 0; } else if (type == GLP_UP) { spec[0] = "MI", data[0] = 0; spec[1] = "UP", data[1] = 1, bnd[1] = P->col[j]->ub; } else if (type == GLP_DB) { if (P->col[j]->lb != 0.0) spec[0] = "LO", data[0] = 1, bnd[0] = P->col[j]->lb; spec[1] = "UP", data[1] = 1, bnd[1] = P->col[j]->ub; } else if (type == GLP_FX) spec[0] = "FX", data[0] = 1, bnd[0] = P->col[j]->lb; else xassert(type != type); for (i = 0; i <= 1; i++) { if (spec[i] != NULL) { xfprintf(fp, " %s %-*s%*s%-*s", spec[i], csa->deck ? 8 : 1, "BND1", csa->deck ? 2 : 1, "", csa->deck ? 8 : 1, col_name(csa, j)); if (data[i]) xfprintf(fp, "%*s%*s", csa->deck ? 2 : 1, "", csa->deck ? 12 : 1, mps_numb(csa, bnd[i])); xfprintf(fp, "\n"), recno++; } } } endt: /* write ENDATA indicator record */ xfprintf(fp, "ENDATA\n"), recno++; xfflush(fp); if (xferror(fp)) { xprintf("Write error on `%s' - %s\n", fname, xerrmsg()); ret = 1; goto done; } /* problem data has been successfully written */ xprintf("%d records were written\n", recno); ret = 0; done: if (fp != NULL) xfclose(fp); return ret; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpapi07.c0000644000076500000240000003504213524616144025172 0ustar tamasstaff00000000000000/* glpapi07.c (exact simplex solver) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glpapi.h" #include "glpssx.h" /*********************************************************************** * NAME * * glp_exact - solve LP problem in exact arithmetic * * SYNOPSIS * * int glp_exact(glp_prob *lp, const glp_smcp *parm); * * DESCRIPTION * * The routine glp_exact is a tentative implementation of the primal * two-phase simplex method based on exact (rational) arithmetic. It is * similar to the routine glp_simplex, however, for all internal * computations it uses arithmetic of rational numbers, which is exact * in mathematical sense, i.e. free of round-off errors unlike floating * point arithmetic. * * Note that the routine glp_exact uses inly two control parameters * passed in the structure glp_smcp, namely, it_lim and tm_lim. * * RETURNS * * 0 The LP problem instance has been successfully solved. This code * does not necessarily mean that the solver has found optimal * solution. It only means that the solution process was successful. * * GLP_EBADB * Unable to start the search, because the initial basis specified * in the problem object is invalid--the number of basic (auxiliary * and structural) variables is not the same as the number of rows in * the problem object. * * GLP_ESING * Unable to start the search, because the basis matrix correspodning * to the initial basis is exactly singular. * * GLP_EBOUND * Unable to start the search, because some double-bounded variables * have incorrect bounds. * * GLP_EFAIL * The problem has no rows/columns. * * GLP_EITLIM * The search was prematurely terminated, because the simplex * iteration limit has been exceeded. * * GLP_ETMLIM * The search was prematurely terminated, because the time limit has * been exceeded. */ static void set_d_eps(mpq_t x, double val) { /* convert double val to rational x obtaining a more adequate fraction than provided by mpq_set_d due to allowing a small approximation error specified by a given relative tolerance; for example, mpq_set_d would give the following 1/3 ~= 0.333333333333333314829616256247391... -> -> 6004799503160661/18014398509481984 while this routine gives exactly 1/3 */ int s, n, j; double f, p, q, eps = 1e-9; mpq_t temp; xassert(-DBL_MAX <= val && val <= +DBL_MAX); #if 1 /* 30/VII-2008 */ if (val == floor(val)) { /* if val is integral, do not approximate */ mpq_set_d(x, val); goto done; } #endif if (val > 0.0) s = +1; else if (val < 0.0) s = -1; else { mpq_set_si(x, 0, 1); goto done; } f = frexp(fabs(val), &n); /* |val| = f * 2^n, where 0.5 <= f < 1.0 */ fp2rat(f, 0.1 * eps, &p, &q); /* f ~= p / q, where p and q are integers */ mpq_init(temp); mpq_set_d(x, p); mpq_set_d(temp, q); mpq_div(x, x, temp); mpq_set_si(temp, 1, 1); for (j = 1; j <= abs(n); j++) mpq_add(temp, temp, temp); if (n > 0) mpq_mul(x, x, temp); else if (n < 0) mpq_div(x, x, temp); mpq_clear(temp); if (s < 0) mpq_neg(x, x); /* check that the desired tolerance has been attained */ xassert(fabs(val - mpq_get_d(x)) <= eps * (1.0 + fabs(val))); done: return; } static void load_data(SSX *ssx, LPX *lp) { /* load LP problem data into simplex solver workspace */ int m = ssx->m; int n = ssx->n; int nnz = ssx->A_ptr[n+1]-1; int j, k, type, loc, len, *ind; double lb, ub, coef, *val; xassert(lpx_get_num_rows(lp) == m); xassert(lpx_get_num_cols(lp) == n); xassert(lpx_get_num_nz(lp) == nnz); /* types and bounds of rows and columns */ for (k = 1; k <= m+n; k++) { if (k <= m) { type = lpx_get_row_type(lp, k); lb = lpx_get_row_lb(lp, k); ub = lpx_get_row_ub(lp, k); } else { type = lpx_get_col_type(lp, k-m); lb = lpx_get_col_lb(lp, k-m); ub = lpx_get_col_ub(lp, k-m); } switch (type) { case LPX_FR: type = SSX_FR; break; case LPX_LO: type = SSX_LO; break; case LPX_UP: type = SSX_UP; break; case LPX_DB: type = SSX_DB; break; case LPX_FX: type = SSX_FX; break; default: xassert(type != type); } ssx->type[k] = type; set_d_eps(ssx->lb[k], lb); set_d_eps(ssx->ub[k], ub); } /* optimization direction */ switch (lpx_get_obj_dir(lp)) { case LPX_MIN: ssx->dir = SSX_MIN; break; case LPX_MAX: ssx->dir = SSX_MAX; break; default: xassert(lp != lp); } /* objective coefficients */ for (k = 0; k <= m+n; k++) { if (k == 0) coef = lpx_get_obj_coef(lp, 0); else if (k <= m) coef = 0.0; else coef = lpx_get_obj_coef(lp, k-m); set_d_eps(ssx->coef[k], coef); } /* constraint coefficients */ ind = xcalloc(1+m, sizeof(int)); val = xcalloc(1+m, sizeof(double)); loc = 0; for (j = 1; j <= n; j++) { ssx->A_ptr[j] = loc+1; len = lpx_get_mat_col(lp, j, ind, val); for (k = 1; k <= len; k++) { loc++; ssx->A_ind[loc] = ind[k]; set_d_eps(ssx->A_val[loc], val[k]); } } xassert(loc == nnz); xfree(ind); xfree(val); return; } static int load_basis(SSX *ssx, LPX *lp) { /* load current LP basis into simplex solver workspace */ int m = ssx->m; int n = ssx->n; int *type = ssx->type; int *stat = ssx->stat; int *Q_row = ssx->Q_row; int *Q_col = ssx->Q_col; int i, j, k; xassert(lpx_get_num_rows(lp) == m); xassert(lpx_get_num_cols(lp) == n); /* statuses of rows and columns */ for (k = 1; k <= m+n; k++) { if (k <= m) stat[k] = lpx_get_row_stat(lp, k); else stat[k] = lpx_get_col_stat(lp, k-m); switch (stat[k]) { case LPX_BS: stat[k] = SSX_BS; break; case LPX_NL: stat[k] = SSX_NL; xassert(type[k] == SSX_LO || type[k] == SSX_DB); break; case LPX_NU: stat[k] = SSX_NU; xassert(type[k] == SSX_UP || type[k] == SSX_DB); break; case LPX_NF: stat[k] = SSX_NF; xassert(type[k] == SSX_FR); break; case LPX_NS: stat[k] = SSX_NS; xassert(type[k] == SSX_FX); break; default: xassert(stat != stat); } } /* build permutation matix Q */ i = j = 0; for (k = 1; k <= m+n; k++) { if (stat[k] == SSX_BS) { i++; if (i > m) return 1; Q_row[k] = i, Q_col[i] = k; } else { j++; if (j > n) return 1; Q_row[k] = m+j, Q_col[m+j] = k; } } xassert(i == m && j == n); return 0; } int glp_exact(glp_prob *lp, const glp_smcp *parm) { glp_smcp _parm; SSX *ssx; int m = lpx_get_num_rows(lp); int n = lpx_get_num_cols(lp); int nnz = lpx_get_num_nz(lp); int i, j, k, type, pst, dst, ret, *stat; double lb, ub, *prim, *dual, sum; if (parm == NULL) parm = &_parm, glp_init_smcp((glp_smcp *)parm); /* check control parameters */ if (parm->it_lim < 0) xerror("glp_exact: it_lim = %d; invalid parameter\n", parm->it_lim); if (parm->tm_lim < 0) xerror("glp_exact: tm_lim = %d; invalid parameter\n", parm->tm_lim); /* the problem must have at least one row and one column */ if (!(m > 0 && n > 0)) { xprintf("glp_exact: problem has no rows/columns\n"); return GLP_EFAIL; } #if 1 /* basic solution is currently undefined */ lp->pbs_stat = lp->dbs_stat = GLP_UNDEF; lp->obj_val = 0.0; lp->some = 0; #endif /* check that all double-bounded variables have correct bounds */ for (k = 1; k <= m+n; k++) { if (k <= m) { type = lpx_get_row_type(lp, k); lb = lpx_get_row_lb(lp, k); ub = lpx_get_row_ub(lp, k); } else { type = lpx_get_col_type(lp, k-m); lb = lpx_get_col_lb(lp, k-m); ub = lpx_get_col_ub(lp, k-m); } if (type == LPX_DB && lb >= ub) { xprintf("glp_exact: %s %d has invalid bounds\n", k <= m ? "row" : "column", k <= m ? k : k-m); return GLP_EBOUND; } } /* create the simplex solver workspace */ xprintf("glp_exact: %d rows, %d columns, %d non-zeros\n", m, n, nnz); #ifdef HAVE_GMP xprintf("GNU MP bignum library is being used\n"); #else xprintf("GLPK bignum module is being used\n"); xprintf("(Consider installing GNU MP to attain a much better perf" "ormance.)\n"); #endif ssx = ssx_create(m, n, nnz); /* load LP problem data into the workspace */ load_data(ssx, lp); /* load current LP basis into the workspace */ if (load_basis(ssx, lp)) { xprintf("glp_exact: initial LP basis is invalid\n"); ret = GLP_EBADB; goto done; } /* inherit some control parameters from the LP object */ #if 0 ssx->it_lim = lpx_get_int_parm(lp, LPX_K_ITLIM); ssx->it_cnt = lpx_get_int_parm(lp, LPX_K_ITCNT); ssx->tm_lim = lpx_get_real_parm(lp, LPX_K_TMLIM); #else ssx->it_lim = parm->it_lim; ssx->it_cnt = lp->it_cnt; ssx->tm_lim = (double)parm->tm_lim / 1000.0; #endif ssx->out_frq = 5.0; ssx->tm_beg = xtime(); ssx->tm_lag = xlset(0); /* solve LP */ ret = ssx_driver(ssx); /* copy back some statistics to the LP object */ #if 0 lpx_set_int_parm(lp, LPX_K_ITLIM, ssx->it_lim); lpx_set_int_parm(lp, LPX_K_ITCNT, ssx->it_cnt); lpx_set_real_parm(lp, LPX_K_TMLIM, ssx->tm_lim); #else lp->it_cnt = ssx->it_cnt; #endif /* analyze the return code */ switch (ret) { case 0: /* optimal solution found */ ret = 0; pst = LPX_P_FEAS, dst = LPX_D_FEAS; break; case 1: /* problem has no feasible solution */ ret = 0; pst = LPX_P_NOFEAS, dst = LPX_D_INFEAS; break; case 2: /* problem has unbounded solution */ ret = 0; pst = LPX_P_FEAS, dst = LPX_D_NOFEAS; #if 1 xassert(1 <= ssx->q && ssx->q <= n); lp->some = ssx->Q_col[m + ssx->q]; xassert(1 <= lp->some && lp->some <= m+n); #endif break; case 3: /* iteration limit exceeded (phase I) */ ret = GLP_EITLIM; pst = LPX_P_INFEAS, dst = LPX_D_INFEAS; break; case 4: /* iteration limit exceeded (phase II) */ ret = GLP_EITLIM; pst = LPX_P_FEAS, dst = LPX_D_INFEAS; break; case 5: /* time limit exceeded (phase I) */ ret = GLP_ETMLIM; pst = LPX_P_INFEAS, dst = LPX_D_INFEAS; break; case 6: /* time limit exceeded (phase II) */ ret = GLP_ETMLIM; pst = LPX_P_FEAS, dst = LPX_D_INFEAS; break; case 7: /* initial basis matrix is singular */ ret = GLP_ESING; goto done; default: xassert(ret != ret); } /* obtain final basic solution components */ stat = xcalloc(1+m+n, sizeof(int)); prim = xcalloc(1+m+n, sizeof(double)); dual = xcalloc(1+m+n, sizeof(double)); for (k = 1; k <= m+n; k++) { if (ssx->stat[k] == SSX_BS) { i = ssx->Q_row[k]; /* x[k] = xB[i] */ xassert(1 <= i && i <= m); stat[k] = LPX_BS; prim[k] = mpq_get_d(ssx->bbar[i]); dual[k] = 0.0; } else { j = ssx->Q_row[k] - m; /* x[k] = xN[j] */ xassert(1 <= j && j <= n); switch (ssx->stat[k]) { case SSX_NF: stat[k] = LPX_NF; prim[k] = 0.0; break; case SSX_NL: stat[k] = LPX_NL; prim[k] = mpq_get_d(ssx->lb[k]); break; case SSX_NU: stat[k] = LPX_NU; prim[k] = mpq_get_d(ssx->ub[k]); break; case SSX_NS: stat[k] = LPX_NS; prim[k] = mpq_get_d(ssx->lb[k]); break; default: xassert(ssx != ssx); } dual[k] = mpq_get_d(ssx->cbar[j]); } } /* and store them into the LP object */ pst = pst - LPX_P_UNDEF + GLP_UNDEF; dst = dst - LPX_D_UNDEF + GLP_UNDEF; for (k = 1; k <= m+n; k++) stat[k] = stat[k] - LPX_BS + GLP_BS; sum = lpx_get_obj_coef(lp, 0); for (j = 1; j <= n; j++) sum += lpx_get_obj_coef(lp, j) * prim[m+j]; lpx_put_solution(lp, 1, &pst, &dst, &sum, &stat[0], &prim[0], &dual[0], &stat[m], &prim[m], &dual[m]); xfree(stat); xfree(prim); xfree(dual); done: /* delete the simplex solver workspace */ ssx_delete(ssx); /* return to the application program */ return ret; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpqmd.c0000644000076500000240000004356513524616144025044 0ustar tamasstaff00000000000000/* glpqmd.c (quotient minimum degree algorithm) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * THIS CODE IS THE RESULT OF TRANSLATION OF THE FORTRAN SUBROUTINES * GENQMD, QMDRCH, QMDQT, QMDUPD, AND QMDMRG FROM THE BOOK: * * ALAN GEORGE, JOSEPH W-H LIU. COMPUTER SOLUTION OF LARGE SPARSE * POSITIVE DEFINITE SYSTEMS. PRENTICE-HALL, 1981. * * THE TRANSLATION HAS BEEN DONE WITH THE PERMISSION OF THE AUTHORS * OF THE ORIGINAL FORTRAN SUBROUTINES: ALAN GEORGE AND JOSEPH LIU, * UNIVERSITY OF WATERLOO, WATERLOO, ONTARIO, CANADA. * * The translation was made by Andrew Makhorin . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glpqmd.h" /*********************************************************************** * NAME * * genqmd - GENeral Quotient Minimum Degree algorithm * * SYNOPSIS * * #include "glpqmd.h" * void genqmd(int *neqns, int xadj[], int adjncy[], int perm[], * int invp[], int deg[], int marker[], int rchset[], int nbrhd[], * int qsize[], int qlink[], int *nofsub); * * PURPOSE * * This routine implements the minimum degree algorithm. It makes use * of the implicit representation of the elimination graph by quotient * graphs, and the notion of indistinguishable nodes. * * CAUTION * * The adjancy vector adjncy will be destroyed. * * INPUT PARAMETERS * * neqns - number of equations; * (xadj, adjncy) - * the adjancy structure. * * OUTPUT PARAMETERS * * perm - the minimum degree ordering; * invp - the inverse of perm. * * WORKING PARAMETERS * * deg - the degree vector. deg[i] is negative means node i has been * numbered; * marker - a marker vector, where marker[i] is negative means node i * has been merged with another nodeand thus can be ignored; * rchset - vector used for the reachable set; * nbrhd - vector used for neighborhood set; * qsize - vector used to store the size of indistinguishable * supernodes; * qlink - vector used to store indistinguishable nodes, i, qlink[i], * qlink[qlink[i]], ... are the members of the supernode * represented by i. * * PROGRAM SUBROUTINES * * qmdrch, qmdqt, qmdupd. ***********************************************************************/ void genqmd(int *_neqns, int xadj[], int adjncy[], int perm[], int invp[], int deg[], int marker[], int rchset[], int nbrhd[], int qsize[], int qlink[], int *_nofsub) { int inode, ip, irch, j, mindeg, ndeg, nhdsze, node, np, num, nump1, nxnode, rchsze, search, thresh; # define neqns (*_neqns) # define nofsub (*_nofsub) /* Initialize degree vector and other working variables. */ mindeg = neqns; nofsub = 0; for (node = 1; node <= neqns; node++) { perm[node] = node; invp[node] = node; marker[node] = 0; qsize[node] = 1; qlink[node] = 0; ndeg = xadj[node+1] - xadj[node]; deg[node] = ndeg; if (ndeg < mindeg) mindeg = ndeg; } num = 0; /* Perform threshold search to get a node of min degree. Variable search point to where search should start. */ s200: search = 1; thresh = mindeg; mindeg = neqns; s300: nump1 = num + 1; if (nump1 > search) search = nump1; for (j = search; j <= neqns; j++) { node = perm[j]; if (marker[node] >= 0) { ndeg = deg[node]; if (ndeg <= thresh) goto s500; if (ndeg < mindeg) mindeg = ndeg; } } goto s200; /* Node has minimum degree. Find its reachable sets by calling qmdrch. */ s500: search = j; nofsub += deg[node]; marker[node] = 1; qmdrch(&node, xadj, adjncy, deg, marker, &rchsze, rchset, &nhdsze, nbrhd); /* Eliminate all nodes indistinguishable from node. They are given by node, qlink[node], ... . */ nxnode = node; s600: num++; np = invp[nxnode]; ip = perm[num]; perm[np] = ip; invp[ip] = np; perm[num] = nxnode; invp[nxnode] = num; deg[nxnode] = -1; nxnode = qlink[nxnode]; if (nxnode > 0) goto s600; if (rchsze > 0) { /* Update the degrees of the nodes in the reachable set and identify indistinguishable nodes. */ qmdupd(xadj, adjncy, &rchsze, rchset, deg, qsize, qlink, marker, &rchset[rchsze+1], &nbrhd[nhdsze+1]); /* Reset marker value of nodes in reach set. Update threshold value for cyclic search. Also call qmdqt to form new quotient graph. */ marker[node] = 0; for (irch = 1; irch <= rchsze; irch++) { inode = rchset[irch]; if (marker[inode] >= 0) { marker[inode] = 0; ndeg = deg[inode]; if (ndeg < mindeg) mindeg = ndeg; if (ndeg <= thresh) { mindeg = thresh; thresh = ndeg; search = invp[inode]; } } } if (nhdsze > 0) qmdqt(&node, xadj, adjncy, marker, &rchsze, rchset, nbrhd); } if (num < neqns) goto s300; return; # undef neqns # undef nofsub } /*********************************************************************** * NAME * * qmdrch - Quotient MD ReaCHable set * * SYNOPSIS * * #include "glpqmd.h" * void qmdrch(int *root, int xadj[], int adjncy[], int deg[], * int marker[], int *rchsze, int rchset[], int *nhdsze, * int nbrhd[]); * * PURPOSE * * This subroutine determines the reachable set of a node through a * given subset. The adjancy structure is assumed to be stored in a * quotient graph format. * * INPUT PARAMETERS * * root - the given node not in the subset; * (xadj, adjncy) - * the adjancy structure pair; * deg - the degree vector. deg[i] < 0 means the node belongs to the * given subset. * * OUTPUT PARAMETERS * * (rchsze, rchset) - * the reachable set; * (nhdsze, nbrhd) - * the neighborhood set. * * UPDATED PARAMETERS * * marker - the marker vector for reach and nbrhd sets. > 0 means the * node is in reach set. < 0 means the node has been merged * with others in the quotient or it is in nbrhd set. ***********************************************************************/ void qmdrch(int *_root, int xadj[], int adjncy[], int deg[], int marker[], int *_rchsze, int rchset[], int *_nhdsze, int nbrhd[]) { int i, istop, istrt, j, jstop, jstrt, nabor, node; # define root (*_root) # define rchsze (*_rchsze) # define nhdsze (*_nhdsze) /* Loop through the neighbors of root in the quotient graph. */ nhdsze = 0; rchsze = 0; istrt = xadj[root]; istop = xadj[root+1] - 1; if (istop < istrt) return; for (i = istrt; i <= istop; i++) { nabor = adjncy[i]; if (nabor == 0) return; if (marker[nabor] == 0) { if (deg[nabor] >= 0) { /* Include nabor into the reachable set. */ rchsze++; rchset[rchsze] = nabor; marker[nabor] = 1; goto s600; } /* nabor has been eliminated. Find nodes reachable from it. */ marker[nabor] = -1; nhdsze++; nbrhd[nhdsze] = nabor; s300: jstrt = xadj[nabor]; jstop = xadj[nabor+1] - 1; for (j = jstrt; j <= jstop; j++) { node = adjncy[j]; nabor = - node; if (node < 0) goto s300; if (node == 0) goto s600; if (marker[node] == 0) { rchsze++; rchset[rchsze] = node; marker[node] = 1; } } } s600: ; } return; # undef root # undef rchsze # undef nhdsze } /*********************************************************************** * NAME * * qmdqt - Quotient MD Quotient graph Transformation * * SYNOPSIS * * #include "glpqmd.h" * void qmdqt(int *root, int xadj[], int adjncy[], int marker[], * int *rchsze, int rchset[], int nbrhd[]); * * PURPOSE * * This subroutine performs the quotient graph transformation after a * node has been eliminated. * * INPUT PARAMETERS * * root - the node just eliminated. It becomes the representative of * the new supernode; * (xadj, adjncy) - * the adjancy structure; * (rchsze, rchset) - * the reachable set of root in the old quotient graph; * nbrhd - the neighborhood set which will be merged with root to form * the new supernode; * marker - the marker vector. * * UPDATED PARAMETERS * * adjncy - becomes the adjncy of the quotient graph. ***********************************************************************/ void qmdqt(int *_root, int xadj[], int adjncy[], int marker[], int *_rchsze, int rchset[], int nbrhd[]) { int inhd, irch, j, jstop, jstrt, link, nabor, node; # define root (*_root) # define rchsze (*_rchsze) irch = 0; inhd = 0; node = root; s100: jstrt = xadj[node]; jstop = xadj[node+1] - 2; if (jstop >= jstrt) { /* Place reach nodes into the adjacent list of node. */ for (j = jstrt; j <= jstop; j++) { irch++; adjncy[j] = rchset[irch]; if (irch >= rchsze) goto s400; } } /* Link to other space provided by the nbrhd set. */ link = adjncy[jstop+1]; node = - link; if (link >= 0) { inhd++; node = nbrhd[inhd]; adjncy[jstop+1] = - node; } goto s100; /* All reachable nodes have been saved. End the adjacent list. Add root to the neighborhood list of each node in the reach set. */ s400: adjncy[j+1] = 0; for (irch = 1; irch <= rchsze; irch++) { node = rchset[irch]; if (marker[node] >= 0) { jstrt = xadj[node]; jstop = xadj[node+1] - 1; for (j = jstrt; j <= jstop; j++) { nabor = adjncy[j]; if (marker[nabor] < 0) { adjncy[j] = root; goto s600; } } } s600: ; } return; # undef root # undef rchsze } /*********************************************************************** * NAME * * qmdupd - Quotient MD UPDate * * SYNOPSIS * * #include "glpqmd.h" * void qmdupd(int xadj[], int adjncy[], int *nlist, int list[], * int deg[], int qsize[], int qlink[], int marker[], int rchset[], * int nbrhd[]); * * PURPOSE * * This routine performs degree update for a set of nodes in the minimum * degree algorithm. * * INPUT PARAMETERS * * (xadj, adjncy) - * the adjancy structure; * (nlist, list) - * the list of nodes whose degree has to be updated. * * UPDATED PARAMETERS * * deg - the degree vector; * qsize - size of indistinguishable supernodes; * qlink - linked list for indistinguishable nodes; * marker - used to mark those nodes in reach/nbrhd sets. * * WORKING PARAMETERS * * rchset - the reachable set; * nbrhd - the neighborhood set. * * PROGRAM SUBROUTINES * * qmdmrg. ***********************************************************************/ void qmdupd(int xadj[], int adjncy[], int *_nlist, int list[], int deg[], int qsize[], int qlink[], int marker[], int rchset[], int nbrhd[]) { int deg0, deg1, il, inhd, inode, irch, j, jstop, jstrt, mark, nabor, nhdsze, node, rchsze; # define nlist (*_nlist) /* Find all eliminated supernodes that are adjacent to some nodes in the given list. Put them into (nhdsze, nbrhd). deg0 contains the number of nodes in the list. */ if (nlist <= 0) return; deg0 = 0; nhdsze = 0; for (il = 1; il <= nlist; il++) { node = list[il]; deg0 += qsize[node]; jstrt = xadj[node]; jstop = xadj[node+1] - 1; for (j = jstrt; j <= jstop; j++) { nabor = adjncy[j]; if (marker[nabor] == 0 && deg[nabor] < 0) { marker[nabor] = -1; nhdsze++; nbrhd[nhdsze] = nabor; } } } /* Merge indistinguishable nodes in the list by calling the subroutine qmdmrg. */ if (nhdsze > 0) qmdmrg(xadj, adjncy, deg, qsize, qlink, marker, °0, &nhdsze, nbrhd, rchset, &nbrhd[nhdsze+1]); /* Find the new degrees of the nodes that have not been merged. */ for (il = 1; il <= nlist; il++) { node = list[il]; mark = marker[node]; if (mark == 0 || mark == 1) { marker[node] = 2; qmdrch(&node, xadj, adjncy, deg, marker, &rchsze, rchset, &nhdsze, nbrhd); deg1 = deg0; if (rchsze > 0) { for (irch = 1; irch <= rchsze; irch++) { inode = rchset[irch]; deg1 += qsize[inode]; marker[inode] = 0; } } deg[node] = deg1 - 1; if (nhdsze > 0) { for (inhd = 1; inhd <= nhdsze; inhd++) { inode = nbrhd[inhd]; marker[inode] = 0; } } } } return; # undef nlist } /*********************************************************************** * NAME * * qmdmrg - Quotient MD MeRGe * * SYNOPSIS * * #include "qmdmrg.h" * void qmdmrg(int xadj[], int adjncy[], int deg[], int qsize[], * int qlink[], int marker[], int *deg0, int *nhdsze, int nbrhd[], * int rchset[], int ovrlp[]); * * PURPOSE * * This routine merges indistinguishable nodes in the minimum degree * ordering algorithm. It also computes the new degrees of these new * supernodes. * * INPUT PARAMETERS * * (xadj, adjncy) - * the adjancy structure; * deg0 - the number of nodes in the given set; * (nhdsze, nbrhd) - * the set of eliminated supernodes adjacent to some nodes in * the set. * * UPDATED PARAMETERS * * deg - the degree vector; * qsize - size of indistinguishable nodes; * qlink - linked list for indistinguishable nodes; * marker - the given set is given by those nodes with marker value set * to 1. Those nodes with degree updated will have marker value * set to 2. * * WORKING PARAMETERS * * rchset - the reachable set; * ovrlp - temp vector to store the intersection of two reachable sets. ***********************************************************************/ void qmdmrg(int xadj[], int adjncy[], int deg[], int qsize[], int qlink[], int marker[], int *_deg0, int *_nhdsze, int nbrhd[], int rchset[], int ovrlp[]) { int deg1, head, inhd, iov, irch, j, jstop, jstrt, link, lnode, mark, mrgsze, nabor, node, novrlp, rchsze, root; # define deg0 (*_deg0) # define nhdsze (*_nhdsze) /* Initialization. */ if (nhdsze <= 0) return; for (inhd = 1; inhd <= nhdsze; inhd++) { root = nbrhd[inhd]; marker[root] = 0; } /* Loop through each eliminated supernode in the set (nhdsze, nbrhd). */ for (inhd = 1; inhd <= nhdsze; inhd++) { root = nbrhd[inhd]; marker[root] = -1; rchsze = 0; novrlp = 0; deg1 = 0; s200: jstrt = xadj[root]; jstop = xadj[root+1] - 1; /* Determine the reachable set and its intersection with the input reachable set. */ for (j = jstrt; j <= jstop; j++) { nabor = adjncy[j]; root = - nabor; if (nabor < 0) goto s200; if (nabor == 0) break; mark = marker[nabor]; if (mark == 0) { rchsze++; rchset[rchsze] = nabor; deg1 += qsize[nabor]; marker[nabor] = 1; } else if (mark == 1) { novrlp++; ovrlp[novrlp] = nabor; marker[nabor] = 2; } } /* From the overlapped set, determine the nodes that can be merged together. */ head = 0; mrgsze = 0; for (iov = 1; iov <= novrlp; iov++) { node = ovrlp[iov]; jstrt = xadj[node]; jstop = xadj[node+1] - 1; for (j = jstrt; j <= jstop; j++) { nabor = adjncy[j]; if (marker[nabor] == 0) { marker[node] = 1; goto s1100; } } /* Node belongs to the new merged supernode. Update the vectors qlink and qsize. */ mrgsze += qsize[node]; marker[node] = -1; lnode = node; s900: link = qlink[lnode]; if (link > 0) { lnode = link; goto s900; } qlink[lnode] = head; head = node; s1100: ; } if (head > 0) { qsize[head] = mrgsze; deg[head] = deg0 + deg1 - 1; marker[head] = 2; } /* Reset marker values. */ root = nbrhd[inhd]; marker[root] = 0; if (rchsze > 0) { for (irch = 1; irch <= rchsze; irch++) { node = rchset[irch]; marker[node] = 0; } } } return; # undef deg0 # undef nhdsze } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpmpl06.c0000644000076500000240000007543713524616144025224 0ustar tamasstaff00000000000000/* glpmpl06.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wshorten-64-to-32" #pragma clang diagnostic ignored "-Wsometimes-uninitialized" #pragma clang diagnostic ignored "-Wself-assign" #endif #define _GLPSTD_ERRNO #define _GLPSTD_STDIO #include "glpmpl.h" #include "glpsql.h" /**********************************************************************/ #define CSV_FIELD_MAX 50 /* maximal number of fields in record */ #define CSV_FDLEN_MAX 100 /* maximal field length */ struct csv { /* comma-separated values file */ int mode; /* 'R' = reading; 'W' = writing */ char *fname; /* name of csv file */ FILE *fp; /* stream assigned to csv file */ jmp_buf jump; /* address for non-local go to in case of error */ int count; /* record count */ /*--------------------------------------------------------------*/ /* used only for input csv file */ int c; /* current character or EOF */ int what; /* current marker: */ #define CSV_EOF 0 /* end-of-file */ #define CSV_EOR 1 /* end-of-record */ #define CSV_NUM 2 /* floating-point number */ #define CSV_STR 3 /* character string */ char field[CSV_FDLEN_MAX+1]; /* current field just read */ int nf; /* number of fields in the csv file */ int ref[1+CSV_FIELD_MAX]; /* ref[k] = k', if k-th field of the csv file corresponds to k'-th field in the table statement; if ref[k] = 0, k-th field of the csv file is ignored */ #if 1 /* 01/VI-2010 */ int nskip; /* number of comment records preceding the header record */ #endif }; #undef read_char static void read_char(struct csv *csv) { /* read character from csv data file */ int c; xassert(csv->c != EOF); if (csv->c == '\n') csv->count++; loop: c = fgetc(csv->fp); if (ferror(csv->fp)) { xprintf("%s:%d: read error - %s\n", csv->fname, csv->count, strerror(errno)); longjmp(csv->jump, 0); } if (feof(csv->fp)) { if (csv->c == '\n') { csv->count--; c = EOF; } else { xprintf("%s:%d: warning: missing final end-of-line\n", csv->fname, csv->count); c = '\n'; } } else if (c == '\r') goto loop; else if (c == '\n') ; else if (iscntrl(c)) { xprintf("%s:%d: invalid control character 0x%02X\n", csv->fname, csv->count, c); longjmp(csv->jump, 0); } csv->c = c; return; } static void read_field(struct csv *csv) { /* read field from csv data file */ /* check for end of file */ if (csv->c == EOF) { csv->what = CSV_EOF; strcpy(csv->field, "EOF"); goto done; } /* check for end of record */ if (csv->c == '\n') { csv->what = CSV_EOR; strcpy(csv->field, "EOR"); read_char(csv); if (csv->c == ',') err1: { xprintf("%s:%d: empty field not allowed\n", csv->fname, csv->count); longjmp(csv->jump, 0); } if (csv->c == '\n') { xprintf("%s:%d: empty record not allowed\n", csv->fname, csv->count); longjmp(csv->jump, 0); } #if 1 /* 01/VI-2010 */ /* skip comment records; may appear only before the very first record containing field names */ if (csv->c == '#' && csv->count == 1) { while (csv->c == '#') { while (csv->c != '\n') read_char(csv); read_char(csv); csv->nskip++; } } #endif goto done; } /* skip comma before next field */ if (csv->c == ',') read_char(csv); /* read field */ if (csv->c == '\'' || csv->c == '"') { /* read a field enclosed in quotes */ int quote = csv->c, len = 0; csv->what = CSV_STR; /* skip opening quote */ read_char(csv); /* read field characters within quotes */ for (;;) { /* check for closing quote and read it */ if (csv->c == quote) { read_char(csv); if (csv->c == quote) ; else if (csv->c == ',' || csv->c == '\n') break; else { xprintf("%s:%d: invalid field\n", csv->fname, csv->count); longjmp(csv->jump, 0); } } /* check the current field length */ if (len == CSV_FDLEN_MAX) err2: { xprintf("%s:%d: field too long\n", csv->fname, csv->count); longjmp(csv->jump, 0); } /* add the current character to the field */ csv->field[len++] = (char)csv->c; /* read the next character */ read_char(csv); } /* the field has been read */ if (len == 0) goto err1; csv->field[len] = '\0'; } else { /* read a field not enclosed in quotes */ int len = 0; double temp; csv->what = CSV_NUM; while (!(csv->c == ',' || csv->c == '\n')) { /* quotes within the field are not allowed */ if (csv->c == '\'' || csv->c == '"') { xprintf("%s:%d: invalid use of single or double quote wi" "thin field\n", csv->fname, csv->count); longjmp(csv->jump, 0); } /* check the current field length */ if (len == CSV_FDLEN_MAX) goto err2; /* add the current character to the field */ csv->field[len++] = (char)csv->c; /* read the next character */ read_char(csv); } /* the field has been read */ if (len == 0) goto err1; csv->field[len] = '\0'; /* check the field type */ if (str2num(csv->field, &temp)) csv->what = CSV_STR; } done: return; } static struct csv *csv_open_file(TABDCA *dca, int mode) { /* open csv data file */ struct csv *csv; /* create control structure */ csv = xmalloc(sizeof(struct csv)); csv->mode = mode; csv->fname = NULL; csv->fp = NULL; if (setjmp(csv->jump)) goto fail; csv->count = 0; csv->c = '\n'; csv->what = 0; csv->field[0] = '\0'; csv->nf = 0; /* try to open the csv data file */ if (mpl_tab_num_args(dca) < 2) { xprintf("csv_driver: file name not specified\n"); longjmp(csv->jump, 0); } csv->fname = xmalloc(strlen(mpl_tab_get_arg(dca, 2))+1); strcpy(csv->fname, mpl_tab_get_arg(dca, 2)); if (mode == 'R') { /* open the file for reading */ int k; csv->fp = fopen(csv->fname, "r"); if (csv->fp == NULL) { xprintf("csv_driver: unable to open %s - %s\n", csv->fname, strerror(errno)); longjmp(csv->jump, 0); } #if 1 /* 01/VI-2010 */ csv->nskip = 0; #endif /* skip fake new-line */ read_field(csv); xassert(csv->what == CSV_EOR); /* read field names */ xassert(csv->nf == 0); for (;;) { read_field(csv); if (csv->what == CSV_EOR) break; if (csv->what != CSV_STR) { xprintf("%s:%d: invalid field name\n", csv->fname, csv->count); longjmp(csv->jump, 0); } if (csv->nf == CSV_FIELD_MAX) { xprintf("%s:%d: too many fields\n", csv->fname, csv->count); longjmp(csv->jump, 0); } csv->nf++; /* find corresponding field in the table statement */ for (k = mpl_tab_num_flds(dca); k >= 1; k--) { if (strcmp(mpl_tab_get_name(dca, k), csv->field) == 0) break; } csv->ref[csv->nf] = k; } /* find dummy RECNO field in the table statement */ for (k = mpl_tab_num_flds(dca); k >= 1; k--) if (strcmp(mpl_tab_get_name(dca, k), "RECNO") == 0) break; csv->ref[0] = k; } else if (mode == 'W') { /* open the file for writing */ int k, nf; csv->fp = fopen(csv->fname, "w"); if (csv->fp == NULL) { xprintf("csv_driver: unable to create %s - %s\n", csv->fname, strerror(errno)); longjmp(csv->jump, 0); } /* write field names */ nf = mpl_tab_num_flds(dca); for (k = 1; k <= nf; k++) fprintf(csv->fp, "%s%c", mpl_tab_get_name(dca, k), k < nf ? ',' : '\n'); csv->count++; } else xassert(mode != mode); /* the file has been open */ return csv; fail: /* the file cannot be open */ if (csv->fname != NULL) xfree(csv->fname); if (csv->fp != NULL) fclose(csv->fp); xfree(csv); return NULL; } static int csv_read_record(TABDCA *dca, struct csv *csv) { /* read next record from csv data file */ int k, ret = 0; xassert(csv->mode == 'R'); if (setjmp(csv->jump)) { ret = 1; goto done; } /* read dummy RECNO field */ if (csv->ref[0] > 0) #if 0 /* 01/VI-2010 */ mpl_tab_set_num(dca, csv->ref[0], csv->count-1); #else mpl_tab_set_num(dca, csv->ref[0], csv->count-csv->nskip-1); #endif /* read fields */ for (k = 1; k <= csv->nf; k++) { read_field(csv); if (csv->what == CSV_EOF) { /* end-of-file reached */ xassert(k == 1); ret = -1; goto done; } else if (csv->what == CSV_EOR) { /* end-of-record reached */ int lack = csv->nf - k + 1; if (lack == 1) xprintf("%s:%d: one field missing\n", csv->fname, csv->count); else xprintf("%s:%d: %d fields missing\n", csv->fname, csv->count, lack); longjmp(csv->jump, 0); } else if (csv->what == CSV_NUM) { /* floating-point number */ if (csv->ref[k] > 0) { double num; xassert(str2num(csv->field, &num) == 0); mpl_tab_set_num(dca, csv->ref[k], num); } } else if (csv->what == CSV_STR) { /* character string */ if (csv->ref[k] > 0) mpl_tab_set_str(dca, csv->ref[k], csv->field); } else xassert(csv != csv); } /* now there must be NL */ read_field(csv); xassert(csv->what != CSV_EOF); if (csv->what != CSV_EOR) { xprintf("%s:%d: too many fields\n", csv->fname, csv->count); longjmp(csv->jump, 0); } done: return ret; } static int csv_write_record(TABDCA *dca, struct csv *csv) { /* write next record to csv data file */ int k, nf, ret = 0; const char *c; xassert(csv->mode == 'W'); nf = mpl_tab_num_flds(dca); for (k = 1; k <= nf; k++) { switch (mpl_tab_get_type(dca, k)) { case 'N': fprintf(csv->fp, "%.*g", DBL_DIG, mpl_tab_get_num(dca, k)); break; case 'S': fputc('"', csv->fp); for (c = mpl_tab_get_str(dca, k); *c != '\0'; c++) { if (*c == '"') fputc('"', csv->fp), fputc('"', csv->fp); else fputc(*c, csv->fp); } fputc('"', csv->fp); break; default: xassert(dca != dca); } fputc(k < nf ? ',' : '\n', csv->fp); } csv->count++; if (ferror(csv->fp)) { xprintf("%s:%d: write error - %s\n", csv->fname, csv->count, strerror(errno)); ret = 1; } return ret; } static int csv_close_file(TABDCA *dca, struct csv *csv) { /* close csv data file */ int ret = 0; xassert(dca == dca); if (csv->mode == 'W') { fflush(csv->fp); if (ferror(csv->fp)) { xprintf("%s:%d: write error - %s\n", csv->fname, csv->count, strerror(errno)); ret = 1; } } xfree(csv->fname); fclose(csv->fp); xfree(csv); return ret; } /**********************************************************************/ #define DBF_FIELD_MAX 50 /* maximal number of fields in record */ #define DBF_FDLEN_MAX 100 /* maximal field length */ struct dbf { /* xBASE data file */ int mode; /* 'R' = reading; 'W' = writing */ char *fname; /* name of xBASE file */ FILE *fp; /* stream assigned to xBASE file */ jmp_buf jump; /* address for non-local go to in case of error */ int offset; /* offset of a byte to be read next */ int count; /* record count */ int nf; /* number of fields */ int ref[1+DBF_FIELD_MAX]; /* ref[k] = k', if k-th field of the csv file corresponds to k'-th field in the table statement; if ref[k] = 0, k-th field of the csv file is ignored */ int type[1+DBF_FIELD_MAX]; /* type[k] is type of k-th field */ int len[1+DBF_FIELD_MAX]; /* len[k] is length of k-th field */ int prec[1+DBF_FIELD_MAX]; /* prec[k] is precision of k-th field */ }; static int read_byte(struct dbf *dbf) { /* read byte from xBASE data file */ int b; b = fgetc(dbf->fp); if (ferror(dbf->fp)) { xprintf("%s:0x%X: read error - %s\n", dbf->fname, dbf->offset, strerror(errno)); longjmp(dbf->jump, 0); } if (feof(dbf->fp)) { xprintf("%s:0x%X: unexpected end of file\n", dbf->fname, dbf->offset); longjmp(dbf->jump, 0); } xassert(0x00 <= b && b <= 0xFF); dbf->offset++; return b; } static void read_header(TABDCA *dca, struct dbf *dbf) { /* read xBASE data file header */ int b, j, k, recl; char name[10+1]; /* (ignored) */ for (j = 1; j <= 10; j++) read_byte(dbf); /* length of each record, in bytes */ recl = read_byte(dbf); recl += read_byte(dbf) << 8; /* (ignored) */ for (j = 1; j <= 20; j++) read_byte(dbf); /* field descriptor array */ xassert(dbf->nf == 0); for (;;) { /* check for end of array */ b = read_byte(dbf); if (b == 0x0D) break; if (dbf->nf == DBF_FIELD_MAX) { xprintf("%s:0x%X: too many fields\n", dbf->fname, dbf->offset); longjmp(dbf->jump, 0); } dbf->nf++; /* field name */ name[0] = (char)b; for (j = 1; j < 10; j++) { b = read_byte(dbf); name[j] = (char)b; } name[10] = '\0'; b = read_byte(dbf); if (b != 0x00) { xprintf("%s:0x%X: invalid field name\n", dbf->fname, dbf->offset); longjmp(dbf->jump, 0); } /* find corresponding field in the table statement */ for (k = mpl_tab_num_flds(dca); k >= 1; k--) if (strcmp(mpl_tab_get_name(dca, k), name) == 0) break; dbf->ref[dbf->nf] = k; /* field type */ b = read_byte(dbf); if (!(b == 'C' || b == 'N')) { xprintf("%s:0x%X: invalid field type\n", dbf->fname, dbf->offset); longjmp(dbf->jump, 0); } dbf->type[dbf->nf] = b; /* (ignored) */ for (j = 1; j <= 4; j++) read_byte(dbf); /* field length */ b = read_byte(dbf); if (b == 0) { xprintf("%s:0x%X: invalid field length\n", dbf->fname, dbf->offset); longjmp(dbf->jump, 0); } if (b > DBF_FDLEN_MAX) { xprintf("%s:0x%X: field too long\n", dbf->fname, dbf->offset); longjmp(dbf->jump, 0); } dbf->len[dbf->nf] = b; recl -= b; /* (ignored) */ for (j = 1; j <= 15; j++) read_byte(dbf); } if (recl != 1) { xprintf("%s:0x%X: invalid file header\n", dbf->fname, dbf->offset); longjmp(dbf->jump, 0); } /* find dummy RECNO field in the table statement */ for (k = mpl_tab_num_flds(dca); k >= 1; k--) if (strcmp(mpl_tab_get_name(dca, k), "RECNO") == 0) break; dbf->ref[0] = k; return; } static void parse_third_arg(TABDCA *dca, struct dbf *dbf) { /* parse xBASE file format (third argument) */ int j, k, temp; const char *arg; dbf->nf = mpl_tab_num_flds(dca); arg = mpl_tab_get_arg(dca, 3), j = 0; for (k = 1; k <= dbf->nf; k++) { /* parse specification of k-th field */ if (arg[j] == '\0') { xprintf("xBASE driver: field %s: specification missing\n", mpl_tab_get_name(dca, k)); longjmp(dbf->jump, 0); } /* parse field type */ if (arg[j] == 'C' || arg[j] == 'N') dbf->type[k] = arg[j], j++; else { xprintf("xBASE driver: field %s: invalid field type\n", mpl_tab_get_name(dca, k)); longjmp(dbf->jump, 0); } /* check for left parenthesis */ if (arg[j] == '(') j++; else err: { xprintf("xBASE driver: field %s: invalid field format\n", mpl_tab_get_name(dca, k)); longjmp(dbf->jump, 0); } /* parse field length */ temp = 0; while (isdigit(arg[j])) { if (temp > DBF_FDLEN_MAX) break; temp = 10 * temp + (arg[j] - '0'), j++; } if (!(1 <= temp && temp <= DBF_FDLEN_MAX)) { xprintf("xBASE driver: field %s: invalid field length\n", mpl_tab_get_name(dca, k)); longjmp(dbf->jump, 0); } dbf->len[k] = temp; /* parse optional field precision */ if (dbf->type[k] == 'N' && arg[j] == ',') { j++; temp = 0; while (isdigit(arg[j])) { if (temp > dbf->len[k]) break; temp = 10 * temp + (arg[j] - '0'), j++; } if (temp > dbf->len[k]) { xprintf("xBASE driver: field %s: invalid field precision" "\n", mpl_tab_get_name(dca, k)); longjmp(dbf->jump, 0); } dbf->prec[k] = temp; } else dbf->prec[k] = 0; /* check for right parenthesis */ if (arg[j] == ')') j++; else goto err; } /* ignore other specifications */ return; } static void write_byte(struct dbf *dbf, int b) { /* write byte to xBASE data file */ fputc(b, dbf->fp); dbf->offset++; return; } static void write_header(TABDCA *dca, struct dbf *dbf) { /* write xBASE data file header */ int j, k, temp; const char *name; /* version number */ write_byte(dbf, 0x03 /* file without DBT */); /* date of last update (YYMMDD) */ write_byte(dbf, 70 /* 1970 */); write_byte(dbf, 1 /* January */); write_byte(dbf, 1 /* 1st */); /* number of records (unknown so far) */ for (j = 1; j <= 4; j++) write_byte(dbf, 0xFF); /* length of the header, in bytes */ temp = 32 + dbf->nf * 32 + 1; write_byte(dbf, temp); write_byte(dbf, temp >> 8); /* length of each record, in bytes */ temp = 1; for (k = 1; k <= dbf->nf; k++) temp += dbf->len[k]; write_byte(dbf, temp); write_byte(dbf, temp >> 8); /* (reserved) */ for (j = 1; j <= 20; j++) write_byte(dbf, 0x00); /* field descriptor array */ for (k = 1; k <= dbf->nf; k++) { /* field name (terminated by 0x00) */ name = mpl_tab_get_name(dca, k); for (j = 0; j < 10 && name[j] != '\0'; j++) write_byte(dbf, name[j]); for (j = j; j < 11; j++) write_byte(dbf, 0x00); /* field type */ write_byte(dbf, dbf->type[k]); /* (reserved) */ for (j = 1; j <= 4; j++) write_byte(dbf, 0x00); /* field length */ write_byte(dbf, dbf->len[k]); /* field precision */ write_byte(dbf, dbf->prec[k]); /* (reserved) */ for (j = 1; j <= 14; j++) write_byte(dbf, 0x00); } /* end of header */ write_byte(dbf, 0x0D); return; } static struct dbf *dbf_open_file(TABDCA *dca, int mode) { /* open xBASE data file */ struct dbf *dbf; /* create control structure */ dbf = xmalloc(sizeof(struct dbf)); dbf->mode = mode; dbf->fname = NULL; dbf->fp = NULL; if (setjmp(dbf->jump)) goto fail; dbf->offset = 0; dbf->count = 0; dbf->nf = 0; /* try to open the xBASE data file */ if (mpl_tab_num_args(dca) < 2) { xprintf("xBASE driver: file name not specified\n"); longjmp(dbf->jump, 0); } dbf->fname = xmalloc(strlen(mpl_tab_get_arg(dca, 2))+1); strcpy(dbf->fname, mpl_tab_get_arg(dca, 2)); if (mode == 'R') { /* open the file for reading */ dbf->fp = fopen(dbf->fname, "rb"); if (dbf->fp == NULL) { xprintf("xBASE driver: unable to open %s - %s\n", dbf->fname, strerror(errno)); longjmp(dbf->jump, 0); } read_header(dca, dbf); } else if (mode == 'W') { /* open the file for writing */ if (mpl_tab_num_args(dca) < 3) { xprintf("xBASE driver: file format not specified\n"); longjmp(dbf->jump, 0); } parse_third_arg(dca, dbf); dbf->fp = fopen(dbf->fname, "wb"); if (dbf->fp == NULL) { xprintf("xBASE driver: unable to create %s - %s\n", dbf->fname, strerror(errno)); longjmp(dbf->jump, 0); } write_header(dca, dbf); } else xassert(mode != mode); /* the file has been open */ return dbf; fail: /* the file cannot be open */ if (dbf->fname != NULL) xfree(dbf->fname); if (dbf->fp != NULL) fclose(dbf->fp); xfree(dbf); return NULL; } static int dbf_read_record(TABDCA *dca, struct dbf *dbf) { /* read next record from xBASE data file */ int b, j, k, ret = 0; char buf[DBF_FDLEN_MAX+1]; xassert(dbf->mode == 'R'); if (setjmp(dbf->jump)) { ret = 1; goto done; } /* check record flag */ b = read_byte(dbf); if (b == 0x1A) { /* end of data */ ret = -1; goto done; } if (b != 0x20) { xprintf("%s:0x%X: invalid record flag\n", dbf->fname, dbf->offset); longjmp(dbf->jump, 0); } /* read dummy RECNO field */ if (dbf->ref[0] > 0) mpl_tab_set_num(dca, dbf->ref[0], dbf->count+1); /* read fields */ for (k = 1; k <= dbf->nf; k++) { /* read k-th field */ for (j = 0; j < dbf->len[k]; j++) buf[j] = (char)read_byte(dbf); buf[dbf->len[k]] = '\0'; /* set field value */ if (dbf->type[k] == 'C') { /* character field */ if (dbf->ref[k] > 0) mpl_tab_set_str(dca, dbf->ref[k], strtrim(buf)); } else if (dbf->type[k] == 'N') { /* numeric field */ if (dbf->ref[k] > 0) { double num; strspx(buf); xassert(str2num(buf, &num) == 0); mpl_tab_set_num(dca, dbf->ref[k], num); } } else xassert(dbf != dbf); } /* increase record count */ dbf->count++; done: return ret; } static int dbf_write_record(TABDCA *dca, struct dbf *dbf) { /* write next record to xBASE data file */ int j, k, ret = 0; char buf[255+1]; xassert(dbf->mode == 'W'); if (setjmp(dbf->jump)) { ret = 1; goto done; } /* record flag */ write_byte(dbf, 0x20); xassert(dbf->nf == mpl_tab_num_flds(dca)); for (k = 1; k <= dbf->nf; k++) { if (dbf->type[k] == 'C') { /* character field */ const char *str; if (mpl_tab_get_type(dca, k) == 'N') { sprintf(buf, "%.*g", DBL_DIG, mpl_tab_get_num(dca, k)); str = buf; } else if (mpl_tab_get_type(dca, k) == 'S') str = mpl_tab_get_str(dca, k); else xassert(dca != dca); if ((int)strlen(str) > dbf->len[k]) { xprintf("xBASE driver: field %s: cannot convert %.15s..." " to field format\n", mpl_tab_get_name(dca, k), str); longjmp(dbf->jump, 0); } for (j = 0; j < dbf->len[k] && str[j] != '\0'; j++) write_byte(dbf, str[j]); for (j = j; j < dbf->len[k]; j++) write_byte(dbf, ' '); } else if (dbf->type[k] == 'N') { /* numeric field */ double num = mpl_tab_get_num(dca, k); if (fabs(num) > 1e20) err: { xprintf("xBASE driver: field %s: cannot convert %g to fi" "eld format\n", mpl_tab_get_name(dca, k), num); longjmp(dbf->jump, 0); } sprintf(buf, "%*.*f", dbf->len[k], dbf->prec[k], num); xassert(strlen(buf) < sizeof(buf)); if ((int)strlen(buf) != dbf->len[k]) goto err; for (j = 0; j < dbf->len[k]; j++) write_byte(dbf, buf[j]); } else xassert(dbf != dbf); } /* increase record count */ dbf->count++; done: return ret; } static int dbf_close_file(TABDCA *dca, struct dbf *dbf) { /* close xBASE data file */ int ret = 0; xassert(dca == dca); if (dbf->mode == 'W') { if (setjmp(dbf->jump)) { ret = 1; goto skip; } /* end-of-file flag */ write_byte(dbf, 0x1A); /* number of records */ dbf->offset = 4; if (fseek(dbf->fp, dbf->offset, SEEK_SET)) { xprintf("%s:0x%X: seek error - %s\n", dbf->fname, dbf->offset, strerror(errno)); longjmp(dbf->jump, 0); } write_byte(dbf, dbf->count); write_byte(dbf, dbf->count >> 8); write_byte(dbf, dbf->count >> 16); write_byte(dbf, dbf->count >> 24); fflush(dbf->fp); if (ferror(dbf->fp)) { xprintf("%s:0x%X: write error - %s\n", dbf->fname, dbf->offset, strerror(errno)); longjmp(dbf->jump, 0); } skip: ; } xfree(dbf->fname); fclose(dbf->fp); xfree(dbf); return ret; } /**********************************************************************/ #define TAB_CSV 1 #define TAB_XBASE 2 #define TAB_ODBC 3 #define TAB_MYSQL 4 void mpl_tab_drv_open(MPL *mpl, int mode) { TABDCA *dca = mpl->dca; xassert(dca->id == 0); xassert(dca->link == NULL); xassert(dca->na >= 1); if (strcmp(dca->arg[1], "CSV") == 0) { dca->id = TAB_CSV; dca->link = csv_open_file(dca, mode); } else if (strcmp(dca->arg[1], "xBASE") == 0) { dca->id = TAB_XBASE; dca->link = dbf_open_file(dca, mode); } else if (strcmp(dca->arg[1], "ODBC") == 0 || strcmp(dca->arg[1], "iODBC") == 0) { dca->id = TAB_ODBC; dca->link = db_iodbc_open(dca, mode); } else if (strcmp(dca->arg[1], "MySQL") == 0) { dca->id = TAB_MYSQL; dca->link = db_mysql_open(dca, mode); } else xprintf("Invalid table driver `%s'\n", dca->arg[1]); if (dca->link == NULL) error(mpl, "error on opening table %s", mpl->stmt->u.tab->name); return; } int mpl_tab_drv_read(MPL *mpl) { TABDCA *dca = mpl->dca; int ret; switch (dca->id) { case TAB_CSV: ret = csv_read_record(dca, dca->link); break; case TAB_XBASE: ret = dbf_read_record(dca, dca->link); break; case TAB_ODBC: ret = db_iodbc_read(dca, dca->link); break; case TAB_MYSQL: ret = db_mysql_read(dca, dca->link); break; default: xassert(dca != dca); } if (ret > 0) error(mpl, "error on reading data from table %s", mpl->stmt->u.tab->name); return ret; } void mpl_tab_drv_write(MPL *mpl) { TABDCA *dca = mpl->dca; int ret; switch (dca->id) { case TAB_CSV: ret = csv_write_record(dca, dca->link); break; case TAB_XBASE: ret = dbf_write_record(dca, dca->link); break; case TAB_ODBC: ret = db_iodbc_write(dca, dca->link); break; case TAB_MYSQL: ret = db_mysql_write(dca, dca->link); break; default: xassert(dca != dca); } if (ret) error(mpl, "error on writing data to table %s", mpl->stmt->u.tab->name); return; } void mpl_tab_drv_close(MPL *mpl) { TABDCA *dca = mpl->dca; int ret; switch (dca->id) { case TAB_CSV: ret = csv_close_file(dca, dca->link); break; case TAB_XBASE: ret = dbf_close_file(dca, dca->link); break; case TAB_ODBC: ret = db_iodbc_close(dca, dca->link); break; case TAB_MYSQL: ret = db_mysql_close(dca, dca->link); break; default: xassert(dca != dca); } dca->id = 0; dca->link = NULL; if (ret) error(mpl, "error on closing table %s", mpl->stmt->u.tab->name); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpfhv.c0000644000076500000240000006553613524616144025050 0ustar tamasstaff00000000000000/* glpfhv.c (LP basis factorization, FHV eta file version) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wsign-conversion" #endif #include "glpfhv.h" #include "glpenv.h" #define xfault xerror /* CAUTION: DO NOT CHANGE THE LIMIT BELOW */ #define M_MAX 100000000 /* = 100*10^6 */ /* maximal order of the basis matrix */ /*********************************************************************** * NAME * * fhv_create_it - create LP basis factorization * * SYNOPSIS * * #include "glpfhv.h" * FHV *fhv_create_it(void); * * DESCRIPTION * * The routine fhv_create_it creates a program object, which represents * a factorization of LP basis. * * RETURNS * * The routine fhv_create_it returns a pointer to the object created. */ FHV *fhv_create_it(void) { FHV *fhv; fhv = xmalloc(sizeof(FHV)); fhv->m_max = fhv->m = 0; fhv->valid = 0; fhv->luf = luf_create_it(); fhv->hh_max = 50; fhv->hh_nfs = 0; fhv->hh_ind = fhv->hh_ptr = fhv->hh_len = NULL; fhv->p0_row = fhv->p0_col = NULL; fhv->cc_ind = NULL; fhv->cc_val = NULL; fhv->upd_tol = 1e-6; fhv->nnz_h = 0; return fhv; } /*********************************************************************** * NAME * * fhv_factorize - compute LP basis factorization * * SYNOPSIS * * #include "glpfhv.h" * int fhv_factorize(FHV *fhv, int m, int (*col)(void *info, int j, * int ind[], double val[]), void *info); * * DESCRIPTION * * The routine fhv_factorize computes the factorization of the basis * matrix B specified by the routine col. * * The parameter fhv specified the basis factorization data structure * created by the routine fhv_create_it. * * The parameter m specifies the order of B, m > 0. * * The formal routine col specifies the matrix B to be factorized. To * obtain j-th column of A the routine fhv_factorize calls the routine * col with the parameter j (1 <= j <= n). In response the routine col * should store row indices and numerical values of non-zero elements * of j-th column of B to locations ind[1,...,len] and val[1,...,len], * respectively, where len is the number of non-zeros in j-th column * returned on exit. Neither zero nor duplicate elements are allowed. * * The parameter info is a transit pointer passed to the routine col. * * RETURNS * * 0 The factorization has been successfully computed. * * FHV_ESING * The specified matrix is singular within the working precision. * * FHV_ECOND * The specified matrix is ill-conditioned. * * For more details see comments to the routine luf_factorize. * * ALGORITHM * * The routine fhv_factorize calls the routine luf_factorize (see the * module GLPLUF), which actually computes LU-factorization of the basis * matrix B in the form * * [B] = (F, V, P, Q), * * where F and V are such matrices that * * B = F * V, * * and P and Q are such permutation matrices that the matrix * * L = P * F * inv(P) * * is lower triangular with unity diagonal, and the matrix * * U = P * V * Q * * is upper triangular. * * In order to build the complete representation of the factorization * (see formula (1) in the file glpfhv.h) the routine fhv_factorize just * additionally sets H = I and P0 = P. */ int fhv_factorize(FHV *fhv, int m, int (*col)(void *info, int j, int ind[], double val[]), void *info) { int ret; if (m < 1) xfault("fhv_factorize: m = %d; invalid parameter\n", m); if (m > M_MAX) xfault("fhv_factorize: m = %d; matrix too big\n", m); fhv->m = m; /* invalidate the factorization */ fhv->valid = 0; /* allocate/reallocate arrays, if necessary */ if (fhv->hh_ind == NULL) fhv->hh_ind = xcalloc(1+fhv->hh_max, sizeof(int)); if (fhv->hh_ptr == NULL) fhv->hh_ptr = xcalloc(1+fhv->hh_max, sizeof(int)); if (fhv->hh_len == NULL) fhv->hh_len = xcalloc(1+fhv->hh_max, sizeof(int)); if (fhv->m_max < m) { if (fhv->p0_row != NULL) xfree(fhv->p0_row); if (fhv->p0_col != NULL) xfree(fhv->p0_col); if (fhv->cc_ind != NULL) xfree(fhv->cc_ind); if (fhv->cc_val != NULL) xfree(fhv->cc_val); fhv->m_max = m + 100; fhv->p0_row = xcalloc(1+fhv->m_max, sizeof(int)); fhv->p0_col = xcalloc(1+fhv->m_max, sizeof(int)); fhv->cc_ind = xcalloc(1+fhv->m_max, sizeof(int)); fhv->cc_val = xcalloc(1+fhv->m_max, sizeof(double)); } /* try to factorize the basis matrix */ switch (luf_factorize(fhv->luf, m, col, info)) { case 0: break; case LUF_ESING: ret = FHV_ESING; goto done; case LUF_ECOND: ret = FHV_ECOND; goto done; default: xassert(fhv != fhv); } /* the basis matrix has been successfully factorized */ fhv->valid = 1; /* H := I */ fhv->hh_nfs = 0; /* P0 := P */ memcpy(&fhv->p0_row[1], &fhv->luf->pp_row[1], sizeof(int) * m); memcpy(&fhv->p0_col[1], &fhv->luf->pp_col[1], sizeof(int) * m); /* currently H has no factors */ fhv->nnz_h = 0; ret = 0; done: /* return to the calling program */ return ret; } /*********************************************************************** * NAME * * fhv_h_solve - solve system H*x = b or H'*x = b * * SYNOPSIS * * #include "glpfhv.h" * void fhv_h_solve(FHV *fhv, int tr, double x[]); * * DESCRIPTION * * The routine fhv_h_solve solves either the system H*x = b (if the * flag tr is zero) or the system H'*x = b (if the flag tr is non-zero), * where the matrix H is a component of the factorization specified by * the parameter fhv, H' is a matrix transposed to H. * * On entry the array x should contain elements of the right-hand side * vector b in locations x[1], ..., x[m], where m is the order of the * matrix H. On exit this array will contain elements of the solution * vector x in the same locations. */ void fhv_h_solve(FHV *fhv, int tr, double x[]) { int nfs = fhv->hh_nfs; int *hh_ind = fhv->hh_ind; int *hh_ptr = fhv->hh_ptr; int *hh_len = fhv->hh_len; int *sv_ind = fhv->luf->sv_ind; double *sv_val = fhv->luf->sv_val; int i, k, beg, end, ptr; double temp; if (!fhv->valid) xfault("fhv_h_solve: the factorization is not valid\n"); if (!tr) { /* solve the system H*x = b */ for (k = 1; k <= nfs; k++) { i = hh_ind[k]; temp = x[i]; beg = hh_ptr[k]; end = beg + hh_len[k] - 1; for (ptr = beg; ptr <= end; ptr++) temp -= sv_val[ptr] * x[sv_ind[ptr]]; x[i] = temp; } } else { /* solve the system H'*x = b */ for (k = nfs; k >= 1; k--) { i = hh_ind[k]; temp = x[i]; if (temp == 0.0) continue; beg = hh_ptr[k]; end = beg + hh_len[k] - 1; for (ptr = beg; ptr <= end; ptr++) x[sv_ind[ptr]] -= sv_val[ptr] * temp; } } return; } /*********************************************************************** * NAME * * fhv_ftran - perform forward transformation (solve system B*x = b) * * SYNOPSIS * * #include "glpfhv.h" * void fhv_ftran(FHV *fhv, double x[]); * * DESCRIPTION * * The routine fhv_ftran performs forward transformation, i.e. solves * the system B*x = b, where B is the basis matrix, x is the vector of * unknowns to be computed, b is the vector of right-hand sides. * * On entry elements of the vector b should be stored in dense format * in locations x[1], ..., x[m], where m is the number of rows. On exit * the routine stores elements of the vector x in the same locations. */ void fhv_ftran(FHV *fhv, double x[]) { int *pp_row = fhv->luf->pp_row; int *pp_col = fhv->luf->pp_col; int *p0_row = fhv->p0_row; int *p0_col = fhv->p0_col; if (!fhv->valid) xfault("fhv_ftran: the factorization is not valid\n"); /* B = F*H*V, therefore inv(B) = inv(V)*inv(H)*inv(F) */ fhv->luf->pp_row = p0_row; fhv->luf->pp_col = p0_col; luf_f_solve(fhv->luf, 0, x); fhv->luf->pp_row = pp_row; fhv->luf->pp_col = pp_col; fhv_h_solve(fhv, 0, x); luf_v_solve(fhv->luf, 0, x); return; } /*********************************************************************** * NAME * * fhv_btran - perform backward transformation (solve system B'*x = b) * * SYNOPSIS * * #include "glpfhv.h" * void fhv_btran(FHV *fhv, double x[]); * * DESCRIPTION * * The routine fhv_btran performs backward transformation, i.e. solves * the system B'*x = b, where B' is a matrix transposed to the basis * matrix B, x is the vector of unknowns to be computed, b is the vector * of right-hand sides. * * On entry elements of the vector b should be stored in dense format * in locations x[1], ..., x[m], where m is the number of rows. On exit * the routine stores elements of the vector x in the same locations. */ void fhv_btran(FHV *fhv, double x[]) { int *pp_row = fhv->luf->pp_row; int *pp_col = fhv->luf->pp_col; int *p0_row = fhv->p0_row; int *p0_col = fhv->p0_col; if (!fhv->valid) xfault("fhv_btran: the factorization is not valid\n"); /* B = F*H*V, therefore inv(B') = inv(F')*inv(H')*inv(V') */ luf_v_solve(fhv->luf, 1, x); fhv_h_solve(fhv, 1, x); fhv->luf->pp_row = p0_row; fhv->luf->pp_col = p0_col; luf_f_solve(fhv->luf, 1, x); fhv->luf->pp_row = pp_row; fhv->luf->pp_col = pp_col; return; } /*********************************************************************** * NAME * * fhv_update_it - update LP basis factorization * * SYNOPSIS * * #include "glpfhv.h" * int fhv_update_it(FHV *fhv, int j, int len, const int ind[], * const double val[]); * * DESCRIPTION * * The routine fhv_update_it updates the factorization of the basis * matrix B after replacing its j-th column by a new vector. * * The parameter j specifies the number of column of B, which has been * replaced, 1 <= j <= m, where m is the order of B. * * Row indices and numerical values of non-zero elements of the new * column of B should be placed in locations ind[1], ..., ind[len] and * val[1], ..., val[len], resp., where len is the number of non-zeros * in the column. Neither zero nor duplicate elements are allowed. * * RETURNS * * 0 The factorization has been successfully updated. * * FHV_ESING * The adjacent basis matrix is structurally singular, since after * changing j-th column of matrix V by the new column (see algorithm * below) the case k1 > k2 occured. * * FHV_ECHECK * The factorization is inaccurate, since after transforming k2-th * row of matrix U = P*V*Q, its diagonal element u[k2,k2] is zero or * close to zero, * * FHV_ELIMIT * Maximal number of H factors has been reached. * * FHV_EROOM * Overflow of the sparse vector area. * * In case of non-zero return code the factorization becomes invalid. * It should not be used until it has been recomputed with the routine * fhv_factorize. * * ALGORITHM * * The routine fhv_update_it is based on the transformation proposed by * Forrest and Tomlin. * * Let j-th column of the basis matrix B have been replaced by new * column B[j]. In order to keep the equality B = F*H*V j-th column of * matrix V should be replaced by the column inv(F*H)*B[j]. * * From the standpoint of matrix U = P*V*Q, replacement of j-th column * of matrix V is equivalent to replacement of k1-th column of matrix U, * where k1 is determined by permutation matrix Q. Thus, matrix U loses * its upper triangular form and becomes the following: * * 1 k1 k2 m * 1 x x * x x x x x x x * . x * x x x x x x x * k1 . . * x x x x x x x * . . * x x x x x x x * . . * . x x x x x x * . . * . . x x x x x * . . * . . . x x x x * k2 . . * . . . . x x x * . . . . . . . . x x * m . . . . . . . . . x * * where row index k2 corresponds to the lowest non-zero element of * k1-th column. * * The routine moves rows and columns k1+1, k1+2, ..., k2 of matrix U * by one position to the left and upwards and moves k1-th row and k1-th * column to position k2. As the result of such symmetric permutations * matrix U becomes the following: * * 1 k1 k2 m * 1 x x x x x x x * x x * . x x x x x x * x x * k1 . . x x x x x * x x * . . . x x x x * x x * . . . . x x x * x x * . . . . . x x * x x * . . . . . . x * x x * k2 . . x x x x x * x x * . . . . . . . . x x * m . . . . . . . . . x * * Then the routine performs gaussian elimination to eliminate elements * u[k2,k1], u[k2,k1+1], ..., u[k2,k2-1] using diagonal elements * u[k1,k1], u[k1+1,k1+1], ..., u[k2-1,k2-1] as pivots in the same way * as described in comments to the routine luf_factorize (see the module * GLPLUF). Note that actually all operations are performed on matrix V, * not on matrix U. During the elimination process the routine permutes * neither rows nor columns, so only k2-th row of matrix U is changed. * * To keep the main equality B = F*H*V, each time when the routine * applies elementary gaussian transformation to the transformed row of * matrix V (which corresponds to k2-th row of matrix U), it also adds * a new element (gaussian multiplier) to the current row-like factor * of matrix H, which corresponds to the transformed row of matrix V. */ int fhv_update_it(FHV *fhv, int j, int len, const int ind[], const double val[]) { int m = fhv->m; LUF *luf = fhv->luf; int *vr_ptr = luf->vr_ptr; int *vr_len = luf->vr_len; int *vr_cap = luf->vr_cap; double *vr_piv = luf->vr_piv; int *vc_ptr = luf->vc_ptr; int *vc_len = luf->vc_len; int *vc_cap = luf->vc_cap; int *pp_row = luf->pp_row; int *pp_col = luf->pp_col; int *qq_row = luf->qq_row; int *qq_col = luf->qq_col; int *sv_ind = luf->sv_ind; double *sv_val = luf->sv_val; double *work = luf->work; double eps_tol = luf->eps_tol; int *hh_ind = fhv->hh_ind; int *hh_ptr = fhv->hh_ptr; int *hh_len = fhv->hh_len; int *p0_row = fhv->p0_row; int *p0_col = fhv->p0_col; int *cc_ind = fhv->cc_ind; double *cc_val = fhv->cc_val; double upd_tol = fhv->upd_tol; int i, i_beg, i_end, i_ptr, j_beg, j_end, j_ptr, k, k1, k2, p, q, p_beg, p_end, p_ptr, ptr, ret; double f, temp; if (!fhv->valid) xfault("fhv_update_it: the factorization is not valid\n"); if (!(1 <= j && j <= m)) xfault("fhv_update_it: j = %d; column number out of range\n", j); /* check if the new factor of matrix H can be created */ if (fhv->hh_nfs == fhv->hh_max) { /* maximal number of updates has been reached */ fhv->valid = 0; ret = FHV_ELIMIT; goto done; } /* convert new j-th column of B to dense format */ for (i = 1; i <= m; i++) cc_val[i] = 0.0; for (k = 1; k <= len; k++) { i = ind[k]; if (!(1 <= i && i <= m)) xfault("fhv_update_it: ind[%d] = %d; row number out of rang" "e\n", k, i); if (cc_val[i] != 0.0) xfault("fhv_update_it: ind[%d] = %d; duplicate row index no" "t allowed\n", k, i); if (val[k] == 0.0) xfault("fhv_update_it: val[%d] = %g; zero element not allow" "ed\n", k, val[k]); cc_val[i] = val[k]; } /* new j-th column of V := inv(F * H) * (new B[j]) */ fhv->luf->pp_row = p0_row; fhv->luf->pp_col = p0_col; luf_f_solve(fhv->luf, 0, cc_val); fhv->luf->pp_row = pp_row; fhv->luf->pp_col = pp_col; fhv_h_solve(fhv, 0, cc_val); /* convert new j-th column of V to sparse format */ len = 0; for (i = 1; i <= m; i++) { temp = cc_val[i]; if (temp == 0.0 || fabs(temp) < eps_tol) continue; len++, cc_ind[len] = i, cc_val[len] = temp; } /* clear old content of j-th column of matrix V */ j_beg = vc_ptr[j]; j_end = j_beg + vc_len[j] - 1; for (j_ptr = j_beg; j_ptr <= j_end; j_ptr++) { /* get row index of v[i,j] */ i = sv_ind[j_ptr]; /* find v[i,j] in the i-th row */ i_beg = vr_ptr[i]; i_end = i_beg + vr_len[i] - 1; for (i_ptr = i_beg; sv_ind[i_ptr] != j; i_ptr++) /* nop */; xassert(i_ptr <= i_end); /* remove v[i,j] from the i-th row */ sv_ind[i_ptr] = sv_ind[i_end]; sv_val[i_ptr] = sv_val[i_end]; vr_len[i]--; } /* now j-th column of matrix V is empty */ luf->nnz_v -= vc_len[j]; vc_len[j] = 0; /* add new elements of j-th column of matrix V to corresponding row lists; determine indices k1 and k2 */ k1 = qq_row[j], k2 = 0; for (ptr = 1; ptr <= len; ptr++) { /* get row index of v[i,j] */ i = cc_ind[ptr]; /* at least one unused location is needed in i-th row */ if (vr_len[i] + 1 > vr_cap[i]) { if (luf_enlarge_row(luf, i, vr_len[i] + 10)) { /* overflow of the sparse vector area */ fhv->valid = 0; luf->new_sva = luf->sv_size + luf->sv_size; xassert(luf->new_sva > luf->sv_size); ret = FHV_EROOM; goto done; } } /* add v[i,j] to i-th row */ i_ptr = vr_ptr[i] + vr_len[i]; sv_ind[i_ptr] = j; sv_val[i_ptr] = cc_val[ptr]; vr_len[i]++; /* adjust index k2 */ if (k2 < pp_col[i]) k2 = pp_col[i]; } /* capacity of j-th column (which is currently empty) should be not less than len locations */ if (vc_cap[j] < len) { if (luf_enlarge_col(luf, j, len)) { /* overflow of the sparse vector area */ fhv->valid = 0; luf->new_sva = luf->sv_size + luf->sv_size; xassert(luf->new_sva > luf->sv_size); ret = FHV_EROOM; goto done; } } /* add new elements of matrix V to j-th column list */ j_ptr = vc_ptr[j]; memmove(&sv_ind[j_ptr], &cc_ind[1], len * sizeof(int)); memmove(&sv_val[j_ptr], &cc_val[1], len * sizeof(double)); vc_len[j] = len; luf->nnz_v += len; /* if k1 > k2, diagonal element u[k2,k2] of matrix U is zero and therefore the adjacent basis matrix is structurally singular */ if (k1 > k2) { fhv->valid = 0; ret = FHV_ESING; goto done; } /* perform implicit symmetric permutations of rows and columns of matrix U */ i = pp_row[k1], j = qq_col[k1]; for (k = k1; k < k2; k++) { pp_row[k] = pp_row[k+1], pp_col[pp_row[k]] = k; qq_col[k] = qq_col[k+1], qq_row[qq_col[k]] = k; } pp_row[k2] = i, pp_col[i] = k2; qq_col[k2] = j, qq_row[j] = k2; /* now i-th row of the matrix V is k2-th row of matrix U; since no pivoting is used, only this row will be transformed */ /* copy elements of i-th row of matrix V to the working array and remove these elements from matrix V */ for (j = 1; j <= m; j++) work[j] = 0.0; i_beg = vr_ptr[i]; i_end = i_beg + vr_len[i] - 1; for (i_ptr = i_beg; i_ptr <= i_end; i_ptr++) { /* get column index of v[i,j] */ j = sv_ind[i_ptr]; /* store v[i,j] to the working array */ work[j] = sv_val[i_ptr]; /* find v[i,j] in the j-th column */ j_beg = vc_ptr[j]; j_end = j_beg + vc_len[j] - 1; for (j_ptr = j_beg; sv_ind[j_ptr] != i; j_ptr++) /* nop */; xassert(j_ptr <= j_end); /* remove v[i,j] from the j-th column */ sv_ind[j_ptr] = sv_ind[j_end]; sv_val[j_ptr] = sv_val[j_end]; vc_len[j]--; } /* now i-th row of matrix V is empty */ luf->nnz_v -= vr_len[i]; vr_len[i] = 0; /* create the next row-like factor of the matrix H; this factor corresponds to i-th (transformed) row */ fhv->hh_nfs++; hh_ind[fhv->hh_nfs] = i; /* hh_ptr[] will be set later */ hh_len[fhv->hh_nfs] = 0; /* up to (k2 - k1) free locations are needed to add new elements to the non-trivial row of the row-like factor */ if (luf->sv_end - luf->sv_beg < k2 - k1) { luf_defrag_sva(luf); if (luf->sv_end - luf->sv_beg < k2 - k1) { /* overflow of the sparse vector area */ fhv->valid = luf->valid = 0; luf->new_sva = luf->sv_size + luf->sv_size; xassert(luf->new_sva > luf->sv_size); ret = FHV_EROOM; goto done; } } /* eliminate subdiagonal elements of matrix U */ for (k = k1; k < k2; k++) { /* v[p,q] = u[k,k] */ p = pp_row[k], q = qq_col[k]; /* this is the crucial point, where even tiny non-zeros should not be dropped */ if (work[q] == 0.0) continue; /* compute gaussian multiplier f = v[i,q] / v[p,q] */ f = work[q] / vr_piv[p]; /* perform gaussian transformation: (i-th row) := (i-th row) - f * (p-th row) in order to eliminate v[i,q] = u[k2,k] */ p_beg = vr_ptr[p]; p_end = p_beg + vr_len[p] - 1; for (p_ptr = p_beg; p_ptr <= p_end; p_ptr++) work[sv_ind[p_ptr]] -= f * sv_val[p_ptr]; /* store new element (gaussian multiplier that corresponds to p-th row) in the current row-like factor */ luf->sv_end--; sv_ind[luf->sv_end] = p; sv_val[luf->sv_end] = f; hh_len[fhv->hh_nfs]++; } /* set pointer to the current row-like factor of the matrix H (if no elements were added to this factor, it is unity matrix and therefore can be discarded) */ if (hh_len[fhv->hh_nfs] == 0) fhv->hh_nfs--; else { hh_ptr[fhv->hh_nfs] = luf->sv_end; fhv->nnz_h += hh_len[fhv->hh_nfs]; } /* store new pivot which corresponds to u[k2,k2] */ vr_piv[i] = work[qq_col[k2]]; /* new elements of i-th row of matrix V (which are non-diagonal elements u[k2,k2+1], ..., u[k2,m] of matrix U = P*V*Q) now are contained in the working array; add them to matrix V */ len = 0; for (k = k2+1; k <= m; k++) { /* get column index and value of v[i,j] = u[k2,k] */ j = qq_col[k]; temp = work[j]; /* if v[i,j] is close to zero, skip it */ if (fabs(temp) < eps_tol) continue; /* at least one unused location is needed in j-th column */ if (vc_len[j] + 1 > vc_cap[j]) { if (luf_enlarge_col(luf, j, vc_len[j] + 10)) { /* overflow of the sparse vector area */ fhv->valid = 0; luf->new_sva = luf->sv_size + luf->sv_size; xassert(luf->new_sva > luf->sv_size); ret = FHV_EROOM; goto done; } } /* add v[i,j] to j-th column */ j_ptr = vc_ptr[j] + vc_len[j]; sv_ind[j_ptr] = i; sv_val[j_ptr] = temp; vc_len[j]++; /* also store v[i,j] to the auxiliary array */ len++, cc_ind[len] = j, cc_val[len] = temp; } /* capacity of i-th row (which is currently empty) should be not less than len locations */ if (vr_cap[i] < len) { if (luf_enlarge_row(luf, i, len)) { /* overflow of the sparse vector area */ fhv->valid = 0; luf->new_sva = luf->sv_size + luf->sv_size; xassert(luf->new_sva > luf->sv_size); ret = FHV_EROOM; goto done; } } /* add new elements to i-th row list */ i_ptr = vr_ptr[i]; memmove(&sv_ind[i_ptr], &cc_ind[1], len * sizeof(int)); memmove(&sv_val[i_ptr], &cc_val[1], len * sizeof(double)); vr_len[i] = len; luf->nnz_v += len; /* updating is finished; check that diagonal element u[k2,k2] is not very small in absolute value among other elements in k2-th row and k2-th column of matrix U = P*V*Q */ /* temp = max(|u[k2,*]|, |u[*,k2]|) */ temp = 0.0; /* walk through k2-th row of U which is i-th row of V */ i = pp_row[k2]; i_beg = vr_ptr[i]; i_end = i_beg + vr_len[i] - 1; for (i_ptr = i_beg; i_ptr <= i_end; i_ptr++) if (temp < fabs(sv_val[i_ptr])) temp = fabs(sv_val[i_ptr]); /* walk through k2-th column of U which is j-th column of V */ j = qq_col[k2]; j_beg = vc_ptr[j]; j_end = j_beg + vc_len[j] - 1; for (j_ptr = j_beg; j_ptr <= j_end; j_ptr++) if (temp < fabs(sv_val[j_ptr])) temp = fabs(sv_val[j_ptr]); /* check that u[k2,k2] is not very small */ if (fabs(vr_piv[i]) < upd_tol * temp) { /* the factorization seems to be inaccurate and therefore must be recomputed */ fhv->valid = 0; ret = FHV_ECHECK; goto done; } /* the factorization has been successfully updated */ ret = 0; done: /* return to the calling program */ return ret; } /*********************************************************************** * NAME * * fhv_delete_it - delete LP basis factorization * * SYNOPSIS * * #include "glpfhv.h" * void fhv_delete_it(FHV *fhv); * * DESCRIPTION * * The routine fhv_delete_it deletes LP basis factorization specified * by the parameter fhv and frees all memory allocated to this program * object. */ void fhv_delete_it(FHV *fhv) { luf_delete_it(fhv->luf); if (fhv->hh_ind != NULL) xfree(fhv->hh_ind); if (fhv->hh_ptr != NULL) xfree(fhv->hh_ptr); if (fhv->hh_len != NULL) xfree(fhv->hh_len); if (fhv->p0_row != NULL) xfree(fhv->p0_row); if (fhv->p0_col != NULL) xfree(fhv->p0_col); if (fhv->cc_ind != NULL) xfree(fhv->cc_ind); if (fhv->cc_val != NULL) xfree(fhv->cc_val); xfree(fhv); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpenv05.c0000644000076500000240000001624613524616144025214 0ustar tamasstaff00000000000000/* glpenv05.c (memory allocation) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wsign-conversion" #endif #include "glpapi.h" /* some processors need data to be properly aligned; the macro align_datasize enlarges the specified size of a data item to provide a proper alignment of immediately following data */ #define align_datasize(size) ((((size) + 15) / 16) * 16) /* 16 bytes is sufficient in both 32- and 64-bit environments (8 bytes is not sufficient in 64-bit environment due to jmp_buf) */ /*********************************************************************** * NAME * * glp_malloc - allocate memory block * * SYNOPSIS * * void *glp_malloc(int size); * * DESCRIPTION * * The routine glp_malloc allocates a memory block of size bytes long. * * Note that being allocated the memory block contains arbitrary data * (not binary zeros). * * RETURNS * * The routine glp_malloc returns a pointer to the allocated block. * To free this block the routine glp_free (not free!) must be used. */ void *glp_malloc(int size) { ENV *env = get_env_ptr(); MEM *desc; int size_of_desc = align_datasize(sizeof(MEM)); if (size < 1 || size > INT_MAX - size_of_desc) xerror("glp_malloc: size = %d; invalid parameter\n", size); size += size_of_desc; if (xlcmp(xlset(size), xlsub(env->mem_limit, env->mem_total)) > 0) xerror("glp_malloc: memory limit exceeded\n"); if (env->mem_count == INT_MAX) xerror("glp_malloc: too many memory blocks allocated\n"); desc = malloc(size); if (desc == NULL) xerror("glp_malloc: no memory available\n"); memset(desc, '?', size); desc->flag = MEM_MAGIC; desc->size = size; desc->prev = NULL; desc->next = env->mem_ptr; if (desc->next != NULL) desc->next->prev = desc; env->mem_ptr = desc; env->mem_count++; if (env->mem_cpeak < env->mem_count) env->mem_cpeak = env->mem_count; env->mem_total = xladd(env->mem_total, xlset(size)); if (xlcmp(env->mem_tpeak, env->mem_total) < 0) env->mem_tpeak = env->mem_total; return (void *)((char *)desc + size_of_desc); } /*********************************************************************** * NAME * * glp_calloc - allocate memory block * * SYNOPSIS * * void *glp_calloc(int n, int size); * * DESCRIPTION * * The routine glp_calloc allocates a memory block of (n*size) bytes * long. * * Note that being allocated the memory block contains arbitrary data * (not binary zeros). * * RETURNS * * The routine glp_calloc returns a pointer to the allocated block. * To free this block the routine glp_free (not free!) must be used. */ void *glp_calloc(int n, int size) { if (n < 1) xerror("glp_calloc: n = %d; invalid parameter\n", n); if (size < 1) xerror("glp_calloc: size = %d; invalid parameter\n", size); if (n > INT_MAX / size) xerror("glp_calloc: n = %d; size = %d; array too big\n", n, size); return xmalloc(n * size); } /*********************************************************************** * NAME * * glp_free - free memory block * * SYNOPSIS * * void glp_free(void *ptr); * * DESCRIPTION * * The routine glp_free frees a memory block pointed to by ptr, which * was previuosly allocated by the routine glp_malloc or glp_calloc. */ void glp_free(void *ptr) { ENV *env = get_env_ptr(); MEM *desc; int size_of_desc = align_datasize(sizeof(MEM)); if (ptr == NULL) xerror("glp_free: ptr = %p; null pointer\n", ptr); desc = (void *)((char *)ptr - size_of_desc); if (desc->flag != MEM_MAGIC) xerror("glp_free: ptr = %p; invalid pointer\n", ptr); if (env->mem_count == 0 || xlcmp(env->mem_total, xlset(desc->size)) < 0) xerror("glp_free: memory allocation error\n"); if (desc->prev == NULL) env->mem_ptr = desc->next; else desc->prev->next = desc->next; if (desc->next == NULL) ; else desc->next->prev = desc->prev; env->mem_count--; env->mem_total = xlsub(env->mem_total, xlset(desc->size)); memset(desc, '?', size_of_desc); free(desc); return; } /*********************************************************************** * NAME * * glp_mem_limit - set memory usage limit * * SYNOPSIS * * void glp_mem_limit(int limit); * * DESCRIPTION * * The routine glp_mem_limit limits the amount of memory available for * dynamic allocation (in GLPK routines) to limit megabytes. */ void glp_mem_limit(int limit) { ENV *env = get_env_ptr(); if (limit < 0) xerror("glp_mem_limit: limit = %d; invalid parameter\n", limit); env->mem_limit = xlmul(xlset(limit), xlset(1 << 20)); return; } /*********************************************************************** * NAME * * glp_mem_usage - get memory usage information * * SYNOPSIS * * void glp_mem_usage(int *count, int *cpeak, glp_long *total, * glp_long *tpeak); * * DESCRIPTION * * The routine glp_mem_usage reports some information about utilization * of the memory by GLPK routines. Information is stored to locations * specified by corresponding parameters (see below). Any parameter can * be specified as NULL, in which case corresponding information is not * stored. * * *count is the number of the memory blocks currently allocated by the * routines xmalloc and xcalloc (one call to xmalloc or xcalloc results * in allocating one memory block). * * *cpeak is the peak value of *count reached since the initialization * of the GLPK library environment. * * *total is the total amount, in bytes, of the memory blocks currently * allocated by the routines xmalloc and xcalloc. * * *tpeak is the peak value of *total reached since the initialization * of the GLPK library envirionment. */ void glp_mem_usage(int *count, int *cpeak, glp_long *total, glp_long *tpeak) { ENV *env = get_env_ptr(); if (count != NULL) *count = env->mem_count; if (cpeak != NULL) *cpeak = env->mem_cpeak; if (total != NULL) *total = env->mem_total; if (tpeak != NULL) *tpeak = env->mem_tpeak; return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpsql.h0000644000076500000240000000414313524616144025054 0ustar tamasstaff00000000000000/* glpsql.h */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Author: Heinrich Schuchardt . * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPSQL_H #define GLPSQL_H #define db_iodbc_open _glp_db_iodbc_open void *db_iodbc_open(TABDCA *dca, int mode); /* open iODBC database connection */ #define db_iodbc_read _glp_db_iodbc_read int db_iodbc_read(TABDCA *dca, void *link); /* read data from iODBC */ #define db_iodbc_write _glp_db_iodbc_write int db_iodbc_write(TABDCA *dca, void *link); /* write data to iODBC */ #define db_iodbc_close _glp_db_iodbc_close int db_iodbc_close(TABDCA *dca, void *link); /* close iODBC database connection */ #define db_mysql_open _glp_db_mysql_open void *db_mysql_open(TABDCA *dca, int mode); /* open MySQL database connection */ #define db_mysql_read _glp_db_mysql_read int db_mysql_read(TABDCA *dca, void *link); /* read data from MySQL */ #define db_mysql_write _glp_db_mysql_write int db_mysql_write(TABDCA *dca, void *link); /* write data to MySQL */ #define db_mysql_close _glp_db_mysql_close int db_mysql_close(TABDCA *dca, void *link); /* close MySQL database connection */ #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpios10.c0000644000076500000240000002766713524616144025223 0ustar tamasstaff00000000000000/* glpios10.c (feasibility pump heuristic) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wlogical-op-parentheses" #pragma clang diagnostic ignored "-Wsign-conversion" #endif #include "glpios.h" #include "glprng.h" /*********************************************************************** * NAME * * ios_feas_pump - feasibility pump heuristic * * SYNOPSIS * * #include "glpios.h" * void ios_feas_pump(glp_tree *T); * * DESCRIPTION * * The routine ios_feas_pump is a simple implementation of the Feasi- * bility Pump heuristic. * * REFERENCES * * M.Fischetti, F.Glover, and A.Lodi. "The feasibility pump." Math. * Program., Ser. A 104, pp. 91-104 (2005). */ struct VAR { /* binary variable */ int j; /* ordinal number */ int x; /* value in the rounded solution (0 or 1) */ double d; /* sorting key */ }; static int fcmp(const void *x, const void *y) { /* comparison routine */ const struct VAR *vx = x, *vy = y; if (vx->d > vy->d) return -1; else if (vx->d < vy->d) return +1; else return 0; } void ios_feas_pump(glp_tree *T) { glp_prob *P = T->mip; int n = P->n; glp_prob *lp = NULL; struct VAR *var = NULL; RNG *rand = NULL; GLPCOL *col; glp_smcp parm; int j, k, new_x, nfail, npass, nv, ret, stalling; double dist, tol; xassert(glp_get_status(P) == GLP_OPT); /* this heuristic is applied only once on the root level */ if (!(T->curr->level == 0 && T->curr->solved == 1)) goto done; /* determine number of binary variables */ nv = 0; for (j = 1; j <= n; j++) { col = P->col[j]; /* if x[j] is continuous, skip it */ if (col->kind == GLP_CV) continue; /* if x[j] is fixed, skip it */ if (col->type == GLP_FX) continue; /* x[j] is non-fixed integer */ xassert(col->kind == GLP_IV); if (col->type == GLP_DB && col->lb == 0.0 && col->ub == 1.0) { /* x[j] is binary */ nv++; } else { /* x[j] is general integer */ if (T->parm->msg_lev >= GLP_MSG_ALL) xprintf("FPUMP heuristic cannot be applied due to genera" "l integer variables\n"); goto done; } } /* there must be at least one binary variable */ if (nv == 0) goto done; if (T->parm->msg_lev >= GLP_MSG_ALL) xprintf("Applying FPUMP heuristic...\n"); /* build the list of binary variables */ var = xcalloc(1+nv, sizeof(struct VAR)); k = 0; for (j = 1; j <= n; j++) { col = P->col[j]; if (col->kind == GLP_IV && col->type == GLP_DB) var[++k].j = j; } xassert(k == nv); /* create working problem object */ lp = glp_create_prob(); more: /* copy the original problem object to keep it intact */ glp_copy_prob(lp, P, GLP_OFF); /* we are interested to find an integer feasible solution, which is better than the best known one */ if (P->mip_stat == GLP_FEAS) { int *ind; double *val, bnd; /* add a row and make it identical to the objective row */ glp_add_rows(lp, 1); ind = xcalloc(1+n, sizeof(int)); val = xcalloc(1+n, sizeof(double)); for (j = 1; j <= n; j++) { ind[j] = j; val[j] = P->col[j]->coef; } glp_set_mat_row(lp, lp->m, n, ind, val); xfree(ind); xfree(val); /* introduce upper (minimization) or lower (maximization) bound to the original objective function; note that this additional constraint is not violated at the optimal point to LP relaxation */ #if 0 /* modified by xypron */ if (P->dir == GLP_MIN) { bnd = P->mip_obj - 0.10 * (1.0 + fabs(P->mip_obj)); if (bnd < P->obj_val) bnd = P->obj_val; glp_set_row_bnds(lp, lp->m, GLP_UP, 0.0, bnd - P->c0); } else if (P->dir == GLP_MAX) { bnd = P->mip_obj + 0.10 * (1.0 + fabs(P->mip_obj)); if (bnd > P->obj_val) bnd = P->obj_val; glp_set_row_bnds(lp, lp->m, GLP_LO, bnd - P->c0, 0.0); } else xassert(P != P); #else bnd = 0.1 * P->obj_val + 0.9 * P->mip_obj; /* xprintf("bnd = %f\n", bnd); */ if (P->dir == GLP_MIN) glp_set_row_bnds(lp, lp->m, GLP_UP, 0.0, bnd - P->c0); else if (P->dir == GLP_MAX) glp_set_row_bnds(lp, lp->m, GLP_LO, bnd - P->c0, 0.0); else xassert(P != P); #endif } /* reset pass count */ npass = 0; /* invalidate the rounded point */ for (k = 1; k <= nv; k++) var[k].x = -1; pass: /* next pass starts here */ npass++; if (T->parm->msg_lev >= GLP_MSG_ALL) xprintf("Pass %d\n", npass); /* initialize minimal distance between the basic point and the rounded one obtained during this pass */ dist = DBL_MAX; /* reset failure count (the number of succeeded iterations failed to improve the distance) */ nfail = 0; /* if it is not the first pass, perturb the last rounded point rather than construct it from the basic solution */ if (npass > 1) { double rho, temp; if (rand == NULL) rand = rng_create_rand(); for (k = 1; k <= nv; k++) { j = var[k].j; col = lp->col[j]; rho = rng_uniform(rand, -0.3, 0.7); if (rho < 0.0) rho = 0.0; temp = fabs((double)var[k].x - col->prim); if (temp + rho > 0.5) var[k].x = 1 - var[k].x; } goto skip; } loop: /* innermost loop begins here */ /* round basic solution (which is assumed primal feasible) */ stalling = 1; for (k = 1; k <= nv; k++) { col = lp->col[var[k].j]; if (col->prim < 0.5) { /* rounded value is 0 */ new_x = 0; } else { /* rounded value is 1 */ new_x = 1; } if (var[k].x != new_x) { stalling = 0; var[k].x = new_x; } } /* if the rounded point has not changed (stalling), choose and flip some its entries heuristically */ if (stalling) { /* compute d[j] = |x[j] - round(x[j])| */ for (k = 1; k <= nv; k++) { col = lp->col[var[k].j]; var[k].d = fabs(col->prim - (double)var[k].x); } /* sort the list of binary variables by descending d[j] */ qsort(&var[1], nv, sizeof(struct VAR), fcmp); /* choose and flip some rounded components */ for (k = 1; k <= nv; k++) { if (k >= 5 && var[k].d < 0.35 || k >= 10) break; var[k].x = 1 - var[k].x; } } skip: /* check if the time limit has been exhausted */ if (T->parm->tm_lim < INT_MAX && (double)(T->parm->tm_lim - 1) <= 1000.0 * xdifftime(xtime(), T->tm_beg)) goto done; /* build the objective, which is the distance between the current (basic) point and the rounded one */ lp->dir = GLP_MIN; lp->c0 = 0.0; for (j = 1; j <= n; j++) lp->col[j]->coef = 0.0; for (k = 1; k <= nv; k++) { j = var[k].j; if (var[k].x == 0) lp->col[j]->coef = +1.0; else { lp->col[j]->coef = -1.0; lp->c0 += 1.0; } } /* minimize the distance with the simplex method */ glp_init_smcp(&parm); if (T->parm->msg_lev <= GLP_MSG_ERR) parm.msg_lev = T->parm->msg_lev; else if (T->parm->msg_lev <= GLP_MSG_ALL) { parm.msg_lev = GLP_MSG_ON; parm.out_dly = 10000; } ret = glp_simplex(lp, &parm); if (ret != 0) { if (T->parm->msg_lev >= GLP_MSG_ERR) xprintf("Warning: glp_simplex returned %d\n", ret); goto done; } ret = glp_get_status(lp); if (ret != GLP_OPT) { if (T->parm->msg_lev >= GLP_MSG_ERR) xprintf("Warning: glp_get_status returned %d\n", ret); goto done; } if (T->parm->msg_lev >= GLP_MSG_DBG) xprintf("delta = %g\n", lp->obj_val); /* check if the basic solution is integer feasible; note that it may be so even if the minimial distance is positive */ tol = 0.3 * T->parm->tol_int; for (k = 1; k <= nv; k++) { col = lp->col[var[k].j]; if (tol < col->prim && col->prim < 1.0 - tol) break; } if (k > nv) { /* okay; the basic solution seems to be integer feasible */ double *x = xcalloc(1+n, sizeof(double)); for (j = 1; j <= n; j++) { x[j] = lp->col[j]->prim; if (P->col[j]->kind == GLP_IV) x[j] = floor(x[j] + 0.5); } #if 1 /* modified by xypron */ /* reset direction and right-hand side of objective */ lp->c0 = P->c0; lp->dir = P->dir; /* fix integer variables */ for (k = 1; k <= nv; k++) { lp->col[var[k].j]->lb = x[var[k].j]; lp->col[var[k].j]->ub = x[var[k].j]; lp->col[var[k].j]->type = GLP_FX; } /* copy original objective function */ for (j = 1; j <= n; j++) lp->col[j]->coef = P->col[j]->coef; /* solve original LP and copy result */ ret = glp_simplex(lp, &parm); if (ret != 0) { if (T->parm->msg_lev >= GLP_MSG_ERR) xprintf("Warning: glp_simplex returned %d\n", ret); goto done; } ret = glp_get_status(lp); if (ret != GLP_OPT) { if (T->parm->msg_lev >= GLP_MSG_ERR) xprintf("Warning: glp_get_status returned %d\n", ret); goto done; } for (j = 1; j <= n; j++) if (P->col[j]->kind != GLP_IV) x[j] = lp->col[j]->prim; #endif ret = glp_ios_heur_sol(T, x); xfree(x); if (ret == 0) { /* the integer solution is accepted */ if (ios_is_hopeful(T, T->curr->bound)) { /* it is reasonable to apply the heuristic once again */ goto more; } else { /* the best known integer feasible solution just found is close to optimal solution to LP relaxation */ goto done; } } } /* the basic solution is fractional */ if (dist == DBL_MAX || lp->obj_val <= dist - 1e-6 * (1.0 + dist)) { /* the distance is reducing */ nfail = 0, dist = lp->obj_val; } else { /* improving the distance failed */ nfail++; } if (nfail < 3) goto loop; if (npass < 5) goto pass; done: /* delete working objects */ if (lp != NULL) glp_delete_prob(lp); if (var != NULL) xfree(var); if (rand != NULL) rng_delete_rand(rand); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpnpp04.c0000644000076500000240000014275313524616144025223 0ustar tamasstaff00000000000000/* glpnpp04.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wlogical-op-parentheses" #pragma clang diagnostic ignored "-Wsometimes-uninitialized" #endif #include "glpnpp.h" /*********************************************************************** * NAME * * npp_binarize_prob - binarize MIP problem * * SYNOPSIS * * #include "glpnpp.h" * int npp_binarize_prob(NPP *npp); * * DESCRIPTION * * The routine npp_binarize_prob replaces in the original MIP problem * every integer variable: * * l[q] <= x[q] <= u[q], (1) * * where l[q] < u[q], by an equivalent sum of binary variables. * * RETURNS * * The routine returns the number of integer variables for which the * transformation failed, because u[q] - l[q] > d_max. * * PROBLEM TRANSFORMATION * * If variable x[q] has non-zero lower bound, it is first processed * with the routine npp_lbnd_col. Thus, we can assume that: * * 0 <= x[q] <= u[q]. (2) * * If u[q] = 1, variable x[q] is already binary, so further processing * is not needed. Let, therefore, that 2 <= u[q] <= d_max, and n be a * smallest integer such that u[q] <= 2^n - 1 (n >= 2, since u[q] >= 2). * Then variable x[q] can be replaced by the following sum: * * n-1 * x[q] = sum 2^k x[k], (3) * k=0 * * where x[k] are binary columns (variables). If u[q] < 2^n - 1, the * following additional inequality constraint must be also included in * the transformed problem: * * n-1 * sum 2^k x[k] <= u[q]. (4) * k=0 * * Note: Assuming that in the transformed problem x[q] becomes binary * variable x[0], this transformation causes new n-1 binary variables * to appear. * * Substituting x[q] from (3) to the objective row gives: * * z = sum c[j] x[j] + c[0] = * j * * = sum c[j] x[j] + c[q] x[q] + c[0] = * j!=q * n-1 * = sum c[j] x[j] + c[q] sum 2^k x[k] + c[0] = * j!=q k=0 * n-1 * = sum c[j] x[j] + sum c[k] x[k] + c[0], * j!=q k=0 * * where: * * c[k] = 2^k c[q], k = 0, ..., n-1. (5) * * And substituting x[q] from (3) to i-th constraint row i gives: * * L[i] <= sum a[i,j] x[j] <= U[i] ==> * j * * L[i] <= sum a[i,j] x[j] + a[i,q] x[q] <= U[i] ==> * j!=q * n-1 * L[i] <= sum a[i,j] x[j] + a[i,q] sum 2^k x[k] <= U[i] ==> * j!=q k=0 * n-1 * L[i] <= sum a[i,j] x[j] + sum a[i,k] x[k] <= U[i], * j!=q k=0 * * where: * * a[i,k] = 2^k a[i,q], k = 0, ..., n-1. (6) * * RECOVERING SOLUTION * * Value of variable x[q] is computed with formula (3). */ struct binarize { int q; /* column reference number for x[q] = x[0] */ int j; /* column reference number for x[1]; x[2] has reference number j+1, x[3] - j+2, etc. */ int n; /* total number of binary variables, n >= 2 */ }; static int rcv_binarize_prob(NPP *npp, void *info); int npp_binarize_prob(NPP *npp) { /* binarize MIP problem */ struct binarize *info; NPPROW *row; NPPCOL *col, *bin; NPPAIJ *aij; int u, n, k, temp, nfails, nvars, nbins, nrows; /* new variables will be added to the end of the column list, so we go from the end to beginning of the column list */ nfails = nvars = nbins = nrows = 0; for (col = npp->c_tail; col != NULL; col = col->prev) { /* skip continuous variable */ if (!col->is_int) continue; /* skip fixed variable */ if (col->lb == col->ub) continue; /* skip binary variable */ if (col->lb == 0.0 && col->ub == 1.0) continue; /* check if the transformation is applicable */ if (col->lb < -1e6 || col->ub > +1e6 || col->ub - col->lb > 4095.0) { /* unfortunately, not */ nfails++; continue; } /* process integer non-binary variable x[q] */ nvars++; /* make x[q] non-negative, if its lower bound is non-zero */ if (col->lb != 0.0) npp_lbnd_col(npp, col); /* now 0 <= x[q] <= u[q] */ xassert(col->lb == 0.0); u = (int)col->ub; xassert(col->ub == (double)u); /* if x[q] is binary, further processing is not needed */ if (u == 1) continue; /* determine smallest n such that u <= 2^n - 1 (thus, n is the number of binary variables needed) */ n = 2, temp = 4; while (u >= temp) n++, temp += temp; nbins += n; /* create transformation stack entry */ info = npp_push_tse(npp, rcv_binarize_prob, sizeof(struct binarize)); info->q = col->j; info->j = 0; /* will be set below */ info->n = n; /* if u < 2^n - 1, we need one additional row for (4) */ if (u < temp - 1) { row = npp_add_row(npp), nrows++; row->lb = -DBL_MAX, row->ub = u; } else row = NULL; /* in the transformed problem variable x[q] becomes binary variable x[0], so its objective and constraint coefficients are not changed */ col->ub = 1.0; /* include x[0] into constraint (4) */ if (row != NULL) npp_add_aij(npp, row, col, 1.0); /* add other binary variables x[1], ..., x[n-1] */ for (k = 1, temp = 2; k < n; k++, temp += temp) { /* add new binary variable x[k] */ bin = npp_add_col(npp); bin->is_int = 1; bin->lb = 0.0, bin->ub = 1.0; bin->coef = (double)temp * col->coef; /* store column reference number for x[1] */ if (info->j == 0) info->j = bin->j; else xassert(info->j + (k-1) == bin->j); /* duplicate constraint coefficients for x[k]; this also automatically includes x[k] into constraint (4) */ for (aij = col->ptr; aij != NULL; aij = aij->c_next) npp_add_aij(npp, aij->row, bin, (double)temp * aij->val); } } if (nvars > 0) xprintf("%d integer variable(s) were replaced by %d binary one" "s\n", nvars, nbins); if (nrows > 0) xprintf("%d row(s) were added due to binarization\n", nrows); if (nfails > 0) xprintf("Binarization failed for %d integer variable(s)\n", nfails); return nfails; } static int rcv_binarize_prob(NPP *npp, void *_info) { /* recovery binarized variable */ struct binarize *info = _info; int k, temp; double sum; /* compute value of x[q]; see formula (3) */ sum = npp->c_value[info->q]; for (k = 1, temp = 2; k < info->n; k++, temp += temp) sum += (double)temp * npp->c_value[info->j + (k-1)]; npp->c_value[info->q] = sum; return 0; } /**********************************************************************/ struct elem { /* linear form element a[j] x[j] */ double aj; /* non-zero coefficient value */ NPPCOL *xj; /* pointer to variable (column) */ struct elem *next; /* pointer to another term */ }; static struct elem *copy_form(NPP *npp, NPPROW *row, double s) { /* copy linear form */ NPPAIJ *aij; struct elem *ptr, *e; ptr = NULL; for (aij = row->ptr; aij != NULL; aij = aij->r_next) { e = dmp_get_atom(npp->pool, sizeof(struct elem)); e->aj = s * aij->val; e->xj = aij->col; e->next = ptr; ptr = e; } return ptr; } static void drop_form(NPP *npp, struct elem *ptr) { /* drop linear form */ struct elem *e; while (ptr != NULL) { e = ptr; ptr = e->next; dmp_free_atom(npp->pool, e, sizeof(struct elem)); } return; } /*********************************************************************** * NAME * * npp_is_packing - test if constraint is packing inequality * * SYNOPSIS * * #include "glpnpp.h" * int npp_is_packing(NPP *npp, NPPROW *row); * * RETURNS * * If the specified row (constraint) is packing inequality (see below), * the routine npp_is_packing returns non-zero. Otherwise, it returns * zero. * * PACKING INEQUALITIES * * In canonical format the packing inequality is the following: * * sum x[j] <= 1, (1) * j in J * * where all variables x[j] are binary. This inequality expresses the * condition that in any integer feasible solution at most one variable * from set J can take non-zero (unity) value while other variables * must be equal to zero. W.l.o.g. it is assumed that |J| >= 2, because * if J is empty or |J| = 1, the inequality (1) is redundant. * * In general case the packing inequality may include original variables * x[j] as well as their complements x~[j]: * * sum x[j] + sum x~[j] <= 1, (2) * j in Jp j in Jn * * where Jp and Jn are not intersected. Therefore, using substitution * x~[j] = 1 - x[j] gives the packing inequality in generalized format: * * sum x[j] - sum x[j] <= 1 - |Jn|. (3) * j in Jp j in Jn */ int npp_is_packing(NPP *npp, NPPROW *row) { /* test if constraint is packing inequality */ NPPCOL *col; NPPAIJ *aij; int b; xassert(npp == npp); if (!(row->lb == -DBL_MAX && row->ub != +DBL_MAX)) return 0; b = 1; for (aij = row->ptr; aij != NULL; aij = aij->r_next) { col = aij->col; if (!(col->is_int && col->lb == 0.0 && col->ub == 1.0)) return 0; if (aij->val == +1.0) ; else if (aij->val == -1.0) b--; else return 0; } if (row->ub != (double)b) return 0; return 1; } /*********************************************************************** * NAME * * npp_hidden_packing - identify hidden packing inequality * * SYNOPSIS * * #include "glpnpp.h" * int npp_hidden_packing(NPP *npp, NPPROW *row); * * DESCRIPTION * * The routine npp_hidden_packing processes specified inequality * constraint, which includes only binary variables, and the number of * the variables is not less than two. If the original inequality is * equivalent to a packing inequality, the routine replaces it by this * equivalent inequality. If the original constraint is double-sided * inequality, it is replaced by a pair of single-sided inequalities, * if necessary. * * RETURNS * * If the original inequality constraint was replaced by equivalent * packing inequality, the routine npp_hidden_packing returns non-zero. * Otherwise, it returns zero. * * PROBLEM TRANSFORMATION * * Consider an inequality constraint: * * sum a[j] x[j] <= b, (1) * j in J * * where all variables x[j] are binary, and |J| >= 2. (In case of '>=' * inequality it can be transformed to '<=' format by multiplying both * its sides by -1.) * * Let Jp = {j: a[j] > 0}, Jn = {j: a[j] < 0}. Performing substitution * x[j] = 1 - x~[j] for all j in Jn, we have: * * sum a[j] x[j] <= b ==> * j in J * * sum a[j] x[j] + sum a[j] x[j] <= b ==> * j in Jp j in Jn * * sum a[j] x[j] + sum a[j] (1 - x~[j]) <= b ==> * j in Jp j in Jn * * sum a[j] x[j] - sum a[j] x~[j] <= b - sum a[j]. * j in Jp j in Jn j in Jn * * Thus, meaning the transformation above, we can assume that in * inequality (1) all coefficients a[j] are positive. Moreover, we can * assume that a[j] <= b. In fact, let a[j] > b; then the following * three cases are possible: * * 1) b < 0. In this case inequality (1) is infeasible, so the problem * has no feasible solution (see the routine npp_analyze_row); * * 2) b = 0. In this case inequality (1) is a forcing inequality on its * upper bound (see the routine npp_forcing row), from which it * follows that all variables x[j] should be fixed at zero; * * 3) b > 0. In this case inequality (1) defines an implied zero upper * bound for variable x[j] (see the routine npp_implied_bounds), from * which it follows that x[j] should be fixed at zero. * * It is assumed that all three cases listed above have been recognized * by the routine npp_process_prob, which performs basic MIP processing * prior to a call the routine npp_hidden_packing. So, if one of these * cases occurs, we should just skip processing such constraint. * * Thus, let 0 < a[j] <= b. Then it is obvious that constraint (1) is * equivalent to packing inquality only if: * * a[j] + a[k] > b + eps (2) * * for all j, k in J, j != k, where eps is an absolute tolerance for * row (linear form) value. Checking the condition (2) for all j and k, * j != k, requires time O(|J|^2). However, this time can be reduced to * O(|J|), if use minimal a[j] and a[k], in which case it is sufficient * to check the condition (2) only once. * * Once the original inequality (1) is replaced by equivalent packing * inequality, we need to perform back substitution x~[j] = 1 - x[j] for * all j in Jn (see above). * * RECOVERING SOLUTION * * None needed. */ static int hidden_packing(NPP *npp, struct elem *ptr, double *_b) { /* process inequality constraint: sum a[j] x[j] <= b; 0 - specified row is NOT hidden packing inequality; 1 - specified row is packing inequality; 2 - specified row is hidden packing inequality. */ struct elem *e, *ej, *ek; int neg; double b = *_b, eps; xassert(npp == npp); /* a[j] must be non-zero, x[j] must be binary, for all j in J */ for (e = ptr; e != NULL; e = e->next) { xassert(e->aj != 0.0); xassert(e->xj->is_int); xassert(e->xj->lb == 0.0 && e->xj->ub == 1.0); } /* check if the specified inequality constraint already has the form of packing inequality */ neg = 0; /* neg is |Jn| */ for (e = ptr; e != NULL; e = e->next) { if (e->aj == +1.0) ; else if (e->aj == -1.0) neg++; else break; } if (e == NULL) { /* all coefficients a[j] are +1 or -1; check rhs b */ if (b == (double)(1 - neg)) { /* it is packing inequality; no processing is needed */ return 1; } } /* substitute x[j] = 1 - x~[j] for all j in Jn to make all a[j] positive; the result is a~[j] = |a[j]| and new rhs b */ for (e = ptr; e != NULL; e = e->next) if (e->aj < 0) b -= e->aj; /* now a[j] > 0 for all j in J (actually |a[j]| are used) */ /* if a[j] > b, skip processing--this case must not appear */ for (e = ptr; e != NULL; e = e->next) if (fabs(e->aj) > b) return 0; /* now 0 < a[j] <= b for all j in J */ /* find two minimal coefficients a[j] and a[k], j != k */ ej = NULL; for (e = ptr; e != NULL; e = e->next) if (ej == NULL || fabs(ej->aj) > fabs(e->aj)) ej = e; xassert(ej != NULL); ek = NULL; for (e = ptr; e != NULL; e = e->next) if (e != ej) if (ek == NULL || fabs(ek->aj) > fabs(e->aj)) ek = e; xassert(ek != NULL); /* the specified constraint is equivalent to packing inequality iff a[j] + a[k] > b + eps */ eps = 1e-3 + 1e-6 * fabs(b); if (fabs(ej->aj) + fabs(ek->aj) <= b + eps) return 0; /* perform back substitution x~[j] = 1 - x[j] and construct the final equivalent packing inequality in generalized format */ b = 1.0; for (e = ptr; e != NULL; e = e->next) { if (e->aj > 0.0) e->aj = +1.0; else /* e->aj < 0.0 */ e->aj = -1.0, b -= 1.0; } *_b = b; return 2; } int npp_hidden_packing(NPP *npp, NPPROW *row) { /* identify hidden packing inequality */ NPPROW *copy; NPPAIJ *aij; struct elem *ptr, *e; int kase, ret, count = 0; double b; /* the row must be inequality constraint */ xassert(row->lb < row->ub); for (kase = 0; kase <= 1; kase++) { if (kase == 0) { /* process row upper bound */ if (row->ub == +DBL_MAX) continue; ptr = copy_form(npp, row, +1.0); b = + row->ub; } else { /* process row lower bound */ if (row->lb == -DBL_MAX) continue; ptr = copy_form(npp, row, -1.0); b = - row->lb; } /* now the inequality has the form "sum a[j] x[j] <= b" */ ret = hidden_packing(npp, ptr, &b); xassert(0 <= ret && ret <= 2); if (kase == 1 && ret == 1 || ret == 2) { /* the original inequality has been identified as hidden packing inequality */ count++; #ifdef GLP_DEBUG xprintf("Original constraint:\n"); for (aij = row->ptr; aij != NULL; aij = aij->r_next) xprintf(" %+g x%d", aij->val, aij->col->j); if (row->lb != -DBL_MAX) xprintf(", >= %g", row->lb); if (row->ub != +DBL_MAX) xprintf(", <= %g", row->ub); xprintf("\n"); xprintf("Equivalent packing inequality:\n"); for (e = ptr; e != NULL; e = e->next) xprintf(" %sx%d", e->aj > 0.0 ? "+" : "-", e->xj->j); xprintf(", <= %g\n", b); #endif if (row->lb == -DBL_MAX || row->ub == +DBL_MAX) { /* the original row is single-sided inequality; no copy is needed */ copy = NULL; } else { /* the original row is double-sided inequality; we need to create its copy for other bound before replacing it with the equivalent inequality */ copy = npp_add_row(npp); if (kase == 0) { /* the copy is for lower bound */ copy->lb = row->lb, copy->ub = +DBL_MAX; } else { /* the copy is for upper bound */ copy->lb = -DBL_MAX, copy->ub = row->ub; } /* copy original row coefficients */ for (aij = row->ptr; aij != NULL; aij = aij->r_next) npp_add_aij(npp, copy, aij->col, aij->val); } /* replace the original inequality by equivalent one */ npp_erase_row(npp, row); row->lb = -DBL_MAX, row->ub = b; for (e = ptr; e != NULL; e = e->next) npp_add_aij(npp, row, e->xj, e->aj); /* continue processing lower bound for the copy */ if (copy != NULL) row = copy; } drop_form(npp, ptr); } return count; } /*********************************************************************** * NAME * * npp_implied_packing - identify implied packing inequality * * SYNOPSIS * * #include "glpnpp.h" * int npp_implied_packing(NPP *npp, NPPROW *row, int which, * NPPCOL *var[], char set[]); * * DESCRIPTION * * The routine npp_implied_packing processes specified row (constraint) * of general format: * * L <= sum a[j] x[j] <= U. (1) * j * * If which = 0, only lower bound L, which must exist, is considered, * while upper bound U is ignored. Similarly, if which = 1, only upper * bound U, which must exist, is considered, while lower bound L is * ignored. Thus, if the specified row is a double-sided inequality or * equality constraint, this routine should be called twice for both * lower and upper bounds. * * The routine npp_implied_packing attempts to find a non-trivial (i.e. * having not less than two binary variables) packing inequality: * * sum x[j] - sum x[j] <= 1 - |Jn|, (2) * j in Jp j in Jn * * which is relaxation of the constraint (1) in the sense that any * solution satisfying to that constraint also satisfies to the packing * inequality (2). If such relaxation exists, the routine stores * pointers to descriptors of corresponding binary variables and their * flags, resp., to locations var[1], var[2], ..., var[len] and set[1], * set[2], ..., set[len], where set[j] = 0 means that j in Jp and * set[j] = 1 means that j in Jn. * * RETURNS * * The routine npp_implied_packing returns len, which is the total * number of binary variables in the packing inequality found, len >= 2. * However, if the relaxation does not exist, the routine returns zero. * * ALGORITHM * * If which = 0, the constraint coefficients (1) are multiplied by -1 * and b is assigned -L; if which = 1, the constraint coefficients (1) * are not changed and b is assigned +U. In both cases the specified * constraint gets the following format: * * sum a[j] x[j] <= b. (3) * j * * (Note that (3) is a relaxation of (1), because one of bounds L or U * is ignored.) * * Let J be set of binary variables, Kp be set of non-binary (integer * or continuous) variables with a[j] > 0, and Kn be set of non-binary * variables with a[j] < 0. Then the inequality (3) can be written as * follows: * * sum a[j] x[j] <= b - sum a[j] x[j] - sum a[j] x[j]. (4) * j in J j in Kp j in Kn * * To get rid of non-binary variables we can replace the inequality (4) * by the following relaxed inequality: * * sum a[j] x[j] <= b~, (5) * j in J * * where: * * b~ = sup(b - sum a[j] x[j] - sum a[j] x[j]) = * j in Kp j in Kn * * = b - inf sum a[j] x[j] - inf sum a[j] x[j] = (6) * j in Kp j in Kn * * = b - sum a[j] l[j] - sum a[j] u[j]. * j in Kp j in Kn * * Note that if lower bound l[j] (if j in Kp) or upper bound u[j] * (if j in Kn) of some non-binary variable x[j] does not exist, then * formally b = +oo, in which case further analysis is not performed. * * Let Bp = {j in J: a[j] > 0}, Bn = {j in J: a[j] < 0}. To make all * the inequality coefficients in (5) positive, we replace all x[j] in * Bn by their complementaries, substituting x[j] = 1 - x~[j] for all * j in Bn, that gives: * * sum a[j] x[j] - sum a[j] x~[j] <= b~ - sum a[j]. (7) * j in Bp j in Bn j in Bn * * This inequality is a relaxation of the original constraint (1), and * it is a binary knapsack inequality. Writing it in the standard format * we have: * * sum alfa[j] z[j] <= beta, (8) * j in J * * where: * ( + a[j], if j in Bp, * alfa[j] = < (9) * ( - a[j], if j in Bn, * * ( x[j], if j in Bp, * z[j] = < (10) * ( 1 - x[j], if j in Bn, * * beta = b~ - sum a[j]. (11) * j in Bn * * In the inequality (8) all coefficients are positive, therefore, the * packing relaxation to be found for this inequality is the following: * * sum z[j] <= 1. (12) * j in P * * It is obvious that set P within J, which we would like to find, must * satisfy to the following condition: * * alfa[j] + alfa[k] > beta + eps for all j, k in P, j != k, (13) * * where eps is an absolute tolerance for value of the linear form. * Thus, it is natural to take P = {j: alpha[j] > (beta + eps) / 2}. * Moreover, if in the equality (8) there exist coefficients alfa[k], * for which alfa[k] <= (beta + eps) / 2, but which, nevertheless, * satisfies to the condition (13) for all j in P, *one* corresponding * variable z[k] (having, for example, maximal coefficient alfa[k]) can * be included in set P, that allows increasing the number of binary * variables in (12) by one. * * Once the set P has been built, for the inequality (12) we need to * perform back substitution according to (10) in order to express it * through the original binary variables. As the result of such back * substitution the relaxed packing inequality get its final format (2), * where Jp = J intersect Bp, and Jn = J intersect Bn. */ int npp_implied_packing(NPP *npp, NPPROW *row, int which, NPPCOL *var[], char set[]) { struct elem *ptr, *e, *i, *k; int len = 0; double b, eps; /* build inequality (3) */ if (which == 0) { ptr = copy_form(npp, row, -1.0); xassert(row->lb != -DBL_MAX); b = - row->lb; } else if (which == 1) { ptr = copy_form(npp, row, +1.0); xassert(row->ub != +DBL_MAX); b = + row->ub; } /* remove non-binary variables to build relaxed inequality (5); compute its right-hand side b~ with formula (6) */ for (e = ptr; e != NULL; e = e->next) { if (!(e->xj->is_int && e->xj->lb == 0.0 && e->xj->ub == 1.0)) { /* x[j] is non-binary variable */ if (e->aj > 0.0) { if (e->xj->lb == -DBL_MAX) goto done; b -= e->aj * e->xj->lb; } else /* e->aj < 0.0 */ { if (e->xj->ub == +DBL_MAX) goto done; b -= e->aj * e->xj->ub; } /* a[j] = 0 means that variable x[j] is removed */ e->aj = 0.0; } } /* substitute x[j] = 1 - x~[j] to build knapsack inequality (8); compute its right-hand side beta with formula (11) */ for (e = ptr; e != NULL; e = e->next) if (e->aj < 0.0) b -= e->aj; /* if beta is close to zero, the knapsack inequality is either infeasible or forcing inequality; this must never happen, so we skip further analysis */ if (b < 1e-3) goto done; /* build set P as well as sets Jp and Jn, and determine x[k] as explained above in comments to the routine */ eps = 1e-3 + 1e-6 * b; i = k = NULL; for (e = ptr; e != NULL; e = e->next) { /* note that alfa[j] = |a[j]| */ if (fabs(e->aj) > 0.5 * (b + eps)) { /* alfa[j] > (b + eps) / 2; include x[j] in set P, i.e. in set Jp or Jn */ var[++len] = e->xj; set[len] = (char)(e->aj > 0.0 ? 0 : 1); /* alfa[i] = min alfa[j] over all j included in set P */ if (i == NULL || fabs(i->aj) > fabs(e->aj)) i = e; } else if (fabs(e->aj) >= 1e-3) { /* alfa[k] = max alfa[j] over all j not included in set P; we skip coefficient a[j] if it is close to zero to avoid numerically unreliable results */ if (k == NULL || fabs(k->aj) < fabs(e->aj)) k = e; } } /* if alfa[k] satisfies to condition (13) for all j in P, include x[k] in P */ if (i != NULL && k != NULL && fabs(i->aj) + fabs(k->aj) > b + eps) { var[++len] = k->xj; set[len] = (char)(k->aj > 0.0 ? 0 : 1); } /* trivial packing inequality being redundant must never appear, so we just ignore it */ if (len < 2) len = 0; done: drop_form(npp, ptr); return len; } /*********************************************************************** * NAME * * npp_is_covering - test if constraint is covering inequality * * SYNOPSIS * * #include "glpnpp.h" * int npp_is_covering(NPP *npp, NPPROW *row); * * RETURNS * * If the specified row (constraint) is covering inequality (see below), * the routine npp_is_covering returns non-zero. Otherwise, it returns * zero. * * COVERING INEQUALITIES * * In canonical format the covering inequality is the following: * * sum x[j] >= 1, (1) * j in J * * where all variables x[j] are binary. This inequality expresses the * condition that in any integer feasible solution variables in set J * cannot be all equal to zero at the same time, i.e. at least one * variable must take non-zero (unity) value. W.l.o.g. it is assumed * that |J| >= 2, because if J is empty, the inequality (1) is * infeasible, and if |J| = 1, the inequality (1) is a forcing row. * * In general case the covering inequality may include original * variables x[j] as well as their complements x~[j]: * * sum x[j] + sum x~[j] >= 1, (2) * j in Jp j in Jn * * where Jp and Jn are not intersected. Therefore, using substitution * x~[j] = 1 - x[j] gives the packing inequality in generalized format: * * sum x[j] - sum x[j] >= 1 - |Jn|. (3) * j in Jp j in Jn * * (May note that the inequality (3) cuts off infeasible solutions, * where x[j] = 0 for all j in Jp and x[j] = 1 for all j in Jn.) * * NOTE: If |J| = 2, the inequality (3) is equivalent to packing * inequality (see the routine npp_is_packing). */ int npp_is_covering(NPP *npp, NPPROW *row) { /* test if constraint is covering inequality */ NPPCOL *col; NPPAIJ *aij; int b; xassert(npp == npp); if (!(row->lb != -DBL_MAX && row->ub == +DBL_MAX)) return 0; b = 1; for (aij = row->ptr; aij != NULL; aij = aij->r_next) { col = aij->col; if (!(col->is_int && col->lb == 0.0 && col->ub == 1.0)) return 0; if (aij->val == +1.0) ; else if (aij->val == -1.0) b--; else return 0; } if (row->lb != (double)b) return 0; return 1; } /*********************************************************************** * NAME * * npp_hidden_covering - identify hidden covering inequality * * SYNOPSIS * * #include "glpnpp.h" * int npp_hidden_covering(NPP *npp, NPPROW *row); * * DESCRIPTION * * The routine npp_hidden_covering processes specified inequality * constraint, which includes only binary variables, and the number of * the variables is not less than three. If the original inequality is * equivalent to a covering inequality (see below), the routine * replaces it by the equivalent inequality. If the original constraint * is double-sided inequality, it is replaced by a pair of single-sided * inequalities, if necessary. * * RETURNS * * If the original inequality constraint was replaced by equivalent * covering inequality, the routine npp_hidden_covering returns * non-zero. Otherwise, it returns zero. * * PROBLEM TRANSFORMATION * * Consider an inequality constraint: * * sum a[j] x[j] >= b, (1) * j in J * * where all variables x[j] are binary, and |J| >= 3. (In case of '<=' * inequality it can be transformed to '>=' format by multiplying both * its sides by -1.) * * Let Jp = {j: a[j] > 0}, Jn = {j: a[j] < 0}. Performing substitution * x[j] = 1 - x~[j] for all j in Jn, we have: * * sum a[j] x[j] >= b ==> * j in J * * sum a[j] x[j] + sum a[j] x[j] >= b ==> * j in Jp j in Jn * * sum a[j] x[j] + sum a[j] (1 - x~[j]) >= b ==> * j in Jp j in Jn * * sum m a[j] x[j] - sum a[j] x~[j] >= b - sum a[j]. * j in Jp j in Jn j in Jn * * Thus, meaning the transformation above, we can assume that in * inequality (1) all coefficients a[j] are positive. Moreover, we can * assume that b > 0, because otherwise the inequality (1) would be * redundant (see the routine npp_analyze_row). It is then obvious that * constraint (1) is equivalent to covering inequality only if: * * a[j] >= b, (2) * * for all j in J. * * Once the original inequality (1) is replaced by equivalent covering * inequality, we need to perform back substitution x~[j] = 1 - x[j] for * all j in Jn (see above). * * RECOVERING SOLUTION * * None needed. */ static int hidden_covering(NPP *npp, struct elem *ptr, double *_b) { /* process inequality constraint: sum a[j] x[j] >= b; 0 - specified row is NOT hidden covering inequality; 1 - specified row is covering inequality; 2 - specified row is hidden covering inequality. */ struct elem *e; int neg; double b = *_b, eps; xassert(npp == npp); /* a[j] must be non-zero, x[j] must be binary, for all j in J */ for (e = ptr; e != NULL; e = e->next) { xassert(e->aj != 0.0); xassert(e->xj->is_int); xassert(e->xj->lb == 0.0 && e->xj->ub == 1.0); } /* check if the specified inequality constraint already has the form of covering inequality */ neg = 0; /* neg is |Jn| */ for (e = ptr; e != NULL; e = e->next) { if (e->aj == +1.0) ; else if (e->aj == -1.0) neg++; else break; } if (e == NULL) { /* all coefficients a[j] are +1 or -1; check rhs b */ if (b == (double)(1 - neg)) { /* it is covering inequality; no processing is needed */ return 1; } } /* substitute x[j] = 1 - x~[j] for all j in Jn to make all a[j] positive; the result is a~[j] = |a[j]| and new rhs b */ for (e = ptr; e != NULL; e = e->next) if (e->aj < 0) b -= e->aj; /* now a[j] > 0 for all j in J (actually |a[j]| are used) */ /* if b <= 0, skip processing--this case must not appear */ if (b < 1e-3) return 0; /* now a[j] > 0 for all j in J, and b > 0 */ /* the specified constraint is equivalent to covering inequality iff a[j] >= b for all j in J */ eps = 1e-9 + 1e-12 * fabs(b); for (e = ptr; e != NULL; e = e->next) if (fabs(e->aj) < b - eps) return 0; /* perform back substitution x~[j] = 1 - x[j] and construct the final equivalent covering inequality in generalized format */ b = 1.0; for (e = ptr; e != NULL; e = e->next) { if (e->aj > 0.0) e->aj = +1.0; else /* e->aj < 0.0 */ e->aj = -1.0, b -= 1.0; } *_b = b; return 2; } int npp_hidden_covering(NPP *npp, NPPROW *row) { /* identify hidden covering inequality */ NPPROW *copy; NPPAIJ *aij; struct elem *ptr, *e; int kase, ret, count = 0; double b; /* the row must be inequality constraint */ xassert(row->lb < row->ub); for (kase = 0; kase <= 1; kase++) { if (kase == 0) { /* process row lower bound */ if (row->lb == -DBL_MAX) continue; ptr = copy_form(npp, row, +1.0); b = + row->lb; } else { /* process row upper bound */ if (row->ub == +DBL_MAX) continue; ptr = copy_form(npp, row, -1.0); b = - row->ub; } /* now the inequality has the form "sum a[j] x[j] >= b" */ ret = hidden_covering(npp, ptr, &b); xassert(0 <= ret && ret <= 2); if (kase == 1 && ret == 1 || ret == 2) { /* the original inequality has been identified as hidden covering inequality */ count++; #ifdef GLP_DEBUG xprintf("Original constraint:\n"); for (aij = row->ptr; aij != NULL; aij = aij->r_next) xprintf(" %+g x%d", aij->val, aij->col->j); if (row->lb != -DBL_MAX) xprintf(", >= %g", row->lb); if (row->ub != +DBL_MAX) xprintf(", <= %g", row->ub); xprintf("\n"); xprintf("Equivalent covering inequality:\n"); for (e = ptr; e != NULL; e = e->next) xprintf(" %sx%d", e->aj > 0.0 ? "+" : "-", e->xj->j); xprintf(", >= %g\n", b); #endif if (row->lb == -DBL_MAX || row->ub == +DBL_MAX) { /* the original row is single-sided inequality; no copy is needed */ copy = NULL; } else { /* the original row is double-sided inequality; we need to create its copy for other bound before replacing it with the equivalent inequality */ copy = npp_add_row(npp); if (kase == 0) { /* the copy is for upper bound */ copy->lb = -DBL_MAX, copy->ub = row->ub; } else { /* the copy is for lower bound */ copy->lb = row->lb, copy->ub = +DBL_MAX; } /* copy original row coefficients */ for (aij = row->ptr; aij != NULL; aij = aij->r_next) npp_add_aij(npp, copy, aij->col, aij->val); } /* replace the original inequality by equivalent one */ npp_erase_row(npp, row); row->lb = b, row->ub = +DBL_MAX; for (e = ptr; e != NULL; e = e->next) npp_add_aij(npp, row, e->xj, e->aj); /* continue processing upper bound for the copy */ if (copy != NULL) row = copy; } drop_form(npp, ptr); } return count; } /*********************************************************************** * NAME * * npp_is_partitioning - test if constraint is partitioning equality * * SYNOPSIS * * #include "glpnpp.h" * int npp_is_partitioning(NPP *npp, NPPROW *row); * * RETURNS * * If the specified row (constraint) is partitioning equality (see * below), the routine npp_is_partitioning returns non-zero. Otherwise, * it returns zero. * * PARTITIONING EQUALITIES * * In canonical format the partitioning equality is the following: * * sum x[j] = 1, (1) * j in J * * where all variables x[j] are binary. This equality expresses the * condition that in any integer feasible solution exactly one variable * in set J must take non-zero (unity) value while other variables must * be equal to zero. W.l.o.g. it is assumed that |J| >= 2, because if * J is empty, the inequality (1) is infeasible, and if |J| = 1, the * inequality (1) is a fixing row. * * In general case the partitioning equality may include original * variables x[j] as well as their complements x~[j]: * * sum x[j] + sum x~[j] = 1, (2) * j in Jp j in Jn * * where Jp and Jn are not intersected. Therefore, using substitution * x~[j] = 1 - x[j] leads to the partitioning equality in generalized * format: * * sum x[j] - sum x[j] = 1 - |Jn|. (3) * j in Jp j in Jn */ int npp_is_partitioning(NPP *npp, NPPROW *row) { /* test if constraint is partitioning equality */ NPPCOL *col; NPPAIJ *aij; int b; xassert(npp == npp); if (row->lb != row->ub) return 0; b = 1; for (aij = row->ptr; aij != NULL; aij = aij->r_next) { col = aij->col; if (!(col->is_int && col->lb == 0.0 && col->ub == 1.0)) return 0; if (aij->val == +1.0) ; else if (aij->val == -1.0) b--; else return 0; } if (row->lb != (double)b) return 0; return 1; } /*********************************************************************** * NAME * * npp_reduce_ineq_coef - reduce inequality constraint coefficients * * SYNOPSIS * * #include "glpnpp.h" * int npp_reduce_ineq_coef(NPP *npp, NPPROW *row); * * DESCRIPTION * * The routine npp_reduce_ineq_coef processes specified inequality * constraint attempting to replace it by an equivalent constraint, * where magnitude of coefficients at binary variables is smaller than * in the original constraint. If the inequality is double-sided, it is * replaced by a pair of single-sided inequalities, if necessary. * * RETURNS * * The routine npp_reduce_ineq_coef returns the number of coefficients * reduced. * * BACKGROUND * * Consider an inequality constraint: * * sum a[j] x[j] >= b. (1) * j in J * * (In case of '<=' inequality it can be transformed to '>=' format by * multiplying both its sides by -1.) Let x[k] be a binary variable; * other variables can be integer as well as continuous. We can write * constraint (1) as follows: * * a[k] x[k] + t[k] >= b, (2) * * where: * * t[k] = sum a[j] x[j]. (3) * j in J\{k} * * Since x[k] is binary, constraint (2) is equivalent to disjunction of * the following two constraints: * * x[k] = 0, t[k] >= b (4) * * OR * * x[k] = 1, t[k] >= b - a[k]. (5) * * Let also that for the partial sum t[k] be known some its implied * lower bound inf t[k]. * * Case a[k] > 0. Let inf t[k] < b, since otherwise both constraints * (4) and (5) and therefore constraint (2) are redundant. * If inf t[k] > b - a[k], only constraint (5) is redundant, in which * case it can be replaced with the following redundant and therefore * equivalent constraint: * * t[k] >= b - a'[k] = inf t[k], (6) * * where: * * a'[k] = b - inf t[k]. (7) * * Thus, the original constraint (2) is equivalent to the following * constraint with coefficient at variable x[k] changed: * * a'[k] x[k] + t[k] >= b. (8) * * From inf t[k] < b it follows that a'[k] > 0, i.e. the coefficient * at x[k] keeps its sign. And from inf t[k] > b - a[k] it follows that * a'[k] < a[k], i.e. the coefficient reduces in magnitude. * * Case a[k] < 0. Let inf t[k] < b - a[k], since otherwise both * constraints (4) and (5) and therefore constraint (2) are redundant. * If inf t[k] > b, only constraint (4) is redundant, in which case it * can be replaced with the following redundant and therefore equivalent * constraint: * * t[k] >= b' = inf t[k]. (9) * * Rewriting constraint (5) as follows: * * t[k] >= b - a[k] = b' - a'[k], (10) * * where: * * a'[k] = a[k] + b' - b = a[k] + inf t[k] - b, (11) * * we can see that disjunction of constraint (9) and (10) is equivalent * to disjunction of constraint (4) and (5), from which it follows that * the original constraint (2) is equivalent to the following constraint * with both coefficient at variable x[k] and right-hand side changed: * * a'[k] x[k] + t[k] >= b'. (12) * * From inf t[k] < b - a[k] it follows that a'[k] < 0, i.e. the * coefficient at x[k] keeps its sign. And from inf t[k] > b it follows * that a'[k] > a[k], i.e. the coefficient reduces in magnitude. * * PROBLEM TRANSFORMATION * * In the routine npp_reduce_ineq_coef the following implied lower * bound of the partial sum (3) is used: * * inf t[k] = sum a[j] l[j] + sum a[j] u[j], (13) * j in Jp\{k} k in Jn\{k} * * where Jp = {j : a[j] > 0}, Jn = {j : a[j] < 0}, l[j] and u[j] are * lower and upper bounds, resp., of variable x[j]. * * In order to compute inf t[k] more efficiently, the following formula, * which is equivalent to (13), is actually used: * * ( h - a[k] l[k] = h, if a[k] > 0, * inf t[k] = < (14) * ( h - a[k] u[k] = h - a[k], if a[k] < 0, * * where: * * h = sum a[j] l[j] + sum a[j] u[j] (15) * j in Jp j in Jn * * is the implied lower bound of row (1). * * Reduction of positive coefficient (a[k] > 0) does not change value * of h, since l[k] = 0. In case of reduction of negative coefficient * (a[k] < 0) from (11) it follows that: * * delta a[k] = a'[k] - a[k] = inf t[k] - b (> 0), (16) * * so new value of h (accounting that u[k] = 1) can be computed as * follows: * * h := h + delta a[k] = h + (inf t[k] - b). (17) * * RECOVERING SOLUTION * * None needed. */ static int reduce_ineq_coef(NPP *npp, struct elem *ptr, double *_b) { /* process inequality constraint: sum a[j] x[j] >= b */ /* returns: the number of coefficients reduced */ struct elem *e; int count = 0; double h, inf_t, new_a, b = *_b; xassert(npp == npp); /* compute h; see (15) */ h = 0.0; for (e = ptr; e != NULL; e = e->next) { if (e->aj > 0.0) { if (e->xj->lb == -DBL_MAX) goto done; h += e->aj * e->xj->lb; } else /* e->aj < 0.0 */ { if (e->xj->ub == +DBL_MAX) goto done; h += e->aj * e->xj->ub; } } /* perform reduction of coefficients at binary variables */ for (e = ptr; e != NULL; e = e->next) { /* skip non-binary variable */ if (!(e->xj->is_int && e->xj->lb == 0.0 && e->xj->ub == 1.0)) continue; if (e->aj > 0.0) { /* compute inf t[k]; see (14) */ inf_t = h; if (b - e->aj < inf_t && inf_t < b) { /* compute reduced coefficient a'[k]; see (7) */ new_a = b - inf_t; if (new_a >= +1e-3 && e->aj - new_a >= 0.01 * (1.0 + e->aj)) { /* accept a'[k] */ #ifdef GLP_DEBUG xprintf("+"); #endif e->aj = new_a; count++; } } } else /* e->aj < 0.0 */ { /* compute inf t[k]; see (14) */ inf_t = h - e->aj; if (b < inf_t && inf_t < b - e->aj) { /* compute reduced coefficient a'[k]; see (11) */ new_a = e->aj + (inf_t - b); if (new_a <= -1e-3 && new_a - e->aj >= 0.01 * (1.0 - e->aj)) { /* accept a'[k] */ #ifdef GLP_DEBUG xprintf("-"); #endif e->aj = new_a; /* update h; see (17) */ h += (inf_t - b); /* compute b'; see (9) */ b = inf_t; count++; } } } } *_b = b; done: return count; } int npp_reduce_ineq_coef(NPP *npp, NPPROW *row) { /* reduce inequality constraint coefficients */ NPPROW *copy; NPPAIJ *aij; struct elem *ptr, *e; int kase, count[2]; double b; /* the row must be inequality constraint */ xassert(row->lb < row->ub); count[0] = count[1] = 0; for (kase = 0; kase <= 1; kase++) { if (kase == 0) { /* process row lower bound */ if (row->lb == -DBL_MAX) continue; #ifdef GLP_DEBUG xprintf("L"); #endif ptr = copy_form(npp, row, +1.0); b = + row->lb; } else { /* process row upper bound */ if (row->ub == +DBL_MAX) continue; #ifdef GLP_DEBUG xprintf("U"); #endif ptr = copy_form(npp, row, -1.0); b = - row->ub; } /* now the inequality has the form "sum a[j] x[j] >= b" */ count[kase] = reduce_ineq_coef(npp, ptr, &b); if (count[kase] > 0) { /* the original inequality has been replaced by equivalent one with coefficients reduced */ if (row->lb == -DBL_MAX || row->ub == +DBL_MAX) { /* the original row is single-sided inequality; no copy is needed */ copy = NULL; } else { /* the original row is double-sided inequality; we need to create its copy for other bound before replacing it with the equivalent inequality */ #ifdef GLP_DEBUG xprintf("*"); #endif copy = npp_add_row(npp); if (kase == 0) { /* the copy is for upper bound */ copy->lb = -DBL_MAX, copy->ub = row->ub; } else { /* the copy is for lower bound */ copy->lb = row->lb, copy->ub = +DBL_MAX; } /* copy original row coefficients */ for (aij = row->ptr; aij != NULL; aij = aij->r_next) npp_add_aij(npp, copy, aij->col, aij->val); } /* replace the original inequality by equivalent one */ npp_erase_row(npp, row); row->lb = b, row->ub = +DBL_MAX; for (e = ptr; e != NULL; e = e->next) npp_add_aij(npp, row, e->xj, e->aj); /* continue processing upper bound for the copy */ if (copy != NULL) row = copy; } drop_form(npp, ptr); } return count[0] + count[1]; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpmpl02.c0000644000076500000240000013072213524616144025205 0ustar tamasstaff00000000000000/* glpmpl02.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #define _GLPSTD_STDIO #include "glpenv.h" #include "glpmpl.h" /**********************************************************************/ /* * * PROCESSING DATA SECTION * * */ /**********************************************************************/ /*---------------------------------------------------------------------- -- create_slice - create slice. -- -- This routine creates a slice, which initially has no components. */ SLICE *create_slice(MPL *mpl) { SLICE *slice; xassert(mpl == mpl); slice = NULL; return slice; } /*---------------------------------------------------------------------- -- expand_slice - append new component to slice. -- -- This routine expands slice appending to it either a given symbol or -- null component, which becomes the last component of the slice. */ SLICE *expand_slice ( MPL *mpl, SLICE *slice, /* destroyed */ SYMBOL *sym /* destroyed */ ) { SLICE *tail, *temp; /* create a new component */ tail = dmp_get_atom(mpl->tuples, sizeof(SLICE)); tail->sym = sym; tail->next = NULL; /* and append it to the component list */ if (slice == NULL) slice = tail; else { for (temp = slice; temp->next != NULL; temp = temp->next); temp->next = tail; } return slice; } /*---------------------------------------------------------------------- -- slice_dimen - determine dimension of slice. -- -- This routine returns dimension of slice, which is number of all its -- components including null ones. */ int slice_dimen ( MPL *mpl, SLICE *slice /* not changed */ ) { SLICE *temp; int dim; xassert(mpl == mpl); dim = 0; for (temp = slice; temp != NULL; temp = temp->next) dim++; return dim; } /*---------------------------------------------------------------------- -- slice_arity - determine arity of slice. -- -- This routine returns arity of slice, i.e. number of null components -- (indicated by asterisks) in the slice. */ int slice_arity ( MPL *mpl, SLICE *slice /* not changed */ ) { SLICE *temp; int arity; xassert(mpl == mpl); arity = 0; for (temp = slice; temp != NULL; temp = temp->next) if (temp->sym == NULL) arity++; return arity; } /*---------------------------------------------------------------------- -- fake_slice - create fake slice of all asterisks. -- -- This routine creates a fake slice of given dimension, which contains -- asterisks in all components. Zero dimension is allowed. */ SLICE *fake_slice(MPL *mpl, int dim) { SLICE *slice; slice = create_slice(mpl); while (dim-- > 0) slice = expand_slice(mpl, slice, NULL); return slice; } /*---------------------------------------------------------------------- -- delete_slice - delete slice. -- -- This routine deletes specified slice. */ void delete_slice ( MPL *mpl, SLICE *slice /* destroyed */ ) { SLICE *temp; while (slice != NULL) { temp = slice; slice = temp->next; if (temp->sym != NULL) delete_symbol(mpl, temp->sym); xassert(sizeof(SLICE) == sizeof(TUPLE)); dmp_free_atom(mpl->tuples, temp, sizeof(TUPLE)); } return; } /*---------------------------------------------------------------------- -- is_number - check if current token is number. -- -- If the current token is a number, this routine returns non-zero. -- Otherwise zero is returned. */ int is_number(MPL *mpl) { return mpl->token == T_NUMBER; } /*---------------------------------------------------------------------- -- is_symbol - check if current token is symbol. -- -- If the current token is suitable to be a symbol, the routine returns -- non-zero. Otherwise zero is returned. */ int is_symbol(MPL *mpl) { return mpl->token == T_NUMBER || mpl->token == T_SYMBOL || mpl->token == T_STRING; } /*---------------------------------------------------------------------- -- is_literal - check if current token is given symbolic literal. -- -- If the current token is given symbolic literal, this routine returns -- non-zero. Otherwise zero is returned. -- -- This routine is used on processing the data section in the same way -- as the routine is_keyword on processing the model section. */ int is_literal(MPL *mpl, char *literal) { return is_symbol(mpl) && strcmp(mpl->image, literal) == 0; } /*---------------------------------------------------------------------- -- read_number - read number. -- -- This routine reads the current token, which must be a number, and -- returns its numeric value. */ double read_number(MPL *mpl) { double num; xassert(is_number(mpl)); num = mpl->value; get_token(mpl /* */); return num; } /*---------------------------------------------------------------------- -- read_symbol - read symbol. -- -- This routine reads the current token, which must be a symbol, and -- returns its symbolic value. */ SYMBOL *read_symbol(MPL *mpl) { SYMBOL *sym; xassert(is_symbol(mpl)); if (is_number(mpl)) sym = create_symbol_num(mpl, mpl->value); else sym = create_symbol_str(mpl, create_string(mpl, mpl->image)); get_token(mpl /* */); return sym; } /*---------------------------------------------------------------------- -- read_slice - read slice. -- -- This routine reads slice using the syntax: -- -- ::= [ ] -- ::= ( ) -- ::= -- ::= , -- ::= -- ::= * -- -- The bracketed form of slice is used for members of multi-dimensional -- objects while the parenthesized form is used for elemental sets. */ SLICE *read_slice ( MPL *mpl, char *name, /* not changed */ int dim ) { SLICE *slice; int close; xassert(name != NULL); switch (mpl->token) { case T_LBRACKET: close = T_RBRACKET; break; case T_LEFT: xassert(dim > 0); close = T_RIGHT; break; default: xassert(mpl != mpl); } if (dim == 0) error(mpl, "%s cannot be subscripted", name); get_token(mpl /* ( | [ */); /* read slice components */ slice = create_slice(mpl); for (;;) { /* the current token must be a symbol or asterisk */ if (is_symbol(mpl)) slice = expand_slice(mpl, slice, read_symbol(mpl)); else if (mpl->token == T_ASTERISK) { slice = expand_slice(mpl, slice, NULL); get_token(mpl /* * */); } else error(mpl, "number, symbol, or asterisk missing where expec" "ted"); /* check a token that follows the symbol */ if (mpl->token == T_COMMA) get_token(mpl /* , */); else if (mpl->token == close) break; else error(mpl, "syntax error in slice"); } /* number of slice components must be the same as the appropriate dimension */ if (slice_dimen(mpl, slice) != dim) { switch (close) { case T_RBRACKET: error(mpl, "%s must have %d subscript%s, not %d", name, dim, dim == 1 ? "" : "s", slice_dimen(mpl, slice)); break; case T_RIGHT: error(mpl, "%s has dimension %d, not %d", name, dim, slice_dimen(mpl, slice)); break; default: xassert(close != close); } } get_token(mpl /* ) | ] */); return slice; } /*---------------------------------------------------------------------- -- select_set - select set to saturate it with elemental sets. -- -- This routine selects set to saturate it with elemental sets provided -- in the data section. */ SET *select_set ( MPL *mpl, char *name /* not changed */ ) { SET *set; AVLNODE *node; xassert(name != NULL); node = avl_find_node(mpl->tree, name); if (node == NULL || avl_get_node_type(node) != A_SET) error(mpl, "%s not a set", name); set = (SET *)avl_get_node_link(node); if (set->assign != NULL || set->gadget != NULL) error(mpl, "%s needs no data", name); set->data = 1; return set; } /*---------------------------------------------------------------------- -- simple_format - read set data block in simple format. -- -- This routine reads set data block using the syntax: -- -- ::= , , ... , -- -- where are used to construct a complete n-tuple, which is -- included in elemental set assigned to the set member. Commae between -- symbols are optional and may be omitted anywhere. -- -- Number of components in the slice must be the same as dimension of -- n-tuples in elemental sets assigned to the set members. To construct -- complete n-tuple the routine replaces null positions in the slice by -- corresponding . -- -- If the slice contains at least one null position, the current token -- must be symbol. Otherwise, the routine reads no symbols to construct -- the n-tuple, so the current token is not checked. */ void simple_format ( MPL *mpl, SET *set, /* not changed */ MEMBER *memb, /* modified */ SLICE *slice /* not changed */ ) { TUPLE *tuple; SLICE *temp; SYMBOL *sym, *with = NULL; xassert(set != NULL); xassert(memb != NULL); xassert(slice != NULL); xassert(set->dimen == slice_dimen(mpl, slice)); xassert(memb->value.set->dim == set->dimen); if (slice_arity(mpl, slice) > 0) xassert(is_symbol(mpl)); /* read symbols and construct complete n-tuple */ tuple = create_tuple(mpl); for (temp = slice; temp != NULL; temp = temp->next) { if (temp->sym == NULL) { /* substitution is needed; read symbol */ if (!is_symbol(mpl)) { int lack = slice_arity(mpl, temp); /* with cannot be null due to assertion above */ xassert(with != NULL); if (lack == 1) error(mpl, "one item missing in data group beginning " "with %s", format_symbol(mpl, with)); else error(mpl, "%d items missing in data group beginning " "with %s", lack, format_symbol(mpl, with)); } sym = read_symbol(mpl); if (with == NULL) with = sym; } else { /* copy symbol from the slice */ sym = copy_symbol(mpl, temp->sym); } /* append the symbol to the n-tuple */ tuple = expand_tuple(mpl, tuple, sym); /* skip optional comma *between* */ if (temp->next != NULL && mpl->token == T_COMMA) get_token(mpl /* , */); } /* add constructed n-tuple to elemental set */ check_then_add(mpl, memb->value.set, tuple); return; } /*---------------------------------------------------------------------- -- matrix_format - read set data block in matrix format. -- -- This routine reads set data block using the syntax: -- -- ::= ... := -- +/- +/- ... +/- -- +/- +/- ... +/- -- . . . . . . . . . . . -- +/- +/- ... +/- -- -- where are symbols that denote rows of the matrix, -- are symbols that denote columns of the matrix, "+" and "-" indicate -- whether corresponding n-tuple needs to be included in the elemental -- set or not, respectively. -- -- Number of the slice components must be the same as dimension of the -- elemental set. The slice must have two null positions. To construct -- complete n-tuple for particular element of the matrix the routine -- replaces first null position of the slice by the corresponding -- (or , if the flag tr is on) and second null position by the -- corresponding (or by , if the flag tr is on). */ void matrix_format ( MPL *mpl, SET *set, /* not changed */ MEMBER *memb, /* modified */ SLICE *slice, /* not changed */ int tr ) { SLICE *list, *col, *temp; TUPLE *tuple; SYMBOL *row; xassert(set != NULL); xassert(memb != NULL); xassert(slice != NULL); xassert(set->dimen == slice_dimen(mpl, slice)); xassert(memb->value.set->dim == set->dimen); xassert(slice_arity(mpl, slice) == 2); /* read the matrix heading that contains column symbols (there may be no columns at all) */ list = create_slice(mpl); while (mpl->token != T_ASSIGN) { /* read column symbol and append it to the column list */ if (!is_symbol(mpl)) error(mpl, "number, symbol, or := missing where expected"); list = expand_slice(mpl, list, read_symbol(mpl)); } get_token(mpl /* := */); /* read zero or more rows that contain matrix data */ while (is_symbol(mpl)) { /* read row symbol (if the matrix has no columns, row symbols are just ignored) */ row = read_symbol(mpl); /* read the matrix row accordingly to the column list */ for (col = list; col != NULL; col = col->next) { int which = 0; /* check indicator */ if (is_literal(mpl, "+")) ; else if (is_literal(mpl, "-")) { get_token(mpl /* - */); continue; } else { int lack = slice_dimen(mpl, col); if (lack == 1) error(mpl, "one item missing in data group beginning " "with %s", format_symbol(mpl, row)); else error(mpl, "%d items missing in data group beginning " "with %s", lack, format_symbol(mpl, row)); } /* construct complete n-tuple */ tuple = create_tuple(mpl); for (temp = slice; temp != NULL; temp = temp->next) { if (temp->sym == NULL) { /* substitution is needed */ switch (++which) { case 1: /* substitute in the first null position */ tuple = expand_tuple(mpl, tuple, copy_symbol(mpl, tr ? col->sym : row)); break; case 2: /* substitute in the second null position */ tuple = expand_tuple(mpl, tuple, copy_symbol(mpl, tr ? row : col->sym)); break; default: xassert(which != which); } } else { /* copy symbol from the slice */ tuple = expand_tuple(mpl, tuple, copy_symbol(mpl, temp->sym)); } } xassert(which == 2); /* add constructed n-tuple to elemental set */ check_then_add(mpl, memb->value.set, tuple); get_token(mpl /* + */); } /* delete the row symbol */ delete_symbol(mpl, row); } /* delete the column list */ delete_slice(mpl, list); return; } /*---------------------------------------------------------------------- -- set_data - read set data. -- -- This routine reads set data using the syntax: -- -- ::= set ; -- ::= set [ ] ; -- ::= -- ::= -- ::= , := -- ::= , ( ) -- ::= , -- ::= , : -- ::= , (tr) -- ::= , (tr) : -- -- Commae in are optional and may be omitted anywhere. */ void set_data(MPL *mpl) { SET *set; TUPLE *tuple; MEMBER *memb; SLICE *slice; int tr = 0; xassert(is_literal(mpl, "set")); get_token(mpl /* set */); /* symbolic name of set must follows the keyword 'set' */ if (!is_symbol(mpl)) error(mpl, "set name missing where expected"); /* select the set to saturate it with data */ set = select_set(mpl, mpl->image); get_token(mpl /* */); /* read optional subscript list, which identifies member of the set to be read */ tuple = create_tuple(mpl); if (mpl->token == T_LBRACKET) { /* subscript list is specified */ if (set->dim == 0) error(mpl, "%s cannot be subscripted", set->name); get_token(mpl /* [ */); /* read symbols and construct subscript list */ for (;;) { if (!is_symbol(mpl)) error(mpl, "number or symbol missing where expected"); tuple = expand_tuple(mpl, tuple, read_symbol(mpl)); if (mpl->token == T_COMMA) get_token(mpl /* , */); else if (mpl->token == T_RBRACKET) break; else error(mpl, "syntax error in subscript list"); } if (set->dim != tuple_dimen(mpl, tuple)) error(mpl, "%s must have %d subscript%s rather than %d", set->name, set->dim, set->dim == 1 ? "" : "s", tuple_dimen(mpl, tuple)); get_token(mpl /* ] */); } else { /* subscript list is not specified */ if (set->dim != 0) error(mpl, "%s must be subscripted", set->name); } /* there must be no member with the same subscript list */ if (find_member(mpl, set->array, tuple) != NULL) error(mpl, "%s%s already defined", set->name, format_tuple(mpl, '[', tuple)); /* add new member to the set and assign it empty elemental set */ memb = add_member(mpl, set->array, tuple); memb->value.set = create_elemset(mpl, set->dimen); /* create an initial fake slice of all asterisks */ slice = fake_slice(mpl, set->dimen); /* read zero or more data assignments */ for (;;) { /* skip optional comma */ if (mpl->token == T_COMMA) get_token(mpl /* , */); /* process assignment element */ if (mpl->token == T_ASSIGN) { /* assignment ligature is non-significant element */ get_token(mpl /* := */); } else if (mpl->token == T_LEFT) { /* left parenthesis begins either new slice or "transpose" indicator */ int is_tr; get_token(mpl /* ( */); is_tr = is_literal(mpl, "tr"); unget_token(mpl /* ( */); if (is_tr) goto left; /* delete the current slice and read new one */ delete_slice(mpl, slice); slice = read_slice(mpl, set->name, set->dimen); /* each new slice resets the "transpose" indicator */ tr = 0; /* if the new slice is 0-ary, formally there is one 0-tuple (in the simple format) that follows it */ if (slice_arity(mpl, slice) == 0) simple_format(mpl, set, memb, slice); } else if (is_symbol(mpl)) { /* number or symbol begins data in the simple format */ simple_format(mpl, set, memb, slice); } else if (mpl->token == T_COLON) { /* colon begins data in the matrix format */ if (slice_arity(mpl, slice) != 2) err1: error(mpl, "slice currently used must specify 2 asterisk" "s, not %d", slice_arity(mpl, slice)); get_token(mpl /* : */); /* read elemental set data in the matrix format */ matrix_format(mpl, set, memb, slice, tr); } else if (mpl->token == T_LEFT) left: { /* left parenthesis begins the "transpose" indicator, which is followed by data in the matrix format */ get_token(mpl /* ( */); if (!is_literal(mpl, "tr")) err2: error(mpl, "transpose indicator (tr) incomplete"); if (slice_arity(mpl, slice) != 2) goto err1; get_token(mpl /* tr */); if (mpl->token != T_RIGHT) goto err2; get_token(mpl /* ) */); /* in this case the colon is optional */ if (mpl->token == T_COLON) get_token(mpl /* : */); /* set the "transpose" indicator */ tr = 1; /* read elemental set data in the matrix format */ matrix_format(mpl, set, memb, slice, tr); } else if (mpl->token == T_SEMICOLON) { /* semicolon terminates the data block */ get_token(mpl /* ; */); break; } else error(mpl, "syntax error in set data block"); } /* delete the current slice */ delete_slice(mpl, slice); return; } /*---------------------------------------------------------------------- -- select_parameter - select parameter to saturate it with data. -- -- This routine selects parameter to saturate it with data provided in -- the data section. */ PARAMETER *select_parameter ( MPL *mpl, char *name /* not changed */ ) { PARAMETER *par; AVLNODE *node; xassert(name != NULL); node = avl_find_node(mpl->tree, name); if (node == NULL || avl_get_node_type(node) != A_PARAMETER) error(mpl, "%s not a parameter", name); par = (PARAMETER *)avl_get_node_link(node); if (par->assign != NULL) error(mpl, "%s needs no data", name); if (par->data) error(mpl, "%s already provided with data", name); par->data = 1; return par; } /*---------------------------------------------------------------------- -- set_default - set default parameter value. -- -- This routine sets default value for specified parameter. */ void set_default ( MPL *mpl, PARAMETER *par, /* not changed */ SYMBOL *altval /* destroyed */ ) { xassert(par != NULL); xassert(altval != NULL); if (par->option != NULL) error(mpl, "default value for %s already specified in model se" "ction", par->name); xassert(par->defval == NULL); par->defval = altval; return; } /*---------------------------------------------------------------------- -- read_value - read value and assign it to parameter member. -- -- This routine reads numeric or symbolic value from the input stream -- and assigns to new parameter member specified by its n-tuple, which -- (the member) is created and added to the parameter array. */ MEMBER *read_value ( MPL *mpl, PARAMETER *par, /* not changed */ TUPLE *tuple /* destroyed */ ) { MEMBER *memb; xassert(par != NULL); xassert(is_symbol(mpl)); /* there must be no member with the same n-tuple */ if (find_member(mpl, par->array, tuple) != NULL) error(mpl, "%s%s already defined", par->name, format_tuple(mpl, '[', tuple)); /* create new parameter member with given n-tuple */ memb = add_member(mpl, par->array, tuple); /* read value and assigns it to the new parameter member */ switch (par->type) { case A_NUMERIC: case A_INTEGER: case A_BINARY: if (!is_number(mpl)) error(mpl, "%s requires numeric data", par->name); memb->value.num = read_number(mpl); break; case A_SYMBOLIC: memb->value.sym = read_symbol(mpl); break; default: xassert(par != par); } return memb; } /*---------------------------------------------------------------------- -- plain_format - read parameter data block in plain format. -- -- This routine reads parameter data block using the syntax: -- -- ::= , , ... , , -- -- where are used to determine a complete subscript list for -- parameter member, is a numeric or symbolic value assigned to -- the parameter member. Commae between data items are optional and may -- be omitted anywhere. -- -- Number of components in the slice must be the same as dimension of -- the parameter. To construct the complete subscript list the routine -- replaces null positions in the slice by corresponding . */ void plain_format ( MPL *mpl, PARAMETER *par, /* not changed */ SLICE *slice /* not changed */ ) { TUPLE *tuple; SLICE *temp; SYMBOL *sym, *with = NULL; xassert(par != NULL); xassert(par->dim == slice_dimen(mpl, slice)); xassert(is_symbol(mpl)); /* read symbols and construct complete subscript list */ tuple = create_tuple(mpl); for (temp = slice; temp != NULL; temp = temp->next) { if (temp->sym == NULL) { /* substitution is needed; read symbol */ if (!is_symbol(mpl)) { int lack = slice_arity(mpl, temp) + 1; xassert(with != NULL); xassert(lack > 1); error(mpl, "%d items missing in data group beginning wit" "h %s", lack, format_symbol(mpl, with)); } sym = read_symbol(mpl); if (with == NULL) with = sym; } else { /* copy symbol from the slice */ sym = copy_symbol(mpl, temp->sym); } /* append the symbol to the subscript list */ tuple = expand_tuple(mpl, tuple, sym); /* skip optional comma */ if (mpl->token == T_COMMA) get_token(mpl /* , */); } /* read value and assign it to new parameter member */ if (!is_symbol(mpl)) { xassert(with != NULL); error(mpl, "one item missing in data group beginning with %s", format_symbol(mpl, with)); } read_value(mpl, par, tuple); return; } /*---------------------------------------------------------------------- -- tabular_format - read parameter data block in tabular format. -- -- This routine reads parameter data block using the syntax: -- -- ::= ... := -- ... -- ... -- . . . . . . . . . . . -- ... -- -- where are symbols that denote rows of the table, -- are symbols that denote columns of the table, are numeric -- or symbolic values assigned to the corresponding parameter members. -- If is specified as single point, no value is provided. -- -- Number of components in the slice must be the same as dimension of -- the parameter. The slice must have two null positions. To construct -- complete subscript list for particular the routine replaces -- the first null position of the slice by the corresponding (or -- , if the flag tr is on) and the second null position by the -- corresponding (or by , if the flag tr is on). */ void tabular_format ( MPL *mpl, PARAMETER *par, /* not changed */ SLICE *slice, /* not changed */ int tr ) { SLICE *list, *col, *temp; TUPLE *tuple; SYMBOL *row; xassert(par != NULL); xassert(par->dim == slice_dimen(mpl, slice)); xassert(slice_arity(mpl, slice) == 2); /* read the table heading that contains column symbols (the table may have no columns) */ list = create_slice(mpl); while (mpl->token != T_ASSIGN) { /* read column symbol and append it to the column list */ if (!is_symbol(mpl)) error(mpl, "number, symbol, or := missing where expected"); list = expand_slice(mpl, list, read_symbol(mpl)); } get_token(mpl /* := */); /* read zero or more rows that contain tabular data */ while (is_symbol(mpl)) { /* read row symbol (if the table has no columns, these symbols are just ignored) */ row = read_symbol(mpl); /* read values accordingly to the column list */ for (col = list; col != NULL; col = col->next) { int which = 0; /* if the token is single point, no value is provided */ if (is_literal(mpl, ".")) { get_token(mpl /* . */); continue; } /* construct complete subscript list */ tuple = create_tuple(mpl); for (temp = slice; temp != NULL; temp = temp->next) { if (temp->sym == NULL) { /* substitution is needed */ switch (++which) { case 1: /* substitute in the first null position */ tuple = expand_tuple(mpl, tuple, copy_symbol(mpl, tr ? col->sym : row)); break; case 2: /* substitute in the second null position */ tuple = expand_tuple(mpl, tuple, copy_symbol(mpl, tr ? row : col->sym)); break; default: xassert(which != which); } } else { /* copy symbol from the slice */ tuple = expand_tuple(mpl, tuple, copy_symbol(mpl, temp->sym)); } } xassert(which == 2); /* read value and assign it to new parameter member */ if (!is_symbol(mpl)) { int lack = slice_dimen(mpl, col); if (lack == 1) error(mpl, "one item missing in data group beginning " "with %s", format_symbol(mpl, row)); else error(mpl, "%d items missing in data group beginning " "with %s", lack, format_symbol(mpl, row)); } read_value(mpl, par, tuple); } /* delete the row symbol */ delete_symbol(mpl, row); } /* delete the column list */ delete_slice(mpl, list); return; } /*---------------------------------------------------------------------- -- tabbing_format - read parameter data block in tabbing format. -- -- This routine reads parameter data block using the syntax: -- -- ::= , ... , , := , -- , ... , , , ... , , -- , ... , , , ... , , -- . . . . . . . . . . . . . . . . . -- , ... , , , ... , -- ::= -- ::= : -- -- where are names of parameters (all the parameters must be -- subscripted and have identical dimensions), are symbols -- used to define subscripts of parameter members, are numeric -- or symbolic values assigned to the corresponding parameter members. -- Optional may specify a simple set, in which case n-tuples -- built of for each row of the data table (i.e. subscripts -- of parameter members) are added to the specified set. Commae between -- data items are optional and may be omitted anywhere. -- -- If the parameter altval is not NULL, it specifies a default value -- provided for all the parameters specified in the data block. */ void tabbing_format ( MPL *mpl, SYMBOL *altval /* not changed */ ) { SET *set = NULL; PARAMETER *par; SLICE *list, *col; TUPLE *tuple; int next_token, j, dim = 0; char *last_name = NULL; /* read the optional */ if (is_symbol(mpl)) { get_token(mpl /* */); next_token = mpl->token; unget_token(mpl /* */); if (next_token == T_COLON) { /* select the set to saturate it with data */ set = select_set(mpl, mpl->image); /* the set must be simple (i.e. not set of sets) */ if (set->dim != 0) error(mpl, "%s must be a simple set", set->name); /* and must not be defined yet */ if (set->array->head != NULL) error(mpl, "%s already defined", set->name); /* add new (the only) member to the set and assign it empty elemental set */ add_member(mpl, set->array, NULL)->value.set = create_elemset(mpl, set->dimen); last_name = set->name, dim = set->dimen; get_token(mpl /* */); xassert(mpl->token == T_COLON); get_token(mpl /* : */); } } /* read the table heading that contains parameter names */ list = create_slice(mpl); while (mpl->token != T_ASSIGN) { /* there must be symbolic name of parameter */ if (!is_symbol(mpl)) error(mpl, "parameter name or := missing where expected"); /* select the parameter to saturate it with data */ par = select_parameter(mpl, mpl->image); /* the parameter must be subscripted */ if (par->dim == 0) error(mpl, "%s not a subscripted parameter", mpl->image); /* the set (if specified) and all the parameters in the data block must have identical dimension */ if (dim != 0 && par->dim != dim) { xassert(last_name != NULL); error(mpl, "%s has dimension %d while %s has dimension %d", last_name, dim, par->name, par->dim); } /* set default value for the parameter (if specified) */ if (altval != NULL) set_default(mpl, par, copy_symbol(mpl, altval)); /* append the parameter to the column list */ list = expand_slice(mpl, list, (SYMBOL *)par); last_name = par->name, dim = par->dim; get_token(mpl /* */); /* skip optional comma */ if (mpl->token == T_COMMA) get_token(mpl /* , */); } if (slice_dimen(mpl, list) == 0) error(mpl, "at least one parameter name required"); get_token(mpl /* := */); /* skip optional comma */ if (mpl->token == T_COMMA) get_token(mpl /* , */); /* read rows that contain tabbing data */ while (is_symbol(mpl)) { /* read subscript list */ tuple = create_tuple(mpl); for (j = 1; j <= dim; j++) { /* read j-th subscript */ if (!is_symbol(mpl)) { int lack = slice_dimen(mpl, list) + dim - j + 1; xassert(tuple != NULL); xassert(lack > 1); error(mpl, "%d items missing in data group beginning wit" "h %s", lack, format_symbol(mpl, tuple->sym)); } /* read and append j-th subscript to the n-tuple */ tuple = expand_tuple(mpl, tuple, read_symbol(mpl)); /* skip optional comma *between* */ if (j < dim && mpl->token == T_COMMA) get_token(mpl /* , */); } /* if the set is specified, add to it new n-tuple, which is a copy of the subscript list just read */ if (set != NULL) check_then_add(mpl, set->array->head->value.set, copy_tuple(mpl, tuple)); /* skip optional comma between and */ if (mpl->token == T_COMMA) get_token(mpl /* , */); /* read values accordingly to the column list */ for (col = list; col != NULL; col = col->next) { /* if the token is single point, no value is provided */ if (is_literal(mpl, ".")) { get_token(mpl /* . */); continue; } /* read value and assign it to new parameter member */ if (!is_symbol(mpl)) { int lack = slice_dimen(mpl, col); xassert(tuple != NULL); if (lack == 1) error(mpl, "one item missing in data group beginning " "with %s", format_symbol(mpl, tuple->sym)); else error(mpl, "%d items missing in data group beginning " "with %s", lack, format_symbol(mpl, tuple->sym)); } read_value(mpl, (PARAMETER *)col->sym, copy_tuple(mpl, tuple)); /* skip optional comma preceding the next value */ if (col->next != NULL && mpl->token == T_COMMA) get_token(mpl /* , */); } /* delete the original subscript list */ delete_tuple(mpl, tuple); /* skip optional comma (only if there is next data group) */ if (mpl->token == T_COMMA) { get_token(mpl /* , */); if (!is_symbol(mpl)) unget_token(mpl /* , */); } } /* delete the column list (it contains parameters, not symbols, so nullify it before) */ for (col = list; col != NULL; col = col->next) col->sym = NULL; delete_slice(mpl, list); return; } /*---------------------------------------------------------------------- -- parameter_data - read parameter data. -- -- This routine reads parameter data using the syntax: -- -- ::= param : ; -- ::= param -- ; -- ::= -- ::= -- ::= default -- ::= -- ::= , := -- ::= , [ ] -- ::= , -- ::= , : -- ::= , (tr) -- ::= , (tr) : -- -- Commae in are optional and may be omitted anywhere. */ void parameter_data(MPL *mpl) { PARAMETER *par; SYMBOL *altval = NULL; SLICE *slice; int tr = 0; xassert(is_literal(mpl, "param")); get_token(mpl /* param */); /* read optional default value */ if (is_literal(mpl, "default")) { get_token(mpl /* default */); if (!is_symbol(mpl)) error(mpl, "default value missing where expected"); altval = read_symbol(mpl); /* if the default value follows the keyword 'param', the next token must be only the colon */ if (mpl->token != T_COLON) error(mpl, "colon missing where expected"); } /* being used after the keyword 'param' or the optional default value the colon begins data in the tabbing format */ if (mpl->token == T_COLON) { get_token(mpl /* : */); /* skip optional comma */ if (mpl->token == T_COMMA) get_token(mpl /* , */); /* read parameter data in the tabbing format */ tabbing_format(mpl, altval); /* on reading data in the tabbing format the default value is always copied, so delete the original symbol */ if (altval != NULL) delete_symbol(mpl, altval); /* the next token must be only semicolon */ if (mpl->token != T_SEMICOLON) error(mpl, "symbol, number, or semicolon missing where expe" "cted"); get_token(mpl /* ; */); goto done; } /* in other cases there must be symbolic name of parameter, which follows the keyword 'param' */ if (!is_symbol(mpl)) error(mpl, "parameter name missing where expected"); /* select the parameter to saturate it with data */ par = select_parameter(mpl, mpl->image); get_token(mpl /* */); /* read optional default value */ if (is_literal(mpl, "default")) { get_token(mpl /* default */); if (!is_symbol(mpl)) error(mpl, "default value missing where expected"); altval = read_symbol(mpl); /* set default value for the parameter */ set_default(mpl, par, altval); } /* create initial fake slice of all asterisks */ slice = fake_slice(mpl, par->dim); /* read zero or more data assignments */ for (;;) { /* skip optional comma */ if (mpl->token == T_COMMA) get_token(mpl /* , */); /* process current assignment */ if (mpl->token == T_ASSIGN) { /* assignment ligature is non-significant element */ get_token(mpl /* := */); } else if (mpl->token == T_LBRACKET) { /* left bracket begins new slice; delete the current slice and read new one */ delete_slice(mpl, slice); slice = read_slice(mpl, par->name, par->dim); /* each new slice resets the "transpose" indicator */ tr = 0; } else if (is_symbol(mpl)) { /* number or symbol begins data in the plain format */ plain_format(mpl, par, slice); } else if (mpl->token == T_COLON) { /* colon begins data in the tabular format */ if (par->dim == 0) err1: error(mpl, "%s not a subscripted parameter", par->name); if (slice_arity(mpl, slice) != 2) err2: error(mpl, "slice currently used must specify 2 asterisk" "s, not %d", slice_arity(mpl, slice)); get_token(mpl /* : */); /* read parameter data in the tabular format */ tabular_format(mpl, par, slice, tr); } else if (mpl->token == T_LEFT) { /* left parenthesis begins the "transpose" indicator, which is followed by data in the tabular format */ get_token(mpl /* ( */); if (!is_literal(mpl, "tr")) err3: error(mpl, "transpose indicator (tr) incomplete"); if (par->dim == 0) goto err1; if (slice_arity(mpl, slice) != 2) goto err2; get_token(mpl /* tr */); if (mpl->token != T_RIGHT) goto err3; get_token(mpl /* ) */); /* in this case the colon is optional */ if (mpl->token == T_COLON) get_token(mpl /* : */); /* set the "transpose" indicator */ tr = 1; /* read parameter data in the tabular format */ tabular_format(mpl, par, slice, tr); } else if (mpl->token == T_SEMICOLON) { /* semicolon terminates the data block */ get_token(mpl /* ; */); break; } else error(mpl, "syntax error in parameter data block"); } /* delete the current slice */ delete_slice(mpl, slice); done: return; } /*---------------------------------------------------------------------- -- data_section - read data section. -- -- This routine reads data section using the syntax: -- -- ::= -- ::= ; -- ::= -- ::= -- -- Reading data section is terminated by either the keyword 'end' or -- the end of file. */ void data_section(MPL *mpl) { while (!(mpl->token == T_EOF || is_literal(mpl, "end"))) { if (is_literal(mpl, "set")) set_data(mpl); else if (is_literal(mpl, "param")) parameter_data(mpl); else error(mpl, "syntax error in data section"); } return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpenv01.c0000644000076500000240000001647613524616144025215 0ustar tamasstaff00000000000000/* glpenv01.c (environment initialization/termination) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wsign-conversion" #pragma clang diagnostic ignored "-Wint-conversion" #endif #include "glpapi.h" #include "igraph_error.h" /*********************************************************************** * NAME * * glp_init_env - initialize GLPK environment * * SYNOPSIS * * int glp_init_env(void); * * DESCRIPTION * * The routine glp_init_env initializes the GLPK environment. Normally * the application program does not need to call this routine, because * it is called automatically on the first call to any API routine. * * RETURNS * * The routine glp_init_env returns one of the following codes: * * 0 - initialization successful; * 1 - environment has been already initialized; * 2 - initialization failed (insufficient memory); * 3 - initialization failed (unsupported programming model). */ int glp_init_env(void) { ENV *env; int ok; /* check if the programming model is supported */ ok = (CHAR_BIT == 8 && sizeof(char) == 1 && sizeof(short) == 2 && sizeof(int) == 4 && (sizeof(void *) == 4 || sizeof(void *) == 8)); if (!ok) return 3; /* check if the environment is already initialized */ if (tls_get_ptr() != NULL) return 1; /* allocate and initialize the environment block */ env = malloc(sizeof(ENV)); if (env == NULL) return 2; env->magic = ENV_MAGIC; sprintf(env->version, "%d.%d", GLP_MAJOR_VERSION, GLP_MINOR_VERSION); env->term_buf = malloc(TERM_BUF_SIZE); if (env->term_buf == NULL) { free(env); return 2; } env->term_out = GLP_ON; env->term_hook = NULL; env->term_info = NULL; env->tee_file = NULL; env->err_file = ""; env->err_line = 0; env->err_hook = NULL; env->err_info = NULL; env->mem_limit.hi = 0x7FFFFFFF, env->mem_limit.lo = 0xFFFFFFFF; env->mem_ptr = NULL; env->mem_count = env->mem_cpeak = 0; env->mem_total = env->mem_tpeak = xlset(0); env->file_ptr = NULL; env->ioerr_msg = malloc(IOERR_MSG_SIZE); if (env->ioerr_msg == NULL) { free(env->term_buf); free(env); return 2; } strcpy(env->ioerr_msg, "No error"); env->h_odbc = env->h_mysql = NULL; /* save pointer to the environment block */ tls_set_ptr(env); /* initialization successful */ return 0; } /*********************************************************************** * NAME * * get_env_ptr - retrieve pointer to environment block * * SYNOPSIS * * #include "glpenv.h" * ENV *get_env_ptr(void); * * DESCRIPTION * * The routine get_env_ptr retrieves and returns a pointer to the GLPK * environment block. * * If the GLPK environment has not been initialized yet, the routine * performs initialization. If initialization fails, the routine prints * an error message to stderr and terminates the program. * * RETURNS * * The routine returns a pointer to the environment block. */ ENV *get_env_ptr(void) { ENV *env = tls_get_ptr(); /* check if the environment has been initialized */ if (env == NULL) { /* not initialized yet; perform initialization */ if (glp_init_env() != 0) { /* initialization failed; display an error message */ igraph_error("GLPK initialization failed", __FILE__, __LINE__, IGRAPH_EGLP); return NULL; } /* initialization successful; retrieve the pointer */ env = tls_get_ptr(); } /* check if the environment block is valid */ if (env->magic != ENV_MAGIC) { igraph_error("Invalid GLPK environment", __FILE__, __LINE__, IGRAPH_EGLP); return NULL; } return env; } /*********************************************************************** * NAME * * glp_version - determine library version * * SYNOPSIS * * const char *glp_version(void); * * RETURNS * * The routine glp_version returns a pointer to a null-terminated * character string, which specifies the version of the GLPK library in * the form "X.Y", where X is the major version number, and Y is the * minor version number, for example, "4.16". */ const char *glp_version(void) { ENV *env = get_env_ptr(); return env->version; } /*********************************************************************** * NAME * * glp_free_env - free GLPK environment * * SYNOPSIS * * int glp_free_env(void); * * DESCRIPTION * * The routine glp_free_env frees all resources used by GLPK routines * (memory blocks, etc.) which are currently still in use. * * Normally the application program does not need to call this routine, * because GLPK routines always free all unused resources. However, if * the application program even has deleted all problem objects, there * will be several memory blocks still allocated for the library needs. * For some reasons the application program may want GLPK to free this * memory, in which case it should call glp_free_env. * * Note that a call to glp_free_env invalidates all problem objects as * if no GLPK routine were called. * * RETURNS * * 0 - termination successful; * 1 - environment is inactive (was not initialized). */ int glp_free_env(void) { ENV *env = tls_get_ptr(); MEM *desc; /* check if the environment is active */ if (env == NULL) return 1; /* check if the environment block is valid */ if (env->magic != ENV_MAGIC) { IGRAPH_ERROR("Invalid GLPK environment", IGRAPH_EGLP); } /* close handles to shared libraries */ if (env->h_odbc != NULL) xdlclose(env->h_odbc); if (env->h_mysql != NULL) xdlclose(env->h_mysql); /* close streams which are still open */ while (env->file_ptr != NULL) xfclose(env->file_ptr); /* free memory blocks which are still allocated */ while (env->mem_ptr != NULL) { desc = env->mem_ptr; env->mem_ptr = desc->next; free(desc); } /* invalidate the environment block */ env->magic = -1; /* free memory allocated to the environment block */ free(env->term_buf); free(env->ioerr_msg); free(env); /* reset a pointer to the environment block */ tls_set_ptr(NULL); /* termination successful */ return 0; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpapi09.c0000644000076500000240000005754413524616144025207 0ustar tamasstaff00000000000000/* glpapi09.c (mixed integer programming routines) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glpios.h" #include "glpnpp.h" /*********************************************************************** * NAME * * glp_set_col_kind - set (change) column kind * * SYNOPSIS * * void glp_set_col_kind(glp_prob *mip, int j, int kind); * * DESCRIPTION * * The routine glp_set_col_kind sets (changes) the kind of j-th column * (structural variable) as specified by the parameter kind: * * GLP_CV - continuous variable; * GLP_IV - integer variable; * GLP_BV - binary variable. */ void glp_set_col_kind(glp_prob *mip, int j, int kind) { GLPCOL *col; if (!(1 <= j && j <= mip->n)) xerror("glp_set_col_kind: j = %d; column number out of range\n" , j); col = mip->col[j]; switch (kind) { case GLP_CV: col->kind = GLP_CV; break; case GLP_IV: col->kind = GLP_IV; break; case GLP_BV: col->kind = GLP_IV; if (!(col->type == GLP_DB && col->lb == 0.0 && col->ub == 1.0)) glp_set_col_bnds(mip, j, GLP_DB, 0.0, 1.0); break; default: xerror("glp_set_col_kind: j = %d; kind = %d; invalid column" " kind\n", j, kind); } return; } /*********************************************************************** * NAME * * glp_get_col_kind - retrieve column kind * * SYNOPSIS * * int glp_get_col_kind(glp_prob *mip, int j); * * RETURNS * * The routine glp_get_col_kind returns the kind of j-th column, i.e. * the kind of corresponding structural variable, as follows: * * GLP_CV - continuous variable; * GLP_IV - integer variable; * GLP_BV - binary variable */ int glp_get_col_kind(glp_prob *mip, int j) { GLPCOL *col; int kind; if (!(1 <= j && j <= mip->n)) xerror("glp_get_col_kind: j = %d; column number out of range\n" , j); col = mip->col[j]; kind = col->kind; switch (kind) { case GLP_CV: break; case GLP_IV: if (col->type == GLP_DB && col->lb == 0.0 && col->ub == 1.0) kind = GLP_BV; break; default: xassert(kind != kind); } return kind; } /*********************************************************************** * NAME * * glp_get_num_int - retrieve number of integer columns * * SYNOPSIS * * int glp_get_num_int(glp_prob *mip); * * RETURNS * * The routine glp_get_num_int returns the current number of columns, * which are marked as integer. */ int glp_get_num_int(glp_prob *mip) { GLPCOL *col; int j, count = 0; for (j = 1; j <= mip->n; j++) { col = mip->col[j]; if (col->kind == GLP_IV) count++; } return count; } /*********************************************************************** * NAME * * glp_get_num_bin - retrieve number of binary columns * * SYNOPSIS * * int glp_get_num_bin(glp_prob *mip); * * RETURNS * * The routine glp_get_num_bin returns the current number of columns, * which are marked as binary. */ int glp_get_num_bin(glp_prob *mip) { GLPCOL *col; int j, count = 0; for (j = 1; j <= mip->n; j++) { col = mip->col[j]; if (col->kind == GLP_IV && col->type == GLP_DB && col->lb == 0.0 && col->ub == 1.0) count++; } return count; } /*********************************************************************** * NAME * * glp_intopt - solve MIP problem with the branch-and-bound method * * SYNOPSIS * * int glp_intopt(glp_prob *P, const glp_iocp *parm); * * DESCRIPTION * * The routine glp_intopt is a driver to the MIP solver based on the * branch-and-bound method. * * On entry the problem object should contain optimal solution to LP * relaxation (which can be obtained with the routine glp_simplex). * * The MIP solver has a set of control parameters. Values of the control * parameters can be passed in a structure glp_iocp, which the parameter * parm points to. * * The parameter parm can be specified as NULL, in which case the MIP * solver uses default settings. * * RETURNS * * 0 The MIP problem instance has been successfully solved. This code * does not necessarily mean that the solver has found optimal * solution. It only means that the solution process was successful. * * GLP_EBOUND * Unable to start the search, because some double-bounded variables * have incorrect bounds or some integer variables have non-integer * (fractional) bounds. * * GLP_EROOT * Unable to start the search, because optimal basis for initial LP * relaxation is not provided. * * GLP_EFAIL * The search was prematurely terminated due to the solver failure. * * GLP_EMIPGAP * The search was prematurely terminated, because the relative mip * gap tolerance has been reached. * * GLP_ETMLIM * The search was prematurely terminated, because the time limit has * been exceeded. * * GLP_ENOPFS * The MIP problem instance has no primal feasible solution (only if * the MIP presolver is used). * * GLP_ENODFS * LP relaxation of the MIP problem instance has no dual feasible * solution (only if the MIP presolver is used). * * GLP_ESTOP * The search was prematurely terminated by application. */ static int solve_mip(glp_prob *P, const glp_iocp *parm) { /* solve MIP directly without using the preprocessor */ glp_tree *T; int ret; /* optimal basis to LP relaxation must be provided */ if (glp_get_status(P) != GLP_OPT) { if (parm->msg_lev >= GLP_MSG_ERR) xprintf("glp_intopt: optimal basis to initial LP relaxation" " not provided\n"); ret = GLP_EROOT; goto done; } /* it seems all is ok */ if (parm->msg_lev >= GLP_MSG_ALL) xprintf("Integer optimization begins...\n"); /* create the branch-and-bound tree */ T = ios_create_tree(P, parm); /* solve the problem instance */ ret = ios_driver(T); /* delete the branch-and-bound tree */ ios_delete_tree(T); /* analyze exit code reported by the mip driver */ if (ret == 0) { if (P->mip_stat == GLP_FEAS) { if (parm->msg_lev >= GLP_MSG_ALL) xprintf("INTEGER OPTIMAL SOLUTION FOUND\n"); P->mip_stat = GLP_OPT; } else { if (parm->msg_lev >= GLP_MSG_ALL) xprintf("PROBLEM HAS NO INTEGER FEASIBLE SOLUTION\n"); P->mip_stat = GLP_NOFEAS; } } else if (ret == GLP_EMIPGAP) { if (parm->msg_lev >= GLP_MSG_ALL) xprintf("RELATIVE MIP GAP TOLERANCE REACHED; SEARCH TERMINA" "TED\n"); } else if (ret == GLP_ETMLIM) { if (parm->msg_lev >= GLP_MSG_ALL) xprintf("TIME LIMIT EXCEEDED; SEARCH TERMINATED\n"); } else if (ret == GLP_EFAIL) { if (parm->msg_lev >= GLP_MSG_ERR) xprintf("glp_intopt: cannot solve current LP relaxation\n"); } else if (ret == GLP_ESTOP) { if (parm->msg_lev >= GLP_MSG_ALL) xprintf("SEARCH TERMINATED BY APPLICATION\n"); } else xassert(ret != ret); done: return ret; } static int preprocess_and_solve_mip(glp_prob *P, const glp_iocp *parm) { /* solve MIP using the preprocessor */ ENV *env = get_env_ptr(); int term_out = env->term_out; NPP *npp; glp_prob *mip = NULL; glp_bfcp bfcp; glp_smcp smcp; int ret; if (parm->msg_lev >= GLP_MSG_ALL) xprintf("Preprocessing...\n"); /* create preprocessor workspace */ npp = npp_create_wksp(); /* load original problem into the preprocessor workspace */ npp_load_prob(npp, P, GLP_OFF, GLP_MIP, GLP_OFF); /* process MIP prior to applying the branch-and-bound method */ if (!term_out || parm->msg_lev < GLP_MSG_ALL) env->term_out = GLP_OFF; else env->term_out = GLP_ON; ret = npp_integer(npp, parm); env->term_out = term_out; if (ret == 0) ; else if (ret == GLP_ENOPFS) { if (parm->msg_lev >= GLP_MSG_ALL) xprintf("PROBLEM HAS NO PRIMAL FEASIBLE SOLUTION\n"); } else if (ret == GLP_ENODFS) { if (parm->msg_lev >= GLP_MSG_ALL) xprintf("LP RELAXATION HAS NO DUAL FEASIBLE SOLUTION\n"); } else xassert(ret != ret); if (ret != 0) goto done; /* build transformed MIP */ mip = glp_create_prob(); npp_build_prob(npp, mip); /* if the transformed MIP is empty, it has empty solution, which is optimal */ if (mip->m == 0 && mip->n == 0) { mip->mip_stat = GLP_OPT; mip->mip_obj = mip->c0; if (parm->msg_lev >= GLP_MSG_ALL) { xprintf("Objective value = %17.9e\n", mip->mip_obj); xprintf("INTEGER OPTIMAL SOLUTION FOUND BY MIP PREPROCESSOR" "\n"); } goto post; } /* display some statistics */ if (parm->msg_lev >= GLP_MSG_ALL) { int ni = glp_get_num_int(mip); int nb = glp_get_num_bin(mip); char s[50]; xprintf("%d row%s, %d column%s, %d non-zero%s\n", mip->m, mip->m == 1 ? "" : "s", mip->n, mip->n == 1 ? "" : "s", mip->nnz, mip->nnz == 1 ? "" : "s"); if (nb == 0) strcpy(s, "none of"); else if (ni == 1 && nb == 1) strcpy(s, ""); else if (nb == 1) strcpy(s, "one of"); else if (nb == ni) strcpy(s, "all of"); else sprintf(s, "%d of", nb); xprintf("%d integer variable%s, %s which %s binary\n", ni, ni == 1 ? "" : "s", s, nb == 1 ? "is" : "are"); } /* inherit basis factorization control parameters */ glp_get_bfcp(P, &bfcp); glp_set_bfcp(mip, &bfcp); /* scale the transformed problem */ if (!term_out || parm->msg_lev < GLP_MSG_ALL) env->term_out = GLP_OFF; else env->term_out = GLP_ON; glp_scale_prob(mip, GLP_SF_GM | GLP_SF_EQ | GLP_SF_2N | GLP_SF_SKIP); env->term_out = term_out; /* build advanced initial basis */ if (!term_out || parm->msg_lev < GLP_MSG_ALL) env->term_out = GLP_OFF; else env->term_out = GLP_ON; glp_adv_basis(mip, 0); env->term_out = term_out; /* solve initial LP relaxation */ if (parm->msg_lev >= GLP_MSG_ALL) xprintf("Solving LP relaxation...\n"); glp_init_smcp(&smcp); smcp.msg_lev = parm->msg_lev; mip->it_cnt = P->it_cnt; ret = glp_simplex(mip, &smcp); P->it_cnt = mip->it_cnt; if (ret != 0) { if (parm->msg_lev >= GLP_MSG_ERR) xprintf("glp_intopt: cannot solve LP relaxation\n"); ret = GLP_EFAIL; goto done; } /* check status of the basic solution */ ret = glp_get_status(mip); if (ret == GLP_OPT) ret = 0; else if (ret == GLP_NOFEAS) ret = GLP_ENOPFS; else if (ret == GLP_UNBND) ret = GLP_ENODFS; else xassert(ret != ret); if (ret != 0) goto done; /* solve the transformed MIP */ mip->it_cnt = P->it_cnt; ret = solve_mip(mip, parm); P->it_cnt = mip->it_cnt; /* only integer feasible solution can be postprocessed */ if (!(mip->mip_stat == GLP_OPT || mip->mip_stat == GLP_FEAS)) { P->mip_stat = mip->mip_stat; goto done; } /* postprocess solution from the transformed MIP */ post: npp_postprocess(npp, mip); /* the transformed MIP is no longer needed */ glp_delete_prob(mip), mip = NULL; /* store solution to the original problem */ npp_unload_sol(npp, P); done: /* delete the transformed MIP, if it exists */ if (mip != NULL) glp_delete_prob(mip); /* delete preprocessor workspace */ npp_delete_wksp(npp); return ret; } #ifndef HAVE_ALIEN_SOLVER /* 28/V-2010 */ int _glp_intopt1(glp_prob *P, const glp_iocp *parm) { xassert(P == P); xassert(parm == parm); xprintf("glp_intopt: no alien solver is available\n"); return GLP_EFAIL; } #endif int glp_intopt(glp_prob *P, const glp_iocp *parm) { /* solve MIP problem with the branch-and-bound method */ glp_iocp _parm; int i, j, ret; /* check problem object */ if (P == NULL || P->magic != GLP_PROB_MAGIC) xerror("glp_intopt: P = %p; invalid problem object\n", P); if (P->tree != NULL) xerror("glp_intopt: operation not allowed\n"); /* check control parameters */ if (parm == NULL) parm = &_parm, glp_init_iocp((glp_iocp *)parm); if (!(parm->msg_lev == GLP_MSG_OFF || parm->msg_lev == GLP_MSG_ERR || parm->msg_lev == GLP_MSG_ON || parm->msg_lev == GLP_MSG_ALL || parm->msg_lev == GLP_MSG_DBG)) xerror("glp_intopt: msg_lev = %d; invalid parameter\n", parm->msg_lev); if (!(parm->br_tech == GLP_BR_FFV || parm->br_tech == GLP_BR_LFV || parm->br_tech == GLP_BR_MFV || parm->br_tech == GLP_BR_DTH || parm->br_tech == GLP_BR_PCH)) xerror("glp_intopt: br_tech = %d; invalid parameter\n", parm->br_tech); if (!(parm->bt_tech == GLP_BT_DFS || parm->bt_tech == GLP_BT_BFS || parm->bt_tech == GLP_BT_BLB || parm->bt_tech == GLP_BT_BPH)) xerror("glp_intopt: bt_tech = %d; invalid parameter\n", parm->bt_tech); if (!(0.0 < parm->tol_int && parm->tol_int < 1.0)) xerror("glp_intopt: tol_int = %g; invalid parameter\n", parm->tol_int); if (!(0.0 < parm->tol_obj && parm->tol_obj < 1.0)) xerror("glp_intopt: tol_obj = %g; invalid parameter\n", parm->tol_obj); if (parm->tm_lim < 0) xerror("glp_intopt: tm_lim = %d; invalid parameter\n", parm->tm_lim); if (parm->out_frq < 0) xerror("glp_intopt: out_frq = %d; invalid parameter\n", parm->out_frq); if (parm->out_dly < 0) xerror("glp_intopt: out_dly = %d; invalid parameter\n", parm->out_dly); if (!(0 <= parm->cb_size && parm->cb_size <= 256)) xerror("glp_intopt: cb_size = %d; invalid parameter\n", parm->cb_size); if (!(parm->pp_tech == GLP_PP_NONE || parm->pp_tech == GLP_PP_ROOT || parm->pp_tech == GLP_PP_ALL)) xerror("glp_intopt: pp_tech = %d; invalid parameter\n", parm->pp_tech); if (parm->mip_gap < 0.0) xerror("glp_intopt: mip_gap = %g; invalid parameter\n", parm->mip_gap); if (!(parm->mir_cuts == GLP_ON || parm->mir_cuts == GLP_OFF)) xerror("glp_intopt: mir_cuts = %d; invalid parameter\n", parm->mir_cuts); if (!(parm->gmi_cuts == GLP_ON || parm->gmi_cuts == GLP_OFF)) xerror("glp_intopt: gmi_cuts = %d; invalid parameter\n", parm->gmi_cuts); if (!(parm->cov_cuts == GLP_ON || parm->cov_cuts == GLP_OFF)) xerror("glp_intopt: cov_cuts = %d; invalid parameter\n", parm->cov_cuts); if (!(parm->clq_cuts == GLP_ON || parm->clq_cuts == GLP_OFF)) xerror("glp_intopt: clq_cuts = %d; invalid parameter\n", parm->clq_cuts); if (!(parm->presolve == GLP_ON || parm->presolve == GLP_OFF)) xerror("glp_intopt: presolve = %d; invalid parameter\n", parm->presolve); if (!(parm->binarize == GLP_ON || parm->binarize == GLP_OFF)) xerror("glp_intopt: binarize = %d; invalid parameter\n", parm->binarize); if (!(parm->fp_heur == GLP_ON || parm->fp_heur == GLP_OFF)) xerror("glp_intopt: fp_heur = %d; invalid parameter\n", parm->fp_heur); #if 1 /* 28/V-2010 */ if (!(parm->alien == GLP_ON || parm->alien == GLP_OFF)) xerror("glp_intopt: alien = %d; invalid parameter\n", parm->alien); #endif /* integer solution is currently undefined */ P->mip_stat = GLP_UNDEF; P->mip_obj = 0.0; /* check bounds of double-bounded variables */ for (i = 1; i <= P->m; i++) { GLPROW *row = P->row[i]; if (row->type == GLP_DB && row->lb >= row->ub) { if (parm->msg_lev >= GLP_MSG_ERR) xprintf("glp_intopt: row %d: lb = %g, ub = %g; incorrect" " bounds\n", i, row->lb, row->ub); ret = GLP_EBOUND; goto done; } } for (j = 1; j <= P->n; j++) { GLPCOL *col = P->col[j]; if (col->type == GLP_DB && col->lb >= col->ub) { if (parm->msg_lev >= GLP_MSG_ERR) xprintf("glp_intopt: column %d: lb = %g, ub = %g; incorr" "ect bounds\n", j, col->lb, col->ub); ret = GLP_EBOUND; goto done; } } /* bounds of all integer variables must be integral */ for (j = 1; j <= P->n; j++) { GLPCOL *col = P->col[j]; if (col->kind != GLP_IV) continue; if (col->type == GLP_LO || col->type == GLP_DB) { if (col->lb != floor(col->lb)) { if (parm->msg_lev >= GLP_MSG_ERR) xprintf("glp_intopt: integer column %d has non-intege" "r lower bound %g\n", j, col->lb); ret = GLP_EBOUND; goto done; } } if (col->type == GLP_UP || col->type == GLP_DB) { if (col->ub != floor(col->ub)) { if (parm->msg_lev >= GLP_MSG_ERR) xprintf("glp_intopt: integer column %d has non-intege" "r upper bound %g\n", j, col->ub); ret = GLP_EBOUND; goto done; } } if (col->type == GLP_FX) { if (col->lb != floor(col->lb)) { if (parm->msg_lev >= GLP_MSG_ERR) xprintf("glp_intopt: integer column %d has non-intege" "r fixed value %g\n", j, col->lb); ret = GLP_EBOUND; goto done; } } } /* solve MIP problem */ if (parm->msg_lev >= GLP_MSG_ALL) { int ni = glp_get_num_int(P); int nb = glp_get_num_bin(P); char s[50]; xprintf("GLPK Integer Optimizer, v%s\n", glp_version()); xprintf("%d row%s, %d column%s, %d non-zero%s\n", P->m, P->m == 1 ? "" : "s", P->n, P->n == 1 ? "" : "s", P->nnz, P->nnz == 1 ? "" : "s"); if (nb == 0) strcpy(s, "none of"); else if (ni == 1 && nb == 1) strcpy(s, ""); else if (nb == 1) strcpy(s, "one of"); else if (nb == ni) strcpy(s, "all of"); else sprintf(s, "%d of", nb); xprintf("%d integer variable%s, %s which %s binary\n", ni, ni == 1 ? "" : "s", s, nb == 1 ? "is" : "are"); } #if 1 /* 28/V-2010 */ if (parm->alien) { /* use alien integer optimizer */ ret = _glp_intopt1(P, parm); goto done; } #endif if (!parm->presolve) ret = solve_mip(P, parm); else ret = preprocess_and_solve_mip(P, parm); done: /* return to the application program */ return ret; } /*********************************************************************** * NAME * * glp_init_iocp - initialize integer optimizer control parameters * * SYNOPSIS * * void glp_init_iocp(glp_iocp *parm); * * DESCRIPTION * * The routine glp_init_iocp initializes control parameters, which are * used by the integer optimizer, with default values. * * Default values of the control parameters are stored in a glp_iocp * structure, which the parameter parm points to. */ void glp_init_iocp(glp_iocp *parm) { parm->msg_lev = GLP_MSG_ALL; parm->br_tech = GLP_BR_DTH; parm->bt_tech = GLP_BT_BLB; parm->tol_int = 1e-5; parm->tol_obj = 1e-7; parm->tm_lim = INT_MAX; parm->out_frq = 5000; parm->out_dly = 10000; parm->cb_func = NULL; parm->cb_info = NULL; parm->cb_size = 0; parm->pp_tech = GLP_PP_ALL; parm->mip_gap = 0.0; parm->mir_cuts = GLP_OFF; parm->gmi_cuts = GLP_OFF; parm->cov_cuts = GLP_OFF; parm->clq_cuts = GLP_OFF; parm->presolve = GLP_OFF; parm->binarize = GLP_OFF; parm->fp_heur = GLP_OFF; #if 1 /* 28/V-2010 */ parm->alien = GLP_OFF; #endif return; } /*********************************************************************** * NAME * * glp_mip_status - retrieve status of MIP solution * * SYNOPSIS * * int glp_mip_status(glp_prob *mip); * * RETURNS * * The routine lpx_mip_status reports the status of MIP solution found * by the branch-and-bound solver as follows: * * GLP_UNDEF - MIP solution is undefined; * GLP_OPT - MIP solution is integer optimal; * GLP_FEAS - MIP solution is integer feasible but its optimality * (or non-optimality) has not been proven, perhaps due to * premature termination of the search; * GLP_NOFEAS - problem has no integer feasible solution (proven by the * solver). */ int glp_mip_status(glp_prob *mip) { int mip_stat = mip->mip_stat; return mip_stat; } /*********************************************************************** * NAME * * glp_mip_obj_val - retrieve objective value (MIP solution) * * SYNOPSIS * * double glp_mip_obj_val(glp_prob *mip); * * RETURNS * * The routine glp_mip_obj_val returns value of the objective function * for MIP solution. */ double glp_mip_obj_val(glp_prob *mip) { /*struct LPXCPS *cps = mip->cps;*/ double z; z = mip->mip_obj; /*if (cps->round && fabs(z) < 1e-9) z = 0.0;*/ return z; } /*********************************************************************** * NAME * * glp_mip_row_val - retrieve row value (MIP solution) * * SYNOPSIS * * double glp_mip_row_val(glp_prob *mip, int i); * * RETURNS * * The routine glp_mip_row_val returns value of the auxiliary variable * associated with i-th row. */ double glp_mip_row_val(glp_prob *mip, int i) { /*struct LPXCPS *cps = mip->cps;*/ double mipx; if (!(1 <= i && i <= mip->m)) xerror("glp_mip_row_val: i = %d; row number out of range\n", i) ; mipx = mip->row[i]->mipx; /*if (cps->round && fabs(mipx) < 1e-9) mipx = 0.0;*/ return mipx; } /*********************************************************************** * NAME * * glp_mip_col_val - retrieve column value (MIP solution) * * SYNOPSIS * * double glp_mip_col_val(glp_prob *mip, int j); * * RETURNS * * The routine glp_mip_col_val returns value of the structural variable * associated with j-th column. */ double glp_mip_col_val(glp_prob *mip, int j) { /*struct LPXCPS *cps = mip->cps;*/ double mipx; if (!(1 <= j && j <= mip->n)) xerror("glp_mip_col_val: j = %d; column number out of range\n", j); mipx = mip->col[j]->mipx; /*if (cps->round && fabs(mipx) < 1e-9) mipx = 0.0;*/ return mipx; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpipm.h0000644000076500000240000000245613524616144025047 0ustar tamasstaff00000000000000/* glpipm.h (primal-dual interior-point method) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPIPM_H #define GLPIPM_H #include "glpapi.h" #define ipm_solve _glp_ipm_solve int ipm_solve(glp_prob *P, const glp_iptcp *parm); /* core LP solver based on the interior-point method */ #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glplpx01.c0000644000076500000240000013770513524616144025227 0ustar tamasstaff00000000000000/* glplpx01.c (obsolete API routines) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wsometimes-uninitialized" #endif #include "glpapi.h" struct LPXCPS { /* control parameters and statistics */ int msg_lev; /* level of messages output by the solver: 0 - no output 1 - error messages only 2 - normal output 3 - full output (includes informational messages) */ int scale; /* scaling option: 0 - no scaling 1 - equilibration scaling 2 - geometric mean scaling 3 - geometric mean scaling, then equilibration scaling */ int dual; /* dual simplex option: 0 - use primal simplex 1 - use dual simplex */ int price; /* pricing option (for both primal and dual simplex): 0 - textbook pricing 1 - steepest edge pricing */ double relax; /* relaxation parameter used in the ratio test; if it is zero, the textbook ratio test is used; if it is non-zero (should be positive), Harris' two-pass ratio test is used; in the latter case on the first pass basic variables (in the case of primal simplex) or reduced costs of non-basic variables (in the case of dual simplex) are allowed to slightly violate their bounds, but not more than (relax * tol_bnd) or (relax * tol_dj) (thus, relax is a percentage of tol_bnd or tol_dj) */ double tol_bnd; /* relative tolerance used to check if the current basic solution is primal feasible */ double tol_dj; /* absolute tolerance used to check if the current basic solution is dual feasible */ double tol_piv; /* relative tolerance used to choose eligible pivotal elements of the simplex table in the ratio test */ int round; /* solution rounding option: 0 - report all computed values and reduced costs "as is" 1 - if possible (allowed by the tolerances), replace computed values and reduced costs which are close to zero by exact zeros */ double obj_ll; /* lower limit of the objective function; if on the phase II the objective function reaches this limit and continues decreasing, the solver stops the search */ double obj_ul; /* upper limit of the objective function; if on the phase II the objective function reaches this limit and continues increasing, the solver stops the search */ int it_lim; /* simplex iterations limit; if this value is positive, it is decreased by one each time when one simplex iteration has been performed, and reaching zero value signals the solver to stop the search; negative value means no iterations limit */ double tm_lim; /* searching time limit, in seconds; if this value is positive, it is decreased each time when one simplex iteration has been performed by the amount of time spent for the iteration, and reaching zero value signals the solver to stop the search; negative value means no time limit */ int out_frq; /* output frequency, in iterations; this parameter specifies how frequently the solver sends information about the solution to the standard output */ double out_dly; /* output delay, in seconds; this parameter specifies how long the solver should delay sending information about the solution to the standard output; zero value means no delay */ int branch; /* MIP */ /* branching heuristic: 0 - branch on first variable 1 - branch on last variable 2 - branch using heuristic by Driebeck and Tomlin 3 - branch on most fractional variable */ int btrack; /* MIP */ /* backtracking heuristic: 0 - select most recent node (depth first search) 1 - select earliest node (breadth first search) 2 - select node using the best projection heuristic 3 - select node with best local bound */ double tol_int; /* MIP */ /* absolute tolerance used to check if the current basic solution is integer feasible */ double tol_obj; /* MIP */ /* relative tolerance used to check if the value of the objective function is not better than in the best known integer feasible solution */ int mps_info; /* lpx_write_mps */ /* if this flag is set, the routine lpx_write_mps outputs several comment cards that contains some information about the problem; otherwise the routine outputs no comment cards */ int mps_obj; /* lpx_write_mps */ /* this parameter tells the routine lpx_write_mps how to output the objective function row: 0 - never output objective function row 1 - always output objective function row 2 - output objective function row if and only if the problem has no free rows */ int mps_orig; /* lpx_write_mps */ /* if this flag is set, the routine lpx_write_mps uses original row and column symbolic names; otherwise the routine generates plain names using ordinal numbers of rows and columns */ int mps_wide; /* lpx_write_mps */ /* if this flag is set, the routine lpx_write_mps uses all data fields; otherwise the routine keeps fields 5 and 6 empty */ int mps_free; /* lpx_write_mps */ /* if this flag is set, the routine lpx_write_mps omits column and vector names everytime if possible (free style); otherwise the routine never omits these names (pedantic style) */ int mps_skip; /* lpx_write_mps */ /* if this flag is set, the routine lpx_write_mps skips empty columns (i.e. which has no constraint coefficients); otherwise the routine outputs all columns */ int lpt_orig; /* lpx_write_lpt */ /* if this flag is set, the routine lpx_write_lpt uses original row and column symbolic names; otherwise the routine generates plain names using ordinal numbers of rows and columns */ int presol; /* lpx_simplex */ /* LP presolver option: 0 - do not use LP presolver 1 - use LP presolver */ int binarize; /* lpx_intopt */ /* if this flag is set, the routine lpx_intopt replaces integer columns by binary ones */ int use_cuts; /* lpx_intopt */ /* if this flag is set, the routine lpx_intopt tries generating cutting planes: LPX_C_COVER - mixed cover cuts LPX_C_CLIQUE - clique cuts LPX_C_GOMORY - Gomory's mixed integer cuts LPX_C_ALL - all cuts */ double mip_gap; /* MIP */ /* relative MIP gap tolerance */ }; LPX *lpx_create_prob(void) { /* create problem object */ return glp_create_prob(); } void lpx_set_prob_name(LPX *lp, const char *name) { /* assign (change) problem name */ glp_set_prob_name(lp, name); return; } void lpx_set_obj_name(LPX *lp, const char *name) { /* assign (change) objective function name */ glp_set_obj_name(lp, name); return; } void lpx_set_obj_dir(LPX *lp, int dir) { /* set (change) optimization direction flag */ glp_set_obj_dir(lp, dir - LPX_MIN + GLP_MIN); return; } int lpx_add_rows(LPX *lp, int nrs) { /* add new rows to problem object */ return glp_add_rows(lp, nrs); } int lpx_add_cols(LPX *lp, int ncs) { /* add new columns to problem object */ return glp_add_cols(lp, ncs); } void lpx_set_row_name(LPX *lp, int i, const char *name) { /* assign (change) row name */ glp_set_row_name(lp, i, name); return; } void lpx_set_col_name(LPX *lp, int j, const char *name) { /* assign (change) column name */ glp_set_col_name(lp, j, name); return; } void lpx_set_row_bnds(LPX *lp, int i, int type, double lb, double ub) { /* set (change) row bounds */ glp_set_row_bnds(lp, i, type - LPX_FR + GLP_FR, lb, ub); return; } void lpx_set_col_bnds(LPX *lp, int j, int type, double lb, double ub) { /* set (change) column bounds */ glp_set_col_bnds(lp, j, type - LPX_FR + GLP_FR, lb, ub); return; } void lpx_set_obj_coef(glp_prob *lp, int j, double coef) { /* set (change) obj. coefficient or constant term */ glp_set_obj_coef(lp, j, coef); return; } void lpx_set_mat_row(LPX *lp, int i, int len, const int ind[], const double val[]) { /* set (replace) row of the constraint matrix */ glp_set_mat_row(lp, i, len, ind, val); return; } void lpx_set_mat_col(LPX *lp, int j, int len, const int ind[], const double val[]) { /* set (replace) column of the constraint matrix */ glp_set_mat_col(lp, j, len, ind, val); return; } void lpx_load_matrix(LPX *lp, int ne, const int ia[], const int ja[], const double ar[]) { /* load (replace) the whole constraint matrix */ glp_load_matrix(lp, ne, ia, ja, ar); return; } void lpx_del_rows(LPX *lp, int nrs, const int num[]) { /* delete specified rows from problem object */ glp_del_rows(lp, nrs, num); return; } void lpx_del_cols(LPX *lp, int ncs, const int num[]) { /* delete specified columns from problem object */ glp_del_cols(lp, ncs, num); return; } void lpx_delete_prob(LPX *lp) { /* delete problem object */ glp_delete_prob(lp); return; } const char *lpx_get_prob_name(LPX *lp) { /* retrieve problem name */ return glp_get_prob_name(lp); } const char *lpx_get_obj_name(LPX *lp) { /* retrieve objective function name */ return glp_get_obj_name(lp); } int lpx_get_obj_dir(LPX *lp) { /* retrieve optimization direction flag */ return glp_get_obj_dir(lp) - GLP_MIN + LPX_MIN; } int lpx_get_num_rows(LPX *lp) { /* retrieve number of rows */ return glp_get_num_rows(lp); } int lpx_get_num_cols(LPX *lp) { /* retrieve number of columns */ return glp_get_num_cols(lp); } const char *lpx_get_row_name(LPX *lp, int i) { /* retrieve row name */ return glp_get_row_name(lp, i); } const char *lpx_get_col_name(LPX *lp, int j) { /* retrieve column name */ return glp_get_col_name(lp, j); } int lpx_get_row_type(LPX *lp, int i) { /* retrieve row type */ return glp_get_row_type(lp, i) - GLP_FR + LPX_FR; } double lpx_get_row_lb(glp_prob *lp, int i) { /* retrieve row lower bound */ double lb; lb = glp_get_row_lb(lp, i); if (lb == -DBL_MAX) lb = 0.0; return lb; } double lpx_get_row_ub(glp_prob *lp, int i) { /* retrieve row upper bound */ double ub; ub = glp_get_row_ub(lp, i); if (ub == +DBL_MAX) ub = 0.0; return ub; } void lpx_get_row_bnds(glp_prob *lp, int i, int *typx, double *lb, double *ub) { /* retrieve row bounds */ if (typx != NULL) *typx = lpx_get_row_type(lp, i); if (lb != NULL) *lb = lpx_get_row_lb(lp, i); if (ub != NULL) *ub = lpx_get_row_ub(lp, i); return; } int lpx_get_col_type(LPX *lp, int j) { /* retrieve column type */ return glp_get_col_type(lp, j) - GLP_FR + LPX_FR; } double lpx_get_col_lb(glp_prob *lp, int j) { /* retrieve column lower bound */ double lb; lb = glp_get_col_lb(lp, j); if (lb == -DBL_MAX) lb = 0.0; return lb; } double lpx_get_col_ub(glp_prob *lp, int j) { /* retrieve column upper bound */ double ub; ub = glp_get_col_ub(lp, j); if (ub == +DBL_MAX) ub = 0.0; return ub; } void lpx_get_col_bnds(glp_prob *lp, int j, int *typx, double *lb, double *ub) { /* retrieve column bounds */ if (typx != NULL) *typx = lpx_get_col_type(lp, j); if (lb != NULL) *lb = lpx_get_col_lb(lp, j); if (ub != NULL) *ub = lpx_get_col_ub(lp, j); return; } double lpx_get_obj_coef(LPX *lp, int j) { /* retrieve obj. coefficient or constant term */ return glp_get_obj_coef(lp, j); } int lpx_get_num_nz(LPX *lp) { /* retrieve number of constraint coefficients */ return glp_get_num_nz(lp); } int lpx_get_mat_row(LPX *lp, int i, int ind[], double val[]) { /* retrieve row of the constraint matrix */ return glp_get_mat_row(lp, i, ind, val); } int lpx_get_mat_col(LPX *lp, int j, int ind[], double val[]) { /* retrieve column of the constraint matrix */ return glp_get_mat_col(lp, j, ind, val); } void lpx_create_index(LPX *lp) { /* create the name index */ glp_create_index(lp); return; } int lpx_find_row(LPX *lp, const char *name) { /* find row by its name */ return glp_find_row(lp, name); } int lpx_find_col(LPX *lp, const char *name) { /* find column by its name */ return glp_find_col(lp, name); } void lpx_delete_index(LPX *lp) { /* delete the name index */ glp_delete_index(lp); return; } void lpx_scale_prob(LPX *lp) { /* scale problem data */ switch (lpx_get_int_parm(lp, LPX_K_SCALE)) { case 0: /* no scaling */ glp_unscale_prob(lp); break; case 1: /* equilibration scaling */ glp_scale_prob(lp, GLP_SF_EQ); break; case 2: /* geometric mean scaling */ glp_scale_prob(lp, GLP_SF_GM); break; case 3: /* geometric mean scaling, then equilibration scaling */ glp_scale_prob(lp, GLP_SF_GM | GLP_SF_EQ); break; default: xassert(lp != lp); } return; } void lpx_unscale_prob(LPX *lp) { /* unscale problem data */ glp_unscale_prob(lp); return; } void lpx_set_row_stat(LPX *lp, int i, int stat) { /* set (change) row status */ glp_set_row_stat(lp, i, stat - LPX_BS + GLP_BS); return; } void lpx_set_col_stat(LPX *lp, int j, int stat) { /* set (change) column status */ glp_set_col_stat(lp, j, stat - LPX_BS + GLP_BS); return; } void lpx_std_basis(LPX *lp) { /* construct standard initial LP basis */ glp_std_basis(lp); return; } void lpx_adv_basis(LPX *lp) { /* construct advanced initial LP basis */ glp_adv_basis(lp, 0); return; } void lpx_cpx_basis(LPX *lp) { /* construct Bixby's initial LP basis */ glp_cpx_basis(lp); return; } static void fill_smcp(LPX *lp, glp_smcp *parm) { glp_init_smcp(parm); switch (lpx_get_int_parm(lp, LPX_K_MSGLEV)) { case 0: parm->msg_lev = GLP_MSG_OFF; break; case 1: parm->msg_lev = GLP_MSG_ERR; break; case 2: parm->msg_lev = GLP_MSG_ON; break; case 3: parm->msg_lev = GLP_MSG_ALL; break; default: xassert(lp != lp); } switch (lpx_get_int_parm(lp, LPX_K_DUAL)) { case 0: parm->meth = GLP_PRIMAL; break; case 1: parm->meth = GLP_DUAL; break; default: xassert(lp != lp); } switch (lpx_get_int_parm(lp, LPX_K_PRICE)) { case 0: parm->pricing = GLP_PT_STD; break; case 1: parm->pricing = GLP_PT_PSE; break; default: xassert(lp != lp); } if (lpx_get_real_parm(lp, LPX_K_RELAX) == 0.0) parm->r_test = GLP_RT_STD; else parm->r_test = GLP_RT_HAR; parm->tol_bnd = lpx_get_real_parm(lp, LPX_K_TOLBND); parm->tol_dj = lpx_get_real_parm(lp, LPX_K_TOLDJ); parm->tol_piv = lpx_get_real_parm(lp, LPX_K_TOLPIV); parm->obj_ll = lpx_get_real_parm(lp, LPX_K_OBJLL); parm->obj_ul = lpx_get_real_parm(lp, LPX_K_OBJUL); if (lpx_get_int_parm(lp, LPX_K_ITLIM) < 0) parm->it_lim = INT_MAX; else parm->it_lim = lpx_get_int_parm(lp, LPX_K_ITLIM); if (lpx_get_real_parm(lp, LPX_K_TMLIM) < 0.0) parm->tm_lim = INT_MAX; else parm->tm_lim = (int)(1000.0 * lpx_get_real_parm(lp, LPX_K_TMLIM)); parm->out_frq = lpx_get_int_parm(lp, LPX_K_OUTFRQ); parm->out_dly = (int)(1000.0 * lpx_get_real_parm(lp, LPX_K_OUTDLY)); switch (lpx_get_int_parm(lp, LPX_K_PRESOL)) { case 0: parm->presolve = GLP_OFF; break; case 1: parm->presolve = GLP_ON; break; default: xassert(lp != lp); } return; } int lpx_simplex(LPX *lp) { /* easy-to-use driver to the simplex method */ glp_smcp parm; int ret; fill_smcp(lp, &parm); ret = glp_simplex(lp, &parm); switch (ret) { case 0: ret = LPX_E_OK; break; case GLP_EBADB: case GLP_ESING: case GLP_ECOND: case GLP_EBOUND: ret = LPX_E_FAULT; break; case GLP_EFAIL: ret = LPX_E_SING; break; case GLP_EOBJLL: ret = LPX_E_OBJLL; break; case GLP_EOBJUL: ret = LPX_E_OBJUL; break; case GLP_EITLIM: ret = LPX_E_ITLIM; break; case GLP_ETMLIM: ret = LPX_E_TMLIM; break; case GLP_ENOPFS: ret = LPX_E_NOPFS; break; case GLP_ENODFS: ret = LPX_E_NODFS; break; default: xassert(ret != ret); } return ret; } int lpx_exact(LPX *lp) { /* easy-to-use driver to the exact simplex method */ glp_smcp parm; int ret; fill_smcp(lp, &parm); ret = glp_exact(lp, &parm); switch (ret) { case 0: ret = LPX_E_OK; break; case GLP_EBADB: case GLP_ESING: case GLP_EBOUND: case GLP_EFAIL: ret = LPX_E_FAULT; break; case GLP_EITLIM: ret = LPX_E_ITLIM; break; case GLP_ETMLIM: ret = LPX_E_TMLIM; break; default: xassert(ret != ret); } return ret; } int lpx_get_status(glp_prob *lp) { /* retrieve generic status of basic solution */ int status; switch (glp_get_status(lp)) { case GLP_OPT: status = LPX_OPT; break; case GLP_FEAS: status = LPX_FEAS; break; case GLP_INFEAS: status = LPX_INFEAS; break; case GLP_NOFEAS: status = LPX_NOFEAS; break; case GLP_UNBND: status = LPX_UNBND; break; case GLP_UNDEF: status = LPX_UNDEF; break; default: xassert(lp != lp); } return status; } int lpx_get_prim_stat(glp_prob *lp) { /* retrieve status of primal basic solution */ return glp_get_prim_stat(lp) - GLP_UNDEF + LPX_P_UNDEF; } int lpx_get_dual_stat(glp_prob *lp) { /* retrieve status of dual basic solution */ return glp_get_dual_stat(lp) - GLP_UNDEF + LPX_D_UNDEF; } double lpx_get_obj_val(LPX *lp) { /* retrieve objective value (basic solution) */ return glp_get_obj_val(lp); } int lpx_get_row_stat(LPX *lp, int i) { /* retrieve row status (basic solution) */ return glp_get_row_stat(lp, i) - GLP_BS + LPX_BS; } double lpx_get_row_prim(LPX *lp, int i) { /* retrieve row primal value (basic solution) */ return glp_get_row_prim(lp, i); } double lpx_get_row_dual(LPX *lp, int i) { /* retrieve row dual value (basic solution) */ return glp_get_row_dual(lp, i); } void lpx_get_row_info(glp_prob *lp, int i, int *tagx, double *vx, double *dx) { /* obtain row solution information */ if (tagx != NULL) *tagx = lpx_get_row_stat(lp, i); if (vx != NULL) *vx = lpx_get_row_prim(lp, i); if (dx != NULL) *dx = lpx_get_row_dual(lp, i); return; } int lpx_get_col_stat(LPX *lp, int j) { /* retrieve column status (basic solution) */ return glp_get_col_stat(lp, j) - GLP_BS + LPX_BS; } double lpx_get_col_prim(LPX *lp, int j) { /* retrieve column primal value (basic solution) */ return glp_get_col_prim(lp, j); } double lpx_get_col_dual(glp_prob *lp, int j) { /* retrieve column dual value (basic solution) */ return glp_get_col_dual(lp, j); } void lpx_get_col_info(glp_prob *lp, int j, int *tagx, double *vx, double *dx) { /* obtain column solution information */ if (tagx != NULL) *tagx = lpx_get_col_stat(lp, j); if (vx != NULL) *vx = lpx_get_col_prim(lp, j); if (dx != NULL) *dx = lpx_get_col_dual(lp, j); return; } int lpx_get_ray_info(LPX *lp) { /* determine what causes primal unboundness */ return glp_get_unbnd_ray(lp); } void lpx_check_kkt(LPX *lp, int scaled, LPXKKT *kkt) { /* check Karush-Kuhn-Tucker conditions */ int ae_ind, re_ind; double ae_max, re_max; xassert(scaled == scaled); _glp_check_kkt(lp, GLP_SOL, GLP_KKT_PE, &ae_max, &ae_ind, &re_max, &re_ind); kkt->pe_ae_max = ae_max; kkt->pe_ae_row = ae_ind; kkt->pe_re_max = re_max; kkt->pe_re_row = re_ind; if (re_max <= 1e-9) kkt->pe_quality = 'H'; else if (re_max <= 1e-6) kkt->pe_quality = 'M'; else if (re_max <= 1e-3) kkt->pe_quality = 'L'; else kkt->pe_quality = '?'; _glp_check_kkt(lp, GLP_SOL, GLP_KKT_PB, &ae_max, &ae_ind, &re_max, &re_ind); kkt->pb_ae_max = ae_max; kkt->pb_ae_ind = ae_ind; kkt->pb_re_max = re_max; kkt->pb_re_ind = re_ind; if (re_max <= 1e-9) kkt->pb_quality = 'H'; else if (re_max <= 1e-6) kkt->pb_quality = 'M'; else if (re_max <= 1e-3) kkt->pb_quality = 'L'; else kkt->pb_quality = '?'; _glp_check_kkt(lp, GLP_SOL, GLP_KKT_DE, &ae_max, &ae_ind, &re_max, &re_ind); kkt->de_ae_max = ae_max; if (ae_ind == 0) kkt->de_ae_col = 0; else kkt->de_ae_col = ae_ind - lp->m; kkt->de_re_max = re_max; if (re_ind == 0) kkt->de_re_col = 0; else kkt->de_re_col = ae_ind - lp->m; if (re_max <= 1e-9) kkt->de_quality = 'H'; else if (re_max <= 1e-6) kkt->de_quality = 'M'; else if (re_max <= 1e-3) kkt->de_quality = 'L'; else kkt->de_quality = '?'; _glp_check_kkt(lp, GLP_SOL, GLP_KKT_DB, &ae_max, &ae_ind, &re_max, &re_ind); kkt->db_ae_max = ae_max; kkt->db_ae_ind = ae_ind; kkt->db_re_max = re_max; kkt->db_re_ind = re_ind; if (re_max <= 1e-9) kkt->db_quality = 'H'; else if (re_max <= 1e-6) kkt->db_quality = 'M'; else if (re_max <= 1e-3) kkt->db_quality = 'L'; else kkt->db_quality = '?'; kkt->cs_ae_max = 0.0, kkt->cs_ae_ind = 0; kkt->cs_re_max = 0.0, kkt->cs_re_ind = 0; kkt->cs_quality = 'H'; return; } int lpx_warm_up(LPX *lp) { /* "warm up" LP basis */ int ret; ret = glp_warm_up(lp); if (ret == 0) ret = LPX_E_OK; else if (ret == GLP_EBADB) ret = LPX_E_BADB; else if (ret == GLP_ESING) ret = LPX_E_SING; else if (ret == GLP_ECOND) ret = LPX_E_SING; else xassert(ret != ret); return ret; } int lpx_eval_tab_row(LPX *lp, int k, int ind[], double val[]) { /* compute row of the simplex tableau */ return glp_eval_tab_row(lp, k, ind, val); } int lpx_eval_tab_col(LPX *lp, int k, int ind[], double val[]) { /* compute column of the simplex tableau */ return glp_eval_tab_col(lp, k, ind, val); } int lpx_transform_row(LPX *lp, int len, int ind[], double val[]) { /* transform explicitly specified row */ return glp_transform_row(lp, len, ind, val); } int lpx_transform_col(LPX *lp, int len, int ind[], double val[]) { /* transform explicitly specified column */ return glp_transform_col(lp, len, ind, val); } int lpx_prim_ratio_test(LPX *lp, int len, const int ind[], const double val[], int how, double tol) { /* perform primal ratio test */ int piv; piv = glp_prim_rtest(lp, len, ind, val, how, tol); xassert(0 <= piv && piv <= len); return piv == 0 ? 0 : ind[piv]; } int lpx_dual_ratio_test(LPX *lp, int len, const int ind[], const double val[], int how, double tol) { /* perform dual ratio test */ int piv; piv = glp_dual_rtest(lp, len, ind, val, how, tol); xassert(0 <= piv && piv <= len); return piv == 0 ? 0 : ind[piv]; } int lpx_interior(LPX *lp) { /* easy-to-use driver to the interior-point method */ int ret; ret = glp_interior(lp, NULL); switch (ret) { case 0: ret = LPX_E_OK; break; case GLP_EFAIL: ret = LPX_E_FAULT; break; case GLP_ENOFEAS: ret = LPX_E_NOFEAS; break; case GLP_ENOCVG: ret = LPX_E_NOCONV; break; case GLP_EITLIM: ret = LPX_E_ITLIM; break; case GLP_EINSTAB: ret = LPX_E_INSTAB; break; default: xassert(ret != ret); } return ret; } int lpx_ipt_status(glp_prob *lp) { /* retrieve status of interior-point solution */ int status; switch (glp_ipt_status(lp)) { case GLP_UNDEF: status = LPX_T_UNDEF; break; case GLP_OPT: status = LPX_T_OPT; break; default: xassert(lp != lp); } return status; } double lpx_ipt_obj_val(LPX *lp) { /* retrieve objective value (interior point) */ return glp_ipt_obj_val(lp); } double lpx_ipt_row_prim(LPX *lp, int i) { /* retrieve row primal value (interior point) */ return glp_ipt_row_prim(lp, i); } double lpx_ipt_row_dual(LPX *lp, int i) { /* retrieve row dual value (interior point) */ return glp_ipt_row_dual(lp, i); } double lpx_ipt_col_prim(LPX *lp, int j) { /* retrieve column primal value (interior point) */ return glp_ipt_col_prim(lp, j); } double lpx_ipt_col_dual(LPX *lp, int j) { /* retrieve column dual value (interior point) */ return glp_ipt_col_dual(lp, j); } void lpx_set_class(LPX *lp, int klass) { /* set problem class */ xassert(lp == lp); if (!(klass == LPX_LP || klass == LPX_MIP)) xerror("lpx_set_class: invalid problem class\n"); return; } int lpx_get_class(LPX *lp) { /* determine problem klass */ return glp_get_num_int(lp) == 0 ? LPX_LP : LPX_MIP; } void lpx_set_col_kind(LPX *lp, int j, int kind) { /* set (change) column kind */ glp_set_col_kind(lp, j, kind - LPX_CV + GLP_CV); return; } int lpx_get_col_kind(LPX *lp, int j) { /* retrieve column kind */ return glp_get_col_kind(lp, j) == GLP_CV ? LPX_CV : LPX_IV; } int lpx_get_num_int(LPX *lp) { /* retrieve number of integer columns */ return glp_get_num_int(lp); } int lpx_get_num_bin(LPX *lp) { /* retrieve number of binary columns */ return glp_get_num_bin(lp); } static int solve_mip(LPX *lp, int presolve) { glp_iocp parm; int ret; glp_init_iocp(&parm); switch (lpx_get_int_parm(lp, LPX_K_MSGLEV)) { case 0: parm.msg_lev = GLP_MSG_OFF; break; case 1: parm.msg_lev = GLP_MSG_ERR; break; case 2: parm.msg_lev = GLP_MSG_ON; break; case 3: parm.msg_lev = GLP_MSG_ALL; break; default: xassert(lp != lp); } switch (lpx_get_int_parm(lp, LPX_K_BRANCH)) { case 0: parm.br_tech = GLP_BR_FFV; break; case 1: parm.br_tech = GLP_BR_LFV; break; case 2: parm.br_tech = GLP_BR_DTH; break; case 3: parm.br_tech = GLP_BR_MFV; break; default: xassert(lp != lp); } switch (lpx_get_int_parm(lp, LPX_K_BTRACK)) { case 0: parm.bt_tech = GLP_BT_DFS; break; case 1: parm.bt_tech = GLP_BT_BFS; break; case 2: parm.bt_tech = GLP_BT_BPH; break; case 3: parm.bt_tech = GLP_BT_BLB; break; default: xassert(lp != lp); } parm.tol_int = lpx_get_real_parm(lp, LPX_K_TOLINT); parm.tol_obj = lpx_get_real_parm(lp, LPX_K_TOLOBJ); if (lpx_get_real_parm(lp, LPX_K_TMLIM) < 0.0 || lpx_get_real_parm(lp, LPX_K_TMLIM) > 1e6) parm.tm_lim = INT_MAX; else parm.tm_lim = (int)(1000.0 * lpx_get_real_parm(lp, LPX_K_TMLIM)); parm.mip_gap = lpx_get_real_parm(lp, LPX_K_MIPGAP); if (lpx_get_int_parm(lp, LPX_K_USECUTS) & LPX_C_GOMORY) parm.gmi_cuts = GLP_ON; else parm.gmi_cuts = GLP_OFF; if (lpx_get_int_parm(lp, LPX_K_USECUTS) & LPX_C_MIR) parm.mir_cuts = GLP_ON; else parm.mir_cuts = GLP_OFF; if (lpx_get_int_parm(lp, LPX_K_USECUTS) & LPX_C_COVER) parm.cov_cuts = GLP_ON; else parm.cov_cuts = GLP_OFF; if (lpx_get_int_parm(lp, LPX_K_USECUTS) & LPX_C_CLIQUE) parm.clq_cuts = GLP_ON; else parm.clq_cuts = GLP_OFF; parm.presolve = presolve; if (lpx_get_int_parm(lp, LPX_K_BINARIZE)) parm.binarize = GLP_ON; ret = glp_intopt(lp, &parm); switch (ret) { case 0: ret = LPX_E_OK; break; case GLP_ENOPFS: ret = LPX_E_NOPFS; break; case GLP_ENODFS: ret = LPX_E_NODFS; break; case GLP_EBOUND: case GLP_EROOT: ret = LPX_E_FAULT; break; case GLP_EFAIL: ret = LPX_E_SING; break; case GLP_EMIPGAP: ret = LPX_E_MIPGAP; break; case GLP_ETMLIM: ret = LPX_E_TMLIM; break; default: xassert(ret != ret); } return ret; } int lpx_integer(LPX *lp) { /* easy-to-use driver to the branch-and-bound method */ return solve_mip(lp, GLP_OFF); } int lpx_intopt(LPX *lp) { /* easy-to-use driver to the branch-and-bound method */ return solve_mip(lp, GLP_ON); } int lpx_mip_status(glp_prob *lp) { /* retrieve status of MIP solution */ int status; switch (glp_mip_status(lp)) { case GLP_UNDEF: status = LPX_I_UNDEF; break; case GLP_OPT: status = LPX_I_OPT; break; case GLP_FEAS: status = LPX_I_FEAS; break; case GLP_NOFEAS: status = LPX_I_NOFEAS; break; default: xassert(lp != lp); } return status; } double lpx_mip_obj_val(LPX *lp) { /* retrieve objective value (MIP solution) */ return glp_mip_obj_val(lp); } double lpx_mip_row_val(LPX *lp, int i) { /* retrieve row value (MIP solution) */ return glp_mip_row_val(lp, i); } double lpx_mip_col_val(LPX *lp, int j) { /* retrieve column value (MIP solution) */ return glp_mip_col_val(lp, j); } void lpx_check_int(LPX *lp, LPXKKT *kkt) { /* check integer feasibility conditions */ int ae_ind, re_ind; double ae_max, re_max; _glp_check_kkt(lp, GLP_MIP, GLP_KKT_PE, &ae_max, &ae_ind, &re_max, &re_ind); kkt->pe_ae_max = ae_max; kkt->pe_ae_row = ae_ind; kkt->pe_re_max = re_max; kkt->pe_re_row = re_ind; if (re_max <= 1e-9) kkt->pe_quality = 'H'; else if (re_max <= 1e-6) kkt->pe_quality = 'M'; else if (re_max <= 1e-3) kkt->pe_quality = 'L'; else kkt->pe_quality = '?'; _glp_check_kkt(lp, GLP_MIP, GLP_KKT_PB, &ae_max, &ae_ind, &re_max, &re_ind); kkt->pb_ae_max = ae_max; kkt->pb_ae_ind = ae_ind; kkt->pb_re_max = re_max; kkt->pb_re_ind = re_ind; if (re_max <= 1e-9) kkt->pb_quality = 'H'; else if (re_max <= 1e-6) kkt->pb_quality = 'M'; else if (re_max <= 1e-3) kkt->pb_quality = 'L'; else kkt->pb_quality = '?'; return; } #if 1 /* 17/XI-2009 */ static void reset_parms(LPX *lp) { /* reset control parameters to default values */ struct LPXCPS *cps = lp->parms; xassert(cps != NULL); cps->msg_lev = 3; cps->scale = 1; cps->dual = 0; cps->price = 1; cps->relax = 0.07; cps->tol_bnd = 1e-7; cps->tol_dj = 1e-7; cps->tol_piv = 1e-9; cps->round = 0; cps->obj_ll = -DBL_MAX; cps->obj_ul = +DBL_MAX; cps->it_lim = -1; #if 0 /* 02/XII-2010 */ lp->it_cnt = 0; #endif cps->tm_lim = -1.0; cps->out_frq = 200; cps->out_dly = 0.0; cps->branch = 2; cps->btrack = 3; cps->tol_int = 1e-5; cps->tol_obj = 1e-7; cps->mps_info = 1; cps->mps_obj = 2; cps->mps_orig = 0; cps->mps_wide = 1; cps->mps_free = 0; cps->mps_skip = 0; cps->lpt_orig = 0; cps->presol = 0; cps->binarize = 0; cps->use_cuts = 0; cps->mip_gap = 0.0; return; } #endif #if 1 /* 17/XI-2009 */ static struct LPXCPS *access_parms(LPX *lp) { /* allocate and initialize control parameters, if necessary */ if (lp->parms == NULL) { lp->parms = xmalloc(sizeof(struct LPXCPS)); reset_parms(lp); } return lp->parms; } #endif #if 1 /* 17/XI-2009 */ void lpx_reset_parms(LPX *lp) { /* reset control parameters to default values */ access_parms(lp); reset_parms(lp); return; } #endif void lpx_set_int_parm(LPX *lp, int parm, int val) { /* set (change) integer control parameter */ #if 0 /* 17/XI-2009 */ struct LPXCPS *cps = lp->cps; #else struct LPXCPS *cps = access_parms(lp); #endif switch (parm) { case LPX_K_MSGLEV: if (!(0 <= val && val <= 3)) xerror("lpx_set_int_parm: MSGLEV = %d; invalid value\n", val); cps->msg_lev = val; break; case LPX_K_SCALE: if (!(0 <= val && val <= 3)) xerror("lpx_set_int_parm: SCALE = %d; invalid value\n", val); cps->scale = val; break; case LPX_K_DUAL: if (!(val == 0 || val == 1)) xerror("lpx_set_int_parm: DUAL = %d; invalid value\n", val); cps->dual = val; break; case LPX_K_PRICE: if (!(val == 0 || val == 1)) xerror("lpx_set_int_parm: PRICE = %d; invalid value\n", val); cps->price = val; break; case LPX_K_ROUND: if (!(val == 0 || val == 1)) xerror("lpx_set_int_parm: ROUND = %d; invalid value\n", val); cps->round = val; break; case LPX_K_ITLIM: cps->it_lim = val; break; case LPX_K_ITCNT: lp->it_cnt = val; break; case LPX_K_OUTFRQ: if (!(val > 0)) xerror("lpx_set_int_parm: OUTFRQ = %d; invalid value\n", val); cps->out_frq = val; break; case LPX_K_BRANCH: if (!(val == 0 || val == 1 || val == 2 || val == 3)) xerror("lpx_set_int_parm: BRANCH = %d; invalid value\n", val); cps->branch = val; break; case LPX_K_BTRACK: if (!(val == 0 || val == 1 || val == 2 || val == 3)) xerror("lpx_set_int_parm: BTRACK = %d; invalid value\n", val); cps->btrack = val; break; case LPX_K_MPSINFO: if (!(val == 0 || val == 1)) xerror("lpx_set_int_parm: MPSINFO = %d; invalid value\n", val); cps->mps_info = val; break; case LPX_K_MPSOBJ: if (!(val == 0 || val == 1 || val == 2)) xerror("lpx_set_int_parm: MPSOBJ = %d; invalid value\n", val); cps->mps_obj = val; break; case LPX_K_MPSORIG: if (!(val == 0 || val == 1)) xerror("lpx_set_int_parm: MPSORIG = %d; invalid value\n", val); cps->mps_orig = val; break; case LPX_K_MPSWIDE: if (!(val == 0 || val == 1)) xerror("lpx_set_int_parm: MPSWIDE = %d; invalid value\n", val); cps->mps_wide = val; break; case LPX_K_MPSFREE: if (!(val == 0 || val == 1)) xerror("lpx_set_int_parm: MPSFREE = %d; invalid value\n", val); cps->mps_free = val; break; case LPX_K_MPSSKIP: if (!(val == 0 || val == 1)) xerror("lpx_set_int_parm: MPSSKIP = %d; invalid value\n", val); cps->mps_skip = val; break; case LPX_K_LPTORIG: if (!(val == 0 || val == 1)) xerror("lpx_set_int_parm: LPTORIG = %d; invalid value\n", val); cps->lpt_orig = val; break; case LPX_K_PRESOL: if (!(val == 0 || val == 1)) xerror("lpx_set_int_parm: PRESOL = %d; invalid value\n", val); cps->presol = val; break; case LPX_K_BINARIZE: if (!(val == 0 || val == 1)) xerror("lpx_set_int_parm: BINARIZE = %d; invalid value\n" , val); cps->binarize = val; break; case LPX_K_USECUTS: if (val & ~LPX_C_ALL) xerror("lpx_set_int_parm: USECUTS = 0x%X; invalid value\n", val); cps->use_cuts = val; break; case LPX_K_BFTYPE: #if 0 if (!(1 <= val && val <= 3)) xerror("lpx_set_int_parm: BFTYPE = %d; invalid value\n", val); cps->bf_type = val; #else { glp_bfcp parm; glp_get_bfcp(lp, &parm); switch (val) { case 1: parm.type = GLP_BF_FT; break; case 2: parm.type = GLP_BF_BG; break; case 3: parm.type = GLP_BF_GR; break; default: xerror("lpx_set_int_parm: BFTYPE = %d; invalid val" "ue\n", val); } glp_set_bfcp(lp, &parm); } #endif break; default: xerror("lpx_set_int_parm: parm = %d; invalid parameter\n", parm); } return; } int lpx_get_int_parm(LPX *lp, int parm) { /* query integer control parameter */ #if 0 /* 17/XI-2009 */ struct LPXCPS *cps = lp->cps; #else struct LPXCPS *cps = access_parms(lp); #endif int val = 0; switch (parm) { case LPX_K_MSGLEV: val = cps->msg_lev; break; case LPX_K_SCALE: val = cps->scale; break; case LPX_K_DUAL: val = cps->dual; break; case LPX_K_PRICE: val = cps->price; break; case LPX_K_ROUND: val = cps->round; break; case LPX_K_ITLIM: val = cps->it_lim; break; case LPX_K_ITCNT: val = lp->it_cnt; break; case LPX_K_OUTFRQ: val = cps->out_frq; break; case LPX_K_BRANCH: val = cps->branch; break; case LPX_K_BTRACK: val = cps->btrack; break; case LPX_K_MPSINFO: val = cps->mps_info; break; case LPX_K_MPSOBJ: val = cps->mps_obj; break; case LPX_K_MPSORIG: val = cps->mps_orig; break; case LPX_K_MPSWIDE: val = cps->mps_wide; break; case LPX_K_MPSFREE: val = cps->mps_free; break; case LPX_K_MPSSKIP: val = cps->mps_skip; break; case LPX_K_LPTORIG: val = cps->lpt_orig; break; case LPX_K_PRESOL: val = cps->presol; break; case LPX_K_BINARIZE: val = cps->binarize; break; case LPX_K_USECUTS: val = cps->use_cuts; break; case LPX_K_BFTYPE: #if 0 val = cps->bf_type; break; #else { glp_bfcp parm; glp_get_bfcp(lp, &parm); switch (parm.type) { case GLP_BF_FT: val = 1; break; case GLP_BF_BG: val = 2; break; case GLP_BF_GR: val = 3; break; default: xassert(lp != lp); } } break; #endif default: xerror("lpx_get_int_parm: parm = %d; invalid parameter\n", parm); } return val; } void lpx_set_real_parm(LPX *lp, int parm, double val) { /* set (change) real control parameter */ #if 0 /* 17/XI-2009 */ struct LPXCPS *cps = lp->cps; #else struct LPXCPS *cps = access_parms(lp); #endif switch (parm) { case LPX_K_RELAX: if (!(0.0 <= val && val <= 1.0)) xerror("lpx_set_real_parm: RELAX = %g; invalid value\n", val); cps->relax = val; break; case LPX_K_TOLBND: if (!(DBL_EPSILON <= val && val <= 0.001)) xerror("lpx_set_real_parm: TOLBND = %g; invalid value\n", val); #if 0 if (cps->tol_bnd > val) { /* invalidate the basic solution */ lp->p_stat = LPX_P_UNDEF; lp->d_stat = LPX_D_UNDEF; } #endif cps->tol_bnd = val; break; case LPX_K_TOLDJ: if (!(DBL_EPSILON <= val && val <= 0.001)) xerror("lpx_set_real_parm: TOLDJ = %g; invalid value\n", val); #if 0 if (cps->tol_dj > val) { /* invalidate the basic solution */ lp->p_stat = LPX_P_UNDEF; lp->d_stat = LPX_D_UNDEF; } #endif cps->tol_dj = val; break; case LPX_K_TOLPIV: if (!(DBL_EPSILON <= val && val <= 0.001)) xerror("lpx_set_real_parm: TOLPIV = %g; invalid value\n", val); cps->tol_piv = val; break; case LPX_K_OBJLL: cps->obj_ll = val; break; case LPX_K_OBJUL: cps->obj_ul = val; break; case LPX_K_TMLIM: cps->tm_lim = val; break; case LPX_K_OUTDLY: cps->out_dly = val; break; case LPX_K_TOLINT: if (!(DBL_EPSILON <= val && val <= 0.001)) xerror("lpx_set_real_parm: TOLINT = %g; invalid value\n", val); cps->tol_int = val; break; case LPX_K_TOLOBJ: if (!(DBL_EPSILON <= val && val <= 0.001)) xerror("lpx_set_real_parm: TOLOBJ = %g; invalid value\n", val); cps->tol_obj = val; break; case LPX_K_MIPGAP: if (val < 0.0) xerror("lpx_set_real_parm: MIPGAP = %g; invalid value\n", val); cps->mip_gap = val; break; default: xerror("lpx_set_real_parm: parm = %d; invalid parameter\n", parm); } return; } double lpx_get_real_parm(LPX *lp, int parm) { /* query real control parameter */ #if 0 /* 17/XI-2009 */ struct LPXCPS *cps = lp->cps; #else struct LPXCPS *cps = access_parms(lp); #endif double val = 0.0; switch (parm) { case LPX_K_RELAX: val = cps->relax; break; case LPX_K_TOLBND: val = cps->tol_bnd; break; case LPX_K_TOLDJ: val = cps->tol_dj; break; case LPX_K_TOLPIV: val = cps->tol_piv; break; case LPX_K_OBJLL: val = cps->obj_ll; break; case LPX_K_OBJUL: val = cps->obj_ul; break; case LPX_K_TMLIM: val = cps->tm_lim; break; case LPX_K_OUTDLY: val = cps->out_dly; break; case LPX_K_TOLINT: val = cps->tol_int; break; case LPX_K_TOLOBJ: val = cps->tol_obj; break; case LPX_K_MIPGAP: val = cps->mip_gap; break; default: xerror("lpx_get_real_parm: parm = %d; invalid parameter\n", parm); } return val; } LPX *lpx_read_mps(const char *fname) { /* read problem data in fixed MPS format */ LPX *lp = lpx_create_prob(); if (glp_read_mps(lp, GLP_MPS_DECK, NULL, fname)) lpx_delete_prob(lp), lp = NULL; return lp; } int lpx_write_mps(LPX *lp, const char *fname) { /* write problem data in fixed MPS format */ return glp_write_mps(lp, GLP_MPS_DECK, NULL, fname); } int lpx_read_bas(LPX *lp, const char *fname) { /* read LP basis in fixed MPS format */ #if 0 /* 13/IV-2009 */ return read_bas(lp, fname); #else xassert(lp == lp); xassert(fname == fname); xerror("lpx_read_bas: operation not supported\n"); return 0; #endif } int lpx_write_bas(LPX *lp, const char *fname) { /* write LP basis in fixed MPS format */ #if 0 /* 13/IV-2009 */ return write_bas(lp, fname); #else xassert(lp == lp); xassert(fname == fname); xerror("lpx_write_bas: operation not supported\n"); return 0; #endif } LPX *lpx_read_freemps(const char *fname) { /* read problem data in free MPS format */ LPX *lp = lpx_create_prob(); if (glp_read_mps(lp, GLP_MPS_FILE, NULL, fname)) lpx_delete_prob(lp), lp = NULL; return lp; } int lpx_write_freemps(LPX *lp, const char *fname) { /* write problem data in free MPS format */ return glp_write_mps(lp, GLP_MPS_FILE, NULL, fname); } LPX *lpx_read_cpxlp(const char *fname) { /* read problem data in CPLEX LP format */ LPX *lp; lp = lpx_create_prob(); if (glp_read_lp(lp, NULL, fname)) lpx_delete_prob(lp), lp = NULL; return lp; } int lpx_write_cpxlp(LPX *lp, const char *fname) { /* write problem data in CPLEX LP format */ return glp_write_lp(lp, NULL, fname); } LPX *lpx_read_model(const char *model, const char *data, const char *output) { /* read LP/MIP model written in GNU MathProg language */ LPX *lp = NULL; glp_tran *tran; /* allocate the translator workspace */ tran = glp_mpl_alloc_wksp(); /* read model section and optional data section */ if (glp_mpl_read_model(tran, model, data != NULL)) goto done; /* read separate data section, if required */ if (data != NULL) if (glp_mpl_read_data(tran, data)) goto done; /* generate the model */ if (glp_mpl_generate(tran, output)) goto done; /* build the problem instance from the model */ lp = glp_create_prob(); glp_mpl_build_prob(tran, lp); done: /* free the translator workspace */ glp_mpl_free_wksp(tran); /* bring the problem object to the calling program */ return lp; } int lpx_print_prob(LPX *lp, const char *fname) { /* write problem data in plain text format */ return glp_write_lp(lp, NULL, fname); } int lpx_print_sol(LPX *lp, const char *fname) { /* write LP problem solution in printable format */ return glp_print_sol(lp, fname); } int lpx_print_sens_bnds(LPX *lp, const char *fname) { /* write bounds sensitivity information */ if (glp_get_status(lp) == GLP_OPT && !glp_bf_exists(lp)) glp_factorize(lp); return glp_print_ranges(lp, 0, NULL, 0, fname); } int lpx_print_ips(LPX *lp, const char *fname) { /* write interior point solution in printable format */ return glp_print_ipt(lp, fname); } int lpx_print_mip(LPX *lp, const char *fname) { /* write MIP problem solution in printable format */ return glp_print_mip(lp, fname); } int lpx_is_b_avail(glp_prob *lp) { /* check if LP basis is available */ return glp_bf_exists(lp); } int lpx_main(int argc, const char *argv[]) { /* stand-alone LP/MIP solver */ return glp_main(argc, argv); } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpapi03.c0000644000076500000240000001215713524616144025170 0ustar tamasstaff00000000000000/* glpapi03.c (row and column searching routines) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glpapi.h" /*********************************************************************** * NAME * * glp_create_index - create the name index * * SYNOPSIS * * void glp_create_index(glp_prob *lp); * * DESCRIPTION * * The routine glp_create_index creates the name index for the * specified problem object. The name index is an auxiliary data * structure, which is intended to quickly (i.e. for logarithmic time) * find rows and columns by their names. * * This routine can be called at any time. If the name index already * exists, the routine does nothing. */ void glp_create_index(glp_prob *lp) { GLPROW *row; GLPCOL *col; int i, j; /* create row name index */ if (lp->r_tree == NULL) { lp->r_tree = avl_create_tree(avl_strcmp, NULL); for (i = 1; i <= lp->m; i++) { row = lp->row[i]; xassert(row->node == NULL); if (row->name != NULL) { row->node = avl_insert_node(lp->r_tree, row->name); avl_set_node_link(row->node, row); } } } /* create column name index */ if (lp->c_tree == NULL) { lp->c_tree = avl_create_tree(avl_strcmp, NULL); for (j = 1; j <= lp->n; j++) { col = lp->col[j]; xassert(col->node == NULL); if (col->name != NULL) { col->node = avl_insert_node(lp->c_tree, col->name); avl_set_node_link(col->node, col); } } } return; } /*********************************************************************** * NAME * * glp_find_row - find row by its name * * SYNOPSIS * * int glp_find_row(glp_prob *lp, const char *name); * * RETURNS * * The routine glp_find_row returns the ordinal number of a row, * which is assigned (by the routine glp_set_row_name) the specified * symbolic name. If no such row exists, the routine returns 0. */ int glp_find_row(glp_prob *lp, const char *name) { AVLNODE *node; int i = 0; if (lp->r_tree == NULL) xerror("glp_find_row: row name index does not exist\n"); if (!(name == NULL || name[0] == '\0' || strlen(name) > 255)) { node = avl_find_node(lp->r_tree, name); if (node != NULL) i = ((GLPROW *)avl_get_node_link(node))->i; } return i; } /*********************************************************************** * NAME * * glp_find_col - find column by its name * * SYNOPSIS * * int glp_find_col(glp_prob *lp, const char *name); * * RETURNS * * The routine glp_find_col returns the ordinal number of a column, * which is assigned (by the routine glp_set_col_name) the specified * symbolic name. If no such column exists, the routine returns 0. */ int glp_find_col(glp_prob *lp, const char *name) { AVLNODE *node; int j = 0; if (lp->c_tree == NULL) xerror("glp_find_col: column name index does not exist\n"); if (!(name == NULL || name[0] == '\0' || strlen(name) > 255)) { node = avl_find_node(lp->c_tree, name); if (node != NULL) j = ((GLPCOL *)avl_get_node_link(node))->j; } return j; } /*********************************************************************** * NAME * * glp_delete_index - delete the name index * * SYNOPSIS * * void glp_delete_index(glp_prob *lp); * * DESCRIPTION * * The routine glp_delete_index deletes the name index previously * created by the routine glp_create_index and frees the memory * allocated to this auxiliary data structure. * * This routine can be called at any time. If the name index does not * exist, the routine does nothing. */ void glp_delete_index(glp_prob *lp) { int i, j; /* delete row name index */ if (lp->r_tree != NULL) { for (i = 1; i <= lp->m; i++) lp->row[i]->node = NULL; avl_delete_tree(lp->r_tree), lp->r_tree = NULL; } /* delete column name index */ if (lp->c_tree != NULL) { for (j = 1; j <= lp->n; j++) lp->col[j]->node = NULL; avl_delete_tree(lp->c_tree), lp->c_tree = NULL; } return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glprgr.c0000644000076500000240000001415413524616144025045 0ustar tamasstaff00000000000000/* glprgr.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #define _GLPSTD_ERRNO #define _GLPSTD_STDIO #include "glpenv.h" #include "glprgr.h" #define xfault xerror /*********************************************************************** * NAME * * rgr_write_bmp16 - write 16-color raster image in BMP file format * * SYNOPSIS * * #include "glprgr.h" * int rgr_write_bmp16(const char *fname, int m, int n, const char * map[]); * * DESCRIPTION * * The routine rgr_write_bmp16 writes 16-color raster image in * uncompressed BMP file format (Windows bitmap) to a binary file whose * name is specified by the character string fname. * * The parameters m and n specify, respectively, the number of rows and * the numbers of columns (i.e. height and width) of the raster image. * * The character array map has m*n elements. Elements map[0, ..., n-1] * correspond to the first (top) scanline, elements map[n, ..., 2*n-1] * correspond to the second scanline, etc. * * Each element of the array map specifies a color of the corresponding * pixel as 8-bit binary number XXXXIRGB, where four high-order bits (X) * are ignored, I is high intensity bit, R is red color bit, G is green * color bit, and B is blue color bit. Thus, all 16 possible colors are * coded as following hexadecimal numbers: * * 0x00 = black 0x08 = dark gray * 0x01 = blue 0x09 = bright blue * 0x02 = green 0x0A = bright green * 0x03 = cyan 0x0B = bright cyan * 0x04 = red 0x0C = bright red * 0x05 = magenta 0x0D = bright magenta * 0x06 = brown 0x0E = yellow * 0x07 = light gray 0x0F = white * * RETURNS * * If no error occured, the routine returns zero; otherwise, it prints * an appropriate error message and returns non-zero. */ static void put_byte(FILE *fp, int c) { fputc(c, fp); return; } static void put_word(FILE *fp, int w) { /* big endian */ put_byte(fp, w); put_byte(fp, w >> 8); return; } static void put_dword(FILE *fp, int d) { /* big endian */ put_word(fp, d); put_word(fp, d >> 16); return; } int rgr_write_bmp16(const char *fname, int m, int n, const char map[]) { FILE *fp; int offset, bmsize, i, j, b, ret = 0; if (!(1 <= m && m <= 32767)) xfault("rgr_write_bmp16: m = %d; invalid height\n", m); if (!(1 <= n && n <= 32767)) xfault("rgr_write_bmp16: n = %d; invalid width\n", n); fp = fopen(fname, "wb"); if (fp == NULL) { xprintf("rgr_write_bmp16: unable to create `%s' - %s\n", fname, strerror(errno)); ret = 1; goto fini; } offset = 14 + 40 + 16 * 4; bmsize = (4 * n + 31) / 32; /* struct BMPFILEHEADER (14 bytes) */ /* UINT bfType */ put_byte(fp, 'B'), put_byte(fp, 'M'); /* DWORD bfSize */ put_dword(fp, offset + bmsize * 4); /* UINT bfReserved1 */ put_word(fp, 0); /* UNIT bfReserved2 */ put_word(fp, 0); /* DWORD bfOffBits */ put_dword(fp, offset); /* struct BMPINFOHEADER (40 bytes) */ /* DWORD biSize */ put_dword(fp, 40); /* LONG biWidth */ put_dword(fp, n); /* LONG biHeight */ put_dword(fp, m); /* WORD biPlanes */ put_word(fp, 1); /* WORD biBitCount */ put_word(fp, 4); /* DWORD biCompression */ put_dword(fp, 0 /* BI_RGB */); /* DWORD biSizeImage */ put_dword(fp, 0); /* LONG biXPelsPerMeter */ put_dword(fp, 2953 /* 75 dpi */); /* LONG biYPelsPerMeter */ put_dword(fp, 2953 /* 75 dpi */); /* DWORD biClrUsed */ put_dword(fp, 0); /* DWORD biClrImportant */ put_dword(fp, 0); /* struct RGBQUAD (16 * 4 = 64 bytes) */ /* CGA-compatible colors: */ /* 0x00 = black */ put_dword(fp, 0x000000); /* 0x01 = blue */ put_dword(fp, 0x000080); /* 0x02 = green */ put_dword(fp, 0x008000); /* 0x03 = cyan */ put_dword(fp, 0x008080); /* 0x04 = red */ put_dword(fp, 0x800000); /* 0x05 = magenta */ put_dword(fp, 0x800080); /* 0x06 = brown */ put_dword(fp, 0x808000); /* 0x07 = light gray */ put_dword(fp, 0xC0C0C0); /* 0x08 = dark gray */ put_dword(fp, 0x808080); /* 0x09 = bright blue */ put_dword(fp, 0x0000FF); /* 0x0A = bright green */ put_dword(fp, 0x00FF00); /* 0x0B = bright cyan */ put_dword(fp, 0x00FFFF); /* 0x0C = bright red */ put_dword(fp, 0xFF0000); /* 0x0D = bright magenta */ put_dword(fp, 0xFF00FF); /* 0x0E = yellow */ put_dword(fp, 0xFFFF00); /* 0x0F = white */ put_dword(fp, 0xFFFFFF); /* pixel data bits */ b = 0; for (i = m - 1; i >= 0; i--) { for (j = 0; j < ((n + 7) / 8) * 8; j++) { b <<= 4; b |= (j < n ? map[i * n + j] & 15 : 0); if (j & 1) put_byte(fp, b); } } fflush(fp); if (ferror(fp)) { xprintf("rgr_write_bmp16: write error on `%s' - %s\n", fname, strerror(errno)); ret = 1; } fini: if (fp != NULL) fclose(fp); return ret; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpnet.h0000644000076500000240000000437313524616144025050 0ustar tamasstaff00000000000000/* glpnet.h (graph and network algorithms) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPNET_H #define GLPNET_H #define mc21a _glp_mc21a int mc21a(int n, const int icn[], const int ip[], const int lenr[], int iperm[], int pr[], int arp[], int cv[], int out[]); /* permutations for zero-free diagonal */ #define mc13d _glp_mc13d int mc13d(int n, const int icn[], const int ip[], const int lenr[], int ior[], int ib[], int lowl[], int numb[], int prev[]); /* permutations to block triangular form */ #define okalg _glp_okalg int okalg(int nv, int na, const int tail[], const int head[], const int low[], const int cap[], const int cost[], int x[], int pi[]); /* out-of-kilter algorithm */ #define ffalg _glp_ffalg void ffalg(int nv, int na, const int tail[], const int head[], int s, int t, const int cap[], int x[], char cut[]); /* Ford-Fulkerson algorithm */ #define wclique _glp_wclique int wclique(int n, const int w[], const unsigned char a[], int ind[]); /* find maximum weight clique with Ostergard's algorithm */ #define kellerman _glp_kellerman int kellerman(int n, int (*func)(void *info, int i, int ind[]), void *info, void /* glp_graph */ *H); /* cover edges by cliques with Kellerman's heuristic */ #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpapi10.c0000644000076500000240000002304313524616144025162 0ustar tamasstaff00000000000000/* glpapi10.c (solution checking routines) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glpapi.h" void _glp_check_kkt(glp_prob *P, int sol, int cond, double *_ae_max, int *_ae_ind, double *_re_max, int *_re_ind) { /* check feasibility and optimality conditions */ int m = P->m; int n = P->n; GLPROW *row; GLPCOL *col; GLPAIJ *aij; int i, j, ae_ind, re_ind; double e, sp, sn, t, ae_max, re_max; if (!(sol == GLP_SOL || sol == GLP_IPT || sol == GLP_MIP)) xerror("glp_check_kkt: sol = %d; invalid solution indicator\n", sol); if (!(cond == GLP_KKT_PE || cond == GLP_KKT_PB || cond == GLP_KKT_DE || cond == GLP_KKT_DB || cond == GLP_KKT_CS)) xerror("glp_check_kkt: cond = %d; invalid condition indicator " "\n", cond); ae_max = re_max = 0.0; ae_ind = re_ind = 0; if (cond == GLP_KKT_PE) { /* xR - A * xS = 0 */ for (i = 1; i <= m; i++) { row = P->row[i]; sp = sn = 0.0; /* t := xR[i] */ if (sol == GLP_SOL) t = row->prim; else if (sol == GLP_IPT) t = row->pval; else if (sol == GLP_MIP) t = row->mipx; else xassert(sol != sol); if (t >= 0.0) sp += t; else sn -= t; for (aij = row->ptr; aij != NULL; aij = aij->r_next) { col = aij->col; /* t := - a[i,j] * xS[j] */ if (sol == GLP_SOL) t = - aij->val * col->prim; else if (sol == GLP_IPT) t = - aij->val * col->pval; else if (sol == GLP_MIP) t = - aij->val * col->mipx; else xassert(sol != sol); if (t >= 0.0) sp += t; else sn -= t; } /* absolute error */ e = fabs(sp - sn); if (ae_max < e) ae_max = e, ae_ind = i; /* relative error */ e /= (1.0 + sp + sn); if (re_max < e) re_max = e, re_ind = i; } } else if (cond == GLP_KKT_PB) { /* lR <= xR <= uR */ for (i = 1; i <= m; i++) { row = P->row[i]; /* t := xR[i] */ if (sol == GLP_SOL) t = row->prim; else if (sol == GLP_IPT) t = row->pval; else if (sol == GLP_MIP) t = row->mipx; else xassert(sol != sol); /* check lower bound */ if (row->type == GLP_LO || row->type == GLP_DB || row->type == GLP_FX) { if (t < row->lb) { /* absolute error */ e = row->lb - t; if (ae_max < e) ae_max = e, ae_ind = i; /* relative error */ e /= (1.0 + fabs(row->lb)); if (re_max < e) re_max = e, re_ind = i; } } /* check upper bound */ if (row->type == GLP_UP || row->type == GLP_DB || row->type == GLP_FX) { if (t > row->ub) { /* absolute error */ e = t - row->ub; if (ae_max < e) ae_max = e, ae_ind = i; /* relative error */ e /= (1.0 + fabs(row->ub)); if (re_max < e) re_max = e, re_ind = i; } } } /* lS <= xS <= uS */ for (j = 1; j <= n; j++) { col = P->col[j]; /* t := xS[j] */ if (sol == GLP_SOL) t = col->prim; else if (sol == GLP_IPT) t = col->pval; else if (sol == GLP_MIP) t = col->mipx; else xassert(sol != sol); /* check lower bound */ if (col->type == GLP_LO || col->type == GLP_DB || col->type == GLP_FX) { if (t < col->lb) { /* absolute error */ e = col->lb - t; if (ae_max < e) ae_max = e, ae_ind = m+j; /* relative error */ e /= (1.0 + fabs(col->lb)); if (re_max < e) re_max = e, re_ind = m+j; } } /* check upper bound */ if (col->type == GLP_UP || col->type == GLP_DB || col->type == GLP_FX) { if (t > col->ub) { /* absolute error */ e = t - col->ub; if (ae_max < e) ae_max = e, ae_ind = m+j; /* relative error */ e /= (1.0 + fabs(col->ub)); if (re_max < e) re_max = e, re_ind = m+j; } } } } else if (cond == GLP_KKT_DE) { /* A' * (lambdaR - cR) + (lambdaS - cS) = 0 */ for (j = 1; j <= n; j++) { col = P->col[j]; sp = sn = 0.0; /* t := lambdaS[j] - cS[j] */ if (sol == GLP_SOL) t = col->dual - col->coef; else if (sol == GLP_IPT) t = col->dval - col->coef; else xassert(sol != sol); if (t >= 0.0) sp += t; else sn -= t; for (aij = col->ptr; aij != NULL; aij = aij->c_next) { row = aij->row; /* t := a[i,j] * (lambdaR[i] - cR[i]) */ if (sol == GLP_SOL) t = aij->val * row->dual; else if (sol == GLP_IPT) t = aij->val * row->dval; else xassert(sol != sol); if (t >= 0.0) sp += t; else sn -= t; } /* absolute error */ e = fabs(sp - sn); if (ae_max < e) ae_max = e, ae_ind = m+j; /* relative error */ e /= (1.0 + sp + sn); if (re_max < e) re_max = e, re_ind = m+j; } } else if (cond == GLP_KKT_DB) { /* check lambdaR */ for (i = 1; i <= m; i++) { row = P->row[i]; /* t := lambdaR[i] */ if (sol == GLP_SOL) t = row->dual; else if (sol == GLP_IPT) t = row->dval; else xassert(sol != sol); /* correct sign */ if (P->dir == GLP_MIN) t = + t; else if (P->dir == GLP_MAX) t = - t; else xassert(P != P); /* check for positivity */ if (row->type == GLP_FR || row->type == GLP_LO) { if (t < 0.0) { e = - t; if (ae_max < e) ae_max = re_max = e, ae_ind = re_ind = i; } } /* check for negativity */ if (row->type == GLP_FR || row->type == GLP_UP) { if (t > 0.0) { e = + t; if (ae_max < e) ae_max = re_max = e, ae_ind = re_ind = i; } } } /* check lambdaS */ for (j = 1; j <= n; j++) { col = P->col[j]; /* t := lambdaS[j] */ if (sol == GLP_SOL) t = col->dual; else if (sol == GLP_IPT) t = col->dval; else xassert(sol != sol); /* correct sign */ if (P->dir == GLP_MIN) t = + t; else if (P->dir == GLP_MAX) t = - t; else xassert(P != P); /* check for positivity */ if (col->type == GLP_FR || col->type == GLP_LO) { if (t < 0.0) { e = - t; if (ae_max < e) ae_max = re_max = e, ae_ind = re_ind = m+j; } } /* check for negativity */ if (col->type == GLP_FR || col->type == GLP_UP) { if (t > 0.0) { e = + t; if (ae_max < e) ae_max = re_max = e, ae_ind = re_ind = m+j; } } } } else xassert(cond != cond); if (_ae_max != NULL) *_ae_max = ae_max; if (_ae_ind != NULL) *_ae_ind = ae_ind; if (_re_max != NULL) *_re_max = re_max; if (_re_ind != NULL) *_re_ind = re_ind; return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpmat.h0000644000076500000240000001646013524616144025043 0ustar tamasstaff00000000000000/* glpmat.h (linear algebra routines) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPMAT_H #define GLPMAT_H /*********************************************************************** * FULL-VECTOR STORAGE * * For a sparse vector x having n elements, ne of which are non-zero, * the full-vector storage format uses two arrays x_ind and x_vec, which * are set up as follows: * * x_ind is an integer array of length [1+ne]. Location x_ind[0] is * not used, and locations x_ind[1], ..., x_ind[ne] contain indices of * non-zero elements in vector x. * * x_vec is a floating-point array of length [1+n]. Location x_vec[0] * is not used, and locations x_vec[1], ..., x_vec[n] contain numeric * values of ALL elements in vector x, including its zero elements. * * Let, for example, the following sparse vector x be given: * * (0, 1, 0, 0, 2, 3, 0, 4) * * Then the arrays are: * * x_ind = { X; 2, 5, 6, 8 } * * x_vec = { X; 0, 1, 0, 0, 2, 3, 0, 4 } * * COMPRESSED-VECTOR STORAGE * * For a sparse vector x having n elements, ne of which are non-zero, * the compressed-vector storage format uses two arrays x_ind and x_vec, * which are set up as follows: * * x_ind is an integer array of length [1+ne]. Location x_ind[0] is * not used, and locations x_ind[1], ..., x_ind[ne] contain indices of * non-zero elements in vector x. * * x_vec is a floating-point array of length [1+ne]. Location x_vec[0] * is not used, and locations x_vec[1], ..., x_vec[ne] contain numeric * values of corresponding non-zero elements in vector x. * * Let, for example, the following sparse vector x be given: * * (0, 1, 0, 0, 2, 3, 0, 4) * * Then the arrays are: * * x_ind = { X; 2, 5, 6, 8 } * * x_vec = { X; 1, 2, 3, 4 } * * STORAGE-BY-ROWS * * For a sparse matrix A, which has m rows, n columns, and ne non-zero * elements the storage-by-rows format uses three arrays A_ptr, A_ind, * and A_val, which are set up as follows: * * A_ptr is an integer array of length [1+m+1] also called "row pointer * array". It contains the relative starting positions of each row of A * in the arrays A_ind and A_val, i.e. element A_ptr[i], 1 <= i <= m, * indicates where row i begins in the arrays A_ind and A_val. If all * elements in row i are zero, then A_ptr[i] = A_ptr[i+1]. Location * A_ptr[0] is not used, location A_ptr[1] must contain 1, and location * A_ptr[m+1] must contain ne+1 that indicates the position after the * last element in the arrays A_ind and A_val. * * A_ind is an integer array of length [1+ne]. Location A_ind[0] is not * used, and locations A_ind[1], ..., A_ind[ne] contain column indices * of (non-zero) elements in matrix A. * * A_val is a floating-point array of length [1+ne]. Location A_val[0] * is not used, and locations A_val[1], ..., A_val[ne] contain numeric * values of non-zero elements in matrix A. * * Non-zero elements of matrix A are stored contiguously, and the rows * of matrix A are stored consecutively from 1 to m in the arrays A_ind * and A_val. The elements in each row of A may be stored in any order * in A_ind and A_val. Note that elements with duplicate column indices * are not allowed. * * Let, for example, the following sparse matrix A be given: * * | 11 . 13 . . . | * | 21 22 . 24 . . | * | . 32 33 . . . | * | . . 43 44 . 46 | * | . . . . . . | * | 61 62 . . . 66 | * * Then the arrays are: * * A_ptr = { X; 1, 3, 6, 8, 11, 11; 14 } * * A_ind = { X; 1, 3; 4, 2, 1; 2, 3; 4, 3, 6; 1, 2, 6 } * * A_val = { X; 11, 13; 24, 22, 21; 32, 33; 44, 43, 46; 61, 62, 66 } * * PERMUTATION MATRICES * * Let P be a permutation matrix of the order n. It is represented as * an integer array P_per of length [1+n+n] as follows: if p[i,j] = 1, * then P_per[i] = j and P_per[n+j] = i. Location P_per[0] is not used. * * Let A' = P*A. If i-th row of A corresponds to i'-th row of A', then * P_per[i'] = i and P_per[n+i] = i'. * * References: * * 1. Gustavson F.G. Some basic techniques for solving sparse systems of * linear equations. In Rose and Willoughby (1972), pp. 41-52. * * 2. Basic Linear Algebra Subprograms Technical (BLAST) Forum Standard. * University of Tennessee (2001). */ #define check_fvs _glp_mat_check_fvs int check_fvs(int n, int nnz, int ind[], double vec[]); /* check sparse vector in full-vector storage format */ #define check_pattern _glp_mat_check_pattern int check_pattern(int m, int n, int A_ptr[], int A_ind[]); /* check pattern of sparse matrix */ #define transpose _glp_mat_transpose void transpose(int m, int n, int A_ptr[], int A_ind[], double A_val[], int AT_ptr[], int AT_ind[], double AT_val[]); /* transpose sparse matrix */ #define adat_symbolic _glp_mat_adat_symbolic int *adat_symbolic(int m, int n, int P_per[], int A_ptr[], int A_ind[], int S_ptr[]); /* compute S = P*A*D*A'*P' (symbolic phase) */ #define adat_numeric _glp_mat_adat_numeric void adat_numeric(int m, int n, int P_per[], int A_ptr[], int A_ind[], double A_val[], double D_diag[], int S_ptr[], int S_ind[], double S_val[], double S_diag[]); /* compute S = P*A*D*A'*P' (numeric phase) */ #define min_degree _glp_mat_min_degree void min_degree(int n, int A_ptr[], int A_ind[], int P_per[]); /* minimum degree ordering */ #define amd_order1 _glp_mat_amd_order1 void amd_order1(int n, int A_ptr[], int A_ind[], int P_per[]); /* approximate minimum degree ordering (AMD) */ #define symamd_ord _glp_mat_symamd_ord void symamd_ord(int n, int A_ptr[], int A_ind[], int P_per[]); /* approximate minimum degree ordering (SYMAMD) */ #define chol_symbolic _glp_mat_chol_symbolic int *chol_symbolic(int n, int A_ptr[], int A_ind[], int U_ptr[]); /* compute Cholesky factorization (symbolic phase) */ #define chol_numeric _glp_mat_chol_numeric int chol_numeric(int n, int A_ptr[], int A_ind[], double A_val[], double A_diag[], int U_ptr[], int U_ind[], double U_val[], double U_diag[]); /* compute Cholesky factorization (numeric phase) */ #define u_solve _glp_mat_u_solve void u_solve(int n, int U_ptr[], int U_ind[], double U_val[], double U_diag[], double x[]); /* solve upper triangular system U*x = b */ #define ut_solve _glp_mat_ut_solve void ut_solve(int n, int U_ptr[], int U_ind[], double U_val[], double U_diag[], double x[]); /* solve lower triangular system U'*x = b */ #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpnet07.c0000644000076500000240000001653413524616144025214 0ustar tamasstaff00000000000000/* glpnet07.c (Ford-Fulkerson algorithm) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glpenv.h" #include "glpnet.h" /*********************************************************************** * NAME * * ffalg - Ford-Fulkerson algorithm * * SYNOPSIS * * #include "glpnet.h" * void ffalg(int nv, int na, const int tail[], const int head[], * int s, int t, const int cap[], int x[], char cut[]); * * DESCRIPTION * * The routine ffalg implements the Ford-Fulkerson algorithm to find a * maximal flow in the specified flow network. * * INPUT PARAMETERS * * nv is the number of nodes, nv >= 2. * * na is the number of arcs, na >= 0. * * tail[a], a = 1,...,na, is the index of tail node of arc a. * * head[a], a = 1,...,na, is the index of head node of arc a. * * s is the source node index, 1 <= s <= nv. * * t is the sink node index, 1 <= t <= nv, t != s. * * cap[a], a = 1,...,na, is the capacity of arc a, cap[a] >= 0. * * NOTE: Multiple arcs are allowed, but self-loops are not allowed. * * OUTPUT PARAMETERS * * x[a], a = 1,...,na, is optimal value of the flow through arc a. * * cut[i], i = 1,...,nv, is 1 if node i is labelled, and 0 otherwise. * The set of arcs, whose one endpoint is labelled and other is not, * defines the minimal cut corresponding to the maximal flow found. * If the parameter cut is NULL, the cut information are not stored. * * REFERENCES * * L.R.Ford, Jr., and D.R.Fulkerson, "Flows in Networks," The RAND * Corp., Report R-375-PR (August 1962), Chap. I "Static Maximal Flow," * pp.30-33. */ void ffalg(int nv, int na, const int tail[], const int head[], int s, int t, const int cap[], int x[], char cut[]) { int a, delta, i, j, k, pos1, pos2, temp, *ptr, *arc, *link, *list; /* sanity checks */ xassert(nv >= 2); xassert(na >= 0); xassert(1 <= s && s <= nv); xassert(1 <= t && t <= nv); xassert(s != t); for (a = 1; a <= na; a++) { i = tail[a], j = head[a]; xassert(1 <= i && i <= nv); xassert(1 <= j && j <= nv); xassert(i != j); xassert(cap[a] >= 0); } /* allocate working arrays */ ptr = xcalloc(1+nv+1, sizeof(int)); arc = xcalloc(1+na+na, sizeof(int)); link = xcalloc(1+nv, sizeof(int)); list = xcalloc(1+nv, sizeof(int)); /* ptr[i] := (degree of node i) */ for (i = 1; i <= nv; i++) ptr[i] = 0; for (a = 1; a <= na; a++) { ptr[tail[a]]++; ptr[head[a]]++; } /* initialize arc pointers */ ptr[1]++; for (i = 1; i < nv; i++) ptr[i+1] += ptr[i]; ptr[nv+1] = ptr[nv]; /* build arc lists */ for (a = 1; a <= na; a++) { arc[--ptr[tail[a]]] = a; arc[--ptr[head[a]]] = a; } xassert(ptr[1] == 1); xassert(ptr[nv+1] == na+na+1); /* now the indices of arcs incident to node i are stored in locations arc[ptr[i]], arc[ptr[i]+1], ..., arc[ptr[i+1]-1] */ /* initialize arc flows */ for (a = 1; a <= na; a++) x[a] = 0; loop: /* main loop starts here */ /* build augmenting tree rooted at s */ /* link[i] = 0 means that node i is not labelled yet; link[i] = a means that arc a immediately precedes node i */ /* initially node s is labelled as the root */ for (i = 1; i <= nv; i++) link[i] = 0; link[s] = -1, list[1] = s, pos1 = pos2 = 1; /* breadth first search */ while (pos1 <= pos2) { /* dequeue node i */ i = list[pos1++]; /* consider all arcs incident to node i */ for (k = ptr[i]; k < ptr[i+1]; k++) { a = arc[k]; if (tail[a] == i) { /* a = i->j is a forward arc from s to t */ j = head[a]; /* if node j has been labelled, skip the arc */ if (link[j] != 0) continue; /* if the arc does not allow increasing the flow through it, skip the arc */ if (x[a] == cap[a]) continue; } else if (head[a] == i) { /* a = i<-j is a backward arc from s to t */ j = tail[a]; /* if node j has been labelled, skip the arc */ if (link[j] != 0) continue; /* if the arc does not allow decreasing the flow through it, skip the arc */ if (x[a] == 0) continue; } else xassert(a != a); /* label node j and enqueue it */ link[j] = a, list[++pos2] = j; /* check for breakthrough */ if (j == t) goto brkt; } } /* NONBREAKTHROUGH */ /* no augmenting path exists; current flow is maximal */ /* store minimal cut information, if necessary */ if (cut != NULL) { for (i = 1; i <= nv; i++) cut[i] = (char)(link[i] != 0); } goto done; brkt: /* BREAKTHROUGH */ /* walk through arcs of the augmenting path (s, ..., t) found in the reverse order and determine maximal change of the flow */ delta = 0; for (j = t; j != s; j = i) { /* arc a immediately precedes node j in the path */ a = link[j]; if (head[a] == j) { /* a = i->j is a forward arc of the cycle */ i = tail[a]; /* x[a] may be increased until its upper bound */ temp = cap[a] - x[a]; } else if (tail[a] == j) { /* a = i<-j is a backward arc of the cycle */ i = head[a]; /* x[a] may be decreased until its lower bound */ temp = x[a]; } else xassert(a != a); if (delta == 0 || delta > temp) delta = temp; } xassert(delta > 0); /* increase the flow along the path */ for (j = t; j != s; j = i) { /* arc a immediately precedes node j in the path */ a = link[j]; if (head[a] == j) { /* a = i->j is a forward arc of the cycle */ i = tail[a]; x[a] += delta; } else if (tail[a] == j) { /* a = i<-j is a backward arc of the cycle */ i = head[a]; x[a] -= delta; } else xassert(a != a); } goto loop; done: /* free working arrays */ xfree(ptr); xfree(arc); xfree(link); xfree(list); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpios03.c0000644000076500000240000012453213524616144025212 0ustar tamasstaff00000000000000/* glpios03.c (branch-and-cut driver) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wsometimes-uninitialized" #pragma clang diagnostic ignored "-Wlogical-op-parentheses" #endif #include "glpios.h" /*********************************************************************** * show_progress - display current progress of the search * * This routine displays some information about current progress of the * search. * * The information includes: * * the current number of iterations performed by the simplex solver; * * the objective value for the best known integer feasible solution, * which is upper (minimization) or lower (maximization) global bound * for optimal solution of the original mip problem; * * the best local bound for active nodes, which is lower (minimization) * or upper (maximization) global bound for optimal solution of the * original mip problem; * * the relative mip gap, in percents; * * the number of open (active) subproblems; * * the number of completely explored subproblems, i.e. whose nodes have * been removed from the tree. */ static void show_progress(glp_tree *T, int bingo) { int p; double temp; char best_mip[50], best_bound[50], *rho, rel_gap[50]; /* format the best known integer feasible solution */ if (T->mip->mip_stat == GLP_FEAS) sprintf(best_mip, "%17.9e", T->mip->mip_obj); else sprintf(best_mip, "%17s", "not found yet"); /* determine reference number of an active subproblem whose local bound is best */ p = ios_best_node(T); /* format the best bound */ if (p == 0) sprintf(best_bound, "%17s", "tree is empty"); else { temp = T->slot[p].node->bound; if (temp == -DBL_MAX) sprintf(best_bound, "%17s", "-inf"); else if (temp == +DBL_MAX) sprintf(best_bound, "%17s", "+inf"); else sprintf(best_bound, "%17.9e", temp); } /* choose the relation sign between global bounds */ if (T->mip->dir == GLP_MIN) rho = ">="; else if (T->mip->dir == GLP_MAX) rho = "<="; else xassert(T != T); /* format the relative mip gap */ temp = ios_relative_gap(T); if (temp == 0.0) sprintf(rel_gap, " 0.0%%"); else if (temp < 0.001) sprintf(rel_gap, "< 0.1%%"); else if (temp <= 9.999) sprintf(rel_gap, "%5.1f%%", 100.0 * temp); else sprintf(rel_gap, "%6s", ""); /* display progress of the search */ xprintf("+%6d: %s %s %s %s %s (%d; %d)\n", T->mip->it_cnt, bingo ? ">>>>>" : "mip =", best_mip, rho, best_bound, rel_gap, T->a_cnt, T->t_cnt - T->n_cnt); T->tm_lag = xtime(); return; } /*********************************************************************** * is_branch_hopeful - check if specified branch is hopeful * * This routine checks if the specified subproblem can have an integer * optimal solution which is better than the best known one. * * The check is based on comparison of the local objective bound stored * in the subproblem descriptor and the incumbent objective value which * is the global objective bound. * * If there is a chance that the specified subproblem can have a better * integer optimal solution, the routine returns non-zero. Otherwise, if * the corresponding branch can pruned, zero is returned. */ static int is_branch_hopeful(glp_tree *T, int p) { xassert(1 <= p && p <= T->nslots); xassert(T->slot[p].node != NULL); return ios_is_hopeful(T, T->slot[p].node->bound); } /*********************************************************************** * check_integrality - check integrality of basic solution * * This routine checks if the basic solution of LP relaxation of the * current subproblem satisfies to integrality conditions, i.e. that all * variables of integer kind have integral primal values. (The solution * is assumed to be optimal.) * * For each variable of integer kind the routine computes the following * quantity: * * ii(x[j]) = min(x[j] - floor(x[j]), ceil(x[j]) - x[j]), (1) * * which is a measure of the integer infeasibility (non-integrality) of * x[j] (for example, ii(2.1) = 0.1, ii(3.7) = 0.3, ii(5.0) = 0). It is * understood that 0 <= ii(x[j]) <= 0.5, and variable x[j] is integer * feasible if ii(x[j]) = 0. However, due to floating-point arithmetic * the routine checks less restrictive condition: * * ii(x[j]) <= tol_int, (2) * * where tol_int is a given tolerance (small positive number) and marks * each variable which does not satisfy to (2) as integer infeasible by * setting its fractionality flag. * * In order to characterize integer infeasibility of the basic solution * in the whole the routine computes two parameters: ii_cnt, which is * the number of variables with the fractionality flag set, and ii_sum, * which is the sum of integer infeasibilities (1). */ static void check_integrality(glp_tree *T) { glp_prob *mip = T->mip; int j, type, ii_cnt = 0; double lb, ub, x, temp1, temp2, ii_sum = 0.0; /* walk through the set of columns (structural variables) */ for (j = 1; j <= mip->n; j++) { GLPCOL *col = mip->col[j]; T->non_int[j] = 0; /* if the column is not integer, skip it */ if (col->kind != GLP_IV) continue; /* if the column is non-basic, it is integer feasible */ if (col->stat != GLP_BS) continue; /* obtain the type and bounds of the column */ type = col->type, lb = col->lb, ub = col->ub; /* obtain value of the column in optimal basic solution */ x = col->prim; /* if the column's primal value is close to the lower bound, the column is integer feasible within given tolerance */ if (type == GLP_LO || type == GLP_DB || type == GLP_FX) { temp1 = lb - T->parm->tol_int; temp2 = lb + T->parm->tol_int; if (temp1 <= x && x <= temp2) continue; #if 0 /* the lower bound must not be violated */ xassert(x >= lb); #else if (x < lb) continue; #endif } /* if the column's primal value is close to the upper bound, the column is integer feasible within given tolerance */ if (type == GLP_UP || type == GLP_DB || type == GLP_FX) { temp1 = ub - T->parm->tol_int; temp2 = ub + T->parm->tol_int; if (temp1 <= x && x <= temp2) continue; #if 0 /* the upper bound must not be violated */ xassert(x <= ub); #else if (x > ub) continue; #endif } /* if the column's primal value is close to nearest integer, the column is integer feasible within given tolerance */ temp1 = floor(x + 0.5) - T->parm->tol_int; temp2 = floor(x + 0.5) + T->parm->tol_int; if (temp1 <= x && x <= temp2) continue; /* otherwise the column is integer infeasible */ T->non_int[j] = 1; /* increase the number of fractional-valued columns */ ii_cnt++; /* compute the sum of integer infeasibilities */ temp1 = x - floor(x); temp2 = ceil(x) - x; xassert(temp1 > 0.0 && temp2 > 0.0); ii_sum += (temp1 <= temp2 ? temp1 : temp2); } /* store ii_cnt and ii_sum to the current problem descriptor */ xassert(T->curr != NULL); T->curr->ii_cnt = ii_cnt; T->curr->ii_sum = ii_sum; /* and also display these parameters */ if (T->parm->msg_lev >= GLP_MSG_DBG) { if (ii_cnt == 0) xprintf("There are no fractional columns\n"); else if (ii_cnt == 1) xprintf("There is one fractional column, integer infeasibil" "ity is %.3e\n", ii_sum); else xprintf("There are %d fractional columns, integer infeasibi" "lity is %.3e\n", ii_cnt, ii_sum); } return; } /*********************************************************************** * record_solution - record better integer feasible solution * * This routine records optimal basic solution of LP relaxation of the * current subproblem, which being integer feasible is better than the * best known integer feasible solution. */ static void record_solution(glp_tree *T) { glp_prob *mip = T->mip; int i, j; mip->mip_stat = GLP_FEAS; mip->mip_obj = mip->obj_val; for (i = 1; i <= mip->m; i++) { GLPROW *row = mip->row[i]; row->mipx = row->prim; } for (j = 1; j <= mip->n; j++) { GLPCOL *col = mip->col[j]; if (col->kind == GLP_CV) col->mipx = col->prim; else if (col->kind == GLP_IV) { /* value of the integer column must be integral */ col->mipx = floor(col->prim + 0.5); } else xassert(col != col); } T->sol_cnt++; return; } /*********************************************************************** * fix_by_red_cost - fix non-basic integer columns by reduced costs * * This routine fixes some non-basic integer columns if their reduced * costs indicate that increasing (decreasing) the column at least by * one involves the objective value becoming worse than the incumbent * objective value. */ static void fix_by_red_cost(glp_tree *T) { glp_prob *mip = T->mip; int j, stat, fixed = 0; double obj, lb, ub, dj; /* the global bound must exist */ xassert(T->mip->mip_stat == GLP_FEAS); /* basic solution of LP relaxation must be optimal */ xassert(mip->pbs_stat == GLP_FEAS && mip->dbs_stat == GLP_FEAS); /* determine the objective function value */ obj = mip->obj_val; /* walk through the column list */ for (j = 1; j <= mip->n; j++) { GLPCOL *col = mip->col[j]; /* if the column is not integer, skip it */ if (col->kind != GLP_IV) continue; /* obtain bounds of j-th column */ lb = col->lb, ub = col->ub; /* and determine its status and reduced cost */ stat = col->stat, dj = col->dual; /* analyze the reduced cost */ switch (mip->dir) { case GLP_MIN: /* minimization */ if (stat == GLP_NL) { /* j-th column is non-basic on its lower bound */ if (dj < 0.0) dj = 0.0; if (obj + dj >= mip->mip_obj) glp_set_col_bnds(mip, j, GLP_FX, lb, lb), fixed++; } else if (stat == GLP_NU) { /* j-th column is non-basic on its upper bound */ if (dj > 0.0) dj = 0.0; if (obj - dj >= mip->mip_obj) glp_set_col_bnds(mip, j, GLP_FX, ub, ub), fixed++; } break; case GLP_MAX: /* maximization */ if (stat == GLP_NL) { /* j-th column is non-basic on its lower bound */ if (dj > 0.0) dj = 0.0; if (obj + dj <= mip->mip_obj) glp_set_col_bnds(mip, j, GLP_FX, lb, lb), fixed++; } else if (stat == GLP_NU) { /* j-th column is non-basic on its upper bound */ if (dj < 0.0) dj = 0.0; if (obj - dj <= mip->mip_obj) glp_set_col_bnds(mip, j, GLP_FX, ub, ub), fixed++; } break; default: xassert(T != T); } } if (T->parm->msg_lev >= GLP_MSG_DBG) { if (fixed == 0) /* nothing to say */; else if (fixed == 1) xprintf("One column has been fixed by reduced cost\n"); else xprintf("%d columns have been fixed by reduced costs\n", fixed); } /* fixing non-basic columns on their current bounds does not change the basic solution */ xassert(mip->pbs_stat == GLP_FEAS && mip->dbs_stat == GLP_FEAS); return; } /*********************************************************************** * branch_on - perform branching on specified variable * * This routine performs branching on j-th column (structural variable) * of the current subproblem. The specified column must be of integer * kind and must have a fractional value in optimal basic solution of * LP relaxation of the current subproblem (i.e. only columns for which * the flag non_int[j] is set are valid candidates to branch on). * * Let x be j-th structural variable, and beta be its primal fractional * value in the current basic solution. Branching on j-th variable is * dividing the current subproblem into two new subproblems, which are * identical to the current subproblem with the following exception: in * the first subproblem that begins the down-branch x has a new upper * bound x <= floor(beta), and in the second subproblem that begins the * up-branch x has a new lower bound x >= ceil(beta). * * Depending on estimation of local bounds for down- and up-branches * this routine returns the following: * * 0 - both branches have been created; * 1 - one branch is hopeless and has been pruned, so now the current * subproblem is other branch; * 2 - both branches are hopeless and have been pruned; new subproblem * selection is needed to continue the search. */ static int branch_on(glp_tree *T, int j, int next) { glp_prob *mip = T->mip; IOSNPD *node; int m = mip->m; int n = mip->n; int type, dn_type, up_type, dn_bad, up_bad, p, ret, clone[1+2]; double lb, ub, beta, new_ub, new_lb, dn_lp, up_lp, dn_bnd, up_bnd; /* determine bounds and value of x[j] in optimal solution to LP relaxation of the current subproblem */ xassert(1 <= j && j <= n); type = mip->col[j]->type; lb = mip->col[j]->lb; ub = mip->col[j]->ub; beta = mip->col[j]->prim; /* determine new bounds of x[j] for down- and up-branches */ new_ub = floor(beta); new_lb = ceil(beta); switch (type) { case GLP_FR: dn_type = GLP_UP; up_type = GLP_LO; break; case GLP_LO: xassert(lb <= new_ub); dn_type = (lb == new_ub ? GLP_FX : GLP_DB); xassert(lb + 1.0 <= new_lb); up_type = GLP_LO; break; case GLP_UP: xassert(new_ub <= ub - 1.0); dn_type = GLP_UP; xassert(new_lb <= ub); up_type = (new_lb == ub ? GLP_FX : GLP_DB); break; case GLP_DB: xassert(lb <= new_ub && new_ub <= ub - 1.0); dn_type = (lb == new_ub ? GLP_FX : GLP_DB); xassert(lb + 1.0 <= new_lb && new_lb <= ub); up_type = (new_lb == ub ? GLP_FX : GLP_DB); break; default: xassert(type != type); } /* compute local bounds to LP relaxation for both branches */ ios_eval_degrad(T, j, &dn_lp, &up_lp); /* and improve them by rounding */ dn_bnd = ios_round_bound(T, dn_lp); up_bnd = ios_round_bound(T, up_lp); /* check local bounds for down- and up-branches */ dn_bad = !ios_is_hopeful(T, dn_bnd); up_bad = !ios_is_hopeful(T, up_bnd); if (dn_bad && up_bad) { if (T->parm->msg_lev >= GLP_MSG_DBG) xprintf("Both down- and up-branches are hopeless\n"); ret = 2; goto done; } else if (up_bad) { if (T->parm->msg_lev >= GLP_MSG_DBG) xprintf("Up-branch is hopeless\n"); glp_set_col_bnds(mip, j, dn_type, lb, new_ub); T->curr->lp_obj = dn_lp; if (mip->dir == GLP_MIN) { if (T->curr->bound < dn_bnd) T->curr->bound = dn_bnd; } else if (mip->dir == GLP_MAX) { if (T->curr->bound > dn_bnd) T->curr->bound = dn_bnd; } else xassert(mip != mip); ret = 1; goto done; } else if (dn_bad) { if (T->parm->msg_lev >= GLP_MSG_DBG) xprintf("Down-branch is hopeless\n"); glp_set_col_bnds(mip, j, up_type, new_lb, ub); T->curr->lp_obj = up_lp; if (mip->dir == GLP_MIN) { if (T->curr->bound < up_bnd) T->curr->bound = up_bnd; } else if (mip->dir == GLP_MAX) { if (T->curr->bound > up_bnd) T->curr->bound = up_bnd; } else xassert(mip != mip); ret = 1; goto done; } /* both down- and up-branches seem to be hopeful */ if (T->parm->msg_lev >= GLP_MSG_DBG) xprintf("Branching on column %d, primal value is %.9e\n", j, beta); /* determine the reference number of the current subproblem */ xassert(T->curr != NULL); p = T->curr->p; T->curr->br_var = j; T->curr->br_val = beta; /* freeze the current subproblem */ ios_freeze_node(T); /* create two clones of the current subproblem; the first clone begins the down-branch, the second one begins the up-branch */ ios_clone_node(T, p, 2, clone); if (T->parm->msg_lev >= GLP_MSG_DBG) xprintf("Node %d begins down branch, node %d begins up branch " "\n", clone[1], clone[2]); /* set new upper bound of j-th column in the down-branch */ node = T->slot[clone[1]].node; xassert(node != NULL); xassert(node->up != NULL); xassert(node->b_ptr == NULL); node->b_ptr = dmp_get_atom(T->pool, sizeof(IOSBND)); node->b_ptr->k = m + j; node->b_ptr->type = (unsigned char)dn_type; node->b_ptr->lb = lb; node->b_ptr->ub = new_ub; node->b_ptr->next = NULL; node->lp_obj = dn_lp; if (mip->dir == GLP_MIN) { if (node->bound < dn_bnd) node->bound = dn_bnd; } else if (mip->dir == GLP_MAX) { if (node->bound > dn_bnd) node->bound = dn_bnd; } else xassert(mip != mip); /* set new lower bound of j-th column in the up-branch */ node = T->slot[clone[2]].node; xassert(node != NULL); xassert(node->up != NULL); xassert(node->b_ptr == NULL); node->b_ptr = dmp_get_atom(T->pool, sizeof(IOSBND)); node->b_ptr->k = m + j; node->b_ptr->type = (unsigned char)up_type; node->b_ptr->lb = new_lb; node->b_ptr->ub = ub; node->b_ptr->next = NULL; node->lp_obj = up_lp; if (mip->dir == GLP_MIN) { if (node->bound < up_bnd) node->bound = up_bnd; } else if (mip->dir == GLP_MAX) { if (node->bound > up_bnd) node->bound = up_bnd; } else xassert(mip != mip); /* suggest the subproblem to be solved next */ xassert(T->child == 0); if (next == GLP_NO_BRNCH) T->child = 0; else if (next == GLP_DN_BRNCH) T->child = clone[1]; else if (next == GLP_UP_BRNCH) T->child = clone[2]; else xassert(next != next); ret = 0; done: return ret; } /*********************************************************************** * cleanup_the_tree - prune hopeless branches from the tree * * This routine walks through the active list and checks the local * bound for every active subproblem. If the local bound indicates that * the subproblem cannot have integer optimal solution better than the * incumbent objective value, the routine deletes such subproblem that, * in turn, involves pruning the corresponding branch of the tree. */ static void cleanup_the_tree(glp_tree *T) { IOSNPD *node, *next_node; int count = 0; /* the global bound must exist */ xassert(T->mip->mip_stat == GLP_FEAS); /* walk through the list of active subproblems */ for (node = T->head; node != NULL; node = next_node) { /* deleting some active problem node may involve deleting its parents recursively; however, all its parents being created *before* it are always *precede* it in the node list, so the next problem node is never affected by such deletion */ next_node = node->next; /* if the branch is hopeless, prune it */ if (!is_branch_hopeful(T, node->p)) ios_delete_node(T, node->p), count++; } if (T->parm->msg_lev >= GLP_MSG_DBG) { if (count == 1) xprintf("One hopeless branch has been pruned\n"); else if (count > 1) xprintf("%d hopeless branches have been pruned\n", count); } return; } /**********************************************************************/ static void generate_cuts(glp_tree *T) { /* generate generic cuts with built-in generators */ if (!(T->parm->mir_cuts == GLP_ON || T->parm->gmi_cuts == GLP_ON || T->parm->cov_cuts == GLP_ON || T->parm->clq_cuts == GLP_ON)) goto done; #if 1 /* 20/IX-2008 */ { int i, max_cuts, added_cuts; max_cuts = T->n; if (max_cuts < 1000) max_cuts = 1000; added_cuts = 0; for (i = T->orig_m+1; i <= T->mip->m; i++) { if (T->mip->row[i]->origin == GLP_RF_CUT) added_cuts++; } /* xprintf("added_cuts = %d\n", added_cuts); */ if (added_cuts >= max_cuts) goto done; } #endif /* generate and add to POOL all cuts violated by x* */ if (T->parm->gmi_cuts == GLP_ON) { if (T->curr->changed < 5) ios_gmi_gen(T); } if (T->parm->mir_cuts == GLP_ON) { xassert(T->mir_gen != NULL); ios_mir_gen(T, T->mir_gen); } if (T->parm->cov_cuts == GLP_ON) { /* cover cuts works well along with mir cuts */ /*if (T->round <= 5)*/ ios_cov_gen(T); } if (T->parm->clq_cuts == GLP_ON) { if (T->clq_gen != NULL) { if (T->curr->level == 0 && T->curr->changed < 50 || T->curr->level > 0 && T->curr->changed < 5) ios_clq_gen(T, T->clq_gen); } } done: return; } /**********************************************************************/ static void remove_cuts(glp_tree *T) { /* remove inactive cuts (some valueable globally valid cut might be saved in the global cut pool) */ int i, cnt = 0, *num = NULL; xassert(T->curr != NULL); for (i = T->orig_m+1; i <= T->mip->m; i++) { if (T->mip->row[i]->origin == GLP_RF_CUT && T->mip->row[i]->level == T->curr->level && T->mip->row[i]->stat == GLP_BS) { if (num == NULL) num = xcalloc(1+T->mip->m, sizeof(int)); num[++cnt] = i; } } if (cnt > 0) { glp_del_rows(T->mip, cnt, num); #if 0 xprintf("%d inactive cut(s) removed\n", cnt); #endif xfree(num); xassert(glp_factorize(T->mip) == 0); } return; } /**********************************************************************/ static void display_cut_info(glp_tree *T) { glp_prob *mip = T->mip; int i, gmi = 0, mir = 0, cov = 0, clq = 0, app = 0; for (i = mip->m; i > 0; i--) { GLPROW *row; row = mip->row[i]; /* if (row->level < T->curr->level) break; */ if (row->origin == GLP_RF_CUT) { if (row->klass == GLP_RF_GMI) gmi++; else if (row->klass == GLP_RF_MIR) mir++; else if (row->klass == GLP_RF_COV) cov++; else if (row->klass == GLP_RF_CLQ) clq++; else app++; } } xassert(T->curr != NULL); if (gmi + mir + cov + clq + app > 0) { xprintf("Cuts on level %d:", T->curr->level); if (gmi > 0) xprintf(" gmi = %d;", gmi); if (mir > 0) xprintf(" mir = %d;", mir); if (cov > 0) xprintf(" cov = %d;", cov); if (clq > 0) xprintf(" clq = %d;", clq); if (app > 0) xprintf(" app = %d;", app); xprintf("\n"); } return; } /*********************************************************************** * NAME * * ios_driver - branch-and-cut driver * * SYNOPSIS * * #include "glpios.h" * int ios_driver(glp_tree *T); * * DESCRIPTION * * The routine ios_driver is a branch-and-cut driver. It controls the * MIP solution process. * * RETURNS * * 0 The MIP problem instance has been successfully solved. This code * does not necessarily mean that the solver has found optimal * solution. It only means that the solution process was successful. * * GLP_EFAIL * The search was prematurely terminated due to the solver failure. * * GLP_EMIPGAP * The search was prematurely terminated, because the relative mip * gap tolerance has been reached. * * GLP_ETMLIM * The search was prematurely terminated, because the time limit has * been exceeded. * * GLP_ESTOP * The search was prematurely terminated by application. */ int ios_driver(glp_tree *T) { int p, curr_p, p_stat, d_stat, ret; #if 1 /* carry out to glp_tree */ int pred_p = 0; /* if the current subproblem has been just created due to branching, pred_p is the reference number of its parent subproblem, otherwise pred_p is zero */ #endif glp_long ttt = T->tm_beg; #if 0 ((glp_iocp *)T->parm)->msg_lev = GLP_MSG_DBG; #endif /* on entry to the B&B driver it is assumed that the active list contains the only active (i.e. root) subproblem, which is the original MIP problem to be solved */ loop: /* main loop starts here */ /* at this point the current subproblem does not exist */ xassert(T->curr == NULL); /* if the active list is empty, the search is finished */ if (T->head == NULL) { if (T->parm->msg_lev >= GLP_MSG_DBG) xprintf("Active list is empty!\n"); xassert(dmp_in_use(T->pool).lo == 0); ret = 0; goto done; } /* select some active subproblem to continue the search */ xassert(T->next_p == 0); /* let the application program select subproblem */ if (T->parm->cb_func != NULL) { xassert(T->reason == 0); T->reason = GLP_ISELECT; T->parm->cb_func(T, T->parm->cb_info); T->reason = 0; if (T->stop) { ret = GLP_ESTOP; goto done; } } if (T->next_p != 0) { /* the application program has selected something */ ; } else if (T->a_cnt == 1) { /* the only active subproblem exists, so select it */ xassert(T->head->next == NULL); T->next_p = T->head->p; } else if (T->child != 0) { /* select one of branching childs suggested by the branching heuristic */ T->next_p = T->child; } else { /* select active subproblem as specified by the backtracking technique option */ T->next_p = ios_choose_node(T); } /* the active subproblem just selected becomes current */ ios_revive_node(T, T->next_p); T->next_p = T->child = 0; /* invalidate pred_p, if it is not the reference number of the parent of the current subproblem */ if (T->curr->up != NULL && T->curr->up->p != pred_p) pred_p = 0; /* determine the reference number of the current subproblem */ p = T->curr->p; if (T->parm->msg_lev >= GLP_MSG_DBG) { xprintf("-----------------------------------------------------" "-------------------\n"); xprintf("Processing node %d at level %d\n", p, T->curr->level); } /* if it is the root subproblem, initialize cut generators */ if (p == 1) { if (T->parm->gmi_cuts == GLP_ON) { if (T->parm->msg_lev >= GLP_MSG_ALL) xprintf("Gomory's cuts enabled\n"); } if (T->parm->mir_cuts == GLP_ON) { if (T->parm->msg_lev >= GLP_MSG_ALL) xprintf("MIR cuts enabled\n"); xassert(T->mir_gen == NULL); T->mir_gen = ios_mir_init(T); } if (T->parm->cov_cuts == GLP_ON) { if (T->parm->msg_lev >= GLP_MSG_ALL) xprintf("Cover cuts enabled\n"); } if (T->parm->clq_cuts == GLP_ON) { xassert(T->clq_gen == NULL); if (T->parm->msg_lev >= GLP_MSG_ALL) xprintf("Clique cuts enabled\n"); T->clq_gen = ios_clq_init(T); } } more: /* minor loop starts here */ /* at this point the current subproblem needs either to be solved for the first time or re-optimized due to reformulation */ /* display current progress of the search */ if (T->parm->msg_lev >= GLP_MSG_DBG || T->parm->msg_lev >= GLP_MSG_ON && (double)(T->parm->out_frq - 1) <= 1000.0 * xdifftime(xtime(), T->tm_lag)) show_progress(T, 0); if (T->parm->msg_lev >= GLP_MSG_ALL && xdifftime(xtime(), ttt) >= 60.0) { glp_long total; glp_mem_usage(NULL, NULL, &total, NULL); xprintf("Time used: %.1f secs. Memory used: %.1f Mb.\n", xdifftime(xtime(), T->tm_beg), xltod(total) / 1048576.0); ttt = xtime(); } /* check the mip gap */ if (T->parm->mip_gap > 0.0 && ios_relative_gap(T) <= T->parm->mip_gap) { if (T->parm->msg_lev >= GLP_MSG_DBG) xprintf("Relative gap tolerance reached; search terminated " "\n"); ret = GLP_EMIPGAP; goto done; } /* check if the time limit has been exhausted */ if (T->parm->tm_lim < INT_MAX && (double)(T->parm->tm_lim - 1) <= 1000.0 * xdifftime(xtime(), T->tm_beg)) { if (T->parm->msg_lev >= GLP_MSG_DBG) xprintf("Time limit exhausted; search terminated\n"); ret = GLP_ETMLIM; goto done; } /* let the application program preprocess the subproblem */ if (T->parm->cb_func != NULL) { xassert(T->reason == 0); T->reason = GLP_IPREPRO; T->parm->cb_func(T, T->parm->cb_info); T->reason = 0; if (T->stop) { ret = GLP_ESTOP; goto done; } } /* perform basic preprocessing */ if (T->parm->pp_tech == GLP_PP_NONE) ; else if (T->parm->pp_tech == GLP_PP_ROOT) { if (T->curr->level == 0) { if (ios_preprocess_node(T, 100)) goto fath; } } else if (T->parm->pp_tech == GLP_PP_ALL) { if (ios_preprocess_node(T, T->curr->level == 0 ? 100 : 10)) goto fath; } else xassert(T != T); /* preprocessing may improve the global bound */ if (!is_branch_hopeful(T, p)) { xprintf("*** not tested yet ***\n"); goto fath; } /* solve LP relaxation of the current subproblem */ if (T->parm->msg_lev >= GLP_MSG_DBG) xprintf("Solving LP relaxation...\n"); ret = ios_solve_node(T); if (!(ret == 0 || ret == GLP_EOBJLL || ret == GLP_EOBJUL)) { if (T->parm->msg_lev >= GLP_MSG_ERR) xprintf("ios_driver: unable to solve current LP relaxation;" " glp_simplex returned %d\n", ret); ret = GLP_EFAIL; goto done; } /* analyze status of the basic solution to LP relaxation found */ p_stat = T->mip->pbs_stat; d_stat = T->mip->dbs_stat; if (p_stat == GLP_FEAS && d_stat == GLP_FEAS) { /* LP relaxation has optimal solution */ if (T->parm->msg_lev >= GLP_MSG_DBG) xprintf("Found optimal solution to LP relaxation\n"); } else if (d_stat == GLP_NOFEAS) { /* LP relaxation has no dual feasible solution */ /* since the current subproblem cannot have a larger feasible region than its parent, there is something wrong */ if (T->parm->msg_lev >= GLP_MSG_ERR) xprintf("ios_driver: current LP relaxation has no dual feas" "ible solution\n"); ret = GLP_EFAIL; goto done; } else if (p_stat == GLP_INFEAS && d_stat == GLP_FEAS) { /* LP relaxation has no primal solution which is better than the incumbent objective value */ xassert(T->mip->mip_stat == GLP_FEAS); if (T->parm->msg_lev >= GLP_MSG_DBG) xprintf("LP relaxation has no solution better than incumben" "t objective value\n"); /* prune the branch */ goto fath; } else if (p_stat == GLP_NOFEAS) { /* LP relaxation has no primal feasible solution */ if (T->parm->msg_lev >= GLP_MSG_DBG) xprintf("LP relaxation has no feasible solution\n"); /* prune the branch */ goto fath; } else { /* other cases cannot appear */ xassert(T->mip != T->mip); } /* at this point basic solution to LP relaxation of the current subproblem is optimal */ xassert(p_stat == GLP_FEAS && d_stat == GLP_FEAS); xassert(T->curr != NULL); T->curr->lp_obj = T->mip->obj_val; /* thus, it defines a local bound to integer optimal solution of the current subproblem */ { double bound = T->mip->obj_val; /* some local bound to the current subproblem could be already set before, so we should only improve it */ bound = ios_round_bound(T, bound); if (T->mip->dir == GLP_MIN) { if (T->curr->bound < bound) T->curr->bound = bound; } else if (T->mip->dir == GLP_MAX) { if (T->curr->bound > bound) T->curr->bound = bound; } else xassert(T->mip != T->mip); if (T->parm->msg_lev >= GLP_MSG_DBG) xprintf("Local bound is %.9e\n", bound); } /* if the local bound indicates that integer optimal solution of the current subproblem cannot be better than the global bound, prune the branch */ if (!is_branch_hopeful(T, p)) { if (T->parm->msg_lev >= GLP_MSG_DBG) xprintf("Current branch is hopeless and can be pruned\n"); goto fath; } /* let the application program generate additional rows ("lazy" constraints) */ xassert(T->reopt == 0); xassert(T->reinv == 0); if (T->parm->cb_func != NULL) { xassert(T->reason == 0); T->reason = GLP_IROWGEN; T->parm->cb_func(T, T->parm->cb_info); T->reason = 0; if (T->stop) { ret = GLP_ESTOP; goto done; } if (T->reopt) { /* some rows were added; re-optimization is needed */ T->reopt = T->reinv = 0; goto more; } if (T->reinv) { /* no rows were added, however, some inactive rows were removed */ T->reinv = 0; xassert(glp_factorize(T->mip) == 0); } } /* check if the basic solution is integer feasible */ check_integrality(T); /* if the basic solution satisfies to all integrality conditions, it is a new, better integer feasible solution */ if (T->curr->ii_cnt == 0) { if (T->parm->msg_lev >= GLP_MSG_DBG) xprintf("New integer feasible solution found\n"); if (T->parm->msg_lev >= GLP_MSG_ALL) display_cut_info(T); record_solution(T); if (T->parm->msg_lev >= GLP_MSG_ON) show_progress(T, 1); /* make the application program happy */ if (T->parm->cb_func != NULL) { xassert(T->reason == 0); T->reason = GLP_IBINGO; T->parm->cb_func(T, T->parm->cb_info); T->reason = 0; if (T->stop) { ret = GLP_ESTOP; goto done; } } /* since the current subproblem has been fathomed, prune its branch */ goto fath; } /* at this point basic solution to LP relaxation of the current subproblem is optimal, but integer infeasible */ /* try to fix some non-basic structural variables of integer kind on their current bounds due to reduced costs */ if (T->mip->mip_stat == GLP_FEAS) fix_by_red_cost(T); /* let the application program try to find some solution to the original MIP with a primal heuristic */ if (T->parm->cb_func != NULL) { xassert(T->reason == 0); T->reason = GLP_IHEUR; T->parm->cb_func(T, T->parm->cb_info); T->reason = 0; if (T->stop) { ret = GLP_ESTOP; goto done; } /* check if the current branch became hopeless */ if (!is_branch_hopeful(T, p)) { if (T->parm->msg_lev >= GLP_MSG_DBG) xprintf("Current branch became hopeless and can be prune" "d\n"); goto fath; } } /* try to find solution with the feasibility pump heuristic */ if (T->parm->fp_heur) { xassert(T->reason == 0); T->reason = GLP_IHEUR; ios_feas_pump(T); T->reason = 0; /* check if the current branch became hopeless */ if (!is_branch_hopeful(T, p)) { if (T->parm->msg_lev >= GLP_MSG_DBG) xprintf("Current branch became hopeless and can be prune" "d\n"); goto fath; } } /* it's time to generate cutting planes */ xassert(T->local != NULL); xassert(T->local->size == 0); /* let the application program generate some cuts; note that it can add cuts either to the local cut pool or directly to the current subproblem */ if (T->parm->cb_func != NULL) { xassert(T->reason == 0); T->reason = GLP_ICUTGEN; T->parm->cb_func(T, T->parm->cb_info); T->reason = 0; if (T->stop) { ret = GLP_ESTOP; goto done; } } /* try to generate generic cuts with built-in generators (as suggested by Matteo Fischetti et al. the built-in cuts are not generated at each branching node; an intense attempt of generating new cuts is only made at the root node, and then a moderate effort is spent after each backtracking step) */ if (T->curr->level == 0 || pred_p == 0) { xassert(T->reason == 0); T->reason = GLP_ICUTGEN; generate_cuts(T); T->reason = 0; } /* if the local cut pool is not empty, select useful cuts and add them to the current subproblem */ if (T->local->size > 0) { xassert(T->reason == 0); T->reason = GLP_ICUTGEN; ios_process_cuts(T); T->reason = 0; } /* clear the local cut pool */ ios_clear_pool(T, T->local); /* perform re-optimization, if necessary */ if (T->reopt) { T->reopt = 0; T->curr->changed++; goto more; } /* no cuts were generated; remove inactive cuts */ remove_cuts(T); if (T->parm->msg_lev >= GLP_MSG_ALL && T->curr->level == 0) display_cut_info(T); /* update history information used on pseudocost branching */ if (T->pcost != NULL) ios_pcost_update(T); /* it's time to perform branching */ xassert(T->br_var == 0); xassert(T->br_sel == 0); /* let the application program choose variable to branch on */ if (T->parm->cb_func != NULL) { xassert(T->reason == 0); xassert(T->br_var == 0); xassert(T->br_sel == 0); T->reason = GLP_IBRANCH; T->parm->cb_func(T, T->parm->cb_info); T->reason = 0; if (T->stop) { ret = GLP_ESTOP; goto done; } } /* if nothing has been chosen, choose some variable as specified by the branching technique option */ if (T->br_var == 0) T->br_var = ios_choose_var(T, &T->br_sel); /* perform actual branching */ curr_p = T->curr->p; ret = branch_on(T, T->br_var, T->br_sel); T->br_var = T->br_sel = 0; if (ret == 0) { /* both branches have been created */ pred_p = curr_p; goto loop; } else if (ret == 1) { /* one branch is hopeless and has been pruned, so now the current subproblem is other branch */ /* the current subproblem should be considered as a new one, since one bound of the branching variable was changed */ T->curr->solved = T->curr->changed = 0; goto more; } else if (ret == 2) { /* both branches are hopeless and have been pruned; new subproblem selection is needed to continue the search */ goto fath; } else xassert(ret != ret); fath: /* the current subproblem has been fathomed */ if (T->parm->msg_lev >= GLP_MSG_DBG) xprintf("Node %d fathomed\n", p); /* freeze the current subproblem */ ios_freeze_node(T); /* and prune the corresponding branch of the tree */ ios_delete_node(T, p); /* if a new integer feasible solution has just been found, other branches may become hopeless and therefore must be pruned */ if (T->mip->mip_stat == GLP_FEAS) cleanup_the_tree(T); /* new subproblem selection is needed due to backtracking */ pred_p = 0; goto loop; done: /* display progress of the search on exit from the solver */ if (T->parm->msg_lev >= GLP_MSG_ON) show_progress(T, 0); if (T->mir_gen != NULL) ios_mir_term(T->mir_gen), T->mir_gen = NULL; if (T->clq_gen != NULL) ios_clq_term(T->clq_gen), T->clq_gen = NULL; /* return to the calling program */ return ret; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpspx02.c0000644000076500000240000030646213524616144025235 0ustar tamasstaff00000000000000/* glpspx02.c (dual simplex method) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wcomment" #pragma clang diagnostic ignored "-Wsign-conversion" #pragma clang diagnostic ignored "-Wsometimes-uninitialized" #pragma clang diagnostic ignored "-Wlogical-op-parentheses" #endif #include "glpspx.h" #define GLP_DEBUG 1 #if 0 #define GLP_LONG_STEP 1 #endif struct csa { /* common storage area */ /*--------------------------------------------------------------*/ /* LP data */ int m; /* number of rows (auxiliary variables), m > 0 */ int n; /* number of columns (structural variables), n > 0 */ char *type; /* char type[1+m+n]; */ /* type[0] is not used; type[k], 1 <= k <= m+n, is the type of variable x[k]: GLP_FR - free variable GLP_LO - variable with lower bound GLP_UP - variable with upper bound GLP_DB - double-bounded variable GLP_FX - fixed variable */ double *lb; /* double lb[1+m+n]; */ /* lb[0] is not used; lb[k], 1 <= k <= m+n, is an lower bound of variable x[k]; if x[k] has no lower bound, lb[k] is zero */ double *ub; /* double ub[1+m+n]; */ /* ub[0] is not used; ub[k], 1 <= k <= m+n, is an upper bound of variable x[k]; if x[k] has no upper bound, ub[k] is zero; if x[k] is of fixed type, ub[k] is the same as lb[k] */ double *coef; /* double coef[1+m+n]; */ /* coef[0] is not used; coef[k], 1 <= k <= m+n, is an objective coefficient at variable x[k] */ /*--------------------------------------------------------------*/ /* original bounds of variables */ char *orig_type; /* char orig_type[1+m+n]; */ double *orig_lb; /* double orig_lb[1+m+n]; */ double *orig_ub; /* double orig_ub[1+m+n]; */ /*--------------------------------------------------------------*/ /* original objective function */ double *obj; /* double obj[1+n]; */ /* obj[0] is a constant term of the original objective function; obj[j], 1 <= j <= n, is an original objective coefficient at structural variable x[m+j] */ double zeta; /* factor used to scale original objective coefficients; its sign defines original optimization direction: zeta > 0 means minimization, zeta < 0 means maximization */ /*--------------------------------------------------------------*/ /* constraint matrix A; it has m rows and n columns and is stored by columns */ int *A_ptr; /* int A_ptr[1+n+1]; */ /* A_ptr[0] is not used; A_ptr[j], 1 <= j <= n, is starting position of j-th column in arrays A_ind and A_val; note that A_ptr[1] is always 1; A_ptr[n+1] indicates the position after the last element in arrays A_ind and A_val */ int *A_ind; /* int A_ind[A_ptr[n+1]]; */ /* row indices */ double *A_val; /* double A_val[A_ptr[n+1]]; */ /* non-zero element values */ #if 1 /* 06/IV-2009 */ /* constraint matrix A stored by rows */ int *AT_ptr; /* int AT_ptr[1+m+1]; /* AT_ptr[0] is not used; AT_ptr[i], 1 <= i <= m, is starting position of i-th row in arrays AT_ind and AT_val; note that AT_ptr[1] is always 1; AT_ptr[m+1] indicates the position after the last element in arrays AT_ind and AT_val */ int *AT_ind; /* int AT_ind[AT_ptr[m+1]]; */ /* column indices */ double *AT_val; /* double AT_val[AT_ptr[m+1]]; */ /* non-zero element values */ #endif /*--------------------------------------------------------------*/ /* basis header */ int *head; /* int head[1+m+n]; */ /* head[0] is not used; head[i], 1 <= i <= m, is the ordinal number of basic variable xB[i]; head[i] = k means that xB[i] = x[k] and i-th column of matrix B is k-th column of matrix (I|-A); head[m+j], 1 <= j <= n, is the ordinal number of non-basic variable xN[j]; head[m+j] = k means that xN[j] = x[k] and j-th column of matrix N is k-th column of matrix (I|-A) */ #if 1 /* 06/IV-2009 */ int *bind; /* int bind[1+m+n]; */ /* bind[0] is not used; bind[k], 1 <= k <= m+n, is the position of k-th column of the matrix (I|-A) in the matrix (B|N); that is, bind[k] = k' means that head[k'] = k */ #endif char *stat; /* char stat[1+n]; */ /* stat[0] is not used; stat[j], 1 <= j <= n, is the status of non-basic variable xN[j], which defines its active bound: GLP_NL - lower bound is active GLP_NU - upper bound is active GLP_NF - free variable GLP_NS - fixed variable */ /*--------------------------------------------------------------*/ /* matrix B is the basis matrix; it is composed from columns of the augmented constraint matrix (I|-A) corresponding to basic variables and stored in a factorized (invertable) form */ int valid; /* factorization is valid only if this flag is set */ BFD *bfd; /* BFD bfd[1:m,1:m]; */ /* factorized (invertable) form of the basis matrix */ #if 0 /* 06/IV-2009 */ /*--------------------------------------------------------------*/ /* matrix N is a matrix composed from columns of the augmented constraint matrix (I|-A) corresponding to non-basic variables except fixed ones; it is stored by rows and changes every time the basis changes */ int *N_ptr; /* int N_ptr[1+m+1]; */ /* N_ptr[0] is not used; N_ptr[i], 1 <= i <= m, is starting position of i-th row in arrays N_ind and N_val; note that N_ptr[1] is always 1; N_ptr[m+1] indicates the position after the last element in arrays N_ind and N_val */ int *N_len; /* int N_len[1+m]; */ /* N_len[0] is not used; N_len[i], 1 <= i <= m, is length of i-th row (0 to n) */ int *N_ind; /* int N_ind[N_ptr[m+1]]; */ /* column indices */ double *N_val; /* double N_val[N_ptr[m+1]]; */ /* non-zero element values */ #endif /*--------------------------------------------------------------*/ /* working parameters */ int phase; /* search phase: 0 - not determined yet 1 - search for dual feasible solution 2 - search for optimal solution */ glp_long tm_beg; /* time value at the beginning of the search */ int it_beg; /* simplex iteration count at the beginning of the search */ int it_cnt; /* simplex iteration count; it increases by one every time the basis changes */ int it_dpy; /* simplex iteration count at the most recent display output */ /*--------------------------------------------------------------*/ /* basic solution components */ double *bbar; /* double bbar[1+m]; */ /* bbar[0] is not used on phase I; on phase II it is the current value of the original objective function; bbar[i], 1 <= i <= m, is primal value of basic variable xB[i] (if xB[i] is free, its primal value is not updated) */ double *cbar; /* double cbar[1+n]; */ /* cbar[0] is not used; cbar[j], 1 <= j <= n, is reduced cost of non-basic variable xN[j] (if xN[j] is fixed, its reduced cost is not updated) */ /*--------------------------------------------------------------*/ /* the following pricing technique options may be used: GLP_PT_STD - standard ("textbook") pricing; GLP_PT_PSE - projected steepest edge; GLP_PT_DVX - Devex pricing (not implemented yet); in case of GLP_PT_STD the reference space is not used, and all steepest edge coefficients are set to 1 */ int refct; /* this count is set to an initial value when the reference space is defined and decreases by one every time the basis changes; once this count reaches zero, the reference space is redefined again */ char *refsp; /* char refsp[1+m+n]; */ /* refsp[0] is not used; refsp[k], 1 <= k <= m+n, is the flag which means that variable x[k] belongs to the current reference space */ double *gamma; /* double gamma[1+m]; */ /* gamma[0] is not used; gamma[i], 1 <= i <= n, is the steepest edge coefficient for basic variable xB[i]; if xB[i] is free, gamma[i] is not used and just set to 1 */ /*--------------------------------------------------------------*/ /* basic variable xB[p] chosen to leave the basis */ int p; /* index of the basic variable xB[p] chosen, 1 <= p <= m; if the set of eligible basic variables is empty (i.e. if the current basic solution is primal feasible within a tolerance) and thus no variable has been chosen, p is set to 0 */ double delta; /* change of xB[p] in the adjacent basis; delta > 0 means that xB[p] violates its lower bound and will increase to achieve it in the adjacent basis; delta < 0 means that xB[p] violates its upper bound and will decrease to achieve it in the adjacent basis */ /*--------------------------------------------------------------*/ /* pivot row of the simplex table corresponding to basic variable xB[p] chosen is the following vector: T' * e[p] = - N' * inv(B') * e[p] = - N' * rho, where B' is a matrix transposed to the current basis matrix, N' is a matrix, whose rows are columns of the matrix (I|-A) corresponding to non-basic non-fixed variables */ int trow_nnz; /* number of non-zero components, 0 <= nnz <= n */ int *trow_ind; /* int trow_ind[1+n]; */ /* trow_ind[0] is not used; trow_ind[t], 1 <= t <= nnz, is an index of non-zero component, i.e. trow_ind[t] = j means that trow_vec[j] != 0 */ double *trow_vec; /* int trow_vec[1+n]; */ /* trow_vec[0] is not used; trow_vec[j], 1 <= j <= n, is a numeric value of j-th component of the row */ double trow_max; /* infinity (maximum) norm of the row (max |trow_vec[j]|) */ int trow_num; /* number of significant non-zero components, which means that: |trow_vec[j]| >= eps for j in trow_ind[1,...,num], |tcol_vec[j]| < eps for j in trow_ind[num+1,...,nnz], where eps is a pivot tolerance */ /*--------------------------------------------------------------*/ #ifdef GLP_LONG_STEP /* 07/IV-2009 */ int nbps; /* number of breakpoints, 0 <= nbps <= n */ struct bkpt { int j; /* index of non-basic variable xN[j], 1 <= j <= n */ double t; /* value of dual ray parameter at breakpoint, t >= 0 */ double dz; /* dz = zeta(t = t[k]) - zeta(t = 0) */ } *bkpt; /* struct bkpt bkpt[1+n]; */ /* bkpt[0] is not used; bkpt[k], 1 <= k <= nbps, is k-th breakpoint of the dual objective */ #endif /*--------------------------------------------------------------*/ /* non-basic variable xN[q] chosen to enter the basis */ int q; /* index of the non-basic variable xN[q] chosen, 1 <= q <= n; if no variable has been chosen, q is set to 0 */ double new_dq; /* reduced cost of xN[q] in the adjacent basis (it is the change of lambdaB[p]) */ /*--------------------------------------------------------------*/ /* pivot column of the simplex table corresponding to non-basic variable xN[q] chosen is the following vector: T * e[q] = - inv(B) * N * e[q] = - inv(B) * N[q], where B is the current basis matrix, N[q] is a column of the matrix (I|-A) corresponding to xN[q] */ int tcol_nnz; /* number of non-zero components, 0 <= nnz <= m */ int *tcol_ind; /* int tcol_ind[1+m]; */ /* tcol_ind[0] is not used; tcol_ind[t], 1 <= t <= nnz, is an index of non-zero component, i.e. tcol_ind[t] = i means that tcol_vec[i] != 0 */ double *tcol_vec; /* double tcol_vec[1+m]; */ /* tcol_vec[0] is not used; tcol_vec[i], 1 <= i <= m, is a numeric value of i-th component of the column */ /*--------------------------------------------------------------*/ /* working arrays */ double *work1; /* double work1[1+m]; */ double *work2; /* double work2[1+m]; */ double *work3; /* double work3[1+m]; */ double *work4; /* double work4[1+m]; */ }; static const double kappa = 0.10; /*********************************************************************** * alloc_csa - allocate common storage area * * This routine allocates all arrays in the common storage area (CSA) * and returns a pointer to the CSA. */ static struct csa *alloc_csa(glp_prob *lp) { struct csa *csa; int m = lp->m; int n = lp->n; int nnz = lp->nnz; csa = xmalloc(sizeof(struct csa)); xassert(m > 0 && n > 0); csa->m = m; csa->n = n; csa->type = xcalloc(1+m+n, sizeof(char)); csa->lb = xcalloc(1+m+n, sizeof(double)); csa->ub = xcalloc(1+m+n, sizeof(double)); csa->coef = xcalloc(1+m+n, sizeof(double)); csa->orig_type = xcalloc(1+m+n, sizeof(char)); csa->orig_lb = xcalloc(1+m+n, sizeof(double)); csa->orig_ub = xcalloc(1+m+n, sizeof(double)); csa->obj = xcalloc(1+n, sizeof(double)); csa->A_ptr = xcalloc(1+n+1, sizeof(int)); csa->A_ind = xcalloc(1+nnz, sizeof(int)); csa->A_val = xcalloc(1+nnz, sizeof(double)); #if 1 /* 06/IV-2009 */ csa->AT_ptr = xcalloc(1+m+1, sizeof(int)); csa->AT_ind = xcalloc(1+nnz, sizeof(int)); csa->AT_val = xcalloc(1+nnz, sizeof(double)); #endif csa->head = xcalloc(1+m+n, sizeof(int)); #if 1 /* 06/IV-2009 */ csa->bind = xcalloc(1+m+n, sizeof(int)); #endif csa->stat = xcalloc(1+n, sizeof(char)); #if 0 /* 06/IV-2009 */ csa->N_ptr = xcalloc(1+m+1, sizeof(int)); csa->N_len = xcalloc(1+m, sizeof(int)); csa->N_ind = NULL; /* will be allocated later */ csa->N_val = NULL; /* will be allocated later */ #endif csa->bbar = xcalloc(1+m, sizeof(double)); csa->cbar = xcalloc(1+n, sizeof(double)); csa->refsp = xcalloc(1+m+n, sizeof(char)); csa->gamma = xcalloc(1+m, sizeof(double)); csa->trow_ind = xcalloc(1+n, sizeof(int)); csa->trow_vec = xcalloc(1+n, sizeof(double)); #ifdef GLP_LONG_STEP /* 07/IV-2009 */ csa->bkpt = xcalloc(1+n, sizeof(struct bkpt)); #endif csa->tcol_ind = xcalloc(1+m, sizeof(int)); csa->tcol_vec = xcalloc(1+m, sizeof(double)); csa->work1 = xcalloc(1+m, sizeof(double)); csa->work2 = xcalloc(1+m, sizeof(double)); csa->work3 = xcalloc(1+m, sizeof(double)); csa->work4 = xcalloc(1+m, sizeof(double)); return csa; } /*********************************************************************** * init_csa - initialize common storage area * * This routine initializes all data structures in the common storage * area (CSA). */ static void init_csa(struct csa *csa, glp_prob *lp) { int m = csa->m; int n = csa->n; char *type = csa->type; double *lb = csa->lb; double *ub = csa->ub; double *coef = csa->coef; char *orig_type = csa->orig_type; double *orig_lb = csa->orig_lb; double *orig_ub = csa->orig_ub; double *obj = csa->obj; int *A_ptr = csa->A_ptr; int *A_ind = csa->A_ind; double *A_val = csa->A_val; #if 1 /* 06/IV-2009 */ int *AT_ptr = csa->AT_ptr; int *AT_ind = csa->AT_ind; double *AT_val = csa->AT_val; #endif int *head = csa->head; #if 1 /* 06/IV-2009 */ int *bind = csa->bind; #endif char *stat = csa->stat; char *refsp = csa->refsp; double *gamma = csa->gamma; int i, j, k, loc; double cmax; /* auxiliary variables */ for (i = 1; i <= m; i++) { GLPROW *row = lp->row[i]; type[i] = (char)row->type; lb[i] = row->lb * row->rii; ub[i] = row->ub * row->rii; coef[i] = 0.0; } /* structural variables */ for (j = 1; j <= n; j++) { GLPCOL *col = lp->col[j]; type[m+j] = (char)col->type; lb[m+j] = col->lb / col->sjj; ub[m+j] = col->ub / col->sjj; coef[m+j] = col->coef * col->sjj; } /* original bounds of variables */ memcpy(&orig_type[1], &type[1], (m+n) * sizeof(char)); memcpy(&orig_lb[1], &lb[1], (m+n) * sizeof(double)); memcpy(&orig_ub[1], &ub[1], (m+n) * sizeof(double)); /* original objective function */ obj[0] = lp->c0; memcpy(&obj[1], &coef[m+1], n * sizeof(double)); /* factor used to scale original objective coefficients */ cmax = 0.0; for (j = 1; j <= n; j++) if (cmax < fabs(obj[j])) cmax = fabs(obj[j]); if (cmax == 0.0) cmax = 1.0; switch (lp->dir) { case GLP_MIN: csa->zeta = + 1.0 / cmax; break; case GLP_MAX: csa->zeta = - 1.0 / cmax; break; default: xassert(lp != lp); } #if 1 if (fabs(csa->zeta) < 1.0) csa->zeta *= 1000.0; #endif /* scale working objective coefficients */ for (j = 1; j <= n; j++) coef[m+j] *= csa->zeta; /* matrix A (by columns) */ loc = 1; for (j = 1; j <= n; j++) { GLPAIJ *aij; A_ptr[j] = loc; for (aij = lp->col[j]->ptr; aij != NULL; aij = aij->c_next) { A_ind[loc] = aij->row->i; A_val[loc] = aij->row->rii * aij->val * aij->col->sjj; loc++; } } A_ptr[n+1] = loc; xassert(loc-1 == lp->nnz); #if 1 /* 06/IV-2009 */ /* matrix A (by rows) */ loc = 1; for (i = 1; i <= m; i++) { GLPAIJ *aij; AT_ptr[i] = loc; for (aij = lp->row[i]->ptr; aij != NULL; aij = aij->r_next) { AT_ind[loc] = aij->col->j; AT_val[loc] = aij->row->rii * aij->val * aij->col->sjj; loc++; } } AT_ptr[m+1] = loc; xassert(loc-1 == lp->nnz); #endif /* basis header */ xassert(lp->valid); memcpy(&head[1], &lp->head[1], m * sizeof(int)); k = 0; for (i = 1; i <= m; i++) { GLPROW *row = lp->row[i]; if (row->stat != GLP_BS) { k++; xassert(k <= n); head[m+k] = i; stat[k] = (char)row->stat; } } for (j = 1; j <= n; j++) { GLPCOL *col = lp->col[j]; if (col->stat != GLP_BS) { k++; xassert(k <= n); head[m+k] = m + j; stat[k] = (char)col->stat; } } xassert(k == n); #if 1 /* 06/IV-2009 */ for (k = 1; k <= m+n; k++) bind[head[k]] = k; #endif /* factorization of matrix B */ csa->valid = 1, lp->valid = 0; csa->bfd = lp->bfd, lp->bfd = NULL; #if 0 /* 06/IV-2009 */ /* matrix N (by rows) */ alloc_N(csa); build_N(csa); #endif /* working parameters */ csa->phase = 0; csa->tm_beg = xtime(); csa->it_beg = csa->it_cnt = lp->it_cnt; csa->it_dpy = -1; /* reference space and steepest edge coefficients */ csa->refct = 0; memset(&refsp[1], 0, (m+n) * sizeof(char)); for (i = 1; i <= m; i++) gamma[i] = 1.0; return; } #if 1 /* copied from primal */ /*********************************************************************** * invert_B - compute factorization of the basis matrix * * This routine computes factorization of the current basis matrix B. * * If the operation is successful, the routine returns zero, otherwise * non-zero. */ static int inv_col(void *info, int i, int ind[], double val[]) { /* this auxiliary routine returns row indices and numeric values of non-zero elements of i-th column of the basis matrix */ struct csa *csa = info; int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; #endif int *A_ptr = csa->A_ptr; int *A_ind = csa->A_ind; double *A_val = csa->A_val; int *head = csa->head; int k, len, ptr, t; #ifdef GLP_DEBUG xassert(1 <= i && i <= m); #endif k = head[i]; /* B[i] is k-th column of (I|-A) */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif if (k <= m) { /* B[i] is k-th column of submatrix I */ len = 1; ind[1] = k; val[1] = 1.0; } else { /* B[i] is (k-m)-th column of submatrix (-A) */ ptr = A_ptr[k-m]; len = A_ptr[k-m+1] - ptr; memcpy(&ind[1], &A_ind[ptr], len * sizeof(int)); memcpy(&val[1], &A_val[ptr], len * sizeof(double)); for (t = 1; t <= len; t++) val[t] = - val[t]; } return len; } static int invert_B(struct csa *csa) { int ret; ret = bfd_factorize(csa->bfd, csa->m, NULL, inv_col, csa); csa->valid = (ret == 0); return ret; } #endif #if 1 /* copied from primal */ /*********************************************************************** * update_B - update factorization of the basis matrix * * This routine replaces i-th column of the basis matrix B by k-th * column of the augmented constraint matrix (I|-A) and then updates * the factorization of B. * * If the factorization has been successfully updated, the routine * returns zero, otherwise non-zero. */ static int update_B(struct csa *csa, int i, int k) { int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; #endif int ret; #ifdef GLP_DEBUG xassert(1 <= i && i <= m); xassert(1 <= k && k <= m+n); #endif if (k <= m) { /* new i-th column of B is k-th column of I */ int ind[1+1]; double val[1+1]; ind[1] = k; val[1] = 1.0; xassert(csa->valid); ret = bfd_update_it(csa->bfd, i, 0, 1, ind, val); } else { /* new i-th column of B is (k-m)-th column of (-A) */ int *A_ptr = csa->A_ptr; int *A_ind = csa->A_ind; double *A_val = csa->A_val; double *val = csa->work1; int beg, end, ptr, len; beg = A_ptr[k-m]; end = A_ptr[k-m+1]; len = 0; for (ptr = beg; ptr < end; ptr++) val[++len] = - A_val[ptr]; xassert(csa->valid); ret = bfd_update_it(csa->bfd, i, 0, len, &A_ind[beg-1], val); } csa->valid = (ret == 0); return ret; } #endif #if 1 /* copied from primal */ /*********************************************************************** * error_ftran - compute residual vector r = h - B * x * * This routine computes the residual vector r = h - B * x, where B is * the current basis matrix, h is the vector of right-hand sides, x is * the solution vector. */ static void error_ftran(struct csa *csa, double h[], double x[], double r[]) { int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; #endif int *A_ptr = csa->A_ptr; int *A_ind = csa->A_ind; double *A_val = csa->A_val; int *head = csa->head; int i, k, beg, end, ptr; double temp; /* compute the residual vector: r = h - B * x = h - B[1] * x[1] - ... - B[m] * x[m], where B[1], ..., B[m] are columns of matrix B */ memcpy(&r[1], &h[1], m * sizeof(double)); for (i = 1; i <= m; i++) { temp = x[i]; if (temp == 0.0) continue; k = head[i]; /* B[i] is k-th column of (I|-A) */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif if (k <= m) { /* B[i] is k-th column of submatrix I */ r[k] -= temp; } else { /* B[i] is (k-m)-th column of submatrix (-A) */ beg = A_ptr[k-m]; end = A_ptr[k-m+1]; for (ptr = beg; ptr < end; ptr++) r[A_ind[ptr]] += A_val[ptr] * temp; } } return; } #endif #if 1 /* copied from primal */ /*********************************************************************** * refine_ftran - refine solution of B * x = h * * This routine performs one iteration to refine the solution of * the system B * x = h, where B is the current basis matrix, h is the * vector of right-hand sides, x is the solution vector. */ static void refine_ftran(struct csa *csa, double h[], double x[]) { int m = csa->m; double *r = csa->work1; double *d = csa->work1; int i; /* compute the residual vector r = h - B * x */ error_ftran(csa, h, x, r); /* compute the correction vector d = inv(B) * r */ xassert(csa->valid); bfd_ftran(csa->bfd, d); /* refine the solution vector (new x) = (old x) + d */ for (i = 1; i <= m; i++) x[i] += d[i]; return; } #endif #if 1 /* copied from primal */ /*********************************************************************** * error_btran - compute residual vector r = h - B'* x * * This routine computes the residual vector r = h - B'* x, where B' * is a matrix transposed to the current basis matrix, h is the vector * of right-hand sides, x is the solution vector. */ static void error_btran(struct csa *csa, double h[], double x[], double r[]) { int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; #endif int *A_ptr = csa->A_ptr; int *A_ind = csa->A_ind; double *A_val = csa->A_val; int *head = csa->head; int i, k, beg, end, ptr; double temp; /* compute the residual vector r = b - B'* x */ for (i = 1; i <= m; i++) { /* r[i] := b[i] - (i-th column of B)'* x */ k = head[i]; /* B[i] is k-th column of (I|-A) */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif temp = h[i]; if (k <= m) { /* B[i] is k-th column of submatrix I */ temp -= x[k]; } else { /* B[i] is (k-m)-th column of submatrix (-A) */ beg = A_ptr[k-m]; end = A_ptr[k-m+1]; for (ptr = beg; ptr < end; ptr++) temp += A_val[ptr] * x[A_ind[ptr]]; } r[i] = temp; } return; } #endif #if 1 /* copied from primal */ /*********************************************************************** * refine_btran - refine solution of B'* x = h * * This routine performs one iteration to refine the solution of the * system B'* x = h, where B' is a matrix transposed to the current * basis matrix, h is the vector of right-hand sides, x is the solution * vector. */ static void refine_btran(struct csa *csa, double h[], double x[]) { int m = csa->m; double *r = csa->work1; double *d = csa->work1; int i; /* compute the residual vector r = h - B'* x */ error_btran(csa, h, x, r); /* compute the correction vector d = inv(B') * r */ xassert(csa->valid); bfd_btran(csa->bfd, d); /* refine the solution vector (new x) = (old x) + d */ for (i = 1; i <= m; i++) x[i] += d[i]; return; } #endif #if 1 /* copied from primal */ /*********************************************************************** * get_xN - determine current value of non-basic variable xN[j] * * This routine returns the current value of non-basic variable xN[j], * which is a value of its active bound. */ static double get_xN(struct csa *csa, int j) { int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; #endif double *lb = csa->lb; double *ub = csa->ub; int *head = csa->head; char *stat = csa->stat; int k; double xN; #ifdef GLP_DEBUG xassert(1 <= j && j <= n); #endif k = head[m+j]; /* x[k] = xN[j] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif switch (stat[j]) { case GLP_NL: /* x[k] is on its lower bound */ xN = lb[k]; break; case GLP_NU: /* x[k] is on its upper bound */ xN = ub[k]; break; case GLP_NF: /* x[k] is free non-basic variable */ xN = 0.0; break; case GLP_NS: /* x[k] is fixed non-basic variable */ xN = lb[k]; break; default: xassert(stat != stat); } return xN; } #endif #if 1 /* copied from primal */ /*********************************************************************** * eval_beta - compute primal values of basic variables * * This routine computes current primal values of all basic variables: * * beta = - inv(B) * N * xN, * * where B is the current basis matrix, N is a matrix built of columns * of matrix (I|-A) corresponding to non-basic variables, and xN is the * vector of current values of non-basic variables. */ static void eval_beta(struct csa *csa, double beta[]) { int m = csa->m; int n = csa->n; int *A_ptr = csa->A_ptr; int *A_ind = csa->A_ind; double *A_val = csa->A_val; int *head = csa->head; double *h = csa->work2; int i, j, k, beg, end, ptr; double xN; /* compute the right-hand side vector: h := - N * xN = - N[1] * xN[1] - ... - N[n] * xN[n], where N[1], ..., N[n] are columns of matrix N */ for (i = 1; i <= m; i++) h[i] = 0.0; for (j = 1; j <= n; j++) { k = head[m+j]; /* x[k] = xN[j] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif /* determine current value of xN[j] */ xN = get_xN(csa, j); if (xN == 0.0) continue; if (k <= m) { /* N[j] is k-th column of submatrix I */ h[k] -= xN; } else { /* N[j] is (k-m)-th column of submatrix (-A) */ beg = A_ptr[k-m]; end = A_ptr[k-m+1]; for (ptr = beg; ptr < end; ptr++) h[A_ind[ptr]] += xN * A_val[ptr]; } } /* solve system B * beta = h */ memcpy(&beta[1], &h[1], m * sizeof(double)); xassert(csa->valid); bfd_ftran(csa->bfd, beta); /* and refine the solution */ refine_ftran(csa, h, beta); return; } #endif #if 1 /* copied from primal */ /*********************************************************************** * eval_pi - compute vector of simplex multipliers * * This routine computes the vector of current simplex multipliers: * * pi = inv(B') * cB, * * where B' is a matrix transposed to the current basis matrix, cB is * a subvector of objective coefficients at basic variables. */ static void eval_pi(struct csa *csa, double pi[]) { int m = csa->m; double *c = csa->coef; int *head = csa->head; double *cB = csa->work2; int i; /* construct the right-hand side vector cB */ for (i = 1; i <= m; i++) cB[i] = c[head[i]]; /* solve system B'* pi = cB */ memcpy(&pi[1], &cB[1], m * sizeof(double)); xassert(csa->valid); bfd_btran(csa->bfd, pi); /* and refine the solution */ refine_btran(csa, cB, pi); return; } #endif #if 1 /* copied from primal */ /*********************************************************************** * eval_cost - compute reduced cost of non-basic variable xN[j] * * This routine computes the current reduced cost of non-basic variable * xN[j]: * * d[j] = cN[j] - N'[j] * pi, * * where cN[j] is the objective coefficient at variable xN[j], N[j] is * a column of the augmented constraint matrix (I|-A) corresponding to * xN[j], pi is the vector of simplex multipliers. */ static double eval_cost(struct csa *csa, double pi[], int j) { int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; #endif double *coef = csa->coef; int *head = csa->head; int k; double dj; #ifdef GLP_DEBUG xassert(1 <= j && j <= n); #endif k = head[m+j]; /* x[k] = xN[j] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif dj = coef[k]; if (k <= m) { /* N[j] is k-th column of submatrix I */ dj -= pi[k]; } else { /* N[j] is (k-m)-th column of submatrix (-A) */ int *A_ptr = csa->A_ptr; int *A_ind = csa->A_ind; double *A_val = csa->A_val; int beg, end, ptr; beg = A_ptr[k-m]; end = A_ptr[k-m+1]; for (ptr = beg; ptr < end; ptr++) dj += A_val[ptr] * pi[A_ind[ptr]]; } return dj; } #endif #if 1 /* copied from primal */ /*********************************************************************** * eval_bbar - compute and store primal values of basic variables * * This routine computes primal values of all basic variables and then * stores them in the solution array. */ static void eval_bbar(struct csa *csa) { eval_beta(csa, csa->bbar); return; } #endif #if 1 /* copied from primal */ /*********************************************************************** * eval_cbar - compute and store reduced costs of non-basic variables * * This routine computes reduced costs of all non-basic variables and * then stores them in the solution array. */ static void eval_cbar(struct csa *csa) { #ifdef GLP_DEBUG int m = csa->m; #endif int n = csa->n; #ifdef GLP_DEBUG int *head = csa->head; #endif double *cbar = csa->cbar; double *pi = csa->work3; int j; #ifdef GLP_DEBUG int k; #endif /* compute simplex multipliers */ eval_pi(csa, pi); /* compute and store reduced costs */ for (j = 1; j <= n; j++) { #ifdef GLP_DEBUG k = head[m+j]; /* x[k] = xN[j] */ xassert(1 <= k && k <= m+n); #endif cbar[j] = eval_cost(csa, pi, j); } return; } #endif /*********************************************************************** * reset_refsp - reset the reference space * * This routine resets (redefines) the reference space used in the * projected steepest edge pricing algorithm. */ static void reset_refsp(struct csa *csa) { int m = csa->m; int n = csa->n; int *head = csa->head; char *refsp = csa->refsp; double *gamma = csa->gamma; int i, k; xassert(csa->refct == 0); csa->refct = 1000; memset(&refsp[1], 0, (m+n) * sizeof(char)); for (i = 1; i <= m; i++) { k = head[i]; /* x[k] = xB[i] */ refsp[k] = 1; gamma[i] = 1.0; } return; } /*********************************************************************** * eval_gamma - compute steepest edge coefficients * * This routine computes the vector of steepest edge coefficients for * all basic variables (except free ones) using its direct definition: * * gamma[i] = eta[i] + sum alfa[i,j]^2, i = 1,...,m, * j in C * * where eta[i] = 1 means that xB[i] is in the current reference space, * and 0 otherwise; C is a set of non-basic non-fixed variables xN[j], * which are in the current reference space; alfa[i,j] are elements of * the current simplex table. * * NOTE: The routine is intended only for debugginig purposes. */ static void eval_gamma(struct csa *csa, double gamma[]) { int m = csa->m; int n = csa->n; char *type = csa->type; int *head = csa->head; char *refsp = csa->refsp; double *alfa = csa->work3; double *h = csa->work3; int i, j, k; /* gamma[i] := eta[i] (or 1, if xB[i] is free) */ for (i = 1; i <= m; i++) { k = head[i]; /* x[k] = xB[i] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif if (type[k] == GLP_FR) gamma[i] = 1.0; else gamma[i] = (refsp[k] ? 1.0 : 0.0); } /* compute columns of the current simplex table */ for (j = 1; j <= n; j++) { k = head[m+j]; /* x[k] = xN[j] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif /* skip column, if xN[j] is not in C */ if (!refsp[k]) continue; #ifdef GLP_DEBUG /* set C must not contain fixed variables */ xassert(type[k] != GLP_FX); #endif /* construct the right-hand side vector h = - N[j] */ for (i = 1; i <= m; i++) h[i] = 0.0; if (k <= m) { /* N[j] is k-th column of submatrix I */ h[k] = -1.0; } else { /* N[j] is (k-m)-th column of submatrix (-A) */ int *A_ptr = csa->A_ptr; int *A_ind = csa->A_ind; double *A_val = csa->A_val; int beg, end, ptr; beg = A_ptr[k-m]; end = A_ptr[k-m+1]; for (ptr = beg; ptr < end; ptr++) h[A_ind[ptr]] = A_val[ptr]; } /* solve system B * alfa = h */ xassert(csa->valid); bfd_ftran(csa->bfd, alfa); /* gamma[i] := gamma[i] + alfa[i,j]^2 */ for (i = 1; i <= m; i++) { k = head[i]; /* x[k] = xB[i] */ if (type[k] != GLP_FR) gamma[i] += alfa[i] * alfa[i]; } } return; } /*********************************************************************** * chuzr - choose basic variable (row of the simplex table) * * This routine chooses basic variable xB[p] having largest weighted * bound violation: * * |r[p]| / sqrt(gamma[p]) = max |r[i]| / sqrt(gamma[i]), * i in I * * / lB[i] - beta[i], if beta[i] < lB[i] * | * r[i] = < 0, if lB[i] <= beta[i] <= uB[i] * | * \ uB[i] - beta[i], if beta[i] > uB[i] * * where beta[i] is primal value of xB[i] in the current basis, lB[i] * and uB[i] are lower and upper bounds of xB[i], I is a subset of * eligible basic variables, which significantly violates their bounds, * gamma[i] is the steepest edge coefficient. * * If |r[i]| is less than a specified tolerance, xB[i] is not included * in I and therefore ignored. * * If I is empty and no variable has been chosen, p is set to 0. */ static void chuzr(struct csa *csa, double tol_bnd) { int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; #endif char *type = csa->type; double *lb = csa->lb; double *ub = csa->ub; int *head = csa->head; double *bbar = csa->bbar; double *gamma = csa->gamma; int i, k, p; double delta, best, eps, ri, temp; /* nothing is chosen so far */ p = 0, delta = 0.0, best = 0.0; /* look through the list of basic variables */ for (i = 1; i <= m; i++) { k = head[i]; /* x[k] = xB[i] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif /* determine bound violation ri[i] */ ri = 0.0; if (type[k] == GLP_LO || type[k] == GLP_DB || type[k] == GLP_FX) { /* xB[i] has lower bound */ eps = tol_bnd * (1.0 + kappa * fabs(lb[k])); if (bbar[i] < lb[k] - eps) { /* and significantly violates it */ ri = lb[k] - bbar[i]; } } if (type[k] == GLP_UP || type[k] == GLP_DB || type[k] == GLP_FX) { /* xB[i] has upper bound */ eps = tol_bnd * (1.0 + kappa * fabs(ub[k])); if (bbar[i] > ub[k] + eps) { /* and significantly violates it */ ri = ub[k] - bbar[i]; } } /* if xB[i] is not eligible, skip it */ if (ri == 0.0) continue; /* xB[i] is eligible basic variable; choose one with largest weighted bound violation */ #ifdef GLP_DEBUG xassert(gamma[i] >= 0.0); #endif temp = gamma[i]; if (temp < DBL_EPSILON) temp = DBL_EPSILON; temp = (ri * ri) / temp; if (best < temp) p = i, delta = ri, best = temp; } /* store the index of basic variable xB[p] chosen and its change in the adjacent basis */ csa->p = p; csa->delta = delta; return; } #if 1 /* copied from primal */ /*********************************************************************** * eval_rho - compute pivot row of the inverse * * This routine computes the pivot (p-th) row of the inverse inv(B), * which corresponds to basic variable xB[p] chosen: * * rho = inv(B') * e[p], * * where B' is a matrix transposed to the current basis matrix, e[p] * is unity vector. */ static void eval_rho(struct csa *csa, double rho[]) { int m = csa->m; int p = csa->p; double *e = rho; int i; #ifdef GLP_DEBUG xassert(1 <= p && p <= m); #endif /* construct the right-hand side vector e[p] */ for (i = 1; i <= m; i++) e[i] = 0.0; e[p] = 1.0; /* solve system B'* rho = e[p] */ xassert(csa->valid); bfd_btran(csa->bfd, rho); return; } #endif #if 1 /* copied from primal */ /*********************************************************************** * refine_rho - refine pivot row of the inverse * * This routine refines the pivot row of the inverse inv(B) assuming * that it was previously computed by the routine eval_rho. */ static void refine_rho(struct csa *csa, double rho[]) { int m = csa->m; int p = csa->p; double *e = csa->work3; int i; #ifdef GLP_DEBUG xassert(1 <= p && p <= m); #endif /* construct the right-hand side vector e[p] */ for (i = 1; i <= m; i++) e[i] = 0.0; e[p] = 1.0; /* refine solution of B'* rho = e[p] */ refine_btran(csa, e, rho); return; } #endif #if 1 /* 06/IV-2009 */ /*********************************************************************** * eval_trow - compute pivot row of the simplex table * * This routine computes the pivot row of the simplex table, which * corresponds to basic variable xB[p] chosen. * * The pivot row is the following vector: * * trow = T'* e[p] = - N'* inv(B') * e[p] = - N' * rho, * * where rho is the pivot row of the inverse inv(B) previously computed * by the routine eval_rho. * * Note that elements of the pivot row corresponding to fixed non-basic * variables are not computed. * * NOTES * * Computing pivot row of the simplex table is one of the most time * consuming operations, and for some instances it may take more than * 50% of the total solution time. * * In the current implementation there are two routines to compute the * pivot row. The routine eval_trow1 computes elements of the pivot row * as inner products of columns of the matrix N and the vector rho; it * is used when the vector rho is relatively dense. The routine * eval_trow2 computes the pivot row as a linear combination of rows of * the matrix N; it is used when the vector rho is relatively sparse. */ static void eval_trow1(struct csa *csa, double rho[]) { int m = csa->m; int n = csa->n; int *A_ptr = csa->A_ptr; int *A_ind = csa->A_ind; double *A_val = csa->A_val; int *head = csa->head; char *stat = csa->stat; int *trow_ind = csa->trow_ind; double *trow_vec = csa->trow_vec; int j, k, beg, end, ptr, nnz; double temp; /* compute the pivot row as inner products of columns of the matrix N and vector rho: trow[j] = - rho * N[j] */ nnz = 0; for (j = 1; j <= n; j++) { if (stat[j] == GLP_NS) { /* xN[j] is fixed */ trow_vec[j] = 0.0; continue; } k = head[m+j]; /* x[k] = xN[j] */ if (k <= m) { /* N[j] is k-th column of submatrix I */ temp = - rho[k]; } else { /* N[j] is (k-m)-th column of submatrix (-A) */ beg = A_ptr[k-m], end = A_ptr[k-m+1]; temp = 0.0; for (ptr = beg; ptr < end; ptr++) temp += rho[A_ind[ptr]] * A_val[ptr]; } if (temp != 0.0) trow_ind[++nnz] = j; trow_vec[j] = temp; } csa->trow_nnz = nnz; return; } static void eval_trow2(struct csa *csa, double rho[]) { int m = csa->m; int n = csa->n; int *AT_ptr = csa->AT_ptr; int *AT_ind = csa->AT_ind; double *AT_val = csa->AT_val; int *bind = csa->bind; char *stat = csa->stat; int *trow_ind = csa->trow_ind; double *trow_vec = csa->trow_vec; int i, j, beg, end, ptr, nnz; double temp; /* clear the pivot row */ for (j = 1; j <= n; j++) trow_vec[j] = 0.0; /* compute the pivot row as a linear combination of rows of the matrix N: trow = - rho[1] * N'[1] - ... - rho[m] * N'[m] */ for (i = 1; i <= m; i++) { temp = rho[i]; if (temp == 0.0) continue; /* trow := trow - rho[i] * N'[i] */ j = bind[i] - m; /* x[i] = xN[j] */ if (j >= 1 && stat[j] != GLP_NS) trow_vec[j] -= temp; beg = AT_ptr[i], end = AT_ptr[i+1]; for (ptr = beg; ptr < end; ptr++) { j = bind[m + AT_ind[ptr]] - m; /* x[k] = xN[j] */ if (j >= 1 && stat[j] != GLP_NS) trow_vec[j] += temp * AT_val[ptr]; } } /* construct sparse pattern of the pivot row */ nnz = 0; for (j = 1; j <= n; j++) { if (trow_vec[j] != 0.0) trow_ind[++nnz] = j; } csa->trow_nnz = nnz; return; } static void eval_trow(struct csa *csa, double rho[]) { int m = csa->m; int i, nnz; double dens; /* determine the density of the vector rho */ nnz = 0; for (i = 1; i <= m; i++) if (rho[i] != 0.0) nnz++; dens = (double)nnz / (double)m; if (dens >= 0.20) { /* rho is relatively dense */ eval_trow1(csa, rho); } else { /* rho is relatively sparse */ eval_trow2(csa, rho); } return; } #endif /*********************************************************************** * sort_trow - sort pivot row of the simplex table * * This routine reorders the list of non-zero elements of the pivot * row to put significant elements, whose magnitude is not less than * a specified tolerance, in front of the list, and stores the number * of significant elements in trow_num. */ static void sort_trow(struct csa *csa, double tol_piv) { #ifdef GLP_DEBUG int n = csa->n; char *stat = csa->stat; #endif int nnz = csa->trow_nnz; int *trow_ind = csa->trow_ind; double *trow_vec = csa->trow_vec; int j, num, pos; double big, eps, temp; /* compute infinity (maximum) norm of the row */ big = 0.0; for (pos = 1; pos <= nnz; pos++) { #ifdef GLP_DEBUG j = trow_ind[pos]; xassert(1 <= j && j <= n); xassert(stat[j] != GLP_NS); #endif temp = fabs(trow_vec[trow_ind[pos]]); if (big < temp) big = temp; } csa->trow_max = big; /* determine absolute pivot tolerance */ eps = tol_piv * (1.0 + 0.01 * big); /* move significant row components to the front of the list */ for (num = 0; num < nnz; ) { j = trow_ind[nnz]; if (fabs(trow_vec[j]) < eps) nnz--; else { num++; trow_ind[nnz] = trow_ind[num]; trow_ind[num] = j; } } csa->trow_num = num; return; } #ifdef GLP_LONG_STEP /* 07/IV-2009 */ static int ls_func(const void *p1_, const void *p2_) { const struct bkpt *p1 = p1_, *p2 = p2_; if (p1->t < p2->t) return -1; if (p1->t > p2->t) return +1; return 0; } static int ls_func1(const void *p1_, const void *p2_) { const struct bkpt *p1 = p1_, *p2 = p2_; if (p1->dz < p2->dz) return -1; if (p1->dz > p2->dz) return +1; return 0; } static void long_step(struct csa *csa) { int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; #endif char *type = csa->type; double *lb = csa->lb; double *ub = csa->ub; int *head = csa->head; char *stat = csa->stat; double *cbar = csa->cbar; double delta = csa->delta; int *trow_ind = csa->trow_ind; double *trow_vec = csa->trow_vec; int trow_num = csa->trow_num; struct bkpt *bkpt = csa->bkpt; int j, k, kk, nbps, pos; double alfa, s, slope, dzmax; /* delta > 0 means that xB[p] violates its lower bound, so to increase the dual objective lambdaB[p] must increase; delta < 0 means that xB[p] violates its upper bound, so to increase the dual objective lambdaB[p] must decrease */ /* s := sign(delta) */ s = (delta > 0.0 ? +1.0 : -1.0); /* determine breakpoints of the dual objective */ nbps = 0; for (pos = 1; pos <= trow_num; pos++) { j = trow_ind[pos]; #ifdef GLP_DEBUG xassert(1 <= j && j <= n); xassert(stat[j] != GLP_NS); #endif /* if there is free non-basic variable, switch to the standard ratio test */ if (stat[j] == GLP_NF) { nbps = 0; goto done; } /* lambdaN[j] = ... - alfa * t - ..., where t = s * lambdaB[i] is the dual ray parameter, t >= 0 */ alfa = s * trow_vec[j]; #ifdef GLP_DEBUG xassert(alfa != 0.0); xassert(stat[j] == GLP_NL || stat[j] == GLP_NU); #endif if (alfa > 0.0 && stat[j] == GLP_NL || alfa < 0.0 && stat[j] == GLP_NU) { /* either lambdaN[j] >= 0 (if stat = GLP_NL) and decreases or lambdaN[j] <= 0 (if stat = GLP_NU) and increases; in both cases we have a breakpoint */ nbps++; #ifdef GLP_DEBUG xassert(nbps <= n); #endif bkpt[nbps].j = j; bkpt[nbps].t = cbar[j] / alfa; /* if (stat[j] == GLP_NL && cbar[j] < 0.0 || stat[j] == GLP_NU && cbar[j] > 0.0) xprintf("%d %g\n", stat[j], cbar[j]); */ /* if t is negative, replace it by exact zero (see comments in the routine chuzc) */ if (bkpt[nbps].t < 0.0) bkpt[nbps].t = 0.0; } } /* if there are less than two breakpoints, switch to the standard ratio test */ if (nbps < 2) { nbps = 0; goto done; } /* sort breakpoints by ascending the dual ray parameter, t */ qsort(&bkpt[1], nbps, sizeof(struct bkpt), ls_func); /* determine last breakpoint, at which the dual objective still greater than at t = 0 */ dzmax = 0.0; slope = fabs(delta); /* initial slope */ for (kk = 1; kk <= nbps; kk++) { if (kk == 1) bkpt[kk].dz = 0.0 + slope * (bkpt[kk].t - 0.0); else bkpt[kk].dz = bkpt[kk-1].dz + slope * (bkpt[kk].t - bkpt[kk-1].t); if (dzmax < bkpt[kk].dz) dzmax = bkpt[kk].dz; else if (bkpt[kk].dz < 0.05 * (1.0 + dzmax)) { nbps = kk - 1; break; } j = bkpt[kk].j; k = head[m+j]; /* x[k] = xN[j] */ if (type[k] == GLP_DB) slope -= fabs(trow_vec[j]) * (ub[k] - lb[k]); else { nbps = kk; break; } } /* if there are less than two breakpoints, switch to the standard ratio test */ if (nbps < 2) { nbps = 0; goto done; } /* sort breakpoints by ascending the dual change, dz */ qsort(&bkpt[1], nbps, sizeof(struct bkpt), ls_func1); /* for (kk = 1; kk <= nbps; kk++) xprintf("%d; t = %g; dz = %g\n", kk, bkpt[kk].t, bkpt[kk].dz); */ done: csa->nbps = nbps; return; } #endif /*********************************************************************** * chuzc - choose non-basic variable (column of the simplex table) * * This routine chooses non-basic variable xN[q], which being entered * in the basis keeps dual feasibility of the basic solution. * * The parameter rtol is a relative tolerance used to relax zero bounds * of reduced costs of non-basic variables. If rtol = 0, the routine * implements the standard ratio test. Otherwise, if rtol > 0, the * routine implements Harris' two-pass ratio test. In the latter case * rtol should be about three times less than a tolerance used to check * dual feasibility. */ static void chuzc(struct csa *csa, double rtol) { #ifdef GLP_DEBUG int m = csa->m; int n = csa->n; #endif char *stat = csa->stat; double *cbar = csa->cbar; #ifdef GLP_DEBUG int p = csa->p; #endif double delta = csa->delta; int *trow_ind = csa->trow_ind; double *trow_vec = csa->trow_vec; int trow_num = csa->trow_num; int j, pos, q; double alfa, big, s, t, teta, tmax; #ifdef GLP_DEBUG xassert(1 <= p && p <= m); #endif /* delta > 0 means that xB[p] violates its lower bound and goes to it in the adjacent basis, so lambdaB[p] is increasing from its lower zero bound; delta < 0 means that xB[p] violates its upper bound and goes to it in the adjacent basis, so lambdaB[p] is decreasing from its upper zero bound */ #ifdef GLP_DEBUG xassert(delta != 0.0); #endif /* s := sign(delta) */ s = (delta > 0.0 ? +1.0 : -1.0); /*** FIRST PASS ***/ /* nothing is chosen so far */ q = 0, teta = DBL_MAX, big = 0.0; /* walk through significant elements of the pivot row */ for (pos = 1; pos <= trow_num; pos++) { j = trow_ind[pos]; #ifdef GLP_DEBUG xassert(1 <= j && j <= n); #endif alfa = s * trow_vec[j]; #ifdef GLP_DEBUG xassert(alfa != 0.0); #endif /* lambdaN[j] = ... - alfa * lambdaB[p] - ..., and due to s we need to consider only increasing lambdaB[p] */ if (alfa > 0.0) { /* lambdaN[j] is decreasing */ if (stat[j] == GLP_NL || stat[j] == GLP_NF) { /* lambdaN[j] has zero lower bound */ t = (cbar[j] + rtol) / alfa; } else { /* lambdaN[j] has no lower bound */ continue; } } else { /* lambdaN[j] is increasing */ if (stat[j] == GLP_NU || stat[j] == GLP_NF) { /* lambdaN[j] has zero upper bound */ t = (cbar[j] - rtol) / alfa; } else { /* lambdaN[j] has no upper bound */ continue; } } /* t is a change of lambdaB[p], on which lambdaN[j] reaches its zero bound (possibly relaxed); since the basic solution is assumed to be dual feasible, t has to be non-negative by definition; however, it may happen that lambdaN[j] slightly (i.e. within a tolerance) violates its zero bound, that leads to negative t; in the latter case, if xN[j] is chosen, negative t means that lambdaB[p] changes in wrong direction that may cause wrong results on updating reduced costs; thus, if t is negative, we should replace it by exact zero assuming that lambdaN[j] is exactly on its zero bound, and violation appears due to round-off errors */ if (t < 0.0) t = 0.0; /* apply minimal ratio test */ if (teta > t || teta == t && big < fabs(alfa)) q = j, teta = t, big = fabs(alfa); } /* the second pass is skipped in the following cases: */ /* if the standard ratio test is used */ if (rtol == 0.0) goto done; /* if no non-basic variable has been chosen on the first pass */ if (q == 0) goto done; /* if lambdaN[q] prevents lambdaB[p] from any change */ if (teta == 0.0) goto done; /*** SECOND PASS ***/ /* here tmax is a maximal change of lambdaB[p], on which the solution remains dual feasible within a tolerance */ #if 0 tmax = (1.0 + 10.0 * DBL_EPSILON) * teta; #else tmax = teta; #endif /* nothing is chosen so far */ q = 0, teta = DBL_MAX, big = 0.0; /* walk through significant elements of the pivot row */ for (pos = 1; pos <= trow_num; pos++) { j = trow_ind[pos]; #ifdef GLP_DEBUG xassert(1 <= j && j <= n); #endif alfa = s * trow_vec[j]; #ifdef GLP_DEBUG xassert(alfa != 0.0); #endif /* lambdaN[j] = ... - alfa * lambdaB[p] - ..., and due to s we need to consider only increasing lambdaB[p] */ if (alfa > 0.0) { /* lambdaN[j] is decreasing */ if (stat[j] == GLP_NL || stat[j] == GLP_NF) { /* lambdaN[j] has zero lower bound */ t = cbar[j] / alfa; } else { /* lambdaN[j] has no lower bound */ continue; } } else { /* lambdaN[j] is increasing */ if (stat[j] == GLP_NU || stat[j] == GLP_NF) { /* lambdaN[j] has zero upper bound */ t = cbar[j] / alfa; } else { /* lambdaN[j] has no upper bound */ continue; } } /* (see comments for the first pass) */ if (t < 0.0) t = 0.0; /* t is a change of lambdaB[p], on which lambdaN[j] reaches its zero (lower or upper) bound; if t <= tmax, all reduced costs can violate their zero bounds only within relaxation tolerance rtol, so we can choose non-basic variable having largest influence coefficient to avoid possible numerical instability */ if (t <= tmax && big < fabs(alfa)) q = j, teta = t, big = fabs(alfa); } /* something must be chosen on the second pass */ xassert(q != 0); done: /* store the index of non-basic variable xN[q] chosen */ csa->q = q; /* store reduced cost of xN[q] in the adjacent basis */ csa->new_dq = s * teta; return; } #if 1 /* copied from primal */ /*********************************************************************** * eval_tcol - compute pivot column of the simplex table * * This routine computes the pivot column of the simplex table, which * corresponds to non-basic variable xN[q] chosen. * * The pivot column is the following vector: * * tcol = T * e[q] = - inv(B) * N * e[q] = - inv(B) * N[q], * * where B is the current basis matrix, N[q] is a column of the matrix * (I|-A) corresponding to variable xN[q]. */ static void eval_tcol(struct csa *csa) { int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; #endif int *head = csa->head; int q = csa->q; int *tcol_ind = csa->tcol_ind; double *tcol_vec = csa->tcol_vec; double *h = csa->tcol_vec; int i, k, nnz; #ifdef GLP_DEBUG xassert(1 <= q && q <= n); #endif k = head[m+q]; /* x[k] = xN[q] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif /* construct the right-hand side vector h = - N[q] */ for (i = 1; i <= m; i++) h[i] = 0.0; if (k <= m) { /* N[q] is k-th column of submatrix I */ h[k] = -1.0; } else { /* N[q] is (k-m)-th column of submatrix (-A) */ int *A_ptr = csa->A_ptr; int *A_ind = csa->A_ind; double *A_val = csa->A_val; int beg, end, ptr; beg = A_ptr[k-m]; end = A_ptr[k-m+1]; for (ptr = beg; ptr < end; ptr++) h[A_ind[ptr]] = A_val[ptr]; } /* solve system B * tcol = h */ xassert(csa->valid); bfd_ftran(csa->bfd, tcol_vec); /* construct sparse pattern of the pivot column */ nnz = 0; for (i = 1; i <= m; i++) { if (tcol_vec[i] != 0.0) tcol_ind[++nnz] = i; } csa->tcol_nnz = nnz; return; } #endif #if 1 /* copied from primal */ /*********************************************************************** * refine_tcol - refine pivot column of the simplex table * * This routine refines the pivot column of the simplex table assuming * that it was previously computed by the routine eval_tcol. */ static void refine_tcol(struct csa *csa) { int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; #endif int *head = csa->head; int q = csa->q; int *tcol_ind = csa->tcol_ind; double *tcol_vec = csa->tcol_vec; double *h = csa->work3; int i, k, nnz; #ifdef GLP_DEBUG xassert(1 <= q && q <= n); #endif k = head[m+q]; /* x[k] = xN[q] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif /* construct the right-hand side vector h = - N[q] */ for (i = 1; i <= m; i++) h[i] = 0.0; if (k <= m) { /* N[q] is k-th column of submatrix I */ h[k] = -1.0; } else { /* N[q] is (k-m)-th column of submatrix (-A) */ int *A_ptr = csa->A_ptr; int *A_ind = csa->A_ind; double *A_val = csa->A_val; int beg, end, ptr; beg = A_ptr[k-m]; end = A_ptr[k-m+1]; for (ptr = beg; ptr < end; ptr++) h[A_ind[ptr]] = A_val[ptr]; } /* refine solution of B * tcol = h */ refine_ftran(csa, h, tcol_vec); /* construct sparse pattern of the pivot column */ nnz = 0; for (i = 1; i <= m; i++) { if (tcol_vec[i] != 0.0) tcol_ind[++nnz] = i; } csa->tcol_nnz = nnz; return; } #endif /*********************************************************************** * update_cbar - update reduced costs of non-basic variables * * This routine updates reduced costs of all (except fixed) non-basic * variables for the adjacent basis. */ static void update_cbar(struct csa *csa) { #ifdef GLP_DEBUG int n = csa->n; #endif double *cbar = csa->cbar; int trow_nnz = csa->trow_nnz; int *trow_ind = csa->trow_ind; double *trow_vec = csa->trow_vec; int q = csa->q; double new_dq = csa->new_dq; int j, pos; #ifdef GLP_DEBUG xassert(1 <= q && q <= n); #endif /* set new reduced cost of xN[q] */ cbar[q] = new_dq; /* update reduced costs of other non-basic variables */ if (new_dq == 0.0) goto done; for (pos = 1; pos <= trow_nnz; pos++) { j = trow_ind[pos]; #ifdef GLP_DEBUG xassert(1 <= j && j <= n); #endif if (j != q) cbar[j] -= trow_vec[j] * new_dq; } done: return; } /*********************************************************************** * update_bbar - update values of basic variables * * This routine updates values of all basic variables for the adjacent * basis. */ static void update_bbar(struct csa *csa) { #ifdef GLP_DEBUG int m = csa->m; int n = csa->n; #endif double *bbar = csa->bbar; int p = csa->p; double delta = csa->delta; int q = csa->q; int tcol_nnz = csa->tcol_nnz; int *tcol_ind = csa->tcol_ind; double *tcol_vec = csa->tcol_vec; int i, pos; double teta; #ifdef GLP_DEBUG xassert(1 <= p && p <= m); xassert(1 <= q && q <= n); #endif /* determine the change of xN[q] in the adjacent basis */ #ifdef GLP_DEBUG xassert(tcol_vec[p] != 0.0); #endif teta = delta / tcol_vec[p]; /* set new primal value of xN[q] */ bbar[p] = get_xN(csa, q) + teta; /* update primal values of other basic variables */ if (teta == 0.0) goto done; for (pos = 1; pos <= tcol_nnz; pos++) { i = tcol_ind[pos]; #ifdef GLP_DEBUG xassert(1 <= i && i <= m); #endif if (i != p) bbar[i] += tcol_vec[i] * teta; } done: return; } /*********************************************************************** * update_gamma - update steepest edge coefficients * * This routine updates steepest-edge coefficients for the adjacent * basis. */ static void update_gamma(struct csa *csa) { int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; #endif char *type = csa->type; int *head = csa->head; char *refsp = csa->refsp; double *gamma = csa->gamma; int p = csa->p; int trow_nnz = csa->trow_nnz; int *trow_ind = csa->trow_ind; double *trow_vec = csa->trow_vec; int q = csa->q; int tcol_nnz = csa->tcol_nnz; int *tcol_ind = csa->tcol_ind; double *tcol_vec = csa->tcol_vec; double *u = csa->work3; int i, j, k,pos; double gamma_p, eta_p, pivot, t, t1, t2; #ifdef GLP_DEBUG xassert(1 <= p && p <= m); xassert(1 <= q && q <= n); #endif /* the basis changes, so decrease the count */ xassert(csa->refct > 0); csa->refct--; /* recompute gamma[p] for the current basis more accurately and compute auxiliary vector u */ #ifdef GLP_DEBUG xassert(type[head[p]] != GLP_FR); #endif gamma_p = eta_p = (refsp[head[p]] ? 1.0 : 0.0); for (i = 1; i <= m; i++) u[i] = 0.0; for (pos = 1; pos <= trow_nnz; pos++) { j = trow_ind[pos]; #ifdef GLP_DEBUG xassert(1 <= j && j <= n); #endif k = head[m+j]; /* x[k] = xN[j] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); xassert(type[k] != GLP_FX); #endif if (!refsp[k]) continue; t = trow_vec[j]; gamma_p += t * t; /* u := u + N[j] * delta[j] * trow[j] */ if (k <= m) { /* N[k] = k-j stolbec submatrix I */ u[k] += t; } else { /* N[k] = k-m-k stolbec (-A) */ int *A_ptr = csa->A_ptr; int *A_ind = csa->A_ind; double *A_val = csa->A_val; int beg, end, ptr; beg = A_ptr[k-m]; end = A_ptr[k-m+1]; for (ptr = beg; ptr < end; ptr++) u[A_ind[ptr]] -= t * A_val[ptr]; } } xassert(csa->valid); bfd_ftran(csa->bfd, u); /* update gamma[i] for other basic variables (except xB[p] and free variables) */ pivot = tcol_vec[p]; #ifdef GLP_DEBUG xassert(pivot != 0.0); #endif for (pos = 1; pos <= tcol_nnz; pos++) { i = tcol_ind[pos]; #ifdef GLP_DEBUG xassert(1 <= i && i <= m); #endif k = head[i]; #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif /* skip xB[p] */ if (i == p) continue; /* skip free basic variable */ if (type[head[i]] == GLP_FR) { #ifdef GLP_DEBUG xassert(gamma[i] == 1.0); #endif continue; } /* compute gamma[i] for the adjacent basis */ t = tcol_vec[i] / pivot; t1 = gamma[i] + t * t * gamma_p + 2.0 * t * u[i]; t2 = (refsp[k] ? 1.0 : 0.0) + eta_p * t * t; gamma[i] = (t1 >= t2 ? t1 : t2); /* (though gamma[i] can be exact zero, because the reference space does not include non-basic fixed variables) */ if (gamma[i] < DBL_EPSILON) gamma[i] = DBL_EPSILON; } /* compute gamma[p] for the adjacent basis */ if (type[head[m+q]] == GLP_FR) gamma[p] = 1.0; else { gamma[p] = gamma_p / (pivot * pivot); if (gamma[p] < DBL_EPSILON) gamma[p] = DBL_EPSILON; } /* if xB[p], which becomes xN[q] in the adjacent basis, is fixed and belongs to the reference space, remove it from there, and change all gamma's appropriately */ k = head[p]; if (type[k] == GLP_FX && refsp[k]) { refsp[k] = 0; for (pos = 1; pos <= tcol_nnz; pos++) { i = tcol_ind[pos]; if (i == p) { if (type[head[m+q]] == GLP_FR) continue; t = 1.0 / tcol_vec[p]; } else { if (type[head[i]] == GLP_FR) continue; t = tcol_vec[i] / tcol_vec[p]; } gamma[i] -= t * t; if (gamma[i] < DBL_EPSILON) gamma[i] = DBL_EPSILON; } } return; } #if 1 /* copied from primal */ /*********************************************************************** * err_in_bbar - compute maximal relative error in primal solution * * This routine returns maximal relative error: * * max |beta[i] - bbar[i]| / (1 + |beta[i]|), * * where beta and bbar are, respectively, directly computed and the * current (updated) values of basic variables. * * NOTE: The routine is intended only for debugginig purposes. */ static double err_in_bbar(struct csa *csa) { int m = csa->m; double *bbar = csa->bbar; int i; double e, emax, *beta; beta = xcalloc(1+m, sizeof(double)); eval_beta(csa, beta); emax = 0.0; for (i = 1; i <= m; i++) { e = fabs(beta[i] - bbar[i]) / (1.0 + fabs(beta[i])); if (emax < e) emax = e; } xfree(beta); return emax; } #endif #if 1 /* copied from primal */ /*********************************************************************** * err_in_cbar - compute maximal relative error in dual solution * * This routine returns maximal relative error: * * max |cost[j] - cbar[j]| / (1 + |cost[j]|), * * where cost and cbar are, respectively, directly computed and the * current (updated) reduced costs of non-basic non-fixed variables. * * NOTE: The routine is intended only for debugginig purposes. */ static double err_in_cbar(struct csa *csa) { int m = csa->m; int n = csa->n; char *stat = csa->stat; double *cbar = csa->cbar; int j; double e, emax, cost, *pi; pi = xcalloc(1+m, sizeof(double)); eval_pi(csa, pi); emax = 0.0; for (j = 1; j <= n; j++) { if (stat[j] == GLP_NS) continue; cost = eval_cost(csa, pi, j); e = fabs(cost - cbar[j]) / (1.0 + fabs(cost)); if (emax < e) emax = e; } xfree(pi); return emax; } #endif /*********************************************************************** * err_in_gamma - compute maximal relative error in steepest edge cff. * * This routine returns maximal relative error: * * max |gamma'[j] - gamma[j]| / (1 + |gamma'[j]), * * where gamma'[j] and gamma[j] are, respectively, directly computed * and the current (updated) steepest edge coefficients for non-basic * non-fixed variable x[j]. * * NOTE: The routine is intended only for debugginig purposes. */ static double err_in_gamma(struct csa *csa) { int m = csa->m; char *type = csa->type; int *head = csa->head; double *gamma = csa->gamma; double *exact = csa->work4; int i; double e, emax, temp; eval_gamma(csa, exact); emax = 0.0; for (i = 1; i <= m; i++) { if (type[head[i]] == GLP_FR) { xassert(gamma[i] == 1.0); xassert(exact[i] == 1.0); continue; } temp = exact[i]; e = fabs(temp - gamma[i]) / (1.0 + fabs(temp)); if (emax < e) emax = e; } return emax; } /*********************************************************************** * change_basis - change basis header * * This routine changes the basis header to make it corresponding to * the adjacent basis. */ static void change_basis(struct csa *csa) { int m = csa->m; #ifdef GLP_DEBUG int n = csa->n; #endif char *type = csa->type; int *head = csa->head; #if 1 /* 06/IV-2009 */ int *bind = csa->bind; #endif char *stat = csa->stat; int p = csa->p; double delta = csa->delta; int q = csa->q; int k; /* xB[p] leaves the basis, xN[q] enters the basis */ #ifdef GLP_DEBUG xassert(1 <= p && p <= m); xassert(1 <= q && q <= n); #endif /* xB[p] <-> xN[q] */ k = head[p], head[p] = head[m+q], head[m+q] = k; #if 1 /* 06/IV-2009 */ bind[head[p]] = p, bind[head[m+q]] = m + q; #endif if (type[k] == GLP_FX) stat[q] = GLP_NS; else if (delta > 0.0) { #ifdef GLP_DEBUG xassert(type[k] == GLP_LO || type[k] == GLP_DB); #endif stat[q] = GLP_NL; } else /* delta < 0.0 */ { #ifdef GLP_DEBUG xassert(type[k] == GLP_UP || type[k] == GLP_DB); #endif stat[q] = GLP_NU; } return; } /*********************************************************************** * check_feas - check dual feasibility of basic solution * * If the current basic solution is dual feasible within a tolerance, * this routine returns zero, otherwise it returns non-zero. */ static int check_feas(struct csa *csa, double tol_dj) { int m = csa->m; int n = csa->n; char *orig_type = csa->orig_type; int *head = csa->head; double *cbar = csa->cbar; int j, k; for (j = 1; j <= n; j++) { k = head[m+j]; /* x[k] = xN[j] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif if (cbar[j] < - tol_dj) if (orig_type[k] == GLP_LO || orig_type[k] == GLP_FR) return 1; if (cbar[j] > + tol_dj) if (orig_type[k] == GLP_UP || orig_type[k] == GLP_FR) return 1; } return 0; } /*********************************************************************** * set_aux_bnds - assign auxiliary bounds to variables * * This routine assigns auxiliary bounds to variables to construct an * LP problem solved on phase I. */ static void set_aux_bnds(struct csa *csa) { int m = csa->m; int n = csa->n; char *type = csa->type; double *lb = csa->lb; double *ub = csa->ub; char *orig_type = csa->orig_type; int *head = csa->head; char *stat = csa->stat; double *cbar = csa->cbar; int j, k; for (k = 1; k <= m+n; k++) { switch (orig_type[k]) { case GLP_FR: #if 0 type[k] = GLP_DB, lb[k] = -1.0, ub[k] = +1.0; #else /* to force free variables to enter the basis */ type[k] = GLP_DB, lb[k] = -1e3, ub[k] = +1e3; #endif break; case GLP_LO: type[k] = GLP_DB, lb[k] = 0.0, ub[k] = +1.0; break; case GLP_UP: type[k] = GLP_DB, lb[k] = -1.0, ub[k] = 0.0; break; case GLP_DB: case GLP_FX: type[k] = GLP_FX, lb[k] = ub[k] = 0.0; break; default: xassert(orig_type != orig_type); } } for (j = 1; j <= n; j++) { k = head[m+j]; /* x[k] = xN[j] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif if (type[k] == GLP_FX) stat[j] = GLP_NS; else if (cbar[j] >= 0.0) stat[j] = GLP_NL; else stat[j] = GLP_NU; } return; } /*********************************************************************** * set_orig_bnds - restore original bounds of variables * * This routine restores original types and bounds of variables and * determines statuses of non-basic variables assuming that the current * basis is dual feasible. */ static void set_orig_bnds(struct csa *csa) { int m = csa->m; int n = csa->n; char *type = csa->type; double *lb = csa->lb; double *ub = csa->ub; char *orig_type = csa->orig_type; double *orig_lb = csa->orig_lb; double *orig_ub = csa->orig_ub; int *head = csa->head; char *stat = csa->stat; double *cbar = csa->cbar; int j, k; memcpy(&type[1], &orig_type[1], (m+n) * sizeof(char)); memcpy(&lb[1], &orig_lb[1], (m+n) * sizeof(double)); memcpy(&ub[1], &orig_ub[1], (m+n) * sizeof(double)); for (j = 1; j <= n; j++) { k = head[m+j]; /* x[k] = xN[j] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif switch (type[k]) { case GLP_FR: stat[j] = GLP_NF; break; case GLP_LO: stat[j] = GLP_NL; break; case GLP_UP: stat[j] = GLP_NU; break; case GLP_DB: if (cbar[j] >= +DBL_EPSILON) stat[j] = GLP_NL; else if (cbar[j] <= -DBL_EPSILON) stat[j] = GLP_NU; else if (fabs(lb[k]) <= fabs(ub[k])) stat[j] = GLP_NL; else stat[j] = GLP_NU; break; case GLP_FX: stat[j] = GLP_NS; break; default: xassert(type != type); } } return; } /*********************************************************************** * check_stab - check numerical stability of basic solution * * If the current basic solution is dual feasible within a tolerance, * this routine returns zero, otherwise it returns non-zero. */ static int check_stab(struct csa *csa, double tol_dj) { int n = csa->n; char *stat = csa->stat; double *cbar = csa->cbar; int j; for (j = 1; j <= n; j++) { if (cbar[j] < - tol_dj) if (stat[j] == GLP_NL || stat[j] == GLP_NF) return 1; if (cbar[j] > + tol_dj) if (stat[j] == GLP_NU || stat[j] == GLP_NF) return 1; } return 0; } #if 1 /* copied from primal */ /*********************************************************************** * eval_obj - compute original objective function * * This routine computes the current value of the original objective * function. */ static double eval_obj(struct csa *csa) { int m = csa->m; int n = csa->n; double *obj = csa->obj; int *head = csa->head; double *bbar = csa->bbar; int i, j, k; double sum; sum = obj[0]; /* walk through the list of basic variables */ for (i = 1; i <= m; i++) { k = head[i]; /* x[k] = xB[i] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif if (k > m) sum += obj[k-m] * bbar[i]; } /* walk through the list of non-basic variables */ for (j = 1; j <= n; j++) { k = head[m+j]; /* x[k] = xN[j] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif if (k > m) sum += obj[k-m] * get_xN(csa, j); } return sum; } #endif /*********************************************************************** * display - display the search progress * * This routine displays some information about the search progress. */ static void display(struct csa *csa, const glp_smcp *parm, int spec) { int m = csa->m; int n = csa->n; double *coef = csa->coef; char *orig_type = csa->orig_type; int *head = csa->head; char *stat = csa->stat; int phase = csa->phase; double *bbar = csa->bbar; double *cbar = csa->cbar; int i, j, cnt; double sum; if (parm->msg_lev < GLP_MSG_ON) goto skip; if (parm->out_dly > 0 && 1000.0 * xdifftime(xtime(), csa->tm_beg) < parm->out_dly) goto skip; if (csa->it_cnt == csa->it_dpy) goto skip; if (!spec && csa->it_cnt % parm->out_frq != 0) goto skip; /* compute the sum of dual infeasibilities */ sum = 0.0; if (phase == 1) { for (i = 1; i <= m; i++) sum -= coef[head[i]] * bbar[i]; for (j = 1; j <= n; j++) sum -= coef[head[m+j]] * get_xN(csa, j); } else { for (j = 1; j <= n; j++) { if (cbar[j] < 0.0) if (stat[j] == GLP_NL || stat[j] == GLP_NF) sum -= cbar[j]; if (cbar[j] > 0.0) if (stat[j] == GLP_NU || stat[j] == GLP_NF) sum += cbar[j]; } } /* determine the number of basic fixed variables */ cnt = 0; for (i = 1; i <= m; i++) if (orig_type[head[i]] == GLP_FX) cnt++; if (csa->phase == 1) xprintf(" %6d: %24s infeas = %10.3e (%d)\n", csa->it_cnt, "", sum, cnt); else xprintf("|%6d: obj = %17.9e infeas = %10.3e (%d)\n", csa->it_cnt, eval_obj(csa), sum, cnt); csa->it_dpy = csa->it_cnt; skip: return; } #if 1 /* copied from primal */ /*********************************************************************** * store_sol - store basic solution back to the problem object * * This routine stores basic solution components back to the problem * object. */ static void store_sol(struct csa *csa, glp_prob *lp, int p_stat, int d_stat, int ray) { int m = csa->m; int n = csa->n; double zeta = csa->zeta; int *head = csa->head; char *stat = csa->stat; double *bbar = csa->bbar; double *cbar = csa->cbar; int i, j, k; #ifdef GLP_DEBUG xassert(lp->m == m); xassert(lp->n == n); #endif /* basis factorization */ #ifdef GLP_DEBUG xassert(!lp->valid && lp->bfd == NULL); xassert(csa->valid && csa->bfd != NULL); #endif lp->valid = 1, csa->valid = 0; lp->bfd = csa->bfd, csa->bfd = NULL; memcpy(&lp->head[1], &head[1], m * sizeof(int)); /* basic solution status */ lp->pbs_stat = p_stat; lp->dbs_stat = d_stat; /* objective function value */ lp->obj_val = eval_obj(csa); /* simplex iteration count */ lp->it_cnt = csa->it_cnt; /* unbounded ray */ lp->some = ray; /* basic variables */ for (i = 1; i <= m; i++) { k = head[i]; /* x[k] = xB[i] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif if (k <= m) { GLPROW *row = lp->row[k]; row->stat = GLP_BS; row->bind = i; row->prim = bbar[i] / row->rii; row->dual = 0.0; } else { GLPCOL *col = lp->col[k-m]; col->stat = GLP_BS; col->bind = i; col->prim = bbar[i] * col->sjj; col->dual = 0.0; } } /* non-basic variables */ for (j = 1; j <= n; j++) { k = head[m+j]; /* x[k] = xN[j] */ #ifdef GLP_DEBUG xassert(1 <= k && k <= m+n); #endif if (k <= m) { GLPROW *row = lp->row[k]; row->stat = stat[j]; row->bind = 0; #if 0 row->prim = get_xN(csa, j) / row->rii; #else switch (stat[j]) { case GLP_NL: row->prim = row->lb; break; case GLP_NU: row->prim = row->ub; break; case GLP_NF: row->prim = 0.0; break; case GLP_NS: row->prim = row->lb; break; default: xassert(stat != stat); } #endif row->dual = (cbar[j] * row->rii) / zeta; } else { GLPCOL *col = lp->col[k-m]; col->stat = stat[j]; col->bind = 0; #if 0 col->prim = get_xN(csa, j) * col->sjj; #else switch (stat[j]) { case GLP_NL: col->prim = col->lb; break; case GLP_NU: col->prim = col->ub; break; case GLP_NF: col->prim = 0.0; break; case GLP_NS: col->prim = col->lb; break; default: xassert(stat != stat); } #endif col->dual = (cbar[j] / col->sjj) / zeta; } } return; } #endif /*********************************************************************** * free_csa - deallocate common storage area * * This routine frees all the memory allocated to arrays in the common * storage area (CSA). */ static void free_csa(struct csa *csa) { xfree(csa->type); xfree(csa->lb); xfree(csa->ub); xfree(csa->coef); xfree(csa->orig_type); xfree(csa->orig_lb); xfree(csa->orig_ub); xfree(csa->obj); xfree(csa->A_ptr); xfree(csa->A_ind); xfree(csa->A_val); #if 1 /* 06/IV-2009 */ xfree(csa->AT_ptr); xfree(csa->AT_ind); xfree(csa->AT_val); #endif xfree(csa->head); #if 1 /* 06/IV-2009 */ xfree(csa->bind); #endif xfree(csa->stat); #if 0 /* 06/IV-2009 */ xfree(csa->N_ptr); xfree(csa->N_len); xfree(csa->N_ind); xfree(csa->N_val); #endif xfree(csa->bbar); xfree(csa->cbar); xfree(csa->refsp); xfree(csa->gamma); xfree(csa->trow_ind); xfree(csa->trow_vec); #ifdef GLP_LONG_STEP /* 07/IV-2009 */ xfree(csa->bkpt); #endif xfree(csa->tcol_ind); xfree(csa->tcol_vec); xfree(csa->work1); xfree(csa->work2); xfree(csa->work3); xfree(csa->work4); xfree(csa); return; } /*********************************************************************** * spx_dual - core LP solver based on the dual simplex method * * SYNOPSIS * * #include "glpspx.h" * int spx_dual(glp_prob *lp, const glp_smcp *parm); * * DESCRIPTION * * The routine spx_dual is a core LP solver based on the two-phase dual * simplex method. * * RETURNS * * 0 LP instance has been successfully solved. * * GLP_EOBJLL * Objective lower limit has been reached (maximization). * * GLP_EOBJUL * Objective upper limit has been reached (minimization). * * GLP_EITLIM * Iteration limit has been exhausted. * * GLP_ETMLIM * Time limit has been exhausted. * * GLP_EFAIL * The solver failed to solve LP instance. */ int spx_dual(glp_prob *lp, const glp_smcp *parm) { struct csa *csa; int binv_st = 2; /* status of basis matrix factorization: 0 - invalid; 1 - just computed; 2 - updated */ int bbar_st = 0; /* status of primal values of basic variables: 0 - invalid; 1 - just computed; 2 - updated */ int cbar_st = 0; /* status of reduced costs of non-basic variables: 0 - invalid; 1 - just computed; 2 - updated */ int rigorous = 0; /* rigorous mode flag; this flag is used to enable iterative refinement on computing pivot rows and columns of the simplex table */ int check = 0; int p_stat, d_stat, ret; /* allocate and initialize the common storage area */ csa = alloc_csa(lp); init_csa(csa, lp); if (parm->msg_lev >= GLP_MSG_DBG) xprintf("Objective scale factor = %g\n", csa->zeta); loop: /* main loop starts here */ /* compute factorization of the basis matrix */ if (binv_st == 0) { ret = invert_B(csa); if (ret != 0) { if (parm->msg_lev >= GLP_MSG_ERR) { xprintf("Error: unable to factorize the basis matrix (%d" ")\n", ret); xprintf("Sorry, basis recovery procedure not implemented" " yet\n"); } xassert(!lp->valid && lp->bfd == NULL); lp->bfd = csa->bfd, csa->bfd = NULL; lp->pbs_stat = lp->dbs_stat = GLP_UNDEF; lp->obj_val = 0.0; lp->it_cnt = csa->it_cnt; lp->some = 0; ret = GLP_EFAIL; goto done; } csa->valid = 1; binv_st = 1; /* just computed */ /* invalidate basic solution components */ bbar_st = cbar_st = 0; } /* compute reduced costs of non-basic variables */ if (cbar_st == 0) { eval_cbar(csa); cbar_st = 1; /* just computed */ /* determine the search phase, if not determined yet */ if (csa->phase == 0) { if (check_feas(csa, 0.90 * parm->tol_dj) != 0) { /* current basic solution is dual infeasible */ /* start searching for dual feasible solution */ csa->phase = 1; set_aux_bnds(csa); } else { /* current basic solution is dual feasible */ /* start searching for optimal solution */ csa->phase = 2; set_orig_bnds(csa); } xassert(check_stab(csa, parm->tol_dj) == 0); /* some non-basic double-bounded variables might become fixed (on phase I) or vice versa (on phase II) */ #if 0 /* 06/IV-2009 */ build_N(csa); #endif csa->refct = 0; /* bounds of non-basic variables have been changed, so invalidate primal values */ bbar_st = 0; } /* make sure that the current basic solution remains dual feasible */ if (check_stab(csa, parm->tol_dj) != 0) { if (parm->msg_lev >= GLP_MSG_ERR) xprintf("Warning: numerical instability (dual simplex, p" "hase %s)\n", csa->phase == 1 ? "I" : "II"); #if 1 if (parm->meth == GLP_DUALP) { store_sol(csa, lp, GLP_UNDEF, GLP_UNDEF, 0); ret = GLP_EFAIL; goto done; } #endif /* restart the search */ csa->phase = 0; binv_st = 0; rigorous = 5; goto loop; } } xassert(csa->phase == 1 || csa->phase == 2); /* on phase I we do not need to wait until the current basic solution becomes primal feasible; it is sufficient to make sure that all reduced costs have correct signs */ if (csa->phase == 1 && check_feas(csa, parm->tol_dj) == 0) { /* the current basis is dual feasible; switch to phase II */ display(csa, parm, 1); csa->phase = 2; if (cbar_st != 1) { eval_cbar(csa); cbar_st = 1; } set_orig_bnds(csa); #if 0 /* 06/IV-2009 */ build_N(csa); #endif csa->refct = 0; bbar_st = 0; } /* compute primal values of basic variables */ if (bbar_st == 0) { eval_bbar(csa); if (csa->phase == 2) csa->bbar[0] = eval_obj(csa); bbar_st = 1; /* just computed */ } /* redefine the reference space, if required */ switch (parm->pricing) { case GLP_PT_STD: break; case GLP_PT_PSE: if (csa->refct == 0) reset_refsp(csa); break; default: xassert(parm != parm); } /* at this point the basis factorization and all basic solution components are valid */ xassert(binv_st && bbar_st && cbar_st); /* check accuracy of current basic solution components (only for debugging) */ if (check) { double e_bbar = err_in_bbar(csa); double e_cbar = err_in_cbar(csa); double e_gamma = (parm->pricing == GLP_PT_PSE ? err_in_gamma(csa) : 0.0); xprintf("e_bbar = %10.3e; e_cbar = %10.3e; e_gamma = %10.3e\n", e_bbar, e_cbar, e_gamma); xassert(e_bbar <= 1e-5 && e_cbar <= 1e-5 && e_gamma <= 1e-3); } /* if the objective has to be maximized, check if it has reached its lower limit */ if (csa->phase == 2 && csa->zeta < 0.0 && parm->obj_ll > -DBL_MAX && csa->bbar[0] <= parm->obj_ll) { if (bbar_st != 1 || cbar_st != 1) { if (bbar_st != 1) bbar_st = 0; if (cbar_st != 1) cbar_st = 0; goto loop; } display(csa, parm, 1); if (parm->msg_lev >= GLP_MSG_ALL) xprintf("OBJECTIVE LOWER LIMIT REACHED; SEARCH TERMINATED\n" ); store_sol(csa, lp, GLP_INFEAS, GLP_FEAS, 0); ret = GLP_EOBJLL; goto done; } /* if the objective has to be minimized, check if it has reached its upper limit */ if (csa->phase == 2 && csa->zeta > 0.0 && parm->obj_ul < +DBL_MAX && csa->bbar[0] >= parm->obj_ul) { if (bbar_st != 1 || cbar_st != 1) { if (bbar_st != 1) bbar_st = 0; if (cbar_st != 1) cbar_st = 0; goto loop; } display(csa, parm, 1); if (parm->msg_lev >= GLP_MSG_ALL) xprintf("OBJECTIVE UPPER LIMIT REACHED; SEARCH TERMINATED\n" ); store_sol(csa, lp, GLP_INFEAS, GLP_FEAS, 0); ret = GLP_EOBJUL; goto done; } /* check if the iteration limit has been exhausted */ if (parm->it_lim < INT_MAX && csa->it_cnt - csa->it_beg >= parm->it_lim) { if (csa->phase == 2 && bbar_st != 1 || cbar_st != 1) { if (csa->phase == 2 && bbar_st != 1) bbar_st = 0; if (cbar_st != 1) cbar_st = 0; goto loop; } display(csa, parm, 1); if (parm->msg_lev >= GLP_MSG_ALL) xprintf("ITERATION LIMIT EXCEEDED; SEARCH TERMINATED\n"); switch (csa->phase) { case 1: d_stat = GLP_INFEAS; set_orig_bnds(csa); eval_bbar(csa); break; case 2: d_stat = GLP_FEAS; break; default: xassert(csa != csa); } store_sol(csa, lp, GLP_INFEAS, d_stat, 0); ret = GLP_EITLIM; goto done; } /* check if the time limit has been exhausted */ if (parm->tm_lim < INT_MAX && 1000.0 * xdifftime(xtime(), csa->tm_beg) >= parm->tm_lim) { if (csa->phase == 2 && bbar_st != 1 || cbar_st != 1) { if (csa->phase == 2 && bbar_st != 1) bbar_st = 0; if (cbar_st != 1) cbar_st = 0; goto loop; } display(csa, parm, 1); if (parm->msg_lev >= GLP_MSG_ALL) xprintf("TIME LIMIT EXCEEDED; SEARCH TERMINATED\n"); switch (csa->phase) { case 1: d_stat = GLP_INFEAS; set_orig_bnds(csa); eval_bbar(csa); break; case 2: d_stat = GLP_FEAS; break; default: xassert(csa != csa); } store_sol(csa, lp, GLP_INFEAS, d_stat, 0); ret = GLP_ETMLIM; goto done; } /* display the search progress */ display(csa, parm, 0); /* choose basic variable xB[p] */ chuzr(csa, parm->tol_bnd); if (csa->p == 0) { if (bbar_st != 1 || cbar_st != 1) { if (bbar_st != 1) bbar_st = 0; if (cbar_st != 1) cbar_st = 0; goto loop; } display(csa, parm, 1); switch (csa->phase) { case 1: if (parm->msg_lev >= GLP_MSG_ALL) xprintf("PROBLEM HAS NO DUAL FEASIBLE SOLUTION\n"); set_orig_bnds(csa); eval_bbar(csa); p_stat = GLP_INFEAS, d_stat = GLP_NOFEAS; break; case 2: if (parm->msg_lev >= GLP_MSG_ALL) xprintf("OPTIMAL SOLUTION FOUND\n"); p_stat = d_stat = GLP_FEAS; break; default: xassert(csa != csa); } store_sol(csa, lp, p_stat, d_stat, 0); ret = 0; goto done; } /* compute pivot row of the simplex table */ { double *rho = csa->work4; eval_rho(csa, rho); if (rigorous) refine_rho(csa, rho); eval_trow(csa, rho); sort_trow(csa, parm->tol_bnd); } /* unlike primal simplex there is no need to check accuracy of the primal value of xB[p] (which might be computed using the pivot row), since bbar is a result of FTRAN */ #ifdef GLP_LONG_STEP /* 07/IV-2009 */ long_step(csa); if (csa->nbps > 0) { csa->q = csa->bkpt[csa->nbps].j; if (csa->delta > 0.0) csa->new_dq = + csa->bkpt[csa->nbps].t; else csa->new_dq = - csa->bkpt[csa->nbps].t; } else #endif /* choose non-basic variable xN[q] */ switch (parm->r_test) { case GLP_RT_STD: chuzc(csa, 0.0); break; case GLP_RT_HAR: chuzc(csa, 0.30 * parm->tol_dj); break; default: xassert(parm != parm); } if (csa->q == 0) { if (bbar_st != 1 || cbar_st != 1 || !rigorous) { if (bbar_st != 1) bbar_st = 0; if (cbar_st != 1) cbar_st = 0; rigorous = 1; goto loop; } display(csa, parm, 1); switch (csa->phase) { case 1: if (parm->msg_lev >= GLP_MSG_ERR) xprintf("Error: unable to choose basic variable on ph" "ase I\n"); xassert(!lp->valid && lp->bfd == NULL); lp->bfd = csa->bfd, csa->bfd = NULL; lp->pbs_stat = lp->dbs_stat = GLP_UNDEF; lp->obj_val = 0.0; lp->it_cnt = csa->it_cnt; lp->some = 0; ret = GLP_EFAIL; break; case 2: if (parm->msg_lev >= GLP_MSG_ALL) xprintf("PROBLEM HAS NO FEASIBLE SOLUTION\n"); store_sol(csa, lp, GLP_NOFEAS, GLP_FEAS, csa->head[csa->p]); ret = 0; break; default: xassert(csa != csa); } goto done; } /* check if the pivot element is acceptable */ { double piv = csa->trow_vec[csa->q]; double eps = 1e-5 * (1.0 + 0.01 * csa->trow_max); if (fabs(piv) < eps) { if (parm->msg_lev >= GLP_MSG_DBG) xprintf("piv = %.12g; eps = %g\n", piv, eps); if (!rigorous) { rigorous = 5; goto loop; } } } /* now xN[q] and xB[p] have been chosen anyhow */ /* compute pivot column of the simplex table */ eval_tcol(csa); if (rigorous) refine_tcol(csa); /* accuracy check based on the pivot element */ { double piv1 = csa->tcol_vec[csa->p]; /* more accurate */ double piv2 = csa->trow_vec[csa->q]; /* less accurate */ xassert(piv1 != 0.0); if (fabs(piv1 - piv2) > 1e-8 * (1.0 + fabs(piv1)) || !(piv1 > 0.0 && piv2 > 0.0 || piv1 < 0.0 && piv2 < 0.0)) { if (parm->msg_lev >= GLP_MSG_DBG) xprintf("piv1 = %.12g; piv2 = %.12g\n", piv1, piv2); if (binv_st != 1 || !rigorous) { if (binv_st != 1) binv_st = 0; rigorous = 5; goto loop; } /* (not a good idea; should be revised later) */ if (csa->tcol_vec[csa->p] == 0.0) { csa->tcol_nnz++; xassert(csa->tcol_nnz <= csa->m); csa->tcol_ind[csa->tcol_nnz] = csa->p; } csa->tcol_vec[csa->p] = piv2; } } /* update primal values of basic variables */ #ifdef GLP_LONG_STEP /* 07/IV-2009 */ if (csa->nbps > 0) { int kk, j, k; for (kk = 1; kk < csa->nbps; kk++) { if (csa->bkpt[kk].t >= csa->bkpt[csa->nbps].t) continue; j = csa->bkpt[kk].j; k = csa->head[csa->m + j]; xassert(csa->type[k] == GLP_DB); if (csa->stat[j] == GLP_NL) csa->stat[j] = GLP_NU; else csa->stat[j] = GLP_NL; } } bbar_st = 0; #else update_bbar(csa); if (csa->phase == 2) csa->bbar[0] += (csa->cbar[csa->q] / csa->zeta) * (csa->delta / csa->tcol_vec[csa->p]); bbar_st = 2; /* updated */ #endif /* update reduced costs of non-basic variables */ update_cbar(csa); cbar_st = 2; /* updated */ /* update steepest edge coefficients */ switch (parm->pricing) { case GLP_PT_STD: break; case GLP_PT_PSE: if (csa->refct > 0) update_gamma(csa); break; default: xassert(parm != parm); } /* update factorization of the basis matrix */ ret = update_B(csa, csa->p, csa->head[csa->m+csa->q]); if (ret == 0) binv_st = 2; /* updated */ else { csa->valid = 0; binv_st = 0; /* invalid */ } #if 0 /* 06/IV-2009 */ /* update matrix N */ del_N_col(csa, csa->q, csa->head[csa->m+csa->q]); if (csa->type[csa->head[csa->p]] != GLP_FX) add_N_col(csa, csa->q, csa->head[csa->p]); #endif /* change the basis header */ change_basis(csa); /* iteration complete */ csa->it_cnt++; if (rigorous > 0) rigorous--; goto loop; done: /* deallocate the common storage area */ free_csa(csa); /* return to the calling program */ return ret; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpini02.c0000644000076500000240000002155713524616144025201 0ustar tamasstaff00000000000000/* glpini02.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wsign-conversion" #endif #include "glpapi.h" struct var { /* structural variable */ int j; /* ordinal number */ double q; /* penalty value */ }; static int fcmp(const void *ptr1, const void *ptr2) { /* this routine is passed to the qsort() function */ struct var *col1 = (void *)ptr1, *col2 = (void *)ptr2; if (col1->q < col2->q) return -1; if (col1->q > col2->q) return +1; return 0; } static int get_column(glp_prob *lp, int j, int ind[], double val[]) { /* Bixby's algorithm assumes that the constraint matrix is scaled such that the maximum absolute value in every non-zero row and column is 1 */ int k, len; double big; len = glp_get_mat_col(lp, j, ind, val); big = 0.0; for (k = 1; k <= len; k++) if (big < fabs(val[k])) big = fabs(val[k]); if (big == 0.0) big = 1.0; for (k = 1; k <= len; k++) val[k] /= big; return len; } static void cpx_basis(glp_prob *lp) { /* main routine */ struct var *C, *C2, *C3, *C4; int m, n, i, j, jk, k, l, ll, t, n2, n3, n4, type, len, *I, *r, *ind; double alpha, gamma, cmax, temp, *v, *val; xprintf("Constructing initial basis...\n"); /* determine the number of rows and columns */ m = glp_get_num_rows(lp); n = glp_get_num_cols(lp); /* allocate working arrays */ C = xcalloc(1+n, sizeof(struct var)); I = xcalloc(1+m, sizeof(int)); r = xcalloc(1+m, sizeof(int)); v = xcalloc(1+m, sizeof(double)); ind = xcalloc(1+m, sizeof(int)); val = xcalloc(1+m, sizeof(double)); /* make all auxiliary variables non-basic */ for (i = 1; i <= m; i++) { if (glp_get_row_type(lp, i) != GLP_DB) glp_set_row_stat(lp, i, GLP_NS); else if (fabs(glp_get_row_lb(lp, i)) <= fabs(glp_get_row_ub(lp, i))) glp_set_row_stat(lp, i, GLP_NL); else glp_set_row_stat(lp, i, GLP_NU); } /* make all structural variables non-basic */ for (j = 1; j <= n; j++) { if (glp_get_col_type(lp, j) != GLP_DB) glp_set_col_stat(lp, j, GLP_NS); else if (fabs(glp_get_col_lb(lp, j)) <= fabs(glp_get_col_ub(lp, j))) glp_set_col_stat(lp, j, GLP_NL); else glp_set_col_stat(lp, j, GLP_NU); } /* C2 is a set of free structural variables */ n2 = 0, C2 = C + 0; for (j = 1; j <= n; j++) { type = glp_get_col_type(lp, j); if (type == GLP_FR) { n2++; C2[n2].j = j; C2[n2].q = 0.0; } } /* C3 is a set of structural variables having excatly one (lower or upper) bound */ n3 = 0, C3 = C2 + n2; for (j = 1; j <= n; j++) { type = glp_get_col_type(lp, j); if (type == GLP_LO) { n3++; C3[n3].j = j; C3[n3].q = + glp_get_col_lb(lp, j); } else if (type == GLP_UP) { n3++; C3[n3].j = j; C3[n3].q = - glp_get_col_ub(lp, j); } } /* C4 is a set of structural variables having both (lower and upper) bounds */ n4 = 0, C4 = C3 + n3; for (j = 1; j <= n; j++) { type = glp_get_col_type(lp, j); if (type == GLP_DB) { n4++; C4[n4].j = j; C4[n4].q = glp_get_col_lb(lp, j) - glp_get_col_ub(lp, j); } } /* compute gamma = max{|c[j]|: 1 <= j <= n} */ gamma = 0.0; for (j = 1; j <= n; j++) { temp = fabs(glp_get_obj_coef(lp, j)); if (gamma < temp) gamma = temp; } /* compute cmax */ cmax = (gamma == 0.0 ? 1.0 : 1000.0 * gamma); /* compute final penalty for all structural variables within sets C2, C3, and C4 */ switch (glp_get_obj_dir(lp)) { case GLP_MIN: temp = +1.0; break; case GLP_MAX: temp = -1.0; break; default: xassert(lp != lp); } for (k = 1; k <= n2+n3+n4; k++) { j = C[k].j; C[k].q += (temp * glp_get_obj_coef(lp, j)) / cmax; } /* sort structural variables within C2, C3, and C4 in ascending order of penalty value */ qsort(C2+1, n2, sizeof(struct var), fcmp); for (k = 1; k < n2; k++) xassert(C2[k].q <= C2[k+1].q); qsort(C3+1, n3, sizeof(struct var), fcmp); for (k = 1; k < n3; k++) xassert(C3[k].q <= C3[k+1].q); qsort(C4+1, n4, sizeof(struct var), fcmp); for (k = 1; k < n4; k++) xassert(C4[k].q <= C4[k+1].q); /*** STEP 1 ***/ for (i = 1; i <= m; i++) { type = glp_get_row_type(lp, i); if (type != GLP_FX) { /* row i is either free or inequality constraint */ glp_set_row_stat(lp, i, GLP_BS); I[i] = 1; r[i] = 1; } else { /* row i is equality constraint */ I[i] = 0; r[i] = 0; } v[i] = +DBL_MAX; } /*** STEP 2 ***/ for (k = 1; k <= n2+n3+n4; k++) { jk = C[k].j; len = get_column(lp, jk, ind, val); /* let alpha = max{|A[l,jk]|: r[l] = 0} and let l' be such that alpha = |A[l',jk]| */ alpha = 0.0, ll = 0; for (t = 1; t <= len; t++) { l = ind[t]; if (r[l] == 0 && alpha < fabs(val[t])) alpha = fabs(val[t]), ll = l; } if (alpha >= 0.99) { /* B := B union {jk} */ glp_set_col_stat(lp, jk, GLP_BS); I[ll] = 1; v[ll] = alpha; /* r[l] := r[l] + 1 for all l such that |A[l,jk]| != 0 */ for (t = 1; t <= len; t++) { l = ind[t]; if (val[t] != 0.0) r[l]++; } /* continue to the next k */ continue; } /* if |A[l,jk]| > 0.01 * v[l] for some l, continue to the next k */ for (t = 1; t <= len; t++) { l = ind[t]; if (fabs(val[t]) > 0.01 * v[l]) break; } if (t <= len) continue; /* otherwise, let alpha = max{|A[l,jk]|: I[l] = 0} and let l' be such that alpha = |A[l',jk]| */ alpha = 0.0, ll = 0; for (t = 1; t <= len; t++) { l = ind[t]; if (I[l] == 0 && alpha < fabs(val[t])) alpha = fabs(val[t]), ll = l; } /* if alpha = 0, continue to the next k */ if (alpha == 0.0) continue; /* B := B union {jk} */ glp_set_col_stat(lp, jk, GLP_BS); I[ll] = 1; v[ll] = alpha; /* r[l] := r[l] + 1 for all l such that |A[l,jk]| != 0 */ for (t = 1; t <= len; t++) { l = ind[t]; if (val[t] != 0.0) r[l]++; } } /*** STEP 3 ***/ /* add an artificial variable (auxiliary variable for equality constraint) to cover each remaining uncovered row */ for (i = 1; i <= m; i++) if (I[i] == 0) glp_set_row_stat(lp, i, GLP_BS); /* free working arrays */ xfree(C); xfree(I); xfree(r); xfree(v); xfree(ind); xfree(val); return; } /*********************************************************************** * NAME * * glp_cpx_basis - construct Bixby's initial LP basis * * SYNOPSIS * * void glp_cpx_basis(glp_prob *lp); * * DESCRIPTION * * The routine glp_cpx_basis constructs an advanced initial basis for * the specified problem object. * * The routine is based on Bixby's algorithm described in the paper: * * Robert E. Bixby. Implementing the Simplex Method: The Initial Basis. * ORSA Journal on Computing, Vol. 4, No. 3, 1992, pp. 267-84. */ void glp_cpx_basis(glp_prob *lp) { if (lp->m == 0 || lp->n == 0) glp_std_basis(lp); else cpx_basis(lp); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpios09.c0000644000076500000240000006342313524616144025221 0ustar tamasstaff00000000000000/* glpios09.c (branching heuristics) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wsometimes-uninitialized" #pragma clang diagnostic ignored "-Wpointer-sign" #pragma clang diagnostic ignored "-Wlogical-op-parentheses" #endif #include "glpios.h" /*********************************************************************** * NAME * * ios_choose_var - select variable to branch on * * SYNOPSIS * * #include "glpios.h" * int ios_choose_var(glp_tree *T, int *next); * * The routine ios_choose_var chooses a variable from the candidate * list to branch on. Additionally the routine provides a flag stored * in the location next to suggests which of the child subproblems * should be solved next. * * RETURNS * * The routine ios_choose_var returns the ordinal number of the column * choosen. */ static int branch_first(glp_tree *T, int *next); static int branch_last(glp_tree *T, int *next); static int branch_mostf(glp_tree *T, int *next); static int branch_drtom(glp_tree *T, int *next); int ios_choose_var(glp_tree *T, int *next) { int j; if (T->parm->br_tech == GLP_BR_FFV) { /* branch on first fractional variable */ j = branch_first(T, next); } else if (T->parm->br_tech == GLP_BR_LFV) { /* branch on last fractional variable */ j = branch_last(T, next); } else if (T->parm->br_tech == GLP_BR_MFV) { /* branch on most fractional variable */ j = branch_mostf(T, next); } else if (T->parm->br_tech == GLP_BR_DTH) { /* branch using the heuristic by Dreebeck and Tomlin */ j = branch_drtom(T, next); } else if (T->parm->br_tech == GLP_BR_PCH) { /* hybrid pseudocost heuristic */ j = ios_pcost_branch(T, next); } else xassert(T != T); return j; } /*********************************************************************** * branch_first - choose first branching variable * * This routine looks up the list of structural variables and chooses * the first one, which is of integer kind and has fractional value in * optimal solution to the current LP relaxation. * * This routine also selects the branch to be solved next where integer * infeasibility of the chosen variable is less than in other one. */ static int branch_first(glp_tree *T, int *_next) { int j, next; double beta; /* choose the column to branch on */ for (j = 1; j <= T->n; j++) if (T->non_int[j]) break; xassert(1 <= j && j <= T->n); /* select the branch to be solved next */ beta = glp_get_col_prim(T->mip, j); if (beta - floor(beta) < ceil(beta) - beta) next = GLP_DN_BRNCH; else next = GLP_UP_BRNCH; *_next = next; return j; } /*********************************************************************** * branch_last - choose last branching variable * * This routine looks up the list of structural variables and chooses * the last one, which is of integer kind and has fractional value in * optimal solution to the current LP relaxation. * * This routine also selects the branch to be solved next where integer * infeasibility of the chosen variable is less than in other one. */ static int branch_last(glp_tree *T, int *_next) { int j, next; double beta; /* choose the column to branch on */ for (j = T->n; j >= 1; j--) if (T->non_int[j]) break; xassert(1 <= j && j <= T->n); /* select the branch to be solved next */ beta = glp_get_col_prim(T->mip, j); if (beta - floor(beta) < ceil(beta) - beta) next = GLP_DN_BRNCH; else next = GLP_UP_BRNCH; *_next = next; return j; } /*********************************************************************** * branch_mostf - choose most fractional branching variable * * This routine looks up the list of structural variables and chooses * that one, which is of integer kind and has most fractional value in * optimal solution to the current LP relaxation. * * This routine also selects the branch to be solved next where integer * infeasibility of the chosen variable is less than in other one. * * (Alexander Martin notices that "...most infeasible is as good as * random...".) */ static int branch_mostf(glp_tree *T, int *_next) { int j, jj, next; double beta, most, temp; /* choose the column to branch on */ jj = 0, most = DBL_MAX; for (j = 1; j <= T->n; j++) { if (T->non_int[j]) { beta = glp_get_col_prim(T->mip, j); temp = floor(beta) + 0.5; if (most > fabs(beta - temp)) { jj = j, most = fabs(beta - temp); if (beta < temp) next = GLP_DN_BRNCH; else next = GLP_UP_BRNCH; } } } *_next = next; return jj; } /*********************************************************************** * branch_drtom - choose branching var using Driebeck-Tomlin heuristic * * This routine chooses a structural variable, which is required to be * integral and has fractional value in optimal solution of the current * LP relaxation, using a heuristic proposed by Driebeck and Tomlin. * * The routine also selects the branch to be solved next, again due to * Driebeck and Tomlin. * * This routine is based on the heuristic proposed in: * * Driebeck N.J. An algorithm for the solution of mixed-integer * programming problems, Management Science, 12: 576-87 (1966); * * and improved in: * * Tomlin J.A. Branch and bound methods for integer and non-convex * programming, in J.Abadie (ed.), Integer and Nonlinear Programming, * North-Holland, Amsterdam, pp. 437-50 (1970). * * Must note that this heuristic is time-expensive, because computing * one-step degradation (see the routine below) requires one BTRAN for * each fractional-valued structural variable. */ static int branch_drtom(glp_tree *T, int *_next) { glp_prob *mip = T->mip; int m = mip->m; int n = mip->n; char *non_int = T->non_int; int j, jj, k, t, next, kase, len, stat, *ind; double x, dk, alfa, delta_j, delta_k, delta_z, dz_dn, dz_up, dd_dn, dd_up, degrad, *val; /* basic solution of LP relaxation must be optimal */ xassert(glp_get_status(mip) == GLP_OPT); /* allocate working arrays */ ind = xcalloc(1+n, sizeof(int)); val = xcalloc(1+n, sizeof(double)); /* nothing has been chosen so far */ jj = 0, degrad = -1.0; /* walk through the list of columns (structural variables) */ for (j = 1; j <= n; j++) { /* if j-th column is not marked as fractional, skip it */ if (!non_int[j]) continue; /* obtain (fractional) value of j-th column in basic solution of LP relaxation */ x = glp_get_col_prim(mip, j); /* since the value of j-th column is fractional, the column is basic; compute corresponding row of the simplex table */ len = glp_eval_tab_row(mip, m+j, ind, val); /* the following fragment computes a change in the objective function: delta Z = new Z - old Z, where old Z is the objective value in the current optimal basis, and new Z is the objective value in the adjacent basis, for two cases: 1) if new upper bound ub' = floor(x[j]) is introduced for j-th column (down branch); 2) if new lower bound lb' = ceil(x[j]) is introduced for j-th column (up branch); since in both cases the solution remaining dual feasible becomes primal infeasible, one implicit simplex iteration is performed to determine the change delta Z; it is obvious that new Z, which is never better than old Z, is a lower (minimization) or upper (maximization) bound of the objective function for down- and up-branches. */ for (kase = -1; kase <= +1; kase += 2) { /* if kase < 0, the new upper bound of x[j] is introduced; in this case x[j] should decrease in order to leave the basis and go to its new upper bound */ /* if kase > 0, the new lower bound of x[j] is introduced; in this case x[j] should increase in order to leave the basis and go to its new lower bound */ /* apply the dual ratio test in order to determine which auxiliary or structural variable should enter the basis to keep dual feasibility */ k = glp_dual_rtest(mip, len, ind, val, kase, 1e-9); if (k != 0) k = ind[k]; /* if no non-basic variable has been chosen, LP relaxation of corresponding branch being primal infeasible and dual unbounded has no primal feasible solution; in this case the change delta Z is formally set to infinity */ if (k == 0) { delta_z = (T->mip->dir == GLP_MIN ? +DBL_MAX : -DBL_MAX); goto skip; } /* row of the simplex table that corresponds to non-basic variable x[k] choosen by the dual ratio test is: x[j] = ... + alfa * x[k] + ... where alfa is the influence coefficient (an element of the simplex table row) */ /* determine the coefficient alfa */ for (t = 1; t <= len; t++) if (ind[t] == k) break; xassert(1 <= t && t <= len); alfa = val[t]; /* since in the adjacent basis the variable x[j] becomes non-basic, knowing its value in the current basis we can determine its change delta x[j] = new x[j] - old x[j] */ delta_j = (kase < 0 ? floor(x) : ceil(x)) - x; /* and knowing the coefficient alfa we can determine the corresponding change delta x[k] = new x[k] - old x[k], where old x[k] is a value of x[k] in the current basis, and new x[k] is a value of x[k] in the adjacent basis */ delta_k = delta_j / alfa; /* Tomlin noticed that if the variable x[k] is of integer kind, its change cannot be less (eventually) than one in the magnitude */ if (k > m && glp_get_col_kind(mip, k-m) != GLP_CV) { /* x[k] is structural integer variable */ if (fabs(delta_k - floor(delta_k + 0.5)) > 1e-3) { if (delta_k > 0.0) delta_k = ceil(delta_k); /* +3.14 -> +4 */ else delta_k = floor(delta_k); /* -3.14 -> -4 */ } } /* now determine the status and reduced cost of x[k] in the current basis */ if (k <= m) { stat = glp_get_row_stat(mip, k); dk = glp_get_row_dual(mip, k); } else { stat = glp_get_col_stat(mip, k-m); dk = glp_get_col_dual(mip, k-m); } /* if the current basis is dual degenerate, some reduced costs which are close to zero may have wrong sign due to round-off errors, so correct the sign of d[k] */ switch (T->mip->dir) { case GLP_MIN: if (stat == GLP_NL && dk < 0.0 || stat == GLP_NU && dk > 0.0 || stat == GLP_NF) dk = 0.0; break; case GLP_MAX: if (stat == GLP_NL && dk > 0.0 || stat == GLP_NU && dk < 0.0 || stat == GLP_NF) dk = 0.0; break; default: xassert(T != T); } /* now knowing the change of x[k] and its reduced cost d[k] we can compute the corresponding change in the objective function delta Z = new Z - old Z = d[k] * delta x[k]; note that due to Tomlin's modification new Z can be even worse than in the adjacent basis */ delta_z = dk * delta_k; skip: /* new Z is never better than old Z, therefore the change delta Z is always non-negative (in case of minimization) or non-positive (in case of maximization) */ switch (T->mip->dir) { case GLP_MIN: xassert(delta_z >= 0.0); break; case GLP_MAX: xassert(delta_z <= 0.0); break; default: xassert(T != T); } /* save the change in the objective fnction for down- and up-branches, respectively */ if (kase < 0) dz_dn = delta_z; else dz_up = delta_z; } /* thus, in down-branch no integer feasible solution can be better than Z + dz_dn, and in up-branch no integer feasible solution can be better than Z + dz_up, where Z is value of the objective function in the current basis */ /* following the heuristic by Driebeck and Tomlin we choose a column (i.e. structural variable) which provides largest degradation of the objective function in some of branches; besides, we select the branch with smaller degradation to be solved next and keep other branch with larger degradation in the active list hoping to minimize the number of further backtrackings */ if (degrad < fabs(dz_dn) || degrad < fabs(dz_up)) { jj = j; if (fabs(dz_dn) < fabs(dz_up)) { /* select down branch to be solved next */ next = GLP_DN_BRNCH; degrad = fabs(dz_up); } else { /* select up branch to be solved next */ next = GLP_UP_BRNCH; degrad = fabs(dz_dn); } /* save the objective changes for printing */ dd_dn = dz_dn, dd_up = dz_up; /* if down- or up-branch has no feasible solution, we does not need to consider other candidates (in principle, the corresponding branch could be pruned right now) */ if (degrad == DBL_MAX) break; } } /* free working arrays */ xfree(ind); xfree(val); /* something must be chosen */ xassert(1 <= jj && jj <= n); #if 1 /* 02/XI-2009 */ if (degrad < 1e-6 * (1.0 + 0.001 * fabs(mip->obj_val))) { jj = branch_mostf(T, &next); goto done; } #endif if (T->parm->msg_lev >= GLP_MSG_DBG) { xprintf("branch_drtom: column %d chosen to branch on\n", jj); if (fabs(dd_dn) == DBL_MAX) xprintf("branch_drtom: down-branch is infeasible\n"); else xprintf("branch_drtom: down-branch bound is %.9e\n", lpx_get_obj_val(mip) + dd_dn); if (fabs(dd_up) == DBL_MAX) xprintf("branch_drtom: up-branch is infeasible\n"); else xprintf("branch_drtom: up-branch bound is %.9e\n", lpx_get_obj_val(mip) + dd_up); } done: *_next = next; return jj; } /**********************************************************************/ struct csa { /* common storage area */ int *dn_cnt; /* int dn_cnt[1+n]; */ /* dn_cnt[j] is the number of subproblems, whose LP relaxations have been solved and which are down-branches for variable x[j]; dn_cnt[j] = 0 means the down pseudocost is uninitialized */ double *dn_sum; /* double dn_sum[1+n]; */ /* dn_sum[j] is the sum of per unit degradations of the objective over all dn_cnt[j] subproblems */ int *up_cnt; /* int up_cnt[1+n]; */ /* up_cnt[j] is the number of subproblems, whose LP relaxations have been solved and which are up-branches for variable x[j]; up_cnt[j] = 0 means the up pseudocost is uninitialized */ double *up_sum; /* double up_sum[1+n]; */ /* up_sum[j] is the sum of per unit degradations of the objective over all up_cnt[j] subproblems */ }; void *ios_pcost_init(glp_tree *tree) { /* initialize working data used on pseudocost branching */ struct csa *csa; int n = tree->n, j; csa = xmalloc(sizeof(struct csa)); csa->dn_cnt = xcalloc(1+n, sizeof(int)); csa->dn_sum = xcalloc(1+n, sizeof(double)); csa->up_cnt = xcalloc(1+n, sizeof(int)); csa->up_sum = xcalloc(1+n, sizeof(double)); for (j = 1; j <= n; j++) { csa->dn_cnt[j] = csa->up_cnt[j] = 0; csa->dn_sum[j] = csa->up_sum[j] = 0.0; } return csa; } static double eval_degrad(glp_prob *P, int j, double bnd) { /* compute degradation of the objective on fixing x[j] at given value with a limited number of dual simplex iterations */ /* this routine fixes column x[j] at specified value bnd, solves resulting LP, and returns a lower bound to degradation of the objective, degrad >= 0 */ glp_prob *lp; glp_smcp parm; int ret; double degrad; /* the current basis must be optimal */ xassert(glp_get_status(P) == GLP_OPT); /* create a copy of P */ lp = glp_create_prob(); glp_copy_prob(lp, P, 0); /* fix column x[j] at specified value */ glp_set_col_bnds(lp, j, GLP_FX, bnd, bnd); /* try to solve resulting LP */ glp_init_smcp(&parm); parm.msg_lev = GLP_MSG_OFF; parm.meth = GLP_DUAL; parm.it_lim = 30; parm.out_dly = 1000; parm.meth = GLP_DUAL; ret = glp_simplex(lp, &parm); if (ret == 0 || ret == GLP_EITLIM) { if (glp_get_prim_stat(lp) == GLP_NOFEAS) { /* resulting LP has no primal feasible solution */ degrad = DBL_MAX; } else if (glp_get_dual_stat(lp) == GLP_FEAS) { /* resulting basis is optimal or at least dual feasible, so we have the correct lower bound to degradation */ if (P->dir == GLP_MIN) degrad = lp->obj_val - P->obj_val; else if (P->dir == GLP_MAX) degrad = P->obj_val - lp->obj_val; else xassert(P != P); /* degradation cannot be negative by definition */ /* note that the lower bound to degradation may be close to zero even if its exact value is zero due to round-off errors on computing the objective value */ if (degrad < 1e-6 * (1.0 + 0.001 * fabs(P->obj_val))) degrad = 0.0; } else { /* the final basis reported by the simplex solver is dual infeasible, so we cannot determine a non-trivial lower bound to degradation */ degrad = 0.0; } } else { /* the simplex solver failed */ degrad = 0.0; } /* delete the copy of P */ glp_delete_prob(lp); return degrad; } void ios_pcost_update(glp_tree *tree) { /* update history information for pseudocost branching */ /* this routine is called every time when LP relaxation of the current subproblem has been solved to optimality with all lazy and cutting plane constraints included */ int j; double dx, dz, psi; struct csa *csa = tree->pcost; xassert(csa != NULL); xassert(tree->curr != NULL); /* if the current subproblem is the root, skip updating */ if (tree->curr->up == NULL) goto skip; /* determine branching variable x[j], which was used in the parent subproblem to create the current subproblem */ j = tree->curr->up->br_var; xassert(1 <= j && j <= tree->n); /* determine the change dx[j] = new x[j] - old x[j], where new x[j] is a value of x[j] in optimal solution to LP relaxation of the current subproblem, old x[j] is a value of x[j] in optimal solution to LP relaxation of the parent subproblem */ dx = tree->mip->col[j]->prim - tree->curr->up->br_val; xassert(dx != 0.0); /* determine corresponding change dz = new dz - old dz in the objective function value */ dz = tree->mip->obj_val - tree->curr->up->lp_obj; /* determine per unit degradation of the objective function */ psi = fabs(dz / dx); /* update history information */ if (dx < 0.0) { /* the current subproblem is down-branch */ csa->dn_cnt[j]++; csa->dn_sum[j] += psi; } else /* dx > 0.0 */ { /* the current subproblem is up-branch */ csa->up_cnt[j]++; csa->up_sum[j] += psi; } skip: return; } void ios_pcost_free(glp_tree *tree) { /* free working area used on pseudocost branching */ struct csa *csa = tree->pcost; xassert(csa != NULL); xfree(csa->dn_cnt); xfree(csa->dn_sum); xfree(csa->up_cnt); xfree(csa->up_sum); xfree(csa); tree->pcost = NULL; return; } static double eval_psi(glp_tree *T, int j, int brnch) { /* compute estimation of pseudocost of variable x[j] for down- or up-branch */ struct csa *csa = T->pcost; double beta, degrad, psi; xassert(csa != NULL); xassert(1 <= j && j <= T->n); if (brnch == GLP_DN_BRNCH) { /* down-branch */ if (csa->dn_cnt[j] == 0) { /* initialize down pseudocost */ beta = T->mip->col[j]->prim; degrad = eval_degrad(T->mip, j, floor(beta)); if (degrad == DBL_MAX) { psi = DBL_MAX; goto done; } csa->dn_cnt[j] = 1; csa->dn_sum[j] = degrad / (beta - floor(beta)); } psi = csa->dn_sum[j] / (double)csa->dn_cnt[j]; } else if (brnch == GLP_UP_BRNCH) { /* up-branch */ if (csa->up_cnt[j] == 0) { /* initialize up pseudocost */ beta = T->mip->col[j]->prim; degrad = eval_degrad(T->mip, j, ceil(beta)); if (degrad == DBL_MAX) { psi = DBL_MAX; goto done; } csa->up_cnt[j] = 1; csa->up_sum[j] = degrad / (ceil(beta) - beta); } psi = csa->up_sum[j] / (double)csa->up_cnt[j]; } else xassert(brnch != brnch); done: return psi; } static void progress(glp_tree *T) { /* display progress of pseudocost initialization */ struct csa *csa = T->pcost; int j, nv = 0, ni = 0; for (j = 1; j <= T->n; j++) { if (glp_ios_can_branch(T, j)) { nv++; if (csa->dn_cnt[j] > 0 && csa->up_cnt[j] > 0) ni++; } } xprintf("Pseudocosts initialized for %d of %d variables\n", ni, nv); return; } int ios_pcost_branch(glp_tree *T, int *_next) { /* choose branching variable with pseudocost branching */ glp_long t = xtime(); int j, jjj, sel; double beta, psi, d1, d2, d, dmax; /* initialize the working arrays */ if (T->pcost == NULL) T->pcost = ios_pcost_init(T); /* nothing has been chosen so far */ jjj = 0, dmax = -1.0; /* go through the list of branching candidates */ for (j = 1; j <= T->n; j++) { if (!glp_ios_can_branch(T, j)) continue; /* determine primal value of x[j] in optimal solution to LP relaxation of the current subproblem */ beta = T->mip->col[j]->prim; /* estimate pseudocost of x[j] for down-branch */ psi = eval_psi(T, j, GLP_DN_BRNCH); if (psi == DBL_MAX) { /* down-branch has no primal feasible solution */ jjj = j, sel = GLP_DN_BRNCH; goto done; } /* estimate degradation of the objective for down-branch */ d1 = psi * (beta - floor(beta)); /* estimate pseudocost of x[j] for up-branch */ psi = eval_psi(T, j, GLP_UP_BRNCH); if (psi == DBL_MAX) { /* up-branch has no primal feasible solution */ jjj = j, sel = GLP_UP_BRNCH; goto done; } /* estimate degradation of the objective for up-branch */ d2 = psi * (ceil(beta) - beta); /* determine d = max(d1, d2) */ d = (d1 > d2 ? d1 : d2); /* choose x[j] which provides maximal estimated degradation of the objective either in down- or up-branch */ if (dmax < d) { dmax = d; jjj = j; /* continue the search from a subproblem, where degradation is less than in other one */ sel = (d1 <= d2 ? GLP_DN_BRNCH : GLP_UP_BRNCH); } /* display progress of pseudocost initialization */ if (T->parm->msg_lev >= GLP_ON) { if (xdifftime(xtime(), t) >= 10.0) { progress(T); t = xtime(); } } } if (dmax == 0.0) { /* no degradation is indicated; choose a variable having most fractional value */ jjj = branch_mostf(T, &sel); } done: *_next = sel; return jjj; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpnet09.c0000644000076500000240000002241713524616144025213 0ustar tamasstaff00000000000000/* glpnet09.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wsign-conversion" #endif #include "glpapi.h" #include "glpnet.h" /*********************************************************************** * NAME * * kellerman - cover edges by cliques with Kellerman's heuristic * * SYNOPSIS * * #include "glpnet.h" * int kellerman(int n, int (*func)(void *info, int i, int ind[]), * void *info, glp_graph *H); * * DESCRIPTION * * The routine kellerman implements Kellerman's heuristic algorithm * to find a minimal set of cliques which cover all edges of specified * graph G = (V, E). * * The parameter n specifies the number of vertices |V|, n >= 0. * * Formal routine func specifies the set of edges E in the following * way. Running the routine kellerman calls the routine func and passes * to it parameter i, which is the number of some vertex, 1 <= i <= n. * In response the routine func should store numbers of all vertices * adjacent to vertex i to locations ind[1], ind[2], ..., ind[len] and * return the value of len, which is the number of adjacent vertices, * 0 <= len <= n. Self-loops are allowed, but ignored. Multiple edges * are not allowed. * * The parameter info is a transit pointer (magic cookie) passed to the * formal routine func as its first parameter. * * The result provided by the routine kellerman is the bipartite graph * H = (V union C, F), which defines the covering found. (The program * object of type glp_graph specified by the parameter H should be * previously created with the routine glp_create_graph. On entry the * routine kellerman erases the content of this object with the routine * glp_erase_graph.) Vertices of first part V correspond to vertices of * the graph G and have the same ordinal numbers 1, 2, ..., n. Vertices * of second part C correspond to cliques and have ordinal numbers * n+1, n+2, ..., n+k, where k is the total number of cliques in the * edge covering found. Every edge f in F in the program object H is * represented as arc f = (i->j), where i in V and j in C, which means * that vertex i of the graph G is in clique C[j], 1 <= j <= k. (Thus, * if two vertices of the graph G are in the same clique, these vertices * are adjacent in G, and corresponding edge is covered by that clique.) * * RETURNS * * The routine Kellerman returns k, the total number of cliques in the * edge covering found. * * REFERENCE * * For more details see: glpk/doc/notes/keller.pdf (in Russian). */ struct set { /* set of vertices */ int size; /* size (cardinality) of the set, 0 <= card <= n */ int *list; /* int list[1+n]; */ /* the set contains vertices list[1,...,size] */ int *pos; /* int pos[1+n]; */ /* pos[i] > 0 means that vertex i is in the set and list[pos[i]] = i; pos[i] = 0 means that vertex i is not in the set */ }; int kellerman(int n, int (*func)(void *info, int i, int ind[]), void *info, void /* glp_graph */ *H_) { glp_graph *H = H_; struct set W_, *W = &W_, V_, *V = &V_; glp_arc *a; int i, j, k, m, t, len, card, best; xassert(n >= 0); /* H := (V, 0; 0), where V is the set of vertices of graph G */ glp_erase_graph(H, H->v_size, H->a_size); glp_add_vertices(H, n); /* W := 0 */ W->size = 0; W->list = xcalloc(1+n, sizeof(int)); W->pos = xcalloc(1+n, sizeof(int)); memset(&W->pos[1], 0, sizeof(int) * n); /* V := 0 */ V->size = 0; V->list = xcalloc(1+n, sizeof(int)); V->pos = xcalloc(1+n, sizeof(int)); memset(&V->pos[1], 0, sizeof(int) * n); /* main loop */ for (i = 1; i <= n; i++) { /* W must be empty */ xassert(W->size == 0); /* W := { j : i > j and (i,j) in E } */ len = func(info, i, W->list); xassert(0 <= len && len <= n); for (t = 1; t <= len; t++) { j = W->list[t]; xassert(1 <= j && j <= n); if (j >= i) continue; xassert(W->pos[j] == 0); W->list[++W->size] = j, W->pos[j] = W->size; } /* on i-th iteration we need to cover edges (i,j) for all j in W */ /* if W is empty, it is a special case */ if (W->size == 0) { /* set k := k + 1 and create new clique C[k] = { i } */ k = glp_add_vertices(H, 1) - n; glp_add_arc(H, i, n + k); continue; } /* try to include vertex i into existing cliques */ /* V must be empty */ xassert(V->size == 0); /* k is the number of cliques found so far */ k = H->nv - n; for (m = 1; m <= k; m++) { /* do while V != W; since here V is within W, we can use equivalent condition: do while |V| < |W| */ if (V->size == W->size) break; /* check if C[m] is within W */ for (a = H->v[n + m]->in; a != NULL; a = a->h_next) { j = a->tail->i; if (W->pos[j] == 0) break; } if (a != NULL) continue; /* C[m] is within W, expand clique C[m] with vertex i */ /* C[m] := C[m] union {i} */ glp_add_arc(H, i, n + m); /* V is a set of vertices whose incident edges are already covered by existing cliques */ /* V := V union C[m] */ for (a = H->v[n + m]->in; a != NULL; a = a->h_next) { j = a->tail->i; if (V->pos[j] == 0) V->list[++V->size] = j, V->pos[j] = V->size; } } /* remove from set W the vertices whose incident edges are already covered by existing cliques */ /* W := W \ V, V := 0 */ for (t = 1; t <= V->size; t++) { j = V->list[t], V->pos[j] = 0; if (W->pos[j] != 0) { /* remove vertex j from W */ if (W->pos[j] != W->size) { int jj = W->list[W->size]; W->list[W->pos[j]] = jj; W->pos[jj] = W->pos[j]; } W->size--, W->pos[j] = 0; } } V->size = 0; /* now set W contains only vertices whose incident edges are still not covered by existing cliques; create new cliques to cover remaining edges until set W becomes empty */ while (W->size > 0) { /* find clique C[m], 1 <= m <= k, which shares maximal number of vertices with W; to break ties choose clique having smallest number m */ m = 0, best = -1; k = H->nv - n; for (t = 1; t <= k; t++) { /* compute cardinality of intersection of W and C[t] */ card = 0; for (a = H->v[n + t]->in; a != NULL; a = a->h_next) { j = a->tail->i; if (W->pos[j] != 0) card++; } if (best < card) m = t, best = card; } xassert(m > 0); /* set k := k + 1 and create new clique: C[k] := (W intersect C[m]) union { i }, which covers all edges incident to vertices from (W intersect C[m]) */ k = glp_add_vertices(H, 1) - n; for (a = H->v[n + m]->in; a != NULL; a = a->h_next) { j = a->tail->i; if (W->pos[j] != 0) { /* vertex j is in both W and C[m]; include it in new clique C[k] */ glp_add_arc(H, j, n + k); /* remove vertex j from W, since edge (i,j) will be covered by new clique C[k] */ if (W->pos[j] != W->size) { int jj = W->list[W->size]; W->list[W->pos[j]] = jj; W->pos[jj] = W->pos[j]; } W->size--, W->pos[j] = 0; } } /* include vertex i to new clique C[k] to cover edges (i,j) incident to all vertices j just removed from W */ glp_add_arc(H, i, n + k); } } /* free working arrays */ xfree(W->list); xfree(W->pos); xfree(V->list); xfree(V->pos); /* return the number of cliques in the edge covering found */ return H->nv - n; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glplpf.c0000644000076500000240000007552713524616144025047 0ustar tamasstaff00000000000000/* glplpf.c (LP basis factorization, Schur complement version) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wself-assign" #pragma clang diagnostic ignored "-Wsign-conversion" #endif #include "glplpf.h" #include "glpenv.h" #define xfault xerror #define _GLPLPF_DEBUG 0 /* CAUTION: DO NOT CHANGE THE LIMIT BELOW */ #define M_MAX 100000000 /* = 100*10^6 */ /* maximal order of the basis matrix */ /*********************************************************************** * NAME * * lpf_create_it - create LP basis factorization * * SYNOPSIS * * #include "glplpf.h" * LPF *lpf_create_it(void); * * DESCRIPTION * * The routine lpf_create_it creates a program object, which represents * a factorization of LP basis. * * RETURNS * * The routine lpf_create_it returns a pointer to the object created. */ LPF *lpf_create_it(void) { LPF *lpf; #if _GLPLPF_DEBUG xprintf("lpf_create_it: warning: debug mode enabled\n"); #endif lpf = xmalloc(sizeof(LPF)); lpf->valid = 0; lpf->m0_max = lpf->m0 = 0; lpf->luf = luf_create_it(); lpf->m = 0; lpf->B = NULL; lpf->n_max = 50; lpf->n = 0; lpf->R_ptr = lpf->R_len = NULL; lpf->S_ptr = lpf->S_len = NULL; lpf->scf = NULL; lpf->P_row = lpf->P_col = NULL; lpf->Q_row = lpf->Q_col = NULL; lpf->v_size = 1000; lpf->v_ptr = 0; lpf->v_ind = NULL; lpf->v_val = NULL; lpf->work1 = lpf->work2 = NULL; return lpf; } /*********************************************************************** * NAME * * lpf_factorize - compute LP basis factorization * * SYNOPSIS * * #include "glplpf.h" * int lpf_factorize(LPF *lpf, int m, const int bh[], int (*col) * (void *info, int j, int ind[], double val[]), void *info); * * DESCRIPTION * * The routine lpf_factorize computes the factorization of the basis * matrix B specified by the routine col. * * The parameter lpf specified the basis factorization data structure * created with the routine lpf_create_it. * * The parameter m specifies the order of B, m > 0. * * The array bh specifies the basis header: bh[j], 1 <= j <= m, is the * number of j-th column of B in some original matrix. The array bh is * optional and can be specified as NULL. * * The formal routine col specifies the matrix B to be factorized. To * obtain j-th column of A the routine lpf_factorize calls the routine * col with the parameter j (1 <= j <= n). In response the routine col * should store row indices and numerical values of non-zero elements * of j-th column of B to locations ind[1,...,len] and val[1,...,len], * respectively, where len is the number of non-zeros in j-th column * returned on exit. Neither zero nor duplicate elements are allowed. * * The parameter info is a transit pointer passed to the routine col. * * RETURNS * * 0 The factorization has been successfully computed. * * LPF_ESING * The specified matrix is singular within the working precision. * * LPF_ECOND * The specified matrix is ill-conditioned. * * For more details see comments to the routine luf_factorize. */ int lpf_factorize(LPF *lpf, int m, const int bh[], int (*col) (void *info, int j, int ind[], double val[]), void *info) { int k, ret; #if _GLPLPF_DEBUG int i, j, len, *ind; double *B, *val; #endif xassert(bh == bh); if (m < 1) xfault("lpf_factorize: m = %d; invalid parameter\n", m); if (m > M_MAX) xfault("lpf_factorize: m = %d; matrix too big\n", m); lpf->m0 = lpf->m = m; /* invalidate the factorization */ lpf->valid = 0; /* allocate/reallocate arrays, if necessary */ if (lpf->R_ptr == NULL) lpf->R_ptr = xcalloc(1+lpf->n_max, sizeof(int)); if (lpf->R_len == NULL) lpf->R_len = xcalloc(1+lpf->n_max, sizeof(int)); if (lpf->S_ptr == NULL) lpf->S_ptr = xcalloc(1+lpf->n_max, sizeof(int)); if (lpf->S_len == NULL) lpf->S_len = xcalloc(1+lpf->n_max, sizeof(int)); if (lpf->scf == NULL) lpf->scf = scf_create_it(lpf->n_max); if (lpf->v_ind == NULL) lpf->v_ind = xcalloc(1+lpf->v_size, sizeof(int)); if (lpf->v_val == NULL) lpf->v_val = xcalloc(1+lpf->v_size, sizeof(double)); if (lpf->m0_max < m) { if (lpf->P_row != NULL) xfree(lpf->P_row); if (lpf->P_col != NULL) xfree(lpf->P_col); if (lpf->Q_row != NULL) xfree(lpf->Q_row); if (lpf->Q_col != NULL) xfree(lpf->Q_col); if (lpf->work1 != NULL) xfree(lpf->work1); if (lpf->work2 != NULL) xfree(lpf->work2); lpf->m0_max = m + 100; lpf->P_row = xcalloc(1+lpf->m0_max+lpf->n_max, sizeof(int)); lpf->P_col = xcalloc(1+lpf->m0_max+lpf->n_max, sizeof(int)); lpf->Q_row = xcalloc(1+lpf->m0_max+lpf->n_max, sizeof(int)); lpf->Q_col = xcalloc(1+lpf->m0_max+lpf->n_max, sizeof(int)); lpf->work1 = xcalloc(1+lpf->m0_max+lpf->n_max, sizeof(double)); lpf->work2 = xcalloc(1+lpf->m0_max+lpf->n_max, sizeof(double)); } /* try to factorize the basis matrix */ switch (luf_factorize(lpf->luf, m, col, info)) { case 0: break; case LUF_ESING: ret = LPF_ESING; goto done; case LUF_ECOND: ret = LPF_ECOND; goto done; default: xassert(lpf != lpf); } /* the basis matrix has been successfully factorized */ lpf->valid = 1; #if _GLPLPF_DEBUG /* store the basis matrix for debugging */ if (lpf->B != NULL) xfree(lpf->B); xassert(m <= 32767); lpf->B = B = xcalloc(1+m*m, sizeof(double)); ind = xcalloc(1+m, sizeof(int)); val = xcalloc(1+m, sizeof(double)); for (k = 1; k <= m * m; k++) B[k] = 0.0; for (j = 1; j <= m; j++) { len = col(info, j, ind, val); xassert(0 <= len && len <= m); for (k = 1; k <= len; k++) { i = ind[k]; xassert(1 <= i && i <= m); xassert(B[(i - 1) * m + j] == 0.0); xassert(val[k] != 0.0); B[(i - 1) * m + j] = val[k]; } } xfree(ind); xfree(val); #endif /* B = B0, so there are no additional rows/columns */ lpf->n = 0; /* reset the Schur complement factorization */ scf_reset_it(lpf->scf); /* P := Q := I */ for (k = 1; k <= m; k++) { lpf->P_row[k] = lpf->P_col[k] = k; lpf->Q_row[k] = lpf->Q_col[k] = k; } /* make all SVA locations free */ lpf->v_ptr = 1; ret = 0; done: /* return to the calling program */ return ret; } /*********************************************************************** * The routine r_prod computes the product y := y + alpha * R * x, * where x is a n-vector, alpha is a scalar, y is a m0-vector. * * Since matrix R is available by columns, the product is computed as * a linear combination: * * y := y + alpha * (R[1] * x[1] + ... + R[n] * x[n]), * * where R[j] is j-th column of R. */ static void r_prod(LPF *lpf, double y[], double a, const double x[]) { int n = lpf->n; int *R_ptr = lpf->R_ptr; int *R_len = lpf->R_len; int *v_ind = lpf->v_ind; double *v_val = lpf->v_val; int j, beg, end, ptr; double t; for (j = 1; j <= n; j++) { if (x[j] == 0.0) continue; /* y := y + alpha * R[j] * x[j] */ t = a * x[j]; beg = R_ptr[j]; end = beg + R_len[j]; for (ptr = beg; ptr < end; ptr++) y[v_ind[ptr]] += t * v_val[ptr]; } return; } /*********************************************************************** * The routine rt_prod computes the product y := y + alpha * R' * x, * where R' is a matrix transposed to R, x is a m0-vector, alpha is a * scalar, y is a n-vector. * * Since matrix R is available by columns, the product components are * computed as inner products: * * y[j] := y[j] + alpha * (j-th column of R) * x * * for j = 1, 2, ..., n. */ static void rt_prod(LPF *lpf, double y[], double a, const double x[]) { int n = lpf->n; int *R_ptr = lpf->R_ptr; int *R_len = lpf->R_len; int *v_ind = lpf->v_ind; double *v_val = lpf->v_val; int j, beg, end, ptr; double t; for (j = 1; j <= n; j++) { /* t := (j-th column of R) * x */ t = 0.0; beg = R_ptr[j]; end = beg + R_len[j]; for (ptr = beg; ptr < end; ptr++) t += v_val[ptr] * x[v_ind[ptr]]; /* y[j] := y[j] + alpha * t */ y[j] += a * t; } return; } /*********************************************************************** * The routine s_prod computes the product y := y + alpha * S * x, * where x is a m0-vector, alpha is a scalar, y is a n-vector. * * Since matrix S is available by rows, the product components are * computed as inner products: * * y[i] = y[i] + alpha * (i-th row of S) * x * * for i = 1, 2, ..., n. */ static void s_prod(LPF *lpf, double y[], double a, const double x[]) { int n = lpf->n; int *S_ptr = lpf->S_ptr; int *S_len = lpf->S_len; int *v_ind = lpf->v_ind; double *v_val = lpf->v_val; int i, beg, end, ptr; double t; for (i = 1; i <= n; i++) { /* t := (i-th row of S) * x */ t = 0.0; beg = S_ptr[i]; end = beg + S_len[i]; for (ptr = beg; ptr < end; ptr++) t += v_val[ptr] * x[v_ind[ptr]]; /* y[i] := y[i] + alpha * t */ y[i] += a * t; } return; } /*********************************************************************** * The routine st_prod computes the product y := y + alpha * S' * x, * where S' is a matrix transposed to S, x is a n-vector, alpha is a * scalar, y is m0-vector. * * Since matrix R is available by rows, the product is computed as a * linear combination: * * y := y + alpha * (S'[1] * x[1] + ... + S'[n] * x[n]), * * where S'[i] is i-th row of S. */ static void st_prod(LPF *lpf, double y[], double a, const double x[]) { int n = lpf->n; int *S_ptr = lpf->S_ptr; int *S_len = lpf->S_len; int *v_ind = lpf->v_ind; double *v_val = lpf->v_val; int i, beg, end, ptr; double t; for (i = 1; i <= n; i++) { if (x[i] == 0.0) continue; /* y := y + alpha * S'[i] * x[i] */ t = a * x[i]; beg = S_ptr[i]; end = beg + S_len[i]; for (ptr = beg; ptr < end; ptr++) y[v_ind[ptr]] += t * v_val[ptr]; } return; } #if _GLPLPF_DEBUG /*********************************************************************** * The routine check_error computes the maximal relative error between * left- and right-hand sides for the system B * x = b (if tr is zero) * or B' * x = b (if tr is non-zero), where B' is a matrix transposed * to B. (This routine is intended for debugging only.) */ static void check_error(LPF *lpf, int tr, const double x[], const double b[]) { int m = lpf->m; double *B = lpf->B; int i, j; double d, dmax = 0.0, s, t, tmax; for (i = 1; i <= m; i++) { s = 0.0; tmax = 1.0; for (j = 1; j <= m; j++) { if (!tr) t = B[m * (i - 1) + j] * x[j]; else t = B[m * (j - 1) + i] * x[j]; if (tmax < fabs(t)) tmax = fabs(t); s += t; } d = fabs(s - b[i]) / tmax; if (dmax < d) dmax = d; } if (dmax > 1e-8) xprintf("%s: dmax = %g; relative error too large\n", !tr ? "lpf_ftran" : "lpf_btran", dmax); return; } #endif /*********************************************************************** * NAME * * lpf_ftran - perform forward transformation (solve system B*x = b) * * SYNOPSIS * * #include "glplpf.h" * void lpf_ftran(LPF *lpf, double x[]); * * DESCRIPTION * * The routine lpf_ftran performs forward transformation, i.e. solves * the system B*x = b, where B is the basis matrix, x is the vector of * unknowns to be computed, b is the vector of right-hand sides. * * On entry elements of the vector b should be stored in dense format * in locations x[1], ..., x[m], where m is the number of rows. On exit * the routine stores elements of the vector x in the same locations. * * BACKGROUND * * Solution of the system B * x = b can be obtained by solving the * following augmented system: * * ( B F^) ( x ) ( b ) * ( ) ( ) = ( ) * ( G^ H^) ( y ) ( 0 ) * * which, using the main equality, can be written as follows: * * ( L0 0 ) ( U0 R ) ( x ) ( b ) * P ( ) ( ) Q ( ) = ( ) * ( S I ) ( 0 C ) ( y ) ( 0 ) * * therefore, * * ( x ) ( U0 R )-1 ( L0 0 )-1 ( b ) * ( ) = Q' ( ) ( ) P' ( ) * ( y ) ( 0 C ) ( S I ) ( 0 ) * * Thus, computing the solution includes the following steps: * * 1. Compute * * ( f ) ( b ) * ( ) = P' ( ) * ( g ) ( 0 ) * * 2. Solve the system * * ( f1 ) ( L0 0 )-1 ( f ) ( L0 0 ) ( f1 ) ( f ) * ( ) = ( ) ( ) => ( ) ( ) = ( ) * ( g1 ) ( S I ) ( g ) ( S I ) ( g1 ) ( g ) * * from which it follows that: * * { L0 * f1 = f f1 = inv(L0) * f * { => * { S * f1 + g1 = g g1 = g - S * f1 * * 3. Solve the system * * ( f2 ) ( U0 R )-1 ( f1 ) ( U0 R ) ( f2 ) ( f1 ) * ( ) = ( ) ( ) => ( ) ( ) = ( ) * ( g2 ) ( 0 C ) ( g1 ) ( 0 C ) ( g2 ) ( g1 ) * * from which it follows that: * * { U0 * f2 + R * g2 = f1 f2 = inv(U0) * (f1 - R * g2) * { => * { C * g2 = g1 g2 = inv(C) * g1 * * 4. Compute * * ( x ) ( f2 ) * ( ) = Q' ( ) * ( y ) ( g2 ) */ void lpf_ftran(LPF *lpf, double x[]) { int m0 = lpf->m0; int m = lpf->m; int n = lpf->n; int *P_col = lpf->P_col; int *Q_col = lpf->Q_col; double *fg = lpf->work1; double *f = fg; double *g = fg + m0; int i, ii; #if _GLPLPF_DEBUG double *b; #endif if (!lpf->valid) xfault("lpf_ftran: the factorization is not valid\n"); xassert(0 <= m && m <= m0 + n); #if _GLPLPF_DEBUG /* save the right-hand side vector */ b = xcalloc(1+m, sizeof(double)); for (i = 1; i <= m; i++) b[i] = x[i]; #endif /* (f g) := inv(P) * (b 0) */ for (i = 1; i <= m0 + n; i++) fg[i] = ((ii = P_col[i]) <= m ? x[ii] : 0.0); /* f1 := inv(L0) * f */ luf_f_solve(lpf->luf, 0, f); /* g1 := g - S * f1 */ s_prod(lpf, g, -1.0, f); /* g2 := inv(C) * g1 */ scf_solve_it(lpf->scf, 0, g); /* f2 := inv(U0) * (f1 - R * g2) */ r_prod(lpf, f, -1.0, g); luf_v_solve(lpf->luf, 0, f); /* (x y) := inv(Q) * (f2 g2) */ for (i = 1; i <= m; i++) x[i] = fg[Q_col[i]]; #if _GLPLPF_DEBUG /* check relative error in solution */ check_error(lpf, 0, x, b); xfree(b); #endif return; } /*********************************************************************** * NAME * * lpf_btran - perform backward transformation (solve system B'*x = b) * * SYNOPSIS * * #include "glplpf.h" * void lpf_btran(LPF *lpf, double x[]); * * DESCRIPTION * * The routine lpf_btran performs backward transformation, i.e. solves * the system B'*x = b, where B' is a matrix transposed to the basis * matrix B, x is the vector of unknowns to be computed, b is the vector * of right-hand sides. * * On entry elements of the vector b should be stored in dense format * in locations x[1], ..., x[m], where m is the number of rows. On exit * the routine stores elements of the vector x in the same locations. * * BACKGROUND * * Solution of the system B' * x = b, where B' is a matrix transposed * to B, can be obtained by solving the following augmented system: * * ( B F^)T ( x ) ( b ) * ( ) ( ) = ( ) * ( G^ H^) ( y ) ( 0 ) * * which, using the main equality, can be written as follows: * * T ( U0 R )T ( L0 0 )T T ( x ) ( b ) * Q ( ) ( ) P ( ) = ( ) * ( 0 C ) ( S I ) ( y ) ( 0 ) * * or, equivalently, as follows: * * ( U'0 0 ) ( L'0 S') ( x ) ( b ) * Q' ( ) ( ) P' ( ) = ( ) * ( R' C') ( 0 I ) ( y ) ( 0 ) * * therefore, * * ( x ) ( L'0 S')-1 ( U'0 0 )-1 ( b ) * ( ) = P ( ) ( ) Q ( ) * ( y ) ( 0 I ) ( R' C') ( 0 ) * * Thus, computing the solution includes the following steps: * * 1. Compute * * ( f ) ( b ) * ( ) = Q ( ) * ( g ) ( 0 ) * * 2. Solve the system * * ( f1 ) ( U'0 0 )-1 ( f ) ( U'0 0 ) ( f1 ) ( f ) * ( ) = ( ) ( ) => ( ) ( ) = ( ) * ( g1 ) ( R' C') ( g ) ( R' C') ( g1 ) ( g ) * * from which it follows that: * * { U'0 * f1 = f f1 = inv(U'0) * f * { => * { R' * f1 + C' * g1 = g g1 = inv(C') * (g - R' * f1) * * 3. Solve the system * * ( f2 ) ( L'0 S')-1 ( f1 ) ( L'0 S') ( f2 ) ( f1 ) * ( ) = ( ) ( ) => ( ) ( ) = ( ) * ( g2 ) ( 0 I ) ( g1 ) ( 0 I ) ( g2 ) ( g1 ) * * from which it follows that: * * { L'0 * f2 + S' * g2 = f1 * { => f2 = inv(L'0) * ( f1 - S' * g2) * { g2 = g1 * * 4. Compute * * ( x ) ( f2 ) * ( ) = P ( ) * ( y ) ( g2 ) */ void lpf_btran(LPF *lpf, double x[]) { int m0 = lpf->m0; int m = lpf->m; int n = lpf->n; int *P_row = lpf->P_row; int *Q_row = lpf->Q_row; double *fg = lpf->work1; double *f = fg; double *g = fg + m0; int i, ii; #if _GLPLPF_DEBUG double *b; #endif if (!lpf->valid) xfault("lpf_btran: the factorization is not valid\n"); xassert(0 <= m && m <= m0 + n); #if _GLPLPF_DEBUG /* save the right-hand side vector */ b = xcalloc(1+m, sizeof(double)); for (i = 1; i <= m; i++) b[i] = x[i]; #endif /* (f g) := Q * (b 0) */ for (i = 1; i <= m0 + n; i++) fg[i] = ((ii = Q_row[i]) <= m ? x[ii] : 0.0); /* f1 := inv(U'0) * f */ luf_v_solve(lpf->luf, 1, f); /* g1 := inv(C') * (g - R' * f1) */ rt_prod(lpf, g, -1.0, f); scf_solve_it(lpf->scf, 1, g); /* g2 := g1 */ g = g; /* f2 := inv(L'0) * (f1 - S' * g2) */ st_prod(lpf, f, -1.0, g); luf_f_solve(lpf->luf, 1, f); /* (x y) := P * (f2 g2) */ for (i = 1; i <= m; i++) x[i] = fg[P_row[i]]; #if _GLPLPF_DEBUG /* check relative error in solution */ check_error(lpf, 1, x, b); xfree(b); #endif return; } /*********************************************************************** * The routine enlarge_sva enlarges the Sparse Vector Area to new_size * locations by reallocating the arrays v_ind and v_val. */ static void enlarge_sva(LPF *lpf, int new_size) { int v_size = lpf->v_size; int used = lpf->v_ptr - 1; int *v_ind = lpf->v_ind; double *v_val = lpf->v_val; xassert(v_size < new_size); while (v_size < new_size) v_size += v_size; lpf->v_size = v_size; lpf->v_ind = xcalloc(1+v_size, sizeof(int)); lpf->v_val = xcalloc(1+v_size, sizeof(double)); xassert(used >= 0); memcpy(&lpf->v_ind[1], &v_ind[1], used * sizeof(int)); memcpy(&lpf->v_val[1], &v_val[1], used * sizeof(double)); xfree(v_ind); xfree(v_val); return; } /*********************************************************************** * NAME * * lpf_update_it - update LP basis factorization * * SYNOPSIS * * #include "glplpf.h" * int lpf_update_it(LPF *lpf, int j, int bh, int len, const int ind[], * const double val[]); * * DESCRIPTION * * The routine lpf_update_it updates the factorization of the basis * matrix B after replacing its j-th column by a new vector. * * The parameter j specifies the number of column of B, which has been * replaced, 1 <= j <= m, where m is the order of B. * * The parameter bh specifies the basis header entry for the new column * of B, which is the number of the new column in some original matrix. * This parameter is optional and can be specified as 0. * * Row indices and numerical values of non-zero elements of the new * column of B should be placed in locations ind[1], ..., ind[len] and * val[1], ..., val[len], resp., where len is the number of non-zeros * in the column. Neither zero nor duplicate elements are allowed. * * RETURNS * * 0 The factorization has been successfully updated. * * LPF_ESING * New basis B is singular within the working precision. * * LPF_ELIMIT * Maximal number of additional rows and columns has been reached. * * BACKGROUND * * Let j-th column of the current basis matrix B have to be replaced by * a new column a. This replacement is equivalent to removing the old * j-th column by fixing it at zero and introducing the new column as * follows: * * ( B F^| a ) * ( B F^) ( | ) * ( ) ---> ( G^ H^| 0 ) * ( G^ H^) (-------+---) * ( e'j 0 | 0 ) * * where ej is a unit vector with 1 in j-th position which used to fix * the old j-th column of B (at zero). Then using the main equality we * have: * * ( B F^| a ) ( B0 F | f ) * ( | ) ( P 0 ) ( | ) ( Q 0 ) * ( G^ H^| 0 ) = ( ) ( G H | g ) ( ) = * (-------+---) ( 0 1 ) (-------+---) ( 0 1 ) * ( e'j 0 | 0 ) ( v' w'| 0 ) * * [ ( B0 F )| ( f ) ] [ ( B0 F ) | ( f ) ] * [ P ( )| P ( ) ] ( Q 0 ) [ P ( ) Q| P ( ) ] * = [ ( G H )| ( g ) ] ( ) = [ ( G H ) | ( g ) ] * [------------+-------- ] ( 0 1 ) [-------------+---------] * [ ( v' w')| 0 ] [ ( v' w') Q| 0 ] * * where: * * ( a ) ( f ) ( f ) ( a ) * ( ) = P ( ) => ( ) = P' * ( ) * ( 0 ) ( g ) ( g ) ( 0 ) * * ( ej ) ( v ) ( v ) ( ej ) * ( e'j 0 ) = ( v' w' ) Q => ( ) = Q' ( ) => ( ) = Q ( ) * ( 0 ) ( w ) ( w ) ( 0 ) * * On the other hand: * * ( B0| F f ) * ( P 0 ) (---+------) ( Q 0 ) ( B0 new F ) * ( ) ( G | H g ) ( ) = new P ( ) new Q * ( 0 1 ) ( | ) ( 0 1 ) ( new G new H ) * ( v'| w' 0 ) * * where: * ( G ) ( H g ) * new F = ( F f ), new G = ( ), new H = ( ), * ( v') ( w' 0 ) * * ( P 0 ) ( Q 0 ) * new P = ( ) , new Q = ( ) . * ( 0 1 ) ( 0 1 ) * * The factorization structure for the new augmented matrix remains the * same, therefore: * * ( B0 new F ) ( L0 0 ) ( U0 new R ) * new P ( ) new Q = ( ) ( ) * ( new G new H ) ( new S I ) ( 0 new C ) * * where: * * new F = L0 * new R => * * new R = inv(L0) * new F = inv(L0) * (F f) = ( R inv(L0)*f ) * * new G = new S * U0 => * * ( G ) ( S ) * new S = new G * inv(U0) = ( ) * inv(U0) = ( ) * ( v') ( v'*inv(U0) ) * * new H = new S * new R + new C => * * new C = new H - new S * new R = * * ( H g ) ( S ) * = ( ) - ( ) * ( R inv(L0)*f ) = * ( w' 0 ) ( v'*inv(U0) ) * * ( H - S*R g - S*inv(L0)*f ) ( C x ) * = ( ) = ( ) * ( w'- v'*inv(U0)*R -v'*inv(U0)*inv(L0)*f) ( y' z ) * * Note that new C is resulted by expanding old C with new column x, * row y', and diagonal element z, where: * * x = g - S * inv(L0) * f = g - S * (new column of R) * * y = w - R'* inv(U'0)* v = w - R'* (new row of S) * * z = - (new row of S) * (new column of R) * * Finally, to replace old B by new B we have to permute j-th and last * (just added) columns of the matrix * * ( B F^| a ) * ( | ) * ( G^ H^| 0 ) * (-------+---) * ( e'j 0 | 0 ) * * and to keep the main equality do the same for matrix Q. */ int lpf_update_it(LPF *lpf, int j, int bh, int len, const int ind[], const double val[]) { int m0 = lpf->m0; int m = lpf->m; #if _GLPLPF_DEBUG double *B = lpf->B; #endif int n = lpf->n; int *R_ptr = lpf->R_ptr; int *R_len = lpf->R_len; int *S_ptr = lpf->S_ptr; int *S_len = lpf->S_len; int *P_row = lpf->P_row; int *P_col = lpf->P_col; int *Q_row = lpf->Q_row; int *Q_col = lpf->Q_col; int v_ptr = lpf->v_ptr; int *v_ind = lpf->v_ind; double *v_val = lpf->v_val; double *a = lpf->work2; /* new column */ double *fg = lpf->work1, *f = fg, *g = fg + m0; double *vw = lpf->work2, *v = vw, *w = vw + m0; double *x = g, *y = w, z; int i, ii, k, ret; xassert(bh == bh); if (!lpf->valid) xfault("lpf_update_it: the factorization is not valid\n"); if (!(1 <= j && j <= m)) xfault("lpf_update_it: j = %d; column number out of range\n", j); xassert(0 <= m && m <= m0 + n); /* check if the basis factorization can be expanded */ if (n == lpf->n_max) { lpf->valid = 0; ret = LPF_ELIMIT; goto done; } /* convert new j-th column of B to dense format */ for (i = 1; i <= m; i++) a[i] = 0.0; for (k = 1; k <= len; k++) { i = ind[k]; if (!(1 <= i && i <= m)) xfault("lpf_update_it: ind[%d] = %d; row number out of rang" "e\n", k, i); if (a[i] != 0.0) xfault("lpf_update_it: ind[%d] = %d; duplicate row index no" "t allowed\n", k, i); if (val[k] == 0.0) xfault("lpf_update_it: val[%d] = %g; zero element not allow" "ed\n", k, val[k]); a[i] = val[k]; } #if _GLPLPF_DEBUG /* change column in the basis matrix for debugging */ for (i = 1; i <= m; i++) B[(i - 1) * m + j] = a[i]; #endif /* (f g) := inv(P) * (a 0) */ for (i = 1; i <= m0+n; i++) fg[i] = ((ii = P_col[i]) <= m ? a[ii] : 0.0); /* (v w) := Q * (ej 0) */ for (i = 1; i <= m0+n; i++) vw[i] = 0.0; vw[Q_col[j]] = 1.0; /* f1 := inv(L0) * f (new column of R) */ luf_f_solve(lpf->luf, 0, f); /* v1 := inv(U'0) * v (new row of S) */ luf_v_solve(lpf->luf, 1, v); /* we need at most 2 * m0 available locations in the SVA to store new column of matrix R and new row of matrix S */ if (lpf->v_size < v_ptr + m0 + m0) { enlarge_sva(lpf, v_ptr + m0 + m0); v_ind = lpf->v_ind; v_val = lpf->v_val; } /* store new column of R */ R_ptr[n+1] = v_ptr; for (i = 1; i <= m0; i++) { if (f[i] != 0.0) v_ind[v_ptr] = i, v_val[v_ptr] = f[i], v_ptr++; } R_len[n+1] = v_ptr - lpf->v_ptr; lpf->v_ptr = v_ptr; /* store new row of S */ S_ptr[n+1] = v_ptr; for (i = 1; i <= m0; i++) { if (v[i] != 0.0) v_ind[v_ptr] = i, v_val[v_ptr] = v[i], v_ptr++; } S_len[n+1] = v_ptr - lpf->v_ptr; lpf->v_ptr = v_ptr; /* x := g - S * f1 (new column of C) */ s_prod(lpf, x, -1.0, f); /* y := w - R' * v1 (new row of C) */ rt_prod(lpf, y, -1.0, v); /* z := - v1 * f1 (new diagonal element of C) */ z = 0.0; for (i = 1; i <= m0; i++) z -= v[i] * f[i]; /* update factorization of new matrix C */ switch (scf_update_exp(lpf->scf, x, y, z)) { case 0: break; case SCF_ESING: lpf->valid = 0; ret = LPF_ESING; goto done; case SCF_ELIMIT: xassert(lpf != lpf); default: xassert(lpf != lpf); } /* expand matrix P */ P_row[m0+n+1] = P_col[m0+n+1] = m0+n+1; /* expand matrix Q */ Q_row[m0+n+1] = Q_col[m0+n+1] = m0+n+1; /* permute j-th and last (just added) column of matrix Q */ i = Q_col[j], ii = Q_col[m0+n+1]; Q_row[i] = m0+n+1, Q_col[m0+n+1] = i; Q_row[ii] = j, Q_col[j] = ii; /* increase the number of additional rows and columns */ lpf->n++; xassert(lpf->n <= lpf->n_max); /* the factorization has been successfully updated */ ret = 0; done: /* return to the calling program */ return ret; } /*********************************************************************** * NAME * * lpf_delete_it - delete LP basis factorization * * SYNOPSIS * * #include "glplpf.h" * void lpf_delete_it(LPF *lpf) * * DESCRIPTION * * The routine lpf_delete_it deletes LP basis factorization specified * by the parameter lpf and frees all memory allocated to this program * object. */ void lpf_delete_it(LPF *lpf) { luf_delete_it(lpf->luf); #if _GLPLPF_DEBUG if (lpf->B != NULL) xfree(lpf->B); #else xassert(lpf->B == NULL); #endif if (lpf->R_ptr != NULL) xfree(lpf->R_ptr); if (lpf->R_len != NULL) xfree(lpf->R_len); if (lpf->S_ptr != NULL) xfree(lpf->S_ptr); if (lpf->S_len != NULL) xfree(lpf->S_len); if (lpf->scf != NULL) scf_delete_it(lpf->scf); if (lpf->P_row != NULL) xfree(lpf->P_row); if (lpf->P_col != NULL) xfree(lpf->P_col); if (lpf->Q_row != NULL) xfree(lpf->Q_row); if (lpf->Q_col != NULL) xfree(lpf->Q_col); if (lpf->v_ind != NULL) xfree(lpf->v_ind); if (lpf->v_val != NULL) xfree(lpf->v_val); if (lpf->work1 != NULL) xfree(lpf->work1); if (lpf->work2 != NULL) xfree(lpf->work2); xfree(lpf); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glplux.h0000644000076500000240000002122213524616144025062 0ustar tamasstaff00000000000000/* glplux.h (LU-factorization, bignum arithmetic) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPLUX_H #define GLPLUX_H #include "glpdmp.h" #include "glpgmp.h" /*---------------------------------------------------------------------- // The structure LUX defines LU-factorization of a square matrix A, // which is the following quartet: // // [A] = (F, V, P, Q), (1) // // where F and V are such matrices that // // A = F * V, (2) // // and P and Q are such permutation matrices that the matrix // // L = P * F * inv(P) (3) // // is lower triangular with unity diagonal, and the matrix // // U = P * V * Q (4) // // is upper triangular. All the matrices have the order n. // // The matrices F and V are stored in row/column-wise sparse format as // row and column linked lists of non-zero elements. Unity elements on // the main diagonal of the matrix F are not stored. Pivot elements of // the matrix V (that correspond to diagonal elements of the matrix U) // are also missing from the row and column lists and stored separately // in an ordinary array. // // The permutation matrices P and Q are stored as ordinary arrays using // both row- and column-like formats. // // The matrices L and U being completely defined by the matrices F, V, // P, and Q are not stored explicitly. // // It is easy to show that the factorization (1)-(3) is some version of // LU-factorization. Indeed, from (3) and (4) it follows that: // // F = inv(P) * L * P, // // V = inv(P) * U * inv(Q), // // and substitution into (2) gives: // // A = F * V = inv(P) * L * U * inv(Q). // // For more details see the program documentation. */ typedef struct LUX LUX; typedef struct LUXELM LUXELM; typedef struct LUXWKA LUXWKA; struct LUX { /* LU-factorization of a square matrix */ int n; /* the order of matrices A, F, V, P, Q */ DMP *pool; /* memory pool for elements of matrices F and V */ LUXELM **F_row; /* LUXELM *F_row[1+n]; */ /* F_row[0] is not used; F_row[i], 1 <= i <= n, is a pointer to the list of elements in i-th row of matrix F (diagonal elements are not stored) */ LUXELM **F_col; /* LUXELM *F_col[1+n]; */ /* F_col[0] is not used; F_col[j], 1 <= j <= n, is a pointer to the list of elements in j-th column of matrix F (diagonal elements are not stored) */ mpq_t *V_piv; /* mpq_t V_piv[1+n]; */ /* V_piv[0] is not used; V_piv[p], 1 <= p <= n, is a pivot element v[p,q] corresponding to a diagonal element u[k,k] of matrix U = P*V*Q (used on k-th elimination step, k = 1, 2, ..., n) */ LUXELM **V_row; /* LUXELM *V_row[1+n]; */ /* V_row[0] is not used; V_row[i], 1 <= i <= n, is a pointer to the list of elements in i-th row of matrix V (except pivot elements) */ LUXELM **V_col; /* LUXELM *V_col[1+n]; */ /* V_col[0] is not used; V_col[j], 1 <= j <= n, is a pointer to the list of elements in j-th column of matrix V (except pivot elements) */ int *P_row; /* int P_row[1+n]; */ /* P_row[0] is not used; P_row[i] = j means that p[i,j] = 1, where p[i,j] is an element of permutation matrix P */ int *P_col; /* int P_col[1+n]; */ /* P_col[0] is not used; P_col[j] = i means that p[i,j] = 1, where p[i,j] is an element of permutation matrix P */ /* if i-th row or column of matrix F is i'-th row or column of matrix L = P*F*inv(P), or if i-th row of matrix V is i'-th row of matrix U = P*V*Q, then P_row[i'] = i and P_col[i] = i' */ int *Q_row; /* int Q_row[1+n]; */ /* Q_row[0] is not used; Q_row[i] = j means that q[i,j] = 1, where q[i,j] is an element of permutation matrix Q */ int *Q_col; /* int Q_col[1+n]; */ /* Q_col[0] is not used; Q_col[j] = i means that q[i,j] = 1, where q[i,j] is an element of permutation matrix Q */ /* if j-th column of matrix V is j'-th column of matrix U = P*V*Q, then Q_row[j] = j' and Q_col[j'] = j */ int rank; /* the (exact) rank of matrices A and V */ }; struct LUXELM { /* element of matrix F or V */ int i; /* row index, 1 <= i <= m */ int j; /* column index, 1 <= j <= n */ mpq_t val; /* numeric (non-zero) element value */ LUXELM *r_prev; /* pointer to previous element in the same row */ LUXELM *r_next; /* pointer to next element in the same row */ LUXELM *c_prev; /* pointer to previous element in the same column */ LUXELM *c_next; /* pointer to next element in the same column */ }; struct LUXWKA { /* working area (used only during factorization) */ /* in order to efficiently implement Markowitz strategy and Duff search technique there are two families {R[0], R[1], ..., R[n]} and {C[0], C[1], ..., C[n]}; member R[k] is a set of active rows of matrix V having k non-zeros, and member C[k] is a set of active columns of matrix V having k non-zeros (in the active submatrix); each set R[k] and C[k] is implemented as a separate doubly linked list */ int *R_len; /* int R_len[1+n]; */ /* R_len[0] is not used; R_len[i], 1 <= i <= n, is the number of non-zero elements in i-th row of matrix V (that is the length of i-th row) */ int *R_head; /* int R_head[1+n]; */ /* R_head[k], 0 <= k <= n, is the number of a first row, which is active and whose length is k */ int *R_prev; /* int R_prev[1+n]; */ /* R_prev[0] is not used; R_prev[i], 1 <= i <= n, is the number of a previous row, which is active and has the same length as i-th row */ int *R_next; /* int R_next[1+n]; */ /* R_prev[0] is not used; R_prev[i], 1 <= i <= n, is the number of a next row, which is active and has the same length as i-th row */ int *C_len; /* int C_len[1+n]; */ /* C_len[0] is not used; C_len[j], 1 <= j <= n, is the number of non-zero elements in j-th column of the active submatrix of matrix V (that is the length of j-th column in the active submatrix) */ int *C_head; /* int C_head[1+n]; */ /* C_head[k], 0 <= k <= n, is the number of a first column, which is active and whose length is k */ int *C_prev; /* int C_prev[1+n]; */ /* C_prev[0] is not used; C_prev[j], 1 <= j <= n, is the number of a previous column, which is active and has the same length as j-th column */ int *C_next; /* int C_next[1+n]; */ /* C_next[0] is not used; C_next[j], 1 <= j <= n, is the number of a next column, which is active and has the same length as j-th column */ }; #define lux_create _glp_lux_create #define lux_decomp _glp_lux_decomp #define lux_f_solve _glp_lux_f_solve #define lux_v_solve _glp_lux_v_solve #define lux_solve _glp_lux_solve #define lux_delete _glp_lux_delete LUX *lux_create(int n); /* create LU-factorization */ int lux_decomp(LUX *lux, int (*col)(void *info, int j, int ind[], mpq_t val[]), void *info); /* compute LU-factorization */ void lux_f_solve(LUX *lux, int tr, mpq_t x[]); /* solve system F*x = b or F'*x = b */ void lux_v_solve(LUX *lux, int tr, mpq_t x[]); /* solve system V*x = b or V'*x = b */ void lux_solve(LUX *lux, int tr, mpq_t x[]); /* solve system A*x = b or A'*x = b */ void lux_delete(LUX *lux); /* delete LU-factorization */ #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpnet03.c0000644000076500000240000006040513524616144025204 0ustar tamasstaff00000000000000/* glpnet03.c (Klingman's network problem generator) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * This code is the result of translation of the Fortran program NETGEN * developed by Dr. Darwin Klingman, which is publically available from * NETLIB at . * * The translation was made by Andrew Makhorin . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glpapi.h" /*********************************************************************** * NAME * * glp_netgen - Klingman's network problem generator * * SYNOPSIS * * int glp_netgen(glp_graph *G, int v_rhs, int a_cap, int a_cost, * const int parm[1+15]); * * DESCRIPTION * * The routine glp_netgen is a network problem generator developed by * Dr. Darwin Klingman. It can create capacitated and uncapacitated * minimum cost flow (or transshipment), transportation, and assignment * problems. * * The parameter G specifies the graph object, to which the generated * problem data have to be stored. Note that on entry the graph object * is erased with the routine glp_erase_graph. * * The parameter v_rhs specifies an offset of the field of type double * in the vertex data block, to which the routine stores the supply or * demand value. If v_rhs < 0, the value is not stored. * * The parameter a_cap specifies an offset of the field of type double * in the arc data block, to which the routine stores the arc capacity. * If a_cap < 0, the capacity is not stored. * * The parameter a_cost specifies an offset of the field of type double * in the arc data block, to which the routine stores the per-unit cost * if the arc flow. If a_cost < 0, the cost is not stored. * * The array parm contains description of the network to be generated: * * parm[0] not used * parm[1] (iseed) 8-digit positive random number seed * parm[2] (nprob) 8-digit problem id number * parm[3] (nodes) total number of nodes * parm[4] (nsorc) total number of source nodes (including * transshipment nodes) * parm[5] (nsink) total number of sink nodes (including * transshipment nodes) * parm[6] (iarcs) number of arcs * parm[7] (mincst) minimum cost for arcs * parm[8] (maxcst) maximum cost for arcs * parm[9] (itsup) total supply * parm[10] (ntsorc) number of transshipment source nodes * parm[11] (ntsink) number of transshipment sink nodes * parm[12] (iphic) percentage of skeleton arcs to be given * the maximum cost * parm[13] (ipcap) percentage of arcs to be capacitated * parm[14] (mincap) minimum upper bound for capacitated arcs * parm[15] (maxcap) maximum upper bound for capacitated arcs * * The routine generates a transportation problem if: * * nsorc + nsink = nodes, ntsorc = 0, and ntsink = 0. * * The routine generates an assignment problem if the requirements for * a transportation problem are met and: * * nsorc = nsink and itsup = nsorc. * * RETURNS * * If the instance was successfully generated, the routine glp_netgen * returns zero; otherwise, if specified parameters are inconsistent, * the routine returns a non-zero error code. * * REFERENCES * * D.Klingman, A.Napier, and J.Stutz. NETGEN: A program for generating * large scale capacitated assignment, transportation, and minimum cost * flow networks. Management Science 20 (1974), 814-20. */ struct csa { /* common storage area */ glp_graph *G; int v_rhs, a_cap, a_cost; int nodes, iarcs, mincst, maxcst, itsup, nsorc, nsink, nonsor, nfsink, narcs, nsort, nftsor, ipcap, mincap, maxcap, ktl, nodlft, *ipred, *ihead, *itail, *iflag, *isup, *lsinks, mult, modul, i15, i16, jran; }; #define G (csa->G) #define v_rhs (csa->v_rhs) #define a_cap (csa->a_cap) #define a_cost (csa->a_cost) #define nodes (csa->nodes) #define iarcs (csa->iarcs) #define mincst (csa->mincst) #define maxcst (csa->maxcst) #define itsup (csa->itsup) #define nsorc (csa->nsorc) #define nsink (csa->nsink) #define nonsor (csa->nonsor) #define nfsink (csa->nfsink) #define narcs (csa->narcs) #define nsort (csa->nsort) #define nftsor (csa->nftsor) #define ipcap (csa->ipcap) #define mincap (csa->mincap) #define maxcap (csa->maxcap) #define ktl (csa->ktl) #define nodlft (csa->nodlft) #if 0 /* spent a day to find out this bug */ #define ist (csa->ist) #else #define ist (ipred[0]) #endif #define ipred (csa->ipred) #define ihead (csa->ihead) #define itail (csa->itail) #define iflag (csa->iflag) #define isup (csa->isup) #define lsinks (csa->lsinks) #define mult (csa->mult) #define modul (csa->modul) #define i15 (csa->i15) #define i16 (csa->i16) #define jran (csa->jran) static void cresup(struct csa *csa); static void chain(struct csa *csa, int lpick, int lsorc); static void chnarc(struct csa *csa, int lsorc); static void sort(struct csa *csa); static void pickj(struct csa *csa, int it); static void assign(struct csa *csa); static void setran(struct csa *csa, int iseed); static int iran(struct csa *csa, int ilow, int ihigh); int glp_netgen(glp_graph *G_, int _v_rhs, int _a_cap, int _a_cost, const int parm[1+15]) { struct csa _csa, *csa = &_csa; int iseed, nprob, ntsorc, ntsink, iphic, i, nskel, nltr, ltsink, ntrans, npsink, nftr, npsorc, ntravl, ntrrem, lsorc, lpick, nsksr, nsrchn, j, item, l, ks, k, ksp, li, n, ii, it, ih, icap, jcap, icost, jcost, ret; G = G_; v_rhs = _v_rhs; a_cap = _a_cap; a_cost = _a_cost; if (G != NULL) { if (v_rhs >= 0 && v_rhs > G->v_size - (int)sizeof(double)) xerror("glp_netgen: v_rhs = %d; invalid offset\n", v_rhs); if (a_cap >= 0 && a_cap > G->a_size - (int)sizeof(double)) xerror("glp_netgen: a_cap = %d; invalid offset\n", a_cap); if (a_cost >= 0 && a_cost > G->a_size - (int)sizeof(double)) xerror("glp_netgen: a_cost = %d; invalid offset\n", a_cost); } /* Input the user's random number seed and fix it if non-positive. */ iseed = parm[1]; nprob = parm[2]; if (iseed <= 0) iseed = 13502460; setran(csa, iseed); /* Input the user's problem characteristics. */ nodes = parm[3]; nsorc = parm[4]; nsink = parm[5]; iarcs = parm[6]; mincst = parm[7]; maxcst = parm[8]; itsup = parm[9]; ntsorc = parm[10]; ntsink = parm[11]; iphic = parm[12]; ipcap = parm[13]; mincap = parm[14]; maxcap = parm[15]; /* Check the size of the problem. */ if (!(10 <= nodes && nodes <= 100000)) { ret = 1; goto done; } /* Check user supplied parameters for consistency. */ if (!(nsorc >= 0 && nsink >= 0 && nsorc + nsink <= nodes)) { ret = 2; goto done; } if (iarcs < 0) { ret = 3; goto done; } if (mincst > maxcst) { ret = 4; goto done; } if (itsup < 0) { ret = 5; goto done; } if (!(0 <= ntsorc && ntsorc <= nsorc)) { ret = 6; goto done; } if (!(0 <= ntsink && ntsink <= nsink)) { ret = 7; goto done; } if (!(0 <= iphic && iphic <= 100)) { ret = 8; goto done; } if (!(0 <= ipcap && ipcap <= 100)) { ret = 9; goto done; } if (mincap > maxcap) { ret = 10; goto done; } /* Initailize the graph object. */ if (G != NULL) { glp_erase_graph(G, G->v_size, G->a_size); glp_add_vertices(G, nodes); if (v_rhs >= 0) { double zero = 0.0; for (i = 1; i <= nodes; i++) { glp_vertex *v = G->v[i]; memcpy((char *)v->data + v_rhs, &zero, sizeof(double)); } } } /* Allocate working arrays. */ ipred = xcalloc(1+nodes, sizeof(int)); ihead = xcalloc(1+nodes, sizeof(int)); itail = xcalloc(1+nodes, sizeof(int)); iflag = xcalloc(1+nodes, sizeof(int)); isup = xcalloc(1+nodes, sizeof(int)); lsinks = xcalloc(1+nodes, sizeof(int)); /* Print the problem documentation records. */ if (G == NULL) { xprintf("BEGIN\n"); xprintf("NETGEN PROBLEM%8d%10s%10d NODES AND%10d ARCS\n", nprob, "", nodes, iarcs); xprintf("USER:%11d%11d%11d%11d%11d%11d\nDATA:%11d%11d%11d%11d%" "11d%11d\n", iseed, nsorc, nsink, mincst, maxcst, itsup, ntsorc, ntsink, iphic, ipcap, mincap, maxcap); } else glp_set_graph_name(G, "NETGEN"); /* Set various constants used in the program. */ narcs = 0; nskel = 0; nltr = nodes - nsink; ltsink = nltr + ntsink; ntrans = nltr - nsorc; nfsink = nltr + 1; nonsor = nodes - nsorc + ntsorc; npsink = nsink - ntsink; nodlft = nodes - nsink + ntsink; nftr = nsorc + 1; nftsor = nsorc - ntsorc + 1; npsorc = nsorc - ntsorc; /* Randomly distribute the supply among the source nodes. */ if (npsorc + npsink == nodes && npsorc == npsink && itsup == nsorc) { assign(csa); nskel = nsorc; goto L390; } cresup(csa); /* Print the supply records. */ if (G == NULL) { xprintf("SUPPLY\n"); for (i = 1; i <= nsorc; i++) xprintf("%6s%6d%18s%10d\n", "", i, "", isup[i]); xprintf("ARCS\n"); } else { if (v_rhs >= 0) { for (i = 1; i <= nsorc; i++) { double temp = (double)isup[i]; glp_vertex *v = G->v[i]; memcpy((char *)v->data + v_rhs, &temp, sizeof(double)); } } } /* Make the sources point to themselves in ipred array. */ for (i = 1; i <= nsorc; i++) ipred[i] = i; if (ntrans == 0) goto L170; /* Chain the transshipment nodes together in the ipred array. */ ist = nftr; ipred[nltr] = 0; for (i = nftr; i < nltr; i++) ipred[i] = i+1; /* Form even length chains for 60 percent of the transshipments.*/ ntravl = 6 * ntrans / 10; ntrrem = ntrans - ntravl; L140: lsorc = 1; while (ntravl != 0) { lpick = iran(csa, 1, ntravl + ntrrem); ntravl--; chain(csa, lpick, lsorc); if (lsorc == nsorc) goto L140; lsorc++; } /* Add the remaining transshipments to the chains. */ while (ntrrem != 0) { lpick = iran(csa, 1, ntrrem); ntrrem--; lsorc = iran(csa, 1, nsorc); chain(csa, lpick, lsorc); } L170: /* Set all demands equal to zero. */ for (i = nfsink; i <= nodes; i++) ipred[i] = 0; /* The following loop takes one chain at a time (through the use of logic contained in the loop and calls to other routines) and creates the remaining network arcs. */ for (lsorc = 1; lsorc <= nsorc; lsorc++) { chnarc(csa, lsorc); for (i = nfsink; i <= nodes; i++) iflag[i] = 0; /* Choose the number of sinks to be hooked up to the current chain. */ if (ntrans != 0) nsksr = (nsort * 2 * nsink) / ntrans; else nsksr = nsink / nsorc + 1; if (nsksr < 2) nsksr = 2; if (nsksr > nsink) nsksr = nsink; nsrchn = nsort; /* Randomly pick nsksr sinks and put their names in lsinks. */ ktl = nsink; for (j = 1; j <= nsksr; j++) { item = iran(csa, 1, ktl); ktl--; for (l = nfsink; l <= nodes; l++) { if (iflag[l] != 1) { item--; if (item == 0) goto L230; } } break; L230: lsinks[j] = l; iflag[l] = 1; } /* If last source chain, add all sinks with zero demand to lsinks list. */ if (lsorc == nsorc) { for (j = nfsink; j <= nodes; j++) { if (ipred[j] == 0 && iflag[j] != 1) { nsksr++; lsinks[nsksr] = j; iflag[j] = 1; } } } /* Create demands for group of sinks in lsinks. */ ks = isup[lsorc] / nsksr; k = ipred[lsorc]; for (i = 1; i <= nsksr; i++) { nsort++; ksp = iran(csa, 1, ks); j = iran(csa, 1, nsksr); itail[nsort] = k; li = lsinks[i]; ihead[nsort] = li; ipred[li] += ksp; li = lsinks[j]; ipred[li] += ks - ksp; n = iran(csa, 1, nsrchn); k = lsorc; for (ii = 1; ii <= n; ii++) k = ipred[k]; } li = lsinks[1]; ipred[li] += isup[lsorc] - ks * nsksr; nskel += nsort; /* Sort the arcs in the chain from source lsorc using itail as sort key. */ sort(csa); /* Print this part of skeleton and create the arcs for these nodes. */ i = 1; itail[nsort+1] = 0; L300: for (j = nftsor; j <= nodes; j++) iflag[j] = 0; ktl = nonsor - 1; it = itail[i]; iflag[it] = 1; L320: ih = ihead[i]; iflag[ih] = 1; narcs++; ktl--; /* Determine if this skeleton arc should be capacitated. */ icap = itsup; jcap = iran(csa, 1, 100); if (jcap <= ipcap) { icap = isup[lsorc]; if (mincap > icap) icap = mincap; } /* Determine if this skeleton arc should have the maximum cost. */ icost = maxcst; jcost = iran(csa, 1, 100); if (jcost > iphic) icost = iran(csa, mincst, maxcst); if (G == NULL) xprintf("%6s%6d%6d%2s%10d%10d\n", "", it, ih, "", icost, icap); else { glp_arc *a = glp_add_arc(G, it, ih); if (a_cap >= 0) { double temp = (double)icap; memcpy((char *)a->data + a_cap, &temp, sizeof(double)); } if (a_cost >= 0) { double temp = (double)icost; memcpy((char *)a->data + a_cost, &temp, sizeof(double)); } } i++; if (itail[i] == it) goto L320; pickj(csa, it); if (i <= nsort) goto L300; } /* Create arcs from the transshipment sinks. */ if (ntsink != 0) { for (i = nfsink; i <= ltsink; i++) { for (j = nftsor; j <= nodes; j++) iflag[j] = 0; ktl = nonsor - 1; iflag[i] = 1; pickj(csa, i); } } L390: /* Print the demand records and end record. */ if (G == NULL) { xprintf("DEMAND\n"); for (i = nfsink; i <= nodes; i++) xprintf("%6s%6d%18s%10d\n", "", i, "", ipred[i]); xprintf("END\n"); } else { if (v_rhs >= 0) { for (i = nfsink; i <= nodes; i++) { double temp = - (double)ipred[i]; glp_vertex *v = G->v[i]; memcpy((char *)v->data + v_rhs, &temp, sizeof(double)); } } } /* Free working arrays. */ xfree(ipred); xfree(ihead); xfree(itail); xfree(iflag); xfree(isup); xfree(lsinks); /* The instance has been successfully generated. */ ret = 0; done: return ret; } /*********************************************************************** * The routine cresup randomly distributes the total supply among the * source nodes. */ static void cresup(struct csa *csa) { int i, j, ks, ksp; xassert(itsup > nsorc); ks = itsup / nsorc; for (i = 1; i <= nsorc; i++) isup[i] = 0; for (i = 1; i <= nsorc; i++) { ksp = iran(csa, 1, ks); j = iran(csa, 1, nsorc); isup[i] += ksp; isup[j] += ks - ksp; } j = iran(csa, 1, nsorc); isup[j] += itsup - ks * nsorc; return; } /*********************************************************************** * The routine chain adds node lpick to the end of the chain with source * node lsorc. */ static void chain(struct csa *csa, int lpick, int lsorc) { int i, j, k, l, m; k = 0; m = ist; for (i = 1; i <= lpick; i++) { l = k; k = m; m = ipred[k]; } ipred[l] = m; j = ipred[lsorc]; ipred[k] = j; ipred[lsorc] = k; return; } /*********************************************************************** * The routine chnarc puts the arcs in the chain from source lsorc into * the ihead and itail arrays for sorting. */ static void chnarc(struct csa *csa, int lsorc) { int ito, ifrom; nsort = 0; ito = ipred[lsorc]; L10: if (ito == lsorc) return; nsort++; ifrom = ipred[ito]; ihead[nsort] = ito; itail[nsort] = ifrom; ito = ifrom; goto L10; } /*********************************************************************** * The routine sort sorts the nsort arcs in the ihead and itail arrays. * ihead is used as the sort key (i.e. forward star sort order). */ static void sort(struct csa *csa) { int i, j, k, l, m, n, it; n = nsort; m = n; L10: m /= 2; if (m == 0) return; k = n - m; j = 1; L20: i = j; L30: l = i + m; if (itail[i] <= itail[l]) goto L40; it = itail[i]; itail[i] = itail[l]; itail[l] = it; it = ihead[i]; ihead[i] = ihead[l]; ihead[l] = it; i -= m; if (i >= 1) goto L30; L40: j++; if (j <= k) goto L20; goto L10; } /*********************************************************************** * The routine pickj creates a random number of arcs out of node 'it'. * Various parameters are dynamically adjusted in an attempt to ensure * that the generated network has the correct number of arcs. */ static void pickj(struct csa *csa, int it) { int j, k, l, nn, nupbnd, icap, jcap, icost; if ((nodlft - 1) * 2 > iarcs - narcs - 1) { nodlft--; return; } if ((iarcs - narcs + nonsor - ktl - 1) / nodlft - nonsor + 1 >= 0) k = nonsor; else { nupbnd = (iarcs - narcs - nodlft) / nodlft * 2; L40: k = iran(csa, 1, nupbnd); if (nodlft == 1) k = iarcs - narcs; if ((nodlft - 1) * (nonsor - 1) < iarcs - narcs - k) goto L40; } nodlft--; for (j = 1; j <= k; j++) { nn = iran(csa, 1, ktl); ktl--; for (l = nftsor; l <= nodes; l++) { if (iflag[l] != 1) { nn--; if (nn == 0) goto L70; } } return; L70: iflag[l] = 1; icap = itsup; jcap = iran(csa, 1, 100); if (jcap <= ipcap) icap = iran(csa, mincap, maxcap); icost = iran(csa, mincst, maxcst); if (G == NULL) xprintf("%6s%6d%6d%2s%10d%10d\n", "", it, l, "", icost, icap); else { glp_arc *a = glp_add_arc(G, it, l); if (a_cap >= 0) { double temp = (double)icap; memcpy((char *)a->data + a_cap, &temp, sizeof(double)); } if (a_cost >= 0) { double temp = (double)icost; memcpy((char *)a->data + a_cost, &temp, sizeof(double)); } } narcs++; } return; } /*********************************************************************** * The routine assign generate assignment problems. It defines the unit * supplies, builds a skeleton, then calls pickj to create the arcs. */ static void assign(struct csa *csa) { int i, it, nn, l, ll, icost; if (G == NULL) xprintf("SUPPLY\n"); for (i = 1; i <= nsorc; i++) { isup[i] = 1; iflag[i] = 0; if (G == NULL) xprintf("%6s%6d%18s%10d\n", "", i, "", isup[i]); else { if (v_rhs >= 0) { double temp = (double)isup[i]; glp_vertex *v = G->v[i]; memcpy((char *)v->data + v_rhs, &temp, sizeof(double)); } } } if (G == NULL) xprintf("ARCS\n"); for (i = nfsink; i <= nodes; i++) ipred[i] = 1; for (it = 1; it <= nsorc; it++) { for (i = nfsink; i <= nodes; i++) iflag[i] = 0; ktl = nsink - 1; nn = iran(csa, 1, nsink - it + 1); for (l = 1; l <= nsorc; l++) { if (iflag[l] != 1) { nn--; if (nn == 0) break; } } narcs++; ll = nsorc + l; icost = iran(csa, mincst, maxcst); if (G == NULL) xprintf("%6s%6d%6d%2s%10d%10d\n", "", it, ll, "", icost, isup[1]); else { glp_arc *a = glp_add_arc(G, it, ll); if (a_cap >= 0) { double temp = (double)isup[1]; memcpy((char *)a->data + a_cap, &temp, sizeof(double)); } if (a_cost >= 0) { double temp = (double)icost; memcpy((char *)a->data + a_cost, &temp, sizeof(double)); } } iflag[l] = 1; iflag[ll] = 1; pickj(csa, it); } return; } /*********************************************************************** * Portable congruential (uniform) random number generator: * * next_value = ((7**5) * previous_value) modulo ((2**31)-1) * * This generator consists of three routines: * * (1) setran - initializes constants and seed * (2) iran - generates an integer random number * (3) rran - generates a real random number * * The generator requires a machine with at least 32 bits of precision. * The seed (iseed) must be in the range [1,(2**31)-1]. */ static void setran(struct csa *csa, int iseed) { xassert(iseed >= 1); mult = 16807; modul = 2147483647; i15 = 1 << 15; i16 = 1 << 16; jran = iseed; return; } /*********************************************************************** * The routine iran generates an integer random number between ilow and * ihigh. If ilow > ihigh then iran returns ihigh. */ static int iran(struct csa *csa, int ilow, int ihigh) { int ixhi, ixlo, ixalo, leftlo, ixahi, ifulhi, irtlo, iover, irthi, j; ixhi = jran / i16; ixlo = jran - ixhi * i16; ixalo = ixlo * mult; leftlo = ixalo / i16; ixahi = ixhi * mult; ifulhi = ixahi + leftlo; irtlo = ixalo - leftlo * i16; iover = ifulhi / i15; irthi = ifulhi - iover * i15; jran = ((irtlo - modul) + irthi * i16) + iover; if (jran < 0) jran += modul; j = ihigh - ilow + 1; if (j > 0) return jran % j + ilow; else return ihigh; } /**********************************************************************/ #if 0 static int scan(char card[80+1], int pos, int len) { char buf[10+1]; memcpy(buf, &card[pos-1], len); buf[len] = '\0'; return atoi(buf); } int main(void) { int parm[1+15]; char card[80+1]; xassert(fgets(card, sizeof(card), stdin) == card); parm[1] = scan(card, 1, 8); parm[2] = scan(card, 9, 8); xassert(fgets(card, sizeof(card), stdin) == card); parm[3] = scan(card, 1, 5); parm[4] = scan(card, 6, 5); parm[5] = scan(card, 11, 5); parm[6] = scan(card, 16, 5); parm[7] = scan(card, 21, 5); parm[8] = scan(card, 26, 5); parm[9] = scan(card, 31, 10); parm[10] = scan(card, 41, 5); parm[11] = scan(card, 46, 5); parm[12] = scan(card, 51, 5); parm[13] = scan(card, 56, 5); parm[14] = scan(card, 61, 10); parm[15] = scan(card, 71, 10); glp_netgen(NULL, 0, 0, 0, parm); return 0; } #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glplib03.c0000644000076500000240000004347513524616144025174 0ustar tamasstaff00000000000000/* glplib03.c (miscellaneous library routines) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wshorten-64-to-32" #endif #include "glpenv.h" #include "glplib.h" /*********************************************************************** * NAME * * str2int - convert character string to value of int type * * SYNOPSIS * * #include "glplib.h" * int str2int(const char *str, int *val); * * DESCRIPTION * * The routine str2int converts the character string str to a value of * integer type and stores the value into location, which the parameter * val points to (in the case of error content of this location is not * changed). * * RETURNS * * The routine returns one of the following error codes: * * 0 - no error; * 1 - value out of range; * 2 - character string is syntactically incorrect. */ int str2int(const char *str, int *_val) { int d, k, s, val = 0; /* scan optional sign */ if (str[0] == '+') s = +1, k = 1; else if (str[0] == '-') s = -1, k = 1; else s = +1, k = 0; /* check for the first digit */ if (!isdigit((unsigned char)str[k])) return 2; /* scan digits */ while (isdigit((unsigned char)str[k])) { d = str[k++] - '0'; if (s > 0) { if (val > INT_MAX / 10) return 1; val *= 10; if (val > INT_MAX - d) return 1; val += d; } else { if (val < INT_MIN / 10) return 1; val *= 10; if (val < INT_MIN + d) return 1; val -= d; } } /* check for terminator */ if (str[k] != '\0') return 2; /* conversion has been done */ *_val = val; return 0; } /*********************************************************************** * NAME * * str2num - convert character string to value of double type * * SYNOPSIS * * #include "glplib.h" * int str2num(const char *str, double *val); * * DESCRIPTION * * The routine str2num converts the character string str to a value of * double type and stores the value into location, which the parameter * val points to (in the case of error content of this location is not * changed). * * RETURNS * * The routine returns one of the following error codes: * * 0 - no error; * 1 - value out of range; * 2 - character string is syntactically incorrect. */ int str2num(const char *str, double *_val) { int k; double val; /* scan optional sign */ k = (str[0] == '+' || str[0] == '-' ? 1 : 0); /* check for decimal point */ if (str[k] == '.') { k++; /* a digit should follow it */ if (!isdigit((unsigned char)str[k])) return 2; k++; goto frac; } /* integer part should start with a digit */ if (!isdigit((unsigned char)str[k])) return 2; /* scan integer part */ while (isdigit((unsigned char)str[k])) k++; /* check for decimal point */ if (str[k] == '.') k++; frac: /* scan optional fraction part */ while (isdigit((unsigned char)str[k])) k++; /* check for decimal exponent */ if (str[k] == 'E' || str[k] == 'e') { k++; /* scan optional sign */ if (str[k] == '+' || str[k] == '-') k++; /* a digit should follow E, E+ or E- */ if (!isdigit((unsigned char)str[k])) return 2; } /* scan optional exponent part */ while (isdigit((unsigned char)str[k])) k++; /* check for terminator */ if (str[k] != '\0') return 2; /* perform conversion */ { char *endptr; val = strtod(str, &endptr); if (*endptr != '\0') return 2; } /* check for overflow */ if (!(-DBL_MAX <= val && val <= +DBL_MAX)) return 1; /* check for underflow */ if (-DBL_MIN < val && val < +DBL_MIN) val = 0.0; /* conversion has been done */ *_val = val; return 0; } /*********************************************************************** * NAME * * strspx - remove all spaces from character string * * SYNOPSIS * * #include "glplib.h" * char *strspx(char *str); * * DESCRIPTION * * The routine strspx removes all spaces from the character string str. * * RETURNS * * The routine returns a pointer to the character string. * * EXAMPLES * * strspx(" Errare humanum est ") => "Errarehumanumest" * * strspx(" ") => "" */ char *strspx(char *str) { char *s, *t; for (s = t = str; *s; s++) if (*s != ' ') *t++ = *s; *t = '\0'; return str; } /*********************************************************************** * NAME * * strtrim - remove trailing spaces from character string * * SYNOPSIS * * #include "glplib.h" * char *strtrim(char *str); * * DESCRIPTION * * The routine strtrim removes trailing spaces from the character * string str. * * RETURNS * * The routine returns a pointer to the character string. * * EXAMPLES * * strtrim("Errare humanum est ") => "Errare humanum est" * * strtrim(" ") => "" */ char *strtrim(char *str) { char *t; for (t = strrchr(str, '\0') - 1; t >= str; t--) { if (*t != ' ') break; *t = '\0'; } return str; } /*********************************************************************** * NAME * * strrev - reverse character string * * SYNOPSIS * * #include "glplib.h" * char *strrev(char *s); * * DESCRIPTION * * The routine strrev changes characters in a character string s to the * reverse order, except the terminating null character. * * RETURNS * * The routine returns the pointer s. * * EXAMPLES * * strrev("") => "" * * strrev("Today is Monday") => "yadnoM si yadoT" */ char *strrev(char *s) { int i, j; char t; for (i = 0, j = strlen(s)-1; i < j; i++, j--) t = s[i], s[i] = s[j], s[j] = t; return s; } /*********************************************************************** * NAME * * gcd - find greatest common divisor of two integers * * SYNOPSIS * * #include "glplib.h" * int gcd(int x, int y); * * RETURNS * * The routine gcd returns gcd(x, y), the greatest common divisor of * the two positive integers given. * * ALGORITHM * * The routine gcd is based on Euclid's algorithm. * * REFERENCES * * Don Knuth, The Art of Computer Programming, Vol.2: Seminumerical * Algorithms, 3rd Edition, Addison-Wesley, 1997. Section 4.5.2: The * Greatest Common Divisor, pp. 333-56. */ int gcd(int x, int y) { int r; xassert(x > 0 && y > 0); while (y > 0) r = x % y, x = y, y = r; return x; } /*********************************************************************** * NAME * * gcdn - find greatest common divisor of n integers * * SYNOPSIS * * #include "glplib.h" * int gcdn(int n, int x[]); * * RETURNS * * The routine gcdn returns gcd(x[1], x[2], ..., x[n]), the greatest * common divisor of n positive integers given, n > 0. * * BACKGROUND * * The routine gcdn is based on the following identity: * * gcd(x, y, z) = gcd(gcd(x, y), z). * * REFERENCES * * Don Knuth, The Art of Computer Programming, Vol.2: Seminumerical * Algorithms, 3rd Edition, Addison-Wesley, 1997. Section 4.5.2: The * Greatest Common Divisor, pp. 333-56. */ int gcdn(int n, int x[]) { int d, j; xassert(n > 0); for (j = 1; j <= n; j++) { xassert(x[j] > 0); if (j == 1) d = x[1]; else d = gcd(d, x[j]); if (d == 1) break; } return d; } /*********************************************************************** * NAME * * lcm - find least common multiple of two integers * * SYNOPSIS * * #include "glplib.h" * int lcm(int x, int y); * * RETURNS * * The routine lcm returns lcm(x, y), the least common multiple of the * two positive integers given. In case of integer overflow the routine * returns zero. * * BACKGROUND * * The routine lcm is based on the following identity: * * lcm(x, y) = (x * y) / gcd(x, y) = x * [y / gcd(x, y)], * * where gcd(x, y) is the greatest common divisor of x and y. */ int lcm(int x, int y) { xassert(x > 0); xassert(y > 0); y /= gcd(x, y); if (x > INT_MAX / y) return 0; return x * y; } /*********************************************************************** * NAME * * lcmn - find least common multiple of n integers * * SYNOPSIS * * #include "glplib.h" * int lcmn(int n, int x[]); * * RETURNS * * The routine lcmn returns lcm(x[1], x[2], ..., x[n]), the least * common multiple of n positive integers given, n > 0. In case of * integer overflow the routine returns zero. * * BACKGROUND * * The routine lcmn is based on the following identity: * * lcmn(x, y, z) = lcm(lcm(x, y), z), * * where lcm(x, y) is the least common multiple of x and y. */ int lcmn(int n, int x[]) { int m, j; xassert(n > 0); for (j = 1; j <= n; j++) { xassert(x[j] > 0); if (j == 1) m = x[1]; else m = lcm(m, x[j]); if (m == 0) break; } return m; } /*********************************************************************** * NAME * * round2n - round floating-point number to nearest power of two * * SYNOPSIS * * #include "glplib.h" * double round2n(double x); * * RETURNS * * Given a positive floating-point value x the routine round2n returns * 2^n such that |x - 2^n| is minimal. * * EXAMPLES * * round2n(10.1) = 2^3 = 8 * round2n(15.3) = 2^4 = 16 * round2n(0.01) = 2^(-7) = 0.0078125 * * BACKGROUND * * Let x = f * 2^e, where 0.5 <= f < 1 is a normalized fractional part, * e is an integer exponent. Then, obviously, 0.5 * 2^e <= x < 2^e, so * if x - 0.5 * 2^e <= 2^e - x, we choose 0.5 * 2^e = 2^(e-1), and 2^e * otherwise. The latter condition can be written as 2 * x <= 1.5 * 2^e * or 2 * f * 2^e <= 1.5 * 2^e or, finally, f <= 0.75. */ double round2n(double x) { int e; double f; xassert(x > 0.0); f = frexp(x, &e); return ldexp(1.0, f <= 0.75 ? e-1 : e); } /*********************************************************************** * NAME * * fp2rat - convert floating-point number to rational number * * SYNOPSIS * * #include "glplib.h" * int fp2rat(double x, double eps, double *p, double *q); * * DESCRIPTION * * Given a floating-point number 0 <= x < 1 the routine fp2rat finds * its "best" rational approximation p / q, where p >= 0 and q > 0 are * integer numbers, such that |x - p / q| <= eps. * * RETURNS * * The routine fp2rat returns the number of iterations used to achieve * the specified precision eps. * * EXAMPLES * * For x = sqrt(2) - 1 = 0.414213562373095 and eps = 1e-6 the routine * gives p = 408 and q = 985, where 408 / 985 = 0.414213197969543. * * BACKGROUND * * It is well known that every positive real number x can be expressed * as the following continued fraction: * * x = b[0] + a[1] * ------------------------ * b[1] + a[2] * ----------------- * b[2] + a[3] * ---------- * b[3] + ... * * where: * * a[k] = 1, k = 0, 1, 2, ... * * b[k] = floor(x[k]), k = 0, 1, 2, ... * * x[0] = x, * * x[k] = 1 / frac(x[k-1]), k = 1, 2, 3, ... * * To find the "best" rational approximation of x the routine computes * partial fractions f[k] by dropping after k terms as follows: * * f[k] = A[k] / B[k], * * where: * * A[-1] = 1, A[0] = b[0], B[-1] = 0, B[0] = 1, * * A[k] = b[k] * A[k-1] + a[k] * A[k-2], * * B[k] = b[k] * B[k-1] + a[k] * B[k-2]. * * Once the condition * * |x - f[k]| <= eps * * has been satisfied, the routine reports p = A[k] and q = B[k] as the * final answer. * * In the table below here is some statistics obtained for one million * random numbers uniformly distributed in the range [0, 1). * * eps max p mean p max q mean q max k mean k * ------------------------------------------------------------- * 1e-1 8 1.6 9 3.2 3 1.4 * 1e-2 98 6.2 99 12.4 5 2.4 * 1e-3 997 20.7 998 41.5 8 3.4 * 1e-4 9959 66.6 9960 133.5 10 4.4 * 1e-5 97403 211.7 97404 424.2 13 5.3 * 1e-6 479669 669.9 479670 1342.9 15 6.3 * 1e-7 1579030 2127.3 3962146 4257.8 16 7.3 * 1e-8 26188823 6749.4 26188824 13503.4 19 8.2 * * REFERENCES * * W. B. Jones and W. J. Thron, "Continued Fractions: Analytic Theory * and Applications," Encyclopedia on Mathematics and Its Applications, * Addison-Wesley, 1980. */ int fp2rat(double x, double eps, double *p, double *q) { int k; double xk, Akm1, Ak, Bkm1, Bk, ak, bk, fk, temp; if (!(0.0 <= x && x < 1.0)) xerror("fp2rat: x = %g; number out of range\n", x); for (k = 0; ; k++) { xassert(k <= 100); if (k == 0) { /* x[0] = x */ xk = x; /* A[-1] = 1 */ Akm1 = 1.0; /* A[0] = b[0] = floor(x[0]) = 0 */ Ak = 0.0; /* B[-1] = 0 */ Bkm1 = 0.0; /* B[0] = 1 */ Bk = 1.0; } else { /* x[k] = 1 / frac(x[k-1]) */ temp = xk - floor(xk); xassert(temp != 0.0); xk = 1.0 / temp; /* a[k] = 1 */ ak = 1.0; /* b[k] = floor(x[k]) */ bk = floor(xk); /* A[k] = b[k] * A[k-1] + a[k] * A[k-2] */ temp = bk * Ak + ak * Akm1; Akm1 = Ak, Ak = temp; /* B[k] = b[k] * B[k-1] + a[k] * B[k-2] */ temp = bk * Bk + ak * Bkm1; Bkm1 = Bk, Bk = temp; } /* f[k] = A[k] / B[k] */ fk = Ak / Bk; #if 0 print("%.*g / %.*g = %.*g", DBL_DIG, Ak, DBL_DIG, Bk, DBL_DIG, fk); #endif if (fabs(x - fk) <= eps) break; } *p = Ak; *q = Bk; return k; } /*********************************************************************** * NAME * * jday - convert calendar date to Julian day number * * SYNOPSIS * * #include "glplib.h" * int jday(int d, int m, int y); * * DESCRIPTION * * The routine jday converts a calendar date, Gregorian calendar, to * corresponding Julian day number j. * * From the given day d, month m, and year y, the Julian day number j * is computed without using tables. * * The routine is valid for 1 <= y <= 4000. * * RETURNS * * The routine jday returns the Julian day number, or negative value if * the specified date is incorrect. * * REFERENCES * * R. G. Tantzen, Algorithm 199: conversions between calendar date and * Julian day number, Communications of the ACM, vol. 6, no. 8, p. 444, * Aug. 1963. */ int jday(int d, int m, int y) { int c, ya, j, dd; if (!(1 <= d && d <= 31 && 1 <= m && m <= 12 && 1 <= y && y <= 4000)) { j = -1; goto done; } if (m >= 3) m -= 3; else m += 9, y--; c = y / 100; ya = y - 100 * c; j = (146097 * c) / 4 + (1461 * ya) / 4 + (153 * m + 2) / 5 + d + 1721119; jdate(j, &dd, NULL, NULL); if (d != dd) j = -1; done: return j; } /*********************************************************************** * NAME * * jdate - convert Julian day number to calendar date * * SYNOPSIS * * #include "glplib.h" * void jdate(int j, int *d, int *m, int *y); * * DESCRIPTION * * The routine jdate converts a Julian day number j to corresponding * calendar date, Gregorian calendar. * * The day d, month m, and year y are computed without using tables and * stored in corresponding locations. * * The routine is valid for 1721426 <= j <= 3182395. * * RETURNS * * If the conversion is successful, the routine returns zero, otherwise * non-zero. * * REFERENCES * * R. G. Tantzen, Algorithm 199: conversions between calendar date and * Julian day number, Communications of the ACM, vol. 6, no. 8, p. 444, * Aug. 1963. */ int jdate(int j, int *_d, int *_m, int *_y) { int d, m, y, ret = 0; if (!(1721426 <= j && j <= 3182395)) { ret = 1; goto done; } j -= 1721119; y = (4 * j - 1) / 146097; j = (4 * j - 1) % 146097; d = j / 4; j = (4 * d + 3) / 1461; d = (4 * d + 3) % 1461; d = (d + 4) / 4; m = (5 * d - 3) / 153; d = (5 * d - 3) % 153; d = (d + 5) / 5; y = 100 * y + j; if (m <= 9) m += 3; else m -= 9, y++; if (_d != NULL) *_d = d; if (_m != NULL) *_m = m; if (_y != NULL) *_y = y; done: return ret; } #if 0 int main(void) { int jbeg, jend, j, d, m, y; jbeg = jday(1, 1, 1); jend = jday(31, 12, 4000); for (j = jbeg; j <= jend; j++) { xassert(jdate(j, &d, &m, &y) == 0); xassert(jday(d, m, y) == j); } xprintf("Routines jday and jdate work correctly.\n"); return 0; } #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpios07.c0000644000076500000240000004523113524616144025214 0ustar tamasstaff00000000000000/* glpios07.c (mixed cover cut generator) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glpios.h" /*---------------------------------------------------------------------- -- COVER INEQUALITIES -- -- Consider the set of feasible solutions to 0-1 knapsack problem: -- -- sum a[j]*x[j] <= b, (1) -- j in J -- -- x[j] is binary, (2) -- -- where, wlog, we assume that a[j] > 0 (since 0-1 variables can be -- complemented) and a[j] <= b (since a[j] > b implies x[j] = 0). -- -- A set C within J is called a cover if -- -- sum a[j] > b. (3) -- j in C -- -- For any cover C the inequality -- -- sum x[j] <= |C| - 1 (4) -- j in C -- -- is called a cover inequality and is valid for (1)-(2). -- -- MIXED COVER INEQUALITIES -- -- Consider the set of feasible solutions to mixed knapsack problem: -- -- sum a[j]*x[j] + y <= b, (5) -- j in J -- -- x[j] is binary, (6) -- -- 0 <= y <= u is continuous, (7) -- -- where again we assume that a[j] > 0. -- -- Let C within J be some set. From (1)-(4) it follows that -- -- sum a[j] > b - y (8) -- j in C -- -- implies -- -- sum x[j] <= |C| - 1. (9) -- j in C -- -- Thus, we need to modify the inequality (9) in such a way that it be -- a constraint only if the condition (8) is satisfied. -- -- Consider the following inequality: -- -- sum x[j] <= |C| - t. (10) -- j in C -- -- If 0 < t <= 1, then (10) is equivalent to (9), because all x[j] are -- binary variables. On the other hand, if t <= 0, (10) being satisfied -- for any values of x[j] is not a constraint. -- -- Let -- -- t' = sum a[j] + y - b. (11) -- j in C -- -- It is understood that the condition t' > 0 is equivalent to (8). -- Besides, from (6)-(7) it follows that t' has an implied upper bound: -- -- t'max = sum a[j] + u - b. (12) -- j in C -- -- This allows to express the parameter t having desired properties: -- -- t = t' / t'max. (13) -- -- In fact, t <= 1 by definition, and t > 0 being equivalent to t' > 0 -- is equivalent to (8). -- -- Thus, the inequality (10), where t is given by formula (13) is valid -- for (5)-(7). -- -- Note that if u = 0, then y = 0, so t = 1, and the conditions (8) and -- (10) is transformed to the conditions (3) and (4). -- -- GENERATING MIXED COVER CUTS -- -- To generate a mixed cover cut in the form (10) we need to find such -- set C which satisfies to the inequality (8) and for which, in turn, -- the inequality (10) is violated in the current point. -- -- Substituting t from (13) to (10) gives: -- -- 1 -- sum x[j] <= |C| - ----- (sum a[j] + y - b), (14) -- j in C t'max j in C -- -- and finally we have the cut inequality in the standard form: -- -- sum x[j] + alfa * y <= beta, (15) -- j in C -- -- where: -- -- alfa = 1 / t'max, (16) -- -- beta = |C| - alfa * (sum a[j] - b). (17) -- j in C */ #if 1 #define MAXTRY 1000 #else #define MAXTRY 10000 #endif static int cover2(int n, double a[], double b, double u, double x[], double y, int cov[], double *_alfa, double *_beta) { /* try to generate mixed cover cut using two-element cover */ int i, j, try = 0, ret = 0; double eps, alfa, beta, temp, rmax = 0.001; eps = 0.001 * (1.0 + fabs(b)); for (i = 0+1; i <= n; i++) for (j = i+1; j <= n; j++) { /* C = {i, j} */ try++; if (try > MAXTRY) goto done; /* check if condition (8) is satisfied */ if (a[i] + a[j] + y > b + eps) { /* compute parameters for inequality (15) */ temp = a[i] + a[j] - b; alfa = 1.0 / (temp + u); beta = 2.0 - alfa * temp; /* compute violation of inequality (15) */ temp = x[i] + x[j] + alfa * y - beta; /* choose C providing maximum violation */ if (rmax < temp) { rmax = temp; cov[1] = i; cov[2] = j; *_alfa = alfa; *_beta = beta; ret = 1; } } } done: return ret; } static int cover3(int n, double a[], double b, double u, double x[], double y, int cov[], double *_alfa, double *_beta) { /* try to generate mixed cover cut using three-element cover */ int i, j, k, try = 0, ret = 0; double eps, alfa, beta, temp, rmax = 0.001; eps = 0.001 * (1.0 + fabs(b)); for (i = 0+1; i <= n; i++) for (j = i+1; j <= n; j++) for (k = j+1; k <= n; k++) { /* C = {i, j, k} */ try++; if (try > MAXTRY) goto done; /* check if condition (8) is satisfied */ if (a[i] + a[j] + a[k] + y > b + eps) { /* compute parameters for inequality (15) */ temp = a[i] + a[j] + a[k] - b; alfa = 1.0 / (temp + u); beta = 3.0 - alfa * temp; /* compute violation of inequality (15) */ temp = x[i] + x[j] + x[k] + alfa * y - beta; /* choose C providing maximum violation */ if (rmax < temp) { rmax = temp; cov[1] = i; cov[2] = j; cov[3] = k; *_alfa = alfa; *_beta = beta; ret = 1; } } } done: return ret; } static int cover4(int n, double a[], double b, double u, double x[], double y, int cov[], double *_alfa, double *_beta) { /* try to generate mixed cover cut using four-element cover */ int i, j, k, l, try = 0, ret = 0; double eps, alfa, beta, temp, rmax = 0.001; eps = 0.001 * (1.0 + fabs(b)); for (i = 0+1; i <= n; i++) for (j = i+1; j <= n; j++) for (k = j+1; k <= n; k++) for (l = k+1; l <= n; l++) { /* C = {i, j, k, l} */ try++; if (try > MAXTRY) goto done; /* check if condition (8) is satisfied */ if (a[i] + a[j] + a[k] + a[l] + y > b + eps) { /* compute parameters for inequality (15) */ temp = a[i] + a[j] + a[k] + a[l] - b; alfa = 1.0 / (temp + u); beta = 4.0 - alfa * temp; /* compute violation of inequality (15) */ temp = x[i] + x[j] + x[k] + x[l] + alfa * y - beta; /* choose C providing maximum violation */ if (rmax < temp) { rmax = temp; cov[1] = i; cov[2] = j; cov[3] = k; cov[4] = l; *_alfa = alfa; *_beta = beta; ret = 1; } } } done: return ret; } static int cover(int n, double a[], double b, double u, double x[], double y, int cov[], double *alfa, double *beta) { /* try to generate mixed cover cut; input (see (5)): n is the number of binary variables; a[1:n] are coefficients at binary variables; b is the right-hand side; u is upper bound of continuous variable; x[1:n] are values of binary variables at current point; y is value of continuous variable at current point; output (see (15), (16), (17)): cov[1:r] are indices of binary variables included in cover C, where r is the set cardinality returned on exit; alfa coefficient at continuous variable; beta is the right-hand side; */ int j; /* perform some sanity checks */ xassert(n >= 2); for (j = 1; j <= n; j++) xassert(a[j] > 0.0); #if 1 /* ??? */ xassert(b > -1e-5); #else xassert(b > 0.0); #endif xassert(u >= 0.0); for (j = 1; j <= n; j++) xassert(0.0 <= x[j] && x[j] <= 1.0); xassert(0.0 <= y && y <= u); /* try to generate mixed cover cut */ if (cover2(n, a, b, u, x, y, cov, alfa, beta)) return 2; if (cover3(n, a, b, u, x, y, cov, alfa, beta)) return 3; if (cover4(n, a, b, u, x, y, cov, alfa, beta)) return 4; return 0; } /*---------------------------------------------------------------------- -- lpx_cover_cut - generate mixed cover cut. -- -- SYNOPSIS -- -- #include "glplpx.h" -- int lpx_cover_cut(LPX *lp, int len, int ind[], double val[], -- double work[]); -- -- DESCRIPTION -- -- The routine lpx_cover_cut generates a mixed cover cut for a given -- row of the MIP problem. -- -- The given row of the MIP problem should be explicitly specified in -- the form: -- -- sum{j in J} a[j]*x[j] <= b. (1) -- -- On entry indices (ordinal numbers) of structural variables, which -- have non-zero constraint coefficients, should be placed in locations -- ind[1], ..., ind[len], and corresponding constraint coefficients -- should be placed in locations val[1], ..., val[len]. The right-hand -- side b should be stored in location val[0]. -- -- The working array work should have at least nb locations, where nb -- is the number of binary variables in (1). -- -- The routine generates a mixed cover cut in the same form as (1) and -- stores the cut coefficients and right-hand side in the same way as -- just described above. -- -- RETURNS -- -- If the cutting plane has been successfully generated, the routine -- returns 1 <= len' <= n, which is the number of non-zero coefficients -- in the inequality constraint. Otherwise, the routine returns zero. */ static int lpx_cover_cut(LPX *lp, int len, int ind[], double val[], double work[]) { int cov[1+4], j, k, nb, newlen, r; double f_min, f_max, alfa, beta, u, *x = work, y; /* substitute and remove fixed variables */ newlen = 0; for (k = 1; k <= len; k++) { j = ind[k]; if (lpx_get_col_type(lp, j) == LPX_FX) val[0] -= val[k] * lpx_get_col_lb(lp, j); else { newlen++; ind[newlen] = ind[k]; val[newlen] = val[k]; } } len = newlen; /* move binary variables to the beginning of the list so that elements 1, 2, ..., nb correspond to binary variables, and elements nb+1, nb+2, ..., len correspond to rest variables */ nb = 0; for (k = 1; k <= len; k++) { j = ind[k]; if (lpx_get_col_kind(lp, j) == LPX_IV && lpx_get_col_type(lp, j) == LPX_DB && lpx_get_col_lb(lp, j) == 0.0 && lpx_get_col_ub(lp, j) == 1.0) { /* binary variable */ int ind_k; double val_k; nb++; ind_k = ind[nb], val_k = val[nb]; ind[nb] = ind[k], val[nb] = val[k]; ind[k] = ind_k, val[k] = val_k; } } /* now the specified row has the form: sum a[j]*x[j] + sum a[j]*y[j] <= b, where x[j] are binary variables, y[j] are rest variables */ /* at least two binary variables are needed */ if (nb < 2) return 0; /* compute implied lower and upper bounds for sum a[j]*y[j] */ f_min = f_max = 0.0; for (k = nb+1; k <= len; k++) { j = ind[k]; /* both bounds must be finite */ if (lpx_get_col_type(lp, j) != LPX_DB) return 0; if (val[k] > 0.0) { f_min += val[k] * lpx_get_col_lb(lp, j); f_max += val[k] * lpx_get_col_ub(lp, j); } else { f_min += val[k] * lpx_get_col_ub(lp, j); f_max += val[k] * lpx_get_col_lb(lp, j); } } /* sum a[j]*x[j] + sum a[j]*y[j] <= b ===> sum a[j]*x[j] + (sum a[j]*y[j] - f_min) <= b - f_min ===> sum a[j]*x[j] + y <= b - f_min, where y = sum a[j]*y[j] - f_min; note that 0 <= y <= u, u = f_max - f_min */ /* determine upper bound of y */ u = f_max - f_min; /* determine value of y at the current point */ y = 0.0; for (k = nb+1; k <= len; k++) { j = ind[k]; y += val[k] * lpx_get_col_prim(lp, j); } y -= f_min; if (y < 0.0) y = 0.0; if (y > u) y = u; /* modify the right-hand side b */ val[0] -= f_min; /* now the transformed row has the form: sum a[j]*x[j] + y <= b, where 0 <= y <= u */ /* determine values of x[j] at the current point */ for (k = 1; k <= nb; k++) { j = ind[k]; x[k] = lpx_get_col_prim(lp, j); if (x[k] < 0.0) x[k] = 0.0; if (x[k] > 1.0) x[k] = 1.0; } /* if a[j] < 0, replace x[j] by its complement 1 - x'[j] */ for (k = 1; k <= nb; k++) { if (val[k] < 0.0) { ind[k] = - ind[k]; val[k] = - val[k]; val[0] += val[k]; x[k] = 1.0 - x[k]; } } /* try to generate a mixed cover cut for the transformed row */ r = cover(nb, val, val[0], u, x, y, cov, &alfa, &beta); if (r == 0) return 0; xassert(2 <= r && r <= 4); /* now the cut is in the form: sum{j in C} x[j] + alfa * y <= beta */ /* store the right-hand side beta */ ind[0] = 0, val[0] = beta; /* restore the original ordinal numbers of x[j] */ for (j = 1; j <= r; j++) cov[j] = ind[cov[j]]; /* store cut coefficients at binary variables complementing back the variables having negative row coefficients */ xassert(r <= nb); for (k = 1; k <= r; k++) { if (cov[k] > 0) { ind[k] = +cov[k]; val[k] = +1.0; } else { ind[k] = -cov[k]; val[k] = -1.0; val[0] -= 1.0; } } /* substitute y = sum a[j]*y[j] - f_min */ for (k = nb+1; k <= len; k++) { r++; ind[r] = ind[k]; val[r] = alfa * val[k]; } val[0] += alfa * f_min; xassert(r <= len); len = r; return len; } /*---------------------------------------------------------------------- -- lpx_eval_row - compute explictily specified row. -- -- SYNOPSIS -- -- #include "glplpx.h" -- double lpx_eval_row(LPX *lp, int len, int ind[], double val[]); -- -- DESCRIPTION -- -- The routine lpx_eval_row computes the primal value of an explicitly -- specified row using current values of structural variables. -- -- The explicitly specified row may be thought as a linear form: -- -- y = a[1]*x[m+1] + a[2]*x[m+2] + ... + a[n]*x[m+n], -- -- where y is an auxiliary variable for this row, a[j] are coefficients -- of the linear form, x[m+j] are structural variables. -- -- On entry column indices and numerical values of non-zero elements of -- the row should be stored in locations ind[1], ..., ind[len] and -- val[1], ..., val[len], where len is the number of non-zero elements. -- The array ind and val are not changed on exit. -- -- RETURNS -- -- The routine returns a computed value of y, the auxiliary variable of -- the specified row. */ static double lpx_eval_row(LPX *lp, int len, int ind[], double val[]) { int n = lpx_get_num_cols(lp); int j, k; double sum = 0.0; if (len < 0) xerror("lpx_eval_row: len = %d; invalid row length\n", len); for (k = 1; k <= len; k++) { j = ind[k]; if (!(1 <= j && j <= n)) xerror("lpx_eval_row: j = %d; column number out of range\n", j); sum += val[k] * lpx_get_col_prim(lp, j); } return sum; } /*********************************************************************** * NAME * * ios_cov_gen - generate mixed cover cuts * * SYNOPSIS * * #include "glpios.h" * void ios_cov_gen(glp_tree *tree); * * DESCRIPTION * * The routine ios_cov_gen generates mixed cover cuts for the current * point and adds them to the cut pool. */ void ios_cov_gen(glp_tree *tree) { glp_prob *prob = tree->mip; int m = lpx_get_num_rows(prob); int n = lpx_get_num_cols(prob); int i, k, type, kase, len, *ind; double r, *val, *work; xassert(lpx_get_status(prob) == LPX_OPT); /* allocate working arrays */ ind = xcalloc(1+n, sizeof(int)); val = xcalloc(1+n, sizeof(double)); work = xcalloc(1+n, sizeof(double)); /* look through all rows */ for (i = 1; i <= m; i++) for (kase = 1; kase <= 2; kase++) { type = lpx_get_row_type(prob, i); if (kase == 1) { /* consider rows of '<=' type */ if (!(type == LPX_UP || type == LPX_DB)) continue; len = lpx_get_mat_row(prob, i, ind, val); val[0] = lpx_get_row_ub(prob, i); } else { /* consider rows of '>=' type */ if (!(type == LPX_LO || type == LPX_DB)) continue; len = lpx_get_mat_row(prob, i, ind, val); for (k = 1; k <= len; k++) val[k] = - val[k]; val[0] = - lpx_get_row_lb(prob, i); } /* generate mixed cover cut: sum{j in J} a[j] * x[j] <= b */ len = lpx_cover_cut(prob, len, ind, val, work); if (len == 0) continue; /* at the current point the cut inequality is violated, i.e. sum{j in J} a[j] * x[j] - b > 0 */ r = lpx_eval_row(prob, len, ind, val) - val[0]; if (r < 1e-3) continue; /* add the cut to the cut pool */ glp_ios_add_row(tree, NULL, GLP_RF_COV, 0, len, ind, val, GLP_UP, val[0]); } /* free working arrays */ xfree(ind); xfree(val); xfree(work); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpssx.h0000644000076500000240000004013013524616144025066 0ustar tamasstaff00000000000000/* glpssx.h (simplex method, bignum arithmetic) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPSSX_H #define GLPSSX_H #include "glpbfx.h" #include "glpenv.h" typedef struct SSX SSX; struct SSX { /* simplex solver workspace */ /*---------------------------------------------------------------------- // LP PROBLEM DATA // // It is assumed that LP problem has the following statement: // // minimize (or maximize) // // z = c[1]*x[1] + ... + c[m+n]*x[m+n] + c[0] (1) // // subject to equality constraints // // x[1] - a[1,1]*x[m+1] - ... - a[1,n]*x[m+n] = 0 // // . . . . . . . (2) // // x[m] - a[m,1]*x[m+1] + ... - a[m,n]*x[m+n] = 0 // // and bounds of variables // // l[1] <= x[1] <= u[1] // // . . . . . . . (3) // // l[m+n] <= x[m+n] <= u[m+n] // // where: // x[1], ..., x[m] - auxiliary variables; // x[m+1], ..., x[m+n] - structural variables; // z - objective function; // c[1], ..., c[m+n] - coefficients of the objective function; // c[0] - constant term of the objective function; // a[1,1], ..., a[m,n] - constraint coefficients; // l[1], ..., l[m+n] - lower bounds of variables; // u[1], ..., u[m+n] - upper bounds of variables. // // Bounds of variables can be finite as well as inifinite. Besides, // lower and upper bounds can be equal to each other. So the following // five types of variables are possible: // // Bounds of variable Type of variable // ------------------------------------------------- // -inf < x[k] < +inf Free (unbounded) variable // l[k] <= x[k] < +inf Variable with lower bound // -inf < x[k] <= u[k] Variable with upper bound // l[k] <= x[k] <= u[k] Double-bounded variable // l[k] = x[k] = u[k] Fixed variable // // Using vector-matrix notations the LP problem (1)-(3) can be written // as follows: // // minimize (or maximize) // // z = c * x + c[0] (4) // // subject to equality constraints // // xR - A * xS = 0 (5) // // and bounds of variables // // l <= x <= u (6) // // where: // xR - vector of auxiliary variables; // xS - vector of structural variables; // x = (xR, xS) - vector of all variables; // z - objective function; // c - vector of objective coefficients; // c[0] - constant term of the objective function; // A - matrix of constraint coefficients (has m rows // and n columns); // l - vector of lower bounds of variables; // u - vector of upper bounds of variables. // // The simplex method makes no difference between auxiliary and // structural variables, so it is convenient to think the system of // equality constraints (5) written in a homogeneous form: // // (I | -A) * x = 0, (7) // // where (I | -A) is an augmented (m+n)xm constraint matrix, I is mxm // unity matrix whose columns correspond to auxiliary variables, and A // is the original mxn constraint matrix whose columns correspond to // structural variables. Note that only the matrix A is stored. ----------------------------------------------------------------------*/ int m; /* number of rows (auxiliary variables), m > 0 */ int n; /* number of columns (structural variables), n > 0 */ int *type; /* int type[1+m+n]; */ /* type[0] is not used; type[k], 1 <= k <= m+n, is the type of variable x[k]: */ #define SSX_FR 0 /* free (unbounded) variable */ #define SSX_LO 1 /* variable with lower bound */ #define SSX_UP 2 /* variable with upper bound */ #define SSX_DB 3 /* double-bounded variable */ #define SSX_FX 4 /* fixed variable */ mpq_t *lb; /* mpq_t lb[1+m+n]; alias: l */ /* lb[0] is not used; lb[k], 1 <= k <= m+n, is an lower bound of variable x[k]; if x[k] has no lower bound, lb[k] is zero */ mpq_t *ub; /* mpq_t ub[1+m+n]; alias: u */ /* ub[0] is not used; ub[k], 1 <= k <= m+n, is an upper bound of variable x[k]; if x[k] has no upper bound, ub[k] is zero; if x[k] is of fixed type, ub[k] is equal to lb[k] */ int dir; /* optimization direction (sense of the objective function): */ #define SSX_MIN 0 /* minimization */ #define SSX_MAX 1 /* maximization */ mpq_t *coef; /* mpq_t coef[1+m+n]; alias: c */ /* coef[0] is a constant term of the objective function; coef[k], 1 <= k <= m+n, is a coefficient of the objective function at variable x[k]; note that auxiliary variables also may have non-zero objective coefficients */ int *A_ptr; /* int A_ptr[1+n+1]; */ int *A_ind; /* int A_ind[A_ptr[n+1]]; */ mpq_t *A_val; /* mpq_t A_val[A_ptr[n+1]]; */ /* constraint matrix A (see (5)) in storage-by-columns format */ /*---------------------------------------------------------------------- // LP BASIS AND CURRENT BASIC SOLUTION // // The LP basis is defined by the following partition of the augmented // constraint matrix (7): // // (B | N) = (I | -A) * Q, (8) // // where B is a mxm non-singular basis matrix whose columns correspond // to basic variables xB, N is a mxn matrix whose columns correspond to // non-basic variables xN, and Q is a permutation (m+n)x(m+n) matrix. // // From (7) and (8) it follows that // // (I | -A) * x = (I | -A) * Q * Q' * x = (B | N) * (xB, xN), // // therefore // // (xB, xN) = Q' * x, (9) // // where x is the vector of all variables in the original order, xB is // a vector of basic variables, xN is a vector of non-basic variables, // Q' = inv(Q) is a matrix transposed to Q. // // Current values of non-basic variables xN[j], j = 1, ..., n, are not // stored; they are defined implicitly by their statuses as follows: // // 0, if xN[j] is free variable // lN[j], if xN[j] is on its lower bound (10) // uN[j], if xN[j] is on its upper bound // lN[j] = uN[j], if xN[j] is fixed variable // // where lN[j] and uN[j] are lower and upper bounds of xN[j]. // // Current values of basic variables xB[i], i = 1, ..., m, are computed // as follows: // // beta = - inv(B) * N * xN, (11) // // where current values of xN are defined by (10). // // Current values of simplex multipliers pi[i], i = 1, ..., m (which // are values of Lagrange multipliers for equality constraints (7) also // called shadow prices) are computed as follows: // // pi = inv(B') * cB, (12) // // where B' is a matrix transposed to B, cB is a vector of objective // coefficients at basic variables xB. // // Current values of reduced costs d[j], j = 1, ..., n, (which are // values of Langrange multipliers for active inequality constraints // corresponding to non-basic variables) are computed as follows: // // d = cN - N' * pi, (13) // // where N' is a matrix transposed to N, cN is a vector of objective // coefficients at non-basic variables xN. ----------------------------------------------------------------------*/ int *stat; /* int stat[1+m+n]; */ /* stat[0] is not used; stat[k], 1 <= k <= m+n, is the status of variable x[k]: */ #define SSX_BS 0 /* basic variable */ #define SSX_NL 1 /* non-basic variable on lower bound */ #define SSX_NU 2 /* non-basic variable on upper bound */ #define SSX_NF 3 /* non-basic free variable */ #define SSX_NS 4 /* non-basic fixed variable */ int *Q_row; /* int Q_row[1+m+n]; */ /* matrix Q in row-like format; Q_row[0] is not used; Q_row[i] = j means that q[i,j] = 1 */ int *Q_col; /* int Q_col[1+m+n]; */ /* matrix Q in column-like format; Q_col[0] is not used; Q_col[j] = i means that q[i,j] = 1 */ /* if k-th column of the matrix (I | A) is k'-th column of the matrix (B | N), then Q_row[k] = k' and Q_col[k'] = k; if x[k] is xB[i], then Q_row[k] = i and Q_col[i] = k; if x[k] is xN[j], then Q_row[k] = m+j and Q_col[m+j] = k */ BFX *binv; /* invertable form of the basis matrix B */ mpq_t *bbar; /* mpq_t bbar[1+m]; alias: beta */ /* bbar[0] is a value of the objective function; bbar[i], 1 <= i <= m, is a value of basic variable xB[i] */ mpq_t *pi; /* mpq_t pi[1+m]; */ /* pi[0] is not used; pi[i], 1 <= i <= m, is a simplex multiplier corresponding to i-th row (equality constraint) */ mpq_t *cbar; /* mpq_t cbar[1+n]; alias: d */ /* cbar[0] is not used; cbar[j], 1 <= j <= n, is a reduced cost of non-basic variable xN[j] */ /*---------------------------------------------------------------------- // SIMPLEX TABLE // // Due to (8) and (9) the system of equality constraints (7) for the // current basis can be written as follows: // // xB = A~ * xN, (14) // // where // // A~ = - inv(B) * N (15) // // is a mxn matrix called the simplex table. // // The revised simplex method uses only two components of A~, namely, // pivot column corresponding to non-basic variable xN[q] chosen to // enter the basis, and pivot row corresponding to basic variable xB[p] // chosen to leave the basis. // // Pivot column alfa_q is q-th column of A~, so // // alfa_q = A~ * e[q] = - inv(B) * N * e[q] = - inv(B) * N[q], (16) // // where N[q] is q-th column of the matrix N. // // Pivot row alfa_p is p-th row of A~ or, equivalently, p-th column of // A~', a matrix transposed to A~, so // // alfa_p = A~' * e[p] = - N' * inv(B') * e[p] = - N' * rho_p, (17) // // where (*)' means transposition, and // // rho_p = inv(B') * e[p], (18) // // is p-th column of inv(B') or, that is the same, p-th row of inv(B). ----------------------------------------------------------------------*/ int p; /* number of basic variable xB[p], 1 <= p <= m, chosen to leave the basis */ mpq_t *rho; /* mpq_t rho[1+m]; */ /* p-th row of the inverse inv(B); see (18) */ mpq_t *ap; /* mpq_t ap[1+n]; */ /* p-th row of the simplex table; see (17) */ int q; /* number of non-basic variable xN[q], 1 <= q <= n, chosen to enter the basis */ mpq_t *aq; /* mpq_t aq[1+m]; */ /* q-th column of the simplex table; see (16) */ /*--------------------------------------------------------------------*/ int q_dir; /* direction in which non-basic variable xN[q] should change on moving to the adjacent vertex of the polyhedron: +1 means that xN[q] increases -1 means that xN[q] decreases */ int p_stat; /* non-basic status which should be assigned to basic variable xB[p] when it has left the basis and become xN[q] */ mpq_t delta; /* actual change of xN[q] in the adjacent basis (it has the same sign as q_dir) */ /*--------------------------------------------------------------------*/ int it_lim; /* simplex iterations limit; if this value is positive, it is decreased by one each time when one simplex iteration has been performed, and reaching zero value signals the solver to stop the search; negative value means no iterations limit */ int it_cnt; /* simplex iterations count; this count is increased by one each time when one simplex iteration has been performed */ double tm_lim; /* searching time limit, in seconds; if this value is positive, it is decreased each time when one simplex iteration has been performed by the amount of time spent for the iteration, and reaching zero value signals the solver to stop the search; negative value means no time limit */ double out_frq; /* output frequency, in seconds; this parameter specifies how frequently the solver sends information about the progress of the search to the standard output */ glp_long tm_beg; /* starting time of the search, in seconds; the total time of the search is the difference between xtime() and tm_beg */ glp_long tm_lag; /* the most recent time, in seconds, at which the progress of the the search was displayed */ }; #define ssx_create _glp_ssx_create #define ssx_factorize _glp_ssx_factorize #define ssx_get_xNj _glp_ssx_get_xNj #define ssx_eval_bbar _glp_ssx_eval_bbar #define ssx_eval_pi _glp_ssx_eval_pi #define ssx_eval_dj _glp_ssx_eval_dj #define ssx_eval_cbar _glp_ssx_eval_cbar #define ssx_eval_rho _glp_ssx_eval_rho #define ssx_eval_row _glp_ssx_eval_row #define ssx_eval_col _glp_ssx_eval_col #define ssx_chuzc _glp_ssx_chuzc #define ssx_chuzr _glp_ssx_chuzr #define ssx_update_bbar _glp_ssx_update_bbar #define ssx_update_pi _glp_ssx_update_pi #define ssx_update_cbar _glp_ssx_update_cbar #define ssx_change_basis _glp_ssx_change_basis #define ssx_delete _glp_ssx_delete #define ssx_phase_I _glp_ssx_phase_I #define ssx_phase_II _glp_ssx_phase_II #define ssx_driver _glp_ssx_driver SSX *ssx_create(int m, int n, int nnz); /* create simplex solver workspace */ int ssx_factorize(SSX *ssx); /* factorize the current basis matrix */ void ssx_get_xNj(SSX *ssx, int j, mpq_t x); /* determine value of non-basic variable */ void ssx_eval_bbar(SSX *ssx); /* compute values of basic variables */ void ssx_eval_pi(SSX *ssx); /* compute values of simplex multipliers */ void ssx_eval_dj(SSX *ssx, int j, mpq_t dj); /* compute reduced cost of non-basic variable */ void ssx_eval_cbar(SSX *ssx); /* compute reduced costs of all non-basic variables */ void ssx_eval_rho(SSX *ssx); /* compute p-th row of the inverse */ void ssx_eval_row(SSX *ssx); /* compute pivot row of the simplex table */ void ssx_eval_col(SSX *ssx); /* compute pivot column of the simplex table */ void ssx_chuzc(SSX *ssx); /* choose pivot column */ void ssx_chuzr(SSX *ssx); /* choose pivot row */ void ssx_update_bbar(SSX *ssx); /* update values of basic variables */ void ssx_update_pi(SSX *ssx); /* update simplex multipliers */ void ssx_update_cbar(SSX *ssx); /* update reduced costs of non-basic variables */ void ssx_change_basis(SSX *ssx); /* change current basis to adjacent one */ void ssx_delete(SSX *ssx); /* delete simplex solver workspace */ int ssx_phase_I(SSX *ssx); /* find primal feasible solution */ int ssx_phase_II(SSX *ssx); /* find optimal solution */ int ssx_driver(SSX *ssx); /* base driver to exact simplex method */ #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpbfx.c0000644000076500000240000000513313524616144025027 0ustar tamasstaff00000000000000/* glpbfx.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ typedef struct BFX BFX; #define GLPBFX_DEFINED #include "glpbfx.h" #include "glpenv.h" #include "glplux.h" struct BFX { int valid; LUX *lux; }; BFX *bfx_create_binv(void) { /* create factorization of the basis matrix */ BFX *bfx; bfx = xmalloc(sizeof(BFX)); bfx->valid = 0; bfx->lux = NULL; return bfx; } int bfx_factorize(BFX *binv, int m, int (*col)(void *info, int j, int ind[], mpq_t val[]), void *info) { /* compute factorization of the basis matrix */ int ret; xassert(m > 0); if (binv->lux != NULL && binv->lux->n != m) { lux_delete(binv->lux); binv->lux = NULL; } if (binv->lux == NULL) binv->lux = lux_create(m); ret = lux_decomp(binv->lux, col, info); binv->valid = (ret == 0); return ret; } void bfx_ftran(BFX *binv, mpq_t x[], int save) { /* perform forward transformation (FTRAN) */ xassert(binv->valid); lux_solve(binv->lux, 0, x); xassert(save == save); return; } void bfx_btran(BFX *binv, mpq_t x[]) { /* perform backward transformation (BTRAN) */ xassert(binv->valid); lux_solve(binv->lux, 1, x); return; } int bfx_update(BFX *binv, int j) { /* update factorization of the basis matrix */ xassert(binv->valid); xassert(1 <= j && j <= binv->lux->n); return 1; } void bfx_delete_binv(BFX *binv) { /* delete factorization of the basis matrix */ if (binv->lux != NULL) lux_delete(binv->lux); xfree(binv); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpapi14.c0000644000076500000240000002210613524616144025165 0ustar tamasstaff00000000000000/* glpapi14.c (processing models in GNU MathProg language) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #define GLP_TRAN_DEFINED typedef struct MPL glp_tran; #include "glpmpl.h" #include "glpapi.h" glp_tran *glp_mpl_alloc_wksp(void) { /* allocate the MathProg translator workspace */ glp_tran *tran; tran = mpl_initialize(); return tran; } #if 1 /* 08/XII-2009 */ void _glp_mpl_init_rand(glp_tran *tran, int seed) { if (tran->phase != 0) xerror("glp_mpl_init_rand: invalid call sequence\n"); rng_init_rand(tran->rand, seed); return; } #endif int glp_mpl_read_model(glp_tran *tran, const char *fname, int skip) { /* read and translate model section */ int ret; if (tran->phase != 0) xerror("glp_mpl_read_model: invalid call sequence\n"); ret = mpl_read_model(tran, (char *)fname, skip); if (ret == 1 || ret == 2) ret = 0; else if (ret == 4) ret = 1; else xassert(ret != ret); return ret; } int glp_mpl_read_data(glp_tran *tran, const char *fname) { /* read and translate data section */ int ret; if (!(tran->phase == 1 || tran->phase == 2)) xerror("glp_mpl_read_data: invalid call sequence\n"); ret = mpl_read_data(tran, (char *)fname); if (ret == 2) ret = 0; else if (ret == 4) ret = 1; else xassert(ret != ret); return ret; } int glp_mpl_generate(glp_tran *tran, const char *fname) { /* generate the model */ int ret; if (!(tran->phase == 1 || tran->phase == 2)) xerror("glp_mpl_generate: invalid call sequence\n"); ret = mpl_generate(tran, (char *)fname); if (ret == 3) ret = 0; else if (ret == 4) ret = 1; return ret; } void glp_mpl_build_prob(glp_tran *tran, glp_prob *prob) { /* build LP/MIP problem instance from the model */ int m, n, i, j, t, kind, type, len, *ind; double lb, ub, *val; if (tran->phase != 3) xerror("glp_mpl_build_prob: invalid call sequence\n"); /* erase the problem object */ glp_erase_prob(prob); /* set problem name */ glp_set_prob_name(prob, mpl_get_prob_name(tran)); /* build rows (constraints) */ m = mpl_get_num_rows(tran); if (m > 0) glp_add_rows(prob, m); for (i = 1; i <= m; i++) { /* set row name */ glp_set_row_name(prob, i, mpl_get_row_name(tran, i)); /* set row bounds */ type = mpl_get_row_bnds(tran, i, &lb, &ub); switch (type) { case MPL_FR: type = GLP_FR; break; case MPL_LO: type = GLP_LO; break; case MPL_UP: type = GLP_UP; break; case MPL_DB: type = GLP_DB; break; case MPL_FX: type = GLP_FX; break; default: xassert(type != type); } if (type == GLP_DB && fabs(lb - ub) < 1e-9 * (1.0 + fabs(lb))) { type = GLP_FX; if (fabs(lb) <= fabs(ub)) ub = lb; else lb = ub; } glp_set_row_bnds(prob, i, type, lb, ub); /* warn about non-zero constant term */ if (mpl_get_row_c0(tran, i) != 0.0) xprintf("glp_mpl_build_prob: row %s; constant term %.12g ig" "nored\n", mpl_get_row_name(tran, i), mpl_get_row_c0(tran, i)); } /* build columns (variables) */ n = mpl_get_num_cols(tran); if (n > 0) glp_add_cols(prob, n); for (j = 1; j <= n; j++) { /* set column name */ glp_set_col_name(prob, j, mpl_get_col_name(tran, j)); /* set column kind */ kind = mpl_get_col_kind(tran, j); switch (kind) { case MPL_NUM: break; case MPL_INT: case MPL_BIN: glp_set_col_kind(prob, j, GLP_IV); break; default: xassert(kind != kind); } /* set column bounds */ type = mpl_get_col_bnds(tran, j, &lb, &ub); switch (type) { case MPL_FR: type = GLP_FR; break; case MPL_LO: type = GLP_LO; break; case MPL_UP: type = GLP_UP; break; case MPL_DB: type = GLP_DB; break; case MPL_FX: type = GLP_FX; break; default: xassert(type != type); } if (kind == MPL_BIN) { if (type == GLP_FR || type == GLP_UP || lb < 0.0) lb = 0.0; if (type == GLP_FR || type == GLP_LO || ub > 1.0) ub = 1.0; type = GLP_DB; } if (type == GLP_DB && fabs(lb - ub) < 1e-9 * (1.0 + fabs(lb))) { type = GLP_FX; if (fabs(lb) <= fabs(ub)) ub = lb; else lb = ub; } glp_set_col_bnds(prob, j, type, lb, ub); } /* load the constraint matrix */ ind = xcalloc(1+n, sizeof(int)); val = xcalloc(1+n, sizeof(double)); for (i = 1; i <= m; i++) { len = mpl_get_mat_row(tran, i, ind, val); glp_set_mat_row(prob, i, len, ind, val); } /* build objective function (the first objective is used) */ for (i = 1; i <= m; i++) { kind = mpl_get_row_kind(tran, i); if (kind == MPL_MIN || kind == MPL_MAX) { /* set objective name */ glp_set_obj_name(prob, mpl_get_row_name(tran, i)); /* set optimization direction */ glp_set_obj_dir(prob, kind == MPL_MIN ? GLP_MIN : GLP_MAX); /* set constant term */ glp_set_obj_coef(prob, 0, mpl_get_row_c0(tran, i)); /* set objective coefficients */ len = mpl_get_mat_row(tran, i, ind, val); for (t = 1; t <= len; t++) glp_set_obj_coef(prob, ind[t], val[t]); break; } } /* free working arrays */ xfree(ind); xfree(val); return; } int glp_mpl_postsolve(glp_tran *tran, glp_prob *prob, int sol) { /* postsolve the model */ int i, j, m, n, stat, ret; double prim, dual; if (!(tran->phase == 3 && !tran->flag_p)) xerror("glp_mpl_postsolve: invalid call sequence\n"); if (!(sol == GLP_SOL || sol == GLP_IPT || sol == GLP_MIP)) xerror("glp_mpl_postsolve: sol = %d; invalid parameter\n", sol); m = mpl_get_num_rows(tran); n = mpl_get_num_cols(tran); if (!(m == glp_get_num_rows(prob) && n == glp_get_num_cols(prob))) xerror("glp_mpl_postsolve: wrong problem object\n"); if (!mpl_has_solve_stmt(tran)) { ret = 0; goto done; } for (i = 1; i <= m; i++) { if (sol == GLP_SOL) { stat = glp_get_row_stat(prob, i); prim = glp_get_row_prim(prob, i); dual = glp_get_row_dual(prob, i); } else if (sol == GLP_IPT) { stat = 0; prim = glp_ipt_row_prim(prob, i); dual = glp_ipt_row_dual(prob, i); } else if (sol == GLP_MIP) { stat = 0; prim = glp_mip_row_val(prob, i); dual = 0.0; } else xassert(sol != sol); if (fabs(prim) < 1e-9) prim = 0.0; if (fabs(dual) < 1e-9) dual = 0.0; mpl_put_row_soln(tran, i, stat, prim, dual); } for (j = 1; j <= n; j++) { if (sol == GLP_SOL) { stat = glp_get_col_stat(prob, j); prim = glp_get_col_prim(prob, j); dual = glp_get_col_dual(prob, j); } else if (sol == GLP_IPT) { stat = 0; prim = glp_ipt_col_prim(prob, j); dual = glp_ipt_col_dual(prob, j); } else if (sol == GLP_MIP) { stat = 0; prim = glp_mip_col_val(prob, j); dual = 0.0; } else xassert(sol != sol); if (fabs(prim) < 1e-9) prim = 0.0; if (fabs(dual) < 1e-9) dual = 0.0; mpl_put_col_soln(tran, j, stat, prim, dual); } ret = mpl_postsolve(tran); if (ret == 3) ret = 0; else if (ret == 4) ret = 1; done: return ret; } void glp_mpl_free_wksp(glp_tran *tran) { /* free the MathProg translator workspace */ mpl_terminate(tran); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpspm.c0000644000076500000240000006047313524616144025057 0ustar tamasstaff00000000000000/* glpspm.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glphbm.h" #include "glprgr.h" #include "glpspm.h" /*********************************************************************** * NAME * * spm_create_mat - create general sparse matrix * * SYNOPSIS * * #include "glpspm.h" * SPM *spm_create_mat(int m, int n); * * DESCRIPTION * * The routine spm_create_mat creates a general sparse matrix having * m rows and n columns. Being created the matrix is zero (empty), i.e. * has no elements. * * RETURNS * * The routine returns a pointer to the matrix created. */ SPM *spm_create_mat(int m, int n) { SPM *A; xassert(0 <= m && m < INT_MAX); xassert(0 <= n && n < INT_MAX); A = xmalloc(sizeof(SPM)); A->m = m; A->n = n; if (m == 0 || n == 0) { A->pool = NULL; A->row = NULL; A->col = NULL; } else { int i, j; A->pool = dmp_create_pool(); A->row = xcalloc(1+m, sizeof(SPME *)); for (i = 1; i <= m; i++) A->row[i] = NULL; A->col = xcalloc(1+n, sizeof(SPME *)); for (j = 1; j <= n; j++) A->col[j] = NULL; } return A; } /*********************************************************************** * NAME * * spm_new_elem - add new element to sparse matrix * * SYNOPSIS * * #include "glpspm.h" * SPME *spm_new_elem(SPM *A, int i, int j, double val); * * DESCRIPTION * * The routine spm_new_elem adds a new element to the specified sparse * matrix. Parameters i, j, and val specify the row number, the column * number, and a numerical value of the element, respectively. * * RETURNS * * The routine returns a pointer to the new element added. */ SPME *spm_new_elem(SPM *A, int i, int j, double val) { SPME *e; xassert(1 <= i && i <= A->m); xassert(1 <= j && j <= A->n); e = dmp_get_atom(A->pool, sizeof(SPME)); e->i = i; e->j = j; e->val = val; e->r_prev = NULL; e->r_next = A->row[i]; if (e->r_next != NULL) e->r_next->r_prev = e; e->c_prev = NULL; e->c_next = A->col[j]; if (e->c_next != NULL) e->c_next->c_prev = e; A->row[i] = A->col[j] = e; return e; } /*********************************************************************** * NAME * * spm_delete_mat - delete general sparse matrix * * SYNOPSIS * * #include "glpspm.h" * void spm_delete_mat(SPM *A); * * DESCRIPTION * * The routine deletes the specified general sparse matrix freeing all * the memory allocated to this object. */ void spm_delete_mat(SPM *A) { /* delete sparse matrix */ if (A->pool != NULL) dmp_delete_pool(A->pool); if (A->row != NULL) xfree(A->row); if (A->col != NULL) xfree(A->col); xfree(A); return; } /*********************************************************************** * NAME * * spm_test_mat_e - create test sparse matrix of E(n,c) class * * SYNOPSIS * * #include "glpspm.h" * SPM *spm_test_mat_e(int n, int c); * * DESCRIPTION * * The routine spm_test_mat_e creates a test sparse matrix of E(n,c) * class as described in the book: Ole 0sterby, Zahari Zlatev. Direct * Methods for Sparse Matrices. Springer-Verlag, 1983. * * Matrix of E(n,c) class is a symmetric positive definite matrix of * the order n. It has the number 4 on its main diagonal and the number * -1 on its four co-diagonals, two of which are neighbour to the main * diagonal and two others are shifted from the main diagonal on the * distance c. * * It is necessary that n >= 3 and 2 <= c <= n-1. * * RETURNS * * The routine returns a pointer to the matrix created. */ SPM *spm_test_mat_e(int n, int c) { SPM *A; int i; xassert(n >= 3 && 2 <= c && c <= n-1); A = spm_create_mat(n, n); for (i = 1; i <= n; i++) spm_new_elem(A, i, i, 4.0); for (i = 1; i <= n-1; i++) { spm_new_elem(A, i, i+1, -1.0); spm_new_elem(A, i+1, i, -1.0); } for (i = 1; i <= n-c; i++) { spm_new_elem(A, i, i+c, -1.0); spm_new_elem(A, i+c, i, -1.0); } return A; } /*********************************************************************** * NAME * * spm_test_mat_d - create test sparse matrix of D(n,c) class * * SYNOPSIS * * #include "glpspm.h" * SPM *spm_test_mat_d(int n, int c); * * DESCRIPTION * * The routine spm_test_mat_d creates a test sparse matrix of D(n,c) * class as described in the book: Ole 0sterby, Zahari Zlatev. Direct * Methods for Sparse Matrices. Springer-Verlag, 1983. * * Matrix of D(n,c) class is a non-singular matrix of the order n. It * has unity main diagonal, three co-diagonals above the main diagonal * on the distance c, which are cyclically continued below the main * diagonal, and a triangle block of the size 10x10 in the upper right * corner. * * It is necessary that n >= 14 and 1 <= c <= n-13. * * RETURNS * * The routine returns a pointer to the matrix created. */ SPM *spm_test_mat_d(int n, int c) { SPM *A; int i, j; xassert(n >= 14 && 1 <= c && c <= n-13); A = spm_create_mat(n, n); for (i = 1; i <= n; i++) spm_new_elem(A, i, i, 1.0); for (i = 1; i <= n-c; i++) spm_new_elem(A, i, i+c, (double)(i+1)); for (i = n-c+1; i <= n; i++) spm_new_elem(A, i, i-n+c, (double)(i+1)); for (i = 1; i <= n-c-1; i++) spm_new_elem(A, i, i+c+1, (double)(-i)); for (i = n-c; i <= n; i++) spm_new_elem(A, i, i-n+c+1, (double)(-i)); for (i = 1; i <= n-c-2; i++) spm_new_elem(A, i, i+c+2, 16.0); for (i = n-c-1; i <= n; i++) spm_new_elem(A, i, i-n+c+2, 16.0); for (j = 1; j <= 10; j++) for (i = 1; i <= 11-j; i++) spm_new_elem(A, i, n-11+i+j, 100.0 * (double)j); return A; } /*********************************************************************** * NAME * * spm_show_mat - write sparse matrix pattern in BMP file format * * SYNOPSIS * * #include "glpspm.h" * int spm_show_mat(const SPM *A, const char *fname); * * DESCRIPTION * * The routine spm_show_mat writes pattern of the specified sparse * matrix in uncompressed BMP file format (Windows bitmap) to a binary * file whose name is specified by the character string fname. * * Each pixel corresponds to one matrix element. The pixel colors have * the following meaning: * * Black structurally zero element * White positive element * Cyan negative element * Green zero element * Red duplicate element * * RETURNS * * If no error occured, the routine returns zero. Otherwise, it prints * an appropriate error message and returns non-zero. */ int spm_show_mat(const SPM *A, const char *fname) { int m = A->m; int n = A->n; int i, j, k, ret; char *map; xprintf("spm_show_mat: writing matrix pattern to `%s'...\n", fname); xassert(1 <= m && m <= 32767); xassert(1 <= n && n <= 32767); map = xmalloc(m * n); memset(map, 0x08, m * n); for (i = 1; i <= m; i++) { SPME *e; for (e = A->row[i]; e != NULL; e = e->r_next) { j = e->j; xassert(1 <= j && j <= n); k = n * (i - 1) + (j - 1); if (map[k] != 0x08) map[k] = 0x0C; else if (e->val > 0.0) map[k] = 0x0F; else if (e->val < 0.0) map[k] = 0x0B; else map[k] = 0x0A; } } ret = rgr_write_bmp16(fname, m, n, map); xfree(map); return ret; } /*********************************************************************** * NAME * * spm_read_hbm - read sparse matrix in Harwell-Boeing format * * SYNOPSIS * * #include "glpspm.h" * SPM *spm_read_hbm(const char *fname); * * DESCRIPTION * * The routine spm_read_hbm reads a sparse matrix in the Harwell-Boeing * format from a text file whose name is the character string fname. * * Detailed description of the Harwell-Boeing format recognised by this * routine can be found in the following report: * * I.S.Duff, R.G.Grimes, J.G.Lewis. User's Guide for the Harwell-Boeing * Sparse Matrix Collection (Release I), TR/PA/92/86, October 1992. * * NOTE * * The routine spm_read_hbm reads the matrix "as is", due to which zero * and/or duplicate elements can appear in the matrix. * * RETURNS * * If no error occured, the routine returns a pointer to the matrix * created. Otherwise, the routine prints an appropriate error message * and returns NULL. */ SPM *spm_read_hbm(const char *fname) { SPM *A = NULL; HBM *hbm; int nrow, ncol, nnzero, i, j, beg, end, ptr, *colptr, *rowind; double val, *values; char *mxtype; hbm = hbm_read_mat(fname); if (hbm == NULL) { xprintf("spm_read_hbm: unable to read matrix\n"); goto fini; } mxtype = hbm->mxtype; nrow = hbm->nrow; ncol = hbm->ncol; nnzero = hbm->nnzero; colptr = hbm->colptr; rowind = hbm->rowind; values = hbm->values; if (!(strcmp(mxtype, "RSA") == 0 || strcmp(mxtype, "PSA") == 0 || strcmp(mxtype, "RUA") == 0 || strcmp(mxtype, "PUA") == 0 || strcmp(mxtype, "RRA") == 0 || strcmp(mxtype, "PRA") == 0)) { xprintf("spm_read_hbm: matrix type `%s' not supported\n", mxtype); goto fini; } A = spm_create_mat(nrow, ncol); if (mxtype[1] == 'S' || mxtype[1] == 'U') xassert(nrow == ncol); for (j = 1; j <= ncol; j++) { beg = colptr[j]; end = colptr[j+1]; xassert(1 <= beg && beg <= end && end <= nnzero + 1); for (ptr = beg; ptr < end; ptr++) { i = rowind[ptr]; xassert(1 <= i && i <= nrow); if (mxtype[0] == 'R') val = values[ptr]; else val = 1.0; spm_new_elem(A, i, j, val); if (mxtype[1] == 'S' && i != j) spm_new_elem(A, j, i, val); } } fini: if (hbm != NULL) hbm_free_mat(hbm); return A; } /*********************************************************************** * NAME * * spm_count_nnz - determine number of non-zeros in sparse matrix * * SYNOPSIS * * #include "glpspm.h" * int spm_count_nnz(const SPM *A); * * RETURNS * * The routine spm_count_nnz returns the number of structural non-zero * elements in the specified sparse matrix. */ int spm_count_nnz(const SPM *A) { SPME *e; int i, nnz = 0; for (i = 1; i <= A->m; i++) for (e = A->row[i]; e != NULL; e = e->r_next) nnz++; return nnz; } /*********************************************************************** * NAME * * spm_drop_zeros - remove zero elements from sparse matrix * * SYNOPSIS * * #include "glpspm.h" * int spm_drop_zeros(SPM *A, double eps); * * DESCRIPTION * * The routine spm_drop_zeros removes all elements from the specified * sparse matrix, whose absolute value is less than eps. * * If the parameter eps is 0, only zero elements are removed from the * matrix. * * RETURNS * * The routine returns the number of elements removed. */ int spm_drop_zeros(SPM *A, double eps) { SPME *e, *next; int i, count = 0; for (i = 1; i <= A->m; i++) { for (e = A->row[i]; e != NULL; e = next) { next = e->r_next; if (e->val == 0.0 || fabs(e->val) < eps) { /* remove element from the row list */ if (e->r_prev == NULL) A->row[e->i] = e->r_next; else e->r_prev->r_next = e->r_next; if (e->r_next == NULL) ; else e->r_next->r_prev = e->r_prev; /* remove element from the column list */ if (e->c_prev == NULL) A->col[e->j] = e->c_next; else e->c_prev->c_next = e->c_next; if (e->c_next == NULL) ; else e->c_next->c_prev = e->c_prev; /* return element to the memory pool */ dmp_free_atom(A->pool, e, sizeof(SPME)); count++; } } } return count; } /*********************************************************************** * NAME * * spm_read_mat - read sparse matrix from text file * * SYNOPSIS * * #include "glpspm.h" * SPM *spm_read_mat(const char *fname); * * DESCRIPTION * * The routine reads a sparse matrix from a text file whose name is * specified by the parameter fname. * * For the file format see description of the routine spm_write_mat. * * RETURNS * * On success the routine returns a pointer to the matrix created, * otherwise NULL. */ #if 1 SPM *spm_read_mat(const char *fname) { xassert(fname != fname); return NULL; } #else SPM *spm_read_mat(const char *fname) { SPM *A = NULL; PDS *pds; jmp_buf jump; int i, j, k, m, n, nnz, fail = 0; double val; xprintf("spm_read_mat: reading matrix from `%s'...\n", fname); pds = pds_open_file(fname); if (pds == NULL) { xprintf("spm_read_mat: unable to open `%s' - %s\n", fname, strerror(errno)); fail = 1; goto done; } if (setjmp(jump)) { fail = 1; goto done; } pds_set_jump(pds, jump); /* number of rows, number of columns, number of non-zeros */ m = pds_scan_int(pds); if (m < 0) pds_error(pds, "invalid number of rows\n"); n = pds_scan_int(pds); if (n < 0) pds_error(pds, "invalid number of columns\n"); nnz = pds_scan_int(pds); if (nnz < 0) pds_error(pds, "invalid number of non-zeros\n"); /* create matrix */ xprintf("spm_read_mat: %d rows, %d columns, %d non-zeros\n", m, n, nnz); A = spm_create_mat(m, n); /* read matrix elements */ for (k = 1; k <= nnz; k++) { /* row index, column index, element value */ i = pds_scan_int(pds); if (!(1 <= i && i <= m)) pds_error(pds, "row index out of range\n"); j = pds_scan_int(pds); if (!(1 <= j && j <= n)) pds_error(pds, "column index out of range\n"); val = pds_scan_num(pds); /* add new element to the matrix */ spm_new_elem(A, i, j, val); } xprintf("spm_read_mat: %d lines were read\n", pds->count); done: if (pds != NULL) pds_close_file(pds); if (fail && A != NULL) spm_delete_mat(A), A = NULL; return A; } #endif /*********************************************************************** * NAME * * spm_write_mat - write sparse matrix to text file * * SYNOPSIS * * #include "glpspm.h" * int spm_write_mat(const SPM *A, const char *fname); * * DESCRIPTION * * The routine spm_write_mat writes the specified sparse matrix to a * text file whose name is specified by the parameter fname. This file * can be read back with the routine spm_read_mat. * * RETURNS * * On success the routine returns zero, otherwise non-zero. * * FILE FORMAT * * The file created by the routine spm_write_mat is a plain text file, * which contains the following information: * * m n nnz * row[1] col[1] val[1] * row[2] col[2] val[2] * . . . * row[nnz] col[nnz] val[nnz] * * where: * m is the number of rows; * n is the number of columns; * nnz is the number of non-zeros; * row[k], k = 1,...,nnz, are row indices; * col[k], k = 1,...,nnz, are column indices; * val[k], k = 1,...,nnz, are element values. */ #if 1 int spm_write_mat(const SPM *A, const char *fname) { xassert(A != A); xassert(fname != fname); return 0; } #else int spm_write_mat(const SPM *A, const char *fname) { FILE *fp; int i, nnz, ret = 0; xprintf("spm_write_mat: writing matrix to `%s'...\n", fname); fp = fopen(fname, "w"); if (fp == NULL) { xprintf("spm_write_mat: unable to create `%s' - %s\n", fname, strerror(errno)); ret = 1; goto done; } /* number of rows, number of columns, number of non-zeros */ nnz = spm_count_nnz(A); fprintf(fp, "%d %d %d\n", A->m, A->n, nnz); /* walk through rows of the matrix */ for (i = 1; i <= A->m; i++) { SPME *e; /* walk through elements of i-th row */ for (e = A->row[i]; e != NULL; e = e->r_next) { /* row index, column index, element value */ fprintf(fp, "%d %d %.*g\n", e->i, e->j, DBL_DIG, e->val); } } fflush(fp); if (ferror(fp)) { xprintf("spm_write_mat: writing error on `%s' - %s\n", fname, strerror(errno)); ret = 1; goto done; } xprintf("spm_write_mat: %d lines were written\n", 1 + nnz); done: if (fp != NULL) fclose(fp); return ret; } #endif /*********************************************************************** * NAME * * spm_transpose - transpose sparse matrix * * SYNOPSIS * * #include "glpspm.h" * SPM *spm_transpose(const SPM *A); * * RETURNS * * The routine computes and returns sparse matrix B, which is a matrix * transposed to sparse matrix A. */ SPM *spm_transpose(const SPM *A) { SPM *B; int i; B = spm_create_mat(A->n, A->m); for (i = 1; i <= A->m; i++) { SPME *e; for (e = A->row[i]; e != NULL; e = e->r_next) spm_new_elem(B, e->j, i, e->val); } return B; } SPM *spm_add_sym(const SPM *A, const SPM *B) { /* add two sparse matrices (symbolic phase) */ SPM *C; int i, j, *flag; xassert(A->m == B->m); xassert(A->n == B->n); /* create resultant matrix */ C = spm_create_mat(A->m, A->n); /* allocate and clear the flag array */ flag = xcalloc(1+C->n, sizeof(int)); for (j = 1; j <= C->n; j++) flag[j] = 0; /* compute pattern of C = A + B */ for (i = 1; i <= C->m; i++) { SPME *e; /* at the beginning i-th row of C is empty */ /* (i-th row of C) := (i-th row of C) union (i-th row of A) */ for (e = A->row[i]; e != NULL; e = e->r_next) { /* (note that i-th row of A may have duplicate elements) */ j = e->j; if (!flag[j]) { spm_new_elem(C, i, j, 0.0); flag[j] = 1; } } /* (i-th row of C) := (i-th row of C) union (i-th row of B) */ for (e = B->row[i]; e != NULL; e = e->r_next) { /* (note that i-th row of B may have duplicate elements) */ j = e->j; if (!flag[j]) { spm_new_elem(C, i, j, 0.0); flag[j] = 1; } } /* reset the flag array */ for (e = C->row[i]; e != NULL; e = e->r_next) flag[e->j] = 0; } /* check and deallocate the flag array */ for (j = 1; j <= C->n; j++) xassert(!flag[j]); xfree(flag); return C; } void spm_add_num(SPM *C, double alfa, const SPM *A, double beta, const SPM *B) { /* add two sparse matrices (numeric phase) */ int i, j; double *work; /* allocate and clear the working array */ work = xcalloc(1+C->n, sizeof(double)); for (j = 1; j <= C->n; j++) work[j] = 0.0; /* compute matrix C = alfa * A + beta * B */ for (i = 1; i <= C->n; i++) { SPME *e; /* work := alfa * (i-th row of A) + beta * (i-th row of B) */ /* (note that A and/or B may have duplicate elements) */ for (e = A->row[i]; e != NULL; e = e->r_next) work[e->j] += alfa * e->val; for (e = B->row[i]; e != NULL; e = e->r_next) work[e->j] += beta * e->val; /* (i-th row of C) := work, work := 0 */ for (e = C->row[i]; e != NULL; e = e->r_next) { j = e->j; e->val = work[j]; work[j] = 0.0; } } /* check and deallocate the working array */ for (j = 1; j <= C->n; j++) xassert(work[j] == 0.0); xfree(work); return; } SPM *spm_add_mat(double alfa, const SPM *A, double beta, const SPM *B) { /* add two sparse matrices (driver routine) */ SPM *C; C = spm_add_sym(A, B); spm_add_num(C, alfa, A, beta, B); return C; } SPM *spm_mul_sym(const SPM *A, const SPM *B) { /* multiply two sparse matrices (symbolic phase) */ int i, j, k, *flag; SPM *C; xassert(A->n == B->m); /* create resultant matrix */ C = spm_create_mat(A->m, B->n); /* allocate and clear the flag array */ flag = xcalloc(1+C->n, sizeof(int)); for (j = 1; j <= C->n; j++) flag[j] = 0; /* compute pattern of C = A * B */ for (i = 1; i <= C->m; i++) { SPME *e, *ee; /* compute pattern of i-th row of C */ for (e = A->row[i]; e != NULL; e = e->r_next) { k = e->j; for (ee = B->row[k]; ee != NULL; ee = ee->r_next) { j = ee->j; /* if a[i,k] != 0 and b[k,j] != 0 then c[i,j] != 0 */ if (!flag[j]) { /* c[i,j] does not exist, so create it */ spm_new_elem(C, i, j, 0.0); flag[j] = 1; } } } /* reset the flag array */ for (e = C->row[i]; e != NULL; e = e->r_next) flag[e->j] = 0; } /* check and deallocate the flag array */ for (j = 1; j <= C->n; j++) xassert(!flag[j]); xfree(flag); return C; } void spm_mul_num(SPM *C, const SPM *A, const SPM *B) { /* multiply two sparse matrices (numeric phase) */ int i, j; double *work; /* allocate and clear the working array */ work = xcalloc(1+A->n, sizeof(double)); for (j = 1; j <= A->n; j++) work[j] = 0.0; /* compute matrix C = A * B */ for (i = 1; i <= C->m; i++) { SPME *e, *ee; double temp; /* work := (i-th row of A) */ /* (note that A may have duplicate elements) */ for (e = A->row[i]; e != NULL; e = e->r_next) work[e->j] += e->val; /* compute i-th row of C */ for (e = C->row[i]; e != NULL; e = e->r_next) { j = e->j; /* c[i,j] := work * (j-th column of B) */ temp = 0.0; for (ee = B->col[j]; ee != NULL; ee = ee->c_next) temp += work[ee->i] * ee->val; e->val = temp; } /* reset the working array */ for (e = A->row[i]; e != NULL; e = e->r_next) work[e->j] = 0.0; } /* check and deallocate the working array */ for (j = 1; j <= A->n; j++) xassert(work[j] == 0.0); xfree(work); return; } SPM *spm_mul_mat(const SPM *A, const SPM *B) { /* multiply two sparse matrices (driver routine) */ SPM *C; C = spm_mul_sym(A, B); spm_mul_num(C, A, B); return C; } PER *spm_create_per(int n) { /* create permutation matrix */ PER *P; int k; xassert(n >= 0); P = xmalloc(sizeof(PER)); P->n = n; P->row = xcalloc(1+n, sizeof(int)); P->col = xcalloc(1+n, sizeof(int)); /* initially it is identity matrix */ for (k = 1; k <= n; k++) P->row[k] = P->col[k] = k; return P; } void spm_check_per(PER *P) { /* check permutation matrix for correctness */ int i, j; xassert(P->n >= 0); for (i = 1; i <= P->n; i++) { j = P->row[i]; xassert(1 <= j && j <= P->n); xassert(P->col[j] == i); } return; } void spm_delete_per(PER *P) { /* delete permutation matrix */ xfree(P->row); xfree(P->col); xfree(P); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpmpl05.c0000644000076500000240000005344613524616144025217 0ustar tamasstaff00000000000000/* glpmpl05.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Authors: Andrew Makhorin * Heinrich Schuchardt * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wsign-conversion" #endif #define _GLPSTD_STDIO #define _GLPSTD_TIME #include "glpmpl.h" double fn_gmtime(MPL *mpl) { /* obtain the current calendar time (UTC) */ time_t timer; struct tm *tm; int j; time(&timer); if (timer == (time_t)(-1)) err: error(mpl, "gmtime(); unable to obtain current calendar time"); tm = gmtime(&timer); if (tm == NULL) goto err; j = jday(tm->tm_mday, tm->tm_mon + 1, 1900 + tm->tm_year); if (j < 0) goto err; return (((double)(j - jday(1, 1, 1970)) * 24.0 + (double)tm->tm_hour) * 60.0 + (double)tm->tm_min) * 60.0 + (double)tm->tm_sec; } static char *week[] = { "Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday" }; static char *moon[] = { "January", "February", "March", "April", "May", "June", "July", "August", "September", "October", "November", "December" }; static void error1(MPL *mpl, const char *str, const char *s, const char *fmt, const char *f, const char *msg) { xprintf("Input string passed to str2time:\n"); xprintf("%s\n", str); xprintf("%*s\n", (s - str) + 1, "^"); xprintf("Format string passed to str2time:\n"); xprintf("%s\n", fmt); xprintf("%*s\n", (f - fmt) + 1, "^"); error(mpl, "%s", msg); /* no return */ } double fn_str2time(MPL *mpl, const char *str, const char *fmt) { /* convert character string to the calendar time */ int j, year, month, day, hh, mm, ss, zone; const char *s, *f; year = month = day = hh = mm = ss = -1, zone = INT_MAX; s = str; for (f = fmt; *f != '\0'; f++) { if (*f == '%') { f++; if (*f == 'b' || *f == 'h') { /* the abbreviated month name */ int k; char *name; if (month >= 0) error1(mpl, str, s, fmt, f, "month multiply specified" ); while (*s == ' ') s++; for (month = 1; month <= 12; month++) { name = moon[month-1]; for (k = 0; k <= 2; k++) { if (toupper((unsigned char)s[k]) != toupper((unsigned char)name[k])) goto next; } s += 3; for (k = 3; name[k] != '\0'; k++) { if (toupper((unsigned char)*s) != toupper((unsigned char)name[k])) break; s++; } break; next: ; } if (month > 12) error1(mpl, str, s, fmt, f, "abbreviated month name m" "issing or invalid"); } else if (*f == 'd') { /* the day of the month as a decimal number (01..31) */ if (day >= 0) error1(mpl, str, s, fmt, f, "day multiply specified"); while (*s == ' ') s++; if (!('0' <= *s && *s <= '9')) error1(mpl, str, s, fmt, f, "day missing or invalid"); day = (*s++) - '0'; if ('0' <= *s && *s <= '9') day = 10 * day + ((*s++) - '0'); if (!(1 <= day && day <= 31)) error1(mpl, str, s, fmt, f, "day out of range"); } else if (*f == 'H') { /* the hour as a decimal number, using a 24-hour clock (00..23) */ if (hh >= 0) error1(mpl, str, s, fmt, f, "hour multiply specified") ; while (*s == ' ') s++; if (!('0' <= *s && *s <= '9')) error1(mpl, str, s, fmt, f, "hour missing or invalid") ; hh = (*s++) - '0'; if ('0' <= *s && *s <= '9') hh = 10 * hh + ((*s++) - '0'); if (!(0 <= hh && hh <= 23)) error1(mpl, str, s, fmt, f, "hour out of range"); } else if (*f == 'm') { /* the month as a decimal number (01..12) */ if (month >= 0) error1(mpl, str, s, fmt, f, "month multiply specified" ); while (*s == ' ') s++; if (!('0' <= *s && *s <= '9')) error1(mpl, str, s, fmt, f, "month missing or invalid" ); month = (*s++) - '0'; if ('0' <= *s && *s <= '9') month = 10 * month + ((*s++) - '0'); if (!(1 <= month && month <= 12)) error1(mpl, str, s, fmt, f, "month out of range"); } else if (*f == 'M') { /* the minute as a decimal number (00..59) */ if (mm >= 0) error1(mpl, str, s, fmt, f, "minute multiply specifie" "d"); while (*s == ' ') s++; if (!('0' <= *s && *s <= '9')) error1(mpl, str, s, fmt, f, "minute missing or invali" "d"); mm = (*s++) - '0'; if ('0' <= *s && *s <= '9') mm = 10 * mm + ((*s++) - '0'); if (!(0 <= mm && mm <= 59)) error1(mpl, str, s, fmt, f, "minute out of range"); } else if (*f == 'S') { /* the second as a decimal number (00..60) */ if (ss >= 0) error1(mpl, str, s, fmt, f, "second multiply specifie" "d"); while (*s == ' ') s++; if (!('0' <= *s && *s <= '9')) error1(mpl, str, s, fmt, f, "second missing or invali" "d"); ss = (*s++) - '0'; if ('0' <= *s && *s <= '9') ss = 10 * ss + ((*s++) - '0'); if (!(0 <= ss && ss <= 60)) error1(mpl, str, s, fmt, f, "second out of range"); } else if (*f == 'y') { /* the year without a century as a decimal number (00..99); the values 00 to 68 mean the years 2000 to 2068 while the values 69 to 99 mean the years 1969 to 1999 */ if (year >= 0) error1(mpl, str, s, fmt, f, "year multiply specified") ; while (*s == ' ') s++; if (!('0' <= *s && *s <= '9')) error1(mpl, str, s, fmt, f, "year missing or invalid") ; year = (*s++) - '0'; if ('0' <= *s && *s <= '9') year = 10 * year + ((*s++) - '0'); year += (year >= 69 ? 1900 : 2000); } else if (*f == 'Y') { /* the year as a decimal number, using the Gregorian calendar */ if (year >= 0) error1(mpl, str, s, fmt, f, "year multiply specified") ; while (*s == ' ') s++; if (!('0' <= *s && *s <= '9')) error1(mpl, str, s, fmt, f, "year missing or invalid") ; year = 0; for (j = 1; j <= 4; j++) { if (!('0' <= *s && *s <= '9')) break; year = 10 * year + ((*s++) - '0'); } if (!(1 <= year && year <= 4000)) error1(mpl, str, s, fmt, f, "year out of range"); } else if (*f == 'z') { /* time zone offset in the form zhhmm */ int z, hh, mm; if (zone != INT_MAX) error1(mpl, str, s, fmt, f, "time zone offset multipl" "y specified"); while (*s == ' ') s++; if (*s == 'Z') { z = hh = mm = 0, s++; goto skip; } if (*s == '+') z = +1, s++; else if (*s == '-') z = -1, s++; else error1(mpl, str, s, fmt, f, "time zone offset sign mi" "ssing"); hh = 0; for (j = 1; j <= 2; j++) { if (!('0' <= *s && *s <= '9')) err1: error1(mpl, str, s, fmt, f, "time zone offset valu" "e incomplete or invalid"); hh = 10 * hh + ((*s++) - '0'); } if (hh > 23) err2: error1(mpl, str, s, fmt, f, "time zone offset value o" "ut of range"); if (*s == ':') { s++; if (!('0' <= *s && *s <= '9')) goto err1; } mm = 0; if (!('0' <= *s && *s <= '9')) goto skip; for (j = 1; j <= 2; j++) { if (!('0' <= *s && *s <= '9')) goto err1; mm = 10 * mm + ((*s++) - '0'); } if (mm > 59) goto err2; skip: zone = z * (60 * hh + mm); } else if (*f == '%') { /* literal % character */ goto test; } else error1(mpl, str, s, fmt, f, "invalid conversion specifie" "r"); } else if (*f == ' ') ; else test: { /* check a matching character in the input string */ if (*s != *f) error1(mpl, str, s, fmt, f, "character mismatch"); s++; } } if (year < 0) year = 1970; if (month < 0) month = 1; if (day < 0) day = 1; if (hh < 0) hh = 0; if (mm < 0) mm = 0; if (ss < 0) ss = 0; if (zone == INT_MAX) zone = 0; j = jday(day, month, year); xassert(j >= 0); return (((double)(j - jday(1, 1, 1970)) * 24.0 + (double)hh) * 60.0 + (double)mm) * 60.0 + (double)ss - 60.0 * (double)zone; } static void error2(MPL *mpl, const char *fmt, const char *f, const char *msg) { xprintf("Format string passed to time2str:\n"); xprintf("%s\n", fmt); xprintf("%*s\n", (f - fmt) + 1, "^"); error(mpl, "%s", msg); /* no return */ } static int weekday(int j) { /* determine weekday number (1 = Mon, ..., 7 = Sun) */ return (j + jday(1, 1, 1970)) % 7 + 1; } static int firstday(int year) { /* determine the first day of the first week for a specified year according to ISO 8601 */ int j; /* if 1 January is Monday, Tuesday, Wednesday or Thursday, it is in week 01; if 1 January is Friday, Saturday or Sunday, it is in week 52 or 53 of the previous year */ j = jday(1, 1, year) - jday(1, 1, 1970); switch (weekday(j)) { case 1: /* 1 Jan is Mon */ j += 0; break; case 2: /* 1 Jan is Tue */ j -= 1; break; case 3: /* 1 Jan is Wed */ j -= 2; break; case 4: /* 1 Jan is Thu */ j -= 3; break; case 5: /* 1 Jan is Fri */ j += 3; break; case 6: /* 1 Jan is Sat */ j += 2; break; case 7: /* 1 Jan is Sun */ j += 1; break; default: xassert(j != j); } /* the first day of the week must be Monday */ xassert(weekday(j) == 1); return j; } void fn_time2str(MPL *mpl, char *str, double t, const char *fmt) { /* convert the calendar time to character string */ int j, year, month, day, hh, mm, ss, len; double temp; const char *f; char buf[MAX_LENGTH+1]; if (!(-62135596800.0 <= t && t <= 64092211199.0)) error(mpl, "time2str(%.*g,...); argument out of range", DBL_DIG, t); t = floor(t + 0.5); temp = fabs(t) / 86400.0; j = (int)floor(temp); if (t < 0.0) { if (temp == floor(temp)) j = - j; else j = - (j + 1); } xassert(jdate(j + jday(1, 1, 1970), &day, &month, &year) == 0); ss = (int)(t - 86400.0 * (double)j); xassert(0 <= ss && ss < 86400); mm = ss / 60, ss %= 60; hh = mm / 60, mm %= 60; len = 0; for (f = fmt; *f != '\0'; f++) { if (*f == '%') { f++; if (*f == 'a') { /* the abbreviated weekday name */ memcpy(buf, week[weekday(j)-1], 3), buf[3] = '\0'; } else if (*f == 'A') { /* the full weekday name */ strcpy(buf, week[weekday(j)-1]); } else if (*f == 'b' || *f == 'h') { /* the abbreviated month name */ memcpy(buf, moon[month-1], 3), buf[3] = '\0'; } else if (*f == 'B') { /* the full month name */ strcpy(buf, moon[month-1]); } else if (*f == 'C') { /* the century of the year */ sprintf(buf, "%02d", year / 100); } else if (*f == 'd') { /* the day of the month as a decimal number (01..31) */ sprintf(buf, "%02d", day); } else if (*f == 'D') { /* the date using the format %m/%d/%y */ sprintf(buf, "%02d/%02d/%02d", month, day, year % 100); } else if (*f == 'e') { /* the day of the month like with %d, but padded with blank (1..31) */ sprintf(buf, "%2d", day); } else if (*f == 'F') { /* the date using the format %Y-%m-%d */ sprintf(buf, "%04d-%02d-%02d", year, month, day); } else if (*f == 'g') { /* the year corresponding to the ISO week number, but without the century (range 00 through 99); this has the same format and value as %y, except that if the ISO week number (see %V) belongs to the previous or next year, that year is used instead */ int iso; if (j < firstday(year)) iso = year - 1; else if (j < firstday(year + 1)) iso = year; else iso = year + 1; sprintf(buf, "%02d", iso % 100); } else if (*f == 'G') { /* the year corresponding to the ISO week number; this has the same format and value as %Y, excepth that if the ISO week number (see %V) belongs to the previous or next year, that year is used instead */ int iso; if (j < firstday(year)) iso = year - 1; else if (j < firstday(year + 1)) iso = year; else iso = year + 1; sprintf(buf, "%04d", iso); } else if (*f == 'H') { /* the hour as a decimal number, using a 24-hour clock (00..23) */ sprintf(buf, "%02d", hh); } else if (*f == 'I') { /* the hour as a decimal number, using a 12-hour clock (01..12) */ sprintf(buf, "%02d", hh == 0 ? 12 : hh <= 12 ? hh : hh - 12); } else if (*f == 'j') { /* the day of the year as a decimal number (001..366) */ sprintf(buf, "%03d", jday(day, month, year) - jday(1, 1, year) + 1); } else if (*f == 'k') { /* the hour as a decimal number, using a 24-hour clock like %H, but padded with blank (0..23) */ sprintf(buf, "%2d", hh); } else if (*f == 'l') { /* the hour as a decimal number, using a 12-hour clock like %I, but padded with blank (1..12) */ sprintf(buf, "%2d", hh == 0 ? 12 : hh <= 12 ? hh : hh - 12); } else if (*f == 'm') { /* the month as a decimal number (01..12) */ sprintf(buf, "%02d", month); } else if (*f == 'M') { /* the minute as a decimal number (00..59) */ sprintf(buf, "%02d", mm); } else if (*f == 'p') { /* either AM or PM, according to the given time value; noon is treated as PM and midnight as AM */ strcpy(buf, hh <= 11 ? "AM" : "PM"); } else if (*f == 'P') { /* either am or pm, according to the given time value; noon is treated as pm and midnight as am */ strcpy(buf, hh <= 11 ? "am" : "pm"); } else if (*f == 'r') { /* the calendar time using the format %I:%M:%S %p */ sprintf(buf, "%02d:%02d:%02d %s", hh == 0 ? 12 : hh <= 12 ? hh : hh - 12, mm, ss, hh <= 11 ? "AM" : "PM"); } else if (*f == 'R') { /* the hour and minute using the format %H:%M */ sprintf(buf, "%02d:%02d", hh, mm); } else if (*f == 'S') { /* the second as a decimal number (00..59) */ sprintf(buf, "%02d", ss); } else if (*f == 'T') { /* the time of day using the format %H:%M:%S */ sprintf(buf, "%02d:%02d:%02d", hh, mm, ss); } else if (*f == 'u') { /* the day of the week as a decimal number (1..7), Monday being 1 */ sprintf(buf, "%d", weekday(j)); } else if (*f == 'U') { /* the week number of the current year as a decimal number (range 00 through 53), starting with the first Sunday as the first day of the first week; days preceding the first Sunday in the year are considered to be in week 00 */ #if 1 /* 09/I-2009 */ #undef sun /* causes compilation error in SunOS */ #endif int sun; /* sun = the first Sunday of the year */ sun = jday(1, 1, year) - jday(1, 1, 1970); sun += (7 - weekday(sun)); sprintf(buf, "%02d", (j + 7 - sun) / 7); } else if (*f == 'V') { /* the ISO week number as a decimal number (range 01 through 53); ISO weeks start with Monday and end with Sunday; week 01 of a year is the first week which has the majority of its days in that year; week 01 of a year can contain days from the previous year; the week before week 01 of a year is the last week (52 or 53) of the previous year even if it contains days from the new year */ int iso; if (j < firstday(year)) iso = j - firstday(year - 1); else if (j < firstday(year + 1)) iso = j - firstday(year); else iso = j - firstday(year + 1); sprintf(buf, "%02d", iso / 7 + 1); } else if (*f == 'w') { /* the day of the week as a decimal number (0..6), Sunday being 0 */ sprintf(buf, "%d", weekday(j) % 7); } else if (*f == 'W') { /* the week number of the current year as a decimal number (range 00 through 53), starting with the first Monday as the first day of the first week; days preceding the first Monday in the year are considered to be in week 00 */ int mon; /* mon = the first Monday of the year */ mon = jday(1, 1, year) - jday(1, 1, 1970); mon += (8 - weekday(mon)) % 7; sprintf(buf, "%02d", (j + 7 - mon) / 7); } else if (*f == 'y') { /* the year without a century as a decimal number (00..99) */ sprintf(buf, "%02d", year % 100); } else if (*f == 'Y') { /* the year as a decimal number, using the Gregorian calendar */ sprintf(buf, "%04d", year); } else if (*f == '%') { /* a literal % character */ buf[0] = '%', buf[1] = '\0'; } else error2(mpl, fmt, f, "invalid conversion specifier"); } else buf[0] = *f, buf[1] = '\0'; if (len + strlen(buf) > MAX_LENGTH) error(mpl, "time2str; output string length exceeds %d chara" "cters", MAX_LENGTH); memcpy(str+len, buf, strlen(buf)); len += strlen(buf); } str[len] = '\0'; return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpenv.h0000644000076500000240000001551013524616144025045 0ustar tamasstaff00000000000000/* glpenv.h (GLPK environment) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPENV_H #define GLPENV_H #include "glpstd.h" #include "glplib.h" typedef struct ENV ENV; typedef struct MEM MEM; typedef struct XFILE XFILE; #define ENV_MAGIC 0x454E5631 /* environment block magic value */ #define TERM_BUF_SIZE 4096 /* terminal output buffer size, in bytes */ #define IOERR_MSG_SIZE 1024 /* i/o error message buffer size, in bytes */ #define MEM_MAGIC 0x4D454D31 /* memory block descriptor magic value */ struct ENV { /* environment block */ int magic; /* magic value used for debugging */ char version[7+1]; /* version string returned by the routine glp_version */ /*--------------------------------------------------------------*/ /* terminal output */ char *term_buf; /* char term_buf[TERM_BUF_SIZE]; */ /* terminal output buffer */ int term_out; /* flag to enable/disable terminal output */ int (*term_hook)(void *info, const char *s); /* user-defined routine to intercept terminal output */ void *term_info; /* transit pointer (cookie) passed to the routine term_hook */ FILE *tee_file; /* output stream used to copy terminal output */ /*--------------------------------------------------------------*/ /* error handling */ const char *err_file; /* value of the __FILE__ macro passed to glp_error */ int err_line; /* value of the __LINE__ macro passed to glp_error */ void (*err_hook)(void *info); /* user-defined routine to intercept abnormal termination */ void *err_info; /* transit pointer (cookie) passed to the routine err_hook */ /*--------------------------------------------------------------*/ /* memory allocation */ glp_long mem_limit; /* maximal amount of memory (in bytes) available for dynamic allocation */ MEM *mem_ptr; /* pointer to the linked list of allocated memory blocks */ int mem_count; /* total number of currently allocated memory blocks */ int mem_cpeak; /* peak value of mem_count */ glp_long mem_total; /* total amount of currently allocated memory (in bytes; is the sum of the size field over all memory block descriptors) */ glp_long mem_tpeak; /* peak value of mem_total */ /*--------------------------------------------------------------*/ /* stream input/output */ XFILE *file_ptr; /* pointer to the linked list of active stream descriptors */ char *ioerr_msg; /* char ioerr_msg[IOERR_MSG_SIZE]; */ /* input/output error message buffer */ /*--------------------------------------------------------------*/ /* shared libraries support */ void *h_odbc; /* handle to ODBC shared library */ void *h_mysql; /* handle to MySQL shared library */ }; struct MEM { /* memory block descriptor */ int flag; /* descriptor flag */ int size; /* size of block (in bytes, including descriptor) */ MEM *prev; /* pointer to previous memory block descriptor */ MEM *next; /* pointer to next memory block descriptor */ }; struct XFILE { /* input/output stream descriptor */ int type; /* stream handle type: */ #define FH_FILE 0x11 /* FILE */ #define FH_ZLIB 0x22 /* gzFile */ void *fh; /* pointer to stream handle */ XFILE *prev; /* pointer to previous stream descriptor */ XFILE *next; /* pointer to next stream descriptor */ }; #define XEOF (-1) #define get_env_ptr _glp_get_env_ptr ENV *get_env_ptr(void); /* retrieve pointer to environment block */ #define tls_set_ptr _glp_tls_set_ptr void tls_set_ptr(void *ptr); /* store global pointer in TLS */ #define tls_get_ptr _glp_tls_get_ptr void *tls_get_ptr(void); /* retrieve global pointer from TLS */ #define xprintf glp_printf void glp_printf(const char *fmt, ...); /* write formatted output to the terminal */ #define xvprintf glp_vprintf void glp_vprintf(const char *fmt, va_list arg); /* write formatted output to the terminal */ #ifndef GLP_ERROR_DEFINED #define GLP_ERROR_DEFINED typedef void (*_glp_error)(const char *fmt, ...); #endif #define xerror glp_error_(__FILE__, __LINE__) _glp_error glp_error_(const char *file, int line); /* display error message and terminate execution */ #define xassert(expr) \ ((void)((expr) || (glp_assert_(#expr, __FILE__, __LINE__), 1))) void glp_assert_(const char *expr, const char *file, int line); /* check for logical condition */ #define xmalloc glp_malloc void *glp_malloc(int size); /* allocate memory block */ #define xcalloc glp_calloc void *glp_calloc(int n, int size); /* allocate memory block */ #define xfree glp_free void glp_free(void *ptr); /* free memory block */ #define xtime glp_time glp_long glp_time(void); /* determine current universal time */ #define xdifftime glp_difftime double glp_difftime(glp_long t1, glp_long t0); /* compute difference between two time values, in seconds */ #define lib_err_msg _glp_lib_err_msg void lib_err_msg(const char *msg); #define xerrmsg _glp_lib_xerrmsg const char *xerrmsg(void); #define xfopen _glp_lib_xfopen XFILE *xfopen(const char *fname, const char *mode); #define xferror _glp_lib_xferror int xferror(XFILE *file); #define xfeof _glp_lib_xfeof int xfeof(XFILE *file); #define xfgetc _glp_lib_xfgetc int xfgetc(XFILE *file); #define xfputc _glp_lib_xfputc int xfputc(int c, XFILE *file); #define xfflush _glp_lib_xfflush int xfflush(XFILE *fp); #define xfclose _glp_lib_xfclose int xfclose(XFILE *file); #define xfprintf _glp_lib_xfprintf int xfprintf(XFILE *file, const char *fmt, ...); #define xdlopen _glp_xdlopen void *xdlopen(const char *module); #define xdlsym _glp_xdlsym void *xdlsym(void *h, const char *symbol); #define xdlclose _glp_xdlclose void xdlclose(void *h); #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpenv06.c0000644000076500000240000001116313524616144025206 0ustar tamasstaff00000000000000/* glpenv06.c (standard time) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef HAVE_CONFIG_H #include #endif #include "glpapi.h" /*********************************************************************** * NAME * * glp_time - determine current universal time * * SYNOPSIS * * glp_long glp_time(void); * * RETURNS * * The routine glp_time returns the current universal time (UTC), in * milliseconds, elapsed since 00:00:00 GMT January 1, 1970. */ static const int epoch = 2440588; /* = jday(1, 1, 1970) */ /* POSIX version ******************************************************/ #if defined(HAVE_SYS_TIME_H) && defined(HAVE_GETTIMEOFDAY) #include #include glp_long glp_time(void) { struct timeval tv; struct tm *tm; glp_long t; int j; gettimeofday(&tv, NULL); tm = gmtime(&tv.tv_sec); j = jday(tm->tm_mday, tm->tm_mon + 1, 1900 + tm->tm_year); xassert(j >= 0); t = xlset(j - epoch); t = xlmul(t, xlset(24)); t = xladd(t, xlset(tm->tm_hour)); t = xlmul(t, xlset(60)); t = xladd(t, xlset(tm->tm_min)); t = xlmul(t, xlset(60)); t = xladd(t, xlset(tm->tm_sec)); t = xlmul(t, xlset(1000)); t = xladd(t, xlset(tv.tv_usec / 1000)); return t; } /* Windows version ****************************************************/ #elif defined(__WOE__) #include glp_long glp_time(void) { SYSTEMTIME st; glp_long t; int j; GetSystemTime(&st); j = jday(st.wDay, st.wMonth, st.wYear); xassert(j >= 0); t = xlset(j - epoch); t = xlmul(t, xlset(24)); t = xladd(t, xlset(st.wHour)); t = xlmul(t, xlset(60)); t = xladd(t, xlset(st.wMinute)); t = xlmul(t, xlset(60)); t = xladd(t, xlset(st.wSecond)); t = xlmul(t, xlset(1000)); t = xladd(t, xlset(st.wMilliseconds)); return t; } /* portable ISO C version *********************************************/ #else #include glp_long glp_time(void) { time_t timer; struct tm *tm; glp_long t; int j; timer = time(NULL); tm = gmtime(&timer); j = jday(tm->tm_mday, tm->tm_mon + 1, 1900 + tm->tm_year); xassert(j >= 0); t = xlset(j - epoch); t = xlmul(t, xlset(24)); t = xladd(t, xlset(tm->tm_hour)); t = xlmul(t, xlset(60)); t = xladd(t, xlset(tm->tm_min)); t = xlmul(t, xlset(60)); t = xladd(t, xlset(tm->tm_sec)); t = xlmul(t, xlset(1000)); return t; } #endif /*********************************************************************** * NAME * * glp_difftime - compute difference between two time values * * SYNOPSIS * * double glp_difftime(glp_long t1, glp_long t0); * * RETURNS * * The routine glp_difftime returns the difference between two time * values t1 and t0, expressed in seconds. */ double glp_difftime(glp_long t1, glp_long t0) { return xltod(xlsub(t1, t0)) / 1000.0; } /**********************************************************************/ #if 0 int main(void) { glp_long t; glp_ldiv d; int ttt, ss, mm, hh, day, month, year; char s[50]; t = glp_time(); xprintf("t = %s\n", xltoa(t, s)); d = xldiv(t, xlset(1000)); ttt = d.rem.lo, t = d.quot; d = xldiv(t, xlset(60)); ss = d.rem.lo, t = d.quot; d = xldiv(t, xlset(60)); mm = d.rem.lo, t = d.quot; d = xldiv(t, xlset(24)); hh = d.rem.lo, t = d.quot; xassert(jdate(t.lo + epoch, &day, &month, &year) == 0); xprintf("%04d-%02d-%02d %02d:%02d:%02d.%03d\n", year, month, day, hh, mm, ss, ttt); return 0; } #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glptsp.c0000644000076500000240000005730413524616144025065 0ustar tamasstaff00000000000000/* glptsp.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wshorten-64-to-32" #pragma clang diagnostic ignored "-Wsometimes-uninitialized" #endif #define _GLPSTD_ERRNO #define _GLPSTD_STDIO #include "glpenv.h" #include "glptsp.h" #define xfault xerror /*---------------------------------------------------------------------- -- tsp_read_data - read TSP instance data. -- -- *Synopsis* -- -- #include "glptsp.h" -- TSP *tsp_read_data(char *fname); -- -- *Description* -- -- The routine tsp_read_data reads a TSP (or related problem) instance -- data from the text file, whose name is the character string fname. -- -- For detailed description of the format recognized by the routine see -- the report: G.Reinelt, TSPLIB 95. -- -- *Returns* -- -- If no error occurred, the routine tsp_read_data returns a pointer to -- the TSP instance data block, which contains loaded data. In the case -- of error the routine prints an error message and returns NULL. */ struct dsa { /* dynamic storage area used by the routine tsp_read_data */ char *fname; /* name of the input text file */ FILE *fp; /* stream assigned to the input text file */ int seqn; /* line sequential number */ int c; /* current character */ char token[255+1]; /* current token */ }; static int get_char(struct dsa *dsa) { dsa->c = fgetc(dsa->fp); if (ferror(dsa->fp)) { xprintf("%s:%d: read error - %s\n", dsa->fname, dsa->seqn, strerror(errno)); return 1; } if (feof(dsa->fp)) dsa->c = EOF; else if (dsa->c == '\n') dsa->seqn++; else if (isspace(dsa->c)) dsa->c = ' '; else if (iscntrl(dsa->c)) { xprintf("%s:%d: invalid control character 0x%02X\n", dsa->fname, dsa->seqn, dsa->c); return 1; } return 0; } static int skip_spaces(struct dsa *dsa, int across) { while (dsa->c == ' ' || (across && dsa->c == '\n')) if (get_char(dsa)) return 1; return 0; } static int scan_keyword(struct dsa *dsa) { int len = 0; if (skip_spaces(dsa, 0)) return 1; dsa->token[0] = '\0'; while (isalnum(dsa->c) || dsa->c == '_') { if (len == 31) { xprintf("%s:%d: keyword `%s...' too long\n", dsa->fname, dsa->seqn, dsa->token); return 1; } dsa->token[len++] = (char)dsa->c, dsa->token[len] = '\0'; if (get_char(dsa)) return 1; } if (len == 0) { xprintf("%s:%d: missing keyword\n", dsa->fname, dsa->seqn); return 1; } return 0; } static int check_colon(struct dsa *dsa) { if (skip_spaces(dsa, 0)) return 1; if (dsa->c != ':') { xprintf("%s:%d: missing colon after `%s'\n", dsa->fname, dsa->seqn, dsa->token); return 1; } if (get_char(dsa)) return 1; return 0; } static int scan_token(struct dsa *dsa, int across) { int len = 0; if (skip_spaces(dsa, across)) return 1; dsa->token[0] = '\0'; while (!(dsa->c == EOF || dsa->c == '\n' || dsa->c == ' ')) { if (len == 255) { dsa->token[31] = '\0'; xprintf("%s:%d: token `%s...' too long\n", dsa->fname, dsa->seqn, dsa->token); return 1; } dsa->token[len++] = (char)dsa->c, dsa->token[len] = '\0'; if (get_char(dsa)) return 1; } return 0; } static int check_newline(struct dsa *dsa) { if (skip_spaces(dsa, 0)) return 1; if (!(dsa->c == EOF || dsa->c == '\n')) { xprintf("%s:%d: extra symbols detected\n", dsa->fname, dsa->seqn); return 1; } if (get_char(dsa)) return 1; return 0; } static int scan_comment(struct dsa *dsa) { int len = 0; if (skip_spaces(dsa, 0)) return 1; dsa->token[0] = '\0'; while (!(dsa->c == EOF || dsa->c == '\n')) { if (len == 255) { xprintf("%s:%d: comment too long\n", dsa->fname, dsa->seqn) ; return 1; } dsa->token[len++] = (char)dsa->c, dsa->token[len] = '\0'; if (get_char(dsa)) return 1; } return 0; } static int scan_integer(struct dsa *dsa, int across, int *val) { if (scan_token(dsa, across)) return 1; if (strlen(dsa->token) == 0) { xprintf("%s:%d: missing integer\n", dsa->fname, dsa->seqn); return 1; } if (str2int(dsa->token, val)) { xprintf("%s:%d: integer `%s' invalid\n", dsa->fname, dsa->seqn , dsa->token); return 1; } return 0; } static int scan_number(struct dsa *dsa, int across, double *val) { if (scan_token(dsa, across)) return 1; if (strlen(dsa->token) == 0) { xprintf("%s:%d: missing number\n", dsa->fname, dsa->seqn); return 1; } if (str2num(dsa->token, val)) { xprintf("%s:%d: number `%s' invalid\n", dsa->fname, dsa->seqn, dsa->token); return 1; } return 0; } TSP *tsp_read_data(char *fname) { struct dsa _dsa, *dsa = &_dsa; TSP *tsp = NULL; dsa->fname = fname; xprintf("tsp_read_data: reading TSP data from `%s'...\n", dsa->fname); dsa->fp = fopen(dsa->fname, "r"); if (dsa->fp == NULL) { xprintf("tsp_read_data: unable to open `%s' - %s\n", dsa->fname, strerror(errno)); goto fail; } tsp = xmalloc(sizeof(TSP)); tsp->name = NULL; tsp->type = TSP_UNDEF; tsp->comment = NULL; tsp->dimension = 0; tsp->edge_weight_type = TSP_UNDEF; tsp->edge_weight_format = TSP_UNDEF; tsp->display_data_type = TSP_UNDEF; tsp->node_x_coord = NULL; tsp->node_y_coord = NULL; tsp->dply_x_coord = NULL; tsp->dply_y_coord = NULL; tsp->tour = NULL; tsp->edge_weight = NULL; dsa->seqn = 1; if (get_char(dsa)) goto fail; loop: if (scan_keyword(dsa)) goto fail; if (strcmp(dsa->token, "NAME") == 0) { if (tsp->name != NULL) { xprintf("%s:%d: NAME entry multiply defined\n", dsa->fname, dsa->seqn); goto fail; } if (check_colon(dsa)) goto fail; if (scan_token(dsa, 0)) goto fail; if (strlen(dsa->token) == 0) { xprintf("%s:%d: NAME entry incomplete\n", dsa->fname, dsa->seqn); goto fail; } tsp->name = xmalloc(strlen(dsa->token) + 1); strcpy(tsp->name, dsa->token); xprintf("tsp_read_data: NAME: %s\n", tsp->name); if (check_newline(dsa)) goto fail; } else if (strcmp(dsa->token, "TYPE") == 0) { if (tsp->type != TSP_UNDEF) { xprintf("%s:%d: TYPE entry multiply defined\n", dsa->fname, dsa->seqn); goto fail; } if (check_colon(dsa)) goto fail; if (scan_keyword(dsa)) goto fail; if (strcmp(dsa->token, "TSP") == 0) tsp->type = TSP_TSP; else if (strcmp(dsa->token, "ATSP") == 0) tsp->type = TSP_ATSP; else if (strcmp(dsa->token, "TOUR") == 0) tsp->type = TSP_TOUR; else { xprintf("%s:%d: data type `%s' not recognized\n", dsa->fname, dsa->seqn, dsa->token); goto fail; } xprintf("tsp_read_data: TYPE: %s\n", dsa->token); if (check_newline(dsa)) goto fail; } else if (strcmp(dsa->token, "COMMENT") == 0) { if (tsp->comment != NULL) { xprintf("%s:%d: COMMENT entry multiply defined\n", dsa->fname, dsa->seqn); goto fail; } if (check_colon(dsa)) goto fail; if (scan_comment(dsa)) goto fail; tsp->comment = xmalloc(strlen(dsa->token) + 1); strcpy(tsp->comment, dsa->token); xprintf("tsp_read_data: COMMENT: %s\n", tsp->comment); if (check_newline(dsa)) goto fail; } else if (strcmp(dsa->token, "DIMENSION") == 0) { if (tsp->dimension != 0) { xprintf("%s:%d: DIMENSION entry multiply defined\n", dsa->fname, dsa->seqn); goto fail; } if (check_colon(dsa)) goto fail; if (scan_integer(dsa, 0, &tsp->dimension)) goto fail; if (tsp->dimension < 1) { xprintf("%s:%d: invalid dimension\n", dsa->fname, dsa->seqn); goto fail; } xprintf("tsp_read_data: DIMENSION: %d\n", tsp->dimension); if (check_newline(dsa)) goto fail; } else if (strcmp(dsa->token, "EDGE_WEIGHT_TYPE") == 0) { if (tsp->edge_weight_type != TSP_UNDEF) { xprintf("%s:%d: EDGE_WEIGHT_TYPE entry multiply defined\n", dsa->fname, dsa->seqn); goto fail; } if (check_colon(dsa)) goto fail; if (scan_keyword(dsa)) goto fail; if (strcmp(dsa->token, "GEO") == 0) tsp->edge_weight_type = TSP_GEO; else if (strcmp(dsa->token, "EUC_2D") == 0) tsp->edge_weight_type = TSP_EUC_2D; else if (strcmp(dsa->token, "ATT") == 0) tsp->edge_weight_type = TSP_ATT; else if (strcmp(dsa->token, "EXPLICIT") == 0) tsp->edge_weight_type = TSP_EXPLICIT; else if (strcmp(dsa->token, "CEIL_2D") == 0) tsp->edge_weight_type = TSP_CEIL_2D; else { xprintf("%s:%d: edge weight type `%s' not recognized\n", dsa->fname, dsa->seqn, dsa->token); goto fail; } xprintf("tsp_read_data: EDGE_WEIGHT_TYPE: %s\n", dsa->token); if (check_newline(dsa)) goto fail; } else if (strcmp(dsa->token, "EDGE_WEIGHT_FORMAT") == 0) { if (tsp->edge_weight_format != TSP_UNDEF) { xprintf( "%s:%d: EDGE_WEIGHT_FORMAT entry multiply defined\n", dsa->fname, dsa->seqn); goto fail; } if (check_colon(dsa)) goto fail; if (scan_keyword(dsa)) goto fail; if (strcmp(dsa->token, "UPPER_ROW") == 0) tsp->edge_weight_format = TSP_UPPER_ROW; else if (strcmp(dsa->token, "FULL_MATRIX") == 0) tsp->edge_weight_format = TSP_FULL_MATRIX; else if (strcmp(dsa->token, "FUNCTION") == 0) tsp->edge_weight_format = TSP_FUNCTION; else if (strcmp(dsa->token, "LOWER_DIAG_ROW") == 0) tsp->edge_weight_format = TSP_LOWER_DIAG_ROW; else { xprintf("%s:%d: edge weight format `%s' not recognized\n", dsa->fname, dsa->seqn, dsa->token); goto fail; } xprintf("tsp_read_data: EDGE_WEIGHT_FORMAT: %s\n", dsa->token); if (check_newline(dsa)) goto fail; } else if (strcmp(dsa->token, "DISPLAY_DATA_TYPE") == 0) { if (tsp->display_data_type != TSP_UNDEF) { xprintf("%s:%d: DISPLAY_DATA_TYPE entry multiply defined\n", dsa->fname, dsa->seqn); goto fail; } if (check_colon(dsa)) goto fail; if (scan_keyword(dsa)) goto fail; if (strcmp(dsa->token, "COORD_DISPLAY") == 0) tsp->display_data_type = TSP_COORD_DISPLAY; else if (strcmp(dsa->token, "TWOD_DISPLAY") == 0) tsp->display_data_type = TSP_TWOD_DISPLAY; else { xprintf("%s:%d: display data type `%s' not recognized\n", dsa->fname, dsa->seqn, dsa->token); goto fail; } xprintf("tsp_read_data: DISPLAY_DATA_TYPE: %s\n", dsa->token); if (check_newline(dsa)) goto fail; } else if (strcmp(dsa->token, "NODE_COORD_SECTION") == 0) { int n = tsp->dimension, k, node; if (n == 0) { xprintf("%s:%d: DIMENSION entry not specified\n", dsa->fname, dsa->seqn); goto fail; } if (tsp->node_x_coord != NULL) { xprintf("%s:%d: NODE_COORD_SECTION multiply specified\n", dsa->fname, dsa->seqn); goto fail; } if (check_newline(dsa)) goto fail; tsp->node_x_coord = xcalloc(1+n, sizeof(double)); tsp->node_y_coord = xcalloc(1+n, sizeof(double)); for (node = 1; node <= n; node++) tsp->node_x_coord[node] = tsp->node_y_coord[node] = DBL_MAX; for (k = 1; k <= n; k++) { if (scan_integer(dsa, 0, &node)) goto fail; if (!(1 <= node && node <= n)) { xprintf("%s:%d: invalid node number %d\n", dsa->fname, dsa->seqn, node); goto fail; } if (tsp->node_x_coord[node] != DBL_MAX) { xprintf("%s:%d: node number %d multiply specified\n", dsa->fname, dsa->seqn, node); goto fail; } if (scan_number(dsa, 0, &tsp->node_x_coord[node])) goto fail; if (scan_number(dsa, 0, &tsp->node_y_coord[node])) goto fail; if (check_newline(dsa)) goto fail; } } else if (strcmp(dsa->token, "DISPLAY_DATA_SECTION") == 0) { int n = tsp->dimension, k, node; if (n == 0) { xprintf("%s:%d: DIMENSION entry not specified\n", dsa->fname, dsa->seqn); goto fail; } if (tsp->dply_x_coord != NULL) { xprintf("%s:%d: DISPLAY_DATA_SECTION multiply specified\n", dsa->fname, dsa->seqn); goto fail; } if (check_newline(dsa)) goto fail; tsp->dply_x_coord = xcalloc(1+n, sizeof(double)); tsp->dply_y_coord = xcalloc(1+n, sizeof(double)); for (node = 1; node <= n; node++) tsp->dply_x_coord[node] = tsp->dply_y_coord[node] = DBL_MAX; for (k = 1; k <= n; k++) { if (scan_integer(dsa, 0, &node)) goto fail; if (!(1 <= node && node <= n)) { xprintf("%s:%d: invalid node number %d\n", dsa->fname, dsa->seqn, node); goto fail; } if (tsp->dply_x_coord[node] != DBL_MAX) { xprintf("%s:%d: node number %d multiply specified\n", dsa->fname, dsa->seqn, node); goto fail; } if (scan_number(dsa, 0, &tsp->dply_x_coord[node])) goto fail; if (scan_number(dsa, 0, &tsp->dply_y_coord[node])) goto fail; if (check_newline(dsa)) goto fail; } } else if (strcmp(dsa->token, "TOUR_SECTION") == 0) { int n = tsp->dimension, k, node; if (n == 0) { xprintf("%s:%d: DIMENSION entry not specified\n", dsa->fname, dsa->seqn); goto fail; } if (tsp->tour != NULL) { xprintf("%s:%d: TOUR_SECTION multiply specified\n", dsa->fname, dsa->seqn); goto fail; } if (check_newline(dsa)) goto fail; tsp->tour = xcalloc(1+n, sizeof(int)); for (k = 1; k <= n; k++) { if (scan_integer(dsa, 1, &node)) goto fail; if (!(1 <= node && node <= n)) { xprintf("%s:%d: invalid node number %d\n", dsa->fname, dsa->seqn, node); goto fail; } tsp->tour[k] = node; } if (scan_integer(dsa, 1, &node)) goto fail; if (node != -1) { xprintf("%s:%d: extra node(s) detected\n", dsa->fname, dsa->seqn); goto fail; } if (check_newline(dsa)) goto fail; } else if (strcmp(dsa->token, "EDGE_WEIGHT_SECTION") == 0) { int n = tsp->dimension, i, j, temp; if (n == 0) { xprintf("%s:%d: DIMENSION entry not specified\n", dsa->fname, dsa->seqn); goto fail; } if (tsp->edge_weight_format == TSP_UNDEF) { xprintf("%s:%d: EDGE_WEIGHT_FORMAT entry not specified\n", dsa->fname, dsa->seqn); goto fail; } if (tsp->edge_weight != NULL) { xprintf("%s:%d: EDGE_WEIGHT_SECTION multiply specified\n", dsa->fname, dsa->seqn); goto fail; } if (check_newline(dsa)) goto fail; tsp->edge_weight = xcalloc(1+n*n, sizeof(int)); switch (tsp->edge_weight_format) { case TSP_FULL_MATRIX: for (i = 1; i <= n; i++) { for (j = 1; j <= n; j++) { if (scan_integer(dsa, 1, &temp)) goto fail; tsp->edge_weight[(i - 1) * n + j] = temp; } } break; case TSP_UPPER_ROW: for (i = 1; i <= n; i++) { tsp->edge_weight[(i - 1) * n + i] = 0; for (j = i + 1; j <= n; j++) { if (scan_integer(dsa, 1, &temp)) goto fail; tsp->edge_weight[(i - 1) * n + j] = temp; tsp->edge_weight[(j - 1) * n + i] = temp; } } break; case TSP_LOWER_DIAG_ROW: for (i = 1; i <= n; i++) { for (j = 1; j <= i; j++) { if (scan_integer(dsa, 1, &temp)) goto fail; tsp->edge_weight[(i - 1) * n + j] = temp; tsp->edge_weight[(j - 1) * n + i] = temp; } } break; default: goto fail; } if (check_newline(dsa)) goto fail; } else if (strcmp(dsa->token, "EOF") == 0) { if (check_newline(dsa)) goto fail; goto done; } else { xprintf("%s:%d: keyword `%s' not recognized\n", dsa->fname, dsa->seqn, dsa->token); goto fail; } goto loop; done: xprintf("tsp_read_data: %d lines were read\n", dsa->seqn-1); fclose(dsa->fp); return tsp; fail: if (tsp != NULL) { if (tsp->name != NULL) xfree(tsp->name); if (tsp->comment != NULL) xfree(tsp->comment); if (tsp->node_x_coord != NULL) xfree(tsp->node_x_coord); if (tsp->node_y_coord != NULL) xfree(tsp->node_y_coord); if (tsp->dply_x_coord != NULL) xfree(tsp->dply_x_coord); if (tsp->dply_y_coord != NULL) xfree(tsp->dply_y_coord); if (tsp->tour != NULL) xfree(tsp->tour); if (tsp->edge_weight != NULL) xfree(tsp->edge_weight); xfree(tsp); } if (dsa->fp != NULL) fclose(dsa->fp); return NULL; } /*---------------------------------------------------------------------- -- tsp_free_data - free TSP instance data. -- -- *Synopsis* -- -- #include "glptsp.h" -- void tsp_free_data(TSP *tsp); -- -- *Description* -- -- The routine tsp_free_data frees all the memory allocated to the TSP -- instance data block, which the parameter tsp points to. */ void tsp_free_data(TSP *tsp) { if (tsp->name != NULL) xfree(tsp->name); if (tsp->comment != NULL) xfree(tsp->comment); if (tsp->node_x_coord != NULL) xfree(tsp->node_x_coord); if (tsp->node_y_coord != NULL) xfree(tsp->node_y_coord); if (tsp->dply_x_coord != NULL) xfree(tsp->dply_x_coord); if (tsp->dply_y_coord != NULL) xfree(tsp->dply_y_coord); if (tsp->tour != NULL) xfree(tsp->tour); if (tsp->edge_weight != NULL) xfree(tsp->edge_weight); xfree(tsp); return; } /*---------------------------------------------------------------------- -- tsp_distance - compute distance between two nodes. -- -- *Synopsis* -- -- #include "glptsp.h" -- int tsp_distance(TSP *tsp, int i, int j); -- -- *Description* -- -- The routine tsp_distance computes the distance between i-th and j-th -- nodes for the TSP instance, which tsp points to. -- -- *Returns* -- -- The routine tsp_distance returns the computed distance. */ #define nint(x) ((int)((x) + 0.5)) static double rad(double x) { /* convert input coordinate to longitude/latitude, in radians */ double pi = 3.141592, deg, min; deg = (int)x; min = x - deg; return pi * (deg + 5.0 * min / 3.0) / 180.0; } int tsp_distance(TSP *tsp, int i, int j) { int n = tsp->dimension, dij; if (!(tsp->type == TSP_TSP || tsp->type == TSP_ATSP)) xfault("tsp_distance: invalid TSP instance\n"); if (!(1 <= i && i <= n && 1 <= j && j <= n)) xfault("tsp_distance: node number out of range\n"); switch (tsp->edge_weight_type) { case TSP_UNDEF: xfault("tsp_distance: edge weight type not specified\n"); case TSP_EXPLICIT: if (tsp->edge_weight == NULL) xfault("tsp_distance: edge weights not specified\n"); dij = tsp->edge_weight[(i - 1) * n + j]; break; case TSP_EUC_2D: if (tsp->node_x_coord == NULL || tsp->node_y_coord == NULL) xfault("tsp_distance: node coordinates not specified\n"); { double xd, yd; xd = tsp->node_x_coord[i] - tsp->node_x_coord[j]; yd = tsp->node_y_coord[i] - tsp->node_y_coord[j]; dij = nint(sqrt(xd * xd + yd * yd)); } break; case TSP_CEIL_2D: if (tsp->node_x_coord == NULL || tsp->node_y_coord == NULL) xfault("tsp_distance: node coordinates not specified\n"); { double xd, yd; xd = tsp->node_x_coord[i] - tsp->node_x_coord[j]; yd = tsp->node_y_coord[i] - tsp->node_y_coord[j]; dij = (int)ceil(sqrt(xd * xd + yd * yd)); } break; case TSP_GEO: if (tsp->node_x_coord == NULL || tsp->node_y_coord == NULL) xfault("tsp_distance: node coordinates not specified\n"); { double rrr = 6378.388; double latitude_i = rad(tsp->node_x_coord[i]); double latitude_j = rad(tsp->node_x_coord[j]); double longitude_i = rad(tsp->node_y_coord[i]); double longitude_j = rad(tsp->node_y_coord[j]); double q1 = cos(longitude_i - longitude_j); double q2 = cos(latitude_i - latitude_j); double q3 = cos(latitude_i + latitude_j); dij = (int)(rrr * acos(0.5 * ((1.0 + q1) * q2 - (1.0 - q1) *q3)) + 1.0); } break; case TSP_ATT: if (tsp->node_x_coord == NULL || tsp->node_y_coord == NULL) xfault("tsp_distance: node coordinates not specified\n"); { int tij; double xd, yd, rij; xd = tsp->node_x_coord[i] - tsp->node_x_coord[j]; yd = tsp->node_y_coord[i] - tsp->node_y_coord[j]; rij = sqrt((xd * xd + yd * yd) / 10.0); tij = nint(rij); if (tij < rij) dij = tij + 1; else dij = tij; } break; default: xassert(tsp->edge_weight_type != tsp->edge_weight_type); } return dij; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpnpp03.c0000644000076500000240000030107413524616144025213 0ustar tamasstaff00000000000000/* glpnpp03.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wlogical-op-parentheses" #endif #include "glpnpp.h" /*********************************************************************** * NAME * * npp_empty_row - process empty row * * SYNOPSIS * * #include "glpnpp.h" * int npp_empty_row(NPP *npp, NPPROW *p); * * DESCRIPTION * * The routine npp_empty_row processes row p, which is empty, i.e. * coefficients at all columns in this row are zero: * * L[p] <= sum 0 x[j] <= U[p], (1) * * where L[p] <= U[p]. * * RETURNS * * 0 - success; * * 1 - problem has no primal feasible solution. * * PROBLEM TRANSFORMATION * * If the following conditions hold: * * L[p] <= +eps, U[p] >= -eps, (2) * * where eps is an absolute tolerance for row value, the row p is * redundant. In this case it can be replaced by equivalent redundant * row, which is free (unbounded), and then removed from the problem. * Otherwise, the row p is infeasible and, thus, the problem has no * primal feasible solution. * * RECOVERING BASIC SOLUTION * * See the routine npp_free_row. * * RECOVERING INTERIOR-POINT SOLUTION * * See the routine npp_free_row. * * RECOVERING MIP SOLUTION * * None needed. */ int npp_empty_row(NPP *npp, NPPROW *p) { /* process empty row */ double eps = 1e-3; /* the row must be empty */ xassert(p->ptr == NULL); /* check primal feasibility */ if (p->lb > +eps || p->ub < -eps) return 1; /* replace the row by equivalent free (unbounded) row */ p->lb = -DBL_MAX, p->ub = +DBL_MAX; /* and process it */ npp_free_row(npp, p); return 0; } /*********************************************************************** * NAME * * npp_empty_col - process empty column * * SYNOPSIS * * #include "glpnpp.h" * int npp_empty_col(NPP *npp, NPPCOL *q); * * DESCRIPTION * * The routine npp_empty_col processes column q: * * l[q] <= x[q] <= u[q], (1) * * where l[q] <= u[q], which is empty, i.e. has zero coefficients in * all constraint rows. * * RETURNS * * 0 - success; * * 1 - problem has no dual feasible solution. * * PROBLEM TRANSFORMATION * * The row of the dual system corresponding to the empty column is the * following: * * sum 0 pi[i] + lambda[q] = c[q], (2) * i * * from which it follows that: * * lambda[q] = c[q]. (3) * * If the following condition holds: * * c[q] < - eps, (4) * * where eps is an absolute tolerance for column multiplier, the lower * column bound l[q] must be active to provide dual feasibility (note * that being preprocessed the problem is always minimization). In this * case the column can be fixed on its lower bound and removed from the * problem (if the column is integral, its bounds are also assumed to * be integral). And if the column has no lower bound (l[q] = -oo), the * problem has no dual feasible solution. * * If the following condition holds: * * c[q] > + eps, (5) * * the upper column bound u[q] must be active to provide dual * feasibility. In this case the column can be fixed on its upper bound * and removed from the problem. And if the column has no upper bound * (u[q] = +oo), the problem has no dual feasible solution. * * Finally, if the following condition holds: * * - eps <= c[q] <= +eps, (6) * * dual feasibility does not depend on a particular value of column q. * In this case the column can be fixed either on its lower bound (if * l[q] > -oo) or on its upper bound (if u[q] < +oo) or at zero (if the * column is unbounded) and then removed from the problem. * * RECOVERING BASIC SOLUTION * * See the routine npp_fixed_col. Having been recovered the column * is assigned status GLP_NS. However, if actually it is not fixed * (l[q] < u[q]), its status should be changed to GLP_NL, GLP_NU, or * GLP_NF depending on which bound it was fixed on transformation stage. * * RECOVERING INTERIOR-POINT SOLUTION * * See the routine npp_fixed_col. * * RECOVERING MIP SOLUTION * * See the routine npp_fixed_col. */ struct empty_col { /* empty column */ int q; /* column reference number */ char stat; /* status in basic solution */ }; static int rcv_empty_col(NPP *npp, void *info); int npp_empty_col(NPP *npp, NPPCOL *q) { /* process empty column */ struct empty_col *info; double eps = 1e-3; /* the column must be empty */ xassert(q->ptr == NULL); /* check dual feasibility */ if (q->coef > +eps && q->lb == -DBL_MAX) return 1; if (q->coef < -eps && q->ub == +DBL_MAX) return 1; /* create transformation stack entry */ info = npp_push_tse(npp, rcv_empty_col, sizeof(struct empty_col)); info->q = q->j; /* fix the column */ if (q->lb == -DBL_MAX && q->ub == +DBL_MAX) { /* free column */ info->stat = GLP_NF; q->lb = q->ub = 0.0; } else if (q->ub == +DBL_MAX) lo: { /* column with lower bound */ info->stat = GLP_NL; q->ub = q->lb; } else if (q->lb == -DBL_MAX) up: { /* column with upper bound */ info->stat = GLP_NU; q->lb = q->ub; } else if (q->lb != q->ub) { /* double-bounded column */ if (q->coef >= +DBL_EPSILON) goto lo; if (q->coef <= -DBL_EPSILON) goto up; if (fabs(q->lb) <= fabs(q->ub)) goto lo; else goto up; } else { /* fixed column */ info->stat = GLP_NS; } /* process fixed column */ npp_fixed_col(npp, q); return 0; } static int rcv_empty_col(NPP *npp, void *_info) { /* recover empty column */ struct empty_col *info = _info; if (npp->sol == GLP_SOL) npp->c_stat[info->q] = info->stat; return 0; } /*********************************************************************** * NAME * * npp_implied_value - process implied column value * * SYNOPSIS * * #include "glpnpp.h" * int npp_implied_value(NPP *npp, NPPCOL *q, double s); * * DESCRIPTION * * For column q: * * l[q] <= x[q] <= u[q], (1) * * where l[q] < u[q], the routine npp_implied_value processes its * implied value s[q]. If this implied value satisfies to the current * column bounds and integrality condition, the routine fixes column q * at the given point. Note that the column is kept in the problem in * any case. * * RETURNS * * 0 - column has been fixed; * * 1 - implied value violates to current column bounds; * * 2 - implied value violates integrality condition. * * ALGORITHM * * Implied column value s[q] satisfies to the current column bounds if * the following condition holds: * * l[q] - eps <= s[q] <= u[q] + eps, (2) * * where eps is an absolute tolerance for column value. If the column * is integral, the following condition also must hold: * * |s[q] - floor(s[q]+0.5)| <= eps, (3) * * where floor(s[q]+0.5) is the nearest integer to s[q]. * * If both condition (2) and (3) are satisfied, the column can be fixed * at the value s[q], or, if it is integral, at floor(s[q]+0.5). * Otherwise, if s[q] violates (2) or (3), the problem has no feasible * solution. * * Note: If s[q] is close to l[q] or u[q], it seems to be reasonable to * fix the column at its lower or upper bound, resp. rather than at the * implied value. */ int npp_implied_value(NPP *npp, NPPCOL *q, double s) { /* process implied column value */ double eps, nint; xassert(npp == npp); /* column must not be fixed */ xassert(q->lb < q->ub); /* check integrality */ if (q->is_int) { nint = floor(s + 0.5); if (fabs(s - nint) <= 1e-5) s = nint; else return 2; } /* check current column lower bound */ if (q->lb != -DBL_MAX) { eps = (q->is_int ? 1e-5 : 1e-5 + 1e-8 * fabs(q->lb)); if (s < q->lb - eps) return 1; /* if s[q] is close to l[q], fix column at its lower bound rather than at the implied value */ if (s < q->lb + 1e-3 * eps) { q->ub = q->lb; return 0; } } /* check current column upper bound */ if (q->ub != +DBL_MAX) { eps = (q->is_int ? 1e-5 : 1e-5 + 1e-8 * fabs(q->ub)); if (s > q->ub + eps) return 1; /* if s[q] is close to u[q], fix column at its upper bound rather than at the implied value */ if (s > q->ub - 1e-3 * eps) { q->lb = q->ub; return 0; } } /* fix column at the implied value */ q->lb = q->ub = s; return 0; } /*********************************************************************** * NAME * * npp_eq_singlet - process row singleton (equality constraint) * * SYNOPSIS * * #include "glpnpp.h" * int npp_eq_singlet(NPP *npp, NPPROW *p); * * DESCRIPTION * * The routine npp_eq_singlet processes row p, which is equiality * constraint having the only non-zero coefficient: * * a[p,q] x[q] = b. (1) * * RETURNS * * 0 - success; * * 1 - problem has no primal feasible solution; * * 2 - problem has no integer feasible solution. * * PROBLEM TRANSFORMATION * * The equality constraint defines implied value of column q: * * x[q] = s[q] = b / a[p,q]. (2) * * If the implied value s[q] satisfies to the column bounds (see the * routine npp_implied_value), the column can be fixed at s[q] and * removed from the problem. In this case row p becomes redundant, so * it can be replaced by equivalent free row and also removed from the * problem. * * Note that the routine removes from the problem only row p. Column q * becomes fixed, however, it is kept in the problem. * * RECOVERING BASIC SOLUTION * * In solution to the original problem row p is assigned status GLP_NS * (active equality constraint), and column q is assigned status GLP_BS * (basic column). * * Multiplier for row p can be computed as follows. In the dual system * of the original problem column q corresponds to the following row: * * sum a[i,q] pi[i] + lambda[q] = c[q] ==> * i * * sum a[i,q] pi[i] + a[p,q] pi[p] + lambda[q] = c[q]. * i!=p * * Therefore: * * 1 * pi[p] = ------ (c[q] - lambda[q] - sum a[i,q] pi[i]), (3) * a[p,q] i!=q * * where lambda[q] = 0 (since column[q] is basic), and pi[i] for all * i != p are known in solution to the transformed problem. * * Value of column q in solution to the original problem is assigned * its implied value s[q]. * * RECOVERING INTERIOR-POINT SOLUTION * * Multiplier for row p is computed with formula (3). Value of column * q is assigned its implied value s[q]. * * RECOVERING MIP SOLUTION * * Value of column q is assigned its implied value s[q]. */ struct eq_singlet { /* row singleton (equality constraint) */ int p; /* row reference number */ int q; /* column reference number */ double apq; /* constraint coefficient a[p,q] */ double c; /* objective coefficient at x[q] */ NPPLFE *ptr; /* list of non-zero coefficients a[i,q], i != p */ }; static int rcv_eq_singlet(NPP *npp, void *info); int npp_eq_singlet(NPP *npp, NPPROW *p) { /* process row singleton (equality constraint) */ struct eq_singlet *info; NPPCOL *q; NPPAIJ *aij; NPPLFE *lfe; int ret; double s; /* the row must be singleton equality constraint */ xassert(p->lb == p->ub); xassert(p->ptr != NULL && p->ptr->r_next == NULL); /* compute and process implied column value */ aij = p->ptr; q = aij->col; s = p->lb / aij->val; ret = npp_implied_value(npp, q, s); xassert(0 <= ret && ret <= 2); if (ret != 0) return ret; /* create transformation stack entry */ info = npp_push_tse(npp, rcv_eq_singlet, sizeof(struct eq_singlet)); info->p = p->i; info->q = q->j; info->apq = aij->val; info->c = q->coef; info->ptr = NULL; /* save column coefficients a[i,q], i != p (not needed for MIP solution) */ if (npp->sol != GLP_MIP) { for (aij = q->ptr; aij != NULL; aij = aij->c_next) { if (aij->row == p) continue; /* skip a[p,q] */ lfe = dmp_get_atom(npp->stack, sizeof(NPPLFE)); lfe->ref = aij->row->i; lfe->val = aij->val; lfe->next = info->ptr; info->ptr = lfe; } } /* remove the row from the problem */ npp_del_row(npp, p); return 0; } static int rcv_eq_singlet(NPP *npp, void *_info) { /* recover row singleton (equality constraint) */ struct eq_singlet *info = _info; NPPLFE *lfe; double temp; if (npp->sol == GLP_SOL) { /* column q must be already recovered as GLP_NS */ if (npp->c_stat[info->q] != GLP_NS) { npp_error(); return 1; } npp->r_stat[info->p] = GLP_NS; npp->c_stat[info->q] = GLP_BS; } if (npp->sol != GLP_MIP) { /* compute multiplier for row p with formula (3) */ temp = info->c; for (lfe = info->ptr; lfe != NULL; lfe = lfe->next) temp -= lfe->val * npp->r_pi[lfe->ref]; npp->r_pi[info->p] = temp / info->apq; } return 0; } /*********************************************************************** * NAME * * npp_implied_lower - process implied column lower bound * * SYNOPSIS * * #include "glpnpp.h" * int npp_implied_lower(NPP *npp, NPPCOL *q, double l); * * DESCRIPTION * * For column q: * * l[q] <= x[q] <= u[q], (1) * * where l[q] < u[q], the routine npp_implied_lower processes its * implied lower bound l'[q]. As the result the current column lower * bound may increase. Note that the column is kept in the problem in * any case. * * RETURNS * * 0 - current column lower bound has not changed; * * 1 - current column lower bound has changed, but not significantly; * * 2 - current column lower bound has significantly changed; * * 3 - column has been fixed on its upper bound; * * 4 - implied lower bound violates current column upper bound. * * ALGORITHM * * If column q is integral, before processing its implied lower bound * should be rounded up: * * ( floor(l'[q]+0.5), if |l'[q] - floor(l'[q]+0.5)| <= eps * l'[q] := < (2) * ( ceil(l'[q]), otherwise * * where floor(l'[q]+0.5) is the nearest integer to l'[q], ceil(l'[q]) * is smallest integer not less than l'[q], and eps is an absolute * tolerance for column value. * * Processing implied column lower bound l'[q] includes the following * cases: * * 1) if l'[q] < l[q] + eps, implied lower bound is redundant; * * 2) if l[q] + eps <= l[q] <= u[q] + eps, current column lower bound * l[q] can be strengthened by replacing it with l'[q]. If in this * case new column lower bound becomes close to current column upper * bound u[q], the column can be fixed on its upper bound; * * 3) if l'[q] > u[q] + eps, implied lower bound violates current * column upper bound u[q], in which case the problem has no primal * feasible solution. */ int npp_implied_lower(NPP *npp, NPPCOL *q, double l) { /* process implied column lower bound */ int ret; double eps, nint; xassert(npp == npp); /* column must not be fixed */ xassert(q->lb < q->ub); /* implied lower bound must be finite */ xassert(l != -DBL_MAX); /* if column is integral, round up l'[q] */ if (q->is_int) { nint = floor(l + 0.5); if (fabs(l - nint) <= 1e-5) l = nint; else l = ceil(l); } /* check current column lower bound */ if (q->lb != -DBL_MAX) { eps = (q->is_int ? 1e-3 : 1e-3 + 1e-6 * fabs(q->lb)); if (l < q->lb + eps) { ret = 0; /* redundant */ goto done; } } /* check current column upper bound */ if (q->ub != +DBL_MAX) { eps = (q->is_int ? 1e-5 : 1e-5 + 1e-8 * fabs(q->ub)); if (l > q->ub + eps) { ret = 4; /* infeasible */ goto done; } /* if l'[q] is close to u[q], fix column at its upper bound */ if (l > q->ub - 1e-3 * eps) { q->lb = q->ub; ret = 3; /* fixed */ goto done; } } /* check if column lower bound changes significantly */ if (q->lb == -DBL_MAX) ret = 2; /* significantly */ else if (q->is_int && l > q->lb + 0.5) ret = 2; /* significantly */ else if (l > q->lb + 0.30 * (1.0 + fabs(q->lb))) ret = 2; /* significantly */ else ret = 1; /* not significantly */ /* set new column lower bound */ q->lb = l; done: return ret; } /*********************************************************************** * NAME * * npp_implied_upper - process implied column upper bound * * SYNOPSIS * * #include "glpnpp.h" * int npp_implied_upper(NPP *npp, NPPCOL *q, double u); * * DESCRIPTION * * For column q: * * l[q] <= x[q] <= u[q], (1) * * where l[q] < u[q], the routine npp_implied_upper processes its * implied upper bound u'[q]. As the result the current column upper * bound may decrease. Note that the column is kept in the problem in * any case. * * RETURNS * * 0 - current column upper bound has not changed; * * 1 - current column upper bound has changed, but not significantly; * * 2 - current column upper bound has significantly changed; * * 3 - column has been fixed on its lower bound; * * 4 - implied upper bound violates current column lower bound. * * ALGORITHM * * If column q is integral, before processing its implied upper bound * should be rounded down: * * ( floor(u'[q]+0.5), if |u'[q] - floor(l'[q]+0.5)| <= eps * u'[q] := < (2) * ( floor(l'[q]), otherwise * * where floor(u'[q]+0.5) is the nearest integer to u'[q], * floor(u'[q]) is largest integer not greater than u'[q], and eps is * an absolute tolerance for column value. * * Processing implied column upper bound u'[q] includes the following * cases: * * 1) if u'[q] > u[q] - eps, implied upper bound is redundant; * * 2) if l[q] - eps <= u[q] <= u[q] - eps, current column upper bound * u[q] can be strengthened by replacing it with u'[q]. If in this * case new column upper bound becomes close to current column lower * bound, the column can be fixed on its lower bound; * * 3) if u'[q] < l[q] - eps, implied upper bound violates current * column lower bound l[q], in which case the problem has no primal * feasible solution. */ int npp_implied_upper(NPP *npp, NPPCOL *q, double u) { int ret; double eps, nint; xassert(npp == npp); /* column must not be fixed */ xassert(q->lb < q->ub); /* implied upper bound must be finite */ xassert(u != +DBL_MAX); /* if column is integral, round down u'[q] */ if (q->is_int) { nint = floor(u + 0.5); if (fabs(u - nint) <= 1e-5) u = nint; else u = floor(u); } /* check current column upper bound */ if (q->ub != +DBL_MAX) { eps = (q->is_int ? 1e-3 : 1e-3 + 1e-6 * fabs(q->ub)); if (u > q->ub - eps) { ret = 0; /* redundant */ goto done; } } /* check current column lower bound */ if (q->lb != -DBL_MAX) { eps = (q->is_int ? 1e-5 : 1e-5 + 1e-8 * fabs(q->lb)); if (u < q->lb - eps) { ret = 4; /* infeasible */ goto done; } /* if u'[q] is close to l[q], fix column at its lower bound */ if (u < q->lb + 1e-3 * eps) { q->ub = q->lb; ret = 3; /* fixed */ goto done; } } /* check if column upper bound changes significantly */ if (q->ub == +DBL_MAX) ret = 2; /* significantly */ else if (q->is_int && u < q->ub - 0.5) ret = 2; /* significantly */ else if (u < q->ub - 0.30 * (1.0 + fabs(q->ub))) ret = 2; /* significantly */ else ret = 1; /* not significantly */ /* set new column upper bound */ q->ub = u; done: return ret; } /*********************************************************************** * NAME * * npp_ineq_singlet - process row singleton (inequality constraint) * * SYNOPSIS * * #include "glpnpp.h" * int npp_ineq_singlet(NPP *npp, NPPROW *p); * * DESCRIPTION * * The routine npp_ineq_singlet processes row p, which is inequality * constraint having the only non-zero coefficient: * * L[p] <= a[p,q] * x[q] <= U[p], (1) * * where L[p] < U[p], L[p] > -oo and/or U[p] < +oo. * * RETURNS * * 0 - current column bounds have not changed; * * 1 - current column bounds have changed, but not significantly; * * 2 - current column bounds have significantly changed; * * 3 - column has been fixed on its lower or upper bound; * * 4 - problem has no primal feasible solution. * * PROBLEM TRANSFORMATION * * Inequality constraint (1) defines implied bounds of column q: * * ( L[p] / a[p,q], if a[p,q] > 0 * l'[q] = < (2) * ( U[p] / a[p,q], if a[p,q] < 0 * * ( U[p] / a[p,q], if a[p,q] > 0 * u'[q] = < (3) * ( L[p] / a[p,q], if a[p,q] < 0 * * If these implied bounds do not violate current bounds of column q: * * l[q] <= x[q] <= u[q], (4) * * they can be used to strengthen the current column bounds: * * l[q] := max(l[q], l'[q]), (5) * * u[q] := min(u[q], u'[q]). (6) * * (See the routines npp_implied_lower and npp_implied_upper.) * * Once bounds of row p (1) have been carried over column q, the row * becomes redundant, so it can be replaced by equivalent free row and * removed from the problem. * * Note that the routine removes from the problem only row p. Column q, * even it has been fixed, is kept in the problem. * * RECOVERING BASIC SOLUTION * * Note that the row in the dual system corresponding to column q is * the following: * * sum a[i,q] pi[i] + lambda[q] = c[q] ==> * i * (7) * sum a[i,q] pi[i] + a[p,q] pi[p] + lambda[q] = c[q], * i!=p * * where pi[i] for all i != p are known in solution to the transformed * problem. Row p does not exist in the transformed problem, so it has * zero multiplier there. This allows computing multiplier for column q * in solution to the transformed problem: * * lambda~[q] = c[q] - sum a[i,q] pi[i]. (8) * i!=p * * Let in solution to the transformed problem column q be non-basic * with lower bound active (GLP_NL, lambda~[q] >= 0), and this lower * bound be implied one l'[q]. From the original problem's standpoint * this then means that actually the original column lower bound l[q] * is inactive, and active is that row bound L[p] or U[p] that defines * the implied bound l'[q] (2). In this case in solution to the * original problem column q is assigned status GLP_BS while row p is * assigned status GLP_NL (if a[p,q] > 0) or GLP_NU (if a[p,q] < 0). * Since now column q is basic, its multiplier lambda[q] is zero. This * allows using (7) and (8) to find multiplier for row p in solution to * the original problem: * * 1 * pi[p] = ------ (c[q] - sum a[i,q] pi[i]) = lambda~[q] / a[p,q] (9) * a[p,q] i!=p * * Now let in solution to the transformed problem column q be non-basic * with upper bound active (GLP_NU, lambda~[q] <= 0), and this upper * bound be implied one u'[q]. As in the previous case this then means * that from the original problem's standpoint actually the original * column upper bound u[q] is inactive, and active is that row bound * L[p] or U[p] that defines the implied bound u'[q] (3). In this case * in solution to the original problem column q is assigned status * GLP_BS, row p is assigned status GLP_NU (if a[p,q] > 0) or GLP_NL * (if a[p,q] < 0), and its multiplier is computed with formula (9). * * Strengthening bounds of column q according to (5) and (6) may make * it fixed. Thus, if in solution to the transformed problem column q is * non-basic and fixed (GLP_NS), we can suppose that if lambda~[q] > 0, * column q has active lower bound (GLP_NL), and if lambda~[q] < 0, * column q has active upper bound (GLP_NU), reducing this case to two * previous ones. If, however, lambda~[q] is close to zero or * corresponding bound of row p does not exist (this may happen if * lambda~[q] has wrong sign due to round-off errors, in which case it * is expected to be close to zero, since solution is assumed to be dual * feasible), column q can be assigned status GLP_BS (basic), and row p * can be made active on its existing bound. In the latter case row * multiplier pi[p] computed with formula (9) will be also close to * zero, and dual feasibility will be kept. * * In all other cases, namely, if in solution to the transformed * problem column q is basic (GLP_BS), or non-basic with original lower * bound l[q] active (GLP_NL), or non-basic with original upper bound * u[q] active (GLP_NU), constraint (1) is inactive. So in solution to * the original problem status of column q remains unchanged, row p is * assigned status GLP_BS, and its multiplier pi[p] is assigned zero * value. * * RECOVERING INTERIOR-POINT SOLUTION * * First, value of multiplier for column q in solution to the original * problem is computed with formula (8). If lambda~[q] > 0 and column q * has implied lower bound, or if lambda~[q] < 0 and column q has * implied upper bound, this means that from the original problem's * standpoint actually row p has corresponding active bound, in which * case its multiplier pi[p] is computed with formula (9). In other * cases, when the sign of lambda~[q] corresponds to original bound of * column q, or when lambda~[q] =~ 0, value of row multiplier pi[p] is * assigned zero value. * * RECOVERING MIP SOLUTION * * None needed. */ struct ineq_singlet { /* row singleton (inequality constraint) */ int p; /* row reference number */ int q; /* column reference number */ double apq; /* constraint coefficient a[p,q] */ double c; /* objective coefficient at x[q] */ double lb; /* row lower bound */ double ub; /* row upper bound */ char lb_changed; /* this flag is set if column lower bound was changed */ char ub_changed; /* this flag is set if column upper bound was changed */ NPPLFE *ptr; /* list of non-zero coefficients a[i,q], i != p */ }; static int rcv_ineq_singlet(NPP *npp, void *info); int npp_ineq_singlet(NPP *npp, NPPROW *p) { /* process row singleton (inequality constraint) */ struct ineq_singlet *info; NPPCOL *q; NPPAIJ *apq, *aij; NPPLFE *lfe; int lb_changed, ub_changed; double ll, uu; /* the row must be singleton inequality constraint */ xassert(p->lb != -DBL_MAX || p->ub != +DBL_MAX); xassert(p->lb < p->ub); xassert(p->ptr != NULL && p->ptr->r_next == NULL); /* compute implied column bounds */ apq = p->ptr; q = apq->col; xassert(q->lb < q->ub); if (apq->val > 0.0) { ll = (p->lb == -DBL_MAX ? -DBL_MAX : p->lb / apq->val); uu = (p->ub == +DBL_MAX ? +DBL_MAX : p->ub / apq->val); } else { ll = (p->ub == +DBL_MAX ? -DBL_MAX : p->ub / apq->val); uu = (p->lb == -DBL_MAX ? +DBL_MAX : p->lb / apq->val); } /* process implied column lower bound */ if (ll == -DBL_MAX) lb_changed = 0; else { lb_changed = npp_implied_lower(npp, q, ll); xassert(0 <= lb_changed && lb_changed <= 4); if (lb_changed == 4) return 4; /* infeasible */ } /* process implied column upper bound */ if (uu == +DBL_MAX) ub_changed = 0; else if (lb_changed == 3) { /* column was fixed on its upper bound due to l'[q] = u[q] */ /* note that L[p] < U[p], so l'[q] = u[q] < u'[q] */ ub_changed = 0; } else { ub_changed = npp_implied_upper(npp, q, uu); xassert(0 <= ub_changed && ub_changed <= 4); if (ub_changed == 4) return 4; /* infeasible */ } /* if neither lower nor upper column bound was changed, the row is originally redundant and can be replaced by free row */ if (!lb_changed && !ub_changed) { p->lb = -DBL_MAX, p->ub = +DBL_MAX; npp_free_row(npp, p); return 0; } /* create transformation stack entry */ info = npp_push_tse(npp, rcv_ineq_singlet, sizeof(struct ineq_singlet)); info->p = p->i; info->q = q->j; info->apq = apq->val; info->c = q->coef; info->lb = p->lb; info->ub = p->ub; info->lb_changed = (char)lb_changed; info->ub_changed = (char)ub_changed; info->ptr = NULL; /* save column coefficients a[i,q], i != p (not needed for MIP solution) */ if (npp->sol != GLP_MIP) { for (aij = q->ptr; aij != NULL; aij = aij->c_next) { if (aij == apq) continue; /* skip a[p,q] */ lfe = dmp_get_atom(npp->stack, sizeof(NPPLFE)); lfe->ref = aij->row->i; lfe->val = aij->val; lfe->next = info->ptr; info->ptr = lfe; } } /* remove the row from the problem */ npp_del_row(npp, p); return lb_changed >= ub_changed ? lb_changed : ub_changed; } static int rcv_ineq_singlet(NPP *npp, void *_info) { /* recover row singleton (inequality constraint) */ struct ineq_singlet *info = _info; NPPLFE *lfe; double lambda; if (npp->sol == GLP_MIP) goto done; /* compute lambda~[q] in solution to the transformed problem with formula (8) */ lambda = info->c; for (lfe = info->ptr; lfe != NULL; lfe = lfe->next) lambda -= lfe->val * npp->r_pi[lfe->ref]; if (npp->sol == GLP_SOL) { /* recover basic solution */ if (npp->c_stat[info->q] == GLP_BS) { /* column q is basic, so row p is inactive */ npp->r_stat[info->p] = GLP_BS; npp->r_pi[info->p] = 0.0; } else if (npp->c_stat[info->q] == GLP_NL) nl: { /* column q is non-basic with lower bound active */ if (info->lb_changed) { /* it is implied bound, so actually row p is active while column q is basic */ npp->r_stat[info->p] = (char)(info->apq > 0.0 ? GLP_NL : GLP_NU); npp->c_stat[info->q] = GLP_BS; npp->r_pi[info->p] = lambda / info->apq; } else { /* it is original bound, so row p is inactive */ npp->r_stat[info->p] = GLP_BS; npp->r_pi[info->p] = 0.0; } } else if (npp->c_stat[info->q] == GLP_NU) nu: { /* column q is non-basic with upper bound active */ if (info->ub_changed) { /* it is implied bound, so actually row p is active while column q is basic */ npp->r_stat[info->p] = (char)(info->apq > 0.0 ? GLP_NU : GLP_NL); npp->c_stat[info->q] = GLP_BS; npp->r_pi[info->p] = lambda / info->apq; } else { /* it is original bound, so row p is inactive */ npp->r_stat[info->p] = GLP_BS; npp->r_pi[info->p] = 0.0; } } else if (npp->c_stat[info->q] == GLP_NS) { /* column q is non-basic and fixed; note, however, that in in the original problem it is non-fixed */ if (lambda > +1e-7) { if (info->apq > 0.0 && info->lb != -DBL_MAX || info->apq < 0.0 && info->ub != +DBL_MAX || !info->lb_changed) { /* either corresponding bound of row p exists or column q remains non-basic with its original lower bound active */ npp->c_stat[info->q] = GLP_NL; goto nl; } } if (lambda < -1e-7) { if (info->apq > 0.0 && info->ub != +DBL_MAX || info->apq < 0.0 && info->lb != -DBL_MAX || !info->ub_changed) { /* either corresponding bound of row p exists or column q remains non-basic with its original upper bound active */ npp->c_stat[info->q] = GLP_NU; goto nu; } } /* either lambda~[q] is close to zero, or corresponding bound of row p does not exist, because lambda~[q] has wrong sign due to round-off errors; in the latter case lambda~[q] is also assumed to be close to zero; so, we can make row p active on its existing bound and column q basic; pi[p] will have wrong sign, but it also will be close to zero (rarus casus of dual degeneracy) */ if (info->lb != -DBL_MAX && info->ub == +DBL_MAX) { /* row lower bound exists, but upper bound doesn't */ npp->r_stat[info->p] = GLP_NL; } else if (info->lb == -DBL_MAX && info->ub != +DBL_MAX) { /* row upper bound exists, but lower bound doesn't */ npp->r_stat[info->p] = GLP_NU; } else if (info->lb != -DBL_MAX && info->ub != +DBL_MAX) { /* both row lower and upper bounds exist */ /* to choose proper active row bound we should not use lambda~[q], because its value being close to zero is unreliable; so we choose that bound which provides primal feasibility for original constraint (1) */ if (info->apq * npp->c_value[info->q] <= 0.5 * (info->lb + info->ub)) npp->r_stat[info->p] = GLP_NL; else npp->r_stat[info->p] = GLP_NU; } else { npp_error(); return 1; } npp->c_stat[info->q] = GLP_BS; npp->r_pi[info->p] = lambda / info->apq; } else { npp_error(); return 1; } } if (npp->sol == GLP_IPT) { /* recover interior-point solution */ if (lambda > +DBL_EPSILON && info->lb_changed || lambda < -DBL_EPSILON && info->ub_changed) { /* actually row p has corresponding active bound */ npp->r_pi[info->p] = lambda / info->apq; } else { /* either bounds of column q are both inactive or its original bound is active */ npp->r_pi[info->p] = 0.0; } } done: return 0; } /*********************************************************************** * NAME * * npp_implied_slack - process column singleton (implied slack variable) * * SYNOPSIS * * #include "glpnpp.h" * void npp_implied_slack(NPP *npp, NPPCOL *q); * * DESCRIPTION * * The routine npp_implied_slack processes column q: * * l[q] <= x[q] <= u[q], (1) * * where l[q] < u[q], having the only non-zero coefficient in row p, * which is equality constraint: * * sum a[p,j] x[j] + a[p,q] x[q] = b. (2) * j!=q * * PROBLEM TRANSFORMATION * * (If x[q] is integral, this transformation must not be used.) * * The term a[p,q] x[q] in constraint (2) can be considered as a slack * variable that allows to carry bounds of column q over row p and then * remove column q from the problem. * * Constraint (2) can be written as follows: * * sum a[p,j] x[j] = b - a[p,q] x[q]. (3) * j!=q * * According to (1) constraint (3) is equivalent to the following * inequality constraint: * * L[p] <= sum a[p,j] x[j] <= U[p], (4) * j!=q * * where * * ( b - a[p,q] u[q], if a[p,q] > 0 * L[p] = < (5) * ( b - a[p,q] l[q], if a[p,q] < 0 * * ( b - a[p,q] l[q], if a[p,q] > 0 * U[p] = < (6) * ( b - a[p,q] u[q], if a[p,q] < 0 * * From (2) it follows that: * * 1 * x[q] = ------ (b - sum a[p,j] x[j]). (7) * a[p,q] j!=q * * In order to eliminate x[q] from the objective row we substitute it * from (6) to that row: * * z = sum c[j] x[j] + c[q] x[q] + c[0] = * j!=q * 1 * = sum c[j] x[j] + c[q] [------ (b - sum a[p,j] x[j])] + c0 = * j!=q a[p,q] j!=q * * = sum c~[j] x[j] + c~[0], * j!=q * a[p,j] b * c~[j] = c[j] - c[q] ------, c~0 = c0 - c[q] ------ (8) * a[p,q] a[p,q] * * are values of objective coefficients and constant term, resp., in * the transformed problem. * * Note that column q is column singleton, so in the dual system of the * original problem it corresponds to the following row singleton: * * a[p,q] pi[p] + lambda[q] = c[q]. (9) * * In the transformed problem row (9) would be the following: * * a[p,q] pi~[p] + lambda[q] = c~[q] = 0. (10) * * Subtracting (10) from (9) we have: * * a[p,q] (pi[p] - pi~[p]) = c[q] * * that gives the following formula to compute multiplier for row p in * solution to the original problem using its value in solution to the * transformed problem: * * pi[p] = pi~[p] + c[q] / a[p,q]. (11) * * RECOVERING BASIC SOLUTION * * Status of column q in solution to the original problem is defined * by status of row p in solution to the transformed problem and the * sign of coefficient a[p,q] in the original inequality constraint (2) * as follows: * * +-----------------------+---------+--------------------+ * | Status of row p | Sign of | Status of column q | * | (transformed problem) | a[p,q] | (original problem) | * +-----------------------+---------+--------------------+ * | GLP_BS | + / - | GLP_BS | * | GLP_NL | + | GLP_NU | * | GLP_NL | - | GLP_NL | * | GLP_NU | + | GLP_NL | * | GLP_NU | - | GLP_NU | * | GLP_NF | + / - | GLP_NF | * +-----------------------+---------+--------------------+ * * Value of column q is computed with formula (7). Since originally row * p is equality constraint, its status is assigned GLP_NS, and value of * its multiplier pi[p] is computed with formula (11). * * RECOVERING INTERIOR-POINT SOLUTION * * Value of column q is computed with formula (7). Row multiplier value * pi[p] is computed with formula (11). * * RECOVERING MIP SOLUTION * * Value of column q is computed with formula (7). */ struct implied_slack { /* column singleton (implied slack variable) */ int p; /* row reference number */ int q; /* column reference number */ double apq; /* constraint coefficient a[p,q] */ double b; /* right-hand side of original equality constraint */ double c; /* original objective coefficient at x[q] */ NPPLFE *ptr; /* list of non-zero coefficients a[p,j], j != q */ }; static int rcv_implied_slack(NPP *npp, void *info); void npp_implied_slack(NPP *npp, NPPCOL *q) { /* process column singleton (implied slack variable) */ struct implied_slack *info; NPPROW *p; NPPAIJ *aij; NPPLFE *lfe; /* the column must be non-integral non-fixed singleton */ xassert(!q->is_int); xassert(q->lb < q->ub); xassert(q->ptr != NULL && q->ptr->c_next == NULL); /* corresponding row must be equality constraint */ aij = q->ptr; p = aij->row; xassert(p->lb == p->ub); /* create transformation stack entry */ info = npp_push_tse(npp, rcv_implied_slack, sizeof(struct implied_slack)); info->p = p->i; info->q = q->j; info->apq = aij->val; info->b = p->lb; info->c = q->coef; info->ptr = NULL; /* save row coefficients a[p,j], j != q, and substitute x[q] into the objective row */ for (aij = p->ptr; aij != NULL; aij = aij->r_next) { if (aij->col == q) continue; /* skip a[p,q] */ lfe = dmp_get_atom(npp->stack, sizeof(NPPLFE)); lfe->ref = aij->col->j; lfe->val = aij->val; lfe->next = info->ptr; info->ptr = lfe; aij->col->coef -= info->c * (aij->val / info->apq); } npp->c0 += info->c * (info->b / info->apq); /* compute new row bounds */ if (info->apq > 0.0) { p->lb = (q->ub == +DBL_MAX ? -DBL_MAX : info->b - info->apq * q->ub); p->ub = (q->lb == -DBL_MAX ? +DBL_MAX : info->b - info->apq * q->lb); } else { p->lb = (q->lb == -DBL_MAX ? -DBL_MAX : info->b - info->apq * q->lb); p->ub = (q->ub == +DBL_MAX ? +DBL_MAX : info->b - info->apq * q->ub); } /* remove the column from the problem */ npp_del_col(npp, q); return; } static int rcv_implied_slack(NPP *npp, void *_info) { /* recover column singleton (implied slack variable) */ struct implied_slack *info = _info; NPPLFE *lfe; double temp; if (npp->sol == GLP_SOL) { /* assign statuses to row p and column q */ if (npp->r_stat[info->p] == GLP_BS || npp->r_stat[info->p] == GLP_NF) npp->c_stat[info->q] = npp->r_stat[info->p]; else if (npp->r_stat[info->p] == GLP_NL) npp->c_stat[info->q] = (char)(info->apq > 0.0 ? GLP_NU : GLP_NL); else if (npp->r_stat[info->p] == GLP_NU) npp->c_stat[info->q] = (char)(info->apq > 0.0 ? GLP_NL : GLP_NU); else { npp_error(); return 1; } npp->r_stat[info->p] = GLP_NS; } if (npp->sol != GLP_MIP) { /* compute multiplier for row p */ npp->r_pi[info->p] += info->c / info->apq; } /* compute value of column q */ temp = info->b; for (lfe = info->ptr; lfe != NULL; lfe = lfe->next) temp -= lfe->val * npp->c_value[lfe->ref]; npp->c_value[info->q] = temp / info->apq; return 0; } /*********************************************************************** * NAME * * npp_implied_free - process column singleton (implied free variable) * * SYNOPSIS * * #include "glpnpp.h" * int npp_implied_free(NPP *npp, NPPCOL *q); * * DESCRIPTION * * The routine npp_implied_free processes column q: * * l[q] <= x[q] <= u[q], (1) * * having non-zero coefficient in the only row p, which is inequality * constraint: * * L[p] <= sum a[p,j] x[j] + a[p,q] x[q] <= U[p], (2) * j!=q * * where l[q] < u[q], L[p] < U[p], L[p] > -oo and/or U[p] < +oo. * * RETURNS * * 0 - success; * * 1 - column lower and/or upper bound(s) can be active; * * 2 - problem has no dual feasible solution. * * PROBLEM TRANSFORMATION * * Constraint (2) can be written as follows: * * L[p] - sum a[p,j] x[j] <= a[p,q] x[q] <= U[p] - sum a[p,j] x[j], * j!=q j!=q * * from which it follows that: * * alfa <= a[p,q] x[q] <= beta, (3) * * where * * alfa = inf(L[p] - sum a[p,j] x[j]) = * j!=q * * = L[p] - sup sum a[p,j] x[j] = (4) * j!=q * * = L[p] - sum a[p,j] u[j] - sum a[p,j] l[j], * j in Jp j in Jn * * beta = sup(L[p] - sum a[p,j] x[j]) = * j!=q * * = L[p] - inf sum a[p,j] x[j] = (5) * j!=q * * = L[p] - sum a[p,j] l[j] - sum a[p,j] u[j], * j in Jp j in Jn * * Jp = {j != q: a[p,j] > 0}, Jn = {j != q: a[p,j] < 0}. (6) * * Inequality (3) defines implied bounds of variable x[q]: * * l'[q] <= x[q] <= u'[q], (7) * * where * * ( alfa / a[p,q], if a[p,q] > 0 * l'[q] = < (8a) * ( beta / a[p,q], if a[p,q] < 0 * * ( beta / a[p,q], if a[p,q] > 0 * u'[q] = < (8b) * ( alfa / a[p,q], if a[p,q] < 0 * * Thus, if l'[q] > l[q] - eps and u'[q] < u[q] + eps, where eps is * an absolute tolerance for column value, column bounds (1) cannot be * active, in which case column q can be replaced by equivalent free * (unbounded) column. * * Note that column q is column singleton, so in the dual system of the * original problem it corresponds to the following row singleton: * * a[p,q] pi[p] + lambda[q] = c[q], (9) * * from which it follows that: * * pi[p] = (c[q] - lambda[q]) / a[p,q]. (10) * * Let x[q] be implied free (unbounded) variable. Then column q can be * only basic, so its multiplier lambda[q] is equal to zero, and from * (10) we have: * * pi[p] = c[q] / a[p,q]. (11) * * There are possible three cases: * * 1) pi[p] < -eps, where eps is an absolute tolerance for row * multiplier. In this case, to provide dual feasibility of the * original problem, row p must be active on its lower bound, and * if its lower bound does not exist (L[p] = -oo), the problem has * no dual feasible solution; * * 2) pi[p] > +eps. In this case row p must be active on its upper * bound, and if its upper bound does not exist (U[p] = +oo), the * problem has no dual feasible solution; * * 3) -eps <= pi[p] <= +eps. In this case any (either lower or upper) * bound of row p can be active, because this does not affect dual * feasibility. * * Thus, in all three cases original inequality constraint (2) can be * replaced by equality constraint, where the right-hand side is either * lower or upper bound of row p, and bounds of column q can be removed * that makes it free (unbounded). (May note that this transformation * can be followed by transformation "Column singleton (implied slack * variable)" performed by the routine npp_implied_slack.) * * RECOVERING BASIC SOLUTION * * Status of row p in solution to the original problem is determined * by its status in solution to the transformed problem and its bound, * which was choosen to be active: * * +-----------------------+--------+--------------------+ * | Status of row p | Active | Status of row p | * | (transformed problem) | bound | (original problem) | * +-----------------------+--------+--------------------+ * | GLP_BS | L[p] | GLP_BS | * | GLP_BS | U[p] | GLP_BS | * | GLP_NS | L[p] | GLP_NL | * | GLP_NS | U[p] | GLP_NU | * +-----------------------+--------+--------------------+ * * Value of row multiplier pi[p] (as well as value of column q) in * solution to the original problem is the same as in solution to the * transformed problem. * * RECOVERING INTERIOR-POINT SOLUTION * * Value of row multiplier pi[p] in solution to the original problem is * the same as in solution to the transformed problem. * * RECOVERING MIP SOLUTION * * None needed. */ struct implied_free { /* column singleton (implied free variable) */ int p; /* row reference number */ char stat; /* row status: GLP_NL - active constraint on lower bound GLP_NU - active constraint on upper bound */ }; static int rcv_implied_free(NPP *npp, void *info); int npp_implied_free(NPP *npp, NPPCOL *q) { /* process column singleton (implied free variable) */ struct implied_free *info; NPPROW *p; NPPAIJ *apq, *aij; double alfa, beta, l, u, pi, eps; /* the column must be non-fixed singleton */ xassert(q->lb < q->ub); xassert(q->ptr != NULL && q->ptr->c_next == NULL); /* corresponding row must be inequality constraint */ apq = q->ptr; p = apq->row; xassert(p->lb != -DBL_MAX || p->ub != +DBL_MAX); xassert(p->lb < p->ub); /* compute alfa */ alfa = p->lb; if (alfa != -DBL_MAX) { for (aij = p->ptr; aij != NULL; aij = aij->r_next) { if (aij == apq) continue; /* skip a[p,q] */ if (aij->val > 0.0) { if (aij->col->ub == +DBL_MAX) { alfa = -DBL_MAX; break; } alfa -= aij->val * aij->col->ub; } else /* < 0.0 */ { if (aij->col->lb == -DBL_MAX) { alfa = -DBL_MAX; break; } alfa -= aij->val * aij->col->lb; } } } /* compute beta */ beta = p->ub; if (beta != +DBL_MAX) { for (aij = p->ptr; aij != NULL; aij = aij->r_next) { if (aij == apq) continue; /* skip a[p,q] */ if (aij->val > 0.0) { if (aij->col->lb == -DBL_MAX) { beta = +DBL_MAX; break; } beta -= aij->val * aij->col->lb; } else /* < 0.0 */ { if (aij->col->ub == +DBL_MAX) { beta = +DBL_MAX; break; } beta -= aij->val * aij->col->ub; } } } /* compute implied column lower bound l'[q] */ if (apq->val > 0.0) l = (alfa == -DBL_MAX ? -DBL_MAX : alfa / apq->val); else /* < 0.0 */ l = (beta == +DBL_MAX ? -DBL_MAX : beta / apq->val); /* compute implied column upper bound u'[q] */ if (apq->val > 0.0) u = (beta == +DBL_MAX ? +DBL_MAX : beta / apq->val); else u = (alfa == -DBL_MAX ? +DBL_MAX : alfa / apq->val); /* check if column lower bound l[q] can be active */ if (q->lb != -DBL_MAX) { eps = 1e-9 + 1e-12 * fabs(q->lb); if (l < q->lb - eps) return 1; /* yes, it can */ } /* check if column upper bound u[q] can be active */ if (q->ub != +DBL_MAX) { eps = 1e-9 + 1e-12 * fabs(q->ub); if (u > q->ub + eps) return 1; /* yes, it can */ } /* okay; make column q free (unbounded) */ q->lb = -DBL_MAX, q->ub = +DBL_MAX; /* create transformation stack entry */ info = npp_push_tse(npp, rcv_implied_free, sizeof(struct implied_free)); info->p = p->i; info->stat = -1; /* compute row multiplier pi[p] */ pi = q->coef / apq->val; /* check dual feasibility for row p */ if (pi > +DBL_EPSILON) { /* lower bound L[p] must be active */ if (p->lb != -DBL_MAX) nl: { info->stat = GLP_NL; p->ub = p->lb; } else { if (pi > +1e-5) return 2; /* dual infeasibility */ /* take a chance on U[p] */ xassert(p->ub != +DBL_MAX); goto nu; } } else if (pi < -DBL_EPSILON) { /* upper bound U[p] must be active */ if (p->ub != +DBL_MAX) nu: { info->stat = GLP_NU; p->lb = p->ub; } else { if (pi < -1e-5) return 2; /* dual infeasibility */ /* take a chance on L[p] */ xassert(p->lb != -DBL_MAX); goto nl; } } else { /* any bound (either L[p] or U[p]) can be made active */ if (p->ub == +DBL_MAX) { xassert(p->lb != -DBL_MAX); goto nl; } if (p->lb == -DBL_MAX) { xassert(p->ub != +DBL_MAX); goto nu; } if (fabs(p->lb) <= fabs(p->ub)) goto nl; else goto nu; } return 0; } static int rcv_implied_free(NPP *npp, void *_info) { /* recover column singleton (implied free variable) */ struct implied_free *info = _info; if (npp->sol == GLP_SOL) { if (npp->r_stat[info->p] == GLP_BS) npp->r_stat[info->p] = GLP_BS; else if (npp->r_stat[info->p] == GLP_NS) { xassert(info->stat == GLP_NL || info->stat == GLP_NU); npp->r_stat[info->p] = info->stat; } else { npp_error(); return 1; } } return 0; } /*********************************************************************** * NAME * * npp_eq_doublet - process row doubleton (equality constraint) * * SYNOPSIS * * #include "glpnpp.h" * NPPCOL *npp_eq_doublet(NPP *npp, NPPROW *p); * * DESCRIPTION * * The routine npp_eq_doublet processes row p, which is equality * constraint having exactly two non-zero coefficients: * * a[p,q] x[q] + a[p,r] x[r] = b. (1) * * As the result of processing one of columns q or r is eliminated from * all other rows and, thus, becomes column singleton of type "implied * slack variable". Row p is not changed and along with column q and r * remains in the problem. * * RETURNS * * The routine npp_eq_doublet returns pointer to the descriptor of that * column q or r which has been eliminated. If, due to some reason, the * elimination was not performed, the routine returns NULL. * * PROBLEM TRANSFORMATION * * First, we decide which column q or r will be eliminated. Let it be * column q. Consider i-th constraint row, where column q has non-zero * coefficient a[i,q] != 0: * * L[i] <= sum a[i,j] x[j] <= U[i]. (2) * j * * In order to eliminate column q from row (2) we subtract from it row * (1) multiplied by gamma[i] = a[i,q] / a[p,q], i.e. we replace in the * transformed problem row (2) by its linear combination with row (1). * This transformation changes only coefficients in columns q and r, * and bounds of row i as follows: * * a~[i,q] = a[i,q] - gamma[i] a[p,q] = 0, (3) * * a~[i,r] = a[i,r] - gamma[i] a[p,r], (4) * * L~[i] = L[i] - gamma[i] b, (5) * * U~[i] = U[i] - gamma[i] b. (6) * * RECOVERING BASIC SOLUTION * * The transformation of the primal system of the original problem: * * L <= A x <= U (7) * * is equivalent to multiplying from the left a transformation matrix F * by components of this primal system, which in the transformed problem * becomes the following: * * F L <= F A x <= F U ==> L~ <= A~x <= U~. (8) * * The matrix F has the following structure: * * ( 1 -gamma[1] ) * ( ) * ( 1 -gamma[2] ) * ( ) * ( ... ... ) * ( ) * F = ( 1 -gamma[p-1] ) (9) * ( ) * ( 1 ) * ( ) * ( -gamma[p+1] 1 ) * ( ) * ( ... ... ) * * where its column containing elements -gamma[i] corresponds to row p * of the primal system. * * From (8) it follows that the dual system of the original problem: * * A'pi + lambda = c, (10) * * in the transformed problem becomes the following: * * A'F'inv(F')pi + lambda = c ==> (A~)'pi~ + lambda = c, (11) * * where: * * pi~ = inv(F')pi (12) * * is the vector of row multipliers in the transformed problem. Thus: * * pi = F'pi~. (13) * * Therefore, as it follows from (13), value of multiplier for row p in * solution to the original problem can be computed as follows: * * pi[p] = pi~[p] - sum gamma[i] pi~[i], (14) * i * * where pi~[i] = pi[i] is multiplier for row i (i != p). * * Note that the statuses of all rows and columns are not changed. * * RECOVERING INTERIOR-POINT SOLUTION * * Multiplier for row p in solution to the original problem is computed * with formula (14). * * RECOVERING MIP SOLUTION * * None needed. */ struct eq_doublet { /* row doubleton (equality constraint) */ int p; /* row reference number */ double apq; /* constraint coefficient a[p,q] */ NPPLFE *ptr; /* list of non-zero coefficients a[i,q], i != p */ }; static int rcv_eq_doublet(NPP *npp, void *info); NPPCOL *npp_eq_doublet(NPP *npp, NPPROW *p) { /* process row doubleton (equality constraint) */ struct eq_doublet *info; NPPROW *i; NPPCOL *q, *r; NPPAIJ *apq, *apr, *aiq, *air, *next; NPPLFE *lfe; double gamma; /* the row must be doubleton equality constraint */ xassert(p->lb == p->ub); xassert(p->ptr != NULL && p->ptr->r_next != NULL && p->ptr->r_next->r_next == NULL); /* choose column to be eliminated */ { NPPAIJ *a1, *a2; a1 = p->ptr, a2 = a1->r_next; if (fabs(a2->val) < 0.001 * fabs(a1->val)) { /* only first column can be eliminated, because second one has too small constraint coefficient */ apq = a1, apr = a2; } else if (fabs(a1->val) < 0.001 * fabs(a2->val)) { /* only second column can be eliminated, because first one has too small constraint coefficient */ apq = a2, apr = a1; } else { /* both columns are appropriate; choose that one which is shorter to minimize fill-in */ if (npp_col_nnz(npp, a1->col) <= npp_col_nnz(npp, a2->col)) { /* first column is shorter */ apq = a1, apr = a2; } else { /* second column is shorter */ apq = a2, apr = a1; } } } /* now columns q and r have been chosen */ q = apq->col, r = apr->col; /* create transformation stack entry */ info = npp_push_tse(npp, rcv_eq_doublet, sizeof(struct eq_doublet)); info->p = p->i; info->apq = apq->val; info->ptr = NULL; /* transform each row i (i != p), where a[i,q] != 0, to eliminate column q */ for (aiq = q->ptr; aiq != NULL; aiq = next) { next = aiq->c_next; if (aiq == apq) continue; /* skip row p */ i = aiq->row; /* row i to be transformed */ /* save constraint coefficient a[i,q] */ if (npp->sol != GLP_MIP) { lfe = dmp_get_atom(npp->stack, sizeof(NPPLFE)); lfe->ref = i->i; lfe->val = aiq->val; lfe->next = info->ptr; info->ptr = lfe; } /* find coefficient a[i,r] in row i */ for (air = i->ptr; air != NULL; air = air->r_next) if (air->col == r) break; /* if a[i,r] does not exist, create a[i,r] = 0 */ if (air == NULL) air = npp_add_aij(npp, i, r, 0.0); /* compute gamma[i] = a[i,q] / a[p,q] */ gamma = aiq->val / apq->val; /* (row i) := (row i) - gamma[i] * (row p); see (3)-(6) */ /* new a[i,q] is exact zero due to elimnation; remove it from row i */ npp_del_aij(npp, aiq); /* compute new a[i,r] */ air->val -= gamma * apr->val; /* if new a[i,r] is close to zero due to numeric cancelation, remove it from row i */ if (fabs(air->val) <= 1e-10) npp_del_aij(npp, air); /* compute new lower and upper bounds of row i */ if (i->lb == i->ub) i->lb = i->ub = (i->lb - gamma * p->lb); else { if (i->lb != -DBL_MAX) i->lb -= gamma * p->lb; if (i->ub != +DBL_MAX) i->ub -= gamma * p->lb; } } return q; } static int rcv_eq_doublet(NPP *npp, void *_info) { /* recover row doubleton (equality constraint) */ struct eq_doublet *info = _info; NPPLFE *lfe; double gamma, temp; /* we assume that processing row p is followed by processing column q as singleton of type "implied slack variable", in which case row p must always be active equality constraint */ if (npp->sol == GLP_SOL) { if (npp->r_stat[info->p] != GLP_NS) { npp_error(); return 1; } } if (npp->sol != GLP_MIP) { /* compute value of multiplier for row p; see (14) */ temp = npp->r_pi[info->p]; for (lfe = info->ptr; lfe != NULL; lfe = lfe->next) { gamma = lfe->val / info->apq; /* a[i,q] / a[p,q] */ temp -= gamma * npp->r_pi[lfe->ref]; } npp->r_pi[info->p] = temp; } return 0; } /*********************************************************************** * NAME * * npp_forcing_row - process forcing row * * SYNOPSIS * * #include "glpnpp.h" * int npp_forcing_row(NPP *npp, NPPROW *p, int at); * * DESCRIPTION * * The routine npp_forcing row processes row p of general format: * * L[p] <= sum a[p,j] x[j] <= U[p], (1) * j * * l[j] <= x[j] <= u[j], (2) * * where L[p] <= U[p] and l[j] < u[j] for all a[p,j] != 0. It is also * assumed that: * * 1) if at = 0 then |L[p] - U'[p]| <= eps, where U'[p] is implied * row upper bound (see below), eps is an absolute tolerance for row * value; * * 2) if at = 1 then |U[p] - L'[p]| <= eps, where L'[p] is implied * row lower bound (see below). * * RETURNS * * 0 - success; * * 1 - cannot fix columns due to too small constraint coefficients. * * PROBLEM TRANSFORMATION * * Implied lower and upper bounds of row (1) are determined by bounds * of corresponding columns (variables) as follows: * * L'[p] = inf sum a[p,j] x[j] = * j * (3) * = sum a[p,j] l[j] + sum a[p,j] u[j], * j in Jp j in Jn * * U'[p] = sup sum a[p,j] x[j] = * (4) * = sum a[p,j] u[j] + sum a[p,j] l[j], * j in Jp j in Jn * * Jp = {j: a[p,j] > 0}, Jn = {j: a[p,j] < 0}. (5) * * If L[p] =~ U'[p] (at = 0), solution can be primal feasible only when * all variables take their boundary values as defined by (4): * * ( u[j], if j in Jp * x[j] = < (6) * ( l[j], if j in Jn * * Similarly, if U[p] =~ L'[p] (at = 1), solution can be primal feasible * only when all variables take their boundary values as defined by (3): * * ( l[j], if j in Jp * x[j] = < (7) * ( u[j], if j in Jn * * Condition (6) or (7) allows fixing all columns (variables x[j]) * in row (1) on their bounds and then removing them from the problem * (see the routine npp_fixed_col). Due to this row p becomes redundant, * so it can be replaced by equivalent free (unbounded) row and also * removed from the problem (see the routine npp_free_row). * * 1. To apply this transformation row (1) should not have coefficients * whose magnitude is too small, i.e. all a[p,j] should satisfy to * the following condition: * * |a[p,j]| >= eps * max(1, |a[p,k]|), (8) * k * where eps is a relative tolerance for constraint coefficients. * Otherwise, fixing columns may be numerically unreliable and may * lead to wrong solution. * * 2. The routine fixes columns and remove bounds of row p, however, * it does not remove the row and columns from the problem. * * RECOVERING BASIC SOLUTION * * In the transformed problem row p being inactive constraint is * assigned status GLP_BS (as the result of transformation of free * row), and all columns in this row are assigned status GLP_NS (as the * result of transformation of fixed columns). * * Note that in the dual system of the transformed (as well as original) * problem every column j in row p corresponds to the following row: * * sum a[i,j] pi[i] + a[p,j] pi[p] + lambda[j] = c[j], (9) * i!=p * * from which it follows that: * * lambda[j] = c[j] - sum a[i,j] pi[i] - a[p,j] pi[p]. (10) * i!=p * * In the transformed problem values of all multipliers pi[i] are known * (including pi[i], whose value is zero, since row p is inactive). * Thus, using formula (10) it is possible to compute values of * multipliers lambda[j] for all columns in row p. * * Note also that in the original problem all columns in row p are * bounded, not fixed. So status GLP_NS assigned to every such column * must be changed to GLP_NL or GLP_NU depending on which bound the * corresponding column has been fixed. This status change may lead to * dual feasibility violation for solution of the original problem, * because now column multipliers must satisfy to the following * condition: * * ( >= 0, if status of column j is GLP_NL, * lambda[j] < (11) * ( <= 0, if status of column j is GLP_NU. * * If this condition holds, solution to the original problem is the * same as to the transformed problem. Otherwise, we have to perform * one degenerate pivoting step of the primal simplex method to obtain * dual feasible (hence, optimal) solution to the original problem as * follows. If, on problem transformation, row p was made active on its * lower bound (case at = 0), we change its status to GLP_NL (or GLP_NS) * and start increasing its multiplier pi[p]. Otherwise, if row p was * made active on its upper bound (case at = 1), we change its status * to GLP_NU (or GLP_NS) and start decreasing pi[p]. From (10) it * follows that: * * delta lambda[j] = - a[p,j] * delta pi[p] = - a[p,j] pi[p]. (12) * * Simple analysis of formulae (3)-(5) shows that changing pi[p] in the * specified direction causes increasing lambda[j] for every column j * assigned status GLP_NL (delta lambda[j] > 0) and decreasing lambda[j] * for every column j assigned status GLP_NU (delta lambda[j] < 0). It * is understood that once the last lambda[q], which violates condition * (11), has reached zero, multipliers lambda[j] for all columns get * valid signs. Such column q can be determined as follows. Let d[j] be * initial value of lambda[j] (i.e. reduced cost of column j) in the * transformed problem computed with formula (10) when pi[p] = 0. Then * lambda[j] = d[j] + delta lambda[j], and from (12) it follows that * lambda[j] becomes zero if: * * delta lambda[j] = - a[p,j] pi[p] = - d[j] ==> * (13) * pi[p] = d[j] / a[p,j]. * * Therefore, the last column q, for which lambda[q] becomes zero, can * be determined from the following condition: * * |d[q] / a[p,q]| = max |pi[p]| = max |d[j] / a[p,j]|, (14) * j in D j in D * * where D is a set of columns j whose, reduced costs d[j] have invalid * signs, i.e. violate condition (11). (Thus, if D is empty, solution * to the original problem is the same as solution to the transformed * problem, and no correction is needed as was noticed above.) In * solution to the original problem column q is assigned status GLP_BS, * since it replaces column of auxiliary variable of row p (becoming * active) in the basis, and multiplier for row p is assigned its new * value, which is pi[p] = d[q] / a[p,q]. Note that due to primal * degeneracy values of all columns having non-zero coefficients in row * p remain unchanged. * * RECOVERING INTERIOR-POINT SOLUTION * * Value of multiplier pi[p] in solution to the original problem is * corrected in the same way as for basic solution. Values of all * columns having non-zero coefficients in row p remain unchanged. * * RECOVERING MIP SOLUTION * * None needed. */ struct forcing_col { /* column fixed on its bound by forcing row */ int j; /* column reference number */ char stat; /* original column status: GLP_NL - fixed on lower bound GLP_NU - fixed on upper bound */ double a; /* constraint coefficient a[p,j] */ double c; /* objective coefficient c[j] */ NPPLFE *ptr; /* list of non-zero coefficients a[i,j], i != p */ struct forcing_col *next; /* pointer to another column fixed by forcing row */ }; struct forcing_row { /* forcing row */ int p; /* row reference number */ char stat; /* status assigned to the row if it becomes active: GLP_NS - active equality constraint GLP_NL - inequality constraint with lower bound active GLP_NU - inequality constraint with upper bound active */ struct forcing_col *ptr; /* list of all columns having non-zero constraint coefficient a[p,j] in the forcing row */ }; static int rcv_forcing_row(NPP *npp, void *info); int npp_forcing_row(NPP *npp, NPPROW *p, int at) { /* process forcing row */ struct forcing_row *info; struct forcing_col *col = NULL; NPPCOL *j; NPPAIJ *apj, *aij; NPPLFE *lfe; double big; xassert(at == 0 || at == 1); /* determine maximal magnitude of the row coefficients */ big = 1.0; for (apj = p->ptr; apj != NULL; apj = apj->r_next) if (big < fabs(apj->val)) big = fabs(apj->val); /* if there are too small coefficients in the row, transformation should not be applied */ for (apj = p->ptr; apj != NULL; apj = apj->r_next) if (fabs(apj->val) < 1e-7 * big) return 1; /* create transformation stack entry */ info = npp_push_tse(npp, rcv_forcing_row, sizeof(struct forcing_row)); info->p = p->i; if (p->lb == p->ub) { /* equality constraint */ info->stat = GLP_NS; } else if (at == 0) { /* inequality constraint; case L[p] = U'[p] */ info->stat = GLP_NL; xassert(p->lb != -DBL_MAX); } else /* at == 1 */ { /* inequality constraint; case U[p] = L'[p] */ info->stat = GLP_NU; xassert(p->ub != +DBL_MAX); } info->ptr = NULL; /* scan the forcing row, fix columns at corresponding bounds, and save column information (the latter is not needed for MIP) */ for (apj = p->ptr; apj != NULL; apj = apj->r_next) { /* column j has non-zero coefficient in the forcing row */ j = apj->col; /* it must be non-fixed */ xassert(j->lb < j->ub); /* allocate stack entry to save column information */ if (npp->sol != GLP_MIP) { col = dmp_get_atom(npp->stack, sizeof(struct forcing_col)); col->j = j->j; col->stat = -1; /* will be set below */ col->a = apj->val; col->c = j->coef; col->ptr = NULL; col->next = info->ptr; info->ptr = col; } /* fix column j */ if (at == 0 && apj->val < 0.0 || at != 0 && apj->val > 0.0) { /* at its lower bound */ if (npp->sol != GLP_MIP) col->stat = GLP_NL; xassert(j->lb != -DBL_MAX); j->ub = j->lb; } else { /* at its upper bound */ if (npp->sol != GLP_MIP) col->stat = GLP_NU; xassert(j->ub != +DBL_MAX); j->lb = j->ub; } /* save column coefficients a[i,j], i != p */ if (npp->sol != GLP_MIP) { for (aij = j->ptr; aij != NULL; aij = aij->c_next) { if (aij == apj) continue; /* skip a[p,j] */ lfe = dmp_get_atom(npp->stack, sizeof(NPPLFE)); lfe->ref = aij->row->i; lfe->val = aij->val; lfe->next = col->ptr; col->ptr = lfe; } } } /* make the row free (unbounded) */ p->lb = -DBL_MAX, p->ub = +DBL_MAX; return 0; } static int rcv_forcing_row(NPP *npp, void *_info) { /* recover forcing row */ struct forcing_row *info = _info; struct forcing_col *col, *piv; NPPLFE *lfe; double d, big, temp; if (npp->sol == GLP_MIP) goto done; /* initially solution to the original problem is the same as to the transformed problem, where row p is inactive constraint with pi[p] = 0, and all columns are non-basic */ if (npp->sol == GLP_SOL) { if (npp->r_stat[info->p] != GLP_BS) { npp_error(); return 1; } for (col = info->ptr; col != NULL; col = col->next) { if (npp->c_stat[col->j] != GLP_NS) { npp_error(); return 1; } npp->c_stat[col->j] = col->stat; /* original status */ } } /* compute reduced costs d[j] for all columns with formula (10) and store them in col.c instead objective coefficients */ for (col = info->ptr; col != NULL; col = col->next) { d = col->c; for (lfe = col->ptr; lfe != NULL; lfe = lfe->next) d -= lfe->val * npp->r_pi[lfe->ref]; col->c = d; } /* consider columns j, whose multipliers lambda[j] has wrong sign in solution to the transformed problem (where lambda[j] = d[j]), and choose column q, whose multipler lambda[q] reaches zero last on changing row multiplier pi[p]; see (14) */ piv = NULL, big = 0.0; for (col = info->ptr; col != NULL; col = col->next) { d = col->c; /* d[j] */ temp = fabs(d / col->a); if (col->stat == GLP_NL) { /* column j has active lower bound */ if (d < 0.0 && big < temp) piv = col, big = temp; } else if (col->stat == GLP_NU) { /* column j has active upper bound */ if (d > 0.0 && big < temp) piv = col, big = temp; } else { npp_error(); return 1; } } /* if column q does not exist, no correction is needed */ if (piv != NULL) { /* correct solution; row p becomes active constraint while column q becomes basic */ if (npp->sol == GLP_SOL) { npp->r_stat[info->p] = info->stat; npp->c_stat[piv->j] = GLP_BS; } /* assign new value to row multiplier pi[p] = d[p] / a[p,q] */ npp->r_pi[info->p] = piv->c / piv->a; } done: return 0; } /*********************************************************************** * NAME * * npp_analyze_row - perform general row analysis * * SYNOPSIS * * #include "glpnpp.h" * int npp_analyze_row(NPP *npp, NPPROW *p); * * DESCRIPTION * * The routine npp_analyze_row performs analysis of row p of general * format: * * L[p] <= sum a[p,j] x[j] <= U[p], (1) * j * * l[j] <= x[j] <= u[j], (2) * * where L[p] <= U[p] and l[j] <= u[j] for all a[p,j] != 0. * * RETURNS * * 0x?0 - row lower bound does not exist or is redundant; * * 0x?1 - row lower bound can be active; * * 0x?2 - row lower bound is a forcing bound; * * 0x0? - row upper bound does not exist or is redundant; * * 0x1? - row upper bound can be active; * * 0x2? - row upper bound is a forcing bound; * * 0x33 - row bounds are inconsistent with column bounds. * * ALGORITHM * * Analysis of row (1) is based on analysis of its implied lower and * upper bounds, which are determined by bounds of corresponding columns * (variables) as follows: * * L'[p] = inf sum a[p,j] x[j] = * j * (3) * = sum a[p,j] l[j] + sum a[p,j] u[j], * j in Jp j in Jn * * U'[p] = sup sum a[p,j] x[j] = * (4) * = sum a[p,j] u[j] + sum a[p,j] l[j], * j in Jp j in Jn * * Jp = {j: a[p,j] > 0}, Jn = {j: a[p,j] < 0}. (5) * * (Note that bounds of all columns in row p are assumed to be correct, * so L'[p] <= U'[p].) * * Analysis of row lower bound L[p] includes the following cases: * * 1) if L[p] > U'[p] + eps, where eps is an absolute tolerance for row * value, row lower bound L[p] and implied row upper bound U'[p] are * inconsistent, ergo, the problem has no primal feasible solution; * * 2) if U'[p] - eps <= L[p] <= U'[p] + eps, i.e. if L[p] =~ U'[p], * the row is a forcing row on its lower bound (see description of * the routine npp_forcing_row); * * 3) if L[p] > L'[p] + eps, row lower bound L[p] can be active (this * conclusion does not account other rows in the problem); * * 4) if L[p] <= L'[p] + eps, row lower bound L[p] cannot be active, so * it is redundant and can be removed (replaced by -oo). * * Analysis of row upper bound U[p] is performed in a similar way and * includes the following cases: * * 1) if U[p] < L'[p] - eps, row upper bound U[p] and implied row lower * bound L'[p] are inconsistent, ergo the problem has no primal * feasible solution; * * 2) if L'[p] - eps <= U[p] <= L'[p] + eps, i.e. if U[p] =~ L'[p], * the row is a forcing row on its upper bound (see description of * the routine npp_forcing_row); * * 3) if U[p] < U'[p] - eps, row upper bound U[p] can be active (this * conclusion does not account other rows in the problem); * * 4) if U[p] >= U'[p] - eps, row upper bound U[p] cannot be active, so * it is redundant and can be removed (replaced by +oo). */ int npp_analyze_row(NPP *npp, NPPROW *p) { /* perform general row analysis */ NPPAIJ *aij; int ret = 0x00; double l, u, eps; xassert(npp == npp); /* compute implied lower bound L'[p]; see (3) */ l = 0.0; for (aij = p->ptr; aij != NULL; aij = aij->r_next) { if (aij->val > 0.0) { if (aij->col->lb == -DBL_MAX) { l = -DBL_MAX; break; } l += aij->val * aij->col->lb; } else /* aij->val < 0.0 */ { if (aij->col->ub == +DBL_MAX) { l = -DBL_MAX; break; } l += aij->val * aij->col->ub; } } /* compute implied upper bound U'[p]; see (4) */ u = 0.0; for (aij = p->ptr; aij != NULL; aij = aij->r_next) { if (aij->val > 0.0) { if (aij->col->ub == +DBL_MAX) { u = +DBL_MAX; break; } u += aij->val * aij->col->ub; } else /* aij->val < 0.0 */ { if (aij->col->lb == -DBL_MAX) { u = +DBL_MAX; break; } u += aij->val * aij->col->lb; } } /* column bounds are assumed correct, so L'[p] <= U'[p] */ /* check if row lower bound is consistent */ if (p->lb != -DBL_MAX) { eps = 1e-3 + 1e-6 * fabs(p->lb); if (p->lb - eps > u) { ret = 0x33; goto done; } } /* check if row upper bound is consistent */ if (p->ub != +DBL_MAX) { eps = 1e-3 + 1e-6 * fabs(p->ub); if (p->ub + eps < l) { ret = 0x33; goto done; } } /* check if row lower bound can be active/forcing */ if (p->lb != -DBL_MAX) { eps = 1e-9 + 1e-12 * fabs(p->lb); if (p->lb - eps > l) { if (p->lb + eps <= u) ret |= 0x01; else ret |= 0x02; } } /* check if row upper bound can be active/forcing */ if (p->ub != +DBL_MAX) { eps = 1e-9 + 1e-12 * fabs(p->ub); if (p->ub + eps < u) { /* check if the upper bound is forcing */ if (p->ub - eps >= l) ret |= 0x10; else ret |= 0x20; } } done: return ret; } /*********************************************************************** * NAME * * npp_inactive_bound - remove row lower/upper inactive bound * * SYNOPSIS * * #include "glpnpp.h" * void npp_inactive_bound(NPP *npp, NPPROW *p, int which); * * DESCRIPTION * * The routine npp_inactive_bound removes lower (if which = 0) or upper * (if which = 1) bound of row p: * * L[p] <= sum a[p,j] x[j] <= U[p], * * which (bound) is assumed to be redundant. * * PROBLEM TRANSFORMATION * * If which = 0, current lower bound L[p] of row p is assigned -oo. * If which = 1, current upper bound U[p] of row p is assigned +oo. * * RECOVERING BASIC SOLUTION * * If in solution to the transformed problem row p is inactive * constraint (GLP_BS), its status is not changed in solution to the * original problem. Otherwise, status of row p in solution to the * original problem is defined by its type before transformation and * its status in solution to the transformed problem as follows: * * +---------------------+-------+---------------+---------------+ * | Row | Flag | Row status in | Row status in | * | type | which | transfmd soln | original soln | * +---------------------+-------+---------------+---------------+ * | sum >= L[p] | 0 | GLP_NF | GLP_NL | * | sum <= U[p] | 1 | GLP_NF | GLP_NU | * | L[p] <= sum <= U[p] | 0 | GLP_NU | GLP_NU | * | L[p] <= sum <= U[p] | 1 | GLP_NL | GLP_NL | * | sum = L[p] = U[p] | 0 | GLP_NU | GLP_NS | * | sum = L[p] = U[p] | 1 | GLP_NL | GLP_NS | * +---------------------+-------+---------------+---------------+ * * RECOVERING INTERIOR-POINT SOLUTION * * None needed. * * RECOVERING MIP SOLUTION * * None needed. */ struct inactive_bound { /* row inactive bound */ int p; /* row reference number */ char stat; /* row status (if active constraint) */ }; static int rcv_inactive_bound(NPP *npp, void *info); void npp_inactive_bound(NPP *npp, NPPROW *p, int which) { /* remove row lower/upper inactive bound */ struct inactive_bound *info; if (npp->sol == GLP_SOL) { /* create transformation stack entry */ info = npp_push_tse(npp, rcv_inactive_bound, sizeof(struct inactive_bound)); info->p = p->i; if (p->ub == +DBL_MAX) info->stat = GLP_NL; else if (p->lb == -DBL_MAX) info->stat = GLP_NU; else if (p->lb != p->ub) info->stat = (char)(which == 0 ? GLP_NU : GLP_NL); else info->stat = GLP_NS; } /* remove row inactive bound */ if (which == 0) { xassert(p->lb != -DBL_MAX); p->lb = -DBL_MAX; } else if (which == 1) { xassert(p->ub != +DBL_MAX); p->ub = +DBL_MAX; } else xassert(which != which); return; } static int rcv_inactive_bound(NPP *npp, void *_info) { /* recover row status */ struct inactive_bound *info = _info; if (npp->sol != GLP_SOL) { npp_error(); return 1; } if (npp->r_stat[info->p] == GLP_BS) npp->r_stat[info->p] = GLP_BS; else npp->r_stat[info->p] = info->stat; return 0; } /*********************************************************************** * NAME * * npp_implied_bounds - determine implied column bounds * * SYNOPSIS * * #include "glpnpp.h" * void npp_implied_bounds(NPP *npp, NPPROW *p); * * DESCRIPTION * * The routine npp_implied_bounds inspects general row (constraint) p: * * L[p] <= sum a[p,j] x[j] <= U[p], (1) * * l[j] <= x[j] <= u[j], (2) * * where L[p] <= U[p] and l[j] <= u[j] for all a[p,j] != 0, to compute * implied bounds of columns (variables x[j]) in this row. * * The routine stores implied column bounds l'[j] and u'[j] in column * descriptors (NPPCOL); it does not change current column bounds l[j] * and u[j]. (Implied column bounds can be then used to strengthen the * current column bounds; see the routines npp_implied_lower and * npp_implied_upper). * * ALGORITHM * * Current column bounds (2) define implied lower and upper bounds of * row (1) as follows: * * L'[p] = inf sum a[p,j] x[j] = * j * (3) * = sum a[p,j] l[j] + sum a[p,j] u[j], * j in Jp j in Jn * * U'[p] = sup sum a[p,j] x[j] = * (4) * = sum a[p,j] u[j] + sum a[p,j] l[j], * j in Jp j in Jn * * Jp = {j: a[p,j] > 0}, Jn = {j: a[p,j] < 0}. (5) * * (Note that bounds of all columns in row p are assumed to be correct, * so L'[p] <= U'[p].) * * If L[p] > L'[p] and/or U[p] < U'[p], the lower and/or upper bound of * row (1) can be active, in which case such row defines implied bounds * of its variables. * * Let x[k] be some variable having in row (1) coefficient a[p,k] != 0. * Consider a case when row lower bound can be active (L[p] > L'[p]): * * sum a[p,j] x[j] >= L[p] ==> * j * * sum a[p,j] x[j] + a[p,k] x[k] >= L[p] ==> * j!=k * (6) * a[p,k] x[k] >= L[p] - sum a[p,j] x[j] ==> * j!=k * * a[p,k] x[k] >= L[p,k], * * where * * L[p,k] = inf(L[p] - sum a[p,j] x[j]) = * j!=k * * = L[p] - sup sum a[p,j] x[j] = (7) * j!=k * * = L[p] - sum a[p,j] u[j] - sum a[p,j] l[j]. * j in Jp\{k} j in Jn\{k} * * Thus: * * x[k] >= l'[k] = L[p,k] / a[p,k], if a[p,k] > 0, (8) * * x[k] <= u'[k] = L[p,k] / a[p,k], if a[p,k] < 0. (9) * * where l'[k] and u'[k] are implied lower and upper bounds of variable * x[k], resp. * * Now consider a similar case when row upper bound can be active * (U[p] < U'[p]): * * sum a[p,j] x[j] <= U[p] ==> * j * * sum a[p,j] x[j] + a[p,k] x[k] <= U[p] ==> * j!=k * (10) * a[p,k] x[k] <= U[p] - sum a[p,j] x[j] ==> * j!=k * * a[p,k] x[k] <= U[p,k], * * where: * * U[p,k] = sup(U[p] - sum a[p,j] x[j]) = * j!=k * * = U[p] - inf sum a[p,j] x[j] = (11) * j!=k * * = U[p] - sum a[p,j] l[j] - sum a[p,j] u[j]. * j in Jp\{k} j in Jn\{k} * * Thus: * * x[k] <= u'[k] = U[p,k] / a[p,k], if a[p,k] > 0, (12) * * x[k] >= l'[k] = U[p,k] / a[p,k], if a[p,k] < 0. (13) * * Note that in formulae (8), (9), (12), and (13) coefficient a[p,k] * must not be too small in magnitude relatively to other non-zero * coefficients in row (1), i.e. the following condition must hold: * * |a[p,k]| >= eps * max(1, |a[p,j]|), (14) * j * * where eps is a relative tolerance for constraint coefficients. * Otherwise the implied column bounds can be numerical inreliable. For * example, using formula (8) for the following inequality constraint: * * 1e-12 x1 - x2 - x3 >= 0, * * where x1 >= -1, x2, x3, >= 0, may lead to numerically unreliable * conclusion that x1 >= 0. * * Using formulae (8), (9), (12), and (13) to compute implied bounds * for one variable requires |J| operations, where J = {j: a[p,j] != 0}, * because this needs computing L[p,k] and U[p,k]. Thus, computing * implied bounds for all variables in row (1) would require |J|^2 * operations, that is not a good technique. However, the total number * of operations can be reduced to |J| as follows. * * Let a[p,k] > 0. Then from (7) and (11) we have: * * L[p,k] = L[p] - (U'[p] - a[p,k] u[k]) = * * = L[p] - U'[p] + a[p,k] u[k], * * U[p,k] = U[p] - (L'[p] - a[p,k] l[k]) = * * = U[p] - L'[p] + a[p,k] l[k], * * where L'[p] and U'[p] are implied row lower and upper bounds defined * by formulae (3) and (4). Substituting these expressions into (8) and * (12) gives: * * l'[k] = L[p,k] / a[p,k] = u[k] + (L[p] - U'[p]) / a[p,k], (15) * * u'[k] = U[p,k] / a[p,k] = l[k] + (U[p] - L'[p]) / a[p,k]. (16) * * Similarly, if a[p,k] < 0, according to (7) and (11) we have: * * L[p,k] = L[p] - (U'[p] - a[p,k] l[k]) = * * = L[p] - U'[p] + a[p,k] l[k], * * U[p,k] = U[p] - (L'[p] - a[p,k] u[k]) = * * = U[p] - L'[p] + a[p,k] u[k], * * and substituting these expressions into (8) and (12) gives: * * l'[k] = U[p,k] / a[p,k] = u[k] + (U[p] - L'[p]) / a[p,k], (17) * * u'[k] = L[p,k] / a[p,k] = l[k] + (L[p] - U'[p]) / a[p,k]. (18) * * Note that formulae (15)-(18) can be used only if L'[p] and U'[p] * exist. However, if for some variable x[j] it happens that l[j] = -oo * and/or u[j] = +oo, values of L'[p] (if a[p,j] > 0) and/or U'[p] (if * a[p,j] < 0) are undefined. Consider, therefore, the most general * situation, when some column bounds (2) may not exist. * * Let: * * J' = {j : (a[p,j] > 0 and l[j] = -oo) or * (19) * (a[p,j] < 0 and u[j] = +oo)}. * * Then (assuming that row upper bound U[p] can be active) the following * three cases are possible: * * 1) |J'| = 0. In this case L'[p] exists, thus, for all variables x[j] * in row (1) we can use formulae (16) and (17); * * 2) J' = {k}. In this case L'[p] = -oo, however, U[p,k] (11) exists, * so for variable x[k] we can use formulae (12) and (13). Note that * for all other variables x[j] (j != k) l'[j] = -oo (if a[p,j] < 0) * or u'[j] = +oo (if a[p,j] > 0); * * 3) |J'| > 1. In this case for all variables x[j] in row [1] we have * l'[j] = -oo (if a[p,j] < 0) or u'[j] = +oo (if a[p,j] > 0). * * Similarly, let: * * J'' = {j : (a[p,j] > 0 and u[j] = +oo) or * (20) * (a[p,j] < 0 and l[j] = -oo)}. * * Then (assuming that row lower bound L[p] can be active) the following * three cases are possible: * * 1) |J''| = 0. In this case U'[p] exists, thus, for all variables x[j] * in row (1) we can use formulae (15) and (18); * * 2) J'' = {k}. In this case U'[p] = +oo, however, L[p,k] (7) exists, * so for variable x[k] we can use formulae (8) and (9). Note that * for all other variables x[j] (j != k) l'[j] = -oo (if a[p,j] > 0) * or u'[j] = +oo (if a[p,j] < 0); * * 3) |J''| > 1. In this case for all variables x[j] in row (1) we have * l'[j] = -oo (if a[p,j] > 0) or u'[j] = +oo (if a[p,j] < 0). */ void npp_implied_bounds(NPP *npp, NPPROW *p) { NPPAIJ *apj, *apk; double big, eps, temp; xassert(npp == npp); /* initialize implied bounds for all variables and determine maximal magnitude of row coefficients a[p,j] */ big = 1.0; for (apj = p->ptr; apj != NULL; apj = apj->r_next) { apj->col->ll.ll = -DBL_MAX, apj->col->uu.uu = +DBL_MAX; if (big < fabs(apj->val)) big = fabs(apj->val); } eps = 1e-6 * big; /* process row lower bound (assuming that it can be active) */ if (p->lb != -DBL_MAX) { apk = NULL; for (apj = p->ptr; apj != NULL; apj = apj->r_next) { if (apj->val > 0.0 && apj->col->ub == +DBL_MAX || apj->val < 0.0 && apj->col->lb == -DBL_MAX) { if (apk == NULL) apk = apj; else goto skip1; } } /* if a[p,k] = NULL then |J'| = 0 else J' = { k } */ temp = p->lb; for (apj = p->ptr; apj != NULL; apj = apj->r_next) { if (apj == apk) /* skip a[p,k] */; else if (apj->val > 0.0) temp -= apj->val * apj->col->ub; else /* apj->val < 0.0 */ temp -= apj->val * apj->col->lb; } /* compute column implied bounds */ if (apk == NULL) { /* temp = L[p] - U'[p] */ for (apj = p->ptr; apj != NULL; apj = apj->r_next) { if (apj->val >= +eps) { /* l'[j] := u[j] + (L[p] - U'[p]) / a[p,j] */ apj->col->ll.ll = apj->col->ub + temp / apj->val; } else if (apj->val <= -eps) { /* u'[j] := l[j] + (L[p] - U'[p]) / a[p,j] */ apj->col->uu.uu = apj->col->lb + temp / apj->val; } } } else { /* temp = L[p,k] */ if (apk->val >= +eps) { /* l'[k] := L[p,k] / a[p,k] */ apk->col->ll.ll = temp / apk->val; } else if (apk->val <= -eps) { /* u'[k] := L[p,k] / a[p,k] */ apk->col->uu.uu = temp / apk->val; } } skip1: ; } /* process row upper bound (assuming that it can be active) */ if (p->ub != +DBL_MAX) { apk = NULL; for (apj = p->ptr; apj != NULL; apj = apj->r_next) { if (apj->val > 0.0 && apj->col->lb == -DBL_MAX || apj->val < 0.0 && apj->col->ub == +DBL_MAX) { if (apk == NULL) apk = apj; else goto skip2; } } /* if a[p,k] = NULL then |J''| = 0 else J'' = { k } */ temp = p->ub; for (apj = p->ptr; apj != NULL; apj = apj->r_next) { if (apj == apk) /* skip a[p,k] */; else if (apj->val > 0.0) temp -= apj->val * apj->col->lb; else /* apj->val < 0.0 */ temp -= apj->val * apj->col->ub; } /* compute column implied bounds */ if (apk == NULL) { /* temp = U[p] - L'[p] */ for (apj = p->ptr; apj != NULL; apj = apj->r_next) { if (apj->val >= +eps) { /* u'[j] := l[j] + (U[p] - L'[p]) / a[p,j] */ apj->col->uu.uu = apj->col->lb + temp / apj->val; } else if (apj->val <= -eps) { /* l'[j] := u[j] + (U[p] - L'[p]) / a[p,j] */ apj->col->ll.ll = apj->col->ub + temp / apj->val; } } } else { /* temp = U[p,k] */ if (apk->val >= +eps) { /* u'[k] := U[p,k] / a[p,k] */ apk->col->uu.uu = temp / apk->val; } else if (apk->val <= -eps) { /* l'[k] := U[p,k] / a[p,k] */ apk->col->ll.ll = temp / apk->val; } } skip2: ; } return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpbfd.c0000644000076500000240000003467213524616144025015 0ustar tamasstaff00000000000000/* glpbfd.c (LP basis factorization driver) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wsometimes-uninitialized" #endif typedef struct BFD BFD; #define GLPBFD_PRIVATE #include "glpapi.h" #include "glpfhv.h" #include "glplpf.h" /* CAUTION: DO NOT CHANGE THE LIMIT BELOW */ #define M_MAX 100000000 /* = 100*10^6 */ /* maximal order of the basis matrix */ struct BFD { /* LP basis factorization */ int valid; /* factorization is valid only if this flag is set */ int type; /* factorization type: GLP_BF_FT - LUF + Forrest-Tomlin GLP_BF_BG - LUF + Schur compl. + Bartels-Golub GLP_BF_GR - LUF + Schur compl. + Givens rotation */ FHV *fhv; /* LP basis factorization (GLP_BF_FT) */ LPF *lpf; /* LP basis factorization (GLP_BF_BG, GLP_BF_GR) */ int lu_size; /* luf.sv_size */ double piv_tol; /* luf.piv_tol */ int piv_lim; /* luf.piv_lim */ int suhl; /* luf.suhl */ double eps_tol; /* luf.eps_tol */ double max_gro; /* luf.max_gro */ int nfs_max; /* fhv.hh_max */ double upd_tol; /* fhv.upd_tol */ int nrs_max; /* lpf.n_max */ int rs_size; /* lpf.v_size */ /* internal control parameters */ int upd_lim; /* the factorization update limit */ int upd_cnt; /* the factorization update count */ }; /*********************************************************************** * NAME * * bfd_create_it - create LP basis factorization * * SYNOPSIS * * #include "glpbfd.h" * BFD *bfd_create_it(void); * * DESCRIPTION * * The routine bfd_create_it creates a program object, which represents * a factorization of LP basis. * * RETURNS * * The routine bfd_create_it returns a pointer to the object created. */ BFD *bfd_create_it(void) { BFD *bfd; bfd = xmalloc(sizeof(BFD)); bfd->valid = 0; bfd->type = GLP_BF_FT; bfd->fhv = NULL; bfd->lpf = NULL; bfd->lu_size = 0; bfd->piv_tol = 0.10; bfd->piv_lim = 4; bfd->suhl = 1; bfd->eps_tol = 1e-15; bfd->max_gro = 1e+10; bfd->nfs_max = 100; bfd->upd_tol = 1e-6; bfd->nrs_max = 100; bfd->rs_size = 1000; bfd->upd_lim = -1; bfd->upd_cnt = 0; return bfd; } /**********************************************************************/ void bfd_set_parm(BFD *bfd, const void *_parm) { /* change LP basis factorization control parameters */ const glp_bfcp *parm = _parm; xassert(bfd != NULL); bfd->type = parm->type; bfd->lu_size = parm->lu_size; bfd->piv_tol = parm->piv_tol; bfd->piv_lim = parm->piv_lim; bfd->suhl = parm->suhl; bfd->eps_tol = parm->eps_tol; bfd->max_gro = parm->max_gro; bfd->nfs_max = parm->nfs_max; bfd->upd_tol = parm->upd_tol; bfd->nrs_max = parm->nrs_max; bfd->rs_size = parm->rs_size; return; } /*********************************************************************** * NAME * * bfd_factorize - compute LP basis factorization * * SYNOPSIS * * #include "glpbfd.h" * int bfd_factorize(BFD *bfd, int m, int bh[], int (*col)(void *info, * int j, int ind[], double val[]), void *info); * * DESCRIPTION * * The routine bfd_factorize computes the factorization of the basis * matrix B specified by the routine col. * * The parameter bfd specified the basis factorization data structure * created with the routine bfd_create_it. * * The parameter m specifies the order of B, m > 0. * * The array bh specifies the basis header: bh[j], 1 <= j <= m, is the * number of j-th column of B in some original matrix. The array bh is * optional and can be specified as NULL. * * The formal routine col specifies the matrix B to be factorized. To * obtain j-th column of A the routine bfd_factorize calls the routine * col with the parameter j (1 <= j <= n). In response the routine col * should store row indices and numerical values of non-zero elements * of j-th column of B to locations ind[1,...,len] and val[1,...,len], * respectively, where len is the number of non-zeros in j-th column * returned on exit. Neither zero nor duplicate elements are allowed. * * The parameter info is a transit pointer passed to the routine col. * * RETURNS * * 0 The factorization has been successfully computed. * * BFD_ESING * The specified matrix is singular within the working precision. * * BFD_ECOND * The specified matrix is ill-conditioned. * * For more details see comments to the routine luf_factorize. */ int bfd_factorize(BFD *bfd, int m, const int bh[], int (*col) (void *info, int j, int ind[], double val[]), void *info) { LUF *luf; int nov, ret; xassert(bfd != NULL); xassert(1 <= m && m <= M_MAX); /* invalidate the factorization */ bfd->valid = 0; /* create the factorization, if necessary */ nov = 0; switch (bfd->type) { case GLP_BF_FT: if (bfd->lpf != NULL) lpf_delete_it(bfd->lpf), bfd->lpf = NULL; if (bfd->fhv == NULL) bfd->fhv = fhv_create_it(), nov = 1; break; case GLP_BF_BG: case GLP_BF_GR: if (bfd->fhv != NULL) fhv_delete_it(bfd->fhv), bfd->fhv = NULL; if (bfd->lpf == NULL) bfd->lpf = lpf_create_it(), nov = 1; break; default: xassert(bfd != bfd); } /* set control parameters specific to LUF */ if (bfd->fhv != NULL) luf = bfd->fhv->luf; else if (bfd->lpf != NULL) luf = bfd->lpf->luf; else xassert(bfd != bfd); if (nov) luf->new_sva = bfd->lu_size; luf->piv_tol = bfd->piv_tol; luf->piv_lim = bfd->piv_lim; luf->suhl = bfd->suhl; luf->eps_tol = bfd->eps_tol; luf->max_gro = bfd->max_gro; /* set control parameters specific to FHV */ if (bfd->fhv != NULL) { if (nov) bfd->fhv->hh_max = bfd->nfs_max; bfd->fhv->upd_tol = bfd->upd_tol; } /* set control parameters specific to LPF */ if (bfd->lpf != NULL) { if (nov) bfd->lpf->n_max = bfd->nrs_max; if (nov) bfd->lpf->v_size = bfd->rs_size; } /* try to factorize the basis matrix */ if (bfd->fhv != NULL) { switch (fhv_factorize(bfd->fhv, m, col, info)) { case 0: break; case FHV_ESING: ret = BFD_ESING; goto done; case FHV_ECOND: ret = BFD_ECOND; goto done; default: xassert(bfd != bfd); } } else if (bfd->lpf != NULL) { switch (lpf_factorize(bfd->lpf, m, bh, col, info)) { case 0: /* set the Schur complement update type */ switch (bfd->type) { case GLP_BF_BG: /* Bartels-Golub update */ bfd->lpf->scf->t_opt = SCF_TBG; break; case GLP_BF_GR: /* Givens rotation update */ bfd->lpf->scf->t_opt = SCF_TGR; break; default: xassert(bfd != bfd); } break; case LPF_ESING: ret = BFD_ESING; goto done; case LPF_ECOND: ret = BFD_ECOND; goto done; default: xassert(bfd != bfd); } } else xassert(bfd != bfd); /* the basis matrix has been successfully factorized */ bfd->valid = 1; bfd->upd_cnt = 0; ret = 0; done: /* return to the calling program */ return ret; } /*********************************************************************** * NAME * * bfd_ftran - perform forward transformation (solve system B*x = b) * * SYNOPSIS * * #include "glpbfd.h" * void bfd_ftran(BFD *bfd, double x[]); * * DESCRIPTION * * The routine bfd_ftran performs forward transformation, i.e. solves * the system B*x = b, where B is the basis matrix, x is the vector of * unknowns to be computed, b is the vector of right-hand sides. * * On entry elements of the vector b should be stored in dense format * in locations x[1], ..., x[m], where m is the number of rows. On exit * the routine stores elements of the vector x in the same locations. */ void bfd_ftran(BFD *bfd, double x[]) { xassert(bfd != NULL); xassert(bfd->valid); if (bfd->fhv != NULL) fhv_ftran(bfd->fhv, x); else if (bfd->lpf != NULL) lpf_ftran(bfd->lpf, x); else xassert(bfd != bfd); return; } /*********************************************************************** * NAME * * bfd_btran - perform backward transformation (solve system B'*x = b) * * SYNOPSIS * * #include "glpbfd.h" * void bfd_btran(BFD *bfd, double x[]); * * DESCRIPTION * * The routine bfd_btran performs backward transformation, i.e. solves * the system B'*x = b, where B' is a matrix transposed to the basis * matrix B, x is the vector of unknowns to be computed, b is the vector * of right-hand sides. * * On entry elements of the vector b should be stored in dense format * in locations x[1], ..., x[m], where m is the number of rows. On exit * the routine stores elements of the vector x in the same locations. */ void bfd_btran(BFD *bfd, double x[]) { xassert(bfd != NULL); xassert(bfd->valid); if (bfd->fhv != NULL) fhv_btran(bfd->fhv, x); else if (bfd->lpf != NULL) lpf_btran(bfd->lpf, x); else xassert(bfd != bfd); return; } /*********************************************************************** * NAME * * bfd_update_it - update LP basis factorization * * SYNOPSIS * * #include "glpbfd.h" * int bfd_update_it(BFD *bfd, int j, int bh, int len, const int ind[], * const double val[]); * * DESCRIPTION * * The routine bfd_update_it updates the factorization of the basis * matrix B after replacing its j-th column by a new vector. * * The parameter j specifies the number of column of B, which has been * replaced, 1 <= j <= m, where m is the order of B. * * The parameter bh specifies the basis header entry for the new column * of B, which is the number of the new column in some original matrix. * This parameter is optional and can be specified as 0. * * Row indices and numerical values of non-zero elements of the new * column of B should be placed in locations ind[1], ..., ind[len] and * val[1], ..., val[len], resp., where len is the number of non-zeros * in the column. Neither zero nor duplicate elements are allowed. * * RETURNS * * 0 The factorization has been successfully updated. * * BFD_ESING * New basis matrix is singular within the working precision. * * BFD_ECHECK * The factorization is inaccurate. * * BFD_ELIMIT * Factorization update limit has been reached. * * BFD_EROOM * Overflow of the sparse vector area. * * In case of non-zero return code the factorization becomes invalid. * It should not be used until it has been recomputed with the routine * bfd_factorize. */ int bfd_update_it(BFD *bfd, int j, int bh, int len, const int ind[], const double val[]) { int ret; xassert(bfd != NULL); xassert(bfd->valid); /* try to update the factorization */ if (bfd->fhv != NULL) { switch (fhv_update_it(bfd->fhv, j, len, ind, val)) { case 0: break; case FHV_ESING: bfd->valid = 0; ret = BFD_ESING; goto done; case FHV_ECHECK: bfd->valid = 0; ret = BFD_ECHECK; goto done; case FHV_ELIMIT: bfd->valid = 0; ret = BFD_ELIMIT; goto done; case FHV_EROOM: bfd->valid = 0; ret = BFD_EROOM; goto done; default: xassert(bfd != bfd); } } else if (bfd->lpf != NULL) { switch (lpf_update_it(bfd->lpf, j, bh, len, ind, val)) { case 0: break; case LPF_ESING: bfd->valid = 0; ret = BFD_ESING; goto done; case LPF_ELIMIT: bfd->valid = 0; ret = BFD_ELIMIT; goto done; default: xassert(bfd != bfd); } } else xassert(bfd != bfd); /* the factorization has been successfully updated */ /* increase the update count */ bfd->upd_cnt++; ret = 0; done: /* return to the calling program */ return ret; } /**********************************************************************/ int bfd_get_count(BFD *bfd) { /* determine factorization update count */ xassert(bfd != NULL); xassert(bfd->valid); return bfd->upd_cnt; } /*********************************************************************** * NAME * * bfd_delete_it - delete LP basis factorization * * SYNOPSIS * * #include "glpbfd.h" * void bfd_delete_it(BFD *bfd); * * DESCRIPTION * * The routine bfd_delete_it deletes LP basis factorization specified * by the parameter fhv and frees all memory allocated to this program * object. */ void bfd_delete_it(BFD *bfd) { xassert(bfd != NULL); if (bfd->fhv != NULL) fhv_delete_it(bfd->fhv); if (bfd->lpf != NULL) lpf_delete_it(bfd->lpf); xfree(bfd); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpapi04.c0000644000076500000240000001102413524616144025161 0ustar tamasstaff00000000000000/* glpapi04.c (problem scaling routines) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glpapi.h" /*********************************************************************** * NAME * * glp_set_rii - set (change) row scale factor * * SYNOPSIS * * void glp_set_rii(glp_prob *lp, int i, double rii); * * DESCRIPTION * * The routine glp_set_rii sets (changes) the scale factor r[i,i] for * i-th row of the specified problem object. */ void glp_set_rii(glp_prob *lp, int i, double rii) { if (!(1 <= i && i <= lp->m)) xerror("glp_set_rii: i = %d; row number out of range\n", i); if (rii <= 0.0) xerror("glp_set_rii: i = %d; rii = %g; invalid scale factor\n", i, rii); if (lp->valid && lp->row[i]->rii != rii) { GLPAIJ *aij; for (aij = lp->row[i]->ptr; aij != NULL; aij = aij->r_next) { if (aij->col->stat == GLP_BS) { /* invalidate the basis factorization */ lp->valid = 0; break; } } } lp->row[i]->rii = rii; return; } /*********************************************************************** * NAME * * glp_set sjj - set (change) column scale factor * * SYNOPSIS * * void glp_set_sjj(glp_prob *lp, int j, double sjj); * * DESCRIPTION * * The routine glp_set_sjj sets (changes) the scale factor s[j,j] for * j-th column of the specified problem object. */ void glp_set_sjj(glp_prob *lp, int j, double sjj) { if (!(1 <= j && j <= lp->n)) xerror("glp_set_sjj: j = %d; column number out of range\n", j); if (sjj <= 0.0) xerror("glp_set_sjj: j = %d; sjj = %g; invalid scale factor\n", j, sjj); if (lp->valid && lp->col[j]->sjj != sjj && lp->col[j]->stat == GLP_BS) { /* invalidate the basis factorization */ lp->valid = 0; } lp->col[j]->sjj = sjj; return; } /*********************************************************************** * NAME * * glp_get_rii - retrieve row scale factor * * SYNOPSIS * * double glp_get_rii(glp_prob *lp, int i); * * RETURNS * * The routine glp_get_rii returns current scale factor r[i,i] for i-th * row of the specified problem object. */ double glp_get_rii(glp_prob *lp, int i) { if (!(1 <= i && i <= lp->m)) xerror("glp_get_rii: i = %d; row number out of range\n", i); return lp->row[i]->rii; } /*********************************************************************** * NAME * * glp_get_sjj - retrieve column scale factor * * SYNOPSIS * * double glp_get_sjj(glp_prob *lp, int j); * * RETURNS * * The routine glp_get_sjj returns current scale factor s[j,j] for j-th * column of the specified problem object. */ double glp_get_sjj(glp_prob *lp, int j) { if (!(1 <= j && j <= lp->n)) xerror("glp_get_sjj: j = %d; column number out of range\n", j); return lp->col[j]->sjj; } /*********************************************************************** * NAME * * glp_unscale_prob - unscale problem data * * SYNOPSIS * * void glp_unscale_prob(glp_prob *lp); * * DESCRIPTION * * The routine glp_unscale_prob performs unscaling of problem data for * the specified problem object. * * "Unscaling" means replacing the current scaling matrices R and S by * unity matrices that cancels the scaling effect. */ void glp_unscale_prob(glp_prob *lp) { int m = glp_get_num_rows(lp); int n = glp_get_num_cols(lp); int i, j; for (i = 1; i <= m; i++) glp_set_rii(lp, i, 1.0); for (j = 1; j <= n; j++) glp_set_sjj(lp, j, 1.0); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpavl.c0000644000076500000240000002621013524616144025031 0ustar tamasstaff00000000000000/* glpavl.c (binary search tree) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glpavl.h" AVL *avl_create_tree(int (*fcmp)(void *info, const void *key1, const void *key2), void *info) { /* create AVL tree */ AVL *tree; tree = xmalloc(sizeof(AVL)); tree->pool = dmp_create_pool(); tree->root = NULL; tree->fcmp = fcmp; tree->info = info; tree->size = 0; tree->height = 0; return tree; } int avl_strcmp(void *info, const void *key1, const void *key2) { /* compare character string keys */ xassert(info == info); return strcmp(key1, key2); } static AVLNODE *rotate_subtree(AVL *tree, AVLNODE *node); AVLNODE *avl_insert_node(AVL *tree, const void *key) { /* insert new node into AVL tree */ AVLNODE *p, *q, *r; short int flag; /* find an appropriate point for insertion */ p = NULL; q = tree->root; while (q != NULL) { p = q; if (tree->fcmp(tree->info, key, p->key) <= 0) { flag = 0; q = p->left; p->rank++; } else { flag = 1; q = p->right; } } /* create new node and insert it into the tree */ r = dmp_get_atom(tree->pool, sizeof(AVLNODE)); r->key = key; r->type = 0; r->link = NULL; r->rank = 1; r->up = p; r->flag = (short int)(p == NULL ? 0 : flag); r->bal = 0; r->left = NULL; r->right = NULL; tree->size++; if (p == NULL) tree->root = r; else if (flag == 0) p->left = r; else p->right = r; /* go upstairs to the root and correct all subtrees affected by insertion */ while (p != NULL) { if (flag == 0) { /* the height of the left subtree of [p] is increased */ if (p->bal > 0) { p->bal = 0; break; } if (p->bal < 0) { rotate_subtree(tree, p); break; } p->bal = -1; flag = p->flag; p = p->up; } else { /* the height of the right subtree of [p] is increased */ if (p->bal < 0) { p->bal = 0; break; } if (p->bal > 0) { rotate_subtree(tree, p); break; } p->bal = +1; flag = p->flag; p = p->up; } } /* if the root has been reached, the height of the entire tree is increased */ if (p == NULL) tree->height++; return r; } void avl_set_node_type(AVLNODE *node, int type) { /* assign the type field of specified node */ node->type = type; return; } void avl_set_node_link(AVLNODE *node, void *link) { /* assign the link field of specified node */ node->link = link; return; } AVLNODE *avl_find_node(AVL *tree, const void *key) { /* find node in AVL tree */ AVLNODE *p; int c; p = tree->root; while (p != NULL) { c = tree->fcmp(tree->info, key, p->key); if (c == 0) break; p = (c < 0 ? p->left : p->right); } return p; } int avl_get_node_type(AVLNODE *node) { /* retrieve the type field of specified node */ return node->type; } void *avl_get_node_link(AVLNODE *node) { /* retrieve the link field of specified node */ return node->link; } static AVLNODE *find_next_node(AVL *tree, AVLNODE *node) { /* find next node in AVL tree */ AVLNODE *p, *q; if (tree->root == NULL) return NULL; p = node; q = (p == NULL ? tree->root : p->right); if (q == NULL) { /* go upstairs from the left subtree */ for (;;) { q = p->up; if (q == NULL) break; if (p->flag == 0) break; p = q; } } else { /* go downstairs into the right subtree */ for (;;) { p = q->left; if (p == NULL) break; q = p; } } return q; } void avl_delete_node(AVL *tree, AVLNODE *node) { /* delete specified node from AVL tree */ AVLNODE *f, *p, *q, *r, *s, *x, *y; short int flag; p = node; /* if both subtrees of the specified node are non-empty, the node should be interchanged with the next one, at least one subtree of which is always empty */ if (p->left == NULL || p->right == NULL) goto skip; f = p->up; q = p->left; r = find_next_node(tree, p); s = r->right; if (p->right == r) { if (f == NULL) tree->root = r; else if (p->flag == 0) f->left = r; else f->right = r; r->rank = p->rank; r->up = f; r->flag = p->flag; r->bal = p->bal; r->left = q; r->right = p; q->up = r; p->rank = 1; p->up = r; p->flag = 1; p->bal = (short int)(s == NULL ? 0 : +1); p->left = NULL; p->right = s; if (s != NULL) s->up = p; } else { x = p->right; y = r->up; if (f == NULL) tree->root = r; else if (p->flag == 0) f->left = r; else f->right = r; r->rank = p->rank; r->up = f; r->flag = p->flag; r->bal = p->bal; r->left = q; r->right = x; q->up = r; x->up = r; y->left = p; p->rank = 1; p->up = y; p->flag = 0; p->bal = (short int)(s == NULL ? 0 : +1); p->left = NULL; p->right = s; if (s != NULL) s->up = p; } skip: /* now the specified node [p] has at least one empty subtree; go upstairs to the root and adjust the rank field of all nodes affected by deletion */ q = p; f = q->up; while (f != NULL) { if (q->flag == 0) f->rank--; q = f; f = q->up; } /* delete the specified node from the tree */ f = p->up; flag = p->flag; q = p->left != NULL ? p->left : p->right; if (f == NULL) tree->root = q; else if (flag == 0) f->left = q; else f->right = q; if (q != NULL) q->up = f, q->flag = flag; tree->size--; /* go upstairs to the root and correct all subtrees affected by deletion */ while (f != NULL) { if (flag == 0) { /* the height of the left subtree of [f] is decreased */ if (f->bal == 0) { f->bal = +1; break; } if (f->bal < 0) f->bal = 0; else { f = rotate_subtree(tree, f); if (f->bal < 0) break; } flag = f->flag; f = f->up; } else { /* the height of the right subtree of [f] is decreased */ if (f->bal == 0) { f->bal = -1; break; } if (f->bal > 0) f->bal = 0; else { f = rotate_subtree(tree, f); if (f->bal > 0) break; } flag = f->flag; f = f->up; } } /* if the root has been reached, the height of the entire tree is decreased */ if (f == NULL) tree->height--; /* returns the deleted node to the memory pool */ dmp_free_atom(tree->pool, p, sizeof(AVLNODE)); return; } static AVLNODE *rotate_subtree(AVL *tree, AVLNODE *node) { /* restore balance of AVL subtree */ AVLNODE *f, *p, *q, *r, *x, *y; xassert(node != NULL); p = node; if (p->bal < 0) { /* perform negative (left) rotation */ f = p->up; q = p->left; r = q->right; if (q->bal <= 0) { /* perform single negative rotation */ if (f == NULL) tree->root = q; else if (p->flag == 0) f->left = q; else f->right = q; p->rank -= q->rank; q->up = f; q->flag = p->flag; q->bal++; q->right = p; p->up = q; p->flag = 1; p->bal = (short int)(-q->bal); p->left = r; if (r != NULL) r->up = p, r->flag = 0; node = q; } else { /* perform double negative rotation */ x = r->left; y = r->right; if (f == NULL) tree->root = r; else if (p->flag == 0) f->left = r; else f->right = r; p->rank -= (q->rank + r->rank); r->rank += q->rank; p->bal = (short int)(r->bal >= 0 ? 0 : +1); q->bal = (short int)(r->bal <= 0 ? 0 : -1); r->up = f; r->flag = p->flag; r->bal = 0; r->left = q; r->right = p; p->up = r; p->flag = 1; p->left = y; q->up = r; q->flag = 0; q->right = x; if (x != NULL) x->up = q, x->flag = 1; if (y != NULL) y->up = p, y->flag = 0; node = r; } } else { /* perform positive (right) rotation */ f = p->up; q = p->right; r = q->left; if (q->bal >= 0) { /* perform single positive rotation */ if (f == NULL) tree->root = q; else if (p->flag == 0) f->left = q; else f->right = q; q->rank += p->rank; q->up = f; q->flag = p->flag; q->bal--; q->left = p; p->up = q; p->flag = 0; p->bal = (short int)(-q->bal); p->right = r; if (r != NULL) r->up = p, r->flag = 1; node = q; } else { /* perform double positive rotation */ x = r->left; y = r->right; if (f == NULL) tree->root = r; else if (p->flag == 0) f->left = r; else f->right = r; q->rank -= r->rank; r->rank += p->rank; p->bal = (short int)(r->bal <= 0 ? 0 : -1); q->bal = (short int)(r->bal >= 0 ? 0 : +1); r->up = f; r->flag = p->flag; r->bal = 0; r->left = p; r->right = q; p->up = r; p->flag = 0; p->right = x; q->up = r; q->flag = 1; q->left = y; if (x != NULL) x->up = p, x->flag = 1; if (y != NULL) y->up = q, y->flag = 0; node = r; } } return node; } void avl_delete_tree(AVL *tree) { /* delete AVL tree */ dmp_delete_pool(tree->pool); xfree(tree); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpluf.c0000644000076500000240000021376213524616144025047 0ustar tamasstaff00000000000000/* glpluf.c (LU-factorization) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wself-assign" #pragma clang diagnostic ignored "-Wsign-conversion" #endif #include "glpenv.h" #include "glpluf.h" #define xfault xerror /* CAUTION: DO NOT CHANGE THE LIMIT BELOW */ #define N_MAX 100000000 /* = 100*10^6 */ /* maximal order of the original matrix */ /*********************************************************************** * NAME * * luf_create_it - create LU-factorization * * SYNOPSIS * * #include "glpluf.h" * LUF *luf_create_it(void); * * DESCRIPTION * * The routine luf_create_it creates a program object, which represents * LU-factorization of a square matrix. * * RETURNS * * The routine luf_create_it returns a pointer to the object created. */ LUF *luf_create_it(void) { LUF *luf; luf = xmalloc(sizeof(LUF)); luf->n_max = luf->n = 0; luf->valid = 0; luf->fr_ptr = luf->fr_len = NULL; luf->fc_ptr = luf->fc_len = NULL; luf->vr_ptr = luf->vr_len = luf->vr_cap = NULL; luf->vr_piv = NULL; luf->vc_ptr = luf->vc_len = luf->vc_cap = NULL; luf->pp_row = luf->pp_col = NULL; luf->qq_row = luf->qq_col = NULL; luf->sv_size = 0; luf->sv_beg = luf->sv_end = 0; luf->sv_ind = NULL; luf->sv_val = NULL; luf->sv_head = luf->sv_tail = 0; luf->sv_prev = luf->sv_next = NULL; luf->vr_max = NULL; luf->rs_head = luf->rs_prev = luf->rs_next = NULL; luf->cs_head = luf->cs_prev = luf->cs_next = NULL; luf->flag = NULL; luf->work = NULL; luf->new_sva = 0; luf->piv_tol = 0.10; luf->piv_lim = 4; luf->suhl = 1; luf->eps_tol = 1e-15; luf->max_gro = 1e+10; luf->nnz_a = luf->nnz_f = luf->nnz_v = 0; luf->max_a = luf->big_v = 0.0; luf->rank = 0; return luf; } /*********************************************************************** * NAME * * luf_defrag_sva - defragment the sparse vector area * * SYNOPSIS * * #include "glpluf.h" * void luf_defrag_sva(LUF *luf); * * DESCRIPTION * * The routine luf_defrag_sva defragments the sparse vector area (SVA) * gathering all unused locations in one continuous extent. In order to * do that the routine moves all unused locations from the left part of * SVA (which contains rows and columns of the matrix V) to the middle * part (which contains free locations). This is attained by relocating * elements of rows and columns of the matrix V toward the beginning of * the left part. * * NOTE that this "garbage collection" involves changing row and column * pointers of the matrix V. */ void luf_defrag_sva(LUF *luf) { int n = luf->n; int *vr_ptr = luf->vr_ptr; int *vr_len = luf->vr_len; int *vr_cap = luf->vr_cap; int *vc_ptr = luf->vc_ptr; int *vc_len = luf->vc_len; int *vc_cap = luf->vc_cap; int *sv_ind = luf->sv_ind; double *sv_val = luf->sv_val; int *sv_next = luf->sv_next; int sv_beg = 1; int i, j, k; /* skip rows and columns, which do not need to be relocated */ for (k = luf->sv_head; k != 0; k = sv_next[k]) { if (k <= n) { /* i-th row of the matrix V */ i = k; if (vr_ptr[i] != sv_beg) break; vr_cap[i] = vr_len[i]; sv_beg += vr_cap[i]; } else { /* j-th column of the matrix V */ j = k - n; if (vc_ptr[j] != sv_beg) break; vc_cap[j] = vc_len[j]; sv_beg += vc_cap[j]; } } /* relocate other rows and columns in order to gather all unused locations in one continuous extent */ for (k = k; k != 0; k = sv_next[k]) { if (k <= n) { /* i-th row of the matrix V */ i = k; memmove(&sv_ind[sv_beg], &sv_ind[vr_ptr[i]], vr_len[i] * sizeof(int)); memmove(&sv_val[sv_beg], &sv_val[vr_ptr[i]], vr_len[i] * sizeof(double)); vr_ptr[i] = sv_beg; vr_cap[i] = vr_len[i]; sv_beg += vr_cap[i]; } else { /* j-th column of the matrix V */ j = k - n; memmove(&sv_ind[sv_beg], &sv_ind[vc_ptr[j]], vc_len[j] * sizeof(int)); memmove(&sv_val[sv_beg], &sv_val[vc_ptr[j]], vc_len[j] * sizeof(double)); vc_ptr[j] = sv_beg; vc_cap[j] = vc_len[j]; sv_beg += vc_cap[j]; } } /* set new pointer to the beginning of the free part */ luf->sv_beg = sv_beg; return; } /*********************************************************************** * NAME * * luf_enlarge_row - enlarge row capacity * * SYNOPSIS * * #include "glpluf.h" * int luf_enlarge_row(LUF *luf, int i, int cap); * * DESCRIPTION * * The routine luf_enlarge_row enlarges capacity of the i-th row of the * matrix V to cap locations (assuming that its current capacity is less * than cap). In order to do that the routine relocates elements of the * i-th row to the end of the left part of SVA (which contains rows and * columns of the matrix V) and then expands the left part by allocating * cap free locations from the free part. If there are less than cap * free locations, the routine defragments the sparse vector area. * * Due to "garbage collection" this operation may change row and column * pointers of the matrix V. * * RETURNS * * If no error occured, the routine returns zero. Otherwise, in case of * overflow of the sparse vector area, the routine returns non-zero. */ int luf_enlarge_row(LUF *luf, int i, int cap) { int n = luf->n; int *vr_ptr = luf->vr_ptr; int *vr_len = luf->vr_len; int *vr_cap = luf->vr_cap; int *vc_cap = luf->vc_cap; int *sv_ind = luf->sv_ind; double *sv_val = luf->sv_val; int *sv_prev = luf->sv_prev; int *sv_next = luf->sv_next; int ret = 0; int cur, k, kk; xassert(1 <= i && i <= n); xassert(vr_cap[i] < cap); /* if there are less than cap free locations, defragment SVA */ if (luf->sv_end - luf->sv_beg < cap) { luf_defrag_sva(luf); if (luf->sv_end - luf->sv_beg < cap) { ret = 1; goto done; } } /* save current capacity of the i-th row */ cur = vr_cap[i]; /* copy existing elements to the beginning of the free part */ memmove(&sv_ind[luf->sv_beg], &sv_ind[vr_ptr[i]], vr_len[i] * sizeof(int)); memmove(&sv_val[luf->sv_beg], &sv_val[vr_ptr[i]], vr_len[i] * sizeof(double)); /* set new pointer and new capacity of the i-th row */ vr_ptr[i] = luf->sv_beg; vr_cap[i] = cap; /* set new pointer to the beginning of the free part */ luf->sv_beg += cap; /* now the i-th row starts in the rightmost location among other rows and columns of the matrix V, so its node should be moved to the end of the row/column linked list */ k = i; /* remove the i-th row node from the linked list */ if (sv_prev[k] == 0) luf->sv_head = sv_next[k]; else { /* capacity of the previous row/column can be increased at the expense of old locations of the i-th row */ kk = sv_prev[k]; if (kk <= n) vr_cap[kk] += cur; else vc_cap[kk-n] += cur; sv_next[sv_prev[k]] = sv_next[k]; } if (sv_next[k] == 0) luf->sv_tail = sv_prev[k]; else sv_prev[sv_next[k]] = sv_prev[k]; /* insert the i-th row node to the end of the linked list */ sv_prev[k] = luf->sv_tail; sv_next[k] = 0; if (sv_prev[k] == 0) luf->sv_head = k; else sv_next[sv_prev[k]] = k; luf->sv_tail = k; done: return ret; } /*********************************************************************** * NAME * * luf_enlarge_col - enlarge column capacity * * SYNOPSIS * * #include "glpluf.h" * int luf_enlarge_col(LUF *luf, int j, int cap); * * DESCRIPTION * * The routine luf_enlarge_col enlarges capacity of the j-th column of * the matrix V to cap locations (assuming that its current capacity is * less than cap). In order to do that the routine relocates elements * of the j-th column to the end of the left part of SVA (which contains * rows and columns of the matrix V) and then expands the left part by * allocating cap free locations from the free part. If there are less * than cap free locations, the routine defragments the sparse vector * area. * * Due to "garbage collection" this operation may change row and column * pointers of the matrix V. * * RETURNS * * If no error occured, the routine returns zero. Otherwise, in case of * overflow of the sparse vector area, the routine returns non-zero. */ int luf_enlarge_col(LUF *luf, int j, int cap) { int n = luf->n; int *vr_cap = luf->vr_cap; int *vc_ptr = luf->vc_ptr; int *vc_len = luf->vc_len; int *vc_cap = luf->vc_cap; int *sv_ind = luf->sv_ind; double *sv_val = luf->sv_val; int *sv_prev = luf->sv_prev; int *sv_next = luf->sv_next; int ret = 0; int cur, k, kk; xassert(1 <= j && j <= n); xassert(vc_cap[j] < cap); /* if there are less than cap free locations, defragment SVA */ if (luf->sv_end - luf->sv_beg < cap) { luf_defrag_sva(luf); if (luf->sv_end - luf->sv_beg < cap) { ret = 1; goto done; } } /* save current capacity of the j-th column */ cur = vc_cap[j]; /* copy existing elements to the beginning of the free part */ memmove(&sv_ind[luf->sv_beg], &sv_ind[vc_ptr[j]], vc_len[j] * sizeof(int)); memmove(&sv_val[luf->sv_beg], &sv_val[vc_ptr[j]], vc_len[j] * sizeof(double)); /* set new pointer and new capacity of the j-th column */ vc_ptr[j] = luf->sv_beg; vc_cap[j] = cap; /* set new pointer to the beginning of the free part */ luf->sv_beg += cap; /* now the j-th column starts in the rightmost location among other rows and columns of the matrix V, so its node should be moved to the end of the row/column linked list */ k = n + j; /* remove the j-th column node from the linked list */ if (sv_prev[k] == 0) luf->sv_head = sv_next[k]; else { /* capacity of the previous row/column can be increased at the expense of old locations of the j-th column */ kk = sv_prev[k]; if (kk <= n) vr_cap[kk] += cur; else vc_cap[kk-n] += cur; sv_next[sv_prev[k]] = sv_next[k]; } if (sv_next[k] == 0) luf->sv_tail = sv_prev[k]; else sv_prev[sv_next[k]] = sv_prev[k]; /* insert the j-th column node to the end of the linked list */ sv_prev[k] = luf->sv_tail; sv_next[k] = 0; if (sv_prev[k] == 0) luf->sv_head = k; else sv_next[sv_prev[k]] = k; luf->sv_tail = k; done: return ret; } /*********************************************************************** * reallocate - reallocate LU-factorization arrays * * This routine reallocates arrays, whose size depends of n, the order * of the matrix A to be factorized. */ static void reallocate(LUF *luf, int n) { int n_max = luf->n_max; luf->n = n; if (n <= n_max) goto done; if (luf->fr_ptr != NULL) xfree(luf->fr_ptr); if (luf->fr_len != NULL) xfree(luf->fr_len); if (luf->fc_ptr != NULL) xfree(luf->fc_ptr); if (luf->fc_len != NULL) xfree(luf->fc_len); if (luf->vr_ptr != NULL) xfree(luf->vr_ptr); if (luf->vr_len != NULL) xfree(luf->vr_len); if (luf->vr_cap != NULL) xfree(luf->vr_cap); if (luf->vr_piv != NULL) xfree(luf->vr_piv); if (luf->vc_ptr != NULL) xfree(luf->vc_ptr); if (luf->vc_len != NULL) xfree(luf->vc_len); if (luf->vc_cap != NULL) xfree(luf->vc_cap); if (luf->pp_row != NULL) xfree(luf->pp_row); if (luf->pp_col != NULL) xfree(luf->pp_col); if (luf->qq_row != NULL) xfree(luf->qq_row); if (luf->qq_col != NULL) xfree(luf->qq_col); if (luf->sv_prev != NULL) xfree(luf->sv_prev); if (luf->sv_next != NULL) xfree(luf->sv_next); if (luf->vr_max != NULL) xfree(luf->vr_max); if (luf->rs_head != NULL) xfree(luf->rs_head); if (luf->rs_prev != NULL) xfree(luf->rs_prev); if (luf->rs_next != NULL) xfree(luf->rs_next); if (luf->cs_head != NULL) xfree(luf->cs_head); if (luf->cs_prev != NULL) xfree(luf->cs_prev); if (luf->cs_next != NULL) xfree(luf->cs_next); if (luf->flag != NULL) xfree(luf->flag); if (luf->work != NULL) xfree(luf->work); luf->n_max = n_max = n + 100; luf->fr_ptr = xcalloc(1+n_max, sizeof(int)); luf->fr_len = xcalloc(1+n_max, sizeof(int)); luf->fc_ptr = xcalloc(1+n_max, sizeof(int)); luf->fc_len = xcalloc(1+n_max, sizeof(int)); luf->vr_ptr = xcalloc(1+n_max, sizeof(int)); luf->vr_len = xcalloc(1+n_max, sizeof(int)); luf->vr_cap = xcalloc(1+n_max, sizeof(int)); luf->vr_piv = xcalloc(1+n_max, sizeof(double)); luf->vc_ptr = xcalloc(1+n_max, sizeof(int)); luf->vc_len = xcalloc(1+n_max, sizeof(int)); luf->vc_cap = xcalloc(1+n_max, sizeof(int)); luf->pp_row = xcalloc(1+n_max, sizeof(int)); luf->pp_col = xcalloc(1+n_max, sizeof(int)); luf->qq_row = xcalloc(1+n_max, sizeof(int)); luf->qq_col = xcalloc(1+n_max, sizeof(int)); luf->sv_prev = xcalloc(1+n_max+n_max, sizeof(int)); luf->sv_next = xcalloc(1+n_max+n_max, sizeof(int)); luf->vr_max = xcalloc(1+n_max, sizeof(double)); luf->rs_head = xcalloc(1+n_max, sizeof(int)); luf->rs_prev = xcalloc(1+n_max, sizeof(int)); luf->rs_next = xcalloc(1+n_max, sizeof(int)); luf->cs_head = xcalloc(1+n_max, sizeof(int)); luf->cs_prev = xcalloc(1+n_max, sizeof(int)); luf->cs_next = xcalloc(1+n_max, sizeof(int)); luf->flag = xcalloc(1+n_max, sizeof(int)); luf->work = xcalloc(1+n_max, sizeof(double)); done: return; } /*********************************************************************** * initialize - initialize LU-factorization data structures * * This routine initializes data structures for subsequent computing * the LU-factorization of a given matrix A, which is specified by the * formal routine col. On exit V = A and F = P = Q = I, where I is the * unity matrix. (Row-wise representation of the matrix F is not used * at the factorization stage and therefore is not initialized.) * * If no error occured, the routine returns zero. Otherwise, in case of * overflow of the sparse vector area, the routine returns non-zero. */ static int initialize(LUF *luf, int (*col)(void *info, int j, int rn[], double aj[]), void *info) { int n = luf->n; int *fc_ptr = luf->fc_ptr; int *fc_len = luf->fc_len; int *vr_ptr = luf->vr_ptr; int *vr_len = luf->vr_len; int *vr_cap = luf->vr_cap; int *vc_ptr = luf->vc_ptr; int *vc_len = luf->vc_len; int *vc_cap = luf->vc_cap; int *pp_row = luf->pp_row; int *pp_col = luf->pp_col; int *qq_row = luf->qq_row; int *qq_col = luf->qq_col; int *sv_ind = luf->sv_ind; double *sv_val = luf->sv_val; int *sv_prev = luf->sv_prev; int *sv_next = luf->sv_next; double *vr_max = luf->vr_max; int *rs_head = luf->rs_head; int *rs_prev = luf->rs_prev; int *rs_next = luf->rs_next; int *cs_head = luf->cs_head; int *cs_prev = luf->cs_prev; int *cs_next = luf->cs_next; int *flag = luf->flag; double *work = luf->work; int ret = 0; int i, i_ptr, j, j_beg, j_end, k, len, nnz, sv_beg, sv_end, ptr; double big, val; /* free all locations of the sparse vector area */ sv_beg = 1; sv_end = luf->sv_size + 1; /* (row-wise representation of the matrix F is not initialized, because it is not used at the factorization stage) */ /* build the matrix F in column-wise format (initially F = I) */ for (j = 1; j <= n; j++) { fc_ptr[j] = sv_end; fc_len[j] = 0; } /* clear rows of the matrix V; clear the flag array */ for (i = 1; i <= n; i++) vr_len[i] = vr_cap[i] = 0, flag[i] = 0; /* build the matrix V in column-wise format (initially V = A); count non-zeros in rows of this matrix; count total number of non-zeros; compute largest of absolute values of elements */ nnz = 0; big = 0.0; for (j = 1; j <= n; j++) { int *rn = pp_row; double *aj = work; /* obtain j-th column of the matrix A */ len = col(info, j, rn, aj); if (!(0 <= len && len <= n)) xfault("luf_factorize: j = %d; len = %d; invalid column len" "gth\n", j, len); /* check for free locations */ if (sv_end - sv_beg < len) { /* overflow of the sparse vector area */ ret = 1; goto done; } /* set pointer to the j-th column */ vc_ptr[j] = sv_beg; /* set length of the j-th column */ vc_len[j] = vc_cap[j] = len; /* count total number of non-zeros */ nnz += len; /* walk through elements of the j-th column */ for (ptr = 1; ptr <= len; ptr++) { /* get row index and numerical value of a[i,j] */ i = rn[ptr]; val = aj[ptr]; if (!(1 <= i && i <= n)) xfault("luf_factorize: i = %d; j = %d; invalid row index" "\n", i, j); if (flag[i]) xfault("luf_factorize: i = %d; j = %d; duplicate element" " not allowed\n", i, j); if (val == 0.0) xfault("luf_factorize: i = %d; j = %d; zero element not " "allowed\n", i, j); /* add new element v[i,j] = a[i,j] to j-th column */ sv_ind[sv_beg] = i; sv_val[sv_beg] = val; sv_beg++; /* big := max(big, |a[i,j]|) */ if (val < 0.0) val = - val; if (big < val) big = val; /* mark non-zero in the i-th position of the j-th column */ flag[i] = 1; /* increase length of the i-th row */ vr_cap[i]++; } /* reset all non-zero marks */ for (ptr = 1; ptr <= len; ptr++) flag[rn[ptr]] = 0; } /* allocate rows of the matrix V */ for (i = 1; i <= n; i++) { /* get length of the i-th row */ len = vr_cap[i]; /* check for free locations */ if (sv_end - sv_beg < len) { /* overflow of the sparse vector area */ ret = 1; goto done; } /* set pointer to the i-th row */ vr_ptr[i] = sv_beg; /* reserve locations for the i-th row */ sv_beg += len; } /* build the matrix V in row-wise format using representation of this matrix in column-wise format */ for (j = 1; j <= n; j++) { /* walk through elements of the j-th column */ j_beg = vc_ptr[j]; j_end = j_beg + vc_len[j] - 1; for (k = j_beg; k <= j_end; k++) { /* get row index and numerical value of v[i,j] */ i = sv_ind[k]; val = sv_val[k]; /* store element in the i-th row */ i_ptr = vr_ptr[i] + vr_len[i]; sv_ind[i_ptr] = j; sv_val[i_ptr] = val; /* increase count of the i-th row */ vr_len[i]++; } } /* initialize the matrices P and Q (initially P = Q = I) */ for (k = 1; k <= n; k++) pp_row[k] = pp_col[k] = qq_row[k] = qq_col[k] = k; /* set sva partitioning pointers */ luf->sv_beg = sv_beg; luf->sv_end = sv_end; /* the initial physical order of rows and columns of the matrix V is n+1, ..., n+n, 1, ..., n (firstly columns, then rows) */ luf->sv_head = n+1; luf->sv_tail = n; for (i = 1; i <= n; i++) { sv_prev[i] = i-1; sv_next[i] = i+1; } sv_prev[1] = n+n; sv_next[n] = 0; for (j = 1; j <= n; j++) { sv_prev[n+j] = n+j-1; sv_next[n+j] = n+j+1; } sv_prev[n+1] = 0; sv_next[n+n] = 1; /* clear working arrays */ for (k = 1; k <= n; k++) { flag[k] = 0; work[k] = 0.0; } /* initialize some statistics */ luf->nnz_a = nnz; luf->nnz_f = 0; luf->nnz_v = nnz; luf->max_a = big; luf->big_v = big; luf->rank = -1; /* initially the active submatrix is the entire matrix V */ /* largest of absolute values of elements in each active row is unknown yet */ for (i = 1; i <= n; i++) vr_max[i] = -1.0; /* build linked lists of active rows */ for (len = 0; len <= n; len++) rs_head[len] = 0; for (i = 1; i <= n; i++) { len = vr_len[i]; rs_prev[i] = 0; rs_next[i] = rs_head[len]; if (rs_next[i] != 0) rs_prev[rs_next[i]] = i; rs_head[len] = i; } /* build linked lists of active columns */ for (len = 0; len <= n; len++) cs_head[len] = 0; for (j = 1; j <= n; j++) { len = vc_len[j]; cs_prev[j] = 0; cs_next[j] = cs_head[len]; if (cs_next[j] != 0) cs_prev[cs_next[j]] = j; cs_head[len] = j; } done: /* return to the factorizing routine */ return ret; } /*********************************************************************** * find_pivot - choose a pivot element * * This routine chooses a pivot element in the active submatrix of the * matrix U = P*V*Q. * * It is assumed that on entry the matrix U has the following partially * triangularized form: * * 1 k n * 1 x x x x x x x x x x * . x x x x x x x x x * . . x x x x x x x x * . . . x x x x x x x * k . . . . * * * * * * * . . . . * * * * * * * . . . . * * * * * * * . . . . * * * * * * * . . . . * * * * * * * n . . . . * * * * * * * * where rows and columns k, k+1, ..., n belong to the active submatrix * (elements of the active submatrix are marked by '*'). * * Since the matrix U = P*V*Q is not stored, the routine works with the * matrix V. It is assumed that the row-wise representation corresponds * to the matrix V, but the column-wise representation corresponds to * the active submatrix of the matrix V, i.e. elements of the matrix V, * which doesn't belong to the active submatrix, are missing from the * column linked lists. It is also assumed that each active row of the * matrix V is in the set R[len], where len is number of non-zeros in * the row, and each active column of the matrix V is in the set C[len], * where len is number of non-zeros in the column (in the latter case * only elements of the active submatrix are counted; such elements are * marked by '*' on the figure above). * * For the reason of numerical stability the routine applies so called * threshold pivoting proposed by J.Reid. It is assumed that an element * v[i,j] can be selected as a pivot candidate if it is not very small * (in absolute value) among other elements in the same row, i.e. if it * satisfies to the stability condition |v[i,j]| >= tol * max|v[i,*]|, * where 0 < tol < 1 is a given tolerance. * * In order to keep sparsity of the matrix V the routine uses Markowitz * strategy, trying to choose such element v[p,q], which satisfies to * the stability condition (see above) and has smallest Markowitz cost * (nr[p]-1) * (nc[q]-1), where nr[p] and nc[q] are numbers of non-zero * elements, respectively, in the p-th row and in the q-th column of the * active submatrix. * * In order to reduce the search, i.e. not to walk through all elements * of the active submatrix, the routine exploits a technique proposed by * I.Duff. This technique is based on using the sets R[len] and C[len] * of active rows and columns. * * If the pivot element v[p,q] has been chosen, the routine stores its * indices to the locations *p and *q and returns zero. Otherwise, if * the active submatrix is empty and therefore the pivot element can't * be chosen, the routine returns non-zero. */ static int find_pivot(LUF *luf, int *_p, int *_q) { int n = luf->n; int *vr_ptr = luf->vr_ptr; int *vr_len = luf->vr_len; int *vc_ptr = luf->vc_ptr; int *vc_len = luf->vc_len; int *sv_ind = luf->sv_ind; double *sv_val = luf->sv_val; double *vr_max = luf->vr_max; int *rs_head = luf->rs_head; int *rs_next = luf->rs_next; int *cs_head = luf->cs_head; int *cs_prev = luf->cs_prev; int *cs_next = luf->cs_next; double piv_tol = luf->piv_tol; int piv_lim = luf->piv_lim; int suhl = luf->suhl; int p, q, len, i, i_beg, i_end, i_ptr, j, j_beg, j_end, j_ptr, ncand, next_j, min_p, min_q, min_len; double best, cost, big, temp; /* initially no pivot candidates have been found so far */ p = q = 0, best = DBL_MAX, ncand = 0; /* if in the active submatrix there is a column that has the only non-zero (column singleton), choose it as pivot */ j = cs_head[1]; if (j != 0) { xassert(vc_len[j] == 1); p = sv_ind[vc_ptr[j]], q = j; goto done; } /* if in the active submatrix there is a row that has the only non-zero (row singleton), choose it as pivot */ i = rs_head[1]; if (i != 0) { xassert(vr_len[i] == 1); p = i, q = sv_ind[vr_ptr[i]]; goto done; } /* there are no singletons in the active submatrix; walk through other non-empty rows and columns */ for (len = 2; len <= n; len++) { /* consider active columns that have len non-zeros */ for (j = cs_head[len]; j != 0; j = next_j) { /* the j-th column has len non-zeros */ j_beg = vc_ptr[j]; j_end = j_beg + vc_len[j] - 1; /* save pointer to the next column with the same length */ next_j = cs_next[j]; /* find an element in the j-th column, which is placed in a row with minimal number of non-zeros and satisfies to the stability condition (such element may not exist) */ min_p = min_q = 0, min_len = INT_MAX; for (j_ptr = j_beg; j_ptr <= j_end; j_ptr++) { /* get row index of v[i,j] */ i = sv_ind[j_ptr]; i_beg = vr_ptr[i]; i_end = i_beg + vr_len[i] - 1; /* if the i-th row is not shorter than that one, where minimal element is currently placed, skip v[i,j] */ if (vr_len[i] >= min_len) continue; /* determine the largest of absolute values of elements in the i-th row */ big = vr_max[i]; if (big < 0.0) { /* the largest value is unknown yet; compute it */ for (i_ptr = i_beg; i_ptr <= i_end; i_ptr++) { temp = sv_val[i_ptr]; if (temp < 0.0) temp = - temp; if (big < temp) big = temp; } vr_max[i] = big; } /* find v[i,j] in the i-th row */ for (i_ptr = vr_ptr[i]; sv_ind[i_ptr] != j; i_ptr++); xassert(i_ptr <= i_end); /* if v[i,j] doesn't satisfy to the stability condition, skip it */ temp = sv_val[i_ptr]; if (temp < 0.0) temp = - temp; if (temp < piv_tol * big) continue; /* v[i,j] is better than the current minimal element */ min_p = i, min_q = j, min_len = vr_len[i]; /* if Markowitz cost of the current minimal element is not greater than (len-1)**2, it can be chosen right now; this heuristic reduces the search and works well in many cases */ if (min_len <= len) { p = min_p, q = min_q; goto done; } } /* the j-th column has been scanned */ if (min_p != 0) { /* the minimal element is a next pivot candidate */ ncand++; /* compute its Markowitz cost */ cost = (double)(min_len - 1) * (double)(len - 1); /* choose between the minimal element and the current candidate */ if (cost < best) p = min_p, q = min_q, best = cost; /* if piv_lim candidates have been considered, there are doubts that a much better candidate exists; therefore it's time to terminate the search */ if (ncand == piv_lim) goto done; } else { /* the j-th column has no elements, which satisfy to the stability condition; Uwe Suhl suggests to exclude such column from the further consideration until it becomes a column singleton; in hard cases this significantly reduces a time needed for pivot searching */ if (suhl) { /* remove the j-th column from the active set */ if (cs_prev[j] == 0) cs_head[len] = cs_next[j]; else cs_next[cs_prev[j]] = cs_next[j]; if (cs_next[j] == 0) /* nop */; else cs_prev[cs_next[j]] = cs_prev[j]; /* the following assignment is used to avoid an error when the routine eliminate (see below) will try to remove the j-th column from the active set */ cs_prev[j] = cs_next[j] = j; } } } /* consider active rows that have len non-zeros */ for (i = rs_head[len]; i != 0; i = rs_next[i]) { /* the i-th row has len non-zeros */ i_beg = vr_ptr[i]; i_end = i_beg + vr_len[i] - 1; /* determine the largest of absolute values of elements in the i-th row */ big = vr_max[i]; if (big < 0.0) { /* the largest value is unknown yet; compute it */ for (i_ptr = i_beg; i_ptr <= i_end; i_ptr++) { temp = sv_val[i_ptr]; if (temp < 0.0) temp = - temp; if (big < temp) big = temp; } vr_max[i] = big; } /* find an element in the i-th row, which is placed in a column with minimal number of non-zeros and satisfies to the stability condition (such element always exists) */ min_p = min_q = 0, min_len = INT_MAX; for (i_ptr = i_beg; i_ptr <= i_end; i_ptr++) { /* get column index of v[i,j] */ j = sv_ind[i_ptr]; /* if the j-th column is not shorter than that one, where minimal element is currently placed, skip v[i,j] */ if (vc_len[j] >= min_len) continue; /* if v[i,j] doesn't satisfy to the stability condition, skip it */ temp = sv_val[i_ptr]; if (temp < 0.0) temp = - temp; if (temp < piv_tol * big) continue; /* v[i,j] is better than the current minimal element */ min_p = i, min_q = j, min_len = vc_len[j]; /* if Markowitz cost of the current minimal element is not greater than (len-1)**2, it can be chosen right now; this heuristic reduces the search and works well in many cases */ if (min_len <= len) { p = min_p, q = min_q; goto done; } } /* the i-th row has been scanned */ if (min_p != 0) { /* the minimal element is a next pivot candidate */ ncand++; /* compute its Markowitz cost */ cost = (double)(len - 1) * (double)(min_len - 1); /* choose between the minimal element and the current candidate */ if (cost < best) p = min_p, q = min_q, best = cost; /* if piv_lim candidates have been considered, there are doubts that a much better candidate exists; therefore it's time to terminate the search */ if (ncand == piv_lim) goto done; } else { /* this can't be because this can never be */ xassert(min_p != min_p); } } } done: /* bring the pivot to the factorizing routine */ *_p = p, *_q = q; return (p == 0); } /*********************************************************************** * eliminate - perform gaussian elimination. * * This routine performs elementary gaussian transformations in order * to eliminate subdiagonal elements in the k-th column of the matrix * U = P*V*Q using the pivot element u[k,k], where k is the number of * the current elimination step. * * The parameters p and q are, respectively, row and column indices of * the element v[p,q], which corresponds to the element u[k,k]. * * Each time when the routine applies the elementary transformation to * a non-pivot row of the matrix V, it stores the corresponding element * to the matrix F in order to keep the main equality A = F*V. * * The routine assumes that on entry the matrices L = P*F*inv(P) and * U = P*V*Q are the following: * * 1 k 1 k n * 1 1 . . . . . . . . . 1 x x x x x x x x x x * x 1 . . . . . . . . . x x x x x x x x x * x x 1 . . . . . . . . . x x x x x x x x * x x x 1 . . . . . . . . . x x x x x x x * k x x x x 1 . . . . . k . . . . * * * * * * * x x x x _ 1 . . . . . . . . # * * * * * * x x x x _ . 1 . . . . . . . # * * * * * * x x x x _ . . 1 . . . . . . # * * * * * * x x x x _ . . . 1 . . . . . # * * * * * * n x x x x _ . . . . 1 n . . . . # * * * * * * * matrix L matrix U * * where rows and columns of the matrix U with numbers k, k+1, ..., n * form the active submatrix (eliminated elements are marked by '#' and * other elements of the active submatrix are marked by '*'). Note that * each eliminated non-zero element u[i,k] of the matrix U gives the * corresponding element l[i,k] of the matrix L (marked by '_'). * * Actually all operations are performed on the matrix V. Should note * that the row-wise representation corresponds to the matrix V, but the * column-wise representation corresponds to the active submatrix of the * matrix V, i.e. elements of the matrix V, which doesn't belong to the * active submatrix, are missing from the column linked lists. * * Let u[k,k] = v[p,q] be the pivot. In order to eliminate subdiagonal * elements u[i',k] = v[i,q], i' = k+1, k+2, ..., n, the routine applies * the following elementary gaussian transformations: * * (i-th row of V) := (i-th row of V) - f[i,p] * (p-th row of V), * * where f[i,p] = v[i,q] / v[p,q] is a gaussian multiplier. * * Additionally, in order to keep the main equality A = F*V, each time * when the routine applies the transformation to i-th row of the matrix * V, it also adds f[i,p] as a new element to the matrix F. * * IMPORTANT: On entry the working arrays flag and work should contain * zeros. This status is provided by the routine on exit. * * If no error occured, the routine returns zero. Otherwise, in case of * overflow of the sparse vector area, the routine returns non-zero. */ static int eliminate(LUF *luf, int p, int q) { int n = luf->n; int *fc_ptr = luf->fc_ptr; int *fc_len = luf->fc_len; int *vr_ptr = luf->vr_ptr; int *vr_len = luf->vr_len; int *vr_cap = luf->vr_cap; double *vr_piv = luf->vr_piv; int *vc_ptr = luf->vc_ptr; int *vc_len = luf->vc_len; int *vc_cap = luf->vc_cap; int *sv_ind = luf->sv_ind; double *sv_val = luf->sv_val; int *sv_prev = luf->sv_prev; int *sv_next = luf->sv_next; double *vr_max = luf->vr_max; int *rs_head = luf->rs_head; int *rs_prev = luf->rs_prev; int *rs_next = luf->rs_next; int *cs_head = luf->cs_head; int *cs_prev = luf->cs_prev; int *cs_next = luf->cs_next; int *flag = luf->flag; double *work = luf->work; double eps_tol = luf->eps_tol; /* at this stage the row-wise representation of the matrix F is not used, so fr_len can be used as a working array */ int *ndx = luf->fr_len; int ret = 0; int len, fill, i, i_beg, i_end, i_ptr, j, j_beg, j_end, j_ptr, k, p_beg, p_end, p_ptr, q_beg, q_end, q_ptr; double fip, val, vpq, temp; xassert(1 <= p && p <= n); xassert(1 <= q && q <= n); /* remove the p-th (pivot) row from the active set; this row will never return there */ if (rs_prev[p] == 0) rs_head[vr_len[p]] = rs_next[p]; else rs_next[rs_prev[p]] = rs_next[p]; if (rs_next[p] == 0) ; else rs_prev[rs_next[p]] = rs_prev[p]; /* remove the q-th (pivot) column from the active set; this column will never return there */ if (cs_prev[q] == 0) cs_head[vc_len[q]] = cs_next[q]; else cs_next[cs_prev[q]] = cs_next[q]; if (cs_next[q] == 0) ; else cs_prev[cs_next[q]] = cs_prev[q]; /* find the pivot v[p,q] = u[k,k] in the p-th row */ p_beg = vr_ptr[p]; p_end = p_beg + vr_len[p] - 1; for (p_ptr = p_beg; sv_ind[p_ptr] != q; p_ptr++) /* nop */; xassert(p_ptr <= p_end); /* store value of the pivot */ vpq = (vr_piv[p] = sv_val[p_ptr]); /* remove the pivot from the p-th row */ sv_ind[p_ptr] = sv_ind[p_end]; sv_val[p_ptr] = sv_val[p_end]; vr_len[p]--; p_end--; /* find the pivot v[p,q] = u[k,k] in the q-th column */ q_beg = vc_ptr[q]; q_end = q_beg + vc_len[q] - 1; for (q_ptr = q_beg; sv_ind[q_ptr] != p; q_ptr++) /* nop */; xassert(q_ptr <= q_end); /* remove the pivot from the q-th column */ sv_ind[q_ptr] = sv_ind[q_end]; vc_len[q]--; q_end--; /* walk through the p-th (pivot) row, which doesn't contain the pivot v[p,q] already, and do the following... */ for (p_ptr = p_beg; p_ptr <= p_end; p_ptr++) { /* get column index of v[p,j] */ j = sv_ind[p_ptr]; /* store v[p,j] to the working array */ flag[j] = 1; work[j] = sv_val[p_ptr]; /* remove the j-th column from the active set; this column will return there later with new length */ if (cs_prev[j] == 0) cs_head[vc_len[j]] = cs_next[j]; else cs_next[cs_prev[j]] = cs_next[j]; if (cs_next[j] == 0) ; else cs_prev[cs_next[j]] = cs_prev[j]; /* find v[p,j] in the j-th column */ j_beg = vc_ptr[j]; j_end = j_beg + vc_len[j] - 1; for (j_ptr = j_beg; sv_ind[j_ptr] != p; j_ptr++) /* nop */; xassert(j_ptr <= j_end); /* since v[p,j] leaves the active submatrix, remove it from the j-th column; however, v[p,j] is kept in the p-th row */ sv_ind[j_ptr] = sv_ind[j_end]; vc_len[j]--; } /* walk through the q-th (pivot) column, which doesn't contain the pivot v[p,q] already, and perform gaussian elimination */ while (q_beg <= q_end) { /* element v[i,q] should be eliminated */ /* get row index of v[i,q] */ i = sv_ind[q_beg]; /* remove the i-th row from the active set; later this row will return there with new length */ if (rs_prev[i] == 0) rs_head[vr_len[i]] = rs_next[i]; else rs_next[rs_prev[i]] = rs_next[i]; if (rs_next[i] == 0) ; else rs_prev[rs_next[i]] = rs_prev[i]; /* find v[i,q] in the i-th row */ i_beg = vr_ptr[i]; i_end = i_beg + vr_len[i] - 1; for (i_ptr = i_beg; sv_ind[i_ptr] != q; i_ptr++) /* nop */; xassert(i_ptr <= i_end); /* compute gaussian multiplier f[i,p] = v[i,q] / v[p,q] */ fip = sv_val[i_ptr] / vpq; /* since v[i,q] should be eliminated, remove it from the i-th row */ sv_ind[i_ptr] = sv_ind[i_end]; sv_val[i_ptr] = sv_val[i_end]; vr_len[i]--; i_end--; /* and from the q-th column */ sv_ind[q_beg] = sv_ind[q_end]; vc_len[q]--; q_end--; /* perform gaussian transformation: (i-th row) := (i-th row) - f[i,p] * (p-th row) note that now the p-th row, which is in the working array, doesn't contain the pivot v[p,q], and the i-th row doesn't contain the eliminated element v[i,q] */ /* walk through the i-th row and transform existing non-zero elements */ fill = vr_len[p]; for (i_ptr = i_beg; i_ptr <= i_end; i_ptr++) { /* get column index of v[i,j] */ j = sv_ind[i_ptr]; /* v[i,j] := v[i,j] - f[i,p] * v[p,j] */ if (flag[j]) { /* v[p,j] != 0 */ temp = (sv_val[i_ptr] -= fip * work[j]); if (temp < 0.0) temp = - temp; flag[j] = 0; fill--; /* since both v[i,j] and v[p,j] exist */ if (temp == 0.0 || temp < eps_tol) { /* new v[i,j] is closer to zero; replace it by exact zero, i.e. remove it from the active submatrix */ /* remove v[i,j] from the i-th row */ sv_ind[i_ptr] = sv_ind[i_end]; sv_val[i_ptr] = sv_val[i_end]; vr_len[i]--; i_ptr--; i_end--; /* find v[i,j] in the j-th column */ j_beg = vc_ptr[j]; j_end = j_beg + vc_len[j] - 1; for (j_ptr = j_beg; sv_ind[j_ptr] != i; j_ptr++); xassert(j_ptr <= j_end); /* remove v[i,j] from the j-th column */ sv_ind[j_ptr] = sv_ind[j_end]; vc_len[j]--; } else { /* v_big := max(v_big, |v[i,j]|) */ if (luf->big_v < temp) luf->big_v = temp; } } } /* now flag is the pattern of the set v[p,*] \ v[i,*], and fill is number of non-zeros in this set; therefore up to fill new non-zeros may appear in the i-th row */ if (vr_len[i] + fill > vr_cap[i]) { /* enlarge the i-th row */ if (luf_enlarge_row(luf, i, vr_len[i] + fill)) { /* overflow of the sparse vector area */ ret = 1; goto done; } /* defragmentation may change row and column pointers of the matrix V */ p_beg = vr_ptr[p]; p_end = p_beg + vr_len[p] - 1; q_beg = vc_ptr[q]; q_end = q_beg + vc_len[q] - 1; } /* walk through the p-th (pivot) row and create new elements of the i-th row that appear due to fill-in; column indices of these new elements are accumulated in the array ndx */ len = 0; for (p_ptr = p_beg; p_ptr <= p_end; p_ptr++) { /* get column index of v[p,j], which may cause fill-in */ j = sv_ind[p_ptr]; if (flag[j]) { /* compute new non-zero v[i,j] = 0 - f[i,p] * v[p,j] */ temp = (val = - fip * work[j]); if (temp < 0.0) temp = - temp; if (temp == 0.0 || temp < eps_tol) /* if v[i,j] is closer to zero; just ignore it */; else { /* add v[i,j] to the i-th row */ i_ptr = vr_ptr[i] + vr_len[i]; sv_ind[i_ptr] = j; sv_val[i_ptr] = val; vr_len[i]++; /* remember column index of v[i,j] */ ndx[++len] = j; /* big_v := max(big_v, |v[i,j]|) */ if (luf->big_v < temp) luf->big_v = temp; } } else { /* there is no fill-in, because v[i,j] already exists in the i-th row; restore the flag of the element v[p,j], which was reset before */ flag[j] = 1; } } /* add new non-zeros v[i,j] to the corresponding columns */ for (k = 1; k <= len; k++) { /* get column index of new non-zero v[i,j] */ j = ndx[k]; /* one free location is needed in the j-th column */ if (vc_len[j] + 1 > vc_cap[j]) { /* enlarge the j-th column */ if (luf_enlarge_col(luf, j, vc_len[j] + 10)) { /* overflow of the sparse vector area */ ret = 1; goto done; } /* defragmentation may change row and column pointers of the matrix V */ p_beg = vr_ptr[p]; p_end = p_beg + vr_len[p] - 1; q_beg = vc_ptr[q]; q_end = q_beg + vc_len[q] - 1; } /* add new non-zero v[i,j] to the j-th column */ j_ptr = vc_ptr[j] + vc_len[j]; sv_ind[j_ptr] = i; vc_len[j]++; } /* now the i-th row has been completely transformed, therefore it can return to the active set with new length */ rs_prev[i] = 0; rs_next[i] = rs_head[vr_len[i]]; if (rs_next[i] != 0) rs_prev[rs_next[i]] = i; rs_head[vr_len[i]] = i; /* the largest of absolute values of elements in the i-th row is currently unknown */ vr_max[i] = -1.0; /* at least one free location is needed to store the gaussian multiplier */ if (luf->sv_end - luf->sv_beg < 1) { /* there are no free locations at all; defragment SVA */ luf_defrag_sva(luf); if (luf->sv_end - luf->sv_beg < 1) { /* overflow of the sparse vector area */ ret = 1; goto done; } /* defragmentation may change row and column pointers of the matrix V */ p_beg = vr_ptr[p]; p_end = p_beg + vr_len[p] - 1; q_beg = vc_ptr[q]; q_end = q_beg + vc_len[q] - 1; } /* add the element f[i,p], which is the gaussian multiplier, to the matrix F */ luf->sv_end--; sv_ind[luf->sv_end] = i; sv_val[luf->sv_end] = fip; fc_len[p]++; /* end of elimination loop */ } /* at this point the q-th (pivot) column should be empty */ xassert(vc_len[q] == 0); /* reset capacity of the q-th column */ vc_cap[q] = 0; /* remove node of the q-th column from the addressing list */ k = n + q; if (sv_prev[k] == 0) luf->sv_head = sv_next[k]; else sv_next[sv_prev[k]] = sv_next[k]; if (sv_next[k] == 0) luf->sv_tail = sv_prev[k]; else sv_prev[sv_next[k]] = sv_prev[k]; /* the p-th column of the matrix F has been completely built; set its pointer */ fc_ptr[p] = luf->sv_end; /* walk through the p-th (pivot) row and do the following... */ for (p_ptr = p_beg; p_ptr <= p_end; p_ptr++) { /* get column index of v[p,j] */ j = sv_ind[p_ptr]; /* erase v[p,j] from the working array */ flag[j] = 0; work[j] = 0.0; /* the j-th column has been completely transformed, therefore it can return to the active set with new length; however the special case c_prev[j] = c_next[j] = j means that the routine find_pivot excluded the j-th column from the active set due to Uwe Suhl's rule, and therefore in this case the column can return to the active set only if it is a column singleton */ if (!(vc_len[j] != 1 && cs_prev[j] == j && cs_next[j] == j)) { cs_prev[j] = 0; cs_next[j] = cs_head[vc_len[j]]; if (cs_next[j] != 0) cs_prev[cs_next[j]] = j; cs_head[vc_len[j]] = j; } } done: /* return to the factorizing routine */ return ret; } /*********************************************************************** * build_v_cols - build the matrix V in column-wise format * * This routine builds the column-wise representation of the matrix V * using its row-wise representation. * * If no error occured, the routine returns zero. Otherwise, in case of * overflow of the sparse vector area, the routine returns non-zero. */ static int build_v_cols(LUF *luf) { int n = luf->n; int *vr_ptr = luf->vr_ptr; int *vr_len = luf->vr_len; int *vc_ptr = luf->vc_ptr; int *vc_len = luf->vc_len; int *vc_cap = luf->vc_cap; int *sv_ind = luf->sv_ind; double *sv_val = luf->sv_val; int *sv_prev = luf->sv_prev; int *sv_next = luf->sv_next; int ret = 0; int i, i_beg, i_end, i_ptr, j, j_ptr, k, nnz; /* it is assumed that on entry all columns of the matrix V are empty, i.e. vc_len[j] = vc_cap[j] = 0 for all j = 1, ..., n, and have been removed from the addressing list */ /* count non-zeros in columns of the matrix V; count total number of non-zeros in this matrix */ nnz = 0; for (i = 1; i <= n; i++) { /* walk through elements of the i-th row and count non-zeros in the corresponding columns */ i_beg = vr_ptr[i]; i_end = i_beg + vr_len[i] - 1; for (i_ptr = i_beg; i_ptr <= i_end; i_ptr++) vc_cap[sv_ind[i_ptr]]++; /* count total number of non-zeros */ nnz += vr_len[i]; } /* store total number of non-zeros */ luf->nnz_v = nnz; /* check for free locations */ if (luf->sv_end - luf->sv_beg < nnz) { /* overflow of the sparse vector area */ ret = 1; goto done; } /* allocate columns of the matrix V */ for (j = 1; j <= n; j++) { /* set pointer to the j-th column */ vc_ptr[j] = luf->sv_beg; /* reserve locations for the j-th column */ luf->sv_beg += vc_cap[j]; } /* build the matrix V in column-wise format using this matrix in row-wise format */ for (i = 1; i <= n; i++) { /* walk through elements of the i-th row */ i_beg = vr_ptr[i]; i_end = i_beg + vr_len[i] - 1; for (i_ptr = i_beg; i_ptr <= i_end; i_ptr++) { /* get column index */ j = sv_ind[i_ptr]; /* store element in the j-th column */ j_ptr = vc_ptr[j] + vc_len[j]; sv_ind[j_ptr] = i; sv_val[j_ptr] = sv_val[i_ptr]; /* increase length of the j-th column */ vc_len[j]++; } } /* now columns are placed in the sparse vector area behind rows in the order n+1, n+2, ..., n+n; so insert column nodes in the addressing list using this order */ for (k = n+1; k <= n+n; k++) { sv_prev[k] = k-1; sv_next[k] = k+1; } sv_prev[n+1] = luf->sv_tail; sv_next[luf->sv_tail] = n+1; sv_next[n+n] = 0; luf->sv_tail = n+n; done: /* return to the factorizing routine */ return ret; } /*********************************************************************** * build_f_rows - build the matrix F in row-wise format * * This routine builds the row-wise representation of the matrix F using * its column-wise representation. * * If no error occured, the routine returns zero. Otherwise, in case of * overflow of the sparse vector area, the routine returns non-zero. */ static int build_f_rows(LUF *luf) { int n = luf->n; int *fr_ptr = luf->fr_ptr; int *fr_len = luf->fr_len; int *fc_ptr = luf->fc_ptr; int *fc_len = luf->fc_len; int *sv_ind = luf->sv_ind; double *sv_val = luf->sv_val; int ret = 0; int i, j, j_beg, j_end, j_ptr, ptr, nnz; /* clear rows of the matrix F */ for (i = 1; i <= n; i++) fr_len[i] = 0; /* count non-zeros in rows of the matrix F; count total number of non-zeros in this matrix */ nnz = 0; for (j = 1; j <= n; j++) { /* walk through elements of the j-th column and count non-zeros in the corresponding rows */ j_beg = fc_ptr[j]; j_end = j_beg + fc_len[j] - 1; for (j_ptr = j_beg; j_ptr <= j_end; j_ptr++) fr_len[sv_ind[j_ptr]]++; /* increase total number of non-zeros */ nnz += fc_len[j]; } /* store total number of non-zeros */ luf->nnz_f = nnz; /* check for free locations */ if (luf->sv_end - luf->sv_beg < nnz) { /* overflow of the sparse vector area */ ret = 1; goto done; } /* allocate rows of the matrix F */ for (i = 1; i <= n; i++) { /* set pointer to the end of the i-th row; later this pointer will be set to the beginning of the i-th row */ fr_ptr[i] = luf->sv_end; /* reserve locations for the i-th row */ luf->sv_end -= fr_len[i]; } /* build the matrix F in row-wise format using this matrix in column-wise format */ for (j = 1; j <= n; j++) { /* walk through elements of the j-th column */ j_beg = fc_ptr[j]; j_end = j_beg + fc_len[j] - 1; for (j_ptr = j_beg; j_ptr <= j_end; j_ptr++) { /* get row index */ i = sv_ind[j_ptr]; /* store element in the i-th row */ ptr = --fr_ptr[i]; sv_ind[ptr] = j; sv_val[ptr] = sv_val[j_ptr]; } } done: /* return to the factorizing routine */ return ret; } /*********************************************************************** * NAME * * luf_factorize - compute LU-factorization * * SYNOPSIS * * #include "glpluf.h" * int luf_factorize(LUF *luf, int n, int (*col)(void *info, int j, * int ind[], double val[]), void *info); * * DESCRIPTION * * The routine luf_factorize computes LU-factorization of a specified * square matrix A. * * The parameter luf specifies LU-factorization program object created * by the routine luf_create_it. * * The parameter n specifies the order of A, n > 0. * * The formal routine col specifies the matrix A to be factorized. To * obtain j-th column of A the routine luf_factorize calls the routine * col with the parameter j (1 <= j <= n). In response the routine col * should store row indices and numerical values of non-zero elements * of j-th column of A to locations ind[1,...,len] and val[1,...,len], * respectively, where len is the number of non-zeros in j-th column * returned on exit. Neither zero nor duplicate elements are allowed. * * The parameter info is a transit pointer passed to the routine col. * * RETURNS * * 0 LU-factorization has been successfully computed. * * LUF_ESING * The specified matrix is singular within the working precision. * (On some elimination step the active submatrix is exactly zero, * so no pivot can be chosen.) * * LUF_ECOND * The specified matrix is ill-conditioned. * (On some elimination step too intensive growth of elements of the * active submatix has been detected.) * * If matrix A is well scaled, the return code LUF_ECOND may also mean * that the threshold pivoting tolerance piv_tol should be increased. * * In case of non-zero return code the factorization becomes invalid. * It should not be used in other operations until the cause of failure * has been eliminated and the factorization has been recomputed again * with the routine luf_factorize. * * REPAIRING SINGULAR MATRIX * * If the routine luf_factorize returns non-zero code, it provides all * necessary information that can be used for "repairing" the matrix A, * where "repairing" means replacing linearly dependent columns of the * matrix A by appropriate columns of the unity matrix. This feature is * needed when this routine is used for factorizing the basis matrix * within the simplex method procedure. * * On exit linearly dependent columns of the (partially transformed) * matrix U have numbers rank+1, rank+2, ..., n, where rank is estimated * rank of the matrix A stored by the routine to the member luf->rank. * The correspondence between columns of A and U is the same as between * columns of V and U. Thus, linearly dependent columns of the matrix A * have numbers qq_col[rank+1], qq_col[rank+2], ..., qq_col[n], where * qq_col is the column-like representation of the permutation matrix Q. * It is understood that each j-th linearly dependent column of the * matrix U should be replaced by the unity vector, where all elements * are zero except the unity diagonal element u[j,j]. On the other hand * j-th row of the matrix U corresponds to the row of the matrix V (and * therefore of the matrix A) with the number pp_row[j], where pp_row is * the row-like representation of the permutation matrix P. Thus, each * j-th linearly dependent column of the matrix U should be replaced by * column of the unity matrix with the number pp_row[j]. * * The code that repairs the matrix A may look like follows: * * for (j = rank+1; j <= n; j++) * { replace the column qq_col[j] of the matrix A by the column * pp_row[j] of the unity matrix; * } * * where rank, pp_row, and qq_col are members of the structure LUF. */ int luf_factorize(LUF *luf, int n, int (*col)(void *info, int j, int ind[], double val[]), void *info) { int *pp_row, *pp_col, *qq_row, *qq_col; double max_gro = luf->max_gro; int i, j, k, p, q, t, ret; if (n < 1) xfault("luf_factorize: n = %d; invalid parameter\n", n); if (n > N_MAX) xfault("luf_factorize: n = %d; matrix too big\n", n); /* invalidate the factorization */ luf->valid = 0; /* reallocate arrays, if necessary */ reallocate(luf, n); pp_row = luf->pp_row; pp_col = luf->pp_col; qq_row = luf->qq_row; qq_col = luf->qq_col; /* estimate initial size of the SVA, if not specified */ if (luf->sv_size == 0 && luf->new_sva == 0) luf->new_sva = 5 * (n + 10); more: /* reallocate the sparse vector area, if required */ if (luf->new_sva > 0) { if (luf->sv_ind != NULL) xfree(luf->sv_ind); if (luf->sv_val != NULL) xfree(luf->sv_val); luf->sv_size = luf->new_sva; luf->sv_ind = xcalloc(1+luf->sv_size, sizeof(int)); luf->sv_val = xcalloc(1+luf->sv_size, sizeof(double)); luf->new_sva = 0; } /* initialize LU-factorization data structures */ if (initialize(luf, col, info)) { /* overflow of the sparse vector area */ luf->new_sva = luf->sv_size + luf->sv_size; xassert(luf->new_sva > luf->sv_size); goto more; } /* main elimination loop */ for (k = 1; k <= n; k++) { /* choose a pivot element v[p,q] */ if (find_pivot(luf, &p, &q)) { /* no pivot can be chosen, because the active submatrix is exactly zero */ luf->rank = k - 1; ret = LUF_ESING; goto done; } /* let v[p,q] correspond to u[i',j']; permute k-th and i'-th rows and k-th and j'-th columns of the matrix U = P*V*Q to move the element u[i',j'] to the position u[k,k] */ i = pp_col[p], j = qq_row[q]; xassert(k <= i && i <= n && k <= j && j <= n); /* permute k-th and i-th rows of the matrix U */ t = pp_row[k]; pp_row[i] = t, pp_col[t] = i; pp_row[k] = p, pp_col[p] = k; /* permute k-th and j-th columns of the matrix U */ t = qq_col[k]; qq_col[j] = t, qq_row[t] = j; qq_col[k] = q, qq_row[q] = k; /* eliminate subdiagonal elements of k-th column of the matrix U = P*V*Q using the pivot element u[k,k] = v[p,q] */ if (eliminate(luf, p, q)) { /* overflow of the sparse vector area */ luf->new_sva = luf->sv_size + luf->sv_size; xassert(luf->new_sva > luf->sv_size); goto more; } /* check relative growth of elements of the matrix V */ if (luf->big_v > max_gro * luf->max_a) { /* the growth is too intensive, therefore most probably the matrix A is ill-conditioned */ luf->rank = k - 1; ret = LUF_ECOND; goto done; } } /* now the matrix U = P*V*Q is upper triangular, the matrix V has been built in row-wise format, and the matrix F has been built in column-wise format */ /* defragment the sparse vector area in order to merge all free locations in one continuous extent */ luf_defrag_sva(luf); /* build the matrix V in column-wise format */ if (build_v_cols(luf)) { /* overflow of the sparse vector area */ luf->new_sva = luf->sv_size + luf->sv_size; xassert(luf->new_sva > luf->sv_size); goto more; } /* build the matrix F in row-wise format */ if (build_f_rows(luf)) { /* overflow of the sparse vector area */ luf->new_sva = luf->sv_size + luf->sv_size; xassert(luf->new_sva > luf->sv_size); goto more; } /* the LU-factorization has been successfully computed */ luf->valid = 1; luf->rank = n; ret = 0; /* if there are few free locations in the sparse vector area, try increasing its size in the future */ t = 3 * (n + luf->nnz_v) + 2 * luf->nnz_f; if (luf->sv_size < t) { luf->new_sva = luf->sv_size; while (luf->new_sva < t) { k = luf->new_sva; luf->new_sva = k + k; xassert(luf->new_sva > k); } } done: /* return to the calling program */ return ret; } /*********************************************************************** * NAME * * luf_f_solve - solve system F*x = b or F'*x = b * * SYNOPSIS * * #include "glpluf.h" * void luf_f_solve(LUF *luf, int tr, double x[]); * * DESCRIPTION * * The routine luf_f_solve solves either the system F*x = b (if the * flag tr is zero) or the system F'*x = b (if the flag tr is non-zero), * where the matrix F is a component of LU-factorization specified by * the parameter luf, F' is a matrix transposed to F. * * On entry the array x should contain elements of the right-hand side * vector b in locations x[1], ..., x[n], where n is the order of the * matrix F. On exit this array will contain elements of the solution * vector x in the same locations. */ void luf_f_solve(LUF *luf, int tr, double x[]) { int n = luf->n; int *fr_ptr = luf->fr_ptr; int *fr_len = luf->fr_len; int *fc_ptr = luf->fc_ptr; int *fc_len = luf->fc_len; int *pp_row = luf->pp_row; int *sv_ind = luf->sv_ind; double *sv_val = luf->sv_val; int i, j, k, beg, end, ptr; double xk; if (!luf->valid) xfault("luf_f_solve: LU-factorization is not valid\n"); if (!tr) { /* solve the system F*x = b */ for (j = 1; j <= n; j++) { k = pp_row[j]; xk = x[k]; if (xk != 0.0) { beg = fc_ptr[k]; end = beg + fc_len[k] - 1; for (ptr = beg; ptr <= end; ptr++) x[sv_ind[ptr]] -= sv_val[ptr] * xk; } } } else { /* solve the system F'*x = b */ for (i = n; i >= 1; i--) { k = pp_row[i]; xk = x[k]; if (xk != 0.0) { beg = fr_ptr[k]; end = beg + fr_len[k] - 1; for (ptr = beg; ptr <= end; ptr++) x[sv_ind[ptr]] -= sv_val[ptr] * xk; } } } return; } /*********************************************************************** * NAME * * luf_v_solve - solve system V*x = b or V'*x = b * * SYNOPSIS * * #include "glpluf.h" * void luf_v_solve(LUF *luf, int tr, double x[]); * * DESCRIPTION * * The routine luf_v_solve solves either the system V*x = b (if the * flag tr is zero) or the system V'*x = b (if the flag tr is non-zero), * where the matrix V is a component of LU-factorization specified by * the parameter luf, V' is a matrix transposed to V. * * On entry the array x should contain elements of the right-hand side * vector b in locations x[1], ..., x[n], where n is the order of the * matrix V. On exit this array will contain elements of the solution * vector x in the same locations. */ void luf_v_solve(LUF *luf, int tr, double x[]) { int n = luf->n; int *vr_ptr = luf->vr_ptr; int *vr_len = luf->vr_len; double *vr_piv = luf->vr_piv; int *vc_ptr = luf->vc_ptr; int *vc_len = luf->vc_len; int *pp_row = luf->pp_row; int *qq_col = luf->qq_col; int *sv_ind = luf->sv_ind; double *sv_val = luf->sv_val; double *b = luf->work; int i, j, k, beg, end, ptr; double temp; if (!luf->valid) xfault("luf_v_solve: LU-factorization is not valid\n"); for (k = 1; k <= n; k++) b[k] = x[k], x[k] = 0.0; if (!tr) { /* solve the system V*x = b */ for (k = n; k >= 1; k--) { i = pp_row[k], j = qq_col[k]; temp = b[i]; if (temp != 0.0) { x[j] = (temp /= vr_piv[i]); beg = vc_ptr[j]; end = beg + vc_len[j] - 1; for (ptr = beg; ptr <= end; ptr++) b[sv_ind[ptr]] -= sv_val[ptr] * temp; } } } else { /* solve the system V'*x = b */ for (k = 1; k <= n; k++) { i = pp_row[k], j = qq_col[k]; temp = b[j]; if (temp != 0.0) { x[i] = (temp /= vr_piv[i]); beg = vr_ptr[i]; end = beg + vr_len[i] - 1; for (ptr = beg; ptr <= end; ptr++) b[sv_ind[ptr]] -= sv_val[ptr] * temp; } } } return; } /*********************************************************************** * NAME * * luf_a_solve - solve system A*x = b or A'*x = b * * SYNOPSIS * * #include "glpluf.h" * void luf_a_solve(LUF *luf, int tr, double x[]); * * DESCRIPTION * * The routine luf_a_solve solves either the system A*x = b (if the * flag tr is zero) or the system A'*x = b (if the flag tr is non-zero), * where the parameter luf specifies LU-factorization of the matrix A, * A' is a matrix transposed to A. * * On entry the array x should contain elements of the right-hand side * vector b in locations x[1], ..., x[n], where n is the order of the * matrix A. On exit this array will contain elements of the solution * vector x in the same locations. */ void luf_a_solve(LUF *luf, int tr, double x[]) { if (!luf->valid) xfault("luf_a_solve: LU-factorization is not valid\n"); if (!tr) { /* A = F*V, therefore inv(A) = inv(V)*inv(F) */ luf_f_solve(luf, 0, x); luf_v_solve(luf, 0, x); } else { /* A' = V'*F', therefore inv(A') = inv(F')*inv(V') */ luf_v_solve(luf, 1, x); luf_f_solve(luf, 1, x); } return; } /*********************************************************************** * NAME * * luf_delete_it - delete LU-factorization * * SYNOPSIS * * #include "glpluf.h" * void luf_delete_it(LUF *luf); * * DESCRIPTION * * The routine luf_delete deletes LU-factorization specified by the * parameter luf and frees all the memory allocated to this program * object. */ void luf_delete_it(LUF *luf) { if (luf->fr_ptr != NULL) xfree(luf->fr_ptr); if (luf->fr_len != NULL) xfree(luf->fr_len); if (luf->fc_ptr != NULL) xfree(luf->fc_ptr); if (luf->fc_len != NULL) xfree(luf->fc_len); if (luf->vr_ptr != NULL) xfree(luf->vr_ptr); if (luf->vr_len != NULL) xfree(luf->vr_len); if (luf->vr_cap != NULL) xfree(luf->vr_cap); if (luf->vr_piv != NULL) xfree(luf->vr_piv); if (luf->vc_ptr != NULL) xfree(luf->vc_ptr); if (luf->vc_len != NULL) xfree(luf->vc_len); if (luf->vc_cap != NULL) xfree(luf->vc_cap); if (luf->pp_row != NULL) xfree(luf->pp_row); if (luf->pp_col != NULL) xfree(luf->pp_col); if (luf->qq_row != NULL) xfree(luf->qq_row); if (luf->qq_col != NULL) xfree(luf->qq_col); if (luf->sv_ind != NULL) xfree(luf->sv_ind); if (luf->sv_val != NULL) xfree(luf->sv_val); if (luf->sv_prev != NULL) xfree(luf->sv_prev); if (luf->sv_next != NULL) xfree(luf->sv_next); if (luf->vr_max != NULL) xfree(luf->vr_max); if (luf->rs_head != NULL) xfree(luf->rs_head); if (luf->rs_prev != NULL) xfree(luf->rs_prev); if (luf->rs_next != NULL) xfree(luf->rs_next); if (luf->cs_head != NULL) xfree(luf->cs_head); if (luf->cs_prev != NULL) xfree(luf->cs_prev); if (luf->cs_next != NULL) xfree(luf->cs_next); if (luf->flag != NULL) xfree(luf->flag); if (luf->work != NULL) xfree(luf->work); xfree(luf); return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glplpx02.c0000644000076500000240000002411013524616144025211 0ustar tamasstaff00000000000000/* glplpx02.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wlogical-op-parentheses" #endif #include "glpapi.h" /*********************************************************************** * NAME * * lpx_put_solution - store basic solution components * * SYNOPSIS * * void lpx_put_solution(glp_prob *lp, int inval, const int *p_stat, * const int *d_stat, const double *obj_val, const int r_stat[], * const double r_prim[], const double r_dual[], const int c_stat[], * const double c_prim[], const double c_dual[]) * * DESCRIPTION * * The routine lpx_put_solution stores basic solution components to the * specified problem object. * * The parameter inval is the basis factorization invalidity flag. * If this flag is clear, the current status of the basis factorization * remains unchanged. If this flag is set, the routine invalidates the * basis factorization. * * The parameter p_stat is a pointer to the status of primal basic * solution, which should be specified as follows: * * GLP_UNDEF - primal solution is undefined; * GLP_FEAS - primal solution is feasible; * GLP_INFEAS - primal solution is infeasible; * GLP_NOFEAS - no primal feasible solution exists. * * If the parameter p_stat is NULL, the current status of primal basic * solution remains unchanged. * * The parameter d_stat is a pointer to the status of dual basic * solution, which should be specified as follows: * * GLP_UNDEF - dual solution is undefined; * GLP_FEAS - dual solution is feasible; * GLP_INFEAS - dual solution is infeasible; * GLP_NOFEAS - no dual feasible solution exists. * * If the parameter d_stat is NULL, the current status of dual basic * solution remains unchanged. * * The parameter obj_val is a pointer to the objective function value. * If it is NULL, the current value of the objective function remains * unchanged. * * The array element r_stat[i], 1 <= i <= m (where m is the number of * rows in the problem object), specifies the status of i-th auxiliary * variable, which should be specified as follows: * * GLP_BS - basic variable; * GLP_NL - non-basic variable on lower bound; * GLP_NU - non-basic variable on upper bound; * GLP_NF - non-basic free variable; * GLP_NS - non-basic fixed variable. * * If the parameter r_stat is NULL, the current statuses of auxiliary * variables remain unchanged. * * The array element r_prim[i], 1 <= i <= m (where m is the number of * rows in the problem object), specifies a primal value of i-th * auxiliary variable. If the parameter r_prim is NULL, the current * primal values of auxiliary variables remain unchanged. * * The array element r_dual[i], 1 <= i <= m (where m is the number of * rows in the problem object), specifies a dual value (reduced cost) * of i-th auxiliary variable. If the parameter r_dual is NULL, the * current dual values of auxiliary variables remain unchanged. * * The array element c_stat[j], 1 <= j <= n (where n is the number of * columns in the problem object), specifies the status of j-th * structural variable, which should be specified as follows: * * GLP_BS - basic variable; * GLP_NL - non-basic variable on lower bound; * GLP_NU - non-basic variable on upper bound; * GLP_NF - non-basic free variable; * GLP_NS - non-basic fixed variable. * * If the parameter c_stat is NULL, the current statuses of structural * variables remain unchanged. * * The array element c_prim[j], 1 <= j <= n (where n is the number of * columns in the problem object), specifies a primal value of j-th * structural variable. If the parameter c_prim is NULL, the current * primal values of structural variables remain unchanged. * * The array element c_dual[j], 1 <= j <= n (where n is the number of * columns in the problem object), specifies a dual value (reduced cost) * of j-th structural variable. If the parameter c_dual is NULL, the * current dual values of structural variables remain unchanged. */ void lpx_put_solution(glp_prob *lp, int inval, const int *p_stat, const int *d_stat, const double *obj_val, const int r_stat[], const double r_prim[], const double r_dual[], const int c_stat[], const double c_prim[], const double c_dual[]) { GLPROW *row; GLPCOL *col; int i, j; /* invalidate the basis factorization, if required */ if (inval) lp->valid = 0; /* store primal status */ if (p_stat != NULL) { if (!(*p_stat == GLP_UNDEF || *p_stat == GLP_FEAS || *p_stat == GLP_INFEAS || *p_stat == GLP_NOFEAS)) xerror("lpx_put_solution: p_stat = %d; invalid primal statu" "s\n", *p_stat); lp->pbs_stat = *p_stat; } /* store dual status */ if (d_stat != NULL) { if (!(*d_stat == GLP_UNDEF || *d_stat == GLP_FEAS || *d_stat == GLP_INFEAS || *d_stat == GLP_NOFEAS)) xerror("lpx_put_solution: d_stat = %d; invalid dual status " "\n", *d_stat); lp->dbs_stat = *d_stat; } /* store objective function value */ if (obj_val != NULL) lp->obj_val = *obj_val; /* store row solution components */ for (i = 1; i <= lp->m; i++) { row = lp->row[i]; if (r_stat != NULL) { if (!(r_stat[i] == GLP_BS || row->type == GLP_FR && r_stat[i] == GLP_NF || row->type == GLP_LO && r_stat[i] == GLP_NL || row->type == GLP_UP && r_stat[i] == GLP_NU || row->type == GLP_DB && r_stat[i] == GLP_NL || row->type == GLP_DB && r_stat[i] == GLP_NU || row->type == GLP_FX && r_stat[i] == GLP_NS)) xerror("lpx_put_solution: r_stat[%d] = %d; invalid row s" "tatus\n", i, r_stat[i]); row->stat = r_stat[i]; } if (r_prim != NULL) row->prim = r_prim[i]; if (r_dual != NULL) row->dual = r_dual[i]; } /* store column solution components */ for (j = 1; j <= lp->n; j++) { col = lp->col[j]; if (c_stat != NULL) { if (!(c_stat[j] == GLP_BS || col->type == GLP_FR && c_stat[j] == GLP_NF || col->type == GLP_LO && c_stat[j] == GLP_NL || col->type == GLP_UP && c_stat[j] == GLP_NU || col->type == GLP_DB && c_stat[j] == GLP_NL || col->type == GLP_DB && c_stat[j] == GLP_NU || col->type == GLP_FX && c_stat[j] == GLP_NS)) xerror("lpx_put_solution: c_stat[%d] = %d; invalid colum" "n status\n", j, c_stat[j]); col->stat = c_stat[j]; } if (c_prim != NULL) col->prim = c_prim[j]; if (c_dual != NULL) col->dual = c_dual[j]; } return; } /*---------------------------------------------------------------------- -- lpx_put_mip_soln - store mixed integer solution components. -- -- *Synopsis* -- -- #include "glplpx.h" -- void lpx_put_mip_soln(glp_prob *lp, int i_stat, double row_mipx[], -- double col_mipx[]); -- -- *Description* -- -- The routine lpx_put_mip_soln stores solution components obtained by -- branch-and-bound solver into the specified problem object. -- -- NOTE: This routine is intended for internal use only. */ void lpx_put_mip_soln(glp_prob *lp, int i_stat, double row_mipx[], double col_mipx[]) { GLPROW *row; GLPCOL *col; int i, j; double sum; /* store mixed integer status */ #if 0 if (!(i_stat == LPX_I_UNDEF || i_stat == LPX_I_OPT || i_stat == LPX_I_FEAS || i_stat == LPX_I_NOFEAS)) fault("lpx_put_mip_soln: i_stat = %d; invalid mixed integer st" "atus", i_stat); lp->i_stat = i_stat; #else switch (i_stat) { case LPX_I_UNDEF: lp->mip_stat = GLP_UNDEF; break; case LPX_I_OPT: lp->mip_stat = GLP_OPT; break; case LPX_I_FEAS: lp->mip_stat = GLP_FEAS; break; case LPX_I_NOFEAS: lp->mip_stat = GLP_NOFEAS; break; default: xerror("lpx_put_mip_soln: i_stat = %d; invalid mixed intege" "r status\n", i_stat); } #endif /* store row solution components */ if (row_mipx != NULL) { for (i = 1; i <= lp->m; i++) { row = lp->row[i]; row->mipx = row_mipx[i]; } } /* store column solution components */ if (col_mipx != NULL) { for (j = 1; j <= lp->n; j++) { col = lp->col[j]; col->mipx = col_mipx[j]; } } /* if the solution is claimed to be integer feasible, check it */ if (lp->mip_stat == GLP_OPT || lp->mip_stat == GLP_FEAS) { for (j = 1; j <= lp->n; j++) { col = lp->col[j]; if (col->kind == GLP_IV && col->mipx != floor(col->mipx)) xerror("lpx_put_mip_soln: col_mipx[%d] = %.*g; must be i" "ntegral\n", j, DBL_DIG, col->mipx); } } /* compute the objective function value */ sum = lp->c0; for (j = 1; j <= lp->n; j++) { col = lp->col[j]; sum += col->coef * col->mipx; } lp->mip_obj = sum; return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpenv08.c0000644000076500000240000000743213524616144025214 0ustar tamasstaff00000000000000/* glpenv08.c (shared library support) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef HAVE_CONFIG_H #include #endif #include "glpenv.h" /* GNU version ********************************************************/ #if defined(HAVE_LTDL) #include void *xdlopen(const char *module) { void *h = NULL; if (lt_dlinit() != 0) { lib_err_msg(lt_dlerror()); goto done; } h = lt_dlopen(module); if (h == NULL) { lib_err_msg(lt_dlerror()); if (lt_dlexit() != 0) xerror("xdlopen: %s\n", lt_dlerror()); } done: return h; } void *xdlsym(void *h, const char *symbol) { void *ptr; xassert(h != NULL); ptr = lt_dlsym(h, symbol); if (ptr == NULL) xerror("xdlsym: %s: %s\n", symbol, lt_dlerror()); return ptr; } void xdlclose(void *h) { xassert(h != NULL); if (lt_dlclose(h) != 0) xerror("xdlclose: %s\n", lt_dlerror()); if (lt_dlexit() != 0) xerror("xdlclose: %s\n", lt_dlerror()); return; } /* POSIX version ******************************************************/ #elif defined(HAVE_DLFCN) #include void *xdlopen(const char *module) { void *h; h = dlopen(module, RTLD_NOW); if (h == NULL) lib_err_msg(dlerror()); return h; } void *xdlsym(void *h, const char *symbol) { void *ptr; xassert(h != NULL); ptr = dlsym(h, symbol); if (ptr == NULL) xerror("xdlsym: %s: %s\n", symbol, dlerror()); return ptr; } void xdlclose(void *h) { xassert(h != NULL); if (dlclose(h) != 0) xerror("xdlclose: %s\n", dlerror()); return; } /* Windows version ****************************************************/ #elif defined(__WOE__) #include void *xdlopen(const char *module) { void *h; h = LoadLibrary(module); if (h == NULL) { char msg[20]; sprintf(msg, "Error %d", GetLastError()); lib_err_msg(msg); } return h; } void *xdlsym(void *h, const char *symbol) { void *ptr; xassert(h != NULL); ptr = GetProcAddress(h, symbol); if (ptr == NULL) xerror("xdlsym: %s: Error %d\n", symbol, GetLastError()); return ptr; } void xdlclose(void *h) { xassert(h != NULL); if (!FreeLibrary(h)) xerror("xdlclose: Error %d\n", GetLastError()); return; } /* NULL version *******************************************************/ #else void *xdlopen(const char *module) { xassert(module == module); lib_err_msg("Shared libraries not supported"); return NULL; } void *xdlsym(void *h, const char *symbol) { xassert(h != h); xassert(symbol != symbol); return NULL; } void xdlclose(void *h) { xassert(h != h); return; } #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpios.h0000644000076500000240000005356613524616144025064 0ustar tamasstaff00000000000000/* glpios.h (integer optimization suite) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPIOS_H #define GLPIOS_H #define GLP_TREE_DEFINED typedef struct glp_tree glp_tree; #include "glpapi.h" typedef struct IOSLOT IOSLOT; typedef struct IOSNPD IOSNPD; typedef struct IOSBND IOSBND; typedef struct IOSTAT IOSTAT; typedef struct IOSROW IOSROW; typedef struct IOSAIJ IOSAIJ; typedef struct IOSPOOL IOSPOOL; typedef struct IOSCUT IOSCUT; struct glp_tree { /* branch-and-bound tree */ int magic; /* magic value used for debugging */ DMP *pool; /* memory pool to store all IOS components */ int n; /* number of columns (variables) */ /*--------------------------------------------------------------*/ /* problem components corresponding to the original MIP and its LP relaxation (used to restore the original problem object on exit from the solver) */ int orig_m; /* number of rows */ unsigned char *orig_type; /* uchar orig_type[1+orig_m+n]; */ /* types of all variables */ double *orig_lb; /* double orig_lb[1+orig_m+n]; */ /* lower bounds of all variables */ double *orig_ub; /* double orig_ub[1+orig_m+n]; */ /* upper bounds of all variables */ unsigned char *orig_stat; /* uchar orig_stat[1+orig_m+n]; */ /* statuses of all variables */ double *orig_prim; /* double orig_prim[1+orig_m+n]; */ /* primal values of all variables */ double *orig_dual; /* double orig_dual[1+orig_m+n]; */ /* dual values of all variables */ double orig_obj; /* optimal objective value for LP relaxation */ /*--------------------------------------------------------------*/ /* branch-and-bound tree */ int nslots; /* length of the array of slots (enlarged automatically) */ int avail; /* index of the first free slot; 0 means all slots are in use */ IOSLOT *slot; /* IOSLOT slot[1+nslots]; */ /* array of slots: slot[0] is not used; slot[p], 1 <= p <= nslots, either contains a pointer to some node of the branch-and-bound tree, in which case p is used on API level as the reference number of corresponding subproblem, or is free; all free slots are linked into single linked list; slot[1] always contains a pointer to the root node (it is free only if the tree is empty) */ IOSNPD *head; /* pointer to the head of the active list */ IOSNPD *tail; /* pointer to the tail of the active list */ /* the active list is a doubly linked list of active subproblems which correspond to leaves of the tree; all subproblems in the active list are ordered chronologically (each a new subproblem is always added to the tail of the list) */ int a_cnt; /* current number of active nodes (including the current one) */ int n_cnt; /* current number of all (active and inactive) nodes */ int t_cnt; /* total number of nodes including those which have been already removed from the tree; this count is increased by one whenever a new node is created and never decreased */ /*--------------------------------------------------------------*/ /* problem components corresponding to the root subproblem */ int root_m; /* number of rows */ unsigned char *root_type; /* uchar root_type[1+root_m+n]; */ /* types of all variables */ double *root_lb; /* double root_lb[1+root_m+n]; */ /* lower bounds of all variables */ double *root_ub; /* double root_ub[1+root_m+n]; */ /* upper bounds of all variables */ unsigned char *root_stat; /* uchar root_stat[1+root_m+n]; */ /* statuses of all variables */ /*--------------------------------------------------------------*/ /* current subproblem and its LP relaxation */ IOSNPD *curr; /* pointer to the current subproblem (which can be only active); NULL means the current subproblem does not exist */ glp_prob *mip; /* original problem object passed to the solver; if the current subproblem exists, its LP segment corresponds to LP relaxation of the current subproblem; if the current subproblem does not exist, its LP segment corresponds to LP relaxation of the root subproblem (note that the root subproblem may differ from the original MIP, because it may be preprocessed and/or may have additional rows) */ unsigned char *non_int; /* uchar non_int[1+n]; */ /* these column flags are set each time when LP relaxation of the current subproblem has been solved; non_int[0] is not used; non_int[j], 1 <= j <= n, is j-th column flag; if this flag is set, corresponding variable is required to be integer, but its value in basic solution is fractional */ /*--------------------------------------------------------------*/ /* problem components corresponding to the parent (predecessor) subproblem for the current subproblem; used to inspect changes on freezing the current subproblem */ int pred_m; /* number of rows */ int pred_max; /* length of the following four arrays (enlarged automatically), pred_max >= pred_m + n */ unsigned char *pred_type; /* uchar pred_type[1+pred_m+n]; */ /* types of all variables */ double *pred_lb; /* double pred_lb[1+pred_m+n]; */ /* lower bounds of all variables */ double *pred_ub; /* double pred_ub[1+pred_m+n]; */ /* upper bounds of all variables */ unsigned char *pred_stat; /* uchar pred_stat[1+pred_m+n]; */ /* statuses of all variables */ /****************************************************************/ /* built-in cut generators segment */ IOSPOOL *local; /* local cut pool */ void *mir_gen; /* pointer to working area used by the MIR cut generator */ void *clq_gen; /* pointer to working area used by the clique cut generator */ /*--------------------------------------------------------------*/ void *pcost; /* pointer to working area used on pseudocost branching */ int *iwrk; /* int iwrk[1+n]; */ /* working array */ double *dwrk; /* double dwrk[1+n]; */ /* working array */ /*--------------------------------------------------------------*/ /* control parameters and statistics */ const glp_iocp *parm; /* copy of control parameters passed to the solver */ glp_long tm_beg; /* starting time of the search, in seconds; the total time of the search is the difference between xtime() and tm_beg */ glp_long tm_lag; /* the most recent time, in seconds, at which the progress of the the search was displayed */ int sol_cnt; /* number of integer feasible solutions found */ /*--------------------------------------------------------------*/ /* advanced solver interface */ int reason; /* flag indicating the reason why the callback routine is being called (see glpk.h) */ int stop; /* flag indicating that the callback routine requires premature termination of the search */ int next_p; /* reference number of active subproblem selected to continue the search; 0 means no subproblem has been selected */ int reopt; /* flag indicating that the current LP relaxation needs to be re-optimized */ int reinv; /* flag indicating that some (non-active) rows were removed from the current LP relaxation, so if there no new rows appear, the basis must be re-factorized */ int br_var; /* the number of variable chosen to branch on */ int br_sel; /* flag indicating which branch (subproblem) is suggested to be selected to continue the search: GLP_DN_BRNCH - select down-branch GLP_UP_BRNCH - select up-branch GLP_NO_BRNCH - use general selection technique */ int child; /* subproblem reference number corresponding to br_sel */ }; struct IOSLOT { /* node subproblem slot */ IOSNPD *node; /* pointer to subproblem descriptor; NULL means free slot */ int next; /* index of another free slot (only if this slot is free) */ }; struct IOSNPD { /* node subproblem descriptor */ int p; /* subproblem reference number (it is the index to corresponding slot, i.e. slot[p] points to this descriptor) */ IOSNPD *up; /* pointer to the parent subproblem; NULL means this node is the root of the tree, in which case p = 1 */ int level; /* node level (the root node has level 0) */ int count; /* if count = 0, this subproblem is active; if count > 0, this subproblem is inactive, in which case count is the number of its child subproblems */ /* the following three linked lists are destroyed on reviving and built anew on freezing the subproblem: */ IOSBND *b_ptr; /* linked list of rows and columns of the parent subproblem whose types and bounds were changed */ IOSTAT *s_ptr; /* linked list of rows and columns of the parent subproblem whose statuses were changed */ IOSROW *r_ptr; /* linked list of rows (cuts) added to the parent subproblem */ int solved; /* how many times LP relaxation of this subproblem was solved; for inactive subproblem this count is always non-zero; for active subproblem, which is not current, this count may be non-zero, if the subproblem was temporarily suspended */ double lp_obj; /* optimal objective value to LP relaxation of this subproblem; on creating a subproblem this value is inherited from its parent; for the root subproblem, which has no parent, this value is initially set to -DBL_MAX (minimization) or +DBL_MAX (maximization); each time the subproblem is re-optimized, this value is appropriately changed */ double bound; /* local lower (minimization) or upper (maximization) bound for integer optimal solution to *this* subproblem; this bound is local in the sense that only subproblems in the subtree rooted at this node cannot have better integer feasible solutions; on creating a subproblem its local bound is inherited from its parent and then can be made stronger (never weaker); for the root subproblem its local bound is initially set to -DBL_MAX (minimization) or +DBL_MAX (maximization) and then improved as the root LP relaxation has been solved */ /* the following two quantities are defined only if LP relaxation of this subproblem was solved at least once (solved > 0): */ int ii_cnt; /* number of integer variables whose value in optimal solution to LP relaxation of this subproblem is fractional */ double ii_sum; /* sum of integer infeasibilities */ #if 1 /* 30/XI-2009 */ int changed; /* how many times this subproblem was re-formulated (by adding cutting plane constraints) */ #endif int br_var; /* ordinal number of branching variable, 1 <= br_var <= n, used to split this subproblem; 0 means that either this subproblem is active or branching was made on a constraint */ double br_val; /* (fractional) value of branching variable in optimal solution to final LP relaxation of this subproblem */ void *data; /* char data[tree->cb_size]; */ /* pointer to the application-specific data */ IOSNPD *temp; /* working pointer used by some routines */ IOSNPD *prev; /* pointer to previous subproblem in the active list */ IOSNPD *next; /* pointer to next subproblem in the active list */ }; struct IOSBND { /* bounds change entry */ int k; /* ordinal number of corresponding row (1 <= k <= m) or column (m+1 <= k <= m+n), where m and n are the number of rows and columns, resp., in the parent subproblem */ unsigned char type; /* new type */ double lb; /* new lower bound */ double ub; /* new upper bound */ IOSBND *next; /* pointer to next entry for the same subproblem */ }; struct IOSTAT { /* status change entry */ int k; /* ordinal number of corresponding row (1 <= k <= m) or column (m+1 <= k <= m+n), where m and n are the number of rows and columns, resp., in the parent subproblem */ unsigned char stat; /* new status */ IOSTAT *next; /* pointer to next entry for the same subproblem */ }; struct IOSROW { /* row (constraint) addition entry */ char *name; /* row name or NULL */ unsigned char origin; /* row origin flag (see glp_attr.origin) */ unsigned char klass; /* row class descriptor (see glp_attr.klass) */ unsigned char type; /* row type (GLP_LO, GLP_UP, etc.) */ double lb; /* row lower bound */ double ub; /* row upper bound */ IOSAIJ *ptr; /* pointer to the row coefficient list */ double rii; /* row scale factor */ unsigned char stat; /* row status (GLP_BS, GLP_NL, etc.) */ IOSROW *next; /* pointer to next entry for the same subproblem */ }; struct IOSAIJ { /* constraint coefficient */ int j; /* variable (column) number, 1 <= j <= n */ double val; /* non-zero coefficient value */ IOSAIJ *next; /* pointer to next coefficient for the same row */ }; struct IOSPOOL { /* cut pool */ int size; /* pool size = number of cuts in the pool */ IOSCUT *head; /* pointer to the first cut */ IOSCUT *tail; /* pointer to the last cut */ int ord; /* ordinal number of the current cut, 1 <= ord <= size */ IOSCUT *curr; /* pointer to the current cut */ }; struct IOSCUT { /* cut (cutting plane constraint) */ char *name; /* cut name or NULL */ unsigned char klass; /* cut class descriptor (see glp_attr.klass) */ IOSAIJ *ptr; /* pointer to the cut coefficient list */ unsigned char type; /* cut type: GLP_LO: sum a[j] * x[j] >= b GLP_UP: sum a[j] * x[j] <= b GLP_FX: sum a[j] * x[j] = b */ double rhs; /* cut right-hand side */ IOSCUT *prev; /* pointer to previous cut */ IOSCUT *next; /* pointer to next cut */ }; #define ios_create_tree _glp_ios_create_tree glp_tree *ios_create_tree(glp_prob *mip, const glp_iocp *parm); /* create branch-and-bound tree */ #define ios_revive_node _glp_ios_revive_node void ios_revive_node(glp_tree *tree, int p); /* revive specified subproblem */ #define ios_freeze_node _glp_ios_freeze_node void ios_freeze_node(glp_tree *tree); /* freeze current subproblem */ #define ios_clone_node _glp_ios_clone_node void ios_clone_node(glp_tree *tree, int p, int nnn, int ref[]); /* clone specified subproblem */ #define ios_delete_node _glp_ios_delete_node void ios_delete_node(glp_tree *tree, int p); /* delete specified subproblem */ #define ios_delete_tree _glp_ios_delete_tree void ios_delete_tree(glp_tree *tree); /* delete branch-and-bound tree */ #define ios_eval_degrad _glp_ios_eval_degrad void ios_eval_degrad(glp_tree *tree, int j, double *dn, double *up); /* estimate obj. degrad. for down- and up-branches */ #define ios_round_bound _glp_ios_round_bound double ios_round_bound(glp_tree *tree, double bound); /* improve local bound by rounding */ #define ios_is_hopeful _glp_ios_is_hopeful int ios_is_hopeful(glp_tree *tree, double bound); /* check if subproblem is hopeful */ #define ios_best_node _glp_ios_best_node int ios_best_node(glp_tree *tree); /* find active node with best local bound */ #define ios_relative_gap _glp_ios_relative_gap double ios_relative_gap(glp_tree *tree); /* compute relative mip gap */ #define ios_solve_node _glp_ios_solve_node int ios_solve_node(glp_tree *tree); /* solve LP relaxation of current subproblem */ #define ios_create_pool _glp_ios_create_pool IOSPOOL *ios_create_pool(glp_tree *tree); /* create cut pool */ #define ios_add_row _glp_ios_add_row int ios_add_row(glp_tree *tree, IOSPOOL *pool, const char *name, int klass, int flags, int len, const int ind[], const double val[], int type, double rhs); /* add row (constraint) to the cut pool */ #define ios_find_row _glp_ios_find_row IOSCUT *ios_find_row(IOSPOOL *pool, int i); /* find row (constraint) in the cut pool */ #define ios_del_row _glp_ios_del_row void ios_del_row(glp_tree *tree, IOSPOOL *pool, int i); /* remove row (constraint) from the cut pool */ #define ios_clear_pool _glp_ios_clear_pool void ios_clear_pool(glp_tree *tree, IOSPOOL *pool); /* remove all rows (constraints) from the cut pool */ #define ios_delete_pool _glp_ios_delete_pool void ios_delete_pool(glp_tree *tree, IOSPOOL *pool); /* delete cut pool */ #define ios_preprocess_node _glp_ios_preprocess_node int ios_preprocess_node(glp_tree *tree, int max_pass); /* preprocess current subproblem */ #define ios_driver _glp_ios_driver int ios_driver(glp_tree *tree); /* branch-and-bound driver */ /**********************************************************************/ typedef struct IOSVEC IOSVEC; struct IOSVEC { /* sparse vector v = (v[j]) */ int n; /* dimension, n >= 0 */ int nnz; /* number of non-zero components, 0 <= nnz <= n */ int *pos; /* int pos[1+n]; */ /* pos[j] = k, 1 <= j <= n, is position of (non-zero) v[j] in the arrays ind and val, where 1 <= k <= nnz; pos[j] = 0 means that v[j] is structural zero */ int *ind; /* int ind[1+n]; */ /* ind[k] = j, 1 <= k <= nnz, is index of v[j] */ double *val; /* double val[1+n]; */ /* val[k], 1 <= k <= nnz, is a numeric value of v[j] */ }; #define ios_create_vec _glp_ios_create_vec IOSVEC *ios_create_vec(int n); /* create sparse vector */ #define ios_check_vec _glp_ios_check_vec void ios_check_vec(IOSVEC *v); /* check that sparse vector has correct representation */ #define ios_get_vj _glp_ios_get_vj double ios_get_vj(IOSVEC *v, int j); /* retrieve component of sparse vector */ #define ios_set_vj _glp_ios_set_vj void ios_set_vj(IOSVEC *v, int j, double val); /* set/change component of sparse vector */ #define ios_clear_vec _glp_ios_clear_vec void ios_clear_vec(IOSVEC *v); /* set all components of sparse vector to zero */ #define ios_clean_vec _glp_ios_clean_vec void ios_clean_vec(IOSVEC *v, double eps); /* remove zero or small components from sparse vector */ #define ios_copy_vec _glp_ios_copy_vec void ios_copy_vec(IOSVEC *x, IOSVEC *y); /* copy sparse vector (x := y) */ #define ios_linear_comb _glp_ios_linear_comb void ios_linear_comb(IOSVEC *x, double a, IOSVEC *y); /* compute linear combination (x := x + a * y) */ #define ios_delete_vec _glp_ios_delete_vec void ios_delete_vec(IOSVEC *v); /* delete sparse vector */ /**********************************************************************/ #define ios_gmi_gen _glp_ios_gmi_gen void ios_gmi_gen(glp_tree *tree); /* generate Gomory's mixed integer cuts */ #define ios_mir_init _glp_ios_mir_init void *ios_mir_init(glp_tree *tree); /* initialize MIR cut generator */ #define ios_mir_gen _glp_ios_mir_gen void ios_mir_gen(glp_tree *tree, void *gen); /* generate MIR cuts */ #define ios_mir_term _glp_ios_mir_term void ios_mir_term(void *gen); /* terminate MIR cut generator */ #define ios_cov_gen _glp_ios_cov_gen void ios_cov_gen(glp_tree *tree); /* generate mixed cover cuts */ #define ios_clq_init _glp_ios_clq_init void *ios_clq_init(glp_tree *tree); /* initialize clique cut generator */ #define ios_clq_gen _glp_ios_clq_gen void ios_clq_gen(glp_tree *tree, void *gen); /* generate clique cuts */ #define ios_clq_term _glp_ios_clq_term void ios_clq_term(void *gen); /* terminate clique cut generator */ #define ios_pcost_init _glp_ios_pcost_init void *ios_pcost_init(glp_tree *tree); /* initialize working data used on pseudocost branching */ #define ios_pcost_branch _glp_ios_pcost_branch int ios_pcost_branch(glp_tree *T, int *next); /* choose branching variable with pseudocost branching */ #define ios_pcost_update _glp_ios_pcost_update void ios_pcost_update(glp_tree *tree); /* update history information for pseudocost branching */ #define ios_pcost_free _glp_ios_pcost_free void ios_pcost_free(glp_tree *tree); /* free working area used on pseudocost branching */ #define ios_feas_pump _glp_ios_feas_pump void ios_feas_pump(glp_tree *T); /* feasibility pump heuristic */ #define ios_process_cuts _glp_ios_process_cuts void ios_process_cuts(glp_tree *T); /* process cuts stored in the local cut pool */ #define ios_choose_node _glp_ios_choose_node int ios_choose_node(glp_tree *T); /* select subproblem to continue the search */ #define ios_choose_var _glp_ios_choose_var int ios_choose_var(glp_tree *T, int *next); /* select variable to branch on */ #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpmpl01.c0000644000076500000240000052734213524616144025214 0ustar tamasstaff00000000000000/* glpmpl01.c */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifdef __clang__ #pragma clang diagnostic ignored "-Wlogical-op-parentheses" #pragma clang diagnostic ignored "-Wshorten-64-to-32" #pragma clang diagnostic ignored "-Wsometimes-uninitialized" #endif #define _GLPSTD_STDIO #include "glpmpl.h" #define dmp_get_atomv dmp_get_atom /**********************************************************************/ /* * * PROCESSING MODEL SECTION * * */ /**********************************************************************/ /*---------------------------------------------------------------------- -- enter_context - enter current token into context queue. -- -- This routine enters the current token into the context queue. */ void enter_context(MPL *mpl) { char *image, *s; if (mpl->token == T_EOF) image = "_|_"; else if (mpl->token == T_STRING) image = "'...'"; else image = mpl->image; xassert(0 <= mpl->c_ptr && mpl->c_ptr < CONTEXT_SIZE); mpl->context[mpl->c_ptr++] = ' '; if (mpl->c_ptr == CONTEXT_SIZE) mpl->c_ptr = 0; for (s = image; *s != '\0'; s++) { mpl->context[mpl->c_ptr++] = *s; if (mpl->c_ptr == CONTEXT_SIZE) mpl->c_ptr = 0; } return; } /*---------------------------------------------------------------------- -- print_context - print current content of context queue. -- -- This routine prints current content of the context queue. */ void print_context(MPL *mpl) { int c; while (mpl->c_ptr > 0) { mpl->c_ptr--; c = mpl->context[0]; memmove(mpl->context, mpl->context+1, CONTEXT_SIZE-1); mpl->context[CONTEXT_SIZE-1] = (char)c; } xprintf("Context: %s%.*s\n", mpl->context[0] == ' ' ? "" : "...", CONTEXT_SIZE, mpl->context); return; } /*---------------------------------------------------------------------- -- get_char - scan next character from input text file. -- -- This routine scans a next ASCII character from the input text file. -- In case of end-of-file, the character is assigned EOF. */ void get_char(MPL *mpl) { int c; if (mpl->c == EOF) goto done; if (mpl->c == '\n') mpl->line++; c = read_char(mpl); if (c == EOF) { if (mpl->c == '\n') mpl->line--; else warning(mpl, "final NL missing before end of file"); } else if (c == '\n') ; else if (isspace(c)) c = ' '; else if (iscntrl(c)) { enter_context(mpl); error(mpl, "control character 0x%02X not allowed", c); } mpl->c = c; done: return; } /*---------------------------------------------------------------------- -- append_char - append character to current token. -- -- This routine appends the current character to the current token and -- then scans a next character. */ void append_char(MPL *mpl) { xassert(0 <= mpl->imlen && mpl->imlen <= MAX_LENGTH); if (mpl->imlen == MAX_LENGTH) { switch (mpl->token) { case T_NAME: enter_context(mpl); error(mpl, "symbolic name %s... too long", mpl->image); case T_SYMBOL: enter_context(mpl); error(mpl, "symbol %s... too long", mpl->image); case T_NUMBER: enter_context(mpl); error(mpl, "numeric literal %s... too long", mpl->image); case T_STRING: enter_context(mpl); error(mpl, "string literal too long"); default: xassert(mpl != mpl); } } mpl->image[mpl->imlen++] = (char)mpl->c; mpl->image[mpl->imlen] = '\0'; get_char(mpl); return; } /*---------------------------------------------------------------------- -- get_token - scan next token from input text file. -- -- This routine scans a next token from the input text file using the -- standard finite automation technique. */ void get_token(MPL *mpl) { /* save the current token */ mpl->b_token = mpl->token; mpl->b_imlen = mpl->imlen; strcpy(mpl->b_image, mpl->image); mpl->b_value = mpl->value; /* if the next token is already scanned, make it current */ if (mpl->f_scan) { mpl->f_scan = 0; mpl->token = mpl->f_token; mpl->imlen = mpl->f_imlen; strcpy(mpl->image, mpl->f_image); mpl->value = mpl->f_value; goto done; } loop: /* nothing has been scanned so far */ mpl->token = 0; mpl->imlen = 0; mpl->image[0] = '\0'; mpl->value = 0.0; /* skip any uninteresting characters */ while (mpl->c == ' ' || mpl->c == '\n') get_char(mpl); /* recognize and construct the token */ if (mpl->c == EOF) { /* end-of-file reached */ mpl->token = T_EOF; } else if (mpl->c == '#') { /* comment; skip anything until end-of-line */ while (mpl->c != '\n' && mpl->c != EOF) get_char(mpl); goto loop; } else if (!mpl->flag_d && (isalpha(mpl->c) || mpl->c == '_')) { /* symbolic name or reserved keyword */ mpl->token = T_NAME; while (isalnum(mpl->c) || mpl->c == '_') append_char(mpl); if (strcmp(mpl->image, "and") == 0) mpl->token = T_AND; else if (strcmp(mpl->image, "by") == 0) mpl->token = T_BY; else if (strcmp(mpl->image, "cross") == 0) mpl->token = T_CROSS; else if (strcmp(mpl->image, "diff") == 0) mpl->token = T_DIFF; else if (strcmp(mpl->image, "div") == 0) mpl->token = T_DIV; else if (strcmp(mpl->image, "else") == 0) mpl->token = T_ELSE; else if (strcmp(mpl->image, "if") == 0) mpl->token = T_IF; else if (strcmp(mpl->image, "in") == 0) mpl->token = T_IN; #if 1 /* 21/VII-2006 */ else if (strcmp(mpl->image, "Infinity") == 0) mpl->token = T_INFINITY; #endif else if (strcmp(mpl->image, "inter") == 0) mpl->token = T_INTER; else if (strcmp(mpl->image, "less") == 0) mpl->token = T_LESS; else if (strcmp(mpl->image, "mod") == 0) mpl->token = T_MOD; else if (strcmp(mpl->image, "not") == 0) mpl->token = T_NOT; else if (strcmp(mpl->image, "or") == 0) mpl->token = T_OR; else if (strcmp(mpl->image, "s") == 0 && mpl->c == '.') { mpl->token = T_SPTP; append_char(mpl); if (mpl->c != 't') sptp: { enter_context(mpl); error(mpl, "keyword s.t. incomplete"); } append_char(mpl); if (mpl->c != '.') goto sptp; append_char(mpl); } else if (strcmp(mpl->image, "symdiff") == 0) mpl->token = T_SYMDIFF; else if (strcmp(mpl->image, "then") == 0) mpl->token = T_THEN; else if (strcmp(mpl->image, "union") == 0) mpl->token = T_UNION; else if (strcmp(mpl->image, "within") == 0) mpl->token = T_WITHIN; } else if (!mpl->flag_d && isdigit(mpl->c)) { /* numeric literal */ mpl->token = T_NUMBER; /* scan integer part */ while (isdigit(mpl->c)) append_char(mpl); /* scan optional fractional part */ if (mpl->c == '.') { append_char(mpl); if (mpl->c == '.') { /* hmm, it is not the fractional part, it is dots that follow the integer part */ mpl->imlen--; mpl->image[mpl->imlen] = '\0'; mpl->f_dots = 1; goto conv; } frac: while (isdigit(mpl->c)) append_char(mpl); } /* scan optional decimal exponent */ if (mpl->c == 'e' || mpl->c == 'E') { append_char(mpl); if (mpl->c == '+' || mpl->c == '-') append_char(mpl); if (!isdigit(mpl->c)) { enter_context(mpl); error(mpl, "numeric literal %s incomplete", mpl->image); } while (isdigit(mpl->c)) append_char(mpl); } /* there must be no letter following the numeric literal */ if (isalpha(mpl->c) || mpl->c == '_') { enter_context(mpl); error(mpl, "symbol %s%c... should be enclosed in quotes", mpl->image, mpl->c); } conv: /* convert numeric literal to floating-point */ if (str2num(mpl->image, &mpl->value)) err: { enter_context(mpl); error(mpl, "cannot convert numeric literal %s to floating-p" "oint number", mpl->image); } } else if (mpl->c == '\'' || mpl->c == '"') { /* character string */ int quote = mpl->c; mpl->token = T_STRING; get_char(mpl); for (;;) { if (mpl->c == '\n' || mpl->c == EOF) { enter_context(mpl); error(mpl, "unexpected end of line; string literal incom" "plete"); } if (mpl->c == quote) { get_char(mpl); if (mpl->c != quote) break; } append_char(mpl); } } else if (!mpl->flag_d && mpl->c == '+') mpl->token = T_PLUS, append_char(mpl); else if (!mpl->flag_d && mpl->c == '-') mpl->token = T_MINUS, append_char(mpl); else if (mpl->c == '*') { mpl->token = T_ASTERISK, append_char(mpl); if (mpl->c == '*') mpl->token = T_POWER, append_char(mpl); } else if (mpl->c == '/') { mpl->token = T_SLASH, append_char(mpl); if (mpl->c == '*') { /* comment sequence */ get_char(mpl); for (;;) { if (mpl->c == EOF) { /* do not call enter_context at this point */ error(mpl, "unexpected end of file; comment sequence " "incomplete"); } else if (mpl->c == '*') { get_char(mpl); if (mpl->c == '/') break; } else get_char(mpl); } get_char(mpl); goto loop; } } else if (mpl->c == '^') mpl->token = T_POWER, append_char(mpl); else if (mpl->c == '<') { mpl->token = T_LT, append_char(mpl); if (mpl->c == '=') mpl->token = T_LE, append_char(mpl); else if (mpl->c == '>') mpl->token = T_NE, append_char(mpl); #if 1 /* 11/II-2008 */ else if (mpl->c == '-') mpl->token = T_INPUT, append_char(mpl); #endif } else if (mpl->c == '=') { mpl->token = T_EQ, append_char(mpl); if (mpl->c == '=') append_char(mpl); } else if (mpl->c == '>') { mpl->token = T_GT, append_char(mpl); if (mpl->c == '=') mpl->token = T_GE, append_char(mpl); #if 1 /* 14/VII-2006 */ else if (mpl->c == '>') mpl->token = T_APPEND, append_char(mpl); #endif } else if (mpl->c == '!') { mpl->token = T_NOT, append_char(mpl); if (mpl->c == '=') mpl->token = T_NE, append_char(mpl); } else if (mpl->c == '&') { mpl->token = T_CONCAT, append_char(mpl); if (mpl->c == '&') mpl->token = T_AND, append_char(mpl); } else if (mpl->c == '|') { mpl->token = T_BAR, append_char(mpl); if (mpl->c == '|') mpl->token = T_OR, append_char(mpl); } else if (!mpl->flag_d && mpl->c == '.') { mpl->token = T_POINT, append_char(mpl); if (mpl->f_dots) { /* dots; the first dot was read on the previous call to the scanner, so the current character is the second dot */ mpl->token = T_DOTS; mpl->imlen = 2; strcpy(mpl->image, ".."); mpl->f_dots = 0; } else if (mpl->c == '.') mpl->token = T_DOTS, append_char(mpl); else if (isdigit(mpl->c)) { /* numeric literal that begins with the decimal point */ mpl->token = T_NUMBER, append_char(mpl); goto frac; } } else if (mpl->c == ',') mpl->token = T_COMMA, append_char(mpl); else if (mpl->c == ':') { mpl->token = T_COLON, append_char(mpl); if (mpl->c == '=') mpl->token = T_ASSIGN, append_char(mpl); } else if (mpl->c == ';') mpl->token = T_SEMICOLON, append_char(mpl); else if (mpl->c == '(') mpl->token = T_LEFT, append_char(mpl); else if (mpl->c == ')') mpl->token = T_RIGHT, append_char(mpl); else if (mpl->c == '[') mpl->token = T_LBRACKET, append_char(mpl); else if (mpl->c == ']') mpl->token = T_RBRACKET, append_char(mpl); else if (mpl->c == '{') mpl->token = T_LBRACE, append_char(mpl); else if (mpl->c == '}') mpl->token = T_RBRACE, append_char(mpl); #if 1 /* 11/II-2008 */ else if (mpl->c == '~') mpl->token = T_TILDE, append_char(mpl); #endif else if (isalnum(mpl->c) || strchr("+-._", mpl->c) != NULL) { /* symbol */ xassert(mpl->flag_d); mpl->token = T_SYMBOL; while (isalnum(mpl->c) || strchr("+-._", mpl->c) != NULL) append_char(mpl); switch (str2num(mpl->image, &mpl->value)) { case 0: mpl->token = T_NUMBER; break; case 1: goto err; case 2: break; default: xassert(mpl != mpl); } } else { enter_context(mpl); error(mpl, "character %c not allowed", mpl->c); } /* enter the current token into the context queue */ enter_context(mpl); /* reset the flag, which may be set by indexing_expression() and is used by expression_list() */ mpl->flag_x = 0; done: return; } /*---------------------------------------------------------------------- -- unget_token - return current token back to input stream. -- -- This routine returns the current token back to the input stream, so -- the previously scanned token becomes the current one. */ void unget_token(MPL *mpl) { /* save the current token, which becomes the next one */ xassert(!mpl->f_scan); mpl->f_scan = 1; mpl->f_token = mpl->token; mpl->f_imlen = mpl->imlen; strcpy(mpl->f_image, mpl->image); mpl->f_value = mpl->value; /* restore the previous token, which becomes the current one */ mpl->token = mpl->b_token; mpl->imlen = mpl->b_imlen; strcpy(mpl->image, mpl->b_image); mpl->value = mpl->b_value; return; } /*---------------------------------------------------------------------- -- is_keyword - check if current token is given non-reserved keyword. -- -- If the current token is given (non-reserved) keyword, this routine -- returns non-zero. Otherwise zero is returned. */ int is_keyword(MPL *mpl, char *keyword) { return mpl->token == T_NAME && strcmp(mpl->image, keyword) == 0; } /*---------------------------------------------------------------------- -- is_reserved - check if current token is reserved keyword. -- -- If the current token is a reserved keyword, this routine returns -- non-zero. Otherwise zero is returned. */ int is_reserved(MPL *mpl) { return mpl->token == T_AND && mpl->image[0] == 'a' || mpl->token == T_BY || mpl->token == T_CROSS || mpl->token == T_DIFF || mpl->token == T_DIV || mpl->token == T_ELSE || mpl->token == T_IF || mpl->token == T_IN || mpl->token == T_INTER || mpl->token == T_LESS || mpl->token == T_MOD || mpl->token == T_NOT && mpl->image[0] == 'n' || mpl->token == T_OR && mpl->image[0] == 'o' || mpl->token == T_SYMDIFF || mpl->token == T_THEN || mpl->token == T_UNION || mpl->token == T_WITHIN; } /*---------------------------------------------------------------------- -- make_code - generate pseudo-code (basic routine). -- -- This routine generates specified pseudo-code. It is assumed that all -- other translator routines use this basic routine. */ CODE *make_code(MPL *mpl, int op, OPERANDS *arg, int type, int dim) { CODE *code; DOMAIN *domain; DOMAIN_BLOCK *block; ARG_LIST *e; /* generate pseudo-code */ code = alloc(CODE); code->op = op; code->vflag = 0; /* is inherited from operand(s) */ /* copy operands and also make them referring to the pseudo-code being generated, because the latter becomes the parent for all its operands */ memset(&code->arg, '?', sizeof(OPERANDS)); switch (op) { case O_NUMBER: code->arg.num = arg->num; break; case O_STRING: code->arg.str = arg->str; break; case O_INDEX: code->arg.index.slot = arg->index.slot; code->arg.index.next = arg->index.next; break; case O_MEMNUM: case O_MEMSYM: for (e = arg->par.list; e != NULL; e = e->next) { xassert(e->x != NULL); xassert(e->x->up == NULL); e->x->up = code; code->vflag |= e->x->vflag; } code->arg.par.par = arg->par.par; code->arg.par.list = arg->par.list; break; case O_MEMSET: for (e = arg->set.list; e != NULL; e = e->next) { xassert(e->x != NULL); xassert(e->x->up == NULL); e->x->up = code; code->vflag |= e->x->vflag; } code->arg.set.set = arg->set.set; code->arg.set.list = arg->set.list; break; case O_MEMVAR: for (e = arg->var.list; e != NULL; e = e->next) { xassert(e->x != NULL); xassert(e->x->up == NULL); e->x->up = code; code->vflag |= e->x->vflag; } code->arg.var.var = arg->var.var; code->arg.var.list = arg->var.list; #if 1 /* 15/V-2010 */ code->arg.var.suff = arg->var.suff; #endif break; #if 1 /* 15/V-2010 */ case O_MEMCON: for (e = arg->con.list; e != NULL; e = e->next) { xassert(e->x != NULL); xassert(e->x->up == NULL); e->x->up = code; code->vflag |= e->x->vflag; } code->arg.con.con = arg->con.con; code->arg.con.list = arg->con.list; code->arg.con.suff = arg->con.suff; break; #endif case O_TUPLE: case O_MAKE: for (e = arg->list; e != NULL; e = e->next) { xassert(e->x != NULL); xassert(e->x->up == NULL); e->x->up = code; code->vflag |= e->x->vflag; } code->arg.list = arg->list; break; case O_SLICE: xassert(arg->slice != NULL); code->arg.slice = arg->slice; break; case O_IRAND224: case O_UNIFORM01: case O_NORMAL01: case O_GMTIME: code->vflag = 1; break; case O_CVTNUM: case O_CVTSYM: case O_CVTLOG: case O_CVTTUP: case O_CVTLFM: case O_PLUS: case O_MINUS: case O_NOT: case O_ABS: case O_CEIL: case O_FLOOR: case O_EXP: case O_LOG: case O_LOG10: case O_SQRT: case O_SIN: case O_COS: case O_ATAN: case O_ROUND: case O_TRUNC: case O_CARD: case O_LENGTH: /* unary operation */ xassert(arg->arg.x != NULL); xassert(arg->arg.x->up == NULL); arg->arg.x->up = code; code->vflag |= arg->arg.x->vflag; code->arg.arg.x = arg->arg.x; break; case O_ADD: case O_SUB: case O_LESS: case O_MUL: case O_DIV: case O_IDIV: case O_MOD: case O_POWER: case O_ATAN2: case O_ROUND2: case O_TRUNC2: case O_UNIFORM: if (op == O_UNIFORM) code->vflag = 1; case O_NORMAL: if (op == O_NORMAL) code->vflag = 1; case O_CONCAT: case O_LT: case O_LE: case O_EQ: case O_GE: case O_GT: case O_NE: case O_AND: case O_OR: case O_UNION: case O_DIFF: case O_SYMDIFF: case O_INTER: case O_CROSS: case O_IN: case O_NOTIN: case O_WITHIN: case O_NOTWITHIN: case O_SUBSTR: case O_STR2TIME: case O_TIME2STR: /* binary operation */ xassert(arg->arg.x != NULL); xassert(arg->arg.x->up == NULL); arg->arg.x->up = code; code->vflag |= arg->arg.x->vflag; xassert(arg->arg.y != NULL); xassert(arg->arg.y->up == NULL); arg->arg.y->up = code; code->vflag |= arg->arg.y->vflag; code->arg.arg.x = arg->arg.x; code->arg.arg.y = arg->arg.y; break; case O_DOTS: case O_FORK: case O_SUBSTR3: /* ternary operation */ xassert(arg->arg.x != NULL); xassert(arg->arg.x->up == NULL); arg->arg.x->up = code; code->vflag |= arg->arg.x->vflag; xassert(arg->arg.y != NULL); xassert(arg->arg.y->up == NULL); arg->arg.y->up = code; code->vflag |= arg->arg.y->vflag; if (arg->arg.z != NULL) { xassert(arg->arg.z->up == NULL); arg->arg.z->up = code; code->vflag |= arg->arg.z->vflag; } code->arg.arg.x = arg->arg.x; code->arg.arg.y = arg->arg.y; code->arg.arg.z = arg->arg.z; break; case O_MIN: case O_MAX: /* n-ary operation */ for (e = arg->list; e != NULL; e = e->next) { xassert(e->x != NULL); xassert(e->x->up == NULL); e->x->up = code; code->vflag |= e->x->vflag; } code->arg.list = arg->list; break; case O_SUM: case O_PROD: case O_MINIMUM: case O_MAXIMUM: case O_FORALL: case O_EXISTS: case O_SETOF: case O_BUILD: /* iterated operation */ domain = arg->loop.domain; xassert(domain != NULL); if (domain->code != NULL) { xassert(domain->code->up == NULL); domain->code->up = code; code->vflag |= domain->code->vflag; } for (block = domain->list; block != NULL; block = block->next) { xassert(block->code != NULL); xassert(block->code->up == NULL); block->code->up = code; code->vflag |= block->code->vflag; } if (arg->loop.x != NULL) { xassert(arg->loop.x->up == NULL); arg->loop.x->up = code; code->vflag |= arg->loop.x->vflag; } code->arg.loop.domain = arg->loop.domain; code->arg.loop.x = arg->loop.x; break; default: xassert(op != op); } /* set other attributes of the pseudo-code */ code->type = type; code->dim = dim; code->up = NULL; code->valid = 0; memset(&code->value, '?', sizeof(VALUE)); return code; } /*---------------------------------------------------------------------- -- make_unary - generate pseudo-code for unary operation. -- -- This routine generates pseudo-code for unary operation. */ CODE *make_unary(MPL *mpl, int op, CODE *x, int type, int dim) { CODE *code; OPERANDS arg; xassert(x != NULL); arg.arg.x = x; code = make_code(mpl, op, &arg, type, dim); return code; } /*---------------------------------------------------------------------- -- make_binary - generate pseudo-code for binary operation. -- -- This routine generates pseudo-code for binary operation. */ CODE *make_binary(MPL *mpl, int op, CODE *x, CODE *y, int type, int dim) { CODE *code; OPERANDS arg; xassert(x != NULL); xassert(y != NULL); arg.arg.x = x; arg.arg.y = y; code = make_code(mpl, op, &arg, type, dim); return code; } /*---------------------------------------------------------------------- -- make_ternary - generate pseudo-code for ternary operation. -- -- This routine generates pseudo-code for ternary operation. */ CODE *make_ternary(MPL *mpl, int op, CODE *x, CODE *y, CODE *z, int type, int dim) { CODE *code; OPERANDS arg; xassert(x != NULL); xassert(y != NULL); /* third operand can be NULL */ arg.arg.x = x; arg.arg.y = y; arg.arg.z = z; code = make_code(mpl, op, &arg, type, dim); return code; } /*---------------------------------------------------------------------- -- numeric_literal - parse reference to numeric literal. -- -- This routine parses primary expression using the syntax: -- -- ::= */ CODE *numeric_literal(MPL *mpl) { CODE *code; OPERANDS arg; xassert(mpl->token == T_NUMBER); arg.num = mpl->value; code = make_code(mpl, O_NUMBER, &arg, A_NUMERIC, 0); get_token(mpl /* */); return code; } /*---------------------------------------------------------------------- -- string_literal - parse reference to string literal. -- -- This routine parses primary expression using the syntax: -- -- ::= */ CODE *string_literal(MPL *mpl) { CODE *code; OPERANDS arg; xassert(mpl->token == T_STRING); arg.str = dmp_get_atomv(mpl->pool, strlen(mpl->image)+1); strcpy(arg.str, mpl->image); code = make_code(mpl, O_STRING, &arg, A_SYMBOLIC, 0); get_token(mpl /* */); return code; } /*---------------------------------------------------------------------- -- create_arg_list - create empty operands list. -- -- This routine creates operands list, which is initially empty. */ ARG_LIST *create_arg_list(MPL *mpl) { ARG_LIST *list; xassert(mpl == mpl); list = NULL; return list; } /*---------------------------------------------------------------------- -- expand_arg_list - append operand to operands list. -- -- This routine appends new operand to specified operands list. */ ARG_LIST *expand_arg_list(MPL *mpl, ARG_LIST *list, CODE *x) { ARG_LIST *tail, *temp; xassert(x != NULL); /* create new operands list entry */ tail = alloc(ARG_LIST); tail->x = x; tail->next = NULL; /* and append it to the operands list */ if (list == NULL) list = tail; else { for (temp = list; temp->next != NULL; temp = temp->next); temp->next = tail; } return list; } /*---------------------------------------------------------------------- -- arg_list_len - determine length of operands list. -- -- This routine returns the number of operands in operands list. */ int arg_list_len(MPL *mpl, ARG_LIST *list) { ARG_LIST *temp; int len; xassert(mpl == mpl); len = 0; for (temp = list; temp != NULL; temp = temp->next) len++; return len; } /*---------------------------------------------------------------------- -- subscript_list - parse subscript list. -- -- This routine parses subscript list using the syntax: -- -- ::= -- ::= , -- ::= */ ARG_LIST *subscript_list(MPL *mpl) { ARG_LIST *list; CODE *x; list = create_arg_list(mpl); for (;;) { /* parse subscript expression */ x = expression_5(mpl); /* convert it to symbolic type, if necessary */ if (x->type == A_NUMERIC) x = make_unary(mpl, O_CVTSYM, x, A_SYMBOLIC, 0); /* check that now the expression is of symbolic type */ if (x->type != A_SYMBOLIC) error(mpl, "subscript expression has invalid type"); xassert(x->dim == 0); /* and append it to the subscript list */ list = expand_arg_list(mpl, list, x); /* check a token that follows the subscript expression */ if (mpl->token == T_COMMA) get_token(mpl /* , */); else if (mpl->token == T_RBRACKET) break; else error(mpl, "syntax error in subscript list"); } return list; } #if 1 /* 15/V-2010 */ /*---------------------------------------------------------------------- -- object_reference - parse reference to named object. -- -- This routine parses primary expression using the syntax: -- -- ::= -- ::= -- ::= [ ] -- ::= -- ::= [ ] -- ::= -- ::= [ ] -- -- ::= -- ::= [ ] -- -- ::= -- ::= -- ::= -- ::= -- ::= -- ::= | .lb | .ub | .status | .val | .dual */ CODE *object_reference(MPL *mpl) { AVLNODE *node; DOMAIN_SLOT *slot; SET *set; PARAMETER *par; VARIABLE *var; CONSTRAINT *con; ARG_LIST *list; OPERANDS arg; CODE *code; char *name; int dim, suff; /* find the object in the symbolic name table */ xassert(mpl->token == T_NAME); node = avl_find_node(mpl->tree, mpl->image); if (node == NULL) error(mpl, "%s not defined", mpl->image); /* check the object type and obtain its dimension */ switch (avl_get_node_type(node)) { case A_INDEX: /* dummy index */ slot = (DOMAIN_SLOT *)avl_get_node_link(node); name = slot->name; dim = 0; break; case A_SET: /* model set */ set = (SET *)avl_get_node_link(node); name = set->name; dim = set->dim; /* if a set object is referenced in its own declaration and the dimen attribute is not specified yet, use dimen 1 by default */ if (set->dimen == 0) set->dimen = 1; break; case A_PARAMETER: /* model parameter */ par = (PARAMETER *)avl_get_node_link(node); name = par->name; dim = par->dim; break; case A_VARIABLE: /* model variable */ var = (VARIABLE *)avl_get_node_link(node); name = var->name; dim = var->dim; break; case A_CONSTRAINT: /* model constraint or objective */ con = (CONSTRAINT *)avl_get_node_link(node); name = con->name; dim = con->dim; break; default: xassert(node != node); } get_token(mpl /* */); /* parse optional subscript list */ if (mpl->token == T_LBRACKET) { /* subscript list is specified */ if (dim == 0) error(mpl, "%s cannot be subscripted", name); get_token(mpl /* [ */); list = subscript_list(mpl); if (dim != arg_list_len(mpl, list)) error(mpl, "%s must have %d subscript%s rather than %d", name, dim, dim == 1 ? "" : "s", arg_list_len(mpl, list)); xassert(mpl->token == T_RBRACKET); get_token(mpl /* ] */); } else { /* subscript list is not specified */ if (dim != 0) error(mpl, "%s must be subscripted", name); list = create_arg_list(mpl); } /* parse optional suffix */ if (!mpl->flag_s && avl_get_node_type(node) == A_VARIABLE) suff = DOT_NONE; else suff = DOT_VAL; if (mpl->token == T_POINT) { get_token(mpl /* . */); if (mpl->token != T_NAME) error(mpl, "invalid use of period"); if (!(avl_get_node_type(node) == A_VARIABLE || avl_get_node_type(node) == A_CONSTRAINT)) error(mpl, "%s cannot have a suffix", name); if (strcmp(mpl->image, "lb") == 0) suff = DOT_LB; else if (strcmp(mpl->image, "ub") == 0) suff = DOT_UB; else if (strcmp(mpl->image, "status") == 0) suff = DOT_STATUS; else if (strcmp(mpl->image, "val") == 0) suff = DOT_VAL; else if (strcmp(mpl->image, "dual") == 0) suff = DOT_DUAL; else error(mpl, "suffix .%s invalid", mpl->image); get_token(mpl /* suffix */); } /* generate pseudo-code to take value of the object */ switch (avl_get_node_type(node)) { case A_INDEX: arg.index.slot = slot; arg.index.next = slot->list; code = make_code(mpl, O_INDEX, &arg, A_SYMBOLIC, 0); slot->list = code; break; case A_SET: arg.set.set = set; arg.set.list = list; code = make_code(mpl, O_MEMSET, &arg, A_ELEMSET, set->dimen); break; case A_PARAMETER: arg.par.par = par; arg.par.list = list; if (par->type == A_SYMBOLIC) code = make_code(mpl, O_MEMSYM, &arg, A_SYMBOLIC, 0); else code = make_code(mpl, O_MEMNUM, &arg, A_NUMERIC, 0); break; case A_VARIABLE: if (!mpl->flag_s && (suff == DOT_STATUS || suff == DOT_VAL || suff == DOT_DUAL)) error(mpl, "invalid reference to status, primal value, o" "r dual value of variable %s above solve statement", var->name); arg.var.var = var; arg.var.list = list; arg.var.suff = suff; code = make_code(mpl, O_MEMVAR, &arg, suff == DOT_NONE ? A_FORMULA : A_NUMERIC, 0); break; case A_CONSTRAINT: if (!mpl->flag_s && (suff == DOT_STATUS || suff == DOT_VAL || suff == DOT_DUAL)) error(mpl, "invalid reference to status, primal value, o" "r dual value of %s %s above solve statement", con->type == A_CONSTRAINT ? "constraint" : "objective" , con->name); arg.con.con = con; arg.con.list = list; arg.con.suff = suff; code = make_code(mpl, O_MEMCON, &arg, A_NUMERIC, 0); break; default: xassert(node != node); } return code; } #endif /*---------------------------------------------------------------------- -- numeric_argument - parse argument passed to built-in function. -- -- This routine parses an argument passed to numeric built-in function -- using the syntax: -- -- ::= */ CODE *numeric_argument(MPL *mpl, char *func) { CODE *x; x = expression_5(mpl); /* convert the argument to numeric type, if necessary */ if (x->type == A_SYMBOLIC) x = make_unary(mpl, O_CVTNUM, x, A_NUMERIC, 0); /* check that now the argument is of numeric type */ if (x->type != A_NUMERIC) error(mpl, "argument for %s has invalid type", func); xassert(x->dim == 0); return x; } #if 1 /* 15/VII-2006 */ CODE *symbolic_argument(MPL *mpl, char *func) { CODE *x; x = expression_5(mpl); /* convert the argument to symbolic type, if necessary */ if (x->type == A_NUMERIC) x = make_unary(mpl, O_CVTSYM, x, A_SYMBOLIC, 0); /* check that now the argument is of symbolic type */ if (x->type != A_SYMBOLIC) error(mpl, "argument for %s has invalid type", func); xassert(x->dim == 0); return x; } #endif #if 1 /* 15/VII-2006 */ CODE *elemset_argument(MPL *mpl, char *func) { CODE *x; x = expression_9(mpl); if (x->type != A_ELEMSET) error(mpl, "argument for %s has invalid type", func); xassert(x->dim > 0); return x; } #endif /*---------------------------------------------------------------------- -- function_reference - parse reference to built-in function. -- -- This routine parses primary expression using the syntax: -- -- ::= abs ( ) -- ::= ceil ( ) -- ::= floor ( ) -- ::= exp ( ) -- ::= log ( ) -- ::= log10 ( ) -- ::= max ( ) -- ::= min ( ) -- ::= sqrt ( ) -- ::= sin ( ) -- ::= cos ( ) -- ::= atan ( ) -- ::= atan2 ( , ) -- ::= round ( ) -- ::= round ( , ) -- ::= trunc ( ) -- ::= trunc ( , ) -- ::= Irand224 ( ) -- ::= Uniform01 ( ) -- ::= Uniform ( , ) -- ::= Normal01 ( ) -- ::= Normal ( , ) -- ::= card ( ) -- ::= length ( ) -- ::= substr ( , ) -- ::= substr ( , , ) -- ::= str2time ( , ) -- ::= time2str ( , ) -- ::= gmtime ( ) -- ::= -- ::= , */ CODE *function_reference(MPL *mpl) { CODE *code; OPERANDS arg; int op; char func[15+1]; /* determine operation code */ xassert(mpl->token == T_NAME); if (strcmp(mpl->image, "abs") == 0) op = O_ABS; else if (strcmp(mpl->image, "ceil") == 0) op = O_CEIL; else if (strcmp(mpl->image, "floor") == 0) op = O_FLOOR; else if (strcmp(mpl->image, "exp") == 0) op = O_EXP; else if (strcmp(mpl->image, "log") == 0) op = O_LOG; else if (strcmp(mpl->image, "log10") == 0) op = O_LOG10; else if (strcmp(mpl->image, "sqrt") == 0) op = O_SQRT; else if (strcmp(mpl->image, "sin") == 0) op = O_SIN; else if (strcmp(mpl->image, "cos") == 0) op = O_COS; else if (strcmp(mpl->image, "atan") == 0) op = O_ATAN; else if (strcmp(mpl->image, "min") == 0) op = O_MIN; else if (strcmp(mpl->image, "max") == 0) op = O_MAX; else if (strcmp(mpl->image, "round") == 0) op = O_ROUND; else if (strcmp(mpl->image, "trunc") == 0) op = O_TRUNC; else if (strcmp(mpl->image, "Irand224") == 0) op = O_IRAND224; else if (strcmp(mpl->image, "Uniform01") == 0) op = O_UNIFORM01; else if (strcmp(mpl->image, "Uniform") == 0) op = O_UNIFORM; else if (strcmp(mpl->image, "Normal01") == 0) op = O_NORMAL01; else if (strcmp(mpl->image, "Normal") == 0) op = O_NORMAL; else if (strcmp(mpl->image, "card") == 0) op = O_CARD; else if (strcmp(mpl->image, "length") == 0) op = O_LENGTH; else if (strcmp(mpl->image, "substr") == 0) op = O_SUBSTR; else if (strcmp(mpl->image, "str2time") == 0) op = O_STR2TIME; else if (strcmp(mpl->image, "time2str") == 0) op = O_TIME2STR; else if (strcmp(mpl->image, "gmtime") == 0) op = O_GMTIME; else error(mpl, "function %s unknown", mpl->image); /* save symbolic name of the function */ strcpy(func, mpl->image); xassert(strlen(func) < sizeof(func)); get_token(mpl /* */); /* check the left parenthesis that follows the function name */ xassert(mpl->token == T_LEFT); get_token(mpl /* ( */); /* parse argument list */ if (op == O_MIN || op == O_MAX) { /* min and max allow arbitrary number of arguments */ arg.list = create_arg_list(mpl); /* parse argument list */ for (;;) { /* parse argument and append it to the operands list */ arg.list = expand_arg_list(mpl, arg.list, numeric_argument(mpl, func)); /* check a token that follows the argument */ if (mpl->token == T_COMMA) get_token(mpl /* , */); else if (mpl->token == T_RIGHT) break; else error(mpl, "syntax error in argument list for %s", func); } } else if (op == O_IRAND224 || op == O_UNIFORM01 || op == O_NORMAL01 || op == O_GMTIME) { /* Irand224, Uniform01, Normal01, gmtime need no arguments */ if (mpl->token != T_RIGHT) error(mpl, "%s needs no arguments", func); } else if (op == O_UNIFORM || op == O_NORMAL) { /* Uniform and Normal need two arguments */ /* parse the first argument */ arg.arg.x = numeric_argument(mpl, func); /* check a token that follows the first argument */ if (mpl->token == T_COMMA) ; else if (mpl->token == T_RIGHT) error(mpl, "%s needs two arguments", func); else error(mpl, "syntax error in argument for %s", func); get_token(mpl /* , */); /* parse the second argument */ arg.arg.y = numeric_argument(mpl, func); /* check a token that follows the second argument */ if (mpl->token == T_COMMA) error(mpl, "%s needs two argument", func); else if (mpl->token == T_RIGHT) ; else error(mpl, "syntax error in argument for %s", func); } else if (op == O_ATAN || op == O_ROUND || op == O_TRUNC) { /* atan, round, and trunc need one or two arguments */ /* parse the first argument */ arg.arg.x = numeric_argument(mpl, func); /* parse the second argument, if specified */ if (mpl->token == T_COMMA) { switch (op) { case O_ATAN: op = O_ATAN2; break; case O_ROUND: op = O_ROUND2; break; case O_TRUNC: op = O_TRUNC2; break; default: xassert(op != op); } get_token(mpl /* , */); arg.arg.y = numeric_argument(mpl, func); } /* check a token that follows the last argument */ if (mpl->token == T_COMMA) error(mpl, "%s needs one or two arguments", func); else if (mpl->token == T_RIGHT) ; else error(mpl, "syntax error in argument for %s", func); } else if (op == O_SUBSTR) { /* substr needs two or three arguments */ /* parse the first argument */ arg.arg.x = symbolic_argument(mpl, func); /* check a token that follows the first argument */ if (mpl->token == T_COMMA) ; else if (mpl->token == T_RIGHT) error(mpl, "%s needs two or three arguments", func); else error(mpl, "syntax error in argument for %s", func); get_token(mpl /* , */); /* parse the second argument */ arg.arg.y = numeric_argument(mpl, func); /* parse the third argument, if specified */ if (mpl->token == T_COMMA) { op = O_SUBSTR3; get_token(mpl /* , */); arg.arg.z = numeric_argument(mpl, func); } /* check a token that follows the last argument */ if (mpl->token == T_COMMA) error(mpl, "%s needs two or three arguments", func); else if (mpl->token == T_RIGHT) ; else error(mpl, "syntax error in argument for %s", func); } else if (op == O_STR2TIME) { /* str2time needs two arguments, both symbolic */ /* parse the first argument */ arg.arg.x = symbolic_argument(mpl, func); /* check a token that follows the first argument */ if (mpl->token == T_COMMA) ; else if (mpl->token == T_RIGHT) error(mpl, "%s needs two arguments", func); else error(mpl, "syntax error in argument for %s", func); get_token(mpl /* , */); /* parse the second argument */ arg.arg.y = symbolic_argument(mpl, func); /* check a token that follows the second argument */ if (mpl->token == T_COMMA) error(mpl, "%s needs two argument", func); else if (mpl->token == T_RIGHT) ; else error(mpl, "syntax error in argument for %s", func); } else if (op == O_TIME2STR) { /* time2str needs two arguments, numeric and symbolic */ /* parse the first argument */ arg.arg.x = numeric_argument(mpl, func); /* check a token that follows the first argument */ if (mpl->token == T_COMMA) ; else if (mpl->token == T_RIGHT) error(mpl, "%s needs two arguments", func); else error(mpl, "syntax error in argument for %s", func); get_token(mpl /* , */); /* parse the second argument */ arg.arg.y = symbolic_argument(mpl, func); /* check a token that follows the second argument */ if (mpl->token == T_COMMA) error(mpl, "%s needs two argument", func); else if (mpl->token == T_RIGHT) ; else error(mpl, "syntax error in argument for %s", func); } else { /* other functions need one argument */ if (op == O_CARD) arg.arg.x = elemset_argument(mpl, func); else if (op == O_LENGTH) arg.arg.x = symbolic_argument(mpl, func); else arg.arg.x = numeric_argument(mpl, func); /* check a token that follows the argument */ if (mpl->token == T_COMMA) error(mpl, "%s needs one argument", func); else if (mpl->token == T_RIGHT) ; else error(mpl, "syntax error in argument for %s", func); } /* make pseudo-code to call the built-in function */ if (op == O_SUBSTR || op == O_SUBSTR3 || op == O_TIME2STR) code = make_code(mpl, op, &arg, A_SYMBOLIC, 0); else code = make_code(mpl, op, &arg, A_NUMERIC, 0); /* the reference ends with the right parenthesis */ xassert(mpl->token == T_RIGHT); get_token(mpl /* ) */); return code; } /*---------------------------------------------------------------------- -- create_domain - create empty domain. -- -- This routine creates empty domain, which is initially empty, i.e. -- has no domain blocks. */ DOMAIN *create_domain(MPL *mpl) { DOMAIN *domain; domain = alloc(DOMAIN); domain->list = NULL; domain->code = NULL; return domain; } /*---------------------------------------------------------------------- -- create_block - create empty domain block. -- -- This routine creates empty domain block, which is initially empty, -- i.e. has no domain slots. */ DOMAIN_BLOCK *create_block(MPL *mpl) { DOMAIN_BLOCK *block; block = alloc(DOMAIN_BLOCK); block->list = NULL; block->code = NULL; block->backup = NULL; block->next = NULL; return block; } /*---------------------------------------------------------------------- -- append_block - append domain block to specified domain. -- -- This routine adds given domain block to the end of the block list of -- specified domain. */ void append_block(MPL *mpl, DOMAIN *domain, DOMAIN_BLOCK *block) { DOMAIN_BLOCK *temp; xassert(mpl == mpl); xassert(domain != NULL); xassert(block != NULL); xassert(block->next == NULL); if (domain->list == NULL) domain->list = block; else { for (temp = domain->list; temp->next != NULL; temp = temp->next); temp->next = block; } return; } /*---------------------------------------------------------------------- -- append_slot - create and append new slot to domain block. -- -- This routine creates new domain slot and adds it to the end of slot -- list of specified domain block. -- -- The parameter name is symbolic name of the dummy index associated -- with the slot (the character string must be allocated). NULL means -- the dummy index is not explicitly specified. -- -- The parameter code is pseudo-code for computing symbolic value, at -- which the dummy index is bounded. NULL means the dummy index is free -- in the domain scope. */ DOMAIN_SLOT *append_slot(MPL *mpl, DOMAIN_BLOCK *block, char *name, CODE *code) { DOMAIN_SLOT *slot, *temp; xassert(block != NULL); slot = alloc(DOMAIN_SLOT); slot->name = name; slot->code = code; slot->value = NULL; slot->list = NULL; slot->next = NULL; if (block->list == NULL) block->list = slot; else { for (temp = block->list; temp->next != NULL; temp = temp->next); temp->next = slot; } return slot; } /*---------------------------------------------------------------------- -- expression_list - parse expression list. -- -- This routine parses a list of one or more expressions enclosed into -- the parentheses using the syntax: -- -- ::= ( ) -- ::= -- ::= , -- -- Note that this construction may have three different meanings: -- -- 1. If consists of only one expression, is a parenthesized expression, which may be of any -- valid type (not necessarily 1-tuple). -- -- 2. If consists of several expressions separated by -- commae, where no expression is undeclared symbolic name, is a n-tuple. -- -- 3. If consists of several expressions separated by -- commae, where at least one expression is undeclared symbolic name -- (that denotes a dummy index), is a slice and -- can be only used as constituent of indexing expression. */ #define max_dim 20 /* maximal number of components allowed within parentheses */ CODE *expression_list(MPL *mpl) { CODE *code; OPERANDS arg; struct { char *name; CODE *code; } list[1+max_dim]; int flag_x, next_token, dim, j, slice = 0; xassert(mpl->token == T_LEFT); /* the flag, which allows recognizing undeclared symbolic names as dummy indices, will be automatically reset by get_token(), so save it before scanning the next token */ flag_x = mpl->flag_x; get_token(mpl /* ( */); /* parse */ for (dim = 1; ; dim++) { if (dim > max_dim) error(mpl, "too many components within parentheses"); /* current component of can be either dummy index or expression */ if (mpl->token == T_NAME) { /* symbolic name is recognized as dummy index only if: the flag, which allows that, is set, and the name is followed by comma or right parenthesis, and the name is undeclared */ get_token(mpl /* */); next_token = mpl->token; unget_token(mpl); if (!(flag_x && (next_token == T_COMMA || next_token == T_RIGHT) && avl_find_node(mpl->tree, mpl->image) == NULL)) { /* this is not dummy index */ goto expr; } /* all dummy indices within the same slice must have unique symbolic names */ for (j = 1; j < dim; j++) { if (list[j].name != NULL && strcmp(list[j].name, mpl->image) == 0) error(mpl, "duplicate dummy index %s not allowed", mpl->image); } /* current component of is dummy index */ list[dim].name = dmp_get_atomv(mpl->pool, strlen(mpl->image)+1); strcpy(list[dim].name, mpl->image); list[dim].code = NULL; get_token(mpl /* */); /* is a slice, because at least one dummy index has appeared */ slice = 1; /* note that the context ( ) is not allowed, i.e. in this case is considered as a parenthesized expression */ if (dim == 1 && mpl->token == T_RIGHT) error(mpl, "%s not defined", list[dim].name); } else expr: { /* current component of is expression */ code = expression_13(mpl); /* if the current expression is followed by comma or it is not the very first expression, entire is n-tuple or slice, in which case the current expression should be converted to symbolic type, if necessary */ if (mpl->token == T_COMMA || dim > 1) { if (code->type == A_NUMERIC) code = make_unary(mpl, O_CVTSYM, code, A_SYMBOLIC, 0); /* now the expression must be of symbolic type */ if (code->type != A_SYMBOLIC) error(mpl, "component expression has invalid type"); xassert(code->dim == 0); } list[dim].name = NULL; list[dim].code = code; } /* check a token that follows the current component */ if (mpl->token == T_COMMA) get_token(mpl /* , */); else if (mpl->token == T_RIGHT) break; else error(mpl, "right parenthesis missing where expected"); } /* generate pseudo-code for */ if (dim == 1 && !slice) { /* is a parenthesized expression */ code = list[1].code; } else if (!slice) { /* is a n-tuple */ arg.list = create_arg_list(mpl); for (j = 1; j <= dim; j++) arg.list = expand_arg_list(mpl, arg.list, list[j].code); code = make_code(mpl, O_TUPLE, &arg, A_TUPLE, dim); } else { /* is a slice */ arg.slice = create_block(mpl); for (j = 1; j <= dim; j++) append_slot(mpl, arg.slice, list[j].name, list[j].code); /* note that actually pseudo-codes with op = O_SLICE are never evaluated */ code = make_code(mpl, O_SLICE, &arg, A_TUPLE, dim); } get_token(mpl /* ) */); /* if is a slice, there must be the keyword 'in', which follows the right parenthesis */ if (slice && mpl->token != T_IN) error(mpl, "keyword in missing where expected"); /* if the slice flag is set and there is the keyword 'in', which follows , the latter must be a slice */ if (flag_x && mpl->token == T_IN && !slice) { if (dim == 1) error(mpl, "syntax error in indexing expression"); else error(mpl, "0-ary slice not allowed"); } return code; } /*---------------------------------------------------------------------- -- literal set - parse literal set. -- -- This routine parses literal set using the syntax: -- -- ::= { } -- ::= -- ::= , -- ::= -- -- It is assumed that the left curly brace and the very first member -- expression that follows it are already parsed. The right curly brace -- remains unscanned on exit. */ CODE *literal_set(MPL *mpl, CODE *code) { OPERANDS arg; int j; xassert(code != NULL); arg.list = create_arg_list(mpl); /* parse */ for (j = 1; ; j++) { /* all member expressions must be n-tuples; so, if the current expression is not n-tuple, convert it to 1-tuple */ if (code->type == A_NUMERIC) code = make_unary(mpl, O_CVTSYM, code, A_SYMBOLIC, 0); if (code->type == A_SYMBOLIC) code = make_unary(mpl, O_CVTTUP, code, A_TUPLE, 1); /* now the expression must be n-tuple */ if (code->type != A_TUPLE) error(mpl, "member expression has invalid type"); /* all member expressions must have identical dimension */ if (arg.list != NULL && arg.list->x->dim != code->dim) error(mpl, "member %d has %d component%s while member %d ha" "s %d component%s", j-1, arg.list->x->dim, arg.list->x->dim == 1 ? "" : "s", j, code->dim, code->dim == 1 ? "" : "s"); /* append the current expression to the member list */ arg.list = expand_arg_list(mpl, arg.list, code); /* check a token that follows the current expression */ if (mpl->token == T_COMMA) get_token(mpl /* , */); else if (mpl->token == T_RBRACE) break; else error(mpl, "syntax error in literal set"); /* parse the next expression that follows the comma */ code = expression_5(mpl); } /* generate pseudo-code for */ code = make_code(mpl, O_MAKE, &arg, A_ELEMSET, arg.list->x->dim); return code; } /*---------------------------------------------------------------------- -- indexing_expression - parse indexing expression. -- -- This routine parses indexing expression using the syntax: -- -- ::= -- ::= { } -- ::= { : } -- ::= -- ::= , -- ::= -- ::= in -- ::= in -- ::= -- ::= ( ) -- ::= -- ::= -- -- This routine creates domain for , where each -- domain block corresponds to , and each domain slot -- corresponds to individual indexing position. */ DOMAIN *indexing_expression(MPL *mpl) { DOMAIN *domain; DOMAIN_BLOCK *block; DOMAIN_SLOT *slot; CODE *code; xassert(mpl->token == T_LBRACE); get_token(mpl /* { */); if (mpl->token == T_RBRACE) error(mpl, "empty indexing expression not allowed"); /* create domain to be constructed */ domain = create_domain(mpl); /* parse either or that follows the left brace */ for (;;) { /* domain block for is not created yet */ block = NULL; /* pseudo-code for is not generated yet */ code = NULL; /* check a token, which begins with */ if (mpl->token == T_NAME) { /* it is a symbolic name */ int next_token; char *name; /* symbolic name is recognized as dummy index only if it is followed by the keyword 'in' and not declared */ get_token(mpl /* */); next_token = mpl->token; unget_token(mpl); if (!(next_token == T_IN && avl_find_node(mpl->tree, mpl->image) == NULL)) { /* this is not dummy index; the symbolic name begins an expression, which is either or the very first in */ goto expr; } /* create domain block with one slot, which is assigned the dummy index */ block = create_block(mpl); name = dmp_get_atomv(mpl->pool, strlen(mpl->image)+1); strcpy(name, mpl->image); append_slot(mpl, block, name, NULL); get_token(mpl /* */); /* the keyword 'in' is already checked above */ xassert(mpl->token == T_IN); get_token(mpl /* in */); /* that follows the keyword 'in' will be parsed below */ } else if (mpl->token == T_LEFT) { /* it is the left parenthesis; parse expression that begins with this parenthesis (the flag is set in order to allow recognizing slices; see the routine expression_list) */ mpl->flag_x = 1; code = expression_9(mpl); if (code->op != O_SLICE) { /* this is either or the very first in */ goto expr; } /* this is a slice; besides the corresponding domain block is already created by expression_list() */ block = code->arg.slice; code = NULL; /* is not parsed yet */ /* the keyword 'in' following the slice is already checked by expression_list() */ xassert(mpl->token == T_IN); get_token(mpl /* in */); /* that follows the keyword 'in' will be parsed below */ } expr: /* parse expression that follows either the keyword 'in' (in which case it can be as well as the very first in ); note that this expression can be already parsed above */ if (code == NULL) code = expression_9(mpl); /* check the type of the expression just parsed */ if (code->type != A_ELEMSET) { /* it is not and therefore it can only be the very first in ; however, then there must be no dummy index neither slice between the left brace and this expression */ if (block != NULL) error(mpl, "domain expression has invalid type"); /* parse the rest part of and make this set be , i.e. the construction {a, b, c} is parsed as it were written as {A}, where A = {a, b, c} is a temporary elemental set */ code = literal_set(mpl, code); } /* now pseudo-code for has been built */ xassert(code != NULL); xassert(code->type == A_ELEMSET); xassert(code->dim > 0); /* if domain block for the current is still not created, create it for fake slice of the same dimension as */ if (block == NULL) { int j; block = create_block(mpl); for (j = 1; j <= code->dim; j++) append_slot(mpl, block, NULL, NULL); } /* number of indexing positions in must be the same as dimension of n-tuples in basic set */ { int dim = 0; for (slot = block->list; slot != NULL; slot = slot->next) dim++; if (dim != code->dim) error(mpl,"%d %s specified for set of dimension %d", dim, dim == 1 ? "index" : "indices", code->dim); } /* store pseudo-code for in the domain block */ xassert(block->code == NULL); block->code = code; /* and append the domain block to the domain */ append_block(mpl, domain, block); /* the current has been completely parsed; include all its dummy indices into the symbolic name table to make them available for referencing from expressions; implicit declarations of dummy indices remain valid while the corresponding domain scope is valid */ for (slot = block->list; slot != NULL; slot = slot->next) if (slot->name != NULL) { AVLNODE *node; xassert(avl_find_node(mpl->tree, slot->name) == NULL); node = avl_insert_node(mpl->tree, slot->name); avl_set_node_type(node, A_INDEX); avl_set_node_link(node, (void *)slot); } /* check a token that follows */ if (mpl->token == T_COMMA) get_token(mpl /* , */); else if (mpl->token == T_COLON || mpl->token == T_RBRACE) break; else error(mpl, "syntax error in indexing expression"); } /* parse that follows the colon */ if (mpl->token == T_COLON) { get_token(mpl /* : */); code = expression_13(mpl); /* convert the expression to logical type, if necessary */ if (code->type == A_SYMBOLIC) code = make_unary(mpl, O_CVTNUM, code, A_NUMERIC, 0); if (code->type == A_NUMERIC) code = make_unary(mpl, O_CVTLOG, code, A_LOGICAL, 0); /* now the expression must be of logical type */ if (code->type != A_LOGICAL) error(mpl, "expression following colon has invalid type"); xassert(code->dim == 0); domain->code = code; /* the right brace must follow the logical expression */ if (mpl->token != T_RBRACE) error(mpl, "syntax error in indexing expression"); } get_token(mpl /* } */); return domain; } /*---------------------------------------------------------------------- -- close_scope - close scope of indexing expression. -- -- The routine closes the scope of indexing expression specified by its -- domain and thereby makes all dummy indices introduced in the indexing -- expression no longer available for referencing. */ void close_scope(MPL *mpl, DOMAIN *domain) { DOMAIN_BLOCK *block; DOMAIN_SLOT *slot; AVLNODE *node; xassert(domain != NULL); /* remove all dummy indices from the symbolic names table */ for (block = domain->list; block != NULL; block = block->next) { for (slot = block->list; slot != NULL; slot = slot->next) { if (slot->name != NULL) { node = avl_find_node(mpl->tree, slot->name); xassert(node != NULL); xassert(avl_get_node_type(node) == A_INDEX); avl_delete_node(mpl->tree, node); } } } return; } /*---------------------------------------------------------------------- -- iterated_expression - parse iterated expression. -- -- This routine parses primary expression using the syntax: -- -- ::= -- ::= sum -- ::= prod -- ::= min -- ::= max -- ::= exists -- -- ::= forall -- -- ::= setof -- -- Note that parsing "integrand" depends on the iterated operator. */ #if 1 /* 07/IX-2008 */ static void link_up(CODE *code) { /* if we have something like sum{(i+1,j,k-1) in E} x[i,j,k], where i and k are dummy indices defined out of the iterated expression, we should link up pseudo-code for computing i+1 and k-1 to pseudo-code for computing the iterated expression; this is needed to invalidate current value of the iterated expression once i or k have been changed */ DOMAIN_BLOCK *block; DOMAIN_SLOT *slot; for (block = code->arg.loop.domain->list; block != NULL; block = block->next) { for (slot = block->list; slot != NULL; slot = slot->next) { if (slot->code != NULL) { xassert(slot->code->up == NULL); slot->code->up = code; } } } return; } #endif CODE *iterated_expression(MPL *mpl) { CODE *code; OPERANDS arg; int op; char opstr[8]; /* determine operation code */ xassert(mpl->token == T_NAME); if (strcmp(mpl->image, "sum") == 0) op = O_SUM; else if (strcmp(mpl->image, "prod") == 0) op = O_PROD; else if (strcmp(mpl->image, "min") == 0) op = O_MINIMUM; else if (strcmp(mpl->image, "max") == 0) op = O_MAXIMUM; else if (strcmp(mpl->image, "forall") == 0) op = O_FORALL; else if (strcmp(mpl->image, "exists") == 0) op = O_EXISTS; else if (strcmp(mpl->image, "setof") == 0) op = O_SETOF; else error(mpl, "operator %s unknown", mpl->image); strcpy(opstr, mpl->image); xassert(strlen(opstr) < sizeof(opstr)); get_token(mpl /* */); /* check the left brace that follows the operator name */ xassert(mpl->token == T_LBRACE); /* parse indexing expression that controls iterating */ arg.loop.domain = indexing_expression(mpl); /* parse "integrand" expression and generate pseudo-code */ switch (op) { case O_SUM: case O_PROD: case O_MINIMUM: case O_MAXIMUM: arg.loop.x = expression_3(mpl); /* convert the integrand to numeric type, if necessary */ if (arg.loop.x->type == A_SYMBOLIC) arg.loop.x = make_unary(mpl, O_CVTNUM, arg.loop.x, A_NUMERIC, 0); /* now the integrand must be of numeric type or linear form (the latter is only allowed for the sum operator) */ if (!(arg.loop.x->type == A_NUMERIC || op == O_SUM && arg.loop.x->type == A_FORMULA)) err: error(mpl, "integrand following %s{...} has invalid type" , opstr); xassert(arg.loop.x->dim == 0); /* generate pseudo-code */ code = make_code(mpl, op, &arg, arg.loop.x->type, 0); break; case O_FORALL: case O_EXISTS: arg.loop.x = expression_12(mpl); /* convert the integrand to logical type, if necessary */ if (arg.loop.x->type == A_SYMBOLIC) arg.loop.x = make_unary(mpl, O_CVTNUM, arg.loop.x, A_NUMERIC, 0); if (arg.loop.x->type == A_NUMERIC) arg.loop.x = make_unary(mpl, O_CVTLOG, arg.loop.x, A_LOGICAL, 0); /* now the integrand must be of logical type */ if (arg.loop.x->type != A_LOGICAL) goto err; xassert(arg.loop.x->dim == 0); /* generate pseudo-code */ code = make_code(mpl, op, &arg, A_LOGICAL, 0); break; case O_SETOF: arg.loop.x = expression_5(mpl); /* convert the integrand to 1-tuple, if necessary */ if (arg.loop.x->type == A_NUMERIC) arg.loop.x = make_unary(mpl, O_CVTSYM, arg.loop.x, A_SYMBOLIC, 0); if (arg.loop.x->type == A_SYMBOLIC) arg.loop.x = make_unary(mpl, O_CVTTUP, arg.loop.x, A_TUPLE, 1); /* now the integrand must be n-tuple */ if (arg.loop.x->type != A_TUPLE) goto err; xassert(arg.loop.x->dim > 0); /* generate pseudo-code */ code = make_code(mpl, op, &arg, A_ELEMSET, arg.loop.x->dim); break; default: xassert(op != op); } /* close the scope of the indexing expression */ close_scope(mpl, arg.loop.domain); #if 1 /* 07/IX-2008 */ link_up(code); #endif return code; } /*---------------------------------------------------------------------- -- domain_arity - determine arity of domain. -- -- This routine returns arity of specified domain, which is number of -- its free dummy indices. */ int domain_arity(MPL *mpl, DOMAIN *domain) { DOMAIN_BLOCK *block; DOMAIN_SLOT *slot; int arity; xassert(mpl == mpl); arity = 0; for (block = domain->list; block != NULL; block = block->next) for (slot = block->list; slot != NULL; slot = slot->next) if (slot->code == NULL) arity++; return arity; } /*---------------------------------------------------------------------- -- set_expression - parse set expression. -- -- This routine parses primary expression using the syntax: -- -- ::= { } -- ::= */ CODE *set_expression(MPL *mpl) { CODE *code; OPERANDS arg; xassert(mpl->token == T_LBRACE); get_token(mpl /* { */); /* check a token that follows the left brace */ if (mpl->token == T_RBRACE) { /* it is the right brace, so the resultant is an empty set of dimension 1 */ arg.list = NULL; /* generate pseudo-code to build the resultant set */ code = make_code(mpl, O_MAKE, &arg, A_ELEMSET, 1); get_token(mpl /* } */); } else { /* the next token begins an indexing expression */ unget_token(mpl); arg.loop.domain = indexing_expression(mpl); arg.loop.x = NULL; /* integrand is not used */ /* close the scope of the indexing expression */ close_scope(mpl, arg.loop.domain); /* generate pseudo-code to build the resultant set */ code = make_code(mpl, O_BUILD, &arg, A_ELEMSET, domain_arity(mpl, arg.loop.domain)); #if 1 /* 07/IX-2008 */ link_up(code); #endif } return code; } /*---------------------------------------------------------------------- -- branched_expression - parse conditional expression. -- -- This routine parses primary expression using the syntax: -- -- ::= -- ::= if then -- ::= if then -- else -- ::= */ CODE *branched_expression(MPL *mpl) { CODE *code, *x, *y, *z; xassert(mpl->token == T_IF); get_token(mpl /* if */); /* parse that follows 'if' */ x = expression_13(mpl); /* convert the expression to logical type, if necessary */ if (x->type == A_SYMBOLIC) x = make_unary(mpl, O_CVTNUM, x, A_NUMERIC, 0); if (x->type == A_NUMERIC) x = make_unary(mpl, O_CVTLOG, x, A_LOGICAL, 0); /* now the expression must be of logical type */ if (x->type != A_LOGICAL) error(mpl, "expression following if has invalid type"); xassert(x->dim == 0); /* the keyword 'then' must follow the logical expression */ if (mpl->token != T_THEN) error(mpl, "keyword then missing where expected"); get_token(mpl /* then */); /* parse that follows 'then' and check its type */ y = expression_9(mpl); if (!(y->type == A_NUMERIC || y->type == A_SYMBOLIC || y->type == A_ELEMSET || y->type == A_FORMULA)) error(mpl, "expression following then has invalid type"); /* if the expression that follows the keyword 'then' is elemental set, the keyword 'else' cannot be omitted; otherwise else-part is optional */ if (mpl->token != T_ELSE) { if (y->type == A_ELEMSET) error(mpl, "keyword else missing where expected"); z = NULL; goto skip; } get_token(mpl /* else */); /* parse that follow 'else' and check its type */ z = expression_9(mpl); if (!(z->type == A_NUMERIC || z->type == A_SYMBOLIC || z->type == A_ELEMSET || z->type == A_FORMULA)) error(mpl, "expression following else has invalid type"); /* convert to identical types, if necessary */ if (y->type == A_FORMULA || z->type == A_FORMULA) { if (y->type == A_SYMBOLIC) y = make_unary(mpl, O_CVTNUM, y, A_NUMERIC, 0); if (y->type == A_NUMERIC) y = make_unary(mpl, O_CVTLFM, y, A_FORMULA, 0); if (z->type == A_SYMBOLIC) z = make_unary(mpl, O_CVTNUM, z, A_NUMERIC, 0); if (z->type == A_NUMERIC) z = make_unary(mpl, O_CVTLFM, z, A_FORMULA, 0); } if (y->type == A_SYMBOLIC || z->type == A_SYMBOLIC) { if (y->type == A_NUMERIC) y = make_unary(mpl, O_CVTSYM, y, A_SYMBOLIC, 0); if (z->type == A_NUMERIC) z = make_unary(mpl, O_CVTSYM, z, A_SYMBOLIC, 0); } /* now both expressions must have identical types */ if (y->type != z->type) error(mpl, "expressions following then and else have incompati" "ble types"); /* and identical dimensions */ if (y->dim != z->dim) error(mpl, "expressions following then and else have different" " dimensions %d and %d, respectively", y->dim, z->dim); skip: /* generate pseudo-code to perform branching */ code = make_ternary(mpl, O_FORK, x, y, z, y->type, y->dim); return code; } /*---------------------------------------------------------------------- -- primary_expression - parse primary expression. -- -- This routine parses primary expression using the syntax: -- -- ::= -- ::= Infinity -- ::= -- ::= -- ::= -- ::= [ ] -- ::= -- ::= [ ] -- ::= -- ::= [ ] -- ::= ( ) -- ::= ( ) -- ::= -- ::= { } -- ::= -- ::= -- -- For complete list of syntactic rules for see -- comments to the corresponding parsing routines. */ CODE *primary_expression(MPL *mpl) { CODE *code; if (mpl->token == T_NUMBER) { /* parse numeric literal */ code = numeric_literal(mpl); } #if 1 /* 21/VII-2006 */ else if (mpl->token == T_INFINITY) { /* parse "infinity" */ OPERANDS arg; arg.num = DBL_MAX; code = make_code(mpl, O_NUMBER, &arg, A_NUMERIC, 0); get_token(mpl /* Infinity */); } #endif else if (mpl->token == T_STRING) { /* parse string literal */ code = string_literal(mpl); } else if (mpl->token == T_NAME) { int next_token; get_token(mpl /* */); next_token = mpl->token; unget_token(mpl); /* check a token that follows */ switch (next_token) { case T_LBRACKET: /* parse reference to subscripted object */ code = object_reference(mpl); break; case T_LEFT: /* parse reference to built-in function */ code = function_reference(mpl); break; case T_LBRACE: /* parse iterated expression */ code = iterated_expression(mpl); break; default: /* parse reference to unsubscripted object */ code = object_reference(mpl); break; } } else if (mpl->token == T_LEFT) { /* parse parenthesized expression */ code = expression_list(mpl); } else if (mpl->token == T_LBRACE) { /* parse set expression */ code = set_expression(mpl); } else if (mpl->token == T_IF) { /* parse conditional expression */ code = branched_expression(mpl); } else if (is_reserved(mpl)) { /* other reserved keywords cannot be used here */ error(mpl, "invalid use of reserved keyword %s", mpl->image); } else error(mpl, "syntax error in expression"); return code; } /*---------------------------------------------------------------------- -- error_preceding - raise error if preceding operand has wrong type. -- -- This routine is called to raise error if operand that precedes some -- infix operator has invalid type. */ void error_preceding(MPL *mpl, char *opstr) { error(mpl, "operand preceding %s has invalid type", opstr); /* no return */ } /*---------------------------------------------------------------------- -- error_following - raise error if following operand has wrong type. -- -- This routine is called to raise error if operand that follows some -- infix operator has invalid type. */ void error_following(MPL *mpl, char *opstr) { error(mpl, "operand following %s has invalid type", opstr); /* no return */ } /*---------------------------------------------------------------------- -- error_dimension - raise error if operands have different dimension. -- -- This routine is called to raise error if two operands of some infix -- operator have different dimension. */ void error_dimension(MPL *mpl, char *opstr, int dim1, int dim2) { error(mpl, "operands preceding and following %s have different di" "mensions %d and %d, respectively", opstr, dim1, dim2); /* no return */ } /*---------------------------------------------------------------------- -- expression_0 - parse expression of level 0. -- -- This routine parses expression of level 0 using the syntax: -- -- ::= */ CODE *expression_0(MPL *mpl) { CODE *code; code = primary_expression(mpl); return code; } /*---------------------------------------------------------------------- -- expression_1 - parse expression of level 1. -- -- This routine parses expression of level 1 using the syntax: -- -- ::= -- ::= -- ::= -- ::= ^ | ** */ CODE *expression_1(MPL *mpl) { CODE *x, *y; char opstr[8]; x = expression_0(mpl); if (mpl->token == T_POWER) { strcpy(opstr, mpl->image); xassert(strlen(opstr) < sizeof(opstr)); if (x->type == A_SYMBOLIC) x = make_unary(mpl, O_CVTNUM, x, A_NUMERIC, 0); if (x->type != A_NUMERIC) error_preceding(mpl, opstr); get_token(mpl /* ^ | ** */); if (mpl->token == T_PLUS || mpl->token == T_MINUS) y = expression_2(mpl); else y = expression_1(mpl); if (y->type == A_SYMBOLIC) y = make_unary(mpl, O_CVTNUM, y, A_NUMERIC, 0); if (y->type != A_NUMERIC) error_following(mpl, opstr); x = make_binary(mpl, O_POWER, x, y, A_NUMERIC, 0); } return x; } /*---------------------------------------------------------------------- -- expression_2 - parse expression of level 2. -- -- This routine parses expression of level 2 using the syntax: -- -- ::= -- ::= + -- ::= - */ CODE *expression_2(MPL *mpl) { CODE *x; if (mpl->token == T_PLUS) { get_token(mpl /* + */); x = expression_1(mpl); if (x->type == A_SYMBOLIC) x = make_unary(mpl, O_CVTNUM, x, A_NUMERIC, 0); if (!(x->type == A_NUMERIC || x->type == A_FORMULA)) error_following(mpl, "+"); x = make_unary(mpl, O_PLUS, x, x->type, 0); } else if (mpl->token == T_MINUS) { get_token(mpl /* - */); x = expression_1(mpl); if (x->type == A_SYMBOLIC) x = make_unary(mpl, O_CVTNUM, x, A_NUMERIC, 0); if (!(x->type == A_NUMERIC || x->type == A_FORMULA)) error_following(mpl, "-"); x = make_unary(mpl, O_MINUS, x, x->type, 0); } else x = expression_1(mpl); return x; } /*---------------------------------------------------------------------- -- expression_3 - parse expression of level 3. -- -- This routine parses expression of level 3 using the syntax: -- -- ::= -- ::= * -- ::= / -- ::= div -- ::= mod */ CODE *expression_3(MPL *mpl) { CODE *x, *y; x = expression_2(mpl); for (;;) { if (mpl->token == T_ASTERISK) { if (x->type == A_SYMBOLIC) x = make_unary(mpl, O_CVTNUM, x, A_NUMERIC, 0); if (!(x->type == A_NUMERIC || x->type == A_FORMULA)) error_preceding(mpl, "*"); get_token(mpl /* * */); y = expression_2(mpl); if (y->type == A_SYMBOLIC) y = make_unary(mpl, O_CVTNUM, y, A_NUMERIC, 0); if (!(y->type == A_NUMERIC || y->type == A_FORMULA)) error_following(mpl, "*"); if (x->type == A_FORMULA && y->type == A_FORMULA) error(mpl, "multiplication of linear forms not allowed"); if (x->type == A_NUMERIC && y->type == A_NUMERIC) x = make_binary(mpl, O_MUL, x, y, A_NUMERIC, 0); else x = make_binary(mpl, O_MUL, x, y, A_FORMULA, 0); } else if (mpl->token == T_SLASH) { if (x->type == A_SYMBOLIC) x = make_unary(mpl, O_CVTNUM, x, A_NUMERIC, 0); if (!(x->type == A_NUMERIC || x->type == A_FORMULA)) error_preceding(mpl, "/"); get_token(mpl /* / */); y = expression_2(mpl); if (y->type == A_SYMBOLIC) y = make_unary(mpl, O_CVTNUM, y, A_NUMERIC, 0); if (y->type != A_NUMERIC) error_following(mpl, "/"); if (x->type == A_NUMERIC) x = make_binary(mpl, O_DIV, x, y, A_NUMERIC, 0); else x = make_binary(mpl, O_DIV, x, y, A_FORMULA, 0); } else if (mpl->token == T_DIV) { if (x->type == A_SYMBOLIC) x = make_unary(mpl, O_CVTNUM, x, A_NUMERIC, 0); if (x->type != A_NUMERIC) error_preceding(mpl, "div"); get_token(mpl /* div */); y = expression_2(mpl); if (y->type == A_SYMBOLIC) y = make_unary(mpl, O_CVTNUM, y, A_NUMERIC, 0); if (y->type != A_NUMERIC) error_following(mpl, "div"); x = make_binary(mpl, O_IDIV, x, y, A_NUMERIC, 0); } else if (mpl->token == T_MOD) { if (x->type == A_SYMBOLIC) x = make_unary(mpl, O_CVTNUM, x, A_NUMERIC, 0); if (x->type != A_NUMERIC) error_preceding(mpl, "mod"); get_token(mpl /* mod */); y = expression_2(mpl); if (y->type == A_SYMBOLIC) y = make_unary(mpl, O_CVTNUM, y, A_NUMERIC, 0); if (y->type != A_NUMERIC) error_following(mpl, "mod"); x = make_binary(mpl, O_MOD, x, y, A_NUMERIC, 0); } else break; } return x; } /*---------------------------------------------------------------------- -- expression_4 - parse expression of level 4. -- -- This routine parses expression of level 4 using the syntax: -- -- ::= -- ::= + -- ::= - -- ::= less */ CODE *expression_4(MPL *mpl) { CODE *x, *y; x = expression_3(mpl); for (;;) { if (mpl->token == T_PLUS) { if (x->type == A_SYMBOLIC) x = make_unary(mpl, O_CVTNUM, x, A_NUMERIC, 0); if (!(x->type == A_NUMERIC || x->type == A_FORMULA)) error_preceding(mpl, "+"); get_token(mpl /* + */); y = expression_3(mpl); if (y->type == A_SYMBOLIC) y = make_unary(mpl, O_CVTNUM, y, A_NUMERIC, 0); if (!(y->type == A_NUMERIC || y->type == A_FORMULA)) error_following(mpl, "+"); if (x->type == A_NUMERIC && y->type == A_FORMULA) x = make_unary(mpl, O_CVTLFM, x, A_FORMULA, 0); if (x->type == A_FORMULA && y->type == A_NUMERIC) y = make_unary(mpl, O_CVTLFM, y, A_FORMULA, 0); x = make_binary(mpl, O_ADD, x, y, x->type, 0); } else if (mpl->token == T_MINUS) { if (x->type == A_SYMBOLIC) x = make_unary(mpl, O_CVTNUM, x, A_NUMERIC, 0); if (!(x->type == A_NUMERIC || x->type == A_FORMULA)) error_preceding(mpl, "-"); get_token(mpl /* - */); y = expression_3(mpl); if (y->type == A_SYMBOLIC) y = make_unary(mpl, O_CVTNUM, y, A_NUMERIC, 0); if (!(y->type == A_NUMERIC || y->type == A_FORMULA)) error_following(mpl, "-"); if (x->type == A_NUMERIC && y->type == A_FORMULA) x = make_unary(mpl, O_CVTLFM, x, A_FORMULA, 0); if (x->type == A_FORMULA && y->type == A_NUMERIC) y = make_unary(mpl, O_CVTLFM, y, A_FORMULA, 0); x = make_binary(mpl, O_SUB, x, y, x->type, 0); } else if (mpl->token == T_LESS) { if (x->type == A_SYMBOLIC) x = make_unary(mpl, O_CVTNUM, x, A_NUMERIC, 0); if (x->type != A_NUMERIC) error_preceding(mpl, "less"); get_token(mpl /* less */); y = expression_3(mpl); if (y->type == A_SYMBOLIC) y = make_unary(mpl, O_CVTNUM, y, A_NUMERIC, 0); if (y->type != A_NUMERIC) error_following(mpl, "less"); x = make_binary(mpl, O_LESS, x, y, A_NUMERIC, 0); } else break; } return x; } /*---------------------------------------------------------------------- -- expression_5 - parse expression of level 5. -- -- This routine parses expression of level 5 using the syntax: -- -- ::= -- ::= & */ CODE *expression_5(MPL *mpl) { CODE *x, *y; x = expression_4(mpl); for (;;) { if (mpl->token == T_CONCAT) { if (x->type == A_NUMERIC) x = make_unary(mpl, O_CVTSYM, x, A_SYMBOLIC, 0); if (x->type != A_SYMBOLIC) error_preceding(mpl, "&"); get_token(mpl /* & */); y = expression_4(mpl); if (y->type == A_NUMERIC) y = make_unary(mpl, O_CVTSYM, y, A_SYMBOLIC, 0); if (y->type != A_SYMBOLIC) error_following(mpl, "&"); x = make_binary(mpl, O_CONCAT, x, y, A_SYMBOLIC, 0); } else break; } return x; } /*---------------------------------------------------------------------- -- expression_6 - parse expression of level 6. -- -- This routine parses expression of level 6 using the syntax: -- -- ::= -- ::= .. -- ::= .. by -- */ CODE *expression_6(MPL *mpl) { CODE *x, *y, *z; x = expression_5(mpl); if (mpl->token == T_DOTS) { if (x->type == A_SYMBOLIC) x = make_unary(mpl, O_CVTNUM, x, A_NUMERIC, 0); if (x->type != A_NUMERIC) error_preceding(mpl, ".."); get_token(mpl /* .. */); y = expression_5(mpl); if (y->type == A_SYMBOLIC) y = make_unary(mpl, O_CVTNUM, y, A_NUMERIC, 0); if (y->type != A_NUMERIC) error_following(mpl, ".."); if (mpl->token == T_BY) { get_token(mpl /* by */); z = expression_5(mpl); if (z->type == A_SYMBOLIC) z = make_unary(mpl, O_CVTNUM, z, A_NUMERIC, 0); if (z->type != A_NUMERIC) error_following(mpl, "by"); } else z = NULL; x = make_ternary(mpl, O_DOTS, x, y, z, A_ELEMSET, 1); } return x; } /*---------------------------------------------------------------------- -- expression_7 - parse expression of level 7. -- -- This routine parses expression of level 7 using the syntax: -- -- ::= -- ::= cross */ CODE *expression_7(MPL *mpl) { CODE *x, *y; x = expression_6(mpl); for (;;) { if (mpl->token == T_CROSS) { if (x->type != A_ELEMSET) error_preceding(mpl, "cross"); get_token(mpl /* cross */); y = expression_6(mpl); if (y->type != A_ELEMSET) error_following(mpl, "cross"); x = make_binary(mpl, O_CROSS, x, y, A_ELEMSET, x->dim + y->dim); } else break; } return x; } /*---------------------------------------------------------------------- -- expression_8 - parse expression of level 8. -- -- This routine parses expression of level 8 using the syntax: -- -- ::= -- ::= inter */ CODE *expression_8(MPL *mpl) { CODE *x, *y; x = expression_7(mpl); for (;;) { if (mpl->token == T_INTER) { if (x->type != A_ELEMSET) error_preceding(mpl, "inter"); get_token(mpl /* inter */); y = expression_7(mpl); if (y->type != A_ELEMSET) error_following(mpl, "inter"); if (x->dim != y->dim) error_dimension(mpl, "inter", x->dim, y->dim); x = make_binary(mpl, O_INTER, x, y, A_ELEMSET, x->dim); } else break; } return x; } /*---------------------------------------------------------------------- -- expression_9 - parse expression of level 9. -- -- This routine parses expression of level 9 using the syntax: -- -- ::= -- ::= union -- ::= diff -- ::= symdiff */ CODE *expression_9(MPL *mpl) { CODE *x, *y; x = expression_8(mpl); for (;;) { if (mpl->token == T_UNION) { if (x->type != A_ELEMSET) error_preceding(mpl, "union"); get_token(mpl /* union */); y = expression_8(mpl); if (y->type != A_ELEMSET) error_following(mpl, "union"); if (x->dim != y->dim) error_dimension(mpl, "union", x->dim, y->dim); x = make_binary(mpl, O_UNION, x, y, A_ELEMSET, x->dim); } else if (mpl->token == T_DIFF) { if (x->type != A_ELEMSET) error_preceding(mpl, "diff"); get_token(mpl /* diff */); y = expression_8(mpl); if (y->type != A_ELEMSET) error_following(mpl, "diff"); if (x->dim != y->dim) error_dimension(mpl, "diff", x->dim, y->dim); x = make_binary(mpl, O_DIFF, x, y, A_ELEMSET, x->dim); } else if (mpl->token == T_SYMDIFF) { if (x->type != A_ELEMSET) error_preceding(mpl, "symdiff"); get_token(mpl /* symdiff */); y = expression_8(mpl); if (y->type != A_ELEMSET) error_following(mpl, "symdiff"); if (x->dim != y->dim) error_dimension(mpl, "symdiff", x->dim, y->dim); x = make_binary(mpl, O_SYMDIFF, x, y, A_ELEMSET, x->dim); } else break; } return x; } /*---------------------------------------------------------------------- -- expression_10 - parse expression of level 10. -- -- This routine parses expression of level 10 using the syntax: -- -- ::= -- ::= -- ::= < | <= | = | == | >= | > | <> | != | in | not in | ! in | -- within | not within | ! within */ CODE *expression_10(MPL *mpl) { CODE *x, *y; int op = -1; char opstr[16]; x = expression_9(mpl); strcpy(opstr, ""); switch (mpl->token) { case T_LT: op = O_LT; break; case T_LE: op = O_LE; break; case T_EQ: op = O_EQ; break; case T_GE: op = O_GE; break; case T_GT: op = O_GT; break; case T_NE: op = O_NE; break; case T_IN: op = O_IN; break; case T_WITHIN: op = O_WITHIN; break; case T_NOT: strcpy(opstr, mpl->image); get_token(mpl /* not | ! */); if (mpl->token == T_IN) op = O_NOTIN; else if (mpl->token == T_WITHIN) op = O_NOTWITHIN; else error(mpl, "invalid use of %s", opstr); strcat(opstr, " "); break; default: goto done; } strcat(opstr, mpl->image); xassert(strlen(opstr) < sizeof(opstr)); switch (op) { case O_EQ: case O_NE: #if 1 /* 02/VIII-2008 */ case O_LT: case O_LE: case O_GT: case O_GE: #endif if (!(x->type == A_NUMERIC || x->type == A_SYMBOLIC)) error_preceding(mpl, opstr); get_token(mpl /* */); y = expression_9(mpl); if (!(y->type == A_NUMERIC || y->type == A_SYMBOLIC)) error_following(mpl, opstr); if (x->type == A_NUMERIC && y->type == A_SYMBOLIC) x = make_unary(mpl, O_CVTSYM, x, A_SYMBOLIC, 0); if (x->type == A_SYMBOLIC && y->type == A_NUMERIC) y = make_unary(mpl, O_CVTSYM, y, A_SYMBOLIC, 0); x = make_binary(mpl, op, x, y, A_LOGICAL, 0); break; #if 0 /* 02/VIII-2008 */ case O_LT: case O_LE: case O_GT: case O_GE: if (x->type == A_SYMBOLIC) x = make_unary(mpl, O_CVTNUM, x, A_NUMERIC, 0); if (x->type != A_NUMERIC) error_preceding(mpl, opstr); get_token(mpl /* */); y = expression_9(mpl); if (y->type == A_SYMBOLIC) y = make_unary(mpl, O_CVTNUM, y, A_NUMERIC, 0); if (y->type != A_NUMERIC) error_following(mpl, opstr); x = make_binary(mpl, op, x, y, A_LOGICAL, 0); break; #endif case O_IN: case O_NOTIN: if (x->type == A_NUMERIC) x = make_unary(mpl, O_CVTSYM, x, A_SYMBOLIC, 0); if (x->type == A_SYMBOLIC) x = make_unary(mpl, O_CVTTUP, x, A_TUPLE, 1); if (x->type != A_TUPLE) error_preceding(mpl, opstr); get_token(mpl /* */); y = expression_9(mpl); if (y->type != A_ELEMSET) error_following(mpl, opstr); if (x->dim != y->dim) error_dimension(mpl, opstr, x->dim, y->dim); x = make_binary(mpl, op, x, y, A_LOGICAL, 0); break; case O_WITHIN: case O_NOTWITHIN: if (x->type != A_ELEMSET) error_preceding(mpl, opstr); get_token(mpl /* */); y = expression_9(mpl); if (y->type != A_ELEMSET) error_following(mpl, opstr); if (x->dim != y->dim) error_dimension(mpl, opstr, x->dim, y->dim); x = make_binary(mpl, op, x, y, A_LOGICAL, 0); break; default: xassert(op != op); } done: return x; } /*---------------------------------------------------------------------- -- expression_11 - parse expression of level 11. -- -- This routine parses expression of level 11 using the syntax: -- -- ::= -- ::= not -- ::= ! */ CODE *expression_11(MPL *mpl) { CODE *x; char opstr[8]; if (mpl->token == T_NOT) { strcpy(opstr, mpl->image); xassert(strlen(opstr) < sizeof(opstr)); get_token(mpl /* not | ! */); x = expression_10(mpl); if (x->type == A_SYMBOLIC) x = make_unary(mpl, O_CVTNUM, x, A_NUMERIC, 0); if (x->type == A_NUMERIC) x = make_unary(mpl, O_CVTLOG, x, A_LOGICAL, 0); if (x->type != A_LOGICAL) error_following(mpl, opstr); x = make_unary(mpl, O_NOT, x, A_LOGICAL, 0); } else x = expression_10(mpl); return x; } /*---------------------------------------------------------------------- -- expression_12 - parse expression of level 12. -- -- This routine parses expression of level 12 using the syntax: -- -- ::= -- ::= and -- ::= && */ CODE *expression_12(MPL *mpl) { CODE *x, *y; char opstr[8]; x = expression_11(mpl); for (;;) { if (mpl->token == T_AND) { strcpy(opstr, mpl->image); xassert(strlen(opstr) < sizeof(opstr)); if (x->type == A_SYMBOLIC) x = make_unary(mpl, O_CVTNUM, x, A_NUMERIC, 0); if (x->type == A_NUMERIC) x = make_unary(mpl, O_CVTLOG, x, A_LOGICAL, 0); if (x->type != A_LOGICAL) error_preceding(mpl, opstr); get_token(mpl /* and | && */); y = expression_11(mpl); if (y->type == A_SYMBOLIC) y = make_unary(mpl, O_CVTNUM, y, A_NUMERIC, 0); if (y->type == A_NUMERIC) y = make_unary(mpl, O_CVTLOG, y, A_LOGICAL, 0); if (y->type != A_LOGICAL) error_following(mpl, opstr); x = make_binary(mpl, O_AND, x, y, A_LOGICAL, 0); } else break; } return x; } /*---------------------------------------------------------------------- -- expression_13 - parse expression of level 13. -- -- This routine parses expression of level 13 using the syntax: -- -- ::= -- ::= or -- ::= || */ CODE *expression_13(MPL *mpl) { CODE *x, *y; char opstr[8]; x = expression_12(mpl); for (;;) { if (mpl->token == T_OR) { strcpy(opstr, mpl->image); xassert(strlen(opstr) < sizeof(opstr)); if (x->type == A_SYMBOLIC) x = make_unary(mpl, O_CVTNUM, x, A_NUMERIC, 0); if (x->type == A_NUMERIC) x = make_unary(mpl, O_CVTLOG, x, A_LOGICAL, 0); if (x->type != A_LOGICAL) error_preceding(mpl, opstr); get_token(mpl /* or | || */); y = expression_12(mpl); if (y->type == A_SYMBOLIC) y = make_unary(mpl, O_CVTNUM, y, A_NUMERIC, 0); if (y->type == A_NUMERIC) y = make_unary(mpl, O_CVTLOG, y, A_LOGICAL, 0); if (y->type != A_LOGICAL) error_following(mpl, opstr); x = make_binary(mpl, O_OR, x, y, A_LOGICAL, 0); } else break; } return x; } /*---------------------------------------------------------------------- -- set_statement - parse set statement. -- -- This routine parses set statement using the syntax: -- -- ::= set -- ; -- ::= -- ::= -- ::= -- ::= -- ::= -- ::= , dimen -- ::= , within -- ::= , := -- ::= , default -- -- Commae in are optional and may be omitted anywhere. */ SET *set_statement(MPL *mpl) { SET *set; int dimen_used = 0; xassert(is_keyword(mpl, "set")); get_token(mpl /* set */); /* symbolic name must follow the keyword 'set' */ if (mpl->token == T_NAME) ; else if (is_reserved(mpl)) error(mpl, "invalid use of reserved keyword %s", mpl->image); else error(mpl, "symbolic name missing where expected"); /* there must be no other object with the same name */ if (avl_find_node(mpl->tree, mpl->image) != NULL) error(mpl, "%s multiply declared", mpl->image); /* create model set */ set = alloc(SET); set->name = dmp_get_atomv(mpl->pool, strlen(mpl->image)+1); strcpy(set->name, mpl->image); set->alias = NULL; set->dim = 0; set->domain = NULL; set->dimen = 0; set->within = NULL; set->assign = NULL; set->option = NULL; set->gadget = NULL; set->data = 0; set->array = NULL; get_token(mpl /* */); /* parse optional alias */ if (mpl->token == T_STRING) { set->alias = dmp_get_atomv(mpl->pool, strlen(mpl->image)+1); strcpy(set->alias, mpl->image); get_token(mpl /* */); } /* parse optional indexing expression */ if (mpl->token == T_LBRACE) { set->domain = indexing_expression(mpl); set->dim = domain_arity(mpl, set->domain); } /* include the set name in the symbolic names table */ { AVLNODE *node; node = avl_insert_node(mpl->tree, set->name); avl_set_node_type(node, A_SET); avl_set_node_link(node, (void *)set); } /* parse the list of optional attributes */ for (;;) { if (mpl->token == T_COMMA) get_token(mpl /* , */); else if (mpl->token == T_SEMICOLON) break; if (is_keyword(mpl, "dimen")) { /* dimension of set members */ int dimen; get_token(mpl /* dimen */); if (!(mpl->token == T_NUMBER && 1.0 <= mpl->value && mpl->value <= 20.0 && floor(mpl->value) == mpl->value)) error(mpl, "dimension must be integer between 1 and 20"); dimen = (int)(mpl->value + 0.5); if (dimen_used) error(mpl, "at most one dimension attribute allowed"); if (set->dimen > 0) error(mpl, "dimension %d conflicts with dimension %d alr" "eady determined", dimen, set->dimen); set->dimen = dimen; dimen_used = 1; get_token(mpl /* */); } else if (mpl->token == T_WITHIN || mpl->token == T_IN) { /* restricting superset */ WITHIN *within, *temp; if (mpl->token == T_IN && !mpl->as_within) { warning(mpl, "keyword in understood as within"); mpl->as_within = 1; } get_token(mpl /* within */); /* create new restricting superset list entry and append it to the within-list */ within = alloc(WITHIN); within->code = NULL; within->next = NULL; if (set->within == NULL) set->within = within; else { for (temp = set->within; temp->next != NULL; temp = temp->next); temp->next = within; } /* parse an expression that follows 'within' */ within->code = expression_9(mpl); if (within->code->type != A_ELEMSET) error(mpl, "expression following within has invalid type" ); xassert(within->code->dim > 0); /* check/set dimension of set members */ if (set->dimen == 0) set->dimen = within->code->dim; if (set->dimen != within->code->dim) error(mpl, "set expression following within must have di" "mension %d rather than %d", set->dimen, within->code->dim); } else if (mpl->token == T_ASSIGN) { /* assignment expression */ if (!(set->assign == NULL && set->option == NULL && set->gadget == NULL)) err: error(mpl, "at most one := or default/data allowed"); get_token(mpl /* := */); /* parse an expression that follows ':=' */ set->assign = expression_9(mpl); if (set->assign->type != A_ELEMSET) error(mpl, "expression following := has invalid type"); xassert(set->assign->dim > 0); /* check/set dimension of set members */ if (set->dimen == 0) set->dimen = set->assign->dim; if (set->dimen != set->assign->dim) error(mpl, "set expression following := must have dimens" "ion %d rather than %d", set->dimen, set->assign->dim); } else if (is_keyword(mpl, "default")) { /* expression for default value */ if (!(set->assign == NULL && set->option == NULL)) goto err; get_token(mpl /* := */); /* parse an expression that follows 'default' */ set->option = expression_9(mpl); if (set->option->type != A_ELEMSET) error(mpl, "expression following default has invalid typ" "e"); xassert(set->option->dim > 0); /* check/set dimension of set members */ if (set->dimen == 0) set->dimen = set->option->dim; if (set->dimen != set->option->dim) error(mpl, "set expression following default must have d" "imension %d rather than %d", set->dimen, set->option->dim); } #if 1 /* 12/XII-2008 */ else if (is_keyword(mpl, "data")) { /* gadget to initialize the set by data from plain set */ GADGET *gadget; AVLNODE *node; int i, k, fff[20]; if (!(set->assign == NULL && set->gadget == NULL)) goto err; get_token(mpl /* data */); set->gadget = gadget = alloc(GADGET); /* set name must follow the keyword 'data' */ if (mpl->token == T_NAME) ; else if (is_reserved(mpl)) error(mpl, "invalid use of reserved keyword %s", mpl->image); else error(mpl, "set name missing where expected"); /* find the set in the symbolic name table */ node = avl_find_node(mpl->tree, mpl->image); if (node == NULL) error(mpl, "%s not defined", mpl->image); if (avl_get_node_type(node) != A_SET) err1: error(mpl, "%s not a plain set", mpl->image); gadget->set = avl_get_node_link(node); if (gadget->set->dim != 0) goto err1; if (gadget->set == set) error(mpl, "set cannot be initialized by itself"); /* check and set dimensions */ if (set->dim >= gadget->set->dimen) err2: error(mpl, "dimension of %s too small", mpl->image); if (set->dimen == 0) set->dimen = gadget->set->dimen - set->dim; if (set->dim + set->dimen > gadget->set->dimen) goto err2; else if (set->dim + set->dimen < gadget->set->dimen) error(mpl, "dimension of %s too big", mpl->image); get_token(mpl /* set name */); /* left parenthesis must follow the set name */ if (mpl->token == T_LEFT) get_token(mpl /* ( */); else error(mpl, "left parenthesis missing where expected"); /* parse permutation of component numbers */ for (k = 0; k < gadget->set->dimen; k++) fff[k] = 0; k = 0; for (;;) { if (mpl->token != T_NUMBER) error(mpl, "component number missing where expected"); if (str2int(mpl->image, &i) != 0) err3: error(mpl, "component number must be integer between " "1 and %d", gadget->set->dimen); if (!(1 <= i && i <= gadget->set->dimen)) goto err3; if (fff[i-1] != 0) error(mpl, "component %d multiply specified", i); gadget->ind[k++] = i, fff[i-1] = 1; xassert(k <= gadget->set->dimen); get_token(mpl /* number */); if (mpl->token == T_COMMA) get_token(mpl /* , */); else if (mpl->token == T_RIGHT) break; else error(mpl, "syntax error in data attribute"); } if (k < gadget->set->dimen) error(mpl, "there are must be %d components rather than " "%d", gadget->set->dimen, k); get_token(mpl /* ) */); } #endif else error(mpl, "syntax error in set statement"); } /* close the domain scope */ if (set->domain != NULL) close_scope(mpl, set->domain); /* if dimension of set members is still unknown, set it to 1 */ if (set->dimen == 0) set->dimen = 1; /* the set statement has been completely parsed */ xassert(mpl->token == T_SEMICOLON); get_token(mpl /* ; */); return set; } /*---------------------------------------------------------------------- -- parameter_statement - parse parameter statement. -- -- This routine parses parameter statement using the syntax: -- -- ::= param -- ; -- ::= -- ::= -- ::= -- ::= -- ::= -- ::= , integer -- ::= , binary -- ::= , symbolic -- ::= , -- ::= , in -- ::= , := -- ::= , default -- ::= < | <= | = | == | >= | > | <> | != -- -- Commae in are optional and may be omitted anywhere. */ PARAMETER *parameter_statement(MPL *mpl) { PARAMETER *par; int integer_used = 0, binary_used = 0, symbolic_used = 0; xassert(is_keyword(mpl, "param")); get_token(mpl /* param */); /* symbolic name must follow the keyword 'param' */ if (mpl->token == T_NAME) ; else if (is_reserved(mpl)) error(mpl, "invalid use of reserved keyword %s", mpl->image); else error(mpl, "symbolic name missing where expected"); /* there must be no other object with the same name */ if (avl_find_node(mpl->tree, mpl->image) != NULL) error(mpl, "%s multiply declared", mpl->image); /* create model parameter */ par = alloc(PARAMETER); par->name = dmp_get_atomv(mpl->pool, strlen(mpl->image)+1); strcpy(par->name, mpl->image); par->alias = NULL; par->dim = 0; par->domain = NULL; par->type = A_NUMERIC; par->cond = NULL; par->in = NULL; par->assign = NULL; par->option = NULL; par->data = 0; par->defval = NULL; par->array = NULL; get_token(mpl /* */); /* parse optional alias */ if (mpl->token == T_STRING) { par->alias = dmp_get_atomv(mpl->pool, strlen(mpl->image)+1); strcpy(par->alias, mpl->image); get_token(mpl /* */); } /* parse optional indexing expression */ if (mpl->token == T_LBRACE) { par->domain = indexing_expression(mpl); par->dim = domain_arity(mpl, par->domain); } /* include the parameter name in the symbolic names table */ { AVLNODE *node; node = avl_insert_node(mpl->tree, par->name); avl_set_node_type(node, A_PARAMETER); avl_set_node_link(node, (void *)par); } /* parse the list of optional attributes */ for (;;) { if (mpl->token == T_COMMA) get_token(mpl /* , */); else if (mpl->token == T_SEMICOLON) break; if (is_keyword(mpl, "integer")) { if (integer_used) error(mpl, "at most one integer allowed"); if (par->type == A_SYMBOLIC) error(mpl, "symbolic parameter cannot be integer"); if (par->type != A_BINARY) par->type = A_INTEGER; integer_used = 1; get_token(mpl /* integer */); } else if (is_keyword(mpl, "binary")) bin: { if (binary_used) error(mpl, "at most one binary allowed"); if (par->type == A_SYMBOLIC) error(mpl, "symbolic parameter cannot be binary"); par->type = A_BINARY; binary_used = 1; get_token(mpl /* binary */); } else if (is_keyword(mpl, "logical")) { if (!mpl->as_binary) { warning(mpl, "keyword logical understood as binary"); mpl->as_binary = 1; } goto bin; } else if (is_keyword(mpl, "symbolic")) { if (symbolic_used) error(mpl, "at most one symbolic allowed"); if (par->type != A_NUMERIC) error(mpl, "integer or binary parameter cannot be symbol" "ic"); /* the parameter may be referenced from expressions given in the same parameter declaration, so its type must be completed before parsing that expressions */ if (!(par->cond == NULL && par->in == NULL && par->assign == NULL && par->option == NULL)) error(mpl, "keyword symbolic must precede any other para" "meter attributes"); par->type = A_SYMBOLIC; symbolic_used = 1; get_token(mpl /* symbolic */); } else if (mpl->token == T_LT || mpl->token == T_LE || mpl->token == T_EQ || mpl->token == T_GE || mpl->token == T_GT || mpl->token == T_NE) { /* restricting condition */ CONDITION *cond, *temp; char opstr[8]; /* create new restricting condition list entry and append it to the conditions list */ cond = alloc(CONDITION); switch (mpl->token) { case T_LT: cond->rho = O_LT, strcpy(opstr, mpl->image); break; case T_LE: cond->rho = O_LE, strcpy(opstr, mpl->image); break; case T_EQ: cond->rho = O_EQ, strcpy(opstr, mpl->image); break; case T_GE: cond->rho = O_GE, strcpy(opstr, mpl->image); break; case T_GT: cond->rho = O_GT, strcpy(opstr, mpl->image); break; case T_NE: cond->rho = O_NE, strcpy(opstr, mpl->image); break; default: xassert(mpl->token != mpl->token); } xassert(strlen(opstr) < sizeof(opstr)); cond->code = NULL; cond->next = NULL; if (par->cond == NULL) par->cond = cond; else { for (temp = par->cond; temp->next != NULL; temp = temp->next); temp->next = cond; } #if 0 /* 13/VIII-2008 */ if (par->type == A_SYMBOLIC && !(cond->rho == O_EQ || cond->rho == O_NE)) error(mpl, "inequality restriction not allowed"); #endif get_token(mpl /* rho */); /* parse an expression that follows relational operator */ cond->code = expression_5(mpl); if (!(cond->code->type == A_NUMERIC || cond->code->type == A_SYMBOLIC)) error(mpl, "expression following %s has invalid type", opstr); xassert(cond->code->dim == 0); /* convert to the parameter type, if necessary */ if (par->type != A_SYMBOLIC && cond->code->type == A_SYMBOLIC) cond->code = make_unary(mpl, O_CVTNUM, cond->code, A_NUMERIC, 0); if (par->type == A_SYMBOLIC && cond->code->type != A_SYMBOLIC) cond->code = make_unary(mpl, O_CVTSYM, cond->code, A_SYMBOLIC, 0); } else if (mpl->token == T_IN || mpl->token == T_WITHIN) { /* restricting superset */ WITHIN *in, *temp; if (mpl->token == T_WITHIN && !mpl->as_in) { warning(mpl, "keyword within understood as in"); mpl->as_in = 1; } get_token(mpl /* in */); /* create new restricting superset list entry and append it to the in-list */ in = alloc(WITHIN); in->code = NULL; in->next = NULL; if (par->in == NULL) par->in = in; else { for (temp = par->in; temp->next != NULL; temp = temp->next); temp->next = in; } /* parse an expression that follows 'in' */ in->code = expression_9(mpl); if (in->code->type != A_ELEMSET) error(mpl, "expression following in has invalid type"); xassert(in->code->dim > 0); if (in->code->dim != 1) error(mpl, "set expression following in must have dimens" "ion 1 rather than %d", in->code->dim); } else if (mpl->token == T_ASSIGN) { /* assignment expression */ if (!(par->assign == NULL && par->option == NULL)) err: error(mpl, "at most one := or default allowed"); get_token(mpl /* := */); /* parse an expression that follows ':=' */ par->assign = expression_5(mpl); /* the expression must be of numeric/symbolic type */ if (!(par->assign->type == A_NUMERIC || par->assign->type == A_SYMBOLIC)) error(mpl, "expression following := has invalid type"); xassert(par->assign->dim == 0); /* convert to the parameter type, if necessary */ if (par->type != A_SYMBOLIC && par->assign->type == A_SYMBOLIC) par->assign = make_unary(mpl, O_CVTNUM, par->assign, A_NUMERIC, 0); if (par->type == A_SYMBOLIC && par->assign->type != A_SYMBOLIC) par->assign = make_unary(mpl, O_CVTSYM, par->assign, A_SYMBOLIC, 0); } else if (is_keyword(mpl, "default")) { /* expression for default value */ if (!(par->assign == NULL && par->option == NULL)) goto err; get_token(mpl /* default */); /* parse an expression that follows 'default' */ par->option = expression_5(mpl); if (!(par->option->type == A_NUMERIC || par->option->type == A_SYMBOLIC)) error(mpl, "expression following default has invalid typ" "e"); xassert(par->option->dim == 0); /* convert to the parameter type, if necessary */ if (par->type != A_SYMBOLIC && par->option->type == A_SYMBOLIC) par->option = make_unary(mpl, O_CVTNUM, par->option, A_NUMERIC, 0); if (par->type == A_SYMBOLIC && par->option->type != A_SYMBOLIC) par->option = make_unary(mpl, O_CVTSYM, par->option, A_SYMBOLIC, 0); } else error(mpl, "syntax error in parameter statement"); } /* close the domain scope */ if (par->domain != NULL) close_scope(mpl, par->domain); /* the parameter statement has been completely parsed */ xassert(mpl->token == T_SEMICOLON); get_token(mpl /* ; */); return par; } /*---------------------------------------------------------------------- -- variable_statement - parse variable statement. -- -- This routine parses variable statement using the syntax: -- -- ::= var -- ; -- ::= -- ::= -- ::= -- ::= -- ::= -- ::= , integer -- ::= , binary -- ::= , -- ::= >= | <= | = | == -- -- Commae in are optional and may be omitted anywhere. */ VARIABLE *variable_statement(MPL *mpl) { VARIABLE *var; int integer_used = 0, binary_used = 0; xassert(is_keyword(mpl, "var")); if (mpl->flag_s) error(mpl, "variable statement must precede solve statement"); get_token(mpl /* var */); /* symbolic name must follow the keyword 'var' */ if (mpl->token == T_NAME) ; else if (is_reserved(mpl)) error(mpl, "invalid use of reserved keyword %s", mpl->image); else error(mpl, "symbolic name missing where expected"); /* there must be no other object with the same name */ if (avl_find_node(mpl->tree, mpl->image) != NULL) error(mpl, "%s multiply declared", mpl->image); /* create model variable */ var = alloc(VARIABLE); var->name = dmp_get_atomv(mpl->pool, strlen(mpl->image)+1); strcpy(var->name, mpl->image); var->alias = NULL; var->dim = 0; var->domain = NULL; var->type = A_NUMERIC; var->lbnd = NULL; var->ubnd = NULL; var->array = NULL; get_token(mpl /* */); /* parse optional alias */ if (mpl->token == T_STRING) { var->alias = dmp_get_atomv(mpl->pool, strlen(mpl->image)+1); strcpy(var->alias, mpl->image); get_token(mpl /* */); } /* parse optional indexing expression */ if (mpl->token == T_LBRACE) { var->domain = indexing_expression(mpl); var->dim = domain_arity(mpl, var->domain); } /* include the variable name in the symbolic names table */ { AVLNODE *node; node = avl_insert_node(mpl->tree, var->name); avl_set_node_type(node, A_VARIABLE); avl_set_node_link(node, (void *)var); } /* parse the list of optional attributes */ for (;;) { if (mpl->token == T_COMMA) get_token(mpl /* , */); else if (mpl->token == T_SEMICOLON) break; if (is_keyword(mpl, "integer")) { if (integer_used) error(mpl, "at most one integer allowed"); if (var->type != A_BINARY) var->type = A_INTEGER; integer_used = 1; get_token(mpl /* integer */); } else if (is_keyword(mpl, "binary")) bin: { if (binary_used) error(mpl, "at most one binary allowed"); var->type = A_BINARY; binary_used = 1; get_token(mpl /* binary */); } else if (is_keyword(mpl, "logical")) { if (!mpl->as_binary) { warning(mpl, "keyword logical understood as binary"); mpl->as_binary = 1; } goto bin; } else if (is_keyword(mpl, "symbolic")) error(mpl, "variable cannot be symbolic"); else if (mpl->token == T_GE) { /* lower bound */ if (var->lbnd != NULL) { if (var->lbnd == var->ubnd) error(mpl, "both fixed value and lower bound not allo" "wed"); else error(mpl, "at most one lower bound allowed"); } get_token(mpl /* >= */); /* parse an expression that specifies the lower bound */ var->lbnd = expression_5(mpl); if (var->lbnd->type == A_SYMBOLIC) var->lbnd = make_unary(mpl, O_CVTNUM, var->lbnd, A_NUMERIC, 0); if (var->lbnd->type != A_NUMERIC) error(mpl, "expression following >= has invalid type"); xassert(var->lbnd->dim == 0); } else if (mpl->token == T_LE) { /* upper bound */ if (var->ubnd != NULL) { if (var->ubnd == var->lbnd) error(mpl, "both fixed value and upper bound not allo" "wed"); else error(mpl, "at most one upper bound allowed"); } get_token(mpl /* <= */); /* parse an expression that specifies the upper bound */ var->ubnd = expression_5(mpl); if (var->ubnd->type == A_SYMBOLIC) var->ubnd = make_unary(mpl, O_CVTNUM, var->ubnd, A_NUMERIC, 0); if (var->ubnd->type != A_NUMERIC) error(mpl, "expression following <= has invalid type"); xassert(var->ubnd->dim == 0); } else if (mpl->token == T_EQ) { /* fixed value */ char opstr[8]; if (!(var->lbnd == NULL && var->ubnd == NULL)) { if (var->lbnd == var->ubnd) error(mpl, "at most one fixed value allowed"); else if (var->lbnd != NULL) error(mpl, "both lower bound and fixed value not allo" "wed"); else error(mpl, "both upper bound and fixed value not allo" "wed"); } strcpy(opstr, mpl->image); xassert(strlen(opstr) < sizeof(opstr)); get_token(mpl /* = | == */); /* parse an expression that specifies the fixed value */ var->lbnd = expression_5(mpl); if (var->lbnd->type == A_SYMBOLIC) var->lbnd = make_unary(mpl, O_CVTNUM, var->lbnd, A_NUMERIC, 0); if (var->lbnd->type != A_NUMERIC) error(mpl, "expression following %s has invalid type", opstr); xassert(var->lbnd->dim == 0); /* indicate that the variable is fixed, not bounded */ var->ubnd = var->lbnd; } else if (mpl->token == T_LT || mpl->token == T_GT || mpl->token == T_NE) error(mpl, "strict bound not allowed"); else error(mpl, "syntax error in variable statement"); } /* close the domain scope */ if (var->domain != NULL) close_scope(mpl, var->domain); /* the variable statement has been completely parsed */ xassert(mpl->token == T_SEMICOLON); get_token(mpl /* ; */); return var; } /*---------------------------------------------------------------------- -- constraint_statement - parse constraint statement. -- -- This routine parses constraint statement using the syntax: -- -- ::= -- : ; -- ::= -- ::= subject to -- ::= subj to -- ::= s.t. -- ::= -- ::= -- ::= -- ::= -- ::= , >= -- ::= , <= -- ::= , = -- ::= , <= , <= -- ::= , >= , >= -- ::= -- -- Commae in are optional and may be omitted anywhere. */ CONSTRAINT *constraint_statement(MPL *mpl) { CONSTRAINT *con; CODE *first, *second, *third; int rho; char opstr[8]; if (mpl->flag_s) error(mpl, "constraint statement must precede solve statement") ; if (is_keyword(mpl, "subject")) { get_token(mpl /* subject */); if (!is_keyword(mpl, "to")) error(mpl, "keyword subject to incomplete"); get_token(mpl /* to */); } else if (is_keyword(mpl, "subj")) { get_token(mpl /* subj */); if (!is_keyword(mpl, "to")) error(mpl, "keyword subj to incomplete"); get_token(mpl /* to */); } else if (mpl->token == T_SPTP) get_token(mpl /* s.t. */); /* the current token must be symbolic name of constraint */ if (mpl->token == T_NAME) ; else if (is_reserved(mpl)) error(mpl, "invalid use of reserved keyword %s", mpl->image); else error(mpl, "symbolic name missing where expected"); /* there must be no other object with the same name */ if (avl_find_node(mpl->tree, mpl->image) != NULL) error(mpl, "%s multiply declared", mpl->image); /* create model constraint */ con = alloc(CONSTRAINT); con->name = dmp_get_atomv(mpl->pool, strlen(mpl->image)+1); strcpy(con->name, mpl->image); con->alias = NULL; con->dim = 0; con->domain = NULL; con->type = A_CONSTRAINT; con->code = NULL; con->lbnd = NULL; con->ubnd = NULL; con->array = NULL; get_token(mpl /* */); /* parse optional alias */ if (mpl->token == T_STRING) { con->alias = dmp_get_atomv(mpl->pool, strlen(mpl->image)+1); strcpy(con->alias, mpl->image); get_token(mpl /* */); } /* parse optional indexing expression */ if (mpl->token == T_LBRACE) { con->domain = indexing_expression(mpl); con->dim = domain_arity(mpl, con->domain); } /* include the constraint name in the symbolic names table */ { AVLNODE *node; node = avl_insert_node(mpl->tree, con->name); avl_set_node_type(node, A_CONSTRAINT); avl_set_node_link(node, (void *)con); } /* the colon must precede the first expression */ if (mpl->token != T_COLON) error(mpl, "colon missing where expected"); get_token(mpl /* : */); /* parse the first expression */ first = expression_5(mpl); if (first->type == A_SYMBOLIC) first = make_unary(mpl, O_CVTNUM, first, A_NUMERIC, 0); if (!(first->type == A_NUMERIC || first->type == A_FORMULA)) error(mpl, "expression following colon has invalid type"); xassert(first->dim == 0); /* relational operator must follow the first expression */ if (mpl->token == T_COMMA) get_token(mpl /* , */); switch (mpl->token) { case T_LE: case T_GE: case T_EQ: break; case T_LT: case T_GT: case T_NE: error(mpl, "strict inequality not allowed"); case T_SEMICOLON: error(mpl, "constraint must be equality or inequality"); default: goto err; } rho = mpl->token; strcpy(opstr, mpl->image); xassert(strlen(opstr) < sizeof(opstr)); get_token(mpl /* rho */); /* parse the second expression */ second = expression_5(mpl); if (second->type == A_SYMBOLIC) second = make_unary(mpl, O_CVTNUM, second, A_NUMERIC, 0); if (!(second->type == A_NUMERIC || second->type == A_FORMULA)) error(mpl, "expression following %s has invalid type", opstr); xassert(second->dim == 0); /* check a token that follow the second expression */ if (mpl->token == T_COMMA) { get_token(mpl /* , */); if (mpl->token == T_SEMICOLON) goto err; } if (mpl->token == T_LT || mpl->token == T_LE || mpl->token == T_EQ || mpl->token == T_GE || mpl->token == T_GT || mpl->token == T_NE) { /* it is another relational operator, therefore the constraint is double inequality */ if (rho == T_EQ || mpl->token != rho) error(mpl, "double inequality must be ... <= ... <= ... or " "... >= ... >= ..."); /* the first expression cannot be linear form */ if (first->type == A_FORMULA) error(mpl, "leftmost expression in double inequality cannot" " be linear form"); get_token(mpl /* rho */); /* parse the third expression */ third = expression_5(mpl); if (third->type == A_SYMBOLIC) third = make_unary(mpl, O_CVTNUM, second, A_NUMERIC, 0); if (!(third->type == A_NUMERIC || third->type == A_FORMULA)) error(mpl, "rightmost expression in double inequality const" "raint has invalid type"); xassert(third->dim == 0); /* the third expression also cannot be linear form */ if (third->type == A_FORMULA) error(mpl, "rightmost expression in double inequality canno" "t be linear form"); } else { /* the constraint is equality or single inequality */ third = NULL; } /* close the domain scope */ if (con->domain != NULL) close_scope(mpl, con->domain); /* convert all expressions to linear form, if necessary */ if (first->type != A_FORMULA) first = make_unary(mpl, O_CVTLFM, first, A_FORMULA, 0); if (second->type != A_FORMULA) second = make_unary(mpl, O_CVTLFM, second, A_FORMULA, 0); if (third != NULL) third = make_unary(mpl, O_CVTLFM, third, A_FORMULA, 0); /* arrange expressions in the constraint */ if (third == NULL) { /* the constraint is equality or single inequality */ switch (rho) { case T_LE: /* first <= second */ con->code = first; con->lbnd = NULL; con->ubnd = second; break; case T_GE: /* first >= second */ con->code = first; con->lbnd = second; con->ubnd = NULL; break; case T_EQ: /* first = second */ con->code = first; con->lbnd = second; con->ubnd = second; break; default: xassert(rho != rho); } } else { /* the constraint is double inequality */ switch (rho) { case T_LE: /* first <= second <= third */ con->code = second; con->lbnd = first; con->ubnd = third; break; case T_GE: /* first >= second >= third */ con->code = second; con->lbnd = third; con->ubnd = first; break; default: xassert(rho != rho); } } /* the constraint statement has been completely parsed */ if (mpl->token != T_SEMICOLON) err: error(mpl, "syntax error in constraint statement"); get_token(mpl /* ; */); return con; } /*---------------------------------------------------------------------- -- objective_statement - parse objective statement. -- -- This routine parses objective statement using the syntax: -- -- ::= : -- ; -- ::= minimize -- ::= maximize -- ::= -- ::= -- ::= -- ::= -- ::= */ CONSTRAINT *objective_statement(MPL *mpl) { CONSTRAINT *obj; int type; if (is_keyword(mpl, "minimize")) type = A_MINIMIZE; else if (is_keyword(mpl, "maximize")) type = A_MAXIMIZE; else xassert(mpl != mpl); if (mpl->flag_s) error(mpl, "objective statement must precede solve statement"); get_token(mpl /* minimize | maximize */); /* symbolic name must follow the verb 'minimize' or 'maximize' */ if (mpl->token == T_NAME) ; else if (is_reserved(mpl)) error(mpl, "invalid use of reserved keyword %s", mpl->image); else error(mpl, "symbolic name missing where expected"); /* there must be no other object with the same name */ if (avl_find_node(mpl->tree, mpl->image) != NULL) error(mpl, "%s multiply declared", mpl->image); /* create model objective */ obj = alloc(CONSTRAINT); obj->name = dmp_get_atomv(mpl->pool, strlen(mpl->image)+1); strcpy(obj->name, mpl->image); obj->alias = NULL; obj->dim = 0; obj->domain = NULL; obj->type = type; obj->code = NULL; obj->lbnd = NULL; obj->ubnd = NULL; obj->array = NULL; get_token(mpl /* */); /* parse optional alias */ if (mpl->token == T_STRING) { obj->alias = dmp_get_atomv(mpl->pool, strlen(mpl->image)+1); strcpy(obj->alias, mpl->image); get_token(mpl /* */); } /* parse optional indexing expression */ if (mpl->token == T_LBRACE) { obj->domain = indexing_expression(mpl); obj->dim = domain_arity(mpl, obj->domain); } /* include the constraint name in the symbolic names table */ { AVLNODE *node; node = avl_insert_node(mpl->tree, obj->name); avl_set_node_type(node, A_CONSTRAINT); avl_set_node_link(node, (void *)obj); } /* the colon must precede the objective expression */ if (mpl->token != T_COLON) error(mpl, "colon missing where expected"); get_token(mpl /* : */); /* parse the objective expression */ obj->code = expression_5(mpl); if (obj->code->type == A_SYMBOLIC) obj->code = make_unary(mpl, O_CVTNUM, obj->code, A_NUMERIC, 0); if (obj->code->type == A_NUMERIC) obj->code = make_unary(mpl, O_CVTLFM, obj->code, A_FORMULA, 0); if (obj->code->type != A_FORMULA) error(mpl, "expression following colon has invalid type"); xassert(obj->code->dim == 0); /* close the domain scope */ if (obj->domain != NULL) close_scope(mpl, obj->domain); /* the objective statement has been completely parsed */ if (mpl->token != T_SEMICOLON) error(mpl, "syntax error in objective statement"); get_token(mpl /* ; */); return obj; } #if 1 /* 11/II-2008 */ /*********************************************************************** * table_statement - parse table statement * * This routine parses table statement using the syntax: * * ::= *
::= * * ::= * table
IN : * [ ] , ; * ::= * ::= * ::= * ::= * ::= , * ::= * ::= <- * ::= * ::= , * ::= * ::= , * ::= * ::= ~ * * ::= * table
OUT : * ; * ::= * ::= * ::= , * ::= * ::= ~ */ TABLE *table_statement(MPL *mpl) { TABLE *tab; TABARG *last_arg, *arg; TABFLD *last_fld, *fld; TABIN *last_in, *in; TABOUT *last_out, *out; AVLNODE *node; int nflds; char name[MAX_LENGTH+1]; xassert(is_keyword(mpl, "table")); get_token(mpl /* solve */); /* symbolic name must follow the keyword table */ if (mpl->token == T_NAME) ; else if (is_reserved(mpl)) error(mpl, "invalid use of reserved keyword %s", mpl->image); else error(mpl, "symbolic name missing where expected"); /* there must be no other object with the same name */ if (avl_find_node(mpl->tree, mpl->image) != NULL) error(mpl, "%s multiply declared", mpl->image); /* create data table */ tab = alloc(TABLE); tab->name = dmp_get_atomv(mpl->pool, strlen(mpl->image)+1); strcpy(tab->name, mpl->image); get_token(mpl /* */); /* parse optional alias */ if (mpl->token == T_STRING) { tab->alias = dmp_get_atomv(mpl->pool, strlen(mpl->image)+1); strcpy(tab->alias, mpl->image); get_token(mpl /* */); } else tab->alias = NULL; /* parse optional indexing expression */ if (mpl->token == T_LBRACE) { /* this is output table */ tab->type = A_OUTPUT; tab->u.out.domain = indexing_expression(mpl); if (!is_keyword(mpl, "OUT")) error(mpl, "keyword OUT missing where expected"); get_token(mpl /* OUT */); } else { /* this is input table */ tab->type = A_INPUT; if (!is_keyword(mpl, "IN")) error(mpl, "keyword IN missing where expected"); get_token(mpl /* IN */); } /* parse argument list */ tab->arg = last_arg = NULL; for (;;) { /* create argument list entry */ arg = alloc(TABARG); /* parse argument expression */ if (mpl->token == T_COMMA || mpl->token == T_COLON || mpl->token == T_SEMICOLON) error(mpl, "argument expression missing where expected"); arg->code = expression_5(mpl); /* convert the result to symbolic type, if necessary */ if (arg->code->type == A_NUMERIC) arg->code = make_unary(mpl, O_CVTSYM, arg->code, A_SYMBOLIC, 0); /* check that now the result is of symbolic type */ if (arg->code->type != A_SYMBOLIC) error(mpl, "argument expression has invalid type"); /* add the entry to the end of the list */ arg->next = NULL; if (last_arg == NULL) tab->arg = arg; else last_arg->next = arg; last_arg = arg; /* argument expression has been parsed */ if (mpl->token == T_COMMA) get_token(mpl /* , */); else if (mpl->token == T_COLON || mpl->token == T_SEMICOLON) break; } xassert(tab->arg != NULL); /* argument list must end with colon */ if (mpl->token == T_COLON) get_token(mpl /* : */); else error(mpl, "colon missing where expected"); /* parse specific part of the table statement */ switch (tab->type) { case A_INPUT: goto input_table; case A_OUTPUT: goto output_table; default: xassert(tab != tab); } input_table: /* parse optional set name */ if (mpl->token == T_NAME) { node = avl_find_node(mpl->tree, mpl->image); if (node == NULL) error(mpl, "%s not defined", mpl->image); if (avl_get_node_type(node) != A_SET) error(mpl, "%s not a set", mpl->image); tab->u.in.set = (SET *)avl_get_node_link(node); if (tab->u.in.set->assign != NULL) error(mpl, "%s needs no data", mpl->image); if (tab->u.in.set->dim != 0) error(mpl, "%s must be a simple set", mpl->image); get_token(mpl /* */); if (mpl->token == T_INPUT) get_token(mpl /* <- */); else error(mpl, "delimiter <- missing where expected"); } else if (is_reserved(mpl)) error(mpl, "invalid use of reserved keyword %s", mpl->image); else tab->u.in.set = NULL; /* parse field list */ tab->u.in.fld = last_fld = NULL; nflds = 0; if (mpl->token == T_LBRACKET) get_token(mpl /* [ */); else error(mpl, "field list missing where expected"); for (;;) { /* create field list entry */ fld = alloc(TABFLD); /* parse field name */ if (mpl->token == T_NAME) ; else if (is_reserved(mpl)) error(mpl, "invalid use of reserved keyword %s", mpl->image); else error(mpl, "field name missing where expected"); fld->name = dmp_get_atomv(mpl->pool, strlen(mpl->image)+1); strcpy(fld->name, mpl->image); get_token(mpl /* */); /* add the entry to the end of the list */ fld->next = NULL; if (last_fld == NULL) tab->u.in.fld = fld; else last_fld->next = fld; last_fld = fld; nflds++; /* field name has been parsed */ if (mpl->token == T_COMMA) get_token(mpl /* , */); else if (mpl->token == T_RBRACKET) break; else error(mpl, "syntax error in field list"); } /* check that the set dimen is equal to the number of fields */ if (tab->u.in.set != NULL && tab->u.in.set->dimen != nflds) error(mpl, "there must be %d field%s rather than %d", tab->u.in.set->dimen, tab->u.in.set->dimen == 1 ? "" : "s", nflds); get_token(mpl /* ] */); /* parse optional input list */ tab->u.in.list = last_in = NULL; while (mpl->token == T_COMMA) { get_token(mpl /* , */); /* create input list entry */ in = alloc(TABIN); /* parse parameter name */ if (mpl->token == T_NAME) ; else if (is_reserved(mpl)) error(mpl, "invalid use of reserved keyword %s", mpl->image); else error(mpl, "parameter name missing where expected"); node = avl_find_node(mpl->tree, mpl->image); if (node == NULL) error(mpl, "%s not defined", mpl->image); if (avl_get_node_type(node) != A_PARAMETER) error(mpl, "%s not a parameter", mpl->image); in->par = (PARAMETER *)avl_get_node_link(node); if (in->par->dim != nflds) error(mpl, "%s must have %d subscript%s rather than %d", mpl->image, nflds, nflds == 1 ? "" : "s", in->par->dim); if (in->par->assign != NULL) error(mpl, "%s needs no data", mpl->image); get_token(mpl /* */); /* parse optional field name */ if (mpl->token == T_TILDE) { get_token(mpl /* ~ */); /* parse field name */ if (mpl->token == T_NAME) ; else if (is_reserved(mpl)) error(mpl, "invalid use of reserved keyword %s", mpl->image); else error(mpl, "field name missing where expected"); xassert(strlen(mpl->image) < sizeof(name)); strcpy(name, mpl->image); get_token(mpl /* */); } else { /* field name is the same as the parameter name */ xassert(strlen(in->par->name) < sizeof(name)); strcpy(name, in->par->name); } /* assign field name */ in->name = dmp_get_atomv(mpl->pool, strlen(name)+1); strcpy(in->name, name); /* add the entry to the end of the list */ in->next = NULL; if (last_in == NULL) tab->u.in.list = in; else last_in->next = in; last_in = in; } goto end_of_table; output_table: /* parse output list */ tab->u.out.list = last_out = NULL; for (;;) { /* create output list entry */ out = alloc(TABOUT); /* parse expression */ if (mpl->token == T_COMMA || mpl->token == T_SEMICOLON) error(mpl, "expression missing where expected"); if (mpl->token == T_NAME) { xassert(strlen(mpl->image) < sizeof(name)); strcpy(name, mpl->image); } else name[0] = '\0'; out->code = expression_5(mpl); /* parse optional field name */ if (mpl->token == T_TILDE) { get_token(mpl /* ~ */); /* parse field name */ if (mpl->token == T_NAME) ; else if (is_reserved(mpl)) error(mpl, "invalid use of reserved keyword %s", mpl->image); else error(mpl, "field name missing where expected"); xassert(strlen(mpl->image) < sizeof(name)); strcpy(name, mpl->image); get_token(mpl /* */); } /* assign field name */ if (name[0] == '\0') error(mpl, "field name required"); out->name = dmp_get_atomv(mpl->pool, strlen(name)+1); strcpy(out->name, name); /* add the entry to the end of the list */ out->next = NULL; if (last_out == NULL) tab->u.out.list = out; else last_out->next = out; last_out = out; /* output item has been parsed */ if (mpl->token == T_COMMA) get_token(mpl /* , */); else if (mpl->token == T_SEMICOLON) break; else error(mpl, "syntax error in output list"); } /* close the domain scope */ close_scope(mpl,tab->u.out.domain); end_of_table: /* the table statement must end with semicolon */ if (mpl->token != T_SEMICOLON) error(mpl, "syntax error in table statement"); get_token(mpl /* ; */); return tab; } #endif /*---------------------------------------------------------------------- -- solve_statement - parse solve statement. -- -- This routine parses solve statement using the syntax: -- -- ::= solve ; -- -- The solve statement can be used at most once. */ void *solve_statement(MPL *mpl) { xassert(is_keyword(mpl, "solve")); if (mpl->flag_s) error(mpl, "at most one solve statement allowed"); mpl->flag_s = 1; get_token(mpl /* solve */); /* semicolon must follow solve statement */ if (mpl->token != T_SEMICOLON) error(mpl, "syntax error in solve statement"); get_token(mpl /* ; */); return NULL; } /*---------------------------------------------------------------------- -- check_statement - parse check statement. -- -- This routine parses check statement using the syntax: -- -- ::= check : ; -- ::= -- ::= -- -- If is omitted, colon following it may also be omitted. */ CHECK *check_statement(MPL *mpl) { CHECK *chk; xassert(is_keyword(mpl, "check")); /* create check descriptor */ chk = alloc(CHECK); chk->domain = NULL; chk->code = NULL; get_token(mpl /* check */); /* parse optional indexing expression */ if (mpl->token == T_LBRACE) { chk->domain = indexing_expression(mpl); #if 0 if (mpl->token != T_COLON) error(mpl, "colon missing where expected"); #endif } /* skip optional colon */ if (mpl->token == T_COLON) get_token(mpl /* : */); /* parse logical expression */ chk->code = expression_13(mpl); if (chk->code->type != A_LOGICAL) error(mpl, "expression has invalid type"); xassert(chk->code->dim == 0); /* close the domain scope */ if (chk->domain != NULL) close_scope(mpl, chk->domain); /* the check statement has been completely parsed */ if (mpl->token != T_SEMICOLON) error(mpl, "syntax error in check statement"); get_token(mpl /* ; */); return chk; } #if 1 /* 15/V-2010 */ /*---------------------------------------------------------------------- -- display_statement - parse display statement. -- -- This routine parses display statement using the syntax: -- -- ::= display : ; -- ::= display ; -- ::= -- ::= -- ::= -- ::= , -- ::= -- ::= -- ::= [ ] -- ::= -- ::= [ ] -- ::= -- ::= [ ] -- ::= -- ::= [ ] -- ::= */ DISPLAY *display_statement(MPL *mpl) { DISPLAY *dpy; DISPLAY1 *entry, *last_entry; xassert(is_keyword(mpl, "display")); /* create display descriptor */ dpy = alloc(DISPLAY); dpy->domain = NULL; dpy->list = last_entry = NULL; get_token(mpl /* display */); /* parse optional indexing expression */ if (mpl->token == T_LBRACE) dpy->domain = indexing_expression(mpl); /* skip optional colon */ if (mpl->token == T_COLON) get_token(mpl /* : */); /* parse display list */ for (;;) { /* create new display entry */ entry = alloc(DISPLAY1); entry->type = 0; entry->next = NULL; /* and append it to the display list */ if (dpy->list == NULL) dpy->list = entry; else last_entry->next = entry; last_entry = entry; /* parse display entry */ if (mpl->token == T_NAME) { AVLNODE *node; int next_token; get_token(mpl /* */); next_token = mpl->token; unget_token(mpl); if (!(next_token == T_COMMA || next_token == T_SEMICOLON)) { /* symbolic name begins expression */ goto expr; } /* display entry is dummy index or model object */ node = avl_find_node(mpl->tree, mpl->image); if (node == NULL) error(mpl, "%s not defined", mpl->image); entry->type = avl_get_node_type(node); switch (avl_get_node_type(node)) { case A_INDEX: entry->u.slot = (DOMAIN_SLOT *)avl_get_node_link(node); break; case A_SET: entry->u.set = (SET *)avl_get_node_link(node); break; case A_PARAMETER: entry->u.par = (PARAMETER *)avl_get_node_link(node); break; case A_VARIABLE: entry->u.var = (VARIABLE *)avl_get_node_link(node); if (!mpl->flag_s) error(mpl, "invalid reference to variable %s above" " solve statement", entry->u.var->name); break; case A_CONSTRAINT: entry->u.con = (CONSTRAINT *)avl_get_node_link(node); if (!mpl->flag_s) error(mpl, "invalid reference to %s %s above solve" " statement", entry->u.con->type == A_CONSTRAINT ? "constraint" : "objective", entry->u.con->name); break; default: xassert(node != node); } get_token(mpl /* */); } else expr: { /* display entry is expression */ entry->type = A_EXPRESSION; entry->u.code = expression_13(mpl); } /* check a token that follows the entry parsed */ if (mpl->token == T_COMMA) get_token(mpl /* , */); else break; } /* close the domain scope */ if (dpy->domain != NULL) close_scope(mpl, dpy->domain); /* the display statement has been completely parsed */ if (mpl->token != T_SEMICOLON) error(mpl, "syntax error in display statement"); get_token(mpl /* ; */); return dpy; } #endif /*---------------------------------------------------------------------- -- printf_statement - parse printf statement. -- -- This routine parses print statement using the syntax: -- -- ::= ; -- ::= > ; -- ::= >> ; -- ::= printf : -- ::= printf -- ::= -- ::= -- ::= -- ::= -- ::= , -- ::= -- ::= */ PRINTF *printf_statement(MPL *mpl) { PRINTF *prt; PRINTF1 *entry, *last_entry; xassert(is_keyword(mpl, "printf")); /* create printf descriptor */ prt = alloc(PRINTF); prt->domain = NULL; prt->fmt = NULL; prt->list = last_entry = NULL; get_token(mpl /* printf */); /* parse optional indexing expression */ if (mpl->token == T_LBRACE) { prt->domain = indexing_expression(mpl); #if 0 if (mpl->token != T_COLON) error(mpl, "colon missing where expected"); #endif } /* skip optional colon */ if (mpl->token == T_COLON) get_token(mpl /* : */); /* parse expression for format string */ prt->fmt = expression_5(mpl); /* convert it to symbolic type, if necessary */ if (prt->fmt->type == A_NUMERIC) prt->fmt = make_unary(mpl, O_CVTSYM, prt->fmt, A_SYMBOLIC, 0); /* check that now the expression is of symbolic type */ if (prt->fmt->type != A_SYMBOLIC) error(mpl, "format expression has invalid type"); /* parse printf list */ while (mpl->token == T_COMMA) { get_token(mpl /* , */); /* create new printf entry */ entry = alloc(PRINTF1); entry->code = NULL; entry->next = NULL; /* and append it to the printf list */ if (prt->list == NULL) prt->list = entry; else last_entry->next = entry; last_entry = entry; /* parse printf entry */ entry->code = expression_9(mpl); if (!(entry->code->type == A_NUMERIC || entry->code->type == A_SYMBOLIC || entry->code->type == A_LOGICAL)) error(mpl, "only numeric, symbolic, or logical expression a" "llowed"); } /* close the domain scope */ if (prt->domain != NULL) close_scope(mpl, prt->domain); #if 1 /* 14/VII-2006 */ /* parse optional redirection */ prt->fname = NULL, prt->app = 0; if (mpl->token == T_GT || mpl->token == T_APPEND) { prt->app = (mpl->token == T_APPEND); get_token(mpl /* > or >> */); /* parse expression for file name string */ prt->fname = expression_5(mpl); /* convert it to symbolic type, if necessary */ if (prt->fname->type == A_NUMERIC) prt->fname = make_unary(mpl, O_CVTSYM, prt->fname, A_SYMBOLIC, 0); /* check that now the expression is of symbolic type */ if (prt->fname->type != A_SYMBOLIC) error(mpl, "file name expression has invalid type"); } #endif /* the printf statement has been completely parsed */ if (mpl->token != T_SEMICOLON) error(mpl, "syntax error in printf statement"); get_token(mpl /* ; */); return prt; } /*---------------------------------------------------------------------- -- for_statement - parse for statement. -- -- This routine parses for statement using the syntax: -- -- ::= for -- ::= for { } -- ::= -- ::= -- ::= -- ::= -- ::= -- ::= -- ::= */ FOR *for_statement(MPL *mpl) { FOR *fur; STATEMENT *stmt, *last_stmt; xassert(is_keyword(mpl, "for")); /* create for descriptor */ fur = alloc(FOR); fur->domain = NULL; fur->list = last_stmt = NULL; get_token(mpl /* for */); /* parse indexing expression */ if (mpl->token != T_LBRACE) error(mpl, "indexing expression missing where expected"); fur->domain = indexing_expression(mpl); /* skip optional colon */ if (mpl->token == T_COLON) get_token(mpl /* : */); /* parse for statement body */ if (mpl->token != T_LBRACE) { /* parse simple statement */ fur->list = simple_statement(mpl, 1); } else { /* parse compound statement */ get_token(mpl /* { */); while (mpl->token != T_RBRACE) { /* parse statement */ stmt = simple_statement(mpl, 1); /* and append it to the end of the statement list */ if (last_stmt == NULL) fur->list = stmt; else last_stmt->next = stmt; last_stmt = stmt; } get_token(mpl /* } */); } /* close the domain scope */ xassert(fur->domain != NULL); close_scope(mpl, fur->domain); /* the for statement has been completely parsed */ return fur; } /*---------------------------------------------------------------------- -- end_statement - parse end statement. -- -- This routine parses end statement using the syntax: -- -- ::= end ; */ void end_statement(MPL *mpl) { if (!mpl->flag_d && is_keyword(mpl, "end") || mpl->flag_d && is_literal(mpl, "end")) { get_token(mpl /* end */); if (mpl->token == T_SEMICOLON) get_token(mpl /* ; */); else warning(mpl, "no semicolon following end statement; missing" " semicolon inserted"); } else warning(mpl, "unexpected end of file; missing end statement in" "serted"); if (mpl->token != T_EOF) warning(mpl, "some text detected beyond end statement; text ig" "nored"); return; } /*---------------------------------------------------------------------- -- simple_statement - parse simple statement. -- -- This routine parses simple statement using the syntax: -- -- ::= -- ::= -- ::= -- ::= -- ::= -- ::= -- ::= -- ::= -- ::= -- ::= -- -- If the flag spec is set, some statements cannot be used. */ STATEMENT *simple_statement(MPL *mpl, int spec) { STATEMENT *stmt; stmt = alloc(STATEMENT); stmt->line = mpl->line; stmt->next = NULL; if (is_keyword(mpl, "set")) { if (spec) error(mpl, "set statement not allowed here"); stmt->type = A_SET; stmt->u.set = set_statement(mpl); } else if (is_keyword(mpl, "param")) { if (spec) error(mpl, "parameter statement not allowed here"); stmt->type = A_PARAMETER; stmt->u.par = parameter_statement(mpl); } else if (is_keyword(mpl, "var")) { if (spec) error(mpl, "variable statement not allowed here"); stmt->type = A_VARIABLE; stmt->u.var = variable_statement(mpl); } else if (is_keyword(mpl, "subject") || is_keyword(mpl, "subj") || mpl->token == T_SPTP) { if (spec) error(mpl, "constraint statement not allowed here"); stmt->type = A_CONSTRAINT; stmt->u.con = constraint_statement(mpl); } else if (is_keyword(mpl, "minimize") || is_keyword(mpl, "maximize")) { if (spec) error(mpl, "objective statement not allowed here"); stmt->type = A_CONSTRAINT; stmt->u.con = objective_statement(mpl); } #if 1 /* 11/II-2008 */ else if (is_keyword(mpl, "table")) { if (spec) error(mpl, "table statement not allowed here"); stmt->type = A_TABLE; stmt->u.tab = table_statement(mpl); } #endif else if (is_keyword(mpl, "solve")) { if (spec) error(mpl, "solve statement not allowed here"); stmt->type = A_SOLVE; stmt->u.slv = solve_statement(mpl); } else if (is_keyword(mpl, "check")) { stmt->type = A_CHECK; stmt->u.chk = check_statement(mpl); } else if (is_keyword(mpl, "display")) { stmt->type = A_DISPLAY; stmt->u.dpy = display_statement(mpl); } else if (is_keyword(mpl, "printf")) { stmt->type = A_PRINTF; stmt->u.prt = printf_statement(mpl); } else if (is_keyword(mpl, "for")) { stmt->type = A_FOR; stmt->u.fur = for_statement(mpl); } else if (mpl->token == T_NAME) { if (spec) error(mpl, "constraint statement not allowed here"); stmt->type = A_CONSTRAINT; stmt->u.con = constraint_statement(mpl); } else if (is_reserved(mpl)) error(mpl, "invalid use of reserved keyword %s", mpl->image); else error(mpl, "syntax error in model section"); return stmt; } /*---------------------------------------------------------------------- -- model_section - parse model section. -- -- This routine parses model section using the syntax: -- -- ::= -- ::= -- -- Parsing model section is terminated by either the keyword 'data', or -- the keyword 'end', or the end of file. */ void model_section(MPL *mpl) { STATEMENT *stmt, *last_stmt; xassert(mpl->model == NULL); last_stmt = NULL; while (!(mpl->token == T_EOF || is_keyword(mpl, "data") || is_keyword(mpl, "end"))) { /* parse statement */ stmt = simple_statement(mpl, 0); /* and append it to the end of the statement list */ if (last_stmt == NULL) mpl->model = stmt; else last_stmt->next = stmt; last_stmt = stmt; } return; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glphbm.h0000644000076500000240000001102013524616144025013 0ustar tamasstaff00000000000000/* glphbm.h (Harwell-Boeing sparse matrix format) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPHBM_H #define GLPHBM_H typedef struct HBM HBM; struct HBM { /* sparse matrix in Harwell-Boeing format; for details see the report: I.S.Duff, R.G.Grimes, J.G.Lewis. User's Guide for the Harwell-Boeing Sparse Matrix Collection (Release I), 1992 */ char title[72+1]; /* matrix title (informative) */ char key[8+1]; /* matrix key (informative) */ char mxtype[3+1]; /* matrix type: R.. real matrix C.. complex matrix P.. pattern only (no numerical values supplied) .S. symmetric (lower triangle + main diagonal) .U. unsymmetric .H. hermitian (lower triangle + main diagonal) .Z. skew symmetric (lower triangle only) .R. rectangular ..A assembled ..E elemental (unassembled) */ char rhstyp[3+1]; /* optional types: F.. right-hand sides in dense format M.. right-hand sides in same format as matrix .G. starting vector(s) (guess) is supplied ..X exact solution vector(s) is supplied */ char ptrfmt[16+1]; /* format for pointers */ char indfmt[16+1]; /* format for row (or variable) indices */ char valfmt[20+1]; /* format for numerical values of coefficient matrix */ char rhsfmt[20+1]; /* format for numerical values of right-hand sides */ int totcrd; /* total number of cards excluding header */ int ptrcrd; /* number of cards for ponters */ int indcrd; /* number of cards for row (or variable) indices */ int valcrd; /* number of cards for numerical values */ int rhscrd; /* number of lines for right-hand sides; including starting guesses and solution vectors if present; zero indicates no right-hand side data is present */ int nrow; /* number of rows (or variables) */ int ncol; /* number of columns (or elements) */ int nnzero; /* number of row (or variable) indices; equal to number of entries for assembled matrix */ int neltvl; /* number of elemental matrix entries; zero in case of assembled matrix */ int nrhs; /* number of right-hand sides */ int nrhsix; /* number of row indices; ignored in case of unassembled matrix */ int nrhsvl; /* total number of entries in all right-hand sides */ int nguess; /* total number of entries in all starting guesses */ int nexact; /* total number of entries in all solution vectors */ int *colptr; /* alias: eltptr */ /* column pointers (in case of assembled matrix); elemental matrix pointers (in case of unassembled matrix) */ int *rowind; /* alias: varind */ /* row indices (in case of assembled matrix); variable indices (in case of unassembled matrix) */ int *rhsptr; /* right-hand side pointers */ int *rhsind; /* right-hand side indices */ double *values; /* matrix values */ double *rhsval; /* right-hand side values */ double *sguess; /* starting guess values */ double *xexact; /* solution vector values */ }; #define hbm_read_mat _glp_hbm_read_mat HBM *hbm_read_mat(const char *fname); /* read sparse matrix in Harwell-Boeing format */ #define hbm_free_mat _glp_hbm_free_mat void hbm_free_mat(HBM *hbm); /* free sparse matrix in Harwell-Boeing format */ #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpenv02.c0000644000076500000240000000410513524616144025200 0ustar tamasstaff00000000000000/* glpenv02.c (thread local storage) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "glpenv.h" static void *tls = NULL; /* in a re-entrant version of the package this variable must be placed in the Thread Local Storage (TLS) */ /*********************************************************************** * NAME * * tls_set_ptr - store global pointer in TLS * * SYNOPSIS * * #include "glpenv.h" * void tls_set_ptr(void *ptr); * * DESCRIPTION * * The routine tls_set_ptr stores a pointer specified by the parameter * ptr in the Thread Local Storage (TLS). */ void tls_set_ptr(void *ptr) { tls = ptr; return; } /*********************************************************************** * NAME * * tls_get_ptr - retrieve global pointer from TLS * * SYNOPSIS * * #include "glpenv.h" * void *tls_get_ptr(void); * * RETURNS * * The routine tls_get_ptr returns a pointer previously stored by the * routine tls_set_ptr. If the latter has not been called yet, NULL is * returned. */ void *tls_get_ptr(void) { void *ptr; ptr = tls; return ptr; } /* eof */ python-igraph-0.8.0/vendor/source/igraph/optional/glpk/glpscf.h0000644000076500000240000001074413524616144025034 0ustar tamasstaff00000000000000/* glpscf.h (Schur complement factorization) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, * Moscow Aviation Institute, Moscow, Russia. All rights reserved. * E-mail: . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #ifndef GLPSCF_H #define GLPSCF_H /*********************************************************************** * The structure SCF defines the following factorization of a square * nxn matrix C (which is the Schur complement): * * F * C = U * P, * * where F is a square transforming matrix, U is an upper triangular * matrix, P is a permutation matrix. * * It is assumed that matrix C is small and dense, so matrices F and U * are stored in the dense format by rows as follows: * * 1 n n_max 1 n n_max * 1 * * * * * * x x x x 1 * * * * * * x x x x * * * * * * * x x x x . * * * * * x x x x * * * * * * * x x x x . . * * * * x x x x * * * * * * * x x x x . . . * * * x x x x * * * * * * * x x x x . . . . * * x x x x * n * * * * * * x x x x n . . . . . * x x x x * x x x x x x x x x x . . . . . . x x x x * x x x x x x x x x x . . . . . . . x x x * x x x x x x x x x x . . . . . . . . x x * n_max x x x x x x x x x x n_max . . . . . . . . . x * * matrix F matrix U * * where '*' are matrix elements, 'x' are reserved locations. * * Permutation matrix P is stored in row-like format. * * Matrix C normally is not stored. * * REFERENCES * * 1. M.A.Saunders, "LUSOL: A basis package for constrained optimiza- * tion," SCCM, Stanford University, 2006. * * 2. M.A.Saunders, "Notes 5: Basis Updates," CME 318, Stanford Univer- * sity, Spring 2006. * * 3. M.A.Saunders, "Notes 6: LUSOL---a Basis Factorization Package," * ibid. */ typedef struct SCF SCF; struct SCF { /* Schur complement factorization */ int n_max; /* maximal order of matrices C, F, U, P; n_max >= 1 */ int n; /* current order of matrices C, F, U, P; n >= 0 */ double *f; /* double f[1+n_max*n_max]; */ /* matrix F stored by rows */ double *u; /* double u[1+n_max*(n_max+1)/2]; */ /* upper triangle of matrix U stored by rows */ int *p; /* int p[1+n_max]; */ /* matrix P; p[i] = j means that P[i,j] = 1 */ int t_opt; /* type of transformation used to restore triangular structure of matrix U: */ #define SCF_TBG 1 /* Bartels-Golub elimination */ #define SCF_TGR 2 /* Givens plane rotation */ int rank; /* estimated rank of matrices C and U */ double *c; /* double c[1+n_max*n_max]; */ /* matrix C stored in the same format as matrix F and used only for debugging; normally this array is not allocated */ double *w; /* double w[1+n_max]; */ /* working array */ }; /* return codes: */ #define SCF_ESING 1 /* singular matrix */ #define SCF_ELIMIT 2 /* update limit reached */ #define scf_create_it _glp_scf_create_it SCF *scf_create_it(int n_max); /* create Schur complement factorization */ #define scf_update_exp _glp_scf_update_exp int scf_update_exp(SCF *scf, const double x[], const double y[], double z); /* update factorization on expanding C */ #define scf_solve_it _glp_scf_solve_it void scf_solve_it(SCF *scf, int tr, double x[]); /* solve either system C * x = b or C' * x = b */ #define scf_reset_it _glp_scf_reset_it void scf_reset_it(SCF *scf); /* reset factorization for empty matrix C */ #define scf_delete_it _glp_scf_delete_it void scf_delete_it(SCF *scf); /* delete Schur complement factorization */ #endif /* eof */ python-igraph-0.8.0/vendor/source/igraph/.astylerc0000644000076500000240000000140313614300625022434 0ustar tamasstaff00000000000000# General Options: # - Only display errors # - Redirect stderr to stdout # - Enforce linux lineendings # - Preserve file modification date # - Do not create file backups, everything should be VCSed anyway --quiet --errors-to-stdout --lineend=linux --preserve-date --suffix=none # Style --style=java # Use 4 spaces --indent=spaces=4 --convert-tabs # Paddings around operators, parentheses, and a header --pad-oper --pad-header # Continuation blocks should have no extra indentation --min-conditional-indent=0 # Indent preprocessor blocks and defines --indent-preproc-block --indent-preproc-define # Add braces around single-line branches --add-braces # Keep complex statement sequences on the same line; they are that way for # a reason --keep-one-line-statements python-igraph-0.8.0/vendor/source/igraph/appveyor.yml0000644000076500000240000000740413614300625023204 0ustar tamasstaff00000000000000# This file is based on one which was automatically generated by conda-smithy # and the one in matplotlib. # It uses conda environment to get the build dependencies for a full windows # build, both the "normal" one and the msvc based one. environment: PATH: C:\msys64\usr\bin;C:\msys64\mingw64\bin;C:\Windows\System32;C:\Windows;%PATH% MSYSTEM: MINGW64 TARGET_ARCH: "x64" matrix: - PYTHON_VERSION: "2.7" CONDA_INSTALL_LOCN: "C:\\Miniconda-x64" - PYTHON_VERSION: "3.5" CONDA_INSTALL_LOCN: "C:\\Miniconda35-x64" - PYTHON_VERSION: "3.6" CONDA_INSTALL_LOCN: "C:\\Miniconda36-x64" - PYTHON_VERSION: "3.7" CONDA_INSTALL_LOCN: "C:\\Miniconda37-x64" - PYTHON_VERSION: "NONE" CONDA_INSTALL_LOCN: "C:\\Miniconda37-x64" # We always use a 64-bit machine, but can build x86 distributions # with the PYTHON_ARCH variable (which is used by CMD_IN_ENV). platform: - x64 init: - cmd: "ECHO %PYTHON_VERSION% %CONDA_INSTALL_LOCN%" # all our builds have to happen in install... build: false install: # setup conda environment for building - cmd: set "PATH=%CONDA_INSTALL_LOCN%;%CONDA_INSTALL_LOCN%\scripts;%PATH%" - cmd: set PYTHONUNBUFFERED=1 # update mysy2 - C:\msys64\usr\bin\bash -lc "pacman --needed --noconfirm -Sy pacman-mirrors" - C:\msys64\usr\bin\bash -lc "pacman --noconfirm -Sy" - C:\msys64\usr\bin\bash -lc "pacman --noconfirm -S autoconf automake bison flex" - C:\msys64\usr\bin\bash -lc "pacman --noconfirm -S libxml2-devel zip" # also install a msvc build environment -> use libxml2 from conda-forge # updating conda always updates python, even with "no-update-deps" and # updating python takes ages on appveyor... So just keep the shorter PATH # workaround for the activate failure and don't update conda itself... #- cmd: conda update conda --no-update-dependencies - cmd: conda config --add channels conda-forge - cmd: conda config --set show_channel_urls yes - cmd: conda config --set always_yes true - cmd: if [%PYTHON_VERSION%] NEQ [NONE] conda install --quiet libxml2 python=%PYTHON_VERSION% - cmd: conda info -a # Now start with the build: first the msys2 based one - cmd: bash bootstrap.sh - cmd: bash configure # for testing purpose removed, takes ages... - cmd: if %PYTHON_VERSION%==NONE make # now make the msvc builds - cmd: if [%PYTHON_VERSION%] NEQ [NONE] make msvc # now build the with the right compiler for each python version - cmd: if [%PYTHON_VERSION%] NEQ [NONE] cd igraph-*-msvc - cmd: if %PYTHON_VERSION%==2.7 call "C:\Program Files (x86)\Microsoft Visual Studio 9.0\VC\bin\vcvars64.bat" - cmd: if %PYTHON_VERSION%==2.7 vcbuild.exe /upgrade - cmd: if %PYTHON_VERSION%==2.7 vcbuild.exe igraph.vcproj "Release|%TARGET_ARCH%" - cmd: if %PYTHON_VERSION%==3.4 call "%VS100COMNTOOLS%\vsvars32.bat" - cmd: if %PYTHON_VERSION%==3.4 VCUpgrade.exe /overwrite igraph.vcproj - cmd: if %PYTHON_VERSION%==3.4 msbuild.exe igraph.vcxproj /logger:"C:\Program Files\AppVeyor\BuildAgent\Appveyor.MSBuildLogger.dll" - cmd: if %PYTHON_VERSION%==3.5 call "%VS140COMNTOOLS%\vsvars32.bat" - cmd: if %PYTHON_VERSION%==3.5 devenv /upgrade igraph.vcproj - cmd: if %PYTHON_VERSION%==3.5 msbuild.exe igraph.vcxproj /logger:"C:\Program Files\AppVeyor\BuildAgent\Appveyor.MSBuildLogger.dll" test_script: - cmd: cd "%APPVEYOR_BUILD_FOLDER%" - cmd: set "PATH=%APPVEYOR_BUILD_FOLDER%\src\.libs;%PATH%" - cmd: path - cmd: if [%PYTHON_VERSION%]==[NONE] make check on_failure: - cmd: echo zipping everything after a failure... - cmd: cd "%APPVEYOR_BUILD_FOLDER%" - cmd: 7z a failed_state.zip . |grep -v "Compressing" - cmd: appveyor PushArtifact failed_state.zip python-igraph-0.8.0/vendor/source/igraph/COPYING0000644000076500000240000004313313524616144021654 0ustar tamasstaff00000000000000 GNU GENERAL PUBLIC LICENSE Version 2, June 1991 Copyright (C) 1989, 1991 Free Software Foundation, Inc. 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed. Preamble The licenses for most software are designed to take away your freedom to share and change it. By contrast, the GNU General Public License is intended to guarantee your freedom to share and change free software--to make sure the software is free for all its users. This General Public License applies to most of the Free Software Foundation's software and to any other program whose authors commit to using it. (Some other Free Software Foundation software is covered by the GNU Library General Public License instead.) You can apply it to your programs, too. When we speak of free software, we are referring to freedom, not price. Our General Public Licenses are designed to make sure that you have the freedom to distribute copies of free software (and charge for this service if you wish), that you receive source code or can get it if you want it, that you can change the software or use pieces of it in new free programs; and that you know you can do these things. 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The "Program", below, refers to any such program or work, and a "work based on the Program" means either the Program or any derivative work under copyright law: that is to say, a work containing the Program or a portion of it, either verbatim or with modifications and/or translated into another language. (Hereinafter, translation is included without limitation in the term "modification".) Each licensee is addressed as "you". Activities other than copying, distribution and modification are not covered by this License; they are outside its scope. The act of running the Program is not restricted, and the output from the Program is covered only if its contents constitute a work based on the Program (independent of having been made by running the Program). Whether that is true depends on what the Program does. 1. 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It is safest to attach them to the start of each source file to most effectively convey the exclusion of warranty; and each file should have at least the "copyright" line and a pointer to where the full notice is found. Copyright (C) This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA Also add information on how to contact you by electronic and paper mail. If the program is interactive, make it output a short notice like this when it starts in an interactive mode: Gnomovision version 69, Copyright (C) year name of author Gnomovision comes with ABSOLUTELY NO WARRANTY; for details type `show w'. This is free software, and you are welcome to redistribute it under certain conditions; type `show c' for details. The hypothetical commands `show w' and `show c' should show the appropriate parts of the General Public License. Of course, the commands you use may be called something other than `show w' and `show c'; they could even be mouse-clicks or menu items--whatever suits your program. You should also get your employer (if you work as a programmer) or your school, if any, to sign a "copyright disclaimer" for the program, if necessary. Here is a sample; alter the names: Yoyodyne, Inc., hereby disclaims all copyright interest in the program `Gnomovision' (which makes passes at compilers) written by James Hacker. , 1 April 1989 Ty Coon, President of Vice This General Public License does not permit incorporating your program into proprietary programs. If your program is a subroutine library, you may consider it more useful to permit linking proprietary applications with the library. If this is what you want to do, use the GNU Library General Public License instead of this License. python-igraph-0.8.0/vendor/source/igraph/bootstrap.sh0000755000076500000240000000127313614300625023166 0ustar tamasstaff00000000000000#! /bin/sh cd "`dirname $0`" ## Find out our version number, need git for this printf "Finding out version number/string... " tools/getversion.sh > IGRAPH_VERSION cat IGRAPH_VERSION for i in glibtoolize libtoolize; do LIBTOOLIZE=`which $i` && break done if [ -z "$LIBTOOLIZE" ]; then echo libtoolize or glibtoolize not found or not in the path! exit 1 fi mkdir -p m4 set -x aclocal $LIBTOOLIZE --force --copy autoheader automake --add-missing --copy autoconf # Try to patch ltmain.sh to allow -fsanitize=* linker flags to be passed # through to the linker. Don't do anything if it fails; maybe libtool has # been upgraded already. patch -N -p0 -r- /dev/null || true python-igraph-0.8.0/vendor/source/igraph/NEWS0000644000076500000240000000032113614300625021302 0ustar tamasstaff00000000000000News about each release of igraph from version 0.8 onwards can be found in CHANGELOG.md. Archived news items before version 0.7 are to be found in ONEWS -- these are most likely of historical interest only. python-igraph-0.8.0/vendor/source/igraph/.gitignore0000644000076500000240000003777313614300625022620 0ustar tamasstaff00000000000000*~ .*.swp *.pyc *.so *.lo *.la .dirstamp .libs .deps /tags /IGRAPH_VERSION /VERSION /aclocal.m4 /autom4te.cache /build /compile /config.guess /config.h /config.h.in /config.log /config.status /config.sub /configure /depcomp /igraph.pc /igraph_Info.plist /install-sh /libtool /ltmain.sh /m4 /missing /stamp-h1 /ylwrap /igraph.msvc /fatbuild /valgrind-testbed /Makefile /src/Makefile /doc/Makefile /Makefile.in /src/Makefile.in /doc/Makefile.in /debian/Makefile /debian/Makefile.in /doc/Makefile /doc/Makefile.in /doc/book/Makefile /doc/book/Makefile.in /src/Makefile /src/Makefile.in /tests/Makefile /tests/Makefile.in /interfaces/Makefile /interfaces/Makefile.in /interfaces/R/Makefile /interfaces/R/Makefile.in /interfaces/R/object_files 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tamasstaff00000000000000# Contributing to this project Please take a moment to review this document in order to make the contribution process easy and effective for everyone involved. Following these guidelines helps to communicate that you respect the time of the developers managing and developing this open source project. In return, they should reciprocate that respect in addressing your issue or assessing patches and features. ## Using the issue tracker The issue tracker is the preferred channel for [bug reports](#bugs), [features requests](#features) and [submitting pull requests](#pull-requests), but please respect the following restrictions: * Please **do not** use the issue tracker for personal support requests (use our [igraph support forum](https://igraph.discourse.group)). * Please **do not** derail or troll issues. Keep the discussion on topic and respect the opinions of others. Please also take a look at our [tips on writing igraph code](#tips) before getting your hands dirty. ## Bug reports A bug is a _demonstrable problem_ that is caused by the code in the repository. Good bug reports are extremely helpful - thank you! Guidelines for bug reports: 1. **Make sure that the bug is in the C code of igraph and not in one of the higher level interfaces** — if you are using igraph from R, Python or Mathematica, consider submitting your issue in [igraph/rigraph](https://github.com/igraph/rigraph/issues/new), [igraph/python-igraph](https://github.com/igraph/python-igraph/issues/new) or [szhorvat/IGraphM](https://github.com/szhorvat/IGraphM/issues/new) instead. If you are unsure whether your issue is in the C layer, submit a bug report in the repository of the higher level interface — we will transfer the issue here if it indeed affects the C layer. 2. **Use the GitHub issue search** — check if the issue has already been reported. 3. **Check if the issue has been fixed** — try to reproduce it using the latest `master` or development branch in the repository. 4. **Isolate the problem** — create a [short, self-contained, correct example](http://sscce.org/). A good bug report shouldn't leave others needing to chase you up for more information. Please try to be as detailed as possible in your report. What is your environment? What steps will reproduce the issue? What would you expect to be the outcome? All these details will help people to fix any potential bugs. Example: > Short and descriptive example bug report title > > A summary of the issue and the compiler/OS environment in which it occurs. If > suitable, include the steps required to reproduce the bug. > > 1. This is the first step > 2. This is the second step > 3. Further steps, etc. > > `` - a link to the reduced test case > > Any other information you want to share that is relevant to the issue being > reported. This might include the lines of code that you have identified as > causing the bug, and potential solutions (and your opinions on their > merits). ## Feature requests Feature requests are welcome. But take a moment to find out whether your idea fits with the scope and aims of the project. It's up to *you* to make a strong case to convince the project's developers of the merits of this feature. Please provide as much detail and context as possible. ## Pull requests Good pull requests - patches, improvements, new features - are a fantastic help. They should remain focused in scope and avoid containing unrelated commits. **Please ask first** before embarking on any significant pull request (e.g. implementing features, refactoring code, porting to a different language), otherwise you risk spending a lot of time working on something that the project's developers might not want to merge into the project. Please adhere to the coding conventions used throughout a project (indentation, accurate comments, etc.) and any other requirements (such as test coverage). Follow this process if you'd like your work considered for inclusion in the project: 1. [Fork](http://help.github.com/fork-a-repo/) the project, clone your fork, and configure the remotes: ```bash # Clone your fork of the repo into the current directory git clone https://github.com// # Navigate to the newly cloned directory cd # Assign the original repo to a remote called "upstream" git remote add upstream https://github.com// ``` 2. If you cloned a while ago, get the latest changes from upstream: ```bash git checkout git pull upstream ``` 3. Create a new topic branch (off the main project development branch) to contain your feature, change, or fix: ```bash git checkout -b ``` 4. Commit your changes in logical chunks. Please adhere to these [git commit message guidelines](http://tbaggery.com/2008/04/19/a-note-about-git-commit-messages.html) or your code is unlikely be merged into the main project. Use Git's [interactive rebase](https://help.github.com/articles/interactive-rebase) feature to tidy up your commits before making them public. 5. We have a handy [checklist for new igraph functions](https://github.com/igraph/igraph/wiki/Checklist-for-new-(and-old)-functions). If you have added any new functions to igraph, please go through the checklist to ensure that your functions play nicely with the rest of the library. 6. Locally merge (or rebase) the upstream development branch into your topic branch: ```bash git pull [--rebase] upstream ``` 7. Push your topic branch up to your fork: ```bash git push origin ``` 8. [Open a Pull Request](https://help.github.com/articles/using-pull-requests/) with a clear title and description. **IMPORTANT**: By submitting a patch, you agree to allow the project owner to license your work under the same license as that used by the project. ## Writing igraph Code Some tips on writing igraph code. In general, look at how things are done, and try to do them similarly. (Unless you think they are not done well, in which case please tell us.) ### Code Formatting We use UNIX line endings and we prefer four spaces for indentation. Otherwise we are not too picky about code style; the general advice is that you should look at the style of some recently committed bigger change around the parts that you intend to change, and try to mimic that. The code style within igraph is not stricly the same, but we want to keep it reasonably similar. ### C vs. C++ Try to use C, unless you are updating already existing C++ code, or you have other good reason for C++ (but then maybe ask us first). ### Data types Please try to use igraph's data types for vectors, matrices, stacks, etc. If they lack some functionality you need, please tell us. ### Memory Allocation, Error Handling Please use igraph's memory allocation functions. Please also use the `FINALLY` stack: `IGRAPH_FINALLY`, `IGRAPH_FINALLY_CLEAN`, etc. See examples in the C code. ### Random Numbers Please look at how random numbers are generated in any function in `src/games.c`. Do the same. I.e. use `RNG_BEGIN`, `RNG_END`, and igraph's RNG calls. Do not use the libc RNGs or other RNGs. ### Documentation Please document your new functions. The C documentation is included in the C source code. ### Test Cases Unless you change something trivial, please consider adding test cases. This is important! See the `tests`, `examples/simple` and `examples/tests` directories for existing tests that you can use as examples. Whenever possible, make sure that the tests are determistic. If you are using random numbers or a random graph generator in the tests, seed the random number generator with a constant in the main function of the test to make sure that every run generates the same set of random numbers. ### Ask Us! In general, if you are not sure about something, please ask! You can open an issue on GitHub, open a thread in our [igraph support forum](https://igraph.discourse.group), or write to [@ntamas](https://github.com/ntamas), [@vtraag](https://github.com/vtraag), [@szhorvat](https://github.com/szhorvat) or [@gaborcsardi](https://github.com/gaborcsardi). We prefer the igraph support forum, because then others can learn from it too. ## Legal Stuff This is a pain to deal with, but we can't avoid it, unfortunately. So, igraph is licensed under the "General Public License (GPL) version 2, or later". The igraph manual is licensed under the "GNU Free Documentation License". By submitting a patch or PR, you agree to allow the project owner to license your work under the same license as that used by the project. python-igraph-0.8.0/vendor/source/igraph/examples/0000755000076500000240000000000013617375000022427 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/examples/tests/0000755000076500000240000000000013617375001023572 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/examples/tests/rng_reproducibility.out0000644000076500000240000000013613524616144030405 0ustar tamasstaff0000000000000095 51 8 29 70 39 70 77 50 19 50 46 90 19 8 43 85 46 35 91 100 51 77 59 76 89 70 29 77 86 0 10 python-igraph-0.8.0/vendor/source/igraph/examples/tests/simplify_and_colorize.out0000644000076500000240000000100713524616144030710 0ustar tamasstaff00000000000000K0 directed: false vcount: 0 edges: { } ( ) ( ) K1 directed: false vcount: 1 edges: { } ( 0 ) ( ) C4 directed: false vcount: 4 edges: { 1 0 3 0 2 1 3 2 } ( 0 0 0 0 ) ( 1 1 1 1 ) Undirected graph 1 directed: false vcount: 2 edges: { 1 0 } ( 0 1 ) ( 2 ) Undirected graph 2 directed: false vcount: 3 edges: { 1 0 2 0 2 1 } ( 0 0 2 ) ( 1 1 2 ) Directed graph 1 directed: true vcount: 3 edges: { 0 1 1 2 2 0 2 1 } ( 0 0 2 ) ( 1 1 1 1 ) Directed graph 2 directed: true vcount: 4 edges: { 0 1 1 0 } ( 0 2 0 0 ) ( 2 3 ) python-igraph-0.8.0/vendor/source/igraph/examples/tests/cattr_bool_bug2.c0000644000076500000240000000206213612122634027002 0ustar tamasstaff00000000000000 #include #include #define FILENAME "mybool.graphml.xml" int main() { igraph_t graph; igraph_error_handler_t* oldhandler; int result; FILE* ifile = fopen("cattr_bool_bug2.graphml", "r"); if (!ifile) { printf("Cannot open input file"); return 1; } igraph_i_set_attribute_table(&igraph_cattribute_table); oldhandler = igraph_set_error_handler(igraph_error_handler_ignore); if ((result = igraph_read_graph_graphml(&graph, ifile, 0))) { /* maybe it is simply disabled at compile-time */ if (result == IGRAPH_UNIMPLEMENTED) { return 77; } return 1; } igraph_set_error_handler(oldhandler); fclose(ifile); if (!igraph_cattribute_has_attr(&graph, IGRAPH_ATTRIBUTE_GRAPH, "mybool")) { printf("boolean value mybool not found\n"); return 2; } else { igraph_bool_t value = igraph_cattribute_GAB(&graph, "mybool"); printf("found boolean value %d\n", value); } igraph_destroy(&graph); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/tests/maximal_cliques_hist.out0000644000076500000240000000000613612122634030520 0ustar tamasstaff000000000000001 1 2 python-igraph-0.8.0/vendor/source/igraph/examples/tests/cattr_bool_bug2.out0000644000076500000240000000002613524616144027373 0ustar tamasstaff00000000000000found boolean value 1 python-igraph-0.8.0/vendor/source/igraph/examples/tests/test_utilities.inc0000644000076500000240000000322613524616144027345 0ustar tamasstaff00000000000000#ifndef TEST_UTILITIES_INC #define TEST_UTILITIES_INC /* * This file contains functions that are useful when writing tests. * Include it in the test program using #include "test_utilities.inc" */ #include #include /* Print elements of a vector. Use parentheses to make it clear when a vector has size zero. */ void print_vector(const igraph_vector_t *v, FILE *f) { long i; fprintf(f, "("); for (i=0; i < igraph_vector_size(v); i++) { fprintf(f, " %f", VECTOR(*v)[i]); } fprintf(f, " )\n"); } /* Round elements of a vector to integers and print them. */ /* This is meant to be used when the elements of a vector are integer values. */ void print_vector_round(const igraph_vector_t *v, FILE *f) { long i; fprintf(f, "("); for (i=0; i < igraph_vector_size(v); i++) { fprintf(f, " %li", (long int) VECTOR(*v)[i]); } fprintf(f, " )\n"); } /* Print elements of an integer vector */ void print_vector_int(const igraph_vector_int_t *v, FILE *f) { long i; fprintf(f, "("); for (i=0; i < igraph_vector_int_size(v); i++) { fprintf(f, " %d", VECTOR(*v)[i]); } fprintf(f, " )\n"); } /* Print a graph. Use brackets to make it obvious when the edge list is empty. */ void print_graph(const igraph_t *graph, FILE *f) { long ecount = igraph_ecount(graph); long vcount = igraph_vcount(graph); long i; fprintf(f, "directed: %s\n", igraph_is_directed(graph) ? "true" : "false"); fprintf(f, "vcount: %ld\n", vcount); fprintf(f, "edges: {\n"); for (i=0; i < ecount; ++i) fprintf(f, "%d %d\n", IGRAPH_FROM(graph, i), IGRAPH_TO(graph, i)); fprintf(f, "}\n"); } #endif /* TEST_UTILITIES_INC */ python-igraph-0.8.0/vendor/source/igraph/examples/tests/igraph_community_leiden.c0000644000076500000240000001446113612122634030637 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void run_leiden_CPM(const igraph_t *graph, const igraph_vector_t *edge_weights, const igraph_real_t resolution_parameter) { igraph_vector_t membership; igraph_integer_t nb_clusters = igraph_vcount(graph); igraph_real_t quality; /* Initialize with singleton partition. */ igraph_vector_init(&membership, igraph_vcount(graph)); igraph_community_leiden(graph, edge_weights, NULL, resolution_parameter, 0.01, 0, &membership, &nb_clusters, &quality); printf("Leiden found %i clusters using CPM (resolution parameter=%.2f), quality is %.4f.\n", nb_clusters, resolution_parameter, quality); printf("Membership: "); igraph_vector_print(&membership); printf("\n"); igraph_vector_destroy(&membership); } void run_leiden_modularity(igraph_t *graph, igraph_vector_t *edge_weights) { igraph_vector_t membership, degree; igraph_integer_t nb_clusters = igraph_vcount(graph); igraph_real_t quality; igraph_real_t m; igraph_vector_init(°ree, igraph_vcount(graph)); if (edge_weights) { igraph_strength(graph, °ree, igraph_vss_all(), IGRAPH_ALL, 1, edge_weights); m = igraph_vector_sum(edge_weights); } else { igraph_degree(graph, °ree, igraph_vss_all(), IGRAPH_ALL, 1); m = (igraph_real_t)igraph_ecount(graph); } /* Initialize with singleton partition. */ igraph_vector_init(&membership, igraph_vcount(graph)); igraph_community_leiden(graph, edge_weights, °ree, 1.0 / (2 * m), 0.01, 0, &membership, &nb_clusters, &quality); if (isnan(quality)) { printf("Leiden found %i clusters using modularity, quality is nan.\n", nb_clusters); } else { printf("Leiden found %i clusters using modularity, quality is %.4f.\n", nb_clusters, quality); } printf("Membership: "); igraph_vector_print(&membership); printf("\n"); igraph_vector_destroy(&membership); igraph_vector_destroy(°ree); } int main() { igraph_t graph; igraph_vector_t weights; igraph_vector_init(&weights, 0); /* Set default seed to get reproducible results */ igraph_rng_seed(igraph_rng_default(), 0); /* Simple unweighted graph */ igraph_small(&graph, 10, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 0, 4, 1, 2, 1, 3, 1, 4, 2, 3, 2, 4, 3, 4, 5, 6, 5, 7, 5, 8, 5, 9, 6, 7, 6, 8, 6, 9, 7, 8, 7, 9, 8, 9, 0, 5, -1); run_leiden_modularity(&graph, NULL); /* Same simple graph, with uniform edge weights */ igraph_vector_resize(&weights, igraph_ecount(&graph)); igraph_vector_fill(&weights, 2); run_leiden_modularity(&graph, &weights); igraph_destroy(&graph); /* Simple nonuniform weighted graph, with and without weights */ igraph_small(&graph, 6, IGRAPH_UNDIRECTED, 0, 1, 1, 2, 2, 3, 2, 4, 2, 5, 3, 4, 3, 5, 4, 5, -1); igraph_vector_resize(&weights, 8); igraph_vector_fill(&weights, 1); VECTOR(weights)[0] = 10; VECTOR(weights)[1] = 10; run_leiden_modularity(&graph, NULL); run_leiden_modularity(&graph, &weights); igraph_destroy(&graph); /* Zachary Karate club */ igraph_small(&graph, 0, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 0, 7, 0, 8, 0, 10, 0, 11, 0, 12, 0, 13, 0, 17, 0, 19, 0, 21, 0, 31, 1, 2, 1, 3, 1, 7, 1, 13, 1, 17, 1, 19, 1, 21, 1, 30, 2, 3, 2, 7, 2, 8, 2, 9, 2, 13, 2, 27, 2, 28, 2, 32, 3, 7, 3, 12, 3, 13, 4, 6, 4, 10, 5, 6, 5, 10, 5, 16, 6, 16, 8, 30, 8, 32, 8, 33, 9, 33, 13, 33, 14, 32, 14, 33, 15, 32, 15, 33, 18, 32, 18, 33, 19, 33, 20, 32, 20, 33, 22, 32, 22, 33, 23, 25, 23, 27, 23, 29, 23, 32, 23, 33, 24, 25, 24, 27, 24, 31, 25, 31, 26, 29, 26, 33, 27, 33, 28, 31, 28, 33, 29, 32, 29, 33, 30, 32, 30, 33, 31, 32, 31, 33, 32, 33, -1); run_leiden_modularity(&graph, NULL); run_leiden_CPM(&graph, NULL, 0.06); igraph_destroy(&graph); /* Simple disconnected graph with isolates */ igraph_small(&graph, 9, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 1, 2, 1, 3, 2, 3, 4, 5, 4, 6, 4, 7, 5, 6, 5, 7, 6, 7, -1); run_leiden_modularity(&graph, NULL); igraph_destroy(&graph); /* Disjoint union of two rings */ igraph_small(&graph, 20, IGRAPH_UNDIRECTED, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7, 7, 8, 8, 9, 0, 9, 10, 11, 11, 12, 12, 13, 13, 14, 14, 15, 15, 16, 16, 17, 17, 18, 18, 19, 10, 19, -1); run_leiden_modularity(&graph, NULL); run_leiden_CPM(&graph, NULL, 0.05); igraph_destroy(&graph); /* Completely empty graph */ igraph_small(&graph, 10, IGRAPH_UNDIRECTED, -1); run_leiden_modularity(&graph, NULL); igraph_destroy(&graph); /* Ring graph with loop edges */ igraph_small(&graph, 6, IGRAPH_UNDIRECTED, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 0, 0, 0, 2, 2, -1); run_leiden_modularity(&graph, NULL); igraph_destroy(&graph); /* Regression test -- graph with two vertices and two edges */ igraph_small(&graph, 2, IGRAPH_UNDIRECTED, 0, 0, 1, 1, -1); run_leiden_modularity(&graph, NULL); igraph_destroy(&graph); igraph_vector_destroy(&weights); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/tests/cattr_bool_bug2.graphml0000644000076500000240000000064313524616144030223 0ustar tamasstaff00000000000000 True python-igraph-0.8.0/vendor/source/igraph/examples/tests/igraph_community_leiden.out0000644000076500000240000000235613610335511031222 0ustar tamasstaff00000000000000Leiden found 2 clusters using modularity, quality is 0.4524. Membership: 0 0 0 0 0 1 1 1 1 1 Leiden found 2 clusters using modularity, quality is 0.4524. Membership: 0 0 0 0 0 1 1 1 1 1 Leiden found 2 clusters using modularity, quality is 0.1797. Membership: 0 0 1 1 1 1 Leiden found 2 clusters using modularity, quality is 0.1709. Membership: 0 0 0 1 1 1 Leiden found 4 clusters using modularity, quality is 0.4188. Membership: 0 0 0 0 1 1 1 0 2 0 1 0 0 0 2 2 1 0 2 0 2 0 2 3 3 3 2 3 3 2 2 3 2 2 Leiden found 2 clusters using CPM (resolution parameter=0.06), quality is 0.6495. Membership: 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 1 0 1 0 1 1 1 1 1 1 1 1 1 1 1 1 Leiden found 3 clusters using modularity, quality is 0.5000. Membership: 0 0 0 0 1 1 1 1 2 Leiden found 4 clusters using modularity, quality is 0.5450. Membership: 0 0 0 0 0 1 1 1 1 1 2 2 2 3 3 3 3 2 2 2 Leiden found 2 clusters using CPM (resolution parameter=0.05), quality is 0.7500. Membership: 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 Leiden found 10 clusters using modularity, quality is nan. Membership: 0 1 2 3 4 5 6 7 8 9 Leiden found 3 clusters using modularity, quality is 0.2812. Membership: 0 0 1 1 2 2 Leiden found 2 clusters using modularity, quality is 0.5000. Membership: 0 1 python-igraph-0.8.0/vendor/source/igraph/examples/tests/igraph_layout_reingold_tilford_extended.in0000644000076500000240000000002013532467671034262 0ustar tamasstaff000000000000001 0 2 0 3 2 4 5 python-igraph-0.8.0/vendor/source/igraph/examples/tests/igraph_community_fluid_communities.out0000644000076500000240000000000013576365615033504 0ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/examples/tests/igraph_community_fluid_communities.c0000755000076500000240000000503213614300625033113 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_integer_t k; igraph_vector_t membership; igraph_rng_seed(igraph_rng_default(), 247); /* Zachary Karate club -- this is just a quick smoke test */ igraph_small(&g, 0, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 0, 7, 0, 8, 0, 10, 0, 11, 0, 12, 0, 13, 0, 17, 0, 19, 0, 21, 0, 31, 1, 2, 1, 3, 1, 7, 1, 13, 1, 17, 1, 19, 1, 21, 1, 30, 2, 3, 2, 7, 2, 8, 2, 9, 2, 13, 2, 27, 2, 28, 2, 32, 3, 7, 3, 12, 3, 13, 4, 6, 4, 10, 5, 6, 5, 10, 5, 16, 6, 16, 8, 30, 8, 32, 8, 33, 9, 33, 13, 33, 14, 32, 14, 33, 15, 32, 15, 33, 18, 32, 18, 33, 19, 33, 20, 32, 20, 33, 22, 32, 22, 33, 23, 25, 23, 27, 23, 29, 23, 32, 23, 33, 24, 25, 24, 27, 24, 31, 25, 31, 26, 29, 26, 33, 27, 33, 28, 31, 28, 33, 29, 32, 29, 33, 30, 32, 30, 33, 31, 32, 31, 33, 32, 33, -1); igraph_vector_init(&membership, 0); k = 2; igraph_community_fluid_communities(&g, k, &membership, /*modularity=*/ 0); if (!igraph_vector_contains(&membership, 0) || !igraph_vector_contains(&membership, 1)) { printf("Resulting graph does not have exactly 2 communities as expected.\n"); igraph_vector_print(&membership); return 1; } igraph_destroy(&g); igraph_vector_destroy(&membership); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/tests/igraph_decompose_strong.out0000644000076500000240000000006413524616144031232 0ustar tamasstaff000000000000000 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 0 0 1 1 2 2 0 python-igraph-0.8.0/vendor/source/igraph/examples/tests/rng_reproducibility.c0000644000076500000240000000057713612122634030023 0ustar tamasstaff00000000000000 #include /* * This test serves to ensure that the same sequence of random numbers are generated for the * same seed on all platforms (different operating systems and 32- or 64-bit systems). */ int main() { int i; igraph_rng_seed(igraph_rng_default(), 137); for (i = 0; i < 32; ++i) { printf("%ld\n", RNG_INTEGER(0, 100)); } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/tests/igraph_decompose_strong.c0000644000076500000240000000436113612122634030643 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include void free_complist(igraph_vector_ptr_t *complist) { long int i; for (i = 0; i < igraph_vector_ptr_size(complist); i++) { igraph_destroy(VECTOR(*complist)[i]); free(VECTOR(*complist)[i]); } } int main() { igraph_t ring, g; igraph_vector_ptr_t complist; long int i; /* A directed ring, a single strongly connected component */ igraph_ring(&ring, 10, IGRAPH_DIRECTED, 0, 1); igraph_vector_ptr_init(&complist, 0); igraph_decompose(&ring, &complist, IGRAPH_STRONG, -1, 0); igraph_write_graph_edgelist(VECTOR(complist)[0], stdout); free_complist(&complist); igraph_destroy(&ring); /* a toy graph, three components maximum, with at least 2 vertices each */ /* 0 >-> 1 >-> 3 >-> 4 ^ v \< 2 < / */ igraph_real_t edges[] = { 0, 1, 1, 2, 2, 0, 1, 3, 3, 4 }; igraph_vector_t v; igraph_create(&g, igraph_vector_view(&v, edges, sizeof(edges) / sizeof(igraph_real_t)), 0, IGRAPH_DIRECTED); igraph_decompose(&g, &complist, IGRAPH_STRONG, 3, 2); for (i = 0; i < igraph_vector_ptr_size(&complist); i++) { igraph_write_graph_edgelist(VECTOR(complist)[i], stdout); } free_complist(&complist); igraph_destroy(&g); igraph_vector_ptr_destroy(&complist); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/tests/igraph_layout_reingold_tilford_extended.c0000644000076500000240000000265513612122634034100 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int main() { igraph_t g; FILE *f; igraph_matrix_t coords; /* long int i, n; */ f = fopen("igraph_layout_reingold_tilford_extended.in", "r"); igraph_read_graph_edgelist(&g, f, 0, 1); igraph_matrix_init(&coords, 0, 0); igraph_layout_reingold_tilford(&g, &coords, IGRAPH_IN, 0, 0); /* n=igraph_vcount(&g); for (i=0; i #include "test_utilities.inc" #define SIMPLIFY_PRINT_DESTROY(name) \ printf(name "\n"); \ igraph_simplify_and_colorize(&graph, &res, &vcol, &ecol); \ print_graph(&res, stdout); \ print_vector_int(&vcol, stdout); \ print_vector_int(&ecol, stdout); \ printf("\n"); \ igraph_destroy(&graph); int main() { igraph_t graph, res; igraph_vector_int_t vcol, ecol; igraph_vector_int_init(&vcol, 0); igraph_vector_int_init(&ecol, 0); /* null graph */ igraph_empty(&graph, 0, 0); SIMPLIFY_PRINT_DESTROY("K0"); /* singleton graph */ igraph_empty(&graph, 1, 0); SIMPLIFY_PRINT_DESTROY("K1"); /* 4-cycle-graph */ igraph_ring(&graph, 4, 0, 0, 1); SIMPLIFY_PRINT_DESTROY("C4"); /* both multi-edges and self loops */ igraph_small(&graph, 2, 0, 0, 1, 0, 1, 1, 1, -1); SIMPLIFY_PRINT_DESTROY("Undirected graph 1"); /* parallel edges specified with different vertex orderings */ igraph_small(&graph, 3, 0, 0, 1, 1, 2, 2, 0, 2, 2, 2, 2, 2, 1, -1); SIMPLIFY_PRINT_DESTROY("Undirected graph 2"); /* directed version of the same as above */ igraph_small(&graph, 3, 1, 0, 1, 1, 2, 2, 0, 2, 2, 2, 2, 2, 1, -1); SIMPLIFY_PRINT_DESTROY("Directed graph 1"); /* isolated vertices */ igraph_small(&graph, 4, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, -1); SIMPLIFY_PRINT_DESTROY("Directed graph 2"); igraph_vector_int_destroy(&vcol); igraph_vector_int_destroy(&ecol); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/tests/maximal_cliques_hist.c0000644000076500000240000000060613612122634030141 0ustar tamasstaff00000000000000 #include int main() { igraph_t graph; igraph_vector_t hist; igraph_small(&graph, 6, 0, 1, 2, 2, 3, 3, 4, 4, 5, 5, 2, 2, 4, -1); igraph_vector_init(&hist, 0); igraph_maximal_cliques_hist(&graph, &hist, 0, 0); igraph_vector_print(&hist); igraph_vector_destroy(&hist); igraph_destroy(&graph); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/tests/maximal_cliques_callback.c0000644000076500000240000000436113612122634030730 0ustar tamasstaff00000000000000 #include #include struct userdata { int i; igraph_vector_ptr_t *list; }; int compare_vectors(const void *p1, const void *p2) { igraph_vector_t *v1, *v2; long s1, s2, i; v1 = *((igraph_vector_t **) p1); v2 = *((igraph_vector_t **) p2); s1 = igraph_vector_size(v1); s2 = igraph_vector_size(v2); if (s1 < s2) { return -1; } if (s1 > s2) { return 1; } for (i = 0; i < s1; ++i) { if (VECTOR(*v1)[i] < VECTOR(*v2)[i]) { return -1; } if (VECTOR(*v1)[i] > VECTOR(*v2)[i]) { return 1; } } return 0; } igraph_bool_t handler(igraph_vector_t *clique, void *arg) { struct userdata *ud; igraph_bool_t cont; ud = (struct userdata *) arg; cont = 1; /* true */ if (compare_vectors(&clique, &(VECTOR(*(ud->list))[ud->i])) != 0) { printf("igraph_maximal_cliques() and igraph_maximal_cliques_callback() give different results.\n"); cont = 0; /* false */ } igraph_vector_destroy(clique); igraph_free(clique); ud->i += 1; return cont; } igraph_bool_t handler_stop(igraph_vector_t *clique, void *arg) { /* Stop search as soon as a 3-clique is found. */ /* Since there are two 3-cliques in the test graph, this will stop the search before it is complete. */ if (igraph_vector_size(clique) == 3) { return 0; /* false */ } igraph_vector_destroy(clique); igraph_free(clique); return 1 /* true */; } int main() { igraph_t graph; igraph_vector_ptr_t list; struct userdata ud; igraph_small(&graph, 6, 0, 1, 2, 2, 3, 3, 4, 4, 5, 5, 2, 2, 4, -1); igraph_vector_ptr_init(&list, 0); igraph_maximal_cliques(&graph, &list, 0, 0); ud.i = 0; ud.list = &list; /* Check that the callback function finds the same cliques as igraph_maximal_cliques() */ igraph_maximal_cliques_callback(&graph, &handler, (void *) &ud, 0, 0); /* Check that the search can be stopped correctly */ igraph_maximal_cliques_callback(&graph, &handler_stop, NULL, 0, 0); IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(&list, igraph_vector_destroy); igraph_vector_ptr_destroy_all(&list); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/tests/tree.out0000644000076500000240000000072013524616144025264 0ustar tamasstaff00000000000000Null graph directed: false vcount: 0 edges: { } Directed null graph directed: true vcount: 0 edges: { } Singleton graph directed: false vcount: 1 edges: { } Path graph directed: true vcount: 3 edges: { 0 1 1 2 } Binary out-tree, n=3 directed: true vcount: 3 edges: { 0 1 0 2 } Binary in-tree, n=3 directed: true vcount: 3 edges: { 1 0 2 0 } Ternary out-tree, n=14 directed: true vcount: 14 edges: { 0 1 0 2 0 3 1 4 1 5 1 6 2 7 2 8 2 9 3 10 3 11 3 12 4 13 } python-igraph-0.8.0/vendor/source/igraph/examples/tests/tree.c0000644000076500000240000000155413524616144024705 0ustar tamasstaff00000000000000 #include #include "test_utilities.inc" #define PRINT_DESTROY(name) \ printf(name "\n"); \ print_graph(&graph, stdout); \ igraph_destroy(&graph); \ printf("\n"); int main() { igraph_t graph; igraph_tree(&graph, 0, 1, IGRAPH_TREE_UNDIRECTED); PRINT_DESTROY("Null graph"); igraph_tree(&graph, 0, 1, IGRAPH_TREE_OUT); PRINT_DESTROY("Directed null graph"); igraph_tree(&graph, 1, 1, IGRAPH_TREE_UNDIRECTED); PRINT_DESTROY("Singleton graph"); igraph_tree(&graph, 3, 1, IGRAPH_TREE_OUT); PRINT_DESTROY("Path graph"); igraph_tree(&graph, 3, 2, IGRAPH_TREE_OUT); PRINT_DESTROY("Binary out-tree, n=3"); igraph_tree(&graph, 3, 2, IGRAPH_TREE_IN); PRINT_DESTROY("Binary in-tree, n=3"); igraph_tree(&graph, 14, 3, IGRAPH_TREE_OUT); PRINT_DESTROY("Ternary out-tree, n=14"); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/0000755000076500000240000000000013617375001023721 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_write_graph_pajek.c0000644000076500000240000000475513612122634031114 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_strvector_t names; igraph_i_set_attribute_table(&igraph_cattribute_table); /* save a simple ring graph */ igraph_ring(&g, 10, IGRAPH_DIRECTED, 0 /* mutual */, 1 /* circular */); igraph_write_graph_pajek(&g, stdout); /* add some vertex attributes */ igraph_strvector_init(&names, 0); igraph_strvector_add(&names, "A"); igraph_strvector_add(&names, "B"); igraph_strvector_add(&names, "C"); igraph_strvector_add(&names, "D"); igraph_strvector_add(&names, "E"); igraph_strvector_add(&names, "F"); igraph_strvector_add(&names, "G"); igraph_strvector_add(&names, "H"); igraph_strvector_add(&names, "I"); igraph_strvector_add(&names, "J"); SETVASV(&g, "id", &names); igraph_strvector_destroy(&names); /* save the graph with vertex names */ igraph_write_graph_pajek(&g, stdout); igraph_strvector_init(&names, 0); igraph_strvector_add(&names, "square"); igraph_strvector_add(&names, "square"); igraph_strvector_add(&names, "square"); igraph_strvector_add(&names, "square"); igraph_strvector_add(&names, "escaping spaces"); igraph_strvector_add(&names, "square"); igraph_strvector_add(&names, "square"); igraph_strvector_add(&names, "escaping \\backslashes\\"); igraph_strvector_add(&names, "square"); igraph_strvector_add(&names, "escaping \"quotes\""); SETVASV(&g, "shape", &names); igraph_strvector_destroy(&names); /* save the graph with escaped shapes */ igraph_write_graph_pajek(&g, stdout); /* destroy the graph */ igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_es_adj.out0000644000076500000240000000017613524616144027240 0ustar tamasstaff000000000000001 1 2 0 2 5 1 2 2 3 4 2 2 4 2 2 3 1 1 1 2 3 2 3 4 1 4 1 0 2 1 2 1 2 2 2 3 1 1 2 0 2 5 1 2 2 3 4 2 2 4 2 2 3 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_isomorphic_vf2.c0000644000076500000240000002340513612122633030350 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include int main() { igraph_t ring1, ring2; igraph_vector_int_t color1, color2; igraph_vector_t perm; igraph_bool_t iso; igraph_integer_t count; long int i; igraph_rng_seed(igraph_rng_default(), 12345); igraph_ring(&ring1, 100, /*directed=*/ 0, /*mutual=*/ 0, /*circular=*/1); igraph_vector_init_seq(&perm, 0, igraph_vcount(&ring1) - 1); igraph_vector_shuffle(&perm); igraph_permute_vertices(&ring1, &ring2, &perm); /* Without colors */ igraph_isomorphic(&ring1, &ring2, &iso); if (!iso) { fprintf(stderr, "Without color failed.\n"); return 1; } /* Without colors, number of isomorphisms */ igraph_count_isomorphisms_vf2(&ring1, &ring2, 0, 0, 0, 0, &count, 0, 0, 0); if (count != 200) { fprintf(stderr, "Count without colors failed, expected %li, got %li.\n", (long int) 200, (long int) count); return 2; } /* Everything has the same colors */ igraph_vector_int_init(&color1, igraph_vcount(&ring1)); igraph_vector_int_init(&color2, igraph_vcount(&ring2)); igraph_isomorphic_vf2(&ring1, &ring2, &color1, &color2, 0, 0, &iso, 0, 0, 0, 0, 0); if (!iso) { fprintf(stderr, "Single color failed.\n"); return 3; } /* Two colors, just counting */ for (i = 0; i < igraph_vector_int_size(&color1); i += 2) { VECTOR(color1)[i] = VECTOR(color2)[(long int)VECTOR(perm)[i]] = 1; } igraph_count_isomorphisms_vf2(&ring1, &ring2, &color1, &color2, 0, 0, &count, 0, 0, 0); if (count != 100) { fprintf(stderr, "Count with two colors failed, expected %li, got %li.\n", (long int) 100, (long int) count); return 4; } /* Separate colors for each vertex */ for (i = 0; i < igraph_vector_int_size(&color1); i++) { VECTOR(color1)[i] = VECTOR(color2)[(long int)VECTOR(perm)[i]] = i; } igraph_count_isomorphisms_vf2(&ring1, &ring2, &color1, &color2, 0, 0, &count, 0, 0, 0); if (count != 1) { fprintf(stderr, "Count with separate colors failed, expected %li, got %li.\n", (long int) 1, (long int) count); return 5; } /* Try a negative result */ igraph_vector_int_fill(&color1, 0); igraph_vector_int_fill(&color2, 0); VECTOR(color1)[0] = 1; igraph_isomorphic_vf2(&ring1, &ring2, &color1, &color2, 0, 0, &iso, 0, 0, 0, 0, 0); if (iso) { fprintf(stderr, "Negative test failed.\n"); return 6; } /* Another negative, same color distribution, different topology */ igraph_vector_int_fill(&color1, 0); igraph_vector_int_fill(&color2, 0); VECTOR(color1)[0] = 1; VECTOR(color1)[1] = 1; VECTOR(color2)[0] = 1; VECTOR(color2)[((long int)VECTOR(perm)[1] + 1) % igraph_vcount(&ring2)] = 1; igraph_isomorphic_vf2(&ring1, &ring2, &color1, &color2, 0, 0, &iso, 0, 0, 0, 0, 0); if (iso) { fprintf(stderr, "Second negative test failed.\n"); return 7; } igraph_vector_int_destroy(&color1); igraph_vector_int_destroy(&color2); igraph_vector_destroy(&perm); igraph_destroy(&ring2); igraph_destroy(&ring1); /* ---------------------------------------------------------------- */ /* SUBGRAPH ISOMORPHISM */ /* ---------------------------------------------------------------- */ igraph_ring(&ring1, 100, /*directed=*/ 0, /*mutual=*/ 0, /*circular=*/0); igraph_ring(&ring2, 80, /*directed=*/ 0, /*mutual=*/ 0, /*circular=*/0); /* One color */ igraph_vector_int_init(&color1, igraph_vcount(&ring1)); igraph_vector_int_init(&color2, igraph_vcount(&ring2)); igraph_count_subisomorphisms_vf2(&ring1, &ring2, &color1, &color2, 0, 0, &count, 0, 0, 0); if (count != 42) { fprintf(stderr, "Count with one color failed, expected %li, got %li.\n", (long int) 42, (long int) count); return 31; } /* Two colors */ for (i = 0; i < igraph_vector_int_size(&color1); i += 2) { VECTOR(color1)[i] = 0; VECTOR(color1)[i + 1] = 1; } for (i = 0; i < igraph_vector_int_size(&color2); i += 2) { VECTOR(color2)[i] = 0; VECTOR(color2)[i + 1] = 1; } igraph_count_subisomorphisms_vf2(&ring1, &ring2, &color1, &color2, 0, 0, &count, 0, 0, 0); if (count != 21) { fprintf(stderr, "Count with two colors failed, expected %li, got %li.\n", (long int) 21, (long int) count); return 32; } igraph_vector_int_destroy(&color1); igraph_vector_int_destroy(&color2); igraph_destroy(&ring1); igraph_destroy(&ring2); /* ---------------------------------------------------------------- */ /* EDGE COLORING, GRAPH ISOMORPHISM */ /* ---------------------------------------------------------------- */ igraph_ring(&ring1, 100, /*directed=*/ 0, /*mutual=*/ 0, /*circular=*/ 1); igraph_vector_init_seq(&perm, 0, igraph_ecount(&ring1) - 1); igraph_vector_shuffle(&perm); igraph_permute_vertices(&ring1, &ring2, &perm); igraph_vector_destroy(&perm); /* Everything has the same color */ igraph_vector_int_init(&color1, igraph_ecount(&ring1)); igraph_vector_int_init(&color2, igraph_ecount(&ring2)); igraph_isomorphic_vf2(&ring1, &ring2, 0, 0, &color1, &color2, &iso, 0, 0, 0, 0, 0); if (!iso) { fprintf(stderr, "Single edge-color failed.\n"); return 41; } /* Two colors, just counting */ for (i = 0; i < igraph_vector_int_size(&color1); i += 2) { VECTOR(color1)[i] = VECTOR(color2)[i] = 0; VECTOR(color1)[i + 1] = VECTOR(color2)[i] = 1; } igraph_count_isomorphisms_vf2(&ring1, &ring2, 0, 0, &color1, &color2, &count, 0, 0, 0); if (count != 100) { fprintf(stderr, "Count with two edge colors failed, expected %li, got %li.\n", (long int) 100, (long int) count); return 42; } /* Separate colors for each edge */ for (i = 0; i < igraph_vector_int_size(&color1); i++) { VECTOR(color1)[i] = VECTOR(color2)[i] = i; } igraph_count_isomorphisms_vf2(&ring1, &ring2, 0, 0, &color1, &color2, &count, 0, 0, 0); if (count != 1) { fprintf(stderr, "Count with separate edge colors failed, expected %li, got %li.\n", (long int) 1, (long int) count); return 43; } /* Try a negative result */ igraph_vector_int_fill(&color1, 0); igraph_vector_int_fill(&color2, 0); VECTOR(color1)[0] = 1; igraph_isomorphic_vf2(&ring1, &ring2, 0, 0, &color1, &color2, &iso, 0, 0, 0, 0, 0); if (iso) { fprintf(stderr, "Negative edge test failed.\n"); return 44; } /* Another negative, same color distribution, different topology */ igraph_vector_int_fill(&color1, 0); igraph_vector_int_fill(&color2, 0); VECTOR(color1)[0] = 1; VECTOR(color1)[1] = 1; VECTOR(color2)[0] = 1; VECTOR(color2)[2] = 1; igraph_isomorphic_vf2(&ring1, &ring2, 0, 0, &color1, &color2, &iso, 0, 0, 0, 0, 0); if (iso) { fprintf(stderr, "Second negative edge test failed.\n"); return 45; } igraph_vector_int_destroy(&color1); igraph_vector_int_destroy(&color2); igraph_destroy(&ring1); igraph_destroy(&ring2); /* ---------------------------------------------------------------- */ /* EDGE COLORED SUBGRAPH ISOMORPHISM */ /* ---------------------------------------------------------------- */ igraph_ring(&ring1, 100, /*directed=*/ 0, /*mutual=*/ 0, /*circular=*/0); igraph_ring(&ring2, 80, /*directed=*/ 0, /*mutual=*/ 0, /*circular=*/0); /* One color */ igraph_vector_int_init(&color1, igraph_ecount(&ring1)); igraph_vector_int_init(&color2, igraph_ecount(&ring2)); igraph_count_subisomorphisms_vf2(&ring1, &ring2, 0, 0, &color1, &color2, &count, 0, 0, 0); if (count != 42) { fprintf(stderr, "Count with one edge color failed, expected %li, got %li.\n", (long int) 42, (long int) count); return 51; } /* Two colors */ for (i = 0; i < igraph_vector_int_size(&color1) - 1; i += 2) { VECTOR(color1)[i] = 0; VECTOR(color1)[i + 1] = 1; } for (i = 0; i < igraph_vector_int_size(&color2) - 1; i += 2) { VECTOR(color2)[i] = 0; VECTOR(color2)[i + 1] = 1; } igraph_count_subisomorphisms_vf2(&ring1, &ring2, 0, 0, &color1, &color2, &count, 0, 0, 0); if (count != 22) { fprintf(stderr, "Count with two edge colors failed, expected %li, got %li.\n", (long int) 22, (long int) count); return 52; } igraph_vector_int_destroy(&color1); igraph_vector_int_destroy(&color2); igraph_destroy(&ring1); igraph_destroy(&ring2); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_stochastic_imitation.c0000644000076500000240000002277013612122634031645 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* Test suite for stochastic imitation via uniform selection. Copyright (C) 2011 Minh Van Nguyen This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include /* test parameters structure */ typedef struct { igraph_t *graph; igraph_integer_t vertex; igraph_imitate_algorithm_t algo; igraph_vector_t *quantities; igraph_vector_t *strategies; igraph_vector_t *known_strats; igraph_neimode_t mode; int retval; } strategy_test_t; /* Error tests. That is, we expect error codes to be returned from such tests. */ int error_tests() { igraph_t g, h; igraph_vector_t quant, strat; int i, n, ret; strategy_test_t *test; /* nonempty graph */ igraph_small(&g, /*n vertices*/ 0, IGRAPH_UNDIRECTED, 0, 1, 1, 2, 2, 0, -1); igraph_empty(&h, 0, 0); /* empty graph */ igraph_vector_init(&quant, 1); /* quantities vector */ igraph_vector_init(&strat, 2); /* strategies vector */ /* test parameters */ /*graph--vertex--algo--quantities--strategies--known_strats--mode--retval*/ /* null pointer for graph */ strategy_test_t null_graph = {NULL, 0, IGRAPH_IMITATE_BLIND, NULL, NULL, NULL, IGRAPH_ALL, IGRAPH_EINVAL}; /* null pointer for quantities vector */ strategy_test_t null_quant = {&g, 0, IGRAPH_IMITATE_BLIND, NULL, NULL, NULL, IGRAPH_ALL, IGRAPH_EINVAL}; /* null pointer for strategies vector */ strategy_test_t null_strat = {&g, 0, IGRAPH_IMITATE_BLIND, &quant, NULL, NULL, IGRAPH_ALL, IGRAPH_EINVAL}; /* empty graph */ strategy_test_t empty_graph = {&h, 0, IGRAPH_IMITATE_BLIND, &quant, &strat, NULL, IGRAPH_ALL, IGRAPH_EINVAL}; /* length of quantities vector different from number of vertices */ strategy_test_t qdiff_length = {&g, 0, IGRAPH_IMITATE_BLIND, &quant, &strat, NULL, IGRAPH_ALL, IGRAPH_EINVAL}; /* length of strategies vector different from number of vertices */ strategy_test_t sdiff_length = {&g, 0, IGRAPH_IMITATE_BLIND, &quant, &strat, NULL, IGRAPH_ALL, IGRAPH_EINVAL}; strategy_test_t unknown_algo = {&g, 0, -1, &quant, &strat, NULL, IGRAPH_ALL, IGRAPH_EINVAL}; strategy_test_t *all_checks[] = {/* 1 */ &null_graph, /* 2 */ &null_quant, /* 3 */ &null_strat, /* 4 */ &empty_graph, /* 5 */ &qdiff_length, /* 6 */ &sdiff_length, /* 7 */ &unknown_algo }; /* Run the error tests. We expect error to be raised for each test. */ igraph_set_error_handler(igraph_error_handler_ignore); n = 7; i = 0; while (i < n) { test = all_checks[i]; ret = igraph_stochastic_imitation(test->graph, test->vertex, test->algo, test->quantities, test->strategies, test->mode); if (ret != test->retval) { printf("Error test no. %d failed.\n", (int)(i + 1)); return IGRAPH_FAILURE; } i++; } /* clean up */ igraph_destroy(&g); igraph_destroy(&h); igraph_vector_destroy(&quant); igraph_vector_destroy(&strat); return IGRAPH_SUCCESS; } /* Updating the strategy of an isolated vertex. In this case, the strategies * vector should not change at all. */ int isolated_vertex_test() { igraph_t g; igraph_vector_t quant, strat, v; int i, ret; /* graph with one isolated vertex */ igraph_small(&g, /*n vertices*/ 0, IGRAPH_UNDIRECTED, 0, 1, 1, 2, 2, 0, -1); igraph_add_vertices(&g, 1, 0); /* new vertex 3 is isolated */ /* quantities vector: all vertices have the same fitness */ igraph_vector_init_real(&quant, 4, 0.25, 0.25, 0.25, 0.25); /* strategies vector: 0 means aggressive strategy; 1 means passive */ igraph_vector_init_real(&strat, 4, 1.0, 0.0, 1.0, 0.0); /* make a copy of the original strategies vector for comparison later on */ igraph_vector_copy(&v, &strat); /* Now update strategy of vertex 3. Since this vertex is isolated, no */ /* strategy update would take place. The resulting strategies vector */ /* would be the same as it was originally. */ ret = igraph_stochastic_imitation(/*graph*/ &g, /*vertex*/ 3, /*algorithm*/ IGRAPH_IMITATE_BLIND, /*quantities*/ &quant, /*strategies*/ &strat, /*mode*/ IGRAPH_ALL); if (ret) { printf("Isolated vertex test failed.\n"); return IGRAPH_FAILURE; } for (i = 0; i < igraph_vector_size(&strat); i++) { if (VECTOR(strat)[i] != VECTOR(v)[i]) { printf("Isolated vertex test failed.\n"); return IGRAPH_FAILURE; } } /* clean up */ igraph_destroy(&g); igraph_vector_destroy(&quant); igraph_vector_destroy(&strat); igraph_vector_destroy(&v); return IGRAPH_SUCCESS; } /* A game on the Petersen graph. This graph has 10 vertices and 15 edges. The * Petersen graph is initialized with a default quantities vector and a * default strategies vector. Some vertices are chosen for strategy revision, * each one via a different stochastic imitation rule. */ int petersen_game_test() { igraph_t g; igraph_bool_t success; igraph_vector_t quant, strat, stratcopy, *knownstrats; igraph_vector_t known0, known2, known4; int i, k, n, nvert, ret; strategy_test_t *test; /* the Petersen graph */ igraph_small(&g, /*n vertices*/ 0, IGRAPH_UNDIRECTED, 0, 1, 0, 4, 0, 5, 1, 2, 1, 6, 2, 3, 2, 7, 3, 4, 3, 8, 4, 9, 5, 7, 5, 8, 6, 8, 6, 9, 7, 9, -1); nvert = igraph_vcount(&g); /* Strategies vector, one strategy for each vertex. Thus vec[i] is the */ /* strategy of vertex i. The strategy space is: {0, 1, 2, 3}. */ /* Each strategy should be an integer. */ igraph_vector_init_real(&strat, nvert, 1.0, 1.0, 2.0, 2.0, 0.0, 0.0, 0.0, 1.0, 2.0, 3.0); /* Quantities vector, one quantity per vertex. Thus vec[i] is the */ /* quantity for vertex i. */ igraph_vector_init_real(&quant, nvert, 0.3, 1.1, 0.5, 1.0, 0.9, 0.8, 0.4, 0.1, 0.7, 0.7); /* parameter settings and known results */ igraph_vector_init_real(&known0, 2, 0.0, 1.0); igraph_vector_init_real(&known2, 2, 1.0, 2.0); igraph_vector_init_real(&known4, 2, 0.0, 2.0); /*graph--vertex--algo--quantities--strategies--known_strats--mode--retval*/ strategy_test_t blind0 = {&g, 0, IGRAPH_IMITATE_BLIND, &quant, NULL, &known0, IGRAPH_ALL, IGRAPH_SUCCESS}; strategy_test_t augmented4 = {&g, 4, IGRAPH_IMITATE_AUGMENTED, &quant, NULL, &known4, IGRAPH_ALL, IGRAPH_SUCCESS}; strategy_test_t contracted2 = {&g, 2, IGRAPH_IMITATE_CONTRACTED, &quant, NULL, &known2, IGRAPH_ALL, IGRAPH_SUCCESS}; strategy_test_t *all_checks[] = {/* 1 */ &blind0, /* 2 */ &augmented4, /* 3 */ &contracted2 }; /* run the tests */ n = 3; i = 0; while (i < n) { test = all_checks[i]; igraph_vector_copy(&stratcopy, &strat); ret = igraph_stochastic_imitation(test->graph, test->vertex, test->algo, test->quantities, &stratcopy, test->mode); if (ret) { printf("Stochastic imitation failed for vertex %d.\n", (int)test->vertex); return IGRAPH_FAILURE; } /* If the updated strategy for the vertex matches one of the known */ /* strategies, then success. Default to failure. */ success = 0; knownstrats = test->known_strats; for (k = 0; k < igraph_vector_size(knownstrats); k++) { if (VECTOR(*knownstrats)[k] == VECTOR(stratcopy)[test->vertex]) { success = 1; break; } } if (!success) { printf("Stochastic imitation failed for vertex %d.\n", (int)test->vertex); return IGRAPH_FAILURE; } igraph_vector_destroy(&stratcopy); i++; } /* clean up */ igraph_destroy(&g); igraph_vector_destroy(&known0); igraph_vector_destroy(&known2); igraph_vector_destroy(&known4); igraph_vector_destroy(&quant); igraph_vector_destroy(&strat); return IGRAPH_SUCCESS; } int main() { int ret; ret = error_tests(); if (ret) { return ret; } ret = isolated_vertex_test(); if (ret) { return ret; } ret = petersen_game_test(); if (ret) { return ret; } return IGRAPH_SUCCESS; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_all_st_cuts.c0000644000076500000240000003245313612122633027736 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include "igraph_marked_queue.h" #include "igraph_estack.h" int igraph_i_all_st_cuts_pivot(const igraph_t *graph, const igraph_marked_queue_t *S, const igraph_estack_t *T, long int source, long int target, long int *v, igraph_vector_t *Isv); int test_all_st_cuts(const igraph_t *graph, long int source, long int target) { igraph_vector_ptr_t cuts, partition1s; long int n, i; igraph_vector_ptr_init(&cuts, 0); igraph_vector_ptr_init(&partition1s, 0); igraph_all_st_cuts(graph, &cuts, &partition1s, source, target); n = igraph_vector_ptr_size(&partition1s); printf("Partitions and cuts:\n"); for (i = 0; i < n; i++) { igraph_vector_t *v = VECTOR(partition1s)[i]; igraph_vector_t *v2 = VECTOR(cuts)[i]; printf("P: "); igraph_vector_print(v); igraph_vector_destroy(v); igraph_free(v); printf("C: "); igraph_vector_print(v2); igraph_vector_destroy(v2); igraph_free(v2); } igraph_vector_ptr_destroy(&partition1s); igraph_vector_ptr_destroy(&cuts); return 0; } int main() { igraph_t g; igraph_vector_ptr_t cuts, partition1s; long int i, n; igraph_marked_queue_t S; igraph_estack_t T; long int v; igraph_vector_t Isv; /* ----------------------------------------------------------- */ /* This is the example from the Provan-Shier paper, for calculating the dominator tree and finding the right pivot element */ igraph_small(&g, 12, IGRAPH_DIRECTED, /* a->b */ 0, 1, /* b->t */ 1, 11, /* c->b */ 2, 1, /* c->d */ 2, 3, /* d->e */ 3, 4, /* d->i */ 3, 8, /* e->c */ 4, 2, /* f->c */ 5, 2, /* f->e */ 5, 4, /* g->d */ 6, 3, /* g->e */ 6, 4, /* g->f */ 6, 5, /* g->j */ 6, 9, /* h->g */ 7, 6, /* h->t */ 7, 11, /* i->a */ 8, 0, /* j->i */ 9, 8, /* s->a */ 10, 0, /* s->c */ 10, 2, /* s->h */ 10, 7, -1); /* S={s,a} */ igraph_marked_queue_init(&S, igraph_vcount(&g)); igraph_marked_queue_start_batch(&S); igraph_marked_queue_push(&S, 10); igraph_marked_queue_push(&S, 0); /* T={t} */ igraph_estack_init(&T, igraph_vcount(&g), 1); igraph_estack_push(&T, 11); igraph_vector_init(&Isv, 0); igraph_i_all_st_cuts_pivot(&g, &S, &T, /*source=*/ 10, /*target=*/ 11, &v, &Isv); /* Expected result: v=c, Isv={c,d,e,i} */ printf("%li; ", v); igraph_vector_print(&Isv); igraph_vector_destroy(&Isv); igraph_estack_destroy(&T); igraph_marked_queue_destroy(&S); igraph_destroy(&g); /* ----------------------------------------------------------- */ igraph_small(&g, 3, IGRAPH_DIRECTED, 0, 1, 1, 2, -1); /* S={}, T={} */ igraph_marked_queue_init(&S, igraph_vcount(&g)); igraph_estack_init(&T, igraph_vcount(&g), 3); igraph_vector_init(&Isv, 0); igraph_i_all_st_cuts_pivot(&g, &S, &T, /*source=*/ 0, /*target=*/ 2, &v, &Isv); printf("%li; ", v); igraph_vector_print(&Isv); igraph_vector_destroy(&Isv); igraph_estack_destroy(&T); igraph_marked_queue_destroy(&S); igraph_destroy(&g); /* ----------------------------------------------------------- */ igraph_small(&g, 3, IGRAPH_DIRECTED, 0, 1, 1, 2, -1); /* S={}, T={0} */ igraph_marked_queue_init(&S, igraph_vcount(&g)); igraph_estack_init(&T, igraph_vcount(&g), 3); igraph_estack_push(&T, 0); igraph_vector_init(&Isv, 0); igraph_i_all_st_cuts_pivot(&g, &S, &T, /*source=*/ 0, /*target=*/ 2, &v, &Isv); printf("%li; ", v); igraph_vector_print(&Isv); igraph_vector_destroy(&Isv); igraph_estack_destroy(&T); igraph_marked_queue_destroy(&S); igraph_destroy(&g); /* ----------------------------------------------------------- */ igraph_small(&g, 3, IGRAPH_DIRECTED, 0, 1, 1, 2, -1); /* S={0}, T={} */ igraph_marked_queue_init(&S, igraph_vcount(&g)); igraph_marked_queue_push(&S, 0); igraph_estack_init(&T, igraph_vcount(&g), 3); igraph_vector_init(&Isv, 0); igraph_i_all_st_cuts_pivot(&g, &S, &T, /*source=*/ 0, /*target=*/ 2, &v, &Isv); printf("%li; ", v); igraph_vector_print(&Isv); igraph_vector_destroy(&Isv); igraph_estack_destroy(&T); igraph_marked_queue_destroy(&S); igraph_destroy(&g); /* ----------------------------------------------------------- */ igraph_small(&g, 3, IGRAPH_DIRECTED, 0, 1, 1, 2, -1); /* S={0}, T={1} */ igraph_marked_queue_init(&S, igraph_vcount(&g)); igraph_marked_queue_push(&S, 0); igraph_estack_init(&T, igraph_vcount(&g), 3); igraph_estack_push(&T, 1); igraph_vector_init(&Isv, 0); igraph_i_all_st_cuts_pivot(&g, &S, &T, /*source=*/ 0, /*target=*/ 2, &v, &Isv); printf("%li; ", v); igraph_vector_print(&Isv); igraph_vector_destroy(&Isv); igraph_estack_destroy(&T); igraph_marked_queue_destroy(&S); igraph_destroy(&g); /* ----------------------------------------------------------- */ igraph_small(&g, 3, IGRAPH_DIRECTED, 0, 1, 1, 2, -1); /* S={0,1}, T={} */ igraph_marked_queue_init(&S, igraph_vcount(&g)); igraph_marked_queue_push(&S, 0); igraph_marked_queue_push(&S, 1); igraph_estack_init(&T, igraph_vcount(&g), 3); igraph_vector_init(&Isv, 0); igraph_i_all_st_cuts_pivot(&g, &S, &T, /*source=*/ 0, /*target=*/ 2, &v, &Isv); printf("%li; ", v); igraph_vector_print(&Isv); igraph_vector_destroy(&Isv); igraph_estack_destroy(&T); igraph_marked_queue_destroy(&S); igraph_destroy(&g); /* ----------------------------------------------------------- */ igraph_small(&g, 3, IGRAPH_DIRECTED, 0, 1, 1, 2, -1); igraph_vector_ptr_init(&partition1s, 0); igraph_all_st_cuts(&g, /*cuts=*/ 0, &partition1s, /*source=*/ 0, /*target=*/ 2); n = igraph_vector_ptr_size(&partition1s); for (i = 0; i < n; i++) { igraph_vector_t *v = VECTOR(partition1s)[i]; igraph_vector_print(v); igraph_vector_destroy(v); igraph_free(v); } igraph_vector_ptr_destroy(&partition1s); igraph_destroy(&g); /* ----------------------------------------------------------- */ igraph_small(&g, 5, IGRAPH_DIRECTED, 0, 1, 1, 2, 1, 3, 2, 4, 3, 4, -1); igraph_vector_ptr_init(&partition1s, 0); igraph_all_st_cuts(&g, /*cuts=*/ 0, &partition1s, /*source=*/ 0, /*target=*/ 4); n = igraph_vector_ptr_size(&partition1s); for (i = 0; i < n; i++) { igraph_vector_t *v = VECTOR(partition1s)[i]; igraph_vector_print(v); igraph_vector_destroy(v); igraph_free(v); } igraph_vector_ptr_destroy(&partition1s); igraph_destroy(&g); /* ----------------------------------------------------------- */ igraph_small(&g, 6, IGRAPH_DIRECTED, 0, 1, 1, 2, 1, 3, 2, 4, 3, 4, 1, 5, 5, 4, -1); igraph_vector_ptr_init(&cuts, 0); igraph_vector_ptr_init(&partition1s, 0); igraph_all_st_cuts(&g, &cuts, &partition1s, /*source=*/ 0, /*target=*/ 4); n = igraph_vector_ptr_size(&partition1s); printf("Partitions and cuts:\n"); for (i = 0; i < n; i++) { igraph_vector_t *v = VECTOR(partition1s)[i]; igraph_vector_t *v2 = VECTOR(cuts)[i]; printf("P: "); igraph_vector_print(v); igraph_vector_destroy(v); igraph_free(v); printf("C: "); igraph_vector_print(v2); igraph_vector_destroy(v2); igraph_free(v2); } igraph_vector_ptr_destroy(&partition1s); igraph_vector_ptr_destroy(&cuts); igraph_destroy(&g); /* ----------------------------------------------------------- */ igraph_small(&g, 3, IGRAPH_DIRECTED, 0, 2, 1, 2, -1); igraph_vector_ptr_init(&cuts, 0); igraph_vector_ptr_init(&partition1s, 0); igraph_all_st_cuts(&g, &cuts, &partition1s, /*source=*/ 1, /*target=*/ 2); n = igraph_vector_ptr_size(&partition1s); printf("Partitions and cuts:\n"); for (i = 0; i < n; i++) { igraph_vector_t *v = VECTOR(partition1s)[i]; igraph_vector_t *v2 = VECTOR(cuts)[i]; printf("P: "); igraph_vector_print(v); igraph_vector_destroy(v); igraph_free(v); printf("C: "); igraph_vector_print(v2); igraph_vector_destroy(v2); igraph_free(v2); } igraph_vector_ptr_destroy(&partition1s); igraph_vector_ptr_destroy(&cuts); igraph_destroy(&g); /* ----------------------------------------------------------- */ igraph_small(&g, 5, IGRAPH_DIRECTED, 0, 1, 1, 2, 2, 3, 3, 4, 3, 1, -1); igraph_vector_ptr_init(&cuts, 0); igraph_vector_ptr_init(&partition1s, 0); igraph_all_st_cuts(&g, &cuts, &partition1s, /*source=*/ 0, /*target=*/ 4); n = igraph_vector_ptr_size(&partition1s); printf("Partitions and cuts:\n"); for (i = 0; i < n; i++) { igraph_vector_t *v = VECTOR(partition1s)[i]; igraph_vector_t *v2 = VECTOR(cuts)[i]; printf("P: "); igraph_vector_print(v); igraph_vector_destroy(v); igraph_free(v); printf("C: "); igraph_vector_print(v2); igraph_vector_destroy(v2); igraph_free(v2); } igraph_vector_ptr_destroy(&partition1s); igraph_vector_ptr_destroy(&cuts); igraph_destroy(&g); /* ----------------------------------------------------------- */ igraph_small(&g, 7, IGRAPH_DIRECTED, 0, 1, 0, 2, 1, 3, 2, 3, 1, 4, 1, 5, 1, 6, 4, 2, 5, 2, 6, 2, -1); igraph_vector_ptr_init(&cuts, 0); igraph_vector_ptr_init(&partition1s, 0); igraph_all_st_cuts(&g, &cuts, &partition1s, /*source=*/ 0, /*target=*/ 3); n = igraph_vector_ptr_size(&partition1s); printf("Partitions and cuts:\n"); for (i = 0; i < n; i++) { igraph_vector_t *v = VECTOR(partition1s)[i]; igraph_vector_t *v2 = VECTOR(cuts)[i]; printf("P: "); igraph_vector_print(v); igraph_vector_destroy(v); igraph_free(v); printf("C: "); igraph_vector_print(v2); igraph_vector_destroy(v2); igraph_free(v2); } igraph_vector_ptr_destroy(&partition1s); igraph_vector_ptr_destroy(&cuts); /* Check whether it also works if we don't provide partition1s */ igraph_vector_ptr_init(&cuts, 0); igraph_vector_ptr_init(&partition1s, 0); igraph_all_st_cuts(&g, &cuts, /*partition1s=*/ 0, /*source=*/ 0, /*target=*/ 3); n = igraph_vector_ptr_size(&cuts); printf("Cuts only (no partitions):\n"); for (i = 0; i < n; i++) { igraph_vector_t *v2 = VECTOR(cuts)[i]; printf("C: "); igraph_vector_print(v2); igraph_vector_destroy(v2); igraph_free(v2); } igraph_vector_ptr_destroy(&partition1s); igraph_vector_ptr_destroy(&cuts); igraph_destroy(&g); /* ----------------------------------------------------------- * Check problematic cases in issue #1102 * ----------------------------------------------------------- */ igraph_small(&g, 4, IGRAPH_DIRECTED, 0, 1, 1, 2, 2, 3, -1); test_all_st_cuts(&g, 0, 2); igraph_destroy(&g); igraph_small(&g, 5, IGRAPH_DIRECTED, 0, 1, 1, 2, 2, 3, 3, 4, -1); test_all_st_cuts(&g, 0, 2); test_all_st_cuts(&g, 1, 3); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/graphml-hsa05010.xml0000644000076500000240000003711013524616144027241 0ustar tamasstaff00000000000000 hsa 05010 compound 1 cpd:C00027 C00027 compound 2 cpd:C00070 C00070... compound 2 cpd:C14818 C00070... gene 4 hsa:51107 APH1A Q96BI3 APH1A GO:0005515,GO:0016021,GO:0016485,GO:0043085 gene 6 hsa:4311 MME P08473 MME GO:0004245,GO:0016021,GO:0016787,GO:0008237,GO:0007267,GO:0006508,GO:0005887,GO:0005886,GO:0016020 gene 7 hsa:2932 GSK3B P49841 GSK3B GO:0016301,GO:0016740,GO:0005977,GO:0004696,GO:0005524,GO:0004674,GO:0006468,GO:0004672 gene 8 hsa:4137 MAPT gene 9 hsa:836 CASP3 P42574 CASP3 GO:0016787,GO:0008233,GO:0006917,GO:0030693,GO:0008234,GO:0006915,GO:0006508 gene 11 hsa:840 CASP7 P55210 CASP7 GO:0008233,GO:0016787,GO:0008632,GO:0008234,GO:0006915,GO:0005737,GO:0006508 gene 12 hsa:55851 PSENEN Q9NZ42 PEN2 gene 13 hsa:6622 SNCA P37840 SNCA GO:0005737,GO:0007417,GO:0006916 gene 14 hsa:5663 PSEN1... P49768 GO:0016021,GO:0007059,GO:0007001,GO:0006916,GO:0000776,GO:0000775,GO:0005639,GO:0005624,GO:0005783,GO:0007242 gene 14 hsa:5664 PSEN1... P49810 PSEN2 GO:0016021,GO:0008632,GO:0007059,GO:0007001,GO:0000776,GO:0005639,GO:0005783,GO:0007242 gene 15 hsa:836 CASP3 P42574 CASP3 GO:0016787,GO:0008233,GO:0006917,GO:0030693,GO:0008234,GO:0006915,GO:0006508 gene 16 hsa:23385 NCSTN Q92542 NCSTN GO:0016021,GO:0016485,GO:0006508 gene 17 hsa:2 A2M P01023 A2M GO:0017114,GO:0004866,GO:0051260,GO:0019899,GO:0008320,GO:0006886,GO:0004867 gene 18 hsa:3416 IDE P14735 IDE GO:0004231,GO:0016787,GO:0008237,GO:0007548,GO:0007267,GO:0007165,GO:0006508,GO:0005777,GO:0005625,GO:0005615,GO:0004871,GO:0003824,GO:0004222 gene 19 hsa:8883 APPBP1 Q13564 APPBP1 GO:0007165,GO:0005737,GO:0003824 gene 20 hsa:23621 BACE1... P56817 BACE1 GO:0004190,GO:0008233,GO:0009049,GO:0016021,GO:0016787,GO:0050435,GO:0005768,GO:0006508,GO:0005794,GO:0006509,GO:0008798,GO:0005887,GO:0004194 gene 20 hsa:25825 BACE1... Q9Y5Z0 GO:0004190,GO:0009049,GO:0016021,GO:0016787,GO:0009306,GO:0006464,GO:0005624,GO:0006508,GO:0004194 gene 22 hsa:351 APP, AD1 P05067 APP GO:0008201,GO:0007155,GO:0006915,GO:0005905,GO:0006897,GO:0016021,GO:0005515,GO:0005887,GO:0005576,GO:0004867 gene 23 hsa:2597 GAPDH, GAPD P04406 gene 24 hsa:348 APOE, AD2 P02649 APOE GO:0001540,GO:0008015,GO:0007271,GO:0005737,GO:0005319,GO:0008201,GO:0006869,GO:0008289 gene 25 hsa:322 APBB1, RIR O00213 APBB1 GO:0007165,GO:0001540,GO:0008134,GO:0045449,GO:0050821,GO:0005634,GO:0030308,GO:0045749,GO:0035035,GO:0007050,GO:0030048,GO:0045202,GO:0030027,GO:0030426,GO:0007409,GO:0050760 gene 26 hsa:4023 LPL P06858 LPL GO:0005319,GO:0004465,GO:0016787,GO:0016042,GO:0008201,GO:0008015,GO:0006631,GO:0005576,GO:0006629,GO:0003824 gene 27 hsa:4035 LRP1, APR, A2MR Q07954 LRP1 GO:0016021,GO:0004872,GO:0016020,GO:0008283,GO:0008034,GO:0006629,GO:0005887,GO:0005624,GO:0005509,GO:0005319,GO:0006897,GO:0005905 4.95265 0.693152 0.185704 0.670769 0.145403 0.05698 0.172033 0.00546283 2.93737 0.556617 0.176068 0.483953 0.50493 0.112413 0.111437 0.033196 0.145403 0.0605613 0.181454 0.00580618 -0 -0 0.171988 -0 7.8977 1 1 0.995807 9.64739 1 1 0.998753 2.93737 0.400174 0.136512 0.347932 3.5307 0.498171 0.123255 0.455066 4.0529 0.366988 0.0822633 0.344877 5.41325 1 1 0.976533 -0 -0 0.151863 -0 9.56439 1 1 0.998679 3.20433 0.383125 0.0883496 0.341558 0.145403 0.0605613 0.181454 0.00580618 10.0077 1 1 0.999029 0.50493 0.0888891 0.0880977 0.0262494 5.53428 1 1 0.978422 -0 -0 0.137908 -0 3.17114 0.346041 0.0972198 0.307624 2.60224 1 1 0.835317 -0 -0 0.137908 -0 python-igraph-0.8.0/vendor/source/igraph/examples/simple/pajek2.out0000644000076500000240000000003313524616144025625 0ustar tamasstaff000000000000000 0 0 0 0 0 0 0 1 1 1 1 1 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_eigen_matrix.c0000644000076500000240000001122113612122633030063 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { int nodes = 10; igraph_real_t triplets[] = { 1, 0, 1 / 4.0, 0, 1, 1 / 3.0, 2, 0, 1 / 4.0, 0, 2, 1 / 3.0, 3, 0, 1.0, 0, 3, 1 / 3.0, 4, 1, 1.0, 1, 4, 1 / 4.0, 5, 1, 1.0, 1, 5, 1 / 4.0, 6, 1, 1.0, 1, 6, 1 / 4.0, 7, 2, 1.0, 2, 7, 1 / 4.0, 8, 2, 1.0, 2, 8, 1 / 4.0, 9, 2, 1.0, 2, 9, 1 / 4.0 }; igraph_sparsemat_t mat; int i, n = sizeof(triplets) / sizeof(igraph_real_t); igraph_eigen_which_t which; igraph_vector_complex_t values, values2; igraph_matrix_complex_t vectors, vectors2; igraph_matrix_t mat2; igraph_sparsemat_init(&mat, nodes, nodes, n / 3); for (i = 0; i < n; i += 3) { igraph_sparsemat_entry(&mat, triplets[i], triplets[i + 1], triplets[i + 2]); } which.pos = IGRAPH_EIGEN_LM; which.howmany = 1; igraph_vector_complex_init(&values, 0); igraph_matrix_complex_init(&vectors, 0, 0); igraph_eigen_matrix(/*matrix=*/ 0, /*sparsemat=*/ &mat, /*fun=*/ 0, nodes, /*extra=*/ 0, IGRAPH_EIGEN_LAPACK, &which, /*options=*/ 0, /*storage=*/ 0, &values, &vectors); if (IGRAPH_REAL(MATRIX(vectors, 0, 0)) < 0) { igraph_matrix_complex_scale(&vectors, igraph_complex(-1.0, -0.0 )); } igraph_vector_complex_print(&values); igraph_matrix_complex_print(&vectors); igraph_sparsemat_destroy(&mat); /* Calcualate all eigenvalues, using SM and LM and then check that they are the same, in opposite order. We use a random matrix this time. */ igraph_rng_seed(igraph_rng_default(), 42); igraph_matrix_init(&mat2, nodes, nodes); for (i = 0; i < nodes; i++) { int j; for (j = 0; j < nodes; j++) { MATRIX(mat2, i, j) = igraph_rng_get_integer(igraph_rng_default(), 1, 10); } } which.pos = IGRAPH_EIGEN_LM; which.howmany = nodes; igraph_eigen_matrix(&mat2, /*sparsemat=*/ 0, /*fun=*/ 0, nodes, /*extra=*/ 0, IGRAPH_EIGEN_LAPACK, &which, /*options=*/ 0, /*storage=*/ 0, &values, &vectors); which.pos = IGRAPH_EIGEN_SM; which.howmany = nodes; igraph_vector_complex_init(&values2, 0); igraph_matrix_complex_init(&vectors2, 0, 0); igraph_eigen_matrix(&mat2, /*sparsemat=*/ 0, /*fun=*/ 0, nodes, /*extra=*/ 0, IGRAPH_EIGEN_LAPACK, &which, /*options=*/ 0, /*storage=*/ 0, &values2, &vectors2); #define DUMP() do { \ igraph_vector_complex_print(&values); \ igraph_vector_complex_print(&values2); \ } while(0) for (i = 0; i < nodes; i++) { int j; igraph_real_t d = igraph_complex_abs(igraph_complex_sub(VECTOR(values)[i], VECTOR(values2)[nodes - i - 1])); if (d > 1e-15) { DUMP(); return 2; } for (j = 0; j < nodes; j++) { igraph_real_t d = igraph_complex_abs(igraph_complex_sub(MATRIX(vectors, j, i), MATRIX(vectors2, j, nodes - i - 1))); if (d > 1e-15) { DUMP(); return 3; } } } igraph_vector_complex_destroy(&values); igraph_matrix_complex_destroy(&vectors); igraph_vector_complex_destroy(&values2); igraph_matrix_complex_destroy(&vectors2); igraph_matrix_destroy(&mat2); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_weighted_cliques.out0000644000076500000240000000363213524616144031340 0ustar tamasstaff0000000000000063 weighted cliques found above weight 6 0 7 w=6.0 0 8 w=8.0 0 9 w=8.0 1 3 w=7.0 1 8 w=7.0 1 9 w=7.0 2 3 w=8.0 2 5 w=6.0 2 7 w=6.0 2 9 w=8.0 3 5 w=8.0 3 6 w=6.0 3 7 w=8.0 3 9 w=10.0 4 9 w=7.0 5 8 w=8.0 6 8 w=6.0 7 8 w=8.0 8 9 w=10.0 0 1 6 w=6.0 0 1 7 w=8.0 0 1 8 w=10.0 0 1 9 w=10.0 0 6 7 w=7.0 0 6 8 w=9.0 0 7 8 w=11.0 0 8 9 w=13.0 1 2 3 w=10.0 1 2 6 w=6.0 1 2 7 w=8.0 1 2 9 w=10.0 1 3 6 w=8.0 1 3 7 w=10.0 1 3 9 w=12.0 1 4 7 w=7.0 1 4 9 w=9.0 1 6 7 w=6.0 1 6 8 w=8.0 1 7 8 w=10.0 1 8 9 w=12.0 2 3 5 w=11.0 2 3 6 w=9.0 2 3 7 w=11.0 2 3 9 w=13.0 2 6 7 w=7.0 3 6 7 w=9.0 4 6 7 w=6.0 6 7 8 w=9.0 0 1 6 7 w=9.0 0 1 6 8 w=11.0 0 1 7 8 w=13.0 0 1 8 9 w=15.0 0 6 7 8 w=12.0 1 2 3 6 w=11.0 1 2 3 7 w=13.0 1 2 3 9 w=15.0 1 2 6 7 w=9.0 1 3 6 7 w=11.0 1 4 6 7 w=8.0 1 6 7 8 w=11.0 2 3 6 7 w=12.0 0 1 6 7 8 w=14.0 1 2 3 6 7 w=14.0 53 weighted cliques found between weights 5 and 10 3 w=5.0 8 w=5.0 9 w=5.0 0 1 w=5.0 0 7 w=6.0 0 8 w=8.0 0 9 w=8.0 1 2 w=5.0 1 3 w=7.0 1 7 w=5.0 1 8 w=7.0 1 9 w=7.0 2 3 w=8.0 2 5 w=6.0 2 7 w=6.0 2 9 w=8.0 3 5 w=8.0 3 6 w=6.0 3 7 w=8.0 3 9 w=10.0 4 5 w=5.0 4 7 w=5.0 4 9 w=7.0 5 8 w=8.0 6 8 w=6.0 7 8 w=8.0 8 9 w=10.0 0 1 6 w=6.0 0 1 7 w=8.0 0 1 8 w=10.0 0 1 9 w=10.0 0 6 7 w=7.0 0 6 8 w=9.0 1 2 3 w=10.0 1 2 6 w=6.0 1 2 7 w=8.0 1 2 9 w=10.0 1 3 6 w=8.0 1 3 7 w=10.0 1 4 6 w=5.0 1 4 7 w=7.0 1 4 9 w=9.0 1 6 7 w=6.0 1 6 8 w=8.0 1 7 8 w=10.0 2 3 6 w=9.0 2 6 7 w=7.0 3 6 7 w=9.0 4 6 7 w=6.0 6 7 8 w=9.0 0 1 6 7 w=9.0 1 2 6 7 w=9.0 1 4 6 7 w=8.0 8 maximal weighted cliques found above weight 7 5 8 w=8.0 1 4 9 w=9.0 2 3 5 w=11.0 0 1 8 9 w=15.0 1 2 3 9 w=15.0 1 4 6 7 w=8.0 0 1 6 7 8 w=14.0 1 2 3 6 7 w=14.0 4 maximal weighted cliques found between weights 5 and 10 4 5 w=5.0 5 8 w=8.0 1 4 9 w=9.0 1 4 6 7 w=8.0 2 largest weight cliques found 0 1 8 9 w=15.0 1 2 3 9 w=15.0 weighted clique number: 15.0 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_sparsemat_is_symmetric.c0000644000076500000240000000363213612122634032206 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #define DIM 10 #define INT(a) (igraph_rng_get_integer(igraph_rng_default(), 0, (a))) int main() { int runs = 100; const int noelements = 20; igraph_sparsemat_t A; int i; igraph_rng_seed(igraph_rng_default(), 42); for (; runs > 0; runs--) { igraph_sparsemat_init(&A, DIM, DIM, noelements * 2); for (i = 0; i < noelements; i++) { int row = INT(DIM - 1); int col = INT(DIM - 1); int val = INT(100); igraph_sparsemat_entry(&A, row, col, val); igraph_sparsemat_entry(&A, col, row, val); } if (!igraph_sparsemat_is_symmetric(&A)) { return 1; } igraph_sparsemat_destroy(&A); igraph_sparsemat_init(&A, DIM, DIM, noelements); for (i = 0; i < noelements; i++) { igraph_sparsemat_entry(&A, INT(DIM - 1), INT(DIM - 1), INT(100)); } if (igraph_sparsemat_is_symmetric(&A)) { return 2; } igraph_sparsemat_destroy(&A); } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/edgelist5.dl0000644000076500000240000000020213524616144026124 0ustar tamasstaff00000000000000DL n=5 format = edgelist1 labels embedded: data: george sally 0.1 george jim 0.5 sally jim billy george 1 jane jim python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_eigen_matrix_symmetric.c0000644000076500000240000000776213612122633032176 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #define DIM 10 int check_ev(const igraph_matrix_t *A, const igraph_vector_t *values, const igraph_matrix_t *vectors) { int i, n = igraph_matrix_nrow(A); int ne = igraph_matrix_ncol(vectors); igraph_vector_t v, lhs, rhs; if (ne != igraph_vector_size(values)) { printf("'values' and 'vectors' sizes do not match\n"); exit(1); } igraph_vector_init(&lhs, n); igraph_vector_init(&rhs, n); for (i = 0; i < ne; i++) { igraph_vector_view(&v, &MATRIX(*vectors, 0, i), n); igraph_blas_dgemv(/*transpose=*/ 0, /*alpha=*/ 1, A, &v, /*beta=*/ 0, &lhs); igraph_vector_update(&rhs, &v); igraph_vector_scale(&rhs, VECTOR(*values)[i]); if (igraph_vector_maxdifference(&lhs, &rhs) > 1e-10) { printf("LHS: "); igraph_vector_print(&lhs); printf("RHS: "); igraph_vector_print(&rhs); exit(2); } } igraph_vector_destroy(&rhs); igraph_vector_destroy(&lhs); return 0; } int main() { igraph_matrix_t A; igraph_vector_t values; igraph_matrix_t vectors; int i, j; igraph_eigen_which_t which; igraph_rng_seed(igraph_rng_default(), 42 * 42); igraph_matrix_init(&A, DIM, DIM); igraph_matrix_init(&vectors, 0, 0); igraph_vector_init(&values, 0); /* All eigenvalues and eigenvectors */ for (i = 0; i < DIM; i++) { for (j = i; j < DIM; j++) { MATRIX(A, i, j) = MATRIX(A, j, i) = igraph_rng_get_integer(igraph_rng_default(), 1, 10); } } which.pos = IGRAPH_EIGEN_LM; which.howmany = 5; igraph_eigen_matrix_symmetric(&A, /*sA=*/ 0, /*fun=*/ 0, DIM, /*extra=*/ 0, IGRAPH_EIGEN_LAPACK, &which, /*options=*/ 0, /*storage=*/ 0, &values, &vectors); igraph_vector_print(&values); check_ev(&A, &values, &vectors); which.howmany = 8; igraph_eigen_matrix_symmetric(&A, /*sA=*/ 0, /*fun=*/ 0, DIM, /*extra=*/ 0, IGRAPH_EIGEN_LAPACK, &which, /*options=*/ 0, /*storage=*/ 0, &values, &vectors); igraph_vector_print(&values); check_ev(&A, &values, &vectors); which.pos = IGRAPH_EIGEN_BE; which.howmany = 5; igraph_eigen_matrix_symmetric(&A, /*sA=*/ 0, /*fun=*/ 0, DIM, /*extra=*/ 0, IGRAPH_EIGEN_LAPACK, &which, /*options=*/ 0, /*storage=*/ 0, &values, &vectors); igraph_vector_print(&values); check_ev(&A, &values, &vectors); which.pos = IGRAPH_EIGEN_SM; which.howmany = 5; igraph_eigen_matrix_symmetric(&A, /*sA=*/ 0, /*fun=*/ 0, DIM, /*extra=*/ 0, IGRAPH_EIGEN_LAPACK, &which, /*options=*/ 0, /*storage=*/ 0, &values, &vectors); igraph_vector_print(&values); check_ev(&A, &values, &vectors); igraph_vector_destroy(&values); igraph_matrix_destroy(&vectors); igraph_matrix_destroy(&A); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/random_seed.c0000644000076500000240000000272413612122634026347 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int main() { igraph_t g1, g2; igraph_bool_t iso; igraph_rng_seed(igraph_rng_default(), 1122); igraph_erdos_renyi_game(&g1, IGRAPH_ERDOS_RENYI_GNP, 100, 3.0 / 100, /*directed=*/ 0, /*loops=*/ 0); igraph_rng_seed(igraph_rng_default(), 1122); igraph_erdos_renyi_game(&g2, IGRAPH_ERDOS_RENYI_GNP, 100, 3.0 / 100, /*directed=*/ 0, /*loops=*/ 0); igraph_isomorphic(&g1, &g2, &iso); if (!iso) { return 1; } igraph_destroy(&g2); igraph_destroy(&g1); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_layout_merge2.out0000644000076500000240000000034013524616144030562 0ustar tamasstaff00000000000000-2.73912 -2.95429 -0.479512 -4.00008 1.96326 -3.51798 3.65613 -1.69214 3.95248 0.780051 2.73912 2.95429 0.479512 4.00008 -1.96326 3.51798 -3.65613 1.69214 -3.95248 -0.780051 -1.6061 6.30088 -4.92661 5.80435 -3.69637 8.92826 python-igraph-0.8.0/vendor/source/igraph/examples/simple/iso_b03_m1000.A000000644000076500000240000001161213524616144026242 0ustar tamasstaff00000000000000èÓ%·6·@iki­Çµ¸m =âÃD7‰]c ÷5h†GÜ„( oÛè%z³É8ö<dæ~AÿØ’y`­<¨Þ.¬¿ •Ø’öÇô3ú‡`5±¹@‰ÈvE~†Õ*÷ßô‰Â¤Ô3üÍ'=F "sÕÈ‹m}aï†R¹Œ fª.¤ÑY6Ãñƒoˆí+¸§7“oD¡£>{0ðÎsc‚QYó[ìCÙœ£ÇÅ>_V‹Ædÿ[,ê xÖ‚û„Ú×–µÂGSèÄ<˳‘J¸Z©¢°Ž¿Is›Ë«Ç3Àê°fcÌM¾¹¹ÂåAüͧïã­’Ž» ¤$±y¯š•Ù‚p±C óôTÉU-ljÊ¡~/Ì«:@tD¨Ðžf¹=r„¸1ÿúyž± Šx WÖ%ÞA&Á$¼üÒ0?ƒ1n>,˜×}…g™i{¤FsßHùÇ€ZéÚËÚˇM¯‡¾€á{r£8Š(^î6?ÜùthU³ð¡ã5aûžá—÷ÉN ~o†¬5û/3oXhµæM(§-æ‚à<`vϸ"u¢¸If᥮ö²&,B|š`ÀÞ Ò:-¨ ^-¤åXz™aºùÇ“²BQÍŽ»jÓ»ñöéªUmw@§ðsz›‰I1`Ù93ú{¾kv0=T–¸¨˜öÙ?/ ¥´Î•ŠòÇRæY!®‚øbu\ÓtdáeD¡Õ|ÑlTº@U-tkr mg™áf™„S—áÐz˜NÎJ‚å œ”“Ae´â2?UãDü`[,M*k y«(4 ÚqZ¶ùçïNm¼Ò×x’'5£ûcP}<Dqº¶à{ªu¥èÄPØýÚ8YóNGhÚ‰÷epë‡0µµ¸:ò n£ã—ä[š‘Õ¬’ò™Vb˜dåÔ|ªC‹;=†¥&J½;äîˆé¶uígïÔ‰4®ZéÕKyv[–•4%†^!ÑYiŠ@Á%)ÉÉ ³¨d¬î…é×CåØÌ«Îm‘–bÊÃÜÇ#ºç{܃©„Üg¢'Ðz7« jÞЛ µ5] *Î/[ˆ÷”6Z“x’Žmß  PŽšŒ¥åã¯1”ÖÎb̯xà[©²bNJ³BQž ¦†Á¯ÒqÂoç1°=jTŸ¨¶é+Xºá\P0;E^­ía²AS2>_2¬±"N܆ÃÜR¬*T®ÅÐ/Ež;n´*¦9@ÖùÈ}‡ ãºd-ƹIú"Ú» z!Ð.‹HƒŽÕkt&…[wq³ð"/,{Ö}ÿ¥´ÑY?ˆí7Ä™ 6xà’·EOêÌKȲšñH8ƒŒN{O[–Cegç± &  ex+$Ù^+s+ç5š“©)&ךþ†ÜT0­@ȇ/¤:¾E^ëæb©#‹«Tv•LÒ+Īê-eÅ PøÞWJ™âŒ#¥|¦ôwˆ³i$Í ö6ZÆÍËi4?Ï¿ÖQ >Ë$Ñ[W×PÝ=߽ů1‘U\VüÇ~½ß^É}¶…ÊŽèßhaÈêFÙê?¿Ïg?'K·}]iƒp¾±˜½å8GJŠ]•Õ|(ÏŸš(Ïf¦QúGo<èŒa)–’õrI&_“© 9 GX¬îzd¬4LY 6Bö” ë³Pº™®f£î˜ÛP$;N!æ­âð\Q÷Š©Å§±&:Z¶¡Rþa9 "Yò®Ÿ©õ¸ÃìDÆC¼Ó,mó^¦Í÷¾0J ‘j1 «ç{Ñ-©„o¢ò]cõFÈtý,,49O_w°G¨°Žr'4ß:Ó®7Äm}XŽ)Ê‘Þ4#Mл@Ÿn˜Ùï œ5ÿF¿Šü.A<\Z8‰F¿'=ë¨]E§¨)´ø¬£°ü[s.Uf»I®$–ïsºÁ•úv»7u3•Íܵt’ÿAIpython-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_difference.c0000644000076500000240000000737613614300625027523 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t orig, sub, diff; igraph_vector_t v; /* Subtract from itself */ printf("subtract itself\n"); igraph_vector_init_int_end(&v, -1, 0, 1, 1, 2, 2, 1, 4, 5, -1); igraph_create(&orig, &v, 0, IGRAPH_DIRECTED); igraph_vector_destroy(&v); igraph_difference(&diff, &orig, &orig); igraph_write_graph_edgelist(&diff, stdout); if (igraph_ecount(&diff) != 0 || igraph_vcount(&diff) != igraph_vcount(&orig)) { return 1; } igraph_destroy(&orig); igraph_destroy(&diff); /* Same for undirected graph */ printf("subtract itself, undirected\n"); igraph_vector_init_int_end(&v, -1, 0, 1, 1, 2, 2, 1, 4, 5, -1); igraph_create(&orig, &v, 0, IGRAPH_UNDIRECTED); igraph_vector_destroy(&v); igraph_vector_init_int_end(&v, -1, 1, 0, 1, 2, 2, 1, 4, 5, -1); igraph_create(&sub, &v, 0, IGRAPH_UNDIRECTED); igraph_vector_destroy(&v); igraph_difference(&diff, &orig, &sub); igraph_write_graph_edgelist(&diff, stdout); if (igraph_ecount(&diff) != 0 || igraph_vcount(&diff) != igraph_vcount(&orig)) { return 2; } igraph_destroy(&orig); igraph_destroy(&sub); igraph_destroy(&diff); /* Subtract the empty graph */ printf("subtract empty\n"); igraph_vector_init_int_end(&v, -1, 0, 1, 1, 2, 2, 1, 4, 5, -1); igraph_create(&orig, &v, 0, IGRAPH_DIRECTED); igraph_vector_destroy(&v); igraph_empty(&sub, 3, IGRAPH_DIRECTED); igraph_difference(&diff, &orig, &sub); igraph_write_graph_edgelist(&diff, stdout); if (igraph_ecount(&diff) != igraph_ecount(&orig) || igraph_vcount(&diff) != igraph_vcount(&orig)) { return 3; } igraph_destroy(&orig); igraph_destroy(&sub); igraph_destroy(&diff); /* A `real' example */ printf("real example\n"); igraph_vector_init_int_end(&v, -1, 0, 1, 1, 2, 2, 1, 4, 5, 8, 9, -1); igraph_create(&orig, &v, 0, IGRAPH_DIRECTED); igraph_vector_destroy(&v); igraph_vector_init_int_end(&v, -1, 0, 1, 5, 4, 2, 1, 6, 7, -1); igraph_create(&sub, &v, 0, IGRAPH_DIRECTED); igraph_vector_destroy(&v); igraph_difference(&diff, &orig, &sub); igraph_write_graph_edgelist(&diff, stdout); igraph_destroy(&diff); igraph_destroy(&orig); igraph_destroy(&sub); /* undirected version */ printf("real example, undirected\n"); igraph_vector_init_int_end(&v, -1, 0, 1, 1, 2, 2, 1, 4, 5, 8, 9, 8, 10, 8, 13, 8, 11, 8, 12, -1); igraph_create(&orig, &v, 0, IGRAPH_UNDIRECTED); igraph_vector_destroy(&v); igraph_vector_init_int_end(&v, -1, 0, 1, 5, 4, 2, 1, 6, 7, 8, 10, 8, 13, -1); igraph_create(&sub, &v, 0, IGRAPH_UNDIRECTED); igraph_vector_destroy(&v); igraph_difference(&diff, &orig, &sub); igraph_write_graph_edgelist(&diff, stdout); igraph_destroy(&diff); igraph_destroy(&orig); igraph_destroy(&sub); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/pajek1.net0000644000076500000240000000100413524616144025602 0ustar tamasstaff00000000000000*Vertices 10 1 "Vert 1" 0 0 box x_fact 1 y_fact 1 ic Green 2 "Vert 2" 0 0 box x_fact 1 y_fact 1 ic Green 3 "Vert 3" 0 0 box x_fact 1 y_fact 1 ic Green 4 "Vert 4" 0 0 box x_fact 1 y_fact 1 ic Green 5 "Vert 5" 0 0 box x_fact 1 y_fact 1 ic Green 6 "Vert 6" 0 0 box x_fact 1 y_fact 1 ic Blue 7 "Vert 7" 0 0 box x_fact 1 y_fact 1 ic Red 8 "Vert 8" 0 0 box x_fact 1 y_fact 1 ic Green 9 "Vert 9" 0 0 box x_fact 1 y_fact 1 ic Green 10 "Vert 10" 0 0 box x_fact 1 y_fact 1 ic Green *Edges 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_lapack_dgeev.c0000644000076500000240000001760013614300625030025 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include #define DIM 10 int real_cplx_mult(const igraph_matrix_t *A, const igraph_vector_t *v_real, const igraph_vector_t *v_imag, igraph_vector_t *res_real, igraph_vector_t *res_imag) { int n = igraph_vector_size(v_real); int r, c; if (igraph_matrix_nrow(A) != n || igraph_matrix_ncol(A) != n || igraph_vector_size(v_imag) != n) { printf("Wrong matrix or vector size"); return 1; } igraph_vector_resize(res_real, n); igraph_vector_resize(res_imag, n); for (r = 0; r < n; r++) { igraph_real_t s_real = 0.0; igraph_real_t s_imag = 0.0; for (c = 0; c < n; c++) { s_real += MATRIX(*A, r, c) * VECTOR(*v_real)[c]; s_imag += MATRIX(*A, r, c) * VECTOR(*v_imag)[c]; } VECTOR(*res_real)[r] = s_real; VECTOR(*res_imag)[r] = s_imag; } return 0; } int sc_cplx_cplx_mult(igraph_real_t lambda_real, igraph_real_t lambda_imag, const igraph_vector_t *v_real, const igraph_vector_t *v_imag, igraph_vector_t *res_real, igraph_vector_t *res_imag) { int r; int n = igraph_vector_size(v_real); if (igraph_vector_size(v_imag) != n) { printf("Wrong vector sizes"); return 1; } igraph_vector_resize(res_real, n); igraph_vector_resize(res_imag, n); for (r = 0; r < n; r++) { VECTOR(*res_real)[r] = (lambda_real * VECTOR(*v_real)[r] - lambda_imag * VECTOR(*v_imag)[r]); VECTOR(*res_imag)[r] = (lambda_imag * VECTOR(*v_real)[r] + lambda_real * VECTOR(*v_imag)[r]); } return 0; } igraph_bool_t check_ev(const igraph_matrix_t *A, const igraph_vector_t *values_real, const igraph_vector_t *values_imag, const igraph_matrix_t *vectors_left, const igraph_matrix_t *vectors_right, igraph_real_t tol) { int i, n = igraph_matrix_nrow(A); igraph_vector_t v_real, v_imag; igraph_vector_t AV_real, AV_imag, lv_real, lv_imag; igraph_vector_t null; if (igraph_matrix_ncol(A) != n) { return 1; } if (igraph_vector_size(values_real) != n) { return 1; } if (igraph_vector_size(values_imag) != n) { return 1; } if (igraph_matrix_nrow(vectors_left) != n) { return 1; } if (igraph_matrix_ncol(vectors_left) != n) { return 1; } if (igraph_matrix_nrow(vectors_right) != n) { return 1; } if (igraph_matrix_ncol(vectors_right) != n) { return 1; } igraph_vector_init(&AV_real, n); igraph_vector_init(&AV_imag, n); igraph_vector_init(&lv_real, n); igraph_vector_init(&lv_imag, n); igraph_vector_init(&null, n); igraph_vector_null(&null); for (i = 0; i < n; i++) { if (VECTOR(*values_imag)[i] == 0.0) { igraph_vector_view(&v_real, &MATRIX(*vectors_right, 0, i), n); igraph_vector_view(&v_imag, VECTOR(null), n); } else if (VECTOR(*values_imag)[i] > 0.0) { igraph_vector_view(&v_real, &MATRIX(*vectors_right, 0, i), n); igraph_vector_view(&v_imag, &MATRIX(*vectors_right, 0, i + 1), n); } else if (VECTOR(*values_imag)[i] < 0.0) { igraph_vector_view(&v_real, &MATRIX(*vectors_right, 0, i - 1), n); igraph_vector_view(&v_imag, &MATRIX(*vectors_right, 0, i), n); igraph_vector_scale(&v_imag, -1.0); } real_cplx_mult(A, &v_real, &v_imag, &AV_real, &AV_imag); sc_cplx_cplx_mult(VECTOR(*values_real)[i], VECTOR(*values_imag)[i], &v_real, &v_imag, &lv_real, &lv_imag); if (igraph_vector_maxdifference(&AV_real, &lv_real) > tol || igraph_vector_maxdifference(&AV_imag, &lv_imag) > tol) { printf("ERROR:\n"); igraph_vector_print(&AV_real); igraph_vector_print(&AV_imag); igraph_vector_print(&lv_real); igraph_vector_print(&lv_imag); return 1; } } igraph_vector_destroy(&null); igraph_vector_destroy(&AV_imag); igraph_vector_destroy(&AV_real); igraph_vector_destroy(&lv_imag); igraph_vector_destroy(&lv_real); return 0; } int main() { igraph_matrix_t A; igraph_matrix_t vectors_left, vectors_right; igraph_vector_t values_real, values_imag; int i, j; int info = 1; igraph_rng_seed(igraph_rng_default(), 42); igraph_matrix_init(&A, DIM, DIM); igraph_matrix_init(&vectors_left, 0, 0); igraph_matrix_init(&vectors_right, 0, 0); igraph_vector_init(&values_real, 0); igraph_vector_init(&values_imag, 0); for (i = 0; i < DIM; i++) { for (j = 0; j < DIM; j++) { MATRIX(A, i, j) = igraph_rng_get_integer(igraph_rng_default(), 1, 10); } } igraph_lapack_dgeev(&A, &values_real, &values_imag, &vectors_left, &vectors_right, &info); if (check_ev(&A, &values_real, &values_imag, &vectors_left, &vectors_right, /*tol=*/ 1e-8)) { return 1; } /* ------------------------------------------------------- */ /* igraph_matrix_resize(&A, 10, 10); */ /* igraph_matrix_null(&A); */ /* for (i=0; i<10; i++) { MATRIX(A, i, i) = 1.0; } */ /* MATRIX(A,0,1) = 1.0; */ /* igraph_lapack_dgeev(&A, &values_real, &values_imag, */ /* &vectors_left, &vectors_right, &info); */ /* if (check_ev(&A, &values_real, &values_imag, */ /* &vectors_left, &vectors_right, /\*tol=*\/ 1e-8)) { */ /* return 2; */ /* } */ /* ------------------------------------------------------- */ igraph_matrix_resize(&A, 10, 10); igraph_matrix_null(&A); MATRIX(A, 0, 1) = MATRIX(A, 0, 2) = MATRIX(A, 0, 3) = 1 / 3.0; MATRIX(A, 1, 0) = MATRIX(A, 1, 4) = MATRIX(A, 1, 5) = MATRIX(A, 1, 6) = 1 / 4.0; MATRIX(A, 2, 0) = MATRIX(A, 2, 7) = MATRIX(A, 2, 8) = MATRIX(A, 2, 9) = 1 / 4.0; MATRIX(A, 3, 0) = 1.0; MATRIX(A, 4, 1) = 1.0; MATRIX(A, 5, 1) = 1.0; MATRIX(A, 6, 1) = 1.0; MATRIX(A, 7, 2) = 1.0; MATRIX(A, 8, 2) = 1.0; MATRIX(A, 9, 2) = 1.0; info = 0; igraph_lapack_dgeev(&A, &values_real, &values_imag, &vectors_left, &vectors_right, &info); /* igraph_matrix_print(&A); */ /* printf("---\n"); */ /* igraph_vector_print(&values_real); */ /* igraph_vector_print(&values_imag); */ /* igraph_matrix_print(&vectors_left); */ if (check_ev(&A, &values_real, &values_imag, &vectors_left, &vectors_right, /*tol=*/ 1e-8)) { return 3; } igraph_vector_destroy(&values_imag); igraph_vector_destroy(&values_real); igraph_matrix_destroy(&vectors_right); igraph_matrix_destroy(&vectors_left); igraph_matrix_destroy(&A); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/input.dl0000644000076500000240000000141713524616144025407 0ustar tamasstaff00000000000000DL n=66 format = edgelist1 labels embedded: data: R1 C1 R1 C5 R1 C7 R1 C9 R1 C11 R1 C12 R1 C13 R1 C16 R1 C17 R1 C23 R1 C24 R1 C25 R1 C28 R2 C8 R2 C11 R2 C12 R2 C17 R2 C20 R2 C24 R2 C26 R2 C27 R2 C28 R3 C2 R3 C3 R4 C17 R4 C23 R5 C6 R5 C13 R5 C19 R5 C22 R5 C24 R6 C14 R7 C17 R7 C22 R7 C26 R8 C1 R8 C17 R8 C19 R8 C22 R9 C19 R9 C22 R9 C23 R10 C6 R10 C18 R10 C28 R11 C25 R12 C25 R13 C13 R13 C19 R14 C1 R14 C4 R14 C21 R15 C15 R15 C17 R16 C17 R16 C23 R17 C4 R18 C28 R19 C6 R20 C17 R21 C28 R22 C4 R23 C6 R23 C17 R24 C11 R25 C4 R26 C16 R26 C20 R27 C1 R27 C2 R27 C5 R27 C17 R28 C13 R28 C20 R28 C21 R29 C12 R30 C1 R30 C2 R30 C22 R31 C10 R31 C13 R31 C15 R32 C6 R32 C22 R32 C28 R33 C14 R33 C23 R34 C3 R34 C28 R35 C28 R36 C13 R36 C20 R36 C27 R36 C28 R37 C28 R38 C8 R38 C10 R38 C13 R38 C14 R38 C23 python-igraph-0.8.0/vendor/source/igraph/examples/simple/tls2.c0000644000076500000240000001635313612122634024756 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard street, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include #include #include "igraph_arpack_internal.h" /* Test whether ARPACK is thread-safe. We will create two threads, each calling a different ARPACK eigensolver. We will make sure that the ARPACK calls from the two threads overlap */ typedef struct thread_data_t { igraph_matrix_t *m; igraph_vector_t *result; pthread_cond_t *cond; pthread_mutex_t *mutex; int *steps, *othersteps; } thread_data_t; int arpack_mult(igraph_real_t *to, igraph_real_t *from, int n, igraph_matrix_t *matrix) { /* TODO */ igraph_blas_dgemv_array(/*transpose=*/ 0, /*alpha=*/ 1.0, matrix, from, /*beta=*/ 0.0, to); return 0; } /* This is the function performed by each thread. It calles the low-level ARPACK symmetric eigensolver, step by step. After each step, it synchronizes with the other thread. The synchronization ensures that the two threads are using the thread-local variables at the same time. If they are really thread-local, then ARPACK still delivers the correct solution for the two matrices. Otherwise the result is undefined: maybe results will be incorrect, or the program will crash. This function is basically a simplified copy of igraph_arpack_rssolve. */ void *thread_function(void *arg) { thread_data_t *data = (thread_data_t*) arg; igraph_matrix_t *M = data->m; igraph_vector_t *result = data->result; pthread_cond_t *cond = data->cond; pthread_mutex_t *mutex = data->mutex; igraph_arpack_options_t options; igraph_real_t *v, *workl, *workd, *d, *resid, *ax; int *select; int ido = 0; #if IGRAPH_THREAD_SAFE int rvec = 1; char *all = "All"; #endif int i; igraph_arpack_options_init(&options); options.n = igraph_matrix_nrow(M); options.ldv = options.n; options.nev = 1; options.ncv = 3; options.lworkl = options.ncv * (options.ncv + 8); options.which[0] = 'L'; options.which[1] = 'M'; options.iparam[0] = options.ishift; options.iparam[2] = options.mxiter; options.iparam[3] = options.nb; options.iparam[4] = 0; options.iparam[6] = options.mode; options.info = options.start; v = igraph_Calloc(options.ldv * options.ncv, igraph_real_t); workl = igraph_Calloc(options.lworkl, igraph_real_t); workd = igraph_Calloc(3 * options.n, igraph_real_t); d = igraph_Calloc(2 * options.ncv, igraph_real_t); resid = igraph_Calloc(options.n, igraph_real_t); ax = igraph_Calloc(options.n, igraph_real_t); select = igraph_Calloc(options.ncv, int); if (!v || !workl || !workd || !d || !resid || !ax || !select) { printf("Out of memory\n"); return 0; } while (1) { #if IGRAPH_THREAD_SAFE igraphdsaupd_(&ido, options.bmat, &options.n, options.which, &options.nev, &options.tol, resid, &options.ncv, v, &options.ldv, options.iparam, options.ipntr, workd, workl, &options.lworkl, &options.info); #endif if (ido == -1 || ido == 1) { igraph_real_t *from = workd + options.ipntr[0] - 1; igraph_real_t *to = workd + options.ipntr[1] - 1; arpack_mult(to, from, options.n, M); } else { break; } pthread_mutex_lock(mutex); *(data->steps) += 1; if ( *(data->othersteps) == *(data->steps) ) { pthread_cond_signal(cond); } while ( *(data->othersteps) < * (data->steps) && *(data->othersteps) != -1 ) { pthread_cond_wait(cond, mutex); } pthread_mutex_unlock(mutex); } pthread_mutex_lock(mutex); *data->steps = -1; pthread_cond_signal(cond); pthread_mutex_unlock(mutex); if (options.info != 0) { printf("ARPACK error\n"); return 0; } #if IGRAPH_THREAD_SAFE igraphdseupd_(&rvec, all, select, d, v, &options.ldv, &options.sigma, options.bmat, &options.n, options.which, &options.nev, &options.tol, resid, &options.ncv, v, &options.ldv, options.iparam, options.ipntr, workd, workl, &options.lworkl, &options.ierr); #endif if (options.ierr != 0) { printf("ARPACK error\n"); return 0; } igraph_vector_resize(result, options.n); for (i = 0; i < options.n; i++) { VECTOR(*result)[i] = v[i]; } free(v); free(workl); free(workd); free(d); free(resid); free(ax); free(select); return 0; } int main() { pthread_t thread_id1, thread_id2; void *exit_status1, *exit_status2; igraph_matrix_t m1, m2; igraph_vector_t result1, result2; pthread_cond_t steps_cond = PTHREAD_COND_INITIALIZER; pthread_mutex_t steps_mutex = PTHREAD_MUTEX_INITIALIZER; int steps1 = 0, steps2 = 0; thread_data_t data1 = { &m1, &result1, &steps_cond, &steps_mutex, &steps1, &steps2 }, data2 = { &m2, &result2, &steps_cond, &steps_mutex, &steps2, &steps1 }; int i, j; /* Skip if igraph is not thread safe */ if (!IGRAPH_THREAD_SAFE) { return 77; } igraph_matrix_init(&m1, 10, 10); igraph_matrix_init(&m2, 10, 10); igraph_vector_init(&result1, igraph_matrix_nrow(&m1)); igraph_vector_init(&result2, igraph_matrix_nrow(&m2)); igraph_rng_seed(igraph_rng_default(), 42); for (i = 0; i < igraph_matrix_nrow(&m1); i++) { for (j = 0; j <= i; j++) { MATRIX(m1, i, j) = MATRIX(m1, j, i) = igraph_rng_get_integer(igraph_rng_default(), 0, 10); } } for (i = 0; i < igraph_matrix_nrow(&m2); i++) { for (j = 0; j <= i; j++) { MATRIX(m2, i, j) = MATRIX(m2, j, i) = igraph_rng_get_integer(igraph_rng_default(), 0, 10); } } pthread_create(&thread_id1, NULL, thread_function, (void *) &data1); pthread_create(&thread_id2, NULL, thread_function, (void *) &data2); pthread_join(thread_id1, &exit_status1); pthread_join(thread_id2, &exit_status2); igraph_matrix_print(&m1); igraph_vector_print(&result1); printf("---\n"); igraph_matrix_print(&m2); igraph_vector_print(&result2); igraph_vector_destroy(&result1); igraph_vector_destroy(&result2); igraph_matrix_destroy(&m1); igraph_matrix_destroy(&m2); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_arpack_rnsolve.c0000644000076500000240000001460513612122633030432 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include typedef struct cb2_data_t { igraph_matrix_t *A; } cb2_data_t; int cb2(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { cb2_data_t *data = (cb2_data_t*) extra; igraph_blas_dgemv_array(/*transpose=*/ 0, /*alpha=*/ 1.0, data->A, from, /*beta=*/ 0.0, to); return 0; } int check_eigenvector( const char* test_name, igraph_matrix_t* A, igraph_matrix_t* values, igraph_matrix_t* vectors, int eval_idx, int evec_col_idx ) { igraph_complex_t eval, prod; igraph_complex_t *evec; int i, j, n = igraph_matrix_nrow(A); eval = igraph_complex(MATRIX(*values, eval_idx, 0), MATRIX(*values, eval_idx, 1)); evec = (igraph_complex_t*) calloc(n, sizeof(igraph_complex_t)); if (IGRAPH_IMAG(eval) == 0) { /* Real eigenvalue, so we have a real eigenvector */ for (i = 0; i < n; i++) { evec[i] = igraph_complex(MATRIX(*vectors, i, evec_col_idx), 0); } } else { /* Complex eigenvalue pair, so we have a complex eigenvector pair */ /* ARPACK always stores the eigenvector corresponding to the eigenvalue * with a positive imaginary part. If the imaginary part is negative, we * need to multiply the imaginary part of the eigenvector by -1 */ for (i = 0; i < n; i++) { evec[i] = igraph_complex( MATRIX(*vectors, i, evec_col_idx), MATRIX(*vectors, i, evec_col_idx + 1) * ( IGRAPH_IMAG(eval) < 0 ? -1 : 1 ) ); } } /* Multiply matrix with eigenvector */ for (i = 0; i < n; i++) { prod = igraph_complex(0, 0); for (j = 0; j < n; j++) { prod = igraph_complex_add( igraph_complex_mul_real(evec[j], MATRIX(*A, i, j)), prod ); } prod = igraph_complex_div(prod, eval); if (!igraph_complex_eq_tol(prod, evec[i], 1e-6)) { prod = igraph_complex_sub(prod, evec[i]); printf("%s: vector corresponding to eigenvalue (%.4f + %.4f*i) is not an " "eigenvector, coordinate %d differs by %.4f + %.4f*i\n", test_name, IGRAPH_REAL(eval), IGRAPH_IMAG(eval), i, IGRAPH_REAL(prod), IGRAPH_IMAG(prod)); return 1; } } /* Free stuff */ free(evec); return 0; } int check_eigenvectors( const char* test_name, igraph_matrix_t* A, igraph_matrix_t* values, igraph_matrix_t* vectors ) { int i, j; int nev = igraph_matrix_nrow(values); int errors = 0; igraph_bool_t conjugate_pair_will_come = 0; for (i = 0, j = 0; i < nev; i++) { errors += check_eigenvector(test_name, A, values, vectors, i, j); if (MATRIX(*values, i, 1) != 0) { /* Complex eigenvalue */ if (conjugate_pair_will_come) { j += 2; conjugate_pair_will_come = 0; } else { conjugate_pair_will_come = 1; } } else { /* Real eigenvalue */ j++; } } return (errors > 0) ? 1 : 0; } void print_debug_output( igraph_matrix_t* values, igraph_matrix_t* vectors ) { printf("---\n"); igraph_matrix_print(values); printf("---\n"); igraph_matrix_print(vectors); printf("---\n"); } #define DIM 10 int main() { igraph_matrix_t A; igraph_matrix_t values, vectors; igraph_arpack_options_t options; cb2_data_t data = { &A }; int i, j; igraph_rng_seed(igraph_rng_default(), 42 * 42); igraph_matrix_init(&A, DIM, DIM); for (i = 0; i < DIM; i++) { for (j = 0; j < DIM; j++) { MATRIX(A, i, j) = igraph_rng_get_integer(igraph_rng_default(), -10, 10); } } igraph_matrix_print(&A); printf("===\n"); igraph_arpack_options_init(&options); options.n = DIM; options.start = 0; options.nev = 4; options.ncv = 9; options.which[0] = 'L' ; options.which[1] = 'M'; igraph_matrix_init(&values, 0, 0); igraph_matrix_init(&vectors, options.n, 1); igraph_arpack_rnsolve(cb2, /*extra=*/ &data, &options, /*storage=*/ 0, &values, &vectors); if (check_eigenvectors("LM #1", &A, &values, &vectors)) { print_debug_output(&values, &vectors); } /* -------------- */ options.nev = 3; options.which[0] = 'L' ; options.which[1] = 'M'; igraph_arpack_rnsolve(cb2, /*extra=*/ &data, &options, /*storage=*/ 0, &values, &vectors); if (check_eigenvectors("LM #2", &A, &values, &vectors)) { print_debug_output(&values, &vectors); } /* -------------- */ options.nev = 3; options.which[0] = 'S' ; options.which[1] = 'R'; igraph_arpack_rnsolve(cb2, /*extra=*/ &data, &options, /*storage=*/ 0, &values, &vectors); if (check_eigenvectors("SR", &A, &values, &vectors)) { print_debug_output(&values, &vectors); } /* -------------- */ options.nev = 3; options.which[0] = 'L' ; options.which[1] = 'I'; igraph_arpack_rnsolve(cb2, /*extra=*/ &data, &options, /*storage=*/ 0, &values, &vectors); if (check_eigenvectors("LI", &A, &values, &vectors)) { print_debug_output(&values, &vectors); } /* -------------- */ igraph_matrix_destroy(&values); igraph_matrix_destroy(&vectors); igraph_matrix_destroy(&A); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_intersection2.out0000644000076500000240000000014713524616144030601 0ustar tamasstaff000000000000000 10 1 10 2 10 3 10 4 10 5 10 6 10 7 10 8 10 9 10 -- 0 10 1 10 2 10 3 10 4 10 5 10 6 10 7 10 8 10 9 10 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_feedback_arc_set_ip.out0000644000076500000240000000002613524616144031721 0ustar tamasstaff000000000000001 1 1 9 10 1 9 10 12 python-igraph-0.8.0/vendor/source/igraph/examples/simple/pajek_bipartite.c0000644000076500000240000000260313612122634027220 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t graph; igraph_vector_bool_t type; igraph_bool_t typev[] = { 0, 1, 0, 1, 0, 1, 0, 1, 0, 1 }; /* turn on attribute handling */ igraph_i_set_attribute_table(&igraph_cattribute_table); igraph_ring(&graph, 10, IGRAPH_UNDIRECTED, /*mutual=*/ 0, /*circular=*/ 1); igraph_vector_bool_view(&type, typev, sizeof(typev) / sizeof(igraph_bool_t)); SETVABV(&graph, "type", &type); igraph_write_graph_pajek(&graph, stdout); igraph_destroy(&graph); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/scg2.c0000644000076500000240000001061313612122634024721 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_vector_t ev; igraph_t scg_graph; igraph_matrix_t scg_matrix; igraph_sparsemat_t scg_sparsemat; igraph_matrix_t L, R; igraph_sparsemat_t Lsparse, Rsparse; igraph_vector_t p; igraph_vector_t groups; igraph_vector_complex_t eval; igraph_matrix_complex_t evec; igraph_tree(&g, 10, /* children= */ 3, IGRAPH_TREE_UNDIRECTED); igraph_vector_init(&ev, 1); igraph_matrix_init(&L, 0, 0); igraph_matrix_init(&R, 0, 0); igraph_matrix_init(&scg_matrix, 0, 0); igraph_vector_init(&p, 0); igraph_vector_init(&groups, 0); igraph_vector_complex_init(&eval, 0); igraph_matrix_complex_init(&evec, 0, 0); #define CALLSTO() do { \ igraph_vector_resize(&p, 0); \ igraph_vector_resize(&groups, 0); \ igraph_vector_complex_resize(&eval, 0); \ igraph_matrix_complex_resize(&evec, 0, 0); \ igraph_scg_stochastic(&g, /*matrix=*/ 0, /*sparsemat=*/ 0, &ev, \ /* intervals= */ 2, /* intervals_vector= */ 0, \ /* algorithm= */ IGRAPH_SCG_EXACT, \ IGRAPH_SCG_NORM_ROW, &eval, &evec, \ &groups, &p, /* use_arpack= */ 0, \ /* maxiter= */ 0, &scg_graph, &scg_matrix, \ &scg_sparsemat, &L, &R, \ &Lsparse, &Rsparse); \ } while (0) #define PRINTRES() \ do { \ printf("--------------------------------\n"); \ igraph_vector_print(&groups); \ printf("---\n"); \ igraph_vector_complex_print(&eval); \ igraph_matrix_complex_print(&evec); \ printf("---\n"); \ igraph_write_graph_edgelist(&scg_graph, stdout); \ printf("---\n"); \ igraph_sparsemat_print(&scg_sparsemat, stdout); \ printf("---\n"); \ igraph_sparsemat_print(&Lsparse, stdout); \ printf("---\n"); \ igraph_sparsemat_print(&Rsparse, stdout); \ printf("---\n"); \ } while (0) VECTOR(ev)[0] = 1; CALLSTO(); PRINTRES(); igraph_destroy(&scg_graph); igraph_sparsemat_destroy(&scg_sparsemat); igraph_sparsemat_destroy(&Lsparse); igraph_sparsemat_destroy(&Rsparse); VECTOR(ev)[0] = 3; CALLSTO(); PRINTRES(); igraph_destroy(&scg_graph); igraph_sparsemat_destroy(&scg_sparsemat); igraph_sparsemat_destroy(&Lsparse); igraph_sparsemat_destroy(&Rsparse); igraph_vector_resize(&ev, 2); VECTOR(ev)[0] = 1; VECTOR(ev)[1] = 3; CALLSTO(); PRINTRES(); igraph_destroy(&scg_graph); igraph_sparsemat_destroy(&scg_sparsemat); igraph_sparsemat_destroy(&Lsparse); igraph_sparsemat_destroy(&Rsparse); igraph_matrix_complex_destroy(&evec); igraph_vector_complex_destroy(&eval); igraph_vector_destroy(&groups); igraph_vector_destroy(&p); igraph_matrix_destroy(&scg_matrix); igraph_matrix_destroy(&L); igraph_matrix_destroy(&R); igraph_vector_destroy(&ev); igraph_destroy(&g); /* -------------------------------------------------------------------- */ return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_is_loop.c0000644000076500000240000000327713612122633027070 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void print_vector(igraph_vector_bool_t *v, FILE *f) { long int i; for (i = 0; i < igraph_vector_bool_size(v); i++) { fprintf(f, " %i", (int) VECTOR(*v)[i]); } fprintf(f, "\n"); } int main() { igraph_t graph; igraph_vector_bool_t v; igraph_vector_bool_init(&v, 0); igraph_small(&graph, 0, IGRAPH_DIRECTED, 0, 1, 1, 2, 2, 1, 0, 1, 1, 0, 3, 4, 11, 10, -1); igraph_is_loop(&graph, &v, igraph_ess_all(IGRAPH_EDGEORDER_ID)); print_vector(&v, stdout); igraph_destroy(&graph); igraph_small(&graph, 0, IGRAPH_UNDIRECTED, 0, 0, 1, 1, 2, 2, 2, 3, 2, 4, 2, 5, 2, 6, 2, 2, 0, 0, -1); igraph_is_loop(&graph, &v, igraph_ess_all(IGRAPH_EDGEORDER_ID)); print_vector(&v, stdout); igraph_destroy(&graph); igraph_vector_bool_destroy(&v); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/lineendings.out0000644000076500000240000000042013524616144026750 0ustar tamasstaff00000000000000*Vertices 10 *Edges 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 *Vertices 10 *Edges 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 *Vertices 10 *Edges 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 *Vertices 10 *Edges 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_vs_seq.out0000644000076500000240000000002713524616144027306 0ustar tamasstaff0000000000000010 0 1 2 3 4 5 6 7 8 9 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_version.c0000644000076500000240000000226413612122634027105 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int main() { char tmp[100]; const char *string; int major, minor, subminor; igraph_version(&string, &major, &minor, &subminor); sprintf(tmp, "%i.%i.%i", major, minor, subminor); if (strncmp(string, tmp, strlen(tmp))) { return 1; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_convex_hull.c0000644000076500000240000001255013612122633027744 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int check_convex_hull(igraph_matrix_t* coords) { igraph_vector_t result; igraph_matrix_t resmat; long int i; /* Testing with index output mode */ igraph_vector_init(&result, 1); if (igraph_convex_hull(coords, &result, 0)) { return 1; } for (i = 0; i < igraph_vector_size(&result); i++) { printf("%ld ", (long)VECTOR(result)[i]); } printf("\n"); igraph_vector_destroy(&result); /* Testing with coordinate output mode */ igraph_matrix_init(&resmat, 0, 0); if (igraph_convex_hull(coords, 0, &resmat)) { return 1; } for (i = 0; i < igraph_matrix_nrow(&resmat); i++) { printf("%.3f %.3f ", MATRIX(resmat, i, 0), MATRIX(resmat, i, 1)); } printf("\n"); igraph_matrix_destroy(&resmat); return 0; } int test_simple() { igraph_real_t coords_array[][2] = { {3, 2}, {5, 1}, {4, 4}, {6, 4}, {4, 3}, {2, 5}, {1, 3}, {2, 4}, {6, 3}, {9, 2} }; igraph_matrix_t coords; int i, result; printf("test_simple\n"); igraph_matrix_init(&coords, 10, 2); for (i = 0; i < 20; i++) { MATRIX(coords, i / 2, i % 2) = coords_array[i / 2][i % 2]; } result = check_convex_hull(&coords); igraph_matrix_destroy(&coords); return result; } int test_collinear() { igraph_real_t coords_array[][2] = {{3, 2}, {5, 1}, {7, 0}, {9, -1}, {11, -2}}; igraph_matrix_t coords; int i, result; printf("test_collinear\n"); igraph_matrix_init(&coords, 5, 2); for (i = 0; i < 10; i++) { MATRIX(coords, i / 2, i % 2) = coords_array[i / 2][i % 2]; } result = check_convex_hull(&coords); igraph_matrix_destroy(&coords); return result; } int test_degenerate() { igraph_matrix_t coords; int result; printf("test_degenerate\n"); igraph_matrix_init(&coords, 2, 2); MATRIX(coords, 0, 0) = 3; MATRIX(coords, 0, 1) = 2; MATRIX(coords, 1, 0) = 5; MATRIX(coords, 1, 1) = 1; result = check_convex_hull(&coords); igraph_matrix_resize(&coords, 1, 2); MATRIX(coords, 0, 0) = 3; MATRIX(coords, 0, 1) = 2; result = check_convex_hull(&coords); igraph_matrix_resize(&coords, 0, 2); result = check_convex_hull(&coords); igraph_matrix_destroy(&coords); return result; } int test_bug_805() { igraph_real_t coords_array[][2] = { {0, 0}, {1, 0}, {0.707, 0.707}, {0, 1}, {-0.707, 0.707}, {-1, 0}, {-0.707, -0.707}, {0, -1}, {0.707, -0.707}, {2, 0}, {1.414, 1.414}, {0, 2}, {-1.414, 1.414}, {-2, 0}, {-1.414, -1.414}, {0, -2}, {1.414, -1.414}, {3, 0}, {2.121, 2.121}, {0, 3}, {-2.121, 2.121}, {-3, 0}, {-2.121, -2.121}, {0, -3}, {2.121, -2.121}, {4, 0}, {2.828, 2.828}, {0, 4}, {-2.828, 2.828}, {-4, 0}, {-2.828, -2.828}, {0, -4}, {2.828, -2.828} }; igraph_matrix_t coords; int i, result; printf("test_bug_805\n"); igraph_matrix_init(&coords, 33, 2); for (i = 0; i < 66; i++) { MATRIX(coords, i / 2, i % 2) = coords_array[i / 2][i % 2]; } result = check_convex_hull(&coords); igraph_matrix_destroy(&coords); return result; } int test_bug_1115() { igraph_real_t coords_array[][2] = { {37, 52}, {49, 49}, {52, 64}, {20, 26}, {40, 30}, {21, 47}, {17, 63}, {31, 62}, {52, 33}, {51, 21}, {42, 41}, {31, 32}, {5, 25}, {12, 42}, {36, 16}, {52, 41}, {27, 23}, {17, 33}, {13, 13}, {57, 58}, {62, 42}, {42, 57}, {16, 57}, {8, 52}, {7, 38}, {27, 68}, {30, 48}, {43, 67}, {58, 48}, {58, 27}, {37, 69}, {38, 46}, {46, 10}, {61, 33}, {62, 63}, {63, 69}, {32, 22}, {45, 35}, {59, 15}, {5, 6}, {10, 17}, {21, 10}, {5, 64}, {30, 15}, {39, 10}, {32, 39}, {25, 32}, {25, 55}, {48, 28}, {56, 37}, {30, 40} }; igraph_matrix_t coords; int i, result; printf("test_bug_1115\n"); igraph_matrix_init(&coords, 51, 2); for (i = 0; i < 102; i++) { MATRIX(coords, i / 2, i % 2) = coords_array[i / 2][i % 2]; } result = check_convex_hull(&coords); igraph_matrix_destroy(&coords); return result; } int main() { int result; result = test_simple(); if (result != 0) { return result; } result = test_collinear(); if (result != 0) { return result; } result = test_degenerate(); if (result != 0) { return result; } result = test_bug_805(); if (result != 0) { return result; } result = test_bug_1115(); if (result != 0) { return result; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_complementer.out0000644000076500000240000000053413524616144030503 0ustar tamasstaff000000000000000 0 0 1 0 2 0 3 0 4 1 0 1 1 1 2 1 3 1 4 2 0 2 1 2 2 2 3 2 4 3 0 3 1 3 2 3 3 3 4 4 0 4 1 4 2 4 3 4 4 --- 0 1 0 2 0 3 0 4 1 0 1 2 1 3 1 4 2 0 2 1 2 3 2 4 3 0 3 1 3 2 3 4 4 0 4 1 4 2 4 3 --- --- 0 0 1 1 2 2 3 3 4 4 --- 0 0 0 1 0 2 0 3 0 4 1 1 1 2 1 3 1 4 2 2 2 3 2 4 3 3 3 4 4 4 --- 0 1 0 2 0 3 0 4 1 2 1 3 1 4 2 3 2 4 3 4 --- --- 0 0 1 1 2 2 3 3 4 4 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_pagerank.c0000644000076500000240000002163713612122633027214 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include void warning_handler_stdout (const char *reason, const char *file, int line, int igraph_errno) { IGRAPH_UNUSED(igraph_errno); printf("Warning: %s\n", reason); } void print_vector(igraph_vector_t *v, FILE *f) { long int i; for (i = 0; i < igraph_vector_size(v); i++) { fprintf(f, " %4.2f", VECTOR(*v)[i]); } fprintf(f, "\n"); } igraph_warning_handler_t *oldwarn; int main() { igraph_t g; igraph_vector_t v, res, reset, weights; igraph_arpack_options_t arpack_options; igraph_real_t value; int ret; igraph_pagerank_power_options_t power_options; /* Test graphs taken from http://www.iprcom.com/papers/pagerank/ */ igraph_vector_init(&v, 10); VECTOR(v)[0] = 0; VECTOR(v)[1] = 1; VECTOR(v)[2] = 1; VECTOR(v)[3] = 2; VECTOR(v)[4] = 2; VECTOR(v)[5] = 0; VECTOR(v)[6] = 3; VECTOR(v)[7] = 2; VECTOR(v)[8] = 0; VECTOR(v)[9] = 2; igraph_create(&g, &v, 0, 1); igraph_vector_init(&res, 0); oldwarn = igraph_set_warning_handler(warning_handler_stdout); igraph_pagerank_old(&g, &res, igraph_vss_all(), 1, 1000, 0.001, 0.85, 0); print_vector(&res, stdout); igraph_vector_destroy(&res); igraph_vector_destroy(&v); igraph_destroy(&g); igraph_vector_init(&v, 28); VECTOR(v)[ 0] = 0; VECTOR(v)[ 1] = 1; VECTOR(v)[ 2] = 0; VECTOR(v)[ 3] = 2; VECTOR(v)[ 4] = 0; VECTOR(v)[ 5] = 3; VECTOR(v)[ 6] = 1; VECTOR(v)[ 7] = 0; VECTOR(v)[ 8] = 2; VECTOR(v)[ 9] = 0; VECTOR(v)[10] = 3; VECTOR(v)[11] = 0; VECTOR(v)[12] = 3; VECTOR(v)[13] = 4; VECTOR(v)[14] = 3; VECTOR(v)[15] = 5; VECTOR(v)[16] = 3; VECTOR(v)[17] = 6; VECTOR(v)[18] = 3; VECTOR(v)[19] = 7; VECTOR(v)[20] = 4; VECTOR(v)[21] = 0; VECTOR(v)[22] = 5; VECTOR(v)[23] = 0; VECTOR(v)[24] = 6; VECTOR(v)[25] = 0; VECTOR(v)[26] = 7; VECTOR(v)[27] = 0; igraph_create(&g, &v, 0, 1); igraph_vector_init(&res, 0); igraph_pagerank_old(&g, &res, igraph_vss_all(), 1, 10000, 0.0001, 0.85, 0); print_vector(&res, stdout); igraph_vector_destroy(&res); igraph_vector_destroy(&v); igraph_destroy(&g); igraph_set_warning_handler(oldwarn); /* New PageRank */ igraph_star(&g, 11, IGRAPH_STAR_UNDIRECTED, 0); igraph_vector_init(&res, 0); igraph_arpack_options_init(&arpack_options); igraph_pagerank(&g, IGRAPH_PAGERANK_ALGO_ARPACK, &res, 0, igraph_vss_all(), 0, 0.85, 0, &arpack_options); print_vector(&res, stdout); igraph_pagerank(&g, IGRAPH_PAGERANK_ALGO_PRPACK, &res, 0, igraph_vss_all(), 0, 0.85, 0, 0); print_vector(&res, stdout); /* Check twice more for consistency */ igraph_pagerank(&g, IGRAPH_PAGERANK_ALGO_ARPACK, &res, 0, igraph_vss_all(), 0, 0.85, 0, &arpack_options); print_vector(&res, stdout); igraph_pagerank(&g, IGRAPH_PAGERANK_ALGO_PRPACK, &res, 0, igraph_vss_all(), 0, 0.85, 0, 0); print_vector(&res, stdout); igraph_pagerank(&g, IGRAPH_PAGERANK_ALGO_ARPACK, &res, 0, igraph_vss_all(), 0, 0.85, 0, &arpack_options); print_vector(&res, stdout); igraph_pagerank(&g, IGRAPH_PAGERANK_ALGO_PRPACK, &res, 0, igraph_vss_all(), 0, 0.85, 0, 0); print_vector(&res, stdout); /* Check personalized PageRank */ igraph_personalized_pagerank_vs(&g, IGRAPH_PAGERANK_ALGO_ARPACK, &res, 0, igraph_vss_all(), 0, 0.5, igraph_vss_1(1), 0, &arpack_options); print_vector(&res, stdout); igraph_personalized_pagerank_vs(&g, IGRAPH_PAGERANK_ALGO_PRPACK, &res, 0, igraph_vss_all(), 0, 0.5, igraph_vss_1(1), 0, 0); print_vector(&res, stdout); /* Errors */ power_options.niter = -1; power_options.eps = 0.0001; igraph_set_error_handler(igraph_error_handler_ignore); igraph_set_warning_handler(igraph_warning_handler_ignore); ret = igraph_pagerank(&g, IGRAPH_PAGERANK_ALGO_POWER, &res, /*value=*/ 0, igraph_vss_all(), 1, 0.85, /*weights=*/ 0, &power_options); if (ret != IGRAPH_EINVAL) { return 1; } power_options.niter = 10000; power_options.eps = -1; ret = igraph_pagerank(&g, IGRAPH_PAGERANK_ALGO_POWER, &res, /*value=*/ 0, igraph_vss_all(), 1, 0.85, /*weights=*/ 0, &power_options); if (ret != IGRAPH_EINVAL) { return 2; } power_options.niter = 10000; power_options.eps = 0.0001; ret = igraph_pagerank(&g, IGRAPH_PAGERANK_ALGO_POWER, &res, /*value=*/ 0, igraph_vss_all(), 1, 1.2, /*weights=*/ 0, &power_options); if (ret != IGRAPH_EINVAL) { return 3; } igraph_vector_init(&reset, 2); ret = igraph_personalized_pagerank(&g, IGRAPH_PAGERANK_ALGO_ARPACK, &res, 0, igraph_vss_all(), 0, 0.85, &reset, 0, &arpack_options); if (ret != IGRAPH_EINVAL) { return 4; } ret = igraph_personalized_pagerank(&g, IGRAPH_PAGERANK_ALGO_PRPACK, &res, 0, igraph_vss_all(), 0, 0.85, &reset, 0, 0); if (ret != IGRAPH_EINVAL) { return 4; } igraph_vector_resize(&reset, 10); igraph_vector_fill(&reset, 0); ret = igraph_personalized_pagerank(&g, IGRAPH_PAGERANK_ALGO_ARPACK, &res, 0, igraph_vss_all(), 0, 0.85, &reset, 0, &arpack_options); if (ret != IGRAPH_EINVAL) { return 5; } ret = igraph_personalized_pagerank(&g, IGRAPH_PAGERANK_ALGO_PRPACK, &res, 0, igraph_vss_all(), 0, 0.85, &reset, 0, 0); if (ret != IGRAPH_EINVAL) { return 5; } igraph_vector_destroy(&reset); igraph_destroy(&g); igraph_set_error_handler(igraph_error_handler_abort); /* Special cases: check for empty graph */ igraph_empty(&g, 10, 0); igraph_pagerank(&g, IGRAPH_PAGERANK_ALGO_ARPACK, &res, &value, igraph_vss_all(), 1, 0.85, 0, &arpack_options); if (value != 1.0) { return 6; } igraph_pagerank(&g, IGRAPH_PAGERANK_ALGO_PRPACK, &res, &value, igraph_vss_all(), 1, 0.85, 0, 0); if (value != 1.0) { return 6; } print_vector(&res, stdout); igraph_destroy(&g); /* Special cases: check for full graph, zero weights */ igraph_full(&g, 10, 0, 0); igraph_vector_init(&v, 45); igraph_vector_fill(&v, 0); igraph_pagerank(&g, IGRAPH_PAGERANK_ALGO_ARPACK, &res, &value, igraph_vss_all(), 1, 0.85, &v, &arpack_options); if (value != 1.0) { return 7; } igraph_pagerank(&g, IGRAPH_PAGERANK_ALGO_PRPACK, &res, &value, igraph_vss_all(), 1, 0.85, &v, 0); if (value != 1.0) { return 7; } igraph_vector_destroy(&v); print_vector(&res, stdout); igraph_destroy(&g); /* Another test case for PageRank (bug #792352) */ igraph_small(&g, 9, 1, 0, 5, 1, 5, 2, 0, 3, 1, 5, 4, 5, 7, 6, 0, 8, 0, 8, 1, -1); igraph_vector_init(&weights, 9); VECTOR(weights)[0] = 4; VECTOR(weights)[1] = 5; VECTOR(weights)[2] = 5; VECTOR(weights)[3] = 4; VECTOR(weights)[4] = 4; VECTOR(weights)[5] = 4; VECTOR(weights)[6] = 3; VECTOR(weights)[7] = 4; VECTOR(weights)[8] = 4; igraph_pagerank(&g, IGRAPH_PAGERANK_ALGO_ARPACK, &res, 0, igraph_vss_all(), 1, 0.85, &weights, &arpack_options); print_vector(&res, stdout); igraph_pagerank(&g, IGRAPH_PAGERANK_ALGO_PRPACK, &res, 0, igraph_vss_all(), 1, 0.85, &weights, 0); print_vector(&res, stdout); igraph_vector_destroy(&weights); igraph_destroy(&g); igraph_vector_destroy(&res); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/vector.out0000644000076500000240000000100113524616144025747 0ustar tamasstaff00000000000000 0 0 0 0 0 0 0 0 0 0 10 9 8 7 6 5 4 3 2 1 0 100 200 300 400 0 20 40 60 80 0 0 0 0 0 0 0 0 0 0 10 10 9 9 8 8 7 7 6 6 5 5 4 4 3 3 2 2 1 1 0 1 2 3 4 5 6 7 8 9 1 2 3 4 5 6 7 8 9 10 100 99 98 97 96 95 94 93 92 91 100 100 99 98 97 96 95 94 93 92 91 11 12 13 14 15 16 17 18 19 20 15 120 8 10 38 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 0 8 1 7 6 2 3 5 4 4 4 5 6 7 8 1 2 3 4 4 4 4 5 6 7 8 0 1 2 3 4 4 4 4 5 6 7 8 0 1 2 6 5 2 1 0 1 3 5 7 6 4 2 0 0 1 2 3 python-igraph-0.8.0/vendor/source/igraph/examples/simple/pajek3.net0000644000076500000240000000103113524616144025604 0ustar tamasstaff00000000000000*Vertices 10 1 "Vert 1" 0 0 box x_fact 1 y_fact 1 ic Green 2 "Vert 2" 0 0 box x_fact 1 y_fact 1 ic Green 3 "Vert 3" 0 0 box x_fact 1 y_fact 1 ic Green 4 "Vert 4" 0 0 box x_fact 1 y_fact 1 ic Green 5 "Vert 5" 0 0 box x_fact 1 y_fact 1 ic Green 6 "Vert 6" 0 0 box x_fact 1 y_fact 1 ic Blue 7 "Vert 7" 0 0 box x_fact 1 y_fact 1 ic Red 8 "Vert 8" 0 0 box x_fact 1 y_fact 1 ic Green 9 "Vert 9" 0 0 box x_fact 1 y_fact 1 ic Green 10 "Vert 10" 0 0 box x_fact 1 y_fact 1 ic Green *Edges 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 python-igraph-0.8.0/vendor/source/igraph/examples/simple/edgelist1.dl0000644000076500000240000000013513524616144026125 0ustar tamasstaff00000000000000DL n=5 format = edgelist1 labels: george, sally, jim, billy, jane data: 1 2 1 3 2 3 3 1 4 3 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_rewire.c0000644000076500000240000000502513614300625026713 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int igraph_rewire_core(igraph_t *graph, igraph_integer_t n, igraph_rewiring_t mode, igraph_bool_t use_adjlist); static void check_rewiring(igraph_tree_mode_t tree_mode, igraph_bool_t use_adjlist, const char* description) { igraph_t g; igraph_vector_t indegree_before, outdegree_before, indegree_after, outdegree_after; igraph_tree(&g, 10, 3, tree_mode); igraph_vector_init(&indegree_before, 0); igraph_vector_init(&outdegree_before, 0); igraph_degree(&g, &indegree_before, igraph_vss_all(), IGRAPH_IN, 0); igraph_degree(&g, &outdegree_before, igraph_vss_all(), IGRAPH_OUT, 0); igraph_rewire_core(&g, 1000, IGRAPH_REWIRING_SIMPLE, use_adjlist); igraph_vector_init(&indegree_after, 0); igraph_vector_init(&outdegree_after, 0); igraph_degree(&g, &indegree_after, igraph_vss_all(), IGRAPH_IN, 0); igraph_degree(&g, &outdegree_after, igraph_vss_all(), IGRAPH_OUT, 0); if ((!igraph_vector_all_e(&indegree_before, &indegree_after)) || (!igraph_vector_all_e(&outdegree_before, &outdegree_after))) { fprintf(stderr, "%s graph degrees changed\n", description); exit(1); } igraph_destroy(&g); igraph_vector_destroy(&indegree_before); igraph_vector_destroy(&outdegree_before); igraph_vector_destroy(&indegree_after); igraph_vector_destroy(&outdegree_after); } int main() { check_rewiring(IGRAPH_TREE_OUT, 0, "Directed, standard-method"); check_rewiring(IGRAPH_TREE_OUT, 1, "Directed, adjlist-method"); check_rewiring(IGRAPH_TREE_UNDIRECTED, 0, "Undirected, standard-method"); check_rewiring(IGRAPH_TREE_UNDIRECTED, 1, "Undirected, adjlist-method"); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_community_label_propagation.out0000644000076500000240000000000013524616144033563 0ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/examples/simple/spmatrix.c0000644000076500000240000001500313612122634025730 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void print_matrix(igraph_spmatrix_t *m, FILE *f) { long int i, j; for (i = 0; i < igraph_spmatrix_nrow(m); i++) { for (j = 0; j < igraph_spmatrix_ncol(m); j++) { fprintf(f, " %li", (long int)igraph_spmatrix_e(m, i, j)); } fprintf(f, "\n"); } fprintf(f, "=========================\n"); } void print_vector(igraph_vector_t *v, FILE *f) { long int i; for (i = 0; i < igraph_vector_size(v); i++) { fprintf(f, " %li", (long int)VECTOR(*v)[i]); } fprintf(f, "\n=========================\n"); } int main() { igraph_spmatrix_t m, m1; igraph_spmatrix_iter_t mit; igraph_real_t arr[12]; igraph_vector_t v; long int i, j; int order[] = { 1, 5, 8, 4, 0, 9, 6, 10, 11, 2, 3, 7 }; /* igraph_spmatrix_init, igraph_spmatrix_destroy */ igraph_spmatrix_init(&m, 10, 10); igraph_spmatrix_destroy(&m); igraph_spmatrix_init(&m, 0, 0); igraph_spmatrix_destroy(&m); /* igraph_spmatrix_ncol, igraph_spmatrix_nrow */ igraph_spmatrix_init(&m, 10, 5); if (igraph_spmatrix_nrow(&m) != 10) { return 1; } if (igraph_spmatrix_ncol(&m) != 5) { return 2; } /* igraph_spmatrix_size, igraph_spmatrix_resize */ igraph_spmatrix_resize(&m, 6, 5); if (igraph_spmatrix_size(&m) != 30) { return 3; } if (igraph_spmatrix_nrow(&m) != 6) { return 4; } if (igraph_spmatrix_ncol(&m) != 5) { return 5; } igraph_spmatrix_resize(&m, 2, 4); if (igraph_spmatrix_nrow(&m) != 2) { return 6; } if (igraph_spmatrix_ncol(&m) != 4) { return 7; } igraph_spmatrix_destroy(&m); /* igraph_spmatrix_get, igraph_spmatrix_set, igraph_spmatrix_null */ igraph_spmatrix_init(&m, 3, 4); for (i = 0; i < igraph_spmatrix_nrow(&m); i++) { for (j = 0; j < igraph_spmatrix_ncol(&m); j++) { igraph_spmatrix_set(&m, i, j, (i + j) % 3); } } print_matrix(&m, stdout); igraph_spmatrix_null(&m); print_matrix(&m, stdout); /* now fill it in shuffled order */ for (i = 0; i < 12; i++) { igraph_spmatrix_set(&m, order[i] / 4, order[i] % 4, (order[i] / 4 + order[i] % 4) % 3); } print_matrix(&m, stdout); /* now decrease all elements by two in shuffled order */ for (i = 0; i < 12; i++) { igraph_spmatrix_add_e(&m, order[i] / 4, order[i] % 4, -2); } print_matrix(&m, stdout); /* now increase all elements by one in shuffled order */ for (i = 0; i < 12; i++) { igraph_spmatrix_add_e(&m, order[i] / 4, order[i] % 4, 1); } print_matrix(&m, stdout); igraph_spmatrix_destroy(&m); /* igraph_matrix_add_cols, igraph_matrix_add_rows */ igraph_spmatrix_init(&m, 4, 3); for (i = 0; i < igraph_spmatrix_nrow(&m); i++) { for (j = 0; j < igraph_spmatrix_ncol(&m); j++) { igraph_spmatrix_set(&m, i, j, (i + 1) * (j + 1)); } } igraph_spmatrix_add_cols(&m, 2); igraph_spmatrix_add_rows(&m, 2); if (igraph_spmatrix_ncol(&m) != 5) { return 8; } if (igraph_spmatrix_nrow(&m) != 6) { return 9; } print_matrix(&m, stdout); igraph_spmatrix_destroy(&m); /* igraph_spmatrix_count_nonzero */ igraph_spmatrix_init(&m, 5, 3); for (i = 0; i < igraph_spmatrix_nrow(&m); i++) { for (j = 0; j < igraph_spmatrix_ncol(&m); j++) { igraph_spmatrix_set(&m, i, j, i * j); } } print_matrix(&m, stdout); if (igraph_spmatrix_count_nonzero(&m) != 8) { return 10; } igraph_spmatrix_destroy(&m); /* igraph_spmatrix_copy */ igraph_spmatrix_init(&m, 3, 4); for (i = 0; i < igraph_spmatrix_nrow(&m); i++) { for (j = 0; j < igraph_spmatrix_ncol(&m); j++) { igraph_spmatrix_set(&m, i, j, i * j); } } igraph_spmatrix_copy(&m1, &m); print_matrix(&m1, stdout); igraph_spmatrix_destroy(&m); igraph_spmatrix_destroy(&m1); /* igraph_spmatrix_copy_to */ igraph_spmatrix_init(&m, 3, 4); for (i = 0; i < igraph_spmatrix_nrow(&m); i++) { for (j = 0; j < igraph_spmatrix_ncol(&m); j++) { igraph_spmatrix_set(&m, i, j, i * j); } } igraph_spmatrix_copy_to(&m, arr); for (i = 0; i < 12; i++) { printf(" %ld", (long)arr[i]); } printf("\n=========================\n"); /* igraph_spmatrix_max */ arr[0] = igraph_spmatrix_max(&m, arr + 1, arr + 2); for (i = 0; i < 3; i++) { printf(" %ld", (long)arr[i]); } printf("\n=========================\n"); igraph_spmatrix_destroy(&m); /* igraph_spmatrix_colsums */ igraph_spmatrix_init(&m, 3, 5); for (i = 0; i < igraph_spmatrix_nrow(&m); i++) { for (j = 0; j < igraph_spmatrix_ncol(&m); j++) { igraph_spmatrix_set(&m, i, j, i + j - 4); } } igraph_vector_init(&v, 0); igraph_spmatrix_colsums(&m, &v); print_vector(&v, stdout); igraph_vector_destroy(&v); igraph_spmatrix_destroy(&m); /* igraph_spmatrix_iter_t */ igraph_spmatrix_init(&m, 5, 5); for (i = 0; i < igraph_spmatrix_nrow(&m); i++) { for (j = 0; j < igraph_spmatrix_ncol(&m); j++) { if (labs(i - j) == 1) { igraph_spmatrix_set(&m, i, j, (i + 1) * (j + 1)); } } } igraph_spmatrix_iter_create(&mit, &m); while (!igraph_spmatrix_iter_end(&mit)) { printf("%ld %ld %ld\n", mit.ri, mit.ci, (long int)mit.value); igraph_spmatrix_iter_next(&mit); } igraph_spmatrix_iter_destroy(&mit); igraph_spmatrix_destroy(&m); printf("=========================\n"); /* TODO: igraph_spmatrix_add_col_values */ return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_small.out0000644000076500000240000000002413524616144027113 0ustar tamasstaff000000000000000 1 1 2 2 3 3 4 6 1 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_maximal_cliques3.c0000644000076500000240000000504713612122633030661 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2013 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int sort_cmp(const void *a, const void *b) { const igraph_vector_t **da = (const igraph_vector_t **) a; const igraph_vector_t **db = (const igraph_vector_t **) b; int i, alen = igraph_vector_size(*da), blen = igraph_vector_size(*db); if (alen != blen) { return (alen < blen) - (alen > blen); } for (i = 0; i < alen; i++) { int ea = VECTOR(**da)[i], eb = VECTOR(**db)[i]; if (ea != eb) { return (ea > eb) - (ea < eb); } } return 0; } void sort_cliques(igraph_vector_ptr_t *cliques) { int i, n = igraph_vector_ptr_size(cliques); for (i = 0; i < n; i++) { igraph_vector_t *v = VECTOR(*cliques)[i]; igraph_vector_sort(v); } igraph_qsort(VECTOR(*cliques), (size_t) n, sizeof(igraph_vector_t *), sort_cmp); } int print_and_destroy(igraph_vector_ptr_t *cliques) { int i, n = igraph_vector_ptr_size(cliques); sort_cliques(cliques); for (i = 0; i < n; i++) { igraph_vector_t *v = VECTOR(*cliques)[i]; igraph_vector_print(v); igraph_vector_destroy(v); } igraph_vector_ptr_destroy_all(cliques); return 0; } int main() { igraph_t graph; igraph_vector_ptr_t cliques; igraph_rng_seed(igraph_rng_default(), 42); igraph_erdos_renyi_game(&graph, IGRAPH_ERDOS_RENYI_GNP, /*n=*/ 100, /*p=*/ 0.7, /*directed=*/ 0, /*loops=*/ 0); igraph_vector_ptr_init(&cliques, 0); igraph_maximal_cliques(&graph, &cliques, /*min_size=*/ 15, /*max_size=*/ 0); print_and_destroy(&cliques); igraph_destroy(&graph); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_intersection2.c0000644000076500000240000000346413612122633030212 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2013 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int main() { igraph_t star, ring, uni, result; igraph_vector_ptr_t glist; igraph_star(&star, 11, IGRAPH_STAR_UNDIRECTED, /*center=*/ 10); igraph_ring(&ring, 10, IGRAPH_UNDIRECTED, /*mutual=*/ 0, /*circular=*/ 1); igraph_union(&uni, &star, &ring, /*edge_map1=*/ 0, /*edge_map2=*/ 0); igraph_intersection(&result, &uni, &star, /*edge_map1*/ 0, /*edge_map2=*/ 0); igraph_write_graph_edgelist(&result, stdout); igraph_destroy(&result); /* ---------------------------- */ igraph_vector_ptr_init(&glist, 2); VECTOR(glist)[0] = &uni; VECTOR(glist)[1] = ☆ igraph_intersection_many(&result, &glist, /*edgemaps=*/ 0); printf("--\n"); igraph_write_graph_edgelist(&result, stdout); igraph_vector_ptr_destroy(&glist); igraph_destroy(&result); igraph_destroy(&uni); igraph_destroy(&ring); igraph_destroy(&star); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_sparsemat.c0000644000076500000240000001254613614300625027423 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_sparsemat_t A, B, C, D; igraph_t G, H; igraph_vector_t vect; long int i; /* Create, compress, destroy */ igraph_sparsemat_init(&A, 100, 20, 50); igraph_sparsemat_compress(&A, &B); igraph_sparsemat_destroy(&B); igraph_sparsemat_destroy(&A); /* Convert a ring graph to a matrix, print it, compress, print again */ #define VC 10 igraph_ring(&G, VC, /*directed=*/ 0, /*mutual=*/ 0, /*circular=*/ 1); igraph_get_sparsemat(&G, &A); igraph_destroy(&G); igraph_sparsemat_compress(&A, &B); igraph_sparsemat_print(&A, stdout); igraph_sparsemat_print(&B, stdout); /* Basic query, nrow, ncol, type, is_triplet, is_cc */ if (igraph_sparsemat_nrow(&A) != VC || igraph_sparsemat_ncol(&A) != VC || igraph_sparsemat_nrow(&B) != VC || igraph_sparsemat_ncol(&B) != VC) { return 1; } if (!igraph_sparsemat_is_triplet(&A)) { return 2; } if (!igraph_sparsemat_is_cc(&B)) { return 3; } if (igraph_sparsemat_type(&A) != IGRAPH_SPARSEMAT_TRIPLET) { return 4; } if (igraph_sparsemat_type(&B) != IGRAPH_SPARSEMAT_CC) { return 5; } igraph_sparsemat_destroy(&A); igraph_sparsemat_destroy(&B); #undef VC printf("------------------------\n"); /* Create unit matrices */ igraph_sparsemat_eye(&A, /*n=*/ 5, /*nzmax=*/ 5, /*value=*/ 1.0, /*compress=*/ 0); igraph_sparsemat_eye(&B, /*n=*/ 5, /*nzmax=*/ 5, /*value=*/ 1.0, /*compress=*/ 1); igraph_sparsemat_print(&A, stdout); igraph_sparsemat_print(&B, stdout); igraph_sparsemat_destroy(&A); igraph_sparsemat_destroy(&B); printf("------------------------\n"); /* Create diagonal matrices */ igraph_vector_init(&vect, 5); for (i = 0; i < 5; i++) { VECTOR(vect)[i] = i; } igraph_sparsemat_diag(&A, /*nzmax=*/ 5, /*values=*/ &vect, /*compress=*/ 0); igraph_sparsemat_diag(&B, /*nzmax=*/ 5, /*values=*/ &vect, /*compress=*/ 1); igraph_vector_destroy(&vect); igraph_sparsemat_print(&A, stdout); igraph_sparsemat_print(&B, stdout); igraph_sparsemat_destroy(&A); igraph_sparsemat_destroy(&B); printf("------------------------\n"); /* Transpose matrices */ igraph_tree(&G, 10, /*children=*/ 2, IGRAPH_TREE_OUT); igraph_get_sparsemat(&G, &A); igraph_destroy(&G); igraph_sparsemat_compress(&A, &B); igraph_sparsemat_print(&B, stdout); igraph_sparsemat_transpose(&B, &C, /*values=*/ 1); igraph_sparsemat_print(&C, stdout); igraph_sparsemat_destroy(&A); igraph_sparsemat_destroy(&B); igraph_sparsemat_destroy(&C); printf("------------------------\n"); /* Add duplicate elements */ igraph_sparsemat_init(&A, 10, 10, /*nzmax=*/ 20); for (i = 1; i < 10; i++) { igraph_sparsemat_entry(&A, 0, i, 1.0); } for (i = 1; i < 10; i++) { igraph_sparsemat_entry(&A, 0, i, 1.0); } igraph_sparsemat_print(&A, stdout); igraph_sparsemat_compress(&A, &B); igraph_sparsemat_print(&B, stdout); igraph_sparsemat_dupl(&B); igraph_sparsemat_print(&B, stdout); igraph_sparsemat_destroy(&A); igraph_sparsemat_destroy(&B); printf("------------------------\n"); /* Drop zero elements */ igraph_sparsemat_init(&A, 10, 10, /*nzmax=*/ 20); igraph_sparsemat_entry(&A, 7, 3, 0.0); for (i = 1; i < 10; i++) { igraph_sparsemat_entry(&A, 0, i, 1.0); igraph_sparsemat_entry(&A, 0, i, 0.0); } igraph_sparsemat_entry(&A, 0, 0, 0.0); igraph_sparsemat_print(&A, stdout); igraph_sparsemat_compress(&A, &B); igraph_sparsemat_print(&B, stdout); igraph_sparsemat_dropzeros(&B); igraph_sparsemat_print(&B, stdout); igraph_sparsemat_destroy(&A); igraph_sparsemat_destroy(&B); printf("------------------------\n"); /* Add two matrices */ igraph_star(&G, 10, IGRAPH_STAR_OUT, /*center=*/ 0); igraph_ring(&H, 10, /*directed=*/ 0, /*mutual=*/ 0, /*circular=*/ 1); igraph_get_sparsemat(&G, &A); igraph_get_sparsemat(&H, &B); igraph_destroy(&G); igraph_destroy(&H); igraph_sparsemat_compress(&A, &C); igraph_sparsemat_compress(&B, &D); igraph_sparsemat_destroy(&A); igraph_sparsemat_destroy(&B); igraph_sparsemat_add(&C, &D, /*alpha=*/ 1.0, /*beta=*/ 2.0, &A); igraph_sparsemat_destroy(&C); igraph_sparsemat_destroy(&D); igraph_sparsemat_print(&A, stdout); igraph_sparsemat_destroy(&A); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_psumtree.c0000644000076500000240000001310113612122633027253 0ustar tamasstaff00000000000000 /* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int print_vector(igraph_vector_t *v) { long int i, n = igraph_vector_size(v); for (i = 0; i < n; i++) { printf("%li ", (long int) VECTOR(*v)[i]); } printf("\n"); return 0; } int main() { igraph_psumtree_t tree; igraph_vector_t vec; long int i; igraph_real_t sum; /* Uniform random numbers */ igraph_vector_init(&vec, 16); igraph_psumtree_init(&tree, 16); sum = igraph_psumtree_sum(&tree); if (sum != 0) { printf("Sum: %f instead of 0.\n", sum); return 1; } for (i = 0; i < 16; i++) { igraph_psumtree_update(&tree, i, 1); } if ((sum = igraph_psumtree_sum(&tree)) != 16) { printf("Sum: %f instead of 16.\n", sum); return 2; } for (i = 0; i < 16000; i++) { igraph_real_t r = ((double)rand()) / RAND_MAX * sum; long int idx; igraph_psumtree_search(&tree, &idx, r); VECTOR(vec)[idx] += 1; } for (i = 0; i < 16; i++) { if (VECTOR(vec)[i] < 800 || VECTOR(vec)[i] > 1200) { return 3; } } /* Nonuniform, even indices have twice as much chance */ for (i = 0; i < 16; i += 2) { igraph_psumtree_update(&tree, i, 2); } if ((sum = igraph_psumtree_sum(&tree)) != 24) { printf("Sum: %f instead of 24.\n", sum); return 4; } igraph_vector_null(&vec); for (i = 0; i < 24000; i++) { igraph_real_t r = ((double)rand()) / RAND_MAX * sum; long int idx; igraph_psumtree_search(&tree, &idx, r); VECTOR(vec)[idx] += 1; } for (i = 0; i < 16; i++) { if (i % 2 == 0 && (VECTOR(vec)[i] < 1800 || VECTOR(vec)[i] > 2200)) { return 5; } if (i % 2 != 0 && (VECTOR(vec)[i] < 800 || VECTOR(vec)[i] > 1200)) { return 6; } } /* Test zero probabilities */ igraph_psumtree_update(&tree, 0, 0); igraph_psumtree_update(&tree, 5, 0); igraph_psumtree_update(&tree, 15, 0); sum = igraph_psumtree_sum(&tree); igraph_vector_null(&vec); for (i = 0; i < 20000; i++) { igraph_real_t r = ((double)rand()) / RAND_MAX * sum; long int idx; igraph_psumtree_search(&tree, &idx, r); VECTOR(vec)[idx] += 1; } if (VECTOR(vec)[0] != 0 || VECTOR(vec)[5] != 0 || VECTOR(vec)[15] != 0) { return 7; } igraph_vector_destroy(&vec); igraph_psumtree_destroy(&tree); /****************************************************/ /* Non power-of-two vector size */ /****************************************************/ igraph_vector_init(&vec, 9); igraph_psumtree_init(&tree, 9); for (i = 0; i < 9; i++) { igraph_psumtree_update(&tree, i, 1); } sum = igraph_psumtree_sum(&tree); for (i = 0; i < 9000; i++) { igraph_real_t r = ((double)rand()) / RAND_MAX * sum; long int idx; igraph_psumtree_search(&tree, &idx, r); VECTOR(vec)[idx] += 1; } for (i = 0; i < 9; i++) { if (VECTOR(vec)[i] < 800 || VECTOR(vec)[i] > 1200) { return 8; } } /* Nonuniform, even indices have twice as much chance */ for (i = 0; i < 9; i += 2) { igraph_psumtree_update(&tree, i, 2); } sum = igraph_psumtree_sum(&tree); igraph_vector_null(&vec); for (i = 0; i < 14000; i++) { igraph_real_t r = ((double)rand()) / RAND_MAX * sum; long int idx; igraph_psumtree_search(&tree, &idx, r); VECTOR(vec)[idx] += 1; } for (i = 0; i < 9; i++) { if (i % 2 == 0 && (VECTOR(vec)[i] < 1800 || VECTOR(vec)[i] > 2200)) { return 9; } if (i % 2 != 0 && (VECTOR(vec)[i] < 800 || VECTOR(vec)[i] > 1200)) { return 10; } } /* Test query */ for (i = 0; i < igraph_psumtree_size(&tree); i++) { if (i % 2 == 0 && igraph_psumtree_get(&tree, i) != 2) { return 11; } if (i % 2 != 0 && igraph_psumtree_get(&tree, i) != 1) { return 12; } } /* Test zero probabilities */ igraph_psumtree_update(&tree, 0, 0); igraph_psumtree_update(&tree, 5, 0); igraph_psumtree_update(&tree, 8, 0); sum = igraph_psumtree_sum(&tree); igraph_vector_null(&vec); for (i = 0; i < 9000; i++) { igraph_real_t r = ((double)rand()) / RAND_MAX * sum; long int idx; igraph_psumtree_search(&tree, &idx, r); VECTOR(vec)[idx] += 1; } if (VECTOR(vec)[0] != 0 || VECTOR(vec)[5] != 0 || VECTOR(vec)[8] != 0) { return 11; } igraph_vector_destroy(&vec); igraph_psumtree_destroy(&tree); if (!IGRAPH_FINALLY_STACK_EMPTY) { return 13; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/fullmatrix3.dl0000644000076500000240000000016413524616144026520 0ustar tamasstaff00000000000000dl n=5 format = fullmatrix labels: barry,david lin,pat russ data: 0 1 1 1 0 1 0 0 0 1 1 0 0 1 0 1 0 1 0 1 0 1 0 1 0 python-igraph-0.8.0/vendor/source/igraph/examples/simple/pajek2.net0000644000076500000240000000100413524616144025603 0ustar tamasstaff00000000000000*Vertices 10 1 "Vert 1" 0 0 box x_fact 1 y_fact 1 ic Green 2 "Vert 2" 0 0 box x_fact 1 y_fact 1 ic Green 3 "Vert 3" 0 0 box x_fact 1 y_fact 1 ic Green 4 "Vert 4" 0 0 box x_fact 1 y_fact 1 ic Green 5 "Vert 5" 0 0 box x_fact 1 y_fact 1 ic Green 6 "Vert 6" 0 0 box x_fact 1 y_fact 1 ic Blue 7 "Vert 7" 0 0 box x_fact 1 y_fact 1 ic Red 8 "Vert 8" 0 0 box x_fact 1 y_fact 1 ic Green 9 "Vert 9" 0 0 box x_fact 1 y_fact 1 ic Green 10 "Vert 10" 0 0 box x_fact 1 y_fact 1 ic Green *Edges 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 python-igraph-0.8.0/vendor/source/igraph/examples/simple/bug-1033045.c0000644000076500000240000000300213612122633025446 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t graph; igraph_vector_ptr_t separators; int i, n; igraph_small(&graph, 0, /*directed=*/ 0, 0, 1, 0, 2, 1, 3, 1, 4, 2, 3, 2, 5, 3, 4, 3, 5, 4, 6, 5, 6, -1); igraph_vector_ptr_init(&separators, 0); igraph_all_minimal_st_separators(&graph, &separators); n = igraph_vector_ptr_size(&separators); for (i = 0; i < n; i++) { igraph_vector_t *sep = VECTOR(separators)[i]; igraph_vector_print(sep); igraph_vector_destroy(sep); igraph_free(sep); } igraph_vector_ptr_destroy(&separators); igraph_destroy(&graph); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/gml.out0000644000076500000240000001104413524616144025234 0ustar tamasstaff00000000000000undirected 0 1 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 10 0 11 0 12 0 13 0 17 0 19 0 21 0 31 1 2 1 3 1 7 1 13 1 17 1 19 1 21 1 30 2 3 2 7 2 8 2 9 2 13 2 27 2 28 2 32 3 7 3 12 3 13 4 6 4 10 5 6 5 10 5 16 6 16 8 30 8 32 8 33 9 33 13 33 14 32 14 33 15 32 15 33 18 32 18 33 19 33 20 32 20 33 22 32 22 33 23 25 23 27 23 29 23 32 23 33 24 25 24 27 24 31 25 31 26 29 26 33 27 33 28 31 28 33 29 32 29 33 30 32 30 33 31 32 31 33 32 33 ----------------- Creator "igraph version @VERSION@ test suite" Version 1 graph [ directed 0 node [ id 0 ] node [ id 1 ] node [ id 2 ] node [ id 3 ] node [ id 4 ] node [ id 5 ] node [ id 6 ] node [ id 7 ] node [ id 8 ] node [ id 9 ] node [ id 10 ] node [ id 11 ] node [ id 12 ] node [ id 13 ] node [ id 14 ] node [ id 15 ] node [ id 16 ] node [ id 17 ] node [ id 18 ] node [ id 19 ] node [ id 20 ] node [ id 21 ] node [ id 22 ] node [ id 23 ] node [ id 24 ] node [ id 25 ] node [ id 26 ] node [ id 27 ] node [ id 28 ] node [ id 29 ] node [ id 30 ] node [ id 31 ] node [ id 32 ] node [ id 33 ] edge [ source 1 target 0 ] edge [ source 2 target 0 ] edge [ source 2 target 1 ] edge [ source 3 target 0 ] edge [ source 3 target 1 ] edge [ source 3 target 2 ] edge [ source 4 target 0 ] edge [ source 5 target 0 ] edge [ source 6 target 0 ] edge [ source 6 target 4 ] edge [ source 6 target 5 ] edge [ source 7 target 0 ] edge [ source 7 target 1 ] edge [ source 7 target 2 ] edge [ source 7 target 3 ] edge [ source 8 target 0 ] edge [ source 8 target 2 ] edge [ source 9 target 2 ] edge [ source 10 target 0 ] edge [ source 10 target 4 ] edge [ source 10 target 5 ] edge [ source 11 target 0 ] edge [ source 12 target 0 ] edge [ source 12 target 3 ] edge [ source 13 target 0 ] edge [ source 13 target 1 ] edge [ source 13 target 2 ] edge [ source 13 target 3 ] edge [ source 16 target 5 ] edge [ source 16 target 6 ] edge [ source 17 target 0 ] edge [ source 17 target 1 ] edge [ source 19 target 0 ] edge [ source 19 target 1 ] edge [ source 21 target 0 ] edge [ source 21 target 1 ] edge [ source 25 target 23 ] edge [ source 25 target 24 ] edge [ source 27 target 2 ] edge [ source 27 target 23 ] edge [ source 27 target 24 ] edge [ source 28 target 2 ] edge [ source 29 target 23 ] edge [ source 29 target 26 ] edge [ source 30 target 1 ] edge [ source 30 target 8 ] edge [ source 31 target 0 ] edge [ source 31 target 24 ] edge [ source 31 target 25 ] edge [ source 31 target 28 ] edge [ source 32 target 2 ] edge [ source 32 target 8 ] edge [ source 32 target 14 ] edge [ source 32 target 15 ] edge [ source 32 target 18 ] edge [ source 32 target 20 ] edge [ source 32 target 22 ] edge [ source 32 target 23 ] edge [ source 32 target 29 ] edge [ source 32 target 30 ] edge [ source 32 target 31 ] edge [ source 33 target 8 ] edge [ source 33 target 9 ] edge [ source 33 target 13 ] edge [ source 33 target 14 ] edge [ source 33 target 15 ] edge [ source 33 target 18 ] edge [ source 33 target 19 ] edge [ source 33 target 20 ] edge [ source 33 target 22 ] edge [ source 33 target 23 ] edge [ source 33 target 26 ] edge [ source 33 target 27 ] edge [ source 33 target 28 ] edge [ source 33 target 29 ] edge [ source 33 target 30 ] edge [ source 33 target 31 ] edge [ source 33 target 32 ] ] python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_motifs_randesu.c0000644000076500000240000000404013612122633030433 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void print_vector(igraph_vector_t *v) { long int i, n = igraph_vector_size(v); igraph_real_t sum = 0.0; for (i = 0; i < n; i++) { if (!igraph_is_nan(VECTOR(*v)[i])) { sum += VECTOR(*v)[i]; } } for (i = 0; i < n; i++) { igraph_real_printf(VECTOR(*v)[i] / sum); printf(" "); } printf("\n"); } igraph_bool_t print_motif(const igraph_t *graph, igraph_vector_t *vids, int isoclass, void* extra) { printf("Class %d: ", isoclass); igraph_vector_print(vids); return 0; } int main() { igraph_t g; igraph_vector_t hist; igraph_vector_t cp; igraph_vector_init_real(&cp, 8, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0); igraph_ring(&g, 1000, IGRAPH_DIRECTED, 1, 1); igraph_vector_init(&hist, 0); igraph_motifs_randesu(&g, &hist, 3, &cp); print_vector(&hist); igraph_destroy(&g); igraph_vector_destroy(&hist); igraph_famous(&g, "bull"); igraph_motifs_randesu_callback(&g, 3, &cp, &print_motif, 0); igraph_motifs_randesu_callback(&g, 4, &cp, &print_motif, 0); igraph_destroy(&g); igraph_vector_destroy(&cp); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_bridges.c0000644000076500000240000000122713612122633027034 0ustar tamasstaff00000000000000 #include #include void sort_and_print_vector(igraph_vector_t *v) { long int i, n = igraph_vector_size(v); igraph_vector_sort(v); for (i = 0; i < n; i++) { printf(" %li", (long int) VECTOR(*v)[i]); } printf("\n"); } int main() { igraph_t graph; igraph_vector_t bridges; igraph_small(&graph, /* num_nodes = */ 7, /* directed = */ 0, 0, 1, 1, 2, 0, 2, 0, 3, 3, 4, 4, 5, 3, 5, 4, 6, -1); igraph_vector_init(&bridges, 0); igraph_bridges(&graph, &bridges); sort_and_print_vector(&bridges); igraph_vector_destroy(&bridges); igraph_destroy(&graph); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_layout_sugiyama.c0000644000076500000240000000663513612122633030641 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include int main() { igraph_t g, extd_g; igraph_matrix_t coords; igraph_vector_t edgelist, extd_edgelist, extd_to_orig_eids; igraph_vector_t layers; igraph_matrix_init(&coords, 0, 0); igraph_vector_init(&extd_to_orig_eids, 0); /* Layout on simple graph with predefined layers */ igraph_vector_init_int_end(&layers, -1, 0, 1, 1, 2, 3, 3, 4, 4, 5, -1); igraph_vector_init_int_end(&edgelist, -1, 0, 1, 0, 2, 0, 3, 1, 2, 2, 2, 1, 4, 2, 5, 4, 6, 5, 7, 6, 8, 7, 8, 3, 8, 8, 1, 8, 2, -1); igraph_create(&g, &edgelist, 0, 1); igraph_layout_sugiyama(&g, &coords, 0, 0, &layers, /* hgap = */ 1, /* vgap = */ 1, /* maxiter = */ 100, /* weights = */ 0); igraph_matrix_print(&coords); printf("===\n"); /* Same, but this time also return the extended graph */ igraph_layout_sugiyama(&g, &coords, &extd_g, &extd_to_orig_eids, &layers, /* hgap = */ 1, /* vgap = */ 1, /* maxiter = */ 100, /* weights = */ 0); igraph_matrix_print(&coords); printf("===\n"); igraph_vector_init(&extd_edgelist, 0); igraph_get_edgelist(&extd_g, &extd_edgelist, 0); igraph_vector_print(&extd_edgelist); igraph_vector_destroy(&extd_edgelist); igraph_destroy(&extd_g); printf("===\n"); igraph_vector_print(&extd_to_orig_eids); printf("===\n"); igraph_vector_destroy(&layers); /* Same, but with automatic layering */ igraph_layout_sugiyama(&g, &coords, 0, 0, 0, /* hgap = */ 1, /* vgap = */ 1, /* maxiter = */ 100, /* weights = */ 0); igraph_matrix_print(&coords); printf("===\n"); /* Layering with gaps in it */ igraph_vector_init_int_end(&layers, -1, 0, 2, 2, 4, 6, 6, 12, 12, 15, -1); igraph_layout_sugiyama(&g, &coords, 0, 0, &layers, /* hgap = */ 1, /* vgap = */ 1, /* maxiter = */ 100, /* weights = */ 0); igraph_matrix_print(&coords); igraph_vector_destroy(&layers); printf("===\n"); igraph_vector_destroy(&edgelist); igraph_matrix_destroy(&coords); igraph_vector_destroy(&extd_to_orig_eids); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/isomorphism_test.c0000644000076500000240000001661013612122634027476 0ustar tamasstaff00000000000000 #include #include #include int random_permutation(igraph_vector_t *vec) { /* We just do size(vec) * 2 swaps */ long int one, two, tmp, i, n = igraph_vector_size(vec); for (i = 0; i < 2 * n; i++) { one = (double)rand() / RAND_MAX * n; two = (double)rand() / RAND_MAX * n; tmp = one; one = two; two = tmp; } return 0; } void test3() { int i, j; igraph_vector_ptr_t graphs3; // Verify that no two 3-vertex graphs of distinct isoclasses are considered isomorphic by Bliss or VF2. igraph_vector_ptr_init(&graphs3, 0); IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(&graphs3, igraph_destroy); for (i = 0; i < 16; i++) { igraph_t *g; g = (igraph_t *) malloc(sizeof(igraph_t)); igraph_vector_ptr_push_back(&graphs3, g); igraph_isoclass_create(g, 3, i, /* directed = */ 1); } for (i = 0; i < 16; i++) for (j = i + 1; j < 16; j++) { igraph_bool_t iso; igraph_isomorphic_bliss( (igraph_t *) VECTOR(graphs3)[i], (igraph_t *) VECTOR(graphs3)[j], NULL, NULL, &iso, NULL, NULL, IGRAPH_BLISS_F, NULL, NULL); if (iso) { printf("Bliss failure, 3 vertex directed graphs of isoclass %d and %d are not isomorphic. Bliss reports otherwise.\n", i, j); } } for (i = 0; i < 16; i++) for (j = i + 1; j < 16; j++) { igraph_bool_t iso; igraph_isomorphic_vf2( (igraph_t *) VECTOR(graphs3)[i], (igraph_t *) VECTOR(graphs3)[j], NULL, NULL, NULL, NULL, &iso, NULL, NULL, NULL, NULL, NULL); if (iso) { printf("VF2 failure, 3 vertex directed graphs of isoclass %d and %d are not isomorphic. VF2 reports otherwise.\n", i, j); } } igraph_vector_ptr_destroy_all(&graphs3); } void test4() { int i, j; igraph_vector_ptr_t graphs4; // Verify that no two 4-vertex graphs of distinct isoclasses are considered isomorphic by Bliss or VF2. igraph_vector_ptr_init(&graphs4, 0); IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(&graphs4, igraph_destroy); for (i = 0; i < 218; i++) { igraph_t *g; g = (igraph_t *) malloc(sizeof(igraph_t)); igraph_vector_ptr_push_back(&graphs4, g); igraph_isoclass_create(g, 4, i, /* directed = */ 1); } for (i = 0; i < 218; i++) for (j = i + 1; j < 218; j++) { igraph_bool_t iso; igraph_isomorphic_bliss( (igraph_t *) VECTOR(graphs4)[i], (igraph_t *) VECTOR(graphs4)[j], NULL, NULL, &iso, NULL, NULL, IGRAPH_BLISS_F, NULL, NULL); if (iso) { printf("Bliss failure, 4 vertex directed graphs of isoclass %d and %d are not isomorphic. Bliss reports otherwise.\n", i, j); } } for (i = 0; i < 218; i++) for (j = i + 1; j < 218; j++) { igraph_bool_t iso; igraph_isomorphic_vf2( (igraph_t *) VECTOR(graphs4)[i], (igraph_t *) VECTOR(graphs4)[j], NULL, NULL, NULL, NULL, &iso, NULL, NULL, NULL, NULL, NULL); if (iso) { printf("VF2 failure, 4 vertex directed graphs of isoclass %d and %d are not isomorphic. VF2 reports otherwise.\n", i, j); } } igraph_vector_ptr_destroy_all(&graphs4); } void test_bliss() { igraph_t ring1, ring2, directed_ring; igraph_vector_t perm; igraph_bool_t iso; igraph_bliss_info_t info; igraph_vector_int_t color; igraph_vector_ptr_t generators; igraph_ring(&ring1, 100, /*directed=*/ 0, /*mutual=*/ 0, /*circular=*/1); igraph_vector_init_seq(&perm, 0, igraph_vcount(&ring1) - 1); random_permutation(&perm); igraph_permute_vertices(&ring1, &ring2, &perm); igraph_ring(&directed_ring, 100, /* directed= */ 1, /* mutual = */0, /* circular = */1); igraph_vector_ptr_init(&generators, 0); IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(&generators, igraph_vector_destroy); igraph_isomorphic_bliss(&ring1, &ring2, NULL, NULL, &iso, NULL, NULL, IGRAPH_BLISS_F, NULL, NULL); if (! iso) { printf("Bliss failed on ring isomorphism.\n"); } igraph_automorphisms(&ring1, NULL, IGRAPH_BLISS_F, &info); if (strcmp(info.group_size, "200") != 0) { printf("Biss automorphism count failed: ring1.\n"); } igraph_free(info.group_size); igraph_automorphisms(&ring2, NULL, IGRAPH_BLISS_F, &info); if (strcmp(info.group_size, "200") != 0) { printf("Biss automorphism count failed: ring2.\n"); } igraph_free(info.group_size); igraph_automorphisms(&directed_ring, NULL, IGRAPH_BLISS_F, &info); if (strcmp(info.group_size, "100") != 0) { printf("Biss automorphism count failed: directed_ring.\n"); } igraph_free(info.group_size); // The follwing test is included so there is at least one call to igraph_automorphism_group // in the test suite. However, the generator set returned may depend on the splitting // heursitics as well as on the Bliss version. If the test fails, please verify manually // that the generating set is valid. For a undirected cycle graph like ring2, there should // be two generators: a cyclic permutation and a reversal of the vertex order. igraph_automorphism_group(&ring2, NULL, &generators, IGRAPH_BLISS_F, NULL); if (igraph_vector_ptr_size(&generators) != 2) printf("Bliss automorphism generators may have failed with ring2. " "Please verify the generators manually. " "Note that the generator set is not guaranteed to be minimal.\n"); igraph_vector_ptr_free_all(&generators); // For a directed ring, the only generator should be a cyclic permutation. igraph_automorphism_group(&directed_ring, NULL, &generators, IGRAPH_BLISS_F, NULL); if (igraph_vector_ptr_size(&generators) != 1) printf("Bliss automorphism generators may have failed with directed_ring. " "Please verify the generators manually. " "Note that the generator set is not guaranteed to be minimal.\n"); igraph_vector_ptr_free_all(&generators); igraph_vector_int_init_seq(&color, 0, igraph_vcount(&ring1) - 1); igraph_automorphisms(&ring1, &color, IGRAPH_BLISS_F, &info); if (strcmp(info.group_size, "1") != 0) { printf("Biss automorphism count with color failed: ring1.\n"); } igraph_free(info.group_size); // There's only one automorphism for this coloured graph, so the generating set is empty. igraph_automorphism_group(&ring1, &color, &generators, IGRAPH_BLISS_F, NULL); if (igraph_vector_ptr_size(&generators) != 0) { printf("Bliss automorphism generators failed with colored graph.\n"); } igraph_vector_ptr_destroy_all(&generators); igraph_vector_int_destroy(&color); igraph_vector_destroy(&perm); igraph_destroy(&ring1); igraph_destroy(&ring2); igraph_destroy(&directed_ring); } void test_bug_995() { igraph_t g1, g2; igraph_bool_t result; igraph_small(&g1, 3, 0, 0, 1, 1, 2, 2, 2, -1); igraph_small(&g2, 3, 0, 0, 1, 1, 2, 1, 1, -1); igraph_isomorphic(&g1, &g2, &result); if (result) { printf("igraph_isomorphic() failed with loop edges, see bug #995\n"); } igraph_destroy(&g1); igraph_destroy(&g2); } int main() { test3(); test4(); test_bliss(); test_bug_995(); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_degree.c0000644000076500000240000001457313612122633026660 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void print_vector(igraph_vector_t *v, FILE *f) { long int i; for (i = 0; i < igraph_vector_size(v); i++) { fprintf(f, " %li", (long int) VECTOR(*v)[i]); } fprintf(f, "\n"); } int main() { igraph_t g; igraph_vector_t v, seq; int ret; igraph_integer_t mdeg, nedges; long int i; long int ndeg; /* Create graph */ igraph_vector_init(&v, 8); VECTOR(v)[0] = 0; VECTOR(v)[1] = 1; VECTOR(v)[2] = 1; VECTOR(v)[3] = 2; VECTOR(v)[4] = 2; VECTOR(v)[5] = 3; VECTOR(v)[6] = 2; VECTOR(v)[7] = 2; igraph_create(&g, &v, 0, IGRAPH_DIRECTED); igraph_degree(&g, &v, igraph_vss_all(), IGRAPH_OUT, IGRAPH_NO_LOOPS); print_vector(&v, stdout); igraph_degree(&g, &v, igraph_vss_all(), IGRAPH_OUT, IGRAPH_LOOPS); print_vector(&v, stdout); igraph_degree(&g, &v, igraph_vss_all(), IGRAPH_IN, IGRAPH_NO_LOOPS); print_vector(&v, stdout); igraph_degree(&g, &v, igraph_vss_all(), IGRAPH_IN, IGRAPH_LOOPS); print_vector(&v, stdout); igraph_degree(&g, &v, igraph_vss_all(), IGRAPH_ALL, IGRAPH_NO_LOOPS); print_vector(&v, stdout); igraph_degree(&g, &v, igraph_vss_all(), IGRAPH_ALL, IGRAPH_LOOPS); print_vector(&v, stdout); igraph_set_error_handler(igraph_error_handler_ignore); /* Consistency check of the handshaking lemma. */ /* If d is the sum of all vertex degrees, then d = 2|E|. */ ndeg = 0; nedges = igraph_ecount(&g); for (i = 0; i < igraph_vector_size(&v); i++) { ndeg += (long int) VECTOR(v)[i]; } if (ndeg != 2 * nedges) { return 1; } igraph_destroy(&g); igraph_vector_resize(&v, 8); VECTOR(v)[0] = 0; VECTOR(v)[1] = 1; VECTOR(v)[2] = 1; VECTOR(v)[3] = 2; VECTOR(v)[4] = 2; VECTOR(v)[5] = 3; VECTOR(v)[6] = 2; VECTOR(v)[7] = 2; igraph_create(&g, &v, 0, IGRAPH_UNDIRECTED); igraph_degree(&g, &v, igraph_vss_all(), IGRAPH_OUT, IGRAPH_NO_LOOPS); print_vector(&v, stdout); igraph_degree(&g, &v, igraph_vss_all(), IGRAPH_OUT, IGRAPH_LOOPS); print_vector(&v, stdout); igraph_degree(&g, &v, igraph_vss_all(), IGRAPH_IN, IGRAPH_NO_LOOPS); print_vector(&v, stdout); igraph_degree(&g, &v, igraph_vss_all(), IGRAPH_IN, IGRAPH_LOOPS); print_vector(&v, stdout); igraph_degree(&g, &v, igraph_vss_all(), IGRAPH_ALL, IGRAPH_NO_LOOPS); print_vector(&v, stdout); igraph_degree(&g, &v, igraph_vss_all(), IGRAPH_ALL, IGRAPH_LOOPS); print_vector(&v, stdout); /* Consistency check of the handshaking lemma. */ /* If d is the sum of all vertex degrees, then d = 2|E|. */ ndeg = 0; nedges = igraph_ecount(&g); for (i = 0; i < igraph_vector_size(&v); i++) { ndeg += (long int) VECTOR(v)[i]; } if (ndeg != 2 * nedges) { return 2; } /* Degree of the same vertex multiple times */ igraph_vector_init(&seq, 3); VECTOR(seq)[0] = 2; VECTOR(seq)[1] = 0; VECTOR(seq)[2] = 2; igraph_degree(&g, &v, igraph_vss_vector(&seq), IGRAPH_ALL, IGRAPH_LOOPS); print_vector(&v, stdout); /* Errors */ ret = igraph_degree(&g, &v, igraph_vss_vector(&seq), (igraph_neimode_t)0, IGRAPH_LOOPS); if (ret != IGRAPH_EINVMODE) { return 3; } VECTOR(seq)[0] = 4; ret = igraph_degree(&g, &v, igraph_vss_vector(&seq), IGRAPH_ALL, IGRAPH_LOOPS); if (ret != IGRAPH_EINVVID) { return 4; } igraph_destroy(&g); igraph_vector_destroy(&seq); /* Maximum degree */ igraph_ring(&g, 10, 0 /*undirected*/, 0 /*undirected*/, 0/*uncircular*/); igraph_maxdegree(&g, &mdeg, igraph_vss_all(), IGRAPH_ALL, IGRAPH_LOOPS); if (mdeg != 2) { return 5; } /* Consistency check of the handshaking lemma. */ /* If d is the sum of all vertex degrees, then d = 2|E|. */ igraph_degree(&g, &v, igraph_vss_all(), IGRAPH_ALL, IGRAPH_LOOPS); ndeg = 0; nedges = igraph_ecount(&g); for (i = 0; i < igraph_vector_size(&v); i++) { ndeg += (long int) VECTOR(v)[i]; } if (ndeg != 2 * nedges) { return 6; } igraph_destroy(&g); igraph_full(&g, 10, 0 /*undirected*/, 0/*no loops*/); igraph_maxdegree(&g, &mdeg, igraph_vss_all(), IGRAPH_ALL, IGRAPH_LOOPS); if (mdeg != 9) { return 7; } /* Consistency check of the handshaking lemma. */ /* If d is the sum of all vertex degrees, then d = 2|E|. */ igraph_degree(&g, &v, igraph_vss_all(), IGRAPH_ALL, IGRAPH_LOOPS); ndeg = 0; nedges = igraph_ecount(&g); for (i = 0; i < igraph_vector_size(&v); i++) { ndeg += (long int) VECTOR(v)[i]; } if (ndeg != 2 * nedges) { return 8; } igraph_destroy(&g); igraph_star(&g, 10, IGRAPH_STAR_OUT, 0); igraph_maxdegree(&g, &mdeg, igraph_vss_all(), IGRAPH_OUT, IGRAPH_LOOPS); if (mdeg != 9) { return 9; } igraph_maxdegree(&g, &mdeg, igraph_vss_all(), IGRAPH_IN, IGRAPH_LOOPS); if (mdeg != 1) { return 10; } igraph_maxdegree(&g, &mdeg, igraph_vss_all(), IGRAPH_ALL, IGRAPH_LOOPS); if (mdeg != 9) { return 11; } /* Consistency check of the handshaking lemma. */ /* If d is the sum of all vertex degrees, then d = 2|E|. */ igraph_degree(&g, &v, igraph_vss_all(), IGRAPH_ALL, IGRAPH_LOOPS); ndeg = 0; nedges = igraph_ecount(&g); for (i = 0; i < igraph_vector_size(&v); i++) { ndeg += (long int) VECTOR(v)[i]; } if (ndeg != 2 * nedges) { return 12; } igraph_destroy(&g); igraph_vector_destroy(&v); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_write_graph_leda.out0000644000076500000240000000176513524616144031320 0ustar tamasstaff00000000000000LEDA.GRAPH void void -1 # Vertices 5 |{}| |{}| |{}| |{}| |{}| # Edges 5 1 2 0 |{}| 2 3 0 |{}| 3 4 0 |{}| 4 5 0 |{}| 5 1 0 |{}| === LEDA.GRAPH void void -2 # Vertices 5 |{}| |{}| |{}| |{}| |{}| # Edges 5 1 2 0 |{}| 1 5 0 |{}| 2 3 0 |{}| 3 4 0 |{}| 4 5 0 |{}| === LEDA.GRAPH float void -1 # Vertices 5 |{5}| |{6}| |{7}| |{8}| |{9}| # Edges 5 1 2 0 |{}| 2 3 0 |{}| 3 4 0 |{}| 4 5 0 |{}| 5 1 0 |{}| === LEDA.GRAPH string void -1 # Vertices 5 |{foo}| |{bar}| |{baz}| |{spam}| |{eggs}| # Edges 5 1 2 0 |{}| 2 3 0 |{}| 3 4 0 |{}| 4 5 0 |{}| 5 1 0 |{}| === LEDA.GRAPH void float -2 # Vertices 5 |{}| |{}| |{}| |{}| |{}| # Edges 5 1 2 0 |{5}| 1 5 0 |{9}| 2 3 0 |{6}| 3 4 0 |{7}| 4 5 0 |{8}| === LEDA.GRAPH void string -2 # Vertices 5 |{}| |{}| |{}| |{}| |{}| # Edges 5 1 2 0 |{foo}| 1 5 0 |{eggs}| 2 3 0 |{bar}| 3 4 0 |{baz}| 4 5 0 |{spam}| === LEDA.GRAPH void float -2 # Vertices 5 |{}| |{}| |{}| |{}| |{}| # Edges 5 1 2 0 |{123456789}| 1 5 0 |{123456793}| 2 3 0 |{123456790}| 3 4 0 |{123456791}| 4 5 0 |{123456792}| === python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_es_fromto.c0000644000076500000240000000473013612122633027414 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void igraph_vector_print(const igraph_vector_t *v) { long int i; for (i = 0; i < igraph_vector_size(v); i++) { printf("%li ", (long int)VECTOR(*v)[i]); } printf("\n"); } int main() { igraph_t g; const igraph_vector_t v = IGRAPH_VECTOR_NULL; igraph_real_t edges1[] = { 0, 1, 1, 2, 2, 2, 2, 3, 2, 4, 3, 4 }; igraph_vector_t from, to; igraph_es_t it; igraph_integer_t size; long int i; igraph_vector_view(&v, edges1, sizeof(edges1) / sizeof(igraph_real_t)); /******************************************/ /* Directed graph */ /******************************************/ igraph_create(&g, &v, 0, IGRAPH_DIRECTED); /* {0,1} -> {2,3}, result should be { 1->2 } */ igraph_vector_init(&from, 2); VECTOR(from)[0] = 0; VECTOR(from)[1] = 1; igraph_vector_init(&to, 2); VECTOR(to) [0] = 2; VECTOR(to) [1] = 3; igraph_es_fromto(&g, &it, IGRAPH_VS_VECTOR(&g, &from), IGRAPH_VS_VECTOR(&g, &to), IGRAPH_DIRECTED); igraph_vector_clear(&from); igraph_vector_clear(&to); igraph_es_size(&g, &it, &size); printf("%ld\n", (long)size); while (!igraph_es_end(&g, &it)) { igraph_vector_push_back(&from, igraph_es_from(&g, &it)); igraph_vector_push_back(&to, igraph_es_to(&g, &it)); igraph_es_next(&g, &it); } igraph_vector_sort(&from); igraph_vector_sort(&to); igraph_vector_print(&from); igraph_vector_print(&to); igraph_es_destroy(&it); igraph_vector_destroy(&from); igraph_vector_destroy(&to); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_sparsemat2.c0000644000076500000240000001732013614300625027500 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include "igraph_blas_internal.h" #include "igraph_arpack_internal.h" int igraph_matrix_dgemv(const igraph_matrix_t *m, const igraph_vector_t *v, igraph_vector_t *res, igraph_real_t alpha, igraph_real_t beta, igraph_bool_t transpose_m) { int nrow = igraph_matrix_nrow(m); int ncol = igraph_matrix_ncol(m); long int vlen = igraph_vector_size(v); int one = 1; char t = transpose_m ? 't' : 'n'; long int input_len = transpose_m ? nrow : ncol; long int output_len = transpose_m ? ncol : nrow; if (vlen != input_len) { IGRAPH_ERROR("Matrix and vector sizes are incompatible", IGRAPH_EINVAL); } if (beta != 0 && igraph_vector_size(res) != output_len) { IGRAPH_ERROR("Non-zero beta and bad `res' vector size, possible mistake", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_vector_resize(res, output_len)); igraphdgemv_(&t, &nrow, &ncol, &alpha, &MATRIX(*m, 0, 0), &nrow, VECTOR(*v), &one, &beta, VECTOR(*res), &one); return 0; } int igraph_matrix_vector_prod(const igraph_matrix_t *m, const igraph_vector_t *v, igraph_vector_t *res) { return igraph_matrix_dgemv(m, v, res, 1.0, 0.0, /*transpose=*/ 0); } int my_dgemv(const igraph_matrix_t *m, const igraph_vector_t *v, igraph_vector_t *res, igraph_real_t alpha, igraph_real_t beta, igraph_bool_t transpose_m) { int nrow = igraph_matrix_nrow(m); int ncol = igraph_matrix_ncol(m); long int vlen = igraph_vector_size(v); int one = 1; char t = transpose_m ? 't' : 'n'; long int input_len = transpose_m ? nrow : ncol; long int output_len = transpose_m ? ncol : nrow; if (vlen != input_len) { IGRAPH_ERROR("Matrix and vector sizes are incompatible", IGRAPH_EINVAL); } if (beta != 0 && igraph_vector_size(res) != output_len) { IGRAPH_ERROR("Non-zero beta and bad `res' vector size, possible mistake", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_vector_resize(res, output_len)); igraphdgemv_(&t, &nrow, &ncol, &alpha, &MATRIX(*m, 0, 0), &nrow, VECTOR(*v), &one, &beta, VECTOR(*res), &one); return 0; } int my_gaxpy(const igraph_matrix_t *m, const igraph_vector_t *v, igraph_vector_t *res) { return my_dgemv(m, v, res, 1.0, 0.0, /*transpose=*/ 0); } int my_dgemm(const igraph_matrix_t *m1, const igraph_matrix_t *m2, igraph_matrix_t *res) { long int m1_r = igraph_matrix_nrow(m1); long int m1_c = igraph_matrix_ncol(m1); long int m2_r = igraph_matrix_nrow(m2); long int m2_c = igraph_matrix_ncol(m2); long int i, j, k; if (m1_c != m2_r) { IGRAPH_ERROR("Cannot multiply matrices, invalid dimensions", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_matrix_resize(res, m1_r, m2_c)); igraph_matrix_null(res); for (i = 0; i < m1_r; i++) { for (j = 0; j < m2_c; j++) { for (k = 0; k < m1_c /* which is also m2_r*/; k++) { MATRIX(*res, i, j) += MATRIX(*m1, i, k) * MATRIX(*m2, k, j); } } } return 0; } igraph_bool_t check_same(const igraph_sparsemat_t *A, const igraph_matrix_t *M) { long int nrow = igraph_sparsemat_nrow(A); long int ncol = igraph_sparsemat_ncol(A); long int j, p, nzero = 0; if (nrow != igraph_matrix_nrow(M) || ncol != igraph_matrix_ncol(M)) { return 0; } for (j = 0; j < A->cs->n; j++) { for (p = A->cs->p[j]; p < A->cs->p[j + 1]; p++) { long int to = A->cs->i[p]; igraph_real_t value = A->cs->x[p]; if (value != MATRIX(*M, to, j)) { return 0; } nzero += 1; } } for (j = 0; j < nrow; j++) { for (p = 0; p < ncol; p++) { if (MATRIX(*M, j, p) != 0) { nzero -= 1; } } } return nzero == 0; } int main() { igraph_sparsemat_t A, B, C, D; igraph_vector_t v, w, x, y; igraph_matrix_t M, N, O; long int i; srand(1); /* Matrix-vector product */ #define NROW 10 #define NCOL 5 #define EDGES NROW*NCOL/3 igraph_matrix_init(&M, NROW, NCOL); igraph_sparsemat_init(&A, NROW, NCOL, EDGES); for (i = 0; i < EDGES; i++) { long int r = RNG_INTEGER(0, NROW - 1); long int c = RNG_INTEGER(0, NCOL - 1); igraph_real_t value = RNG_INTEGER(1, 5); MATRIX(M, r, c) = MATRIX(M, r, c) + value; igraph_sparsemat_entry(&A, r, c, value); } igraph_sparsemat_compress(&A, &B); igraph_sparsemat_destroy(&A); igraph_vector_init(&v, NCOL); igraph_vector_init(&w, NCOL); for (i = 0; i < NCOL; i++) { VECTOR(v)[i] = VECTOR(w)[i] = RNG_INTEGER(1, 5); } igraph_vector_init(&x, NROW); igraph_vector_init(&y, NROW); my_gaxpy(&M, &v, &x); igraph_vector_null(&y); igraph_sparsemat_gaxpy(&B, &w, &y); if (!igraph_vector_all_e(&x, &y)) { return 1; } igraph_vector_destroy(&x); igraph_vector_destroy(&y); igraph_vector_destroy(&v); igraph_vector_destroy(&w); igraph_sparsemat_destroy(&B); igraph_matrix_destroy(&M); #undef NROW #undef NCOL #undef EDGES /* Matrix-matrix product */ #define NROW_A 10 #define NCOL_A 7 #define EDGES_A NROW_A*NCOL_A/3 #define NROW_B 7 #define NCOL_B 9 #define EDGES_B NROW_B*NCOL_B/3 igraph_matrix_init(&M, NROW_A, NCOL_A); igraph_sparsemat_init(&A, NROW_A, NCOL_A, EDGES_A); for (i = 0; i < EDGES_A; i++) { long int r = RNG_INTEGER(0, NROW_A - 1); long int c = RNG_INTEGER(0, NCOL_A - 1); igraph_real_t value = RNG_INTEGER(1, 5); MATRIX(M, r, c) = MATRIX(M, r, c) + value; igraph_sparsemat_entry(&A, r, c, value); } igraph_sparsemat_compress(&A, &C); igraph_sparsemat_destroy(&A); igraph_matrix_init(&N, NROW_B, NCOL_B); igraph_sparsemat_init(&B, NROW_B, NCOL_B, EDGES_B); for (i = 0; i < EDGES_B; i++) { long int r = RNG_INTEGER(0, NROW_B - 1); long int c = RNG_INTEGER(0, NCOL_B - 1); igraph_real_t value = RNG_INTEGER(1, 5); MATRIX(N, r, c) = MATRIX(N, r, c) + value; igraph_sparsemat_entry(&B, r, c, value); } igraph_sparsemat_compress(&B, &D); igraph_sparsemat_destroy(&B); igraph_matrix_init(&O, 0, 0); my_dgemm(&M, &N, &O); igraph_sparsemat_multiply(&C, &D, &A); if (! check_same(&A, &O)) { return 2; } igraph_sparsemat_destroy(&C); igraph_sparsemat_destroy(&D); igraph_sparsemat_destroy(&A); igraph_matrix_destroy(&M); igraph_matrix_destroy(&N); igraph_matrix_destroy(&O); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_atlas.c0000644000076500000240000000300713612122633026517 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; int ret; igraph_atlas(&g, 45); igraph_write_graph_edgelist(&g, stdout); printf("\n"); igraph_destroy(&g); igraph_atlas(&g, 0); igraph_write_graph_edgelist(&g, stdout); printf("\n"); igraph_destroy(&g); igraph_atlas(&g, 1252); igraph_write_graph_edgelist(&g, stdout); printf("\n"); igraph_destroy(&g); igraph_set_error_handler(igraph_error_handler_ignore); ret = igraph_atlas(&g, -1); if (ret != IGRAPH_EINVAL) { return 1; } ret = igraph_atlas(&g, 1253); if (ret != IGRAPH_EINVAL) { return 2; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_read_graph_graphdb.c0000644000076500000240000000225513612122633031202 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; FILE *input; input = fopen("iso_b03_m1000.A00", "rb"); if (!input) { return 1; } igraph_read_graph_graphdb(&g, input, IGRAPH_DIRECTED); fclose(input); igraph_write_graph_edgelist(&g, stdout); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_realize_degree_sequence.out0000644000076500000240000000121413524616144032643 0ustar tamasstaff000000000000003 2 2 1 2 0 1 0 3 0 2 1 3 0 2 0 2 1 1 0 1 0 2 0 3 0 2 1 1 3 3 4 1 2 1 1 1 3 9 3 3 2 3 1 5 3 9 2 9 1 2 1 8 5 7 6 4 0 8 3 7 3 6 1 4 2 9 0 9 5 5 2 2 1 9 3 3 1 3 0 3 1 2 1 9 1 3 2 9 2 5 3 5 4 9 6 8 7 2 0 3 2 2 2 2 3 7 2 7 6 7 5 4 2 3 2 4 0 3 0 6 5 6 2 7 6 5 2 7 5 7 0 3 2 4 0 4 3 2 0 7 0 7 2 3 2 4 3 5 4 6 5 7 6 3 0 1 1 1 1 0 1 2 1 0 2 2 1 0 0 0 3 0 4 0 5 3 0 4 0 5 4 2 3 7 1 7 0 2 3 5 4 3 0 0 4 0 3 0 5 4 1 0 3 0 4 0 5 2 0 3 4 4 3 5 0 7 1 3 1 2 3 1 2 2 2 2 1 2 3 2 2 4 0 3 4 3 5 3 6 1 4 0 1 0 3 0 5 6 2 6 1 2 6 2 3 5 0 5 4 2 4 2 0 0 3 0 5 0 6 6 4 6 1 1 3 3 5 3 4 3 1 4 6 5 0 5 2 0 4 0 3 0 5 1 6 2 4 2 1 3 0 3 6 3 5 4 0 5 4 5 3 6 1 6 2 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_convex_hull.out0000644000076500000240000000074513524616144030343 0ustar tamasstaff00000000000000test_simple 1 6 5 3 9 5.000 1.000 1.000 3.000 2.000 5.000 6.000 4.000 9.000 2.000 test_collinear 4 0 11.000 -2.000 3.000 2.000 test_degenerate 1 0 5.000 1.000 3.000 2.000 0 3.000 2.000 test_bug_805 31 30 29 28 27 26 25 32 0.000 -4.000 -2.828 -2.828 -4.000 0.000 -2.828 2.828 0.000 4.000 2.828 2.828 4.000 0.000 2.828 -2.828 test_bug_1115 39 42 25 30 35 20 38 32 5.000 6.000 5.000 64.000 27.000 68.000 37.000 69.000 63.000 69.000 62.000 42.000 59.000 15.000 46.000 10.000 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_neighbors.c0000644000076500000240000000407613612122633027402 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void print_vector(igraph_vector_t *v, FILE *f) { long int i; for (i = 0; i < igraph_vector_size(v); i++) { fprintf(f, " %li", (long int) VECTOR(*v)[i]); } fprintf(f, "\n"); } int main() { igraph_t g; igraph_vector_t v; int ret; igraph_vector_init(&v, 8); VECTOR(v)[0] = 0; VECTOR(v)[1] = 1; VECTOR(v)[2] = 1; VECTOR(v)[3] = 2; VECTOR(v)[4] = 2; VECTOR(v)[5] = 3; VECTOR(v)[6] = 2; VECTOR(v)[7] = 2; igraph_create(&g, &v, 0, 1); igraph_neighbors(&g, &v, 2, IGRAPH_OUT); igraph_vector_sort(&v); print_vector(&v, stdout); igraph_neighbors(&g, &v, 2, IGRAPH_IN); igraph_vector_sort(&v); print_vector(&v, stdout); igraph_neighbors(&g, &v, 2, IGRAPH_ALL); igraph_vector_sort(&v); print_vector(&v, stdout); /* Errors */ igraph_set_error_handler(igraph_error_handler_ignore); ret = igraph_neighbors(&g, &v, 2, (igraph_neimode_t)0); /* conv for c++ */ if (ret != IGRAPH_EINVMODE) { return 1; } ret = igraph_neighbors(&g, &v, 4, IGRAPH_ALL); if (ret != IGRAPH_EINVVID) { return 2; } igraph_vector_destroy(&v); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_average_path_length.c0000644000076500000240000000245413612122633031407 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_real_t result; igraph_barabasi_game(&g, 30, /*power=*/ 1, 30, 0, 0, /*A=*/ 1, IGRAPH_DIRECTED, IGRAPH_BARABASI_BAG, /*start_from=*/ 0); igraph_average_path_length(&g, &result, IGRAPH_UNDIRECTED, 1); /* printf("Length of the average shortest paths: %f\n", (float) result); */ igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/ak-4102.max0000644000076500000240000143633613524616144025432 0ustar tamasstaff00000000000000c very bad maxflow problem p max 16414 24619 n 1 s n 2 t a 3 4 4103 a 3 4106 1 a 4 5 4102 a 4 4106 1 a 5 6 4101 a 5 4106 1 a 6 7 4100 a 6 4106 1 a 7 8 4099 a 7 4106 1 a 8 9 4098 a 8 4106 1 a 9 10 4097 a 9 4106 1 a 10 11 4096 a 10 4106 1 a 11 12 4095 a 11 4106 1 a 12 13 4094 a 12 4106 1 a 13 14 4093 a 13 4106 1 a 14 15 4092 a 14 4106 1 a 15 16 4091 a 15 4106 1 a 16 17 4090 a 16 4106 1 a 17 18 4089 a 17 4106 1 a 18 19 4088 a 18 4106 1 a 19 20 4087 a 19 4106 1 a 20 21 4086 a 20 4106 1 a 21 22 4085 a 21 4106 1 a 22 23 4084 a 22 4106 1 a 23 24 4083 a 23 4106 1 a 24 25 4082 a 24 4106 1 a 25 26 4081 a 25 4106 1 a 26 27 4080 a 26 4106 1 a 27 28 4079 a 27 4106 1 a 28 29 4078 a 28 4106 1 a 29 30 4077 a 29 4106 1 a 30 31 4076 a 30 4106 1 a 31 32 4075 a 31 4106 1 a 32 33 4074 a 32 4106 1 a 33 34 4073 a 33 4106 1 a 34 35 4072 a 34 4106 1 a 35 36 4071 a 35 4106 1 a 36 37 4070 a 36 4106 1 a 37 38 4069 a 37 4106 1 a 38 39 4068 a 38 4106 1 a 39 40 4067 a 39 4106 1 a 40 41 4066 a 40 4106 1 a 41 42 4065 a 41 4106 1 a 42 43 4064 a 42 4106 1 a 43 44 4063 a 43 4106 1 a 44 45 4062 a 44 4106 1 a 45 46 4061 a 45 4106 1 a 46 47 4060 a 46 4106 1 a 47 48 4059 a 47 4106 1 a 48 49 4058 a 48 4106 1 a 49 50 4057 a 49 4106 1 a 50 51 4056 a 50 4106 1 a 51 52 4055 a 51 4106 1 a 52 53 4054 a 52 4106 1 a 53 54 4053 a 53 4106 1 a 54 55 4052 a 54 4106 1 a 55 56 4051 a 55 4106 1 a 56 57 4050 a 56 4106 1 a 57 58 4049 a 57 4106 1 a 58 59 4048 a 58 4106 1 a 59 60 4047 a 59 4106 1 a 60 61 4046 a 60 4106 1 a 61 62 4045 a 61 4106 1 a 62 63 4044 a 62 4106 1 a 63 64 4043 a 63 4106 1 a 64 65 4042 a 64 4106 1 a 65 66 4041 a 65 4106 1 a 66 67 4040 a 66 4106 1 a 67 68 4039 a 67 4106 1 a 68 69 4038 a 68 4106 1 a 69 70 4037 a 69 4106 1 a 70 71 4036 a 70 4106 1 a 71 72 4035 a 71 4106 1 a 72 73 4034 a 72 4106 1 a 73 74 4033 a 73 4106 1 a 74 75 4032 a 74 4106 1 a 75 76 4031 a 75 4106 1 a 76 77 4030 a 76 4106 1 a 77 78 4029 a 77 4106 1 a 78 79 4028 a 78 4106 1 a 79 80 4027 a 79 4106 1 a 80 81 4026 a 80 4106 1 a 81 82 4025 a 81 4106 1 a 82 83 4024 a 82 4106 1 a 83 84 4023 a 83 4106 1 a 84 85 4022 a 84 4106 1 a 85 86 4021 a 85 4106 1 a 86 87 4020 a 86 4106 1 a 87 88 4019 a 87 4106 1 a 88 89 4018 a 88 4106 1 a 89 90 4017 a 89 4106 1 a 90 91 4016 a 90 4106 1 a 91 92 4015 a 91 4106 1 a 92 93 4014 a 92 4106 1 a 93 94 4013 a 93 4106 1 a 94 95 4012 a 94 4106 1 a 95 96 4011 a 95 4106 1 a 96 97 4010 a 96 4106 1 a 97 98 4009 a 97 4106 1 a 98 99 4008 a 98 4106 1 a 99 100 4007 a 99 4106 1 a 100 101 4006 a 100 4106 1 a 101 102 4005 a 101 4106 1 a 102 103 4004 a 102 4106 1 a 103 104 4003 a 103 4106 1 a 104 105 4002 a 104 4106 1 a 105 106 4001 a 105 4106 1 a 106 107 4000 a 106 4106 1 a 107 108 3999 a 107 4106 1 a 108 109 3998 a 108 4106 1 a 109 110 3997 a 109 4106 1 a 110 111 3996 a 110 4106 1 a 111 112 3995 a 111 4106 1 a 112 113 3994 a 112 4106 1 a 113 114 3993 a 113 4106 1 a 114 115 3992 a 114 4106 1 a 115 116 3991 a 115 4106 1 a 116 117 3990 a 116 4106 1 a 117 118 3989 a 117 4106 1 a 118 119 3988 a 118 4106 1 a 119 120 3987 a 119 4106 1 a 120 121 3986 a 120 4106 1 a 121 122 3985 a 121 4106 1 a 122 123 3984 a 122 4106 1 a 123 124 3983 a 123 4106 1 a 124 125 3982 a 124 4106 1 a 125 126 3981 a 125 4106 1 a 126 127 3980 a 126 4106 1 a 127 128 3979 a 127 4106 1 a 128 129 3978 a 128 4106 1 a 129 130 3977 a 129 4106 1 a 130 131 3976 a 130 4106 1 a 131 132 3975 a 131 4106 1 a 132 133 3974 a 132 4106 1 a 133 134 3973 a 133 4106 1 a 134 135 3972 a 134 4106 1 a 135 136 3971 a 135 4106 1 a 136 137 3970 a 136 4106 1 a 137 138 3969 a 137 4106 1 a 138 139 3968 a 138 4106 1 a 139 140 3967 a 139 4106 1 a 140 141 3966 a 140 4106 1 a 141 142 3965 a 141 4106 1 a 142 143 3964 a 142 4106 1 a 143 144 3963 a 143 4106 1 a 144 145 3962 a 144 4106 1 a 145 146 3961 a 145 4106 1 a 146 147 3960 a 146 4106 1 a 147 148 3959 a 147 4106 1 a 148 149 3958 a 148 4106 1 a 149 150 3957 a 149 4106 1 a 150 151 3956 a 150 4106 1 a 151 152 3955 a 151 4106 1 a 152 153 3954 a 152 4106 1 a 153 154 3953 a 153 4106 1 a 154 155 3952 a 154 4106 1 a 155 156 3951 a 155 4106 1 a 156 157 3950 a 156 4106 1 a 157 158 3949 a 157 4106 1 a 158 159 3948 a 158 4106 1 a 159 160 3947 a 159 4106 1 a 160 161 3946 a 160 4106 1 a 161 162 3945 a 161 4106 1 a 162 163 3944 a 162 4106 1 a 163 164 3943 a 163 4106 1 a 164 165 3942 a 164 4106 1 a 165 166 3941 a 165 4106 1 a 166 167 3940 a 166 4106 1 a 167 168 3939 a 167 4106 1 a 168 169 3938 a 168 4106 1 a 169 170 3937 a 169 4106 1 a 170 171 3936 a 170 4106 1 a 171 172 3935 a 171 4106 1 a 172 173 3934 a 172 4106 1 a 173 174 3933 a 173 4106 1 a 174 175 3932 a 174 4106 1 a 175 176 3931 a 175 4106 1 a 176 177 3930 a 176 4106 1 a 177 178 3929 a 177 4106 1 a 178 179 3928 a 178 4106 1 a 179 180 3927 a 179 4106 1 a 180 181 3926 a 180 4106 1 a 181 182 3925 a 181 4106 1 a 182 183 3924 a 182 4106 1 a 183 184 3923 a 183 4106 1 a 184 185 3922 a 184 4106 1 a 185 186 3921 a 185 4106 1 a 186 187 3920 a 186 4106 1 a 187 188 3919 a 187 4106 1 a 188 189 3918 a 188 4106 1 a 189 190 3917 a 189 4106 1 a 190 191 3916 a 190 4106 1 a 191 192 3915 a 191 4106 1 a 192 193 3914 a 192 4106 1 a 193 194 3913 a 193 4106 1 a 194 195 3912 a 194 4106 1 a 195 196 3911 a 195 4106 1 a 196 197 3910 a 196 4106 1 a 197 198 3909 a 197 4106 1 a 198 199 3908 a 198 4106 1 a 199 200 3907 a 199 4106 1 a 200 201 3906 a 200 4106 1 a 201 202 3905 a 201 4106 1 a 202 203 3904 a 202 4106 1 a 203 204 3903 a 203 4106 1 a 204 205 3902 a 204 4106 1 a 205 206 3901 a 205 4106 1 a 206 207 3900 a 206 4106 1 a 207 208 3899 a 207 4106 1 a 208 209 3898 a 208 4106 1 a 209 210 3897 a 209 4106 1 a 210 211 3896 a 210 4106 1 a 211 212 3895 a 211 4106 1 a 212 213 3894 a 212 4106 1 a 213 214 3893 a 213 4106 1 a 214 215 3892 a 214 4106 1 a 215 216 3891 a 215 4106 1 a 216 217 3890 a 216 4106 1 a 217 218 3889 a 217 4106 1 a 218 219 3888 a 218 4106 1 a 219 220 3887 a 219 4106 1 a 220 221 3886 a 220 4106 1 a 221 222 3885 a 221 4106 1 a 222 223 3884 a 222 4106 1 a 223 224 3883 a 223 4106 1 a 224 225 3882 a 224 4106 1 a 225 226 3881 a 225 4106 1 a 226 227 3880 a 226 4106 1 a 227 228 3879 a 227 4106 1 a 228 229 3878 a 228 4106 1 a 229 230 3877 a 229 4106 1 a 230 231 3876 a 230 4106 1 a 231 232 3875 a 231 4106 1 a 232 233 3874 a 232 4106 1 a 233 234 3873 a 233 4106 1 a 234 235 3872 a 234 4106 1 a 235 236 3871 a 235 4106 1 a 236 237 3870 a 236 4106 1 a 237 238 3869 a 237 4106 1 a 238 239 3868 a 238 4106 1 a 239 240 3867 a 239 4106 1 a 240 241 3866 a 240 4106 1 a 241 242 3865 a 241 4106 1 a 242 243 3864 a 242 4106 1 a 243 244 3863 a 243 4106 1 a 244 245 3862 a 244 4106 1 a 245 246 3861 a 245 4106 1 a 246 247 3860 a 246 4106 1 a 247 248 3859 a 247 4106 1 a 248 249 3858 a 248 4106 1 a 249 250 3857 a 249 4106 1 a 250 251 3856 a 250 4106 1 a 251 252 3855 a 251 4106 1 a 252 253 3854 a 252 4106 1 a 253 254 3853 a 253 4106 1 a 254 255 3852 a 254 4106 1 a 255 256 3851 a 255 4106 1 a 256 257 3850 a 256 4106 1 a 257 258 3849 a 257 4106 1 a 258 259 3848 a 258 4106 1 a 259 260 3847 a 259 4106 1 a 260 261 3846 a 260 4106 1 a 261 262 3845 a 261 4106 1 a 262 263 3844 a 262 4106 1 a 263 264 3843 a 263 4106 1 a 264 265 3842 a 264 4106 1 a 265 266 3841 a 265 4106 1 a 266 267 3840 a 266 4106 1 a 267 268 3839 a 267 4106 1 a 268 269 3838 a 268 4106 1 a 269 270 3837 a 269 4106 1 a 270 271 3836 a 270 4106 1 a 271 272 3835 a 271 4106 1 a 272 273 3834 a 272 4106 1 a 273 274 3833 a 273 4106 1 a 274 275 3832 a 274 4106 1 a 275 276 3831 a 275 4106 1 a 276 277 3830 a 276 4106 1 a 277 278 3829 a 277 4106 1 a 278 279 3828 a 278 4106 1 a 279 280 3827 a 279 4106 1 a 280 281 3826 a 280 4106 1 a 281 282 3825 a 281 4106 1 a 282 283 3824 a 282 4106 1 a 283 284 3823 a 283 4106 1 a 284 285 3822 a 284 4106 1 a 285 286 3821 a 285 4106 1 a 286 287 3820 a 286 4106 1 a 287 288 3819 a 287 4106 1 a 288 289 3818 a 288 4106 1 a 289 290 3817 a 289 4106 1 a 290 291 3816 a 290 4106 1 a 291 292 3815 a 291 4106 1 a 292 293 3814 a 292 4106 1 a 293 294 3813 a 293 4106 1 a 294 295 3812 a 294 4106 1 a 295 296 3811 a 295 4106 1 a 296 297 3810 a 296 4106 1 a 297 298 3809 a 297 4106 1 a 298 299 3808 a 298 4106 1 a 299 300 3807 a 299 4106 1 a 300 301 3806 a 300 4106 1 a 301 302 3805 a 301 4106 1 a 302 303 3804 a 302 4106 1 a 303 304 3803 a 303 4106 1 a 304 305 3802 a 304 4106 1 a 305 306 3801 a 305 4106 1 a 306 307 3800 a 306 4106 1 a 307 308 3799 a 307 4106 1 a 308 309 3798 a 308 4106 1 a 309 310 3797 a 309 4106 1 a 310 311 3796 a 310 4106 1 a 311 312 3795 a 311 4106 1 a 312 313 3794 a 312 4106 1 a 313 314 3793 a 313 4106 1 a 314 315 3792 a 314 4106 1 a 315 316 3791 a 315 4106 1 a 316 317 3790 a 316 4106 1 a 317 318 3789 a 317 4106 1 a 318 319 3788 a 318 4106 1 a 319 320 3787 a 319 4106 1 a 320 321 3786 a 320 4106 1 a 321 322 3785 a 321 4106 1 a 322 323 3784 a 322 4106 1 a 323 324 3783 a 323 4106 1 a 324 325 3782 a 324 4106 1 a 325 326 3781 a 325 4106 1 a 326 327 3780 a 326 4106 1 a 327 328 3779 a 327 4106 1 a 328 329 3778 a 328 4106 1 a 329 330 3777 a 329 4106 1 a 330 331 3776 a 330 4106 1 a 331 332 3775 a 331 4106 1 a 332 333 3774 a 332 4106 1 a 333 334 3773 a 333 4106 1 a 334 335 3772 a 334 4106 1 a 335 336 3771 a 335 4106 1 a 336 337 3770 a 336 4106 1 a 337 338 3769 a 337 4106 1 a 338 339 3768 a 338 4106 1 a 339 340 3767 a 339 4106 1 a 340 341 3766 a 340 4106 1 a 341 342 3765 a 341 4106 1 a 342 343 3764 a 342 4106 1 a 343 344 3763 a 343 4106 1 a 344 345 3762 a 344 4106 1 a 345 346 3761 a 345 4106 1 a 346 347 3760 a 346 4106 1 a 347 348 3759 a 347 4106 1 a 348 349 3758 a 348 4106 1 a 349 350 3757 a 349 4106 1 a 350 351 3756 a 350 4106 1 a 351 352 3755 a 351 4106 1 a 352 353 3754 a 352 4106 1 a 353 354 3753 a 353 4106 1 a 354 355 3752 a 354 4106 1 a 355 356 3751 a 355 4106 1 a 356 357 3750 a 356 4106 1 a 357 358 3749 a 357 4106 1 a 358 359 3748 a 358 4106 1 a 359 360 3747 a 359 4106 1 a 360 361 3746 a 360 4106 1 a 361 362 3745 a 361 4106 1 a 362 363 3744 a 362 4106 1 a 363 364 3743 a 363 4106 1 a 364 365 3742 a 364 4106 1 a 365 366 3741 a 365 4106 1 a 366 367 3740 a 366 4106 1 a 367 368 3739 a 367 4106 1 a 368 369 3738 a 368 4106 1 a 369 370 3737 a 369 4106 1 a 370 371 3736 a 370 4106 1 a 371 372 3735 a 371 4106 1 a 372 373 3734 a 372 4106 1 a 373 374 3733 a 373 4106 1 a 374 375 3732 a 374 4106 1 a 375 376 3731 a 375 4106 1 a 376 377 3730 a 376 4106 1 a 377 378 3729 a 377 4106 1 a 378 379 3728 a 378 4106 1 a 379 380 3727 a 379 4106 1 a 380 381 3726 a 380 4106 1 a 381 382 3725 a 381 4106 1 a 382 383 3724 a 382 4106 1 a 383 384 3723 a 383 4106 1 a 384 385 3722 a 384 4106 1 a 385 386 3721 a 385 4106 1 a 386 387 3720 a 386 4106 1 a 387 388 3719 a 387 4106 1 a 388 389 3718 a 388 4106 1 a 389 390 3717 a 389 4106 1 a 390 391 3716 a 390 4106 1 a 391 392 3715 a 391 4106 1 a 392 393 3714 a 392 4106 1 a 393 394 3713 a 393 4106 1 a 394 395 3712 a 394 4106 1 a 395 396 3711 a 395 4106 1 a 396 397 3710 a 396 4106 1 a 397 398 3709 a 397 4106 1 a 398 399 3708 a 398 4106 1 a 399 400 3707 a 399 4106 1 a 400 401 3706 a 400 4106 1 a 401 402 3705 a 401 4106 1 a 402 403 3704 a 402 4106 1 a 403 404 3703 a 403 4106 1 a 404 405 3702 a 404 4106 1 a 405 406 3701 a 405 4106 1 a 406 407 3700 a 406 4106 1 a 407 408 3699 a 407 4106 1 a 408 409 3698 a 408 4106 1 a 409 410 3697 a 409 4106 1 a 410 411 3696 a 410 4106 1 a 411 412 3695 a 411 4106 1 a 412 413 3694 a 412 4106 1 a 413 414 3693 a 413 4106 1 a 414 415 3692 a 414 4106 1 a 415 416 3691 a 415 4106 1 a 416 417 3690 a 416 4106 1 a 417 418 3689 a 417 4106 1 a 418 419 3688 a 418 4106 1 a 419 420 3687 a 419 4106 1 a 420 421 3686 a 420 4106 1 a 421 422 3685 a 421 4106 1 a 422 423 3684 a 422 4106 1 a 423 424 3683 a 423 4106 1 a 424 425 3682 a 424 4106 1 a 425 426 3681 a 425 4106 1 a 426 427 3680 a 426 4106 1 a 427 428 3679 a 427 4106 1 a 428 429 3678 a 428 4106 1 a 429 430 3677 a 429 4106 1 a 430 431 3676 a 430 4106 1 a 431 432 3675 a 431 4106 1 a 432 433 3674 a 432 4106 1 a 433 434 3673 a 433 4106 1 a 434 435 3672 a 434 4106 1 a 435 436 3671 a 435 4106 1 a 436 437 3670 a 436 4106 1 a 437 438 3669 a 437 4106 1 a 438 439 3668 a 438 4106 1 a 439 440 3667 a 439 4106 1 a 440 441 3666 a 440 4106 1 a 441 442 3665 a 441 4106 1 a 442 443 3664 a 442 4106 1 a 443 444 3663 a 443 4106 1 a 444 445 3662 a 444 4106 1 a 445 446 3661 a 445 4106 1 a 446 447 3660 a 446 4106 1 a 447 448 3659 a 447 4106 1 a 448 449 3658 a 448 4106 1 a 449 450 3657 a 449 4106 1 a 450 451 3656 a 450 4106 1 a 451 452 3655 a 451 4106 1 a 452 453 3654 a 452 4106 1 a 453 454 3653 a 453 4106 1 a 454 455 3652 a 454 4106 1 a 455 456 3651 a 455 4106 1 a 456 457 3650 a 456 4106 1 a 457 458 3649 a 457 4106 1 a 458 459 3648 a 458 4106 1 a 459 460 3647 a 459 4106 1 a 460 461 3646 a 460 4106 1 a 461 462 3645 a 461 4106 1 a 462 463 3644 a 462 4106 1 a 463 464 3643 a 463 4106 1 a 464 465 3642 a 464 4106 1 a 465 466 3641 a 465 4106 1 a 466 467 3640 a 466 4106 1 a 467 468 3639 a 467 4106 1 a 468 469 3638 a 468 4106 1 a 469 470 3637 a 469 4106 1 a 470 471 3636 a 470 4106 1 a 471 472 3635 a 471 4106 1 a 472 473 3634 a 472 4106 1 a 473 474 3633 a 473 4106 1 a 474 475 3632 a 474 4106 1 a 475 476 3631 a 475 4106 1 a 476 477 3630 a 476 4106 1 a 477 478 3629 a 477 4106 1 a 478 479 3628 a 478 4106 1 a 479 480 3627 a 479 4106 1 a 480 481 3626 a 480 4106 1 a 481 482 3625 a 481 4106 1 a 482 483 3624 a 482 4106 1 a 483 484 3623 a 483 4106 1 a 484 485 3622 a 484 4106 1 a 485 486 3621 a 485 4106 1 a 486 487 3620 a 486 4106 1 a 487 488 3619 a 487 4106 1 a 488 489 3618 a 488 4106 1 a 489 490 3617 a 489 4106 1 a 490 491 3616 a 490 4106 1 a 491 492 3615 a 491 4106 1 a 492 493 3614 a 492 4106 1 a 493 494 3613 a 493 4106 1 a 494 495 3612 a 494 4106 1 a 495 496 3611 a 495 4106 1 a 496 497 3610 a 496 4106 1 a 497 498 3609 a 497 4106 1 a 498 499 3608 a 498 4106 1 a 499 500 3607 a 499 4106 1 a 500 501 3606 a 500 4106 1 a 501 502 3605 a 501 4106 1 a 502 503 3604 a 502 4106 1 a 503 504 3603 a 503 4106 1 a 504 505 3602 a 504 4106 1 a 505 506 3601 a 505 4106 1 a 506 507 3600 a 506 4106 1 a 507 508 3599 a 507 4106 1 a 508 509 3598 a 508 4106 1 a 509 510 3597 a 509 4106 1 a 510 511 3596 a 510 4106 1 a 511 512 3595 a 511 4106 1 a 512 513 3594 a 512 4106 1 a 513 514 3593 a 513 4106 1 a 514 515 3592 a 514 4106 1 a 515 516 3591 a 515 4106 1 a 516 517 3590 a 516 4106 1 a 517 518 3589 a 517 4106 1 a 518 519 3588 a 518 4106 1 a 519 520 3587 a 519 4106 1 a 520 521 3586 a 520 4106 1 a 521 522 3585 a 521 4106 1 a 522 523 3584 a 522 4106 1 a 523 524 3583 a 523 4106 1 a 524 525 3582 a 524 4106 1 a 525 526 3581 a 525 4106 1 a 526 527 3580 a 526 4106 1 a 527 528 3579 a 527 4106 1 a 528 529 3578 a 528 4106 1 a 529 530 3577 a 529 4106 1 a 530 531 3576 a 530 4106 1 a 531 532 3575 a 531 4106 1 a 532 533 3574 a 532 4106 1 a 533 534 3573 a 533 4106 1 a 534 535 3572 a 534 4106 1 a 535 536 3571 a 535 4106 1 a 536 537 3570 a 536 4106 1 a 537 538 3569 a 537 4106 1 a 538 539 3568 a 538 4106 1 a 539 540 3567 a 539 4106 1 a 540 541 3566 a 540 4106 1 a 541 542 3565 a 541 4106 1 a 542 543 3564 a 542 4106 1 a 543 544 3563 a 543 4106 1 a 544 545 3562 a 544 4106 1 a 545 546 3561 a 545 4106 1 a 546 547 3560 a 546 4106 1 a 547 548 3559 a 547 4106 1 a 548 549 3558 a 548 4106 1 a 549 550 3557 a 549 4106 1 a 550 551 3556 a 550 4106 1 a 551 552 3555 a 551 4106 1 a 552 553 3554 a 552 4106 1 a 553 554 3553 a 553 4106 1 a 554 555 3552 a 554 4106 1 a 555 556 3551 a 555 4106 1 a 556 557 3550 a 556 4106 1 a 557 558 3549 a 557 4106 1 a 558 559 3548 a 558 4106 1 a 559 560 3547 a 559 4106 1 a 560 561 3546 a 560 4106 1 a 561 562 3545 a 561 4106 1 a 562 563 3544 a 562 4106 1 a 563 564 3543 a 563 4106 1 a 564 565 3542 a 564 4106 1 a 565 566 3541 a 565 4106 1 a 566 567 3540 a 566 4106 1 a 567 568 3539 a 567 4106 1 a 568 569 3538 a 568 4106 1 a 569 570 3537 a 569 4106 1 a 570 571 3536 a 570 4106 1 a 571 572 3535 a 571 4106 1 a 572 573 3534 a 572 4106 1 a 573 574 3533 a 573 4106 1 a 574 575 3532 a 574 4106 1 a 575 576 3531 a 575 4106 1 a 576 577 3530 a 576 4106 1 a 577 578 3529 a 577 4106 1 a 578 579 3528 a 578 4106 1 a 579 580 3527 a 579 4106 1 a 580 581 3526 a 580 4106 1 a 581 582 3525 a 581 4106 1 a 582 583 3524 a 582 4106 1 a 583 584 3523 a 583 4106 1 a 584 585 3522 a 584 4106 1 a 585 586 3521 a 585 4106 1 a 586 587 3520 a 586 4106 1 a 587 588 3519 a 587 4106 1 a 588 589 3518 a 588 4106 1 a 589 590 3517 a 589 4106 1 a 590 591 3516 a 590 4106 1 a 591 592 3515 a 591 4106 1 a 592 593 3514 a 592 4106 1 a 593 594 3513 a 593 4106 1 a 594 595 3512 a 594 4106 1 a 595 596 3511 a 595 4106 1 a 596 597 3510 a 596 4106 1 a 597 598 3509 a 597 4106 1 a 598 599 3508 a 598 4106 1 a 599 600 3507 a 599 4106 1 a 600 601 3506 a 600 4106 1 a 601 602 3505 a 601 4106 1 a 602 603 3504 a 602 4106 1 a 603 604 3503 a 603 4106 1 a 604 605 3502 a 604 4106 1 a 605 606 3501 a 605 4106 1 a 606 607 3500 a 606 4106 1 a 607 608 3499 a 607 4106 1 a 608 609 3498 a 608 4106 1 a 609 610 3497 a 609 4106 1 a 610 611 3496 a 610 4106 1 a 611 612 3495 a 611 4106 1 a 612 613 3494 a 612 4106 1 a 613 614 3493 a 613 4106 1 a 614 615 3492 a 614 4106 1 a 615 616 3491 a 615 4106 1 a 616 617 3490 a 616 4106 1 a 617 618 3489 a 617 4106 1 a 618 619 3488 a 618 4106 1 a 619 620 3487 a 619 4106 1 a 620 621 3486 a 620 4106 1 a 621 622 3485 a 621 4106 1 a 622 623 3484 a 622 4106 1 a 623 624 3483 a 623 4106 1 a 624 625 3482 a 624 4106 1 a 625 626 3481 a 625 4106 1 a 626 627 3480 a 626 4106 1 a 627 628 3479 a 627 4106 1 a 628 629 3478 a 628 4106 1 a 629 630 3477 a 629 4106 1 a 630 631 3476 a 630 4106 1 a 631 632 3475 a 631 4106 1 a 632 633 3474 a 632 4106 1 a 633 634 3473 a 633 4106 1 a 634 635 3472 a 634 4106 1 a 635 636 3471 a 635 4106 1 a 636 637 3470 a 636 4106 1 a 637 638 3469 a 637 4106 1 a 638 639 3468 a 638 4106 1 a 639 640 3467 a 639 4106 1 a 640 641 3466 a 640 4106 1 a 641 642 3465 a 641 4106 1 a 642 643 3464 a 642 4106 1 a 643 644 3463 a 643 4106 1 a 644 645 3462 a 644 4106 1 a 645 646 3461 a 645 4106 1 a 646 647 3460 a 646 4106 1 a 647 648 3459 a 647 4106 1 a 648 649 3458 a 648 4106 1 a 649 650 3457 a 649 4106 1 a 650 651 3456 a 650 4106 1 a 651 652 3455 a 651 4106 1 a 652 653 3454 a 652 4106 1 a 653 654 3453 a 653 4106 1 a 654 655 3452 a 654 4106 1 a 655 656 3451 a 655 4106 1 a 656 657 3450 a 656 4106 1 a 657 658 3449 a 657 4106 1 a 658 659 3448 a 658 4106 1 a 659 660 3447 a 659 4106 1 a 660 661 3446 a 660 4106 1 a 661 662 3445 a 661 4106 1 a 662 663 3444 a 662 4106 1 a 663 664 3443 a 663 4106 1 a 664 665 3442 a 664 4106 1 a 665 666 3441 a 665 4106 1 a 666 667 3440 a 666 4106 1 a 667 668 3439 a 667 4106 1 a 668 669 3438 a 668 4106 1 a 669 670 3437 a 669 4106 1 a 670 671 3436 a 670 4106 1 a 671 672 3435 a 671 4106 1 a 672 673 3434 a 672 4106 1 a 673 674 3433 a 673 4106 1 a 674 675 3432 a 674 4106 1 a 675 676 3431 a 675 4106 1 a 676 677 3430 a 676 4106 1 a 677 678 3429 a 677 4106 1 a 678 679 3428 a 678 4106 1 a 679 680 3427 a 679 4106 1 a 680 681 3426 a 680 4106 1 a 681 682 3425 a 681 4106 1 a 682 683 3424 a 682 4106 1 a 683 684 3423 a 683 4106 1 a 684 685 3422 a 684 4106 1 a 685 686 3421 a 685 4106 1 a 686 687 3420 a 686 4106 1 a 687 688 3419 a 687 4106 1 a 688 689 3418 a 688 4106 1 a 689 690 3417 a 689 4106 1 a 690 691 3416 a 690 4106 1 a 691 692 3415 a 691 4106 1 a 692 693 3414 a 692 4106 1 a 693 694 3413 a 693 4106 1 a 694 695 3412 a 694 4106 1 a 695 696 3411 a 695 4106 1 a 696 697 3410 a 696 4106 1 a 697 698 3409 a 697 4106 1 a 698 699 3408 a 698 4106 1 a 699 700 3407 a 699 4106 1 a 700 701 3406 a 700 4106 1 a 701 702 3405 a 701 4106 1 a 702 703 3404 a 702 4106 1 a 703 704 3403 a 703 4106 1 a 704 705 3402 a 704 4106 1 a 705 706 3401 a 705 4106 1 a 706 707 3400 a 706 4106 1 a 707 708 3399 a 707 4106 1 a 708 709 3398 a 708 4106 1 a 709 710 3397 a 709 4106 1 a 710 711 3396 a 710 4106 1 a 711 712 3395 a 711 4106 1 a 712 713 3394 a 712 4106 1 a 713 714 3393 a 713 4106 1 a 714 715 3392 a 714 4106 1 a 715 716 3391 a 715 4106 1 a 716 717 3390 a 716 4106 1 a 717 718 3389 a 717 4106 1 a 718 719 3388 a 718 4106 1 a 719 720 3387 a 719 4106 1 a 720 721 3386 a 720 4106 1 a 721 722 3385 a 721 4106 1 a 722 723 3384 a 722 4106 1 a 723 724 3383 a 723 4106 1 a 724 725 3382 a 724 4106 1 a 725 726 3381 a 725 4106 1 a 726 727 3380 a 726 4106 1 a 727 728 3379 a 727 4106 1 a 728 729 3378 a 728 4106 1 a 729 730 3377 a 729 4106 1 a 730 731 3376 a 730 4106 1 a 731 732 3375 a 731 4106 1 a 732 733 3374 a 732 4106 1 a 733 734 3373 a 733 4106 1 a 734 735 3372 a 734 4106 1 a 735 736 3371 a 735 4106 1 a 736 737 3370 a 736 4106 1 a 737 738 3369 a 737 4106 1 a 738 739 3368 a 738 4106 1 a 739 740 3367 a 739 4106 1 a 740 741 3366 a 740 4106 1 a 741 742 3365 a 741 4106 1 a 742 743 3364 a 742 4106 1 a 743 744 3363 a 743 4106 1 a 744 745 3362 a 744 4106 1 a 745 746 3361 a 745 4106 1 a 746 747 3360 a 746 4106 1 a 747 748 3359 a 747 4106 1 a 748 749 3358 a 748 4106 1 a 749 750 3357 a 749 4106 1 a 750 751 3356 a 750 4106 1 a 751 752 3355 a 751 4106 1 a 752 753 3354 a 752 4106 1 a 753 754 3353 a 753 4106 1 a 754 755 3352 a 754 4106 1 a 755 756 3351 a 755 4106 1 a 756 757 3350 a 756 4106 1 a 757 758 3349 a 757 4106 1 a 758 759 3348 a 758 4106 1 a 759 760 3347 a 759 4106 1 a 760 761 3346 a 760 4106 1 a 761 762 3345 a 761 4106 1 a 762 763 3344 a 762 4106 1 a 763 764 3343 a 763 4106 1 a 764 765 3342 a 764 4106 1 a 765 766 3341 a 765 4106 1 a 766 767 3340 a 766 4106 1 a 767 768 3339 a 767 4106 1 a 768 769 3338 a 768 4106 1 a 769 770 3337 a 769 4106 1 a 770 771 3336 a 770 4106 1 a 771 772 3335 a 771 4106 1 a 772 773 3334 a 772 4106 1 a 773 774 3333 a 773 4106 1 a 774 775 3332 a 774 4106 1 a 775 776 3331 a 775 4106 1 a 776 777 3330 a 776 4106 1 a 777 778 3329 a 777 4106 1 a 778 779 3328 a 778 4106 1 a 779 780 3327 a 779 4106 1 a 780 781 3326 a 780 4106 1 a 781 782 3325 a 781 4106 1 a 782 783 3324 a 782 4106 1 a 783 784 3323 a 783 4106 1 a 784 785 3322 a 784 4106 1 a 785 786 3321 a 785 4106 1 a 786 787 3320 a 786 4106 1 a 787 788 3319 a 787 4106 1 a 788 789 3318 a 788 4106 1 a 789 790 3317 a 789 4106 1 a 790 791 3316 a 790 4106 1 a 791 792 3315 a 791 4106 1 a 792 793 3314 a 792 4106 1 a 793 794 3313 a 793 4106 1 a 794 795 3312 a 794 4106 1 a 795 796 3311 a 795 4106 1 a 796 797 3310 a 796 4106 1 a 797 798 3309 a 797 4106 1 a 798 799 3308 a 798 4106 1 a 799 800 3307 a 799 4106 1 a 800 801 3306 a 800 4106 1 a 801 802 3305 a 801 4106 1 a 802 803 3304 a 802 4106 1 a 803 804 3303 a 803 4106 1 a 804 805 3302 a 804 4106 1 a 805 806 3301 a 805 4106 1 a 806 807 3300 a 806 4106 1 a 807 808 3299 a 807 4106 1 a 808 809 3298 a 808 4106 1 a 809 810 3297 a 809 4106 1 a 810 811 3296 a 810 4106 1 a 811 812 3295 a 811 4106 1 a 812 813 3294 a 812 4106 1 a 813 814 3293 a 813 4106 1 a 814 815 3292 a 814 4106 1 a 815 816 3291 a 815 4106 1 a 816 817 3290 a 816 4106 1 a 817 818 3289 a 817 4106 1 a 818 819 3288 a 818 4106 1 a 819 820 3287 a 819 4106 1 a 820 821 3286 a 820 4106 1 a 821 822 3285 a 821 4106 1 a 822 823 3284 a 822 4106 1 a 823 824 3283 a 823 4106 1 a 824 825 3282 a 824 4106 1 a 825 826 3281 a 825 4106 1 a 826 827 3280 a 826 4106 1 a 827 828 3279 a 827 4106 1 a 828 829 3278 a 828 4106 1 a 829 830 3277 a 829 4106 1 a 830 831 3276 a 830 4106 1 a 831 832 3275 a 831 4106 1 a 832 833 3274 a 832 4106 1 a 833 834 3273 a 833 4106 1 a 834 835 3272 a 834 4106 1 a 835 836 3271 a 835 4106 1 a 836 837 3270 a 836 4106 1 a 837 838 3269 a 837 4106 1 a 838 839 3268 a 838 4106 1 a 839 840 3267 a 839 4106 1 a 840 841 3266 a 840 4106 1 a 841 842 3265 a 841 4106 1 a 842 843 3264 a 842 4106 1 a 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2017 4106 1 a 2018 2019 2088 a 2018 4106 1 a 2019 2020 2087 a 2019 4106 1 a 2020 2021 2086 a 2020 4106 1 a 2021 2022 2085 a 2021 4106 1 a 2022 2023 2084 a 2022 4106 1 a 2023 2024 2083 a 2023 4106 1 a 2024 2025 2082 a 2024 4106 1 a 2025 2026 2081 a 2025 4106 1 a 2026 2027 2080 a 2026 4106 1 a 2027 2028 2079 a 2027 4106 1 a 2028 2029 2078 a 2028 4106 1 a 2029 2030 2077 a 2029 4106 1 a 2030 2031 2076 a 2030 4106 1 a 2031 2032 2075 a 2031 4106 1 a 2032 2033 2074 a 2032 4106 1 a 2033 2034 2073 a 2033 4106 1 a 2034 2035 2072 a 2034 4106 1 a 2035 2036 2071 a 2035 4106 1 a 2036 2037 2070 a 2036 4106 1 a 2037 2038 2069 a 2037 4106 1 a 2038 2039 2068 a 2038 4106 1 a 2039 2040 2067 a 2039 4106 1 a 2040 2041 2066 a 2040 4106 1 a 2041 2042 2065 a 2041 4106 1 a 2042 2043 2064 a 2042 4106 1 a 2043 2044 2063 a 2043 4106 1 a 2044 2045 2062 a 2044 4106 1 a 2045 2046 2061 a 2045 4106 1 a 2046 2047 2060 a 2046 4106 1 a 2047 2048 2059 a 2047 4106 1 a 2048 2049 2058 a 2048 4106 1 a 2049 2050 2057 a 2049 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2082 2083 2024 a 2082 4106 1 a 2083 2084 2023 a 2083 4106 1 a 2084 2085 2022 a 2084 4106 1 a 2085 2086 2021 a 2085 4106 1 a 2086 2087 2020 a 2086 4106 1 a 2087 2088 2019 a 2087 4106 1 a 2088 2089 2018 a 2088 4106 1 a 2089 2090 2017 a 2089 4106 1 a 2090 2091 2016 a 2090 4106 1 a 2091 2092 2015 a 2091 4106 1 a 2092 2093 2014 a 2092 4106 1 a 2093 2094 2013 a 2093 4106 1 a 2094 2095 2012 a 2094 4106 1 a 2095 2096 2011 a 2095 4106 1 a 2096 2097 2010 a 2096 4106 1 a 2097 2098 2009 a 2097 4106 1 a 2098 2099 2008 a 2098 4106 1 a 2099 2100 2007 a 2099 4106 1 a 2100 2101 2006 a 2100 4106 1 a 2101 2102 2005 a 2101 4106 1 a 2102 2103 2004 a 2102 4106 1 a 2103 2104 2003 a 2103 4106 1 a 2104 2105 2002 a 2104 4106 1 a 2105 2106 2001 a 2105 4106 1 a 2106 2107 2000 a 2106 4106 1 a 2107 2108 1999 a 2107 4106 1 a 2108 2109 1998 a 2108 4106 1 a 2109 2110 1997 a 2109 4106 1 a 2110 2111 1996 a 2110 4106 1 a 2111 2112 1995 a 2111 4106 1 a 2112 2113 1994 a 2112 4106 1 a 2113 2114 1993 a 2113 4106 1 a 2114 2115 1992 a 2114 4106 1 a 2115 2116 1991 a 2115 4106 1 a 2116 2117 1990 a 2116 4106 1 a 2117 2118 1989 a 2117 4106 1 a 2118 2119 1988 a 2118 4106 1 a 2119 2120 1987 a 2119 4106 1 a 2120 2121 1986 a 2120 4106 1 a 2121 2122 1985 a 2121 4106 1 a 2122 2123 1984 a 2122 4106 1 a 2123 2124 1983 a 2123 4106 1 a 2124 2125 1982 a 2124 4106 1 a 2125 2126 1981 a 2125 4106 1 a 2126 2127 1980 a 2126 4106 1 a 2127 2128 1979 a 2127 4106 1 a 2128 2129 1978 a 2128 4106 1 a 2129 2130 1977 a 2129 4106 1 a 2130 2131 1976 a 2130 4106 1 a 2131 2132 1975 a 2131 4106 1 a 2132 2133 1974 a 2132 4106 1 a 2133 2134 1973 a 2133 4106 1 a 2134 2135 1972 a 2134 4106 1 a 2135 2136 1971 a 2135 4106 1 a 2136 2137 1970 a 2136 4106 1 a 2137 2138 1969 a 2137 4106 1 a 2138 2139 1968 a 2138 4106 1 a 2139 2140 1967 a 2139 4106 1 a 2140 2141 1966 a 2140 4106 1 a 2141 2142 1965 a 2141 4106 1 a 2142 2143 1964 a 2142 4106 1 a 2143 2144 1963 a 2143 4106 1 a 2144 2145 1962 a 2144 4106 1 a 2145 2146 1961 a 2145 4106 1 a 2146 2147 1960 a 2146 4106 1 a 2147 2148 1959 a 2147 4106 1 a 2148 2149 1958 a 2148 4106 1 a 2149 2150 1957 a 2149 4106 1 a 2150 2151 1956 a 2150 4106 1 a 2151 2152 1955 a 2151 4106 1 a 2152 2153 1954 a 2152 4106 1 a 2153 2154 1953 a 2153 4106 1 a 2154 2155 1952 a 2154 4106 1 a 2155 2156 1951 a 2155 4106 1 a 2156 2157 1950 a 2156 4106 1 a 2157 2158 1949 a 2157 4106 1 a 2158 2159 1948 a 2158 4106 1 a 2159 2160 1947 a 2159 4106 1 a 2160 2161 1946 a 2160 4106 1 a 2161 2162 1945 a 2161 4106 1 a 2162 2163 1944 a 2162 4106 1 a 2163 2164 1943 a 2163 4106 1 a 2164 2165 1942 a 2164 4106 1 a 2165 2166 1941 a 2165 4106 1 a 2166 2167 1940 a 2166 4106 1 a 2167 2168 1939 a 2167 4106 1 a 2168 2169 1938 a 2168 4106 1 a 2169 2170 1937 a 2169 4106 1 a 2170 2171 1936 a 2170 4106 1 a 2171 2172 1935 a 2171 4106 1 a 2172 2173 1934 a 2172 4106 1 a 2173 2174 1933 a 2173 4106 1 a 2174 2175 1932 a 2174 4106 1 a 2175 2176 1931 a 2175 4106 1 a 2176 2177 1930 a 2176 4106 1 a 2177 2178 1929 a 2177 4106 1 a 2178 2179 1928 a 2178 4106 1 a 2179 2180 1927 a 2179 4106 1 a 2180 2181 1926 a 2180 4106 1 a 2181 2182 1925 a 2181 4106 1 a 2182 2183 1924 a 2182 4106 1 a 2183 2184 1923 a 2183 4106 1 a 2184 2185 1922 a 2184 4106 1 a 2185 2186 1921 a 2185 4106 1 a 2186 2187 1920 a 2186 4106 1 a 2187 2188 1919 a 2187 4106 1 a 2188 2189 1918 a 2188 4106 1 a 2189 2190 1917 a 2189 4106 1 a 2190 2191 1916 a 2190 4106 1 a 2191 2192 1915 a 2191 4106 1 a 2192 2193 1914 a 2192 4106 1 a 2193 2194 1913 a 2193 4106 1 a 2194 2195 1912 a 2194 4106 1 a 2195 2196 1911 a 2195 4106 1 a 2196 2197 1910 a 2196 4106 1 a 2197 2198 1909 a 2197 4106 1 a 2198 2199 1908 a 2198 4106 1 a 2199 2200 1907 a 2199 4106 1 a 2200 2201 1906 a 2200 4106 1 a 2201 2202 1905 a 2201 4106 1 a 2202 2203 1904 a 2202 4106 1 a 2203 2204 1903 a 2203 4106 1 a 2204 2205 1902 a 2204 4106 1 a 2205 2206 1901 a 2205 4106 1 a 2206 2207 1900 a 2206 4106 1 a 2207 2208 1899 a 2207 4106 1 a 2208 2209 1898 a 2208 4106 1 a 2209 2210 1897 a 2209 4106 1 a 2210 2211 1896 a 2210 4106 1 a 2211 2212 1895 a 2211 4106 1 a 2212 2213 1894 a 2212 4106 1 a 2213 2214 1893 a 2213 4106 1 a 2214 2215 1892 a 2214 4106 1 a 2215 2216 1891 a 2215 4106 1 a 2216 2217 1890 a 2216 4106 1 a 2217 2218 1889 a 2217 4106 1 a 2218 2219 1888 a 2218 4106 1 a 2219 2220 1887 a 2219 4106 1 a 2220 2221 1886 a 2220 4106 1 a 2221 2222 1885 a 2221 4106 1 a 2222 2223 1884 a 2222 4106 1 a 2223 2224 1883 a 2223 4106 1 a 2224 2225 1882 a 2224 4106 1 a 2225 2226 1881 a 2225 4106 1 a 2226 2227 1880 a 2226 4106 1 a 2227 2228 1879 a 2227 4106 1 a 2228 2229 1878 a 2228 4106 1 a 2229 2230 1877 a 2229 4106 1 a 2230 2231 1876 a 2230 4106 1 a 2231 2232 1875 a 2231 4106 1 a 2232 2233 1874 a 2232 4106 1 a 2233 2234 1873 a 2233 4106 1 a 2234 2235 1872 a 2234 4106 1 a 2235 2236 1871 a 2235 4106 1 a 2236 2237 1870 a 2236 4106 1 a 2237 2238 1869 a 2237 4106 1 a 2238 2239 1868 a 2238 4106 1 a 2239 2240 1867 a 2239 4106 1 a 2240 2241 1866 a 2240 4106 1 a 2241 2242 1865 a 2241 4106 1 a 2242 2243 1864 a 2242 4106 1 a 2243 2244 1863 a 2243 4106 1 a 2244 2245 1862 a 2244 4106 1 a 2245 2246 1861 a 2245 4106 1 a 2246 2247 1860 a 2246 4106 1 a 2247 2248 1859 a 2247 4106 1 a 2248 2249 1858 a 2248 4106 1 a 2249 2250 1857 a 2249 4106 1 a 2250 2251 1856 a 2250 4106 1 a 2251 2252 1855 a 2251 4106 1 a 2252 2253 1854 a 2252 4106 1 a 2253 2254 1853 a 2253 4106 1 a 2254 2255 1852 a 2254 4106 1 a 2255 2256 1851 a 2255 4106 1 a 2256 2257 1850 a 2256 4106 1 a 2257 2258 1849 a 2257 4106 1 a 2258 2259 1848 a 2258 4106 1 a 2259 2260 1847 a 2259 4106 1 a 2260 2261 1846 a 2260 4106 1 a 2261 2262 1845 a 2261 4106 1 a 2262 2263 1844 a 2262 4106 1 a 2263 2264 1843 a 2263 4106 1 a 2264 2265 1842 a 2264 4106 1 a 2265 2266 1841 a 2265 4106 1 a 2266 2267 1840 a 2266 4106 1 a 2267 2268 1839 a 2267 4106 1 a 2268 2269 1838 a 2268 4106 1 a 2269 2270 1837 a 2269 4106 1 a 2270 2271 1836 a 2270 4106 1 a 2271 2272 1835 a 2271 4106 1 a 2272 2273 1834 a 2272 4106 1 a 2273 2274 1833 a 2273 4106 1 a 2274 2275 1832 a 2274 4106 1 a 2275 2276 1831 a 2275 4106 1 a 2276 2277 1830 a 2276 4106 1 a 2277 2278 1829 a 2277 4106 1 a 2278 2279 1828 a 2278 4106 1 a 2279 2280 1827 a 2279 4106 1 a 2280 2281 1826 a 2280 4106 1 a 2281 2282 1825 a 2281 4106 1 a 2282 2283 1824 a 2282 4106 1 a 2283 2284 1823 a 2283 4106 1 a 2284 2285 1822 a 2284 4106 1 a 2285 2286 1821 a 2285 4106 1 a 2286 2287 1820 a 2286 4106 1 a 2287 2288 1819 a 2287 4106 1 a 2288 2289 1818 a 2288 4106 1 a 2289 2290 1817 a 2289 4106 1 a 2290 2291 1816 a 2290 4106 1 a 2291 2292 1815 a 2291 4106 1 a 2292 2293 1814 a 2292 4106 1 a 2293 2294 1813 a 2293 4106 1 a 2294 2295 1812 a 2294 4106 1 a 2295 2296 1811 a 2295 4106 1 a 2296 2297 1810 a 2296 4106 1 a 2297 2298 1809 a 2297 4106 1 a 2298 2299 1808 a 2298 4106 1 a 2299 2300 1807 a 2299 4106 1 a 2300 2301 1806 a 2300 4106 1 a 2301 2302 1805 a 2301 4106 1 a 2302 2303 1804 a 2302 4106 1 a 2303 2304 1803 a 2303 4106 1 a 2304 2305 1802 a 2304 4106 1 a 2305 2306 1801 a 2305 4106 1 a 2306 2307 1800 a 2306 4106 1 a 2307 2308 1799 a 2307 4106 1 a 2308 2309 1798 a 2308 4106 1 a 2309 2310 1797 a 2309 4106 1 a 2310 2311 1796 a 2310 4106 1 a 2311 2312 1795 a 2311 4106 1 a 2312 2313 1794 a 2312 4106 1 a 2313 2314 1793 a 2313 4106 1 a 2314 2315 1792 a 2314 4106 1 a 2315 2316 1791 a 2315 4106 1 a 2316 2317 1790 a 2316 4106 1 a 2317 2318 1789 a 2317 4106 1 a 2318 2319 1788 a 2318 4106 1 a 2319 2320 1787 a 2319 4106 1 a 2320 2321 1786 a 2320 4106 1 a 2321 2322 1785 a 2321 4106 1 a 2322 2323 1784 a 2322 4106 1 a 2323 2324 1783 a 2323 4106 1 a 2324 2325 1782 a 2324 4106 1 a 2325 2326 1781 a 2325 4106 1 a 2326 2327 1780 a 2326 4106 1 a 2327 2328 1779 a 2327 4106 1 a 2328 2329 1778 a 2328 4106 1 a 2329 2330 1777 a 2329 4106 1 a 2330 2331 1776 a 2330 4106 1 a 2331 2332 1775 a 2331 4106 1 a 2332 2333 1774 a 2332 4106 1 a 2333 2334 1773 a 2333 4106 1 a 2334 2335 1772 a 2334 4106 1 a 2335 2336 1771 a 2335 4106 1 a 2336 2337 1770 a 2336 4106 1 a 2337 2338 1769 a 2337 4106 1 a 2338 2339 1768 a 2338 4106 1 a 2339 2340 1767 a 2339 4106 1 a 2340 2341 1766 a 2340 4106 1 a 2341 2342 1765 a 2341 4106 1 a 2342 2343 1764 a 2342 4106 1 a 2343 2344 1763 a 2343 4106 1 a 2344 2345 1762 a 2344 4106 1 a 2345 2346 1761 a 2345 4106 1 a 2346 2347 1760 a 2346 4106 1 a 2347 2348 1759 a 2347 4106 1 a 2348 2349 1758 a 2348 4106 1 a 2349 2350 1757 a 2349 4106 1 a 2350 2351 1756 a 2350 4106 1 a 2351 2352 1755 a 2351 4106 1 a 2352 2353 1754 a 2352 4106 1 a 2353 2354 1753 a 2353 4106 1 a 2354 2355 1752 a 2354 4106 1 a 2355 2356 1751 a 2355 4106 1 a 2356 2357 1750 a 2356 4106 1 a 2357 2358 1749 a 2357 4106 1 a 2358 2359 1748 a 2358 4106 1 a 2359 2360 1747 a 2359 4106 1 a 2360 2361 1746 a 2360 4106 1 a 2361 2362 1745 a 2361 4106 1 a 2362 2363 1744 a 2362 4106 1 a 2363 2364 1743 a 2363 4106 1 a 2364 2365 1742 a 2364 4106 1 a 2365 2366 1741 a 2365 4106 1 a 2366 2367 1740 a 2366 4106 1 a 2367 2368 1739 a 2367 4106 1 a 2368 2369 1738 a 2368 4106 1 a 2369 2370 1737 a 2369 4106 1 a 2370 2371 1736 a 2370 4106 1 a 2371 2372 1735 a 2371 4106 1 a 2372 2373 1734 a 2372 4106 1 a 2373 2374 1733 a 2373 4106 1 a 2374 2375 1732 a 2374 4106 1 a 2375 2376 1731 a 2375 4106 1 a 2376 2377 1730 a 2376 4106 1 a 2377 2378 1729 a 2377 4106 1 a 2378 2379 1728 a 2378 4106 1 a 2379 2380 1727 a 2379 4106 1 a 2380 2381 1726 a 2380 4106 1 a 2381 2382 1725 a 2381 4106 1 a 2382 2383 1724 a 2382 4106 1 a 2383 2384 1723 a 2383 4106 1 a 2384 2385 1722 a 2384 4106 1 a 2385 2386 1721 a 2385 4106 1 a 2386 2387 1720 a 2386 4106 1 a 2387 2388 1719 a 2387 4106 1 a 2388 2389 1718 a 2388 4106 1 a 2389 2390 1717 a 2389 4106 1 a 2390 2391 1716 a 2390 4106 1 a 2391 2392 1715 a 2391 4106 1 a 2392 2393 1714 a 2392 4106 1 a 2393 2394 1713 a 2393 4106 1 a 2394 2395 1712 a 2394 4106 1 a 2395 2396 1711 a 2395 4106 1 a 2396 2397 1710 a 2396 4106 1 a 2397 2398 1709 a 2397 4106 1 a 2398 2399 1708 a 2398 4106 1 a 2399 2400 1707 a 2399 4106 1 a 2400 2401 1706 a 2400 4106 1 a 2401 2402 1705 a 2401 4106 1 a 2402 2403 1704 a 2402 4106 1 a 2403 2404 1703 a 2403 4106 1 a 2404 2405 1702 a 2404 4106 1 a 2405 2406 1701 a 2405 4106 1 a 2406 2407 1700 a 2406 4106 1 a 2407 2408 1699 a 2407 4106 1 a 2408 2409 1698 a 2408 4106 1 a 2409 2410 1697 a 2409 4106 1 a 2410 2411 1696 a 2410 4106 1 a 2411 2412 1695 a 2411 4106 1 a 2412 2413 1694 a 2412 4106 1 a 2413 2414 1693 a 2413 4106 1 a 2414 2415 1692 a 2414 4106 1 a 2415 2416 1691 a 2415 4106 1 a 2416 2417 1690 a 2416 4106 1 a 2417 2418 1689 a 2417 4106 1 a 2418 2419 1688 a 2418 4106 1 a 2419 2420 1687 a 2419 4106 1 a 2420 2421 1686 a 2420 4106 1 a 2421 2422 1685 a 2421 4106 1 a 2422 2423 1684 a 2422 4106 1 a 2423 2424 1683 a 2423 4106 1 a 2424 2425 1682 a 2424 4106 1 a 2425 2426 1681 a 2425 4106 1 a 2426 2427 1680 a 2426 4106 1 a 2427 2428 1679 a 2427 4106 1 a 2428 2429 1678 a 2428 4106 1 a 2429 2430 1677 a 2429 4106 1 a 2430 2431 1676 a 2430 4106 1 a 2431 2432 1675 a 2431 4106 1 a 2432 2433 1674 a 2432 4106 1 a 2433 2434 1673 a 2433 4106 1 a 2434 2435 1672 a 2434 4106 1 a 2435 2436 1671 a 2435 4106 1 a 2436 2437 1670 a 2436 4106 1 a 2437 2438 1669 a 2437 4106 1 a 2438 2439 1668 a 2438 4106 1 a 2439 2440 1667 a 2439 4106 1 a 2440 2441 1666 a 2440 4106 1 a 2441 2442 1665 a 2441 4106 1 a 2442 2443 1664 a 2442 4106 1 a 2443 2444 1663 a 2443 4106 1 a 2444 2445 1662 a 2444 4106 1 a 2445 2446 1661 a 2445 4106 1 a 2446 2447 1660 a 2446 4106 1 a 2447 2448 1659 a 2447 4106 1 a 2448 2449 1658 a 2448 4106 1 a 2449 2450 1657 a 2449 4106 1 a 2450 2451 1656 a 2450 4106 1 a 2451 2452 1655 a 2451 4106 1 a 2452 2453 1654 a 2452 4106 1 a 2453 2454 1653 a 2453 4106 1 a 2454 2455 1652 a 2454 4106 1 a 2455 2456 1651 a 2455 4106 1 a 2456 2457 1650 a 2456 4106 1 a 2457 2458 1649 a 2457 4106 1 a 2458 2459 1648 a 2458 4106 1 a 2459 2460 1647 a 2459 4106 1 a 2460 2461 1646 a 2460 4106 1 a 2461 2462 1645 a 2461 4106 1 a 2462 2463 1644 a 2462 4106 1 a 2463 2464 1643 a 2463 4106 1 a 2464 2465 1642 a 2464 4106 1 a 2465 2466 1641 a 2465 4106 1 a 2466 2467 1640 a 2466 4106 1 a 2467 2468 1639 a 2467 4106 1 a 2468 2469 1638 a 2468 4106 1 a 2469 2470 1637 a 2469 4106 1 a 2470 2471 1636 a 2470 4106 1 a 2471 2472 1635 a 2471 4106 1 a 2472 2473 1634 a 2472 4106 1 a 2473 2474 1633 a 2473 4106 1 a 2474 2475 1632 a 2474 4106 1 a 2475 2476 1631 a 2475 4106 1 a 2476 2477 1630 a 2476 4106 1 a 2477 2478 1629 a 2477 4106 1 a 2478 2479 1628 a 2478 4106 1 a 2479 2480 1627 a 2479 4106 1 a 2480 2481 1626 a 2480 4106 1 a 2481 2482 1625 a 2481 4106 1 a 2482 2483 1624 a 2482 4106 1 a 2483 2484 1623 a 2483 4106 1 a 2484 2485 1622 a 2484 4106 1 a 2485 2486 1621 a 2485 4106 1 a 2486 2487 1620 a 2486 4106 1 a 2487 2488 1619 a 2487 4106 1 a 2488 2489 1618 a 2488 4106 1 a 2489 2490 1617 a 2489 4106 1 a 2490 2491 1616 a 2490 4106 1 a 2491 2492 1615 a 2491 4106 1 a 2492 2493 1614 a 2492 4106 1 a 2493 2494 1613 a 2493 4106 1 a 2494 2495 1612 a 2494 4106 1 a 2495 2496 1611 a 2495 4106 1 a 2496 2497 1610 a 2496 4106 1 a 2497 2498 1609 a 2497 4106 1 a 2498 2499 1608 a 2498 4106 1 a 2499 2500 1607 a 2499 4106 1 a 2500 2501 1606 a 2500 4106 1 a 2501 2502 1605 a 2501 4106 1 a 2502 2503 1604 a 2502 4106 1 a 2503 2504 1603 a 2503 4106 1 a 2504 2505 1602 a 2504 4106 1 a 2505 2506 1601 a 2505 4106 1 a 2506 2507 1600 a 2506 4106 1 a 2507 2508 1599 a 2507 4106 1 a 2508 2509 1598 a 2508 4106 1 a 2509 2510 1597 a 2509 4106 1 a 2510 2511 1596 a 2510 4106 1 a 2511 2512 1595 a 2511 4106 1 a 2512 2513 1594 a 2512 4106 1 a 2513 2514 1593 a 2513 4106 1 a 2514 2515 1592 a 2514 4106 1 a 2515 2516 1591 a 2515 4106 1 a 2516 2517 1590 a 2516 4106 1 a 2517 2518 1589 a 2517 4106 1 a 2518 2519 1588 a 2518 4106 1 a 2519 2520 1587 a 2519 4106 1 a 2520 2521 1586 a 2520 4106 1 a 2521 2522 1585 a 2521 4106 1 a 2522 2523 1584 a 2522 4106 1 a 2523 2524 1583 a 2523 4106 1 a 2524 2525 1582 a 2524 4106 1 a 2525 2526 1581 a 2525 4106 1 a 2526 2527 1580 a 2526 4106 1 a 2527 2528 1579 a 2527 4106 1 a 2528 2529 1578 a 2528 4106 1 a 2529 2530 1577 a 2529 4106 1 a 2530 2531 1576 a 2530 4106 1 a 2531 2532 1575 a 2531 4106 1 a 2532 2533 1574 a 2532 4106 1 a 2533 2534 1573 a 2533 4106 1 a 2534 2535 1572 a 2534 4106 1 a 2535 2536 1571 a 2535 4106 1 a 2536 2537 1570 a 2536 4106 1 a 2537 2538 1569 a 2537 4106 1 a 2538 2539 1568 a 2538 4106 1 a 2539 2540 1567 a 2539 4106 1 a 2540 2541 1566 a 2540 4106 1 a 2541 2542 1565 a 2541 4106 1 a 2542 2543 1564 a 2542 4106 1 a 2543 2544 1563 a 2543 4106 1 a 2544 2545 1562 a 2544 4106 1 a 2545 2546 1561 a 2545 4106 1 a 2546 2547 1560 a 2546 4106 1 a 2547 2548 1559 a 2547 4106 1 a 2548 2549 1558 a 2548 4106 1 a 2549 2550 1557 a 2549 4106 1 a 2550 2551 1556 a 2550 4106 1 a 2551 2552 1555 a 2551 4106 1 a 2552 2553 1554 a 2552 4106 1 a 2553 2554 1553 a 2553 4106 1 a 2554 2555 1552 a 2554 4106 1 a 2555 2556 1551 a 2555 4106 1 a 2556 2557 1550 a 2556 4106 1 a 2557 2558 1549 a 2557 4106 1 a 2558 2559 1548 a 2558 4106 1 a 2559 2560 1547 a 2559 4106 1 a 2560 2561 1546 a 2560 4106 1 a 2561 2562 1545 a 2561 4106 1 a 2562 2563 1544 a 2562 4106 1 a 2563 2564 1543 a 2563 4106 1 a 2564 2565 1542 a 2564 4106 1 a 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2822 4106 1 a 2823 2824 1283 a 2823 4106 1 a 2824 2825 1282 a 2824 4106 1 a 2825 2826 1281 a 2825 4106 1 a 2826 2827 1280 a 2826 4106 1 a 2827 2828 1279 a 2827 4106 1 a 2828 2829 1278 a 2828 4106 1 a 2829 2830 1277 a 2829 4106 1 a 2830 2831 1276 a 2830 4106 1 a 2831 2832 1275 a 2831 4106 1 a 2832 2833 1274 a 2832 4106 1 a 2833 2834 1273 a 2833 4106 1 a 2834 2835 1272 a 2834 4106 1 a 2835 2836 1271 a 2835 4106 1 a 2836 2837 1270 a 2836 4106 1 a 2837 2838 1269 a 2837 4106 1 a 2838 2839 1268 a 2838 4106 1 a 2839 2840 1267 a 2839 4106 1 a 2840 2841 1266 a 2840 4106 1 a 2841 2842 1265 a 2841 4106 1 a 2842 2843 1264 a 2842 4106 1 a 2843 2844 1263 a 2843 4106 1 a 2844 2845 1262 a 2844 4106 1 a 2845 2846 1261 a 2845 4106 1 a 2846 2847 1260 a 2846 4106 1 a 2847 2848 1259 a 2847 4106 1 a 2848 2849 1258 a 2848 4106 1 a 2849 2850 1257 a 2849 4106 1 a 2850 2851 1256 a 2850 4106 1 a 2851 2852 1255 a 2851 4106 1 a 2852 2853 1254 a 2852 4106 1 a 2853 2854 1253 a 2853 4106 1 a 2854 2855 1252 a 2854 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8756 15867 1 a 8757 15866 1 a 8758 15865 1 a 8759 15864 1 a 8760 15863 1 a 8761 15862 1 a 8762 15861 1 a 8763 15860 1 a 8764 15859 1 a 8765 15858 1 a 8766 15857 1 a 8767 15856 1 a 8768 15855 1 a 8769 15854 1 a 8770 15853 1 a 8771 15852 1 a 8772 15851 1 a 8773 15850 1 a 8774 15849 1 a 8775 15848 1 a 8776 15847 1 a 8777 15846 1 a 8778 15845 1 a 8779 15844 1 a 8780 15843 1 a 8781 15842 1 a 8782 15841 1 a 8783 15840 1 a 8784 15839 1 a 8785 15838 1 a 8786 15837 1 a 8787 15836 1 a 8788 15835 1 a 8789 15834 1 a 8790 15833 1 a 8791 15832 1 a 8792 15831 1 a 8793 15830 1 a 8794 15829 1 a 8795 15828 1 a 8796 15827 1 a 8797 15826 1 a 8798 15825 1 a 8799 15824 1 a 8800 15823 1 a 8801 15822 1 a 8802 15821 1 a 8803 15820 1 a 8804 15819 1 a 8805 15818 1 a 8806 15817 1 a 8807 15816 1 a 8808 15815 1 a 8809 15814 1 a 8810 15813 1 a 8811 15812 1 a 8812 15811 1 a 8813 15810 1 a 8814 15809 1 a 8815 15808 1 a 8816 15807 1 a 8817 15806 1 a 8818 15805 1 a 8819 15804 1 a 8820 15803 1 a 8821 15802 1 a 8822 15801 1 a 8823 15800 1 a 8824 15799 1 a 8825 15798 1 a 8826 15797 1 a 8827 15796 1 a 8828 15795 1 a 8829 15794 1 a 8830 15793 1 a 8831 15792 1 a 8832 15791 1 a 8833 15790 1 a 8834 15789 1 a 8835 15788 1 a 8836 15787 1 a 8837 15786 1 a 8838 15785 1 a 8839 15784 1 a 8840 15783 1 a 8841 15782 1 a 8842 15781 1 a 8843 15780 1 a 8844 15779 1 a 8845 15778 1 a 8846 15777 1 a 8847 15776 1 a 8848 15775 1 a 8849 15774 1 a 8850 15773 1 a 8851 15772 1 a 8852 15771 1 a 8853 15770 1 a 8854 15769 1 a 8855 15768 1 a 8856 15767 1 a 8857 15766 1 a 8858 15765 1 a 8859 15764 1 a 8860 15763 1 a 8861 15762 1 a 8862 15761 1 a 8863 15760 1 a 8864 15759 1 a 8865 15758 1 a 8866 15757 1 a 8867 15756 1 a 8868 15755 1 a 8869 15754 1 a 8870 15753 1 a 8871 15752 1 a 8872 15751 1 a 8873 15750 1 a 8874 15749 1 a 8875 15748 1 a 8876 15747 1 a 8877 15746 1 a 8878 15745 1 a 8879 15744 1 a 8880 15743 1 a 8881 15742 1 a 8882 15741 1 a 8883 15740 1 a 8884 15739 1 a 8885 15738 1 a 8886 15737 1 a 8887 15736 1 a 8888 15735 1 a 8889 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8956 15667 1 a 8957 15666 1 a 8958 15665 1 a 8959 15664 1 a 8960 15663 1 a 8961 15662 1 a 8962 15661 1 a 8963 15660 1 a 8964 15659 1 a 8965 15658 1 a 8966 15657 1 a 8967 15656 1 a 8968 15655 1 a 8969 15654 1 a 8970 15653 1 a 8971 15652 1 a 8972 15651 1 a 8973 15650 1 a 8974 15649 1 a 8975 15648 1 a 8976 15647 1 a 8977 15646 1 a 8978 15645 1 a 8979 15644 1 a 8980 15643 1 a 8981 15642 1 a 8982 15641 1 a 8983 15640 1 a 8984 15639 1 a 8985 15638 1 a 8986 15637 1 a 8987 15636 1 a 8988 15635 1 a 8989 15634 1 a 8990 15633 1 a 8991 15632 1 a 8992 15631 1 a 8993 15630 1 a 8994 15629 1 a 8995 15628 1 a 8996 15627 1 a 8997 15626 1 a 8998 15625 1 a 8999 15624 1 a 9000 15623 1 a 9001 15622 1 a 9002 15621 1 a 9003 15620 1 a 9004 15619 1 a 9005 15618 1 a 9006 15617 1 a 9007 15616 1 a 9008 15615 1 a 9009 15614 1 a 9010 15613 1 a 9011 15612 1 a 9012 15611 1 a 9013 15610 1 a 9014 15609 1 a 9015 15608 1 a 9016 15607 1 a 9017 15606 1 a 9018 15605 1 a 9019 15604 1 a 9020 15603 1 a 9021 15602 1 a 9022 15601 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15534 1 a 9090 15533 1 a 9091 15532 1 a 9092 15531 1 a 9093 15530 1 a 9094 15529 1 a 9095 15528 1 a 9096 15527 1 a 9097 15526 1 a 9098 15525 1 a 9099 15524 1 a 9100 15523 1 a 9101 15522 1 a 9102 15521 1 a 9103 15520 1 a 9104 15519 1 a 9105 15518 1 a 9106 15517 1 a 9107 15516 1 a 9108 15515 1 a 9109 15514 1 a 9110 15513 1 a 9111 15512 1 a 9112 15511 1 a 9113 15510 1 a 9114 15509 1 a 9115 15508 1 a 9116 15507 1 a 9117 15506 1 a 9118 15505 1 a 9119 15504 1 a 9120 15503 1 a 9121 15502 1 a 9122 15501 1 a 9123 15500 1 a 9124 15499 1 a 9125 15498 1 a 9126 15497 1 a 9127 15496 1 a 9128 15495 1 a 9129 15494 1 a 9130 15493 1 a 9131 15492 1 a 9132 15491 1 a 9133 15490 1 a 9134 15489 1 a 9135 15488 1 a 9136 15487 1 a 9137 15486 1 a 9138 15485 1 a 9139 15484 1 a 9140 15483 1 a 9141 15482 1 a 9142 15481 1 a 9143 15480 1 a 9144 15479 1 a 9145 15478 1 a 9146 15477 1 a 9147 15476 1 a 9148 15475 1 a 9149 15474 1 a 9150 15473 1 a 9151 15472 1 a 9152 15471 1 a 9153 15470 1 a 9154 15469 1 a 9155 15468 1 a 9156 15467 1 a 9157 15466 1 a 9158 15465 1 a 9159 15464 1 a 9160 15463 1 a 9161 15462 1 a 9162 15461 1 a 9163 15460 1 a 9164 15459 1 a 9165 15458 1 a 9166 15457 1 a 9167 15456 1 a 9168 15455 1 a 9169 15454 1 a 9170 15453 1 a 9171 15452 1 a 9172 15451 1 a 9173 15450 1 a 9174 15449 1 a 9175 15448 1 a 9176 15447 1 a 9177 15446 1 a 9178 15445 1 a 9179 15444 1 a 9180 15443 1 a 9181 15442 1 a 9182 15441 1 a 9183 15440 1 a 9184 15439 1 a 9185 15438 1 a 9186 15437 1 a 9187 15436 1 a 9188 15435 1 a 9189 15434 1 a 9190 15433 1 a 9191 15432 1 a 9192 15431 1 a 9193 15430 1 a 9194 15429 1 a 9195 15428 1 a 9196 15427 1 a 9197 15426 1 a 9198 15425 1 a 9199 15424 1 a 9200 15423 1 a 9201 15422 1 a 9202 15421 1 a 9203 15420 1 a 9204 15419 1 a 9205 15418 1 a 9206 15417 1 a 9207 15416 1 a 9208 15415 1 a 9209 15414 1 a 9210 15413 1 a 9211 15412 1 a 9212 15411 1 a 9213 15410 1 a 9214 15409 1 a 9215 15408 1 a 9216 15407 1 a 9217 15406 1 a 9218 15405 1 a 9219 15404 1 a 9220 15403 1 a 9221 15402 1 a 9222 15401 1 a 9223 15400 1 a 9224 15399 1 a 9225 15398 1 a 9226 15397 1 a 9227 15396 1 a 9228 15395 1 a 9229 15394 1 a 9230 15393 1 a 9231 15392 1 a 9232 15391 1 a 9233 15390 1 a 9234 15389 1 a 9235 15388 1 a 9236 15387 1 a 9237 15386 1 a 9238 15385 1 a 9239 15384 1 a 9240 15383 1 a 9241 15382 1 a 9242 15381 1 a 9243 15380 1 a 9244 15379 1 a 9245 15378 1 a 9246 15377 1 a 9247 15376 1 a 9248 15375 1 a 9249 15374 1 a 9250 15373 1 a 9251 15372 1 a 9252 15371 1 a 9253 15370 1 a 9254 15369 1 a 9255 15368 1 a 9256 15367 1 a 9257 15366 1 a 9258 15365 1 a 9259 15364 1 a 9260 15363 1 a 9261 15362 1 a 9262 15361 1 a 9263 15360 1 a 9264 15359 1 a 9265 15358 1 a 9266 15357 1 a 9267 15356 1 a 9268 15355 1 a 9269 15354 1 a 9270 15353 1 a 9271 15352 1 a 9272 15351 1 a 9273 15350 1 a 9274 15349 1 a 9275 15348 1 a 9276 15347 1 a 9277 15346 1 a 9278 15345 1 a 9279 15344 1 a 9280 15343 1 a 9281 15342 1 a 9282 15341 1 a 9283 15340 1 a 9284 15339 1 a 9285 15338 1 a 9286 15337 1 a 9287 15336 1 a 9288 15335 1 a 9289 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1 a 9423 15200 1 a 9424 15199 1 a 9425 15198 1 a 9426 15197 1 a 9427 15196 1 a 9428 15195 1 a 9429 15194 1 a 9430 15193 1 a 9431 15192 1 a 9432 15191 1 a 9433 15190 1 a 9434 15189 1 a 9435 15188 1 a 9436 15187 1 a 9437 15186 1 a 9438 15185 1 a 9439 15184 1 a 9440 15183 1 a 9441 15182 1 a 9442 15181 1 a 9443 15180 1 a 9444 15179 1 a 9445 15178 1 a 9446 15177 1 a 9447 15176 1 a 9448 15175 1 a 9449 15174 1 a 9450 15173 1 a 9451 15172 1 a 9452 15171 1 a 9453 15170 1 a 9454 15169 1 a 9455 15168 1 a 9456 15167 1 a 9457 15166 1 a 9458 15165 1 a 9459 15164 1 a 9460 15163 1 a 9461 15162 1 a 9462 15161 1 a 9463 15160 1 a 9464 15159 1 a 9465 15158 1 a 9466 15157 1 a 9467 15156 1 a 9468 15155 1 a 9469 15154 1 a 9470 15153 1 a 9471 15152 1 a 9472 15151 1 a 9473 15150 1 a 9474 15149 1 a 9475 15148 1 a 9476 15147 1 a 9477 15146 1 a 9478 15145 1 a 9479 15144 1 a 9480 15143 1 a 9481 15142 1 a 9482 15141 1 a 9483 15140 1 a 9484 15139 1 a 9485 15138 1 a 9486 15137 1 a 9487 15136 1 a 9488 15135 1 a 9489 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9556 15067 1 a 9557 15066 1 a 9558 15065 1 a 9559 15064 1 a 9560 15063 1 a 9561 15062 1 a 9562 15061 1 a 9563 15060 1 a 9564 15059 1 a 9565 15058 1 a 9566 15057 1 a 9567 15056 1 a 9568 15055 1 a 9569 15054 1 a 9570 15053 1 a 9571 15052 1 a 9572 15051 1 a 9573 15050 1 a 9574 15049 1 a 9575 15048 1 a 9576 15047 1 a 9577 15046 1 a 9578 15045 1 a 9579 15044 1 a 9580 15043 1 a 9581 15042 1 a 9582 15041 1 a 9583 15040 1 a 9584 15039 1 a 9585 15038 1 a 9586 15037 1 a 9587 15036 1 a 9588 15035 1 a 9589 15034 1 a 9590 15033 1 a 9591 15032 1 a 9592 15031 1 a 9593 15030 1 a 9594 15029 1 a 9595 15028 1 a 9596 15027 1 a 9597 15026 1 a 9598 15025 1 a 9599 15024 1 a 9600 15023 1 a 9601 15022 1 a 9602 15021 1 a 9603 15020 1 a 9604 15019 1 a 9605 15018 1 a 9606 15017 1 a 9607 15016 1 a 9608 15015 1 a 9609 15014 1 a 9610 15013 1 a 9611 15012 1 a 9612 15011 1 a 9613 15010 1 a 9614 15009 1 a 9615 15008 1 a 9616 15007 1 a 9617 15006 1 a 9618 15005 1 a 9619 15004 1 a 9620 15003 1 a 9621 15002 1 a 9622 15001 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a 12146 12477 1 a 12147 12476 1 a 12148 12475 1 a 12149 12474 1 a 12150 12473 1 a 12151 12472 1 a 12152 12471 1 a 12153 12470 1 a 12154 12469 1 a 12155 12468 1 a 12156 12467 1 a 12157 12466 1 a 12158 12465 1 a 12159 12464 1 a 12160 12463 1 a 12161 12462 1 a 12162 12461 1 a 12163 12460 1 a 12164 12459 1 a 12165 12458 1 a 12166 12457 1 a 12167 12456 1 a 12168 12455 1 a 12169 12454 1 a 12170 12453 1 a 12171 12452 1 a 12172 12451 1 a 12173 12450 1 a 12174 12449 1 a 12175 12448 1 a 12176 12447 1 a 12177 12446 1 a 12178 12445 1 a 12179 12444 1 a 12180 12443 1 a 12181 12442 1 a 12182 12441 1 a 12183 12440 1 a 12184 12439 1 a 12185 12438 1 a 12186 12437 1 a 12187 12436 1 a 12188 12435 1 a 12189 12434 1 a 12190 12433 1 a 12191 12432 1 a 12192 12431 1 a 12193 12430 1 a 12194 12429 1 a 12195 12428 1 a 12196 12427 1 a 12197 12426 1 a 12198 12425 1 a 12199 12424 1 a 12200 12423 1 a 12201 12422 1 a 12202 12421 1 a 12203 12420 1 a 12204 12419 1 a 12205 12418 1 a 12206 12417 1 a 12207 12416 1 a 12208 12415 1 a 12209 12414 1 a 12210 12413 1 a 12211 12412 1 a 12212 12411 1 a 12213 12410 1 a 12214 12409 1 a 12215 12408 1 a 12216 12407 1 a 12217 12406 1 a 12218 12405 1 a 12219 12404 1 a 12220 12403 1 a 12221 12402 1 a 12222 12401 1 a 12223 12400 1 a 12224 12399 1 a 12225 12398 1 a 12226 12397 1 a 12227 12396 1 a 12228 12395 1 a 12229 12394 1 a 12230 12393 1 a 12231 12392 1 a 12232 12391 1 a 12233 12390 1 a 12234 12389 1 a 12235 12388 1 a 12236 12387 1 a 12237 12386 1 a 12238 12385 1 a 12239 12384 1 a 12240 12383 1 a 12241 12382 1 a 12242 12381 1 a 12243 12380 1 a 12244 12379 1 a 12245 12378 1 a 12246 12377 1 a 12247 12376 1 a 12248 12375 1 a 12249 12374 1 a 12250 12373 1 a 12251 12372 1 a 12252 12371 1 a 12253 12370 1 a 12254 12369 1 a 12255 12368 1 a 12256 12367 1 a 12257 12366 1 a 12258 12365 1 a 12259 12364 1 a 12260 12363 1 a 12261 12362 1 a 12262 12361 1 a 12263 12360 1 a 12264 12359 1 a 12265 12358 1 a 12266 12357 1 a 12267 12356 1 a 12268 12355 1 a 12269 12354 1 a 12270 12353 1 a 12271 12352 1 a 12272 12351 1 a 12273 12350 1 a 12274 12349 1 a 12275 12348 1 a 12276 12347 1 a 12277 12346 1 a 12278 12345 1 a 12279 12344 1 a 12280 12343 1 a 12281 12342 1 a 12282 12341 1 a 12283 12340 1 a 12284 12339 1 a 12285 12338 1 a 12286 12337 1 a 12287 12336 1 a 12288 12335 1 a 12289 12334 1 a 12290 12333 1 a 12291 12332 1 a 12292 12331 1 a 12293 12330 1 a 12294 12329 1 a 12295 12328 1 a 12296 12327 1 a 12297 12326 1 a 12298 12325 1 a 12299 12324 1 a 12300 12323 1 a 12301 12322 1 a 12302 12321 1 a 12303 12320 1 a 12304 12319 1 a 12305 12318 1 a 12306 12317 1 a 12307 12316 1 a 12308 12315 1 a 12309 12314 1 a 12310 12313 1 a 1 3 1000000 a 1 8209 1000000 a 8208 2 1000000 a 16414 2 1000000 python-igraph-0.8.0/vendor/source/igraph/examples/simple/pajek6.net0000644000076500000240000000100513524616144025610 0ustar tamasstaff00000000000000*Vertices 10 1 "Vert 1" 0 0 box x_fact 1 y_fact 1 ic Green 2 "Vert 2" 0 0 box x_fact 1 y_fact 1 ic Green 3 "Vert 3" 0 0 box x_fact 1 y_fact 1 ic Green 4 "Vert 4" 0 0 box x_fact 1 y_fact 1 ic Green 5 "Vert 5" 0 0 box x_fact 1 y_fact 1 ic Green 6 "Vert 6" 0 0 box x_fact 1 y_fact 1 ic Blue 7 "Vert 7" 0 0 box x_fact 1 y_fact 1 ic Red 8 "Vert 8" 0 0 box x_fact 1 y_fact 1 ic Green 9 "Vert 9" 0 0 box x_fact 1 y_fact 1 ic Green 10 "Vert 10" 0 0 box x_fact 1 y_fact 1 ic Green *Arcs 9 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_sparsemat8.c0000644000076500000240000001405013612122634027503 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #define DIM1 10 #define DIM2 5 #define INT(a) (igraph_rng_get_integer(igraph_rng_default(), 0, (a))) int main() { igraph_matrix_t mat, mat2; igraph_sparsemat_t spmat, spmat2; int i, j, nz1, nz2; igraph_vector_t sums1, sums2; igraph_rng_seed(igraph_rng_default(), 42); /* COPY */ igraph_sparsemat_init(&spmat, DIM1, DIM2, 20); for (i = 0; i < 10; i++) { igraph_sparsemat_entry(&spmat, INT(DIM1 - 1), INT(DIM2 - 1), 1.0); } igraph_sparsemat_copy(&spmat2, &spmat); igraph_matrix_init(&mat, 0, 0); igraph_sparsemat_as_matrix(&mat, &spmat); igraph_matrix_init(&mat2, 0, 0); igraph_sparsemat_as_matrix(&mat2, &spmat2); if (!igraph_matrix_all_e(&mat, &mat2)) { return 1; } igraph_matrix_destroy(&mat2); igraph_sparsemat_destroy(&spmat2); igraph_sparsemat_compress(&spmat, &spmat2); igraph_sparsemat_destroy(&spmat); igraph_sparsemat_copy(&spmat, &spmat2); igraph_matrix_init(&mat2, 0, 0); igraph_sparsemat_as_matrix(&mat2, &spmat); if (!igraph_matrix_all_e(&mat, &mat2)) { return 2; } igraph_sparsemat_destroy(&spmat); igraph_sparsemat_destroy(&spmat2); igraph_matrix_destroy(&mat); igraph_matrix_destroy(&mat2); /* COLSUMS, ROWSUMS */ igraph_sparsemat_init(&spmat, DIM1, DIM2, 20); for (i = 0; i < 10; i++) { igraph_sparsemat_entry(&spmat, INT(DIM1 - 1), INT(DIM2 - 1), 1.0); } igraph_sparsemat_compress(&spmat, &spmat2); igraph_matrix_init(&mat, 0, 0); igraph_sparsemat_as_matrix(&mat, &spmat); igraph_vector_init(&sums1, 0); igraph_vector_init(&sums2, 0); igraph_sparsemat_colsums(&spmat, &sums1); igraph_matrix_colsum(&mat, &sums2); if (!igraph_vector_all_e(&sums1, &sums2)) { return 3; } igraph_sparsemat_colsums(&spmat2, &sums1); if (!igraph_vector_all_e(&sums1, &sums2)) { return 4; } igraph_sparsemat_rowsums(&spmat, &sums1); igraph_matrix_rowsum(&mat, &sums2); if (!igraph_vector_all_e(&sums1, &sums2)) { return 5; } igraph_sparsemat_rowsums(&spmat2, &sums1); if (!igraph_vector_all_e(&sums1, &sums2)) { return 6; } igraph_matrix_destroy(&mat); igraph_sparsemat_destroy(&spmat); igraph_sparsemat_destroy(&spmat2); igraph_vector_destroy(&sums1); igraph_vector_destroy(&sums2); /* COUNT_NONZERO, COUNT_NONZEROTOL */ igraph_sparsemat_init(&spmat, DIM1, DIM2, 20); igraph_sparsemat_entry(&spmat, 1, 2, 1.0); igraph_sparsemat_entry(&spmat, 1, 2, 1.0); igraph_sparsemat_entry(&spmat, 1, 3, 1e-12); for (i = 0; i < 10; i++) { igraph_sparsemat_entry(&spmat, INT(DIM1 - 1), INT(DIM2 - 1), 1.0); } igraph_sparsemat_compress(&spmat, &spmat2); igraph_matrix_init(&mat, 0, 0); igraph_sparsemat_as_matrix(&mat, &spmat2); nz1 = igraph_sparsemat_count_nonzero(&spmat2); for (nz2 = 0, i = 0; i < igraph_matrix_nrow(&mat); i++) { for (j = 0; j < igraph_matrix_ncol(&mat); j++) { if (MATRIX(mat, i, j) != 0) { nz2++; } } } if (nz1 != nz2) { printf("%i %i\n", nz1, nz2); return 7; } nz1 = igraph_sparsemat_count_nonzerotol(&spmat2, 1e-10); for (nz2 = 0, i = 0; i < igraph_matrix_nrow(&mat); i++) { for (j = 0; j < igraph_matrix_ncol(&mat); j++) { if (fabs(MATRIX(mat, i, j)) >= 1e-10) { nz2++; } } } if (nz1 != nz2) { printf("%i %i\n", nz1, nz2); return 8; } igraph_matrix_destroy(&mat); igraph_sparsemat_destroy(&spmat); igraph_sparsemat_destroy(&spmat2); /* SCALE */ igraph_sparsemat_init(&spmat, DIM1, DIM2, 20); for (i = 0; i < 10; i++) { igraph_sparsemat_entry(&spmat, INT(DIM1 - 1), INT(DIM2 - 1), 1.0); } igraph_sparsemat_compress(&spmat, &spmat2); igraph_sparsemat_scale(&spmat, 2.0); igraph_sparsemat_scale(&spmat2, 2.0); igraph_matrix_init(&mat, 0, 0); igraph_sparsemat_as_matrix(&mat, &spmat); igraph_matrix_init(&mat2, 0, 0); igraph_sparsemat_as_matrix(&mat2, &spmat2); igraph_matrix_scale(&mat, 1.0 / 2.0); igraph_matrix_scale(&mat2, 1.0 / 2.0); if (!igraph_matrix_all_e(&mat, &mat2)) { return 9; } igraph_matrix_destroy(&mat); igraph_matrix_destroy(&mat2); igraph_sparsemat_destroy(&spmat); igraph_sparsemat_destroy(&spmat2); /* ADDROWS, ADDCOLS */ igraph_sparsemat_init(&spmat, DIM1, DIM2, 20); for (i = 0; i < 10; i++) { igraph_sparsemat_entry(&spmat, INT(DIM1 - 1), INT(DIM2 - 1), 1.0); } igraph_sparsemat_compress(&spmat, &spmat2); igraph_sparsemat_add_rows(&spmat, 3); igraph_sparsemat_add_cols(&spmat, 2); igraph_sparsemat_add_rows(&spmat2, 3); igraph_sparsemat_add_cols(&spmat2, 2); igraph_matrix_init(&mat, 0, 0); igraph_sparsemat_as_matrix(&mat, &spmat); igraph_matrix_init(&mat2, 0, 0); igraph_sparsemat_as_matrix(&mat2, &spmat2); if (!igraph_matrix_all_e(&mat, &mat2)) { return 10; } igraph_matrix_destroy(&mat); igraph_matrix_destroy(&mat2); igraph_sparsemat_destroy(&spmat); igraph_sparsemat_destroy(&spmat2); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_add_vertices.c0000644000076500000240000000332313612122633030050 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g1; igraph_vector_t v1; int ret; /* Create a graph */ igraph_vector_init(&v1, 8); VECTOR(v1)[0] = 0; VECTOR(v1)[1] = 1; VECTOR(v1)[2] = 1; VECTOR(v1)[3] = 2; VECTOR(v1)[4] = 2; VECTOR(v1)[5] = 3; VECTOR(v1)[6] = 2; VECTOR(v1)[7] = 2; igraph_create(&g1, &v1, 0, 0); igraph_vector_destroy(&v1); /* Add more vertices */ igraph_add_vertices(&g1, 10, 0); if (igraph_vcount(&g1) != 14) { return 1; } /* Add more vertices */ igraph_add_vertices(&g1, 0, 0); if (igraph_vcount(&g1) != 14) { return 2; } /* Error */ igraph_set_error_handler(igraph_error_handler_ignore); ret = igraph_add_vertices(&g1, -1, 0); if (ret != IGRAPH_EINVAL) { return 3; } igraph_destroy(&g1); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_get_shortest_paths2.out0000644000076500000240000000024613524616144032004 0ustar tamasstaff000000000000000 V: 0 0 E: 1 V: 0 1 1 E: 0 2 V: 0 2 2 E: 1 3 V: 0 1 3 3 E: 0 4 4 V: 0 1 4 4 E: 0 5 5 V: 0 1 5 5 E: 0 6 6 V: 0 1 6 6 E: 0 2 pred: 0 0 0 1 1 1 1 inbe: -1 0 1 4 5 6 2 python-igraph-0.8.0/vendor/source/igraph/examples/simple/dot.c0000644000076500000240000000255513612122633024656 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int main() { igraph_t g; FILE *ifile; ifile = fopen("karate.gml", "r"); if (ifile == 0) { return 10; } igraph_read_graph_gml(&g, ifile); fclose(ifile); if (igraph_is_directed(&g)) { printf("directed\n"); } else { printf("undirected\n"); } igraph_write_graph_edgelist(&g, stdout); printf("-----------------\n"); igraph_write_graph_dot(&g, stdout); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_community_optimal_modularity.c0000644000076500000240000000760013612122633033440 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void prepare_weights_vector(igraph_vector_t* weights, const igraph_t* graph) { int i, n = igraph_ecount(graph); igraph_vector_resize(weights, n); for (i = 0; i < n; i++) { VECTOR(*weights)[i] = i % 5; } } int main() { igraph_t graph; igraph_vector_t v; igraph_real_t edges[] = { 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 0, 7, 0, 8, 0, 10, 0, 11, 0, 12, 0, 13, 0, 17, 0, 19, 0, 21, 0, 31, 1, 2, 1, 3, 1, 7, 1, 13, 1, 17, 1, 19, 1, 21, 1, 30, 2, 3, 2, 7, 2, 27, 2, 28, 2, 32, 2, 9, 2, 8, 2, 13, 3, 7, 3, 12, 3, 13, 4, 6, 4, 10, 5, 6, 5, 10, 5, 16, 6, 16, 8, 30, 8, 32, 8, 33, 9, 33, 13, 33, 14, 32, 14, 33, 15, 32, 15, 33, 18, 32, 18, 33, 19, 33, 20, 32, 20, 33, 22, 32, 22, 33, 23, 25, 23, 27, 23, 32, 23, 33, 23, 29, 24, 25, 24, 27, 24, 31, 25, 31, 26, 29, 26, 33, 27, 33, 28, 31, 28, 33, 29, 32, 29, 33, 30, 32, 30, 33, 31, 32, 31, 33, 32, 33 }; igraph_vector_t membership; igraph_vector_t weights; igraph_real_t modularity; igraph_bool_t simple; int retval; igraph_vector_view(&v, edges, sizeof(edges) / sizeof(double)); igraph_create(&graph, &v, 0, IGRAPH_UNDIRECTED); igraph_vector_init(&weights, 0); igraph_is_simple(&graph, &simple); if (!simple) { return 1; } igraph_vector_init(&membership, 0); igraph_set_error_handler(&igraph_error_handler_printignore); /* Zachary karate club, unweighted */ retval = igraph_community_optimal_modularity(&graph, &modularity, &membership, 0); if (retval == IGRAPH_UNIMPLEMENTED) { return 77; } if (fabs(modularity - 0.4197896) > 0.0000001) { return 2; } /* Zachary karate club, weighted */ prepare_weights_vector(&weights, &graph); igraph_community_optimal_modularity(&graph, &modularity, &membership, &weights); if (fabs(modularity - 0.5115767) > 0.0000001) { return 4; } igraph_destroy(&graph); /* simple graph with loop edges, unweighted */ igraph_small(&graph, 6, IGRAPH_UNDIRECTED, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 0, 0, 0, 2, 2, -1); igraph_community_optimal_modularity(&graph, &modularity, &membership, 0); if (fabs(modularity - 0.28125) > 0.00001) { return 3; } /* simple graph with loop edges, weighted */ prepare_weights_vector(&weights, &graph); igraph_community_optimal_modularity(&graph, &modularity, &membership, &weights); if (fabs(modularity - 0.36686) > 0.00001) { return 5; } igraph_destroy(&graph); igraph_vector_destroy(&membership); igraph_vector_destroy(&weights); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_community_leiden.c0000644000076500000240000000547713612122633030774 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t graph; igraph_vector_t membership, degree; igraph_integer_t nb_clusters; igraph_real_t quality; long int i; /* Set default seed to get reproducible results */ igraph_rng_seed(igraph_rng_default(), 0); /* Simple unweighted graph */ igraph_small(&graph, 10, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 0, 4, 1, 2, 1, 3, 1, 4, 2, 3, 2, 4, 3, 4, 5, 6, 5, 7, 5, 8, 5, 9, 6, 7, 6, 8, 6, 9, 7, 8, 7, 9, 8, 9, 0, 5, -1); /* Perform Leiden algorithm using CPM */ igraph_vector_init(&membership, igraph_vcount(&graph)); igraph_community_leiden(&graph, NULL, NULL, 0.05, 0.01, 0, &membership, &nb_clusters, &quality); printf("Leiden found %i clusters using CPM (resolution parameter 0.05), quality is %.4f.\n", nb_clusters, quality); printf("Membership: "); igraph_vector_print(&membership); printf("\n"); /* Start from existing membership to improve it further */ igraph_community_leiden(&graph, NULL, NULL, 0.05, 0.01, 1, &membership, &nb_clusters, &quality); printf("Iterated Leiden, using CPM (resolution parameter 0.05), quality is %.4f.\n", nb_clusters, quality); printf("Membership: "); igraph_vector_print(&membership); printf("\n"); /* Initialize degree vector to use for optimizing modularity */ igraph_vector_init(°ree, igraph_vcount(&graph)); igraph_degree(&graph, °ree, igraph_vss_all(), IGRAPH_ALL, 1); /* Perform Leiden algorithm using modularity */ igraph_community_leiden(&graph, NULL, °ree, 1.0 / (2 * igraph_ecount(&graph)), 0.01, 0, &membership, &nb_clusters, &quality); printf("Leiden found %i clusters using modularity, quality is %.4f.\n", nb_clusters, quality); printf("Membership: "); igraph_vector_print(&membership); printf("\n"); igraph_vector_destroy(°ree); igraph_vector_destroy(&membership); igraph_destroy(&graph); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_tree.c0000644000076500000240000000253013612122634026353 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t graph; igraph_bool_t res; /* Create a directed binary tree on 15 nodes, with edges pointing towards the root. */ igraph_tree(&graph, 15, 2, IGRAPH_TREE_IN); igraph_is_tree(&graph, &res, NULL, IGRAPH_IN); printf("Is it an in-tree? %s\n", res ? "Yes" : "No"); igraph_is_tree(&graph, &res, NULL, IGRAPH_OUT); printf("Is it an out-tree? %s\n", res ? "Yes" : "No"); igraph_destroy(&graph); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/single_target_shortest_path.c0000644000076500000240000000461713612122634031670 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void igraph_warnings_ignore(const char *reason, const char *file, int line, int igraph_errno) { /* Do nothing */ } int main() { igraph_t g; igraph_vector_t vpath, epath; igraph_vector_t w; /* Unweighted */ igraph_small(&g, 5, IGRAPH_DIRECTED, 0, 1, 1, 2, 2, 3, 3, 4, 0, 3, -1); igraph_vector_init(&vpath, 0); igraph_vector_init(&epath, 0); igraph_get_shortest_path(&g, &vpath, &epath, 0, 4, IGRAPH_OUT); igraph_vector_print(&vpath); igraph_vector_print(&epath); igraph_get_shortest_path(&g, &vpath, &epath, 0, 0, IGRAPH_OUT); igraph_vector_print(&vpath); igraph_vector_print(&epath); igraph_set_warning_handler(igraph_warnings_ignore); igraph_get_shortest_path(&g, &vpath, &epath, 4, 0, IGRAPH_OUT); igraph_vector_print(&vpath); igraph_vector_print(&epath); igraph_set_warning_handler(igraph_warning_handler_print); igraph_get_shortest_path(&g, &vpath, &epath, 4, 0, IGRAPH_ALL); igraph_vector_print(&vpath); igraph_vector_print(&epath); /* Weighted */ igraph_vector_init(&w, 5); VECTOR(w)[0] = 1; VECTOR(w)[1] = 1; VECTOR(w)[2] = 1; VECTOR(w)[3] = 1; VECTOR(w)[4] = 3.1; igraph_get_shortest_path_dijkstra(&g, &vpath, &epath, 0, 4, &w, IGRAPH_OUT); igraph_vector_print(&vpath); igraph_vector_print(&epath); igraph_vector_destroy(&w); igraph_vector_destroy(&epath); igraph_vector_destroy(&vpath); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_read_graph_dl.out0000644000076500000240000000115313524616144030562 0ustar tamasstaff00000000000000Doing fullmatrix1.dl 0 1 0 2 0 3 0 4 1 0 1 2 2 0 2 1 2 4 3 0 4 0 4 2 Doing fullmatrix2.dl 0 1 0 2 0 3 1 0 1 4 2 0 2 3 3 0 3 2 3 4 4 1 4 3 Doing fullmatrix3.dl 0 1 0 2 0 3 1 0 1 4 2 0 2 3 3 0 3 2 3 4 4 1 4 3 Doing fullmatrix4.dl 0 1 0 2 0 3 1 0 1 4 2 0 2 3 3 0 3 2 3 4 4 1 4 3 Doing edgelist1.dl 0 1 0 2 1 2 2 0 3 2 Doing edgelist2.dl 0 1 0 2 1 2 3 0 4 2 Doing edgelist3.dl 0 1 0 2 1 2 3 0 4 2 Doing edgelist4.dl 0 1 0 2 1 2 2 0 3 2 Doing edgelist5.dl 0 1 0 2 1 2 3 0 4 2 Doing edgelist6.dl 0 1 0 2 1 2 3 0 4 2 Doing edgelist7.dl 0 1 1 2 1 3 Doing nodelist1.dl 0 1 0 2 1 2 2 0 3 2 Doing nodelist2.dl 0 1 0 2 1 2 3 0 4 2 python-igraph-0.8.0/vendor/source/igraph/examples/simple/fullmatrix2.dl0000644000076500000240000000016413524616144026517 0ustar tamasstaff00000000000000dl n=5 format = fullmatrix labels: barry,david,lin,pat,russ data: 0 1 1 1 0 1 0 0 0 1 1 0 0 1 0 1 0 1 0 1 0 1 0 1 0 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_scg_grouping3.c0000644000076500000240000000762513612122633030176 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { const int nodes = 10; igraph_t g; igraph_matrix_t V, V3; igraph_matrix_complex_t V2; igraph_sparsemat_t stochastic, stochasticT; igraph_vector_t groups; igraph_eigen_which_t which; igraph_vector_t p, selcol; igraph_tree(&g, nodes, /* children= */ 3, IGRAPH_TREE_UNDIRECTED); igraph_matrix_complex_init(&V2, 0, 0); igraph_matrix_init(&V, 0, 0); igraph_matrix_init(&V3, 0, 0); igraph_vector_init(&groups, 0); igraph_vector_init(&p, 0); igraph_vector_init(&selcol, 1); igraph_rng_seed(igraph_rng_default(), 42); igraph_get_stochastic_sparsemat(&g, &stochastic, /*column-wise=*/ 0); igraph_sparsemat_transpose(&stochastic, &stochasticT, /*values=*/ 1); which.pos = IGRAPH_EIGEN_LR; which.howmany = 1; igraph_eigen_matrix(/*matrix=*/ 0, &stochasticT, /*fun=*/ 0, nodes, /*extra=*/ 0, /*1algorithm=*/ IGRAPH_EIGEN_LAPACK, &which, /*options=*/ 0, /*storage=*/ 0, /*values=*/ 0, &V2); igraph_matrix_complex_real(&V2, &V); /* `p' is always the eigenvector corresponding to the 1-eigenvalue */ igraph_matrix_get_col(&V, &p, 0); igraph_vector_print(&p); which.howmany = 3; igraph_eigen_matrix(/*matrix=*/ 0, &stochastic, /*fun=*/ 0, nodes, /*extra=*/ 0, /*algorithm=*/ IGRAPH_EIGEN_LAPACK, &which, /*options=*/ 0, /*storage=*/ 0, /*values=*/ 0, &V2); igraph_matrix_complex_real(&V2, &V3); VECTOR(selcol)[0] = 2; igraph_matrix_select_cols(&V3, &V, &selcol); /* ------------ */ igraph_scg_grouping(&V, &groups, /*intervals=*/ 3, /*intervals_vector=*/ 0, IGRAPH_SCG_STOCHASTIC, IGRAPH_SCG_OPTIMUM, &p, /*maxiter=*/ 10000); igraph_vector_print(&groups); /* ------------ */ igraph_scg_grouping(&V, &groups, /*intervals=*/ 3, /*intervals_vector=*/ 0, IGRAPH_SCG_STOCHASTIC, IGRAPH_SCG_INTERV_KM, &p, /*maxiter=*/ 10000); igraph_vector_print(&groups); /* ------------ */ igraph_scg_grouping(&V, &groups, /*intervals=*/ 3, /*intervals_vector=*/ 0, IGRAPH_SCG_STOCHASTIC, IGRAPH_SCG_INTERV, &p, /*maxiter=*/ 10000); igraph_vector_print(&groups); /* ------------ */ igraph_scg_grouping(&V, &groups, /*(ignored) intervals=*/ 0, /*intervals_vector=*/ 0, IGRAPH_SCG_STOCHASTIC, IGRAPH_SCG_EXACT, &p, /*maxiter=*/ 10000); igraph_vector_print(&groups); /* ------------ */ igraph_vector_destroy(&p); igraph_vector_destroy(&selcol); igraph_vector_destroy(&groups); igraph_matrix_destroy(&V); igraph_matrix_destroy(&V3); igraph_matrix_complex_destroy(&V2); igraph_sparsemat_destroy(&stochasticT); igraph_sparsemat_destroy(&stochastic); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_gomory_hu_tree.c0000644000076500000240000001101613612122633030441 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2013 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int validate_tree(const igraph_t *graph, const igraph_t *tree, const igraph_vector_t *flow, const igraph_vector_t *capacity) { igraph_integer_t n = igraph_vcount(graph); igraph_vector_t edges; igraph_real_t min_weight, flow_value; long int i, j, k, m; if (igraph_vcount(tree) != n) { printf("Gomory-Hu tree should have %ld vertices\n", (long int)n); return IGRAPH_EINVAL; } if (igraph_ecount(tree) != n - 1) { printf("Gomory-Hu tree should have %ld edges\n", (long int)n - 1); return IGRAPH_EINVAL; } if (igraph_is_directed(tree)) { printf("Gomory-Hu tree should be undirected\n"); return IGRAPH_EINVAL; } if (n < 2) { return IGRAPH_SUCCESS; } IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); for (i = 0; i < n; i++) { for (j = i + 1; j < n; j++) { IGRAPH_CHECK(igraph_get_shortest_path(tree, 0, &edges, i, j, IGRAPH_ALL)); m = igraph_vector_size(&edges); if (m == 0) { continue; } min_weight = VECTOR(*flow)[(long int)VECTOR(edges)[0]]; for (k = 1; k < m; k++) { if (VECTOR(*flow)[(long int)VECTOR(edges)[k]] < min_weight) { min_weight = VECTOR(*flow)[(long int)VECTOR(edges)[k]]; } } IGRAPH_CHECK(igraph_maxflow(graph, &flow_value, 0, 0, 0, 0, i, j, capacity, 0)); if (flow_value != min_weight) { printf("Min weight of path %ld --> %ld in Gomory-Hu tree is %.4f, " "expected %.4f from flow calculation\n", i, j, min_weight, flow_value); return IGRAPH_EINVAL; } } } igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } int main() { igraph_t g; igraph_t tree; igraph_vector_t flow; igraph_vector_t capacity; /* initialize flow and capacity vectors */ igraph_vector_init(&capacity, 0); igraph_vector_init(&flow, 0); /* empty undirected graph */ igraph_empty(&g, 0, 0); if (igraph_gomory_hu_tree(&g, &tree, &flow, &capacity)) { return 1; } if (igraph_vcount(&tree) != 0) { return 1; } if (igraph_vector_size(&flow) != 0) { return 1; } igraph_destroy(&tree); igraph_destroy(&g); /* simple undirected graph */ igraph_small(&g, 6, 0, 0, 1, 0, 2, 1, 2, 1, 3, 1, 4, 2, 4, 3, 4, 3, 5, 4, 5, -1); igraph_vector_resize(&capacity, 9); VECTOR(capacity)[0] = 1; VECTOR(capacity)[1] = 7; VECTOR(capacity)[2] = 1; VECTOR(capacity)[3] = 3; VECTOR(capacity)[4] = 2; VECTOR(capacity)[5] = 4; VECTOR(capacity)[6] = 1; VECTOR(capacity)[7] = 6; VECTOR(capacity)[8] = 2; if (igraph_gomory_hu_tree(&g, &tree, &flow, &capacity)) { return 2; } if (validate_tree(&g, &tree, &flow, &capacity)) { return 2; } igraph_destroy(&tree); /* Make sure we don't blow up without an outgoing flow vector */ if (igraph_gomory_hu_tree(&g, &tree, 0, &capacity)) { return 2; } igraph_destroy(&tree); igraph_destroy(&g); /* simple directed graph - should throw an error */ igraph_small(&g, 6, 1, 0, 1, 0, 2, 1, 2, 1, 3, 1, 4, 2, 4, 3, 4, 3, 5, 4, 5, -1); igraph_set_error_handler(igraph_error_handler_ignore); if (!igraph_gomory_hu_tree(&g, &tree, &flow, &capacity)) { return 3; } igraph_set_error_handler(igraph_error_handler_abort); igraph_destroy(&g); /* destroy flow and capacity vectors */ igraph_vector_destroy(&flow); igraph_vector_destroy(&capacity); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_hrg2.c0000644000076500000240000000476213612122633026266 0ustar tamasstaff00000000000000/* -*- mode: C++ -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int main() { igraph_t karate; igraph_vector_t parents, weights; igraph_rng_seed(igraph_rng_default(), 42); igraph_small(&karate, 34, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 0, 7, 0, 8, 0, 10, 0, 11, 0, 12, 0, 13, 0, 17, 0, 19, 0, 21, 0, 31, 1, 2, 1, 3, 1, 7, 1, 13, 1, 17, 1, 19, 1, 21, 1, 30, 2, 3, 2, 7, 2, 27, 2, 28, 2, 32, 2, 9, 2, 8, 2, 13, 3, 7, 3, 12, 3, 13, 4, 6, 4, 10, 5, 6, 5, 10, 5, 16, 6, 16, 8, 30, 8, 32, 8, 33, 9, 33, 13, 33, 14, 32, 14, 33, 15, 32, 15, 33, 18, 32, 18, 33, 19, 33, 20, 32, 20, 33, 22, 32, 22, 33, 23, 25, 23, 27, 23, 32, 23, 33, 23, 29, 24, 25, 24, 27, 24, 31, 25, 31, 26, 29, 26, 33, 27, 33, 28, 31, 28, 33, 29, 32, 29, 33, 30, 32, 30, 33, 31, 32, 31, 33, 32, 33, -1); igraph_vector_init(&parents, 0); igraph_vector_init(&weights, 0); igraph_hrg_consensus(&karate, &parents, &weights, /* hrg= */ 0, /* start= */ 0, /* num_samples= */ 100); /* Check */ igraph_vector_print(&parents); igraph_vector_print(&weights); igraph_vector_destroy(&parents); igraph_vector_destroy(&weights); igraph_destroy(&karate); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_isomorphic_bliss.c0000644000076500000240000000740213612122633030766 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include int main() { igraph_t g1, g2; igraph_t ring1, ring2; igraph_vector_int_t color1, color2; igraph_vector_t perm; igraph_bool_t iso; igraph_rng_seed(igraph_rng_default(), 54321); igraph_ring(&ring1, 100, /*directed=*/ 0, /*mutual=*/ 0, /*circular=*/1); igraph_vector_init_seq(&perm, 0, igraph_vcount(&ring1) - 1); igraph_vector_shuffle(&perm); igraph_permute_vertices(&ring1, &ring2, &perm); /* Without colors */ igraph_isomorphic_bliss(&ring1, &ring2, 0, 0, &iso, 0, 0, 0, 0, 0); if (!iso) { fprintf(stderr, "Without color failed.\n"); return 1; } /* Everything has the same colors */ igraph_vector_int_init(&color1, igraph_vcount(&ring1)); igraph_vector_int_init(&color2, igraph_vcount(&ring2)); igraph_isomorphic_bliss(&ring1, &ring2, &color1, &color2, &iso, 0, 0, 0, 0, 0); if (!iso) { fprintf(stderr, "Single color failed.\n"); return 2; } /* Try a negative result */ igraph_vector_int_fill(&color1, 0); igraph_vector_int_fill(&color2, 0); VECTOR(color1)[0] = 1; igraph_isomorphic_bliss(&ring1, &ring2, &color1, &color2, &iso, 0, 0, 0, 0, 0); if (iso) { fprintf(stderr, "Negative test failed.\n"); return 3; } /* Another negative, same color distribution, different topology */ igraph_vector_int_fill(&color1, 0); igraph_vector_int_fill(&color2, 0); VECTOR(color1)[0] = 1; VECTOR(color1)[1] = 1; VECTOR(color2)[0] = 1; VECTOR(color2)[2] = 1; igraph_isomorphic_bliss(&ring1, &ring2, &color1, &color2, &iso, 0, 0, 0, 0, 0); if (iso) { fprintf(stderr, "Second negative test failed.\n"); return 4; } /* More complicated test with colors */ igraph_vector_int_destroy(&color1); igraph_vector_int_destroy(&color2); igraph_vector_destroy(&perm); igraph_destroy(&ring2); igraph_destroy(&ring1); igraph_small(&g1, 8, IGRAPH_DIRECTED, 0, 4, 0, 5, 0, 6, 1, 4, 1, 5, 1, 7, 2, 4, 2, 6, 2, 7, 3, 5, 3, 6, 3, 7, -1 ); igraph_small(&g2, 8, IGRAPH_DIRECTED, 0, 1, 0, 3, 0, 4, 2, 3, 2, 1, 2, 6, 5, 1, 5, 4, 5, 6, 7, 3, 7, 6, 7, 4, -1 ); igraph_vector_int_init(&color1, 8); igraph_vector_int_init(&color2, 8); VECTOR(color1)[1] = 1; VECTOR(color1)[3] = 1; VECTOR(color1)[5] = 1; VECTOR(color1)[7] = 1; VECTOR(color2)[2] = 1; VECTOR(color2)[3] = 1; VECTOR(color2)[6] = 1; VECTOR(color2)[7] = 1; iso = 0; igraph_isomorphic_bliss(&g1, &g2, &color1, &color2, &iso, 0, 0, 0, 0, 0); if (!iso) { fprintf(stderr, "BLISS failed to identify colored graphs as isomorphic.\n"); return 5; } igraph_vector_int_destroy(&color1); igraph_vector_int_destroy(&color2); igraph_destroy(&g2); igraph_destroy(&g1); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/even_tarjan.c0000644000076500000240000000403513612122633026357 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int main() { igraph_t g, gbar; igraph_integer_t k1, k2 = (igraph_integer_t) INT_MAX; igraph_real_t tmpk; long int i, j, n; igraph_maxflow_stats_t stats; /* --------------------------------------------------- */ igraph_famous(&g, "meredith"); igraph_even_tarjan_reduction(&g, &gbar, /*capacity=*/ 0); igraph_vertex_connectivity(&g, &k1, /* checks= */ 0); n = igraph_vcount(&g); for (i = 0; i < n; i++) { for (j = i + 1; j < n; j++) { igraph_bool_t conn; igraph_are_connected(&g, i, j, &conn); if (conn) { continue; } igraph_maxflow_value(&gbar, &tmpk, /* source= */ i + n, /* target= */ j, /* capacity= */ 0, &stats); if (tmpk < k2) { k2 = tmpk; } } } igraph_destroy(&gbar); igraph_destroy(&g); if (k1 != k2) { printf("k1 = %ld while k2 = %ld\n", (long int) k1, (long int) k2); return 1; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/heap.c0000644000076500000240000000177513612122633025010 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { /* This is not used by any functions any more, no need to test it right now */ return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_i_cutheap.c0000644000076500000240000000355513612122633027364 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include "igraph_types_internal.h" void print_vector(igraph_vector_t *v, FILE *f) { long int i; for (i = 0; i < igraph_vector_size(v); i++) { fprintf(f, " %li", (long int) VECTOR(*v)[i]); } fprintf(f, "\n"); } int main() { igraph_i_cutheap_t ch; long int i; igraph_i_cutheap_init(&ch, 10); for (i = 0; i < 10; i++) { igraph_i_cutheap_update(&ch, i, i); } /* print_vector(&ch.heap, stdout); */ /* print_vector(&ch.index, stdout); */ /* print_vector(&ch.hptr, stdout); */ while (!igraph_i_cutheap_empty(&ch)) { long int idx = igraph_i_cutheap_popmax(&ch); printf("%li ", idx); /* print_vector(&ch.heap, stdout); */ /* print_vector(&ch.index, stdout); */ /* print_vector(&ch.hptr, stdout); */ /* printf("------------\n"); */ } printf("\n"); igraph_i_cutheap_destroy(&ch); if (!IGRAPH_FINALLY_STACK_EMPTY) { return 1; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/blas.out0000644000076500000240000000001413524616144025371 0ustar tamasstaff0000000000000040 55 70 85 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_get_eid.out0000644000076500000240000000004613524616144027407 0ustar tamasstaff00000000000000 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 python-igraph-0.8.0/vendor/source/igraph/examples/simple/flow.c0000644000076500000240000000661513612122633025040 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_real_t flow; igraph_vector_t capacity; igraph_integer_t source, target; FILE *infile; igraph_maxflow_stats_t stats; igraph_vector_init(&capacity, 0); /***************/ infile = fopen("ak-4102.max", "r"); igraph_read_graph_dimacs(&g, infile, 0, 0, &source, &target, &capacity, IGRAPH_DIRECTED); fclose(infile); igraph_maxflow_value(&g, &flow, source, target, &capacity, &stats); if (flow != 8207) { return 1; } igraph_destroy(&g); /***************/ /* /\***************\/ */ /* infile=fopen("ak-8198.max", "r"); */ /* igraph_read_graph_dimacs(&g, infile, 0, 0, &source, &target, &capacity, */ /* IGRAPH_DIRECTED); */ /* fclose(infile); */ /* t=timer(); */ /* igraph_maxflow_value(&g, &flow, source, target, &capacity, &stats); */ /* t=timer()-t; */ /* printf("8198: %g (time %.10f)\n", flow, t); */ /* igraph_destroy(&g); */ /* /\***************\/ */ /* /\***************\/ */ /* infile=fopen("ak-16390.max", "r"); */ /* igraph_read_graph_dimacs(&g, infile, 0, 0, &source, &target, &capacity, */ /* IGRAPH_DIRECTED); */ /* fclose(infile); */ /* t=timer(); */ /* igraph_maxflow_value(&g, &flow, source, target, &capacity, &stats); */ /* t=timer()-t; */ /* printf("16390: %g (time %.10f)\n", flow, t); */ /* igraph_destroy(&g); */ /* /\***************\/ */ /* /\***************\/ */ /* infile=fopen("ak-32774.max", "r"); */ /* igraph_read_graph_dimacs(&g, infile, 0, 0, &source, &target, &capacity, */ /* IGRAPH_DIRECTED); */ /* fclose(infile); */ /* t=timer(); */ /* igraph_maxflow_value(&g, &flow, source, target, &capacity, &stats); */ /* t=timer()-t; */ /* printf("32774: %g (time %.10f)\n", flow, t); */ /* igraph_destroy(&g); */ /* /\***************\/ */ /* /\***************\/ */ /* infile=fopen("ak-65542.max", "r"); */ /* igraph_read_graph_dimacs(&g, infile, 0, 0, &source, &target, &capacity, */ /* IGRAPH_DIRECTED); */ /* fclose(infile); */ /* t=timer(); */ /* igraph_maxflow_value(&g, &flow, source, target, &capacity, &stats); */ /* t=timer()-t; */ /* printf("65542: %g (time %.10f)\n", flow, t); */ /* igraph_destroy(&g); */ /* /\***************\/ */ igraph_vector_destroy(&capacity); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/dijkstra.c0000644000076500000240000000455213612122633025702 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2008-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int print_matrix(const igraph_matrix_t *m) { long int nrow = igraph_matrix_nrow(m); long int ncol = igraph_matrix_ncol(m); long int i, j; igraph_real_t val; for (i = 0; i < nrow; i++) { printf("%li:", i); for (j = 0; j < ncol; j++) { val = MATRIX(*m, i, j); if (igraph_is_inf(val)) { if (val < 0) { printf("-inf"); } else { printf(" inf"); } } else { printf(" %3.0f", val); } } printf("\n"); } return 0; } int main() { igraph_t g; igraph_vector_t weights; igraph_real_t weights_data[] = { 0, 2, 1, 0, 5, 2, 1, 1, 0, 2, 2, 8, 1, 1, 3, 1, 1, 4, 2, 1 }; igraph_matrix_t res; igraph_small(&g, 10, IGRAPH_DIRECTED, 0, 1, 0, 2, 0, 3, 1, 2, 1, 4, 1, 5, 2, 3, 2, 6, 3, 2, 3, 6, 4, 5, 4, 7, 5, 6, 5, 8, 5, 9, 7, 5, 7, 8, 8, 9, 5, 2, 2, 1, -1); igraph_vector_view(&weights, weights_data, sizeof(weights_data) / sizeof(igraph_real_t)); igraph_matrix_init(&res, 0, 0); igraph_shortest_paths_dijkstra(&g, &res, igraph_vss_all(), igraph_vss_all(), &weights, IGRAPH_OUT); print_matrix(&res); igraph_matrix_destroy(&res); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/cattributes4.c0000644000076500000240000000635613612122633026510 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int mf(const igraph_strvector_t *input, char *output) { /* TODO */ return 0; } int main() { igraph_t g, g2; igraph_attribute_combination_t comb; igraph_i_set_attribute_table(&igraph_cattribute_table); igraph_small(&g, 4, IGRAPH_DIRECTED, 0, 1, 0, 1, 0, 1, 1, 2, 2, 3, -1); SETEAS(&g, "color", 0, "green"); SETEAS(&g, "color", 1, "red"); SETEAS(&g, "color", 2, "blue"); SETEAS(&g, "color", 3, "white"); SETEAS(&g, "color", 4, "black"); /* ****************************************************** */ igraph_copy(&g2, &g); igraph_attribute_combination(&comb, "weight", IGRAPH_ATTRIBUTE_COMBINE_SUM, "color", IGRAPH_ATTRIBUTE_COMBINE_FIRST, "", IGRAPH_ATTRIBUTE_COMBINE_IGNORE, IGRAPH_NO_MORE_ATTRIBUTES); igraph_simplify(&g2, /*multiple=*/ 1, /*loops=*/ 1, &comb); igraph_attribute_combination_destroy(&comb); igraph_write_graph_graphml(&g2, stdout, /*prefixattr=*/ 1); igraph_destroy(&g2); /* ****************************************************** */ /* ****************************************************** */ igraph_copy(&g2, &g); igraph_attribute_combination(&comb, "", IGRAPH_ATTRIBUTE_COMBINE_LAST, IGRAPH_NO_MORE_ATTRIBUTES); igraph_simplify(&g2, /*multiple=*/ 1, /*loops=*/ 1, &comb); igraph_attribute_combination_destroy(&comb); igraph_write_graph_graphml(&g2, stdout, /*prefixattr=*/ 1); igraph_destroy(&g2); /* ****************************************************** */ /* ****************************************************** */ igraph_copy(&g2, &g); igraph_attribute_combination(&comb, "", IGRAPH_ATTRIBUTE_COMBINE_IGNORE, "color", IGRAPH_ATTRIBUTE_COMBINE_CONCAT, IGRAPH_NO_MORE_ATTRIBUTES); igraph_simplify(&g2, /*multiple=*/ 1, /*loops=*/ 1, &comb); igraph_attribute_combination_destroy(&comb); igraph_write_graph_graphml(&g2, stdout, /*prefixattr=*/ 1); igraph_destroy(&g2); /* ****************************************************** */ igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/pajek_bip.net0000644000076500000240000000034513524616144026362 0ustar tamasstaff00000000000000*vertices 15 10 1 "A" 2 "B" 3 "C" 4 "D" 5 "E" 6 "F" 7 "G" 8 "H" 9 "I" 10 "J" 11 "1" 12 "2" 13 "3" 14 "4" 15 "5" *matrix 1 0 0 0 0 1 1 0 0 0 1 1 1 0 0 1 1 1 1 0 1 1 1 1 1 0 0 0 0 1 1 0 0 0 1 1 1 0 1 1 0 0 0 0 0 1 0 1 0 1 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_from_prufer.out0000644000076500000240000000006713524616144030340 0ustar tamasstaff000000000000002 0 3 1 4 2 3 2 5 3 3 0 5 2 4 2 4 1 6 1 1 0 7 0 1 0 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_union.out0000644000076500000240000000047613524616144027146 0ustar tamasstaff000000000000000 1 1 2 2 2 2 3 2 4 0 1 2 3 0 1 2 4 --- === 0 1 1 0 --- 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 === 0 1 1 0 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 --- 10 9 8 9 7 9 6 9 5 9 4 9 3 9 2 9 1 9 0 9 === 0 1 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 --- 10 9 8 9 7 9 6 9 5 9 4 9 3 9 2 9 1 9 0 9 === python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_bfs.c0000644000076500000240000000344313612122633026171 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void vector_print(igraph_vector_t *v) { long int i; for (i = 0; i < igraph_vector_size(v); i++) { printf(" %li", (long int) VECTOR(*v)[i]); } printf("\n"); } int main() { igraph_t g; igraph_vector_t vids, layers, parents; igraph_ring(&g, 10, IGRAPH_UNDIRECTED, 0, 0); igraph_vector_init(&vids, 0); igraph_vector_init(&layers, 0); igraph_vector_init(&parents, 0); igraph_i_bfs(&g, 0, IGRAPH_ALL, &vids, &layers, &parents); vector_print(&vids); vector_print(&layers); vector_print(&parents); igraph_destroy(&g); igraph_tree(&g, 20, 2, IGRAPH_TREE_UNDIRECTED); igraph_i_bfs(&g, 0, IGRAPH_ALL, &vids, &layers, &parents); vector_print(&vids); vector_print(&layers); vector_print(&parents); igraph_destroy(&g); igraph_vector_destroy(&vids); igraph_vector_destroy(&layers); igraph_vector_destroy(&parents); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_sparsemat_minmax.c0000644000076500000240000001266113612122634030772 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2014 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #define N 10 #define M 20 #define NZ 50 #define MIN 0 #define MAX 10 typedef int fun(igraph_sparsemat_t *A, igraph_vector_t *res); int doit(int which) { int i; igraph_sparsemat_t A, A2; igraph_vector_t vec; fun *colfun, *rowfun; if (which == MIN) { colfun = igraph_sparsemat_colmins; rowfun = igraph_sparsemat_rowmins; } else { colfun = igraph_sparsemat_colmaxs; rowfun = igraph_sparsemat_rowmaxs; } igraph_rng_seed(igraph_rng_default(), 42); /* Triplet diagonal matrix */ igraph_vector_init(&vec, N); for (i = 0; i < N; i++) { VECTOR(vec)[i] = i; } igraph_sparsemat_diag(&A, /*nzmax=*/ N, /*values=*/ &vec, /*compress=*/ 0); igraph_vector_null(&vec); rowfun(&A, &vec); for (i = 0; i < N; i++) { if (VECTOR(vec)[i] != i) { return which + 1; } } igraph_vector_null(&vec); colfun(&A, &vec); for (i = 0; i < N; i++) { if (VECTOR(vec)[i] != i) { return which + 2; } } igraph_vector_destroy(&vec); igraph_sparsemat_destroy(&A); /* Compressed diagonal matrix */ igraph_vector_init(&vec, N); for (i = 0; i < N; i++) { VECTOR(vec)[i] = i; } igraph_sparsemat_diag(&A, /*nzmax=*/ N, /*values=*/ &vec, /*compress=*/ 1); igraph_vector_null(&vec); rowfun(&A, &vec); for (i = 0; i < N; i++) { if (VECTOR(vec)[i] != i) { return which + 3; } } igraph_vector_null(&vec); colfun(&A, &vec); for (i = 0; i < N; i++) { if (VECTOR(vec)[i] != i) { return which + 4; } } igraph_vector_destroy(&vec); igraph_sparsemat_destroy(&A); /* Random triplet matrix */ igraph_sparsemat_init(&A, /*rows=*/ N, /*cols=*/ M, /*nzmax=*/ NZ + 5); for (i = 0; i < NZ; i++) { int r = igraph_rng_get_integer(igraph_rng_default(), 0, N - 1); int c = igraph_rng_get_integer(igraph_rng_default(), 0, M - 1); igraph_real_t x = igraph_rng_get_integer(igraph_rng_default(), -10, 10); igraph_sparsemat_entry(&A, r, c, x); } if (which == MAX) { igraph_sparsemat_scale(&A, -1.0); } igraph_vector_init(&vec, 0); colfun(&A, &vec); igraph_vector_print(&vec); igraph_vector_null(&vec); rowfun(&A, &vec); igraph_vector_print(&vec); /* Random compresssed matrix */ igraph_sparsemat_compress(&A, &A2); igraph_vector_null(&vec); colfun(&A2, &vec); igraph_vector_print(&vec); igraph_vector_null(&vec); rowfun(&A2, &vec); igraph_vector_print(&vec); igraph_vector_destroy(&vec); igraph_sparsemat_destroy(&A); igraph_sparsemat_destroy(&A2); /* Matrix with zero rows, triplet */ igraph_sparsemat_init(&A, /*rows=*/ 0, /*cols=*/ M, /*nzmax=*/ NZ); if (which == MAX) { igraph_sparsemat_scale(&A, -1.0); } igraph_vector_init(&vec, 5); rowfun(&A, &vec); if (igraph_vector_size(&vec) != 0) { return which + 5; } igraph_vector_null(&vec); colfun(&A, &vec); igraph_vector_print(&vec); /* Matrix with zero rows, compressed */ igraph_sparsemat_compress(&A, &A2); igraph_vector_null(&vec); rowfun(&A, &vec); if (igraph_vector_size(&vec) != 0) { return which + 6; } igraph_vector_null(&vec); colfun(&A, &vec); igraph_vector_print(&vec); igraph_vector_destroy(&vec); igraph_sparsemat_destroy(&A); igraph_sparsemat_destroy(&A2); /* Matrix with zero columns, triplet */ igraph_sparsemat_init(&A, /*rows=*/ N, /*cols=*/ 0, /*nzmax=*/ NZ); if (which == MAX) { igraph_sparsemat_scale(&A, -1.0); } igraph_vector_init(&vec, 5); colfun(&A, &vec); if (igraph_vector_size(&vec) != 0) { return which + 7; } igraph_vector_null(&vec); rowfun(&A, &vec); igraph_vector_print(&vec); /* Matrix with zero columns, compressed */ igraph_sparsemat_compress(&A, &A2); igraph_vector_null(&vec); colfun(&A, &vec); if (igraph_vector_size(&vec) != 0) { return which + 8; } igraph_vector_null(&vec); rowfun(&A, &vec); igraph_vector_print(&vec); igraph_vector_destroy(&vec); igraph_sparsemat_destroy(&A); igraph_sparsemat_destroy(&A2); return 0; } int main() { int res; res = doit(/*which=*/ MIN); if (res) { return res; } res = doit(/*which=*/ MAX); if (res) { return res; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/pajek5.net0000644000076500000240000000100613524616144025610 0ustar tamasstaff00000000000000*Vertices 10 1 "Vert 1" 0 0 box x_fact 1 y_fact 1 ic Green 2 "Vert 2" 0 0 box x_fact 1 y_fact 1 ic Green 3 "Vert 3" 0 0 box x_fact 1 y_fact 1 ic Green 4 "Vert 4" 0 0 box x_fact 1 y_fact 1 ic Green 5 "Vert 5" 0 0 box x_fact 1 y_fact 1 ic Green 6 "Vert 6" 0 0 box x_fact 1 y_fact 1 ic Blue 7 "Vert 7" 0 0 box x_fact 1 y_fact 1 ic Red 8 "Vert 8" 0 0 box x_fact 1 y_fact 1 ic Green 9 "Vert 9" 0 0 box x_fact 1 y_fact 1 ic Green 10 "Vert 10" 0 0 box x_fact 1 y_fact 1 ic Green *Edges 9 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_read_graph_lgl.out0000644000076500000240000000006013524616144030735 0ustar tamasstaff000000000000000 1 0 2 2 3 2 4 0 1 0 2 2 3 2 4 0 1 0 2 2 3 2 4 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_get_eid.c0000644000076500000240000001064313612122633027017 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void print_vector(igraph_vector_t *v, FILE *f) { long int i; for (i = 0; i < igraph_vector_size(v); i++) { fprintf(f, " %li", (long int) VECTOR(*v)[i]); } fprintf(f, "\n"); } int main() { igraph_t g; igraph_integer_t eid; igraph_vector_t hist; long int i; int ret; /* DIRECTED */ igraph_star(&g, 10, IGRAPH_STAR_OUT, 0); igraph_vector_init(&hist, 9); for (i = 1; i < 10; i++) { igraph_get_eid(&g, &eid, 0, i, IGRAPH_DIRECTED, /*error=*/ 1); VECTOR(hist)[ (long int) eid ] = 1; } print_vector(&hist, stdout); igraph_vector_destroy(&hist); igraph_destroy(&g); /* UNDIRECTED */ igraph_star(&g, 10, IGRAPH_STAR_UNDIRECTED, 0); igraph_vector_init(&hist, 9); for (i = 1; i < 10; i++) { igraph_get_eid(&g, &eid, 0, i, IGRAPH_UNDIRECTED, /*error=*/ 1); VECTOR(hist)[ (long int) eid ] += 1; igraph_get_eid(&g, &eid, i, 0, IGRAPH_DIRECTED, /*error=*/ 1); VECTOR(hist)[ (long int) eid ] += 1; } print_vector(&hist, stdout); igraph_vector_destroy(&hist); igraph_destroy(&g); /* NON-EXISTANT EDGE */ igraph_star(&g, 10, IGRAPH_STAR_UNDIRECTED, 0); igraph_set_error_handler(igraph_error_handler_ignore); ret = igraph_get_eid(&g, &eid, 5, 6, IGRAPH_UNDIRECTED, /*error=*/ 1); if (ret != IGRAPH_EINVAL) { return 1; } igraph_destroy(&g); return 0; } /* Stress test */ /* int main() { */ /* igraph_t g; */ /* long int i, n; */ /* igraph_integer_t from, to, eid; */ /* igraph_barabasi_game(&g, 10000, 100, 0, 0, 1); */ /* n=igraph_ecount(&g); */ /* for (i=0; i 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void igraph_vector_print(const igraph_vector_t *v) { long int i; for (i = 0; i < igraph_vector_size(v); i++) { printf("%li ", (long int)VECTOR(*v)[i]); } printf("\n"); } int main() { igraph_t g; const igraph_vector_t v = IGRAPH_VECTOR_NULL; igraph_real_t edges1[] = { 0, 1, 1, 2, 2, 2, 2, 3, 2, 4, 3, 4 }; igraph_vector_t was; igraph_integer_t size; igraph_es_t it; long int i; igraph_vector_view(&v, edges1, sizeof(edges1) / sizeof(igraph_real_t)); igraph_vector_init(&was, 0); /******************************************/ /* Directed graph */ /******************************************/ igraph_create(&g, &v, 0, IGRAPH_DIRECTED); /* Simple test, all neighbors */ for (i = 0; i <= igraph_vector_max(&v); i++) { igraph_vector_clear(&was); igraph_es_adj(&g, &it, i, IGRAPH_ALL); igraph_es_size(&g, &it, &size); printf("%ld\n", (long)size); while (!igraph_es_end(&g, &it)) { igraph_vector_push_back(&was, igraph_es_adj_vertex(&g, &it)); igraph_es_next(&g, &it); } igraph_es_destroy(&it); igraph_vector_sort(&was); igraph_vector_print(&was); } /* Simple test, outgoing neighbors */ for (i = 0; i <= igraph_vector_max(&v); i++) { igraph_vector_clear(&was); igraph_es_adj(&g, &it, i, IGRAPH_OUT); igraph_es_size(&g, &it, &size); printf("%ld\n", (long)size); while (!igraph_es_end(&g, &it)) { igraph_vector_push_back(&was, igraph_es_adj_vertex(&g, &it)); igraph_es_next(&g, &it); } igraph_es_destroy(&it); igraph_vector_sort(&was); igraph_vector_print(&was); } /* Simple test, incoming neighbors */ for (i = 0; i <= igraph_vector_max(&v); i++) { igraph_vector_clear(&was); igraph_es_adj(&g, &it, i, IGRAPH_IN); igraph_es_size(&g, &it, &size); printf("%ld\n", (long)size); while (!igraph_es_end(&g, &it)) { igraph_vector_push_back(&was, igraph_es_adj_vertex(&g, &it)); igraph_es_next(&g, &it); } igraph_es_destroy(&it); igraph_vector_sort(&was); igraph_vector_print(&was); } igraph_destroy(&g); /******************************************/ /* Undirected graph */ /******************************************/ igraph_create(&g, &v, 0, IGRAPH_UNDIRECTED); /* Simple test, all neighbors */ for (i = 0; i <= igraph_vector_max(&v); i++) { igraph_vector_clear(&was); igraph_es_adj(&g, &it, i, IGRAPH_ALL); igraph_es_size(&g, &it, &size); printf("%ld\n", (long)size); while (!igraph_es_end(&g, &it)) { igraph_vector_push_back(&was, igraph_es_adj_vertex(&g, &it)); igraph_es_next(&g, &it); } igraph_es_destroy(&it); igraph_vector_sort(&was); igraph_vector_print(&was); } igraph_destroy(&g); igraph_vector_destroy(&was); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_eigen_matrix4.c0000644000076500000240000000624513612122633030161 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #define DUMP() do { \ igraph_vector_complex_print(&values); \ igraph_vector_complex_print(&values2); \ } while(0) int main() { const int nodes = 10; igraph_matrix_t mat2; igraph_vector_complex_t values, values2; igraph_matrix_complex_t vectors, vectors2; igraph_eigen_which_t which; int i; igraph_rng_seed(igraph_rng_default(), 42); igraph_matrix_init(&mat2, nodes, nodes); for (i = 0; i < nodes; i++) { int j; for (j = 0; j < nodes; j++) { MATRIX(mat2, i, j) = igraph_rng_get_integer(igraph_rng_default(), 1, 10); } } igraph_vector_complex_init(&values, 0); igraph_matrix_complex_init(&vectors, 0, 0); which.pos = IGRAPH_EIGEN_LI; which.howmany = nodes; igraph_eigen_matrix(&mat2, /*sparsemat=*/ 0, /*fun=*/ 0, nodes, /*extra=*/ 0, IGRAPH_EIGEN_LAPACK, &which, /*options=*/ 0, /*storage=*/ 0, &values, &vectors); igraph_vector_complex_init(&values2, 0); igraph_matrix_complex_init(&vectors2, 0, 0); which.pos = IGRAPH_EIGEN_SI; which.howmany = nodes; igraph_eigen_matrix(&mat2, /*sparsemat=*/ 0, /*fun=*/ 0, nodes, /*extra=*/ 0, IGRAPH_EIGEN_LAPACK, &which, /*options=*/ 0, /*storage=*/ 0, &values2, &vectors2); igraph_vector_complex_print(&values); igraph_vector_complex_print(&values2); for (i = 0; i < nodes; i++) { int j; igraph_real_t d = igraph_complex_abs(igraph_complex_sub(VECTOR(values)[i], VECTOR(values2)[nodes - i - 1])); if (d > 1e-15) { DUMP(); return 2; } for (j = 0; j < nodes; j++) { igraph_real_t d = igraph_complex_abs(igraph_complex_sub(MATRIX(vectors, j, i), MATRIX(vectors2, j, nodes - i - 1))); if (d > 1e-15) { DUMP(); return 3; } } } igraph_vector_complex_destroy(&values); igraph_matrix_complex_destroy(&vectors); igraph_vector_complex_destroy(&values2); igraph_matrix_complex_destroy(&vectors2); igraph_matrix_destroy(&mat2); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_are_connected.c0000644000076500000240000000700413612122633030205 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* Test suite for whether two vertices are connected by an edge. Copyright (C) 2011 Minh Van Nguyen This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include #define R_INTEGER(a,b) (igraph_rng_get_integer(igraph_rng_default(), (a), (b))) /* Crash the library function here. We expect error codes to be returned here. */ int error_test() { igraph_t g; igraph_bool_t connected; igraph_integer_t nvert, u, v; int ret; igraph_rng_seed(igraph_rng_default(), time(0)); igraph_small(&g, /*nvert*/ 0, IGRAPH_UNDIRECTED, 0, 1, 1, 2, 2, 0, -1); nvert = igraph_vcount(&g); u = (igraph_integer_t)R_INTEGER(-100 * nvert, 100 * nvert); v = (igraph_integer_t)R_INTEGER(nvert, 100 * nvert); igraph_set_error_handler(igraph_error_handler_ignore); ret = igraph_are_connected(&g, u, v, &connected); if (ret != IGRAPH_EINVVID) { printf("Error test failed.\n"); return IGRAPH_FAILURE; } igraph_destroy(&g); return IGRAPH_SUCCESS; } /* Testing for two vertices being connected by an edge in various graphs. */ int connected_test() { igraph_t gcomplete, gempty; igraph_bool_t connected; igraph_integer_t nvert, u, v; igraph_rng_seed(igraph_rng_default(), time(0)); /* A complete graph on n vertices. Any two distinct vertices are connected */ /* by an edge. Hence we expect the test to return true for any given pair */ /* of distinct vertices. */ nvert = (igraph_integer_t)R_INTEGER(2, 100); igraph_full(&gcomplete, nvert, IGRAPH_UNDIRECTED, IGRAPH_NO_LOOPS); u = (igraph_integer_t)R_INTEGER(0, nvert - 1); do { v = (igraph_integer_t)R_INTEGER(0, nvert - 1); } while (v == u); igraph_are_connected(&gcomplete, u, v, &connected); if (!connected) { printf("Expected connected = true, but received connected = false.\n"); return IGRAPH_FAILURE; } igraph_destroy(&gcomplete); /* A graph with n vertices, but no edges. Any two distinct vertices are */ /* not joined by an edge. Thus we expect the test to return false for any */ /* given pair of distinct vertices. */ nvert = (igraph_integer_t)R_INTEGER(2, 100); igraph_empty(&gempty, nvert, IGRAPH_DIRECTED); u = (igraph_integer_t)R_INTEGER(0, nvert - 1); do { v = (igraph_integer_t)R_INTEGER(0, nvert - 1); } while (v == u); igraph_are_connected(&gempty, u, v, &connected); if (connected) { printf("Expected connected = false, but received connected = true.\n"); return IGRAPH_FAILURE; } igraph_destroy(&gempty); return IGRAPH_SUCCESS; } int main() { int ret; ret = error_test(); if (ret) { return IGRAPH_FAILURE; } ret = connected_test(); if (ret) { return IGRAPH_FAILURE; } return IGRAPH_SUCCESS; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/stack.c0000644000076500000240000000446313612122634025176 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_stack_t st; int i; /* igraph_stack_init, igraph_stack_destroy */ igraph_stack_init(&st, 0); igraph_stack_destroy(&st); igraph_stack_init(&st, 10); igraph_stack_destroy(&st); /* igraph_stack_reserve */ igraph_stack_init(&st, 0); igraph_stack_reserve(&st, 10); igraph_stack_reserve(&st, 5); /* igraph_stack_empty */ if (!igraph_stack_empty(&st)) { return 1; } igraph_stack_push(&st, 1); if (igraph_stack_empty(&st)) { return 2; } /* igraph_stack_size */ if (igraph_stack_size(&st) != 1) { return 3; } for (i = 0; i < 10; i++) { igraph_stack_push(&st, i); } if (igraph_stack_size(&st) != 11) { return 4; } /* igraph_stack_clear */ igraph_stack_clear(&st); if (!igraph_stack_empty(&st)) { return 5; } igraph_stack_push(&st, 100); if (igraph_stack_pop(&st) != 100) { return 6; } igraph_stack_clear(&st); igraph_stack_clear(&st); /* igraph_stack_push, igraph_stack_pop */ for (i = 0; i < 100; i++) { igraph_stack_push(&st, 100 - i); } for (i = 0; i < 100; i++) { if (igraph_stack_pop(&st) != i + 1) { return 7; } } if (!igraph_stack_empty(&st)) { return 8; } igraph_stack_destroy(&st); if (IGRAPH_FINALLY_STACK_SIZE() != 0) { return 9; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/edgelist4.dl0000644000076500000240000000014713524616144026133 0ustar tamasstaff00000000000000DL n=5 format = edgelist1 labels: george, sally, jim, billy, jane data: 1 2 1 3 -1 2 3 3 1 -1 4 3 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_weighted_adjacency.c0000644000076500000240000000571313612122634031223 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include void print(igraph_t *g) { igraph_vector_t el; long int i, j, n; char ch = igraph_is_directed(g) ? '>' : '-'; igraph_vector_init(&el, 0); igraph_get_edgelist(g, &el, 0); n = igraph_ecount(g); for (i = 0, j = 0; i < n; i++, j += 2) { printf("%ld --%c %ld: %ld\n", (long)VECTOR(el)[j], ch, (long)VECTOR(el)[j + 1], (long)EAN(g, "weight", i)); } printf("\n"); igraph_vector_destroy(&el); } int main() { igraph_t g; igraph_matrix_t mat; int m[4][4] = { { 0, 1, 2, 0 }, { 2, 0, 0, 1 }, { 0, 0, 1, 0 }, { 0, 1, 0, 0 } }; long int i, j; igraph_matrix_init(&mat, 4, 4); for (i = 0; i < 4; i++) for (j = 0; j < 4; j++) { MATRIX(mat, i, j) = m[i][j]; } igraph_i_set_attribute_table(&igraph_cattribute_table); /* [ 0 1 2 0 ] [ 2 0 0 1 ] [ 0 0 1 0 ] [ 0 1 0 0 ] */ igraph_weighted_adjacency(&g, &mat, IGRAPH_ADJ_DIRECTED, 0, /*loops=*/ 1); print(&g); igraph_destroy(&g); /* [ 0 1 2 0 ] [ - 0 0 1 ] [ - - 1 0 ] [ - - - 0 ] */ igraph_weighted_adjacency(&g, &mat, IGRAPH_ADJ_UPPER, 0, /*loops=*/ 1); print(&g); igraph_destroy(&g); /* [ 0 - - - ] [ 2 0 - - ] [ 0 0 1 - ] [ 0 1 0 0 ] */ igraph_weighted_adjacency(&g, &mat, IGRAPH_ADJ_LOWER, 0, /*loops=*/ 1); print(&g); igraph_destroy(&g); /* [ 0 1 0 0 ] [ 1 0 0 1 ] [ 0 0 1 0 ] [ 0 1 0 0 ] */ igraph_weighted_adjacency(&g, &mat, IGRAPH_ADJ_MIN, 0, /*loops=*/ 1); print(&g); igraph_destroy(&g); /* [ 0 2 2 0 ] [ 2 0 0 1 ] [ 2 0 1 0 ] [ 0 1 0 0 ] */ igraph_weighted_adjacency(&g, &mat, IGRAPH_ADJ_MAX, 0, /*loops=*/ 1); print(&g); igraph_destroy(&g); /* [ 0 3 2 0 ] [ 3 0 0 2 ] [ 2 0 1 0 ] [ 0 2 0 0 ] */ igraph_weighted_adjacency(&g, &mat, IGRAPH_ADJ_PLUS, 0, /*loops=*/ 1); print(&g); igraph_destroy(&g); igraph_matrix_destroy(&mat); if (IGRAPH_FINALLY_STACK_SIZE() != 0) { return 1; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/isomorphism_test.out0000644000076500000240000000000013524616144030053 0ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_marked_queue.c0000644000076500000240000000331213612122633030061 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include "igraph_marked_queue.h" int main() { igraph_marked_queue_t Q; long int i; igraph_marked_queue_init(&Q, 100); for (i = 0; i < 50; i++) { igraph_marked_queue_push(&Q, i); if (!igraph_marked_queue_iselement(&Q, i)) { return 4; } if (! ((i + 1) % 5)) { igraph_marked_queue_start_batch(&Q); } } for (i = 1; i < 50; i++) { if (!igraph_marked_queue_iselement(&Q, i)) { printf("Problem with %li.\n", i); return 3; } } for (i = 0; i <= 50 / 5; i++) { if (igraph_marked_queue_empty(&Q)) { return 1; } igraph_marked_queue_pop_back_batch(&Q); } if (!igraph_marked_queue_empty(&Q)) { return 2; } igraph_marked_queue_destroy(&Q); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_degree.out0000644000076500000240000000016313524616144027242 0ustar tamasstaff00000000000000 1 1 1 0 1 1 2 0 0 1 1 1 0 1 2 1 1 2 2 1 1 2 4 1 1 2 2 1 1 2 4 1 1 2 2 1 1 2 4 1 1 2 2 1 1 2 4 1 4 1 4 python-igraph-0.8.0/vendor/source/igraph/examples/simple/scg3.out0000644000076500000240000000364113524616144025320 0ustar tamasstaff00000000000000-------------------------------- 0 3 3 2 1 1 1 1 1 1 --- 5.52892+0i -0.493741+0i 0.569806+0i 0.569806+0i 0.10902+0i -0.125815+0i -0.125815+0i -0.125815+0i -0.125815+0i -0.125815+0i -0.125815+0i --- 0 2 0 3 1 3 2 0 3 0 3 1 --- col 0: locations 0 to 2 0 : 3 3 : -1 2 : -1 col 1: locations 3 to 4 1 : 1 3 : -3 col 2: locations 5 to 6 2 : 1 0 : -1 col 3: locations 7 to 9 3 : 4 0 : -2 1 : -1 --- 0 0 : 1 3 1 : 0.5 3 2 : 0.5 2 3 : 1 1 4 : 0.166667 1 5 : 0.166667 1 6 : 0.166667 1 7 : 0.166667 1 8 : 0.166667 1 9 : 0.166667 --- 0 0 : 1 3 1 : 1 3 2 : 1 2 3 : 1 1 4 : 1 1 5 : 1 1 6 : 1 1 7 : 1 1 8 : 1 1 9 : 1 --- -------------------------------- 3 2 2 0 1 1 1 1 1 1 --- 2.83255+0i 0.749697+0i 0.267318+0i 0.267318+0i -0.4091+0i -0.145872+0i -0.145872+0i -0.145872+0i -0.145872+0i -0.145872+0i -0.145872+0i --- 0 3 1 2 2 1 2 3 3 0 3 2 --- col 0: locations 0 to 1 0 : 1 3 : -1 col 1: locations 2 to 3 1 : 1 2 : -3 col 2: locations 4 to 6 2 : 4 3 : -2 1 : -1 col 3: locations 7 to 9 3 : 3 2 : -1 0 : -1 --- 3 0 : 1 2 1 : 0.5 2 2 : 0.5 0 3 : 1 1 4 : 0.166667 1 5 : 0.166667 1 6 : 0.166667 1 7 : 0.166667 1 8 : 0.166667 1 9 : 0.166667 --- 3 0 : 1 2 1 : 1 2 2 : 1 0 3 : 1 1 4 : 1 1 5 : 1 1 6 : 1 1 7 : 1 1 8 : 1 1 9 : 1 --- -------------------------------- 0 3 3 2 1 1 1 1 1 1 --- 5.52892+0i 2.83255+0i -0.493741+0i 0.749697+0i 0.569806+0i 0.267318+0i 0.569806+0i 0.267318+0i 0.10902+0i -0.4091+0i -0.125815+0i -0.145872+0i -0.125815+0i -0.145872+0i -0.125815+0i -0.145872+0i -0.125815+0i -0.145872+0i -0.125815+0i -0.145872+0i -0.125815+0i -0.145872+0i --- 0 2 0 3 1 3 2 0 3 0 3 1 --- col 0: locations 0 to 2 0 : 3 3 : -1 2 : -1 col 1: locations 3 to 4 1 : 1 3 : -3 col 2: locations 5 to 6 2 : 1 0 : -1 col 3: locations 7 to 9 3 : 4 0 : -2 1 : -1 --- 0 0 : 1 3 1 : 0.5 3 2 : 0.5 2 3 : 1 1 4 : 0.166667 1 5 : 0.166667 1 6 : 0.166667 1 7 : 0.166667 1 8 : 0.166667 1 9 : 0.166667 --- 0 0 : 1 3 1 : 1 3 2 : 1 2 3 : 1 1 4 : 1 1 5 : 1 1 6 : 1 1 7 : 1 1 8 : 1 1 9 : 1 --- python-igraph-0.8.0/vendor/source/igraph/examples/simple/pajek2.c0000644000076500000240000000271313614300625025241 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; FILE *ifile; int i, n; /* turn on attribute handling */ igraph_i_set_attribute_table(&igraph_cattribute_table); ifile = fopen("bipartite.net", "r"); if (!ifile) { return 5; } igraph_read_graph_pajek(&g, ifile); fclose(ifile); if (igraph_vcount(&g) != 13 || igraph_ecount(&g) != 11 || igraph_is_directed(&g)) { return 6; } for (i = 0, n = igraph_vcount(&g); i < n; i++) { printf("%i ", (int) VAN(&g, "type", i)); } printf("\n"); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/pajek_bipartite2.c0000644000076500000240000000667113612122634027313 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int print_attributes(const igraph_t *g) { igraph_vector_t gtypes, vtypes, etypes; igraph_strvector_t gnames, vnames, enames; long int i; igraph_vector_init(>ypes, 0); igraph_vector_init(&vtypes, 0); igraph_vector_init(&etypes, 0); igraph_strvector_init(&gnames, 0); igraph_strvector_init(&vnames, 0); igraph_strvector_init(&enames, 0); igraph_cattribute_list(g, &gnames, >ypes, &vnames, &vtypes, &enames, &etypes); for (i = 0; i < igraph_vcount(g); i++) { long int j; printf("Vertex %li: ", i); for (j = 0; j < igraph_strvector_size(&vnames); j++) { printf("%s=", STR(vnames, j)); if (VECTOR(vtypes)[j] == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_real_printf(VAN(g, STR(vnames, j), i)); putchar(' '); } else { printf("\"%s\" ", VAS(g, STR(vnames, j), i)); } } printf("\n"); } for (i = 0; i < igraph_ecount(g); i++) { long int j; int u = IGRAPH_FROM(g, i), v = IGRAPH_TO(g, i); if (u < v && !igraph_is_directed(g)) { u = IGRAPH_TO(g, i); v = IGRAPH_FROM(g, i); } printf("Edge %li (%i-%i): ", i, u, v); for (j = 0; j < igraph_strvector_size(&enames); j++) { printf("%s=", STR(enames, j)); if (VECTOR(etypes)[j] == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_real_printf(EAN(g, STR(enames, j), i)); putchar(' '); } else { printf("\"%s\" ", EAS(g, STR(enames, j), i)); } } printf("\n"); } igraph_strvector_destroy(&enames); igraph_strvector_destroy(&vnames); igraph_strvector_destroy(&gnames); igraph_vector_destroy(&etypes); igraph_vector_destroy(&vtypes); igraph_vector_destroy(>ypes); return 0; } int main() { igraph_t graph; FILE *input; /* turn on attribute handling */ igraph_i_set_attribute_table(&igraph_cattribute_table); /* first file, without marginals */ input = fopen("pajek_bip.net", "r"); if (input == 0) { return 1; } igraph_read_graph_pajek(&graph, input); fclose(input); print_attributes(&graph); igraph_destroy(&graph); /* second file, with marginals */ printf("---\n"); input = fopen("pajek_bip2.net", "r"); if (input == 0) { return 1; } igraph_read_graph_pajek(&graph, input); fclose(input); print_attributes(&graph); igraph_destroy(&graph); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/pajek4.net0000644000076500000240000000103113524616144025605 0ustar tamasstaff00000000000000*Vertices 10 1 "Vert 1" 0 0 box x_fact 1 y_fact 1 ic Green 2 "Vert 2" 0 0 box x_fact 1 y_fact 1 ic Green 3 "Vert 3" 0 0 box x_fact 1 y_fact 1 ic Green 4 "Vert 4" 0 0 box x_fact 1 y_fact 1 ic Green 5 "Vert 5" 0 0 box x_fact 1 y_fact 1 ic Green 6 "Vert 6" 0 0 box x_fact 1 y_fact 1 ic Blue 7 "Vert 7" 0 0 box x_fact 1 y_fact 1 ic Red 8 "Vert 8" 0 0 box x_fact 1 y_fact 1 ic Green 9 "Vert 9" 0 0 box x_fact 1 y_fact 1 ic Green 10 "Vert 10" 0 0 box x_fact 1 y_fact 1 ic Green *Edges 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_sparsemat6.c0000644000076500000240000000400613612122634027501 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_matrix_t mat, mat2, mat3; igraph_sparsemat_t spmat, spmat2; int i; igraph_rng_seed(igraph_rng_default(), 42); #define NROW 10 #define NCOL 7 #define NZERO 15 igraph_matrix_init(&mat, NROW, NCOL); for (i = 0; i < NZERO; i++) { int r = igraph_rng_get_integer(igraph_rng_default(), 0, NROW - 1); int c = igraph_rng_get_integer(igraph_rng_default(), 0, NCOL - 1); igraph_real_t val = igraph_rng_get_integer(igraph_rng_default(), 1, 10); MATRIX(mat, r, c) = val; } igraph_matrix_as_sparsemat(&spmat, &mat, /*tol=*/ 1e-14); igraph_matrix_init(&mat2, 0, 0); igraph_sparsemat_as_matrix(&mat2, &spmat); if (!igraph_matrix_all_e(&mat, &mat2)) { return 1; } igraph_sparsemat_compress(&spmat, &spmat2); igraph_matrix_init(&mat3, 0, 0); igraph_sparsemat_as_matrix(&mat3, &spmat2); if (!igraph_matrix_all_e(&mat, &mat3)) { return 2; } igraph_matrix_destroy(&mat); igraph_matrix_destroy(&mat2); igraph_matrix_destroy(&mat3); igraph_sparsemat_destroy(&spmat); igraph_sparsemat_destroy(&spmat2); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_simplify.c0000644000076500000240000000611513612122633027252 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; /* Multiple edges */ igraph_small(&g, 0, IGRAPH_DIRECTED, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, -1); igraph_simplify(&g, 1, 1, /*edge_comb=*/ 0); igraph_write_graph_edgelist(&g, stdout); igraph_destroy(&g); igraph_small(&g, 0, IGRAPH_UNDIRECTED, 1, 0, 0, 1, 1, 0, 0, 1, 0, 1, -1); igraph_simplify(&g, 1, 1, /*edge_comb=*/ 0); if (igraph_ecount(&g) != 1) { return 1; } igraph_destroy(&g); /* Loop edges*/ igraph_small(&g, 0, IGRAPH_DIRECTED, 0, 0, 1, 1, 2, 2, 1, 2, -1); igraph_simplify(&g, 1, 1, /*edge_comb=*/ 0); igraph_write_graph_edgelist(&g, stdout); igraph_destroy(&g); igraph_small(&g, 0, IGRAPH_UNDIRECTED, 0, 0, 1, 1, 2, 2, 1, 2, -1); igraph_simplify(&g, 1, 1, /*edge_comb=*/ 0); igraph_write_graph_edgelist(&g, stdout); igraph_destroy(&g); /* Loop & multiple edges */ igraph_small(&g, 0, IGRAPH_DIRECTED, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, -1); igraph_simplify(&g, 1 /* multiple */, 0 /* loop */, /*edge_comb=*/ 0); igraph_write_graph_edgelist(&g, stdout); igraph_destroy(&g); igraph_small(&g, 0, IGRAPH_UNDIRECTED, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, -1); igraph_simplify(&g, 1 /* multiple */, 0 /* loop */, /*edge_comb=*/ 0); igraph_write_graph_edgelist(&g, stdout); igraph_destroy(&g); igraph_small(&g, 0, IGRAPH_DIRECTED, 2, 2, 2, 2, 2, 2, 3, 2, -1); igraph_simplify(&g, 0 /* multiple */, 1 /* loop */, /*edge_comb=*/ 0); igraph_write_graph_edgelist(&g, stdout); igraph_destroy(&g); igraph_small(&g, 0, IGRAPH_UNDIRECTED, 3, 3, 3, 3, 3, 4, -1); igraph_simplify(&g, 0 /* multiple */, 1 /* loop */, /*edge_comb=*/ 0); igraph_write_graph_edgelist(&g, stdout); igraph_destroy(&g); igraph_small(&g, 0, IGRAPH_DIRECTED, 2, 2, 2, 2, 2, 2, 2, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3, 2, -1); igraph_simplify(&g, 1, 1, /*edge_comb=*/ 0); igraph_write_graph_edgelist(&g, stdout); igraph_destroy(&g); igraph_small(&g, 0, IGRAPH_UNDIRECTED, 2, 2, 2, 2, 2, 2, 2, 2, 3, 2, 2, 3, 3, 2, 3, 2, 3, 2, -1); igraph_simplify(&g, 1, 1, /*edge_comb=*/ 0); if (igraph_ecount(&g) != 1) { return 2; } igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/bellman_ford.c0000644000076500000240000000732213612122633026511 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2008-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int print_matrix(const igraph_matrix_t *m) { long int nrow = igraph_matrix_nrow(m); long int ncol = igraph_matrix_ncol(m); long int i, j; igraph_real_t val; for (i = 0; i < nrow; i++) { printf("%li:", i); for (j = 0; j < ncol; j++) { val = MATRIX(*m, i, j); if (igraph_is_inf(val)) { if (val < 0) { printf("-inf"); } else { printf(" inf"); } } else { printf(" %3.0f", val); } } printf("\n"); } return 0; } int main() { igraph_t g; igraph_vector_t weights; igraph_real_t weights_data_0[] = { 0, 2, 1, 0, 5, 2, 1, 1, 0, 2, 2, 8, 1, 1, 3, 1, 1, 4, 2, 1 }; igraph_real_t weights_data_1[] = { 6, 7, 8, -4, -2, -3, 9, 2, 7 }; igraph_real_t weights_data_2[] = { 6, 7, 2, -4, -2, -3, 9, 2, 7 }; igraph_matrix_t res; /* Graph with only positive weights */ igraph_small(&g, 10, IGRAPH_DIRECTED, 0, 1, 0, 2, 0, 3, 1, 2, 1, 4, 1, 5, 2, 3, 2, 6, 3, 2, 3, 6, 4, 5, 4, 7, 5, 6, 5, 8, 5, 9, 7, 5, 7, 8, 8, 9, 5, 2, 2, 1, -1); igraph_vector_view(&weights, weights_data_0, sizeof(weights_data_0) / sizeof(igraph_real_t)); igraph_matrix_init(&res, 0, 0); igraph_shortest_paths_bellman_ford(&g, &res, igraph_vss_all(), igraph_vss_all(), &weights, IGRAPH_OUT); print_matrix(&res); igraph_matrix_destroy(&res); igraph_destroy(&g); printf("\n"); /***************************************/ /* Graph with negative weights */ igraph_small(&g, 5, IGRAPH_DIRECTED, 0, 1, 0, 3, 1, 3, 1, 4, 2, 1, 3, 2, 3, 4, 4, 0, 4, 2, -1); igraph_vector_view(&weights, weights_data_1, sizeof(weights_data_1) / sizeof(igraph_real_t)); igraph_matrix_init(&res, 0, 0); igraph_shortest_paths_bellman_ford(&g, &res, igraph_vss_all(), igraph_vss_all(), &weights, IGRAPH_OUT); print_matrix(&res); /***************************************/ /* Same graph with negative loop */ igraph_set_error_handler(igraph_error_handler_ignore); igraph_vector_view(&weights, weights_data_2, sizeof(weights_data_2) / sizeof(igraph_real_t)); if (igraph_shortest_paths_bellman_ford(&g, &res, igraph_vss_all(), igraph_vss_all(), &weights, IGRAPH_OUT) != IGRAPH_ENEGLOOP) { return 1; } igraph_matrix_destroy(&res); igraph_destroy(&g); if (!IGRAPH_FINALLY_STACK_EMPTY) { return 1; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/single_target_shortest_path.out0000644000076500000240000000005313524616144032251 0ustar tamasstaff000000000000000 3 4 4 3 0 4 3 0 3 4 0 1 2 3 4 0 1 2 3 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_write_graph_lgl.c0000644000076500000240000000313313612122634030565 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int main(int argc, char **argv) { /* igraph_t g; */ /* igraph_error_handler_t *oldhandler; */ /* FILE *ofile; */ /* int ret; */ /* This is not used right now, as we don't have attributes */ /* Testing error handling */ /* igraph_barabasi_game(&g, 10, 1, 0, 0, IGRAPH_DIRECTED); */ /* oldhandler=igraph_set_error_handler(igraph_error_handler_ignore); */ /* ofile=fopen("test.txt", "w"); */ /* ret=igraph_write_graph_lgl(&g, ofile, "names", "weights", 1); */ /* if (ret != IGRAPH_EINVAL) { */ /* return 1; */ /* } */ /* fclose(ofile); */ /* igraph_destroy(&g); */ /* igraph_set_error_handler(oldhandler); */ return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_lapack_dgesv.out0000644000076500000240000000005013524616144030425 0ustar tamasstaff00000000000000Warning: LU: factor is exactly singular python-igraph-0.8.0/vendor/source/igraph/examples/simple/VF2-compat.c0000644000076500000240000001701213612122633025740 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include /* ----------------------------------------------------------- */ /* Vertices/edges with the same parity match */ igraph_bool_t compat_parity(const igraph_t *graph1, const igraph_t *graph2, const igraph_integer_t g1_num, const igraph_integer_t g2_num, void *arg) { return (g1_num % 2) == (g2_num % 2); } /* Nothing vertex/edge 0 in graph1 */ igraph_bool_t compat_not0(const igraph_t *graph1, const igraph_t *graph2, const igraph_integer_t g1_num, const igraph_integer_t g2_num, void *arg) { return g1_num != 0; } int match_rings() { igraph_t r1, r2; igraph_bool_t iso; igraph_integer_t count; igraph_ring(&r1, 10, /*directed=*/ 0, /*mutual=*/ 0, /*circular=*/ 1); igraph_ring(&r2, 10, /*directed=*/ 0, /*mutual=*/ 0, /*circular=*/ 1); igraph_isomorphic_vf2(&r1, &r2, /*colors(4x)*/ 0, 0, 0, 0, &iso, /*map12=*/ 0, /*map21=*/ 0, /*node_compat_fn=*/ 0, /*edge_compat_fn=*/ 0, /*arg=*/ 0); if (!iso) { exit(1); } igraph_isomorphic_vf2(&r1, &r2, /*colors(4x)*/ 0, 0, 0, 0, &iso, /*map12=*/ 0, /*map21=*/ 0, compat_parity, /*edge_compat_fn=*/ 0, /*arg=*/ 0); if (!iso) { exit(2); } igraph_isomorphic_vf2(&r1, &r2, /*colors(4x)*/ 0, 0, 0, 0, &iso, /*map12=*/ 0, /*map21=*/ 0, compat_not0, /*edge_compat_fn=*/ 0, /*arg=*/ 0); if (iso) { exit(3); } /* ------- */ igraph_isomorphic_vf2(&r1, &r2, /*colors(4x)*/ 0, 0, 0, 0, &iso, /*map12=*/ 0, /*map21=*/ 0, /*node_compat_fn=*/ 0, compat_parity, /*arg=*/ 0); if (!iso) { exit(4); } igraph_isomorphic_vf2(&r1, &r2, /*colors(4x)*/ 0, 0, 0, 0, &iso, /*map12=*/ 0, /*map21=*/ 0, /*node_compat_fn=*/ 0, compat_not0, /*arg=*/ 0); if (iso) { exit(5); } /* ------- */ igraph_count_isomorphisms_vf2(&r1, &r2, /*colors(4x)*/ 0, 0, 0, 0, &count, /*node_compat_fn=*/ 0, /*edge_compat_fn=*/ 0, /*arg=*/ 0); if (count != 20) { exit(6); } igraph_count_isomorphisms_vf2(&r1, &r2, /*colors(4x)*/ 0, 0, 0, 0, &count, compat_parity, /*edge_compat_fn=*/ 0, /*arg=*/ 0); if (count != 10) { exit(7); } igraph_count_isomorphisms_vf2(&r1, &r2, /*colors(4x)*/ 0, 0, 0, 0, &count, compat_not0, /*edge_compat_fn=*/ 0, /*arg=*/ 0); if (count != 0) { exit(8); } /* ------- */ igraph_count_isomorphisms_vf2(&r1, &r2, /*colors(4x)*/ 0, 0, 0, 0, &count, /*node_compat_fn=*/ 0, compat_parity, /*arg=*/ 0); if (count != 10) { exit(9); } igraph_count_isomorphisms_vf2(&r1, &r2, /*colors(4x)*/ 0, 0, 0, 0, &count, /*node_compat_fn=*/ 0, compat_not0, /*arg=*/ 0); if (count != 0) { exit(10); } igraph_destroy(&r1); igraph_destroy(&r2); return 0; } int match_rings_open_closed() { igraph_t ro, rc; igraph_bool_t iso; igraph_integer_t count; igraph_ring(&ro, 10, /*directed=*/ 0, /*mutual=*/ 0, /*circular=*/ 0); igraph_ring(&rc, 10, /*directed=*/ 0, /*mutual=*/ 0, /*circular=*/ 1); igraph_subisomorphic_vf2(&rc, &ro, /*colors(4x)*/ 0, 0, 0, 0, &iso, /*map12=*/ 0, /*map21=*/ 0, /*node_compat_fn=*/ 0, /*edge_compat_fn=*/ 0, /*arg=*/ 0); if (!iso) { exit(31); } igraph_subisomorphic_vf2(&rc, &ro, /*colors(4x)*/ 0, 0, 0, 0, &iso, /*map12=*/ 0, /*map21=*/ 0, compat_parity, /*edge_compat_fn=*/ 0, /*arg=*/ 0); if (!iso) { exit(32); } igraph_subisomorphic_vf2(&rc, &ro, /*colors(4x)*/ 0, 0, 0, 0, &iso, /*map12=*/ 0, /*map21=*/ 0, compat_not0, /*edge_compat_fn=*/ 0, /*arg=*/ 0); if (iso) { exit(33); } /* ------- */ igraph_subisomorphic_vf2(&rc, &ro, /*colors(4x)*/ 0, 0, 0, 0, &iso, /*map12=*/ 0, /*map21=*/ 0, /*node_compat_fn=*/ 0, compat_parity, /*arg=*/ 0); if (!iso) { exit(34); } igraph_subisomorphic_vf2(&rc, &ro, /*colors(4x)*/ 0, 0, 0, 0, &iso, /*map12=*/ 0, /*map21=*/ 0, /*node_compat_fn=*/ 0, compat_not0, /*arg=*/ 0); if (!iso) { exit(35); } /* ------- */ igraph_count_subisomorphisms_vf2(&rc, &ro, /*colors(4x)*/ 0, 0, 0, 0, &count, /*node_compat_fn=*/ 0, /*edge_compat_fn=*/ 0, /*arg=*/ 0); if (count != 20) { exit(36); } igraph_count_subisomorphisms_vf2(&rc, &ro, /*colors(4x)*/ 0, 0, 0, 0, &count, compat_parity, /*edge_compat_fn=*/ 0, /*arg=*/ 0); if (count != 10) { exit(37); } igraph_count_subisomorphisms_vf2(&rc, &ro, /*colors(4x)*/ 0, 0, 0, 0, &count, compat_not0, /*edge_compat_fn=*/ 0, /*arg=*/ 0); if (count != 0) { exit(38); } /* ------- */ igraph_count_subisomorphisms_vf2(&rc, &ro, /*colors(4x)*/ 0, 0, 0, 0, &count, /*node_compat_fn=*/ 0, compat_parity, /*arg=*/ 0); if (count != 10) { exit(39); } igraph_count_subisomorphisms_vf2(&rc, &ro, /*colors(4x)*/ 0, 0, 0, 0, &count, /*node_compat_fn=*/ 0, compat_not0, /*arg=*/ 0); if (count != 2) { exit(40); } igraph_destroy(&ro); igraph_destroy(&rc); return 0; } /* ----------------------------------------------------------- */ int main() { match_rings(); match_rings_open_closed(); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_hrg3.out0000644000076500000240000001631413524616144026657 0ustar tamasstaff0000000000000028 32 0 16 27 32 9 32 26 32 4 5 4 16 10 16 6 10 1 12 2 17 2 19 2 21 2 18 2 31 2 30 2 29 2 23 2 20 2 33 2 15 2 22 2 14 2 26 2 12 3 17 3 21 7 13 3 19 2 24 2 25 23 26 24 33 27 29 0 26 25 33 2 11 0 25 2 16 2 4 2 5 2 6 2 10 1 11 26 27 9 24 14 25 25 30 25 29 20 25 18 25 22 25 25 32 15 25 25 28 8 25 0 9 0 27 0 22 0 32 0 33 0 14 0 28 0 15 0 29 0 18 0 30 0 20 0 23 9 25 24 26 14 24 15 24 22 24 24 29 23 24 24 28 18 24 20 24 24 30 24 32 8 24 25 27 25 26 0 24 12 13 7 12 12 21 12 17 12 19 3 11 9 27 7 19 26 30 23 31 8 27 26 31 27 28 9 31 18 26 8 26 15 26 7 17 14 26 20 26 27 30 26 28 27 31 8 14 29 31 22 26 20 27 14 27 7 21 8 9 13 19 18 23 15 27 30 31 8 31 9 30 22 27 8 23 11 16 28 29 14 23 9 29 9 26 13 21 6 11 19 25 17 24 19 24 19 26 1 24 3 24 13 24 9 19 15 19 19 20 19 31 19 28 19 23 18 19 19 30 8 19 19 32 19 29 19 27 14 19 23 30 19 22 12 24 7 24 9 23 21 24 17 25 3 25 1 25 18 27 13 25 8 28 9 11 12 25 11 26 5 11 7 25 6 26 11 18 3 26 11 14 11 22 6 25 11 31 11 23 11 20 11 27 11 32 3 9 11 33 11 29 11 15 11 28 11 30 8 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0.0228156 0.022807 0.0228039 0.0228029 0.0228021 0.0224223 0.0224216 0.0224215 0.0224211 0.0224203 0.0224197 0.0224191 0.0224184 0.022417 0.0224165 0.0224151 0.0224148 0.0224143 0.0224142 0.0224142 0.0224141 0.0224134 0.0224131 0.0224131 0.0224129 0.0224128 0.0224125 0.0224125 0.0224124 0.0224123 0.0224121 0.0224121 0.0224114 0.022411 0.0224107 0.0224104 0.0224102 0.0224101 0.0224096 0.0224095 0.0224094 0.0224077 0.0224072 0.0224065 0.0224063 0.0224056 0.0224052 0.0224049 0.0224044 0.0224042 0.0224041 0.022404 0.0224037 0.0224036 0.0224034 0.0224032 0.0224031 0.022403 0.0224029 0.0224026 0.0224018 0.0224016 0.0224013 0.0224007 0.0216173 0.0216148 0.0216058 0.0212203 0.0212042 0.0208108 0.0200013 0.0196172 0.0196143 0.0196133 0.019607 0.0196048 0.0196009 0.0192092 0.0192003 0.018008 0.0176086 0.0172075 0.0168134 0.0156149 0.0156131 0.0156029 0.014807 0.0136058 0.0136001 0.0124021 0.0108058 0.0100088 0.010001 0.00960377 0.00960348 0.00960337 0.00800783 0.00800481 0.00800239 0.00760756 0.00760068 0.00720552 0.00720059 0.00680338 0.00680201 0.00680079 0.00640602 0.00640375 0.00640105 0.00640075 0.00640054 0.00600575 0.0060053 0.00600322 0.00600158 0.00520508 0.00520475 0.00520195 0.00520112 0.00480422 0.00480307 0.00480259 0.00480227 0.00480201 0.00480169 0.00480167 0.00480059 0.00480054 0.0048004 0.00480027 0.00480025 0.00400192 0.00360318 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_to_undirected.out0000644000076500000240000000036113524616144030637 0ustar tamasstaff000000000000000 1 0 5 1 2 1 6 2 3 2 7 3 4 3 8 4 9 5 6 5 10 6 7 6 11 7 8 7 12 8 9 8 13 9 14 10 11 10 15 11 12 11 16 12 13 12 17 13 14 13 18 14 19 15 16 15 20 16 17 16 21 17 18 17 22 18 19 18 23 19 24 20 21 21 22 22 23 23 24 --- 5 6 6 7 7 8 7 8 8 8 9 9 9 9 python-igraph-0.8.0/vendor/source/igraph/examples/simple/tls1.c0000644000076500000240000000274313612122634024753 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard street, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include void *thread_function(void *arg) { IGRAPH_FINALLY(0, 0); return 0; } int main() { pthread_t thread_id; void *exit_status; /* Skip if igraph is not thread-safe */ if (!IGRAPH_THREAD_SAFE) { return 77; } /* Run a thread that leaves some junk in the error stack */ pthread_create(&thread_id, NULL, thread_function, 0); pthread_join(thread_id, &exit_status); /* Check that the error stack is not common */ if (!IGRAPH_FINALLY_STACK_EMPTY) { printf("Foobar\n"); return 1; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/matrix3.c0000644000076500000240000000237413612122634025457 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2012 Gabor Csardi 334 Harvard st, Cambridge MA, USA 02139 This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_matrix_t m; igraph_matrix_init(&m, 10, 10); if (igraph_matrix_capacity(&m) != 100) { return 1; } igraph_matrix_add_cols(&m, 5); igraph_matrix_resize(&m, 5, 5); igraph_matrix_resize_min(&m); if (igraph_matrix_capacity(&m) != igraph_matrix_size(&m)) { return 2; } igraph_matrix_destroy(&m); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_set.out0000644000076500000240000000006713524616144026605 0ustar tamasstaff00000000000000 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_convergence_degree.c0000644000076500000240000000313413612122633031225 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_vector_t result; long i; igraph_vector_init(&result, 0); igraph_small(&g, 7, 0, 0, 1, 0, 2, 0, 3, 1, 2, 1, 3, 2, 3, 3, 4, 4, 5, 4, 6, 5, 6, -1); igraph_convergence_degree(&g, &result, 0, 0); for (i = 0; i < igraph_ecount(&g); i++) { printf("%.4f ", (float)igraph_vector_e(&result, i)); } printf("\n"); igraph_destroy(&g); igraph_small(&g, 6, 1, 1, 0, 2, 0, 3, 0, 4, 0, 0, 5, -1); igraph_convergence_degree(&g, &result, 0, 0); for (i = 0; i < igraph_ecount(&g); i++) { printf("%.4f ", (float)igraph_vector_e(&result, i)); } printf("\n"); igraph_destroy(&g); igraph_vector_destroy(&result); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_read_graph_dl.c0000644000076500000240000000377213612122633030177 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include int main() { const char *files[] = { "fullmatrix1.dl", "fullmatrix2.dl", "fullmatrix3.dl", "fullmatrix4.dl", "edgelist1.dl", "edgelist2.dl", "edgelist3.dl", "edgelist4.dl", "edgelist5.dl", "edgelist6.dl", "edgelist7.dl", "nodelist1.dl", "nodelist2.dl" }; int no_files = sizeof(files) / sizeof(const char*); int i, ret; igraph_t g; FILE *infile; for (i = 0; i < no_files; i++) { printf("Doing %s\n", files[i]); infile = fopen(files[i], "r"); if (!infile) { printf("Cannot open file: %s\n", files[i]); exit(1 + i); } igraph_read_graph_dl(&g, infile, /*directed=*/ 1); ret = fclose(infile); if (ret) { printf("Cannot close file: %s\n", files[i]); exit(101 + i); } igraph_write_graph_edgelist(&g, stdout); igraph_destroy(&g); } if (IGRAPH_FINALLY_STACK_SIZE() != 0) { return 1; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_bfs.out0000644000076500000240000000025513524616144026563 0ustar tamasstaff00000000000000 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 10 0 0 1 2 3 4 5 6 7 8 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 0 1 3 7 15 20 0 0 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 python-igraph-0.8.0/vendor/source/igraph/examples/simple/topology.out0000644000076500000240000000004613524616144026331 0ustar tamasstaff00000000000000class: 12 class: 5 class: 15 class: 0 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_maximal_cliques2.out0000644000076500000240000000010213524616144031237 0ustar tamasstaff000000000000000 1 0 9 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 --- 0 7 10 11 13 24 34 42 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_get_shortest_paths.c0000644000076500000240000001006513614300625031327 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include void print_vector(igraph_vector_t *v) { long int i, l = igraph_vector_size(v); for (i = 0; i < l; i++) { printf(" %li", (long int) VECTOR(*v)[i]); } printf("\n"); } int check_evecs(const igraph_t *graph, const igraph_vector_ptr_t *vecs, const igraph_vector_ptr_t *evecs, int error_code) { igraph_bool_t directed = igraph_is_directed(graph); long int i, n = igraph_vector_ptr_size(vecs); if (igraph_vector_ptr_size(evecs) != n) { exit(error_code + 1); } for (i = 0; i < n; i++) { igraph_vector_t *vvec = VECTOR(*vecs)[i]; igraph_vector_t *evec = VECTOR(*evecs)[i]; long int j, n2 = igraph_vector_size(evec); if (igraph_vector_size(vvec) == 0 && n2 == 0) { continue; } if (igraph_vector_size(vvec) != n2 + 1) { exit(error_code + 2); } for (j = 0; j < n2; j++) { long int edge = VECTOR(*evec)[j]; long int from = VECTOR(*vvec)[j]; long int to = VECTOR(*vvec)[j + 1]; if (directed) { if (from != IGRAPH_FROM(graph, edge) || to != IGRAPH_TO (graph, edge)) { exit(error_code); } } else { long int from2 = IGRAPH_FROM(graph, edge); long int to2 = IGRAPH_TO(graph, edge); long int min1 = from < to ? from : to; long int max1 = from < to ? to : from; long int min2 = from2 < to2 ? from2 : to2; long int max2 = from2 < to2 ? to2 : from2; if (min1 != min2 || max1 != max2) { exit(error_code + 3); } } } } return 0; } int main() { igraph_t g; igraph_vector_ptr_t vecs, evecs; igraph_vector_long_t pred, inbound; long int i; igraph_vs_t vs; igraph_ring(&g, 10, IGRAPH_DIRECTED, 0, 1); igraph_vector_ptr_init(&vecs, 5); igraph_vector_ptr_init(&evecs, 5); igraph_vector_long_init(&pred, 0); igraph_vector_long_init(&inbound, 0); for (i = 0; i < igraph_vector_ptr_size(&vecs); i++) { VECTOR(vecs)[i] = calloc(1, sizeof(igraph_vector_t)); igraph_vector_init(VECTOR(vecs)[i], 0); VECTOR(evecs)[i] = calloc(1, sizeof(igraph_vector_t)); igraph_vector_init(VECTOR(evecs)[i], 0); } igraph_vs_vector_small(&vs, 1, 3, 5, 2, 1, -1); igraph_get_shortest_paths(&g, &vecs, &evecs, 0, vs, IGRAPH_OUT, &pred, &inbound); check_evecs(&g, &vecs, &evecs, 10); for (i = 0; i < igraph_vector_ptr_size(&vecs); i++) { print_vector(VECTOR(vecs)[i]); igraph_vector_destroy(VECTOR(vecs)[i]); free(VECTOR(vecs)[i]); igraph_vector_destroy(VECTOR(evecs)[i]); free(VECTOR(evecs)[i]); } igraph_vector_long_print(&pred); igraph_vector_long_print(&inbound); igraph_vector_ptr_destroy(&vecs); igraph_vector_ptr_destroy(&evecs); igraph_vector_long_destroy(&pred); igraph_vector_long_destroy(&inbound); igraph_vs_destroy(&vs); igraph_destroy(&g); if (!IGRAPH_FINALLY_STACK_EMPTY) { return 1; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_cliques.c0000644000076500000240000001056013612122633027062 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int compare_vectors(const void *p1, const void *p2) { igraph_vector_t *v1, *v2; long s1, s2, i; v1 = *((igraph_vector_t **) p1); v2 = *((igraph_vector_t **) p2); s1 = igraph_vector_size(v1); s2 = igraph_vector_size(v2); if (s1 < s2) { return -1; } if (s1 > s2) { return 1; } for (i = 0; i < s1; ++i) { if (VECTOR(*v1)[i] < VECTOR(*v2)[i]) { return -1; } if (VECTOR(*v1)[i] > VECTOR(*v2)[i]) { return 1; } } return 0; } /* Takes a pointer vector of vectors. Sorts each vector, then sorts the pointer vector */ void canonicalize_list(igraph_vector_ptr_t *list) { long i, len; len = igraph_vector_ptr_size(list); for (i = 0; i < len; ++i) { igraph_vector_sort((igraph_vector_t *) VECTOR(*list)[i]); } qsort(&(VECTOR(*list)[0]), len, sizeof(void *), &compare_vectors); } void print_vector(igraph_vector_t *v) { long int i, n = igraph_vector_size(v); for (i = 0; i < n; i++) { printf(" %li", (long int) VECTOR(*v)[i]); } printf("\n"); } void warning_handler_ignore(const char* reason, const char* file, int line, int e) { } struct userdata { int i; igraph_vector_ptr_t *list; }; igraph_bool_t handler(igraph_vector_t *clique, void *arg) { struct userdata *ud; igraph_bool_t cont; ud = (struct userdata *) arg; cont = 1; /* true */ if (compare_vectors(&clique, &(VECTOR(*(ud->list))[ud->i])) != 0) { printf("igraph_cliques() and igraph_cliques_callback() give different results.\n"); cont = 0; /* false */ } igraph_vector_destroy(clique); igraph_free(clique); ud->i += 1; return cont; } void test_callback(const igraph_t *graph) { igraph_vector_ptr_t list; struct userdata ud; igraph_vector_ptr_init(&list, 0); igraph_cliques(graph, &list, 0, 0); ud.i = 0; ud.list = &list; igraph_cliques_callback(graph, 0, 0, &handler, (void *) &ud); IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(&list, igraph_vector_destroy); igraph_vector_ptr_destroy_all(&list); } int main() { igraph_t g; igraph_vector_ptr_t result; igraph_es_t es; igraph_integer_t omega; long int i, j, n; const int params[] = {4, -1, 2, 2, 0, 0, -1, -1}; igraph_set_warning_handler(warning_handler_ignore); igraph_vector_ptr_init(&result, 0); igraph_full(&g, 6, 0, 0); igraph_es_pairs_small(&es, 0, 0, 1, 0, 2, 3, 5, -1); igraph_delete_edges(&g, es); igraph_es_destroy(&es); for (j = 0; j < sizeof(params) / (2 * sizeof(params[0])); j++) { if (params[2 * j + 1] != 0) { igraph_cliques(&g, &result, params[2 * j], params[2 * j + 1]); } else { igraph_largest_cliques(&g, &result); } n = igraph_vector_ptr_size(&result); printf("%ld cliques found\n", (long)n); canonicalize_list(&result); for (i = 0; i < n; i++) { igraph_vector_t* v = (igraph_vector_t*) igraph_vector_ptr_e(&result, i); print_vector(v); igraph_vector_destroy(v); free(v); } } igraph_clique_number(&g, &omega); printf("omega=%ld\n", (long)omega); test_callback(&g); igraph_destroy(&g); igraph_tree(&g, 5, 2, IGRAPH_TREE_OUT); igraph_cliques(&g, &result, 5, 5); if (igraph_vector_ptr_size(&result) != 0) { return 1; } igraph_destroy(&g); igraph_vector_ptr_destroy(&result); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/vector.c0000644000076500000240000002356313612122634025375 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include void print_vector(igraph_vector_t *v, FILE *f) { long int i; for (i = 0; i < igraph_vector_size(v); i++) { fprintf(f, " %li", (long int) VECTOR(*v)[i]); } fprintf(f, "\n"); } int main() { igraph_vector_t v, v2, v3; int i; igraph_real_t *ptr; long int pos; /* simple init */ igraph_vector_init(&v, 0); igraph_vector_destroy(&v); /* vector of zeros */ igraph_vector_init(&v, 10); print_vector(&v, stdout); igraph_vector_destroy(&v); /* VECTOR(), igraph_vector_size */ igraph_vector_init(&v, 10); for (i = 0; i < igraph_vector_size(&v); i++) { VECTOR(v)[i] = 10 - i; } print_vector(&v, stdout); igraph_vector_destroy(&v); /* igraph_vector_reserve, igraph_vector_push_back */ igraph_vector_init(&v, 0); igraph_vector_reserve(&v, 10); for (i = 0; i < 10; i++) { igraph_vector_push_back(&v, i); } /* igraph_vector_empty, igraph_vector_clear */ if (igraph_vector_empty(&v)) { return 1; } igraph_vector_clear(&v); if (!igraph_vector_empty(&v)) { return 2; } igraph_vector_destroy(&v); /* igraph_vector_e, igraph_vector_e_ptr */ igraph_vector_init(&v, 5); for (i = 0; i < igraph_vector_size(&v); i++) { *igraph_vector_e_ptr(&v, i) = 100 * i; } for (i = 0; i < igraph_vector_size(&v); i++) { fprintf(stdout, " %li", (long int)igraph_vector_e(&v, i)); } fprintf(stdout, "\n"); igraph_vector_destroy(&v); /* igraph_vector_set */ igraph_vector_init(&v, 5); for (i = 0; i < igraph_vector_size(&v); i++) { igraph_vector_set(&v, i, 20 * i); } print_vector(&v, stdout); igraph_vector_destroy(&v); /* igraph_vector_null */ igraph_vector_init(&v, 0); igraph_vector_null(&v); igraph_vector_destroy(&v); igraph_vector_init(&v, 10); for (i = 0; i < igraph_vector_size(&v); i++) { VECTOR(v)[i] = i + 1; } igraph_vector_null(&v); print_vector(&v, stdout); igraph_vector_destroy(&v); /* igraph_vector_tail, igraph_vector_pop_back */ igraph_vector_init(&v, 10); for (i = 0; i < igraph_vector_size(&v); i++) { VECTOR(v)[i] = i + 1; } while (!igraph_vector_empty(&v)) { fprintf(stdout, " %li", (long int)igraph_vector_tail(&v)); fprintf(stdout, " %li", (long int)igraph_vector_pop_back(&v)); } fprintf(stdout, "\n"); igraph_vector_destroy(&v); /* igraph_vector_init_seq, igraph_vector_order */ igraph_vector_init_seq(&v, 1, 10); igraph_vector_init(&v2, 0); igraph_vector_order1(&v, &v2, 10); print_vector(&v2, stdout); igraph_vector_destroy(&v2); igraph_vector_destroy(&v); /* igraph_vector_resize, igraph_vector_sort */ igraph_vector_init(&v, 20); for (i = 0; i < 10; i++) { VECTOR(v)[i] = 10 - i; } igraph_vector_resize(&v, 10); igraph_vector_sort(&v); print_vector(&v, stdout); igraph_vector_destroy(&v); /* igraph_vector_max, igraph_vector_init_copy */ igraph_vector_init(&v, 10); for (i = 0; i < igraph_vector_size(&v); i++) { VECTOR(v)[i] = 100 - i; } for (i = 0; i < 10; i++) { fprintf(stdout, " %li", (long int)VECTOR(v)[i]); } fprintf(stdout, "\n"); fprintf(stdout, " %li\n", (long int)igraph_vector_max(&v)); igraph_vector_destroy(&v); ptr = (igraph_real_t*) malloc(10 * sizeof(igraph_real_t)); igraph_vector_init_copy(&v, ptr, 10); free(ptr); for (i = 0; i < 10; i++) { VECTOR(v)[i] = 100 - i; } print_vector(&v, stdout); igraph_vector_destroy(&v); /* igraph_vector_copy_to */ ptr = (igraph_real_t*) malloc(10 * sizeof(igraph_real_t)); igraph_vector_init_seq(&v, 11, 20); igraph_vector_copy_to(&v, ptr); for (i = 0; i < 10; i++) { fprintf(stdout, " %li", (long int)ptr[i]); } fprintf(stdout, "\n"); free(ptr); igraph_vector_destroy(&v); /* igraph_vector_init_seq, igraph_vector_sum, igraph_vector_prod */ igraph_vector_init_seq(&v, 1, 5); fprintf(stdout, " %li", (long int)igraph_vector_sum(&v)); fprintf(stdout, " %li\n", (long int)igraph_vector_prod(&v)); /* igraph_vector_remove_section */ igraph_vector_remove_section(&v, 2, 4); fprintf(stdout, " %li", (long int)igraph_vector_sum(&v)); fprintf(stdout, " %li\n", (long int)igraph_vector_prod(&v)); igraph_vector_destroy(&v); /* igraph_vector_remove */ igraph_vector_init_seq(&v, 1, 10); igraph_vector_remove(&v, 9); igraph_vector_remove(&v, 0); igraph_vector_remove(&v, 4); fprintf(stdout, " %li\n", (long int)igraph_vector_sum(&v)); igraph_vector_destroy(&v); /* igraph_vector_move_interval */ igraph_vector_init_seq(&v, 0, 9); igraph_vector_move_interval(&v, 5, 10, 0); if (igraph_vector_sum(&v) != 70) { return 3; } igraph_vector_destroy(&v); /* igraph_vector_isininterval */ igraph_vector_init_seq(&v, 1, 10); if (!igraph_vector_isininterval(&v, 1, 10)) { return 4; } if (igraph_vector_isininterval(&v, 2, 10)) { return 5; } if (igraph_vector_isininterval(&v, 1, 9)) { return 6; } /* igraph_vector_any_smaller */ if (igraph_vector_any_smaller(&v, 1)) { return 7; } if (!igraph_vector_any_smaller(&v, 2)) { return 8; } igraph_vector_destroy(&v); /* igraph_vector_all_e */ /* igraph_vector_binsearch */ igraph_vector_init_seq(&v, 0, 9); for (i = 0; i < igraph_vector_size(&v); i++) { if (!igraph_vector_binsearch(&v, 0, 0)) { return 9; } } if (igraph_vector_binsearch(&v, 10, 0)) { return 10; } if (igraph_vector_binsearch(&v, -1, 0)) { return 11; } for (i = 0; i < igraph_vector_size(&v); i++) { VECTOR(v)[i] = 2 * i; } for (i = 0; i < igraph_vector_size(&v); i++) { long int pos; if (!igraph_vector_binsearch(&v, VECTOR(v)[i], &pos)) { fprintf(stderr, "cannot find %i\n", (int)VECTOR(v)[i]); return 12; } if (pos != i) { return 13; } if (igraph_vector_binsearch(&v, VECTOR(v)[i] + 1, &pos)) { return 14; } } igraph_vector_destroy(&v); /* Binsearch in empty vector */ igraph_vector_init(&v, 0); if (igraph_vector_binsearch2(&v, 0)) { return 16; } if (igraph_vector_binsearch(&v, 1, &pos)) { return 17; } if (pos != 0) { return 18; } igraph_vector_destroy(&v); /* igraph_vector_init_real */ igraph_vector_init_real(&v, 10, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0); print_vector(&v, stdout); igraph_vector_destroy(&v); /* igraph_vector_init_int */ igraph_vector_init_int(&v, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10); print_vector(&v, stdout); igraph_vector_destroy(&v); /* igraph_vector_init_real */ igraph_vector_init_real_end(&v, -1, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, -1.0); print_vector(&v, stdout); igraph_vector_destroy(&v); /* igraph_vector_init_int */ igraph_vector_init_int_end(&v, -1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, -1); print_vector(&v, stdout); igraph_vector_destroy(&v); /* igraph_vector_permdelete */ /* igraph_vector_remove_negidx */ /* order2 */ igraph_vector_init_int_end(&v, -1, 10, 9, 8, 7, 6, 7, 8, 9, 10, -1); igraph_vector_order2(&v); print_vector(&v, stdout); igraph_vector_destroy(&v); /* filter_smaller, quite special.... */ igraph_vector_init_int_end(&v, -1, 0, 1, 2, 3, 4, 4, 4, 4, 5, 6, 7, 8, -1); igraph_vector_filter_smaller(&v, 4); print_vector(&v, stdout); igraph_vector_destroy(&v); igraph_vector_init_int_end(&v, -1, 1, 2, 3, 4, 4, 4, 4, 5, 6, 7, 8, -1); igraph_vector_filter_smaller(&v, 0); print_vector(&v, stdout); igraph_vector_destroy(&v); igraph_vector_init_int_end(&v, -1, 0, 0, 1, 2, 3, 4, 4, 4, 4, 5, 6, 7, 8, -1); igraph_vector_filter_smaller(&v, 0); print_vector(&v, stdout); igraph_vector_destroy(&v); /* rank */ igraph_vector_init_int_end(&v, -1, 0, 1, 2, 6, 5, 2, 1, 0, -1); igraph_vector_init(&v2, 0); igraph_vector_rank(&v, &v2, 7); print_vector(&v, stdout); print_vector(&v2, stdout); igraph_vector_destroy(&v); igraph_vector_destroy(&v2); /* order */ igraph_vector_init_int_end(&v, -1, 1, 1, 2, 2, -1); igraph_vector_init_int_end(&v2, -1, 2, 3, 1, 3, -1); igraph_vector_init(&v3, 0); igraph_vector_order(&v, &v2, &v3, 3); print_vector(&v3, stdout); igraph_vector_destroy(&v); igraph_vector_destroy(&v2); igraph_vector_destroy(&v3); /* fill */ igraph_vector_init(&v, 100); igraph_vector_fill(&v, 1.234567); for (i = 0; i < igraph_vector_size(&v); i++) { if (VECTOR(v)[i] != 1.234567) { return 15; } } igraph_vector_destroy(&v); if (IGRAPH_FINALLY_STACK_SIZE() != 0) { return 16; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_lapack_dgehrd.c0000644000076500000240000000464613612122633030175 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { int nodes = 10; igraph_t tree; igraph_matrix_t sto; igraph_matrix_t hess; igraph_matrix_complex_t evec1, evec2; igraph_vector_complex_t eval1, eval2; igraph_eigen_which_t which; int i; igraph_tree(&tree, nodes, /* children= */ 3, IGRAPH_TREE_UNDIRECTED); igraph_matrix_init(&sto, nodes, nodes); igraph_get_stochastic(&tree, &sto, /*column_wise=*/ 0); igraph_matrix_transpose(&sto); igraph_matrix_init(&hess, nodes, nodes); igraph_lapack_dgehrd(&sto, 1, nodes, &hess); igraph_matrix_complex_init(&evec1, 0, 0); igraph_vector_complex_init(&eval1, 0); which.pos = IGRAPH_EIGEN_ALL; igraph_eigen_matrix(&sto, 0, 0, nodes, 0, IGRAPH_EIGEN_LAPACK, &which, 0, 0, &eval1, &evec1); igraph_matrix_complex_init(&evec2, 0, 0); igraph_vector_complex_init(&eval2, 0); igraph_eigen_matrix(&hess, 0, 0, nodes, 0, IGRAPH_EIGEN_LAPACK, &which, 0, 0, &eval2, &evec2); for (i = 0; i < nodes; i++) { igraph_real_t d = igraph_complex_abs(igraph_complex_sub(VECTOR(eval1)[i], VECTOR(eval2)[i])); if (d > 1e-14) { printf("Difference: %g\n", d); return 1; } } igraph_matrix_complex_destroy(&evec2); igraph_vector_complex_destroy(&eval2); igraph_matrix_complex_destroy(&evec1); igraph_vector_complex_destroy(&eval1); igraph_matrix_destroy(&hess); igraph_matrix_destroy(&sto); igraph_destroy(&tree); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_hashtable.c0000644000076500000240000001054013612122633027346 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include "igraph_types_internal.h" int main() { igraph_hashtable_t ht; char *str; const igraph_strvector_t *keys; long int i; /* init and destroy */ igraph_hashtable_init(&ht); igraph_hashtable_destroy(&ht); /* init, add some elements and destroy */ igraph_hashtable_init(&ht); igraph_hashtable_addset(&ht, "color", "green", "red"); igraph_hashtable_addset(&ht, "size", "", "4"); igraph_hashtable_addset(&ht, "color", "", "grey"); igraph_hashtable_addset(&ht, "shape", "", "circle"); igraph_hashtable_addset(&ht, "shape", "", "diamond"); igraph_hashtable_destroy(&ht); /* reset */ igraph_hashtable_init(&ht); igraph_hashtable_addset(&ht, "color", "green", "red"); igraph_hashtable_addset(&ht, "size", "", "4"); igraph_hashtable_addset(&ht, "color", "", "grey"); igraph_hashtable_addset(&ht, "shape", "", "circle"); igraph_hashtable_addset(&ht, "shape", "", "diamond"); igraph_hashtable_reset(&ht); igraph_hashtable_addset(&ht, "color", "green", "red"); igraph_hashtable_addset(&ht, "size", "", "4"); igraph_hashtable_addset(&ht, "color", "", "grey"); igraph_hashtable_addset(&ht, "shape", "", "circle"); igraph_hashtable_addset(&ht, "shape", "", "diamond"); igraph_hashtable_destroy(&ht); /* Check semantics */ igraph_hashtable_init(&ht); igraph_hashtable_addset(&ht, "color", "green", "red"); igraph_hashtable_addset(&ht, "size", "", "4"); igraph_hashtable_addset(&ht, "color", "", "grey"); igraph_hashtable_addset(&ht, "shape", "", "circle"); igraph_hashtable_addset(&ht, "shape", "", "diamond"); igraph_hashtable_get(&ht, "color", &str); printf("color: %s\n", str); igraph_hashtable_get(&ht, "size", &str); printf("size: %s\n", str); igraph_hashtable_get(&ht, "shape", &str); printf("shape: %s\n", str); igraph_hashtable_reset(&ht); igraph_hashtable_get(&ht, "color", &str); printf("color: %s\n", str); igraph_hashtable_get(&ht, "size", &str); printf("size: %s\n", str); igraph_hashtable_get(&ht, "shape", &str); printf("shape: %s\n", str); igraph_hashtable_getkeys(&ht, &keys); for (i = 0; i < igraph_strvector_size(keys); i++) { igraph_strvector_get(keys, i, &str); printf("%s ", str); } printf("\n"); igraph_hashtable_destroy(&ht); /* addset2 */ igraph_hashtable_init(&ht); igraph_hashtable_addset2(&ht, "color", "green", "redddd", 3); igraph_hashtable_addset2(&ht, "size", "", "4111", 1); igraph_hashtable_addset2(&ht, "color", "", "greysdsdf", 4); igraph_hashtable_addset2(&ht, "shape", "", "circle", 6); igraph_hashtable_addset(&ht, "shape", "", "diamond"); igraph_hashtable_get(&ht, "color", &str); printf("color: %s\n", str); igraph_hashtable_get(&ht, "size", &str); printf("size: %s\n", str); igraph_hashtable_get(&ht, "shape", &str); printf("shape: %s\n", str); igraph_hashtable_reset(&ht); igraph_hashtable_get(&ht, "color", &str); printf("color: %s\n", str); igraph_hashtable_get(&ht, "size", &str); printf("size: %s\n", str); igraph_hashtable_get(&ht, "shape", &str); printf("shape: %s\n", str); igraph_hashtable_getkeys(&ht, &keys); for (i = 0; i < igraph_strvector_size(keys); i++) { igraph_strvector_get(keys, i, &str); printf("%s ", str); } printf("\n"); igraph_hashtable_destroy(&ht); if (!IGRAPH_FINALLY_STACK_EMPTY) { return 1; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/topology.c0000644000076500000240000000410613612122634025737 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_vector_t edges; igraph_vector_t vids; igraph_integer_t class; igraph_vector_init_int_end(&edges, -1, 0, 1, 1, 3, 1, 4, 1, 6, 3, 1, 4, 1, 4, 2, 6, 4, 6, 5, 7, 8, 8, 7, 7, 9, 9, 7, 8, 9, 9, 8, -1); igraph_create(&g, &edges, 0, IGRAPH_DIRECTED); igraph_vector_destroy(&edges); igraph_vector_init_int_end(&vids, -1, 1, 4, 6, -1); igraph_isoclass_subgraph(&g, &vids, &class); printf("class: %i\n", (int)class); igraph_vector_destroy(&vids); igraph_vector_init_int_end(&vids, -1, 0, 1, 3, -1); igraph_isoclass_subgraph(&g, &vids, &class); printf("class: %i\n", (int)class); igraph_vector_destroy(&vids); igraph_vector_init_int_end(&vids, -1, 7, 8, 9, -1); igraph_isoclass_subgraph(&g, &vids, &class); printf("class: %i\n", (int)class); igraph_vector_destroy(&vids); igraph_vector_init_int_end(&vids, -1, 0, 2, 5, -1); igraph_isoclass_subgraph(&g, &vids, &class); printf("class: %i\n", (int)class); igraph_vector_destroy(&vids); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_maximal_cliques3.out0000644000076500000240000000225713524616144031255 0ustar tamasstaff000000000000000 6 17 19 25 30 33 35 40 73 74 79 90 92 97 0 6 17 19 25 30 33 35 47 73 74 79 90 92 97 0 11 12 17 19 30 33 35 47 53 62 79 91 92 97 0 17 19 25 30 33 35 47 73 74 79 90 91 92 97 1 3 6 17 25 28 37 40 49 50 69 74 85 86 97 1 3 6 17 25 28 37 40 49 50 73 74 85 86 97 1 3 6 17 25 28 37 40 50 54 69 74 85 86 97 1 3 6 17 25 28 37 40 50 54 73 74 85 86 97 1 3 6 17 25 37 40 49 50 69 74 85 86 90 97 1 3 6 17 25 37 40 49 50 73 74 85 86 90 97 1 3 6 17 25 37 40 50 69 74 85 86 90 95 97 1 3 6 17 25 37 40 50 73 74 85 86 90 95 97 1 3 17 25 28 37 40 49 50 69 74 85 86 97 98 1 3 17 25 28 37 40 49 50 73 74 85 86 97 98 1 3 17 25 28 37 40 50 54 69 74 85 86 97 98 1 3 17 25 28 37 40 50 54 73 74 85 86 97 98 1 6 17 25 28 37 40 49 50 61 69 74 85 86 97 1 6 17 25 28 37 40 49 50 61 73 74 85 86 97 1 6 17 25 28 37 40 50 54 61 69 74 85 86 97 1 6 17 25 28 37 40 50 54 61 73 74 85 86 97 1 6 17 25 37 40 49 50 61 69 74 85 86 90 97 1 6 17 25 37 40 49 50 61 73 74 85 86 90 97 1 6 17 25 37 40 50 61 69 74 85 86 90 95 97 1 6 17 25 37 40 50 61 73 74 85 86 90 95 97 1 9 16 25 28 54 57 58 67 78 85 86 87 97 99 1 9 16 25 28 54 57 58 67 85 86 87 97 98 99 1 9 25 28 54 57 58 67 69 85 86 87 97 98 99 8 15 28 39 43 48 55 56 59 61 62 63 76 78 84 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_get_all_simple_paths.out0000644000076500000240000000045213532467671032177 0ustar tamasstaff00000000000000Paths for cutoff 0: Paths for cutoff 1: Paths for cutoff 2: 0 3 5 -1 Paths for cutoff 3: 0 1 2 5 -1 0 3 2 5 -1 0 3 4 5 -1 0 3 5 -1 Paths for cutoff 4: 0 1 2 3 5 -1 0 1 2 5 -1 0 3 2 5 -1 0 3 4 5 -1 0 3 5 -1 Paths for cutoff 5: 0 1 2 3 4 5 -1 0 1 2 3 5 -1 0 1 2 5 -1 0 3 2 5 -1 0 3 4 5 -1 0 3 5 -1 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_add_edges.c0000644000076500000240000000501113612122633027307 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void print_vector(igraph_vector_t *v, FILE *f) { long int i; for (i = 0; i < igraph_vector_size(v); i++) { fprintf(f, " %li", (long int) VECTOR(*v)[i]); } fprintf(f, "\n"); } int main() { igraph_t g; igraph_vector_t v; int ret; /* Create graph */ igraph_vector_init(&v, 8); VECTOR(v)[0] = 0; VECTOR(v)[1] = 1; VECTOR(v)[2] = 1; VECTOR(v)[3] = 2; VECTOR(v)[4] = 2; VECTOR(v)[5] = 3; VECTOR(v)[6] = 2; VECTOR(v)[7] = 2; igraph_create(&g, &v, 0, 1); /* Add edges */ igraph_vector_resize(&v, 4); VECTOR(v)[0] = 2; VECTOR(v)[1] = 1; VECTOR(v)[2] = 3; VECTOR(v)[3] = 3; igraph_add_edges(&g, &v, 0); /* Check result */ igraph_get_edgelist(&g, &v, 0); igraph_vector_sort(&v); print_vector(&v, stdout); /* Error, vector length */ igraph_set_error_handler(igraph_error_handler_ignore); igraph_vector_resize(&v, 3); VECTOR(v)[0] = 0; VECTOR(v)[1] = 1; VECTOR(v)[2] = 2; ret = igraph_add_edges(&g, &v, 0); if (ret != IGRAPH_EINVEVECTOR) { return 1; } /* Check result */ igraph_get_edgelist(&g, &v, 0); igraph_vector_sort(&v); print_vector(&v, stdout); /* Error, vector ids */ igraph_vector_resize(&v, 4); VECTOR(v)[0] = 0; VECTOR(v)[1] = 1; VECTOR(v)[2] = 2; VECTOR(v)[3] = 4; ret = igraph_add_edges(&g, &v, 0); if (ret != IGRAPH_EINVVID) { return 2; } /* Check result */ igraph_get_edgelist(&g, &v, 0); igraph_vector_sort(&v); print_vector(&v, stdout); igraph_vector_destroy(&v); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_get_shortest_paths_dijkstra.c0000644000076500000240000001700613614300625033224 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include void print_vector(igraph_vector_t *v) { long int i, l = igraph_vector_size(v); for (i = 0; i < l; i++) { printf(" %li", (long int) VECTOR(*v)[i]); } printf("\n"); } int check_evecs(const igraph_t *graph, const igraph_vector_ptr_t *vecs, const igraph_vector_ptr_t *evecs, int error_code) { igraph_bool_t directed = igraph_is_directed(graph); long int i, n = igraph_vector_ptr_size(vecs); if (igraph_vector_ptr_size(evecs) != n) { exit(error_code + 1); } for (i = 0; i < n; i++) { igraph_vector_t *vvec = VECTOR(*vecs)[i]; igraph_vector_t *evec = VECTOR(*evecs)[i]; long int j, n2 = igraph_vector_size(evec); if (igraph_vector_size(vvec) == 0 && n2 == 0) { continue; } if (igraph_vector_size(vvec) != n2 + 1) { exit(error_code + 2); } for (j = 0; j < n2; j++) { long int edge = VECTOR(*evec)[j]; long int from = VECTOR(*vvec)[j]; long int to = VECTOR(*vvec)[j + 1]; if (directed) { if (from != IGRAPH_FROM(graph, edge) || to != IGRAPH_TO (graph, edge)) { exit(error_code); } } else { long int from2 = IGRAPH_FROM(graph, edge); long int to2 = IGRAPH_TO(graph, edge); long int min1 = from < to ? from : to; long int max1 = from < to ? to : from; long int min2 = from2 < to2 ? from2 : to2; long int max2 = from2 < to2 ? to2 : from2; if (min1 != min2 || max1 != max2) { exit(error_code + 3); } } } } return 0; } int check_pred_inbound(const igraph_t* graph, const igraph_vector_long_t* pred, const igraph_vector_long_t* inbound, int start, int error_code) { long int i, n = igraph_vcount(graph); if (igraph_vector_long_size(pred) != n || igraph_vector_long_size(inbound) != n) { exit(error_code); } if (VECTOR(*pred)[start] != start || VECTOR(*inbound)[start] != -1) { exit(error_code + 1); } for (i = 0; i < n; i++) { if (VECTOR(*pred)[i] == -1) { if (VECTOR(*inbound)[i] != -1) { exit(error_code + 2); } } else if (VECTOR(*pred)[i] == i) { if (i != start) { exit(error_code + 3); } if (VECTOR(*inbound)[i] != -1) { exit(error_code + 4); } } else { long int eid = VECTOR(*inbound)[i]; long int u = IGRAPH_FROM(graph, eid), v = IGRAPH_TO(graph, eid); if (v != i && !igraph_is_directed(graph)) { long int dummy = u; u = v; v = dummy; } if (v != i) { exit(error_code + 5); } else if (u != VECTOR(*pred)[i]) { exit(error_code + 6); } } } return 0; } int main() { igraph_t g; igraph_vector_ptr_t vecs, evecs; igraph_vector_long_t pred, inbound; long int i; igraph_real_t weights[] = { 1, 2, 3, 4, 5, 1, 1, 1, 1, 1 }; igraph_real_t weights2[] = { 0, 2, 1, 0, 5, 2, 1, 1, 0, 2, 2, 8, 1, 1, 3, 1, 1, 4, 2, 1 }; igraph_vector_t weights_vec; igraph_vs_t vs; /* Simple ring graph without weights */ igraph_ring(&g, 10, IGRAPH_UNDIRECTED, 0, 1); igraph_vector_ptr_init(&vecs, 6); igraph_vector_ptr_init(&evecs, 6); igraph_vector_long_init(&pred, 0); igraph_vector_long_init(&inbound, 0); for (i = 0; i < igraph_vector_ptr_size(&vecs); i++) { VECTOR(vecs)[i] = calloc(1, sizeof(igraph_vector_t)); igraph_vector_init(VECTOR(vecs)[i], 0); VECTOR(evecs)[i] = calloc(1, sizeof(igraph_vector_t)); igraph_vector_init(VECTOR(evecs)[i], 0); } igraph_vs_vector_small(&vs, 0, 1, 3, 5, 2, 1, -1); igraph_get_shortest_paths_dijkstra(&g, /*vertices=*/ &vecs, /*edges=*/ &evecs, /*from=*/ 0, /*to=*/ vs, /*weights=*/ 0, /*mode=*/ IGRAPH_OUT, /*predecessors=*/ &pred, /*inbound_edges=*/ &inbound); check_evecs(&g, &vecs, &evecs, 10); check_pred_inbound(&g, &pred, &inbound, /* from= */ 0, 40); for (i = 0; i < igraph_vector_ptr_size(&vecs); i++) { print_vector(VECTOR(vecs)[i]); } /* Same ring, but with weights */ igraph_vector_view(&weights_vec, weights, sizeof(weights) / sizeof(igraph_real_t)); igraph_get_shortest_paths_dijkstra(&g, /*vertices=*/ &vecs, /*edges=*/ &evecs, /*from=*/ 0, /*to=*/ vs, &weights_vec, IGRAPH_OUT, /*predecessors=*/ &pred, /*inbound_edges=*/ &inbound); check_evecs(&g, &vecs, &evecs, 20); check_pred_inbound(&g, &pred, &inbound, /* from= */ 0, 50); for (i = 0; i < igraph_vector_ptr_size(&vecs); i++) { print_vector(VECTOR(vecs)[i]); } igraph_destroy(&g); /* More complicated example */ igraph_small(&g, 10, IGRAPH_DIRECTED, 0, 1, 0, 2, 0, 3, 1, 2, 1, 4, 1, 5, 2, 3, 2, 6, 3, 2, 3, 6, 4, 5, 4, 7, 5, 6, 5, 8, 5, 9, 7, 5, 7, 8, 8, 9, 5, 2, 2, 1, -1); igraph_vector_view(&weights_vec, weights2, sizeof(weights2) / sizeof(igraph_real_t)); igraph_get_shortest_paths_dijkstra(&g, /*vertices=*/ &vecs, /*edges=*/ &evecs, /*from=*/ 0, /*to=*/ vs, &weights_vec, IGRAPH_OUT, /*predecessors=*/ &pred, /*inbound_edges=*/ &inbound); check_evecs(&g, &vecs, &evecs, 30); check_pred_inbound(&g, &pred, &inbound, /* from= */ 0, 60); for (i = 0; i < igraph_vector_ptr_size(&vecs); i++) { print_vector(VECTOR(vecs)[i]); igraph_vector_destroy(VECTOR(vecs)[i]); free(VECTOR(vecs)[i]); igraph_vector_destroy(VECTOR(evecs)[i]); free(VECTOR(evecs)[i]); } igraph_vector_ptr_destroy(&vecs); igraph_vector_ptr_destroy(&evecs); igraph_vector_long_destroy(&pred); igraph_vector_long_destroy(&inbound); igraph_vs_destroy(&vs); igraph_destroy(&g); if (!IGRAPH_FINALLY_STACK_EMPTY) { return 1; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_barabasi_game.c0000644000076500000240000000726013612122633030155 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_vector_t v, v2; int i, ret; igraph_barabasi_game(&g, 10, /*power=*/ 1, 2, 0, 0, /*A=*/ 1, 1, IGRAPH_BARABASI_BAG, /*start_from=*/ 0); if (igraph_ecount(&g) != 18) { return 1; } if (igraph_vcount(&g) != 10) { return 2; } if (!igraph_is_directed(&g)) { return 3; } igraph_vector_init(&v, 0); igraph_get_edgelist(&g, &v, 0); for (i = 0; i < igraph_ecount(&g); i++) { if (VECTOR(v)[2 * i] <= VECTOR(v)[2 * i + 1]) { return 4; } } igraph_destroy(&g); /* out degree sequence */ igraph_vector_resize(&v, 10); VECTOR(v)[0] = 0; VECTOR(v)[1] = 1; VECTOR(v)[2] = 3; VECTOR(v)[3] = 3; VECTOR(v)[4] = 4; VECTOR(v)[5] = 5; VECTOR(v)[6] = 6; VECTOR(v)[7] = 7; VECTOR(v)[8] = 8; VECTOR(v)[9] = 9; igraph_barabasi_game(&g, 10, /*power=*/ 1, 0, &v, 0, /*A=*/ 1, 1, IGRAPH_BARABASI_BAG, /*start_from=*/ 0); if (igraph_ecount(&g) != igraph_vector_sum(&v)) { return 5; } igraph_vector_init(&v2, 0); igraph_degree(&g, &v2, igraph_vss_all(), IGRAPH_OUT, 1); for (i = 0; i < igraph_vcount(&g); i++) { if (VECTOR(v)[i] != VECTOR(v2)[i]) { igraph_vector_print(&v); printf("\n"); igraph_vector_print(&v2); return 6; } } igraph_vector_destroy(&v); igraph_vector_destroy(&v2); igraph_destroy(&g); /* outpref, we cannot really test this quantitatively, would need to set random seed */ igraph_barabasi_game(&g, 10, /*power=*/ 1, 2, 0, 1, /*A=*/ 1, 1, IGRAPH_BARABASI_BAG, /*start_from=*/ 0); igraph_vector_init(&v, 0); igraph_get_edgelist(&g, &v, 0); for (i = 0; i < igraph_ecount(&g); i++) { if (VECTOR(v)[2 * i] <= VECTOR(v)[2 * i + 1]) { return 7; } } if (!igraph_is_directed(&g)) { return 8; } igraph_vector_destroy(&v); igraph_destroy(&g); /* Error tests */ igraph_set_error_handler(igraph_error_handler_ignore); ret = igraph_barabasi_game(&g, -10, /*power=*/ 1, 1, 0, 0, /*A=*/ 1, 0, IGRAPH_BARABASI_BAG, /*start_from=*/ 0); if (ret != IGRAPH_EINVAL) { return 9; } ret = igraph_barabasi_game(&g, 10, /*power=*/ 1, -2, 0, 0, /*A=*/ 1, 0, IGRAPH_BARABASI_BAG, /*start_from=*/ 0); if (ret != IGRAPH_EINVAL) { return 10; } igraph_vector_init(&v, 9); ret = igraph_barabasi_game(&g, 10, /*power=*/ 1, 0, &v, 0, /*A=*/ 1, 0, IGRAPH_BARABASI_BAG, /*start_from=*/ 0); if (ret != IGRAPH_EINVAL) { return 11; } igraph_vector_destroy(&v); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_maximal_cliques4.c0000644000076500000240000000673313612122633030665 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2013 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int sort_cmp(const void *a, const void *b) { const igraph_vector_t **da = (const igraph_vector_t **) a; const igraph_vector_t **db = (const igraph_vector_t **) b; int i, alen = igraph_vector_size(*da), blen = igraph_vector_size(*db); if (alen != blen) { return (alen < blen) - (alen > blen); } for (i = 0; i < alen; i++) { int ea = VECTOR(**da)[i], eb = VECTOR(**db)[i]; if (ea != eb) { return (ea > eb) - (ea < eb); } } return 0; } void sort_cliques(igraph_vector_ptr_t *cliques) { int i, n = igraph_vector_ptr_size(cliques); for (i = 0; i < n; i++) { igraph_vector_t *v = VECTOR(*cliques)[i]; igraph_vector_sort(v); } igraph_qsort(VECTOR(*cliques), (size_t) n, sizeof(igraph_vector_t *), sort_cmp); } int print_and_destroy(igraph_vector_ptr_t *cliques) { int i, n = igraph_vector_ptr_size(cliques); sort_cliques(cliques); for (i = 0; i < n; i++) { igraph_vector_t *v = VECTOR(*cliques)[i]; igraph_vector_print(v); igraph_vector_destroy(v); } igraph_vector_ptr_destroy_all(cliques); return 0; } int main() { igraph_t graph; igraph_vector_ptr_t cliques, cl1, cl2; igraph_vector_int_t v1, v2; igraph_integer_t n, n1, n2; igraph_rng_seed(igraph_rng_default(), 42); igraph_erdos_renyi_game(&graph, IGRAPH_ERDOS_RENYI_GNP, /*n=*/ 100, /*p=*/ 0.5, /*directed=*/ 0, /*loops=*/ 0); igraph_vector_ptr_init(&cliques, 0); igraph_maximal_cliques_subset(&graph, /*subset=*/ 0, &cliques, &n, /*outfile=*/ 0, /*min_size=*/ 9, /*max_size=*/ 0); igraph_vector_int_init_seq(&v1, 0, 12); igraph_vector_int_init_seq(&v2, 13, 99); igraph_vector_ptr_init(&cl1, 0); igraph_vector_ptr_init(&cl2, 0); igraph_maximal_cliques_subset(&graph, &v1, &cl1, &n1, /*outfile=*/ 0, /*min_size=*/ 9, /*max_size=*/ 0); igraph_maximal_cliques_subset(&graph, &v2, &cl2, &n2, /*outfile=*/ 0, /*min_size=*/ 9, /*max_size=*/ 0); igraph_vector_int_destroy(&v1); igraph_vector_int_destroy(&v2); if (n1 + n2 != n) { return 1; } if (n1 != igraph_vector_ptr_size(&cl1)) { return 2; } if (n2 != igraph_vector_ptr_size(&cl2)) { return 3; } print_and_destroy(&cliques); printf("---\n"); print_and_destroy(&cl1); printf("+\n"); print_and_destroy(&cl2); igraph_destroy(&graph); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/pajek_signed.c0000644000076500000240000000576413612122634026521 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int print_attributes(const igraph_t *g) { igraph_vector_t gtypes, vtypes, etypes; igraph_strvector_t gnames, vnames, enames; long int i; igraph_vector_init(>ypes, 0); igraph_vector_init(&vtypes, 0); igraph_vector_init(&etypes, 0); igraph_strvector_init(&gnames, 0); igraph_strvector_init(&vnames, 0); igraph_strvector_init(&enames, 0); igraph_cattribute_list(g, &gnames, >ypes, &vnames, &vtypes, &enames, &etypes); for (i = 0; i < igraph_vcount(g); i++) { long int j; printf("Vertex %li: ", i); for (j = 0; j < igraph_strvector_size(&vnames); j++) { printf("%s=", STR(vnames, j)); if (VECTOR(vtypes)[j] == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_real_printf(VAN(g, STR(vnames, j), i)); putchar(' '); } else { printf("\"%s\" ", VAS(g, STR(vnames, j), i)); } } printf("\n"); } for (i = 0; i < igraph_ecount(g); i++) { long int j; printf("Edge %li (%i-%i): ", i, (int)IGRAPH_FROM(g, i), (int)IGRAPH_TO(g, i)); for (j = 0; j < igraph_strvector_size(&enames); j++) { printf("%s=", STR(enames, j)); if (VECTOR(etypes)[j] == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_real_printf(EAN(g, STR(enames, j), i)); putchar(' '); } else { printf("\"%s\" ", EAS(g, STR(enames, j), i)); } } printf("\n"); } igraph_strvector_destroy(&enames); igraph_strvector_destroy(&vnames); igraph_strvector_destroy(&gnames); igraph_vector_destroy(&etypes); igraph_vector_destroy(&vtypes); igraph_vector_destroy(>ypes); return 0; } int main() { igraph_t graph; FILE *input; /* turn on attribute handling */ igraph_i_set_attribute_table(&igraph_cattribute_table); input = fopen("pajek_signed.net", "r"); if (input == 0) { return 1; } igraph_read_graph_pajek(&graph, input); fclose(input); print_attributes(&graph); igraph_destroy(&graph); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/cattr_bool_bug.c0000644000076500000240000000346313612122633027054 0ustar tamasstaff00000000000000 #include #include #include void check_attr(igraph_t *graph, int offset) { if (!igraph_cattribute_has_attr(graph, IGRAPH_ATTRIBUTE_GRAPH, "name")) { printf("No graph attribute `name`\n"); exit(offset + 2); } if (!igraph_cattribute_has_attr(graph, IGRAPH_ATTRIBUTE_GRAPH, "type")) { printf("No graph attribute `type`\n"); exit(offset + 3); } if (!igraph_cattribute_has_attr(graph, IGRAPH_ATTRIBUTE_GRAPH, "p")) { printf("No graph attribute `p`\n"); exit(offset + 4); } if (!igraph_cattribute_has_attr(graph, IGRAPH_ATTRIBUTE_VERTEX, "name")) { printf("No vertex attribute `id`\n"); exit(offset + 5); } if (!igraph_cattribute_has_attr(graph, IGRAPH_ATTRIBUTE_EDGE, "weight")) { printf("No edge attribute `weight'\n"); exit(offset + 6); } } int main() { igraph_t graph; igraph_error_handler_t* oldhandler; int result; FILE *ifile = fopen("cattr_bool_bug.graphml", "r"); if (!ifile) { printf("Cannot open input file"); return 1; } igraph_i_set_attribute_table(&igraph_cattribute_table); oldhandler = igraph_set_error_handler(igraph_error_handler_ignore); if ((result = igraph_read_graph_graphml(&graph, ifile, 0))) { /* maybe it is simply disabled at compile-time */ if (result == IGRAPH_UNIMPLEMENTED) { return 77; } return 1; } igraph_set_error_handler(oldhandler); fclose(ifile); check_attr(&graph, 10); igraph_to_directed(&graph, IGRAPH_TO_DIRECTED_ARBITRARY); check_attr(&graph, 20); if (GAB(&graph, "loops")) { return 2; } igraph_destroy(&graph); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/bellman_ford.out0000644000076500000240000000104213524616144027076 0ustar tamasstaff000000000000000: 0 0 0 1 5 2 1 13 3 5 1: inf 0 0 1 5 2 1 13 3 5 2: inf 1 0 1 6 3 1 14 4 6 3: inf 1 0 0 6 3 1 14 4 6 4: inf 5 4 5 0 2 3 8 3 5 5: inf 3 2 3 8 0 1 16 1 3 6: inf inf inf inf inf inf 0 inf inf inf 7: inf 4 3 4 9 1 2 0 1 4 8: inf inf inf inf inf inf inf inf 0 4 9: inf inf inf inf inf inf inf inf inf 0 0: 0 2 4 7 -2 1: -2 0 2 5 -4 2: -4 -2 0 3 -6 3: -7 -5 -3 0 -9 4: 2 4 6 9 0 python-igraph-0.8.0/vendor/source/igraph/examples/simple/mt.c0000644000076500000240000000216113612122634024502 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int main() { long int i; for (i = 0; i < 1000; i++) { igraph_real_t r = igraph_rng_get_unif01(igraph_rng_default()); if (r < 0 || r > 1) { return 1; } } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_cocitation.out0000644000076500000240000000011013524616144030133 0ustar tamasstaff00000000000000 0 0 1 0 0 0 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_hrg2.out0000644000076500000240000000017713524616144026656 0ustar tamasstaff0000000000000037 37 37 37 36 36 36 37 34 37 36 37 37 37 37 37 36 37 37 37 37 37 37 37 35 35 37 37 37 37 34 37 37 37 37 37 37 -1 54 59 71 100 python-igraph-0.8.0/vendor/source/igraph/examples/simple/scg.c0000644000076500000240000001356613612122634024651 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_vector_t ev; igraph_t scg_graph; igraph_matrix_t scg_matrix; igraph_sparsemat_t scg_sparsemat; igraph_matrix_t L, R; igraph_sparsemat_t Lsparse, Rsparse; igraph_matrix_t input_matrix; igraph_vector_t groups; igraph_vector_t eval; igraph_matrix_t evec; igraph_tree(&g, 10, /* children= */ 3, IGRAPH_TREE_UNDIRECTED); igraph_vector_init(&ev, 1); igraph_matrix_init(&L, 0, 0); igraph_matrix_init(&R, 0, 0); igraph_matrix_init(&scg_matrix, 0, 0); igraph_vector_init(&groups, 0); igraph_vector_init(&eval, 0); igraph_matrix_init(&evec, 0, 0); #define CALLSYM(algo) do { \ igraph_vector_clear(&eval); \ igraph_matrix_resize(&evec, 0, 0); \ igraph_scg_adjacency(&g, /*matrix=*/ 0, /*sparsemat=*/ 0, &ev, \ /* intervals= */ 3, /* intervals_vector= */ 0, \ /* algorithm= */ algo, &eval, &evec, \ /* groups= */ &groups, /* use_arpack= */ 0, \ /* maxiter= */ 0, &scg_graph, &scg_matrix, \ &scg_sparsemat, &L, &R, \ &Lsparse, &Rsparse); } while(0) #define PRINTRES() \ do { \ printf("------------------------------------\n"); \ igraph_write_graph_edgelist(&scg_graph, stdout); \ printf("---\n"); \ igraph_vector_print(&groups); \ printf("---\n"); \ igraph_vector_print(&eval); \ igraph_matrix_print(&evec); \ printf("---\n"); \ igraph_sparsemat_print(&scg_sparsemat, stdout); \ printf("---\n"); \ igraph_sparsemat_print(&Lsparse, stdout); \ printf("---\n"); \ igraph_sparsemat_print(&Rsparse, stdout); \ printf("---\n"); \ } while (0) VECTOR(ev)[0] = 1; CALLSYM(IGRAPH_SCG_EXACT); PRINTRES(); igraph_destroy(&scg_graph); igraph_sparsemat_destroy(&scg_sparsemat); igraph_sparsemat_destroy(&Lsparse); igraph_sparsemat_destroy(&Rsparse); VECTOR(ev)[0] = 3; CALLSYM(IGRAPH_SCG_EXACT); PRINTRES(); igraph_destroy(&scg_graph); igraph_sparsemat_destroy(&scg_sparsemat); igraph_sparsemat_destroy(&Lsparse); igraph_sparsemat_destroy(&Rsparse); igraph_vector_resize(&ev, 2); VECTOR(ev)[0] = 1; VECTOR(ev)[1] = 3; CALLSYM(IGRAPH_SCG_EXACT); PRINTRES(); igraph_destroy(&scg_graph); igraph_sparsemat_destroy(&scg_sparsemat); igraph_sparsemat_destroy(&Lsparse); igraph_sparsemat_destroy(&Rsparse); #define CALLSYM2(algo) do { \ igraph_vector_clear(&eval); \ igraph_matrix_resize(&evec, 0, 0); \ igraph_scg_adjacency(/* graph=*/ 0, &input_matrix, /*sparsemat=*/ 0, \ &ev, /* intervals= */ 3, \ /* intervals_vector= */ 0, \ /* algorithm= */ algo, &eval, &evec, \ /* groups= */ &groups, /* use_arpack= */ 0, \ /* maxiter= */ 0, &scg_graph, &scg_matrix, \ &scg_sparsemat, &L, &R, \ &Lsparse, &Rsparse); } while (0) igraph_matrix_init(&input_matrix, 0, 0); igraph_get_adjacency(&g, &input_matrix, IGRAPH_GET_ADJACENCY_BOTH, /* eids= */ 0); igraph_vector_resize(&ev, 1); VECTOR(ev)[0] = 1; CALLSYM2(IGRAPH_SCG_EXACT); PRINTRES(); igraph_destroy(&scg_graph); igraph_sparsemat_destroy(&scg_sparsemat); igraph_sparsemat_destroy(&Lsparse); igraph_sparsemat_destroy(&Rsparse); VECTOR(ev)[0] = 3; CALLSYM2(IGRAPH_SCG_EXACT); PRINTRES(); igraph_destroy(&scg_graph); igraph_sparsemat_destroy(&scg_sparsemat); igraph_sparsemat_destroy(&Lsparse); igraph_sparsemat_destroy(&Rsparse); igraph_vector_resize(&ev, 2); VECTOR(ev)[0] = 1; VECTOR(ev)[1] = 3; CALLSYM2(IGRAPH_SCG_EXACT); PRINTRES(); igraph_destroy(&scg_graph); igraph_sparsemat_destroy(&scg_sparsemat); igraph_sparsemat_destroy(&Lsparse); igraph_sparsemat_destroy(&Rsparse); igraph_matrix_destroy(&evec); igraph_vector_destroy(&eval); igraph_vector_destroy(&groups); igraph_matrix_destroy(&input_matrix); igraph_matrix_destroy(&scg_matrix); igraph_matrix_destroy(&L); igraph_matrix_destroy(&R); igraph_vector_destroy(&ev); igraph_destroy(&g); /* -------------------------------------------------------------------- */ return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_get_all_shortest_paths_dijkstra.out0000644000076500000240000000022313524616144034440 0ustar tamasstaff000000000000000 1 0 1 2 0 1 2 3 0 1 2 3 4 0 9 8 7 6 5 0 1 2 3 4 5 0 1 0 1 2 0 1 2 3 0 9 8 7 6 5 4 0 1 2 3 4 0 9 8 7 6 5 0 1 0 1 2 0 3 0 1 2 3 0 1 4 0 1 5 4 4 12 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_lapack_dgesv.c0000644000076500000240000001032513612122633030037 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include #define DIM 10 void igraph_print_warning(const char *reason, const char *file, int line, int igraph_errno) { printf("Warning: %s\n", reason); } int main() { igraph_matrix_t A, B, RHS; int info; int i; /* Identity matrix, you have to start somewhere */ igraph_matrix_init(&A, DIM, DIM); igraph_matrix_init(&B, DIM, 1); for (i = 0; i < DIM; i++) { MATRIX(A, i, i) = 1.0; MATRIX(B, i, 0) = i + 1; } igraph_matrix_copy(&RHS, &B); igraph_lapack_dgesv(&A, /*ipiv=*/ 0, &RHS, &info); if (info != 0) { return 1; } if (!igraph_matrix_all_e(&B, &RHS)) { return 2; } igraph_matrix_destroy(&A); igraph_matrix_destroy(&B); igraph_matrix_destroy(&RHS); /* Diagonal matrix */ igraph_matrix_init(&A, DIM, DIM); igraph_matrix_init(&RHS, DIM, 1); for (i = 0; i < DIM; i++) { MATRIX(A, i, i) = i + 1; MATRIX(RHS, i, 0) = i + 1; } igraph_lapack_dgesv(&A, /*ipiv=*/ 0, &RHS, &info); if (info != 0) { return 3; } for (i = 0; i < DIM; i++) { if (MATRIX(RHS, i, 0) != 1.0) { return 4; } } igraph_matrix_destroy(&A); igraph_matrix_destroy(&RHS); /* A general matrix */ igraph_rng_seed(igraph_rng_default(), 42); igraph_matrix_init(&A, DIM, DIM); igraph_matrix_init(&B, DIM, 1); igraph_matrix_init(&RHS, DIM, 1); for (i = 0; i < DIM; i++) { int j; MATRIX(B, i, 0) = igraph_rng_get_integer(igraph_rng_default(), 1, 10); for (j = 0; j < DIM; j++) { MATRIX(A, i, j) = igraph_rng_get_integer(igraph_rng_default(), 1, 10); } } igraph_blas_dgemv_array(/*transpose=*/ 0, /*alpha=*/ 1.0, /*a=*/ &A, /*x-*/ &MATRIX(B, 0, 0), /*beta=*/ 0, /*y=*/ &MATRIX(RHS, 0, 0)); igraph_lapack_dgesv(&A, /*ipiv=*/ 0, &RHS, &info); if (info != 0) { return 5; } for (i = 0; i < DIM; i++) { if (fabs(MATRIX(B, i, 0) - MATRIX(RHS, i, 0)) > 1e-13) { return 6; } } igraph_matrix_destroy(&A); igraph_matrix_destroy(&B); igraph_matrix_destroy(&RHS); /* A singular matrix */ igraph_rng_seed(igraph_rng_default(), 42); igraph_matrix_init(&A, DIM, DIM); igraph_matrix_init(&B, DIM, 1); igraph_matrix_init(&RHS, DIM, 1); for (i = 0; i < DIM; i++) { int j; MATRIX(B, i, 0) = igraph_rng_get_integer(igraph_rng_default(), 1, 10); for (j = 0; j < DIM; j++) { MATRIX(A, i, j) = igraph_rng_get_integer(igraph_rng_default(), 1, 10); } } for (i = 0; i < DIM; i++) { MATRIX(A, DIM - 1, i) = MATRIX(A, 0, i); } igraph_blas_dgemv_array(/*transpose=*/ 0, /*alpha=*/ 1.0, /*a=*/ &A, /*x-*/ &MATRIX(B, 0, 0), /*beta=*/ 0, /*y=*/ &MATRIX(RHS, 0, 0)); igraph_set_warning_handler(igraph_print_warning); igraph_lapack_dgesv(&A, /*ipiv=*/ 0, &RHS, &info); if (info != 10) { printf("LAPACK returned info = %d, should have been 10", info); return 7; } igraph_matrix_destroy(&A); igraph_matrix_destroy(&B); igraph_matrix_destroy(&RHS); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_to_prufer.c0000644000076500000240000001103613612122634027422 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int test_from_prufer_back_to_prufer() { igraph_t graph; igraph_integer_t prufer[] = {2, 3, 2, 3}; igraph_vector_int_t expected_prufer, output_prufer; igraph_bool_t success = 0; igraph_vector_int_view(&expected_prufer, prufer, 4); IGRAPH_CHECK(igraph_from_prufer(&graph, &expected_prufer)); IGRAPH_CHECK(igraph_vector_int_init(&output_prufer, 4)); IGRAPH_CHECK(igraph_to_prufer(&graph, &output_prufer)); success = igraph_vector_int_all_e(&expected_prufer, &output_prufer); igraph_destroy(&graph); igraph_vector_int_destroy(&output_prufer); return success; } int test_from_prufer_back_to_prufer_with_resize() { igraph_t graph; igraph_integer_t prufer[] = {0, 2, 4, 1, 1, 0}; igraph_vector_int_t expected_prufer, output_prufer; igraph_bool_t success; igraph_vector_int_view(&expected_prufer, prufer, 6); IGRAPH_CHECK(igraph_from_prufer(&graph, &expected_prufer)); IGRAPH_CHECK(igraph_vector_int_init(&output_prufer, 0)); IGRAPH_CHECK(igraph_to_prufer(&graph, &output_prufer)); success = igraph_vector_int_all_e(&expected_prufer, &output_prufer); igraph_destroy(&graph); igraph_vector_int_destroy(&output_prufer); return success; } int test_from_prufer_back_to_prufer_with_resize2() { igraph_t graph; igraph_integer_t prufer[] = {2, 4, 5, 1, 3}; igraph_vector_int_t expected_prufer, output_prufer; igraph_bool_t success; igraph_vector_int_view(&expected_prufer, prufer, 5); IGRAPH_CHECK(igraph_from_prufer(&graph, &expected_prufer)); IGRAPH_CHECK(igraph_vector_int_init(&output_prufer, 0)); IGRAPH_CHECK(igraph_to_prufer(&graph, &output_prufer)); success = igraph_vector_int_all_e(&output_prufer, &expected_prufer); igraph_destroy(&graph); igraph_vector_int_destroy(&output_prufer); return success; } int random_tree(int size, igraph_t* tree, igraph_vector_int_t* prufer) { int i, j; int prufer_length; if (size < 0) { return IGRAPH_EINVAL; } if (size < 2) { return igraph_empty(tree, size, IGRAPH_UNDIRECTED); } prufer_length = size - 2; IGRAPH_CHECK(igraph_vector_int_resize(prufer, prufer_length)); for (i = 0; i < prufer_length; ++i) { j = RNG_INTEGER(0, size - 1); VECTOR(*prufer)[i] = j; } IGRAPH_CHECK(igraph_from_prufer(tree, prufer)); return IGRAPH_SUCCESS; } int test_from_random_prufer_back_to_prufer(int tree_size) { igraph_t graph; igraph_vector_int_t expected_prufer, output_prufer; igraph_bool_t success = 0; igraph_integer_t random_seed = 4096; IGRAPH_CHECK(igraph_vector_int_init(&output_prufer, 0)); IGRAPH_CHECK(igraph_vector_int_init(&expected_prufer, 0)); igraph_rng_seed(igraph_rng_default(), random_seed); IGRAPH_CHECK(random_tree(tree_size, &graph, &expected_prufer)); IGRAPH_CHECK(igraph_to_prufer(&graph, &output_prufer)); success = igraph_vector_int_all_e(&output_prufer, &expected_prufer); igraph_destroy(&graph); igraph_vector_int_destroy(&expected_prufer); igraph_vector_int_destroy(&output_prufer); return success; } int test_num = 0; #define RUN_TEST(TEST) \ test_num++; \ if(!(TEST)) { \ return test_num; \ } int main() { RUN_TEST(test_from_prufer_back_to_prufer()); RUN_TEST(test_from_prufer_back_to_prufer_with_resize()); RUN_TEST(test_from_prufer_back_to_prufer_with_resize2()); RUN_TEST(test_from_random_prufer_back_to_prufer(10)); RUN_TEST(test_from_random_prufer_back_to_prufer(100)); RUN_TEST(test_from_random_prufer_back_to_prufer(1000)); RUN_TEST(test_from_random_prufer_back_to_prufer(10000)); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/nodelist1.dl0000644000076500000240000000013313524616144026144 0ustar tamasstaff00000000000000DL n=5 format = nodelist1 labels: george, sally, jim, billy, jane data: 1 2 3 2 3 3 1 4 3 python-igraph-0.8.0/vendor/source/igraph/examples/simple/dqueue.c0000644000076500000240000000600313612122633025350 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_dqueue_t q; int i; /* igraph_dqueue_init, igraph_dqueue_destroy, igraph_dqueue_empty */ igraph_dqueue_init(&q, 5); if (!igraph_dqueue_empty(&q)) { return 1; } igraph_dqueue_destroy(&q); /* igraph_dqueue_push, igraph_dqueue_pop */ igraph_dqueue_init(&q, 4); igraph_dqueue_push(&q, 1); igraph_dqueue_push(&q, 2); igraph_dqueue_push(&q, 3); igraph_dqueue_push(&q, 4); if (igraph_dqueue_pop(&q) != 1) { return 2; } if (igraph_dqueue_pop(&q) != 2) { return 3; } if (igraph_dqueue_pop(&q) != 3) { return 4; } if (igraph_dqueue_pop(&q) != 4) { return 5; } igraph_dqueue_destroy(&q); /* igraph_dqueue_clear, igraph_dqueue_size */ igraph_dqueue_init(&q, 0); if (igraph_dqueue_size(&q) != 0) { return 6; } igraph_dqueue_clear(&q); if (igraph_dqueue_size(&q) != 0) { return 7; } for (i = 0; i < 10; i++) { igraph_dqueue_push(&q, i); } igraph_dqueue_clear(&q); if (igraph_dqueue_size(&q) != 0) { return 8; } igraph_dqueue_destroy(&q); /* TODO: igraph_dqueue_full */ /* igraph_dqueue_head, igraph_dqueue_back, igraph_dqueue_pop_back */ igraph_dqueue_init(&q, 0); for (i = 0; i < 10; i++) { igraph_dqueue_push(&q, i); } for (i = 0; i < 10; i++) { if (igraph_dqueue_head(&q) != 0) { return 9; } if (igraph_dqueue_back(&q) != 9 - i) { return 10; } if (igraph_dqueue_pop_back(&q) != 9 - i) { return 11; } } igraph_dqueue_destroy(&q); /* print */ igraph_dqueue_init(&q, 4); igraph_dqueue_push(&q, 1); igraph_dqueue_push(&q, 2); igraph_dqueue_push(&q, 3); igraph_dqueue_push(&q, 4); igraph_dqueue_pop(&q); igraph_dqueue_pop(&q); igraph_dqueue_push(&q, 5); igraph_dqueue_push(&q, 6); igraph_dqueue_print(&q); igraph_dqueue_clear(&q); igraph_dqueue_print(&q); igraph_dqueue_destroy(&q); if (IGRAPH_FINALLY_STACK_SIZE() != 0) { return 12; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_intersection.c0000644000076500000240000000764313612122633030133 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void print_vector(igraph_vector_t *v) { long int i, l = igraph_vector_size(v); for (i = 0; i < l; i++) { printf(" %li", (long int) VECTOR(*v)[i]); } printf("\n"); } int main() { igraph_t left, right, isec; igraph_vector_t v; igraph_vector_ptr_t glist; igraph_t g1, g2, g3; igraph_vector_t edge_map1, edge_map2; igraph_vector_init_int_end(&v, -1, 0, 1, 1, 2, 2, 3, -1); igraph_create(&left, &v, 0, IGRAPH_DIRECTED); igraph_vector_destroy(&v); igraph_vector_init_int_end(&v, -1, 1, 0, 5, 4, 1, 2, 3, 2, -1); igraph_create(&right, &v, 0, IGRAPH_DIRECTED); igraph_vector_destroy(&v); igraph_vector_init(&edge_map1, 0); igraph_vector_init(&edge_map2, 0); igraph_intersection(&isec, &left, &right, &edge_map1, &edge_map2); igraph_vector_init(&v, 0); igraph_get_edgelist(&isec, &v, 0); printf("---\n"); print_vector(&v); print_vector(&edge_map1); print_vector(&edge_map2); printf("---\n"); igraph_vector_destroy(&v); igraph_destroy(&left); igraph_destroy(&right); igraph_destroy(&isec); igraph_vector_destroy(&edge_map1); igraph_vector_destroy(&edge_map2); /* empty graph list */ igraph_vector_ptr_init(&glist, 0); igraph_intersection_many(&isec, &glist, 0); if (igraph_vcount(&isec) != 0 || !igraph_is_directed(&isec)) { return 1; } igraph_destroy(&isec); igraph_vector_ptr_destroy(&glist); /* graph list with an empty graph */ igraph_vector_ptr_init(&glist, 3); igraph_vector_init_int_end(&v, -1, 0, 1, 1, 2, 2, 3, -1); igraph_create(&g1, &v, 0, IGRAPH_DIRECTED); igraph_vector_destroy(&v); igraph_vector_init_int_end(&v, -1, 0, 1, 1, 2, 2, 3, -1); igraph_create(&g2, &v, 0, IGRAPH_DIRECTED); igraph_vector_destroy(&v); igraph_empty(&g3, 10, IGRAPH_DIRECTED); VECTOR(glist)[0] = &g1; VECTOR(glist)[1] = &g2; VECTOR(glist)[2] = &g3; igraph_intersection_many(&isec, &glist, 0); if (igraph_ecount(&isec) != 0 || igraph_vcount(&isec) != 10) { return 2; } igraph_destroy(&g1); igraph_destroy(&g2); igraph_destroy(&g3); igraph_destroy(&isec); igraph_vector_ptr_destroy(&glist); /* "proper" graph list */ igraph_vector_ptr_init(&glist, 3); igraph_vector_init_int_end(&v, -1, 0, 1, 1, 2, 2, 3, -1); igraph_create(&g1, &v, 0, IGRAPH_DIRECTED); igraph_vector_destroy(&v); igraph_vector_init_int_end(&v, -1, 0, 1, 1, 2, 2, 3, 3, 2, 4, 5, 6, 5, -1); igraph_create(&g2, &v, 0, IGRAPH_DIRECTED); igraph_vector_destroy(&v); igraph_vector_init_int_end(&v, -1, 2, 3, 1, 0, 1, 2, 3, 2, 4, 5, 6, 5, 2, 3, -1); igraph_create(&g3, &v, 0, IGRAPH_DIRECTED); igraph_vector_destroy(&v); VECTOR(glist)[0] = &g1; VECTOR(glist)[1] = &g2; VECTOR(glist)[2] = &g3; igraph_intersection_many(&isec, &glist, 0); igraph_write_graph_edgelist(&isec, stdout); igraph_destroy(&g1); igraph_destroy(&g2); igraph_destroy(&g3); igraph_destroy(&isec); igraph_vector_ptr_destroy(&glist); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_degree_sequence_game.c0000644000076500000240000000715313612122633031535 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_vector_t outdeg, indeg, vec; igraph_bool_t is_simple; igraph_vector_init_real(&outdeg, 10, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0); igraph_vector_init_real(&indeg, 10, 4.0, 4.0, 2.0, 2.0, 4.0, 4.0, 2.0, 2.0, 3.0, 3.0); igraph_vector_init(&vec, 0); /* checking the simple method, undirected graphs */ igraph_degree_sequence_game(&g, &outdeg, 0, IGRAPH_DEGSEQ_SIMPLE); if (igraph_is_directed(&g) || igraph_vcount(&g) != 10) { return 1; } if (igraph_degree(&g, &vec, igraph_vss_all(), IGRAPH_OUT, 1)) { return 2; } igraph_vector_print(&vec); igraph_destroy(&g); /* checking the Viger-Latapy method, undirected graphs */ igraph_degree_sequence_game(&g, &outdeg, 0, IGRAPH_DEGSEQ_VL); if (igraph_is_directed(&g) || igraph_vcount(&g) != 10) { return 3; } if (igraph_is_simple(&g, &is_simple) || !is_simple) { return 4; } if (igraph_degree(&g, &vec, igraph_vss_all(), IGRAPH_OUT, 0)) { return 5; } igraph_vector_print(&vec); igraph_destroy(&g); /* checking the simple method, directed graphs */ igraph_degree_sequence_game(&g, &outdeg, &indeg, IGRAPH_DEGSEQ_SIMPLE); if (!igraph_is_directed(&g) || igraph_vcount(&g) != 10) { return 6; } if (igraph_degree(&g, &vec, igraph_vss_all(), IGRAPH_OUT, 1)) { return 7; } igraph_vector_print(&vec); if (igraph_degree(&g, &vec, igraph_vss_all(), IGRAPH_IN, 1)) { return 8; } igraph_vector_print(&vec); igraph_destroy(&g); /* checking the no multiple edges method, undirected graphs */ igraph_degree_sequence_game(&g, &outdeg, 0, IGRAPH_DEGSEQ_SIMPLE_NO_MULTIPLE); if (igraph_is_directed(&g) || igraph_vcount(&g) != 10) { return 9; } if (igraph_is_simple(&g, &is_simple) || !is_simple) { return 10; } if (igraph_degree(&g, &vec, igraph_vss_all(), IGRAPH_OUT, 1)) { return 11; } igraph_vector_print(&vec); igraph_destroy(&g); /* checking the no multiple edges method, directed graphs */ igraph_degree_sequence_game(&g, &outdeg, &indeg, IGRAPH_DEGSEQ_SIMPLE_NO_MULTIPLE); if (!igraph_is_directed(&g) || igraph_vcount(&g) != 10) { return 12; } if (igraph_is_simple(&g, &is_simple) || !is_simple) { return 13; } if (igraph_degree(&g, &vec, igraph_vss_all(), IGRAPH_OUT, 1)) { return 14; } igraph_vector_print(&vec); if (igraph_degree(&g, &vec, igraph_vss_all(), IGRAPH_IN, 1)) { return 15; } igraph_vector_print(&vec); igraph_destroy(&g); igraph_vector_destroy(&vec); igraph_vector_destroy(&outdeg); igraph_vector_destroy(&indeg); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/assortativity.c0000644000076500000240000002465513612122633027022 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int main() { igraph_t g; FILE *karate, *neural; igraph_real_t res; igraph_vector_t types; igraph_vector_t degree, outdegree, indegree; igraph_real_t football_types[] = { 7, 0, 2, 3, 7, 3, 2, 8, 8, 7, 3, 10, 6, 2, 6, 2, 7, 9, 6, 1, 9, 8, 8, 7, 10, 0, 6, 9, 11, 1, 1, 6, 2, 0, 6, 1, 5, 0, 6, 2, 3, 7, 5, 6, 4, 0, 11, 2, 4, 11, 10, 8, 3, 11, 6, 1, 9, 4, 11, 10, 2, 6, 9, 10, 2, 9, 4, 11, 8, 10, 9, 6, 3, 11, 3, 4, 9, 8, 8, 1, 5, 3, 5, 11, 3, 6, 4, 9, 11, 0, 5, 4, 4, 7, 1, 9, 9, 10, 3, 6, 2, 1, 3, 0, 7, 0, 2, 3, 8, 0, 4, 8, 4, 9, 11 }; karate = fopen("karate.gml", "r"); igraph_read_graph_gml(&g, karate); fclose(karate); igraph_vector_init(&types, 0); igraph_degree(&g, &types, igraph_vss_all(), IGRAPH_ALL, /*loops=*/ 1); igraph_assortativity_nominal(&g, &types, &res, /*directed=*/ 0); printf("%.5f\n", res); igraph_destroy(&g); /*---------------------*/ neural = fopen("celegansneural.gml", "r"); igraph_read_graph_gml(&g, neural); fclose(neural); igraph_degree(&g, &types, igraph_vss_all(), IGRAPH_ALL, /*loops=*/ 1); igraph_assortativity_nominal(&g, &types, &res, /*directed=*/ 1); printf("%.5f\n", res); igraph_assortativity_nominal(&g, &types, &res, /*directed=*/ 0); printf("%.5f\n", res); igraph_destroy(&g); igraph_vector_destroy(&types); /*---------------------*/ karate = fopen("karate.gml", "r"); igraph_read_graph_gml(&g, karate); fclose(karate); igraph_vector_init(°ree, 0); igraph_degree(&g, °ree, igraph_vss_all(), IGRAPH_ALL, /*loops=*/ 1); igraph_vector_add_constant(°ree, -1); igraph_assortativity(&g, °ree, 0, &res, /*directed=*/ 0); printf("%.5f\n", res); igraph_destroy(&g); /*---------------------*/ neural = fopen("celegansneural.gml", "r"); igraph_read_graph_gml(&g, neural); fclose(neural); igraph_degree(&g, °ree, igraph_vss_all(), IGRAPH_ALL, /*loops=*/ 1); igraph_vector_add_constant(°ree, -1); igraph_assortativity(&g, °ree, 0, &res, /*directed=*/ 1); printf("%.5f\n", res); igraph_assortativity(&g, °ree, 0, &res, /*directed=*/ 0); printf("%.5f\n", res); igraph_vector_destroy(°ree); /*---------------------*/ igraph_vector_init(&indegree, 0); igraph_vector_init(&outdegree, 0); igraph_degree(&g, &indegree, igraph_vss_all(), IGRAPH_IN, /*loops=*/ 1); igraph_degree(&g, &outdegree, igraph_vss_all(), IGRAPH_OUT, /*loops=*/ 1); igraph_vector_add_constant(&indegree, -1); igraph_vector_add_constant(&outdegree, -1); igraph_assortativity(&g, &outdegree, &indegree, &res, /*directed=*/ 1); printf("%.5f\n", res); igraph_vector_destroy(&indegree); igraph_vector_destroy(&outdegree); /*---------------------*/ igraph_assortativity_degree(&g, &res, /*directed=*/ 1); printf("%.5f\n", res); igraph_destroy(&g); /*---------------------*/ karate = fopen("karate.gml", "r"); igraph_read_graph_gml(&g, karate); fclose(karate); igraph_assortativity_degree(&g, &res, /*directed=*/ 1); printf("%.5f\n", res); igraph_destroy(&g); /*---------------------*/ igraph_small(&g, sizeof(football_types) / sizeof(igraph_real_t), IGRAPH_UNDIRECTED, 0, 1, 2, 3, 0, 4, 4, 5, 3, 5, 2, 6, 6, 7, 7, 8, 8, 9, 0, 9, 4, 9, 5, 10, 10, 11, 5, 11, 3, 11, 12, 13, 2, 13, 2, 14, 12, 14, 14, 15, 13, 15, 2, 15, 4, 16, 9, 16, 0, 16, 16, 17, 12, 17, 12, 18, 18, 19, 17, 20, 20, 21, 8, 21, 7, 21, 9, 22, 7, 22, 21, 22, 8, 22, 22, 23, 9, 23, 4, 23, 16, 23, 0, 23, 11, 24, 24, 25, 1, 25, 3, 26, 12, 26, 14, 26, 26, 27, 17, 27, 1, 27, 17, 27, 4, 28, 11, 28, 24, 28, 19, 29, 29, 30, 19, 30, 18, 31, 31, 32, 21, 32, 15, 32, 13, 32, 6, 32, 0, 33, 1, 33, 25, 33, 19, 33, 31, 34, 26, 34, 12, 34, 18, 34, 34, 35, 0, 35, 29, 35, 19, 35, 30, 35, 18, 36, 12, 36, 20, 36, 19, 36, 36, 37, 1, 37, 25, 37, 33, 37, 18, 38, 16, 38, 28, 38, 26, 38, 14, 38, 12, 38, 38, 39, 6, 39, 32, 39, 13, 39, 15, 39, 7, 40, 3, 40, 40, 41, 8, 41, 4, 41, 23, 41, 9, 41, 0, 41, 16, 41, 34, 42, 29, 42, 18, 42, 26, 42, 42, 43, 36, 43, 26, 43, 31, 43, 38, 43, 12, 43, 14, 43, 19, 44, 35, 44, 30, 44, 44, 45, 13, 45, 33, 45, 1, 45, 37, 45, 25, 45, 21, 46, 46, 47, 22, 47, 6, 47, 15, 47, 2, 47, 39, 47, 32, 47, 44, 48, 48, 49, 32, 49, 46, 49, 30, 50, 24, 50, 11, 50, 28, 50, 50, 51, 40, 51, 8, 51, 22, 51, 21, 51, 3, 52, 40, 52, 5, 52, 52, 53, 25, 53, 48, 53, 49, 53, 46, 53, 39, 54, 31, 54, 38, 54, 14, 54, 34, 54, 18, 54, 54, 55, 31, 55, 6, 55, 35, 55, 29, 55, 19, 55, 30, 55, 27, 56, 56, 57, 1, 57, 42, 57, 44, 57, 48, 57, 3, 58, 6, 58, 17, 58, 36, 58, 36, 59, 58, 59, 59, 60, 10, 60, 39, 60, 6, 60, 47, 60, 13, 60, 15, 60, 2, 60, 43, 61, 47, 61, 54, 61, 18, 61, 26, 61, 31, 61, 34, 61, 61, 62, 20, 62, 45, 62, 17, 62, 27, 62, 56, 62, 27, 63, 58, 63, 59, 63, 42, 63, 63, 64, 9, 64, 32, 64, 60, 64, 2, 64, 6, 64, 47, 64, 13, 64, 0, 65, 27, 65, 17, 65, 63, 65, 56, 65, 20, 65, 65, 66, 59, 66, 24, 66, 44, 66, 48, 66, 16, 67, 41, 67, 46, 67, 53, 67, 49, 67, 67, 68, 15, 68, 50, 68, 21, 68, 51, 68, 7, 68, 22, 68, 8, 68, 4, 69, 24, 69, 28, 69, 50, 69, 11, 69, 69, 70, 43, 70, 65, 70, 20, 70, 56, 70, 62, 70, 27, 70, 60, 71, 18, 71, 14, 71, 34, 71, 54, 71, 38, 71, 61, 71, 31, 71, 71, 72, 2, 72, 10, 72, 3, 72, 40, 72, 52, 72, 7, 73, 49, 73, 53, 73, 67, 73, 46, 73, 73, 74, 2, 74, 72, 74, 5, 74, 10, 74, 52, 74, 3, 74, 40, 74, 20, 75, 66, 75, 48, 75, 57, 75, 44, 75, 75, 76, 27, 76, 59, 76, 20, 76, 70, 76, 66, 76, 56, 76, 62, 76, 73, 77, 22, 77, 7, 77, 51, 77, 21, 77, 8, 77, 77, 78, 23, 78, 50, 78, 28, 78, 22, 78, 8, 78, 68, 78, 7, 78, 51, 78, 31, 79, 43, 79, 30, 79, 19, 79, 29, 79, 35, 79, 55, 79, 79, 80, 37, 80, 29, 80, 16, 81, 5, 81, 40, 81, 10, 81, 72, 81, 3, 81, 81, 82, 74, 82, 39, 82, 77, 82, 80, 82, 30, 82, 29, 82, 7, 82, 53, 83, 81, 83, 69, 83, 73, 83, 46, 83, 67, 83, 49, 83, 83, 84, 24, 84, 49, 84, 52, 84, 3, 84, 74, 84, 10, 84, 81, 84, 5, 84, 3, 84, 6, 85, 14, 85, 38, 85, 43, 85, 80, 85, 12, 85, 26, 85, 31, 85, 44, 86, 53, 86, 75, 86, 57, 86, 48, 86, 80, 86, 66, 86, 86, 87, 17, 87, 62, 87, 56, 87, 24, 87, 20, 87, 65, 87, 49, 88, 58, 88, 83, 88, 69, 88, 46, 88, 53, 88, 73, 88, 67, 88, 88, 89, 1, 89, 37, 89, 25, 89, 33, 89, 55, 89, 45, 89, 5, 90, 8, 90, 23, 90, 0, 90, 11, 90, 50, 90, 24, 90, 69, 90, 28, 90, 29, 91, 48, 91, 66, 91, 69, 91, 44, 91, 86, 91, 57, 91, 80, 91, 91, 92, 35, 92, 15, 92, 86, 92, 48, 92, 57, 92, 61, 92, 66, 92, 75, 92, 0, 93, 23, 93, 80, 93, 16, 93, 4, 93, 82, 93, 91, 93, 41, 93, 9, 93, 34, 94, 19, 94, 55, 94, 79, 94, 80, 94, 29, 94, 30, 94, 82, 94, 35, 94, 70, 95, 69, 95, 76, 95, 62, 95, 56, 95, 27, 95, 17, 95, 87, 95, 37, 95, 48, 96, 17, 96, 76, 96, 27, 96, 56, 96, 65, 96, 20, 96, 87, 96, 5, 97, 86, 97, 58, 97, 11, 97, 59, 97, 63, 97, 97, 98, 77, 98, 48, 98, 84, 98, 40, 98, 10, 98, 5, 98, 52, 98, 81, 98, 89, 99, 34, 99, 14, 99, 85, 99, 54, 99, 18, 99, 31, 99, 61, 99, 71, 99, 14, 99, 99, 100, 82, 100, 13, 100, 2, 100, 15, 100, 32, 100, 64, 100, 47, 100, 39, 100, 6, 100, 51, 101, 30, 101, 94, 101, 1, 101, 79, 101, 58, 101, 19, 101, 55, 101, 35, 101, 29, 101, 100, 102, 74, 102, 52, 102, 98, 102, 72, 102, 40, 102, 10, 102, 3, 102, 102, 103, 33, 103, 45, 103, 25, 103, 89, 103, 37, 103, 1, 103, 70, 103, 72, 104, 11, 104, 0, 104, 93, 104, 67, 104, 41, 104, 16, 104, 87, 104, 23, 104, 4, 104, 9, 104, 89, 105, 103, 105, 33, 105, 62, 105, 37, 105, 45, 105, 1, 105, 80, 105, 25, 105, 25, 106, 56, 106, 92, 106, 2, 106, 13, 106, 32, 106, 60, 106, 6, 106, 64, 106, 15, 106, 39, 106, 88, 107, 75, 107, 98, 107, 102, 107, 72, 107, 40, 107, 81, 107, 5, 107, 10, 107, 84, 107, 4, 108, 9, 108, 7, 108, 51, 108, 77, 108, 21, 108, 78, 108, 22, 108, 68, 108, 79, 109, 30, 109, 63, 109, 1, 109, 33, 109, 103, 109, 105, 109, 45, 109, 25, 109, 89, 109, 37, 109, 67, 110, 13, 110, 24, 110, 80, 110, 88, 110, 49, 110, 73, 110, 46, 110, 83, 110, 53, 110, 23, 111, 64, 111, 46, 111, 78, 111, 8, 111, 21, 111, 51, 111, 7, 111, 108, 111, 68, 111, 77, 111, 52, 112, 96, 112, 97, 112, 57, 112, 66, 112, 63, 112, 44, 112, 92, 112, 75, 112, 91, 112, 28, 113, 20, 113, 95, 113, 59, 113, 70, 113, 17, 113, 87, 113, 76, 113, 65, 113, 96, 113, 83, 114, 88, 114, 110, 114, 53, 114, 49, 114, 73, 114, 46, 114, 67, 114, 58, 114, 15, 114, 104, 114, -1); igraph_simplify(&g, /*multiple=*/ 1, /*loops=*/ 1, /*edge_comb=*/ 0); igraph_vector_view(&types, football_types, sizeof(football_types) / sizeof(igraph_real_t)); igraph_assortativity_nominal(&g, &types, &res, /*directed=*/ 0); printf("%.5f\n", res); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_eigen_matrix_symmetric_arpack.c0000644000076500000240000001007113612122633033502 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2012 Gabor Csardi 334 Harvard street, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #define DIM 10 int check_ev(const igraph_matrix_t *A, const igraph_vector_t *values, const igraph_matrix_t *vectors, int err_off) { int i, n = igraph_matrix_nrow(A); int ne = igraph_matrix_ncol(vectors); igraph_vector_t v, lhs, rhs; if (ne != igraph_vector_size(values)) { printf("'values' and 'vectors' sizes do not match\n"); exit(err_off + 1); } igraph_vector_init(&lhs, n); igraph_vector_init(&rhs, n); for (i = 0; i < ne; i++) { igraph_vector_view(&v, &MATRIX(*vectors, 0, i), n); igraph_blas_dgemv(/*transpose=*/ 0, /*alpha=*/ 1, A, &v, /*beta=*/ 0, &lhs); igraph_vector_update(&rhs, &v); igraph_vector_scale(&rhs, VECTOR(*values)[i]); if (igraph_vector_maxdifference(&lhs, &rhs) > 1e-10) { printf("LHS %i: ", i); igraph_vector_print(&lhs); printf("RHS %i: ", i); igraph_vector_print(&rhs); exit(err_off + 2); } } igraph_vector_destroy(&rhs); igraph_vector_destroy(&lhs); return 0; } int main() { igraph_matrix_t A; igraph_vector_t values; igraph_matrix_t vectors; int i, j; igraph_eigen_which_t which; igraph_arpack_options_t options; igraph_rng_seed(igraph_rng_default(), 42 * 42); igraph_matrix_init(&A, DIM, DIM); igraph_matrix_init(&vectors, 0, 0); igraph_vector_init(&values, 0); igraph_arpack_options_init(&options); for (i = 0; i < DIM; i++) { for (j = i; j < DIM; j++) { MATRIX(A, i, j) = MATRIX(A, j, i) = igraph_rng_get_integer(igraph_rng_default(), 1, 10); } } which.pos = IGRAPH_EIGEN_LM; which.howmany = 2; igraph_eigen_matrix_symmetric(&A, /*sA=*/ 0, /*fun=*/ 0, DIM, /*extra=*/ 0, IGRAPH_EIGEN_ARPACK, &which, &options, /*storage=*/ 0, &values, &vectors); igraph_vector_print(&values); check_ev(&A, &values, &vectors, 0); which.howmany = 8; igraph_eigen_matrix_symmetric(&A, /*sA=*/ 0, /*fun=*/ 0, DIM, /*extra=*/ 0, IGRAPH_EIGEN_ARPACK, &which, &options, /*storage=*/ 0, &values, &vectors); igraph_vector_print(&values); check_ev(&A, &values, &vectors, 10); which.pos = IGRAPH_EIGEN_BE; which.howmany = 5; igraph_eigen_matrix_symmetric(&A, /*sA=*/ 0, /*fun=*/ 0, DIM, /*extra=*/ 0, IGRAPH_EIGEN_ARPACK, &which, &options, /*storage=*/ 0, &values, &vectors); igraph_vector_print(&values); check_ev(&A, &values, &vectors, 20); which.pos = IGRAPH_EIGEN_SM; which.howmany = 5; igraph_eigen_matrix_symmetric(&A, /*sA=*/ 0, /*fun=*/ 0, DIM, /*extra=*/ 0, IGRAPH_EIGEN_ARPACK, &which, &options, /*storage=*/ 0, &values, &vectors); igraph_vector_print(&values); check_ev(&A, &values, &vectors, 30); igraph_vector_destroy(&values); igraph_matrix_destroy(&vectors); igraph_matrix_destroy(&A); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_from_prufer.c0000644000076500000240000000242513612122633027744 0ustar tamasstaff00000000000000 #include #include #include void print_edges(const igraph_t *graph) { long ecount = igraph_ecount(graph); long i; for (i = 0; i < ecount; ++i) { printf("%d %d\n", IGRAPH_FROM(graph, i), IGRAPH_TO(graph, i)); } printf("\n"); } int main() { igraph_t graph; igraph_integer_t prufer1[] = {2, 3, 2, 3}; igraph_integer_t prufer2[] = {0, 2, 4, 1, 1, 0}; igraph_integer_t prufer3[] = {}; igraph_vector_int_t prufer; igraph_bool_t tree; igraph_vector_int_view(&prufer, prufer1, sizeof(prufer1) / sizeof(igraph_integer_t)); igraph_from_prufer(&graph, &prufer); igraph_is_tree(&graph, &tree, NULL, IGRAPH_ALL); assert(tree); print_edges(&graph); igraph_destroy(&graph); igraph_vector_int_view(&prufer, prufer2, sizeof(prufer2) / sizeof(igraph_integer_t)); igraph_from_prufer(&graph, &prufer); igraph_is_tree(&graph, &tree, NULL, IGRAPH_ALL); assert(tree); print_edges(&graph); igraph_destroy(&graph); igraph_vector_int_view(&prufer, prufer3, sizeof(prufer3) / sizeof(igraph_integer_t)); igraph_from_prufer(&graph, &prufer); igraph_is_tree(&graph, &tree, NULL, IGRAPH_ALL); assert(tree); print_edges(&graph); igraph_destroy(&graph); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_community_label_propagation.c0000644000076500000240000000774313614300625033215 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_vector_t membership, weights, initial; igraph_vector_bool_t fixed; long int i; /* Zachary Karate club -- this is just a quick smoke test */ igraph_small(&g, 0, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 0, 7, 0, 8, 0, 10, 0, 11, 0, 12, 0, 13, 0, 17, 0, 19, 0, 21, 0, 31, 1, 2, 1, 3, 1, 7, 1, 13, 1, 17, 1, 19, 1, 21, 1, 30, 2, 3, 2, 7, 2, 8, 2, 9, 2, 13, 2, 27, 2, 28, 2, 32, 3, 7, 3, 12, 3, 13, 4, 6, 4, 10, 5, 6, 5, 10, 5, 16, 6, 16, 8, 30, 8, 32, 8, 33, 9, 33, 13, 33, 14, 32, 14, 33, 15, 32, 15, 33, 18, 32, 18, 33, 19, 33, 20, 32, 20, 33, 22, 32, 22, 33, 23, 25, 23, 27, 23, 29, 23, 32, 23, 33, 24, 25, 24, 27, 24, 31, 25, 31, 26, 29, 26, 33, 27, 33, 28, 31, 28, 33, 29, 32, 29, 33, 30, 32, 30, 33, 31, 32, 31, 33, 32, 33, -1); igraph_vector_init(&membership, 0); igraph_community_label_propagation(&g, &membership, 0, 0, 0, /*modularity=*/ 0); if (igraph_vector_max(&membership) > 3) { printf("Resulting graph had more than four clusters:\n"); for (i = 0; i < igraph_vcount(&g); i++) { printf("%li ", (long)VECTOR(membership)[i]); } printf("\n"); return 1; } igraph_destroy(&g); /* Simple star graph to test weights */ igraph_small(&g, 0, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 2, 3, 2, 4, 3, 4, 3, 5, 4, 5, -1); igraph_vector_init_int_end(&weights, -1, 5, 1, 1, 1, 1, 1, 1, 1, 1, 1, -1); igraph_vector_init_int_end(&initial, -1, 0, 0, 1, 1, 1, 1, -1); igraph_vector_bool_init(&fixed, 6); VECTOR(fixed)[3] = 1; VECTOR(fixed)[4] = 1; VECTOR(fixed)[5] = 1; igraph_community_label_propagation(&g, &membership, &weights, &initial, &fixed, /*modularity=*/ 0); for (i = 0; i < igraph_vcount(&g); i++) if (VECTOR(membership)[i] != (i < 2 ? 0 : 1)) { return 3; } igraph_community_label_propagation(&g, &membership, 0, &initial, &fixed, /*modularity=*/ 0); for (i = 0; i < igraph_vcount(&g); i++) if (VECTOR(membership)[i] != 0) { return 4; } /* Check whether it works with no fixed vertices at all * while an initial configuration is given -- see bug * #570902 in Launchpad. This is a simple smoke test only. */ igraph_community_label_propagation(&g, &membership, &weights, &initial, 0, /*modularity=*/ 0); igraph_vector_bool_destroy(&fixed); igraph_vector_destroy(&weights); igraph_vector_destroy(&initial); igraph_destroy(&g); igraph_vector_destroy(&membership); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/walktrap.c0000644000076500000240000000451713612122634025716 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_matrix_t merges; igraph_vector_t modularity; long int no_of_nodes; long int i; igraph_small(&g, 5, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 0, 4, 1, 2, 1, 3, 1, 4, 2, 3, 2, 4, 3, 4, 5, 6, 5, 7, 5, 8, 5, 9, 6, 7, 6, 8, 6, 9, 7, 8, 7, 9, 8, 9, 0, 5, -1); igraph_vector_init(&modularity, 0); igraph_matrix_init(&merges, 0, 0); igraph_community_walktrap(&g, 0 /* no weights */, 4 /* steps */, &merges, &modularity, /* membership=*/ 0); no_of_nodes = igraph_vcount(&g); printf("Merges:\n"); for (i = 0; i < igraph_matrix_nrow(&merges); i++) { printf("%2.1li + %2.li -> %2.li (modularity %4.2f)\n", (long int)MATRIX(merges, i, 0), (long int)MATRIX(merges, i, 1), no_of_nodes + i, VECTOR(modularity)[i]); } igraph_destroy(&g); /* isolated vertices */ igraph_small(&g, 5, IGRAPH_UNDIRECTED, -1); if (igraph_community_walktrap(&g, 0 /* no weights */, 4 /* steps */, &merges, &modularity, /* membership = */ 0)) { return 1; } if (igraph_vector_min(&modularity) != 0 || igraph_vector_max(&modularity) != 0) { return 2; } igraph_destroy(&g); igraph_matrix_destroy(&merges); igraph_vector_destroy(&modularity); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_lapack_dgehrd.out0000644000076500000240000000000013524616144030545 0ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_feedback_arc_set.c0000644000076500000240000000516313614300625030645 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int main() { igraph_t g; igraph_vector_t weights, result; igraph_bool_t dag; igraph_vector_init(&result, 0); /***********************************************************************/ /* Approximation with Eades' method */ /***********************************************************************/ /* Simple unweighted graph */ igraph_small(&g, 0, IGRAPH_DIRECTED, 0, 1, 1, 2, 2, 0, 2, 3, 2, 4, 0, 4, 4, 3, 5, 0, 6, 5, -1); igraph_feedback_arc_set(&g, &result, 0, IGRAPH_FAS_APPROX_EADES); igraph_vector_print(&result); igraph_delete_edges(&g, igraph_ess_vector(&result)); igraph_is_dag(&g, &dag); if (!dag) { return 1; } igraph_destroy(&g); /* Simple weighted graph */ igraph_small(&g, 0, IGRAPH_DIRECTED, 0, 1, 1, 2, 2, 0, 2, 3, 2, 4, 0, 4, 4, 3, 5, 0, 6, 5, -1); igraph_vector_init_int_end(&weights, -1, 1, 1, 3, 1, 1, 1, 1, 1, 1, -1); igraph_feedback_arc_set(&g, &result, &weights, IGRAPH_FAS_APPROX_EADES); igraph_vector_print(&result); igraph_delete_edges(&g, igraph_ess_vector(&result)); igraph_is_dag(&g, &dag); if (!dag) { return 2; } igraph_vector_destroy(&weights); igraph_destroy(&g); /* Simple unweighted graph with loops */ igraph_small(&g, 0, IGRAPH_DIRECTED, 0, 1, 1, 2, 2, 0, 2, 3, 2, 4, 0, 4, 4, 3, 5, 0, 6, 5, 1, 1, 4, 4, -1); igraph_feedback_arc_set(&g, &result, 0, IGRAPH_FAS_APPROX_EADES); igraph_vector_print(&result); igraph_delete_edges(&g, igraph_ess_vector(&result)); igraph_is_dag(&g, &dag); if (!dag) { return 3; } igraph_destroy(&g); igraph_vector_destroy(&result); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_laplacian.c0000644000076500000240000001530213612122633027340 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include igraph_bool_t check_laplacian(igraph_t* graph, igraph_matrix_t* matrix, igraph_vector_t* w) { igraph_vector_t vec, res; long int i, j; igraph_vector_init(&vec, 0); igraph_vector_init(&res, igraph_vcount(graph)); if (w) { igraph_strength(graph, &vec, igraph_vss_all(), IGRAPH_OUT, IGRAPH_NO_LOOPS, w); } else { igraph_degree(graph, &vec, igraph_vss_all(), IGRAPH_OUT, IGRAPH_NO_LOOPS); } for (i = 0; i < igraph_vcount(graph); i++) { VECTOR(vec)[i] = sqrt(VECTOR(vec)[i]); } for (i = 0; i < igraph_vcount(graph); i++) { for (j = 0; j < igraph_vcount(graph); j++) { VECTOR(res)[i] += MATRIX(*matrix, i, j) * VECTOR(vec)[j]; } } if (igraph_vector_min(&res) > 1e-7) { printf("Invalid Laplacian matrix:\n"); igraph_matrix_print(matrix); return 0; } igraph_vector_destroy(&vec); igraph_vector_destroy(&res); return 1; } int test_unnormalized_laplacian(igraph_vector_t* w, igraph_bool_t dir) { igraph_t g; igraph_matrix_t m, m2; igraph_sparsemat_t sm; igraph_vector_t vec, *weights = 0; igraph_matrix_init(&m, 1, 1); igraph_sparsemat_init(&sm, 0, 0, 0); if (w) { weights = (igraph_vector_t*)calloc(1, sizeof(igraph_vector_t)); igraph_vector_copy(weights, w); } /* No loop or multiple edges */ igraph_ring(&g, 5, dir, 0, 1); igraph_laplacian(&g, &m, &sm, 0, weights); igraph_matrix_init(&m2, 0, 0); igraph_sparsemat_as_matrix(&m2, &sm); if (!igraph_matrix_all_e_tol(&m, &m2, 0)) { return 41; } igraph_matrix_destroy(&m2); igraph_matrix_print(&m); printf("===\n"); /* Add some loop edges */ igraph_vector_init_real(&vec, 4, 1.0, 1.0, 2.0, 2.0); igraph_add_edges(&g, &vec, 0); igraph_vector_destroy(&vec); if (weights) { igraph_vector_push_back(weights, 2); igraph_vector_push_back(weights, 2); } igraph_laplacian(&g, &m, &sm, 0, weights); igraph_matrix_init(&m2, 0, 0); igraph_sparsemat_as_matrix(&m2, &sm); if (!igraph_matrix_all_e_tol(&m, &m2, 0)) { return 42; } igraph_matrix_destroy(&m2); igraph_matrix_print(&m); printf("===\n"); /* Duplicate some edges */ igraph_vector_init_real(&vec, 4, 1.0, 2.0, 3.0, 4.0); igraph_add_edges(&g, &vec, 0); igraph_vector_destroy(&vec); if (weights) { igraph_vector_push_back(weights, 3); igraph_vector_push_back(weights, 3); } igraph_laplacian(&g, &m, &sm, 0, weights); igraph_matrix_init(&m2, 0, 0); igraph_sparsemat_as_matrix(&m2, &sm); if (!igraph_matrix_all_e_tol(&m, &m2, 0)) { return 43; } igraph_matrix_destroy(&m2); igraph_matrix_print(&m); igraph_destroy(&g); igraph_matrix_destroy(&m); if (weights) { igraph_vector_destroy(weights); free(weights); } igraph_sparsemat_destroy(&sm); return 0; } int test_normalized_laplacian(igraph_vector_t *w, igraph_bool_t dir) { igraph_t g; igraph_matrix_t m, m2; igraph_sparsemat_t sm; igraph_vector_t vec, *weights = 0; igraph_bool_t ok = 1; igraph_matrix_init(&m, 1, 1); igraph_sparsemat_init(&sm, 0, 0, 0); if (w) { weights = (igraph_vector_t*)calloc(1, sizeof(igraph_vector_t)); igraph_vector_copy(weights, w); } /* Undirected graph, no loop or multiple edges */ igraph_ring(&g, 5, dir, 0, 1); igraph_laplacian(&g, &m, &sm, 1, weights); igraph_matrix_init(&m2, 0, 0); igraph_sparsemat_as_matrix(&m2, &sm); if (!igraph_matrix_all_e_tol(&m, &m2, 0)) { return 44; } igraph_matrix_destroy(&m2); ok = ok && check_laplacian(&g, &m, weights); /* Add some loop edges */ igraph_vector_init_real(&vec, 4, 1.0, 1.0, 2.0, 2.0); igraph_add_edges(&g, &vec, 0); igraph_vector_destroy(&vec); if (weights) { igraph_vector_push_back(weights, 2); igraph_vector_push_back(weights, 2); } igraph_laplacian(&g, &m, &sm, 1, weights); igraph_matrix_init(&m2, 0, 0); igraph_sparsemat_as_matrix(&m2, &sm); if (!igraph_matrix_all_e_tol(&m, &m2, 0)) { return 45; } igraph_matrix_destroy(&m2); ok = ok && check_laplacian(&g, &m, weights); /* Duplicate some edges */ igraph_vector_init_real(&vec, 4, 1.0, 2.0, 3.0, 4.0); igraph_add_edges(&g, &vec, 0); igraph_vector_destroy(&vec); if (weights) { igraph_vector_push_back(weights, 3); igraph_vector_push_back(weights, 3); } igraph_laplacian(&g, &m, &sm, 1, weights); igraph_matrix_init(&m2, 0, 0); igraph_sparsemat_as_matrix(&m2, &sm); if (!igraph_matrix_all_e_tol(&m, &m2, 0)) { return 46; } igraph_matrix_destroy(&m2); ok = ok && check_laplacian(&g, &m, weights); igraph_destroy(&g); igraph_matrix_destroy(&m); if (weights) { igraph_vector_destroy(weights); free(weights); } if (ok) { printf("OK\n"); } igraph_sparsemat_destroy(&sm); return !ok; } int main() { int res; int i; igraph_vector_t weights; igraph_vector_init_real(&weights, 5, 1.0, 2.0, 3.0, 4.0, 5.0); for (i = 0; i < 8; i++) { igraph_bool_t is_normalized = i / 4; igraph_vector_t* v = ((i & 2) / 2 ? &weights : 0); igraph_bool_t dir = (i % 2 ? IGRAPH_DIRECTED : IGRAPH_UNDIRECTED); printf("=== %sormalized, %sweighted, %sdirected\n", (is_normalized ? "N" : "Unn"), (v != 0 ? "" : "un"), (dir == IGRAPH_DIRECTED ? "" : "un") ); if (is_normalized) { res = test_normalized_laplacian(v, dir); } else { res = test_unnormalized_laplacian(v, dir); } if (res) { return i + 1; } } igraph_vector_destroy(&weights); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/cohesive_blocks.c0000644000076500000240000001307513612122633027231 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int doit(igraph_t *g) { igraph_vector_ptr_t blocks; igraph_vector_t cohesion; igraph_vector_t parent; igraph_t block_tree; long int i; igraph_vector_ptr_init(&blocks, 0); igraph_vector_init(&cohesion, 0); igraph_vector_init(&parent, 0); igraph_cohesive_blocks(g, &blocks, &cohesion, &parent, &block_tree); printf("Blocks:\n"); for (i = 0; i < igraph_vector_ptr_size(&blocks); i++) { igraph_vector_t *sg = VECTOR(blocks)[i]; printf(" "); igraph_vector_print(sg); igraph_vector_destroy(sg); igraph_free(sg); } printf("Cohesion:\n "); igraph_vector_print(&cohesion); printf("Parents:\n "); igraph_vector_print(&parent); printf("Block graph:\n"); igraph_write_graph_edgelist(&block_tree, stdout); igraph_vector_ptr_destroy(&blocks); igraph_vector_destroy(&cohesion); igraph_vector_destroy(&parent); igraph_destroy(&block_tree); return 0; } int main() { igraph_t g; int ret; /* --------------------------------------------------------*/ /* The graph from the Moody-White paper */ igraph_small(&g, 23, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 1, 2, 1, 3, 1, 4, 1, 6, 2, 3, 2, 5, 2, 6, 3, 4, 3, 5, 3, 6, 4, 5, 4, 6, 4, 20, 5, 6, 6, 7, 6, 10, 6, 13, 6, 18, 7, 8, 7, 10, 7, 13, 8, 9, 9, 11, 9, 12, 10, 11, 10, 13, 11, 15, 12, 15, 13, 14, 14, 15, 16, 17, 16, 18, 16, 19, 17, 19, 17, 20, 18, 19, 18, 21, 18, 22, 19, 20, 20, 21, 20, 22, 21, 22, -1); if ( (ret = doit(&g)) ) { return ret; } igraph_destroy(&g); printf("--\n"); /* --------------------------------------------------------*/ /* A tricky graph, where the separators themselves */ /* form a block. But recently we don't include this */ /* block in the results. */ igraph_small(&g, 8, IGRAPH_UNDIRECTED, 0, 1, 0, 4, 0, 5, 1, 2, 1, 4, 1, 5, 1, 6, 2, 3, 2, 5, 2, 6, 2, 7, 3, 6, 3, 7, 4, 5, 5, 6, 6, 7, -1); if ( (ret = doit(&g)) ) { return ret; } igraph_destroy(&g); printf("--\n"); /* --------------------------------------------------------*/ /* The science camp graph from http://intersci.ss.uci.edu/ */ /* wiki/index.php/Cohesive_blocking */ igraph_small(&g, 18, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 1, 2, 1, 3, 1, 16, 1, 17, 2, 3, 3, 17, 4, 5, 4, 6, 4, 7, 4, 8, 5, 6, 5, 7, 6, 7, 6, 8, 7, 8, 7, 16, 8, 9, 8, 10, 9, 11, 9, 12, 9, 13, 9, 14, 10, 11, 10, 12, 10, 13, 11, 14, 12, 13, 12, 14, 12, 15, 15, 16, 15, 17, 16, 17, -1); if ( (ret = doit(&g)) ) { return ret; } igraph_destroy(&g); printf("--\n"); /* --------------------------------------------------------*/ /* Zachary karate-club */ igraph_small(&g, 34, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 0, 7, 0, 8, 0, 10, 0, 11, 0, 12, 0, 13, 0, 17, 0, 19, 0, 21, 0, 31, 1, 2, 1, 3, 1, 7, 1, 13, 1, 17, 1, 19, 1, 21, 1, 30, 2, 3, 2, 7, 2, 27, 2, 28, 2, 32, 2, 9, 2, 8, 2, 13, 3, 7, 3, 12, 3, 13, 4, 6, 4, 10, 5, 6, 5, 10, 5, 16, 6, 16, 8, 30, 8, 32, 8, 33, 9, 33, 13, 33, 14, 32, 14, 33, 15, 32, 15, 33, 18, 32, 18, 33, 19, 33, 20, 32, 20, 33, 22, 32, 22, 33, 23, 25, 23, 27, 23, 32, 23, 33, 23, 29, 24, 25, 24, 27, 24, 31, 25, 31, 26, 29, 26, 33, 27, 33, 28, 31, 28, 33, 29, 32, 29, 33, 30, 32, 30, 33, 31, 32, 31, 33, 32, 33, -1); if ( (ret = doit(&g)) ) { return ret; } igraph_destroy(&g); printf("--\n"); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_qsort.out0000644000076500000240000000044213524616144027157 0ustar tamasstaff000000000000000 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_minimal_separators.c0000644000076500000240000000334513612122633031311 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int main() { igraph_t graph; igraph_vector_ptr_t separators; long int i, n; igraph_famous(&graph, "zachary"); igraph_vector_ptr_init(&separators, 0); igraph_all_minimal_st_separators(&graph, &separators); n = igraph_vector_ptr_size(&separators); for (i = 0; i < n; i++) { igraph_bool_t res; igraph_vector_t *sep = VECTOR(separators)[i]; igraph_is_separator(&graph, igraph_vss_vector(sep), &res); if (!res) { printf("Vertex set %li is not a separator!\n", i); igraph_vector_print(sep); return 1; } } igraph_destroy(&graph); for (i = 0; i < n; i++) { igraph_vector_t *v = VECTOR(separators)[i]; igraph_vector_destroy(v); igraph_Free(v); } igraph_vector_ptr_destroy(&separators); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/indheap.c0000644000076500000240000000177113612122634025500 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { /* This is not used by any functions any more, no need to test it right now */ return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_scg_semiprojectors3.c0000644000076500000240000001005713612122633031405 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { int nodes = 10; igraph_t g; igraph_matrix_t L, R; igraph_sparsemat_t Lsparse, Rsparse; igraph_matrix_t V; igraph_matrix_complex_t V2; igraph_sparsemat_t laplacian; igraph_vector_t groups; igraph_eigen_which_t which; igraph_matrix_init(&L, 0, 0); igraph_matrix_init(&R, 0, 0); igraph_matrix_init(&V, 0, 0); igraph_matrix_complex_init(&V2, 0, 0); igraph_vector_init(&groups, 0); igraph_rng_seed(igraph_rng_default(), 42); igraph_tree(&g, 10, /* children= */ 3, IGRAPH_TREE_UNDIRECTED); igraph_sparsemat_init(&laplacian, nodes, nodes, igraph_ecount(&g) * 2); igraph_rng_seed(igraph_rng_default(), 42); igraph_laplacian(&g, /*res=*/ 0, /*sparseres=*/ &laplacian, /*normalized=*/ 0, /*weights=*/ 0); which.pos = IGRAPH_EIGEN_LM; which.howmany = 1; igraph_eigen_matrix(/*matrix=*/ 0, &laplacian, /*fun=*/ 0, 10, /*extra=*/ 0, /*algorithm=*/ IGRAPH_EIGEN_LAPACK, &which, /*options=*/ 0, /*storage=*/ 0, /*values=*/ 0, &V2); igraph_matrix_complex_real(&V2, &V); #define SEMI() \ do { \ igraph_scg_semiprojectors(&groups, IGRAPH_SCG_LAPLACIAN, &L, &R, \ &Lsparse, &Rsparse, /*p=*/ 0, \ IGRAPH_SCG_NORM_ROW); \ } while(0) #define PRINTRES() \ do { \ printf("----------------------\n"); \ igraph_matrix_print(&L); \ printf("---\n"); \ igraph_matrix_print(&R); \ printf("---\n"); \ igraph_sparsemat_destroy(&Lsparse); \ igraph_sparsemat_destroy(&Rsparse); \ } while (0) /* -------------- */ igraph_scg_grouping(&V, &groups, /*intervals=*/ 3, /*intervals_vector=*/ 0, IGRAPH_SCG_LAPLACIAN, IGRAPH_SCG_OPTIMUM, /*p=*/ 0, /*maxiter=*/ 10000); SEMI(); PRINTRES(); /* -------------- */ igraph_scg_grouping(&V, &groups, /*intervals=*/ 2, /*intervals_vector=*/ 0, IGRAPH_SCG_LAPLACIAN, IGRAPH_SCG_INTERV_KM, /*p=*/ 0, /*maxiter=*/ 10000); SEMI(); PRINTRES(); /* -------------- */ igraph_scg_grouping(&V, &groups, /*intervals=*/ 2, /*intervals_vector=*/ 0, IGRAPH_SCG_LAPLACIAN, IGRAPH_SCG_INTERV, /*p=*/ 0, /*maxiter=*/ 10000); SEMI(); PRINTRES(); /* -------------- */ igraph_scg_grouping(&V, &groups, /*(ignored) intervals=*/ 0, /*intervals_vector=*/ 0, IGRAPH_SCG_LAPLACIAN, IGRAPH_SCG_EXACT, /*p=*/ 0, /*maxiter=*/ 10000); SEMI(); PRINTRES(); /* -------------- */ igraph_matrix_destroy(&L); igraph_matrix_destroy(&R); igraph_matrix_destroy(&V); igraph_matrix_complex_destroy(&V2); igraph_vector_destroy(&groups); igraph_sparsemat_destroy(&laplacian); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_biconnected_components.c0000644000076500000240000000522113612122633032135 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include void sort_and_print_vector(igraph_vector_t *v) { long int i, n = igraph_vector_size(v); igraph_vector_sort(v); for (i = 0; i < n; i++) { printf(" %li", (long int) VECTOR(*v)[i]); } printf("\n"); } void warning_handler_ignore(const char* reason, const char* file, int line, int e) { } int main() { igraph_t g; igraph_vector_ptr_t result; igraph_integer_t no; long int i; igraph_set_warning_handler(warning_handler_ignore); igraph_vector_ptr_init(&result, 0); igraph_small(&g, 7, 0, 0, 1, 1, 2, 2, 3, 3, 0, 2, 4, 4, 5, 2, 5, -1); igraph_biconnected_components(&g, &no, 0, 0, &result, 0); if (no != 2 || no != igraph_vector_ptr_size(&result)) { return 1; } for (i = 0; i < no; i++) { sort_and_print_vector((igraph_vector_t*)VECTOR(result)[i]); igraph_vector_destroy((igraph_vector_t*)VECTOR(result)[i]); free((igraph_vector_t*)VECTOR(result)[i]); } igraph_biconnected_components(&g, &no, 0, &result, 0, 0); if (no != 2 || no != igraph_vector_ptr_size(&result)) { return 2; } for (i = 0; i < no; i++) { sort_and_print_vector((igraph_vector_t*)VECTOR(result)[i]); igraph_vector_destroy((igraph_vector_t*)VECTOR(result)[i]); free((igraph_vector_t*)VECTOR(result)[i]); } igraph_biconnected_components(&g, &no, &result, 0, 0, 0); if (no != 2 || no != igraph_vector_ptr_size(&result)) { return 3; } for (i = 0; i < no; i++) { sort_and_print_vector((igraph_vector_t*)VECTOR(result)[i]); igraph_vector_destroy((igraph_vector_t*)VECTOR(result)[i]); free((igraph_vector_t*)VECTOR(result)[i]); } igraph_vector_ptr_destroy(&result); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_is_separator.c0000644000076500000240000000511113612122633030104 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #define FAIL(msg, error) do { printf(msg "\n") ; return error; } while (0) int main() { igraph_t graph; igraph_vector_t sep; igraph_bool_t result; /* Simple star graph, remove the center */ igraph_star(&graph, 10, IGRAPH_STAR_UNDIRECTED, 0); igraph_is_separator(&graph, igraph_vss_1(0), &result); if (!result) { FAIL("Center of star graph failed.", 1); } /* Same graph, but another vertex */ igraph_is_separator(&graph, igraph_vss_1(6), &result); if (result) { FAIL("Non-center of star graph failed.", 2); } /* Same graph, all vertices but the center */ igraph_is_separator(&graph, igraph_vss_seq(1, 9), &result); if (result) { FAIL("All non-central vertices of star graph failed.", 5); } igraph_destroy(&graph); /* Same graph, all vertices */ igraph_is_separator(&graph, igraph_vss_seq(0, 9), &result); if (result) { FAIL("All vertices of star graph failed.", 6); } igraph_destroy(&graph); /* Karate club */ igraph_famous(&graph, "zachary"); igraph_vector_init(&sep, 0); igraph_vector_push_back(&sep, 32); igraph_vector_push_back(&sep, 33); igraph_is_separator(&graph, igraph_vss_vector(&sep), &result); if (!result) { FAIL("Karate network (32,33) failed", 3); } igraph_vector_resize(&sep, 5); VECTOR(sep)[0] = 8; VECTOR(sep)[1] = 9; VECTOR(sep)[2] = 19; VECTOR(sep)[3] = 30; VECTOR(sep)[4] = 31; igraph_is_separator(&graph, igraph_vss_vector(&sep), &result); if (result) { FAIL("Karate network (8,9,19,30,31) failed", 4); } igraph_destroy(&graph); igraph_vector_destroy(&sep); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_i_cutheap.out0000644000076500000240000000002513524616144027745 0ustar tamasstaff000000000000009 8 7 6 5 4 3 2 1 0 python-igraph-0.8.0/vendor/source/igraph/examples/simple/spinglass.c0000644000076500000240000000744613612122634026100 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_real_t modularity, temperature; igraph_vector_t membership, csize; /* long int i; */ igraph_real_t cohesion, adhesion; igraph_integer_t inner_links; igraph_integer_t outer_links; igraph_small(&g, 5, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 0, 4, 1, 2, 1, 3, 1, 4, 2, 3, 2, 4, 3, 4, 5, 6, 5, 7, 5, 8, 5, 9, 6, 7, 6, 8, 6, 9, 7, 8, 7, 9, 8, 9, 0, 5, -1); igraph_vector_init(&membership, 0); igraph_vector_init(&csize, 0); igraph_community_spinglass(&g, 0, /* no weights */ &modularity, &temperature, &membership, &csize, 2, /* no of spins */ 0, /* parallel update */ 1.0, /* start temperature */ 0.01, /* stop temperature */ 0.99, /* cooling factor */ IGRAPH_SPINCOMM_UPDATE_CONFIG, 1.0, /* gamma */ IGRAPH_SPINCOMM_IMP_ORIG, /*gamma-=*/ 0); /* printf("Modularity: %f\n", modularity); */ /* printf("Temperature: %f\n", temperature); */ /* printf("Cluster sizes: "); */ /* for (i=0; i 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t small, big; igraph_matrix_t small_coords, big_coords, merged_coords; igraph_vector_ptr_t graph_ptr, coords_ptr; igraph_arpack_options_t arpack_opts; /* To make things reproducible */ igraph_rng_seed(igraph_rng_default(), 42); igraph_small(&big, 10, IGRAPH_UNDIRECTED, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7, 7, 8, 8, 9, 9, 0, -1); igraph_small(&small, 3, IGRAPH_UNDIRECTED, 0, 1, 1, 2, 2, 0, -1); igraph_arpack_options_init(&arpack_opts); igraph_matrix_init(&big_coords, 0, 0); igraph_layout_mds(&big, &big_coords, /*dist=*/ 0, /*dim=*/ 2, &arpack_opts); igraph_matrix_init(&small_coords, 0, 0); igraph_layout_mds(&small, &small_coords, /*dist=*/ 0, /*dim=*/ 2, &arpack_opts); igraph_vector_ptr_init(&graph_ptr, 2); igraph_vector_ptr_init(&coords_ptr, 2); igraph_matrix_init(&merged_coords, 0, 0); VECTOR(graph_ptr)[0] = &big; VECTOR(graph_ptr)[1] = &small; VECTOR(coords_ptr)[0] = &big_coords; VECTOR(coords_ptr)[1] = &small_coords; igraph_layout_merge_dla(&graph_ptr, &coords_ptr, &merged_coords); igraph_matrix_print(&merged_coords); igraph_matrix_destroy(&merged_coords); igraph_matrix_destroy(&small_coords); igraph_matrix_destroy(&big_coords); igraph_vector_ptr_destroy(&graph_ptr); igraph_vector_ptr_destroy(&coords_ptr); igraph_destroy(&small); igraph_destroy(&big); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_atlas.out0000644000076500000240000000016313524616144027113 0ustar tamasstaff000000000000000 4 1 2 1 3 1 4 2 3 2 4 3 4 0 1 0 2 0 3 0 4 0 5 0 6 1 2 1 3 1 4 1 5 1 6 2 3 2 4 2 5 2 6 3 4 3 5 3 6 4 5 4 6 5 6 python-igraph-0.8.0/vendor/source/igraph/examples/simple/triad_census.out0000644000076500000240000000011113524616144027131 0ustar tamasstaff0000000000000025 45 7 7 12 11 2 4 4 1 1 0 0 1 0 0 25 0 52 0 0 0 0 0 0 0 37 0 0 0 0 6 python-igraph-0.8.0/vendor/source/igraph/examples/simple/dominator_tree.c0000644000076500000240000001201113612122633027067 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int main() { igraph_t g, domtree; igraph_vector_t dom, leftout; igraph_vector_init(&dom, 0); igraph_small(&g, 13, IGRAPH_DIRECTED, 0, 1, 0, 7, 0, 10, 1, 2, 1, 5, 2, 3, 3, 4, 4, 3, 4, 0, 5, 3, 5, 6, 6, 3, 7, 8, 7, 10, 7, 11, 8, 9, 9, 4, 9, 8, 10, 11, 11, 12, 12, 9, -1); /* Check NULL vector arguments */ igraph_dominator_tree(&g, /*root=*/ 0, /*dom=*/ 0, /*domtree=*/ 0, /*leftout=*/ 0, /*mode=*/ IGRAPH_OUT); /* Proper calculation */ igraph_dominator_tree(&g, /*root=*/ 0, &dom, /*domtree=*/ 0, /*leftout=*/ 0, /*mode=*/ IGRAPH_OUT); igraph_vector_print(&dom); /* Tree calculation */ igraph_dominator_tree(&g, /*root=*/ 0, /*dom=*/ 0, /*domtree=*/ &domtree, /*leftout=*/ 0, /*mode=*/ IGRAPH_OUT); igraph_write_graph_edgelist(&domtree, stdout); igraph_vector_destroy(&dom); igraph_destroy(&domtree); igraph_destroy(&g); /* -------------------------------------------------------------------*/ igraph_vector_init(&dom, 0); igraph_small(&g, 13, IGRAPH_DIRECTED, 1, 0, 2, 0, 3, 0, 4, 1, 1, 2, 4, 2, 5, 2, 6, 3, 7, 3, 12, 4, 8, 5, 9, 6, 9, 7, 10, 7, 5, 8, 11, 8, 11, 9, 9, 10, 9, 11, 0, 11, 8, 12, -1); /* Check NULL vector arguments */ igraph_dominator_tree(&g, /*root=*/ 0, /*dom=*/ 0, /*domtree=*/ 0, /*leftout=*/ 0, /*mode=*/ IGRAPH_IN); /* Proper calculation */ igraph_dominator_tree(&g, /*root=*/ 0, &dom, /*domtree=*/ 0, /*leftout=*/ 0, /*mode=*/ IGRAPH_IN); igraph_vector_print(&dom); /* Tree calculation */ igraph_dominator_tree(&g, /*root=*/ 0, /*dom=*/ 0, /*domtree=*/ &domtree, /*leftout=*/ 0, /*mode=*/ IGRAPH_IN); igraph_write_graph_edgelist(&domtree, stdout); igraph_vector_destroy(&dom); igraph_destroy(&domtree); igraph_destroy(&g); /* -------------------------------------------------------------------*/ igraph_vector_init(&dom, 0); igraph_vector_init(&leftout, 0); /* Check a graph with more components */ igraph_small(&g, 20, IGRAPH_DIRECTED, 0, 1, 0, 2, 0, 3, 1, 4, 2, 1, 2, 4, 2, 8, 3, 9, 3, 10, 4, 15, 8, 11, 9, 12, 10, 12, 10, 13, 11, 8, 11, 14, 12, 14, 13, 12, 14, 12, 14, 0, 15, 11, -1); igraph_dominator_tree(&g, /*root=*/ 0, &dom, &domtree, &leftout, /*mode=*/ IGRAPH_OUT); igraph_vector_print(&dom); igraph_vector_print(&leftout); igraph_write_graph_edgelist(&domtree, stdout); igraph_vector_destroy(&dom); igraph_vector_destroy(&leftout); igraph_destroy(&domtree); igraph_destroy(&g); /* -------------------------------------------------------------------*/ igraph_vector_init(&dom, 0); igraph_vector_init(&leftout, 0); igraph_small(&g, 10, IGRAPH_DIRECTED, 0, 9, 1, 0, 1, 2, 2, 3, 2, 7, 3, 1, 4, 1, 4, 3, 5, 2, 5, 3, 5, 4, 5, 8, 6, 5, 6, 9, 8, 7, -1); igraph_dominator_tree(&g, /*root=*/ 9, &dom, &domtree, &leftout, /*mode=*/ IGRAPH_IN); igraph_vector_print(&dom); igraph_vector_print(&leftout); igraph_write_graph_edgelist(&domtree, stdout); igraph_vector_destroy(&dom); igraph_vector_destroy(&leftout); igraph_destroy(&domtree); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_eigen_matrix3.c0000644000076500000240000000607613612122633030162 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #define DUMP() do { \ igraph_vector_complex_print(&values); \ igraph_vector_complex_print(&values2); \ } while(0) int main() { const int nodes = 10, skip = 3; igraph_matrix_t mat2; igraph_vector_complex_t values, values2; igraph_matrix_complex_t vectors, vectors2; igraph_eigen_which_t which; int i; igraph_rng_seed(igraph_rng_default(), 42); igraph_matrix_init(&mat2, nodes, nodes); for (i = 0; i < nodes; i++) { int j; for (j = 0; j < nodes; j++) { MATRIX(mat2, i, j) = igraph_rng_get_integer(igraph_rng_default(), 1, 10); } } which.pos = IGRAPH_EIGEN_SELECT; which.il = skip; which.iu = nodes - skip; igraph_vector_complex_init(&values, 0); igraph_matrix_complex_init(&vectors, 0, 0); igraph_eigen_matrix(&mat2, /*sparsemat=*/ 0, /*fun=*/ 0, nodes, /*extra=*/ 0, IGRAPH_EIGEN_LAPACK, &which, /*options=*/ 0, /*storage=*/ 0, &values, &vectors); which.pos = IGRAPH_EIGEN_ALL; igraph_vector_complex_init(&values2, 0); igraph_matrix_complex_init(&vectors2, 0, 0); igraph_eigen_matrix(&mat2, /*sparsemat=*/ 0, /*fun=*/ 0, nodes, /*extra=*/ 0, IGRAPH_EIGEN_LAPACK, &which, /*options=*/ 0, /*storage=*/ 0, &values2, &vectors2); for (i = 0; i < nodes - skip * 2 + 1; i++) { int j; igraph_real_t d = igraph_complex_abs(igraph_complex_sub(VECTOR(values)[i], VECTOR(values2)[i + skip - 1])); if (d > 1e-15) { DUMP(); return 2; } for (j = 0; j < nodes; j++) { igraph_real_t d = igraph_complex_abs(igraph_complex_sub(MATRIX(vectors, j, i), MATRIX(vectors2, j, i + skip - 1))); if (d > 1e-15) { DUMP(); return 3; } } } igraph_vector_complex_destroy(&values); igraph_matrix_complex_destroy(&vectors); igraph_vector_complex_destroy(&values2); igraph_matrix_complex_destroy(&vectors2); igraph_matrix_destroy(&mat2); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_layout_mds.c0000644000076500000240000000563713612122633027606 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include #define sqr(x) ((x)*(x)) int main() { igraph_t g; igraph_matrix_t coords, dist_mat; igraph_arpack_options_t options; int i, j; srand(time(0)); igraph_arpack_options_init(&options); igraph_tree(&g, 10, 2, IGRAPH_TREE_UNDIRECTED); igraph_matrix_init(&coords, 0, 0); igraph_layout_mds(&g, &coords, 0, 2, &options); if (MATRIX(coords, 0, 0) > 0) { for (i = 0; i < igraph_matrix_nrow(&coords); i++) { MATRIX(coords, i, 0) *= -1; } } if (MATRIX(coords, 0, 1) < 0) { for (i = 0; i < igraph_matrix_nrow(&coords); i++) { MATRIX(coords, i, 1) *= -1; } } igraph_matrix_print(&coords); igraph_matrix_destroy(&coords); igraph_destroy(&g); igraph_full(&g, 8, IGRAPH_UNDIRECTED, 0); igraph_matrix_init(&coords, 8, 2); igraph_matrix_init(&dist_mat, 8, 8); for (i = 0; i < 8; i++) for (j = 0; j < 2; j++) { MATRIX(coords, i, j) = rand() % 1000; } for (i = 0; i < 8; i++) for (j = i + 1; j < 8; j++) { double dist_sq = 0.0; dist_sq += sqr(MATRIX(coords, i, 0) - MATRIX(coords, j, 0)); dist_sq += sqr(MATRIX(coords, i, 1) - MATRIX(coords, j, 1)); MATRIX(dist_mat, i, j) = sqrt(dist_sq); MATRIX(dist_mat, j, i) = sqrt(dist_sq); } igraph_layout_mds(&g, &coords, &dist_mat, 2, &options); for (i = 0; i < 8; i++) for (j = i + 1; j < 8; j++) { double dist_sq = 0.0; dist_sq += sqr(MATRIX(coords, i, 0) - MATRIX(coords, j, 0)); dist_sq += sqr(MATRIX(coords, i, 1) - MATRIX(coords, j, 1)); if (fabs(sqrt(dist_sq) - MATRIX(dist_mat, i, j)) > 1e-2) { printf("dist(%d,%d) should be %.4f, but it is %.4f\n", i, j, MATRIX(dist_mat, i, j), sqrt(dist_sq)); return 1; } } igraph_matrix_destroy(&dist_mat); igraph_matrix_destroy(&coords); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_hashtable.out0000644000076500000240000000024213524616144027740 0ustar tamasstaff00000000000000color: grey size: 4 shape: diamond color: green size: shape: color size shape color: grey size: 4 shape: diamond color: green size: shape: color size shape python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_scg_semiprojectors.out0000644000076500000240000000205613524616144031716 0ustar tamasstaff00000000000000---------------------- 1 0 0 0 0 0 0 0 0 0 0 0.707107 0.707107 0 0 0 0 0 0 0 0 0 0 0.377964 0.377964 0.377964 0.377964 0.377964 0.377964 0.377964 --- 1 0 0 0 0 0 0 0 0 0 0 0.707107 0.707107 0 0 0 0 0 0 0 0 0 0 0.377964 0.377964 0.377964 0.377964 0.377964 0.377964 0.377964 --- ---------------------- 0.57735 0.57735 0.57735 0 0 0 0 0 0 0 0 0 0 0.377964 0.377964 0.377964 0.377964 0.377964 0.377964 0.377964 --- 0.57735 0.57735 0.57735 0 0 0 0 0 0 0 0 0 0 0.377964 0.377964 0.377964 0.377964 0.377964 0.377964 0.377964 --- ---------------------- 0.57735 0.57735 0.57735 0 0 0 0 0 0 0 0 0 0 0.377964 0.377964 0.377964 0.377964 0.377964 0.377964 0.377964 --- 0.57735 0.57735 0.57735 0 0 0 0 0 0 0 0 0 0 0.377964 0.377964 0.377964 0.377964 0.377964 0.377964 0.377964 --- ---------------------- 1 0 0 0 0 0 0 0 0 0 0 0.707107 0.707107 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0.408248 0.408248 0.408248 0.408248 0.408248 0.408248 --- 1 0 0 0 0 0 0 0 0 0 0 0.707107 0.707107 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0.408248 0.408248 0.408248 0.408248 0.408248 0.408248 --- python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_empty.c0000644000076500000240000000374113612122633026556 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; int ret; /* empty directed graph, zero vertices */ igraph_empty(&g, 0, 1); if (igraph_vcount(&g) != 0) { return 1; } if (igraph_ecount(&g) != 0) { return 2; } igraph_destroy(&g); /* empty undirected graph, zero vertices */ igraph_empty(&g, 0, 0); if (igraph_vcount(&g) != 0) { return 3; } if (igraph_ecount(&g) != 0) { return 4; } igraph_destroy(&g); /* empty directed graph, 20 vertices */ igraph_empty(&g, 20, 1); if (igraph_vcount(&g) != 20) { return 5; } if (igraph_ecount(&g) != 0) { return 6; } igraph_destroy(&g); /* empty undirected graph, 30 vertices */ igraph_empty(&g, 30, 0); if (igraph_vcount(&g) != 30) { return 7; } if (igraph_ecount(&g) != 0) { return 8; } igraph_destroy(&g); /* error: negative number of vertices */ igraph_set_error_handler(igraph_error_handler_ignore); ret = igraph_empty(&g, -1, 0); if (ret != IGRAPH_EINVAL) { return 9; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_get_eids.out0000644000076500000240000000002113524616144027563 0ustar tamasstaff00000000000000 0 1 0 1 2 1 2 python-igraph-0.8.0/vendor/source/igraph/examples/simple/cattributes3.c0000644000076500000240000001534513612122633026505 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int mf(const igraph_vector_t *input, igraph_real_t *output) { *output = 0.0; return 0; } int main() { igraph_t g, g2; igraph_vector_t weight; igraph_attribute_combination_t comb; igraph_i_set_attribute_table(&igraph_cattribute_table); igraph_small(&g, 4, IGRAPH_DIRECTED, 0, 1, 0, 1, 0, 1, 1, 2, 2, 3, -1); igraph_vector_init_seq(&weight, 1, igraph_ecount(&g)); SETEANV(&g, "weight", &weight); igraph_vector_destroy(&weight); /* ****************************************************** */ igraph_copy(&g2, &g); igraph_attribute_combination(&comb, "weight", IGRAPH_ATTRIBUTE_COMBINE_SUM, "", IGRAPH_ATTRIBUTE_COMBINE_IGNORE, IGRAPH_NO_MORE_ATTRIBUTES); igraph_simplify(&g2, /*multiple=*/ 1, /*loops=*/ 1, &comb); igraph_attribute_combination_destroy(&comb); igraph_write_graph_graphml(&g2, stdout, /*prefixattr=*/ 1); igraph_destroy(&g2); /* ****************************************************** */ /* ****************************************************** */ igraph_copy(&g2, &g); igraph_attribute_combination(&comb, "weight", IGRAPH_ATTRIBUTE_COMBINE_PROD, "", IGRAPH_ATTRIBUTE_COMBINE_IGNORE, IGRAPH_NO_MORE_ATTRIBUTES); igraph_simplify(&g2, /*multiple=*/ 1, /*loops=*/ 1, &comb); igraph_attribute_combination_destroy(&comb); igraph_write_graph_graphml(&g2, stdout, /*prefixattr=*/ 1); igraph_destroy(&g2); /* ****************************************************** */ /* ****************************************************** */ igraph_copy(&g2, &g); igraph_attribute_combination(&comb, "weight", IGRAPH_ATTRIBUTE_COMBINE_MIN, "", IGRAPH_ATTRIBUTE_COMBINE_IGNORE, IGRAPH_NO_MORE_ATTRIBUTES); igraph_simplify(&g2, /*multiple=*/ 1, /*loops=*/ 1, &comb); igraph_attribute_combination_destroy(&comb); igraph_write_graph_graphml(&g2, stdout, /*prefixattr=*/ 1); igraph_destroy(&g2); /* ****************************************************** */ /* ****************************************************** */ igraph_copy(&g2, &g); igraph_attribute_combination(&comb, "weight", IGRAPH_ATTRIBUTE_COMBINE_MAX, "", IGRAPH_ATTRIBUTE_COMBINE_IGNORE, IGRAPH_NO_MORE_ATTRIBUTES); igraph_simplify(&g2, /*multiple=*/ 1, /*loops=*/ 1, &comb); igraph_attribute_combination_destroy(&comb); igraph_write_graph_graphml(&g2, stdout, /*prefixattr=*/ 1); igraph_destroy(&g2); /* ****************************************************** */ /* ****************************************************** */ igraph_copy(&g2, &g); igraph_attribute_combination(&comb, "weight", IGRAPH_ATTRIBUTE_COMBINE_FIRST, "", IGRAPH_ATTRIBUTE_COMBINE_IGNORE, IGRAPH_NO_MORE_ATTRIBUTES); igraph_simplify(&g2, /*multiple=*/ 1, /*loops=*/ 1, &comb); igraph_attribute_combination_destroy(&comb); igraph_write_graph_graphml(&g2, stdout, /*prefixattr=*/ 1); igraph_destroy(&g2); /* ****************************************************** */ /* ****************************************************** */ igraph_copy(&g2, &g); igraph_attribute_combination(&comb, "weight", IGRAPH_ATTRIBUTE_COMBINE_LAST, "", IGRAPH_ATTRIBUTE_COMBINE_IGNORE, IGRAPH_NO_MORE_ATTRIBUTES); igraph_simplify(&g2, /*multiple=*/ 1, /*loops=*/ 1, &comb); igraph_attribute_combination_destroy(&comb); igraph_write_graph_graphml(&g2, stdout, /*prefixattr=*/ 1); igraph_destroy(&g2); /* ****************************************************** */ /* ****************************************************** */ igraph_copy(&g2, &g); igraph_attribute_combination(&comb, "weight", IGRAPH_ATTRIBUTE_COMBINE_MEAN, "", IGRAPH_ATTRIBUTE_COMBINE_IGNORE, IGRAPH_NO_MORE_ATTRIBUTES); igraph_simplify(&g2, /*multiple=*/ 1, /*loops=*/ 1, &comb); igraph_attribute_combination_destroy(&comb); igraph_write_graph_graphml(&g2, stdout, /*prefixattr=*/ 1); igraph_destroy(&g2); /* ****************************************************** */ /* ****************************************************** */ igraph_copy(&g2, &g); igraph_attribute_combination(&comb, "weight", IGRAPH_ATTRIBUTE_COMBINE_FUNCTION, mf, "", IGRAPH_ATTRIBUTE_COMBINE_IGNORE, IGRAPH_NO_MORE_ATTRIBUTES); igraph_simplify(&g2, /*multiple=*/ 1, /*loops=*/ 1, &comb); igraph_attribute_combination_destroy(&comb); igraph_write_graph_graphml(&g2, stdout, /*prefixattr=*/ 1); igraph_destroy(&g2); /* ****************************************************** */ /* ****************************************************** */ igraph_copy(&g2, &g); igraph_attribute_combination(&comb, "", IGRAPH_ATTRIBUTE_COMBINE_MEAN, IGRAPH_NO_MORE_ATTRIBUTES); igraph_simplify(&g2, /*multiple=*/ 1, /*loops=*/ 1, &comb); igraph_attribute_combination_destroy(&comb); igraph_write_graph_graphml(&g2, stdout, /*prefixattr=*/ 1); igraph_destroy(&g2); /* ****************************************************** */ igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_transitivity.c0000644000076500000240000000602513612122634030170 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_real_t res; /* Trivial cases */ igraph_ring(&g, 100, IGRAPH_UNDIRECTED, 0, 0); igraph_transitivity_undirected(&g, &res, IGRAPH_TRANSITIVITY_NAN); igraph_destroy(&g); if (res != 0) { return 1; } igraph_full(&g, 20, IGRAPH_UNDIRECTED, IGRAPH_NO_LOOPS); igraph_transitivity_undirected(&g, &res, IGRAPH_TRANSITIVITY_NAN); igraph_destroy(&g); if (res != 1) { return 2; } /* Degenerate cases */ igraph_small(&g, 0, IGRAPH_UNDIRECTED, 0, 1, 2, 3, 4, 5, -1); igraph_transitivity_undirected(&g, &res, IGRAPH_TRANSITIVITY_NAN); /* res should be NaN here, any comparison must return false */ if (res == 0 || res > 0 || res < 0) { return 4; } igraph_transitivity_undirected(&g, &res, IGRAPH_TRANSITIVITY_ZERO); /* res should be zero here */ if (res) { return 5; } igraph_destroy(&g); /* Zachary Karate club */ igraph_small(&g, 0, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 0, 7, 0, 8, 0, 10, 0, 11, 0, 12, 0, 13, 0, 17, 0, 19, 0, 21, 0, 31, 1, 2, 1, 3, 1, 7, 1, 13, 1, 17, 1, 19, 1, 21, 1, 30, 2, 3, 2, 7, 2, 8, 2, 9, 2, 13, 2, 27, 2, 28, 2, 32, 3, 7, 3, 12, 3, 13, 4, 6, 4, 10, 5, 6, 5, 10, 5, 16, 6, 16, 8, 30, 8, 32, 8, 33, 9, 33, 13, 33, 14, 32, 14, 33, 15, 32, 15, 33, 18, 32, 18, 33, 19, 33, 20, 32, 20, 33, 22, 32, 22, 33, 23, 25, 23, 27, 23, 29, 23, 32, 23, 33, 24, 25, 24, 27, 24, 31, 25, 31, 26, 29, 26, 33, 27, 33, 28, 31, 28, 33, 29, 32, 29, 33, 30, 32, 30, 33, 31, 32, 31, 33, 32, 33, -1); igraph_transitivity_undirected(&g, &res, IGRAPH_TRANSITIVITY_NAN); igraph_destroy(&g); if (res != 0.2556818181818181767717) { fprintf(stderr, "%f != %f\n", res, 0.2556818181818181767717); return 3; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_maximal_cliques4.out0000644000076500000240000000135013524616144031247 0ustar tamasstaff000000000000000 10 11 13 24 34 42 79 97 0 11 13 24 34 42 58 64 97 2 5 7 34 42 64 67 78 92 4 24 30 31 47 52 60 87 95 4 24 30 47 52 60 84 87 95 6 11 13 26 35 38 54 62 79 6 11 13 60 66 73 81 82 84 11 13 16 34 45 58 64 67 82 13 29 33 49 50 62 63 66 96 13 29 33 50 62 63 66 86 96 24 30 31 47 52 60 69 87 95 24 30 31 52 60 69 79 87 95 24 30 31 52 60 69 79 88 95 24 31 32 52 60 69 79 88 95 --- 0 10 11 13 24 34 42 79 97 0 11 13 24 34 42 58 64 97 2 5 7 34 42 64 67 78 92 4 24 30 31 47 52 60 87 95 4 24 30 47 52 60 84 87 95 6 11 13 26 35 38 54 62 79 6 11 13 60 66 73 81 82 84 11 13 16 34 45 58 64 67 82 13 29 33 49 50 62 63 66 96 13 29 33 50 62 63 66 86 96 + 24 30 31 47 52 60 69 87 95 24 30 31 52 60 69 79 87 95 24 30 31 52 60 69 79 88 95 24 31 32 52 60 69 79 88 95 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_scg_grouping.c0000644000076500000240000000503713612122633030106 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #define SIZE (1000) int main() { igraph_matrix_t M, M2; igraph_vector_t lambda; igraph_matrix_t V; igraph_vector_t groups; igraph_vector_t ivec; int i, j; int n; igraph_rng_seed(igraph_rng_default(), 42); /* Symmetric matrix, exponentially distributed elements */ igraph_matrix_init(&M, SIZE, SIZE); n = igraph_matrix_nrow(&M); for (i = 0; i < n; i++) { for (j = 0; j < n; j++) { MATRIX(M, i, j) = igraph_rng_get_exp(igraph_rng_default(), 1); } } igraph_matrix_init(&M2, n, n); igraph_matrix_update(&M2, &M); igraph_matrix_transpose(&M2); igraph_matrix_add(&M, &M2); igraph_matrix_scale(&M, 0.5); igraph_matrix_destroy(&M2); /* Get first (most positive) two eigenvectors */ igraph_vector_init(&lambda, 0); igraph_matrix_init(&V, 0, 0); igraph_lapack_dsyevr(&M, IGRAPH_LAPACK_DSYEV_SELECT, /*vl=*/ 0, /*vu=*/ 0, /*vestimate=*/ 0, /*il=*/ n - 1, /*iu=*/ n, /*abstol=*/ 0.0, /*values=*/ &lambda, /*vectors=*/ &V, /*support=*/ 0); /* Grouping */ igraph_vector_init(&groups, 0); igraph_vector_init(&ivec, 2); VECTOR(ivec)[0] = 2; VECTOR(ivec)[1] = 3; igraph_scg_grouping(&V, &groups, /*invervals=*/ 0, /*intervals_vector=*/ &ivec, IGRAPH_SCG_SYMMETRIC, IGRAPH_SCG_OPTIMUM, /*p=*/ 0, /*maxiter=*/ 100); igraph_vector_print(&groups); igraph_vector_destroy(&ivec); igraph_vector_destroy(&groups); igraph_vector_destroy(&lambda); igraph_matrix_destroy(&V); igraph_matrix_destroy(&M); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/dqueue.out0000644000076500000240000000001113524616144025735 0ustar tamasstaff000000000000003 4 5 6 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_topological_sorting.out0000644000076500000240000000014313524616144032066 0ustar tamasstaff00000000000000 0 1 2 3 4 5 7 6 5 6 7 4 3 2 0 1 Warning: graph contains a cycle, partial result is returned 1 2 python-igraph-0.8.0/vendor/source/igraph/examples/simple/vector3.c0000644000076500000240000000245113612122634025451 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2012 Gabor Csardi 334 Harvard st, Cambridge MA, USA 02139 This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_vector_t v; igraph_vector_init_seq(&v, 1, 1000); if (igraph_vector_capacity(&v) != 1000) { return 1; } igraph_vector_push_back(&v, 1001); if (igraph_vector_capacity(&v) != 2000) { return 2; } igraph_vector_resize_min(&v); if (igraph_vector_capacity(&v) != igraph_vector_size(&v)) { return 3; } igraph_vector_destroy(&v); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/bug-1033045.out0000644000076500000240000000006213524616144026045 0ustar tamasstaff000000000000001 2 0 3 4 0 3 5 4 5 1 3 6 2 3 6 2 3 4 1 3 5 0 3 6 python-igraph-0.8.0/vendor/source/igraph/examples/simple/graphml.out0000644000076500000240000000122313524616144026105 0ustar tamasstaff00000000000000Warning: unknown attribute key 'd3' in a tag, ignoring attribute The directed graph: Vertices: 6 Edges: 7 Directed: 0 0 1 0 2 1 3 2 3 2 4 3 5 4 5 Warning: unknown attribute key 'd3' in a tag, ignoring attribute The undirected graph: Vertices: 6 Edges: 7 Directed: 0 0 1 0 2 1 3 2 3 2 4 3 5 4 5 The directed graph: Vertices: 3 Edges: 2 Directed: 1 0 1 0 2 Vertex attribute 'type': false true true Vertex attribute 'gender': male female male Vertex attribute 'age': 30 20 20 Vertex attribute 'retired': false false false The undirected graph: Vertices: 3 Edges: 2 Directed: 0 0 1 1 2 The undirected graph: Vertices: 3 Edges: 2 Directed: 0 0 1 1 2 python-igraph-0.8.0/vendor/source/igraph/examples/simple/pajek.c0000644000076500000240000000276713614300625025170 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; FILE *ifile; ifile = fopen("pajek5.net", "r"); if (!ifile) { return 1; } igraph_read_graph_pajek(&g, ifile); fclose(ifile); if (igraph_vcount(&g) != 10 || igraph_ecount(&g) != 9 || igraph_is_directed(&g)) { return 2; } igraph_destroy(&g); ifile = fopen("pajek6.net", "r"); if (!ifile) { return 3; } igraph_read_graph_pajek(&g, ifile); fclose(ifile); if (igraph_vcount(&g) != 10 || igraph_ecount(&g) != 9 || !igraph_is_directed(&g)) { return 4; } igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_community_leading_eigenvector.out0000644000076500000240000000023113524616144034104 0ustar tamasstaff000000000000000 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 1 0 0 1 0 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 3 0 2 5 4 0 2 2 2 0 0 0 2 1 1 0 0 2 2 1 1 0 2 1 2 1 2 1 3 3 3 1 3 3 1 1 3 1 1 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_disjoint_union.c0000644000076500000240000000544013612122633030451 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include void print_vector(igraph_vector_t *v) { long int i, l = igraph_vector_size(v); for (i = 0; i < l; i++) { printf(" %li", (long int) VECTOR(*v)[i]); } printf("\n"); } int main() { igraph_t left, right, uni; igraph_vector_t v; igraph_vector_ptr_t glist; long int i; igraph_vector_init_int_end(&v, -1, 0, 1, 1, 2, 2, 2, 2, 3, -1); igraph_create(&left, &v, 0, IGRAPH_DIRECTED); igraph_vector_destroy(&v); igraph_vector_init_int_end(&v, -1, 0, 1, 1, 2, 2, 2, 2, 4, -1); igraph_create(&right, &v, 0, IGRAPH_DIRECTED); igraph_vector_destroy(&v); igraph_disjoint_union(&uni, &left, &right); igraph_vector_init(&v, 0); igraph_get_edgelist(&uni, &v, 0); igraph_vector_sort(&v); print_vector(&v); igraph_vector_destroy(&v); igraph_destroy(&left); igraph_destroy(&right); igraph_destroy(&uni); /* Empty graph list */ igraph_vector_ptr_init(&glist, 0); igraph_disjoint_union_many(&uni, &glist); if (!igraph_is_directed(&uni) || igraph_vcount(&uni) != 0) { return 1; } igraph_vector_ptr_destroy(&glist); igraph_destroy(&uni); /* Non-empty graph list */ igraph_vector_ptr_init(&glist, 10); for (i = 0; i < igraph_vector_ptr_size(&glist); i++) { VECTOR(glist)[i] = calloc(1, sizeof(igraph_t)); igraph_vector_init_int_end(&v, -1, 0, 1, 1, 0, -1); igraph_create(VECTOR(glist)[i], &v, 0, IGRAPH_DIRECTED); igraph_vector_destroy(&v); } igraph_disjoint_union_many(&uni, &glist); igraph_vector_init(&v, 0); igraph_get_edgelist(&uni, &v, 0); igraph_vector_sort(&v); print_vector(&v); igraph_vector_destroy(&v); for (i = 0; i < igraph_vector_ptr_size(&glist); i++) { igraph_destroy(VECTOR(glist)[i]); free(VECTOR(glist)[i]); } igraph_vector_ptr_destroy(&glist); igraph_destroy(&uni); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_get_all_shortest_paths_dijkstra.c0000644000076500000240000001575313614300625034063 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include /* Compares two paths based on their last elements. If they are equal, proceeds * with the ones preceding these elements, until we find a difference. If one * of the vectors is a suffix of the other, the shorter vector gets ordered * first. */ int vector_tail_cmp(const void* path1, const void* path2) { const igraph_vector_t* vec1 = *(const igraph_vector_t**)path1; const igraph_vector_t* vec2 = *(const igraph_vector_t**)path2; size_t length1 = igraph_vector_size(vec1); size_t length2 = igraph_vector_size(vec2); int diff; while (length1 > 0 && length2 > 0) { length1--; length2--; diff = VECTOR(*vec1)[length1] - VECTOR(*vec2)[length2]; if (diff != 0) { return diff; } } if (length1 == 0 && length2 == 0) { return 0; } else if (length1 == 0) { return -1; } else { return 1; } } void check_nrgeo(igraph_t *graph, igraph_vs_t vs, igraph_vector_ptr_t* paths, igraph_vector_t* nrgeo) { long int i, n; igraph_vector_t nrgeo2, *path; igraph_vit_t vit; n = igraph_vcount(graph); igraph_vector_init(&nrgeo2, n); if (igraph_vector_size(nrgeo) != n) { printf("nrgeo vector length must be %ld, was %ld", n, igraph_vector_size(nrgeo)); return; } n = igraph_vector_ptr_size(paths); for (i = 0; i < n; i++) { path = VECTOR(*paths)[i]; if (path == 0) { printf("Null path found in result vector at index %ld\n", i); return; } if (igraph_vector_size(path) == 0) { printf("Empty path found in result vector at index %ld\n", i); return; } VECTOR(nrgeo2)[(long int)igraph_vector_tail(path)] += 1; } igraph_vit_create(graph, vs, &vit); for (IGRAPH_VIT_RESET(vit); !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit)) { long int node = IGRAPH_VIT_GET(vit); if (VECTOR(*nrgeo)[node] - VECTOR(nrgeo2)[node]) { printf("nrgeo[%ld] invalid, observed = %ld, expected = %ld\n", node, (long int)VECTOR(*nrgeo)[node], (long int)VECTOR(nrgeo2)[node]); } } igraph_vit_destroy(&vit); igraph_vector_destroy(&nrgeo2); } int main() { igraph_t g; igraph_vector_ptr_t res; long int i; igraph_real_t weights[] = { 1, 2, 3, 4, 5, 1, 1, 1, 1, 1 }; igraph_real_t weights2[] = { 0, 2, 1, 0, 5, 2, 1, 1, 0, 2, 2, 8, 1, 1, 3, 1, 1, 4, 2, 1 }; igraph_real_t dim[] = { 4, 4 }; igraph_vector_t weights_vec, dim_vec, nrgeo; igraph_vs_t vs; igraph_vector_init(&nrgeo, 0); /* Simple ring graph without weights */ igraph_ring(&g, 10, IGRAPH_UNDIRECTED, 0, 1); igraph_vector_ptr_init(&res, 5); igraph_vs_vector_small(&vs, 1, 3, 4, 5, 2, 1, -1); igraph_get_all_shortest_paths_dijkstra(&g, /*res=*/ &res, /*nrgeo=*/ &nrgeo, /*from=*/ 0, /*to=*/ vs, /*weights=*/ 0, /*mode=*/ IGRAPH_OUT); check_nrgeo(&g, vs, &res, &nrgeo); for (i = 0; i < igraph_vector_ptr_size(&res); i++) { igraph_vector_print(VECTOR(res)[i]); igraph_vector_destroy(VECTOR(res)[i]); free(VECTOR(res)[i]); VECTOR(res)[i] = 0; } /* Same ring, but with weights */ igraph_vector_view(&weights_vec, weights, sizeof(weights) / sizeof(igraph_real_t)); igraph_get_all_shortest_paths_dijkstra(&g, /*res=*/ &res, /*nrgeo=*/ &nrgeo, /*from=*/ 0, /*to=*/ vs, /*weights=*/ &weights_vec, /*mode=*/ IGRAPH_OUT); check_nrgeo(&g, vs, &res, &nrgeo); for (i = 0; i < igraph_vector_ptr_size(&res); i++) { igraph_vector_print(VECTOR(res)[i]); igraph_vector_destroy(VECTOR(res)[i]); free(VECTOR(res)[i]); VECTOR(res)[i] = 0; } igraph_destroy(&g); /* More complicated example */ igraph_small(&g, 10, IGRAPH_DIRECTED, 0, 1, 0, 2, 0, 3, 1, 2, 1, 4, 1, 5, 2, 3, 2, 6, 3, 2, 3, 6, 4, 5, 4, 7, 5, 6, 5, 8, 5, 9, 7, 5, 7, 8, 8, 9, 5, 2, 2, 1, -1); igraph_vector_view(&weights_vec, weights2, sizeof(weights2) / sizeof(igraph_real_t)); igraph_get_all_shortest_paths_dijkstra(&g, /*res=*/ &res, /*nrgeo=*/ &nrgeo, /*from=*/ 0, /*to=*/ vs, /*weights=*/ &weights_vec, /*mode=*/ IGRAPH_OUT); check_nrgeo(&g, vs, &res, &nrgeo); /* Sort the paths in a deterministic manner to avoid problems with * different qsort() implementations on different platforms */ igraph_vector_ptr_sort(&res, vector_tail_cmp); for (i = 0; i < igraph_vector_ptr_size(&res); i++) { igraph_vector_print(VECTOR(res)[i]); igraph_vector_destroy(VECTOR(res)[i]); free(VECTOR(res)[i]); VECTOR(res)[i] = 0; } igraph_vs_destroy(&vs); igraph_destroy(&g); /* Regular lattice with some heavyweight edges */ igraph_vector_view(&dim_vec, dim, sizeof(dim) / sizeof(igraph_real_t)); igraph_lattice(&g, &dim_vec, 1, 0, 0, 0); igraph_vs_vector_small(&vs, 3, 12, 15, -1); igraph_vector_init(&weights_vec, 24); igraph_vector_fill(&weights_vec, 1); VECTOR(weights_vec)[2] = 100; VECTOR(weights_vec)[8] = 100; /* 1-->2, 4-->8 */ igraph_get_all_shortest_paths_dijkstra(&g, /*res=*/ 0, /*nrgeo=*/ &nrgeo, /*from=*/ 0, /*to=*/ vs, /*weights=*/ &weights_vec, /*mode=*/ IGRAPH_OUT); igraph_vector_destroy(&weights_vec); igraph_vs_destroy(&vs); igraph_destroy(&g); printf("%ld ", (long int)VECTOR(nrgeo)[3]); printf("%ld ", (long int)VECTOR(nrgeo)[12]); printf("%ld\n", (long int)VECTOR(nrgeo)[15]); igraph_vector_ptr_destroy(&res); igraph_vector_destroy(&nrgeo); if (!IGRAPH_FINALLY_STACK_EMPTY) { return 1; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/biguint_betweenness.c0000644000076500000240000001555113612122633030133 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int check(const igraph_vector_t *v1, const igraph_vector_t *v2, int code) { igraph_vector_t v; long int i, n = igraph_vector_size(v1); igraph_real_t m; igraph_vector_copy(&v, v1); igraph_vector_sub(&v, v2); for (i = 0; i < n; i++) { VECTOR(v)[i] = fabs(VECTOR(v)[i]); } if ( (m = igraph_vector_max(&v)) > 0.01) { printf("Difference: %g\n", m); exit(code); } igraph_vector_destroy(&v); return 0; } int main() { igraph_t g; igraph_vector_t bet, bet2, weights, edges; igraph_vector_t bbet, bbet2; igraph_real_t nontriv[] = { 0, 19, 0, 16, 0, 20, 1, 19, 2, 5, 3, 7, 3, 8, 4, 15, 4, 11, 5, 8, 5, 19, 6, 7, 6, 10, 6, 8, 6, 9, 7, 20, 9, 10, 9, 20, 10, 19, 11, 12, 11, 20, 12, 15, 13, 15, 14, 18, 14, 16, 14, 17, 15, 16, 17, 18 }; igraph_real_t nontriv_weights[] = { 0.5249, 1, 0.1934, 0.6274, 0.5249, 0.0029, 0.3831, 0.05, 0.6274, 0.3831, 0.5249, 0.0587, 0.0579, 0.0562, 0.0562, 0.1934, 0.6274, 0.6274, 0.6274, 0.0418, 0.6274, 0.3511, 0.3511, 0.1486, 1, 1, 0.0711, 0.2409 }; igraph_real_t nontriv_res[] = { 20, 0, 0, 0, 0, 19, 80, 85, 32, 0, 10, 75, 70, 0, 36, 81, 60, 0, 19, 19, 86 }; /*******************************************************/ igraph_barabasi_game(/* graph= */ &g, /* n= */ 1000, /* power= */ 1, /* m= */ 3, /* outseq= */ 0, /* outpref= */ 0, /* A= */ 1, /* directed= */ 0, /* algo= */ IGRAPH_BARABASI_BAG, /* start_from= */ 0); igraph_simplify(&g, /* multiple= */ 1, /* loops= */ 1, /*edge_comb=*/ 0); igraph_vector_init(&bet, 0); igraph_vector_init(&bbet, 0); igraph_betweenness_estimate(/* graph= */ &g, /* res= */ &bet, /* vids= */ igraph_vss_all(), /* directed = */ 0, /* cutoff= */ 2, /* weights= */ 0, /* nobigint= */ 1); igraph_betweenness_estimate(/* graph= */ &g, /* res= */ &bbet, /* vids= */ igraph_vss_all(), /* directed = */ 0, /* cutoff= */ 2, /* weights= */ 0, /* nobigint= */ 0); check(&bet, &bbet, 10); igraph_vector_destroy(&bet); igraph_vector_destroy(&bbet); igraph_destroy(&g); /*******************************************************/ igraph_tree(&g, 20000, 10, IGRAPH_TREE_UNDIRECTED); igraph_vector_init(&bet, 0); igraph_vector_init(&bbet, 0); igraph_betweenness_estimate(/* graph= */ &g, /* res= */ &bet, /* vids= */ igraph_vss_all(), /* directed = */ 0, /* cutoff= */ 3, /* weights= */ 0, /* nobigint= */ 1); igraph_betweenness_estimate(/* graph= */ &g, /* res= */ &bbet, /* vids= */ igraph_vss_all(), /* directed = */ 0, /* cutoff= */ 3, /* weights= */ 0, /* nobigint= */ 0); check(&bet, &bbet, 20); igraph_vector_init(&bet2, 0); igraph_vector_init(&bbet2, 0); igraph_vector_init(&weights, igraph_ecount(&g)); igraph_vector_fill(&weights, 1.0); igraph_betweenness_estimate(/* graph= */ &g, /* res= */ &bet2, /* vids= */ igraph_vss_all(), /* directed = */ 0, /* cutoff= */ 3, /* weights= */ &weights, /* nobigint= */ 1); igraph_betweenness_estimate(/* graph= */ &g, /* res= */ &bbet2, /* vids= */ igraph_vss_all(), /* directed = */ 0, /* cutoff= */ 3, /* weights= */ &weights, /* nobigint= */ 0); if (!igraph_vector_all_e(&bet, &bet2)) { return 1; } /* if (!igraph_vector_all_e(&bbet, &bbet2)) { */ /* return 2; */ /* } */ check(&bet, &bbet, 30); check(&bet2, &bbet2, 40); igraph_vector_destroy(&bet); igraph_vector_destroy(&bet2); igraph_vector_destroy(&bbet); igraph_vector_destroy(&bbet2); igraph_vector_destroy(&weights); igraph_destroy(&g); /* Non-trivial weighted graph */ igraph_vector_view(&edges, nontriv, sizeof(nontriv) / sizeof(igraph_real_t)); igraph_create(&g, &edges, 0, /* directed= */ 0); igraph_vector_view(&weights, nontriv_weights, sizeof(nontriv_weights) / sizeof(igraph_real_t)); igraph_vector_init(&bet, 0); igraph_vector_init(&bbet, 0); igraph_betweenness(/*graph=*/ &g, /*res=*/ &bet, /*vids=*/ igraph_vss_all(), /*directed=*/0, /*weights=*/ &weights, /*nobigint=*/ 1); igraph_betweenness(/*graph=*/ &g, /*res=*/ &bbet, /*vids=*/ igraph_vss_all(), /*directed=*/0, /*weights=*/ &weights, /*nobigint=*/ 0); igraph_vector_view(&bet2, nontriv_res, sizeof(nontriv_res) / sizeof(igraph_real_t)); if (!igraph_vector_all_e(&bet, &bet2)) { return 2; } check(&bet, &bbet, 50); igraph_vector_destroy(&bet); igraph_vector_destroy(&bbet); igraph_destroy(&g); if (IGRAPH_FINALLY_STACK_SIZE() != 0) { return 3; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_independent_sets.c0000644000076500000240000000525313612122633030753 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include void print_vector(igraph_vector_t *v) { long int i, n = igraph_vector_size(v); for (i = 0; i < n; i++) { printf(" %li", (long int) VECTOR(*v)[i]); } printf("\n"); } void warning_handler_ignore(const char* reason, const char* file, int line, int e) { } int main() { igraph_t g; igraph_vector_ptr_t result; long int i, j, n; igraph_integer_t alpha; const int params[] = {4, -1, 2, 2, 0, 0, -1, -1}; igraph_set_warning_handler(warning_handler_ignore); igraph_vector_ptr_init(&result, 0); igraph_tree(&g, 5, 2, IGRAPH_TREE_OUT); for (j = 0; j < sizeof(params) / (2 * sizeof(params[0])); j++) { if (params[2 * j + 1] != 0) { igraph_independent_vertex_sets(&g, &result, params[2 * j], params[2 * j + 1]); } else { igraph_largest_independent_vertex_sets(&g, &result); } n = igraph_vector_ptr_size(&result); printf("%ld independent sets found\n", (long)n); for (i = 0; i < n; i++) { igraph_vector_t* v; v = igraph_vector_ptr_e(&result, i); print_vector((igraph_vector_t*)v); igraph_vector_destroy(v); free(v); } } igraph_destroy(&g); igraph_tree(&g, 10, 2, IGRAPH_TREE_OUT); igraph_maximal_independent_vertex_sets(&g, &result); n = igraph_vector_ptr_size(&result); printf("%ld maximal independent sets found\n", (long)n); for (i = 0; i < n; i++) { igraph_vector_t* v; v = igraph_vector_ptr_e(&result, i); print_vector((igraph_vector_t*)v); igraph_vector_destroy(v); free(v); } igraph_vector_ptr_destroy(&result); igraph_independence_number(&g, &alpha); printf("alpha=%ld\n", (long)alpha); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_es_path.c0000644000076500000240000000415413612122633027042 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include int main() { igraph_t g; igraph_es_t es; igraph_eit_t eit; igraph_integer_t size; /* DIRECTED */ igraph_ring(&g, 10, IGRAPH_DIRECTED, 0, 1); igraph_es_path_small(&es, IGRAPH_DIRECTED, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, -1); igraph_eit_create(&g, es, &eit); igraph_es_size(&g, &es, &size); while (!IGRAPH_EIT_END(eit)) { long int edge = IGRAPH_EIT_GET(eit); igraph_integer_t from, to; igraph_edge(&g, edge, &from, &to); IGRAPH_EIT_NEXT(eit); size--; } if (size != 0) { return 1; } igraph_eit_destroy(&eit); igraph_es_destroy(&es); igraph_destroy(&g); /* UNDIRECTED */ igraph_ring(&g, 10, IGRAPH_UNDIRECTED, 0, 1); igraph_es_path_small(&es, IGRAPH_DIRECTED, 0, 1, 2, 3, 4, 3, 2, 3, 4, 5, 6, 5, 4, 5, 6, 7, 8, 9, 0, 1, 0, 9, -1); igraph_eit_create(&g, es, &eit); while (!IGRAPH_EIT_END(eit)) { long int edge = IGRAPH_EIT_GET(eit); igraph_integer_t from, to; igraph_edge(&g, edge, &from, &to); IGRAPH_EIT_NEXT(eit); } igraph_eit_destroy(&eit); igraph_es_destroy(&es); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_community_fastgreedy.c0000644000076500000240000001673013612122633031663 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void show_results(igraph_t *g, igraph_vector_t *mod, igraph_matrix_t *merges, igraph_vector_t *membership, FILE* f) { long int i = 0; igraph_vector_t our_membership; igraph_vector_init(&our_membership, 0); if (mod != 0) { i = igraph_vector_which_max(mod); fprintf(f, "Modularity: %f\n", VECTOR(*mod)[i]); } else { fprintf(f, "Modularity: ---\n"); } if (membership != 0) { igraph_vector_update(&our_membership, membership); } else if (merges != 0) { igraph_community_to_membership(merges, igraph_vcount(g), i, &our_membership, 0); } printf("Membership: "); for (i = 0; i < igraph_vector_size(&our_membership); i++) { printf("%li ", (long int)VECTOR(our_membership)[i]); } printf("\n"); igraph_vector_destroy(&our_membership); } int main() { igraph_t g; igraph_vector_t modularity, weights, membership; igraph_matrix_t merges; igraph_vector_init(&modularity, 0); igraph_matrix_init(&merges, 0, 0); igraph_vector_init(&weights, 0); igraph_vector_init(&membership, 0); /* Simple unweighted graph */ igraph_small(&g, 10, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 0, 4, 1, 2, 1, 3, 1, 4, 2, 3, 2, 4, 3, 4, 5, 6, 5, 7, 5, 8, 5, 9, 6, 7, 6, 8, 6, 9, 7, 8, 7, 9, 8, 9, 0, 5, -1); igraph_community_fastgreedy(&g, 0, &merges, &modularity, /*membership=*/ 0); show_results(&g, &modularity, &merges, 0, stdout); /* Same simple graph, with uniform edge weights */ igraph_vector_resize(&weights, igraph_ecount(&g)); igraph_vector_fill(&weights, 2); igraph_community_fastgreedy(&g, &weights, &merges, &modularity, /*membership=*/ 0); show_results(&g, &modularity, &merges, 0, stdout); igraph_destroy(&g); /* Simple nonuniform weighted graph, with and without weights */ igraph_small(&g, 6, IGRAPH_UNDIRECTED, 0, 1, 1, 2, 2, 3, 2, 4, 2, 5, 3, 4, 3, 5, 4, 5, -1); igraph_vector_resize(&weights, 8); igraph_vector_fill(&weights, 1); VECTOR(weights)[0] = 10; VECTOR(weights)[1] = 10; igraph_community_fastgreedy(&g, 0, &merges, &modularity, /*membership=*/ 0); show_results(&g, &modularity, &merges, 0, stdout); igraph_community_fastgreedy(&g, &weights, &merges, &modularity, /*membership=*/ 0); show_results(&g, &modularity, &merges, 0, stdout); igraph_destroy(&g); /* Zachary Karate club */ igraph_small(&g, 0, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 0, 7, 0, 8, 0, 10, 0, 11, 0, 12, 0, 13, 0, 17, 0, 19, 0, 21, 0, 31, 1, 2, 1, 3, 1, 7, 1, 13, 1, 17, 1, 19, 1, 21, 1, 30, 2, 3, 2, 7, 2, 8, 2, 9, 2, 13, 2, 27, 2, 28, 2, 32, 3, 7, 3, 12, 3, 13, 4, 6, 4, 10, 5, 6, 5, 10, 5, 16, 6, 16, 8, 30, 8, 32, 8, 33, 9, 33, 13, 33, 14, 32, 14, 33, 15, 32, 15, 33, 18, 32, 18, 33, 19, 33, 20, 32, 20, 33, 22, 32, 22, 33, 23, 25, 23, 27, 23, 29, 23, 32, 23, 33, 24, 25, 24, 27, 24, 31, 25, 31, 26, 29, 26, 33, 27, 33, 28, 31, 28, 33, 29, 32, 29, 33, 30, 32, 30, 33, 31, 32, 31, 33, 32, 33, -1); igraph_community_fastgreedy(&g, 0, &merges, &modularity, /*membership=*/ 0); show_results(&g, &modularity, &merges, 0, stdout); igraph_destroy(&g); /* Simple disconnected graph with isolates */ igraph_small(&g, 9, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 1, 2, 1, 3, 2, 3, 4, 5, 4, 6, 4, 7, 5, 6, 5, 7, 6, 7, -1); igraph_community_fastgreedy(&g, 0, &merges, &modularity, /*membership=*/ 0); show_results(&g, &modularity, &merges, 0, stdout); igraph_destroy(&g); /* Disjoint union of two rings */ igraph_small(&g, 20, IGRAPH_UNDIRECTED, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7, 7, 8, 8, 9, 0, 9, 10, 11, 11, 12, 12, 13, 13, 14, 14, 15, 15, 16, 16, 17, 17, 18, 18, 19, 10, 19, -1); igraph_community_fastgreedy(&g, 0, &merges, &modularity, /*membership=*/ 0); show_results(&g, &modularity, &merges, 0, stdout); igraph_destroy(&g); /* Completely empty graph */ igraph_small(&g, 10, IGRAPH_UNDIRECTED, -1); igraph_community_fastgreedy(&g, 0, &merges, &modularity, /*membership=*/ 0); show_results(&g, &modularity, &merges, 0, stdout); igraph_destroy(&g); /* Ring graph with loop edges */ igraph_small(&g, 6, IGRAPH_UNDIRECTED, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 0, 0, 0, 2, 2, -1); igraph_community_fastgreedy(&g, 0, &merges, &modularity, /*membership=*/ 0); show_results(&g, &modularity, &merges, 0, stdout); igraph_destroy(&g); /* Regression test -- graph with two vertices and two edges */ igraph_small(&g, 2, IGRAPH_UNDIRECTED, 0, 0, 1, 1, -1); igraph_community_fastgreedy(&g, 0, &merges, &modularity, /*membership=*/ 0); show_results(&g, &modularity, &merges, 0, stdout); igraph_destroy(&g); /* Regression test -- asking for optimal membership vector but not * providing a modularity vector */ igraph_small(&g, 10, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 0, 4, 1, 2, 1, 3, 1, 4, 2, 3, 2, 4, 3, 4, 5, 6, 5, 7, 5, 8, 5, 9, 6, 7, 6, 8, 6, 9, 7, 8, 7, 9, 8, 9, 0, 5, -1); igraph_community_fastgreedy(&g, 0, &merges, 0, &membership); show_results(&g, 0, &merges, &membership, stdout); igraph_destroy(&g); /* Regression test -- asking for optimal membership vector but not * providing a merge matrix */ igraph_small(&g, 10, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 0, 4, 1, 2, 1, 3, 1, 4, 2, 3, 2, 4, 3, 4, 5, 6, 5, 7, 5, 8, 5, 9, 6, 7, 6, 8, 6, 9, 7, 8, 7, 9, 8, 9, 0, 5, -1); igraph_community_fastgreedy(&g, 0, 0, &modularity, &membership); show_results(&g, &modularity, 0, &membership, stdout); /* Regression test -- asking for optimal membership vector but not * providing a merge matrix or a modularity vector */ igraph_community_fastgreedy(&g, 0, 0, 0, &membership); show_results(&g, 0, 0, &membership, stdout); igraph_destroy(&g); igraph_vector_destroy(&membership); igraph_vector_destroy(&modularity); igraph_vector_destroy(&weights); igraph_matrix_destroy(&merges); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/foreign.c0000644000076500000240000000264013612122633025514 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int main(int argc, char **argv) { igraph_t g; FILE *ifile; /* PAJEK */ ifile = fopen("LINKS.NET", "r"); if (ifile == 0) { return 10; } igraph_read_graph_pajek(&g, ifile); fclose(ifile); printf("The graph:\n"); printf("Vertices: %li\n", (long int) igraph_vcount(&g)); printf("Edges: %li\n", (long int) igraph_ecount(&g)); printf("Directed: %i\n", (int) igraph_is_directed(&g)); igraph_write_graph_edgelist(&g, stdout); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/eigenvector_centrality.c0000644000076500000240000000456613612122633030644 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph.h" #include int main() { igraph_t g; igraph_vector_t v, weights; long int i; igraph_real_t value; igraph_arpack_options_t options; igraph_star(&g, 100, IGRAPH_STAR_UNDIRECTED, 0); igraph_arpack_options_init(&options); igraph_vector_init(&v, 0); igraph_eigenvector_centrality(&g, &v, &value, /*directed=*/ 0, /*scale=*/0, /*weights=*/0, &options); if (options.info != 0) { return 1; } for (i = 0; i < igraph_vector_size(&v); i++) { printf(" %.3f", fabs(VECTOR(v)[i])); } printf("\n"); igraph_destroy(&g); /* Special cases: check for empty graph */ igraph_empty(&g, 10, 0); igraph_eigenvector_centrality(&g, &v, &value, 0, 0, 0, &options); if (value != 0.0) { return 1; } for (i = 0; i < igraph_vector_size(&v); i++) { printf(" %.2f", fabs(VECTOR(v)[i])); } printf("\n"); igraph_destroy(&g); /* Special cases: check for full graph, zero weights */ igraph_full(&g, 10, 0, 0); igraph_vector_init(&weights, 45); igraph_vector_fill(&weights, 0); igraph_eigenvector_centrality(&g, &v, &value, 0, 0, &weights, &options); igraph_vector_destroy(&weights); if (value != 0.0) { return 2; } for (i = 0; i < igraph_vector_size(&v); i++) { printf(" %.2f", fabs(VECTOR(v)[i])); } printf("\n"); igraph_destroy(&g); igraph_vector_destroy(&v); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/tls2.out0000644000076500000240000000113613524616144025342 0ustar tamasstaff000000000000004 8 2 6 1 3 0 2 4 10 8 10 8 6 1 6 10 10 0 4 2 8 8 1 0 1 7 2 3 2 6 6 1 4 5 7 9 6 5 5 1 1 0 5 9 7 10 3 6 0 3 6 1 7 7 0 2 6 4 8 0 10 7 9 10 2 0 5 1 6 2 10 2 6 3 6 5 0 0 2 4 0 3 5 6 4 1 0 3 4 10 4 2 5 0 8 6 2 4 5 0.286678 0.451579 0.240944 0.373405 0.279524 0.306442 0.358295 0.280974 0.192354 0.316299 --- 10 6 0 7 0 8 7 9 8 10 6 5 9 1 10 4 2 0 3 9 0 9 6 4 10 3 4 1 4 8 7 1 4 0 10 0 7 10 5 4 0 10 10 10 6 1 1 4 2 10 8 4 3 0 1 2 6 2 6 4 7 2 4 7 1 6 5 2 6 9 9 0 1 10 4 2 2 7 2 10 8 3 4 5 2 6 6 2 0 6 10 9 8 4 10 4 9 10 6 7 0.383729 0.301458 0.289645 0.287748 0.324551 0.214976 0.2921 0.298273 0.252215 0.453578 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_all_st_mincuts.c0000644000076500000240000001313113612122633030432 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int print_and_destroy(igraph_t *g, igraph_real_t value, igraph_vector_ptr_t *partitions, igraph_vector_ptr_t *cuts) { long int i, e, m, n = igraph_vector_ptr_size(partitions); printf("Found %li cuts, value: %g\n", n, value); for (i = 0; i < n; i++) { igraph_vector_t *vec = VECTOR(*partitions)[i]; igraph_vector_t *vec2 = cuts ? VECTOR(*cuts)[i] : 0; printf("Partition %li: ", i); igraph_vector_print(vec); if (vec2) { printf("Cut %li:\n", i); m = igraph_vector_size(vec2); for (e = 0; e < m; e++) { igraph_integer_t from, to; igraph_edge(g, VECTOR(*vec2)[e], &from, &to); if (igraph_is_directed(g)) { printf(" %i -> %i\n", from, to); } else { printf(" %i -- %i\n", from, to); } } } igraph_vector_destroy(vec); if (vec2) { igraph_vector_destroy(vec2); } igraph_free(vec); if (vec2) { igraph_free(vec2); } } igraph_vector_ptr_destroy(partitions); if (cuts) { igraph_vector_ptr_destroy(cuts); } printf("\n"); return 0; } int main() { igraph_t g; igraph_vector_ptr_t partitions; igraph_vector_ptr_t cuts; igraph_real_t value; igraph_small(&g, 5, IGRAPH_DIRECTED, 0, 1, 1, 2, 2, 3, 3, 4, -1); igraph_vector_ptr_init(&partitions, 0); igraph_vector_ptr_init(&cuts, 0); igraph_all_st_mincuts(&g, &value, &cuts, &partitions, /*source=*/ 0, /*target=*/ 4, /*capacity=*/ 0); print_and_destroy(&g, value, &partitions, &cuts); igraph_destroy(&g); /* ---------------------------------------------------------------- */ igraph_small(&g, 6, IGRAPH_DIRECTED, 0, 1, 1, 2, 1, 3, 2, 4, 3, 4, 4, 5, -1); igraph_vector_ptr_init(&partitions, 0); igraph_vector_ptr_init(&cuts, 0); igraph_all_st_mincuts(&g, &value, &cuts, &partitions, /*source=*/ 0, /*target=*/ 5, /*capacity=*/ 0); print_and_destroy(&g, value, &partitions, &cuts); igraph_destroy(&g); /* ---------------------------------------------------------------- */ igraph_small(&g, 6, IGRAPH_DIRECTED, 0, 1, 1, 2, 1, 3, 2, 4, 3, 4, 4, 5, -1); igraph_vector_ptr_init(&partitions, 0); igraph_vector_ptr_init(&cuts, 0); igraph_all_st_mincuts(&g, &value, &cuts, &partitions, /*source=*/ 0, /*target=*/ 4, /*capacity=*/ 0); print_and_destroy(&g, value, &partitions, &cuts); igraph_destroy(&g); /* ---------------------------------------------------------------- */ igraph_small(&g, 9, IGRAPH_DIRECTED, 0, 1, 0, 2, 1, 3, 2, 3, 1, 4, 4, 2, 1, 5, 5, 2, 1, 6, 6, 2, 1, 7, 7, 2, 1, 8, 8, 2, -1); igraph_vector_ptr_init(&partitions, 0); igraph_vector_ptr_init(&cuts, 0); igraph_all_st_mincuts(&g, &value, &cuts, &partitions, /*source=*/ 0, /*target=*/ 3, /*capacity=*/ 0); print_and_destroy(&g, value, &partitions, &cuts); igraph_destroy(&g); /* ---------------------------------------------------------------- */ igraph_small(&g, 4, IGRAPH_DIRECTED, 1, 0, 2, 0, 2, 1, 3, 2, -1); igraph_vector_ptr_init(&partitions, 0); igraph_vector_ptr_init(&cuts, 0); igraph_all_st_mincuts(&g, &value, &cuts, &partitions, /*source=*/ 2, /*target=*/ 0, /*capacity=*/ 0); print_and_destroy(&g, value, &partitions, &cuts); igraph_destroy(&g); /* ---------------------------------------------------------------- */ igraph_small(&g, 4, IGRAPH_DIRECTED, 1, 0, 2, 0, 2, 1, 2, 3, -1); igraph_vector_ptr_init(&partitions, 0); igraph_vector_ptr_init(&cuts, 0); igraph_all_st_mincuts(&g, &value, &cuts, &partitions, /*source=*/ 2, /*target=*/ 0, /*capacity=*/ 0); print_and_destroy(&g, value, &partitions, &cuts); igraph_destroy(&g); /* ---------------------------------------------------------------- */ igraph_small(&g, 9, IGRAPH_DIRECTED, 0, 4, 0, 7, 1, 6, 2, 1, 3, 8, 4, 0, 4, 2, 4, 5, 5, 0, 5, 3, 6, 7, 7, 8, -1); igraph_vector_ptr_init(&partitions, 0); igraph_vector_ptr_init(&cuts, 0); igraph_all_st_mincuts(&g, &value, &cuts, &partitions, /*source=*/ 0, /*target=*/ 8, /*capacity=*/ 0); print_and_destroy(&g, value, &partitions, &cuts); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_ring.c0000644000076500000240000001371613612122633026362 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA Ring test suite Copyright (C) 2011 Minh Van Nguyen This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include typedef struct { int n, m; igraph_bool_t directed, mutual, circular; igraph_real_t *edges; } ring_test_t; #define RING_TEST(id, n, m, di, mu, ci, ...) \ igraph_real_t ring_ ## id ## _edges[] = { __VA_ARGS__ }; \ ring_test_t ring_ ## id = { n, m, di, mu, ci, ring_ ## id ## _edges } /*---------------n--m--di-mu-ci--edges-------------------------------------*/ RING_TEST(uc_6, 6, 6, 0, 0, 1, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 0 ); RING_TEST(uc_0, 0, 0, 0, 0, 1, -1 ); RING_TEST(uc_1, 1, 0, 0, 0, 1, -1 ); RING_TEST(uc_2, 2, 1, 0, 0, 1, 0, 1 ); RING_TEST(u_6, 6, 5, 0, 0, 0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5 ); RING_TEST(u_0, 0, 0, 0, 0, 0, -1 ); RING_TEST(u_1, 1, 0, 0, 0, 0, -1 ); RING_TEST(u_2, 2, 1, 0, 0, 0, 0, 1 ); RING_TEST(umc_6, 6, 6, 0, 1, 1, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 0 ); RING_TEST(umc_0, 0, 0, 0, 1, 1, -1 ); RING_TEST(umc_1, 1, 0, 0, 1, 1, -1 ); RING_TEST(umc_2, 2, 1, 0, 1, 1, 0, 1 ); RING_TEST(um_6, 6, 5, 0, 1, 0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5 ); RING_TEST(um_0, 0, 0, 0, 1, 0, -1 ); RING_TEST(um_1, 1, 0, 0, 1, 0, -1 ); RING_TEST(um_2, 2, 1, 0, 1, 0, 0, 1 ); RING_TEST(dc_6, 6, 6, 1, 0, 1, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 0 ); RING_TEST(dc_0, 0, 0, 1, 0, 1, -1 ); RING_TEST(dc_1, 1, 0, 1, 0, 1, -1 ); RING_TEST(dc_2, 2, 2, 1, 0, 1, 0, 1, 1, 0 ); RING_TEST(d_6, 6, 5, 1, 0, 1, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5 ); RING_TEST(d_0, 0, 0, 1, 0, 1, -1 ); RING_TEST(d_1, 1, 0, 1, 0, 1, -1 ); RING_TEST(d_2, 2, 1, 1, 0, 1, 0, 1 ); RING_TEST(dmc_6, 6, 12, 1, 1, 1, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 0, 1, 0, 2, 1, 3, 2, 4, 3, 5, 4, 0, 5 ); RING_TEST(dmc_0, 0, 0, 1, 1, 1, -1 ); RING_TEST(dmc_1, 1, 0, 1, 1, 1, -1 ); RING_TEST(dmc_2, 2, 2, 1, 1, 1, 0, 1, 1, 0 ); RING_TEST(dm_6, 6, 10, 1, 1, 0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 1, 0, 2, 1, 3, 2, 4, 3, 5, 4 ); RING_TEST(dm_0, 0, 0, 1, 1, 0, -1 ); RING_TEST(dm_1, 1, 0, 1, 1, 0, -1 ); RING_TEST(dm_2, 2, 2, 1, 1, 0, 0, 1, 1, 0 ); /*---------------n--m--di-mu-ci--edges-------------------------------------*/ ring_test_t *all_checks[] = { /* 1 */ &ring_uc_6, /* 2 */ &ring_uc_0, /* 3 */ &ring_uc_1, /* 4 */ &ring_uc_2, /* 5 */ &ring_u_6, /* 6 */ &ring_u_0, /* 7 */ &ring_u_1, /* 8 */ &ring_u_2, /* 9 */ &ring_umc_6, /* 10 */ &ring_umc_0, /* 11 */ &ring_umc_1, /* 12 */ &ring_umc_2, /* 13 */ &ring_um_6, /* 14 */ &ring_um_0, /* 15 */ &ring_um_1, /* 16 */ &ring_um_2, /* 17 */ &ring_dc_6, /* 18 */ &ring_dc_0, /* 19 */ &ring_dc_1, /* 20 */ &ring_dc_2, /* 21 */ &ring_dmc_6, /* 22 */ &ring_dmc_0, /* 23 */ &ring_dmc_1, /* 24 */ &ring_dmc_2, /* 25 */ &ring_dm_6, /* 26 */ &ring_dm_0, /* 27 */ &ring_dm_1, /* 28 */ &ring_dm_2, 0 }; int check_ring_properties(const igraph_t *ring, igraph_bool_t directed, igraph_bool_t mutual, igraph_bool_t circular) { igraph_bool_t res; /* Connected */ igraph_is_connected(ring, &res, IGRAPH_WEAK); if (!res) { printf("Not connected\n"); return 1; } /* Simple */ igraph_is_simple(ring, &res); if (!res) { printf("Not simple\n"); return 2; } /* Girth, for big enough circular graphs */ if (circular && igraph_vcount(ring) > 2) { igraph_integer_t girth; igraph_girth(ring, &girth, NULL); if (girth != igraph_vcount(ring)) { printf("Wrong girth\n"); return 3; } } return 0; } int check_ring(const ring_test_t *test) { igraph_t graph, othergraph; igraph_vector_t otheredges; igraph_bool_t iso; int ret; /* Create ring */ igraph_ring(&graph, test->n, test->directed, test->mutual, test->circular); /* Check its properties */ if ((ret = check_ring_properties(&graph, test->directed, test->mutual, test->circular))) { return ret; } /* Check that it is isomorphic to the stored graph */ igraph_vector_view(&otheredges, test->edges, test->m * 2); igraph_create(&othergraph, &otheredges, test->n, test->directed); igraph_isomorphic(&graph, &othergraph, &iso); if (!iso) { return 50; } /* Clean up */ igraph_destroy(&graph); igraph_destroy(&othergraph); return 0; } int main() { int i, ret; i = 0; while (all_checks[i]) { if ((ret = check_ring(all_checks[i]))) { printf("Check no #%d failed.\n", (int) (i + 1)); return ret; } i++; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_get_shortest_paths.out0000644000076500000240000000013013524616144031712 0ustar tamasstaff00000000000000 0 1 0 1 2 3 0 1 2 3 4 5 0 1 2 0 1 0 0 1 2 3 4 -1 -1 -1 -1 -1 0 1 2 3 4 -1 -1 -1 -1 python-igraph-0.8.0/vendor/source/igraph/examples/simple/2wheap.c0000644000076500000240000001116513612122633025253 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2008-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include "igraph_types_internal.h" #include #include int main() { igraph_vector_t elems; igraph_2wheap_t Q; long int i; igraph_real_t prev = IGRAPH_INFINITY; srand(time(0)); igraph_vector_init(&elems, 100); for (i = 0; i < igraph_vector_size(&elems); i++) { VECTOR(elems)[i] = rand() / (double)RAND_MAX; } igraph_2wheap_init(&Q, igraph_vector_size(&elems)); for (i = 0; i < igraph_vector_size(&elems); i++) { igraph_2wheap_push_with_index(&Q, i, VECTOR(elems)[i]); } /*****/ for (i = 0; i < igraph_vector_size(&elems); i++) { if (VECTOR(elems)[i] != igraph_2wheap_get(&Q, i)) { return 1; } } /*****/ for (i = 0; i < igraph_vector_size(&elems); i++) { long int j; igraph_real_t tmp = igraph_2wheap_max(&Q); if (tmp > prev) { return 2; } if (tmp != igraph_2wheap_delete_max_index(&Q, &j)) { return 3; } if (VECTOR(elems)[j] != tmp) { return 4; } prev = tmp; } /*****/ for (i = 0; i < igraph_vector_size(&elems); i++) { igraph_2wheap_push_with_index(&Q, i, VECTOR(elems)[i]); } if (igraph_2wheap_size(&Q) != igraph_vector_size(&elems)) { return 5; } for (i = 0; i < igraph_vector_size(&elems); i++) { VECTOR(elems)[i] = rand() / (double)RAND_MAX; igraph_2wheap_modify(&Q, i, VECTOR(elems)[i]); } for (i = 0; i < igraph_vector_size(&elems); i++) { if (VECTOR(elems)[i] != igraph_2wheap_get(&Q, i)) { return 6; } } prev = IGRAPH_INFINITY; for (i = 0; i < igraph_vector_size(&elems); i++) { long int j; igraph_real_t tmp = igraph_2wheap_max(&Q); if (tmp > prev) { return 7; } if (tmp != igraph_2wheap_delete_max_index(&Q, &j)) { return 8; } if (VECTOR(elems)[j] != tmp) { return 9; } prev = tmp; } if (!igraph_2wheap_empty(&Q)) { return 10; } if (igraph_2wheap_size(&Q) != 0) { return 11; } igraph_2wheap_destroy(&Q); igraph_vector_destroy(&elems); /* Hand-made example */ #define MAX do { igraph_2wheap_delete_max(&Q); igraph_2wheap_check(&Q); } while (0) #define PUSH(i,e) do { igraph_2wheap_push_with_index(&Q, (i), -(e)); igraph_2wheap_check(&Q); } while (0); #define MOD(i, e) do { igraph_2wheap_modify(&Q, (i), -(e)); igraph_2wheap_check(&Q); } while (0) igraph_2wheap_init(&Q, 21); /* 0.00 [ 4] */ PUSH(4, 0); /* MAX */ MAX; /* 0.63 [11] */ PUSH(11, 0.63); /* 0.05 [15] */ PUSH(15, 0.05); /* MAX */ MAX; /* 0.4 [12] */ PUSH(12, 0.4); /* 0.4 [13] */ PUSH(13, 0.4); /* 0.12 [16] */ PUSH(16, 0.12); /* MAX */ MAX; /* 1.1 [ 0] */ PUSH(0, 1.1); /* 1.1 [14] */ PUSH(14, 1.1); /* MAX */ MAX; /* [11]/0.44 */ MOD(11, 0.44); /* MAX */ MAX; /* MAX */ MAX; /* 1.1 [20] */ PUSH(20, 1.1); /* MAX */ MAX; /* 1.3 [ 7] */ PUSH(7, 1.3); /* 1.7 [ 9] */ PUSH(9, 1.7); /* MAX */ MAX; /* 1.6 [19] */ PUSH(19, 1.6); /* MAX */ MAX; /* 2.1 [17] */ PUSH(17, 2.1); /* 1.3 [18] */ PUSH(18, 1.3); /* MAX */ MAX; /* 2.3 [ 1] */ PUSH(1, 2.3); /* 2.2 [ 5] */ PUSH(5, 2.2); /* 2.3 [10] */ PUSH(10, 2.3); /* MAX */ MAX; /* [17]/1.5 */ MOD(17, 1.5); /* MAX */ MAX; /* 1.8 [ 6] */ PUSH(6, 1.8); /* MAX */ MAX; /* 1.3 [ 3] */ PUSH(3, 1.3); /* [ 6]/1.3 */ MOD(6, 1.3); /* MAX */ MAX; /* 1.6 [ 8] */ PUSH(8, 1.6); /* MAX */ MAX; igraph_2wheap_destroy(&Q); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/cattributes.c0000644000076500000240000003177213614300625026425 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include int print_attributes(const igraph_t *g) { igraph_vector_t gtypes, vtypes, etypes; igraph_strvector_t gnames, vnames, enames; long int i; igraph_vector_t vec; igraph_strvector_t svec; long int j; igraph_vector_init(>ypes, 0); igraph_vector_init(&vtypes, 0); igraph_vector_init(&etypes, 0); igraph_strvector_init(&gnames, 0); igraph_strvector_init(&vnames, 0); igraph_strvector_init(&enames, 0); igraph_cattribute_list(g, &gnames, >ypes, &vnames, &vtypes, &enames, &etypes); /* Graph attributes */ for (i = 0; i < igraph_strvector_size(&gnames); i++) { printf("%s=", STR(gnames, i)); if (VECTOR(gtypes)[i] == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_real_printf(GAN(g, STR(gnames, i))); putchar(' '); } else { printf("\"%s\" ", GAS(g, STR(gnames, i))); } } printf("\n"); for (i = 0; i < igraph_vcount(g); i++) { long int j; printf("Vertex %li: ", i); for (j = 0; j < igraph_strvector_size(&vnames); j++) { printf("%s=", STR(vnames, j)); if (VECTOR(vtypes)[j] == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_real_printf(VAN(g, STR(vnames, j), i)); putchar(' '); } else { printf("\"%s\" ", VAS(g, STR(vnames, j), i)); } } printf("\n"); } for (i = 0; i < igraph_ecount(g); i++) { long int j; printf("Edge %li (%i-%i): ", i, (int)IGRAPH_FROM(g, i), (int)IGRAPH_TO(g, i)); for (j = 0; j < igraph_strvector_size(&enames); j++) { printf("%s=", STR(enames, j)); if (VECTOR(etypes)[j] == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_real_printf(EAN(g, STR(enames, j), i)); putchar(' '); } else { printf("\"%s\" ", EAS(g, STR(enames, j), i)); } } printf("\n"); } /* Check vector-based query functions */ igraph_vector_init(&vec, 0); igraph_strvector_init(&svec, 0); for (j = 0; j < igraph_strvector_size(&vnames); j++) { if (VECTOR(vtypes)[j] == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_cattribute_VANV(g, STR(vnames, j), igraph_vss_all(), &vec); for (i = 0; i < igraph_vcount(g); i++) { igraph_real_t num = VAN(g, STR(vnames, j), i); if (num != VECTOR(vec)[i] && (!isnan(num) || !isnan(VECTOR(vec)[i]))) { exit(51); } } } else { igraph_cattribute_VASV(g, STR(vnames, j), igraph_vss_all(), &svec); for (i = 0; i < igraph_vcount(g); i++) { const char *str = VAS(g, STR(vnames, j), i); if (strcmp(str, STR(svec, i))) { exit(52); } } } } for (j = 0; j < igraph_strvector_size(&enames); j++) { if (VECTOR(etypes)[j] == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_cattribute_EANV(g, STR(enames, j), igraph_ess_all(IGRAPH_EDGEORDER_ID), &vec); for (i = 0; i < igraph_ecount(g); i++) { igraph_real_t num = EAN(g, STR(enames, j), i); if (num != VECTOR(vec)[i] && (!isnan(num) || !isnan(VECTOR(vec)[i]))) { exit(53); } } } else { igraph_cattribute_EASV(g, STR(enames, j), igraph_ess_all(IGRAPH_EDGEORDER_ID), &svec); for (i = 0; i < igraph_ecount(g); i++) { const char *str = EAS(g, STR(enames, j), i); if (strcmp(str, STR(svec, i))) { exit(54); } } } } igraph_strvector_destroy(&svec); igraph_vector_destroy(&vec); igraph_strvector_destroy(&enames); igraph_strvector_destroy(&vnames); igraph_strvector_destroy(&gnames); igraph_vector_destroy(&etypes); igraph_vector_destroy(&vtypes); igraph_vector_destroy(>ypes); return 0; } int main() { igraph_t g, g2; FILE *ifile; igraph_vector_t gtypes, vtypes, etypes; igraph_strvector_t gnames, vnames, enames; long int i; igraph_vector_t y; igraph_strvector_t id; igraph_vector_bool_t type; char str[21]; /* turn on attribute handling */ igraph_i_set_attribute_table(&igraph_cattribute_table); ifile = fopen("LINKS.NET", "r"); if (ifile == 0) { return 10; } igraph_read_graph_pajek(&g, ifile); fclose(ifile); igraph_vector_init(>ypes, 0); igraph_vector_init(&vtypes, 0); igraph_vector_init(&etypes, 0); igraph_strvector_init(&gnames, 0); igraph_strvector_init(&vnames, 0); igraph_strvector_init(&enames, 0); igraph_cattribute_list(&g, &gnames, >ypes, &vnames, &vtypes, &enames, &etypes); /* List attribute names and types */ printf("Graph attributes: "); for (i = 0; i < igraph_strvector_size(&gnames); i++) { printf("%s (%i) ", STR(gnames, i), (int)VECTOR(gtypes)[i]); } printf("\n"); printf("Vertex attributes: "); for (i = 0; i < igraph_strvector_size(&vnames); i++) { printf("%s (%i) ", STR(vnames, i), (int)VECTOR(vtypes)[i]); } printf("\n"); printf("Edge attributes: "); for (i = 0; i < igraph_strvector_size(&enames); i++) { printf("%s (%i) ", STR(enames, i), (int)VECTOR(etypes)[i]); } printf("\n"); print_attributes(&g); /* Copying a graph */ igraph_copy(&g2, &g); print_attributes(&g2); igraph_destroy(&g2); /* Adding vertices */ igraph_add_vertices(&g, 3, 0); print_attributes(&g); /* Adding edges */ igraph_add_edge(&g, 1, 1); igraph_add_edge(&g, 2, 5); igraph_add_edge(&g, 3, 6); print_attributes(&g); /* Deleting vertices */ igraph_delete_vertices(&g, igraph_vss_1(1)); igraph_delete_vertices(&g, igraph_vss_1(4)); print_attributes(&g); /* Deleting edges */ igraph_delete_edges(&g, igraph_ess_1(igraph_ecount(&g) - 1)); igraph_delete_edges(&g, igraph_ess_1(0)); print_attributes(&g); /* Set graph attributes */ SETGAN(&g, "id", 10); if (GAN(&g, "id") != 10) { return 11; } SETGAS(&g, "name", "toy"); if (strcmp(GAS(&g, "name"), "toy")) { return 12; } SETGAB(&g, "is_regular", 0); if (GAB(&g, "is_regular") != 0) { return 13; } /* Delete graph attributes */ DELGA(&g, "id"); DELGA(&g, "name"); DELGA(&g, "is_regular"); igraph_cattribute_list(&g, &gnames, 0, 0, 0, 0, 0); if (igraph_strvector_size(&gnames) != 0) { return 14; } /* Delete vertex attributes */ DELVA(&g, "x"); DELVA(&g, "shape"); DELVA(&g, "xfact"); DELVA(&g, "yfact"); igraph_cattribute_list(&g, 0, 0, &vnames, 0, 0, 0); if (igraph_strvector_size(&vnames) != 3) { return 15; } /* Delete edge attributes */ igraph_cattribute_list(&g, 0, 0, 0, 0, &enames, 0); i = igraph_strvector_size(&enames); DELEA(&g, "hook1"); DELEA(&g, "hook2"); DELEA(&g, "label"); igraph_cattribute_list(&g, 0, 0, 0, 0, &enames, 0); if (igraph_strvector_size(&enames) != i - 3) { return 16; } /* Set vertex attributes */ SETVAN(&g, "y", 0, -1); SETVAN(&g, "y", 1, 2.1); if (VAN(&g, "y", 0) != -1 || VAN(&g, "y", 1) != 2.1) { return 17; } SETVAS(&g, "id", 0, "foo"); SETVAS(&g, "id", 1, "bar"); if (strcmp(VAS(&g, "id", 0), "foo") || strcmp(VAS(&g, "id", 1), "bar")) { return 18; } SETVAB(&g, "type", 0, 1); SETVAB(&g, "type", 1, 0); if (!VAB(&g, "type", 0) || VAB(&g, "type", 1)) { return 26; } /* Set edge attributes */ SETEAN(&g, "weight", 2, 100.0); SETEAN(&g, "weight", 0, -100.1); if (EAN(&g, "weight", 2) != 100.0 || EAN(&g, "weight", 0) != -100.1) { return 19; } SETEAS(&g, "color", 2, "RED"); SETEAS(&g, "color", 0, "Blue"); if (strcmp(EAS(&g, "color", 2), "RED") || strcmp(EAS(&g, "color", 0), "Blue")) { return 20; } SETEAB(&g, "type", 0, 1); SETEAB(&g, "type", 2, 0); if (!EAB(&g, "type", 0) || EAB(&g, "type", 2)) { return 27; } /* Set vertex attributes as vector */ igraph_vector_init(&y, igraph_vcount(&g)); igraph_vector_fill(&y, 1.23); SETVANV(&g, "y", &y); igraph_vector_destroy(&y); for (i = 0; i < igraph_vcount(&g); i++) { if (VAN(&g, "y", i) != 1.23) { return 21; } } igraph_vector_init_seq(&y, 0, igraph_vcount(&g) - 1); SETVANV(&g, "foobar", &y); igraph_vector_destroy(&y); for (i = 0; i < igraph_vcount(&g); i++) { if (VAN(&g, "foobar", i) != i) { return 22; } } igraph_vector_bool_init(&type, igraph_vcount(&g)); for (i = 0; i < igraph_vcount(&g); i++) { VECTOR(type)[i] = (i % 2 == 1); } SETVABV(&g, "type", &type); igraph_vector_bool_destroy(&type); for (i = 0; i < igraph_vcount(&g); i++) { if (VAB(&g, "type", i) != (i % 2 == 1)) { return 28; } } igraph_strvector_init(&id, igraph_vcount(&g)); for (i = 0; i < igraph_vcount(&g); i++) { snprintf(str, sizeof(str) - 1, "%li", i); igraph_strvector_set(&id, i, str); } SETVASV(&g, "foo", &id); igraph_strvector_destroy(&id); for (i = 0; i < igraph_vcount(&g); i++) { printf("%s ", VAS(&g, "foo", i)); } printf("\n"); igraph_strvector_init(&id, igraph_vcount(&g)); for (i = 0; i < igraph_vcount(&g); i++) { snprintf(str, sizeof(str) - 1, "%li", i); igraph_strvector_set(&id, i, str); } SETVASV(&g, "id", &id); igraph_strvector_destroy(&id); for (i = 0; i < igraph_vcount(&g); i++) { printf("%s ", VAS(&g, "id", i)); } printf("\n"); /* Set edge attributes as vector */ igraph_vector_init(&y, igraph_ecount(&g)); igraph_vector_fill(&y, 12.3); SETEANV(&g, "weight", &y); igraph_vector_destroy(&y); for (i = 0; i < igraph_ecount(&g); i++) { if (EAN(&g, "weight", i) != 12.3) { return 23; } } igraph_vector_init_seq(&y, 0, igraph_ecount(&g) - 1); SETEANV(&g, "foobar", &y); igraph_vector_destroy(&y); for (i = 0; i < igraph_ecount(&g); i++) { if (VAN(&g, "foobar", i) != i) { return 24; } } igraph_vector_bool_init(&type, igraph_ecount(&g)); for (i = 0; i < igraph_ecount(&g); i++) { VECTOR(type)[i] = (i % 2 == 1); } SETEABV(&g, "type", &type); igraph_vector_bool_destroy(&type); for (i = 0; i < igraph_ecount(&g); i++) { if (EAB(&g, "type", i) != (i % 2 == 1)) { return 29; } } igraph_strvector_init(&id, igraph_ecount(&g)); for (i = 0; i < igraph_ecount(&g); i++) { snprintf(str, sizeof(str) - 1, "%li", i); igraph_strvector_set(&id, i, str); } SETEASV(&g, "foo", &id); igraph_strvector_destroy(&id); for (i = 0; i < igraph_ecount(&g); i++) { printf("%s ", EAS(&g, "foo", i)); } printf("\n"); igraph_strvector_init(&id, igraph_ecount(&g)); for (i = 0; i < igraph_ecount(&g); i++) { snprintf(str, sizeof(str) - 1, "%li", i); igraph_strvector_set(&id, i, str); } SETEASV(&g, "color", &id); igraph_strvector_destroy(&id); for (i = 0; i < igraph_ecount(&g); i++) { printf("%s ", EAS(&g, "color", i)); } printf("\n"); /* Delete all remaining attributes */ DELALL(&g); igraph_cattribute_list(&g, &gnames, >ypes, &vnames, &vtypes, &enames, &etypes); if (igraph_strvector_size(&gnames) != 0 || igraph_strvector_size(&vnames) != 0 || igraph_strvector_size(&enames) != 0) { return 25; } /* Destroy */ igraph_vector_destroy(>ypes); igraph_vector_destroy(&vtypes); igraph_vector_destroy(&etypes); igraph_strvector_destroy(&gnames); igraph_strvector_destroy(&vnames); igraph_strvector_destroy(&enames); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/lineendings.c0000644000076500000240000000356313612122634026370 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; FILE *ifile; /* turn on attribute handling */ /* igraph_i_set_attribute_table(&igraph_cattribute_table); */ ifile = fopen("pajek1.net", "r"); if (ifile == 0) { return 1; } igraph_read_graph_pajek(&g, ifile); fclose(ifile); igraph_write_graph_pajek(&g, stdout); igraph_destroy(&g); ifile = fopen("pajek2.net", "r"); if (ifile == 0) { return 2; } igraph_read_graph_pajek(&g, ifile); fclose(ifile); igraph_write_graph_pajek(&g, stdout); igraph_destroy(&g); ifile = fopen("pajek3.net", "r"); if (ifile == 0) { return 3; } igraph_read_graph_pajek(&g, ifile); fclose(ifile); igraph_write_graph_pajek(&g, stdout); igraph_destroy(&g); ifile = fopen("pajek4.net", "r"); if (ifile == 0) { return 4; } igraph_read_graph_pajek(&g, ifile); fclose(ifile); igraph_write_graph_pajek(&g, stdout); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_sparsemat.out0000644000076500000240000000714413524616144030014 0ustar tamasstaff000000000000001 0 : 1 0 1 : 1 2 1 : 1 1 2 : 1 3 2 : 1 2 3 : 1 4 3 : 1 3 4 : 1 5 4 : 1 4 5 : 1 6 5 : 1 5 6 : 1 7 6 : 1 6 7 : 1 8 7 : 1 7 8 : 1 9 8 : 1 8 9 : 1 9 0 : 1 0 9 : 1 col 0: locations 0 to 1 1 : 1 9 : 1 col 1: locations 2 to 3 0 : 1 2 : 1 col 2: locations 4 to 5 1 : 1 3 : 1 col 3: locations 6 to 7 2 : 1 4 : 1 col 4: locations 8 to 9 3 : 1 5 : 1 col 5: locations 10 to 11 4 : 1 6 : 1 col 6: locations 12 to 13 5 : 1 7 : 1 col 7: locations 14 to 15 6 : 1 8 : 1 col 8: locations 16 to 17 7 : 1 9 : 1 col 9: locations 18 to 19 8 : 1 0 : 1 ------------------------ 0 0 : 1 1 1 : 1 2 2 : 1 3 3 : 1 4 4 : 1 col 0: locations 0 to 0 0 : 1 col 1: locations 1 to 1 1 : 1 col 2: locations 2 to 2 2 : 1 col 3: locations 3 to 3 3 : 1 col 4: locations 4 to 4 4 : 1 ------------------------ 0 0 : 0 1 1 : 1 2 2 : 2 3 3 : 3 4 4 : 4 col 0: locations 0 to 0 0 : 0 col 1: locations 1 to 1 1 : 1 col 2: locations 2 to 2 2 : 2 col 3: locations 3 to 3 3 : 3 col 4: locations 4 to 4 4 : 4 ------------------------ col 0: locations 0 to -1 col 1: locations 0 to 0 0 : 1 col 2: locations 1 to 1 0 : 1 col 3: locations 2 to 2 1 : 1 col 4: locations 3 to 3 1 : 1 col 5: locations 4 to 4 2 : 1 col 6: locations 5 to 5 2 : 1 col 7: locations 6 to 6 3 : 1 col 8: locations 7 to 7 3 : 1 col 9: locations 8 to 8 4 : 1 col 0: locations 0 to 1 1 : 1 2 : 1 col 1: locations 2 to 3 3 : 1 4 : 1 col 2: locations 4 to 5 5 : 1 6 : 1 col 3: locations 6 to 7 7 : 1 8 : 1 col 4: locations 8 to 8 9 : 1 col 5: locations 9 to 8 col 6: locations 9 to 8 col 7: locations 9 to 8 col 8: locations 9 to 8 col 9: locations 9 to 8 ------------------------ 0 1 : 1 0 2 : 1 0 3 : 1 0 4 : 1 0 5 : 1 0 6 : 1 0 7 : 1 0 8 : 1 0 9 : 1 0 1 : 1 0 2 : 1 0 3 : 1 0 4 : 1 0 5 : 1 0 6 : 1 0 7 : 1 0 8 : 1 0 9 : 1 col 0: locations 0 to -1 col 1: locations 0 to 1 0 : 1 0 : 1 col 2: locations 2 to 3 0 : 1 0 : 1 col 3: locations 4 to 5 0 : 1 0 : 1 col 4: locations 6 to 7 0 : 1 0 : 1 col 5: locations 8 to 9 0 : 1 0 : 1 col 6: locations 10 to 11 0 : 1 0 : 1 col 7: locations 12 to 13 0 : 1 0 : 1 col 8: locations 14 to 15 0 : 1 0 : 1 col 9: locations 16 to 17 0 : 1 0 : 1 col 0: locations 0 to -1 col 1: locations 0 to 0 0 : 2 col 2: locations 1 to 1 0 : 2 col 3: locations 2 to 2 0 : 2 col 4: locations 3 to 3 0 : 2 col 5: locations 4 to 4 0 : 2 col 6: locations 5 to 5 0 : 2 col 7: locations 6 to 6 0 : 2 col 8: locations 7 to 7 0 : 2 col 9: locations 8 to 8 0 : 2 ------------------------ 7 3 : 0 0 1 : 1 0 1 : 0 0 2 : 1 0 2 : 0 0 3 : 1 0 3 : 0 0 4 : 1 0 4 : 0 0 5 : 1 0 5 : 0 0 6 : 1 0 6 : 0 0 7 : 1 0 7 : 0 0 8 : 1 0 8 : 0 0 9 : 1 0 9 : 0 0 0 : 0 col 0: locations 0 to 0 0 : 0 col 1: locations 1 to 2 0 : 1 0 : 0 col 2: locations 3 to 4 0 : 1 0 : 0 col 3: locations 5 to 7 7 : 0 0 : 1 0 : 0 col 4: locations 8 to 9 0 : 1 0 : 0 col 5: locations 10 to 11 0 : 1 0 : 0 col 6: locations 12 to 13 0 : 1 0 : 0 col 7: locations 14 to 15 0 : 1 0 : 0 col 8: locations 16 to 17 0 : 1 0 : 0 col 9: locations 18 to 19 0 : 1 0 : 0 col 0: locations 0 to -1 col 1: locations 0 to 0 0 : 1 col 2: locations 1 to 1 0 : 1 col 3: locations 2 to 2 0 : 1 col 4: locations 3 to 3 0 : 1 col 5: locations 4 to 4 0 : 1 col 6: locations 5 to 5 0 : 1 col 7: locations 6 to 6 0 : 1 col 8: locations 7 to 7 0 : 1 col 9: locations 8 to 8 0 : 1 ------------------------ col 0: locations 0 to 1 1 : 2 9 : 2 col 1: locations 2 to 3 0 : 3 2 : 2 col 2: locations 4 to 6 0 : 1 1 : 2 3 : 2 col 3: locations 7 to 9 0 : 1 2 : 2 4 : 2 col 4: locations 10 to 12 0 : 1 3 : 2 5 : 2 col 5: locations 13 to 15 0 : 1 4 : 2 6 : 2 col 6: locations 16 to 18 0 : 1 5 : 2 7 : 2 col 7: locations 19 to 21 0 : 1 6 : 2 8 : 2 col 8: locations 22 to 24 0 : 1 7 : 2 9 : 2 col 9: locations 25 to 26 0 : 3 8 : 2 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_sparsemat5.c0000644000076500000240000002755613612122634027517 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #define EPS 1e-13 /* Generic test for 1x1 matrices */ void test_1x1(igraph_real_t value) { igraph_sparsemat_t A, B; igraph_matrix_t values, vectors; igraph_vector_t values2; igraph_arpack_options_t options; igraph_arpack_options_init(&options); igraph_sparsemat_init(&A, 1, 1, 1); igraph_sparsemat_entry(&A, 0, 0, value); igraph_sparsemat_compress(&A, &B); igraph_sparsemat_destroy(&A); igraph_matrix_init(&values, 0, 0); igraph_matrix_init(&vectors, 0, 0); options.mode = 1; igraph_sparsemat_arpack_rnsolve(&B, &options, /*storage=*/ 0, &values, &vectors); printf("rnsolve:\n - eigenvalues:\n "); igraph_matrix_print(&values); printf(" - eigenvectors:\n "); igraph_matrix_print(&vectors); igraph_matrix_destroy(&values); igraph_matrix_destroy(&vectors); igraph_vector_init(&values2, 0); igraph_matrix_init(&vectors, 0, 0); options.mode = 1; igraph_sparsemat_arpack_rssolve(&B, &options, /*storage=*/ 0, &values2, &vectors, IGRAPH_SPARSEMAT_SOLVE_LU); printf("rssolve:\n - eigenvalues:\n "); igraph_vector_print(&values2); printf(" - eigenvectors:\n "); igraph_matrix_print(&vectors); igraph_vector_destroy(&values2); igraph_matrix_destroy(&vectors); igraph_sparsemat_destroy(&B); } /* Generic test for 2x2 matrices */ void test_2x2(igraph_real_t a, igraph_real_t b, igraph_real_t c, igraph_real_t d) { igraph_sparsemat_t A, B; igraph_matrix_t values, vectors; igraph_vector_t values2; igraph_arpack_options_t options; igraph_arpack_options_init(&options); options.mode = 1; options.nev = 2; igraph_sparsemat_init(&A, 2, 2, 4); igraph_sparsemat_entry(&A, 0, 0, a); igraph_sparsemat_entry(&A, 0, 1, b); igraph_sparsemat_entry(&A, 1, 0, c); igraph_sparsemat_entry(&A, 1, 1, d); igraph_sparsemat_compress(&A, &B); igraph_sparsemat_destroy(&A); igraph_matrix_init(&values, 0, 0); igraph_matrix_init(&vectors, 0, 0); igraph_sparsemat_arpack_rnsolve(&B, &options, /*storage=*/ 0, &values, &vectors); printf("rnsolve:\n - eigenvalues:\n "); igraph_matrix_print(&values); printf(" - eigenvectors:\n "); igraph_matrix_print(&vectors); igraph_matrix_destroy(&values); igraph_matrix_destroy(&vectors); if (b == c) { igraph_vector_init(&values2, 0); igraph_matrix_init(&vectors, 0, 0); igraph_sparsemat_arpack_rssolve(&B, &options, /*storage=*/ 0, &values2, &vectors, IGRAPH_SPARSEMAT_SOLVE_QR); printf("rssolve:\n - eigenvalues:\n "); igraph_vector_print(&values2); printf(" - eigenvectors:\n "); igraph_matrix_print(&vectors); igraph_vector_destroy(&values2); igraph_matrix_destroy(&vectors); } igraph_sparsemat_destroy(&B); } int main() { igraph_sparsemat_t A, B; igraph_matrix_t vectors, values2; igraph_vector_t values; long int i; igraph_arpack_options_t options; igraph_real_t min, max; igraph_t g1, g2, g3; /***********************************************************************/ /* Identity matrix */ #define DIM 10 igraph_sparsemat_init(&A, DIM, DIM, DIM); for (i = 0; i < DIM; i++) { igraph_sparsemat_entry(&A, i, i, 1.0); } igraph_sparsemat_compress(&A, &B); igraph_sparsemat_destroy(&A); igraph_vector_init(&values, 0); igraph_arpack_options_init(&options); options.mode = 1; igraph_sparsemat_arpack_rssolve(&B, &options, /*storage=*/ 0, &values, /*vectors=*/ 0, /*solvemethod=*/0); if (VECTOR(values)[0] != 1.0) { return 1; } options.mode = 3; options.sigma = 2; igraph_sparsemat_arpack_rssolve(&B, &options, /*storage=*/ 0, &values, /*vectors=*/ 0, IGRAPH_SPARSEMAT_SOLVE_LU); if (VECTOR(values)[0] != 1.0) { return 21; } igraph_sparsemat_arpack_rssolve(&B, &options, /*storage=*/ 0, &values, /*vectors=*/ 0, IGRAPH_SPARSEMAT_SOLVE_QR); if (VECTOR(values)[0] != 1.0) { return 31; } igraph_vector_destroy(&values); igraph_sparsemat_destroy(&B); #undef DIM /***********************************************************************/ /* Diagonal matrix */ #define DIM 10 igraph_sparsemat_init(&A, DIM, DIM, DIM); for (i = 0; i < DIM; i++) { igraph_sparsemat_entry(&A, i, i, i + 1.0); } igraph_sparsemat_compress(&A, &B); igraph_sparsemat_destroy(&A); igraph_vector_init(&values, 0); igraph_matrix_init(&vectors, 0, 0); options.mode = 1; igraph_sparsemat_arpack_rssolve(&B, &options, /*storage=*/ 0, &values, /*vectors=*/ &vectors, /*solvemethod=*/ 0); if ( fabs(VECTOR(values)[0] - DIM) > EPS ) { printf("VECTOR(values)[0] numerical precision is only %g, should be %g", fabs((double)VECTOR(values)[0] - DIM), EPS); return 2; } if ( fabs(fabs(MATRIX(vectors, DIM - 1, 0)) - 1.0) > EPS) { return 3; } MATRIX(vectors, DIM - 1, 0) = 0.0; igraph_matrix_minmax(&vectors, &min, &max); if (fabs(min) > EPS) { return 3; } if (fabs(max) > EPS) { return 3; } options.mode = 3; options.sigma = 11; igraph_sparsemat_arpack_rssolve(&B, &options, /*storage=*/ 0, &values, /*vectors=*/ &vectors, IGRAPH_SPARSEMAT_SOLVE_LU); if ( fabs(VECTOR(values)[0] - DIM) > EPS ) { printf("VECTOR(values)[0] numerical precision is only %g, should be %g", fabs((double)VECTOR(values)[0] - DIM), EPS); return 22; } igraph_sparsemat_arpack_rssolve(&B, &options, /*storage=*/ 0, &values, /*vectors=*/ &vectors, IGRAPH_SPARSEMAT_SOLVE_QR); if ( fabs(VECTOR(values)[0] - DIM) > EPS ) { printf("VECTOR(values)[0] numerical precision is only %g, should be %g", fabs((double)VECTOR(values)[0] - DIM), EPS); return 32; } if ( fabs(fabs(MATRIX(vectors, DIM - 1, 0)) - 1.0) > EPS) { return 23; } MATRIX(vectors, DIM - 1, 0) = 0.0; igraph_matrix_minmax(&vectors, &min, &max); if (fabs(min) > EPS) { return 23; } if (fabs(max) > EPS) { return 23; } igraph_vector_destroy(&values); igraph_matrix_destroy(&vectors); igraph_sparsemat_destroy(&B); #undef DIM /***********************************************************************/ /* A tree, plus a ring */ #define DIM 10 igraph_tree(&g1, DIM, /*children=*/ 2, IGRAPH_TREE_UNDIRECTED); igraph_ring(&g2, DIM, IGRAPH_UNDIRECTED, /*mutual=*/ 0, /*circular=*/ 1); igraph_union(&g3, &g1, &g2, /*edge_map1=*/ 0, /*edge_map1=*/ 0); igraph_destroy(&g1); igraph_destroy(&g2); igraph_get_sparsemat(&g3, &A); igraph_destroy(&g3); igraph_sparsemat_compress(&A, &B); igraph_sparsemat_destroy(&A); igraph_vector_init(&values, 0); igraph_matrix_init(&vectors, 0, 0); options.mode = 1; igraph_sparsemat_arpack_rssolve(&B, &options, /*storage=*/ 0, &values, &vectors, /*solvemethod=*/ 0); if (MATRIX(vectors, 0, 0) < 0.0) { igraph_matrix_scale(&vectors, -1.0); } igraph_vector_print(&values); igraph_matrix_print(&vectors); options.mode = 3; options.sigma = VECTOR(values)[0] * 1.1; igraph_sparsemat_arpack_rssolve(&B, &options, /*storage=*/ 0, &values, &vectors, IGRAPH_SPARSEMAT_SOLVE_LU); if (MATRIX(vectors, 0, 0) < 0.0) { igraph_matrix_scale(&vectors, -1.0); } igraph_vector_print(&values); igraph_matrix_print(&vectors); igraph_sparsemat_arpack_rssolve(&B, &options, /*storage=*/ 0, &values, &vectors, IGRAPH_SPARSEMAT_SOLVE_QR); if (MATRIX(vectors, 0, 0) < 0.0) { igraph_matrix_scale(&vectors, -1.0); } igraph_vector_print(&values); igraph_matrix_print(&vectors); igraph_vector_destroy(&values); igraph_matrix_destroy(&vectors); igraph_sparsemat_destroy(&B); #undef DIM printf("--\n"); /***********************************************************************/ /* A directed tree and a directed, mutual ring */ #define DIM 10 igraph_tree(&g1, DIM, /*children=*/ 2, IGRAPH_TREE_OUT); igraph_ring(&g2, DIM, IGRAPH_DIRECTED, /*mutual=*/ 1, /*circular=*/ 1); igraph_union(&g3, &g1, &g2, /*edge_map1=*/ 0, /*edge_map2=*/ 0); igraph_destroy(&g1); igraph_destroy(&g2); igraph_get_sparsemat(&g3, &A); igraph_destroy(&g3); igraph_sparsemat_compress(&A, &B); igraph_sparsemat_destroy(&A); igraph_matrix_init(&values2, 0, 0); igraph_matrix_init(&vectors, 0, 0); options.mode = 1; igraph_sparsemat_arpack_rnsolve(&B, &options, /*storage=*/ 0, &values2, &vectors); if (MATRIX(vectors, 0, 0) < 0.0) { igraph_matrix_scale(&vectors, -1.0); } igraph_matrix_print(&values2); igraph_matrix_print(&vectors); igraph_matrix_destroy(&values2); igraph_matrix_destroy(&vectors); igraph_sparsemat_destroy(&B); #undef DIM /***********************************************************************/ /* A small test graph */ igraph_small(&g1, 11, IGRAPH_DIRECTED, 0, 1, 1, 3, 1, 8, 2, 10, 3, 6, 3, 10, 4, 2, 5, 4, 6, 1, 6, 4, 7, 9, 8, 5, 8, 7, 9, 8, 10, 0, -1); igraph_get_sparsemat(&g1, &A); igraph_destroy(&g1); igraph_sparsemat_compress(&A, &B); igraph_sparsemat_destroy(&A); igraph_matrix_init(&values2, 0, 0); igraph_matrix_init(&vectors, 0, 0); options.mode = 1; igraph_sparsemat_arpack_rnsolve(&B, &options, /*storage=*/ 0, &values2, &vectors); if (MATRIX(vectors, 0, 0) < 0.0) { igraph_matrix_scale(&vectors, -1.0); } igraph_matrix_destroy(&values2); igraph_matrix_destroy(&vectors); igraph_sparsemat_destroy(&B); /***********************************************************************/ /* Testing the special case solver for 1x1 matrices */ printf("--\n"); test_1x1(2); test_1x1(0); test_1x1(-3); /***********************************************************************/ /* Testing the special case solver for 2x2 matrices */ printf("--\n"); test_2x2(1, 2, 2, 4); /* symmetric */ test_2x2(1, 2, 3, 4); /* non-symmetric, real eigenvalues */ test_2x2(1, -5, 10, 4); /* non-symmetric, complex eigenvalues */ test_2x2(0, 0, 0, 0); /* symmetric, pathological */ return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_community_leading_eigenvector2.c0000644000076500000240000001023313612122633033575 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int print_vector(const igraph_vector_t *v) { long int i, n = igraph_vector_size(v); for (i = 0; i < n; i++) { printf("%.2g", (double)VECTOR(*v)[i]); if (i != n - 1) { printf(" "); } } printf("\n"); return 0; } int print_matrix(const igraph_matrix_t *m) { long int i, j, nrow = igraph_matrix_nrow(m), ncol = igraph_matrix_ncol(m); for (i = 0; i < nrow; i++) { for (j = 0; j < ncol; j++) { printf("%.2g", (double)MATRIX(*m, i, j)); if (j != ncol - 1) { printf(" "); } } printf("\n"); } return 0; } int main() { igraph_t g; igraph_matrix_t merges; igraph_vector_t membership; igraph_vector_t x; igraph_arpack_options_t options; igraph_vector_t weights; /* Zachary Karate club */ igraph_small(&g, 0, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 0, 7, 0, 8, 0, 10, 0, 11, 0, 12, 0, 13, 0, 17, 0, 19, 0, 21, 0, 31, 1, 2, 1, 3, 1, 7, 1, 13, 1, 17, 1, 19, 1, 21, 1, 30, 2, 3, 2, 7, 2, 8, 2, 9, 2, 13, 2, 27, 2, 28, 2, 32, 3, 7, 3, 12, 3, 13, 4, 6, 4, 10, 5, 6, 5, 10, 5, 16, 6, 16, 8, 30, 8, 32, 8, 33, 9, 33, 13, 33, 14, 32, 14, 33, 15, 32, 15, 33, 18, 32, 18, 33, 19, 33, 20, 32, 20, 33, 22, 32, 22, 33, 23, 25, 23, 27, 23, 29, 23, 32, 23, 33, 24, 25, 24, 27, 24, 31, 25, 31, 26, 29, 26, 33, 27, 33, 28, 31, 28, 33, 29, 32, 29, 33, 30, 32, 30, 33, 31, 32, 31, 33, 32, 33, -1); igraph_matrix_init(&merges, 0, 0); igraph_vector_init(&membership, 0); igraph_vector_init(&x, 0); igraph_arpack_options_init(&options); igraph_vector_init(&weights, igraph_ecount(&g)); igraph_vector_fill(&weights, 1); igraph_community_leading_eigenvector(&g, &weights, &merges, &membership, 1, &options, /*modularity=*/ 0, /*start=*/ 0, /*eigenvalues=*/ 0, /*eigenvectors=*/ 0, /*history=*/ 0, /*callback=*/ 0, /*callback_extra=*/ 0); print_matrix(&merges); print_vector(&membership); printf("\n"); /* Make all the steps */ igraph_community_leading_eigenvector(&g, &weights, &merges, &membership, igraph_vcount(&g), &options, /*modularity=*/ 0, /*start=*/ 0, /*eigenvalues=*/ 0, /*eigenvectors=*/ 0, /*history=*/ 0, /*callback=*/ 0, /*callback_extra=*/ 0); print_matrix(&merges); print_vector(&membership); igraph_vector_destroy(&weights); igraph_vector_destroy(&x); igraph_vector_destroy(&membership); igraph_matrix_destroy(&merges); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/biguint.out0000644000076500000240000000002613524616144026114 0ustar tamasstaff000000000000004294967295 8589934590 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_create.c0000644000076500000240000000446713612122633026671 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_vector_t v1, v2; int ret; /* simple use */ igraph_vector_init(&v1, 8); VECTOR(v1)[0] = 0; VECTOR(v1)[1] = 1; VECTOR(v1)[2] = 1; VECTOR(v1)[3] = 2; VECTOR(v1)[4] = 2; VECTOR(v1)[5] = 3; VECTOR(v1)[6] = 2; VECTOR(v1)[7] = 2; igraph_create(&g, &v1, 0, 0); if (igraph_vcount(&g) != 4) { return 1; } igraph_vector_init(&v2, 0); igraph_get_edgelist(&g, &v2, 0); igraph_vector_sort(&v1); igraph_vector_sort(&v2); if (!igraph_vector_all_e(&v1, &v2)) { return 2; } igraph_destroy(&g); /* higher number of vertices */ igraph_create(&g, &v1, 10, 0); if (igraph_vcount(&g) != 10) { return 1; } igraph_get_edgelist(&g, &v2, 0); igraph_vector_sort(&v1); igraph_vector_sort(&v2); if (!igraph_vector_all_e(&v1, &v2)) { return 3; } igraph_destroy(&g); /* error: IGRAPH_EINVEVECTOR */ igraph_set_error_handler(igraph_error_handler_ignore); igraph_vector_resize(&v1, 9); VECTOR(v1)[8] = 0; ret = igraph_create(&g, &v1, 0, 0); if (ret != IGRAPH_EINVEVECTOR) { return 4; } /* error: IGRAPH_EINVVID */ igraph_vector_resize(&v1, 8); VECTOR(v1)[7] = -1; ret = igraph_create(&g, &v1, 10, 1); if (ret != IGRAPH_EINVVID) { return 5; } igraph_vector_destroy(&v1); igraph_vector_destroy(&v2); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/dot.out0000644000076500000240000000301213524616144025237 0ustar tamasstaff00000000000000undirected 0 1 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 10 0 11 0 12 0 13 0 17 0 19 0 21 0 31 1 2 1 3 1 7 1 13 1 17 1 19 1 21 1 30 2 3 2 7 2 8 2 9 2 13 2 27 2 28 2 32 3 7 3 12 3 13 4 6 4 10 5 6 5 10 5 16 6 16 8 30 8 32 8 33 9 33 13 33 14 32 14 33 15 32 15 33 18 32 18 33 19 33 20 32 20 33 22 32 22 33 23 25 23 27 23 29 23 32 23 33 24 25 24 27 24 31 25 31 26 29 26 33 27 33 28 31 28 33 29 32 29 33 30 32 30 33 31 32 31 33 32 33 ----------------- /* Created by igraph @VERSION@ */ graph { 0; 1; 2; 3; 4; 5; 6; 7; 8; 9; 10; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23; 24; 25; 26; 27; 28; 29; 30; 31; 32; 33; 1 -- 0; 2 -- 0; 2 -- 1; 3 -- 0; 3 -- 1; 3 -- 2; 4 -- 0; 5 -- 0; 6 -- 0; 6 -- 4; 6 -- 5; 7 -- 0; 7 -- 1; 7 -- 2; 7 -- 3; 8 -- 0; 8 -- 2; 9 -- 2; 10 -- 0; 10 -- 4; 10 -- 5; 11 -- 0; 12 -- 0; 12 -- 3; 13 -- 0; 13 -- 1; 13 -- 2; 13 -- 3; 16 -- 5; 16 -- 6; 17 -- 0; 17 -- 1; 19 -- 0; 19 -- 1; 21 -- 0; 21 -- 1; 25 -- 23; 25 -- 24; 27 -- 2; 27 -- 23; 27 -- 24; 28 -- 2; 29 -- 23; 29 -- 26; 30 -- 1; 30 -- 8; 31 -- 0; 31 -- 24; 31 -- 25; 31 -- 28; 32 -- 2; 32 -- 8; 32 -- 14; 32 -- 15; 32 -- 18; 32 -- 20; 32 -- 22; 32 -- 23; 32 -- 29; 32 -- 30; 32 -- 31; 33 -- 8; 33 -- 9; 33 -- 13; 33 -- 14; 33 -- 15; 33 -- 18; 33 -- 19; 33 -- 20; 33 -- 22; 33 -- 23; 33 -- 26; 33 -- 27; 33 -- 28; 33 -- 29; 33 -- 30; 33 -- 31; 33 -- 32; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_mincut.c0000644000076500000240000000714213612122633026716 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int print_mincut(const igraph_t *graph, igraph_real_t value, const igraph_vector_t *partition, const igraph_vector_t *partition2, const igraph_vector_t *cut, const igraph_vector_t *capacity) { long int i, nc = igraph_vector_size(cut); igraph_bool_t directed = igraph_is_directed(graph); printf("mincut value: %g\n", (double) value); printf("first partition: "); igraph_vector_print(partition); printf("second partition: "); igraph_vector_print(partition2); printf("edges in the cut: "); for (i = 0; i < nc; i++) { long int edge = VECTOR(*cut)[i]; long int from = IGRAPH_FROM(graph, edge); long int to = IGRAPH_TO (graph, edge); if (!directed && from > to) { igraph_integer_t tmp = from; from = to; to = tmp; } printf("%li-%li (%g), ", from, to, VECTOR(*capacity)[edge]); } printf("\n"); return 0; } int main() { igraph_t g; igraph_vector_t weights, partition, partition2, cut; igraph_real_t value; igraph_vector_init(&partition, 0); igraph_vector_init(&partition2, 0); igraph_vector_init(&cut, 0); /* -------------------------------------------- */ igraph_small(&g, 0, IGRAPH_UNDIRECTED, 0, 1, 0, 4, 1, 2, 1, 4, 1, 5, 2, 3, 2, 6, 3, 6, 3, 7, 4, 5, 5, 6, 6, 7, -1); igraph_vector_init_int_end(&weights, -1, 2, 3, 3, 2, 2, 4, 2, 2, 2, 3, 1, 3, -1); igraph_mincut(&g, &value, &partition, &partition2, &cut, &weights); print_mincut(&g, value, &partition, &partition2, &cut, &weights); igraph_vector_destroy(&weights); igraph_destroy(&g); /* -------------------------------------------- */ igraph_small(&g, 6, IGRAPH_DIRECTED, 0, 1, 1, 2, 2, 3, 0, 5, 5, 4, 4, 3, 3, 0, -1); igraph_vector_init_int_end(&weights, -1, 3, 1, 2, 10, 1, 3, 2, -1); igraph_mincut(&g, &value, &partition, &partition2, &cut, &weights); print_mincut(&g, value, &partition, &partition2, &cut, &weights); igraph_vector_destroy(&weights); igraph_destroy(&g); /* -------------------------------------------- */ igraph_small(&g, 5, IGRAPH_DIRECTED, 4, 3, 3, 2, 2, 1, 1, 0, -1); igraph_vector_init_int_end(&weights, -1, 1, 1, 1, 1, -1); igraph_mincut(&g, &value, &partition, &partition2, &cut, &weights); print_mincut(&g, value, &partition, &partition2, &cut, &weights); igraph_vector_destroy(&weights); igraph_destroy(&g); /* -------------------------------------------- */ igraph_vector_destroy(&cut); igraph_vector_destroy(&partition2); igraph_vector_destroy(&partition); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_delete_vertices.c0000644000076500000240000000402013612122633030555 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_vector_t v; int ret; /* without edges */ igraph_empty(&g, 5, IGRAPH_DIRECTED); igraph_add_vertices(&g, 2, 0); igraph_add_vertices(&g, 3, 0); igraph_add_vertices(&g, 1, 0); igraph_add_vertices(&g, 4, 0); if (igraph_vcount(&g) != 15) { return 1; } igraph_delete_vertices(&g, igraph_vss_1(2)); if (igraph_vcount(&g) != 14) { return 2; } igraph_destroy(&g); igraph_vector_init(&v, 8); VECTOR(v)[0] = 0; VECTOR(v)[1] = 1; VECTOR(v)[2] = 1; VECTOR(v)[3] = 2; VECTOR(v)[4] = 2; VECTOR(v)[5] = 3; VECTOR(v)[6] = 2; VECTOR(v)[7] = 2; igraph_create(&g, &v, 0, 0); igraph_vector_destroy(&v); /* resize vector */ igraph_delete_vertices(&g, igraph_vss_1(2)); if (igraph_vcount(&g) != 3) { return 3; } if (igraph_ecount(&g) != 1) { return 4; } /* error test */ igraph_set_error_handler(igraph_error_handler_ignore); ret = igraph_delete_vertices(&g, igraph_vss_1(3)); if (ret != IGRAPH_EINVVID) { return 5; } igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_layout_sugiyama.out0000644000076500000240000000105013524616144031217 0ustar tamasstaff000000000000002.5 0 0.5 1 2.5 1 4 2 0 3 2 3 0 4 2 4 2 5 4 1 0 2 2 2 4 3 4 4 1 2 1 3 1 4 3 2 3 3 3 4 === 2.5 0 0.5 1 2.5 1 4 2 0 3 2 3 0 4 2 4 2 5 4 1 0 2 2 2 4 3 4 4 1 2 1 3 1 4 3 2 3 3 3 4 === 0 1 0 2 0 9 9 3 1 2 1 10 10 4 2 2 2 11 11 5 3 12 12 13 13 8 4 6 5 7 6 8 7 8 8 16 16 15 15 14 14 1 8 19 19 18 18 17 17 2 === 0 1 2 2 3 5 5 4 6 6 11 11 11 7 8 9 10 12 12 12 12 13 13 13 13 === 2.5 0 1 1 2.5 2 4 1 0 2 2 3 0 3 2 4 2 5 2.5 1 4 2 4 3 4 4 0 4 1 2 1 3 1 4 3 3 3 4 === 2.5 0 0.5 2 2.5 2 4 4 0 6 2 6 0 12 2 12 2 15 4 2 0 4 2 4 4 6 4 12 1 4 1 6 1 12 3 4 3 6 3 12 === python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_moran_process.c0000644000076500000240000002070413612122633030270 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* Test suite for the Moran process in a network setting. Copyright (C) 2011 Minh Van Nguyen This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include /* test parameters structure */ typedef struct { igraph_t *graph; igraph_vector_t *weights; igraph_vector_t *quantities; igraph_vector_t *strategies; igraph_neimode_t mode; int retval; } strategy_test_t; /* Error tests, i.e. we expect errors to be raised for each test. */ int error_tests() { igraph_t g, gzero, h; igraph_vector_t quant, quantnvert, quantzero; igraph_vector_t strat, stratnvert, stratzero; igraph_vector_t wgt, wgtnedge, wgtzero; int i, n, nvert, ret; strategy_test_t *test; igraph_empty(&h, 0, 0); /* empty graph */ /* nonempty graph */ igraph_small(&g, /*nvert=*/ 0, IGRAPH_UNDIRECTED, 0, 1, 1, 2, 2, 0, -1); nvert = igraph_vcount(&g); /* weights vectors */ igraph_vector_init(&wgt, 0); igraph_vector_init(&wgtnedge, igraph_ecount(&g)); /* quantities vectors */ igraph_vector_init(&quant, 1); igraph_vector_init_real(&quantnvert, nvert, 0.1, 0.2, 0.3); /* strategies vectors */ igraph_vector_init(&strat, 2); igraph_vector_init_real(&stratnvert, nvert, 0.0, 1.0, 2.0); igraph_small(&gzero, /*nvert=*/ 0, IGRAPH_UNDIRECTED, 0, 3, 0, 4, 1, 2, 1, 4, 1, 5, 2, 3, 2, 4, 3, 4, -1); nvert = igraph_vcount(&gzero); igraph_vector_init(&quantzero, nvert); /* vector of zeros */ igraph_vector_init(&stratzero, nvert); /* vector of zeros */ igraph_vector_init(&wgtzero, igraph_ecount(&gzero)); /* vector of zeros */ /* igraph_vector_init_real(&stratzero, nvert, 1.0, 0.0, 1.0, 2.0, 0.0, 3.0); */ /* test parameters */ /*------graph--weights--quantities--strategies--mode--retval------*/ /* null pointer for graph */ strategy_test_t null_graph = {NULL, NULL, NULL, NULL, IGRAPH_ALL, IGRAPH_EINVAL}; /* null pointer for weights vector */ strategy_test_t null_wgt = {&g, NULL, &quantnvert, &stratnvert, IGRAPH_ALL, IGRAPH_EINVAL}; /* null pointer for quantities vector */ strategy_test_t null_quant = {&g, &wgt, NULL, NULL, IGRAPH_ALL, IGRAPH_EINVAL}; /* null pointer for strategies vector */ strategy_test_t null_strat = {&g, &wgt, &quant, NULL, IGRAPH_ALL, IGRAPH_EINVAL}; /* empty graph */ strategy_test_t empty_graph = {&h, &wgt, &quant, &strat, IGRAPH_ALL, IGRAPH_EINVAL}; /* length of quantities vector different from number of vertices */ strategy_test_t qdiff_length = {&g, &wgtnedge, &quant, &strat, IGRAPH_ALL, IGRAPH_EINVAL}; /* length of strategies vector different from number of vertices */ strategy_test_t sdiff_length = {&g, &wgtnedge, &quantnvert, &strat, IGRAPH_ALL, IGRAPH_EINVAL}; /* length of weights vector different from number of edges */ strategy_test_t wdiff_length = {&g, &wgt, &quantnvert, &stratnvert, IGRAPH_ALL, IGRAPH_EINVAL}; /* weights vector contains all zeros */ strategy_test_t zero_wgt = {&g, &wgtnedge, &quantnvert, &stratnvert, IGRAPH_ALL, IGRAPH_EINVAL}; /* quantities vector contains all zeros */ strategy_test_t zero_quant = {&gzero, &wgtzero, &quantzero, &stratzero, IGRAPH_ALL, IGRAPH_EINVAL}; strategy_test_t *all_checks[] = {/* 1 */ &null_graph, /* 2 */ &null_quant, /* 3 */ &null_strat, /* 4 */ &null_wgt, /* 5 */ &empty_graph, /* 6 */ &qdiff_length, /* 7 */ &sdiff_length, /* 8 */ &wdiff_length, /* 9 */ &zero_quant, /* 10 */ &zero_wgt }; /* Run the error tests. We expect error to be raised for each test. */ igraph_set_error_handler(igraph_error_handler_ignore); n = 10; i = 0; while (i < n) { test = all_checks[i]; ret = igraph_moran_process(test->graph, test->weights, test->quantities, test->strategies, test->mode); if (ret != test->retval) { printf("Error test no. %d failed.\n", (int)(i + 1)); return IGRAPH_FAILURE; } i++; } /* clean up */ igraph_destroy(&g); igraph_destroy(&gzero); igraph_destroy(&h); igraph_vector_destroy(&quant); igraph_vector_destroy(&quantnvert); igraph_vector_destroy(&quantzero); igraph_vector_destroy(&strat); igraph_vector_destroy(&stratnvert); igraph_vector_destroy(&stratzero); igraph_vector_destroy(&wgt); igraph_vector_destroy(&wgtnedge); igraph_vector_destroy(&wgtzero); return IGRAPH_SUCCESS; } /* One iteration of the Moran process on a simple digraph. */ int moran_one_test() { igraph_t g; igraph_integer_t u = -1; /* vertex chosen for reproduction */ igraph_integer_t v = -1; /* clone of u */ igraph_integer_t nedge, nvert; igraph_real_t q = 0.0; igraph_vector_t quant, quantcp; igraph_vector_t strat, stratcp; igraph_vector_t wgt; long int i; /* graph representing the game network; quantities and strategies vectors */ igraph_small(&g, /*nvert*/ 0, IGRAPH_DIRECTED, 0, 1, 0, 4, 1, 2, 1, 4, 2, 1, 3, 2, 4, 0, 4, 3, -1); nvert = igraph_vcount(&g); nedge = igraph_ecount(&g); igraph_vector_init_real(&quant, nvert, 0.77, 0.83, 0.64, 0.81, 0.05); igraph_vector_init_real(&strat, nvert, 2.0, 0.0, 0.0, 1.0, 2.0); /* Set the edge weights. Here we assume the following correspondence */ /* between edge IDs and directed edges: */ /* edge 0: 0 -> 1 */ /* edge 1: 0 -> 4 */ /* edge 2: 1 -> 2 */ /* edge 3: 1 -> 4 */ /* edge 4: 2 -> 1 */ /* edge 5: 3 -> 2 */ /* edge 6: 4 -> 0 */ /* edge 7: 4 -> 3 */ igraph_vector_init_real(&wgt, nedge, 1.9, 0.8, 6.2, 2.4, 1.1, 5.2, 7.3, 8.8); /* play game */ igraph_vector_copy(&quantcp, &quant); igraph_vector_copy(&stratcp, &strat); igraph_moran_process(&g, &wgt, &quantcp, &stratcp, IGRAPH_OUT); /* Determine which vertex was chosen for death. The original quantities */ /* vector contain unique values, i.e. no duplicates. Thus we compare the */ /* updated quantities with the original one. */ for (i = 0; i < igraph_vector_size(&quant); i++) { if (VECTOR(quant)[i] != VECTOR(quantcp)[i]) { /* found the new clone vertex */ v = (igraph_integer_t)i; q = (igraph_real_t)VECTOR(quantcp)[i]; break; } } assert(v >= 0); assert(q != 0.0); /* Now we know that v is a clone of some vertex. Determine the vertex that */ /* v is a clone of. */ for (i = 0; i < igraph_vector_size(&quant); i++) { if (VECTOR(quant)[i] == q) { /* found the vertex chosen for reproduction */ u = (igraph_integer_t)i; break; } } assert(u >= 0); /* check that v is indeed a clone of u */ if (VECTOR(quant)[u] != VECTOR(quantcp)[v]) { return IGRAPH_FAILURE; } if (VECTOR(strat)[u] != VECTOR(stratcp)[v]) { return IGRAPH_FAILURE; } igraph_destroy(&g); igraph_vector_destroy(&quant); igraph_vector_destroy(&quantcp); igraph_vector_destroy(&strat); igraph_vector_destroy(&stratcp); igraph_vector_destroy(&wgt); return IGRAPH_SUCCESS; } int main() { int ret; ret = error_tests(); if (ret) { return IGRAPH_FAILURE; } ret = moran_one_test(); if (ret) { return IGRAPH_FAILURE; } return IGRAPH_SUCCESS; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_is_minimal_separator.c0000644000076500000240000000431413612122633031616 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #define FAIL(msg, error) do { printf(msg "\n") ; return error; } while (0) int main() { igraph_t graph; igraph_vector_t sep; igraph_bool_t result; /* Simple star graph, remove the center */ igraph_star(&graph, 10, IGRAPH_STAR_UNDIRECTED, 0); igraph_is_minimal_separator(&graph, igraph_vss_1(0), &result); if (!result) { FAIL("Center of star graph failed.", 1); } /* Same graph, but another vertex */ igraph_is_minimal_separator(&graph, igraph_vss_1(6), &result); if (result) { FAIL("Non-center of star graph failed.", 2); } igraph_destroy(&graph); /* Karate club */ igraph_famous(&graph, "zachary"); igraph_vector_init(&sep, 0); igraph_vector_push_back(&sep, 32); igraph_vector_push_back(&sep, 33); igraph_is_minimal_separator(&graph, igraph_vss_vector(&sep), &result); if (!result) { FAIL("Karate network (32,33) failed", 3); } igraph_vector_resize(&sep, 5); VECTOR(sep)[0] = 8; VECTOR(sep)[1] = 9; VECTOR(sep)[2] = 19; VECTOR(sep)[3] = 30; VECTOR(sep)[4] = 31; igraph_is_minimal_separator(&graph, igraph_vss_vector(&sep), &result); if (result) { FAIL("Karate network (8,9,19,30,31) failed", 4); } igraph_destroy(&graph); igraph_vector_destroy(&sep); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/assortativity.out0000644000076500000240000000012713524616144027402 0ustar tamasstaff00000000000000-0.07775 0.00303 0.00147 -0.47561 -0.15328 -0.14996 -0.22580 -0.22580 -0.47561 0.60794 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_erdos_renyi_game.c0000644000076500000240000002255513612122633030737 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; int i; igraph_bool_t simple; /* G(n,p) */ igraph_erdos_renyi_game(&g, IGRAPH_ERDOS_RENYI_GNP, 10, 0.0, IGRAPH_UNDIRECTED, IGRAPH_NO_LOOPS); if (igraph_ecount(&g) != 0) { return 1; } if (igraph_is_directed(&g)) { return 2; } igraph_destroy(&g); igraph_erdos_renyi_game(&g, IGRAPH_ERDOS_RENYI_GNP, 10, 1.0, IGRAPH_DIRECTED, IGRAPH_NO_LOOPS); if (igraph_ecount(&g) != 10 * 9) { return 3; } if (!igraph_is_directed(&g)) { return 4; } igraph_destroy(&g); /* More useful tests */ /* printf("directed with loops\n"); */ for (i = 0; i < 100; i++) { igraph_erdos_renyi_game(&g, IGRAPH_ERDOS_RENYI_GNP, 10, 0.9999999, IGRAPH_DIRECTED, IGRAPH_LOOPS); if (igraph_vcount(&g) != 10) { return 5; } if (igraph_ecount(&g) != 10 * 10) { return 77; } igraph_simplify(&g, /*multiple=*/0, /*loops=*/1, /*edge_comb=*/ 0); if (igraph_ecount(&g) != 10 * 9) { return 77; } igraph_destroy(&g); } /* printf("directed without loops\n"); */ for (i = 0; i < 100; i++) { igraph_erdos_renyi_game(&g, IGRAPH_ERDOS_RENYI_GNP, 10, 0.9999999, IGRAPH_DIRECTED, IGRAPH_NO_LOOPS); if (igraph_vcount(&g) != 10) { return 7; } if (igraph_ecount(&g) != 10 * (10 - 1)) { return 77; } igraph_simplify(&g, /*multiple=*/0, /*loops=*/1, /*edge_comb=*/ 0); if (igraph_ecount(&g) != 10 * 9) { return 77; } igraph_destroy(&g); } /* printf("undirected with loops\n"); */ for (i = 0; i < 100; i++) { igraph_erdos_renyi_game(&g, IGRAPH_ERDOS_RENYI_GNP, 10, 0.9999999, IGRAPH_UNDIRECTED, IGRAPH_LOOPS); if (igraph_vcount(&g) != 10) { return 9; } if (igraph_ecount(&g) != 10 * (10 + 1) / 2) { return 77; } igraph_simplify(&g, /*multiple=*/0, /*loops=*/1, /*edge_comb=*/ 0); if (igraph_ecount(&g) != 10 * (10 - 1) / 2) { return 77; } igraph_destroy(&g); } /* printf("undirected without loops\n"); */ for (i = 0; i < 100; i++) { igraph_erdos_renyi_game(&g, IGRAPH_ERDOS_RENYI_GNP, 10, 0.9999999, IGRAPH_UNDIRECTED, IGRAPH_NO_LOOPS); if (igraph_vcount(&g) != 10) { return 11; } if (igraph_ecount(&g) != 10 * (10 - 1) / 2) { return 77; } igraph_simplify(&g, /*multiple=*/0, /*loops=*/1, /*edge_comb=*/ 0); if (igraph_ecount(&g) != 10 * (10 - 1) / 2) { return 77; } igraph_destroy(&g); } /* Create a couple of large graphs too */ igraph_erdos_renyi_game(&g, IGRAPH_ERDOS_RENYI_GNP, 100000, 2.0 / 100000, IGRAPH_UNDIRECTED, IGRAPH_NO_LOOPS); if (igraph_vcount(&g) != 100000) { return 25; } igraph_destroy(&g); igraph_erdos_renyi_game(&g, IGRAPH_ERDOS_RENYI_GNP, 100000, 2.0 / 100000, IGRAPH_DIRECTED, IGRAPH_NO_LOOPS); if (igraph_vcount(&g) != 100000) { return 25; } igraph_destroy(&g); igraph_erdos_renyi_game(&g, IGRAPH_ERDOS_RENYI_GNP, 100000, 2.0 / 100000, IGRAPH_UNDIRECTED, IGRAPH_LOOPS); if (igraph_vcount(&g) != 100000) { return 25; } igraph_destroy(&g); igraph_erdos_renyi_game(&g, IGRAPH_ERDOS_RENYI_GNP, 100000, 2.0 / 100000, IGRAPH_DIRECTED, IGRAPH_LOOPS); if (igraph_vcount(&g) != 100000) { return 25; } igraph_destroy(&g); /* --------------------------------------------------------------------- */ /* G(n,m) */ igraph_erdos_renyi_game(&g, IGRAPH_ERDOS_RENYI_GNM, 10, 0.5, IGRAPH_DIRECTED, IGRAPH_NO_LOOPS); igraph_destroy(&g); /* More useful tests */ /* printf("directed with loops\n"); */ for (i = 0; i < 100; i++) { long int ec; igraph_erdos_renyi_game(&g, IGRAPH_ERDOS_RENYI_GNM, 10, 10 * 10 - 1, IGRAPH_DIRECTED, IGRAPH_LOOPS); if (igraph_vcount(&g) != 10) { return 13; } if (igraph_ecount(&g) != 10 * 10 - 1) { return 14; } igraph_simplify(&g, /*multiple=*/0, /*loops=*/1, /*edge_comb=*/ 0); igraph_is_simple(&g, &simple); if (!simple) { return 27; } ec = igraph_ecount(&g); if (ec != 10 * 9 && ec != 10 * 9 - 1) { return 15; } igraph_destroy(&g); } /* printf("directed without loops\n"); */ for (i = 0; i < 100; i++) { igraph_erdos_renyi_game(&g, IGRAPH_ERDOS_RENYI_GNM, 10, 10 * 9 - 1, IGRAPH_DIRECTED, IGRAPH_NO_LOOPS); igraph_is_simple(&g, &simple); if (!simple) { return 28; } if (igraph_vcount(&g) != 10) { return 16; } if (igraph_ecount(&g) != 10 * (10 - 1) - 1) { return 17; } igraph_simplify(&g, /*multiple=*/0, /*loops=*/1, /*edge_comb=*/ 0); if (igraph_ecount(&g) != 10 * 9 - 1) { return 18; } igraph_destroy(&g); } /* printf("undirected with loops\n"); */ for (i = 0; i < 100; i++) { long int ec; igraph_erdos_renyi_game(&g, IGRAPH_ERDOS_RENYI_GNM, 10, 10 * 11 / 2 - 1, IGRAPH_UNDIRECTED, IGRAPH_LOOPS); if (igraph_vcount(&g) != 10) { return 19; } if (igraph_ecount(&g) != 10 * (10 + 1) / 2 - 1) { return 20; } igraph_simplify(&g, /*multiple=*/0, /*loops=*/1, /*edge_comb=*/ 0); igraph_is_simple(&g, &simple); if (!simple) { return 29; } ec = igraph_ecount(&g); if (ec != 10 * (10 - 1) / 2 && ec != 10 * 9 / 2 - 1) { return 21; } igraph_destroy(&g); } /* printf("undirected without loops\n"); */ for (i = 0; i < 100; i++) { igraph_erdos_renyi_game(&g, IGRAPH_ERDOS_RENYI_GNM, 10, 10 * 9 / 2 - 1, IGRAPH_UNDIRECTED, IGRAPH_NO_LOOPS); igraph_is_simple(&g, &simple); if (!simple) { return 30; } if (igraph_vcount(&g) != 10) { return 22; } if (igraph_ecount(&g) != 10 * (10 - 1) / 2 - 1) { return 23; } igraph_simplify(&g, /*multiple=*/0, /*loops=*/1, /*edge_comb=*/ 0); if (igraph_ecount(&g) != 10 * (10 - 1) / 2 - 1) { return 24; } igraph_destroy(&g); } /* Create a couple of large graphs too */ igraph_erdos_renyi_game(&g, IGRAPH_ERDOS_RENYI_GNM, 100000, 2.0 * 100000, IGRAPH_UNDIRECTED, IGRAPH_NO_LOOPS); if (igraph_vcount(&g) != 100000) { return 26; } if (igraph_ecount(&g) != 200000) { return 26; } igraph_is_simple(&g, &simple); if (!simple) { return 31; } igraph_destroy(&g); igraph_erdos_renyi_game(&g, IGRAPH_ERDOS_RENYI_GNM, 100000, 2.0 * 100000, IGRAPH_DIRECTED, IGRAPH_NO_LOOPS); igraph_is_simple(&g, &simple); if (!simple) { return 32; } if (igraph_vcount(&g) != 100000) { return 26; } if (igraph_ecount(&g) != 200000) { return 26; } igraph_destroy(&g); igraph_erdos_renyi_game(&g, IGRAPH_ERDOS_RENYI_GNM, 100000, 2.0 * 100000, IGRAPH_UNDIRECTED, IGRAPH_LOOPS); if (igraph_vcount(&g) != 100000) { return 26; } if (igraph_ecount(&g) != 200000) { return 26; } igraph_simplify(&g, 0, 1, /*edge_comb=*/ 0); /* only remove loops */ igraph_is_simple(&g, &simple); if (!simple) { return 33; } igraph_destroy(&g); igraph_erdos_renyi_game(&g, IGRAPH_ERDOS_RENYI_GNM, 100000, 2.0 * 100000, IGRAPH_DIRECTED, IGRAPH_LOOPS); if (igraph_vcount(&g) != 100000) { return 26; } if (igraph_ecount(&g) != 200000) { return 26; } igraph_simplify(&g, 0, 1, /*edge_comb=*/ 0); /* only remove loops */ igraph_is_simple(&g, &simple); if (!simple) { return 34; } igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_vs_vector.c0000644000076500000240000000442413612122634027432 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_vector_t v = IGRAPH_VECTOR_NULL; igraph_real_t edges[] = { 0, 1, 1, 2, 2, 2, 2, 3, 2, 4, 3, 4 }; igraph_vector_t v2; long int i; igraph_vit_t vit; igraph_vs_t vs; igraph_integer_t size; igraph_vector_view(&v, edges, sizeof(edges) / sizeof(igraph_real_t)); igraph_create(&g, &v, 0, IGRAPH_DIRECTED); /* Create iterator based on a vector (view) */ igraph_vector_init(&v2, 6); VECTOR(v2)[0] = 0; VECTOR(v2)[1] = 2; VECTOR(v2)[2] = 4; VECTOR(v2)[3] = 0; VECTOR(v2)[4] = 2; VECTOR(v2)[5] = 4; igraph_vit_create(&g, igraph_vss_vector(&v2), &vit); i = 0; while (!IGRAPH_VIT_END(vit)) { if (IGRAPH_VIT_GET(vit) != VECTOR(v2)[i]) { return 1; } IGRAPH_VIT_NEXT(vit); i++; } if (i != igraph_vector_size(&v2)) { return 2; } igraph_vit_destroy(&vit); igraph_vector_destroy(&v2); /* Create small vector iterator */ igraph_vs_vector_small(&vs, 0, 2, 4, 0, 2, 4, 2, -1); igraph_vit_create(&g, vs, &vit); igraph_vs_size(&g, &vs, &size); printf("%li ", (long int) size); for (; !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit)) { printf("%li ", (long int) IGRAPH_VIT_GET(vit)); } printf("\n"); igraph_vit_destroy(&vit); igraph_vs_destroy(&vs); /* Clean up */ igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/cohesive_blocks.out0000644000076500000240000000161613524616144027623 0ustar tamasstaff00000000000000Blocks: 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 0 1 2 3 4 5 6 16 17 18 19 20 21 22 6 7 8 9 10 11 12 13 14 15 0 1 2 3 4 5 6 6 7 10 13 Cohesion: 1 2 2 5 3 Parents: -1 0 0 1 2 Block graph: 0 1 0 2 1 3 2 4 -- Blocks: 0 1 2 3 4 5 6 7 0 1 4 5 2 3 6 7 1 2 5 6 Cohesion: 2 3 3 3 Parents: -1 0 0 0 Block graph: 0 1 0 2 0 3 -- Blocks: 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Cohesion: 2 3 3 3 Parents: -1 0 0 0 Block graph: 0 1 0 2 0 3 -- Blocks: 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 0 1 2 3 7 8 9 12 13 14 15 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 0 4 5 6 10 16 0 1 2 3 7 0 1 2 8 30 32 33 0 4 5 6 10 0 1 2 3 13 2 23 24 25 27 28 29 31 32 33 Cohesion: 1 2 2 4 3 3 4 3 Parents: -1 0 0 1 1 2 1 1 Block graph: 0 1 0 2 1 3 1 4 1 6 1 7 2 5 -- python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_scg_grouping4.c0000644000076500000240000000612513612122633030171 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { const int nodes = 10; igraph_t g; igraph_matrix_t V; igraph_matrix_complex_t V2; igraph_sparsemat_t laplacian; igraph_vector_t groups; igraph_eigen_which_t which; igraph_tree(&g, nodes, /* children= */ 3, IGRAPH_TREE_UNDIRECTED); igraph_matrix_complex_init(&V2, 0, 0); igraph_matrix_init(&V, 0, 0); igraph_vector_init(&groups, 0); igraph_rng_seed(igraph_rng_default(), 42); igraph_sparsemat_init(&laplacian, 0, 0, 0); igraph_laplacian(&g, /*res=*/ 0, /*sparseres=*/ &laplacian, /*normalized=*/ 0, /*weights=*/ 0); which.pos = IGRAPH_EIGEN_LR; which.howmany = 1; igraph_eigen_matrix(/*matrix=*/ 0, &laplacian, /*fun=*/ 0, nodes, /*extra=*/ 0, /*algorithm=*/ IGRAPH_EIGEN_LAPACK, &which, /*options=*/ 0, /*storage=*/ 0, /*values=*/ 0, &V2); igraph_matrix_complex_real(&V2, &V); /* ------------ */ igraph_scg_grouping(&V, &groups, /*intervals=*/ 3, /*intervals_vector=*/ 0, IGRAPH_SCG_LAPLACIAN, IGRAPH_SCG_OPTIMUM, /*p=*/ 0, /*maxiter=*/ 10000); igraph_vector_print(&groups); /* ------------ */ igraph_scg_grouping(&V, &groups, /*intervals=*/ 3, /*intervals_vector=*/ 0, IGRAPH_SCG_LAPLACIAN, IGRAPH_SCG_INTERV_KM, /*p=*/ 0, /*maxiter=*/ 10000); igraph_vector_print(&groups); /* ------------ */ igraph_scg_grouping(&V, &groups, /*intervals=*/ 3, /*intervals_vector=*/ 0, IGRAPH_SCG_LAPLACIAN, IGRAPH_SCG_INTERV, /*p=*/ 0, /*maxiter=*/ 10000); igraph_vector_print(&groups); /* ------------ */ igraph_scg_grouping(&V, &groups, /*(ignored) intervals=*/ 0, /*intervals_vector=*/ 0, IGRAPH_SCG_LAPLACIAN, IGRAPH_SCG_EXACT, /*p=*/ 0, /*maxiter=*/ 10000); igraph_vector_print(&groups); /* ------------ */ igraph_vector_destroy(&groups); igraph_matrix_destroy(&V); igraph_matrix_complex_destroy(&V2); igraph_sparsemat_destroy(&laplacian); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_vs_vector.out0000644000076500000240000000002113524616144030012 0ustar tamasstaff000000000000007 0 2 4 0 2 4 2 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_compose.c0000644000076500000240000000700513612122633027062 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g1, g2, res; igraph_vector_t v; igraph_vector_t map1, map2; igraph_vector_init(&map1, 0); igraph_vector_init(&map2, 0); /* composition with the empty graph */ igraph_empty(&g1, 5, IGRAPH_DIRECTED); igraph_full(&g2, 5, IGRAPH_DIRECTED, IGRAPH_NO_LOOPS); igraph_compose(&res, &g1, &g2, &map1, &map2); if (igraph_ecount(&res) != 0) { return 1; } if (igraph_vector_size(&map1) != 0 || igraph_vector_size(&map2) != 0) { return 11; } igraph_destroy(&res); igraph_compose(&res, &g2, &g1, &map1, &map2); if (igraph_ecount(&res) != 0) { return 2; } if (igraph_vector_size(&map1) != 0 || igraph_vector_size(&map2) != 0) { return 12; } igraph_destroy(&res); igraph_destroy(&g1); igraph_destroy(&g2); /* same but undirected */ igraph_empty(&g1, 5, IGRAPH_UNDIRECTED); igraph_full(&g2, 5, IGRAPH_UNDIRECTED, IGRAPH_NO_LOOPS); igraph_compose(&res, &g1, &g2, &map1, &map2); if (igraph_ecount(&res) != 0) { return 1; } if (igraph_vector_size(&map1) != 0 || igraph_vector_size(&map2) != 0) { return 11; } igraph_destroy(&res); igraph_compose(&res, &g2, &g1, &map1, &map2); if (igraph_ecount(&res) != 0) { return 2; } if (igraph_vector_size(&map1) != 0 || igraph_vector_size(&map2) != 0) { return 12; } igraph_destroy(&res); igraph_destroy(&g1); igraph_destroy(&g2); /* proper directed graph */ igraph_vector_init_int_end(&v, -1, 0, 1, 1, 2, 5, 6, -1); igraph_create(&g1, &v, 0, IGRAPH_DIRECTED); igraph_vector_destroy(&v); igraph_vector_init_int_end(&v, -1, 0, 1, 2, 4, 5, 6, -1); igraph_create(&g2, &v, 0, IGRAPH_DIRECTED); igraph_vector_destroy(&v); igraph_compose(&res, &g1, &g2, &map1, &map2); igraph_write_graph_edgelist(&res, stdout); igraph_vector_print(&map1); igraph_vector_print(&map2); igraph_destroy(&res); igraph_destroy(&g1); igraph_destroy(&g2); /* undirected graph */ igraph_vector_init_int_end(&v, -1, 0, 1, 1, 2, 5, 6, -1); igraph_create(&g1, &v, 0, IGRAPH_UNDIRECTED); igraph_vector_destroy(&v); igraph_vector_init_int_end(&v, -1, 0, 1, 0, 4, 5, 6, -1); igraph_create(&g2, &v, 0, IGRAPH_UNDIRECTED); igraph_vector_destroy(&v); igraph_compose(&res, &g1, &g2, &map1, &map2); igraph_write_graph_edgelist(&res, stdout); igraph_vector_print(&map1); igraph_vector_print(&map2); igraph_destroy(&res); igraph_destroy(&g1); igraph_destroy(&g2); igraph_vector_destroy(&map2); igraph_vector_destroy(&map1); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_decompose.c0000644000076500000240000000726013612122633027376 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include void free_complist(igraph_vector_ptr_t *complist) { long int i; for (i = 0; i < igraph_vector_ptr_size(complist); i++) { igraph_destroy(VECTOR(*complist)[i]); free(VECTOR(*complist)[i]); } } int main() { igraph_t ring, g; igraph_vector_ptr_t complist; long int i; igraph_real_t edges[] = { 0, 1, 1, 2, 2, 0, 3, 4, 4, 5, 5, 6, 8, 9, 9, 10 }; igraph_vector_t v; /* A ring, a single component */ igraph_ring(&ring, 10, IGRAPH_UNDIRECTED, 0, 1); igraph_vector_ptr_init(&complist, 0); igraph_decompose(&ring, &complist, IGRAPH_WEAK, -1, 0); igraph_write_graph_edgelist(VECTOR(complist)[0], stdout); free_complist(&complist); igraph_destroy(&ring); /* random graph with a giant component */ igraph_erdos_renyi_game(&g, IGRAPH_ERDOS_RENYI_GNP, 100, 4.0 / 100, IGRAPH_UNDIRECTED, 0); igraph_decompose(&g, &complist, IGRAPH_WEAK, -1, 20); if (igraph_vector_ptr_size(&complist) != 1) { return 1; } free_complist(&complist); igraph_destroy(&g); /* a toy graph, three components maximum, with at least 2 vertices each */ igraph_create(&g, igraph_vector_view(&v, edges, sizeof(edges) / sizeof(igraph_real_t)), 0, IGRAPH_DIRECTED); igraph_decompose(&g, &complist, IGRAPH_WEAK, 3, 2); for (i = 0; i < igraph_vector_ptr_size(&complist); i++) { igraph_write_graph_edgelist(VECTOR(complist)[i], stdout); } free_complist(&complist); igraph_destroy(&g); /* The same graph, this time with vertex attributes */ /* igraph_vector_init_seq(&idvect, 0, igraph_vcount(&g)-1); */ /* igraph_add_vertex_attribute(&g, "id", IGRAPH_ATTRIBUTE_NUM); */ /* igraph_set_vertex_attributes(&g, "id", IGRAPH_VS_ALL(&g), &idvect); */ /* igraph_vector_destroy(&idvect); */ /* igraph_decompose(&g, &complist, IGRAPH_WEAK, 3, 2); */ /* for (i=0; i 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g, tree; igraph_vector_t eb, edges; long int i; igraph_small(&g, 0, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 0, 7, 0, 8, 0, 10, 0, 11, 0, 12, 0, 13, 0, 17, 0, 19, 0, 21, 0, 31, 1, 2, 1, 3, 1, 7, 1, 13, 1, 17, 1, 19, 1, 21, 1, 30, 2, 3, 2, 7, 2, 8, 2, 9, 2, 13, 2, 27, 2, 28, 2, 32, 3, 7, 3, 12, 3, 13, 4, 6, 4, 10, 5, 6, 5, 10, 5, 16, 6, 16, 8, 30, 8, 32, 8, 33, 9, 33, 13, 33, 14, 32, 14, 33, 15, 32, 15, 33, 18, 32, 18, 33, 19, 33, 20, 32, 20, 33, 22, 32, 22, 33, 23, 25, 23, 27, 23, 29, 23, 32, 23, 33, 24, 25, 24, 27, 24, 31, 25, 31, 26, 29, 26, 33, 27, 33, 28, 31, 28, 33, 29, 32, 29, 33, 30, 32, 30, 33, 31, 32, 31, 33, 32, 33, -1); igraph_vector_init(&eb, igraph_ecount(&g)); igraph_edge_betweenness(&g, &eb, IGRAPH_UNDIRECTED, /*weights=*/ 0); for (i = 0; i < igraph_vector_size(&eb); i++) { VECTOR(eb)[i] = -VECTOR(eb)[i]; } igraph_minimum_spanning_tree_prim(&g, &tree, &eb); igraph_write_graph_edgelist(&tree, stdout); igraph_vector_init(&edges, 0); igraph_minimum_spanning_tree(&g, &edges, &eb); igraph_vector_print(&edges); igraph_vector_destroy(&edges); igraph_destroy(&tree); igraph_destroy(&g); igraph_vector_destroy(&eb); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_independent_sets.out0000644000076500000240000000052413524616144031343 0ustar tamasstaff000000000000000 independent sets found 6 independent sets found 0 3 0 4 1 2 2 3 2 4 3 4 2 independent sets found 0 3 4 2 3 4 13 independent sets found 0 1 2 3 4 0 3 0 4 1 2 2 3 2 4 3 4 0 3 4 2 3 4 9 maximal independent sets found 0 3 4 5 6 0 3 5 6 9 0 4 5 6 7 8 0 5 6 7 8 9 1 2 7 8 9 1 5 6 7 8 9 2 3 4 2 3 9 2 4 7 8 alpha=6 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_feedback_arc_set.out0000644000076500000240000000001313524616144031225 0ustar tamasstaff000000000000002 1 2 9 10 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_compose.out0000644000076500000240000000007013524616144027451 0ustar tamasstaff000000000000001 4 1 1 0 0 0 2 1 1 1 4 5 5 6 6 0 0 0 1 2 2 0 1 0 0 2 2 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_neighbors.out0000644000076500000240000000002313524616144027762 0ustar tamasstaff00000000000000 2 3 1 2 1 2 2 3 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_eccentricity.out0000644000076500000240000000007413524616144030475 0ustar tamasstaff000000000000001 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 1 0 0 0 0 0 0 0 0 0 python-igraph-0.8.0/vendor/source/igraph/examples/simple/celegansneural.gml0000644000076500000240000043241413524616144027425 0ustar tamasstaff00000000000000Creator "Mark Newman on Thu Aug 31 12:59:09 2006" graph [ 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source 34 target 74 value 1 ] edge [ source 34 target 44 value 4 ] edge [ source 35 target 43 value 10 ] edge [ source 35 target 44 value 10 ] edge [ source 36 target 49 value 1 ] edge [ source 36 target 93 value 1 ] edge [ source 36 target 44 value 7 ] edge [ source 37 target 190 value 1 ] edge [ source 38 target 50 value 1 ] edge [ source 38 target 33 value 4 ] edge [ source 38 target 43 value 1 ] edge [ source 38 target 49 value 2 ] edge [ source 38 target 64 value 2 ] edge [ source 38 target 44 value 9 ] edge [ source 40 target 41 value 1 ] edge [ source 40 target 42 value 1 ] edge [ source 40 target 22 value 3 ] edge [ source 40 target 43 value 6 ] edge [ source 40 target 44 value 4 ] edge [ source 41 target 4 value 2 ] edge [ source 41 target 40 value 1 ] edge [ source 41 target 23 value 3 ] edge [ source 41 target 47 value 1 ] edge [ source 41 target 48 value 3 ] edge [ source 41 target 43 value 4 ] edge [ source 41 target 46 value 2 ] edge [ source 41 target 49 value 1 ] edge [ source 41 target 44 value 10 ] edge [ source 42 target 84 value 4 ] edge [ source 42 target 86 value 3 ] edge [ source 42 target 119 value 2 ] edge [ source 42 target 98 value 2 ] edge [ source 42 target 218 value 1 ] edge [ source 42 target 167 value 1 ] edge [ source 42 target 232 value 1 ] edge [ source 42 target 168 value 1 ] edge [ source 42 target 137 value 1 ] edge [ source 42 target 40 value 1 ] edge [ source 42 target 45 value 1 ] edge [ source 42 target 17 value 1 ] edge [ source 42 target 29 value 1 ] edge [ source 42 target 185 value 1 ] edge [ source 42 target 172 value 1 ] edge [ source 42 target 22 value 4 ] edge [ source 42 target 33 value 3 ] edge [ source 42 target 173 value 1 ] edge [ source 43 target 6 value 1 ] edge [ source 43 target 23 value 1 ] edge [ source 43 target 35 value 6 ] edge [ source 43 target 44 value 7 ] edge [ source 45 target 33 value 7 ] edge [ source 45 target 46 value 8 ] edge [ source 45 target 44 value 8 ] edge [ source 46 target 23 value 10 ] edge [ source 46 target 79 value 1 ] edge [ source 46 target 44 value 9 ] edge [ source 47 target 31 value 1 ] edge [ source 47 target 13 value 5 ] edge [ source 47 target 6 value 3 ] edge [ source 47 target 35 value 1 ] edge [ source 47 target 48 value 2 ] edge [ source 47 target 214 value 1 ] edge [ source 47 target 44 value 11 ] edge [ source 48 target 213 value 1 ] edge [ source 48 target 13 value 5 ] edge [ source 48 target 6 value 7 ] edge [ source 48 target 23 value 1 ] edge [ source 48 target 47 value 1 ] edge [ source 48 target 44 value 4 ] edge [ source 49 target 44 value 14 ] edge [ source 50 target 3 value 1 ] edge [ source 50 target 45 value 1 ] edge [ source 50 target 23 value 3 ] edge [ source 50 target 35 value 4 ] edge [ source 50 target 47 value 4 ] edge [ source 50 target 48 value 1 ] edge [ source 50 target 43 value 1 ] edge [ source 50 target 46 value 4 ] edge [ source 50 target 51 value 2 ] edge [ source 50 target 52 value 1 ] edge [ source 50 target 44 value 12 ] edge [ source 51 target 44 value 11 ] edge [ source 52 target 99 value 4 ] edge [ source 52 target 84 value 1 ] edge [ source 52 target 86 value 1 ] edge [ source 52 target 4 value 1 ] edge [ source 52 target 32 value 1 ] edge [ source 52 target 6 value 4 ] edge [ source 52 target 21 value 1 ] edge [ source 52 target 9 value 2 ] edge [ source 52 target 33 value 3 ] edge [ source 52 target 48 value 1 ] edge [ source 52 target 37 value 1 ] edge [ source 53 target 86 value 1 ] edge [ source 53 target 4 value 5 ] edge [ source 53 target 17 value 1 ] edge [ source 53 target 13 value 1 ] edge [ source 53 target 14 value 2 ] edge [ source 53 target 59 value 1 ] edge [ source 53 target 90 value 1 ] edge [ source 53 target 23 value 4 ] edge [ source 53 target 46 value 2 ] edge [ source 53 target 78 value 1 ] edge [ source 53 target 75 value 4 ] edge [ source 54 target 11 value 1 ] edge [ source 54 target 40 value 7 ] edge [ source 54 target 55 value 2 ] edge [ source 54 target 14 value 1 ] edge [ source 54 target 22 value 9 ] edge [ source 54 target 51 value 4 ] edge [ source 54 target 49 value 4 ] edge [ source 54 target 56 value 3 ] edge [ source 55 target 21 value 1 ] edge [ source 55 target 35 value 4 ] edge [ source 55 target 78 value 3 ] edge [ source 56 target 40 value 2 ] edge [ source 56 target 22 value 3 ] edge [ source 56 target 35 value 1 ] edge [ source 56 target 51 value 1 ] edge [ source 56 target 44 value 6 ] edge [ source 57 target 58 value 1 ] edge [ source 57 target 45 value 7 ] edge [ source 57 target 21 value 1 ] edge [ source 57 target 59 value 1 ] edge [ source 57 target 33 value 12 ] edge [ source 57 target 60 value 1 ] edge [ source 57 target 51 value 3 ] edge [ source 57 target 49 value 2 ] edge [ source 57 target 61 value 3 ] edge [ source 58 target 3 value 5 ] edge [ source 58 target 95 value 1 ] edge [ source 58 target 45 value 5 ] edge [ source 58 target 50 value 1 ] edge [ source 58 target 31 value 6 ] edge [ source 58 target 68 value 5 ] edge [ source 58 target 7 value 1 ] edge [ source 58 target 20 value 4 ] edge [ source 58 target 21 value 2 ] edge [ source 58 target 23 value 1 ] edge [ source 58 target 46 value 2 ] edge [ source 58 target 87 value 1 ] edge [ source 58 target 24 value 4 ] edge [ source 58 target 88 value 1 ] edge [ source 58 target 85 value 1 ] edge [ source 58 target 61 value 1 ] edge [ source 58 target 69 value 2 ] edge [ source 58 target 82 value 1 ] edge [ source 59 target 105 value 1 ] edge [ source 59 target 102 value 5 ] edge [ source 59 target 108 value 4 ] edge [ source 59 target 99 value 1 ] edge [ source 59 target 5 value 1 ] edge [ source 59 target 71 value 1 ] edge [ source 59 target 58 value 1 ] edge [ source 59 target 15 value 1 ] edge [ source 59 target 27 value 2 ] edge [ source 59 target 66 value 1 ] edge [ source 59 target 55 value 3 ] edge [ source 59 target 68 value 3 ] edge [ source 59 target 19 value 3 ] edge [ source 59 target 32 value 7 ] edge [ source 59 target 13 value 12 ] edge [ source 59 target 6 value 9 ] edge [ source 59 target 14 value 5 ] edge [ source 59 target 7 value 4 ] edge [ source 59 target 22 value 5 ] edge [ source 59 target 33 value 5 ] edge [ source 59 target 49 value 1 ] edge [ source 59 target 64 value 1 ] edge [ source 59 target 91 value 1 ] edge [ source 59 target 39 value 1 ] edge [ source 60 target 14 value 1 ] edge [ source 60 target 7 value 1 ] edge [ source 60 target 44 value 10 ] edge [ source 61 target 33 value 3 ] edge [ source 61 target 46 value 1 ] edge [ source 61 target 60 value 1 ] edge [ source 61 target 49 value 1 ] edge [ source 61 target 82 value 1 ] edge [ source 61 target 44 value 6 ] edge [ source 62 target 63 value 2 ] edge [ source 62 target 3 value 1 ] edge [ source 62 target 41 value 1 ] edge [ source 62 target 55 value 6 ] edge [ source 62 target 19 value 8 ] edge [ source 62 target 20 value 1 ] edge [ source 62 target 59 value 9 ] edge [ source 62 target 47 value 3 ] edge [ source 62 target 48 value 1 ] edge 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source 67 target 218 value 1 ] edge [ source 67 target 58 value 1 ] edge [ source 67 target 129 value 1 ] edge [ source 67 target 224 value 2 ] edge [ source 67 target 31 value 2 ] edge [ source 67 target 8 value 7 ] edge [ source 67 target 9 value 4 ] edge [ source 67 target 59 value 1 ] edge [ source 67 target 48 value 2 ] edge [ source 67 target 87 value 2 ] edge [ source 67 target 212 value 1 ] edge [ source 68 target 20 value 1 ] edge [ source 68 target 21 value 1 ] edge [ source 68 target 23 value 3 ] edge [ source 68 target 36 value 1 ] edge [ source 68 target 79 value 2 ] edge [ source 69 target 86 value 1 ] edge [ source 69 target 58 value 1 ] edge [ source 69 target 50 value 3 ] edge [ source 69 target 66 value 1 ] edge [ source 69 target 21 value 1 ] edge [ source 69 target 47 value 1 ] edge [ source 69 target 48 value 1 ] edge [ source 69 target 87 value 1 ] edge [ source 69 target 88 value 1 ] edge [ source 69 target 37 value 1 ] edge [ source 69 target 89 value 1 ] edge [ source 69 target 52 value 7 ] edge [ source 70 target 5 value 1 ] edge [ source 70 target 17 value 6 ] edge [ source 70 target 19 value 1 ] edge [ source 70 target 13 value 1 ] edge [ source 70 target 59 value 2 ] edge [ source 70 target 22 value 11 ] edge [ source 70 target 51 value 2 ] edge [ source 70 target 49 value 5 ] edge [ source 70 target 64 value 1 ] edge [ source 70 target 26 value 4 ] edge [ source 71 target 4 value 5 ] edge [ source 71 target 40 value 4 ] edge [ source 71 target 41 value 1 ] edge [ source 71 target 18 value 2 ] edge [ source 71 target 55 value 6 ] edge [ source 71 target 14 value 2 ] edge [ source 71 target 20 value 1 ] edge [ source 71 target 21 value 3 ] edge [ source 71 target 22 value 2 ] edge [ source 71 target 90 value 1 ] edge [ source 71 target 43 value 3 ] edge [ source 71 target 93 value 3 ] edge [ source 71 target 36 value 4 ] edge [ source 71 target 94 value 1 ] edge [ source 71 target 89 value 1 ] edge [ source 71 target 56 value 2 ] edge [ 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source 87 target 52 value 1 ] edge [ source 87 target 44 value 3 ] edge [ source 88 target 190 value 1 ] edge [ source 89 target 2 value 1 ] edge [ source 89 target 60 value 4 ] edge [ source 89 target 212 value 2 ] edge [ source 89 target 44 value 9 ] edge [ source 90 target 3 value 8 ] edge [ source 90 target 4 value 6 ] edge [ source 90 target 213 value 1 ] edge [ source 90 target 218 value 3 ] edge [ source 90 target 187 value 2 ] edge [ source 90 target 71 value 1 ] edge [ source 90 target 58 value 2 ] edge [ source 90 target 15 value 2 ] edge [ source 90 target 27 value 1 ] edge [ source 90 target 31 value 1 ] edge [ source 90 target 14 value 3 ] edge [ source 90 target 7 value 6 ] edge [ source 90 target 132 value 2 ] edge [ source 90 target 130 value 4 ] edge [ source 90 target 23 value 1 ] edge [ source 90 target 47 value 2 ] edge [ source 90 target 48 value 5 ] edge [ source 90 target 73 value 1 ] edge [ source 90 target 74 value 1 ] edge [ source 90 target 77 value 1 ] edge [ source 90 target 75 value 1 ] edge [ source 90 target 91 value 1 ] edge [ source 91 target 12 value 1 ] edge [ source 91 target 3 value 6 ] edge [ source 91 target 29 value 1 ] edge [ source 91 target 6 value 1 ] edge [ source 91 target 7 value 1 ] edge [ source 91 target 23 value 1 ] edge [ source 91 target 35 value 4 ] edge [ source 91 target 43 value 3 ] edge [ source 91 target 78 value 1 ] edge [ source 91 target 79 value 1 ] edge [ source 91 target 77 value 3 ] edge [ source 92 target 3 value 2 ] edge [ source 92 target 4 value 2 ] edge [ source 92 target 48 value 1 ] edge [ source 92 target 39 value 1 ] edge [ source 92 target 39 value 2 ] edge [ source 93 target 101 value 1 ] edge [ source 93 target 114 value 1 ] edge [ source 93 target 216 value 1 ] edge [ source 93 target 235 value 1 ] edge [ source 93 target 141 value 1 ] edge [ source 93 target 12 value 1 ] edge [ source 93 target 86 value 2 ] edge [ source 93 target 3 value 2 ] edge [ source 93 target 71 value 1 ] edge [ source 93 target 47 value 1 ] edge [ source 93 target 48 value 3 ] edge [ source 93 target 43 value 4 ] edge [ source 93 target 36 value 1 ] edge [ source 93 target 25 value 1 ] edge [ source 93 target 78 value 2 ] edge [ source 93 target 104 value 2 ] edge [ source 93 target 65 value 1 ] edge [ source 93 target 44 value 5 ] edge [ source 94 target 190 value 1 ] edge [ source 95 target 63 value 1 ] edge [ source 95 target 67 value 1 ] edge [ source 95 target 240 value 1 ] edge [ source 95 target 12 value 5 ] edge [ source 95 target 198 value 1 ] edge [ source 95 target 119 value 2 ] edge [ source 95 target 142 value 7 ] edge [ source 95 target 125 value 2 ] edge [ source 95 target 172 value 2 ] edge [ source 95 target 207 value 4 ] edge [ source 95 target 204 value 1 ] edge [ source 95 target 72 value 1 ] edge [ source 95 target 241 value 1 ] edge [ source 95 target 61 value 1 ] edge [ source 96 target 97 value 1 ] edge [ source 96 target 60 value 1 ] edge [ source 96 target 44 value 1 ] edge [ source 97 target 166 value 2 ] edge [ source 97 target 227 value 1 ] edge [ source 97 target 221 value 1 ] edge [ source 97 target 44 value 29 ] edge [ source 98 target 2 value 2 ] edge [ source 98 target 84 value 4 ] edge [ source 98 target 86 value 1 ] edge [ source 98 target 118 value 4 ] edge [ source 98 target 3 value 4 ] edge [ source 98 target 202 value 1 ] edge [ source 98 target 198 value 1 ] edge [ source 98 target 119 value 1 ] edge [ source 98 target 206 value 1 ] edge [ source 98 target 191 value 1 ] edge [ source 98 target 125 value 2 ] edge [ source 98 target 172 value 4 ] edge [ source 98 target 207 value 1 ] edge [ source 98 target 145 value 1 ] edge [ source 98 target 186 value 1 ] edge [ source 99 target 107 value 1 ] edge [ source 99 target 2 value 1 ] edge [ source 99 target 4 value 3 ] edge [ source 99 target 6 value 10 ] edge [ source 99 target 7 value 12 ] edge [ source 99 target 52 value 1 ] edge [ source 100 target 101 value 1 ] edge [ source 100 target 102 value 11 ] edge [ source 100 target 11 value 3 ] edge [ source 100 target 19 value 1 ] edge [ source 100 target 13 value 12 ] edge [ source 100 target 103 value 2 ] edge [ source 100 target 104 value 2 ] edge [ source 101 target 1 value 1 ] edge [ source 101 target 114 value 2 ] edge [ source 101 target 2 value 1 ] edge [ source 101 target 84 value 4 ] edge [ source 101 target 86 value 5 ] edge [ source 101 target 3 value 1 ] edge [ source 101 target 98 value 4 ] edge [ source 101 target 224 value 1 ] edge [ source 101 target 132 value 3 ] edge [ source 101 target 22 value 1 ] edge [ source 101 target 22 value 1 ] edge [ source 101 target 77 value 2 ] edge [ source 102 target 100 value 2 ] edge [ source 102 target 113 value 2 ] edge [ source 102 target 1 value 4 ] edge [ source 102 target 114 value 7 ] edge [ source 102 target 135 value 1 ] edge [ source 102 target 136 value 1 ] edge [ source 102 target 4 value 4 ] edge [ source 102 target 137 value 1 ] edge [ source 102 target 13 value 7 ] edge [ source 102 target 59 value 1 ] edge [ source 102 target 132 value 3 ] edge [ source 102 target 89 value 4 ] edge [ source 102 target 104 value 7 ] edge [ source 103 target 102 value 6 ] edge [ source 103 target 108 value 5 ] edge [ source 103 target 201 value 1 ] edge [ source 103 target 11 value 1 ] edge [ source 103 target 5 value 1 ] edge [ source 103 target 137 value 3 ] edge [ source 103 target 191 value 1 ] edge [ source 103 target 13 value 6 ] edge [ source 103 target 6 value 1 ] edge [ source 103 target 65 value 5 ] edge [ source 103 target 52 value 2 ] edge [ source 104 target 222 value 1 ] edge [ source 104 target 64 value 5 ] edge [ source 104 target 131 value 3 ] edge [ source 104 target 44 value 4 ] edge [ source 105 target 106 value 1 ] edge [ source 105 target 107 value 1 ] edge [ source 105 target 108 value 8 ] edge [ source 105 target 109 value 1 ] edge [ source 105 target 99 value 3 ] edge [ source 105 target 110 value 2 ] edge [ source 105 target 111 value 1 ] edge [ source 105 target 6 value 12 ] edge [ source 105 target 9 value 2 ] edge [ source 105 target 103 value 3 ] edge [ source 105 target 89 value 1 ] edge [ source 105 target 112 value 2 ] edge [ source 105 target 52 value 1 ] edge [ source 106 target 84 value 3 ] edge [ source 106 target 86 value 4 ] edge [ source 106 target 3 value 1 ] edge [ source 106 target 119 value 3 ] edge [ source 106 target 130 value 4 ] edge [ source 106 target 33 value 1 ] edge [ source 106 target 209 value 1 ] edge [ source 106 target 75 value 2 ] edge [ source 107 target 105 value 1 ] edge [ source 107 target 108 value 6 ] edge [ source 107 target 139 value 1 ] edge [ source 107 target 191 value 1 ] edge [ source 107 target 6 value 4 ] edge [ source 107 target 7 value 4 ] edge [ source 108 target 122 value 1 ] edge [ source 108 target 1 value 9 ] edge [ source 108 target 114 value 1 ] edge [ source 108 target 3 value 4 ] edge [ source 108 target 4 value 1 ] edge [ source 108 target 137 value 2 ] edge [ source 108 target 6 value 7 ] edge [ source 108 target 130 value 4 ] edge [ source 108 target 85 value 5 ] edge [ source 108 target 112 value 3 ] edge [ source 109 target 106 value 1 ] edge [ source 109 target 105 value 2 ] edge [ source 109 target 122 value 9 ] edge [ source 109 target 114 value 3 ] edge [ source 109 target 2 value 5 ] edge [ source 109 target 86 value 3 ] edge [ source 109 target 117 value 5 ] edge [ source 109 target 118 value 1 ] edge [ source 109 target 4 value 2 ] edge [ source 109 target 142 value 1 ] edge [ source 109 target 111 value 1 ] edge [ source 109 target 6 value 2 ] edge [ source 109 target 87 value 2 ] edge [ source 110 target 105 value 4 ] edge [ source 110 target 108 value 4 ] edge [ source 110 target 28 value 1 ] edge [ source 110 target 86 value 2 ] edge [ source 110 target 6 value 1 ] edge [ source 110 target 103 value 2 ] edge [ source 110 target 112 value 1 ] edge [ source 111 target 105 value 1 ] edge [ source 111 target 201 value 1 ] edge [ source 111 target 12 value 1 ] edge [ source 111 target 2 value 2 ] edge [ source 111 target 84 value 3 ] edge [ source 111 target 86 value 7 ] edge [ source 111 target 3 value 1 ] edge [ source 111 target 198 value 3 ] edge [ source 111 target 187 value 4 ] edge [ source 111 target 233 value 1 ] edge [ source 111 target 193 value 2 ] edge [ source 111 target 125 value 5 ] edge [ source 111 target 172 value 7 ] edge [ source 111 target 145 value 1 ] edge [ source 111 target 6 value 2 ] edge [ source 111 target 9 value 1 ] edge [ source 111 target 130 value 1 ] edge [ source 111 target 190 value 3 ] edge [ source 112 target 223 value 3 ] edge [ source 112 target 64 value 3 ] edge [ source 112 target 72 value 4 ] edge [ source 112 target 44 value 4 ] edge [ source 113 target 101 value 1 ] edge [ source 113 target 1 value 11 ] edge [ source 113 target 149 value 2 ] edge [ source 113 target 102 value 2 ] edge [ source 113 target 115 value 2 ] edge [ source 113 target 140 value 1 ] edge [ source 113 target 141 value 3 ] edge [ source 113 target 124 value 1 ] edge [ source 113 target 191 value 1 ] edge [ source 113 target 215 value 1 ] edge [ source 114 target 2 value 1 ] edge [ source 114 target 86 value 3 ] edge [ source 114 target 3 value 1 ] edge [ source 114 target 13 value 1 ] edge [ source 114 target 14 value 4 ] edge [ source 114 target 132 value 14 ] edge [ source 114 target 130 value 1 ] edge [ source 114 target 131 value 1 ] edge [ source 114 target 73 value 3 ] edge [ source 114 target 133 value 1 ] edge [ source 115 target 126 value 3 ] edge [ source 115 target 128 value 1 ] edge [ source 115 target 113 value 4 ] edge [ source 115 target 122 value 3 ] edge [ source 115 target 1 value 1 ] edge [ source 115 target 114 value 7 ] edge [ source 115 target 10 value 4 ] edge [ source 115 target 107 value 12 ] edge [ source 115 target 139 value 1 ] edge [ source 115 target 138 value 1 ] edge [ source 115 target 124 value 2 ] edge [ source 116 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3 ] edge [ source 118 target 166 value 1 ] edge [ source 118 target 167 value 1 ] edge [ source 118 target 192 value 1 ] edge [ source 118 target 193 value 1 ] edge [ source 118 target 184 value 3 ] edge [ source 118 target 194 value 1 ] edge [ source 118 target 172 value 1 ] edge [ source 118 target 173 value 3 ] edge [ source 118 target 174 value 6 ] edge [ source 118 target 176 value 1 ] edge [ source 118 target 178 value 1 ] edge [ source 118 target 179 value 3 ] edge [ source 118 target 181 value 1 ] edge [ source 118 target 182 value 2 ] edge [ source 119 target 12 value 2 ] edge [ source 119 target 84 value 1 ] edge [ source 119 target 86 value 5 ] edge [ source 119 target 117 value 3 ] edge [ source 119 target 4 value 4 ] edge [ source 119 target 199 value 1 ] edge [ source 119 target 123 value 1 ] edge [ source 119 target 142 value 1 ] edge [ source 119 target 125 value 1 ] edge [ source 119 target 172 value 3 ] edge [ source 119 target 204 value 2 ] edge [ source 119 target 148 value 1 ] edge [ source 119 target 205 value 1 ] edge [ source 119 target 90 value 2 ] edge [ source 119 target 174 value 1 ] edge [ source 120 target 100 value 8 ] edge [ source 120 target 114 value 1 ] edge [ source 120 target 102 value 7 ] edge [ source 120 target 84 value 1 ] edge [ source 120 target 13 value 3 ] edge [ source 120 target 85 value 1 ] edge [ source 121 target 122 value 10 ] edge [ source 121 target 114 value 11 ] edge [ source 121 target 115 value 1 ] edge [ source 121 target 109 value 3 ] edge [ source 121 target 2 value 2 ] edge [ source 121 target 84 value 1 ] edge [ source 121 target 86 value 2 ] edge [ source 121 target 117 value 5 ] edge [ source 121 target 118 value 2 ] edge [ source 121 target 123 value 1 ] edge [ source 121 target 98 value 2 ] edge [ source 121 target 124 value 3 ] edge [ source 121 target 31 value 1 ] edge [ source 121 target 125 value 2 ] edge [ source 121 target 20 value 1 ] edge [ source 121 target 21 value 1 ] edge [ source 122 target 106 value 1 ] edge [ source 122 target 121 value 1 ] edge [ source 122 target 114 value 12 ] edge [ source 122 target 108 value 1 ] edge [ source 122 target 115 value 1 ] edge [ source 122 target 139 value 1 ] edge [ source 122 target 124 value 1 ] edge [ source 122 target 205 value 2 ] edge [ source 123 target 121 value 2 ] edge [ source 123 target 201 value 1 ] edge [ source 123 target 84 value 1 ] edge [ source 123 target 118 value 1 ] edge [ source 123 target 202 value 5 ] edge [ source 123 target 198 value 2 ] edge [ source 123 target 119 value 1 ] edge [ source 123 target 98 value 2 ] edge [ source 123 target 203 value 4 ] edge [ source 123 target 145 value 2 ] edge [ source 123 target 8 value 1 ] edge [ source 123 target 103 value 3 ] edge [ source 123 target 89 value 1 ] edge [ source 123 target 104 value 1 ] edge [ source 123 target 200 value 1 ] edge [ source 124 target 121 value 1 ] edge [ source 124 target 122 value 2 ] edge [ source 124 target 1 value 1 ] edge [ source 124 target 114 value 3 ] edge [ source 124 target 10 value 4 ] edge [ source 124 target 107 value 9 ] edge [ source 124 target 138 value 2 ] edge [ source 125 target 151 value 1 ] edge [ source 125 target 154 value 2 ] edge [ source 125 target 12 value 7 ] edge [ source 125 target 2 value 9 ] edge [ source 125 target 84 value 4 ] edge [ source 125 target 86 value 16 ] edge [ source 125 target 117 value 3 ] edge [ source 125 target 118 value 6 ] edge [ source 125 target 3 value 2 ] edge [ source 125 target 4 value 1 ] edge [ source 125 target 119 value 3 ] edge [ source 125 target 187 value 1 ] edge [ source 125 target 160 value 1 ] edge [ source 125 target 232 value 4 ] edge [ source 125 target 168 value 5 ] edge [ source 125 target 192 value 7 ] edge [ source 125 target 169 value 3 ] edge [ source 125 target 253 value 4 ] edge [ source 125 target 137 value 4 ] edge [ source 125 target 184 value 1 ] edge [ source 125 target 171 value 1 ] edge [ source 125 target 172 value 3 ] edge [ source 125 target 42 value 1 ] edge [ source 125 target 256 value 1 ] edge [ source 125 target 96 value 5 ] edge [ source 125 target 90 value 2 ] edge [ source 125 target 78 value 2 ] edge [ source 125 target 254 value 1 ] edge [ source 125 target 262 value 1 ] edge [ source 125 target 263 value 4 ] edge [ source 125 target 264 value 1 ] edge [ source 125 target 265 value 5 ] edge [ source 125 target 266 value 3 ] edge [ source 125 target 267 value 2 ] edge [ source 126 target 127 value 1 ] edge [ source 126 target 10 value 7 ] edge [ source 127 target 126 value 5 ] edge [ source 127 target 113 value 2 ] edge [ source 127 target 1 value 2 ] edge [ source 127 target 115 value 3 ] edge [ source 127 target 5 value 3 ] edge [ source 127 target 14 value 1 ] edge [ source 127 target 96 value 1 ] edge [ source 127 target 39 value 1 ] edge [ source 128 target 107 value 11 ] edge [ source 128 target 115 value 1 ] edge [ source 129 target 63 value 1 ] edge [ source 129 target 67 value 2 ] edge [ source 129 target 1 value 1 ] edge [ source 129 target 114 value 2 ] edge [ source 129 target 12 value 13 ] edge [ source 129 target 2 value 18 ] edge [ source 129 target 84 value 4 ] edge [ source 129 target 86 value 5 ] edge [ source 129 target 117 value 6 ] edge [ source 129 target 118 value 14 ] edge [ source 129 target 137 value 1 ] edge [ source 129 target 224 value 1 ] edge [ source 130 target 106 value 1 ] edge [ source 130 target 1 value 4 ] edge [ source 130 target 12 value 2 ] edge [ source 130 target 84 value 2 ] edge [ source 130 target 86 value 5 ] edge [ source 130 target 119 value 1 ] edge [ source 130 target 213 value 1 ] edge [ source 130 target 7 value 1 ] edge [ source 130 target 90 value 1 ] edge [ source 130 target 47 value 2 ] edge [ source 130 target 48 value 1 ] edge [ source 130 target 210 value 2 ] edge [ source 130 target 211 value 3 ] edge [ source 130 target 212 value 3 ] edge [ source 130 target 73 value 2 ] edge [ source 130 target 74 value 3 ] edge [ source 130 target 44 value 4 ] edge [ source 131 target 1 value 1 ] edge [ source 131 target 12 value 5 ] edge [ source 131 target 132 value 3 ] edge [ source 131 target 130 value 5 ] edge [ source 131 target 93 value 1 ] edge [ source 132 target 12 value 1 ] edge [ source 132 target 84 value 2 ] edge [ source 132 target 86 value 3 ] edge [ source 132 target 14 value 1 ] edge [ source 132 target 90 value 1 ] edge [ source 132 target 47 value 1 ] edge [ source 132 target 48 value 3 ] edge [ source 132 target 210 value 1 ] edge [ source 132 target 72 value 1 ] edge [ source 132 target 211 value 3 ] edge [ source 132 target 212 value 2 ] edge [ source 132 target 74 value 5 ] edge [ source 132 target 77 value 1 ] edge [ source 132 target 44 value 4 ] edge [ source 133 target 114 value 1 ] edge [ source 133 target 219 value 1 ] edge [ source 133 target 132 value 1 ] edge [ source 133 target 214 value 2 ] edge [ source 133 target 131 value 9 ] edge [ source 133 target 72 value 4 ] edge [ source 133 target 173 value 1 ] edge [ source 133 target 196 value 3 ] edge [ source 133 target 178 value 1 ] edge [ source 133 target 179 value 1 ] edge [ source 133 target 200 value 2 ] edge [ source 133 target 197 value 1 ] edge [ source 133 target 44 value 5 ] edge [ source 134 target 128 value 5 ] edge [ source 134 target 135 value 2 ] edge [ source 134 target 28 value 1 ] edge [ source 134 target 99 value 1 ] edge [ source 134 target 0 value 3 ] edge [ source 134 target 14 value 1 ] edge [ source 134 target 7 value 2 ] edge [ source 134 target 39 value 1 ] edge [ source 135 target 105 value 1 ] edge [ source 135 target 113 value 4 ] edge [ source 135 target 1 value 7 ] edge [ source 135 target 114 value 3 ] edge [ source 135 target 10 value 12 ] edge [ source 135 target 107 value 6 ] edge [ source 135 target 138 value 4 ] edge [ source 135 target 124 value 2 ] edge [ source 135 target 6 value 1 ] edge [ source 136 target 1 value 1 ] edge [ source 136 target 10 value 2 ] edge [ source 136 target 102 value 1 ] edge [ source 136 target 135 value 1 ] edge [ source 136 target 115 value 1 ] edge [ source 136 target 141 value 2 ] edge [ source 136 target 138 value 2 ] edge [ source 136 target 124 value 2 ] edge [ source 137 target 102 value 3 ] edge [ source 137 target 201 value 3 ] edge [ source 137 target 11 value 1 ] edge [ source 137 target 99 value 1 ] edge [ source 137 target 12 value 3 ] edge [ source 137 target 84 value 1 ] edge [ source 137 target 3 value 8 ] edge [ source 137 target 4 value 6 ] edge [ source 137 target 232 value 1 ] edge [ source 137 target 168 value 3 ] edge [ source 137 target 192 value 1 ] edge [ source 137 target 169 value 1 ] edge [ source 137 target 253 value 2 ] edge [ source 137 target 185 value 2 ] edge [ source 137 target 125 value 5 ] edge [ source 137 target 42 value 2 ] edge [ source 137 target 13 value 1 ] edge [ source 137 target 6 value 2 ] edge [ source 137 target 130 value 1 ] edge [ source 137 target 103 value 1 ] edge [ source 137 target 72 value 1 ] edge [ source 137 target 211 value 1 ] edge [ source 137 target 212 value 1 ] edge [ source 137 target 89 value 3 ] edge [ source 137 target 85 value 2 ] edge [ source 137 target 104 value 3 ] edge [ source 137 target 112 value 2 ] edge [ source 137 target 177 value 1 ] edge [ source 137 target 133 value 1 ] edge [ source 137 target 254 value 2 ] edge [ source 138 target 113 value 2 ] edge [ source 138 target 122 value 4 ] edge [ source 138 target 1 value 1 ] edge [ source 138 target 114 value 1 ] edge [ source 138 target 10 value 13 ] edge [ source 138 target 12 value 1 ] edge [ source 138 target 13 value 2 ] edge [ source 139 target 105 value 3 ] edge [ source 139 target 128 value 9 ] edge [ source 139 target 107 value 2 ] edge [ source 139 target 108 value 7 ] edge [ source 139 target 135 value 1 ] edge [ source 139 target 115 value 2 ] edge [ source 139 target 110 value 2 ] edge [ source 139 target 205 value 2 ] edge [ source 139 target 103 value 1 ] edge [ source 140 target 113 value 9 ] edge [ source 140 target 1 value 3 ] edge [ source 140 target 127 value 1 ] edge [ source 140 target 141 value 1 ] edge [ source 141 target 113 value 11 ] edge [ source 141 target 1 value 3 ] edge [ source 141 target 149 value 2 ] edge [ source 141 target 144 value 1 ] edge [ source 142 target 1 value 1 ] edge [ source 142 target 114 value 1 ] edge [ source 142 target 102 value 1 ] edge [ source 142 target 108 value 1 ] edge [ source 142 target 157 value 1 ] edge [ source 142 target 116 value 2 ] edge [ source 142 target 117 value 3 ] edge [ source 142 target 202 value 2 ] edge [ source 142 target 119 value 1 ] edge [ source 142 target 120 value 1 ] edge [ source 142 target 95 value 2 ] edge [ source 142 target 163 value 2 ] edge [ source 142 target 164 value 1 ] edge [ source 142 target 169 value 1 ] edge [ source 142 target 191 value 1 ] edge [ source 142 target 204 value 2 ] edge [ source 142 target 148 value 1 ] edge [ source 142 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value 2 ] edge [ source 149 target 86 value 2 ] edge [ source 149 target 117 value 1 ] edge [ source 149 target 118 value 1 ] edge [ source 149 target 4 value 1 ] edge [ source 149 target 202 value 4 ] edge [ source 149 target 199 value 1 ] edge [ source 149 target 198 value 1 ] edge [ source 149 target 123 value 2 ] edge [ source 149 target 119 value 1 ] edge [ source 149 target 145 value 1 ] edge [ source 149 target 215 value 1 ] edge [ source 149 target 104 value 1 ] edge [ source 149 target 39 value 1 ] edge [ source 149 target 39 value 1 ] edge [ source 150 target 122 value 4 ] edge [ source 150 target 28 value 2 ] edge [ source 150 target 146 value 2 ] edge [ source 150 target 147 value 2 ] edge [ source 150 target 118 value 1 ] edge [ source 150 target 202 value 3 ] edge [ source 150 target 199 value 2 ] edge [ source 150 target 98 value 1 ] edge [ source 150 target 191 value 1 ] edge [ source 150 target 142 value 2 ] edge [ source 150 target 205 value 1 ] edge [ source 150 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value 10 ] edge [ source 181 target 275 value 8 ] edge [ source 181 target 182 value 1 ] edge [ source 181 target 231 value 3 ] edge [ source 181 target 234 value 2 ] edge [ source 181 target 44 value 10 ] edge [ source 182 target 275 value 8 ] edge [ source 182 target 188 value 1 ] edge [ source 182 target 44 value 10 ] edge [ source 183 target 177 value 1 ] edge [ source 183 target 44 value 8 ] edge [ source 184 target 12 value 3 ] edge [ source 184 target 2 value 7 ] edge [ source 184 target 117 value 1 ] edge [ source 184 target 118 value 3 ] edge [ source 184 target 98 value 1 ] edge [ source 184 target 194 value 1 ] edge [ source 184 target 172 value 3 ] edge [ source 184 target 42 value 1 ] edge [ source 184 target 256 value 1 ] edge [ source 185 target 218 value 22 ] edge [ source 185 target 137 value 61 ] edge [ source 185 target 171 value 1 ] edge [ source 185 target 172 value 2 ] edge [ source 185 target 217 value 1 ] edge [ source 185 target 42 value 2 ] edge [ source 185 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value 1 ] edge [ source 192 target 234 value 9 ] edge [ source 192 target 269 value 22 ] edge [ source 192 target 271 value 7 ] edge [ source 192 target 44 value 22 ] edge [ source 193 target 1 value 1 ] edge [ source 193 target 114 value 3 ] edge [ source 193 target 12 value 5 ] edge [ source 193 target 2 value 7 ] edge [ source 193 target 84 value 1 ] edge [ source 193 target 213 value 2 ] edge [ source 193 target 218 value 1 ] edge [ source 193 target 195 value 1 ] edge [ source 193 target 14 value 1 ] edge [ source 193 target 8 value 5 ] edge [ source 193 target 9 value 5 ] edge [ source 193 target 214 value 2 ] edge [ source 193 target 210 value 4 ] edge [ source 194 target 12 value 7 ] edge [ source 194 target 2 value 7 ] edge [ source 194 target 118 value 23 ] edge [ source 194 target 226 value 1 ] edge [ source 194 target 170 value 1 ] edge [ source 194 target 204 value 1 ] edge [ source 195 target 1 value 2 ] edge [ source 195 target 114 value 5 ] edge [ source 195 target 213 value 7 ] edge [ source 195 target 218 value 7 ] edge [ source 195 target 187 value 2 ] edge [ source 195 target 166 value 2 ] edge [ source 195 target 97 value 1 ] edge [ source 195 target 97 value 3 ] edge [ source 195 target 193 value 5 ] edge [ source 195 target 250 value 1 ] edge [ source 195 target 111 value 2 ] edge [ source 195 target 8 value 2 ] edge [ source 195 target 9 value 3 ] edge [ source 195 target 59 value 1 ] edge [ source 195 target 64 value 1 ] edge [ source 195 target 214 value 2 ] edge [ source 195 target 210 value 4 ] edge [ source 195 target 85 value 1 ] edge [ source 195 target 44 value 5 ] edge [ source 195 target 190 value 5 ] edge [ source 196 target 219 value 8 ] edge [ source 196 target 178 value 1 ] edge [ source 196 target 133 value 1 ] edge [ source 196 target 200 value 3 ] edge [ source 196 target 44 value 10 ] edge [ source 197 target 155 value 2 ] edge [ source 197 target 237 value 2 ] edge [ source 197 target 44 value 8 ] edge [ source 198 target 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target 191 value 1 ] edge [ source 202 target 171 value 1 ] edge [ source 202 target 145 value 2 ] edge [ source 202 target 133 value 1 ] edge [ source 202 target 227 value 1 ] edge [ source 202 target 44 value 2 ] edge [ source 203 target 101 value 1 ] edge [ source 203 target 201 value 1 ] edge [ source 203 target 12 value 2 ] edge [ source 203 target 2 value 2 ] edge [ source 203 target 84 value 5 ] edge [ source 203 target 86 value 6 ] edge [ source 203 target 118 value 2 ] edge [ source 203 target 4 value 1 ] edge [ source 203 target 123 value 2 ] edge [ source 203 target 187 value 4 ] edge [ source 203 target 233 value 1 ] edge [ source 203 target 193 value 2 ] edge [ source 203 target 172 value 4 ] edge [ source 203 target 148 value 1 ] edge [ source 203 target 8 value 2 ] edge [ source 203 target 190 value 3 ] edge [ source 204 target 2 value 6 ] edge [ source 204 target 86 value 3 ] edge [ source 204 target 118 value 6 ] edge [ source 204 target 4 value 3 ] edge [ source 204 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4 ] edge [ source 208 target 140 value 1 ] edge [ source 208 target 120 value 1 ] edge [ source 209 target 13 value 2 ] edge [ source 209 target 6 value 2 ] edge [ source 209 target 23 value 1 ] edge [ source 209 target 48 value 1 ] edge [ source 209 target 46 value 1 ] edge [ source 209 target 64 value 1 ] edge [ source 209 target 131 value 2 ] edge [ source 209 target 25 value 2 ] edge [ source 209 target 73 value 2 ] edge [ source 209 target 75 value 2 ] edge [ source 209 target 44 value 5 ] edge [ source 210 target 114 value 1 ] edge [ source 210 target 213 value 1 ] edge [ source 210 target 218 value 3 ] edge [ source 210 target 48 value 2 ] edge [ source 210 target 44 value 4 ] edge [ source 211 target 12 value 15 ] edge [ source 211 target 31 value 1 ] edge [ source 211 target 132 value 2 ] edge [ source 211 target 130 value 9 ] edge [ source 211 target 210 value 2 ] edge [ source 211 target 74 value 6 ] edge [ source 212 target 2 value 11 ] edge [ source 212 target 132 value 4 ] edge [ source 212 target 130 value 1 ] edge [ source 212 target 73 value 6 ] edge [ source 213 target 84 value 1 ] edge [ source 213 target 3 value 2 ] edge [ source 213 target 4 value 1 ] edge [ source 213 target 206 value 1 ] edge [ source 213 target 137 value 1 ] edge [ source 213 target 185 value 4 ] edge [ source 213 target 217 value 1 ] edge [ source 213 target 148 value 1 ] edge [ source 213 target 132 value 2 ] edge [ source 213 target 130 value 1 ] edge [ source 213 target 72 value 1 ] edge [ source 213 target 37 value 1 ] edge [ source 213 target 190 value 5 ] edge [ source 214 target 1 value 1 ] edge [ source 214 target 213 value 1 ] edge [ source 214 target 218 value 4 ] edge [ source 214 target 47 value 5 ] edge [ source 214 target 48 value 1 ] edge [ source 214 target 87 value 1 ] edge [ source 214 target 44 value 5 ] edge [ source 215 target 216 value 2 ] edge [ source 215 target 84 value 10 ] edge [ source 215 target 86 value 1 ] edge [ source 215 target 123 value 1 ] 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value 1 ] edge [ source 218 target 132 value 3 ] edge [ source 218 target 130 value 3 ] edge [ source 218 target 131 value 1 ] edge [ source 218 target 85 value 1 ] edge [ source 218 target 73 value 1 ] edge [ source 218 target 74 value 2 ] edge [ source 218 target 75 value 1 ] edge [ source 218 target 190 value 5 ] edge [ source 219 target 159 value 2 ] edge [ source 219 target 200 value 1 ] edge [ source 219 target 197 value 1 ] edge [ source 219 target 44 value 29 ] edge [ source 220 target 2 value 1 ] edge [ source 220 target 118 value 1 ] edge [ source 220 target 119 value 1 ] edge [ source 220 target 172 value 1 ] edge [ source 220 target 252 value 3 ] edge [ source 220 target 256 value 1 ] edge [ source 220 target 177 value 1 ] edge [ source 221 target 177 value 1 ] edge [ source 221 target 44 value 8 ] edge [ source 222 target 72 value 3 ] edge [ source 222 target 112 value 5 ] edge [ source 223 target 131 value 5 ] edge [ source 223 target 104 value 6 ] edge [ source 224 target 67 value 2 ] edge [ source 224 target 114 value 1 ] edge [ source 224 target 12 value 10 ] edge [ source 224 target 2 value 4 ] edge [ source 224 target 84 value 4 ] edge [ source 224 target 86 value 2 ] edge [ source 224 target 117 value 10 ] edge [ source 224 target 118 value 2 ] edge [ source 224 target 3 value 3 ] edge [ source 224 target 4 value 2 ] edge [ source 224 target 137 value 1 ] edge [ source 224 target 129 value 1 ] edge [ source 224 target 125 value 2 ] edge [ source 224 target 133 value 1 ] edge [ source 224 target 190 value 3 ] edge [ source 225 target 63 value 4 ] edge [ source 225 target 2 value 2 ] edge [ source 225 target 198 value 1 ] edge [ source 225 target 98 value 1 ] edge [ source 225 target 191 value 4 ] edge [ source 225 target 125 value 2 ] edge [ source 225 target 207 value 1 ] edge [ source 225 target 204 value 2 ] edge [ source 225 target 131 value 2 ] edge [ source 225 target 56 value 1 ] edge [ source 225 target 39 value 1 ] edge [ source 226 target 12 value 3 ] edge [ source 226 target 2 value 1 ] edge [ source 226 target 84 value 4 ] edge [ source 226 target 117 value 1 ] edge [ source 226 target 118 value 1 ] edge [ source 226 target 4 value 1 ] edge [ source 226 target 202 value 1 ] edge [ source 226 target 98 value 1 ] edge [ source 226 target 166 value 1 ] edge [ source 226 target 166 value 1 ] edge [ source 226 target 195 value 1 ] edge [ source 226 target 228 value 2 ] edge [ source 226 target 229 value 1 ] edge [ source 226 target 125 value 1 ] edge [ source 226 target 172 value 1 ] edge [ source 226 target 207 value 2 ] edge [ source 226 target 204 value 2 ] edge [ source 226 target 203 value 1 ] edge [ source 226 target 111 value 1 ] edge [ source 226 target 145 value 1 ] edge [ source 226 target 148 value 1 ] edge [ source 226 target 176 value 1 ] edge [ source 226 target 176 value 1 ] edge [ source 226 target 190 value 1 ] edge [ source 226 target 190 value 1 ] edge [ source 227 target 44 value 8 ] edge [ source 228 target 118 value 1 ] edge [ source 228 target 202 value 3 ] edge [ source 228 target 226 value 5 ] edge [ source 228 target 198 value 1 ] edge [ source 228 target 123 value 1 ] edge [ source 228 target 166 value 1 ] edge [ source 228 target 137 value 2 ] edge [ source 228 target 229 value 5 ] edge [ source 228 target 255 value 5 ] edge [ source 228 target 257 value 4 ] edge [ source 228 target 145 value 2 ] edge [ source 229 target 226 value 3 ] edge [ source 229 target 123 value 1 ] edge [ source 229 target 137 value 2 ] edge [ source 229 target 228 value 6 ] edge [ source 229 target 255 value 1 ] edge [ source 229 target 257 value 5 ] edge [ source 229 target 145 value 2 ] edge [ source 230 target 151 value 1 ] edge [ source 230 target 154 value 1 ] edge [ source 230 target 219 value 4 ] edge [ source 230 target 200 value 1 ] edge [ source 230 target 197 value 9 ] edge [ source 230 target 189 value 22 ] edge [ source 230 target 231 value 7 ] edge [ source 230 target 44 value 22 ] edge [ source 231 target 44 value 25 ] edge [ source 232 target 155 value 1 ] edge [ source 232 target 219 value 1 ] edge [ source 232 target 233 value 4 ] edge [ source 232 target 197 value 1 ] edge [ source 232 target 189 value 9 ] edge [ source 232 target 231 value 22 ] edge [ source 232 target 234 value 7 ] edge [ source 232 target 44 value 22 ] edge [ source 233 target 161 value 2 ] edge [ source 233 target 189 value 1 ] edge [ source 233 target 231 value 1 ] edge [ source 233 target 44 value 29 ] edge [ source 234 target 44 value 25 ] edge [ source 235 target 211 value 3 ] edge [ source 235 target 85 value 2 ] edge [ source 235 target 77 value 1 ] edge [ source 236 target 36 value 1 ] edge [ source 236 target 212 value 3 ] edge [ source 236 target 89 value 1 ] edge [ source 236 target 74 value 1 ] edge [ source 236 target 77 value 1 ] edge [ source 237 target 219 value 19 ] edge [ source 237 target 233 value 1 ] edge [ source 237 target 178 value 1 ] edge [ source 237 target 238 value 1 ] edge [ source 237 target 197 value 6 ] edge [ source 237 target 189 value 4 ] edge [ source 237 target 44 value 23 ] edge [ source 238 target 233 value 4 ] edge [ source 238 target 142 value 1 ] edge [ source 238 target 200 value 1 ] edge [ source 238 target 231 value 2 ] edge [ source 238 target 44 value 2 ] edge [ source 238 target 44 value 8 ] edge [ source 239 target 114 value 1 ] edge [ source 239 target 216 value 1 ] edge [ source 239 target 12 value 2 ] edge [ source 239 target 2 value 3 ] edge [ source 239 target 3 value 1 ] edge [ source 239 target 129 value 1 ] edge [ source 239 target 21 value 1 ] edge [ source 239 target 90 value 2 ] edge [ source 239 target 214 value 1 ] edge [ source 240 target 95 value 5 ] edge [ source 240 target 58 value 1 ] edge [ source 240 target 27 value 1 ] edge [ source 240 target 172 value 2 ] edge [ source 240 target 23 value 1 ] edge [ source 240 target 88 value 1 ] edge [ source 241 target 16 value 1 ] edge [ source 241 target 1 value 2 ] edge [ source 241 target 12 value 2 ] edge [ source 241 target 84 value 5 ] edge [ source 241 target 86 value 4 ] edge [ source 241 target 137 value 3 ] edge [ source 241 target 24 value 2 ] edge [ source 241 target 36 value 1 ] edge [ source 242 target 190 value 1 ] edge [ source 243 target 190 value 1 ] edge [ source 244 target 202 value 1 ] edge [ source 244 target 199 value 1 ] edge [ source 244 target 195 value 1 ] edge [ source 244 target 193 value 2 ] edge [ source 244 target 245 value 1 ] edge [ source 244 target 283 value 1 ] edge [ source 244 target 44 value 10 ] edge [ source 245 target 187 value 1 ] edge [ source 245 target 219 value 2 ] edge [ source 245 target 233 value 4 ] edge [ source 245 target 275 value 4 ] edge [ source 245 target 276 value 10 ] edge [ source 245 target 142 value 1 ] edge [ source 245 target 148 value 3 ] edge [ source 245 target 252 value 1 ] edge [ source 245 target 282 value 2 ] edge [ source 245 target 238 value 1 ] edge [ 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value 1 ] edge [ source 250 target 97 value 1 ] edge [ source 250 target 204 value 1 ] edge [ source 250 target 44 value 1 ] edge [ source 251 target 97 value 1 ] edge [ source 251 target 44 value 1 ] edge [ source 252 target 190 value 1 ] edge [ source 253 target 152 value 1 ] edge [ source 253 target 153 value 1 ] edge [ source 253 target 97 value 4 ] edge [ source 253 target 249 value 22 ] edge [ source 253 target 227 value 7 ] edge [ source 253 target 273 value 1 ] edge [ source 253 target 268 value 9 ] edge [ source 253 target 44 value 22 ] edge [ source 254 target 97 value 15 ] edge [ source 254 target 177 value 1 ] edge [ source 254 target 44 value 18 ] edge [ source 255 target 12 value 9 ] edge [ source 255 target 2 value 6 ] edge [ source 255 target 117 value 1 ] edge [ source 255 target 257 value 1 ] edge [ source 255 target 125 value 13 ] edge [ source 255 target 177 value 2 ] edge [ source 256 target 12 value 1 ] edge [ source 256 target 117 value 1 ] edge [ source 256 target 98 value 1 ] edge [ source 256 target 125 value 1 ] edge [ source 256 target 252 value 3 ] edge [ source 256 target 220 value 1 ] edge [ source 256 target 177 value 1 ] edge [ source 257 target 12 value 7 ] edge [ source 257 target 2 value 7 ] edge [ source 257 target 117 value 1 ] edge [ source 257 target 118 value 1 ] edge [ source 257 target 255 value 1 ] edge [ source 257 target 125 value 6 ] edge [ source 257 target 172 value 3 ] edge [ source 257 target 177 value 1 ] edge [ source 258 target 12 value 1 ] edge [ source 258 target 137 value 5 ] edge [ source 258 target 170 value 1 ] edge [ source 258 target 125 value 2 ] edge [ source 258 target 177 value 1 ] edge [ source 259 target 123 value 1 ] edge [ source 259 target 167 value 6 ] edge [ source 259 target 137 value 7 ] edge [ source 259 target 184 value 1 ] edge [ source 259 target 258 value 1 ] edge [ source 259 target 172 value 8 ] edge [ source 259 target 177 value 1 ] edge [ source 260 target 191 value 2 ] edge [ source 261 target 12 value 5 ] edge [ source 261 target 117 value 4 ] edge [ source 261 target 137 value 5 ] edge [ source 261 target 142 value 2 ] edge [ source 261 target 185 value 5 ] edge [ source 261 target 172 value 1 ] edge [ source 262 target 233 value 15 ] edge [ source 262 target 44 value 18 ] edge [ source 263 target 233 value 6 ] edge [ source 263 target 275 value 15 ] edge [ source 263 target 44 value 18 ] edge [ source 264 target 275 value 15 ] edge [ source 264 target 44 value 18 ] edge [ source 265 target 275 value 6 ] edge [ source 265 target 276 value 15 ] edge [ source 265 target 44 value 18 ] edge [ source 266 target 276 value 15 ] edge [ source 266 target 44 value 18 ] edge [ source 267 target 276 value 6 ] edge [ source 267 target 277 value 15 ] edge [ source 267 target 44 value 18 ] edge [ source 268 target 44 value 25 ] edge [ source 269 target 44 value 25 ] edge [ source 270 target 269 value 2 ] edge [ source 270 target 271 value 16 ] edge [ source 270 target 44 value 15 ] edge [ source 271 target 44 value 25 ] edge [ source 272 target 164 value 1 ] edge [ source 272 target 271 value 2 ] edge [ source 272 target 273 value 16 ] edge [ source 272 target 44 value 15 ] edge [ source 273 target 44 value 25 ] edge [ source 274 target 273 value 2 ] edge [ source 274 target 268 value 16 ] edge [ source 274 target 44 value 15 ] edge [ source 275 target 162 value 2 ] edge [ source 275 target 234 value 1 ] edge [ source 275 target 269 value 1 ] edge [ source 275 target 44 value 29 ] edge [ source 276 target 164 value 2 ] edge [ source 276 target 271 value 1 ] edge [ source 276 target 273 value 1 ] edge [ source 276 target 44 value 29 ] edge [ source 277 target 165 value 2 ] edge [ source 277 target 249 value 1 ] edge [ source 277 target 268 value 1 ] edge [ source 277 target 44 value 29 ] edge [ source 278 target 274 value 1 ] edge [ source 278 target 277 value 4 ] edge [ source 278 target 97 value 9 ] edge [ source 278 target 269 value 1 ] edge [ source 278 target 271 value 9 ] edge [ source 278 target 273 value 22 ] edge [ source 278 target 268 value 7 ] edge [ source 278 target 44 value 22 ] edge [ source 279 target 276 value 8 ] edge [ source 279 target 246 value 1 ] edge [ source 279 target 44 value 10 ] edge [ source 280 target 277 value 6 ] edge [ source 280 target 97 value 15 ] edge [ source 280 target 44 value 18 ] edge [ source 281 target 277 value 15 ] edge [ source 281 target 44 value 18 ] edge [ source 282 target 219 value 1 ] edge [ source 282 target 142 value 1 ] edge [ source 282 target 238 value 1 ] edge [ source 282 target 200 value 1 ] edge [ source 282 target 44 value 2 ] edge [ source 282 target 44 value 2 ] edge [ source 283 target 202 value 1 ] edge [ source 283 target 199 value 1 ] edge [ source 283 target 276 value 2 ] edge [ source 283 target 195 value 2 ] edge [ source 283 target 193 value 2 ] edge [ source 283 target 244 value 2 ] edge [ source 283 target 44 value 8 ] edge [ source 284 target 187 value 1 ] edge [ source 284 target 233 value 1 ] edge [ source 284 target 275 value 1 ] edge [ source 284 target 276 value 1 ] edge [ source 284 target 277 value 1 ] edge [ source 284 target 142 value 1 ] edge [ source 284 target 145 value 1 ] edge [ source 284 target 244 value 1 ] edge [ source 284 target 249 value 1 ] edge [ source 284 target 227 value 1 ] edge [ source 284 target 221 value 1 ] edge [ source 284 target 183 value 1 ] edge [ source 284 target 271 value 1 ] edge [ source 284 target 273 value 1 ] edge [ source 284 target 268 value 1 ] edge [ source 284 target 44 value 1 ] edge [ source 284 target 44 value 10 ] edge [ source 285 target 44 value 1 ] edge [ source 286 target 44 value 1 ] edge [ source 287 target 44 value 1 ] edge [ source 288 target 44 value 1 ] edge [ source 289 target 44 value 1 ] edge [ source 290 target 44 value 1 ] edge [ source 291 target 44 value 1 ] edge [ source 292 target 44 value 1 ] edge [ source 293 target 44 value 1 ] edge [ source 294 target 44 value 1 ] edge [ source 295 target 190 value 1 ] edge [ source 296 target 190 value 1 ] ] python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_lcf.c0000644000076500000240000000422413612122633026161 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g, g2; igraph_bool_t iso; // Franklin graph igraph_lcf(&g, 12, 5, -5, 6, 0); igraph_famous(&g2, "franklin"); igraph_isomorphic_vf2(&g, &g2, /*vertex.color1=*/ 0, /*vertex.color2=*/ 0, /*edge.color1=*/ 0, /*edge.color2=*/ 0, &iso, 0, 0, 0, 0, 0); if (!iso) { printf("Failure: Franklin\n"); return 1; } igraph_destroy(&g); igraph_destroy(&g2); // [3, -2]^4, n=8 igraph_lcf(&g, 8, 3, -2, 4, 0); if (igraph_ecount(&g) != 16) { printf("Failure: [3, -2]^4, n=8\n"); return 1; } igraph_destroy(&g); // [2, -2]^2, n=2 igraph_lcf(&g, 2, 2, -2, 2, 0); if (igraph_ecount(&g) != 1) { printf("Failure: [2, -2]^2, n=2\n"); return 1; } igraph_destroy(&g); // [2]^2, n=2 igraph_lcf(&g, 2, 2, 2, 0); if (igraph_ecount(&g) != 1) { printf("Failure: [2]^2, n=2\n"); return 1; } igraph_destroy(&g); // Regression test for bug #996 igraph_lcf(&g, 0, 0); if (igraph_vcount(&g) != 0 || igraph_ecount(&g) != 0) { printf("Failure: regression test for #996\n"); return 1; } igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_sparsemat5.out0000644000076500000240000000226213524616144030075 0ustar tamasstaff000000000000003.79369 0.272513 0.387127 0.421856 0.429479 0.344793 0.266584 0.24469 0.239837 0.235697 0.224848 3.79369 0.272513 0.387127 0.421856 0.429479 0.344793 0.266584 0.24469 0.239837 0.235697 0.224848 3.79369 0.272513 0.387127 0.421856 0.429479 0.344793 0.266584 0.24469 0.239837 0.235697 0.224848 -- 2.61264 0 0.467245 0.571573 0.427081 0.335532 0.263456 0.130696 0.0780048 0.0731022 0.112985 0.222086 -- rnsolve: - eigenvalues: 2 0 - eigenvectors: 1 rssolve: - eigenvalues: 2 - eigenvectors: 1 rnsolve: - eigenvalues: 0 0 - eigenvectors: 1 rssolve: - eigenvalues: 0 - eigenvectors: 1 rnsolve: - eigenvalues: -3 0 - eigenvectors: 1 rssolve: - eigenvalues: -3 - eigenvectors: 1 -- rnsolve: - eigenvalues: 5 0 0 0 - eigenvectors: 1 -4 2 2 rssolve: - eigenvalues: 5 0 - eigenvectors: 1 -4 2 2 rnsolve: - eigenvalues: 5.37228 0 -0.372281 0 - eigenvectors: 1.37228 -4.37228 3 3 rnsolve: - eigenvalues: 2.5 6.91014 2.5 -6.91014 - eigenvectors: -1.5 6.91014 10 0 rnsolve: - eigenvalues: 0 0 0 0 - eigenvectors: 1 0 0 1 rssolve: - eigenvalues: 0 0 - eigenvectors: 1 0 0 1 python-igraph-0.8.0/vendor/source/igraph/examples/simple/bipartite.net0000644000076500000240000000025113524616144026415 0ustar tamasstaff00000000000000*Vertices 13 8 1 "A" 2 "B" 3 "C" 4 "D" 5 "E" 6 "F" 7 "G" 8 "H" 9 "x-1" 10 "x-2" 11 "x-3" 12 "x-4" 13 "x-5" *Edges 1 10 1 13 2 12 3 10 3 11 4 11 5 12 5 13 6 12 8 11 8 13 python-igraph-0.8.0/vendor/source/igraph/examples/simple/matrix2.c0000644000076500000240000002246413612122634025460 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include void print_matrix(igraph_matrix_t *m) { long int i, j; for (i = 0; i < igraph_matrix_nrow(m); i++) { for (j = 0; j < igraph_matrix_ncol(m); j++) { printf(" %g", MATRIX(*m, i, j)); } printf("\n"); } } void print_vector(igraph_vector_t *v) { long int i, n = igraph_vector_size(v); for (i = 0; i < n; i++) { printf(" %g", VECTOR(*v)[i]); } printf("\n"); } void byrow(igraph_matrix_t *m) { long int r = igraph_matrix_nrow(m), c = igraph_matrix_ncol(m); long int n = 0, i, j; for (i = 0; i < r; i++) { for (j = 0; j < c; j++) { MATRIX(*m, i, j) = n++; } } } #define apply(m,a,b) \ for (i=0; i 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void print_result(const igraph_plfit_result_t* result) { printf("continuous = %s\n", result->continuous ? "true" : "false"); printf("alpha = %.5f\n", result->alpha); printf("xmin = %.5f\n", result->xmin); printf("L = %.5f\n", result->L); printf("D = %.5f\n", result->D); printf("p = %.5f\n", result->p); printf("====================\n"); } int test_continuous() { igraph_plfit_result_t result; igraph_vector_t vector; double data[] = { 1.52219974, 6.80675663, 1.02798042, 1.31180733, 3.97473174, 1.17209342, 1.64889191, 2.47764721, 1.32939375, 3.03762554, 1.62638327, 6.08405495, 1.70890382, 1.05294973, 1.17408407, 4.48945532, 1.16777371, 2.52502391, 1.09755984, 1.63838051, 1.03811206, 1.47224168, 1.57161431, 1.60163451, 2.08280263, 1.04678340, 1.33317526, 1.58588741, 1.26484666, 1.02367503, 1.57045702, 3.42374138, 1.23190611, 1.09378228, 1.04959505, 1.05818408, 1.43879491, 2.22750459, 1.41027204, 1.81964745, 2.80239939, 1.25399323, 1.07479219, 3.94616077, 1.26367914, 1.87367507, 1.35741026, 1.14867526, 7.33024762, 1.87957274, 2.79258534, 1.21682159, 1.61194300, 2.81885973, 1.21514746, 1.12850917, 51.85245035, 1.21883209, 1.04861029, 1.69215609, 2.18429429, 1.59752172, 1.41909984, 3.14393355, 1.18298455, 1.67063821, 1.88568524, 1.07445906, 1.45007973, 1.12568920, 1.56806310, 1.36996101, 1.19440982, 6.57296980, 1.35860725, 1.06552137, 1.16950701, 1.34750790, 1.66977492, 1.22658722, 1.62247444, 1.23458784, 8.55843760, 1.70020162, 4.76368831, 1.04846170, 1.13689661, 1.94449567, 1.10584812, 1.32525767, 1.26640912, 1.91372972, 1.56185373, 2.37829675, 1.04616674, 2.43549177, 1.14961092, 1.82106455, 1.25818298, 1.64763037, 1.43019402, 1.50439978, 1.90281251, 1.34827040, 1.57935671, 1.77260751, 1.06976614, 1.12236012, 2.19770254, 1.51825533, 1.19027804, 1.08307524, 1.57912902, 3.33313888, 2.14005088, 1.38341873, 1.20088138, 1.25870539, 1.03811620, 1.86622820, 2.99310953, 1.55615055, 2.12364873, 4.49081000, 1.01274439, 1.22373389, 3.79059729, 3.10099275, 2.70218546, 1.03609624, 2.20776919, 1.00651347, 1.87344592, 1.04903307, 1.24899747, 1.20377911, 1.12706494, 1.01706713, 7.01069306, 1.05363146, 2.50105512, 1.11168552, 1.71133998, 1.17714528, 1.37986755, 2.20981534, 1.18179277, 2.07982010, 4.04967099, 1.00680257, 1.62850069, 2.58816230, 1.35079027, 1.03382890, 4.54326500, 1.62489905, 1.36102570, 1.52349738, 1.06606346, 7.80558026, 1.02602538, 1.43330925, 1.36040920, 9.29692547, 15.27015690, 1.75966437, 1.02635409, 1.40421505, 2.87296958, 1.46232202, 1.87065204, 3.37278803, 1.82589564, 1.06488044, 1.72568108, 1.21062115, 4.39311214, 1.12636227, 2.20820528, 1.09826903, 2.58989998, 1.34944949, 1.08654244, 2.38021951, 3.96308780, 1.37494639, 1.18245279, 3.72506217, 3.79775023, 1.19018356, 2.86924476, 3.40015888, 1.92317855, 1.55203754, 1.34985008, 1.31480190, 1.65899877, 4.77446435, 1.41073246, 1.35555456, 2.40543613, 2.72162935, 1.34475982, 1.41342115, 5.15278473, 1.69654436, 3.21081899, 1.18822397, 1.40394863, 1.06793574, 1.67085563, 1.08125975, 1.11765459, 1.17245045, 1.15711479, 1.18656910, 1.61296203, 1.71427634, 1.24017302, 2.05291524, 2.52658791, 2.04645295, 34.07541626, 1.32670899, 1.03893757, 1.08957199, 5.55332328, 1.17276097, 1.60389480, 2.02098430, 2.92934928, 1.00558653, 1.05830070, 1.81440889, 3.85044779, 1.12317456, 1.39547640, 2.93105179, 1.95048788, 1.05602445, 1.96855429, 1.60432293, 3.28820202, 1.50117325, 1.19775674, 1.28280841, 1.08318646, 1.02098264, 1.24861938, 1.06511473, 1.07549717, 3.57739126, 1.07265409, 1.06312441, 1.16296512, 3.83654484, 2.02366951, 1.73168875, 1.60443228, 2.30779766, 1.50531775, 1.31925607, 1.87926179, 1.86249354, 2.14768716, 2.31583955, 2.15651148, 1.29677318, 1.10110071, 1.03383916, 1.50665009, 1.16502917, 1.40055008, 2.80847193, 1.29824634, 2.76239920, 1.73123621, 1.15286577, 1.89493526, 1.63112634, 1.17828846, 1.01293513, 1.84834048, 4.19026736, 1.82684815, 3.51812301, 1.33499862, 2.03087497, 1.32419883, 1.34126954, 1.98250684, 1.00025697, 1.59416883, 6.38249787, 2.79055559, 1.57750678, 1.36953983, 1.37513919, 3.63573178, 1.15637432, 9.28386344, 1.16947695, 1.54995742, 1.44018755, 1.29332881, 1.81274872, 1.14900153, 1.07117403, 1.17035915, 1.39229249, 1.96645872, 1.09147706, 1.25211993, 1.07092474, 1.85394206, 1.29807741, 3.41499510, 1.22444449, 1.00913782, 3.87431854, 1.01072376, 1.01186727, 3.00175639, 2.52183377, 1.23992099, 1.69819010, 1.36850400, 1.14577814, 1.06035078, 1.08414298, 1.55920217, 5.07059630, 1.15434572, 1.41873305, 1.24712256, 1.10478618, 1.30707247, 1.85719110, 1.89873207, 1.72629431, 1.65171651, 7.10864875, 2.31945709, 1.06722361, 1.26696259, 2.23845503, 1.38674196, 1.91015397, 1.29590323, 1.10448028, 4.52757499, 2.00258408, 1.38299092, 1.01431427, 1.54039270, 1.34880396, 1.08784083, 1.35553378, 1.37307373, 1.32320467, 1.50261683, 6.91050685, 1.06083157, 1.20841351, 2.92719840, 2.82178183, 2.05765813, 1.84621661, 1.04677388, 2.13801850, 1.39654855, 1.13037727, 1.37887598, 1.03221650, 1.15981176, 1.09896163, 1.88624084, 1.43459062, 1.54587662, 1.48604380, 2.06197392, 1.97079675, 4.31388672, 2.94376994, 3.48708489, 1.09674551, 2.46926816, 1.23705940, 1.57512843, 1.15595205, 1.18432818, 1.54298936, 1.60600489, 1.07361787, 1.38666771, 1.45533003, 1.78940830, 1.33799752, 1.12955889, 4.59400278, 1.15170228, 1.39346636, 1.61408789, 2.21293753, 5.33166143, 1.18147947, 1.54426891, 1.32496426, 1.25037632, 3.31244261, 1.36211171, 1.82239599, 1.75235087, 1.67044831, 1.24802350, 1.34776327, 1.34740665, 1.30664120, 1.06852680, 1.22513631, 1.25310923, 1.36394926, 1.07796356, 3.10823551, 1.46770227, 1.40264883, 1.08787681, 1.26460358, 1.10348946, 2.03168839, 1.09435135, 1.66991715, 1.19738540, 1.28922229, 2.85704149, 1.33952521, 1.73497688, 2.90052876, 5.34596348, 1.36399078, 3.38399264, 1.06089658, 1.09370142, 1.37523679, 3.01964907, 1.40684792, 1.11312672, 2.44666372, 1.73953904, 1.65569280, 1.05813000, 2.02893022, 1.72877601, 1.55758690, 1.83904301, 1.14316984, 1.17792251, 1.44106281, 9.67126482, 1.93207441, 1.08242887, 2.87271135, 2.19095115, 2.13195479, 1.02355472, 1.18218470, 1.30907724, 1.13291587, 2.85659336, 12.62726889, 1.18818589, 1.02852443, 1.12838670, 1.36349361, 1.34817100, 1.30535737, 3.22225028, 1.28680350, 1.83979657, 1.11088952, 1.43866586, 8.52587567, 3.73988696, 2.65816056, 1.17373111, 2.61567111, 3.24024082, 2.96798864, 1.05335616, 1.31159271, 1.36485918, 1.24988767, 7.80609746, 1.54892174, 1.10682809, 1.21728827, 1.20429971, 1.72719055, 1.78534831, 1.04414979, 1.25646988, 1.19788383, 1.08854812, 1.04859628, 1.04676064, 5.07295341, 3.83595341, 1.61079632, 1.10528426, 1.15050241, 2.78129736, 1.25494119, 1.28692155, 1.06812292, 3.29393761, 1.37542463, 1.67241953, 1.21698665, 10.57727604, 8.63598976, 1.18886984, 1.30609583, 9.47777457, 1.69612900, 2.23002585, 1.58461615, 1.04110023, 3.08140806, 1.39599251, 1.06575789, 1.29741002, 1.75253864, 1.82594258, 1.15111702, 1.17370053, 1.15254396, 1.94401179, 5.36344596, 4.66322185, 1.15073993, 3.21478159, 1.39843306, 1.03961906, 5.72845289, 1.72454161, 1.04610704, 1.38975310, 1.77732797, 1.10139931, 2.23656355, 1.89952669, 1.72136921, 1.15798212, 1.59545971, 1.08789161, 1.93272206, 2.57480708, 1.04977784, 2.00874078, 3.40065861, 1.00978603, 3.97804652, 1.54762586, 1.01015493, 1.15148220, 1.15246483, 19.67426012, 1.33290993, 2.33137522, 1.12841749, 1.73407057, 2.00469493, 1.27418995, 1.49814918, 1.10398785, 1.20063760, 1.05536150, 1.87616599, 1.49305736, 1.60241346, 1.16666060, 1.05013736, 1.77929210, 1.00206028, 3.41096863, 1.47499925, 1.14071240, 1.65361002, 1.76466424, 8.49298111, 1.41069285, 2.11681605, 4.90260842, 1.13029658, 1.20802818, 1.42525579, 1.00310774, 1.08082363, 9.95194247, 2.82773946, 2.77420002, 1.82543685, 1.28557906, 1.97711769, 1.19001264, 1.95712650, 1.54230291, 1.31625757, 2.36364128, 1.11523099, 1.00343756, 1.71299382, 1.44667100, 2.38154868, 1.41174217, 1.80660493, 1.51020853, 1.16761479, 1.25898190, 1.18150781, 1.58465451, 2.03560597, 3.48531184, 1.21187672, 1.35111036, 1.02954922, 1.90892663, 3.99078548, 5.67385199, 4.38055264, 1.17446048, 13.41617858, 1.60241740, 1.14811206, 4.68120263, 3.83763710, 2.66095263, 1.83338503, 4.75973082, 1.08982301, 4.04104276, 1.34220189, 1.06135891, 2.71185882, 1.46085873, 1.09915614, 10.35178646, 2.54402271, 2.65696704, 1.31388649, 1.02942408, 1.57780748, 1.01552697, 2.24860361, 2.22011778, 1.13595134, 1.11492512, 2.11966788, 1.20420149, 1.11112428, 3.09324603, 2.87240762, 1.50486558, 1.92227231, 4.12480449, 1.58244751, 1.69922308, 6.28134904, 2.91944178, 1.85386792, 1.41799519, 1.64636127, 2.05837832, 1.07153521, 2.05376943, 2.60053549, 1.09773382, 1.54671309, 1.68007415, 3.43941489, 1.41601033, 2.00237256, 1.20830978, 1.25582363, 1.10830461, 1.24850906, 1.88035202, 1.70557719, 1.04191110, 1.33501003, 1.33554804, 1.36935735, 4.79153510, 1.06566392, 1.14495966, 1.90020028, 1.08266994, 1.20588153, 1.40730214, 4.34320304, 1.71762330, 1.06620797, 1.39695239, 1.03024563, 3.94971225, 5.02945862, 1.06145571, 1.42511911, 2.13889169, 1.04986044, 1.91400616, 5.50708156, 1.52870464, 1.11303137, 1.05282759, 1.83793940, 3.05244089, 2.64499634, 1.51688076, 2.63350152, 1.31014486, 1.69462474, 1.67792130, 1.34236945, 1.02358460, 1.04593509, 1.04007620, 1.87990081, 1.28585413, 1.01636283, 3.55338495, 1.19542700, 1.23630628, 1.32321942, 4.03762786, 1.25379147, 1.12330233, 1.24966418, 1.26323243, 1.14779989, 1.20378343, 1.01531796, 1.44500318, 1.72723672, 15.68799957, 1.37641063, 7.00788166, 3.89674130, 1.68303382, 1.10089816, 1.72831362, 2.70479861, 1.75821836, 2.32404215, 2.64165162, 1.42441301, 1.83256456, 1.12548819, 4.81273800, 2.52840227, 2.68430190, 1.00928919, 1.02438446, 1.33909276, 2.32261242, 1.01299124, 1.07614975, 1.66823898, 1.97172786, 1.01707292, 1.68325092, 1.76834032, 1.08952069, 1.02265517, 1.96843176, 1.83351706, 1.92704772, 18.44811035, 1.00178046, 2.70555953, 1.35839004, 1.04834633, 1.26649072, 2.87152600, 4.12536409, 1.25200853, 1.71199647, 1.61175739, 1.26313274, 1.75224120, 2.70412800, 1.33998630, 1.61271556, 2.65784769, 10.38771107, 1.33121364, 1.01207979, 2.00238212, 2.50195600, 1.96917548, 1.71618169, 1.37050585, 10.11861690, 1.18339112, 1.80083386, 2.88582103, 1.21935761, 2.37900131, 1.49449487, 4.75106319, 2.33977804, 2.87963540, 1.01807103, 3.74847411, 1.71981276, 1.50726964, 1.20723219, 1.37904840, 1.04565533, 1.59877004, 1.11481349, 2.17320556, 2.07108468, 1.23274077, 1.75180110, 1.27558910, 1.63240839, 1.58760550, 1.01266256, 1.30395323, 1.14618521, 1.02385023, 2.24198100, 1.26765471, 1.15855534, 1.83936251, 1.32970987, 1.25844192, 1.31133485, 4.74300303, 6.19325623, 1.31832913, 3.97645560, 1.00545340, 1.24431862, 1.25855820, 1.15514241, 1.35986865, 1.72446070, 1.13069572, 2.45890932, 1.00394684, 1.03533631, 1.87698184, 2.34576160, 1.03997887, 1.02694456, 2.52227100, 2.66278467, 1.17002905, 3.42239624, 2.46753038, 1.17103623, 1.07832850, 1.42782632, 1.29110546, 1.03435772, 1.33512109, 1.14337058, 1.34103634, 1.15155161, 2.59805360, 2.09650343, 1.53399143, 1.02319185, 1.32210667, 1.05720671, 1.20882651, 2.34881662, 1.05163662, 3.26219380, 10.58124156, 1.07283644, 1.02105339, 1.23268679, 1.81469813, 1.49393533, 1.29760853, 5.37676625, 1.02529938, 1.86815537, 1.57961476, 3.77408176, 2.79405589, 3.25246617, 1.63913824, 3.12133428, 1.03787574, 4.17232960, 1.33406468, 1.57119541, 1.13675102, 3.42874720, 1.13066210, 1.33896458, 1.23883935, 1.35272696, 1.15172654, 2.18633755, 1.23251881, 1.59742606, 1.08718410, 1.06168544, 1.19926517, 1.00214807, 1.29121086, 3.44575916, 1.26524744, 1.16718301, 4.11789988, 1.25375574, 1.35753968, 1.69247751, 1.28473150, 2.20669768, 1.53213883, 2.30598771, 1.68420243, 1.37320685, 2.08619411, 1.26990265, 1.82215898, 1.10656122, 1.40229835, 1.11896817, 1.00127366, 2.88218857, 2.79105702, 1.28699225, 1.15929737, 1.07928363, 10.54130128, 8.79261793, 1.15699405, 1.69050500, 2.76586152, 1.22802809, 1.38014655, 2.19208585, 1.64409370, 1.46918371, 2.99582898, 1.37759923, 1.29776632, 1.82884215, 2.67317357, 1.37063041, 1.26884340, 1.07874723, 1.48172681, 1.01771849, 2.40642202, 1.37115433, 1.05954574, 2.12998246, 2.34178079, 1.54515623, 1.00179963, 2.12228030, 1.46007334, 1.20664530, 1.31417158, 1.03322353, 1.95420119, 1.30541569, 1.15016102, 2.17036908, 2.81707947, 1.16173181, 2.01742565, 1.02478594, 1.57428560, 1.21209176, 2.20735202, 1.12935761, 2.08850147, 1.05353378, 1.02324910, 1.49636415, 1.48061026, 2.25651770, 3.04296168, 1.24380806, 1.07707360, 2.00284318, 10.02810932, 3.38695326, 6.82841534, 2.13556915, 1.19152238 }; igraph_vector_view(&vector, data, sizeof(data) / sizeof(data[0])); /* determining xmin and alpha */ if (igraph_power_law_fit(&vector, &result, -1, 0)) { return 1; } print_result(&result); /* determining alpha only */ if (igraph_power_law_fit(&vector, &result, 2, 0)) { return 2; } print_result(&result); return 0; } int test_discrete() { igraph_plfit_result_t result; igraph_vector_t vector; double data[] = { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 2, 5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 4, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 5, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 1, 6, 1, 1, 5, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 4, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 3, 1, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 5, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 4, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 4, 1, 1, 14, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 2, 1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 4, 1, 1, 1, 1, 1, 5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 5, 1, 1, 5, 1, 1, 1, 2, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 1, 2, 1, 3, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 1, 1, 1, 1, 2, 4, 1, 1, 1, 1, 1, 1, 1, 4, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 2, 11, 1, 33, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 9, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 2, 1, 1, 1, 2, 2, 1, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 16, 1, 1, 1, 1, 1, 2, 1, 1, 3, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 12, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 5, 1, 1, 1, 1, 1, 1, 2, 1, 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 4, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 2, 1, 1, 1, 2 }; igraph_vector_view(&vector, data, sizeof(data) / sizeof(data[0])); /* determining xmin and alpha */ if (igraph_power_law_fit(&vector, &result, -1, 0)) { return 3; } print_result(&result); /* determining alpha only */ if (igraph_power_law_fit(&vector, &result, 2, 0)) { return 4; } print_result(&result); /* forcing continuous fitting */ if (igraph_power_law_fit(&vector, &result, -1, 1)) { return 5; } print_result(&result); /* forcing continuous fitting, xmin given */ if (igraph_power_law_fit(&vector, &result, 2, 1)) { return 6; } print_result(&result); return 0; } int main() { int retval; retval = test_continuous(); if (retval) { return retval; } retval = test_discrete(); if (retval) { return retval; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_complementer.c0000644000076500000240000000607413612122633030114 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g1, g2; /* complementer of the empty graph */ igraph_empty(&g1, 5, IGRAPH_DIRECTED); igraph_complementer(&g2, &g1, IGRAPH_LOOPS); igraph_write_graph_edgelist(&g2, stdout); igraph_destroy(&g1); igraph_destroy(&g2); printf("---\n"); /* the same without loops */ igraph_empty(&g1, 5, IGRAPH_DIRECTED); igraph_complementer(&g2, &g1, IGRAPH_NO_LOOPS); igraph_write_graph_edgelist(&g2, stdout); igraph_destroy(&g1); igraph_destroy(&g2); printf("---\n"); /* complementer of the full graph */ igraph_full(&g1, 5, IGRAPH_DIRECTED, IGRAPH_LOOPS); igraph_complementer(&g2, &g1, IGRAPH_LOOPS); if (igraph_ecount(&g2) != 0) { return 1; } igraph_destroy(&g1); igraph_destroy(&g2); printf("---\n"); /* complementer of the full graph, results loops only */ igraph_full(&g1, 5, IGRAPH_DIRECTED, IGRAPH_NO_LOOPS); igraph_complementer(&g2, &g1, IGRAPH_LOOPS); igraph_write_graph_edgelist(&g2, stdout); igraph_destroy(&g1); igraph_destroy(&g2); printf("---\n"); /************** * undirected * *************/ /* complementer of the empty graph */ igraph_empty(&g1, 5, IGRAPH_UNDIRECTED); igraph_complementer(&g2, &g1, IGRAPH_LOOPS); igraph_write_graph_edgelist(&g2, stdout); igraph_destroy(&g1); igraph_destroy(&g2); printf("---\n"); /* the same without loops */ igraph_empty(&g1, 5, IGRAPH_UNDIRECTED); igraph_complementer(&g2, &g1, IGRAPH_NO_LOOPS); igraph_write_graph_edgelist(&g2, stdout); igraph_destroy(&g1); igraph_destroy(&g2); printf("---\n"); /* complementer of the full graph */ igraph_full(&g1, 5, IGRAPH_UNDIRECTED, IGRAPH_LOOPS); igraph_complementer(&g2, &g1, IGRAPH_LOOPS); if (igraph_ecount(&g2) != 0) { return 1; } igraph_destroy(&g1); igraph_destroy(&g2); printf("---\n"); /* complementer of the full graph, results loops only */ igraph_full(&g1, 5, IGRAPH_UNDIRECTED, IGRAPH_NO_LOOPS); igraph_complementer(&g2, &g1, IGRAPH_LOOPS); igraph_write_graph_edgelist(&g2, stdout); igraph_destroy(&g1); igraph_destroy(&g2); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_is_multiple.c0000644000076500000240000000337413612122633027750 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void print_vector(igraph_vector_bool_t *v, FILE *f) { long int i; for (i = 0; i < igraph_vector_bool_size(v); i++) { fprintf(f, " %i", (int) VECTOR(*v)[i]); } fprintf(f, "\n"); } int main() { igraph_t graph; igraph_vector_bool_t v; igraph_vector_bool_init(&v, 0); igraph_small(&graph, 0, IGRAPH_DIRECTED, 0, 1, 1, 2, 2, 1, 0, 1, 1, 0, 3, 4, 11, 10, -1); igraph_is_multiple(&graph, &v, igraph_ess_all(IGRAPH_EDGEORDER_ID)); print_vector(&v, stdout); igraph_destroy(&graph); igraph_small(&graph, 0, IGRAPH_UNDIRECTED, 0, 0, 1, 2, 1, 1, 2, 2, 2, 1, 2, 3, 2, 4, 2, 5, 2, 6, 2, 2, 3, 2, 0, 0, 6, 2, 2, 2, 0, 0, -1); igraph_is_multiple(&graph, &v, igraph_ess_all(IGRAPH_EDGEORDER_ID)); print_vector(&v, stdout); igraph_destroy(&graph); igraph_vector_bool_destroy(&v); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_star.c0000644000076500000240000000163713612122634026374 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_k_regular_game.out0000644000076500000240000000047013524616144030754 0ustar tamasstaff000000000000004 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_scg_grouping.out0000644000076500000240000000372013524616144030477 0ustar tamasstaff000000000000000 1 3 2 4 4 3 5 3 3 5 0 3 0 5 1 1 0 0 4 0 4 4 1 4 4 5 0 4 0 1 1 1 0 4 5 5 3 1 5 3 5 1 4 1 4 5 1 3 0 4 4 4 5 5 4 5 1 0 1 1 4 5 2 2 2 0 1 1 4 4 5 2 4 4 3 1 0 4 2 4 1 2 1 3 0 2 1 4 4 3 2 4 5 1 5 3 4 0 5 4 1 4 0 3 4 0 0 2 4 2 5 1 0 1 3 4 2 1 2 3 5 2 2 5 2 4 4 4 0 1 4 2 3 0 4 4 1 5 4 5 2 3 4 4 4 4 4 4 4 1 3 2 0 4 1 0 4 1 0 4 1 0 5 5 1 4 3 2 4 5 2 2 1 4 0 2 3 4 1 4 0 0 1 2 5 2 1 4 0 0 1 1 5 5 2 2 2 4 2 1 0 1 5 2 2 0 1 3 4 1 5 1 2 5 2 4 2 0 1 0 1 5 4 0 4 0 4 1 4 1 5 1 5 2 4 5 0 4 0 3 4 1 4 1 5 0 4 4 2 5 2 1 3 1 1 4 1 0 1 2 3 1 5 4 4 1 1 5 1 3 5 1 4 1 1 1 0 1 5 0 0 1 2 4 0 4 3 0 5 0 4 2 4 3 4 5 0 5 5 2 1 2 4 1 2 2 1 5 4 0 2 5 5 3 1 5 5 0 0 4 5 3 5 1 1 5 3 3 3 3 4 2 3 2 0 1 1 1 4 5 4 4 1 1 1 2 2 2 3 3 4 5 2 1 2 3 4 1 0 1 1 0 0 3 5 4 1 2 3 3 1 1 4 4 1 2 4 0 2 1 4 4 4 3 4 4 3 3 4 4 4 3 1 3 2 4 2 1 3 3 4 3 1 4 5 4 4 3 0 0 4 5 5 0 1 5 1 1 3 4 4 4 1 4 3 0 2 2 3 5 3 2 1 3 4 1 4 1 4 4 1 0 4 3 2 1 0 5 1 1 4 2 2 3 0 2 4 2 1 2 1 1 4 2 3 5 5 4 1 5 4 4 4 5 0 1 3 3 2 1 4 1 1 5 2 2 2 5 2 2 4 0 2 2 1 3 0 5 5 5 4 0 4 0 4 0 2 1 0 3 3 2 1 1 4 2 5 1 3 2 1 4 4 3 1 5 1 2 2 3 1 0 5 0 5 3 4 4 1 4 1 1 5 4 1 0 5 2 4 4 1 3 4 1 4 5 5 1 2 1 4 4 5 3 5 5 0 5 2 1 4 5 0 4 4 2 1 2 5 4 1 1 5 5 1 2 3 2 1 1 2 4 0 5 5 5 0 4 3 2 4 1 4 5 5 2 3 1 4 1 5 4 1 3 1 2 1 1 4 3 4 1 5 1 5 5 4 2 2 5 1 5 1 1 0 2 5 4 4 2 1 1 4 4 4 5 2 3 0 1 0 4 2 4 1 1 4 4 3 2 0 3 2 2 1 4 3 2 0 4 4 3 0 4 1 2 0 1 4 1 4 1 0 3 2 3 3 1 2 1 4 2 2 3 0 0 4 4 1 1 4 0 5 2 4 4 5 1 2 4 2 2 5 3 4 1 2 3 4 2 0 1 4 5 1 0 4 5 1 1 4 0 5 4 4 0 2 0 4 3 1 2 0 5 5 1 1 0 3 4 5 4 5 1 4 2 1 4 4 3 1 2 4 2 5 0 2 2 4 3 5 4 3 0 0 1 2 1 1 5 1 1 5 0 1 3 4 1 2 4 5 1 1 0 2 4 1 5 4 1 5 1 2 3 0 4 1 4 4 4 5 4 1 0 5 5 5 5 1 5 4 5 3 4 1 2 1 4 2 3 5 5 5 5 5 2 4 0 4 1 1 0 1 5 5 4 4 0 4 5 0 1 1 3 5 2 4 3 0 1 0 3 4 1 4 4 4 1 1 1 1 1 5 5 0 1 2 3 3 5 3 5 4 2 5 2 5 3 1 4 2 4 1 1 4 1 4 4 0 3 1 3 3 2 4 3 3 3 5 3 0 2 1 3 5 4 2 5 3 5 1 4 0 4 0 5 2 4 1 1 3 1 0 4 1 3 4 2 4 3 4 1 4 1 0 0 0 5 4 3 4 1 3 2 3 0 4 4 3 3 0 3 4 0 4 5 1 3 4 1 2 0 2 3 3 4 2 4 3 1 4 1 1 1 1 4 4 2 2 1 1 1 4 0 1 1 1 1 4 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_vs_nonadj.out0000644000076500000240000000003113524616144027762 0ustar tamasstaff0000000000000010 0 1 2 3 4 5 6 7 8 9 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_diameter.out0000644000076500000240000000005613524616144027602 0ustar tamasstaff00000000000000diameter: 9, from 0 to 9 0 1 2 3 4 5 6 7 8 9 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_pagerank.out0000644000076500000240000000156013524616144027601 0ustar tamasstaff00000000000000Warning: igraph_pagerank_old is deprecated from igraph 0.7, use igraph_pagerank instead 0.37 0.20 0.39 0.04 Warning: igraph_pagerank_old is deprecated from igraph 0.7, use igraph_pagerank instead 0.42 0.14 0.14 0.14 0.04 0.04 0.04 0.04 0.47 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.47 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.47 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.47 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.47 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.47 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.33 0.52 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.33 0.52 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.14 0.10 0.05 0.05 0.16 0.26 0.05 0.16 0.05 0.14 0.10 0.05 0.05 0.16 0.26 0.05 0.16 0.05 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_delete_edges.c0000644000076500000240000000445513612122633030034 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_vector_t v; int ret; igraph_es_t es; igraph_vector_init(&v, 8); VECTOR(v)[0] = 0; VECTOR(v)[1] = 1; VECTOR(v)[2] = 1; VECTOR(v)[3] = 2; VECTOR(v)[4] = 2; VECTOR(v)[5] = 3; VECTOR(v)[6] = 2; VECTOR(v)[7] = 2; igraph_create(&g, &v, 0, 0); igraph_es_pairs_small(&es, IGRAPH_DIRECTED, 3, 2, -1); igraph_delete_edges(&g, es); if (igraph_ecount(&g) != 3) { return 1; } /* error test, no such edge to delete */ igraph_set_error_handler(igraph_error_handler_ignore); ret = igraph_delete_edges(&g, es); if (ret != IGRAPH_EINVAL) { printf("Error code: %i\n", ret); return 2; } if (igraph_ecount(&g) != 3) { return 3; } /* error test, invalid vertex id */ igraph_es_destroy(&es); igraph_es_pairs_small(&es, IGRAPH_DIRECTED, 10, 2, -1); ret = igraph_delete_edges(&g, es); if (ret != IGRAPH_EINVVID) { return 4; } if (igraph_ecount(&g) != 3) { return 5; } /* error test, invalid (odd) length */ igraph_es_destroy(&es); igraph_es_pairs_small(&es, IGRAPH_DIRECTED, 0, 1, 2, -1); ret = igraph_delete_edges(&g, es); if (ret != IGRAPH_EINVAL) { return 6; } if (igraph_ecount(&g) != 3) { return 7; } igraph_es_destroy(&es); igraph_vector_destroy(&v); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/cattr_bool_bug.graphml0000644000076500000240000000444713524616144030276 0ustar tamasstaff00000000000000 Erdos renyi (gnp) graph gnp false 0.2 n0 n1 n2 n3 n4 n5 n6 n7 n8 n9 10 11 12 13 14 15 16 17 18 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_degree_sequence_game.out0000644000076500000240000000021413524616144032120 0ustar tamasstaff000000000000003 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 2 2 4 4 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 2 2 4 4 2 2 3 3 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_scg_semiprojectors.c0000644000076500000240000000740313612122633031323 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_matrix_t L, R; igraph_sparsemat_t Lsparse, Rsparse; igraph_matrix_t adj, V; igraph_vector_t groups; igraph_eigen_which_t which; igraph_matrix_init(&L, 0, 0); igraph_matrix_init(&R, 0, 0); igraph_matrix_init(&adj, 0, 0); igraph_matrix_init(&V, 0, 0); igraph_vector_init(&groups, 0); igraph_rng_seed(igraph_rng_default(), 42); igraph_tree(&g, 10, /* children= */ 3, IGRAPH_TREE_UNDIRECTED); igraph_get_adjacency(&g, &adj, IGRAPH_GET_ADJACENCY_BOTH, /*eids=*/ 0); which.pos = IGRAPH_EIGEN_LM; which.howmany = 1; igraph_eigen_matrix_symmetric(&adj, /*sparsemat=*/ 0, /*fun=*/ 0, igraph_vcount(&g), /*extra=*/ 0, /*algorithm=*/ IGRAPH_EIGEN_LAPACK, &which, /*options=*/ 0, /*storage=*/ 0, /*values=*/ 0, &V); #define SEMI() \ do { \ igraph_scg_semiprojectors(&groups, IGRAPH_SCG_SYMMETRIC, &L, &R, \ &Lsparse, &Rsparse, /*p=*/ 0, \ IGRAPH_SCG_NORM_ROW); \ } while(0) #define PRINTRES() \ do { \ printf("----------------------\n"); \ igraph_matrix_print(&L); \ printf("---\n"); \ igraph_matrix_print(&R); \ printf("---\n"); \ igraph_sparsemat_destroy(&Lsparse); \ igraph_sparsemat_destroy(&Rsparse); \ } while (0) /* -------------- */ igraph_scg_grouping(&V, &groups, /*intervals=*/ 3, /*intervals_vector=*/ 0, IGRAPH_SCG_SYMMETRIC, IGRAPH_SCG_OPTIMUM, /*p=*/ 0, /*maxiter=*/ 10000); SEMI(); PRINTRES(); /* -------------- */ igraph_scg_grouping(&V, &groups, /*intervals=*/ 2, /*intervals_vector=*/ 0, IGRAPH_SCG_SYMMETRIC, IGRAPH_SCG_INTERV_KM, /*p=*/ 0, /*maxiter=*/ 10000); SEMI(); PRINTRES(); /* -------------- */ igraph_scg_grouping(&V, &groups, /*intervals=*/ 2, /*intervals_vector=*/ 0, IGRAPH_SCG_SYMMETRIC, IGRAPH_SCG_INTERV, /*p=*/ 0, /*maxiter=*/ 10000); SEMI(); PRINTRES(); /* -------------- */ igraph_scg_grouping(&V, &groups, /*(ignored) intervals=*/ 0, /*intervals_vector=*/ 0, IGRAPH_SCG_SYMMETRIC, IGRAPH_SCG_EXACT, /*p=*/ 0, /*maxiter=*/ 10000); SEMI(); PRINTRES(); /* -------------- */ igraph_vector_destroy(&groups); igraph_matrix_destroy(&L); igraph_matrix_destroy(&R); igraph_matrix_destroy(&V); igraph_matrix_destroy(&adj); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_sparsemat4.out0000644000076500000240000000000013524616144030060 0ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_to_undirected.c0000644000076500000240000000323413612122634030246 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_vector_t v; igraph_t g; igraph_vector_init_int(&v, 2, 5, 5); igraph_lattice(&g, &v, 1, IGRAPH_DIRECTED, 1 /*mutual*/, 0 /*circular*/); igraph_to_undirected(&g, IGRAPH_TO_UNDIRECTED_COLLAPSE, /*edge_comb=*/ 0); igraph_write_graph_edgelist(&g, stdout); igraph_destroy(&g); igraph_vector_destroy(&v); printf("---\n"); igraph_small(&g, 10, IGRAPH_DIRECTED, 0, 1, 2, 1, 2, 3, 2, 3, 4, 3, 4, 3, 5, 6, 6, 5, 6, 7, 6, 7, 7, 6, 7, 8, 7, 8, 8, 7, 8, 7, 8, 8, 9, 9, 9, 9, -1); igraph_to_undirected(&g, IGRAPH_TO_UNDIRECTED_MUTUAL, /*edge_comb=*/ 0); igraph_write_graph_edgelist(&g, stdout); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_full.c0000644000076500000240000000163713612122633026364 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_is_multiple.out0000644000076500000240000000005613524616144030336 0ustar tamasstaff00000000000000 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 1 1 1 1 1 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_transitive_closure_dag.c0000644000076500000240000000310713612122634032154 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g, g2; igraph_vector_t deg; igraph_small(&g, 9, IGRAPH_DIRECTED, 8, 7, 7, 6, 6, 3, 6, 0, 3, 2, 3, 1, 5, 0, 4, 1, -1); igraph_transitive_closure_dag(&g, &g2); if (igraph_vcount(&g2) != igraph_vcount(&g)) { return 1; } if (igraph_ecount(&g2) != 19) { return 1; } igraph_vector_init(°, 0); igraph_degree(&g2, °, igraph_vss_all(), IGRAPH_IN, IGRAPH_LOOPS); igraph_vector_print(°); igraph_degree(&g2, °, igraph_vss_all(), IGRAPH_OUT, IGRAPH_LOOPS); igraph_vector_print(°); igraph_vector_destroy(°); igraph_destroy(&g2); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_community_edge_betweenness.c0000644000076500000240000001461013614300625033030 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int igraph_vector_between(const igraph_vector_t* v, const igraph_vector_t* lo, const igraph_vector_t* hi) { return igraph_vector_all_le(lo, v) && igraph_vector_all_ge(hi, v); } void test_unweighted() { igraph_t g; igraph_vector_t edges, eb; long int i; long int no_of_edges; /* Zachary Karate club */ igraph_small(&g, 0, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 0, 7, 0, 8, 0, 10, 0, 11, 0, 12, 0, 13, 0, 17, 0, 19, 0, 21, 0, 31, 1, 2, 1, 3, 1, 7, 1, 13, 1, 17, 1, 19, 1, 21, 1, 30, 2, 3, 2, 7, 2, 8, 2, 9, 2, 13, 2, 27, 2, 28, 2, 32, 3, 7, 3, 12, 3, 13, 4, 6, 4, 10, 5, 6, 5, 10, 5, 16, 6, 16, 8, 30, 8, 32, 8, 33, 9, 33, 13, 33, 14, 32, 14, 33, 15, 32, 15, 33, 18, 32, 18, 33, 19, 33, 20, 32, 20, 33, 22, 32, 22, 33, 23, 25, 23, 27, 23, 29, 23, 32, 23, 33, 24, 25, 24, 27, 24, 31, 25, 31, 26, 29, 26, 33, 27, 33, 28, 31, 28, 33, 29, 32, 29, 33, 30, 32, 30, 33, 31, 32, 31, 33, 32, 33, -1); igraph_vector_init(&edges, 0); igraph_vector_init(&eb, 0); igraph_community_edge_betweenness(&g, &edges, &eb, 0 /*merges */, 0 /*bridges */, /*modularity=*/ 0, /*membership=*/ 0, IGRAPH_UNDIRECTED, /*weights=*/ 0); no_of_edges = igraph_ecount(&g); for (i = 0; i < no_of_edges; i++) { printf("%li ", (long int)VECTOR(edges)[i]); } printf("\n"); for (i = 0; i < no_of_edges; i++) { printf("%.2f ", VECTOR(eb)[i]); } printf("\n"); /* Try it once again without storage space for edges */ igraph_community_edge_betweenness(&g, 0, &eb, 0 /*merges */, 0 /*bridges */, /*modularity=*/ 0, /*membership=*/ 0, IGRAPH_UNDIRECTED, /*weights=*/ 0); for (i = 0; i < no_of_edges; i++) { printf("%.2f ", VECTOR(eb)[i]); } printf("\n"); igraph_vector_destroy(&eb); igraph_vector_destroy(&edges); igraph_destroy(&g); } #define EPS 1e-4 void test_weighted() { igraph_t g; igraph_vector_t edges, eb, weights; igraph_real_t weights_array[] = { 4, 1, 3, 2, 5, 8, 6, 7 }; igraph_real_t edges_array1[] = { 2, 3, 0, 1, 4, 7, 5, 6 }; igraph_real_t edges_array2[] = { 2, 3, 6, 5, 0, 1, 4, 7 }; igraph_real_t eb_array1_lo[] = { 4, 5, 3 + 1 / 3.0 - EPS, 4, 2.5, 4, 1, 1 }; igraph_real_t eb_array1_hi[] = { 4, 5, 3 + 1 / 3.0 + EPS, 4, 2.5, 4, 1, 1 }; igraph_real_t eb_array2_lo[] = { 4, 5, 3 + 1 / 3.0 - EPS, 6, 1.5, 2, 1, 1 }; igraph_real_t eb_array2_hi[] = { 4, 5, 3 + 1 / 3.0 + EPS, 6, 1.5, 2, 1, 1 }; igraph_vector_t edges_sol1, edges_sol2, eb_sol1_lo, eb_sol1_hi, eb_sol2_lo, eb_sol2_hi; igraph_vector_view(&edges_sol1, edges_array1, sizeof(edges_array1) / sizeof(double)); igraph_vector_view(&edges_sol2, edges_array2, sizeof(edges_array2) / sizeof(double)); igraph_vector_view(&eb_sol1_lo, eb_array1_lo, sizeof(eb_array1_lo) / sizeof(double)); igraph_vector_view(&eb_sol2_lo, eb_array2_lo, sizeof(eb_array2_lo) / sizeof(double)); igraph_vector_view(&eb_sol1_hi, eb_array1_hi, sizeof(eb_array1_hi) / sizeof(double)); igraph_vector_view(&eb_sol2_hi, eb_array2_hi, sizeof(eb_array2_hi) / sizeof(double)); /* Small graph as follows: A--B--C--A, A--D--E--A, B--D, C--E */ igraph_small(&g, 0, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 0, 4, 1, 2, 1, 3, 2, 4, 3, 4, -1); igraph_vector_view(&weights, weights_array, igraph_ecount(&g)); igraph_vector_init(&edges, 0); igraph_vector_init(&eb, 0); igraph_community_edge_betweenness(&g, &edges, &eb, 0 /*merges */, 0 /*bridges */, /*modularity=*/ 0, /*membership=*/ 0, IGRAPH_UNDIRECTED, &weights); if (!igraph_vector_all_e(&edges_sol1, &edges) && !igraph_vector_all_e(&edges_sol2, &edges)) { printf("Error, edges vector was: \n"); igraph_vector_print(&edges); exit(2); } if (!igraph_vector_between(&eb, &eb_sol1_lo, &eb_sol1_hi) && !igraph_vector_between(&eb, &eb_sol2_lo, &eb_sol2_hi)) { printf("Error, eb vector was: \n"); igraph_vector_print(&eb); exit(2); } /* Try it once again without storage space for edges */ igraph_community_edge_betweenness(&g, 0, &eb, 0 /*merges */, 0 /*bridges */, /*modularity=*/ 0, /*membership=*/ 0, IGRAPH_UNDIRECTED, &weights); if (!igraph_vector_between(&eb, &eb_sol1_lo, &eb_sol1_hi) && !igraph_vector_between(&eb, &eb_sol2_lo, &eb_sol2_hi)) { printf("Error, eb vector was: \n"); igraph_vector_print(&eb); exit(2); } igraph_vector_destroy(&eb); igraph_vector_destroy(&edges); igraph_destroy(&g); } int main() { test_unweighted(); test_weighted(); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_subisomorphic_lad.out0000644000076500000240000000046613524616144031523 0ustar tamasstaff000000000000001 0 6 5 4 1 0 6 5 4 0 1 2 3 4 5 3 2 1 4 7 3 4 5 8 4 3 7 8 5 8 3 4 6 5 0 4 3 5 6 0 4 3 2 1 3 4 0 6 5 6 4 3 8 5 5 4 1 2 3 5 4 1 0 6 1 4 5 6 0 8 5 6 4 3 4 5 8 7 3 3 5 6 0 4 6 5 8 3 4 0 6 5 3 4 5 6 0 1 4 7 8 5 4 3 --------- 0 1 2 3 4 0 1 2 3 4 5 3 2 1 4 5 4 1 2 3 0 4 3 2 1 --------- 0 4 3 2 1 0 4 3 2 1 --------- python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_edge_betweenness.out0000644000076500000240000000164513524616144031323 0ustar tamasstaff0000000000000014.16667 43.63889 11.50000 29.33333 43.83333 43.83333 12.80238 41.64841 29.33333 33.00000 26.10000 23.77063 22.50952 25.77063 22.50952 71.39286 13.03333 4.33333 4.16429 6.95952 10.49048 8.20952 10.49048 18.10952 12.58333 14.14524 5.14762 17.28095 4.28095 23.10873 12.78095 38.70159 1.88810 6.90000 8.37143 2.66667 1.66667 1.66667 2.66667 16.50000 16.50000 5.50000 17.07778 22.68492 16.61429 38.04921 13.51111 19.48889 13.51111 19.48889 13.51111 19.48889 33.31349 13.51111 19.48889 13.51111 19.48889 11.09444 5.91111 3.73333 12.53333 18.32778 2.36667 10.46667 22.50000 23.59444 2.54286 30.45714 17.09762 8.33333 13.78095 13.08730 16.72222 9.56667 15.04286 23.24444 29.95397 4.61429 4.00000 3.00000 3.00000 2.00000 3.00000 3.00000 3.00000 4.00000 3.00000 4.00000 3.00000 4.00000 4.00000 3.00000 3.00000 3.00000 0.00000 0.00000 2.33333 2.33333 2.33333 0.00000 2.33333 2.33333 2.33333 2.33333 2.33333 2.33333 0.00000 0.00000 0.00000 python-igraph-0.8.0/vendor/source/igraph/examples/simple/walktrap.out0000644000076500000240000000045213524616144026303 0ustar tamasstaff00000000000000Merges: 6 + 7 -> 10 (modularity 0.00) 2 + 4 -> 11 (modularity -0.07) 8 + 10 -> 12 (modularity -0.04) 3 + 11 -> 13 (modularity 0.02) 9 + 12 -> 14 (modularity 0.08) 1 + 13 -> 15 (modularity 0.16) 0 + 15 -> 16 (modularity 0.25) 5 + 14 -> 17 (modularity 0.35) 16 + 17 -> 18 (modularity 0.45) python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_minimum_spanning_tree.out0000644000076500000240000000041013524616144032371 0ustar tamasstaff000000000000000 2 0 4 0 5 0 6 0 8 0 10 0 11 0 12 0 17 0 21 0 31 1 30 2 3 2 7 2 9 2 27 2 32 6 16 13 33 14 33 15 33 18 33 19 33 20 33 22 33 23 33 24 31 25 31 26 33 28 33 29 33 30 33 31 33 15 5 4 1 7 31 9 76 45 52 67 8 3 10 65 29 12 14 64 49 47 51 56 54 61 27 72 40 74 23 25 70 24 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_write_graph_leda.c0000644000076500000240000000672713612122634030730 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int main(int argc, char **argv) { int i; igraph_t g; igraph_vector_t values; igraph_strvector_t strvalues; const char* strings[] = {"foo", "bar", "baz", "spam", "eggs", "bacon"}; /* Setting up attribute handler */ igraph_i_set_attribute_table(&igraph_cattribute_table); /* Saving directed graph, no attributes */ igraph_ring(&g, 5, /* directed = */ 1, /* mutual = */ 0, /* circular = */ 1); igraph_write_graph_leda(&g, stdout, 0, 0); printf("===\n"); igraph_destroy(&g); /* Saving undirected graph, no attributes */ igraph_ring(&g, 5, /* directed = */ 0, /* mutual = */ 0, /* circular = */ 1); igraph_write_graph_leda(&g, stdout, 0, 0); printf("===\n"); igraph_destroy(&g); /* Saving directed graph with vertex attributes */ igraph_ring(&g, 5, /* directed = */ 1, /* mutual = */ 0, /* circular = */ 1); igraph_vector_init_seq(&values, 5, 9); SETVANV(&g, "name", &values); igraph_write_graph_leda(&g, stdout, "name", 0); igraph_vector_destroy(&values); printf("===\n"); DELVAS(&g); igraph_strvector_init(&strvalues, 5); for (i = 0; i < 5; i++) { igraph_strvector_set(&strvalues, i, strings[i]); } SETVASV(&g, "name", &strvalues); igraph_write_graph_leda(&g, stdout, "name", 0); igraph_strvector_destroy(&strvalues); printf("===\n"); igraph_destroy(&g); /* Saving undirected graph with edge attributes */ igraph_ring(&g, 5, /* directed = */ 0, /* mutual = */ 0, /* circular = */ 1); igraph_vector_init_seq(&values, 5, 9); SETEANV(&g, "weight", &values); igraph_write_graph_leda(&g, stdout, 0, "weight"); igraph_vector_destroy(&values); printf("===\n"); DELEAS(&g); igraph_strvector_init(&strvalues, 5); for (i = 0; i < 5; i++) { igraph_strvector_set(&strvalues, i, strings[i]); } SETEASV(&g, "weight", &strvalues); igraph_write_graph_leda(&g, stdout, 0, "weight"); igraph_strvector_destroy(&strvalues); printf("===\n"); igraph_destroy(&g); /* Saving undirected graph with edge attributes and large weights */ igraph_ring(&g, 5, /* directed = */ 0, /* mutual = */ 0, /* circular = */ 1); igraph_vector_init_seq(&values, 123456789, 123456793); SETEANV(&g, "weight", &values); igraph_write_graph_leda(&g, stdout, 0, "weight"); igraph_vector_destroy(&values); printf("===\n"); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_es_pairs.c0000644000076500000240000000431313612122633027221 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; long int i; igraph_integer_t size; /* DIRECTED */ igraph_star(&g, 10, IGRAPH_STAR_OUT, 0); for (i = 0; i < 100; i++) { igraph_es_t es; igraph_eit_t it; igraph_es_pairs_small(&es, IGRAPH_DIRECTED, 0, 1, 0, 2, 0, 5, 0, 2, 0, 3, 0, 4, 0, 7, 0, 9, -1); igraph_eit_create(&g, es, &it); igraph_es_size(&g, &es, &size); IGRAPH_EIT_RESET(it); while (!IGRAPH_EIT_END(it)) { (void) IGRAPH_EIT_GET(it); IGRAPH_EIT_NEXT(it); size--; } if (size != 0) { return 1; } igraph_eit_destroy(&it); igraph_es_destroy(&es); } igraph_destroy(&g); /* UNDIRECTED */ igraph_star(&g, 10, IGRAPH_STAR_UNDIRECTED, 0); for (i = 0; i < 100; i++) { igraph_es_t es; igraph_eit_t it; igraph_es_pairs_small(&es, IGRAPH_DIRECTED, 0, 1, 2, 0, 5, 0, 0, 2, 3, 0, 0, 4, 7, 0, 0, 9, -1); igraph_eit_create(&g, es, &it); IGRAPH_EIT_RESET(it); while (!IGRAPH_EIT_END(it)) { (void) IGRAPH_EIT_GET(it); IGRAPH_EIT_NEXT(it); } igraph_eit_destroy(&it); igraph_es_destroy(&es); } igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_adjacency_spectral_embedding.c0000644000076500000240000000373413612122633033236 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2013 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include /* R library(igraph) g <- graph.tree(10, 3, mode="out") A <- get.adjacency(g) svd(A + .5 * degree(g) * diag(vcount(g))) */ int main() { igraph_t graph; igraph_matrix_t U, V; igraph_arpack_options_t options; igraph_vector_t cvec; igraph_tree(&graph, /*n=*/ 10, /*children=*/ 3, IGRAPH_TREE_OUT); igraph_matrix_init(&U, 0, 0); igraph_matrix_init(&V, 0, 0); igraph_arpack_options_init(&options); igraph_vector_init(&cvec, 0); igraph_degree(&graph, &cvec, igraph_vss_all(), IGRAPH_ALL, IGRAPH_LOOPS); igraph_vector_scale(&cvec, .5); igraph_adjacency_spectral_embedding(&graph, 4, /*weights=*/ 0, IGRAPH_EIGEN_LA, /*scaled=*/ 0, &U, &V, /*D=*/ 0, &cvec, &options); igraph_matrix_printf(&U, "%8.4f"); printf("--\n"); igraph_matrix_printf(&V, "%8.4f"); igraph_vector_destroy(&cvec); igraph_matrix_destroy(&V); igraph_matrix_destroy(&U); igraph_destroy(&graph); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_knn.c0000644000076500000240000000430513612122633026203 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_vector_t v, v2; igraph_vector_t v_weighted, v2_weighted; igraph_integer_t n; igraph_neimode_t mode, neighbour_degree_mode; mode = IGRAPH_IN; neighbour_degree_mode = IGRAPH_OUT; igraph_ring(&g, 10, /*directed=*/ 1, /*mutual=*/ 0, /*circular=*/ 1); n = igraph_vcount(&g); igraph_vector_init(&v, (long int)n); igraph_vector_init(&v2, (long int)n); igraph_avg_nearest_neighbor_degree(&g, igraph_vss_all(), mode, neighbour_degree_mode, &v, &v2, /*weights=*/ 0); igraph_vector_t weights; igraph_vector_init(&weights, igraph_ecount(&g)); igraph_vector_fill(&weights, 2.0); igraph_vector_init(&v_weighted, (long int)n); igraph_vector_init(&v2_weighted, (long int)n); igraph_avg_nearest_neighbor_degree(&g, igraph_vss_all(), mode, neighbour_degree_mode, &v_weighted, &v2_weighted, &weights); if (!igraph_vector_all_e(&v, &v_weighted)) { return 1; } igraph_vector_destroy(&v_weighted); igraph_vector_destroy(&v2_weighted); igraph_vector_destroy(&weights); igraph_vector_destroy(&v); igraph_vector_destroy(&v2); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/graphml-malformed.xml0000755000076500000240000000211313524616144030044 0ustar tamasstaff00000000000000 yellYw 1 ta> green true blue 0 red "w" false t i 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #define N 10 #define M 20 #define NZ 50 #define MIN 0 #define MAX 10 typedef int fun(igraph_sparsemat_t *A, igraph_vector_t *res, igraph_vector_int_t *pos); int doit(int which) { int i; igraph_sparsemat_t A, A2; igraph_vector_t vec; igraph_vector_int_t pos; fun *colfun, *rowfun; if (which == MIN) { colfun = igraph_sparsemat_which_min_cols; rowfun = igraph_sparsemat_which_min_rows; } else { /* colfun = */ /* TODO */ /* rowfun = */ /* TODO */ } igraph_rng_seed(igraph_rng_default(), 42); /* Triplet diagonal matrix */ igraph_vector_init(&vec, N); igraph_vector_int_init(&pos, N); for (i = 0; i < N; i++) { VECTOR(vec)[i] = i; } igraph_sparsemat_diag(&A, /*nzmax=*/ N, /*values=*/ &vec, /*compress=*/ 0); igraph_vector_null(&vec); igraph_vector_int_null(&pos); rowfun(&A, &vec, &pos); for (i = 0; i < N; i++) { if (VECTOR(vec)[i] != i) { return which + 1; } } for (i = 0; i < N; i++) { if (VECTOR(pos)[i] != i) { return which + 2; } } igraph_vector_null(&vec); colfun(&A, &vec, &pos); for (i = 0; i < N; i++) { if (VECTOR(vec)[i] != i) { return which + 3; } } for (i = 0; i < N; i++) { if (VECTOR(pos)[i] != i) { return which + 4; } } igraph_vector_destroy(&vec); igraph_vector_int_destroy(&pos); igraph_sparsemat_destroy(&A); /* Compressed diagonal matrix */ igraph_vector_init(&vec, N); igraph_vector_int_init(&pos, N); for (i = 0; i < N; i++) { VECTOR(vec)[i] = i; } igraph_sparsemat_diag(&A, /*nzmax=*/ N, /*values=*/ &vec, /*compress=*/ 1); igraph_vector_null(&vec); rowfun(&A, &vec, &pos); for (i = 0; i < N; i++) { if (VECTOR(vec)[i] != i) { return which + 5; } } for (i = 0; i < N; i++) { if (VECTOR(pos)[i] != i) { return which + 6; } } igraph_vector_null(&vec); colfun(&A, &vec, &pos); for (i = 0; i < N; i++) { if (VECTOR(vec)[i] != i) { return which + 7; } } for (i = 0; i < N; i++) { if (VECTOR(pos)[i] != i) { return which + 8; } } igraph_vector_destroy(&vec); igraph_vector_int_destroy(&pos); igraph_sparsemat_destroy(&A); /* Random triplet matrix */ igraph_sparsemat_init(&A, /*rows=*/ N, /*cols=*/ M, /*nzmax=*/ NZ + 5); for (i = 0; i < NZ; i++) { int r = igraph_rng_get_integer(igraph_rng_default(), 0, N - 1); int c = igraph_rng_get_integer(igraph_rng_default(), 0, M - 1); igraph_real_t x = igraph_rng_get_integer(igraph_rng_default(), -10, 10); igraph_sparsemat_entry(&A, r, c, x); } if (which == MAX) { igraph_sparsemat_scale(&A, -1.0); } igraph_vector_init(&vec, 0); igraph_vector_int_init(&pos, 0); colfun(&A, &vec, &pos); igraph_vector_print(&vec); igraph_vector_int_print(&pos); igraph_vector_null(&vec); rowfun(&A, &vec, &pos); igraph_vector_print(&vec); igraph_vector_int_print(&pos); /* Random compresssed matrix */ igraph_sparsemat_compress(&A, &A2); igraph_vector_null(&vec); colfun(&A2, &vec, &pos); igraph_vector_print(&vec); igraph_vector_int_print(&pos); igraph_vector_null(&vec); rowfun(&A2, &vec, &pos); igraph_vector_print(&vec); igraph_vector_int_print(&pos); igraph_vector_destroy(&vec); igraph_vector_int_destroy(&pos); igraph_sparsemat_destroy(&A); igraph_sparsemat_destroy(&A2); /* Matrix with zero rows, triplet */ igraph_sparsemat_init(&A, /*rows=*/ 0, /*cols=*/ M, /*nzmax=*/ NZ); if (which == MAX) { igraph_sparsemat_scale(&A, -1.0); } igraph_vector_init(&vec, 5); igraph_vector_int_init(&pos, 5); rowfun(&A, &vec, &pos); if (igraph_vector_size(&vec) != 0) { return which + 5; } igraph_vector_null(&vec); colfun(&A, &vec, &pos); igraph_vector_print(&vec); igraph_vector_int_print(&pos); /* Matrix with zero rows, compressed */ igraph_sparsemat_compress(&A, &A2); igraph_vector_null(&vec); rowfun(&A, &vec, &pos); if (igraph_vector_size(&vec) != 0) { return which + 6; } igraph_vector_null(&vec); colfun(&A, &vec, &pos); igraph_vector_print(&vec); igraph_vector_int_print(&pos); igraph_vector_destroy(&vec); igraph_vector_int_destroy(&pos); igraph_sparsemat_destroy(&A); igraph_sparsemat_destroy(&A2); /* Matrix with zero columns, triplet */ igraph_sparsemat_init(&A, /*rows=*/ N, /*cols=*/ 0, /*nzmax=*/ NZ); if (which == MAX) { igraph_sparsemat_scale(&A, -1.0); } igraph_vector_init(&vec, 5); igraph_vector_int_init(&pos, 5); colfun(&A, &vec, &pos); if (igraph_vector_size(&vec) != 0) { return which + 7; } igraph_vector_null(&vec); rowfun(&A, &vec, &pos); igraph_vector_print(&vec); igraph_vector_int_print(&pos); /* Matrix with zero columns, compressed */ igraph_sparsemat_compress(&A, &A2); igraph_vector_null(&vec); colfun(&A, &vec, &pos); if (igraph_vector_size(&vec) != 0) { return which + 8; } igraph_vector_null(&vec); rowfun(&A, &vec, &pos); igraph_vector_print(&vec); igraph_vector_int_print(&pos); igraph_vector_destroy(&vec); igraph_vector_int_destroy(&pos); igraph_sparsemat_destroy(&A); igraph_sparsemat_destroy(&A2); return 0; } int main() { int res; res = doit(/*which=*/ MIN); if (res) { return res; } /* res = doit(/\*which=*\/ MAX); */ /* if (res) { return res; } */ return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_community_edge_betweenness.out0000644000076500000240000000206113524616144033420 0ustar tamasstaff0000000000000015 1 7 45 52 31 23 16 24 25 28 44 68 27 4 5 3 8 76 75 70 57 58 26 9 67 66 10 33 46 47 48 49 63 69 50 51 12 20 53 54 13 21 35 38 55 56 14 22 29 42 43 41 73 74 6 18 32 0 2 11 17 19 30 34 36 37 39 40 59 60 61 62 64 65 71 72 77 71.39 66.90 77.32 82.00 123.23 100.21 143.63 109.25 107.67 142.75 285.00 16.83 18.18 18.00 15.33 25.33 25.00 50.00 14.50 22.37 25.62 29.65 40.67 72.00 9.00 9.00 11.00 5.50 8.00 5.00 10.00 4.50 9.00 4.50 9.00 4.00 8.00 3.50 7.00 3.50 7.00 3.00 6.00 3.00 6.00 3.00 6.00 2.50 5.00 2.00 2.00 3.50 5.00 2.00 4.00 1.33 2.00 4.00 1.00 1.50 3.00 1.00 2.00 1.00 1.00 1.00 1.00 2.00 1.00 1.00 1.50 3.00 1.00 2.00 1.00 1.00 2.00 1.00 71.39 66.90 77.32 82.00 123.23 100.21 143.63 109.25 107.67 142.75 285.00 16.83 18.18 18.00 15.33 25.33 25.00 50.00 14.50 22.37 25.62 29.65 40.67 72.00 9.00 9.00 11.00 5.50 8.00 5.00 10.00 4.50 9.00 4.50 9.00 4.00 8.00 3.50 7.00 3.50 7.00 3.00 6.00 3.00 6.00 3.00 6.00 2.50 5.00 2.00 2.00 3.50 5.00 2.00 4.00 1.33 2.00 4.00 1.00 1.50 3.00 1.00 2.00 1.00 1.00 1.00 1.00 2.00 1.00 1.00 1.50 3.00 1.00 2.00 1.00 1.00 2.00 1.00 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_read_graph_lgl.c0000644000076500000240000000443113614300625030350 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph R package. Copyright (C) 2005-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; FILE *input; /* Without names and weights */ input = fopen("igraph_read_graph_lgl-1.lgl", "r"); if (!input) { return 1; } igraph_read_graph_lgl(&g, input, 0, IGRAPH_ADD_WEIGHTS_NO, 1); fclose(input); if (!igraph_is_directed(&g)) { return 2; } igraph_write_graph_edgelist(&g, stdout); igraph_destroy(&g); /* With names and weights */ input = fopen("igraph_read_graph_lgl-2.lgl", "r"); if (!input) { return 3; } igraph_read_graph_lgl(&g, input, 0, IGRAPH_ADD_WEIGHTS_NO, 1); fclose(input); if (!igraph_is_directed(&g)) { return 4; } igraph_write_graph_ncol(&g, stdout, 0, 0); igraph_destroy(&g); /* Same graph, but forcing undirected mode */ input = fopen("igraph_read_graph_lgl-2.lgl", "r"); igraph_read_graph_lgl(&g, input, 0, IGRAPH_ADD_WEIGHTS_NO, 0); fclose(input); if (igraph_is_directed(&g)) { return 5; } igraph_write_graph_ncol(&g, stdout, 0, 0); igraph_destroy(&g); /* Erroneous LGL file (empty vertex name) */ input = fopen("igraph_read_graph_lgl-3.lgl", "r"); if (!input) { return 6; } igraph_set_error_handler(igraph_error_handler_ignore); if (igraph_read_graph_lgl(&g, input, 0, IGRAPH_ADD_WEIGHTS_NO, 1) != IGRAPH_PARSEERROR) { return 7; } fclose(input); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/LINKS.NET0000644000076500000240000000176513524616144025165 0ustar tamasstaff00000000000000*Network TRALALA *vertices 4 1 "1" 0.0938 0.0896 ellipse x_fact 1 y_fact 1 2 "2" 0.8188 0.2458 ellipse x_fact 1 y_fact 1 3 "3" 0.3688 0.7792 ellipse x_fact 1 4 "4" 0.9583 0.8563 ellipse x_fact 1 *arcs 1 1 1 h2 0 w 3 c Blue s 3 a1 -130 k1 0.6 a2 -130 k2 0.6 ap 0.5 l "Bezier loop" lc BlueViolet fos 20 lr 58 lp 0.3 la 360 2 1 1 h2 0 a1 120 k1 1.3 a2 -120 k2 0.3 ap 25 l "Bezier arc" lphi 270 la 180 lr 19 lp 0.5 1 2 1 h2 0 a1 40 k1 2.8 a2 30 k2 0.8 ap 25 l "Bezier arc" lphi 90 la 0 lp 0.65 4 2 -1 h2 0 w 1 k1 -2 k2 250 ap 25 l "Circular arc" c Red lc OrangeRed 3 4 1 p Dashed h2 0 w 2 c OliveGreen ap 25 l "Straight arc" lc PineGreen 1 3 1 p Dashed h2 0 w 5 k1 -1 k2 -20 ap 25 l "Oval arc" c Brown lc Black 3 3 -1 h1 6 w 1 h2 12 k1 -2 k2 -15 ap 0.5 l "Circular loop" c Red lc OrangeRed lphi 270 la 180 python-igraph-0.8.0/vendor/source/igraph/examples/simple/foreign.out0000644000076500000240000000011013524616144026076 0ustar tamasstaff00000000000000The graph: Vertices: 4 Edges: 7 Directed: 1 0 0 0 1 0 2 1 0 2 2 2 3 3 1 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_random_walk.c0000644000076500000240000000326313612122633027715 0ustar tamasstaff00000000000000 #include #include int main() { igraph_t graph; igraph_vector_t walk, weights; igraph_integer_t ec, i; igraph_rng_seed(igraph_rng_default(), 137); igraph_vector_init(&walk, 0); igraph_vector_init(&weights, 0); /* This directed graph has loop edges. It also has multi-edges when considered as undirected. */ igraph_de_bruijn(&graph, 3, 2); ec = igraph_ecount(&graph); /* unweighted, directed */ igraph_random_edge_walk(&graph, NULL, &walk, 0, IGRAPH_OUT, 1000, IGRAPH_RANDOM_WALK_STUCK_RETURN); assert(igraph_vector_size(&walk) == 1000); /* unweighted, undirected */ igraph_random_edge_walk(&graph, NULL, &walk, 0, IGRAPH_ALL, 1000, IGRAPH_RANDOM_WALK_STUCK_RETURN); assert(igraph_vector_size(&walk) == 1000); igraph_vector_resize(&weights, ec); for (i = 0; i < ec; ++i) { VECTOR(weights)[i] = igraph_rng_get_unif01(igraph_rng_default()); } /* weighted, directed */ igraph_random_edge_walk(&graph, &weights, &walk, 0, IGRAPH_OUT, 1000, IGRAPH_RANDOM_WALK_STUCK_RETURN); assert(igraph_vector_size(&walk) == 1000); /* weighted, undirecetd */ igraph_random_edge_walk(&graph, &weights, &walk, 0, IGRAPH_ALL, 1000, IGRAPH_RANDOM_WALK_STUCK_RETURN); assert(igraph_vector_size(&walk) == 1000); igraph_destroy(&graph); /* 1-vertex graph, should get stuck */ igraph_empty(&graph, 1, /* directed = */ 0); igraph_random_edge_walk(&graph, NULL, &walk, 0, IGRAPH_OUT, 1000, IGRAPH_RANDOM_WALK_STUCK_RETURN); assert(igraph_vector_size(&walk) == 0); igraph_destroy(&graph); igraph_vector_destroy(&weights); igraph_vector_destroy(&walk); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_bfs2.out0000644000076500000240000000075113524616144026646 0ustar tamasstaff000000000000000 1 9 2 8 3 7 4 6 5 10 11 19 12 18 13 17 14 16 15 0 1 3 5 7 9 8 6 4 2 10 11 13 15 17 19 18 16 14 12 -1 0 1 2 3 4 7 8 9 0 -1 10 11 12 13 14 17 18 19 10 -1 0 9 8 7 6 4 3 2 1 -1 10 19 18 17 16 14 13 12 11 1 9 8 7 6 -1 5 4 3 2 11 19 18 17 16 -1 15 14 13 12 0 1 2 3 4 5 4 3 2 1 0 1 2 3 4 5 4 3 2 1 0 1 9 2 8 3 7 4 6 5 10 11 19 12 18 13 17 14 16 15 2 1 3 0 4 9 5 8 6 7 10 11 19 12 18 13 17 14 16 15 5 6 7 8 9 10 11 19 12 18 13 17 14 16 15 5 6 7 8 9 10 11 19 12 18 13 17 14 16 15 6 5 7 8 9 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_betweenness.c0000644000076500000240000001537513612122633027750 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2008-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void print_vector(igraph_vector_t *v, FILE *f) { long int i; for (i = 0; i < igraph_vector_size(v); i++) { fprintf(f, " %li", (long int) VECTOR(*v)[i]); } fprintf(f, "\n"); } int main() { igraph_t g; igraph_vector_t bet, bet2, weights, edges; igraph_real_t nontriv[] = { 0, 19, 0, 16, 0, 20, 1, 19, 2, 5, 3, 7, 3, 8, 4, 15, 4, 11, 5, 8, 5, 19, 6, 7, 6, 10, 6, 8, 6, 9, 7, 20, 9, 10, 9, 20, 10, 19, 11, 12, 11, 20, 12, 15, 13, 15, 14, 18, 14, 16, 14, 17, 15, 16, 17, 18 }; igraph_real_t nontriv_weights[] = { 0.5249, 1, 0.1934, 0.6274, 0.5249, 0.0029, 0.3831, 0.05, 0.6274, 0.3831, 0.5249, 0.0587, 0.0579, 0.0562, 0.0562, 0.1934, 0.6274, 0.6274, 0.6274, 0.0418, 0.6274, 0.3511, 0.3511, 0.1486, 1, 1, 0.0711, 0.2409 }; igraph_real_t nontriv_res[] = { 20, 0, 0, 0, 0, 19, 80, 85, 32, 0, 10, 75, 70, 0, 36, 81, 60, 0, 19, 19, 86 }; /*******************************************************/ igraph_barabasi_game(/* graph= */ &g, /* n= */ 1000, /* power= */ 1, /* m= */ 3, /* outseq= */ 0, /* outpref= */ 0, /* A= */ 1, /* directed= */ 0, /* algo= */ IGRAPH_BARABASI_BAG, /* start_from= */ 0); igraph_simplify(&g, /* multiple= */ 1, /* loops= */ 1, /*edge_comb=*/ 0); igraph_vector_init(&bet, 0); igraph_betweenness_estimate(/* graph= */ &g, /* res= */ &bet, /* vids= */ igraph_vss_all(), /* directed = */ 0, /* cutoff= */ 2, /* weights= */ 0, /* nobigint= */ 1); igraph_vector_destroy(&bet); igraph_destroy(&g); /*******************************************************/ igraph_tree(&g, 20000, 10, IGRAPH_TREE_UNDIRECTED); igraph_vector_init(&bet, 0); igraph_betweenness_estimate(/* graph= */ &g, /* res= */ &bet, /* vids= */ igraph_vss_all(), /* directed = */ 0, /* cutoff= */ 3, /* weights= */ 0, /* nobigint= */ 1); igraph_vector_init(&bet2, 0); igraph_vector_init(&weights, igraph_ecount(&g)); igraph_vector_fill(&weights, 1.0); igraph_betweenness_estimate(/* graph= */ &g, /* res= */ &bet2, /* vids= */ igraph_vss_all(), /* directed = */ 0, /* cutoff= */ 3, /* weights= */ &weights, /* nobigint= */ 1); if (!igraph_vector_all_e(&bet, &bet2)) { return 1; } igraph_vector_destroy(&bet); igraph_vector_destroy(&bet2); igraph_vector_destroy(&weights); igraph_destroy(&g); /* Non-trivial weighted graph */ igraph_vector_view(&edges, nontriv, sizeof(nontriv) / sizeof(igraph_real_t)); igraph_create(&g, &edges, 0, /* directed= */ 0); igraph_vector_view(&weights, nontriv_weights, sizeof(nontriv_weights) / sizeof(igraph_real_t)); igraph_vector_init(&bet, 0); igraph_betweenness(/*graph=*/ &g, /*res=*/ &bet, /*vids=*/ igraph_vss_all(), /*directed=*/0, /*weights=*/ &weights, /*nobigint=*/ 1); igraph_vector_view(&bet2, nontriv_res, sizeof(nontriv_res) / sizeof(igraph_real_t)); if (!igraph_vector_all_e(&bet, &bet2)) { return 2; } igraph_vector_destroy(&bet); igraph_destroy(&g); /* test corner case of cutoff = 0 */ igraph_tree(&g, 20, 3, IGRAPH_TREE_UNDIRECTED); /* unweighted */ igraph_vector_init(&bet, 0); igraph_betweenness_estimate(/* graph= */ &g, /* res= */ &bet, /* vids= */ igraph_vss_all(), /* directed = */ 0, /* cutoff= */ 0, /* weights= */ 0, /* nobigint= */ 1); igraph_vector_init(&bet2, 0); igraph_betweenness_estimate(/* graph= */ &g, /* res= */ &bet2, /* vids= */ igraph_vss_all(), /* directed = */ 0, /* cutoff= */ -1, /* weights= */ 0, /* nobigint= */ 1); if (!igraph_vector_all_e(&bet, &bet2)) { return 1; } igraph_vector_destroy(&bet); igraph_vector_destroy(&bet2); /* weighted */ igraph_vector_init(&weights, igraph_ecount(&g)); igraph_vector_fill(&weights, 2.0); igraph_vector_init(&bet, 0); igraph_betweenness_estimate(/* graph= */ &g, /* res= */ &bet, /* vids= */ igraph_vss_all(), /* directed = */ 0, /* cutoff= */ 0, /* weights= */ &weights, /* nobigint= */ 1); igraph_vector_init(&bet2, 0); igraph_betweenness_estimate(/* graph= */ &g, /* res= */ &bet2, /* vids= */ igraph_vss_all(), /* directed = */ 0, /* cutoff= */ -1, /* weights= */ &weights, /* nobigint= */ 1); if (!igraph_vector_all_e(&bet, &bet2)) { return 1; } igraph_vector_destroy(&bet); igraph_vector_destroy(&bet2); igraph_vector_destroy(&weights); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_coloring.c0000644000076500000240000000140713612122633027231 0ustar tamasstaff00000000000000 #include #include int main() { igraph_t graph; igraph_vector_int_t colors; igraph_rng_seed(igraph_rng_default(), 42); igraph_erdos_renyi_game(&graph, IGRAPH_ERDOS_RENYI_GNM, 1000, 10000, /* directed = */ 0, /* loops = */ 0); igraph_vector_int_init(&colors, 0); igraph_vertex_coloring_greedy(&graph, &colors, IGRAPH_COLORING_GREEDY_COLORED_NEIGHBORS); /* verify that the colouring is valid: */ { long i; long no_of_edges = igraph_ecount(&graph); for (i = 0; i < no_of_edges; ++i) { assert( VECTOR(colors)[ IGRAPH_FROM(&graph, i) ] != VECTOR(colors)[ IGRAPH_TO(&graph, i) ] ); } } igraph_vector_int_destroy(&colors); igraph_destroy(&graph); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/pajek_bipartite.out0000644000076500000240000000022413524616144027610 0ustar tamasstaff00000000000000*Vertices 10 5 1 "1" 2 "3" 3 "5" 4 "7" 5 "9" 6 "2" 7 "4" 8 "6" 9 "8" 10 "10" *Edges 1 6 6 2 2 7 7 3 3 8 8 4 4 9 9 5 5 10 1 10 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_get_all_simple_paths.c0000644000076500000240000000347413612122633031602 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_small(&g, 6, IGRAPH_UNDIRECTED, 0, 1, 1, 2, 2, 5, 0, 3, 3, 4, 4, 5, 3, 2, 3, 5, -1); igraph_vector_int_t res; igraph_vector_int_init(&res, 0); int i; for (i = 0; i <= 5; i++) { igraph_get_all_simple_paths(&g, &res, 0, igraph_vss_1(5), i, IGRAPH_ALL); printf("Paths for cutoff %i:\n", i); igraph_vector_int_print(&res); igraph_vector_int_clear(&res); } igraph_vector_int_t res_all; igraph_vector_int_init(&res_all, 0); igraph_get_all_simple_paths(&g, &res_all, 0, igraph_vss_1(5), -1, IGRAPH_ALL); if (igraph_vector_int_all_e(&res, &res_all)) { printf("Paths of all lengths does not equal result for maximum cutoff."); return 1; } igraph_vector_int_destroy(&res_all); igraph_vector_int_destroy(&res); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/cattributes4.out0000644000076500000240000000470013524616144027073 0ustar tamasstaff00000000000000 green white black blue white black greenredblue green green python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_scg_semiprojectors3.out0000644000076500000240000000140113524616144031772 0ustar tamasstaff00000000000000---------------------- 1 0 0 0 0 0 0 0 0 0 0 0 0 0.142857 0.142857 0.142857 0.142857 0.142857 0.142857 0.142857 0 0.5 0.5 0 0 0 0 0 0 0 --- 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 0 1 1 0 0 0 0 0 0 0 --- ---------------------- 0.125 0 0 0.125 0.125 0.125 0.125 0.125 0.125 0.125 0 0.5 0.5 0 0 0 0 0 0 0 --- 1 0 0 1 1 1 1 1 1 1 0 1 1 0 0 0 0 0 0 0 --- ---------------------- 0.142857 0 0 0 0.142857 0.142857 0.142857 0.142857 0.142857 0.142857 0 0.333333 0.333333 0.333333 0 0 0 0 0 0 --- 1 0 0 0 1 1 1 1 1 1 0 1 1 1 0 0 0 0 0 0 --- ---------------------- 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0.166667 0.166667 0.166667 0.166667 0.166667 0.166667 0 0 0 1 0 0 0 0 0 0 0 0.5 0.5 0 0 0 0 0 0 0 --- 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 --- python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_power_law_fit.out0000644000076500000240000000121713524616144030651 0ustar tamasstaff00000000000000continuous = true alpha = 2.81976 xmin = 1.00979 L = -946.14703 D = 0.01454 p = 0.98525 ==================== continuous = true alpha = 2.81157 xmin = 2.00000 L = -463.92064 D = 0.05091 p = 0.46011 ==================== continuous = false alpha = 3.11402 xmin = 1.00000 L = -622.60933 D = 0.00941 p = 0.99999 ==================== continuous = false alpha = 3.27159 xmin = 2.00000 L = -185.83215 D = 0.04504 p = 0.90576 ==================== continuous = true alpha = 3.77550 xmin = 11.00000 L = -13.68681 D = 0.15260 p = 0.99902 ==================== continuous = true alpha = 5.26868 xmin = 2.00000 L = -75.22503 D = 0.70253 p = 0.00000 ==================== python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_local_transitivity.c0000644000076500000240000000350513612122633031341 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_vs_t vertices; igraph_vector_t result1, result2; igraph_rng_seed(igraph_rng_default(), 42); igraph_vector_init(&result1, 0); igraph_vector_init(&result2, 0); igraph_erdos_renyi_game(&g, IGRAPH_ERDOS_RENYI_GNP, 100, .1, IGRAPH_UNDIRECTED, IGRAPH_NO_LOOPS); igraph_vs_seq(&vertices, 0, 99); igraph_transitivity_local_undirected(&g, &result1, igraph_vss_all(), IGRAPH_TRANSITIVITY_NAN); igraph_transitivity_local_undirected(&g, &result2, vertices, IGRAPH_TRANSITIVITY_NAN); if (!igraph_vector_all_e(&result1, &result2)) { igraph_vector_print(&result1); igraph_vector_print(&result2); return 1; } igraph_vector_destroy(&result1); igraph_vector_destroy(&result2); igraph_vs_destroy(&vertices); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_density.out0000644000076500000240000000027113524616144027466 0ustar tamasstaff00000000000000nan nan nan nan ====== nan 0.0000 nan 0.0000 ====== 1.0000 1.0000 ====== 2.0000 2.0000 ====== 1.0000 0.3333 0.5000 0.2500 ====== 0.6667 0.5000 ====== 1.0000 0.7500 ====== 0.1390 0.1311 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_lapack_dsyevr.c0000644000076500000240000001470113614300625030246 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #define DIM 10 igraph_bool_t check_ev(const igraph_matrix_t *A, const igraph_vector_t *values, const igraph_matrix_t *vectors, igraph_real_t tol) { igraph_vector_t v, y; int i, j; int m = igraph_matrix_ncol(vectors); int n = igraph_matrix_nrow(A); if (igraph_matrix_ncol(A) != n) { return 1; } if (igraph_vector_size(values) != m) { return 1; } if (igraph_matrix_nrow(vectors) != n) { return 1; } igraph_vector_init(&y, n); for (i = 0; i < m; i++) { igraph_vector_view(&v, &MATRIX(*vectors, 0, i), n); igraph_vector_update(&y, &v); igraph_blas_dgemv(/*transpose=*/ 0, /*alpha=*/ 1.0, A, &v, /*beta=*/ -VECTOR(*values)[i], &y); for (j = 0; j < n; j++) { if (fabs(VECTOR(y)[i]) > tol) { printf("Matrix:\n"); igraph_matrix_print(A); printf("lambda= %g\n", VECTOR(*values)[i]); printf("v= "); igraph_vector_print(&v); printf("residual: "); igraph_vector_print(&y); return 1; } } } igraph_vector_destroy(&y); return 0; } int main() { igraph_matrix_t A; igraph_matrix_t vectors, vectors2; igraph_vector_t values, values2; int i, j; int il, iu; igraph_real_t vl, vu; igraph_rng_seed(igraph_rng_default(), 42); igraph_matrix_init(&A, DIM, DIM); igraph_matrix_init(&vectors, 0, 0); igraph_vector_init(&values, 0); /* All eigenvalues and eigenvectors */ for (i = 0; i < DIM; i++) { for (j = i; j < DIM; j++) { MATRIX(A, i, j) = MATRIX(A, j, i) = igraph_rng_get_integer(igraph_rng_default(), 1, 10); } } igraph_lapack_dsyevr(&A, IGRAPH_LAPACK_DSYEV_ALL, /*vl=*/ 0, /*vu=*/ 0, /*vestimate=*/ 0, /*il=*/ 0, /*iu=*/ 0, /*abstol=*/ 1e-10, &values, &vectors, /*support=*/ 0); if (igraph_vector_size(&values) != DIM) { return 1; } if (igraph_matrix_nrow(&vectors) != DIM || igraph_matrix_ncol(&vectors) != DIM) { return 2; } if (check_ev(&A, &values, &vectors, /*tol=*/ 1e-8)) { return 3; } /* Only a subset */ igraph_matrix_init(&vectors2, 0, 0); igraph_vector_init(&values2, 0); il = 2; iu = 5; igraph_lapack_dsyevr(&A, IGRAPH_LAPACK_DSYEV_SELECT, /*vl=*/ 0, /*vu=*/ 0, /*vestimate=*/ 0, /*il=*/ il, /*iu=*/ iu, /*abstol=*/ 1e-10, &values2, &vectors2, /*support=*/ 0); if (igraph_vector_size(&values2) != iu - il + 1) { return 4; } if (igraph_matrix_nrow(&vectors2) != DIM || igraph_matrix_ncol(&vectors2) != iu - il + 1) { return 5; } for (i = 0; i < iu - il + 1; i++) { igraph_real_t m1 = 1.0; if (fabs(VECTOR(values)[il + i - 1] - VECTOR(values2)[i]) > 1e-8) { printf("Full: "); igraph_vector_print(&values); printf("Subset: "); igraph_vector_print(&values2); return 6; } if (MATRIX(vectors, 0, il + i - 1) * MATRIX(vectors2, 0, i) < 0) { m1 = -1.0; } else { m1 = 1.0; } for (j = 0; j < DIM; j++) { if (fabs(MATRIX(vectors, j, il + i - 1) - m1 * MATRIX(vectors2, j, i)) > 1e-8) { printf("Full:\n"); igraph_matrix_print(&vectors); printf("Subset:\n"); igraph_matrix_print(&vectors2); return 7; } } } igraph_vector_destroy(&values2); igraph_matrix_destroy(&vectors2); /* Subset based on an interval */ igraph_matrix_init(&vectors2, 0, 0); igraph_vector_init(&values2, 0); il = 2; iu = 5; vl = (VECTOR(values)[il - 1] + VECTOR(values)[il - 2]) / 2.0; vu = (VECTOR(values)[iu] + VECTOR(values)[iu - 1]) / 2.0; igraph_lapack_dsyevr(&A, IGRAPH_LAPACK_DSYEV_INTERVAL, vl, vu, /*vestimate=*/ iu - il + 1, /*il=*/ 0, /*iu=*/ 0, /*abstol=*/ 1e-10, &values2, &vectors2, /*support=*/ 0); if (igraph_vector_size(&values2) != iu - il + 1) { return 4; } if (igraph_matrix_nrow(&vectors2) != DIM || igraph_matrix_ncol(&vectors2) != iu - il + 1) { return 5; } for (i = 0; i < iu - il + 1; i++) { igraph_real_t m1 = 1.0; if (fabs(VECTOR(values)[il + i - 1] - VECTOR(values2)[i]) > 1e-8) { printf("Full: "); igraph_vector_print(&values); printf("Subset: "); igraph_vector_print(&values2); return 6; } if (MATRIX(vectors, 0, il + i - 1) * MATRIX(vectors2, 0, i) < 0) { m1 = -1.0; } else { m1 = 1.0; } for (j = 0; j < DIM; j++) { if (fabs(MATRIX(vectors, j, il + i - 1) - m1 * MATRIX(vectors2, j, i)) > 1e-8) { printf("Full:\n"); igraph_matrix_print(&vectors); printf("Subset:\n"); igraph_matrix_print(&vectors2); return 7; } } } igraph_vector_destroy(&values2); igraph_matrix_destroy(&vectors2); igraph_vector_destroy(&values); igraph_matrix_destroy(&vectors); igraph_matrix_destroy(&A); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/levc-stress.c0000644000076500000240000000436513614300625026344 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set sw=4 ts=4 sts=4 et: */ /* IGraph library. Copyright (C) 2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ /* This is a test for bug #1002140, reported by Luiz Fernando Bittencourt: https://bugs.launchpad.net/igraph/+bug/1002140 */ #include int main() { int k; for (k = 0; k < 20; k++) { igraph_t g; igraph_matrix_t merges; igraph_vector_t membership; igraph_arpack_options_t options; double modularity; igraph_vector_t history; FILE *DLFile = fopen("input.dl", "r"); igraph_read_graph_dl(&g, DLFile, /*directed=*/ 0); fclose(DLFile); igraph_matrix_init(&merges, 0, 0); igraph_vector_init(&membership, 0); igraph_vector_init(&history, 0); igraph_arpack_options_init(&options); igraph_community_leading_eigenvector(&g, /*weights=*/ 0, &merges, &membership, igraph_vcount(&g), &options, &modularity, /*start=*/ 0, /*eigenvalues=*/ 0, /*eigenvectors=*/ 0, &history, /*callback=*/ 0, /*callback_extra=*/ 0); igraph_vector_destroy(&history); igraph_vector_destroy(&membership); igraph_matrix_destroy(&merges); igraph_destroy(&g); } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_vs_seq.c0000644000076500000240000000262713612122634026723 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_vs_t vs; igraph_vit_t vit; igraph_t g; igraph_integer_t size; igraph_ring(&g, 10, IGRAPH_UNDIRECTED, 0, 1); igraph_vs_seq(&vs, 0, 9); igraph_vit_create(&g, vs, &vit); igraph_vs_size(&g, &vs, &size); printf("%li", (long int) size); while (!IGRAPH_VIT_END(vit)) { printf(" %li", (long int)IGRAPH_VIT_GET(vit)); IGRAPH_VIT_NEXT(vit); } printf("\n"); igraph_vit_destroy(&vit); igraph_vs_destroy(&vs); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_scg_semiprojectors2.out0000644000076500000240000000154213524616144031777 0ustar tamasstaff00000000000000---------------------- 0.75 0 0 0.25 0 0 0 0 0 0 0 0.5 0.5 0 0 0 0 0 0 0 0 0 0 0 0.166667 0.166667 0.166667 0.166667 0.166667 0.166667 --- 1 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 --- ---------------------- 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0.285714 0.285714 0 0.0714286 0.0714286 0.0714286 0.0714286 0.0714286 0.0714286 --- 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 1 0 1 1 1 1 1 1 --- ---------------------- 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0.285714 0.285714 0 0.0714286 0.0714286 0.0714286 0.0714286 0.0714286 0.0714286 --- 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 1 0 1 1 1 1 1 1 --- ---------------------- 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0.5 0.5 0 0 0 0 0 0 0 0 0 0 0 0.166667 0.166667 0.166667 0.166667 0.166667 0.166667 --- 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 --- python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_intersection.out0000644000076500000240000000003313524616144030511 0ustar tamasstaff00000000000000--- 1 2 1 2 --- 1 2 2 3 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_girth.c0000644000076500000240000000242013612122633026526 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_integer_t girth; igraph_vector_t v; igraph_real_t chord[] = { 0, 50 }; igraph_ring(&g, 100, IGRAPH_UNDIRECTED, 0, 1); igraph_vector_view(&v, chord, sizeof(chord) / sizeof(igraph_real_t)); igraph_add_edges(&g, &v, 0); igraph_girth(&g, &girth, 0); if (girth != 51) { return 1; } igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/cattributes5.out0000644000076500000240000001637413524616144027106 0ustar tamasstaff00000000000000 true false true false false true false false true true false true false false true false false true true false true true false true true false true python-igraph-0.8.0/vendor/source/igraph/examples/simple/dijkstra.out0000644000076500000240000000065613524616144026277 0ustar tamasstaff000000000000000: 0 0 0 1 5 2 1 13 3 5 1: inf 0 0 1 5 2 1 13 3 5 2: inf 1 0 1 6 3 1 14 4 6 3: inf 1 0 0 6 3 1 14 4 6 4: inf 5 4 5 0 2 3 8 3 5 5: inf 3 2 3 8 0 1 16 1 3 6: inf inf inf inf inf inf 0 inf inf inf 7: inf 4 3 4 9 1 2 0 1 4 8: inf inf inf inf inf inf inf inf 0 4 9: inf inf inf inf inf inf inf inf inf 0 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_growing_random_game.c0000644000076500000240000000163713612122633031427 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_layout_davidson_harel.c0000644000076500000240000000714413614300625032001 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph R package. Copyright (C) 2014 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include igraph_bool_t igraph_i_segments_intersect(float p0_x, float p0_y, float p1_x, float p1_y, float p2_x, float p2_y, float p3_x, float p3_y); float igraph_i_point_segment_dist2(float v_x, float v_y, float u1_x, float u1_y, float u2_x, float u2_y); int intersect() { float negative[][8] = { { 1, 2, 2, 2, 1, 1, 2, 1 }, /* 1 */ { 1, 2, 1, 1, 2, 2, 2, 1 }, /* 2 */ { 1, 0, 0, 1, 2, 0, 3, 1 }, /* 3 */ { 1, 0, 1, 1, 0, 2, 2, 2 }, /* 4 */ { 1, 0, 1, 2, 3, 1, 3, 3 }, /* 5 */ { 0, 0, 0, 2, 1, 1, 1, 2 }, /* 6 */ { 0, 1, 1, 1, 2, 0, 2, 3 }, /* 7 */ { 0, 0, 5, 0, 2, 1, 4, 3 }, /* 8 */ { 0, 0, 5, 5, 3, 2, 3, 2 } }; /* 9 */ float positive[][8] = { { 0, 1, 2, 1, 1, 0, 1, 2 }, /* 10 */ { 0, 2, 5, 2, 1, 1, 4, 3 }, /* 11 */ { 0, 0, 0, 3, 0, 1, 5, 1 }, /* 12 */ { 0, 4, 2, 6, 0, 4, 2, 2 } }; /* 13 */ /* { 1,1,1,1, 1,1,0,0 }, /\* 14 *\/ */ /* { 0,0,1,1, 1,1,1,1 }, /\* 15 *\/ */ /* { 0,0,2,2, 1,1,1,1 }}; /\* 16 *\/ */ int no_neg = sizeof(negative) / sizeof(float) / 8; int no_pos = sizeof(positive) / sizeof(float) / 8; int i; for (i = 0; i < no_neg; i++) { float *co = negative[i]; if (igraph_i_segments_intersect(co[0], co[1], co[2], co[3], co[4], co[5], co[6], co[7])) { return i + 1; } } for (i = 0; i < no_pos; i++) { float *co = positive[i]; if (!igraph_i_segments_intersect(co[0], co[1], co[2], co[3], co[4], co[5], co[6], co[7])) { return no_neg + i + 1; } } return 0; } int distance() { float configs[][7] = { { 1, 1, 2, 0, 2, 3, 1.0 }, /* 1 */ { 1, 1, 1, 0, 1, 3, 0.0 }, /* 2 */ { 1, 1, 0, 1, 1, 0, 0.5 }, /* 3 */ { 1, 2, 0, 0, 0, 1, 2.0 }, /* 4 */ { 1, 0, 0, 1, 0, 2, 2.0 }, /* 5 */ { 0, 0, 1, 1, 1, 2, 2.0 }, /* 6 */ { 0, 3, 1, 1, 1, 2, 2.0 } }; /* 7 */ int no = sizeof(configs) / sizeof(float) / 8; int i; for (i = 0; i < no; i++) { float *co = configs[i]; float res = igraph_i_point_segment_dist2(co[0], co[1], co[2], co[3], co[4], co[5]); if (fabsf(res - co[6]) > 1e-12) { printf("%g\n", (double) res); return i + 1; } } return 0; } int main() { int res1, res2; res1 = intersect(); if (res1 != 0) { printf("I\n"); return res1; } res2 = distance() ; if (res2 != 0) { printf("D\n"); return res2; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_layout_merge3.c0000644000076500000240000000256713612122633030204 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t graph; igraph_matrix_t coords; int i; igraph_matrix_init(&coords, 0, 0); for (i = 0; i < 10; i++) { igraph_erdos_renyi_game(&graph, IGRAPH_ERDOS_RENYI_GNP, /*n=*/ 100, /*p=*/ 2.0 / 100, IGRAPH_UNDIRECTED, /*loops=*/ 0); igraph_layout_mds(&graph, &coords, /*dist=*/ 0, /*dim=*/ 2, /*options=*/ 0); igraph_destroy(&graph); } igraph_matrix_destroy(&coords); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_lapack_dgeevx.c0000644000076500000240000001541013614300625030212 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include #define DIM 10 int real_cplx_mult(const igraph_matrix_t *A, const igraph_vector_t *v_real, const igraph_vector_t *v_imag, igraph_vector_t *res_real, igraph_vector_t *res_imag) { int n = igraph_vector_size(v_real); int r, c; if (igraph_matrix_nrow(A) != n || igraph_matrix_ncol(A) != n || igraph_vector_size(v_imag) != n) { printf("Wrong matrix or vector size"); return 1; } igraph_vector_resize(res_real, n); igraph_vector_resize(res_imag, n); for (r = 0; r < n; r++) { igraph_real_t s_real = 0.0; igraph_real_t s_imag = 0.0; for (c = 0; c < n; c++) { s_real += MATRIX(*A, r, c) * VECTOR(*v_real)[c]; s_imag += MATRIX(*A, r, c) * VECTOR(*v_imag)[c]; } VECTOR(*res_real)[r] = s_real; VECTOR(*res_imag)[r] = s_imag; } return 0; } int sc_cplx_cplx_mult(igraph_real_t lambda_real, igraph_real_t lambda_imag, const igraph_vector_t *v_real, const igraph_vector_t *v_imag, igraph_vector_t *res_real, igraph_vector_t *res_imag) { int r; int n = igraph_vector_size(v_real); if (igraph_vector_size(v_imag) != n) { printf("Wrong vector sizes"); return 1; } igraph_vector_resize(res_real, n); igraph_vector_resize(res_imag, n); for (r = 0; r < n; r++) { VECTOR(*res_real)[r] = (lambda_real * VECTOR(*v_real)[r] - lambda_imag * VECTOR(*v_imag)[r]); VECTOR(*res_imag)[r] = (lambda_imag * VECTOR(*v_real)[r] + lambda_real * VECTOR(*v_imag)[r]); } return 0; } igraph_bool_t check_ev(const igraph_matrix_t *A, const igraph_vector_t *values_real, const igraph_vector_t *values_imag, const igraph_matrix_t *vectors_left, const igraph_matrix_t *vectors_right, igraph_real_t tol) { int n = igraph_matrix_nrow(A); igraph_vector_t v_real, v_imag; igraph_vector_t AV_real, AV_imag, lv_real, lv_imag; igraph_vector_t null; int i; if (igraph_matrix_ncol(A) != n) { return 1; } if (igraph_vector_size(values_real) != n) { return 1; } if (igraph_vector_size(values_imag) != n) { return 1; } if (igraph_matrix_nrow(vectors_left) != n) { return 1; } if (igraph_matrix_ncol(vectors_left) != n) { return 1; } if (igraph_matrix_nrow(vectors_right) != n) { return 1; } if (igraph_matrix_ncol(vectors_right) != n) { return 1; } igraph_vector_init(&AV_real, n); igraph_vector_init(&AV_imag, n); igraph_vector_init(&lv_real, n); igraph_vector_init(&lv_imag, n); igraph_vector_init(&null, n); igraph_vector_null(&null); for (i = 0; i < n; i++) { if (VECTOR(*values_imag)[i] == 0.0) { igraph_vector_view(&v_real, &MATRIX(*vectors_right, 0, i), n); igraph_vector_view(&v_imag, VECTOR(null), n); } else if (VECTOR(*values_imag)[i] > 0.0) { igraph_vector_view(&v_real, &MATRIX(*vectors_right, 0, i), n); igraph_vector_view(&v_imag, &MATRIX(*vectors_right, 0, i + 1), n); } else if (VECTOR(*values_imag)[i] < 0.0) { igraph_vector_view(&v_real, &MATRIX(*vectors_right, 0, i - 1), n); igraph_vector_view(&v_imag, &MATRIX(*vectors_right, 0, i), n); igraph_vector_scale(&v_imag, -1.0); } real_cplx_mult(A, &v_real, &v_imag, &AV_real, &AV_imag); sc_cplx_cplx_mult(VECTOR(*values_real)[i], VECTOR(*values_imag)[i], &v_real, &v_imag, &lv_real, &lv_imag); if (igraph_vector_maxdifference(&AV_real, &lv_real) > tol || igraph_vector_maxdifference(&AV_imag, &lv_imag) > tol) { igraph_vector_print(&AV_real); igraph_vector_print(&AV_imag); igraph_vector_print(&lv_real); igraph_vector_print(&lv_imag); return 1; } } igraph_vector_destroy(&null); igraph_vector_destroy(&AV_imag); igraph_vector_destroy(&AV_real); igraph_vector_destroy(&lv_imag); igraph_vector_destroy(&lv_real); return 0; } int main() { igraph_matrix_t A; igraph_matrix_t vectors_left, vectors_right; igraph_vector_t values_real, values_imag; int i, j; int info = 1; int ilo, ihi; igraph_real_t abnrm; igraph_rng_seed(igraph_rng_default(), 42); igraph_matrix_init(&A, DIM, DIM); igraph_matrix_init(&vectors_left, 0, 0); igraph_matrix_init(&vectors_right, 0, 0); igraph_vector_init(&values_real, 0); igraph_vector_init(&values_imag, 0); for (i = 0; i < DIM; i++) { for (j = 0; j < DIM; j++) { MATRIX(A, i, j) = igraph_rng_get_integer(igraph_rng_default(), 1, 10); } } igraph_lapack_dgeevx(IGRAPH_LAPACK_DGEEVX_BALANCE_BOTH, &A, &values_real, &values_imag, &vectors_left, &vectors_right, &ilo, &ihi, /*scale=*/ 0, &abnrm, /*rconde=*/ 0, /*rcondv=*/ 0, &info); if (check_ev(&A, &values_real, &values_imag, &vectors_left, &vectors_right, /*tol=*/ 1e-8)) { return 1; } /* igraph_matrix_print(&A); */ /* igraph_vector_print(&values_real); */ /* igraph_vector_print(&values_imag); */ /* igraph_matrix_print(&vectors_left); */ /* igraph_matrix_print(&vectors_right); */ igraph_vector_destroy(&values_imag); igraph_vector_destroy(&values_real); igraph_matrix_destroy(&vectors_right); igraph_matrix_destroy(&vectors_left); igraph_matrix_destroy(&A); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_small.c0000644000076500000240000000210213612122633026516 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_small(&g, 0, IGRAPH_DIRECTED, 0, 1, 1, 2, 2, 3, 3, 4, 6, 1, -1); igraph_write_graph_edgelist(&g, stdout); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/graphml-namespace.xml0000644000076500000240000000064413524616144030036 0ustar tamasstaff00000000000000 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_random_sample.c0000644000076500000240000001422313614300625030237 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* Test suite for random sampling. Copyright (C) 2011 Minh Van Nguyen This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include #include #include #define R_INTEGER(a,b) (igraph_rng_get_integer(igraph_rng_default(), (a), (b))) /* test parameters */ typedef struct { igraph_integer_t low; igraph_integer_t high; igraph_integer_t length; int retval; } sampling_test_t; /* Error tests. Don't be afraid to crash the library function. */ int error_test() { igraph_vector_t V; int i, n, ret; sampling_test_t *test; igraph_rng_seed(igraph_rng_default(), time(0)); igraph_vector_init(&V, /*size*/ 0); /* test parameters */ /*----------low----high----length----retval----------*/ /* lower limit is greater than upper limit */ sampling_test_t lower_bigger = {300, 200, 10, IGRAPH_EINVAL}; /* sample size is greater than size of candidate pool */ sampling_test_t sample_size_bigger = {200, 300, 500, IGRAPH_EINVAL}; sampling_test_t *all_checks[] = {/* 1 */ &lower_bigger, /* 2 */ &sample_size_bigger}; /* failure is the mother of success */ igraph_set_error_handler(igraph_error_handler_ignore); n = 2; for (i = 0; i < n; i++) { test = all_checks[i]; ret = igraph_random_sample(&V, test->low, test->high, test->length); if (ret != test->retval) { printf("Error test no. %d failed.\n", (int)(i + 1)); return IGRAPH_FAILURE; } } igraph_set_error_handler(igraph_error_handler_abort); igraph_vector_destroy(&V); return IGRAPH_SUCCESS; } /* Get a few random samples and test their properties. */ int random_sample_test() { const igraph_integer_t min = -1000; const igraph_integer_t max = 1000; igraph_integer_t low; /* lower limit */ igraph_integer_t high; /* upper limit */ igraph_integer_t length; /* sample size */ igraph_integer_t poolsize; /* size of candidate pool */ igraph_real_t sP; /* population total sum */ igraph_real_t ss; /* sample total sum */ igraph_vector_t V; int i; igraph_rng_seed(igraph_rng_default(), time(0)); /* The generated sequence of numbers must be in increasing order. */ igraph_vector_init(&V, /*size*/ 0); do { high = (igraph_integer_t)R_INTEGER(min, max); } while (high == min); do { low = (igraph_integer_t)R_INTEGER(min, max); } while (low >= high); poolsize = (igraph_integer_t)fabs((double)high - (double)low); do { length = (igraph_integer_t)R_INTEGER(1, max); } while (length > poolsize); igraph_random_sample(&V, low, high, length); if (length != igraph_vector_size(&V)) { printf("Requested vector length and resulting length mismatch.\n"); return IGRAPH_FAILURE; } for (i = 0; i < length - 1; i++) { if (VECTOR(V)[i] >= VECTOR(V)[i + 1]) { printf("Sample not in increasing order.\n"); return IGRAPH_FAILURE; } } igraph_vector_destroy(&V); /* Let P be a candidate pool of positive integers with total sum s_P. */ /* Let S be a random sample from P and having total sum s_S. Then we */ /* have the bound s_s <= s_P. */ igraph_vector_init(&V, /*size*/ 0); low = 1; do { high = (igraph_integer_t)R_INTEGER(low, max); } while (high == low); poolsize = (igraph_integer_t)fabs((double)high - (double)low); do { length = (igraph_integer_t)R_INTEGER(low, max); } while (length > poolsize); igraph_random_sample(&V, low, high, length); /* Use Gauss' formula to sum all consecutive positive integers from 1 */ /* up to and including an upper limit. In LaTeX, Gauss' formula is */ /* \sum_{i=1}^n i = \frac{n(n+1)}{2} where n is the upper limit. */ sP = (high * (high + 1)) / 2; ss = igraph_vector_sum(&V); if (ss > sP) { printf("Sum of sampled sequence exceeds sum of whole population.\n"); return IGRAPH_FAILURE; } igraph_vector_destroy(&V); return IGRAPH_SUCCESS; } int equal_test() { igraph_vector_t V; int i; igraph_vector_init(&V, 0); igraph_random_sample(&V, 0, 0, 1); if (igraph_vector_size(&V) != 1) { return 1; } if (VECTOR(V)[0] != 0) { return 2; } igraph_random_sample(&V, 10, 10, 1); if (igraph_vector_size(&V) != 1) { return 3; } if (VECTOR(V)[0] != 10) { return 4; } igraph_random_sample(&V, 2, 12, 11); if (igraph_vector_size(&V) != 11) { return 5; } for (i = 0; i < 11; i++) if (VECTOR(V)[i] != i + 2) { return 6; } igraph_vector_destroy(&V); return 0; } int rare_test() { igraph_vector_t V; igraph_vector_init(&V, 0); igraph_random_sample(&V, 0, 0, 1); if (igraph_vector_size(&V) != 1) { return 1; } if (VECTOR(V)[0] != 0) { return 2; } igraph_random_sample(&V, 10, 10, 1); if (igraph_vector_size(&V) != 1) { return 3; } if (VECTOR(V)[0] != 10) { return 4; } igraph_vector_destroy(&V); return 0; } int main() { int ret; ret = error_test(); if (ret) { return 1; } ret = random_sample_test(); if (ret) { return 2; } ret = equal_test(); if (ret) { return 3; } ret = rare_test(); if (ret) { return 4; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_scg_semiprojectors2.c0000644000076500000240000001143413612122633031404 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_matrix_t L, R; igraph_sparsemat_t Lsparse, Rsparse; igraph_matrix_t V, V3; igraph_matrix_complex_t V2; igraph_sparsemat_t stochastic, stochasticT; igraph_vector_t groups; igraph_eigen_which_t which; igraph_vector_t p, selcol; igraph_matrix_init(&L, 0, 0); igraph_matrix_init(&R, 0, 0); igraph_matrix_init(&V, 0, 0); igraph_matrix_init(&V3, 0, 0); igraph_vector_init(&groups, 0); igraph_vector_init(&selcol, 1); igraph_rng_seed(igraph_rng_default(), 42); igraph_tree(&g, 10, /* children= */ 3, IGRAPH_TREE_UNDIRECTED); igraph_matrix_complex_init(&V2, 0, 0); igraph_vector_init(&p, 0); igraph_rng_seed(igraph_rng_default(), 42); igraph_get_stochastic_sparsemat(&g, &stochastic, /*column-wise=*/ 0); igraph_sparsemat_transpose(&stochastic, &stochasticT, /*values=*/ 1); which.pos = IGRAPH_EIGEN_LR; which.howmany = 1; igraph_eigen_matrix(/*matrix=*/ 0, &stochasticT, /*fun=*/ 0, 10, /*extra=*/ 0, /*algorithm=*/ IGRAPH_EIGEN_LAPACK, &which, /*options=*/ 0, /*storage=*/ 0, /*values=*/ 0, &V2); igraph_matrix_complex_real(&V2, &V); /* `p' is always the eigenvector corresponding to the 1-eigenvalue */ igraph_matrix_get_col(&V, &p, 0); which.howmany = 3; igraph_eigen_matrix(/*matrix=*/ 0, &stochastic, /*fun=*/ 0, 10, /*extra=*/ 0, /*algorithm=*/ IGRAPH_EIGEN_LAPACK, &which, /*options=*/ 0, /*storage=*/ 0, /*values=*/ 0, &V2); igraph_matrix_complex_real(&V2, &V3); VECTOR(selcol)[0] = 2; igraph_matrix_select_cols(&V3, &V, &selcol); #define SEMI() \ do { \ igraph_scg_semiprojectors(&groups, IGRAPH_SCG_STOCHASTIC, &L, &R, \ &Lsparse, &Rsparse, &p, \ IGRAPH_SCG_NORM_ROW); \ } while(0) #define PRINTRES() \ do { \ printf("----------------------\n"); \ igraph_matrix_print(&L); \ printf("---\n"); \ igraph_matrix_print(&R); \ printf("---\n"); \ igraph_sparsemat_destroy(&Lsparse); \ igraph_sparsemat_destroy(&Rsparse); \ } while (0) /* -------------- */ igraph_scg_grouping(&V, &groups, /*intervals=*/ 3, /*intervals_vector=*/ 0, IGRAPH_SCG_STOCHASTIC, IGRAPH_SCG_OPTIMUM, &p, /*maxiter=*/ 10000); SEMI(); PRINTRES(); /* -------------- */ igraph_scg_grouping(&V, &groups, /*intervals=*/ 3, /*intervals_vector=*/ 0, IGRAPH_SCG_STOCHASTIC, IGRAPH_SCG_INTERV_KM, &p, /*maxiter=*/ 10000); SEMI(); PRINTRES(); /* -------------- */ igraph_scg_grouping(&V, &groups, /*intervals=*/ 3, /*intervals_vector=*/ 0, IGRAPH_SCG_STOCHASTIC, IGRAPH_SCG_INTERV, &p, /*maxiter=*/ 10000); SEMI(); PRINTRES(); /* -------------- */ igraph_scg_grouping(&V, &groups, /*(ignored) intervals=*/ 0, /*intervals_vector=*/ 0, IGRAPH_SCG_STOCHASTIC, IGRAPH_SCG_EXACT, &p, /*maxiter=*/ 10000); SEMI(); PRINTRES(); /* -------------- */ igraph_vector_destroy(&p); igraph_vector_destroy(&selcol); igraph_vector_destroy(&groups); igraph_matrix_destroy(&L); igraph_matrix_destroy(&R); igraph_matrix_destroy(&V); igraph_matrix_destroy(&V3); igraph_matrix_complex_destroy(&V2); igraph_sparsemat_destroy(&stochasticT); igraph_sparsemat_destroy(&stochastic); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_grg_game.c0000644000076500000240000000441413612122633027166 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int main() { igraph_t g; /* long int i; */ /* struct tms time; */ /* clock_t current_time,start_time; */ /* long int runs=100, n=10000; */ /* igraph_real_t r=0.01; */ /* Empty graph */ igraph_grg_game(&g, 100, 0, 0, 0, 0); if (igraph_ecount(&g) != 0) { return 1; } igraph_destroy(&g); /* Full graph */ igraph_grg_game(&g, 10, sqrt(2.0) / 2, 1, 0, 0); if (igraph_ecount(&g) != igraph_vcount(&g) * (igraph_vcount(&g) - 1) / 2) { return 2; } igraph_destroy(&g); /* Measure running time */ /* tps=sysconf(_SC_CLK_TCK); // clock ticks per second */ /* times(&time); start_time=time.tms_utime; */ /* for (i=0; i 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int main() { igraph_t g; igraph_vector_t tdist; igraph_matrix_t pmat; igraph_bool_t conn; igraph_vector_bool_t bs; int i; /* Symmetric preference game */ igraph_vector_bool_init(&bs, 0); igraph_vector_init_real(&tdist, 3, 1.0, 1.0, 1.0); igraph_matrix_init(&pmat, 3, 3); for (i = 0; i < 3; i++) { MATRIX(pmat, i, i) = 0.2; } /* undirected, no loops */ IGRAPH_CHECK(igraph_preference_game(&g, 1000, 3, &tdist, /*fixed_sizes=*/ 0, &pmat, 0, 0, 0)); if (igraph_vcount(&g) != 1000) { return 18; } if (igraph_is_directed(&g)) { return 2; } igraph_is_connected(&g, &conn, IGRAPH_STRONG); if (conn) { return 3; } igraph_is_loop(&g, &bs, igraph_ess_all(IGRAPH_EDGEORDER_ID)); if (igraph_vector_bool_sum(&bs)) { return 4; } igraph_is_multiple(&g, &bs, igraph_ess_all(IGRAPH_EDGEORDER_ID)); if (igraph_vector_bool_sum(&bs)) { return 5; } igraph_destroy(&g); for (i = 0; i < 2; i++) { MATRIX(pmat, i, i + 1) = 0.1; } /* directed, no loops */ IGRAPH_CHECK(igraph_preference_game(&g, 1000, 3, &tdist, /*fixed_sizes=*/0, &pmat, 0, 1, 0)); if (igraph_vcount(&g) != 1000) { return 17; } if (!igraph_is_directed(&g)) { return 6; } igraph_is_loop(&g, &bs, igraph_ess_all(IGRAPH_EDGEORDER_ID)); if (igraph_vector_bool_sum(&bs)) { return 7; } igraph_is_multiple(&g, &bs, igraph_ess_all(IGRAPH_EDGEORDER_ID)); if (igraph_vector_bool_sum(&bs)) { return 8; } igraph_destroy(&g); /* undirected, loops */ for (i = 0; i < 3; i++) { MATRIX(pmat, i, i) = 1.0; } IGRAPH_CHECK(igraph_preference_game(&g, 100, 3, &tdist, /*fixed_sizes=*/ 0, &pmat, 0, 0, 1)); if (igraph_vcount(&g) != 100) { return 16; } if (igraph_ecount(&g) < 1395) { return 20; } if (igraph_is_directed(&g)) { return 9; } igraph_is_loop(&g, &bs, igraph_ess_all(IGRAPH_EDGEORDER_ID)); if (igraph_vector_bool_sum(&bs) == 0) { return 10; } igraph_is_multiple(&g, &bs, igraph_ess_all(IGRAPH_EDGEORDER_ID)); if (igraph_vector_bool_sum(&bs)) { return 11; } igraph_destroy(&g); /* directed, loops */ IGRAPH_CHECK(igraph_preference_game(&g, 100, 3, &tdist, /*fixed_sizes=*/ 0, &pmat, 0, 1, 1)); if (igraph_vcount(&g) != 100) { return 15; } if (igraph_ecount(&g) < 2700) { return 19; } if (!igraph_is_directed(&g)) { return 12; } igraph_is_loop(&g, &bs, igraph_ess_all(IGRAPH_EDGEORDER_ID)); if (igraph_vector_bool_sum(&bs) == 0) { return 13; } igraph_is_multiple(&g, &bs, igraph_ess_all(IGRAPH_EDGEORDER_ID)); if (igraph_vector_bool_sum(&bs)) { return 14; } igraph_destroy(&g); /* Asymmetric preference game */ /* directed, no loops */ igraph_matrix_resize(&pmat, 2, 2); MATRIX(pmat, 0, 0) = 1; MATRIX(pmat, 0, 1) = 1; MATRIX(pmat, 1, 0) = 1; MATRIX(pmat, 1, 1) = 1; IGRAPH_CHECK(igraph_asymmetric_preference_game(&g, 100, 2, 0, &pmat, 0, 0, 0)); if (igraph_vcount(&g) != 100) { return 21; } if (igraph_ecount(&g) != 9900) { return 22; } if (!igraph_is_directed(&g)) { return 23; } igraph_is_loop(&g, &bs, igraph_ess_all(IGRAPH_EDGEORDER_ID)); if (igraph_vector_bool_sum(&bs)) { return 24; } igraph_is_multiple(&g, &bs, igraph_ess_all(IGRAPH_EDGEORDER_ID)); if (igraph_vector_bool_sum(&bs)) { return 25; } igraph_destroy(&g); /* directed, loops */ igraph_matrix_resize(&pmat, 2, 2); MATRIX(pmat, 0, 0) = 1; MATRIX(pmat, 0, 1) = 1; MATRIX(pmat, 1, 0) = 1; MATRIX(pmat, 1, 1) = 1; IGRAPH_CHECK(igraph_asymmetric_preference_game(&g, 100, 2, 0, &pmat, 0, 0, 1)); if (igraph_vcount(&g) != 100) { return 26; } if (igraph_ecount(&g) != 10000) { return 27; } if (!igraph_is_directed(&g)) { return 28; } igraph_is_loop(&g, &bs, igraph_ess_all(IGRAPH_EDGEORDER_ID)); if (igraph_vector_bool_sum(&bs) != 100) { return 29; } igraph_is_multiple(&g, &bs, igraph_ess_all(IGRAPH_EDGEORDER_ID)); if (igraph_vector_bool_sum(&bs)) { return 30; } igraph_destroy(&g); igraph_vector_destroy(&tdist); igraph_matrix_destroy(&pmat); igraph_vector_bool_destroy(&bs); assert(IGRAPH_FINALLY_STACK_EMPTY); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_simplify.out0000644000076500000240000000005013524616144027636 0ustar tamasstaff000000000000000 1 1 2 1 2 0 0 1 2 1 1 2 3 3 2 3 4 3 2 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_get_shortest_paths2.c0000644000076500000240000000601313612122633031406 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { const igraph_real_t edges[] = { 0, 1, 0, 2, 1, 6, 2, 6, 1, 3, 1, 4, 1, 5, 3, 2, 4, 2, 5, 2 }; igraph_t g; igraph_vector_t edgev; igraph_vector_ptr_t resvertices, resedges; igraph_vector_long_t predecessors, inbound_edges; int vcount, i; igraph_vector_view(&edgev, edges, sizeof(edges) / sizeof(igraph_real_t)); vcount = igraph_vector_max(&edgev) + 1; igraph_create(&g, &edgev, vcount, IGRAPH_DIRECTED); igraph_vector_ptr_init(&resvertices, vcount); igraph_vector_ptr_init(&resedges, vcount); igraph_vector_long_init(&predecessors, 0); igraph_vector_long_init(&inbound_edges, 0); for (i = 0; i < vcount; i++) { igraph_vector_t *v1 = malloc(sizeof(igraph_vector_t)); igraph_vector_t *v2 = malloc(sizeof(igraph_vector_t)); if (!v1 || !v2) { exit(2); } igraph_vector_init(v1, 0); igraph_vector_init(v2, 0); VECTOR(resvertices)[i] = v1; VECTOR(resedges)[i] = v2; } igraph_get_shortest_paths(&g, &resvertices, &resedges, /*from=*/ 0, /*to=*/ igraph_vss_all(), /*mode=*/ IGRAPH_OUT, &predecessors, &inbound_edges); for (i = 0; i < vcount; i++) { igraph_vector_t *v1 = VECTOR(resvertices)[i]; igraph_vector_t *v2 = VECTOR(resedges)[i]; printf("%i V: ", i); igraph_vector_print(v1); printf("%i E: ", i); igraph_vector_print(v2); } printf("pred: "); igraph_vector_long_print(&predecessors); printf("inbe: "); igraph_vector_long_print(&inbound_edges); igraph_vector_long_destroy(&inbound_edges); igraph_vector_long_destroy(&predecessors); for (i = 0; i < vcount; i++) { igraph_vector_t *v1 = VECTOR(resvertices)[i]; igraph_vector_t *v2 = VECTOR(resedges)[i]; igraph_vector_destroy(v1); igraph_vector_destroy(v2); igraph_free(v1); igraph_free(v2); } igraph_vector_ptr_destroy(&resedges); igraph_vector_ptr_destroy(&resvertices); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/cattributes2.c0000644000076500000240000000457613612122633026510 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void null_warning_handler (const char *reason, const char *file, int line, int igraph_errno) { } int main() { igraph_t g; igraph_vector_t y; igraph_warning_handler_t* oldwarnhandler; /* turn on attribute handling */ igraph_i_set_attribute_table(&igraph_cattribute_table); /* Create a graph, add some attributes and save it as a GraphML file */ igraph_famous(&g, "Petersen"); SETGAS(&g, "name", "Petersen's graph"); SETGAN(&g, "vertices", igraph_vcount(&g)); SETGAN(&g, "edges", igraph_ecount(&g)); SETGAB(&g, "famous", 1); igraph_vector_init_seq(&y, 1, igraph_vcount(&g)); SETVANV(&g, "id", &y); igraph_vector_destroy(&y); SETVAS(&g, "name", 0, "foo"); SETVAS(&g, "name", 1, "foobar"); SETVAB(&g, "is_first", 0, 1); igraph_vector_init_seq(&y, 1, igraph_ecount(&g)); SETEANV(&g, "id", &y); igraph_vector_destroy(&y); SETEAS(&g, "name", 0, "FOO"); SETEAS(&g, "name", 1, "FOOBAR"); SETEAB(&g, "is_first", 0, 1); /* Turn off the warning handler temporarily because the GML writer will * print warnings about boolean attributes being converted to numbers, and * we don't care about these */ oldwarnhandler = igraph_set_warning_handler(null_warning_handler); igraph_write_graph_gml(&g, stdout, 0, ""); igraph_set_warning_handler(oldwarnhandler); /* Back to business */ igraph_write_graph_graphml(&g, stdout, /*prefixattr=*/ 1); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_eccentricity.c0000644000076500000240000000305113614300625030100 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sts=4 sw=4 et: */ /* IGraph library. Copyright (C) 2011-12 Gabor Csardi 334 Harvard street, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_vector_t ecc; igraph_vector_init(&ecc, 0); igraph_star(&g, 10, IGRAPH_STAR_UNDIRECTED, 0); igraph_eccentricity(&g, &ecc, igraph_vss_all(), IGRAPH_OUT); igraph_vector_print(&ecc); igraph_destroy(&g); igraph_star(&g, 10, IGRAPH_STAR_OUT, 0); igraph_eccentricity(&g, &ecc, igraph_vss_all(), IGRAPH_ALL); igraph_vector_print(&ecc); igraph_destroy(&g); igraph_star(&g, 10, IGRAPH_STAR_OUT, 0); igraph_eccentricity(&g, &ecc, igraph_vss_all(), IGRAPH_OUT); igraph_vector_print(&ecc); igraph_destroy(&g); igraph_vector_destroy(&ecc); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_is_directed.c0000644000076500000240000000221713612122633027673 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_empty(&g, 0, 0); if (igraph_is_directed(&g)) { return 1; } igraph_destroy(&g); igraph_empty(&g, 0, 1); if (!igraph_is_directed(&g)) { return 2; } igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_reciprocity.c0000644000076500000240000000340213612122633027746 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int main() { igraph_t g; igraph_real_t res; /* Trivial cases */ igraph_ring(&g, 100, IGRAPH_UNDIRECTED, 0, 0); igraph_reciprocity(&g, &res, 0, IGRAPH_RECIPROCITY_DEFAULT); igraph_destroy(&g); if (res != 1) { return 1; } /* Small test graph */ igraph_small(&g, 0, IGRAPH_DIRECTED, 0, 1, 0, 2, 0, 3, 1, 0, 2, 3, 3, 2, -1); igraph_reciprocity(&g, &res, 0, IGRAPH_RECIPROCITY_RATIO); igraph_destroy(&g); if (res != 0.5) { fprintf(stderr, "%f != %f\n", res, 0.5); return 2; } igraph_small(&g, 0, IGRAPH_DIRECTED, 0, 1, 1, 2, 2, 1, -1); igraph_reciprocity(&g, &res, 0, IGRAPH_RECIPROCITY_DEFAULT); igraph_destroy(&g); if (fabs(res - 2.0 / 3.0) > 1e-15) { fprintf(stderr, "%f != %f\n", res, 2.0 / 3.0); return 3; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_get_eids.c0000644000076500000240000001621313612122633027201 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2008-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include void print_vector(igraph_vector_t *v, FILE *f) { long int i; for (i = 0; i < igraph_vector_size(v); i++) { fprintf(f, " %li", (long int) VECTOR(*v)[i]); } fprintf(f, "\n"); } int check_simple() { igraph_t g; long int nodes = 100; long int edges = 1000; igraph_real_t p = 3.0 / nodes; long int runs = 10; long int r, e, ecount; igraph_vector_t eids, pairs, path; srand(time(0)); igraph_vector_init(&pairs, edges * 2); igraph_vector_init(&path, 0); igraph_vector_init(&eids, 0); for (r = 0; r < runs; r++) { igraph_erdos_renyi_game(&g, IGRAPH_ERDOS_RENYI_GNP, nodes, p, /*directed=*/ 0, /*loops=*/ 0); ecount = igraph_ecount(&g); for (e = 0; e < edges; e++) { long int edge = RNG_INTEGER(0, ecount - 1); VECTOR(pairs)[2 * e] = IGRAPH_FROM(&g, edge); VECTOR(pairs)[2 * e + 1] = IGRAPH_TO(&g, edge); } igraph_get_eids(&g, &eids, &pairs, /*path=*/ 0, 0, /*error=*/ 1); for (e = 0; e < edges; e++) { long int edge = VECTOR(eids)[e]; long int from1 = VECTOR(pairs)[2 * e]; long int to1 = VECTOR(pairs)[2 * e + 1]; long int from2 = IGRAPH_FROM(&g, edge); long int to2 = IGRAPH_TO(&g, edge); long int min1 = from1 < to1 ? from1 : to1; long int max1 = from1 < to1 ? to1 : from1; long int min2 = from2 < to2 ? from2 : to2; long int max2 = from2 < to2 ? to2 : from2; if (min1 != min2 || max1 != max2) { return 11; } } igraph_diameter(&g, /*res=*/ 0, /*from=*/ 0, /*to=*/ 0, &path, IGRAPH_UNDIRECTED, /*unconn=*/ 1); igraph_get_eids(&g, &eids, /*pairs=*/ 0, &path, 0, /*error=*/ 1); for (e = 0; e < igraph_vector_size(&path) - 1; e++) { long int edge = VECTOR(eids)[e]; long int from1 = VECTOR(path)[e]; long int to1 = VECTOR(path)[e + 1]; long int from2 = IGRAPH_FROM(&g, edge); long int to2 = IGRAPH_TO(&g, edge); long int min1 = from1 < to1 ? from1 : to1; long int max1 = from1 < to1 ? to1 : from1; long int min2 = from2 < to2 ? from2 : to2; long int max2 = from2 < to2 ? to2 : from2; if (min1 != min2 || max1 != max2) { return 12; } } igraph_destroy(&g); } igraph_vector_destroy(&path); igraph_vector_destroy(&pairs); igraph_vector_destroy(&eids); return 0; } int check_multi() { igraph_t g; igraph_vector_t vec; igraph_vector_t eids, eids2; int ret; long int i; igraph_real_t q1[] = { 0, 1, 0, 1 }; igraph_real_t q2[] = { 0, 1, 0, 1, 0, 1 }; igraph_real_t q3[] = { 1, 0, 3, 4, 1, 0, 0, 1, 3, 4, 0, 1 }; igraph_vector_init(&eids, 0); /*********************************/ igraph_small(&g, /*n=*/ 10, /*directed=*/ 1, 0, 1, 0, 1, 1, 0, 1, 2, 3, 4, 3, 4, 3, 4, 3, 5, 3, 7, 9, 8, -1); igraph_vector_view(&vec, q1, sizeof(q1) / sizeof(igraph_real_t)); igraph_get_eids_multi(&g, &eids, &vec, 0, /*directed=*/ 1, /*error=*/ 1); igraph_vector_sort(&eids); print_vector(&eids, stdout); igraph_vector_view(&vec, q2, sizeof(q2) / sizeof(igraph_real_t)); igraph_get_eids_multi(&g, &eids, &vec, 0, /*directed=*/ 0, /*error=*/ 1); igraph_vector_sort(&eids); print_vector(&eids, stdout); igraph_vector_view(&vec, q2, sizeof(q2) / sizeof(igraph_real_t)); igraph_set_error_handler(igraph_error_handler_ignore); ret = igraph_get_eids_multi(&g, &eids, &vec, 0, /*directed=*/ 1, /*error=*/1); if (ret != IGRAPH_EINVAL) { return 1; } igraph_set_error_handler(igraph_error_handler_abort); igraph_destroy(&g); /*********************************/ /*********************************/ igraph_small(&g, /*n=*/10, /*directed=*/0, 0, 1, 1, 0, 0, 1, 3, 4, 3, 4, 5, 4, 9, 8, -1); igraph_vector_view(&vec, q1, sizeof(q1) / sizeof(igraph_real_t)); igraph_get_eids_multi(&g, &eids, &vec, 0, /*directed=*/1, /*error=*/ 1); igraph_vector_sort(&eids); print_vector(&eids, stdout); igraph_vector_view(&vec, q3, sizeof(q3) / sizeof(igraph_real_t)); igraph_set_error_handler(igraph_error_handler_ignore); ret = igraph_get_eids_multi(&g, &eids, &vec, 0, /*directed=*/0, /*error=*/ 1); if (ret != IGRAPH_EINVAL) { return 2; } igraph_set_error_handler(igraph_error_handler_abort); igraph_destroy(&g); /*********************************/ igraph_vector_destroy(&eids); /*********************************/ /* Speed tests */ #define NODES 10000 igraph_barabasi_game(&g, /*n=*/ NODES, /*power=*/ 1.0, /*m=*/ 3, /*outseq=*/ 0, /*outpref=*/ 0, /*A=*/ 1, /*directed=*/ 1, IGRAPH_BARABASI_BAG, /*start_from=*/ 0); igraph_simplify(&g, /*multiple=*/ 1, /*loops=*/ 0, /*edge_comb=*/ 0); igraph_vector_init(&eids, NODES / 2); igraph_random_sample(&eids, 0, igraph_ecount(&g) - 1, NODES / 2); igraph_vector_init(&vec, NODES); for (i = 0; i < NODES / 2; i++) { VECTOR(vec)[2 * i] = IGRAPH_FROM(&g, VECTOR(eids)[i]); VECTOR(vec)[2 * i + 1] = IGRAPH_TO(&g, VECTOR(eids)[i]); } igraph_vector_init(&eids2, 0); igraph_get_eids_multi(&g, &eids2, &vec, 0, /*directed=*/ 1, /*error=*/ 1); if (!igraph_vector_all_e(&eids, &eids2)) { return 3; } /**/ for (i = 0; i < NODES / 2; i++) { VECTOR(vec)[2 * i] = IGRAPH_TO(&g, VECTOR(eids)[i]); VECTOR(vec)[2 * i + 1] = IGRAPH_FROM(&g, VECTOR(eids)[i]); } igraph_get_eids_multi(&g, &eids2, &vec, 0, /*directed=*/ 0, /*error=*/ 1); if (!igraph_vector_all_e(&eids, &eids2)) { return 4; } igraph_vector_destroy(&eids); igraph_vector_destroy(&eids2); igraph_vector_destroy(&vec); igraph_destroy(&g); /*********************************/ return 0; } int main() { int ret; if ( (ret = check_simple()) != 0) { return ret; } if ( (ret = check_multi()) != 0) { return ret; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_similarity.out0000644000076500000240000000157013524616144030200 0ustar tamasstaff00000000000000 1.00 0.75 0.75 0.50 0.75 1.00 1.00 0.25 0.75 1.00 1.00 0.25 0.50 0.25 0.25 1.00 ========== 1.00 0.33 0.33 1.00 ========== 1.00 0.50 0.67 0.33 0.50 1.00 0.33 0.00 0.67 0.33 1.00 0.25 0.33 0.00 0.25 1.00 ========== 1.00 0.33 0.00 0.00 0.33 1.00 0.00 0.00 0.00 0.00 1.00 0.00 0.00 0.00 0.00 1.00 ========== 1.00 0.86 0.86 0.67 0.86 1.00 1.00 0.40 0.86 1.00 1.00 0.40 0.67 0.40 0.40 1.00 ========== 1.00 0.67 0.80 0.50 0.67 1.00 0.50 0.00 0.80 0.50 1.00 0.40 0.50 0.00 0.40 1.00 ========== 1.00 0.50 0.00 0.00 0.50 1.00 0.00 0.00 0.00 0.00 1.00 0.00 0.00 0.00 0.00 1.00 ========== 0.00 1.44 1.44 0.00 1.44 0.00 0.91 0.91 1.44 0.91 0.00 0.91 0.00 0.91 0.91 0.00 ========== 0.00 0.00 1.44 0.00 0.00 0.00 0.00 0.00 1.44 0.00 0.00 1.44 0.00 0.00 1.44 0.00 ========== 0.00 1.44 0.00 0.00 1.44 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 ========== python-igraph-0.8.0/vendor/source/igraph/examples/simple/eigenvector_centrality.out0000644000076500000240000000127713524616144031234 0ustar tamasstaff00000000000000 0.707 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 0.071 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_sparsemat3.out0000644000076500000240000000000013524616144030057 0ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_eigen_matrix2.c0000644000076500000240000000727413612122633030162 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #define DUMP() do { \ igraph_vector_complex_print(&values); \ igraph_vector_complex_print(&values2); \ } while(0) int main() { const int nodes = 10; igraph_matrix_t mat2; igraph_vector_complex_t values, values2; igraph_matrix_complex_t vectors, vectors2; igraph_eigen_which_t which; int i; igraph_rng_seed(igraph_rng_default(), 42); igraph_matrix_init(&mat2, nodes, nodes); for (i = 0; i < nodes; i++) { int j; for (j = 0; j < nodes; j++) { MATRIX(mat2, i, j) = igraph_rng_get_integer(igraph_rng_default(), 1, 10); } } /* Test LR, a single eigenvalue first */ igraph_vector_complex_init(&values, 0); igraph_matrix_complex_init(&vectors, 0, 0); which.pos = IGRAPH_EIGEN_LR; which.howmany = 1; igraph_eigen_matrix(&mat2, /*sparsemat=*/ 0, /*fun=*/ 0, nodes, /*extra=*/ 0, IGRAPH_EIGEN_LAPACK, &which, /*options=*/ 0, /*storage=*/ 0, &values, &vectors); igraph_vector_complex_print(&values); igraph_matrix_complex_print(&vectors); igraph_vector_complex_destroy(&values); igraph_matrix_complex_destroy(&vectors); /* LR, and SR, all eigenvalues */ igraph_vector_complex_init(&values, 0); igraph_matrix_complex_init(&vectors, 0, 0); which.pos = IGRAPH_EIGEN_LR; which.howmany = nodes; igraph_eigen_matrix(&mat2, /*sparsemat=*/ 0, /*fun=*/ 0, nodes, /*extra=*/ 0, IGRAPH_EIGEN_LAPACK, &which, /*options=*/ 0, /*storage=*/ 0, &values, &vectors); igraph_vector_complex_init(&values2, 0); igraph_matrix_complex_init(&vectors2, 0, 0); which.pos = IGRAPH_EIGEN_SR; which.howmany = nodes; igraph_eigen_matrix(&mat2, /*sparsemat=*/ 0, /*fun=*/ 0, nodes, /*extra=*/ 0, IGRAPH_EIGEN_LAPACK, &which, /*options=*/ 0, /*storage=*/ 0, &values2, &vectors2); for (i = 0; i < nodes; i++) { int j; igraph_real_t d = igraph_complex_abs(igraph_complex_sub(VECTOR(values)[i], VECTOR(values2)[nodes - i - 1])); if (d > 1e-15) { DUMP(); return 2; } for (j = 0; j < nodes; j++) { igraph_real_t d = igraph_complex_abs(igraph_complex_sub(MATRIX(vectors, j, i), MATRIX(vectors2, j, nodes - i - 1))); if (d > 1e-15) { DUMP(); return 3; } } } igraph_vector_complex_destroy(&values); igraph_matrix_complex_destroy(&vectors); igraph_vector_complex_destroy(&values2); igraph_matrix_complex_destroy(&vectors2); igraph_matrix_destroy(&mat2); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_set.c0000644000076500000240000000420613612122633026210 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include "igraph_types_internal.h" #include void print_set(igraph_set_t *set, FILE *f) { long int state = 0; igraph_integer_t element; while (igraph_set_iterate(set, &state, &element)) { fprintf(f, " %li", (long int) element); } fprintf(f, "\n"); } int main() { igraph_set_t set; int i; /* simple init */ igraph_set_init(&set, 0); igraph_set_destroy(&set); /* addition, igraph_set_size */ igraph_set_init(&set, 10); i = 10; while (igraph_set_size(&set) < 10) { igraph_set_add(&set, 2 * i); i--; } while (igraph_set_size(&set) < 21) { igraph_set_add(&set, 2 * i + 1); i++; } print_set(&set, stdout); /* adding existing element */ igraph_set_add(&set, 8); if (igraph_set_size(&set) != 21) { return 4; } /* igraph_set_contains */ if (igraph_set_contains(&set, 42) || !igraph_set_contains(&set, 7)) { return 3; } /* igraph_set_empty, igraph_set_clear */ if (igraph_set_empty(&set)) { return 1; } igraph_set_clear(&set); if (!igraph_set_empty(&set)) { return 2; } igraph_set_destroy(&set); if (!IGRAPH_FINALLY_STACK_EMPTY) { return 5; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/karate.gml0000644000076500000240000001014213524616144025672 0ustar tamasstaff00000000000000Creator "Mark Newman on Fri Jul 21 12:39:27 2006" graph [ node [ id 1 ] node [ id 2 ] node [ id 3 ] node [ id 4 ] node [ id 5 ] node [ id 6 ] node [ id 7 ] node [ id 8 ] node [ id 9 ] node [ id 10 ] node [ id 11 ] node [ id 12 ] node [ id 13 ] node [ id 14 ] node [ id 15 ] node [ id 16 ] node [ id 17 ] node [ id 18 ] node [ id 19 ] node [ id 20 ] node [ id 21 ] node [ id 22 ] node [ id 23 ] node [ id 24 ] node [ id 25 ] node [ id 26 ] node [ id 27 ] node [ id 28 ] node [ id 29 ] node [ id 30 ] node [ id 31 ] node [ id 32 ] node [ id 33 ] node [ id 34 ] edge [ source 2 target 1 ] edge [ source 3 target 1 ] edge [ source 3 target 2 ] edge [ source 4 target 1 ] edge [ source 4 target 2 ] edge [ source 4 target 3 ] edge [ source 5 target 1 ] edge [ source 6 target 1 ] edge [ source 7 target 1 ] edge [ source 7 target 5 ] edge [ source 7 target 6 ] edge [ source 8 target 1 ] edge [ source 8 target 2 ] edge [ source 8 target 3 ] edge [ source 8 target 4 ] edge [ source 9 target 1 ] edge [ source 9 target 3 ] edge [ source 10 target 3 ] edge [ source 11 target 1 ] edge [ source 11 target 5 ] edge [ source 11 target 6 ] edge [ source 12 target 1 ] edge [ source 13 target 1 ] edge [ source 13 target 4 ] edge [ source 14 target 1 ] edge [ source 14 target 2 ] edge [ source 14 target 3 ] edge [ source 14 target 4 ] edge [ source 17 target 6 ] edge [ source 17 target 7 ] edge [ source 18 target 1 ] edge [ source 18 target 2 ] edge [ source 20 target 1 ] edge [ source 20 target 2 ] edge [ source 22 target 1 ] edge [ source 22 target 2 ] edge [ source 26 target 24 ] edge [ source 26 target 25 ] edge [ source 28 target 3 ] edge [ source 28 target 24 ] edge [ source 28 target 25 ] edge [ source 29 target 3 ] edge [ source 30 target 24 ] edge [ source 30 target 27 ] edge [ source 31 target 2 ] edge [ source 31 target 9 ] edge [ source 32 target 1 ] edge [ source 32 target 25 ] edge [ source 32 target 26 ] edge [ source 32 target 29 ] edge [ source 33 target 3 ] edge [ source 33 target 9 ] edge [ source 33 target 15 ] edge [ source 33 target 16 ] edge [ source 33 target 19 ] edge [ source 33 target 21 ] edge [ source 33 target 23 ] edge [ source 33 target 24 ] edge [ source 33 target 30 ] edge [ source 33 target 31 ] edge [ source 33 target 32 ] edge [ source 34 target 9 ] edge [ source 34 target 10 ] edge [ source 34 target 14 ] edge [ source 34 target 15 ] edge [ source 34 target 16 ] edge [ source 34 target 19 ] edge [ source 34 target 20 ] edge [ source 34 target 21 ] edge [ source 34 target 23 ] edge [ source 34 target 24 ] edge [ source 34 target 27 ] edge [ source 34 target 28 ] edge [ source 34 target 29 ] edge [ source 34 target 30 ] edge [ source 34 target 31 ] edge [ source 34 target 32 ] edge [ source 34 target 33 ] ] python-igraph-0.8.0/vendor/source/igraph/examples/simple/pajek_signed.net0000644000076500000240000000055413524616144027063 0ustar tamasstaff00000000000000*NETWORK First.net; 14.04.2009 / 09:46:56 *Vertices 10 1 "S65" 2 "S29" 3 "S04" 4 "S75" 5 "S24" 6 "S81" 7 "S51" 8 "S78" 9 "S86" 10 "S39" *Matrix 0 0 0 0 0 1 0 0 0 -1 0 0 1 1 0 1 1 0 1 0 -1 0 0 1 0 0 1 0 1 0 -1 1 0 0 1 1 1 0 1 0 0 1 0 1 0 0 0 0 -1 -1 1 -1 0 0 0 0 0 1 0 0 0 -1 1 1 0 -1 0 0 1 0 0 0 1 1 0 1 -1 0 1 1 0 0 0 0 0 0 0 0 0 -1 1 1 1 1 1 1 1 1 1 0 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_arpack_rnsolve.out0000644000076500000240000000040013524616144031012 0ustar tamasstaff00000000000000-6 0 10 3 8 1 -4 10 -8 0 -6 1 0 8 -4 4 -7 1 1 6 7 -7 8 6 -4 -8 -1 -7 -3 -7 6 8 -4 -1 10 3 7 7 -3 -8 1 -7 -4 9 0 5 5 6 -8 10 -9 10 -5 -9 5 3 -5 7 -7 10 -3 0 8 -6 -2 -7 1 -3 -8 1 2 0 9 -3 0 -9 -4 0 10 0 -9 1 -6 -1 7 10 9 9 8 -2 -7 1 9 -7 10 -1 -2 -5 7 6 === python-igraph-0.8.0/vendor/source/igraph/examples/simple/watts_strogatz_game.c0000644000076500000240000000754213612122634030162 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph R library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard street, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #define N 1000 igraph_bool_t has_loops(const igraph_t *graph) { int i, n = igraph_ecount(graph); for (i = 0; i < n; i++) { if (IGRAPH_FROM(graph, i) == IGRAPH_TO(graph, i)) { return 1; } } return 0; } igraph_bool_t has_multiple(const igraph_t *graph) { igraph_bool_t res; igraph_has_multiple(graph, &res); return res; } #define ERR() do { \ printf("Seed: %d\n", seed); \ igraph_write_graph_edgelist(&ws, stdout); \ } while (0) #define SEED() do { \ seed=igraph_rng_get_integer(igraph_rng_default(), 1, 10000); \ igraph_rng_seed(igraph_rng_default(), seed); \ } while (0) int main() { igraph_t ws; igraph_bool_t sim, seen_loops, seen_multiple; int i, seed = 1305473657; igraph_rng_seed(igraph_rng_default(), seed); /* No loops, no multiple edges */ for (i = 0; i < N; i++) { SEED(); igraph_watts_strogatz_game(&ws, /*dim=*/ 1, /*size=*/ 5, /*nei=*/ 1, /*p=*/ 0.5, /*loops=*/ 0, /*multiple=*/ 0); igraph_is_simple(&ws, &sim); if (!sim) { ERR(); return 1; } if (has_loops(&ws)) { ERR(); return 1; } if (has_multiple(&ws)) { ERR(); return 2; } igraph_destroy(&ws); } /* No loops, multiple edges possible */ seen_multiple = 0; for (i = 0; i < N; i++) { SEED(); igraph_watts_strogatz_game(&ws, /*dim=*/ 1, /*size=*/ 5, /*nei=*/ 1, /*p=*/ 0.5, /*loops=*/ 0, /*multiple=*/ 1); if (has_loops(&ws)) { ERR(); return 3; } seen_multiple = seen_multiple || has_multiple(&ws); igraph_destroy(&ws); } /* This might actually happen */ /* if (!seen_multiple) { return 4; } */ /* Loops possible, no multiple edges */ seen_loops = 0; for (i = 0; i < N; i++) { SEED(); igraph_watts_strogatz_game(&ws, /*dim=*/ 1, /*size=*/ 5, /*nei=*/ 1, /*p=*/ 0.5, /*loops=*/ 1, /*multiple=*/ 0); if (has_multiple(&ws)) { return 5; } seen_loops = seen_loops || has_loops(&ws); igraph_destroy(&ws); } /* This might actually happen */ /* if (!seen_loops) { return 6; } */ /* Both loops and multiple edges are possible */ for (i = 0; i < N; i++) { SEED(); igraph_watts_strogatz_game(&ws, /*dim=*/ 1, /*size=*/ 5, /*nei=*/ 1, /*p=*/ 0.5, /*loops=*/ 1, /*multiple=*/ 1); seen_loops = seen_loops || has_loops(&ws); seen_multiple = seen_multiple || has_multiple(&ws); igraph_destroy(&ws); } /* This might actually happen */ /* if (!seen_loops) { return 7; } */ /* if (!seen_multiple) { return 8; } */ return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/vector2.out0000644000076500000240000000037713524616144026050 0ustar tamasstaff00000000000000 0 1 2 3 4 5 6 7 8 9 1 2 3 4 5 6 7 8 9 10 9 1 2 6 4 5 3 7 8 0 10 9 8 7 6 5 4 3 2 1 1 2 3 4 5 6 7 8 9 10 6 6 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 4 4 2 2 2 2 2 2 2 2 2 2 4 4 4 4 4 4 4 4 4 4 4 4 0 0 1 10 0 9 1 10 9 0 3 6 6 9 5 7 8 8 10 1 12 15 17 20 python-igraph-0.8.0/vendor/source/igraph/examples/simple/scg.out0000644000076500000240000000714613524616144025241 0ustar tamasstaff00000000000000------------------------------------ 0 1 0 2 1 3 --- 0 1 1 2 3 3 3 3 3 3 --- 2.33441 -0.5 -0.47651 -0.47651 -0.214186 -0.204124 -0.204124 -0.204124 -0.204124 -0.204124 -0.204124 --- col 0: locations 0 to 1 1 : 1.41421 2 : 1 col 1: locations 2 to 3 0 : 1.41421 3 : 1.73205 col 2: locations 4 to 4 0 : 1 col 3: locations 5 to 5 1 : 1.73205 --- 0 0 : 1 1 1 : 0.707107 1 2 : 0.707107 2 3 : 1 3 4 : 0.408248 3 5 : 0.408248 3 6 : 0.408248 3 7 : 0.408248 3 8 : 0.408248 3 9 : 0.408248 --- 0 0 : 1 1 1 : 0.707107 1 2 : 0.707107 2 3 : 1 3 4 : 0.408248 3 5 : 0.408248 3 6 : 0.408248 3 7 : 0.408248 3 8 : 0.408248 3 9 : 0.408248 --- ------------------------------------ 0 1 0 2 1 3 --- 0 1 1 2 3 3 3 3 3 3 --- 0.741964 0.5 -0.151453 -0.151453 0.673887 -0.204124 -0.204124 -0.204124 -0.204124 -0.204124 -0.204124 --- col 0: locations 0 to 1 1 : 1.41421 2 : 1 col 1: locations 2 to 3 0 : 1.41421 3 : 1.73205 col 2: locations 4 to 4 0 : 1 col 3: locations 5 to 5 1 : 1.73205 --- 0 0 : 1 1 1 : 0.707107 1 2 : 0.707107 2 3 : 1 3 4 : 0.408248 3 5 : 0.408248 3 6 : 0.408248 3 7 : 0.408248 3 8 : 0.408248 3 9 : 0.408248 --- 0 0 : 1 1 1 : 0.707107 1 2 : 0.707107 2 3 : 1 3 4 : 0.408248 3 5 : 0.408248 3 6 : 0.408248 3 7 : 0.408248 3 8 : 0.408248 3 9 : 0.408248 --- ------------------------------------ 0 1 0 2 1 3 --- 0 1 1 2 3 3 3 3 3 3 --- 2.33441 0.741964 -0.5 0.5 -0.47651 -0.151453 -0.47651 -0.151453 -0.214186 0.673887 -0.204124 -0.204124 -0.204124 -0.204124 -0.204124 -0.204124 -0.204124 -0.204124 -0.204124 -0.204124 -0.204124 -0.204124 --- col 0: locations 0 to 1 1 : 1.41421 2 : 1 col 1: locations 2 to 3 0 : 1.41421 3 : 1.73205 col 2: locations 4 to 4 0 : 1 col 3: locations 5 to 5 1 : 1.73205 --- 0 0 : 1 1 1 : 0.707107 1 2 : 0.707107 2 3 : 1 3 4 : 0.408248 3 5 : 0.408248 3 6 : 0.408248 3 7 : 0.408248 3 8 : 0.408248 3 9 : 0.408248 --- 0 0 : 1 1 1 : 0.707107 1 2 : 0.707107 2 3 : 1 3 4 : 0.408248 3 5 : 0.408248 3 6 : 0.408248 3 7 : 0.408248 3 8 : 0.408248 3 9 : 0.408248 --- ------------------------------------ 0 1 0 2 1 3 --- 0 1 1 2 3 3 3 3 3 3 --- 2.33441 -0.5 -0.47651 -0.47651 -0.214186 -0.204124 -0.204124 -0.204124 -0.204124 -0.204124 -0.204124 --- 0 1 : 1.41421 0 2 : 1 1 0 : 1.41421 1 3 : 1.73205 2 0 : 1 3 1 : 1.73205 --- 0 0 : 1 1 1 : 0.707107 1 2 : 0.707107 2 3 : 1 3 4 : 0.408248 3 5 : 0.408248 3 6 : 0.408248 3 7 : 0.408248 3 8 : 0.408248 3 9 : 0.408248 --- 0 0 : 1 1 1 : 0.707107 1 2 : 0.707107 2 3 : 1 3 4 : 0.408248 3 5 : 0.408248 3 6 : 0.408248 3 7 : 0.408248 3 8 : 0.408248 3 9 : 0.408248 --- ------------------------------------ 0 1 0 2 1 3 --- 0 1 1 2 3 3 3 3 3 3 --- 0.741964 0.5 -0.151453 -0.151453 0.673887 -0.204124 -0.204124 -0.204124 -0.204124 -0.204124 -0.204124 --- 0 1 : 1.41421 0 2 : 1 1 0 : 1.41421 1 3 : 1.73205 2 0 : 1 3 1 : 1.73205 --- 0 0 : 1 1 1 : 0.707107 1 2 : 0.707107 2 3 : 1 3 4 : 0.408248 3 5 : 0.408248 3 6 : 0.408248 3 7 : 0.408248 3 8 : 0.408248 3 9 : 0.408248 --- 0 0 : 1 1 1 : 0.707107 1 2 : 0.707107 2 3 : 1 3 4 : 0.408248 3 5 : 0.408248 3 6 : 0.408248 3 7 : 0.408248 3 8 : 0.408248 3 9 : 0.408248 --- ------------------------------------ 0 1 0 2 1 3 --- 0 1 1 2 3 3 3 3 3 3 --- 2.33441 0.741964 -0.5 0.5 -0.47651 -0.151453 -0.47651 -0.151453 -0.214186 0.673887 -0.204124 -0.204124 -0.204124 -0.204124 -0.204124 -0.204124 -0.204124 -0.204124 -0.204124 -0.204124 -0.204124 -0.204124 --- 0 1 : 1.41421 0 2 : 1 1 0 : 1.41421 1 3 : 1.73205 2 0 : 1 3 1 : 1.73205 --- 0 0 : 1 1 1 : 0.707107 1 2 : 0.707107 2 3 : 1 3 4 : 0.408248 3 5 : 0.408248 3 6 : 0.408248 3 7 : 0.408248 3 8 : 0.408248 3 9 : 0.408248 --- 0 0 : 1 1 1 : 0.707107 1 2 : 0.707107 2 3 : 1 3 4 : 0.408248 3 5 : 0.408248 3 6 : 0.408248 3 7 : 0.408248 3 8 : 0.408248 3 9 : 0.408248 --- python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_adjacency_spectral_embedding.out0000644000076500000240000000132313524616144033622 0ustar tamasstaff00000000000000 -0.5877 0.0000 0.7948 0.0000 -0.5689 0.7015 -0.4032 0.0000 -0.5689 -0.7015 -0.4032 0.0000 -0.0330 0.0000 0.1302 0.0000 -0.0320 0.0511 -0.0660 0.1236 -0.0320 0.0511 -0.0660 0.5430 -0.0320 0.0511 -0.0660 -0.6667 -0.0320 -0.0511 -0.0660 0.1819 -0.0320 -0.0511 -0.0660 -0.4038 -0.0320 -0.0511 -0.0660 0.2219 -- -0.2914 0.0000 0.6560 0.0000 -0.5705 0.5262 -0.0063 0.0000 -0.5705 -0.5262 -0.0063 0.0000 -0.1997 0.0000 0.4732 0.0000 -0.1934 0.2727 -0.2400 0.1236 -0.1934 0.2727 -0.2400 0.5430 -0.1934 0.2727 -0.2400 -0.6667 -0.1934 -0.2727 -0.2400 0.1819 -0.1934 -0.2727 -0.2400 -0.4038 -0.1934 -0.2727 -0.2400 0.2219 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_maximum_bipartite_matching.c0000644000076500000240000002340613614300625033013 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int test_graph_from_leda_tutorial() { /* Test graph from the LEDA tutorial: * http://www.leda-tutorial.org/en/unofficial/ch05s03s05.html */ igraph_t graph; igraph_vector_bool_t types; igraph_vector_long_t matching; igraph_integer_t matching_size; igraph_real_t matching_weight; igraph_bool_t is_matching; int i; igraph_small(&graph, 0, 0, 0, 8, 0, 12, 0, 14, 1, 9, 1, 10, 1, 13, 2, 8, 2, 9, 3, 10, 3, 11, 3, 13, 4, 9, 4, 14, 5, 14, 6, 9, 6, 14, 7, 8, 7, 12, 7, 14 , -1); igraph_vector_bool_init(&types, 15); for (i = 0; i < 15; i++) { VECTOR(types)[i] = (i >= 8); } igraph_vector_long_init(&matching, 0); igraph_maximum_bipartite_matching(&graph, &types, &matching_size, &matching_weight, &matching, 0, 0); if (matching_size != 6) { printf("matching_size is %ld, expected: 6\n", (long)matching_size); return 1; } if (matching_weight != 6) { printf("matching_weight is %ld, expected: 6\n", (long)matching_weight); return 2; } igraph_is_maximal_matching(&graph, &types, &matching, &is_matching); if (!is_matching) { printf("not a matching: "); igraph_vector_long_print(&matching); return 3; } igraph_vector_long_destroy(&matching); igraph_vector_bool_destroy(&types); igraph_destroy(&graph); return 0; } int test_weighted_graph_from_mit_notes() { /* Test graph from the following lecture notes: * http://math.mit.edu/~goemans/18433S07/matching-notes.pdf */ igraph_t graph; igraph_vector_bool_t types; igraph_vector_long_t matching; igraph_vector_t weights; igraph_integer_t matching_size; igraph_real_t matching_weight; igraph_bool_t is_matching; igraph_real_t weight_array[] = { 2, 7, 2, 3, 1, 3, 9, 3, 3, 1, 3, 3, 1, 2, 4, 1, 2, 3 }; int i; igraph_small(&graph, 0, 0, 0, 6, 0, 7, 0, 8, 0, 9, 1, 5, 1, 6, 1, 7, 1, 8, 1, 9, 2, 5, 2, 6, 2, 7, 2, 8, 2, 9, 3, 5, 3, 7, 3, 9, 4, 7, -1); igraph_vector_bool_init(&types, 10); for (i = 0; i < 10; i++) { VECTOR(types)[i] = (i >= 5); } igraph_vector_long_init(&matching, 0); igraph_vector_init_copy(&weights, weight_array, sizeof(weight_array) / sizeof(weight_array[0])); igraph_maximum_bipartite_matching(&graph, &types, &matching_size, &matching_weight, &matching, &weights, 0); if (matching_size != 4) { printf("matching_size is %ld, expected: 4\n", (long)matching_size); return 1; } if (matching_weight != 19) { printf("matching_weight is %ld, expected: 19\n", (long)matching_weight); return 2; } igraph_is_maximal_matching(&graph, &types, &matching, &is_matching); if (!is_matching) { printf("not a matching: "); igraph_vector_long_print(&matching); return 3; } igraph_vector_destroy(&weights); igraph_vector_long_destroy(&matching); igraph_vector_bool_destroy(&types); igraph_destroy(&graph); return 0; } int test_weighted_graph_generated() { /* Several randomly generated small test graphs */ igraph_t graph; igraph_vector_bool_t types; igraph_vector_long_t matching; igraph_vector_t weights; igraph_integer_t matching_size; igraph_real_t matching_weight; igraph_real_t weight_array_1[] = { 8, 5, 9, 18, 20, 13 }; igraph_real_t weight_array_2[] = { 20, 4, 20, 3, 13, 1 }; int i; igraph_vector_bool_init(&types, 10); for (i = 0; i < 10; i++) { VECTOR(types)[i] = (i >= 5); } igraph_vector_long_init(&matching, 0); /* Case 1 */ igraph_small(&graph, 0, 0, 0, 8, 2, 7, 3, 7, 3, 8, 4, 5, 4, 9, -1); igraph_vector_init_copy(&weights, weight_array_1, sizeof(weight_array_1) / sizeof(weight_array_1[0])); igraph_maximum_bipartite_matching(&graph, &types, &matching_size, &matching_weight, &matching, &weights, 0); if (matching_weight != 43) { printf("matching_weight is %ld, expected: 43\n", (long)matching_weight); return 2; } igraph_vector_destroy(&weights); igraph_destroy(&graph); /* Case 2 */ igraph_small(&graph, 0, 0, 0, 5, 0, 6, 1, 7, 2, 5, 3, 5, 3, 9, -1); igraph_vector_init_copy(&weights, weight_array_2, sizeof(weight_array_2) / sizeof(weight_array_2[0])); igraph_maximum_bipartite_matching(&graph, &types, &matching_size, &matching_weight, &matching, &weights, 0); if (matching_weight != 41) { printf("matching_weight is %ld, expected: 41\n", (long)matching_weight); return 2; } igraph_vector_destroy(&weights); igraph_destroy(&graph); igraph_vector_long_destroy(&matching); igraph_vector_bool_destroy(&types); return 0; } int test_weighted_graph_from_file(const char* fname, int type1_count, long exp_weight) { igraph_t graph; igraph_vector_bool_t types; igraph_vector_long_t matching; igraph_vector_t weights; igraph_real_t matching_weight; FILE* f; int i, n; f = fopen(fname, "r"); if (!f) { fprintf(stderr, "No such file: %s\n", fname); return 1; } igraph_read_graph_ncol(&graph, f, 0, 1, 1, 0); fclose(f); n = igraph_vcount(&graph); igraph_vector_bool_init(&types, n); for (i = 0; i < n; i++) { VECTOR(types)[i] = (i >= type1_count); } igraph_vector_long_init(&matching, 0); igraph_vector_init(&weights, 0); EANV(&graph, "weight", &weights); igraph_maximum_bipartite_matching(&graph, &types, 0, &matching_weight, &matching, &weights, 0); igraph_vector_destroy(&weights); igraph_vector_long_print(&matching); if (matching_weight != exp_weight) { printf("matching_weight is %ld, expected: %ld\n", (long)matching_weight, (long)exp_weight); return 2; } igraph_vector_destroy(&weights); igraph_vector_long_destroy(&matching); igraph_vector_bool_destroy(&types); igraph_destroy(&graph); return 0; } // This test addresses issue #1110, where an incorrect // types vector (i.e. that doesn't correspond to a bipartite // labelling of the graph) would cause a possible infinite loop. int test_incorrect_types() { igraph_t g; igraph_vector_bool_t types; igraph_vector_t weights; igraph_integer_t matching_size; igraph_real_t weighted_size; igraph_vector_long_t matching; igraph_error_type_t err; igraph_small(&g, 4, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, -1); igraph_vector_bool_init(&types, 4); VECTOR(types)[0] = 0; VECTOR(types)[1] = 1; VECTOR(types)[2] = 0; VECTOR(types)[3] = 1; igraph_vector_long_init(&matching, 0); igraph_vector_init(&weights, igraph_vcount(&g)); igraph_vector_fill(&weights, 1.0); igraph_set_error_handler(&igraph_error_handler_ignore); // Test incorrect types err = igraph_maximum_bipartite_matching(&g, &types, &matching_size, NULL, &matching, NULL, 0); if (err != IGRAPH_EINVAL) { return 3; } // Test correct types VECTOR(types)[2] = 1; err = igraph_maximum_bipartite_matching(&g, &types, &matching_size, NULL, &matching, NULL, 0); if (err == IGRAPH_EINVAL) { return 4; } // Test incorrect types for weighted graph VECTOR(types)[2] = 0; err = igraph_maximum_bipartite_matching(&g, &types, &matching_size, &weighted_size, &matching, &weights, 0); if (err != IGRAPH_EINVAL) { return 5; } // Test correct types for weighted graph VECTOR(types)[2] = 1; err = igraph_maximum_bipartite_matching(&g, &types, &matching_size, &weighted_size, &matching, &weights, 0); if (err == IGRAPH_EINVAL) { return 6; } igraph_vector_destroy(&weights); igraph_vector_long_destroy(&matching); igraph_vector_bool_destroy(&types); igraph_destroy(&g); return 0; } int main() { igraph_i_set_attribute_table(&igraph_cattribute_table); if (test_graph_from_leda_tutorial()) { return 1; } if (test_weighted_graph_from_mit_notes()) { return 2; } if (test_weighted_graph_generated()) { return 3; } if (test_incorrect_types()) { return 4; } if (!IGRAPH_FINALLY_STACK_EMPTY) { printf("Finally stack still has %d elements.\n", IGRAPH_FINALLY_STACK_SIZE()); return 5; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_edge_betweenness.c0000644000076500000240000001227113612122633030724 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void print_vector(igraph_vector_t *v, FILE *f) { long int i; for (i = 0; i < igraph_vector_size(v); i++) { fprintf(f, "%.5f\n", (double) VECTOR(*v)[i]); } fprintf(f, "\n"); } int test_bug950() { /* Testing the case of weighted graphs with multiple alternate * paths to the same node with slightly different weights due to * floating point inaccuracies. */ igraph_t g; igraph_vector_t eb; igraph_vector_t weights; igraph_integer_t from, to; long int i; igraph_full(&g, 6, 0, 0); igraph_vector_init(&weights, igraph_ecount(&g)); igraph_vector_init(&eb, igraph_ecount(&g)); for (i = 0; i < igraph_ecount(&g); i++) { igraph_edge(&g, i, &from, &to); VECTOR(weights)[i] = ((from < 3 && to < 3) || (from >= 3 && to >= 3)) ? 1 : 0.1; } igraph_edge_betweenness(&g, &eb, IGRAPH_UNDIRECTED, &weights); print_vector(&eb, stdout); igraph_vector_destroy(&eb); igraph_vector_destroy(&weights); igraph_destroy(&g); return 0; } int test_bug1050() { /* compare cutoff = -1 with cutoff = 0 */ igraph_t g; igraph_vector_t eb, eb2; igraph_full(&g, 6, 0, 0); /* unweighted */ igraph_vector_init(&eb, igraph_ecount(&g)); igraph_vector_init(&eb2, igraph_ecount(&g)); igraph_edge_betweenness_estimate(&g, &eb, IGRAPH_UNDIRECTED, /* cutoff */ -1, /* weights */ 0); igraph_edge_betweenness_estimate(&g, &eb2, IGRAPH_UNDIRECTED, /* cutoff */ 0, /* weights */ 0); if (!igraph_vector_all_e(&eb, &eb2)) { return 1; } igraph_vector_destroy(&eb); igraph_vector_destroy(&eb2); /* weighted */ igraph_vector_t weights; igraph_vector_init(&eb, igraph_ecount(&g)); igraph_vector_init(&eb2, igraph_ecount(&g)); igraph_vector_init(&weights, igraph_ecount(&g)); igraph_vector_fill(&weights, 1); VECTOR(weights)[0] = 2; igraph_edge_betweenness_estimate(&g, &eb, IGRAPH_UNDIRECTED, /* cutoff */ -1, &weights); igraph_edge_betweenness_estimate(&g, &eb2, IGRAPH_UNDIRECTED, /* cutoff */ 0, &weights); if (!igraph_vector_all_e(&eb, &eb2)) { return 1; } igraph_vector_destroy(&eb); igraph_vector_destroy(&eb2); igraph_vector_destroy(&weights); igraph_destroy(&g); return 0; } int main() { igraph_t g; igraph_vector_t eb; igraph_small(&g, 0, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 0, 7, 0, 8, 0, 10, 0, 11, 0, 12, 0, 13, 0, 17, 0, 19, 0, 21, 0, 31, 1, 2, 1, 3, 1, 7, 1, 13, 1, 17, 1, 19, 1, 21, 1, 30, 2, 3, 2, 7, 2, 8, 2, 9, 2, 13, 2, 27, 2, 28, 2, 32, 3, 7, 3, 12, 3, 13, 4, 6, 4, 10, 5, 6, 5, 10, 5, 16, 6, 16, 8, 30, 8, 32, 8, 33, 9, 33, 13, 33, 14, 32, 14, 33, 15, 32, 15, 33, 18, 32, 18, 33, 19, 33, 20, 32, 20, 33, 22, 32, 22, 33, 23, 25, 23, 27, 23, 29, 23, 32, 23, 33, 24, 25, 24, 27, 24, 31, 25, 31, 26, 29, 26, 33, 27, 33, 28, 31, 28, 33, 29, 32, 29, 33, 30, 32, 30, 33, 31, 32, 31, 33, 32, 33, -1); igraph_vector_init(&eb, igraph_ecount(&g)); igraph_edge_betweenness(&g, &eb, IGRAPH_UNDIRECTED, /*weights=*/ 0); print_vector(&eb, stdout); igraph_vector_destroy(&eb); igraph_destroy(&g); igraph_small(&g, 0, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 1, 4, -1); igraph_vector_init(&eb, igraph_ecount(&g)); igraph_edge_betweenness_estimate(&g, &eb, IGRAPH_UNDIRECTED, 2, /*weights=*/ 0); print_vector(&eb, stdout); igraph_vector_destroy(&eb); igraph_destroy(&g); igraph_small(&g, 0, IGRAPH_UNDIRECTED, 0, 1, 0, 3, 1, 2, 1, 4, 2, 5, 3, 4, 3, 6, 4, 5, 4, 7, 5, 8, 6, 7, 7, 8, -1); igraph_vector_init(&eb, igraph_ecount(&g)); igraph_edge_betweenness_estimate(&g, &eb, IGRAPH_UNDIRECTED, 2, /*weights=*/ 0); print_vector(&eb, stdout); igraph_vector_destroy(&eb); igraph_destroy(&g); if (test_bug950()) { return 1; } if (test_bug1050()) { return 2; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_motifs_randesu.out0000644000076500000240000000024513524616144031032 0ustar tamasstaff00000000000000NaN NaN 0 NaN 0 0 0 0 0 0 1 0 0 0 0 0 Class 3: 0 2 1 Class 2: 0 2 4 Class 2: 0 1 3 Class 2: 1 3 2 Class 2: 1 2 4 Class 7: 0 2 4 1 Class 7: 0 2 1 3 Class 6: 1 3 2 4 python-igraph-0.8.0/vendor/source/igraph/examples/simple/biguint.c0000644000076500000240000000600213612122633025520 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include "igraph_types_internal.h" #include "bigint.h" #include int main() { igraph_biguint_t A, B, C, D, E, zero, one; igraph_biguint_init(&A); igraph_biguint_init(&B); igraph_biguint_init(&C); igraph_biguint_init(&D); igraph_biguint_init(&E); igraph_biguint_init(&zero); igraph_biguint_init(&one); /* set & add & sub */ igraph_biguint_set_limb(&one, 1); igraph_biguint_set_limb(&A, UINT_MAX); igraph_biguint_set_limb(&B, UINT_MAX); igraph_biguint_add(&A, &A, &B); /* A <- A + B */ igraph_biguint_print(&B); putchar('\n'); igraph_biguint_print(&A); putchar('\n'); igraph_biguint_sub(&A, &A, &B); /* A <- A - B */ if (!igraph_biguint_equal(&A, &B)) { return 1; } /* inc & dec */ igraph_biguint_inc(&A, &A); /* A <- A + 1 */ igraph_biguint_dec(&A, &A); /* A <- A - 1 */ if (!igraph_biguint_equal(&A, &B)) { return 2; } /* mul & div */ igraph_biguint_mul(&C, &A, &B); /* C <- A * B */ igraph_biguint_div(&E, &D, &C, &B); /* E <- C / B */ /* D <- C % B */ if (!igraph_biguint_equal(&E, &A)) { return 3; } if (!igraph_biguint_equal(&D, &zero)) { return 4; } igraph_biguint_mul(&C, &A, &A); /* C <- A * A */ igraph_biguint_mul(&D, &C, &A); /* C <- C * A */ igraph_biguint_mul(&C, &D, &A); /* C <- C * A */ igraph_biguint_div(&C, &D, &C, &A); /* C <- C / A */ igraph_biguint_div(&C, &D, &C, &A); /* C <- C / A */ igraph_biguint_div(&C, &D, &C, &A); /* C <- C / A */ igraph_biguint_div(&C, &D, &C, &A); /* C <- C / A */ if (!igraph_biguint_equal(&C, &one)) { return 5; } igraph_biguint_destroy(&A); igraph_biguint_destroy(&B); igraph_biguint_destroy(&C); igraph_biguint_destroy(&D); igraph_biguint_destroy(&E); igraph_biguint_destroy(&zero); igraph_biguint_destroy(&one); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_sparsemat2.out0000644000076500000240000000000013524616144030056 0ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_i_layout_sphere.c0000644000076500000240000000571213612122633030613 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include #include int igraph_i_layout_sphere_2d(igraph_matrix_t *coords, igraph_real_t *x, igraph_real_t *y, igraph_real_t *r); int igraph_i_layout_sphere_3d(igraph_matrix_t *coords, igraph_real_t *x, igraph_real_t *y, igraph_real_t *z, igraph_real_t *r); int main () { long int i; igraph_matrix_t m; igraph_real_t x, y, z, r; srand(time(0)); /* 2D */ igraph_matrix_init(&m, 1000, 2); for (i = 0; i < igraph_matrix_nrow(&m); i++) { MATRIX(m, i, 0) = rand() / (double)RAND_MAX; MATRIX(m, i, 1) = rand() / (double)RAND_MAX; } igraph_i_layout_sphere_2d(&m, &x, &y, &r); for (i = 0; i < igraph_matrix_nrow(&m); i++) { igraph_real_t dist = sqrt((MATRIX(m, i, 0) - x) * (MATRIX(m, i, 0) - x) + (MATRIX(m, i, 1) - y) * (MATRIX(m, i, 1) - y)); if (dist > r) { printf("x: %f y: %f r: %f\n", x, y, r); printf("x: %f y: %f dist: %f (%li)\n", MATRIX(m, i, 0), MATRIX(m, i, 1), dist, i); return 1; } } igraph_matrix_destroy(&m); /* 3D */ igraph_matrix_init(&m, 1000, 3); for (i = 0; i < igraph_matrix_nrow(&m); i++) { MATRIX(m, i, 0) = rand() / (double)RAND_MAX; MATRIX(m, i, 1) = rand() / (double)RAND_MAX; MATRIX(m, i, 2) = rand() / (double)RAND_MAX; } igraph_i_layout_sphere_3d(&m, &x, &y, &z, &r); for (i = 0; i < igraph_matrix_nrow(&m); i++) { igraph_real_t dist = sqrt((MATRIX(m, i, 0) - x) * (MATRIX(m, i, 0) - x) + (MATRIX(m, i, 1) - y) * (MATRIX(m, i, 1) - y) + (MATRIX(m, i, 2) - z) * (MATRIX(m, i, 2) - z)); if (dist > r) { printf("x: %f y: %f z: %f r: %f\n", x, y, z, r); printf("x: %f y: %f z: %f dist: %f (%li)\n", MATRIX(m, i, 0), MATRIX(m, i, 1), MATRIX(m, i, 2), dist, i); return 1; } } igraph_matrix_destroy(&m); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_decompose.out0000644000076500000240000000011013524616144027755 0ustar tamasstaff000000000000000 1 0 9 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 0 1 1 2 2 0 0 1 1 2 2 3 0 1 1 2 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_similarity.c0000644000076500000240000001526113614300625027607 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void print_matrix(igraph_matrix_t *m, FILE *f) { long int i, j; for (i = 0; i < igraph_matrix_nrow(m); i++) { for (j = 0; j < igraph_matrix_ncol(m); j++) { fprintf(f, " %.2f", MATRIX(*m, i, j)); } fprintf(f, "\n"); } fprintf(f, "==========\n"); } int check_jaccard_all(const igraph_t* g, igraph_matrix_t* m, igraph_neimode_t mode, igraph_bool_t loops) { igraph_vector_t pairs, res; long int i, j, k, n; igraph_eit_t eit; igraph_vector_init(&res, 0); /* First, query the similarities for all the vertices to a matrix */ igraph_similarity_jaccard(g, m, igraph_vss_all(), mode, loops); /* Second, query the similarities for all pairs using a pair vector */ n = igraph_vcount(g); igraph_vector_init(&pairs, 0); for (i = 0; i < n; i++) { for (j = n - 1; j >= 0; j--) { igraph_vector_push_back(&pairs, i); igraph_vector_push_back(&pairs, j); } } igraph_similarity_jaccard_pairs(g, &res, &pairs, mode, loops); for (i = 0, k = 0; i < n; i++) { for (j = n - 1; j >= 0; j--, k++) { if (fabs(VECTOR(res)[k] - MATRIX(*m, i, j)) > 1e-6) { fprintf(stderr, "Jaccard similarity calculation for vertex pair %ld-%ld " "does not match the value in the full matrix (%.6f vs %.6f)\n", i, j, VECTOR(res)[k], MATRIX(*m, i, j)); return 1; } } } igraph_vector_destroy(&pairs); /* Third, query the similarities for all edges */ igraph_similarity_jaccard_es(g, &res, igraph_ess_all(IGRAPH_EDGEORDER_FROM), mode, loops); igraph_eit_create(g, igraph_ess_all(IGRAPH_EDGEORDER_FROM), &eit); k = 0; while (!IGRAPH_EIT_END(eit)) { long int eid = IGRAPH_EIT_GET(eit); i = IGRAPH_FROM(g, eid); j = IGRAPH_TO(g, eid); if (fabs(VECTOR(res)[k] - MATRIX(*m, i, j)) > 1e-6) { fprintf(stderr, "Jaccard similarity calculation for edge %ld-%ld (ID=%ld) " "does not match the value in the full matrix (%.6f vs %.6f)\n", i, j, eid, VECTOR(res)[k], MATRIX(*m, i, j)); return 1; } IGRAPH_EIT_NEXT(eit); k++; } igraph_eit_destroy(&eit); igraph_vector_destroy(&res); return 0; } int check_dice_all(const igraph_t* g, igraph_matrix_t* m, igraph_neimode_t mode, igraph_bool_t loops) { igraph_vector_t pairs, res; long int i, j, k, n; igraph_eit_t eit; igraph_vector_init(&res, 0); /* First, query the similarities for all the vertices to a matrix */ igraph_similarity_dice(g, m, igraph_vss_all(), mode, loops); /* Second, query the similarities for all pairs using a pair vector */ n = igraph_vcount(g); igraph_vector_init(&pairs, 0); for (i = 0; i < n; i++) { for (j = n - 1; j >= 0; j--) { igraph_vector_push_back(&pairs, i); igraph_vector_push_back(&pairs, j); } } igraph_similarity_dice_pairs(g, &res, &pairs, mode, loops); for (i = 0, k = 0; i < n; i++) { for (j = n - 1; j >= 0; j--, k++) { if (fabs(VECTOR(res)[k] - MATRIX(*m, i, j)) > 1e-6) { fprintf(stderr, "Dice similarity calculation for vertex pair %ld-%ld " "does not match the value in the full matrix (%.6f vs %.6f)\n", i, j, VECTOR(res)[k], MATRIX(*m, i, j)); return 1; } } } igraph_vector_destroy(&pairs); /* Third, query the similarities for all edges */ igraph_similarity_dice_es(g, &res, igraph_ess_all(IGRAPH_EDGEORDER_FROM), mode, loops); igraph_eit_create(g, igraph_ess_all(IGRAPH_EDGEORDER_FROM), &eit); k = 0; while (!IGRAPH_EIT_END(eit)) { long int eid = IGRAPH_EIT_GET(eit); i = IGRAPH_FROM(g, eid); j = IGRAPH_TO(g, eid); if (fabs(VECTOR(res)[k] - MATRIX(*m, i, j)) > 1e-6) { fprintf(stderr, "Dice similarity calculation for edge %ld-%ld (ID=%ld) " "does not match the value in the full matrix (%.6f vs %.6f)\n", i, j, eid, VECTOR(res)[k], MATRIX(*m, i, j)); return 1; } IGRAPH_EIT_NEXT(eit); k++; } igraph_eit_destroy(&eit); igraph_vector_destroy(&res); return 0; } int main() { igraph_t g; igraph_matrix_t m; int ret; igraph_small(&g, 0, IGRAPH_DIRECTED, 0, 1, 2, 1, 2, 0, 3, 0, -1); igraph_matrix_init(&m, 0, 0); ret = check_jaccard_all(&g, &m, IGRAPH_ALL, 1); print_matrix(&m, stdout); if (ret) { return 1; } igraph_similarity_jaccard(&g, &m, igraph_vss_seq(1, 2), IGRAPH_ALL, 0); print_matrix(&m, stdout); ret = check_jaccard_all(&g, &m, IGRAPH_OUT, 1); print_matrix(&m, stdout); if (ret) { return 3; } ret = check_jaccard_all(&g, &m, IGRAPH_IN, 0); print_matrix(&m, stdout); if (ret) { return 4; } ret = check_dice_all(&g, &m, IGRAPH_ALL, 1); print_matrix(&m, stdout); if (ret) { return 5; } ret = check_dice_all(&g, &m, IGRAPH_OUT, 1); print_matrix(&m, stdout); if (ret) { return 6; } ret = check_dice_all(&g, &m, IGRAPH_IN, 0); print_matrix(&m, stdout); if (ret) { return 7; } igraph_similarity_inverse_log_weighted(&g, &m, igraph_vss_all(), IGRAPH_ALL); print_matrix(&m, stdout); igraph_similarity_inverse_log_weighted(&g, &m, igraph_vss_all(), IGRAPH_OUT); print_matrix(&m, stdout); igraph_similarity_inverse_log_weighted(&g, &m, igraph_vss_all(), IGRAPH_IN); print_matrix(&m, stdout); igraph_matrix_destroy(&m); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_topological_sorting.c0000644000076500000240000000544513612122634031505 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void print_vector(igraph_vector_t *v, FILE *f) { long int i; for (i = 0; i < igraph_vector_size(v); i++) { fprintf(f, " %d", (int)VECTOR(*v)[i]); } fprintf(f, "\n"); } void igraph_warning_handler_print_stdout(const char *reason, const char *file, int line, int igraph_errno) { fprintf(stdout, "Warning: %s\n", reason); } int main() { igraph_t g; igraph_vector_t v, res; igraph_bool_t is_dag; int ret; igraph_set_warning_handler(igraph_warning_handler_print_stdout); /* Test graph taken from http://en.wikipedia.org/wiki/Topological_sorting * @ 05.03.2006 */ igraph_small(&g, 8, 1, 0, 3, 0, 4, 1, 3, 2, 4, 2, 7, \ 3, 5, 3, 6, 3, 7, 4, 6, -1); igraph_vector_init(&res, 0); igraph_is_dag(&g, &is_dag); if (!is_dag) { return 2; } igraph_topological_sorting(&g, &res, IGRAPH_OUT); print_vector(&res, stdout); igraph_topological_sorting(&g, &res, IGRAPH_IN); print_vector(&res, stdout); /* Add a circle: 5 -> 0 */ igraph_vector_init_int(&v, 2, 5, 0); igraph_add_edges(&g, &v, 0); igraph_is_dag(&g, &is_dag); if (is_dag) { return 3; } igraph_topological_sorting(&g, &res, IGRAPH_OUT); print_vector(&res, stdout); igraph_vector_destroy(&v); igraph_destroy(&g); /* Error handling */ igraph_set_error_handler(igraph_error_handler_ignore); /* This graph is the same but undirected */ igraph_small(&g, 8, 0, 0, 3, 0, 4, 1, 3, 2, 4, 2, 7, \ 3, 5, 3, 6, 3, 7, 4, 6, -1); igraph_is_dag(&g, &is_dag); if (is_dag) { return 4; } ret = igraph_topological_sorting(&g, &res, IGRAPH_ALL); if (ret != IGRAPH_EINVAL) { return 1; } ret = igraph_topological_sorting(&g, &res, IGRAPH_OUT); if (ret != IGRAPH_EINVAL) { return 1; } igraph_destroy(&g); igraph_vector_destroy(&res); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_layout_mds.out0000644000076500000240000000025713524616144030173 0ustar tamasstaff00000000000000-0.692039 0.0247583 0.399957 0.178289 -1.78403 -0.128772 1.25186 -0.697105 0.891182 1.32979 -2.6988 -0.242629 -2.6988 -0.242629 1.97413 -1.3515 1.97413 -1.3515 1.38241 2.4813 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_trie.c0000644000076500000240000000745613612122634026373 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include "igraph_types_internal.h" int main() { igraph_trie_t trie; long int id; int i; char *str; /* init */ igraph_trie_init(&trie, 0); /* add and get values */ igraph_trie_get(&trie, "hello", &id); printf("hello: %li\n", id); igraph_trie_get(&trie, "hepp", &id); printf("hepp: %li\n", id); igraph_trie_get(&trie, "alma", &id); printf("alma: %li\n", id); igraph_trie_get(&trie, "also", &id); printf("also: %li\n", id); igraph_trie_get(&trie, "hello", &id); printf("hello: %li\n", id); igraph_trie_get(&trie, "hepp", &id); printf("hepp: %li\n", id); igraph_trie_get(&trie, "alma", &id); printf("alma: %li\n", id); igraph_trie_get(&trie, "also", &id); printf("also: %li\n", id); igraph_trie_get(&trie, "a", &id); printf("a: %li\n", id); igraph_trie_get(&trie, "axon", &id); printf("axon: %li\n", id); igraph_trie_get(&trie, "hello", &id); printf("hello: %li\n", id); igraph_trie_get(&trie, "hepp", &id); printf("hepp: %li\n", id); igraph_trie_get(&trie, "alma", &id); printf("alma: %li\n", id); igraph_trie_get(&trie, "also", &id); printf("also: %li\n", id); /* check for existence */ igraph_trie_check(&trie, "head", &id); printf("head: %li\n", id); igraph_trie_check(&trie, "alma", &id); printf("alma: %li\n", id); /* destroy */ igraph_trie_destroy(&trie); /* the same with index */ igraph_trie_init(&trie, 1); igraph_trie_get(&trie, "hello", &id); printf("hello: %li\n", id); igraph_trie_get(&trie, "hepp", &id); printf("hepp: %li\n", id); igraph_trie_get(&trie, "alma", &id); printf("alma: %li\n", id); igraph_trie_get(&trie, "also", &id); printf("also: %li\n", id); igraph_trie_get(&trie, "hello", &id); printf("hello: %li\n", id); igraph_trie_get(&trie, "hepp", &id); printf("hepp: %li\n", id); igraph_trie_get(&trie, "alma", &id); printf("alma: %li\n", id); igraph_trie_get(&trie, "also", &id); printf("also: %li\n", id); igraph_trie_get(&trie, "a", &id); printf("a: %li\n", id); igraph_trie_get(&trie, "axon", &id); printf("axon: %li\n", id); igraph_trie_get(&trie, "hello", &id); printf("hello: %li\n", id); igraph_trie_get(&trie, "hepp", &id); printf("hepp: %li\n", id); igraph_trie_get(&trie, "alma", &id); printf("alma: %li\n", id); igraph_trie_get(&trie, "also", &id); printf("also: %li\n", id); /* check for existence */ igraph_trie_check(&trie, "head", &id); printf("head: %li\n", id); igraph_trie_check(&trie, "alma", &id); printf("alma: %li\n", id); for (i = 0; i < igraph_trie_size(&trie); i++) { igraph_trie_idx(&trie, i, &str); printf("%d: %s\n", i, str); } igraph_trie_destroy(&trie); if (!IGRAPH_FINALLY_STACK_EMPTY) { return 1; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/vector2.c0000644000076500000240000000712113612122634025447 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include void print_vector(igraph_vector_t *v, FILE *f) { long int i; for (i = 0; i < igraph_vector_size(v); i++) { fprintf(f, " %li", (long int) VECTOR(*v)[i]); } fprintf(f, "\n"); } int main() { igraph_vector_t v1, v2, v3; igraph_real_t min, max; long int imin, imax; int i; igraph_vector_init_seq(&v1, 1, 10); igraph_vector_init_seq(&v2, 0, 9); igraph_vector_swap(&v1, &v2); print_vector(&v1, stdout); print_vector(&v2, stdout); igraph_vector_swap_elements(&v1, 0, 9); igraph_vector_swap_elements(&v1, 3, 6); print_vector(&v1, stdout); igraph_vector_reverse(&v2); print_vector(&v2, stdout); igraph_vector_reverse(&v2); print_vector(&v2, stdout); igraph_vector_destroy(&v1); igraph_vector_destroy(&v2); igraph_vector_init(&v1, 10); igraph_vector_init(&v2, 10); igraph_vector_fill(&v1, 4); igraph_vector_fill(&v2, 2); igraph_vector_add(&v1, &v2); print_vector(&v1, stdout); igraph_vector_sub(&v1, &v2); print_vector(&v1, stdout); igraph_vector_div(&v1, &v2); print_vector(&v1, stdout); igraph_vector_mul(&v1, &v2); print_vector(&v1, stdout); igraph_vector_minmax(&v1, &min, &max); igraph_vector_which_minmax(&v1, &imin, &imax); printf("%g %g %li %li\n", min, max, imin, imax); igraph_vector_destroy(&v1); igraph_vector_destroy(&v2); igraph_vector_init_seq(&v1, 1, 10); igraph_vector_init(&v2, 10); for (i = 0; i < 10; i++) { VECTOR(v2)[i] = 10 - i; } igraph_vector_minmax(&v1, &min, &max); igraph_vector_which_minmax(&v1, &imin, &imax); printf("%g %g %li %li\n", min, max, imin, imax); igraph_vector_minmax(&v2, &min, &max); igraph_vector_which_minmax(&v2, &imin, &imax); printf("%g %g %li %li\n", min, max, imin, imax); if (igraph_vector_isnull(&v1)) { return 1; } igraph_vector_null(&v1); if (!igraph_vector_isnull(&v1)) { return 2; } igraph_vector_destroy(&v1); igraph_vector_destroy(&v2); igraph_vector_init_int(&v1, 10, 3, 5, 6, 6, 6, 7, 8, 8, 9, 10); igraph_vector_init_int(&v2, 10, 1, 3, 3, 6, 6, 9, 12, 15, 17, 20); igraph_vector_init(&v3, 0); igraph_vector_intersect_sorted(&v1, &v2, &v3); print_vector(&v3, stdout); igraph_vector_difference_sorted(&v1, &v2, &v3); print_vector(&v3, stdout); igraph_vector_difference_sorted(&v2, &v1, &v3); print_vector(&v3, stdout); igraph_vector_difference_sorted(&v2, &v2, &v3); print_vector(&v3, stdout); igraph_vector_destroy(&v1); igraph_vector_destroy(&v2); igraph_vector_destroy(&v3); if (IGRAPH_FINALLY_STACK_SIZE() != 0) { return 3; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/test.gxl0000644000076500000240000000362013524616144025420 0ustar tamasstaff00000000000000 yellow 1 2006-11-12 green incorrect true blue 0 red "with entities" false turquoise fAlSe 1.0 1.0 2.0 1.1 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_rng_get_exp.c0000644000076500000240000000211113612122633027707 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { int i; igraph_rng_seed(igraph_rng_default(), 42); for (i = 0; i < 1000; i++) { printf("%g\n", igraph_rng_get_exp(igraph_rng_default(), 2.5)); } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_copy.c0000644000076500000240000000275113612122633026372 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g1, g2; igraph_vector_t v1, v2; igraph_vector_init(&v1, 8); VECTOR(v1)[0] = 0; VECTOR(v1)[1] = 1; VECTOR(v1)[2] = 1; VECTOR(v1)[3] = 2; VECTOR(v1)[4] = 2; VECTOR(v1)[5] = 3; VECTOR(v1)[6] = 2; VECTOR(v1)[7] = 2; igraph_create(&g1, &v1, 0, 0); igraph_copy(&g2, &g1); igraph_vector_init(&v2, 0); igraph_get_edgelist(&g2, &v2, 0); if (!igraph_vector_all_e(&v1, &v2)) { return 1; } igraph_vector_destroy(&v1); igraph_vector_destroy(&v2); igraph_destroy(&g1); igraph_destroy(&g2); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_community_fastgreedy.out0000644000076500000240000000133313524616144032250 0ustar tamasstaff00000000000000Modularity: 0.452381 Membership: 1 1 1 1 1 0 0 0 0 0 Modularity: 0.452381 Membership: 1 1 1 1 1 0 0 0 0 0 Modularity: 0.179688 Membership: 1 1 0 0 0 0 Modularity: 0.170858 Membership: 1 1 1 0 0 0 Modularity: 0.380671 Membership: 0 2 2 2 0 0 0 2 1 2 0 0 2 2 1 1 0 2 1 0 1 2 1 1 1 1 1 1 1 1 1 1 1 1 Modularity: 0.500000 Membership: 1 1 1 1 0 0 0 0 2 Modularity: 0.540000 Membership: 1 1 1 1 3 3 3 3 1 1 0 0 0 0 0 0 2 2 2 2 Modularity: 0.000000 Membership: 0 1 2 3 4 5 6 7 8 9 Modularity: 0.281250 Membership: 0 1 1 2 2 0 Modularity: 0.500000 Membership: 0 1 Modularity: --- Membership: 1 1 1 1 1 0 0 0 0 0 Modularity: 0.452381 Membership: 1 1 1 1 1 0 0 0 0 0 Modularity: --- Membership: 1 1 1 1 1 0 0 0 0 0 python-igraph-0.8.0/vendor/source/igraph/examples/simple/graphml-lenient.xml0000644000076500000240000000044313524616144027535 0ustar tamasstaff00000000000000 python-igraph-0.8.0/vendor/source/igraph/examples/simple/nodelist2.dl0000644000076500000240000000015013524616144026144 0ustar tamasstaff00000000000000DL n=5 format = nodelist1 labels embedded: data: george sally jim sally jim billy george jane jim python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_weighted_cliques.c0000644000076500000240000001311113612122634030736 0ustar tamasstaff00000000000000 #include #include int compare_vectors(const void *p1, const void *p2) { igraph_vector_t *v1, *v2; long s1, s2, i; v1 = *((igraph_vector_t **) p1); v2 = *((igraph_vector_t **) p2); s1 = igraph_vector_size(v1); s2 = igraph_vector_size(v2); if (s1 < s2) { return -1; } if (s1 > s2) { return 1; } for (i = 0; i < s1; ++i) { if (VECTOR(*v1)[i] < VECTOR(*v2)[i]) { return -1; } if (VECTOR(*v1)[i] > VECTOR(*v2)[i]) { return 1; } } return 0; } /* Takes a pointer vector of vectors. Sorts each vector, then sorts the pointer vector */ void canonicalize_list(igraph_vector_ptr_t *list) { long i, len; len = igraph_vector_ptr_size(list); for (i = 0; i < len; ++i) { igraph_vector_sort((igraph_vector_t *) VECTOR(*list)[i]); } qsort(&(VECTOR(*list)[0]), len, sizeof(void *), &compare_vectors); } /* Prints a clique vector along with its weight */ void print_weighted_clique(const igraph_vector_t *clique, const igraph_vector_t *vertex_weights) { long int i, n = igraph_vector_size(clique); igraph_real_t clique_weight = 0.0; for (i = 0; i < n; i++) { int v = VECTOR(*clique)[i]; clique_weight += igraph_vector_e(vertex_weights, v); printf(" %d", v); } printf(" w=%.1f\n", clique_weight); } int main() { igraph_t graph; const igraph_integer_t n = 10; /* number of vertices in test graph */ /* edges of the test graph */ igraph_vector_t edges; igraph_real_t edge_data[] = {0., 1., 0., 6., 0., 7., 0., 8., 0., 9., 1., 2., 1., 3., 1., 4., 1., 6., 1., 7., 1., 8., 1., 9., 2., 3., 2., 5., 2., 6., 2., 7., 2., 9., 3., 5., 3., 6., 3., 7., 3., 9., 4., 5., 4., 6., 4., 7., 4., 9., 5., 8., 6., 7., 6., 8., 7., 8., 8., 9. }; /* vertex weights in test graph, note that current implementation only supports integer weights */ igraph_vector_t vertex_weights; igraph_real_t vertex_weight_data[] = {3., 2., 3., 5., 2., 3., 1., 3., 5., 5.}; igraph_vector_ptr_t result; /* result clique list */ igraph_integer_t count; /* number of cliques found */ igraph_real_t weighted_clique_no; int i; /* create graph */ igraph_vector_init_copy(&edges, edge_data, (sizeof edge_data) / sizeof(igraph_real_t)); igraph_create(&graph, &edges, n, /* directed= */ 0); /* set up vertex weight vector */ igraph_vector_init_copy(&vertex_weights, vertex_weight_data, (sizeof vertex_weight_data) / sizeof(igraph_real_t)); /* initialize result vector_ptr */ igraph_vector_ptr_init(&result, 0); /* all weighed cliques above weight 6 */ igraph_weighted_cliques(&graph, &vertex_weights, &result, 6, 0, /* maximal= */ 0); count = igraph_vector_ptr_size(&result); printf("%ld weighted cliques found above weight 6\n", (long) count); canonicalize_list(&result); for (i = 0; i < count; i++) { igraph_vector_t* v = (igraph_vector_t*) igraph_vector_ptr_e(&result, i); print_weighted_clique(v, &vertex_weights); igraph_vector_destroy(v); free(v); } /* all weighed cliques beteen weights 5 and 10 */ igraph_weighted_cliques(&graph, &vertex_weights, &result, 5, 10, /* maximal= */ 0); count = igraph_vector_ptr_size(&result); printf("%ld weighted cliques found between weights 5 and 10\n", (long) count); canonicalize_list(&result); for (i = 0; i < count; i++) { igraph_vector_t* v = (igraph_vector_t*) igraph_vector_ptr_e(&result, i); print_weighted_clique(v, &vertex_weights); igraph_vector_destroy(v); free(v); } /* maximal weighed cliques above weight 7 */ igraph_weighted_cliques(&graph, &vertex_weights, &result, 7, 0, /* maximal= */ 1); count = igraph_vector_ptr_size(&result); printf("%ld maximal weighted cliques found above weight 7\n", (long) count); canonicalize_list(&result); for (i = 0; i < count; i++) { igraph_vector_t* v = (igraph_vector_t*) igraph_vector_ptr_e(&result, i); print_weighted_clique(v, &vertex_weights); igraph_vector_destroy(v); free(v); } /* maximal weighed cliques beteen weights 5 and 10 */ igraph_weighted_cliques(&graph, &vertex_weights, &result, 5, 10, /* maximal= */ 1); count = igraph_vector_ptr_size(&result); printf("%ld maximal weighted cliques found between weights 5 and 10\n", (long) count); canonicalize_list(&result); for (i = 0; i < count; i++) { igraph_vector_t* v = (igraph_vector_t*) igraph_vector_ptr_e(&result, i); print_weighted_clique(v, &vertex_weights); igraph_vector_destroy(v); free(v); } /* largest weight cliques */ igraph_largest_weighted_cliques(&graph, &vertex_weights, &result); count = igraph_vector_ptr_size(&result); printf("%ld largest weight cliques found\n", (long) count); canonicalize_list(&result); for (i = 0; i < count; i++) { igraph_vector_t* v = (igraph_vector_t*) igraph_vector_ptr_e(&result, i); print_weighted_clique(v, &vertex_weights); igraph_vector_destroy(v); free(v); } igraph_weighted_clique_number(&graph, &vertex_weights, &weighted_clique_no); printf("weighted clique number: %.1f\n", weighted_clique_no); /* free data structures */ igraph_vector_ptr_destroy(&result); igraph_vector_destroy(&vertex_weights); igraph_destroy(&graph); igraph_vector_destroy(&edges); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_sparsemat4.c0000644000076500000240000001745513612122634027513 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include igraph_bool_t check_solution(const igraph_sparsemat_t *A, const igraph_vector_t *x, const igraph_vector_t *b) { long int dim = igraph_vector_size(x); igraph_vector_t res; int j, p; igraph_real_t min, max; igraph_vector_copy(&res, b); for (j = 0; j < dim; j++) { for (p = A->cs->p[j]; p < A->cs->p[j + 1]; p++) { long int from = A->cs->i[p]; igraph_real_t value = A->cs->x[p]; VECTOR(res)[from] -= VECTOR(*x)[j] * value; } } igraph_vector_minmax(&res, &min, &max); igraph_vector_destroy(&res); return fabs(min) < 1e-15 && fabs(max) < 1e-15; } int main() { igraph_sparsemat_t A, B, C; igraph_vector_t b, x; long int i; /* lsolve */ #define DIM 10 #define EDGES (DIM*DIM/6) igraph_sparsemat_init(&A, DIM, DIM, EDGES + DIM); for (i = 0; i < DIM; i++) { igraph_sparsemat_entry(&A, i, i, RNG_INTEGER(1, 3)); } for (i = 0; i < EDGES; i++) { long int r = RNG_INTEGER(0, DIM - 1); long int c = RNG_INTEGER(0, r); igraph_real_t value = RNG_INTEGER(1, 5); igraph_sparsemat_entry(&A, r, c, value); } igraph_sparsemat_compress(&A, &B); igraph_sparsemat_destroy(&A); igraph_sparsemat_dupl(&B); igraph_vector_init(&b, DIM); for (i = 0; i < DIM; i++) { VECTOR(b)[i] = RNG_INTEGER(1, 10); } igraph_vector_init(&x, DIM); igraph_sparsemat_lsolve(&B, &b, &x); if (! check_solution(&B, &x, &b)) { return 1; } igraph_vector_destroy(&b); igraph_vector_destroy(&x); igraph_sparsemat_destroy(&B); #undef DIM #undef EDGES /* ltsolve */ #define DIM 10 #define EDGES (DIM*DIM/6) igraph_sparsemat_init(&A, DIM, DIM, EDGES + DIM); for (i = 0; i < DIM; i++) { igraph_sparsemat_entry(&A, i, i, RNG_INTEGER(1, 3)); } for (i = 0; i < EDGES; i++) { long int r = RNG_INTEGER(0, DIM - 1); long int c = RNG_INTEGER(0, r); igraph_real_t value = RNG_INTEGER(1, 5); igraph_sparsemat_entry(&A, r, c, value); } igraph_sparsemat_compress(&A, &B); igraph_sparsemat_destroy(&A); igraph_sparsemat_dupl(&B); igraph_vector_init(&b, DIM); for (i = 0; i < DIM; i++) { VECTOR(b)[i] = RNG_INTEGER(1, 10); } igraph_vector_init(&x, DIM); igraph_sparsemat_ltsolve(&B, &b, &x); igraph_sparsemat_transpose(&B, &A, /*values=*/ 1); if (! check_solution(&A, &x, &b)) { return 2; } igraph_vector_destroy(&b); igraph_vector_destroy(&x); igraph_sparsemat_destroy(&B); igraph_sparsemat_destroy(&A); #undef DIM #undef EDGES /* usolve */ #define DIM 10 #define EDGES (DIM*DIM/6) igraph_sparsemat_init(&A, DIM, DIM, EDGES + DIM); for (i = 0; i < DIM; i++) { igraph_sparsemat_entry(&A, i, i, RNG_INTEGER(1, 3)); } for (i = 0; i < EDGES; i++) { long int r = RNG_INTEGER(0, DIM - 1); long int c = RNG_INTEGER(0, r); igraph_real_t value = RNG_INTEGER(1, 5); igraph_sparsemat_entry(&A, r, c, value); } igraph_sparsemat_compress(&A, &B); igraph_sparsemat_destroy(&A); igraph_sparsemat_dupl(&B); igraph_sparsemat_transpose(&B, &A, /*values=*/ 1); igraph_vector_init(&b, DIM); for (i = 0; i < DIM; i++) { VECTOR(b)[i] = RNG_INTEGER(1, 10); } igraph_vector_init(&x, DIM); igraph_sparsemat_usolve(&A, &b, &x); if (! check_solution(&A, &x, &b)) { return 3; } igraph_vector_destroy(&b); igraph_vector_destroy(&x); igraph_sparsemat_destroy(&B); igraph_sparsemat_destroy(&A); #undef DIM #undef EDGES /* utsolve */ #define DIM 10 #define EDGES (DIM*DIM/6) igraph_sparsemat_init(&A, DIM, DIM, EDGES + DIM); for (i = 0; i < DIM; i++) { igraph_sparsemat_entry(&A, i, i, RNG_INTEGER(1, 3)); } for (i = 0; i < EDGES; i++) { long int r = RNG_INTEGER(0, DIM - 1); long int c = RNG_INTEGER(0, r); igraph_real_t value = RNG_INTEGER(1, 5); igraph_sparsemat_entry(&A, r, c, value); } igraph_sparsemat_compress(&A, &B); igraph_sparsemat_destroy(&A); igraph_sparsemat_dupl(&B); igraph_sparsemat_transpose(&B, &A, /*values=*/ 1); igraph_sparsemat_destroy(&B); igraph_vector_init(&b, DIM); for (i = 0; i < DIM; i++) { VECTOR(b)[i] = RNG_INTEGER(1, 10); } igraph_vector_init(&x, DIM); igraph_sparsemat_utsolve(&A, &b, &x); igraph_sparsemat_transpose(&A, &B, /*values=*/ 1); if (! check_solution(&B, &x, &b)) { return 4; } igraph_vector_destroy(&b); igraph_vector_destroy(&x); igraph_sparsemat_destroy(&B); igraph_sparsemat_destroy(&A); #undef DIM #undef EDGES /* cholsol */ /* We need a positive definite matrix, so we create a full-rank matrix first and then calculate A'A, which will be positive definite. */ #define DIM 10 #define EDGES (DIM*DIM/6) igraph_sparsemat_init(&A, DIM, DIM, EDGES + DIM); for (i = 0; i < DIM; i++) { igraph_sparsemat_entry(&A, i, i, RNG_INTEGER(1, 3)); } for (i = 0; i < EDGES; i++) { long int from = RNG_INTEGER(0, DIM - 1); long int to = RNG_INTEGER(0, DIM - 1); igraph_real_t value = RNG_INTEGER(1, 5); igraph_sparsemat_entry(&A, from, to, value); } igraph_sparsemat_compress(&A, &B); igraph_sparsemat_destroy(&A); igraph_sparsemat_dupl(&B); igraph_sparsemat_transpose(&B, &A, /*values=*/ 1); igraph_sparsemat_multiply(&A, &B, &C); igraph_sparsemat_destroy(&A); igraph_sparsemat_destroy(&B); igraph_vector_init(&b, DIM); for (i = 0; i < DIM; i++) { VECTOR(b)[i] = RNG_INTEGER(1, 10); } igraph_vector_init(&x, DIM); igraph_sparsemat_cholsol(&C, &b, &x, /*order=*/ 0); if (! check_solution(&C, &x, &b)) { return 5; } igraph_vector_destroy(&b); igraph_vector_destroy(&x); igraph_sparsemat_destroy(&C); #undef DIM #undef EDGES /* lusol */ #define DIM 10 #define EDGES (DIM*DIM/4) igraph_sparsemat_init(&A, DIM, DIM, EDGES + DIM); for (i = 0; i < DIM; i++) { igraph_sparsemat_entry(&A, i, i, RNG_INTEGER(1, 3)); } for (i = 0; i < EDGES; i++) { long int from = RNG_INTEGER(0, DIM - 1); long int to = RNG_INTEGER(0, DIM - 1); igraph_real_t value = RNG_INTEGER(1, 5); igraph_sparsemat_entry(&A, from, to, value); } igraph_sparsemat_compress(&A, &B); igraph_sparsemat_destroy(&A); igraph_sparsemat_dupl(&B); igraph_vector_init(&b, DIM); for (i = 0; i < DIM; i++) { VECTOR(b)[i] = RNG_INTEGER(1, 10); } igraph_vector_init(&x, DIM); igraph_sparsemat_lusol(&B, &b, &x, /*order=*/ 0, /*tol=*/ 1e-10); if (! check_solution(&B, &x, &b)) { return 6; } igraph_vector_destroy(&b); igraph_vector_destroy(&x); igraph_sparsemat_destroy(&B); #undef DIM #undef EDGES return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_sparsemat_minmax.out0000644000076500000240000000154013524616144031357 0ustar tamasstaff00000000000000-7 -9 Inf -7 Inf -6 7 -5 6 7 -9 -6 -6 -9 -4 -3 -1 9 -5 -4 5 -9 -4 -7 -9 -6 -9 -9 -5 -5 -7 -9 Inf -7 Inf -6 7 -5 6 7 -13 -12 -6 -9 -4 -3 1 9 -5 -4 7 -9 -4 -7 -7 -12 -13 -9 -5 -5 Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf 7 9 -Inf 7 -Inf 6 -7 5 -6 -7 9 6 6 9 4 3 1 -9 5 4 -5 9 4 7 9 6 9 9 5 5 7 9 -Inf 7 -Inf 6 -7 5 -6 -7 13 12 6 9 4 3 -1 -9 5 4 -7 9 4 7 7 12 13 9 5 5 -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf python-igraph-0.8.0/vendor/source/igraph/examples/simple/spmatrix.out0000644000076500000240000000125613524616144026330 0ustar tamasstaff00000000000000 0 1 2 0 1 2 0 1 2 0 1 2 ========================= 0 0 0 0 0 0 0 0 0 0 0 0 ========================= 0 1 2 0 1 2 0 1 2 0 1 2 ========================= -2 -1 0 -2 -1 0 -2 -1 0 -2 -1 0 ========================= -1 0 1 -1 0 1 -1 0 1 -1 0 1 ========================= 1 2 3 0 0 2 4 6 0 0 3 6 9 0 0 4 8 12 0 0 0 0 0 0 0 0 0 0 0 0 ========================= 0 0 0 0 1 2 0 2 4 0 3 6 0 4 8 ========================= 0 0 0 0 0 1 2 3 0 2 4 6 ========================= 0 0 0 0 1 2 0 2 4 0 3 6 ========================= 6 2 3 ========================= -9 -6 -3 0 3 ========================= 1 0 2 0 1 2 2 1 6 1 2 6 3 2 12 2 3 12 4 3 20 3 4 20 ========================= python-igraph-0.8.0/vendor/source/igraph/examples/simple/triad_census.c0000644000076500000240000000212213612122634026542 0ustar tamasstaff00000000000000 #include void print_vector(igraph_vector_t *v) { long int i, n = igraph_vector_size(v); for (i = 0; i < n; i++) { igraph_real_printf(VECTOR(*v)[i]); printf(" "); } printf("\n"); } int main() { // this is a directed graph with 10 vertices and 20 edges: igraph_integer_t vc = 10, ec = 20; igraph_real_t edge_data[] = { 0, 2, 1, 4, 2, 5, 2, 7, 3, 7, 3, 8, 4, 2, 5, 8, 6, 0, 6, 1, 6, 2, 7, 0, 8, 0, 8, 2, 8, 3, 8, 5, 9, 2, 9, 3, 9, 4, 9, 5 }; igraph_vector_t edges; igraph_vector_t tri; igraph_t graph; igraph_set_warning_handler(igraph_warning_handler_ignore); igraph_vector_view(&edges, edge_data, 2 * ec); igraph_create(&graph, &edges, vc, 1 /* directed=true */); igraph_vector_init(&tri, 0); igraph_triad_census(&graph, &tri); print_vector(&tri); igraph_to_undirected(&graph, IGRAPH_TO_UNDIRECTED_COLLAPSE, NULL); // convert to undirected igraph_triad_census(&graph, &tri); print_vector(&tri); igraph_vector_destroy(&tri); igraph_destroy(&graph); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/dominator_tree.out0000644000076500000240000000053013524616144027466 0ustar tamasstaff00000000000000-1 0 1 0 0 1 5 0 0 0 0 0 11 0 1 0 3 0 4 0 7 0 8 0 9 0 10 0 11 1 2 1 5 5 6 11 12 -1 0 0 0 0 0 3 3 0 0 7 0 4 1 0 2 0 3 0 4 0 5 0 6 3 7 3 8 0 9 0 10 7 11 0 12 4 -1 0 0 0 0 NaN NaN NaN 0 3 3 0 0 10 0 4 NaN NaN NaN NaN 5 6 7 16 17 18 19 0 1 0 2 0 3 0 4 0 8 0 11 0 12 0 14 3 9 3 10 4 15 10 13 9 0 3 1 1 1 9 NaN NaN -1 7 8 0 9 1 0 2 3 3 1 4 1 5 1 6 9 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_radius.c0000644000076500000240000000273113614300625026706 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sts=4 sw=4 et: */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard street, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_real_t radius; igraph_star(&g, 10, IGRAPH_STAR_UNDIRECTED, 0); igraph_radius(&g, &radius, IGRAPH_OUT); if (radius != 1) { return 1; } igraph_destroy(&g); igraph_star(&g, 10, IGRAPH_STAR_OUT, 0); igraph_radius(&g, &radius, IGRAPH_ALL); if (radius != 1) { return 2; } igraph_destroy(&g); igraph_star(&g, 10, IGRAPH_STAR_OUT, 0); igraph_radius(&g, &radius, IGRAPH_OUT); if (radius != 0) { return 3; } igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_sparsemat_which_minmax.out0000644000076500000240000000123513524616144032542 0ustar tamasstaff00000000000000-7 -9 Inf -7 Inf -6 7 -5 6 7 -9 -6 -6 -9 -4 -3 -1 9 -5 -4 3 4 0 4 0 3 9 9 9 6 6 5 3 7 3 6 5 3 8 3 5 -9 -4 -7 -9 -6 -9 -9 -5 -5 19 10 13 0 1 11 10 13 18 7 -7 -9 Inf -7 Inf -6 7 -5 6 7 -13 -12 -6 -9 -4 -3 1 9 -5 -4 3 1 0 4 0 3 9 9 9 6 6 5 3 7 3 6 5 3 8 3 7 -9 -4 -7 -7 -12 -13 -9 -5 -5 0 1 13 0 3 11 10 13 18 7 Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf 0 0 0 0 0 0 0 0 0 0 Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf 0 0 0 0 0 0 0 0 0 0 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_community_leading_eigenvector.c0000644000076500000240000001002013612122633033505 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int print_vector(const igraph_vector_t *v) { long int i, n = igraph_vector_size(v); for (i = 0; i < n; i++) { printf("%.2g", (double)VECTOR(*v)[i]); if (i != n - 1) { printf(" "); } } printf("\n"); return 0; } int print_matrix(const igraph_matrix_t *m) { long int i, j, nrow = igraph_matrix_nrow(m), ncol = igraph_matrix_ncol(m); for (i = 0; i < nrow; i++) { for (j = 0; j < ncol; j++) { printf("%.2g", (double)MATRIX(*m, i, j)); if (j != ncol - 1) { printf(" "); } } printf("\n"); } return 0; } int main() { igraph_t g; igraph_matrix_t merges; igraph_vector_t membership; igraph_vector_t x; igraph_arpack_options_t options; /* Zachary Karate club */ igraph_small(&g, 0, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 0, 7, 0, 8, 0, 10, 0, 11, 0, 12, 0, 13, 0, 17, 0, 19, 0, 21, 0, 31, 1, 2, 1, 3, 1, 7, 1, 13, 1, 17, 1, 19, 1, 21, 1, 30, 2, 3, 2, 7, 2, 8, 2, 9, 2, 13, 2, 27, 2, 28, 2, 32, 3, 7, 3, 12, 3, 13, 4, 6, 4, 10, 5, 6, 5, 10, 5, 16, 6, 16, 8, 30, 8, 32, 8, 33, 9, 33, 13, 33, 14, 32, 14, 33, 15, 32, 15, 33, 18, 32, 18, 33, 19, 33, 20, 32, 20, 33, 22, 32, 22, 33, 23, 25, 23, 27, 23, 29, 23, 32, 23, 33, 24, 25, 24, 27, 24, 31, 25, 31, 26, 29, 26, 33, 27, 33, 28, 31, 28, 33, 29, 32, 29, 33, 30, 32, 30, 33, 31, 32, 31, 33, 32, 33, -1); igraph_matrix_init(&merges, 0, 0); igraph_vector_init(&membership, 0); igraph_vector_init(&x, 0); igraph_arpack_options_init(&options); igraph_community_leading_eigenvector(&g, /*weights=*/ 0, &merges, &membership, 1, &options, /*modularity=*/ 0, /*start=*/ 0, /*eigenvalues=*/ 0, /*eigenvectors=*/ 0, /*history=*/ 0, /*callback=*/ 0, /*callback_extra=*/ 0); print_matrix(&merges); print_vector(&membership); printf("\n"); /* Make all the steps */ igraph_community_leading_eigenvector(&g, /*weights=*/ 0, &merges, &membership, igraph_vcount(&g), &options, /*modularity=*/ 0, /*start=*/ 0, /*eigenvalues=*/ 0, /*eigenvectors=*/ 0, /*history=*/ 0, /*callback=*/ 0, /*callback_extra=*/ 0); print_matrix(&merges); print_vector(&membership); igraph_vector_destroy(&x); igraph_vector_destroy(&membership); igraph_matrix_destroy(&merges); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/cattributes2.out0000644000076500000240000001515113524616144027073 0ustar tamasstaff00000000000000Creator "igraph version @VERSION@ " Version 1 graph [ directed 0 name "Petersen's graph" vertices 10 edges 15 famous 1 node [ id 1 name "foo" isfirst 1 ] node [ id 2 name "foobar" isfirst 0 ] node [ id 3 name "" isfirst 0 ] node [ id 4 name "" isfirst 0 ] node [ id 5 name "" isfirst 0 ] node [ id 6 name "" isfirst 0 ] node [ id 7 name "" isfirst 0 ] node [ id 8 name "" isfirst 0 ] node [ id 9 name "" isfirst 0 ] node [ id 10 name "" isfirst 0 ] edge [ source 2 target 1 id 1 name "FOO" isfirst 1 ] edge [ source 5 target 1 id 2 name "FOOBAR" isfirst 0 ] edge [ source 6 target 1 id 3 name "" isfirst 0 ] edge [ source 3 target 2 id 4 name "" isfirst 0 ] edge [ source 7 target 2 id 5 name "" isfirst 0 ] edge [ source 4 target 3 id 6 name "" isfirst 0 ] edge [ source 8 target 3 id 7 name "" isfirst 0 ] edge [ source 5 target 4 id 8 name "" isfirst 0 ] edge [ source 9 target 4 id 9 name "" isfirst 0 ] edge [ source 10 target 5 id 10 name "" isfirst 0 ] edge [ source 8 target 6 id 11 name "" isfirst 0 ] edge [ source 9 target 6 id 12 name "" isfirst 0 ] edge [ source 9 target 7 id 13 name "" isfirst 0 ] edge [ source 10 target 7 id 14 name "" isfirst 0 ] edge [ source 10 target 8 id 15 name "" isfirst 0 ] ] Petersen's graph 10 15 true 1 foo true 2 foobar false 3 false 4 false 5 false 6 false 7 false 8 false 9 false 10 false 1 FOO true 2 FOOBAR false 3 false 4 false 5 false 6 false 7 false 8 false 9 false 10 false 11 false 12 false 13 false 14 false 15 false python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_k_regular_game.c0000644000076500000240000001407213612122633030363 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_vector_t deg; igraph_bool_t is_simple; igraph_set_error_handler(&igraph_error_handler_ignore); igraph_vector_init(°, 0); /* k-regular undirected graph, even degrees, no multiple edges */ igraph_k_regular_game(&g, 10, 4, 0, 0); igraph_degree(&g, °, igraph_vss_all(), IGRAPH_ALL, 1); igraph_vector_print(°); igraph_is_simple(&g, &is_simple); if (!is_simple) { return 1; } if (igraph_is_directed(&g)) { return 1; } igraph_destroy(&g); /* k-regular undirected graph, odd degrees, even number of vertices, no multiple edges */ igraph_k_regular_game(&g, 10, 3, 0, 0); igraph_degree(&g, °, igraph_vss_all(), IGRAPH_ALL, 1); igraph_vector_print(°); igraph_is_simple(&g, &is_simple); if (!is_simple) { return 2; } if (igraph_is_directed(&g)) { return 2; } igraph_destroy(&g); /* k-regular undirected graph, odd degrees, odd number of vertices, no multiple edges */ if (!igraph_k_regular_game(&g, 9, 3, 0, 0)) { return 3; } /* k-regular undirected graph, even degrees, multiple edges */ igraph_k_regular_game(&g, 10, 4, 0, 1); igraph_degree(&g, °, igraph_vss_all(), IGRAPH_ALL, 1); igraph_vector_print(°); if (igraph_is_directed(&g)) { return 14; } igraph_destroy(&g); /* k-regular undirected graph, odd degrees, even number of vertices, multiple edges */ igraph_k_regular_game(&g, 10, 3, 0, 1); igraph_degree(&g, °, igraph_vss_all(), IGRAPH_ALL, 1); igraph_vector_print(°); if (igraph_is_directed(&g)) { return 15; } igraph_destroy(&g); /* k-regular undirected graph, odd degrees, odd number of vertices, multiple edges */ if (!igraph_k_regular_game(&g, 9, 3, 0, 1)) { return 4; } /* k-regular directed graph, even degrees, no multiple edges */ igraph_k_regular_game(&g, 10, 4, 1, 0); igraph_degree(&g, °, igraph_vss_all(), IGRAPH_IN, 1); igraph_vector_print(°); igraph_degree(&g, °, igraph_vss_all(), IGRAPH_OUT, 1); igraph_vector_print(°); igraph_is_simple(&g, &is_simple); if (!is_simple) { return 5; } if (!igraph_is_directed(&g)) { return 5; } igraph_destroy(&g); /* k-regular directed graph, odd degrees, even number of vertices, no multiple edges */ igraph_k_regular_game(&g, 10, 3, 1, 0); igraph_degree(&g, °, igraph_vss_all(), IGRAPH_IN, 1); igraph_vector_print(°); igraph_degree(&g, °, igraph_vss_all(), IGRAPH_OUT, 1); igraph_vector_print(°); igraph_is_simple(&g, &is_simple); if (!is_simple) { return 6; } if (!igraph_is_directed(&g)) { return 6; } igraph_destroy(&g); /* k-regular directed graph, odd degrees, odd number of vertices, no multiple edges */ igraph_k_regular_game(&g, 9, 3, 1, 0); igraph_degree(&g, °, igraph_vss_all(), IGRAPH_IN, 1); igraph_vector_print(°); igraph_degree(&g, °, igraph_vss_all(), IGRAPH_OUT, 1); igraph_vector_print(°); igraph_is_simple(&g, &is_simple); if (!is_simple) { return 7; } if (!igraph_is_directed(&g)) { return 7; } igraph_destroy(&g); /* k-regular directed graph, even degrees, multiple edges */ igraph_k_regular_game(&g, 10, 4, 1, 1); igraph_degree(&g, °, igraph_vss_all(), IGRAPH_IN, 1); igraph_vector_print(°); igraph_degree(&g, °, igraph_vss_all(), IGRAPH_OUT, 1); igraph_vector_print(°); if (!igraph_is_directed(&g)) { return 16; } igraph_destroy(&g); /* k-regular directed graph, odd degrees, even number of vertices, multiple edges */ igraph_k_regular_game(&g, 10, 3, 1, 1); igraph_degree(&g, °, igraph_vss_all(), IGRAPH_IN, 1); igraph_vector_print(°); igraph_degree(&g, °, igraph_vss_all(), IGRAPH_OUT, 1); igraph_vector_print(°); if (!igraph_is_directed(&g)) { return 17; } igraph_destroy(&g); /* k-regular directed graph, odd degrees, odd number of vertices, multiple edges */ igraph_k_regular_game(&g, 9, 3, 1, 1); igraph_degree(&g, °, igraph_vss_all(), IGRAPH_IN, 1); igraph_vector_print(°); igraph_degree(&g, °, igraph_vss_all(), IGRAPH_OUT, 1); igraph_vector_print(°); if (!igraph_is_directed(&g)) { return 18; } igraph_destroy(&g); /* k-regular undirected graph, too large degree, no multiple edges */ if (!igraph_k_regular_game(&g, 10, 10, 0, 0)) { return 8; } /* k-regular directed graph, too large degree, no multiple edges */ if (!igraph_k_regular_game(&g, 10, 10, 1, 0)) { return 9; } /* empty graph */ if (igraph_k_regular_game(&g, 0, 0, 0, 0)) { return 10; } if (igraph_vcount(&g) != 0 || igraph_ecount(&g) != 0 || igraph_is_directed(&g)) { return 11; } igraph_destroy(&g); if (igraph_k_regular_game(&g, 0, 0, 1, 0)) { return 12; } if (igraph_vcount(&g) != 0 || igraph_ecount(&g) != 0 || !igraph_is_directed(&g)) { return 13; } igraph_destroy(&g); igraph_vector_destroy(°); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/graphml.c0000644000076500000240000001302013612122633025507 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include /* unlink */ void custom_warning_handler (const char *reason, const char *file, int line, int igraph_errno) { printf("Warning: %s\n", reason); } void dump_graph(const char* header, const igraph_t* g) { fputs(header, stdout); printf("Vertices: %li\n", (long int) igraph_vcount(g)); printf("Edges: %li\n", (long int) igraph_ecount(g)); printf("Directed: %i\n", (int) igraph_is_directed(g)); igraph_write_graph_edgelist(g, stdout); } void dump_vertex_attribute_bool(const char* name, const igraph_t* g) { long int i, n = igraph_vcount(g); printf("Vertex attribute '%s':", name); for (i = 0; i < n; i++) { printf(" %s", VAB(g, name, i) ? "true" : "false"); } printf("\n"); } void dump_vertex_attribute_numeric(const char* name, const igraph_t* g) { long int i, n = igraph_vcount(g); printf("Vertex attribute '%s':", name); for (i = 0; i < n; i++) { printf(" %g", (float)VAN(g, name, i)); } printf("\n"); } void dump_vertex_attribute_string(const char* name, const igraph_t* g) { long int i, n = igraph_vcount(g); printf("Vertex attribute '%s':", name); for (i = 0; i < n; i++) { printf(" %s", VAS(g, name, i)); } printf("\n"); } int main(int argc, char **argv) { igraph_t g; igraph_error_handler_t* oldhandler; igraph_warning_handler_t* oldwarnhandler; int result; FILE *ifile, *ofile; igraph_i_set_attribute_table(&igraph_cattribute_table); /* GraphML */ ifile = fopen("test.gxl", "r"); if (ifile == 0) { return 10; } oldhandler = igraph_set_error_handler(igraph_error_handler_ignore); oldwarnhandler = igraph_set_warning_handler(custom_warning_handler); if ((result = igraph_read_graph_graphml(&g, ifile, 0))) { /* maybe it is simply disabled at compile-time */ if (result == IGRAPH_UNIMPLEMENTED) { return 77; } return 1; } igraph_set_error_handler(oldhandler); fclose(ifile); /* Write it back */ ofile = fopen("test2.gxl", "w"); /* If we can't create the test file, just skip the test */ if (ofile) { if ((result = igraph_write_graph_graphml(&g, ofile, /*prefixattr=*/ 1))) { return 1; } fclose(ofile); unlink("test2.gxl"); } dump_graph("The directed graph:\n", &g); igraph_destroy(&g); /* The same with undirected graph */ ifile = fopen("test.gxl", "r"); if ((result = igraph_read_graph_graphml(&g, ifile, 0))) { return 1; } fclose(ifile); dump_graph("The undirected graph:\n", &g); igraph_destroy(&g); /* Test a GraphML file with default attributes */ ifile = fopen("graphml-default-attrs.xml", "r"); if ((result = igraph_read_graph_graphml(&g, ifile, 0))) { return 1; } fclose(ifile); dump_graph("The directed graph:\n", &g); dump_vertex_attribute_bool("type", &g); dump_vertex_attribute_string("gender", &g); dump_vertex_attribute_numeric("age", &g); dump_vertex_attribute_bool("retired", &g); igraph_destroy(&g); /* Test a GraphML file with namespaces */ ifile = fopen("graphml-namespace.xml", "r"); if ((result = igraph_read_graph_graphml(&g, ifile, 0))) { return 1; } fclose(ifile); dump_graph("The undirected graph:\n", &g); igraph_destroy(&g); /* Test a not-really-valid GraphML file as it has no namespace information */ ifile = fopen("graphml-lenient.xml", "r"); if ((result = igraph_read_graph_graphml(&g, ifile, 0))) { return 1; } fclose(ifile); dump_graph("The undirected graph:\n", &g); igraph_destroy(&g); /* Test a completely malformed GraphML file */ ifile = fopen("graphml-malformed.xml", "r"); igraph_set_error_handler(igraph_error_handler_ignore); igraph_set_warning_handler(igraph_warning_handler_ignore); result = igraph_read_graph_graphml(&g, ifile, 0); if (result != IGRAPH_PARSEERROR) { return 1; } fclose(ifile); igraph_destroy(&g); /* Restore the old error handler */ igraph_set_error_handler(igraph_error_handler_abort); /* Restore the old warning handler */ igraph_set_warning_handler(oldwarnhandler); /* There were sometimes problems with this file */ /* Only if called from R though, and only on random occasions, once in every ten reads. Do testing here doesn't make much sense, but if we have the file then let's do it anyway. */ ifile = fopen("graphml-hsa05010.xml", "r"); igraph_read_graph_graphml(&g, ifile, 0); fclose(ifile); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_all_st_cuts.out0000644000076500000240000000156613532467671030343 0ustar tamasstaff000000000000002; 2 3 4 8 0; 0 0; 1; 1 1; 1; 0 0 1 0 0 1 0 1 3 0 1 2 0 1 2 3 Partitions and cuts: P: 0 C: 0 P: 0 1 C: 1 2 5 P: 0 1 5 C: 1 2 6 P: 0 1 3 C: 1 4 5 P: 0 1 3 5 C: 1 4 6 P: 0 1 2 C: 2 3 5 P: 0 1 2 5 C: 2 3 6 P: 0 1 2 3 C: 3 4 5 P: 0 1 2 3 5 C: 3 4 6 Partitions and cuts: P: 1 C: 1 Partitions and cuts: P: 0 C: 0 P: 0 1 C: 1 P: 0 1 2 C: 2 P: 0 1 2 3 C: 3 Partitions and cuts: P: 0 C: 0 1 P: 0 2 C: 0 3 P: 0 1 C: 1 2 4 5 6 P: 0 1 6 C: 1 2 4 5 9 P: 0 1 5 C: 1 2 4 6 8 P: 0 1 5 6 C: 1 2 4 8 9 P: 0 1 4 C: 1 2 5 6 7 P: 0 1 4 6 C: 1 2 5 7 9 P: 0 1 4 5 C: 1 2 6 7 8 P: 0 1 4 5 6 C: 1 2 7 8 9 P: 0 1 4 5 6 2 C: 2 3 Cuts only (no partitions): C: 0 1 C: 0 3 C: 1 2 4 5 6 C: 1 2 4 5 9 C: 1 2 4 6 8 C: 1 2 4 8 9 C: 1 2 5 6 7 C: 1 2 5 7 9 C: 1 2 6 7 8 C: 1 2 7 8 9 C: 2 3 Partitions and cuts: P: 0 C: 0 P: 0 1 C: 1 Partitions and cuts: P: 0 C: 0 P: 0 1 C: 1 Partitions and cuts: P: 1 C: 1 P: 1 2 C: 2 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_array.c0000644000076500000240000000454613612122633026542 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include void print_vector(const igraph_vector_t *v, FILE *f) { long int i; for (i = 0; i < igraph_vector_size(v); i++) { fprintf(f, " %li", (long int) VECTOR(*v)[i]); } fprintf(f, "\n"); } void print_array(const igraph_array3_t *a, FILE *f) { long int i, j, k; for (k = 0; k < igraph_array3_n(a, 3); k++) { for (i = 0; i < igraph_array3_n(a, 1); i++) { for (j = 0; j < igraph_array3_n(a, 2); j++) { fprintf(f, " %li", (long int) ARRAY3(*a, i, j, k)); } fprintf(f, "\n"); } fprintf(f, "\n"); } } int main() { igraph_array3_t a; long int i, j, k; long int s = 1; igraph_array3_init(&a, 5, 4, 3); igraph_array3_destroy(&a); igraph_array3_init(&a, 5, 4, 3); print_array(&a, stdout); if (igraph_array3_n(&a, 1) != 5) { return 1; } if (igraph_array3_n(&a, 2) != 4) { return 1; } if (igraph_array3_n(&a, 3) != 3) { return 1; } igraph_array3_destroy(&a); igraph_array3_init(&a, 5, 4, 3); for (k = 0; k < igraph_array3_n(&a, 3); k++) { for (j = 0; j < igraph_array3_n(&a, 2); j++) { for (i = 0; i < igraph_array3_n(&a, 1); i++) { ARRAY3(a, i, j, k) = s++; } } } print_array(&a, stdout); print_vector(&a.data, stdout); igraph_array3_destroy(&a); if (!IGRAPH_FINALLY_STACK_EMPTY) { return 2; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_laplacian.out0000644000076500000240000000202013524616144027725 0ustar tamasstaff00000000000000=== Unnormalized, unweighted, undirected 2 -1 0 0 -1 -1 2 -1 0 0 0 -1 2 -1 0 0 0 -1 2 -1 -1 0 0 -1 2 === 2 -1 0 0 -1 -1 2 -1 0 0 0 -1 2 -1 0 0 0 -1 2 -1 -1 0 0 -1 2 === 2 -1 0 0 -1 -1 3 -2 0 0 0 -2 3 -1 0 0 0 -1 3 -2 -1 0 0 -2 3 === Unnormalized, unweighted, directed 1 -1 0 0 0 0 1 -1 0 0 0 0 1 -1 0 0 0 0 1 -1 -1 0 0 0 1 === 1 -1 0 0 0 0 1 -1 0 0 0 0 1 -1 0 0 0 0 1 -1 -1 0 0 0 1 === 1 -1 0 0 0 0 2 -2 0 0 0 0 1 -1 0 0 0 0 2 -2 -1 0 0 0 1 === Unnormalized, weighted, undirected 6 -1 0 0 -5 -1 3 -2 0 0 0 -2 5 -3 0 0 0 -3 7 -4 -5 0 0 -4 9 === 6 -1 0 0 -5 -1 3 -2 0 0 0 -2 5 -3 0 0 0 -3 7 -4 -5 0 0 -4 9 === 6 -1 0 0 -5 -1 6 -5 0 0 0 -5 8 -3 0 0 0 -3 10 -7 -5 0 0 -7 12 === Unnormalized, weighted, directed 1 -1 0 0 0 0 2 -2 0 0 0 0 3 -3 0 0 0 0 4 -4 -5 0 0 0 5 === 1 -1 0 0 0 0 2 -2 0 0 0 0 3 -3 0 0 0 0 4 -4 -5 0 0 0 5 === 1 -1 0 0 0 0 5 -5 0 0 0 0 3 -3 0 0 0 0 7 -7 -5 0 0 0 5 === Normalized, unweighted, undirected OK === Normalized, unweighted, directed OK === Normalized, weighted, undirected OK === Normalized, weighted, directed OK python-igraph-0.8.0/vendor/source/igraph/examples/simple/pajek_signed.out0000644000076500000240000000263313524616144027104 0ustar tamasstaff00000000000000Vertex 0: id="S65" name="S65" Vertex 1: id="S29" name="S29" Vertex 2: id="S04" name="S04" Vertex 3: id="S75" name="S75" Vertex 4: id="S24" name="S24" Vertex 5: id="S81" name="S81" Vertex 6: id="S51" name="S51" Vertex 7: id="S78" name="S78" Vertex 8: id="S86" name="S86" Vertex 9: id="S39" name="S39" Edge 0 (0-5): weight=1 Edge 1 (0-9): weight=-1 Edge 2 (1-2): weight=1 Edge 3 (1-3): weight=1 Edge 4 (1-5): weight=1 Edge 5 (1-6): weight=1 Edge 6 (1-8): weight=1 Edge 7 (2-0): weight=-1 Edge 8 (2-3): weight=1 Edge 9 (2-6): weight=1 Edge 10 (2-8): weight=1 Edge 11 (3-0): weight=-1 Edge 12 (3-1): weight=1 Edge 13 (3-4): weight=1 Edge 14 (3-5): weight=1 Edge 15 (3-6): weight=1 Edge 16 (3-8): weight=1 Edge 17 (4-1): weight=1 Edge 18 (4-3): weight=1 Edge 19 (4-8): weight=-1 Edge 20 (4-9): weight=-1 Edge 21 (5-0): weight=1 Edge 22 (5-1): weight=-1 Edge 23 (5-7): weight=1 Edge 24 (6-1): weight=-1 Edge 25 (6-2): weight=1 Edge 26 (6-3): weight=1 Edge 27 (6-5): weight=-1 Edge 28 (6-8): weight=1 Edge 29 (7-2): weight=1 Edge 30 (7-3): weight=1 Edge 31 (7-5): weight=1 Edge 32 (7-6): weight=-1 Edge 33 (7-8): weight=1 Edge 34 (7-9): weight=1 Edge 35 (8-9): weight=-1 Edge 36 (9-0): weight=1 Edge 37 (9-1): weight=1 Edge 38 (9-2): weight=1 Edge 39 (9-3): weight=1 Edge 40 (9-4): weight=1 Edge 41 (9-5): weight=1 Edge 42 (9-6): weight=1 Edge 43 (9-7): weight=1 Edge 44 (9-8): weight=1 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_array.out0000644000076500000240000000076313524616144027133 0ustar tamasstaff00000000000000 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 6 11 16 2 7 12 17 3 8 13 18 4 9 14 19 5 10 15 20 21 26 31 36 22 27 32 37 23 28 33 38 24 29 34 39 25 30 35 40 41 46 51 56 42 47 52 57 43 48 53 58 44 49 54 59 45 50 55 60 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 python-igraph-0.8.0/vendor/source/igraph/examples/simple/cattributes3.out0000644000076500000240000001635713524616144027105 0ustar tamasstaff00000000000000 6 4 5 6 4 5 1 4 5 3 4 5 1 4 5 3 4 5 2 4 5 0 0 0 2 4 5 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_bridges.out0000644000076500000240000000000513524616144027421 0ustar tamasstaff00000000000000 3 7 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_deterministic_optimal_imitation.c0000644000076500000240000002330313612122633034061 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* Test suite for deterministic optimal imitation. Copyright (C) 2011 Minh Van Nguyen This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include /* test parameters structure */ typedef struct { igraph_t *graph; igraph_integer_t vertex; igraph_optimal_t optimality; igraph_vector_t *quantities; igraph_vector_t *strategies; igraph_neimode_t mode; int retval; } strategy_test_t; /* Error tests. That is, we expect error codes to be returned from such tests. */ int error_tests() { igraph_t g, h; igraph_vector_t quant, strat; int i, n, ret; strategy_test_t *test; /* nonempty graph */ igraph_small(&g, 0, IGRAPH_UNDIRECTED, 0, 1, 1, 2, 2, 0, -1); igraph_empty(&h, 0, 0); /* empty graph */ igraph_vector_init(&quant, 1); /* quantities vector */ igraph_vector_init(&strat, 2); /* strategies vector */ { /* test parameters */ /*--graph--vertex--optimality--quantities--strategies--mode--retval--*/ /* null pointer for graph */ strategy_test_t null_graph = { NULL, 0, 0, NULL, NULL, IGRAPH_ALL, IGRAPH_EINVAL }; /* null pointer for quantities vector */ strategy_test_t null_quant = { &g, 0, 0, NULL, NULL, IGRAPH_ALL, IGRAPH_EINVAL }; /* null pointer for strategies vector */ strategy_test_t null_strat = { &g, 0, 0, &quant, NULL, IGRAPH_ALL, IGRAPH_EINVAL }; /* empty graph */ strategy_test_t empty_graph = {&h, 0, 0, &quant, &strat, IGRAPH_ALL, IGRAPH_EINVAL }; /* length of quantities vector different from number of vertices */ strategy_test_t qdiff_length = {&g, 0, 0, &quant, &strat, IGRAPH_ALL, IGRAPH_EINVAL }; /* length of strategies vector different from number of vertices */ strategy_test_t sdiff_length = {&g, 0, 0, &quant, &strat, IGRAPH_ALL, IGRAPH_EINVAL }; strategy_test_t *all_checks[] = {/* 1 */ &null_graph, /* 2 */ &null_quant, /* 3 */ &null_strat, /* 4 */ &empty_graph, /* 5 */ &qdiff_length, /* 6 */ &sdiff_length }; n = 6; /* Run the error tests. We expect an error to be raised for each test. */ igraph_set_error_handler(igraph_error_handler_ignore); i = 0; while (i < n) { test = all_checks[i]; ret = igraph_deterministic_optimal_imitation(test->graph, test->vertex, test->optimality, test->quantities, test->strategies, test->mode); if (ret != test->retval) { printf("Error test no. %d failed.\n", (int)(i + 1)); return IGRAPH_FAILURE; } i++; } } /* clean up */ igraph_destroy(&g); igraph_destroy(&h); igraph_vector_destroy(&quant); igraph_vector_destroy(&strat); return IGRAPH_SUCCESS; } /* Updating the strategy of an isolated vertex. In this case, the strategies * vector should not change at all. */ int isolated_vertex_test() { igraph_t g; igraph_vector_t quant, strat, v; int i, ret; /* graph with one isolated vertex */ igraph_small(&g, 0, IGRAPH_UNDIRECTED, 0, 1, 1, 2, 2, 0, -1); igraph_add_vertices(&g, 1, 0); /* new vertex 3 is isolated */ /* quantities vector: all vertices have the same fitness */ igraph_vector_init_real(&quant, 4, 0.25, 0.25, 0.25, 0.25); /* strategies vector: 0 means aggressive strategy; 1 means passive */ igraph_vector_init_real(&strat, 4, 1., 0., 1., 0.); /* make a copy of the original strategies vector for comparison later on */ igraph_vector_copy(&v, &strat); /* Now update strategy of vertex 3. Since this vertex is isolated, no */ /* strategy update would take place. The resulting strategies vector */ /* would be the same as it was originally. */ ret = igraph_deterministic_optimal_imitation(/*graph*/ &g, /*vertex*/ 3, /*optimality*/ IGRAPH_MAXIMUM, /*quantities*/ &quant, /*strategies*/ &strat, /*mode*/ IGRAPH_ALL); if (ret) { printf("Isolated vertex test failed.\n"); return IGRAPH_FAILURE; } for (i = 0; i < igraph_vector_size(&strat); i++) { if (VECTOR(strat)[i] != VECTOR(v)[i]) { printf("Isolated vertex test failed.\n"); return IGRAPH_FAILURE; } } /* clean up */ igraph_destroy(&g); igraph_vector_destroy(&quant); igraph_vector_destroy(&strat); igraph_vector_destroy(&v); return IGRAPH_SUCCESS; } /* A game on the Petersen graph. This graph has 10 vertices and 15 edges. * The Petersen graph is initialized with a default quantities vector and a * default strategies vector. For each vertex v in the graph, we update the * strategy of v via deterministic optimal imitation. The resulting updated * strategies vector is compared with the known result vector. A mismatch would * raise an error code. If the updated strategies vector matches the known * result vector, we reset the strategies vector to its default state and * repeat the game with another vertex. */ int petersen_game_test() { igraph_t g; igraph_vector_t known_max_v, known_min_v, quant, strat, stratcopy; int i, nvert; /* the Petersen graph */ igraph_small(&g, /*n=*/ 0, IGRAPH_UNDIRECTED, 0, 1, 0, 4, 0, 5, 1, 2, 1, 6, 2, 3, 2, 7, 3, 4, 3, 8, 4, 9, 5, 7, 5, 8, 6, 8, 6, 9, 7, 9, -1); nvert = igraph_vcount(&g); /* Strategies vector, one strategy for each vertex. Thus vec[i] is the */ /* strategy of vertex i. The strategy space is: {0, 1, 2, 3}. */ igraph_vector_init_real(&strat, nvert, 1., 1., 2., 2., 0., 0., 0., 1., 2., 3.); /* Quantities vector, one quantity per vertex. Thus vec[i] is the */ /* quantity for vertex i. */ igraph_vector_init_real(&quant, nvert, 0.3, 1.1, 0.5, 1.0, 0.9, 0.8, 0.4, 0.1, 0.7, 0.7); /* Known strategies that would be adopted. Thus vec[i] means that in */ /* game i where we revise the strategy of vertex i, the strategy */ /* vec[i] would be adopted by i. */ /*maximum deterministic imitation*/ igraph_vector_init_real(&known_max_v, nvert, 1., 1., 1., 2., 2., 0., 1., 0., 2., 0.); /*minimum deterministic imitation*/ igraph_vector_init_real(&known_min_v, nvert, 1., 1., 1., 2., 1., 1., 0., 1., 0., 1.); /* play game and compare resulting updated strategies */ for (i = 0; i < nvert; i++) { /* maximum deterministic imitation */ igraph_vector_copy(&stratcopy, &strat); igraph_deterministic_optimal_imitation(/*graph*/ &g, /*vertex*/ (igraph_integer_t)i, /*optimality*/ IGRAPH_MAXIMUM, /*quantities*/ &quant, /*strategies*/ &stratcopy, /*neighbours*/ IGRAPH_ALL); if (VECTOR(stratcopy)[i] != VECTOR(known_max_v)[i]) { printf("Maximum deterministic imitation failed for vertex %d.\n", i); return IGRAPH_FAILURE; } igraph_vector_destroy(&stratcopy); /* minimum deterministic imitation */ igraph_vector_copy(&stratcopy, &strat); igraph_deterministic_optimal_imitation(/*graph*/ &g, /*vertex*/ (igraph_integer_t)i, /*optimality*/ IGRAPH_MINIMUM, /*quantities*/ &quant, /*strategies*/ &stratcopy, /*neighbours*/ IGRAPH_ALL); if (VECTOR(stratcopy)[i] != VECTOR(known_min_v)[i]) { printf("Minimum deterministic imitation failed for vertex %d.\n", i); return IGRAPH_FAILURE; } igraph_vector_destroy(&stratcopy); } /* clean up */ igraph_destroy(&g); igraph_vector_destroy(&known_max_v); igraph_vector_destroy(&known_min_v); igraph_vector_destroy(&quant); igraph_vector_destroy(&strat); return IGRAPH_SUCCESS; } int main() { int ret; ret = error_tests(); if (ret) { return ret; } ret = isolated_vertex_test(); if (ret) { return ret; } ret = petersen_game_test(); if (ret) { return ret; } return IGRAPH_SUCCESS; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/d_indheap.c0000644000076500000240000000620313612122633025775 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include "igraph_types_internal.h" int main() { igraph_d_indheap_t h; long int idx1, idx2; /* igraph_d_indheap_init, igraph_d_indheap_destroy */ igraph_d_indheap_init(&h, 0); igraph_d_indheap_destroy(&h); igraph_d_indheap_init(&h, 100); igraph_d_indheap_destroy(&h); /* igraph_d_indheap_empty, igraph_d_indheap_size */ igraph_d_indheap_init(&h, 10); if (!igraph_d_indheap_empty(&h)) { return 1; } if (igraph_d_indheap_size(&h) != 0) { return 2; } igraph_d_indheap_push(&h, 10, 0, 0); if (igraph_d_indheap_empty(&h)) { return 3; } if (igraph_d_indheap_size(&h) != 1) { return 4; } /* igraph_d_indheap_push */ igraph_d_indheap_push(&h, 9, 9, 8); igraph_d_indheap_push(&h, 3, 3, 2); igraph_d_indheap_push(&h, 2, 2, 1); igraph_d_indheap_push(&h, 1, 1, 0); igraph_d_indheap_push(&h, 7, 7, 6); igraph_d_indheap_push(&h, 4, 4, 3); igraph_d_indheap_push(&h, 0, 0, 1); igraph_d_indheap_push(&h, 6, 6, 5); igraph_d_indheap_push(&h, 5, 5, 4); igraph_d_indheap_push(&h, 8, 8, 7); /* igraph_d_indheap_max, igraph_d_indheap_delete_max */ while (!igraph_d_indheap_empty(&h)) { printf("% li", (long int)igraph_d_indheap_max(&h)); printf("% li\n", (long int)igraph_d_indheap_delete_max(&h)); } /* igraph_d_indheap_reserve */ igraph_d_indheap_reserve(&h, 5); igraph_d_indheap_reserve(&h, 20); igraph_d_indheap_reserve(&h, 0); igraph_d_indheap_reserve(&h, 3); /* igraph_d_indheap_max_index */ igraph_d_indheap_push(&h, 0, 0, 1); igraph_d_indheap_push(&h, 8, 8, 7); igraph_d_indheap_push(&h, 2, 2, 1); igraph_d_indheap_push(&h, 7, 7, 6); igraph_d_indheap_push(&h, 9, 9, 8); igraph_d_indheap_push(&h, 4, 4, 3); igraph_d_indheap_push(&h, 3, 3, 2); igraph_d_indheap_push(&h, 5, 5, 4); igraph_d_indheap_push(&h, 1, 1, 0); igraph_d_indheap_push(&h, 6, 6, 5); while (!igraph_d_indheap_empty(&h)) { igraph_d_indheap_max_index(&h, &idx1, &idx2); printf(" %li %li", idx1, idx2); igraph_d_indheap_delete_max(&h); } printf("\n"); igraph_d_indheap_destroy(&h); if (IGRAPH_FINALLY_STACK_SIZE() != 0) { return 5; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_convergence_degree.out0000644000076500000240000000015713524616144031623 0ustar tamasstaff000000000000000.0000 0.0000 0.6000 0.0000 0.6000 0.6000 0.1429 0.6667 0.6667 0.0000 -0.3333 -0.3333 -0.3333 -0.3333 0.6667 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_difference.out0000644000076500000240000000021713524616144030101 0ustar tamasstaff00000000000000subtract itself subtract itself, undirected subtract empty 0 1 1 2 2 1 4 5 real example 1 2 4 5 8 9 real example, undirected 1 2 8 9 8 11 8 12 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_bipartite_projection.c0000644000076500000240000001314213612122633031633 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2008-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int check_projection(const igraph_t *graph, const igraph_vector_bool_t *types, const igraph_t *proj1, const igraph_t *proj2) { igraph_integer_t vcount1, ecount1, vcount2, ecount2; igraph_bipartite_projection_size(graph, types, &vcount1, &ecount1, &vcount2, &ecount2); if (proj1 && igraph_vcount(proj1) != vcount1) { exit(10); } if (proj1 && igraph_ecount(proj1) != ecount1) { exit(11); } if (proj2 && igraph_vcount(proj2) != vcount2) { exit(12); } if (proj2 && igraph_ecount(proj2) != ecount2) { exit(13); } return 0; } int main() { igraph_t g, p1, p2, full, ring; igraph_vector_bool_t types; igraph_bool_t iso; long int i, m2 = 0, w, f, t; igraph_vector_t mult1, mult2; /*******************************************************/ /* Full bipartite graph -> full graphs */ /*******************************************************/ igraph_vector_bool_init(&types, 0); igraph_full_bipartite(&g, &types, 5, 3, /*directed=*/ 0, /*mode=*/ IGRAPH_ALL); /* Get both projections */ igraph_bipartite_projection(&g, &types, &p1, &p2, 0, 0, /*probe1=*/ -1); check_projection(&g, &types, &p1, &p2); /* Check first projection */ igraph_full(&full, igraph_vcount(&p1), /*directed=*/0, /*loops=*/0); igraph_isomorphic_bliss(&p1, &full, 0, 0, &iso, 0, 0, IGRAPH_BLISS_FM, 0, 0); if (!iso) { return 1; } igraph_destroy(&full); /* Check second projection */ igraph_full(&full, igraph_vcount(&p2), /*directed=*/0, /*loops=*/0); igraph_isomorphic_bliss(&p2, &full, 0, 0, &iso, 0, 0, IGRAPH_BLISS_FM, 0, 0); if (!iso) { return 2; } igraph_destroy(&full); igraph_destroy(&p1); igraph_destroy(&p2); igraph_destroy(&g); igraph_vector_bool_destroy(&types); /*******************************************************/ /* More sophisticated test */ /*******************************************************/ igraph_ring(&g, 100, /*directed=*/ 1, /*mutual=*/ 1, /*circular=*/ 1); igraph_vector_bool_init(&types, igraph_vcount(&g)); for (i = 0; i < igraph_vector_bool_size(&types); i++) { VECTOR(types)[i] = i % 2 ? 0 : 1; } /* Get both projections */ igraph_bipartite_projection(&g, &types, &p1, &p2, 0, 0, /*probe1=*/ -1); check_projection(&g, &types, &p1, &p2); /* Check first projection */ igraph_ring(&ring, igraph_vcount(&g) / 2, /*directed=*/ 0, /*mutual=*/ 0, /*circular=*/ 1); igraph_isomorphic_bliss(&p1, &ring, 0, 0, &iso, 0, 0, IGRAPH_BLISS_FM, 0, 0); if (!iso) { return 1; } /* Check second projection */ igraph_isomorphic_bliss(&p2, &ring, 0, 0, &iso, 0, 0, IGRAPH_BLISS_FM, 0, 0); if (!iso) { return 2; } igraph_destroy(&ring); igraph_destroy(&p1); igraph_destroy(&p2); igraph_destroy(&g); igraph_vector_bool_destroy(&types); /*******************************************************/ /* Multiplicity test */ /*******************************************************/ igraph_small(&g, 10, IGRAPH_UNDIRECTED, 0, 8, 1, 8, 2, 8, 3, 8, 4, 8, 4, 9, 5, 9, 6, 9, 7, 9, 0, 9, -1); igraph_vector_bool_init(&types, igraph_vcount(&g)); igraph_vector_bool_fill(&types, 1); VECTOR(types)[8] = VECTOR(types)[9] = 0; igraph_vector_init(&mult1, 0); igraph_vector_init(&mult2, 0); igraph_bipartite_projection(&g, &types, &p1, &p2, &mult1, &mult2, /*probe=*/ -1); check_projection(&g, &types, &p1, &p2); if (igraph_vector_size(&mult1) != igraph_ecount(&p1)) { return 21; } if (igraph_vector_size(&mult2) != igraph_ecount(&p2)) { return 22; } if (VECTOR(mult1)[0] != 2) { return 23; } for (i = 0; i < igraph_vector_size(&mult2); i++) { if (VECTOR(mult2)[i] != 1 && VECTOR(mult2)[i] != 2) { return 24; } if (VECTOR(mult2)[i] == 2) { m2++; w = i; } } if (m2 != 1) { return 25; } f = IGRAPH_FROM(&p2, w); t = IGRAPH_TO(&p2, w); if (fmin(f, t) != 0 || fmax(f, t) != 4) { return 26; } igraph_vector_destroy(&mult1); igraph_vector_destroy(&mult2); igraph_destroy(&p1); igraph_destroy(&p2); igraph_destroy(&g); igraph_vector_bool_destroy(&types); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_weighted_adjacency.out0000644000076500000240000000041613524616144031611 0ustar tamasstaff000000000000000 --> 1: 1 0 --> 2: 2 1 --> 0: 2 1 --> 3: 1 2 --> 2: 1 3 --> 1: 1 0 --- 1: 1 0 --- 2: 2 1 --- 3: 1 2 --- 2: 1 0 --- 1: 2 2 --- 2: 1 1 --- 3: 1 0 --- 1: 1 1 --- 3: 1 2 --- 2: 1 0 --- 1: 2 0 --- 2: 2 1 --- 3: 1 2 --- 2: 1 0 --- 1: 3 0 --- 2: 2 1 --- 3: 2 2 --- 2: 1 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_scg_grouping4.out0000644000076500000240000000012013524616144030552 0ustar tamasstaff000000000000000 2 2 1 1 1 1 1 1 1 0 2 2 1 1 1 1 1 1 1 0 2 2 1 1 1 1 1 1 1 0 3 3 2 1 1 1 1 1 1 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_community_multilevel.out0000644000076500000240000000156413524616144032303 0ustar tamasstaff00000000000000Modularities: 0.346301 0.392219 0 0 0 1 0 0 1 1 2 2 2 3 2 3 2 2 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 Modularities: 0.875758 0.887879 0 0 0 0 0 1 1 1 1 1 2 2 2 2 2 3 3 3 3 3 4 4 4 4 4 5 5 5 5 5 6 6 6 6 6 7 7 7 7 7 8 8 8 8 8 9 9 9 9 9 10 10 10 10 10 11 11 11 11 11 12 12 12 12 12 13 13 13 13 13 14 14 14 14 14 15 15 15 15 15 16 16 16 16 16 17 17 17 17 17 18 18 18 18 18 19 19 19 19 19 20 20 20 20 20 21 21 21 21 21 22 22 22 22 22 23 23 23 23 23 24 24 24 24 24 25 25 25 25 25 26 26 26 26 26 27 27 27 27 27 28 28 28 28 28 29 29 29 29 29 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 9 9 10 10 10 10 10 10 10 10 10 10 11 11 11 11 11 11 11 11 11 11 12 12 12 12 12 12 12 12 12 12 13 13 13 13 13 13 13 13 13 13 14 14 14 14 14 14 14 14 14 14 python-igraph-0.8.0/vendor/source/igraph/examples/simple/wikti_en_V_syn.elist0000644000076500000240000023235713524616144027771 0ustar 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7304 7306 7307 7308 7310 7311 7313 7314 7316 7317 7321 7322 7323 7324 7326 7327 7332 7333 7332 7334 7335 7336 7335 7337 7335 7338 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_eigen_matrix2.out0000644000076500000240000000020313524616144030537 0ustar tamasstaff0000000000000049.9655+0i 0.376489+0i 0.280558+0i 0.344153+0i 0.252112+0i 0.265478+0i 0.372991+0i 0.367542+0i 0.289639+0i 0.280074+0i 0.300868+0i python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_has_multiple.c0000644000076500000240000000514513612122633030106 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void print_vector(igraph_vector_bool_t *v, FILE *f) { long int i; for (i = 0; i < igraph_vector_bool_size(v); i++) { fprintf(f, " %i", (int) VECTOR(*v)[i]); } fprintf(f, "\n"); } int main() { igraph_t graph; igraph_bool_t res; igraph_small(&graph, 0, IGRAPH_DIRECTED, 0, 1, 1, 2, 2, 1, 0, 1, 1, 0, 3, 4, 11, 10, -1); igraph_has_multiple(&graph, &res); if (!res) { return 1; } igraph_destroy(&graph); igraph_small(&graph, 0, IGRAPH_UNDIRECTED, 0, 0, 1, 2, 1, 1, 2, 2, 2, 1, 2, 3, 2, 4, 2, 5, 2, 6, 2, 2, 3, 2, 0, 0, 6, 2, 2, 2, 0, 0, -1); igraph_has_multiple(&graph, &res); if (!res) { return 2; } igraph_destroy(&graph); igraph_small(&graph, 0, IGRAPH_DIRECTED, 0, 1, 1, 2, 2, 1, 1, 0, 3, 4, 11, 10, -1); igraph_has_multiple(&graph, &res); if (res) { return 3; } igraph_destroy(&graph); igraph_small(&graph, 0, IGRAPH_UNDIRECTED, 0, 0, 1, 2, 1, 1, 2, 2, 2, 3, 2, 4, 2, 5, 2, 6, 2, 2, -1); igraph_has_multiple(&graph, &res); if (!res) { return 4; } igraph_destroy(&graph); igraph_small(&graph, 0, IGRAPH_UNDIRECTED, 0, 0, 1, 2, 1, 1, 2, 2, 2, 3, 2, 4, 2, 5, 2, 6, -1); igraph_has_multiple(&graph, &res); if (res) { return 5; } igraph_destroy(&graph); igraph_small(&graph, 0, IGRAPH_UNDIRECTED, 0, 1, 0, 1, 1, 2, -1); igraph_has_multiple(&graph, &res); if (!res) { return 6; } igraph_destroy(&graph); igraph_small(&graph, 0, IGRAPH_UNDIRECTED, 0, 0, 0, 0, -1); igraph_has_multiple(&graph, &res); if (!res) { return 7; } igraph_destroy(&graph); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_diameter.c0000644000076500000240000000355313612122633027213 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void print_vector(igraph_vector_t *v) { long int i, n = igraph_vector_size(v); for (i = 0; i < n; i++) { printf(" %li", (long int) VECTOR(*v)[i]); } printf("\n"); } int main() { igraph_t g; igraph_integer_t result; igraph_integer_t from, to; igraph_vector_t path; igraph_barabasi_game(&g, 30, /*power=*/ 1, 30, 0, 0, /*A=*/ 1, IGRAPH_DIRECTED, IGRAPH_BARABASI_BAG, /*start_from=*/ 0); igraph_diameter(&g, &result, 0, 0, 0, IGRAPH_UNDIRECTED, 1); /* printf("Diameter: %li\n", (long int) result); */ igraph_destroy(&g); igraph_ring(&g, 10, IGRAPH_DIRECTED, 0, 0); igraph_vector_init(&path, 0); igraph_diameter(&g, &result, &from, &to, &path, IGRAPH_DIRECTED, 1); printf("diameter: %li, from %li to %li\n", (long int) result, (long int) from, (long int) to); print_vector(&path); igraph_vector_destroy(&path); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_complex.c0000644000076500000240000001415113614300625027065 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #define ARE 4 #define AIM 5 #define BRE 6 #define BIM 2 int main() { igraph_complex_t a = igraph_complex(ARE, AIM); igraph_complex_t b = igraph_complex(BRE, BIM); igraph_complex_t c, d, e; /* polar, mod, arg */ c = igraph_complex_polar(igraph_complex_mod(a), igraph_complex_arg(a)); if (!igraph_complex_eq_tol(a, c, 1e-14)) { return 1; } /* add */ c = igraph_complex_add(a, b); if (IGRAPH_REAL(c) != ARE + BRE || IGRAPH_IMAG(c) != AIM + BIM) { return 2; } /* sub */ c = igraph_complex_sub(a, b); if (IGRAPH_REAL(c) != ARE - BRE || IGRAPH_IMAG(c) != AIM - BIM) { return 3; } /* mul */ c = igraph_complex_mul(a, b); if (IGRAPH_REAL(c) != ARE * BRE - AIM * BIM || IGRAPH_IMAG(c) != ARE * BIM + AIM * BRE) { return 4; } /* div */ c = igraph_complex_div(a, b); c = igraph_complex_mul(c, b); if (!igraph_complex_eq_tol(a, c, 1e-14)) { return 5; } /* add_real */ c = igraph_complex_add_real(a, IGRAPH_REAL(b)); if (IGRAPH_REAL(c) != IGRAPH_REAL(a) + IGRAPH_REAL(b)) { return 6; } if (IGRAPH_IMAG(c) != IGRAPH_IMAG(a)) { return 7; } /* add_imag */ c = igraph_complex_add_imag(a, IGRAPH_IMAG(b)); if (IGRAPH_REAL(c) != IGRAPH_REAL(a)) { return 8; } if (IGRAPH_IMAG(c) != IGRAPH_IMAG(a) + IGRAPH_IMAG(b)) { return 9; } /* sub_real */ c = igraph_complex_sub_real(a, IGRAPH_REAL(b)); if (IGRAPH_REAL(c) != IGRAPH_REAL(a) - IGRAPH_REAL(b)) { return 10; } if (IGRAPH_IMAG(c) != IGRAPH_IMAG(a)) { return 11; } /* sub_imag */ c = igraph_complex_sub_imag(a, IGRAPH_IMAG(b)); if (IGRAPH_REAL(c) != IGRAPH_REAL(a)) { return 12; } if (IGRAPH_IMAG(c) != IGRAPH_IMAG(a) - IGRAPH_IMAG(b)) { return 13; } /* mul_real */ c = igraph_complex_mul_real(a, IGRAPH_REAL(b)); if (IGRAPH_REAL(c) != IGRAPH_REAL(a) * IGRAPH_REAL(b)) { return 14; } if (IGRAPH_IMAG(c) != IGRAPH_IMAG(a) * IGRAPH_REAL(b)) { return 15; } /* mul_imag */ c = igraph_complex_mul_imag(a, IGRAPH_REAL(b)); if (IGRAPH_REAL(c) != - IGRAPH_IMAG(a) * IGRAPH_REAL(b)) { return 14; } if (IGRAPH_IMAG(c) != IGRAPH_REAL(a) * IGRAPH_REAL(b)) { return 15; } /* div_real */ c = igraph_complex_div_real(a, IGRAPH_REAL(b)); if (fabs(IGRAPH_REAL(c) - IGRAPH_REAL(a) / IGRAPH_REAL(b)) > 1e-15) { return 16; } if (fabs(IGRAPH_IMAG(c) - IGRAPH_IMAG(a) / IGRAPH_REAL(b)) > 1e-15) { return 17; } /* div_imag */ c = igraph_complex_div_imag(a, IGRAPH_IMAG(b)); if (IGRAPH_REAL(c) != IGRAPH_IMAG(a) / IGRAPH_IMAG(b)) { return 18; } if (IGRAPH_IMAG(c) != - IGRAPH_REAL(a) / IGRAPH_IMAG(b)) { return 19; } /* conj */ c = igraph_complex_conj(a); if (IGRAPH_REAL(c) != ARE || IGRAPH_IMAG(c) != -AIM) { return 20; } /* neg */ c = igraph_complex_neg(a); if (IGRAPH_REAL(c) != - IGRAPH_REAL(a) || IGRAPH_IMAG(c) != - IGRAPH_IMAG(a)) { return 21; } /* inv */ c = igraph_complex_inv(a); d = igraph_complex(1.0, 0.0); e = igraph_complex_div(d, a); if (!igraph_complex_eq_tol(c, e, 1e-14)) { return 22; } /* abs */ if (igraph_complex_abs(a) != igraph_complex_mod(a)) { return 23; } /* logabs */ /* sqrt */ c = igraph_complex_sqrt(a); d = igraph_complex_mul(c, c); if (!igraph_complex_eq_tol(a, d, 1e-14)) { return 24; } /* sqrt_real */ c = igraph_complex_sqrt(igraph_complex(-1.0, 0.0)); d = igraph_complex_sqrt_real(-1.0); if (!igraph_complex_eq_tol(c, d, 1e-14)) { return 25; } /* exp */ c = igraph_complex_exp(igraph_complex(0.0, M_PI)); if (!igraph_complex_eq_tol(c, igraph_complex(-1.0, 0.0), 1e-14)) { return 26; } /* pow */ c = igraph_complex_pow(igraph_complex(M_E, 0.0), igraph_complex(0.0, M_PI)); if (!igraph_complex_eq_tol(c, igraph_complex(-1.0, 0.0), 1e-14)) { return 27; } /* pow_real */ c = igraph_complex_pow_real(a, 2.0); d = igraph_complex_mul(a, a); if (!igraph_complex_eq_tol(c, d, 1e-12)) { return 28; } /* log */ c = igraph_complex_exp(igraph_complex_log(a)); if (!igraph_complex_eq_tol(a, c, 1e-14)) { return 29; } /* log10 */ c = igraph_complex_pow(igraph_complex(10.0, 0), igraph_complex_log10(a)); if (!igraph_complex_eq_tol(a, c, 1e-14)) { return 30; } /* log_b */ c = igraph_complex_pow(b, igraph_complex_log_b(a, b)); if (!igraph_complex_eq_tol(a, c, 1e-14)) { return 31; } /* sin, cos */ c = igraph_complex_sin(a); d = igraph_complex_cos(a); e = igraph_complex_add(igraph_complex_mul(c, c), igraph_complex_mul(d, d)); if (!igraph_complex_eq_tol(e, igraph_complex(1.0, 0.0), 1e-11)) { return 32; } /* tan */ c = igraph_complex_tan(a); d = igraph_complex_div(igraph_complex_sin(a), igraph_complex_cos(a)); if (!igraph_complex_eq_tol(c, d, 1e-14)) { return 33; } /* sec */ /* csc */ /* cot */ return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_correlated_game.c0000644000076500000240000000232413614300625030532 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph R library. Copyright (C) 2003-2013 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g1, g2; igraph_erdos_renyi_game(&g1, IGRAPH_ERDOS_RENYI_GNP, 10, .3, IGRAPH_UNDIRECTED, IGRAPH_NO_LOOPS); igraph_correlated_game(&g1, &g2, .9, .3, /* permutation=*/ 0); igraph_destroy(&g2); igraph_destroy(&g1); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_vs_nonadj.c0000644000076500000240000000352313612122634027400 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main () { igraph_t g; igraph_vs_t vs; igraph_vit_t vit; igraph_integer_t size; /* empty graph, all vertices */ igraph_empty(&g, 10, IGRAPH_DIRECTED); igraph_vs_nonadj(&vs, 0, IGRAPH_ALL); igraph_vs_size(&g, &vs, &size); printf("%li ", (long int) size); igraph_vit_create(&g, vs, &vit); while (!IGRAPH_VIT_END(vit)) { printf("%li ", (long int) IGRAPH_VIT_GET(vit)); IGRAPH_VIT_NEXT(vit); } printf("\n"); igraph_vit_destroy(&vit); igraph_vs_destroy(&vs); igraph_destroy(&g); /* full graph, no vertices */ igraph_full(&g, 10, IGRAPH_UNDIRECTED, IGRAPH_LOOPS); igraph_vs_nonadj(&vs, 0, IGRAPH_ALL); igraph_vit_create(&g, vs, &vit); while (!IGRAPH_VIT_END(vit)) { printf("%li ", (long int) IGRAPH_VIT_GET(vit)); IGRAPH_VIT_NEXT(vit); } printf("\n"); igraph_vit_destroy(&vit); igraph_vs_destroy(&vs); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/edgelist3.dl0000644000076500000240000000022213524616144026124 0ustar tamasstaff00000000000000DL n=5 format = edgelist1 labels: george, sally, jim, billy, jane labels embedded: data: george sally george jim sally jim billy george jane jim python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_cliques.out0000644000076500000240000000051113524616144027451 0ustar tamasstaff000000000000002 cliques found 1 2 3 4 1 2 4 5 12 cliques found 0 3 0 4 0 5 1 2 1 3 1 4 1 5 2 3 2 4 2 5 3 4 4 5 2 cliques found 1 2 3 4 1 2 4 5 29 cliques found 0 1 2 3 4 5 0 3 0 4 0 5 1 2 1 3 1 4 1 5 2 3 2 4 2 5 3 4 4 5 0 3 4 0 4 5 1 2 3 1 2 4 1 2 5 1 3 4 1 4 5 2 3 4 2 4 5 1 2 3 4 1 2 4 5 omega=4 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_is_tree.c0000644000076500000240000000520713612122633027051 0ustar tamasstaff00000000000000 #include #include int main() { igraph_t g; igraph_bool_t res; igraph_integer_t root; /* the null graph is not a tree */ igraph_empty(&g, 0, 0); igraph_is_tree(&g, &res, &root, IGRAPH_ALL); assert(! res); igraph_destroy(&g); /* the single-vertex graph is a tree */ igraph_empty(&g, 1, 0); root = -1; igraph_is_tree(&g, &res, &root, IGRAPH_ALL); assert(res); assert(root == 0); igraph_destroy(&g); /* 4-cycle, not a tree */ igraph_small(&g, 4, 0, 0, 1, 1, 2, 2, 3, 3, 0, -1); igraph_is_tree(&g, &res, &root, IGRAPH_ALL); assert(! res); igraph_destroy(&g); /* disconnected graph with the same number of edges a tree would have */ igraph_small(&g, 4, 0, 0, 1, 1, 2, 0, 2, 3, 4, -1); igraph_is_tree(&g, &res, &root, IGRAPH_ALL); assert(! res); igraph_destroy(&g); /* 3-star, tree */ igraph_small(&g, 4, 0, 0, 1, 0, 2, 0, 3, -1); root = -1; igraph_is_tree(&g, &res, &root, IGRAPH_ALL); assert(res); assert(root == 0); igraph_destroy(&g); /* out-tree */ igraph_small(&g, 4, 1, 0, 1, 1, 2, 1, 3, -1); root = -1; igraph_is_tree(&g, &res, &root, IGRAPH_OUT); assert(res); assert(root == 0); igraph_is_tree(&g, &res, &root, IGRAPH_IN); assert(! res); root = -1; igraph_is_tree(&g, &res, &root, IGRAPH_ALL); assert(res); assert(root == 0); igraph_destroy(&g); /* in-tree */ igraph_small(&g, 4, 1, 0, 1, 2, 1, 1, 3, -1); root = -1; igraph_is_tree(&g, &res, &root, IGRAPH_IN); assert(res); assert(root == 3); igraph_is_tree(&g, &res, &root, IGRAPH_OUT); assert(! res); root = -1; igraph_is_tree(&g, &res, &root, IGRAPH_ALL); assert(res); assert(root == 0); igraph_destroy(&g); /* neither an in-tree, nor an out-ree, but still a tree when ignoring edge-directions */ igraph_small(&g, 6, 1, 0, 1, 1, 2, 2, 3, 4, 1, 2, 5, -1); root = -1; igraph_is_tree(&g, &res, &root, IGRAPH_ALL); assert(res); assert(root == 0); igraph_is_tree(&g, &res, &root, IGRAPH_IN); assert(! res); igraph_is_tree(&g, &res, &root, IGRAPH_OUT); assert(! res); igraph_destroy(&g); /* Regression test, see: * https://github.com/szhorvat/IGraphM/issues/90 * https://github.com/igraph/igraph/pull/1160 */ igraph_small(&g, 5, 0, 0, 3, 0, 4, 1, 3, 1, 4, -1); igraph_is_tree(&g, &res, &root, IGRAPH_ALL); assert(! res); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_bipartite_create.out0000644000076500000240000000004013524616144031307 0ustar tamasstaff000000000000000 1 0 3 1 2 1 4 1 6 3 4 5 6 6 5 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_qsort_r.out0000644000076500000240000000044313524616144027501 0ustar tamasstaff000000000000000 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_feedback_arc_set_ip.c0000644000076500000240000000720213614300625031331 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int main() { igraph_t g; igraph_vector_t weights, result; igraph_bool_t dag; int retval; igraph_vector_init(&result, 0); igraph_set_error_handler(&igraph_error_handler_printignore); /***********************************************************************/ /* Exact solution with integer programming */ /***********************************************************************/ /* Simple unweighted graph */ igraph_small(&g, 0, IGRAPH_DIRECTED, 0, 1, 1, 2, 2, 0, 2, 3, 2, 4, 0, 4, 4, 3, 5, 0, 6, 5, -1); retval = igraph_feedback_arc_set(&g, &result, 0, IGRAPH_FAS_EXACT_IP); if (retval == IGRAPH_UNIMPLEMENTED) { return 77; } igraph_vector_print(&result); igraph_delete_edges(&g, igraph_ess_vector(&result)); igraph_is_dag(&g, &dag); if (!dag) { return 1; } igraph_destroy(&g); /* Simple weighted graph */ igraph_small(&g, 0, IGRAPH_DIRECTED, 0, 1, 1, 2, 2, 0, 2, 3, 2, 4, 0, 4, 4, 3, 5, 0, 6, 5, -1); igraph_vector_init_int_end(&weights, -1, 1, 1, 3, 1, 1, 1, 1, 1, 1, -1); igraph_feedback_arc_set(&g, &result, &weights, IGRAPH_FAS_EXACT_IP); igraph_vector_print(&result); igraph_delete_edges(&g, igraph_ess_vector(&result)); igraph_is_dag(&g, &dag); if (!dag) { return 2; } igraph_vector_destroy(&weights); igraph_destroy(&g); /* Simple unweighted graph with loops */ igraph_small(&g, 0, IGRAPH_DIRECTED, 0, 1, 1, 2, 2, 0, 2, 3, 2, 4, 0, 4, 4, 3, 5, 0, 6, 5, 1, 1, 4, 4, -1); igraph_feedback_arc_set(&g, &result, 0, IGRAPH_FAS_EXACT_IP); igraph_vector_print(&result); igraph_delete_edges(&g, igraph_ess_vector(&result)); igraph_is_dag(&g, &dag); if (!dag) { return 3; } igraph_destroy(&g); /* Disjoint union of two almost identical graphs */ igraph_small(&g, 0, IGRAPH_DIRECTED, 0, 1, 1, 2, 2, 0, 2, 3, 2, 4, 0, 4, 4, 3, 5, 0, 6, 5, 1, 1, 4, 4, 7, 8, 8, 9, 9, 7, 9, 10, 9, 11, 7, 11, 11, 10, 12, 7, 13, 12, -1); igraph_feedback_arc_set(&g, &result, 0, IGRAPH_FAS_EXACT_IP); igraph_vector_print(&result); igraph_delete_edges(&g, igraph_ess_vector(&result)); igraph_is_dag(&g, &dag); if (!dag) { return 4; } igraph_destroy(&g); /* Graph with lots of isolated vertices */ igraph_small(&g, 10000, IGRAPH_DIRECTED, 0, 1, -1); igraph_feedback_arc_set(&g, &result, 0, IGRAPH_FAS_EXACT_IP); igraph_vector_print(&result); igraph_delete_edges(&g, igraph_ess_vector(&result)); igraph_is_dag(&g, &dag); if (!dag) { return 5; } igraph_destroy(&g); igraph_vector_destroy(&result); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_all_st_mincuts.out0000644000076500000240000000217513536224031031025 0ustar tamasstaff00000000000000Found 4 cuts, value: 1 Partition 0: 0 Cut 0: 0 -> 1 Partition 1: 0 1 Cut 1: 1 -> 2 Partition 2: 0 1 2 Cut 2: 2 -> 3 Partition 3: 0 1 2 3 Cut 3: 3 -> 4 Found 2 cuts, value: 1 Partition 0: 0 Cut 0: 0 -> 1 Partition 1: 0 4 3 2 1 Cut 1: 4 -> 5 Found 1 cuts, value: 1 Partition 0: 0 Cut 0: 0 -> 1 Found 4 cuts, value: 2 Partition 0: 0 Cut 0: 0 -> 1 0 -> 2 Partition 1: 0 1 8 7 6 5 4 Cut 1: 0 -> 2 1 -> 3 Partition 2: 0 2 Cut 2: 0 -> 1 2 -> 3 Partition 3: 0 2 1 8 7 6 5 4 Cut 3: 1 -> 3 2 -> 3 Found 2 cuts, value: 2 Partition 0: 2 Cut 0: 2 -> 0 2 -> 1 Partition 1: 2 1 Cut 1: 1 -> 0 2 -> 0 Found 2 cuts, value: 2 Partition 0: 2 3 Cut 0: 2 -> 0 2 -> 1 Partition 1: 2 3 1 Cut 1: 1 -> 0 2 -> 0 Found 8 cuts, value: 2 Partition 0: 0 Cut 0: 0 -> 4 0 -> 7 Partition 1: 0 4 2 1 6 Cut 1: 0 -> 7 4 -> 5 Partition 2: 0 4 2 1 6 5 Cut 2: 0 -> 7 5 -> 3 Partition 3: 0 4 2 1 6 5 3 Cut 3: 0 -> 7 3 -> 8 Partition 4: 0 7 Cut 4: 0 -> 4 7 -> 8 Partition 5: 0 7 4 2 1 6 Cut 5: 4 -> 5 7 -> 8 Partition 6: 0 7 4 2 1 6 5 Cut 6: 5 -> 3 7 -> 8 Partition 7: 0 7 4 2 1 6 5 3 Cut 7: 3 -> 8 7 -> 8 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_minimum_size_separators.out0000644000076500000240000000025613524616144032762 0ustar tamasstaff000000000000000 3 4 0 1 2 3 1 2 3 0 2 3 0 1 3 0 1 2 Orig: 6 1-7,17-23: 4 6 6 11 4 9 9 11 7-16: 3 9 7 9 1 3 17-23: 2 4 7,8,11,14: 1 2 3 0 2 3 0 1 3 0 1 2 1-7: 1 2 3 4 5 0 2 3 4 6 0 1 3 5 6 python-igraph-0.8.0/vendor/source/igraph/examples/simple/fullmatrix1.dl0000644000076500000240000000010613524616144026512 0ustar tamasstaff00000000000000DL N = 5 Data: 0 1 1 1 1 1 0 1 0 0 1 1 0 0 1 1 0 0 0 0 1 0 1 0 0 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_subisomorphic_lad.c0000644000076500000240000002277713612122634031141 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include /* This test counts motifs using LAD and compares the results with * the RANDESU motif finder */ void test_motifs() { igraph_t graph; igraph_vector_t randesu_counts, lad_counts; igraph_vector_t cut_prob; int i, n; igraph_bool_t equal; igraph_integer_t vcount; igraph_rng_seed(igraph_rng_default(), 42); igraph_erdos_renyi_game_gnm(&graph, 40, 400, /* directed = */ 1, /* loops = */ 0); vcount = igraph_vcount(&graph); /* 3-motifs */ n = 16; /* there are 16 size-3 directed graphs */ igraph_vector_init(&lad_counts, n); for (i = 0; i < n; i++) { igraph_t pattern; igraph_vector_ptr_t maps; igraph_integer_t nAutomorphisms; igraph_isoclass_create(&pattern, 3, i, /* directed = */ 1); igraph_vector_ptr_init(&maps, 0); igraph_subisomorphic_lad(&pattern, &graph, NULL, NULL, NULL, &maps, /* induced = */ 1, 0); igraph_count_subisomorphisms_vf2(&pattern, &pattern, NULL, NULL, NULL, NULL, &nAutomorphisms, NULL, NULL, NULL); VECTOR(lad_counts)[i] = igraph_vector_ptr_size(&maps) / nAutomorphisms; IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(&maps, igraph_vector_destroy); igraph_vector_ptr_destroy_all(&maps); igraph_destroy(&pattern); } igraph_vector_init(&cut_prob, 3); igraph_vector_init(&randesu_counts, 0); igraph_motifs_randesu(&graph, &randesu_counts, 3, &cut_prob); equal = 1 /* true */; for (i = 0; i < n; i++) { if (igraph_is_nan(VECTOR(randesu_counts)[i])) { continue; } if (VECTOR(randesu_counts)[i] != VECTOR(lad_counts)[i]) { equal = 0; break; } } if (! equal) { printf("LAD 3-motif count does not agree with RANDESU.\n"); } if (igraph_vector_sum(&lad_counts) != vcount * (vcount - 1) * (vcount - 2) / 6) { printf("Total 3-vertex subgraph count is incorrect.\n"); } igraph_vector_destroy(&randesu_counts); igraph_vector_destroy(&lad_counts); igraph_vector_destroy(&cut_prob); /* 4-motifs */ n = 218; /* there are 218 size-4 directed graphs */ igraph_vector_init(&lad_counts, n); for (i = 0; i < n; i++) { igraph_t pattern; igraph_vector_ptr_t maps; igraph_integer_t nAutomorphisms; igraph_isoclass_create(&pattern, 4, i, /* directed = */ 1); igraph_vector_ptr_init(&maps, 0); igraph_subisomorphic_lad(&pattern, &graph, NULL, NULL, NULL, &maps, /* induced = */ 1, 0); igraph_count_subisomorphisms_vf2(&pattern, &pattern, NULL, NULL, NULL, NULL, &nAutomorphisms, NULL, NULL, NULL); VECTOR(lad_counts)[i] = igraph_vector_ptr_size(&maps) / nAutomorphisms; IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(&maps, igraph_vector_destroy); igraph_vector_ptr_destroy_all(&maps); igraph_destroy(&pattern); } igraph_vector_init(&cut_prob, 4); igraph_vector_init(&randesu_counts, 0); igraph_motifs_randesu(&graph, &randesu_counts, 4, &cut_prob); equal = 1 /* true */; for (i = 0; i < n; i++) { if (igraph_is_nan(VECTOR(randesu_counts)[i])) { continue; } if (VECTOR(randesu_counts)[i] != VECTOR(lad_counts)[i]) { equal = 0; break; } } if (! equal) { printf("LAD 4-motif count does not agree with RANDESU.\n"); } if (igraph_vector_sum(&lad_counts) != vcount * (vcount - 1) * (vcount - 2) * (vcount - 3) / 24) { printf("Total 4-vertex subgraph count is incorrect.\n"); } igraph_vector_destroy(&randesu_counts); igraph_vector_destroy(&lad_counts); igraph_vector_destroy(&cut_prob); igraph_destroy(&graph); } int main() { igraph_t target, pattern; igraph_bool_t iso; igraph_vector_t map; igraph_vector_ptr_t maps; int i, n, result; int domainsvec[] = { 0, 2, 8, -1, 4, 5, 6, 7, -1, 1, 3, 5, 6, 7, 8, -1, 0, 2, 8, -1, 1, 3, 7, 8, -1, -2 }; igraph_vector_ptr_t domains; igraph_vector_t *v = 0; igraph_small(&target, 9, IGRAPH_UNDIRECTED, 0, 1, 0, 4, 0, 6, 1, 0, 1, 4, 1, 2, 2, 1, 2, 3, 3, 2, 3, 4, 3, 5, 3, 7, 3, 8, 4, 0, 4, 1, 4, 3, 4, 5, 4, 6, 5, 6, 5, 4, 5, 3, 5, 8, 6, 0, 6, 4, 6, 5, 7, 3, 7, 8, 8, 5, 8, 3, 8, 7, -1); igraph_simplify(&target, /*multiple=*/ 1, /*loops=*/ 0, /*edge_comb=*/ 0); igraph_small(&pattern, 5, IGRAPH_UNDIRECTED, 0, 1, 0, 4, 1, 0, 1, 4, 1, 2, 2, 1, 2, 3, 3, 2, 3, 4, 4, 3, 4, 1, 4, 0, -1); igraph_simplify(&pattern, /*multiple=*/ 1, /*loops=*/ 0, /*edge_comb=*/ 0); igraph_vector_init(&map, 0); igraph_vector_ptr_init(&maps, 0); igraph_subisomorphic_lad(&pattern, &target, /*domains=*/ 0, &iso, &map, &maps, /*induced=*/ 0, /*time_limit=*/ 0); if (!iso) { return 1; } igraph_vector_print(&map); n = igraph_vector_ptr_size(&maps); for (i = 0; i < n; i++) { igraph_vector_t *v = VECTOR(maps)[i]; igraph_vector_print(v); igraph_vector_destroy(v); igraph_free(v); } printf("---------\n"); igraph_subisomorphic_lad(&pattern, &target, /*domains=*/ 0, &iso, &map, &maps, /*induced=*/ 1, /*time_limit=*/ 0); if (!iso) { return 2; } igraph_vector_print(&map); n = igraph_vector_ptr_size(&maps); for (i = 0; i < n; i++) { igraph_vector_t *v = VECTOR(maps)[i]; igraph_vector_print(v); igraph_vector_destroy(v); igraph_free(v); } printf("---------\n"); igraph_vector_ptr_init(&domains, 0); i = 0; while (1) { if (domainsvec[i] == -2) { break; } else if (domainsvec[i] == -1) { igraph_vector_ptr_push_back(&domains, v); v = 0; } else { if (!v) { v = (igraph_vector_t *) malloc(sizeof(igraph_vector_t)); igraph_vector_init(v, 0); } igraph_vector_push_back(v, domainsvec[i]); } i++; } igraph_subisomorphic_lad(&pattern, &target, &domains, &iso, &map, &maps, /*induced=*/ 0, /*time_limit=*/ 0); if (!iso) { return 3; } igraph_vector_print(&map); n = igraph_vector_ptr_size(&maps); for (i = 0; i < n; i++) { igraph_vector_t *v = VECTOR(maps)[i]; igraph_vector_print(v); igraph_vector_destroy(v); igraph_free(v); } n = igraph_vector_ptr_size(&domains); for (i = 0; i < n; i++) { igraph_vector_t *v = VECTOR(domains)[i]; igraph_vector_destroy(v); free(v); } igraph_vector_ptr_destroy(&domains); igraph_vector_destroy(&map); igraph_vector_ptr_destroy(&maps); igraph_destroy(&pattern); igraph_destroy(&target); printf("---------\n"); igraph_vector_init(&map, 0); igraph_vector_ptr_init(&maps, 0); igraph_small(&target, 9, IGRAPH_UNDIRECTED, 0, 1, 0, 4, 0, 6, 1, 0, 1, 4, 1, 2, 2, 1, 2, 3, 3, 2, 3, 4, 3, 5, 3, 7, 3, 8, 4, 0, 4, 1, 4, 3, 4, 5, 4, 6, 5, 6, 5, 4, 5, 3, 5, 8, 6, 0, 6, 4, 6, 5, 7, 3, 7, 8, 8, 5, 8, 3, 8, 7, -1); igraph_simplify(&target, /*multiple=*/ 1, /*loops=*/ 0, /*edge_comb=*/ 0); igraph_small(&pattern, 0, IGRAPH_DIRECTED, -1); igraph_set_error_handler(igraph_error_handler_ignore); result = igraph_subisomorphic_lad(&pattern, &target, /*domains=*/ 0, &iso, &map, &maps, /*induced=*/ 0, /*time_limit=*/ 0); igraph_set_error_handler(igraph_error_handler_abort); if (result != IGRAPH_EINVAL) { return 4; } igraph_destroy(&pattern); igraph_small(&pattern, 0, IGRAPH_UNDIRECTED, -1); igraph_subisomorphic_lad(&pattern, &target, /*domains=*/ 0, &iso, &map, &maps, /*induced=*/ 0, /*time_limit=*/ 0); if (!iso) { return 5; } if (igraph_vector_size(&map) != 0) { return 6; } if (igraph_vector_ptr_size(&maps) != 0) { return 7; } igraph_destroy(&pattern); igraph_destroy(&target); igraph_vector_destroy(&map); igraph_vector_ptr_destroy(&maps); test_motifs(); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/scg3.c0000644000076500000240000001046313612122634024725 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_vector_t ev; igraph_t scg_graph; igraph_matrix_t scg_matrix; igraph_sparsemat_t scg_sparsemat; igraph_matrix_t L, R; igraph_sparsemat_t Lsparse, Rsparse; igraph_vector_t groups; igraph_vector_complex_t eval; igraph_matrix_complex_t evec; igraph_tree(&g, 10, /* children= */ 3, IGRAPH_TREE_UNDIRECTED); igraph_vector_init(&ev, 1); igraph_matrix_init(&L, 0, 0); igraph_matrix_init(&R, 0, 0); igraph_matrix_init(&scg_matrix, 0, 0); igraph_vector_init(&groups, 0); igraph_vector_complex_init(&eval, 0); igraph_matrix_complex_init(&evec, 0, 0); #define CALLLAP() do { \ igraph_vector_resize(&groups, 0); \ igraph_vector_complex_resize(&eval, 0); \ igraph_matrix_complex_resize(&evec, 0, 0); \ igraph_scg_laplacian(&g, /*matrix=*/ 0, /*sparsemat=*/ 0, &ev, \ /* intervals= */ 2, /* intervals_vector= */ 0, \ /* algorithm= */ IGRAPH_SCG_EXACT, \ IGRAPH_SCG_NORM_ROW, \ IGRAPH_SCG_DIRECTION_DEFAULT, &eval, &evec, \ &groups, /* use_arpack= */ 0, \ /* maxiter= */ 0, &scg_graph, &scg_matrix, \ &scg_sparsemat, &L, &R, \ &Lsparse, &Rsparse); \ } while (0) #define PRINTRES() \ do { \ printf("--------------------------------\n"); \ igraph_vector_print(&groups); \ printf("---\n"); \ igraph_vector_complex_print(&eval); \ igraph_matrix_complex_print(&evec); \ printf("---\n"); \ igraph_write_graph_edgelist(&scg_graph, stdout); \ printf("---\n"); \ igraph_sparsemat_print(&scg_sparsemat, stdout); \ printf("---\n"); \ igraph_sparsemat_print(&Lsparse, stdout); \ printf("---\n"); \ igraph_sparsemat_print(&Rsparse, stdout); \ printf("---\n"); \ } while (0) VECTOR(ev)[0] = 1; CALLLAP(); PRINTRES(); igraph_destroy(&scg_graph); igraph_sparsemat_destroy(&scg_sparsemat); igraph_sparsemat_destroy(&Lsparse); igraph_sparsemat_destroy(&Rsparse); VECTOR(ev)[0] = 3; CALLLAP(); PRINTRES(); igraph_destroy(&scg_graph); igraph_sparsemat_destroy(&scg_sparsemat); igraph_sparsemat_destroy(&Lsparse); igraph_sparsemat_destroy(&Rsparse); igraph_vector_resize(&ev, 2); VECTOR(ev)[0] = 1; VECTOR(ev)[1] = 3; CALLLAP(); PRINTRES(); igraph_destroy(&scg_graph); igraph_sparsemat_destroy(&scg_sparsemat); igraph_sparsemat_destroy(&Lsparse); igraph_sparsemat_destroy(&Rsparse); igraph_matrix_complex_destroy(&evec); igraph_vector_complex_destroy(&eval); igraph_vector_destroy(&groups); igraph_matrix_destroy(&scg_matrix); igraph_matrix_destroy(&L); igraph_matrix_destroy(&R); igraph_vector_destroy(&ev); igraph_destroy(&g); /* -------------------------------------------------------------------- */ return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/gml.c0000644000076500000240000000257613612122633024652 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int main() { igraph_t g; FILE *ifile; ifile = fopen("karate.gml", "r"); if (ifile == 0) { return 10; } igraph_read_graph_gml(&g, ifile); fclose(ifile); if (igraph_is_directed(&g)) { printf("directed\n"); } else { printf("undirected\n"); } igraph_write_graph_edgelist(&g, stdout); printf("-----------------\n"); igraph_write_graph_gml(&g, stdout, 0, "test suite"); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/vector_ptr.c0000644000076500000240000002012213614300625026246 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include igraph_vector_ptr_t custom_destructor_stack; void custom_destructor(void* ptr) { igraph_vector_ptr_push_back(&custom_destructor_stack, ptr); } int main() { igraph_vector_ptr_t v1, v2; igraph_vector_ptr_t v3 = IGRAPH_VECTOR_PTR_NULL; int i; void ** ptr; int d1 = 1, d2 = 2, d3 = 3, d4 = 4, d5 = 5; char *block1 = 0, *block2 = 0; /* igraph_vector_ptr_init, igraph_vector_ptr_destroy */ igraph_vector_ptr_init(&v1, 10); igraph_vector_ptr_destroy(&v1); igraph_vector_ptr_init(&v1, 0); igraph_vector_ptr_destroy(&v1); /* igraph_vector_ptr_free_all, igraph_vector_ptr_destroy_all */ igraph_vector_ptr_init(&v1, 5); for (i = 0; i < igraph_vector_ptr_size(&v1); i++) { VECTOR(v1)[i] = (void*)malloc(i * 10); } igraph_vector_ptr_free_all(&v1); for (i = 0; i < igraph_vector_ptr_size(&v1); i++) { VECTOR(v1)[i] = (void*)malloc(i * 10); } igraph_vector_ptr_destroy_all(&v1); /* igraph_vector_ptr_reserve */ igraph_vector_ptr_init(&v1, 0); igraph_vector_ptr_reserve(&v1, 5); igraph_vector_ptr_reserve(&v1, 15); igraph_vector_ptr_reserve(&v1, 1); igraph_vector_ptr_reserve(&v1, 0); igraph_vector_ptr_destroy(&v1); /* igraph_vector_ptr_empty, igraph_vector_ptr_clear */ igraph_vector_ptr_init(&v1, 10); if (igraph_vector_ptr_empty(&v1)) { return 1; } igraph_vector_ptr_clear(&v1); if (!igraph_vector_ptr_empty(&v1)) { return 2; } /* igraph_vector_ptr_size */ if (igraph_vector_ptr_size(&v1) != 0) { return 3; } igraph_vector_ptr_resize(&v1, 10); if (igraph_vector_ptr_size(&v1) != 10) { return 4; } igraph_vector_ptr_destroy(&v1); /* igraph_vector_ptr_push_back */ igraph_vector_ptr_init(&v1, 0); for (i = 0; i < 10; i++) { igraph_vector_ptr_push_back(&v1, (void*)malloc(i * 10)); } igraph_vector_ptr_destroy_all(&v1); /* igraph_vector_ptr_e */ igraph_vector_ptr_init(&v1, 5); VECTOR(v1)[0] = &d1; VECTOR(v1)[1] = &d2; VECTOR(v1)[2] = &d3; VECTOR(v1)[3] = &d4; VECTOR(v1)[4] = &d5; if (igraph_vector_ptr_e(&v1, 0) != &d1) { return 5; } if (igraph_vector_ptr_e(&v1, 1) != &d2) { return 6; } if (igraph_vector_ptr_e(&v1, 2) != &d3) { return 7; } if (igraph_vector_ptr_e(&v1, 3) != &d4) { return 8; } if (igraph_vector_ptr_e(&v1, 4) != &d5) { return 9; } igraph_vector_ptr_destroy(&v1); /* igraph_vector_ptr_set */ igraph_vector_ptr_init(&v1, 5); igraph_vector_ptr_set(&v1, 0, &d1); igraph_vector_ptr_set(&v1, 1, &d2); igraph_vector_ptr_set(&v1, 2, &d3); igraph_vector_ptr_set(&v1, 3, &d4); igraph_vector_ptr_set(&v1, 4, &d5); if (igraph_vector_ptr_e(&v1, 0) != &d1) { return 5; } if (igraph_vector_ptr_e(&v1, 1) != &d2) { return 6; } if (igraph_vector_ptr_e(&v1, 2) != &d3) { return 7; } if (igraph_vector_ptr_e(&v1, 3) != &d4) { return 8; } if (igraph_vector_ptr_e(&v1, 4) != &d5) { return 9; } igraph_vector_ptr_destroy(&v1); /* igraph_vector_ptr_null */ igraph_vector_ptr_init(&v1, 5); igraph_vector_ptr_set(&v1, 0, &d1); igraph_vector_ptr_set(&v1, 1, &d2); igraph_vector_ptr_set(&v1, 2, &d3); igraph_vector_ptr_set(&v1, 3, &d4); igraph_vector_ptr_set(&v1, 4, &d5); igraph_vector_ptr_null(&v1); for (i = 0; i < igraph_vector_ptr_size(&v1); i++) { if (VECTOR(v1)[i] != 0) { return 10; } } igraph_vector_ptr_destroy(&v1); /* igraph_vector_ptr_resize */ igraph_vector_ptr_init(&v1, 10); igraph_vector_ptr_set(&v1, 0, &d1); igraph_vector_ptr_set(&v1, 1, &d2); igraph_vector_ptr_set(&v1, 2, &d3); igraph_vector_ptr_set(&v1, 3, &d4); igraph_vector_ptr_set(&v1, 4, &d5); igraph_vector_ptr_resize(&v1, 10); igraph_vector_ptr_resize(&v1, 15); igraph_vector_ptr_resize(&v1, 5); if (igraph_vector_ptr_size(&v1) != 5) { return 11; } if (igraph_vector_ptr_e(&v1, 0) != &d1) { return 12; } if (igraph_vector_ptr_e(&v1, 1) != &d2) { return 13; } if (igraph_vector_ptr_e(&v1, 2) != &d3) { return 14; } if (igraph_vector_ptr_e(&v1, 3) != &d4) { return 15; } if (igraph_vector_ptr_e(&v1, 4) != &d5) { return 16; } igraph_vector_ptr_destroy(&v1); /* igraph_vector_ptr_view */ ptr = (void**) malloc(5 * sizeof(void*)); igraph_vector_ptr_view(&v3, ptr, 5); ptr[0] = &d1; ptr[1] = &d2; ptr[2] = &d3; ptr[3] = &d4; ptr[4] = &d5; for (i = 0; i < igraph_vector_ptr_size(&v3); i++) { if ( *((int*)VECTOR(v3)[i]) != i + 1) { return 17; } } /* igraph_vector_ptr_init_copy */ igraph_vector_ptr_init_copy(&v1, ptr, 5); for (i = 0; i < igraph_vector_ptr_size(&v1); i++) { if ( *((int*)VECTOR(v1)[i]) != i + 1) { return 18; } } /* igraph_vector_ptr_copy_to */ igraph_vector_ptr_copy_to(&v1, ptr); for (i = 0; i < igraph_vector_ptr_size(&v1); i++) { if ( *((int*)ptr[i]) != i + 1) { return 19; } } free(ptr); igraph_vector_ptr_destroy(&v1); /* igraph_vector_ptr_copy */ igraph_vector_ptr_init(&v1, 5); igraph_vector_ptr_set(&v1, 0, &d1); igraph_vector_ptr_set(&v1, 1, &d2); igraph_vector_ptr_set(&v1, 2, &d3); igraph_vector_ptr_set(&v1, 3, &d4); igraph_vector_ptr_set(&v1, 4, &d5); igraph_vector_ptr_copy(&v2, &v1); igraph_vector_ptr_destroy(&v1); for (i = 0; i < igraph_vector_ptr_size(&v2); i++) { if ( *((int*)VECTOR(v2)[i]) != i + 1) { return 20; } } /* igraph_vector_ptr_remove */ igraph_vector_ptr_remove(&v2, 0); igraph_vector_ptr_remove(&v2, 3); if ( *((int*)VECTOR(v2)[0]) != 2) { return 21; } if ( *((int*)VECTOR(v2)[1]) != 3) { return 22; } if ( *((int*)VECTOR(v2)[2]) != 4) { return 23; } igraph_vector_ptr_destroy(&v2); /* Testing destructor */ igraph_vector_ptr_init(&custom_destructor_stack, 0); igraph_vector_ptr_init(&v1, 2); block1 = igraph_Calloc(32, char); block2 = igraph_Calloc(64, char); VECTOR(v1)[0] = block1; VECTOR(v1)[1] = block2; if (igraph_vector_ptr_get_item_destructor(&v1) != 0) { return 24; } if (igraph_vector_ptr_set_item_destructor(&v1, &custom_destructor) != 0) { return 25; } /* Okay, let's clear the vector. This should push the blocks in the * custom destructor stack */ igraph_vector_ptr_clear(&v1); /* Put the blocks back and destroy the vector */ igraph_vector_ptr_push_back(&v1, block1); igraph_vector_ptr_push_back(&v1, block2); igraph_vector_ptr_destroy_all(&v1); if (VECTOR(custom_destructor_stack)[0] != block1 || VECTOR(custom_destructor_stack)[1] != block2 || VECTOR(custom_destructor_stack)[2] != block1 || VECTOR(custom_destructor_stack)[3] != block2 ) { return 26; } igraph_vector_ptr_destroy(&custom_destructor_stack); if (IGRAPH_FINALLY_STACK_SIZE() != 0) { return 27; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_lattice.c0000644000076500000240000001502613612122633027044 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include typedef struct { int dim; int m; int nei; igraph_bool_t directed, mutual, circular; igraph_real_t *dimedges; } lat_test_t; #define LAT_TEST(id, d, m, ne, di, mu, ci, ...) \ igraph_real_t lat_ ## id ## _edges[] = { __VA_ARGS__ } ; \ lat_test_t lat_ ## id = { d, m, ne, di, mu, ci, lat_ ## id ## _edges } /*----------------d--m--ne-di-mu-ci-dimedges------------------------*/ LAT_TEST(u_0, 0, 0, 1, 0, 0, 0, -1 ); LAT_TEST(u_01, 1, 0, 1, 0, 0, 0, 0 ); LAT_TEST(u_02, 2, 0, 1, 0, 0, 0, 0, 1 ); LAT_TEST(u_03, 2, 0, 1, 0, 0, 0, 1, 0 ); LAT_TEST(d_0, 0, 0, 1, 1, 0, 0, -1 ); LAT_TEST(d_01, 1, 0, 1, 1, 0, 0, 0 ); LAT_TEST(d_02, 2, 0, 1, 1, 0, 0, 0, 1 ); LAT_TEST(d_03, 2, 0, 1, 1, 0, 0, 1, 0 ); LAT_TEST(u_1, 1, 0, 1, 0, 0, 0, 1 ); LAT_TEST(u_1x1, 2, 0, 1, 0, 0, 0, 1, 1 ); LAT_TEST(u_2, 1, 1, 1, 0, 0, 0, 2, 0, 1 ); LAT_TEST(u_2x1, 2, 1, 1, 0, 0, 0, 2, 1, 0, 1 ); LAT_TEST(u_2x2, 2, 4, 1, 0, 0, 0, 2, 2, 0, 1, 0, 2, 1, 3, 2, 3 ); LAT_TEST(uc_1, 1, 0, 1, 0, 0, 1, 1 ); LAT_TEST(uc_1x1, 2, 0, 1, 0, 0, 1, 1, 1 ); LAT_TEST(uc_2, 1, 1, 1, 0, 0, 1, 2, 0, 1 ); LAT_TEST(uc_2x1, 2, 1, 1, 0, 0, 1, 2, 1, 0, 1 ); LAT_TEST(uc_2x2, 2, 4, 1, 0, 0, 1, 2, 2, 0, 1, 0, 2, 1, 3, 2, 3 ); LAT_TEST(dc_1, 1, 0, 1, 1, 0, 1, 1 ); LAT_TEST(dc_1x1, 2, 0, 1, 1, 0, 1, 1, 1 ); LAT_TEST(dc_2, 1, 2, 1, 1, 0, 1, 2, 0, 1, 1, 0 ); LAT_TEST(dc_2x1, 2, 2, 1, 1, 0, 1, 2, 1, 0, 1, 1, 0 ); LAT_TEST(dc_2x2, 2, 8, 1, 1, 0, 1, 2, 2, 0, 1, 0, 2, 1, 3, 2, 3, 1, 0, 2, 0, 3, 1, 3, 2, ); LAT_TEST(d_1, 1, 0, 1, 1, 0, 0, 1 ); LAT_TEST(d_1x1, 2, 0, 1, 1, 0, 0, 1, 1 ); LAT_TEST(d_2, 1, 1, 1, 1, 0, 0, 2, 0, 1 ); LAT_TEST(d_2x1, 2, 1, 1, 1, 0, 0, 2, 1, 0, 1 ); LAT_TEST(d_2x2, 2, 4, 1, 1, 0, 0, 2, 2, 0, 1, 0, 2, 1, 3, 2, 3 ); LAT_TEST(dmc_1, 1, 0, 1, 1, 0, 1, 1 ); LAT_TEST(dmc_1x1, 2, 0, 1, 1, 0, 1, 1, 1 ); LAT_TEST(dmc_2, 1, 2, 1, 1, 0, 1, 2, 0, 1, 1, 0 ); LAT_TEST(dmc_2x1, 2, 2, 1, 1, 0, 1, 2, 1, 0, 1, 1, 0 ); LAT_TEST(dmc_2x2, 2, 4, 1, 1, 0, 1, 2, 2, 0, 1, 0, 2, 1, 3, 2, 3, 1, 0, 3, 2, ); /*----------------d--m--ne-di-mu-ci-dimedges------------------------*/ /* TODO: add more */ lat_test_t *all_checks[] = { /* 1 */ &lat_u_0, /* 2 */ &lat_u_01, /* 3 */ &lat_u_02, /* 4 */ &lat_u_03, /* 5 */ &lat_d_0, /* 6 */ &lat_d_01, /* 7 */ &lat_d_02, /* 8 */ &lat_d_03, /* 9 */ &lat_u_1, /* 10 */ &lat_u_1x1, /* 11 */ &lat_u_2, /* 12 */ &lat_u_2x1, /* 13 */ &lat_u_2x2, /* 14 */ &lat_u_1, /* 15 */ &lat_u_1x1, /* 16 */ &lat_u_2, /* 17 */ &lat_u_2x1, /* 18 */ &lat_uc_2x2, /* 19 */ &lat_dc_1, /* 20 */ &lat_dc_1x1, /* 21 */ &lat_dc_2, /* 22 */ &lat_dc_2x1, /* 23 */ &lat_dc_2x2,/* 24 */ &lat_d_1, /* 25 */ &lat_d_1x1, /* 26 */ &lat_d_2, /* 27 */ &lat_d_2x1, /* 28 */ &lat_d_2x2, /* 29 */ &lat_dc_2x2,/* 30 */ &lat_d_1, /* 31 */ &lat_d_1x1, /* 32 */ &lat_d_2, /* 33 */ &lat_d_2x1, /* 34 */ &lat_d_2x2, 0 }; int check_lattice_properties(const igraph_t *lattice, const igraph_vector_t *dim, igraph_bool_t directed, igraph_bool_t mutual, igraph_bool_t circular) { igraph_bool_t res; /* Connected */ igraph_is_connected(lattice, &res, IGRAPH_WEAK); if (!res) { printf("Not connected\n"); return 1; } /* Simple */ igraph_is_simple(lattice, &res); if (!res) { printf("Not simple\n"); return 2; } return 0; } int check_lattice(const lat_test_t *test) { igraph_t graph, othergraph; igraph_vector_t otheredges; igraph_vector_t dimvector; igraph_bool_t iso; int ret; /* Create lattice */ igraph_vector_view(&dimvector, test->dimedges, test->dim); igraph_lattice(&graph, &dimvector, test->nei, test->directed, test->mutual, test->circular); /* Check its properties */ if ((ret = check_lattice_properties(&graph, &dimvector, test->directed, test->mutual, test->circular))) { igraph_destroy(&graph); printf("Lattice properties are not satisfied\n"); return ret; } /* Check that it is isomorphic to the stored graph */ igraph_vector_view(&otheredges, test->dimedges + test->dim, test->m * 2); igraph_create(&othergraph, &otheredges, igraph_vector_prod(&dimvector), test->directed); igraph_isomorphic(&graph, &othergraph, &iso); if (!iso) { printf("--\n"); igraph_write_graph_edgelist(&graph, stdout); printf("--\n"); igraph_write_graph_edgelist(&othergraph, stdout); igraph_destroy(&graph); igraph_destroy(&othergraph); return 50; } igraph_destroy(&graph); igraph_destroy(&othergraph); return 0; } int main() { int i, ret; i = 0; while (all_checks[i]) { if ((ret = check_lattice(all_checks[i]))) { printf("Check no #%d failed.\n", (int) (i + 1)); return ret; } i++; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_eigen_matrix3.out0000644000076500000240000000000013524616144030533 0ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_fisher_yates_shuffle.c0000644000076500000240000000672113612122633031622 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* Test suite for the Fisher-Yates shuffle. Copyright (C) 2011 Minh Van Nguyen This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #define R_INTEGER(a,b) (igraph_rng_get_integer(igraph_rng_default(), (a), (b))) #define R_UNIF(a,b) (igraph_rng_get_unif(igraph_rng_default(), (a), (b))) int main() { igraph_real_t d; igraph_vector_t u, v; int ret; long int i, k, n; /******************************** * Example usage ********************************/ /* Sequences with one element. Such sequences are trivially permuted. * The result of any Fisher-Yates shuffle on a sequence with one element * must be the original sequence itself. */ n = 1; igraph_vector_init(&v, n); igraph_rng_seed(igraph_rng_default(), time(0)); k = R_INTEGER(-1000, 1000); VECTOR(v)[0] = k; igraph_vector_shuffle(&v); if (VECTOR(v)[0] != k) { return 1; } d = R_UNIF(-1000.0, 1000.0); VECTOR(v)[0] = d; igraph_vector_shuffle(&v); if (VECTOR(v)[0] != d) { return 2; } igraph_vector_destroy(&v); /* Sequences with multiple elements. A Fisher-Yates shuffle of a sequence S * is a random permutation \pi(S) of S. Thus \pi(S) must have the same * length and elements as the original sequence S. A major difference between * S and its random permutation \pi(S) is that the order in which elements * appear in \pi(S) is probably different from how elements are ordered in S. * If S has length n = 1, then both \pi(S) and S are equivalent sequences in * that \pi(S) is merely S and no permutation has taken place. If S has * length n > 1, then there are n! possible permutations of S. Assume that * each such permutation is equally likely to appear as a result of the * Fisher-Yates shuffle. As n increases, the probability that S is different * from \pi(S) also increases. We have a probability of 1 / n! that S and * \pi(S) are equivalent sequences. */ n = 100; igraph_vector_init(&u, n); igraph_vector_init(&v, n); for (i = 0; i < n; i++) { k = R_INTEGER(-1000, 1000); VECTOR(u)[i] = k; VECTOR(v)[i] = k; } igraph_vector_shuffle(&v); /* must have same length */ if (igraph_vector_size(&v) != n) { return 3; } if (igraph_vector_size(&u) != igraph_vector_size(&v)) { return 4; } /* must have same elements */ igraph_vector_sort(&u); igraph_vector_sort(&v); if (!igraph_vector_all_e(&u, &v)) { return 5; } igraph_vector_destroy(&u); igraph_vector_destroy(&v); /* empty sequence */ igraph_vector_init(&v, 0); ret = igraph_vector_shuffle(&v); igraph_vector_destroy(&v); return ret == 0 ? 0 : 6; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_is_degree_sequence.c0000644000076500000240000001603513612122633031236 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2012 Gabor Csardi 334 Harvard st, Cambridge, MA 02139, USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_vector_t outseq, inseq; igraph_bool_t result; /***** Testing igraph_is_degree_sequence *****/ /* Valid undirected degree sequence */ igraph_vector_init_int_end(&outseq, -1, 3, 3, 3, 3, 3, 3, 3, 3, -1); igraph_is_degree_sequence(&outseq, 0, &result); if (!result) { return 1; } igraph_vector_destroy(&outseq); /* Undirected degree sequence with negative degree */ igraph_vector_init_int_end(&outseq, -1, 3, -2, 3, 3, 3, 3, 3, 3, -1); igraph_is_degree_sequence(&outseq, 0, &result); if (result) { return 2; } igraph_vector_destroy(&outseq); /* Undirected degree sequence with uneven sum */ igraph_vector_init_int_end(&outseq, -1, 3, 3, 3, 3, 3, 3, 3, -1); igraph_is_degree_sequence(&outseq, 0, &result); if (result) { return 3; } igraph_vector_destroy(&outseq); /* Valid directed degree sequences */ igraph_vector_init_int_end(&outseq, -1, 0, 2, 3, 0, 4, 3, 1, 3, 4, 2, -1); igraph_vector_init_int_end(&inseq, -1, 0, 3, 1, 3, 2, 4, 4, 1, 3, 1, -1); igraph_is_degree_sequence(&outseq, &inseq, &result); if (!result) { return 4; } igraph_vector_destroy(&outseq); igraph_vector_destroy(&inseq); /* Directed degree sequence with negative degree */ igraph_vector_init_int_end(&outseq, -1, 0, 2, 3, 0, 4, 3, 1, 3, 4, 2, -1); igraph_vector_init_int_end(&inseq, -1, 0, 3, 1, -7, 2, 4, 4, 1, 3, 1, -1); igraph_is_degree_sequence(&outseq, &inseq, &result); if (result) { return 5; } igraph_vector_destroy(&outseq); igraph_vector_destroy(&inseq); /* Directed degree sequence with different lengths */ igraph_vector_init_int_end(&outseq, -1, 0, 2, 3, 0, 4, 3, 1, 3, 4, 2, -1); igraph_vector_init_int_end(&inseq, -1, 0, 3, 1, 2, 4, 4, 1, 3, 1, -1); igraph_is_degree_sequence(&outseq, &inseq, &result); if (result) { return 5; } igraph_vector_destroy(&outseq); igraph_vector_destroy(&inseq); /* Directed degree sequence with different sums */ igraph_vector_init_int_end(&outseq, -1, 0, 2, 3, 0, 4, 3, 1, 3, 4, 2, -1); igraph_vector_init_int_end(&inseq, -1, 0, 3, 1, 2, 2, 4, 4, 1, 3, 1, -1); igraph_is_degree_sequence(&outseq, &inseq, &result); if (result) { return 6; } igraph_vector_destroy(&outseq); igraph_vector_destroy(&inseq); /***** Testing igraph_is_graphical_degree_sequence *****/ /* Valid undirected graphical degree sequence */ igraph_vector_init_int_end(&outseq, -1, 3, 3, 3, 3, 3, 3, 3, 3, -1); igraph_is_graphical_degree_sequence(&outseq, 0, &result); if (!result) { return 7; } igraph_vector_destroy(&outseq); /* Another valid undirected graphical degree sequence */ igraph_vector_init_int_end(&outseq, -1, 4, 7, 4, 7, 7, 8, 9, 9, 4, 6, 5, -1); igraph_is_graphical_degree_sequence(&outseq, 0, &result); if (!result) { return 8; } igraph_vector_destroy(&outseq); /* Valid undirected degree sequence but not graphical */ igraph_vector_init_int_end(&outseq, -1, 3, 3, -1); igraph_is_graphical_degree_sequence(&outseq, 0, &result); if (result) { return 9; } igraph_vector_destroy(&outseq); /* Valid directed graphical degree sequence */ igraph_vector_init_int_end(&inseq, -1, 3, 3, 3, 3, 3, 3, 3, 3, 3, -1); igraph_vector_init_int_end(&outseq, -1, 3, 3, 3, 3, 3, 3, 3, 3, 3, -1); igraph_is_graphical_degree_sequence(&outseq, &inseq, &result); if (!result) { return 10; } igraph_vector_destroy(&outseq); igraph_vector_destroy(&inseq); /* Another valid directed graphical degree sequence */ igraph_vector_init_int_end(&inseq, -1, 1, 3, 2, 1, 3, 4, 3, 3, 1, 3, -1); igraph_vector_init_int_end(&outseq, -1, 4, 1, 2, 3, 2, 3, 2, 3, 2, 2, -1); igraph_is_graphical_degree_sequence(&outseq, &inseq, &result); if (!result) { return 11; } igraph_vector_destroy(&outseq); igraph_vector_destroy(&inseq); /* Yet another valid directed graphical degree sequence */ igraph_vector_init_int_end(&inseq, -1, 7, 4, 6, 4, 7, 8, 8, 8, 7, 4, -1); igraph_vector_init_int_end(&outseq, -1, 8, 5, 6, 8, 6, 6, 5, 7, 5, 7, -1); igraph_is_graphical_degree_sequence(&outseq, &inseq, &result); if (!result) { return 12; } igraph_vector_destroy(&outseq); igraph_vector_destroy(&inseq); /* Invalid directed graphical degree sequence when there is only one vertex * with a non-zero out-degree. Regression test for bug #851 */ igraph_vector_init_int_end(&inseq, -1, 1, -1); igraph_vector_init_int_end(&outseq, -1, 1, -1); igraph_is_graphical_degree_sequence(&outseq, &inseq, &result); if (result) { return 13; } igraph_vector_destroy(&outseq); igraph_vector_destroy(&inseq); /* Another invalid directed graphical degree sequence when there is only * one vertex with a non-zero out-degree. Regression test for bug #851 */ igraph_vector_init_int_end(&inseq, -1, 2, 0, -1); igraph_vector_init_int_end(&outseq, -1, 0, 2, -1); igraph_is_graphical_degree_sequence(&outseq, &inseq, &result); if (result) { return 14; } igraph_vector_destroy(&outseq); igraph_vector_destroy(&inseq); /* Another invalid directed graphical degree sequence when there is only * one vertex with a non-zero out-degree. Regression test for bug #851 */ igraph_vector_init_int_end(&inseq, -1, 2, 2, -1); igraph_vector_init_int_end(&outseq, -1, 2, 2, -1); igraph_is_graphical_degree_sequence(&outseq, &inseq, &result); if (result) { return 15; } igraph_vector_destroy(&outseq); igraph_vector_destroy(&inseq); /* Valid directed graphical degree sequence. Regression test for bug #1092 */ igraph_vector_init_int_end(&inseq, -1, 1, 0, 1, -1); igraph_vector_init_int_end(&outseq, -1, 0, 2, 0, -1); igraph_is_graphical_degree_sequence(&outseq, &inseq, &result); if (!result) { return 16; } igraph_is_graphical_degree_sequence(&inseq, &outseq, &result); if (!result) { return 17; } igraph_vector_destroy(&outseq); igraph_vector_destroy(&inseq); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/graphml-default-attrs.xml0000644000076500000240000000200513524616144030652 0ustar tamasstaff00000000000000 TRUE male 20 FALSE FALSE30 female python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_community_infomap.c0000644000076500000240000003005113614300625031150 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void gsumary(const igraph_t * g) { printf("|V|=%d |E|=%d directed=%d\n", (int)igraph_vcount(g), (int)igraph_ecount(g), (int)igraph_is_directed(g)); } void show_results(igraph_vector_t * membership, igraph_real_t codelength) { printf("Codelength: %0.5f (in %d modules)\n", codelength, (int)igraph_vector_max(membership) + 1 ); printf("Membership: "); int i; for (i = 0; i < igraph_vector_size(membership); i++) { printf("%li ", (long)VECTOR(*membership)[i] ); } printf("\n"); } void show_results_lite(igraph_vector_t * membership, igraph_real_t codelength) { printf("Codelength: %0.5f (in %d modules)\n", codelength, (int)igraph_vector_max(membership) + 1 ); printf("Membership (1/100 of vertices): "); int i; for (i = 0; i < igraph_vector_size(membership); i += 100) { printf("%li ", (long)VECTOR(*membership)[i] ); } printf("\n"); } void infomap_weighted_test(const igraph_t * g, const igraph_vector_t *weights) { igraph_vector_t membership; igraph_real_t codelength = 1000; igraph_vector_init(&membership, 0); igraph_community_infomap(/*in */ g, /*e_weight=*/ weights, NULL, /*nb_trials=*/5, /*out*/ &membership, &codelength); if (igraph_vcount(g) > 500) { show_results_lite(&membership, codelength); } else { show_results(&membership, codelength); } igraph_vector_destroy(&membership); } void infomap_test(const igraph_t * g) { infomap_weighted_test(g, 0); } int main() { igraph_t g; igraph_vector_t weights; igraph_rng_seed(igraph_rng_default(), 42); /* Two triangles connected by one edge */ printf("# Two triangles connected by one edge\n"); igraph_small(&g, 0, IGRAPH_UNDIRECTED, 0, 1, 1, 2, 2, 0, 3, 4, 4, 5, 5, 3, 0, 5, -1); infomap_test(&g); igraph_destroy(&g); //return 0; /* Two 4-cliques with one commun vertex (vertex 3) */ printf("# Two 4-cliques (0123 and 4567) connected by two edges (0-4 and 1-5)\n"); igraph_small(&g, 0, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 1, 2, 1, 3, 2, 3, // 4-clique 0,1,2,3 7, 4, 7, 5, 7, 6, 4, 5, 4, 6, 5, 6, // 4-clique 4,5,6,7 0, 4, 1, 5, //8, 0, 8, 4, -1); infomap_test(&g); printf("# Two 4-cliques (0123 and 4567) connected by two edges (0-4 and 1-5)\n"); igraph_add_edge(&g, 0, 4); igraph_add_edge(&g, 1, 5); infomap_test(&g); igraph_destroy(&g); /* Zachary Karate club -- this is just a quick smoke test */ printf("# Zachary Karate club\n"); igraph_small(&g, 0, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, //0, 5, 0, 5, 0, 5, 0, 6, 0, 7, 0, 8, 0, 10, 0, 11, 0, 12, 0, 13, 0, 17, 0, 19, 0, 21, 0, 31, 1, 2, 1, 3, 1, 7, 1, 13, 1, 17, 1, 19, 1, 21, 1, 30, 2, 3, 2, 7, 2, 8, 2, 9, 2, 13, 2, 27, 2, 28, 2, 32, 3, 7, 3, 12, 3, 13, 4, 6, 4, 10, 5, 6, 5, 10, 5, 16, 6, 16, 8, 30, 8, 32, 8, 33, 9, 33, 13, 33, 14, 32, 14, 33, 15, 32, 15, 33, 18, 32, 18, 33, 19, 33, 20, 32, 20, 33, 22, 32, 22, 33, 23, 25, 23, 27, 23, 29, 23, 32, 23, 33, 24, 25, 24, 27, 24, 31, 25, 31, 26, 29, 26, 33, 27, 33, 28, 31, 28, 33, 29, 32, 29, 33, 30, 32, 30, 33, 31, 32, 31, 33, 32, 33, -1); infomap_test(&g); igraph_destroy(&g); /* Flow.net that come in infomap_dir.tgz */ printf("# Flow (from infomap_dir.tgz)\n"); igraph_small(&g, 0, IGRAPH_DIRECTED, 0, 1, 1, 2, 2, 3, 3, 0, 1, 4, 4, 5, 5, 6, 6, 7, 7, 4, 5, 8, 8, 9, 9, 10, 10, 11, 11, 8, 9, 12, 12, 13, 13, 14, 14, 15, 15, 12, 13, 0, -1); infomap_test(&g); igraph_destroy(&g); /* MultiphysChemBioEco40W_weighted_dir.net */ printf("# MultiphysChemBioEco40W_weighted_dir.net (from infomap_dir.tgz)\n"); igraph_small(&g, 0, IGRAPH_DIRECTED, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 0, 7, 0, 8, 0, 9, 0, 16, 0, 18, 0, 0, 1, 2, 1, 3, 1, 5, 1, 6, 1, 7, 1, 9, 1, 10, 1, 16, 1, 18, 1, 0, 2, 3, 2, 4, 2, 5, 2, 6, 2, 7, 2, 0, 3, 1, 3, 2, 3, 4, 3, 5, 3, 6, 3, 7, 3, 8, 3, 9, 3, 10, 3, 11, 3, 13, 3, 14, 3, 16, 3, 17, 3, 18, 3, 19, 3, 26, 3, 30, 3, 1, 4, 3, 4, 5, 4, 6, 4, 13, 4, 18, 4, 0, 5, 1, 5, 2, 5, 3, 5, 6, 5, 7, 5, 9, 5, 1, 6, 3, 6, 7, 6, 9, 6, 16, 6, 0, 7, 1, 7, 2, 7, 3, 7, 5, 7, 6, 7, 9, 7, 3, 8, 5, 8, 3, 9, 7, 9, 12, 10, 13, 10, 14, 10, 15, 10, 16, 10, 17, 10, 18, 10, 19, 10, 21, 10, 3, 11, 18, 11, 10, 12, 14, 12, 16, 12, 17, 12, 18, 12, 3, 13, 10, 13, 14, 13, 16, 13, 10, 14, 12, 14, 13, 14, 15, 14, 16, 14, 17, 14, 18, 14, 10, 15, 14, 15, 18, 15, 0, 16, 2, 16, 3, 16, 6, 16, 10, 16, 12, 16, 13, 16, 14, 16, 17, 16, 18, 16, 10, 17, 12, 17, 14, 17, 18, 17, 3, 18, 10, 18, 12, 18, 14, 18, 15, 18, 16, 18, 17, 18, 19, 18, 21, 18, 11, 19, 16, 19, 17, 19, 16, 20, 18, 20, 21, 20, 22, 20, 23, 20, 24, 20, 25, 20, 26, 20, 27, 20, 28, 20, 29, 20, 3, 21, 14, 21, 18, 21, 20, 21, 22, 21, 23, 21, 24, 21, 25, 21, 26, 21, 27, 21, 28, 21, 29, 21, 35, 21, 36, 21, 38, 21, 18, 22, 20, 22, 21, 22, 23, 22, 24, 22, 25, 22, 26, 22, 27, 22, 29, 22, 3, 23, 20, 23, 21, 23, 22, 23, 24, 23, 25, 23, 26, 23, 27, 23, 28, 23, 29, 23, 35, 23, 38, 23, 39, 23, 20, 24, 21, 24, 23, 24, 25, 24, 26, 24, 27, 24, 28, 24, 29, 24, 9, 25, 20, 25, 21, 25, 22, 25, 23, 25, 24, 25, 26, 25, 27, 25, 28, 25, 29, 25, 18, 26, 20, 26, 21, 26, 22, 26, 23, 26, 25, 26, 27, 26, 28, 26, 29, 26, 30, 26, 32, 26, 35, 26, 36, 26, 38, 26, 39, 26, 3, 27, 14, 27, 20, 27, 21, 27, 22, 27, 23, 27, 24, 27, 25, 27, 26, 27, 28, 27, 29, 27, 38, 27, 3, 28, 18, 28, 20, 28, 21, 28, 23, 28, 24, 28, 25, 28, 26, 28, 27, 28, 29, 28, 35, 28, 14, 29, 16, 29, 18, 29, 20, 29, 21, 29, 22, 29, 23, 29, 24, 29, 25, 29, 26, 29, 27, 29, 28, 29, 31, 30, 32, 30, 33, 30, 34, 30, 35, 30, 36, 30, 38, 30, 39, 30, 30, 31, 32, 31, 34, 31, 36, 31, 30, 32, 34, 32, 35, 32, 36, 32, 30, 33, 32, 33, 34, 33, 35, 33, 36, 33, 38, 33, 30, 34, 31, 34, 32, 34, 33, 34, 35, 34, 36, 34, 38, 34, 39, 34, 26, 35, 30, 35, 32, 35, 33, 35, 34, 35, 36, 35, 38, 35, 39, 35, 30, 36, 34, 36, 35, 36, 38, 36, 39, 36, 34, 37, 26, 38, 30, 38, 32, 38, 33, 38, 34, 38, 35, 38, 36, 38, 39, 38, 26, 39, 30, 39, 33, 39, 34, 39, 35, 39, 36, 39, 38, 39, -1); igraph_vector_init_real(&weights, 306, 5.0, 3.0, 130.0, 4.0, 15.0, 9.0, 7.0, 1.0, 1.0, 3.0, 1.0, 1.0, 1.0, 34.0, 38.0, 2.0, 23.0, 1.0, 1.0, 3.0, 2.0, 2.0, 16.0, 1.0, 3.0, 1.0, 3.0, 63.0, 92.0, 72.0, 25.0, 447.0, 121.0, 65.0, 4.0, 16.0, 35.0, 1.0, 19.0, 1.0, 78.0, 1.0, 45.0, 1.0, 3.0, 1.0, 1.0, 25.0, 1.0, 3.0, 1.0, 1.0, 3.0, 36.0, 19.0, 136.0, 41.0, 96.0, 1.0, 7.0, 26.0, 1.0, 2.0, 2.0, 3.0, 2.0, 2.0, 23.0, 52.0, 4.0, 1.0, 2.0, 1.0, 3.0, 1.0, 11.0, 2.0, 17.0, 1.0, 5.0, 18.0, 86.0, 5.0, 1.0, 1.0, 1.0, 6.0, 1.0, 2.0, 2.0, 20.0, 4.0, 5.0, 1.0, 5.0, 12.0, 4.0, 1.0, 1.0, 4.0, 9.0, 40.0, 2.0, 1.0, 4.0, 1.0, 1.0, 48.0, 2.0, 18.0, 1.0, 7.0, 2.0, 2.0, 53.0, 25.0, 9.0, 1.0, 23.0, 8.0, 62.0, 29.0, 35.0, 4.0, 34.0, 35.0, 3.0, 1.0, 24.0, 1.0, 6.0, 2.0, 2.0, 22.0, 7.0, 2.0, 5.0, 14.0, 3.0, 28.0, 14.0, 20.0, 3.0, 1.0, 5.0, 77.0, 20.0, 25.0, 35.0, 55.0, 35.0, 115.0, 68.0, 105.0, 2.0, 2.0, 2.0, 4.0, 2.0, 17.0, 12.0, 3.0, 3.0, 11.0, 10.0, 7.0, 2.0, 12.0, 31.0, 11.0, 5.0, 11.0, 65.0, 39.0, 17.0, 26.0, 3.0, 4.0, 2.0, 3.0, 6.0, 4.0, 8.0, 1.0, 7.0, 7.0, 6.0, 1.0, 39.0, 42.0, 9.0, 6.0, 9.0, 5.0, 45.0, 43.0, 26.0, 1.0, 2.0, 6.0, 2.0, 15.0, 3.0, 9.0, 2.0, 1.0, 1.0, 1.0, 4.0, 2.0, 9.0, 2.0, 1.0, 2.0, 28.0, 80.0, 10.0, 18.0, 13.0, 17.0, 28.0, 40.0, 76.0, 1.0, 2.0, 1.0, 11.0, 37.0, 5.0, 11.0, 14.0, 4.0, 14.0, 10.0, 1.0, 1.0, 1.0, 1.0, 41.0, 121.0, 6.0, 21.0, 12.0, 30.0, 6.0, 141.0, 43.0, 2.0, 12.0, 6.0, 35.0, 10.0, 7.0, 2.0, 12.0, 6.0, 2.0, 11.0, 1.0, 7.0, 6.0, 5.0, 3.0, 1.0, 2.0, 1.0, 1.0, 1.0, 1.0, 67.0, 9.0, 9.0, 11.0, 10.0, 21.0, 7.0, 12.0, 9.0, 16.0, 7.0, 4.0, 11.0, 17.0, 37.0, 32.0, 9.0, 2.0, 2.0, 5.0, 4.0, 2.0, 7.0, 3.0, 3.0, 5.0, 8.0, 14.0, 3.0, 38.0, 3.0, 9.0, 2.0, 8.0, 21.0, 18.0, 58.0); infomap_weighted_test(&g, &weights); igraph_vector_destroy(&weights); igraph_destroy(&g); /* Two triangles connected by one edge */ printf("# Wiktionary english verbs (synonymy 2008)\n"); FILE *wikt = fopen("wikti_en_V_syn.elist", "r"); igraph_read_graph_edgelist(&g, wikt, 0, 0); fclose(wikt); gsumary(&g); infomap_test(&g); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/flow2.out0000644000076500000240000000033513524616144025507 0ustar tamasstaff00000000000000flow value: 4 flow: 4 0 2 2 2 first partition: 0 1 2 second partition: 3 edges in the cut: 1-3 (2), 2-3 (2), flow value: 1 flow: 1 1 0 0 0 0 0 first partition: 0 1 3 4 5 second partition: 2 edges in the cut: 1-2 (1), python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_layout_reingold_tilford.in0000644000076500000240000000034713524616144032535 0ustar tamasstaff000000000000001 0 2 0 3 0 4 0 5 0 6 1 7 13 8 0 9 5 10 1 11 0 12 2 13 0 14 2 15 13 16 11 17 5 18 4 19 4 20 4 21 4 22 28 23 4 24 10 25 24 26 2 27 4 28 5 29 8 30 14 31 33 32 14 33 14 34 12 35 37 36 14 37 16 38 14 39 12 40 9 41 37 42 36 43 41 44 41 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_hrg.c0000644000076500000240000000442713612122633026202 0ustar tamasstaff00000000000000/* -*- mode: C++ -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int main() { igraph_t graph; igraph_t full, tree; igraph_hrg_t hrg; igraph_t dendrogram; // int i, j; // igraph_vector_t neis; igraph_rng_seed(igraph_rng_default(), 42); // We need attributes igraph_i_set_attribute_table(&igraph_cattribute_table); igraph_full(&full, 10, /*directed=*/ 0, /*loops=*/ 0); igraph_tree(&tree, 15, /*children=*/ 2, /*type=*/ IGRAPH_TREE_UNDIRECTED); igraph_disjoint_union(&graph, &full, &tree); igraph_add_edge(&graph, 0, 10); igraph_destroy(&full); igraph_destroy(&tree); // Fit igraph_hrg_init(&hrg, igraph_vcount(&graph)); igraph_hrg_fit(&graph, &hrg, /*start=*/ 0, /*steps=*/ 0); // Create a graph from it igraph_hrg_dendrogram(&dendrogram, &hrg); // Print the tree, with labels // igraph_vector_init(&neis, 0); // for (i=0; i 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #define ALMOST_EQUALS(a, b) (fabs((a)-(b)) < 1e-8) int main() { igraph_t g; igraph_real_t cent; igraph_arpack_options_t arpack_options; /****************************/ /* in-star */ igraph_star(&g, 10, IGRAPH_STAR_IN, /*center=*/ 0); igraph_centralization_degree(&g, /*res=*/ 0, /*mode=*/ IGRAPH_IN, IGRAPH_NO_LOOPS, ¢, /*theoretical_max=*/ 0, /*normalized=*/ 1); if (cent != 1.0) { fprintf(stderr, "in-star, degree: %g\n", cent); return 1; } igraph_centralization_betweenness(&g, /*res=*/ 0, IGRAPH_UNDIRECTED, /*nobigint=*/ 1, ¢, /*theoretical_max=*/ 0, /*normalized=*/ 1); if (cent != 1.0) { fprintf(stderr, "in-star, betweenness: %g\n", cent); return 2; } igraph_set_warning_handler(igraph_warning_handler_ignore); igraph_centralization_closeness(&g, /*res=*/ 0, IGRAPH_IN, ¢, /*theoretical_max=*/ 0, /*normalization=*/ 1); igraph_set_warning_handler(igraph_warning_handler_print); if (!ALMOST_EQUALS(cent, 1.0)) { fprintf(stderr, "in-star, closeness: %g\n", cent); return 3; } igraph_destroy(&g); /****************************/ /* out-star */ igraph_star(&g, 10, IGRAPH_STAR_OUT, /*center=*/ 0); igraph_centralization_degree(&g, /*res=*/ 0, /*mode=*/ IGRAPH_OUT, IGRAPH_NO_LOOPS, ¢, /*theoretical_max=*/ 0, /*normalized=*/ 1); if (cent != 1.0) { fprintf(stderr, "out-star, degree: %g\n", cent); return 11; } igraph_centralization_betweenness(&g, /*res=*/ 0, IGRAPH_UNDIRECTED, /*nobigint=*/ 1, ¢, /*theoretical_max=*/ 0, /*normalized=*/ 1); if (cent != 1.0) { fprintf(stderr, "out-star, betweenness: %g\n", cent); return 12; } igraph_set_warning_handler(igraph_warning_handler_ignore); igraph_centralization_closeness(&g, /*res=*/ 0, IGRAPH_OUT, ¢, /*theoretical_max=*/ 0, /*normalization=*/ 1); igraph_set_warning_handler(igraph_warning_handler_print); if (!ALMOST_EQUALS(cent, 1.0)) { fprintf(stderr, "out-star, closeness: %g\n", cent); return 13; } igraph_destroy(&g); /****************************/ /* undricted star */ igraph_star(&g, 10, IGRAPH_STAR_UNDIRECTED, /*center=*/ 0); igraph_centralization_degree(&g, /*res=*/ 0, /*mode=*/ IGRAPH_ALL, IGRAPH_NO_LOOPS, ¢, /*theoretical_max=*/ 0, /*normalized=*/ 1); if (cent != 1.0) { fprintf(stderr, "undirected star, degree: %g\n", cent); return 21; } igraph_centralization_betweenness(&g, /*res=*/ 0, IGRAPH_UNDIRECTED, /*nobigint=*/ 1, ¢, /*theoretical_max=*/ 0, /*normalized=*/ 1); if (cent != 1.0) { fprintf(stderr, "undirected star, betweenness: %g\n", cent); return 22; } igraph_centralization_closeness(&g, /*res=*/ 0, IGRAPH_ALL, ¢, /*theoretical_max=*/ 0, /*normalization=*/ 1); if (!ALMOST_EQUALS(cent, 1.0)) { fprintf(stderr, "undirected star, closeness: %g\n", cent); return 23; } igraph_destroy(&g); /****************************/ /* single dyad */ igraph_small(&g, /*n=*/ 10, /*directed=*/ 0, 0, 1, -1); igraph_arpack_options_init(&arpack_options); igraph_centralization_eigenvector_centrality(&g, /*vector=*/ 0, /*value=*/ 0, /*directed=*/ 1, /*scale=*/ 1, &arpack_options, ¢, /*theoretical_max=*/ 0, /*normalization=*/ 1); if (!ALMOST_EQUALS(cent, 1.0)) { fprintf(stderr, "dyad, eigenvector centrality: %g\n", cent); return 24; } igraph_centralization_eigenvector_centrality(&g, /*vector=*/ 0, /*value=*/ 0, /*directed=*/ 1, /*scale=*/ 0, &arpack_options, ¢, /*theoretical_max=*/ 0, /*normalization=*/ 1); if (!ALMOST_EQUALS(cent, 1.0)) { fprintf(stderr, "dyad, eigenvector centrality, not scaled: %g\n", cent); return 25; } igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_is_loop.out0000644000076500000240000000004213524616144027447 0ustar tamasstaff00000000000000 0 0 0 0 0 0 0 1 1 1 0 0 0 0 1 1 python-igraph-0.8.0/vendor/source/igraph/examples/simple/pajek_bipartite2.out0000644000076500000240000000441213524616144027675 0ustar tamasstaff00000000000000Vertex 0: type=0 id="A" name="A" Vertex 1: type=0 id="B" name="B" Vertex 2: type=0 id="C" name="C" Vertex 3: type=0 id="D" name="D" Vertex 4: type=0 id="E" name="E" Vertex 5: type=0 id="F" name="F" Vertex 6: type=0 id="G" name="G" Vertex 7: type=0 id="H" name="H" Vertex 8: type=0 id="I" name="I" Vertex 9: type=0 id="J" name="J" Vertex 10: type=1 id="1" name="1" Vertex 11: type=1 id="2" name="2" Vertex 12: type=1 id="3" name="3" Vertex 13: type=1 id="4" name="4" Vertex 14: type=1 id="5" name="5" Edge 0 (10-0): weight=1 Edge 1 (10-1): weight=1 Edge 2 (11-1): weight=1 Edge 3 (10-2): weight=1 Edge 4 (11-2): weight=1 Edge 5 (12-2): weight=1 Edge 6 (10-3): weight=1 Edge 7 (11-3): weight=1 Edge 8 (12-3): weight=1 Edge 9 (13-3): weight=1 Edge 10 (10-4): weight=1 Edge 11 (11-4): weight=1 Edge 12 (12-4): weight=1 Edge 13 (13-4): weight=1 Edge 14 (14-4): weight=1 Edge 15 (14-5): weight=1 Edge 16 (10-6): weight=1 Edge 17 (14-6): weight=1 Edge 18 (10-7): weight=1 Edge 19 (11-7): weight=1 Edge 20 (13-7): weight=1 Edge 21 (14-7): weight=1 Edge 22 (10-9): weight=1 Edge 23 (12-9): weight=1 Edge 24 (14-9): weight=1 --- Vertex 0: type=0 id="A" name="A" Vertex 1: type=0 id="B" name="B" Vertex 2: type=0 id="C" name="C" Vertex 3: type=0 id="D" name="D" Vertex 4: type=0 id="E" name="E" Vertex 5: type=0 id="F" name="F" Vertex 6: type=0 id="G" name="G" Vertex 7: type=0 id="H" name="H" Vertex 8: type=0 id="I" name="I" Vertex 9: type=0 id="J" name="J" Vertex 10: type=1 id="1" name="1" Vertex 11: type=1 id="2" name="2" Vertex 12: type=1 id="3" name="3" Vertex 13: type=1 id="4" name="4" Vertex 14: type=1 id="5" name="5" Edge 0 (10-0): weight=1 Edge 1 (10-1): weight=1 Edge 2 (11-1): weight=1 Edge 3 (10-2): weight=1 Edge 4 (11-2): weight=1 Edge 5 (12-2): weight=1 Edge 6 (10-3): weight=1 Edge 7 (11-3): weight=1 Edge 8 (12-3): weight=1 Edge 9 (13-3): weight=1 Edge 10 (10-4): weight=1 Edge 11 (11-4): weight=1 Edge 12 (12-4): weight=1 Edge 13 (13-4): weight=1 Edge 14 (14-4): weight=1 Edge 15 (14-5): weight=1 Edge 16 (10-6): weight=1 Edge 17 (14-6): weight=1 Edge 18 (10-7): weight=1 Edge 19 (11-7): weight=1 Edge 20 (13-7): weight=1 Edge 21 (14-7): weight=1 Edge 22 (10-9): weight=1 Edge 23 (12-9): weight=1 Edge 24 (14-9): weight=1 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_get_shortest_paths_dijkstra.out0000644000076500000240000000016413524616144033614 0ustar tamasstaff00000000000000 0 0 1 0 1 2 3 0 1 2 3 4 5 0 1 2 0 1 0 0 1 0 1 2 3 0 9 8 7 6 5 0 1 2 0 1 0 0 1 0 3 0 1 5 0 1 2 0 1 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_transitive_closure_dag.out0000644000076500000240000000004413524616144032544 0ustar tamasstaff000000000000004 5 4 3 0 0 2 1 0 0 0 0 2 1 1 4 5 6 python-igraph-0.8.0/vendor/source/igraph/examples/simple/pajek_bip2.net0000644000076500000240000000037113524616144026443 0ustar tamasstaff00000000000000*vertices 15 10 1 "A" 2 "B" 3 "C" 4 "D" 5 "E" 6 "F" 7 "G" 8 "H" 9 "I" 10 "J" 11 "1" 12 "2" 13 "3" 14 "4" 15 "5" *matrix 1 0 0 0 0 1 1 1 0 0 0 2 1 1 1 0 0 3 1 1 1 1 0 4 1 1 1 1 1 5 0 0 0 0 1 1 1 0 0 0 1 2 1 1 0 1 1 4 0 0 0 0 0 0 1 0 1 0 1 3 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_realize_degree_sequence.c0000644000076500000240000001055513612122633032257 0ustar tamasstaff00000000000000 #include #include void print_edges(const igraph_t *graph) { long ecount = igraph_ecount(graph); long i; for (i = 0; i < ecount; ++i) { printf("%d %d\n", IGRAPH_FROM(graph, i), IGRAPH_TO(graph, i)); } printf("\n"); } void print_vector(igraph_vector_t *v) { long int i, n; n = igraph_vector_size(v); for (i = 0; i < n; i++) if (i != n - 1 ) { printf("%li ", (long int) VECTOR(*v)[i]); } else { printf("%li", (long int) VECTOR(*v)[i]); } printf("\n"); } int main() { igraph_t graph; { igraph_vector_t ds; const igraph_real_t rawds[] = { 3, 2, 2, 1 }; igraph_vector_view(&ds, &rawds[0], sizeof(rawds) / sizeof(igraph_real_t)); print_vector(&ds); printf("\n"); igraph_realize_degree_sequence(&graph, &ds, NULL, IGRAPH_REALIZE_DEGSEQ_LARGEST); print_edges(&graph); igraph_destroy(&graph); igraph_realize_degree_sequence(&graph, &ds, NULL, IGRAPH_REALIZE_DEGSEQ_SMALLEST); print_edges(&graph); igraph_destroy(&graph); igraph_realize_degree_sequence(&graph, &ds, NULL, IGRAPH_REALIZE_DEGSEQ_INDEX); print_edges(&graph); igraph_destroy(&graph); } { igraph_vector_t ds; const igraph_real_t rawds[] = {1, 3, 3, 4, 1, 2, 1, 1, 1, 3}; igraph_vector_view(&ds, &rawds[0], sizeof(rawds) / sizeof(igraph_real_t)); print_vector(&ds); printf("\n"); igraph_realize_degree_sequence(&graph, &ds, NULL, IGRAPH_REALIZE_DEGSEQ_LARGEST); print_edges(&graph); igraph_destroy(&graph); igraph_realize_degree_sequence(&graph, &ds, NULL, IGRAPH_REALIZE_DEGSEQ_SMALLEST); print_edges(&graph); igraph_destroy(&graph); igraph_realize_degree_sequence(&graph, &ds, NULL, IGRAPH_REALIZE_DEGSEQ_INDEX); print_edges(&graph); igraph_destroy(&graph); } { igraph_vector_t ds; const igraph_real_t rawds[] = {2, 0, 3, 2, 2, 2, 2, 3}; igraph_vector_view(&ds, &rawds[0], sizeof(rawds) / sizeof(igraph_real_t)); print_vector(&ds); printf("\n"); igraph_realize_degree_sequence(&graph, &ds, NULL, IGRAPH_REALIZE_DEGSEQ_LARGEST); print_edges(&graph); igraph_destroy(&graph); igraph_realize_degree_sequence(&graph, &ds, NULL, IGRAPH_REALIZE_DEGSEQ_SMALLEST); print_edges(&graph); igraph_destroy(&graph); igraph_realize_degree_sequence(&graph, &ds, NULL, IGRAPH_REALIZE_DEGSEQ_INDEX); print_edges(&graph); igraph_destroy(&graph); } { igraph_vector_t ods, ids; const igraph_real_t rawods[] = {3, 0, 1, 1, 1, 1, 0, 1}; const igraph_real_t rawids[] = {2, 1, 0, 2, 2, 1, 0, 0}; igraph_vector_view(&ods, &rawods[0], sizeof(rawods) / sizeof(igraph_real_t)); igraph_vector_view(&ids, &rawids[0], sizeof(rawids) / sizeof(igraph_real_t)); print_vector(&ods); print_vector(&ids); printf("\n"); igraph_realize_degree_sequence(&graph, &ods, &ids, IGRAPH_REALIZE_DEGSEQ_LARGEST); print_edges(&graph); igraph_destroy(&graph); igraph_realize_degree_sequence(&graph, &ods, &ids, IGRAPH_REALIZE_DEGSEQ_SMALLEST); print_edges(&graph); igraph_destroy(&graph); igraph_realize_degree_sequence(&graph, &ods, &ids, IGRAPH_REALIZE_DEGSEQ_INDEX); print_edges(&graph); igraph_destroy(&graph); } { igraph_vector_t ods, ids; const igraph_real_t rawods[] = {3, 1, 2, 3, 1, 2, 2}; const igraph_real_t rawids[] = {2, 2, 1, 2, 3, 2, 2}; igraph_vector_view(&ods, &rawods[0], sizeof(rawods) / sizeof(igraph_real_t)); igraph_vector_view(&ids, &rawids[0], sizeof(rawids) / sizeof(igraph_real_t)); print_vector(&ods); print_vector(&ids); printf("\n"); igraph_realize_degree_sequence(&graph, &ods, &ids, IGRAPH_REALIZE_DEGSEQ_LARGEST); print_edges(&graph); igraph_destroy(&graph); igraph_realize_degree_sequence(&graph, &ods, &ids, IGRAPH_REALIZE_DEGSEQ_SMALLEST); print_edges(&graph); igraph_destroy(&graph); igraph_realize_degree_sequence(&graph, &ods, &ids, IGRAPH_REALIZE_DEGSEQ_INDEX); print_edges(&graph); igraph_destroy(&graph); } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_strvector.c0000644000076500000240000001363513612122634027457 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void strvector_print(const igraph_strvector_t *sv) { long int i, s = igraph_strvector_size(sv); for (i = 0; i < s; i++) { printf("---%s---\n", STR(*sv, i)); } } int main() { igraph_strvector_t sv1, sv2; char *str1; int i; /* igraph_strvector_init, igraph_strvector_destroy */ igraph_strvector_init(&sv1, 10); igraph_strvector_destroy(&sv1); igraph_strvector_init(&sv1, 0); igraph_strvector_destroy(&sv1); /* igraph_strvector_get, igraph_strvector_set */ igraph_strvector_init(&sv1, 5); for (i = 0; i < igraph_strvector_size(&sv1); i++) { igraph_strvector_get(&sv1, i, &str1); printf("---%s---\n", str1); } igraph_strvector_set(&sv1, 0, "zero"); igraph_strvector_set(&sv1, 1, "one"); igraph_strvector_set(&sv1, 2, "two"); igraph_strvector_set(&sv1, 3, "three"); igraph_strvector_set(&sv1, 4, "four"); for (i = 0; i < igraph_strvector_size(&sv1); i++) { igraph_strvector_get(&sv1, i, &str1); printf("---%s---\n", str1); } /* igraph_strvector_remove_section, igraph_strvector_remove, igraph_strvector_resize, igraph_strvector_size */ igraph_strvector_remove_section(&sv1, 0, 5); if (igraph_strvector_size(&sv1) != 0) { return 1; } igraph_strvector_resize(&sv1, 10); igraph_strvector_set(&sv1, 0, "zero"); igraph_strvector_set(&sv1, 1, "one"); igraph_strvector_set(&sv1, 2, "two"); igraph_strvector_set(&sv1, 3, "three"); igraph_strvector_set(&sv1, 4, "four"); igraph_strvector_resize(&sv1, 5); for (i = 0; i < igraph_strvector_size(&sv1); i++) { igraph_strvector_get(&sv1, i, &str1); printf("---%s---\n", str1); } igraph_strvector_resize(&sv1, 0); if (igraph_strvector_size(&sv1) != 0) { return 1; } igraph_strvector_resize(&sv1, 10); igraph_strvector_set(&sv1, 0, "zero"); igraph_strvector_set(&sv1, 1, "one"); igraph_strvector_set(&sv1, 2, "two"); igraph_strvector_set(&sv1, 3, "three"); igraph_strvector_set(&sv1, 4, "four"); igraph_strvector_resize(&sv1, 5); for (i = 0; i < igraph_strvector_size(&sv1); i++) { igraph_strvector_get(&sv1, i, &str1); printf("---%s---\n", str1); } /* igraph_strvector_move_interval */ igraph_strvector_move_interval(&sv1, 3, 5, 0); for (i = 0; i < igraph_strvector_size(&sv1); i++) { igraph_strvector_get(&sv1, i, &str1); printf("---%s---\n", str1); } /* igraph_strvector_copy */ igraph_strvector_copy(&sv2, &sv1); for (i = 0; i < igraph_strvector_size(&sv2); i++) { igraph_strvector_get(&sv2, i, &str1); printf("---%s---\n", str1); } igraph_strvector_resize(&sv1, 0); igraph_strvector_destroy(&sv2); igraph_strvector_copy(&sv2, &sv1); if (igraph_strvector_size(&sv2) != 0) { return 2; } igraph_strvector_destroy(&sv2); /* igraph_strvector_add */ igraph_strvector_add(&sv1, "zeroth"); igraph_strvector_add(&sv1, "first"); igraph_strvector_add(&sv1, "second"); igraph_strvector_add(&sv1, "third"); igraph_strvector_add(&sv1, "fourth"); for (i = 0; i < igraph_strvector_size(&sv1); i++) { igraph_strvector_get(&sv1, i, &str1); printf("---%s---\n", str1); } /* TODO: igraph_strvector_permdelete */ /* TODO: igraph_strvector_remove_negidx */ igraph_strvector_destroy(&sv1); /* append */ printf("---\n"); igraph_strvector_init(&sv1, 0); igraph_strvector_init(&sv2, 0); igraph_strvector_append(&sv1, &sv2); strvector_print(&sv1); printf("---\n"); igraph_strvector_resize(&sv1, 3); igraph_strvector_append(&sv1, &sv2); strvector_print(&sv1); printf("---\n"); igraph_strvector_append(&sv2, &sv1); strvector_print(&sv2); printf("---\n"); igraph_strvector_set(&sv1, 0, "0"); igraph_strvector_set(&sv1, 1, "1"); igraph_strvector_set(&sv1, 2, "2"); igraph_strvector_set(&sv2, 0, "3"); igraph_strvector_set(&sv2, 1, "4"); igraph_strvector_set(&sv2, 2, "5"); igraph_strvector_append(&sv1, &sv2); strvector_print(&sv1); igraph_strvector_destroy(&sv1); igraph_strvector_destroy(&sv2); /* clear */ igraph_strvector_init(&sv1, 3); igraph_strvector_set(&sv1, 0, "0"); igraph_strvector_set(&sv1, 1, "1"); igraph_strvector_set(&sv1, 2, "2"); igraph_strvector_clear(&sv1); if (igraph_strvector_size(&sv1) != 0) { return 3; } igraph_strvector_resize(&sv1, 4); strvector_print(&sv1); igraph_strvector_set(&sv1, 0, "one"); igraph_strvector_set(&sv1, 2, "two"); strvector_print(&sv1); igraph_strvector_destroy(&sv1); /* STR */ igraph_strvector_init(&sv1, 5); igraph_strvector_set(&sv1, 0, "one"); igraph_strvector_set(&sv1, 1, "two"); igraph_strvector_set(&sv1, 2, "three"); igraph_strvector_set(&sv1, 3, "four"); igraph_strvector_set(&sv1, 4, "five"); strvector_print(&sv1); igraph_strvector_destroy(&sv1); if (!IGRAPH_FINALLY_STACK_EMPTY) { return 4; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_maximal_cliques2.c0000644000076500000240000000652113612122633030656 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2013 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int sort_cmp(const void *a, const void *b) { const igraph_vector_t **da = (const igraph_vector_t **) a; const igraph_vector_t **db = (const igraph_vector_t **) b; int i, alen = igraph_vector_size(*da), blen = igraph_vector_size(*db); if (alen != blen) { return (alen < blen) - (alen > blen); } for (i = 0; i < alen; i++) { int ea = VECTOR(**da)[i], eb = VECTOR(**db)[i]; if (ea != eb) { return (ea > eb) - (ea < eb); } } return 0; } void sort_cliques(igraph_vector_ptr_t *cliques) { int i, n = igraph_vector_ptr_size(cliques); for (i = 0; i < n; i++) { igraph_vector_t *v = VECTOR(*cliques)[i]; igraph_vector_sort(v); } igraph_qsort(VECTOR(*cliques), (size_t) n, sizeof(igraph_vector_t *), sort_cmp); } int print_and_destroy(igraph_vector_ptr_t *cliques) { int i, n = igraph_vector_ptr_size(cliques); sort_cliques(cliques); for (i = 0; i < n; i++) { igraph_vector_t *v = VECTOR(*cliques)[i]; igraph_vector_print(v); igraph_vector_destroy(v); } igraph_vector_ptr_destroy_all(cliques); return 0; } int main() { igraph_t graph; igraph_vector_ptr_t cliques; igraph_integer_t no; igraph_rng_seed(igraph_rng_default(), 42); igraph_ring(&graph, /*n=*/ 10, /*directed=*/ 0, /*mutual=*/ 0, /*circular=*/ 1); igraph_vector_ptr_init(&cliques, 0); igraph_maximal_cliques(&graph, &cliques, /*min_size=*/ 0, /*max_size=*/ 0); igraph_maximal_cliques_count(&graph, &no, /*min_size=*/ 0, /*max_size=*/ 0 /*no limit*/); if (no != igraph_vector_ptr_size(&cliques)) { return 1; } print_and_destroy(&cliques); igraph_destroy(&graph); printf("---\n"); /* ----------------------------------------------------------- */ igraph_erdos_renyi_game(&graph, IGRAPH_ERDOS_RENYI_GNP, /*n=*/ 50, /*p=*/ 0.5, /*directed=*/ 0, /*loops=*/ 0); igraph_vector_ptr_init(&cliques, 0); igraph_maximal_cliques(&graph, &cliques, /*min_size=*/ 8, /*max_size=*/ 0); igraph_maximal_cliques_count(&graph, &no, /*min_size=*/ 8, /*max_size=*/ 0 /*no limit*/); if (no != igraph_vector_ptr_size(&cliques)) { return 2; } print_and_destroy(&cliques); igraph_destroy(&graph); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_scg_grouping2.out0000644000076500000240000000012013524616144030550 0ustar tamasstaff000000000000000 1 1 2 2 2 2 2 2 2 0 0 0 2 2 2 2 2 2 2 0 0 0 2 2 2 2 2 2 2 0 1 1 2 3 3 3 3 3 3 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_qsort_r.c0000644000076500000240000000350713612122633027111 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard st, Cambridge, MA 02139, USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int comp(void *extra, const void *a, const void *b) { igraph_vector_t *v = (igraph_vector_t*) extra; int *aa = (int*) a; int *bb = (int*) b; igraph_real_t aaa = VECTOR(*v)[*aa]; igraph_real_t bbb = VECTOR(*v)[*bb]; if (aaa < bbb) { return -1; } else if (aaa > bbb) { return 1; } return 0; } int main() { const int len = 100; igraph_vector_t v; igraph_vector_int_t idx; int i; igraph_rng_seed(igraph_rng_default(), 42); igraph_vector_init(&v, len); igraph_vector_int_init(&idx, len); for (i = 0; i < len; i++) { VECTOR(v)[i] = i; VECTOR(idx)[i] = i; } igraph_vector_shuffle(&v); igraph_qsort_r(VECTOR(idx), len, sizeof(VECTOR(idx)[0]), (void*) &v, comp); for (i = 0; i < len; i++) { printf("%g ", VECTOR(v)[ VECTOR(idx)[i] ]); } printf("\n"); igraph_vector_int_destroy(&idx); igraph_vector_destroy(&v); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_eigen_matrix.out0000644000076500000240000000017513524616144030465 0ustar tamasstaff000000000000001+0i 0.316228+0i 0.316228+0i 0.316228+0i 0.316228+0i 0.316228+0i 0.316228+0i 0.316228+0i 0.316228+0i 0.316228+0i 0.316228+0i python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_eigen_matrix4.out0000644000076500000240000000046413524616144030552 0ustar tamasstaff00000000000000-0.533366+6.22277i 6.77236+3.96835i -5.06056+2.90197i 49.9655+0i 12.0702+0i -3.82636+0i -8.56628+0i -5.06056-2.90197i 6.77236-3.96835i -0.533366-6.22277i -0.533366-6.22277i 6.77236-3.96835i -5.06056-2.90197i -8.56628+0i -3.82636+0i 12.0702+0i 49.9655+0i -5.06056+2.90197i 6.77236+3.96835i -0.533366+6.22277i python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_rng_get_exp.out0000644000076500000240000002154113524616144030313 0ustar tamasstaff000000000000000.476523 0.237234 0.0508589 0.223753 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0.942172 0.0299165 0.255038 0.431412 0.373455 0.190001 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_eigen_matrix_symmetric.out0000644000076500000240000000030013524616144032547 0ustar tamasstaff0000000000000056.5915 14.2507 -12.9906 11.1434 -10.4525 56.5915 14.2507 -12.9906 11.1434 -10.4525 -8.0168 7.44269 -4.93995 56.5915 -12.9906 14.2507 -10.4525 11.1434 1.36756 4.60399 -4.93995 7.44269 -8.0168 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_sparsemat9.c0000644000076500000240000000505713614300625027513 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard street, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #define DIM1 10 #define DIM2 5 #define DIM3 6 #define INT(a) (igraph_rng_get_integer(igraph_rng_default(), 0, (a))) #define REAL() (igraph_rng_get_normal(igraph_rng_default(), 0, 1)) int main() { igraph_sparsemat_t sA, sB, sC; igraph_matrix_t A1, A2, A3, B, C; int i; igraph_rng_seed(igraph_rng_default(), 42); igraph_sparsemat_init(&sA, DIM1, DIM2, 20); for (i = 0; i < 10; i++) { igraph_sparsemat_entry(&sA, INT(DIM1 - 1), INT(DIM2 - 1), REAL()); } igraph_sparsemat_compress(&sA, &sB); igraph_sparsemat_destroy(&sA); igraph_sparsemat_init(&sA, DIM2, DIM3, 20); for (i = 0; i < 10; i++) { igraph_sparsemat_entry(&sA, INT(DIM2 - 1), INT(DIM3 - 1), REAL()); } igraph_sparsemat_compress(&sA, &sC); igraph_sparsemat_destroy(&sA); igraph_matrix_init(&B, 0, 0); igraph_sparsemat_as_matrix(&B, &sB); igraph_matrix_init(&C, 0, 0); igraph_sparsemat_as_matrix(&C, &sC); /* All possible products */ igraph_sparsemat_multiply(&sB, &sC, &sA); igraph_matrix_init(&A1, 0, 0); igraph_sparsemat_as_matrix(&A1, &sA); igraph_matrix_init(&A2, 0, 0); igraph_sparsemat_dense_multiply(&B, &sC, &A2); igraph_matrix_init(&A3, 0, 0); igraph_sparsemat_multiply_by_dense(&sB, &C, &A3); if (igraph_matrix_maxdifference(&A1, &A2) > 1e-10 || igraph_matrix_maxdifference(&A2, &A3) > 1e-10) { return 1; } igraph_sparsemat_destroy(&sA); igraph_sparsemat_destroy(&sB); igraph_sparsemat_destroy(&sC); igraph_matrix_destroy(&A1); igraph_matrix_destroy(&A2); igraph_matrix_destroy(&A3); igraph_matrix_destroy(&B); igraph_matrix_destroy(&C); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/flow2.c0000644000076500000240000002023213612122633025111 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int check_flow(int errorinc, const igraph_t *graph, igraph_real_t flow_value, const igraph_vector_t *flow, const igraph_vector_t *cut, const igraph_vector_t *partition, const igraph_vector_t *partition2, long int source, long int target, const igraph_vector_t *capacity, igraph_bool_t print) { long int i, n = igraph_vcount(graph), m = igraph_ecount(graph); long int nc = igraph_vector_size(cut); igraph_vector_t inedges, outedges; igraph_bool_t directed = igraph_is_directed(graph); igraph_real_t cutsize; igraph_t graph_copy; igraph_matrix_t sp; if (print) { printf("flow value: %g\n", (double) flow_value); printf("flow: "); igraph_vector_print(flow); printf("first partition: "); igraph_vector_print(partition); printf("second partition: "); igraph_vector_print(partition2); printf("edges in the cut: "); for (i = 0; i < nc; i++) { long int edge = VECTOR(*cut)[i]; long int from = IGRAPH_FROM(graph, edge); long int to = IGRAPH_TO (graph, edge); if (!directed && from > to) { igraph_integer_t tmp = from; from = to; to = tmp; } printf("%li-%li (%g), ", from, to, VECTOR(*capacity)[edge]); } printf("\n"); } fflush(stdout); /* Always less than the capacity */ for (i = 0; i < m; i++) { if (VECTOR(*flow)[i] > VECTOR(*capacity)[i]) { return errorinc + 3; } } /* What comes in goes out, but only in directed graphs, there is no in and out in undirected ones... */ if (igraph_is_directed(graph)) { igraph_vector_init(&inedges, 0); igraph_vector_init(&outedges, 0); for (i = 0; i < n; i++) { long int n1, n2, j; igraph_real_t in_flow = 0.0, out_flow = 0.0; igraph_incident(graph, &inedges, i, IGRAPH_IN); igraph_incident(graph, &outedges, i, IGRAPH_OUT); n1 = igraph_vector_size(&inedges); n2 = igraph_vector_size(&outedges); for (j = 0; j < n1; j++) { long int e = VECTOR(inedges)[j]; in_flow += VECTOR(*flow)[e]; } for (j = 0; j < n2; j++) { long int e = VECTOR(outedges)[j]; out_flow += VECTOR(*flow)[e]; } if (i == source) { if (in_flow > 0) { return errorinc + 4; } if (out_flow != flow_value) { return errorinc + 5; } } else if (i == target) { if (out_flow > 0) { return errorinc + 6; } if (in_flow != flow_value) { return errorinc + 7; } } else { if (in_flow != out_flow) { return errorinc + 8; } } } igraph_vector_destroy(&inedges); igraph_vector_destroy(&outedges); } /* Check the minimum cut size*/ for (i = 0, cutsize = 0.0; i < nc; i++) { long int edge = VECTOR(*cut)[i]; cutsize += VECTOR(*capacity)[edge]; } if (fabs(cutsize - flow_value) > 1e-14) { return errorinc + 9; } /* Check that the cut indeed cuts */ igraph_copy(&graph_copy, graph); igraph_delete_edges(&graph_copy, igraph_ess_vector(cut)); igraph_matrix_init(&sp, 1, 1); igraph_shortest_paths(&graph_copy, &sp, /*from=*/ igraph_vss_1(source), /*to=*/ igraph_vss_1(target), IGRAPH_OUT); if (MATRIX(sp, 0, 0) != IGRAPH_INFINITY) { return errorinc + 10; } igraph_matrix_destroy(&sp); igraph_destroy(&graph_copy); return 0; } int main() { igraph_t g; igraph_real_t flow_value; igraph_vector_t cut; igraph_vector_t capacity; igraph_vector_t partition, partition2; igraph_vector_t flow; long int i, n; igraph_integer_t source, target; FILE *infile; igraph_real_t flow_value2 = 0.0; int check; igraph_maxflow_stats_t stats; igraph_vector_init(&capacity, 0); /***************/ infile = fopen("ak-4102.max", "r"); igraph_read_graph_dimacs(&g, infile, 0, 0, &source, &target, &capacity, IGRAPH_DIRECTED); fclose(infile); igraph_vector_init(&cut, 0); igraph_vector_init(&partition, 0); igraph_vector_init(&partition2, 0); igraph_vector_init(&flow, 0); igraph_maxflow(&g, &flow_value, &flow, &cut, &partition, &partition2, source, target, &capacity, &stats); if (flow_value != 8207) { return 1; } n = igraph_vector_size(&cut); for (i = 0; i < n; i++) { long int e = VECTOR(cut)[i]; flow_value2 += VECTOR(capacity)[e]; } if (flow_value != flow_value2) { return 2; } /* Check the flow */ if ( (check = check_flow(0, &g, flow_value, &flow, &cut, &partition, &partition2, source, target, &capacity, /*print=*/ 0))) { return check; } igraph_destroy(&g); igraph_vector_destroy(&capacity); igraph_vector_destroy(&cut); igraph_vector_destroy(&partition); igraph_vector_destroy(&partition2); igraph_vector_destroy(&flow); /* ------------------------------------- */ igraph_small(&g, 4, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 1, 2, 1, 3, 2, 3, -1); igraph_vector_init_int_end(&capacity, -1, 4, 2, 10, 2, 2, -1); igraph_vector_init(&cut, 0); igraph_vector_init(&partition, 0); igraph_vector_init(&partition2, 0); igraph_vector_init(&flow, 0); igraph_maxflow(&g, &flow_value, &flow, &cut, &partition, &partition2, /*source=*/ 0, /*target=*/ 3, &capacity, &stats); if ( (check = check_flow(20, &g, flow_value, &flow, &cut, &partition, &partition2, 0, 3, &capacity, /*print=*/ 1))) { return check; } igraph_vector_destroy(&cut); igraph_vector_destroy(&partition2); igraph_vector_destroy(&partition); igraph_vector_destroy(&capacity); igraph_vector_destroy(&flow); igraph_destroy(&g); /* ------------------------------------- */ igraph_small(&g, 6, IGRAPH_DIRECTED, 0, 1, 1, 2, 2, 3, 0, 5, 5, 4, 4, 3, 3, 0, -1); igraph_vector_init_int_end(&capacity, -1, 3, 1, 2, 10, 1, 3, 2, -1); igraph_vector_init(&cut, 0); igraph_vector_init(&partition, 0); igraph_vector_init(&partition2, 0); igraph_vector_init(&flow, 0); igraph_maxflow(&g, &flow_value, &flow, &cut, &partition, &partition2, /*source=*/ 0, /*target=*/ 2, &capacity, &stats); if ( (check = check_flow(40, &g, flow_value, &flow, &cut, &partition, &partition2, 0, 2, &capacity, /*print=*/ 1))) { return check; } igraph_vector_destroy(&cut); igraph_vector_destroy(&partition2); igraph_vector_destroy(&partition); igraph_vector_destroy(&capacity); igraph_vector_destroy(&flow); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_biconnected_components.out0000644000076500000240000000005413524616144032530 0ustar tamasstaff00000000000000 2 4 5 0 1 2 3 4 5 6 0 1 2 3 4 5 0 1 2 python-igraph-0.8.0/vendor/source/igraph/examples/simple/blas.c0000644000076500000240000000313113614300625025001 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2008-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_matrix_t m; igraph_vector_t x, y; igraph_vector_init_real(&x, 3, 1.0, 2.0, 3.0); igraph_vector_init_real(&y, 4, 4.0, 5.0, 6.0, 7.0); igraph_matrix_init(&m, 4, 3); MATRIX(m, 0, 0) = 1; MATRIX(m, 0, 1) = 2; MATRIX(m, 0, 2) = 3; MATRIX(m, 1, 0) = 2; MATRIX(m, 1, 1) = 3; MATRIX(m, 1, 2) = 4; MATRIX(m, 2, 0) = 3; MATRIX(m, 2, 1) = 4; MATRIX(m, 2, 2) = 5; MATRIX(m, 3, 0) = 4; MATRIX(m, 3, 1) = 5; MATRIX(m, 3, 2) = 6; igraph_blas_dgemv(0, 2, &m, &x, 3, &y); igraph_vector_print(&y); igraph_vector_destroy(&x); igraph_vector_destroy(&y); igraph_matrix_destroy(&m); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/d_indheap.out0000644000076500000240000000014213524616144026365 0ustar tamasstaff00000000000000 10 10 9 9 8 8 7 7 6 6 5 5 4 4 3 3 2 2 1 1 0 0 9 8 8 7 7 6 6 5 5 4 4 3 3 2 2 1 1 0 0 1 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_community_multilevel.c0000644000076500000240000000673013614300625031710 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sts=4 sw=4 et: */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void show_results(igraph_t *g, igraph_vector_t *membership, igraph_matrix_t *memberships, igraph_vector_t *modularity, FILE* f) { long int i, j, no_of_nodes = igraph_vcount(g); j = igraph_vector_which_max(modularity); for (i = 0; i < igraph_vector_size(membership); i++) { if (VECTOR(*membership)[i] != MATRIX(*memberships, j, i)) { fprintf(f, "WARNING: best membership vector element %li does not match the best one in the membership matrix\n", i); } } fprintf(f, "Modularities:\n"); igraph_vector_print(modularity); for (i = 0; i < igraph_matrix_nrow(memberships); i++) { for (j = 0; j < no_of_nodes; j++) { fprintf(f, "%ld ", (long int)MATRIX(*memberships, i, j)); } fprintf(f, "\n"); } fprintf(f, "\n"); } int main() { igraph_t g; igraph_vector_t modularity, membership, edges; igraph_matrix_t memberships; int i, j, k; igraph_vector_init(&modularity, 0); igraph_vector_init(&membership, 0); igraph_matrix_init(&memberships, 0, 0); /* Unweighted test graph from the paper of Blondel et al */ igraph_small(&g, 16, IGRAPH_UNDIRECTED, 0, 2, 0, 3, 0, 4, 0, 5, 1, 2, 1, 4, 1, 7, 2, 4, 2, 5, 2, 6, 3, 7, 4, 10, 5, 7, 5, 11, 6, 7, 6, 11, 8, 9, 8, 10, 8, 11, 8, 14, 8, 15, 9, 12, 9, 14, 10, 11, 10, 12, 10, 13, 10, 14, 11, 13, -1); igraph_community_multilevel(&g, 0, &membership, &memberships, &modularity); show_results(&g, &membership, &memberships, &modularity, stdout); igraph_destroy(&g); /* Ring of 30 cliques */ igraph_vector_init(&edges, 0); for (i = 0; i < 30; i++) { for (j = 0; j < 5; j++) { for (k = j + 1; k < 5; k++) { igraph_vector_push_back(&edges, i * 5 + j); igraph_vector_push_back(&edges, i * 5 + k); } } } for (i = 0; i < 30; i++) { igraph_vector_push_back(&edges, i * 5 % 150); igraph_vector_push_back(&edges, (i * 5 + 6) % 150); } igraph_create(&g, &edges, 150, 0); igraph_community_multilevel(&g, 0, &membership, &memberships, &modularity); show_results(&g, &membership, &memberships, &modularity, stdout); igraph_destroy(&g); igraph_vector_destroy(&modularity); igraph_vector_destroy(&membership); igraph_vector_destroy(&edges); igraph_matrix_destroy(&memberships); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_sparsemat3.c0000644000076500000240000002042113614300625027475 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int permute(const igraph_matrix_t *M, const igraph_vector_int_t *p, const igraph_vector_int_t *q, igraph_matrix_t *res) { long int nrow = igraph_vector_int_size(p); long int ncol = igraph_vector_int_size(q); long int i, j; igraph_matrix_resize(res, nrow, ncol); for (i = 0; i < nrow; i++) { for (j = 0; j < ncol; j++) { int ii = VECTOR(*p)[i]; int jj = VECTOR(*q)[j]; MATRIX(*res, i, j) = MATRIX(*M, ii, jj); } } return 0; } int permute_rows(const igraph_matrix_t *M, const igraph_vector_int_t *p, igraph_matrix_t *res) { long int nrow = igraph_vector_int_size(p); long int ncol = igraph_matrix_ncol(M); long int i, j; igraph_matrix_resize(res, nrow, ncol); for (i = 0; i < nrow; i++) { for (j = 0; j < ncol; j++) { int ii = VECTOR(*p)[i]; MATRIX(*res, i, j) = MATRIX(*M, ii, j); } } return 0; } int permute_cols(const igraph_matrix_t *M, const igraph_vector_int_t *q, igraph_matrix_t *res) { long int nrow = igraph_matrix_nrow(M); long int ncol = igraph_vector_int_size(q); long int i, j; igraph_matrix_resize(res, nrow, ncol); for (i = 0; i < nrow; i++) { for (j = 0; j < ncol; j++) { int jj = VECTOR(*q)[j]; MATRIX(*res, i, j) = MATRIX(*M, i, jj); } } return 0; } int random_permutation(igraph_vector_int_t *vec) { /* We just do size(vec) * 2 swaps */ long int one, two, i, n = igraph_vector_int_size(vec); int tmp; for (i = 0; i < 2 * n; i++) { one = RNG_INTEGER(0, n - 1); two = RNG_INTEGER(0, n - 1); tmp = VECTOR(*vec)[one]; VECTOR(*vec)[one] = VECTOR(*vec)[two]; VECTOR(*vec)[two] = tmp; } return 0; } igraph_bool_t check_same(const igraph_sparsemat_t *A, const igraph_matrix_t *M) { long int nrow = igraph_sparsemat_nrow(A); long int ncol = igraph_sparsemat_ncol(A); long int j, p, nzero = 0; if (nrow != igraph_matrix_nrow(M) || ncol != igraph_matrix_ncol(M)) { return 0; } for (j = 0; j < A->cs->n; j++) { for (p = A->cs->p[j]; p < A->cs->p[j + 1]; p++) { long int to = A->cs->i[p]; igraph_real_t value = A->cs->x[p]; if (value != MATRIX(*M, to, j)) { return 0; } nzero += 1; } } for (j = 0; j < nrow; j++) { for (p = 0; p < ncol; p++) { if (MATRIX(*M, j, p) != 0) { nzero -= 1; } } } return nzero == 0; } int main() { igraph_sparsemat_t A, B; igraph_matrix_t M, N; igraph_vector_int_t p, q; long int i; /* Permutation of a matrix */ #define NROW 10 #define NCOL 5 #define EDGES NROW*NCOL/3 igraph_matrix_init(&M, NROW, NCOL); igraph_sparsemat_init(&A, NROW, NCOL, EDGES); for (i = 0; i < EDGES; i++) { long int r = RNG_INTEGER(0, NROW - 1); long int c = RNG_INTEGER(0, NCOL - 1); igraph_real_t value = RNG_INTEGER(1, 5); MATRIX(M, r, c) = MATRIX(M, r, c) + value; igraph_sparsemat_entry(&A, r, c, value); } igraph_sparsemat_compress(&A, &B); igraph_sparsemat_destroy(&A); igraph_vector_int_init_seq(&p, 0, NROW - 1); igraph_vector_int_init_seq(&q, 0, NCOL - 1); /* Identity */ igraph_matrix_init(&N, 0, 0); permute(&M, &p, &q, &N); igraph_sparsemat_permute(&B, &p, &q, &A); igraph_sparsemat_dupl(&A); if (! check_same(&A, &N)) { return 1; } /* Random permutation */ random_permutation(&p); random_permutation(&q); permute(&M, &p, &q, &N); igraph_sparsemat_destroy(&A); igraph_sparsemat_permute(&B, &p, &q, &A); igraph_sparsemat_dupl(&A); if (! check_same(&A, &N)) { return 2; } igraph_vector_int_destroy(&p); igraph_vector_int_destroy(&q); igraph_sparsemat_destroy(&A); igraph_sparsemat_destroy(&B); igraph_matrix_destroy(&M); igraph_matrix_destroy(&N); #undef NROW #undef NCOL #undef EDGES /* Indexing */ #define NROW 10 #define NCOL 5 #define EDGES NROW*NCOL/3 #define I_NROW 6 #define I_NCOL 3 igraph_matrix_init(&M, NROW, NCOL); igraph_sparsemat_init(&A, NROW, NCOL, EDGES); for (i = 0; i < EDGES; i++) { long int r = RNG_INTEGER(0, NROW - 1); long int c = RNG_INTEGER(0, NCOL - 1); igraph_real_t value = RNG_INTEGER(1, 5); MATRIX(M, r, c) = MATRIX(M, r, c) + value; igraph_sparsemat_entry(&A, r, c, value); } igraph_sparsemat_compress(&A, &B); igraph_sparsemat_destroy(&A); igraph_vector_int_init(&p, I_NROW); igraph_vector_int_init(&q, I_NCOL); for (i = 0; i < I_NROW; i++) { VECTOR(p)[i] = RNG_INTEGER(0, I_NROW - 1); } for (i = 0; i < I_NCOL; i++) { VECTOR(p)[i] = RNG_INTEGER(0, I_NCOL - 1); } igraph_matrix_init(&N, 0, 0); permute(&M, &p, &q, &N); igraph_sparsemat_index(&B, &p, &q, &A, 0); if (! check_same(&A, &N)) { return 3; } /* A single element */ igraph_vector_int_resize(&p, 1); igraph_vector_int_resize(&q, 1); for (i = 0; i < 100; i++) { igraph_real_t value; VECTOR(p)[0] = RNG_INTEGER(0, NROW - 1); VECTOR(q)[0] = RNG_INTEGER(0, NCOL - 1); igraph_sparsemat_index(&B, &p, &q, /*res=*/ 0, &value); if (value != MATRIX(M, VECTOR(p)[0], VECTOR(q)[0])) { return 4; } } igraph_sparsemat_destroy(&A); for (i = 0; i < 100; i++) { igraph_real_t value; VECTOR(p)[0] = RNG_INTEGER(0, NROW - 1); VECTOR(q)[0] = RNG_INTEGER(0, NCOL - 1); igraph_sparsemat_index(&B, &p, &q, /*res=*/ &A, &value); igraph_sparsemat_destroy(&A); if (value != MATRIX(M, VECTOR(p)[0], VECTOR(q)[0])) { return 4; } } igraph_vector_int_destroy(&p); igraph_vector_int_destroy(&q); igraph_sparsemat_destroy(&B); igraph_matrix_destroy(&M); igraph_matrix_destroy(&N); /* Indexing only the rows or the columns */ igraph_matrix_init(&M, NROW, NCOL); igraph_sparsemat_init(&A, NROW, NCOL, EDGES); for (i = 0; i < EDGES; i++) { long int r = RNG_INTEGER(0, NROW - 1); long int c = RNG_INTEGER(0, NCOL - 1); igraph_real_t value = RNG_INTEGER(1, 5); MATRIX(M, r, c) = MATRIX(M, r, c) + value; igraph_sparsemat_entry(&A, r, c, value); } igraph_sparsemat_compress(&A, &B); igraph_sparsemat_destroy(&A); igraph_vector_int_init(&p, I_NROW); igraph_vector_int_init(&q, I_NCOL); for (i = 0; i < I_NROW; i++) { VECTOR(p)[i] = RNG_INTEGER(0, I_NROW - 1); } for (i = 0; i < I_NCOL; i++) { VECTOR(p)[i] = RNG_INTEGER(0, I_NCOL - 1); } igraph_matrix_init(&N, 0, 0); permute_rows(&M, &p, &N); igraph_sparsemat_index(&B, &p, 0, &A, 0); if (! check_same(&A, &N)) { return 5; } permute_cols(&M, &q, &N); igraph_sparsemat_destroy(&A); igraph_sparsemat_index(&B, 0, &q, &A, 0); if (! check_same(&A, &N)) { return 6; } igraph_sparsemat_destroy(&A); igraph_sparsemat_destroy(&B); igraph_vector_int_destroy(&p); igraph_vector_int_destroy(&q); igraph_matrix_destroy(&M); igraph_matrix_destroy(&N); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/edgelist6.dl0000644000076500000240000000025413524616144026134 0ustar tamasstaff00000000000000DL n=5 format = edgelist1 labels: george, sally, jim, billy, jane labels embedded: data: george sally george jim 2 sally jim billy george 1 jane jim 1e-5 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_disjoint_union.out0000644000076500000240000000020613524616144031040 0ustar tamasstaff00000000000000 0 1 1 2 2 2 2 3 4 5 5 6 6 6 6 8 0 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_density.c0000644000076500000240000001015713612122633027076 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2013 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void test_density(const igraph_t *graph, igraph_bool_t loops) { igraph_real_t density; if (igraph_density(graph, &density, loops)) { printf("FAILED!\n"); return; } if (igraph_is_nan(density)) { printf("nan\n"); } else { printf("%.4f\n", density); } } int main() { igraph_t g; igraph_vector_t v; igraph_vector_init(&v, 0); /* Test graphs with no vertices and no edges */ igraph_create(&g, &v, 0, IGRAPH_UNDIRECTED); test_density(&g, 0); test_density(&g, 1); igraph_destroy(&g); igraph_create(&g, &v, 0, IGRAPH_DIRECTED); test_density(&g, 0); test_density(&g, 1); igraph_destroy(&g); printf("======\n"); /* Test graphs with one vertex and no edges */ igraph_create(&g, &v, 1, IGRAPH_UNDIRECTED); test_density(&g, 0); test_density(&g, 1); igraph_destroy(&g); igraph_create(&g, &v, 1, IGRAPH_DIRECTED); test_density(&g, 0); test_density(&g, 1); igraph_destroy(&g); printf("======\n"); /* Test graphs with one vertex and a loop edge */ igraph_vector_resize(&v, 2); VECTOR(v)[0] = 0; VECTOR(v)[1] = 0; igraph_create(&g, &v, 1, IGRAPH_UNDIRECTED); test_density(&g, 1); igraph_destroy(&g); igraph_create(&g, &v, 1, IGRAPH_DIRECTED); test_density(&g, 1); igraph_destroy(&g); printf("======\n"); /* Test graphs with one vertex and two loop edges */ igraph_vector_resize(&v, 4); VECTOR(v)[0] = 0; VECTOR(v)[1] = 0; VECTOR(v)[2] = 0; VECTOR(v)[3] = 0; igraph_create(&g, &v, 1, IGRAPH_UNDIRECTED); test_density(&g, 1); igraph_destroy(&g); igraph_create(&g, &v, 1, IGRAPH_DIRECTED); test_density(&g, 1); igraph_destroy(&g); printf("======\n"); /* Test graphs with two vertices and one edge between them */ igraph_vector_resize(&v, 2); VECTOR(v)[0] = 0; VECTOR(v)[1] = 1; igraph_create(&g, &v, 2, IGRAPH_UNDIRECTED); test_density(&g, 0); test_density(&g, 1); igraph_destroy(&g); igraph_create(&g, &v, 1, IGRAPH_DIRECTED); test_density(&g, 0); test_density(&g, 1); igraph_destroy(&g); printf("======\n"); /* Test graphs with two vertices, one edge between them and a loop on one * of them */ igraph_vector_resize(&v, 4); VECTOR(v)[0] = 0; VECTOR(v)[1] = 1; VECTOR(v)[2] = 1; VECTOR(v)[3] = 1; igraph_create(&g, &v, 2, IGRAPH_UNDIRECTED); test_density(&g, 1); igraph_destroy(&g); igraph_create(&g, &v, 1, IGRAPH_DIRECTED); test_density(&g, 1); igraph_destroy(&g); printf("======\n"); /* Test graphs with two vertices, one edge between them and a loop on both * of them */ igraph_vector_resize(&v, 6); VECTOR(v)[0] = 0; VECTOR(v)[1] = 1; VECTOR(v)[2] = 1; VECTOR(v)[3] = 1; VECTOR(v)[4] = 0; VECTOR(v)[5] = 0; igraph_create(&g, &v, 2, IGRAPH_UNDIRECTED); test_density(&g, 1); igraph_destroy(&g); igraph_create(&g, &v, 1, IGRAPH_DIRECTED); test_density(&g, 1); igraph_destroy(&g); printf("======\n"); /* Zachary karate club graph */ igraph_famous(&g, "zachary"); test_density(&g, 0); test_density(&g, 1); igraph_destroy(&g); igraph_vector_destroy(&v); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_layout_merge.c0000644000076500000240000000531013612122633030106 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include "igraph_types_internal.h" #include #include int igraph_i_layout_merge_dla(igraph_i_layout_mergegrid_t *grid, long int actg, igraph_real_t *x, igraph_real_t *y, igraph_real_t r, igraph_real_t cx, igraph_real_t cy, igraph_real_t startr, igraph_real_t killr); int main() { /*******************/ /* Testing the DLA */ /*******************/ long int nodes = 10; igraph_i_layout_mergegrid_t grid; igraph_vector_t x, y, r; long int i; igraph_rng_seed(igraph_rng_default(), 42); igraph_vector_init(&x, nodes); igraph_vector_init(&y, nodes); igraph_vector_init(&r, nodes); igraph_i_layout_mergegrid_init(&grid, -5, 5, 100, -5, 5, 100); /* radius */ for (i = 0; i < nodes; i++) { VECTOR(r)[i] = rand() / (double)RAND_MAX; } igraph_vector_sort(&r); /* place */ VECTOR(x)[0] = 0; VECTOR(y)[0] = 0; igraph_i_layout_merge_place_sphere(&grid, 0, 0, VECTOR(r)[nodes - 1], 0); for (i = 1; i < nodes; i++) { /* fprintf(stderr, "%li ", i); */ igraph_i_layout_merge_dla(&grid, i, igraph_vector_e_ptr(&x, i), igraph_vector_e_ptr(&y, i), VECTOR(r)[nodes - i - 1], 0, 0, 4, 7); igraph_i_layout_merge_place_sphere(&grid, VECTOR(x)[i], VECTOR(y)[i], VECTOR(r)[nodes - i - 1], i); } /* for (i=0; i 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include void print_vector(igraph_vector_t *v) { long int i, l = igraph_vector_size(v); for (i = 0; i < l; i++) { printf(" %li", (long int) VECTOR(*v)[i]); } printf("\n"); } int print_free_vector_ptr(igraph_vector_ptr_t *v) { long int i, l = igraph_vector_ptr_size(v); printf("---\n"); for (i = 0; i < l; i++) { print_vector(VECTOR(*v)[i]); igraph_vector_destroy(VECTOR(*v)[i]); igraph_Free(VECTOR(*v)[i]); } printf("===\n"); return 0; } int main() { igraph_t left, right, uni; igraph_vector_t v; igraph_vector_ptr_t glist; igraph_vector_t edge_map1, edge_map2; igraph_vector_ptr_t edgemaps; long int i; igraph_vector_init(&edge_map1, 0); igraph_vector_init(&edge_map2, 0); igraph_vector_init_int_end(&v, -1, 0, 1, 1, 2, 2, 2, 2, 3, -1); igraph_create(&left, &v, 0, IGRAPH_DIRECTED); igraph_vector_destroy(&v); igraph_vector_init_int_end(&v, -1, 0, 1, 1, 2, 2, 2, 2, 4, -1); igraph_create(&right, &v, 0, IGRAPH_DIRECTED); igraph_vector_destroy(&v); igraph_union(&uni, &left, &right, &edge_map1, &edge_map2); igraph_write_graph_edgelist(&uni, stdout); igraph_vector_print(&edge_map1); igraph_vector_print(&edge_map2); igraph_destroy(&uni); igraph_destroy(&left); igraph_destroy(&right); igraph_vector_destroy(&edge_map1); igraph_vector_destroy(&edge_map2); /* Empty graph list */ igraph_vector_ptr_init(&glist, 0); igraph_vector_ptr_init(&edgemaps, 0); igraph_union_many(&uni, &glist, &edgemaps); if (!igraph_is_directed(&uni) || igraph_vcount(&uni) != 0) { return 1; } print_free_vector_ptr(&edgemaps); igraph_vector_ptr_destroy(&glist); igraph_destroy(&uni); /* Non-empty graph list */ igraph_vector_ptr_init(&glist, 10); for (i = 0; i < igraph_vector_ptr_size(&glist); i++) { VECTOR(glist)[i] = calloc(1, sizeof(igraph_t)); igraph_vector_init_int_end(&v, -1, 0, 1, 1, 0, -1); igraph_create(VECTOR(glist)[i], &v, 0, IGRAPH_DIRECTED); igraph_vector_destroy(&v); } igraph_union_many(&uni, &glist, &edgemaps); igraph_write_graph_edgelist(&uni, stdout); for (i = 0; i < igraph_vector_ptr_size(&glist); i++) { igraph_destroy(VECTOR(glist)[i]); free(VECTOR(glist)[i]); } print_free_vector_ptr(&edgemaps); igraph_vector_ptr_destroy(&glist); igraph_destroy(&uni); /* Another non-empty graph list */ igraph_vector_ptr_init(&glist, 10); for (i = 0; i < igraph_vector_ptr_size(&glist); i++) { VECTOR(glist)[i] = calloc(1, sizeof(igraph_t)); igraph_vector_init_int_end(&v, -1, i, i + 1, 1, 0, -1); igraph_create(VECTOR(glist)[i], &v, 0, IGRAPH_DIRECTED); igraph_vector_destroy(&v); } igraph_union_many(&uni, &glist, &edgemaps); igraph_write_graph_edgelist(&uni, stdout); for (i = 0; i < igraph_vector_ptr_size(&glist); i++) { igraph_destroy(VECTOR(glist)[i]); free(VECTOR(glist)[i]); } print_free_vector_ptr(&edgemaps); igraph_vector_ptr_destroy(&glist); igraph_destroy(&uni); /* Undirected graph list*/ igraph_vector_ptr_init(&glist, 10); for (i = 0; i < igraph_vector_ptr_size(&glist); i++) { VECTOR(glist)[i] = calloc(1, sizeof(igraph_t)); igraph_vector_init_int_end(&v, -1, i, i + 1, 1, 0, -1); igraph_create(VECTOR(glist)[i], &v, 0, IGRAPH_UNDIRECTED); igraph_vector_destroy(&v); } igraph_union_many(&uni, &glist, &edgemaps); igraph_write_graph_edgelist(&uni, stdout); for (i = 0; i < igraph_vector_ptr_size(&glist); i++) { igraph_destroy(VECTOR(glist)[i]); free(VECTOR(glist)[i]); } print_free_vector_ptr(&edgemaps); igraph_vector_ptr_destroy(&glist); igraph_destroy(&uni); igraph_vector_ptr_destroy(&edgemaps); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_read_graph_lgl-1.lgl0000644000076500000240000000005413524616144031045 0ustar tamasstaff00000000000000# foo bar foobar 5 # foobar bat tab # tab python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_hrg3.c0000644000076500000240000000475113612122633026265 0ustar tamasstaff00000000000000/* -*- mode: C++ -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int main() { igraph_t karate; igraph_vector_t edges, prob; igraph_rng_seed(igraph_rng_default(), 42); igraph_small(&karate, 34, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 0, 7, 0, 8, 0, 10, 0, 11, 0, 12, 0, 13, 0, 17, 0, 19, 0, 21, 0, 31, 1, 2, 1, 3, 1, 7, 1, 13, 1, 17, 1, 19, 1, 21, 1, 30, 2, 3, 2, 7, 2, 27, 2, 28, 2, 32, 2, 9, 2, 8, 2, 13, 3, 7, 3, 12, 3, 13, 4, 6, 4, 10, 5, 6, 5, 10, 5, 16, 6, 16, 8, 30, 8, 32, 8, 33, 9, 33, 13, 33, 14, 32, 14, 33, 15, 32, 15, 33, 18, 32, 18, 33, 19, 33, 20, 32, 20, 33, 22, 32, 22, 33, 23, 25, 23, 27, 23, 32, 23, 33, 23, 29, 24, 25, 24, 27, 24, 31, 25, 31, 26, 29, 26, 33, 27, 33, 28, 31, 28, 33, 29, 32, 29, 33, 30, 32, 30, 33, 31, 32, 31, 33, 32, 33, -1); igraph_vector_init(&edges, 0); igraph_vector_init(&prob, 0); igraph_hrg_predict(&karate, &edges, &prob, /* hrg= */ 0, /* start= */ 0, /* num_samples= */ 100, /* num_bins= */ 25); /* Check */ igraph_vector_print(&edges); igraph_vector_print(&prob); igraph_vector_destroy(&edges); igraph_vector_destroy(&prob); igraph_destroy(&karate); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_scg_grouping2.c0000644000076500000240000000536413612122633030173 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g; igraph_matrix_t adj, V; igraph_vector_t groups; igraph_eigen_which_t which; igraph_matrix_init(&adj, 0, 0); igraph_matrix_init(&V, 0, 0); igraph_vector_init(&groups, 0); igraph_rng_seed(igraph_rng_default(), 42); igraph_tree(&g, 10, /* children= */ 3, IGRAPH_TREE_UNDIRECTED); igraph_get_adjacency(&g, &adj, IGRAPH_GET_ADJACENCY_BOTH, /*eids=*/ 0); which.pos = IGRAPH_EIGEN_LM; which.howmany = 1; igraph_eigen_matrix_symmetric(&adj, /*sparsemat=*/ 0, /*fun=*/ 0, igraph_vcount(&g), /*extra=*/ 0, /*algorithm=*/ IGRAPH_EIGEN_LAPACK, &which, /*options=*/ 0, /*storage=*/ 0, /*values=*/ 0, &V); igraph_scg_grouping(&V, &groups, /*intervals=*/ 3, /*intervals_vector=*/ 0, IGRAPH_SCG_SYMMETRIC, IGRAPH_SCG_OPTIMUM, /*p=*/ 0, /*maxiter=*/ 10000); igraph_vector_print(&groups); igraph_scg_grouping(&V, &groups, /*intervals=*/ 3, /*intervals_vector=*/ 0, IGRAPH_SCG_SYMMETRIC, IGRAPH_SCG_INTERV_KM, /*p=*/ 0, /*maxiter=*/ 10000); igraph_vector_print(&groups); igraph_scg_grouping(&V, &groups, /*intervals=*/ 3, /*intervals_vector=*/ 0, IGRAPH_SCG_SYMMETRIC, IGRAPH_SCG_INTERV, /*p=*/ 0, /*maxiter=*/ 10000); igraph_vector_print(&groups); igraph_scg_grouping(&V, &groups, /*(ignored) intervals=*/ 0, /*intervals_vector=*/ 0, IGRAPH_SCG_SYMMETRIC, IGRAPH_SCG_EXACT, /*p=*/ 0, /*maxiter=*/ 10000); igraph_vector_print(&groups); igraph_vector_destroy(&groups); igraph_matrix_destroy(&V); igraph_matrix_destroy(&adj); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_tree.out0000644000076500000240000000005413524616144026745 0ustar tamasstaff00000000000000Is it an in-tree? Yes Is it an out-tree? No python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_scg_grouping3.out0000644000076500000240000000025013524616144030555 0ustar tamasstaff000000000000000.433013 0.57735 0.57735 0.144338 0.144338 0.144338 0.144338 0.144338 0.144338 0.144338 0 1 1 0 2 2 2 2 2 2 1 2 2 0 2 2 2 2 2 2 1 2 2 0 2 2 2 2 2 2 1 2 2 0 3 3 3 3 3 3 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_bipartite_create.c0000644000076500000240000000414513612122633030725 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2008-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_real_t edges2[] = {0, 1, 1, 2, 3, 4, 5, 6, 6, 5, 1, 4, 1, 6, 0, 3 }; igraph_real_t edges3[] = {0, 1, 1, 2, 3, 4, 5, 6, 6, 5, 2, 4, 1, 6, 0, 3 }; igraph_t g; igraph_vector_bool_t types; igraph_vector_t edges; long int i; int ret; igraph_vector_view(&edges, edges2, sizeof(edges2) / sizeof(igraph_real_t)); igraph_vector_bool_init(&types, igraph_vector_max(&edges) + 1); for (i = 0; i < igraph_vector_bool_size(&types); i++) { VECTOR(types)[i] = i % 2; } igraph_create_bipartite(&g, &types, &edges, /*directed=*/ 1); igraph_write_graph_edgelist(&g, stdout); igraph_vector_bool_destroy(&types); igraph_destroy(&g); /* Error handling */ igraph_set_error_handler(igraph_error_handler_ignore); igraph_vector_view(&edges, edges3, sizeof(edges3) / sizeof(igraph_real_t)); igraph_vector_bool_init(&types, igraph_vector_max(&edges) + 1); for (i = 0; i < igraph_vector_bool_size(&types); i++) { VECTOR(types)[i] = i % 2; } ret = igraph_create_bipartite(&g, &types, &edges, /*directed=*/ 1); if (ret != IGRAPH_EINVAL) { return 1; } igraph_vector_bool_destroy(&types); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_bfs2.c0000644000076500000240000001012513612122633026246 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include igraph_bool_t bfs_callback(const igraph_t *graph, igraph_integer_t vid, igraph_integer_t pred, igraph_integer_t succ, igraph_integer_t rank, igraph_integer_t dist, void *extra) { printf(" %li", (long int) vid); return 0; } int main() { igraph_t graph, ring; igraph_vector_t order, rank, father, pred, succ, dist; igraph_vector_t restricted; igraph_vector_t roots; long int i; igraph_ring(&ring, 10, /*directed=*/ 0, /*mutual=*/ 0, /*circular=*/ 1); igraph_disjoint_union(&graph, &ring, &ring); igraph_destroy(&ring); igraph_vector_init(&order, 0); igraph_vector_init(&rank, 0); igraph_vector_init(&father, 0); igraph_vector_init(&pred, 0); igraph_vector_init(&succ, 0); igraph_vector_init(&dist, 0); igraph_bfs(&graph, /*root=*/0, /*roots=*/ 0, /*neimode=*/ IGRAPH_OUT, /*unreachable=*/ 1, /*restricted=*/ 0, &order, &rank, &father, &pred, &succ, &dist, /*callback=*/ 0, /*extra=*/ 0); igraph_vector_print(&order); igraph_vector_print(&rank); igraph_vector_print(&father); igraph_vector_print(&pred); igraph_vector_print(&succ); igraph_vector_print(&dist); igraph_vector_destroy(&order); igraph_vector_destroy(&rank); igraph_vector_destroy(&father); igraph_vector_destroy(&pred); igraph_vector_destroy(&succ); igraph_vector_destroy(&dist); /* Test the callback */ igraph_bfs(&graph, /*root=*/ 0, /*roots=*/ 0, /*neimode=*/ IGRAPH_OUT, /*unreachable=*/ 1, /*restricted=*/ 0, 0, 0, 0, 0, 0, 0, &bfs_callback, 0); printf("\n"); /* Test different roots */ igraph_bfs(&graph, /*root=*/ 2, /*roots=*/ 0, /*neimode=*/ IGRAPH_OUT, /*unreachable=*/ 1, /*restricted=*/ 0, 0, 0, 0, 0, 0, 0, &bfs_callback, 0); printf("\n"); /* Test restricted */ igraph_vector_init(&restricted, 0); for (i = 5; i < igraph_vcount(&graph); i++) { igraph_vector_push_back(&restricted, i); } igraph_bfs(&graph, /*root=*/ 5, /*roots=*/ 0, /*neimode=*/ IGRAPH_OUT, /*unreachable=*/ 1, &restricted, 0, 0, 0, 0, 0, 0, &bfs_callback, 0); printf("\n"); /* Root not in restricted set */ igraph_bfs(&graph, /*root=*/ 4, /*roots=*/ 0, /*neimode=*/ IGRAPH_OUT, /*unreachable=*/ 1, &restricted, 0, 0, 0, 0, 0, 0, &bfs_callback, 0); printf("\n"); igraph_bfs(&graph, /*root=*/ 3, /*roots=*/ 0, /*neimode=*/ IGRAPH_OUT, /*unreachable=*/ 0, &restricted, 0, 0, 0, 0, 0, 0, &bfs_callback, 0); printf("\n"); /* Multiple root vertices */ igraph_vector_init(&roots, 3); VECTOR(roots)[0] = 3; VECTOR(roots)[1] = 4; VECTOR(roots)[2] = 6; igraph_bfs(&graph, /*root=*/ -1, &roots, /*neimode=*/ IGRAPH_OUT, /*unreachable=*/ 0, &restricted, 0, 0, 0, 0, 0, 0, &bfs_callback, 0); printf("\n"); igraph_vector_destroy(&roots); igraph_vector_destroy(&restricted); igraph_destroy(&graph); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_maximal_cliques.out0000644000076500000240000000102013524616144031155 0ustar tamasstaff000000000000000 1 2 3 4 5 6 7 8 9 0 1 3 4 5 7 270 279 534 606 0 1 3 4 5 7 270 534 606 919 9 164 307 416 613 725 749 822 940 949 13 56 75 273 498 534 691 812 864 999 13 82 150 392 418 594 691 810 985 987 13 150 380 418 480 594 749 810 985 987 22 307 450 476 498 520 671 772 831 852 129 205 228 241 247 251 274 377 606 954 129 205 228 247 377 380 392 831 940 954 13 150 380 392 418 594 810 985 987 129 205 228 241 247 377 380 940 954 1 534 999 9 749 987 107 609 835 137 273 691 193 594 691 295 307 450 307 831 940 338 610 840 380 749 940 0 1 2 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_barabasi_game2.c0000644000076500000240000000710013612122633030230 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int main() { igraph_t g; igraph_bool_t simple; igraph_barabasi_game(/* graph= */ &g, /* n= */ 100, /* power= */ 1.0, /* m= */ 2, /* outseq= */ 0, /* outpref= */ 0, /* A= */ 1.0, /* directed= */ IGRAPH_DIRECTED, /* algo= */ IGRAPH_BARABASI_PSUMTREE, /* start_from= */ 0); if (igraph_ecount(&g) != 197) { return 1; } if (igraph_vcount(&g) != 100) { return 2; } igraph_is_simple(&g, &simple); if (!simple) { return 3; } igraph_destroy(&g); /* ============================== */ igraph_barabasi_game(/* graph= */ &g, /* n= */ 100, /* power= */ 1.0, /* m= */ 2, /* outseq= */ 0, /* outpref= */ 0, /* A= */ 1.0, /* directed= */ IGRAPH_DIRECTED, /* algo= */ IGRAPH_BARABASI_PSUMTREE_MULTIPLE, /* start_from= */ 0); if (igraph_ecount(&g) != 198) { return 4; } if (igraph_vcount(&g) != 100) { return 5; } igraph_is_simple(&g, &simple); if (simple) { return 6; } igraph_destroy(&g); /* ============================== */ igraph_barabasi_game(/* graph= */ &g, /* n= */ 100, /* power= */ 1.0, /* m= */ 2, /* outseq= */ 0, /* outpref= */ 0, /* A= */ 1.0, /* directed= */ IGRAPH_DIRECTED, /* algo= */ IGRAPH_BARABASI_BAG, /* start_from= */ 0); if (igraph_ecount(&g) != 198) { return 7; } if (igraph_vcount(&g) != 100) { return 8; } igraph_is_simple(&g, &simple); if (simple) { return 9; } igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_roulette_wheel_imitation.c0000644000076500000240000002661213612122633032526 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* Test suite for stochastic imitation via roulette wheel selection. Copyright (C) 2011 Minh Van Nguyen This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include #define R_INTEGER(a,b) (igraph_rng_get_integer(igraph_rng_default(), (a), (b))) /* test parameters structure */ typedef struct { igraph_t *graph; igraph_integer_t vertex; igraph_bool_t islocal; igraph_vector_t *quantities; igraph_vector_t *strategies; igraph_vector_t *known_strats; igraph_neimode_t mode; int retval; } strategy_test_t; /* Error tests. That is, we expect error codes to be returned from such tests. */ int error_tests() { igraph_t g, gzero, h; igraph_vector_t quant, quantzero, strat, stratzero; int i, n, nvert, ret; strategy_test_t *test; /* nonempty graph */ igraph_small(&g, /*nvert=*/ 0, IGRAPH_UNDIRECTED, 0, 1, 1, 2, 2, 0, -1); igraph_empty(&h, 0, 0); /* empty graph */ igraph_vector_init(&quant, 1); /* quantities vector */ igraph_vector_init(&strat, 2); /* strategies vector */ igraph_small(&gzero, /*nvert=*/ 0, IGRAPH_UNDIRECTED, 0, 3, 0, 4, 1, 2, 1, 4, 1, 5, 2, 3, 2, 4, 3, 4, -1); nvert = igraph_vcount(&gzero); igraph_vector_init_real(&stratzero, nvert, 1.0, 0.0, 1.0, 2.0, 0.0, 3.0); igraph_vector_init(&quantzero, nvert); /* vector of zeros */ /* test parameters */ /*graph--vert--islocal--quantities--strategies--known_strats--mode--retval*/ /* null pointer for graph */ strategy_test_t null_graph = {NULL, 0, 1, NULL, NULL, NULL, IGRAPH_ALL, IGRAPH_EINVAL}; /* null pointer for quantities vector */ strategy_test_t null_quant = {&g, 0, 1, NULL, NULL, NULL, IGRAPH_ALL, IGRAPH_EINVAL}; /* null pointer for strategies vector */ strategy_test_t null_strat = {&g, 0, 1, &quant, NULL, NULL, IGRAPH_ALL, IGRAPH_EINVAL}; /* empty graph */ strategy_test_t empty_graph = {&h, 0, 1, &quant, &strat, NULL, IGRAPH_ALL, IGRAPH_EINVAL}; /* length of quantities vector different from number of vertices */ strategy_test_t qdiff_length = {&g, 0, 1, &quant, &strat, NULL, IGRAPH_ALL, IGRAPH_EINVAL}; /* length of strategies vector different from number of vertices */ strategy_test_t sdiff_length = {&g, 0, 1, &quant, &strat, NULL, IGRAPH_ALL, IGRAPH_EINVAL}; /* quantities vector contains all zeros */ strategy_test_t zero_quant = {&gzero, 4, 1, &quantzero, &stratzero, NULL, IGRAPH_ALL, IGRAPH_EINVAL}; strategy_test_t *all_checks[] = {/* 1 */ &null_graph, /* 2 */ &null_quant, /* 3 */ &null_strat, /* 4 */ &empty_graph, /* 5 */ &qdiff_length, /* 6 */ &sdiff_length, /* 7 */ &zero_quant }; /* Run the error tests. We expect error to be raised for each test. */ igraph_set_error_handler(igraph_error_handler_ignore); n = 7; i = 0; while (i < n) { test = all_checks[i]; ret = igraph_roulette_wheel_imitation(test->graph, test->vertex, test->islocal, test->quantities, test->strategies, test->mode); if (ret != test->retval) { printf("Error test no. %d failed.\n", (int)(i + 1)); return IGRAPH_FAILURE; } i++; } /* clean up */ igraph_destroy(&g); igraph_destroy(&gzero); igraph_destroy(&h); igraph_vector_destroy(&quant); igraph_vector_destroy(&quantzero); igraph_vector_destroy(&strat); igraph_vector_destroy(&stratzero); return IGRAPH_SUCCESS; } /* A game on a graph with 5 vertices and 7 edges. Use roulette wheel selection * to update strategies. This example also illustrates how a choice of * perspective (whether local or global) could affect the range of * possible strategies a vertex could adopt. */ int roulette_test() { igraph_t g; igraph_bool_t success; igraph_vector_t *known, quant, strat, stratcopy; igraph_vector_t known0, known1, known2, known3, known4, known5; int i, k, n, nvert, ret;; strategy_test_t *test; /* the game network */ igraph_small(&g, /*nvert=*/ 0, IGRAPH_UNDIRECTED, 0, 3, 0, 4, 1, 2, 1, 4, 1, 5, 2, 3, 2, 4, 3, 4, -1); nvert = igraph_vcount(&g); /* strategies vector; the strategy space is {0, 1, 2, 3} */ /* V[i] is strategy of vertex i */ igraph_vector_init_real(&strat, nvert, 1.0, 0.0, 1.0, 2.0, 0.0, 3.0); /* quantities vector; V[i] is quantity of vertex i */ igraph_vector_init_real(&quant, nvert, 0.56, 0.13, 0.26, 0.73, 0.67, 0.82); /* possible strategies each vertex can adopt */ igraph_vector_init_real(&known0, /*n=*/ 3, 0.0, 1.0, 2.0); /* local */ igraph_vector_init_real(&known1, /*n=*/ 3, 0.0, 1.0, 3.0); /* local */ igraph_vector_init_real(&known2, /*n=*/ 3, 0.0, 1.0, 2.0); /* local */ igraph_vector_init_real(&known3, /*n=*/ 3, 0.0, 1.0, 2.0); /* local */ igraph_vector_init_real(&known4, /*n=*/ 3, 0.0, 1.0, 2.0); /* local */ igraph_vector_init_real(&known5, /*n=*/ 4, 0.0, 1.0, 2.0, 3.0); /* global */ /* test parameters */ /*graph--vert--islocal--quantities--strategies--known_strats--mode-retval*/ strategy_test_t game0 = {&g, 0, 1, &quant, NULL, &known0, IGRAPH_ALL, IGRAPH_SUCCESS}; strategy_test_t game1 = {&g, 1, 1, &quant, NULL, &known1, IGRAPH_ALL, IGRAPH_SUCCESS}; strategy_test_t game2 = {&g, 2, 1, &quant, NULL, &known2, IGRAPH_ALL, IGRAPH_SUCCESS}; strategy_test_t game3 = {&g, 3, 1, &quant, NULL, &known3, IGRAPH_ALL, IGRAPH_SUCCESS}; strategy_test_t game4 = {&g, 4, 1, &quant, NULL, &known4, IGRAPH_ALL, IGRAPH_SUCCESS}; strategy_test_t game5 = {&g, 5, 0, &quant, NULL, &known5, IGRAPH_ALL, IGRAPH_SUCCESS}; strategy_test_t *all_checks[] = {/* 1 */ &game0, /* 2 */ &game1, /* 3 */ &game2, /* 4 */ &game3, /* 5 */ &game4, /* 6 */ &game5 }; /* play game */ n = 6; i = 0; while (i < n) { test = all_checks[i]; igraph_vector_copy(&stratcopy, &strat); ret = igraph_roulette_wheel_imitation(test->graph, test->vertex, test->islocal, test->quantities, &stratcopy, test->mode); if (ret != test->retval) { printf("Test no. %d failed.\n", i + 1); return IGRAPH_FAILURE; } /* If the revised strategy s matches one of the candidate strategies, */ /* then success. If s doesn't match any of the possible strategies, then */ /* failure. Default to failure. */ success = 0; known = test->known_strats; for (k = 0; k < igraph_vector_size(known); k++) { if (VECTOR(*known)[k] == VECTOR(stratcopy)[test->vertex]) { success = 1; break; } } if (!success) { printf("Roulette wheel imitation failed for vertex %d.\n", (int)test->vertex); return IGRAPH_FAILURE; } igraph_vector_destroy(&stratcopy); i++; } /* game finished; pack up */ igraph_destroy(&g); igraph_vector_destroy(&known0); igraph_vector_destroy(&known1); igraph_vector_destroy(&known2); igraph_vector_destroy(&known3); igraph_vector_destroy(&known4); igraph_vector_destroy(&known5); igraph_vector_destroy(&quant); igraph_vector_destroy(&strat); return IGRAPH_SUCCESS; } /* It is possible for a vertex to retain its current strategy. This can * happen both in the local and global perspectives. */ int retain_strategy_test() { igraph_t g; igraph_integer_t max, min, v; igraph_vector_t quant, strat, stratcp; int i, ntry, nvert; /* the game network */ igraph_small(&g, /*nvert=*/ 0, IGRAPH_UNDIRECTED, 0, 3, 0, 4, 1, 2, 1, 4, 1, 5, 2, 3, 2, 4, 3, 4, -1); nvert = igraph_vcount(&g); /* strategies vector; the strategy space is {0, 1, 2, 3} */ /* V[i] is strategy of vertex i */ igraph_vector_init_real(&strat, nvert, 1.0, 0.0, 1.0, 2.0, 0.0, 3.0); /* quantities vector; V[i] is quantity of vertex i */ igraph_vector_init_real(&quant, nvert, 0.56, 0.13, 0.26, 0.73, 0.67, 0.82); /* random vertex */ min = 0; max = 5; igraph_rng_seed(igraph_rng_default(), time(0)); v = R_INTEGER(min, max); /* min <= v <= max */ /* Ensure that it is possible for v to retain its current strategy. We */ /* will try to do this at most ntry times. As there are at most 6 vertices */ /* to choose from, it shouldn't take long before we encounter a strategy */ /* revision round where v retains its current strategy. */ /* With local perspective. */ i = 0; ntry = 100; igraph_vector_init(&stratcp, 0); do { i++; if (i > ntry) { return IGRAPH_FAILURE; /* ideally this should never happen */ } igraph_vector_destroy(&stratcp); igraph_vector_copy(&stratcp, &strat); igraph_roulette_wheel_imitation(&g, v, /*is local?*/ 1, &quant, &stratcp, IGRAPH_ALL); } while (VECTOR(stratcp)[v] != VECTOR(strat)[v]); /* If we get to this point, we know that there was an update round */ /* i <= ntry as a result of which v retains its current strategy. */ /* Now try again, but this time with the global perspective. */ i = 0; do { i++; if (i > ntry) { return IGRAPH_FAILURE; /* ideally this should never happen */ } igraph_vector_destroy(&stratcp); igraph_vector_copy(&stratcp, &strat); igraph_roulette_wheel_imitation(&g, v, /*is local?*/ 0, &quant, &stratcp, IGRAPH_ALL); } while (VECTOR(stratcp)[v] != VECTOR(strat)[v]); /* nothing further to do, but housekeeping */ igraph_destroy(&g); igraph_vector_destroy(&quant); igraph_vector_destroy(&strat); igraph_vector_destroy(&stratcp); return IGRAPH_SUCCESS; } int main() { int ret; ret = error_tests(); if (ret) { return IGRAPH_FAILURE; } ret = roulette_test(); if (ret) { return IGRAPH_FAILURE; } ret = retain_strategy_test(); if (ret) { return IGRAPH_FAILURE; } return IGRAPH_SUCCESS; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_layout_lgl.c0000644000076500000240000000313613612122633027571 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int main() { igraph_t g; igraph_matrix_t coords; igraph_real_t vc; igraph_tree(&g, 100, 3, IGRAPH_TREE_UNDIRECTED); /* igraph_barabasi_game(&g, 1000, 1, 0, 0, IGRAPH_UNDIRECTED); */ igraph_matrix_init(&coords, 0, 0); vc = igraph_vcount(&g); igraph_layout_lgl(&g, &coords, /* maxiter */ 150, /* maxdelta */ vc, /* area */ vc * vc, /* coolexp */ 1.5, /* repulserad */ vc * vc * vc, /* cellsize */ sqrt(sqrt(vc)), /* root */ 0); igraph_matrix_destroy(&coords); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/edgelist2.dl0000644000076500000240000000015213524616144026125 0ustar tamasstaff00000000000000DL n=5 format = edgelist1 labels embedded: data: george sally george jim sally jim billy george jane jim python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_layout_grid.out0000644000076500000240000000077213524616144030337 0ustar tamasstaff000000000000000 0 1 0 2 0 3 0 4 0 0 1 1 1 2 1 3 1 4 1 0 2 1 2 2 2 3 2 4 2 === 0 0 1 0 2 0 3 0 0 1 1 1 2 1 3 1 0 2 1 2 2 2 3 2 0 3 1 3 2 3 === 0 0 0 1 0 0 2 0 0 3 0 0 0 1 0 1 1 0 2 1 0 3 1 0 0 0 1 1 0 1 2 0 1 3 0 1 0 1 1 1 1 1 2 1 1 ===== 0 0 0 1 0 0 2 0 0 3 0 0 0 1 0 1 1 0 2 1 0 3 1 0 0 0 1 1 0 1 2 0 1 3 0 1 0 1 1 1 1 1 2 1 1 ===== 0 0 0 1 0 0 2 0 0 0 1 0 1 1 0 2 1 0 0 2 0 1 2 0 2 2 0 0 0 1 1 0 1 2 0 1 0 1 1 1 1 1 2 1 1 ===== 0 0 0 1 0 0 2 0 0 0 1 0 1 1 0 2 1 0 0 2 0 1 2 0 2 2 0 0 0 1 1 0 1 2 0 1 0 1 1 1 1 1 2 1 1 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_read_graph_lgl-3.lgl0000644000076500000240000000001213524616144031041 0ustar tamasstaff00000000000000# 1 # 1 2 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_layout_grid.c0000644000076500000240000000362013612122633027736 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include int main() { igraph_t g; igraph_matrix_t coords; igraph_empty(&g, 15, 0); igraph_matrix_init(&coords, 0, 0); /* Predefined width, 2D */ igraph_layout_grid(&g, &coords, 5); igraph_matrix_print(&coords); printf("===\n"); /* Automatic width, 2D */ igraph_layout_grid(&g, &coords, -1); igraph_matrix_print(&coords); printf("===\n"); /* Predefined width and height, 3D */ igraph_layout_grid_3d(&g, &coords, 4, 2); igraph_matrix_print(&coords); printf("=====\n"); /* Predefined width, 3D */ igraph_layout_grid_3d(&g, &coords, 4, -1); igraph_matrix_print(&coords); printf("=====\n"); /* Predefined height, 3D */ igraph_layout_grid_3d(&g, &coords, -1, 3); igraph_matrix_print(&coords); printf("=====\n"); /* Automatic width and height, 3D */ igraph_layout_grid_3d(&g, &coords, -1, -1); igraph_matrix_print(&coords); igraph_matrix_destroy(&coords); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_maximal_cliques.c0000644000076500000240000001114413612122633030571 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #define NODES 1000 #define CLIQUE_SIZE 10 #define NO_CLIQUES 10 #define INT(a) (igraph_rng_get_integer(igraph_rng_default(), 0, (a))) int permutation(igraph_vector_t *vec) { int i, r, tmp; for (i = 0; i < CLIQUE_SIZE; i++) { r = INT(NODES - 1); tmp = VECTOR(*vec)[i]; VECTOR(*vec)[i] = VECTOR(*vec)[r]; VECTOR(*vec)[r] = tmp; } return 0; } int sort_cmp(const void *a, const void *b) { const igraph_vector_t **da = (const igraph_vector_t **) a; const igraph_vector_t **db = (const igraph_vector_t **) b; int i, alen = igraph_vector_size(*da), blen = igraph_vector_size(*db); if (alen != blen) { return (alen < blen) - (alen > blen); } for (i = 0; i < alen; i++) { int ea = VECTOR(**da)[i], eb = VECTOR(**db)[i]; if (ea != eb) { return (ea > eb) - (ea < eb); } } return 0; } void sort_cliques(igraph_vector_ptr_t *cliques) { int i, n = igraph_vector_ptr_size(cliques); for (i = 0; i < n; i++) { igraph_vector_t *v = VECTOR(*cliques)[i]; igraph_vector_sort(v); } igraph_qsort(VECTOR(*cliques), (size_t) n, sizeof(igraph_vector_t *), sort_cmp); } void print_and_destroy_cliques(igraph_vector_ptr_t *cliques) { int i; sort_cliques(cliques); for (i = 0; i < igraph_vector_ptr_size(cliques); i++) { igraph_vector_t *v = VECTOR(*cliques)[i]; igraph_vector_print(v); igraph_vector_destroy(v); igraph_free(v); } } int main() { igraph_t g, g2, cli; igraph_vector_t perm; igraph_vector_ptr_t cliques; igraph_integer_t no; int i; igraph_rng_seed(igraph_rng_default(), 42); /* Create a graph that has a random component, plus a number of relatively small cliques */ igraph_vector_init_seq(&perm, 0, NODES - 1); igraph_erdos_renyi_game(&g, IGRAPH_ERDOS_RENYI_GNM, NODES, NODES, /*directed=*/ 0, /*loops=*/ 0); igraph_full(&cli, CLIQUE_SIZE, /*directed=*/ 0, /*loops=*/ 0); for (i = 0; i < NO_CLIQUES; i++) { /* Permute vertices of g */ permutation(&perm); igraph_permute_vertices(&g, &g2, &perm); igraph_destroy(&g); g = g2; /* Add a clique */ igraph_union(&g2, &g, &cli, /*edge_map1=*/ 0, /*edge_map2=*/ 0); igraph_destroy(&g); g = g2; } igraph_simplify(&g, /*multiple=*/ 1, /*loop=*/ 0, /*edge_comb=*/ 0); igraph_vector_destroy(&perm); igraph_destroy(&cli); /* Find the maximal cliques */ igraph_vector_ptr_init(&cliques, 0); igraph_maximal_cliques(&g, &cliques, /*min_size=*/ 3, /*max_size=*/ 0 /*no limit*/); igraph_maximal_cliques_count(&g, &no, /*min_size=*/ 3, /*max_size=*/ 0 /*no limit*/); if (no != igraph_vector_ptr_size(&cliques)) { return 1; } /* Print and destroy them */ print_and_destroy_cliques(&cliques); /* Clean up */ igraph_vector_ptr_destroy(&cliques); igraph_destroy(&g); /* Build a triangle with a loop (thanks to Emmanuel Navarro) */ igraph_small(&g, 3, IGRAPH_UNDIRECTED, 0, 1, 1, 2, 2, 0, 0, 0, -1); /* Find the maximal cliques */ igraph_vector_ptr_init(&cliques, 0); igraph_maximal_cliques(&g, &cliques, /*min_size=*/ 3, /*max_size=*/ 0 /*no limit*/); igraph_maximal_cliques_count(&g, &no, /*min_size=*/ 3, /*max_size=*/ 0 /*no limit*/); if (no != igraph_vector_ptr_size(&cliques)) { return 2; } /* Print and destroy them */ print_and_destroy_cliques(&cliques); /* Clean up */ igraph_vector_ptr_destroy(&cliques); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/bug-1149658.c0000644000076500000240000000250313614300625025476 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2013 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t graph; igraph_vector_t mod; igraph_empty(&graph, 25, IGRAPH_UNDIRECTED); igraph_vector_init(&mod, 0); igraph_community_multilevel(&graph, /*weights=*/ 0, /*membership=*/ 0, /*memberships=*/ 0, &mod); if (igraph_vector_size(&mod) != 1 || VECTOR(mod)[0] != 0) { return 1; } igraph_vector_destroy(&mod); igraph_destroy(&graph); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/cattributes5.c0000644000076500000240000001542713612122633026510 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int mf(const igraph_strvector_t *input, char *output) { /* TODO */ return 0; } int main() { igraph_t g, g2; igraph_attribute_combination_t comb; igraph_i_set_attribute_table(&igraph_cattribute_table); igraph_small(&g, 4, IGRAPH_DIRECTED, 0, 1, 0, 1, 0, 1, 1, 2, 2, 3, -1); SETEAB(&g, "type", 0, 1); SETEAB(&g, "type", 1, 1); SETEAB(&g, "type", 2, 0); SETEAB(&g, "type", 3, 0); SETEAB(&g, "type", 4, 1); /* ****************************************************** */ igraph_copy(&g2, &g); igraph_attribute_combination(&comb, "weight", IGRAPH_ATTRIBUTE_COMBINE_SUM, "type", IGRAPH_ATTRIBUTE_COMBINE_FIRST, "", IGRAPH_ATTRIBUTE_COMBINE_IGNORE, IGRAPH_NO_MORE_ATTRIBUTES); igraph_simplify(&g2, /*multiple=*/ 1, /*loops=*/ 1, &comb); igraph_attribute_combination_destroy(&comb); igraph_write_graph_graphml(&g2, stdout, /*prefixattr=*/ 1); igraph_destroy(&g2); /* ****************************************************** */ /* ****************************************************** */ igraph_copy(&g2, &g); igraph_attribute_combination(&comb, "", IGRAPH_ATTRIBUTE_COMBINE_LAST, IGRAPH_NO_MORE_ATTRIBUTES); igraph_simplify(&g2, /*multiple=*/ 1, /*loops=*/ 1, &comb); igraph_attribute_combination_destroy(&comb); igraph_write_graph_graphml(&g2, stdout, /*prefixattr=*/ 1); igraph_destroy(&g2); /* ****************************************************** */ /* ****************************************************** */ igraph_copy(&g2, &g); igraph_attribute_combination(&comb, "", IGRAPH_ATTRIBUTE_COMBINE_IGNORE, "type", IGRAPH_ATTRIBUTE_COMBINE_LAST, IGRAPH_NO_MORE_ATTRIBUTES); igraph_simplify(&g2, /*multiple=*/ 1, /*loops=*/ 1, &comb); igraph_attribute_combination_destroy(&comb); igraph_write_graph_graphml(&g2, stdout, /*prefixattr=*/ 1); igraph_destroy(&g2); /* ****************************************************** */ /* ****************************************************** */ igraph_copy(&g2, &g); igraph_attribute_combination(&comb, "", IGRAPH_ATTRIBUTE_COMBINE_IGNORE, "type", IGRAPH_ATTRIBUTE_COMBINE_SUM, IGRAPH_NO_MORE_ATTRIBUTES); igraph_simplify(&g2, /*multiple=*/ 1, /*loops=*/ 1, &comb); igraph_attribute_combination_destroy(&comb); igraph_write_graph_graphml(&g2, stdout, /*prefixattr=*/ 1); igraph_destroy(&g2); /* ****************************************************** */ /* ****************************************************** */ igraph_copy(&g2, &g); igraph_attribute_combination(&comb, "", IGRAPH_ATTRIBUTE_COMBINE_IGNORE, "type", IGRAPH_ATTRIBUTE_COMBINE_PROD, IGRAPH_NO_MORE_ATTRIBUTES); igraph_simplify(&g2, /*multiple=*/ 1, /*loops=*/ 1, &comb); igraph_attribute_combination_destroy(&comb); igraph_write_graph_graphml(&g2, stdout, /*prefixattr=*/ 1); igraph_destroy(&g2); /* ****************************************************** */ /* ****************************************************** */ igraph_copy(&g2, &g); igraph_attribute_combination(&comb, "", IGRAPH_ATTRIBUTE_COMBINE_IGNORE, "type", IGRAPH_ATTRIBUTE_COMBINE_MIN, IGRAPH_NO_MORE_ATTRIBUTES); igraph_simplify(&g2, /*multiple=*/ 1, /*loops=*/ 1, &comb); igraph_attribute_combination_destroy(&comb); igraph_write_graph_graphml(&g2, stdout, /*prefixattr=*/ 1); igraph_destroy(&g2); /* ****************************************************** */ /* ****************************************************** */ igraph_copy(&g2, &g); igraph_attribute_combination(&comb, "", IGRAPH_ATTRIBUTE_COMBINE_IGNORE, "type", IGRAPH_ATTRIBUTE_COMBINE_MAX, IGRAPH_NO_MORE_ATTRIBUTES); igraph_simplify(&g2, /*multiple=*/ 1, /*loops=*/ 1, &comb); igraph_attribute_combination_destroy(&comb); igraph_write_graph_graphml(&g2, stdout, /*prefixattr=*/ 1); igraph_destroy(&g2); /* ****************************************************** */ /* ****************************************************** */ igraph_copy(&g2, &g); igraph_attribute_combination(&comb, "", IGRAPH_ATTRIBUTE_COMBINE_IGNORE, "type", IGRAPH_ATTRIBUTE_COMBINE_MEAN, IGRAPH_NO_MORE_ATTRIBUTES); igraph_simplify(&g2, /*multiple=*/ 1, /*loops=*/ 1, &comb); igraph_attribute_combination_destroy(&comb); igraph_write_graph_graphml(&g2, stdout, /*prefixattr=*/ 1); igraph_destroy(&g2); /* ****************************************************** */ /* ****************************************************** */ igraph_copy(&g2, &g); igraph_attribute_combination(&comb, "", IGRAPH_ATTRIBUTE_COMBINE_IGNORE, "type", IGRAPH_ATTRIBUTE_COMBINE_MEDIAN, IGRAPH_NO_MORE_ATTRIBUTES); igraph_simplify(&g2, /*multiple=*/ 1, /*loops=*/ 1, &comb); igraph_attribute_combination_destroy(&comb); igraph_write_graph_graphml(&g2, stdout, /*prefixattr=*/ 1); igraph_destroy(&g2); /* ****************************************************** */ igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_cocitation.c0000644000076500000240000000310513612122633027546 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void print_matrix(igraph_matrix_t *m, FILE *f) { long int i, j; for (i = 0; i < igraph_matrix_nrow(m); i++) { for (j = 0; j < igraph_matrix_ncol(m); j++) { fprintf(f, " %li", (long int) MATRIX(*m, i, j)); } fprintf(f, "\n"); } } int main() { igraph_t g; igraph_matrix_t m; igraph_small(&g, 0, IGRAPH_DIRECTED, 0, 1, 2, 1, 2, 0, 3, 0, -1); igraph_matrix_init(&m, 0, 0); igraph_bibcoupling(&g, &m, igraph_vss_all()); print_matrix(&m, stdout); igraph_cocitation(&g, &m, igraph_vss_all()); print_matrix(&m, stdout); igraph_matrix_destroy(&m); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_adjacency.c0000644000076500000240000000164313612122633027340 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_minimum_size_separators.c0000644000076500000240000001264513612122633032373 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int print_and_destroy(igraph_vector_ptr_t *ptr) { long int i, n = igraph_vector_ptr_size(ptr); for (i = 0; i < n; i++) { igraph_vector_t *v = VECTOR(*ptr)[i]; igraph_vector_print(v); igraph_vector_destroy(v); igraph_free(v); } igraph_vector_ptr_destroy(ptr); return 0; } int main() { igraph_t g, g2; igraph_vector_ptr_t sep; igraph_vs_t vs; igraph_small(&g, 7, IGRAPH_UNDIRECTED, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 0, -1); igraph_vector_ptr_init(&sep, 0); igraph_minimum_size_separators(&g, &sep); print_and_destroy(&sep); igraph_destroy(&g); /* ----------------------------------------------------------- */ igraph_small(&g, 5, IGRAPH_UNDIRECTED, 0, 3, 1, 3, 2, 3, 0, 4, 1, 4, 2, 4, -1); igraph_vector_ptr_init(&sep, 0); igraph_minimum_size_separators(&g, &sep); print_and_destroy(&sep); igraph_destroy(&g); /* ----------------------------------------------------------- */ igraph_small(&g, 5, IGRAPH_UNDIRECTED, 2, 0, 3, 0, 4, 0, 2, 1, 3, 1, 4, 1, -1); igraph_vector_ptr_init(&sep, 0); igraph_minimum_size_separators(&g, &sep); print_and_destroy(&sep); igraph_destroy(&g); /* ----------------------------------------------------------- */ igraph_small(&g, 10, IGRAPH_UNDIRECTED, 0, 2, 0, 3, 1, 2, 1, 3, 5, 2, 5, 3, 6, 2, 6, 3, 7, 2, 7, 3, 8, 2, 8, 3, 9, 2, 9, 3, 2, 4, 4, 3, -1); igraph_vector_ptr_init(&sep, 0); igraph_minimum_size_separators(&g, &sep); print_and_destroy(&sep); igraph_destroy(&g); /* ----------------------------------------------------------- */ igraph_full(&g, 4, IGRAPH_UNDIRECTED, /*loops=*/ 0); igraph_vector_ptr_init(&sep, 0); igraph_minimum_size_separators(&g, &sep); print_and_destroy(&sep); igraph_destroy(&g); /* ----------------------------------------------------------- */ igraph_small(&g, 23, IGRAPH_UNDIRECTED, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 1, 2, 1, 3, 1, 4, 1, 6, 2, 3, 2, 5, 2, 6, 3, 4, 3, 5, 3, 6, 4, 5, 4, 6, 4, 20, 5, 6, 6, 7, 6, 10, 6, 13, 6, 18, 7, 8, 7, 10, 7, 13, 8, 9, 9, 11, 9, 12, 10, 11, 10, 13, 11, 15, 12, 15, 13, 14, 14, 15, 16, 17, 16, 18, 16, 19, 17, 19, 17, 20, 18, 19, 18, 21, 18, 22, 19, 20, 20, 21, 20, 22, 21, 22, -1); igraph_vector_ptr_init(&sep, 0); igraph_minimum_size_separators(&g, &sep); printf("Orig:\n"); print_and_destroy(&sep); igraph_vector_ptr_init(&sep, 0); igraph_vs_vector_small(&vs, 0, 1, 2, 3, 4, 5, 6, 16, 17, 18, 19, 20, 21, 22, -1); igraph_induced_subgraph(&g, &g2, vs, IGRAPH_SUBGRAPH_AUTO); igraph_minimum_size_separators(&g2, &sep); printf("1-7,17-23:\n"); print_and_destroy(&sep); igraph_vs_destroy(&vs); igraph_destroy(&g2); igraph_vector_ptr_init(&sep, 0); igraph_vs_vector_small(&vs, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, -1); igraph_induced_subgraph(&g, &g2, vs, IGRAPH_SUBGRAPH_AUTO); igraph_minimum_size_separators(&g2, &sep); printf("7-16:\n"); print_and_destroy(&sep); igraph_vs_destroy(&vs); igraph_destroy(&g2); igraph_vector_ptr_init(&sep, 0); igraph_vs_vector_small(&vs, 16, 17, 18, 19, 20, 21, 22, -1); igraph_induced_subgraph(&g, &g2, vs, IGRAPH_SUBGRAPH_AUTO); igraph_minimum_size_separators(&g2, &sep); printf("17-23:\n"); print_and_destroy(&sep); igraph_vs_destroy(&vs); igraph_destroy(&g2); igraph_vector_ptr_init(&sep, 0); igraph_vs_vector_small(&vs, 6, 7, 10, 13, -1); igraph_induced_subgraph(&g, &g2, vs, IGRAPH_SUBGRAPH_AUTO); igraph_minimum_size_separators(&g2, &sep); printf("7,8,11,14:\n"); print_and_destroy(&sep); igraph_vs_destroy(&vs); igraph_destroy(&g2); igraph_vector_ptr_init(&sep, 0); igraph_vs_vector_small(&vs, 0, 1, 2, 3, 4, 5, 6, -1); igraph_induced_subgraph(&g, &g2, vs, IGRAPH_SUBGRAPH_AUTO); igraph_minimum_size_separators(&g2, &sep); printf("1-7:\n"); print_and_destroy(&sep); igraph_vs_destroy(&vs); igraph_destroy(&g2); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/matrix.c0000644000076500000240000001144713612122634025375 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include void print_matrix(igraph_matrix_t *m, FILE *f) { long int i, j; for (i = 0; i < igraph_matrix_nrow(m); i++) { for (j = 0; j < igraph_matrix_ncol(m); j++) { fprintf(f, " %li", (long int)MATRIX(*m, i, j)); } fprintf(f, "\n"); } } int main() { igraph_matrix_t m, m1; long int i, j, k; /* igraph_matrix_init, igraph_matrix_destroy */ igraph_matrix_init(&m, 10, 10); igraph_matrix_destroy(&m); igraph_matrix_init(&m, 0, 0); igraph_matrix_destroy(&m); /* igraph_matrix_ncol, igraph_matrix_nrow */ igraph_matrix_init(&m, 10, 5); if (igraph_matrix_nrow(&m) != 10) { return 1; } if (igraph_matrix_ncol(&m) != 5) { return 2; } /* igraph_matrix_size, igraph_matrix_resize */ igraph_matrix_resize(&m, 6, 5); if (igraph_matrix_size(&m) != 30) { return 3; } if (igraph_matrix_nrow(&m) != 6) { return 4; } if (igraph_matrix_ncol(&m) != 5) { return 5; } igraph_matrix_resize(&m, 2, 4); if (igraph_matrix_nrow(&m) != 2) { return 6; } if (igraph_matrix_ncol(&m) != 4) { return 7; } igraph_matrix_destroy(&m); /* MATRIX, igraph_matrix_null */ igraph_matrix_init(&m, 3, 4); for (i = 0; i < igraph_matrix_nrow(&m); i++) { for (j = 0; j < igraph_matrix_ncol(&m); j++) { MATRIX(m, i, j) = i + 1; } } print_matrix(&m, stdout); igraph_matrix_null(&m); print_matrix(&m, stdout); igraph_matrix_destroy(&m); /* igraph_matrix_add_cols, igraph_matrix_add_rows */ igraph_matrix_init(&m, 4, 3); for (i = 0; i < igraph_matrix_nrow(&m); i++) { for (j = 0; j < igraph_matrix_ncol(&m); j++) { MATRIX(m, i, j) = (i + 1) * (j + 1); } } igraph_matrix_add_cols(&m, 2); igraph_matrix_add_rows(&m, 2); if (igraph_matrix_ncol(&m) != 5) { return 8; } if (igraph_matrix_nrow(&m) != 6) { return 9; } igraph_matrix_destroy(&m); /* igraph_matrix_remove_col */ igraph_matrix_init(&m, 5, 3); for (i = 0; i < igraph_matrix_nrow(&m); i++) { for (j = 0; j < igraph_matrix_ncol(&m); j++) { MATRIX(m, i, j) = (i + 1) * (j + 1); } } igraph_matrix_remove_col(&m, 0); print_matrix(&m, stdout); igraph_matrix_remove_col(&m, 1); print_matrix(&m, stdout); igraph_matrix_destroy(&m); /* TODO: igraph_matrix_permdelete_rows */ /* TODO: igraph_matrix_delete_rows_neg */ /* igraph_matrix_copy */ igraph_matrix_init(&m, 2, 3); for (i = 0; i < igraph_matrix_nrow(&m); i++) { for (j = 0; j < igraph_matrix_ncol(&m); j++) { MATRIX(m, i, j) = (i + 1) * (j + 1); } } igraph_matrix_copy(&m1, &m); print_matrix(&m1, stdout); igraph_matrix_destroy(&m); igraph_matrix_destroy(&m1); /* in-place transpose */ igraph_matrix_init(&m, 5, 2); k = 0; for (i = 0; i < igraph_matrix_ncol(&m); i++) { for (j = 0; j < igraph_matrix_nrow(&m); j++) { MATRIX(m, j, i) = k++; } } print_matrix(&m, stdout); igraph_matrix_transpose(&m); print_matrix(&m, stdout); igraph_matrix_destroy(&m); igraph_matrix_init(&m, 5, 1); k = 0; for (i = 0; i < igraph_matrix_ncol(&m); i++) { for (j = 0; j < igraph_matrix_nrow(&m); j++) { MATRIX(m, j, i) = k++; } } print_matrix(&m, stdout); igraph_matrix_transpose(&m); print_matrix(&m, stdout); igraph_matrix_destroy(&m); igraph_matrix_init(&m, 1, 5); k = 0; for (i = 0; i < igraph_matrix_ncol(&m); i++) { for (j = 0; j < igraph_matrix_nrow(&m); j++) { MATRIX(m, j, i) = k++; } } print_matrix(&m, stdout); igraph_matrix_transpose(&m); print_matrix(&m, stdout); igraph_matrix_destroy(&m); if (IGRAPH_FINALLY_STACK_SIZE() != 0) { return 10; } return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/adjlist.c0000644000076500000240000000401313612122633025511 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2008-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int main() { igraph_t g, g2; igraph_adjlist_t adjlist; igraph_bool_t iso; /* Directed, out */ igraph_tree(&g, 42, 3, IGRAPH_TREE_OUT); igraph_adjlist_init(&g, &adjlist, IGRAPH_OUT); igraph_adjlist(&g2, &adjlist, IGRAPH_OUT, /*duplicate=*/ 0); igraph_isomorphic(&g, &g2, &iso); if (!iso) { return 1; } igraph_adjlist_destroy(&adjlist); igraph_destroy(&g2); igraph_destroy(&g); /* Directed, in */ igraph_tree(&g, 42, 3, IGRAPH_TREE_OUT); igraph_adjlist_init(&g, &adjlist, IGRAPH_IN); igraph_adjlist(&g2, &adjlist, IGRAPH_IN, /*duplicate=*/ 0); igraph_isomorphic(&g, &g2, &iso); if (!iso) { return 1; } igraph_adjlist_destroy(&adjlist); igraph_destroy(&g2); igraph_destroy(&g); /* Undirected */ igraph_tree(&g, 42, 3, IGRAPH_TREE_UNDIRECTED); igraph_adjlist_init(&g, &adjlist, IGRAPH_OUT); igraph_adjlist(&g2, &adjlist, IGRAPH_ALL, /*duplicate=*/ 1); igraph_isomorphic(&g, &g2, &iso); if (!iso) { return 1; } igraph_adjlist_destroy(&adjlist); igraph_destroy(&g2); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_read_graph_lgl-2.lgl0000644000076500000240000000005713524616144031051 0ustar tamasstaff00000000000000# foo bar 1 foobar 2 # foobar bat 10 tab # tab python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_sparsemat7.c0000644000076500000240000000433113612122634027503 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #define DIM1 10 #define DIM2 5 #define INT(a) (igraph_rng_get_integer(igraph_rng_default(), 0, (a))) int main() { igraph_matrix_t mat; igraph_sparsemat_t spmat, spmat2; int i; igraph_real_t m1, m2; igraph_rng_seed(igraph_rng_default(), 42); igraph_sparsemat_init(&spmat, DIM1, DIM2, 20); igraph_sparsemat_entry(&spmat, 1, 2, -1.0); igraph_sparsemat_entry(&spmat, 3, 2, 10.0); for (i = 0; i < 10; i++) { igraph_sparsemat_entry(&spmat, INT(DIM1 - 1), INT(DIM2 - 1), 1.0); } igraph_sparsemat_entry(&spmat, 1, 2, -1.0); igraph_sparsemat_entry(&spmat, 3, 2, 10.0); igraph_sparsemat_compress(&spmat, &spmat2); igraph_matrix_init(&mat, 0, 0); igraph_sparsemat_as_matrix(&mat, &spmat2); m1 = igraph_sparsemat_min(&spmat2); m2 = igraph_matrix_min(&mat); if (m1 != m2) { printf("%f %f\n", m1, m2); return 1; } m1 = igraph_sparsemat_max(&spmat2); m2 = igraph_matrix_max(&mat); if (m1 != m2) { printf("%f %f\n", m1, m2); return 2; } igraph_sparsemat_minmax(&spmat2, &m1, &m2); if (m1 != igraph_matrix_min(&mat)) { return 3; } if (m2 != igraph_matrix_max(&mat)) { return 4; } igraph_matrix_destroy(&mat); igraph_sparsemat_destroy(&spmat); igraph_sparsemat_destroy(&spmat2); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_community_leading_eigenvector2.out0000644000076500000240000000023113524616144034166 0ustar tamasstaff000000000000000 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 1 0 0 1 0 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 3 0 2 5 4 0 2 2 2 0 0 0 2 1 1 0 0 2 2 1 1 0 2 1 2 1 2 1 3 3 3 1 3 3 1 1 3 1 1 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_write_graph_pajek.out0000644000076500000240000000075313524616144031501 0ustar tamasstaff00000000000000*Vertices 10 *Arcs 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 1 *Vertices 10 1 "A" 2 "B" 3 "C" 4 "D" 5 "E" 6 "F" 7 "G" 8 "H" 9 "I" 10 "J" *Arcs 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 1 *Vertices 10 1 "A" "square" 2 "B" "square" 3 "C" "square" 4 "D" "square" 5 "E" "escaping spaces" 6 "F" "square" 7 "G" "square" 8 "H" "escaping \\backslashes\\" 9 "I" "square" 10 "J" "escaping \"quotes\"" *Arcs 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 1 python-igraph-0.8.0/vendor/source/igraph/examples/simple/matrix2.out0000644000076500000240000000320113524616144026037 0ustar tamasstaff00000000000000igraph_matrix_e 0 1 2 3 4 5 6 7 8 9 10 11 igraph_matrix_e_ptr 0 1 2 3 4 5 6 7 8 9 10 11 igraph_matrix_set 0 0 0 1 1 1 2 2 2 3 3 3 0 1 2 0 1 2 0 1 2 0 1 2 igraph_matrix_fill 42 42 42 42 42 42 42 42 42 42 42 42 -42.1 -42.1 -42.1 -42.1 -42.1 -42.1 -42.1 -42.1 -42.1 -42.1 -42.1 -42.1 igraph_matrix_update 0 1 2 3 4 5 6 7 8 9 10 11 igraph_matrix_rbind 0 1 2 3 4 5 6 7 8 9 10 11 0 1 2 3 4 5 6 7 8 9 10 11 0 1 2 3 4 5 6 7 8 9 10 11 0 1 2 3 4 5 6 7 8 9 10 11 0 1 2 3 4 5 6 7 8 9 10 11 0 1 2 3 4 5 6 7 8 9 10 11 igraph_matrix_cbind 0 1 2 0 1 3 4 5 2 3 6 7 8 4 5 9 10 11 6 7 igraph_matrix_swap 0 1 2 3 4 5 6 7 0 0 0 0 0 0 0 0 igraph_matrix_get_row igraph_matrix_set_row 0 1 2 3 4 5 6 7 igraph_matrix_set_col 0 1 2 3 4 5 6 7 igraph_matrix_swap_rows 4 5 2 3 0 1 6 7 igraph_matrix_swap_cols 5 4 3 2 1 0 7 6 igraph_matrix_add_constant 5 4 3 2 1 0 7 6 4 3 2 1 0 -1 6 5 igraph_matrix_add 0 2 4 6 8 10 12 14 igraph_matrix_sub 0 1 2 3 4 5 6 7 igraph_matrix_mul_elements 0 1 4 9 16 25 36 49 igraph_matrix_div_elements 0 0.5 2 4.5 8 12.5 18 24.5 igraph_matrix_min igraph_matrix_which_min igraph_matrix_which_max igraph_matrix_minmax -2 100 igraph_matrix_which_minmax igraph_matrix_isnull igraph_matrix_empty igraph_matrix_is_symmetric igraph_matrix_prod 1 2 3 4 5 6 product: 720 igraph_matrix_rowsum 3 7 11 igraph_matrix_colsum 9 12 igraph_matrix_contains igraph_matrix_search igraph_matrix_remove_row 1 2 5 6 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 4 5 6 7 8 9 10 11 12 13 14 15 igraph_matrix_select_cols 0 4 2 0 4 2 0 4 2 0 4 2 0 4 2 0 4 2 0 0 0 0 0 0 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_add_edges.out0000644000076500000240000000011313524616144027701 0ustar tamasstaff00000000000000 0 1 1 1 2 2 2 2 2 3 3 3 0 1 1 1 2 2 2 2 2 3 3 3 0 1 1 1 2 2 2 2 2 3 3 3 python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_induced_subgraph_map.c0000644000076500000240000000364213612122633031563 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int main() { igraph_t g, sub; igraph_vector_t map, invmap; igraph_vector_t keep; long int i; igraph_small(&g, 9, IGRAPH_DIRECTED, 0, 1, 0, 2, 1, 3, 2, 3, 1, 4, 4, 2, 1, 5, 5, 2, 1, 6, 6, 2, 1, 7, 7, 2, 1, 8, 8, 2, -1); igraph_vector_init(&map, 0); igraph_vector_init(&invmap, 0); igraph_vector_init(&keep, igraph_vcount(&g)); for (i = 0; i < igraph_vector_size(&keep); i++) { VECTOR(keep)[i] = i; } igraph_induced_subgraph_map(&g, &sub, igraph_vss_vector(&keep), IGRAPH_SUBGRAPH_COPY_AND_DELETE, &map, &invmap); printf("Map: "); igraph_vector_print(&map); printf("Inverse map: "); igraph_vector_print(&invmap); igraph_write_graph_edgelist(&sub, stdout); igraph_vector_destroy(&keep); igraph_vector_destroy(&map); igraph_vector_destroy(&invmap); igraph_destroy(&sub); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_layout_reingold_tilford.c0000644000076500000240000000263113612122633032340 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include int main() { igraph_t g; FILE *f; igraph_matrix_t coords; /* long int i, n; */ f = fopen("igraph_layout_reingold_tilford.in", "r"); igraph_read_graph_edgelist(&g, f, 0, 1); igraph_matrix_init(&coords, 0, 0); igraph_layout_reingold_tilford(&g, &coords, IGRAPH_IN, 0, 0); /*n=igraph_vcount(&g); for (i=0; i 334 Harvard st, Cambridge, MA 02139, USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include int comp(const void *a, const void *b) { igraph_real_t *aa = (igraph_real_t *) a; igraph_real_t *bb = (igraph_real_t *) b; if (*aa < *bb) { return -1; } else if (*aa > *bb) { return 1; } return 0; } int main() { const int len = 100; igraph_vector_t v; int i; igraph_rng_seed(igraph_rng_default(), 42); igraph_vector_init(&v, len); for (i = 0; i < len; i++) { VECTOR(v)[i] = i; } igraph_vector_shuffle(&v); igraph_qsort(VECTOR(v), igraph_vector_size(&v), sizeof(VECTOR(v)[0]), comp); igraph_vector_print(&v); igraph_vector_destroy(&v); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/simple/igraph_trie.out0000644000076500000240000000052013524616144026747 0ustar tamasstaff00000000000000hello: 0 hepp: 1 alma: 2 also: 3 hello: 0 hepp: 1 alma: 2 also: 3 a: 4 axon: 5 hello: 0 hepp: 1 alma: 2 also: 3 head: -1 alma: 2 hello: 0 hepp: 1 alma: 2 also: 3 hello: 0 hepp: 1 alma: 2 also: 3 a: 4 axon: 5 hello: 0 hepp: 1 alma: 2 also: 3 head: -1 alma: 2 0: hello 1: hepp 2: alma 3: also 4: a 5: axon python-igraph-0.8.0/vendor/source/igraph/examples/benchmarks/0000755000076500000240000000000013617375001024545 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/examples/benchmarks/igraph_cliques.c0000644000076500000240000000133613612122633027707 0ustar tamasstaff00000000000000 #include #include "bench.h" int main() { igraph_t g; igraph_vector_ptr_t res; igraph_integer_t i, n; igraph_rng_seed(igraph_rng_default(), 42); igraph_erdos_renyi_game(&g, IGRAPH_ERDOS_RENYI_GNM, 100, 3000, /* directed = */ 0, /* loops= */ 0); igraph_vector_ptr_init(&res, 0); BENCH("1 Cliques in random graph with 100 vertices and 3000 edges", igraph_cliques(&g, &res, /* min_size= */ 0, /* max_size= */ 0); ); igraph_destroy(&g); n = igraph_vector_ptr_size(&res); for (i = 0; i < n; i++) { igraph_vector_t *v = VECTOR(res)[i]; igraph_vector_destroy(v); igraph_free(v); } igraph_vector_ptr_destroy(&res); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/benchmarks/bench.h0000644000076500000240000000434113612122633025773 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2013 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_BENCH_H #define IGRAPH_BENCH_H static inline void igraph_get_cpu_time(igraph_real_t *data) { struct rusage self, children; getrusage(RUSAGE_SELF, &self); getrusage(RUSAGE_CHILDREN, &children); data[0] = (double) self.ru_utime.tv_sec + 1e-3 * (self.ru_utime.tv_usec / 1000); data[1] = (double) self.ru_stime.tv_sec + 1e-3 * (self.ru_stime.tv_usec / 1000); data[2] = (double) children.ru_utime.tv_sec + 1e-3 * (children.ru_utime.tv_usec / 1000); data[3] = (double) children.ru_stime.tv_sec + 1e-3 * (children.ru_stime.tv_usec / 1000); } #define BENCH(NAME, ...) do { \ double start[4], stop[4]; \ igraph_get_cpu_time(start); \ { __VA_ARGS__; }; \ igraph_get_cpu_time(stop); \ printf("%s %.3gs\n", NAME, \ stop[0]+stop[1]+stop[2]+stop[3] - \ start[0]-start[1]-start[2]-start[3]); \ } while (0) #endif python-igraph-0.8.0/vendor/source/igraph/examples/benchmarks/igraph_transitivity.c0000644000076500000240000000344713612122633031020 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2013 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include "bench.h" #define N 6000 #define M 2000000 int main() { igraph_t g; igraph_vector_t trans; igraph_erdos_renyi_game(&g, IGRAPH_ERDOS_RENYI_GNM, N, M, IGRAPH_UNDIRECTED, IGRAPH_NO_LOOPS); igraph_vector_init(&trans, igraph_vcount(&g)); BENCH("1 Transitivity GNM ", igraph_transitivity_local_undirected(&g, &trans, igraph_vss_all(), IGRAPH_TRANSITIVITY_NAN); ); igraph_destroy(&g); igraph_barabasi_game(&g, N, /*power=*/ 1, M / N, /*outseq=*/ 0, /*outpref=*/ 0, /*A=*/ 1, IGRAPH_UNDIRECTED, IGRAPH_BARABASI_PSUMTREE, /*start_from=*/ 0); BENCH("2 Transitivity Skewed", igraph_transitivity_local_undirected(&g, &trans, igraph_vss_all(), IGRAPH_TRANSITIVITY_NAN); ); igraph_destroy(&g); igraph_vector_destroy(&trans); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/benchmarks/igraph_random_walk.c0000644000076500000240000000677413612122633030553 0ustar tamasstaff00000000000000 #include #include "bench.h" int main() { igraph_t graph; igraph_vector_t walk, weights; igraph_integer_t ec, i; igraph_rng_seed(igraph_rng_default(), 137); igraph_vector_init(&walk, 0); igraph_vector_init(&weights, 0); /* create a small graph, and a compatible weight vector */ igraph_de_bruijn(&graph, 3, 2); /* 9 vertices, 27 edges, average degree: 6 */ ec = igraph_ecount(&graph); igraph_vector_resize(&weights, ec); for (i = 0; i < ec; ++i) { VECTOR(weights)[i] = igraph_rng_get_unif01(igraph_rng_default()); } BENCH(" 1 Random edge walk, directed, unweighted, small graph ", igraph_random_edge_walk(&graph, NULL, &walk, 0, IGRAPH_OUT, 50000000, IGRAPH_RANDOM_WALK_STUCK_RETURN) ); BENCH(" 2 Random edge walk, directed, weighted, small graph ", igraph_random_edge_walk(&graph, &weights, &walk, 0, IGRAPH_OUT, 50000000, IGRAPH_RANDOM_WALK_STUCK_RETURN) ); BENCH(" 3 Random vertex walk, directed, unweighted, small graph ", igraph_random_walk(&graph, &walk, 0, IGRAPH_OUT, 50000000, IGRAPH_RANDOM_WALK_STUCK_RETURN) ); igraph_to_undirected(&graph, IGRAPH_TO_UNDIRECTED_EACH, NULL); BENCH(" 4 Random edge walk, undirected, unweighted, small graph ", igraph_random_edge_walk(&graph, NULL, &walk, 0, IGRAPH_OUT, 50000000, IGRAPH_RANDOM_WALK_STUCK_RETURN) ); BENCH(" 5 Random edge walk, undirected, weighted, small graph ", igraph_random_edge_walk(&graph, &weights, &walk, 0, IGRAPH_OUT, 50000000, IGRAPH_RANDOM_WALK_STUCK_RETURN) ); BENCH(" 6 Random vertex walk, undirected, unweighted, small graph ", igraph_random_walk(&graph, &walk, 0, IGRAPH_OUT, 50000000, IGRAPH_RANDOM_WALK_STUCK_RETURN) ); igraph_destroy(&graph); /* create a big graph, and a compatible weight vector */ igraph_de_bruijn(&graph, 8, 5); /* 32768 vertices, 262144 edges, average degree: 16 */ ec = igraph_ecount(&graph); igraph_vector_resize(&weights, ec); for (i = 0; i < ec; ++i) { VECTOR(weights)[i] = igraph_rng_get_unif01(igraph_rng_default()); } BENCH(" 7 Random edge walk, directed, unweighted, large graph ", igraph_random_edge_walk(&graph, NULL, &walk, 0, IGRAPH_OUT, 50000000, IGRAPH_RANDOM_WALK_STUCK_RETURN) ); BENCH(" 8 Random edge walk, directed, weighted, large graph ", igraph_random_edge_walk(&graph, &weights, &walk, 0, IGRAPH_OUT, 50000000, IGRAPH_RANDOM_WALK_STUCK_RETURN) ); BENCH(" 9 Random vertex walk, directed, unweighted, large graph ", igraph_random_walk(&graph, &walk, 0, IGRAPH_OUT, 50000000, IGRAPH_RANDOM_WALK_STUCK_RETURN) ); igraph_to_undirected(&graph, IGRAPH_TO_UNDIRECTED_EACH, NULL); BENCH("10 Random edge walk, undirected, unweighted, large graph ", igraph_random_edge_walk(&graph, NULL, &walk, 0, IGRAPH_OUT, 50000000, IGRAPH_RANDOM_WALK_STUCK_RETURN) ); BENCH("11 Random edge walk, undirected, weighted, large graph ", igraph_random_edge_walk(&graph, &weights, &walk, 0, IGRAPH_OUT, 50000000, IGRAPH_RANDOM_WALK_STUCK_RETURN) ); BENCH("12 Random vertex walk, undirected, unweighted, large graph ", igraph_random_walk(&graph, &walk, 0, IGRAPH_OUT, 50000000, IGRAPH_RANDOM_WALK_STUCK_RETURN) ); igraph_destroy(&graph); igraph_vector_destroy(&weights); igraph_vector_destroy(&walk); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/benchmarks/igraph_coloring.c0000644000076500000240000000130613612122633030053 0ustar tamasstaff00000000000000 #include #include "bench.h" int main() { igraph_t g; igraph_vector_int_t colors; igraph_rng_seed(igraph_rng_default(), 42); igraph_erdos_renyi_game(&g, IGRAPH_ERDOS_RENYI_GNM, 30000, 300000, /* directed = */ 0, /* loops = */ 0); igraph_vector_int_init(&colors, 0); BENCH("1 Vertex coloring a random graph with 30,000 vertices and 300,000 edges.", igraph_vertex_coloring_greedy(&g, &colors, IGRAPH_COLORING_GREEDY_COLORED_NEIGHBORS) ); /* Use the result to prevent optimizing it away. */ printf("Number of colors used: %d\n", igraph_vector_int_max(&colors)); igraph_vector_int_destroy(&colors); igraph_destroy(&g); return 0; } python-igraph-0.8.0/vendor/source/igraph/examples/benchmarks/igraph_maximal_cliques.c0000644000076500000240000000376713612122633031431 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2013 Gabor Csardi 334 Harvard st, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include "bench.h" int main() { igraph_t g; igraph_real_t toremovev[] = { 2609, 2098, 14517, 7540, 19560, 8855, 5939, 14947, 441, 16976, 19642, 4188, 15447, 11837, 2333, 7309, 18539, 14099, 14264, 9240 }; igraph_vector_t toremove; igraph_vector_ptr_t res; int i, n; igraph_vector_view(&toremove, toremovev, sizeof(toremovev) / sizeof(igraph_real_t)); igraph_full(&g, 200, IGRAPH_UNDIRECTED, IGRAPH_NO_LOOPS); igraph_delete_edges(&g, igraph_ess_vector(&toremove)); igraph_vector_ptr_init(&res, 0); BENCH("1 Maximal cliques of almost complete graph", igraph_maximal_cliques(&g, &res, /* min_size= */ 0, /* max_size= */ 0); ); igraph_destroy(&g); n = igraph_vector_ptr_size(&res); for (i = 0; i < n; i++) { igraph_vector_t *v = VECTOR(res)[i]; igraph_vector_destroy(v); igraph_free(v); } igraph_vector_ptr_destroy(&res); return 0; } python-igraph-0.8.0/vendor/source/igraph/.github/0000755000076500000240000000000013617375000022151 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/.github/stale.yml0000644000076500000240000000130513614300630023775 0ustar tamasstaff00000000000000# Number of days of inactivity before an issue becomes stale daysUntilStale: 60 # Number of days of inactivity before a stale issue is closed daysUntilClose: 7 # Issues with these labels will never be considered stale exemptLabels: - pinned - security - todo - wishlist # Label to use when marking an issue as stale staleLabel: stale # Comment to post when marking an issue as stale. Set to `false` to disable markComment: > This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions. # Comment to post when closing a stale issue. Set to `false` to disable closeComment: false python-igraph-0.8.0/vendor/source/igraph/.github/ISSUE_TEMPLATE.md0000644000076500000240000000053613614300625024660 0ustar tamasstaff00000000000000Please **do not** use the issue tracker for personal support requests -- use our [Discourse group](https://igraph.discourse.group) instead. Make sure that these boxes are checked before submitting your issue -- thank you! - [ ] This issue is for the C core of igraph. - [ ] This issue is a bug report or a feature request, not a support question. python-igraph-0.8.0/vendor/source/igraph/igraph_Info.plist.in0000644000076500000240000000126013524616144024523 0ustar tamasstaff00000000000000 CFBundleDevelopmentRegion English CFBundleExecutable igraph CFBundleIdentifier hu.kfki.rmki.cneuro.igraph CFBundleInfoDictionaryVersion 6.0 CFBundlePackageType FMWK CFBundleShortVersionString @VERSION@ CFBundleSignature DARC CFBundleVersion @VERSION@ python-igraph-0.8.0/vendor/source/igraph/doc/0000755000076500000240000000000013617375000021356 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/doc/attributes.xxml0000644000076500000240000000720713524616144024470 0ustar tamasstaff00000000000000 ]> Graph, Vertex and Edge Attributes
The Attribute Handler Interface
Accessing attributes from C
Query attributes
Set attributes
Remove attributes
python-igraph-0.8.0/vendor/source/igraph/doc/vector.xxml0000644000076500000240000001115313524616144023577 0ustar tamasstaff00000000000000 ]>
Vectors
Initializing elements
Vector views
Copying vectors
Exchanging elements
Vector operations
Vector comparisons
Finding minimum and maximum
Vector properties
Searching for elements
Resizing operations
Sorting
Set operations on sorted vectors
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Status handlers
Setting up status handlers
Invoking the status handler
python-igraph-0.8.0/vendor/source/igraph/doc/community.xxml0000644000076500000240000000416613614300625024321 0ustar tamasstaff00000000000000 ]> Detecting Community Structure
Common functions related to community structure
Community structure based on statistical mechanics
Community structure based on eigenvectors of matrices
Walktrap: community structure based on random walks
Edge betweenness based community detection
Community structure based on the optimization of modularity
Fluid Communities
Label propagation
The InfoMAP algorithm
python-igraph-0.8.0/vendor/source/igraph/doc/iterators.xxml0000644000076500000240000000620413524616144024312 0ustar tamasstaff00000000000000 ]> Vertex and Edge Selectors and Sequences, Iterators
Vertex selector constructors
Generic vertex selector operations
Immediate vertex selectors
Vertex iterators
Edge selector constructors
Immediate edge selectors
Generic edge selector operations
Edge iterators
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Cliques
Weighted cliques
Independent Vertex Sets
python-igraph-0.8.0/vendor/source/igraph/doc/igraph-docs.xml0000644000076500000240000000721013614300625024276 0ustar tamasstaff00000000000000 ]> &igraph; Reference Manual &version; GáborCsárdi Department of Statistics, Harvard University
1 Oxford street, Cambridge, MA, 02138 USA
 TamásNepusz Department of Biological Physics, Eötvös University
1/a Pázmány Péter sétány, 1117 Budapest, Hungary
 This manual is for &igraph;, version &version;. Copyright (C) 2005-2020 Gábor Csárdi and Tamás Nepusz. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. A copy of the license is included in the section entitled GNU Free Documentation License. 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KU“ŽšwÔA Z.C{ÑkUmvQõ&ß,’Ì°åKð†_õðÆÌ-JµûKšG§×.»¨M8$†±§^y˜Û¢ÔŽ^µûÂM@¯‚n°H6.ZÏ27àŽÞhüO¥pÇiÛÁgôjØÊH‹…‘l¸V €åË ÚåûXvåòà]âmDzÆ~#ld$Ù!¡Œ°2‡HGLo£Ó+ Ù4™Û4K`ª@âmD†µ?—“m‘lĆM•Ñ^.3´»ËgPË‹daÎá1wXªZ.‰p“T†ó>OèÉÂ|¦Ó庘3Âa© ×,{=“^Év•H£ž=£–šj¼uRaÇ°HÚu­0á&\½Õæ*«ûÒÑ+’…fy„£¥{¼E:æ[)—Ð+’,ÞFWO¨¼Ô©Í ¤zÃ’m@±j–\ÇÆo͆›Ëµèl££K_2K°Ø½áe¨F¢)(’mLyf¶Iõ„@âíÜ9µÑl³[¹dV–í'ÌŽ!Þ²N Y Þëô’…ôã­[ájO ÞÜXܱ’ê ®¡ÿ YWíÁY–U¬KHAv´õô HÖ=åu a„ñ½’õf…Y¶_ý’Œ·²O´öÕ£W@²ý©’‰·ei–GdY6›Í0, Y€6ñV­'h†£N¤gÙn€dºÆÛÊQ'”à¡ [Ø”É Y€È)W¨’pƒ¼º¥Z•9-¡;\øØäÙ,ËTÏbX@²îó,å$ €dÉ Y@²HÉ’@²H,’@²€d,’$ €d, Y€èÐW«Íóœà%É>ýôÓl/IöĉÓé”-àX²§Nú­ßú-¶ÄÄÿQgYj?ÍíIEND®B`‚python-igraph-0.8.0/vendor/source/igraph/doc/pmt.xml0000644000076500000240000001023113524616144022701 0ustar tamasstaff00000000000000 ]>
About template types Some of the container types listed in this section are defined for many base types. This is similar to templates in C++ and generics in Ada, but it is implemented via precompiler macros since the C language cannot handle it. Here is the list of template types and the all base types they currently support: vector Vector is currently defined for igraph_real_t, long int (long), char (char), igraph_bool_t (bool). The default is igraph_real_t. matrix Matrix is currently defined for igraph_real_t, long int (long), char (char), igraph_bool_t (bool). The default is igraph_real_t. array3 Array3 is currently defined for igraph_real_t, long int (long), char (char), igraph_bool_t (bool). The default is igraph_real_t. stack Stack is currently defined for igraph_real_t, long int (long), char (char), igraph_bool_t (bool). The default is igraph_real_t. double-ended queue Dqueue is currently defined for igraph_real_t, long int (long), char (char), igraph_bool_t (bool). The default is igraph_real_t. heap Heap is currently defined for igraph_real_t, long int (long), char (char). In addition both maximum and minimum heaps are available. The default is the igraph_real_t maximum heap. The name of the base element (in parens) is added to the function names, except for te default type. Some examples: igraph_vector_t is a vector of igraph_real_t elements. Its functions are igraph_vector_init, igraph_vector_destroy, igraph_vector_sort, etc. igraph_vector_bool_t is a vector of igraph_bool_t elements, initialize it with igraph_vector_bool_init, destroy it with igraph_vector_bool_destroy, etc. igraph_heap_t is a maximum heap with igraph_real_t elements. The corresponding functions are igraph_heap_init, igraph_heap_pop, etc. igraph_heap_min_t is a minimum heap with igraph_real_t elements. The corresponding functions are called igraph_heap_min_init, igraph_heap_min_pop, etc. igraph_heap_long_t is a maximum heap with long int elements. Its function have the igraph_heap_long_ prefix. igraph_heap_min_long_t is a minimum heap containing long int elements. Its functions have the igraph_heap_min_long_ prefix. Note that the VECTOR and the MATRIX macros can be used on all vector and matrix types.
python-igraph-0.8.0/vendor/source/igraph/doc/bibdatabase.xml0000644000076500000240000000360413524616144024330 0ustar tamasstaff00000000000000 Albert-László Barabási RékaAlbert Emergence of scaling in random networks Science 1999 286 509-512 LászlóZalányi GáborCsárdi TamásKiss MátéLengyel RebeccaWarner JanTobochnik PéterÉrdi Properties of a random attachment growing network Phyisical Review E 2003 68 066104 L. R.Ford Jr. D. R.Fulkerson Maximal ow through a network Canadian J. Math. 1956 8 399--404 python-igraph-0.8.0/vendor/source/igraph/doc/progress.xxml0000644000076500000240000000170013524616144024136 0ustar tamasstaff00000000000000 ]>
Progress handlers
Setting up progress handlers
Invoking the progress handler
python-igraph-0.8.0/vendor/source/igraph/doc/igraph.30000644000076500000240000000320313524616144022716 0ustar tamasstaff00000000000000.\" Hey, Emacs! This is an -*- nroff -*- source file. .\" .\" Copyright (C) 2006-2012 Tamas Nepusz .\" Pázmány Péter sétány 1/a, 1117 Budapest, Hungary .\" .\" This is free software; you can redistribute it and/or modify it under .\" the terms of the GNU General Public License as published by the Free .\" Software Foundation; either version 2, or (at your option) any later .\" version. .\" .\" This is distributed in the hope that it will be useful, but WITHOUT .\" ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or .\" FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License .\" for more details. .\" .\" You should have received a copy of the GNU General Public License with .\" your Debian GNU/Linux system, in /usr/share/common-licenses/GPL, or with .\" the dpkg source package as the file COPYING. If not, write to the Free .\" Software Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA. .\" .TH IGRAPH 3 "March 2007" "igraph library" .SH NAME igraph \- a library for creating and manipulating graphs .SH DESCRIPTION .B igraph is a library for creating and manipulating graphs. It is intended to be as powerful (ie. fast) as possible to enable the analysis of large graphs. .SH DOCUMENTATION The full documentation can be downloaded from the homepage of the library: .RI < http://igraph.org > .PP You might also try the info pages of igraph if they are installed: info igraph-docs .SH BUGS If you think you have found a bug in igraph, feel free to use the mailing list at .B igraph-help@nongnu.org. .SH AUTHORS Gabor Csardi , .br Tamas Nepusz python-igraph-0.8.0/vendor/source/igraph/doc/matrix.xxml0000644000076500000240000000741313524616144023605 0ustar tamasstaff00000000000000 ]>
Matrices
Initializing elements
Copying matrices
Operations on rows and columns
Matrix operations
Matrix comparisons
Combining matrices
Finding minimum and maximum
Matrix properties
Searching for elements
Resizing operations
python-igraph-0.8.0/vendor/source/igraph/doc/layout.xxml0000644000076500000240000000347713524616144023624 0ustar tamasstaff00000000000000 ]> Generating Layouts for Graph Drawing
2D layout generators
The DrL layout generator
3D layout generators
Merging layouts
python-igraph-0.8.0/vendor/source/igraph/doc/sitemap_gen.py0000755000076500000240000020311113524616144024230 0ustar tamasstaff00000000000000#!/usr/bin/env python # # Copyright (c) 2004, 2005 Google Inc. # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions # are met: # # * Redistributions of source code must retain the above copyright # notice, this list of conditions and the following disclaimer. # # * Redistributions in binary form must reproduce the above copyright # notice, this list of conditions and the following disclaimer in # the documentation and/or other materials provided with the # distribution. # # * Neither the name of Google nor the names of its contributors may # be used to endorse or promote products derived from this software # without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS # "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT # LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS # FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE # COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, # INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, # BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; # LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT # LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN # ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE # POSSIBILITY OF SUCH DAMAGE. # # # The sitemap_gen.py script is written in Python 2.2 and released to # the open source community for continuous improvements under the BSD # 2.0 new license, which can be found at: # # http://www.opensource.org/licenses/bsd-license.php # __usage__ = \ """A simple script to automatically produce sitemaps for a webserver, in the Google Sitemap Protocol (GSP). Usage: python sitemap_gen.py --config=config.xml [--help] [--testing] --config=config.xml, specifies config file location --help, displays usage message --testing, specified when user is experimenting """ # Please be careful that all syntax used in this file can be parsed on # Python 1.5 -- this version check is not evaluated until after the # entire file has been parsed. import sys if sys.hexversion < 0x02020000: print 'This script requires Python 2.2 or later.' print 'Currently run with version: %s' % sys.version sys.exit(1) import fnmatch import glob import gzip import md5 import os import re import stat import time import types import urllib import urlparse import xml.sax # True and False were introduced in Python2.2.2 try: testTrue=True del testTrue except NameError: True=1 False=0 # Text encodings ENC_ASCII = 'ASCII' ENC_UTF8 = 'UTF-8' ENC_IDNA = 'IDNA' ENC_ASCII_LIST = ['ASCII', 'US-ASCII', 'US', 'IBM367', 'CP367', 'ISO646-US' 'ISO_646.IRV:1991', 'ISO-IR-6', 'ANSI_X3.4-1968', 'ANSI_X3.4-1986', 'CPASCII' ] ENC_DEFAULT_LIST = ['ISO-8859-1', 'ISO-8859-2', 'ISO-8859-5'] # Available Sitemap types SITEMAP_TYPES = ['web', 'mobile', 'news'] # General Sitemap tags GENERAL_SITEMAP_TAGS = ['loc', 'changefreq', 'priority', 'lastmod'] # News specific tags NEWS_SPECIFIC_TAGS = ['keywords', 'publication_date', 'stock_tickers'] # News Sitemap tags NEWS_SITEMAP_TAGS = GENERAL_SITEMAP_TAGS + NEWS_SPECIFIC_TAGS # Maximum number of urls in each sitemap, before next Sitemap is created MAXURLS_PER_SITEMAP = 50000 # Suffix on a Sitemap index file SITEINDEX_SUFFIX = '_index.xml' # Regular expressions tried for extracting URLs from access logs. ACCESSLOG_CLF_PATTERN = re.compile( r'.+\s+"([^\s]+)\s+([^\s]+)\s+HTTP/\d+\.\d+"\s+200\s+.*' ) # Match patterns for lastmod attributes DATE_PATTERNS = map(re.compile, [ r'^\d\d\d\d$', r'^\d\d\d\d-\d\d$', r'^\d\d\d\d-\d\d-\d\d$', r'^\d\d\d\d-\d\d-\d\dT\d\d:\d\dZ$', r'^\d\d\d\d-\d\d-\d\dT\d\d:\d\d[+-]\d\d:\d\d$', r'^\d\d\d\d-\d\d-\d\dT\d\d:\d\d:\d\d(\.\d+)?Z$', r'^\d\d\d\d-\d\d-\d\dT\d\d:\d\d:\d\d(\.\d+)?[+-]\d\d:\d\d$', ]) # Match patterns for changefreq attributes CHANGEFREQ_PATTERNS = [ 'always', 'hourly', 'daily', 'weekly', 'monthly', 'yearly', 'never' ] # XML formats GENERAL_SITEINDEX_HEADER = \ '\n' \ '\n' NEWS_SITEINDEX_HEADER = \ '\n' \ '\n' SITEINDEX_FOOTER = '\n' SITEINDEX_ENTRY = \ ' \n' \ ' %(loc)s\n' \ ' %(lastmod)s\n' \ ' \n' GENERAL_SITEMAP_HEADER = \ '\n' \ '\n' NEWS_SITEMAP_HEADER = \ '\n' \ '\n' SITEMAP_FOOTER = '\n' SITEURL_XML_PREFIX = ' \n' SITEURL_XML_SUFFIX = ' \n' NEWS_TAG_XML_PREFIX = ' \n' NEWS_TAG_XML_SUFFIX = ' \n' # Search engines to notify with the updated sitemaps # # This list is very non-obvious in what's going on. Here's the gist: # Each item in the list is a 6-tuple of items. The first 5 are "almost" # the same as the input arguments to urlparse.urlunsplit(): # 0 - schema # 1 - netloc # 2 - path # 3 - query <-- EXCEPTION: specify a query map rather than a string # 4 - fragment # Additionally, add item 5: # 5 - query attribute that should be set to the new Sitemap URL # Clear as mud, I know. NOTIFICATION_SITES = [ ('http', 'www.google.com', 'webmasters/sitemaps/ping', {}, '', 'sitemap'), ] class Error(Exception): """ Base exception class. In this module we tend not to use our own exception types for very much, but they come in very handy on XML parsing with SAX. """ pass #end class Error class SchemaError(Error): """Failure to process an XML file according to the schema we know.""" pass #end class SchemeError class Encoder: """ Manages wide-character/narrow-character conversions for just about all text that flows into or out of the script. You should always use this class for string coercion, as opposed to letting Python handle coercions automatically. Reason: Python usually assumes ASCII (7-bit) as a default narrow character encoding, which is not the kind of data we generally deal with. General high-level methodologies used in sitemap_gen: [PATHS] File system paths may be wide or narrow, depending on platform. This works fine, just be aware of it and be very careful to not mix them. That is, if you have to pass several file path arguments into a library call, make sure they are all narrow or all wide. This class has MaybeNarrowPath() which should be called on every file system path you deal with. [URLS] URL locations are stored in Narrow form, already escaped. This has the benefit of keeping escaping and encoding as close as possible to the format we read them in. The downside is we may end up with URLs that have intermingled encodings -- the root path may be encoded in one way while the filename is encoded in another. This is obviously wrong, but it should hopefully be an issue hit by very few users. The workaround from the user level (assuming they notice) is to specify a default_encoding parameter in their config file. [OTHER] Other text, such as attributes of the URL class, configuration options, etc, are generally stored in Unicode for simplicity. """ def __init__(self): self._user = None # User-specified default encoding self._learned = [] # Learned default encodings self._widefiles = False # File system can be wide # Can the file system be Unicode? try: self._widefiles = os.path.supports_unicode_filenames except AttributeError: try: self._widefiles = sys.getwindowsversion() == os.VER_PLATFORM_WIN32_NT except AttributeError: pass # Try to guess a working default try: encoding = sys.getfilesystemencoding() if encoding and not (encoding.upper() in ENC_ASCII_LIST): self._learned = [ encoding ] except AttributeError: pass if not self._learned: encoding = sys.getdefaultencoding() if encoding and not (encoding.upper() in ENC_ASCII_LIST): self._learned = [ encoding ] # If we had no guesses, start with some European defaults if not self._learned: self._learned = ENC_DEFAULT_LIST #end def __init__ def SetUserEncoding(self, encoding): self._user = encoding #end def SetUserEncoding def NarrowText(self, text, encoding): """ Narrow a piece of arbitrary text """ if type(text) != types.UnicodeType: return text # Try the passed in preference if encoding: try: result = text.encode(encoding) if not encoding in self._learned: self._learned.append(encoding) return result except UnicodeError: pass except LookupError: output.Warn('Unknown encoding: %s' % encoding) # Try the user preference if self._user: try: return text.encode(self._user) except UnicodeError: pass except LookupError: temp = self._user self._user = None output.Warn('Unknown default_encoding: %s' % temp) # Look through learned defaults, knock any failing ones out of the list while self._learned: try: return text.encode(self._learned[0]) except: del self._learned[0] # When all other defaults are exhausted, use UTF-8 try: return text.encode(ENC_UTF8) except UnicodeError: pass # Something is seriously wrong if we get to here return text.encode(ENC_ASCII, 'ignore') #end def NarrowText def MaybeNarrowPath(self, text): """ Paths may be allowed to stay wide """ if self._widefiles: return text return self.NarrowText(text, None) #end def MaybeNarrowPath def WidenText(self, text, encoding): """ Widen a piece of arbitrary text """ if type(text) != types.StringType: return text # Try the passed in preference if encoding: try: result = unicode(text, encoding) if not encoding in self._learned: self._learned.append(encoding) return result except UnicodeError: pass except LookupError: output.Warn('Unknown encoding: %s' % encoding) # Try the user preference if self._user: try: return unicode(text, self._user) except UnicodeError: pass except LookupError: temp = self._user self._user = None output.Warn('Unknown default_encoding: %s' % temp) # Look through learned defaults, knock any failing ones out of the list while self._learned: try: return unicode(text, self._learned[0]) except: del self._learned[0] # When all other defaults are exhausted, use UTF-8 try: return unicode(text, ENC_UTF8) except UnicodeError: pass # Getting here means it wasn't UTF-8 and we had no working default. # We really don't have anything "right" we can do anymore. output.Warn('Unrecognized encoding in text: %s' % text) if not self._user: output.Warn('You may need to set a default_encoding in your ' 'configuration file.') return text.decode(ENC_ASCII, 'ignore') #end def WidenText #end class Encoder encoder = Encoder() class Output: """ Exposes logging functionality, and tracks how many errors we have thus output. Logging levels should be used as thus: Fatal -- extremely sparingly Error -- config errors, entire blocks of user 'intention' lost Warn -- individual URLs lost Log(,0) -- Un-suppressable text that's not an error Log(,1) -- touched files, major actions Log(,2) -- parsing notes, filtered or duplicated URLs Log(,3) -- each accepted URL """ def __init__(self): self.num_errors = 0 # Count of errors self.num_warns = 0 # Count of warnings self._errors_shown = {} # Shown errors self._warns_shown = {} # Shown warnings self._verbose = 0 # Level of verbosity #end def __init__ def Log(self, text, level): """ Output a blurb of diagnostic text, if the verbose level allows it """ if text: text = encoder.NarrowText(text, None) if self._verbose >= level: print text #end def Log def Warn(self, text): """ Output and count a warning. Suppress duplicate warnings. """ if text: text = encoder.NarrowText(text, None) hash = md5.new(text).digest() if not self._warns_shown.has_key(hash): self._warns_shown[hash] = 1 print '[WARNING] ' + text else: self.Log('(suppressed) [WARNING] ' + text, 3) self.num_warns = self.num_warns + 1 #end def Warn def Error(self, text): """ Output and count an error. Suppress duplicate errors. """ if text: text = encoder.NarrowText(text, None) hash = md5.new(text).digest() if not self._errors_shown.has_key(hash): self._errors_shown[hash] = 1 print '[ERROR] ' + text else: self.Log('(suppressed) [ERROR] ' + text, 3) self.num_errors = self.num_errors + 1 #end def Error def Fatal(self, text): """ Output an error and terminate the program. """ if text: text = encoder.NarrowText(text, None) print '[FATAL] ' + text else: print 'Fatal error.' sys.exit(1) #end def Fatal def SetVerbose(self, level): """ Sets the verbose level. """ try: if type(level) != types.IntType: level = int(level) if (level >= 0) and (level <= 3): self._verbose = level return except ValueError: pass self.Error('Verbose level (%s) must be between 0 and 3 inclusive.' % level) #end def SetVerbose #end class Output output = Output() class URL(object): """ URL is a smart structure grouping together the properties we care about for a single web reference. """ __slots__ = 'loc', 'lastmod', 'changefreq', 'priority' def __init__(self): self.loc = None # URL -- in Narrow characters self.lastmod = None # ISO8601 timestamp of last modify self.changefreq = None # Text term for update frequency self.priority = None # Float between 0 and 1 (inc) #end def __init__ def __cmp__(self, other): if self.loc < other.loc: return -1 if self.loc > other.loc: return 1 return 0 #end def __cmp__ def TrySetAttribute(self, attribute, value): """ Attempt to set the attribute to the value, with a pretty try block around it. """ if attribute == 'loc': self.loc = self.Canonicalize(value) else: try: setattr(self, attribute, value) except AttributeError: output.Warn('Unknown URL attribute: %s' % attribute) #end def TrySetAttribute def IsAbsolute(loc): """ Decide if the URL is absolute or not """ if not loc: return False narrow = encoder.NarrowText(loc, None) (scheme, netloc, path, query, frag) = urlparse.urlsplit(narrow) if (not scheme) or (not netloc): return False return True #end def IsAbsolute IsAbsolute = staticmethod(IsAbsolute) def Canonicalize(loc): """ Do encoding and canonicalization on a URL string """ if not loc: return loc # Let the encoder try to narrow it narrow = encoder.NarrowText(loc, None) # Escape components individually (scheme, netloc, path, query, frag) = urlparse.urlsplit(narrow) unr = '-._~' sub = '!$&\'()*+,;=' netloc = urllib.quote(netloc, unr + sub + '%:@/[]') path = urllib.quote(path, unr + sub + '%:@/') query = urllib.quote(query, unr + sub + '%:@/?') frag = urllib.quote(frag, unr + sub + '%:@/?') # Try built-in IDNA encoding on the netloc try: (ignore, widenetloc, ignore, ignore, ignore) = urlparse.urlsplit(loc) for c in widenetloc: if c >= unichr(128): netloc = widenetloc.encode(ENC_IDNA) netloc = urllib.quote(netloc, unr + sub + '%:@/[]') break except UnicodeError: # urlsplit must have failed, based on implementation differences in the # library. There is not much we can do here, except ignore it. pass except LookupError: output.Warn('An International Domain Name (IDN) is being used, but this ' 'version of Python does not have support for IDNA encoding. ' ' (IDNA support was introduced in Python 2.3) The encoding ' 'we have used instead is wrong and will probably not yield ' 'valid URLs.') bad_netloc = False if '%' in netloc: bad_netloc = True # Put it all back together narrow = urlparse.urlunsplit((scheme, netloc, path, query, frag)) # I let '%' through. Fix any that aren't pre-existing escapes. HEXDIG = '0123456789abcdefABCDEF' list = narrow.split('%') narrow = list[0] del list[0] for item in list: if (len(item) >= 2) and (item[0] in HEXDIG) and (item[1] in HEXDIG): narrow = narrow + '%' + item else: narrow = narrow + '%25' + item # Issue a warning if this is a bad URL if bad_netloc: output.Warn('Invalid characters in the host or domain portion of a URL: ' + narrow) return narrow #end def Canonicalize Canonicalize = staticmethod(Canonicalize) def VerifyDate(self, date, metatag): """Verify the date format is valid""" match = False if date: date = date.upper() for pattern in DATE_PATTERNS: match = pattern.match(date) if match: return True if not match: output.Warn('The value for %s does not appear to be in ISO8601 ' 'format on URL: %s' % (metatag, self.loc)) return False #end of VerifyDate def Validate(self, base_url, allow_fragment): """ Verify the data in this URL is well-formed, and override if not. """ assert type(base_url) == types.StringType # Test (and normalize) the ref if not self.loc: output.Warn('Empty URL') return False if allow_fragment: self.loc = urlparse.urljoin(base_url, self.loc) if not self.loc.startswith(base_url): output.Warn('Discarded URL for not starting with the base_url: %s' % self.loc) self.loc = None return False # Test the lastmod if self.lastmod: if not self.VerifyDate(self.lastmod, "lastmod"): self.lastmod = None # Test the changefreq if self.changefreq: match = False self.changefreq = self.changefreq.lower() for pattern in CHANGEFREQ_PATTERNS: if self.changefreq == pattern: match = True break if not match: output.Warn('Changefreq "%s" is not a valid change frequency on URL ' ': %s' % (self.changefreq, self.loc)) self.changefreq = None # Test the priority if self.priority: priority = -1.0 try: priority = float(self.priority) except ValueError: pass if (priority < 0.0) or (priority > 1.0): output.Warn('Priority "%s" is not a number between 0 and 1 inclusive ' 'on URL: %s' % (self.priority, self.loc)) self.priority = None return True #end def Validate def MakeHash(self): """ Provides a uniform way of hashing URLs """ if not self.loc: return None if self.loc.endswith('/'): return md5.new(self.loc[:-1]).digest() return md5.new(self.loc).digest() #end def MakeHash def Log(self, prefix='URL', level=3): """ Dump the contents, empty or not, to the log. """ out = prefix + ':' for attribute in self.__slots__: value = getattr(self, attribute) if not value: value = '' out = out + (' %s=[%s]' % (attribute, value)) output.Log('%s' % encoder.NarrowText(out, None), level) #end def Log def WriteXML(self, file): """ Dump non-empty contents to the output file, in XML format. """ if not self.loc: return out = SITEURL_XML_PREFIX for attribute in self.__slots__: value = getattr(self, attribute) if value: if type(value) == types.UnicodeType: value = encoder.NarrowText(value, None) elif type(value) != types.StringType: value = str(value) value = xml.sax.saxutils.escape(value) out = out + (' <%s>%s\n' % (attribute, value, attribute)) out = out + SITEURL_XML_SUFFIX file.write(out) #end def WriteXML #end class URL class NewsURL(URL): """ NewsURL is a subclass of URL with News-Sitemap specific properties. """ __slots__ = 'loc', 'lastmod', 'changefreq', 'priority', 'publication_date', \ 'keywords', 'stock_tickers' def __init__(self): URL.__init__(self) self.publication_date = None # ISO8601 timestamp of publication date self.keywords = None # Text keywords self.stock_tickers = None # Text stock #end def __init__ def Validate(self, base_url, allow_fragment): """ Verify the data in this News URL is well-formed, and override if not. """ assert type(base_url) == types.StringType if not URL.Validate(self, base_url, allow_fragment): return False if not URL.VerifyDate(self, self.publication_date, "publication_date"): self.publication_date = None return True #end def Validate def WriteXML(self, file): """ Dump non-empty contents to the output file, in XML format. """ if not self.loc: return out = SITEURL_XML_PREFIX # printed_news_tag indicates if news-specific metatags are present printed_news_tag = False for attribute in self.__slots__: value = getattr(self, attribute) if value: if type(value) == types.UnicodeType: value = encoder.NarrowText(value, None) elif type(value) != types.StringType: value = str(value) value = xml.sax.saxutils.escape(value) if attribute in NEWS_SPECIFIC_TAGS: if not printed_news_tag: printed_news_tag = True out = out + NEWS_TAG_XML_PREFIX out = out + (' %s\n' % (attribute, value, attribute)) else: out = out + (' <%s>%s\n' % (attribute, value, attribute)) if printed_news_tag: out = out + NEWS_TAG_XML_SUFFIX out = out + SITEURL_XML_SUFFIX file.write(out) #end def WriteXML #end class NewsURL class Filter: """ A filter on the stream of URLs we find. A filter is, in essence, a wildcard applied to the stream. You can think of this as an operator that returns a tri-state when given a URL: True -- this URL is to be included in the sitemap None -- this URL is undecided False -- this URL is to be dropped from the sitemap """ def __init__(self, attributes): self._wildcard = None # Pattern for wildcard match self._regexp = None # Pattern for regexp match self._pass = False # "Drop" filter vs. "Pass" filter if not ValidateAttributes('FILTER', attributes, ('pattern', 'type', 'action')): return # Check error count on the way in num_errors = output.num_errors # Fetch the attributes pattern = attributes.get('pattern') type = attributes.get('type', 'wildcard') action = attributes.get('action', 'drop') if type: type = type.lower() if action: action = action.lower() # Verify the attributes if not pattern: output.Error('On a filter you must specify a "pattern" to match') elif (not type) or ((type != 'wildcard') and (type != 'regexp')): output.Error('On a filter you must specify either \'type="wildcard"\' ' 'or \'type="regexp"\'') elif (action != 'pass') and (action != 'drop'): output.Error('If you specify a filter action, it must be either ' '\'action="pass"\' or \'action="drop"\'') # Set the rule if action == 'drop': self._pass = False elif action == 'pass': self._pass = True if type == 'wildcard': self._wildcard = pattern elif type == 'regexp': try: self._regexp = re.compile(pattern) except re.error: output.Error('Bad regular expression: %s' % pattern) # Log the final results iff we didn't add any errors if num_errors == output.num_errors: output.Log('Filter: %s any URL that matches %s "%s"' % (action, type, pattern), 2) #end def __init__ def Apply(self, url): """ Process the URL, as above. """ if (not url) or (not url.loc): return None if self._wildcard: if fnmatch.fnmatchcase(url.loc, self._wildcard): return self._pass return None if self._regexp: if self._regexp.search(url.loc): return self._pass return None assert False # unreachable #end def Apply #end class Filter class InputURL: """ Each Input class knows how to yield a set of URLs from a data source. This one handles a single URL, manually specified in the config file. """ def __init__(self, attributes): self._url = None # The lonely URL if not ValidateAttributes('URL', attributes, ('href', 'lastmod', 'changefreq', 'priority')): return url = URL() for attr in attributes.keys(): if attr == 'href': url.TrySetAttribute('loc', attributes[attr]) else: url.TrySetAttribute(attr, attributes[attr]) if not url.loc: output.Error('Url entries must have an href attribute.') return self._url = url output.Log('Input: From URL "%s"' % self._url.loc, 2) #end def __init__ def ProduceURLs(self, consumer): """ Produces URLs from our data source, hands them in to the consumer. """ if self._url: consumer(self._url, True) #end def ProduceURLs #end class InputURL class InputURLList: """ Each Input class knows how to yield a set of URLs from a data source. This one handles a text file with a list of URLs """ def __init__(self, attributes): self._path = None # The file path self._encoding = None # Encoding of that file if not ValidateAttributes('URLLIST', attributes, ('path', 'encoding')): return self._path = attributes.get('path') self._encoding = attributes.get('encoding', ENC_UTF8) if self._path: self._path = encoder.MaybeNarrowPath(self._path) if os.path.isfile(self._path): output.Log('Input: From URLLIST "%s"' % self._path, 2) else: output.Error('Can not locate file: %s' % self._path) self._path = None else: output.Error('Urllist entries must have a "path" attribute.') #end def __init__ def ProduceURLs(self, consumer): """ Produces URLs from our data source, hands them in to the consumer. """ # Open the file (frame, file) = OpenFileForRead(self._path, 'URLLIST') if not file: return # Iterate lines linenum = 0 for line in file.readlines(): linenum = linenum + 1 # Strip comments and empty lines if self._encoding: line = encoder.WidenText(line, self._encoding) line = line.strip() if (not line) or line[0] == '#': continue # Split the line on space url = URL() cols = line.split(' ') for i in range(0,len(cols)): cols[i] = cols[i].strip() url.TrySetAttribute('loc', cols[0]) # Extract attributes from the other columns for i in range(1,len(cols)): if cols[i]: try: (attr_name, attr_val) = cols[i].split('=', 1) url.TrySetAttribute(attr_name, attr_val) except ValueError: output.Warn('Line %d: Unable to parse attribute: %s' % (linenum, cols[i])) # Pass it on consumer(url, False) file.close() if frame: frame.close() #end def ProduceURLs #end class InputURLList class InputNewsURLList: """ Each Input class knows how to yield a set of URLs from a data source. This one handles a text file with a list of News URLs and their metadata """ def __init__(self, attributes): self._path = None # The file path self._encoding = None # Encoding of that file self._tag_order = [] # Order of URL metadata if not ValidateAttributes('URLLIST', attributes, ('path', 'encoding', \ 'tag_order')): return self._path = attributes.get('path') self._encoding = attributes.get('encoding', ENC_UTF8) self._tag_order = attributes.get('tag_order') if self._path: self._path = encoder.MaybeNarrowPath(self._path) if os.path.isfile(self._path): output.Log('Input: From URLLIST "%s"' % self._path, 2) else: output.Error('Can not locate file: %s' % self._path) self._path = None else: output.Error('Urllist entries must have a "path" attribute.') # parse tag_order into an array # tag_order_ascii created for more readable logging tag_order_ascii = [] if self._tag_order: self._tag_order = self._tag_order.split(",") for i in range(0, len(self._tag_order)): element = self._tag_order[i].strip().lower() self._tag_order[i]= element tag_order_ascii.append(element.encode('ascii')) output.Log('Input: From URLLIST tag order is "%s"' % tag_order_ascii, 0) else: output.Error('News Urllist configuration file must contain tag_order ' 'to define Sitemap metatags.') # verify all tag_order inputs are valid tag_order_dict = {} for tag in self._tag_order: tag_order_dict[tag] = "" if not ValidateAttributes('URLLIST', tag_order_dict, \ NEWS_SITEMAP_TAGS): return # loc tag must be present loc_tag = False for tag in self._tag_order: if tag == 'loc': loc_tag = True break if not loc_tag: output.Error('News Urllist tag_order in configuration file ' 'does not contain "loc" value: %s' % tag_order_ascii) #end def __init__ def ProduceURLs(self, consumer): """ Produces URLs from our data source, hands them in to the consumer. """ # Open the file (frame, file) = OpenFileForRead(self._path, 'URLLIST') if not file: return # Iterate lines linenum = 0 for line in file.readlines(): linenum = linenum + 1 # Strip comments and empty lines if self._encoding: line = encoder.WidenText(line, self._encoding) line = line.strip() if (not line) or line[0] == '#': continue # Split the line on tabs url = NewsURL() cols = line.split('\t') for i in range(0,len(cols)): cols[i] = cols[i].strip() for i in range(0,len(cols)): if cols[i]: attr_value = cols[i] if i < len(self._tag_order): attr_name = self._tag_order[i] try: url.TrySetAttribute(attr_name, attr_value) except ValueError: output.Warn('Line %d: Unable to parse attribute: %s' % (linenum, cols[i])) # Pass it on consumer(url, False) file.close() if frame: frame.close() #end def ProduceURLs #end class InputNewsURLList class InputDirectory: """ Each Input class knows how to yield a set of URLs from a data source. This one handles a directory that acts as base for walking the filesystem. """ def __init__(self, attributes, base_url): self._path = None # The directory self._url = None # The URL equivalent self._default_file = None self._remove_empty_directories = False if not ValidateAttributes('DIRECTORY', attributes, ('path', 'url', 'default_file', 'remove_empty_directories')): return # Prep the path -- it MUST end in a sep path = attributes.get('path') if not path: output.Error('Directory entries must have both "path" and "url" ' 'attributes') return path = encoder.MaybeNarrowPath(path) if not path.endswith(os.sep): path = path + os.sep if not os.path.isdir(path): output.Error('Can not locate directory: %s' % path) return # Prep the URL -- it MUST end in a sep url = attributes.get('url') if not url: output.Error('Directory entries must have both "path" and "url" ' 'attributes') return url = URL.Canonicalize(url) if not url.endswith('/'): url = url + '/' if not url.startswith(base_url): url = urlparse.urljoin(base_url, url) if not url.startswith(base_url): output.Error('The directory URL "%s" is not relative to the ' 'base_url: %s' % (url, base_url)) return # Prep the default file -- it MUST be just a filename file = attributes.get('default_file') if file: file = encoder.MaybeNarrowPath(file) if os.sep in file: output.Error('The default_file "%s" can not include path information.' % file) file = None # Prep the remove_empty_directories -- default is false remove_empty_directories = attributes.get('remove_empty_directories') if remove_empty_directories: if (remove_empty_directories == '1') or \ (remove_empty_directories.lower() == 'true'): remove_empty_directories = True elif (remove_empty_directories == '0') or \ (remove_empty_directories.lower() == 'false'): remove_empty_directories = False # otherwise the user set a non-default value else: output.Error('Configuration file remove_empty_directories ' 'value is not recognized. Value must be true or false.') return else: remove_empty_directories = False self._path = path self._url = url self._default_file = file self._remove_empty_directories = remove_empty_directories if file: output.Log('Input: From DIRECTORY "%s" (%s) with default file "%s"' % (path, url, file), 2) else: output.Log('Input: From DIRECTORY "%s" (%s) with no default file' % (path, url), 2) #end def __init__ def ProduceURLs(self, consumer): """ Produces URLs from our data source, hands them in to the consumer. """ if not self._path: return root_path = self._path root_URL = self._url root_file = self._default_file remove_empty_directories = self._remove_empty_directories def HasReadPermissions(path): """ Verifies a given path has read permissions. """ stat_info = os.stat(path) mode = stat_info[stat.ST_MODE] if mode & stat.S_IREAD: return True else: return None def PerFile(dirpath, name): """ Called once per file. Note that 'name' will occasionally be None -- for a directory itself """ # Pull a timestamp url = URL() isdir = False try: if name: path = os.path.join(dirpath, name) else: path = dirpath isdir = os.path.isdir(path) time = None if isdir and root_file: file = os.path.join(path, root_file) try: time = os.stat(file)[stat.ST_MTIME]; except OSError: pass if not time: time = os.stat(path)[stat.ST_MTIME]; url.lastmod = TimestampISO8601(time) except OSError: pass except ValueError: pass # Build a URL middle = dirpath[len(root_path):] if os.sep != '/': middle = middle.replace(os.sep, '/') if middle: middle = middle + '/' if name: middle = middle + name if isdir: middle = middle + '/' url.TrySetAttribute('loc', root_URL + encoder.WidenText(middle, None)) # Suppress default files. (All the way down here so we can log it.) if name and (root_file == name): url.Log(prefix='IGNORED (default file)', level=2) return # Suppress directories when remove_empty_directories="true" try: if isdir: if HasReadPermissions(path): if remove_empty_directories == 'true' and \ len(os.listdir(path)) == 0: output.Log('IGNORED empty directory %s' % str(path), level=1) return elif path == self._path: output.Error('IGNORED configuration file directory input %s due ' 'to file permissions' % self._path) else: output.Log('IGNORED files within directory %s due to file ' 'permissions' % str(path), level=0) except OSError: pass except ValueError: pass consumer(url, False) #end def PerFile def PerDirectory(ignore, dirpath, namelist): """ Called once per directory with a list of all the contained files/dirs. """ ignore = ignore # Avoid warnings of an unused parameter if not dirpath.startswith(root_path): output.Warn('Unable to decide what the root path is for directory: ' '%s' % dirpath) return for name in namelist: PerFile(dirpath, name) #end def PerDirectory output.Log('Walking DIRECTORY "%s"' % self._path, 1) PerFile(self._path, None) os.path.walk(self._path, PerDirectory, None) #end def ProduceURLs #end class InputDirectory class InputAccessLog: """ Each Input class knows how to yield a set of URLs from a data source. This one handles access logs. It's non-trivial in that we want to auto-detect log files in the Common Logfile Format (as used by Apache, for instance) and the Extended Log File Format (as used by IIS, for instance). """ def __init__(self, attributes): self._path = None # The file path self._encoding = None # Encoding of that file self._is_elf = False # Extended Log File Format? self._is_clf = False # Common Logfile Format? self._elf_status = -1 # ELF field: '200' self._elf_method = -1 # ELF field: 'HEAD' self._elf_uri = -1 # ELF field: '/foo?bar=1' self._elf_urifrag1 = -1 # ELF field: '/foo' self._elf_urifrag2 = -1 # ELF field: 'bar=1' if not ValidateAttributes('ACCESSLOG', attributes, ('path', 'encoding')): return self._path = attributes.get('path') self._encoding = attributes.get('encoding', ENC_UTF8) if self._path: self._path = encoder.MaybeNarrowPath(self._path) if os.path.isfile(self._path): output.Log('Input: From ACCESSLOG "%s"' % self._path, 2) else: output.Error('Can not locate file: %s' % self._path) self._path = None else: output.Error('Accesslog entries must have a "path" attribute.') #end def __init__ def RecognizeELFLine(self, line): """ Recognize the Fields directive that heads an ELF file """ if not line.startswith('#Fields:'): return False fields = line.split(' ') del fields[0] for i in range(0, len(fields)): field = fields[i].strip() if field == 'sc-status': self._elf_status = i elif field == 'cs-method': self._elf_method = i elif field == 'cs-uri': self._elf_uri = i elif field == 'cs-uri-stem': self._elf_urifrag1 = i elif field == 'cs-uri-query': self._elf_urifrag2 = i output.Log('Recognized an Extended Log File Format file.', 2) return True #end def RecognizeELFLine def GetELFLine(self, line): """ Fetch the requested URL from an ELF line """ fields = line.split(' ') count = len(fields) # Verify status was Ok if self._elf_status >= 0: if self._elf_status >= count: return None if not fields[self._elf_status].strip() == '200': return None # Verify method was HEAD or GET if self._elf_method >= 0: if self._elf_method >= count: return None if not fields[self._elf_method].strip() in ('HEAD', 'GET'): return None # Pull the full URL if we can if self._elf_uri >= 0: if self._elf_uri >= count: return None url = fields[self._elf_uri].strip() if url != '-': return url # Put together a fragmentary URL if self._elf_urifrag1 >= 0: if self._elf_urifrag1 >= count or self._elf_urifrag2 >= count: return None urlfrag1 = fields[self._elf_urifrag1].strip() urlfrag2 = None if self._elf_urifrag2 >= 0: urlfrag2 = fields[self._elf_urifrag2] if urlfrag1 and (urlfrag1 != '-'): if urlfrag2 and (urlfrag2 != '-'): urlfrag1 = urlfrag1 + '?' + urlfrag2 return urlfrag1 return None #end def GetELFLine def RecognizeCLFLine(self, line): """ Try to tokenize a logfile line according to CLF pattern and see if it works. """ match = ACCESSLOG_CLF_PATTERN.match(line) recognize = match and (match.group(1) in ('HEAD', 'GET')) if recognize: output.Log('Recognized a Common Logfile Format file.', 2) return recognize #end def RecognizeCLFLine def GetCLFLine(self, line): """ Fetch the requested URL from a CLF line """ match = ACCESSLOG_CLF_PATTERN.match(line) if match: request = match.group(1) if request in ('HEAD', 'GET'): return match.group(2) return None #end def GetCLFLine def ProduceURLs(self, consumer): """ Produces URLs from our data source, hands them in to the consumer. """ # Open the file (frame, file) = OpenFileForRead(self._path, 'ACCESSLOG') if not file: return # Iterate lines for line in file.readlines(): if self._encoding: line = encoder.WidenText(line, self._encoding) line = line.strip() # If we don't know the format yet, try them both if (not self._is_clf) and (not self._is_elf): self._is_elf = self.RecognizeELFLine(line) self._is_clf = self.RecognizeCLFLine(line) # Digest the line match = None if self._is_elf: match = self.GetELFLine(line) elif self._is_clf: match = self.GetCLFLine(line) if not match: continue # Pass it on url = URL() url.TrySetAttribute('loc', match) consumer(url, True) file.close() if frame: frame.close() #end def ProduceURLs #end class InputAccessLog class FilePathGenerator: """ This class generates filenames in a series, upon request. You can request any iteration number at any time, you don't have to go in order. Example of iterations for '/path/foo.xml.gz': 0 --> /path/foo.xml.gz 1 --> /path/foo1.xml.gz 2 --> /path/foo2.xml.gz _index.xml --> /path/foo_index.xml """ def __init__(self): self.is_gzip = False # Is this a GZIP file? self._path = None # '/path/' self._prefix = None # 'foo' self._suffix = None # '.xml.gz' #end def __init__ def Preload(self, path): """ Splits up a path into forms ready for recombination. """ path = encoder.MaybeNarrowPath(path) # Get down to a base name path = os.path.normpath(path) base = os.path.basename(path).lower() if not base: output.Error('Couldn\'t parse the file path: %s' % path) return False lenbase = len(base) # Recognize extension lensuffix = 0 compare_suffix = ['.xml', '.xml.gz', '.gz'] for suffix in compare_suffix: if base.endswith(suffix): lensuffix = len(suffix) break if not lensuffix: output.Error('The path "%s" doesn\'t end in a supported file ' 'extension.' % path) return False self.is_gzip = suffix.endswith('.gz') # Split the original path lenpath = len(path) self._path = path[:lenpath-lenbase] self._prefix = path[lenpath-lenbase:lenpath-lensuffix] self._suffix = path[lenpath-lensuffix:] return True #end def Preload def GeneratePath(self, instance): """ Generates the iterations, as described above. """ prefix = self._path + self._prefix if type(instance) == types.IntType: if instance: return '%s%d%s' % (prefix, instance, self._suffix) return prefix + self._suffix return prefix + instance #end def GeneratePath def GenerateURL(self, instance, root_url): """ Generates iterations, but as a URL instead of a path. """ prefix = root_url + self._prefix retval = None if type(instance) == types.IntType: if instance: retval = '%s%d%s' % (prefix, instance, self._suffix) else: retval = prefix + self._suffix else: retval = prefix + instance return URL.Canonicalize(retval) #end def GenerateURL def GenerateWildURL(self, root_url): """ Generates a wildcard that should match all our iterations """ prefix = URL.Canonicalize(root_url + self._prefix) temp = URL.Canonicalize(prefix + self._suffix) suffix = temp[len(prefix):] return prefix + '*' + suffix #end def GenerateURL #end class FilePathGenerator class PerURLStatistics: """ Keep track of some simple per-URL statistics, like file extension. """ def __init__(self): self._extensions = {} # Count of extension instances #end def __init__ def Consume(self, url): """ Log some stats for the URL. At the moment, that means extension. """ if url and url.loc: (scheme, netloc, path, query, frag) = urlparse.urlsplit(url.loc) if not path: return # Recognize directories if path.endswith('/'): if self._extensions.has_key('/'): self._extensions['/'] = self._extensions['/'] + 1 else: self._extensions['/'] = 1 return # Strip to a filename i = path.rfind('/') if i >= 0: assert i < len(path) path = path[i:] # Find extension i = path.rfind('.') if i > 0: assert i < len(path) ext = path[i:].lower() if self._extensions.has_key(ext): self._extensions[ext] = self._extensions[ext] + 1 else: self._extensions[ext] = 1 else: if self._extensions.has_key('(no extension)'): self._extensions['(no extension)'] = self._extensions[ '(no extension)'] + 1 else: self._extensions['(no extension)'] = 1 #end def Consume def Log(self): """ Dump out stats to the output. """ if len(self._extensions): output.Log('Count of file extensions on URLs:', 1) set = self._extensions.keys() set.sort() for ext in set: output.Log(' %7d %s' % (self._extensions[ext], ext), 1) #end def Log class Sitemap(xml.sax.handler.ContentHandler): """ This is the big workhorse class that processes your inputs and spits out sitemap files. It is built as a SAX handler for set up purposes. That is, it processes an XML stream to bring itself up. """ def __init__(self, suppress_notify): xml.sax.handler.ContentHandler.__init__(self) self._filters = [] # Filter objects self._inputs = [] # Input objects self._urls = {} # Maps URLs to count of dups self._set = [] # Current set of URLs self._filegen = None # Path generator for output files self._wildurl1 = None # Sitemap URLs to filter out self._wildurl2 = None # Sitemap URLs to filter out self._sitemaps = 0 # Number of output files # We init _dup_max to 2 so the default priority is 0.5 instead of 1.0 self._dup_max = 2 # Max number of duplicate URLs self._stat = PerURLStatistics() # Some simple stats self._in_site = False # SAX: are we in a Site node? self._in_Site_ever = False # SAX: were we ever in a Site? self._default_enc = None # Best encoding to try on URLs self._base_url = None # Prefix to all valid URLs self._store_into = None # Output filepath self._sitemap_type = None # Sitemap type (web, mobile or news) self._suppress = suppress_notify # Suppress notify of servers #end def __init__ def ValidateBasicConfig(self): """ Verifies (and cleans up) the basic user-configurable options. """ all_good = True if self._default_enc: encoder.SetUserEncoding(self._default_enc) # Canonicalize the base_url if all_good and not self._base_url: output.Error('A site needs a "base_url" attribute.') all_good = False if all_good and not URL.IsAbsolute(self._base_url): output.Error('The "base_url" must be absolute, not relative: %s' % self._base_url) all_good = False if all_good: self._base_url = URL.Canonicalize(self._base_url) if not self._base_url.endswith('/'): self._base_url = self._base_url + '/' output.Log('BaseURL is set to: %s' % self._base_url, 2) # Load store_into into a generator if all_good: if self._store_into: self._filegen = FilePathGenerator() if not self._filegen.Preload(self._store_into): all_good = False else: output.Error('A site needs a "store_into" attribute.') all_good = False # Ask the generator for patterns on what its output will look like if all_good: self._wildurl1 = self._filegen.GenerateWildURL(self._base_url) self._wildurl2 = self._filegen.GenerateURL(SITEINDEX_SUFFIX, self._base_url) # Unify various forms of False if all_good: if self._suppress: if (type(self._suppress) == types.StringType) or (type(self._suppress) == types.UnicodeType): if (self._suppress == '0') or (self._suppress.lower() == 'false'): self._suppress = False # Clean up the sitemap_type if all_good: match = False # If sitemap_type is not specified, default to web sitemap if not self._sitemap_type: self._sitemap_type = 'web' else: self._sitemap_type = self._sitemap_type.lower() for pattern in SITEMAP_TYPES: if self._sitemap_type == pattern: match = True break if not match: output.Error('The "sitemap_type" value must be "web", "mobile" ' 'or "news": %s' % self._sitemap_type) all_good = False output.Log('The Sitemap type is %s Sitemap.' % \ self._sitemap_type.upper(), 0) # Done if not all_good: output.Log('See "example_config.xml" for more information.', 0) return all_good #end def ValidateBasicConfig def Generate(self): """ Run over all the Inputs and ask them to Produce """ # Run the inputs for input in self._inputs: input.ProduceURLs(self.ConsumeURL) # Do last flushes if len(self._set): self.FlushSet() if not self._sitemaps: output.Warn('No URLs were recorded, writing an empty sitemap.') self.FlushSet() # Write an index as needed if self._sitemaps > 1: self.WriteIndex() # Notify self.NotifySearch() # Dump stats self._stat.Log() #end def Generate def ConsumeURL(self, url, allow_fragment): """ All per-URL processing comes together here, regardless of Input. Here we run filters, remove duplicates, spill to disk as needed, etc. """ if not url: return # Validate if not url.Validate(self._base_url, allow_fragment): return # Run filters accept = None for filter in self._filters: accept = filter.Apply(url) if accept != None: break if not (accept or (accept == None)): url.Log(prefix='FILTERED', level=2) return # Ignore our out output URLs if fnmatch.fnmatchcase(url.loc, self._wildurl1) or fnmatch.fnmatchcase( url.loc, self._wildurl2): url.Log(prefix='IGNORED (output file)', level=2) return # Note the sighting hash = url.MakeHash() if self._urls.has_key(hash): dup = self._urls[hash] if dup > 0: dup = dup + 1 self._urls[hash] = dup if self._dup_max < dup: self._dup_max = dup url.Log(prefix='DUPLICATE') return # Acceptance -- add to set self._urls[hash] = 1 self._set.append(url) self._stat.Consume(url) url.Log() # Flush the set if needed if len(self._set) >= MAXURLS_PER_SITEMAP: self.FlushSet() #end def ConsumeURL def FlushSet(self): """ Flush the current set of URLs to the output. This is a little slow because we like to sort them all and normalize the priorities before dumping. """ # Determine what Sitemap header to use (News or General) if self._sitemap_type == 'news': sitemap_header = NEWS_SITEMAP_HEADER else: sitemap_header = GENERAL_SITEMAP_HEADER # Sort and normalize output.Log('Sorting and normalizing collected URLs.', 1) self._set.sort() for url in self._set: hash = url.MakeHash() dup = self._urls[hash] if dup > 0: self._urls[hash] = -1 if not url.priority: url.priority = '%.4f' % (float(dup) / float(self._dup_max)) # Get the filename we're going to write to filename = self._filegen.GeneratePath(self._sitemaps) if not filename: output.Fatal('Unexpected: Couldn\'t generate output filename.') self._sitemaps = self._sitemaps + 1 output.Log('Writing Sitemap file "%s" with %d URLs' % (filename, len(self._set)), 1) # Write to it frame = None file = None try: if self._filegen.is_gzip: basename = os.path.basename(filename); frame = open(filename, 'wb') file = gzip.GzipFile(fileobj=frame, filename=basename, mode='wt') else: file = open(filename, 'wt') file.write(sitemap_header) for url in self._set: url.WriteXML(file) file.write(SITEMAP_FOOTER) file.close() if frame: frame.close() frame = None file = None except IOError: output.Fatal('Couldn\'t write out to file: %s' % filename) os.chmod(filename, 0644) # Flush self._set = [] #end def FlushSet def WriteIndex(self): """ Write the master index of all Sitemap files """ # Make a filename filename = self._filegen.GeneratePath(SITEINDEX_SUFFIX) if not filename: output.Fatal('Unexpected: Couldn\'t generate output index filename.') output.Log('Writing index file "%s" with %d Sitemaps' % (filename, self._sitemaps), 1) # Determine what Sitemap index header to use (News or General) if self._sitemap_type == 'news': sitemap_index_header = NEWS_SITEMAP_HEADER else: sitemap__index_header = GENERAL_SITEMAP_HEADER # Make a lastmod time lastmod = TimestampISO8601(time.time()) # Write to it try: fd = open(filename, 'wt') fd.write(sitemap_index_header) for mapnumber in range(0,self._sitemaps): # Write the entry mapurl = self._filegen.GenerateURL(mapnumber, self._base_url) mapattributes = { 'loc' : mapurl, 'lastmod' : lastmod } fd.write(SITEINDEX_ENTRY % mapattributes) fd.write(SITEINDEX_FOOTER) fd.close() fd = None except IOError: output.Fatal('Couldn\'t write out to file: %s' % filename) os.chmod(filename, 0644) #end def WriteIndex def NotifySearch(self): """ Send notification of the new Sitemap(s) to the search engines. """ if self._suppress: output.Log('Search engine notification is suppressed.', 1) return output.Log('Notifying search engines.', 1) # Override the urllib's opener class with one that doesn't ignore 404s class ExceptionURLopener(urllib.FancyURLopener): def http_error_default(self, url, fp, errcode, errmsg, headers): output.Log('HTTP error %d: %s' % (errcode, errmsg), 2) raise IOError #end def http_error_default #end class ExceptionURLOpener old_opener = urllib._urlopener urllib._urlopener = ExceptionURLopener() # Build the URL we want to send in if self._sitemaps > 1: url = self._filegen.GenerateURL(SITEINDEX_SUFFIX, self._base_url) else: url = self._filegen.GenerateURL(0, self._base_url) # Test if we can hit it ourselves try: u = urllib.urlopen(url) u.close() except IOError: output.Error('When attempting to access our generated Sitemap at the ' 'following URL:\n %s\n we failed to read it. Please ' 'verify the store_into path you specified in\n' ' your configuration file is web-accessable. Consult ' 'the FAQ for more\n information.' % url) output.Warn('Proceeding to notify with an unverifyable URL.') # Cycle through notifications # To understand this, see the comment near the NOTIFICATION_SITES comment for ping in NOTIFICATION_SITES: query_map = ping[3] query_attr = ping[5] query_map[query_attr] = url query = urllib.urlencode(query_map) notify = urlparse.urlunsplit((ping[0], ping[1], ping[2], query, ping[4])) # Send the notification output.Log('Notifying: %s' % ping[1], 0) output.Log('Notification URL: %s' % notify, 2) try: u = urllib.urlopen(notify) u.read() u.close() except IOError: output.Warn('Cannot contact: %s' % ping[1]) if old_opener: urllib._urlopener = old_opener #end def NotifySearch def startElement(self, tag, attributes): """ SAX processing, called per node in the config stream. """ if tag == 'site': if self._in_site: output.Error('Can not nest Site entries in the configuration.') else: self._in_site = True if not ValidateAttributes('SITE', attributes, ('verbose', 'default_encoding', 'base_url', 'store_into', 'suppress_search_engine_notify', 'sitemap_type')): return verbose = attributes.get('verbose', 0) if verbose: output.SetVerbose(verbose) self._default_enc = attributes.get('default_encoding') self._base_url = attributes.get('base_url') self._store_into = attributes.get('store_into') self._sitemap_type= attributes.get('sitemap_type') if not self._suppress: self._suppress = attributes.get('suppress_search_engine_notify', False) self.ValidateBasicConfig() elif tag == 'filter': self._filters.append(Filter(attributes)) elif tag == 'url': print type(attributes) self._inputs.append(InputURL(attributes)) elif tag == 'urllist': for attributeset in ExpandPathAttribute(attributes, 'path'): if self._sitemap_type == 'news': self._inputs.append(InputNewsURLList(attributeset)) else: self._inputs.append(InputURLList(attributeset)) elif tag == 'directory': self._inputs.append(InputDirectory(attributes, self._base_url)) elif tag == 'accesslog': for attributeset in ExpandPathAttribute(attributes, 'path'): self._inputs.append(InputAccessLog(attributeset)) else: output.Error('Unrecognized tag in the configuration: %s' % tag) #end def startElement def endElement(self, tag): """ SAX processing, called per node in the config stream. """ if tag == 'site': assert self._in_site self._in_site = False self._in_site_ever = True #end def endElement def endDocument(self): """ End of SAX, verify we can proceed. """ if not self._in_site_ever: output.Error('The configuration must specify a "site" element.') else: if not self._inputs: output.Warn('There were no inputs to generate a sitemap from.') #end def endDocument #end class Sitemap def ValidateAttributes(tag, attributes, goodattributes): """ Makes sure 'attributes' does not contain any attribute not listed in 'goodattributes' """ all_good = True for attr in attributes.keys(): if not attr in goodattributes: output.Error('Unknown %s attribute: %s' % (tag, attr)) all_good = False return all_good #end def ValidateAttributes def ExpandPathAttribute(src, attrib): """ Given a dictionary of attributes, return a list of dictionaries with all the same attributes except for the one named attrib. That one, we treat as a file path and expand into all its possible variations. """ # Do the path expansion. On any error, just return the source dictionary. path = src.get(attrib) if not path: return [src] path = encoder.MaybeNarrowPath(path); pathlist = glob.glob(path) if not pathlist: return [src] # If this isn't actually a dictionary, make it one if type(src) != types.DictionaryType: tmp = {} for key in src.keys(): tmp[key] = src[key] src = tmp # Create N new dictionaries retval = [] for path in pathlist: dst = src.copy() dst[attrib] = path retval.append(dst) return retval #end def ExpandPathAttribute def OpenFileForRead(path, logtext): """ Opens a text file, be it GZip or plain """ frame = None file = None if not path: return (frame, file) try: if path.endswith('.gz'): frame = open(path, 'rb') file = gzip.GzipFile(fileobj=frame, mode='rt') else: file = open(path, 'rt') if logtext: output.Log('Opened %s file: %s' % (logtext, path), 1) else: output.Log('Opened file: %s' % path, 1) except IOError: output.Error('Can not open file: %s' % path) return (frame, file) #end def OpenFileForRead def TimestampISO8601(t): """Seconds since epoch (1970-01-01) --> ISO 8601 time string.""" return time.strftime('%Y-%m-%dT%H:%M:%SZ', time.gmtime(t)) #end def TimestampISO8601 def CreateSitemapFromFile(configpath, suppress_notify): """ Sets up a new Sitemap object from the specified configuration file. """ # Remember error count on the way in num_errors = output.num_errors # Rev up SAX to parse the config sitemap = Sitemap(suppress_notify) try: output.Log('Reading configuration file: %s' % configpath, 0) xml.sax.parse(configpath, sitemap) except IOError: output.Error('Cannot read configuration file: %s' % configpath) except xml.sax._exceptions.SAXParseException, e: output.Error('XML error in the config file (line %d, column %d): %s' % (e._linenum, e._colnum, e.getMessage())) except xml.sax._exceptions.SAXReaderNotAvailable: output.Error('Some installs of Python 2.2 did not include complete support' ' for XML.\n Please try upgrading your version of Python' ' and re-running the script.') # If we added any errors, return no sitemap if num_errors == output.num_errors: return sitemap return None #end def CreateSitemapFromFile def ProcessCommandFlags(args): """ Parse command line flags per specified usage, pick off key, value pairs All flags of type "--key=value" will be processed as __flags[key] = value, "--option" will be processed as __flags[option] = option """ flags = {} rkeyval = '--(?P\S*)[=](?P\S*)' # --key=val roption = '--(?P
(igraph_)|(IGRAPH_)|())(?P\w+)) # the keyword, remove igraph_ prefix
[\s]*(?P[^\n]*?)\n        # brief description
(?P.*?)\*\/               # tail of the comment
\s*
(?P.*?\))                   # function head
(?=(\s*;)|(\s*\{))               # prototype ends with ; function head with {
.*\Z                             # and the remainder

WITH --------------------------------------------------------------------------



<function>\g<name></function> — \g<brief>
\g


\g;



\g
\g




REPLACE -----  for functions (not used currently) -------------------

(?P[^<]*)\n

RUN ---------------------------------------------------------------------------

if matched != None:
    dr_params=string.split(matched.group("params"), ',')
    dr_out=""
    for dr_i in dr_params:
        dr_i=string.strip(dr_i)
        if dr_i=="...":
            dr_out=dr_out+""
        else:
            dr_words=re.match(r"([\w\*\&\s]+)(\b\w+)$", dr_i).groups()
            dr_out=dr_out+""+dr_words[0]+""+dr_words[1]+ \
                    "\n"
    actch=actch[0:matched.start()]+dr_out+actch[matched.end():]

REPLACE ----- function parameter descriptions, head ---------------------------

(?P\A.*?)               # head of the comment
\\param\b                       # first \param commant

WITH --------------------------------------------------------------------------

\g
Arguments:

\param

REPLACE ----- function parameter descriptions, tail ---------------------------

# the end of the params is either an empty line after the last \param
# command or a \return or \sa statement (others might be added later)
# or the end of the comment

\\param\b                         # the last \param command
(?P.*?)                # the text of the \param command
(?P                      # this marks the end of the \param text
 (\\return\b)|(\\sa\b)|           # it is either a \return or \sa or
 (\n\s*?\n)|                      # (at least) one empty line or
 (\*\/))                          # the end of the comment
(?P.*?\Z)                  # remaining part

WITH

\param\g
\g\g

REPLACE ----- function parameter descriptions ---------------------------------

\\param\b\s*                      # \param command
(?P(\w+)|(...))\s+     # name of the parameter
(?P.*?)                # text of the \param command
(?=(\\param)|()|
 (\n\s*\n))


WITH --------------------------------------------------------------------------

  \g:
  
  \g  

REPLACE ----- \return command -------------------------------------------------

# a return statement ends with an empty line or the end of the comment
\\return\b\s*                     # \return command
(?P.*?)                     # the text
(?=(\n\s*?\n)|                    # empty line or 
 (\*\/)|                          # the end of the comment or
 (\\sa\b))                        # \sa command

WITH ----------------------------------------------------------------------TODO

Returns:
  
  
  \g
  


REPLACE ----- variables -------------------------------------------------------

(?P\A.*?)                 # head of the comment
\\var\s+                          # \var keyword + argument
(?P(?P
(igraph_)|(IGRAPH_)|())(?P\w+))
[\s]*(?P[^\n]*?)\n         # brief description
(?P.*?)\*\/                # tail of the comment
\s*(?P[^;]*;)                # the definition of the variable
.*\Z                              # and the remainder

WITH --------------------------------------------------------------------------


<function>\g<name></function> — \g<brief>
\g


\g


\g\g




REPLACE ----- \define ---------------------------------------------------------

(?P\A.*?)                 # head of the comment
\\define\s+                       # \define command
(?P(?P
(igraph_)|(IGRAPH_)|())(?P\w+))
[\s]*(?P[^\n]*?)\n         # brief description
(?P.*?)\*\/                # tail of the comment
\s*                               # whitespace
(?P\#define\s+[\w0-9,()]+)           # macro
.*\Z                              # drop the remainder

WITH --------------------------------------------------------------------------


<function>\g<name></function> — \g<brief>
\g


\g


\g\g




REPLACE ----- \section without title ------------------------------------------

(?P\A.*?)                 # head of the comment
\\section\s+(?P\w+)\s*$     # \section + argument
(?P.*?)\*\/                # tail of the comment
.*\Z                              # and the remainder, this is dropped

WITH

\g
\g

REPLACE ----- \section with title ---------------------------------------------

(?P\A.*?)                 # head of the comment
\\section\s+(?P\w+)         # \section + argument
(?P.*?)                    # section title
\n\s*?\n                          # empty line
(?P<after>.*?)\*\/                # tail of the comment
.*\Z                              # and the remainder, this is dropped

WITH

<title>\g<title>
\g
\g

REPLACE ----- \section with title ---------------------------------------------

(?P\A.*?)                 # head of the comment
\\section\s+(?P\w+)         # \section + argument
(?P.*?)\s*\*\/             # section title
.*\Z                              # and the remainder, this is dropped

WITH

<title>\g<title>
\g

REPLACE ----- an enumeration typedef ------------------------------------------

(?P\A.*?)                 # head of the comment
\\typedef\s+                      # \typedef command
(?P(?P
(igraph_)|(IGRAPH_)|())(?P\w+))
[\s]*(?P[^\n]*?)\n         # brief description
(?P.*?)                    # tail of the comment
 \*\/\s*                          # closing the comment
(?Ptypedef\s*enum\s*\{       # typedef enum
 [^\}]*\}\s*\w+\s*;)                  # rest of the definition
.*\Z

WITH --------------------------------------------------------------------------


<function>\g<name></function> — \g<brief>
\g


\g



\g\g




REPLACE ----- enumeration value descriptions, head ----------------------------

(?P\A.*?)               # head of the comment
\\enumval\b                     # first \param commant

WITH --------------------------------------------------------------------------

\g
Values:

\enumval

REPLACE ----- enumeration value descriptions, tail ----------------------------

\\enumval\b                       # the last \enumval command
(?P.*?)                # the text of the \enumval command
(?P                      # this marks the end of the \enumval text
 (\\return\b)|(\\sa\b)|           # it is either a \return or \sa or
 (\n\s*?\n)|                      # (at least) one empty line or
 (\*\/))                          # the end of the comment
(?P.*?\Z)                  # remaining part

WITH

\enumval\g
\g\g

REPLACE ----- enumeration value descriptions ----------------------------------

\\enumval\b\s*                    # \enumval command
(?P(\w+)|(...))\s+     # name of the parameter
(?P.*?)                # text of the \enumval command
(?=(\\enumval)|()|
 (\n\s*\n))

WITH --------------------------------------------------------------------------

  \g:
  
  \g  

REPLACE ----- \struct ---------------------------------------------------------

(?P\A.*?)                 # head of the comment
\\struct\s+                       # \struct command
(?P(?P
(igraph_)|(IGRAPH_)|())(?P[\w_]+))
[\s]*(?P[^\n]*?)(?=\n)     # brief description
(?P.*?)                    # tail of the command
\*\/\s*                           # closing the comment
(?Ptypedef \s*struct\s*\w+\s*\{
 .*\}\s*\w+\s*;)
.*\Z

WITH --------------------------------------------------------------------------


<function>\g<name></function> — \g<brief>
\g


\g



\g\g




REPLACE ----- structure member descriptions, one block ------------------------

^[\s]*\n
(?P.*?)                # empty line+text
(?P\\member\b.*?)      # member commands
(?=                             # this marks the end of the \member text
 (\\return\b)|(\\sa\b)|         # it is either a \return or \sa or
 (^[\s]*\n)|                    # (at least) one empty line or
 (\*\/))                        # the end of the comment

WITH --------------------------------------------------------------------------


\g
Values:

\g


REPLACE ----- structure member descriptions -----------------------------------

\\member\b\s*                    # \enumval command
(?P(\w+)|(...))\s+     # name of the parameter
(?P.*?)                # text of the \enumval command
(?=(\\member)|()|
 (\n\s*\n))

WITH --------------------------------------------------------------------------

  \g:
  
  \g

REPLACE ----- \typedef function -----------------------------------------------

(?P.*?)                   # comment head
\\typedef\s+                      # \typedef command
(?P(?P
(igraph_)|(IGRAPH_)|())(?P\w+))
[\s]*(?P[^\n]*?)\n         # brief description
(?P.*?)                    # comment tail
\*\/                              # end of comment block
\s*
(?Ptypedef\s+[^;]*;)        # the typedef definition
.*\Z

WITH --------------------------------------------------------------------------


<function>\g<name></function> — \g<brief>
\g

\g


\g\g




REPLACE ----- ignore doxygen \ingroup command ---------------------------------

\\ingroup\s+\w+

WITH --------------------------------------------------------------------------

REPLACE ----- ignore doxygen \defgroup command --------------------------------

\\defgroup\s+\w+

WITH --------------------------------------------------------------------------

REPLACE ----- add the contents of \brief to the description -------------------

\\brief\b

WITH --------------------------------------------------------------------------

REPLACE ----- \varname command ------------------------------------------------

\\varname\b\s*
(?P\w+\b)

WITH

\g

REPLACE ----- references, \ref command ----------------------------------------

\\ref\b\s*
(?P\w+)(?P([\(][\)])?)

WITH --------------------------------------------------------------------------

\g\g

REPLACE ----- \sa command -----------------------------------------------------

\\sa\b
\s*
(?P.*?)
(?=(\n\s*?\n)|(\*\/))

WITH ----------------------------------------------------------------------TODO

See also:
  
  
  \g
  


REPLACE ----- \em command -----------------------------------------------------

\\em\b
\s*
(?P[^\s]+)

WITH

\g

REPLACE ----- \emb command ----------------------------------------------------

\\emb\b

WITH



REPLACE ----- \eme command ----------------------------------------------------

\\eme\b

WITH



REPLACE ----- \verbatim -------------------------------------------------------

\\verbatim\b

WITH



REPLACE ----- \endverbatim ----------------------------------------------------

\\endverbatim\b

WITH



REPLACE ----- \clist ----------------------------------------------------------

\\clist\b

WITH



REPLACE ----- \cli ------------------------------------------------------------

\\cli\s+(?P.*?)$
(?P.*?)
(?=(\\cli)|(\\endclist))

WITH --------------------------------------------------------------------------

\g

\g


REPLACE ----- \endclist -------------------------------------------------------

\\endclist\b

WITH



REPLACE ----- \olist ----------------------------------------------------------

\\olist\b

WITH



REPLACE ----- \oli ------------------------------------------------------------

\\oli\s+(?P.*?)
(?=(\\oli)|(\\endolist))

WITH


\g


REPLACE ----- \endolist -------------------------------------------------------

\\endolist\b

WITH



REPLACE ----- \ilist ----------------------------------------------------------

\\ilist\b

WITH



REPLACE ----- \ili ------------------------------------------------------------

\\ili\s+(?P.*?)
(?=(\\ili)|(\\endilist))

WITH


\g


REPLACE ----- \endilist -------------------------------------------------------

\\endilist\b

WITH



REPLACE ----- doxygen \c command is for  ----------------------------

\\c\s+(?P[\w\-^\']+)\b

WITH

\g

REPLACE ----- doxygen \p command is for  ---------------------------

\\p\s+(?P\w+)\b

WITH

\g

REPLACE ----- doxygen \type command is for  -----------------------------

\\type\s+(?P\w+)\b

WITH

\g

REPLACE ----- doxygen \a command is for  -----------------------------

\\a\s+(?P\w+)\b

WITH

\g

REPLACE ----- doxygen \quote command is for  ---------------------------

\\quote\s+

WITH



REPLACE ----- doxygen \endquote command is for  -----------------------

\s*\\endquote\b

WITH



REPLACE ----- replace  with  -----------------------------------

<(?P/?)code>

WITH --------------------------------------------------------------------------

<\gliteral> 

REPLACE ----- add http:// and https:// links ----------------------------------

(?Phttps?:\/\/.*?)
(?=(\s)|\))

WITH --------------------------------------------------------------------------

\g

REPLACE ----- blockquote ------------------------------------------------------

\\blockquote

WITH --------------------------------------------------------------------------




REPLACE ----- blockquote ------------------------------------------------------

\\endblockquote

WITH --------------------------------------------------------------------------




REPLACE ----- example file  ---------------------------------------------------

\\example\b\s*
(?P[^\n]*?)\n

WITH --------------------------------------------------------------------------


   File <code>\g<filename></code>
  
  

python-igraph-0.8.0/vendor/source/igraph/doc/bipartite.xxml0000644000076500000240000000171413524616144024262 0ustar  tamasstaff00000000000000

]>


Bipartite, i.e. two-mode graphs








Create two-mode networks







Incidence matrices






Project a two-mode graphs






Other operations on bipartite graphs





python-igraph-0.8.0/vendor/source/igraph/doc/nongraph.xxml0000644000076500000240000000214613614300625024105 0ustar  tamasstaff00000000000000

]>


Not Graph Related Functions 


Igraph Version Number





Running Mean of a Time Series





Random Sampling from Very Long Sequences





Random Sampling of Spatial Points







Convex Hull of A Set of Points on A Plane





Fitting Power-law Distributions to Empirical Data






python-igraph-0.8.0/vendor/source/igraph/doc/adjlist.xxml0000644000076500000240000000350513524616144023731 0ustar  tamasstaff00000000000000

]>



Adjacency lists




Adjacent vertices












Incident edges








Lazy adjacency list for vertices








Lazy incidence list for edges








Deprecated functions










python-igraph-0.8.0/vendor/source/igraph/doc/licenses.xml0000644000076500000240000000066613524616144023721 0ustar  tamasstaff00000000000000

]>


Licenses for igraph and this manual

  
  


python-igraph-0.8.0/vendor/source/igraph/doc/isomorphism.xxml0000644000076500000240000000370113524616144024646 0ustar  tamasstaff00000000000000

]>


Graph Isomorphism


The simple interface







The BLISS algorithm











The VF2 algorithm















The LAD algorithm






Functions for graphs with 3 or 4 vertices








Utility functions






python-igraph-0.8.0/vendor/source/igraph/doc/operators.xxml0000644000076500000240000000141213524616144024310 0ustar  tamasstaff00000000000000

]>


Graph Operators


Union and intersection










Other set-like operators







python-igraph-0.8.0/vendor/source/igraph/doc/kkplots-small.png0000644000076500000240000000375513524616144024677 0ustar  tamasstaff00000000000000‰PNG


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#á’ê¦_~Ñí?íphFјw§DYÎC#Àÿ‰*ó;Í .1ùkTËIEND®B`‚python-igraph-0.8.0/vendor/source/igraph/doc/fdl.xml0000644000076500000240000005401113524616144022652 0ustar  tamasstaff00000000000000



  
    Version 1.2, November 2002
    200020012002      
    Free Software Foundation, Inc.
      51 Franklin St, Fifth Floor, Boston, MA  02110-1301  USA
    
    
    
     Everyone is permitted to copy and distribute verbatim copies
     of this license document, but changing it is not allowed.
    
    
  

The GNU Free Documentation License


0. PREAMBLE

The purpose of this License is to make a manual, textbook, or other
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We have designed this License in order to use it for manuals for free
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it can be used for any textual work, regardless of subject matter or
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python-igraph-0.8.0/vendor/source/igraph/doc/arpack.xxml0000644000076500000240000000322413524616144023536 0ustar  tamasstaff00000000000000


]>


Using BLAS, LAPACK and ARPACK for igraph matrices and graphs











  
  
Matrix factorization, solving linear systems
  
  
  
  

  
Eigenvalues and eigenvectors of matrices
  
  
  
  








Data structures










ARPACK solvers










python-igraph-0.8.0/vendor/source/igraph/doc/strvector.xxml0000644000076500000240000000157613524616144024340 0ustar  tamasstaff00000000000000

]>



String vectors


















python-igraph-0.8.0/vendor/source/igraph/doc/generators.xxml0000644000076500000240000000545213614300625024445 0ustar  tamasstaff00000000000000

]>


Graph Generators




Deterministic Graph Generators

























Games: Randomized Graph Generators




































python-igraph-0.8.0/vendor/source/igraph/doc/gtk-doc.xsl0000644000076500000240000003174313610335511023442 0ustar  tamasstaff00000000000000 


  
  
  
  

  
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1.66 1.66

python-igraph-0.8.0/vendor/source/igraph/doc/embedding.xxml0000644000076500000240000000073613614300625024212 0ustar tamasstaff00000000000000 ]> Embedding of graphs
Functions
python-igraph-0.8.0/vendor/source/igraph/doc/structural.xxml0000644000076500000240000001724413614300625024506 0ustar tamasstaff00000000000000 ]> Structural Properties of Graphs
Basic Properties
(Shortest) Path Related Functions
Neighborhood of a Vertex
Local Scan Statistics
"Us" statistics
"Them" statistics
Pre-calculated neighborhoods
Graph Components
Degree Sequences
Centrality Measures
Estimating Centrality Measures
Centralization
Similarity Measures
Spanning Trees
Transitivity or Clustering Coefficient
Directedness Conversion
Spectral Properties
Non-simple Graphs: Multiple and Loop Edges
Mixing Patterns
K-Cores
Topological Sorting, Directed Acyclic Graphs
Maximum Cardinality Search, Graph Decomposition, Chordal Graphs
Matchings
Line Graphs
Unfolding a Graph Into a Tree
Other Operations
python-igraph-0.8.0/vendor/source/igraph/doc/gpl.xml0000644000076500000240000004620013524616144022670 0ustar tamasstaff00000000000000
Version 2, June 1991 19891991 Free Software Foundation, Inc. 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed. THE GNU GENERAL PUBLIC LICENSE
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python-igraph-0.8.0/vendor/source/igraph/doc/sitemap_gen_config.xml0000644000076500000240000000110513524616144025721 0ustar tamasstaff00000000000000 python-igraph-0.8.0/vendor/source/igraph/doc/visitors.xxml0000644000076500000240000000124013524616144024153 0ustar tamasstaff00000000000000 ]> Graph visitors
Breadth-first search
Depth-first search
Random walks
python-igraph-0.8.0/vendor/source/igraph/doc/sparsemat.xxml0000644000076500000240000000700413524616144024274 0ustar tamasstaff00000000000000 ]>
Sparse matrices, another kind
Creating sparse matrix objects
Query properties of a sparse matrix
Operations on sprase matrices
Operations that change the internal representation
Decompositions and solving linear systems
Eigenvalues and eigenvectors
Conversion to other data types
Writing to a file, or to the screen
python-igraph-0.8.0/vendor/source/igraph/doc/error.xxml0000644000076500000240000000417013524616144023427 0ustar tamasstaff00000000000000 ]> Error Handling
Advanced topics
python-igraph-0.8.0/vendor/source/igraph/doc/hrg.xxml0000644000076500000240000000212613524616144023055 0ustar tamasstaff00000000000000 ]> Hierarchical random graphs
Representing HRGs
Fitting HRGs
HRG sampling
Conversion to and from igraph graphs
Predicting missing edges
python-igraph-0.8.0/vendor/source/igraph/doc/motifs.xxml0000644000076500000240000000204113524616144023572 0ustar tamasstaff00000000000000 ]> Graph Motifs, Dyad Census and Triad Census This section deals with functions which find small induced subgraphs in a graph. These were first defined for subgraphs of two and three vertices by Holland and Leinhardt, and named dyad census and triad census.
Finding triangles
Graph motifs
python-igraph-0.8.0/vendor/source/igraph/doc/doxrox.py0000755000076500000240000002033413524616144023264 0ustar tamasstaff00000000000000#! /usr/bin/env python # IGraph R package # Copyright (C) 2005-2012 Gabor Csardi # 334 Harvard street, Cambridge, MA 02139 USA # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA # ################################################################### import sys import getopt import re import string ################# # constants, these might turn to parameters some time ################# doxhead='\/\*\*' ################# # global variables ################# verbose=False cutit=False ######################################################################### # The main function ######################################################################### def main(): global verbose, cutit # get command line arguments try: optlist, args = getopt.getopt(sys.argv[1:], 't:e:o:hvc', ['help']) except getopt.GetoptError: # print help information and exit: usage() sys.exit(2) # handle command line arguments templatefile=regexfile=outputfile="" verbose=False for o, a in optlist: if o in ("-h", "--help"): usage() sys.exit() if o == "-t": templatefile = a if o == "-e": regexfile = a if o == "-o": outputfile = a if o == "-v": verbose = True if o == "-c": cutit = True if templatefile == "" or regexfile == "" or outputfile == "": print("Error, some special file is not given") usage() sys.exit(2) if templatefile in args or regexfile in args or outputfile in args: print("Error, special file is also used as an input file") usage() sys.exit(2) if templatefile == regexfile or templatefile == outputfile or \ regexfile == outputfile: print('Error, some special files are the same') usage() sys.exit(2) # get all regular expressions if verbose: print 'Reading regular expressions...', regexlist=readregex(regexfile) if verbose: print("done, "+str(len(regexlist))+" rules read.") # parse all input files and extract chunks, apply rules docchunks=dict() for ifile in args: if verbose: print 'Parsing input file '+ifile+'...', try: f=open(ifile, 'r') strinput=f.read() f.close() except IOError: print("Error reading input file: "+ifile) sys.exit(3) parsestring(strinput, regexlist, docchunks) if verbose: print('done, '+str(len(docchunks))+" chunks read.") # substitute the template file try: if verbose: print "Reading template file...", tfile=open(templatefile, 'r') tstring=tfile.read() tfile.close() if verbose: print('done.') except IOError: print("Error reading the template file: "+templatefile) sys.exit(7) if verbose: print "Substituting template file...", chunkit=re.finditer(r'', tstring) outstring="" last=0 for chunk in chunkit: outstring=outstring+tstring[last:chunk.start()]+\ docchunks[chunk.group(1)] last=chunk.end() outstring=outstring+tstring[last:] if verbose: print "done." # write output file try: if verbose: print "Writing output file...", ofile=open(outputfile, 'w') ofile.write(outstring) ofile.close() except IOError: print("Error writing output file:"+outputfile) sysexit(8) if verbose: print "done." ######################################################################### # End of the main function ######################################################################### ################# # read the regular expressions ################# def readregex(regexfile): lines=[] mode="empty" actreplace="" actwith="" acttype="" lineno=1 try: f=open(regexfile, "r") for line in f: # a new pattern block starts if line[0:7]=="REPLACE": if mode not in ("empty","with"): print("Parse error in regex file ("+regexfile+"), line "+ str(lineno)) sys.exit(4) else: if (actreplace != ""): readregexappend(lines, actreplace, actwith, acttype) actreplace=actwith="" mode="replace" # the second half of the pattern block starts elif line[0:4]=="WITH" or line[0:3]=="RUN": if mode != "replace": print("Parse error in regex file ("+regexfile+"), line "+ str(lineno)) sys.exit(4) else: mode="with" if line[0:4]=="WITH": acttype="with" else: acttype="run" # empty line, do nothing elif re.match("^\s*$", line): 1==1 # normal line, append else: if mode=="replace": actreplace=actreplace+line elif mode=="with": actwith=actwith+line else: print("Parse error in regex file ("+regexfile+"), line "+ str(lineno)) sys.exit(4) lineno=lineno+1 if actreplace != "": readregexappend(lines, actreplace, actwith, acttype) f.close() except IOError: print("Error reading regex file: "+regexfile) sys.exit(4) return (lines) def readregexappend(lines, actreplace, actwith, acttype): compactreplace=re.compile(actreplace,re.VERBOSE|re.MULTILINE|re.DOTALL) actwith=actwith[:(len(actwith)-1)] lines.append( (compactreplace, actwith, acttype) ) ################# # parse an input file string ################# def parsestring(strinput, regexlist, docchunks): global cutit # split the file chunks=re.split(doxhead, strinput) chunks=chunks[1:] # apply all rules to the chunks for ch in chunks: if cutit: ch=ch.split("/*")[0] actch=ch name="" for reg in regexlist: matched=reg[0].match(actch) if name=="" and matched != None: try: name=matched.group('name') except IndexError: name="" if reg[2]=="with": try: actch=reg[0].sub(reg[1], actch) except IndexError: print("Index error:"+ch[0:60]+"...") print("Pattern:\n"+reg[0].pattern) print("Current state:"+actch[0:60]+"...") sys.exit(6) elif reg[2]=="run": exec(reg[1]) if name=="": print("Chunk without a name ignored:"+ch[0:60]+"...") continue if docchunks.has_key(name): print("Multiple defined name: "+name) sys.exit(6) if verbose: print name, docchunks[name]=string.strip(actch) return(docchunks) ################# # print out some help ################# def usage(): print("Usage: " + sys.argv[0] + " [-vh] -t template-file -e regex-file -o output-file\n"+ " [--help] [inputfile]...") if __name__ == "__main__": main() python-igraph-0.8.0/vendor/source/igraph/doc/frplots-small.png0000644000076500000240000000373513524616144024677 0ustar tamasstaff00000000000000‰PNG  IHDR¤¤dÛmÒ PLTEÿÿÿÿgd pHYs  šœtIMEÖ,Š™@¼gIDATXÃÕYÍŠGî!$s2:,aOF$ ê)ŸŒNÆ'££OažB+´BîSX|5;¦ÔO™ªêê¿éYBÛH­™êêªêª¯~lü_ýc¾‘rS< ëcñä.Sâ¶xÖçÅô‰Pº}~lmøò~ç1<ÈìÅ9 òá,×Ö»–ÒÉ¿x¢#Zà•™\<”0nSÙyÉ”àt;ë$E^ +yëýË–z ñçî™)³âàã/GEsY¿àW“Í7…ÚĘ%zìâmº(õµ/èØŒ¼|Aù:J9×>©%ÆgµŽ ¢ðé£W%»Zbׄˆ"6zsQåÌmy4-­uɦ–èM´9ñ ·Æ˜¬žLM”NmÍdŒ´(‚FØj?@:Û”é ›w&ó!ðN£$˜¾Ã¦=›^Y Î{bt5L¬—?²J¸˜ðÖA’ˆâÂ5ÑsP؃‰àÄ+ü}Š-SÚâj¢RÈð+/¾CŸë ;蕇-˜¬=Ü@¼kܘHáòÑcbOîåȘrkÄOj¥ â{ú&9„¯¹Á¿POÆ ZH º½í”Ñ8,¬Þñ1Êe²çNâý1‚OÔèp · Œ£ä Î*.­²X¨³G_xdºwœ@Ç@–ÞªF6“X[]j2³úÒ+c⽜lÎ#ÏçÝ ì?þÜñoRªØׯÊtæ/ByÞE·­þ”錬Ȕê²õ¢IRa¯#øûʅ½¯Oåt©ëE}é eˆŽ^{h¹T¿B¯Ð᜻·<Ón÷uJJ<+ ß ZçSB›@vF݉î!χ“KA/}Uæ‰ V®ô2µç¸ÊàJƒ_=}çŠNg‹Ú/(”ë=îÝ"†\¡­«ÑŒ3—°3çBл¼"g¢t’$̲ôC—rœ,¾£”ãÀ]ï|×U—=–×ÆÀŒŠö ©f±ÅÞ‡\#ÔÌÚ¹«?«bV)9× -4=â=åß7¡~L&¯Gh¼’^\!Æ““:Ä®ý§Àåj”,3ñmªÂÜu±5¡€rÖ·:½÷Åk“® Ÿ»†R¸"¸© ÛÉož ®­[Ÿ§r ì©{IP¨°Î€ƒ—¡Àëwè‡ÍL*˜R"îœ/xº’5º?a_‰eÉ °­0ƒÉ8¸i!2ƒcÂó©Þ=Z(kÊçõ¯ðßÉGßDym2WížÇH‰\–Õ™ë}Ey+”Gî`êo°ôu#fŠBÊ«ÂÏ“ö§êP¤Ì©q){‰©\-¿Ý´ ­­t°óF)‹ªk=“gP‰Ëzž» Ìe]q“Xü¤oà‘ÞL½6ÙAÏim $ø"%dÄÇ^¬æZAÉ(‘»:—zJÒÖ”)(4-jUz}ê_ô:¿ûØÃ\ßÎR>*WHýì.öŸE°²t\–`÷®ãÊ? \u:IvW\ؾÓÈt)ofJÔÞÍà¨iÚ÷½hz~—.ÔŒÓöy)Øpßcný¥äŽiØ\iÞôÐœ¾ÎMkN`8s›>µyÛОTz•·IvÓËþ.và`Êx“ºŠ­×Æ?ñ3±Ûh "¿ÛššèçbÛB±tg"O˜ÂqI‡ÔÛšÚð³u¯ýr¥ªí²y9¥ºó¬‡àL>W‡™U|SÓ•çKTøwÏ å¥‡J~¦|Õ5ÇUIkLr~®z«L e&û¿e®çÔZùfe {¡|ôÃ"~:MucqUöjÍG˜cNÍ8$bu ™ë”/¼ÆŽûªÖ1:ë„Ã6sJmÅÊ¥N_›‰M9›ˆ  ñx…–ÊɨČ·D³Ž*Ÿ[ÞhNÖaZLï°q1šÖ]1 ⣮}αԇlbepíE*sMU·¼!{ðù'Òç8ÎH+r@› äúÌ肤p@Lù}Ÿ -L&B¯u) ­ïå–$6O!gÅ Ok]tÀlð²æô°uÀb+<×iºhwé‰PüÁRg&‡_4e‚b/×z­µ.rGáâSl;º4û!t:ŸgU¨U¬_yFÒÙu†ÏSèøøê^/Î2­L‡øÿ÷”|Af€”ñ1ïÓ¬pëSvb1aŒŠ5V‡€Æÿ¤dýòΛ>æ£bFlƒ¬t¤¨Š›Ã‚`-U€07þ órŽÓÆÈvœçO©«îC¥jºLgÀŽVjž:WðaB ¡ÑXj6$ç37 ,ç]w;Í[øf4¡*›IÛñÊ2°Å>ôïónIEND®B`‚python-igraph-0.8.0/vendor/source/igraph/doc/stack.xxml0000644000076500000240000000117513524616144023405 0ustar tamasstaff00000000000000 ]>
Stacks
python-igraph-0.8.0/vendor/source/igraph/doc/introduction.xml0000644000076500000240000001061113614300625024616 0ustar tamasstaff00000000000000 ]> Introduction igraph is a library for creating and manipulating graphs. You can look at it in two ways: first, igraph contains the implementation of quite a lot of graph algorithms. These include classic graph algorithms like graph isomorphism, graph girth and connectivity and also the new wave graph algorithms like transitivity, graph motifs and community structure detection. Skim through the table of contents or the index of this book to get an impression of what is available. Second, igraph provides a platform for developing and/or implementing graph algorithms. It has an efficient data structure for representing graphs, and a number of other data structures like flexible vectors, stacks, heaps, queues, adjacency lists that are useful for implementing graph algorthms. In fact these data structures evolved along with the implementation of the classic and non-classic graph algorithms which make up the major part of the igraph library. This way, they were fine-tuned and checked for correctness several times. Our main goal with developing igraph was to create a graph library which is efficient on large, but not extremely large graphs. More precisely, it is assumed that the graph(s) fit into the physical memory of the computer. Nowadays this means graphs with several million vertices and/or edges. Our definition of efficient is that it runs fast, both in theory and (more importantly) in practice. We believe that one of the big strengths of igraph is that it can be embedded into a higher-level language or environment. Three such embeddings (or interfaces if you look at them another way) are currently being developed by us: an R package, a Python extension module, and a Mathematica (Wolfram Language) package. Others are likely to come. High level languages such as R or Python make it possible to use graph routines with much greater comfort, without actually writing a single line of C code. They have some, usually very small, speed penalty compared to the C version, but add ease of use and much flexibility. This manual, however, covers only the C library. If you want to use Python, R or the Wolfram Language, please see the documentation written specifically for these interfaces and come back here only if you are interested in some detail which is not covered in those documents. We still consider igraph as a child project. It has much room for development and we are sure that it will improve a lot in the near future. Any feedback we can get from the users is very important for us, as most of the time these questions and comments guide us in what to add and what to improve. igraph is open source and distributed under the terms of the GNU GPL. We strongly believe that all the algorithms used in science, let that be graph theory or not, should have an efficient open-source implementation allowing use and modification for anyone.
&igraph; is free software igraph library Copyright (C) 2003-2012 Gábor Csardi <csardi.gabor@gmail.com> 334 Harvard st, Cambridge MA, 02139, USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
Citing &igraph; To cite &igraph; in publications, please use the following reference: Gábor Csárdi, Tamás Nepusz: The igraph software package for complex network research. InterJournal Complex Systems, 1695, 2006.
python-igraph-0.8.0/vendor/source/igraph/doc/graphlets.xxml0000644000076500000240000000103113524616144024260 0ustar tamasstaff00000000000000 ]> Graphlets
Performing graphlet decomposition
python-igraph-0.8.0/vendor/source/igraph/doc/devhelp.xsl0000644000076500000240000001126513524616144023546 0ustar tamasstaff00000000000000 book .devhelp , python-igraph-0.8.0/vendor/source/igraph/doc/foreign.xxml0000644000076500000240000000300113524616144023717 0ustar tamasstaff00000000000000 ]> Reading and Writing Graphs from and to Files
Simple edge list and similar formats
Binary formats
GraphML format
GML format
Pajek format
UCINET's DL file format
Graphviz format
python-igraph-0.8.0/vendor/source/igraph/doc/coloring.xxml0000644000076500000240000000055513524616144024115 0ustar tamasstaff00000000000000 ]> Graph Coloring python-igraph-0.8.0/vendor/source/igraph/.git0000644000076500000240000000006313524616144021400 0ustar tamasstaff00000000000000gitdir: ../../../.git/modules/vendor/source/igraph python-igraph-0.8.0/vendor/source/igraph/.travis.yml0000644000076500000240000000154213614300630022716 0ustar tamasstaff00000000000000 language: c addons: apt: packages: - gfortran - flex - bison - docbook2x - xmlto - texinfo - source-highlight - libxml2-utils - xsltproc - fop homebrew: packages: - flex - bison script: - make check after_failure: - find tests/testsuite.dir -name testsuite.log -exec cat \{\} \; jobs: include: - stage: test os: linux install: - ./bootstrap.sh - ./configure - make - stage: test os: osx install: - ./bootstrap.sh - ./configure - make - stage: documentation language: shell os: linux install: - ./bootstrap.sh - ./configure - cd doc script: - make html - make pdf notifications: email: on_success: change on_failure: always sudo: false python-igraph-0.8.0/vendor/source/igraph/.zenodo.json0000644000076500000240000000033513614300625023057 0ustar tamasstaff00000000000000{ "title": "igraph", "upload_type": "software", "keywords": [ "graph theory", "network analysis" ], "creators": [ { "name": "The igraph Core Team" } ] } python-igraph-0.8.0/vendor/source/igraph/ONEWS0000644000076500000240000017272113614300625021437 0ustar tamasstaff00000000000000 igraph 0.6.5 ============ Released February 24, 2013 The version number is not a mistake, we jump to 0.6.5 from 0.6, for technical reasons. R: new features and bug fixes ----------------------------- - Added a vertex shape API for defining new vertex shapes, and also a couple of new vertex shapes. - Added the get.data.frame() function, opposite of graph.data.frame(). - Added bipartite support to the Pajek reader and writer, closes bug \#1042298. - `degree.sequence.game()` has a new method now: "simple_no_multiple". - Added the is.degree.sequence() and is.graphical.degree.sequence() functions. - rewire() has a new method: "loops", that can create loop edges. - Walktrap community detection now handles isolates. - layout.mds() returns a layout matrix now. - layout.mds() uses LAPACK instead of ARPACK. - Handle the '~' character in write.graph and read.graph. Bug \#1066986. - Added k.regular.game(). - Use vertex names to plot if no labels are specified in the function call or as vetex attributes. Fixes issue \#1085431. - power.law.fit() can now use a C implementation. - Fixed a bug in barabasi.game() when out.seq was an empty vector. - Fixed a bug that made functions with a progress bar fail if called from another package. - Fixed a bug when creating graphs from a weighted integer adjacency matrix via graph.adjacency(). Bug \#1019624. - Fixed overflow issues in centralization calculations. - Fixed a minimal.st.separators() bug, some vertex sets were incorrectly reported as separators. Bug \#1033045. - Fixed a bug that mishandled vertex colors in VF2 isomorphism functions. Bug \#1032819. - Pajek exporter now always quotes strings, thanks to Elena Tea Russo. - Fixed a bug with handling small edge weights in shortest paths calculation in shortest.paths() (Dijkstra's algorithm.) Thanks to Martin J Reed. - Weighted transitivity uses V(graph) as 'vids' if it is NULL. - Fixed a bug when 'pie' vertices were drawn together with other vertex shapes. - Speed up printing graphs. - Speed up attribute queries and other basic operations, by avoiding copying of the graph. Bug \#1043616. - Fixed a bug in the NCV setting for ARPACK functions. It cannot be bigger than the matrix size. - layout.merge()'s DLA mode has better defaults now. - Fixed a bug in layout.mds() that resulted vertices on top of each other. - Fixed a bug in layout.spring(), it was not working properly. - Fixed layout.svd(), which was completely defunct. - Fixed a bug in layout.graphopt() that caused warnings and on some platforms crashes. - Fixed community.to.membership(). Bug \#1022850. - Fixed a graph.incidence() crash if it was called with a non-matrix argument. - Fixed a get.shortest.paths bug, when output was set to "both". - Motif finding functions return NA for isomorphism classes that are not motifs (i.e. not connected). Fixes bug \#1050859. - Fixed get.adjacency() when attr is given, and the attribute has some complex type. Bug \#1025799. - Fixed attribute name in graph.adjacency() for dense matrices. Bug \#1066952. - Fixed erratic behavior of alpha.centrality(). - Fixed igraph indexing, when attr is given. Bug \#1073705. - Fixed a bug when calculating the largest cliques of a directed graph. Bug \#1073800. - Fixed a bug in the maximal clique search, closes \#1074402. - Warn for negative weights when calculating PageRank. - Fixed dense, unweighted graph.adjacency when diag=FALSE. Closes issue \#1077425. - Fixed a bug in eccentricity() and radius(), the results were often simply wrong. - Fixed a bug in get.all.shortest.paths() when some edges had zero weight. - graph.data.frame() is more careful when vertex names are numbers, to avoid their scientific notation. Fixes issue \#1082221. - Better check for NAs in vertex names. Fixes issue \#1087215 - Fixed some potential crashes in the DrL layout generator. - Fixed a bug in the Reingold-Tilford layout when the graph is directed and mode != ALL. - Eliminate gap between vertex and edge when plotting an edge without an arrow. Fixes \#1118448. - Fixed a bug in has.multiple() that resulted in false negatives for some undirected graphs. - Fixed a crash in weighted betweenness calculation. - R plotting: fixed a bug that caused misplaced arrows at rectangle vertex shapes. Python news and fixes --------------------- - Added bipartite support to the Pajek reader and writer, closes bug \#1042298. - Graph.Degree_Sequence() has a new method now: "no_multiple". - Added the is_degree_sequence() and is_graphical_degree_sequence() functions. - rewire() has a new mode: "loops", that can create loop edges. - Walktrap community detection now handles isolates. - Added Graph.K_Regular(). - power_law_fit() now uses a C implementation. - Added support for setting the frame (stroke) width of vertices using the frame_width attribute or the vertex_frame_width keyword argument in plot() - Improved Inkscape-friendly SVG output from Graph.write_svg(), thanks to drlog - Better handling of named vertices in Graph.delete_vertices() - Added experimental Gephi graph streaming support; see igraph.remote.gephi and igraph.drawing.graph.GephiGraphStreamingDrawer - Nicer __repr__ output for Flow and Cut instances - Arrows are now placed correctly around diamond-shaped nodes on plots - Added Graph.TupleList, a function that allows one to create graphs with edge attributes quickly from a list of tuples. - plot() now also supports .eps as an extension, not only .ps - Fixed overflow issues in centralization calculations. - Fixed a bug that mishandled vertex colors in VF2 isomorphism functions. Bug \#1032819. - Pajek exporter now always quotes strings, thanks to Elena Tea Russo. - Fixed a bug with handling small edge weights in shortest paths calculation in Graph.shortest_paths() (Dijkstra's algorithm.) Thanks to Martin J Reed. - Fixed a bug in the NCV setting for ARPACK functions. It cannot be bigger than the matrix size. - Fixed a bug in Graph.layout_mds() that resulted vertices on top of each other. - Motif finding functions return nan for isomorphism classes that are not motifs (i.e. not connected). Fixes bug \#1050859. - Fixed a bug when calculating the largest cliques of a directed graph. Bug \#1073800. - Warn for negative weights when calculating PageRank. - Fixed a bug in Graph.eccentricity() and Graph.radius(), the results were often simply wrong. - Fixed a bug in Graph.get.all.shortest.paths() when some edges had zero weight. - Fixed some potential crashes in the DrL layout generator. - Fixed a bug in the Reingold-Tilford layout when the graph is directed and mode != ALL. - Fixed a bug in Graph.layout_sugiyama() when the graph had no edges. - Fixed a bug in Graph.community_label_propagation() when initial labels contained -1 entries. Issue \#1105460. - Repaired the DescartesCoordinateSystem class (which is not used too frequently anyway) - Fixed a bug that caused segfaults when an igraph Graph was used in a thread forked from the main Python interpreter thread - Fixed a bug that affected file handles created from Python strings in the C layer - Fixed a bug in has_multiple() that resulted in false negatives for some undirected graphs. - Fixed a crash in weighted betweenness calculation. C library news and changes -------------------------- - Added bipartite support to the Pajek reader and writer, closes bug \#1042298. - igraph_layout_mds() uses LAPACK instead of ARPACK. - igraph_degree_sequence_game has a new method: IGRAPH_DEGSEQ_SIMPLE_NO_MULTIPLE. - Added the igraph_is_degree_sequence() and igraph_is_graphical_degree_sequence() functions. - igraph_rewire() has a new method: IGRAPH_REWIRING_SIMPLE_LOOPS, that can create loops. - Walktrap community detection now handles isolates. - Added igraph_k_regular_game(). - Added igraph_power_law_fit. - Fixed a bug in igraph_barabasi_game when outseq was an empty vector. - Fixed overflow issues in centralization calculations. - Fixed an invalid return value of igraph_vector_ptr_pop_back. - Fixed a igraph_all_minimal_st_separators() bug, some vertex sets were incorrectly reported as separators. Bug \#1033045. - Pajek exporter now always quotes strings, thanks to Elena Tea Russo. - Fixed a bug with handling small edge weights in igraph_shortest_paths_dijkstra(), thanks to Martin J Reed. - Fixed a bug in the NCV setting for ARPACK functions. It cannot be bigger than the matrix size. - igraph_layout_merge_dla uses better default parameter values now. - Fixed a bug in igraph_layout_mds() that resulted vertices on top of each other. - Attribute handler table is not thread-local any more. - Motif finding functions return IGRAPH_NAN for isomorphism classes that are not motifs (i.e. not connected). Fixes bug \#1050859. - Fixed a bug when calculating the largest cliques of a directed graph. Bug \#1073800. - Fix a bug in degree_sequence_game(), in_seq can be an empty vector as well instead of NULL, for an undirected graph. - Fixed a bug in the maximal clique search, closes \#1074402. - Warn for negative weights when calculating PageRank. - Fixed a bug in igraph_eccentricity() (and also igraph_radius()), the results were often simply wrong. - Fixed a bug in igraph_get_all_shortest_paths_dijkstra() when edges had zero weight. - Fixed some potential crashes in the DrL layout generator. - Fixed a bug in the Reingold-Tilford layout when the graph is directed and mode != ALL. - Fixed a bug in igraph_has_multiple() that resulted in false negatives for some undirected graphs. - Fixed a crash in weighted betweenness calculation. igraph 0.6 ========== Released June 11, 2012 See also the release notes at http://igraph.sf.net/relnotes-0.6.html R: Major new features --------------------- - Vertices and edges are numbered from 1 instead of 0. Note that this makes most of the old R igraph code incompatible with igraph 0.6. If you want to use your old code, please use the igraph0 package. See more at http://igraph.sf.net/relnotes-0.6.html. - The '\[' and '\[\[' operators can now be used on igraph graphs, for '\[' the graph behaves as an adjacency matrix, for '[[' is is treated as an adjacency list. It is also much simpler to manipulate the graph structure, i.e. add/remove edges and vertices, with some new operators. See more at ?graph.structure. - In all functions that take a vector or list of vertices or edges, vertex/edge names can be given instead of the numeric ids. - New package 'igraphdata', contains a number of data sets that can be used directly in igraph. - Igraph now supports loading graphs from the Nexus online data repository, see nexus.get(), nexus.info(), nexus.list() and nexus.search(). - All the community structure finding algorithm return a 'communities' object now, which has a bunch of useful operations, see ?communities for details. - Vertex and edge attributes are handled much better now. They are kept whenever possible, and can be combined via a flexible API. See ?attribute.combination. - R now prints igraph graphs to the screen in a more structured and informative way. The output of summary() was also updated accordingly. R: Other new features --------------------- - It is possible to mark vertex groups on plots, via shading. Communities and cohesive blocks are plotted using this by default. - Some igraph demos are now available, see a list via 'demo(package="igraph")'. - igraph now tries to select the optimal layout algorithm, when plotting a graph. - Added a simple console, using Tcl/Tk. It contains a text area for status messages and also a status bar. See igraph.console(). - Reimplemented igraph options support, see igraph.options() and getIgraphOpt(). - Igraph functions can now print status messages. R: New or updated functions --------------------------- Community detection ------------------- - The multi-level modularity optimization community structure detection algorithm by Blondel et al. was added, see multilevel.community(). - Distance between two community structures: compare.communities(). - Community structure via exact modularity optimization, optimal.community(). - Hierarchical random graphs and community finding, porting the code from Aaron Clauset. See hrg.game(), hrg.fit(), etc. - Added the InfoMAP community finding method, thanks to Emmanuel Navarro for the code. See infomap.community(). Shortest paths -------------- - Eccentricity (eccentricity()), and radius (radius()) calculations. - Shortest path calculations with get.shortest.paths() can now return the edges along the shortest paths. - get.all.shortest.paths() now supports edge weights. Centrality ---------- - Centralization scores for degree, closeness, betweenness and eigenvector centrality. See centralization.scores(). - Personalized Page-Rank scores, see page.rank(). - Subgraph centrality, subgraph.centrality(). - Authority (authority.score()) and hub (hub.score()) scores support edge weights now. - Support edge weights in betweenness and closeness calculations. - bonpow(), Bonacich's power centrality and alpha.centrality(), Alpha centrality calculations now use sparse matrices by default. - Eigenvector centrality calculation, evcent() now works for directed graphs. - Betweenness calculation can now use arbitrarily large integers, this is required for some lattice-like graphs to avoid overflow. Input/output and file formats ----------------------------- - Support the DL file format in graph.read(). See http://www.analytictech.com/networks/dataentry.htm. - Support writing the LEDA file format in write.graph(). Plotting and layouts -------------------- - Star layout: layout.star(). - Layout based on multidimensional scaling, layout.mds(). - New layouts layout.grid() and layout.grid.3d(). - Sugiyama layout algorithm for layered directed acyclic graphs, layout.sugiyama(). Graph generators ---------------- - New graph generators: static.fitness.game(), static.power.law.game(). - barabasi.game() was rewritten and it supports three algorithms now, the default algorithm does not generate multiple or loop edges. The graph generation process can now start from a supplied graph. - The Watts-Strogatz graph generator, igraph_watts_strogatz() can now create graphs without loop edges. Others ------ - Added the Spectral Coarse Graining algorithm, see scg(). - The cohesive.blocks() function was rewritten in C, it is much faster now. It has a nicer API, too. See demo("cohesive"). - Added generic breadth-first and depth-first search implementations with many callbacks, graph.bfs() and graph_dfs(). - Support vertex and edge coloring in the VF2 (sub)graph isomorphism functions (graph.isomorphic.vf2(), graph.count.isomorphisms.vf2(), graph.get.isomorphisms.vf2(), graph.subisomorphic.vf2(), graph.count.subisomorphisms.vf2(), graph.get.subisomorphisms.vf2()). - Assortativity coefficient, assortativity(), assortativity.nominal() and assortativity.degree(). - Vertex operators that work by vertex names: graph.intersection.by.name(), graph.union.by.name(), graph.difference.by.name(). Thanks to Magnus Torfason for contributing his code! - Function to calculate a non-induced subraph: subgraph.edges(). - More comprehensive maximum flow and minimum cut calculation, see functions graph.maxflow(), graph.mincut(), stCuts(), stMincuts(). - Check whether a directed graph is a DAG, is.dag(). - has.multiple() to decide whether a graph has multiple edges. - Added a function to calculate a diversity score for the vertices, graph.diversity(). - Graph Laplacian calculation (graph.laplacian()) supports edge weights now. - Biconnected component calculation, biconnected.components() now returns the components themselves. - bipartite.projection() calculates multiplicity of edges. - Maximum cardinality search: maximum.cardinality.search() and chordality test: is.chordal() - Convex hull computation, convex.hull(). - Contract vertices, contract.vertices(). New in the Python interface --------------------------- TODO Major changes in the Python interface ------------------------------------- TODO New in the C layer ------------------ - Maximum cardinality search: igraph_maximum_cardinality_search() and chordality test: igraph_is_chordal(). - Support the DL file format, igraph_read_graph_dl(). See http://www.analytictech.com/networks/dataentry.htm. - Added generic breadth-first and depth-first search implementations with many callbacks (igraph_bfs(), igraph_dfs()). - Centralization scores for degree, closeness, betweenness and eigenvector centrality, see igraph_centralization(). - Added igraph_sparsemat_t, a type that implements sparse matrices based on the CXSparse library by Tim Davis. See http://www.cise.ufl.edu/research/sparse/CXSparse/. - Personalized Page-Rank scores, igraph_personalized_pagerank() and igraph_personalized_pagerank_vs(). - Assortativity coefficient, igraph_assortativity(), igraph_assortativity_nominal(), and igraph_assortativity_degree(). - The multi-level modularity optimization community structure detection algorithm by Blondel et al. was added, see igraph_community_multilevel(). - Added the igraph_version() function. - Star layout: igraph_layout_star(). - Function to calculate a non-induced subraph: igraph_subgraph_edges(). - Distance between two community structures: igraph_compare_communities(). - Community structure via exact modularity optimization, igraph_community_optimal_community(). - More comprehensive maximum flow and minimum cut calculation, see functions igraph_maxflow(), igraph_mincut(), igraph_all_st_cuts(), igraph_all_st_mincuts(). - Layout based on multidimensional scaling, igraph_layout_mds(). - It is now possible to access the random number generator(s) via an API. Multiple RNGs can be used, from external sources as well. The default RNG is MT19937. - Added igraph_get_all_shortest_paths_dijkstra, for calculating all non-negatively weighted shortest paths. - Check whether a directed graph is a DAG, igraph_is_dag(). - Cohesive blocking, a'la Moody & White, igraph_cohesive_blocks(). - Igraph functions can now print status messages, see igraph_status() and related functions. - Support writing the LEDA file format, igraph_write_graph_leda(). - Contract vertices, igraph_contract_vertices(). - The C reference manual has now a lot of example programs. - Hierarchical random graphs and community finding, porting the code from Aaron Clauset. See igraph_hrg_game(), igraph_hrg_fit(), etc. - igraph_has_multiple() to decide whether a graph has multiple edges. - New layouts igraph_layout_grid() and igraph_layout_grid_3d(). - igraph_integer_t is really an integer now, it used to be a double. - igraph_minimum_spanning_tree(), calls either the weighted or the unweighted implementation. - Eccentricity (igraph_eccentricity()), and radius (igraph_radius()) calculations. - Several game theory update rules, written by Minh Van Nguyen. See igraph_deterministic_optimal_imitation(), igraph_stochastic_imitation(), igraph_roulette_wheel_imitation(), igraph_moran_process(), - Sugiyama layout algorithm for layered directed acyclic graphs, igraph_layout_sugiyama(). - New graph generators: igraph_static_fitness_game(), igraph_static_power_law_game(). - Added the InfoMAP community finding method, thanks to Emmanuel Navarro for the code. See igraph_community_infomap(). - Added the Spectral Coarse Graining algorithm, see igraph_scg(). - Added a function to calculate a diversity score for the vertices, igraph_diversity(). Major changes in the C layer ---------------------------- - Authority (igraph_authority_score()) and hub (igraph_hub_score()) scores support edge weights now. - Graph Laplacian calculation (igraph_laplacian()) supports edge weights now. - Support edge weights in betweenness (igraph_betweenness()) and closeness (igraph_closeness()) calculations. - Support vertex and edge coloring in the VF2 graph isomorphism algorithm (igraph_isomorphic_vf2(), igraph_count_isomorphisms_vf2(), igraph_get_isomorphisms_vf2(), igraph_subisomorphic_vf2(), igraph_count_subisomorphisms_vf2(), igraph_get_subisomorphisms_vf2()). - Added print operations for the igraph_vector*_t, igraph_matrix*_t and igraph_strvector_t types. - Biconnected component calculation (igraph_biconnected_components()) can now return the components themselves. - Eigenvector centrality calculation, igraph_eigenvector_centrality() now works for directed graphs. - Shortest path calculations with get_shortest_paths() and get_shortest_paths_dijkstra() can now return the edges along the paths. - Betweenness calculation can now use arbitrarily large integers, this is required for some lattice-like graphs to avoid overflow. - igraph_bipartite_projection() calculates multiplicity of edges. - igraph_barabasi_game() was rewritten and it supports three algorithms now, the default algorithm does not generate multiple or loop edges. - The Watts-Strogatz graph generator, igraph_watts_strogatz() can now create graphs without loop edges. - igraph should be now thread-safe, on architectures that support thread-local storage (Linux and Windows: yes, Mac OSX: no). We also fixed numerous bugs, too many to include them here, sorry. You may look at our bug tracker at https://bugs.launchpad.net/igraph to check whether a bug was fixed or not. Thanks for all the people reporting bugs. Special thanks to Minh Van Nguyen for a lot of bug reports, documentation fixes and contributed code! igraph 0.5.3 ============ Released November 22, 2009 Bugs corrected in the R interface --------------------------------- - Some small changes to make 'R CMD check' clean - Fixed a bug in graph.incidence, the 'directed' and 'mode' arguments were not handled correctly - Betweenness and edge betweenness functions work for graphs with many shortest paths now (up to the limit of long long int) - When compiling the package, the configure script fails if there is no C compiler available - igraph.from.graphNEL creates the right number of loop edges now - Fixed a bug in bipartite.projection() that caused occasional crashes on some systems New in the Python interface --------------------------- - Added support for weighted diameter - get_eid() considers edge directions by default from now on - Fixed a memory leak in the attribute handler - 'NaN' and 'inf' are treated correctly now Bugs corrected in the C layer ----------------------------- - Betweenness and edge betweenness functions work for graphs with many shortest paths now (up to the limit of long long int) - The configure script fails if there is no C compiler available - Fixed a bug in igraph_community_spinglass, when csize was a NULL pointer, but membership was not - Fixed a bug in igraph_bipartite_projection that caused occasional crashes on some systems igraph 0.5.2 ============ Released April 10, 2009 See also the release notes at http://igraph.sf.net/relnotes-0.5.2.html New in the R interface ---------------------- - Added progress bar support to beweenness() and betweenness.estimate(), layout.drl() - Speeded up betweenness estimation - Speeded up are.connected() - Johnson's shortest paths algorithm added - shortest.paths() has now an 'algorithm' argument to choose from the various implementations manually - Always quote symbolic vertex names when printing graphs or edges - Average nearest neighbor degree calculation, graph.knn() - Weighted degree (also called strength) calculation, graph.strength() - Some new functions to support bipartite graphs: graph.bipartite(), is.bipartite(), get.indicence(), graph.incidence(), bipartite.projection(), bipartite.projection.size() - Support for plotting curved edges with plot.igraph() and tkplot() - Added support for weighted graphs in alpha.centrality() - Added the label propagation community detection algorithm by Raghavan et al., label.propagation.community() - cohesive.blocks() now has a 'cutsetHeuristic' argument to choose between two cutset algorithms - Added a function to "unfold" a tree, unfold.tree() - New tkplot() arguments to change the drawing area - Added a minimal GUI, invoke it with tkigraph() - The DrL layout generator, layout.drl() has a three dimensional mode now. Bugs corrected in the R interface --------------------------------- - Fixed a bug in VF2 graph isomorphism functions - Fixed a bug when a sparse adjacency matrix was requested in get.adjacency() and the graph was named - VL graph generator in degree.sequence.game() checks now that the sum of the degrees is even - Many fixes for supporting various compilers, e.g. GCC 4.4 and Sun's C compiler - Fixed memory leaks in graph.automorphisms(), Bellman-Ford shortest.paths(), independent.vertex.sets() - Fix a bug when a graph was imported from LGL and exported to NCOL format (\#289596) - cohesive.blocks() creates its temporary file in the session temporary directory - write.graph() and read.graph() now give error messages when unknown arguments are given - The GraphML reader checks the name of the attributes to avoid adding a duplicate 'id' attribute - It is possible to change the 'ncv' ARPACK parameter for leading.eigenvector.community() - Fixed a bug in path.length.hist(), 'unconnected' was wrong for unconnected and undirected graphs - Better handling of attribute assingment via iterators, this is now also clarified in the manual - Better error messages for unknown vertex shapes - Make R package unload cleanly if unloadNamespace() is used - Fixed a bug in plotting square shaped vertices (\#325244) - Fixed a bug in graph.adjacency() when the matrix is a sparse matrix of class "dgTMatrix" New in the Python interface --------------------------- - Speeded up betweenness estimation - Johnson's shortest paths algorithm added (selected automatically by Graph.shortest_paths() if needed) - Weighted degree (also called strength) calculation, Graph.strength() - Some new methods to support bipartite graphs: Graph.Bipartite(), Graph.is_bipartite(), Graph.get_indicence(), Graph.Incidence(), Graph.bipartite_projection(), Graph.bipartite_projection_size() - Added the label propagation community detection algorithm by Raghavan et al., Graph.community_label_propagation() - Added a function to "unfold" a tree, Graph.unfold_tree() - setup.py script improvements - Graph plotting now supports edge_arrow_size and edge_arrow_width - Added Graph.Formula to create small graphs from a simple notation - VertexSeq and EdgeSeq objects can now be indexed by slices New in the C layer ------------------ - Added progress bar support to igraph_betweenness() and igraph_betweenness_estimate(), igraph_layout_drl() - Speeded up igraph_betweenness_estimate(), igraph_get_eid(), igraph_are_connected(), igraph_get_eids() - Added igraph_get_eid2() - Johnson's shortest path algorithm added: igraph_shortest_paths_johnson() - Average nearest neighbor degree calculation, igraph_avg_nearest_neighbor_degree() - Weighted degree (also called strength) calculation, igraph_strength() - Some functions to support bipartite graphs: igraph_full_bipartite(), igraph_bipartite_projection(), igraph_create_bipartite(), igraph_incidence(), igraph_get_incidence(), igraph_bipartite_projection_size(), igraph_is_bipartite() - Added the label propagation community detection algorithm by Raghavan et al., igraph_community_label_propagation() - Added an example that shows how to set the random number generator's seed from C (examples/simple/random_seed.c) - Added a function to "unfold" a tree, igraph_unfold_tree() - C attribute handler updates: added functions to query many vertices/edges at once - Three dimensional DrL layout, igraph_layout_drl_3d() Bugs corrected in the C layer ----------------------------- - Fixed a bug in igraph_isomorphic_function_vf2(), affecting all VF2 graph isomorphism functions - VL graph generator in igraph_degree_sequence_game() checks now that the sum of the degrees is even - Many small corrections to make igraph compile with Microsoft Visual Studio 2003, 2005 and 2008 - Many fixes for supporting various compilers, e.g. GCC 4.4 and Sun's C compiler - Fix a bug when a graph was imported from LGL and exported to NCOL format (\#289596) - Fixed memory leaks in igraph_automorphisms(), igraph_shortest_paths_bellman_ford(), igraph_independent_vertex_sets() - The GraphML reader checks the name of the attributes to avoid adding a duplicate 'id' attribute - It is possible to change the 'ncv' ARPACK parameter for igraph_community_leading_eigenvector() - Fixed a bug in igraph_path_length_hist(), 'unconnected' was wrong for unconnected and undirected graphs. igraph 0.5.1 ============ Released July 14, 2008 See also the release notes at http://igraph.sf.net/relnotes-0.5.1.html New in the R interface ---------------------- - A new layout generator called DrL. - Uniform sampling of random connected undirected graphs with a given degree sequence. - Edge labels are plotted at 1/3 of the edge, this is better if the graph has mutual edges. - Initial and experimental vertex shape support in 'plot'. - New function, 'graph.adjlist' creates igraph graphs from adjacency lists. - Conversion to/from graphNEL graphs, from the 'graph' R package. - Fastgreedy community detection can utilize edge weights now, this was missing from the R interface. - The 'arrow.width' graphical parameter was added. - graph.data.frame has a new argument 'vertices'. - graph.adjacency and get.adjacency support sparse matrices, the 'Matrix' package is required to use this functionality. - graph.adjacency adds column/row names as 'name' attribute. - Weighted shortest paths using Dijkstra's or the Belmann-Ford algorithm. - Shortest path functions return 'Inf' for unreachable vertices. - New function 'is.mutual' to find mutual edges in a directed graph. - Added inverse log-weighted similarity measure (a.k.a. Adamic/Adar similarity). - preference.game and asymmetric.preference.game were rewritten, they are O(|V|+|E|) now, instead of O(|V|^2). - Edge weight support in function 'get.shortest.paths', it uses Dijkstra's algorithm. Bugs corrected in the R interface --------------------------------- - A bug was corrected in write.pajek.bgraph. - Several bugs were corrected in graph.adjacency. - Pajek reader bug corrected, used to segfault if '\*Vertices' was missing. - Directedness is handled correctly when writing GML files. (But note that 'correct' conflicts the standard here.) - Corrected a bug when calculating weighted, directed PageRank on an undirected graph. (Which does not make sense anyway.) - Several bugs were fixed in the Reingold-Tilford layout to avoid edge crossings. - A bug was fixed in the GraphML reader, when the value of a graph attribute was not specified. - Fixed a bug in the graph isomorphism routine for small (3-4 vertices) graphs. - Corrected the random sampling implementation (igraph_random_sample), now it always generates unique numbers. This affects the Gnm Erdos-Renyi generator, it always generates simple graphs now. - The basic igraph constructor (igraph_empty_attrs, all functions are expected to call this internally) now checks whether the number of vertices is finite. - The LGL, NCOL and Pajek graph readers handle errors properly now. - The non-symmetric ARPACK solver returns results in a consistent form now. - The fast greedy community detection routine now checks that the graph is simple. - The LGL and NCOL parsers were corrected to work with all kinds of end-of-line encodings. - Hub & authority score calculations initialize ARPACK parameters now. - Fixed a bug in the Walktrap community detection routine, when applied to unconnected graphs. - Several small memory leaks were removed, and a big one from the Spinglass community structure detection function New in the Python interface --------------------------- - A new layout generator called DrL. - Uniform sampling of random connected undirected graphs with a given degree sequence. - Methods parameters accepting igraph.IN, igraph.OUT and igraph.ALL constants now also accept these as strings ("in", "out" and "all"). Prefix matches also allowed as long as the prefix match is unique. - Graph.shortest_paths() now supports edge weights (Dijkstra's and Bellman-Ford algorithm implemented) - Graph.get_shortest_paths() also supports edge weights (only Dijkstra's algorithm yet) - Added Graph.is_mutual() to find mutual edges in a directed graph. - Added inverse log-weighted similarity measure (a.k.a. Adamic/Adar similarity). - preference.game and asymmetric.preference.game were rewritten, they are O(|V|+|E|) now, instead of O(|V|^2). - ARPACK options can now be modified from the Python interface (thanks to Kurt Jacobson) - Layout.to_radial() added -- now you can create a top-down tree layout by the Reingold-Tilford algorithm and then turn it to a radial tree layout - Added Graph.write_pajek() to save graphs in Pajek format - Some vertex and edge related methods can now also be accessed via the methods of VertexSeq and EdgeSeq, restricted to the current vertex/edge sequence of course - Visualisations now support triangle shaped vertices - Added Graph.mincut() - Added Graph.Weighted_Adjacency() to create graphs from weighted adjacency matrices - Kamada-Kawai and Fruchterman-Reingold layouts now accept initial vertex positions - Graph.Preference() and Graph.Asymmetric_Preference() were rewritten, they are O(|V|+|E|) now, instead of O(|V|^2). Bugs corrected in the Python interface -------------------------------------- - Graph.constraint() now properly returns floats instead of integers (thanks to Eytan Bakshy) - Graphs given by adjacency matrices are now finally loaded and saved properly - Graph.Preference() now accepts floats in type distributions - A small bug in Graph.community_edge_betweenness() corrected - Some bugs in numeric attribute handling resolved - VertexSeq and EdgeSeq objects can now be subsetted by lists and tuples as well - Fixed a bug when dealing with extremely small layout sizes - Eigenvector centality now always return positive values - Graph.authority_score() now really returns the authority scores instead of the hub scores (blame copypasting) - Pajek reader bug corrected, used to segfault if '\*Vertices' was missing. - Directedness is handled correctly when writing GML files. (But note that 'correct' conflicts the standard here.) - Corrected a bug when calculating weighted, directed PageRank on an undirected graph. (Which does not make sense anyway.) - Several bugs were fixed in the Reingold-Tilford layout to avoid edge crossings. - A bug was fixed in the GraphML reader, when the value of a graph attribute was not specified. - Fixed a bug in the graph isomorphism routine for small (3-4 vertices) graphs. - Corrected the random sampling implementation (igraph_random_sample), now it always generates unique numbers. This affects the Gnm Erdos-Renyi generator, it always generates simple graphs now. - The LGL, NCOL and Pajek graph readers handle errors properly now. - The non-symmetric ARPACK solver returns results in a consistent form now. - The fast greedy community detection routine now checks that the graph is simple. - The LGL and NCOL parsers were corrected to work with all kinds of end-of-line encodings. - Hub & authority score calculations initialize ARPACK parameters now. - Fixed a bug in the Walktrap community detection routine, when applied to unconnected graphs. - Several small memory leaks were removed, and a big one from the Spinglass community structure detection function New in the C layer ------------------ - A new layout generator called DrL. - Uniform sampling of random connected undirected graphs with a given degree sequence. - Some stochastic test results are ignored (for spinglass community detection, some Erdos-Renyi generator tests) - Weighted shortest paths, Dijkstra's algorithm. - The unweigthed shortest path routine returns 'Inf' for unreachable vertices. - New function, igraph_adjlist can create igraph graphs from adjacency lists. - New function, igraph_weighted_adjacency can create weighted graphs from weight matrices. - New function, igraph_is_mutual to search for mutual edges. - Added inverse log-weighted similarity measure (a.k.a. Adamic/Adar similarity). - igraph_preference_game and igraph_asymmetric_preference_game were rewritten, they are O(|V|+|E|) now, instead of O(|V|^2). - The Bellman-Ford shortest path algorithm was added. - Added weighted variant of igraph_get_shortest_paths, based on Dijkstra's algorithm. - Several small memory leaks were removed, and a big one from the Spinglass community structure detection function Bugs corrected in the C layer ----------------------------- - Several bugs were corrected in the (still experimental) C attribute handler. - Pajek reader bug corrected, used to segfault if '\*Vertices' was missing. - Directedness is handled correctly when writing GML files. (But note that 'correct' conflicts the standard here.) - Corrected a bug when calculating weighted, directed PageRank on an undirected graph. (Which does not make sense anyway.) - Some code polish to make igraph compile with GCC 4.3 - Several bugs were fixed in the Reingold-Tilford layout to avoid edge crossings. - A bug was fixed in the GraphML reader, when the value of a graph attribute was not specified. - Fixed a bug in the graph isomorphism routine for small (3-4 vertices) graphs. - Corrected the random sampling implementation (igraph_random_sample), now it always generates unique numbers. This affects the Gnm Erdos-Renyi generator, it always generates simple graphs now. - The basic igraph constructor (igraph_empty_attrs, all functions are expected to call this internally) now checks whether the number of vertices is finite. - The LGL, NCOL and Pajek graph readers handle errors properly now. - The non-symmetric ARPACK solver returns results in a consistent form now. - The fast greedy community detection routine now checks that the graph is simple. - The LGL and NCOL parsers were corrected to work with all kinds of end-of-line encodings. - Hub & authority score calculations initialize ARPACK parameters now.x - Fixed a bug in the Walktrap community detection routine, when applied to unconnected graphs. igraph 0.5 ========= Released February 14, 2008 See also the release notes at http://igraph.sf.net/relnotes-0.5.html New in the R interface ---------------------- - The 'rescale', 'asp' and 'frame' graphical parameters were added - Create graphs from a formula notation (graph.formula) - Handle graph attributes properly - Calculate the actual minimum cut for undirected graphs - Adjacency lists, get.adjlist and get.adjedgelist added - Eigenvector centrality computation is much faster now - Proper R warnings, instead of writing the warning to the terminal - R checks graphical parameters now, the unknown ones are not just ignored, but an error message is given - plot.igraph has an 'add' argument now to compose plots with multiple graphs - plot.igraph supports the 'main' and 'sub' arguments - layout.norm is public now, it can normalize a layout - It is possible to supply startup positions to layout generators - Always free memory when CTRL+C/ESC is pressed, in all operating systems - plot.igraph can plot square vertices now, see the 'shape' parameter - graph.adjacency rewritten when creating weighted graphs - We use match.arg whenever possible. This means that character scalar options can be abbreviated and they are always case insensitive - VF2 graph isomorphism routines can check subgraph isomorphism now, and they are able to return matching(s) - The BLISS graph isomorphism algorithm is included in igraph now. See canonical.permutation, graph.isomorphic.bliss - We use ARPACK for eigenvalue/eigenvector calculation. This means that the following functions were rewritten: page.rank, leading.eigenvector.community.\*, evcent. New functions based on ARPACK: hub.score, authority.score, arpack. - Edge weights for Fruchterman-Reingold layout (layout.fruchterman.reingold). - Line graph calculation (line.graph) - Kautz and de Bruijn graph generators (graph.kautz, graph.de.bruijn) - Support for writing graphs in DOT format - Jaccard and Dice similarity coefficients added (similarity.jaccard, similarity.dice) - Counting the multiplicity of edges (count.multiple) - The graphopt layout algorithm was added, layout.graphopt - Generation of "famous" graphs (graph.famous). - Create graphs from LCF notation (graph.cf). - Dyad census and triad cencus functions (dyad.census, triad.census) - Cheking for simple graphs (is.simple) - Create full citation networks (graph.full.citation) - Create a histogram of path lengths (path.length.hist) - Forest fire model added (forest.fire.game) - DIMACS reader can handle different file types now - Biconnected components and articulation points (biconnected.components, articulation.points) - Kleinberg's hub and authority scores (hub.score, authority.score) - as.undirected handles attributes now - Geometric random graph generator (grg.game) can return the coordinates of the vertices - Function added to convert leading eigenvector community structure result to a membership vector (community.le.to.membership) - Weighted fast greedy community detection - Weighted page rank calculation - Functions for estimating closeness, betweenness, edge betweenness by introducing a cutoff for path lengths (closeness.estimate, betweenness.estimate, edge.betweenness.estimate) - Weighted modularity calculation - Function for permuting vertices (permute.vertices) - Betweenness and closeness calculations are speeded up - read.graph can handle all possible line terminators now (\r, \n, \r\n, \n\r) - Error handling was rewritten for walktrap community detection, the calculation can be interrupted now - The maxflow/mincut functions allow to supply NULL pointer for edge capacities, implying unit capacities for all edges Bugs corrected in the R interface --------------------------------- - Fixed a bug in cohesive.blocks, cohesive blocks were sometimes not calculated correctly New in the Python interface --------------------------- - Added shell interface: igraph can now be invoked by calling the script called igraph from the command line. The script launches the Python interpreter and automatically imports igraph functions into the main namespace - Pickling (serialization) support for Graph objects - Plotting functionality based on the Cairo graphics library (so you need to install python-cairo if you want to use it). Currently the following objects can be plotted: graphs, adjacency matrices and dendrograms. Some crude support for plotting histograms is also implemented. Plots can be saved in PNG, SVG and PDF formats. - Unified Graph.layout method for accessing layout algorithms - Added interfaces to walktrap community detection and the BLISS isomorphism algorithm - Added dyad and triad census functionality and motif counting - VertexSeq and EdgeSeq objects can now be restricted to subsets of the whole network (e.g., you can select vertices/edges based on attributes, degree, centrality and so on) New in the C library -------------------- - Many types (stack, matrix, dqueue, etc.) are templates now They were also rewritten to provide a better organized interface - VF2 graph isomorphism routines can check subgraph isomorphism now, and they are able to return matching(s) - The BLISS graph isomorphism algorithm is included in igraph now. See igraph_canonical_permutation, igraph_isomorphic_bliss - We use ARPACK for eigenvalue/eigenvector calculation. This means that the following functions were rewritten: igraph_pagerank, igraph_community_leading_eigenvector_\*. New functions based on ARPACK: igraph_eigenvector_centrality, igraph_hub_score, igraph_authority_score, igraph_arpack_rssolve, igraph_arpack_rnsolve - Experimental C attribute interface added. I.e. it is possible to use graph/vertex/edge attributes from C code now. - Edge weights for Fruchterman-Reingold layout. - Line graph calculation. - Kautz and de Bruijn graph generators - Support for writing graphs in DOT format - Jaccard and Dice similarity coefficients added - igraph_count_multiple added - igraph_is_loop and igraph_is_multiple "return" boolean vectors - The graphopt layout algorithm was added, igraph_layout_graphopt - Generation of "famous" graphs, igraph_famous - Create graphs from LCF notation, igraph_lcf, igraph_lcf_vector - igraph_add_edge adds a single edge to the graph - Dyad census and triad cencus functions added - igraph_is_simple added - progress handlers are allowed to stop calculation - igraph_full_citation to create full citation networks - igraph_path_length_hist, create a histogram of path lengths - forest fire model added - DIMACS reader can handle different file types now - Adjacency list types made public now (igraph_adjlist_t, igraph_adjedgelist_t) - Biconnected components and articulation points can be computed - Eigenvector centrality computation - Kleinberg's hub and authority scores - igraph_to_undirected handles attributes now - Geometric random graph generator can return the coordinates of the vertices - Function added to convert leading eigenvector community structure result to a membership vector (igraph_le_community_to_membership) - Weighted fast greedy community detection - Weighted page rank calculation - Functions for estimating closeness, betweenness, edge betweenness by introducing a cutoff for path lengths - Weighted modularity calculation - igraph_permute_vertices added - Betweenness ans closeness calculations are speeded up - Startup positions can be supplied to the Kamada-Kawai layout algorithms - igraph_read_graph_\* functions can handle all possible line terminators now (\r, \n, \r\n, \n\r) - Error handling was rewritten for walktrap community detection, the calculation can be interrupted now - The maxflow/mincut functions allow to supply a null pointer for edge capacities, implying unit capacities for all edges Bugs corrected in the C library ------------------------------- - Memory leak fixed in adjacency list handling - Memory leak fixed in maximal independent vertex set calculation - Fixed a bug when rewiring undirected graphs with igraph_rewire - Fixed edge betweenness community structure detection for unconnected graphs - Make igraph compile with Sun Studio - Betweenness bug fixed, when not computing for all vertices - memory usage of clique finding reduced - Corrected bugs for motif counts when not all motifs were counted, but a 'cut' vector was used - Bugs fixed in trait games and cited type game - Accept underscore as letter in GML files - GML file directedness notation reversed, more logical this way igraph 0.4.5 ========= Released January 1, 2008 New: - Cohesive block finding in the R interface, thanks to Peter McMahan for contributing his code. See James Moody and Douglas R. White, 2003, in Structural Cohesion and Embeddedness: A Hierarchical Conception of Social Groups American Sociological Review 68(1):1-25 - Biconnected components and articulation points. - R interface: better printing of attributes. - R interface: graph attributes can be used via '$'. New in the C library: - igraph_vector_bool_t data type. Bug fixed: - Erdos-Renyi random graph generators rewritten. igraph 0.4.4 ========= Released October 3, 2007 This release should work seemlessly with the new R 2.6.0 version. Some other bugs were also fixed: - A bug was fixed in the Erdos-Renyi graph generator, which sometimes added an extra vertex. - MSVC compilation issues were fixed. - MinGW compilation fixes. igraph 0.4.3 ========= Released August 13, 2007 The next one in the sequence of bugfix releases. Thanks to many people sending bug reports. Here are the changes: - Some memory leaks removed when using attributes from R or Python. - GraphML parser: entities and character data in multiple chunks are now handled correctly. - A bug corrected in edge betweenness community structure detection, it failed if called many times from the same program/session. - Bug corrected in 'adjacent edges' edge iterator. - Python interface: edge and vertex attribute deletion bug corrected. - Edge betweeness community structure: handle unconnected graphs properly. - Fixed bug related to fast greedy community detection in unconnected graphs. - Use a different kind of parser (Push) for reading GraphML files. This is almost invisible for users but fixed a nondeterministic bug when reading in GraphML files. - R interface: plot now handles properly if called with a vector as the edge.width argument for directed graphs. - R interface: bug (typo) corrected for walktrap.community and weighted graphs. - Test suite should run correctly on Cygwin now. igraph 0.4.2 ========= Released June 7, 2007 This is another bugfix release, as there was a serious bug in the R package of the previous version: it could not read and write graphs to files in any format under MS Windows. Some other bits added: - circular Reingold-Tilford layout generator for trees - corrected a bug, Pajek files are written properly under MS Windows now. - arrow.size graphical edge parameter added in the R interface. igraph 0.4.1 ========= Released May 23, 2007 This is a minor release, it corrects a number of bugs, mostly in the R package. igraph 0.4 ========= Released May 21, 2007 The major new additions in this release is a bunch of community detection algorithms and support for the GML file format. Here is the complete list of changes: New in the C library -------------------- - internal representation changed - neighbors always returns an ordered list - igraph_is_loop and igraph_is_multiple added - topological sorting - VF2 isomorphism algorithm - support for reading the file format of the Graph Database for isomorphism - igraph_mincut cat calculate the actual minimum cut - girth calculation added, thanks to Keith Briggs - support for reading and writing GML files - Walktrap community detection algorithm added, thanks to Matthieu Latapy and Pascal Pons - edge betweenness based community detection algorithm added - fast greedy algorithm for community detection by Clauset et al. added thanks to Aaron Clauset for sharing his code - leading eigenvector community detection algorithm by Mark Newman added - igraph_community_to_membership supporting function added, creates a membership vector from a community structure merge tree - modularity calculation added New in the R interface ---------------------- - as the internal representation changed, graphs stored with 'save' with an older igraph version cannot be read back with the new version reliably. - neighbors returns ordered lists - topological sorting - VF2 isomorphism algorithm - support for reading graphs from the Graph Database for isomorphism - girth calculation added, thanks to Keith Briggs - support for reading and writing GML files - Walktrap community detection algorithm added, thanks to Matthieu Latapy and Pascal Pons - edge betweenness based community detection algorithm added - fast greedy algorithm for community detection by Clauset et al. added thanks to Aaron Clauset for sharing his code - leading eigenvector community detection algorithm by Mark Newman added - functions for creating denrdograms from the output of the community detection algorithms added - community.membership supporting function added, creates a membership vector from a community structure merge tree - modularity calculation added - graphics parameter handling is completely rewritten, uniform handling of colors and fonts, make sure you read ?igraph.plotting - new plotting parameter for edges: arrow.mode - a bug corrected when playing a nonlinear barabasi.game - better looking plotting in 3d using rglplot: edges are 3d too - rglplot layout is allowed to be two dimensional now - rglplot suspends updates while drawing, this makes it faster - loop edges are correctly plotted by all three plotting functions - better printing of attributes when printing graphs - summary of a graph prints attribute names - is.igraph rewritten to make it possible to inherit from the 'igraph' class - somewhat better looking progress meter for functions which support it Others ------ - proper support for Debian packages (re)added - many functions benefit from the new internal representation and are faster now: transitivity, reciprocity, graph operator functions like intersection and union, etc. - igraph compiles with Microsoft Visual C++ now - there were some internal changes to make igraph a real graph algorithm platform in the near future, but these are undocumented now Bugs corrected -------------- - corrected a bug when reading Pajek files: directed graphs were read as undirected Debian package repository available ================================== Debian Linux users can now install and update the C interface using the standard package manager. Just add the following two lines to /etc/apt/sources.list and install the libigraph and libigraph-dev packages. Packages for the Python interface are coming soon. deb http://cneurocvs.rmki.kfki.hu /packages/binary/ deb-src http://cneurocvs.rmki.kfki.hu /packages/source/ igraph 0.3.3 ============ Released February 28, 2007 New in the C library -------------------- * igraph_connect_neighborhood, nomen est omen * igraph_watts_strogatz_game and igraph_rewire_edges * K-core decomposition: igraph_coreness * Clique and independent vertex set related functions: igraph_cliques, igraph_independent_vertex_sets, igraph_maximal_cliques, igraph_maximal_independent_vertex_sets, igraph_independence_number, igraph_clique_number, Some of these function were ported from the very_nauty library of Keith Briggs, thanks Keith! * The GraphML file format now supports graph attributes * Transitivity calculation speeded up * Correct transitivity calculation for multigraphs (ie. non-simple graphs) New in the R interface ---------------------- * connect.neighborhood * watts.strogatz.game and rewire.edges * K-core decomposition: graph.coreness * added the 'innei' and 'outnei' shorthands for vertex sequence indexing see help(iterators) * Clique and independent vertex set related functions: cliques, largest.cliques, maximal.cliques, clique.number, independent.vertex.sets, largest.independent.vertex.sets, maximal.independent.vertex.sets, independence.number * The GraphML file format now supports graph attributes * edge.lty argument added to plot.igraph and tkplot * Transitivity calculation speeded up * Correct transitivity calculation for multigraphs (ie. non-simple graphs) * alpha.centrality added, calculates Bonacich alpha centrality, see docs. Bugs corrected -------------- * 'make install' installs the library correctly on Cygwin now * Pajek parser corrected to read files with MacOS newline characters correctly * overflow bug in transitivity calculation for large graphs corrected * an internal memcpy/memmove bug causing some segfaults removed * R interface: tkplot bug with graphs containing a 'name' attribute * R interface: attribute handling bug when adding vertices * R interface: color selection bug corrected * R interface: plot.igraph when plotting loops Python interface documentation ==================== Jan 8, 2007 The documentation of the Python interface is available. See section 'documentation' in the menu on the left. igraph 0.3.2 ========= Released Dec 19, 2006 This is a new major release, it contains many new things: Changes in the C library ------------------------ - igraph_maxdegree added, calculates the maximum degree in the graph - igraph_grg_game, geometric random graphs - igraph_density, graph density calculation - push-relabel maximum flow algorithm added, igraph_maxflow_value - minimum cut functions added based on maximum flow: igraph_st_mincut_value, igraph_mincut_value, the Stoer-Wagner algorithm is implemented for undirected graphs - vertex connectivity functions, usually based on maximum flow: igraph_st_vertex_connectivity, igraph_vertex_connectivity - edge connectivity functions, usually based on maximum flow: igraph_st_edge_connectivity, igraph_edge_connectivity - other functions based on maximum flow: igraph_edge_disjoint_paths, igraph_vertex_disjoint_paths, igraph_adhesion, igraph_cohesion - dimacs file format added - igraph_to_directed handles attributes - igraph_constraint calculation corrected, it handles weighted graphs - spinglass-based community structure detection, the Joerg Reichardt -- Stefan Bornholdt algorithm added: igraph_spinglass_community, igraph_spinglass_my_community - igraph_extended_chordal_rings, it creates extended chordal rings - 'no' argument added to igraph_clusters, it is possible to calculate the number of clusters without calculating the clusters themselves - minimum spanning tree functions keep attributes now and also the direction of the edges is kept in directed graphs - there are separate functions to calculate different types of transitivity now - igraph_delete_vertices rewritten to allocate less memory for the new graph - neighborhood related functions added: igraph_neighborhood, igraph_neighborhood_size, igraph_neighborhood_graphs - two new games added based on different node types: igraph_preference_game and igraph_asymmetric_preference_game - Laplacian of a graph can be calculated by the igraph_laplacian function Changes in the R interface -------------------------- - bonpow function ported from SNA to calculate Bonacich power centrality - get.adjacency supports attributes now, this means that it sets the colnames and rownames attributes and can return attribute values in the matrix instead of 0/1 - grg.game, geometric random graphs - graph.density, graph density calculation - edge and vertex attributes can be added easily now when added new edges with add.edges or new vertices with add.vertices - graph.data.frame creates graph from data frames, this can be used to create graphs with edge attributes easily - plot.igraph and tkplot can plot self-loop edges now - graph.edgelist to create a graph from an edge list, can also handle edge lists with symbolic names - get.edgelist has now a 'names' argument and can return symbolic vertex names instead of vertex ids, by default id uses the 'name' vertex attribute is returned - printing graphs on screen also prints symbolic symbolic names (the 'name' attribute if present) - maximum flow and minimum cut functions: graph.maxflow, graph.mincut - vertex and edge connectivity: edge.connectivity, vertex.connectivity - edge and vertex disjoint paths: edge.disjoint.paths, vertex.disjoint.paths - White's cohesion and adhesion measure: graph.adhesion, graph.cohesion - dimacs file format added - as.directed handles attributes now - constraint corrected, it handles weighted graphs as well now - weighted attribute to graph.adjacency - spinglass-based community structure detection, the Joerg Reichardt -- Stefan Bornholdt algorithm added: spinglass.community - graph.extended.chordal.ring, extended chordal ring generation - no.clusters calculates the number of clusters without calculating the clusters themselves - minimum spanning tree functions updated to keep attributes - transitivity can calculate local transitivity as well - neighborhood related functions added: neighborhood, neighborhood.size, graph.neighborhood - new graph generators based on vertex types: preference.game and asymmetric.preference.game Bugs corrected -------------- - attribute handling bug when deleting edges corrected - GraphML escaping and NaN handling corrected - bug corrected to make it possible compile the R package without the libxml2 library - a bug in Erdos-Renyi graph generation corrected: it had problems with generating large directed graphs - bug in constraint calculation corrected, it works well now - fixed memory leaks in igraph_read_graph_graphml - error handling bug corrected in igraph_read_graph_graphml - bug corrected in R version of graph.laplacian when normalized Laplacian is requested - memory leak corrected in get.all.shortest.paths in the R package igraph 0.2.1 ========= Released Aug 23, 2006 This is a bug-fix release. Bugs fixed: - igraph_reciprocity (reciprocity in R) corrected to avoid segfaults - some docs updates - various R package updated to make it conform to the CRAN rules igraph 0.2 ========= Released Aug 18, 2006 Release time at last! There are many new things in igraph 0.2, the most important ones: - reading writing Pajek and GraphML formats with attributes (not all Pajek and GraphML files are supported, see documentation for details) - iterators totally rewritten, it is much faster and cleaner now - the RANDEDU fast motif search algorithm is implemented - many new graph generators, both games and regular graphs - many new structural properties: transitivity, reciprocity, etc. - graph operators: union, intersection, difference, structural holes, etc. - conversion between directed and undirected graphs - new layout algorithms for trees and large graphs, 3D layouts and many more. New things in the R package: - support for CTRL+C - new functions: Graph Laplacian, Burt's constraint, etc. - vertex/edge sequences totally rewritten, smart indexing (see manual) - new R manual and tutorial: 'Network Analysis with igraph', still under development but useful - very basic 3D plotting using OpenGL Although this release was somewhat tested on Linux, MS Windows, Mac OSX, Solaris 8 and FreeBSD, no heavy testing was done, so it might contain bugs, and we kindly ask you to send bug reports to make igraph better. igraph mailing lists ==================== Aug 18, 2006 I've set up two igraph mailing lists: igraph-help for general igraph questions and discussion and igraph-anonunce for announcements. See http://lists.nongnu.org/mailman/listinfo/igraph-help and http://lists.nongnu.org/mailman/listinfo/igraph-announce for subscription information, archives, etc. igraph 0.1 ========= Released Jan 30, 2006 After about a year of development this is the first "official" release of the igraph library. This release should be considered as beta software, but it should be useful in general. Please send your questions and comments. python-igraph-0.8.0/vendor/source/igraph/src/0000755000076500000240000000000013617375001021401 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/src/glet.c0000644000076500000240000007510213614300625022502 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2013 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_graphlets.h" #include "igraph_memory.h" #include "igraph_constructors.h" #include "igraph_cliques.h" #include "igraph_structural.h" #include "igraph_qsort.h" #include "igraph_conversion.h" /** * \section graphlets_intro Introduction * * * Graphlet decomposition models a weighted undirected graph * via the union of potentially overlapping dense social groups. * This is done by a two-step algorithm. In the first step, a candidate * set of groups (a candidate basis) is created by finding cliques * in the thresholded input graph. In the second step, * the graph is projected onto the candidate basis, resulting in a * weight coefficient for each clique in the candidate basis. * * * * For more information on graphlet decomposition, see * Hossein Azari Soufiani and Edoardo M Airoldi: "Graphlet decomposition of a weighted network", * https://arxiv.org/abs/1203.2821 and http://proceedings.mlr.press/v22/azari12/azari12.pdf * * * * igraph contains three functions for performing the graphlet * decomponsition of a graph. The first is \ref igraph_graphlets(), which * performs both steps of the method and returns a list of subgraphs * with their corresponding weights. The other two functions * correspond to the first and second steps of the algorithm, and they are * useful if the user wishes to perform them individually: * \ref igraph_graphlets_candidate_basis() and * \ref igraph_graphlets_project(). * * * * * Note: The term "graphlet" is used for several unrelated concepts * in the literature. If you are looking to count induced subgraphs, see * \ref igraph_motifs_randesu() and \ref igraph_subisomorphic_lad(). * * */ typedef struct { igraph_vector_int_t *resultids; igraph_t *result; igraph_vector_t *resultweights; int nc; } igraph_i_subclique_next_free_t; void igraph_i_subclique_next_free(void *ptr) { igraph_i_subclique_next_free_t *data = ptr; int i; if (data->resultids) { for (i = 0; i < data->nc; i++) { if (data->resultids + i) { igraph_vector_int_destroy(data->resultids + i); } } igraph_Free(data->resultids); } if (data->result) { for (i = 0; i < data->nc; i++) { if (data->result + i) { igraph_destroy(data->result + i); } } igraph_Free(data->result); } if (data->resultweights) { for (i = 0; i < data->nc; i++) { if (data->resultweights + i) { igraph_vector_destroy(data->resultweights + i); } } igraph_Free(data->resultweights); } } /** * \function igraph_i_subclique_next * Calculate subcliques of the cliques found at the previous level * * \param graph Input graph. * \param weight Edge weights. * \param ids The ids of the vertices in the input graph. * \param cliques A list of vectors, vertex ids for cliques. * \param result The result is stored here, a list of graphs is stored * here. * \param resultids The ids of the vertices in the result graphs is * stored here. * \param clique_thr The thresholds for the cliques are stored here, * if not a null pointer. * \param next_thr The next thresholds for the cliques are stored * here, if not a null pointer. * */ int igraph_i_subclique_next(const igraph_t *graph, const igraph_vector_t *weights, const igraph_vector_int_t *ids, const igraph_vector_ptr_t *cliques, igraph_t **result, igraph_vector_t **resultweights, igraph_vector_int_t **resultids, igraph_vector_t *clique_thr, igraph_vector_t *next_thr) { /* The input is a set of cliques, that were found at a previous level. For each clique, we calculate the next threshold, drop the isolate vertices, and create a new graph from them. */ igraph_vector_int_t mark, map; igraph_vector_int_t edges; igraph_vector_t neis, newedges; igraph_integer_t c, nc = igraph_vector_ptr_size(cliques); igraph_integer_t no_of_nodes = igraph_vcount(graph); igraph_integer_t no_of_edges = igraph_ecount(graph); igraph_i_subclique_next_free_t freedata = { 0, 0, 0, nc }; if (igraph_vector_size(weights) != no_of_edges) { IGRAPH_ERROR("Invalid length of weight vector", IGRAPH_EINVAL); } if (igraph_vector_int_size(ids) != no_of_nodes) { IGRAPH_ERROR("Invalid length of ID vector", IGRAPH_EINVAL); } IGRAPH_FINALLY(igraph_i_subclique_next_free, &freedata); *resultids = igraph_Calloc(nc, igraph_vector_int_t); if (!*resultids) { IGRAPH_ERROR("Cannot calculate next cliques", IGRAPH_ENOMEM); } freedata.resultids = *resultids; *resultweights = igraph_Calloc(nc, igraph_vector_t); if (!*resultweights) { IGRAPH_ERROR("Cannot calculate next cliques", IGRAPH_ENOMEM); } freedata.resultweights = *resultweights; *result = igraph_Calloc(nc, igraph_t); if (!*result) { IGRAPH_ERROR("Cannot calculate next cliques", IGRAPH_ENOMEM); } freedata.result = *result; igraph_vector_init(&newedges, 100); IGRAPH_FINALLY(igraph_vector_destroy, &newedges); igraph_vector_int_init(&mark, no_of_nodes); IGRAPH_FINALLY(igraph_vector_destroy, &mark); igraph_vector_int_init(&map, no_of_nodes); IGRAPH_FINALLY(igraph_vector_destroy, &map); igraph_vector_int_init(&edges, 100); IGRAPH_FINALLY(igraph_vector_int_destroy, &edges); igraph_vector_init(&neis, 10); IGRAPH_FINALLY(igraph_vector_destroy, &neis); if (clique_thr) { igraph_vector_resize(clique_thr, nc); } if (next_thr) { igraph_vector_resize(next_thr, nc); } /* Iterate over all cliques. We will create graphs for all subgraphs defined by the cliques. */ for (c = 0; c < nc; c++) { igraph_vector_t *clique = VECTOR(*cliques)[c]; igraph_real_t minweight = IGRAPH_INFINITY, nextweight = IGRAPH_INFINITY; igraph_integer_t e, v, clsize = igraph_vector_size(clique); igraph_integer_t noe, nov = 0; igraph_vector_int_t *newids = (*resultids) + c; igraph_vector_t *neww = (*resultweights) + c; igraph_t *newgraph = (*result) + c; igraph_vector_int_clear(&edges); igraph_vector_clear(&newedges); /* --------------------------------------------------- */ /* Iterate over the vertices of a clique and find the edges within the clique, put them in a list. At the same time, search for the minimum edge weight within the clique and the next edge weight if any. */ for (v = 0; v < clsize; v++) { igraph_integer_t i, neilen, node = VECTOR(*clique)[v]; igraph_incident(graph, &neis, node, IGRAPH_ALL); neilen = igraph_vector_size(&neis); VECTOR(mark)[node] = c + 1; for (i = 0; i < neilen; i++) { igraph_integer_t edge = VECTOR(neis)[i]; igraph_integer_t nei = IGRAPH_OTHER(graph, edge, node); if (VECTOR(mark)[nei] == c + 1) { igraph_real_t w = VECTOR(*weights)[edge]; igraph_vector_int_push_back(&edges, edge); if (w < minweight) { nextweight = minweight; minweight = w; } else if (w > minweight && w < nextweight) { nextweight = w; } } } } /* v < clsize */ /* --------------------------------------------------- */ /* OK, we have stored the edges and found the weight of the clique and the next weight to consider */ if (clique_thr) { VECTOR(*clique_thr)[c] = minweight; } if (next_thr) { VECTOR(*next_thr )[c] = nextweight; } /* --------------------------------------------------- */ /* Now we create the subgraph from the edges above the next threshold, and their incident vertices. */ igraph_vector_int_init(newids, 0); igraph_vector_init(neww, 0); /* We use mark[] to denote the vertices already mapped to the new graph. If this is -(c+1), then the vertex was mapped, otherwise it was not. The mapping itself is in map[]. */ noe = igraph_vector_int_size(&edges); for (e = 0; e < noe; e++) { igraph_integer_t edge = VECTOR(edges)[e]; igraph_integer_t from, to; igraph_real_t w = VECTOR(*weights)[edge]; igraph_edge(graph, edge, &from, &to); if (w >= nextweight) { if (VECTOR(mark)[from] == c + 1) { VECTOR(map)[from] = nov++; VECTOR(mark)[from] = -(c + 1); igraph_vector_int_push_back(newids, VECTOR(*ids)[from]); } if (VECTOR(mark)[to] == c + 1) { VECTOR(map)[to] = nov++; VECTOR(mark)[to] = -(c + 1); igraph_vector_int_push_back(newids, VECTOR(*ids)[to]); } igraph_vector_push_back(neww, w); igraph_vector_push_back(&newedges, VECTOR(map)[from]); igraph_vector_push_back(&newedges, VECTOR(map)[to]); } } igraph_create(newgraph, &newedges, nov, IGRAPH_UNDIRECTED); /* --------------------------------------------------- */ } /* c < nc */ igraph_vector_destroy(&neis); igraph_vector_int_destroy(&edges); igraph_vector_int_destroy(&mark); igraph_vector_int_destroy(&map); igraph_vector_destroy(&newedges); IGRAPH_FINALLY_CLEAN(6); /* + freedata */ return 0; } void igraph_i_graphlets_destroy_vectorlist(igraph_vector_ptr_t *vl) { int i, n = igraph_vector_ptr_size(vl); for (i = 0; i < n; i++) { igraph_vector_t *v = (igraph_vector_t*) VECTOR(*vl)[i]; if (v) { igraph_vector_destroy(v); } } igraph_vector_ptr_destroy(vl); } int igraph_i_graphlets(const igraph_t *graph, const igraph_vector_t *weights, igraph_vector_ptr_t *cliques, igraph_vector_t *thresholds, const igraph_vector_int_t *ids, igraph_real_t startthr) { /* This version is different from the main function, and is appropriate to use in recursive calls, because it _adds_ the results to 'cliques' and 'thresholds' and uses the supplied 'startthr' */ igraph_vector_ptr_t mycliques; int no_of_edges = igraph_ecount(graph); igraph_vector_t subv; igraph_t subg; int i, nographs, nocliques; igraph_t *newgraphs = 0; igraph_vector_t *newweights = 0; igraph_vector_int_t *newids = 0; igraph_vector_t clique_thr, next_thr; igraph_i_subclique_next_free_t freedata = { 0, 0, 0, 0 }; IGRAPH_CHECK(igraph_vector_ptr_init(&mycliques, 0)); IGRAPH_FINALLY(igraph_i_graphlets_destroy_vectorlist, &mycliques); IGRAPH_VECTOR_INIT_FINALLY(&subv, 0); /* We start by finding cliques at the lowest threshold */ for (i = 0; i < no_of_edges; i++) { if (VECTOR(*weights)[i] >= startthr) { IGRAPH_CHECK(igraph_vector_push_back(&subv, i)); } } igraph_subgraph_edges(graph, &subg, igraph_ess_vector(&subv), /*delete_vertices=*/ 0); IGRAPH_FINALLY(igraph_destroy, &subg); igraph_maximal_cliques(&subg, &mycliques, /*min_size=*/ 0, /*max_size=*/ 0); igraph_destroy(&subg); IGRAPH_FINALLY_CLEAN(1); nocliques = igraph_vector_ptr_size(&mycliques); igraph_vector_destroy(&subv); IGRAPH_FINALLY_CLEAN(1); /* Get the next cliques and thresholds */ IGRAPH_VECTOR_INIT_FINALLY(&next_thr, 0); IGRAPH_VECTOR_INIT_FINALLY(&clique_thr, 0); igraph_i_subclique_next(graph, weights, ids, &mycliques, &newgraphs, &newweights, &newids, &clique_thr, &next_thr); freedata.result = newgraphs; freedata.resultids = newids; freedata.resultweights = newweights; freedata.nc = nocliques; IGRAPH_FINALLY(igraph_i_subclique_next_free, &freedata); /* Store cliques at the current level */ igraph_vector_append(thresholds, &clique_thr); for (i = 0; i < nocliques; i++) { igraph_vector_t *cl = (igraph_vector_t*) VECTOR(mycliques)[i]; int j, n = igraph_vector_size(cl); for (j = 0; j < n; j++) { int node = VECTOR(*cl)[j]; VECTOR(*cl)[j] = VECTOR(*ids)[node]; } igraph_vector_sort(cl); } igraph_vector_ptr_append(cliques, &mycliques); /* Recursive calls for cliques found */ nographs = igraph_vector_ptr_size(&mycliques); for (i = 0; i < nographs; i++) { igraph_t *g = newgraphs + i; if (igraph_vcount(g) > 1) { igraph_vector_t *w = newweights + i; igraph_vector_int_t *ids = newids + i; igraph_i_graphlets(g, w, cliques, thresholds, ids, VECTOR(next_thr)[i]); } } igraph_vector_destroy(&clique_thr); igraph_vector_destroy(&next_thr); igraph_i_subclique_next_free(&freedata); igraph_vector_ptr_destroy(&mycliques); /* contents was copied over */ IGRAPH_FINALLY_CLEAN(4); return 0; } typedef struct { const igraph_vector_ptr_t *cliques; const igraph_vector_t *thresholds; } igraph_i_graphlets_filter_t; int igraph_i_graphlets_filter_cmp(void *data, const void *a, const void *b) { igraph_i_graphlets_filter_t *ddata = (igraph_i_graphlets_filter_t *) data; int *aa = (int*) a; int *bb = (int*) b; igraph_real_t t_a = VECTOR(*ddata->thresholds)[*aa]; igraph_real_t t_b = VECTOR(*ddata->thresholds)[*bb]; igraph_vector_t *v_a, *v_b; int s_a, s_b; if (t_a < t_b) { return -1; } else if (t_a > t_b) { return 1; } v_a = (igraph_vector_t*) VECTOR(*ddata->cliques)[*aa]; v_b = (igraph_vector_t*) VECTOR(*ddata->cliques)[*bb]; s_a = igraph_vector_size(v_a); s_b = igraph_vector_size(v_b); if (s_a < s_b) { return -1; } else if (s_a > s_b) { return 1; } else { return 0; } } int igraph_i_graphlets_filter(igraph_vector_ptr_t *cliques, igraph_vector_t *thresholds) { /* Filter out non-maximal cliques. Every non-maximal clique is part of a maximal clique, at the same threshold. First we order the cliques, according to their threshold, and then according to their size. So when we look for a candidate superset, we only need to check the cliques next in the list, until their threshold is different. */ int i, iptr, nocliques = igraph_vector_ptr_size(cliques); igraph_vector_int_t order; igraph_i_graphlets_filter_t sortdata = { cliques, thresholds }; igraph_vector_int_init(&order, nocliques); IGRAPH_FINALLY(igraph_vector_int_destroy, &order); for (i = 0; i < nocliques; i++) { VECTOR(order)[i] = i; } igraph_qsort_r(VECTOR(order), nocliques, sizeof(int), &sortdata, igraph_i_graphlets_filter_cmp); for (i = 0; i < nocliques - 1; i++) { int ri = VECTOR(order)[i]; igraph_vector_t *needle = VECTOR(*cliques)[ri]; igraph_real_t thr_i = VECTOR(*thresholds)[ri]; int n_i = igraph_vector_size(needle); int j = i + 1; for (j = i + 1; j < nocliques; j++) { int rj = VECTOR(order)[j]; igraph_real_t thr_j = VECTOR(*thresholds)[rj]; igraph_vector_t *hay; int n_j, pi = 0, pj = 0; /* Done, not found */ if (thr_j != thr_i) { break; } /* Check size of hay */ hay = VECTOR(*cliques)[rj]; n_j = igraph_vector_size(hay); if (n_i > n_j) { continue; } /* Check if hay is a superset */ while (pi < n_i && pj < n_j && n_i - pi <= n_j - pj) { int ei = VECTOR(*needle)[pi]; int ej = VECTOR(*hay)[pj]; if (ei < ej) { break; } else if (ei > ej) { pj++; } else { pi++; pj++; } } if (pi == n_i) { /* Found, delete immediately */ igraph_vector_destroy(needle); igraph_free(needle); VECTOR(*cliques)[ri] = 0; break; } } } /* Remove null pointers from the list of cliques */ for (i = 0, iptr = 0; i < nocliques; i++) { igraph_vector_t *v = VECTOR(*cliques)[i]; if (v) { VECTOR(*cliques)[iptr] = v; VECTOR(*thresholds)[iptr] = VECTOR(*thresholds)[i]; iptr++; } } igraph_vector_ptr_resize(cliques, iptr); igraph_vector_resize(thresholds, iptr); igraph_vector_int_destroy(&order); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_graphlets_candidate_basis * Calculate a candidate graphlets basis * * \param graph The input graph, it must be a simple graph, edge directions are * ignored. * \param weights Weights of the edges, a vector. * \param cliques An initialized vector of pointers. * The graphlet basis is stored here. Each element of the pointer * vector will be a vector of vertex ids. Each elements must be * destroyed using \ref igraph_vector_destroy() and \ref igraph_free(). * \param thresholds An initialized vector, the (highest possible) * weight thresholds for finding the basis subgraphs are stored * here. * \return Error code. * * See also: \ref igraph_graphlets() and \ref igraph_graphlets_project(). */ int igraph_graphlets_candidate_basis(const igraph_t *graph, const igraph_vector_t *weights, igraph_vector_ptr_t *cliques, igraph_vector_t *thresholds) { int no_of_nodes = igraph_vcount(graph); int no_of_edges = igraph_ecount(graph); igraph_real_t minthr; igraph_vector_int_t ids; igraph_bool_t simple; int i; /* Some checks */ if (weights == NULL) { IGRAPH_ERROR("Graphlet functions require weighted graphs", IGRAPH_EINVAL); } if (igraph_vector_size(weights) != no_of_edges) { IGRAPH_ERROR("Invalid weight vector length", IGRAPH_EINVAL); } igraph_is_simple(graph, &simple); if (!simple) { IGRAPH_ERROR("Graphlets work on simple graphs only", IGRAPH_EINVAL); } minthr = igraph_vector_min(weights); igraph_vector_ptr_clear(cliques); igraph_vector_clear(thresholds); igraph_vector_int_init(&ids, no_of_nodes); IGRAPH_FINALLY(igraph_vector_int_destroy, &ids); for (i = 0; i < no_of_nodes; i++) { VECTOR(ids)[i] = i; } igraph_i_graphlets(graph, weights, cliques, thresholds, &ids, minthr); igraph_vector_int_destroy(&ids); IGRAPH_FINALLY_CLEAN(1); igraph_i_graphlets_filter(cliques, thresholds); return 0; } int igraph_i_graphlets_project(const igraph_t *graph, const igraph_vector_t *weights, const igraph_vector_ptr_t *cliques, igraph_vector_t *Mu, igraph_bool_t startMu, int niter, int vid1) { int no_of_nodes = igraph_vcount(graph); int no_of_edges = igraph_ecount(graph); int no_cliques = igraph_vector_ptr_size(cliques); igraph_vector_int_t vcl, vclidx, ecl, eclidx, cel, celidx; igraph_vector_t edgelist, newweights, normfact; int i, total_vertices, e, ptr, total_edges; igraph_bool_t simple; /* Check arguments */ if (weights == NULL) { IGRAPH_ERROR("Graphlet functions require weighted graphs", IGRAPH_EINVAL); } if (no_of_edges != igraph_vector_size(weights)) { IGRAPH_ERROR("Invalid weight vector size", IGRAPH_EINVAL); } if (startMu && igraph_vector_size(Mu) != no_cliques) { IGRAPH_ERROR("Invalid start coefficient vector size", IGRAPH_EINVAL); } if (niter < 0) { IGRAPH_ERROR("Number of iterations must be non-negative", IGRAPH_EINVAL); } igraph_is_simple(graph, &simple); if (!simple) { IGRAPH_ERROR("Graphlets work on simple graphs only", IGRAPH_EINVAL); } if (!startMu) { igraph_vector_resize(Mu, no_cliques); igraph_vector_fill(Mu, 1); } /* Count # cliques per vertex. Also, create an index for the edges per clique. */ IGRAPH_CHECK(igraph_vector_int_init(&vclidx, no_of_nodes + 2)); IGRAPH_FINALLY(igraph_vector_int_destroy, &vclidx); IGRAPH_CHECK(igraph_vector_int_init(&celidx, no_cliques + 3)); IGRAPH_FINALLY(igraph_vector_int_destroy, &celidx); for (i = 0, total_vertices = 0, total_edges = 0; i < no_cliques; i++) { igraph_vector_t *v = VECTOR(*cliques)[i]; int j, n = igraph_vector_size(v); total_vertices += n; total_edges += n * (n - 1) / 2; VECTOR(celidx)[i + 2] = total_edges; for (j = 0; j < n; j++) { int vv = VECTOR(*v)[j] - vid1; VECTOR(vclidx)[vv + 2] += 1; } } VECTOR(celidx)[i + 2] = total_edges; /* Finalize index vector */ for (i = 0; i < no_of_nodes; i++) { VECTOR(vclidx)[i + 2] += VECTOR(vclidx)[i + 1]; } /* Create vertex-clique list, the cliques for each vertex. */ IGRAPH_CHECK(igraph_vector_int_init(&vcl, total_vertices)); IGRAPH_FINALLY(igraph_vector_int_destroy, &vcl); for (i = 0; i < no_cliques; i++) { igraph_vector_t *v = VECTOR(*cliques)[i]; int j, n = igraph_vector_size(v); for (j = 0; j < n; j++) { int vv = VECTOR(*v)[j] - vid1; int p = VECTOR(vclidx)[vv + 1]; VECTOR(vcl)[p] = i; VECTOR(vclidx)[vv + 1] += 1; } } /* Create an edge-clique list, the cliques of each edge */ IGRAPH_CHECK(igraph_vector_int_init(&ecl, total_edges)); IGRAPH_FINALLY(igraph_vector_int_destroy, &ecl); IGRAPH_CHECK(igraph_vector_int_init(&eclidx, no_of_edges + 1)); IGRAPH_FINALLY(igraph_vector_int_destroy, &eclidx); IGRAPH_CHECK(igraph_vector_init(&edgelist, no_of_edges * 2)); IGRAPH_FINALLY(igraph_vector_destroy, &edgelist); IGRAPH_CHECK(igraph_get_edgelist(graph, &edgelist, /*by_col=*/ 0)); for (i = 0, e = 0, ptr = 0; e < no_of_edges; e++) { int from = VECTOR(edgelist)[i++]; int to = VECTOR(edgelist)[i++]; int from_s = VECTOR(vclidx)[from]; int from_e = VECTOR(vclidx)[from + 1]; int to_s = VECTOR(vclidx)[to]; int to_e = VECTOR(vclidx)[to + 1]; VECTOR(eclidx)[e] = ptr; while (from_s < from_e && to_s < to_e) { int from_v = VECTOR(vcl)[from_s]; int to_v = VECTOR(vcl)[to_s]; if (from_v == to_v) { VECTOR(ecl)[ptr++] = from_v; from_s++; to_s++; } else if (from_v < to_v) { from_s++; } else { to_s++; } } } VECTOR(eclidx)[e] = ptr; igraph_vector_destroy(&edgelist); IGRAPH_FINALLY_CLEAN(1); /* Convert the edge-clique list to a clique-edge list */ IGRAPH_CHECK(igraph_vector_int_init(&cel, total_edges)); IGRAPH_FINALLY(igraph_vector_int_destroy, &cel); for (i = 0; i < no_of_edges; i++) { int ecl_s = VECTOR(eclidx)[i], ecl_e = VECTOR(eclidx)[i + 1], j; for (j = ecl_s; j < ecl_e; j++) { int cl = VECTOR(ecl)[j]; int epos = VECTOR(celidx)[cl + 1]; VECTOR(cel)[epos] = i; VECTOR(celidx)[cl + 1] += 1; } } /* Normalizing factors for the iteration */ IGRAPH_CHECK(igraph_vector_init(&normfact, no_cliques)); IGRAPH_FINALLY(igraph_vector_destroy, &normfact); for (i = 0; i < no_cliques; i++) { igraph_vector_t *v = VECTOR(*cliques)[i]; int n = igraph_vector_size(v); VECTOR(normfact)[i] = n * (n + 1) / 2; } /* We have the clique-edge list, so do the projection now */ IGRAPH_CHECK(igraph_vector_init(&newweights, no_of_edges)); IGRAPH_FINALLY(igraph_vector_destroy, &newweights); for (i = 0; i < niter; i++) { for (e = 0; e < no_of_edges; e++) { int start = VECTOR(eclidx)[e]; int end = VECTOR(eclidx)[e + 1]; VECTOR(newweights)[e] = 0.0001; while (start < end) { int clique = VECTOR(ecl)[start++]; VECTOR(newweights)[e] += VECTOR(*Mu)[clique]; } } for (e = 0; e < no_cliques; e++) { igraph_real_t sumratio = 0; int start = VECTOR(celidx)[e]; int end = VECTOR(celidx)[e + 1]; while (start < end) { int edge = VECTOR(cel)[start++]; sumratio += VECTOR(*weights)[edge] / VECTOR(newweights)[edge]; } VECTOR(*Mu)[e] *= sumratio / VECTOR(normfact)[e]; } } igraph_vector_destroy(&newweights); igraph_vector_destroy(&normfact); igraph_vector_int_destroy(&cel); igraph_vector_int_destroy(&eclidx); igraph_vector_int_destroy(&ecl); igraph_vector_int_destroy(&vcl); igraph_vector_int_destroy(&celidx); igraph_vector_int_destroy(&vclidx); IGRAPH_FINALLY_CLEAN(8); return 0; } /** * \function igraph_graphlets_project * Project a graph on a graphlets basis * * Note that the graph projected does not have to be the same that * was used to calculate the graphlet basis, but it is assumed that * it has the same number of vertices, and the vertex ids of the two * graphs match. * \param graph The input graph, it must be a simple graph, edge directions are * ignored. * \param weights Weights of the edges in the input graph, a vector. * \param cliques The graphlet basis, a pointer vector, in which each * element is a vector of vertex ids. * \param Mu An initialized vector, the weights of the graphlets will * be stored here. This vector is also used to initialize the * the weight vector for the iterative algorithm, if the * \c startMu argument is true (non-zero). * \param startMu If true (non-zero), then the supplied Mu vector is * used as the starting point of the iteration. Otherwise a * constant 1 vector is used. * \param niter Integer scalar, the number of iterations to perform. * \return Error code. * * See also: \ref igraph_graphlets() and * \ref igraph_graphlets_candidate_basis(). */ int igraph_graphlets_project(const igraph_t *graph, const igraph_vector_t *weights, const igraph_vector_ptr_t *cliques, igraph_vector_t *Mu, igraph_bool_t startMu, int niter) { return igraph_i_graphlets_project(graph, weights, cliques, Mu, startMu, niter, /*vid1=*/ 0); } typedef struct igraph_i_graphlets_order_t { const igraph_vector_ptr_t *cliques; const igraph_vector_t *Mu; } igraph_i_graphlets_order_t; int igraph_i_graphlets_order_cmp(void *data, const void *a, const void *b) { igraph_i_graphlets_order_t *ddata = (igraph_i_graphlets_order_t*) data; int *aa = (int*) a; int *bb = (int*) b; igraph_real_t Mu_a = VECTOR(*ddata->Mu)[*aa]; igraph_real_t Mu_b = VECTOR(*ddata->Mu)[*bb]; if (Mu_a < Mu_b) { return 1; } else if (Mu_a > Mu_b) { return -1; } else { return 0; } } /** * \function igraph_graphlets * Calculate graphlets basis and project the graph on it * * This function simply calls \ref igraph_graphlets_candidate_basis() * and \ref igraph_graphlets_project(), and then orders the graphlets * according to decreasing weights. * \param graph The input graph, it must be a simple graph, edge directions are * ignored. * \param weights Weights of the edges, a vector. * \param cliques An initialized vector of pointers. * The graphlet basis is stored here. Each element of the pointer * vector will be a vector of vertex ids. * \param Mu An initialized vector, the weights of the graphlets will * be stored here. * \param niter Integer scalar, the number of iterations to perform * for the projection step. * \return Error code. * * See also: \ref igraph_graphlets_candidate_basis() and * \ref igraph_graphlets_project(). */ int igraph_graphlets(const igraph_t *graph, const igraph_vector_t *weights, igraph_vector_ptr_t *cliques, igraph_vector_t *Mu, int niter) { int i, nocliques; igraph_vector_t thresholds; igraph_vector_int_t order; igraph_i_graphlets_order_t sortdata = { cliques, Mu }; igraph_vector_init(&thresholds, 0); IGRAPH_FINALLY(igraph_vector_destroy, &thresholds); igraph_graphlets_candidate_basis(graph, weights, cliques, &thresholds); igraph_vector_destroy(&thresholds); IGRAPH_FINALLY_CLEAN(1); igraph_graphlets_project(graph, weights, cliques, Mu, /*startMu=*/ 0, niter); nocliques = igraph_vector_ptr_size(cliques); igraph_vector_int_init(&order, nocliques); IGRAPH_FINALLY(igraph_vector_int_destroy, &order); for (i = 0; i < nocliques; i++) { VECTOR(order)[i] = i; } igraph_qsort_r(VECTOR(order), nocliques, sizeof(int), &sortdata, igraph_i_graphlets_order_cmp); igraph_vector_ptr_index_int(cliques, &order); igraph_vector_index_int(Mu, &order); igraph_vector_int_destroy(&order); IGRAPH_FINALLY_CLEAN(1); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/plfit/0000755000076500000240000000000013617375001022517 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/src/plfit/error.h0000644000076500000240000000473013524616145024031 0ustar tamasstaff00000000000000/* error.h * * Copyright (C) 2010-2011 Tamas Nepusz * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 3 of the License, or (at * your option) any later version. * * This program is distributed in the hope that it will be useful, but * WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. */ #ifndef __ERROR_H__ #define __ERROR_H__ #undef __BEGIN_DECLS #undef __END_DECLS #ifdef __cplusplus # define __BEGIN_DECLS extern "C" { # define __END_DECLS } #else # define __BEGIN_DECLS /* empty */ # define __END_DECLS /* empty */ #endif __BEGIN_DECLS enum { PLFIT_SUCCESS = 0, PLFIT_FAILURE = 1, PLFIT_EINVAL = 2, PLFIT_UNDRFLOW = 3, PLFIT_OVERFLOW = 4, PLFIT_ENOMEM = 5 }; #if (defined(__GNUC__) && GCC_VERSION_MAJOR >= 3) # define PLFIT_UNLIKELY(a) __builtin_expect((a), 0) # define PLFIT_LIKELY(a) __builtin_expect((a), 1) #else # define PLFIT_UNLIKELY(a) a # define PLFIT_LIKELY(a) a #endif #define PLFIT_CHECK(a) \ do {\ int plfit_i_ret=(a); \ if (PLFIT_UNLIKELY(plfit_i_ret != PLFIT_SUCCESS)) {\ return plfit_i_ret; \ } \ } while(0) #define PLFIT_ERROR(reason,plfit_errno) \ do {\ plfit_error (reason, __FILE__, __LINE__, plfit_errno) ; \ return plfit_errno ; \ } while (0) typedef void plfit_error_handler_t(const char*, const char*, int, int); extern plfit_error_handler_t plfit_error_handler_abort; extern plfit_error_handler_t plfit_error_handler_ignore; extern plfit_error_handler_t plfit_error_handler_printignore; plfit_error_handler_t* plfit_set_error_handler(plfit_error_handler_t* new_handler); void plfit_error(const char *reason, const char *file, int line, int plfit_errno); const char* plfit_strerror(const int plfit_errno); void plfit_error_handler_abort(const char *reason, const char *file, int line, int plfit_errno); void plfit_error_handler_ignore(const char *reason, const char *file, int line, int plfit_errno); void plfit_error_handler_printignore(const char *reason, const char *file, int line, int plfit_errno); __END_DECLS #endif /* __ERROR_H__ */ python-igraph-0.8.0/vendor/source/igraph/src/plfit/zeta.h0000644000076500000240000000265013524616145023642 0ustar tamasstaff00000000000000/* specfunc/gsl_sf_zeta.h * * Copyright (C) 1996, 1997, 1998, 1999, 2000, 2004 Gerard Jungman * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 3 of the License, or (at * your option) any later version. * * This program is distributed in the hope that it will be useful, but * WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. */ /* Author: G. Jungman */ /* This file was taken from the GNU Scientific Library. Some modifications * were done in order to make it independent from the rest of GSL */ #ifndef __ZETA_H__ #define __ZETA_H__ #undef __BEGIN_DECLS #undef __END_DECLS #ifdef __cplusplus # define __BEGIN_DECLS extern "C" { # define __END_DECLS } #else # define __BEGIN_DECLS /* empty */ # define __END_DECLS /* empty */ #endif __BEGIN_DECLS /* Hurwitz Zeta Function * zeta(s,q) = Sum[ (k+q)^(-s), {k,0,Infinity} ] * * s > 1.0, q > 0.0 */ double gsl_sf_hzeta(const double s, const double q); __END_DECLS #endif /* __ZETA_H__ */ python-igraph-0.8.0/vendor/source/igraph/src/plfit/arithmetic_sse_float.h0000644000076500000240000002122513524616145027066 0ustar tamasstaff00000000000000/* * SSE/SSE3 implementation of vector oprations (32bit float). * * Copyright (c) 2007-2010 Naoaki Okazaki * All rights reserved. * * Permission is hereby granted, free of charge, to any person obtaining a copy * of this software and associated documentation files (the "Software"), to deal * in the Software without restriction, including without limitation the rights * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell * copies of the Software, and to permit persons to whom the Software is * furnished to do so, subject to the following conditions: * * The above copyright notice and this permission notice shall be included in * all copies or substantial portions of the Software. * * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN * THE SOFTWARE. */ /* $Id: arithmetic_sse_float.h 65 2010-01-29 12:19:16Z naoaki $ */ #include #if !defined(__APPLE__) #include #endif #include #if 1400 <= _MSC_VER #include #endif/*_MSC_VER*/ #if HAVE_XMMINTRIN_H #include #endif/*HAVE_XMMINTRIN_H*/ #if LBFGS_FLOAT == 32 && LBFGS_IEEE_FLOAT #define fsigndiff(x, y) (((*(uint32_t*)(x)) ^ (*(uint32_t*)(y))) & 0x80000000U) #else #define fsigndiff(x, y) (*(x) * (*(y) / fabs(*(y))) < 0.) #endif/*LBFGS_IEEE_FLOAT*/ inline static void* vecalloc(size_t size) { void *memblock = _aligned_malloc(size, 16); if (memblock != NULL) { memset(memblock, 0, size); } return memblock; } inline static void vecfree(void *memblock) { _aligned_free(memblock); } #define vecset(x, c, n) \ { \ int i; \ __m128 XMM0 = _mm_set_ps1(c); \ for (i = 0;i < (n);i += 16) { \ _mm_store_ps((x)+i , XMM0); \ _mm_store_ps((x)+i+ 4, XMM0); \ _mm_store_ps((x)+i+ 8, XMM0); \ _mm_store_ps((x)+i+12, XMM0); \ } \ } #define veccpy(y, x, n) \ { \ int i; \ for (i = 0;i < (n);i += 16) { \ __m128 XMM0 = _mm_load_ps((x)+i ); \ __m128 XMM1 = _mm_load_ps((x)+i+ 4); \ __m128 XMM2 = _mm_load_ps((x)+i+ 8); \ __m128 XMM3 = _mm_load_ps((x)+i+12); \ _mm_store_ps((y)+i , XMM0); \ _mm_store_ps((y)+i+ 4, XMM1); \ _mm_store_ps((y)+i+ 8, XMM2); \ _mm_store_ps((y)+i+12, XMM3); \ } \ } #define vecncpy(y, x, n) \ { \ int i; \ const uint32_t mask = 0x80000000; \ __m128 XMM4 = _mm_load_ps1((float*)&mask); \ for (i = 0;i < (n);i += 16) { \ __m128 XMM0 = _mm_load_ps((x)+i ); \ __m128 XMM1 = _mm_load_ps((x)+i+ 4); \ __m128 XMM2 = _mm_load_ps((x)+i+ 8); \ __m128 XMM3 = _mm_load_ps((x)+i+12); \ XMM0 = _mm_xor_ps(XMM0, XMM4); \ XMM1 = _mm_xor_ps(XMM1, XMM4); \ XMM2 = _mm_xor_ps(XMM2, XMM4); \ XMM3 = _mm_xor_ps(XMM3, XMM4); \ _mm_store_ps((y)+i , XMM0); \ _mm_store_ps((y)+i+ 4, XMM1); \ _mm_store_ps((y)+i+ 8, XMM2); \ _mm_store_ps((y)+i+12, XMM3); \ } \ } #define vecadd(y, x, c, n) \ { \ int i; \ __m128 XMM7 = _mm_set_ps1(c); \ for (i = 0;i < (n);i += 8) { \ __m128 XMM0 = _mm_load_ps((x)+i ); \ __m128 XMM1 = _mm_load_ps((x)+i+4); \ __m128 XMM2 = _mm_load_ps((y)+i ); \ __m128 XMM3 = _mm_load_ps((y)+i+4); \ XMM0 = _mm_mul_ps(XMM0, XMM7); \ XMM1 = _mm_mul_ps(XMM1, XMM7); \ XMM2 = _mm_add_ps(XMM2, XMM0); \ XMM3 = _mm_add_ps(XMM3, XMM1); \ _mm_store_ps((y)+i , XMM2); \ _mm_store_ps((y)+i+4, XMM3); \ } \ } #define vecdiff(z, x, y, n) \ { \ int i; \ for (i = 0;i < (n);i += 16) { \ __m128 XMM0 = _mm_load_ps((x)+i ); \ __m128 XMM1 = _mm_load_ps((x)+i+ 4); \ __m128 XMM2 = _mm_load_ps((x)+i+ 8); \ __m128 XMM3 = _mm_load_ps((x)+i+12); \ __m128 XMM4 = _mm_load_ps((y)+i ); \ __m128 XMM5 = _mm_load_ps((y)+i+ 4); \ __m128 XMM6 = _mm_load_ps((y)+i+ 8); \ __m128 XMM7 = _mm_load_ps((y)+i+12); \ XMM0 = _mm_sub_ps(XMM0, XMM4); \ XMM1 = _mm_sub_ps(XMM1, XMM5); \ XMM2 = _mm_sub_ps(XMM2, XMM6); \ XMM3 = _mm_sub_ps(XMM3, XMM7); \ _mm_store_ps((z)+i , XMM0); \ _mm_store_ps((z)+i+ 4, XMM1); \ _mm_store_ps((z)+i+ 8, XMM2); \ _mm_store_ps((z)+i+12, XMM3); \ } \ } #define vecscale(y, c, n) \ { \ int i; \ __m128 XMM7 = _mm_set_ps1(c); \ for (i = 0;i < (n);i += 8) { \ __m128 XMM0 = _mm_load_ps((y)+i ); \ __m128 XMM1 = _mm_load_ps((y)+i+4); \ XMM0 = _mm_mul_ps(XMM0, XMM7); \ XMM1 = _mm_mul_ps(XMM1, XMM7); \ _mm_store_ps((y)+i , XMM0); \ _mm_store_ps((y)+i+4, XMM1); \ } \ } #define vecmul(y, x, n) \ { \ int i; \ for (i = 0;i < (n);i += 16) { \ __m128 XMM0 = _mm_load_ps((x)+i ); \ __m128 XMM1 = _mm_load_ps((x)+i+ 4); \ __m128 XMM2 = _mm_load_ps((x)+i+ 8); \ __m128 XMM3 = _mm_load_ps((x)+i+12); \ __m128 XMM4 = _mm_load_ps((y)+i ); \ __m128 XMM5 = _mm_load_ps((y)+i+ 4); \ __m128 XMM6 = _mm_load_ps((y)+i+ 8); \ __m128 XMM7 = _mm_load_ps((y)+i+12); \ XMM4 = _mm_mul_ps(XMM4, XMM0); \ XMM5 = _mm_mul_ps(XMM5, XMM1); \ XMM6 = _mm_mul_ps(XMM6, XMM2); \ XMM7 = _mm_mul_ps(XMM7, XMM3); \ _mm_store_ps((y)+i , XMM4); \ _mm_store_ps((y)+i+ 4, XMM5); \ _mm_store_ps((y)+i+ 8, XMM6); \ _mm_store_ps((y)+i+12, XMM7); \ } \ } #if 3 <= __SSE__ /* Horizontal add with haddps SSE3 instruction. The work register (rw) is unused. */ #define __horizontal_sum(r, rw) \ r = _mm_hadd_ps(r, r); \ r = _mm_hadd_ps(r, r); #else /* Horizontal add with SSE instruction. The work register (rw) is used. */ #define __horizontal_sum(r, rw) \ rw = r; \ r = _mm_shuffle_ps(r, rw, _MM_SHUFFLE(1, 0, 3, 2)); \ r = _mm_add_ps(r, rw); \ rw = r; \ r = _mm_shuffle_ps(r, rw, _MM_SHUFFLE(2, 3, 0, 1)); \ r = _mm_add_ps(r, rw); #endif #define vecdot(s, x, y, n) \ { \ int i; \ __m128 XMM0 = _mm_setzero_ps(); \ __m128 XMM1 = _mm_setzero_ps(); \ __m128 XMM2, XMM3, XMM4, XMM5; \ for (i = 0;i < (n);i += 8) { \ XMM2 = _mm_load_ps((x)+i ); \ XMM3 = _mm_load_ps((x)+i+4); \ XMM4 = _mm_load_ps((y)+i ); \ XMM5 = _mm_load_ps((y)+i+4); \ XMM2 = _mm_mul_ps(XMM2, XMM4); \ XMM3 = _mm_mul_ps(XMM3, XMM5); \ XMM0 = _mm_add_ps(XMM0, XMM2); \ XMM1 = _mm_add_ps(XMM1, XMM3); \ } \ XMM0 = _mm_add_ps(XMM0, XMM1); \ __horizontal_sum(XMM0, XMM1); \ _mm_store_ss((s), XMM0); \ } #define vec2norm(s, x, n) \ { \ int i; \ __m128 XMM0 = _mm_setzero_ps(); \ __m128 XMM1 = _mm_setzero_ps(); \ __m128 XMM2, XMM3; \ for (i = 0;i < (n);i += 8) { \ XMM2 = _mm_load_ps((x)+i ); \ XMM3 = _mm_load_ps((x)+i+4); \ XMM2 = _mm_mul_ps(XMM2, XMM2); \ XMM3 = _mm_mul_ps(XMM3, XMM3); \ XMM0 = _mm_add_ps(XMM0, XMM2); \ XMM1 = _mm_add_ps(XMM1, XMM3); \ } \ XMM0 = _mm_add_ps(XMM0, XMM1); \ __horizontal_sum(XMM0, XMM1); \ XMM2 = XMM0; \ XMM1 = _mm_rsqrt_ss(XMM0); \ XMM3 = XMM1; \ XMM1 = _mm_mul_ss(XMM1, XMM1); \ XMM1 = _mm_mul_ss(XMM1, XMM3); \ XMM1 = _mm_mul_ss(XMM1, XMM0); \ XMM1 = _mm_mul_ss(XMM1, _mm_set_ss(-0.5f)); \ XMM3 = _mm_mul_ss(XMM3, _mm_set_ss(1.5f)); \ XMM3 = _mm_add_ss(XMM3, XMM1); \ XMM3 = _mm_mul_ss(XMM3, XMM2); \ _mm_store_ss((s), XMM3); \ } #define vec2norminv(s, x, n) \ { \ int i; \ __m128 XMM0 = _mm_setzero_ps(); \ __m128 XMM1 = _mm_setzero_ps(); \ __m128 XMM2, XMM3; \ for (i = 0;i < (n);i += 16) { \ XMM2 = _mm_load_ps((x)+i ); \ XMM3 = _mm_load_ps((x)+i+4); \ XMM2 = _mm_mul_ps(XMM2, XMM2); \ XMM3 = _mm_mul_ps(XMM3, XMM3); \ XMM0 = _mm_add_ps(XMM0, XMM2); \ XMM1 = _mm_add_ps(XMM1, XMM3); \ } \ XMM0 = _mm_add_ps(XMM0, XMM1); \ __horizontal_sum(XMM0, XMM1); \ XMM2 = XMM0; \ XMM1 = _mm_rsqrt_ss(XMM0); \ XMM3 = XMM1; \ XMM1 = _mm_mul_ss(XMM1, XMM1); \ XMM1 = _mm_mul_ss(XMM1, XMM3); \ XMM1 = _mm_mul_ss(XMM1, XMM0); \ XMM1 = _mm_mul_ss(XMM1, _mm_set_ss(-0.5f)); \ XMM3 = _mm_mul_ss(XMM3, _mm_set_ss(1.5f)); \ XMM3 = _mm_add_ss(XMM3, XMM1); \ _mm_store_ss((s), XMM3); \ } python-igraph-0.8.0/vendor/source/igraph/src/plfit/arithmetic_ansi.h0000644000076500000240000000654713524616145026053 0ustar tamasstaff00000000000000/* * ANSI C implementation of vector operations. * * Copyright (c) 2007-2010 Naoaki Okazaki * All rights reserved. * * Permission is hereby granted, free of charge, to any person obtaining a copy * of this software and associated documentation files (the "Software"), to deal * in the Software without restriction, including without limitation the rights * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell * copies of the Software, and to permit persons to whom the Software is * furnished to do so, subject to the following conditions: * * The above copyright notice and this permission notice shall be included in * all copies or substantial portions of the Software. * * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN * THE SOFTWARE. */ /* $Id: arithmetic_ansi.h 65 2010-01-29 12:19:16Z naoaki $ */ #include #include #if LBFGS_FLOAT == 32 && LBFGS_IEEE_FLOAT #define fsigndiff(x, y) (((*(uint32_t*)(x)) ^ (*(uint32_t*)(y))) & 0x80000000U) #else #define fsigndiff(x, y) (*(x) * (*(y) / fabs(*(y))) < 0.) #endif/*LBFGS_IEEE_FLOAT*/ inline static void* vecalloc(size_t size) { void *memblock = malloc(size); if (memblock) { memset(memblock, 0, size); } return memblock; } inline static void vecfree(void *memblock) { free(memblock); } inline static void vecset(lbfgsfloatval_t *x, const lbfgsfloatval_t c, const int n) { int i; for (i = 0;i < n;++i) { x[i] = c; } } inline static void veccpy(lbfgsfloatval_t *y, const lbfgsfloatval_t *x, const int n) { int i; for (i = 0;i < n;++i) { y[i] = x[i]; } } inline static void vecncpy(lbfgsfloatval_t *y, const lbfgsfloatval_t *x, const int n) { int i; for (i = 0;i < n;++i) { y[i] = -x[i]; } } inline static void vecadd(lbfgsfloatval_t *y, const lbfgsfloatval_t *x, const lbfgsfloatval_t c, const int n) { int i; for (i = 0;i < n;++i) { y[i] += c * x[i]; } } inline static void vecdiff(lbfgsfloatval_t *z, const lbfgsfloatval_t *x, const lbfgsfloatval_t *y, const int n) { int i; for (i = 0;i < n;++i) { z[i] = x[i] - y[i]; } } inline static void vecscale(lbfgsfloatval_t *y, const lbfgsfloatval_t c, const int n) { int i; for (i = 0;i < n;++i) { y[i] *= c; } } inline static void vecmul(lbfgsfloatval_t *y, const lbfgsfloatval_t *x, const int n) { int i; for (i = 0;i < n;++i) { y[i] *= x[i]; } } inline static void vecdot(lbfgsfloatval_t* s, const lbfgsfloatval_t *x, const lbfgsfloatval_t *y, const int n) { int i; *s = 0.; for (i = 0;i < n;++i) { *s += x[i] * y[i]; } } inline static void vec2norm(lbfgsfloatval_t* s, const lbfgsfloatval_t *x, const int n) { vecdot(s, x, x, n); *s = (lbfgsfloatval_t)sqrt(*s); } inline static void vec2norminv(lbfgsfloatval_t* s, const lbfgsfloatval_t *x, const int n) { vec2norm(s, x, n); *s = (lbfgsfloatval_t)(1.0 / *s); } python-igraph-0.8.0/vendor/source/igraph/src/plfit/kolmogorov.c0000644000076500000240000000355213524616145025072 0ustar tamasstaff00000000000000/* kolmogorov.c * * Copyright (C) 2010-2011 Tamas Nepusz * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 3 of the License, or (at * your option) any later version. * * This program is distributed in the hope that it will be useful, but * WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. */ #include #include "kolmogorov.h" double plfit_kolmogorov(double z) { const double fj[4] = { -2, -8, -18, -32 }; const double w = 2.50662827; const double c1 = -1.2337005501361697; /* -pi^2 / 8 */ const double c2 = -11.103304951225528; /* 9*c1 */ const double c3 = -30.842513753404244; /* 25*c1 */ double u = fabs(z); double v; if (u < 0.2) return 1; if (u < 0.755) { v = 1.0 / (u*u); return 1 - w * (exp(c1*v) + exp(c2*v) + exp(c3*v)) / u; } if (u < 6.8116) { double r[4] = { 0, 0, 0, 0 }; long int maxj = (long int)(3.0 / u + 0.5); long int j; if (maxj < 1) maxj = 1; v = u*u; for (j = 0; j < maxj; j++) { r[j] = exp(fj[j] * v); } return 2*(r[0] - r[1] + r[2] - r[3]); } return 0; } double plfit_ks_test_one_sample_p(double d, size_t n) { return plfit_kolmogorov(d * sqrt(n)); } double plfit_ks_test_two_sample_p(double d, size_t n1, size_t n2) { return plfit_kolmogorov(d * sqrt(n1*n2 / ((double)(n1+n2)))); } python-igraph-0.8.0/vendor/source/igraph/src/plfit/plfit.c0000644000076500000240000005416013524616145024013 0ustar tamasstaff00000000000000/* plfit.c * * Copyright (C) 2010-2011 Tamas Nepusz * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 3 of the License, or (at * your option) any later version. * * This program is distributed in the hope that it will be useful, but * WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. */ #include #include #include #include #include #include "error.h" #include "gss.h" #include "lbfgs.h" #include "platform.h" #include "plfit.h" #include "kolmogorov.h" #include "zeta.h" /* #define PLFIT_DEBUG */ #define DATA_POINTS_CHECK \ if (n <= 0) { \ PLFIT_ERROR("no data points", PLFIT_EINVAL); \ } #define XMIN_CHECK_ZERO \ if (xmin <= 0) { \ PLFIT_ERROR("xmin must be greater than zero", PLFIT_EINVAL); \ } #define XMIN_CHECK_ONE \ if (xmin < 1) { \ PLFIT_ERROR("xmin must be at least 1", PLFIT_EINVAL); \ } static int double_comparator(const void *a, const void *b) { const double *da = (const double*)a; const double *db = (const double*)b; return (*da > *db) - (*da < *db); } /** * Given a sorted array of doubles, return another array that contains pointers * into the array for the start of each block of identical elements. * * \param begin pointer to the beginning of the array * \param end pointer to the first element after the end of the array * \param result_length if not \c NULL, the number of unique elements in the * given array is returned here */ static double** unique_element_pointers(double* begin, double* end, size_t* result_length) { double* ptr = begin; double** result; double prev_x; size_t num_elts = 15; size_t used_elts = 0; /* Special case: empty array */ if (begin == end) { result = calloc(1, sizeof(double*)); if (result != 0) { result[0] = 0; } return result; } /* Allocate initial result array, including the guard element */ result = calloc(num_elts+1, sizeof(double*)); if (result == 0) return 0; prev_x = *begin; result[used_elts++] = begin; /* Process the input array */ for (ptr = begin+1; ptr < end; ptr++) { if (*ptr == prev_x) continue; /* New block found */ if (used_elts >= num_elts) { /* Array full; allocate a new chunk */ num_elts = num_elts*2 + 1; result = realloc(result, sizeof(double*) * (num_elts+1)); if (result == 0) return 0; } /* Store the new element */ result[used_elts++] = ptr; prev_x = *ptr; } /* Calculate the result length */ if (result_length != 0) { *result_length = used_elts; } /* Add the guard entry to the end of the result */ result[used_elts++] = 0; return result; } static void plfit_i_perform_finite_size_correction(plfit_result_t* result, size_t n) { result->alpha = result->alpha * (n-1) / n + 1.0 / n; } /********** Continuous power law distribution fitting **********/ void plfit_i_logsum_less_than_continuous(double* begin, double* end, double xmin, double* result, size_t* m) { double logsum = 0.0; size_t count = 0; for (; begin != end; begin++) { if (*begin >= xmin) { count++; logsum += log(*begin / xmin); } } *m = count; *result = logsum; } double plfit_i_logsum_continuous(double* begin, double* end, double xmin) { double logsum = 0.0; for (; begin != end; begin++) logsum += log(*begin / xmin); return logsum; } int plfit_i_estimate_alpha_continuous(double* xs, size_t n, double xmin, double* alpha) { double result; size_t m; XMIN_CHECK_ZERO; plfit_i_logsum_less_than_continuous(xs, xs+n, xmin, &result, &m); if (m == 0) { PLFIT_ERROR("no data point was larger than xmin", PLFIT_EINVAL); } *alpha = 1 + m / result; return PLFIT_SUCCESS; } int plfit_i_estimate_alpha_continuous_sorted(double* xs, size_t n, double xmin, double* alpha) { double* end = xs+n; XMIN_CHECK_ZERO; for (; xs != end && *xs < xmin; xs++); if (xs == end) { PLFIT_ERROR("no data point was larger than xmin", PLFIT_EINVAL); } *alpha = 1 + (end-xs) / plfit_i_logsum_continuous(xs, end, xmin); return PLFIT_SUCCESS; } static int plfit_i_ks_test_continuous(double* xs, double* xs_end, const double alpha, const double xmin, double* D) { /* Assumption: xs is sorted and cut off at xmin so the first element is * always larger than or equal to xmin. */ double result = 0, n; int m = 0; n = xs_end - xs; while (xs < xs_end) { double d = fabs(1-pow(xmin / *xs, alpha-1) - m / n); if (d > result) result = d; xs++; m++; } *D = result; return PLFIT_SUCCESS; } int plfit_log_likelihood_continuous(double* xs, size_t n, double alpha, double xmin, double* L) { double logsum, c; size_t m; if (alpha <= 1) { PLFIT_ERROR("alpha must be greater than one", PLFIT_EINVAL); } XMIN_CHECK_ZERO; c = (alpha - 1) / xmin; plfit_i_logsum_less_than_continuous(xs, xs+n, xmin, &logsum, &m); *L = -alpha * logsum + log(c) * m; return PLFIT_SUCCESS; } int plfit_estimate_alpha_continuous(double* xs, size_t n, double xmin, const plfit_continuous_options_t* options, plfit_result_t *result) { double *xs_copy; if (!options) options = &plfit_continuous_default_options; /* Make a copy of xs and sort it */ xs_copy = (double*)malloc(sizeof(double) * n); memcpy(xs_copy, xs, sizeof(double) * n); qsort(xs_copy, n, sizeof(double), double_comparator); PLFIT_CHECK(plfit_estimate_alpha_continuous_sorted(xs_copy, n, xmin, options, result)); free(xs_copy); return PLFIT_SUCCESS; } int plfit_estimate_alpha_continuous_sorted(double* xs, size_t n, double xmin, const plfit_continuous_options_t* options, plfit_result_t *result) { double* end; if (!options) options = &plfit_continuous_default_options; end = xs + n; while (xs < end && *xs < xmin) xs++; n = (size_t) (end - xs); PLFIT_CHECK(plfit_i_estimate_alpha_continuous_sorted(xs, n, xmin, &result->alpha)); PLFIT_CHECK(plfit_i_ks_test_continuous(xs, end, result->alpha, xmin, &result->D)); if (options->finite_size_correction) plfit_i_perform_finite_size_correction(result, n); result->xmin = xmin; result->p = plfit_ks_test_one_sample_p(result->D, n); plfit_log_likelihood_continuous(xs, n, result->alpha, result->xmin, &result->L); return PLFIT_SUCCESS; } typedef struct { double *begin; /**< Pointer to the beginning of the array holding the data */ double *end; /**< Pointer to after the end of the array holding the data */ double **uniques; /**< Pointers to unique elements of the input array */ plfit_result_t last; /**< Result of the last evaluation */ } plfit_continuous_xmin_opt_data_t; double plfit_i_continuous_xmin_opt_evaluate(void* instance, double x) { plfit_continuous_xmin_opt_data_t* data = (plfit_continuous_xmin_opt_data_t*)instance; double* begin = data->uniques[(int)x]; data->last.xmin = *begin; #ifdef PLFIT_DEBUG printf("Trying with xmin = %.4f\n", *begin); #endif plfit_i_estimate_alpha_continuous_sorted(begin, (size_t) (data->end-begin), *begin, &data->last.alpha); plfit_i_ks_test_continuous(begin, data->end, data->last.alpha, *begin, &data->last.D); return data->last.D; } int plfit_i_continuous_xmin_opt_progress(void* instance, double x, double fx, double min, double fmin, double left, double right, int k) { #ifdef PLFIT_DEBUG printf("Iteration #%d: [%.4f; %.4f), x=%.4f, fx=%.4f, min=%.4f, fmin=%.4f\n", k, left, right, x, fx, min, fmin); #endif /* Continue only if `left' and `right' point to different integers */ return (int)left == (int)right; } int plfit_continuous(double* xs, size_t n, const plfit_continuous_options_t* options, plfit_result_t* result) { gss_parameter_t gss_param; plfit_continuous_xmin_opt_data_t opt_data; plfit_result_t best_result; int success; size_t i, best_n, num_uniques; double x, *px; DATA_POINTS_CHECK; if (!options) options = &plfit_continuous_default_options; /* Make a copy of xs and sort it */ opt_data.begin = (double*)malloc(sizeof(double) * n); memcpy(opt_data.begin, xs, sizeof(double) * n); qsort(opt_data.begin, n, sizeof(double), double_comparator); opt_data.end = opt_data.begin + n; /* Create an array containing pointers to the unique elements of the input. From * each block of unique elements, we add the pointer to the first one. */ opt_data.uniques = unique_element_pointers(opt_data.begin, opt_data.end, &num_uniques); if (opt_data.uniques == 0) return PLFIT_ENOMEM; /* We will now determine the best xmin that yields the lowest D-score. * First we try a golden section search if needed. If that fails, we try * a linear search. */ if (options->xmin_method == PLFIT_GSS_OR_LINEAR && num_uniques > 5) { gss_parameter_init(&gss_param); success = (gss(0, num_uniques-5, &x, 0, plfit_i_continuous_xmin_opt_evaluate, plfit_i_continuous_xmin_opt_progress, &opt_data, &gss_param) == 0); best_result = opt_data.last; /* plfit_i_continuous_xmin_opt_evaluate will set opt_data.last to * indicate the location of the optimum and the value of D */ } else { success = 0; } if (success) { /* calculate best_n because we'll need it later. Luckily x indicates * the index in opt_data.uniques that we have to look up in order to * find the first element in the array that is included */ px = opt_data.uniques[(int)x]; best_n = (size_t) (opt_data.end-px+1); } else { /* GSS failed or skipped; try linear search */ /* Prepare some variables */ best_n = 0; best_result.D = DBL_MAX; best_result.xmin = 0; best_result.alpha = 0; for (i = 0; i < num_uniques-1; i++) { plfit_i_continuous_xmin_opt_evaluate(&opt_data, i); if (opt_data.last.D < best_result.D) { best_result = opt_data.last; best_n = (size_t) (opt_data.end - opt_data.uniques[i] + 1); } } } /* Get rid of the uniques array, we don't need it any more */ free(opt_data.uniques); /* Sort out the result */ *result = best_result; if (options->finite_size_correction) plfit_i_perform_finite_size_correction(result, best_n); result->p = plfit_ks_test_one_sample_p(result->D, best_n); plfit_log_likelihood_continuous(opt_data.begin + n - best_n, best_n, result->alpha, result->xmin, &result->L); /* Get rid of the copied data as well */ free(opt_data.begin); return PLFIT_SUCCESS; } /********** Discrete power law distribution fitting **********/ typedef struct { size_t m; double logsum; double xmin; } plfit_i_estimate_alpha_discrete_data_t; double plfit_i_logsum_discrete(double* begin, double* end, double xmin) { double logsum = 0.0; for (; begin != end; begin++) logsum += log(*begin); return logsum; } void plfit_i_logsum_less_than_discrete(double* begin, double* end, double xmin, double* logsum, size_t* m) { double result = 0.0; size_t count = 0; for (; begin != end; begin++) { if (*begin < xmin) continue; result += log(*begin); count++; } *logsum = result; *m = count; } lbfgsfloatval_t plfit_i_estimate_alpha_discrete_lbfgs_evaluate( void* instance, const lbfgsfloatval_t* x, lbfgsfloatval_t* g, const int n, const lbfgsfloatval_t step) { plfit_i_estimate_alpha_discrete_data_t* data; lbfgsfloatval_t result; double dx = step; double huge = 1e10; /* pseudo-infinity; apparently DBL_MAX does not work */ data = (plfit_i_estimate_alpha_discrete_data_t*)instance; #ifdef PLFIT_DEBUG printf("- Evaluating at %.4f (step = %.4f, xmin = %.4f)\n", *x, step, data->xmin); #endif if (isnan(*x)) { g[0] = huge; return huge; } /* Find the delta X value to estimate the gradient */ if (dx > 0.001 || dx == 0) dx = 0.001; else if (dx < -0.001) dx = -0.001; /* Is x[0] in its valid range? */ if (x[0] <= 1.0) { /* The Hurwitz zeta function is infinite in this case */ g[0] = (dx > 0) ? -huge : huge; return huge; } if (x[0] + dx <= 1.0) g[0] = huge; else g[0] = data->logsum + data->m * (log(gsl_sf_hzeta(x[0] + dx, data->xmin)) - log(gsl_sf_hzeta(x[0], data->xmin))) / dx; result = x[0] * data->logsum + data->m * log(gsl_sf_hzeta(x[0], data->xmin)); #ifdef PLFIT_DEBUG printf(" - Gradient: %.4f\n", g[0]); printf(" - Result: %.4f\n", result); #endif return result; } int plfit_i_estimate_alpha_discrete_lbfgs_progress(void* instance, const lbfgsfloatval_t* x, const lbfgsfloatval_t* g, const lbfgsfloatval_t fx, const lbfgsfloatval_t xnorm, const lbfgsfloatval_t gnorm, const lbfgsfloatval_t step, int n, int k, int ls) { return 0; } int plfit_i_estimate_alpha_discrete_linear_scan(double* xs, size_t n, double xmin, double* alpha, const plfit_discrete_options_t* options, plfit_bool_t sorted) { double curr_alpha, best_alpha, L, L_max; double logsum; size_t m; XMIN_CHECK_ONE; if (options->alpha.min <= 1.0) { PLFIT_ERROR("alpha.min must be greater than 1.0", PLFIT_EINVAL); } if (options->alpha.max < options->alpha.min) { PLFIT_ERROR("alpha.max must be greater than alpha.min", PLFIT_EINVAL); } if (options->alpha.step <= 0) { PLFIT_ERROR("alpha.step must be positive", PLFIT_EINVAL); } if (sorted) { logsum = plfit_i_logsum_discrete(xs, xs+n, xmin); m = n; } else { plfit_i_logsum_less_than_discrete(xs, xs+n, xmin, &logsum, &m); } best_alpha = options->alpha.min; L_max = -DBL_MAX; for (curr_alpha = options->alpha.min; curr_alpha <= options->alpha.max; curr_alpha += options->alpha.step) { L = -curr_alpha * logsum - m * log(gsl_sf_hzeta(curr_alpha, xmin)); if (L > L_max) { L_max = L; best_alpha = curr_alpha; } } *alpha = best_alpha; return PLFIT_SUCCESS; } int plfit_i_estimate_alpha_discrete_lbfgs(double* xs, size_t n, double xmin, double* alpha, const plfit_discrete_options_t* options, plfit_bool_t sorted) { lbfgs_parameter_t param; lbfgsfloatval_t* variables; plfit_i_estimate_alpha_discrete_data_t data; int ret; XMIN_CHECK_ONE; /* Initialize algorithm parameters */ lbfgs_parameter_init(¶m); param.max_iterations = 0; /* proceed until infinity */ /* Set up context for optimization */ data.xmin = xmin; if (sorted) { data.logsum = plfit_i_logsum_discrete(xs, xs+n, xmin); data.m = n; } else { plfit_i_logsum_less_than_discrete(xs, xs+n, xmin, &data.logsum, &data.m); } /* Allocate space for the single alpha variable */ variables = lbfgs_malloc(1); variables[0] = 3.0; /* initial guess */ /* Optimization */ ret = lbfgs(1, variables, /* ptr_fx = */ 0, plfit_i_estimate_alpha_discrete_lbfgs_evaluate, plfit_i_estimate_alpha_discrete_lbfgs_progress, &data, ¶m); if (ret < 0 && ret != LBFGSERR_ROUNDING_ERROR && ret != LBFGSERR_MAXIMUMLINESEARCH && ret != LBFGSERR_CANCELED) { char buf[4096]; snprintf(buf, 4096, "L-BFGS optimization signaled an error (error code = %d)", ret); lbfgs_free(variables); PLFIT_ERROR(buf, PLFIT_FAILURE); } *alpha = variables[0]; /* Deallocate the variable array */ lbfgs_free(variables); return PLFIT_SUCCESS; } int plfit_i_estimate_alpha_discrete_fast(double* xs, size_t n, double xmin, double* alpha, const plfit_discrete_options_t* options, plfit_bool_t sorted) { plfit_continuous_options_t cont_options; if (!options) options = &plfit_discrete_default_options; plfit_continuous_options_init(&cont_options); cont_options.finite_size_correction = options->finite_size_correction; XMIN_CHECK_ONE; if (sorted) { return plfit_i_estimate_alpha_continuous_sorted(xs, n, xmin-0.5, alpha); } else { return plfit_i_estimate_alpha_continuous(xs, n, xmin-0.5, alpha); } } int plfit_i_estimate_alpha_discrete(double* xs, size_t n, double xmin, double* alpha, const plfit_discrete_options_t* options, plfit_bool_t sorted) { switch (options->alpha_method) { case PLFIT_LBFGS: PLFIT_CHECK(plfit_i_estimate_alpha_discrete_lbfgs(xs, n, xmin, alpha, options, sorted)); break; case PLFIT_LINEAR_SCAN: PLFIT_CHECK(plfit_i_estimate_alpha_discrete_linear_scan(xs, n, xmin, alpha, options, sorted)); break; case PLFIT_PRETEND_CONTINUOUS: PLFIT_CHECK(plfit_i_estimate_alpha_discrete_fast(xs, n, xmin, alpha, options, sorted)); break; default: PLFIT_ERROR("unknown optimization method specified", PLFIT_EINVAL); } return PLFIT_SUCCESS; } static int plfit_i_ks_test_discrete(double* xs, double* xs_end, const double alpha, const double xmin, double* D) { /* Assumption: xs is sorted and cut off at xmin so the first element is * always larger than or equal to xmin. */ double result = 0, n, hzeta, x; int m = 0; n = xs_end - xs; hzeta = gsl_sf_hzeta(alpha, xmin); while (xs < xs_end) { double d; x = *xs; d = fabs(1-(gsl_sf_hzeta(alpha, x) / hzeta) - m / n); if (d > result) result = d; do { xs++; m++; } while (xs < xs_end && *xs == x); } *D = result; return PLFIT_SUCCESS; } int plfit_log_likelihood_discrete(double* xs, size_t n, double alpha, double xmin, double* L) { double result; size_t m; if (alpha <= 1) { PLFIT_ERROR("alpha must be greater than one", PLFIT_EINVAL); } XMIN_CHECK_ONE; plfit_i_logsum_less_than_discrete(xs, xs+n, xmin, &result, &m); result = - alpha * result - m * log(gsl_sf_hzeta(alpha, xmin)); *L = result; return PLFIT_SUCCESS; } int plfit_estimate_alpha_discrete(double* xs, size_t n, double xmin, const plfit_discrete_options_t* options, plfit_result_t *result) { double *xs_copy, *end; if (!options) options = &plfit_discrete_default_options; /* Check the validity of the input parameters */ DATA_POINTS_CHECK; if (options->alpha_method == PLFIT_LINEAR_SCAN) { if (options->alpha.min <= 1.0) { PLFIT_ERROR("alpha.min must be greater than 1.0", PLFIT_EINVAL); } if (options->alpha.max < options->alpha.min) { PLFIT_ERROR("alpha.max must be greater than alpha.min", PLFIT_EINVAL); } if (options->alpha.step <= 0) { PLFIT_ERROR("alpha.step must be positive", PLFIT_EINVAL); } } /* Make a copy of xs and sort it */ xs_copy = (double*)malloc(sizeof(double) * n); memcpy(xs_copy, xs, sizeof(double) * n); qsort(xs_copy, n, sizeof(double), double_comparator); xs = xs_copy; end = xs_copy + n; while (xs < end && *xs < xmin) xs++; n = (size_t) (end - xs); PLFIT_CHECK(plfit_i_estimate_alpha_discrete(xs, n, xmin, &result->alpha, options, /* sorted = */ 1)); PLFIT_CHECK(plfit_i_ks_test_discrete(xs, end, result->alpha, xmin, &result->D)); result->xmin = xmin; if (options->finite_size_correction) plfit_i_perform_finite_size_correction(result, n); result->p = plfit_ks_test_one_sample_p(result->D, n); plfit_log_likelihood_discrete(xs, n, result->alpha, result->xmin, &result->L); free(xs_copy); return PLFIT_SUCCESS; } int plfit_discrete(double* xs, size_t n, const plfit_discrete_options_t* options, plfit_result_t* result) { double curr_D, curr_alpha; plfit_result_t best_result; double *xs_copy, *px, *end, *end_xmin, prev_x; size_t best_n; size_t m; if (!options) options = &plfit_discrete_default_options; /* Check the validity of the input parameters */ DATA_POINTS_CHECK; if (options->alpha_method == PLFIT_LINEAR_SCAN) { if (options->alpha.min <= 1.0) { PLFIT_ERROR("alpha.min must be greater than 1.0", PLFIT_EINVAL); } if (options->alpha.max < options->alpha.min) { PLFIT_ERROR("alpha.max must be greater than alpha.min", PLFIT_EINVAL); } if (options->alpha.step <= 0) { PLFIT_ERROR("alpha.step must be positive", PLFIT_EINVAL); } } /* Make a copy of xs and sort it */ xs_copy = (double*)malloc(sizeof(double) * n); memcpy(xs_copy, xs, sizeof(double) * n); qsort(xs_copy, n, sizeof(double), double_comparator); best_result.D = DBL_MAX; best_result.xmin = 1; best_result.alpha = 1; best_n = 0; /* Make sure there are at least three distinct values if possible */ px = xs_copy; end = px + n; end_xmin = end - 1; m = 0; prev_x = *end_xmin; while (*end_xmin == prev_x && end_xmin > px) end_xmin--; prev_x = *end_xmin; while (*end_xmin == prev_x && end_xmin > px) end_xmin--; prev_x = 0; while (px < end_xmin) { while (px < end_xmin && *px == prev_x) { px++; m++; } plfit_i_estimate_alpha_discrete(px, n - m, *px, &curr_alpha, options, /* sorted = */ 1); plfit_i_ks_test_discrete(px, end, curr_alpha, *px, &curr_D); if (curr_D < best_result.D) { best_result.alpha = curr_alpha; best_result.xmin = *px; best_result.D = curr_D; best_n = n - m; } prev_x = *px; px++; m++; } *result = best_result; if (options->finite_size_correction) plfit_i_perform_finite_size_correction(result, best_n); result->p = plfit_ks_test_one_sample_p(result->D, best_n); plfit_log_likelihood_discrete(xs_copy+(n-best_n), best_n, result->alpha, result->xmin, &result->L); free(xs_copy); return PLFIT_SUCCESS; } python-igraph-0.8.0/vendor/source/igraph/src/plfit/arithmetic_sse_double.h0000644000076500000240000002113613524616145027234 0ustar tamasstaff00000000000000/* * SSE2 implementation of vector oprations (64bit double). * * Copyright (c) 2007-2010 Naoaki Okazaki * All rights reserved. * * Permission is hereby granted, free of charge, to any person obtaining a copy * of this software and associated documentation files (the "Software"), to deal * in the Software without restriction, including without limitation the rights * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell * copies of the Software, and to permit persons to whom the Software is * furnished to do so, subject to the following conditions: * * The above copyright notice and this permission notice shall be included in * all copies or substantial portions of the Software. * * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN * THE SOFTWARE. */ /* $Id: arithmetic_sse_double.h 65 2010-01-29 12:19:16Z naoaki $ */ #include #if !defined(__APPLE__) #include #endif #include #if 1400 <= _MSC_VER #include #endif/*1400 <= _MSC_VER*/ #if HAVE_EMMINTRIN_H #include #endif/*HAVE_EMMINTRIN_H*/ inline static void* vecalloc(size_t size) { #ifdef _MSC_VER void *memblock = _aligned_malloc(size, 16); #elif defined(__APPLE__) /* Memory on Mac OS X is already aligned to 16 bytes */ void *memblock = malloc(size); #else void *memblock = memalign(16, size); #endif if (memblock != NULL) { memset(memblock, 0, size); } return memblock; } inline static void vecfree(void *memblock) { #ifdef _MSC_VER _aligned_free(memblock); #else free(memblock); #endif } #define fsigndiff(x, y) \ ((_mm_movemask_pd(_mm_set_pd(*(x), *(y))) + 1) & 0x002) #define vecset(x, c, n) \ { \ int i; \ __m128d XMM0 = _mm_set1_pd(c); \ for (i = 0;i < (n);i += 8) { \ _mm_store_pd((x)+i , XMM0); \ _mm_store_pd((x)+i+2, XMM0); \ _mm_store_pd((x)+i+4, XMM0); \ _mm_store_pd((x)+i+6, XMM0); \ } \ } #define veccpy(y, x, n) \ { \ int i; \ for (i = 0;i < (n);i += 8) { \ __m128d XMM0 = _mm_load_pd((x)+i ); \ __m128d XMM1 = _mm_load_pd((x)+i+2); \ __m128d XMM2 = _mm_load_pd((x)+i+4); \ __m128d XMM3 = _mm_load_pd((x)+i+6); \ _mm_store_pd((y)+i , XMM0); \ _mm_store_pd((y)+i+2, XMM1); \ _mm_store_pd((y)+i+4, XMM2); \ _mm_store_pd((y)+i+6, XMM3); \ } \ } #define vecncpy(y, x, n) \ { \ int i; \ for (i = 0;i < (n);i += 8) { \ __m128d XMM0 = _mm_setzero_pd(); \ __m128d XMM1 = _mm_setzero_pd(); \ __m128d XMM2 = _mm_setzero_pd(); \ __m128d XMM3 = _mm_setzero_pd(); \ __m128d XMM4 = _mm_load_pd((x)+i ); \ __m128d XMM5 = _mm_load_pd((x)+i+2); \ __m128d XMM6 = _mm_load_pd((x)+i+4); \ __m128d XMM7 = _mm_load_pd((x)+i+6); \ XMM0 = _mm_sub_pd(XMM0, XMM4); \ XMM1 = _mm_sub_pd(XMM1, XMM5); \ XMM2 = _mm_sub_pd(XMM2, XMM6); \ XMM3 = _mm_sub_pd(XMM3, XMM7); \ _mm_store_pd((y)+i , XMM0); \ _mm_store_pd((y)+i+2, XMM1); \ _mm_store_pd((y)+i+4, XMM2); \ _mm_store_pd((y)+i+6, XMM3); \ } \ } #define vecadd(y, x, c, n) \ { \ int i; \ __m128d XMM7 = _mm_set1_pd(c); \ for (i = 0;i < (n);i += 4) { \ __m128d XMM0 = _mm_load_pd((x)+i ); \ __m128d XMM1 = _mm_load_pd((x)+i+2); \ __m128d XMM2 = _mm_load_pd((y)+i ); \ __m128d XMM3 = _mm_load_pd((y)+i+2); \ XMM0 = _mm_mul_pd(XMM0, XMM7); \ XMM1 = _mm_mul_pd(XMM1, XMM7); \ XMM2 = _mm_add_pd(XMM2, XMM0); \ XMM3 = _mm_add_pd(XMM3, XMM1); \ _mm_store_pd((y)+i , XMM2); \ _mm_store_pd((y)+i+2, XMM3); \ } \ } #define vecdiff(z, x, y, n) \ { \ int i; \ for (i = 0;i < (n);i += 8) { \ __m128d XMM0 = _mm_load_pd((x)+i ); \ __m128d XMM1 = _mm_load_pd((x)+i+2); \ __m128d XMM2 = _mm_load_pd((x)+i+4); \ __m128d XMM3 = _mm_load_pd((x)+i+6); \ __m128d XMM4 = _mm_load_pd((y)+i ); \ __m128d XMM5 = _mm_load_pd((y)+i+2); \ __m128d XMM6 = _mm_load_pd((y)+i+4); \ __m128d XMM7 = _mm_load_pd((y)+i+6); \ XMM0 = _mm_sub_pd(XMM0, XMM4); \ XMM1 = _mm_sub_pd(XMM1, XMM5); \ XMM2 = _mm_sub_pd(XMM2, XMM6); \ XMM3 = _mm_sub_pd(XMM3, XMM7); \ _mm_store_pd((z)+i , XMM0); \ _mm_store_pd((z)+i+2, XMM1); \ _mm_store_pd((z)+i+4, XMM2); \ _mm_store_pd((z)+i+6, XMM3); \ } \ } #define vecscale(y, c, n) \ { \ int i; \ __m128d XMM7 = _mm_set1_pd(c); \ for (i = 0;i < (n);i += 4) { \ __m128d XMM0 = _mm_load_pd((y)+i ); \ __m128d XMM1 = _mm_load_pd((y)+i+2); \ XMM0 = _mm_mul_pd(XMM0, XMM7); \ XMM1 = _mm_mul_pd(XMM1, XMM7); \ _mm_store_pd((y)+i , XMM0); \ _mm_store_pd((y)+i+2, XMM1); \ } \ } #define vecmul(y, x, n) \ { \ int i; \ for (i = 0;i < (n);i += 8) { \ __m128d XMM0 = _mm_load_pd((x)+i ); \ __m128d XMM1 = _mm_load_pd((x)+i+2); \ __m128d XMM2 = _mm_load_pd((x)+i+4); \ __m128d XMM3 = _mm_load_pd((x)+i+6); \ __m128d XMM4 = _mm_load_pd((y)+i ); \ __m128d XMM5 = _mm_load_pd((y)+i+2); \ __m128d XMM6 = _mm_load_pd((y)+i+4); \ __m128d XMM7 = _mm_load_pd((y)+i+6); \ XMM4 = _mm_mul_pd(XMM4, XMM0); \ XMM5 = _mm_mul_pd(XMM5, XMM1); \ XMM6 = _mm_mul_pd(XMM6, XMM2); \ XMM7 = _mm_mul_pd(XMM7, XMM3); \ _mm_store_pd((y)+i , XMM4); \ _mm_store_pd((y)+i+2, XMM5); \ _mm_store_pd((y)+i+4, XMM6); \ _mm_store_pd((y)+i+6, XMM7); \ } \ } #if 3 <= __SSE__ /* Horizontal add with haddps SSE3 instruction. The work register (rw) is unused. */ #define __horizontal_sum(r, rw) \ r = _mm_hadd_ps(r, r); \ r = _mm_hadd_ps(r, r); #else /* Horizontal add with SSE instruction. The work register (rw) is used. */ #define __horizontal_sum(r, rw) \ rw = r; \ r = _mm_shuffle_ps(r, rw, _MM_SHUFFLE(1, 0, 3, 2)); \ r = _mm_add_ps(r, rw); \ rw = r; \ r = _mm_shuffle_ps(r, rw, _MM_SHUFFLE(2, 3, 0, 1)); \ r = _mm_add_ps(r, rw); #endif #define vecdot(s, x, y, n) \ { \ int i; \ __m128d XMM0 = _mm_setzero_pd(); \ __m128d XMM1 = _mm_setzero_pd(); \ __m128d XMM2, XMM3, XMM4, XMM5; \ for (i = 0;i < (n);i += 4) { \ XMM2 = _mm_load_pd((x)+i ); \ XMM3 = _mm_load_pd((x)+i+2); \ XMM4 = _mm_load_pd((y)+i ); \ XMM5 = _mm_load_pd((y)+i+2); \ XMM2 = _mm_mul_pd(XMM2, XMM4); \ XMM3 = _mm_mul_pd(XMM3, XMM5); \ XMM0 = _mm_add_pd(XMM0, XMM2); \ XMM1 = _mm_add_pd(XMM1, XMM3); \ } \ XMM0 = _mm_add_pd(XMM0, XMM1); \ XMM1 = _mm_shuffle_pd(XMM0, XMM0, _MM_SHUFFLE2(1, 1)); \ XMM0 = _mm_add_pd(XMM0, XMM1); \ _mm_store_sd((s), XMM0); \ } #define vec2norm(s, x, n) \ { \ int i; \ __m128d XMM0 = _mm_setzero_pd(); \ __m128d XMM1 = _mm_setzero_pd(); \ __m128d XMM2, XMM3, XMM4, XMM5; \ for (i = 0;i < (n);i += 4) { \ XMM2 = _mm_load_pd((x)+i ); \ XMM3 = _mm_load_pd((x)+i+2); \ XMM4 = XMM2; \ XMM5 = XMM3; \ XMM2 = _mm_mul_pd(XMM2, XMM4); \ XMM3 = _mm_mul_pd(XMM3, XMM5); \ XMM0 = _mm_add_pd(XMM0, XMM2); \ XMM1 = _mm_add_pd(XMM1, XMM3); \ } \ XMM0 = _mm_add_pd(XMM0, XMM1); \ XMM1 = _mm_shuffle_pd(XMM0, XMM0, _MM_SHUFFLE2(1, 1)); \ XMM0 = _mm_add_pd(XMM0, XMM1); \ XMM0 = _mm_sqrt_pd(XMM0); \ _mm_store_sd((s), XMM0); \ } #define vec2norminv(s, x, n) \ { \ int i; \ __m128d XMM0 = _mm_setzero_pd(); \ __m128d XMM1 = _mm_setzero_pd(); \ __m128d XMM2, XMM3, XMM4, XMM5; \ for (i = 0;i < (n);i += 4) { \ XMM2 = _mm_load_pd((x)+i ); \ XMM3 = _mm_load_pd((x)+i+2); \ XMM4 = XMM2; \ XMM5 = XMM3; \ XMM2 = _mm_mul_pd(XMM2, XMM4); \ XMM3 = _mm_mul_pd(XMM3, XMM5); \ XMM0 = _mm_add_pd(XMM0, XMM2); \ XMM1 = _mm_add_pd(XMM1, XMM3); \ } \ XMM2 = _mm_set1_pd(1.0); \ XMM0 = _mm_add_pd(XMM0, XMM1); \ XMM1 = _mm_shuffle_pd(XMM0, XMM0, _MM_SHUFFLE2(1, 1)); \ XMM0 = _mm_add_pd(XMM0, XMM1); \ XMM0 = _mm_sqrt_pd(XMM0); \ XMM2 = _mm_div_pd(XMM2, XMM0); \ _mm_store_sd((s), XMM2); \ } python-igraph-0.8.0/vendor/source/igraph/src/plfit/plfit.inc0000644000076500000240000000056613524616145024343 0ustar tamasstaff00000000000000PLFIT = plfit/error.c plfit/gss.c plfit/kolmogorov.c \ plfit/lbfgs.c plfit/options.c plfit/plfit.c \ plfit/zeta.c \ plfit/arithmetic_ansi.h plfit/arithmetic_sse_double.h plfit/arithmetic_sse_float.h \ plfit/error.h plfit/gss.h plfit/kolmogorov.h \ plfit/lbfgs.h plfit/platform.h plfit/plfit.h \ plfit/zeta.h python-igraph-0.8.0/vendor/source/igraph/src/plfit/lbfgs.h0000644000076500000240000007627613524616145024013 0ustar tamasstaff00000000000000/* * C library of Limited memory BFGS (L-BFGS). * * Copyright (c) 1990, Jorge Nocedal * Copyright (c) 2007-2010 Naoaki Okazaki * All rights reserved. * * Permission is hereby granted, free of charge, to any person obtaining a copy * of this software and associated documentation files (the "Software"), to deal * in the Software without restriction, including without limitation the rights * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell * copies of the Software, and to permit persons to whom the Software is * furnished to do so, subject to the following conditions: * * The above copyright notice and this permission notice shall be included in * all copies or substantial portions of the Software. * * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN * THE SOFTWARE. */ /* $Id: lbfgs.h 65 2010-01-29 12:19:16Z naoaki $ */ #ifndef __LBFGS_H__ #define __LBFGS_H__ #ifdef __cplusplus extern "C" { #endif/*__cplusplus*/ /* * The default precision of floating point values is 64bit (double). */ #ifndef LBFGS_FLOAT #define LBFGS_FLOAT 64 #endif/*LBFGS_FLOAT*/ /* * Activate optimization routines for IEEE754 floating point values. */ #ifndef LBFGS_IEEE_FLOAT #define LBFGS_IEEE_FLOAT 1 #endif/*LBFGS_IEEE_FLOAT*/ #if LBFGS_FLOAT == 32 typedef float lbfgsfloatval_t; #elif LBFGS_FLOAT == 64 typedef double lbfgsfloatval_t; #else #error "libLBFGS supports single (float; LBFGS_FLOAT = 32) or double (double; LBFGS_FLOAT=64) precision only." #endif /** * \addtogroup liblbfgs_api libLBFGS API * @{ * * The libLBFGS API. */ /** * Return values of lbfgs(). * * Roughly speaking, a negative value indicates an error. */ enum { /** L-BFGS reaches convergence. */ LBFGS_SUCCESS = 0, LBFGS_CONVERGENCE = 0, LBFGS_STOP, /** The initial variables already minimize the objective function. */ LBFGS_ALREADY_MINIMIZED, /** Unknown error. */ LBFGSERR_UNKNOWNERROR = -1024, /** Logic error. */ LBFGSERR_LOGICERROR, /** Insufficient memory. */ LBFGSERR_OUTOFMEMORY, /** The minimization process has been canceled. */ LBFGSERR_CANCELED, /** Invalid number of variables specified. */ LBFGSERR_INVALID_N, /** Invalid number of variables (for SSE) specified. */ LBFGSERR_INVALID_N_SSE, /** The array x must be aligned to 16 (for SSE). */ LBFGSERR_INVALID_X_SSE, /** Invalid parameter lbfgs_parameter_t::epsilon specified. */ LBFGSERR_INVALID_EPSILON, /** Invalid parameter lbfgs_parameter_t::past specified. */ LBFGSERR_INVALID_TESTPERIOD, /** Invalid parameter lbfgs_parameter_t::delta specified. */ LBFGSERR_INVALID_DELTA, /** Invalid parameter lbfgs_parameter_t::linesearch specified. */ LBFGSERR_INVALID_LINESEARCH, /** Invalid parameter lbfgs_parameter_t::max_step specified. */ LBFGSERR_INVALID_MINSTEP, /** Invalid parameter lbfgs_parameter_t::max_step specified. */ LBFGSERR_INVALID_MAXSTEP, /** Invalid parameter lbfgs_parameter_t::ftol specified. */ LBFGSERR_INVALID_FTOL, /** Invalid parameter lbfgs_parameter_t::wolfe specified. */ LBFGSERR_INVALID_WOLFE, /** Invalid parameter lbfgs_parameter_t::gtol specified. */ LBFGSERR_INVALID_GTOL, /** Invalid parameter lbfgs_parameter_t::xtol specified. */ LBFGSERR_INVALID_XTOL, /** Invalid parameter lbfgs_parameter_t::max_linesearch specified. */ LBFGSERR_INVALID_MAXLINESEARCH, /** Invalid parameter lbfgs_parameter_t::orthantwise_c specified. */ LBFGSERR_INVALID_ORTHANTWISE, /** Invalid parameter lbfgs_parameter_t::orthantwise_start specified. */ LBFGSERR_INVALID_ORTHANTWISE_START, /** Invalid parameter lbfgs_parameter_t::orthantwise_end specified. */ LBFGSERR_INVALID_ORTHANTWISE_END, /** The line-search step went out of the interval of uncertainty. */ LBFGSERR_OUTOFINTERVAL, /** A logic error occurred; alternatively, the interval of uncertainty became too small. */ LBFGSERR_INCORRECT_TMINMAX, /** A rounding error occurred; alternatively, no line-search step satisfies the sufficient decrease and curvature conditions. */ LBFGSERR_ROUNDING_ERROR, /** The line-search step became smaller than lbfgs_parameter_t::min_step. */ LBFGSERR_MINIMUMSTEP, /** The line-search step became larger than lbfgs_parameter_t::max_step. */ LBFGSERR_MAXIMUMSTEP, /** The line-search routine reaches the maximum number of evaluations. */ LBFGSERR_MAXIMUMLINESEARCH, /** The algorithm routine reaches the maximum number of iterations. */ LBFGSERR_MAXIMUMITERATION, /** Relative width of the interval of uncertainty is at most lbfgs_parameter_t::xtol. */ LBFGSERR_WIDTHTOOSMALL, /** A logic error (negative line-search step) occurred. */ LBFGSERR_INVALIDPARAMETERS, /** The current search direction increases the objective function value. */ LBFGSERR_INCREASEGRADIENT, }; /** * Line search algorithms. */ enum { /** The default algorithm (MoreThuente method). */ LBFGS_LINESEARCH_DEFAULT = 0, /** MoreThuente method proposd by More and Thuente. */ LBFGS_LINESEARCH_MORETHUENTE = 0, /** * Backtracking method with the Armijo condition. * The backtracking method finds the step length such that it satisfies * the sufficient decrease (Armijo) condition, * - f(x + a * d) <= f(x) + lbfgs_parameter_t::ftol * a * g(x)^T d, * * where x is the current point, d is the current search direction, and * a is the step length. */ LBFGS_LINESEARCH_BACKTRACKING_ARMIJO = 1, /** The backtracking method with the defualt (regular Wolfe) condition. */ LBFGS_LINESEARCH_BACKTRACKING = 2, /** * Backtracking method with regular Wolfe condition. * The backtracking method finds the step length such that it satisfies * both the Armijo condition (LBFGS_LINESEARCH_BACKTRACKING_ARMIJO) * and the curvature condition, * - g(x + a * d)^T d >= lbfgs_parameter_t::wolfe * g(x)^T d, * * where x is the current point, d is the current search direction, and * a is the step length. */ LBFGS_LINESEARCH_BACKTRACKING_WOLFE = 2, /** * Backtracking method with strong Wolfe condition. * The backtracking method finds the step length such that it satisfies * both the Armijo condition (LBFGS_LINESEARCH_BACKTRACKING_ARMIJO) * and the following condition, * - |g(x + a * d)^T d| <= lbfgs_parameter_t::wolfe * |g(x)^T d|, * * where x is the current point, d is the current search direction, and * a is the step length. */ LBFGS_LINESEARCH_BACKTRACKING_STRONG_WOLFE = 3, }; /** * L-BFGS optimization parameters. * Call lbfgs_parameter_init() function to initialize parameters to the * default values. */ typedef struct { /** * The number of corrections to approximate the inverse hessian matrix. * The L-BFGS routine stores the computation results of previous \ref m * iterations to approximate the inverse hessian matrix of the current * iteration. This parameter controls the size of the limited memories * (corrections). The default value is \c 6. Values less than \c 3 are * not recommended. Large values will result in excessive computing time. */ int m; /** * Epsilon for convergence test. * This parameter determines the accuracy with which the solution is to * be found. A minimization terminates when * ||g|| < \ref epsilon * max(1, ||x||), * where ||.|| denotes the Euclidean (L2) norm. The default value is * \c 1e-5. */ lbfgsfloatval_t epsilon; /** * Distance for delta-based convergence test. * This parameter determines the distance, in iterations, to compute * the rate of decrease of the objective function. If the value of this * parameter is zero, the library does not perform the delta-based * convergence test. The default value is \c 0. */ int past; /** * Delta for convergence test. * This parameter determines the minimum rate of decrease of the * objective function. The library stops iterations when the * following condition is met: * (f' - f) / f < \ref delta, * where f' is the objective value of \ref past iterations ago, and f is * the objective value of the current iteration. * The default value is \c 0. */ lbfgsfloatval_t delta; /** * The maximum number of iterations. * The lbfgs() function terminates an optimization process with * ::LBFGSERR_MAXIMUMITERATION status code when the iteration count * exceedes this parameter. Setting this parameter to zero continues an * optimization process until a convergence or error. The default value * is \c 0. */ int max_iterations; /** * The line search algorithm. * This parameter specifies a line search algorithm to be used by the * L-BFGS routine. */ int linesearch; /** * The maximum number of trials for the line search. * This parameter controls the number of function and gradients evaluations * per iteration for the line search routine. The default value is \c 20. */ int max_linesearch; /** * The minimum step of the line search routine. * The default value is \c 1e-20. This value need not be modified unless * the exponents are too large for the machine being used, or unless the * problem is extremely badly scaled (in which case the exponents should * be increased). */ lbfgsfloatval_t min_step; /** * The maximum step of the line search. * The default value is \c 1e+20. This value need not be modified unless * the exponents are too large for the machine being used, or unless the * problem is extremely badly scaled (in which case the exponents should * be increased). */ lbfgsfloatval_t max_step; /** * A parameter to control the accuracy of the line search routine. * The default value is \c 1e-4. This parameter should be greater * than zero and smaller than \c 0.5. */ lbfgsfloatval_t ftol; /** * A coefficient for the Wolfe condition. * This parameter is valid only when the backtracking line-search * algorithm is used with the Wolfe condition, * ::LBFGS_LINESEARCH_BACKTRACKING_STRONG_WOLFE or * ::LBFGS_LINESEARCH_BACKTRACKING_WOLFE . * The default value is \c 0.9. This parameter should be greater * the \ref ftol parameter and smaller than \c 1.0. */ lbfgsfloatval_t wolfe; /** * A parameter to control the accuracy of the line search routine. * The default value is \c 0.9. If the function and gradient * evaluations are inexpensive with respect to the cost of the * iteration (which is sometimes the case when solving very large * problems) it may be advantageous to set this parameter to a small * value. A typical small value is \c 0.1. This parameter shuold be * greater than the \ref ftol parameter (\c 1e-4) and smaller than * \c 1.0. */ lbfgsfloatval_t gtol; /** * The machine precision for floating-point values. * This parameter must be a positive value set by a client program to * estimate the machine precision. The line search routine will terminate * with the status code (::LBFGSERR_ROUNDING_ERROR) if the relative width * of the interval of uncertainty is less than this parameter. */ lbfgsfloatval_t xtol; /** * Coeefficient for the L1 norm of variables. * This parameter should be set to zero for standard minimization * problems. Setting this parameter to a positive value activates * Orthant-Wise Limited-memory Quasi-Newton (OWL-QN) method, which * minimizes the objective function F(x) combined with the L1 norm |x| * of the variables, {F(x) + C |x|}. This parameter is the coeefficient * for the |x|, i.e., C. As the L1 norm |x| is not differentiable at * zero, the library modifies function and gradient evaluations from * a client program suitably; a client program thus have only to return * the function value F(x) and gradients G(x) as usual. The default value * is zero. */ lbfgsfloatval_t orthantwise_c; /** * Start index for computing L1 norm of the variables. * This parameter is valid only for OWL-QN method * (i.e., \ref orthantwise_c != 0). This parameter b (0 <= b < N) * specifies the index number from which the library computes the * L1 norm of the variables x, * |x| := |x_{b}| + |x_{b+1}| + ... + |x_{N}| . * In other words, variables x_1, ..., x_{b-1} are not used for * computing the L1 norm. Setting b (0 < b < N), one can protect * variables, x_1, ..., x_{b-1} (e.g., a bias term of logistic * regression) from being regularized. The default value is zero. */ int orthantwise_start; /** * End index for computing L1 norm of the variables. * This parameter is valid only for OWL-QN method * (i.e., \ref orthantwise_c != 0). This parameter e (0 < e <= N) * specifies the index number at which the library stops computing the * L1 norm of the variables x, */ int orthantwise_end; } lbfgs_parameter_t; /** * Callback interface to provide objective function and gradient evaluations. * * The lbfgs() function call this function to obtain the values of objective * function and its gradients when needed. A client program must implement * this function to evaluate the values of the objective function and its * gradients, given current values of variables. * * @param instance The user data sent for lbfgs() function by the client. * @param x The current values of variables. * @param g The gradient vector. The callback function must compute * the gradient values for the current variables. * @param n The number of variables. * @param step The current step of the line search routine. * @retval lbfgsfloatval_t The value of the objective function for the current * variables. */ typedef lbfgsfloatval_t (*lbfgs_evaluate_t)( void *instance, const lbfgsfloatval_t *x, lbfgsfloatval_t *g, const int n, const lbfgsfloatval_t step ); /** * Callback interface to receive the progress of the optimization process. * * The lbfgs() function call this function for each iteration. Implementing * this function, a client program can store or display the current progress * of the optimization process. * * @param instance The user data sent for lbfgs() function by the client. * @param x The current values of variables. * @param g The current gradient values of variables. * @param fx The current value of the objective function. * @param xnorm The Euclidean norm of the variables. * @param gnorm The Euclidean norm of the gradients. * @param step The line-search step used for this iteration. * @param n The number of variables. * @param k The iteration count. * @param ls The number of evaluations called for this iteration. * @retval int Zero to continue the optimization process. Returning a * non-zero value will cancel the optimization process. */ typedef int (*lbfgs_progress_t)( void *instance, const lbfgsfloatval_t *x, const lbfgsfloatval_t *g, const lbfgsfloatval_t fx, const lbfgsfloatval_t xnorm, const lbfgsfloatval_t gnorm, const lbfgsfloatval_t step, int n, int k, int ls ); /* A user must implement a function compatible with ::lbfgs_evaluate_t (evaluation callback) and pass the pointer to the callback function to lbfgs() arguments. Similarly, a user can implement a function compatible with ::lbfgs_progress_t (progress callback) to obtain the current progress (e.g., variables, function value, ||G||, etc) and to cancel the iteration process if necessary. Implementation of a progress callback is optional: a user can pass \c NULL if progress notification is not necessary. In addition, a user must preserve two requirements: - The number of variables must be multiples of 16 (this is not 4). - The memory block of variable array ::x must be aligned to 16. This algorithm terminates an optimization when: ||G|| < \epsilon \cdot \max(1, ||x||) . In this formula, ||.|| denotes the Euclidean norm. */ /** * Start a L-BFGS optimization. * * @param n The number of variables. * @param x The array of variables. A client program can set * default values for the optimization and receive the * optimization result through this array. This array * must be allocated by ::lbfgs_malloc function * for libLBFGS built with SSE/SSE2 optimization routine * enabled. The library built without SSE/SSE2 * optimization does not have such a requirement. * @param ptr_fx The pointer to the variable that receives the final * value of the objective function for the variables. * This argument can be set to \c NULL if the final * value of the objective function is unnecessary. * @param proc_evaluate The callback function to provide function and * gradient evaluations given a current values of * variables. A client program must implement a * callback function compatible with \ref * lbfgs_evaluate_t and pass the pointer to the * callback function. * @param proc_progress The callback function to receive the progress * (the number of iterations, the current value of * the objective function) of the minimization * process. This argument can be set to \c NULL if * a progress report is unnecessary. * @param instance A user data for the client program. The callback * functions will receive the value of this argument. * @param param The pointer to a structure representing parameters for * L-BFGS optimization. A client program can set this * parameter to \c NULL to use the default parameters. * Call lbfgs_parameter_init() function to fill a * structure with the default values. * @retval int The status code. This function returns zero if the * minimization process terminates without an error. A * non-zero value indicates an error. */ int lbfgs( int n, lbfgsfloatval_t *x, lbfgsfloatval_t *ptr_fx, lbfgs_evaluate_t proc_evaluate, lbfgs_progress_t proc_progress, void *instance, lbfgs_parameter_t *param ); /** * Initialize L-BFGS parameters to the default values. * * Call this function to fill a parameter structure with the default values * and overwrite parameter values if necessary. * * @param param The pointer to the parameter structure. */ void lbfgs_parameter_init(lbfgs_parameter_t *param); /** * Allocate an array for variables. * * This function allocates an array of variables for the convenience of * ::lbfgs function; the function has a requreiemt for a variable array * when libLBFGS is built with SSE/SSE2 optimization routines. A user does * not have to use this function for libLBFGS built without SSE/SSE2 * optimization. * * @param n The number of variables. */ lbfgsfloatval_t* lbfgs_malloc(int n); /** * Free an array of variables. * * @param x The array of variables allocated by ::lbfgs_malloc * function. */ void lbfgs_free(lbfgsfloatval_t *x); /** @} */ #ifdef __cplusplus } #endif/*__cplusplus*/ /** @mainpage libLBFGS: a library of Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) @section intro Introduction This library is a C port of the implementation of Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method written by Jorge Nocedal. The original FORTRAN source code is available at: http://www.ece.northwestern.edu/~nocedal/lbfgs.html The L-BFGS method solves the unconstrainted minimization problem, 
    minimize F(x), x = (x1, x2, ..., xN),
only if the objective function F(x) and its gradient G(x) are computable. The well-known Newton's method requires computation of the inverse of the hessian matrix of the objective function. However, the computational cost for the inverse hessian matrix is expensive especially when the objective function takes a large number of variables. The L-BFGS method iteratively finds a minimizer by approximating the inverse hessian matrix by information from last m iterations. This innovation saves the memory storage and computational time drastically for large-scaled problems. Among the various ports of L-BFGS, this library provides several features: - Optimization with L1-norm (Orthant-Wise Limited-memory Quasi-Newton (OWL-QN) method): In addition to standard minimization problems, the library can minimize a function F(x) combined with L1-norm |x| of the variables, {F(x) + C |x|}, where C is a constant scalar parameter. This feature is useful for estimating parameters of sparse log-linear models (e.g., logistic regression and maximum entropy) with L1-regularization (or Laplacian prior). - Clean C code: Unlike C codes generated automatically by f2c (Fortran 77 into C converter), this port includes changes based on my interpretations, improvements, optimizations, and clean-ups so that the ported code would be well-suited for a C code. In addition to comments inherited from the original code, a number of comments were added through my interpretations. - Callback interface: The library receives function and gradient values via a callback interface. The library also notifies the progress of the optimization by invoking a callback function. In the original implementation, a user had to set function and gradient values every time the function returns for obtaining updated values. - Thread safe: The library is thread-safe, which is the secondary gain from the callback interface. - Cross platform. The source code can be compiled on Microsoft Visual Studio 2005, GNU C Compiler (gcc), etc. - Configurable precision: A user can choose single-precision (float) or double-precision (double) accuracy by changing ::LBFGS_FLOAT macro. - SSE/SSE2 optimization: This library includes SSE/SSE2 optimization (written in compiler intrinsics) for vector arithmetic operations on Intel/AMD processors. The library uses SSE for float values and SSE2 for double values. The SSE/SSE2 optimization routine is disabled by default. This library is used by: - CRFsuite: A fast implementation of Conditional Random Fields (CRFs) - Classias: A collection of machine-learning algorithms for classification - mlegp: an R package for maximum likelihood estimates for Gaussian processes - imaging2: the imaging2 class library - Algorithm::LBFGS - Perl extension for L-BFGS - YAP-LBFGS (an interface to call libLBFGS from YAP Prolog) @section download Download - Source code libLBFGS is distributed under the term of the MIT license. @section changelog History - Version 1.9 (2010-01-29): - Fixed a mistake in checking the validity of the parameters "ftol" and "wolfe"; this was discovered by Kevin S. Van Horn. - Version 1.8 (2009-07-13): - Accepted the patch submitted by Takashi Imamichi; the backtracking method now has three criteria for choosing the step length: - ::LBFGS_LINESEARCH_BACKTRACKING_ARMIJO: sufficient decrease (Armijo) condition only - ::LBFGS_LINESEARCH_BACKTRACKING_WOLFE: regular Wolfe condition (sufficient decrease condition + curvature condition) - ::LBFGS_LINESEARCH_BACKTRACKING_STRONG_WOLFE: strong Wolfe condition - Updated the documentation to explain the above three criteria. - Version 1.7 (2009-02-28): - Improved OWL-QN routines for stability. - Removed the support of OWL-QN method in MoreThuente algorithm because it accidentally fails in early stages of iterations for some objectives. Because of this change, the OW-LQN method must be used with the backtracking algorithm (::LBFGS_LINESEARCH_BACKTRACKING), or the library returns ::LBFGSERR_INVALID_LINESEARCH. - Renamed line search algorithms as follows: - ::LBFGS_LINESEARCH_BACKTRACKING: regular Wolfe condition. - ::LBFGS_LINESEARCH_BACKTRACKING_LOOSE: regular Wolfe condition. - ::LBFGS_LINESEARCH_BACKTRACKING_STRONG: strong Wolfe condition. - Source code clean-up. - Version 1.6 (2008-11-02): - Improved line-search algorithm with strong Wolfe condition, which was contributed by Takashi Imamichi. This routine is now default for ::LBFGS_LINESEARCH_BACKTRACKING. The previous line search algorithm with regular Wolfe condition is still available as ::LBFGS_LINESEARCH_BACKTRACKING_LOOSE. - Configurable stop index for L1-norm computation. A member variable ::lbfgs_parameter_t::orthantwise_end was added to specify the index number at which the library stops computing the L1 norm of the variables. This is useful to prevent some variables from being regularized by the OW-LQN method. - A sample program written in C++ (sample/sample.cpp). - Version 1.5 (2008-07-10): - Configurable starting index for L1-norm computation. A member variable ::lbfgs_parameter_t::orthantwise_start was added to specify the index number from which the library computes the L1 norm of the variables. This is useful to prevent some variables from being regularized by the OWL-QN method. - Fixed a zero-division error when the initial variables have already been a minimizer (reported by Takashi Imamichi). In this case, the library returns ::LBFGS_ALREADY_MINIMIZED status code. - Defined ::LBFGS_SUCCESS status code as zero; removed unused constants, LBFGSFALSE and LBFGSTRUE. - Fixed a compile error in an implicit down-cast. - Version 1.4 (2008-04-25): - Configurable line search algorithms. A member variable ::lbfgs_parameter_t::linesearch was added to choose either MoreThuente method (::LBFGS_LINESEARCH_MORETHUENTE) or backtracking algorithm (::LBFGS_LINESEARCH_BACKTRACKING). - Fixed a bug: the previous version did not compute psuedo-gradients properly in the line search routines for OWL-QN. This bug might quit an iteration process too early when the OWL-QN routine was activated (0 < ::lbfgs_parameter_t::orthantwise_c). - Configure script for POSIX environments. - SSE/SSE2 optimizations with GCC. - New functions ::lbfgs_malloc and ::lbfgs_free to use SSE/SSE2 routines transparently. It is uncessary to use these functions for libLBFGS built without SSE/SSE2 routines; you can still use any memory allocators if SSE/SSE2 routines are disabled in libLBFGS. - Version 1.3 (2007-12-16): - An API change. An argument was added to lbfgs() function to receive the final value of the objective function. This argument can be set to \c NULL if the final value is unnecessary. - Fixed a null-pointer bug in the sample code (reported by Takashi Imamichi). - Added build scripts for Microsoft Visual Studio 2005 and GCC. - Added README file. - Version 1.2 (2007-12-13): - Fixed a serious bug in orthant-wise L-BFGS. An important variable was used without initialization. - Version 1.1 (2007-12-01): - Implemented orthant-wise L-BFGS. - Implemented lbfgs_parameter_init() function. - Fixed several bugs. - API documentation. - Version 1.0 (2007-09-20): - Initial release. @section api Documentation - @ref liblbfgs_api "libLBFGS API" @section sample Sample code @include sample.c @section ack Acknowledgements The L-BFGS algorithm is described in: - Jorge Nocedal. Updating Quasi-Newton Matrices with Limited Storage. Mathematics of Computation, Vol. 35, No. 151, pp. 773--782, 1980. - Dong C. Liu and Jorge Nocedal. On the limited memory BFGS method for large scale optimization. Mathematical Programming B, Vol. 45, No. 3, pp. 503-528, 1989. The line search algorithms used in this implementation are described in: - John E. Dennis and Robert B. Schnabel. Numerical Methods for Unconstrained Optimization and Nonlinear Equations, Englewood Cliffs, 1983. - Jorge J. More and David J. Thuente. Line search algorithm with guaranteed sufficient decrease. ACM Transactions on Mathematical Software (TOMS), Vol. 20, No. 3, pp. 286-307, 1994. This library also implements Orthant-Wise Limited-memory Quasi-Newton (OWL-QN) method presented in: - Galen Andrew and Jianfeng Gao. Scalable training of L1-regularized log-linear models. In Proceedings of the 24th International Conference on Machine Learning (ICML 2007), pp. 33-40, 2007. Special thanks go to: - Yoshimasa Tsuruoka and Daisuke Okanohara for technical information about OWL-QN - Takashi Imamichi for the useful enhancements of the backtracking method Finally I would like to thank the original author, Jorge Nocedal, who has been distributing the effieicnt and explanatory implementation in an open source licence. @section reference Reference - L-BFGS by Jorge Nocedal. - Orthant-Wise Limited-memory Quasi-Newton Optimizer for L1-regularized Objectives by Galen Andrew. - C port (via f2c) by Taku Kudo. - C#/C++/Delphi/VisualBasic6 port in ALGLIB. - Computational Crystallography Toolbox includes scitbx::lbfgs. */ #endif/*__LBFGS_H__*/ python-igraph-0.8.0/vendor/source/igraph/src/plfit/gss.c0000644000076500000240000000661713524616145023475 0ustar tamasstaff00000000000000/* gss.c * * Copyright (C) 2012 Tamas Nepusz * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 3 of the License, or (at * your option) any later version. * * This program is distributed in the hope that it will be useful, but * WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. */ #include #include #include #include "error.h" #include "gss.h" #include "platform.h" /** * \def PHI * * The golden ratio, i.e. 1+sqrt(5)/2 */ #define PHI 1.618033988749895 /** * \def RESPHI * * Constant defined as 2 - \c PHI */ #define RESPHI 0.3819660112501051 /** * \const _defparam * * Default parameters for the GSS algorithm. */ static const gss_parameter_t _defparam = { /* .epsilon = */ DBL_MIN, /* .on_error = */ GSS_ERROR_STOP }; /** * Stores whether the last optimization run triggered a warning or not. */ static unsigned short int gss_i_warning_flag = 0; void gss_parameter_init(gss_parameter_t *param) { memcpy(param, &_defparam, sizeof(*param)); } unsigned short int gss_get_warning_flag() { return gss_i_warning_flag; } #define TERMINATE { \ if (_min) { \ *(_min) = min; \ } \ if (_fmin) { \ *(_fmin) = fmin; \ } \ } #define EVALUATE(x, fx) { \ fx = proc_evaluate(instance, x); \ if (fmin > fx) { \ min = x; \ fmin = fx; \ } \ if (proc_progress) { \ retval = proc_progress(instance, x, fx, min, fmin, \ (a < b) ? a : b, (a < b) ? b : a, k); \ if (retval) { \ TERMINATE; \ return PLFIT_SUCCESS; \ } \ } \ } int gss(double a, double b, double *_min, double *_fmin, gss_evaluate_t proc_evaluate, gss_progress_t proc_progress, void* instance, const gss_parameter_t *_param) { double c, d, min; double fa, fb, fc, fd, fmin; int k = 0; int retval; unsigned short int successful = 1; gss_parameter_t param = _param ? (*_param) : _defparam; gss_i_warning_flag = 0; if (a > b) { c = a; a = b; b = c; } min = a; fmin = proc_evaluate(instance, a); c = a + RESPHI*(b-a); EVALUATE(a, fa); EVALUATE(b, fb); EVALUATE(c, fc); if (fc >= fa || fc >= fb) { if (param.on_error == GSS_ERROR_STOP) { return PLFIT_FAILURE; } else { gss_i_warning_flag = 1; } } while (fabs(a-b) > param.epsilon) { k++; d = c + RESPHI*(b-c); EVALUATE(d, fd); if (fd >= fa || fd >= fb) { if (param.on_error == GSS_ERROR_STOP) { successful = 0; break; } else { gss_i_warning_flag = 1; } } if (fc <= fd) { b = a; a = d; } else { a = c; c = d; fc = fd; } } if (successful) { c = (a+b) / 2.0; k++; EVALUATE(c, fc); TERMINATE; } return successful ? PLFIT_SUCCESS : PLFIT_FAILURE; } python-igraph-0.8.0/vendor/source/igraph/src/plfit/zeta.c0000644000076500000240000001101013524616145023623 0ustar tamasstaff00000000000000/* specfunc/zeta.c * * Copyright (C) 1996, 1997, 1998, 1999, 2000, 2004 Gerard Jungman * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 3 of the License, or (at * your option) any later version. * * This program is distributed in the hope that it will be useful, but * WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. */ /* Author: G. Jungman */ /* This file was taken from the GNU Scientific Library. Some modifications * were done in order to make it independent from the rest of GSL */ /* #include #include #include #include #include #include #include #include #include "error.h" #include "chebyshev.h" #include "cheb_eval.c" */ #include #include #include "error.h" /*-*-*-*-*-*-*-*-*-*- From gsl_machine.h -*-*-*-*-*-*-*-*-*-*-*-*-*/ #define GSL_LOG_DBL_MIN (-7.0839641853226408e+02) #define GSL_LOG_DBL_MAX 7.0978271289338397e+02 #define GSL_DBL_EPSILON 2.2204460492503131e-16 /*-*-*-*-*-*-*-*-*-* From gsl_sf_result.h *-*-*-*-*-*-*-*-*-*-*-*/ struct gsl_sf_result_struct { double val; double err; }; typedef struct gsl_sf_result_struct gsl_sf_result; /*-*-*-*-*-*-*-*-*-*-*-* Private Section *-*-*-*-*-*-*-*-*-*-*-*/ /* coefficients for Maclaurin summation in hzeta() * B_{2j}/(2j)! */ static double hzeta_c[15] = { 1.00000000000000000000000000000, 0.083333333333333333333333333333, -0.00138888888888888888888888888889, 0.000033068783068783068783068783069, -8.2671957671957671957671957672e-07, 2.0876756987868098979210090321e-08, -5.2841901386874931848476822022e-10, 1.3382536530684678832826980975e-11, -3.3896802963225828668301953912e-13, 8.5860620562778445641359054504e-15, -2.1748686985580618730415164239e-16, 5.5090028283602295152026526089e-18, -1.3954464685812523340707686264e-19, 3.5347070396294674716932299778e-21, -8.9535174270375468504026113181e-23 }; /*-*-*-*-*-*-*-*-*-*-*-* Functions with Error Codes *-*-*-*-*-*-*-*-*-*-*-*/ static int gsl_sf_hzeta_e(const double s, const double q, gsl_sf_result * result) { /* CHECK_POINTER(result) */ if(s <= 1.0 || q <= 0.0) { PLFIT_ERROR("s must be larger than 1.0 and q must be larger than zero", PLFIT_EINVAL); } else { const double max_bits = 54.0; const double ln_term0 = -s * log(q); if(ln_term0 < GSL_LOG_DBL_MIN + 1.0) { PLFIT_ERROR("underflow", PLFIT_UNDRFLOW); } else if(ln_term0 > GSL_LOG_DBL_MAX - 1.0) { PLFIT_ERROR("overflow", PLFIT_OVERFLOW); } else if((s > max_bits && q < 1.0) || (s > 0.5*max_bits && q < 0.25)) { result->val = pow(q, -s); result->err = 2.0 * GSL_DBL_EPSILON * fabs(result->val); return PLFIT_SUCCESS; } else if(s > 0.5*max_bits && q < 1.0) { const double p1 = pow(q, -s); const double p2 = pow(q/(1.0+q), s); const double p3 = pow(q/(2.0+q), s); result->val = p1 * (1.0 + p2 + p3); result->err = GSL_DBL_EPSILON * (0.5*s + 2.0) * fabs(result->val); return PLFIT_SUCCESS; } else { /* Euler-Maclaurin summation formula * [Moshier, p. 400, with several typo corrections] */ const int jmax = 12; const int kmax = 10; int j, k; const double pmax = pow(kmax + q, -s); double scp = s; double pcp = pmax / (kmax + q); double ans = pmax*((kmax+q)/(s-1.0) + 0.5); for(k=0; kval = ans; result->err = 2.0 * (jmax + 1.0) * GSL_DBL_EPSILON * fabs(ans); return PLFIT_SUCCESS; } } } /*-*-*-*-*-*-*-*-*-* Functions w/ Natural Prototypes *-*-*-*-*-*-*-*-*-*-*/ double gsl_sf_hzeta(const double s, const double a) { gsl_sf_result result; gsl_sf_hzeta_e(s, a, &result); return result.val; } python-igraph-0.8.0/vendor/source/igraph/src/plfit/error.c0000644000076500000240000000437113524616145024025 0ustar tamasstaff00000000000000/* error.c * * Copyright (C) 2010-2011 Tamas Nepusz * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 3 of the License, or (at * your option) any later version. * * This program is distributed in the hope that it will be useful, but * WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. */ #include #include #include "error.h" static char *plfit_i_error_strings[] = { "No error", "Failed", "Invalid value", "Underflow", "Overflow", "Not enough memory" }; #ifndef USING_R static plfit_error_handler_t* plfit_error_handler = plfit_error_handler_abort; #else /* This is overwritten, anyway */ static plfit_error_handler_t* plfit_error_handler = plfit_error_handler_ignore; #endif const char* plfit_strerror(const int plfit_errno) { return plfit_i_error_strings[plfit_errno]; } plfit_error_handler_t* plfit_set_error_handler(plfit_error_handler_t* new_handler) { plfit_error_handler_t* old_handler = plfit_error_handler; plfit_error_handler = new_handler; return old_handler; } void plfit_error(const char *reason, const char *file, int line, int plfit_errno) { plfit_error_handler(reason, file, line, plfit_errno); } #ifndef USING_R void plfit_error_handler_abort(const char *reason, const char *file, int line, int plfit_errno) { fprintf(stderr, "Error at %s:%i : %s, %s\n", file, line, reason, plfit_strerror(plfit_errno)); abort(); } #endif #ifndef USING_R void plfit_error_handler_printignore(const char *reason, const char *file, int line, int plfit_errno) { fprintf(stderr, "Error at %s:%i : %s, %s\n", file, line, reason, plfit_strerror(plfit_errno)); } #endif void plfit_error_handler_ignore(const char *reason, const char *file, int line, int plfit_errno) { } python-igraph-0.8.0/vendor/source/igraph/src/plfit/kolmogorov.h0000644000076500000240000000234613524616145025077 0ustar tamasstaff00000000000000/* kolmogorov.h * * Copyright (C) 2010-2011 Tamas Nepusz * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 3 of the License, or (at * your option) any later version. * * This program is distributed in the hope that it will be useful, but * WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. */ #ifndef __KOLMOGOROV_H__ #define __KOLMOGOROV_H__ #undef __BEGIN_DECLS #undef __END_DECLS #ifdef __cplusplus # define __BEGIN_DECLS extern "C" { # define __END_DECLS } #else # define __BEGIN_DECLS /* empty */ # define __END_DECLS /* empty */ #endif #include __BEGIN_DECLS double plfit_kolmogorov(double z); double plfit_ks_test_one_sample_p(double d, size_t n); double plfit_ks_test_two_sample_p(double d, size_t n1, size_t n2); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/src/plfit/plfit.h0000644000076500000240000000676613524616145024031 0ustar tamasstaff00000000000000/* plfit.h * * Copyright (C) 2010-2011 Tamas Nepusz * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 3 of the License, or (at * your option) any later version. * * This program is distributed in the hope that it will be useful, but * WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. */ #ifndef __PLFIT_H__ #define __PLFIT_H__ #include #undef __BEGIN_DECLS #undef __END_DECLS #ifdef __cplusplus # define __BEGIN_DECLS extern "C" { # define __END_DECLS } #else # define __BEGIN_DECLS /* empty */ # define __END_DECLS /* empty */ #endif __BEGIN_DECLS #define PLFIT_VERSION_MAJOR 0 #define PLFIT_VERSION_MINOR 6 #define PLFIT_VERSION_STRING "0.6" typedef unsigned short int plfit_bool_t; typedef enum { PLFIT_GSS_OR_LINEAR, PLFIT_LINEAR_ONLY, PLFIT_DEFAULT_CONTINUOUS_METHOD = PLFIT_GSS_OR_LINEAR } plfit_continuous_method_t; typedef enum { PLFIT_LBFGS, PLFIT_LINEAR_SCAN, PLFIT_PRETEND_CONTINUOUS, PLFIT_DEFAULT_DISCRETE_METHOD = PLFIT_LBFGS } plfit_discrete_method_t; typedef struct _plfit_result_t { double alpha; /* fitted power-law exponent */ double xmin; /* cutoff where the power-law behaviour kicks in */ double L; /* log-likelihood of the sample */ double D; /* test statistic for the KS test */ double p; /* p-value of the KS test */ } plfit_result_t; /********** structure that holds the options of plfit **********/ typedef struct _plfit_continuous_options_t { plfit_bool_t finite_size_correction; plfit_continuous_method_t xmin_method; } plfit_continuous_options_t; typedef struct _plfit_discrete_options_t { plfit_bool_t finite_size_correction; plfit_discrete_method_t alpha_method; struct { double min; double max; double step; } alpha; } plfit_discrete_options_t; int plfit_continuous_options_init(plfit_continuous_options_t* options); int plfit_discrete_options_init(plfit_discrete_options_t* options); extern const plfit_continuous_options_t plfit_continuous_default_options; extern const plfit_discrete_options_t plfit_discrete_default_options; /********** continuous power law distribution fitting **********/ int plfit_log_likelihood_continuous(double* xs, size_t n, double alpha, double xmin, double* l); int plfit_estimate_alpha_continuous(double* xs, size_t n, double xmin, const plfit_continuous_options_t* options, plfit_result_t* result); int plfit_estimate_alpha_continuous_sorted(double* xs, size_t n, double xmin, const plfit_continuous_options_t* options, plfit_result_t* result); int plfit_continuous(double* xs, size_t n, const plfit_continuous_options_t* options, plfit_result_t* result); /********** discrete power law distribution fitting **********/ int plfit_estimate_alpha_discrete(double* xs, size_t n, double xmin, const plfit_discrete_options_t* options, plfit_result_t *result); int plfit_log_likelihood_discrete(double* xs, size_t n, double alpha, double xmin, double* l); int plfit_discrete(double* xs, size_t n, const plfit_discrete_options_t* options, plfit_result_t* result); __END_DECLS #endif /* __PLFIT_H__ */ python-igraph-0.8.0/vendor/source/igraph/src/plfit/lbfgs.c0000644000076500000240000012036013524616145023766 0ustar tamasstaff00000000000000/* * Limited memory BFGS (L-BFGS). * * Copyright (c) 1990, Jorge Nocedal * Copyright (c) 2007-2010 Naoaki Okazaki * All rights reserved. * * Permission is hereby granted, free of charge, to any person obtaining a copy * of this software and associated documentation files (the "Software"), to deal * in the Software without restriction, including without limitation the rights * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell * copies of the Software, and to permit persons to whom the Software is * furnished to do so, subject to the following conditions: * * The above copyright notice and this permission notice shall be included in * all copies or substantial portions of the Software. * * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN * THE SOFTWARE. */ /* $Id: lbfgs.c 65 2010-01-29 12:19:16Z naoaki $ */ /* This library is a C port of the FORTRAN implementation of Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method written by Jorge Nocedal. The original FORTRAN source code is available at: http://www.ece.northwestern.edu/~nocedal/lbfgs.html The L-BFGS algorithm is described in: - Jorge Nocedal. Updating Quasi-Newton Matrices with Limited Storage. Mathematics of Computation, Vol. 35, No. 151, pp. 773--782, 1980. - Dong C. Liu and Jorge Nocedal. On the limited memory BFGS method for large scale optimization. Mathematical Programming B, Vol. 45, No. 3, pp. 503-528, 1989. The line search algorithms used in this implementation are described in: - John E. Dennis and Robert B. Schnabel. Numerical Methods for Unconstrained Optimization and Nonlinear Equations, Englewood Cliffs, 1983. - Jorge J. More and David J. Thuente. Line search algorithm with guaranteed sufficient decrease. ACM Transactions on Mathematical Software (TOMS), Vol. 20, No. 3, pp. 286-307, 1994. This library also implements Orthant-Wise Limited-memory Quasi-Newton (OWL-QN) method presented in: - Galen Andrew and Jianfeng Gao. Scalable training of L1-regularized log-linear models. In Proceedings of the 24th International Conference on Machine Learning (ICML 2007), pp. 33-40, 2007. I would like to thank the original author, Jorge Nocedal, who has been distributing the effieicnt and explanatory implementation in an open source licence. */ #ifdef HAVE_CONFIG_H #include "config.h" #endif/*HAVE_CONFIG_H*/ #ifndef _MSC_VER #include #endif #include #include #include #include "lbfgs.h" #ifdef _MSC_VER #define inline __inline typedef unsigned int uint32_t; #endif/*_MSC_VER*/ #if defined(USE_SSE) && defined(__SSE2__) && LBFGS_FLOAT == 64 /* Use SSE2 optimization for 64bit double precision. */ #include "arithmetic_sse_double.h" #elif defined(USE_SSE) && defined(__SSE__) && LBFGS_FLOAT == 32 /* Use SSE optimization for 32bit float precision. */ #include "arithmetic_sse_float.h" #else /* No CPU specific optimization. */ #include "arithmetic_ansi.h" #endif #define min2(a, b) ((a) <= (b) ? (a) : (b)) #define max2(a, b) ((a) >= (b) ? (a) : (b)) #define max3(a, b, c) max2(max2((a), (b)), (c)); #define is_aligned(p, bytes) \ (((uintptr_t)(const void*)(p)) % (bytes) == 0) struct tag_callback_data { int n; void *instance; lbfgs_evaluate_t proc_evaluate; lbfgs_progress_t proc_progress; }; typedef struct tag_callback_data callback_data_t; struct tag_iteration_data { lbfgsfloatval_t alpha; lbfgsfloatval_t *s; /* [n] */ lbfgsfloatval_t *y; /* [n] */ lbfgsfloatval_t ys; /* vecdot(y, s) */ }; typedef struct tag_iteration_data iteration_data_t; static const lbfgs_parameter_t _defparam = { 6, 1e-5, 0, 1e-5, 0, LBFGS_LINESEARCH_DEFAULT, 40, 1e-20, 1e20, 1e-4, 0.9, 0.9, 1.0e-16, 0.0, 0, -1, }; /* Forward function declarations. */ typedef int (*line_search_proc)( int n, lbfgsfloatval_t *x, lbfgsfloatval_t *f, lbfgsfloatval_t *g, lbfgsfloatval_t *s, lbfgsfloatval_t *stp, const lbfgsfloatval_t* xp, const lbfgsfloatval_t* gp, lbfgsfloatval_t *wa, callback_data_t *cd, const lbfgs_parameter_t *param ); static int line_search_backtracking( int n, lbfgsfloatval_t *x, lbfgsfloatval_t *f, lbfgsfloatval_t *g, lbfgsfloatval_t *s, lbfgsfloatval_t *stp, const lbfgsfloatval_t* xp, const lbfgsfloatval_t* gp, lbfgsfloatval_t *wa, callback_data_t *cd, const lbfgs_parameter_t *param ); static int line_search_backtracking_owlqn( int n, lbfgsfloatval_t *x, lbfgsfloatval_t *f, lbfgsfloatval_t *g, lbfgsfloatval_t *s, lbfgsfloatval_t *stp, const lbfgsfloatval_t* xp, const lbfgsfloatval_t* gp, lbfgsfloatval_t *wp, callback_data_t *cd, const lbfgs_parameter_t *param ); static int line_search_morethuente( int n, lbfgsfloatval_t *x, lbfgsfloatval_t *f, lbfgsfloatval_t *g, lbfgsfloatval_t *s, lbfgsfloatval_t *stp, const lbfgsfloatval_t* xp, const lbfgsfloatval_t* gp, lbfgsfloatval_t *wa, callback_data_t *cd, const lbfgs_parameter_t *param ); static int update_trial_interval( lbfgsfloatval_t *x, lbfgsfloatval_t *fx, lbfgsfloatval_t *dx, lbfgsfloatval_t *y, lbfgsfloatval_t *fy, lbfgsfloatval_t *dy, lbfgsfloatval_t *t, lbfgsfloatval_t *ft, lbfgsfloatval_t *dt, const lbfgsfloatval_t tmin, const lbfgsfloatval_t tmax, int *brackt ); static lbfgsfloatval_t owlqn_x1norm( const lbfgsfloatval_t* x, const int start, const int n ); static void owlqn_pseudo_gradient( lbfgsfloatval_t* pg, const lbfgsfloatval_t* x, const lbfgsfloatval_t* g, const int n, const lbfgsfloatval_t c, const int start, const int end ); static void owlqn_project( lbfgsfloatval_t* d, const lbfgsfloatval_t* sign, const int start, const int end ); #if defined(USE_SSE) && (defined(__SSE__) || defined(__SSE2__)) static int round_out_variables(int n) { n += 7; n /= 8; n *= 8; return n; } #endif/*defined(USE_SSE)*/ lbfgsfloatval_t* lbfgs_malloc(int n) { #if defined(USE_SSE) && (defined(__SSE__) || defined(__SSE2__)) n = round_out_variables(n); #endif/*defined(USE_SSE)*/ return (lbfgsfloatval_t*)vecalloc(sizeof(lbfgsfloatval_t) * (size_t) n); } void lbfgs_free(lbfgsfloatval_t *x) { vecfree(x); } void lbfgs_parameter_init(lbfgs_parameter_t *param) { memcpy(param, &_defparam, sizeof(*param)); } int lbfgs( int n, lbfgsfloatval_t *x, lbfgsfloatval_t *ptr_fx, lbfgs_evaluate_t proc_evaluate, lbfgs_progress_t proc_progress, void *instance, lbfgs_parameter_t *_param ) { int ret; int i, j, k, ls, end, bound; lbfgsfloatval_t step; /* Constant parameters and their default values. */ lbfgs_parameter_t param = (_param != NULL) ? (*_param) : _defparam; const int m = param.m; lbfgsfloatval_t *xp = NULL; lbfgsfloatval_t *g = NULL, *gp = NULL, *pg = NULL; lbfgsfloatval_t *d = NULL, *w = NULL, *pf = NULL; iteration_data_t *lm = NULL, *it = NULL; lbfgsfloatval_t ys, yy; lbfgsfloatval_t xnorm, gnorm, beta; lbfgsfloatval_t fx = 0.; lbfgsfloatval_t rate = 0.; line_search_proc linesearch = line_search_morethuente; /* Construct a callback data. */ callback_data_t cd; cd.n = n; cd.instance = instance; cd.proc_evaluate = proc_evaluate; cd.proc_progress = proc_progress; #if defined(USE_SSE) && (defined(__SSE__) || defined(__SSE2__)) /* Round out the number of variables. */ n = round_out_variables(n); #endif/*defined(USE_SSE)*/ /* Check the input parameters for errors. */ if (n <= 0) { return LBFGSERR_INVALID_N; } #if defined(USE_SSE) && (defined(__SSE__) || defined(__SSE2__)) if (n % 8 != 0) { return LBFGSERR_INVALID_N_SSE; } if (!is_aligned(x, 16)) { return LBFGSERR_INVALID_X_SSE; } #endif/*defined(USE_SSE)*/ if (param.epsilon < 0.) { return LBFGSERR_INVALID_EPSILON; } if (param.past < 0) { return LBFGSERR_INVALID_TESTPERIOD; } if (param.delta < 0.) { return LBFGSERR_INVALID_DELTA; } if (param.min_step < 0.) { return LBFGSERR_INVALID_MINSTEP; } if (param.max_step < param.min_step) { return LBFGSERR_INVALID_MAXSTEP; } if (param.ftol < 0.) { return LBFGSERR_INVALID_FTOL; } if (param.linesearch == LBFGS_LINESEARCH_BACKTRACKING_WOLFE || param.linesearch == LBFGS_LINESEARCH_BACKTRACKING_STRONG_WOLFE) { if (param.wolfe <= param.ftol || 1. <= param.wolfe) { return LBFGSERR_INVALID_WOLFE; } } if (param.gtol < 0.) { return LBFGSERR_INVALID_GTOL; } if (param.xtol < 0.) { return LBFGSERR_INVALID_XTOL; } if (param.max_linesearch <= 0) { return LBFGSERR_INVALID_MAXLINESEARCH; } if (param.orthantwise_c < 0.) { return LBFGSERR_INVALID_ORTHANTWISE; } if (param.orthantwise_start < 0 || n < param.orthantwise_start) { return LBFGSERR_INVALID_ORTHANTWISE_START; } if (param.orthantwise_end < 0) { param.orthantwise_end = n; } if (n < param.orthantwise_end) { return LBFGSERR_INVALID_ORTHANTWISE_END; } if (param.orthantwise_c != 0.) { switch (param.linesearch) { case LBFGS_LINESEARCH_BACKTRACKING: linesearch = line_search_backtracking_owlqn; break; default: /* Only the backtracking method is available. */ return LBFGSERR_INVALID_LINESEARCH; } } else { switch (param.linesearch) { case LBFGS_LINESEARCH_MORETHUENTE: linesearch = line_search_morethuente; break; case LBFGS_LINESEARCH_BACKTRACKING_ARMIJO: case LBFGS_LINESEARCH_BACKTRACKING_WOLFE: case LBFGS_LINESEARCH_BACKTRACKING_STRONG_WOLFE: linesearch = line_search_backtracking; break; default: return LBFGSERR_INVALID_LINESEARCH; } } /* Allocate working space. */ xp = (lbfgsfloatval_t*)vecalloc((size_t) n * sizeof(lbfgsfloatval_t)); g = (lbfgsfloatval_t*)vecalloc((size_t) n * sizeof(lbfgsfloatval_t)); gp = (lbfgsfloatval_t*)vecalloc((size_t) n * sizeof(lbfgsfloatval_t)); d = (lbfgsfloatval_t*)vecalloc((size_t) n * sizeof(lbfgsfloatval_t)); w = (lbfgsfloatval_t*)vecalloc((size_t) n * sizeof(lbfgsfloatval_t)); if (xp == NULL || g == NULL || gp == NULL || d == NULL || w == NULL) { ret = LBFGSERR_OUTOFMEMORY; goto lbfgs_exit; } if (param.orthantwise_c != 0.) { /* Allocate working space for OW-LQN. */ pg = (lbfgsfloatval_t*)vecalloc((size_t) n * sizeof(lbfgsfloatval_t)); if (pg == NULL) { ret = LBFGSERR_OUTOFMEMORY; goto lbfgs_exit; } } /* Allocate limited memory storage. */ lm = (iteration_data_t*)vecalloc((size_t) m * sizeof(iteration_data_t)); if (lm == NULL) { ret = LBFGSERR_OUTOFMEMORY; goto lbfgs_exit; } /* Initialize the limited memory. */ for (i = 0;i < m;++i) { it = &lm[i]; it->alpha = 0; it->ys = 0; it->s = (lbfgsfloatval_t*)vecalloc((size_t) n * sizeof(lbfgsfloatval_t)); it->y = (lbfgsfloatval_t*)vecalloc((size_t) n * sizeof(lbfgsfloatval_t)); if (it->s == NULL || it->y == NULL) { ret = LBFGSERR_OUTOFMEMORY; goto lbfgs_exit; } } /* Allocate an array for storing previous values of the objective function. */ if (0 < param.past) { pf = (lbfgsfloatval_t*)vecalloc((size_t) param.past * sizeof(lbfgsfloatval_t)); } /* Evaluate the function value and its gradient. */ fx = cd.proc_evaluate(cd.instance, x, g, cd.n, 0); if (0. != param.orthantwise_c) { /* Compute the L1 norm of the variable and add it to the object value. */ xnorm = owlqn_x1norm(x, param.orthantwise_start, param.orthantwise_end); fx += xnorm * param.orthantwise_c; owlqn_pseudo_gradient( pg, x, g, n, param.orthantwise_c, param.orthantwise_start, param.orthantwise_end ); } /* Store the initial value of the objective function. */ if (pf != NULL) { pf[0] = fx; } /* Compute the direction; we assume the initial hessian matrix H_0 as the identity matrix. */ if (param.orthantwise_c == 0.) { vecncpy(d, g, n); } else { vecncpy(d, pg, n); } /* Make sure that the initial variables are not a minimizer. */ vec2norm(&xnorm, x, n); if (param.orthantwise_c == 0.) { vec2norm(&gnorm, g, n); } else { vec2norm(&gnorm, pg, n); } if (xnorm < 1.0) xnorm = 1.0; if (gnorm / xnorm <= param.epsilon) { ret = LBFGS_ALREADY_MINIMIZED; goto lbfgs_exit; } /* Compute the initial step: step = 1.0 / sqrt(vecdot(d, d, n)) */ vec2norminv(&step, d, n); k = 1; end = 0; for (;;) { /* Store the current position and gradient vectors. */ veccpy(xp, x, n); veccpy(gp, g, n); /* Search for an optimal step. */ if (param.orthantwise_c == 0.) { ls = linesearch(n, x, &fx, g, d, &step, xp, gp, w, &cd, ¶m); } else { ls = linesearch(n, x, &fx, g, d, &step, xp, pg, w, &cd, ¶m); owlqn_pseudo_gradient( pg, x, g, n, param.orthantwise_c, param.orthantwise_start, param.orthantwise_end ); } if (ls < 0) { /* Revert to the previous point. */ veccpy(x, xp, n); veccpy(g, gp, n); ret = ls; goto lbfgs_exit; } /* Compute x and g norms. */ vec2norm(&xnorm, x, n); if (param.orthantwise_c == 0.) { vec2norm(&gnorm, g, n); } else { vec2norm(&gnorm, pg, n); } /* Report the progress. */ if (cd.proc_progress) { if ((ret = cd.proc_progress(cd.instance, x, g, fx, xnorm, gnorm, step, cd.n, k, ls))) { goto lbfgs_exit; } } /* Convergence test. The criterion is given by the following formula: |g(x)| / \max(1, |x|) < \epsilon */ if (xnorm < 1.0) xnorm = 1.0; if (gnorm / xnorm <= param.epsilon) { /* Convergence. */ ret = LBFGS_SUCCESS; break; } /* Test for stopping criterion. The criterion is given by the following formula: (f(past_x) - f(x)) / f(x) < \delta */ if (pf != NULL) { /* We don't test the stopping criterion while k < past. */ if (param.past <= k) { /* Compute the relative improvement from the past. */ rate = (pf[k % param.past] - fx) / fx; /* The stopping criterion. */ if (rate < param.delta) { ret = LBFGS_STOP; break; } } /* Store the current value of the objective function. */ pf[k % param.past] = fx; } if (param.max_iterations != 0 && param.max_iterations < k+1) { /* Maximum number of iterations. */ ret = LBFGSERR_MAXIMUMITERATION; break; } /* Update vectors s and y: s_{k+1} = x_{k+1} - x_{k} = \step * d_{k}. y_{k+1} = g_{k+1} - g_{k}. */ it = &lm[end]; vecdiff(it->s, x, xp, n); vecdiff(it->y, g, gp, n); /* Compute scalars ys and yy: ys = y^t \cdot s = 1 / \rho. yy = y^t \cdot y. Notice that yy is used for scaling the hessian matrix H_0 (Cholesky factor). */ vecdot(&ys, it->y, it->s, n); vecdot(&yy, it->y, it->y, n); it->ys = ys; /* Recursive formula to compute dir = -(H \cdot g). This is described in page 779 of: Jorge Nocedal. Updating Quasi-Newton Matrices with Limited Storage. Mathematics of Computation, Vol. 35, No. 151, pp. 773--782, 1980. */ bound = (m <= k) ? m : k; ++k; end = (end + 1) % m; /* Compute the steepest direction. */ if (param.orthantwise_c == 0.) { /* Compute the negative of gradients. */ vecncpy(d, g, n); } else { vecncpy(d, pg, n); } j = end; for (i = 0;i < bound;++i) { j = (j + m - 1) % m; /* if (--j == -1) j = m-1; */ it = &lm[j]; /* \alpha_{j} = \rho_{j} s^{t}_{j} \cdot q_{k+1}. */ vecdot(&it->alpha, it->s, d, n); it->alpha /= it->ys; /* q_{i} = q_{i+1} - \alpha_{i} y_{i}. */ vecadd(d, it->y, -it->alpha, n); } vecscale(d, ys / yy, n); for (i = 0;i < bound;++i) { it = &lm[j]; /* \beta_{j} = \rho_{j} y^t_{j} \cdot \gamma_{i}. */ vecdot(&beta, it->y, d, n); beta /= it->ys; /* \gamma_{i+1} = \gamma_{i} + (\alpha_{j} - \beta_{j}) s_{j}. */ vecadd(d, it->s, it->alpha - beta, n); j = (j + 1) % m; /* if (++j == m) j = 0; */ } /* Constrain the search direction for orthant-wise updates. */ if (param.orthantwise_c != 0.) { for (i = param.orthantwise_start;i < param.orthantwise_end;++i) { if (d[i] * pg[i] >= 0) { d[i] = 0; } } } /* Now the search direction d is ready. We try step = 1 first. */ step = 1.0; } lbfgs_exit: /* Return the final value of the objective function. */ if (ptr_fx != NULL) { *ptr_fx = fx; } vecfree(pf); /* Free memory blocks used by this function. */ if (lm != NULL) { for (i = 0;i < m;++i) { vecfree(lm[i].s); vecfree(lm[i].y); } vecfree(lm); } vecfree(pg); vecfree(w); vecfree(d); vecfree(gp); vecfree(g); vecfree(xp); return ret; } static int line_search_backtracking( int n, lbfgsfloatval_t *x, lbfgsfloatval_t *f, lbfgsfloatval_t *g, lbfgsfloatval_t *s, lbfgsfloatval_t *stp, const lbfgsfloatval_t* xp, const lbfgsfloatval_t* gp, lbfgsfloatval_t *wp, callback_data_t *cd, const lbfgs_parameter_t *param ) { int count = 0; lbfgsfloatval_t width, dg; lbfgsfloatval_t finit, dginit = 0., dgtest; const lbfgsfloatval_t dec = 0.5, inc = 2.1; /* Check the input parameters for errors. */ if (*stp <= 0.) { return LBFGSERR_INVALIDPARAMETERS; } /* Compute the initial gradient in the search direction. */ vecdot(&dginit, g, s, n); /* Make sure that s points to a descent direction. */ if (0 < dginit) { return LBFGSERR_INCREASEGRADIENT; } /* The initial value of the objective function. */ finit = *f; dgtest = param->ftol * dginit; for (;;) { veccpy(x, xp, n); vecadd(x, s, *stp, n); /* Evaluate the function and gradient values. */ *f = cd->proc_evaluate(cd->instance, x, g, cd->n, *stp); ++count; if (*f > finit + *stp * dgtest) { width = dec; } else { /* The sufficient decrease condition (Armijo condition). */ if (param->linesearch == LBFGS_LINESEARCH_BACKTRACKING_ARMIJO) { /* Exit with the Armijo condition. */ return count; } /* Check the Wolfe condition. */ vecdot(&dg, g, s, n); if (dg < param->wolfe * dginit) { width = inc; } else { if(param->linesearch == LBFGS_LINESEARCH_BACKTRACKING_WOLFE) { /* Exit with the regular Wolfe condition. */ return count; } /* Check the strong Wolfe condition. */ if(dg > -param->wolfe * dginit) { width = dec; } else { /* Exit with the strong Wolfe condition. */ return count; } } } if (*stp < param->min_step) { /* The step is the minimum value. */ return LBFGSERR_MINIMUMSTEP; } if (*stp > param->max_step) { /* The step is the maximum value. */ return LBFGSERR_MAXIMUMSTEP; } if (param->max_linesearch <= count) { /* Maximum number of iteration. */ return LBFGSERR_MAXIMUMLINESEARCH; } (*stp) *= width; } } static int line_search_backtracking_owlqn( int n, lbfgsfloatval_t *x, lbfgsfloatval_t *f, lbfgsfloatval_t *g, lbfgsfloatval_t *s, lbfgsfloatval_t *stp, const lbfgsfloatval_t* xp, const lbfgsfloatval_t* gp, lbfgsfloatval_t *wp, callback_data_t *cd, const lbfgs_parameter_t *param ) { int i, count = 0; lbfgsfloatval_t width = 0.5, norm = 0.; lbfgsfloatval_t finit = *f, dgtest; /* Check the input parameters for errors. */ if (*stp <= 0.) { return LBFGSERR_INVALIDPARAMETERS; } /* Choose the orthant for the new point. */ for (i = 0;i < n;++i) { wp[i] = (xp[i] == 0.) ? -gp[i] : xp[i]; } for (;;) { /* Update the current point. */ veccpy(x, xp, n); vecadd(x, s, *stp, n); /* The current point is projected onto the orthant. */ owlqn_project(x, wp, param->orthantwise_start, param->orthantwise_end); /* Evaluate the function and gradient values. */ *f = cd->proc_evaluate(cd->instance, x, g, cd->n, *stp); /* Compute the L1 norm of the variables and add it to the object value. */ norm = owlqn_x1norm(x, param->orthantwise_start, param->orthantwise_end); *f += norm * param->orthantwise_c; ++count; dgtest = 0.; for (i = 0;i < n;++i) { dgtest += (x[i] - xp[i]) * gp[i]; } if (*f <= finit + param->ftol * dgtest) { /* The sufficient decrease condition. */ return count; } if (*stp < param->min_step) { /* The step is the minimum value. */ return LBFGSERR_MINIMUMSTEP; } if (*stp > param->max_step) { /* The step is the maximum value. */ return LBFGSERR_MAXIMUMSTEP; } if (param->max_linesearch <= count) { /* Maximum number of iteration. */ return LBFGSERR_MAXIMUMLINESEARCH; } (*stp) *= width; } } static int line_search_morethuente( int n, lbfgsfloatval_t *x, lbfgsfloatval_t *f, lbfgsfloatval_t *g, lbfgsfloatval_t *s, lbfgsfloatval_t *stp, const lbfgsfloatval_t* xp, const lbfgsfloatval_t* gp, lbfgsfloatval_t *wa, callback_data_t *cd, const lbfgs_parameter_t *param ) { int count = 0; int brackt, stage1, uinfo = 0; lbfgsfloatval_t dg; lbfgsfloatval_t stx, fx, dgx; lbfgsfloatval_t sty, fy, dgy; lbfgsfloatval_t fxm, dgxm, fym, dgym, fm, dgm; lbfgsfloatval_t finit, ftest1, dginit, dgtest; lbfgsfloatval_t width, prev_width; lbfgsfloatval_t stmin, stmax; /* Check the input parameters for errors. */ if (*stp <= 0.) { return LBFGSERR_INVALIDPARAMETERS; } /* Compute the initial gradient in the search direction. */ vecdot(&dginit, g, s, n); /* Make sure that s points to a descent direction. */ if (0 < dginit) { return LBFGSERR_INCREASEGRADIENT; } /* Initialize local variables. */ brackt = 0; stage1 = 1; finit = *f; dgtest = param->ftol * dginit; width = param->max_step - param->min_step; prev_width = 2.0 * width; /* The variables stx, fx, dgx contain the values of the step, function, and directional derivative at the best step. The variables sty, fy, dgy contain the value of the step, function, and derivative at the other endpoint of the interval of uncertainty. The variables stp, f, dg contain the values of the step, function, and derivative at the current step. */ stx = sty = 0.; fx = fy = finit; dgx = dgy = dginit; for (;;) { /* Set the minimum and maximum steps to correspond to the present interval of uncertainty. */ if (brackt) { stmin = min2(stx, sty); stmax = max2(stx, sty); } else { stmin = stx; stmax = *stp + 4.0 * (*stp - stx); } /* Clip the step in the range of [stpmin, stpmax]. */ if (*stp < param->min_step) *stp = param->min_step; if (param->max_step < *stp) *stp = param->max_step; /* If an unusual termination is to occur then let stp be the lowest point obtained so far. */ if ((brackt && ((*stp <= stmin || stmax <= *stp) || param->max_linesearch <= count + 1 || uinfo != 0)) || (brackt && (stmax - stmin <= param->xtol * stmax))) { *stp = stx; } /* Compute the current value of x: x <- x + (*stp) * s. */ veccpy(x, xp, n); vecadd(x, s, *stp, n); /* Evaluate the function and gradient values. */ *f = cd->proc_evaluate(cd->instance, x, g, cd->n, *stp); vecdot(&dg, g, s, n); ftest1 = finit + *stp * dgtest; ++count; /* Test for errors and convergence. */ if (brackt && ((*stp <= stmin || stmax <= *stp) || uinfo != 0)) { /* Rounding errors prevent further progress. */ return LBFGSERR_ROUNDING_ERROR; } if (*stp == param->max_step && *f <= ftest1 && dg <= dgtest) { /* The step is the maximum value. */ return LBFGSERR_MAXIMUMSTEP; } if (*stp == param->min_step && (ftest1 < *f || dgtest <= dg)) { /* The step is the minimum value. */ return LBFGSERR_MINIMUMSTEP; } if (brackt && (stmax - stmin) <= param->xtol * stmax) { /* Relative width of the interval of uncertainty is at most xtol. */ return LBFGSERR_WIDTHTOOSMALL; } if (param->max_linesearch <= count) { /* Maximum number of iteration. */ return LBFGSERR_MAXIMUMLINESEARCH; } if (*f <= ftest1 && fabs(dg) <= param->gtol * (-dginit)) { /* The sufficient decrease condition and the directional derivative condition hold. */ return count; } /* In the first stage we seek a step for which the modified function has a nonpositive value and nonnegative derivative. */ if (stage1 && *f <= ftest1 && min2(param->ftol, param->gtol) * dginit <= dg) { stage1 = 0; } /* A modified function is used to predict the step only if we have not obtained a step for which the modified function has a nonpositive function value and nonnegative derivative, and if a lower function value has been obtained but the decrease is not sufficient. */ if (stage1 && ftest1 < *f && *f <= fx) { /* Define the modified function and derivative values. */ fm = *f - *stp * dgtest; fxm = fx - stx * dgtest; fym = fy - sty * dgtest; dgm = dg - dgtest; dgxm = dgx - dgtest; dgym = dgy - dgtest; /* Call update_trial_interval() to update the interval of uncertainty and to compute the new step. */ uinfo = update_trial_interval( &stx, &fxm, &dgxm, &sty, &fym, &dgym, stp, &fm, &dgm, stmin, stmax, &brackt ); /* Reset the function and gradient values for f. */ fx = fxm + stx * dgtest; fy = fym + sty * dgtest; dgx = dgxm + dgtest; dgy = dgym + dgtest; } else { /* Call update_trial_interval() to update the interval of uncertainty and to compute the new step. */ uinfo = update_trial_interval( &stx, &fx, &dgx, &sty, &fy, &dgy, stp, f, &dg, stmin, stmax, &brackt ); } /* Force a sufficient decrease in the interval of uncertainty. */ if (brackt) { if (0.66 * prev_width <= fabs(sty - stx)) { *stp = stx + 0.5 * (sty - stx); } prev_width = width; width = fabs(sty - stx); } } return LBFGSERR_LOGICERROR; } /** * Define the local variables for computing minimizers. */ #define USES_MINIMIZER \ lbfgsfloatval_t a, d, gamma, theta, p, q, r, s; /** * Find a minimizer of an interpolated cubic function. * @param cm The minimizer of the interpolated cubic. * @param u The value of one point, u. * @param fu The value of f(u). * @param du The value of f'(u). * @param v The value of another point, v. * @param fv The value of f(v). * @param du The value of f'(v). */ #define CUBIC_MINIMIZER(cm, u, fu, du, v, fv, dv) \ d = (v) - (u); \ theta = ((fu) - (fv)) * 3 / d + (du) + (dv); \ p = fabs(theta); \ q = fabs(du); \ r = fabs(dv); \ s = max3(p, q, r); \ /* gamma = s*sqrt((theta/s)**2 - (du/s) * (dv/s)) */ \ a = theta / s; \ gamma = s * sqrt(a * a - ((du) / s) * ((dv) / s)); \ if ((v) < (u)) gamma = -gamma; \ p = gamma - (du) + theta; \ q = gamma - (du) + gamma + (dv); \ r = p / q; \ (cm) = (u) + r * d; /** * Find a minimizer of an interpolated cubic function. * @param cm The minimizer of the interpolated cubic. * @param u The value of one point, u. * @param fu The value of f(u). * @param du The value of f'(u). * @param v The value of another point, v. * @param fv The value of f(v). * @param du The value of f'(v). * @param xmin The maximum value. * @param xmin The minimum value. */ #define CUBIC_MINIMIZER2(cm, u, fu, du, v, fv, dv, xmin, xmax) \ d = (v) - (u); \ theta = ((fu) - (fv)) * 3 / d + (du) + (dv); \ p = fabs(theta); \ q = fabs(du); \ r = fabs(dv); \ s = max3(p, q, r); \ /* gamma = s*sqrt((theta/s)**2 - (du/s) * (dv/s)) */ \ a = theta / s; \ gamma = s * sqrt(max2(0, a * a - ((du) / s) * ((dv) / s))); \ if ((u) < (v)) gamma = -gamma; \ p = gamma - (dv) + theta; \ q = gamma - (dv) + gamma + (du); \ r = p / q; \ if (r < 0. && gamma != 0.) { \ (cm) = (v) - r * d; \ } else if (a < 0) { \ (cm) = (xmax); \ } else { \ (cm) = (xmin); \ } /** * Find a minimizer of an interpolated quadratic function. * @param qm The minimizer of the interpolated quadratic. * @param u The value of one point, u. * @param fu The value of f(u). * @param du The value of f'(u). * @param v The value of another point, v. * @param fv The value of f(v). */ #define QUARD_MINIMIZER(qm, u, fu, du, v, fv) \ a = (v) - (u); \ (qm) = (u) + (du) / (((fu) - (fv)) / a + (du)) / 2 * a; /** * Find a minimizer of an interpolated quadratic function. * @param qm The minimizer of the interpolated quadratic. * @param u The value of one point, u. * @param du The value of f'(u). * @param v The value of another point, v. * @param dv The value of f'(v). */ #define QUARD_MINIMIZER2(qm, u, du, v, dv) \ a = (u) - (v); \ (qm) = (v) + (dv) / ((dv) - (du)) * a; /** * Update a safeguarded trial value and interval for line search. * * The parameter x represents the step with the least function value. * The parameter t represents the current step. This function assumes * that the derivative at the point of x in the direction of the step. * If the bracket is set to true, the minimizer has been bracketed in * an interval of uncertainty with endpoints between x and y. * * @param x The pointer to the value of one endpoint. * @param fx The pointer to the value of f(x). * @param dx The pointer to the value of f'(x). * @param y The pointer to the value of another endpoint. * @param fy The pointer to the value of f(y). * @param dy The pointer to the value of f'(y). * @param t The pointer to the value of the trial value, t. * @param ft The pointer to the value of f(t). * @param dt The pointer to the value of f'(t). * @param tmin The minimum value for the trial value, t. * @param tmax The maximum value for the trial value, t. * @param brackt The pointer to the predicate if the trial value is * bracketed. * @retval int Status value. Zero indicates a normal termination. * * @see * Jorge J. More and David J. Thuente. Line search algorithm with * guaranteed sufficient decrease. ACM Transactions on Mathematical * Software (TOMS), Vol 20, No 3, pp. 286-307, 1994. */ static int update_trial_interval( lbfgsfloatval_t *x, lbfgsfloatval_t *fx, lbfgsfloatval_t *dx, lbfgsfloatval_t *y, lbfgsfloatval_t *fy, lbfgsfloatval_t *dy, lbfgsfloatval_t *t, lbfgsfloatval_t *ft, lbfgsfloatval_t *dt, const lbfgsfloatval_t tmin, const lbfgsfloatval_t tmax, int *brackt ) { int bound; int dsign = fsigndiff(dt, dx); lbfgsfloatval_t mc; /* minimizer of an interpolated cubic. */ lbfgsfloatval_t mq; /* minimizer of an interpolated quadratic. */ lbfgsfloatval_t newt; /* new trial value. */ USES_MINIMIZER; /* for CUBIC_MINIMIZER and QUARD_MINIMIZER. */ /* Check the input parameters for errors. */ if (*brackt) { if (*t <= min2(*x, *y) || max2(*x, *y) <= *t) { /* The trival value t is out of the interval. */ return LBFGSERR_OUTOFINTERVAL; } if (0. <= *dx * (*t - *x)) { /* The function must decrease from x. */ return LBFGSERR_INCREASEGRADIENT; } if (tmax < tmin) { /* Incorrect tmin and tmax specified. */ return LBFGSERR_INCORRECT_TMINMAX; } } /* Trial value selection. */ if (*fx < *ft) { /* Case 1: a higher function value. The minimum is brackt. If the cubic minimizer is closer to x than the quadratic one, the cubic one is taken, else the average of the minimizers is taken. */ *brackt = 1; bound = 1; CUBIC_MINIMIZER(mc, *x, *fx, *dx, *t, *ft, *dt); QUARD_MINIMIZER(mq, *x, *fx, *dx, *t, *ft); if (fabs(mc - *x) < fabs(mq - *x)) { newt = mc; } else { newt = mc + 0.5 * (mq - mc); } } else if (dsign) { /* Case 2: a lower function value and derivatives of opposite sign. The minimum is brackt. If the cubic minimizer is closer to x than the quadratic (secant) one, the cubic one is taken, else the quadratic one is taken. */ *brackt = 1; bound = 0; CUBIC_MINIMIZER(mc, *x, *fx, *dx, *t, *ft, *dt); QUARD_MINIMIZER2(mq, *x, *dx, *t, *dt); if (fabs(mc - *t) > fabs(mq - *t)) { newt = mc; } else { newt = mq; } } else if (fabs(*dt) < fabs(*dx)) { /* Case 3: a lower function value, derivatives of the same sign, and the magnitude of the derivative decreases. The cubic minimizer is only used if the cubic tends to infinity in the direction of the minimizer or if the minimum of the cubic is beyond t. Otherwise the cubic minimizer is defined to be either tmin or tmax. The quadratic (secant) minimizer is also computed and if the minimum is brackt then the the minimizer closest to x is taken, else the one farthest away is taken. */ bound = 1; CUBIC_MINIMIZER2(mc, *x, *fx, *dx, *t, *ft, *dt, tmin, tmax); QUARD_MINIMIZER2(mq, *x, *dx, *t, *dt); if (*brackt) { if (fabs(*t - mc) < fabs(*t - mq)) { newt = mc; } else { newt = mq; } } else { if (fabs(*t - mc) > fabs(*t - mq)) { newt = mc; } else { newt = mq; } } } else { /* Case 4: a lower function value, derivatives of the same sign, and the magnitude of the derivative does not decrease. If the minimum is not brackt, the step is either tmin or tmax, else the cubic minimizer is taken. */ bound = 0; if (*brackt) { CUBIC_MINIMIZER(newt, *t, *ft, *dt, *y, *fy, *dy); } else if (*x < *t) { newt = tmax; } else { newt = tmin; } } /* Update the interval of uncertainty. This update does not depend on the new step or the case analysis above. - Case a: if f(x) < f(t), x <- x, y <- t. - Case b: if f(t) <= f(x) && f'(t)*f'(x) > 0, x <- t, y <- y. - Case c: if f(t) <= f(x) && f'(t)*f'(x) < 0, x <- t, y <- x. */ if (*fx < *ft) { /* Case a */ *y = *t; *fy = *ft; *dy = *dt; } else { /* Case c */ if (dsign) { *y = *x; *fy = *fx; *dy = *dx; } /* Cases b and c */ *x = *t; *fx = *ft; *dx = *dt; } /* Clip the new trial value in [tmin, tmax]. */ if (tmax < newt) newt = tmax; if (newt < tmin) newt = tmin; /* Redefine the new trial value if it is close to the upper bound of the interval. */ if (*brackt && bound) { mq = *x + 0.66 * (*y - *x); if (*x < *y) { if (mq < newt) newt = mq; } else { if (newt < mq) newt = mq; } } /* Return the new trial value. */ *t = newt; return 0; } static lbfgsfloatval_t owlqn_x1norm( const lbfgsfloatval_t* x, const int start, const int n ) { int i; lbfgsfloatval_t norm = 0.; for (i = start;i < n;++i) { norm += fabs(x[i]); } return norm; } static void owlqn_pseudo_gradient( lbfgsfloatval_t* pg, const lbfgsfloatval_t* x, const lbfgsfloatval_t* g, const int n, const lbfgsfloatval_t c, const int start, const int end ) { int i; /* Compute the negative of gradients. */ for (i = 0;i < start;++i) { pg[i] = g[i]; } /* Compute the psuedo-gradients. */ for (i = start;i < end;++i) { if (x[i] < 0.) { /* Differentiable. */ pg[i] = g[i] - c; } else if (0. < x[i]) { /* Differentiable. */ pg[i] = g[i] + c; } else { if (g[i] < -c) { /* Take the right partial derivative. */ pg[i] = g[i] + c; } else if (c < g[i]) { /* Take the left partial derivative. */ pg[i] = g[i] - c; } else { pg[i] = 0.; } } } for (i = end;i < n;++i) { pg[i] = g[i]; } } static void owlqn_project( lbfgsfloatval_t* d, const lbfgsfloatval_t* sign, const int start, const int end ) { int i; for (i = start;i < end;++i) { if (d[i] * sign[i] <= 0) { d[i] = 0; } } } python-igraph-0.8.0/vendor/source/igraph/src/plfit/gss.h0000644000076500000240000001366013524616145023476 0ustar tamasstaff00000000000000/* gss.h * * Copyright (C) 2012 Tamas Nepusz * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 3 of the License, or (at * your option) any later version. * * This program is distributed in the hope that it will be useful, but * WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. */ #ifndef __GSS_H__ #define __GSS_H__ #undef __BEGIN_DECLS #undef __END_DECLS #ifdef __cplusplus # define __BEGIN_DECLS extern "C" { # define __END_DECLS } #else # define __BEGIN_DECLS /* empty */ # define __END_DECLS /* empty */ #endif __BEGIN_DECLS /** * Enum specifying what the search should do when the function is not U-shaped. */ typedef enum { GSS_ERROR_STOP, /**< Stop and return an error code */ GSS_ERROR_WARN /**< Continue and set the warning flag */ } gss_error_handling_t; /** * Parameter settings for a golden section search. */ typedef struct { double epsilon; gss_error_handling_t on_error; } gss_parameter_t; /** * Callback interface to provide objective function evaluations for the golden * section search. * * The gss() function calls this function to obtain the values of the objective * function when needed. A client program must implement this function to evaluate * the value of the objective function, given the location. * * @param instance The user data sent for the gss() function by the client. * @param x The current value of the variable. * @retval double The value of the objective function for the current * variable. */ typedef double (*gss_evaluate_t)(void *instance, double x); /** * Callback interface to receive the progress of the optimization process for * the golden section search. * * The gss() function calls this function for each iteration. Implementing * this function, a client program can store or display the current progress * of the optimization process. * * @param instance The user data sent for the gss() function by the client. * @param x The current value of the variable. * @param fx The value of the objective function at x. * @param min The location of the minimum value of the objective * function found so far. * @param fmin The minimum value of the objective function found so far. * @param left The left side of the current bracket. * @param right The right side of the current bracket. * @param k The index of the current iteration. * @retval int Zero to continue the optimization process. Returning a * non-zero value will cancel the optimization process. */ typedef int (*gss_progress_t)(void *instance, double x, double fx, double min, double fmin, double left, double right, int k); /** * Start a golden section search optimization. * * @param a The left side of the bracket to start from * @param b The right side of the bracket to start from * @param min The pointer to the variable that receives the location of the * final value of the objective function. This argument can be set to * \c NULL if the location of the final value of the objective * function is unnecessary. * @param fmin The pointer to the variable that receives the final value of * the objective function. This argument can be st to \c NULL if the * final value of the objective function is unnecessary. * @param proc_evaluate The callback function to evaluate the objective * function at a given location. * @param proc_progress The callback function to receive the progress (the * last evaluated location, the value of the objective * function at that location, the width of the current * bracket, the minimum found so far and the step * count). This argument can be set to \c NULL if * a progress report is unnecessary. * @param instance A user data for the client program. The callback * functions will receive the value of this argument. * @param param The pointer to a structure representing parameters for * GSS algorithm. A client program can set this parameter * to \c NULL to use the default parameters. * Call the \ref gss_parameter_init() function to fill a * structure with the default values. * @retval int The status code. This function returns zero if the * minimization process terminates without an error. A * non-zero value indicates an error; in particular, * \c PLFIT_FAILURE means that the function is not * U-shaped. */ int gss(double a, double b, double *min, double *fmin, gss_evaluate_t proc_evaluate, gss_progress_t proc_progress, void* instance, const gss_parameter_t *_param); /** * Return the state of the warning flag. * * The warning flag is 1 if the last optimization was run on a function that * was not U-shaped. */ unsigned short int gss_get_warning_flag(); /** * Initialize GSS parameters to the default values. * * Call this function to fill a parameter structure with the default values * and overwrite parameter values if necessary. * * @param param The pointer to the parameter structure. */ void gss_parameter_init(gss_parameter_t *param); __END_DECLS #endif /* __GSS_H__ */ python-igraph-0.8.0/vendor/source/igraph/src/plfit/platform.h0000644000076500000240000000250613524616145024523 0ustar tamasstaff00000000000000/* platform.h * * Copyright (C) 2010-2011 Tamas Nepusz * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 3 of the License, or (at * your option) any later version. * * This program is distributed in the hope that it will be useful, but * WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. */ #ifndef __PLATFORM_H__ #define __PLATFORM_H__ #undef __BEGIN_DECLS #undef __END_DECLS #ifdef __cplusplus # define __BEGIN_DECLS extern "C" { # define __END_DECLS } #else # define __BEGIN_DECLS /* empty */ # define __END_DECLS /* empty */ #endif #include __BEGIN_DECLS #ifdef _MSC_VER #define snprintf sprintf_s #define inline __inline #define isnan(x) _isnan(x) #define isfinite(x) _finite(x) #endif #ifndef INFINITY # define INFINITY (1.0/0.0) #endif #ifndef NAN # define NAN (INFINITY-INFINITY) #endif __END_DECLS #endif /* __PLATFORM_H__ */ python-igraph-0.8.0/vendor/source/igraph/src/plfit/options.c0000644000076500000240000000272113524616145024364 0ustar tamasstaff00000000000000/* options.c * * Copyright (C) 2012 Tamas Nepusz * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 3 of the License, or (at * your option) any later version. * * This program is distributed in the hope that it will be useful, but * WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. */ #include "error.h" #include "plfit.h" const plfit_continuous_options_t plfit_continuous_default_options = { /* .finite_size_correction = */ 0, /* .xmin_method = */ PLFIT_GSS_OR_LINEAR }; const plfit_discrete_options_t plfit_discrete_default_options = { /* .finite_size_correction = */ 0, /* .alpha_method = */ PLFIT_LBFGS, /* .alpha = */ { /* .min = */ 1.01, /* .max = */ 5, /* .step = */ 0.01 } }; int plfit_continuous_options_init(plfit_continuous_options_t* options) { *options = plfit_continuous_default_options; return PLFIT_SUCCESS; } int plfit_discrete_options_init(plfit_discrete_options_t* options) { *options = plfit_discrete_default_options; return PLFIT_SUCCESS; } python-igraph-0.8.0/vendor/source/igraph/src/NetRoutines.cpp0000644000076500000240000002406413614300625024367 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ /* The original version of this file was written by Jörg Reichardt The original copyright notice follows here */ /*************************************************************************** NetRoutines.cpp - description ------------------- begin : Tue Oct 28 2003 copyright : (C) 2003 by Joerg Reichardt email : reichardt@mitte ***************************************************************************/ /*************************************************************************** * * * This program is free software; you can redistribute it and/or modify * * it under the terms of the GNU General Public License as published by * * the Free Software Foundation; either version 2 of the License, or * * (at your option) any later version. * * * ***************************************************************************/ #include #include #include #include "NetRoutines.h" #include "NetDataTypes.h" #include "igraph_types.h" #include "igraph_interface.h" #include "igraph_conversion.h" int igraph_i_read_network(const igraph_t *graph, const igraph_vector_t *weights, network *net, igraph_bool_t use_weights, unsigned int states) { double av_k = 0.0, sum_weight = 0.0, min_weight = 1e60, max_weight = -1e60; unsigned long min_k = 999999999, max_k = 0; long max_index = 0; char name[255]; NNode *node1, *node2; DLList_Iter iter; igraph_vector_t edgelist; long int no_of_edges = (long int)igraph_ecount(graph); long int ii; char *empty = new char[1]; empty[0] = '\0'; IGRAPH_VECTOR_INIT_FINALLY(&edgelist, no_of_edges * 2); IGRAPH_CHECK(igraph_get_edgelist(graph, &edgelist, 0 /* rowwise */)); for (ii = 0; ii < no_of_edges; ii++) { long int i1 = (long int)VECTOR(edgelist)[2 * ii] + 1; long int i2 = (long int)VECTOR(edgelist)[2 * ii + 1] + 1; igraph_real_t Links; if (use_weights) { Links = VECTOR(*weights)[ii]; } else { Links = 1.0; } // From the original source if (max_index < i1) { for (int i = max_index; i < i1; i++) { net->node_list->Push(new NNode(i, 0, net->link_list, empty, states)); } max_index = i1; } if (max_index < i2) { for (int i = max_index; i < i2; i++) { net->node_list->Push(new NNode(i, 0, net->link_list, empty, states)); } max_index = i2; } node1 = net->node_list->Get(i1 - 1); sprintf(name, "%li", i1); node1->Set_Name(name); node2 = net->node_list->Get(i2 - 1); sprintf(name, "%li", i2); node2->Set_Name(name); node1->Connect_To(node2, Links); if (Links < min_weight) { min_weight = Links; } if (Links > max_weight) { max_weight = Links; } sum_weight += Links; } IGRAPH_FINALLY_CLEAN(1); igraph_vector_destroy(&edgelist); node1 = iter.First(net->node_list); while (!iter.End()) { if (node1->Get_Degree() > max_k) { max_k = node1->Get_Degree(); } if (node1->Get_Degree() < min_k) { min_k = node1->Get_Degree(); } av_k += node1->Get_Degree(); node1 = iter.Next(); } net->av_k = av_k / double(net->node_list->Size()); net->sum_weights = sum_weight; net->av_weight = sum_weight / double(net->link_list->Size()); net->min_k = min_k; net->max_k = max_k; net->min_weight = min_weight; net->max_weight = max_weight; net->sum_bids = 0; net->min_bids = 0; net->max_bids = 0; delete [] empty; return 0; } //############################################################################################################### void reduce_cliques(DLList*> *global_cluster_list, FILE *file) { unsigned long size; ClusterList *c_cur, *largest_c = 0; DLList*> *subsets; DLList_Iter*> c_iter, sub_iter; DLList_Iter iter; NNode *n_cur; if (!(global_cluster_list->Size())) { return; } //wir suchen den groessten Cluster c_cur = c_iter.First(global_cluster_list); size = 0; while (!(c_iter.End())) { if (c_cur->Size() > size) { size = c_cur->Size(); largest_c = c_cur; } c_cur = c_iter.Next(); } // printf("Groesster Cluster hat %u Elemente.\n",largest_c->Size()); //Schauen, ob es Teilmengen gibt, die ebenfalls gefunden wurden subsets = new DLList*>(); c_cur = c_iter.First(global_cluster_list); while (!(c_iter.End())) { if ((*c_cur < *largest_c || *c_cur == *largest_c) && c_cur != largest_c) { //alle echten Teilcluster von largest_c und die doppelten subsets->Push(c_cur); } c_cur = c_iter.Next(); } // die gefundenen Subsets werden aus der cluster_liste geloescht while (subsets->Size()) { global_cluster_list->fDelete(subsets->Pop()); } delete subsets; // Dann schreiben wir den groessten Cluster in das File fprintf(file, "Energie: %1.12f Nodes:%3lu - ", largest_c->Get_Energy(), largest_c->Size()); n_cur = iter.First(largest_c); while (!(iter.End())) { fprintf(file, "%s", n_cur->Get_Name()); n_cur = iter.Next(); if (n_cur) { fprintf(file, ", "); } } fprintf(file, "\n"); //Schliesslich schmeissen wir noch den eben gefundenen groessten Cluster raus global_cluster_list->fDelete(largest_c); //und dann geht es von vorn mit der Reduzierten ClusterListe los reduce_cliques(global_cluster_list, file); } //################################################################################## void reduce_cliques2(network *net, bool only_double, long marker) { unsigned long size; ClusterList *c_cur, *largest_c = 0; DLList_Iter*> c_iter; do { //wir suchen den groessten, nicht markierten Cluster size = 0; c_cur = c_iter.First(net->cluster_list); while (!(c_iter.End())) { if ((c_cur->Size() > size) && (c_cur->Get_Marker() != marker)) { size = c_cur->Size(); largest_c = c_cur; } c_cur = c_iter.Next(); } // printf("Groesster Cluster hat %u Elemente.\n",largest_c->Size()); //Schauen, ob es Teilmengen gibt, die ebenfalls gefunden wurden c_cur = c_iter.First(net->cluster_list); while (!(c_iter.End())) { if (((!only_double && (*c_cur < *largest_c)) || (*c_cur == *largest_c)) && (c_cur != largest_c)) { //alle echten Teilcluster von largest_c und die doppelten net->cluster_list->fDelete(c_cur); while (c_cur->Get_Candidates()->Size()) { c_cur->Get_Candidates()->Pop(); } while (c_cur->Size()) { c_cur->Pop(); // die knoten aber nicht loeschen!! } delete c_cur; // nicht vergessen, die global geloeschte Clusterliste zu loeschen } c_cur = c_iter.Next(); } //Schliesslich markieren wir noch den eben gefundenen groessten Cluster largest_c->Set_Marker(marker); } while (size); } //################################################################################################## unsigned long iterate_nsf_hierarchy(NNode *parent, unsigned long depth, FILE *file) { NNode* next_node; unsigned long newdepth, maxdepth; bool first = true; DLList_Iter *iter; maxdepth = newdepth = depth; iter = new DLList_Iter; next_node = iter->First(parent->Get_Neighbours()); while (!(iter->End())) { if (next_node->Get_Marker() > parent->Get_Marker()) { // wir gehen nach unten if (first) { fprintf(file, ",("); // eine Neue Klammer auf } if (first) { fprintf(file, "%s", next_node->Get_Name()); // nur vor dem ersten kein Komma } else { fprintf(file, ",%s", next_node->Get_Name()); // sonst immer mit Komma } first = false; newdepth = iterate_nsf_hierarchy(next_node, depth + 1, file); if (maxdepth < newdepth) { maxdepth = newdepth; } } next_node = iter->Next(); } if (!first) { fprintf(file, ")"); //hat es ueberhaupt einen gegeben? } //dann klamer zu! delete iter; return maxdepth; } //################################################################ void clear_all_markers(network *net) { DLList_Iter iter; NNode *n_cur; n_cur = iter.First(net->node_list); while (!iter.End()) { n_cur->Set_Marker(0); n_cur = iter.Next(); } } python-igraph-0.8.0/vendor/source/igraph/src/igraph_estack.h0000644000076500000240000000307013614300625024353 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_ESTACK_H #define IGRAPH_ESTACK_H #include "igraph_stack.h" #include "igraph_vector.h" typedef struct igraph_estack_t { igraph_stack_long_t stack; igraph_vector_bool_t isin; } igraph_estack_t; int igraph_estack_init(igraph_estack_t *s, long int setsize, long int stacksize); void igraph_estack_destroy(igraph_estack_t *s); int igraph_estack_push(igraph_estack_t *s, long int elem); long int igraph_estack_pop(igraph_estack_t *s); igraph_bool_t igraph_estack_iselement(const igraph_estack_t *s, long int elem); long int igraph_estack_size(const igraph_estack_t *s); int igraph_estack_print(const igraph_estack_t *s); #endif python-igraph-0.8.0/vendor/source/igraph/src/igraph_blas_internal.h0000644000076500000240000000421013614300625025713 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef BLAS_INTERNAL_H #define BLAS_INTERNAL_H /* Note: only files calling the BLAS routines directly need to include this header. */ #include "igraph_types.h" #include "config.h" #ifndef INTERNAL_BLAS #define igraphdaxpy_ daxpy_ #define igraphdger_ dger_ #define igraphdcopy_ dcopy_ #define igraphdscal_ dscal_ #define igraphdswap_ dswap_ #define igraphdgemm_ dgemm_ #define igraphdgemv_ dgemv_ #define igraphddot_ ddot_ #define igraphdnrm2_ dnrm2_ #define igraphlsame_ lsame_ #define igraphdrot_ drot_ #define igraphidamax_ idamax_ #define igraphdtrmm_ dtrmm_ #define igraphdasum_ dasum_ #define igraphdtrsm_ dtrsm_ #define igraphdtrsv_ dtrsv_ #define igraphdnrm2_ dnrm2_ #endif int igraphdgemv_(char *trans, int *m, int *n, igraph_real_t *alpha, igraph_real_t *a, int *lda, igraph_real_t *x, int *incx, igraph_real_t *beta, igraph_real_t *y, int *incy); int igraphdgemm_(char *transa, char *transb, int *m, int *n, int *k, double *alpha, double *a, int *lda, double *b, int *ldb, double *beta, double *c__, int *ldc); double igraphdnrm2_(int *n, double *x, int *incx); #endif python-igraph-0.8.0/vendor/source/igraph/src/components.c0000644000076500000240000013314613614300625023737 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2003-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_components.h" #include "igraph_memory.h" #include "igraph_interface.h" #include "igraph_adjlist.h" #include "igraph_interrupt_internal.h" #include "igraph_progress.h" #include "igraph_structural.h" #include "igraph_dqueue.h" #include "igraph_stack.h" #include "igraph_vector.h" #include "config.h" #include #include static int igraph_i_clusters_weak(const igraph_t *graph, igraph_vector_t *membership, igraph_vector_t *csize, igraph_integer_t *no); static int igraph_i_clusters_strong(const igraph_t *graph, igraph_vector_t *membership, igraph_vector_t *csize, igraph_integer_t *no); /** * \ingroup structural * \function igraph_clusters * \brief Calculates the (weakly or strongly) connected components in a graph. * * \param graph The graph object to analyze. * \param membership First half of the result will be stored here. For * every vertex the id of its component is given. The vector * has to be preinitialized and will be resized. Alternatively * this argument can be \c NULL, in which case it is ignored. * \param csize The second half of the result. For every component it * gives its size, the order is defined by the component ids. * The vector has to be preinitialized and will be resized. * Alternatively this argument can be \c NULL, in which * case it is ignored. * \param no Pointer to an integer, if not \c NULL then the number of * clusters will be stored here. * \param mode For directed graph this specifies whether to calculate * weakly or strongly connected components. Possible values: * \c IGRAPH_WEAK, * \c IGRAPH_STRONG. This argument is * ignored for undirected graphs. * \return Error code: * \c IGRAPH_EINVAL: invalid mode argument. * * Time complexity: O(|V|+|E|), * |V| and * |E| are the number of vertices and * edges in the graph. */ int igraph_clusters(const igraph_t *graph, igraph_vector_t *membership, igraph_vector_t *csize, igraph_integer_t *no, igraph_connectedness_t mode) { if (mode == IGRAPH_WEAK || !igraph_is_directed(graph)) { return igraph_i_clusters_weak(graph, membership, csize, no); } else if (mode == IGRAPH_STRONG) { return igraph_i_clusters_strong(graph, membership, csize, no); } else { IGRAPH_ERROR("Cannot calculate clusters", IGRAPH_EINVAL); } return 1; } static int igraph_i_clusters_weak(const igraph_t *graph, igraph_vector_t *membership, igraph_vector_t *csize, igraph_integer_t *no) { long int no_of_nodes = igraph_vcount(graph); char *already_added; long int first_node, act_cluster_size = 0, no_of_clusters = 1; igraph_dqueue_t q = IGRAPH_DQUEUE_NULL; long int i; igraph_vector_t neis = IGRAPH_VECTOR_NULL; already_added = igraph_Calloc(no_of_nodes, char); if (already_added == 0) { IGRAPH_ERROR("Cannot calculate clusters", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, already_added); IGRAPH_DQUEUE_INIT_FINALLY(&q, no_of_nodes > 100000 ? 10000 : no_of_nodes / 10); IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); /* Memory for result, csize is dynamically allocated */ if (membership) { IGRAPH_CHECK(igraph_vector_resize(membership, no_of_nodes)); } if (csize) { igraph_vector_clear(csize); } /* The algorithm */ for (first_node = 0; first_node < no_of_nodes; ++first_node) { if (already_added[first_node] == 1) { continue; } IGRAPH_ALLOW_INTERRUPTION(); already_added[first_node] = 1; act_cluster_size = 1; if (membership) { VECTOR(*membership)[first_node] = no_of_clusters - 1; } IGRAPH_CHECK(igraph_dqueue_push(&q, first_node)); while ( !igraph_dqueue_empty(&q) ) { long int act_node = (long int) igraph_dqueue_pop(&q); IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) act_node, IGRAPH_ALL)); for (i = 0; i < igraph_vector_size(&neis); i++) { long int neighbor = (long int) VECTOR(neis)[i]; if (already_added[neighbor] == 1) { continue; } IGRAPH_CHECK(igraph_dqueue_push(&q, neighbor)); already_added[neighbor] = 1; act_cluster_size++; if (membership) { VECTOR(*membership)[neighbor] = no_of_clusters - 1; } } } no_of_clusters++; if (csize) { IGRAPH_CHECK(igraph_vector_push_back(csize, act_cluster_size)); } } /* Cleaning up */ if (no) { *no = (igraph_integer_t) no_of_clusters - 1; } igraph_Free(already_added); igraph_dqueue_destroy(&q); igraph_vector_destroy(&neis); IGRAPH_FINALLY_CLEAN(3); return 0; } static int igraph_i_clusters_strong(const igraph_t *graph, igraph_vector_t *membership, igraph_vector_t *csize, igraph_integer_t *no) { long int no_of_nodes = igraph_vcount(graph); igraph_vector_t next_nei = IGRAPH_VECTOR_NULL; long int i, n, num_seen; igraph_dqueue_t q = IGRAPH_DQUEUE_NULL; long int no_of_clusters = 1; long int act_cluster_size; igraph_vector_t out = IGRAPH_VECTOR_NULL; const igraph_vector_int_t* tmp; igraph_adjlist_t adjlist; /* The result */ IGRAPH_VECTOR_INIT_FINALLY(&next_nei, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&out, 0); IGRAPH_DQUEUE_INIT_FINALLY(&q, 100); if (membership) { IGRAPH_CHECK(igraph_vector_resize(membership, no_of_nodes)); } IGRAPH_CHECK(igraph_vector_reserve(&out, no_of_nodes)); igraph_vector_null(&out); if (csize) { igraph_vector_clear(csize); } IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist, IGRAPH_OUT)); IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist); num_seen = 0; for (i = 0; i < no_of_nodes; i++) { IGRAPH_ALLOW_INTERRUPTION(); tmp = igraph_adjlist_get(&adjlist, i); if (VECTOR(next_nei)[i] > igraph_vector_int_size(tmp)) { continue; } IGRAPH_CHECK(igraph_dqueue_push(&q, i)); while (!igraph_dqueue_empty(&q)) { long int act_node = (long int) igraph_dqueue_back(&q); tmp = igraph_adjlist_get(&adjlist, act_node); if (VECTOR(next_nei)[act_node] == 0) { /* this is the first time we've met this vertex */ VECTOR(next_nei)[act_node]++; } else if (VECTOR(next_nei)[act_node] <= igraph_vector_int_size(tmp)) { /* we've already met this vertex but it has more children */ long int neighbor = (long int) VECTOR(*tmp)[(long int) VECTOR(next_nei)[act_node] - 1]; if (VECTOR(next_nei)[neighbor] == 0) { IGRAPH_CHECK(igraph_dqueue_push(&q, neighbor)); } VECTOR(next_nei)[act_node]++; } else { /* we've met this vertex and it has no more children */ IGRAPH_CHECK(igraph_vector_push_back(&out, act_node)); igraph_dqueue_pop_back(&q); num_seen++; if (num_seen % 10000 == 0) { /* time to report progress and allow the user to interrupt */ IGRAPH_PROGRESS("Strongly connected components: ", num_seen * 50.0 / no_of_nodes, NULL); IGRAPH_ALLOW_INTERRUPTION(); } } } /* while q */ } /* for */ IGRAPH_PROGRESS("Strongly connected components: ", 50.0, NULL); igraph_adjlist_destroy(&adjlist); IGRAPH_FINALLY_CLEAN(1); IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist, IGRAPH_IN)); IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist); /* OK, we've the 'out' values for the nodes, let's use them in decreasing order with the help of a heap */ igraph_vector_null(&next_nei); /* mark already added vertices */ num_seen = 0; while (!igraph_vector_empty(&out)) { long int grandfather = (long int) igraph_vector_pop_back(&out); if (VECTOR(next_nei)[grandfather] != 0) { continue; } VECTOR(next_nei)[grandfather] = 1; act_cluster_size = 1; if (membership) { VECTOR(*membership)[grandfather] = no_of_clusters - 1; } IGRAPH_CHECK(igraph_dqueue_push(&q, grandfather)); num_seen++; if (num_seen % 10000 == 0) { /* time to report progress and allow the user to interrupt */ IGRAPH_PROGRESS("Strongly connected components: ", 50.0 + num_seen * 50.0 / no_of_nodes, NULL); IGRAPH_ALLOW_INTERRUPTION(); } while (!igraph_dqueue_empty(&q)) { long int act_node = (long int) igraph_dqueue_pop_back(&q); tmp = igraph_adjlist_get(&adjlist, act_node); n = igraph_vector_int_size(tmp); for (i = 0; i < n; i++) { long int neighbor = (long int) VECTOR(*tmp)[i]; if (VECTOR(next_nei)[neighbor] != 0) { continue; } IGRAPH_CHECK(igraph_dqueue_push(&q, neighbor)); VECTOR(next_nei)[neighbor] = 1; act_cluster_size++; if (membership) { VECTOR(*membership)[neighbor] = no_of_clusters - 1; } num_seen++; if (num_seen % 10000 == 0) { /* time to report progress and allow the user to interrupt */ IGRAPH_PROGRESS("Strongly connected components: ", 50.0 + num_seen * 50.0 / no_of_nodes, NULL); IGRAPH_ALLOW_INTERRUPTION(); } } } no_of_clusters++; if (csize) { IGRAPH_CHECK(igraph_vector_push_back(csize, act_cluster_size)); } } IGRAPH_PROGRESS("Strongly connected components: ", 100.0, NULL); if (no) { *no = (igraph_integer_t) no_of_clusters - 1; } /* Clean up, return */ igraph_adjlist_destroy(&adjlist); igraph_vector_destroy(&out); igraph_dqueue_destroy(&q); igraph_vector_destroy(&next_nei); IGRAPH_FINALLY_CLEAN(4); return 0; } int igraph_is_connected_weak(const igraph_t *graph, igraph_bool_t *res); /** * \ingroup structural * \function igraph_is_connected * \brief Decides whether the graph is (weakly or strongly) connected. * * A graph with zero vertices (i.e. the null graph) is connected by definition. * * \param graph The graph object to analyze. * \param res Pointer to a logical variable, the result will be stored * here. * \param mode For a directed graph this specifies whether to calculate * weak or strong connectedness. Possible values: * \c IGRAPH_WEAK, * \c IGRAPH_STRONG. This argument is * ignored for undirected graphs. * \return Error code: * \c IGRAPH_EINVAL: invalid mode argument. * * Time complexity: O(|V|+|E|), the * number of vertices * plus the number of edges in the graph. */ int igraph_is_connected(const igraph_t *graph, igraph_bool_t *res, igraph_connectedness_t mode) { if (igraph_vcount(graph) == 0) { *res = 1; return IGRAPH_SUCCESS; } if (mode == IGRAPH_WEAK || !igraph_is_directed(graph)) { return igraph_is_connected_weak(graph, res); } else if (mode == IGRAPH_STRONG) { int retval; igraph_integer_t no; retval = igraph_i_clusters_strong(graph, 0, 0, &no); *res = (no == 1); return retval; } else { IGRAPH_ERROR("mode argument", IGRAPH_EINVAL); } return 0; } /** * \ingroup structural * \function igraph_is_connected_weak * \brief Query whether the graph is weakly connected. * * A graph with zero vertices (i.e. the null graph) is weakly connected by * definition. A directed graph is weakly connected if its undirected version * is connected. In the case of undirected graphs, weakly connected and * connected are equivalent. * * \param graph The graph object to analyze. * \param res Pointer to a logical variable; the result will be stored here. * \return Error code: * \c IGRAPH_ENOMEM: unable to allocate requested memory. * * Time complexity: O(|V|+|E|), the number of vertices plus the number of * edges in the graph. */ int igraph_is_connected_weak(const igraph_t *graph, igraph_bool_t *res) { long int no_of_nodes = igraph_vcount(graph); char *already_added; igraph_vector_t neis = IGRAPH_VECTOR_NULL; igraph_dqueue_t q = IGRAPH_DQUEUE_NULL; long int i, j; if (no_of_nodes == 0) { *res = 1; return IGRAPH_SUCCESS; } already_added = igraph_Calloc(no_of_nodes, char); if (already_added == 0) { IGRAPH_ERROR("is connected (weak) failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, already_added); /* TODO: hack */ IGRAPH_DQUEUE_INIT_FINALLY(&q, 10); IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); /* Try to find at least two clusters */ already_added[0] = 1; IGRAPH_CHECK(igraph_dqueue_push(&q, 0)); j = 1; while ( !igraph_dqueue_empty(&q)) { long int actnode = (long int) igraph_dqueue_pop(&q); IGRAPH_ALLOW_INTERRUPTION(); IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) actnode, IGRAPH_ALL)); for (i = 0; i < igraph_vector_size(&neis); i++) { long int neighbor = (long int) VECTOR(neis)[i]; if (already_added[neighbor] != 0) { continue; } IGRAPH_CHECK(igraph_dqueue_push(&q, neighbor)); j++; already_added[neighbor]++; } } /* Connected? */ *res = (j == no_of_nodes); igraph_Free(already_added); igraph_dqueue_destroy(&q); igraph_vector_destroy(&neis); IGRAPH_FINALLY_CLEAN(3); return 0; } /** * \function igraph_decompose_destroy * \brief Free the memory allocated by \ref igraph_decompose(). * * \param complist The list of graph components, as returned by * \ref igraph_decompose(). * * Time complexity: O(c), c is the number of components. */ void igraph_decompose_destroy(igraph_vector_ptr_t *complist) { long int i; for (i = 0; i < igraph_vector_ptr_size(complist); i++) { if (VECTOR(*complist)[i] != 0) { igraph_destroy(VECTOR(*complist)[i]); igraph_free(VECTOR(*complist)[i]); } } } static int igraph_i_decompose_weak(const igraph_t *graph, igraph_vector_ptr_t *components, long int maxcompno, long int minelements); static int igraph_i_decompose_strong(const igraph_t *graph, igraph_vector_ptr_t *components, long int maxcompno, long int minelements); /** * \function igraph_decompose * \brief Decompose a graph into connected components. * * Create separate graph for each component of a graph. Note that the * vertex ids in the new graphs will be different than in the original * graph. (Except if there is only one component in the original graph.) * * \param graph The original graph. * \param components This pointer vector will contain pointers to the * subcomponent graphs. It should be initialized before calling this * function and will be resized to hold the graphs. Don't forget to * call \ref igraph_destroy() and free() on the elements of * this pointer vector to free unneeded memory. Alternatively, you can * simply call \ref igraph_decompose_destroy() that does this for you. * \param mode Either \c IGRAPH_WEAK or \c IGRAPH_STRONG for weakly * and strongly connected components respectively. * \param maxcompno The maximum number of components to return. The * first \p maxcompno components will be returned (which hold at * least \p minelements vertices, see the next parameter), the * others will be ignored. Supply -1 here if you don't want to limit * the number of components. * \param minelements The minimum number of vertices a component * should contain in order to place it in the \p components * vector. Eg. supply 2 here to ignore isolated vertices. * \return Error code, \c IGRAPH_ENOMEM if there is not enough memory * to perform the operation. * * Added in version 0.2. * * Time complexity: O(|V|+|E|), the number of vertices plus the number * of edges. * * \example examples/simple/igraph_decompose.c */ int igraph_decompose(const igraph_t *graph, igraph_vector_ptr_t *components, igraph_connectedness_t mode, long int maxcompno, long int minelements) { if (mode == IGRAPH_WEAK || !igraph_is_directed(graph)) { return igraph_i_decompose_weak(graph, components, maxcompno, minelements); } else if (mode == IGRAPH_STRONG) { return igraph_i_decompose_strong(graph, components, maxcompno, minelements); } else { IGRAPH_ERROR("Cannot decompose graph", IGRAPH_EINVAL); } return 1; } static int igraph_i_decompose_weak(const igraph_t *graph, igraph_vector_ptr_t *components, long int maxcompno, long int minelements) { long int actstart; long int no_of_nodes = igraph_vcount(graph); long int resco = 0; /* number of graphs created so far */ char *already_added; igraph_dqueue_t q; igraph_vector_t verts; igraph_vector_t neis; long int i; igraph_t *newg; if (maxcompno < 0) { maxcompno = LONG_MAX; } igraph_vector_ptr_clear(components); IGRAPH_FINALLY(igraph_decompose_destroy, components); /* already_added keeps track of what nodes made it into a graph already */ already_added = igraph_Calloc(no_of_nodes, char); if (already_added == 0) { IGRAPH_ERROR("Cannot decompose graph", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, already_added); IGRAPH_CHECK(igraph_dqueue_init(&q, 100)); IGRAPH_FINALLY(igraph_dqueue_destroy, &q); IGRAPH_VECTOR_INIT_FINALLY(&verts, 0); IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); /* add a node and its neighbors at once, recursively then switch to next node that has not been added already */ for (actstart = 0; resco < maxcompno && actstart < no_of_nodes; actstart++) { if (already_added[actstart]) { continue; } IGRAPH_ALLOW_INTERRUPTION(); igraph_vector_clear(&verts); /* add the node itself */ already_added[actstart] = 1; IGRAPH_CHECK(igraph_vector_push_back(&verts, actstart)); IGRAPH_CHECK(igraph_dqueue_push(&q, actstart)); /* add the neighbors, recursively */ while (!igraph_dqueue_empty(&q) ) { /* pop from the queue of this component */ long int actvert = (long int) igraph_dqueue_pop(&q); IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) actvert, IGRAPH_ALL)); /* iterate over the neighbors */ for (i = 0; i < igraph_vector_size(&neis); i++) { long int neighbor = (long int) VECTOR(neis)[i]; if (already_added[neighbor] == 1) { continue; } /* add neighbor */ already_added[neighbor] = 1; /* recursion: append neighbor to the queues */ IGRAPH_CHECK(igraph_dqueue_push(&q, neighbor)); IGRAPH_CHECK(igraph_vector_push_back(&verts, neighbor)); } } /* ok, we have a component */ if (igraph_vector_size(&verts) < minelements) { continue; } newg = igraph_Calloc(1, igraph_t); if (newg == 0) { IGRAPH_ERROR("Cannot decompose graph", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_ptr_push_back(components, newg)); IGRAPH_CHECK(igraph_induced_subgraph(graph, newg, igraph_vss_vector(&verts), IGRAPH_SUBGRAPH_AUTO)); resco++; } /* for actstart++ */ igraph_vector_destroy(&neis); igraph_vector_destroy(&verts); igraph_dqueue_destroy(&q); igraph_free(already_added); IGRAPH_FINALLY_CLEAN(5); /* + components */ return 0; } static int igraph_i_decompose_strong(const igraph_t *graph, igraph_vector_ptr_t *components, long int maxcompno, long int minelements) { long int no_of_nodes = igraph_vcount(graph); /* this is a heap used twice for checking what nodes have * been counted already */ igraph_vector_t next_nei = IGRAPH_VECTOR_NULL; long int i, n, num_seen; igraph_dqueue_t q = IGRAPH_DQUEUE_NULL; long int no_of_clusters = 1; long int act_cluster_size; igraph_vector_t out = IGRAPH_VECTOR_NULL; const igraph_vector_int_t* tmp; igraph_adjlist_t adjlist; igraph_vector_t verts; igraph_t *newg; igraph_vector_ptr_clear(components); IGRAPH_FINALLY(igraph_decompose_destroy, components); /* The result */ IGRAPH_VECTOR_INIT_FINALLY(&verts, 0); IGRAPH_VECTOR_INIT_FINALLY(&next_nei, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&out, 0); IGRAPH_DQUEUE_INIT_FINALLY(&q, 100); IGRAPH_CHECK(igraph_vector_reserve(&out, no_of_nodes)); igraph_vector_null(&out); IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist, IGRAPH_OUT)); IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist); /* number of components seen */ num_seen = 0; /* populate the 'out' vector by browsing a node and following up all its neighbors recursively, then switching to the next unassigned node */ for (i = 0; i < no_of_nodes; i++) { IGRAPH_ALLOW_INTERRUPTION(); /* get all the 'out' neighbors of this node * NOTE: next_nei is initialized [0, 0, ...] */ tmp = igraph_adjlist_get(&adjlist, i); if (VECTOR(next_nei)[i] > igraph_vector_int_size(tmp)) { continue; } /* add this node to the queue for this component */ IGRAPH_CHECK(igraph_dqueue_push(&q, i)); /* consume the tree from this node ("root") recursively * until there is no more */ while (!igraph_dqueue_empty(&q)) { /* this looks up but does NOT consume the queue */ long int act_node = (long int) igraph_dqueue_back(&q); /* get all neighbors of this node */ tmp = igraph_adjlist_get(&adjlist, act_node); if (VECTOR(next_nei)[act_node] == 0) { /* this is the first time we've met this vertex, * because next_nei is initialized [0, 0, ...] */ VECTOR(next_nei)[act_node]++; /* back to the queue, same vertex is up again */ } else if (VECTOR(next_nei)[act_node] <= igraph_vector_int_size(tmp)) { /* we've already met this vertex but it has more children */ long int neighbor = (long int) VECTOR(*tmp)[(long int) VECTOR(next_nei)[act_node] - 1]; if (VECTOR(next_nei)[neighbor] == 0) { /* add the root of the other children to the queue */ IGRAPH_CHECK(igraph_dqueue_push(&q, neighbor)); } VECTOR(next_nei)[act_node]++; } else { /* we've met this vertex and it has no more children */ IGRAPH_CHECK(igraph_vector_push_back(&out, act_node)); /* this consumes the queue, since there's nowhere to go */ igraph_dqueue_pop_back(&q); num_seen++; if (num_seen % 10000 == 0) { /* time to report progress and allow the user to interrupt */ IGRAPH_PROGRESS("Strongly connected components: ", num_seen * 50.0 / no_of_nodes, NULL); IGRAPH_ALLOW_INTERRUPTION(); } } } /* while q */ } /* for */ IGRAPH_PROGRESS("Strongly connected components: ", 50.0, NULL); igraph_adjlist_destroy(&adjlist); IGRAPH_FINALLY_CLEAN(1); IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist, IGRAPH_IN)); IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist); /* OK, we've the 'out' values for the nodes, let's use them in * decreasing order with the help of the next_nei heap */ igraph_vector_null(&next_nei); /* mark already added vertices */ /* number of components built */ num_seen = 0; while (!igraph_vector_empty(&out)) { /* consume the vector from the last element */ long int grandfather = (long int) igraph_vector_pop_back(&out); /* been here, done that * NOTE: next_nei is initialized as [0, 0, ...] */ if (VECTOR(next_nei)[grandfather] != 0) { continue; } /* collect all the members of this component */ igraph_vector_clear(&verts); /* this node is gone for any future components */ VECTOR(next_nei)[grandfather] = 1; act_cluster_size = 1; /* add to component */ IGRAPH_CHECK(igraph_vector_push_back(&verts, grandfather)); IGRAPH_CHECK(igraph_dqueue_push(&q, grandfather)); num_seen++; if (num_seen % 10000 == 0) { /* time to report progress and allow the user to interrupt */ IGRAPH_PROGRESS("Strongly connected components: ", 50.0 + num_seen * 50.0 / no_of_nodes, NULL); IGRAPH_ALLOW_INTERRUPTION(); } while (!igraph_dqueue_empty(&q)) { /* consume the queue from this node */ long int act_node = (long int) igraph_dqueue_pop_back(&q); tmp = igraph_adjlist_get(&adjlist, act_node); n = igraph_vector_int_size(tmp); for (i = 0; i < n; i++) { long int neighbor = (long int) VECTOR(*tmp)[i]; if (VECTOR(next_nei)[neighbor] != 0) { continue; } IGRAPH_CHECK(igraph_dqueue_push(&q, neighbor)); VECTOR(next_nei)[neighbor] = 1; act_cluster_size++; /* add to component */ IGRAPH_CHECK(igraph_vector_push_back(&verts, neighbor)); num_seen++; if (num_seen % 10000 == 0) { /* time to report progress and allow the user to interrupt */ IGRAPH_PROGRESS("Strongly connected components: ", 50.0 + num_seen * 50.0 / no_of_nodes, NULL); IGRAPH_ALLOW_INTERRUPTION(); } } } /* ok, we have a component */ if (igraph_vector_size(&verts) < minelements) { continue; } newg = igraph_Calloc(1, igraph_t); if (newg == 0) { IGRAPH_ERROR("Cannot decompose graph", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_ptr_push_back(components, newg)); IGRAPH_CHECK(igraph_induced_subgraph(graph, newg, igraph_vss_vector(&verts), IGRAPH_SUBGRAPH_AUTO)); no_of_clusters++; } IGRAPH_PROGRESS("Strongly connected components: ", 100.0, NULL); /* Clean up, return */ igraph_vector_destroy(&verts); igraph_adjlist_destroy(&adjlist); igraph_vector_destroy(&out); igraph_dqueue_destroy(&q); igraph_vector_destroy(&next_nei); IGRAPH_FINALLY_CLEAN(6); /* + components */ return 0; } /** * \function igraph_articulation_points * Find the articulation points in a graph. * * A vertex is an articulation point if its removal increases * the number of connected components in the graph. * \param graph The input graph. * \param res Pointer to an initialized vector, the * articulation points will be stored here. * \return Error code. * * Time complexity: O(|V|+|E|), linear in the number of vertices and edges. * * \sa \ref igraph_biconnected_components(), \ref igraph_clusters(), \ref igraph_bridges() */ int igraph_articulation_points(const igraph_t *graph, igraph_vector_t *res) { igraph_integer_t no; return igraph_biconnected_components(graph, &no, 0, 0, 0, res); } void igraph_i_free_vectorlist(igraph_vector_ptr_t *list); void igraph_i_free_vectorlist(igraph_vector_ptr_t *list) { long int i, n = igraph_vector_ptr_size(list); for (i = 0; i < n; i++) { igraph_vector_t *v = VECTOR(*list)[i]; if (v) { igraph_vector_destroy(v); igraph_Free(v); } } igraph_vector_ptr_destroy(list); } /** * \function igraph_biconnected_components * Calculate biconnected components * * A graph is biconnected if the removal of any single vertex (and * its incident edges) does not disconnect it. * * * A biconnected component of a graph is a maximal biconnected * subgraph of it. The biconnected components of a graph can be given * by the partition of its edges: every edge is a member of exactly * one biconnected component. Note that this is not true for * vertices: the same vertex can be part of many biconnected * components. * * * Somewhat arbitrarily, igraph does not consider comppnents containing * a single vertex only as being biconnected. Isolated vertices will * not be part of any of the biconnected components. * * \param graph The input graph. * \param no The number of biconnected components will be stored here. * \param tree_edges If not a NULL pointer, then the found components * are stored here, in a list of vectors. Every vector in the list * is a biconnected component, represented by its edges. More precisely, * a spanning tree of the biconnected component is returned. * Note you'll have to * destroy each vector first by calling \ref igraph_vector_destroy() * and then free() on it, plus you need to call * \ref igraph_vector_ptr_destroy() on the list to regain all * allocated memory. * \param component_edges If not a NULL pointer, then the edges of the * biconnected components are stored here, in the same form as for * \c tree_edges. * \param components If not a NULL pointer, then the vertices of the * biconnected components are stored here, in the same format as * for the previous two arguments. * \param articulation_points If not a NULL pointer, then the * articulation points of the graph are stored in this vector. * A vertex is an articulation point if its removal increases the * number of (weakly) connected components in the graph. * \return Error code. * * Time complexity: O(|V|+|E|), linear in the number of vertices and * edges, but only if you do not calculate \c components and * \c component_edges. If you calculate \c components, then it is * quadratic in the number of vertices. If you calculate \c * component_edges as well, then it is cubic in the number of * vertices. * * \sa \ref igraph_articulation_points(), \ref igraph_clusters(). * * \example examples/simple/igraph_biconnected_components.c */ int igraph_biconnected_components(const igraph_t *graph, igraph_integer_t *no, igraph_vector_ptr_t *tree_edges, igraph_vector_ptr_t *component_edges, igraph_vector_ptr_t *components, igraph_vector_t *articulation_points) { long int no_of_nodes = igraph_vcount(graph); igraph_vector_long_t nextptr; igraph_vector_long_t num, low; igraph_vector_bool_t found; igraph_vector_int_t *adjedges; igraph_stack_t path; igraph_vector_t edgestack; igraph_inclist_t inclist; long int i, counter, rootdfs = 0; igraph_vector_long_t vertex_added; long int comps = 0; igraph_vector_ptr_t *mycomponents = components, vcomponents; IGRAPH_CHECK(igraph_vector_long_init(&nextptr, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_long_destroy, &nextptr); IGRAPH_CHECK(igraph_vector_long_init(&num, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_long_destroy, &num); IGRAPH_CHECK(igraph_vector_long_init(&low, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_long_destroy, &low); IGRAPH_CHECK(igraph_vector_bool_init(&found, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_bool_destroy, &found); IGRAPH_CHECK(igraph_stack_init(&path, 100)); IGRAPH_FINALLY(igraph_stack_destroy, &path); IGRAPH_VECTOR_INIT_FINALLY(&edgestack, 0); IGRAPH_CHECK(igraph_vector_reserve(&edgestack, 100)); IGRAPH_CHECK(igraph_inclist_init(graph, &inclist, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_inclist_destroy, &inclist); IGRAPH_CHECK(igraph_vector_long_init(&vertex_added, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_long_destroy, &vertex_added); if (no) { *no = 0; } if (tree_edges) { igraph_vector_ptr_clear(tree_edges); } if (components) { igraph_vector_ptr_clear(components); } if (component_edges) { igraph_vector_ptr_clear(component_edges); } if (articulation_points) { igraph_vector_clear(articulation_points); } if (component_edges && !components) { mycomponents = &vcomponents; IGRAPH_CHECK(igraph_vector_ptr_init(mycomponents, 0)); IGRAPH_FINALLY(igraph_i_free_vectorlist, mycomponents); } for (i = 0; i < no_of_nodes; i++) { if (VECTOR(low)[i] != 0) { continue; /* already visited */ } IGRAPH_ALLOW_INTERRUPTION(); IGRAPH_CHECK(igraph_stack_push(&path, i)); counter = 1; rootdfs = 0; VECTOR(low)[i] = VECTOR(num)[i] = counter++; while (!igraph_stack_empty(&path)) { long int n; long int act = (long int) igraph_stack_top(&path); long int actnext = VECTOR(nextptr)[act]; adjedges = igraph_inclist_get(&inclist, act); n = igraph_vector_int_size(adjedges); if (actnext < n) { /* Step down (maybe) */ long int edge = (long int) VECTOR(*adjedges)[actnext]; long int nei = IGRAPH_OTHER(graph, edge, act); if (VECTOR(low)[nei] == 0) { if (act == i) { rootdfs++; } IGRAPH_CHECK(igraph_vector_push_back(&edgestack, edge)); IGRAPH_CHECK(igraph_stack_push(&path, nei)); VECTOR(low)[nei] = VECTOR(num)[nei] = counter++; } else { /* Update low value if needed */ if (VECTOR(num)[nei] < VECTOR(low)[act]) { VECTOR(low)[act] = VECTOR(num)[nei]; } } VECTOR(nextptr)[act] += 1; } else { /* Step up */ igraph_stack_pop(&path); if (!igraph_stack_empty(&path)) { long int prev = (long int) igraph_stack_top(&path); /* Update LOW value if needed */ if (VECTOR(low)[act] < VECTOR(low)[prev]) { VECTOR(low)[prev] = VECTOR(low)[act]; } /* Check for articulation point */ if (VECTOR(low)[act] >= VECTOR(num)[prev]) { if (articulation_points && !VECTOR(found)[prev] && prev != i /* the root */) { IGRAPH_CHECK(igraph_vector_push_back(articulation_points, prev)); VECTOR(found)[prev] = 1; } if (no) { *no += 1; } /*------------------------------------*/ /* Record the biconnected component just found */ if (tree_edges || mycomponents) { igraph_vector_t *v = 0, *v2 = 0; comps++; if (tree_edges) { v = igraph_Calloc(1, igraph_vector_t); if (!v) { IGRAPH_ERROR("Out of memory", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_init(v, 0)); IGRAPH_FINALLY(igraph_vector_destroy, v); } if (mycomponents) { v2 = igraph_Calloc(1, igraph_vector_t); if (!v2) { IGRAPH_ERROR("Out of memory", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_init(v2, 0)); IGRAPH_FINALLY(igraph_vector_destroy, v2); } while (!igraph_vector_empty(&edgestack)) { long int e = (long int) igraph_vector_pop_back(&edgestack); long int from = IGRAPH_FROM(graph, e); long int to = IGRAPH_TO(graph, e); if (tree_edges) { IGRAPH_CHECK(igraph_vector_push_back(v, e)); } if (mycomponents) { if (VECTOR(vertex_added)[from] != comps) { VECTOR(vertex_added)[from] = comps; IGRAPH_CHECK(igraph_vector_push_back(v2, from)); } if (VECTOR(vertex_added)[to] != comps) { VECTOR(vertex_added)[to] = comps; IGRAPH_CHECK(igraph_vector_push_back(v2, to)); } } if (from == prev || to == prev) { break; } } if (mycomponents) { IGRAPH_CHECK(igraph_vector_ptr_push_back(mycomponents, v2)); IGRAPH_FINALLY_CLEAN(1); } if (tree_edges) { IGRAPH_CHECK(igraph_vector_ptr_push_back(tree_edges, v)); IGRAPH_FINALLY_CLEAN(1); } if (component_edges) { igraph_vector_t *nodes = VECTOR(*mycomponents)[comps - 1]; igraph_vector_t *vv = igraph_Calloc(1, igraph_vector_t); long int ii, no_vert = igraph_vector_size(nodes); if (!vv) { IGRAPH_ERROR("Out of memory", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_init(vv, 0)); IGRAPH_FINALLY(igraph_vector_destroy, vv); for (ii = 0; ii < no_vert; ii++) { long int vert = (long int) VECTOR(*nodes)[ii]; igraph_vector_int_t *edges = igraph_inclist_get(&inclist, vert); long int j, nn = igraph_vector_int_size(edges); for (j = 0; j < nn; j++) { long int e = (long int) VECTOR(*edges)[j]; long int nei = IGRAPH_OTHER(graph, e, vert); if (VECTOR(vertex_added)[nei] == comps && nei < vert) { IGRAPH_CHECK(igraph_vector_push_back(vv, e)); } } } IGRAPH_CHECK(igraph_vector_ptr_push_back(component_edges, vv)); IGRAPH_FINALLY_CLEAN(1); } } /* record component if requested */ /*------------------------------------*/ } } /* !igraph_stack_empty(&path) */ } } /* !igraph_stack_empty(&path) */ if (articulation_points && rootdfs >= 2) { IGRAPH_CHECK(igraph_vector_push_back(articulation_points, i)); } } /* i < no_of_nodes */ if (mycomponents != components) { igraph_i_free_vectorlist(mycomponents); IGRAPH_FINALLY_CLEAN(1); } igraph_vector_long_destroy(&vertex_added); igraph_inclist_destroy(&inclist); igraph_vector_destroy(&edgestack); igraph_stack_destroy(&path); igraph_vector_bool_destroy(&found); igraph_vector_long_destroy(&low); igraph_vector_long_destroy(&num); igraph_vector_long_destroy(&nextptr); IGRAPH_FINALLY_CLEAN(8); return 0; } /* igraph_bridges -- find all bridges in the graph */ /* based on https://www.geeksforgeeks.org/bridge-in-a-graph/ */ static int igraph_i_bridges_rec(const igraph_t *graph, const igraph_inclist_t *il, igraph_integer_t u, igraph_integer_t *time, igraph_vector_t *bridges, igraph_vector_bool_t *visited, igraph_vector_int_t *disc, igraph_vector_int_t *low, igraph_vector_int_t *parent) { igraph_vector_int_t *incedges; long nc; /* neighbour count */ long i; VECTOR(*visited)[u] = 1; *time += 1; VECTOR(*disc)[u] = *time; VECTOR(*low)[u] = *time; incedges = igraph_inclist_get(il, u); nc = igraph_vector_int_size(incedges); for (i = 0; i < nc; ++i) { long edge = (long) VECTOR(*incedges)[i]; igraph_integer_t v = IGRAPH_TO(graph, edge) == u ? IGRAPH_FROM(graph, edge) : IGRAPH_TO(graph, edge); if (! VECTOR(*visited)[v]) { VECTOR(*parent)[v] = u; IGRAPH_CHECK(igraph_i_bridges_rec(graph, il, v, time, bridges, visited, disc, low, parent)); VECTOR(*low)[u] = VECTOR(*low)[u] < VECTOR(*low)[v] ? VECTOR(*low)[u] : VECTOR(*low)[v]; if (VECTOR(*low)[v] > VECTOR(*disc)[u]) { IGRAPH_CHECK(igraph_vector_push_back(bridges, edge)); } } else if (v != VECTOR(*parent)[u]) { VECTOR(*low)[u] = VECTOR(*low)[u] < VECTOR(*disc)[v] ? VECTOR(*low)[u] : VECTOR(*disc)[v]; } } return IGRAPH_SUCCESS; } /** * \function igraph_bridges * Find all bridges in a graph. * * An edge is a bridge if its removal increases the number of (weakly) * connected components in the graph. * * \param graph The input graph. * \param res Pointer to an initialized vector, the * bridges will be stored here as edge indices. * \return Error code. * * Time complexity: O(|V|+|E|), linear in the number of vertices and edges. * * \sa \ref igraph_articulation_points(), \ref igraph_biconnected_components(), \ref igraph_clusters() */ int igraph_bridges(const igraph_t *graph, igraph_vector_t *bridges) { igraph_inclist_t il; igraph_vector_bool_t visited; igraph_vector_int_t disc, low; igraph_vector_int_t parent; long n; long i; igraph_integer_t time; n = igraph_vcount(graph); IGRAPH_CHECK(igraph_inclist_init(graph, &il, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_inclist_destroy, &il); IGRAPH_CHECK(igraph_vector_bool_init(&visited, n)); IGRAPH_FINALLY(igraph_vector_bool_destroy, &visited); IGRAPH_CHECK(igraph_vector_int_init(&disc, n)); IGRAPH_FINALLY(igraph_vector_int_destroy, &disc); IGRAPH_CHECK(igraph_vector_int_init(&low, n)); IGRAPH_FINALLY(igraph_vector_int_destroy, &low); IGRAPH_CHECK(igraph_vector_int_init(&parent, n)); IGRAPH_FINALLY(igraph_vector_int_destroy, &parent); for (i = 0; i < n; ++i) { VECTOR(parent)[i] = -1; } igraph_vector_clear(bridges); time = 0; for (i = 0; i < n; ++i) if (! VECTOR(visited)[i]) { IGRAPH_CHECK(igraph_i_bridges_rec(graph, &il, i, &time, bridges, &visited, &disc, &low, &parent)); } igraph_vector_int_destroy(&parent); igraph_vector_int_destroy(&low); igraph_vector_int_destroy(&disc); igraph_vector_bool_destroy(&visited); igraph_inclist_destroy(&il); IGRAPH_FINALLY_CLEAN(5); return IGRAPH_SUCCESS; } python-igraph-0.8.0/vendor/source/igraph/src/feedback_arc_set.c0000644000076500000240000006236213614300625024777 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_centrality.h" #include "igraph_components.h" #include "igraph_constants.h" #include "igraph_datatype.h" #include "igraph_dqueue.h" #include "igraph_error.h" #include "igraph_glpk_support.h" #include "igraph_interface.h" #include "igraph_memory.h" #include "igraph_structural.h" #include "igraph_types.h" #include "igraph_visitor.h" int igraph_i_feedback_arc_set_ip(const igraph_t *graph, igraph_vector_t *result, const igraph_vector_t *weights); /** * \ingroup structural * \function igraph_feedback_arc_set * \brief Calculates a feedback arc set of the graph using different * algorithms. * * * A feedback arc set is a set of edges whose removal makes the graph acyclic. * We are usually interested in \em minimum feedback arc sets, i.e. sets of edges * whose total weight is minimal among all the feedback arc sets. * * * For undirected graphs, the problem is simple: one has to find a maximum weight * spanning tree and then remove all the edges not in the spanning tree. For directed * graphs, this is an NP-hard problem, and various heuristics are usually used to * find an approximate solution to the problem. This function implements a few of * these heuristics. * * \param graph The graph object. * \param result An initialized vector, the result will be returned here. * \param weights Weight vector or NULL if no weights are specified. * \param algo The algorithm to use to solve the problem if the graph is directed. * Possible values: * \clist * \cli IGRAPH_FAS_EXACT_IP * Finds a \em minimum feedback arc set using integer programming (IP). * The complexity of this algorithm is exponential of course. * \cli IGRAPH_FAS_APPROX_EADES * Finds a feedback arc set using the heuristic of Eades, Lin and * Smyth (1993). This is guaranteed to be smaller than |E|/2 - |V|/6, * and it is linear in the number of edges (i.e. O(|E|)). * For more details, see Eades P, Lin X and Smyth WF: A fast and effective * heuristic for the feedback arc set problem. In: Proc Inf Process Lett * 319-323, 1993. * \endclist * * \return Error code: * \c IGRAPH_EINVAL if an unknown method was specified or the weight vector * is invalid. * * \example examples/simple/igraph_feedback_arc_set.c * \example examples/simple/igraph_feedback_arc_set_ip.c * * Time complexity: depends on \p algo, see the time complexities there. */ int igraph_feedback_arc_set(const igraph_t *graph, igraph_vector_t *result, const igraph_vector_t *weights, igraph_fas_algorithm_t algo) { if (weights && igraph_vector_size(weights) < igraph_ecount(graph)) IGRAPH_ERROR("cannot calculate feedback arc set, weight vector too short", IGRAPH_EINVAL); if (!igraph_is_directed(graph)) { return igraph_i_feedback_arc_set_undirected(graph, result, weights, 0); } switch (algo) { case IGRAPH_FAS_EXACT_IP: return igraph_i_feedback_arc_set_ip(graph, result, weights); case IGRAPH_FAS_APPROX_EADES: return igraph_i_feedback_arc_set_eades(graph, result, weights, 0); default: IGRAPH_ERROR("Invalid algorithm", IGRAPH_EINVAL); } } /** * Solves the feedback arc set problem for undirected graphs. */ int igraph_i_feedback_arc_set_undirected(const igraph_t *graph, igraph_vector_t *result, const igraph_vector_t *weights, igraph_vector_t *layering) { igraph_vector_t edges; long int i, j, n, no_of_nodes = igraph_vcount(graph); IGRAPH_VECTOR_INIT_FINALLY(&edges, no_of_nodes - 1); if (weights) { /* Find a maximum weight spanning tree. igraph has a routine for minimum * spanning trees, so we negate the weights */ igraph_vector_t vcopy; IGRAPH_CHECK(igraph_vector_copy(&vcopy, weights)); IGRAPH_FINALLY(igraph_vector_destroy, &vcopy); igraph_vector_scale(&vcopy, -1); IGRAPH_CHECK(igraph_minimum_spanning_tree(graph, &edges, &vcopy)); igraph_vector_destroy(&vcopy); IGRAPH_FINALLY_CLEAN(1); } else { /* Any spanning tree will do */ IGRAPH_CHECK(igraph_minimum_spanning_tree(graph, &edges, 0)); } /* Now we have a bunch of edges that constitute a spanning forest. We have * to come up with a layering, and return those edges that are not in the * spanning forest */ igraph_vector_sort(&edges); IGRAPH_CHECK(igraph_vector_push_back(&edges, -1)); /* guard element */ if (result != 0) { igraph_vector_clear(result); n = igraph_ecount(graph); for (i = 0, j = 0; i < n; i++) { if (i == VECTOR(edges)[j]) { j++; continue; } IGRAPH_CHECK(igraph_vector_push_back(result, i)); } } if (layering != 0) { igraph_vector_t degrees; igraph_vector_t roots; IGRAPH_VECTOR_INIT_FINALLY(°rees, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&roots, no_of_nodes); IGRAPH_CHECK(igraph_strength(graph, °rees, igraph_vss_all(), IGRAPH_ALL, 0, weights)); IGRAPH_CHECK((int) igraph_vector_qsort_ind(°rees, &roots, /* descending = */ 1)); IGRAPH_CHECK(igraph_bfs(graph, /* root = */ 0, /* roots = */ &roots, /* mode = */ IGRAPH_OUT, /* unreachable = */ 0, /* restricted = */ 0, /* order = */ 0, /* rank = */ 0, /* father = */ 0, /* pred = */ 0, /* succ = */ 0, /* dist = */ layering, /* callback = */ 0, /* extra = */ 0)); igraph_vector_destroy(°rees); igraph_vector_destroy(&roots); IGRAPH_FINALLY_CLEAN(2); } igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } /** * Solves the feedback arc set problem using the heuristics of Eades et al. */ int igraph_i_feedback_arc_set_eades(const igraph_t *graph, igraph_vector_t *result, const igraph_vector_t *weights, igraph_vector_t *layers) { long int i, j, k, v, eid, no_of_nodes = igraph_vcount(graph), nodes_left; igraph_dqueue_t sources, sinks; igraph_vector_t neis; igraph_vector_t indegrees, outdegrees; igraph_vector_t instrengths, outstrengths; long int* ordering; long int order_next_pos = 0, order_next_neg = -1; igraph_real_t diff, maxdiff; ordering = igraph_Calloc(no_of_nodes, long int); IGRAPH_FINALLY(igraph_free, ordering); IGRAPH_VECTOR_INIT_FINALLY(&indegrees, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&outdegrees, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&instrengths, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&outstrengths, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); IGRAPH_CHECK(igraph_dqueue_init(&sources, 0)); IGRAPH_FINALLY(igraph_dqueue_destroy, &sources); IGRAPH_CHECK(igraph_dqueue_init(&sinks, 0)); IGRAPH_FINALLY(igraph_dqueue_destroy, &sinks); IGRAPH_CHECK(igraph_degree(graph, &indegrees, igraph_vss_all(), IGRAPH_IN, 0)); IGRAPH_CHECK(igraph_degree(graph, &outdegrees, igraph_vss_all(), IGRAPH_OUT, 0)); if (weights) { IGRAPH_CHECK(igraph_strength(graph, &instrengths, igraph_vss_all(), IGRAPH_IN, 0, weights)); IGRAPH_CHECK(igraph_strength(graph, &outstrengths, igraph_vss_all(), IGRAPH_OUT, 0, weights)); } else { IGRAPH_CHECK(igraph_vector_update(&instrengths, &indegrees)); IGRAPH_CHECK(igraph_vector_update(&outstrengths, &outdegrees)); } /* Find initial sources and sinks */ nodes_left = no_of_nodes; for (i = 0; i < no_of_nodes; i++) { if (VECTOR(indegrees)[i] == 0) { if (VECTOR(outdegrees)[i] == 0) { /* Isolated vertex, we simply ignore it */ nodes_left--; ordering[i] = order_next_pos++; VECTOR(indegrees)[i] = VECTOR(outdegrees)[i] = -1; } else { /* This is a source */ igraph_dqueue_push(&sources, i); } } else if (VECTOR(outdegrees)[i] == 0) { /* This is a sink */ igraph_dqueue_push(&sinks, i); } } /* While we have any nodes left... */ while (nodes_left > 0) { /* (1) Remove the sources one by one */ while (!igraph_dqueue_empty(&sources)) { i = (long)igraph_dqueue_pop(&sources); /* Add the node to the ordering */ ordering[i] = order_next_pos++; /* Exclude the node from further searches */ VECTOR(indegrees)[i] = VECTOR(outdegrees)[i] = -1; /* Get the neighbors and decrease their degrees */ IGRAPH_CHECK(igraph_incident(graph, &neis, (igraph_integer_t) i, IGRAPH_OUT)); j = igraph_vector_size(&neis); for (i = 0; i < j; i++) { eid = (long int) VECTOR(neis)[i]; k = IGRAPH_TO(graph, eid); if (VECTOR(indegrees)[k] <= 0) { /* Already removed, continue */ continue; } VECTOR(indegrees)[k]--; VECTOR(instrengths)[k] -= (weights ? VECTOR(*weights)[eid] : 1.0); if (VECTOR(indegrees)[k] == 0) { IGRAPH_CHECK(igraph_dqueue_push(&sources, k)); } } nodes_left--; } /* (2) Remove the sinks one by one */ while (!igraph_dqueue_empty(&sinks)) { i = (long)igraph_dqueue_pop(&sinks); /* Maybe the vertex became sink and source at the same time, hence it * was already removed in the previous iteration. Check it. */ if (VECTOR(indegrees)[i] < 0) { continue; } /* Add the node to the ordering */ ordering[i] = order_next_neg--; /* Exclude the node from further searches */ VECTOR(indegrees)[i] = VECTOR(outdegrees)[i] = -1; /* Get the neighbors and decrease their degrees */ IGRAPH_CHECK(igraph_incident(graph, &neis, (igraph_integer_t) i, IGRAPH_IN)); j = igraph_vector_size(&neis); for (i = 0; i < j; i++) { eid = (long int) VECTOR(neis)[i]; k = IGRAPH_FROM(graph, eid); if (VECTOR(outdegrees)[k] <= 0) { /* Already removed, continue */ continue; } VECTOR(outdegrees)[k]--; VECTOR(outstrengths)[k] -= (weights ? VECTOR(*weights)[eid] : 1.0); if (VECTOR(outdegrees)[k] == 0) { IGRAPH_CHECK(igraph_dqueue_push(&sinks, k)); } } nodes_left--; } /* (3) No more sources or sinks. Find the node with the largest * difference between its out-strength and in-strength */ v = -1; maxdiff = -IGRAPH_INFINITY; for (i = 0; i < no_of_nodes; i++) { if (VECTOR(outdegrees)[i] < 0) { continue; } diff = VECTOR(outstrengths)[i] - VECTOR(instrengths)[i]; if (diff > maxdiff) { maxdiff = diff; v = i; } } if (v >= 0) { /* Remove vertex v */ ordering[v] = order_next_pos++; /* Remove outgoing edges */ IGRAPH_CHECK(igraph_incident(graph, &neis, (igraph_integer_t) v, IGRAPH_OUT)); j = igraph_vector_size(&neis); for (i = 0; i < j; i++) { eid = (long int) VECTOR(neis)[i]; k = IGRAPH_TO(graph, eid); if (VECTOR(indegrees)[k] <= 0) { /* Already removed, continue */ continue; } VECTOR(indegrees)[k]--; VECTOR(instrengths)[k] -= (weights ? VECTOR(*weights)[eid] : 1.0); if (VECTOR(indegrees)[k] == 0) { IGRAPH_CHECK(igraph_dqueue_push(&sources, k)); } } /* Remove incoming edges */ IGRAPH_CHECK(igraph_incident(graph, &neis, (igraph_integer_t) v, IGRAPH_IN)); j = igraph_vector_size(&neis); for (i = 0; i < j; i++) { eid = (long int) VECTOR(neis)[i]; k = IGRAPH_FROM(graph, eid); if (VECTOR(outdegrees)[k] <= 0) { /* Already removed, continue */ continue; } VECTOR(outdegrees)[k]--; VECTOR(outstrengths)[k] -= (weights ? VECTOR(*weights)[eid] : 1.0); if (VECTOR(outdegrees)[k] == 0 && VECTOR(indegrees)[k] > 0) { IGRAPH_CHECK(igraph_dqueue_push(&sinks, k)); } } VECTOR(outdegrees)[v] = -1; VECTOR(indegrees)[v] = -1; nodes_left--; } } igraph_dqueue_destroy(&sinks); igraph_dqueue_destroy(&sources); igraph_vector_destroy(&neis); igraph_vector_destroy(&outstrengths); igraph_vector_destroy(&instrengths); igraph_vector_destroy(&outdegrees); igraph_vector_destroy(&indegrees); IGRAPH_FINALLY_CLEAN(7); /* Tidy up the ordering */ for (i = 0; i < no_of_nodes; i++) { if (ordering[i] < 0) { ordering[i] += no_of_nodes; } } /* Find the feedback edges based on the ordering */ if (result != 0) { igraph_vector_clear(result); j = igraph_ecount(graph); for (i = 0; i < j; i++) { long int from = IGRAPH_FROM(graph, i), to = IGRAPH_TO(graph, i); if (from == to || ordering[from] > ordering[to]) { IGRAPH_CHECK(igraph_vector_push_back(result, i)); } } } /* If we have also requested a layering, return that as well */ if (layers != 0) { igraph_vector_t ranks; igraph_vector_long_t order_vec; IGRAPH_CHECK(igraph_vector_resize(layers, no_of_nodes)); igraph_vector_null(layers); igraph_vector_long_view(&order_vec, ordering, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); IGRAPH_VECTOR_INIT_FINALLY(&ranks, 0); IGRAPH_CHECK((int) igraph_vector_long_qsort_ind(&order_vec, &ranks, 0)); for (i = 0; i < no_of_nodes; i++) { long int from = (long int) VECTOR(ranks)[i]; IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) from, IGRAPH_OUT)); k = igraph_vector_size(&neis); for (j = 0; j < k; j++) { long int to = (long int) VECTOR(neis)[j]; if (from == to) { continue; } if (ordering[from] > ordering[to]) { continue; } if (VECTOR(*layers)[to] < VECTOR(*layers)[from] + 1) { VECTOR(*layers)[to] = VECTOR(*layers)[from] + 1; } } } igraph_vector_destroy(&neis); igraph_vector_destroy(&ranks); IGRAPH_FINALLY_CLEAN(2); } /* Free the ordering vector */ igraph_free(ordering); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } /** * Solves the feedback arc set problem using integer programming. */ int igraph_i_feedback_arc_set_ip(const igraph_t *graph, igraph_vector_t *result, const igraph_vector_t *weights) { #ifndef HAVE_GLPK IGRAPH_ERROR("GLPK is not available", IGRAPH_UNIMPLEMENTED); #else igraph_integer_t no_of_components; igraph_integer_t no_of_vertices = igraph_vcount(graph); igraph_integer_t no_of_edges = igraph_ecount(graph); igraph_vector_t membership, ordering, vertex_remapping; igraph_vector_ptr_t vertices_by_components, edges_by_components; long int i, j, k, l, m, n, from, to; igraph_real_t weight; glp_prob *ip; glp_iocp parm; IGRAPH_VECTOR_INIT_FINALLY(&membership, 0); IGRAPH_VECTOR_INIT_FINALLY(&ordering, 0); IGRAPH_VECTOR_INIT_FINALLY(&vertex_remapping, no_of_vertices); igraph_vector_clear(result); /* Decompose the graph into connected components */ IGRAPH_CHECK(igraph_clusters(graph, &membership, 0, &no_of_components, IGRAPH_WEAK)); /* Construct vertex and edge lists for each of the components */ IGRAPH_CHECK(igraph_vector_ptr_init(&vertices_by_components, no_of_components)); IGRAPH_CHECK(igraph_vector_ptr_init(&edges_by_components, no_of_components)); IGRAPH_FINALLY(igraph_vector_ptr_destroy_all, &vertices_by_components); IGRAPH_FINALLY(igraph_vector_ptr_destroy_all, &edges_by_components); for (i = 0; i < no_of_components; i++) { igraph_vector_t* vptr; vptr = igraph_Calloc(1, igraph_vector_t); if (vptr == 0) { IGRAPH_ERROR("cannot calculate feedback arc set using IP", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, vptr); IGRAPH_CHECK(igraph_vector_init(vptr, 0)); IGRAPH_FINALLY_CLEAN(1); VECTOR(vertices_by_components)[i] = vptr; } IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(&vertices_by_components, igraph_vector_destroy); for (i = 0; i < no_of_components; i++) { igraph_vector_t* vptr; vptr = igraph_Calloc(1, igraph_vector_t); if (vptr == 0) { IGRAPH_ERROR("cannot calculate feedback arc set using IP", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, vptr); IGRAPH_CHECK(igraph_vector_init(vptr, 0)); IGRAPH_FINALLY_CLEAN(1); VECTOR(edges_by_components)[i] = vptr; } IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(&edges_by_components, igraph_vector_destroy); for (i = 0; i < no_of_vertices; i++) { j = (long int) VECTOR(membership)[i]; IGRAPH_CHECK(igraph_vector_push_back(VECTOR(vertices_by_components)[j], i)); } for (i = 0; i < no_of_edges; i++) { j = (long int) VECTOR(membership)[(long)IGRAPH_FROM(graph, i)]; IGRAPH_CHECK(igraph_vector_push_back(VECTOR(edges_by_components)[j], i)); } #define VAR2IDX(i, j) (i*(n-1)+j-(i+1)*i/2) /* Configure GLPK */ glp_term_out(GLP_OFF); glp_init_iocp(&parm); parm.br_tech = GLP_BR_DTH; parm.bt_tech = GLP_BT_BLB; parm.pp_tech = GLP_PP_ALL; parm.presolve = GLP_ON; parm.binarize = GLP_OFF; parm.cb_func = igraph_i_glpk_interruption_hook; /* Solve an IP for feedback arc sets in each of the components */ for (i = 0; i < no_of_components; i++) { igraph_vector_t* vertices_in_comp = (igraph_vector_t*)VECTOR(vertices_by_components)[i]; igraph_vector_t* edges_in_comp = (igraph_vector_t*)VECTOR(edges_by_components)[i]; /* * Let x_ij denote whether layer(i) < layer(j). * * The standard formulation of the problem is as follows: * * max sum_{i,j} w_ij x_ij * * subject to * * (1) x_ij + x_ji = 1 (i.e. either layer(i) < layer(j) or layer(i) > layer(j)) * for all i < j * (2) x_ij + x_jk + x_ki <= 2 for all i < j, i < k, j != k * * Note that x_ij = 1 implies that x_ji = 0 and vice versa; in other words, * x_ij = 1 - x_ji. Thus, we can get rid of the (1) constraints and half of the * x_ij variables (where j < i) if we rewrite constraints of type (2) as follows: * * (2a) x_ij + x_jk - x_ik <= 1 for all i < j, i < k, j < k * (2b) x_ij - x_kj - x_ik <= 0 for all i < j, i < k, j > k * * The goal function then becomes: * * max sum_{i 0) { glp_add_cols(ip, (int) k); for (j = 1; j <= k; j++) { glp_set_col_kind(ip, (int) j, GLP_BV); } } /* Set up coefficients in the goal function */ k = igraph_vector_size(edges_in_comp); for (j = 0; j < k; j++) { l = (long int) VECTOR(*edges_in_comp)[j]; from = (long int) VECTOR(vertex_remapping)[(long)IGRAPH_FROM(graph, l)]; to = (long int) VECTOR(vertex_remapping)[(long)IGRAPH_TO(graph, l)]; if (from == to) { continue; } weight = weights ? VECTOR(*weights)[l] : 1; if (from < to) { l = VAR2IDX(from, to); glp_set_obj_coef(ip, (int) l, glp_get_obj_coef(ip, (int) l) + weight); } else { l = VAR2IDX(to, from); glp_set_obj_coef(ip, (int) l, glp_get_obj_coef(ip, (int) l) - weight); } } /* Add constraints */ if (n > 1) { glp_add_rows(ip, (int)(n * (n - 1) / 2 + n * (n - 1) * (n - 2) / 3)); m = 1; for (j = 0; j < n; j++) { int ind[4]; double val[4] = {0, 1, 1, -1}; for (k = j + 1; k < n; k++) { ind[1] = (int) VAR2IDX(j, k); /* Type (2a) */ val[2] = 1; for (l = k + 1; l < n; l++, m++) { ind[2] = (int) VAR2IDX(k, l); ind[3] = (int) VAR2IDX(j, l); glp_set_row_bnds(ip, (int) m, GLP_UP, 1, 1); glp_set_mat_row(ip, (int) m, 3, ind, val); } /* Type (2b) */ val[2] = -1; for (l = j + 1; l < k; l++, m++) { ind[2] = (int) VAR2IDX(l, k); ind[3] = (int) VAR2IDX(j, l); glp_set_row_bnds(ip, (int) m, GLP_UP, 0, 0); glp_set_mat_row(ip, (int) m, 3, ind, val); } } } } /* Solve the problem */ IGRAPH_GLPK_CHECK(glp_intopt(ip, &parm), "Feedback arc set using IP failed"); /* Find the ordering of the vertices */ IGRAPH_CHECK(igraph_vector_resize(&ordering, n)); igraph_vector_null(&ordering); m = n * (n - 1) / 2; j = 0; k = 1; for (l = 1; l <= m; l++) { /* variable l always corresponds to the (j, k) vertex pair */ /* printf("(%ld, %ld) = %g\n", i, j, glp_mip_col_val(ip, l)); */ if (glp_mip_col_val(ip, (int) l) > 0) { /* j comes earlier in the ordering than k */ VECTOR(ordering)[j]++; } else { /* k comes earlier in the ordering than j */ VECTOR(ordering)[k]++; } k++; if (k == n) { j++; k = j + 1; } } /* Find the feedback edges */ k = igraph_vector_size(edges_in_comp); for (j = 0; j < k; j++) { l = (long int) VECTOR(*edges_in_comp)[j]; from = (long int) VECTOR(vertex_remapping)[(long)IGRAPH_FROM(graph, l)]; to = (long int) VECTOR(vertex_remapping)[(long)IGRAPH_TO(graph, l)]; if (from == to || VECTOR(ordering)[from] < VECTOR(ordering)[to]) { IGRAPH_CHECK(igraph_vector_push_back(result, l)); } } /* Clean up */ glp_delete_prob(ip); IGRAPH_FINALLY_CLEAN(1); } igraph_vector_ptr_destroy_all(&vertices_by_components); igraph_vector_ptr_destroy_all(&edges_by_components); igraph_vector_destroy(&vertex_remapping); igraph_vector_destroy(&ordering); igraph_vector_destroy(&membership); IGRAPH_FINALLY_CLEAN(5); return IGRAPH_SUCCESS; #endif } python-igraph-0.8.0/vendor/source/igraph/src/fast_community.c0000644000076500000240000012637313614300625024617 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_community.h" #include "igraph_memory.h" #include "igraph_iterators.h" #include "igraph_interface.h" #include "igraph_progress.h" #include "igraph_interrupt_internal.h" #include "igraph_structural.h" #include "igraph_vector_ptr.h" #include "config.h" /* #define IGRAPH_FASTCOMM_DEBUG */ #ifdef _MSC_VER /* MSVC does not support variadic macros */ #include void debug(const char* fmt, ...) { va_list args; va_start(args, fmt); #ifdef IGRAPH_FASTCOMM_DEBUG vfprintf(stderr, fmt, args); #endif va_end(args); } #else #ifdef IGRAPH_FASTCOMM_DEBUG #define debug(...) fprintf(stderr, __VA_ARGS__) #else #define debug(...) #endif #endif /* * Implementation of the community structure algorithm originally published * by Clauset et al in: * * A. Clauset, M.E.J. Newman and C. Moore, "Finding community structure in * very large networks.". Phys. Rev. E 70, 066111 (2004). * * The data structures being used are slightly different and they are described * most closely in: * * K. Wakita, T. Tsurumi, "Finding community structure in mega-scale social * networks.". arXiv:cs/0702048v1. * * We maintain a vector of communities, each of which containing a list of * pointers to their neighboring communities along with the increase in the * modularity score that could be achieved by joining the two communities. * Each community has a pointer to one of its neighbors - the one which would * result in the highest increase in modularity after a join. The local * (community-level) maximums are also stored in an indexed max-heap. The * max-heap itself stores its elements in an array which satisfies the heap * property, but to allow us to access any of the elements in the array based * on the community index (and not based on the array index - which depends on * the element's actual position in the heap), we also maintain an index * vector in the heap: the ith element of the index vector contains the * position of community i in the array of the max-heap. When we perform * sifting operations on the heap to restore the heap property, we also maintain * the index vector. */ /* Structure storing a pair of communities along with their dQ values */ typedef struct s_igraph_i_fastgreedy_commpair { long int first; /* first member of the community pair */ long int second; /* second member of the community pair */ igraph_real_t *dq; /* pointer to a member of the dq vector storing the */ /* increase in modularity achieved when joining */ struct s_igraph_i_fastgreedy_commpair *opposite; } igraph_i_fastgreedy_commpair; /* Structure storing a community */ typedef struct { igraph_integer_t id; /* Identifier of the community (for merges matrix) */ igraph_integer_t size; /* Size of the community */ igraph_vector_ptr_t neis; /* references to neighboring communities */ igraph_i_fastgreedy_commpair* maxdq; /* community pair with maximal dq */ } igraph_i_fastgreedy_community; /* Global community list structure */ typedef struct { long int no_of_communities, n; /* number of communities, number of vertices */ igraph_i_fastgreedy_community* e; /* list of communities */ igraph_i_fastgreedy_community** heap; /* heap of communities */ igraph_integer_t *heapindex; /* heap index to speed up lookup by community idx */ } igraph_i_fastgreedy_community_list; /* Scans the community neighborhood list for the new maximal dq value. * Returns 1 if the maximum is different from the previous one, * 0 otherwise. */ int igraph_i_fastgreedy_community_rescan_max( igraph_i_fastgreedy_community* comm) { long int i, n; igraph_i_fastgreedy_commpair *p, *best; igraph_real_t bestdq, currdq; n = igraph_vector_ptr_size(&comm->neis); if (n == 0) { comm->maxdq = 0; return 1; } best = (igraph_i_fastgreedy_commpair*)VECTOR(comm->neis)[0]; bestdq = *best->dq; for (i = 1; i < n; i++) { p = (igraph_i_fastgreedy_commpair*)VECTOR(comm->neis)[i]; currdq = *p->dq; if (currdq > bestdq) { best = p; bestdq = currdq; } } if (best != comm->maxdq) { comm->maxdq = best; return 1; } else { return 0; } } /* Destroys the global community list object */ void igraph_i_fastgreedy_community_list_destroy( igraph_i_fastgreedy_community_list* list) { long int i; for (i = 0; i < list->n; i++) { igraph_vector_ptr_destroy(&list->e[i].neis); } free(list->e); if (list->heapindex != 0) { free(list->heapindex); } if (list->heap != 0) { free(list->heap); } } /* Community list heap maintenance: sift down */ void igraph_i_fastgreedy_community_list_sift_down( igraph_i_fastgreedy_community_list* list, long int idx) { long int root, child, c1, c2; igraph_i_fastgreedy_community* dummy; igraph_integer_t dummy2; igraph_i_fastgreedy_community** heap = list->heap; igraph_integer_t* heapindex = list->heapindex; root = idx; while (root * 2 + 1 < list->no_of_communities) { child = root * 2 + 1; if (child + 1 < list->no_of_communities && *heap[child]->maxdq->dq < *heap[child + 1]->maxdq->dq) { child++; } if (*heap[root]->maxdq->dq < *heap[child]->maxdq->dq) { c1 = heap[root]->maxdq->first; c2 = heap[child]->maxdq->first; dummy = heap[root]; heap[root] = heap[child]; heap[child] = dummy; dummy2 = heapindex[c1]; heapindex[c1] = heapindex[c2]; heapindex[c2] = dummy2; root = child; } else { break; } } } /* Community list heap maintenance: sift up */ void igraph_i_fastgreedy_community_list_sift_up( igraph_i_fastgreedy_community_list* list, long int idx) { long int root, parent, c1, c2; igraph_i_fastgreedy_community* dummy; igraph_integer_t dummy2; igraph_i_fastgreedy_community** heap = list->heap; igraph_integer_t* heapindex = list->heapindex; root = idx; while (root > 0) { parent = (root - 1) / 2; if (*heap[parent]->maxdq->dq < *heap[root]->maxdq->dq) { c1 = heap[root]->maxdq->first; c2 = heap[parent]->maxdq->first; dummy = heap[parent]; heap[parent] = heap[root]; heap[root] = dummy; dummy2 = heapindex[c1]; heapindex[c1] = heapindex[c2]; heapindex[c2] = dummy2; root = parent; } else { break; } } } /* Builds the community heap for the first time */ void igraph_i_fastgreedy_community_list_build_heap( igraph_i_fastgreedy_community_list* list) { long int i; for (i = list->no_of_communities / 2 - 1; i >= 0; i--) { igraph_i_fastgreedy_community_list_sift_down(list, i); } } /* Finds the element belonging to a given community in the heap and return its * index in the heap array */ #define igraph_i_fastgreedy_community_list_find_in_heap(list, idx) (list)->heapindex[idx] /* Dumps the heap - for debugging purposes */ void igraph_i_fastgreedy_community_list_dump_heap( igraph_i_fastgreedy_community_list* list) { long int i; debug("Heap:\n"); for (i = 0; i < list->no_of_communities; i++) { debug("(%ld, %p, %p)", i, list->heap[i], list->heap[i]->maxdq); if (list->heap[i]->maxdq) { debug(" (%ld, %ld, %.7f)", list->heap[i]->maxdq->first, list->heap[i]->maxdq->second, *list->heap[i]->maxdq->dq); } debug("\n"); } debug("Heap index:\n"); for (i = 0; i < list->no_of_communities; i++) { debug("%ld ", (long)list->heapindex[i]); } debug("\nEND\n"); } /* Checks if the community heap satisfies the heap property. * Only useful for debugging. */ void igraph_i_fastgreedy_community_list_check_heap( igraph_i_fastgreedy_community_list* list) { long int i; for (i = 0; i < list->no_of_communities / 2; i++) { if ((2 * i + 1 < list->no_of_communities && *list->heap[i]->maxdq->dq < *list->heap[2 * i + 1]->maxdq->dq) || (2 * i + 2 < list->no_of_communities && *list->heap[i]->maxdq->dq < *list->heap[2 * i + 2]->maxdq->dq)) { IGRAPH_WARNING("Heap property violated"); debug("Position: %ld, %ld and %ld\n", i, 2 * i + 1, 2 * i + 2); igraph_i_fastgreedy_community_list_dump_heap(list); } } } /* Removes a given element from the heap */ void igraph_i_fastgreedy_community_list_remove( igraph_i_fastgreedy_community_list* list, long int idx) { igraph_real_t old; long int commidx; /* First adjust the index */ commidx = list->heap[list->no_of_communities - 1]->maxdq->first; list->heapindex[commidx] = (igraph_integer_t) idx; commidx = list->heap[idx]->maxdq->first; list->heapindex[commidx] = -1; /* Now remove the element */ old = *list->heap[idx]->maxdq->dq; list->heap[idx] = list->heap[list->no_of_communities - 1]; list->no_of_communities--; /* Recover heap property */ if (old > *list->heap[idx]->maxdq->dq) { igraph_i_fastgreedy_community_list_sift_down(list, idx); } else { igraph_i_fastgreedy_community_list_sift_up(list, idx); } } /* Removes a given element from the heap when there are no more neighbors * for it (comm->maxdq is NULL) */ void igraph_i_fastgreedy_community_list_remove2( igraph_i_fastgreedy_community_list* list, long int idx, long int comm) { long int i; if (idx == list->no_of_communities - 1) { /* We removed the rightmost element on the bottom level, no problem, * there's nothing to be done */ list->heapindex[comm] = -1; list->no_of_communities--; return; } /* First adjust the index */ i = list->heap[list->no_of_communities - 1]->maxdq->first; list->heapindex[i] = (igraph_integer_t) idx; list->heapindex[comm] = -1; /* Now remove the element */ list->heap[idx] = list->heap[list->no_of_communities - 1]; list->no_of_communities--; /* Recover heap property */ for (i = list->no_of_communities / 2 - 1; i >= 0; i--) { igraph_i_fastgreedy_community_list_sift_down(list, i); } } /* Removes the pair belonging to community k from the neighborhood list * of community c (that is, clist[c]) and recalculates maxdq */ void igraph_i_fastgreedy_community_remove_nei( igraph_i_fastgreedy_community_list* list, long int c, long int k) { long int i, n; igraph_bool_t rescan = 0; igraph_i_fastgreedy_commpair *p; igraph_i_fastgreedy_community *comm; igraph_real_t olddq; comm = &list->e[c]; n = igraph_vector_ptr_size(&comm->neis); for (i = 0; i < n; i++) { p = (igraph_i_fastgreedy_commpair*)VECTOR(comm->neis)[i]; if (p->second == k) { /* Check current maxdq */ if (comm->maxdq == p) { rescan = 1; } break; } } if (i < n) { olddq = *comm->maxdq->dq; igraph_vector_ptr_remove(&comm->neis, i); if (rescan) { igraph_i_fastgreedy_community_rescan_max(comm); i = igraph_i_fastgreedy_community_list_find_in_heap(list, c); if (comm->maxdq) { if (*comm->maxdq->dq > olddq) { igraph_i_fastgreedy_community_list_sift_up(list, i); } else { igraph_i_fastgreedy_community_list_sift_down(list, i); } } else { /* no more neighbors for this community. we should remove this * community from the heap and restore the heap property */ debug("REMOVING (NO MORE NEIS): %ld\n", i); igraph_i_fastgreedy_community_list_remove2(list, i, c); } } } } /* Auxiliary function to sort a community pair list with respect to the * `second` field */ int igraph_i_fastgreedy_commpair_cmp(const void* p1, const void* p2) { igraph_i_fastgreedy_commpair *cp1, *cp2; cp1 = *(igraph_i_fastgreedy_commpair**)p1; cp2 = *(igraph_i_fastgreedy_commpair**)p2; return (int) (cp1->second - cp2->second); } /* Sorts the neighbor list of the community with the given index, optionally * optimizing the process if we know that the list is nearly sorted and only * a given pair is in the wrong place. */ void igraph_i_fastgreedy_community_sort_neighbors_of( igraph_i_fastgreedy_community_list* list, long int index, igraph_i_fastgreedy_commpair* changed_pair) { igraph_vector_ptr_t* vec; long int i, n; igraph_bool_t can_skip_sort = 0; igraph_i_fastgreedy_commpair *other_pair; vec = &list->e[index].neis; if (changed_pair != 0) { /* Optimized sorting */ /* First we look for changed_pair in vec */ n = igraph_vector_ptr_size(vec); for (i = 0; i < n; i++) { if (VECTOR(*vec)[i] == changed_pair) { break; } } /* Did we find it? We should have -- otherwise it's a bug */ if (i >= n) { IGRAPH_WARNING("changed_pair not found in neighbor vector while re-sorting " "the neighbors of a community; this is probably a bug. Falling back to " "full sort instead." ); } else { /* Okay, the pair that changed is at index i. We need to figure out where * its new place should be. We can simply try moving the item all the way * to the left as long as the comparison function tells so (since the * rest of the vector is sorted), and then move all the way to the right * as long as the comparison function tells so, and we will be okay. */ /* Shifting to the left */ while (i > 0) { other_pair = VECTOR(*vec)[i - 1]; if (other_pair->second > changed_pair->second) { VECTOR(*vec)[i] = other_pair; i--; } else { break; } } VECTOR(*vec)[i] = changed_pair; /* Shifting to the right */ while (i < n - 1) { other_pair = VECTOR(*vec)[i + 1]; if (other_pair->second < changed_pair->second) { VECTOR(*vec)[i] = other_pair; i++; } else { break; } } VECTOR(*vec)[i] = changed_pair; /* Mark that we don't need a full sort */ can_skip_sort = 1; } } if (!can_skip_sort) { /* Fallback to full sorting */ igraph_vector_ptr_sort(vec, igraph_i_fastgreedy_commpair_cmp); } } /* Updates the dq value of community pair p in the community with index p->first * of the community list clist to newdq and restores the heap property * in community c if necessary. Returns 1 if the maximum in the row had * to be updated, zero otherwise */ int igraph_i_fastgreedy_community_update_dq( igraph_i_fastgreedy_community_list* list, igraph_i_fastgreedy_commpair* p, igraph_real_t newdq) { long int i, j, to, from; igraph_real_t olddq; igraph_i_fastgreedy_community *comm_to, *comm_from; to = p->first; from = p->second; comm_to = &list->e[to]; comm_from = &list->e[from]; if (comm_to->maxdq == p && newdq >= *p->dq) { /* If we are adjusting the current maximum and it is increased, we don't * have to re-scan for the new maximum */ *p->dq = newdq; /* The maximum was increased, so perform a sift-up in the heap */ i = igraph_i_fastgreedy_community_list_find_in_heap(list, to); igraph_i_fastgreedy_community_list_sift_up(list, i); /* Let's check the opposite side. If the pair was not the maximal in * the opposite side (the other community list)... */ if (comm_from->maxdq != p->opposite) { if (*comm_from->maxdq->dq < newdq) { /* ...and it will become the maximal, we need to adjust and sift up */ comm_from->maxdq = p->opposite; j = igraph_i_fastgreedy_community_list_find_in_heap(list, from); igraph_i_fastgreedy_community_list_sift_up(list, j); } else { /* The pair was not the maximal in the opposite side and it will * NOT become the maximal, there's nothing to do there */ } } else { /* The pair was maximal in the opposite side, so we need to sift it up * with the new value */ j = igraph_i_fastgreedy_community_list_find_in_heap(list, from); igraph_i_fastgreedy_community_list_sift_up(list, j); } return 1; } else if (comm_to->maxdq != p && (newdq <= *comm_to->maxdq->dq)) { /* If we are modifying an item which is not the current maximum, and the * new value is less than the current maximum, we don't * have to re-scan for the new maximum */ olddq = *p->dq; *p->dq = newdq; /* However, if the item was the maximum on the opposite side, we'd better * re-scan it */ if (comm_from->maxdq == p->opposite) { if (olddq > newdq) { /* Decreased the maximum on the other side, we have to re-scan for the * new maximum */ igraph_i_fastgreedy_community_rescan_max(comm_from); j = igraph_i_fastgreedy_community_list_find_in_heap(list, from); igraph_i_fastgreedy_community_list_sift_down(list, j); } else { /* Increased the maximum on the other side, we don't have to re-scan * but we might have to sift up */ j = igraph_i_fastgreedy_community_list_find_in_heap(list, from); igraph_i_fastgreedy_community_list_sift_up(list, j); } } return 0; } else { /* We got here in two cases: (1) the pair we are modifying right now is the maximum in the given community and we are decreasing it (2) the pair we are modifying right now is NOT the maximum in the given community, but we increase it so much that it will become the new maximum */ *p->dq = newdq; if (comm_to->maxdq != p) { /* case (2) */ comm_to->maxdq = p; /* The maximum was increased, so perform a sift-up in the heap */ i = igraph_i_fastgreedy_community_list_find_in_heap(list, to); igraph_i_fastgreedy_community_list_sift_up(list, i); /* Opposite side. Chances are that the new value became the maximum * in the opposite side, but check it first */ if (comm_from->maxdq != p->opposite) { if (*comm_from->maxdq->dq < newdq) { /* Yes, it will become the new maximum */ comm_from->maxdq = p->opposite; j = igraph_i_fastgreedy_community_list_find_in_heap(list, from); igraph_i_fastgreedy_community_list_sift_up(list, j); } else { /* No, nothing to do there */ } } else { /* Already increased the maximum on the opposite side, so sift it up */ j = igraph_i_fastgreedy_community_list_find_in_heap(list, from); igraph_i_fastgreedy_community_list_sift_up(list, j); } } else { /* case (1) */ /* This is the worst, we have to re-scan the whole community to find * the new maximum and update the global maximum as well if necessary */ igraph_i_fastgreedy_community_rescan_max(comm_to); /* The maximum was decreased, so perform a sift-down in the heap */ i = igraph_i_fastgreedy_community_list_find_in_heap(list, to); igraph_i_fastgreedy_community_list_sift_down(list, i); if (comm_from->maxdq != p->opposite) { /* The one that we decreased on the opposite side is not the * maximal one. Nothing to do. */ } else { /* We decreased the maximal on the opposite side as well. Re-scan * and sift down */ igraph_i_fastgreedy_community_rescan_max(comm_from); j = igraph_i_fastgreedy_community_list_find_in_heap(list, from); igraph_i_fastgreedy_community_list_sift_down(list, j); } } } return 1; } /** * \function igraph_community_fastgreedy * \brief Finding community structure by greedy optimization of modularity * * This function implements the fast greedy modularity optimization * algorithm for finding community structure, see * A Clauset, MEJ Newman, C Moore: Finding community structure in very * large networks, http://www.arxiv.org/abs/cond-mat/0408187 for the * details. * * * Some improvements proposed in K Wakita, T Tsurumi: Finding community * structure in mega-scale social networks, * http://www.arxiv.org/abs/cs.CY/0702048v1 have also been implemented. * * \param graph The input graph. It must be a graph without multiple edges. * This is checked and an error message is given for graphs with multiple * edges. * \param weights Potentially a numeric vector containing edge * weights. Supply a null pointer here for unweighted graphs. The * weights are expected to be non-negative. * \param merges Pointer to an initialized matrix or NULL, the result of the * computation is stored here. The matrix has two columns and each * merge corresponds to one merge, the ids of the two merged * components are stored. The component ids are numbered from zero and * the first \c n components are the individual vertices, \c n is * the number of vertices in the graph. Component \c n is created * in the first merge, component \c n+1 in the second merge, etc. * The matrix will be resized as needed. If this argument is NULL * then it is ignored completely. * \param modularity Pointer to an initialized vector or NULL pointer, * in the former case the modularity scores along the stages of the * computation are recorded here. The vector will be resized as * needed. * \param membership Pointer to a vector. If not a null pointer, then * the membership vector corresponding to the best split (in terms * of modularity) is stored here. * \return Error code. * * \sa \ref igraph_community_walktrap(), \ref * igraph_community_edge_betweenness() for other community detection * algorithms, \ref igraph_community_to_membership() to convert the * dendrogram to a membership vector. * * Time complexity: O(|E||V|log|V|) in the worst case, * O(|E|+|V|log^2|V|) typically, |V| is the number of vertices, |E| is * the number of edges. * * \example examples/simple/igraph_community_fastgreedy.c */ int igraph_community_fastgreedy(const igraph_t *graph, const igraph_vector_t *weights, igraph_matrix_t *merges, igraph_vector_t *modularity, igraph_vector_t *membership) { long int no_of_edges, no_of_nodes, no_of_joins, total_joins; long int i, j, k, n, m, from, to, dummy, best_no_of_joins; igraph_integer_t ffrom, fto; igraph_eit_t edgeit; igraph_i_fastgreedy_commpair *pairs, *p1, *p2; igraph_i_fastgreedy_community_list communities; igraph_vector_t a; igraph_real_t q, *dq, bestq, weight_sum, loop_weight_sum; igraph_bool_t has_multiple; igraph_matrix_t merges_local; /*long int join_order[] = { 16,5, 5,6, 6,0, 4,0, 10,0, 26,29, 29,33, 23,33, 27,33, 25,24, 24,31, 12,3, 21,1, 30,8, 8,32, 9,2, 17,1, 11,0, 7,3, 3,2, 13,2, 1,2, 28,31, 31,33, 22,32, 18,32, 20,32, 32,33, 15,33, 14,33, 0,19, 19,2, -1,-1 };*/ /*long int join_order[] = { 43,42, 42,41, 44,41, 41,36, 35,36, 37,36, 36,29, 38,29, 34,29, 39,29, 33,29, 40,29, 32,29, 14,29, 30,29, 31,29, 6,18, 18,4, 23,4, 21,4, 19,4, 27,4, 20,4, 22,4, 26,4, 25,4, 24,4, 17,4, 0,13, 13,2, 1,2, 11,2, 8,2, 5,2, 3,2, 10,2, 9,2, 7,2, 2,28, 28,15, 12,15, 29,16, 4,15, -1,-1 };*/ no_of_nodes = igraph_vcount(graph); no_of_edges = igraph_ecount(graph); if (igraph_is_directed(graph)) { IGRAPH_ERROR("fast greedy community detection works for undirected graphs only", IGRAPH_UNIMPLEMENTED); } total_joins = no_of_nodes - 1; if (weights != 0) { if (igraph_vector_size(weights) < igraph_ecount(graph)) { IGRAPH_ERROR("fast greedy community detection: weight vector too short", IGRAPH_EINVAL); } if (igraph_vector_any_smaller(weights, 0)) { IGRAPH_ERROR("weights must be positive", IGRAPH_EINVAL); } weight_sum = igraph_vector_sum(weights); } else { weight_sum = no_of_edges; } IGRAPH_CHECK(igraph_has_multiple(graph, &has_multiple)); if (has_multiple) { IGRAPH_ERROR("fast-greedy community finding works only on graphs without multiple edges", IGRAPH_EINVAL); } if (membership != 0 && merges == 0) { /* We need the merge matrix because the user wants the membership * vector, so we allocate one on our own */ IGRAPH_CHECK(igraph_matrix_init(&merges_local, total_joins, 2)); IGRAPH_FINALLY(igraph_matrix_destroy, &merges_local); merges = &merges_local; } if (merges != 0) { IGRAPH_CHECK(igraph_matrix_resize(merges, total_joins, 2)); igraph_matrix_null(merges); } if (modularity != 0) { IGRAPH_CHECK(igraph_vector_resize(modularity, total_joins + 1)); } /* Create degree vector */ IGRAPH_VECTOR_INIT_FINALLY(&a, no_of_nodes); if (weights) { debug("Calculating weighted degrees\n"); for (i = 0; i < no_of_edges; i++) { VECTOR(a)[(long int)IGRAPH_FROM(graph, i)] += VECTOR(*weights)[i]; VECTOR(a)[(long int)IGRAPH_TO(graph, i)] += VECTOR(*weights)[i]; } } else { debug("Calculating degrees\n"); IGRAPH_CHECK(igraph_degree(graph, &a, igraph_vss_all(), IGRAPH_ALL, 1)); } /* Create list of communities */ debug("Creating community list\n"); communities.n = no_of_nodes; communities.no_of_communities = no_of_nodes; communities.e = (igraph_i_fastgreedy_community*)calloc((size_t) no_of_nodes, sizeof(igraph_i_fastgreedy_community)); if (communities.e == 0) { IGRAPH_ERROR("can't run fast greedy community detection", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, communities.e); communities.heap = (igraph_i_fastgreedy_community**)calloc((size_t) no_of_nodes, sizeof(igraph_i_fastgreedy_community*)); if (communities.heap == 0) { IGRAPH_ERROR("can't run fast greedy community detection", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, communities.heap); communities.heapindex = (igraph_integer_t*)calloc((size_t)no_of_nodes, sizeof(igraph_integer_t)); if (communities.heapindex == 0) { IGRAPH_ERROR("can't run fast greedy community detection", IGRAPH_ENOMEM); } IGRAPH_FINALLY_CLEAN(2); IGRAPH_FINALLY(igraph_i_fastgreedy_community_list_destroy, &communities); for (i = 0; i < no_of_nodes; i++) { igraph_vector_ptr_init(&communities.e[i].neis, 0); communities.e[i].id = (igraph_integer_t) i; communities.e[i].size = 1; } /* Create list of community pairs from edges */ debug("Allocating dq vector\n"); dq = (igraph_real_t*)calloc((size_t) no_of_edges, sizeof(igraph_real_t)); if (dq == 0) { IGRAPH_ERROR("can't run fast greedy community detection", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, dq); debug("Creating community pair list\n"); IGRAPH_CHECK(igraph_eit_create(graph, igraph_ess_all(0), &edgeit)); IGRAPH_FINALLY(igraph_eit_destroy, &edgeit); pairs = (igraph_i_fastgreedy_commpair*)calloc(2 * (size_t) no_of_edges, sizeof(igraph_i_fastgreedy_commpair)); if (pairs == 0) { IGRAPH_ERROR("can't run fast greedy community detection", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, pairs); loop_weight_sum = 0; for (i = 0, j = 0; !IGRAPH_EIT_END(edgeit); i += 2, j++, IGRAPH_EIT_NEXT(edgeit)) { long int eidx = IGRAPH_EIT_GET(edgeit); igraph_edge(graph, (igraph_integer_t) eidx, &ffrom, &fto); /* Create the pairs themselves */ from = (long int)ffrom; to = (long int)fto; if (from == to) { loop_weight_sum += weights ? 2 * VECTOR(*weights)[eidx] : 2; continue; } if (from > to) { dummy = from; from = to; to = dummy; } if (weights) { dq[j] = 2 * (VECTOR(*weights)[eidx] / (weight_sum * 2.0) - VECTOR(a)[from] * VECTOR(a)[to] / (4.0 * weight_sum * weight_sum)); } else { dq[j] = 2 * (1.0 / (no_of_edges * 2.0) - VECTOR(a)[from] * VECTOR(a)[to] / (4.0 * no_of_edges * no_of_edges)); } pairs[i].first = from; pairs[i].second = to; pairs[i].dq = &dq[j]; pairs[i].opposite = &pairs[i + 1]; pairs[i + 1].first = to; pairs[i + 1].second = from; pairs[i + 1].dq = pairs[i].dq; pairs[i + 1].opposite = &pairs[i]; /* Link the pair to the communities */ igraph_vector_ptr_push_back(&communities.e[from].neis, &pairs[i]); igraph_vector_ptr_push_back(&communities.e[to].neis, &pairs[i + 1]); /* Update maximums */ if (communities.e[from].maxdq == 0 || *communities.e[from].maxdq->dq < *pairs[i].dq) { communities.e[from].maxdq = &pairs[i]; } if (communities.e[to].maxdq == 0 || *communities.e[to].maxdq->dq < *pairs[i + 1].dq) { communities.e[to].maxdq = &pairs[i + 1]; } } igraph_eit_destroy(&edgeit); IGRAPH_FINALLY_CLEAN(1); /* Sorting community neighbor lists by community IDs */ debug("Sorting community neighbor lists\n"); for (i = 0, j = 0; i < no_of_nodes; i++) { igraph_i_fastgreedy_community_sort_neighbors_of(&communities, i, 0); /* Isolated vertices and vertices with loop edges only won't be stored in * the heap (to avoid maxdq == 0) */ if (communities.e[i].maxdq != 0) { communities.heap[j] = &communities.e[i]; communities.heapindex[i] = (igraph_integer_t) j; j++; } else { communities.heapindex[i] = -1; } } communities.no_of_communities = j; /* Calculate proper vector a (see paper) and initial modularity */ q = 2.0 * (weights ? weight_sum : no_of_edges); if (q == 0) { /* All the weights are zero */ } else { igraph_vector_scale(&a, 1.0 / q); q = loop_weight_sum / q; for (i = 0; i < no_of_nodes; i++) { q -= VECTOR(a)[i] * VECTOR(a)[i]; } } /* Initialize "best modularity" value and best merge counter */ bestq = q; best_no_of_joins = 0; /* Initializing community heap */ debug("Initializing community heap\n"); igraph_i_fastgreedy_community_list_build_heap(&communities); debug("Initial modularity: %.4f\n", q); /* Let's rock ;) */ no_of_joins = 0; while (no_of_joins < total_joins) { IGRAPH_ALLOW_INTERRUPTION(); IGRAPH_PROGRESS("fast greedy community detection", no_of_joins * 100.0 / total_joins, 0); /* Store the modularity */ if (modularity) { VECTOR(*modularity)[no_of_joins] = q; } /* Update best modularity if needed */ if (q >= bestq) { bestq = q; best_no_of_joins = no_of_joins; } /* Some debug info if needed */ /* igraph_i_fastgreedy_community_list_check_heap(&communities); */ #ifdef DEBUG debug("===========================================\n"); for (i = 0; i < communities.n; i++) { if (communities.e[i].maxdq == 0) { debug("Community #%ld: PASSIVE\n", i); continue; } debug("Community #%ld\n ", i); for (j = 0; j < igraph_vector_ptr_size(&communities.e[i].neis); j++) { p1 = (igraph_i_fastgreedy_commpair*)VECTOR(communities.e[i].neis)[j]; debug(" (%ld,%ld,%.4f)", p1->first, p1->second, *p1->dq); } p1 = communities.e[i].maxdq; debug("\n Maxdq: (%ld,%ld,%.4f)\n", p1->first, p1->second, *p1->dq); } debug("Global maxdq is: (%ld,%ld,%.4f)\n", communities.heap[0]->maxdq->first, communities.heap[0]->maxdq->second, *communities.heap[0]->maxdq->dq); for (i = 0; i < communities.no_of_communities; i++) { debug("(%ld,%ld,%.4f) ", communities.heap[i]->maxdq->first, communities.heap[i]->maxdq->second, *communities.heap[0]->maxdq->dq); } debug("\n"); #endif if (communities.heap[0] == 0) { break; /* no more communities */ } if (communities.heap[0]->maxdq == 0) { break; /* there are only isolated comms */ } to = communities.heap[0]->maxdq->second; from = communities.heap[0]->maxdq->first; debug("Q[%ld] = %.7f\tdQ = %.7f\t |H| = %ld\n", no_of_joins, q, *communities.heap[0]->maxdq->dq, no_of_nodes - no_of_joins - 1); /* DEBUG */ /* from=join_order[no_of_joins*2]; to=join_order[no_of_joins*2+1]; if (to == -1) break; for (i=0; isecond == from) communities.maxdq = p1; } */ n = igraph_vector_ptr_size(&communities.e[to].neis); m = igraph_vector_ptr_size(&communities.e[from].neis); /*if (n>m) { dummy=n; n=m; m=dummy; dummy=to; to=from; from=dummy; }*/ debug(" joining: %ld <- %ld\n", to, from); q += *communities.heap[0]->maxdq->dq; /* Merge the second community into the first */ i = j = 0; while (i < n && j < m) { p1 = (igraph_i_fastgreedy_commpair*)VECTOR(communities.e[to].neis)[i]; p2 = (igraph_i_fastgreedy_commpair*)VECTOR(communities.e[from].neis)[j]; debug("Pairs: %ld-%ld and %ld-%ld\n", p1->first, p1->second, p2->first, p2->second); if (p1->second < p2->second) { /* Considering p1 from now on */ debug(" Considering: %ld-%ld\n", p1->first, p1->second); if (p1->second == from) { debug(" WILL REMOVE: %ld-%ld\n", to, from); } else { /* chain, case 1 */ debug(" CHAIN(1): %ld-%ld %ld, now=%.7f, adding=%.7f, newdq(%ld,%ld)=%.7f\n", to, p1->second, from, *p1->dq, -2 * VECTOR(a)[from]*VECTOR(a)[p1->second], p1->first, p1->second, *p1->dq - 2 * VECTOR(a)[from]*VECTOR(a)[p1->second]); igraph_i_fastgreedy_community_update_dq(&communities, p1, *p1->dq - 2 * VECTOR(a)[from]*VECTOR(a)[p1->second]); } i++; } else if (p1->second == p2->second) { /* p1->first, p1->second and p2->first form a triangle */ debug(" Considering: %ld-%ld and %ld-%ld\n", p1->first, p1->second, p2->first, p2->second); /* Update dq value */ debug(" TRIANGLE: %ld-%ld-%ld, now=%.7f, adding=%.7f, newdq(%ld,%ld)=%.7f\n", to, p1->second, from, *p1->dq, *p2->dq, p1->first, p1->second, *p1->dq + *p2->dq); igraph_i_fastgreedy_community_update_dq(&communities, p1, *p1->dq + *p2->dq); igraph_i_fastgreedy_community_remove_nei(&communities, p1->second, from); i++; j++; } else { debug(" Considering: %ld-%ld\n", p2->first, p2->second); if (p2->second == to) { debug(" WILL REMOVE: %ld-%ld\n", p2->second, p2->first); } else { /* chain, case 2 */ debug(" CHAIN(2): %ld %ld-%ld, newdq(%ld,%ld)=%.7f\n", to, p2->second, from, to, p2->second, *p2->dq - 2 * VECTOR(a)[to]*VECTOR(a)[p2->second]); p2->opposite->second = to; /* p2->opposite->second changed, so it means that * communities.e[p2->second].neis (which contains p2->opposite) is * not sorted any more. We have to find the index of p2->opposite in * this vector and move it to the correct place. Moving should be an * O(n) operation; re-sorting would be O(n*logn) or even worse, * depending on the pivoting strategy used by qsort() since the * vector is nearly sorted */ igraph_i_fastgreedy_community_sort_neighbors_of( &communities, p2->second, p2->opposite); /* link from.neis[j] to the current place in to.neis if * from.neis[j] != to */ p2->first = to; IGRAPH_CHECK(igraph_vector_ptr_insert(&communities.e[to].neis, i, p2)); n++; i++; if (*p2->dq > *communities.e[to].maxdq->dq) { communities.e[to].maxdq = p2; k = igraph_i_fastgreedy_community_list_find_in_heap(&communities, to); igraph_i_fastgreedy_community_list_sift_up(&communities, k); } igraph_i_fastgreedy_community_update_dq(&communities, p2, *p2->dq - 2 * VECTOR(a)[to]*VECTOR(a)[p2->second]); } j++; } } while (i < n) { p1 = (igraph_i_fastgreedy_commpair*)VECTOR(communities.e[to].neis)[i]; if (p1->second == from) { debug(" WILL REMOVE: %ld-%ld\n", p1->first, from); } else { /* chain, case 1 */ debug(" CHAIN(1): %ld-%ld %ld, now=%.7f, adding=%.7f, newdq(%ld,%ld)=%.7f\n", to, p1->second, from, *p1->dq, -2 * VECTOR(a)[from]*VECTOR(a)[p1->second], p1->first, p1->second, *p1->dq - 2 * VECTOR(a)[from]*VECTOR(a)[p1->second]); igraph_i_fastgreedy_community_update_dq(&communities, p1, *p1->dq - 2 * VECTOR(a)[from]*VECTOR(a)[p1->second]); } i++; } while (j < m) { p2 = (igraph_i_fastgreedy_commpair*)VECTOR(communities.e[from].neis)[j]; if (to == p2->second) { j++; continue; } /* chain, case 2 */ debug(" CHAIN(2): %ld %ld-%ld, newdq(%ld,%ld)=%.7f\n", to, p2->second, from, p1->first, p2->second, *p2->dq - 2 * VECTOR(a)[to]*VECTOR(a)[p2->second]); p2->opposite->second = to; /* need to re-sort community nei list `p2->second` */ igraph_i_fastgreedy_community_sort_neighbors_of(&communities, p2->second, p2->opposite); /* link from.neis[j] to the current place in to.neis if * from.neis[j] != to */ p2->first = to; IGRAPH_CHECK(igraph_vector_ptr_push_back(&communities.e[to].neis, p2)); if (*p2->dq > *communities.e[to].maxdq->dq) { communities.e[to].maxdq = p2; k = igraph_i_fastgreedy_community_list_find_in_heap(&communities, to); igraph_i_fastgreedy_community_list_sift_up(&communities, k); } igraph_i_fastgreedy_community_update_dq(&communities, p2, *p2->dq - 2 * VECTOR(a)[to]*VECTOR(a)[p2->second]); j++; } /* Now, remove community `from` from the neighbors of community `to` */ if (communities.no_of_communities > 2) { debug(" REMOVING: %ld-%ld\n", to, from); igraph_i_fastgreedy_community_remove_nei(&communities, to, from); i = igraph_i_fastgreedy_community_list_find_in_heap(&communities, from); igraph_i_fastgreedy_community_list_remove(&communities, i); } communities.e[from].maxdq = 0; /* Update community sizes */ communities.e[to].size += communities.e[from].size; communities.e[from].size = 0; /* record what has been merged */ /* igraph_vector_ptr_clear is not enough here as it won't free * the memory consumed by communities.e[from].neis. Thanks * to Tom Gregorovic for pointing that out. */ igraph_vector_ptr_destroy(&communities.e[from].neis); if (merges) { MATRIX(*merges, no_of_joins, 0) = communities.e[to].id; MATRIX(*merges, no_of_joins, 1) = communities.e[from].id; communities.e[to].id = (igraph_integer_t) (no_of_nodes + no_of_joins); } /* Update vector a */ VECTOR(a)[to] += VECTOR(a)[from]; VECTOR(a)[from] = 0.0; no_of_joins++; } /* TODO: continue merging when some isolated communities remained. Always * joining the communities with the least number of nodes results in the * smallest decrease in modularity every step. Now we're simply deleting * the excess rows from the merge matrix */ if (no_of_joins < total_joins) { long int *ivec; ivec = igraph_Calloc(igraph_matrix_nrow(merges), long int); if (ivec == 0) { IGRAPH_ERROR("can't run fast greedy community detection", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, ivec); for (i = 0; i < no_of_joins; i++) { ivec[i] = i + 1; } igraph_matrix_permdelete_rows(merges, ivec, total_joins - no_of_joins); free(ivec); IGRAPH_FINALLY_CLEAN(1); } IGRAPH_PROGRESS("fast greedy community detection", 100.0, 0); if (modularity) { VECTOR(*modularity)[no_of_joins] = q; igraph_vector_resize(modularity, no_of_joins + 1); } debug("Freeing memory\n"); free(pairs); free(dq); igraph_i_fastgreedy_community_list_destroy(&communities); igraph_vector_destroy(&a); IGRAPH_FINALLY_CLEAN(4); if (membership) { IGRAPH_CHECK(igraph_community_to_membership(merges, (igraph_integer_t) no_of_nodes, /*steps=*/ (igraph_integer_t) best_no_of_joins, membership, /*csize=*/ 0)); } if (merges == &merges_local) { igraph_matrix_destroy(&merges_local); IGRAPH_FINALLY_CLEAN(1); } return 0; } #ifdef IGRAPH_FASTCOMM_DEBUG #undef IGRAPH_FASTCOMM_DEBUG #endif python-igraph-0.8.0/vendor/source/igraph/src/foreign-gml-lexer.l0000644000076500000240000000601413524616145025106 0ustar tamasstaff00000000000000/* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ %{ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "config.h" #include #include "foreign-gml-header.h" #include "foreign-gml-parser.h" #define YY_EXTRA_TYPE igraph_i_gml_parsedata_t* #define YY_USER_ACTION yylloc->first_line = yylineno; /* We assume that 'file' is 'stderr' here. */ #ifdef USING_R #define fprintf(file, msg, ...) (1) #endif #ifdef stdout # undef stdout #endif #define stdout 0 #define exit(code) igraph_error("Fatal error in DL parser", __FILE__, \ __LINE__, IGRAPH_PARSEERROR); %} %option noyywrap %option prefix="igraph_gml_yy" %option outfile="lex.yy.c" %option nounput %option noinput %option nodefault %option reentrant %option bison-bridge %option bison-locations digit [0-9] whitespace [ \r\n\t] %% ^#[^\n\r]*[\n]|[\r] { /* comments ignored */ } \"[^\"]*\" { return STRING; } \-?{digit}+(\.{digit}+)?([eE](\+|\-)?{digit}+)? { return NUM; } [a-zA-Z_][a-zA-Z_0-9]* { return KEYWORD; } \[ { return LISTOPEN; } \] { return LISTCLOSE; } \n\r|\r\n|\r|\n { } {whitespace} { /* other whitespace ignored */ } <> { if (yyextra->eof) { yyterminate(); } else { yyextra->eof=1; return EOFF; } } . { return ERROR; } %% python-igraph-0.8.0/vendor/source/igraph/src/DensityGrid_3d.h0000644000076500000240000000542713614300625024372 0ustar tamasstaff00000000000000/* * Copyright 2007 Sandia Corporation. Under the terms of Contract * DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains * certain rights in this software. * * All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are * met: * * * Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * Neither the name of Sandia National Laboratories nor the names of * its contributors may be used to endorse or promote products derived from * this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT * OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED * TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF * LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING * NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. */ #ifndef __DENSITY_GRID_H__ #define __DENSITY_GRID_H__ // Compile time adjustable parameters #include using namespace std; #include "drl_layout_3d.h" #include "drl_Node_3d.h" #ifdef MUSE_MPI #include #endif namespace drl3d { class DensityGrid { public: // Methods void Init(); void Subtract(Node &n, bool first_add, bool fine_first_add, bool fineDensity); void Add(Node &n, bool fineDensity ); float GetDensity(float Nx, float Ny, float Nz, bool fineDensity); // Contructor/Destructor DensityGrid() {}; ~DensityGrid(); private: // Private Members void Subtract( Node &N ); void Add( Node &N ); void fineSubtract( Node &N ); void fineAdd( Node &N ); // new dynamic variables -- SBM float (*fall_off)[RADIUS * 2 + 1][RADIUS * 2 + 1]; float (*Density)[GRID_SIZE][GRID_SIZE]; deque* Bins; // old static variables //float fall_off[RADIUS*2+1][RADIUS*2+1]; //float Density[GRID_SIZE][GRID_SIZE]; //deque Bins[GRID_SIZE][GRID_SIZE]; }; } // namespace drl3d #endif // __DENSITY_GRID_H__ python-igraph-0.8.0/vendor/source/igraph/src/foreign-dl-parser.y0000644000076500000240000002240213524616145025117 0ustar tamasstaff00000000000000/* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ %{ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "config.h" #include "igraph_hacks_internal.h" #include "igraph_math.h" #include "igraph_types_internal.h" #include "foreign-dl-header.h" #include "foreign-dl-parser.h" #include #define yyscan_t void* int igraph_dl_yylex(YYSTYPE* lvalp, YYLTYPE* llocp, void* scanner); int igraph_dl_yyerror(YYLTYPE* locp, igraph_i_dl_parsedata_t* context, const char *s); char *igraph_dl_yyget_text (yyscan_t yyscanner ); int igraph_dl_yyget_leng (yyscan_t yyscanner ); int igraph_i_dl_add_str(char *newstr, int length, igraph_i_dl_parsedata_t *context); int igraph_i_dl_add_edge(long int from, long int to, igraph_i_dl_parsedata_t *context); int igraph_i_dl_add_edge_w(long int from, long int to, igraph_real_t weight, igraph_i_dl_parsedata_t *context); extern igraph_real_t igraph_pajek_get_number(const char *str, long int len); #define scanner context->scanner %} %pure-parser %output="y.tab.c" %name-prefix="igraph_dl_yy" %defines %locations %error-verbose %parse-param { igraph_i_dl_parsedata_t* context } %lex-param { void* scanner } %union { long int integer; igraph_real_t real; }; %type integer elabel; %type weight; %token NUM %token NEWLINE %token DL %token NEQ %token DATA %token LABELS %token LABELSEMBEDDED %token FORMATFULLMATRIX %token FORMATEDGELIST1 %token FORMATNODELIST1 %token DIGIT %token LABEL %token EOFF %token ERROR %% input: DL NEQ integer NEWLINE rest trail eof { context->n=$3; }; trail: | trail newline; eof: | EOFF; rest: formfullmatrix { context->type=IGRAPH_DL_MATRIX; } | edgelist1 { context->type=IGRAPH_DL_EDGELIST1; } | nodelist1 { context->type=IGRAPH_DL_NODELIST1; } ; formfullmatrix: FORMATFULLMATRIX newline fullmatrix {} | fullmatrix {} ; newline: | NEWLINE ; fullmatrix: DATA newline fullmatrixdata { } | LABELS newline labels newline DATA newline fullmatrixdata { } | LABELSEMBEDDED newline DATA newline labeledfullmatrixdata { } ; labels: {} /* nothing, empty matrix */ | labels newline LABEL { igraph_i_dl_add_str(igraph_dl_yyget_text(scanner), igraph_dl_yyget_leng(scanner), context); } ; fullmatrixdata: {} | fullmatrixdata zerooneseq NEWLINE { context->from += 1; context->to = 0; } ; zerooneseq: | zerooneseq zeroone { } ; zeroone: DIGIT { if (igraph_dl_yyget_text(scanner)[0]=='1') { IGRAPH_CHECK(igraph_vector_push_back(&context->edges, context->from)); IGRAPH_CHECK(igraph_vector_push_back(&context->edges, context->to)); } context->to += 1; } ; labeledfullmatrixdata: reallabeledfullmatrixdata {} ; reallabeledfullmatrixdata: labelseq NEWLINE labeledmatrixlines {} ; labelseq: | labelseq newline label ; label: LABEL { igraph_i_dl_add_str(igraph_dl_yyget_text(scanner), igraph_dl_yyget_leng(scanner), context); }; labeledmatrixlines: labeledmatrixline { context->from += 1; context->to = 0; } | labeledmatrixlines labeledmatrixline { context->from += 1; context->to = 0; }; labeledmatrixline: LABEL zerooneseq NEWLINE { } ; /*-----------------------------------------------------------*/ edgelist1: FORMATEDGELIST1 newline edgelist1rest {} ; edgelist1rest: DATA newline edgelist1data {} | LABELS newline labels newline DATA newline edgelist1data {} | LABELSEMBEDDED newline DATA newline labelededgelist1data {} | LABELS newline labels newline LABELSEMBEDDED newline DATA newline labelededgelist1data {} | LABELSEMBEDDED newline LABELS newline labels newline DATA newline labelededgelist1data {} ; edgelist1data: {} /* nothing, empty graph */ | edgelist1data edgelist1dataline {} ; edgelist1dataline: integer integer weight NEWLINE { igraph_i_dl_add_edge_w($1-1, $2-1, $3, context); } | integer integer NEWLINE { igraph_i_dl_add_edge($1-1, $2-1, context); } ; integer: NUM { $$=igraph_pajek_get_number(igraph_dl_yyget_text(scanner), igraph_dl_yyget_leng(scanner)); }; labelededgelist1data: {} /* nothing, empty graph */ | labelededgelist1data labelededgelist1dataline {} ; labelededgelist1dataline: elabel elabel weight NEWLINE { igraph_i_dl_add_edge_w($1, $2, $3, context); } | elabel elabel NEWLINE { igraph_i_dl_add_edge($1, $2, context); }; weight: NUM { $$=igraph_pajek_get_number(igraph_dl_yyget_text(scanner), igraph_dl_yyget_leng(scanner)); }; elabel: LABEL { /* Copy label list to trie, if needed */ if (igraph_strvector_size(&context->labels) != 0) { long int i, id, n=igraph_strvector_size(&context->labels); for (i=0; itrie, STR(context->labels, i), &id); } igraph_strvector_clear(&context->labels); } igraph_trie_get2(&context->trie, igraph_dl_yyget_text(scanner), igraph_dl_yyget_leng(scanner), &$$); }; /*-----------------------------------------------------------*/ nodelist1: FORMATNODELIST1 newline nodelist1rest {} ; nodelist1rest: DATA nodelist1data {} | LABELS newline labels newline DATA newline nodelist1data {} | LABELSEMBEDDED newline DATA newline labelednodelist1data {} | LABELS newline labels newline LABELSEMBEDDED newline DATA newline labelednodelist1data {} | LABELSEMBEDDED newline LABELS newline labels newline DATA newline labelednodelist1data {} ; nodelist1data: {} /* nothing, empty graph */ | nodelist1data nodelist1dataline {} ; nodelist1dataline: from tolist NEWLINE {} ; from: NUM { context->from=igraph_pajek_get_number(igraph_dl_yyget_text(scanner), igraph_dl_yyget_leng(scanner)); } ; tolist: {} | tolist integer { IGRAPH_CHECK(igraph_vector_push_back(&context->edges, context->from-1)); IGRAPH_CHECK(igraph_vector_push_back(&context->edges, $2-1)); } ; labelednodelist1data: {} /* nothing, empty graph */ | labelednodelist1data labelednodelist1dataline {} ; labelednodelist1dataline: fromelabel labeltolist NEWLINE { } ; fromelabel: elabel { context->from=$1; }; labeltolist: | labeltolist elabel { IGRAPH_CHECK(igraph_vector_push_back(&context->edges, context->from)); IGRAPH_CHECK(igraph_vector_push_back(&context->edges, $2)); } ; %% int igraph_dl_yyerror(YYLTYPE* locp, igraph_i_dl_parsedata_t* context, const char *s) { snprintf(context->errmsg, sizeof(context->errmsg)/sizeof(char)-1, "%s in line %i", s, locp->first_line); return 0; } int igraph_i_dl_add_str(char *newstr, int length, igraph_i_dl_parsedata_t *context) { int tmp=newstr[length]; newstr[length]='\0'; IGRAPH_CHECK(igraph_strvector_add(&context->labels, newstr)); newstr[length]=tmp; return 0; } int igraph_i_dl_add_edge(long int from, long int to, igraph_i_dl_parsedata_t *context) { IGRAPH_CHECK(igraph_vector_push_back(&context->edges, from)); IGRAPH_CHECK(igraph_vector_push_back(&context->edges, to)); return 0; } int igraph_i_dl_add_edge_w(long int from, long int to, igraph_real_t weight, igraph_i_dl_parsedata_t *context) { long int n=igraph_vector_size(&context->weights); long int n2=igraph_vector_size(&context->edges)/2; if (n != n2) { igraph_vector_resize(&context->weights, n2); for (; nweights)[n]=IGRAPH_NAN; } } IGRAPH_CHECK(igraph_i_dl_add_edge(from, to, context)); IGRAPH_CHECK(igraph_vector_push_back(&context->weights, weight)); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/layout.c0000644000076500000240000026614713614300625023077 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph R package. Copyright (C) 2003-2014 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_layout.h" #include "igraph_random.h" #include "igraph_memory.h" #include "igraph_iterators.h" #include "igraph_interface.h" #include "igraph_adjlist.h" #include "igraph_progress.h" #include "igraph_interrupt_internal.h" #include "igraph_paths.h" #include "igraph_structural.h" #include "igraph_visitor.h" #include "igraph_topology.h" #include "igraph_components.h" #include "igraph_types_internal.h" #include "igraph_dqueue.h" #include "igraph_arpack.h" #include "igraph_blas.h" #include "igraph_centrality.h" #include "igraph_eigen.h" #include "config.h" #include #include "igraph_math.h" #include /* FIXME */ /** * \section about_layouts * * Layout generator functions (or at least most of them) try to place the * vertices and edges of a graph on a 2D plane or in 3D space in a way * which visually pleases the human eye. * * They take a graph object and a number of parameters as arguments * and return an \type igraph_matrix_t, in which each row gives the * coordinates of a vertex. */ /** * \ingroup layout * \function igraph_layout_random * \brief Places the vertices uniform randomly on a plane. * * \param graph Pointer to an initialized graph object. * \param res Pointer to an initialized matrix object. This will * contain the result and will be resized as needed. * \return Error code. The current implementation always returns with * success. * * Time complexity: O(|V|), the * number of vertices. */ int igraph_layout_random(const igraph_t *graph, igraph_matrix_t *res) { long int no_of_nodes = igraph_vcount(graph); long int i; IGRAPH_CHECK(igraph_matrix_resize(res, no_of_nodes, 2)); RNG_BEGIN(); for (i = 0; i < no_of_nodes; i++) { MATRIX(*res, i, 0) = RNG_UNIF(-1, 1); MATRIX(*res, i, 1) = RNG_UNIF(-1, 1); } RNG_END(); return 0; } /** * \function igraph_layout_random_3d * \brief Random layout in 3D * * \param graph The graph to place. * \param res Pointer to an initialized matrix object. It will be * resized to hold the result. * \return Error code. The current implementation always returns with * success. * * Added in version 0.2. * * Time complexity: O(|V|), the number of vertices. */ int igraph_layout_random_3d(const igraph_t *graph, igraph_matrix_t *res) { long int no_of_nodes = igraph_vcount(graph); long int i; IGRAPH_CHECK(igraph_matrix_resize(res, no_of_nodes, 3)); RNG_BEGIN(); for (i = 0; i < no_of_nodes; i++) { MATRIX(*res, i, 0) = RNG_UNIF(-1, 1); MATRIX(*res, i, 1) = RNG_UNIF(-1, 1); MATRIX(*res, i, 2) = RNG_UNIF(-1, 1); } RNG_END(); return 0; } /** * \ingroup layout * \function igraph_layout_circle * \brief Places the vertices uniformly on a circle, in the order of vertex ids. * * \param graph Pointer to an initialized graph object. * \param res Pointer to an initialized matrix object. This will * contain the result and will be resized as needed. * \param order The order of the vertices on the circle. The vertices * not included here, will be placed at (0,0). Supply * \ref igraph_vss_all() here for all vertices, in the order of * their vertex ids. * \return Error code. * * Time complexity: O(|V|), the * number of vertices. */ int igraph_layout_circle(const igraph_t *graph, igraph_matrix_t *res, igraph_vs_t order) { long int no_of_nodes = igraph_vcount(graph); igraph_integer_t vs_size; long int i; igraph_vit_t vit; IGRAPH_CHECK(igraph_vs_size(graph, &order, &vs_size)); IGRAPH_CHECK(igraph_matrix_resize(res, no_of_nodes, 2)); igraph_matrix_null(res); igraph_vit_create(graph, order, &vit); for (i = 0; !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit), i++) { igraph_real_t phi = 2 * M_PI / vs_size * i; int idx = IGRAPH_VIT_GET(vit); MATRIX(*res, idx, 0) = cos(phi); MATRIX(*res, idx, 1) = sin(phi); } igraph_vit_destroy(&vit); return 0; } /** * \function igraph_layout_star * Generate a star-like layout * * \param graph The input graph. * \param res Pointer to an initialized matrix object. This will * contain the result and will be resized as needed. * \param center The id of the vertex to put in the center. * \param order A numeric vector giving the order of the vertices * (including the center vertex!). If a null pointer, then the * vertices are placed in increasing vertex id order. * \return Error code. * * Time complexity: O(|V|), linear in the number of vertices. * * \sa \ref igraph_layout_circle() and other layout generators. */ int igraph_layout_star(const igraph_t *graph, igraph_matrix_t *res, igraph_integer_t center, const igraph_vector_t *order) { long int no_of_nodes = igraph_vcount(graph); long int c = center; long int i; igraph_real_t step; igraph_real_t phi; if (order && igraph_vector_size(order) != no_of_nodes) { IGRAPH_ERROR("Invalid order vector length", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_matrix_resize(res, no_of_nodes, 2)); if (no_of_nodes == 1) { MATRIX(*res, 0, 0) = MATRIX(*res, 0, 1) = 0.0; } else { for (i = 0, step = 2 * M_PI / (no_of_nodes - 1), phi = 0; i < no_of_nodes; i++) { long int node = order ? (long int) VECTOR(*order)[i] : i; if (node != c) { MATRIX(*res, node, 0) = cos(phi); MATRIX(*res, node, 1) = sin(phi); phi += step; } else { MATRIX(*res, node, 0) = MATRIX(*res, node, 1) = 0.0; } } } return 0; } /** * \function igraph_layout_sphere * \brief Places vertices (more or less) uniformly on a sphere. * * * The algorithm was described in the following paper: * Distributing many points on a sphere by E.B. Saff and * A.B.J. Kuijlaars, \emb Mathematical Intelligencer \eme 19.1 (1997) * 5--11. * * \param graph Pointer to an initialized graph object. * \param res Pointer to an initialized matrix object. This will * contain the result and will be resized as needed. * \return Error code. The current implementation always returns with * success. * * Added in version 0.2. * * Time complexity: O(|V|), the number of vertices in the graph. */ int igraph_layout_sphere(const igraph_t *graph, igraph_matrix_t *res) { long int no_of_nodes = igraph_vcount(graph); long int i; igraph_real_t h; IGRAPH_CHECK(igraph_matrix_resize(res, no_of_nodes, 3)); if (no_of_nodes != 0) { MATRIX(*res, 0, 0) = M_PI; MATRIX(*res, 0, 1) = 0; } for (i = 1; i < no_of_nodes - 1; i++) { h = -1 + 2 * i / (double)(no_of_nodes - 1); MATRIX(*res, i, 0) = acos(h); MATRIX(*res, i, 1) = fmod((MATRIX(*res, i - 1, 1) + 3.6 / sqrt(no_of_nodes * (1 - h * h))), 2 * M_PI); IGRAPH_ALLOW_INTERRUPTION(); } if (no_of_nodes >= 2) { MATRIX(*res, no_of_nodes - 1, 0) = 0; MATRIX(*res, no_of_nodes - 1, 1) = 0; } for (i = 0; i < no_of_nodes; i++) { igraph_real_t x = cos(MATRIX(*res, i, 1)) * sin(MATRIX(*res, i, 0)); igraph_real_t y = sin(MATRIX(*res, i, 1)) * sin(MATRIX(*res, i, 0)); igraph_real_t z = cos(MATRIX(*res, i, 0)); MATRIX(*res, i, 0) = x; MATRIX(*res, i, 1) = y; MATRIX(*res, i, 2) = z; IGRAPH_ALLOW_INTERRUPTION(); } return 0; } /** * \ingroup layout * \function igraph_layout_grid * \brief Places the vertices on a regular grid on the plane. * * \param graph Pointer to an initialized graph object. * \param res Pointer to an initialized matrix object. This will * contain the result and will be resized as needed. * \param width The number of vertices in a single row of the grid. * When zero or negative, the width of the grid will be the * square root of the number of vertices, rounded up if needed. * \return Error code. The current implementation always returns with * success. * * Time complexity: O(|V|), the number of vertices. */ int igraph_layout_grid(const igraph_t *graph, igraph_matrix_t *res, long int width) { long int i, no_of_nodes = igraph_vcount(graph); igraph_real_t x, y; IGRAPH_CHECK(igraph_matrix_resize(res, no_of_nodes, 2)); if (width <= 0) { width = (long int) ceil(sqrt(no_of_nodes)); } x = y = 0; for (i = 0; i < no_of_nodes; i++) { MATRIX(*res, i, 0) = x++; MATRIX(*res, i, 1) = y; if (x == width) { x = 0; y++; } } return 0; } /** * \ingroup layout * \function igraph_layout_grid_3d * \brief Places the vertices on a regular grid in the 3D space. * * \param graph Pointer to an initialized graph object. * \param res Pointer to an initialized matrix object. This will * contain the result and will be resized as needed. * \param width The number of vertices in a single row of the grid. When * zero or negative, the width is determined automatically. * \param height The number of vertices in a single column of the grid. When * zero or negative, the height is determined automatically. * * \return Error code. The current implementation always returns with * success. * * Time complexity: O(|V|), the number of vertices. */ int igraph_layout_grid_3d(const igraph_t *graph, igraph_matrix_t *res, long int width, long int height) { long int i, no_of_nodes = igraph_vcount(graph); igraph_real_t x, y, z; IGRAPH_CHECK(igraph_matrix_resize(res, no_of_nodes, 3)); if (width <= 0 && height <= 0) { width = height = (long int) ceil(pow(no_of_nodes, 1.0 / 3)); } else if (width <= 0) { width = (long int) ceil(sqrt(no_of_nodes / (double)height)); } else if (height <= 0) { height = (long int) ceil(sqrt(no_of_nodes / (double)width)); } x = y = z = 0; for (i = 0; i < no_of_nodes; i++) { MATRIX(*res, i, 0) = x++; MATRIX(*res, i, 1) = y; MATRIX(*res, i, 2) = z; if (x == width) { x = 0; y++; if (y == height) { y = 0; z++; } } } return 0; } int igraph_layout_springs(const igraph_t *graph, igraph_matrix_t *res, igraph_real_t mass, igraph_real_t equil, igraph_real_t k, igraph_real_t repeqdis, igraph_real_t kfr, igraph_bool_t repulse) { IGRAPH_UNUSED(graph); IGRAPH_UNUSED(res); IGRAPH_UNUSED(mass); IGRAPH_UNUSED(equil); IGRAPH_UNUSED(k); IGRAPH_UNUSED(repeqdis); IGRAPH_UNUSED(kfr); IGRAPH_UNUSED(repulse); IGRAPH_ERROR("Springs layout not implemented", IGRAPH_UNIMPLEMENTED); /* TODO */ return 0; } void igraph_i_norm2d(igraph_real_t *x, igraph_real_t *y); void igraph_i_norm2d(igraph_real_t *x, igraph_real_t *y) { igraph_real_t len = sqrt((*x) * (*x) + (*y) * (*y)); if (len != 0) { *x /= len; *y /= len; } } /** * \function igraph_layout_lgl * \brief Force based layout algorithm for large graphs. * * * This is a layout generator similar to the Large Graph Layout * algorithm and program * (http://lgl.sourceforge.net/). But unlike LGL, this * version uses a Fruchterman-Reingold style simulated annealing * algorithm for placing the vertices. The speedup is achieved by * placing the vertices on a grid and calculating the repulsion only * for vertices which are closer to each other than a limit. * * \param graph The (initialized) graph object to place. * \param res Pointer to an initialized matrix object to hold the * result. It will be resized if needed. * \param maxit The maximum number of cooling iterations to perform * for each layout step. A reasonable default is 150. * \param maxdelta The maximum length of the move allowed for a vertex * in a single iteration. A reasonable default is the number of * vertices. * \param area This parameter gives the area of the square on which * the vertices will be placed. A reasonable default value is the * number of vertices squared. * \param coolexp The cooling exponent. A reasonable default value is * 1.5. * \param repulserad Determines the radius at which vertex-vertex * repulsion cancels out attraction of adjacent vertices. A * reasonable default value is \p area times the number of vertices. * \param cellsize The size of the grid cells, one side of the * square. A reasonable default value is the fourth root of * \p area (or the square root of the number of vertices if \p area * is also left at its default value). * \param proot The root vertex, this is placed first, its neighbors * in the first iteration, second neighbors in the second, etc. If * negative then a random vertex is chosen. * \return Error code. * * Added in version 0.2. * * Time complexity: ideally O(dia*maxit*(|V|+|E|)), |V| is the number * of vertices, * dia is the diameter of the graph, worst case complexity is still * O(dia*maxit*(|V|^2+|E|)), this is the case when all vertices happen to be * in the same grid cell. */ int igraph_layout_lgl(const igraph_t *graph, igraph_matrix_t *res, igraph_integer_t maxit, igraph_real_t maxdelta, igraph_real_t area, igraph_real_t coolexp, igraph_real_t repulserad, igraph_real_t cellsize, igraph_integer_t proot) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_t mst; long int root; long int no_of_layers, actlayer = 0; igraph_vector_t vids; igraph_vector_t layers; igraph_vector_t parents; igraph_vector_t edges; igraph_2dgrid_t grid; igraph_vector_t eids; igraph_vector_t forcex; igraph_vector_t forcey; igraph_real_t frk = sqrt(area / no_of_nodes); igraph_real_t H_n = 0; IGRAPH_CHECK(igraph_minimum_spanning_tree_unweighted(graph, &mst)); IGRAPH_FINALLY(igraph_destroy, &mst); IGRAPH_CHECK(igraph_matrix_resize(res, no_of_nodes, 2)); /* Determine the root vertex, random pick right now */ if (proot < 0) { root = RNG_INTEGER(0, no_of_nodes - 1); } else { root = proot; } /* Assign the layers */ IGRAPH_VECTOR_INIT_FINALLY(&vids, 0); IGRAPH_VECTOR_INIT_FINALLY(&layers, 0); IGRAPH_VECTOR_INIT_FINALLY(&parents, 0); IGRAPH_CHECK(igraph_i_bfs(&mst, (igraph_integer_t) root, IGRAPH_ALL, &vids, &layers, &parents)); no_of_layers = igraph_vector_size(&layers) - 1; /* We don't need the mst any more */ igraph_destroy(&mst); igraph_empty(&mst, 0, IGRAPH_UNDIRECTED); /* to make finalization work */ IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_CHECK(igraph_vector_reserve(&edges, no_of_edges)); IGRAPH_VECTOR_INIT_FINALLY(&eids, 0); IGRAPH_VECTOR_INIT_FINALLY(&forcex, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&forcey, no_of_nodes); /* Place the vertices randomly */ IGRAPH_CHECK(igraph_layout_random(graph, res)); igraph_matrix_scale(res, 1e6); /* This is the grid for calculating the vertices near to a given vertex */ IGRAPH_CHECK(igraph_2dgrid_init(&grid, res, -sqrt(area / M_PI), sqrt(area / M_PI), cellsize, -sqrt(area / M_PI), sqrt(area / M_PI), cellsize)); IGRAPH_FINALLY(igraph_2dgrid_destroy, &grid); /* Place the root vertex */ igraph_2dgrid_add(&grid, root, 0, 0); for (actlayer = 1; actlayer < no_of_layers; actlayer++) { H_n += 1.0 / actlayer; } for (actlayer = 1; actlayer < no_of_layers; actlayer++) { igraph_real_t c = 1; long int i, j; igraph_real_t massx, massy; igraph_real_t px, py; igraph_real_t sx, sy; long int it = 0; igraph_real_t epsilon = 10e-6; igraph_real_t maxchange = epsilon + 1; long int pairs; igraph_real_t sconst = sqrt(area / M_PI) / H_n; igraph_2dgrid_iterator_t vidit; /* printf("Layer %li:\n", actlayer); */ /*-----------------------------------------*/ /* Step 1: place the next layer on spheres */ /*-----------------------------------------*/ RNG_BEGIN(); j = (long int) VECTOR(layers)[actlayer]; for (i = (long int) VECTOR(layers)[actlayer - 1]; i < VECTOR(layers)[actlayer]; i++) { long int vid = (long int) VECTOR(vids)[i]; long int par = (long int) VECTOR(parents)[vid]; IGRAPH_ALLOW_INTERRUPTION(); igraph_2dgrid_getcenter(&grid, &massx, &massy); igraph_i_norm2d(&massx, &massy); px = MATRIX(*res, vid, 0) - MATRIX(*res, par, 0); py = MATRIX(*res, vid, 1) - MATRIX(*res, par, 1); igraph_i_norm2d(&px, &py); sx = c * (massx + px) + MATRIX(*res, vid, 0); sy = c * (massy + py) + MATRIX(*res, vid, 1); /* The neighbors of 'vid' */ while (j < VECTOR(layers)[actlayer + 1] && VECTOR(parents)[(long int)VECTOR(vids)[j]] == vid) { igraph_real_t rx, ry; if (actlayer == 1) { igraph_real_t phi = 2 * M_PI / (VECTOR(layers)[2] - 1) * (j - 1); rx = cos(phi); ry = sin(phi); } else { rx = RNG_UNIF(-1, 1); ry = RNG_UNIF(-1, 1); } igraph_i_norm2d(&rx, &ry); rx = rx / actlayer * sconst; ry = ry / actlayer * sconst; igraph_2dgrid_add(&grid, (long int) VECTOR(vids)[j], sx + rx, sy + ry); j++; } } RNG_END(); /*-----------------------------------------*/ /* Step 2: add the edges of the next layer */ /*-----------------------------------------*/ for (j = (long int) VECTOR(layers)[actlayer]; j < VECTOR(layers)[actlayer + 1]; j++) { long int vid = (long int) VECTOR(vids)[j]; long int k; IGRAPH_ALLOW_INTERRUPTION(); IGRAPH_CHECK(igraph_incident(graph, &eids, (igraph_integer_t) vid, IGRAPH_ALL)); for (k = 0; k < igraph_vector_size(&eids); k++) { long int eid = (long int) VECTOR(eids)[k]; igraph_integer_t from, to; igraph_edge(graph, (igraph_integer_t) eid, &from, &to); if ((from != vid && igraph_2dgrid_in(&grid, from)) || (to != vid && igraph_2dgrid_in(&grid, to))) { igraph_vector_push_back(&edges, eid); } } } /*-----------------------------------------*/ /* Step 3: let the springs spring */ /*-----------------------------------------*/ maxchange = epsilon + 1; while (it < maxit && maxchange > epsilon) { long int jj; igraph_real_t t = maxdelta * pow((maxit - it) / (double)maxit, coolexp); long int vid, nei; IGRAPH_PROGRESS("Large graph layout", 100.0 * ((actlayer - 1.0) / (no_of_layers - 1.0) + ((float)it) / (maxit * (no_of_layers - 1.0))), 0); /* init */ igraph_vector_null(&forcex); igraph_vector_null(&forcey); maxchange = 0; /* attractive "forces" along the edges */ for (jj = 0; jj < igraph_vector_size(&edges); jj++) { igraph_integer_t from, to; igraph_real_t xd, yd, dist, force; IGRAPH_ALLOW_INTERRUPTION(); igraph_edge(graph, (igraph_integer_t) VECTOR(edges)[jj], &from, &to); xd = MATRIX(*res, (long int)from, 0) - MATRIX(*res, (long int)to, 0); yd = MATRIX(*res, (long int)from, 1) - MATRIX(*res, (long int)to, 1); dist = sqrt(xd * xd + yd * yd); if (dist != 0) { xd /= dist; yd /= dist; } force = dist * dist / frk; VECTOR(forcex)[(long int)from] -= xd * force; VECTOR(forcex)[(long int)to] += xd * force; VECTOR(forcey)[(long int)from] -= yd * force; VECTOR(forcey)[(long int)to] += yd * force; } /* repulsive "forces" of the vertices nearby */ pairs = 0; igraph_2dgrid_reset(&grid, &vidit); while ( (vid = igraph_2dgrid_next(&grid, &vidit) - 1) != -1) { while ( (nei = igraph_2dgrid_next_nei(&grid, &vidit) - 1) != -1) { igraph_real_t xd = MATRIX(*res, (long int)vid, 0) - MATRIX(*res, (long int)nei, 0); igraph_real_t yd = MATRIX(*res, (long int)vid, 1) - MATRIX(*res, (long int)nei, 1); igraph_real_t dist = sqrt(xd * xd + yd * yd); igraph_real_t force; if (dist < cellsize) { pairs++; if (dist == 0) { dist = epsilon; }; xd /= dist; yd /= dist; force = frk * frk * (1.0 / dist - dist * dist / repulserad); VECTOR(forcex)[(long int)vid] += xd * force; VECTOR(forcex)[(long int)nei] -= xd * force; VECTOR(forcey)[(long int)vid] += yd * force; VECTOR(forcey)[(long int)nei] -= yd * force; } } } /* printf("verties: %li iterations: %li\n", */ /* (long int) VECTOR(layers)[actlayer+1], pairs); */ /* apply the changes */ for (jj = 0; jj < VECTOR(layers)[actlayer + 1]; jj++) { long int vvid = (long int) VECTOR(vids)[jj]; igraph_real_t fx = VECTOR(forcex)[vvid]; igraph_real_t fy = VECTOR(forcey)[vvid]; igraph_real_t ded = sqrt(fx * fx + fy * fy); if (ded > t) { ded = t / ded; fx *= ded; fy *= ded; } igraph_2dgrid_move(&grid, vvid, fx, fy); if (fx > maxchange) { maxchange = fx; } if (fy > maxchange) { maxchange = fy; } } it++; /* printf("%li iterations, maxchange: %f\n", it, (double)maxchange); */ } } IGRAPH_PROGRESS("Large graph layout", 100.0, 0); igraph_destroy(&mst); igraph_vector_destroy(&vids); igraph_vector_destroy(&layers); igraph_vector_destroy(&parents); igraph_vector_destroy(&edges); igraph_2dgrid_destroy(&grid); igraph_vector_destroy(&eids); igraph_vector_destroy(&forcex); igraph_vector_destroy(&forcey); IGRAPH_FINALLY_CLEAN(9); return 0; } int igraph_i_layout_reingold_tilford_unreachable( const igraph_t *graph, igraph_neimode_t mode, long int real_root, long int no_of_nodes, igraph_vector_t *pnewedges); int igraph_i_layout_reingold_tilford_unreachable( const igraph_t *graph, igraph_neimode_t mode, long int real_root, long int no_of_nodes, igraph_vector_t *pnewedges) { long int no_of_newedges; igraph_vector_t visited; long int i, j, n; igraph_dqueue_t q = IGRAPH_DQUEUE_NULL; igraph_adjlist_t allneis; igraph_vector_int_t *neis; igraph_vector_resize(pnewedges, 0); /* traverse from real_root and see what nodes you cannot reach */ no_of_newedges = 0; IGRAPH_VECTOR_INIT_FINALLY(&visited, no_of_nodes); IGRAPH_DQUEUE_INIT_FINALLY(&q, 100); IGRAPH_CHECK(igraph_adjlist_init(graph, &allneis, mode)); IGRAPH_FINALLY(igraph_adjlist_destroy, &allneis); /* start from real_root and go BFS */ IGRAPH_CHECK(igraph_dqueue_push(&q, real_root)); while (!igraph_dqueue_empty(&q)) { long int actnode = (long int) igraph_dqueue_pop(&q); neis = igraph_adjlist_get(&allneis, actnode); n = igraph_vector_int_size(neis); VECTOR(visited)[actnode] = 1; for (j = 0; j < n; j++) { long int neighbor = (long int) VECTOR(*neis)[j]; if (!(long int)VECTOR(visited)[neighbor]) { IGRAPH_CHECK(igraph_dqueue_push(&q, neighbor)); } } } for (j = 0; j < no_of_nodes; j++) { no_of_newedges += 1 - VECTOR(visited)[j]; } /* if any nodes are unreachable, add edges between them and real_root */ if (no_of_newedges != 0) { igraph_vector_resize(pnewedges, no_of_newedges * 2); j = 0; for (i = 0; i < no_of_nodes; i++) { if (!VECTOR(visited)[i]) { if (mode != IGRAPH_IN) { VECTOR(*pnewedges)[2 * j] = real_root; VECTOR(*pnewedges)[2 * j + 1] = i; } else { VECTOR(*pnewedges)[2 * j] = i; VECTOR(*pnewedges)[2 * j + 1] = real_root; } j++; } } } igraph_dqueue_destroy(&q); igraph_adjlist_destroy(&allneis); igraph_vector_destroy(&visited); IGRAPH_FINALLY_CLEAN(3); return IGRAPH_SUCCESS; } /* Internal structure for Reingold-Tilford layout */ struct igraph_i_reingold_tilford_vertex { long int parent; /* Parent node index */ long int level; /* Level of the node */ igraph_real_t offset; /* X offset from parent node */ long int left_contour; /* Next left node of the contour of the subtree rooted at this node */ long int right_contour; /* Next right node of the contour of the subtree rooted at this node */ igraph_real_t offset_follow_lc; /* X offset when following the left contour */ igraph_real_t offset_follow_rc; /* X offset when following the right contour */ }; int igraph_i_layout_reingold_tilford_postorder(struct igraph_i_reingold_tilford_vertex *vdata, long int node, long int vcount); int igraph_i_layout_reingold_tilford_calc_coords(struct igraph_i_reingold_tilford_vertex *vdata, igraph_matrix_t *res, long int node, long int vcount, igraph_real_t xpos); int igraph_i_layout_reingold_tilford(const igraph_t *graph, igraph_matrix_t *res, igraph_neimode_t mode, long int root); int igraph_i_layout_reingold_tilford(const igraph_t *graph, igraph_matrix_t *res, igraph_neimode_t mode, long int root) { long int no_of_nodes = igraph_vcount(graph); long int i, n, j; igraph_dqueue_t q = IGRAPH_DQUEUE_NULL; igraph_adjlist_t allneis; igraph_vector_int_t *neis; struct igraph_i_reingold_tilford_vertex *vdata; IGRAPH_CHECK(igraph_matrix_resize(res, no_of_nodes, 2)); IGRAPH_DQUEUE_INIT_FINALLY(&q, 100); IGRAPH_CHECK(igraph_adjlist_init(graph, &allneis, mode)); IGRAPH_FINALLY(igraph_adjlist_destroy, &allneis); vdata = igraph_Calloc(no_of_nodes, struct igraph_i_reingold_tilford_vertex); if (vdata == 0) { IGRAPH_ERROR("igraph_layout_reingold_tilford failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, vdata); for (i = 0; i < no_of_nodes; i++) { vdata[i].parent = -1; vdata[i].level = -1; vdata[i].offset = 0.0; vdata[i].left_contour = -1; vdata[i].right_contour = -1; vdata[i].offset_follow_lc = 0.0; vdata[i].offset_follow_rc = 0.0; } vdata[root].parent = root; vdata[root].level = 0; MATRIX(*res, root, 1) = 0; /* Step 1: assign Y coordinates based on BFS and setup parents vector */ IGRAPH_CHECK(igraph_dqueue_push(&q, root)); IGRAPH_CHECK(igraph_dqueue_push(&q, 0)); while (!igraph_dqueue_empty(&q)) { long int actnode = (long int) igraph_dqueue_pop(&q); long int actdist = (long int) igraph_dqueue_pop(&q); neis = igraph_adjlist_get(&allneis, actnode); n = igraph_vector_int_size(neis); for (j = 0; j < n; j++) { long int neighbor = (long int) VECTOR(*neis)[j]; if (vdata[neighbor].parent >= 0) { continue; } MATRIX(*res, neighbor, 1) = actdist + 1; IGRAPH_CHECK(igraph_dqueue_push(&q, neighbor)); IGRAPH_CHECK(igraph_dqueue_push(&q, actdist + 1)); vdata[neighbor].parent = actnode; vdata[neighbor].level = actdist + 1; } } /* Step 2: postorder tree traversal, determines the appropriate X * offsets for every node */ igraph_i_layout_reingold_tilford_postorder(vdata, root, no_of_nodes); /* Step 3: calculate real coordinates based on X offsets */ igraph_i_layout_reingold_tilford_calc_coords(vdata, res, root, no_of_nodes, vdata[root].offset); igraph_dqueue_destroy(&q); igraph_adjlist_destroy(&allneis); igraph_free(vdata); IGRAPH_FINALLY_CLEAN(3); IGRAPH_PROGRESS("Reingold-Tilford tree layout", 100.0, NULL); return 0; } int igraph_i_layout_reingold_tilford_calc_coords(struct igraph_i_reingold_tilford_vertex *vdata, igraph_matrix_t *res, long int node, long int vcount, igraph_real_t xpos) { long int i; MATRIX(*res, node, 0) = xpos; for (i = 0; i < vcount; i++) { if (i == node) { continue; } if (vdata[i].parent == node) { igraph_i_layout_reingold_tilford_calc_coords(vdata, res, i, vcount, xpos + vdata[i].offset); } } return 0; } int igraph_i_layout_reingold_tilford_postorder(struct igraph_i_reingold_tilford_vertex *vdata, long int node, long int vcount) { long int i, j, childcount, leftroot, leftrootidx; igraph_real_t avg; /* printf("Starting visiting node %d\n", node); */ /* Check whether this node is a leaf node */ childcount = 0; for (i = 0; i < vcount; i++) { if (i == node) { continue; } if (vdata[i].parent == node) { /* Node i is a child, so visit it recursively */ childcount++; igraph_i_layout_reingold_tilford_postorder(vdata, i, vcount); } } if (childcount == 0) { return 0; } /* Here we can assume that all of the subtrees have been placed and their * left and right contours are calculated. Let's place them next to each * other as close as we can. * We will take each subtree in an arbitrary order. The root of the * first one will be placed at offset 0, the next ones will be placed * as close to each other as possible. leftroot stores the root of the * rightmost subtree of the already placed subtrees - its right contour * will be checked against the left contour of the next subtree */ leftroot = leftrootidx = -1; avg = 0.0; /*printf("Visited node %d and arranged its subtrees\n", node);*/ for (i = 0, j = 0; i < vcount; i++) { if (i == node) { continue; } if (vdata[i].parent == node) { /*printf(" Placing child %d on level %d\n", i, vdata[i].level);*/ if (leftroot >= 0) { /* Now we will follow the right contour of leftroot and the * left contour of the subtree rooted at i */ long lnode, rnode; igraph_real_t loffset, roffset, minsep, rootsep; lnode = leftroot; rnode = i; minsep = 1; rootsep = vdata[leftroot].offset + minsep; loffset = 0; roffset = minsep; /*printf(" Contour: [%d, %d], offsets: [%lf, %lf], rootsep: %lf\n", lnode, rnode, loffset, roffset, rootsep);*/ while ((lnode >= 0) && (rnode >= 0)) { /* Step to the next level on the right contour of the left subtree */ if (vdata[lnode].right_contour >= 0) { loffset += vdata[lnode].offset_follow_rc; lnode = vdata[lnode].right_contour; } else { /* Left subtree ended there. The right contour of the left subtree * will continue to the next step on the right subtree. */ if (vdata[rnode].left_contour >= 0) { /*printf(" Left subtree ended, continuing left subtree's left and right contour on right subtree (node %ld)\n", vdata[rnode].left_contour);*/ vdata[lnode].left_contour = vdata[rnode].left_contour; vdata[lnode].right_contour = vdata[rnode].left_contour; vdata[lnode].offset_follow_lc = vdata[lnode].offset_follow_rc = (roffset - loffset) + vdata[rnode].offset_follow_lc; /*printf(" vdata[lnode].offset_follow_* = %.4f\n", vdata[lnode].offset_follow_lc);*/ } lnode = -1; } /* Step to the next level on the left contour of the right subtree */ if (vdata[rnode].left_contour >= 0) { roffset += vdata[rnode].offset_follow_lc; rnode = vdata[rnode].left_contour; } else { /* Right subtree ended here. The left contour of the right * subtree will continue to the next step on the left subtree. * Note that lnode has already been advanced here */ if (lnode >= 0) { /*printf(" Right subtree ended, continuing right subtree's left and right contour on left subtree (node %ld)\n", lnode);*/ vdata[rnode].left_contour = lnode; vdata[rnode].right_contour = lnode; vdata[rnode].offset_follow_lc = vdata[rnode].offset_follow_rc = (loffset - roffset); /* loffset has also been increased earlier */ /*printf(" vdata[rnode].offset_follow_* = %.4f\n", vdata[rnode].offset_follow_lc);*/ } rnode = -1; } /*printf(" Contour: [%d, %d], offsets: [%lf, %lf], rootsep: %lf\n", lnode, rnode, loffset, roffset, rootsep);*/ /* Push subtrees away if necessary */ if ((lnode >= 0) && (rnode >= 0) && (roffset - loffset < minsep)) { /*printf(" Pushing right subtree away by %lf\n", minsep-roffset+loffset);*/ rootsep += minsep - roffset + loffset; roffset = loffset + minsep; } } /*printf(" Offset of subtree with root node %d will be %lf\n", i, rootsep);*/ vdata[i].offset = rootsep; vdata[node].right_contour = i; vdata[node].offset_follow_rc = rootsep; avg = (avg * j) / (j + 1) + rootsep / (j + 1); leftrootidx = j; leftroot = i; } else { leftrootidx = j; leftroot = i; vdata[node].left_contour = i; vdata[node].right_contour = i; vdata[node].offset_follow_lc = 0.0; vdata[node].offset_follow_rc = 0.0; avg = vdata[i].offset; } j++; } } /*printf("Shifting node to be centered above children. Shift amount: %lf\n", avg);*/ vdata[node].offset_follow_lc -= avg; vdata[node].offset_follow_rc -= avg; for (i = 0, j = 0; i < vcount; i++) { if (i == node) { continue; } if (vdata[i].parent == node) { vdata[i].offset -= avg; } } return 0; } /** * \function igraph_layout_reingold_tilford * \brief Reingold-Tilford layout for tree graphs * * * Arranges the nodes in a tree where the given node is used as the root. * The tree is directed downwards and the parents are centered above its * children. For the exact algorithm, see: * * * Reingold, E and Tilford, J: Tidier drawing of trees. * IEEE Trans. Softw. Eng., SE-7(2):223--228, 1981 * * * If the given graph is not a tree, a breadth-first search is executed * first to obtain a possible spanning tree. * * \param graph The graph object. * \param res The result, the coordinates in a matrix. The parameter * should point to an initialized matrix object and will be resized. * \param mode Specifies which edges to consider when building the tree. * If it is \c IGRAPH_OUT then only the outgoing, if it is \c IGRAPH_IN * then only the incoming edges of a parent are considered. If it is * \c IGRAPH_ALL then all edges are used (this was the behavior in * igraph 0.5 and before). This parameter also influences how the root * vertices are calculated, if they are not given. See the \p roots parameter. * \param roots The index of the root vertex or root vertices. * If this is a non-empty vector then the supplied vertex ids are used * as the roots of the trees (or a single tree if the graph is connected). * If it is a null pointer of a pointer to an empty vector, then the root * vertices are automatically calculated based on topological sorting, * performed with the opposite mode than the \p mode argument. * After the vertices have been sorted, one is selected from each component. * \param rootlevel This argument can be useful when drawing forests which are * not trees (i.e. they are unconnected and have tree components). It specifies * the level of the root vertices for every tree in the forest. It is only * considered if not a null pointer and the \p roots argument is also given * (and it is not a null pointer of an empty vector). * \return Error code. * * Added in version 0.2. * * \sa \ref igraph_layout_reingold_tilford_circular(). * * \example examples/simple/igraph_layout_reingold_tilford.c */ int igraph_layout_reingold_tilford(const igraph_t *graph, igraph_matrix_t *res, igraph_neimode_t mode, const igraph_vector_t *roots, const igraph_vector_t *rootlevel) { long int no_of_nodes_orig = igraph_vcount(graph); long int no_of_nodes = no_of_nodes_orig; long int real_root; igraph_t extended; const igraph_t *pextended = graph; igraph_vector_t myroots; const igraph_vector_t *proots = roots; igraph_neimode_t mode2; long int i; igraph_vector_t newedges; /* TODO: possible speedup could be achieved if we use a table for storing * the children of each node in the tree. (Now the implementation uses a * single array containing the parent of each node and a node's children * are determined by looking for other nodes that have this node as parent) */ /* at various steps it might be necessary to add edges to the graph */ IGRAPH_VECTOR_INIT_FINALLY(&newedges, 0); if (!igraph_is_directed(graph)) { mode = IGRAPH_ALL; } if ( (!roots || igraph_vector_size(roots) == 0) && rootlevel && igraph_vector_size(rootlevel) != 0 ) { IGRAPH_WARNING("Reingold-Tilford layout: 'rootlevel' ignored"); } /* ----------------------------------------------------------------------- */ /* If root vertices are not given, then do a topological sort and take the last element from every component for directed graphs and mode == out, or the first element from every component for directed graphs and mode == in,or select the vertex with the maximum degree from each component for undirected graphs */ if (!roots || igraph_vector_size(roots) == 0) { igraph_vector_t order, membership; igraph_integer_t no_comps; long int i, noseen = 0; IGRAPH_VECTOR_INIT_FINALLY(&myroots, 0); IGRAPH_VECTOR_INIT_FINALLY(&order, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&membership, no_of_nodes); if (mode != IGRAPH_ALL) { /* look for roots by swimming against the stream */ mode2 = (mode == IGRAPH_IN) ? IGRAPH_OUT : IGRAPH_IN; IGRAPH_CHECK(igraph_topological_sorting(graph, &order, mode2)); IGRAPH_CHECK(igraph_clusters(graph, &membership, /*csize=*/ 0, &no_comps, IGRAPH_WEAK)); } else { IGRAPH_CHECK(igraph_sort_vertex_ids_by_degree(graph, &order, igraph_vss_all(), IGRAPH_ALL, 0, IGRAPH_ASCENDING, 0)); IGRAPH_CHECK(igraph_clusters(graph, &membership, /*csize=*/ 0, &no_comps, IGRAPH_WEAK)); } IGRAPH_CHECK(igraph_vector_resize(&myroots, no_comps)); /* go backwards and fill the roots vector with indices [1, no_of_nodes] The index 0 is used to signal this root has not been found yet: all indices are then decreased by one to [0, no_of_nodes - 1] */ igraph_vector_null(&myroots); proots = &myroots; for (i = no_of_nodes - 1; noseen < no_comps && i >= 0; i--) { long int v = (long int) VECTOR(order)[i]; long int mem = (long int) VECTOR(membership)[v]; if (VECTOR(myroots)[mem] == 0) { noseen += 1; VECTOR(myroots)[mem] = v + 1; } } for (i = 0; i < no_comps; i++) { VECTOR(myroots)[i] -= 1; } igraph_vector_destroy(&membership); igraph_vector_destroy(&order); IGRAPH_FINALLY_CLEAN(2); } else if (rootlevel && igraph_vector_size(rootlevel) > 0 && igraph_vector_size(roots) > 1) { /* ----------------------------------------------------------------------- */ /* Many roots were given to us, check 'rootlevel' */ long int plus_levels = 0; long int i; if (igraph_vector_size(roots) != igraph_vector_size(rootlevel)) { IGRAPH_ERROR("Reingold-Tilford: 'roots' and 'rootlevel' lengths differ", IGRAPH_EINVAL); } /* count the rootlevels that are not zero */ for (i = 0; i < igraph_vector_size(roots); i++) { plus_levels += VECTOR(*rootlevel)[i]; } /* make copy of graph, add vertices/edges */ if (plus_levels != 0) { long int edgeptr = 0; pextended = &extended; IGRAPH_CHECK(igraph_copy(&extended, graph)); IGRAPH_FINALLY(igraph_destroy, &extended); IGRAPH_CHECK(igraph_add_vertices(&extended, (igraph_integer_t) plus_levels, 0)); igraph_vector_resize(&newedges, plus_levels * 2); for (i = 0; i < igraph_vector_size(roots); i++) { long int rl = (long int) VECTOR(*rootlevel)[i]; long int rn = (long int) VECTOR(*roots)[i]; long int j; /* zero-level roots don't get anything special */ if (rl == 0) { continue; } /* for each nonzero-level root, add vertices and edges at all levels [1, 2, .., rl] piercing through the graph. If mode=="in" they pierce the other way */ if (mode != IGRAPH_IN) { VECTOR(newedges)[edgeptr++] = no_of_nodes; VECTOR(newedges)[edgeptr++] = rn; for (j = 0; j < rl - 1; j++) { VECTOR(newedges)[edgeptr++] = no_of_nodes + 1; VECTOR(newedges)[edgeptr++] = no_of_nodes; no_of_nodes++; } } else { VECTOR(newedges)[edgeptr++] = rn; VECTOR(newedges)[edgeptr++] = no_of_nodes; for (j = 0; j < rl - 1; j++) { VECTOR(newedges)[edgeptr++] = no_of_nodes; VECTOR(newedges)[edgeptr++] = no_of_nodes + 1; no_of_nodes++; } } /* move on to the next root */ VECTOR(*roots)[i] = no_of_nodes++; } /* actually add the edges to the graph */ IGRAPH_CHECK(igraph_add_edges(&extended, &newedges, 0)); } } /* We have root vertices now. If one or more nonzero-level roots were chosen by the user, we have copied the graph and added a few vertices and (directed) edges to connect those floating roots to nonfloating, zero-level equivalent roots. Below, the function igraph_i_layout_reingold_tilford(pextended, res, mode, real_root) calculates the actual rt coordinates of the graph. However, for simplicity that function requires a connected graph and a single root. For directed graphs, it needs not be strongly connected, however all nodes must be reachable from the root following the stream (i.e. the root must be a "mother vertex"). So before we call that function we have to make sure the (copied) graph satisfies that condition. That requires: 1. if there is more than one root, defining a single real_root 2. if a real_root is defined, adding edges to connect all roots to it 3. ensure real_root is mother of the whole graph. If it is not, add shortcut edges from real_root to any disconnected node for now. NOTE: 3. could be done better, e.g. by topological sorting of some kind. But for now it's ok like this. */ /* if there is only one root, no need for real_root */ if (igraph_vector_size(proots) == 1) { real_root = (long int) VECTOR(*proots)[0]; if (real_root < 0 || real_root >= no_of_nodes) { IGRAPH_ERROR("invalid vertex id", IGRAPH_EINVVID); } /* else, we need to make real_root */ } else { long int no_of_newedges; /* Make copy of the graph unless it exists already */ if (pextended == graph) { pextended = &extended; IGRAPH_CHECK(igraph_copy(&extended, graph)); IGRAPH_FINALLY(igraph_destroy, &extended); } /* add real_root to the vertices */ real_root = no_of_nodes; IGRAPH_CHECK(igraph_add_vertices(&extended, 1, 0)); no_of_nodes++; /* add edges from the roots to real_root */ no_of_newedges = igraph_vector_size(proots); igraph_vector_resize(&newedges, no_of_newedges * 2); for (i = 0; i < no_of_newedges; i++) { VECTOR(newedges)[2 * i] = no_of_nodes - 1; VECTOR(newedges)[2 * i + 1] = VECTOR(*proots)[i]; } IGRAPH_CHECK(igraph_add_edges(&extended, &newedges, 0)); } /* prepare edges to unreachable parts of the graph */ IGRAPH_CHECK(igraph_i_layout_reingold_tilford_unreachable(pextended, mode, real_root, no_of_nodes, &newedges)); if (igraph_vector_size(&newedges) != 0) { /* Make copy of the graph unless it exists already */ if (pextended == graph) { pextended = &extended; IGRAPH_CHECK(igraph_copy(&extended, graph)); IGRAPH_FINALLY(igraph_destroy, &extended); } IGRAPH_CHECK(igraph_add_edges(&extended, &newedges, 0)); } igraph_vector_destroy(&newedges); IGRAPH_FINALLY_CLEAN(1); /* ----------------------------------------------------------------------- */ /* Layout */ IGRAPH_CHECK(igraph_i_layout_reingold_tilford(pextended, res, mode, real_root)); /* Remove the new vertices from the layout */ if (no_of_nodes != no_of_nodes_orig) { if (no_of_nodes - 1 == no_of_nodes_orig) { IGRAPH_CHECK(igraph_matrix_remove_row(res, no_of_nodes_orig)); } else { igraph_matrix_t tmp; long int i; IGRAPH_MATRIX_INIT_FINALLY(&tmp, no_of_nodes_orig, 2); for (i = 0; i < no_of_nodes_orig; i++) { MATRIX(tmp, i, 0) = MATRIX(*res, i, 0); MATRIX(tmp, i, 1) = MATRIX(*res, i, 1); } IGRAPH_CHECK(igraph_matrix_update(res, &tmp)); igraph_matrix_destroy(&tmp); IGRAPH_FINALLY_CLEAN(1); } } if (pextended != graph) { igraph_destroy(&extended); IGRAPH_FINALLY_CLEAN(1); } /* Remove the roots vector if it was created by us */ if (proots != roots) { igraph_vector_destroy(&myroots); IGRAPH_FINALLY_CLEAN(1); } return 0; } /** * \function igraph_layout_reingold_tilford_circular * \brief Circular Reingold-Tilford layout for trees * * * This layout is almost the same as \ref igraph_layout_reingold_tilford(), but * the tree is drawn in a circular way, with the root vertex in the center. * * \param graph The graph object. * \param res The result, the coordinates in a matrix. The parameter * should point to an initialized matrix object and will be resized. * \param mode Specifies which edges to consider when building the tree. * If it is \c IGRAPH_OUT then only the outgoing, if it is \c IGRAPH_IN * then only the incoming edges of a parent are considered. If it is * \c IGRAPH_ALL then all edges are used (this was the behavior in * igraph 0.5 and before). This parameter also influences how the root * vertices are calculated, if they are not given. See the \p roots parameter. * \param roots The index of the root vertex or root vertices. * If this is a non-empty vector then the supplied vertex ids are used * as the roots of the trees (or a single tree if the graph is connected). * If it is a null pointer of a pointer to an empty vector, then the root * vertices are automatically calculated based on topological sorting, * performed with the opposite mode than the \p mode argument. * After the vertices have been sorted, one is selected from each component. * \param rootlevel This argument can be useful when drawing forests which are * not trees (i.e. they are unconnected and have tree components). It specifies * the level of the root vertices for every tree in the forest. It is only * considered if not a null pointer and the \p roots argument is also given * (and it is not a null pointer of an empty vector). Note that if you supply * a null pointer here and the graph has multiple components, all of the root * vertices will be mapped to the origin of the coordinate system, which does * not really make sense. * \return Error code. * * \sa \ref igraph_layout_reingold_tilford(). */ int igraph_layout_reingold_tilford_circular(const igraph_t *graph, igraph_matrix_t *res, igraph_neimode_t mode, const igraph_vector_t *roots, const igraph_vector_t *rootlevel) { long int no_of_nodes = igraph_vcount(graph); long int i; igraph_real_t ratio = 2 * M_PI * (no_of_nodes - 1.0) / no_of_nodes; igraph_real_t minx, maxx; IGRAPH_CHECK(igraph_layout_reingold_tilford(graph, res, mode, roots, rootlevel)); if (no_of_nodes == 0) { return 0; } minx = maxx = MATRIX(*res, 0, 0); for (i = 1; i < no_of_nodes; i++) { if (MATRIX(*res, i, 0) > maxx) { maxx = MATRIX(*res, i, 0); } if (MATRIX(*res, i, 0) < minx) { minx = MATRIX(*res, i, 0); } } if (maxx > minx) { ratio /= (maxx - minx); } for (i = 0; i < no_of_nodes; i++) { igraph_real_t phi = (MATRIX(*res, i, 0) - minx) * ratio; igraph_real_t r = MATRIX(*res, i, 1); MATRIX(*res, i, 0) = r * cos(phi); MATRIX(*res, i, 1) = r * sin(phi); } return 0; } #define COULOMBS_CONSTANT 8987500000.0 igraph_real_t igraph_i_distance_between(const igraph_matrix_t *c, long int a, long int b); int igraph_i_determine_electric_axal_forces(const igraph_matrix_t *pos, igraph_real_t *x, igraph_real_t *y, igraph_real_t directed_force, igraph_real_t distance, long int other_node, long int this_node); int igraph_i_apply_electrical_force(const igraph_matrix_t *pos, igraph_vector_t *pending_forces_x, igraph_vector_t *pending_forces_y, long int other_node, long int this_node, igraph_real_t node_charge, igraph_real_t distance); int igraph_i_determine_spring_axal_forces(const igraph_matrix_t *pos, igraph_real_t *x, igraph_real_t *y, igraph_real_t directed_force, igraph_real_t distance, int spring_length, long int other_node, long int this_node); int igraph_i_apply_spring_force(const igraph_matrix_t *pos, igraph_vector_t *pending_forces_x, igraph_vector_t *pending_forces_y, long int other_node, long int this_node, int spring_length, igraph_real_t spring_constant); int igraph_i_move_nodes(igraph_matrix_t *pos, const igraph_vector_t *pending_forces_x, const igraph_vector_t *pending_forces_y, igraph_real_t node_mass, igraph_real_t max_sa_movement); igraph_real_t igraph_i_distance_between(const igraph_matrix_t *c, long int a, long int b) { igraph_real_t diffx = MATRIX(*c, a, 0) - MATRIX(*c, b, 0); igraph_real_t diffy = MATRIX(*c, a, 1) - MATRIX(*c, b, 1); return sqrt( diffx * diffx + diffy * diffy ); } int igraph_i_determine_electric_axal_forces(const igraph_matrix_t *pos, igraph_real_t *x, igraph_real_t *y, igraph_real_t directed_force, igraph_real_t distance, long int other_node, long int this_node) { // We know what the directed force is. We now need to translate it // into the appropriate x and y components. // First, assume: // other_node // /| // directed_force / | // / | y // /______| // this_node x // // other_node.x > this_node.x // other_node.y > this_node.y // the force will be on this_node away from other_node // the proportion (distance/y_distance) is equal to the proportion // (directed_force/y_force), as the two triangles are similar. // therefore, the magnitude of y_force = (directed_force*y_distance)/distance // the sign of y_force is negative, away from other_node igraph_real_t x_distance, y_distance; y_distance = MATRIX(*pos, other_node, 1) - MATRIX(*pos, this_node, 1); if (y_distance < 0) { y_distance = -y_distance; } *y = -1 * ((directed_force * y_distance) / distance); // the x component works in exactly the same way. x_distance = MATRIX(*pos, other_node, 0) - MATRIX(*pos, this_node, 0); if (x_distance < 0) { x_distance = -x_distance; } *x = -1 * ((directed_force * x_distance) / distance); // Now we need to reverse the polarity of our answers based on the falsness // of our assumptions. if (MATRIX(*pos, other_node, 0) < MATRIX(*pos, this_node, 0)) { *x = *x * -1; } if (MATRIX(*pos, other_node, 1) < MATRIX(*pos, this_node, 1)) { *y = *y * -1; } return 0; } int igraph_i_apply_electrical_force(const igraph_matrix_t *pos, igraph_vector_t *pending_forces_x, igraph_vector_t *pending_forces_y, long int other_node, long int this_node, igraph_real_t node_charge, igraph_real_t distance) { igraph_real_t directed_force = COULOMBS_CONSTANT * ((node_charge * node_charge) / (distance * distance)); igraph_real_t x_force, y_force; igraph_i_determine_electric_axal_forces(pos, &x_force, &y_force, directed_force, distance, other_node, this_node); VECTOR(*pending_forces_x)[this_node] += x_force; VECTOR(*pending_forces_y)[this_node] += y_force; VECTOR(*pending_forces_x)[other_node] -= x_force; VECTOR(*pending_forces_y)[other_node] -= y_force; return 0; } int igraph_i_determine_spring_axal_forces(const igraph_matrix_t *pos, igraph_real_t *x, igraph_real_t *y, igraph_real_t directed_force, igraph_real_t distance, int spring_length, long int other_node, long int this_node) { // if the spring is just the right size, the forces will be 0, so we can // skip the computation. // // if the spring is too long, our forces will be identical to those computed // by determine_electrical_axal_forces() (this_node will be pulled toward // other_node). // // if the spring is too short, our forces will be the opposite of those // computed by determine_electrical_axal_forces() (this_node will be pushed // away from other_node) // // finally, since both nodes are movable, only one-half of the total force // should be applied to each node, so half the forces for our answer. if (distance == spring_length) { *x = 0.0; *y = 0.0; } else { igraph_i_determine_electric_axal_forces(pos, x, y, directed_force, distance, other_node, this_node); if (distance < spring_length) { *x = -1 * *x; *y = -1 * *y; } *x = 0.5 * *x; *y = 0.5 * *y; } return 0; } int igraph_i_apply_spring_force(const igraph_matrix_t *pos, igraph_vector_t *pending_forces_x, igraph_vector_t *pending_forces_y, long int other_node, long int this_node, int spring_length, igraph_real_t spring_constant) { // determined using Hooke's Law: // force = -kx // where: // k = spring constant // x = displacement from ideal length in meters igraph_real_t distance, displacement, directed_force, x_force, y_force; distance = igraph_i_distance_between(pos, other_node, this_node); // let's protect ourselves from division by zero by ignoring two nodes that // happen to be in the same place. Since we separate all nodes before we // work on any of them, this will only happen in extremely rare circumstances, // and when it does, electrical force will probably push one or both of them // one way or another anyway. if (distance == 0.0) { return 0; } displacement = distance - spring_length; if (displacement < 0) { displacement = -displacement; } directed_force = -1 * spring_constant * displacement; // remember, this is force directed away from the spring; // a negative number is back towards the spring (or, in our case, back towards // the other node) // get the force that should be applied to >this< node igraph_i_determine_spring_axal_forces(pos, &x_force, &y_force, directed_force, distance, spring_length, other_node, this_node); VECTOR(*pending_forces_x)[this_node] += x_force; VECTOR(*pending_forces_y)[this_node] += y_force; VECTOR(*pending_forces_x)[other_node] -= x_force; VECTOR(*pending_forces_y)[other_node] -= y_force; return 0; } int igraph_i_move_nodes(igraph_matrix_t *pos, const igraph_vector_t *pending_forces_x, const igraph_vector_t *pending_forces_y, igraph_real_t node_mass, igraph_real_t max_sa_movement) { // Since each iteration is isolated, time is constant at 1. // Therefore: // Force effects acceleration. // acceleration (d(velocity)/time) = velocity // velocity (d(displacement)/time) = displacement // displacement = acceleration // determined using Newton's second law: // sum(F) = ma // therefore: // acceleration = force / mass // velocity = force / mass // displacement = force / mass long int this_node, no_of_nodes = igraph_vector_size(pending_forces_x); for (this_node = 0; this_node < no_of_nodes; this_node++) { igraph_real_t x_movement, y_movement; x_movement = VECTOR(*pending_forces_x)[this_node] / node_mass; if (x_movement > max_sa_movement) { x_movement = max_sa_movement; } else if (x_movement < -max_sa_movement) { x_movement = -max_sa_movement; } y_movement = VECTOR(*pending_forces_y)[this_node] / node_mass; if (y_movement > max_sa_movement) { y_movement = max_sa_movement; } else if (y_movement < -max_sa_movement) { y_movement = -max_sa_movement; } MATRIX(*pos, this_node, 0) += x_movement; MATRIX(*pos, this_node, 1) += y_movement; } return 0; } /** * \function igraph_layout_graphopt * \brief Optimizes vertex layout via the graphopt algorithm. * * * This is a port of the graphopt layout algorithm by Michael Schmuhl. * graphopt version 0.4.1 was rewritten in C and the support for * layers was removed (might be added later) and a code was a bit * reorganized to avoid some unnecessary steps is the node charge (see below) * is zero. * * * graphopt uses physical analogies for defining attracting and repelling * forces among the vertices and then the physical system is simulated * until it reaches an equilibrium. (There is no simulated annealing or * anything like that, so a stable fixed point is not guaranteed.) * * * See also http://www.schmuhl.org/graphopt/ for the original graphopt. * \param graph The input graph. * \param res Pointer to an initialized matrix, the result will be stored here * and its initial contents is used the starting point of the simulation * if the \p use_seed argument is true. Note that in this case the * matrix should have the proper size, otherwise a warning is issued and * the supplied values are ignored. If no starting positions are given * (or they are invalid) then a random staring position is used. * The matrix will be resized if needed. * \param niter Integer constant, the number of iterations to perform. * Should be a couple of hundred in general. If you have a large graph * then you might want to only do a few iterations and then check the * result. If it is not good enough you can feed it in again in * the \p res argument. The original graphopt default if 500. * \param node_charge The charge of the vertices, used to calculate electric * repulsion. The original graphopt default is 0.001. * \param node_mass The mass of the vertices, used for the spring forces. * The original graphopt defaults to 30. * \param spring_length The length of the springs, an integer number. * The original graphopt defaults to zero. * \param spring_constant The spring constant, the original graphopt defaults * to one. * \param max_sa_movement Real constant, it gives the maximum amount of movement * allowed in a single step along a single axis. The original graphopt * default is 5. * \param use_seed Logical scalar, whether to use the positions in \p res as * a starting configuration. See also \p res above. * \return Error code. * * Time complexity: O(n (|V|^2+|E|) ), n is the number of iterations, * |V| is the number of vertices, |E| the number * of edges. If \p node_charge is zero then it is only O(n|E|). */ int igraph_layout_graphopt(const igraph_t *graph, igraph_matrix_t *res, igraph_integer_t niter, igraph_real_t node_charge, igraph_real_t node_mass, igraph_real_t spring_length, igraph_real_t spring_constant, igraph_real_t max_sa_movement, igraph_bool_t use_seed) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); int my_spring_length = (int) spring_length; igraph_vector_t pending_forces_x, pending_forces_y; /* Set a flag to calculate (or not) the electrical forces that the nodes */ /* apply on each other based on if both node types' charges are zero. */ igraph_bool_t apply_electric_charges = (node_charge != 0); long int this_node, other_node, edge; igraph_real_t distance; long int i; IGRAPH_VECTOR_INIT_FINALLY(&pending_forces_x, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&pending_forces_y, no_of_nodes); if (use_seed) { if (igraph_matrix_nrow(res) != no_of_nodes || igraph_matrix_ncol(res) != 2) { IGRAPH_WARNING("Invalid size for initial matrix, starting from random layout"); IGRAPH_CHECK(igraph_layout_random(graph, res)); } } else { IGRAPH_CHECK(igraph_layout_random(graph, res)); } IGRAPH_PROGRESS("Graphopt layout", 0, NULL); for (i = niter; i > 0; i--) { /* Report progress in approx. every 100th step */ if (i % 10 == 0) { IGRAPH_PROGRESS("Graphopt layout", 100.0 - 100.0 * i / niter, NULL); } /* Clear pending forces on all nodes */ igraph_vector_null(&pending_forces_x); igraph_vector_null(&pending_forces_y); // Apply electrical force applied by all other nodes if (apply_electric_charges) { // Iterate through all nodes for (this_node = 0; this_node < no_of_nodes; this_node++) { IGRAPH_ALLOW_INTERRUPTION(); for (other_node = this_node + 1; other_node < no_of_nodes; other_node++) { distance = igraph_i_distance_between(res, this_node, other_node); // let's protect ourselves from division by zero by ignoring // two nodes that happen to be in the same place. Since we // separate all nodes before we work on any of them, this // will only happen in extremely rare circumstances, and when // it does, springs will probably pull them apart anyway. // also, if we are more than 50 away, the electric force // will be negligible. // ***** may not always be desirable **** if ((distance != 0.0) && (distance < 500.0)) { // if (distance != 0.0) { // Apply electrical force from node(counter2) on // node(counter) igraph_i_apply_electrical_force(res, &pending_forces_x, &pending_forces_y, other_node, this_node, node_charge, distance); } } } } // Apply force from springs for (edge = 0; edge < no_of_edges; edge++) { long int tthis_node = IGRAPH_FROM(graph, edge); long int oother_node = IGRAPH_TO(graph, edge); // Apply spring force on both nodes igraph_i_apply_spring_force(res, &pending_forces_x, &pending_forces_y, oother_node, tthis_node, my_spring_length, spring_constant); } // Effect the movement of the nodes based on all pending forces igraph_i_move_nodes(res, &pending_forces_x, &pending_forces_y, node_mass, max_sa_movement); } IGRAPH_PROGRESS("Graphopt layout", 100, NULL); igraph_vector_destroy(&pending_forces_y); igraph_vector_destroy(&pending_forces_x); IGRAPH_FINALLY_CLEAN(2); return 0; } int igraph_i_layout_merge_dla(igraph_i_layout_mergegrid_t *grid, long int actg, igraph_real_t *x, igraph_real_t *y, igraph_real_t r, igraph_real_t cx, igraph_real_t cy, igraph_real_t startr, igraph_real_t killr); int igraph_i_layout_sphere_2d(igraph_matrix_t *coords, igraph_real_t *x, igraph_real_t *y, igraph_real_t *r); int igraph_i_layout_sphere_3d(igraph_matrix_t *coords, igraph_real_t *x, igraph_real_t *y, igraph_real_t *z, igraph_real_t *r); /** * \function igraph_layout_merge_dla * \brief Merge multiple layouts by using a DLA algorithm * * * First each layout is covered by a circle. Then the layout of the * largest graph is placed at the origin. Then the other layouts are * placed by the DLA algorithm, larger ones first and smaller ones * last. * \param thegraphs Pointer vector containing the graph object of * which the layouts will be merged. * \param coords Pointer vector containing matrix objects with the 2d * layouts of the graphs in \p thegraphs. * \param res Pointer to an initialized matrix object, the result will * be stored here. It will be resized if needed. * \return Error code. * * Added in version 0.2. This function is experimental. * * * Time complexity: TODO. */ int igraph_layout_merge_dla(igraph_vector_ptr_t *thegraphs, igraph_vector_ptr_t *coords, igraph_matrix_t *res) { long int graphs = igraph_vector_ptr_size(coords); igraph_vector_t sizes; igraph_vector_t x, y, r; igraph_vector_t nx, ny, nr; long int allnodes = 0; long int i, j; long int actg; igraph_i_layout_mergegrid_t grid; long int jpos = 0; igraph_real_t minx, maxx, miny, maxy; igraph_real_t area = 0; igraph_real_t maxr = 0; long int respos; /* Graphs are currently not used, only the coordinates */ IGRAPH_UNUSED(thegraphs); IGRAPH_VECTOR_INIT_FINALLY(&sizes, graphs); IGRAPH_VECTOR_INIT_FINALLY(&x, graphs); IGRAPH_VECTOR_INIT_FINALLY(&y, graphs); IGRAPH_VECTOR_INIT_FINALLY(&r, graphs); IGRAPH_VECTOR_INIT_FINALLY(&nx, graphs); IGRAPH_VECTOR_INIT_FINALLY(&ny, graphs); IGRAPH_VECTOR_INIT_FINALLY(&nr, graphs); RNG_BEGIN(); for (i = 0; i < igraph_vector_ptr_size(coords); i++) { igraph_matrix_t *mat = VECTOR(*coords)[i]; long int size = igraph_matrix_nrow(mat); if (igraph_matrix_ncol(mat) != 2) { IGRAPH_ERROR("igraph_layout_merge_dla works for 2D layouts only", IGRAPH_EINVAL); } IGRAPH_ALLOW_INTERRUPTION(); allnodes += size; VECTOR(sizes)[i] = size; VECTOR(r)[i] = pow(size, .75); area += VECTOR(r)[i] * VECTOR(r)[i]; if (VECTOR(r)[i] > maxr) { maxr = VECTOR(r)[i]; } igraph_i_layout_sphere_2d(mat, igraph_vector_e_ptr(&nx, i), igraph_vector_e_ptr(&ny, i), igraph_vector_e_ptr(&nr, i)); } igraph_vector_order2(&sizes); /* largest first */ /* 0. create grid */ minx = miny = -sqrt(5 * area); maxx = maxy = sqrt(5 * area); igraph_i_layout_mergegrid_init(&grid, minx, maxx, 200, miny, maxy, 200); IGRAPH_FINALLY(igraph_i_layout_mergegrid_destroy, &grid); /* fprintf(stderr, "Ok, starting DLA\n"); */ /* 1. place the largest */ actg = (long int) VECTOR(sizes)[jpos++]; igraph_i_layout_merge_place_sphere(&grid, 0, 0, VECTOR(r)[actg], actg); IGRAPH_PROGRESS("Merging layouts via DLA", 0.0, NULL); while (jpos < graphs) { IGRAPH_ALLOW_INTERRUPTION(); /* fprintf(stderr, "comp: %li", jpos); */ IGRAPH_PROGRESS("Merging layouts via DLA", (100.0 * jpos) / graphs, NULL); actg = (long int) VECTOR(sizes)[jpos++]; /* 2. random walk, TODO: tune parameters */ igraph_i_layout_merge_dla(&grid, actg, igraph_vector_e_ptr(&x, actg), igraph_vector_e_ptr(&y, actg), VECTOR(r)[actg], 0, 0, maxx, maxx + 5); /* 3. place sphere */ igraph_i_layout_merge_place_sphere(&grid, VECTOR(x)[actg], VECTOR(y)[actg], VECTOR(r)[actg], actg); } IGRAPH_PROGRESS("Merging layouts via DLA", 100.0, NULL); /* Create the result */ IGRAPH_CHECK(igraph_matrix_resize(res, allnodes, 2)); respos = 0; for (i = 0; i < graphs; i++) { long int size = igraph_matrix_nrow(VECTOR(*coords)[i]); igraph_real_t xx = VECTOR(x)[i]; igraph_real_t yy = VECTOR(y)[i]; igraph_real_t rr = VECTOR(r)[i] / VECTOR(nr)[i]; igraph_matrix_t *mat = VECTOR(*coords)[i]; IGRAPH_ALLOW_INTERRUPTION(); if (VECTOR(nr)[i] == 0) { rr = 1; } for (j = 0; j < size; j++) { MATRIX(*res, respos, 0) = rr * (MATRIX(*mat, j, 0) - VECTOR(nx)[i]); MATRIX(*res, respos, 1) = rr * (MATRIX(*mat, j, 1) - VECTOR(ny)[i]); MATRIX(*res, respos, 0) += xx; MATRIX(*res, respos, 1) += yy; ++respos; } } RNG_END(); igraph_i_layout_mergegrid_destroy(&grid); igraph_vector_destroy(&sizes); igraph_vector_destroy(&x); igraph_vector_destroy(&y); igraph_vector_destroy(&r); igraph_vector_destroy(&nx); igraph_vector_destroy(&ny); igraph_vector_destroy(&nr); IGRAPH_FINALLY_CLEAN(8); return 0; } int igraph_i_layout_sphere_2d(igraph_matrix_t *coords, igraph_real_t *x, igraph_real_t *y, igraph_real_t *r) { long int nodes = igraph_matrix_nrow(coords); long int i; igraph_real_t xmin, xmax, ymin, ymax; xmin = xmax = MATRIX(*coords, 0, 0); ymin = ymax = MATRIX(*coords, 0, 1); for (i = 1; i < nodes; i++) { if (MATRIX(*coords, i, 0) < xmin) { xmin = MATRIX(*coords, i, 0); } else if (MATRIX(*coords, i, 0) > xmax) { xmax = MATRIX(*coords, i, 0); } if (MATRIX(*coords, i, 1) < ymin) { ymin = MATRIX(*coords, i, 1); } else if (MATRIX(*coords, i, 1) > ymax) { ymax = MATRIX(*coords, i, 1); } } *x = (xmin + xmax) / 2; *y = (ymin + ymax) / 2; *r = sqrt( (xmax - xmin) * (xmax - xmin) + (ymax - ymin) * (ymax - ymin) ) / 2; return 0; } int igraph_i_layout_sphere_3d(igraph_matrix_t *coords, igraph_real_t *x, igraph_real_t *y, igraph_real_t *z, igraph_real_t *r) { long int nodes = igraph_matrix_nrow(coords); long int i; igraph_real_t xmin, xmax, ymin, ymax, zmin, zmax; xmin = xmax = MATRIX(*coords, 0, 0); ymin = ymax = MATRIX(*coords, 0, 1); zmin = zmax = MATRIX(*coords, 0, 2); for (i = 1; i < nodes; i++) { if (MATRIX(*coords, i, 0) < xmin) { xmin = MATRIX(*coords, i, 0); } else if (MATRIX(*coords, i, 0) > xmax) { xmax = MATRIX(*coords, i, 0); } if (MATRIX(*coords, i, 1) < ymin) { ymin = MATRIX(*coords, i, 1); } else if (MATRIX(*coords, i, 1) > ymax) { ymax = MATRIX(*coords, i, 1); } if (MATRIX(*coords, i, 2) < zmin) { zmin = MATRIX(*coords, i, 2); } else if (MATRIX(*coords, i, 2) > zmax) { zmax = MATRIX(*coords, i, 2); } } *x = (xmin + xmax) / 2; *y = (ymin + ymax) / 2; *z = (zmin + zmax) / 2; *r = sqrt( (xmax - xmin) * (xmax - xmin) + (ymax - ymin) * (ymax - ymin) + (zmax - zmin) * (zmax - zmin) ) / 2; return 0; } #define DIST(x,y) (sqrt(pow((x)-cx,2)+pow((y)-cy,2))) int igraph_i_layout_merge_dla(igraph_i_layout_mergegrid_t *grid, long int actg, igraph_real_t *x, igraph_real_t *y, igraph_real_t r, igraph_real_t cx, igraph_real_t cy, igraph_real_t startr, igraph_real_t killr) { long int sp = -1; igraph_real_t angle, len; long int steps = 0; /* The graph is not used, only its coordinates */ IGRAPH_UNUSED(actg); while (sp < 0) { /* start particle */ do { steps++; angle = RNG_UNIF(0, 2 * M_PI); len = RNG_UNIF(.5 * startr, startr); *x = cx + len * cos(angle); *y = cy + len * sin(angle); sp = igraph_i_layout_mergegrid_get_sphere(grid, *x, *y, r); } while (sp >= 0); while (sp < 0 && DIST(*x, *y) < killr) { igraph_real_t nx, ny; steps++; angle = RNG_UNIF(0, 2 * M_PI); len = RNG_UNIF(0, startr / 100); nx = *x + len * cos(angle); ny = *y + len * sin(angle); sp = igraph_i_layout_mergegrid_get_sphere(grid, nx, ny, r); if (sp < 0) { *x = nx; *y = ny; } } } /* fprintf(stderr, "%li ", steps); */ return 0; } int igraph_i_layout_mds_step(igraph_real_t *to, const igraph_real_t *from, int n, void *extra); int igraph_i_layout_mds_single(const igraph_t* graph, igraph_matrix_t *res, igraph_matrix_t *dist, long int dim); int igraph_i_layout_mds_step(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_matrix_t* matrix = (igraph_matrix_t*)extra; IGRAPH_UNUSED(n); igraph_blas_dgemv_array(0, 1, matrix, from, 0, to); return 0; } /* MDS layout for a connected graph, with no error checking on the * input parameters. The distance matrix will be modified in-place. */ int igraph_i_layout_mds_single(const igraph_t* graph, igraph_matrix_t *res, igraph_matrix_t *dist, long int dim) { long int no_of_nodes = igraph_vcount(graph); long int nev = dim; igraph_matrix_t vectors; igraph_vector_t values, row_means; igraph_real_t grand_mean; long int i, j, k; igraph_eigen_which_t which; /* Handle the trivial cases */ if (no_of_nodes == 1) { IGRAPH_CHECK(igraph_matrix_resize(res, 1, dim)); igraph_matrix_fill(res, 0); return IGRAPH_SUCCESS; } if (no_of_nodes == 2) { IGRAPH_CHECK(igraph_matrix_resize(res, 2, dim)); igraph_matrix_fill(res, 0); for (j = 0; j < dim; j++) { MATRIX(*res, 1, j) = 1; } return IGRAPH_SUCCESS; } /* Initialize some stuff */ IGRAPH_VECTOR_INIT_FINALLY(&values, no_of_nodes); IGRAPH_CHECK(igraph_matrix_init(&vectors, no_of_nodes, dim)); IGRAPH_FINALLY(igraph_matrix_destroy, &vectors); /* Take the square of the distance matrix */ for (i = 0; i < no_of_nodes; i++) { for (j = 0; j < no_of_nodes; j++) { MATRIX(*dist, i, j) *= MATRIX(*dist, i, j); } } /* Double centering of the distance matrix */ IGRAPH_VECTOR_INIT_FINALLY(&row_means, no_of_nodes); igraph_vector_fill(&values, 1.0 / no_of_nodes); igraph_blas_dgemv(0, 1, dist, &values, 0, &row_means); grand_mean = igraph_vector_sum(&row_means) / no_of_nodes; igraph_matrix_add_constant(dist, grand_mean); for (i = 0; i < no_of_nodes; i++) { for (j = 0; j < no_of_nodes; j++) { MATRIX(*dist, i, j) -= VECTOR(row_means)[i] + VECTOR(row_means)[j]; MATRIX(*dist, i, j) *= -0.5; } } igraph_vector_destroy(&row_means); IGRAPH_FINALLY_CLEAN(1); /* Calculate the top `dim` eigenvectors. */ which.pos = IGRAPH_EIGEN_LA; which.howmany = (int) nev; IGRAPH_CHECK(igraph_eigen_matrix_symmetric(/*A=*/ 0, /*sA=*/ 0, /*fun=*/ igraph_i_layout_mds_step, /*n=*/ (int) no_of_nodes, /*extra=*/ dist, /*algorithm=*/ IGRAPH_EIGEN_LAPACK, &which, /*options=*/ 0, /*storage=*/ 0, &values, &vectors)); /* Calculate and normalize the final coordinates */ for (j = 0; j < nev; j++) { VECTOR(values)[j] = sqrt(fabs(VECTOR(values)[j])); } IGRAPH_CHECK(igraph_matrix_resize(res, no_of_nodes, dim)); for (i = 0; i < no_of_nodes; i++) { for (j = 0, k = nev - 1; j < nev; j++, k--) { MATRIX(*res, i, k) = VECTOR(values)[j] * MATRIX(vectors, i, j); } } igraph_matrix_destroy(&vectors); igraph_vector_destroy(&values); IGRAPH_FINALLY_CLEAN(2); return IGRAPH_SUCCESS; } /** * \function igraph_layout_mds * \brief Place the vertices on a plane using multidimensional scaling. * * * This layout requires a distance matrix, where the intersection of * row i and column j specifies the desired distance between vertex i * and vertex j. The algorithm will try to place the vertices in a * space having a given number of dimensions in a way that approximates * the distance relations prescribed in the distance matrix. igraph * uses the classical multidimensional scaling by Torgerson; for more * details, see Cox & Cox: Multidimensional Scaling (1994), Chapman * and Hall, London. * * * If the input graph is disconnected, igraph will decompose it * first into its subgraphs, lay out the subgraphs one by one * using the appropriate submatrices of the distance matrix, and * then merge the layouts using \ref igraph_layout_merge_dla. * Since \ref igraph_layout_merge_dla works for 2D layouts only, * you cannot run the MDS layout on disconnected graphs for * more than two dimensions. * * * Warning: if the graph is symmetric to the exchange of two vertices * (as is the case with leaves of a tree connecting to the same parent), * classical multidimensional scaling may assign the same coordinates to * these vertices. * * \param graph A graph object. * \param res Pointer to an initialized matrix object. This will * contain the result and will be resized if needed. * \param dist The distance matrix. It must be symmetric and this * function does not check whether the matrix is indeed * symmetric. Results are unspecified if you pass a non-symmetric * matrix here. You can set this parameter to null; in this * case, the shortest path lengths between vertices will be * used as distances. * \param dim The number of dimensions in the embedding space. For * 2D layouts, supply 2 here. * \param options This argument is currently ignored, it was used for * ARPACK, but LAPACK is used now for calculating the eigenvectors. * \return Error code. * * Added in version 0.6. * * * Time complexity: usually around O(|V|^2 dim). */ int igraph_layout_mds(const igraph_t* graph, igraph_matrix_t *res, const igraph_matrix_t *dist, long int dim, igraph_arpack_options_t *options) { long int i, no_of_nodes = igraph_vcount(graph); igraph_matrix_t m; igraph_bool_t conn; RNG_BEGIN(); /* Check the distance matrix */ if (dist && (igraph_matrix_nrow(dist) != no_of_nodes || igraph_matrix_ncol(dist) != no_of_nodes)) { IGRAPH_ERROR("invalid distance matrix size", IGRAPH_EINVAL); } /* Check the number of dimensions */ if (dim <= 1) { IGRAPH_ERROR("dim must be positive", IGRAPH_EINVAL); } if (dim > no_of_nodes) { IGRAPH_ERROR("dim must be less than the number of nodes", IGRAPH_EINVAL); } /* Copy or obtain the distance matrix */ if (dist == 0) { IGRAPH_CHECK(igraph_matrix_init(&m, no_of_nodes, no_of_nodes)); IGRAPH_FINALLY(igraph_matrix_destroy, &m); IGRAPH_CHECK(igraph_shortest_paths(graph, &m, igraph_vss_all(), igraph_vss_all(), IGRAPH_ALL)); } else { IGRAPH_CHECK(igraph_matrix_copy(&m, dist)); IGRAPH_FINALLY(igraph_matrix_destroy, &m); /* Make sure that the diagonal contains zeroes only */ for (i = 0; i < no_of_nodes; i++) { MATRIX(m, i, i) = 0.0; } } /* Check whether the graph is connected */ IGRAPH_CHECK(igraph_is_connected(graph, &conn, IGRAPH_WEAK)); if (conn) { /* Yes, it is, just do the MDS */ IGRAPH_CHECK(igraph_i_layout_mds_single(graph, res, &m, dim)); } else { /* The graph is not connected, lay out the components one by one */ igraph_vector_ptr_t layouts; igraph_vector_t comp, vertex_order; igraph_t subgraph; igraph_matrix_t *layout; igraph_matrix_t dist_submatrix; igraph_bool_t *seen_vertices; long int j, n, processed_vertex_count = 0; IGRAPH_VECTOR_INIT_FINALLY(&comp, 0); IGRAPH_VECTOR_INIT_FINALLY(&vertex_order, no_of_nodes); IGRAPH_CHECK(igraph_vector_ptr_init(&layouts, 0)); IGRAPH_FINALLY(igraph_vector_ptr_destroy_all, &layouts); igraph_vector_ptr_set_item_destructor(&layouts, (igraph_finally_func_t*)igraph_matrix_destroy); IGRAPH_CHECK(igraph_matrix_init(&dist_submatrix, 0, 0)); IGRAPH_FINALLY(igraph_matrix_destroy, &dist_submatrix); seen_vertices = igraph_Calloc(no_of_nodes, igraph_bool_t); if (seen_vertices == 0) { IGRAPH_ERROR("cannot calculate MDS layout", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, seen_vertices); for (i = 0; i < no_of_nodes; i++) { if (seen_vertices[i]) { continue; } /* This is a vertex whose component we did not lay out so far */ IGRAPH_CHECK(igraph_subcomponent(graph, &comp, i, IGRAPH_ALL)); /* Take the subgraph */ IGRAPH_CHECK(igraph_induced_subgraph(graph, &subgraph, igraph_vss_vector(&comp), IGRAPH_SUBGRAPH_AUTO)); IGRAPH_FINALLY(igraph_destroy, &subgraph); /* Calculate the submatrix of the distances */ IGRAPH_CHECK(igraph_matrix_select_rows_cols(&m, &dist_submatrix, &comp, &comp)); /* Allocate a new matrix for storing the layout */ layout = igraph_Calloc(1, igraph_matrix_t); if (layout == 0) { IGRAPH_ERROR("cannot calculate MDS layout", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, layout); IGRAPH_CHECK(igraph_matrix_init(layout, 0, 0)); IGRAPH_FINALLY(igraph_matrix_destroy, layout); /* Lay out the subgraph */ IGRAPH_CHECK(igraph_i_layout_mds_single(&subgraph, layout, &dist_submatrix, dim)); /* Store the layout */ IGRAPH_CHECK(igraph_vector_ptr_push_back(&layouts, layout)); IGRAPH_FINALLY_CLEAN(2); /* ownership of layout taken by layouts */ /* Free the newly created subgraph */ igraph_destroy(&subgraph); IGRAPH_FINALLY_CLEAN(1); /* Mark all the vertices in the component as visited */ n = igraph_vector_size(&comp); for (j = 0; j < n; j++) { seen_vertices[(long int)VECTOR(comp)[j]] = 1; VECTOR(vertex_order)[(long int)VECTOR(comp)[j]] = processed_vertex_count++; } } /* Merge the layouts - reusing dist_submatrix here */ IGRAPH_CHECK(igraph_layout_merge_dla(0, &layouts, &dist_submatrix)); /* Reordering the rows of res to match the original graph */ IGRAPH_CHECK(igraph_matrix_select_rows(&dist_submatrix, res, &vertex_order)); igraph_free(seen_vertices); igraph_matrix_destroy(&dist_submatrix); igraph_vector_ptr_destroy_all(&layouts); igraph_vector_destroy(&vertex_order); igraph_vector_destroy(&comp); IGRAPH_FINALLY_CLEAN(5); } RNG_END(); igraph_matrix_destroy(&m); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } /** * \function igraph_layout_bipartite * Simple layout for bipartite graphs * * The layout is created by first placing the vertices in two rows, * according to their types. Then the positions within the rows are * optimized to minimize edge crossings, by calling \ref * igraph_layout_sugiyama(). * * \param graph The input graph. * \param types A boolean vector containing ones and zeros, the vertex * types. Its length must match the number of vertices in the graph. * \param res Pointer to an initialized matrix, the result, the x and * y coordinates are stored here. * \param hgap The preferred minimum horizontal gap between vertices * in the same layer (i.e. vertices of the same type). * \param vgap The distance between layers. * \param maxiter Maximum number of iterations in the crossing * minimization stage. 100 is a reasonable default; if you feel * that you have too many edge crossings, increase this. * \return Error code. * * \sa \ref igraph_layout_sugiyama(). */ int igraph_layout_bipartite(const igraph_t *graph, const igraph_vector_bool_t *types, igraph_matrix_t *res, igraph_real_t hgap, igraph_real_t vgap, long int maxiter) { long int i, no_of_nodes = igraph_vcount(graph); igraph_vector_t layers; if (igraph_vector_bool_size(types) != no_of_nodes) { IGRAPH_ERROR("Invalid vertex type vector size", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(&layers, no_of_nodes); for (i = 0; i < no_of_nodes; i++) { VECTOR(layers)[i] = 1 - VECTOR(*types)[i]; } IGRAPH_CHECK(igraph_layout_sugiyama(graph, res, /*extd_graph=*/ 0, /*extd_to_orig_eids=*/ 0, &layers, hgap, vgap, maxiter, /*weights=*/ 0)); igraph_vector_destroy(&layers); IGRAPH_FINALLY_CLEAN(1); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/spmatrix.c0000644000076500000240000007723513614300625023427 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et */ /* IGraph library. Copyright (C) 2003-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_types.h" #include "igraph_spmatrix.h" #include "igraph_memory.h" #include "igraph_random.h" #include "igraph_error.h" #include "config.h" #include #include /* memcpy & co. */ #include /** * \section igraph_spmatrix_constructor_and_destructor Sparse matrix constructors * and destructors. */ /** * \ingroup matrix * \function igraph_spmatrix_init * \brief Initializes a sparse matrix. * * * Every sparse matrix needs to be initialized before using it, this is done * by calling this function. A matrix has to be destroyed if it is not * needed any more, see \ref igraph_spmatrix_destroy(). * \param m Pointer to a not yet initialized sparse matrix object to be * initialized. * \param nrow The number of rows in the matrix. * \param ncol The number of columns in the matrix. * \return Error code. * * Time complexity: operating system dependent. */ int igraph_spmatrix_init(igraph_spmatrix_t *m, long int nrow, long int ncol) { assert(m != NULL); IGRAPH_VECTOR_INIT_FINALLY(&m->ridx, 0); IGRAPH_VECTOR_INIT_FINALLY(&m->cidx, ncol + 1); IGRAPH_VECTOR_INIT_FINALLY(&m->data, 0); IGRAPH_FINALLY_CLEAN(3); m->nrow = nrow; m->ncol = ncol; return 0; } /** * \ingroup matrix * \function igraph_spmatrix_destroy * \brief Destroys a sparse matrix object. * * * This function frees all the memory allocated for a sparse matrix * object. The destroyed object needs to be reinitialized before using * it again. * \param m The matrix to destroy. * * Time complexity: operating system dependent. */ void igraph_spmatrix_destroy(igraph_spmatrix_t *m) { assert(m != NULL); igraph_vector_destroy(&m->ridx); igraph_vector_destroy(&m->cidx); igraph_vector_destroy(&m->data); } /** * \ingroup matrix * \function igraph_spmatrix_copy * \brief Copies a sparse matrix. * * * Creates a sparse matrix object by copying another one. * \param to Pointer to an uninitialized sparse matrix object. * \param from The initialized sparse matrix object to copy. * \return Error code, \c IGRAPH_ENOMEM if there * isn't enough memory to allocate the new sparse matrix. * * Time complexity: O(n), the number * of elements in the matrix. */ int igraph_spmatrix_copy(igraph_spmatrix_t *to, const igraph_spmatrix_t *from) { assert(from != NULL); assert(to != NULL); to->nrow = from->nrow; to->ncol = from->ncol; IGRAPH_CHECK(igraph_vector_copy(&to->ridx, &from->ridx)); IGRAPH_CHECK(igraph_vector_copy(&to->cidx, &from->cidx)); IGRAPH_CHECK(igraph_vector_copy(&to->data, &from->data)); return 0; } /** * \section igraph_spmatrix_accessing_elements Accessing elements of a sparse matrix */ /** * \ingroup matrix * \function igraph_spmatrix_e * \brief Accessing an element of a sparse matrix. * * Note that there are no range checks right now. * \param m The matrix object. * \param row The index of the row, starting with zero. * \param col The index of the column, starting with zero. * * Time complexity: O(log n), where n is the number of nonzero elements in * the requested column. */ igraph_real_t igraph_spmatrix_e(const igraph_spmatrix_t *m, long int row, long int col) { long int start, end; assert(m != NULL); start = (long) VECTOR(m->cidx)[col]; end = (long) VECTOR(m->cidx)[col + 1] - 1; if (end < start) { return 0; } /* Elements residing in column col are between m->data[start] and * m->data[end], inclusive, ordered by row index */ while (start < end - 1) { long int mid = (start + end) / 2; if (VECTOR(m->ridx)[mid] > row) { end = mid; } else if (VECTOR(m->ridx)[mid] < row) { start = mid; } else { start = mid; break; } } if (VECTOR(m->ridx)[start] == row) { return VECTOR(m->data)[start]; } if (VECTOR(m->ridx)[start] != row && VECTOR(m->ridx)[end] == row) { return VECTOR(m->data)[end]; } return 0; } /** * \ingroup matrix * \function igraph_spmatrix_set * \brief Setting an element of a sparse matrix. * * Note that there are no range checks right now. * \param m The matrix object. * \param row The index of the row, starting with zero. * \param col The index of the column, starting with zero. * \param value The new value. * * Time complexity: O(log n), where n is the number of nonzero elements in * the requested column. */ int igraph_spmatrix_set(igraph_spmatrix_t *m, long int row, long int col, igraph_real_t value) { long int start, end; assert(m != NULL); start = (long) VECTOR(m->cidx)[col]; end = (long) VECTOR(m->cidx)[col + 1] - 1; if (end < start) { /* First element in the column */ if (value == 0.0) { return 0; } IGRAPH_CHECK(igraph_vector_insert(&m->ridx, start, row)); IGRAPH_CHECK(igraph_vector_insert(&m->data, start, value)); for (start = col + 1; start < m->ncol + 1; start++) { VECTOR(m->cidx)[start]++; } return 0; } /* Elements residing in column col are between m->data[start] and * m->data[end], inclusive, ordered by row index */ while (start < end - 1) { long int mid = (start + end) / 2; if (VECTOR(m->ridx)[mid] > row) { end = mid; } else if (VECTOR(m->ridx)[mid] < row) { start = mid; } else { start = mid; break; } } if (VECTOR(m->ridx)[start] == row) { /* Overwriting a value - or deleting it if it has been overwritten by zero */ if (value == 0) { igraph_vector_remove(&m->ridx, start); igraph_vector_remove(&m->data, start); for (start = col + 1; start < m->ncol + 1; start++) { VECTOR(m->cidx)[start]--; } } else { VECTOR(m->data)[start] = value; } return 0; } else if (VECTOR(m->ridx)[end] == row) { /* Overwriting a value - or deleting it if it has been overwritten by zero */ if (value == 0) { igraph_vector_remove(&m->ridx, end); igraph_vector_remove(&m->data, end); for (start = col + 1; start < m->ncol + 1; start++) { VECTOR(m->cidx)[start]--; } } else { VECTOR(m->data)[end] = value; } return 0; } /* New element has to be inserted, but only if not a zero is * being written into the matrix */ if (value != 0.0) { if (VECTOR(m->ridx)[end] < row) { IGRAPH_CHECK(igraph_vector_insert(&m->ridx, end + 1, row)); IGRAPH_CHECK(igraph_vector_insert(&m->data, end + 1, value)); } else if (VECTOR(m->ridx)[start] < row) { IGRAPH_CHECK(igraph_vector_insert(&m->ridx, start + 1, row)); IGRAPH_CHECK(igraph_vector_insert(&m->data, start + 1, value)); } else { IGRAPH_CHECK(igraph_vector_insert(&m->ridx, start, row)); IGRAPH_CHECK(igraph_vector_insert(&m->data, start, value)); } for (start = col + 1; start < m->ncol + 1; start++) { VECTOR(m->cidx)[start]++; } } return 0; } /** * \ingroup matrix * \function igraph_spmatrix_add_e * \brief Adding a real value to an element of a sparse matrix. * * Note that there are no range checks right now. This is implemented to avoid * double lookup of a given element in the matrix by using \ref igraph_spmatrix_e() * and \ref igraph_spmatrix_set() consecutively. * * \param m The matrix object. * \param row The index of the row, starting with zero. * \param col The index of the column, starting with zero. * \param value The value to add. * * Time complexity: O(log n), where n is the number of nonzero elements in * the requested column. */ int igraph_spmatrix_add_e(igraph_spmatrix_t *m, long int row, long int col, igraph_real_t value) { long int start, end; assert(m != NULL); start = (long) VECTOR(m->cidx)[col]; end = (long) VECTOR(m->cidx)[col + 1] - 1; if (end < start) { /* First element in the column */ if (value == 0.0) { return 0; } IGRAPH_CHECK(igraph_vector_insert(&m->ridx, start, row)); IGRAPH_CHECK(igraph_vector_insert(&m->data, start, value)); for (start = col + 1; start < m->ncol + 1; start++) { VECTOR(m->cidx)[start]++; } return 0; } /* Elements residing in column col are between m->data[start] and * m->data[end], inclusive, ordered by row index */ while (start < end - 1) { long int mid = (start + end) / 2; if (VECTOR(m->ridx)[mid] > row) { end = mid; } else if (VECTOR(m->ridx)[mid] < row) { start = mid; } else { start = mid; break; } } if (VECTOR(m->ridx)[start] == row) { /* Overwriting a value */ if (VECTOR(m->data)[start] == -1) { igraph_vector_remove(&m->ridx, start); igraph_vector_remove(&m->data, start); for (start = col + 1; start < m->ncol + 1; start++) { VECTOR(m->cidx)[start]--; } } else { VECTOR(m->data)[start] += value; } return 0; } else if (VECTOR(m->ridx)[end] == row) { /* Overwriting a value */ if (VECTOR(m->data)[end] == -1) { igraph_vector_remove(&m->ridx, end); igraph_vector_remove(&m->data, end); for (start = col + 1; start < m->ncol + 1; start++) { VECTOR(m->cidx)[start]--; } } else { VECTOR(m->data)[end] += value; } return 0; } /* New element has to be inserted, but only if not a zero is * being added to a zero element of the matrix */ if (value != 0.0) { if (VECTOR(m->ridx)[end] < row) { IGRAPH_CHECK(igraph_vector_insert(&m->ridx, end + 1, row)); IGRAPH_CHECK(igraph_vector_insert(&m->data, end + 1, value)); } else if (VECTOR(m->ridx)[start] < row) { IGRAPH_CHECK(igraph_vector_insert(&m->ridx, start + 1, row)); IGRAPH_CHECK(igraph_vector_insert(&m->data, start + 1, value)); } else { IGRAPH_CHECK(igraph_vector_insert(&m->ridx, start, row)); IGRAPH_CHECK(igraph_vector_insert(&m->data, start, value)); } for (start = col + 1; start < m->ncol + 1; start++) { VECTOR(m->cidx)[start]++; } } return 0; } /** * \function igraph_spmatrix_add_col_values * \brief Adds the values of a column to another column. * * \param to The index of the column to be added to * \param from The index of the column to be added * \return Error code. */ int igraph_spmatrix_add_col_values(igraph_spmatrix_t *m, long int to, long int from) { long int i; /* TODO: I think this implementation could be speeded up if I don't use * igraph_spmatrix_add_e directly -- but maybe it's not worth the fuss */ for (i = (long int) VECTOR(m->cidx)[from]; i < VECTOR(m->cidx)[from + 1]; i++) { IGRAPH_CHECK(igraph_spmatrix_add_e(m, (long int) VECTOR(m->ridx)[i], to, VECTOR(m->data)[i])); } return 0; } /** * \ingroup matrix * \function igraph_spmatrix_resize * \brief Resizes a sparse matrix. * * * This function resizes a sparse matrix by adding more elements to it. * The matrix retains its data even after resizing it, except for the data * which lies outside the new boundaries (if the new size is smaller). * \param m Pointer to an already initialized sparse matrix object. * \param nrow The number of rows in the resized matrix. * \param ncol The number of columns in the resized matrix. * \return Error code. * * Time complexity: O(n). * n is the number of elements in the old matrix. */ int igraph_spmatrix_resize(igraph_spmatrix_t *m, long int nrow, long int ncol) { long int i, j, ci, ei, mincol; assert(m != NULL); /* Iterating through the matrix data and deleting unnecessary data. */ /* At the same time, we create the new indices as well */ if (nrow < m->nrow) { ei = j = 0; mincol = (m->ncol < ncol) ? m->ncol : ncol; for (ci = 0; ci < mincol; ci++) { for (; ei < VECTOR(m->cidx)[ci + 1]; ei++) { if (VECTOR(m->ridx)[ei] < nrow) { VECTOR(m->ridx)[j] = VECTOR(m->ridx)[ei]; VECTOR(m->data)[j] = VECTOR(m->data)[ei]; j++; } } VECTOR(m->cidx)[ci] = j; } /* Contract the row index and the data vector */ IGRAPH_CHECK(igraph_vector_resize(&m->ridx, j)); IGRAPH_CHECK(igraph_vector_resize(&m->cidx, j)); } /* Updating cidx */ IGRAPH_CHECK(igraph_vector_resize(&m->cidx, ncol + 1)); for (i = m->ncol + 1; i < ncol + 1; i++) { VECTOR(m->cidx)[i] = VECTOR(m->cidx)[m->ncol]; } m->nrow = nrow; m->ncol = ncol; return 0; } /** * \ingroup matrix * \function igraph_spmatrix_count_nonzero * \brief The number of non-zero elements in a sparse matrix. * * \param m Pointer to an initialized sparse matrix object. * \return The size of the matrix. * * Time complexity: O(1). */ long int igraph_spmatrix_count_nonzero(const igraph_spmatrix_t *m) { assert(m != NULL); return igraph_vector_size(&m->data); } /** * \ingroup matrix * \function igraph_spmatrix_size * \brief The number of elements in a sparse matrix. * * \param m Pointer to an initialized sparse matrix object. * \return The size of the matrix. * * Time complexity: O(1). */ long int igraph_spmatrix_size(const igraph_spmatrix_t *m) { assert(m != NULL); return (m->nrow) * (m->ncol); } /** * \ingroup matrix * \function igraph_spmatrix_nrow * \brief The number of rows in a sparse matrix. * * \param m Pointer to an initialized sparse matrix object. * \return The number of rows in the matrix. * * Time complexity: O(1). */ long int igraph_spmatrix_nrow(const igraph_spmatrix_t *m) { assert(m != NULL); return m->nrow; } /** * \ingroup matrix * \function igraph_spmatrix_ncol * \brief The number of columns in a sparse matrix. * * \param m Pointer to an initialized sparse matrix object. * \return The number of columns in the sparse matrix. * * Time complexity: O(1). */ long int igraph_spmatrix_ncol(const igraph_spmatrix_t *m) { assert(m != NULL); return m->ncol; } /** * \ingroup matrix * \brief Copies a sparse matrix to a regular C array. * * * The matrix is copied columnwise, as this is the format most * programs and languages use. * The C array should be of sufficient size, there are (of course) no * range checks done. * \param m Pointer to an initialized sparse matrix object. * \param to Pointer to a C array, the place to copy the data to. * \return Error code. * * Time complexity: O(n), * n is the number of * elements in the matrix. */ int igraph_spmatrix_copy_to(const igraph_spmatrix_t *m, igraph_real_t *to) { long int c, dest_idx, idx; memset(to, 0, sizeof(igraph_real_t) * (size_t) igraph_spmatrix_size(m)); for (c = 0, dest_idx = 0; c < m->ncol; c++, dest_idx += m->nrow) { for (idx = (long int) VECTOR(m->cidx)[c]; idx < VECTOR(m->cidx)[c + 1]; idx++) { to[dest_idx + (long)VECTOR(m->ridx)[idx]] = VECTOR(m->data)[idx]; } } return 0; } /** * \ingroup matrix * \brief Sets all element in a sparse matrix to zero. * * \param m Pointer to an initialized matrix object. * \return Error code, always returns with success. * * Time complexity: O(n), * n is the number of columns in the matrix */ int igraph_spmatrix_null(igraph_spmatrix_t *m) { assert(m != NULL); igraph_vector_clear(&m->data); igraph_vector_clear(&m->ridx); igraph_vector_null(&m->cidx); return 0; } /** * \ingroup matrix * \function igraph_spmatrix_add_cols * \brief Adds columns to a sparse matrix. * \param m The sparse matrix object. * \param n The number of columns to add. * \return Error code. * * Time complexity: O(1). */ int igraph_spmatrix_add_cols(igraph_spmatrix_t *m, long int n) { igraph_spmatrix_resize(m, m->nrow, m->ncol + n); return 0; } /** * \ingroup matrix * \function igraph_spmatrix_add_rows * \brief Adds rows to a sparse matrix. * \param m The sparse matrix object. * \param n The number of rows to add. * \return Error code. * * Time complexity: O(1). */ int igraph_spmatrix_add_rows(igraph_spmatrix_t *m, long int n) { igraph_spmatrix_resize(m, m->nrow + n, m->ncol); return 0; } /** * \function igraph_spmatrix_clear_row * \brief Clears a row in the matrix (sets all of its elements to zero) * \param m The matrix. * \param row The index of the row to be cleared. * * Time complexity: O(n), the number of nonzero elements in the matrix. */ int igraph_spmatrix_clear_row(igraph_spmatrix_t *m, long int row) { long int ci, ei, i, j, nremove = 0, nremove_old = 0; igraph_vector_t permvec; assert(m != NULL); IGRAPH_VECTOR_INIT_FINALLY(&permvec, igraph_vector_size(&m->data)); for (ci = 0, i = 0, j = 1; ci < m->ncol; ci++) { for (ei = (long int) VECTOR(m->cidx)[ci]; ei < VECTOR(m->cidx)[ci + 1]; ei++) { if (VECTOR(m->ridx)[ei] == row) { /* this element will be deleted, so all elements in cidx from the * column index of this element will have to be decreased by one */ nremove++; } else { /* this element will be kept */ VECTOR(permvec)[i] = j; j++; } i++; } if (ci > 0) { VECTOR(m->cidx)[ci] -= nremove_old; } nremove_old = nremove; } VECTOR(m->cidx)[m->ncol] -= nremove; igraph_vector_permdelete(&m->ridx, &permvec, nremove); igraph_vector_permdelete(&m->data, &permvec, nremove); igraph_vector_destroy(&permvec); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_i_spmatrix_clear_row_fast(igraph_spmatrix_t *m, long int row) { long int ei, n; assert(m != NULL); n = igraph_vector_size(&m->data); for (ei = 0; ei < n; ei++) { if (VECTOR(m->ridx)[ei] == row) { VECTOR(m->data)[ei] = 0.0; } } return 0; } int igraph_i_spmatrix_cleanup(igraph_spmatrix_t *m) { long int ci, ei, i, j, nremove = 0, nremove_old = 0; igraph_vector_t permvec; assert(m != NULL); IGRAPH_VECTOR_INIT_FINALLY(&permvec, igraph_vector_size(&m->data)); for (ci = 0, i = 0, j = 1; ci < m->ncol; ci++) { for (ei = (long int) VECTOR(m->cidx)[ci]; ei < VECTOR(m->cidx)[ci + 1]; ei++) { if (VECTOR(m->data)[ei] == 0.0) { /* this element will be deleted, so all elements in cidx from the * column index of this element will have to be decreased by one */ nremove++; } else { /* this element will be kept */ VECTOR(permvec)[i] = j; j++; } i++; } if (ci > 0) { VECTOR(m->cidx)[ci] -= nremove_old; } nremove_old = nremove; } VECTOR(m->cidx)[m->ncol] -= nremove; igraph_vector_permdelete(&m->ridx, &permvec, nremove); igraph_vector_permdelete(&m->data, &permvec, nremove); igraph_vector_destroy(&permvec); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_spmatrix_clear_col * \brief Clears a column in the matrix (sets all of its elements to zero) * \param m The matrix. * \param col The index of the column to be cleared. * \return Error code. The current implementation always succeeds. * * Time complexity: TODO */ int igraph_spmatrix_clear_col(igraph_spmatrix_t *m, long int col) { long int i, n; assert(m != NULL); n = (long)VECTOR(m->cidx)[col + 1] - (long)VECTOR(m->cidx)[col]; if (n == 0) { return 0; } igraph_vector_remove_section(&m->ridx, (long int) VECTOR(m->cidx)[col], (long int) VECTOR(m->cidx)[col + 1]); igraph_vector_remove_section(&m->data, (long int) VECTOR(m->cidx)[col], (long int) VECTOR(m->cidx)[col + 1]); for (i = col + 1; i <= m->ncol; i++) { VECTOR(m->cidx)[i] -= n; } return 0; } /** * \function igraph_spmatrix_scale * \brief Multiplies each element of the sparse matrix by a constant. * \param m The matrix. * \param by The constant. * * Time complexity: O(n), the number of elements in the matrix. */ void igraph_spmatrix_scale(igraph_spmatrix_t *m, igraph_real_t by) { assert(m != NULL); igraph_vector_scale(&m->data, by); } /** * \function igraph_spmatrix_colsums * \brief Calculates the column sums of the matrix. * \param m The matrix. * \param res An initialized \c igraph_vector_t, the result will be stored here. * The vector will be resized as needed. * * Time complexity: O(n), the number of nonzero elements in the matrix. */ int igraph_spmatrix_colsums(const igraph_spmatrix_t *m, igraph_vector_t *res) { long int i, c; assert(m != NULL); IGRAPH_CHECK(igraph_vector_resize(res, m->ncol)); igraph_vector_null(res); for (c = 0; c < m->ncol; c++) { for (i = (long int) VECTOR(m->cidx)[c]; i < VECTOR(m->cidx)[c + 1]; i++) { VECTOR(*res)[c] += VECTOR(m->data)[i]; } } return 0; } /** * \function igraph_spmatrix_rowsums * \brief Calculates the row sums of the matrix. * \param m The matrix. * \param res An initialized \c igraph_vector_t, the result will be stored here. * The vector will be resized as needed. * * Time complexity: O(n), the number of nonzero elements in the matrix. */ int igraph_spmatrix_rowsums(const igraph_spmatrix_t *m, igraph_vector_t *res) { long int i, n; assert(m != NULL); IGRAPH_CHECK(igraph_vector_resize(res, m->nrow)); n = igraph_vector_size(&m->data); igraph_vector_null(res); for (i = 0; i < n; i++) { VECTOR(*res)[(long int)VECTOR(m->ridx)[i]] += VECTOR(m->data)[i]; } return 0; } /** * \function igraph_spmatrix_max_nonzero * \brief Returns the maximum nonzero element of a matrix. * If the matrix is empty, zero is returned. * * \param m the matrix object. * \param ridx the row index of the maximum element if not \c NULL. * \param cidx the column index of the maximum element if not \c NULL. * * Time complexity: O(n), the number of nonzero elements in the matrix. */ igraph_real_t igraph_spmatrix_max_nonzero(const igraph_spmatrix_t *m, igraph_real_t *ridx, igraph_real_t *cidx) { igraph_real_t res; long int i, n, maxidx; assert(m != NULL); n = igraph_vector_size(&m->data); if (n == 0) { return 0.0; } maxidx = -1; for (i = 0; i < n; i++) if (VECTOR(m->data)[i] != 0.0 && (maxidx == -1 || VECTOR(m->data)[i] >= VECTOR(m->data)[maxidx])) { maxidx = i; } if (maxidx == -1) { return 0.0; } res = VECTOR(m->data)[maxidx]; if (ridx != 0) { *ridx = VECTOR(m->ridx)[maxidx]; } if (cidx != 0) { igraph_vector_binsearch(&m->cidx, maxidx, &i); while (VECTOR(m->cidx)[i + 1] == VECTOR(m->cidx)[i]) { i++; } *cidx = (igraph_real_t)i; } return res; } /** * \function igraph_spmatrix_max * \brief Returns the maximum element of a matrix. * If the matrix is empty, zero is returned. * * \param m the matrix object. * \param ridx the row index of the maximum element if not \c NULL. * \param cidx the column index of the maximum element if not \c NULL. * * Time complexity: O(n), the number of nonzero elements in the matrix. */ igraph_real_t igraph_spmatrix_max(const igraph_spmatrix_t *m, igraph_real_t *ridx, igraph_real_t *cidx) { igraph_real_t res; long int i, j, k, maxidx; assert(m != NULL); i = igraph_vector_size(&m->data); if (i == 0) { return 0.0; } maxidx = (long)igraph_vector_which_max(&m->data); res = VECTOR(m->data)[maxidx]; if (res >= 0.0 || i == m->nrow * m->ncol) { if (ridx != 0) { *ridx = VECTOR(m->ridx)[maxidx]; } if (cidx != 0) { igraph_vector_binsearch(&m->cidx, maxidx, &i); i--; while (i < m->ncol - 1 && VECTOR(m->cidx)[i + 1] == VECTOR(m->cidx)[i]) { i++; } *cidx = (igraph_real_t)i; } return res; } /* the maximal nonzero element is negative and there is at least a * single zero */ res = 0.0; if (cidx != 0 || ridx != 0) { for (i = 0; i < m->ncol; i++) { if (VECTOR(m->cidx)[i + 1] - VECTOR(m->cidx)[i] < m->nrow) { if (cidx != 0) { *cidx = i; } if (ridx != 0) { for (j = (long int) VECTOR(m->cidx)[i], k = 0; j < VECTOR(m->cidx)[i + 1]; j++, k++) { if (VECTOR(m->ridx)[j] != k) { *ridx = k; break; } } } break; } } } return res; } int igraph_i_spmatrix_get_col_nonzero_indices(const igraph_spmatrix_t *m, igraph_vector_t *res, long int col) { long int i, n; assert(m != NULL); n = (long int) (VECTOR(m->cidx)[col + 1] - VECTOR(m->cidx)[col]); IGRAPH_CHECK(igraph_vector_resize(res, n)); for (i = (long int) VECTOR(m->cidx)[col], n = 0; i < VECTOR(m->cidx)[col + 1]; i++, n++) if (VECTOR(m->data)[i] != 0.0) { VECTOR(*res)[n] = VECTOR(m->ridx)[i]; } return 0; } /** * \section igraph_spmatrix_iterating Iterating over the non-zero elements of a sparse matrix * * The \type igraph_spmatrix_iter_t type represents an iterator that can * be used to step over the non-zero elements of a sparse matrix in columnwise * order efficiently. In general, you shouldn't modify the elements of the matrix * while iterating over it; doing so will probably invalidate the iterator, but * there are no checks to prevent you from doing this. * * To access the row index of the current element of the iterator, use its * \c ri field. Similarly, the \c ci field stores the column index of the current * element and the \c value field stores the value of the element. */ /** * \function igraph_spmatrix_iter_create * \brief Creates a sparse matrix iterator corresponding to the given matrix. * * \param mit pointer to the matrix iterator being initialized * \param m pointer to the matrix we will be iterating over * \return Error code. The current implementation is always successful. * * Time complexity: O(1). */ int igraph_spmatrix_iter_create(igraph_spmatrix_iter_t *mit, const igraph_spmatrix_t *m) { mit->m = m; IGRAPH_CHECK(igraph_spmatrix_iter_reset(mit)); return 0; } /** * \function igraph_spmatrix_iter_reset * \brief Resets a sparse matrix iterator. * * * After resetting, the iterator will point to the first nonzero element (if any). * * \param mit pointer to the matrix iterator being reset * \return Error code. The current implementation is always successful. * * Time complexity: O(1). */ int igraph_spmatrix_iter_reset(igraph_spmatrix_iter_t *mit) { assert(mit->m); if (igraph_spmatrix_count_nonzero(mit->m) == 0) { mit->pos = mit->ri = mit->ci = -1L; mit->value = -1; return 0; } mit->ci = 0; mit->pos = -1; IGRAPH_CHECK(igraph_spmatrix_iter_next(mit)); return 0; } /** * \function igraph_spmatrix_iter_next * \brief Moves a sparse matrix iterator to the next nonzero element. * * * You should call this function only if \ref igraph_spmatrix_iter_end() * returns FALSE (0). * * \param mit pointer to the matrix iterator being moved * \return Error code. The current implementation is always successful. * * Time complexity: O(1). */ int igraph_spmatrix_iter_next(igraph_spmatrix_iter_t *mit) { mit->pos++; if (igraph_spmatrix_iter_end(mit)) { return 0; } mit->ri = (long int)VECTOR(mit->m->ridx)[mit->pos]; mit->value = VECTOR(mit->m->data)[mit->pos]; while (VECTOR(mit->m->cidx)[mit->ci + 1] <= mit->pos) { mit->ci++; } return 0; } /** * \function igraph_spmatrix_iter_end * \brief Checks whether there are more elements in the iterator. * * * You should call this function before calling \ref igraph_spmatrix_iter_next() * to make sure you have more elements in the iterator. * * \param mit pointer to the matrix iterator being checked * \return TRUE (1) if there are more elements in the iterator, * FALSE (0) otherwise. * * Time complexity: O(1). */ igraph_bool_t igraph_spmatrix_iter_end(igraph_spmatrix_iter_t *mit) { return mit->pos >= igraph_spmatrix_count_nonzero(mit->m); } /** * \function igraph_spmatrix_iter_destroy * \brief Frees the memory used by the iterator. * * * The current implementation does not allocate any memory upon * creation, so this function does nothing. However, since there is * no guarantee that future implementations will not allocate any * memory in \ref igraph_spmatrix_iter_create(), you are still * required to call this function whenever you are done with the * iterator. * * \param mit pointer to the matrix iterator being destroyed * * Time complexity: O(1). */ void igraph_spmatrix_iter_destroy(igraph_spmatrix_iter_t *mit) { IGRAPH_UNUSED(mit); /* Nothing to do at the moment */ } #ifndef USING_R /** * \function igraph_spmatrix_print * \brief Prints a sparse matrix. * * Prints a sparse matrix to the standard output. Only the non-zero entries * are printed. * * \return Error code. * * Time complexity: O(n), the number of non-zero elements. */ int igraph_spmatrix_print(const igraph_spmatrix_t* matrix) { return igraph_spmatrix_fprint(matrix, stdout); } #endif /** * \function igraph_spmatrix_fprint * \brief Prints a sparse matrix to the given file. * * Prints a sparse matrix to the given file. Only the non-zero entries * are printed. * * \return Error code. * * Time complexity: O(n), the number of non-zero elements. */ int igraph_spmatrix_fprint(const igraph_spmatrix_t* matrix, FILE *file) { igraph_spmatrix_iter_t mit; IGRAPH_CHECK(igraph_spmatrix_iter_create(&mit, matrix)); IGRAPH_FINALLY(igraph_spmatrix_iter_destroy, &mit); while (!igraph_spmatrix_iter_end(&mit)) { fprintf(file, "[%ld, %ld] = %.4f\n", (long int)mit.ri, (long int)mit.ci, mit.value); igraph_spmatrix_iter_next(&mit); } igraph_spmatrix_iter_destroy(&mit); IGRAPH_FINALLY_CLEAN(1); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/walktrap.cpp0000644000076500000240000001524713614300625023740 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ /* The original version of this file was written by Pascal Pons The original copyright notice follows here. The FSF address was fixed by Tamas Nepusz */ // File: walktrap.cpp //----------------------------------------------------------------------------- // Walktrap v0.2 -- Finds community structure of networks using random walks // Copyright (C) 2004-2005 Pascal Pons // // This program is free software; you can redistribute it and/or modify // it under the terms of the GNU General Public License as published by // the Free Software Foundation; either version 2 of the License, or // (at your option) any later version. // // This program is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU General Public License for more details. // // You should have received a copy of the GNU General Public License // along with this program; if not, write to the Free Software // Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA // 02110-1301 USA //----------------------------------------------------------------------------- // Author : Pascal Pons // Email : pascal.pons@gmail.com // Web page : http://www-rp.lip6.fr/~latapy/PP/walktrap.html // Location : Paris, France // Time : June 2005 //----------------------------------------------------------------------------- // see readme.txt for more details #include "walktrap_graph.h" #include "walktrap_communities.h" #include #include #include #include #include #include "igraph_community.h" #include "igraph_components.h" #include "igraph_interface.h" #include "igraph_interrupt_internal.h" using namespace std; using namespace igraph::walktrap; /** * \function igraph_community_walktrap * * This function is the implementation of the Walktrap community * finding algorithm, see Pascal Pons, Matthieu Latapy: Computing * communities in large networks using random walks, * http://arxiv.org/abs/physics/0512106 * * * Currently the original C++ implementation is used in igraph, * see http://www-rp.lip6.fr/~latapy/PP/walktrap.html * I'm grateful to Matthieu Latapy and Pascal Pons for providing this * source code. * * * In contrast to the original implementation, isolated vertices are allowed * in the graph and they are assumed to have a single incident loop edge with * weight 1. * * \param graph The input graph, edge directions are ignored. * \param weights Numeric vector giving the weights of the edges. * If it is a NULL pointer then all edges will have equal * weights. The weights are expected to be positive. * \param steps Integer constant, the length of the random walks. * \param merges Pointer to a matrix, the merges performed by the * algorithm will be stored here (if not NULL). Each merge is a * row in a two-column matrix and contains the ids of the merged * clusters. Clusters are numbered from zero and cluster numbers * smaller than the number of nodes in the network belong to the * individual vertices as singleton clusters. In each step a new * cluster is created from two other clusters and its id will be * one larger than the largest cluster id so far. This means that * before the first merge we have \c n clusters (the number of * vertices in the graph) numbered from zero to \c n-1. The first * merge creates cluster \c n, the second cluster \c n+1, etc. * \param modularity Pointer to a vector. If not NULL then the * modularity score of the current clustering is stored here after * each merge operation. * \param membership Pointer to a vector. If not a NULL pointer, then * the membership vector corresponding to the maximal modularity * score is stored here. If it is not a NULL pointer, then neither * \p modularity nor \p merges may be NULL. * \return Error code. * * \sa \ref igraph_community_spinglass(), \ref * igraph_community_edge_betweenness(). * * Time complexity: O(|E||V|^2) in the worst case, O(|V|^2 log|V|) typically, * |V| is the number of vertices, |E| is the number of edges. * * \example examples/simple/walktrap.c */ int igraph_community_walktrap(const igraph_t *graph, const igraph_vector_t *weights, int steps, igraph_matrix_t *merges, igraph_vector_t *modularity, igraph_vector_t *membership) { long int no_of_nodes = (long int)igraph_vcount(graph); int length = steps; long max_memory = -1; if (membership && !(modularity && merges)) { IGRAPH_ERROR("Cannot calculate membership without modularity or merges", IGRAPH_EINVAL); } Graph* G = new Graph; if (G->convert_from_igraph(graph, weights)) { IGRAPH_ERROR("Cannot convert igraph graph into walktrap format", IGRAPH_EINVAL); } if (merges) { igraph_integer_t no; IGRAPH_CHECK(igraph_clusters(graph, /*membership=*/ 0, /*csize=*/ 0, &no, IGRAPH_WEAK)); IGRAPH_CHECK(igraph_matrix_resize(merges, no_of_nodes - no, 2)); } if (modularity) { IGRAPH_CHECK(igraph_vector_resize(modularity, no_of_nodes)); igraph_vector_null(modularity); } Communities C(G, length, max_memory, merges, modularity); while (!C.H->is_empty()) { IGRAPH_ALLOW_INTERRUPTION(); C.merge_nearest_communities(); } delete G; if (membership) { long int m = igraph_vector_which_max(modularity); IGRAPH_CHECK(igraph_community_to_membership(merges, no_of_nodes, /*steps=*/ m, membership, /*csize=*/ 0)); } return 0; } python-igraph-0.8.0/vendor/source/igraph/src/atlas-edges.h0000644000076500000240000027450313614300625023753 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #undef __BEGIN_DECLS #undef __END_DECLS #ifdef __cplusplus #define __BEGIN_DECLS extern "C" { #define __END_DECLS } #else #define __BEGIN_DECLS /* empty */ #define __END_DECLS /* empty */ #endif __BEGIN_DECLS #include "igraph_types.h" const igraph_real_t igraph_i_atlas_edges[] = { 0, 0, 1, 0, 2, 0, 2, 1, 0, 1, 3, 0, 3, 1, 1, 2, 3, 2, 0, 1, 0, 2, 3, 3, 0, 1, 0, 2, 1, 2, 4, 0, 4, 1, 3, 2, 4, 2, 3, 2, 3, 1, 4, 2, 0, 1, 3, 2, 4, 3, 3, 2, 1, 2, 3, 1, 4, 3, 3, 0, 3, 1, 3, 2, 4, 3, 0, 1, 1, 2, 0, 3, 4, 4, 3, 2, 1, 2, 3, 1, 3, 0, 4, 4, 0, 1, 1, 2, 2, 3, 0, 3, 4, 5, 0, 1, 0, 2, 0, 3, 1, 2, 2, 3, 4, 6, 0, 1, 1, 2, 0, 2, 3, 0, 3, 1, 3, 2, 5, 0, 5, 1, 4, 3, 5, 2, 1, 2, 0, 1, 5, 2, 0, 2, 4, 3, 5, 3, 1, 2, 0, 1, 2, 0, 5, 3, 4, 3, 3, 2, 3, 1, 5, 3, 3, 2, 4, 3, 0, 4, 5, 3, 1, 2, 0, 1, 4, 3, 5, 4, 4, 3, 1, 2, 3, 1, 3, 2, 5, 4, 0, 3, 1, 0, 2, 1, 3, 2, 5, 4, 4, 3, 4, 0, 4, 1, 4, 2, 5, 4, 4, 0, 3, 1, 4, 3, 3, 2, 5, 4, 2, 3, 1, 2, 0, 1, 4, 0, 5, 4, 1, 2, 0, 1, 2, 0, 4, 3, 5, 5, 0, 3, 2, 0, 3, 2, 1, 0, 2, 1, 5, 5, 4, 2, 4, 3, 2, 3, 4, 1, 4, 0, 5, 5, 0, 1, 1, 2, 2, 3, 0, 4, 0, 2, 5, 5, 4, 0, 1, 2, 4, 3, 3, 2, 3, 1, 5, 5, 1, 0, 4, 1, 2, 4, 3, 2, 1, 3, 5, 5, 0, 1, 1, 2, 2, 3, 3, 4, 0, 4, 5, 6, 1, 0, 4, 1, 4, 0, 0, 3, 1, 3, 3, 4, 5, 6, 1, 0, 4, 1, 2, 4, 3, 2, 1, 3, 2, 1, 5, 6, 1, 0, 4, 1, 2, 4, 3, 2, 1, 3, 3, 4, 5, 6, 0, 1, 4, 3, 2, 3, 4, 2, 4, 0, 4, 1, 5, 6, 0, 4, 3, 0, 4, 3, 2, 3, 1, 2, 0, 1, 5, 6, 2, 1, 0, 2, 3, 0, 1, 3, 4, 1, 0, 4, 5, 7, 4, 0, 1, 2, 4, 3, 3, 2, 3, 1, 4, 1, 2, 4, 5, 7, 4, 1, 2, 4, 3, 2, 1, 3, 3, 4, 0, 3, 4, 0, 5, 7, 0, 1, 1, 2, 2, 3, 3, 4, 0, 4, 1, 3, 4, 1, 5, 7, 2, 1, 0, 2, 3, 0, 1, 3, 4, 1, 0, 4, 2, 4, 5, 8, 1, 0, 4, 1, 2, 4, 3, 2, 1, 3, 4, 0, 3, 4, 0, 3, 5, 8, 0, 1, 1, 2, 2, 3, 0, 3, 4, 0, 4, 1, 4, 2, 4, 3, 5, 9, 0, 1, 3, 4, 0, 3, 0, 4, 1, 2, 1, 3, 1, 4, 2, 3, 2, 4, 5, 10, 0, 1, 0, 2, 0, 3, 0, 4, 1, 2, 1, 3, 1, 4, 2, 3, 2, 4, 3, 4, 6, 0, 6, 1, 5, 4, 6, 2, 0, 3, 5, 4, 6, 2, 1, 3, 1, 2, 6, 3, 1, 3, 2, 1, 3, 2, 6, 3, 0, 3, 5, 0, 4, 0, 6, 3, 4, 3, 5, 4, 0, 5, 6, 3, 4, 3, 5, 1, 5, 2, 6, 3, 1, 2, 3, 0, 5, 4, 6, 4, 0, 3, 4, 0, 5, 4, 0, 5, 6, 4, 3, 0, 5, 3, 4, 5, 0, 4, 6, 4, 5, 1, 5, 3, 5, 2, 0, 5, 6, 4, 4, 3, 3, 1, 4, 0, 3, 2, 6, 4, 0, 2, 1, 3, 2, 1, 5, 3, 6, 4, 1, 3, 2, 1, 3, 2, 0, 5, 6, 4, 1, 2, 0, 3, 5, 0, 4, 0, 6, 4, 4, 5, 1, 2, 0, 5, 3, 4, 6, 4, 0, 2, 4, 0, 3, 1, 5, 3, 6, 5, 3, 0, 5, 3, 4, 5, 0, 4, 5, 0, 6, 5, 5, 3, 3, 1, 3, 2, 4, 3, 4, 5, 6, 5, 5, 3, 5, 4, 2, 3, 3, 4, 0, 4, 6, 5, 4, 3, 1, 2, 4, 0, 3, 2, 3, 1, 6, 5, 1, 4, 3, 4, 4, 0, 2, 1, 3, 2, 6, 5, 0, 1, 1, 2, 2, 3, 3, 4, 0, 4, 6, 5, 5, 3, 5, 4, 5, 0, 5, 1, 5, 2, 6, 5, 1, 4, 5, 1, 1, 0, 2, 1, 2, 3, 6, 5, 0, 1, 3, 4, 0, 2, 3, 0, 5, 3, 6, 5, 1, 0, 2, 1, 2, 4, 1, 3, 5, 3, 6, 5, 4, 3, 0, 5, 4, 0, 3, 2, 3, 1, 6, 5, 1, 2, 0, 1, 4, 5, 1, 3, 2, 3, 6, 5, 0, 1, 0, 5, 2, 3, 3, 4, 4, 5, 6, 5, 4, 3, 5, 1, 5, 2, 0, 3, 4, 0, 6, 5, 1, 2, 3, 0, 5, 3, 4, 5, 0, 4, 6, 6, 0, 3, 5, 0, 4, 5, 3, 4, 5, 3, 4, 0, 6, 6, 1, 4, 2, 4, 4, 0, 2, 3, 3, 1, 3, 4, 6, 6, 1, 4, 2, 4, 4, 0, 2, 1, 3, 1, 2, 3, 6, 6, 2, 0, 5, 4, 4, 3, 5, 3, 4, 0, 2, 4, 6, 6, 3, 2, 4, 3, 0, 4, 1, 0, 2, 1, 0, 3, 6, 6, 4, 1, 3, 1, 4, 2, 3, 2, 2, 0, 1, 0, 6, 6, 5, 2, 5, 3, 5, 4, 3, 4, 5, 1, 5, 0, 6, 6, 4, 3, 4, 2, 4, 0, 1, 4, 3, 0, 5, 3, 6, 6, 4, 3, 3, 5, 5, 4, 5, 1, 3, 2, 4, 0, 6, 6, 4, 2, 1, 2, 4, 3, 4, 1, 4, 0, 0, 5, 6, 6, 1, 2, 3, 1, 0, 3, 2, 0, 4, 0, 5, 0, 6, 6, 2, 0, 4, 2, 1, 4, 2, 1, 3, 1, 5, 3, 6, 6, 1, 2, 3, 1, 0, 3, 2, 0, 4, 0, 5, 3, 6, 6, 5, 3, 2, 5, 2, 0, 4, 2, 4, 3, 3, 1, 6, 6, 0, 2, 3, 4, 1, 0, 5, 3, 4, 5, 3, 0, 6, 6, 1, 2, 3, 0, 5, 3, 4, 5, 0, 4, 5, 0, 6, 6, 4, 3, 1, 2, 4, 0, 3, 2, 3, 1, 5, 0, 6, 6, 1, 4, 2, 4, 4, 0, 0, 5, 3, 1, 2, 3, 6, 6, 0, 1, 1, 2, 2, 3, 3, 4, 0, 4, 1, 5, 6, 6, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 0, 5, 6, 6, 1, 3, 2, 1, 3, 2, 0, 4, 5, 0, 4, 5, 6, 7, 0, 1, 1, 2, 0, 2, 3, 0, 3, 1, 3, 2, 0, 5, 6, 7, 1, 4, 2, 4, 2, 1, 3, 1, 2, 3, 2, 0, 0, 1, 6, 7, 0, 1, 1, 2, 2, 3, 3, 4, 0, 4, 1, 3, 4, 1, 6, 7, 0, 1, 3, 2, 0, 2, 3, 0, 3, 1, 5, 1, 5, 2, 6, 7, 1, 4, 2, 4, 2, 3, 0, 4, 3, 1, 4, 5, 3, 4, 6, 7, 1, 0, 4, 1, 2, 4, 3, 2, 5, 1, 2, 5, 1, 2, 6, 7, 0, 4, 2, 0, 1, 2, 3, 1, 5, 3, 3, 0, 2, 3, 6, 7, 1, 4, 2, 4, 2, 3, 2, 1, 3, 1, 4, 5, 0, 4, 6, 7, 1, 0, 4, 1, 2, 4, 3, 2, 5, 1, 2, 5, 4, 5, 6, 7, 0, 1, 1, 2, 0, 2, 3, 0, 3, 1, 3, 2, 5, 4, 6, 7, 0, 5, 4, 0, 5, 4, 0, 2, 3, 0, 3, 2, 0, 1, 6, 7, 0, 1, 1, 2, 2, 3, 3, 4, 0, 4, 1, 5, 4, 1, 6, 7, 0, 1, 4, 0, 1, 4, 0, 2, 3, 0, 3, 2, 3, 5, 6, 7, 1, 4, 2, 4, 4, 0, 0, 5, 3, 1, 2, 3, 3, 4, 6, 7, 2, 0, 3, 2, 4, 3, 5, 4, 2, 5, 1, 2, 4, 1, 6, 7, 1, 5, 0, 1, 4, 0, 3, 4, 2, 3, 1, 2, 0, 3, 6, 7, 1, 4, 2, 4, 4, 0, 0, 5, 3, 1, 2, 3, 2, 1, 6, 7, 0, 1, 1, 2, 2, 3, 3, 4, 0, 4, 0, 2, 5, 1, 6, 7, 2, 0, 4, 1, 1, 2, 5, 4, 2, 5, 3, 1, 5, 3, 6, 7, 5, 0, 3, 5, 2, 3, 0, 2, 1, 3, 4, 1, 3, 4, 6, 7, 1, 3, 2, 1, 0, 2, 5, 0, 4, 5, 3, 4, 2, 3, 6, 7, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 0, 5, 0, 3, 6, 7, 4, 3, 0, 4, 1, 0, 2, 1, 3, 2, 0, 5, 5, 3, 6, 7, 1, 2, 0, 1, 2, 0, 3, 0, 4, 3, 5, 4, 3, 5, 6, 8, 0, 1, 2, 5, 0, 2, 3, 0, 3, 1, 3, 2, 2, 1, 5, 1, 6, 8, 0, 1, 1, 2, 2, 3, 0, 3, 4, 0, 4, 1, 4, 2, 4, 3, 6, 8, 0, 1, 1, 2, 0, 2, 3, 0, 3, 1, 3, 2, 5, 0, 0, 4, 6, 8, 1, 2, 3, 1, 0, 3, 1, 0, 2, 0, 3, 2, 5, 3, 4, 0, 6, 8, 0, 1, 2, 4, 0, 2, 5, 2, 3, 1, 3, 2, 2, 1, 4, 1, 6, 8, 0, 1, 1, 2, 2, 3, 3, 4, 0, 4, 1, 3, 4, 1, 1, 5, 6, 8, 0, 1, 1, 2, 2, 3, 3, 4, 0, 4, 1, 3, 4, 1, 5, 4, 6, 8, 0, 1, 2, 5, 0, 2, 4, 0, 3, 1, 3, 2, 2, 1, 5, 1, 6, 8, 0, 1, 1, 2, 2, 3, 3, 4, 0, 4, 1, 3, 4, 1, 5, 0, 6, 8, 0, 1, 2, 5, 0, 2, 4, 0, 3, 1, 3, 2, 3, 0, 5, 1, 6, 8, 2, 0, 3, 2, 4, 3, 5, 4, 2, 5, 1, 2, 4, 1, 5, 3, 6, 8, 0, 1, 1, 2, 0, 2, 3, 0, 3, 1, 3, 2, 0, 5, 5, 4, 6, 8, 0, 1, 2, 5, 0, 2, 4, 0, 3, 1, 3, 2, 5, 1, 5, 3, 6, 8, 1, 4, 2, 4, 2, 3, 0, 4, 3, 1, 4, 5, 0, 5, 3, 4, 6, 8, 0, 1, 1, 2, 2, 3, 3, 4, 0, 4, 5, 0, 5, 2, 0, 2, 6, 8, 1, 5, 4, 1, 0, 4, 5, 0, 2, 5, 4, 2, 3, 4, 5, 3, 6, 8, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 0, 5, 2, 4, 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5, 0, 6, 3, 6, 4, 6, 5, 6, 1, 5, 3, 5, 2, 3, 2, 4, 1, 6, 0, 1, 7, 15, 3, 4, 4, 5, 0, 3, 0, 4, 0, 5, 0, 6, 3, 6, 1, 3, 1, 4, 1, 5, 3, 5, 2, 3, 2, 4, 6, 1, 4, 6, 7, 15, 0, 1, 1, 2, 2, 3, 0, 3, 4, 0, 4, 1, 4, 2, 4, 3, 5, 1, 0, 5, 5, 2, 3, 5, 4, 5, 6, 1, 5, 6, 7, 15, 4, 3, 4, 5, 5, 3, 0, 1, 0, 5, 0, 3, 2, 4, 1, 5, 1, 3, 6, 5, 3, 6, 6, 0, 1, 6, 6, 2, 4, 6, 7, 15, 3, 4, 4, 5, 5, 6, 0, 4, 0, 5, 0, 6, 3, 6, 1, 3, 4, 6, 1, 5, 3, 5, 2, 3, 2, 4, 1, 6, 0, 1, 7, 15, 0, 2, 0, 6, 1, 3, 1, 4, 1, 5, 1, 6, 2, 3, 2, 4, 2, 5, 3, 4, 3, 5, 3, 6, 4, 5, 4, 6, 5, 6, 7, 15, 6, 1, 4, 5, 0, 3, 0, 4, 0, 5, 0, 6, 3, 6, 1, 3, 1, 4, 1, 5, 3, 5, 2, 3, 2, 4, 5, 6, 4, 6, 7, 15, 3, 4, 4, 5, 0, 3, 0, 4, 0, 5, 4, 6, 3, 6, 1, 3, 1, 4, 1, 5, 3, 5, 2, 3, 2, 4, 5, 6, 5, 2, 7, 15, 3, 4, 4, 5, 0, 3, 0, 4, 6, 0, 4, 6, 3, 6, 1, 3, 1, 4, 1, 5, 3, 5, 2, 3, 2, 4, 5, 6, 5, 2, 7, 15, 0, 1, 1, 2, 0, 2, 3, 0, 1, 3, 2, 3, 5, 1, 3, 5, 4, 3, 2, 4, 6, 2, 3, 6, 6, 1, 0, 5, 4, 0, 7, 15, 0, 1, 2, 0, 3, 2, 4, 3, 1, 4, 3, 1, 4, 2, 0, 4, 3, 0, 6, 3, 4, 6, 5, 4, 3, 5, 6, 2, 5, 1, 7, 15, 0, 1, 0, 2, 0, 3, 0, 4, 1, 2, 1, 3, 1, 4, 2, 3, 2, 4, 3, 4, 5, 3, 4, 5, 6, 4, 5, 6, 6, 3, 7, 15, 0, 1, 1, 2, 2, 3, 0, 3, 4, 0, 4, 3, 4, 2, 6, 1, 2, 6, 5, 2, 4, 5, 6, 4, 0, 6, 6, 5, 3, 6, 7, 15, 0, 1, 5, 3, 1, 3, 0, 4, 3, 0, 4, 3, 2, 4, 5, 2, 4, 5, 6, 4, 2, 6, 6, 5, 3, 6, 6, 1, 0, 6, 7, 15, 5, 2, 4, 5, 3, 1, 0, 4, 0, 5, 0, 3, 2, 4, 1, 5, 1, 4, 6, 3, 1, 6, 6, 0, 5, 6, 6, 2, 4, 6, 7, 15, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 0, 5, 0, 3, 2, 0, 3, 1, 6, 4, 5, 6, 6, 3, 0, 6, 6, 2, 1, 6, 7, 15, 5, 2, 3, 0, 5, 3, 0, 4, 0, 5, 4, 3, 2, 4, 1, 5, 1, 4, 6, 4, 2, 6, 6, 0, 5, 6, 6, 3, 1, 6, 7, 15, 0, 4, 0, 5, 0, 6, 1, 2, 1, 3, 1, 6, 2, 3, 2, 4, 2, 5, 3, 4, 3, 5, 3, 6, 4, 5, 4, 6, 5, 6, 7, 15, 6, 1, 4, 5, 0, 3, 0, 4, 0, 5, 4, 6, 3, 6, 1, 3, 1, 4, 0, 6, 3, 5, 2, 3, 2, 4, 5, 6, 5, 2, 7, 15, 3, 4, 0, 1, 0, 3, 0, 4, 0, 5, 4, 6, 3, 6, 1, 3, 1, 4, 6, 0, 1, 6, 2, 3, 2, 4, 5, 6, 5, 2, 7, 15, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 1, 5, 1, 6, 2, 4, 2, 5, 2, 6, 3, 4, 3, 5, 3, 6, 4, 6, 7, 15, 5, 2, 4, 5, 5, 3, 0, 4, 0, 1, 1, 3, 2, 4, 3, 0, 1, 4, 6, 4, 1, 6, 6, 0, 3, 6, 6, 2, 5, 6, 7, 15, 5, 0, 4, 3, 5, 3, 5, 2, 0, 1, 1, 3, 2, 4, 3, 0, 1, 4, 6, 2, 5, 6, 6, 4, 3, 6, 6, 0, 1, 6, 7, 15, 3, 4, 4, 5, 0, 3, 4, 6, 0, 1, 1, 6, 3, 6, 1, 3, 1, 4, 6, 0, 0, 5, 2, 3, 2, 4, 5, 6, 5, 2, 7, 15, 0, 2, 0, 3, 0, 6, 1, 3, 1, 4, 1, 5, 1, 6, 2, 4, 2, 5, 2, 6, 3, 4, 3, 5, 4, 5, 4, 6, 5, 6, 7, 15, 0, 4, 0, 5, 0, 6, 1, 3, 1, 4, 1, 5, 1, 6, 2, 3, 2, 4, 2, 5, 2, 6, 3, 5, 3, 6, 4, 5, 4, 6, 7, 15, 3, 4, 5, 0, 0, 3, 0, 4, 4, 6, 1, 6, 3, 6, 1, 3, 1, 4, 6, 0, 1, 5, 2, 3, 2, 4, 5, 6, 5, 2, 7, 15, 6, 4, 5, 2, 0, 3, 0, 4, 2, 4, 1, 6, 3, 6, 1, 3, 1, 4, 6, 0, 3, 5, 2, 3, 0, 1, 5, 6, 4, 5, 7, 15, 0, 4, 0, 5, 0, 6, 1, 2, 1, 3, 1, 5, 1, 6, 2, 3, 2, 4, 2, 6, 3, 4, 3, 5, 4, 5, 4, 6, 5, 6, 7, 15, 0, 1, 0, 2, 0, 3, 1, 4, 1, 5, 1, 6, 2, 4, 2, 5, 2, 6, 3, 4, 3, 5, 3, 6, 4, 5, 4, 6, 5, 6, 7, 15, 2, 3, 0, 2, 3, 0, 4, 3, 1, 4, 5, 1, 4, 5, 1, 0, 5, 2, 6, 2, 5, 6, 6, 1, 0, 6, 6, 4, 3, 6, 7, 15, 3, 0, 3, 5, 3, 4, 2, 0, 2, 5, 2, 4, 1, 4, 1, 5, 1, 0, 6, 0, 1, 6, 6, 5, 3, 6, 6, 4, 2, 6, 7, 15, 0, 3, 0, 4, 0, 5, 0, 6, 1, 2, 1, 4, 1, 5, 1, 6, 2, 3, 2, 5, 2, 6, 3, 4, 3, 6, 4, 5, 5, 6, 7, 15, 3, 4, 6, 2, 0, 3, 0, 4, 5, 0, 1, 6, 3, 6, 1, 3, 1, 4, 6, 0, 4, 5, 2, 3, 2, 4, 5, 1, 5, 2, 7, 15, 3, 4, 6, 2, 0, 3, 0, 4, 5, 0, 5, 6, 3, 6, 1, 3, 1, 4, 0, 1, 4, 6, 2, 3, 2, 4, 5, 1, 5, 2, 7, 15, 0, 1, 1, 2, 2, 3, 3, 4, 0, 4, 6, 2, 1, 6, 6, 0, 4, 6, 5, 4, 0, 5, 3, 5, 6, 3, 5, 2, 1, 5, 7, 16, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 1, 2, 1, 3, 1, 4, 1, 5, 2, 3, 2, 4, 2, 5, 3, 4, 3, 5, 4, 5, 2, 6, 7, 16, 3, 0, 4, 1, 4, 3, 1, 3, 4, 0, 2, 5, 6, 2, 5, 6, 1, 5, 4, 5, 3, 5, 0, 5, 0, 6, 3, 6, 4, 6, 6, 1, 7, 16, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 1, 6, 2, 3, 2, 4, 2, 5, 3, 4, 3, 5, 3, 6, 4, 5, 4, 6, 5, 6, 7, 16, 0, 5, 0, 6, 1, 2, 1, 3, 1, 4, 1, 5, 1, 6, 2, 3, 2, 4, 2, 5, 2, 6, 3, 4, 3, 5, 3, 6, 4, 5, 4, 6, 7, 16, 3, 4, 5, 1, 0, 3, 0, 4, 5, 0, 4, 6, 3, 6, 1, 3, 1, 4, 6, 0, 3, 5, 2, 3, 2, 4, 5, 6, 4, 5, 2, 5, 7, 16, 2, 4, 3, 1, 3, 0, 4, 3, 4, 0, 5, 2, 4, 5, 5, 0, 3, 5, 5, 1, 6, 5, 1, 6, 3, 6, 6, 0, 4, 6, 6, 2, 7, 16, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 1, 5, 1, 6, 2, 3, 2, 4, 3, 4, 3, 5, 3, 6, 4, 5, 4, 6, 5, 6, 7, 16, 2, 4, 4, 1, 3, 0, 3, 1, 4, 0, 5, 2, 4, 5, 5, 0, 3, 5, 6, 5, 1, 5, 6, 1, 3, 6, 4, 6, 6, 2, 6, 0, 7, 16, 0, 1, 0, 3, 0, 5, 0, 6, 1, 3, 1, 5, 1, 6, 2, 4, 2, 5, 2, 6, 3, 4, 3, 5, 3, 6, 4, 5, 4, 6, 5, 6, 7, 16, 2, 5, 0, 1, 4, 5, 1, 3, 5, 0, 4, 3, 5, 3, 2, 4, 1, 4, 3, 0, 6, 3, 2, 6, 6, 4, 5, 6, 6, 1, 0, 6, 7, 16, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 1, 3, 1, 6, 2, 4, 2, 5, 2, 6, 3, 4, 3, 5, 4, 5, 4, 6, 5, 6, 7, 16, 2, 5, 5, 1, 3, 1, 0, 4, 5, 0, 4, 3, 5, 3, 2, 4, 1, 4, 3, 0, 6, 2, 4, 6, 5, 6, 6, 1, 0, 6, 3, 6, 7, 16, 1, 6, 0, 1, 0, 3, 0, 4, 5, 0, 4, 6, 3, 6, 1, 3, 1, 4, 6, 0, 3, 5, 2, 3, 2, 4, 5, 6, 4, 5, 2, 5, 7, 16, 3, 4, 5, 1, 0, 3, 0, 4, 5, 0, 4, 6, 3, 6, 1, 3, 1, 4, 6, 0, 1, 6, 2, 3, 2, 4, 5, 6, 0, 1, 2, 5, 7, 16, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 1, 2, 1, 3, 1, 4, 1, 5, 1, 6, 2, 5, 2, 6, 3, 4, 3, 6, 4, 5, 7, 16, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 1, 4, 1, 5, 1, 6, 2, 3, 2, 5, 2, 6, 3, 4, 3, 6, 4, 5, 5, 6, 7, 16, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 1, 4, 1, 5, 1, 6, 2, 4, 2, 5, 2, 6, 3, 4, 3, 5, 3, 6, 5, 6, 7, 16, 2, 5, 5, 1, 3, 5, 0, 4, 0, 1, 4, 3, 3, 2, 2, 4, 1, 4, 0, 5, 6, 4, 2, 6, 6, 3, 5, 6, 6, 1, 0, 6, 7, 16, 5, 6, 5, 1, 0, 3, 0, 4, 0, 1, 4, 6, 3, 6, 1, 3, 1, 4, 6, 0, 3, 5, 2, 3, 2, 4, 6, 2, 4, 5, 2, 5, 7, 16, 3, 4, 5, 1, 0, 3, 0, 4, 0, 1, 4, 6, 3, 6, 1, 3, 1, 4, 6, 0, 5, 0, 2, 3, 2, 4, 6, 2, 6, 5, 2, 5, 7, 16, 5, 0, 5, 1, 0, 3, 0, 4, 6, 1, 4, 6, 3, 6, 1, 3, 1, 4, 6, 0, 3, 5, 2, 3, 2, 4, 6, 2, 4, 5, 2, 5, 7, 17, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 1, 2, 1, 3, 1, 4, 1, 5, 2, 3, 2, 4, 2, 5, 3, 4, 3, 5, 4, 5, 6, 2, 1, 6, 7, 17, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 1, 2, 1, 3, 1, 4, 1, 5, 1, 6, 2, 3, 2, 4, 2, 5, 2, 6, 4, 5, 4, 6, 7, 17, 4, 0, 4, 3, 0, 1, 3, 0, 2, 4, 3, 1, 5, 3, 4, 5, 5, 2, 6, 5, 5, 0, 1, 5, 6, 1, 0, 6, 6, 4, 2, 6, 3, 6, 7, 17, 0, 1, 5, 1, 5, 3, 0, 4, 5, 0, 4, 3, 3, 1, 2, 5, 1, 4, 3, 0, 2, 4, 6, 2, 5, 6, 6, 3, 1, 6, 6, 0, 4, 6, 7, 17, 3, 4, 5, 1, 0, 3, 0, 4, 4, 5, 4, 6, 3, 6, 1, 3, 1, 4, 0, 1, 3, 5, 2, 3, 2, 4, 2, 5, 5, 0, 5, 6, 6, 2, 7, 17, 3, 2, 4, 1, 0, 1, 3, 0, 2, 4, 4, 3, 5, 1, 4, 5, 5, 2, 0, 5, 5, 3, 6, 5, 2, 6, 6, 3, 0, 6, 1, 6, 4, 6, 7, 17, 3, 2, 4, 1, 4, 0, 3, 0, 2, 4, 3, 1, 5, 2, 4, 5, 5, 0, 3, 5, 5, 1, 6, 5, 2, 6, 6, 0, 3, 6, 6, 4, 1, 6, 7, 17, 3, 2, 5, 1, 5, 0, 0, 4, 0, 1, 4, 3, 5, 3, 2, 5, 1, 4, 3, 0, 2, 4, 6, 4, 5, 6, 6, 2, 3, 6, 6, 0, 1, 6, 7, 17, 3, 2, 5, 1, 5, 0, 0, 4, 4, 5, 0, 1, 3, 1, 2, 5, 1, 4, 3, 0, 2, 4, 6, 0, 3, 6, 6, 1, 5, 6, 6, 2, 4, 6, 7, 17, 0, 3, 0, 4, 0, 5, 0, 6, 1, 2, 1, 3, 1, 4, 1, 5, 1, 6, 2, 3, 2, 4, 2, 5, 2, 6, 3, 5, 3, 6, 4, 5, 4, 6, 7, 18, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 1, 2, 1, 3, 1, 4, 1, 5, 2, 3, 2, 4, 2, 5, 3, 4, 3, 5, 4, 5, 6, 1, 0, 6, 5, 6, 7, 18, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 1, 2, 1, 3, 1, 4, 1, 5, 1, 6, 2, 3, 2, 4, 2, 5, 2, 6, 3, 4, 3, 5, 3, 6, 7, 18, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 1, 2, 1, 4, 1, 5, 2, 3, 2, 4, 2, 5, 2, 6, 3, 4, 3, 6, 4, 5, 4, 6, 5, 6, 7, 18, 0, 1, 0, 2, 0, 3, 0, 5, 0, 6, 1, 2, 1, 3, 1, 4, 1, 5, 1, 6, 2, 3, 2, 4, 3, 4, 3, 5, 3, 6, 4, 5, 4, 6, 5, 6, 7, 18, 4, 0, 4, 5, 3, 0, 3, 5, 2, 0, 2, 5, 1, 3, 1, 4, 1, 5, 1, 0, 2, 3, 2, 4, 6, 0, 5, 6, 6, 1, 2, 6, 6, 4, 3, 6, 7, 19, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 1, 2, 1, 3, 1, 4, 1, 5, 1, 6, 2, 3, 2, 4, 3, 4, 3, 5, 3, 6, 4, 5, 4, 6, 5, 6, 7, 19, 0, 1, 0, 2, 0, 3, 0, 5, 0, 6, 1, 2, 1, 3, 1, 4, 1, 5, 1, 6, 2, 3, 2, 4, 2, 5, 2, 6, 3, 4, 3, 6, 4, 5, 4, 6, 5, 6, 7, 20, 0, 1, 0, 2, 0, 3, 0, 5, 0, 6, 1, 2, 1, 3, 1, 4, 1, 5, 1, 6, 2, 3, 2, 4, 2, 5, 2, 6, 3, 4, 3, 5, 3, 6, 4, 5, 4, 6, 5, 6, 7, 21, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 1, 2, 1, 3, 1, 4, 1, 5, 1, 6, 2, 3, 2, 4, 2, 5, 2, 6, 3, 4, 3, 5, 3, 6, 4, 5, 4, 6, 5, 6, }; const long int igraph_i_atlas_edges_pos[] = {0, 2, 4, 6, 10, 12, 16, 22, 30, 32, 36, 42, 48, 56, 64, 72, 82, 92, 104, 118, 120, 124, 130, 136, 144, 152, 160, 168, 178, 188, 198, 208, 218, 228, 240, 252, 264, 276, 288, 300, 314, 328, 342, 356, 370, 384, 400, 416, 432, 448, 466, 484, 504, 526, 528, 532, 538, 544, 552, 560, 568, 576, 584, 594, 604, 614, 624, 634, 644, 654, 664, 674, 686, 698, 710, 722, 734, 746, 758, 770, 782, 794, 806, 818, 830, 842, 854, 868, 882, 896, 910, 924, 938, 952, 966, 980, 994, 1008, 1022, 1036, 1050, 1064, 1078, 1092, 1106, 1120, 1134, 1148, 1164, 1180, 1196, 1212, 1228, 1244, 1260, 1276, 1292, 1308, 1324, 1340, 1356, 1372, 1388, 1404, 1420, 1436, 1452, 1468, 1484, 1500, 1516, 1532, 1550, 1568, 1586, 1604, 1622, 1640, 1658, 1676, 1694, 1712, 1730, 1748, 1766, 1784, 1802, 1820, 1838, 1856, 1874, 1892, 1910, 1928, 1946, 1964, 1984, 2004, 2024, 2044, 2064, 2084, 2104, 2124, 2144, 2164, 2184, 2204, 2224, 2244, 2264, 2284, 2304, 2324, 2344, 2364, 2384, 2406, 2428, 2450, 2472, 2494, 2516, 2538, 2560, 2582, 2604, 2626, 2648, 2670, 2692, 2714, 2738, 2762, 2786, 2810, 2834, 2858, 2882, 2906, 2930, 2956, 2982, 3008, 3034, 3060, 3088, 3116, 3146, 3178, 3180, 3184, 3190, 3196, 3204, 3212, 3220, 3228, 3236, 3246, 3256, 3266, 3276, 3286, 3296, 3306, 3316, 3326, 3336, 3348, 3360, 3372, 3384, 3396, 3408, 3420, 3432, 3444, 3456, 3468, 3480, 3492, 3504, 3516, 3528, 3540, 3552, 3564, 3576, 3588, 3602, 3616, 3630, 3644, 3658, 3672, 3686, 3700, 3714, 3728, 3742, 3756, 3770, 3784, 3798, 3812, 3826, 3840, 3854, 3868, 3882, 3896, 3910, 3924, 3938, 3952, 3966, 3980, 3994, 4008, 4022, 4036, 4050, 4064, 4078, 4092, 4106, 4120, 4134, 4148, 4162, 4178, 4194, 4210, 4226, 4242, 4258, 4274, 4290, 4306, 4322, 4338, 4354, 4370, 4386, 4402, 4418, 4434, 4450, 4466, 4482, 4498, 4514, 4530, 4546, 4562, 4578, 4594, 4610, 4626, 4642, 4658, 4674, 4690, 4706, 4722, 4738, 4754, 4770, 4786, 4802, 4818, 4834, 4850, 4866, 4882, 4898, 4914, 4930, 4946, 4962, 4978, 4994, 5010, 5026, 5042, 5058, 5074, 5090, 5106, 5122, 5138, 5154, 5170, 5186, 5202, 5220, 5238, 5256, 5274, 5292, 5310, 5328, 5346, 5364, 5382, 5400, 5418, 5436, 5454, 5472, 5490, 5508, 5526, 5544, 5562, 5580, 5598, 5616, 5634, 5652, 5670, 5688, 5706, 5724, 5742, 5760, 5778, 5796, 5814, 5832, 5850, 5868, 5886, 5904, 5922, 5940, 5958, 5976, 5994, 6012, 6030, 6048, 6066, 6084, 6102, 6120, 6138, 6156, 6174, 6192, 6210, 6228, 6246, 6264, 6282, 6300, 6318, 6336, 6354, 6372, 6390, 6408, 6426, 6444, 6462, 6480, 6498, 6516, 6534, 6552, 6570, 6588, 6606, 6624, 6642, 6660, 6678, 6696, 6714, 6732, 6750, 6768, 6786, 6804, 6822, 6840, 6858, 6876, 6894, 6912, 6930, 6948, 6968, 6988, 7008, 7028, 7048, 7068, 7088, 7108, 7128, 7148, 7168, 7188, 7208, 7228, 7248, 7268, 7288, 7308, 7328, 7348, 7368, 7388, 7408, 7428, 7448, 7468, 7488, 7508, 7528, 7548, 7568, 7588, 7608, 7628, 7648, 7668, 7688, 7708, 7728, 7748, 7768, 7788, 7808, 7828, 7848, 7868, 7888, 7908, 7928, 7948, 7968, 7988, 8008, 8028, 8048, 8068, 8088, 8108, 8128, 8148, 8168, 8188, 8208, 8228, 8248, 8268, 8288, 8308, 8328, 8348, 8368, 8388, 8408, 8428, 8448, 8468, 8488, 8508, 8528, 8548, 8568, 8588, 8608, 8628, 8648, 8668, 8688, 8708, 8728, 8748, 8768, 8788, 8808, 8828, 8848, 8868, 8888, 8908, 8928, 8948, 8968, 8988, 9008, 9028, 9048, 9068, 9088, 9108, 9128, 9148, 9168, 9188, 9208, 9228, 9248, 9268, 9288, 9308, 9328, 9348, 9368, 9388, 9408, 9428, 9448, 9468, 9488, 9508, 9528, 9548, 9568, 9590, 9612, 9634, 9656, 9678, 9700, 9722, 9744, 9766, 9788, 9810, 9832, 9854, 9876, 9898, 9920, 9942, 9964, 9986, 10008, 10030, 10052, 10074, 10096, 10118, 10140, 10162, 10184, 10206, 10228, 10250, 10272, 10294, 10316, 10338, 10360, 10382, 10404, 10426, 10448, 10470, 10492, 10514, 10536, 10558, 10580, 10602, 10624, 10646, 10668, 10690, 10712, 10734, 10756, 10778, 10800, 10822, 10844, 10866, 10888, 10910, 10932, 10954, 10976, 10998, 11020, 11042, 11064, 11086, 11108, 11130, 11152, 11174, 11196, 11218, 11240, 11262, 11284, 11306, 11328, 11350, 11372, 11394, 11416, 11438, 11460, 11482, 11504, 11526, 11548, 11570, 11592, 11614, 11636, 11658, 11680, 11702, 11724, 11746, 11768, 11790, 11812, 11834, 11856, 11878, 11900, 11922, 11944, 11966, 11988, 12010, 12032, 12054, 12076, 12098, 12120, 12142, 12164, 12186, 12208, 12230, 12252, 12274, 12296, 12318, 12340, 12362, 12384, 12406, 12428, 12450, 12472, 12494, 12516, 12538, 12560, 12582, 12604, 12626, 12648, 12670, 12692, 12714, 12736, 12758, 12780, 12802, 12824, 12848, 12872, 12896, 12920, 12944, 12968, 12992, 13016, 13040, 13064, 13088, 13112, 13136, 13160, 13184, 13208, 13232, 13256, 13280, 13304, 13328, 13352, 13376, 13400, 13424, 13448, 13472, 13496, 13520, 13544, 13568, 13592, 13616, 13640, 13664, 13688, 13712, 13736, 13760, 13784, 13808, 13832, 13856, 13880, 13904, 13928, 13952, 13976, 14000, 14024, 14048, 14072, 14096, 14120, 14144, 14168, 14192, 14216, 14240, 14264, 14288, 14312, 14336, 14360, 14384, 14408, 14432, 14456, 14480, 14504, 14528, 14552, 14576, 14600, 14624, 14648, 14672, 14696, 14720, 14744, 14768, 14792, 14816, 14840, 14864, 14888, 14912, 14936, 14960, 14984, 15008, 15032, 15056, 15080, 15104, 15128, 15152, 15176, 15200, 15224, 15248, 15272, 15296, 15320, 15344, 15368, 15392, 15416, 15440, 15464, 15488, 15512, 15536, 15560, 15584, 15608, 15632, 15656, 15680, 15704, 15728, 15752, 15776, 15800, 15824, 15848, 15872, 15896, 15920, 15944, 15968, 15992, 16016, 16040, 16064, 16088, 16112, 16136, 16160, 16184, 16208, 16232, 16256, 16280, 16304, 16328, 16352, 16376, 16402, 16428, 16454, 16480, 16506, 16532, 16558, 16584, 16610, 16636, 16662, 16688, 16714, 16740, 16766, 16792, 16818, 16844, 16870, 16896, 16922, 16948, 16974, 17000, 17026, 17052, 17078, 17104, 17130, 17156, 17182, 17208, 17234, 17260, 17286, 17312, 17338, 17364, 17390, 17416, 17442, 17468, 17494, 17520, 17546, 17572, 17598, 17624, 17650, 17676, 17702, 17728, 17754, 17780, 17806, 17832, 17858, 17884, 17910, 17936, 17962, 17988, 18014, 18040, 18066, 18092, 18118, 18144, 18170, 18196, 18222, 18248, 18274, 18300, 18326, 18352, 18378, 18404, 18430, 18456, 18482, 18508, 18534, 18560, 18586, 18612, 18638, 18664, 18690, 18716, 18742, 18768, 18794, 18820, 18846, 18872, 18898, 18924, 18950, 18976, 19002, 19028, 19054, 19080, 19106, 19132, 19158, 19184, 19210, 19236, 19262, 19288, 19314, 19340, 19366, 19392, 19418, 19444, 19470, 19496, 19522, 19548, 19574, 19600, 19626, 19652, 19678, 19704, 19730, 19756, 19782, 19810, 19838, 19866, 19894, 19922, 19950, 19978, 20006, 20034, 20062, 20090, 20118, 20146, 20174, 20202, 20230, 20258, 20286, 20314, 20342, 20370, 20398, 20426, 20454, 20482, 20510, 20538, 20566, 20594, 20622, 20650, 20678, 20706, 20734, 20762, 20790, 20818, 20846, 20874, 20902, 20930, 20958, 20986, 21014, 21042, 21070, 21098, 21126, 21154, 21182, 21210, 21238, 21266, 21294, 21322, 21350, 21378, 21406, 21434, 21462, 21490, 21518, 21546, 21574, 21602, 21630, 21658, 21686, 21714, 21742, 21770, 21798, 21826, 21854, 21882, 21910, 21938, 21966, 21994, 22022, 22050, 22078, 22106, 22134, 22162, 22190, 22218, 22246, 22274, 22302, 22330, 22358, 22386, 22414, 22442, 22470, 22498, 22528, 22558, 22588, 22618, 22648, 22678, 22708, 22738, 22768, 22798, 22828, 22858, 22888, 22918, 22948, 22978, 23008, 23038, 23068, 23098, 23128, 23158, 23188, 23218, 23248, 23278, 23308, 23338, 23368, 23398, 23428, 23458, 23488, 23518, 23548, 23578, 23608, 23638, 23668, 23698, 23728, 23758, 23788, 23818, 23848, 23878, 23908, 23938, 23968, 23998, 24028, 24058, 24088, 24118, 24148, 24178, 24208, 24238, 24268, 24298, 24328, 24358, 24388, 24418, 24448, 24480, 24512, 24544, 24576, 24608, 24640, 24672, 24704, 24736, 24768, 24800, 24832, 24864, 24896, 24928, 24960, 24992, 25024, 25056, 25088, 25120, 25152, 25184, 25216, 25248, 25280, 25312, 25344, 25376, 25408, 25440, 25472, 25504, 25536, 25568, 25600, 25632, 25664, 25696, 25728, 25760, 25794, 25828, 25862, 25896, 25930, 25964, 25998, 26032, 26066, 26100, 26134, 26168, 26202, 26236, 26270, 26304, 26338, 26372, 26406, 26440, 26474, 26510, 26546, 26582, 26618, 26654, 26690, 26726, 26762, 26798, 26834, 26872, 26910, 26948, 26986, 27024, 27064, 27104, 27146}; __END_DECLS python-igraph-0.8.0/vendor/source/igraph/src/gengraph_random.cpp0000644000076500000240000001723713614300625025247 0ustar tamasstaff00000000000000/* * * gengraph - generation of random simple connected graphs with prescribed * degree sequence * * Copyright (C) 2006 Fabien Viger * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #define RNG_C #ifdef RCSID static const char rcsid[] = "$Id: random.cpp,v 1.15 2003/05/14 03:04:45 wilder Exp wilder $"; #endif //________________________________________________________________________ // See the header file random.h for a description of the contents of this // file as well as references and credits. #include #include "gengraph_random.h" using namespace std; using namespace KW_RNG; //________________________________________________________________________ // RNG::RNOR generates normal variates with rejection. // nfix() generates variates after rejection in RNOR. // Despite rejection, this method is much faster than Box-Muller. // double RNG::nfix(slong h, ulong i) // { // const double r = 3.442620f; // The starting of the right tail // static double x, y; // for(;;) { // x = h * wn[i]; // // If i == 0, handle the base strip // if (i==0){ // do { // x = -log(rand_open01()) * 0.2904764; // .2904764 is 1/r // y = -log(rand_open01()); // } while (y + y < x * x); // return ((h > 0) ? r + x : -r - x); // } // // If i > 0, handle the wedges of other strips // if (fn[i] + rand_open01() * (fn[i - 1] - fn[i]) < exp(-.5 * x * x) ) // return x; // // start all over // h = rand_int32(); // i = h & 127; // if ((ulong) abs((sint) h) < kn[i]) // return (h * wn[i]); // } // } // RNG::nfix // // __________________________________________________________________________ // // RNG::RNOR generates exponential variates with rejection. // // efix() generates variates after rejection in REXP. // double RNG::efix(ulong j, ulong i) // { // double x; // for (;;) // { // if (i == 0) // return (7.69711 - log(rand_open01())); // x = j * we[i]; // if (fe[i] + rand_open01() * (fe[i - 1] - fe[i]) < exp(-x)) // return (x); // j = rand_int32(); // i = (j & 255); // if (j < ke[i]) // return (j * we[i]); // } // } // RNG::efix // // __________________________________________________________________________ // // This procedure creates the tables used by RNOR and REXP // void RNG::zigset() // { // const double m1 = 2147483648.0; // 2^31 // const double m2 = 4294967296.0; // 2^32 // const double vn = 9.91256303526217e-3; // const double ve = 3.949659822581572e-3; // double dn = 3.442619855899, tn = dn; // double de = 7.697117470131487, te = de; // int i; // // Set up tables for RNOR // double q = vn / exp(-.5 * dn * dn); // kn[0] = (ulong) ((dn / q) * m1); // kn[1] = 0; // wn[0] = q / m1; // wn[127] = dn / m1; // fn[0]=1.; // fn[127] = exp(-.5 * dn * dn); // for(i = 126; i >= 1; i--) // { // dn = sqrt(-2 * log(vn / dn + exp(-.5 * dn * dn))); // kn[i + 1] = (ulong) ((dn / tn) * m1); // tn = dn; // fn[i] = exp(-.5 * dn * dn); // wn[i] = dn / m1; // } // // Set up tables for REXP // q = ve / exp(-de); // ke[0] = (ulong) ((de / q) * m2); // ke[1] = 0; // we[0] = q / m2; // we[255] = de / m2; // fe[0] = 1.; // fe[255] = exp(-de); // for (i = 254; i >= 1; i--) // { // de = -log(ve / de + exp(-de)); // ke[i+1] = (ulong) ((de / te) * m2); // te = de; // fe[i] = exp(-de); // we[i] = de / m2; // } // } // RNG::zigset // // __________________________________________________________________________ // // Generate a gamma variate with parameters 'shape' and 'scale' // double RNG::gamma(double shape, double scale) // { // if (shape < 1) // return gamma(shape + 1, scale) * pow(rand_open01(), 1.0 / shape); // const double d = shape - 1.0 / 3.0; // const double c = 1.0 / sqrt(9.0 * d); // double x, v, u; // for (;;) { // do { // x = RNOR(); // v = 1.0 + c * x; // } while (v <= 0.0); // v = v * v * v; // u = rand_open01(); // if (u < 1.0 - 0.0331 * x * x * x * x) // return (d * v / scale); // if (log(u) < 0.5 * x * x + d * (1.0 - v + log(v))) // return (d * v / scale); // } // } // RNG::gamma // // __________________________________________________________________________ // // gammalog returns the logarithm of the gamma function. From Numerical // // Recipes. // double gammalog(double xx) // { // static double cof[6]={ // 76.18009172947146, -86.50532032941677, 24.01409824083091, // -1.231739572450155, 0.1208650973866179e-2, -0.5395239384953e-5}; // double x = xx; // double y = xx; // double tmp = x + 5.5; // tmp -= (x + 0.5) * log(tmp); // double ser=1.000000000190015; // for (int j=0; j<=5; j++) // ser += cof[j] / ++y; // return -tmp + log(2.5066282746310005 * ser / x); // } // // __________________________________________________________________________ // // Generate a Poisson variate // // This is essentially the algorithm from Numerical Recipes // double RNG::poisson(double lambda) // { // static double sq, alxm, g, oldm = -1.0; // double em, t, y; // if (lambda < 12.0) { // if (lambda != oldm) { // oldm = lambda; // g = exp(-lambda); // } // em = -1; // t = 1.0; // do { // ++em; // t *= rand_open01(); // } while (t > g); // } else { // if (lambda != oldm) { // oldm = lambda; // sq = sqrt(2.0 * lambda); // alxm = log(lambda); // g = lambda * alxm - gammalog(lambda + 1.0); // } // do { // do { // y = tan(PI * rand_open01()); // em = sq * y + lambda; // } while (em < 0.0); // em = floor(em); // t = 0.9 * (1.0 + y * y) * exp(em * alxm - gammalog(em + 1.0)-g); // } while (rand_open01() > t); // } // return em; // } // RNG::poisson // // __________________________________________________________________________ // // Generate a binomial variate // // This is essentially the algorithm from Numerical Recipes // int RNG::binomial(double pp, int n) // { // if(n==0) return 0; // if(pp==0.0) return 0; // if(pp==1.0) return n; // double p = (pp<0.5 ? pp : 1.0-pp); // double am = n*p; // int bnl = 0; // if(n<25) { // for(int j=n; j--; ) if(rand_closed01()= en + 1.0); // em = floor(em); // t = 1.2 * sq * (1 + y * y) * exp(oldg - gammalog(em + 1.0) - // gammalog(en - em + 1.0) + em * log(p) + (en - em) * log(pc)); // } while (rand_closed01() > t); // bnl = int(em); // } // if (p!=pp) bnl=n-bnl; // return bnl; // } // RNG::binomial // __________________________________________________________________________ // rng.C python-igraph-0.8.0/vendor/source/igraph/src/lad.c0000644000076500000240000017642313614300625022317 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ /* The contents of this file was originally taken from the LAD homepage: http://liris.cnrs.fr/csolnon/LAD.html and then modified to fit better into igraph. Unfortunately LAD seems to have no version numbers. The files were apparently last changed on the 29th of June, 2010. The original copyright message follows here. The CeCILL-B V1 license is GPL compatible, because instead of V1, one can freely choose to use V2, and V2 is explicitly GPL compatible. */ /* This software has been written by Christine Solnon. It is distributed under the CeCILL-B FREE SOFTWARE LICENSE see http://www.cecill.info/licences/Licence_CeCILL-B_V1-en.html for more details */ /* Several modifications had to be made to the original LAD implementation to make it compile with non-C99-compliant compilers such as MSVC. In particular, I had to remove all the variable-sized arrays. -- Tamas Nepusz, 11 July 2013 */ #include #include #include #include #include #include #include "igraph_interface.h" #include "igraph_adjlist.h" #include "igraph_vector.h" #include "igraph_vector_ptr.h" #include "igraph_memory.h" #include "igraph_matrix.h" #include "igraph_interrupt_internal.h" /* define boolean type as char */ #define true 1 #define false 0 #define bool char /* helper to allocate an array of given size and free it using IGRAPH_FINALLY * when needed */ #define ALLOC_ARRAY(VAR, SIZE, TYPE) { \ VAR = igraph_Calloc(SIZE, TYPE); \ if (VAR == 0) { \ IGRAPH_ERROR("cannot allocate '" #VAR "' array in LAD isomorphism search", IGRAPH_ENOMEM); \ } \ IGRAPH_FINALLY(igraph_free, VAR); \ } /* helper to allocate an array of given size and store its address in a * pointer array */ #define ALLOC_ARRAY_IN_HISTORY(VAR, SIZE, TYPE, HISTORY) { \ VAR = igraph_Calloc(SIZE, TYPE); \ if (VAR == 0) { \ IGRAPH_ERROR("cannot allocate '" #VAR "' array in LAD isomorphism search", IGRAPH_ENOMEM); \ } \ IGRAPH_FINALLY(igraph_free, VAR); \ IGRAPH_CHECK(igraph_vector_ptr_push_back(HISTORY, VAR)); \ IGRAPH_FINALLY_CLEAN(1); \ } /* ---------------------------------------------------------*/ /* Coming from graph.c */ /* ---------------------------------------------------------*/ typedef struct { long int nbVertices; /* Number of vertices */ igraph_vector_t nbSucc; igraph_adjlist_t succ; igraph_matrix_char_t isEdge; } Tgraph; int igraph_i_lad_createGraph(const igraph_t *igraph, Tgraph* graph) { long int i, j, n; long int no_of_nodes = igraph_vcount(igraph); igraph_vector_int_t *neis; IGRAPH_VECTOR_INIT_FINALLY(&graph->nbSucc, no_of_nodes); IGRAPH_CHECK(igraph_degree(igraph, &graph->nbSucc, igraph_vss_all(), IGRAPH_OUT, IGRAPH_LOOPS)); graph->nbVertices = no_of_nodes; IGRAPH_CHECK(igraph_adjlist_init(igraph, &graph->succ, IGRAPH_OUT)); IGRAPH_FINALLY(igraph_adjlist_destroy, &graph->succ); IGRAPH_CHECK(igraph_matrix_char_init(&graph->isEdge, no_of_nodes, no_of_nodes)); IGRAPH_FINALLY(igraph_matrix_char_destroy, &graph->isEdge); for (i = 0; i < no_of_nodes; i++) { neis = igraph_adjlist_get(&graph->succ, i); n = igraph_vector_int_size(neis); for (j = 0; j < n; j++) { int v = (int)VECTOR(*neis)[j]; if (MATRIX(graph->isEdge, i, v)) { IGRAPH_ERROR("LAD functions only work on simple graphs, " "simplify your graph", IGRAPH_EINVAL); } MATRIX(graph->isEdge, i, v) = 1; } } return 0; } /* ---------------------------------------------------------*/ /* Coming from domains.c */ /* ---------------------------------------------------------*/ typedef struct { igraph_vector_int_t nbVal; /* nbVal[u] = number of values in D[u] */ igraph_vector_int_t firstVal; /* firstVal[u] = pos in val of the first value of D[u] */ igraph_vector_int_t val; /* val[firstVal[u]..firstVal[u]+nbVal[u]-1] = values of D[u] */ igraph_matrix_int_t posInVal; /* If v in D[u] then firstVal[u] <= posInVal[u][v] < firstVal[u]+nbVal[u] and val[posInVal[u][v]] = v otherwise posInVal[u][v] >= firstVal[u]+nbVal[u] */ int valSize; /* size of val */ igraph_matrix_int_t firstMatch; /* firstMatch[u][v] = pos in match of the first vertex of the covering matching of G_(u, v) */ igraph_vector_int_t matching; /* matching[firstMatch[u][v]..firstMatch[u][v]+nbSucc[u]-1] = covering matching of G_(u, v) */ int nextOutToFilter; /* position in toFilter of the next pattern node whose domain should be filtered (-1 if no domain to filter) */ int lastInToFilter; /* position in toFilter of the last pattern node whose domain should be filtered */ igraph_vector_int_t toFilter; /* contain all pattern nodes whose domain should be filtered */ igraph_vector_char_t markedToFilter; /* markedToFilter[u]=true if u is in toFilter; false otherwise */ igraph_vector_int_t globalMatchingP; /* globalMatchingP[u] = node of Gt matched to u in globalAllDiff(Np) */ igraph_vector_int_t globalMatchingT; /* globalMatchingT[v] = node of Gp matched to v in globalAllDiff(Np) or -1 if v is not matched */ } Tdomain; bool igraph_i_lad_toFilterEmpty(Tdomain* D) { /* return true if there is no more nodes in toFilter */ return (D->nextOutToFilter < 0); } void igraph_i_lad_resetToFilter(Tdomain *D) { /* empty to filter and unmark the vertices that are marked to be filtered */ igraph_vector_char_null(&D->markedToFilter); D->nextOutToFilter = -1; } int igraph_i_lad_nextToFilter(Tdomain* D, int size) { /* precondition: emptyToFilter = false remove a node from toFilter (FIFO) unmark this node and return it */ int u = VECTOR(D->toFilter)[D->nextOutToFilter]; VECTOR(D->markedToFilter)[u] = false; if (D->nextOutToFilter == D->lastInToFilter) { /* u was the last node in tofilter */ D->nextOutToFilter = -1; } else if (D->nextOutToFilter == size - 1) { D->nextOutToFilter = 0; } else { D->nextOutToFilter++; } return u; } void igraph_i_lad_addToFilter(int u, Tdomain* D, int size) { /* if u is not marked, then add it to toFilter and mark it */ if (VECTOR(D->markedToFilter)[u]) { return; } VECTOR(D->markedToFilter)[u] = true; if (D->nextOutToFilter < 0) { D->lastInToFilter = 0; D->nextOutToFilter = 0; } else if (D->lastInToFilter == size - 1) { D->lastInToFilter = 0; } else { D->lastInToFilter++; } VECTOR(D->toFilter)[D->lastInToFilter] = u; } bool igraph_i_lad_isInD(int u, int v, Tdomain* D) { /* returns true if v belongs to D(u); false otherwise */ return (MATRIX(D->posInVal, u, v) < VECTOR(D->firstVal)[u] + VECTOR(D->nbVal)[u]); } int igraph_i_lad_augmentingPath(int u, Tdomain* D, int nbV, bool* result) { /* return true if there exists an augmenting path starting from u and ending on a free vertex v in the bipartite directed graph G=(U, V, E) such that U=pattern nodes, V=target nodes, and E={(u, v), v in D(u)} U {(v, u), D->globalMatchingP[u]=v} update D-globalMatchingP and D->globalMatchingT consequently */ int *fifo, *pred; bool *marked; int nextIn = 0; int nextOut = 0; int i, v, v2, u2; *result = false; /* Allocate memory */ ALLOC_ARRAY(fifo, nbV, int); ALLOC_ARRAY(pred, nbV, int); ALLOC_ARRAY(marked, nbV, bool); for (i = 0; i < VECTOR(D->nbVal)[u]; i++) { v = VECTOR(D->val)[ VECTOR(D->firstVal)[u] + i ]; /* v in D(u) */ if (VECTOR(D->globalMatchingT)[v] < 0) { /* v is free => augmenting path found */ VECTOR(D->globalMatchingP)[u] = v; VECTOR(D->globalMatchingT)[v] = u; *result = true; goto cleanup; } /* v is not free => add it to fifo */ pred[v] = u; fifo[nextIn++] = v; marked[v] = true; } while (nextOut < nextIn) { u2 = VECTOR(D->globalMatchingT)[fifo[nextOut++]]; for (i = 0; i < VECTOR(D->nbVal)[u2]; i++) { v = VECTOR(D->val)[ VECTOR(D->firstVal)[u2] + i ]; /* v in D(u2) */ if (VECTOR(D->globalMatchingT)[v] < 0) { /* v is free => augmenting path found */ while (u2 != u) { /* update global matching wrt path */ v2 = VECTOR(D->globalMatchingP)[u2]; VECTOR(D->globalMatchingP)[u2] = v; VECTOR(D->globalMatchingT)[v] = u2; v = v2; u2 = pred[v]; } VECTOR(D->globalMatchingP)[u] = v; VECTOR(D->globalMatchingT)[v] = u; *result = true; goto cleanup; } if (!marked[v]) { /* v is not free and not marked => add it to fifo */ pred[v] = u2; fifo[nextIn++] = v; marked[v] = true; } } } cleanup: igraph_free(fifo); igraph_free(pred); igraph_free(marked); IGRAPH_FINALLY_CLEAN(3); return 0; } int igraph_i_lad_removeAllValuesButOne(int u, int v, Tdomain* D, Tgraph* Gp, Tgraph* Gt, bool* result) { /* remove all values but v from D(u) and add all successors of u in toFilter return false if an inconsistency is detected wrt to global all diff */ int j, oldPos, newPos; igraph_vector_int_t *uneis = igraph_adjlist_get(&Gp->succ, u); int n = (int) igraph_vector_int_size(uneis); /* add all successors of u in toFilter */ for (j = 0; j < n; j++) { igraph_i_lad_addToFilter((int) VECTOR(*uneis)[j], D, (int) (Gp->nbVertices)); } /* remove all values but v from D[u] */ oldPos = MATRIX(D->posInVal, u, v); newPos = VECTOR(D->firstVal)[u]; VECTOR(D->val)[oldPos] = VECTOR(D->val)[newPos]; VECTOR(D->val)[newPos] = v; MATRIX(D->posInVal, u, VECTOR(D->val)[newPos]) = newPos; MATRIX(D->posInVal, u, VECTOR(D->val)[oldPos]) = oldPos; VECTOR(D->nbVal)[u] = 1; /* update global matchings that support the global all different constraint */ if (VECTOR(D->globalMatchingP)[u] != v) { VECTOR(D->globalMatchingT)[ VECTOR(D->globalMatchingP)[u] ] = -1; VECTOR(D->globalMatchingP)[u] = -1; IGRAPH_CHECK(igraph_i_lad_augmentingPath(u, D, (int) (Gt->nbVertices), result)); } else { *result = true; } return 0; } int igraph_i_lad_removeValue(int u, int v, Tdomain* D, Tgraph* Gp, Tgraph* Gt, bool* result) { /* remove v from D(u) and add all successors of u in toFilter return false if an inconsistency is detected wrt global all diff */ int j; igraph_vector_int_t *uneis = igraph_adjlist_get(&Gp->succ, u); int n = (int) igraph_vector_int_size(uneis); int oldPos, newPos; /* add all successors of u in toFilter */ for (j = 0; j < n; j++) { igraph_i_lad_addToFilter((int) VECTOR(*uneis)[j], D, (int) (Gp->nbVertices)); } /* remove v from D[u] */ oldPos = MATRIX(D->posInVal, u, v); VECTOR(D->nbVal)[u]--; newPos = VECTOR(D->firstVal)[u] + VECTOR(D->nbVal)[u]; VECTOR(D->val)[oldPos] = VECTOR(D->val)[newPos]; VECTOR(D->val)[newPos] = v; MATRIX(D->posInVal, u, VECTOR(D->val)[oldPos]) = oldPos; MATRIX(D->posInVal, u, VECTOR(D->val)[newPos]) = newPos; /* update global matchings that support the global all different constraint */ if (VECTOR(D->globalMatchingP)[u] == v) { VECTOR(D->globalMatchingP)[u] = -1; VECTOR(D->globalMatchingT)[v] = -1; IGRAPH_CHECK(igraph_i_lad_augmentingPath(u, D, (int) (Gt->nbVertices), result)); } else { *result = true; } return 0; } int igraph_i_lad_matchVertices(int nb, igraph_vector_int_t* toBeMatched, bool induced, Tdomain* D, Tgraph* Gp, Tgraph* Gt, int *invalid) { /* for each u in toBeMatched[0..nb-1], match u to D->val[D->firstVal[u] and filter domains of other non matched vertices wrt FC(Edges) and FC(diff) (this is not mandatory, as LAD is stronger than FC(Edges) and GAC(allDiff) is stronger than FC(diff), but this speeds up the solution process). return false if an inconsistency is detected by FC(Edges) or FC(diff); true otherwise; */ int j, u, v, u2, oldNbVal; igraph_vector_int_t *vneis; bool result = false; while (nb > 0) { u = VECTOR(*toBeMatched)[--nb]; v = VECTOR(D->val)[ VECTOR(D->firstVal)[u] ]; vneis = igraph_adjlist_get(&Gt->succ, v); /* match u to v */ for (u2 = 0; u2 < Gp->nbVertices; u2++) { if (u != u2) { oldNbVal = VECTOR(D->nbVal)[u2]; if (igraph_i_lad_isInD(u2, v, D)) { IGRAPH_CHECK(igraph_i_lad_removeValue(u2, v, D, Gp, Gt, &result)); if (!result) { *invalid = 1 ; return 0; } } if (MATRIX(Gp->isEdge, u, u2)) { /* remove from D[u2] vertices which are not adjacent to v */ j = VECTOR(D->firstVal)[u2]; while (j < VECTOR(D->firstVal)[u2] + VECTOR(D->nbVal)[u2]) { if (MATRIX(Gt->isEdge, v, VECTOR(D->val)[j])) { j++; } else { IGRAPH_CHECK(igraph_i_lad_removeValue(u2, VECTOR(D->val)[j], D, Gp, Gt, &result)); if (!result) { *invalid = 1; return 0; } } } } else if (induced) { /* (u, u2) is not an edge => remove neighbors of v from D[u2] */ if (VECTOR(D->nbVal)[u2] < VECTOR(Gt->nbSucc)[v]) { j = VECTOR(D->firstVal)[u2]; while (j < VECTOR(D->firstVal)[u2] + VECTOR(D->nbVal)[u2]) { if (!MATRIX(Gt->isEdge, v, VECTOR(D->val)[j])) { j++; } else { IGRAPH_CHECK(igraph_i_lad_removeValue(u2, VECTOR(D->val)[j], D, Gp, Gt, &result)); if (!result) { *invalid = 1; return 0; } } } } else { for (j = 0; j < VECTOR(Gt->nbSucc)[v]; j++) { if (igraph_i_lad_isInD(u2, (int) VECTOR(*vneis)[j], D)) { IGRAPH_CHECK(igraph_i_lad_removeValue(u2, (int) VECTOR(*vneis)[j], D, Gp, Gt, &result)); if (!result) { *invalid = 1; return 0; } } } } } if (VECTOR(D->nbVal)[u2] == 0) { *invalid = 1; /* D[u2] is empty */ return 0; } if ((VECTOR(D->nbVal)[u2] == 1) && (oldNbVal > 1)) { VECTOR(*toBeMatched)[nb++] = u2; } } } } *invalid = 0; return 0; } bool igraph_i_lad_matchVertex(int u, bool induced, Tdomain* D, Tgraph* Gp, Tgraph *Gt) { int invalid; /* match u to D->val[D->firstVal[u]] and filter domains of other non matched vertices wrt FC(Edges) and FC(diff) (this is not mandatory, as LAD is stronger than FC(Edges) and GAC(allDiff) is stronger than FC(diff), but this speeds up the solution process). return false if an inconsistency is detected by FC(Edges) or FC(diff); true otherwise; */ igraph_vector_int_t toBeMatched; igraph_vector_int_init(&toBeMatched, Gp->nbVertices); IGRAPH_FINALLY(igraph_vector_int_destroy, &toBeMatched); VECTOR(toBeMatched)[0] = u; igraph_i_lad_matchVertices(1, &toBeMatched, induced, D, Gp, Gt, &invalid); igraph_vector_int_destroy(&toBeMatched); IGRAPH_FINALLY_CLEAN(1); return invalid ? false : true; } int igraph_i_lad_qcompare (void const *a, void const *b) { /* function used by the qsort function */ int pa = *((int*)a) - *((int*)b); return pa; } bool igraph_i_lad_compare(int size_mu, int* mu, int size_mv, int* mv) { /* return true if for every element u of mu there exists a different element v of mv such that u <= v; return false otherwise */ int i, j; qsort(mu, (size_t) size_mu, sizeof(int), igraph_i_lad_qcompare); qsort(mv, (size_t) size_mv, sizeof(int), igraph_i_lad_qcompare); i = size_mv - 1; for (j = size_mu - 1; j >= 0; j--) { if (mu[j] > mv[i]) { return false; } i--; } return true; } int igraph_i_lad_initDomains(bool initialDomains, igraph_vector_ptr_t *domains, Tdomain* D, Tgraph* Gp, Tgraph* Gt, int *empty) { /* for every pattern node u, initialize D(u) with every vertex v such that for every neighbor u' of u there exists a different neighbor v' of v such that degree(u) <= degree(v) if initialDomains, then filter initial domains wrt compatibilities given in file return false if a domain is empty and true otherwise */ int *val; bool *dom; int *mu, *mv; int matchingSize, u, v, i, j; igraph_vector_t *vec; igraph_vector_t *Gp_uneis; igraph_vector_t *Gt_vneis; val = igraph_Calloc(Gp->nbVertices * Gt->nbVertices, int); if (val == 0) { IGRAPH_ERROR("cannot allocated 'val' array in igraph_i_lad_initDomains", IGRAPH_ENOMEM); } dom = igraph_Calloc(Gt->nbVertices, bool); if (dom == 0) { igraph_free(val); IGRAPH_ERROR("cannot allocated 'dom' array in igraph_i_lad_initDomains", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_int_init(&D->globalMatchingP, Gp->nbVertices)); IGRAPH_FINALLY(igraph_vector_int_destroy, &D->globalMatchingP); igraph_vector_int_fill(&D->globalMatchingP, -1L); IGRAPH_CHECK(igraph_vector_int_init(&D->globalMatchingT, Gt->nbVertices)); IGRAPH_FINALLY(igraph_vector_int_destroy, &D->globalMatchingT); igraph_vector_int_fill(&D->globalMatchingT, -1L); IGRAPH_CHECK(igraph_vector_int_init(&D->nbVal, Gp->nbVertices)); IGRAPH_FINALLY(igraph_vector_int_destroy, &D->nbVal); IGRAPH_CHECK(igraph_vector_int_init(&D->firstVal, Gp->nbVertices)); IGRAPH_FINALLY(igraph_vector_int_destroy, &D->firstVal); IGRAPH_CHECK(igraph_matrix_int_init(&D->posInVal, Gp->nbVertices, Gt->nbVertices)); IGRAPH_FINALLY(igraph_matrix_int_destroy, &D->posInVal); IGRAPH_CHECK(igraph_matrix_int_init(&D->firstMatch, Gp->nbVertices, Gt->nbVertices)); IGRAPH_FINALLY(igraph_matrix_int_destroy, &D->firstMatch); IGRAPH_CHECK(igraph_vector_char_init(&D->markedToFilter, Gp->nbVertices)); IGRAPH_FINALLY(igraph_vector_char_destroy, &D->markedToFilter); IGRAPH_CHECK(igraph_vector_int_init(&D->toFilter, Gp->nbVertices)); IGRAPH_FINALLY(igraph_vector_int_destroy, &D->toFilter); D->valSize = 0; matchingSize = 0; for (u = 0; u < Gp->nbVertices; u++) { igraph_vector_int_t *Gp_uneis = igraph_adjlist_get(&Gp->succ, u); if (initialDomains) { /* read the list of target vertices which are compatible with u */ vec = VECTOR(*domains)[u]; i = (int) igraph_vector_size(vec); memset(dom, false, sizeof(bool) * (size_t)(Gt->nbVertices)); for (j = 0; j < i; j++) { v = (int) VECTOR(*vec)[j]; dom[v] = true; } } VECTOR(D->markedToFilter)[u] = true; VECTOR(D->toFilter)[u] = u; VECTOR(D->nbVal)[u] = 0; VECTOR(D->firstVal)[u] = D->valSize; for (v = 0; v < Gt->nbVertices; v++) { igraph_vector_int_t *Gt_vneis = igraph_adjlist_get(&Gt->succ, v); if ((initialDomains) && (!dom[v])) { /* v not in D(u) */ MATRIX(D->posInVal, u, v) = (int) (VECTOR(D->firstVal)[u] + Gt->nbVertices); } else { MATRIX(D->firstMatch, u, v) = matchingSize; matchingSize += VECTOR(Gp->nbSucc)[u]; if (VECTOR(Gp->nbSucc)[u] <= VECTOR(Gt->nbSucc)[v]) { mu = igraph_Calloc((long int) VECTOR(Gp->nbSucc)[u], int); if (mu == 0) { igraph_free(val); igraph_free(dom); IGRAPH_ERROR("cannot allocate 'mu' array in igraph_i_lad_initDomains", IGRAPH_ENOMEM); } mv = igraph_Calloc((long int) VECTOR(Gt->nbSucc)[v], int); if (mv == 0) { igraph_free(mu); igraph_free(val); igraph_free(dom); IGRAPH_ERROR("cannot allocate 'mv' array in igraph_i_lad_initDomains", IGRAPH_ENOMEM); } for (i = 0; i < VECTOR(Gp->nbSucc)[u]; i++) { mu[i] = (int) VECTOR(Gp->nbSucc)[(long int) VECTOR(*Gp_uneis)[i]]; } for (i = 0; i < VECTOR(Gt->nbSucc)[v]; i++) { mv[i] = (int) VECTOR(Gt->nbSucc)[(long int) VECTOR(*Gt_vneis)[i]]; } if (igraph_i_lad_compare((int) VECTOR(Gp->nbSucc)[u], mu, (int) VECTOR(Gt->nbSucc)[v], mv) == 1) { val[D->valSize] = v; VECTOR(D->nbVal)[u]++; MATRIX(D->posInVal, u, v) = D->valSize++; } else { /* v not in D(u) */ MATRIX(D->posInVal, u, v) = (int)(VECTOR(D->firstVal)[u] + Gt->nbVertices); } igraph_free(mu); mu = 0; igraph_free(mv); mv = 0; } else { /* v not in D(u) */ MATRIX(D->posInVal, u, v) = (int) (VECTOR(D->firstVal)[u] + Gt->nbVertices); } } } if (VECTOR(D->nbVal)[u] == 0) { *empty = 1; /* empty domain */ igraph_free(val); igraph_free(dom); return 0; } } IGRAPH_CHECK(igraph_vector_int_init(&D->val, D->valSize)); IGRAPH_FINALLY(igraph_vector_int_destroy, &D->val); for (i = 0; i < D->valSize; i++) { VECTOR(D->val)[i] = val[i]; } IGRAPH_CHECK(igraph_vector_int_init(&D->matching, matchingSize)); IGRAPH_FINALLY(igraph_vector_int_destroy, &D->matching); igraph_vector_int_fill(&D->matching, -1); D->nextOutToFilter = 0; D->lastInToFilter = (int) (Gp->nbVertices - 1); *empty = 0; igraph_free(val); igraph_free(dom); return 0; } /* ---------------------------------------------------------*/ /* Coming from allDiff.c */ /* ---------------------------------------------------------*/ #define white 0 #define grey 1 #define black 2 #define toBeDeleted 3 #define deleted 4 void igraph_i_lad_addToDelete(int u, int* list, int* nb, int* marked) { if (marked[u] < toBeDeleted) { list[(*nb)++] = u; marked[u] = toBeDeleted; } } int igraph_i_lad_updateMatching(int sizeOfU, int sizeOfV, igraph_vector_int_t *degree, igraph_vector_int_t *firstAdj, igraph_vector_int_t *adj, igraph_vector_int_t * matchedWithU, int *invalid) { /* input: sizeOfU = number of vertices in U sizeOfV = number of vertices in V degree[u] = number of vertices of V which are adjacent to u firstAdj[u] = pos in adj of the first vertex of V adjacent to u adj[firstAdj[u]..firstAdj[u]+sizeOfU[u]-1] = vertices of V adjacent to u input/output: matchedWithU[u] = vertex of V matched with u returns true if there exists a matching that covers U, i.e., if for every u in 0..nbU-1, there exists a different v in 0..nb-1 such that v is adjacent to u; returns false otherwise */ int *matchedWithV; /* matchedWithV[matchedWithU[u]]=u */ int *nbPred; /* nbPred[i] = nb of predecessors of the ith vertex of V in the DAG */ int *pred; /* pred[i][j] = jth predecessor the ith vertex of V in the DAG */ int *nbSucc; /* nbSucc[i] = nb of successors of the ith vertex of U in the DAG */ int *succ; /* succ[i][j] = jth successor of the ith vertex of U in the DAG */ int *listV, *listU, *listDV, *listDU; int nbV, nbU, nbDV, nbDU; int i, j, k, stop, u, v, w; int *markedV, *markedU; /* markedX[i]=white if X[i] is not in the DAG markedX[i]=grey if X[i] has been added to the DAG, but not its successors markedX[i]=black if X[i] and its successors have been added to the DAG markedX[i]=toBeDeleted if X[i] must be deleted from the DAG markedX[i]=deleted if X[i] has been deleted from the DAG */ int nbUnmatched = 0; /* number of vertices of U that are not matched */ int *unmatched; /* vertices of U that are not matched */ int *posInUnmatched; /* unmatched[posInUnmatched[u]]=u */ igraph_vector_int_t path; if (sizeOfU > sizeOfV) { *invalid = 1; /* trivial case of infeasibility */ return 0; } ALLOC_ARRAY(matchedWithV, sizeOfV, int); ALLOC_ARRAY(nbPred, sizeOfV, int); ALLOC_ARRAY(pred, sizeOfV * sizeOfU, int); ALLOC_ARRAY(nbSucc, sizeOfU, int); ALLOC_ARRAY(succ, sizeOfU * sizeOfV, int); ALLOC_ARRAY(listV, sizeOfV, int); ALLOC_ARRAY(listU, sizeOfU, int); ALLOC_ARRAY(listDV, sizeOfV, int); ALLOC_ARRAY(listDU, sizeOfU, int); ALLOC_ARRAY(markedV, sizeOfV, int); ALLOC_ARRAY(markedU, sizeOfU, int); ALLOC_ARRAY(unmatched, sizeOfU, int); ALLOC_ARRAY(posInUnmatched, sizeOfU, int); IGRAPH_CHECK(igraph_vector_int_init(&path, 0)); IGRAPH_FINALLY(igraph_vector_int_destroy, &path); /* initialize matchedWithV and unmatched */ memset(matchedWithV, -1, (size_t)sizeOfV * sizeof(int)); for (u = 0; u < sizeOfU; u++) { if (VECTOR(*matchedWithU)[u] >= 0) { matchedWithV[VECTOR(*matchedWithU)[u]] = u; } else { posInUnmatched[u] = nbUnmatched; unmatched[nbUnmatched++] = u; } } /* try to match unmatched vertices of U with free vertices of V */ j = 0; while (j < nbUnmatched) { u = unmatched[j]; for (i = VECTOR(*firstAdj)[u]; ((i < VECTOR(*firstAdj)[u] + VECTOR(*degree)[u]) && (matchedWithV[VECTOR(*adj)[i]] >= 0)); i++) { } if (i == VECTOR(*firstAdj)[u] + VECTOR(*degree)[u]) { j++; /* no free vertex for u */ } else { v = VECTOR(*adj)[i]; /* v is free => match u with v */ VECTOR(*matchedWithU)[u] = v; matchedWithV[v] = u; unmatched[j] = unmatched[--nbUnmatched]; posInUnmatched[unmatched[j]] = j; } } while (nbUnmatched > 0) { /* Try to increase the number of matched vertices */ /* step 1 : build the DAG */ memset(markedU, white, (size_t) sizeOfU * sizeof(int)); memset(nbSucc, 0, (size_t) sizeOfU * sizeof(int)); memset(markedV, white, (size_t) sizeOfV * sizeof(int)); memset(nbPred, 0, (size_t) sizeOfV * sizeof(int)); /* first layer of the DAG from the free nodes of U */ nbV = 0; for (j = 0; j < nbUnmatched; j++) { u = unmatched[j]; /* u is a free node of U */ markedU[u] = black; for (i = VECTOR(*firstAdj)[u]; i < VECTOR(*firstAdj)[u] + VECTOR(*degree)[u]; i++) { v = VECTOR(*adj)[i]; /* add edge (u, v) to the DAG */ pred[v * sizeOfU + (nbPred[v]++)] = u; succ[u * sizeOfV + (nbSucc[u]++)] = v; if (markedV[v] == white) { /* first time v is added to the DAG*/ markedV[v] = grey; listV[nbV++] = v; } } } stop = 0; while ((stop == 0) && (nbV > 0)) { /* build next layer from nodes of V to nodes of U */ nbU = 0; for (i = 0; i < nbV; i++) { v = listV[i]; markedV[v] = black; u = matchedWithV[v]; if (markedU[u] == white) { /* edge (v, u) belongs to the DAG */ markedU[u] = grey; listU[nbU++] = u; } } /* build next layer from nodes of U to nodes of V */ nbV = 0; for (j = 0; j < nbU; j++) { u = listU[j]; markedU[u] = black; for (i = VECTOR(*firstAdj)[u]; i < VECTOR(*firstAdj)[u] + VECTOR(*degree)[u]; i++) { v = VECTOR(*adj)[i]; if (markedV[v] != black) { /* add edge (u, v) to the DAG */ pred[v * sizeOfU + (nbPred[v]++)] = u; succ[u * sizeOfV + (nbSucc[u]++)] = v; if (markedV[v] == white) { /* first time v is added to the DAG */ markedV[v] = grey; listV[nbV++] = v; } if (matchedWithV[v] == -1) { /* we have found a free node ! */ stop = 1; } } } } } if (nbV == 0) { *invalid = 1; /* I know it's ugly. */ goto cleanup; } /* step 2: look for augmenting paths */ for (k = 0; k < nbV; k++) { v = listV[k]; if ((matchedWithV[v] == -1) && (nbPred[v] > 0)) { /* v is the final node of an augmenting path */ IGRAPH_CHECK(igraph_vector_int_resize(&path, 1)); VECTOR(path)[0] = v; nbDV = 0; nbDU = 0; igraph_i_lad_addToDelete(v, listDV, &nbDV, markedV); do { u = pred[v * sizeOfU + 0]; /* (u, v) belongs to the augmenting path */ IGRAPH_CHECK(igraph_vector_int_push_back(&path, u)); igraph_i_lad_addToDelete(u, listDU, &nbDU, markedU); if (VECTOR(*matchedWithU)[u] != -1) { /* u is not the initial node of the augmenting path */ v = VECTOR(*matchedWithU)[u]; /* (v, u) belongs to the augmenting path */ IGRAPH_CHECK(igraph_vector_int_push_back(&path, v)); igraph_i_lad_addToDelete(v, listDV, &nbDV, markedV); } } while (VECTOR(*matchedWithU)[u] != -1); /* delete nodes of listDV and listDU */ while ((nbDV > 0) || (nbDU > 0)) { while (nbDV > 0) { /* delete v */ v = listDV[--nbDV]; markedV[v] = deleted; u = matchedWithV[v]; if (u != -1) { igraph_i_lad_addToDelete(u, listDU, &nbDU, markedU); } for (i = 0; i < nbPred[v]; i++) { u = pred[v * sizeOfU + i]; /* delete edge (u, v) */ for (j = 0; ((j < nbSucc[u]) && (v != succ[u * sizeOfV + j])); j++) { } succ[u * sizeOfV + j] = succ[u * sizeOfV + (--nbSucc[u])]; if (nbSucc[u] == 0) { igraph_i_lad_addToDelete(u, listDU, &nbDU, markedU); } } } while (nbDU > 0) { /* delete u */ u = listDU[--nbDU]; markedU[u] = deleted; v = VECTOR(*matchedWithU)[u]; if (v != -1) { igraph_i_lad_addToDelete(v, listDV, &nbDV, markedV); } j = 0; for (i = 0; i < nbSucc[u]; i++) { /* delete edge (u, v) */ v = succ[u * sizeOfV + i]; for (j = 0; ((j < nbPred[v]) && (u != pred[v * sizeOfU + j])); j++) { } pred[v * sizeOfU + j] = pred[v * sizeOfU + (--nbPred[v])]; if (nbPred[v] == 0) { igraph_i_lad_addToDelete(v, listDV, &nbDV, markedV); } } } } /* Remove the last node of the augmenting path from the set of unmatched vertices */ u = VECTOR(path)[igraph_vector_int_size(&path) - 1]; i = posInUnmatched[u]; unmatched[i] = unmatched[--nbUnmatched]; posInUnmatched[unmatched[i]] = i; /* Update the matching wrt the augmenting path */ while (igraph_vector_int_size(&path) > 1) { u = igraph_vector_int_pop_back(&path); v = igraph_vector_int_pop_back(&path); w = matchedWithV[v]; /* match v with u instead of v with w */ VECTOR(*matchedWithU)[u] = v; matchedWithV[v] = u; } } } } *invalid = 0; cleanup: /* Free the allocated arrays */ igraph_vector_int_destroy(&path); igraph_free(posInUnmatched); igraph_free(unmatched); igraph_free(markedU); igraph_free(markedV); igraph_free(listDU); igraph_free(listDV); igraph_free(listU); igraph_free(listV); igraph_free(succ); igraph_free(nbSucc); igraph_free(pred); igraph_free(nbPred); igraph_free(matchedWithV); IGRAPH_FINALLY_CLEAN(14); return 0; } void igraph_i_lad_DFS(int nbU, int nbV, int u, bool* marked, int* nbSucc, int* succ, igraph_vector_int_t * matchedWithU, int* order, int* nb) { /* perform a depth first search, starting from u, in the bipartite graph Go=(U, V, E) such that U = vertices of Gp V = vertices of Gt E = { (u, matchedWithU[u]) / u is a vertex of Gp } U { (v, u) / v is a vertex of D[u] which is not matched to v} Given a vertex v of Gt, nbSucc[v]=number of successors of v and succ[v]=list of successors of v. order[nb^out+1..nb^in] contains the vertices discovered by the DFS */ int i; int v = VECTOR(*matchedWithU)[u]; /* the only one predecessor of v is u */ marked[u] = true; if (v >= 0) { for (i = 0; i < nbSucc[v]; i++) { if (!marked[succ[v * nbU + i]]) { igraph_i_lad_DFS(nbU, nbV, succ[v * nbU + i], marked, nbSucc, succ, matchedWithU, order, nb); } } } /* we have finished with u => number it */ order[*nb] = u; (*nb)--; } int igraph_i_lad_SCC(int nbU, int nbV, int* numV, int* numU, int* nbSucc, int* succ, int* nbPred, int* pred, igraph_vector_int_t * matchedWithU, igraph_vector_int_t * matchedWithV) { /* postrelation: numV[v]==numU[u] iff they belong to the same strongly connected component in the bipartite graph Go=(U, V, E) such that U = vertices of Gp V = vertices of Gt E = { (u, matchedWithU[u]) / u is a vertex of Gp } U { (v, u) / v is a vertex of D[u] which is not matched to v} Given a vertex v of Gt, nbSucc[v]=number of sucessors of v and succ[v]=list of successors of v */ int *order; bool *marked; int *fifo; int u, v, i, j, k, nbSCC, nb; /* Allocate memory */ ALLOC_ARRAY(order, nbU, int); ALLOC_ARRAY(marked, nbU, bool); ALLOC_ARRAY(fifo, nbV, int); /* Order vertices of Gp wrt DFS */ nb = nbU - 1; for (u = 0; u < nbU; u++) { if (!marked[u]) { igraph_i_lad_DFS(nbU, nbV, u, marked, nbSucc, succ, matchedWithU, order, &nb); } } /* traversal starting from order[0], then order[1], ... */ nbSCC = 0; memset(numU, -1, (size_t) nbU * sizeof(int)); memset(numV, -1, (size_t) nbV * sizeof(int)); for (i = 0; i < nbU; i++) { u = order[i]; v = VECTOR(*matchedWithU)[u]; if (v == -1) { continue; } if (numV[v] == -1) { /* v belongs to a new SCC */ nbSCC++; k = 1; fifo[0] = v; numV[v] = nbSCC; while (k > 0) { v = fifo[--k]; u = VECTOR(*matchedWithV)[v]; if (u != -1) { numU[u] = nbSCC; for (j = 0; j < nbPred[u]; j++) { v = pred[u * nbV + j]; if (numV[v] == -1) { numV[v] = nbSCC; fifo[k++] = v; } } } } } } /* Free memory */ igraph_free(fifo); igraph_free(marked); igraph_free(order); IGRAPH_FINALLY_CLEAN(3); return 0; } int igraph_i_lad_ensureGACallDiff(bool induced, Tgraph* Gp, Tgraph* Gt, Tdomain* D, int *invalid) { /* precondition: D->globalMatchingP is an all different matching of the pattern vertices postcondition: filter domains wrt GAC(allDiff) return false if an inconsistency is detected; true otherwise Build the bipartite directed graph Go=(U, V, E) such that E = { (u, v) / u is a vertex of Gp which is matched to v (i.e., v=D->globalMatchingP[u])} U { (v, u) / v is a vertex of Gt which is in D(u) but is not matched to u} */ int *nbPred; /* nbPred[u] = nb of predecessors of u in Go */ int *pred; /* pred[u][i] = ith predecessor of u in Go */ int *nbSucc; /* nbSucc[v] = nb of successors of v in Go */ int *succ; /* succ[v][i] = ith successor of v in Go */ int u, v, i, w, oldNbVal, nbToMatch; int *numV, *numU; igraph_vector_int_t toMatch; bool *used; int *list; int nb = 0; bool result; /* Allocate memory */ ALLOC_ARRAY(nbPred, Gp->nbVertices, int); ALLOC_ARRAY(pred, Gp->nbVertices * Gt->nbVertices, int); ALLOC_ARRAY(nbSucc, Gt->nbVertices, int); ALLOC_ARRAY(succ, Gt->nbVertices * Gp->nbVertices, int); ALLOC_ARRAY(numV, Gt->nbVertices, int); ALLOC_ARRAY(numU, Gp->nbVertices, int); ALLOC_ARRAY(used, Gp->nbVertices * Gt->nbVertices, bool); ALLOC_ARRAY(list, Gt->nbVertices, int); IGRAPH_CHECK(igraph_vector_int_init(&toMatch, Gp->nbVertices)); IGRAPH_FINALLY(igraph_vector_int_destroy, &toMatch); for (u = 0; u < Gp->nbVertices; u++) { for (i = 0; i < VECTOR(D->nbVal)[u]; i++) { v = VECTOR(D->val)[ VECTOR(D->firstVal)[u] + i ]; /* v in D(u) */ used[u * Gt->nbVertices + v] = false; if (v != VECTOR(D->globalMatchingP)[u]) { pred[u * Gt->nbVertices + (nbPred[u]++)] = v; succ[v * Gp->nbVertices + (nbSucc[v]++)] = u; } } } /* mark as used all edges of paths starting from free vertices */ for (v = 0; v < Gt->nbVertices; v++) { if (VECTOR(D->globalMatchingT)[v] < 0) { /* v is free */ list[nb++] = v; numV[v] = true; } } while (nb > 0) { v = list[--nb]; for (i = 0; i < nbSucc[v]; i++) { u = succ[v * Gp->nbVertices + i]; used[u * Gt->nbVertices + v] = true; if (numU[u] == false) { numU[u] = true; w = VECTOR(D->globalMatchingP)[u]; used[u * Gt->nbVertices + w] = true; if (numV[w] == false) { list[nb++] = w; numV[w] = true; } } } } /* look for strongly connected components in Go */ IGRAPH_CHECK( igraph_i_lad_SCC((int)(Gp->nbVertices), (int)(Gt->nbVertices), numV, numU, nbSucc, succ, nbPred, pred, &D->globalMatchingP, &D->globalMatchingT)); /* remove v from D[u] if (u, v) is not marked as used and u and v are not in the same SCC and D->globalMatchingP[u] != v */ nbToMatch = 0; for (u = 0; u < Gp->nbVertices; u++) { oldNbVal = VECTOR(D->nbVal)[u]; for (i = 0; i < VECTOR(D->nbVal)[u]; i++) { v = VECTOR(D->val)[ VECTOR(D->firstVal)[u] + i ]; /* v in D(u) */ if ((!used[u * Gt->nbVertices + v]) && (numV[v] != numU[u]) && (VECTOR(D->globalMatchingP)[u] != v)) { IGRAPH_CHECK(igraph_i_lad_removeValue(u, v, D, Gp, Gt, &result)); if (!result) { *invalid = 1; /* Yes, this is ugly. */ goto cleanup; } } } if (VECTOR(D->nbVal)[u] == 0) { *invalid = 1; /* Yes, this is ugly. */ goto cleanup; } if ((oldNbVal > 1) && (VECTOR(D->nbVal)[u] == 1)) { VECTOR(toMatch)[nbToMatch++] = u; } } IGRAPH_CHECK(igraph_i_lad_matchVertices(nbToMatch, &toMatch, induced, D, Gp, Gt, invalid)); cleanup: igraph_vector_int_destroy(&toMatch); igraph_free(list); igraph_free(used); igraph_free(numU); igraph_free(numV); igraph_free(succ); igraph_free(nbSucc); igraph_free(pred); igraph_free(nbPred); IGRAPH_FINALLY_CLEAN(9); return 0; } /* ---------------------------------------------------------*/ /* Coming from lad.c */ /* ---------------------------------------------------------*/ int igraph_i_lad_checkLAD(int u, int v, Tdomain* D, Tgraph* Gp, Tgraph* Gt, bool *result) { /* return true if G_(u, v) has a adj(u)-covering matching; false otherwise */ int u2, v2, i, j; int nbMatched = 0; igraph_vector_int_t *Gp_uneis = igraph_adjlist_get(&Gp->succ, u); int *num, *numInv; igraph_vector_int_t nbComp; igraph_vector_int_t firstComp; igraph_vector_int_t comp; int nbNum = 0; int posInComp = 0; igraph_vector_int_t matchedWithU; int invalid; /* special case when u has only 1 adjacent node => no need to call Hopcroft and Karp */ if (VECTOR(Gp->nbSucc)[u] == 1) { u2 = (int) VECTOR(*Gp_uneis)[0]; /* u2 is the only node adjacent to u */ v2 = VECTOR(D->matching)[ MATRIX(D->firstMatch, u, v) ]; if ((v2 != -1) && (igraph_i_lad_isInD(u2, v2, D))) { *result = true; return 0; } /* look for a support of edge (u, u2) for v */ for (i = VECTOR(D->firstVal)[u2]; i < VECTOR(D->firstVal)[u2] + VECTOR(D->nbVal)[u2]; i++) { if (MATRIX(Gt->isEdge, v, VECTOR(D->val)[i])) { VECTOR(D->matching)[ MATRIX(D->firstMatch, u, v) ] = VECTOR(D->val)[i]; *result = true; return 0; } } *result = false; return 0; } /* general case (when u has more than 1 adjacent node) */ for (i = 0; i < VECTOR(Gp->nbSucc)[u]; i++) { /* remove from the matching of G_(u, v) edges which no longer belong to G_(u, v) */ u2 = (int) VECTOR(*Gp_uneis)[i]; v2 = VECTOR(D->matching)[ MATRIX(D->firstMatch, u, v) + i]; if ((v2 != -1) && (igraph_i_lad_isInD(u2, v2, D))) { nbMatched++; } } if (nbMatched == VECTOR(Gp->nbSucc)[u]) { *result = true; return 0; } /* The matching still covers adj(u) */ /* Allocate memory */ ALLOC_ARRAY(num, Gt->nbVertices, int); ALLOC_ARRAY(numInv, Gt->nbVertices, int); /* Build the bipartite graph let U be the set of nodes adjacent to u let V be the set of nodes that are adjacent to v, and that belong to domains of nodes of U */ /* nbComp[u]=number of elements of V that are compatible with u */ IGRAPH_CHECK(igraph_vector_int_init(&nbComp, (long int) VECTOR(Gp->nbSucc)[u])); IGRAPH_FINALLY(igraph_vector_int_destroy, &nbComp); IGRAPH_CHECK(igraph_vector_int_init(&firstComp, (long int) VECTOR(Gp->nbSucc)[u])); IGRAPH_FINALLY(igraph_vector_int_destroy, &firstComp); /* comp[firstComp[u]..firstComp[u]+nbComp[u]-1] = nodes of Gt that are compatible with u */ IGRAPH_CHECK(igraph_vector_int_init(&comp, (long int) (VECTOR(Gp->nbSucc)[u] * Gt->nbVertices))); IGRAPH_FINALLY(igraph_vector_int_destroy, &comp); IGRAPH_CHECK(igraph_vector_int_init(&matchedWithU, (long int) VECTOR(Gp->nbSucc)[u])); IGRAPH_FINALLY(igraph_vector_int_destroy, &matchedWithU); memset(num, -1, (size_t) (Gt->nbVertices) * sizeof(int)); for (i = 0; i < VECTOR(Gp->nbSucc)[u]; i++) { u2 = (int) VECTOR(*Gp_uneis)[i]; /* u2 is adjacent to u */ /* search for all nodes v2 in D[u2] which are adjacent to v */ VECTOR(nbComp)[i] = 0; VECTOR(firstComp)[i] = posInComp; if (VECTOR(D->nbVal)[u2] > VECTOR(Gt->nbSucc)[v]) { for (j = VECTOR(D->firstVal)[u2]; j < VECTOR(D->firstVal)[u2] + VECTOR(D->nbVal)[u2]; j++) { v2 = VECTOR(D->val)[j]; /* v2 belongs to D[u2] */ if (MATRIX(Gt->isEdge, v, v2)) { /* v2 is a successor of v */ if (num[v2] < 0) { /* v2 has not yet been added to V */ num[v2] = nbNum; numInv[nbNum++] = v2; } VECTOR(comp)[posInComp++] = num[v2]; VECTOR(nbComp)[i]++; } } } else { igraph_vector_int_t *Gt_vneis = igraph_adjlist_get(&Gt->succ, v); for (j = 0; j < VECTOR(Gt->nbSucc)[v]; j++) { v2 = (int) VECTOR(*Gt_vneis)[j]; /* v2 is a successor of v */ if (igraph_i_lad_isInD(u2, v2, D)) { /* v2 belongs to D[u2] */ if (num[v2] < 0) { /* v2 has not yet been added to V */ num[v2] = nbNum; numInv[nbNum++] = v2; } VECTOR(comp)[posInComp++] = num[v2]; VECTOR(nbComp)[i]++; } } } if (VECTOR(nbComp)[i] == 0) { *result = false; /* u2 has no compatible vertex in succ[v] */ goto cleanup; } /* u2 is matched to v2 in the matching that supports (u, v) */ v2 = VECTOR(D->matching)[ MATRIX(D->firstMatch, u, v) + i]; if ((v2 != -1) && (igraph_i_lad_isInD(u2, v2, D))) { VECTOR(matchedWithU)[i] = num[v2]; } else { VECTOR(matchedWithU)[i] = -1; } } /* Call Hopcroft Karp to update the matching */ IGRAPH_CHECK( igraph_i_lad_updateMatching((int) VECTOR(Gp->nbSucc)[u], nbNum, &nbComp, &firstComp, &comp, &matchedWithU, &invalid) ); if (invalid) { *result = false; goto cleanup; } for (i = 0; i < VECTOR(Gp->nbSucc)[u]; i++) { VECTOR(D->matching)[ MATRIX(D->firstMatch, u, v) + i] = numInv[ VECTOR(matchedWithU)[i] ]; } *result = true; cleanup: igraph_free(numInv); igraph_free(num); igraph_vector_int_destroy(&matchedWithU); igraph_vector_int_destroy(&comp); igraph_vector_int_destroy(&firstComp); igraph_vector_int_destroy(&nbComp); IGRAPH_FINALLY_CLEAN(6); return 0; } /* ---------------------------------------------------------*/ /* Coming from main.c */ /* ---------------------------------------------------------*/ int igraph_i_lad_filter(bool induced, Tdomain* D, Tgraph* Gp, Tgraph* Gt, bool *result) { /* filter domains of all vertices in D->toFilter wrt LAD and ensure GAC(allDiff) return false if some domain becomes empty; true otherwise */ int u, v, i, oldNbVal; int invalid; bool result2; while (!igraph_i_lad_toFilterEmpty(D)) { while (!igraph_i_lad_toFilterEmpty(D)) { u = igraph_i_lad_nextToFilter(D, (int) (Gp->nbVertices)); oldNbVal = VECTOR(D->nbVal)[u]; i = VECTOR(D->firstVal)[u]; while (i < VECTOR(D->firstVal)[u] + VECTOR(D->nbVal)[u]) { /* for every target node v in D(u), check if G_(u, v) has a covering matching */ v = VECTOR(D->val)[i]; IGRAPH_CHECK(igraph_i_lad_checkLAD(u, v, D, Gp, Gt, &result2)); if (result2) { i++; } else { IGRAPH_CHECK(igraph_i_lad_removeValue(u, v, D, Gp, Gt, &result2)); if (!result2) { *result = false; return 0; } } } if ((VECTOR(D->nbVal)[u] == 1) && (oldNbVal > 1) && (!igraph_i_lad_matchVertex(u, induced, D, Gp, Gt))) { *result = false; return 0; } if (VECTOR(D->nbVal)[u] == 0) { *result = false; return 0; } } igraph_i_lad_ensureGACallDiff(induced, Gp, Gt, D, &invalid); if (invalid) { *result = false; return 0; } } *result = true; return 0; } int igraph_i_lad_solve(int timeLimit, bool firstSol, bool induced, Tdomain* D, Tgraph* Gp, Tgraph* Gt, int *invalid, igraph_bool_t *iso, igraph_vector_t *map, igraph_vector_ptr_t *maps, int *nbNodes, int *nbFail, int *nbSol, clock_t *begin, igraph_vector_ptr_t *alloc_history) { /* if firstSol then search for the first solution; otherwise search for all solutions if induced then search for induced subgraphs; otherwise search for partial subgraphs return false if CPU time limit exceeded before the search is completed, return true otherwise */ int u, v, minDom, i; int* nbVal; int* globalMatching; clock_t end = clock(); igraph_vector_t *vec; int* val; bool result; (*nbNodes)++; if ( (double)(end - *begin) / CLOCKS_PER_SEC >= timeLimit) { /* CPU time limit exceeded */ IGRAPH_ERROR("LAD CPU time exceeded", IGRAPH_CPUTIME); } /* Allocate memory */ ALLOC_ARRAY_IN_HISTORY(nbVal, Gp->nbVertices, int, alloc_history); ALLOC_ARRAY_IN_HISTORY(globalMatching, Gp->nbVertices, int, alloc_history); IGRAPH_CHECK(igraph_i_lad_filter(induced, D, Gp, Gt, &result)); if (!result) { /* filtering has detected an inconsistency */ (*nbFail)++; igraph_i_lad_resetToFilter(D); *invalid = 0; goto cleanup; } /* The current node of the search tree is consistent wrt to LAD and GAC(allDiff) Save domain sizes and global all different matching and search for the non matched vertex minDom with smallest domain */ minDom = -1; for (u = 0; u < Gp->nbVertices; u++) { nbVal[u] = VECTOR(D->nbVal)[u]; if ((nbVal[u] > 1) && ((minDom < 0) || (nbVal[u] < nbVal[minDom]))) { minDom = u; } globalMatching[u] = VECTOR(D->globalMatchingP)[u]; } if (minDom == -1) { /* All vertices are matched => Solution found */ if (iso) { *iso = 1; } (*nbSol)++; if (map && igraph_vector_size(map) == 0) { IGRAPH_CHECK(igraph_vector_resize(map, Gp->nbVertices)); for (u = 0; u < Gp->nbVertices; u++) { VECTOR(*map)[u] = VECTOR(D->val)[ VECTOR(D->firstVal)[u] ]; } } if (maps) { vec = igraph_Calloc(1, igraph_vector_t); if (!vec) { IGRAPH_ERROR("LAD failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, vec); IGRAPH_CHECK(igraph_vector_init(vec, Gp->nbVertices)); IGRAPH_FINALLY(igraph_vector_destroy, vec); for (u = 0; u < Gp->nbVertices; u++) { VECTOR(*vec)[u] = VECTOR(D->val)[ VECTOR(D->firstVal)[u] ]; } IGRAPH_CHECK(igraph_vector_ptr_push_back(maps, vec)); IGRAPH_FINALLY_CLEAN(2); } igraph_i_lad_resetToFilter(D); *invalid = 0; goto cleanup; } /* save the domain of minDom to iterate on its values */ ALLOC_ARRAY_IN_HISTORY(val, VECTOR(D->nbVal)[minDom], int, alloc_history); for (i = 0; i < VECTOR(D->nbVal)[minDom]; i++) { val[i] = VECTOR(D->val)[ VECTOR(D->firstVal)[minDom] + i ]; } /* branch on minDom=v, for every target node v in D(u) */ for (i = 0; ((i < nbVal[minDom]) && ((firstSol == 0) || (*nbSol == 0))); i++) { IGRAPH_ALLOW_INTERRUPTION(); v = val[i]; IGRAPH_CHECK(igraph_i_lad_removeAllValuesButOne(minDom, v, D, Gp, Gt, &result)); if (!result || (!igraph_i_lad_matchVertex(minDom, induced, D, Gp, Gt))) { (*nbFail)++; (*nbNodes)++; igraph_i_lad_resetToFilter(D); } else { IGRAPH_CHECK(igraph_i_lad_solve(timeLimit, firstSol, induced, D, Gp, Gt, invalid, iso, map, maps, nbNodes, nbFail, nbSol, begin, alloc_history)); } /* restore domain sizes and global all different matching */ igraph_vector_int_fill(&D->globalMatchingT, -1); for (u = 0; u < Gp->nbVertices; u++) { VECTOR(D->nbVal)[u] = nbVal[u]; VECTOR(D->globalMatchingP)[u] = globalMatching[u]; VECTOR(D->globalMatchingT)[globalMatching[u]] = u; } } *invalid = 0; igraph_free(val); igraph_vector_ptr_pop_back(alloc_history); cleanup: igraph_free(globalMatching); igraph_vector_ptr_pop_back(alloc_history); igraph_free(nbVal); igraph_vector_ptr_pop_back(alloc_history); return 0; } /** * \section about_lad * * * The LAD algorithm can search for a subgraph in a larger graph, or check * if two graphs are isomorphic. * See Christine Solnon: AllDifferent-based Filtering for Subgraph * Isomorphism. Artificial Intelligence, 174(12-13):850-864, 2010. * https://doi.org/10.1016/j.artint.2010.05.002 * as well as the homepage of the LAD library at http://liris.cnrs.fr/csolnon/LAD.html * The implementation in igraph is based on LADv1, but it is * modified to use igraph's own memory allocation and error handling. * * * * LAD uses the concept of domains to indicate vertex compatibility when matching the * pattern graph. Domains can be used to implement matching of colored vertices. * * * * LAD works with both directed and undirected graphs. Only simple graphs are supported. * */ /** * \function igraph_subisomorphic_lad * Check subgraph isomorphism with the LAD algorithm * * Check whether \p pattern is isomorphic to a subgraph os \p target. * The original LAD implementation by Christine Solnon was used as the * basis of this code. * * * See more about LAD at http://liris.cnrs.fr/csolnon/LAD.html and in * Christine Solnon: AllDifferent-based Filtering for Subgraph * Isomorphism. Artificial Intelligence, 174(12-13):850-864, 2010. * https://doi.org/10.1016/j.artint.2010.05.002 * * \param pattern The smaller graph, it can be directed or undirected. * \param target The bigger graph, it can be directed or undirected. * \param domains A pointer vector, or a null pointer. If a pointer * vector, then it must contain pointers to \c igraph_vector_t * objects and the length of the vector must match the number of * vertices in the \p pattern graph. For each vertex, the ids of * the compatible vertices in the target graph are listed. * \param iso Pointer to a boolean, or a null pointer. If not a null * pointer, then the boolean is set to TRUE (1) if a subgraph * isomorphism is found, and to FALSE (0) otherwise. * \param map Pointer to a vector or a null pointer. If not a null * pointer and a subgraph isomorphism is found, the matching * vertices from the target graph are listed here, for each vertex * (in vertex id order) from the pattern graph. * \param maps Pointer vector or a null pointer. If not a null * pointer, then all subgraph isomorphisms are stored in the * pointer vector, in \c igraph_vector_t objects. * \param induced Boolean, whether to search for induced matching * subgraphs. * \param time_limit Processor time limit in seconds. Supply zero * here for no limit. If the time limit is over, then the function * signals an error. * \return Error code * * \sa \ref igraph_subisomorphic_vf2() for the VF2 algorithm. * * Time complexity: exponential. * * \example examples/simple/igraph_subisomorphic_lad.c */ int igraph_subisomorphic_lad(const igraph_t *pattern, const igraph_t *target, igraph_vector_ptr_t *domains, igraph_bool_t *iso, igraph_vector_t *map, igraph_vector_ptr_t *maps, igraph_bool_t induced, int time_limit) { bool firstSol = maps == 0; bool initialDomains = domains != 0; Tgraph Gp, Gt; Tdomain D; int invalidDomain; int u, nbToMatch = 0; igraph_vector_int_t toMatch; /* Number of nodes in the search tree */ int nbNodes = 0; /* number of failed nodes in the search tree */ int nbFail = 0; /* number of solutions found */ int nbSol = 0; /* reusable structure to get CPU time usage */ clock_t begin = clock(); /* Stack to store memory blocks that are allocated during igraph_i_lad_solve */ igraph_vector_ptr_t alloc_history; if (!iso && !map && !maps) { IGRAPH_ERROR("Please give least one of `iso', `map' or `maps'", IGRAPH_EINVAL); } if (igraph_is_directed(pattern) != igraph_is_directed(target)) { IGRAPH_ERROR("Cannot search for a directed pattern in an undirected target " "or vice versa", IGRAPH_EINVAL); } if (time_limit <= 0) { time_limit = INT_MAX; } if (iso) { *iso = (igraph_vcount(pattern) == 0); } if (map) { igraph_vector_clear(map); } if (maps) { igraph_vector_ptr_clear(maps); } if (igraph_vcount(pattern) == 0) { /* Special case for empty graphs */ return IGRAPH_SUCCESS; } IGRAPH_CHECK(igraph_i_lad_createGraph(pattern, &Gp)); IGRAPH_CHECK(igraph_i_lad_createGraph(target, &Gt)); if (Gp.nbVertices > Gt.nbVertices) { goto exit3; } IGRAPH_CHECK(igraph_i_lad_initDomains(initialDomains, domains, &D, &Gp, &Gt, &invalidDomain)); if (invalidDomain) { goto exit2; } IGRAPH_CHECK(igraph_i_lad_updateMatching((int) (Gp.nbVertices), (int) (Gt.nbVertices), &D.nbVal, &D.firstVal, &D.val, &D.globalMatchingP, &invalidDomain)); if (invalidDomain) { goto exit; } IGRAPH_CHECK(igraph_i_lad_ensureGACallDiff((char) induced, &Gp, &Gt, &D, &invalidDomain)); if (invalidDomain) { goto exit; } for (u = 0; u < Gp.nbVertices; u++) { VECTOR(D.globalMatchingT)[ VECTOR(D.globalMatchingP)[u] ] = u; } IGRAPH_CHECK(igraph_vector_int_init(&toMatch, Gp.nbVertices)); IGRAPH_FINALLY(igraph_vector_int_destroy, &toMatch); for (u = 0; u < Gp.nbVertices; u++) { if (VECTOR(D.nbVal)[u] == 1) { VECTOR(toMatch)[nbToMatch++] = u; } } IGRAPH_CHECK(igraph_i_lad_matchVertices(nbToMatch, &toMatch, (char) induced, &D, &Gp, &Gt, &invalidDomain)); igraph_vector_int_destroy(&toMatch); IGRAPH_FINALLY_CLEAN(1); if (invalidDomain) { goto exit; } IGRAPH_CHECK(igraph_vector_ptr_init(&alloc_history, 0)); IGRAPH_FINALLY(igraph_vector_ptr_destroy_all, &alloc_history); IGRAPH_CHECK(igraph_i_lad_solve(time_limit, firstSol, (char) induced, &D, &Gp, &Gt, &invalidDomain, iso, map, maps, &nbNodes, &nbFail, &nbSol, &begin, &alloc_history)); igraph_vector_ptr_destroy_all(&alloc_history); IGRAPH_FINALLY_CLEAN(1); exit: igraph_vector_int_destroy(&D.val); igraph_vector_int_destroy(&D.matching); IGRAPH_FINALLY_CLEAN(2); exit2: igraph_vector_int_destroy(&D.globalMatchingP); igraph_vector_int_destroy(&D.globalMatchingT); igraph_vector_int_destroy(&D.nbVal); igraph_vector_int_destroy(&D.firstVal); igraph_matrix_int_destroy(&D.posInVal); igraph_matrix_int_destroy(&D.firstMatch); igraph_vector_char_destroy(&D.markedToFilter); igraph_vector_int_destroy(&D.toFilter); IGRAPH_FINALLY_CLEAN(8); exit3: igraph_matrix_char_destroy(&Gt.isEdge); igraph_adjlist_destroy(&Gt.succ); igraph_vector_destroy(&Gt.nbSucc); igraph_matrix_char_destroy(&Gp.isEdge); igraph_adjlist_destroy(&Gp.succ); igraph_vector_destroy(&Gp.nbSucc); IGRAPH_FINALLY_CLEAN(6); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/igraph_psumtree.c0000644000076500000240000000562113614300625024744 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA Copyright (C) 2006 Elliot Paquette Kalamazoo College, 1200 Academy st, Kalamazoo, MI This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_types.h" #include "igraph_psumtree.h" #include "igraph_error.h" #include "config.h" #include #include double igraph_i_log2(double f) { return log(f) / log(2.0); } int igraph_psumtree_init(igraph_psumtree_t *t, long int size) { t->size = size; t->offset = (long int) (pow(2, ceil(igraph_i_log2(size))) - 1); IGRAPH_CHECK(igraph_vector_init((igraph_vector_t *)t, t->offset + t->size)); return 0; } void igraph_psumtree_reset(igraph_psumtree_t *t) { igraph_vector_fill(&(t->v), 0); } void igraph_psumtree_destroy(igraph_psumtree_t *t) { igraph_vector_destroy((igraph_vector_t *)t); } igraph_real_t igraph_psumtree_get(const igraph_psumtree_t *t, long int idx) { const igraph_vector_t *tree = &t->v; return VECTOR(*tree)[t->offset + idx]; } int igraph_psumtree_search(const igraph_psumtree_t *t, long int *idx, igraph_real_t search) { const igraph_vector_t *tree = &t->v; long int i = 1; long int size = igraph_vector_size(tree); while ( 2 * i + 1 <= size) { if ( search <= VECTOR(*tree)[i * 2 - 1] ) { i <<= 1; } else { search -= VECTOR(*tree)[i * 2 - 1]; i <<= 1; i += 1; } } if (2 * i <= size) { i = 2 * i; } *idx = i - t->offset - 1; return IGRAPH_SUCCESS; } int igraph_psumtree_update(igraph_psumtree_t *t, long int idx, igraph_real_t new_value) { const igraph_vector_t *tree = &t->v; igraph_real_t difference; idx = idx + t->offset + 1; difference = new_value - VECTOR(*tree)[idx - 1]; while ( idx >= 1 ) { VECTOR(*tree)[idx - 1] += difference; idx >>= 1; } return IGRAPH_SUCCESS; } long int igraph_psumtree_size(const igraph_psumtree_t *t) { return t->size; } igraph_real_t igraph_psumtree_sum(const igraph_psumtree_t *t) { return VECTOR(t->v)[0]; } python-igraph-0.8.0/vendor/source/igraph/src/igraph_error.c0000644000076500000240000002473413614300625024237 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2005-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "config.h" #include "igraph_error.h" #include "igraph_types.h" #include #include #include #include static IGRAPH_THREAD_LOCAL igraph_error_handler_t *igraph_i_error_handler = 0; static IGRAPH_THREAD_LOCAL char igraph_i_errormsg_buffer[500]; static IGRAPH_THREAD_LOCAL char igraph_i_warningmsg_buffer[500]; /* Error strings corresponding to each igraph_error_type_t enum value. */ static const char *igraph_i_error_strings[] = { /* 0 */ "No error", /* 1 */ "Failed", /* 2 */ "Out of memory", /* 3 */ "Parse error", /* 4 */ "Invalid value", /* 5 */ "Already exists", /* 6 */ "Invalid edge vector", /* 7 */ "Invalid vertex id", /* 8 */ "Non-square matrix", /* 9 */ "Invalid mode", /* 10 */ "File operation error", /* 11 */ "Unfold infinite iterator", /* 12 */ "Unimplemented function call", /* 13 */ "Interrupted", /* 14 */ "Numeric procedure did not converge", /* 15 */ "Matrix-vector product failed", /* 16 */ "N must be positive", /* 17 */ "NEV must be positive", /* 18 */ "NCV must be greater than NEV and less than or equal to N " "(and for the non-symmetric solver NCV-NEV >=2 must also hold)", /* 19 */ "Maximum number of iterations should be positive", /* 20 */ "Invalid WHICH parameter", /* 21 */ "Invalid BMAT parameter", /* 22 */ "WORKL is too small", /* 23 */ "LAPACK error in tridiagonal eigenvalue calculation", /* 24 */ "Starting vector is zero", /* 25 */ "MODE is invalid", /* 26 */ "MODE and BMAT are not compatible", /* 27 */ "ISHIFT must be 0 or 1", /* 28 */ "NEV and WHICH='BE' are incompatible", /* 29 */ "Could not build an Arnoldi factorization", /* 30 */ "No eigenvalues to sufficient accuracy", /* 31 */ "HOWMNY is invalid", /* 32 */ "HOWMNY='S' is not implemented", /* 33 */ "Different number of converged Ritz values", /* 34 */ "Error from calculation of a real Schur form", /* 35 */ "LAPACK (dtrevc) error for calculating eigenvectors", /* 36 */ "Unknown ARPACK error", /* 37 */ "Negative loop detected while calculating shortest paths", /* 38 */ "Internal error, likely a bug in igraph", /* 39 */ "Maximum number of iterations reached", /* 40 */ "No shifts could be applied during a cycle of the " "Implicitly restarted Arnoldi iteration. One possibility " "is to increase the size of NCV relative to NEV", /* 41 */ "The Schur form computed by LAPACK routine dlahqr " "could not be reordered by LAPACK routine dtrsen.", /* 42 */ "Big integer division by zero", /* 43 */ "GLPK Error, GLP_EBOUND", /* 44 */ "GLPK Error, GLP_EROOT", /* 45 */ "GLPK Error, GLP_ENOPFS", /* 46 */ "GLPK Error, GLP_ENODFS", /* 47 */ "GLPK Error, GLP_EFAIL", /* 48 */ "GLPK Error, GLP_EMIPGAP", /* 49 */ "GLPK Error, GLP_ETMLIM", /* 50 */ "GLPK Error, GLP_STOP", /* 51 */ "Internal attribute handler error", /* 52 */ "Unimplemented attribute combination for this type", /* 53 */ "LAPACK call resulted an error", /* 54 */ "Internal DrL error", /* 55 */ "Integer or double overflow", /* 56 */ "Internal GPLK error", /* 57 */ "CPU time exceeded", /* 58 */ "Integer or double underflow", /* 59 */ "Random walk got stuck", /* 60 */ "Search stopped; this error should never be visible to the user, " "please report this error along with the steps to reproduce it." }; const char* igraph_strerror(const int igraph_errno) { if (igraph_errno < 0 || igraph_errno >= sizeof(igraph_i_error_strings) / sizeof(char *)) { return "Invalid error code; no error string available."; } return igraph_i_error_strings[igraph_errno]; } int igraph_error(const char *reason, const char *file, int line, int igraph_errno) { if (igraph_i_error_handler) { igraph_i_error_handler(reason, file, line, igraph_errno); #ifndef USING_R } else { igraph_error_handler_abort(reason, file, line, igraph_errno); #endif } return igraph_errno; } int igraph_errorf(const char *reason, const char *file, int line, int igraph_errno, ...) { va_list ap; va_start(ap, igraph_errno); vsnprintf(igraph_i_errormsg_buffer, sizeof(igraph_i_errormsg_buffer) / sizeof(char), reason, ap); return igraph_error(igraph_i_errormsg_buffer, file, line, igraph_errno); } int igraph_errorvf(const char *reason, const char *file, int line, int igraph_errno, va_list ap) { vsnprintf(igraph_i_errormsg_buffer, sizeof(igraph_i_errormsg_buffer) / sizeof(char), reason, ap); return igraph_error(igraph_i_errormsg_buffer, file, line, igraph_errno); } #ifndef USING_R void igraph_error_handler_abort (const char *reason, const char *file, int line, int igraph_errno) { fprintf(stderr, "Error at %s:%i :%s, %s\n", file, line, reason, igraph_strerror(igraph_errno)); abort(); } #endif void igraph_error_handler_ignore (const char *reason, const char *file, int line, int igraph_errno) { IGRAPH_UNUSED(reason); IGRAPH_UNUSED(file); IGRAPH_UNUSED(line); IGRAPH_UNUSED(igraph_errno); IGRAPH_FINALLY_FREE(); } #ifndef USING_R void igraph_error_handler_printignore (const char *reason, const char *file, int line, int igraph_errno) { IGRAPH_FINALLY_FREE(); fprintf(stderr, "Error at %s:%i :%s, %s\n", file, line, reason, igraph_strerror(igraph_errno)); } #endif igraph_error_handler_t * igraph_set_error_handler (igraph_error_handler_t * new_handler) { igraph_error_handler_t * previous_handler = igraph_i_error_handler; igraph_i_error_handler = new_handler; return previous_handler; } IGRAPH_THREAD_LOCAL struct igraph_i_protectedPtr igraph_i_finally_stack[100]; /* * Adds another element to the free list */ void IGRAPH_FINALLY_REAL(void (*func)(void*), void* ptr) { int no = igraph_i_finally_stack[0].all; assert (no < 100); assert (no >= 0); igraph_i_finally_stack[no].ptr = ptr; igraph_i_finally_stack[no].func = func; igraph_i_finally_stack[0].all ++; /* printf("--> Finally stack contains now %d elements\n", igraph_i_finally_stack[0].all); */ } void IGRAPH_FINALLY_CLEAN(int minus) { igraph_i_finally_stack[0].all -= minus; if (igraph_i_finally_stack[0].all < 0) { /* fprintf(stderr, "corrupt finally stack, popping %d elements when only %d left\n", minus, igraph_i_finally_stack[0].all+minus); */ igraph_i_finally_stack[0].all = 0; } /* printf("<-- Finally stack contains now %d elements\n", igraph_i_finally_stack[0].all); */ } void IGRAPH_FINALLY_FREE(void) { int p; /* printf("[X] Finally stack will be cleaned (contained %d elements)\n", igraph_i_finally_stack[0].all); */ for (p = igraph_i_finally_stack[0].all - 1; p >= 0; p--) { igraph_i_finally_stack[p].func(igraph_i_finally_stack[p].ptr); } igraph_i_finally_stack[0].all = 0; } int IGRAPH_FINALLY_STACK_SIZE(void) { return igraph_i_finally_stack[0].all; } static IGRAPH_THREAD_LOCAL igraph_warning_handler_t *igraph_i_warning_handler = 0; /** * \function igraph_warning_handler_ignore * Ignore all warnings * * This warning handler function simply ignores all warnings. * \param reason Textual description of the warning. * \param file The source file in which the warning was noticed. * \param line The number of line in the source file which triggered the * warning.. * \param igraph_errno Warnings could have potentially error codes as well, * but this is currently not used in igraph. */ void igraph_warning_handler_ignore (const char *reason, const char *file, int line, int igraph_errno) { IGRAPH_UNUSED(reason); IGRAPH_UNUSED(file); IGRAPH_UNUSED(line); IGRAPH_UNUSED(igraph_errno); } #ifndef USING_R /** * \function igraph_warning_handler_print * Print all warning to the standard error * * This warning handler function simply prints all warnings to the * standard error. * \param reason Textual description of the warning. * \param file The source file in which the warning was noticed. * \param line The number of line in the source file which triggered the * warning.. * \param igraph_errno Warnings could have potentially error codes as well, * but this is currently not used in igraph. */ void igraph_warning_handler_print (const char *reason, const char *file, int line, int igraph_errno) { IGRAPH_UNUSED(igraph_errno); fprintf(stderr, "Warning: %s in file %s, line %i\n", reason, file, line); } #endif int igraph_warning(const char *reason, const char *file, int line, int igraph_errno) { if (igraph_i_warning_handler) { igraph_i_warning_handler(reason, file, line, igraph_errno); #ifndef USING_R } else { igraph_warning_handler_print(reason, file, line, igraph_errno); #endif } return igraph_errno; } int igraph_warningf(const char *reason, const char *file, int line, int igraph_errno, ...) { va_list ap; va_start(ap, igraph_errno); vsnprintf(igraph_i_warningmsg_buffer, sizeof(igraph_i_warningmsg_buffer) / sizeof(char), reason, ap); return igraph_warning(igraph_i_warningmsg_buffer, file, line, igraph_errno); } igraph_warning_handler_t * igraph_set_warning_handler (igraph_warning_handler_t * new_handler) { igraph_warning_handler_t * previous_handler = igraph_i_warning_handler; igraph_i_warning_handler = new_handler; return previous_handler; } python-igraph-0.8.0/vendor/source/igraph/src/igraph_cliquer.h0000644000076500000240000000242413614300625024547 0ustar tamasstaff00000000000000#ifndef IGRAPH_CLIQUER_H #define IGRAPH_CLIQUER_H #include "igraph_types_internal.h" #include "igraph_interface.h" #include "igraph_cliques.h" int igraph_i_cliquer_cliques(const igraph_t *graph, igraph_vector_ptr_t *res, igraph_integer_t min_size, igraph_integer_t max_size); int igraph_i_cliquer_histogram(const igraph_t *graph, igraph_vector_t *hist, igraph_integer_t min_size, igraph_integer_t max_size); int igraph_i_cliquer_callback(const igraph_t *graph, igraph_integer_t min_size, igraph_integer_t max_size, igraph_clique_handler_t *cliquehandler_fn, void *arg); int igraph_i_weighted_cliques(const igraph_t *graph, const igraph_vector_t *vertex_weights, igraph_vector_ptr_t *res, igraph_real_t min_weight, igraph_real_t max_weight, igraph_bool_t maximal); int igraph_i_largest_weighted_cliques(const igraph_t *graph, const igraph_vector_t *vertex_weights, igraph_vector_ptr_t *res); int igraph_i_weighted_clique_number(const igraph_t *graph, const igraph_vector_t *vertex_weights, igraph_real_t *res); #endif // IGRAPH_CLIQUER_H python-igraph-0.8.0/vendor/source/igraph/src/igraph_fixed_vectorlist.c0000644000076500000240000000503213614300625026451 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_types_internal.h" #include "igraph_memory.h" void igraph_fixed_vectorlist_destroy(igraph_fixed_vectorlist_t *l) { long int i, n = igraph_vector_ptr_size(&l->v); for (i = 0; i < n; i++) { igraph_vector_t *v = VECTOR(l->v)[i]; if (v) { igraph_vector_destroy(v); } } igraph_vector_ptr_destroy(&l->v); igraph_free(l->vecs); } int igraph_fixed_vectorlist_convert(igraph_fixed_vectorlist_t *l, const igraph_vector_t *from, long int size) { igraph_vector_t sizes; long int i, no = igraph_vector_size(from); l->vecs = igraph_Calloc(size, igraph_vector_t); if (!l->vecs) { IGRAPH_ERROR("Cannot merge attributes for simplify", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, l->vecs); IGRAPH_CHECK(igraph_vector_ptr_init(&l->v, size)); IGRAPH_FINALLY(igraph_fixed_vectorlist_destroy, &l->v); IGRAPH_VECTOR_INIT_FINALLY(&sizes, size); for (i = 0; i < no; i++) { long int to = (long int) VECTOR(*from)[i]; if (to >= 0) { VECTOR(sizes)[to] += 1; } } for (i = 0; i < size; i++) { igraph_vector_t *v = &(l->vecs[i]); IGRAPH_CHECK(igraph_vector_init(v, (long int) VECTOR(sizes)[i])); igraph_vector_clear(v); VECTOR(l->v)[i] = v; } for (i = 0; i < no; i++) { long int to = (long int) VECTOR(*from)[i]; if (to >= 0) { igraph_vector_t *v = &(l->vecs[to]); igraph_vector_push_back(v, i); } } igraph_vector_destroy(&sizes); IGRAPH_FINALLY_CLEAN(3); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/forestfire.c0000644000076500000240000002332413614300625023716 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_games.h" #include "igraph_memory.h" #include "igraph_random.h" #include "igraph_progress.h" #include "igraph_interrupt_internal.h" #include "igraph_interface.h" #include "igraph_constructors.h" #include "igraph_dqueue.h" #include "config.h" typedef struct igraph_i_forest_fire_data_t { igraph_vector_t *inneis; igraph_vector_t *outneis; long int no_of_nodes; } igraph_i_forest_fire_data_t; void igraph_i_forest_fire_free(igraph_i_forest_fire_data_t *data) { long int i; for (i = 0; i < data->no_of_nodes; i++) { igraph_vector_destroy(data->inneis + i); igraph_vector_destroy(data->outneis + i); } } /** * \function igraph_forest_fire_game * \brief Generates a network according to the \quote forest fire game \endquote * * The forest fire model intends to reproduce the following network * characteristics, observed in real networks: * \ilist * \ili Heavy-tailed in-degree distribution. * \ili Heavy-tailed out-degree distribution. * \ili Communities. * \ili Densification power-law. The network is densifying in time, * according to a power-law rule. * \ili Shrinking diameter. The diameter of the network decreases in * time. * \endilist * * * The network is generated in the following way. One vertex is added at * a time. This vertex connects to (cites) ambs vertices already * present in the network, chosen uniformly random. Now, for each cited * vertex v we do the following procedure: * \olist * \oli We generate two random number, x and y, that are * geometrically distributed with means p/(1-p) and * rp(1-rp). (p is fw_prob, r is * bw_factor.) The new vertex cites x outgoing neighbors * and y incoming neighbors of v, from those which are * not yet cited by the new vertex. If there are less than x or * y such vertices available then we cite all of them. * \oli The same procedure is applied to all the newly cited * vertices. * \endolist * * See also: * Jure Leskovec, Jon Kleinberg and Christos Faloutsos. Graphs over time: * densification laws, shrinking diameters and possible explanations. * \emb KDD '05: Proceeding of the eleventh ACM SIGKDD international * conference on Knowledge discovery in data mining \eme, 177--187, 2005. * * Note however, that the version of the model in the published paper is incorrect * in the sense that it cannot generate the kind of graphs the authors * claim. A corrected version is available from * http://cs.stanford.edu/people/jure/pubs/powergrowth-tkdd.pdf , our * implementation is based on this. * * \param graph Pointer to an uninitialized graph object. * \param nodes The number of vertices in the graph. * \param fw_prob The forward burning probability. * \param bw_factor The backward burning ratio. The backward burning probability is calculated as bw.factor*fw.prob. * \param pambs The number of ambassador vertices. * \param directed Whether to create a directed graph. * \return Error code. * * Time complexity: TODO. */ int igraph_forest_fire_game(igraph_t *graph, igraph_integer_t nodes, igraph_real_t fw_prob, igraph_real_t bw_factor, igraph_integer_t pambs, igraph_bool_t directed) { igraph_vector_long_t visited; long int no_of_nodes = nodes, actnode, i; igraph_vector_t edges; igraph_vector_t *inneis, *outneis; igraph_i_forest_fire_data_t data; igraph_dqueue_t neiq; long int ambs = pambs; igraph_real_t param_geom_out = 1 - fw_prob; igraph_real_t param_geom_in = 1 - fw_prob * bw_factor; if (fw_prob < 0) { IGRAPH_ERROR("Forest fire model: 'fw_prob' should be between non-negative", IGRAPH_EINVAL); } if (bw_factor < 0) { IGRAPH_ERROR("Forest fire model: 'bw_factor' should be non-negative", IGRAPH_EINVAL); } if (ambs < 0) { IGRAPH_ERROR("Number of ambassadors ('ambs') should be non-negative", IGRAPH_EINVAL); } if (fw_prob == 0 || ambs == 0) { IGRAPH_WARNING("'fw_prob or ambs is zero, creating empty graph"); IGRAPH_CHECK(igraph_empty(graph, nodes, directed)); return 0; } IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); inneis = igraph_Calloc(no_of_nodes, igraph_vector_t); if (!inneis) { IGRAPH_ERROR("Cannot run forest fire model", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, inneis); outneis = igraph_Calloc(no_of_nodes, igraph_vector_t); if (!outneis) { IGRAPH_ERROR("Cannot run forest fire model", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, outneis); data.inneis = inneis; data.outneis = outneis; data.no_of_nodes = no_of_nodes; IGRAPH_FINALLY(igraph_i_forest_fire_free, &data); for (i = 0; i < no_of_nodes; i++) { IGRAPH_CHECK(igraph_vector_init(inneis + i, 0)); IGRAPH_CHECK(igraph_vector_init(outneis + i, 0)); } IGRAPH_CHECK(igraph_vector_long_init(&visited, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_long_destroy, &visited); IGRAPH_DQUEUE_INIT_FINALLY(&neiq, 10); RNG_BEGIN(); #define ADD_EDGE_TO(nei) \ if (VECTOR(visited)[(nei)] != actnode+1) { \ VECTOR(visited)[(nei)] = actnode+1; \ IGRAPH_CHECK(igraph_dqueue_push(&neiq, nei)); \ IGRAPH_CHECK(igraph_vector_push_back(&edges, actnode)); \ IGRAPH_CHECK(igraph_vector_push_back(&edges, nei)); \ IGRAPH_CHECK(igraph_vector_push_back(outneis+actnode, nei)); \ IGRAPH_CHECK(igraph_vector_push_back(inneis+nei, actnode)); \ } IGRAPH_PROGRESS("Forest fire: ", 0.0, NULL); for (actnode = 1; actnode < no_of_nodes; actnode++) { IGRAPH_PROGRESS("Forest fire: ", 100.0 * actnode / no_of_nodes, NULL); IGRAPH_ALLOW_INTERRUPTION(); /* We don't want to visit the current vertex */ VECTOR(visited)[actnode] = actnode + 1; /* Choose ambassador(s) */ for (i = 0; i < ambs; i++) { long int a = RNG_INTEGER(0, actnode - 1); ADD_EDGE_TO(a); } while (!igraph_dqueue_empty(&neiq)) { long int actamb = (long int) igraph_dqueue_pop(&neiq); igraph_vector_t *outv = outneis + actamb; igraph_vector_t *inv = inneis + actamb; long int no_in = igraph_vector_size(inv); long int no_out = igraph_vector_size(outv); long int neis_out = (long int) RNG_GEOM(param_geom_out); long int neis_in = (long int) RNG_GEOM(param_geom_in); /* outgoing neighbors */ if (neis_out >= no_out) { for (i = 0; i < no_out; i++) { long int nei = (long int) VECTOR(*outv)[i]; ADD_EDGE_TO(nei); } } else { long int oleft = no_out; for (i = 0; i < neis_out && oleft > 0; ) { long int which = RNG_INTEGER(0, oleft - 1); long int nei = (long int) VECTOR(*outv)[which]; VECTOR(*outv)[which] = VECTOR(*outv)[oleft - 1]; VECTOR(*outv)[oleft - 1] = nei; if (VECTOR(visited)[nei] != actnode + 1) { ADD_EDGE_TO(nei); i++; } oleft--; } } /* incoming neighbors */ if (neis_in >= no_in) { for (i = 0; i < no_in; i++) { long int nei = (long int) VECTOR(*inv)[i]; ADD_EDGE_TO(nei); } } else { long int ileft = no_in; for (i = 0; i < neis_in && ileft > 0; ) { long int which = RNG_INTEGER(0, ileft - 1); long int nei = (long int) VECTOR(*inv)[which]; VECTOR(*inv)[which] = VECTOR(*inv)[ileft - 1]; VECTOR(*inv)[ileft - 1] = nei; if (VECTOR(visited)[nei] != actnode + 1) { ADD_EDGE_TO(nei); i++; } ileft--; } } } /* while neiq not empty */ } /* actnode < no_of_nodes */ #undef ADD_EDGE_TO RNG_END(); IGRAPH_PROGRESS("Forest fire: ", 100.0, NULL); igraph_dqueue_destroy(&neiq); igraph_vector_long_destroy(&visited); igraph_i_forest_fire_free(&data); igraph_free(outneis); igraph_free(inneis); IGRAPH_FINALLY_CLEAN(5); IGRAPH_CHECK(igraph_create(graph, &edges, nodes, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/structural_properties_internal.h0000644000076500000240000000316713614300625030136 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-2016 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef STRUCTURAL_PROPERTIES_INTERNAL_H #define STRUCTURAL_PROPERTIES_INTERNAL_H #include "igraph_constants.h" #include "igraph_types.h" #include "igraph_iterators.h" int igraph_i_induced_subgraph_suggest_implementation( const igraph_t *graph, const igraph_vs_t vids, igraph_subgraph_implementation_t* result ); int igraph_i_subgraph_copy_and_delete(const igraph_t *graph, igraph_t *res, const igraph_vs_t vids, igraph_vector_t *map, igraph_vector_t *invmap); int igraph_i_subgraph_create_from_scratch(const igraph_t *graph, igraph_t *res, const igraph_vs_t vids, igraph_vector_t *map, igraph_vector_t *invmap); #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c.h0000644000076500000240000001222613614300625022224 0ustar tamasstaff00000000000000/* f2c.h -- Standard Fortran to C header file */ /** barf [ba:rf] 2. "He suggested using FORTRAN, and everybody barfed." - From The Shogakukan DICTIONARY OF NEW ENGLISH (Second edition) */ #ifndef F2C_INCLUDE #define F2C_INCLUDE #include "igraph_blas_internal.h" #include "igraph_lapack_internal.h" #include "igraph_arpack_internal.h" typedef int integer; typedef unsigned int uinteger; typedef char *address; typedef short int shortint; typedef float real; typedef double doublereal; typedef struct { real r, i; } f2c_complex; typedef struct { doublereal r, i; } doublecomplex; typedef int logical; typedef short int shortlogical; typedef char logical1; typedef char integer1; #ifdef INTEGER_STAR_8 /* Adjust for integer*8. */ typedef long longint; /* system-dependent */ typedef unsigned long ulongint; /* system-dependent */ #define qbit_clear(a,b) ((a) & ~((ulongint)1 << (b))) #define qbit_set(a,b) ((a) | ((ulongint)1 << (b))) #endif #define TRUE_ (1) #define FALSE_ (0) /* Extern is for use with -E */ #ifndef Extern #define Extern extern #endif /* I/O stuff */ #ifdef f2c_i2 /* for -i2 */ typedef short flag; typedef short ftnlen; typedef short ftnint; #else typedef int flag; typedef int ftnlen; typedef int ftnint; #endif /*external read, write*/ typedef struct { flag cierr; ftnint ciunit; flag ciend; char *cifmt; ftnint cirec; } cilist; /*internal read, write*/ typedef struct { flag icierr; char *iciunit; flag iciend; char *icifmt; ftnint icirlen; ftnint icirnum; } icilist; /*open*/ typedef struct { flag oerr; ftnint ounit; char *ofnm; ftnlen ofnmlen; char *osta; char *oacc; char *ofm; ftnint orl; char *oblnk; } olist; /*close*/ typedef struct { flag cerr; ftnint cunit; char *csta; } cllist; /*rewind, backspace, endfile*/ typedef struct { flag aerr; ftnint aunit; } alist; /* inquire */ typedef struct { flag inerr; ftnint inunit; char *infile; ftnlen infilen; ftnint *inex; /*parameters in standard's order*/ ftnint *inopen; ftnint *innum; ftnint *innamed; char *inname; ftnlen innamlen; char *inacc; ftnlen inacclen; char *inseq; ftnlen inseqlen; char *indir; ftnlen indirlen; char *infmt; ftnlen infmtlen; char *inform; ftnint informlen; char *inunf; ftnlen inunflen; ftnint *inrecl; ftnint *innrec; char *inblank; ftnlen inblanklen; } inlist; #define VOID void union Multitype { /* for multiple entry points */ integer1 g; shortint h; integer i; /* longint j; */ real r; doublereal d; f2c_complex c; doublecomplex z; }; typedef union Multitype Multitype; /*typedef long int Long;*/ /* No longer used; formerly in Namelist */ struct Vardesc { /* for Namelist */ char *name; char *addr; ftnlen *dims; int type; }; typedef struct Vardesc Vardesc; struct Namelist { char *name; Vardesc **vars; int nvars; }; typedef struct Namelist Namelist; #define abs(x) ((x) >= 0 ? (x) : -(x)) #define dabs(x) (doublereal)abs(x) #define min(a,b) ((a) <= (b) ? (a) : (b)) #define max(a,b) ((a) >= (b) ? (a) : (b)) #define dmin(a,b) (doublereal)min(a,b) #define dmax(a,b) (doublereal)max(a,b) #define bit_test(a,b) ((a) >> (b) & 1) #define bit_clear(a,b) ((a) & ~((uinteger)1 << (b))) #define bit_set(a,b) ((a) | ((uinteger)1 << (b))) /* procedure parameter types for -A and -C++ */ #define F2C_proc_par_types 1 #ifdef __cplusplus typedef int /* Unknown procedure type */ (*U_fp)(...); typedef shortint (*J_fp)(...); typedef integer (*I_fp)(...); typedef real (*R_fp)(...); typedef doublereal (*D_fp)(...), (*E_fp)(...); typedef /* Complex */ VOID (*C_fp)(...); typedef /* Double Complex */ VOID (*Z_fp)(...); typedef logical (*L_fp)(...); typedef shortlogical (*K_fp)(...); typedef /* Character */ VOID (*H_fp)(...); typedef /* Subroutine */ int (*S_fp)(...); #else typedef int /* Unknown procedure type */ (*U_fp)(); typedef shortint (*J_fp)(); typedef integer (*I_fp)(); typedef real (*R_fp)(); typedef doublereal (*D_fp)(), (*E_fp)(); typedef /* Complex */ VOID (*C_fp)(); typedef /* Double Complex */ VOID (*Z_fp)(); typedef logical (*L_fp)(); typedef shortlogical (*K_fp)(); typedef /* Character */ VOID (*H_fp)(); typedef /* Subroutine */ int (*S_fp)(); #endif /* E_fp is for real functions when -R is not specified */ typedef VOID C_f; /* complex function */ typedef VOID H_f; /* character function */ typedef VOID Z_f; /* double complex function */ typedef doublereal E_f; /* real function with -R not specified */ /* undef any lower-case symbols that your C compiler predefines, e.g.: */ #ifndef Skip_f2c_Undefs #undef cray #undef gcos #undef mc68010 #undef mc68020 #undef mips #undef pdp11 #undef sgi #undef sparc #undef sun #undef sun2 #undef sun3 #undef sun4 #undef u370 #undef u3b #undef u3b2 #undef u3b5 #undef unix #undef vax #endif #include "config.h" #endif python-igraph-0.8.0/vendor/source/igraph/src/gengraph_box_list.h0000644000076500000240000000526413614300625025254 0ustar tamasstaff00000000000000/* * * gengraph - generation of random simple connected graphs with prescribed * degree sequence * * Copyright (C) 2006 Fabien Viger * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ // This class allows to maintain a list of vertices, // sorted by degree (largest degrees first) // Operations allowed : // - get the vertex having max degree -> Cost = O(1) // - remove any vertex from the graph -> Cost = Sum(degrees of neighbours) // [ could be O(degree) if optimized ] #ifndef _BOX_LIST_H #define _BOX_LIST_H #ifndef _MSC_VER #ifndef register #define register #endif #endif namespace gengraph { class box_list { private: int n; // INITIAL number of vertices int dmax; // CURRENT Maximum degree int *deg; // CURRENT Degrees (points directly to the deg[] of the graph // Vertices are grouped by degree: one double-chained lists for each degree int *list; // list[d-1] is the head of list of vertices of degree d int *next; // next[v]/prev[v] are the vertices next/previous to v int *prev; // in the list where v belongs void pop(int); // pop(v) just removes v from its list void insert(int); // insert(v) insert v at the head of its list public: // Ctor. Takes O(n) time. box_list(int n0, int *deg0); // Dtor ~box_list(); // Self-explaining inline routines inline bool is_empty() { return dmax < 1; }; inline int get_max() { return list[dmax - 1]; }; inline int get_one() { return list[0]; }; inline int get_min() { int i = 0; while (list[i] < 0) { i++; } return list[i]; }; // Remove v from box_list // Also, semi-remove vertex v from graph: all neighbours of v will swap // their last neighbour wit hv, and then decrease their degree, so // that any arc w->v virtually disappear // Actually, adjacency lists are just permuted, and deg[] is changed void pop_vertex(int v, int **neigh); }; } // namespace gengraph #endif //_BOX_LIST_H python-igraph-0.8.0/vendor/source/igraph/src/drl_layout_3d.cpp0000644000076500000240000001103713614300625024650 0ustar tamasstaff00000000000000/* * Copyright 2007 Sandia Corporation. Under the terms of Contract * DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains * certain rights in this software. * * All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are * met: * * * Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * Neither the name of Sandia National Laboratories nor the names of * its contributors may be used to endorse or promote products derived from * this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT * OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED * TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF * LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING * NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. */ // Layout // // This program implements a parallel force directed graph drawing // algorithm. The algorithm used is based upon a random decomposition // of the graph and simulated shared memory of node position and density. // In this version, the simulated shared memory is spread among all processors // // The structure of the inputs and outputs of this code will be displayed // if the program is called without parameters, or if an erroneous // parameter is passed to the program. // // S. Martin // 5/6/2005 // C++ library routines #include #include #include #include #include #include #include using namespace std; // layout routines and constants #include "drl_layout_3d.h" #include "drl_parse.h" #include "drl_graph_3d.h" // MPI #ifdef MUSE_MPI #include #endif using namespace drl3d; #include "igraph_layout.h" #include "igraph_random.h" #include "igraph_interface.h" /** * \function igraph_layout_drl_3d * The DrL layout generator, 3d version. * * This function implements the force-directed DrL layout generator. * Please see more in the technical report: Martin, S., Brown, W.M., * Klavans, R., Boyack, K.W., DrL: Distributed Recursive (Graph) * Layout. SAND Reports, 2008. 2936: p. 1-10. * * This function uses a modified DrL generator that does * the layout in three dimensions. * \param graph The input graph. * \param use_seed Logical scalar, if true, then the coordinates * supplied in the \p res argument are used as starting points. * \param res Pointer to a matrix, the result layout is stored * here. It will be resized as needed. * \param options The parameters to pass to the layout generator. * \param weights Edge weights, pointer to a vector. If this is a null * pointer then every edge will have the same weight. * \param fixed Pointer to a logical vector, or a null pointer. This * can be used to fix the position of some vertices. Vertices for * which it is true will not be moved, but stay at the coordinates * given in the \p res matrix. This argument is ignored if it is a * null pointer or if use_seed is false. * \return Error code. * * Time complexity: ???. * * \sa \ref igraph_layout_drl() for the standard 2d version. */ int igraph_layout_drl_3d(const igraph_t *graph, igraph_matrix_t *res, igraph_bool_t use_seed, igraph_layout_drl_options_t *options, const igraph_vector_t *weights, const igraph_vector_bool_t *fixed) { RNG_BEGIN(); drl3d::graph neighbors(graph, options, weights); neighbors.init_parms(options); if (use_seed) { IGRAPH_CHECK(igraph_matrix_resize(res, igraph_vcount(graph), 3)); neighbors.read_real(res, fixed); } neighbors.draw_graph(res); RNG_END(); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/interrupt.c0000644000076500000240000000277013614300625023604 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2005-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_interrupt.h" #include "config.h" #include #include #include IGRAPH_THREAD_LOCAL igraph_interruption_handler_t *igraph_i_interruption_handler = 0; int igraph_allow_interruption(void* data) { if (igraph_i_interruption_handler) { return igraph_i_interruption_handler(data); } return IGRAPH_SUCCESS; } igraph_interruption_handler_t * igraph_set_interruption_handler (igraph_interruption_handler_t * new_handler) { igraph_interruption_handler_t * previous_handler = igraph_i_interruption_handler; igraph_i_interruption_handler = new_handler; return previous_handler; } python-igraph-0.8.0/vendor/source/igraph/src/foreign-lgl-parser.y0000644000076500000240000001027713524616145025305 0ustar tamasstaff00000000000000/* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ %{ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include "igraph_hacks_internal.h" #include "igraph_types.h" #include "igraph_types_internal.h" #include "igraph_math.h" #include "igraph_memory.h" #include "igraph_error.h" #include "config.h" #include "foreign-lgl-header.h" #include "foreign-lgl-parser.h" #define yyscan_t void* int igraph_lgl_yylex(YYSTYPE* lvalp, YYLTYPE* llocp, void* scanner); int igraph_lgl_yyerror(YYLTYPE* locp, igraph_i_lgl_parsedata_t *context, const char *s); char *igraph_lgl_yyget_text (yyscan_t yyscanner ); int igraph_lgl_yyget_leng (yyscan_t yyscanner ); igraph_real_t igraph_lgl_get_number(const char *str, long int len); #define scanner context->scanner %} %pure-parser %output="y.tab.c" %name-prefix="igraph_lgl_yy" %defines %locations %error-verbose %parse-param { igraph_i_lgl_parsedata_t* context } %lex-param { void *scanner } %union { long int edgenum; double weightnum; } %type edgeid %type weight %token ALNUM %token NEWLINE %token HASH %token ERROR %% input : /* empty */ | input NEWLINE | input vertex ; vertex : vertexdef edges ; vertexdef : HASH edgeid NEWLINE { context->actvertex=$2; } ; edges : /* empty */ | edges edge ; edge : edgeid NEWLINE { igraph_vector_push_back(context->vector, context->actvertex); igraph_vector_push_back(context->vector, $1); igraph_vector_push_back(context->weights, 0); } | edgeid weight NEWLINE { igraph_vector_push_back(context->vector, context->actvertex); igraph_vector_push_back(context->vector, $1); igraph_vector_push_back(context->weights, $2); context->has_weights = 1; } ; edgeid : ALNUM { igraph_trie_get2(context->trie, igraph_lgl_yyget_text(scanner), igraph_lgl_yyget_leng(scanner), &$$); }; weight : ALNUM { $$=igraph_lgl_get_number(igraph_lgl_yyget_text(scanner), igraph_lgl_yyget_leng(scanner)); } ; %% int igraph_lgl_yyerror(YYLTYPE* locp, igraph_i_lgl_parsedata_t *context, const char *s) { snprintf(context->errmsg, sizeof(context->errmsg)/sizeof(char), "Parse error in LGL file, line %i (%s)", locp->first_line, s); return 0; } igraph_real_t igraph_lgl_get_number(const char *str, long int length) { igraph_real_t num; char *tmp=igraph_Calloc(length+1, char); strncpy(tmp, str, length); tmp[length]='\0'; sscanf(tmp, "%lf", &num); igraph_Free(tmp); return num; } python-igraph-0.8.0/vendor/source/igraph/src/bipartite.c0000644000076500000240000012055113614300625023531 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2008-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_bipartite.h" #include "igraph_attributes.h" #include "igraph_adjlist.h" #include "igraph_interface.h" #include "igraph_constructors.h" #include "igraph_dqueue.h" #include "igraph_random.h" #include "igraph_nongraph.h" /** * \section about_bipartite Bipartite networks in igraph * * * A bipartite network contains two kinds of vertices and connections * are only possible between two vertices of different kind. There are * many natural examples, e.g. movies and actors as vertices and a * movie is connected to all participating actors, etc. * * * igraph does not have direct support for bipartite networks, at * least not at the C language level. In other words the igraph_t * structure does not contain information about the vertex types. * The C functions for bipartite networks usually have an additional * input argument to graph, called \c types, a boolean vector giving * the vertex types. * * * Most functions creating bipartite networks are able to create this * extra vector, you just need to supply an initialized boolean vector * to them. */ /** * \function igraph_bipartite_projection_size * Calculate the number of vertices and edges in the bipartite projections * * This function calculates the number of vertices and edges in the * two projections of a bipartite network. This is useful if you have * a big bipartite network and you want to estimate the amount of * memory you would need to calculate the projections themselves. * * \param graph The input graph. * \param types Boolean vector giving the vertex types of the graph. * \param vcount1 Pointer to an \c igraph_integer_t, the number of * vertices in the first projection is stored here. * \param ecount1 Pointer to an \c igraph_integer_t, the number of * edges in the first projection is stored here. * \param vcount2 Pointer to an \c igraph_integer_t, the number of * vertices in the second projection is stored here. * \param ecount2 Pointer to an \c igraph_integer_t, the number of * edges in the second projection is stored here. * \return Error code. * * \sa \ref igraph_bipartite_projection() to calculate the actual * projection. * * Time complexity: O(|V|*d^2+|E|), |V| is the number of vertices, |E| * is the number of edges, d is the average (total) degree of the * graphs. * * \example examples/simple/igraph_bipartite_projection.c */ int igraph_bipartite_projection_size(const igraph_t *graph, const igraph_vector_bool_t *types, igraph_integer_t *vcount1, igraph_integer_t *ecount1, igraph_integer_t *vcount2, igraph_integer_t *ecount2) { long int no_of_nodes = igraph_vcount(graph); long int vc1 = 0, ec1 = 0, vc2 = 0, ec2 = 0; igraph_adjlist_t adjlist; igraph_vector_long_t added; long int i; IGRAPH_CHECK(igraph_vector_long_init(&added, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_long_destroy, &added); IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist); for (i = 0; i < no_of_nodes; i++) { igraph_vector_int_t *neis1; long int neilen1, j; long int *ecptr; if (VECTOR(*types)[i]) { vc2++; ecptr = &ec2; } else { vc1++; ecptr = &ec1; } neis1 = igraph_adjlist_get(&adjlist, i); neilen1 = igraph_vector_int_size(neis1); for (j = 0; j < neilen1; j++) { long int k, neilen2, nei = (long int) VECTOR(*neis1)[j]; igraph_vector_int_t *neis2 = igraph_adjlist_get(&adjlist, nei); if (IGRAPH_UNLIKELY(VECTOR(*types)[i] == VECTOR(*types)[nei])) { IGRAPH_ERROR("Non-bipartite edge found in bipartite projection", IGRAPH_EINVAL); } neilen2 = igraph_vector_int_size(neis2); for (k = 0; k < neilen2; k++) { long int nei2 = (long int) VECTOR(*neis2)[k]; if (nei2 <= i) { continue; } if (VECTOR(added)[nei2] == i + 1) { continue; } VECTOR(added)[nei2] = i + 1; (*ecptr)++; } } } *vcount1 = (igraph_integer_t) vc1; *ecount1 = (igraph_integer_t) ec1; *vcount2 = (igraph_integer_t) vc2; *ecount2 = (igraph_integer_t) ec2; igraph_adjlist_destroy(&adjlist); igraph_vector_long_destroy(&added); IGRAPH_FINALLY_CLEAN(2); return 0; } int igraph_i_bipartite_projection(const igraph_t *graph, const igraph_vector_bool_t *types, igraph_t *proj, int which, igraph_vector_t *multiplicity) { long int no_of_nodes = igraph_vcount(graph); long int i, j, k; igraph_integer_t remaining_nodes = 0; igraph_vector_t vertex_perm, vertex_index; igraph_vector_t edges; igraph_adjlist_t adjlist; igraph_vector_int_t *neis1, *neis2; long int neilen1, neilen2; igraph_vector_long_t added; igraph_vector_t mult; if (which < 0) { return 0; } IGRAPH_VECTOR_INIT_FINALLY(&vertex_perm, 0); IGRAPH_CHECK(igraph_vector_reserve(&vertex_perm, no_of_nodes)); IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_VECTOR_INIT_FINALLY(&vertex_index, no_of_nodes); IGRAPH_CHECK(igraph_vector_long_init(&added, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_long_destroy, &added); IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist); if (multiplicity) { IGRAPH_VECTOR_INIT_FINALLY(&mult, no_of_nodes); igraph_vector_clear(multiplicity); } for (i = 0; i < no_of_nodes; i++) { if (VECTOR(*types)[i] == which) { VECTOR(vertex_index)[i] = ++remaining_nodes; igraph_vector_push_back(&vertex_perm, i); } } for (i = 0; i < no_of_nodes; i++) { if (VECTOR(*types)[i] == which) { long int new_i = (long int) VECTOR(vertex_index)[i] - 1; long int iedges = 0; neis1 = igraph_adjlist_get(&adjlist, i); neilen1 = igraph_vector_int_size(neis1); for (j = 0; j < neilen1; j++) { long int nei = (long int) VECTOR(*neis1)[j]; if (IGRAPH_UNLIKELY(VECTOR(*types)[i] == VECTOR(*types)[nei])) { IGRAPH_ERROR("Non-bipartite edge found in bipartite projection", IGRAPH_EINVAL); } neis2 = igraph_adjlist_get(&adjlist, nei); neilen2 = igraph_vector_int_size(neis2); for (k = 0; k < neilen2; k++) { long int nei2 = (long int) VECTOR(*neis2)[k], new_nei2; if (nei2 <= i) { continue; } if (VECTOR(added)[nei2] == i + 1) { if (multiplicity) { VECTOR(mult)[nei2] += 1; } continue; } VECTOR(added)[nei2] = i + 1; if (multiplicity) { VECTOR(mult)[nei2] = 1; } iedges++; IGRAPH_CHECK(igraph_vector_push_back(&edges, new_i)); if (multiplicity) { /* If we need the multiplicity as well, then we put in the old vertex ids here and rewrite it later */ IGRAPH_CHECK(igraph_vector_push_back(&edges, nei2)); } else { new_nei2 = (long int) VECTOR(vertex_index)[nei2] - 1; IGRAPH_CHECK(igraph_vector_push_back(&edges, new_nei2)); } } } if (multiplicity) { /* OK, we need to go through all the edges added for vertex new_i and check their multiplicity */ long int now = igraph_vector_size(&edges); long int from = now - iedges * 2; for (j = from; j < now; j += 2) { long int nei2 = (long int) VECTOR(edges)[j + 1]; long int new_nei2 = (long int) VECTOR(vertex_index)[nei2] - 1; long int m = (long int) VECTOR(mult)[nei2]; VECTOR(edges)[j + 1] = new_nei2; IGRAPH_CHECK(igraph_vector_push_back(multiplicity, m)); } } } /* if VECTOR(*type)[i] == which */ } if (multiplicity) { igraph_vector_destroy(&mult); IGRAPH_FINALLY_CLEAN(1); } igraph_adjlist_destroy(&adjlist); igraph_vector_long_destroy(&added); igraph_vector_destroy(&vertex_index); IGRAPH_FINALLY_CLEAN(3); IGRAPH_CHECK(igraph_create(proj, &edges, remaining_nodes, /*directed=*/ 0)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); IGRAPH_FINALLY(igraph_destroy, proj); IGRAPH_I_ATTRIBUTE_DESTROY(proj); IGRAPH_I_ATTRIBUTE_COPY(proj, graph, 1, 0, 0); IGRAPH_CHECK(igraph_i_attribute_permute_vertices(graph, proj, &vertex_perm)); igraph_vector_destroy(&vertex_perm); IGRAPH_FINALLY_CLEAN(2); return 0; } /** * \function igraph_bipartite_projection * Create one or both projections of a bipartite (two-mode) network * * Creates one or both projections of a bipartite graph. * \param graph The bipartite input graph. Directedness of the edges * is ignored. * \param types Boolean vector giving the vertex types of the graph. * \param proj1 Pointer to an uninitialized graph object, the first * projection will be created here. It a null pointer, then it is * ignored, see also the \p probe1 argument. * \param proj2 Pointer to an uninitialized graph object, the second * projection is created here, if it is not a null pointer. See also * the \p probe1 argument. * \param multiplicity1 Pointer to a vector, or a null pointer. If not * the latter, then the multiplicity of the edges is stored * here. E.g. if there is an A-C-B and also an A-D-B triple in the * bipartite graph (but no more X, such that A-X-B is also in the * graph), then the multiplicity of the A-B edge in the projection * will be 2. * \param multiplicity2 The same as \c multiplicity1, but for the * other projection. * \param probe1 This argument can be used to specify the order of the * projections in the resulting list. When it is non-negative, then * it is considered as a vertex ID and the projection containing * this vertex will be the first one in the result. Setting this * argument to a non-negative value implies that \c proj1 must be * a non-null pointer. If you don't care about the ordering of the * projections, pass -1 here. * \return Error code. * * \sa \ref igraph_bipartite_projection_size() to calculate the number * of vertices and edges in the projections, without creating the * projection graphs themselves. * * Time complexity: O(|V|*d^2+|E|), |V| is the number of vertices, |E| * is the number of edges, d is the average (total) degree of the * graphs. * * \example examples/simple/igraph_bipartite_projection.c */ int igraph_bipartite_projection(const igraph_t *graph, const igraph_vector_bool_t *types, igraph_t *proj1, igraph_t *proj2, igraph_vector_t *multiplicity1, igraph_vector_t *multiplicity2, igraph_integer_t probe1) { long int no_of_nodes = igraph_vcount(graph); /* t1 is -1 if proj1 is omitted, it is 0 if it belongs to type zero, it is 1 if it belongs to type one. The same for t2 */ int t1, t2; if (igraph_vector_bool_size(types) != no_of_nodes) { IGRAPH_ERROR("Invalid bipartite type vector size", IGRAPH_EINVAL); } if (probe1 >= no_of_nodes) { IGRAPH_ERROR("No such vertex to probe", IGRAPH_EINVAL); } if (probe1 >= 0 && !proj1) { IGRAPH_ERROR("`probe1' given, but `proj1' is a null pointer", IGRAPH_EINVAL); } if (probe1 >= 0) { t1 = VECTOR(*types)[(long int)probe1]; if (proj2) { t2 = 1 - t1; } else { t2 = -1; } } else { t1 = proj1 ? 0 : -1; t2 = proj2 ? 1 : -1; } IGRAPH_CHECK(igraph_i_bipartite_projection(graph, types, proj1, t1, multiplicity1)); IGRAPH_FINALLY(igraph_destroy, proj1); IGRAPH_CHECK(igraph_i_bipartite_projection(graph, types, proj2, t2, multiplicity2)); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_full_bipartite * Create a full bipartite network * * A bipartite network contains two kinds of vertices and connections * are only possible between two vertices of different kind. There are * many natural examples, e.g. movies and actors as vertices and a * movie is connected to all participating actors, etc. * * * igraph does not have direct support for bipartite networks, at * least not at the C language level. In other words the igraph_t * structure does not contain information about the vertex types. * The C functions for bipartite networks usually have an additional * input argument to graph, called \c types, a boolean vector giving * the vertex types. * * * Most functions creating bipartite networks are able to create this * extra vector, you just need to supply an initialized boolean vector * to them. * * \param graph Pointer to an igraph_t object, the graph will be * created here. * \param types Pointer to a boolean vector. If not a null pointer, * then the vertex types will be stored here. * \param n1 Integer, the number of vertices of the first kind. * \param n2 Integer, the number of vertices of the second kind. * \param directed Boolean, whether to create a directed graph. * \param mode A constant that gives the type of connections for * directed graphs. If \c IGRAPH_OUT, then edges point from vertices * of the first kind to vertices of the second kind; if \c * IGRAPH_IN, then the opposite direction is realized; if \c * IGRAPH_ALL, then mutual edges will be created. * \return Error code. * * Time complexity: O(|V|+|E|), linear in the number of vertices and * edges. * * \sa \ref igraph_full() for non-bipartite full graphs. */ int igraph_full_bipartite(igraph_t *graph, igraph_vector_bool_t *types, igraph_integer_t n1, igraph_integer_t n2, igraph_bool_t directed, igraph_neimode_t mode) { igraph_integer_t nn1 = n1, nn2 = n2; igraph_integer_t no_of_nodes = nn1 + nn2; igraph_vector_t edges; long int no_of_edges; long int ptr = 0; long int i, j; if (!directed) { no_of_edges = nn1 * nn2; } else if (mode == IGRAPH_OUT || mode == IGRAPH_IN) { no_of_edges = nn1 * nn2; } else { /* mode==IGRAPH_ALL */ no_of_edges = nn1 * nn2 * 2; } IGRAPH_VECTOR_INIT_FINALLY(&edges, no_of_edges * 2); if (!directed || mode == IGRAPH_OUT) { for (i = 0; i < nn1; i++) { for (j = 0; j < nn2; j++) { VECTOR(edges)[ptr++] = i; VECTOR(edges)[ptr++] = nn1 + j; } } } else if (mode == IGRAPH_IN) { for (i = 0; i < nn1; i++) { for (j = 0; j < nn2; j++) { VECTOR(edges)[ptr++] = nn1 + j; VECTOR(edges)[ptr++] = i; } } } else { for (i = 0; i < nn1; i++) { for (j = 0; j < nn2; j++) { VECTOR(edges)[ptr++] = i; VECTOR(edges)[ptr++] = nn1 + j; VECTOR(edges)[ptr++] = nn1 + j; VECTOR(edges)[ptr++] = i; } } } IGRAPH_CHECK(igraph_create(graph, &edges, no_of_nodes, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); IGRAPH_FINALLY(igraph_destroy, graph); if (types) { IGRAPH_CHECK(igraph_vector_bool_resize(types, no_of_nodes)); igraph_vector_bool_null(types); for (i = nn1; i < no_of_nodes; i++) { VECTOR(*types)[i] = 1; } } IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_create_bipartite * Create a bipartite graph * * This is a simple wrapper function to create a bipartite graph. It * does a little more than \ref igraph_create(), e.g. it checks that * the graph is indeed bipartite with respect to the given \p types * vector. If there is an edge connecting two vertices of the same * kind, then an error is reported. * \param graph Pointer to an uninitialized graph object, the result is * created here. * \param types Boolean vector giving the vertex types. The length of * the vector defines the number of vertices in the graph. * \param edges Vector giving the edges of the graph. The highest * vertex id in this vector must be smaller than the length of the * \p types vector. * \param directed Boolean scalar, whether to create a directed * graph. * \return Error code. * * Time complexity: O(|V|+|E|), linear in the number of vertices and * edges. * * \example examples/simple/igraph_bipartite_create.c */ int igraph_create_bipartite(igraph_t *graph, const igraph_vector_bool_t *types, const igraph_vector_t *edges, igraph_bool_t directed) { igraph_integer_t no_of_nodes = (igraph_integer_t) igraph_vector_bool_size(types); long int no_of_edges = igraph_vector_size(edges); igraph_real_t min_edge = 0, max_edge = 0; igraph_bool_t min_type = 0, max_type = 0; long int i; if (no_of_edges % 2 != 0) { IGRAPH_ERROR("Invalid (odd) edges vector", IGRAPH_EINVEVECTOR); } no_of_edges /= 2; if (no_of_edges != 0) { igraph_vector_minmax(edges, &min_edge, &max_edge); } if (min_edge < 0 || max_edge >= no_of_nodes) { IGRAPH_ERROR("Invalid (negative) vertex id", IGRAPH_EINVVID); } /* Check types vector */ if (no_of_nodes != 0) { igraph_vector_bool_minmax(types, &min_type, &max_type); if (min_type < 0 || max_type > 1) { IGRAPH_WARNING("Non-binary type vector when creating a bipartite graph"); } } /* Check bipartiteness */ for (i = 0; i < no_of_edges * 2; i += 2) { long int from = (long int) VECTOR(*edges)[i]; long int to = (long int) VECTOR(*edges)[i + 1]; long int t1 = VECTOR(*types)[from]; long int t2 = VECTOR(*types)[to]; if ( (t1 && t2) || (!t1 && !t2) ) { IGRAPH_ERROR("Invalid edges, not a bipartite graph", IGRAPH_EINVAL); } } IGRAPH_CHECK(igraph_empty(graph, no_of_nodes, directed)); IGRAPH_FINALLY(igraph_destroy, graph); IGRAPH_CHECK(igraph_add_edges(graph, edges, 0)); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_incidence * Create a bipartite graph from an incidence matrix * * A bipartite (or two-mode) graph contains two types of vertices and * edges always connect vertices of different types. An incidence * matrix is an nxm matrix, n and m are the number of vertices of the * two types, respectively. Nonzero elements in the matrix denote * edges between the two corresponding vertices. * * * Note that this function can operate in two modes, depending on the * \p multiple argument. If it is FALSE (i.e. 0), then a single edge is * created for every non-zero element in the incidence matrix. If \p * multiple is TRUE (i.e. 1), then the matrix elements are rounded up * to the closest non-negative integer to get the number of edges to * create between a pair of vertices. * * * This function does not create multiple edges if \p multiple is * FALSE, but might create some if it is TRUE. * * \param graph Pointer to an uninitialized graph object. * \param types Pointer to an initialized boolean vector, or a null * pointer. If not a null pointer, then the vertex types are stored * here. It is resized as needed. * \param incidence The incidence matrix. * \param directed Gives whether to create an undirected or a directed * graph. * \param mode Specifies the direction of the edges in a directed * graph. If \c IGRAPH_OUT, then edges point from vertices * of the first kind (corresponding to rows) to vertices of the * second kind (corresponding to columns); if \c * IGRAPH_IN, then the opposite direction is realized; if \c * IGRAPH_ALL, then mutual edges will be created. * \param multiple How to interpret the incidence matrix elements. See * details below. * \return Error code. * * Time complexity: O(n*m), the size of the incidence matrix. */ int igraph_incidence(igraph_t *graph, igraph_vector_bool_t *types, const igraph_matrix_t *incidence, igraph_bool_t directed, igraph_neimode_t mode, igraph_bool_t multiple) { igraph_integer_t n1 = (igraph_integer_t) igraph_matrix_nrow(incidence); igraph_integer_t n2 = (igraph_integer_t) igraph_matrix_ncol(incidence); igraph_integer_t no_of_nodes = n1 + n2; igraph_vector_t edges; long int i, j, k; IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); if (multiple) { for (i = 0; i < n1; i++) { for (j = 0; j < n2; j++) { long int elem = (long int) MATRIX(*incidence, i, j); long int from, to; if (!elem) { continue; } if (mode == IGRAPH_IN) { from = n1 + j; to = i; } else { from = i; to = n1 + j; } if (mode != IGRAPH_ALL || !directed) { for (k = 0; k < elem; k++) { IGRAPH_CHECK(igraph_vector_push_back(&edges, from)); IGRAPH_CHECK(igraph_vector_push_back(&edges, to)); } } else { for (k = 0; k < elem; k++) { IGRAPH_CHECK(igraph_vector_push_back(&edges, from)); IGRAPH_CHECK(igraph_vector_push_back(&edges, to)); IGRAPH_CHECK(igraph_vector_push_back(&edges, to)); IGRAPH_CHECK(igraph_vector_push_back(&edges, from)); } } } } } else { for (i = 0; i < n1; i++) { for (j = 0; j < n2; j++) { long int from, to; if (MATRIX(*incidence, i, j) != 0) { if (mode == IGRAPH_IN) { from = n1 + j; to = i; } else { from = i; to = n1 + j; } if (mode != IGRAPH_ALL || !directed) { IGRAPH_CHECK(igraph_vector_push_back(&edges, from)); IGRAPH_CHECK(igraph_vector_push_back(&edges, to)); } else { IGRAPH_CHECK(igraph_vector_push_back(&edges, from)); IGRAPH_CHECK(igraph_vector_push_back(&edges, to)); IGRAPH_CHECK(igraph_vector_push_back(&edges, to)); IGRAPH_CHECK(igraph_vector_push_back(&edges, from)); } } } } } IGRAPH_CHECK(igraph_create(graph, &edges, no_of_nodes, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); IGRAPH_FINALLY(igraph_destroy, graph); if (types) { IGRAPH_CHECK(igraph_vector_bool_resize(types, no_of_nodes)); igraph_vector_bool_null(types); for (i = n1; i < no_of_nodes; i++) { VECTOR(*types)[i] = 1; } } IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_get_incidence * Convert a bipartite graph into an incidence matrix * * \param graph The input graph, edge directions are ignored. * \param types Boolean vector containing the vertex types. * \param res Pointer to an initialized matrix, the result is stored * here. An element of the matrix gives the number of edges * (irrespectively of their direction) between the two corresponding * vertices. * \param row_ids Pointer to an initialized vector or a null * pointer. If not a null pointer, then the vertex ids (in the * graph) corresponding to the rows of the result matrix are stored * here. * \param col_ids Pointer to an initialized vector or a null * pointer. If not a null pointer, then the vertex ids corresponding * to the columns of the result matrix are stored here. * \return Error code. * * Time complexity: O(n*m), n and m are number of vertices of the two * different kind. * * \sa \ref igraph_incidence() for the opposite operation. */ int igraph_get_incidence(const igraph_t *graph, const igraph_vector_bool_t *types, igraph_matrix_t *res, igraph_vector_t *row_ids, igraph_vector_t *col_ids) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); long int n1 = 0, n2 = 0, i; igraph_vector_t perm; long int p1, p2; if (igraph_vector_bool_size(types) != no_of_nodes) { IGRAPH_ERROR("Invalid vertex type vector for bipartite graph", IGRAPH_EINVAL); } for (i = 0; i < no_of_nodes; i++) { n1 += VECTOR(*types)[i] == 0 ? 1 : 0; } n2 = no_of_nodes - n1; IGRAPH_VECTOR_INIT_FINALLY(&perm, no_of_nodes); for (i = 0, p1 = 0, p2 = n1; i < no_of_nodes; i++) { VECTOR(perm)[i] = VECTOR(*types)[i] ? p2++ : p1++; } IGRAPH_CHECK(igraph_matrix_resize(res, n1, n2)); igraph_matrix_null(res); for (i = 0; i < no_of_edges; i++) { long int from = IGRAPH_FROM(graph, i); long int to = IGRAPH_TO(graph, i); long int from2 = (long int) VECTOR(perm)[from]; long int to2 = (long int) VECTOR(perm)[to]; if (! VECTOR(*types)[from]) { MATRIX(*res, from2, to2 - n1) += 1; } else { MATRIX(*res, to2, from2 - n1) += 1; } } if (row_ids) { IGRAPH_CHECK(igraph_vector_resize(row_ids, n1)); } if (col_ids) { IGRAPH_CHECK(igraph_vector_resize(col_ids, n2)); } if (row_ids || col_ids) { for (i = 0; i < no_of_nodes; i++) { if (! VECTOR(*types)[i]) { if (row_ids) { long int i2 = (long int) VECTOR(perm)[i]; VECTOR(*row_ids)[i2] = i; } } else { if (col_ids) { long int i2 = (long int) VECTOR(perm)[i]; VECTOR(*col_ids)[i2 - n1] = i; } } } } igraph_vector_destroy(&perm); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_is_bipartite * Check whether a graph is bipartite * * * This function simply checks whether a graph \emph{could} be * bipartite. It tries to find a mapping that gives a possible division * of the vertices into two classes, such that no two vertices of the * same class are connected by an edge. * * * The existence of such a mapping is equivalent of having no circuits of * odd length in the graph. A graph with loop edges cannot bipartite. * * * Note that the mapping is not necessarily unique, e.g. if the graph has * at least two components, then the vertices in the separate components * can be mapped independently. * * \param graph The input graph. * \param res Pointer to a boolean, the result is stored here. * \param type Pointer to an initialized boolean vector, or a null * pointer. If not a null pointer and a mapping was found, then it * is stored here. If not a null pointer, but no mapping was found, * the contents of this vector is invalid. * \return Error code. * * Time complexity: O(|V|+|E|), linear in the number of vertices and * edges. */ int igraph_is_bipartite(const igraph_t *graph, igraph_bool_t *res, igraph_vector_bool_t *type) { /* We basically do a breadth first search and label the vertices along the way. We stop as soon as we can find a contradiction. In the 'seen' vector 0 means 'not seen yet', 1 means type 1, 2 means type 2. */ long int no_of_nodes = igraph_vcount(graph); igraph_vector_char_t seen; igraph_dqueue_t Q; igraph_vector_t neis; igraph_bool_t bi = 1; long int i; IGRAPH_CHECK(igraph_vector_char_init(&seen, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_char_destroy, &seen); IGRAPH_DQUEUE_INIT_FINALLY(&Q, 100); IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); for (i = 0; bi && i < no_of_nodes; i++) { if (VECTOR(seen)[i]) { continue; } IGRAPH_CHECK(igraph_dqueue_push(&Q, i)); VECTOR(seen)[i] = 1; while (bi && !igraph_dqueue_empty(&Q)) { long int n, j; igraph_integer_t actnode = (igraph_integer_t) igraph_dqueue_pop(&Q); char acttype = VECTOR(seen)[actnode]; IGRAPH_CHECK(igraph_neighbors(graph, &neis, actnode, IGRAPH_ALL)); n = igraph_vector_size(&neis); for (j = 0; j < n; j++) { long int nei = (long int) VECTOR(neis)[j]; if (VECTOR(seen)[nei]) { long int neitype = VECTOR(seen)[nei]; if (neitype == acttype) { bi = 0; break; } } else { VECTOR(seen)[nei] = 3 - acttype; IGRAPH_CHECK(igraph_dqueue_push(&Q, nei)); } } } } igraph_vector_destroy(&neis); igraph_dqueue_destroy(&Q); IGRAPH_FINALLY_CLEAN(2); if (res) { *res = bi; } if (type && bi) { IGRAPH_CHECK(igraph_vector_bool_resize(type, no_of_nodes)); for (i = 0; i < no_of_nodes; i++) { VECTOR(*type)[i] = VECTOR(seen)[i] - 1; } } igraph_vector_char_destroy(&seen); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_bipartite_game_gnp(igraph_t *graph, igraph_vector_bool_t *types, igraph_integer_t n1, igraph_integer_t n2, igraph_real_t p, igraph_bool_t directed, igraph_neimode_t mode) { int retval = 0; igraph_vector_t edges, s; int i; if (p < 0.0 || p > 1.0) { IGRAPH_ERROR("Invalid connection probability", IGRAPH_EINVAL); } if (types) { IGRAPH_CHECK(igraph_vector_bool_resize(types, n1 + n2)); igraph_vector_bool_null(types); for (i = n1; i < n1 + n2; i++) { VECTOR(*types)[i] = 1; } } if (p == 0 || n1 * n2 < 1) { IGRAPH_CHECK(retval = igraph_empty(graph, n1 + n2, directed)); } else if (p == 1.0) { IGRAPH_CHECK(retval = igraph_full_bipartite(graph, types, n1, n2, directed, mode)); } else { long int to, from, slen; double maxedges, last; if (!directed || mode != IGRAPH_ALL) { maxedges = (double) n1 * (double) n2; } else { maxedges = 2.0 * (double) n1 * (double) n2; } IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_VECTOR_INIT_FINALLY(&s, 0); IGRAPH_CHECK(igraph_vector_reserve(&s, (long) (maxedges * p * 1.1))); RNG_BEGIN(); last = RNG_GEOM(p); while (last < maxedges) { IGRAPH_CHECK(igraph_vector_push_back(&s, last)); last += RNG_GEOM(p); last += 1; } RNG_END(); slen = igraph_vector_size(&s); IGRAPH_CHECK(igraph_vector_reserve(&edges, slen * 2)); for (i = 0; i < slen; i++) { if (!directed || mode != IGRAPH_ALL) { to = (long) floor(VECTOR(s)[i] / n1); from = (long) (VECTOR(s)[i] - ((igraph_real_t) to) * n1); to += n1; } else { long int n1n2 = n1 * n2; if (VECTOR(s)[i] < n1n2) { to = (long) floor(VECTOR(s)[i] / n1); from = (long) (VECTOR(s)[i] - ((igraph_real_t) to) * n1); to += n1; } else { to = (long) floor( (VECTOR(s)[i] - n1n2) / n2); from = (long) (VECTOR(s)[i] - n1n2 - ((igraph_real_t) to) * n2); from += n1; } } if (mode != IGRAPH_IN) { igraph_vector_push_back(&edges, from); igraph_vector_push_back(&edges, to); } else { igraph_vector_push_back(&edges, to); igraph_vector_push_back(&edges, from); } } igraph_vector_destroy(&s); IGRAPH_FINALLY_CLEAN(1); IGRAPH_CHECK(retval = igraph_create(graph, &edges, n1 + n2, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); } return retval; } int igraph_bipartite_game_gnm(igraph_t *graph, igraph_vector_bool_t *types, igraph_integer_t n1, igraph_integer_t n2, igraph_integer_t m, igraph_bool_t directed, igraph_neimode_t mode) { igraph_vector_t edges; igraph_vector_t s; int retval = 0; if (n1 < 0 || n2 < 0) { IGRAPH_ERROR("Invalid number of vertices", IGRAPH_EINVAL); } if (m < 0) { IGRAPH_ERROR("Invalid number of edges", IGRAPH_EINVAL); } if (types) { long int i; IGRAPH_CHECK(igraph_vector_bool_resize(types, n1 + n2)); igraph_vector_bool_null(types); for (i = n1; i < n1 + n2; i++) { VECTOR(*types)[i] = 1; } } if (m == 0 || n1 * n2 == 0) { if (m > 0) { IGRAPH_ERROR("Invalid number (too large) of edges", IGRAPH_EINVAL); } IGRAPH_CHECK(retval = igraph_empty(graph, n1 + n2, directed)); } else { long int i; double maxedges; if (!directed || mode != IGRAPH_ALL) { maxedges = (double) n1 * (double) n2; } else { maxedges = 2.0 * (double) n1 * (double) n2; } if (m > maxedges) { IGRAPH_ERROR("Invalid number (too large) of edges", IGRAPH_EINVAL); } if (maxedges == m) { IGRAPH_CHECK(retval = igraph_full_bipartite(graph, types, n1, n2, directed, mode)); } else { long int to, from; IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_VECTOR_INIT_FINALLY(&s, 0); IGRAPH_CHECK(igraph_random_sample(&s, 0, maxedges - 1, m)); IGRAPH_CHECK(igraph_vector_reserve(&edges, igraph_vector_size(&s) * 2)); for (i = 0; i < m; i++) { if (!directed || mode != IGRAPH_ALL) { to = (long) floor(VECTOR(s)[i] / n1); from = (long) (VECTOR(s)[i] - ((igraph_real_t) to) * n1); to += n1; } else { long int n1n2 = n1 * n2; if (VECTOR(s)[i] < n1n2) { to = (long) floor(VECTOR(s)[i] / n1); from = (long) (VECTOR(s)[i] - ((igraph_real_t) to) * n1); to += n1; } else { to = (long) floor( (VECTOR(s)[i] - n1n2) / n2); from = (long) (VECTOR(s)[i] - n1n2 - ((igraph_real_t) to) * n2); from += n1; } } if (mode != IGRAPH_IN) { igraph_vector_push_back(&edges, from); igraph_vector_push_back(&edges, to); } else { igraph_vector_push_back(&edges, to); igraph_vector_push_back(&edges, from); } } igraph_vector_destroy(&s); IGRAPH_FINALLY_CLEAN(1); IGRAPH_CHECK(retval = igraph_create(graph, &edges, n1 + n2, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); } } return retval; } /** * \function igraph_bipartite_game * Generate a bipartite random graph (similar to Erdos-Renyi) * * Similarly to unipartite (one-mode) networks, we can define the * G(n,p), and G(n,m) graph classes for bipartite graphs, via their * generating process. In G(n,p) every possible edge between top and * bottom vertices is realized with probablity p, independently of the * rest of the edges. In G(n,m), we uniformly choose m edges to * realize. * \param graph Pointer to an uninitialized igraph graph, the result * is stored here. * \param types Pointer to an initialized boolean vector, or a null * pointer. If not a null pointer, then the vertex types are stored * here. Bottom vertices come first, n1 of them, then n2 top * vertices. * \param type The type of the random graph, possible values: * \clist * \cli IGRAPH_ERDOS_RENYI_GNM * G(n,m) graph, * m edges are * selected uniformly randomly in a graph with * n vertices. * \cli IGRAPH_ERDOS_RENYI_GNP * G(n,p) graph, * every possible edge is included in the graph with * probability p. * \endclist * \param n1 The number of bottom vertices. * \param n2 The number of top verices. * \param p The connection probability for G(n,p) graphs. It is * ignored for G(n,m) graphs. * \param m The number of edges for G(n,m) graphs. It is ignored for * G(n,p) graphs. * \param directed Boolean, whether to generate a directed graph. See * also the \p mode argument. * \param mode Specifies how to direct the edges in directed * graphs. If it is \c IGRAPH_OUT, then directed edges point from * bottom vertices to top vertices. If it is \c IGRAPH_IN, edges * point from top vertices to bottom vertices. \c IGRAPH_OUT and * \c IGRAPH_IN do not generate mutual edges. If this argument is * \c IGRAPH_ALL, then each edge direction is considered * independently and mutual edges might be generated. This * argument is ignored for undirected graphs. * \return Error code. * * \sa \ref igraph_erdos_renyi_game. * * Time complexity: O(|V|+|E|), linear in the number of vertices and * edges. */ int igraph_bipartite_game(igraph_t *graph, igraph_vector_bool_t *types, igraph_erdos_renyi_t type, igraph_integer_t n1, igraph_integer_t n2, igraph_real_t p, igraph_integer_t m, igraph_bool_t directed, igraph_neimode_t mode) { int retval = 0; if (n1 < 0 || n2 < 0) { IGRAPH_ERROR("Invalid number of vertices", IGRAPH_EINVAL); } if (type == IGRAPH_ERDOS_RENYI_GNP) { retval = igraph_bipartite_game_gnp(graph, types, n1, n2, p, directed, mode); } else if (type == IGRAPH_ERDOS_RENYI_GNM) { retval = igraph_bipartite_game_gnm(graph, types, n1, n2, m, directed, mode); } else { IGRAPH_ERROR("Invalid type", IGRAPH_EINVAL); } return retval; } python-igraph-0.8.0/vendor/source/igraph/src/drl_parse.cpp0000644000076500000240000001645313614300625024066 0ustar tamasstaff00000000000000/* * Copyright 2007 Sandia Corporation. Under the terms of Contract * DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains * certain rights in this software. * * All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are * met: * * * Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * Neither the name of Sandia National Laboratories nor the names of * its contributors may be used to endorse or promote products derived from * this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT * OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED * TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF * LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING * NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. */ // This file contains the methods for the parse.h class #include #include #include #include #include using namespace std; #include "drl_layout.h" #include "drl_parse.h" namespace drl { // void parse::print_syntax( const char *error_string ) // { // cout << endl << "Error: " << error_string << endl; // cout << endl << "Layout" << endl // << "------" << endl // << "S. Martin" << endl // << "Version " << DRL_VERSION << endl << endl // << "This program provides a parallel adaptation of a force directed" << endl // << "graph layout algorithm for use with large datasets." << endl << endl // << "Usage: layout [options] root_file" << endl << endl // << "root_file -- the root name of the file being processed." << endl << endl // << "INPUT" << endl // << "-----" << endl // << "root_file.int -- the input file containing the graph to draw using layout." << endl // << " The .int file must have the suffix \".int\" and each line of .int file" << endl // << " should have the form" << endl // << "\tnode_id node_id weight" << endl // << " where node_id's are integers in sequence starting from 0, and" << endl // << " weight is a float > 0." << endl << endl // << "OUTPUT" << endl // << "------" << endl // << "root_file.icoord -- the resulting output file, containing an ordination" << endl // << " of the graph. The .icoord file will have the suffix \".icoord\" and" << endl // << " each line of the .icoord file will be of the form" << endl // << "\tnode_id x-coord y-coord" << endl << endl // << "Options:" << endl << endl // << "\t-s {int>=0} random seed (default value is 0)" << endl // << "\t-c {real[0,1]} edge cutting (default 32/40 = .8)" << endl // << "\t (old max was 39/40 = .975)" << endl // << "\t-p input parameters from .parms file" << endl // << "\t-r {real[0,1]} input coordinates from .real file" << endl // << "\t (hold fixed until fraction of optimization schedule reached)" << endl // << "\t-i {int>=0} intermediate output interval (default 0: no output)" << endl // << "\t-e output .iedges file (same prefix as .coord file)" << endl << endl; // #ifdef MUSE_MPI // MPI_Abort ( MPI_COMM_WORLD, 1 ); // #else // exit (1); // #endif // } // parse::parse ( int argc, char** argv) // { // map m; // // make sure there is at least one argument // if ( argc < 2) // print_syntax ( "not enough arguments!" ); // // make sure coord_file ends in ".coord" // parms_file = real_file = sim_file = coord_file = argv[argc-1]; // parms_file = parms_file + ".parms"; // real_file = real_file + ".real"; // sim_file = sim_file + ".int"; // coord_file = coord_file + ".icoord"; // char error_string[200]; // sprintf ( error_string, "%s %d %s", "root file name cannot be longer than", MAX_FILE_NAME-7, // "characters."); // if ( coord_file.length() > MAX_FILE_NAME ) // print_syntax ( error_string ); // // echo sim_file and coord_file // cout << "Using " << sim_file << " for .int file, and " << coord_file << " for .icoord file." << endl; // // set defaults // rand_seed = 0; // //edge_cut = 32.0/39.0; // (old default) // edge_cut = 32.0/40.0; // int_out = 0; // edges_out = 0; // parms_in = 0; // real_in = -1.0; // // now check for optional arguments // string arg; // for( int i = 1; i= (argc-1) ) // print_syntax ( "-s flag has no argument." ); // else // { // rand_seed = atoi ( argv[i] ); // if ( rand_seed < 0 ) // print_syntax ( "random seed must be >= 0." ); // } // } // // check for edge cutting // else if ( arg == "-c" ) // { // i++; // if ( i >= (argc-1) ) // print_syntax ( "-c flag has no argument." ); // else // { // edge_cut = atof ( argv[i] ); // if ( (edge_cut < 0) || (edge_cut > 1) ) // print_syntax ( "edge cut must be between 0 and 1." ); // } // } // // check for intermediate output // else if ( arg == "-i" ) // { // i++; // if ( i >= (argc-1) ) // print_syntax ( "-i flag has no argument." ); // else // { // int_out = atoi ( argv[i] ); // if ( int_out < 0 ) // print_syntax ( "intermediate output must be >= 0." ); // } // } // // check for .real input // else if ( arg == "-r" ) // { // i++; // if ( i >= (argc-1) ) // print_syntax ( "-r flag has no argument." ); // else // { // real_in = atof ( argv[i] ); // if ( (real_in < 0) || (real_in > 1) ) // print_syntax ( "real iteration fraction must be from 0 to 1." ); // } // } // else if ( arg == "-e" ) // edges_out = 1; // else if ( arg == "-p" ) // parms_in = 1; // else // print_syntax ( "unrecongized option!" ); // } // if ( parms_in ) // cout << "Using " << parms_file << " for .parms file." << endl; // if ( real_in >= 0 ) // cout << "Using " << real_file << " for .real file." << endl; // // echo arguments input or default // cout << "Using random seed = " << rand_seed << endl // << " edge_cutting = " << edge_cut << endl // << " intermediate output = " << int_out << endl // << " output .iedges file = " << edges_out << endl; // if ( real_in >= 0 ) // cout << " holding .real fixed until iterations = " << real_in << endl; // } } // namespace drl python-igraph-0.8.0/vendor/source/igraph/src/hrg_rbtree.h0000644000076500000240000001376213614300625023703 0ustar tamasstaff00000000000000/* -*- mode: C++ -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ // **************************************************************************************************** // *** COPYRIGHT NOTICE ******************************************************************************* // rbtree - red-black tree (self-balancing binary tree data structure) // Copyright (C) 2004 Aaron Clauset // // This program is free software; you can redistribute it and/or modify // it under the terms of the GNU General Public License as published by // the Free Software Foundation; either version 2 of the License, or // (at your option) any later version. // // This program is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU General Public License for more details. // // You should have received a copy of the GNU General Public License // along with this program; if not, write to the Free Software // Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA // // See http://www.gnu.org/licenses/gpl.txt for more details. // // **************************************************************************************************** // Author : Aaron Clauset ( aaronc@santafe.edu | http://www.santafe.edu/~aaronc/ ) // Collaborators: Cristopher Moore and Mark Newman // Project : Hierarchical Random Graphs // Location : University of New Mexico, Dept. of Computer Science AND Santa Fe Institute // Created : Spring 2004 // Modified : many, many times // // **************************************************************************************************** #ifndef IGRAPH_HRG_RBTREE #define IGRAPH_HRG_RBTREE #include using namespace std; namespace fitHRG { // ******** Basic Structures ********************************************* #ifndef IGRAPH_HRG_LIST #define IGRAPH_HRG_LIST class list { public: int x; // stored elementd in linked-list list* next; // pointer to next elementd list(): x(-1), next(0) { } ~list() { } }; #endif class keyValuePair { public: int x; // elementrb key (int) int y; // stored value (int) keyValuePair* next; // linked-list pointer keyValuePair(): x(-1), y(-1), next(0) { } ~keyValuePair() { } }; // ******** Tree elementrb Class ***************************************** class elementrb { public: int key; // search key (int) int value; // stored value (int) bool color; // F: BLACK, T: RED short int mark; // marker elementrb *parent; // pointer to parent node elementrb *left; // pointer for left subtree elementrb *right; // pointer for right subtree elementrb(): key(-1), value(-1), color(false), mark(0), parent(0), left(0), right(0) { } ~elementrb() { } }; // ******** Red-Black Tree Class ***************************************** // This vector implementation is a red-black balanced binary tree data // structure. It provides find a stored elementrb in time O(log n), // find the maximum elementrb in time O(1), delete an elementrb in // time O(log n), and insert an elementrb in time O(log n). // // Note that the key=0 is assumed to be a special value, and thus you // cannot insert such an item. Beware of this limitation. class rbtree { private: elementrb* root; // binary tree root elementrb* leaf; // all leaf nodes int support; // number of nodes in the tree void rotateLeft(elementrb *x); // left-rotation operator void rotateRight(elementrb *y); // right-rotation operator void insertCleanup(elementrb *z); // house-keeping after insertion void deleteCleanup(elementrb *x); // house-keeping after deletion keyValuePair* returnSubtreeAsList(elementrb *z, keyValuePair *head); void deleteSubTree(elementrb *z); // delete subtree rooted at z elementrb* returnMinKey(elementrb *z); // returns minimum of subtree // rooted at z elementrb* returnSuccessor(elementrb *z); // returns successor of z's key public: rbtree(); ~rbtree(); // default constructor/destructor // returns value associated with searchKey int returnValue(const int searchKey); // returns T if searchKey found, and points foundNode at the // corresponding node elementrb* findItem(const int searchKey); // insert a new key with stored value void insertItem(int newKey, int newValue); // selete a node with given key void deleteItem(int killKey); // replace value of a node with given key void replaceItem(int key, int newValue); // increment the value of the given key void incrementValue(int key); // delete the entire tree void deleteTree(); // return array of keys in tree int* returnArrayOfKeys(); // return list of keys in tree list* returnListOfKeys(); // return the tree as a list of keyValuePairs keyValuePair* returnTreeAsList(); // returns the maximum key in the tree keyValuePair returnMaxKey(); // returns the minimum key in the tree keyValuePair returnMinKey(); // returns number of items in tree int returnNodecount(); }; } #endif python-igraph-0.8.0/vendor/source/igraph/src/memory.c0000644000076500000240000000574413614300625023064 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2003-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_memory.h" #include "config.h" /** * \function igraph_free * Deallocate memory that was allocated by igraph functions * * Some igraph functions return a pointer vector (igraph_vector_ptr_t) * containing pointers to other igraph or other data types. These data * types are dynamically allocated and have to be deallocated * manually, if the user does not need them any more. This can be done * by calling igraph_free on them. * * * Here is a complete example on how to use \c igraph_free properly. * * * * int main(void) * { * igraph_t graph; * igraph_vector_ptr_t seps; * long int i; * * igraph_famous(&graph, "tutte"); * igraph_vector_ptr_init(&seps, 0); * igraph_minimum_size_separators(&graph, &seps); * * for (i=0; i * * * * \param p Pointer to the piece of memory to be deallocated. * \return Error code, currently always zero, meaning success. * * Time complexity: platform dependent, ideally it should be O(1). * * \sa \ref igraph_malloc() */ int igraph_free(void *p) { igraph_Free(p); return 0; } /** * \function igraph_malloc * Allocate memory that can be safely deallocated by igraph functions * * Some igraph functions, such as \ref igraph_vector_ptr_free_all() and * \ref igraph_vector_ptr_destroy_all() can free memory that may have been * allocated by the user. \c igraph_malloc() works exactly like \c malloc() * from the C standard library, but it is guaranteed that it can be safely * paired with the \c free() function used by igraph internally (which is * also user-accessible through \ref igraph_free()). * * \param n Number of bytes to be allocated. * \return Pointer to the piece of allocated memory. * * \sa \ref igraph_free() */ void *igraph_malloc(size_t n) { return malloc(n); } python-igraph-0.8.0/vendor/source/igraph/src/math.c0000644000076500000240000002255613614300625022505 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include #include "config.h" #include "igraph_math.h" #include "igraph_types.h" #ifdef _MSC_VER #define isinf(x) (!_finite(x) && !_isnan(x)) #endif int igraph_finite(double x) { #ifdef isfinite return isfinite(x); #elif HAVE_ISFINITE == 1 return isfinite(x); #elif HAVE_FINITE == 1 return finite(x); #else /* neither finite nor isfinite work. Do we really need the AIX exception? */ # ifdef _AIX # include return FINITE(x); # else return (!isnan(x) & (x != IGRAPH_POSINFINITY) & (x != IGRAPH_NEGINFINITY)); # endif #endif } double igraph_log2(const double a) { return log(a) / log(2.0); } int igraph_chebyshev_init(const double *dos, int nos, double eta) { int i, ii; double err; if (nos < 1) { return 0; } err = 0.0; i = 0; /* just to avoid compiler warnings */ for (ii = 1; ii <= nos; ii++) { i = nos - ii; err += fabs(dos[i]); if (err > eta) { return i; } } return i; } double igraph_chebyshev_eval(double x, const double *a, const int n) { double b0, b1, b2, twox; int i; if (n < 1 || n > 1000) { IGRAPH_NAN; } if (x < -1.1 || x > 1.1) { IGRAPH_NAN; } twox = x * 2; b2 = b1 = 0; b0 = 0; for (i = 1; i <= n; i++) { b2 = b1; b1 = b0; b0 = twox * b1 - b2 + a[n - i]; } return (b0 - b2) * 0.5; } double igraph_log1p(double x) { /* series for log1p on the interval -.375 to .375 * with weighted error 6.35e-32 * log weighted error 31.20 * significant figures required 30.93 * decimal places required 32.01 */ static const double alnrcs[43] = { +.10378693562743769800686267719098e+1, -.13364301504908918098766041553133e+0, +.19408249135520563357926199374750e-1, -.30107551127535777690376537776592e-2, +.48694614797154850090456366509137e-3, -.81054881893175356066809943008622e-4, +.13778847799559524782938251496059e-4, -.23802210894358970251369992914935e-5, +.41640416213865183476391859901989e-6, -.73595828378075994984266837031998e-7, +.13117611876241674949152294345011e-7, -.23546709317742425136696092330175e-8, +.42522773276034997775638052962567e-9, -.77190894134840796826108107493300e-10, +.14075746481359069909215356472191e-10, -.25769072058024680627537078627584e-11, +.47342406666294421849154395005938e-12, -.87249012674742641745301263292675e-13, +.16124614902740551465739833119115e-13, -.29875652015665773006710792416815e-14, +.55480701209082887983041321697279e-15, -.10324619158271569595141333961932e-15, +.19250239203049851177878503244868e-16, -.35955073465265150011189707844266e-17, +.67264542537876857892194574226773e-18, -.12602624168735219252082425637546e-18, +.23644884408606210044916158955519e-19, -.44419377050807936898878389179733e-20, +.83546594464034259016241293994666e-21, -.15731559416479562574899253521066e-21, +.29653128740247422686154369706666e-22, -.55949583481815947292156013226666e-23, +.10566354268835681048187284138666e-23, -.19972483680670204548314999466666e-24, +.37782977818839361421049855999999e-25, -.71531586889081740345038165333333e-26, +.13552488463674213646502024533333e-26, -.25694673048487567430079829333333e-27, +.48747756066216949076459519999999e-28, -.92542112530849715321132373333333e-29, +.17578597841760239233269760000000e-29, -.33410026677731010351377066666666e-30, +.63533936180236187354180266666666e-31, }; static IGRAPH_THREAD_LOCAL int nlnrel = 0; static IGRAPH_THREAD_LOCAL double xmin = 0.0; if (xmin == 0.0) { xmin = -1 + sqrt(DBL_EPSILON); /*was sqrt(d1mach(4)); */ } if (nlnrel == 0) { /* initialize chebychev coefficients */ nlnrel = igraph_chebyshev_init(alnrcs, 43, DBL_EPSILON / 20); /*was .1*d1mach(3)*/ } if (x == 0.) { return 0.; /* speed */ } if (x == -1) { return (IGRAPH_NEGINFINITY); } if (x < -1) { return (IGRAPH_NAN); } if (fabs(x) <= .375) { /* Improve on speed (only); again give result accurate to IEEE double precision: */ if (fabs(x) < .5 * DBL_EPSILON) { return x; } if ( (0 < x && x < 1e-8) || (-1e-9 < x && x < 0)) { return x * (1 - .5 * x); } /* else */ return x * (1 - x * igraph_chebyshev_eval(x / .375, alnrcs, nlnrel)); } /* else */ /* if (x < xmin) { */ /* /\* answer less than half precision because x too near -1 *\/ */ /* ML_ERROR(ME_PRECISION, "log1p"); */ /* } */ return log(1 + x); } long double igraph_fabsl(long double a) { if (a < 0) { return -a; } else { return a; } } double igraph_fmin(double a, double b) { if (b < a) { return b; } else { return a; } } double igraph_i_round(double X) { /* NaN */ if (X != X) { return X; } if (X < 0.0) { return floor(X); } return ceil(X); } #ifdef _MSC_VER /** * Internal function, replacement for snprintf * Used only in case of the Microsoft Visual C compiler which does not * provide a proper sprintf implementation. * * This implementation differs from the standard in the value returned * when the number of characters needed by the output, excluding the * terminating '\0' is larger than count */ int igraph_i_snprintf(char *buffer, size_t count, const char *format, ...) { int n; va_list args; if (count > 0) { va_start(args, format); n = _vsnprintf(buffer, count, format, args); buffer[count - 1] = 0; va_end(args); } else { n = 0; } return n; } #endif int igraph_is_nan(double x) { return isnan(x); } int igraph_is_inf(double x) { return isinf(x) != 0; } int igraph_is_posinf(double x) { return isinf(x) == 1; } int igraph_is_neginf(double x) { return isinf(x) == -1; } /** * \function igraph_almost_equals * Compare two double-precision floats with a tolerance * * Determines whether two double-precision floats are "almost equal" * to each other with a given level of tolerance on the relative error. * * \param a the first float * \param b the second float * \param eps the level of tolerance on the relative error. The relative * error is defined as \c "abs(a-b) / (abs(a) + abs(b))". The * two numbers are considered equal if this is less than \c eps. * * \return nonzero if the two floats are nearly equal to each other within * the given level of tolerance, zero otherwise */ int igraph_almost_equals(double a, double b, double eps) { return igraph_cmp_epsilon(a, b, eps) == 0 ? 1 : 0; } /** * \function igraph_cmp_epsilon * Compare two double-precision floats with a tolerance * * Determines whether two double-precision floats are "almost equal" * to each other with a given level of tolerance on the relative error. * * \param a the first float * \param b the second float * \param eps the level of tolerance on the relative error. The relative * error is defined as \c "abs(a-b) / (abs(a) + abs(b))". The * two numbers are considered equal if this is less than \c eps. * * \return zero if the two floats are nearly equal to each other within * the given level of tolerance, positive number if the first float is * larger, negative number if the second float is larger */ int igraph_cmp_epsilon(double a, double b, double eps) { double diff; double abs_diff; if (a == b) { /* shortcut, handles infinities */ return 0; } diff = a - b; abs_diff = fabs(diff); if (a == 0 || b == 0 || diff < DBL_MIN) { /* a or b is zero or both are extremely close to it; relative * error is less meaningful here so just compare it with * epsilon */ return abs_diff < (eps * DBL_MIN) ? 0 : (diff < 0 ? -1 : 1); } else { /* use relative error */ return (abs_diff / (fabs(a) + fabs(b)) < eps) ? 0 : (diff < 0 ? -1 : 1); } } python-igraph-0.8.0/vendor/source/igraph/src/eigen.c0000644000076500000240000014256713614300625022650 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_eigen.h" #include "igraph_qsort.h" #include "igraph_blas.h" #include "igraph_interface.h" #include "igraph_adjlist.h" #include #include #include int igraph_i_eigen_arpackfun_to_mat(igraph_arpack_function_t *fun, int n, void *extra, igraph_matrix_t *res) { int i; igraph_vector_t v; IGRAPH_CHECK(igraph_matrix_init(res, n, n)); IGRAPH_FINALLY(igraph_matrix_destroy, res); IGRAPH_VECTOR_INIT_FINALLY(&v, n); VECTOR(v)[0] = 1; IGRAPH_CHECK(fun(/*to=*/ &MATRIX(*res, 0, 0), /*from=*/ VECTOR(v), n, extra)); for (i = 1; i < n; i++) { VECTOR(v)[i - 1] = 0; VECTOR(v)[i ] = 1; IGRAPH_CHECK(fun(/*to=*/ &MATRIX(*res, 0, i), /*from=*/ VECTOR(v), n, extra)); } igraph_vector_destroy(&v); IGRAPH_FINALLY_CLEAN(2); return 0; } int igraph_i_eigen_matrix_symmetric_lapack_lm(const igraph_matrix_t *A, const igraph_eigen_which_t *which, igraph_vector_t *values, igraph_matrix_t *vectors) { igraph_matrix_t vec1, vec2; igraph_vector_t val1, val2; int n = (int) igraph_matrix_nrow(A); int p1 = 0, p2 = which->howmany - 1, pr = 0; IGRAPH_VECTOR_INIT_FINALLY(&val1, 0); IGRAPH_VECTOR_INIT_FINALLY(&val2, 0); if (vectors) { IGRAPH_CHECK(igraph_matrix_init(&vec1, 0, 0)); IGRAPH_FINALLY(igraph_matrix_destroy, &vec1); IGRAPH_CHECK(igraph_matrix_init(&vec2, 0, 0)); IGRAPH_FINALLY(igraph_matrix_destroy, &vec1); } IGRAPH_CHECK(igraph_lapack_dsyevr(A, IGRAPH_LAPACK_DSYEV_SELECT, /*vl=*/ 0, /*vu=*/ 0, /*vestimate=*/ 0, /*il=*/ 1, /*iu=*/ which->howmany, /*abstol=*/ 1e-14, &val1, vectors ? &vec1 : 0, /*support=*/ 0)); IGRAPH_CHECK(igraph_lapack_dsyevr(A, IGRAPH_LAPACK_DSYEV_SELECT, /*vl=*/ 0, /*vu=*/ 0, /*vestimate=*/ 0, /*il=*/ n - which->howmany + 1, /*iu=*/ n, /*abstol=*/ 1e-14, &val2, vectors ? &vec2 : 0, /*support=*/ 0)); if (values) { IGRAPH_CHECK(igraph_vector_resize(values, which->howmany)); } if (vectors) { IGRAPH_CHECK(igraph_matrix_resize(vectors, n, which->howmany)); } while (pr < which->howmany) { if (p2 < 0 || fabs(VECTOR(val1)[p1]) > fabs(VECTOR(val2)[p2])) { if (values) { VECTOR(*values)[pr] = VECTOR(val1)[p1]; } if (vectors) { memcpy(&MATRIX(*vectors, 0, pr), &MATRIX(vec1, 0, p1), sizeof(igraph_real_t) * (size_t) n); } p1++; pr++; } else { if (values) { VECTOR(*values)[pr] = VECTOR(val2)[p2]; } if (vectors) { memcpy(&MATRIX(*vectors, 0, pr), &MATRIX(vec2, 0, p2), sizeof(igraph_real_t) * (size_t) n); } p2--; pr++; } } if (vectors) { igraph_matrix_destroy(&vec2); igraph_matrix_destroy(&vec1); IGRAPH_FINALLY_CLEAN(2); } igraph_vector_destroy(&val2); igraph_vector_destroy(&val1); IGRAPH_FINALLY_CLEAN(2); return 0; } int igraph_i_eigen_matrix_symmetric_lapack_sm(const igraph_matrix_t *A, const igraph_eigen_which_t *which, igraph_vector_t *values, igraph_matrix_t *vectors) { igraph_vector_t val; igraph_matrix_t vec; int i, w = 0, n = (int) igraph_matrix_nrow(A); igraph_real_t small; int p1, p2, pr = 0; IGRAPH_VECTOR_INIT_FINALLY(&val, 0); if (vectors) { IGRAPH_MATRIX_INIT_FINALLY(&vec, 0, 0); } IGRAPH_CHECK(igraph_lapack_dsyevr(A, IGRAPH_LAPACK_DSYEV_ALL, /*vl=*/ 0, /*vu=*/ 0, /*vestimate=*/ 0, /*il=*/ 0, /*iu=*/ 0, /*abstol=*/ 1e-14, &val, vectors ? &vec : 0, /*support=*/ 0)); /* Look for smallest value */ small = fabs(VECTOR(val)[0]); for (i = 1; i < n; i++) { igraph_real_t v = fabs(VECTOR(val)[i]); if (v < small) { small = v; w = i; } } p1 = w - 1; p2 = w; if (values) { IGRAPH_CHECK(igraph_vector_resize(values, which->howmany)); } if (vectors) { IGRAPH_CHECK(igraph_matrix_resize(vectors, n, which->howmany)); } while (pr < which->howmany) { if (p2 == n - 1 || fabs(VECTOR(val)[p1]) < fabs(VECTOR(val)[p2])) { if (values) { VECTOR(*values)[pr] = VECTOR(val)[p1]; } if (vectors) { memcpy(&MATRIX(*vectors, 0, pr), &MATRIX(vec, 0, p1), sizeof(igraph_real_t) * (size_t) n); } p1--; pr++; } else { if (values) { VECTOR(*values)[pr] = VECTOR(val)[p2]; } if (vectors) { memcpy(&MATRIX(*vectors, 0, pr), &MATRIX(vec, 0, p2), sizeof(igraph_real_t) * (size_t) n); } p2++; pr++; } } if (vectors) { igraph_matrix_destroy(&vec); IGRAPH_FINALLY_CLEAN(1); } igraph_vector_destroy(&val); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_i_eigen_matrix_symmetric_lapack_la(const igraph_matrix_t *A, const igraph_eigen_which_t *which, igraph_vector_t *values, igraph_matrix_t *vectors) { /* TODO: ordering? */ int n = (int) igraph_matrix_nrow(A); int il = n - which->howmany + 1; IGRAPH_CHECK(igraph_lapack_dsyevr(A, IGRAPH_LAPACK_DSYEV_SELECT, /*vl=*/ 0, /*vu=*/ 0, /*vestimate=*/ 0, /*il=*/ il, /*iu=*/ n, /*abstol=*/ 1e-14, values, vectors, /*support=*/ 0)); return 0; } int igraph_i_eigen_matrix_symmetric_lapack_sa(const igraph_matrix_t *A, const igraph_eigen_which_t *which, igraph_vector_t *values, igraph_matrix_t *vectors) { /* TODO: ordering? */ IGRAPH_CHECK(igraph_lapack_dsyevr(A, IGRAPH_LAPACK_DSYEV_SELECT, /*vl=*/ 0, /*vu=*/ 0, /*vestimate=*/ 0, /*il=*/ 1, /*iu=*/ which->howmany, /*abstol=*/ 1e-14, values, vectors, /*support=*/ 0)); return 0; } int igraph_i_eigen_matrix_symmetric_lapack_be(const igraph_matrix_t *A, const igraph_eigen_which_t *which, igraph_vector_t *values, igraph_matrix_t *vectors) { /* TODO: ordering? */ igraph_matrix_t vec1, vec2; igraph_vector_t val1, val2; int n = (int) igraph_matrix_nrow(A); int p1 = 0, p2 = which->howmany / 2, pr = 0; IGRAPH_VECTOR_INIT_FINALLY(&val1, 0); IGRAPH_VECTOR_INIT_FINALLY(&val2, 0); if (vectors) { IGRAPH_CHECK(igraph_matrix_init(&vec1, 0, 0)); IGRAPH_FINALLY(igraph_matrix_destroy, &vec1); IGRAPH_CHECK(igraph_matrix_init(&vec2, 0, 0)); IGRAPH_FINALLY(igraph_matrix_destroy, &vec1); } IGRAPH_CHECK(igraph_lapack_dsyevr(A, IGRAPH_LAPACK_DSYEV_SELECT, /*vl=*/ 0, /*vu=*/ 0, /*vestimate=*/ 0, /*il=*/ 1, /*iu=*/ (which->howmany) / 2, /*abstol=*/ 1e-14, &val1, vectors ? &vec1 : 0, /*support=*/ 0)); IGRAPH_CHECK(igraph_lapack_dsyevr(A, IGRAPH_LAPACK_DSYEV_SELECT, /*vl=*/ 0, /*vu=*/ 0, /*vestimate=*/ 0, /*il=*/ n - (which->howmany) / 2, /*iu=*/ n, /*abstol=*/ 1e-14, &val2, vectors ? &vec2 : 0, /*support=*/ 0)); if (values) { IGRAPH_CHECK(igraph_vector_resize(values, which->howmany)); } if (vectors) { IGRAPH_CHECK(igraph_matrix_resize(vectors, n, which->howmany)); } while (pr < which->howmany) { if (pr % 2) { if (values) { VECTOR(*values)[pr] = VECTOR(val1)[p1]; } if (vectors) { memcpy(&MATRIX(*vectors, 0, pr), &MATRIX(vec1, 0, p1), sizeof(igraph_real_t) * (size_t) n); } p1++; pr++; } else { if (values) { VECTOR(*values)[pr] = VECTOR(val2)[p2]; } if (vectors) { memcpy(&MATRIX(*vectors, 0, pr), &MATRIX(vec2, 0, p2), sizeof(igraph_real_t) * (size_t) n); } p2--; pr++; } } if (vectors) { igraph_matrix_destroy(&vec2); igraph_matrix_destroy(&vec1); IGRAPH_FINALLY_CLEAN(2); } igraph_vector_destroy(&val2); igraph_vector_destroy(&val1); IGRAPH_FINALLY_CLEAN(2); return 0; } int igraph_i_eigen_matrix_symmetric_lapack_all(const igraph_matrix_t *A, igraph_vector_t *values, igraph_matrix_t *vectors) { IGRAPH_CHECK(igraph_lapack_dsyevr(A, IGRAPH_LAPACK_DSYEV_ALL, /*vl=*/ 0, /*vu=*/ 0, /*vestimate=*/ 0, /*il=*/ 0, /*iu=*/ 0, /*abstol=*/ 1e-14, values, vectors, /*support=*/ 0)); return 0; } int igraph_i_eigen_matrix_symmetric_lapack_iv(const igraph_matrix_t *A, const igraph_eigen_which_t *which, igraph_vector_t *values, igraph_matrix_t *vectors) { IGRAPH_CHECK(igraph_lapack_dsyevr(A, IGRAPH_LAPACK_DSYEV_INTERVAL, /*vl=*/ which->vl, /*vu=*/ which->vu, /*vestimate=*/ which->vestimate, /*il=*/ 0, /*iu=*/ 0, /*abstol=*/ 1e-14, values, vectors, /*support=*/ 0)); return 0; } int igraph_i_eigen_matrix_symmetric_lapack_sel(const igraph_matrix_t *A, const igraph_eigen_which_t *which, igraph_vector_t *values, igraph_matrix_t *vectors) { IGRAPH_CHECK(igraph_lapack_dsyevr(A, IGRAPH_LAPACK_DSYEV_SELECT, /*vl=*/ 0, /*vu=*/ 0, /*vestimate=*/ 0, /*il=*/ which->il, /*iu=*/ which->iu, /*abstol=*/ 1e-14, values, vectors, /*support=*/ 0)); return 0; } int igraph_i_eigen_matrix_symmetric_lapack(const igraph_matrix_t *A, const igraph_sparsemat_t *sA, igraph_arpack_function_t *fun, int n, void *extra, const igraph_eigen_which_t *which, igraph_vector_t *values, igraph_matrix_t *vectors) { const igraph_matrix_t *myA = A; igraph_matrix_t mA; /* First we need to create a dense square matrix */ if (A) { n = (int) igraph_matrix_nrow(A); } else if (sA) { n = (int) igraph_sparsemat_nrow(sA); IGRAPH_CHECK(igraph_matrix_init(&mA, 0, 0)); IGRAPH_FINALLY(igraph_matrix_destroy, &mA); IGRAPH_CHECK(igraph_sparsemat_as_matrix(&mA, sA)); myA = &mA; } else if (fun) { IGRAPH_CHECK(igraph_i_eigen_arpackfun_to_mat(fun, n, extra, &mA)); IGRAPH_FINALLY(igraph_matrix_destroy, &mA); myA = &mA; } switch (which->pos) { case IGRAPH_EIGEN_LM: IGRAPH_CHECK(igraph_i_eigen_matrix_symmetric_lapack_lm(myA, which, values, vectors)); break; case IGRAPH_EIGEN_SM: IGRAPH_CHECK(igraph_i_eigen_matrix_symmetric_lapack_sm(myA, which, values, vectors)); break; case IGRAPH_EIGEN_LA: IGRAPH_CHECK(igraph_i_eigen_matrix_symmetric_lapack_la(myA, which, values, vectors)); break; case IGRAPH_EIGEN_SA: IGRAPH_CHECK(igraph_i_eigen_matrix_symmetric_lapack_sa(myA, which, values, vectors)); break; case IGRAPH_EIGEN_BE: IGRAPH_CHECK(igraph_i_eigen_matrix_symmetric_lapack_be(myA, which, values, vectors)); break; case IGRAPH_EIGEN_ALL: IGRAPH_CHECK(igraph_i_eigen_matrix_symmetric_lapack_all(myA, values, vectors)); break; case IGRAPH_EIGEN_INTERVAL: IGRAPH_CHECK(igraph_i_eigen_matrix_symmetric_lapack_iv(myA, which, values, vectors)); break; case IGRAPH_EIGEN_SELECT: IGRAPH_CHECK(igraph_i_eigen_matrix_symmetric_lapack_sel(myA, which, values, vectors)); break; default: /* This cannot happen */ break; } if (!A) { igraph_matrix_destroy(&mA); IGRAPH_FINALLY_CLEAN(1); } return 0; } typedef struct igraph_i_eigen_matrix_sym_arpack_data_t { const igraph_matrix_t *A; const igraph_sparsemat_t *sA; } igraph_i_eigen_matrix_sym_arpack_data_t; int igraph_i_eigen_matrix_sym_arpack_cb(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_i_eigen_matrix_sym_arpack_data_t *data = (igraph_i_eigen_matrix_sym_arpack_data_t *) extra; if (data->A) { igraph_blas_dgemv_array(/*transpose=*/ 0, /*alpha=*/ 1.0, data->A, from, /*beta=*/ 0.0, to); } else { /* data->sA */ igraph_vector_t vto, vfrom; igraph_vector_view(&vto, to, n); igraph_vector_view(&vfrom, to, n); igraph_vector_null(&vto); igraph_sparsemat_gaxpy(data->sA, &vfrom, &vto); } return 0; } int igraph_i_eigen_matrix_symmetric_arpack_be(const igraph_matrix_t *A, const igraph_sparsemat_t *sA, igraph_arpack_function_t *fun, int n, void *extra, const igraph_eigen_which_t *which, igraph_arpack_options_t *options, igraph_arpack_storage_t *storage, igraph_vector_t *values, igraph_matrix_t *vectors) { igraph_vector_t tmpvalues, tmpvalues2; igraph_matrix_t tmpvectors, tmpvectors2; igraph_i_eigen_matrix_sym_arpack_data_t myextra = { A, sA }; int low = (int) floor(which->howmany / 2.0), high = (int) ceil(which->howmany / 2.0); int l1, l2, w; if (low + high >= n) { IGRAPH_ERROR("Requested too many eigenvalues/vectors", IGRAPH_EINVAL); } if (!fun) { fun = igraph_i_eigen_matrix_sym_arpack_cb; extra = (void*) &myextra; } IGRAPH_VECTOR_INIT_FINALLY(&tmpvalues, high); IGRAPH_MATRIX_INIT_FINALLY(&tmpvectors, n, high); IGRAPH_VECTOR_INIT_FINALLY(&tmpvalues2, low); IGRAPH_MATRIX_INIT_FINALLY(&tmpvectors2, n, low); options->n = n; options->nev = high; options->ncv = 2 * options->nev < n ? 2 * options->nev : n; options->which[0] = 'L'; options->which[1] = 'A'; IGRAPH_CHECK(igraph_arpack_rssolve(fun, extra, options, storage, &tmpvalues, &tmpvectors)); options->nev = low; options->ncv = 2 * options->nev < n ? 2 * options->nev : n; options->which[0] = 'S'; options->which[1] = 'A'; IGRAPH_CHECK(igraph_arpack_rssolve(fun, extra, options, storage, &tmpvalues2, &tmpvectors2)); IGRAPH_CHECK(igraph_vector_resize(values, low + high)); IGRAPH_CHECK(igraph_matrix_resize(vectors, n, low + high)); l1 = 0; l2 = 0; w = 0; while (w < which->howmany) { VECTOR(*values)[w] = VECTOR(tmpvalues)[l1]; memcpy(&MATRIX(*vectors, 0, w), &MATRIX(tmpvectors, 0, l1), (size_t) n * sizeof(igraph_real_t)); w++; l1++; if (w < which->howmany) { VECTOR(*values)[w] = VECTOR(tmpvalues2)[l2]; memcpy(&MATRIX(*vectors, 0, w), &MATRIX(tmpvectors2, 0, l2), (size_t) n * sizeof(igraph_real_t)); w++; l2++; } } igraph_matrix_destroy(&tmpvectors2); igraph_vector_destroy(&tmpvalues2); igraph_matrix_destroy(&tmpvectors); igraph_vector_destroy(&tmpvalues); IGRAPH_FINALLY_CLEAN(4); return 0; } int igraph_i_eigen_matrix_symmetric_arpack(const igraph_matrix_t *A, const igraph_sparsemat_t *sA, igraph_arpack_function_t *fun, int n, void *extra, const igraph_eigen_which_t *which, igraph_arpack_options_t *options, igraph_arpack_storage_t *storage, igraph_vector_t *values, igraph_matrix_t *vectors) { /* For ARPACK we need a matrix multiplication operation. This can be done in any format, so everything is fine, we don't have to convert. */ igraph_i_eigen_matrix_sym_arpack_data_t myextra = { A, sA }; if (!options) { IGRAPH_ERROR("`options' must be given for ARPACK algorithm", IGRAPH_EINVAL); } if (which->pos == IGRAPH_EIGEN_BE) { return igraph_i_eigen_matrix_symmetric_arpack_be(A, sA, fun, n, extra, which, options, storage, values, vectors); } else { switch (which->pos) { case IGRAPH_EIGEN_LM: options->which[0] = 'L'; options->which[1] = 'M'; options->nev = which->howmany; break; case IGRAPH_EIGEN_SM: options->which[0] = 'S'; options->which[1] = 'M'; options->nev = which->howmany; break; case IGRAPH_EIGEN_LA: options->which[0] = 'L'; options->which[1] = 'A'; options->nev = which->howmany; break; case IGRAPH_EIGEN_SA: options->which[0] = 'S'; options->which[1] = 'A'; options->nev = which->howmany; break; case IGRAPH_EIGEN_ALL: options->which[0] = 'L'; options->which[1] = 'M'; options->nev = n; break; case IGRAPH_EIGEN_INTERVAL: IGRAPH_ERROR("Interval of eigenvectors with ARPACK", IGRAPH_UNIMPLEMENTED); /* TODO */ break; case IGRAPH_EIGEN_SELECT: IGRAPH_ERROR("Selected eigenvalues with ARPACK", IGRAPH_UNIMPLEMENTED); /* TODO */ break; default: /* This cannot happen */ break; } options->n = n; options->ncv = 2 * options->nev < n ? 2 * options->nev : n; if (!fun) { fun = igraph_i_eigen_matrix_sym_arpack_cb; extra = (void*) &myextra; } IGRAPH_CHECK(igraph_arpack_rssolve(fun, extra, options, storage, values, vectors)); return 0; } } /* Get the eigenvalues and the eigenvectors from the compressed form. Order them according to the ordering criteria. Comparison functions for the reordering first */ typedef int (*igraph_i_eigen_matrix_lapack_cmp_t)(void*, const void*, const void *); typedef struct igraph_i_eml_cmp_t { const igraph_vector_t *mag, *real, *imag; } igraph_i_eml_cmp_t; /* TODO: these should be defined in some header */ #define EPS (DBL_EPSILON*100) #define LESS(a,b) ((a) < (b)-EPS) #define MORE(a,b) ((a) > (b)+EPS) #define ZERO(a) ((a) > -EPS && (a) < EPS) #define NONZERO(a) ((a) < -EPS || (a) > EPS) /* Largest magnitude. Ordering is according to 1 Larger magnitude 2 Real eigenvalues before complex ones 3 Larger real part 4 Larger imaginary part */ int igraph_i_eigen_matrix_lapack_cmp_lm(void *extra, const void *a, const void *b) { igraph_i_eml_cmp_t *myextra = (igraph_i_eml_cmp_t *) extra; int *aa = (int*) a, *bb = (int*) b; igraph_real_t a_m = VECTOR(*myextra->mag)[*aa]; igraph_real_t b_m = VECTOR(*myextra->mag)[*bb]; if (LESS(a_m, b_m)) { return 1; } else if (MORE(a_m, b_m)) { return -1; } else { igraph_real_t a_r = VECTOR(*myextra->real)[*aa]; igraph_real_t a_i = VECTOR(*myextra->imag)[*aa]; igraph_real_t b_r = VECTOR(*myextra->real)[*bb]; igraph_real_t b_i = VECTOR(*myextra->imag)[*bb]; if (ZERO(a_i) && NONZERO(b_i)) { return -1; } if (NONZERO(a_i) && ZERO(b_i)) { return 1; } if (MORE(a_r, b_r)) { return -1; } if (LESS(a_r, b_r)) { return 1; } if (MORE(a_i, b_i)) { return -1; } if (LESS(a_i, b_i)) { return 1; } } return 0; } /* Smallest marginude. Ordering is according to 1 Magnitude (smaller first) 2 Complex eigenvalues before real ones 3 Smaller real part 4 Smaller imaginary part This ensures that lm has exactly the opposite order to sm */ int igraph_i_eigen_matrix_lapack_cmp_sm(void *extra, const void *a, const void *b) { igraph_i_eml_cmp_t *myextra = (igraph_i_eml_cmp_t *) extra; int *aa = (int*) a, *bb = (int*) b; igraph_real_t a_m = VECTOR(*myextra->mag)[*aa]; igraph_real_t b_m = VECTOR(*myextra->mag)[*bb]; if (MORE(a_m, b_m)) { return 1; } else if (LESS(a_m, b_m)) { return -1; } else { igraph_real_t a_r = VECTOR(*myextra->real)[*aa]; igraph_real_t a_i = VECTOR(*myextra->imag)[*aa]; igraph_real_t b_r = VECTOR(*myextra->real)[*bb]; igraph_real_t b_i = VECTOR(*myextra->imag)[*bb]; if (NONZERO(a_i) && ZERO(b_i)) { return -1; } if (ZERO(a_i) && NONZERO(b_i)) { return 1; } if (LESS(a_r, b_r)) { return -1; } if (MORE(a_r, b_r)) { return 1; } if (LESS(a_i, b_i)) { return -1; } if (MORE(a_i, b_i)) { return 1; } } return 0; } /* Largest real part. Ordering is according to 1 Larger real part 2 Real eigenvalues come before complex ones 3 Larger complex part */ int igraph_i_eigen_matrix_lapack_cmp_lr(void *extra, const void *a, const void *b) { igraph_i_eml_cmp_t *myextra = (igraph_i_eml_cmp_t *) extra; int *aa = (int*) a, *bb = (int*) b; igraph_real_t a_r = VECTOR(*myextra->real)[*aa]; igraph_real_t b_r = VECTOR(*myextra->real)[*bb]; if (MORE(a_r, b_r)) { return -1; } else if (LESS(a_r, b_r)) { return 1; } else { igraph_real_t a_i = VECTOR(*myextra->imag)[*aa]; igraph_real_t b_i = VECTOR(*myextra->imag)[*bb]; if (ZERO(a_i) && NONZERO(b_i)) { return -1; } if (NONZERO(a_i) && ZERO(b_i)) { return 1; } if (MORE(a_i, b_i)) { return -1; } if (LESS(a_i, b_i)) { return 1; } } return 0; } /* Largest real part. Ordering is according to 1 Smaller real part 2 Complex eigenvalues come before real ones 3 Smaller complex part This is opposite to LR */ int igraph_i_eigen_matrix_lapack_cmp_sr(void *extra, const void *a, const void *b) { igraph_i_eml_cmp_t *myextra = (igraph_i_eml_cmp_t *) extra; int *aa = (int*) a, *bb = (int*) b; igraph_real_t a_r = VECTOR(*myextra->real)[*aa]; igraph_real_t b_r = VECTOR(*myextra->real)[*bb]; if (LESS(a_r, b_r)) { return -1; } else if (MORE(a_r, b_r)) { return 1; } else { igraph_real_t a_i = VECTOR(*myextra->imag)[*aa]; igraph_real_t b_i = VECTOR(*myextra->imag)[*bb]; if (NONZERO(a_i) && ZERO(b_i)) { return -1; } if (ZERO(a_i) && NONZERO(b_i)) { return 1; } if (LESS(a_i, b_i)) { return -1; } if (MORE(a_i, b_i)) { return 1; } } return 0; } /* Order: 1 Larger imaginary part 2 Real eigenvalues before complex ones 3 Larger real part */ int igraph_i_eigen_matrix_lapack_cmp_li(void *extra, const void *a, const void *b) { igraph_i_eml_cmp_t *myextra = (igraph_i_eml_cmp_t *) extra; int *aa = (int*) a, *bb = (int*) b; igraph_real_t a_i = VECTOR(*myextra->imag)[*aa]; igraph_real_t b_i = VECTOR(*myextra->imag)[*bb]; if (MORE(a_i, b_i)) { return -1; } else if (LESS(a_i, b_i)) { return 1; } else { igraph_real_t a_r = VECTOR(*myextra->real)[*aa]; igraph_real_t b_r = VECTOR(*myextra->real)[*bb]; if (ZERO(a_i) && NONZERO(b_i)) { return -1; } if (NONZERO(a_i) && ZERO(b_i)) { return 1; } if (MORE(a_r, b_r)) { return -1; } if (LESS(a_r, b_r)) { return 1; } } return 0; } /* Order: 1 Smaller imaginary part 2 Complex eigenvalues before real ones 3 Smaller real part Order is opposite to LI */ int igraph_i_eigen_matrix_lapack_cmp_si(void *extra, const void *a, const void *b) { igraph_i_eml_cmp_t *myextra = (igraph_i_eml_cmp_t *) extra; int *aa = (int*) a, *bb = (int*) b; igraph_real_t a_i = VECTOR(*myextra->imag)[*aa]; igraph_real_t b_i = VECTOR(*myextra->imag)[*bb]; if (LESS(a_i, b_i)) { return -1; } else if (MORE(a_i, b_i)) { return 1; } else { igraph_real_t a_r = VECTOR(*myextra->real)[*aa]; igraph_real_t b_r = VECTOR(*myextra->real)[*bb]; if (NONZERO(a_i) && ZERO(b_i)) { return -1; } if (ZERO(a_i) && NONZERO(b_i)) { return 1; } if (LESS(a_r, b_r)) { return -1; } if (MORE(a_r, b_r)) { return 1; } } return 0; } #undef EPS #undef LESS #undef MORE #undef ZERO #undef NONZERO #define INITMAG() \ do { \ int i; \ IGRAPH_VECTOR_INIT_FINALLY(&mag, nev); \ hasmag=1; \ for (i=0; ipos) { case IGRAPH_EIGEN_LM: INITMAG(); cmpfunc = igraph_i_eigen_matrix_lapack_cmp_lm; howmany = which->howmany; break; case IGRAPH_EIGEN_ALL: INITMAG(); cmpfunc = igraph_i_eigen_matrix_lapack_cmp_sm; howmany = nev; break; case IGRAPH_EIGEN_SM: INITMAG(); cmpfunc = igraph_i_eigen_matrix_lapack_cmp_sm; howmany = which->howmany; break; case IGRAPH_EIGEN_LR: cmpfunc = igraph_i_eigen_matrix_lapack_cmp_lr; howmany = which->howmany; break; case IGRAPH_EIGEN_SR: cmpfunc = igraph_i_eigen_matrix_lapack_cmp_sr; howmany = which->howmany; break; case IGRAPH_EIGEN_SELECT: INITMAG(); cmpfunc = igraph_i_eigen_matrix_lapack_cmp_sm; start = which->il - 1; howmany = which->iu - which->il + 1; break; case IGRAPH_EIGEN_LI: cmpfunc = igraph_i_eigen_matrix_lapack_cmp_li; howmany = which->howmany; break; case IGRAPH_EIGEN_SI: cmpfunc = igraph_i_eigen_matrix_lapack_cmp_si; howmany = which->howmany; break; case IGRAPH_EIGEN_INTERVAL: case IGRAPH_EIGEN_BE: default: IGRAPH_ERROR("Unimplemented eigenvalue ordering", IGRAPH_UNIMPLEMENTED); break; } for (i = 0; i < nev; i++) { VECTOR(idx)[i] = i; } igraph_qsort_r(VECTOR(idx), (size_t) nev, sizeof(VECTOR(idx)[0]), extra, cmpfunc); if (hasmag) { igraph_vector_destroy(&mag); IGRAPH_FINALLY_CLEAN(1); } if (values) { IGRAPH_CHECK(igraph_vector_complex_resize(values, howmany)); for (i = 0; i < howmany; i++) { int x = VECTOR(idx)[start + i]; VECTOR(*values)[i] = igraph_complex(VECTOR(*real)[x], VECTOR(*imag)[x]); } } if (vectors) { int n = (int) igraph_matrix_nrow(compressed); IGRAPH_CHECK(igraph_matrix_complex_resize(vectors, n, howmany)); for (i = 0; i < howmany; i++) { int j, x = VECTOR(idx)[start + i]; if (VECTOR(*imag)[x] == 0) { /* real eigenvalue */ for (j = 0; j < n; j++) { MATRIX(*vectors, j, i) = igraph_complex(MATRIX(*compressed, j, x), 0.0); } } else { /* complex eigenvalue */ int neg = 1, co = 0; if (VECTOR(*imag)[x] < 0) { neg = -1; co = 1; } for (j = 0; j < n; j++) { MATRIX(*vectors, j, i) = igraph_complex(MATRIX(*compressed, j, x - co), neg * MATRIX(*compressed, j, x + 1 - co)); } } } } igraph_vector_int_destroy(&idx); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_i_eigen_matrix_lapack_common(const igraph_matrix_t *A, const igraph_eigen_which_t *which, igraph_vector_complex_t *values, igraph_matrix_complex_t *vectors) { igraph_vector_t valuesreal, valuesimag; igraph_matrix_t vectorsright, *myvectors = vectors ? &vectorsright : 0; int n = (int) igraph_matrix_nrow(A); int info = 1; IGRAPH_VECTOR_INIT_FINALLY(&valuesreal, n); IGRAPH_VECTOR_INIT_FINALLY(&valuesimag, n); if (vectors) { IGRAPH_MATRIX_INIT_FINALLY(&vectorsright, n, n); } IGRAPH_CHECK(igraph_lapack_dgeev(A, &valuesreal, &valuesimag, /*vectorsleft=*/ 0, myvectors, &info)); IGRAPH_CHECK(igraph_i_eigen_matrix_lapack_reorder(&valuesreal, &valuesimag, myvectors, which, values, vectors)); if (vectors) { igraph_matrix_destroy(&vectorsright); IGRAPH_FINALLY_CLEAN(1); } igraph_vector_destroy(&valuesimag); igraph_vector_destroy(&valuesreal); IGRAPH_FINALLY_CLEAN(2); return 0; } int igraph_i_eigen_matrix_lapack_lm(const igraph_matrix_t *A, const igraph_eigen_which_t *which, igraph_vector_complex_t *values, igraph_matrix_complex_t *vectors) { return igraph_i_eigen_matrix_lapack_common(A, which, values, vectors); } int igraph_i_eigen_matrix_lapack_sm(const igraph_matrix_t *A, const igraph_eigen_which_t *which, igraph_vector_complex_t *values, igraph_matrix_complex_t *vectors) { return igraph_i_eigen_matrix_lapack_common(A, which, values, vectors); } int igraph_i_eigen_matrix_lapack_lr(const igraph_matrix_t *A, const igraph_eigen_which_t *which, igraph_vector_complex_t *values, igraph_matrix_complex_t *vectors) { return igraph_i_eigen_matrix_lapack_common(A, which, values, vectors); } int igraph_i_eigen_matrix_lapack_sr(const igraph_matrix_t *A, const igraph_eigen_which_t *which, igraph_vector_complex_t *values, igraph_matrix_complex_t *vectors) { return igraph_i_eigen_matrix_lapack_common(A, which, values, vectors); } int igraph_i_eigen_matrix_lapack_li(const igraph_matrix_t *A, const igraph_eigen_which_t *which, igraph_vector_complex_t *values, igraph_matrix_complex_t *vectors) { return igraph_i_eigen_matrix_lapack_common(A, which, values, vectors); } int igraph_i_eigen_matrix_lapack_si(const igraph_matrix_t *A, const igraph_eigen_which_t *which, igraph_vector_complex_t *values, igraph_matrix_complex_t *vectors) { return igraph_i_eigen_matrix_lapack_common(A, which, values, vectors); } int igraph_i_eigen_matrix_lapack_select(const igraph_matrix_t *A, const igraph_eigen_which_t *which, igraph_vector_complex_t *values, igraph_matrix_complex_t *vectors) { return igraph_i_eigen_matrix_lapack_common(A, which, values, vectors); } int igraph_i_eigen_matrix_lapack_all(const igraph_matrix_t *A, const igraph_eigen_which_t *which, igraph_vector_complex_t *values, igraph_matrix_complex_t *vectors) { return igraph_i_eigen_matrix_lapack_common(A, which, values, vectors); } int igraph_i_eigen_matrix_lapack(const igraph_matrix_t *A, const igraph_sparsemat_t *sA, igraph_arpack_function_t *fun, int n, void *extra, const igraph_eigen_which_t *which, igraph_vector_complex_t *values, igraph_matrix_complex_t *vectors) { const igraph_matrix_t *myA = A; igraph_matrix_t mA; /* We need to create a dense square matrix first */ if (A) { n = (int) igraph_matrix_nrow(A); } else if (sA) { n = (int) igraph_sparsemat_nrow(sA); IGRAPH_CHECK(igraph_matrix_init(&mA, 0, 0)); IGRAPH_FINALLY(igraph_matrix_destroy, &mA); IGRAPH_CHECK(igraph_sparsemat_as_matrix(&mA, sA)); myA = &mA; } else if (fun) { IGRAPH_CHECK(igraph_i_eigen_arpackfun_to_mat(fun, n, extra, &mA)); IGRAPH_FINALLY(igraph_matrix_destroy, &mA); } switch (which->pos) { case IGRAPH_EIGEN_LM: IGRAPH_CHECK(igraph_i_eigen_matrix_lapack_lm(myA, which, values, vectors)); break; case IGRAPH_EIGEN_SM: IGRAPH_CHECK(igraph_i_eigen_matrix_lapack_sm(myA, which, values, vectors)); break; case IGRAPH_EIGEN_LR: IGRAPH_CHECK(igraph_i_eigen_matrix_lapack_lr(myA, which, values, vectors)); break; case IGRAPH_EIGEN_SR: IGRAPH_CHECK(igraph_i_eigen_matrix_lapack_sr(myA, which, values, vectors)); break; case IGRAPH_EIGEN_LI: IGRAPH_CHECK(igraph_i_eigen_matrix_lapack_li(myA, which, values, vectors)); break; case IGRAPH_EIGEN_SI: IGRAPH_CHECK(igraph_i_eigen_matrix_lapack_si(myA, which, values, vectors)); break; case IGRAPH_EIGEN_SELECT: IGRAPH_CHECK(igraph_i_eigen_matrix_lapack_select(myA, which, values, vectors)); break; case IGRAPH_EIGEN_ALL: IGRAPH_CHECK(igraph_i_eigen_matrix_lapack_all(myA, which, values, vectors)); break; default: /* This cannot happen */ break; } if (!A) { igraph_matrix_destroy(&mA); IGRAPH_FINALLY_CLEAN(1); } return 0; } int igraph_i_eigen_checks(const igraph_matrix_t *A, const igraph_sparsemat_t *sA, igraph_arpack_function_t *fun, int n) { if ( (A ? 1 : 0) + (sA ? 1 : 0) + (fun ? 1 : 0) != 1) { IGRAPH_ERROR("Exactly one of 'A', 'sA' and 'fun' must be given", IGRAPH_EINVAL); } if (A) { if (n != igraph_matrix_ncol(A) || n != igraph_matrix_nrow(A)) { IGRAPH_ERROR("Invalid matrix", IGRAPH_NONSQUARE); } } else if (sA) { if (n != igraph_sparsemat_ncol(sA) || n != igraph_sparsemat_nrow(sA)) { IGRAPH_ERROR("Invalid matrix", IGRAPH_NONSQUARE); } } return 0; } /** * \function igraph_eigen_matrix_symmetric * * \example examples/simple/igraph_eigen_matrix_symmetric.c */ int igraph_eigen_matrix_symmetric(const igraph_matrix_t *A, const igraph_sparsemat_t *sA, igraph_arpack_function_t *fun, int n, void *extra, igraph_eigen_algorithm_t algorithm, const igraph_eigen_which_t *which, igraph_arpack_options_t *options, igraph_arpack_storage_t *storage, igraph_vector_t *values, igraph_matrix_t *vectors) { IGRAPH_CHECK(igraph_i_eigen_checks(A, sA, fun, n)); if (which->pos != IGRAPH_EIGEN_LM && which->pos != IGRAPH_EIGEN_SM && which->pos != IGRAPH_EIGEN_LA && which->pos != IGRAPH_EIGEN_SA && which->pos != IGRAPH_EIGEN_BE && which->pos != IGRAPH_EIGEN_ALL && which->pos != IGRAPH_EIGEN_INTERVAL && which->pos != IGRAPH_EIGEN_SELECT) { IGRAPH_ERROR("Invalid 'pos' position in 'which'", IGRAPH_EINVAL); } switch (algorithm) { case IGRAPH_EIGEN_AUTO: if (which->howmany == n || n < 100) { IGRAPH_CHECK(igraph_i_eigen_matrix_symmetric_lapack(A, sA, fun, n, extra, which, values, vectors)); } else { IGRAPH_CHECK(igraph_i_eigen_matrix_symmetric_arpack(A, sA, fun, n, extra, which, options, storage, values, vectors)); } break; case IGRAPH_EIGEN_LAPACK: IGRAPH_CHECK(igraph_i_eigen_matrix_symmetric_lapack(A, sA, fun, n, extra, which, values, vectors)); break; case IGRAPH_EIGEN_ARPACK: IGRAPH_CHECK(igraph_i_eigen_matrix_symmetric_arpack(A, sA, fun, n, extra, which, options, storage, values, vectors)); break; default: IGRAPH_ERROR("Unknown 'algorithm'", IGRAPH_EINVAL); } return 0; } /** * \function igraph_eigen_matrix * */ int igraph_eigen_matrix(const igraph_matrix_t *A, const igraph_sparsemat_t *sA, igraph_arpack_function_t *fun, int n, void *extra, igraph_eigen_algorithm_t algorithm, const igraph_eigen_which_t *which, igraph_arpack_options_t *options, igraph_arpack_storage_t *storage, igraph_vector_complex_t *values, igraph_matrix_complex_t *vectors) { IGRAPH_CHECK(igraph_i_eigen_checks(A, sA, fun, n)); if (which->pos != IGRAPH_EIGEN_LM && which->pos != IGRAPH_EIGEN_SM && which->pos != IGRAPH_EIGEN_LR && which->pos != IGRAPH_EIGEN_SR && which->pos != IGRAPH_EIGEN_LI && which->pos != IGRAPH_EIGEN_SI && which->pos != IGRAPH_EIGEN_SELECT && which->pos != IGRAPH_EIGEN_ALL) { IGRAPH_ERROR("Invalid 'pos' position in 'which'", IGRAPH_EINVAL); } switch (algorithm) { case IGRAPH_EIGEN_AUTO: IGRAPH_ERROR("'AUTO' algorithm not implemented yet", IGRAPH_UNIMPLEMENTED); /* TODO */ break; case IGRAPH_EIGEN_LAPACK: IGRAPH_CHECK(igraph_i_eigen_matrix_lapack(A, sA, fun, n, extra, which, values, vectors)); /* TODO */ break; case IGRAPH_EIGEN_ARPACK: IGRAPH_ERROR("'ARPACK' algorithm not implemented yet", IGRAPH_UNIMPLEMENTED); /* TODO */ break; case IGRAPH_EIGEN_COMP_AUTO: IGRAPH_ERROR("'COMP_AUTO' algorithm not implemented yet", IGRAPH_UNIMPLEMENTED); /* TODO */ break; case IGRAPH_EIGEN_COMP_LAPACK: IGRAPH_ERROR("'COMP_LAPACK' algorithm not implemented yet", IGRAPH_UNIMPLEMENTED); /* TODO */ break; case IGRAPH_EIGEN_COMP_ARPACK: IGRAPH_ERROR("'COMP_ARPACK' algorithm not implemented yet", IGRAPH_UNIMPLEMENTED); /* TODO */ break; default: IGRAPH_ERROR("Unknown `algorithm'", IGRAPH_EINVAL); } return 0; } int igraph_i_eigen_adjacency_arpack_sym_cb(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_adjlist_t *adjlist = (igraph_adjlist_t *) extra; igraph_vector_int_t *neis; int i, j, nlen; for (i = 0; i < n; i++) { neis = igraph_adjlist_get(adjlist, i); nlen = igraph_vector_int_size(neis); to[i] = 0.0; for (j = 0; j < nlen; j++) { int nei = VECTOR(*neis)[j]; to[i] += from[nei]; } } return 0; } int igraph_i_eigen_adjacency_arpack(const igraph_t *graph, const igraph_eigen_which_t *which, igraph_arpack_options_t *options, igraph_arpack_storage_t* storage, igraph_vector_t *values, igraph_matrix_t *vectors, igraph_vector_complex_t *cmplxvalues, igraph_matrix_complex_t *cmplxvectors) { igraph_adjlist_t adjlist; void *extra = (void*) &adjlist; int n = igraph_vcount(graph); if (!options) { IGRAPH_ERROR("`options' must be given for ARPACK algorithm", IGRAPH_EINVAL); } if (igraph_is_directed(graph)) { IGRAPH_ERROR("ARPACK adjacency eigensolver not implemented for " "directed graphs", IGRAPH_UNIMPLEMENTED); } if (which->pos == IGRAPH_EIGEN_INTERVAL) { IGRAPH_ERROR("ARPACK adjacency eigensolver does not implement " "`INTERNAL' eigenvalues", IGRAPH_UNIMPLEMENTED); } if (which->pos == IGRAPH_EIGEN_SELECT) { IGRAPH_ERROR("ARPACK adjacency eigensolver does not implement " "`SELECT' eigenvalues", IGRAPH_UNIMPLEMENTED); } if (which->pos == IGRAPH_EIGEN_ALL) { IGRAPH_ERROR("ARPACK adjacency eigensolver does not implement " "`ALL' eigenvalues", IGRAPH_UNIMPLEMENTED); } switch (which->pos) { case IGRAPH_EIGEN_LM: options->which[0] = 'L'; options->which[1] = 'M'; options->nev = which->howmany; break; case IGRAPH_EIGEN_SM: options->which[0] = 'S'; options->which[1] = 'M'; options->nev = which->howmany; break; case IGRAPH_EIGEN_LA: options->which[0] = 'L'; options->which[1] = 'A'; options->nev = which->howmany; break; case IGRAPH_EIGEN_SA: options->which[0] = 'S'; options->which[1] = 'A'; options->nev = which->howmany; break; case IGRAPH_EIGEN_ALL: options->which[0] = 'L'; options->which[1] = 'M'; options->nev = n; break; case IGRAPH_EIGEN_BE: IGRAPH_ERROR("Eigenvectors from both ends with ARPACK", IGRAPH_UNIMPLEMENTED); /* TODO */ break; case IGRAPH_EIGEN_INTERVAL: IGRAPH_ERROR("Interval of eigenvectors with ARPACK", IGRAPH_UNIMPLEMENTED); /* TODO */ break; case IGRAPH_EIGEN_SELECT: IGRAPH_ERROR("Selected eigenvalues with ARPACK", IGRAPH_UNIMPLEMENTED); /* TODO */ break; default: /* This cannot happen */ break; } options->n = n; options->ncv = 2 * options->nev < n ? 2 * options->nev : n; IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist, IGRAPH_IN)); IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist); IGRAPH_CHECK(igraph_arpack_rssolve(igraph_i_eigen_adjacency_arpack_sym_cb, extra, options, storage, values, vectors)); igraph_adjlist_destroy(&adjlist); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_eigen_adjacency * */ int igraph_eigen_adjacency(const igraph_t *graph, igraph_eigen_algorithm_t algorithm, const igraph_eigen_which_t *which, igraph_arpack_options_t *options, igraph_arpack_storage_t *storage, igraph_vector_t *values, igraph_matrix_t *vectors, igraph_vector_complex_t *cmplxvalues, igraph_matrix_complex_t *cmplxvectors) { if (which->pos != IGRAPH_EIGEN_LM && which->pos != IGRAPH_EIGEN_SM && which->pos != IGRAPH_EIGEN_LA && which->pos != IGRAPH_EIGEN_SA && which->pos != IGRAPH_EIGEN_BE && which->pos != IGRAPH_EIGEN_SELECT && which->pos != IGRAPH_EIGEN_INTERVAL && which->pos != IGRAPH_EIGEN_ALL) { IGRAPH_ERROR("Invalid 'pos' position in 'which'", IGRAPH_EINVAL); } switch (algorithm) { case IGRAPH_EIGEN_AUTO: IGRAPH_ERROR("'AUTO' algorithm not implemented yet", IGRAPH_UNIMPLEMENTED); /* TODO */ break; case IGRAPH_EIGEN_LAPACK: IGRAPH_ERROR("'LAPACK' algorithm not implemented yet", IGRAPH_UNIMPLEMENTED); /* TODO */ break; case IGRAPH_EIGEN_ARPACK: IGRAPH_CHECK(igraph_i_eigen_adjacency_arpack(graph, which, options, storage, values, vectors, cmplxvalues, cmplxvectors)); break; case IGRAPH_EIGEN_COMP_AUTO: IGRAPH_ERROR("'COMP_AUTO' algorithm not implemented yet", IGRAPH_UNIMPLEMENTED); /* TODO */ break; case IGRAPH_EIGEN_COMP_LAPACK: IGRAPH_ERROR("'COMP_LAPACK' algorithm not implemented yet", IGRAPH_UNIMPLEMENTED); /* TODO */ break; case IGRAPH_EIGEN_COMP_ARPACK: IGRAPH_ERROR("'COMP_ARPACK' algorithm not implemented yet", IGRAPH_UNIMPLEMENTED); /* TODO */ break; default: IGRAPH_ERROR("Unknown `algorithm'", IGRAPH_EINVAL); } return 0; } /** * \function igraph_eigen_laplacian * */ int igraph_eigen_laplacian(const igraph_t *graph, igraph_eigen_algorithm_t algorithm, const igraph_eigen_which_t *which, igraph_arpack_options_t *options, igraph_arpack_storage_t *storage, igraph_vector_t *values, igraph_matrix_t *vectors, igraph_vector_complex_t *cmplxvalues, igraph_matrix_complex_t *cmplxvectors) { IGRAPH_ERROR("'igraph_eigen_laplacian'", IGRAPH_UNIMPLEMENTED); /* TODO */ return 0; } python-igraph-0.8.0/vendor/source/igraph/src/optimal_modularity.c0000644000076500000240000002131613614300625025463 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_interface.h" #include "igraph_structural.h" #include "igraph_community.h" #include "igraph_error.h" #include "igraph_glpk_support.h" #include "igraph_interrupt_internal.h" #include "igraph_centrality.h" #include "config.h" #ifdef HAVE_GLPK #include #endif /** * \function igraph_community_optimal_modularity * Calculate the community structure with the highest modularity value * * This function calculates the optimal community structure for a * graph, in terms of maximal modularity score. * * * The calculation is done by transforming the modularity maximization * into an integer programming problem, and then calling the GLPK * library to solve that. Please see Ulrik Brandes et al.: On * Modularity Clustering, IEEE Transactions on Knowledge and Data * Engineering 20(2):172-188, 2008. * * * Note that modularity optimization is an NP-complete problem, and * all known algorithms for it have exponential time complexity. This * means that you probably don't want to run this function on larger * graphs. Graphs with up to fifty vertices should be fine, graphs * with a couple of hundred vertices might be possible. * * \param graph The input graph. It is always treated as undirected. * \param modularity Pointer to a real number, or a null pointer. * If it is not a null pointer, then a optimal modularity value * is returned here. * \param membership Pointer to a vector, or a null pointer. If not a * null pointer, then the membership vector of the optimal * community structure is stored here. * \param weights Vector giving the weights of the edges. If it is * \c NULL then each edge is supposed to have the same weight. * \return Error code. * * \sa \ref igraph_modularity(), \ref igraph_community_fastgreedy() * for an algorithm that finds a local optimum in a greedy way. * * Time complexity: exponential in the number of vertices. * * \example examples/simple/igraph_community_optimal_modularity.c */ int igraph_community_optimal_modularity(const igraph_t *graph, igraph_real_t *modularity, igraph_vector_t *membership, const igraph_vector_t *weights) { #ifndef HAVE_GLPK IGRAPH_ERROR("GLPK is not available", IGRAPH_UNIMPLEMENTED); #else igraph_integer_t no_of_nodes = (igraph_integer_t) igraph_vcount(graph); igraph_integer_t no_of_edges = (igraph_integer_t) igraph_ecount(graph); igraph_bool_t directed = igraph_is_directed(graph); int no_of_variables = no_of_nodes * (no_of_nodes + 1) / 2; int i, j, k, l, st; int idx[] = { 0, 0, 0, 0 }; double coef[] = { 0.0, 1.0, 1.0, -2.0 }; igraph_real_t total_weight; igraph_vector_t indegree; igraph_vector_t outdegree; glp_prob *ip; glp_iocp parm; if (weights != 0) { if (igraph_vector_size(weights) != no_of_edges) { IGRAPH_ERROR("Invalid length of weight vector", IGRAPH_EINVAL); } if (igraph_vector_min(weights) < 0) { IGRAPH_ERROR("Negative weights are not allowed in weight vector", IGRAPH_EINVAL); } } if (weights) { total_weight = igraph_vector_sum(weights); } else { total_weight = no_of_edges; } if (!directed) { total_weight *= 2; } /* Special case */ if (no_of_edges == 0 || total_weight == 0) { if (modularity) { *modularity = IGRAPH_NAN; } if (membership) { IGRAPH_CHECK(igraph_vector_resize(membership, no_of_nodes)); igraph_vector_null(membership); } } IGRAPH_VECTOR_INIT_FINALLY(&indegree, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&outdegree, no_of_nodes); IGRAPH_CHECK(igraph_strength(graph, &indegree, igraph_vss_all(), IGRAPH_IN, IGRAPH_LOOPS, weights)); IGRAPH_CHECK(igraph_strength(graph, &outdegree, igraph_vss_all(), IGRAPH_OUT, IGRAPH_LOOPS, weights)); glp_term_out(GLP_OFF); ip = glp_create_prob(); IGRAPH_FINALLY(glp_delete_prob, ip); glp_set_obj_dir(ip, GLP_MAX); st = glp_add_cols(ip, no_of_variables); /* variables are binary */ for (i = 0; i < no_of_variables; i++) { glp_set_col_kind(ip, (st + i), GLP_BV); } #define IDX(a,b) ((b)*((b)+1)/2+(a)) /* reflexivity */ for (i = 0; i < no_of_nodes; i++) { glp_set_col_bnds(ip, (st + IDX(i, i)), GLP_FX, 1.0, 1.0); } /* transitivity */ for (i = 0; i < no_of_nodes; i++) { for (j = i + 1; j < no_of_nodes; j++) { IGRAPH_ALLOW_INTERRUPTION(); for (k = j + 1; k < no_of_nodes; k++) { int newrow = glp_add_rows(ip, 3); glp_set_row_bnds(ip, newrow, GLP_UP, 0.0, 1.0); idx[1] = (st + IDX(i, j)); idx[2] = (st + IDX(j, k)); idx[3] = (st + IDX(i, k)); glp_set_mat_row(ip, newrow, 3, idx, coef); glp_set_row_bnds(ip, newrow + 1, GLP_UP, 0.0, 1.0); idx[1] = st + IDX(i, j); idx[2] = st + IDX(i, k); idx[3] = st + IDX(j, k); glp_set_mat_row(ip, newrow + 1, 3, idx, coef); glp_set_row_bnds(ip, newrow + 2, GLP_UP, 0.0, 1.0); idx[1] = st + IDX(i, k); idx[2] = st + IDX(j, k); idx[3] = st + IDX(i, j); glp_set_mat_row(ip, newrow + 2, 3, idx, coef); } } } /* objective function */ { igraph_real_t c; /* first part: -strength(i)*strength(j)/total_weight for every node pair */ for (i = 0; i < no_of_nodes; i++) { for (j = i + 1; j < no_of_nodes; j++) { c = -VECTOR(indegree)[i] * VECTOR(outdegree)[j] / total_weight \ -VECTOR(outdegree)[i] * VECTOR(indegree)[j] / total_weight; glp_set_obj_coef(ip, st + IDX(i, j), c); } /* special case for (i,i) */ c = -VECTOR(indegree)[i] * VECTOR(outdegree)[i] / total_weight; glp_set_obj_coef(ip, st + IDX(i, i), c); } /* second part: add the weighted adjacency matrix to the coefficient matrix */ for (k = 0; k < no_of_edges; k++) { i = IGRAPH_FROM(graph, k); j = IGRAPH_TO(graph, k); if (i > j) { l = i; i = j; j = l; } c = weights ? VECTOR(*weights)[k] : 1.0; if (!directed || i == j) { c *= 2.0; } glp_set_obj_coef(ip, st + IDX(i, j), c + glp_get_obj_coef(ip, st + IDX(i, j))); } } /* solve it */ glp_init_iocp(&parm); parm.br_tech = GLP_BR_DTH; parm.bt_tech = GLP_BT_BLB; parm.presolve = GLP_ON; parm.binarize = GLP_ON; parm.cb_func = igraph_i_glpk_interruption_hook; IGRAPH_GLPK_CHECK(glp_intopt(ip, &parm), "Modularity optimization failed"); /* store the results */ if (modularity) { *modularity = glp_mip_obj_val(ip) / total_weight; } if (membership) { long int comm = 0; /* id of the last community that was found */ IGRAPH_CHECK(igraph_vector_resize(membership, no_of_nodes)); for (i = 0; i < no_of_nodes; i++) { IGRAPH_ALLOW_INTERRUPTION(); for (j = 0; j < i; j++) { int val = (int) glp_mip_col_val(ip, st + IDX(j, i)); if (val == 1) { VECTOR(*membership)[i] = VECTOR(*membership)[j]; break; } } if (j == i) { /* new community */ VECTOR(*membership)[i] = comm++; } } } #undef IDX igraph_vector_destroy(&indegree); igraph_vector_destroy(&outdegree); glp_delete_prob(ip); IGRAPH_FINALLY_CLEAN(3); return 0; #endif } python-igraph-0.8.0/vendor/source/igraph/src/dqueue.pmt0000644000076500000240000002260213614300625023412 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2003-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_memory.h" #include "igraph_error.h" #include "config.h" #include #include /* memcpy & co. */ #include /** * \section igraph_dqueue * * This is the classic data type of the double ended queue. Most of * the time it is used if a First-In-First-Out (FIFO) behavior is * needed. See the operations below. * * * * \example examples/simple/dqueue.c * */ /** * \ingroup dqueue * \function igraph_dqueue_init * \brief Initialize a double ended queue (deque). * * The queue will be always empty. * \param q Pointer to an uninitialized deque. * \param size How many elements to allocate memory for. * \return Error code. * * Time complexity: O(\p size). */ int FUNCTION(igraph_dqueue, init) (TYPE(igraph_dqueue)* q, long int size) { assert(q != 0); if (size <= 0 ) { size = 1; } q->stor_begin = igraph_Calloc(size, BASE); if (q->stor_begin == 0) { IGRAPH_ERROR("dqueue init failed", IGRAPH_ENOMEM); } q->stor_end = q->stor_begin + size; q->begin = q->stor_begin; q->end = NULL; return 0; } /** * \ingroup dqueue * \function igraph_dqueue_destroy * \brief Destroy a double ended queue. * * \param q The queue to destroy * * Time complexity: O(1). */ void FUNCTION(igraph_dqueue, destroy) (TYPE(igraph_dqueue)* q) { assert(q != 0); if (q->stor_begin != 0) { igraph_Free(q->stor_begin); q->stor_begin = 0; } } /** * \ingroup dqueue * \function igraph_dqueue_empty * \brief Decide whether the queue is empty. * * \param q The queue. * \return Boolean, \c TRUE if \p q contains at least one element, \c * FALSE otherwise. * * Time complexity: O(1). */ igraph_bool_t FUNCTION(igraph_dqueue, empty) (const TYPE(igraph_dqueue)* q) { assert(q != 0); assert(q->stor_begin != 0); return q->end == NULL; } /** * \ingroup dqueue * \function igraph_dqueue_clear * \brief Remove all elements from the queue. * * \param q The queue * * Time complexity: O(1). */ void FUNCTION(igraph_dqueue, clear) (TYPE(igraph_dqueue)* q) { assert(q != 0); assert(q->stor_begin != 0); q->begin = q->stor_begin; q->end = NULL; } /** * \ingroup dqueue * \function igraph_dqueue_full * \brief Check whether the queue is full. * * If a queue is full the next igraph_dqueue_push() operation will allocate * more memory. * \param q The queue. * \return \c TRUE if \p q is full, \c FALSE otherwise. * * Time complecity: O(1). */ igraph_bool_t FUNCTION(igraph_dqueue, full) (TYPE(igraph_dqueue)* q) { assert(q != 0); assert(q->stor_begin != 0); return q->begin == q->end; } /** * \ingroup dqueue * \function igraph_dqueue_size * \brief Number of elements in the queue. * * \param q The queue. * \return Integer, the number of elements currently in the queue. * * Time complexity: O(1). */ long int FUNCTION(igraph_dqueue, size) (const TYPE(igraph_dqueue)* q) { assert(q != 0); assert(q->stor_begin != 0); if (q->end == NULL) { return 0; } else if (q->begin < q->end) { return q->end - q->begin; } else { return q->stor_end - q->begin + q->end - q->stor_begin; } } /** * \ingroup dqueue * \function igraph_dqueue_head * \brief Head of the queue. * * The queue must contain at least one element. * \param q The queue. * \return The first element in the queue. * * Time complexity: O(1). */ BASE FUNCTION(igraph_dqueue, head) (const TYPE(igraph_dqueue)* q) { assert(q != 0); assert(q->stor_begin != 0); return *(q->begin); } /** * \ingroup dqueue * \function igraph_dqueue_back * \brief Tail of the queue. * * The queue must contain at least one element. * \param q The queue. * \return The last element in the queue. * * Time complexity: O(1). */ BASE FUNCTION(igraph_dqueue, back) (const TYPE(igraph_dqueue)* q) { assert(q != 0); assert(q->stor_begin != 0); if (q->end == q->stor_begin) { return *(q->stor_end - 1); } return *(q->end - 1); } /** * \ingroup dqueue * \function igraph_dqueue_pop * \brief Remove the head. * * Removes and returns the first element in the queue. The queue must * be non-empty. * \param q The input queue. * \return The first element in the queue. * * Time complexity: O(1). */ BASE FUNCTION(igraph_dqueue, pop) (TYPE(igraph_dqueue)* q) { BASE tmp = *(q->begin); assert(q != 0); assert(q->stor_begin != 0); (q->begin)++; if (q->begin == q->stor_end) { q->begin = q->stor_begin; } if (q->begin == q->end) { q->end = NULL; } return tmp; } /** * \ingroup dqueue * \function igraph_dqueue_pop_back * \brief Remove the tail * * Removes and returns the last element in the queue. The queue must * be non-empty. * \param q The queue. * \return The last element in the queue. * * Time complexity: O(1). */ BASE FUNCTION(igraph_dqueue, pop_back) (TYPE(igraph_dqueue)* q) { BASE tmp; assert(q != 0); assert(q->stor_begin != 0); if (q->end != q->stor_begin) { tmp = *((q->end) - 1); q->end = (q->end) - 1; } else { tmp = *((q->stor_end) - 1); q->end = (q->stor_end) - 1; } if (q->begin == q->end) { q->end = NULL; } return tmp; } /** * \ingroup dqueue * \function igraph_dqueue_push * \brief Appends an element. * * Append an element to the end of the queue. * \param q The queue. * \param elem The element to append. * \return Error code. * * Time complexity: O(1) if no memory allocation is needed, O(n), the * number of elements in the queue otherwise. But not that by * allocating always twice as much memory as the current size of the * queue we ensure that n push operations can always be done in at * most O(n) time. (Assuming memory allocation is at most linear.) */ int FUNCTION(igraph_dqueue, push) (TYPE(igraph_dqueue)* q, BASE elem) { assert(q != 0); assert(q->stor_begin != 0); if (q->begin != q->end) { /* not full */ if (q->end == NULL) { q->end = q->begin; } *(q->end) = elem; (q->end)++; if (q->end == q->stor_end) { q->end = q->stor_begin; } } else { /* full, allocate more storage */ BASE *bigger = NULL, *old = q->stor_begin; bigger = igraph_Calloc( 2 * (q->stor_end - q->stor_begin) + 1, BASE ); if (bigger == 0) { IGRAPH_ERROR("dqueue push failed", IGRAPH_ENOMEM); } if (q->stor_end - q->begin) { memcpy(bigger, q->begin, (size_t)(q->stor_end - q->begin) * sizeof(BASE)); } if (q->end - q->stor_begin > 0) { memcpy(bigger + (q->stor_end - q->begin), q->stor_begin, (size_t)(q->end - q->stor_begin) * sizeof(BASE)); } q->end = bigger + (q->stor_end - q->stor_begin); q->stor_end = bigger + 2 * (q->stor_end - q->stor_begin) + 1; q->stor_begin = bigger; q->begin = bigger; *(q->end) = elem; (q->end)++; if (q->end == q->stor_end) { q->end = q->stor_begin; } igraph_Free(old); } return 0; } #if defined (OUT_FORMAT) #ifndef USING_R int FUNCTION(igraph_dqueue, print)(const TYPE(igraph_dqueue)* q) { return FUNCTION(igraph_dqueue, fprint)(q, stdout); } #endif int FUNCTION(igraph_dqueue, fprint)(const TYPE(igraph_dqueue)* q, FILE *file) { if (q->end != NULL) { /* There is one element at least */ BASE *p = q->begin; fprintf(file, OUT_FORMAT, *p); p++; if (q->end > q->begin) { /* Q is in one piece */ while (p != q->end) { fprintf(file, " " OUT_FORMAT, *p); p++; } } else { /* Q is in two pieces */ while (p != q->stor_end) { fprintf(file, " " OUT_FORMAT, *p); p++; } p = q->stor_begin; while (p != q->end) { fprintf(file, " " OUT_FORMAT, *p); p++; } } } fprintf(file, "\n"); return 0; } #endif BASE FUNCTION(igraph_dqueue, e)(const TYPE(igraph_dqueue) *q, long int idx) { if ((q->begin + idx < q->end) || (q->begin >= q->end && q->begin + idx < q->stor_end)) { return q->begin[idx]; } else if (q->begin >= q->end && q->stor_begin + idx < q->end) { idx = idx - (q->stor_end - q->begin); return q->stor_begin[idx]; } else { return 0; /* Error */ } } python-igraph-0.8.0/vendor/source/igraph/src/NetRoutines.h0000644000076500000240000000473413614300625024036 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ /* The original version of this file was written by Jörg Reichardt The original copyright notice follows here */ /*************************************************************************** NetRoutines.h - description ------------------- begin : Tue Oct 28 2003 copyright : (C) 2003 by Joerg Reichardt email : reichardt@mitte ***************************************************************************/ /*************************************************************************** * * * This program is free software; you can redistribute it and/or modify * * it under the terms of the GNU General Public License as published by * * the Free Software Foundation; either version 2 of the License, or * * (at your option) any later version. * * * ***************************************************************************/ #ifndef NETROUTINES_H #define NETROUTINES_H #include "NetDataTypes.h" #include "igraph_types.h" #include "igraph_datatype.h" int igraph_i_read_network(const igraph_t *graph, const igraph_vector_t *weights, network *net, igraph_bool_t use_weights, unsigned int states); void reduce_cliques(DLList*>*, FILE *file); void reduce_cliques2(network*, bool, long ); void clear_all_markers(network *net); #endif python-igraph-0.8.0/vendor/source/igraph/src/glpk_support.c0000644000076500000240000000556613614300625024307 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "config.h" #ifdef HAVE_GLPK #include "igraph_types.h" #include "igraph_error.h" #include "igraph_interrupt_internal.h" #include #include #include void igraph_i_glpk_interruption_hook(glp_tree *tree, void *info) { IGRAPH_UNUSED(info); /* This is a special version of IGRAPH_ALLOW_INTERRUPTION(). Calling glp_ios_terminate() from glp_intopt()'s callback function signals to GLPK that it should terminate the optimization and return with the code GLP_ESTOP. */ if (igraph_i_interruption_handler) { if (igraph_allow_interruption(NULL) != IGRAPH_SUCCESS) { glp_ios_terminate(tree); } } } int igraph_i_glpk_check(int retval, const char* message) { char* code = "none"; char message_and_code[4096]; if (retval == IGRAPH_SUCCESS) { return IGRAPH_SUCCESS; } /* handle errors */ #define HANDLE_CODE(c) case c: code = #c; retval = IGRAPH_##c; break; #define HANDLE_CODE2(c) case c: code = #c; retval = IGRAPH_FAILURE; break; #define HANDLE_CODE3(c) case c: code = #c; retval = IGRAPH_INTERRUPTED; break; switch (retval) { HANDLE_CODE(GLP_EBOUND); HANDLE_CODE(GLP_EROOT); HANDLE_CODE(GLP_ENOPFS); HANDLE_CODE(GLP_ENODFS); HANDLE_CODE(GLP_EFAIL); HANDLE_CODE(GLP_EMIPGAP); HANDLE_CODE(GLP_ETMLIM); HANDLE_CODE3(GLP_ESTOP); HANDLE_CODE2(GLP_EBADB); HANDLE_CODE2(GLP_ESING); HANDLE_CODE2(GLP_ECOND); HANDLE_CODE2(GLP_EOBJLL); HANDLE_CODE2(GLP_EOBJUL); HANDLE_CODE2(GLP_EITLIM); default: IGRAPH_ERROR("unknown GLPK error", IGRAPH_FAILURE); } #undef HANDLE_CODE #undef HANDLE_CODE2 #undef HANDLE_CODE3 sprintf(message_and_code, "%s (%s)", message, code); IGRAPH_ERROR(message_and_code, retval); } #endif #ifdef USING_R int igraph_glpk_dummy() { return 'b' + 'a' + 's' + 's' + 'z' + 'a' + 't' + 'o' + 'k' + 'm' + 'e' + 'g'; } #endif python-igraph-0.8.0/vendor/source/igraph/src/heap.c0000644000076500000240000007320713614300625022470 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2003-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_types.h" #include "igraph_types_internal.h" #include "igraph_memory.h" #include "igraph_random.h" #include "igraph_error.h" #include "config.h" #include "igraph_math.h" #include #include /* memcpy & co. */ #include #define PARENT(x) (((x)+1)/2-1) #define LEFTCHILD(x) (((x)+1)*2-1) #define RIGHTCHILD(x) (((x)+1)*2) /** * \ingroup indheap * \brief Initializes an indexed heap (constructor). * * @return Error code: * - IGRAPH_ENOMEM: out of memory */ int igraph_indheap_init (igraph_indheap_t* h, long int alloc_size) { if (alloc_size <= 0 ) { alloc_size = 1; } h->stor_begin = igraph_Calloc(alloc_size, igraph_real_t); if (h->stor_begin == 0) { h->index_begin = 0; IGRAPH_ERROR("indheap init failed", IGRAPH_ENOMEM); } h->index_begin = igraph_Calloc(alloc_size, long int); if (h->index_begin == 0) { igraph_Free(h->stor_begin); h->stor_begin = 0; IGRAPH_ERROR("indheap init failed", IGRAPH_ENOMEM); } h->stor_end = h->stor_begin + alloc_size; h->end = h->stor_begin; h->destroy = 1; return 0; } int igraph_indheap_clear(igraph_indheap_t *h) { h->end = h->stor_begin; return 0; } /** * \ingroup indheap * \brief Initializes and build an indexed heap from a C array (constructor). * * @return Error code: * - IGRAPH_ENOMEM: out of memory */ int igraph_indheap_init_array (igraph_indheap_t *h, igraph_real_t* data, long int len) { long int i; h->stor_begin = igraph_Calloc(len, igraph_real_t); if (h->stor_begin == 0) { h->index_begin = 0; IGRAPH_ERROR("indheap init from array failed", IGRAPH_ENOMEM); } h->index_begin = igraph_Calloc(len, long int); if (h->index_begin == 0) { igraph_Free(h->stor_begin); h->stor_begin = 0; IGRAPH_ERROR("indheap init from array failed", IGRAPH_ENOMEM); } h->stor_end = h->stor_begin + len; h->end = h->stor_end; h->destroy = 1; memcpy(h->stor_begin, data, (size_t) len * sizeof(igraph_real_t)); for (i = 0; i < len; i++) { h->index_begin[i] = i + 1; } igraph_indheap_i_build (h, 0); return 0; } /** * \ingroup indheap * \brief Destroys an initialized indexed heap. */ void igraph_indheap_destroy (igraph_indheap_t* h) { assert(h != 0); if (h->destroy) { if (h->stor_begin != 0) { igraph_Free(h->stor_begin); h->stor_begin = 0; } if (h->index_begin != 0) { igraph_Free(h->index_begin); h->index_begin = 0; } } } /** * \ingroup indheap * \brief Checks whether a heap is empty. */ igraph_bool_t igraph_indheap_empty (igraph_indheap_t* h) { assert(h != 0); assert(h->stor_begin != 0); return h->stor_begin == h->end; } /** * \ingroup indheap * \brief Adds an element to an indexed heap. */ int igraph_indheap_push (igraph_indheap_t* h, igraph_real_t elem) { assert(h != 0); assert(h->stor_begin != 0); /* full, allocate more storage */ if (h->stor_end == h->end) { long int new_size = igraph_indheap_size(h) * 2; if (new_size == 0) { new_size = 1; } IGRAPH_CHECK(igraph_indheap_reserve(h, new_size)); } *(h->end) = elem; h->end += 1; *(h->index_begin + igraph_indheap_size(h) - 1) = igraph_indheap_size(h) - 1; /* maintain indheap */ igraph_indheap_i_shift_up(h, igraph_indheap_size(h) - 1); return 0; } /** * \ingroup indheap * \brief Adds an element to an indexed heap with a given index. */ int igraph_indheap_push_with_index(igraph_indheap_t* h, long int idx, igraph_real_t elem) { assert(h != 0); assert(h->stor_begin != 0); /* full, allocate more storage */ if (h->stor_end == h->end) { long int new_size = igraph_indheap_size(h) * 2; if (new_size == 0) { new_size = 1; } IGRAPH_CHECK(igraph_indheap_reserve(h, new_size)); } *(h->end) = elem; h->end += 1; *(h->index_begin + igraph_indheap_size(h) - 1) = idx; /* maintain indheap */ igraph_indheap_i_shift_up(h, igraph_indheap_size(h) - 1); return 0; } /** * \ingroup indheap * \brief Modifies an element in an indexed heap. */ int igraph_indheap_modify(igraph_indheap_t* h, long int idx, igraph_real_t elem) { long int i, n; assert(h != 0); assert(h->stor_begin != 0); n = igraph_indheap_size(h); for (i = 0; i < n; i++) if (h->index_begin[i] == idx) { h->stor_begin[i] = elem; break; } if (i == n) { return 0; } /* maintain indheap */ igraph_indheap_i_build(h, 0); return 0; } /** * \ingroup indheap * \brief Returns the largest element in an indexed heap. */ igraph_real_t igraph_indheap_max (igraph_indheap_t* h) { assert(h != NULL); assert(h->stor_begin != NULL); assert(h->stor_begin != h->end); return h->stor_begin[0]; } /** * \ingroup indheap * \brief Removes the largest element from an indexed heap. */ igraph_real_t igraph_indheap_delete_max(igraph_indheap_t* h) { igraph_real_t tmp; assert(h != NULL); assert(h->stor_begin != NULL); tmp = h->stor_begin[0]; igraph_indheap_i_switch(h, 0, igraph_indheap_size(h) - 1); h->end -= 1; igraph_indheap_i_sink(h, 0); return tmp; } /** * \ingroup indheap * \brief Gives the number of elements in an indexed heap. */ long int igraph_indheap_size (igraph_indheap_t* h) { assert(h != 0); assert(h->stor_begin != 0); return h->end - h->stor_begin; } /** * \ingroup indheap * \brief Reserves more memory for an indexed heap. * * @return Error code: * - IGRAPH_ENOMEM: out of memory */ int igraph_indheap_reserve (igraph_indheap_t* h, long int size) { long int actual_size = igraph_indheap_size(h); igraph_real_t *tmp1; long int *tmp2; assert(h != 0); assert(h->stor_begin != 0); if (size <= actual_size) { return 0; } tmp1 = igraph_Calloc(size, igraph_real_t); if (tmp1 == 0) { IGRAPH_ERROR("indheap reserve failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, tmp1); /* TODO: hack */ tmp2 = igraph_Calloc(size, long int); if (tmp2 == 0) { IGRAPH_ERROR("indheap reserve failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, tmp2); memcpy(tmp1, h->stor_begin, (size_t) actual_size * sizeof(igraph_real_t)); memcpy(tmp2, h->index_begin, (size_t) actual_size * sizeof(long int)); igraph_Free(h->stor_begin); igraph_Free(h->index_begin); h->stor_begin = tmp1; h->index_begin = tmp2; h->stor_end = h->stor_begin + size; h->end = h->stor_begin + actual_size; IGRAPH_FINALLY_CLEAN(2); return 0; } /** * \ingroup indheap * \brief Returns the index of the largest element in an indexed heap. */ long int igraph_indheap_max_index(igraph_indheap_t *h) { assert(h != 0); assert(h->stor_begin != 0); return h->index_begin[0]; } /** * \ingroup indheap * \brief Builds an indexed heap, this function should not be called * directly. */ void igraph_indheap_i_build(igraph_indheap_t* h, long int head) { long int size = igraph_indheap_size(h); if (RIGHTCHILD(head) < size) { /* both subtrees */ igraph_indheap_i_build(h, LEFTCHILD(head) ); igraph_indheap_i_build(h, RIGHTCHILD(head)); igraph_indheap_i_sink(h, head); } else if (LEFTCHILD(head) < size) { /* only left */ igraph_indheap_i_build(h, LEFTCHILD(head)); igraph_indheap_i_sink(h, head); } else { /* none */ } } /** * \ingroup indheap * \brief Moves an element up in the heap, don't call this function * directly. */ void igraph_indheap_i_shift_up(igraph_indheap_t *h, long int elem) { if (elem == 0 || h->stor_begin[elem] < h->stor_begin[PARENT(elem)]) { /* at the top */ } else { igraph_indheap_i_switch(h, elem, PARENT(elem)); igraph_indheap_i_shift_up(h, PARENT(elem)); } } /** * \ingroup indheap * \brief Moves an element down in the heap, don't call this function * directly. */ void igraph_indheap_i_sink(igraph_indheap_t* h, long int head) { long int size = igraph_indheap_size(h); if (LEFTCHILD(head) >= size) { /* no subtrees */ } else if (RIGHTCHILD(head) == size || h->stor_begin[LEFTCHILD(head)] >= h->stor_begin[RIGHTCHILD(head)]) { /* sink to the left if needed */ if (h->stor_begin[head] < h->stor_begin[LEFTCHILD(head)]) { igraph_indheap_i_switch(h, head, LEFTCHILD(head)); igraph_indheap_i_sink(h, LEFTCHILD(head)); } } else { /* sink to the right */ if (h->stor_begin[head] < h->stor_begin[RIGHTCHILD(head)]) { igraph_indheap_i_switch(h, head, RIGHTCHILD(head)); igraph_indheap_i_sink(h, RIGHTCHILD(head)); } } } /** * \ingroup indheap * \brief Switches two elements in a heap, don't call this function * directly. */ void igraph_indheap_i_switch(igraph_indheap_t* h, long int e1, long int e2) { if (e1 != e2) { igraph_real_t tmp = h->stor_begin[e1]; h->stor_begin[e1] = h->stor_begin[e2]; h->stor_begin[e2] = tmp; tmp = h->index_begin[e1]; h->index_begin[e1] = h->index_begin[e2]; h->index_begin[e2] = (long int) tmp; } } /** * \ingroup doubleindheap * \brief Initializes an empty doubly indexed heap object (constructor). * * @return Error code: * - IGRAPH_ENOMEM: out of memory */ int igraph_d_indheap_init (igraph_d_indheap_t* h, long int alloc_size) { if (alloc_size <= 0 ) { alloc_size = 1; } h->stor_begin = igraph_Calloc(alloc_size, igraph_real_t); if (h->stor_begin == 0) { h->index_begin = 0; h->index2_begin = 0; IGRAPH_ERROR("d_indheap init failed", IGRAPH_ENOMEM); } h->stor_end = h->stor_begin + alloc_size; h->end = h->stor_begin; h->destroy = 1; h->index_begin = igraph_Calloc(alloc_size, long int); if (h->index_begin == 0) { igraph_Free(h->stor_begin); h->stor_begin = 0; h->index2_begin = 0; IGRAPH_ERROR("d_indheap init failed", IGRAPH_ENOMEM); } h->index2_begin = igraph_Calloc(alloc_size, long int); if (h->index2_begin == 0) { igraph_Free(h->stor_begin); igraph_Free(h->index_begin); h->stor_begin = 0; h->index_begin = 0; IGRAPH_ERROR("d_indheap init failed", IGRAPH_ENOMEM); } return 0; } /** * \ingroup doubleindheap * \brief Destroys an initialized doubly indexed heap object. */ void igraph_d_indheap_destroy (igraph_d_indheap_t* h) { assert(h != 0); if (h->destroy) { if (h->stor_begin != 0) { igraph_Free(h->stor_begin); h->stor_begin = 0; } if (h->index_begin != 0) { igraph_Free(h->index_begin); h->index_begin = 0; } if (h->index2_begin != 0) { igraph_Free(h->index2_begin); h->index2_begin = 0; } } } /** * \ingroup doubleindheap * \brief Decides whether a heap is empty. */ igraph_bool_t igraph_d_indheap_empty (igraph_d_indheap_t* h) { assert(h != 0); assert(h->stor_begin != 0); return h->stor_begin == h->end; } /** * \ingroup doubleindheap * \brief Adds an element to the heap. */ int igraph_d_indheap_push (igraph_d_indheap_t* h, igraph_real_t elem, long int idx, long int idx2) { assert(h != 0); assert(h->stor_begin != 0); /* full, allocate more storage */ if (h->stor_end == h->end) { long int new_size = igraph_d_indheap_size(h) * 2; if (new_size == 0) { new_size = 1; } IGRAPH_CHECK(igraph_d_indheap_reserve(h, new_size)); } *(h->end) = elem; h->end += 1; *(h->index_begin + igraph_d_indheap_size(h) - 1) = idx ; *(h->index2_begin + igraph_d_indheap_size(h) - 1) = idx2 ; /* maintain d_indheap */ igraph_d_indheap_i_shift_up(h, igraph_d_indheap_size(h) - 1); return 0; } /** * \ingroup doubleindheap * \brief Returns the largest element in the heap. */ igraph_real_t igraph_d_indheap_max (igraph_d_indheap_t* h) { assert(h != NULL); assert(h->stor_begin != NULL); assert(h->stor_begin != h->end); return h->stor_begin[0]; } /** * \ingroup doubleindheap * \brief Removes the largest element from the heap. */ igraph_real_t igraph_d_indheap_delete_max(igraph_d_indheap_t* h) { igraph_real_t tmp; assert(h != NULL); assert(h->stor_begin != NULL); tmp = h->stor_begin[0]; igraph_d_indheap_i_switch(h, 0, igraph_d_indheap_size(h) - 1); h->end -= 1; igraph_d_indheap_i_sink(h, 0); return tmp; } /** * \ingroup doubleindheap * \brief Gives the number of elements in the heap. */ long int igraph_d_indheap_size (igraph_d_indheap_t* h) { assert(h != 0); assert(h->stor_begin != 0); return h->end - h->stor_begin; } /** * \ingroup doubleindheap * \brief Allocates memory for a heap. * * @return Error code: * - IGRAPH_ENOMEM: out of memory */ int igraph_d_indheap_reserve (igraph_d_indheap_t* h, long int size) { long int actual_size = igraph_d_indheap_size(h); igraph_real_t *tmp1; long int *tmp2, *tmp3; assert(h != 0); assert(h->stor_begin != 0); if (size <= actual_size) { return 0; } tmp1 = igraph_Calloc(size, igraph_real_t); if (tmp1 == 0) { IGRAPH_ERROR("d_indheap reserve failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, tmp1); /* TODO: hack */ tmp2 = igraph_Calloc(size, long int); if (tmp2 == 0) { IGRAPH_ERROR("d_indheap reserve failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, tmp2); /* TODO: hack */ tmp3 = igraph_Calloc(size, long int); if (tmp3 == 0) { IGRAPH_ERROR("d_indheap reserve failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, tmp3); /* TODO: hack */ memcpy(tmp1, h->stor_begin, (size_t) actual_size * sizeof(igraph_real_t)); memcpy(tmp2, h->index_begin, (size_t) actual_size * sizeof(long int)); memcpy(tmp3, h->index2_begin, (size_t) actual_size * sizeof(long int)); igraph_Free(h->stor_begin); igraph_Free(h->index_begin); igraph_Free(h->index2_begin); h->stor_begin = tmp1; h->stor_end = h->stor_begin + size; h->end = h->stor_begin + actual_size; h->index_begin = tmp2; h->index2_begin = tmp3; IGRAPH_FINALLY_CLEAN(3); return 0; } /** * \ingroup doubleindheap * \brief Gives the indices of the maximal element in the heap. */ void igraph_d_indheap_max_index(igraph_d_indheap_t *h, long int *idx, long int *idx2) { assert(h != 0); assert(h->stor_begin != 0); (*idx) = h->index_begin[0]; (*idx2) = h->index2_begin[0]; } /** * \ingroup doubleindheap * \brief Builds the heap, don't call it directly. */ void igraph_d_indheap_i_build(igraph_d_indheap_t* h, long int head) { long int size = igraph_d_indheap_size(h); if (RIGHTCHILD(head) < size) { /* both subtrees */ igraph_d_indheap_i_build(h, LEFTCHILD(head) ); igraph_d_indheap_i_build(h, RIGHTCHILD(head)); igraph_d_indheap_i_sink(h, head); } else if (LEFTCHILD(head) < size) { /* only left */ igraph_d_indheap_i_build(h, LEFTCHILD(head)); igraph_d_indheap_i_sink(h, head); } else { /* none */ } } /** * \ingroup doubleindheap * \brief Moves an element up in the heap, don't call it directly. */ void igraph_d_indheap_i_shift_up(igraph_d_indheap_t *h, long int elem) { if (elem == 0 || h->stor_begin[elem] < h->stor_begin[PARENT(elem)]) { /* at the top */ } else { igraph_d_indheap_i_switch(h, elem, PARENT(elem)); igraph_d_indheap_i_shift_up(h, PARENT(elem)); } } /** * \ingroup doubleindheap * \brief Moves an element down in the heap, don't call it directly. */ void igraph_d_indheap_i_sink(igraph_d_indheap_t* h, long int head) { long int size = igraph_d_indheap_size(h); if (LEFTCHILD(head) >= size) { /* no subtrees */ } else if (RIGHTCHILD(head) == size || h->stor_begin[LEFTCHILD(head)] >= h->stor_begin[RIGHTCHILD(head)]) { /* sink to the left if needed */ if (h->stor_begin[head] < h->stor_begin[LEFTCHILD(head)]) { igraph_d_indheap_i_switch(h, head, LEFTCHILD(head)); igraph_d_indheap_i_sink(h, LEFTCHILD(head)); } } else { /* sink to the right */ if (h->stor_begin[head] < h->stor_begin[RIGHTCHILD(head)]) { igraph_d_indheap_i_switch(h, head, RIGHTCHILD(head)); igraph_d_indheap_i_sink(h, RIGHTCHILD(head)); } } } /** * \ingroup doubleindheap * \brief Switches two elements in the heap, don't call it directly. */ void igraph_d_indheap_i_switch(igraph_d_indheap_t* h, long int e1, long int e2) { if (e1 != e2) { long int tmpi; igraph_real_t tmp = h->stor_begin[e1]; h->stor_begin[e1] = h->stor_begin[e2]; h->stor_begin[e2] = tmp; tmpi = h->index_begin[e1]; h->index_begin[e1] = h->index_begin[e2]; h->index_begin[e2] = tmpi; tmpi = h->index2_begin[e1]; h->index2_begin[e1] = h->index2_begin[e2]; h->index2_begin[e2] = tmpi; } } /*************************************************/ #undef PARENT #undef LEFTCHILD #undef RIGHTCHILD #define PARENT(x) ((x)/2) #define LEFTCHILD(x) ((x)*2+1) #define RIGHTCHILD(x) ((x)*2) #define INACTIVE IGRAPH_INFINITY #define UNDEFINED 0.0 #define INDEXINC 1 void igraph_i_cutheap_switch(igraph_i_cutheap_t *ch, long int hidx1, long int hidx2) { if (hidx1 != hidx2) { long int idx1 = (long int) VECTOR(ch->index)[hidx1]; long int idx2 = (long int) VECTOR(ch->index)[hidx2]; igraph_real_t tmp = VECTOR(ch->heap)[hidx1]; VECTOR(ch->heap)[hidx1] = VECTOR(ch->heap)[hidx2]; VECTOR(ch->heap)[hidx2] = tmp; VECTOR(ch->index)[hidx1] = idx2; VECTOR(ch->index)[hidx2] = idx1; VECTOR(ch->hptr)[idx1] = hidx2 + INDEXINC; VECTOR(ch->hptr)[idx2] = hidx1 + INDEXINC; } } void igraph_i_cutheap_sink(igraph_i_cutheap_t *ch, long int hidx) { long int size = igraph_vector_size(&ch->heap); if (LEFTCHILD(hidx) >= size) { /* leaf node */ } else if (RIGHTCHILD(hidx) == size || VECTOR(ch->heap)[LEFTCHILD(hidx)] >= VECTOR(ch->heap)[RIGHTCHILD(hidx)]) { /* sink to the left if needed */ if (VECTOR(ch->heap)[hidx] < VECTOR(ch->heap)[LEFTCHILD(hidx)]) { igraph_i_cutheap_switch(ch, hidx, LEFTCHILD(hidx)); igraph_i_cutheap_sink(ch, LEFTCHILD(hidx)); } } else { /* sink to the right */ if (VECTOR(ch->heap)[hidx] < VECTOR(ch->heap)[RIGHTCHILD(hidx)]) { igraph_i_cutheap_switch(ch, hidx, RIGHTCHILD(hidx)); igraph_i_cutheap_sink(ch, RIGHTCHILD(hidx)); } } } void igraph_i_cutheap_shift_up(igraph_i_cutheap_t *ch, long int hidx) { if (hidx == 0 || VECTOR(ch->heap)[hidx] < VECTOR(ch->heap)[PARENT(hidx)]) { /* at the top */ } else { igraph_i_cutheap_switch(ch, hidx, PARENT(hidx)); igraph_i_cutheap_shift_up(ch, PARENT(hidx)); } } int igraph_i_cutheap_init(igraph_i_cutheap_t *ch, igraph_integer_t nodes) { ch->dnodes = nodes; IGRAPH_VECTOR_INIT_FINALLY(&ch->heap, nodes); /* all zero */ IGRAPH_CHECK(igraph_vector_init_seq(&ch->index, 0, nodes - 1)); IGRAPH_FINALLY(igraph_vector_destroy, &ch->index); IGRAPH_CHECK(igraph_vector_init_seq(&ch->hptr, INDEXINC, nodes + INDEXINC - 1)); IGRAPH_FINALLY_CLEAN(2); return 0; } void igraph_i_cutheap_destroy(igraph_i_cutheap_t *ch) { igraph_vector_destroy(&ch->hptr); igraph_vector_destroy(&ch->index); igraph_vector_destroy(&ch->heap); } igraph_bool_t igraph_i_cutheap_empty(igraph_i_cutheap_t *ch) { return igraph_vector_empty(&ch->heap); } /* Number of active vertices */ igraph_integer_t igraph_i_cutheap_active_size(igraph_i_cutheap_t *ch) { return (igraph_integer_t) igraph_vector_size(&ch->heap); } /* Number of all (defined) vertices */ igraph_integer_t igraph_i_cutheap_size(igraph_i_cutheap_t *ch) { return (igraph_integer_t) (ch->dnodes); } igraph_real_t igraph_i_cutheap_maxvalue(igraph_i_cutheap_t *ch) { return VECTOR(ch->heap)[0]; } igraph_integer_t igraph_i_cutheap_popmax(igraph_i_cutheap_t *ch) { long int size = igraph_vector_size(&ch->heap); igraph_integer_t maxindex = (igraph_integer_t) VECTOR(ch->index)[0]; /* put the last element to the top */ igraph_i_cutheap_switch(ch, 0, size - 1); /* remove the last element */ VECTOR(ch->hptr)[(long int) igraph_vector_tail(&ch->index)] = INACTIVE; igraph_vector_pop_back(&ch->heap); igraph_vector_pop_back(&ch->index); igraph_i_cutheap_sink(ch, 0); return maxindex; } /* Update the value of an active vertex, if not active it will be ignored */ int igraph_i_cutheap_update(igraph_i_cutheap_t *ch, igraph_integer_t index, igraph_real_t add) { igraph_real_t hidx = VECTOR(ch->hptr)[(long int)index]; if (hidx != INACTIVE && hidx != UNDEFINED) { long int hidx2 = (long int) (hidx - INDEXINC); /* printf("updating vertex %li, heap index %li\n", (long int) index, hidx2); */ VECTOR(ch->heap)[hidx2] += add; igraph_i_cutheap_sink(ch, hidx2); igraph_i_cutheap_shift_up(ch, hidx2); } return 0; } /* Reset the value of all vertices to zero and make them active */ int igraph_i_cutheap_reset_undefine(igraph_i_cutheap_t *ch, long int vertex) { long int i, j, n = igraph_vector_size(&ch->hptr); /* undefine */ VECTOR(ch->hptr)[vertex] = UNDEFINED; ch->dnodes -= 1; IGRAPH_CHECK(igraph_vector_resize(&ch->heap, ch->dnodes)); igraph_vector_null(&ch->heap); IGRAPH_CHECK(igraph_vector_resize(&ch->index, ch->dnodes)); j = 0; for (i = 0; i < n; i++) { if (VECTOR(ch->hptr)[i] != UNDEFINED) { VECTOR(ch->index)[j] = i; VECTOR(ch->hptr)[i] = j + INDEXINC; j++; } } return 0; } /* -------------------------------------------------- */ /* Two-way indexed heap */ /* -------------------------------------------------- */ #undef PARENT #undef LEFTCHILD #undef RIGHTCHILD #define PARENT(x) (((x)+1)/2-1) #define LEFTCHILD(x) (((x)+1)*2-1) #define RIGHTCHILD(x) (((x)+1)*2) /* This is a smart indexed heap. In addition to the "normal" indexed heap it allows to access every element through its index in O(1) time. In other words, for this heap the indexing operation is O(1), the normal heap does this in O(n) time.... */ void igraph_i_2wheap_switch(igraph_2wheap_t *h, long int e1, long int e2) { if (e1 != e2) { long int tmp1, tmp2; igraph_real_t tmp3 = VECTOR(h->data)[e1]; VECTOR(h->data)[e1] = VECTOR(h->data)[e2]; VECTOR(h->data)[e2] = tmp3; tmp1 = VECTOR(h->index)[e1]; tmp2 = VECTOR(h->index)[e2]; VECTOR(h->index2)[tmp1] = e2 + 2; VECTOR(h->index2)[tmp2] = e1 + 2; VECTOR(h->index)[e1] = tmp2; VECTOR(h->index)[e2] = tmp1; } } void igraph_i_2wheap_shift_up(igraph_2wheap_t *h, long int elem) { if (elem == 0 || VECTOR(h->data)[elem] < VECTOR(h->data)[PARENT(elem)]) { /* at the top */ } else { igraph_i_2wheap_switch(h, elem, PARENT(elem)); igraph_i_2wheap_shift_up(h, PARENT(elem)); } } void igraph_i_2wheap_sink(igraph_2wheap_t *h, long int head) { long int size = igraph_2wheap_size(h); if (LEFTCHILD(head) >= size) { /* no subtrees */ } else if (RIGHTCHILD(head) == size || VECTOR(h->data)[LEFTCHILD(head)] >= VECTOR(h->data)[RIGHTCHILD(head)]) { /* sink to the left if needed */ if (VECTOR(h->data)[head] < VECTOR(h->data)[LEFTCHILD(head)]) { igraph_i_2wheap_switch(h, head, LEFTCHILD(head)); igraph_i_2wheap_sink(h, LEFTCHILD(head)); } } else { /* sink to the right */ if (VECTOR(h->data)[head] < VECTOR(h->data)[RIGHTCHILD(head)]) { igraph_i_2wheap_switch(h, head, RIGHTCHILD(head)); igraph_i_2wheap_sink(h, RIGHTCHILD(head)); } } } /* ------------------ */ /* These are public */ /* ------------------ */ int igraph_2wheap_init(igraph_2wheap_t *h, long int size) { h->size = size; /* We start with the biggest */ IGRAPH_CHECK(igraph_vector_long_init(&h->index2, size)); IGRAPH_FINALLY(igraph_vector_long_destroy, &h->index2); IGRAPH_VECTOR_INIT_FINALLY(&h->data, 0); IGRAPH_CHECK(igraph_vector_long_init(&h->index, 0)); /* IGRAPH_FINALLY(igraph_vector_long_destroy, &h->index); */ IGRAPH_FINALLY_CLEAN(2); return 0; } void igraph_2wheap_destroy(igraph_2wheap_t *h) { igraph_vector_destroy(&h->data); igraph_vector_long_destroy(&h->index); igraph_vector_long_destroy(&h->index2); } int igraph_2wheap_clear(igraph_2wheap_t *h) { igraph_vector_clear(&h->data); igraph_vector_long_clear(&h->index); igraph_vector_long_null(&h->index2); return 0; } igraph_bool_t igraph_2wheap_empty(const igraph_2wheap_t *h) { return igraph_vector_empty(&h->data); } int igraph_2wheap_push_with_index(igraph_2wheap_t *h, long int idx, igraph_real_t elem) { /* printf("-> %.2g [%li]\n", elem, idx); */ long int size = igraph_vector_size(&h->data); IGRAPH_CHECK(igraph_vector_push_back(&h->data, elem)); IGRAPH_CHECK(igraph_vector_long_push_back(&h->index, idx)); VECTOR(h->index2)[idx] = size + 2; /* maintain heap */ igraph_i_2wheap_shift_up(h, size); return 0; } long int igraph_2wheap_size(const igraph_2wheap_t *h) { return igraph_vector_size(&h->data); } long int igraph_2wheap_max_size(const igraph_2wheap_t *h) { return h->size; } igraph_real_t igraph_2wheap_max(const igraph_2wheap_t *h) { return VECTOR(h->data)[0]; } long int igraph_2wheap_max_index(const igraph_2wheap_t *h) { return VECTOR(h->index)[0]; } igraph_bool_t igraph_2wheap_has_elem(const igraph_2wheap_t *h, long int idx) { return VECTOR(h->index2)[idx] != 0; } igraph_bool_t igraph_2wheap_has_active(const igraph_2wheap_t *h, long int idx) { return VECTOR(h->index2)[idx] > 1; } igraph_real_t igraph_2wheap_get(const igraph_2wheap_t *h, long int idx) { long int i = VECTOR(h->index2)[idx] - 2; return VECTOR(h->data)[i]; } igraph_real_t igraph_2wheap_delete_max(igraph_2wheap_t *h) { igraph_real_t tmp = VECTOR(h->data)[0]; long int tmpidx = VECTOR(h->index)[0]; igraph_i_2wheap_switch(h, 0, igraph_2wheap_size(h) - 1); igraph_vector_pop_back(&h->data); igraph_vector_long_pop_back(&h->index); VECTOR(h->index2)[tmpidx] = 0; igraph_i_2wheap_sink(h, 0); /* printf("<-max %.2g\n", tmp); */ return tmp; } igraph_real_t igraph_2wheap_deactivate_max(igraph_2wheap_t *h) { igraph_real_t tmp = VECTOR(h->data)[0]; long int tmpidx = VECTOR(h->index)[0]; igraph_i_2wheap_switch(h, 0, igraph_2wheap_size(h) - 1); igraph_vector_pop_back(&h->data); igraph_vector_long_pop_back(&h->index); VECTOR(h->index2)[tmpidx] = 1; igraph_i_2wheap_sink(h, 0); return tmp; } igraph_real_t igraph_2wheap_delete_max_index(igraph_2wheap_t *h, long int *idx) { igraph_real_t tmp = VECTOR(h->data)[0]; long int tmpidx = VECTOR(h->index)[0]; igraph_i_2wheap_switch(h, 0, igraph_2wheap_size(h) - 1); igraph_vector_pop_back(&h->data); igraph_vector_long_pop_back(&h->index); VECTOR(h->index2)[tmpidx] = 0; igraph_i_2wheap_sink(h, 0); if (idx) { *idx = tmpidx; } return tmp; } int igraph_2wheap_modify(igraph_2wheap_t *h, long int idx, igraph_real_t elem) { long int pos = VECTOR(h->index2)[idx] - 2; /* printf("-- %.2g -> %.2g\n", VECTOR(h->data)[pos], elem); */ VECTOR(h->data)[pos] = elem; igraph_i_2wheap_sink(h, pos); igraph_i_2wheap_shift_up(h, pos); return 0; } /* Check that the heap is in a consistent state */ int igraph_2wheap_check(igraph_2wheap_t *h) { long int size = igraph_2wheap_size(h); long int i; igraph_bool_t error = 0; /* Check the heap property */ for (i = 0; i < size; i++) { if (LEFTCHILD(i) >= size) { break; } if (VECTOR(h->data)[LEFTCHILD(i)] > VECTOR(h->data)[i]) { error = 1; break; } if (RIGHTCHILD(i) >= size) { break; } if (VECTOR(h->data)[RIGHTCHILD(i)] > VECTOR(h->data)[i]) { error = 1; break; } } if (error) { IGRAPH_ERROR("Inconsistent heap", IGRAPH_EINTERNAL); } return 0; } python-igraph-0.8.0/vendor/source/igraph/src/basic_query.c0000644000076500000240000000411413614300625024050 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2005-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_datatype.h" #include "igraph_types.h" #include "igraph_interface.h" #include "igraph_structural.h" #include "config.h" /** * \ingroup structural * \function igraph_are_connected * \brief Decides whether two vertices are connected * * \param graph The graph object. * \param v1 The first vertex. * \param v2 The second vertex. * \param res Boolean, \c TRUE if there is an edge from * \p v1 to \p v2, \c FALSE otherwise. * \return The error code \c IGRAPH_EINVVID is returned if an invalid * vertex ID is given. * * The function is of course symmetric for undirected graphs. * * * Time complexity: O( min(log(d1), log(d2)) ), * d1 is the (out-)degree of \p v1 and d2 is the (in-)degree of \p v2. */ int igraph_are_connected(const igraph_t *graph, igraph_integer_t v1, igraph_integer_t v2, igraph_bool_t *res) { long int nov = igraph_vcount(graph); igraph_integer_t eid = -1; if (v1 < 0 || v2 < 0 || v1 > nov - 1 || v2 > nov - 1) { IGRAPH_ERROR("are connected", IGRAPH_EINVVID); } igraph_get_eid(graph, &eid, v1, v2, /*directed=*/1, /*error=*/ 0); *res = (eid >= 0); return IGRAPH_SUCCESS; } python-igraph-0.8.0/vendor/source/igraph/src/gengraph_definitions.h0000644000076500000240000001142613614300625025741 0ustar tamasstaff00000000000000/* * * gengraph - generation of random simple connected graphs with prescribed * degree sequence * * Copyright (C) 2006 Fabien Viger * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #ifndef DEFINITIONS_H #define DEFINITIONS_H #ifndef _MSC_VER #ifndef register #define register #endif #endif #include #include #include namespace gengraph { // Max line size in files #define FBUFF_SIZE 1000000 // disable lousy VC++ warnings #ifdef _ATL_VER_ #pragma warning(disable : 4127) #endif //_ATL_VER_ // Verbose #define VERBOSE_NONE 0 #define VERBOSE_SOME 1 #define VERBOSE_LOTS 2 int VERBOSE(); void SET_VERBOSE(int v); // Random number generator void my_srandom(int); int my_random(); int my_binomial(double pp, int n); double my_random01(); // (0,1] #define MY_RAND_MAX 0x7FFFFFFF // IPv4 address direct translation into 32-bit uint + special IP defs typedef unsigned int ip_addr; #define IP_NONE 0x7FFFFFFF #define IP_STAR 0x00000000 #define IP_MYSELF 0x7F000001 // Compatibility #ifdef _WIN32 #define strcasecmp _stricmp #endif //inline double round(double x) throw () { return (floor(0.5+x)); } // No assert #ifndef _DEBUG #ifndef NDEBUG #define NDEBUG #endif //NDEBUG #endif //_DEBUG // Min & Max #ifndef min #define defmin(type) inline type min(type a, type b) { return ab ? a : b; } defmax(int) defmax(double) defmax(unsigned long) #endif //max // Traceroute Sampling #define MODE_USP 0 #define MODE_ASP 1 #define MODE_RSP 2 // Debug definitions //#define PERFORMANCE_MONITOR //#define OPT_ISOLATED // Max Int #ifndef MAX_INT #define MAX_INT 0x7FFFFFFF #endif //MAX_INT //Edge type typedef struct { int from; int to; } edge; // Tag Int #define TAG_INT 0x40000000 // Oldies .... #define S_VECTOR_RAW //********************* // Routine definitions //********************* /* log(1+x) inline double logp(double x) { if(fabs(x)<1e-6) return x+0.5*x*x+0.333333333333333*x*x*x; else return log(1.0+x); } //*/ //Fast search or replace inline int* fast_rpl(int *m, const int a, const int b) { while (*m != a) { m++; } *m = b; return m; } inline int* fast_search(int *m, const int size, const int a) { int *p = m + size; while (m != p--) if (*p == a) { return p; } return NULL; } // Lovely percentage print // inline void print_percent(double yo, FILE *f = stderr) { // int arf = int(100.0*yo); // if(double(arf)>100.0*yo) arf--; // if(arf<100) fprintf(f," "); // if(arf<10) fprintf(f," "); // fprintf(f,"%d.%d%%",arf,int(1000.0*yo-double(10*arf))); // } // Skips non-numerical chars, then numerical chars, then non-numerical chars. inline char skip_int(char* &c) { while (*c < '0' || *c > '9') { c++; } while (*c >= '0' && *c <= '9') { c++; } while (*c != 0 && (*c < '0' || *c > '9')) { c++; } return *c; } // distance+1 modulo 255 for breadth-first search inline unsigned char next_dist(const unsigned char c) { return c == 255 ? 1 : c + 1; } inline unsigned char prev_dist(const unsigned char c) { return c == 1 ? 255 : c - 1; } // 1/(RANDMAX+1) #define inv_RANDMAX (1.0/(1.0+double(MY_RAND_MAX))) // random number in ]0,1[, _very_ accurate around 0 inline double random_float() { int r = my_random(); double mul = inv_RANDMAX; while (r <= 0x7FFFFF) { r <<= 8; r += (my_random() & 0xFF); mul *= (1.0 / 256.0); } return double(r) * mul; } // Return true with probability p. Very accurate when p is small. #define test_proba(p) (random_float()<(p)) // Random bit generator, sparwise. static int _random_bits_stored = 0; static int _random_bits = 0; inline int random_bit() { register int a = _random_bits; _random_bits = a >> 1; if (_random_bits_stored--) { return a & 0x1; } a = my_random(); _random_bits = a >> 1; _random_bits_stored = 30; return a & 0x1; } // Hash Profiling (see hash.h) void _hash_prof(); } // namespace gengraph #endif //DEFINITIONS_H python-igraph-0.8.0/vendor/source/igraph/src/arpack.c0000644000076500000240000014500313614300625023006 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 noet: */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_arpack.h" #include "igraph_arpack_internal.h" #include "igraph_memory.h" #include #include #include /* The ARPACK example file dssimp.f is used as a template */ int igraph_i_arpack_err_dsaupd(int error) { switch (error) { case 1: return IGRAPH_ARPACK_MAXIT; case 3: return IGRAPH_ARPACK_NOSHIFT; case -1: return IGRAPH_ARPACK_NPOS; case -2: return IGRAPH_ARPACK_NEVNPOS; case -3: return IGRAPH_ARPACK_NCVSMALL; case -4: return IGRAPH_ARPACK_NONPOSI; case -5: return IGRAPH_ARPACK_WHICHINV; case -6: return IGRAPH_ARPACK_BMATINV; case -7: return IGRAPH_ARPACK_WORKLSMALL; case -8: return IGRAPH_ARPACK_TRIDERR; case -9: return IGRAPH_ARPACK_ZEROSTART; case -10: return IGRAPH_ARPACK_MODEINV; case -11: return IGRAPH_ARPACK_MODEBMAT; case -12: return IGRAPH_ARPACK_ISHIFT; case -13: return IGRAPH_ARPACK_NEVBE; case -9999: return IGRAPH_ARPACK_NOFACT; default: return IGRAPH_ARPACK_UNKNOWN; } } int igraph_i_arpack_err_dseupd(int error) { switch (error) { case -1: return IGRAPH_ARPACK_NPOS; case -2: return IGRAPH_ARPACK_NEVNPOS; case -3: return IGRAPH_ARPACK_NCVSMALL; case -5: return IGRAPH_ARPACK_WHICHINV; case -6: return IGRAPH_ARPACK_BMATINV; case -7: return IGRAPH_ARPACK_WORKLSMALL; case -8: return IGRAPH_ARPACK_TRIDERR; case -9: return IGRAPH_ARPACK_ZEROSTART; case -10: return IGRAPH_ARPACK_MODEINV; case -11: return IGRAPH_ARPACK_MODEBMAT; case -12: return IGRAPH_ARPACK_NEVBE; case -14: return IGRAPH_ARPACK_FAILED; case -15: return IGRAPH_ARPACK_HOWMNY; case -16: return IGRAPH_ARPACK_HOWMNYS; case -17: return IGRAPH_ARPACK_EVDIFF; default: return IGRAPH_ARPACK_UNKNOWN; } } int igraph_i_arpack_err_dnaupd(int error) { switch (error) { case 1: return IGRAPH_ARPACK_MAXIT; case 3: return IGRAPH_ARPACK_NOSHIFT; case -1: return IGRAPH_ARPACK_NPOS; case -2: return IGRAPH_ARPACK_NEVNPOS; case -3: return IGRAPH_ARPACK_NCVSMALL; case -4: return IGRAPH_ARPACK_NONPOSI; case -5: return IGRAPH_ARPACK_WHICHINV; case -6: return IGRAPH_ARPACK_BMATINV; case -7: return IGRAPH_ARPACK_WORKLSMALL; case -8: return IGRAPH_ARPACK_TRIDERR; case -9: return IGRAPH_ARPACK_ZEROSTART; case -10: return IGRAPH_ARPACK_MODEINV; case -11: return IGRAPH_ARPACK_MODEBMAT; case -12: return IGRAPH_ARPACK_ISHIFT; case -9999: return IGRAPH_ARPACK_NOFACT; default: return IGRAPH_ARPACK_UNKNOWN; } } int igraph_i_arpack_err_dneupd(int error) { switch (error) { case 1: return IGRAPH_ARPACK_REORDER; case -1: return IGRAPH_ARPACK_NPOS; case -2: return IGRAPH_ARPACK_NEVNPOS; case -3: return IGRAPH_ARPACK_NCVSMALL; case -5: return IGRAPH_ARPACK_WHICHINV; case -6: return IGRAPH_ARPACK_BMATINV; case -7: return IGRAPH_ARPACK_WORKLSMALL; case -8: return IGRAPH_ARPACK_SHUR; case -9: return IGRAPH_ARPACK_LAPACK; case -10: return IGRAPH_ARPACK_MODEINV; case -11: return IGRAPH_ARPACK_MODEBMAT; case -12: return IGRAPH_ARPACK_HOWMNYS; case -13: return IGRAPH_ARPACK_HOWMNY; case -14: return IGRAPH_ARPACK_FAILED; case -15: return IGRAPH_ARPACK_EVDIFF; default: return IGRAPH_ARPACK_UNKNOWN; } } /** * \function igraph_arpack_options_init * Initialize ARPACK options * * Initializes ARPACK options, set them to default values. * You can always pass the initialized \ref igraph_arpack_options_t * object to built-in igraph functions without any modification. The * built-in igraph functions modify the options to perform their * calculation, e.g. \ref igraph_pagerank() always searches for the * eigenvalue with the largest magnitude, regardless of the supplied * value. * * If you want to implement your own function involving eigenvalue * calculation using ARPACK, however, you will likely need to set up * the fields for yourself. * \param o The \ref igraph_arpack_options_t object to initialize. * * Time complexity: O(1). */ void igraph_arpack_options_init(igraph_arpack_options_t *o) { o->bmat[0] = 'I'; o->n = 0; /* needs to be updated! */ o->which[0] = 'X'; o->which[1] = 'X'; o->nev = 1; o->tol = 0; o->ncv = 0; /* 0 means "automatic" */ o->ldv = o->n; /* will be updated to (real) n */ o->ishift = 1; o->mxiter = 3000; o->nb = 1; o->mode = 1; o->start = 0; o->lworkl = 0; o->sigma = 0; o->sigmai = 0; o->info = o->start; o->iparam[0] = o->ishift; o->iparam[1] = 0; o->iparam[2] = o->mxiter; o->iparam[3] = o->nb; o->iparam[4] = 0; o->iparam[5] = 0; o->iparam[6] = o->mode; o->iparam[7] = 0; o->iparam[8] = 0; o->iparam[9] = 0; o->iparam[10] = 0; } /** * \function igraph_arpack_storage_init * Initialize ARPACK storage * * You only need this function if you want to run multiple eigenvalue * calculations using ARPACK, and want to spare the memory * allocation/deallocation between each two runs. Otherwise it is safe * to supply a null pointer as the \c storage argument of both \ref * igraph_arpack_rssolve() and \ref igraph_arpack_rnsolve() to make * memory allocated and deallocated automatically. * * Don't forget to call the \ref * igraph_arpack_storage_destroy() function on the storage object if * you don't need it any more. * \param s The \ref igraph_arpack_storage_t object to initialize. * \param maxn The maximum order of the matrices. * \param maxncv The maximum NCV parameter intended to use. * \param maxldv The maximum LDV parameter intended to use. * \param symm Whether symmetric or non-symmetric problems will be * solved using this \ref igraph_arpack_storage_t. (You cannot use * the same storage both with symmetric and non-symmetric solvers.) * \return Error code. * * Time complexity: O(maxncv*(maxldv+maxn)). */ int igraph_arpack_storage_init(igraph_arpack_storage_t *s, long int maxn, long int maxncv, long int maxldv, igraph_bool_t symm) { /* TODO: check arguments */ s->maxn = (int) maxn; s->maxncv = (int) maxncv; s->maxldv = (int) maxldv; #define CHECKMEM(x) \ if (!x) { \ IGRAPH_ERROR("Cannot allocate memory for ARPACK", IGRAPH_ENOMEM); \ } \ IGRAPH_FINALLY(igraph_free, x); s->v = igraph_Calloc(maxldv * maxncv, igraph_real_t); CHECKMEM(s->v); s->workd = igraph_Calloc(3 * maxn, igraph_real_t); CHECKMEM(s->workd); s->d = igraph_Calloc(2 * maxncv, igraph_real_t); CHECKMEM(s->d); s->resid = igraph_Calloc(maxn, igraph_real_t); CHECKMEM(s->resid); s->ax = igraph_Calloc(maxn, igraph_real_t); CHECKMEM(s->ax); s->select = igraph_Calloc(maxncv, int); CHECKMEM(s->select); if (symm) { s->workl = igraph_Calloc(maxncv * (maxncv + 8), igraph_real_t); CHECKMEM(s->workl); s->di = 0; s->workev = 0; } else { s->workl = igraph_Calloc(3 * maxncv * (maxncv + 2), igraph_real_t); CHECKMEM(s->workl); s->di = igraph_Calloc(2 * maxncv, igraph_real_t); CHECKMEM(s->di); s->workev = igraph_Calloc(3 * maxncv, igraph_real_t); CHECKMEM(s->workev); IGRAPH_FINALLY_CLEAN(2); } #undef CHECKMEM IGRAPH_FINALLY_CLEAN(7); return 0; } /** * \function igraph_arpack_storage_destroy * Deallocate ARPACK storage * * \param s The \ref igraph_arpack_storage_t object for which the * memory will be deallocated. * * Time complexity: operating system dependent. */ void igraph_arpack_storage_destroy(igraph_arpack_storage_t *s) { if (s->di) { igraph_Free(s->di); } if (s->workev) { igraph_Free(s->workev); } igraph_Free(s->workl); igraph_Free(s->select); igraph_Free(s->ax); igraph_Free(s->resid); igraph_Free(s->d); igraph_Free(s->workd); igraph_Free(s->v); } /** * "Solver" for 1x1 eigenvalue problems since ARPACK sometimes blows up with * these. */ int igraph_i_arpack_rssolve_1x1(igraph_arpack_function_t *fun, void *extra, igraph_arpack_options_t* options, igraph_vector_t* values, igraph_matrix_t* vectors) { igraph_real_t a, b; int nev = options->nev; if (nev <= 0) { IGRAPH_ERROR("ARPACK error", IGRAPH_ARPACK_NEVNPOS); } /* Probe the value in the matrix */ a = 1; if (fun(&b, &a, 1, extra)) { IGRAPH_ERROR("ARPACK error while evaluating matrix-vector product", IGRAPH_ARPACK_PROD); } options->nconv = nev; if (values != 0) { IGRAPH_CHECK(igraph_vector_resize(values, 1)); VECTOR(*values)[0] = b; } if (vectors != 0) { IGRAPH_CHECK(igraph_matrix_resize(vectors, 1, 1)); MATRIX(*vectors, 0, 0) = 1; } return IGRAPH_SUCCESS; } /** * "Solver" for 1x1 eigenvalue problems since ARPACK sometimes blows up with * these. */ int igraph_i_arpack_rnsolve_1x1(igraph_arpack_function_t *fun, void *extra, igraph_arpack_options_t* options, igraph_matrix_t* values, igraph_matrix_t* vectors) { igraph_real_t a, b; int nev = options->nev; if (nev <= 0) { IGRAPH_ERROR("ARPACK error", IGRAPH_ARPACK_NEVNPOS); } /* Probe the value in the matrix */ a = 1; if (fun(&b, &a, 1, extra)) { IGRAPH_ERROR("ARPACK error while evaluating matrix-vector product", IGRAPH_ARPACK_PROD); } options->nconv = nev; if (values != 0) { IGRAPH_CHECK(igraph_matrix_resize(values, 1, 2)); MATRIX(*values, 0, 0) = b; MATRIX(*values, 0, 1) = 0; } if (vectors != 0) { IGRAPH_CHECK(igraph_matrix_resize(vectors, 1, 1)); MATRIX(*vectors, 0, 0) = 1; } return IGRAPH_SUCCESS; } /** * "Solver" for 2x2 nonsymmetric eigenvalue problems since ARPACK sometimes * blows up with these. */ int igraph_i_arpack_rnsolve_2x2(igraph_arpack_function_t *fun, void *extra, igraph_arpack_options_t* options, igraph_matrix_t* values, igraph_matrix_t* vectors) { igraph_real_t vec[2], mat[4]; igraph_real_t a, b, c, d; igraph_real_t trace, det, tsq4_minus_d; igraph_complex_t eval1, eval2; igraph_complex_t evec1[2], evec2[2]; igraph_bool_t swap_evals = 0; igraph_bool_t complex_evals = 0; int nev = options->nev; if (nev <= 0) { IGRAPH_ERROR("ARPACK error", IGRAPH_ARPACK_NEVNPOS); } if (nev > 2) { nev = 2; } /* Probe the values in the matrix */ vec[0] = 1; vec[1] = 0; if (fun(mat, vec, 2, extra)) { IGRAPH_ERROR("ARPACK error while evaluating matrix-vector product", IGRAPH_ARPACK_PROD); } vec[0] = 0; vec[1] = 1; if (fun(mat + 2, vec, 2, extra)) { IGRAPH_ERROR("ARPACK error while evaluating matrix-vector product", IGRAPH_ARPACK_PROD); } a = mat[0]; b = mat[2]; c = mat[1]; d = mat[3]; /* Get the trace and the determinant */ trace = a + d; det = a * d - b * c; tsq4_minus_d = trace * trace / 4 - det; /* Calculate the eigenvalues */ complex_evals = tsq4_minus_d < 0; eval1 = igraph_complex_sqrt_real(tsq4_minus_d); if (complex_evals) { eval2 = igraph_complex_mul_real(eval1, -1); } else { /* to avoid having -0 in the imaginary part */ eval2 = igraph_complex(-IGRAPH_REAL(eval1), 0); } eval1 = igraph_complex_add_real(eval1, trace / 2); eval2 = igraph_complex_add_real(eval2, trace / 2); if (c != 0) { evec1[0] = igraph_complex_sub_real(eval1, d); evec1[1] = igraph_complex(c, 0); evec2[0] = igraph_complex_sub_real(eval2, d); evec2[1] = igraph_complex(c, 0); } else if (b != 0) { evec1[0] = igraph_complex(b, 0); evec1[1] = igraph_complex_sub_real(eval1, a); evec2[0] = igraph_complex(b, 0); evec2[1] = igraph_complex_sub_real(eval2, a); } else { evec1[0] = igraph_complex(1, 0); evec1[1] = igraph_complex(0, 0); evec2[0] = igraph_complex(0, 0); evec2[1] = igraph_complex(1, 0); } /* Sometimes we have to swap eval1 with eval2 and evec1 with eval2; * determine whether we have to do it now */ if (options->which[0] == 'S') { if (options->which[1] == 'M') { /* eval1 must be the one with the smallest magnitude */ swap_evals = (igraph_complex_mod(eval1) > igraph_complex_mod(eval2)); } else if (options->which[1] == 'R') { /* eval1 must be the one with the smallest real part */ swap_evals = (IGRAPH_REAL(eval1) > IGRAPH_REAL(eval2)); } else if (options->which[1] == 'I') { /* eval1 must be the one with the smallest imaginary part */ swap_evals = (IGRAPH_IMAG(eval1) > IGRAPH_IMAG(eval2)); } else { IGRAPH_ERROR("ARPACK error", IGRAPH_ARPACK_WHICHINV); } } else if (options->which[0] == 'L') { if (options->which[1] == 'M') { /* eval1 must be the one with the largest magnitude */ swap_evals = (igraph_complex_mod(eval1) < igraph_complex_mod(eval2)); } else if (options->which[1] == 'R') { /* eval1 must be the one with the largest real part */ swap_evals = (IGRAPH_REAL(eval1) < IGRAPH_REAL(eval2)); } else if (options->which[1] == 'I') { /* eval1 must be the one with the largest imaginary part */ swap_evals = (IGRAPH_IMAG(eval1) < IGRAPH_IMAG(eval2)); } else { IGRAPH_ERROR("ARPACK error", IGRAPH_ARPACK_WHICHINV); } } else if (options->which[0] == 'X' && options->which[1] == 'X') { /* No preference on the ordering of eigenvectors */ } else { /* fprintf(stderr, "%c%c\n", options->which[0], options->which[1]); */ IGRAPH_ERROR("ARPACK error", IGRAPH_ARPACK_WHICHINV); } options->nconv = nev; if (swap_evals) { igraph_complex_t dummy; dummy = eval1; eval1 = eval2; eval2 = dummy; dummy = evec1[0]; evec1[0] = evec2[0]; evec2[0] = dummy; dummy = evec1[1]; evec1[1] = evec2[1]; evec2[1] = dummy; } if (complex_evals) { /* The eigenvalues are conjugate pairs, so we store only the * one with positive imaginary part */ if (IGRAPH_IMAG(eval1) < 0) { eval1 = eval2; evec1[0] = evec2[0]; evec1[1] = evec2[1]; } } if (values != 0) { IGRAPH_CHECK(igraph_matrix_resize(values, nev, 2)); MATRIX(*values, 0, 0) = IGRAPH_REAL(eval1); MATRIX(*values, 0, 1) = IGRAPH_IMAG(eval1); if (nev > 1) { MATRIX(*values, 1, 0) = IGRAPH_REAL(eval2); MATRIX(*values, 1, 1) = IGRAPH_IMAG(eval2); } } if (vectors != 0) { if (complex_evals) { IGRAPH_CHECK(igraph_matrix_resize(vectors, 2, 2)); MATRIX(*vectors, 0, 0) = IGRAPH_REAL(evec1[0]); MATRIX(*vectors, 1, 0) = IGRAPH_REAL(evec1[1]); MATRIX(*vectors, 0, 1) = IGRAPH_IMAG(evec1[0]); MATRIX(*vectors, 1, 1) = IGRAPH_IMAG(evec1[1]); } else { IGRAPH_CHECK(igraph_matrix_resize(vectors, 2, nev)); MATRIX(*vectors, 0, 0) = IGRAPH_REAL(evec1[0]); MATRIX(*vectors, 1, 0) = IGRAPH_REAL(evec1[1]); if (nev > 1) { MATRIX(*vectors, 0, 1) = IGRAPH_REAL(evec2[0]); MATRIX(*vectors, 1, 1) = IGRAPH_REAL(evec2[1]); } } } return IGRAPH_SUCCESS; } /** * "Solver" for symmetric 2x2 eigenvalue problems since ARPACK sometimes blows * up with these. */ int igraph_i_arpack_rssolve_2x2(igraph_arpack_function_t *fun, void *extra, igraph_arpack_options_t* options, igraph_vector_t* values, igraph_matrix_t* vectors) { igraph_real_t vec[2], mat[4]; igraph_real_t a, b, c, d; igraph_real_t trace, det, tsq4_minus_d; igraph_real_t eval1, eval2; int nev = options->nev; if (nev <= 0) { IGRAPH_ERROR("ARPACK error", IGRAPH_ARPACK_NEVNPOS); } if (nev > 2) { nev = 2; } /* Probe the values in the matrix */ vec[0] = 1; vec[1] = 0; if (fun(mat, vec, 2, extra)) { IGRAPH_ERROR("ARPACK error while evaluating matrix-vector product", IGRAPH_ARPACK_PROD); } vec[0] = 0; vec[1] = 1; if (fun(mat + 2, vec, 2, extra)) { IGRAPH_ERROR("ARPACK error while evaluating matrix-vector product", IGRAPH_ARPACK_PROD); } a = mat[0]; b = mat[2]; c = mat[1]; d = mat[3]; /* Get the trace and the determinant */ trace = a + d; det = a * d - b * c; tsq4_minus_d = trace * trace / 4 - det; if (tsq4_minus_d >= 0) { /* Both eigenvalues are real */ eval1 = trace / 2 + sqrt(tsq4_minus_d); eval2 = trace / 2 - sqrt(tsq4_minus_d); if (c != 0) { mat[0] = eval1 - d; mat[2] = eval2 - d; mat[1] = c; mat[3] = c; } else if (b != 0) { mat[0] = b; mat[2] = b; mat[1] = eval1 - a; mat[3] = eval2 - a; } else { mat[0] = 1; mat[2] = 0; mat[1] = 0; mat[3] = 1; } } else { /* Both eigenvalues are complex. Should not happen with symmetric * matrices. */ IGRAPH_ERROR("ARPACK error, 2x2 matrix is not symmetric", IGRAPH_EINVAL); } /* eval1 is always the larger eigenvalue. If we want the smaller * one, we have to swap eval1 with eval2 and also the columns of mat */ if (options->which[0] == 'S') { trace = eval1; eval1 = eval2; eval2 = trace; trace = mat[0]; mat[0] = mat[2]; mat[2] = trace; trace = mat[1]; mat[1] = mat[3]; mat[3] = trace; } else if (options->which[0] == 'L' || options->which[0] == 'B') { /* Nothing to do here */ } else if (options->which[0] == 'X' && options->which[1] == 'X') { /* No preference on the ordering of eigenvectors */ } else { IGRAPH_ERROR("ARPACK error", IGRAPH_ARPACK_WHICHINV); } options->nconv = nev; if (values != 0) { IGRAPH_CHECK(igraph_vector_resize(values, nev)); VECTOR(*values)[0] = eval1; if (nev > 1) { VECTOR(*values)[1] = eval2; } } if (vectors != 0) { IGRAPH_CHECK(igraph_matrix_resize(vectors, 2, nev)); MATRIX(*vectors, 0, 0) = mat[0]; MATRIX(*vectors, 1, 0) = mat[1]; if (nev > 1) { MATRIX(*vectors, 0, 1) = mat[2]; MATRIX(*vectors, 1, 1) = mat[3]; } } return IGRAPH_SUCCESS; } int igraph_arpack_rssort(igraph_vector_t *values, igraph_matrix_t *vectors, const igraph_arpack_options_t *options, igraph_real_t *d, const igraph_real_t *v) { igraph_vector_t order; char sort[2]; int apply = 1; unsigned int n = (unsigned int) options->n; int nconv = options->nconv; int nev = options->nev; unsigned int nans = (unsigned int) (nconv < nev ? nconv : nev); #define which(a,b) (options->which[0]==a && options->which[1]==b) if (which('L', 'A')) { sort[0] = 'S'; sort[1] = 'A'; } else if (which('S', 'A')) { sort[0] = 'L'; sort[1] = 'A'; } else if (which('L', 'M')) { sort[0] = 'S'; sort[1] = 'M'; } else if (which('S', 'M')) { sort[0] = 'L'; sort[1] = 'M'; } else if (which('B', 'E')) { sort[0] = 'L'; sort[1] = 'A'; } IGRAPH_CHECK(igraph_vector_init_seq(&order, 0, nconv - 1)); IGRAPH_FINALLY(igraph_vector_destroy, &order); #ifdef HAVE_GFORTRAN igraphdsortr_(sort, &apply, &nconv, d, VECTOR(order), /*which_len=*/ 2); #else igraphdsortr_(sort, &apply, &nconv, d, VECTOR(order)); #endif /* BE is special */ if (which('B', 'E')) { int w = 0, l1 = 0, l2 = nev - 1; igraph_vector_t order2, d2; IGRAPH_VECTOR_INIT_FINALLY(&order2, nev); IGRAPH_VECTOR_INIT_FINALLY(&d2, nev); while (l1 <= l2) { VECTOR(order2)[w] = VECTOR(order)[l1]; VECTOR(d2)[w] = d[l1]; w++; l1++; if (l1 <= l2) { VECTOR(order2)[w] = VECTOR(order)[l2]; VECTOR(d2)[w] = d[l2]; w++; l2--; } } igraph_vector_update(&order, &order2); igraph_vector_copy_to(&d2, d); igraph_vector_destroy(&order2); igraph_vector_destroy(&d2); IGRAPH_FINALLY_CLEAN(2); } #undef which /* Copy values */ if (values) { IGRAPH_CHECK(igraph_vector_resize(values, nans)); memcpy(VECTOR(*values), d, sizeof(igraph_real_t) * nans); } /* Reorder vectors */ if (vectors) { int i; IGRAPH_CHECK(igraph_matrix_resize(vectors, n, nans)); for (i = 0; i < nans; i++) { unsigned int idx = (unsigned int) VECTOR(order)[i]; const igraph_real_t *ptr = v + n * idx; memcpy(&MATRIX(*vectors, 0, i), ptr, sizeof(igraph_real_t) * n); } } igraph_vector_destroy(&order); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_arpack_rnsort(igraph_matrix_t *values, igraph_matrix_t *vectors, const igraph_arpack_options_t *options, igraph_real_t *dr, igraph_real_t *di, igraph_real_t *v) { igraph_vector_t order; char sort[2]; int apply = 1, i; unsigned int n = (unsigned int) options->n; int nconv = options->nconv; int nev = options->nev; unsigned int nans = (unsigned int) (nconv < nev ? nconv : nev); #define which(a,b) (options->which[0]==a && options->which[1]==b) if (which('L', 'M')) { sort[0] = 'S'; sort[1] = 'M'; } else if (which('S', 'M')) { sort[0] = 'L'; sort[1] = 'M'; } else if (which('L', 'R')) { sort[0] = 'S'; sort[1] = 'R'; } else if (which('S', 'R')) { sort[0] = 'L'; sort[1] = 'R'; } else if (which('L', 'I')) { sort[0] = 'S'; sort[1] = 'I'; } else if (which('S', 'I')) { sort[0] = 'L'; sort[1] = 'I'; } #undef which IGRAPH_CHECK(igraph_vector_init_seq(&order, 0, nconv - 1)); IGRAPH_FINALLY(igraph_vector_destroy, &order); #ifdef HAVE_GFORTRAN igraphdsortc_(sort, &apply, &nconv, dr, di, VECTOR(order), /*which_len=*/ 2); #else igraphdsortc_(sort, &apply, &nconv, dr, di, VECTOR(order)); #endif if (values) { IGRAPH_CHECK(igraph_matrix_resize(values, nans, 2)); memcpy(&MATRIX(*values, 0, 0), dr, sizeof(igraph_real_t) * nans); memcpy(&MATRIX(*values, 0, 1), di, sizeof(igraph_real_t) * nans); } if (vectors) { int nc = 0, nr = 0, ncol, vx = 0; for (i = 0; i < nans; i++) { if (di[i] == 0) { nr++; } else { nc++; } } ncol = (nc / 2) * 2 + (nc % 2) * 2 + nr; IGRAPH_CHECK(igraph_matrix_resize(vectors, n, ncol)); for (i = 0; i < nans; i++) { unsigned int idx; idx = (unsigned int) VECTOR(order)[i]; if (di[i] == 0) { /* real eigenvalue, single eigenvector */ memcpy(&MATRIX(*vectors, 0, vx), v + n * idx, sizeof(igraph_real_t) * n); vx++; } else if (di[i] > 0) { /* complex eigenvalue, positive imaginary part encountered first. * ARPACK stores its eigenvector directly in two consecutive columns. * The complex conjugate pair of the eigenvalue (if any) will be in * the next column and we will skip it because we advance 'i' below */ memcpy(&MATRIX(*vectors, 0, vx), v + n * idx, sizeof(igraph_real_t) * 2 * n); vx += 2; i++; } else { /* complex eigenvalue, negative imaginary part encountered first. * The positive one will be the next one, but we need to copy the * eigenvector corresponding to the eigenvalue with the positive * imaginary part. */ idx = (unsigned int) VECTOR(order)[i + 1]; memcpy(&MATRIX(*vectors, 0, vx), v + n * idx, sizeof(igraph_real_t) * 2 * n); vx += 2; i++; } } } igraph_vector_destroy(&order); IGRAPH_FINALLY_CLEAN(1); if (values) { /* Strive to include complex conjugate eigenvalue pairs in a way that the * positive imaginary part comes first */ for (i = 0; i < nans; i++) { if (MATRIX(*values, i, 1) == 0) { /* Real eigenvalue, nothing to do */ } else if (MATRIX(*values, i, 1) < 0) { /* Negative imaginary part came first; negate the imaginary part for * this eigenvalue and the next one (which is the complex conjugate * pair), and skip it */ MATRIX(*values, i, 1) *= -1; i++; if (i < nans) { MATRIX(*values, i, 1) *= -1; } } else { /* Positive imaginary part; skip the next eigenvalue, which is the * complex conjugate pair */ i++; } } } return 0; } /** * \function igraph_i_arpack_auto_ncv * \brief Tries to set up the value of \c ncv in an \c igraph_arpack_options_t * automagically. */ void igraph_i_arpack_auto_ncv(igraph_arpack_options_t* options) { /* This is similar to how Octave determines the value of ncv, with some * modifications. */ int min_ncv = options->nev * 2 + 1; /* Use twice the number of desired eigenvectors plus one by default */ options->ncv = min_ncv; /* ...but use at least 20 Lanczos vectors... */ if (options->ncv < 20) { options->ncv = 20; } /* ...but having ncv close to n leads to some problems with small graphs * (example: PageRank of "A <--> C, D <--> E, B"), so we don't let it * to be larger than n / 2... */ if (options->ncv > options->n / 2) { options->ncv = options->n / 2; } /* ...but we need at least min_ncv. */ if (options->ncv < min_ncv) { options->ncv = min_ncv; } /* ...but at most n */ if (options->ncv > options->n) { options->ncv = options->n; } } /** * \function igraph_i_arpack_report_no_convergence * \brief Prints a warning that informs the user that the ARPACK solver * did not converge. */ void igraph_i_arpack_report_no_convergence(const igraph_arpack_options_t* options) { char buf[1024]; snprintf(buf, sizeof(buf), "ARPACK solver failed to converge (%d iterations, " "%d/%d eigenvectors converged)", options->iparam[2], options->iparam[4], options->nev); IGRAPH_WARNING(buf); } /** * \function igraph_arpack_rssolve * \brief ARPACK solver for symmetric matrices * * This is the ARPACK solver for symmetric matrices. Please use * \ref igraph_arpack_rnsolve() for non-symmetric matrices. * \param fun Pointer to an \ref igraph_arpack_function_t object, * the function that performs the matrix-vector multiplication. * \param extra An extra argument to be passed to \c fun. * \param options An \ref igraph_arpack_options_t object. * \param storage An \ref igraph_arpack_storage_t object, or a null * pointer. In the latter case memory allocation and deallocation * is performed automatically. Either this or the \p vectors argument * must be non-null if the ARPACK iteration is started from a * given starting vector. If both are given \p vectors take * precedence. * \param values If not a null pointer, then it should be a pointer to an * initialized vector. The eigenvalues will be stored here. The * vector will be resized as needed. * \param vectors If not a null pointer, then it must be a pointer to * an initialized matrix. The eigenvectors will be stored in the * columns of the matrix. The matrix will be resized as needed. * Either this or the \p vectors argument must be non-null if the * ARPACK iteration is started from a given starting vector. If * both are given \p vectors take precedence. * \return Error code. * * Time complexity: depends on the matrix-vector * multiplication. Usually a small number of iterations is enough, so * if the matrix is sparse and the matrix-vector multiplication can be * done in O(n) time (the number of vertices), then the eigenvalues * are found in O(n) time as well. */ int igraph_arpack_rssolve(igraph_arpack_function_t *fun, void *extra, igraph_arpack_options_t *options, igraph_arpack_storage_t *storage, igraph_vector_t *values, igraph_matrix_t *vectors) { igraph_real_t *v, *workl, *workd, *d, *resid, *ax; igraph_bool_t free_them = 0; int *select, i; int ido = 0; int rvec = vectors || storage ? 1 : 0; /* calculate eigenvectors? */ char *all = "All"; int origldv = options->ldv, origlworkl = options->lworkl, orignev = options->nev, origncv = options->ncv; char origwhich[2] = { options->which[0], options->which[1] }; igraph_real_t origtol = options->tol; /* Special case for 1x1 and 2x2 matrices in mode 1 */ if (options->mode == 1 && options->n == 1) { return igraph_i_arpack_rssolve_1x1(fun, extra, options, values, vectors); } else if (options->mode == 1 && options->n == 2) { return igraph_i_arpack_rssolve_2x2(fun, extra, options, values, vectors); } /* Brush up options if needed */ if (options->ldv == 0) { options->ldv = options->n; } if (options->ncv == 0) { igraph_i_arpack_auto_ncv(options); } if (options->lworkl == 0) { options->lworkl = options->ncv * (options->ncv + 8); } if (options->which[0] == 'X') { options->which[0] = 'L'; options->which[1] = 'M'; } if (storage) { /* Storage provided */ if (storage->maxn < options->n) { IGRAPH_ERROR("Not enough storage for ARPACK (`n')", IGRAPH_EINVAL); } if (storage->maxncv < options->ncv) { IGRAPH_ERROR("Not enough storage for ARPACK (`ncv')", IGRAPH_EINVAL); } if (storage->maxldv < options->ldv) { IGRAPH_ERROR("Not enough storage for ARPACK (`ldv')", IGRAPH_EINVAL); } v = storage->v; workl = storage->workl; workd = storage->workd; d = storage->d; resid = storage->resid; ax = storage->ax; select = storage->select; } else { /* Storage not provided */ free_them = 1; #define CHECKMEM(x) \ if (!x) { \ IGRAPH_ERROR("Cannot allocate memory for ARPACK", IGRAPH_ENOMEM); \ } \ IGRAPH_FINALLY(igraph_free, x); v = igraph_Calloc(options->ldv * options->ncv, igraph_real_t); CHECKMEM(v); workl = igraph_Calloc(options->lworkl, igraph_real_t); CHECKMEM(workl); workd = igraph_Calloc(3 * options->n, igraph_real_t); CHECKMEM(workd); d = igraph_Calloc(2 * options->ncv, igraph_real_t); CHECKMEM(d); resid = igraph_Calloc(options->n, igraph_real_t); CHECKMEM(resid); ax = igraph_Calloc(options->n, igraph_real_t); CHECKMEM(ax); select = igraph_Calloc(options->ncv, int); CHECKMEM(select); #undef CHECKMEM } /* Set final bits */ options->bmat[0] = 'I'; options->iparam[0] = options->ishift; options->iparam[1] = 0; // not referenced options->iparam[2] = options->mxiter; options->iparam[3] = 1; // currently dsaupd() works only for nb=1 options->iparam[4] = 0; options->iparam[5] = 0; // not referenced options->iparam[6] = options->mode; options->iparam[7] = 0; // return value options->iparam[8] = 0; // return value options->iparam[9] = 0; // return value options->iparam[10] = 0; // return value options->info = options->start; if (options->start) { if (!storage && !vectors) { IGRAPH_ERROR("Starting vector not given", IGRAPH_EINVAL); } if (vectors && (igraph_matrix_nrow(vectors) != options->n || igraph_matrix_ncol(vectors) != 1)) { IGRAPH_ERROR("Invalid starting vector size", IGRAPH_EINVAL); } if (vectors) { for (i = 0; i < options->n; i++) { resid[i] = MATRIX(*vectors, i, 0); } } } /* Ok, we have everything */ while (1) { #ifdef HAVE_GFORTRAN igraphdsaupd_(&ido, options->bmat, &options->n, options->which, &options->nev, &options->tol, resid, &options->ncv, v, &options->ldv, options->iparam, options->ipntr, workd, workl, &options->lworkl, &options->info, /*bmat_len=*/ 1, /*which_len=*/ 2); #else igraphdsaupd_(&ido, options->bmat, &options->n, options->which, &options->nev, &options->tol, resid, &options->ncv, v, &options->ldv, options->iparam, options->ipntr, workd, workl, &options->lworkl, &options->info); #endif if (ido == -1 || ido == 1) { igraph_real_t *from = workd + options->ipntr[0] - 1; igraph_real_t *to = workd + options->ipntr[1] - 1; if (fun(to, from, options->n, extra) != 0) { IGRAPH_ERROR("ARPACK error while evaluating matrix-vector product", IGRAPH_ARPACK_PROD); } } else { break; } } if (options->info == 1) { igraph_i_arpack_report_no_convergence(options); } if (options->info != 0) { IGRAPH_ERROR("ARPACK error", igraph_i_arpack_err_dsaupd(options->info)); } options->ierr = 0; #ifdef HAVE_GFORTRAN igraphdseupd_(&rvec, all, select, d, v, &options->ldv, &options->sigma, options->bmat, &options->n, options->which, &options->nev, &options->tol, resid, &options->ncv, v, &options->ldv, options->iparam, options->ipntr, workd, workl, &options->lworkl, &options->ierr, /*howmny_len=*/ 1, /*bmat_len=*/ 1, /*which_len=*/ 2); #else igraphdseupd_(&rvec, all, select, d, v, &options->ldv, &options->sigma, options->bmat, &options->n, options->which, &options->nev, &options->tol, resid, &options->ncv, v, &options->ldv, options->iparam, options->ipntr, workd, workl, &options->lworkl, &options->ierr); #endif if (options->ierr != 0) { IGRAPH_ERROR("ARPACK error", igraph_i_arpack_err_dseupd(options->ierr)); } /* Save the result */ options->noiter = options->iparam[2]; options->nconv = options->iparam[4]; options->numop = options->iparam[8]; options->numopb = options->iparam[9]; options->numreo = options->iparam[10]; if (options->nconv < options->nev) { IGRAPH_WARNING("Not enough eigenvalues/vectors in symmetric ARPACK " "solver"); } if (values || vectors) { IGRAPH_CHECK(igraph_arpack_rssort(values, vectors, options, d, v)); } options->ldv = origldv; options->ncv = origncv; options->lworkl = origlworkl; options->which[0] = origwhich[0]; options->which[1] = origwhich[1]; options->tol = origtol; options->nev = orignev; /* Clean up if needed */ if (free_them) { igraph_Free(select); igraph_Free(ax); igraph_Free(resid); igraph_Free(d); igraph_Free(workd); igraph_Free(workl); igraph_Free(v); IGRAPH_FINALLY_CLEAN(7); } return 0; } /** * \function igraph_arpack_rnsolve * \brief ARPACK solver for non-symmetric matrices * * Please always consider calling \ref igraph_arpack_rssolve() if your * matrix is symmetric, it is much faster. * \ref igraph_arpack_rnsolve() for non-symmetric matrices. * * Note that ARPACK is not called for 2x2 matrices as an exact algebraic * solution exists in these cases. * * \param fun Pointer to an \ref igraph_arpack_function_t object, * the function that performs the matrix-vector multiplication. * \param extra An extra argument to be passed to \c fun. * \param options An \ref igraph_arpack_options_t object. * \param storage An \ref igraph_arpack_storage_t object, or a null * pointer. In the latter case memory allocation and deallocation * is performed automatically. * \param values If not a null pointer, then it should be a pointer to an * initialized matrix. The (possibly complex) eigenvalues will be * stored here. The matrix will have two columns, the first column * contains the real, the second the imaginary parts of the * eigenvalues. * The matrix will be resized as needed. * \param vectors If not a null pointer, then it must be a pointer to * an initialized matrix. The eigenvectors will be stored in the * columns of the matrix. The matrix will be resized as needed. * Note that real eigenvalues will have real eigenvectors in a single * column in this matrix; however, complex eigenvalues come in conjugate * pairs and the result matrix will store the eigenvector corresponding to * the eigenvalue with \em positive imaginary part only. Since in this case * the eigenvector is also complex, it will occupy \em two columns in the * eigenvector matrix (the real and the imaginary parts, in this order). * Caveat: if the eigenvalue vector returns only the eigenvalue with the * \em negative imaginary part for a complex conjugate eigenvalue pair, the * result vector will \em still store the eigenvector corresponding to the * eigenvalue with the positive imaginary part (since this is how ARPACK * works). * \return Error code. * * Time complexity: depends on the matrix-vector * multiplication. Usually a small number of iterations is enough, so * if the matrix is sparse and the matrix-vector multiplication can be * done in O(n) time (the number of vertices), then the eigenvalues * are found in O(n) time as well. */ int igraph_arpack_rnsolve(igraph_arpack_function_t *fun, void *extra, igraph_arpack_options_t *options, igraph_arpack_storage_t *storage, igraph_matrix_t *values, igraph_matrix_t *vectors) { igraph_real_t *v, *workl, *workd, *dr, *di, *resid, *workev; igraph_bool_t free_them = 0; int *select, i; int ido = 0; int rvec = vectors || storage ? 1 : 0; char *all = "All"; int origldv = options->ldv, origlworkl = options->lworkl, orignev = options->nev, origncv = options->ncv; char origwhich[2] = { options->which[0], options->which[1] }; igraph_real_t origtol = options->tol; int d_size; /* Special case for 1x1 and 2x2 matrices in mode 1 */ if (options->mode == 1 && options->n == 1) { return igraph_i_arpack_rnsolve_1x1(fun, extra, options, values, vectors); } else if (options->mode == 1 && options->n == 2) { return igraph_i_arpack_rnsolve_2x2(fun, extra, options, values, vectors); } /* Brush up options if needed */ if (options->ldv == 0) { options->ldv = options->n; } if (options->ncv == 0) { igraph_i_arpack_auto_ncv(options); } if (options->lworkl == 0) { options->lworkl = 3 * options->ncv * (options->ncv + 2); } if (options->which[0] == 'X') { options->which[0] = 'L'; options->which[1] = 'M'; } if (storage) { /* Storage provided */ if (storage->maxn < options->n) { IGRAPH_ERROR("Not enough storage for ARPACK (`n')", IGRAPH_EINVAL); } if (storage->maxncv < options->ncv) { IGRAPH_ERROR("Not enough storage for ARPACK (`ncv')", IGRAPH_EINVAL); } if (storage->maxldv < options->ldv) { IGRAPH_ERROR("Not enough storage for ARPACK (`ldv')", IGRAPH_EINVAL); } v = storage->v; workl = storage->workl; workd = storage->workd; workev = storage->workev; dr = storage->d; di = storage->di; d_size = options->n; resid = storage->resid; select = storage->select; } else { /* Storage not provided */ free_them = 1; #define CHECKMEM(x) \ if (!x) { \ IGRAPH_ERROR("Cannot allocate memory for ARPACK", IGRAPH_ENOMEM); \ } \ IGRAPH_FINALLY(igraph_free, x); v = igraph_Calloc(options->n * options->ncv, igraph_real_t); CHECKMEM(v); workl = igraph_Calloc(options->lworkl, igraph_real_t); CHECKMEM(workl); workd = igraph_Calloc(3 * options->n, igraph_real_t); CHECKMEM(workd); d_size = 2 * options->nev + 1 > options->ncv ? 2 * options->nev + 1 : options->ncv; dr = igraph_Calloc(d_size, igraph_real_t); CHECKMEM(dr); di = igraph_Calloc(d_size, igraph_real_t); CHECKMEM(di); resid = igraph_Calloc(options->n, igraph_real_t); CHECKMEM(resid); select = igraph_Calloc(options->ncv, int); CHECKMEM(select); workev = igraph_Calloc(3 * options->ncv, igraph_real_t); CHECKMEM(workev); #undef CHECKMEM } /* Set final bits */ options->bmat[0] = 'I'; options->iparam[0] = options->ishift; options->iparam[1] = 0; // not referenced options->iparam[2] = options->mxiter; options->iparam[3] = 1; // currently dnaupd() works only for nb=1 options->iparam[4] = 0; options->iparam[5] = 0; // not referenced options->iparam[6] = options->mode; options->iparam[7] = 0; // return value options->iparam[8] = 0; // return value options->iparam[9] = 0; // return value options->iparam[10] = 0; // return value options->info = options->start; if (options->start) { if (igraph_matrix_nrow(vectors) != options->n || igraph_matrix_ncol(vectors) != 1) { IGRAPH_ERROR("Invalid starting vector size", IGRAPH_EINVAL); } for (i = 0; i < options->n; i++) { resid[i] = MATRIX(*vectors, i, 0); } } /* Ok, we have everything */ while (1) { #ifdef HAVE_GFORTRAN igraphdnaupd_(&ido, options->bmat, &options->n, options->which, &options->nev, &options->tol, resid, &options->ncv, v, &options->ldv, options->iparam, options->ipntr, workd, workl, &options->lworkl, &options->info, /*bmat_len=*/ 1, /*which_len=*/ 2); #else igraphdnaupd_(&ido, options->bmat, &options->n, options->which, &options->nev, &options->tol, resid, &options->ncv, v, &options->ldv, options->iparam, options->ipntr, workd, workl, &options->lworkl, &options->info); #endif if (ido == -1 || ido == 1) { igraph_real_t *from = workd + options->ipntr[0] - 1; igraph_real_t *to = workd + options->ipntr[1] - 1; if (fun(to, from, options->n, extra) != 0) { IGRAPH_ERROR("ARPACK error while evaluating matrix-vector product", IGRAPH_ARPACK_PROD); } } else { break; } } if (options->info == 1) { igraph_i_arpack_report_no_convergence(options); } if (options->info != 0 && options->info != -9999) { IGRAPH_ERROR("ARPACK error", igraph_i_arpack_err_dnaupd(options->info)); } options->ierr = 0; #ifdef HAVE_GFORTRAN igraphdneupd_(&rvec, all, select, dr, di, v, &options->ldv, &options->sigma, &options->sigmai, workev, options->bmat, &options->n, options->which, &options->nev, &options->tol, resid, &options->ncv, v, &options->ldv, options->iparam, options->ipntr, workd, workl, &options->lworkl, &options->ierr, /*howmny_len=*/ 1, /*bmat_len=*/ 1, /*which_len=*/ 2); #else igraphdneupd_(&rvec, all, select, dr, di, v, &options->ldv, &options->sigma, &options->sigmai, workev, options->bmat, &options->n, options->which, &options->nev, &options->tol, resid, &options->ncv, v, &options->ldv, options->iparam, options->ipntr, workd, workl, &options->lworkl, &options->ierr); #endif if (options->ierr != 0) { IGRAPH_ERROR("ARPACK error", igraph_i_arpack_err_dneupd(options->info)); } /* Save the result */ options->noiter = options->iparam[2]; options->nconv = options->iparam[4]; options->numop = options->iparam[8]; options->numopb = options->iparam[9]; options->numreo = options->iparam[10]; if (options->nconv < options->nev) { IGRAPH_WARNING("Not enough eigenvalues/vectors in ARPACK " "solver"); } /* ARPACK might modify stuff in 'options' so reset everything that could * potentially get modified */ options->ldv = origldv; options->ncv = origncv; options->lworkl = origlworkl; options->which[0] = origwhich[0]; options->which[1] = origwhich[1]; options->tol = origtol; options->nev = orignev; if (values || vectors) { IGRAPH_CHECK(igraph_arpack_rnsort(values, vectors, options, dr, di, v)); } /* Clean up if needed */ if (free_them) { igraph_Free(workev); igraph_Free(select); igraph_Free(resid); igraph_Free(di); igraph_Free(dr); igraph_Free(workd); igraph_Free(workl); igraph_Free(v); IGRAPH_FINALLY_CLEAN(8); } return 0; } /** * \function igraph_arpack_unpack_complex * \brief Make the result of the non-symmetric ARPACK solver more readable * * This function works on the output of \ref igraph_arpack_rnsolve and * brushes it up a bit: it only keeps \p nev eigenvalues/vectors and * every eigenvector is stored in two columns of the \p vectors * matrix. * * * The output of the non-symmetric ARPACK solver is somewhat hard to * parse, as real eigenvectors occupy only one column in the matrix, * and the complex conjugate eigenvectors are not stored at all * (usually). The other problem is that the solver might return more * eigenvalues than requested. The common use of this function is to * call it directly after \ref igraph_arpack_rnsolve with its \p * vectors and \p values argument and \c options->nev as \p nev. * \param vectors The eigenvector matrix, as returned by \ref * igraph_arpack_rnsolve. It will be resized, typically it will be * larger. * \param values The eigenvalue matrix, as returned by \ref * igraph_arpack_rnsolve. It will be resized, typically extra, * unneeded rows (=eigenvalues) will be removed. * \param nev The number of eigenvalues/vectors to keep. Can be less * or equal than the number originally requested from ARPACK. * \return Error code. * * Time complexity: linear in the number of elements in the \p vectors * matrix. */ int igraph_arpack_unpack_complex(igraph_matrix_t *vectors, igraph_matrix_t *values, long int nev) { long int nodes = igraph_matrix_nrow(vectors); long int no_evs = igraph_matrix_nrow(values); long int i, j, k, wh; size_t colsize = (unsigned) nodes * sizeof(igraph_real_t); /* Error checks */ if (nev < 0) { IGRAPH_ERROR("`nev' cannot be negative", IGRAPH_EINVAL); } if (nev > no_evs) { IGRAPH_ERROR("`nev' too large, we don't have that many in `values'", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_matrix_resize(vectors, nodes, nev * 2)); for (i = nev; i < igraph_matrix_nrow(values); i++) { IGRAPH_CHECK(igraph_matrix_remove_row(values, i)); } /* Calculate where to start copying */ for (i = 0, j = 0, wh = 0; i < nev; i++) { if (MATRIX(*values, i, 1) == 0) { /* TODO: == 0.0 ???? */ /* real */ j++; } else { /* complex */ if (wh == 0) { j += 2; wh = 1 - wh; } } } j--; /* if (j>=origcol) { */ /* IGRAPH_WARNING("Too few columns in `vectors', ARPACK results are likely wrong"); */ /* } */ /* We copy the j-th eigenvector to the (k-1)-th and k-th column */ k = nev * 2 - 1; for (i = nev - 1; i >= 0; i--) { if (MATRIX(*values, i, 1) == 0) { /* real */ memset( &MATRIX(*vectors, 0, k), 0, colsize); if (k - 1 != j) { memcpy( &MATRIX(*vectors, 0, k - 1), &MATRIX(*vectors, 0, j), colsize); } k -= 2; j -= 1; } else { /* complex */ if (k != j) { /* Separate copy required, otherwise 'from' and 'to' might overlap */ memcpy( &MATRIX(*vectors, 0, k), &MATRIX(*vectors, 0, j), colsize); memcpy( &MATRIX(*vectors, 0, k - 1), &MATRIX(*vectors, 0, j - 1), colsize); } if (i > 1 && MATRIX(*values, i, 1) != -MATRIX(*values, i - 1, 1)) { /* The next one is not a conjugate of this one */ j -= 2; } else { /* Conjugate */ int l; for (l = 0; l < nodes; l++) { MATRIX(*vectors, l, k) = - MATRIX(*vectors, l, k); } } k -= 2; } } return 0; } python-igraph-0.8.0/vendor/source/igraph/src/spanning_trees.c0000644000076500000240000004513013614300625024564 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2011 Gabor Csardi Rue de l'Industrie 5, Lausanne 1005, Switzerland This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_structural.h" #include "igraph_dqueue.h" #include "igraph_interface.h" #include "igraph_interrupt_internal.h" #include "igraph_memory.h" #include "igraph_adjlist.h" #include "igraph_random.h" #include "igraph_components.h" #include "igraph_progress.h" #include "igraph_types_internal.h" int igraph_i_minimum_spanning_tree_unweighted(const igraph_t *graph, igraph_vector_t *result); int igraph_i_minimum_spanning_tree_prim(const igraph_t *graph, igraph_vector_t *result, const igraph_vector_t *weights); /** * \ingroup structural * \function igraph_minimum_spanning_tree * \brief Calculates one minimum spanning tree of a graph. * * * If the graph has more minimum spanning trees (this is always the * case, except if it is a forest) this implementation returns only * the same one. * * * Directed graphs are considered as undirected for this computation. * * * If the graph is not connected then its minimum spanning forest is * returned. This is the set of the minimum spanning trees of each * component. * * \param graph The graph object. * \param res An initialized vector, the IDs of the edges that constitute * a spanning tree will be returned here. Use * \ref igraph_subgraph_edges() to extract the spanning tree as * a separate graph object. * \param weights A vector containing the weights of the edges * in the same order as the simple edge iterator visits them * (i.e. in increasing order of edge IDs). * \return Error code: * \c IGRAPH_ENOMEM, not enough memory for * temporary data. * * Time complexity: O(|V|+|E|) for the unweighted case, O(|E| log |V|) * for the weighted case. |V| is the number of vertices, |E| the * number of edges in the graph. * * \sa \ref igraph_minimum_spanning_tree_unweighted() and * \ref igraph_minimum_spanning_tree_prim() if you only need the * tree as a separate graph object. * * \example examples/simple/igraph_minimum_spanning_tree.c */ int igraph_minimum_spanning_tree(const igraph_t* graph, igraph_vector_t* res, const igraph_vector_t* weights) { if (weights == 0) { IGRAPH_CHECK(igraph_i_minimum_spanning_tree_unweighted(graph, res)); } else { IGRAPH_CHECK(igraph_i_minimum_spanning_tree_prim(graph, res, weights)); } return IGRAPH_SUCCESS; } /** * \ingroup structural * \function igraph_minimum_spanning_tree_unweighted * \brief Calculates one minimum spanning tree of an unweighted graph. * * * If the graph has more minimum spanning trees (this is always the * case, except if it is a forest) this implementation returns only * the same one. * * * Directed graphs are considered as undirected for this computation. * * * If the graph is not connected then its minimum spanning forest is * returned. This is the set of the minimum spanning trees of each * component. * \param graph The graph object. * \param mst The minimum spanning tree, another graph object. Do * \em not initialize this object before passing it to * this function, but be sure to call \ref igraph_destroy() on it if * you don't need it any more. * \return Error code: * \c IGRAPH_ENOMEM, not enough memory for * temporary data. * * Time complexity: O(|V|+|E|), * |V| is the * number of vertices, |E| the number * of edges in the graph. * * \sa \ref igraph_minimum_spanning_tree_prim() for weighted graphs, * \ref igraph_minimum_spanning_tree() if you need the IDs of the * edges that constitute the spanning tree. */ int igraph_minimum_spanning_tree_unweighted(const igraph_t *graph, igraph_t *mst) { igraph_vector_t edges = IGRAPH_VECTOR_NULL; IGRAPH_VECTOR_INIT_FINALLY(&edges, igraph_vcount(graph) - 1); IGRAPH_CHECK(igraph_i_minimum_spanning_tree_unweighted(graph, &edges)); IGRAPH_CHECK(igraph_subgraph_edges(graph, mst, igraph_ess_vector(&edges), /* delete_vertices = */ 0)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \ingroup structural * \function igraph_minimum_spanning_tree_prim * \brief Calculates one minimum spanning tree of a weighted graph. * * * This function uses Prim's method for carrying out the computation, * see Prim, R.C.: Shortest connection networks and some * generalizations, Bell System Technical * Journal, Vol. 36, * 1957, 1389--1401. * * * If the graph has more than one minimum spanning tree, the current * implementation returns always the same one. * * * Directed graphs are considered as undirected for this computation. * * * If the graph is not connected then its minimum spanning forest is * returned. This is the set of the minimum spanning trees of each * component. * * \param graph The graph object. * \param mst The result of the computation, a graph object containing * the minimum spanning tree of the graph. * Do \em not initialize this object before passing it to * this function, but be sure to call \ref igraph_destroy() on it if * you don't need it any more. * \param weights A vector containing the weights of the edges * in the same order as the simple edge iterator visits them * (i.e. in increasing order of edge IDs). * \return Error code: * \c IGRAPH_ENOMEM, not enough memory. * \c IGRAPH_EINVAL, length of weight vector does not * match number of edges. * * Time complexity: O(|E| log |V|), * |V| is the number of vertices, * |E| the number of edges in the * graph. * * \sa \ref igraph_minimum_spanning_tree_unweighted() for unweighted graphs, * \ref igraph_minimum_spanning_tree() if you need the IDs of the * edges that constitute the spanning tree. * * \example examples/simple/igraph_minimum_spanning_tree.c */ int igraph_minimum_spanning_tree_prim(const igraph_t *graph, igraph_t *mst, const igraph_vector_t *weights) { igraph_vector_t edges = IGRAPH_VECTOR_NULL; IGRAPH_VECTOR_INIT_FINALLY(&edges, igraph_vcount(graph) - 1); IGRAPH_CHECK(igraph_i_minimum_spanning_tree_prim(graph, &edges, weights)); IGRAPH_CHECK(igraph_subgraph_edges(graph, mst, igraph_ess_vector(&edges), /* delete_vertices = */ 0)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_i_minimum_spanning_tree_unweighted(const igraph_t* graph, igraph_vector_t* res) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); char *already_added; char *added_edges; igraph_dqueue_t q = IGRAPH_DQUEUE_NULL; igraph_vector_t tmp = IGRAPH_VECTOR_NULL; long int i, j; igraph_vector_clear(res); added_edges = igraph_Calloc(no_of_edges, char); if (added_edges == 0) { IGRAPH_ERROR("unweighted spanning tree failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, added_edges); already_added = igraph_Calloc(no_of_nodes, char); if (already_added == 0) { IGRAPH_ERROR("unweighted spanning tree failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, already_added); IGRAPH_VECTOR_INIT_FINALLY(&tmp, 0); IGRAPH_DQUEUE_INIT_FINALLY(&q, 100); for (i = 0; i < no_of_nodes; i++) { if (already_added[i] > 0) { continue; } IGRAPH_ALLOW_INTERRUPTION(); already_added[i] = 1; IGRAPH_CHECK(igraph_dqueue_push(&q, i)); while (! igraph_dqueue_empty(&q)) { long int act_node = (long int) igraph_dqueue_pop(&q); IGRAPH_CHECK(igraph_incident(graph, &tmp, (igraph_integer_t) act_node, IGRAPH_ALL)); for (j = 0; j < igraph_vector_size(&tmp); j++) { long int edge = (long int) VECTOR(tmp)[j]; if (added_edges[edge] == 0) { igraph_integer_t from, to; igraph_edge(graph, (igraph_integer_t) edge, &from, &to); if (act_node == to) { to = from; } if (already_added[(long int) to] == 0) { already_added[(long int) to] = 1; added_edges[edge] = 1; IGRAPH_CHECK(igraph_vector_push_back(res, edge)); IGRAPH_CHECK(igraph_dqueue_push(&q, to)); } } } } } igraph_dqueue_destroy(&q); igraph_Free(already_added); igraph_vector_destroy(&tmp); igraph_Free(added_edges); IGRAPH_FINALLY_CLEAN(4); return IGRAPH_SUCCESS; } int igraph_i_minimum_spanning_tree_prim(const igraph_t* graph, igraph_vector_t* res, const igraph_vector_t *weights) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); char *already_added; char *added_edges; igraph_d_indheap_t heap = IGRAPH_D_INDHEAP_NULL; igraph_integer_t mode = IGRAPH_ALL; igraph_vector_t adj; long int i, j; igraph_vector_clear(res); if (weights == 0) { return igraph_i_minimum_spanning_tree_unweighted(graph, res); } if (igraph_vector_size(weights) != igraph_ecount(graph)) { IGRAPH_ERROR("Invalid weights length", IGRAPH_EINVAL); } added_edges = igraph_Calloc(no_of_edges, char); if (added_edges == 0) { IGRAPH_ERROR("prim spanning tree failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, added_edges); already_added = igraph_Calloc(no_of_nodes, char); if (already_added == 0) { IGRAPH_ERROR("prim spanning tree failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, already_added); IGRAPH_CHECK(igraph_d_indheap_init(&heap, 0)); IGRAPH_FINALLY(igraph_d_indheap_destroy, &heap); IGRAPH_VECTOR_INIT_FINALLY(&adj, 0); for (i = 0; i < no_of_nodes; i++) { if (already_added[i] > 0) { continue; } IGRAPH_ALLOW_INTERRUPTION(); already_added[i] = 1; /* add all edges of the first vertex */ igraph_incident(graph, &adj, (igraph_integer_t) i, (igraph_neimode_t) mode); for (j = 0; j < igraph_vector_size(&adj); j++) { long int edgeno = (long int) VECTOR(adj)[j]; igraph_integer_t edgefrom, edgeto; long int neighbor; igraph_edge(graph, (igraph_integer_t) edgeno, &edgefrom, &edgeto); neighbor = edgefrom != i ? edgefrom : edgeto; if (already_added[neighbor] == 0) { IGRAPH_CHECK(igraph_d_indheap_push(&heap, -VECTOR(*weights)[edgeno], i, edgeno)); } } while (! igraph_d_indheap_empty(&heap)) { /* Get minimal edge */ long int from, edge; igraph_integer_t tmp, to; igraph_d_indheap_max_index(&heap, &from, &edge); igraph_edge(graph, (igraph_integer_t) edge, &tmp, &to); /* Erase it */ igraph_d_indheap_delete_max(&heap); /* Is this edge already included? */ if (added_edges[edge] == 0) { if (from == to) { to = tmp; } /* Does it point to a visited node? */ if (already_added[(long int)to] == 0) { already_added[(long int)to] = 1; added_edges[edge] = 1; IGRAPH_CHECK(igraph_vector_push_back(res, edge)); /* add all outgoing edges */ igraph_incident(graph, &adj, to, (igraph_neimode_t) mode); for (j = 0; j < igraph_vector_size(&adj); j++) { long int edgeno = (long int) VECTOR(adj)[j]; igraph_integer_t edgefrom, edgeto; long int neighbor; igraph_edge(graph, (igraph_integer_t) edgeno, &edgefrom, &edgeto); neighbor = edgefrom != to ? edgefrom : edgeto; if (already_added[neighbor] == 0) { IGRAPH_CHECK(igraph_d_indheap_push(&heap, -VECTOR(*weights)[edgeno], to, edgeno)); } } } /* for */ } /* if !already_added */ } /* while in the same component */ } /* for all nodes */ igraph_d_indheap_destroy(&heap); igraph_Free(already_added); igraph_vector_destroy(&adj); igraph_Free(added_edges); IGRAPH_FINALLY_CLEAN(4); return IGRAPH_SUCCESS; } /* igraph_random_spanning_tree */ /* Loop-erased random walk (LERW) implementation. * res must be an initialized vector. The edge IDs of the spanning tree * will be added to the end of it. res will not be cleared before doing this. * * The walk is started from vertex start. comp_size must be the size of the connected * component containing start. */ static int igraph_i_lerw(const igraph_t *graph, igraph_vector_t *res, igraph_integer_t start, igraph_integer_t comp_size, igraph_vector_bool_t *visited, const igraph_inclist_t *il) { igraph_integer_t visited_count; IGRAPH_CHECK(igraph_vector_reserve(res, igraph_vector_size(res) + comp_size - 1)); RNG_BEGIN(); VECTOR(*visited)[start] = 1; visited_count = 1; while (visited_count < comp_size) { long degree, edge; igraph_vector_int_t *edges; edges = igraph_inclist_get(il, start); /* choose a random edge */ degree = igraph_vector_int_size(edges); edge = VECTOR(*edges)[ RNG_INTEGER(0, degree - 1) ]; /* set 'start' to the next vertex */ start = IGRAPH_OTHER(graph, edge, start); /* if the next vertex hasn't been visited yet, register the edge we just traversed */ if (! VECTOR(*visited)[start]) { IGRAPH_CHECK(igraph_vector_push_back(res, edge)); VECTOR(*visited)[start] = 1; visited_count++; } IGRAPH_ALLOW_INTERRUPTION(); } RNG_END(); return IGRAPH_SUCCESS; } /** * \function igraph_random_spanning_tree * \brief Uniformly sample the spanning trees of a graph * * Performs a loop-erased random walk on the graph to uniformly sample * its spanning trees. Edge directions are ignored. * * * Multi-graphs are supported, and edge multiplicities will affect the sampling * frequency. For example, consider the 3-cycle graph 1=2-3-1, with two edges * between vertices 1 and 2. Due to these parallel edges, the trees 1-2-3 * and 3-1-2 will be sampled with multiplicity 2, while the tree * 2-3-1 will be sampled with multiplicity 1. * * \param graph The input graph. Edge directions are ignored. * \param res An initialized vector, the IDs of the edges that constitute * a spanning tree will be returned here. Use * \ref igraph_subgraph_edges() to extract the spanning tree as * a separate graph object. * \param vid This parameter is relevant if the graph is not connected. * If negative, a random spanning forest of all components will be * generated. Otherwise, it should be the ID of a vertex. A random * spanning tree of the component containing the vertex will be * generated. * * \return Error code. * * \sa \ref igraph_minimum_spanning_tree(), \ref igraph_random_walk() * */ int igraph_random_spanning_tree(const igraph_t *graph, igraph_vector_t *res, igraph_integer_t vid) { igraph_inclist_t il; igraph_vector_bool_t visited; igraph_integer_t vcount = igraph_vcount(graph); if (vid >= vcount) { IGRAPH_ERROR("Invalid vertex id given for random spanning tree", IGRAPH_EINVVID); } IGRAPH_CHECK(igraph_inclist_init(graph, &il, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_inclist_destroy, &il); IGRAPH_CHECK(igraph_vector_bool_init(&visited, vcount)); IGRAPH_FINALLY(igraph_vector_bool_destroy, &visited); igraph_vector_clear(res); if (vid < 0) { /* generate random spanning forest: consider each component separately */ igraph_vector_t membership, csize; igraph_integer_t comp_count; igraph_integer_t i; IGRAPH_VECTOR_INIT_FINALLY(&membership, 0); IGRAPH_VECTOR_INIT_FINALLY(&csize, 0); IGRAPH_CHECK(igraph_clusters(graph, &membership, &csize, &comp_count, IGRAPH_WEAK)); /* for each component ... */ for (i = 0; i < comp_count; ++i) { /* ... find a vertex to start the LERW from */ igraph_integer_t j = 0; while (VECTOR(membership)[j] != i) { ++j; } IGRAPH_CHECK(igraph_i_lerw(graph, res, j, (igraph_integer_t) VECTOR(csize)[i], &visited, &il)); } igraph_vector_destroy(&membership); igraph_vector_destroy(&csize); IGRAPH_FINALLY_CLEAN(2); } else { /* consider the component containing vid */ igraph_vector_t comp_vertices; igraph_integer_t comp_size; /* we measure the size of the component */ IGRAPH_VECTOR_INIT_FINALLY(&comp_vertices, 0); IGRAPH_CHECK(igraph_subcomponent(graph, &comp_vertices, vid, IGRAPH_ALL)); comp_size = (igraph_integer_t) igraph_vector_size(&comp_vertices); igraph_vector_destroy(&comp_vertices); IGRAPH_FINALLY_CLEAN(1); IGRAPH_CHECK(igraph_i_lerw(graph, res, vid, comp_size, &visited, &il)); } igraph_vector_bool_destroy(&visited); igraph_inclist_destroy(&il); IGRAPH_FINALLY_CLEAN(2); return IGRAPH_SUCCESS; } python-igraph-0.8.0/vendor/source/igraph/src/gengraph_degree_sequence.h0000644000076500000240000000465613614300625026560 0ustar tamasstaff00000000000000/* * * gengraph - generation of random simple connected graphs with prescribed * degree sequence * * Copyright (C) 2006 Fabien Viger * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #ifndef DEGREE_SEQUENCE_H #define DEGREE_SEQUENCE_H #include "igraph_types.h" #include "igraph_datatype.h" namespace gengraph { class degree_sequence { private: int n; int * deg; int total; public : // #vertices inline int size() { return n; }; inline int sum() { return total; }; inline int operator[](int i) { return deg[i]; }; inline int *seq() { return deg; }; inline void assign(int n0, int* d0) { n = n0; deg = d0; }; inline int dmax() { int dm = deg[0]; for (int i = 1; i < n; i++) if (deg[i] > dm) { dm = deg[i]; } return dm; } void make_even(int mini = -1, int maxi = -1); void sort(); void shuffle(); // raw constructor degree_sequence(int n, int *degs); // read-from-file constrictor degree_sequence(FILE *f, bool DISTRIB = true); // simple power-law constructor : Pk = int((x+k0)^(-exp),x=k..k+1), with k0 so that avg(X)=z degree_sequence(int n, double exp, int degmin, int degmax, double avg_degree = -1.0); // igraph constructor degree_sequence(const igraph_vector_t *out_seq); // destructor ~degree_sequence(); // unbind the deg[] vector (so that it doesn't get deleted when the class is destroyed) void detach(); // compute total number of arcs void compute_total(); // raw print (vertex by vertex) void print(); // distribution print (degree frequency) void print_cumul(); // is degree sequence realizable ? bool havelhakimi(); }; } // namespace gengraph #endif //DEGREE_SEQUENCE_H python-igraph-0.8.0/vendor/source/igraph/src/flow.c0000644000076500000240000027733313614300625022530 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_flow.h" #include "igraph_error.h" #include "igraph_memory.h" #include "igraph_constants.h" #include "igraph_interface.h" #include "igraph_adjlist.h" #include "igraph_conversion.h" #include "igraph_constructors.h" #include "igraph_progress.h" #include "igraph_structural.h" #include "igraph_components.h" #include "igraph_types_internal.h" #include "config.h" #include "igraph_math.h" #include "igraph_dqueue.h" #include "igraph_visitor.h" #include "igraph_interrupt_internal.h" #include "igraph_topology.h" #include #include /* * Some general remarks about the functions in this file. * * The following measures can be calculated: * ( 1) s-t maximum flow value, directed graph * ( 2) s-t maximum flow value, undirected graph * ( 3) s-t maximum flow, directed graph * ( 4) s-t maximum flow, undirected graph * ( 5) s-t minimum cut value, directed graph * ( 6) s-t minimum cut value, undirected graph * ( 7) minimum cut value, directed graph * ( 8) minimum cut value, undirected graph * ( 9) s-t minimum cut, directed graph * (10) s-t minimum cut, undirected graph * (11) minimum cut, directed graph * (12) minimum cut, undirected graph * (13) s-t edge connectivity, directed graph * (14) s-t edge connectivity, undirected graph * (15) edge connectivity, directed graph * (16) edge connectivity, undirected graph * (17) s-t vertex connectivity, directed graph * (18) s-t vertex connectivity, undirected graph * (19) vertex connectivity, directed graph * (20) vertex connectivity, undirected graph * (21) s-t number of edge disjoint paths, directed graph * (22) s-t number of edge disjoint paths, undirected graph * (23) s-t number of vertex disjoint paths, directed graph * (24) s-t number of vertex disjoint paths, undirected graph * (25) graph adhesion, directed graph * (26) graph adhesion, undirected graph * (27) graph cohesion, directed graph * (28) graph cohesion, undirected graph * * This is how they are calculated: * ( 1) igraph_maxflow_value, calls igraph_maxflow. * ( 2) igraph_maxflow_value, calls igraph_maxflow, this calls * igraph_i_maxflow_undirected. This transforms the graph into a * directed graph, including two mutual edges instead of every * undirected edge, then igraph_maxflow is called again with the * directed graph. * ( 3) igraph_maxflow, does the push-relabel algorithm, optionally * calculates the cut, the partitions and the flow itself. * ( 4) igraph_maxflow calls igraph_i_maxflow_undirected, this converts * the undirected graph into a directed one, adding two mutual edges * for each undirected edge, then igraph_maxflow is called again, * with the directed graph. After igraph_maxflow returns, we need * to edit the flow (and the cut) to make it sense for the * original graph. * ( 5) igraph_st_mincut_value, we just call igraph_maxflow_value * ( 6) igraph_st_mincut_value, we just call igraph_maxflow_value * ( 7) igraph_mincut_value, we call igraph_maxflow_value (|V|-1)*2 * times, from vertex 0 to all other vertices and from all other * vertices to vertex 0 * ( 8) We call igraph_i_mincut_value_undirected, that calls * igraph_i_mincut_undirected with partition=partition2=cut=NULL * The Stoer-Wagner algorithm is used. * ( 9) igraph_st_mincut, just calls igraph_maxflow. * (10) igraph_st_mincut, just calls igraph_maxflow. * (11) igraph_mincut, calls igraph_i_mincut_directed, which runs * the maximum flow algorithm 2(|V|-1) times, from vertex zero to * and from all other vertices and stores the smallest cut. * (12) igraph_mincut, igraph_i_mincut_undirected is called, * this is the Stoer-Wagner algorithm * (13) We just call igraph_maxflow_value, back to (1) * (14) We just call igraph_maxflow_value, back to (2) * (15) We just call igraph_mincut_value (possibly after some basic * checks). Back to (7) * (16) We just call igraph_mincut_value (possibly after some basic * checks). Back to (8). * (17) We call igraph_i_st_vertex_connectivity_directed. * That creates a new graph with 2*|V| vertices and smartly chosen * edges, so that the s-t edge connectivity of this graph is the * same as the s-t vertex connectivity of the original graph. * So finally it calls igraph_maxflow_value, go to (1) * (18) We call igraph_i_st_vertex_connectivity_undirected. * We convert the graph to a directed one, * IGRAPH_TO_DIRECTED_MUTUAL method. Then we call * igraph_i_st_vertex_connectivity_directed, see (17). * (19) We call igraph_i_vertex_connectivity_directed. * That calls igraph_st_vertex_connectivity for all pairs of * vertices. Back to (17). * (20) We call igraph_i_vertex_connectivity_undirected. * That converts the graph into a directed one * (IGRAPH_TO_DIRECTED_MUTUAL) and calls the directed version, * igraph_i_vertex_connectivity_directed, see (19). * (21) igraph_edge_disjoint_paths, we just call igraph_maxflow_value, (1). * (22) igraph_edge_disjoint_paths, we just call igraph_maxflow_value, (2). * (23) igraph_vertex_disjoint_paths, if there is a connection between * the two vertices, then we remove that (or all of them if there * are many), as this could mess up vertex connectivity * calculation. The we call * igraph_i_st_vertex_connectivity_directed, see (19). * (24) igraph_vertex_disjoint_paths, if there is a connection between * the two vertices, then we remove that (or all of them if there * are many), as this could mess up vertex connectivity * calculation. The we call * igraph_i_st_vertex_connectivity_undirected, see (20). * (25) We just call igraph_edge_connectivity, see (15). * (26) We just call igraph_edge_connectivity, see (16). * (27) We just call igraph_vertex_connectivity, see (19). * (28) We just call igraph_vertex_connectivity, see (20). */ /* * This is an internal function that calculates the maximum flow value * on undirected graphs, either for an s-t vertex pair or for the * graph (i.e. all vertex pairs). * * It does it by converting the undirected graph to a corresponding * directed graph, including reciprocal directed edges instead of each * undirected edge. */ int igraph_i_maxflow_undirected(const igraph_t *graph, igraph_real_t *value, igraph_vector_t *flow, igraph_vector_t *cut, igraph_vector_t *partition, igraph_vector_t *partition2, igraph_integer_t source, igraph_integer_t target, const igraph_vector_t *capacity, igraph_maxflow_stats_t *stats) { igraph_integer_t no_of_edges = (igraph_integer_t) igraph_ecount(graph); igraph_integer_t no_of_nodes = (igraph_integer_t) igraph_vcount(graph); igraph_vector_t edges; igraph_vector_t newcapacity; igraph_t newgraph; long int i; /* We need to convert this to directed by hand, since we need to be sure that the edge ids will be handled properly to build the new capacity vector. */ IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_VECTOR_INIT_FINALLY(&newcapacity, no_of_edges * 2); IGRAPH_CHECK(igraph_vector_reserve(&edges, no_of_edges * 4)); IGRAPH_CHECK(igraph_get_edgelist(graph, &edges, 0)); IGRAPH_CHECK(igraph_vector_resize(&edges, no_of_edges * 4)); for (i = 0; i < no_of_edges; i++) { VECTOR(edges)[no_of_edges * 2 + i * 2] = VECTOR(edges)[i * 2 + 1]; VECTOR(edges)[no_of_edges * 2 + i * 2 + 1] = VECTOR(edges)[i * 2]; VECTOR(newcapacity)[i] = VECTOR(newcapacity)[no_of_edges + i] = capacity ? VECTOR(*capacity)[i] : 1.0; } IGRAPH_CHECK(igraph_create(&newgraph, &edges, no_of_nodes, IGRAPH_DIRECTED)); IGRAPH_FINALLY(igraph_destroy, &newgraph); IGRAPH_CHECK(igraph_maxflow(&newgraph, value, flow, cut, partition, partition2, source, target, &newcapacity, stats)); if (cut) { long int i, cs = igraph_vector_size(cut); for (i = 0; i < cs; i++) { if (VECTOR(*cut)[i] >= no_of_edges) { VECTOR(*cut)[i] -= no_of_edges; } } } /* The flow has one non-zero value for each real-nonreal edge pair, by definition, we convert it to a positive-negative vector. If for an edge the flow is negative that means that it is going from the bigger vertex id to the smaller one. For positive values the direction is the opposite. */ if (flow) { long int i; for (i = 0; i < no_of_edges; i++) { VECTOR(*flow)[i] -= VECTOR(*flow)[i + no_of_edges]; } IGRAPH_CHECK(igraph_vector_resize(flow, no_of_edges)); } igraph_destroy(&newgraph); igraph_vector_destroy(&edges); igraph_vector_destroy(&newcapacity); IGRAPH_FINALLY_CLEAN(3); return 0; } #define FIRST(i) (VECTOR(*first)[(i)]) #define LAST(i) (VECTOR(*first)[(i)+1]) #define CURRENT(i) (VECTOR(*current)[(i)]) #define RESCAP(i) (VECTOR(*rescap)[(i)]) #define REV(i) (VECTOR(*rev)[(i)]) #define HEAD(i) (VECTOR(*to)[(i)]) #define EXCESS(i) (VECTOR(*excess)[(i)]) #define DIST(i) (VECTOR(*distance)[(i)]) #define DISCHARGE(v) (igraph_i_mf_discharge((v), ¤t, &first, &rescap, \ &to, &distance, &excess, \ no_of_nodes, source, target, \ &buckets, &ibuckets, \ &rev, stats, &npushsince, \ &nrelabelsince)) #define PUSH(v,e,n) (igraph_i_mf_push((v), (e), (n), current, rescap, \ excess, target, source, buckets, \ ibuckets, distance, rev, stats, \ npushsince)) #define RELABEL(v) (igraph_i_mf_relabel((v), no_of_nodes, distance, \ first, rescap, to, current, \ stats, nrelabelsince)) #define GAP(b) (igraph_i_mf_gap((b), stats, buckets, ibuckets, \ no_of_nodes, distance)) #define BFS() (igraph_i_mf_bfs(&bfsq, source, target, no_of_nodes, \ &buckets, &ibuckets, &distance, \ &first, ¤t, &to, &excess, \ &rescap, &rev)) void igraph_i_mf_gap(long int b, igraph_maxflow_stats_t *stats, igraph_buckets_t *buckets, igraph_dbuckets_t *ibuckets, long int no_of_nodes, igraph_vector_long_t *distance) { long int bo; (stats->nogap)++; for (bo = b + 1; bo <= no_of_nodes; bo++) { while (!igraph_dbuckets_empty_bucket(ibuckets, bo)) { long int n = igraph_dbuckets_pop(ibuckets, bo); (stats->nogapnodes)++; DIST(n) = no_of_nodes; } } } void igraph_i_mf_relabel(long int v, long int no_of_nodes, igraph_vector_long_t *distance, igraph_vector_long_t *first, igraph_vector_t *rescap, igraph_vector_long_t *to, igraph_vector_long_t *current, igraph_maxflow_stats_t *stats, int *nrelabelsince) { long int min = no_of_nodes; long int k, l, min_edge = 0; (stats->norelabel)++; (*nrelabelsince)++; DIST(v) = no_of_nodes; for (k = FIRST(v), l = LAST(v); k < l; k++) { if (RESCAP(k) > 0 && DIST(HEAD(k)) < min) { min = DIST(HEAD(k)); min_edge = k; } } min++; if (min < no_of_nodes) { DIST(v) = min; CURRENT(v) = min_edge; } } void igraph_i_mf_push(long int v, long int e, long int n, igraph_vector_long_t *current, igraph_vector_t *rescap, igraph_vector_t *excess, long int target, long int source, igraph_buckets_t *buckets, igraph_dbuckets_t *ibuckets, igraph_vector_long_t *distance, igraph_vector_long_t *rev, igraph_maxflow_stats_t *stats, int *npushsince) { igraph_real_t delta = RESCAP(e) < EXCESS(v) ? RESCAP(e) : EXCESS(v); (stats->nopush)++; (*npushsince)++; if (EXCESS(n) == 0 && n != target) { igraph_dbuckets_delete(ibuckets, DIST(n), n); igraph_buckets_add(buckets, (long int) DIST(n), n); } RESCAP(e) -= delta; RESCAP(REV(e)) += delta; EXCESS(n) += delta; EXCESS(v) -= delta; } void igraph_i_mf_discharge(long int v, igraph_vector_long_t *current, igraph_vector_long_t *first, igraph_vector_t *rescap, igraph_vector_long_t *to, igraph_vector_long_t *distance, igraph_vector_t *excess, long int no_of_nodes, long int source, long int target, igraph_buckets_t *buckets, igraph_dbuckets_t *ibuckets, igraph_vector_long_t *rev, igraph_maxflow_stats_t *stats, int *npushsince, int *nrelabelsince) { do { long int i; long int start = (long int) CURRENT(v); long int stop = (long int) LAST(v); for (i = start; i < stop; i++) { if (RESCAP(i) > 0) { long int nei = HEAD(i); if (DIST(v) == DIST(nei) + 1) { PUSH((v), i, nei); if (EXCESS(v) == 0) { break; } } } } if (i == stop) { long int origdist = DIST(v); RELABEL(v); if (igraph_buckets_empty_bucket(buckets, origdist) && igraph_dbuckets_empty_bucket(ibuckets, origdist)) { GAP(origdist); } if (DIST(v) == no_of_nodes) { break; } } else { CURRENT(v) = i; igraph_dbuckets_add(ibuckets, DIST(v), v); break; } } while (1); } void igraph_i_mf_bfs(igraph_dqueue_long_t *bfsq, long int source, long int target, long int no_of_nodes, igraph_buckets_t *buckets, igraph_dbuckets_t *ibuckets, igraph_vector_long_t *distance, igraph_vector_long_t *first, igraph_vector_long_t *current, igraph_vector_long_t *to, igraph_vector_t *excess, igraph_vector_t *rescap, igraph_vector_long_t *rev) { long int k, l; igraph_buckets_clear(buckets); igraph_dbuckets_clear(ibuckets); igraph_vector_long_fill(distance, no_of_nodes); DIST(target) = 0; igraph_dqueue_long_push(bfsq, target); while (!igraph_dqueue_long_empty(bfsq)) { long int node = igraph_dqueue_long_pop(bfsq); long int ndist = DIST(node) + 1; for (k = FIRST(node), l = LAST(node); k < l; k++) { if (RESCAP(REV(k)) > 0) { long int nei = HEAD(k); if (DIST(nei) == no_of_nodes) { DIST(nei) = ndist; CURRENT(nei) = FIRST(nei); if (EXCESS(nei) > 0) { igraph_buckets_add(buckets, ndist, nei); } else { igraph_dbuckets_add(ibuckets, ndist, nei); } igraph_dqueue_long_push(bfsq, nei); } } } } } /** * \function igraph_maxflow * Maximum network flow between a pair of vertices * * This function implements the Goldberg-Tarjan algorithm for * calculating value of the maximum flow in a directed or undirected * graph. The algorithm was given in Andrew V. Goldberg, Robert * E. Tarjan: A New Approach to the Maximum-Flow Problem, Journal of * the ACM, 35(4), 921-940, 1988. * * The input of the function is a graph, a vector * of real numbers giving the capacity of the edges and two vertices * of the graph, the source and the target. A flow is a function * assigning positive real numbers to the edges and satisfying two * requirements: (1) the flow value is less than the capacity of the * edge and (2) at each vertex except the source and the target, the * incoming flow (ie. the sum of the flow on the incoming edges) is * the same as the outgoing flow (ie. the sum of the flow on the * outgoing edges). The value of the flow is the incoming flow at the * target vertex. The maximum flow is the flow with the maximum * value. * * \param graph The input graph, either directed or undirected. * \param value Pointer to a real number, the value of the maximum * will be placed here, unless it is a null pointer. * \param flow If not a null pointer, then it must be a pointer to an * initialized vector. The vector will be resized, and the flow * on each edge will be placed in it, in the order of the edge * ids. For undirected graphs this argument is bit trickier, * since for these the flow direction is not predetermined by * the edge direction. For these graphs the elements of the * \p flow vector can be negative, this means that the flow * goes from the bigger vertex id to the smaller one. Positive * values mean that the flow goes from the smaller vertex id to * the bigger one. * \param cut A null pointer or a pointer to an initialized vector. * If not a null pointer, then the minimum cut corresponding to * the maximum flow is stored here, i.e. all edge ids that are * part of the minimum cut are stored in the vector. * \param partition A null pointer or a pointer to an initialized * vector. If not a null pointer, then the first partition of * the minimum cut that corresponds to the maximum flow will be * placed here. The first partition is always the one that * contains the source vertex. * \param partition2 A null pointer or a pointer to an initialized * vector. If not a null pointer, then the second partition of * the minimum cut that corresponds to the maximum flow will be * placed here. The second partition is always the one that * contains the target vertex. * \param source The id of the source vertex. * \param target The id of the target vertex. * \param capacity Vector containing the capacity of the edges. If NULL, then * every edge is considered to have capacity 1.0. * \param stats Counts of the number of different operations * preformed by the algorithm are stored here. * \return Error code. * * Time complexity: O(|V|^3). In practice it is much faster, but i * cannot prove a better lower bound for the data structure i've * used. In fact, this implementation runs much faster than the * \c hi_pr implementation discussed in * B. V. Cherkassky and A. V. Goldberg: On implementing the * push-relabel method for the maximum flow problem, (Algorithmica, * 19:390--410, 1997) on all the graph classes i've tried. * * \sa \ref igraph_mincut_value(), \ref igraph_edge_connectivity(), * \ref igraph_vertex_connectivity() for * properties based on the maximum flow. * * \example examples/simple/flow.c * \example examples/simple/flow2.c */ int igraph_maxflow(const igraph_t *graph, igraph_real_t *value, igraph_vector_t *flow, igraph_vector_t *cut, igraph_vector_t *partition, igraph_vector_t *partition2, igraph_integer_t source, igraph_integer_t target, const igraph_vector_t *capacity, igraph_maxflow_stats_t *stats) { igraph_integer_t no_of_nodes = (igraph_integer_t) igraph_vcount(graph); igraph_integer_t no_of_orig_edges = (igraph_integer_t) igraph_ecount(graph); igraph_integer_t no_of_edges = 2 * no_of_orig_edges; igraph_vector_t rescap, excess; igraph_vector_long_t from, to, rev, distance; igraph_vector_t edges, rank; igraph_vector_long_t current, first; igraph_buckets_t buckets; igraph_dbuckets_t ibuckets; igraph_dqueue_long_t bfsq; long int i, j, idx; int npushsince = 0, nrelabelsince = 0; igraph_maxflow_stats_t local_stats; /* used if the user passed a null pointer for stats */ if (stats == 0) { stats = &local_stats; } if (!igraph_is_directed(graph)) { IGRAPH_CHECK(igraph_i_maxflow_undirected(graph, value, flow, cut, partition, partition2, source, target, capacity, stats)); return 0; } if (capacity && igraph_vector_size(capacity) != no_of_orig_edges) { IGRAPH_ERROR("Invalid capacity vector", IGRAPH_EINVAL); } if (source < 0 || source >= no_of_nodes || target < 0 || target >= no_of_nodes) { IGRAPH_ERROR("Invalid source or target vertex", IGRAPH_EINVAL); } stats->nopush = stats->norelabel = stats->nogap = stats->nogapnodes = stats->nobfs = 0; /* * The data structure: * - First of all, we consider every edge twice, first the edge * itself, but also its opposite. * - (from, to) contain all edges (original + opposite), ordered by * the id of the source vertex. During the algorithm we just need * 'to', so from is destroyed soon. We only need it in the * beginning, to create the 'first' pointers. * - 'first' is a pointer vector for 'to', first[i] points to the * first neighbor of vertex i and first[i+1]-1 is the last * neighbor of vertex i. (Unless vertex i is isolate, in which * case first[i]==first[i+1]). * - 'rev' contains a mapping from an edge to its opposite pair * - 'rescap' contains the residual capacities of the edges, this is * initially equal to the capacity of the edges for the original * edges and it is zero for the opposite edges. * - 'excess' contains the excess flow for the vertices. I.e. the flow * that is coming in, but it is not going out. * - 'current' stores the next neighboring vertex to check, for every * vertex, when excess flow is being pushed to neighbors. * - 'distance' stores the distance of the vertices from the source. * - 'rank' and 'edges' are only needed temporarily, for ordering and * storing the edges. * - we use an igraph_buckets_t data structure ('buckets') to find * the vertices with the highest 'distance' values quickly. * This always contains the vertices that have a positive excess * flow. */ #undef FIRST #undef LAST #undef CURRENT #undef RESCAP #undef REV #undef HEAD #undef EXCESS #undef DIST #define FIRST(i) (VECTOR(first)[(i)]) #define LAST(i) (VECTOR(first)[(i)+1]) #define CURRENT(i) (VECTOR(current)[(i)]) #define RESCAP(i) (VECTOR(rescap)[(i)]) #define REV(i) (VECTOR(rev)[(i)]) #define HEAD(i) (VECTOR(to)[(i)]) #define EXCESS(i) (VECTOR(excess)[(i)]) #define DIST(i) (VECTOR(distance)[(i)]) igraph_dqueue_long_init(&bfsq, no_of_nodes); IGRAPH_FINALLY(igraph_dqueue_long_destroy, &bfsq); IGRAPH_VECTOR_LONG_INIT_FINALLY(&to, no_of_edges); IGRAPH_VECTOR_LONG_INIT_FINALLY(&rev, no_of_edges); IGRAPH_VECTOR_INIT_FINALLY(&rescap, no_of_edges); IGRAPH_VECTOR_INIT_FINALLY(&excess, no_of_nodes); IGRAPH_VECTOR_LONG_INIT_FINALLY(&distance, no_of_nodes); IGRAPH_VECTOR_LONG_INIT_FINALLY(&first, no_of_nodes + 1); IGRAPH_VECTOR_INIT_FINALLY(&rank, no_of_edges); IGRAPH_VECTOR_LONG_INIT_FINALLY(&from, no_of_edges); IGRAPH_VECTOR_INIT_FINALLY(&edges, no_of_edges); /* Create the basic data structure */ IGRAPH_CHECK(igraph_get_edgelist(graph, &edges, 0)); IGRAPH_CHECK(igraph_vector_rank(&edges, &rank, no_of_nodes)); for (i = 0; i < no_of_edges; i += 2) { long int pos = (long int) VECTOR(rank)[i]; long int pos2 = (long int) VECTOR(rank)[i + 1]; VECTOR(from)[pos] = VECTOR(edges)[i]; VECTOR(to)[pos] = VECTOR(edges)[i + 1]; VECTOR(from)[pos2] = VECTOR(edges)[i + 1]; VECTOR(to)[pos2] = VECTOR(edges)[i]; VECTOR(rev)[pos] = pos2; VECTOR(rev)[pos2] = pos; VECTOR(rescap)[pos] = capacity ? VECTOR(*capacity)[i / 2] : 1.0; VECTOR(rescap)[pos2] = 0.0; } /* The first pointers. This is a but trickier, than one would think, because of the possible isolate vertices. */ idx = -1; for (i = 0; i <= VECTOR(from)[0]; i++) { idx++; VECTOR(first)[idx] = 0; } for (i = 1; i < no_of_edges; i++) { long int n = (long int) (VECTOR(from)[i] - VECTOR(from)[ (long int) VECTOR(first)[idx] ]); for (j = 0; j < n; j++) { idx++; VECTOR(first)[idx] = i; } } idx++; while (idx < no_of_nodes + 1) { VECTOR(first)[idx++] = no_of_edges; } igraph_vector_long_destroy(&from); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(2); if (!flow) { igraph_vector_destroy(&rank); IGRAPH_FINALLY_CLEAN(1); } /* And the current pointers, initially the same as the first */ IGRAPH_VECTOR_LONG_INIT_FINALLY(¤t, no_of_nodes); for (i = 0; i < no_of_nodes; i++) { VECTOR(current)[i] = VECTOR(first)[i]; } /* OK, the graph is set up, initialization */ IGRAPH_CHECK(igraph_buckets_init(&buckets, no_of_nodes + 1, no_of_nodes)); IGRAPH_FINALLY(igraph_buckets_destroy, &buckets); IGRAPH_CHECK(igraph_dbuckets_init(&ibuckets, no_of_nodes + 1, no_of_nodes)); IGRAPH_FINALLY(igraph_dbuckets_destroy, &ibuckets); /* Send as much flow as possible from the source to its neighbors */ for (i = FIRST(source), j = LAST(source); i < j; i++) { if (HEAD(i) != source) { igraph_real_t delta = RESCAP(i); RESCAP(i) = 0; RESCAP(REV(i)) += delta; EXCESS(HEAD(i)) += delta; } } BFS(); (stats->nobfs)++; while (!igraph_buckets_empty(&buckets)) { long int vertex = igraph_buckets_popmax(&buckets); DISCHARGE(vertex); if (npushsince > no_of_nodes / 2 && nrelabelsince > no_of_nodes) { (stats->nobfs)++; BFS(); npushsince = nrelabelsince = 0; } } /* Store the result */ if (value) { *value = EXCESS(target); } /* If we also need the minimum cut */ if (cut || partition || partition2) { /* We need to find all vertices from which the target is reachable in the residual graph. We do a breadth-first search, going backwards. */ igraph_dqueue_t Q; igraph_vector_bool_t added; long int marked = 0; IGRAPH_CHECK(igraph_vector_bool_init(&added, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_bool_destroy, &added); IGRAPH_CHECK(igraph_dqueue_init(&Q, 100)); IGRAPH_FINALLY(igraph_dqueue_destroy, &Q); igraph_dqueue_push(&Q, target); VECTOR(added)[(long int)target] = 1; marked++; while (!igraph_dqueue_empty(&Q)) { long int actnode = (long int) igraph_dqueue_pop(&Q); for (i = FIRST(actnode), j = LAST(actnode); i < j; i++) { long int nei = HEAD(i); if (!VECTOR(added)[nei] && RESCAP(REV(i)) > 0.0) { VECTOR(added)[nei] = 1; marked++; IGRAPH_CHECK(igraph_dqueue_push(&Q, nei)); } } } igraph_dqueue_destroy(&Q); IGRAPH_FINALLY_CLEAN(1); /* Now we marked each vertex that is on one side of the cut, check the crossing edges */ if (cut) { igraph_vector_clear(cut); for (i = 0; i < no_of_orig_edges; i++) { long int f = IGRAPH_FROM(graph, i); long int t = IGRAPH_TO(graph, i); if (!VECTOR(added)[f] && VECTOR(added)[t]) { IGRAPH_CHECK(igraph_vector_push_back(cut, i)); } } } if (partition2) { long int x = 0; IGRAPH_CHECK(igraph_vector_resize(partition2, marked)); for (i = 0; i < no_of_nodes; i++) { if (VECTOR(added)[i]) { VECTOR(*partition2)[x++] = i; } } } if (partition) { long int x = 0; IGRAPH_CHECK(igraph_vector_resize(partition, no_of_nodes - marked)); for (i = 0; i < no_of_nodes; i++) { if (!VECTOR(added)[i]) { VECTOR(*partition)[x++] = i; } } } igraph_vector_bool_destroy(&added); IGRAPH_FINALLY_CLEAN(1); } if (flow) { /* Initialize the backward distances, with a breadth-first search from the source */ igraph_dqueue_t Q; igraph_vector_int_t added; long int j, k, l; igraph_t flow_graph; igraph_vector_t flow_edges; igraph_bool_t dag; IGRAPH_CHECK(igraph_vector_int_init(&added, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_int_destroy, &added); IGRAPH_CHECK(igraph_dqueue_init(&Q, 100)); IGRAPH_FINALLY(igraph_dqueue_destroy, &added); igraph_dqueue_push(&Q, source); igraph_dqueue_push(&Q, 0); VECTOR(added)[(long int)source] = 1; while (!igraph_dqueue_empty(&Q)) { long int actnode = (long int) igraph_dqueue_pop(&Q); long int actdist = (long int) igraph_dqueue_pop(&Q); DIST(actnode) = actdist; for (i = FIRST(actnode), j = LAST(actnode); i < j; i++) { long int nei = HEAD(i); if (!VECTOR(added)[nei] && RESCAP(REV(i)) > 0.0) { VECTOR(added)[nei] = 1; IGRAPH_CHECK(igraph_dqueue_push(&Q, nei)); IGRAPH_CHECK(igraph_dqueue_push(&Q, actdist + 1)); } } } /* !igraph_dqueue_empty(&Q) */ igraph_vector_int_destroy(&added); igraph_dqueue_destroy(&Q); IGRAPH_FINALLY_CLEAN(2); /* Reinitialize the buckets */ igraph_buckets_clear(&buckets); for (i = 0; i < no_of_nodes; i++) { if (EXCESS(i) > 0.0 && i != source && i != target) { igraph_buckets_add(&buckets, (long int) DIST(i), i); } } /* Now we return the flow to the source */ while (!igraph_buckets_empty(&buckets)) { long int vertex = igraph_buckets_popmax(&buckets); /* DISCHARGE(vertex) comes here */ do { for (i = (long int) CURRENT(vertex), j = LAST(vertex); i < j; i++) { if (RESCAP(i) > 0) { long int nei = HEAD(i); if (DIST(vertex) == DIST(nei) + 1) { igraph_real_t delta = RESCAP(i) < EXCESS(vertex) ? RESCAP(i) : EXCESS(vertex); RESCAP(i) -= delta; RESCAP(REV(i)) += delta; if (nei != source && EXCESS(nei) == 0.0 && DIST(nei) != no_of_nodes) { igraph_buckets_add(&buckets, (long int) DIST(nei), nei); } EXCESS(nei) += delta; EXCESS(vertex) -= delta; if (EXCESS(vertex) == 0) { break; } } } } if (i == j) { /* RELABEL(vertex) comes here */ igraph_real_t min; long int min_edge = 0; DIST(vertex) = min = no_of_nodes; for (k = FIRST(vertex), l = LAST(vertex); k < l; k++) { if (RESCAP(k) > 0) { if (DIST(HEAD(k)) < min) { min = DIST(HEAD(k)); min_edge = k; } } } min++; if (min < no_of_nodes) { DIST(vertex) = min; CURRENT(vertex) = min_edge; /* Vertex is still active */ igraph_buckets_add(&buckets, (long int) DIST(vertex), vertex); } /* TODO: gap heuristics here ??? */ } else { CURRENT(vertex) = FIRST(vertex); } break; } while (1); } /* We need to eliminate flow cycles now. Before that we check that there is a cycle in the flow graph. First we do a couple of DFSes from the source vertex to the target and factor out the paths we find. If there is no more path to the target, then all remaining flow must be in flow cycles, so we don't need it at all. Some details. 'stack' contains the whole path of the DFS, both the vertices and the edges, they are alternating in the stack. 'current' helps finding the next outgoing edge of a vertex quickly, the next edge of 'v' is FIRST(v)+CURRENT(v). If this is LAST(v), then there are no more edges to try. The 'added' vector contains 0 if the vertex was not visited before, 1 if it is currently in 'stack', and 2 if it is not in 'stack', but it was visited before. */ IGRAPH_VECTOR_INIT_FINALLY(&flow_edges, 0); for (i = 0, j = 0; i < no_of_edges; i += 2, j++) { long int pos = (long int) VECTOR(rank)[i]; if ((capacity ? VECTOR(*capacity)[j] : 1.0) > RESCAP(pos)) { IGRAPH_CHECK(igraph_vector_push_back(&flow_edges, IGRAPH_FROM(graph, j))); IGRAPH_CHECK(igraph_vector_push_back(&flow_edges, IGRAPH_TO(graph, j))); } } IGRAPH_CHECK(igraph_create(&flow_graph, &flow_edges, no_of_nodes, IGRAPH_DIRECTED)); igraph_vector_destroy(&flow_edges); IGRAPH_FINALLY_CLEAN(1); IGRAPH_FINALLY(igraph_destroy, &flow_graph); IGRAPH_CHECK(igraph_is_dag(&flow_graph, &dag)); igraph_destroy(&flow_graph); IGRAPH_FINALLY_CLEAN(1); if (!dag) { igraph_vector_long_t stack; igraph_vector_t mycap; IGRAPH_CHECK(igraph_vector_long_init(&stack, 0)); IGRAPH_FINALLY(igraph_vector_long_destroy, &stack); IGRAPH_CHECK(igraph_vector_int_init(&added, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_int_destroy, &added); IGRAPH_VECTOR_INIT_FINALLY(&mycap, no_of_edges); #define MYCAP(i) (VECTOR(mycap)[(i)]) for (i = 0; i < no_of_edges; i += 2) { long int pos = (long int) VECTOR(rank)[i]; long int pos2 = (long int) VECTOR(rank)[i + 1]; MYCAP(pos) = (capacity ? VECTOR(*capacity)[i / 2] : 1.0) - RESCAP(pos); MYCAP(pos2) = 0.0; } do { igraph_vector_long_null(¤t); igraph_vector_long_clear(&stack); igraph_vector_int_null(&added); IGRAPH_CHECK(igraph_vector_long_push_back(&stack, -1)); IGRAPH_CHECK(igraph_vector_long_push_back(&stack, source)); VECTOR(added)[(long int)source] = 1; while (!igraph_vector_long_empty(&stack) && igraph_vector_long_tail(&stack) != target) { long int actnode = igraph_vector_long_tail(&stack); long int edge = FIRST(actnode) + (long int) CURRENT(actnode); long int nei; while (edge < LAST(actnode) && MYCAP(edge) == 0.0) { edge++; } nei = edge < LAST(actnode) ? HEAD(edge) : -1; if (edge < LAST(actnode) && !VECTOR(added)[nei]) { /* Go forward along next edge, if the vertex was not visited before */ IGRAPH_CHECK(igraph_vector_long_push_back(&stack, edge)); IGRAPH_CHECK(igraph_vector_long_push_back(&stack, nei)); VECTOR(added)[nei] = 1; CURRENT(actnode) += 1; } else if (edge < LAST(actnode) && VECTOR(added)[nei] == 1) { /* We found a flow cycle, factor it out. Go back in stack until we find 'nei' again, determine the flow along the cycle. */ igraph_real_t thisflow = MYCAP(edge); long int idx; for (idx = igraph_vector_long_size(&stack) - 2; idx >= 0 && VECTOR(stack)[idx + 1] != nei; idx -= 2) { long int e = VECTOR(stack)[idx]; igraph_real_t rcap = e >= 0 ? MYCAP(e) : MYCAP(edge); if (rcap < thisflow) { thisflow = rcap; } } MYCAP(edge) -= thisflow; RESCAP(edge) += thisflow; for (idx = igraph_vector_long_size(&stack) - 2; idx >= 0 && VECTOR(stack)[idx + 1] != nei; idx -= 2) { long int e = VECTOR(stack)[idx]; if (e >= 0) { MYCAP(e) -= thisflow; RESCAP(e) += thisflow; } } CURRENT(actnode) += 1; } else if (edge < LAST(actnode)) { /* && VECTOR(added)[nei]==2 */ /* The next edge leads to a vertex that was visited before, but it is currently not in 'stack' */ CURRENT(actnode) += 1; } else { /* Go backward, take out the node and the edge that leads to it */ igraph_vector_long_pop_back(&stack); igraph_vector_long_pop_back(&stack); VECTOR(added)[actnode] = 2; } } /* If non-empty, then it contains a path from source to target in the residual graph. We factor out this path from the flow. */ if (!igraph_vector_long_empty(&stack)) { long int pl = igraph_vector_long_size(&stack); igraph_real_t thisflow = EXCESS(target); for (i = 2; i < pl; i += 2) { long int edge = VECTOR(stack)[i]; igraph_real_t rcap = MYCAP(edge); if (rcap < thisflow) { thisflow = rcap; } } for (i = 2; i < pl; i += 2) { long int edge = VECTOR(stack)[i]; MYCAP(edge) -= thisflow; } } } while (!igraph_vector_long_empty(&stack)); igraph_vector_destroy(&mycap); igraph_vector_int_destroy(&added); igraph_vector_long_destroy(&stack); IGRAPH_FINALLY_CLEAN(3); } /* ----------------------------------------------------------- */ IGRAPH_CHECK(igraph_vector_resize(flow, no_of_orig_edges)); for (i = 0, j = 0; i < no_of_edges; i += 2, j++) { long int pos = (long int) VECTOR(rank)[i]; VECTOR(*flow)[j] = (capacity ? VECTOR(*capacity)[j] : 1.0) - RESCAP(pos); } igraph_vector_destroy(&rank); IGRAPH_FINALLY_CLEAN(1); } igraph_dbuckets_destroy(&ibuckets); igraph_buckets_destroy(&buckets); igraph_vector_long_destroy(¤t); igraph_vector_long_destroy(&first); igraph_vector_long_destroy(&distance); igraph_vector_destroy(&excess); igraph_vector_destroy(&rescap); igraph_vector_long_destroy(&rev); igraph_vector_long_destroy(&to); igraph_dqueue_long_destroy(&bfsq); IGRAPH_FINALLY_CLEAN(10); return 0; } /** * \function igraph_maxflow_value * \brief Maximum flow in a network with the push/relabel algorithm * * This function implements the Goldberg-Tarjan algorithm for * calculating value of the maximum flow in a directed or undirected * graph. The algorithm was given in Andrew V. Goldberg, Robert * E. Tarjan: A New Approach to the Maximum-Flow Problem, Journal of * the ACM, 35(4), 921-940, 1988. * * The input of the function is a graph, a vector * of real numbers giving the capacity of the edges and two vertices * of the graph, the source and the target. A flow is a function * assigning positive real numbers to the edges and satisfying two * requirements: (1) the flow value is less than the capacity of the * edge and (2) at each vertex except the source and the target, the * incoming flow (ie. the sum of the flow on the incoming edges) is * the same as the outgoing flow (ie. the sum of the flow on the * outgoing edges). The value of the flow is the incoming flow at the * target vertex. The maximum flow is the flow with the maximum * value. * * According to a theorem by Ford and Fulkerson * (L. R. Ford Jr. and D. R. Fulkerson. Maximal flow through a * network. Canadian J. Math., 8:399-404, 1956.) the maximum flow * between two vertices is the same as the * minimum cut between them (also called the minimum s-t cut). So \ref * igraph_st_mincut_value() gives the same result in all cases as \c * igraph_maxflow_value(). * * Note that the value of the maximum flow is the same as the * minimum cut in the graph. * \param graph The input graph, either directed or undirected. * \param value Pointer to a real number, the result will be placed here. * \param source The id of the source vertex. * \param target The id of the target vertex. * \param capacity Vector containing the capacity of the edges. If NULL, then * every edge is considered to have capacity 1.0. * \param stats Counts of the number of different operations * preformed by the algorithm are stored here. * \return Error code. * * Time complexity: O(|V|^3). * * \sa \ref igraph_maxflow() to calculate the actual flow. * \ref igraph_mincut_value(), \ref igraph_edge_connectivity(), * \ref igraph_vertex_connectivity() for * properties based on the maximum flow. */ int igraph_maxflow_value(const igraph_t *graph, igraph_real_t *value, igraph_integer_t source, igraph_integer_t target, const igraph_vector_t *capacity, igraph_maxflow_stats_t *stats) { return igraph_maxflow(graph, value, /*flow=*/ 0, /*cut=*/ 0, /*partition=*/ 0, /*partition1=*/ 0, source, target, capacity, stats); } /** * \function igraph_st_mincut_value * \brief The minimum s-t cut in a graph * * The minimum s-t cut in a weighted (=valued) graph is the * total minimum edge weight needed to remove from the graph to * eliminate all paths from a given vertex (\c source) to * another vertex (\c target). Directed paths are considered in * directed graphs, and undirected paths in undirected graphs. * * The minimum s-t cut between two vertices is known to be same * as the maximum flow between these two vertices. So this function * calls \ref igraph_maxflow_value() to do the calculation. * \param graph The input graph. * \param value Pointer to a real variable, the result will be stored * here. * \param source The id of the source vertex. * \param target The id of the target vertex. * \param capacity Pointer to the capacity vector, it should contain * non-negative numbers and its length should be the same the * the number of edges in the graph. It can be a null pointer, then * every edge has unit capacity. * \return Error code. * * Time complexity: O(|V|^3), see also the discussion for \ref * igraph_maxflow_value(), |V| is the number of vertices. */ int igraph_st_mincut_value(const igraph_t *graph, igraph_real_t *value, igraph_integer_t source, igraph_integer_t target, const igraph_vector_t *capacity) { if (source == target) { IGRAPH_ERROR("source and target vertices are the same", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_maxflow_value(graph, value, source, target, capacity, 0)); return 0; } /** * \function igraph_st_mincut * Minimum cut between a source and a target vertex * * Finds the edge set that has the smallest total capacity among all * edge sets that disconnect the source and target vertices. * * The calculation is performed using maximum flow * techniques, by calling \ref igraph_maxflow(). * \param graph The input graph. * \param value Pointer to a real variable, the value of the cut is * stored here. * \param cut Pointer to a real vector, the edge ids that are included * in the cut are stored here. This argument is ignored if it * is a null pointer. * \param partition Pointer to a real vector, the vertex ids of the * vertices in the first partition of the cut are stored * here. The first partition is always the one that contains the * source vertex. This argument is ignored if it is a null pointer. * \param partition2 Pointer to a real vector, the vertex ids of the * vertices in the second partition of the cut are stored here. * The second partition is always the one that contains the * target vertex. This argument is ignored if it is a null pointer. * \param source Integer, the id of the source vertex. * \param target Integer, the id of the target vertex. * \param capacity Vector containing the capacity of the edges. If a * null pointer, then every edge is considered to have capacity * 1.0. * \return Error code. * * \sa \ref igraph_maxflow(). * * Time complexity: see \ref igraph_maxflow(). */ int igraph_st_mincut(const igraph_t *graph, igraph_real_t *value, igraph_vector_t *cut, igraph_vector_t *partition, igraph_vector_t *partition2, igraph_integer_t source, igraph_integer_t target, const igraph_vector_t *capacity) { return igraph_maxflow(graph, value, /*flow=*/ 0, cut, partition, partition2, source, target, capacity, 0); } /* This is a flow-based version, but there is a better one for undirected graphs */ /* int igraph_i_mincut_value_undirected(const igraph_t *graph, */ /* igraph_real_t *res, */ /* const igraph_vector_t *capacity) { */ /* long int no_of_edges=igraph_ecount(graph); */ /* long int no_of_nodes=igraph_vcount(graph); */ /* igraph_vector_t edges; */ /* igraph_vector_t newcapacity; */ /* igraph_t newgraph; */ /* long int i; */ /* /\* We need to convert this to directed by hand, since we need to be */ /* sure that the edge ids will be handled properly to build the new */ /* capacity vector. *\/ */ /* IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); */ /* IGRAPH_VECTOR_INIT_FINALLY(&newcapacity, no_of_edges*2); */ /* IGRAPH_CHECK(igraph_vector_reserve(&edges, no_of_edges*4)); */ /* IGRAPH_CHECK(igraph_get_edgelist(graph, &edges, 0)); */ /* IGRAPH_CHECK(igraph_vector_resize(&edges, no_of_edges*4)); */ /* for (i=0; i= 2) { long int last; igraph_real_t acut; long int a, n; igraph_vector_int_t *edges, *edges2; igraph_vector_int_t *neis, *neis2; do { a = igraph_i_cutheap_popmax(&heap); /* update the weights of the active vertices connected to a */ edges = igraph_inclist_get(&inclist, a); neis = igraph_adjlist_get(&adjlist, a); n = igraph_vector_int_size(edges); for (i = 0; i < n; i++) { igraph_integer_t edge = (igraph_integer_t) VECTOR(*edges)[i]; igraph_integer_t to = (igraph_integer_t) VECTOR(*neis)[i]; igraph_real_t weight = capacity ? VECTOR(*capacity)[(long int)edge] : 1.0; igraph_i_cutheap_update(&heap, to, weight); } } while (igraph_i_cutheap_active_size(&heap) > 1); /* Now, there is only one active vertex left, calculate the cut of the phase */ acut = igraph_i_cutheap_maxvalue(&heap); last = igraph_i_cutheap_popmax(&heap); if (acut < mincut) { mincut = acut; mincut_step = act_step; } if (mincut == 0) { break; } /* And contract the last and the remaining vertex (a and last) */ /* Before actually doing that, make some notes */ act_step++; if (calc_cut) { IGRAPH_CHECK(igraph_vector_push_back(&mergehist, a)); IGRAPH_CHECK(igraph_vector_push_back(&mergehist, last)); } /* First remove the a--last edge if there is one, a is still the last deactivated vertex */ edges = igraph_inclist_get(&inclist, a); neis = igraph_adjlist_get(&adjlist, a); n = igraph_vector_int_size(edges); for (i = 0; i < n; ) { if (VECTOR(*neis)[i] == last) { VECTOR(*neis)[i] = VECTOR(*neis)[n - 1]; VECTOR(*edges)[i] = VECTOR(*edges)[n - 1]; igraph_vector_int_pop_back(neis); igraph_vector_int_pop_back(edges); n--; } else { i++; } } edges = igraph_inclist_get(&inclist, last); neis = igraph_adjlist_get(&adjlist, last); n = igraph_vector_int_size(edges); for (i = 0; i < n; ) { if (VECTOR(*neis)[i] == a) { VECTOR(*neis)[i] = VECTOR(*neis)[n - 1]; VECTOR(*edges)[i] = VECTOR(*edges)[n - 1]; igraph_vector_int_pop_back(neis); igraph_vector_int_pop_back(edges); n--; } else { i++; } } /* Now rewrite the edge lists of last's neighbors */ neis = igraph_adjlist_get(&adjlist, last); n = igraph_vector_int_size(neis); for (i = 0; i < n; i++) { igraph_integer_t nei = (igraph_integer_t) VECTOR(*neis)[i]; long int n2, j; neis2 = igraph_adjlist_get(&adjlist, nei); n2 = igraph_vector_int_size(neis2); for (j = 0; j < n2; j++) { if (VECTOR(*neis2)[j] == last) { VECTOR(*neis2)[j] = a; } } } /* And append the lists of last to the lists of a */ edges = igraph_inclist_get(&inclist, a); neis = igraph_adjlist_get(&adjlist, a); edges2 = igraph_inclist_get(&inclist, last); neis2 = igraph_adjlist_get(&adjlist, last); IGRAPH_CHECK(igraph_vector_int_append(edges, edges2)); IGRAPH_CHECK(igraph_vector_int_append(neis, neis2)); igraph_vector_int_clear(edges2); /* TODO: free it */ igraph_vector_int_clear(neis2); /* TODO: free it */ /* Remove the deleted vertex from the heap entirely */ igraph_i_cutheap_reset_undefine(&heap, last); } *res = mincut; igraph_inclist_destroy(&inclist); igraph_adjlist_destroy(&adjlist); igraph_i_cutheap_destroy(&heap); IGRAPH_FINALLY_CLEAN(3); if (calc_cut) { long int bignode = (long int) VECTOR(mergehist)[2 * mincut_step + 1]; long int i, idx; long int size = 1; char *mark; mark = igraph_Calloc(no_of_nodes, char); if (!mark) { IGRAPH_ERROR("Not enough memory for minimum cut", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, mark); /* first count the vertices in the partition */ mark[bignode] = 1; for (i = mincut_step - 1; i >= 0; i--) { if ( mark[ (long int) VECTOR(mergehist)[2 * i] ] ) { size++; mark [ (long int) VECTOR(mergehist)[2 * i + 1] ] = 1; } } /* now store them, if requested */ if (partition) { IGRAPH_CHECK(igraph_vector_resize(partition, size)); idx = 0; VECTOR(*partition)[idx++] = bignode; for (i = mincut_step - 1; i >= 0; i--) { if (mark[ (long int) VECTOR(mergehist)[2 * i] ]) { VECTOR(*partition)[idx++] = VECTOR(mergehist)[2 * i + 1]; } } } /* The other partition too? */ if (partition2) { IGRAPH_CHECK(igraph_vector_resize(partition2, no_of_nodes - size)); idx = 0; for (i = 0; i < no_of_nodes; i++) { if (!mark[i]) { VECTOR(*partition2)[idx++] = i; } } } /* The edges in the cut are also requested? */ /* We want as few memory allocated for 'cut' as possible, so we first collect the edges in mergehist, we don't need that anymore. Then we copy it to 'cut'; */ if (cut) { igraph_integer_t from, to; igraph_vector_clear(&mergehist); for (i = 0; i < no_of_edges; i++) { igraph_edge(graph, (igraph_integer_t) i, &from, &to); if ((mark[(long int)from] && !mark[(long int)to]) || (mark[(long int)to] && !mark[(long int)from])) { IGRAPH_CHECK(igraph_vector_push_back(&mergehist, i)); } } igraph_vector_clear(cut); IGRAPH_CHECK(igraph_vector_append(cut, &mergehist)); } igraph_free(mark); igraph_vector_destroy(&mergehist); IGRAPH_FINALLY_CLEAN(2); } return 0; } int igraph_i_mincut_directed(const igraph_t *graph, igraph_real_t *value, igraph_vector_t *partition, igraph_vector_t *partition2, igraph_vector_t *cut, const igraph_vector_t *capacity) { long int i; long int no_of_nodes = igraph_vcount(graph); igraph_real_t flow; igraph_real_t minmaxflow = IGRAPH_INFINITY; igraph_vector_t mypartition, mypartition2, mycut; igraph_vector_t *ppartition = 0, *ppartition2 = 0, *pcut = 0; igraph_vector_t bestpartition, bestpartition2, bestcut; if (partition) { IGRAPH_VECTOR_INIT_FINALLY(&bestpartition, 0); } if (partition2) { IGRAPH_VECTOR_INIT_FINALLY(&bestpartition2, 0); } if (cut) { IGRAPH_VECTOR_INIT_FINALLY(&bestcut, 0); } if (partition) { IGRAPH_VECTOR_INIT_FINALLY(&mypartition, 0); ppartition = &mypartition; } if (partition2) { IGRAPH_VECTOR_INIT_FINALLY(&mypartition2, 0); ppartition2 = &mypartition2; } if (cut) { IGRAPH_VECTOR_INIT_FINALLY(&mycut, 0); pcut = &mycut; } for (i = 1; i < no_of_nodes; i++) { IGRAPH_CHECK(igraph_maxflow(graph, /*value=*/ &flow, /*flow=*/ 0, pcut, ppartition, ppartition2, /*source=*/ 0, /*target=*/ (igraph_integer_t) i, capacity, 0)); if (flow < minmaxflow) { minmaxflow = flow; if (cut) { IGRAPH_CHECK(igraph_vector_update(&bestcut, &mycut)); } if (partition) { IGRAPH_CHECK(igraph_vector_update(&bestpartition, &mypartition)); } if (partition2) { IGRAPH_CHECK(igraph_vector_update(&bestpartition2, &mypartition2)); } if (minmaxflow == 0) { break; } } IGRAPH_CHECK(igraph_maxflow(graph, /*value=*/ &flow, /*flow=*/ 0, pcut, ppartition, ppartition2, /*source=*/ (igraph_integer_t) i, /*target=*/ 0, capacity, 0)); if (flow < minmaxflow) { minmaxflow = flow; if (cut) { IGRAPH_CHECK(igraph_vector_update(&bestcut, &mycut)); } if (partition) { IGRAPH_CHECK(igraph_vector_update(&bestpartition, &mypartition)); } if (partition2) { IGRAPH_CHECK(igraph_vector_update(&bestpartition2, &mypartition2)); } if (minmaxflow == 0) { break; } } } if (value) { *value = minmaxflow; } if (cut) { igraph_vector_destroy(&mycut); IGRAPH_FINALLY_CLEAN(1); } if (partition) { igraph_vector_destroy(&mypartition); IGRAPH_FINALLY_CLEAN(1); } if (partition2) { igraph_vector_destroy(&mypartition2); IGRAPH_FINALLY_CLEAN(1); } if (cut) { IGRAPH_CHECK(igraph_vector_update(cut, &bestcut)); igraph_vector_destroy(&bestcut); IGRAPH_FINALLY_CLEAN(1); } if (partition2) { IGRAPH_CHECK(igraph_vector_update(partition2, &bestpartition2)); igraph_vector_destroy(&bestpartition2); IGRAPH_FINALLY_CLEAN(1); } if (partition) { IGRAPH_CHECK(igraph_vector_update(partition, &bestpartition)); igraph_vector_destroy(&bestpartition); IGRAPH_FINALLY_CLEAN(1); } return 0; } /** * \function igraph_mincut * \brief Calculates the minimum cut in a graph. * * This function calculates the minimum cut in a graph. * The minimum cut is the minimum set of edges which needs to be * removed to disconnect the graph. The minimum is calculated using * the weights (\p capacity) of the edges, so the cut with the minimum * total capacity is calculated. * * For directed graphs an implementation based on * calculating 2|V|-2 maximum flows is used. * For undirected graphs we use the Stoer-Wagner * algorithm, as described in M. Stoer and F. Wagner: A simple min-cut * algorithm, Journal of the ACM, 44 585-591, 1997. * * * The first implementation of the actual cut calculation for * undirected graphs was made by Gregory Benison, thanks Greg. * \param graph The input graph. * \param value Pointer to a float, the value of the cut will be * stored here. * \param partition Pointer to an initialized vector, the ids * of the vertices in the first partition after separating the * graph will be stored here. The vector will be resized as * needed. This argument is ignored if it is a NULL pointer. * \param partition2 Pointer to an initialized vector the ids * of the vertices in the second partition will be stored here. * The vector will be resized as needed. This argument is ignored * if it is a NULL pointer. * \param cut Pointer to an initialized vector, the ids of the edges * in the cut will be stored here. This argument is ignored if it * is a NULL pointer. * \param capacity A numeric vector giving the capacities of the * edges. If a null pointer then all edges have unit capacity. * \return Error code. * * \sa \ref igraph_mincut_value(), a simpler interface for calculating * the value of the cut only. * * Time complexity: for directed graphs it is O(|V|^4), but see the * remarks at \ref igraph_maxflow(). For undirected graphs it is * O(|V||E|+|V|^2 log|V|). |V| and |E| are the number of vertices and * edges respectively. * * \example examples/simple/igraph_mincut.c */ int igraph_mincut(const igraph_t *graph, igraph_real_t *value, igraph_vector_t *partition, igraph_vector_t *partition2, igraph_vector_t *cut, const igraph_vector_t *capacity) { if (igraph_is_directed(graph)) { if (partition || partition2 || cut) { igraph_i_mincut_directed(graph, value, partition, partition2, cut, capacity); } else { return igraph_mincut_value(graph, value, capacity); } } else { IGRAPH_CHECK(igraph_i_mincut_undirected(graph, value, partition, partition2, cut, capacity)); return IGRAPH_SUCCESS; } return 0; } int igraph_i_mincut_value_undirected(const igraph_t *graph, igraph_real_t *res, const igraph_vector_t *capacity) { return igraph_i_mincut_undirected(graph, res, 0, 0, 0, capacity); } /** * \function igraph_mincut_value * \brief The minimum edge cut in a graph * * The minimum edge cut in a graph is the total minimum * weight of the edges needed to remove from the graph to make the * graph \em not strongly connected. (If the original graph is not * strongly connected then this is zero.) Note that in undirected * graphs strong connectedness is the same as weak connectedness. * * The minimum cut can be calculated with maximum flow * techniques, although the current implementation does this only for * directed graphs and a separate non-flow based implementation is * used for undirected graphs. See Mechthild Stoer and Frank Wagner: A * simple min-cut algorithm, Journal of the ACM 44 585--591, 1997. * For directed graphs * the maximum flow is calculated between a fixed vertex and all the * other vertices in the graph and this is done in both * directions. Then the minimum is taken to get the minimum cut. * * \param graph The input graph. * \param res Pointer to a real variable, the result will be stored * here. * \param capacity Pointer to the capacity vector, it should contain * the same number of non-negative numbers as the number of edges in * the graph. If a null pointer then all edges will have unit capacity. * \return Error code. * * \sa \ref igraph_mincut(), \ref igraph_maxflow_value(), \ref * igraph_st_mincut_value(). * * Time complexity: O(log(|V|)*|V|^2) for undirected graphs and * O(|V|^4) for directed graphs, but see also the discussion at the * documentation of \ref igraph_maxflow_value(). */ int igraph_mincut_value(const igraph_t *graph, igraph_real_t *res, const igraph_vector_t *capacity) { long int no_of_nodes = igraph_vcount(graph); igraph_real_t minmaxflow, flow; long int i; minmaxflow = IGRAPH_INFINITY; if (!igraph_is_directed(graph)) { IGRAPH_CHECK(igraph_i_mincut_value_undirected(graph, res, capacity)); return 0; } for (i = 1; i < no_of_nodes; i++) { IGRAPH_CHECK(igraph_maxflow_value(graph, &flow, 0, (igraph_integer_t) i, capacity, 0)); if (flow < minmaxflow) { minmaxflow = flow; if (flow == 0) { break; } } IGRAPH_CHECK(igraph_maxflow_value(graph, &flow, (igraph_integer_t) i, 0, capacity, 0)); if (flow < minmaxflow) { minmaxflow = flow; if (flow == 0) { break; } } } if (res) { *res = minmaxflow; } return 0; } int igraph_i_st_vertex_connectivity_directed(const igraph_t *graph, igraph_integer_t *res, igraph_integer_t source, igraph_integer_t target, igraph_vconn_nei_t neighbors) { igraph_integer_t no_of_nodes = (igraph_integer_t) igraph_vcount(graph); igraph_integer_t no_of_edges = (igraph_integer_t) igraph_ecount(graph); igraph_vector_t edges; igraph_real_t real_res; igraph_t newgraph; long int i; igraph_bool_t conn1; if (source < 0 || source >= no_of_nodes || target < 0 || target >= no_of_nodes) { IGRAPH_ERROR("Invalid source or target vertex", IGRAPH_EINVAL); } switch (neighbors) { case IGRAPH_VCONN_NEI_ERROR: IGRAPH_CHECK(igraph_are_connected(graph, source, target, &conn1)); if (conn1) { IGRAPH_ERROR("vertices connected", IGRAPH_EINVAL); return 0; } break; case IGRAPH_VCONN_NEI_NEGATIVE: IGRAPH_CHECK(igraph_are_connected(graph, source, target, &conn1)); if (conn1) { *res = -1; return 0; } break; case IGRAPH_VCONN_NEI_NUMBER_OF_NODES: IGRAPH_CHECK(igraph_are_connected(graph, source, target, &conn1)); if (conn1) { *res = no_of_nodes; return 0; } break; case IGRAPH_VCONN_NEI_IGNORE: break; default: IGRAPH_ERROR("Unknown `igraph_vconn_nei_t'", IGRAPH_EINVAL); break; } /* Create the new graph */ IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_CHECK(igraph_vector_reserve(&edges, 2 * (no_of_edges + no_of_nodes))); IGRAPH_CHECK(igraph_get_edgelist(graph, &edges, 0)); IGRAPH_CHECK(igraph_vector_resize(&edges, 2 * (no_of_edges + no_of_nodes))); for (i = 0; i < 2 * no_of_edges; i += 2) { igraph_integer_t to = (igraph_integer_t) VECTOR(edges)[i + 1]; if (to != source && to != target) { VECTOR(edges)[i + 1] = no_of_nodes + to; } } for (i = 0; i < no_of_nodes; i++) { VECTOR(edges)[ 2 * (no_of_edges + i) ] = no_of_nodes + i; VECTOR(edges)[ 2 * (no_of_edges + i) + 1 ] = i; } IGRAPH_CHECK(igraph_create(&newgraph, &edges, 2 * no_of_nodes, igraph_is_directed(graph))); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); IGRAPH_FINALLY(igraph_destroy, &newgraph); /* Do the maximum flow */ no_of_nodes = igraph_vcount(&newgraph); no_of_edges = igraph_ecount(&newgraph); IGRAPH_CHECK(igraph_maxflow_value(&newgraph, &real_res, source, target, 0, 0)); *res = (igraph_integer_t)real_res; igraph_destroy(&newgraph); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_i_st_vertex_connectivity_undirected(const igraph_t *graph, igraph_integer_t *res, igraph_integer_t source, igraph_integer_t target, igraph_vconn_nei_t neighbors) { igraph_integer_t no_of_nodes = (igraph_integer_t) igraph_vcount(graph); igraph_t newgraph; igraph_bool_t conn; if (source < 0 || source >= no_of_nodes || target < 0 || target >= no_of_nodes) { IGRAPH_ERROR("Invalid source or target vertex", IGRAPH_EINVAL); } switch (neighbors) { case IGRAPH_VCONN_NEI_ERROR: IGRAPH_CHECK(igraph_are_connected(graph, source, target, &conn)); if (conn) { IGRAPH_ERROR("vertices connected", IGRAPH_EINVAL); return 0; } break; case IGRAPH_VCONN_NEI_NEGATIVE: IGRAPH_CHECK(igraph_are_connected(graph, source, target, &conn)); if (conn) { *res = -1; return 0; } break; case IGRAPH_VCONN_NEI_NUMBER_OF_NODES: IGRAPH_CHECK(igraph_are_connected(graph, source, target, &conn)); if (conn) { *res = no_of_nodes; return 0; } break; case IGRAPH_VCONN_NEI_IGNORE: break; default: IGRAPH_ERROR("Unknown `igraph_vconn_nei_t'", IGRAPH_EINVAL); break; } IGRAPH_CHECK(igraph_copy(&newgraph, graph)); IGRAPH_FINALLY(igraph_destroy, &newgraph); IGRAPH_CHECK(igraph_to_directed(&newgraph, IGRAPH_TO_DIRECTED_MUTUAL)); IGRAPH_CHECK(igraph_i_st_vertex_connectivity_directed(&newgraph, res, source, target, IGRAPH_VCONN_NEI_IGNORE)); igraph_destroy(&newgraph); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_st_vertex_connectivity * \brief The vertex connectivity of a pair of vertices * * The vertex connectivity of two vertices (\c source and * \c target) is the minimum number of vertices that have to be * deleted to eliminate all paths from \c source to \c * target. Directed paths are considered in directed graphs. * * The vertex connectivity of a pair is the same as the number * of different (ie. node-independent) paths from source to * target. * * The current implementation uses maximum flow calculations to * obtain the result. * \param graph The input graph. * \param res Pointer to an integer, the result will be stored here. * \param source The id of the source vertex. * \param target The id of the target vertex. * \param neighbors A constant giving what to do if the two vertices * are connected. Possible values: * \c IGRAPH_VCONN_NEI_ERROR, stop with an error message, * \c IGRAPH_VCONN_NEGATIVE, return -1. * \c IGRAPH_VCONN_NUMBER_OF_NODES, return the number of nodes. * \c IGRAPH_VCONN_IGNORE, ignore the fact that the two vertices * are connected and calculated the number of vertices needed * to eliminate all paths except for the trivial (direct) paths * between \c source and \c vertex. TOOD: what about neighbors? * \return Error code. * * Time complexity: O(|V|^3), but see the discussion at \ref * igraph_maxflow_value(). * * \sa \ref igraph_vertex_connectivity(), * \ref igraph_edge_connectivity(), * \ref igraph_maxflow_value(). */ int igraph_st_vertex_connectivity(const igraph_t *graph, igraph_integer_t *res, igraph_integer_t source, igraph_integer_t target, igraph_vconn_nei_t neighbors) { if (source == target) { IGRAPH_ERROR("source and target vertices are the same", IGRAPH_EINVAL); } if (igraph_is_directed(graph)) { IGRAPH_CHECK(igraph_i_st_vertex_connectivity_directed(graph, res, source, target, neighbors)); } else { IGRAPH_CHECK(igraph_i_st_vertex_connectivity_undirected(graph, res, source, target, neighbors)); } return 0; } int igraph_i_vertex_connectivity_directed(const igraph_t *graph, igraph_integer_t *res) { igraph_integer_t no_of_nodes = (igraph_integer_t) igraph_vcount(graph); long int i, j; igraph_integer_t minconn = no_of_nodes - 1, conn; for (i = 0; i < no_of_nodes; i++) { for (j = 0; j < no_of_nodes; j++) { if (i == j) { continue; } IGRAPH_ALLOW_INTERRUPTION(); IGRAPH_CHECK(igraph_st_vertex_connectivity(graph, &conn, (igraph_integer_t) i, (igraph_integer_t) j, IGRAPH_VCONN_NEI_NUMBER_OF_NODES)); if (conn < minconn) { minconn = conn; if (conn == 0) { break; } } } if (conn == 0) { break; } } if (res) { *res = minconn; } return 0; } int igraph_i_vertex_connectivity_undirected(const igraph_t *graph, igraph_integer_t *res) { igraph_t newgraph; IGRAPH_CHECK(igraph_copy(&newgraph, graph)); IGRAPH_FINALLY(igraph_destroy, &newgraph); IGRAPH_CHECK(igraph_to_directed(&newgraph, IGRAPH_TO_DIRECTED_MUTUAL)); IGRAPH_CHECK(igraph_i_vertex_connectivity_directed(&newgraph, res)); igraph_destroy(&newgraph); IGRAPH_FINALLY_CLEAN(1); return 0; } /* Use that vertex.connectivity(G) <= edge.connectivity(G) <= min(degree(G)) */ int igraph_i_connectivity_checks(const igraph_t *graph, igraph_integer_t *res, igraph_bool_t *found) { igraph_bool_t conn; *found = 0; if (igraph_vcount(graph) == 0) { *res = 0; *found = 1; return 0; } IGRAPH_CHECK(igraph_is_connected(graph, &conn, IGRAPH_STRONG)); if (!conn) { *res = 0; *found = 1; } else { igraph_vector_t degree; IGRAPH_VECTOR_INIT_FINALLY(°ree, 0); if (!igraph_is_directed(graph)) { IGRAPH_CHECK(igraph_degree(graph, °ree, igraph_vss_all(), IGRAPH_OUT, IGRAPH_LOOPS)); if (igraph_vector_min(°ree) == 1) { *res = 1; *found = 1; } } else { /* directed, check both in- & out-degree */ IGRAPH_CHECK(igraph_degree(graph, °ree, igraph_vss_all(), IGRAPH_OUT, IGRAPH_LOOPS)); if (igraph_vector_min(°ree) == 1) { *res = 1; *found = 1; } else { IGRAPH_CHECK(igraph_degree(graph, °ree, igraph_vss_all(), IGRAPH_IN, IGRAPH_LOOPS)); if (igraph_vector_min(°ree) == 1) { *res = 1; *found = 1; } } } igraph_vector_destroy(°ree); IGRAPH_FINALLY_CLEAN(1); } return 0; } /** * \function igraph_vertex_connectivity * The vertex connectivity of a graph * * The vertex connectivity of a graph is the minimum * vertex connectivity along each pairs of vertices in the graph. * * The vertex connectivity of a graph is the same as group * cohesion as defined in Douglas R. White and Frank Harary: The * cohesiveness of blocks in social networks: node connectivity and * conditional density, Sociological Methodology 31:305--359, 2001. * \param graph The input graph. * \param res Pointer to an integer, the result will be stored here. * \param checks Logical constant. Whether to check that the graph is * connected and also the degree of the vertices. If the graph is * not (strongly) connected then the connectivity is obviously zero. Otherwise * if the minimum degree is one then the vertex connectivity is also * one. It is a good idea to perform these checks, as they can be * done quickly compared to the connectivity calculation itself. * They were suggested by Peter McMahan, thanks Peter. * \return Error code. * * Time complexity: O(|V|^5). * * \sa \ref igraph_st_vertex_connectivity(), \ref igraph_maxflow_value(), * and \ref igraph_edge_connectivity(). */ int igraph_vertex_connectivity(const igraph_t *graph, igraph_integer_t *res, igraph_bool_t checks) { igraph_bool_t ret = 0; if (checks) { IGRAPH_CHECK(igraph_i_connectivity_checks(graph, res, &ret)); } /* Are we done yet? */ if (!ret) { if (igraph_is_directed(graph)) { IGRAPH_CHECK(igraph_i_vertex_connectivity_directed(graph, res)); } else { IGRAPH_CHECK(igraph_i_vertex_connectivity_undirected(graph, res)); } } return 0; } /** * \function igraph_st_edge_connectivity * \brief Edge connectivity of a pair of vertices * * The edge connectivity of two vertices (\c source and * \c target) in a graph is the minimum number of edges that * have to be deleted from the graph to eliminate all paths from \c * source to \c target. * * This function uses the maximum flow algorithm to calculate * the edge connectivity. * \param graph The input graph, it has to be directed. * \param res Pointer to an integer, the result will be stored here. * \param source The id of the source vertex. * \param target The id of the target vertex. * \return Error code. * * Time complexity: O(|V|^3). * * \sa \ref igraph_maxflow_value(), \ref igraph_edge_connectivity(), * \ref igraph_st_vertex_connectivity(), \ref * igraph_vertex_connectivity(). */ int igraph_st_edge_connectivity(const igraph_t *graph, igraph_integer_t *res, igraph_integer_t source, igraph_integer_t target) { igraph_real_t flow; if (source == target) { IGRAPH_ERROR("source and target vertices are the same", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_maxflow_value(graph, &flow, source, target, 0, 0)); *res = (igraph_integer_t) flow; return 0; } /** * \function igraph_edge_connectivity * \brief The minimum edge connectivity in a graph. * * This is the minimum of the edge connectivity over all * pairs of vertices in the graph. * * * The edge connectivity of a graph is the same as group adhesion as * defined in Douglas R. White and Frank Harary: The cohesiveness of * blocks in social networks: node connectivity and conditional * density, Sociological Methodology 31:305--359, 2001. * \param graph The input graph. * \param res Pointer to an integer, the result will be stored here. * \param checks Logical constant. Whether to check that the graph is * connected and also the degree of the vertices. If the graph is * not (strongly) connected then the connectivity is obviously zero. Otherwise * if the minimum degree is one then the edge connectivity is also * one. It is a good idea to perform these checks, as they can be * done quickly compared to the connectivity calculation itself. * They were suggested by Peter McMahan, thanks Peter. * \return Error code. * * Time complexity: O(log(|V|)*|V|^2) for undirected graphs and * O(|V|^4) for directed graphs, but see also the discussion at the * documentation of \ref igraph_maxflow_value(). * * \sa \ref igraph_st_edge_connectivity(), \ref igraph_maxflow_value(), * \ref igraph_vertex_connectivity(). */ int igraph_edge_connectivity(const igraph_t *graph, igraph_integer_t *res, igraph_bool_t checks) { igraph_bool_t ret = 0; igraph_integer_t number_of_nodes = igraph_vcount(graph); /* igraph_mincut_value returns infinity for the singleton graph, * which cannot be cast to an integer. We catch this case early * and postulate the edge-connectivity of this graph to be 0. * This is consistent with what other software packages return. */ if (number_of_nodes <= 1) { *res = 0; return 0; } /* Use that vertex.connectivity(G) <= edge.connectivity(G) <= min(degree(G)) */ if (checks) { IGRAPH_CHECK(igraph_i_connectivity_checks(graph, res, &ret)); } if (!ret) { igraph_real_t real_res; IGRAPH_CHECK(igraph_mincut_value(graph, &real_res, 0)); *res = (igraph_integer_t)real_res; } return 0; } /** * \function igraph_edge_disjoint_paths * \brief The maximum number of edge-disjoint paths between two vertices. * * A set of paths between two vertices is called * edge-disjoint if they do not share any edges. The maximum number of * edge-disjoint paths are calculated by this function using maximum * flow techniques. Directed paths are considered in directed * graphs. * * Note that the number of disjoint paths is the same as the * edge connectivity of the two vertices using uniform edge weights. * \param graph The input graph, can be directed or undirected. * \param res Pointer to an integer variable, the result will be * stored here. * \param source The id of the source vertex. * \param target The id of the target vertex. * \return Error code. * * Time complexity: O(|V|^3), but see the discussion at \ref * igraph_maxflow_value(). * * \sa \ref igraph_vertex_disjoint_paths(), \ref * igraph_st_edge_connectivity(), \ref igraph_maxflow_value(). */ int igraph_edge_disjoint_paths(const igraph_t *graph, igraph_integer_t *res, igraph_integer_t source, igraph_integer_t target) { igraph_real_t flow; if (source == target) { IGRAPH_ERROR("Not implemented for source=target", IGRAPH_UNIMPLEMENTED); } IGRAPH_CHECK(igraph_maxflow_value(graph, &flow, source, target, 0, 0)); *res = (igraph_integer_t) flow; return 0; } /** * \function igraph_vertex_disjoint_paths * \brief Maximum number of vertex-disjoint paths between two vertices. * * A set of paths between two vertices is called * vertex-disjoint if they share no vertices. The calculation is * performed by using maximum flow techniques. * * Note that the number of vertex-disjoint paths is the same as * the vertex connectivity of the two vertices in most cases (if the * two vertices are not connected by an edge). * \param graph The input graph. * \param res Pointer to an integer variable, the result will be * stored here. * \param source The id of the source vertex. * \param target The id of the target vertex. * \return Error code. * * Time complexity: O(|V|^3). * * \sa \ref igraph_edge_disjoint_paths(), \ref * igraph_vertex_connectivity(), \ref igraph_maxflow_value(). */ int igraph_vertex_disjoint_paths(const igraph_t *graph, igraph_integer_t *res, igraph_integer_t source, igraph_integer_t target) { igraph_bool_t conn; if (source == target) { IGRAPH_ERROR("The source==target case is not implemented", IGRAPH_UNIMPLEMENTED); } igraph_are_connected(graph, source, target, &conn); if (conn) { /* We need to remove every (possibly directed) edge between source and target and calculate the disjoint paths on the new graph. Finally we add 1 for the removed connection(s). */ igraph_es_t es; igraph_vector_t v; igraph_t newgraph; IGRAPH_VECTOR_INIT_FINALLY(&v, 2); VECTOR(v)[0] = source; VECTOR(v)[1] = target; IGRAPH_CHECK(igraph_es_multipairs(&es, &v, IGRAPH_DIRECTED)); IGRAPH_FINALLY(igraph_es_destroy, &es); IGRAPH_CHECK(igraph_copy(&newgraph, graph)); IGRAPH_FINALLY(igraph_destroy, &newgraph); IGRAPH_CHECK(igraph_delete_edges(&newgraph, es)); if (igraph_is_directed(graph)) { IGRAPH_CHECK(igraph_i_st_vertex_connectivity_directed(&newgraph, res, source, target, IGRAPH_VCONN_NEI_IGNORE)); } else { IGRAPH_CHECK(igraph_i_st_vertex_connectivity_undirected(&newgraph, res, source, target, IGRAPH_VCONN_NEI_IGNORE)); } if (res) { *res += 1; } IGRAPH_FINALLY_CLEAN(3); igraph_destroy(&newgraph); igraph_es_destroy(&es); igraph_vector_destroy(&v); } /* These do nothing if the two vertices are connected, so it is safe to call them. */ if (igraph_is_directed(graph)) { IGRAPH_CHECK(igraph_i_st_vertex_connectivity_directed(graph, res, source, target, IGRAPH_VCONN_NEI_IGNORE)); } else { IGRAPH_CHECK(igraph_i_st_vertex_connectivity_undirected(graph, res, source, target, IGRAPH_VCONN_NEI_IGNORE)); } return 0; } /** * \function igraph_adhesion * \brief Graph adhesion, this is (almost) the same as edge connectivity. * * This quantity is defined by White and Harary in * The cohesiveness of blocks in social networks: node connectivity and * conditional density, (Sociological Methodology 31:305--359, 2001) * and basically it is the edge connectivity of the graph * with uniform edge weights. * \param graph The input graph, either directed or undirected. * \param res Pointer to an integer, the result will be stored here. * \param checks Logical constant. Whether to check that the graph is * connected and also the degree of the vertices. If the graph is * not (strongly) connected then the adhesion is obviously zero. Otherwise * if the minimum degree is one then the adhesion is also * one. It is a good idea to perform these checks, as they can be * done quickly compared to the edge connectivity calculation itself. * They were suggested by Peter McMahan, thanks Peter. * \return Error code. * * Time complexity: O(log(|V|)*|V|^2) for undirected graphs and * O(|V|^4) for directed graphs, but see also the discussion at the * documentation of \ref igraph_maxflow_value(). * * \sa \ref igraph_cohesion(), \ref igraph_maxflow_value(), \ref * igraph_edge_connectivity(), \ref igraph_mincut_value(). */ int igraph_adhesion(const igraph_t *graph, igraph_integer_t *res, igraph_bool_t checks) { return igraph_edge_connectivity(graph, res, checks); } /** * \function igraph_cohesion * \brief Graph cohesion, this is the same as vertex connectivity. * * This quantity was defined by White and Harary in The * cohesiveness of blocks in social networks: node connectivity and * conditional density, (Sociological Methodology 31:305--359, 2001) * and it is the same as the vertex connectivity of a * graph. * \param graph The input graph. * \param res Pointer to an integer variable, the result will be * stored here. * \param checks Logical constant. Whether to check that the graph is * connected and also the degree of the vertices. If the graph is * not (strongly) connected then the cohesion is obviously zero. Otherwise * if the minimum degree is one then the cohesion is also * one. It is a good idea to perform these checks, as they can be * done quickly compared to the vertex connectivity calculation itself. * They were suggested by Peter McMahan, thanks Peter. * \return Error code. * * Time complexity: O(|V|^4), |V| is the number of vertices. In * practice it is more like O(|V|^2), see \ref igraph_maxflow_value(). * * \sa \ref igraph_vertex_connectivity(), \ref igraph_adhesion(), * \ref igraph_maxflow_value(). */ int igraph_cohesion(const igraph_t *graph, igraph_integer_t *res, igraph_bool_t checks) { IGRAPH_CHECK(igraph_vertex_connectivity(graph, res, checks)); return 0; } /** * \function igraph_gomory_hu_tree * \brief Gomory-Hu tree of a graph. * * * The Gomory-Hu tree is a concise representation of the value of all the * maximum flows (or minimum cuts) in a graph. The vertices of the tree * correspond exactly to the vertices of the original graph in the same order. * Edges of the Gomory-Hu tree are annotated by flow values. The value of * the maximum flow (or minimum cut) between an arbitrary (u,v) vertex * pair in the original graph is then given by the minimum flow value (i.e. * edge annotation) along the shortest path between u and v in the * Gomory-Hu tree. * * This implementation uses Gusfield's algorithm to construct the * Gomory-Hu tree. See the following paper for more details: * * * Gusfield D: Very simple methods for all pairs network flow analysis. SIAM J * Comput 19(1):143-155, 1990. * * \param graph The input graph. * \param tree Pointer to an uninitialized graph; the result will be * stored here. * \param flows Pointer to an uninitialized vector; the flow values * corresponding to each edge in the Gomory-Hu tree will * be returned here. You may pass a NULL pointer here if you are * not interested in the flow values. * \param capacity Vector containing the capacity of the edges. If NULL, then * every edge is considered to have capacity 1.0. * \return Error code. * * Time complexity: O(|V|^4) since it performs a max-flow calculation * between vertex zero and every other vertex and max-flow is * O(|V|^3). * * \sa \ref igraph_maxflow() */ int igraph_gomory_hu_tree(const igraph_t *graph, igraph_t *tree, igraph_vector_t *flows, const igraph_vector_t *capacity) { igraph_integer_t no_of_nodes = igraph_vcount(graph); igraph_integer_t source, target, mid, i, n; igraph_vector_t neighbors; igraph_vector_t flow_values; igraph_vector_t partition; igraph_vector_t partition2; igraph_real_t flow_value; if (igraph_is_directed(graph)) { IGRAPH_ERROR("Gomory-Hu tree can only be calculated for undirected graphs", IGRAPH_EINVAL); } /* Allocate memory */ IGRAPH_VECTOR_INIT_FINALLY(&neighbors, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&flow_values, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&partition, 0); IGRAPH_VECTOR_INIT_FINALLY(&partition2, 0); /* Initialize the tree: every edge points to node 0 */ /* Actually, this is done implicitly since both 'neighbors' and 'flow_values' are * initialized to zero already */ /* For each source vertex except vertex zero... */ for (source = 1; source < no_of_nodes; source++) { IGRAPH_ALLOW_INTERRUPTION(); IGRAPH_PROGRESS("Gomory-Hu tree", (100.0 * (source - 1)) / (no_of_nodes - 1), 0); /* Find its current neighbor in the tree */ target = VECTOR(neighbors)[(long int)source]; /* Find the maximum flow between source and target */ IGRAPH_CHECK(igraph_maxflow(graph, &flow_value, 0, 0, &partition, &partition2, source, target, capacity, 0)); /* Store the maximum flow and determine which side each node is on */ VECTOR(flow_values)[(long int)source] = flow_value; /* Update the tree */ /* igraph_maxflow() guarantees that the source vertex will be in &partition * and not in &partition2 */ n = igraph_vector_size(&partition); for (i = 0; i < n; i++) { mid = VECTOR(partition)[i]; if (mid > source && VECTOR(neighbors)[(long int)mid] == target) { VECTOR(neighbors)[(long int)mid] = source; } } } IGRAPH_PROGRESS("Gomory-Hu tree", 100.0, 0); /* Re-use the 'partition' vector as an edge list now */ IGRAPH_CHECK(igraph_vector_resize(&partition, 2 * (no_of_nodes - 1))); for (i = 1, mid = 0; i < no_of_nodes; i++, mid += 2) { VECTOR(partition)[(long int)mid] = i; VECTOR(partition)[(long int)mid + 1] = VECTOR(neighbors)[(long int)i]; } /* Create the tree graph; we use igraph_subgraph_edges here to keep the * graph and vertex attributes */ IGRAPH_CHECK(igraph_subgraph_edges(graph, tree, igraph_ess_none(), 0)); IGRAPH_CHECK(igraph_add_edges(tree, &partition, 0)); /* Free the allocated memory */ igraph_vector_destroy(&partition2); igraph_vector_destroy(&partition); igraph_vector_destroy(&neighbors); IGRAPH_FINALLY_CLEAN(3); /* Return the flow values to the caller */ if (flows != 0) { IGRAPH_CHECK(igraph_vector_update(flows, &flow_values)); if (no_of_nodes > 0) { igraph_vector_remove(flows, 0); } } /* Free the remaining allocated memory */ igraph_vector_destroy(&flow_values); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } python-igraph-0.8.0/vendor/source/igraph/src/bliss/0000755000076500000240000000000013617375001022515 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/src/bliss/kqueue.hh0000644000076500000240000000612313524616144024342 0ustar tamasstaff00000000000000#ifndef BLISS_KQUEUE_HH #define BLISS_KQUEUE_HH /* Copyright (c) 2003-2015 Tommi Junttila Released under the GNU Lesser General Public License version 3. This file is part of bliss. bliss is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, version 3 of the License. bliss is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with bliss. If not, see . */ #include "defs.hh" namespace bliss { /** \internal * \brief A very simple implementation of queues with fixed capacity. */ template class KQueue { public: /** * Create a new queue with capacity zero. * The function init() should be called next. */ KQueue(); ~KQueue(); /** * Initialize the queue to have the capacity to hold at most \a N elements. */ void init(const unsigned int N); /** Is the queue empty? */ bool is_empty() const; /** Return the number of elements in the queue. */ unsigned int size() const; /** Remove all the elements in the queue. */ void clear(); /** Return (but don't remove) the first element in the queue. */ Type front() const; /** Remove and return the first element of the queue. */ Type pop_front(); /** Push the element \a e in the front of the queue. */ void push_front(Type e); /** Remove and return the last element of the queue. */ Type pop_back(); /** Push the element \a e in the back of the queue. */ void push_back(Type e); private: Type *entries, *end; Type *head, *tail; }; template KQueue::KQueue() { entries = 0; end = 0; head = 0; tail = 0; } template KQueue::~KQueue() { if(entries) free(entries); } template void KQueue::init(const unsigned int k) { assert(k > 0); if(entries) free(entries); entries = (Type*)malloc((k + 1) * sizeof(Type)); end = entries + k + 1; head = entries; tail = head; } template void KQueue::clear() { head = entries; tail = head; } template bool KQueue::is_empty() const { return(head == tail); } template unsigned int KQueue::size() const { if(tail >= head) return(tail - head); return((end - head) + (tail - entries)); } template Type KQueue::front() const { return *head; } template Type KQueue::pop_front() { Type *old_head = head; head++; if(head == end) head = entries; return *old_head; } template void KQueue::push_front(Type e) { if(head == entries) head = end - 1; else head--; *head = e; } template void KQueue::push_back(Type e) { *tail = e; tail++; if(tail == end) tail = entries; } } // namespace bliss #endif python-igraph-0.8.0/vendor/source/igraph/src/bliss/utils.hh0000644000076500000240000000400713524616144024202 0ustar tamasstaff00000000000000#ifndef BLISS_UTILS_HH #define BLISS_UTILS_HH /* Copyright (c) 2003-2015 Tommi Junttila Released under the GNU Lesser General Public License version 3. This file is part of bliss. bliss is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, version 3 of the License. bliss is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with bliss. If not, see . */ /** * \file * \brief Some small utilities. * */ #include using namespace std; namespace bliss { /** * Print the permutation \a perm of {0,...,N-1} in the cycle format * in the file stream \a fp. * The amount \a offset is added to each element before printing, * e.g. the permutation (2 4) is printed as (3 5) when \a offset is 1. */ void print_permutation(FILE* fp, const unsigned int N, const unsigned int* perm, const unsigned int offset = 0); /** * Print the permutation \a perm of {0,...,N-1} in the cycle format * in the file stream \a fp. * The amount \a offset is added to each element before printing, * e.g. the permutation (2 4) is printed as (3 5) when \a offset is 1. */ void print_permutation(FILE* fp, const std::vector& perm, const unsigned int offset = 0); /** * Check whether \a perm is a valid permutation on {0,...,N-1}. * Slow, mainly for debugging and validation purposes. */ bool is_permutation(const unsigned int N, const unsigned int* perm); /** * Check whether \a perm is a valid permutation on {0,...,N-1}. * Slow, mainly for debugging and validation purposes. */ bool is_permutation(const std::vector& perm); } // namespace bliss #endif python-igraph-0.8.0/vendor/source/igraph/src/bliss/utils.cc0000644000076500000240000000521613524616144024173 0ustar tamasstaff00000000000000#include #include #include "utils.hh" /* Copyright (c) 2003-2015 Tommi Junttila Released under the GNU Lesser General Public License version 3. This file is part of bliss. bliss is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, version 3 of the License. bliss is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with bliss. If not, see . */ namespace bliss { void print_permutation(FILE* const fp, const unsigned int N, const unsigned int* perm, const unsigned int offset) { assert(N > 0); assert(perm); for(unsigned int i = 0; i < N; i++) { unsigned int j = perm[i]; if(j == i) continue; bool is_first = true; while(j != i) { if(j < i) { is_first = false; break; } j = perm[j]; } if(!is_first) continue; fprintf(fp, "(%u,", i+offset); j = perm[i]; while(j != i) { fprintf(fp, "%u", j+offset); j = perm[j]; if(j != i) fprintf(fp, ","); } fprintf(fp, ")"); } } void print_permutation(FILE* const fp, const std::vector& perm, const unsigned int offset) { const unsigned int N = perm.size(); for(unsigned int i = 0; i < N; i++) { unsigned int j = perm[i]; if(j == i) continue; bool is_first = true; while(j != i) { if(j < i) { is_first = false; break; } j = perm[j]; } if(!is_first) continue; fprintf(fp, "(%u,", i+offset); j = perm[i]; while(j != i) { fprintf(fp, "%u", j+offset); j = perm[j]; if(j != i) fprintf(fp, ","); } fprintf(fp, ")"); } } bool is_permutation(const unsigned int N, const unsigned int* perm) { if(N == 0) return true; std::vector m(N, false); for(unsigned int i = 0; i < N; i++) { if(perm[i] >= N) return false; if(m[perm[i]]) return false; m[perm[i]] = true; } return true; } bool is_permutation(const std::vector& perm) { const unsigned int N = perm.size(); if(N == 0) return true; std::vector m(N, false); for(unsigned int i = 0; i < N; i++) { if(perm[i] >= N) return false; if(m[perm[i]]) return false; m[perm[i]] = true; } return true; } } // namespace bliss python-igraph-0.8.0/vendor/source/igraph/src/bliss/bignum.hh0000644000076500000240000000560313524616144024326 0ustar tamasstaff00000000000000#ifndef BLISS_BIGNUM_HH #define BLISS_BIGNUM_HH /* Copyright (c) 2003-2015 Tommi Junttila Released under the GNU Lesser General Public License version 3. This file is part of bliss. bliss is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, version 3 of the License. bliss is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with bliss. If not, see . */ #include #include #include #include #include #include "defs.hh" #include "igraph_memory.h" #include "igraph_error.h" #if defined(BLISS_USE_GMP) #include #endif namespace bliss { /** * \brief A very simple class for big integers (or approximation of them). * * If the compile time flag BLISS_USE_GMP is set, * then the GNU Multiple Precision Arithmetic library (GMP) is used to * obtain arbitrary precision, otherwise "long double" is used to * approximate big integers. */ #if defined(BLISS_USE_GMP) class BigNum { mpz_t v; public: /** * Create a new big number and set it to zero. */ BigNum() {mpz_init(v); } /** * Destroy the number. */ ~BigNum() {mpz_clear(v); } /** * Set the number to \a n. */ void assign(const int n) {mpz_set_si(v, n); } /** * Multiply the number with \a n. */ void multiply(const int n) {mpz_mul_si(v, v, n); } /** * Print the number in the file stream \a fp. */ size_t print(FILE* const fp) const {return mpz_out_str(fp, 10, v); } int tostring(char **str) const { *str=igraph_Calloc(mpz_sizeinbase(v, 10)+2, char); if (! *str) { IGRAPH_ERROR("Cannot convert big number to string", IGRAPH_ENOMEM); } mpz_get_str(*str, 10, v); return 0; } }; #else class BigNum { long double v; public: /** * Create a new big number and set it to zero. */ BigNum(): v(0.0) {} /** * Set the number to \a n. */ void assign(const int n) {v = (long double)n; } /** * Multiply the number with \a n. */ void multiply(const int n) {v *= (long double)n; } /** * Print the number in the file stream \a fp. */ size_t print(FILE* const fp) const {return fprintf(fp, "%Lg", v); } int tostring(char **str) const { int size=static_cast( (std::log(std::abs(v))/std::log(10.0))+4 ); *str=igraph_Calloc(size, char ); if (! *str) { IGRAPH_ERROR("Cannot convert big number to string", IGRAPH_ENOMEM); } std::stringstream ss; ss << v; strncpy(*str, ss.str().c_str(), size); return 0; } }; #endif } //namespace bliss #endif python-igraph-0.8.0/vendor/source/igraph/src/bliss/graph.cc0000644000076500000240000042732513524616144024145 0ustar tamasstaff00000000000000#include #include #include #include #include #include #include "defs.hh" #include "graph.hh" #include "partition.hh" #include "utils.hh" /* use 'and' instead of '&&' */ #if _MSC_VER #include #endif #ifdef USING_R #undef stdout #define stdout NULL #endif /* Copyright (c) 2003-2015 Tommi Junttila Released under the GNU Lesser General Public License version 3. This file is part of bliss. bliss is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, version 3 of the License. bliss is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with bliss. If not, see . */ namespace bliss { #define _INTERNAL_ERROR() fatal_error("%s:%d: internal error",__FILE__,__LINE__) #define _OUT_OF_MEMORY() fatal_error("%s:%d: out of memory",__FILE__,__LINE__) /*------------------------------------------------------------------------- * * Constructor and destructor routines for the abstract graph class * *-------------------------------------------------------------------------*/ AbstractGraph::AbstractGraph() { /* Initialize stuff */ first_path_labeling = 0; first_path_labeling_inv = 0; best_path_labeling = 0; best_path_labeling_inv = 0; first_path_automorphism = 0; best_path_automorphism = 0; in_search = false; /* Default value for using "long prune" */ opt_use_long_prune = true; /* Default value for using failure recording */ opt_use_failure_recording = true; /* Default value for using component recursion */ opt_use_comprec = true; verbose_level = 0; verbstr = stdout; report_hook = 0; report_user_param = 0; } AbstractGraph::~AbstractGraph() { if(first_path_labeling) { free(first_path_labeling); first_path_labeling = 0; } if(first_path_labeling_inv) { free(first_path_labeling_inv); first_path_labeling_inv = 0; } if(best_path_labeling) { free(best_path_labeling); best_path_labeling = 0; } if(best_path_labeling_inv) { free(best_path_labeling_inv); best_path_labeling_inv = 0; } if(first_path_automorphism) { free(first_path_automorphism); first_path_automorphism = 0; } if(best_path_automorphism) { free(best_path_automorphism); best_path_automorphism = 0; } report_hook = 0; report_user_param = 0; } /*------------------------------------------------------------------------- * * Verbose output management routines * *-------------------------------------------------------------------------*/ void AbstractGraph::set_verbose_level(const unsigned int level) { verbose_level = level; } void AbstractGraph::set_verbose_file(FILE* const fp) { verbstr = fp; } /*------------------------------------------------------------------------- * * Routines for refinement to equitable partition * *-------------------------------------------------------------------------*/ void AbstractGraph::refine_to_equitable() { /* Start refinement from all cells -> push 'em all in the splitting queue */ for(Partition::Cell* cell = p.first_cell; cell; cell = cell->next) p.splitting_queue_add(cell); do_refine_to_equitable(); } void AbstractGraph::refine_to_equitable(Partition::Cell* const unit_cell) { p.splitting_queue_add(unit_cell); do_refine_to_equitable(); } void AbstractGraph::refine_to_equitable(Partition::Cell* const unit_cell1, Partition::Cell* const unit_cell2) { p.splitting_queue_add(unit_cell1); p.splitting_queue_add(unit_cell2); do_refine_to_equitable(); } bool AbstractGraph::do_refine_to_equitable() { eqref_hash.reset(); while(!p.splitting_queue_is_empty()) { Partition::Cell* const cell = p.splitting_queue_pop(); if(cell->is_unit()) { if(in_search) { const unsigned int index = cell->first; if(first_path_automorphism) { /* Build the (potential) automorphism on-the-fly */ first_path_automorphism[first_path_labeling_inv[index]] = p.elements[index]; } if(best_path_automorphism) { /* Build the (potential) automorphism on-the-fly */ best_path_automorphism[best_path_labeling_inv[index]] = p.elements[index]; } } const bool worse = split_neighbourhood_of_unit_cell(cell); if(in_search and worse) goto worse_exit; } else { const bool worse = split_neighbourhood_of_cell(cell); if(in_search and worse) goto worse_exit; } } return true; worse_exit: /* Clear splitting_queue */ p.splitting_queue_clear(); return false; } /*------------------------------------------------------------------------- * * Routines for handling the canonical labeling * *-------------------------------------------------------------------------*/ /** \internal * Assign the labeling induced by the current partition 'this.p' to * \a labeling. * That is, if the partition is [[2,0],[1]], * then \a labeling will map 0 to 1, 1 to 2, and 2 to 0. */ void AbstractGraph::update_labeling(unsigned int* const labeling) { const unsigned int N = get_nof_vertices(); unsigned int* ep = p.elements; for(unsigned int i = 0; i < N; i++, ep++) labeling[*ep] = i; } /** \internal * The same as update_labeling() except that the inverse of the labeling * is also produced and assigned to \a labeling_inv. */ void AbstractGraph::update_labeling_and_its_inverse(unsigned int* const labeling, unsigned int* const labeling_inv) { const unsigned int N = get_nof_vertices(); unsigned int* ep = p.elements; unsigned int* clip = labeling_inv; for(unsigned int i = 0; i < N; ) { labeling[*ep] = i; i++; *clip = *ep; ep++; clip++; } } /*------------------------------------------------------------------------- * * Routines for handling automorphisms * *-------------------------------------------------------------------------*/ /** \internal * Reset the permutation \a perm to the identity permutation. */ void AbstractGraph::reset_permutation(unsigned int* perm) { const unsigned int N = get_nof_vertices(); for(unsigned int i = 0; i < N; i++, perm++) *perm = i; } bool AbstractGraph::is_automorphism(unsigned int* const perm) { _INTERNAL_ERROR(); return false; } bool AbstractGraph::is_automorphism(const std::vector& perm) const { _INTERNAL_ERROR(); return false; } /*------------------------------------------------------------------------- * * Certificate building * *-------------------------------------------------------------------------*/ void AbstractGraph::cert_add(const unsigned int v1, const unsigned int v2, const unsigned int v3) { if(refine_compare_certificate) { if(refine_equal_to_first) { /* So far equivalent to the first path... */ unsigned int index = certificate_current_path.size(); if(index >= refine_first_path_subcertificate_end) { refine_equal_to_first = false; } else if(certificate_first_path[index] != v1) { refine_equal_to_first = false; } else if(certificate_first_path[++index] != v2) { refine_equal_to_first = false; } else if(certificate_first_path[++index] != v3) { refine_equal_to_first = false; } if(opt_use_failure_recording and !refine_equal_to_first) { /* We just became different from the first path, * remember the deviation point tree-specific invariant * for the use of failure recording */ UintSeqHash h; h.update(v1); h.update(v2); h.update(v3); h.update(index); h.update(eqref_hash.get_value()); failure_recording_fp_deviation = h.get_value(); } } if(refine_cmp_to_best == 0) { /* So far equivalent to the current best path... */ unsigned int index = certificate_current_path.size(); if(index >= refine_best_path_subcertificate_end) { refine_cmp_to_best = 1; } else if(v1 > certificate_best_path[index]) { refine_cmp_to_best = 1; } else if(v1 < certificate_best_path[index]) { refine_cmp_to_best = -1; } else if(v2 > certificate_best_path[++index]) { refine_cmp_to_best = 1; } else if(v2 < certificate_best_path[index]) { refine_cmp_to_best = -1; } else if(v3 > certificate_best_path[++index]) { refine_cmp_to_best = 1; } else if(v3 < certificate_best_path[index]) { refine_cmp_to_best = -1; } } if((refine_equal_to_first == false) and (refine_cmp_to_best < 0)) return; } /* Update the current path certificate */ certificate_current_path.push_back(v1); certificate_current_path.push_back(v2); certificate_current_path.push_back(v3); } void AbstractGraph::cert_add_redundant(const unsigned int v1, const unsigned int v2, const unsigned int v3) { return cert_add(v1, v2, v3); } /*------------------------------------------------------------------------- * * Long prune code * *-------------------------------------------------------------------------*/ void AbstractGraph::long_prune_init() { const unsigned int N = get_nof_vertices(); long_prune_temp.clear(); long_prune_temp.resize(N); /* Of how many automorphisms we can store information in the predefined, fixed amount of memory? */ const unsigned int nof_fitting_in_max_mem = (long_prune_options_max_mem * 1024 * 1024) / (((N * 2) / 8)+1); long_prune_max_stored_autss = long_prune_options_max_stored_auts; /* Had some problems with g++ in using (a* tmp = long_prune_fixed[real_i]; long_prune_fixed[real_i] = long_prune_fixed[real_j]; long_prune_fixed[real_j] = tmp; tmp = long_prune_mcrs[real_i]; long_prune_mcrs[real_i] = long_prune_mcrs[real_j]; long_prune_mcrs[real_j] = tmp; } std::vector& AbstractGraph::long_prune_allocget_fixed(const unsigned int index) { const unsigned int i = index % long_prune_max_stored_autss; if(!long_prune_fixed[i]) long_prune_fixed[i] = new std::vector(get_nof_vertices()); return *long_prune_fixed[i]; } std::vector& AbstractGraph::long_prune_get_fixed(const unsigned int index) { return *long_prune_fixed[index % long_prune_max_stored_autss]; } std::vector& AbstractGraph::long_prune_allocget_mcrs(const unsigned int index) { const unsigned int i = index % long_prune_max_stored_autss; if(!long_prune_mcrs[i]) long_prune_mcrs[i] = new std::vector(get_nof_vertices()); return *long_prune_mcrs[i]; } std::vector& AbstractGraph::long_prune_get_mcrs(const unsigned int index) { return *long_prune_mcrs[index % long_prune_max_stored_autss]; } void AbstractGraph::long_prune_add_automorphism(const unsigned int* aut) { if(long_prune_max_stored_autss == 0) return; const unsigned int N = get_nof_vertices(); /* If the buffer of stored auts is full, remove the oldest aut */ if(long_prune_end - long_prune_begin == long_prune_max_stored_autss) { long_prune_begin++; } long_prune_end++; std::vector& fixed = long_prune_allocget_fixed(long_prune_end-1); std::vector& mcrs = long_prune_allocget_mcrs(long_prune_end-1); /* Mark nodes that are (i) fixed or (ii) minimal orbit representatives * under the automorphism 'aut' */ for(unsigned int i = 0; i < N; i++) { fixed[i] = (aut[i] == i); if(long_prune_temp[i] == false) { mcrs[i] = true; unsigned int j = aut[i]; while(j != i) { long_prune_temp[j] = true; j = aut[j]; } } else { mcrs[i] = false; } /* Clear the temp array on-the-fly... */ long_prune_temp[i] = false; } } /*------------------------------------------------------------------------- * * Routines for handling orbit information * *-------------------------------------------------------------------------*/ void AbstractGraph::update_orbit_information(Orbit& o, const unsigned int* perm) { const unsigned int N = get_nof_vertices(); for(unsigned int i = 0; i < N; i++) if(perm[i] != i) o.merge_orbits(i, perm[i]); } /*------------------------------------------------------------------------- * * The actual backtracking search * *-------------------------------------------------------------------------*/ class TreeNode { //friend class AbstractGraph; public: unsigned int split_cell_first; int split_element; static const int SPLIT_START = -1; static const int SPLIT_END = -2; Partition::BacktrackPoint partition_bt_point; unsigned int certificate_index; static const char NO = -1; static const char MAYBE = 0; static const char YES = 1; /* First path stuff */ bool fp_on; bool fp_cert_equal; char fp_extendable; /* Best path stuff */ bool in_best_path; int cmp_to_best_path; unsigned int failure_recording_ival; /* Component recursion related data */ unsigned int cr_cep_stack_size; unsigned int cr_cep_index; unsigned int cr_level; bool needs_long_prune; unsigned int long_prune_begin; std::set > long_prune_redundant; UintSeqHash eqref_hash; unsigned int subcertificate_length; }; typedef struct { unsigned int splitting_element; unsigned int certificate_index; unsigned int subcertificate_length; UintSeqHash eqref_hash; } PathInfo; void AbstractGraph::search(const bool canonical, Stats& stats) { const unsigned int N = get_nof_vertices(); unsigned int all_same_level = UINT_MAX; p.graph = this; /* * Must be done! */ remove_duplicate_edges(); /* * Reset search statistics */ stats.reset(); stats.nof_nodes = 1; stats.nof_leaf_nodes = 1; /* Free old first path data structures */ if(first_path_labeling) { free(first_path_labeling); first_path_labeling = 0; } if(first_path_labeling_inv) { free(first_path_labeling_inv); first_path_labeling_inv = 0; } if(first_path_automorphism) { free(first_path_automorphism); first_path_automorphism = 0; } /* Free old best path data structures */ if(best_path_labeling) { free(best_path_labeling); best_path_labeling = 0; } if(best_path_labeling_inv) { free(best_path_labeling_inv); best_path_labeling_inv = 0; } if(best_path_automorphism) { free(best_path_automorphism); best_path_automorphism = 0; } if(N == 0) { /* Nothing to do, return... */ return; } /* Initialize the partition ... */ p.init(N); /* ... and the component recursion data structures in the partition */ if(opt_use_comprec) p.cr_init(); neighbour_heap.init(N); in_search = false; /* Do not compute certificate when building the initial partition */ refine_compare_certificate = false; /* The 'eqref_hash' hash value is not computed when building * the initial partition as it is not used for anything at the moment. * This saves some cycles. */ compute_eqref_hash = false; make_initial_equitable_partition(); /* * Allocate space for the "first path" and "best path" labelings */ if(first_path_labeling) free(first_path_labeling); first_path_labeling = (unsigned int*)calloc(N, sizeof(unsigned int)); if(!first_path_labeling) _OUT_OF_MEMORY(); if(best_path_labeling) free(best_path_labeling); best_path_labeling = (unsigned int*)calloc(N, sizeof(unsigned int)); if(!best_path_labeling) _OUT_OF_MEMORY(); /* * Is the initial partition discrete? */ if(p.is_discrete()) { /* Make the best path labeling i.e. the canonical labeling */ update_labeling(best_path_labeling); /* Update statistics */ stats.nof_leaf_nodes = 1; /* Free component recursion data */ if(opt_use_comprec) p.cr_free(); return; } /* * Allocate the inverses of the "first path" and "best path" labelings */ if(first_path_labeling_inv) free(first_path_labeling_inv); first_path_labeling_inv = (unsigned int*)calloc(N, sizeof(unsigned int)); if(!first_path_labeling_inv) _OUT_OF_MEMORY(); if(best_path_labeling_inv) free(best_path_labeling_inv); best_path_labeling_inv = (unsigned int*)calloc(N, sizeof(unsigned int)); if(!best_path_labeling_inv) _OUT_OF_MEMORY(); /* * Allocate space for the automorphisms */ if(first_path_automorphism) free(first_path_automorphism); first_path_automorphism = (unsigned int*)malloc(N * sizeof(unsigned int)); if(!first_path_automorphism) _OUT_OF_MEMORY(); if(best_path_automorphism) free(best_path_automorphism); best_path_automorphism = (unsigned int*)malloc(N * sizeof(unsigned int)); if(!best_path_automorphism) _OUT_OF_MEMORY(); /* * Initialize orbit information so that all vertices are in their own orbits */ first_path_orbits.init(N); best_path_orbits.init(N); /* * Initialize certificate memory */ initialize_certificate(); std::vector search_stack; std::vector first_path_info; std::vector best_path_info; search_stack.clear(); /* Initialize "long prune" data structures */ if(opt_use_long_prune) long_prune_init(); /* * Initialize failure recording data structures */ typedef std::set > FailureRecordingSet; std::vector failure_recording_hashes; /* * Initialize component recursion data structures */ cr_cep_stack.clear(); unsigned int cr_cep_index = 0; { /* Inset a sentinel "component end point" */ CR_CEP sentinel; sentinel.creation_level = 0; sentinel.discrete_cell_limit = get_nof_vertices(); sentinel.next_cr_level = 0; sentinel.next_cep_index = 0; sentinel.first_checked = false; sentinel.best_checked = false; cr_cep_index = 0; cr_cep_stack.push_back(sentinel); } cr_level = 0; if(opt_use_comprec and nucr_find_first_component(cr_level) == true and p.nof_discrete_cells() + cr_component_elements < cr_cep_stack[cr_cep_index].discrete_cell_limit) { cr_level = p.cr_split_level(0, cr_component); CR_CEP cep; cep.creation_level = 0; cep.discrete_cell_limit = p.nof_discrete_cells() + cr_component_elements; cep.next_cr_level = 0; cep.next_cep_index = cr_cep_index; cep.first_checked = false; cep.best_checked = false; cr_cep_index = cr_cep_stack.size(); cr_cep_stack.push_back(cep); } /* * Build the root node of the search tree */ { TreeNode root; Partition::Cell* split_cell = find_next_cell_to_be_splitted(p.first_cell); root.split_cell_first = split_cell->first; root.split_element = TreeNode::SPLIT_START; root.partition_bt_point = p.set_backtrack_point(); root.certificate_index = 0; root.fp_on = true; root.fp_cert_equal = true; root.fp_extendable = TreeNode::MAYBE; root.in_best_path = false; root.cmp_to_best_path = 0; root.long_prune_begin = 0; root.failure_recording_ival = 0; /* Save component recursion info for backtracking */ root.cr_level = cr_level; root.cr_cep_stack_size = cr_cep_stack.size(); root.cr_cep_index = cr_cep_index; search_stack.push_back(root); } /* * Set status and global flags for search related procedures */ in_search = true; /* Do not compare certificates during refinement until the first path has been traversed to the leaf */ refine_compare_certificate = false; /* * The actual backtracking search */ while(!search_stack.empty()) { TreeNode& current_node = search_stack.back(); const unsigned int current_level = (unsigned int)search_stack.size()-1; if(opt_use_comprec) { CR_CEP& cep = cr_cep_stack[current_node.cr_cep_index]; if(cep.first_checked == true and current_node.fp_extendable == TreeNode::MAYBE and !search_stack[cep.creation_level].fp_on) { current_node.fp_extendable = TreeNode::NO; } } if(current_node.fp_on) { if(current_node.split_element == TreeNode::SPLIT_END) { search_stack.pop_back(); continue; } } else { if(current_node.fp_extendable == TreeNode::YES) { search_stack.pop_back(); continue; } if(current_node.split_element == TreeNode::SPLIT_END) { if(opt_use_failure_recording) { TreeNode& parent_node = search_stack[current_level-1]; if(parent_node.fp_on) failure_recording_hashes[current_level-1].insert(current_node.failure_recording_ival); } search_stack.pop_back(); continue; } if(current_node.fp_extendable == TreeNode::NO and (!canonical or current_node.cmp_to_best_path < 0)) { if(opt_use_failure_recording) { TreeNode& parent_node = search_stack[current_level-1]; if(parent_node.fp_on) failure_recording_hashes[current_level-1].insert(current_node.failure_recording_ival); } search_stack.pop_back(); continue; } } /* Restore partition ... */ p.goto_backtrack_point(current_node.partition_bt_point); /* ... and re-remember backtracking point */ current_node.partition_bt_point = p.set_backtrack_point(); /* Restore current path certificate */ certificate_index = current_node.certificate_index; refine_current_path_certificate_index = current_node.certificate_index; certificate_current_path.resize(certificate_index); /* Fetch split cell information */ Partition::Cell * const cell = p.get_cell(p.elements[current_node.split_cell_first]); /* Restore component recursion information */ cr_level = current_node.cr_level; cr_cep_stack.resize(current_node.cr_cep_stack_size); cr_cep_index = current_node.cr_cep_index; /* * Update long prune redundancy sets */ if(opt_use_long_prune and current_level >= 1 and !current_node.fp_on) { unsigned int begin = (current_node.long_prune_begin>long_prune_begin)?current_node.long_prune_begin:long_prune_begin; for(unsigned int i = begin; i < long_prune_end; i++) { const std::vector& fixed = long_prune_get_fixed(i); #if defined(BLISS_CONSISTENCY_CHECKS) for(unsigned int l = 0; l < search_stack.size()-2; l++) assert(fixed[search_stack[l].split_element]); #endif if(fixed[search_stack[search_stack.size()-1-1].split_element] == false) { long_prune_swap(begin, i); begin++; current_node.long_prune_begin = begin; continue; } } if(current_node.split_element == TreeNode::SPLIT_START) { current_node.needs_long_prune = true; } else if(current_node.needs_long_prune) { current_node.needs_long_prune = false; unsigned int begin = (current_node.long_prune_begin>long_prune_begin)?current_node.long_prune_begin:long_prune_begin; for(unsigned int i = begin; i < long_prune_end; i++) { const std::vector& fixed = long_prune_get_fixed(i); #if defined(BLISS_CONSISTENCY_CHECKS) for(unsigned int l = 0; l < search_stack.size()-2; l++) assert(fixed[search_stack[l].split_element]); #endif assert(fixed[search_stack[current_level-1].split_element] == true); if(fixed[search_stack[current_level-1].split_element] == false) { long_prune_swap(begin, i); begin++; current_node.long_prune_begin = begin; continue; } const std::vector& mcrs = long_prune_get_mcrs(i); unsigned int* ep = p.elements + cell->first; for(unsigned int j = cell->length; j > 0; j--, ep++) { if(mcrs[*ep] == false) current_node.long_prune_redundant.insert(*ep); } } } } /* * Find the next smallest, non-isomorphic element in the cell and * store it in current_node.split_element */ { unsigned int next_split_element = UINT_MAX; //unsigned int* next_split_element_pos = 0; unsigned int* ep = p.elements + cell->first; if(current_node.fp_on) { /* Find the next larger splitting element that is * a minimal orbit representative w.r.t. first_path_orbits */ for(unsigned int i = cell->length; i > 0; i--, ep++) { if((int)(*ep) > current_node.split_element and *ep < next_split_element and first_path_orbits.is_minimal_representative(*ep)) { next_split_element = *ep; //next_split_element_pos = ep; } } } else if(current_node.in_best_path) { /* Find the next larger splitting element that is * a minimal orbit representative w.r.t. best_path_orbits */ for(unsigned int i = cell->length; i > 0; i--, ep++) { if((int)(*ep) > current_node.split_element and *ep < next_split_element and best_path_orbits.is_minimal_representative(*ep) and (!opt_use_long_prune or current_node.long_prune_redundant.find(*ep) == current_node.long_prune_redundant.end())) { next_split_element = *ep; //next_split_element_pos = ep; } } } else { /* Find the next larger splitting element */ for(unsigned int i = cell->length; i > 0; i--, ep++) { if((int)(*ep) > current_node.split_element and *ep < next_split_element and (!opt_use_long_prune or current_node.long_prune_redundant.find(*ep) == current_node.long_prune_redundant.end())) { next_split_element = *ep; //next_split_element_pos = ep; } } } if(next_split_element == UINT_MAX) { /* No more (unexplored children) in the cell */ current_node.split_element = TreeNode::SPLIT_END; if(current_node.fp_on) { /* Update group size */ const unsigned int index = first_path_orbits.orbit_size(first_path_info[search_stack.size()-1].splitting_element); stats.group_size.multiply(index); stats.group_size_approx *= (long double)index; /* * Update all_same_level */ if(index == cell->length and all_same_level == current_level+1) all_same_level = current_level; if(verbstr and verbose_level >= 2) { fprintf(verbstr, "Level %u: orbits=%u, index=%u/%u, all_same_level=%u\n", current_level, first_path_orbits.nof_orbits(), index, cell->length, all_same_level); fflush(verbstr); } } continue; } /* Split on smallest */ current_node.split_element = next_split_element; } const unsigned int child_level = current_level+1; /* Update some statistics */ stats.nof_nodes++; if(search_stack.size() > stats.max_level) stats.max_level = search_stack.size(); /* Set flags and indices for the refiner certificate builder */ refine_equal_to_first = current_node.fp_cert_equal; refine_cmp_to_best = current_node.cmp_to_best_path; if(!first_path_info.empty()) { if(refine_equal_to_first) refine_first_path_subcertificate_end = first_path_info[search_stack.size()-1].certificate_index + first_path_info[search_stack.size()-1].subcertificate_length; if(canonical) { if(refine_cmp_to_best == 0) refine_best_path_subcertificate_end = best_path_info[search_stack.size()-1].certificate_index + best_path_info[search_stack.size()-1].subcertificate_length; } else refine_cmp_to_best = -1; } const bool was_fp_cert_equal = current_node.fp_cert_equal; /* Individualize, i.e. split the cell in two, the latter new cell * will be a unit one containing info.split_element */ Partition::Cell* const new_cell = p.individualize(cell, current_node.split_element); /* * Refine the new partition to equitable */ if(cell->is_unit()) refine_to_equitable(cell, new_cell); else refine_to_equitable(new_cell); /* Update statistics */ if(p.is_discrete()) stats.nof_leaf_nodes++; if(!first_path_info.empty()) { /* We are no longer on the first path */ const unsigned int subcertificate_length = certificate_current_path.size() - certificate_index; if(refine_equal_to_first) { /* Was equal to the first path so far */ PathInfo& first_pinfo = first_path_info[current_level]; assert(first_pinfo.certificate_index == certificate_index); if(subcertificate_length != first_pinfo.subcertificate_length) { refine_equal_to_first = false; if(opt_use_failure_recording) failure_recording_fp_deviation = subcertificate_length; } else if(first_pinfo.eqref_hash.cmp(eqref_hash) != 0) { refine_equal_to_first = false; if(opt_use_failure_recording) failure_recording_fp_deviation = eqref_hash.get_value(); } } if(canonical and (refine_cmp_to_best == 0)) { /* Was equal to the best path so far */ PathInfo& bestp_info = best_path_info[current_level]; assert(bestp_info.certificate_index == certificate_index); if(subcertificate_length < bestp_info.subcertificate_length) { refine_cmp_to_best = -1; } else if(subcertificate_length > bestp_info.subcertificate_length) { refine_cmp_to_best = 1; } else if(bestp_info.eqref_hash.cmp(eqref_hash) > 0) { refine_cmp_to_best = -1; } else if(bestp_info.eqref_hash.cmp(eqref_hash) < 0) { refine_cmp_to_best = 1; } } if(opt_use_failure_recording and was_fp_cert_equal and !refine_equal_to_first) { UintSeqHash k; k.update(failure_recording_fp_deviation); k.update(eqref_hash.get_value()); failure_recording_fp_deviation = k.get_value(); if(current_node.fp_on) failure_recording_hashes[current_level].insert(failure_recording_fp_deviation); else { for(unsigned int i = current_level; i > 0; i--) { if(search_stack[i].fp_on) break; const FailureRecordingSet& s = failure_recording_hashes[i]; if(i == current_level and s.find(failure_recording_fp_deviation) != s.end()) break; if(s.find(0) != s.end()) break; search_stack[i].fp_extendable = TreeNode::NO; } } } /* Check if no longer equal to the first path and, * if canonical labeling is desired, also worse than the * current best path */ if(refine_equal_to_first == false and (!canonical or (refine_cmp_to_best < 0))) { /* Yes, backtrack */ stats.nof_bad_nodes++; if(current_node.fp_cert_equal == true and current_level+1 > all_same_level) { assert(all_same_level >= 1); for(unsigned int i = all_same_level; i < search_stack.size(); i++) { search_stack[i].fp_extendable = TreeNode::NO; } } continue; } } #if defined(BLISS_VERIFY_EQUITABLEDNESS) /* The new partition should be equitable */ if(!is_equitable()) fatal_error("consistency check failed - partition after refinement is not equitable"); #endif /* * Next level search tree node info */ TreeNode child_node; /* No more in the first path */ child_node.fp_on = false; /* No more in the best path */ child_node.in_best_path = false; child_node.fp_cert_equal = refine_equal_to_first; if(current_node.fp_extendable == TreeNode::NO or (current_node.fp_extendable == TreeNode::MAYBE and child_node.fp_cert_equal == false)) child_node.fp_extendable = TreeNode::NO; else child_node.fp_extendable = TreeNode::MAYBE; child_node.cmp_to_best_path = refine_cmp_to_best; child_node.failure_recording_ival = 0; child_node.cr_cep_stack_size = current_node.cr_cep_stack_size; child_node.cr_cep_index = current_node.cr_cep_index; child_node.cr_level = current_node.cr_level; certificate_index = certificate_current_path.size(); current_node.eqref_hash = eqref_hash; current_node.subcertificate_length = certificate_index - current_node.certificate_index; /* * The first encountered leaf node at the end of the "first path"? */ if(p.is_discrete() and first_path_info.empty()) { //fprintf(stdout, "Level %u: FIRST\n", child_level); fflush(stdout); stats.nof_canupdates++; /* * Update labelings and their inverses */ update_labeling_and_its_inverse(first_path_labeling, first_path_labeling_inv); update_labeling_and_its_inverse(best_path_labeling, best_path_labeling_inv); /* * Reset automorphism array */ reset_permutation(first_path_automorphism); reset_permutation(best_path_automorphism); /* * Reset orbit information */ first_path_orbits.reset(); best_path_orbits.reset(); /* * Reset group size */ stats.group_size.assign(1); stats.group_size_approx = 1.0; /* * Reset all_same_level */ all_same_level = child_level; /* * Mark the current path to be the first and best one and save it */ const unsigned int base_size = search_stack.size(); best_path_info.clear(); //fprintf(stdout, " New base is: "); for(unsigned int i = 0; i < base_size; i++) { search_stack[i].fp_on = true; search_stack[i].fp_cert_equal = true; search_stack[i].fp_extendable = TreeNode::YES; search_stack[i].in_best_path = true; search_stack[i].cmp_to_best_path = 0; PathInfo path_info; path_info.splitting_element = search_stack[i].split_element; path_info.certificate_index = search_stack[i].certificate_index; path_info.eqref_hash = search_stack[i].eqref_hash; path_info.subcertificate_length = search_stack[i].subcertificate_length; first_path_info.push_back(path_info); best_path_info.push_back(path_info); //fprintf(stdout, "%u ", search_stack[i].split_element); } //fprintf(stdout, "\n"); fflush(stdout); /* Copy certificates */ certificate_first_path = certificate_current_path; certificate_best_path = certificate_current_path; /* From now on, compare certificates when refining */ refine_compare_certificate = true; if(opt_use_failure_recording) failure_recording_hashes.resize(base_size); /* for(unsigned int j = 0; j < search_stack.size(); j++) fprintf(stderr, "%u ", search_stack[j].split_element); fprintf(stderr, "\n"); p.print(stderr); fprintf(stderr, "\n"); */ /* * Backtrack to the previous level */ continue; } if(p.is_discrete() and child_node.fp_cert_equal) { /* * A leaf node that is equal to the first one. * An automorphism found: aut[i] = elements[first_path_labeling[i]] */ goto handle_first_path_automorphism; } if(!p.is_discrete()) { Partition::Cell* next_split_cell = 0; /* * An internal, non-leaf node */ if(opt_use_comprec) { assert(p.nof_discrete_cells() <= cr_cep_stack[cr_cep_index].discrete_cell_limit); assert(cr_level == child_node.cr_level); if(p.nof_discrete_cells() == cr_cep_stack[cr_cep_index].discrete_cell_limit) { /* We have reached the end of a component */ assert(cr_cep_index != 0); CR_CEP& cep = cr_cep_stack[cr_cep_index]; /* First, compare with respect to the first path */ if(first_path_info.empty() or child_node.fp_cert_equal) { if(cep.first_checked == false) { /* First time, go to the next component */ cep.first_checked = true; } else { assert(!first_path_info.empty()); assert(cep.creation_level < search_stack.size()); TreeNode& old_info = search_stack[cep.creation_level]; /* If the component was found when on the first path, * handle the found automorphism as the other * first path automorphisms */ if(old_info.fp_on) goto handle_first_path_automorphism; } } if(canonical and !first_path_info.empty() and child_node.cmp_to_best_path >= 0) { if(cep.best_checked == false) { /* First time, go to the next component */ cep.best_checked = true; } else { assert(cep.creation_level < search_stack.size()); TreeNode& old_info = search_stack[cep.creation_level]; if(child_node.cmp_to_best_path == 0) { /* If the component was found when on the best path, * handle the found automorphism as the other * best path automorphisms */ if(old_info.in_best_path) goto handle_best_path_automorphism; /* Otherwise, we do not remember the automorhism as * we didn't memorize the path that was invariant * equal to the best one and passed through the * component. * Thus we can only backtrack to the previous level */ child_node.cmp_to_best_path = -1; if(!child_node.fp_cert_equal) { continue; } } else { assert(child_node.cmp_to_best_path > 0); if(old_info.in_best_path) { stats.nof_canupdates++; /* * Update canonical labeling and its inverse */ for(unsigned int i = 0; i < N; i++) { if(p.get_cell(p.elements[i])->is_unit()) { best_path_labeling[p.elements[i]] = i; best_path_labeling_inv[i] = p.elements[i]; } } //update_labeling_and_its_inverse(best_path_labeling, best_path_labeling_inv); /* Reset best path automorphism */ reset_permutation(best_path_automorphism); /* Reset best path orbit structure */ best_path_orbits.reset(); /* Mark to be the best one and save prefix */ unsigned int postfix_start = cep.creation_level; assert(postfix_start < best_path_info.size()); while(p.get_cell(best_path_info[postfix_start].splitting_element)->is_unit()) { postfix_start++; assert(postfix_start < best_path_info.size()); } unsigned int postfix_start_cert = best_path_info[postfix_start].certificate_index; std::vector best_path_temp = best_path_info; best_path_info.clear(); for(unsigned int i = 0; i < search_stack.size(); i++) { TreeNode& ss_info = search_stack[i]; PathInfo bp_info; ss_info.cmp_to_best_path = 0; ss_info.in_best_path = true; bp_info.splitting_element = ss_info.split_element; bp_info.certificate_index = ss_info.certificate_index; bp_info.subcertificate_length = ss_info.subcertificate_length; bp_info.eqref_hash = ss_info.eqref_hash; best_path_info.push_back(bp_info); } /* Copy the postfix of the previous best path */ for(unsigned int i = postfix_start; i < best_path_temp.size(); i++) { best_path_info.push_back(best_path_temp[i]); best_path_info[best_path_info.size()-1].certificate_index = best_path_info[best_path_info.size()-2].certificate_index + best_path_info[best_path_info.size()-2].subcertificate_length; } std::vector certificate_best_path_old = certificate_best_path; certificate_best_path = certificate_current_path; for(unsigned int i = postfix_start_cert; i < certificate_best_path_old.size(); i++) certificate_best_path.push_back(certificate_best_path_old[i]); assert(certificate_best_path.size() == best_path_info.back().certificate_index + best_path_info.back().subcertificate_length); /* Backtrack to the previous level */ continue; } } } } /* No backtracking performed, go to next componenet */ cr_level = cep.next_cr_level; cr_cep_index = cep.next_cep_index; } /* Check if the current component has been split into * new non-uniformity subcomponents */ //if(nucr_find_first_component(cr_level) == true and // p.nof_discrete_cells() + cr_component_elements < // cr_cep_stack[cr_cep_index].discrete_cell_limit) if(nucr_find_first_component(cr_level, cr_component, cr_component_elements, next_split_cell) == true and p.nof_discrete_cells() + cr_component_elements < cr_cep_stack[cr_cep_index].discrete_cell_limit) { const unsigned int next_cr_level = p.cr_split_level(cr_level, cr_component); CR_CEP cep; cep.creation_level = search_stack.size(); cep.discrete_cell_limit = p.nof_discrete_cells() + cr_component_elements; cep.next_cr_level = cr_level; cep.next_cep_index = cr_cep_index; cep.first_checked = false; cep.best_checked = false; cr_cep_index = cr_cep_stack.size(); cr_cep_stack.push_back(cep); cr_level = next_cr_level; } } /* * Build the next node info */ /* Find the next cell to be splitted */ if(!next_split_cell) next_split_cell = find_next_cell_to_be_splitted(p.get_cell(p.elements[current_node.split_cell_first])); //Partition::Cell * const next_split_cell = find_next_cell_to_be_splitted(p.get_cell(p.elements[current_node.split_cell_first])); child_node.split_cell_first = next_split_cell->first; child_node.split_element = TreeNode::SPLIT_START; child_node.certificate_index = certificate_index; child_node.partition_bt_point = p.set_backtrack_point(); child_node.long_prune_redundant.clear(); child_node.long_prune_begin = current_node.long_prune_begin; /* Save component recursion info for backtracking */ child_node.cr_level = cr_level; child_node.cr_cep_stack_size = cr_cep_stack.size(); child_node.cr_cep_index = cr_cep_index; search_stack.push_back(child_node); continue; } /* * A leaf node not in the first path or equivalent to the first path */ if(child_node.cmp_to_best_path > 0) { /* * A new, better representative found */ //fprintf(stdout, "Level %u: NEW BEST\n", child_level); fflush(stdout); stats.nof_canupdates++; /* * Update canonical labeling and its inverse */ update_labeling_and_its_inverse(best_path_labeling, best_path_labeling_inv); /* Reset best path automorphism */ reset_permutation(best_path_automorphism); /* Reset best path orbit structure */ best_path_orbits.reset(); /* * Mark the current path to be the best one and save it */ const unsigned int base_size = search_stack.size(); assert(current_level+1 == base_size); best_path_info.clear(); for(unsigned int i = 0; i < base_size; i++) { search_stack[i].cmp_to_best_path = 0; search_stack[i].in_best_path = true; PathInfo path_info; path_info.splitting_element = search_stack[i].split_element; path_info.certificate_index = search_stack[i].certificate_index; path_info.subcertificate_length = search_stack[i].subcertificate_length; path_info.eqref_hash = search_stack[i].eqref_hash; best_path_info.push_back(path_info); } certificate_best_path = certificate_current_path; /* * Backtrack to the previous level */ continue; } handle_best_path_automorphism: /* * * Best path automorphism handling * */ { /* * Equal to the previous best path */ if(p.is_discrete()) { #if defined(BLISS_CONSISTENCY_CHECKS) /* Verify that the automorphism is correctly built */ for(unsigned int i = 0; i < N; i++) assert(best_path_automorphism[i] == p.elements[best_path_labeling[i]]); #endif } else { /* An automorphism that was found before the partition was discrete. * Set the image of all elements in non-disrete cells accordingly */ for(Partition::Cell* c = p.first_nonsingleton_cell; c; c = c->next_nonsingleton) { for(unsigned int i = c->first; i < c->first+c->length; i++) if(p.get_cell(p.elements[best_path_labeling[p.elements[i]]])->is_unit()) best_path_automorphism[p.elements[best_path_labeling[p.elements[i]]]] = p.elements[i]; else best_path_automorphism[p.elements[i]] = p.elements[i]; } } #if defined(BLISS_VERIFY_AUTOMORPHISMS) /* Verify that it really is an automorphism */ if(!is_automorphism(best_path_automorphism)) fatal_error("Best path automorhism validation check failed"); #endif unsigned int gca_level_with_first = 0; for(unsigned int i = search_stack.size(); i > 0; i--) { if((int)first_path_info[gca_level_with_first].splitting_element != search_stack[gca_level_with_first].split_element) break; gca_level_with_first++; } unsigned int gca_level_with_best = 0; for(unsigned int i = search_stack.size(); i > 0; i--) { if((int)best_path_info[gca_level_with_best].splitting_element != search_stack[gca_level_with_best].split_element) break; gca_level_with_best++; } if(opt_use_long_prune) { /* Record automorphism */ long_prune_add_automorphism(best_path_automorphism); } /* * Update orbit information */ update_orbit_information(best_path_orbits, best_path_automorphism); /* * Update orbit information */ const unsigned int nof_old_orbits = first_path_orbits.nof_orbits(); update_orbit_information(first_path_orbits, best_path_automorphism); if(nof_old_orbits != first_path_orbits.nof_orbits()) { /* Some orbits were merged */ /* Report automorphism */ if(report_hook) (*report_hook)(report_user_param, get_nof_vertices(), best_path_automorphism); /* Update statistics */ stats.nof_generators++; } /* * Compute backjumping level */ unsigned int backjumping_level = current_level+1-1; if(!first_path_orbits.is_minimal_representative(search_stack[gca_level_with_first].split_element)) { backjumping_level = gca_level_with_first; } else { assert(!best_path_orbits.is_minimal_representative(search_stack[gca_level_with_best].split_element)); backjumping_level = gca_level_with_best; } /* Backtrack */ search_stack.resize(backjumping_level + 1); continue; } _INTERNAL_ERROR(); handle_first_path_automorphism: /* * * A first-path automorphism: aut[i] = elements[first_path_labeling[i]] * */ if(p.is_discrete()) { #if defined(BLISS_CONSISTENCY_CHECKS) /* Verify that the complete automorphism is correctly built */ for(unsigned int i = 0; i < N; i++) assert(first_path_automorphism[i] == p.elements[first_path_labeling[i]]); #endif } else { /* An automorphism that was found before the partition was discrete. * Set the image of all elements in non-disrete cells accordingly */ for(Partition::Cell* c = p.first_nonsingleton_cell; c; c = c->next_nonsingleton) { for(unsigned int i = c->first; i < c->first+c->length; i++) if(p.get_cell(p.elements[first_path_labeling[p.elements[i]]])->is_unit()) first_path_automorphism[p.elements[first_path_labeling[p.elements[i]]]] = p.elements[i]; else first_path_automorphism[p.elements[i]] = p.elements[i]; } } #if defined(BLISS_VERIFY_AUTOMORPHISMS) /* Verify that it really is an automorphism */ if(!is_automorphism(first_path_automorphism)) fatal_error("First path automorphism validation check failed"); #endif if(opt_use_long_prune) { long_prune_add_automorphism(first_path_automorphism); } /* * Update orbit information */ update_orbit_information(first_path_orbits, first_path_automorphism); /* * Compute backjumping level */ for(unsigned int i = 0; i < search_stack.size(); i++) { TreeNode& n = search_stack[i]; if(n.fp_on) { ; } else { n.fp_extendable = TreeNode::YES; } } /* Report automorphism by calling the user defined hook function */ if(report_hook) (*report_hook)(report_user_param, get_nof_vertices(), first_path_automorphism); /* Update statistics */ stats.nof_generators++; continue; } /* while(!search_stack.empty()) */ /* Free "long prune" technique memory */ if(opt_use_long_prune) long_prune_deallocate(); /* Release component recursion data in partition */ if(opt_use_comprec) p.cr_free(); } void AbstractGraph::find_automorphisms(Stats& stats, void (*hook)(void *user_param, unsigned int n, const unsigned int *aut), void *user_param) { report_hook = hook; report_user_param = user_param; search(false, stats); if(first_path_labeling) { free(first_path_labeling); first_path_labeling = 0; } if(best_path_labeling) { free(best_path_labeling); best_path_labeling = 0; } } const unsigned int * AbstractGraph::canonical_form(Stats& stats, void (*hook)(void *user_param, unsigned int n, const unsigned int *aut), void *user_param) { report_hook = hook; report_user_param = user_param; search(true, stats); return best_path_labeling; } /*------------------------------------------------------------------------- * * Routines for directed graphs * *-------------------------------------------------------------------------*/ Digraph::Vertex::Vertex() { color = 0; } Digraph::Vertex::~Vertex() { ; } void Digraph::Vertex::add_edge_to(const unsigned int other_vertex) { edges_out.push_back(other_vertex); } void Digraph::Vertex::add_edge_from(const unsigned int other_vertex) { edges_in.push_back(other_vertex); } void Digraph::Vertex::remove_duplicate_edges(std::vector& tmp) { #if defined(BLISS_CONSISTENCY_CHECKS) /* Pre-conditions */ for(unsigned int i = 0; i < tmp.size(); i++) assert(tmp[i] == false); #endif for(std::vector::iterator iter = edges_out.begin(); iter != edges_out.end(); ) { const unsigned int dest_vertex = *iter; if(tmp[dest_vertex] == true) { /* A duplicate edge found! */ iter = edges_out.erase(iter); } else { /* Not seen earlier, mark as seen */ tmp[dest_vertex] = true; iter++; } } /* Clear tmp */ for(std::vector::iterator iter = edges_out.begin(); iter != edges_out.end(); iter++) { tmp[*iter] = false; } for(std::vector::iterator iter = edges_in.begin(); iter != edges_in.end(); ) { const unsigned int dest_vertex = *iter; if(tmp[dest_vertex] == true) { /* A duplicate edge found! */ iter = edges_in.erase(iter); } else { /* Not seen earlier, mark as seen */ tmp[dest_vertex] = true; iter++; } } /* Clear tmp */ for(std::vector::iterator iter = edges_in.begin(); iter != edges_in.end(); iter++) { tmp[*iter] = false; } #if defined(BLISS_CONSISTENCY_CHECKS) /* Post-conditions */ for(unsigned int i = 0; i < tmp.size(); i++) assert(tmp[i] == false); #endif } /** * Sort the edges entering and leaving the vertex according to * the vertex number of the other edge end. * Time complexity: O(e log(e)), where e is the number of edges * entering/leaving the vertex. */ void Digraph::Vertex::sort_edges() { std::sort(edges_in.begin(), edges_in.end()); std::sort(edges_out.begin(), edges_out.end()); } /*------------------------------------------------------------------------- * * Constructor and destructor for directed graphs * *-------------------------------------------------------------------------*/ Digraph::Digraph(const unsigned int nof_vertices) { vertices.resize(nof_vertices); sh = shs_flm; } Digraph::~Digraph() { ; } unsigned int Digraph::add_vertex(const unsigned int color) { const unsigned int new_vertex_num = vertices.size(); vertices.resize(new_vertex_num + 1); vertices.back().color = color; return new_vertex_num; } void Digraph::add_edge(const unsigned int vertex1, const unsigned int vertex2) { assert(vertex1 < get_nof_vertices()); assert(vertex2 < get_nof_vertices()); vertices[vertex1].add_edge_to(vertex2); vertices[vertex2].add_edge_from(vertex1); } void Digraph::change_color(const unsigned int vertex, const unsigned int new_color) { assert(vertex < get_nof_vertices()); vertices[vertex].color = new_color; } void Digraph::sort_edges() { for(unsigned int i = 0; i < get_nof_vertices(); i++) vertices[i].sort_edges(); } int Digraph::cmp(Digraph& other) { /* Compare the numbers of vertices */ if(get_nof_vertices() < other.get_nof_vertices()) return -1; if(get_nof_vertices() > other.get_nof_vertices()) return 1; /* Compare vertex colors */ for(unsigned int i = 0; i < get_nof_vertices(); i++) { if(vertices[i].color < other.vertices[i].color) return -1; if(vertices[i].color > other.vertices[i].color) return 1; } /* Compare vertex degrees */ remove_duplicate_edges(); other.remove_duplicate_edges(); for(unsigned int i = 0; i < get_nof_vertices(); i++) { if(vertices[i].nof_edges_in() < other.vertices[i].nof_edges_in()) return -1; if(vertices[i].nof_edges_in() > other.vertices[i].nof_edges_in()) return 1; if(vertices[i].nof_edges_out() < other.vertices[i].nof_edges_out()) return -1; if(vertices[i].nof_edges_out() > other.vertices[i].nof_edges_out()) return 1; } /* Compare edges */ for(unsigned int i = 0; i < get_nof_vertices(); i++) { Vertex& v1 = vertices[i]; Vertex& v2 = other.vertices[i]; v1.sort_edges(); v2.sort_edges(); std::vector::const_iterator ei1 = v1.edges_in.begin(); std::vector::const_iterator ei2 = v2.edges_in.begin(); while(ei1 != v1.edges_in.end()) { if(*ei1 < *ei2) return -1; if(*ei1 > *ei2) return 1; ei1++; ei2++; } ei1 = v1.edges_out.begin(); ei2 = v2.edges_out.begin(); while(ei1 != v1.edges_out.end()) { if(*ei1 < *ei2) return -1; if(*ei1 > *ei2) return 1; ei1++; ei2++; } } return 0; } Digraph* Digraph::permute(const std::vector& perm) const { Digraph* const g = new Digraph(get_nof_vertices()); for(unsigned int i = 0; i < get_nof_vertices(); i++) { const Vertex& v = vertices[i]; g->change_color(perm[i], v.color); for(std::vector::const_iterator ei = v.edges_out.begin(); ei != v.edges_out.end(); ei++) { g->add_edge(perm[i], perm[*ei]); } } g->sort_edges(); return g; } Digraph* Digraph::permute(const unsigned int* const perm) const { Digraph* const g = new Digraph(get_nof_vertices()); for(unsigned int i = 0; i < get_nof_vertices(); i++) { const Vertex &v = vertices[i]; g->change_color(perm[i], v.color); for(std::vector::const_iterator ei = v.edges_out.begin(); ei != v.edges_out.end(); ei++) { g->add_edge(perm[i], perm[*ei]); } } g->sort_edges(); return g; } /*------------------------------------------------------------------------- * * Print graph in graphviz format * *-------------------------------------------------------------------------*/ void Digraph::write_dot(const char* const filename) { FILE* const fp = fopen(filename, "w"); if(fp) { write_dot(fp); fclose(fp); } } void Digraph::write_dot(FILE* const fp) { remove_duplicate_edges(); fprintf(fp, "digraph g {\n"); unsigned int vnum = 0; for(std::vector::const_iterator vi = vertices.begin(); vi != vertices.end(); vi++, vnum++) { const Vertex& v = *vi; fprintf(fp, "v%u [label=\"%u:%u\"];\n", vnum, vnum, v.color); for(std::vector::const_iterator ei = v.edges_out.begin(); ei != v.edges_out.end(); ei++) { fprintf(fp, "v%u -> v%u\n", vnum, *ei); } } fprintf(fp, "}\n"); } void Digraph::remove_duplicate_edges() { std::vector tmp(get_nof_vertices(), false); for(std::vector::iterator vi = vertices.begin(); vi != vertices.end(); vi++) { #if defined(BLISS_EXPENSIVE_CONSISTENCY_CHECKS) for(unsigned int i = 0; i < tmp.size(); i++) assert(tmp[i] == false); #endif (*vi).remove_duplicate_edges(tmp); } } /*------------------------------------------------------------------------- * * Get a hash value for the graph. * *-------------------------------------------------------------------------*/ unsigned int Digraph::get_hash() { remove_duplicate_edges(); sort_edges(); UintSeqHash h; h.update(get_nof_vertices()); /* Hash the color of each vertex */ for(unsigned int i = 0; i < get_nof_vertices(); i++) { h.update(vertices[i].color); } /* Hash the edges */ for(unsigned int i = 0; i < get_nof_vertices(); i++) { Vertex &v = vertices[i]; for(std::vector::const_iterator ei = v.edges_out.begin(); ei != v.edges_out.end(); ei++) { h.update(i); h.update(*ei); } } return h.get_value(); } /*------------------------------------------------------------------------- * * Read directed graph in the DIMACS format. * Returns 0 if an error occurred. * *-------------------------------------------------------------------------*/ Digraph* Digraph::read_dimacs(FILE* const fp, FILE* const errstr) { Digraph* g = 0; unsigned int nof_vertices; unsigned int nof_edges; unsigned int line_num = 1; const bool verbose = false; FILE* const verbstr = stdout; /* Read comments and the problem definition line */ while(1) { int c = getc(fp); if(c == 'c') { /* A comment, ignore the rest of the line */ while((c = getc(fp)) != '\n') { if(c == EOF) { if(errstr) fprintf(errstr, "error in line %u: not in DIMACS format\n", line_num); goto error_exit; } } line_num++; continue; } if(c == 'p') { /* The problem definition line */ if(fscanf(fp, " edge %u %u\n", &nof_vertices, &nof_edges) != 2) { if(errstr) fprintf(errstr, "error in line %u: not in DIMACS format\n", line_num); goto error_exit; } line_num++; break; } if(errstr) fprintf(errstr, "error in line %u: not in DIMACS format\n", line_num); goto error_exit; } if(nof_vertices <= 0) { if(errstr) fprintf(errstr, "error: no vertices\n"); goto error_exit; } if(verbose) { fprintf(verbstr, "Instance has %d vertices and %d edges\n", nof_vertices, nof_edges); fflush(verbstr); } g = new Digraph(nof_vertices); // // Read vertex colors // if(verbose) { fprintf(verbstr, "Reading vertex colors...\n"); fflush(verbstr); } while(1) { int c = getc(fp); if(c != 'n') { ungetc(c, fp); break; } ungetc(c, fp); unsigned int vertex; unsigned int color; if(fscanf(fp, "n %u %u\n", &vertex, &color) != 2) { if(errstr) fprintf(errstr, "error in line %u: not in DIMACS format\n", line_num); goto error_exit; } if(!((vertex >= 1) && (vertex <= nof_vertices))) { if(errstr) fprintf(errstr, "error in line %u: vertex %u not in range [1,...%u]\n", line_num, vertex, nof_vertices); goto error_exit; } line_num++; g->change_color(vertex - 1, color); } if(verbose) { fprintf(verbstr, "Done\n"); fflush(verbstr); } // // Read edges // if(verbose) { fprintf(verbstr, "Reading edges...\n"); fflush(verbstr); } for(unsigned i = 0; i < nof_edges; i++) { unsigned int from, to; if(fscanf(fp, "e %u %u\n", &from, &to) != 2) { if(errstr) fprintf(errstr, "error in line %u: not in DIMACS format\n", line_num); goto error_exit; } if(not((1 <= from) and (from <= nof_vertices))) { if(errstr) fprintf(errstr, "error in line %u: vertex %u not in range [1,...%u]\n", line_num, from, nof_vertices); goto error_exit; } if(not((1 <= to) and (to <= nof_vertices))) { if(errstr) fprintf(errstr, "error in line %u: vertex %u not in range [1,...%u]\n", line_num, to, nof_vertices); goto error_exit; } line_num++; g->add_edge(from-1, to-1); } if(verbose) { fprintf(verbstr, "Done\n"); fflush(verbstr); } return g; error_exit: if(g) delete g; return 0; } void Digraph::write_dimacs(FILE* const fp) { remove_duplicate_edges(); sort_edges(); /* First count the total number of edges */ unsigned int nof_edges = 0; for(unsigned int i = 0; i < get_nof_vertices(); i++) { nof_edges += vertices[i].edges_out.size(); } /* Output the "header" line */ fprintf(fp, "p edge %u %u\n", get_nof_vertices(), nof_edges); /* Print the color of each vertex */ for(unsigned int i = 0; i < get_nof_vertices(); i++) { Vertex& v = vertices[i]; fprintf(fp, "n %u %u\n", i+1, v.color); /* if(v.color != 0) { fprintf(fp, "n %u %u\n", i+1, v.color); } */ } /* Print the edges */ for(unsigned int i = 0; i < get_nof_vertices(); i++) { Vertex& v = vertices[i]; for(std::vector::const_iterator ei = v.edges_out.begin(); ei != v.edges_out.end(); ei++) { fprintf(fp, "e %u %u\n", i+1, (*ei)+1); } } } /*------------------------------------------------------------------------- * * Partition independent invariants * *-------------------------------------------------------------------------*/ unsigned int Digraph::vertex_color_invariant(const Digraph* const g, const unsigned int vnum) { return g->vertices[vnum].color; } unsigned int Digraph::indegree_invariant(const Digraph* const g, const unsigned int vnum) { return g->vertices[vnum].nof_edges_in(); } unsigned int Digraph::outdegree_invariant(const Digraph* const g, const unsigned int vnum) { return g->vertices[vnum].nof_edges_out(); } unsigned int Digraph::selfloop_invariant(const Digraph* const g, const unsigned int vnum) { /* Quite inefficient but luckily not in the critical path */ const Vertex& v = g->vertices[vnum]; for(std::vector::const_iterator ei = v.edges_out.begin(); ei != v.edges_out.end(); ei++) { if(*ei == vnum) return 1; } return 0; } /*------------------------------------------------------------------------- * * Refine the partition p according to a partition independent invariant * *-------------------------------------------------------------------------*/ bool Digraph::refine_according_to_invariant(unsigned int (*inv)(const Digraph* const g, const unsigned int v)) { bool refined = false; for(Partition::Cell* cell = p.first_nonsingleton_cell; cell; ) { Partition::Cell* const next_cell = cell->next_nonsingleton; const unsigned int* ep = p.elements + cell->first; for(unsigned int i = cell->length; i > 0; i--, ep++) { unsigned int ival = inv(this, *ep); p.invariant_values[*ep] = ival; if(ival > cell->max_ival) { cell->max_ival = ival; cell->max_ival_count = 1; } else if(ival == cell->max_ival) { cell->max_ival_count++; } } Partition::Cell* const last_new_cell = p.zplit_cell(cell, true); refined |= (last_new_cell != cell); cell = next_cell; } return refined; } /*------------------------------------------------------------------------- * * Split the neighbourhood of a cell according to the equitable invariant * *-------------------------------------------------------------------------*/ bool Digraph::split_neighbourhood_of_cell(Partition::Cell* const cell) { const bool was_equal_to_first = refine_equal_to_first; if(compute_eqref_hash) { eqref_hash.update(cell->first); eqref_hash.update(cell->length); } const unsigned int* ep = p.elements + cell->first; for(unsigned int i = cell->length; i > 0; i--) { const Vertex& v = vertices[*ep++]; std::vector::const_iterator ei = v.edges_out.begin(); for(unsigned int j = v.nof_edges_out(); j != 0; j--) { const unsigned int dest_vertex = *ei++; Partition::Cell* const neighbour_cell = p.get_cell(dest_vertex); if(neighbour_cell->is_unit()) continue; const unsigned int ival = ++p.invariant_values[dest_vertex]; if(ival > neighbour_cell->max_ival) { neighbour_cell->max_ival = ival; neighbour_cell->max_ival_count = 1; if(ival == 1) neighbour_heap.insert(neighbour_cell->first); } else if(ival == neighbour_cell->max_ival) { neighbour_cell->max_ival_count++; } } } while(!neighbour_heap.is_empty()) { const unsigned int start = neighbour_heap.remove(); Partition::Cell* const neighbour_cell = p.get_cell(p.elements[start]); if(compute_eqref_hash) { eqref_hash.update(neighbour_cell->first); eqref_hash.update(neighbour_cell->length); eqref_hash.update(neighbour_cell->max_ival); eqref_hash.update(neighbour_cell->max_ival_count); } Partition::Cell* const last_new_cell = p.zplit_cell(neighbour_cell, true); /* Update certificate and hash if needed */ const Partition::Cell* c = neighbour_cell; while(1) { if(in_search) { /* Build certificate */ cert_add_redundant(CERT_SPLIT, c->first, c->length); /* No need to continue? */ if(refine_compare_certificate and (refine_equal_to_first == false) and (refine_cmp_to_best < 0)) goto worse_exit; } if(compute_eqref_hash) { eqref_hash.update(c->first); eqref_hash.update(c->length); } if(c == last_new_cell) break; c = c->next; } } if(cell->is_in_splitting_queue()) { return false; } ep = p.elements + cell->first; for(unsigned int i = cell->length; i > 0; i--) { const Vertex& v = vertices[*ep++]; std::vector::const_iterator ei = v.edges_in.begin(); for(unsigned int j = v.nof_edges_in(); j > 0; j--) { const unsigned int dest_vertex = *ei++; Partition::Cell* const neighbour_cell = p.get_cell(dest_vertex); if(neighbour_cell->is_unit()) continue; const unsigned int ival = ++p.invariant_values[dest_vertex]; if(ival > neighbour_cell->max_ival) { neighbour_cell->max_ival = ival; neighbour_cell->max_ival_count = 1; if(ival == 1) neighbour_heap.insert(neighbour_cell->first); } else if(ival == neighbour_cell->max_ival) { neighbour_cell->max_ival_count++; } } } while(!neighbour_heap.is_empty()) { const unsigned int start = neighbour_heap.remove(); Partition::Cell* const neighbour_cell = p.get_cell(p.elements[start]); if(compute_eqref_hash) { eqref_hash.update(neighbour_cell->first); eqref_hash.update(neighbour_cell->length); eqref_hash.update(neighbour_cell->max_ival); eqref_hash.update(neighbour_cell->max_ival_count); } Partition::Cell* const last_new_cell = p.zplit_cell(neighbour_cell, true); /* Update certificate and hash if needed */ const Partition::Cell* c = neighbour_cell; while(1) { if(in_search) { /* Build certificate */ cert_add_redundant(CERT_SPLIT, c->first, c->length); /* No need to continue? */ if(refine_compare_certificate and (refine_equal_to_first == false) and (refine_cmp_to_best < 0)) goto worse_exit; } if(compute_eqref_hash) { eqref_hash.update(c->first); eqref_hash.update(c->length); } if(c == last_new_cell) break; c = c->next; } } if(refine_compare_certificate and (refine_equal_to_first == false) and (refine_cmp_to_best < 0)) return true; return false; worse_exit: /* Clear neighbour heap */ UintSeqHash rest; while(!neighbour_heap.is_empty()) { const unsigned int start = neighbour_heap.remove(); Partition::Cell* const neighbour_cell = p.get_cell(p.elements[start]); if(opt_use_failure_recording and was_equal_to_first) { rest.update(neighbour_cell->first); rest.update(neighbour_cell->length); rest.update(neighbour_cell->max_ival); rest.update(neighbour_cell->max_ival_count); } neighbour_cell->max_ival = 0; neighbour_cell->max_ival_count = 0; p.clear_ivs(neighbour_cell); } if(opt_use_failure_recording and was_equal_to_first) { for(unsigned int i = p.splitting_queue.size(); i > 0; i--) { Partition::Cell* const cell = p.splitting_queue.pop_front(); rest.update(cell->first); rest.update(cell->length); p.splitting_queue.push_back(cell); } rest.update(failure_recording_fp_deviation); failure_recording_fp_deviation = rest.get_value(); } return true; } bool Digraph::split_neighbourhood_of_unit_cell(Partition::Cell* const unit_cell) { const bool was_equal_to_first = refine_equal_to_first; if(compute_eqref_hash) { eqref_hash.update(0x87654321); eqref_hash.update(unit_cell->first); eqref_hash.update(1); } const Vertex& v = vertices[p.elements[unit_cell->first]]; /* * Phase 1 * Refine neighbours according to the edges that leave the vertex v */ std::vector::const_iterator ei = v.edges_out.begin(); for(unsigned int j = v.nof_edges_out(); j > 0; j--) { const unsigned int dest_vertex = *ei++; Partition::Cell* const neighbour_cell = p.get_cell(dest_vertex); if(neighbour_cell->is_unit()) { if(in_search) { /* Remember neighbour in order to generate certificate */ neighbour_heap.insert(neighbour_cell->first); } continue; } if(neighbour_cell->max_ival_count == 0) { neighbour_heap.insert(neighbour_cell->first); } neighbour_cell->max_ival_count++; unsigned int* const swap_position = p.elements + neighbour_cell->first + neighbour_cell->length - neighbour_cell->max_ival_count; *p.in_pos[dest_vertex] = *swap_position; p.in_pos[*swap_position] = p.in_pos[dest_vertex]; *swap_position = dest_vertex; p.in_pos[dest_vertex] = swap_position; } while(!neighbour_heap.is_empty()) { const unsigned int start = neighbour_heap.remove(); Partition::Cell* neighbour_cell = p.get_cell(p.elements[start]); #if defined(BLISS_CONSISTENCY_CHECKS) assert(neighbour_cell->first == start); if(neighbour_cell->is_unit()) { assert(neighbour_cell->max_ival_count == 0); } else { assert(neighbour_cell->max_ival_count > 0); assert(neighbour_cell->max_ival_count <= neighbour_cell->length); } #endif if(compute_eqref_hash) { eqref_hash.update(neighbour_cell->first); eqref_hash.update(neighbour_cell->length); eqref_hash.update(neighbour_cell->max_ival_count); } if(neighbour_cell->length > 1 and neighbour_cell->max_ival_count != neighbour_cell->length) { Partition::Cell* const new_cell = p.aux_split_in_two(neighbour_cell, neighbour_cell->length - neighbour_cell->max_ival_count); unsigned int* ep = p.elements + new_cell->first; unsigned int* const lp = p.elements+new_cell->first+new_cell->length; while(ep < lp) { p.element_to_cell_map[*ep] = new_cell; ep++; } neighbour_cell->max_ival_count = 0; if(compute_eqref_hash) { /* Update hash */ eqref_hash.update(neighbour_cell->first); eqref_hash.update(neighbour_cell->length); eqref_hash.update(0); eqref_hash.update(new_cell->first); eqref_hash.update(new_cell->length); eqref_hash.update(1); } /* Add cells in splitting_queue */ if(neighbour_cell->is_in_splitting_queue()) { /* Both cells must be included in splitting_queue in order to have refinement to equitable partition */ p.splitting_queue_add(new_cell); } else { Partition::Cell *min_cell, *max_cell; if(neighbour_cell->length <= new_cell->length) { min_cell = neighbour_cell; max_cell = new_cell; } else { min_cell = new_cell; max_cell = neighbour_cell; } /* Put the smaller cell in splitting_queue */ p.splitting_queue_add(min_cell); if(max_cell->is_unit()) { /* Put the "larger" cell also in splitting_queue */ p.splitting_queue_add(max_cell); } } /* Update pointer for certificate generation */ neighbour_cell = new_cell; } else { neighbour_cell->max_ival_count = 0; } /* * Build certificate if required */ if(in_search) { for(unsigned int i = neighbour_cell->first, j = neighbour_cell->length; j > 0; j--, i++) { /* Build certificate */ cert_add(CERT_EDGE, unit_cell->first, i); /* No need to continue? */ if(refine_compare_certificate and (refine_equal_to_first == false) and (refine_cmp_to_best < 0)) goto worse_exit; } } /* if(in_search) */ } /* while(!neighbour_heap.is_empty()) */ /* * Phase 2 * Refine neighbours according to the edges that enter the vertex v */ ei = v.edges_in.begin(); for(unsigned int j = v.nof_edges_in(); j > 0; j--) { const unsigned int dest_vertex = *ei++; Partition::Cell* const neighbour_cell = p.get_cell(dest_vertex); if(neighbour_cell->is_unit()) { if(in_search) { neighbour_heap.insert(neighbour_cell->first); } continue; } if(neighbour_cell->max_ival_count == 0) { neighbour_heap.insert(neighbour_cell->first); } neighbour_cell->max_ival_count++; unsigned int* const swap_position = p.elements + neighbour_cell->first + neighbour_cell->length - neighbour_cell->max_ival_count; *p.in_pos[dest_vertex] = *swap_position; p.in_pos[*swap_position] = p.in_pos[dest_vertex]; *swap_position = dest_vertex; p.in_pos[dest_vertex] = swap_position; } while(!neighbour_heap.is_empty()) { const unsigned int start = neighbour_heap.remove(); Partition::Cell* neighbour_cell = p.get_cell(p.elements[start]); #if defined(BLISS_CONSISTENCY_CHECKS) assert(neighbour_cell->first == start); if(neighbour_cell->is_unit()) { assert(neighbour_cell->max_ival_count == 0); } else { assert(neighbour_cell->max_ival_count > 0); assert(neighbour_cell->max_ival_count <= neighbour_cell->length); } #endif if(compute_eqref_hash) { eqref_hash.update(neighbour_cell->first); eqref_hash.update(neighbour_cell->length); eqref_hash.update(neighbour_cell->max_ival_count); } if(neighbour_cell->length > 1 and neighbour_cell->max_ival_count != neighbour_cell->length) { Partition::Cell* const new_cell = p.aux_split_in_two(neighbour_cell, neighbour_cell->length - neighbour_cell->max_ival_count); unsigned int* ep = p.elements + new_cell->first; unsigned int* const lp = p.elements+new_cell->first+new_cell->length; while(ep < lp) { p.element_to_cell_map[*ep] = new_cell; ep++; } neighbour_cell->max_ival_count = 0; if(compute_eqref_hash) { eqref_hash.update(neighbour_cell->first); eqref_hash.update(neighbour_cell->length); eqref_hash.update(0); eqref_hash.update(new_cell->first); eqref_hash.update(new_cell->length); eqref_hash.update(1); } /* Add cells in splitting_queue */ if(neighbour_cell->is_in_splitting_queue()) { /* Both cells must be included in splitting_queue in order to have refinement to equitable partition */ p.splitting_queue_add(new_cell); } else { Partition::Cell *min_cell, *max_cell; if(neighbour_cell->length <= new_cell->length) { min_cell = neighbour_cell; max_cell = new_cell; } else { min_cell = new_cell; max_cell = neighbour_cell; } /* Put the smaller cell in splitting_queue */ p.splitting_queue_add(min_cell); if(max_cell->is_unit()) { /* Put the "larger" cell also in splitting_queue */ p.splitting_queue_add(max_cell); } } /* Update pointer for certificate generation */ neighbour_cell = new_cell; } else { neighbour_cell->max_ival_count = 0; } /* * Build certificate if required */ if(in_search) { for(unsigned int i = neighbour_cell->first, j = neighbour_cell->length; j > 0; j--, i++) { /* Build certificate */ cert_add(CERT_EDGE, i, unit_cell->first); /* No need to continue? */ if(refine_compare_certificate and (refine_equal_to_first == false) and (refine_cmp_to_best < 0)) goto worse_exit; } } /* if(in_search) */ } /* while(!neighbour_heap.is_empty()) */ if(refine_compare_certificate and (refine_equal_to_first == false) and (refine_cmp_to_best < 0)) return true; return false; worse_exit: /* Clear neighbour heap */ UintSeqHash rest; while(!neighbour_heap.is_empty()) { const unsigned int start = neighbour_heap.remove(); Partition::Cell* const neighbour_cell = p.get_cell(p.elements[start]); if(opt_use_failure_recording and was_equal_to_first) { rest.update(neighbour_cell->first); rest.update(neighbour_cell->length); rest.update(neighbour_cell->max_ival_count); } neighbour_cell->max_ival_count = 0; } if(opt_use_failure_recording and was_equal_to_first) { rest.update(failure_recording_fp_deviation); failure_recording_fp_deviation = rest.get_value(); } return true; } /*------------------------------------------------------------------------- * * Check whether the current partition p is equitable. * Performance: very slow, use only for debugging purposes. * *-------------------------------------------------------------------------*/ bool Digraph::is_equitable() const { const unsigned int N = get_nof_vertices(); if(N == 0) return true; std::vector first_count = std::vector(N, 0); std::vector other_count = std::vector(N, 0); /* * Check equitabledness w.r.t. outgoing edges */ for(Partition::Cell* cell = p.first_cell; cell; cell = cell->next) { if(cell->is_unit()) continue; unsigned int* ep = p.elements + cell->first; const Vertex& first_vertex = vertices[*ep++]; /* Count outgoing edges of the first vertex for cells */ for(std::vector::const_iterator ei = first_vertex.edges_out.begin(); ei != first_vertex.edges_out.end(); ei++) { first_count[p.get_cell(*ei)->first]++; } /* Count and compare outgoing edges of the other vertices */ for(unsigned int i = cell->length; i > 1; i--) { const Vertex &vertex = vertices[*ep++]; for(std::vector::const_iterator ei = vertex.edges_out.begin(); ei != vertex.edges_out.end(); ei++) { other_count[p.get_cell(*ei)->first]++; } for(Partition::Cell *cell2 = p.first_cell; cell2; cell2 = cell2->next) { if(first_count[cell2->first] != other_count[cell2->first]) { /* Not equitable */ return false; } other_count[cell2->first] = 0; } } /* Reset first_count */ for(unsigned int i = 0; i < N; i++) first_count[i] = 0; } /* * Check equitabledness w.r.t. incoming edges */ for(Partition::Cell* cell = p.first_cell; cell; cell = cell->next) { if(cell->is_unit()) continue; unsigned int* ep = p.elements + cell->first; const Vertex& first_vertex = vertices[*ep++]; /* Count incoming edges of the first vertex for cells */ for(std::vector::const_iterator ei = first_vertex.edges_in.begin(); ei != first_vertex.edges_in.end(); ei++) { first_count[p.get_cell(*ei)->first]++; } /* Count and compare incoming edges of the other vertices */ for(unsigned int i = cell->length; i > 1; i--) { const Vertex &vertex = vertices[*ep++]; for(std::vector::const_iterator ei = vertex.edges_in.begin(); ei != vertex.edges_in.end(); ei++) { other_count[p.get_cell(*ei)->first]++; } for(Partition::Cell *cell2 = p.first_cell; cell2; cell2 = cell2->next) { if(first_count[cell2->first] != other_count[cell2->first]) { /* Not equitable */ return false; } other_count[cell2->first] = 0; } } /* Reset first_count */ for(unsigned int i = 0; i < N; i++) first_count[i] = 0; } return true; } /*------------------------------------------------------------------------- * * Build the initial equitable partition * *-------------------------------------------------------------------------*/ void Digraph::make_initial_equitable_partition() { refine_according_to_invariant(&vertex_color_invariant); p.splitting_queue_clear(); //p.print_signature(stderr); fprintf(stderr, "\n"); refine_according_to_invariant(&selfloop_invariant); p.splitting_queue_clear(); //p.print_signature(stderr); fprintf(stderr, "\n"); refine_according_to_invariant(&outdegree_invariant); p.splitting_queue_clear(); //p.print_signature(stderr); fprintf(stderr, "\n"); refine_according_to_invariant(&indegree_invariant); p.splitting_queue_clear(); //p.print_signature(stderr); fprintf(stderr, "\n"); refine_to_equitable(); //p.print_signature(stderr); fprintf(stderr, "\n"); } /*------------------------------------------------------------------------- * * Find the next cell to be splitted * *-------------------------------------------------------------------------*/ Partition::Cell* Digraph::find_next_cell_to_be_splitted(Partition::Cell* cell) { switch(sh) { case shs_f: return sh_first(); case shs_fs: return sh_first_smallest(); case shs_fl: return sh_first_largest(); case shs_fm: return sh_first_max_neighbours(); case shs_fsm: return sh_first_smallest_max_neighbours(); case shs_flm: return sh_first_largest_max_neighbours(); default: fatal_error("Internal error - unknown splitting heuristics"); return 0; } } /** \internal * A splitting heuristic. * Returns the first nonsingleton cell in the current partition. * The argument \a cell is ignored. */ Partition::Cell* Digraph::sh_first() { Partition::Cell* best_cell = 0; for(Partition::Cell* cell = p.first_nonsingleton_cell; cell; cell = cell->next_nonsingleton) { if(opt_use_comprec and p.cr_get_level(cell->first) != cr_level) continue; best_cell = cell; break; } return best_cell; } /** \internal * A splitting heuristic. * Returns the first smallest nonsingleton cell in the current partition. * The argument \a cell is ignored. */ Partition::Cell* Digraph::sh_first_smallest() { Partition::Cell* best_cell = 0; unsigned int best_size = UINT_MAX; for(Partition::Cell* cell = p.first_nonsingleton_cell; cell; cell = cell->next_nonsingleton) { if(opt_use_comprec and p.cr_get_level(cell->first) != cr_level) continue; if(cell->length < best_size) { best_size = cell->length; best_cell = cell; } } return best_cell; } /** \internal * A splitting heuristic. * Returns the first largest nonsingleton cell in the current partition. * The argument \a cell is ignored. */ Partition::Cell* Digraph::sh_first_largest() { Partition::Cell* best_cell = 0; unsigned int best_size = 0; for(Partition::Cell* cell = p.first_nonsingleton_cell; cell; cell = cell->next_nonsingleton) { if(opt_use_comprec and p.cr_get_level(cell->first) != cr_level) continue; if(cell->length > best_size) { best_size = cell->length; best_cell = cell; } } return best_cell; } /** \internal * A splitting heuristic. * Returns the first nonsingleton cell with max number of neighbouring * nonsingleton cells. * Assumes that the partition p is equitable. * Assumes that the max_ival fields of the cells are all 0. */ Partition::Cell* Digraph::sh_first_max_neighbours() { Partition::Cell* best_cell = 0; int best_value = -1; KStack neighbour_cells_visited; neighbour_cells_visited.init(get_nof_vertices()); for(Partition::Cell* cell = p.first_nonsingleton_cell; cell; cell = cell->next_nonsingleton) { if(opt_use_comprec and p.cr_get_level(cell->first) != cr_level) continue; int value = 0; const Vertex &v = vertices[p.elements[cell->first]]; std::vector::const_iterator ei; ei = v.edges_in.begin(); for(unsigned int j = v.nof_edges_in(); j > 0; j--) { Partition::Cell * const neighbour_cell = p.get_cell(*ei++); if(neighbour_cell->is_unit()) continue; neighbour_cell->max_ival++; if(neighbour_cell->max_ival == 1) neighbour_cells_visited.push(neighbour_cell); } while(!neighbour_cells_visited.is_empty()) { Partition::Cell* const neighbour_cell = neighbour_cells_visited.pop(); if(neighbour_cell->max_ival != neighbour_cell->length) value++; neighbour_cell->max_ival = 0; } ei = v.edges_out.begin(); for(unsigned int j = v.nof_edges_out(); j > 0; j--) { Partition::Cell * const neighbour_cell = p.get_cell(*ei++); if(neighbour_cell->is_unit()) continue; neighbour_cell->max_ival++; if(neighbour_cell->max_ival == 1) neighbour_cells_visited.push(neighbour_cell); } while(!neighbour_cells_visited.is_empty()) { Partition::Cell* const neighbour_cell = neighbour_cells_visited.pop(); if(neighbour_cell->max_ival != neighbour_cell->length) value++; neighbour_cell->max_ival = 0; } if(value > best_value) { best_value = value; best_cell = cell; } } return best_cell; } /** \internal * A splitting heuristic. * Returns the first smallest nonsingleton cell with max number of neighbouring * nonsingleton cells. * Assumes that the partition p is equitable. * Assumes that the max_ival fields of the cells are all 0. */ Partition::Cell* Digraph::sh_first_smallest_max_neighbours() { Partition::Cell* best_cell = 0; int best_value = -1; unsigned int best_size = UINT_MAX; KStack neighbour_cells_visited; neighbour_cells_visited.init(get_nof_vertices()); for(Partition::Cell* cell = p.first_nonsingleton_cell; cell; cell = cell->next_nonsingleton) { if(opt_use_comprec and p.cr_get_level(cell->first) != cr_level) continue; int value = 0; const Vertex& v = vertices[p.elements[cell->first]]; std::vector::const_iterator ei; ei = v.edges_in.begin(); for(unsigned int j = v.nof_edges_in(); j > 0; j--) { Partition::Cell * const neighbour_cell = p.get_cell(*ei++); if(neighbour_cell->is_unit()) continue; neighbour_cell->max_ival++; if(neighbour_cell->max_ival == 1) neighbour_cells_visited.push(neighbour_cell); } while(!neighbour_cells_visited.is_empty()) { Partition::Cell * const neighbour_cell = neighbour_cells_visited.pop(); if(neighbour_cell->max_ival != neighbour_cell->length) value++; neighbour_cell->max_ival = 0; } ei = v.edges_out.begin(); for(unsigned int j = v.nof_edges_out(); j > 0; j--) { Partition::Cell * const neighbour_cell = p.get_cell(*ei++); if(neighbour_cell->is_unit()) continue; neighbour_cell->max_ival++; if(neighbour_cell->max_ival == 1) neighbour_cells_visited.push(neighbour_cell); } while(!neighbour_cells_visited.is_empty()) { Partition::Cell * const neighbour_cell = neighbour_cells_visited.pop(); if(neighbour_cell->max_ival != neighbour_cell->length) value++; neighbour_cell->max_ival = 0; } if((value > best_value) or (value == best_value and cell->length < best_size)) { best_value = value; best_size = cell->length; best_cell = cell; } } return best_cell; } /** \internal * A splitting heuristic. * Returns the first largest nonsingleton cell with max number of neighbouring * nonsingleton cells. * Assumes that the partition p is equitable. * Assumes that the max_ival fields of the cells are all 0. */ Partition::Cell* Digraph::sh_first_largest_max_neighbours() { Partition::Cell* best_cell = 0; int best_value = -1; unsigned int best_size = 0; KStack neighbour_cells_visited; neighbour_cells_visited.init(get_nof_vertices()); for(Partition::Cell* cell = p.first_nonsingleton_cell; cell; cell = cell->next_nonsingleton) { if(opt_use_comprec and p.cr_get_level(cell->first) != cr_level) continue; int value = 0; const Vertex &v = vertices[p.elements[cell->first]]; std::vector::const_iterator ei; ei = v.edges_in.begin(); for(unsigned int j = v.nof_edges_in(); j > 0; j--) { Partition::Cell* const neighbour_cell = p.get_cell(*ei++); if(neighbour_cell->is_unit()) continue; neighbour_cell->max_ival++; if(neighbour_cell->max_ival == 1) neighbour_cells_visited.push(neighbour_cell); } while(!neighbour_cells_visited.is_empty()) { Partition::Cell* const neighbour_cell = neighbour_cells_visited.pop(); if(neighbour_cell->max_ival != neighbour_cell->length) value++; neighbour_cell->max_ival = 0; } ei = v.edges_out.begin(); for(unsigned int j = v.nof_edges_out(); j > 0; j--) { Partition::Cell* const neighbour_cell = p.get_cell(*ei++); if(neighbour_cell->is_unit()) continue; neighbour_cell->max_ival++; if(neighbour_cell->max_ival == 1) neighbour_cells_visited.push(neighbour_cell); } while(!neighbour_cells_visited.is_empty()) { Partition::Cell* const neighbour_cell = neighbour_cells_visited.pop(); if(neighbour_cell->max_ival != neighbour_cell->length) value++; neighbour_cell->max_ival = 0; } if((value > best_value) || (value == best_value && cell->length > best_size)) { best_value = value; best_size = cell->length; best_cell = cell; } } return best_cell; } /*------------------------------------------------------------------------ * * Initialize the certificate size and memory * *-------------------------------------------------------------------------*/ void Digraph::initialize_certificate() { certificate_index = 0; certificate_current_path.clear(); certificate_first_path.clear(); certificate_best_path.clear(); } /* * Check whether perm is an automorphism. * Slow, mainly for debugging and validation purposes. */ bool Digraph::is_automorphism(unsigned int* const perm) { std::set > edges1; std::set > edges2; #if defined(BLISS_CONSISTENCY_CHECKS) if(!is_permutation(get_nof_vertices(), perm)) _INTERNAL_ERROR(); #endif for(unsigned int i = 0; i < get_nof_vertices(); i++) { Vertex& v1 = vertices[i]; Vertex& v2 = vertices[perm[i]]; edges1.clear(); for(std::vector::iterator ei = v1.edges_in.begin(); ei != v1.edges_in.end(); ei++) edges1.insert(perm[*ei]); edges2.clear(); for(std::vector::iterator ei = v2.edges_in.begin(); ei != v2.edges_in.end(); ei++) edges2.insert(*ei); if(!(edges1 == edges2)) return false; edges1.clear(); for(std::vector::iterator ei = v1.edges_out.begin(); ei != v1.edges_out.end(); ei++) edges1.insert(perm[*ei]); edges2.clear(); for(std::vector::iterator ei = v2.edges_out.begin(); ei != v2.edges_out.end(); ei++) edges2.insert(*ei); if(!(edges1 == edges2)) return false; } return true; } bool Digraph::is_automorphism(const std::vector& perm) const { if(!(perm.size() == get_nof_vertices() and is_permutation(perm))) return false; std::set > edges1; std::set > edges2; for(unsigned int i = 0; i < get_nof_vertices(); i++) { const Vertex& v1 = vertices[i]; const Vertex& v2 = vertices[perm[i]]; edges1.clear(); for(std::vector::const_iterator ei = v1.edges_in.begin(); ei != v1.edges_in.end(); ei++) edges1.insert(perm[*ei]); edges2.clear(); for(std::vector::const_iterator ei = v2.edges_in.begin(); ei != v2.edges_in.end(); ei++) edges2.insert(*ei); if(!(edges1 == edges2)) return false; edges1.clear(); for(std::vector::const_iterator ei = v1.edges_out.begin(); ei != v1.edges_out.end(); ei++) edges1.insert(perm[*ei]); edges2.clear(); for(std::vector::const_iterator ei = v2.edges_out.begin(); ei != v2.edges_out.end(); ei++) edges2.insert(*ei); if(!(edges1 == edges2)) return false; } return true; } bool Digraph::nucr_find_first_component(const unsigned int level) { cr_component.clear(); cr_component_elements = 0; /* Find first non-discrete cell in the component level */ Partition::Cell* first_cell = p.first_nonsingleton_cell; while(first_cell) { if(p.cr_get_level(first_cell->first) == level) break; first_cell = first_cell->next_nonsingleton; } /* The component is discrete, return false */ if(!first_cell) return false; std::vector component; first_cell->max_ival = 1; component.push_back(first_cell); for(unsigned int i = 0; i < component.size(); i++) { Partition::Cell* const cell = component[i]; const Vertex& v = vertices[p.elements[cell->first]]; std::vector::const_iterator ei; ei = v.edges_out.begin(); for(unsigned int j = v.nof_edges_out(); j > 0; j--) { const unsigned int neighbour = *ei++; Partition::Cell* const neighbour_cell = p.get_cell(neighbour); /* Skip unit neighbours */ if(neighbour_cell->is_unit()) continue; /* Already marked to be in the same component? */ if(neighbour_cell->max_ival == 1) continue; /* Is the neighbour at the same component recursion level? */ if(p.cr_get_level(neighbour_cell->first) != level) continue; if(neighbour_cell->max_ival_count == 0) neighbour_heap.insert(neighbour_cell->first); neighbour_cell->max_ival_count++; } while(!neighbour_heap.is_empty()) { const unsigned int start = neighbour_heap.remove(); Partition::Cell* const neighbour_cell = p.get_cell(p.elements[start]); /* Skip saturated neighbour cells */ if(neighbour_cell->max_ival_count == neighbour_cell->length) { neighbour_cell->max_ival_count = 0; continue; } neighbour_cell->max_ival_count = 0; neighbour_cell->max_ival = 1; component.push_back(neighbour_cell); } ei = v.edges_in.begin(); for(unsigned int j = v.nof_edges_in(); j > 0; j--) { const unsigned int neighbour = *ei++; Partition::Cell* const neighbour_cell = p.get_cell(neighbour); /* Skip unit neighbours */ if(neighbour_cell->is_unit()) continue; /* Already marked to be in the same component? */ if(neighbour_cell->max_ival == 1) continue; /* Is the neighbour at the same component recursion level? */ if(p.cr_get_level(neighbour_cell->first) != level) continue; if(neighbour_cell->max_ival_count == 0) neighbour_heap.insert(neighbour_cell->first); neighbour_cell->max_ival_count++; } while(!neighbour_heap.is_empty()) { const unsigned int start = neighbour_heap.remove(); Partition::Cell* const neighbour_cell = p.get_cell(p.elements[start]); /* Skip saturated neighbour cells */ if(neighbour_cell->max_ival_count == neighbour_cell->length) { neighbour_cell->max_ival_count = 0; continue; } neighbour_cell->max_ival_count = 0; neighbour_cell->max_ival = 1; component.push_back(neighbour_cell); } } for(unsigned int i = 0; i < component.size(); i++) { Partition::Cell* const cell = component[i]; cell->max_ival = 0; cr_component.push_back(cell->first); cr_component_elements += cell->length; } if(verbstr and verbose_level > 2) { fprintf(verbstr, "NU-component with %lu cells and %u vertices\n", (long unsigned)cr_component.size(), cr_component_elements); fflush(verbstr); } return true; } bool Digraph::nucr_find_first_component(const unsigned int level, std::vector& component, unsigned int& component_elements, Partition::Cell*& sh_return) { component.clear(); component_elements = 0; sh_return = 0; unsigned int sh_first = 0; unsigned int sh_size = 0; unsigned int sh_nuconn = 0; /* Find first non-discrete cell in the component level */ Partition::Cell* first_cell = p.first_nonsingleton_cell; while(first_cell) { if(p.cr_get_level(first_cell->first) == level) break; first_cell = first_cell->next_nonsingleton; } if(!first_cell) { /* The component is discrete, return false */ return false; } std::vector comp; KStack neighbours; neighbours.init(get_nof_vertices()); first_cell->max_ival = 1; comp.push_back(first_cell); for(unsigned int i = 0; i < comp.size(); i++) { Partition::Cell* const cell = comp[i]; unsigned int nuconn = 1; const Vertex& v = vertices[p.elements[cell->first]]; std::vector::const_iterator ei; /*| Phase 1: outgoing edges */ ei = v.edges_out.begin(); for(unsigned int j = v.nof_edges_out(); j > 0; j--) { const unsigned int neighbour = *ei++; Partition::Cell* const neighbour_cell = p.get_cell(neighbour); /* Skip unit neighbours */ if(neighbour_cell->is_unit()) continue; /* Is the neighbour at the same component recursion level? */ //if(p.cr_get_level(neighbour_cell->first) != level) // continue; if(neighbour_cell->max_ival_count == 0) neighbours.push(neighbour_cell); neighbour_cell->max_ival_count++; } while(!neighbours.is_empty()) { Partition::Cell* const neighbour_cell = neighbours.pop(); /* Skip saturated neighbour cells */ if(neighbour_cell->max_ival_count == neighbour_cell->length) { neighbour_cell->max_ival_count = 0; continue; } nuconn++; neighbour_cell->max_ival_count = 0; if(neighbour_cell->max_ival == 0) { comp.push_back(neighbour_cell); neighbour_cell->max_ival = 1; } } /*| Phase 2: incoming edges */ ei = v.edges_in.begin(); for(unsigned int j = v.nof_edges_in(); j > 0; j--) { const unsigned int neighbour = *ei++; Partition::Cell* const neighbour_cell = p.get_cell(neighbour); /*| Skip unit neighbours */ if(neighbour_cell->is_unit()) continue; /* Is the neighbour at the same component recursion level? */ //if(p.cr_get_level(neighbour_cell->first) != level) // continue; if(neighbour_cell->max_ival_count == 0) neighbours.push(neighbour_cell); neighbour_cell->max_ival_count++; } while(!neighbours.is_empty()) { Partition::Cell* const neighbour_cell = neighbours.pop(); /* Skip saturated neighbour cells */ if(neighbour_cell->max_ival_count == neighbour_cell->length) { neighbour_cell->max_ival_count = 0; continue; } nuconn++; neighbour_cell->max_ival_count = 0; if(neighbour_cell->max_ival == 0) { comp.push_back(neighbour_cell); neighbour_cell->max_ival = 1; } } /*| Phase 3: splitting heuristics */ switch(sh) { case shs_f: if(sh_return == 0 or cell->first <= sh_first) { sh_return = cell; sh_first = cell->first; } break; case shs_fs: if(sh_return == 0 or cell->length < sh_size or (cell->length == sh_size and cell->first <= sh_first)) { sh_return = cell; sh_first = cell->first; sh_size = cell->length; } break; case shs_fl: if(sh_return == 0 or cell->length > sh_size or (cell->length == sh_size and cell->first <= sh_first)) { sh_return = cell; sh_first = cell->first; sh_size = cell->length; } break; case shs_fm: if(sh_return == 0 or nuconn > sh_nuconn or (nuconn == sh_nuconn and cell->first <= sh_first)) { sh_return = cell; sh_first = cell->first; sh_nuconn = nuconn; } break; case shs_fsm: if(sh_return == 0 or nuconn > sh_nuconn or (nuconn == sh_nuconn and (cell->length < sh_size or (cell->length == sh_size and cell->first <= sh_first)))) { sh_return = cell; sh_first = cell->first; sh_size = cell->length; sh_nuconn = nuconn; } break; case shs_flm: if(sh_return == 0 or nuconn > sh_nuconn or (nuconn == sh_nuconn and (cell->length > sh_size or (cell->length == sh_size and cell->first <= sh_first)))) { sh_return = cell; sh_first = cell->first; sh_size = cell->length; sh_nuconn = nuconn; } break; default: fatal_error("Internal error - unknown splitting heuristics"); return 0; } } assert(sh_return); for(unsigned int i = 0; i < comp.size(); i++) { Partition::Cell* const cell = comp[i]; cell->max_ival = 0; component.push_back(cell->first); component_elements += cell->length; } if(verbstr and verbose_level > 2) { fprintf(verbstr, "NU-component with %lu cells and %u vertices\n", (long unsigned)component.size(), component_elements); fflush(verbstr); } return true; } /*------------------------------------------------------------------------- * * Routines for undirected graphs * *-------------------------------------------------------------------------*/ Graph::Vertex::Vertex() { color = 0; } Graph::Vertex::~Vertex() { ; } void Graph::Vertex::add_edge(const unsigned int other_vertex) { edges.push_back(other_vertex); } void Graph::Vertex::remove_duplicate_edges(std::vector& tmp) { #if defined(BLISS_CONSISTENCY_CHECKS) /* Pre-conditions */ for(unsigned int i = 0; i < tmp.size(); i++) assert(tmp[i] == false); #endif for(std::vector::iterator iter = edges.begin(); iter != edges.end(); ) { const unsigned int dest_vertex = *iter; if(tmp[dest_vertex] == true) { /* A duplicate edge found! */ iter = edges.erase(iter); } else { /* Not seen earlier, mark as seen */ tmp[dest_vertex] = true; iter++; } } /* Clear tmp */ for(std::vector::iterator iter = edges.begin(); iter != edges.end(); iter++) { tmp[*iter] = false; } #if defined(BLISS_CONSISTENCY_CHECKS) /* Post-conditions */ for(unsigned int i = 0; i < tmp.size(); i++) assert(tmp[i] == false); #endif } /** * Sort the edges leaving the vertex according to * the vertex number of the other edge end. * Time complexity: O(e log(e)), where e is the number of edges * leaving the vertex. */ void Graph::Vertex::sort_edges() { std::sort(edges.begin(), edges.end()); } /*------------------------------------------------------------------------- * * Constructor and destructor for undirected graphs * *-------------------------------------------------------------------------*/ Graph::Graph(const unsigned int nof_vertices) { vertices.resize(nof_vertices); sh = shs_flm; } Graph::~Graph() { ; } unsigned int Graph::add_vertex(const unsigned int color) { const unsigned int vertex_num = vertices.size(); vertices.resize(vertex_num + 1); vertices.back().color = color; return vertex_num; } void Graph::add_edge(const unsigned int vertex1, const unsigned int vertex2) { //fprintf(stderr, "(%u,%u) ", vertex1, vertex2); vertices[vertex1].add_edge(vertex2); vertices[vertex2].add_edge(vertex1); } void Graph::change_color(const unsigned int vertex, const unsigned int color) { vertices[vertex].color = color; } /*------------------------------------------------------------------------- * * Read graph in the DIMACS format. * Returns 0 if an error occurred. * *-------------------------------------------------------------------------*/ Graph* Graph::read_dimacs(FILE* const fp, FILE* const errstr) { Graph *g = 0; unsigned int nof_vertices; unsigned int nof_edges; unsigned int line_num = 1; int c; const bool verbose = false; FILE* const verbstr = stdout; /* Read comments and the problem definition line */ while(1) { c = getc(fp); if(c == 'c') { /* A comment, ignore the rest of the line */ while((c = getc(fp)) != '\n') { if(c == EOF) { if(errstr) fprintf(errstr, "error in line %u: not in DIMACS format\n", line_num); goto error_exit; } } line_num++; continue; } if(c == 'p') { /* The problem definition line */ if(fscanf(fp, " edge %u %u\n", &nof_vertices, &nof_edges) != 2) { if(errstr) fprintf(errstr, "error in line %u: not in DIMACS format\n", line_num); goto error_exit; } line_num++; break; } if(errstr) fprintf(errstr, "error in line %u: not in DIMACS format\n", line_num); goto error_exit; } if(nof_vertices <= 0) { if(errstr) fprintf(errstr, "error: no vertices\n"); goto error_exit; } if(verbose) { fprintf(verbstr, "Instance has %d vertices and %d edges\n", nof_vertices, nof_edges); fflush(verbstr); } g = new Graph(nof_vertices); // // Read vertex colors // if(verbose) { fprintf(verbstr, "Reading vertex colors...\n"); fflush(verbstr); } while(1) { c = getc(fp); if(c != 'n') { ungetc(c, fp); break; } ungetc(c, fp); unsigned int vertex; unsigned int color; if(fscanf(fp, "n %u %u\n", &vertex, &color) != 2) { if(errstr) fprintf(errstr, "error in line %u: not in DIMACS format\n", line_num); goto error_exit; } if(!((vertex >= 1) && (vertex <= nof_vertices))) { if(errstr) fprintf(errstr, "error in line %u: vertex %u not in range [1,...,%u]\n", line_num, vertex, nof_vertices); goto error_exit; } line_num++; g->change_color(vertex - 1, color); } if(verbose) { fprintf(verbstr, "Done\n"); fflush(verbstr); } // // Read edges // if(verbose) { fprintf(verbstr, "Reading edges...\n"); fflush(verbstr); } for(unsigned i = 0; i < nof_edges; i++) { unsigned int from, to; if(fscanf(fp, "e %u %u\n", &from, &to) != 2) { if(errstr) fprintf(errstr, "error in line %u: not in DIMACS format\n", line_num); goto error_exit; } if(!((from >= 1) && (from <= nof_vertices))) { if(errstr) fprintf(errstr, "error in line %u: vertex %u not in range [1,...,%u]\n", line_num, from, nof_vertices); goto error_exit; } if(!((to >= 1) && (to <= nof_vertices))) { if(errstr) fprintf(errstr, "error in line %u: vertex %u not in range [1,...,%u]\n", line_num, to, nof_vertices); goto error_exit; } line_num++; g->add_edge(from-1, to-1); } if(verbose) { fprintf(verbstr, "Done\n"); fflush(verbstr); } return g; error_exit: if(g) delete g; return 0; } void Graph::write_dimacs(FILE* const fp) { remove_duplicate_edges(); sort_edges(); /* First count the total number of edges */ unsigned int nof_edges = 0; for(unsigned int i = 0; i < get_nof_vertices(); i++) { Vertex &v = vertices[i]; for(std::vector::const_iterator ei = v.edges.begin(); ei != v.edges.end(); ei++) { const unsigned int dest_i = *ei; if(dest_i < i) continue; nof_edges++; } } /* Output the "header" line */ fprintf(fp, "p edge %u %u\n", get_nof_vertices(), nof_edges); /* Print the color of each vertex */ for(unsigned int i = 0; i < get_nof_vertices(); i++) { Vertex &v = vertices[i]; fprintf(fp, "n %u %u\n", i+1, v.color); /* if(v.color != 0) { fprintf(fp, "n %u %u\n", i+1, v.color); } */ } /* Print the edges */ for(unsigned int i = 0; i < get_nof_vertices(); i++) { Vertex &v = vertices[i]; for(std::vector::const_iterator ei = v.edges.begin(); ei != v.edges.end(); ei++) { const unsigned int dest_i = *ei; if(dest_i < i) continue; fprintf(fp, "e %u %u\n", i+1, dest_i+1); } } } void Graph::sort_edges() { for(unsigned int i = 0; i < get_nof_vertices(); i++) vertices[i].sort_edges(); } int Graph::cmp(Graph& other) { /* Compare the numbers of vertices */ if(get_nof_vertices() < other.get_nof_vertices()) return -1; if(get_nof_vertices() > other.get_nof_vertices()) return 1; /* Compare vertex colors */ for(unsigned int i = 0; i < get_nof_vertices(); i++) { if(vertices[i].color < other.vertices[i].color) return -1; if(vertices[i].color > other.vertices[i].color) return 1; } /* Compare vertex degrees */ remove_duplicate_edges(); other.remove_duplicate_edges(); for(unsigned int i = 0; i < get_nof_vertices(); i++) { if(vertices[i].nof_edges() < other.vertices[i].nof_edges()) return -1; if(vertices[i].nof_edges() > other.vertices[i].nof_edges()) return 1; } /* Compare edges */ for(unsigned int i = 0; i < get_nof_vertices(); i++) { Vertex &v1 = vertices[i]; Vertex &v2 = other.vertices[i]; v1.sort_edges(); v2.sort_edges(); std::vector::const_iterator ei1 = v1.edges.begin(); std::vector::const_iterator ei2 = v2.edges.begin(); while(ei1 != v1.edges.end()) { if(*ei1 < *ei2) return -1; if(*ei1 > *ei2) return 1; ei1++; ei2++; } } return 0; } Graph* Graph::permute(const std::vector& perm) const { #if defined(BLISS_CONSISTENCY_CHECKS) #endif Graph* const g = new Graph(get_nof_vertices()); for(unsigned int i = 0; i < get_nof_vertices(); i++) { const Vertex& v = vertices[i]; Vertex& permuted_v = g->vertices[perm[i]]; permuted_v.color = v.color; for(std::vector::const_iterator ei = v.edges.begin(); ei != v.edges.end(); ei++) { const unsigned int dest_v = *ei; permuted_v.add_edge(perm[dest_v]); } permuted_v.sort_edges(); } return g; } Graph* Graph::permute(const unsigned int* perm) const { #if defined(BLISS_CONSISTENCY_CHECKS) if(!is_permutation(get_nof_vertices(), perm)) _INTERNAL_ERROR(); #endif Graph* const g = new Graph(get_nof_vertices()); for(unsigned int i = 0; i < get_nof_vertices(); i++) { const Vertex& v = vertices[i]; Vertex& permuted_v = g->vertices[perm[i]]; permuted_v.color = v.color; for(std::vector::const_iterator ei = v.edges.begin(); ei != v.edges.end(); ei++) { const unsigned int dest_v = *ei; permuted_v.add_edge(perm[dest_v]); } permuted_v.sort_edges(); } return g; } /*------------------------------------------------------------------------- * * Print graph in graphviz format * *-------------------------------------------------------------------------*/ void Graph::write_dot(const char* const filename) { FILE *fp = fopen(filename, "w"); if(fp) { write_dot(fp); fclose(fp); } } void Graph::write_dot(FILE* const fp) { remove_duplicate_edges(); fprintf(fp, "graph g {\n"); unsigned int vnum = 0; for(std::vector::iterator vi = vertices.begin(); vi != vertices.end(); vi++, vnum++) { Vertex& v = *vi; fprintf(fp, "v%u [label=\"%u:%u\"];\n", vnum, vnum, v.color); for(std::vector::const_iterator ei = v.edges.begin(); ei != v.edges.end(); ei++) { const unsigned int vnum2 = *ei; if(vnum2 > vnum) fprintf(fp, "v%u -- v%u\n", vnum, vnum2); } } fprintf(fp, "}\n"); } /*------------------------------------------------------------------------- * * Get a hash value for the graph. * *-------------------------------------------------------------------------*/ unsigned int Graph::get_hash() { remove_duplicate_edges(); sort_edges(); UintSeqHash h; h.update(get_nof_vertices()); /* Hash the color of each vertex */ for(unsigned int i = 0; i < get_nof_vertices(); i++) { h.update(vertices[i].color); } /* Hash the edges */ for(unsigned int i = 0; i < get_nof_vertices(); i++) { Vertex &v = vertices[i]; for(std::vector::const_iterator ei = v.edges.begin(); ei != v.edges.end(); ei++) { const unsigned int dest_i = *ei; if(dest_i < i) continue; h.update(i); h.update(dest_i); } } return h.get_value(); } void Graph::remove_duplicate_edges() { std::vector tmp(vertices.size(), false); for(std::vector::iterator vi = vertices.begin(); vi != vertices.end(); vi++) { #if defined(BLISS_EXPENSIVE_CONSISTENCY_CHECKS) for(unsigned int i = 0; i < tmp.size(); i++) assert(tmp[i] == false); #endif (*vi).remove_duplicate_edges(tmp); } } /*------------------------------------------------------------------------- * * Partition independent invariants * *-------------------------------------------------------------------------*/ /* * Return the color of the vertex. * Time complexity: O(1) */ unsigned int Graph::vertex_color_invariant(const Graph* const g, const unsigned int v) { return g->vertices[v].color; } /* * Return the degree of the vertex. * Time complexity: O(1) */ unsigned int Graph::degree_invariant(const Graph* const g, const unsigned int v) { return g->vertices[v].nof_edges(); } /* * Return 1 if the vertex v has a self-loop, 0 otherwise * Time complexity: O(E_v), where E_v is the number of edges leaving v */ unsigned int Graph::selfloop_invariant(const Graph* const g, const unsigned int v) { const Vertex& vertex = g->vertices[v]; for(std::vector::const_iterator ei = vertex.edges.begin(); ei != vertex.edges.end(); ei++) { if(*ei == v) return 1; } return 0; } /*------------------------------------------------------------------------- * * Refine the partition p according to a partition independent invariant * *-------------------------------------------------------------------------*/ bool Graph::refine_according_to_invariant(unsigned int (*inv)(const Graph* const g, const unsigned int v)) { bool refined = false; for(Partition::Cell* cell = p.first_nonsingleton_cell; cell; ) { Partition::Cell* const next_cell = cell->next_nonsingleton; const unsigned int* ep = p.elements + cell->first; for(unsigned int i = cell->length; i > 0; i--, ep++) { const unsigned int ival = inv(this, *ep); p.invariant_values[*ep] = ival; if(ival > cell->max_ival) { cell->max_ival = ival; cell->max_ival_count = 1; } else if(ival == cell->max_ival) { cell->max_ival_count++; } } Partition::Cell* const last_new_cell = p.zplit_cell(cell, true); refined |= (last_new_cell != cell); cell = next_cell; } return refined; } /*------------------------------------------------------------------------- * * Split the neighbourhood of a cell according to the equitable invariant * *-------------------------------------------------------------------------*/ bool Graph::split_neighbourhood_of_cell(Partition::Cell* const cell) { const bool was_equal_to_first = refine_equal_to_first; if(compute_eqref_hash) { eqref_hash.update(cell->first); eqref_hash.update(cell->length); } const unsigned int* ep = p.elements + cell->first; for(unsigned int i = cell->length; i > 0; i--) { const Vertex& v = vertices[*ep++]; std::vector::const_iterator ei = v.edges.begin(); for(unsigned int j = v.nof_edges(); j != 0; j--) { const unsigned int dest_vertex = *ei++; Partition::Cell * const neighbour_cell = p.get_cell(dest_vertex); if(neighbour_cell->is_unit()) continue; const unsigned int ival = ++p.invariant_values[dest_vertex]; if(ival > neighbour_cell->max_ival) { neighbour_cell->max_ival = ival; neighbour_cell->max_ival_count = 1; if(ival == 1) { neighbour_heap.insert(neighbour_cell->first); } } else if(ival == neighbour_cell->max_ival) { neighbour_cell->max_ival_count++; } } } while(!neighbour_heap.is_empty()) { const unsigned int start = neighbour_heap.remove(); Partition::Cell * const neighbour_cell = p.get_cell(p.elements[start]); if(compute_eqref_hash) { eqref_hash.update(neighbour_cell->first); eqref_hash.update(neighbour_cell->length); eqref_hash.update(neighbour_cell->max_ival); eqref_hash.update(neighbour_cell->max_ival_count); } Partition::Cell* const last_new_cell = p.zplit_cell(neighbour_cell, true); /* Update certificate and hash if needed */ const Partition::Cell* c = neighbour_cell; while(1) { if(in_search) { /* Build certificate */ cert_add_redundant(CERT_SPLIT, c->first, c->length); /* No need to continue? */ if(refine_compare_certificate and (refine_equal_to_first == false) and (refine_cmp_to_best < 0)) goto worse_exit; } if(compute_eqref_hash) { eqref_hash.update(c->first); eqref_hash.update(c->length); } if(c == last_new_cell) break; c = c->next; } } if(refine_compare_certificate and (refine_equal_to_first == false) and (refine_cmp_to_best < 0)) return true; return false; worse_exit: /* Clear neighbour heap */ UintSeqHash rest; while(!neighbour_heap.is_empty()) { const unsigned int start = neighbour_heap.remove(); Partition::Cell * const neighbour_cell = p.get_cell(p.elements[start]); if(opt_use_failure_recording and was_equal_to_first) { rest.update(neighbour_cell->first); rest.update(neighbour_cell->length); rest.update(neighbour_cell->max_ival); rest.update(neighbour_cell->max_ival_count); } neighbour_cell->max_ival = 0; neighbour_cell->max_ival_count = 0; p.clear_ivs(neighbour_cell); } if(opt_use_failure_recording and was_equal_to_first) { for(unsigned int i = p.splitting_queue.size(); i > 0; i--) { Partition::Cell* const cell = p.splitting_queue.pop_front(); rest.update(cell->first); rest.update(cell->length); p.splitting_queue.push_back(cell); } rest.update(failure_recording_fp_deviation); failure_recording_fp_deviation = rest.get_value(); } return true; } bool Graph::split_neighbourhood_of_unit_cell(Partition::Cell* const unit_cell) { const bool was_equal_to_first = refine_equal_to_first; if(compute_eqref_hash) { eqref_hash.update(0x87654321); eqref_hash.update(unit_cell->first); eqref_hash.update(1); } const Vertex& v = vertices[p.elements[unit_cell->first]]; std::vector::const_iterator ei = v.edges.begin(); for(unsigned int j = v.nof_edges(); j > 0; j--) { const unsigned int dest_vertex = *ei++; Partition::Cell * const neighbour_cell = p.get_cell(dest_vertex); if(neighbour_cell->is_unit()) { if(in_search) { /* Remember neighbour in order to generate certificate */ neighbour_heap.insert(neighbour_cell->first); } continue; } if(neighbour_cell->max_ival_count == 0) { neighbour_heap.insert(neighbour_cell->first); } neighbour_cell->max_ival_count++; unsigned int * const swap_position = p.elements + neighbour_cell->first + neighbour_cell->length - neighbour_cell->max_ival_count; *p.in_pos[dest_vertex] = *swap_position; p.in_pos[*swap_position] = p.in_pos[dest_vertex]; *swap_position = dest_vertex; p.in_pos[dest_vertex] = swap_position; } while(!neighbour_heap.is_empty()) { const unsigned int start = neighbour_heap.remove(); Partition::Cell* neighbour_cell = p.get_cell(p.elements[start]); #if defined(BLISS_CONSISTENCY_CHECKS) if(neighbour_cell->is_unit()) { } else { } #endif if(compute_eqref_hash) { eqref_hash.update(neighbour_cell->first); eqref_hash.update(neighbour_cell->length); eqref_hash.update(neighbour_cell->max_ival_count); } if(neighbour_cell->length > 1 and neighbour_cell->max_ival_count != neighbour_cell->length) { Partition::Cell * const new_cell = p.aux_split_in_two(neighbour_cell, neighbour_cell->length - neighbour_cell->max_ival_count); unsigned int *ep = p.elements + new_cell->first; unsigned int * const lp = p.elements+new_cell->first+new_cell->length; while(ep < lp) { p.element_to_cell_map[*ep] = new_cell; ep++; } neighbour_cell->max_ival_count = 0; if(compute_eqref_hash) { /* Update hash */ eqref_hash.update(neighbour_cell->first); eqref_hash.update(neighbour_cell->length); eqref_hash.update(0); eqref_hash.update(new_cell->first); eqref_hash.update(new_cell->length); eqref_hash.update(1); } /* Add cells in splitting_queue */ if(neighbour_cell->is_in_splitting_queue()) { /* Both cells must be included in splitting_queue in order to ensure refinement into equitable partition */ p.splitting_queue_add(new_cell); } else { Partition::Cell *min_cell, *max_cell; if(neighbour_cell->length <= new_cell->length) { min_cell = neighbour_cell; max_cell = new_cell; } else { min_cell = new_cell; max_cell = neighbour_cell; } /* Put the smaller cell in splitting_queue */ p.splitting_queue_add(min_cell); if(max_cell->is_unit()) { /* Put the "larger" cell also in splitting_queue */ p.splitting_queue_add(max_cell); } } /* Update pointer for certificate generation */ neighbour_cell = new_cell; } else { /* neighbour_cell->length == 1 || neighbour_cell->max_ival_count == neighbour_cell->length */ neighbour_cell->max_ival_count = 0; } /* * Build certificate if required */ if(in_search) { for(unsigned int i = neighbour_cell->first, j = neighbour_cell->length; j > 0; j--, i++) { /* Build certificate */ cert_add(CERT_EDGE, unit_cell->first, i); /* No need to continue? */ if(refine_compare_certificate and (refine_equal_to_first == false) and (refine_cmp_to_best < 0)) goto worse_exit; } } /* if(in_search) */ } /* while(!neighbour_heap.is_empty()) */ if(refine_compare_certificate and (refine_equal_to_first == false) and (refine_cmp_to_best < 0)) return true; return false; worse_exit: /* Clear neighbour heap */ UintSeqHash rest; while(!neighbour_heap.is_empty()) { const unsigned int start = neighbour_heap.remove(); Partition::Cell * const neighbour_cell = p.get_cell(p.elements[start]); if(opt_use_failure_recording and was_equal_to_first) { rest.update(neighbour_cell->first); rest.update(neighbour_cell->length); rest.update(neighbour_cell->max_ival_count); } neighbour_cell->max_ival_count = 0; } if(opt_use_failure_recording and was_equal_to_first) { rest.update(failure_recording_fp_deviation); failure_recording_fp_deviation = rest.get_value(); } return true; } /*------------------------------------------------------------------------- * * Check whether the current partition p is equitable. * Performance: very slow, use only for debugging purposes. * *-------------------------------------------------------------------------*/ bool Graph::is_equitable() const { const unsigned int N = get_nof_vertices(); if(N == 0) return true; std::vector first_count = std::vector(N, 0); std::vector other_count = std::vector(N, 0); for(Partition::Cell *cell = p.first_cell; cell; cell = cell->next) { if(cell->is_unit()) continue; unsigned int *ep = p.elements + cell->first; const Vertex &first_vertex = vertices[*ep++]; /* Count how many edges lead from the first vertex to * the neighbouring cells */ for(std::vector::const_iterator ei = first_vertex.edges.begin(); ei != first_vertex.edges.end(); ei++) { first_count[p.get_cell(*ei)->first]++; } /* Count and compare to the edges of the other vertices */ for(unsigned int i = cell->length; i > 1; i--) { const Vertex &vertex = vertices[*ep++]; for(std::vector::const_iterator ei = vertex.edges.begin(); ei != vertex.edges.end(); ei++) { other_count[p.get_cell(*ei)->first]++; } for(Partition::Cell *cell2 = p.first_cell; cell2; cell2 = cell2->next) { if(first_count[cell2->first] != other_count[cell2->first]) { /* Not equitable */ return false; } other_count[cell2->first] = 0; } } /* Reset first_count */ for(unsigned int i = 0; i < N; i++) first_count[i] = 0; } return true; } /*------------------------------------------------------------------------- * * Build the initial equitable partition * *-------------------------------------------------------------------------*/ void Graph::make_initial_equitable_partition() { refine_according_to_invariant(&vertex_color_invariant); p.splitting_queue_clear(); //p.print_signature(stderr); fprintf(stderr, "\n"); refine_according_to_invariant(&selfloop_invariant); p.splitting_queue_clear(); //p.print_signature(stderr); fprintf(stderr, "\n"); refine_according_to_invariant(°ree_invariant); p.splitting_queue_clear(); //p.print_signature(stderr); fprintf(stderr, "\n"); refine_to_equitable(); //p.print_signature(stderr); fprintf(stderr, "\n"); } /*------------------------------------------------------------------------- * * Find the next cell to be splitted * *-------------------------------------------------------------------------*/ Partition::Cell* Graph::find_next_cell_to_be_splitted(Partition::Cell* cell) { switch(sh) { case shs_f: return sh_first(); case shs_fs: return sh_first_smallest(); case shs_fl: return sh_first_largest(); case shs_fm: return sh_first_max_neighbours(); case shs_fsm: return sh_first_smallest_max_neighbours(); case shs_flm: return sh_first_largest_max_neighbours(); default: fatal_error("Internal error - unknown splitting heuristics"); return 0; } } /** \internal * A splitting heuristic. * Returns the first nonsingleton cell in the current partition. */ Partition::Cell* Graph::sh_first() { Partition::Cell* best_cell = 0; for(Partition::Cell* cell = p.first_nonsingleton_cell; cell; cell = cell->next_nonsingleton) { if(opt_use_comprec and p.cr_get_level(cell->first) != cr_level) continue; best_cell = cell; break; } return best_cell; } /** \internal * A splitting heuristic. * Returns the first smallest nonsingleton cell in the current partition. */ Partition::Cell* Graph::sh_first_smallest() { Partition::Cell* best_cell = 0; unsigned int best_size = UINT_MAX; for(Partition::Cell* cell = p.first_nonsingleton_cell; cell; cell = cell->next_nonsingleton) { if(opt_use_comprec and p.cr_get_level(cell->first) != cr_level) continue; if(cell->length < best_size) { best_size = cell->length; best_cell = cell; } } return best_cell; } /** \internal * A splitting heuristic. * Returns the first largest nonsingleton cell in the current partition. */ Partition::Cell* Graph::sh_first_largest() { Partition::Cell* best_cell = 0; unsigned int best_size = 0; for(Partition::Cell* cell = p.first_nonsingleton_cell; cell; cell = cell->next_nonsingleton) { if(opt_use_comprec and p.cr_get_level(cell->first) != cr_level) continue; if(cell->length > best_size) { best_size = cell->length; best_cell = cell; } } return best_cell; } /** \internal * A splitting heuristic. * Returns the first nonsingleton cell with max number of neighbouring * nonsingleton cells. * Assumes that the partition p is equitable. * Assumes that the max_ival fields of the cells are all 0. */ Partition::Cell* Graph::sh_first_max_neighbours() { Partition::Cell* best_cell = 0; int best_value = -1; KStack neighbour_cells_visited; neighbour_cells_visited.init(get_nof_vertices()); for(Partition::Cell* cell = p.first_nonsingleton_cell; cell; cell = cell->next_nonsingleton) { if(opt_use_comprec and p.cr_get_level(cell->first) != cr_level) continue; const Vertex& v = vertices[p.elements[cell->first]]; std::vector::const_iterator ei = v.edges.begin(); for(unsigned int j = v.nof_edges(); j > 0; j--) { Partition::Cell * const neighbour_cell = p.get_cell(*ei++); if(neighbour_cell->is_unit()) continue; neighbour_cell->max_ival++; if(neighbour_cell->max_ival == 1) neighbour_cells_visited.push(neighbour_cell); } int value = 0; while(!neighbour_cells_visited.is_empty()) { Partition::Cell* const neighbour_cell = neighbour_cells_visited.pop(); if(neighbour_cell->max_ival != neighbour_cell->length) value++; neighbour_cell->max_ival = 0; } if(value > best_value) { best_value = value; best_cell = cell; } } return best_cell; } /** \internal * A splitting heuristic. * Returns the first smallest nonsingleton cell with max number of neighbouring * nonsingleton cells. * Assumes that the partition p is equitable. * Assumes that the max_ival fields of the cells are all 0. */ Partition::Cell* Graph::sh_first_smallest_max_neighbours() { Partition::Cell* best_cell = 0; int best_value = -1; unsigned int best_size = UINT_MAX; KStack neighbour_cells_visited; neighbour_cells_visited.init(get_nof_vertices()); for(Partition::Cell* cell = p.first_nonsingleton_cell; cell; cell = cell->next_nonsingleton) { if(opt_use_comprec and p.cr_get_level(cell->first) != cr_level) continue; const Vertex& v = vertices[p.elements[cell->first]]; std::vector::const_iterator ei = v.edges.begin(); for(unsigned int j = v.nof_edges(); j > 0; j--) { Partition::Cell* const neighbour_cell = p.get_cell(*ei++); if(neighbour_cell->is_unit()) continue; neighbour_cell->max_ival++; if(neighbour_cell->max_ival == 1) neighbour_cells_visited.push(neighbour_cell); } int value = 0; while(!neighbour_cells_visited.is_empty()) { Partition::Cell* const neighbour_cell = neighbour_cells_visited.pop(); if(neighbour_cell->max_ival != neighbour_cell->length) value++; neighbour_cell->max_ival = 0; } if((value > best_value) or (value == best_value and cell->length < best_size)) { best_value = value; best_size = cell->length; best_cell = cell; } } return best_cell; } /** \internal * A splitting heuristic. * Returns the first largest nonsingleton cell with max number of neighbouring * nonsingleton cells. * Assumes that the partition p is equitable. * Assumes that the max_ival fields of the cells are all 0. */ Partition::Cell* Graph::sh_first_largest_max_neighbours() { Partition::Cell* best_cell = 0; int best_value = -1; unsigned int best_size = 0; KStack neighbour_cells_visited; neighbour_cells_visited.init(get_nof_vertices()); for(Partition::Cell* cell = p.first_nonsingleton_cell; cell; cell = cell->next_nonsingleton) { if(opt_use_comprec and p.cr_get_level(cell->first) != cr_level) continue; const Vertex& v = vertices[p.elements[cell->first]]; std::vector::const_iterator ei = v.edges.begin(); for(unsigned int j = v.nof_edges(); j > 0; j--) { Partition::Cell* const neighbour_cell = p.get_cell(*ei++); if(neighbour_cell->is_unit()) continue; neighbour_cell->max_ival++; if(neighbour_cell->max_ival == 1) neighbour_cells_visited.push(neighbour_cell); } int value = 0; while(!neighbour_cells_visited.is_empty()) { Partition::Cell* const neighbour_cell = neighbour_cells_visited.pop(); if(neighbour_cell->max_ival != neighbour_cell->length) value++; neighbour_cell->max_ival = 0; } if((value > best_value) or (value == best_value and cell->length > best_size)) { best_value = value; best_size = cell->length; best_cell = cell; } } return best_cell; } /*------------------------------------------------------------------------- * * Initialize the certificate size and memory * *-------------------------------------------------------------------------*/ void Graph::initialize_certificate() { certificate_index = 0; certificate_current_path.clear(); certificate_first_path.clear(); certificate_best_path.clear(); } /*------------------------------------------------------------------------- * * Check whether perm is an automorphism. * Slow, mainly for debugging and validation purposes. * *-------------------------------------------------------------------------*/ bool Graph::is_automorphism(unsigned int* const perm) { std::set > edges1; std::set > edges2; #if defined(BLISS_CONSISTENCY_CHECKS) if(!is_permutation(get_nof_vertices(), perm)) _INTERNAL_ERROR(); #endif for(unsigned int i = 0; i < get_nof_vertices(); i++) { Vertex& v1 = vertices[i]; edges1.clear(); for(std::vector::iterator ei = v1.edges.begin(); ei != v1.edges.end(); ei++) edges1.insert(perm[*ei]); Vertex& v2 = vertices[perm[i]]; edges2.clear(); for(std::vector::iterator ei = v2.edges.begin(); ei != v2.edges.end(); ei++) edges2.insert(*ei); if(!(edges1 == edges2)) return false; } return true; } bool Graph::is_automorphism(const std::vector& perm) const { if(!(perm.size() == get_nof_vertices() and is_permutation(perm))) return false; std::set > edges1; std::set > edges2; for(unsigned int i = 0; i < get_nof_vertices(); i++) { const Vertex& v1 = vertices[i]; edges1.clear(); for(std::vector::const_iterator ei = v1.edges.begin(); ei != v1.edges.end(); ei++) edges1.insert(perm[*ei]); const Vertex& v2 = vertices[perm[i]]; edges2.clear(); for(std::vector::const_iterator ei = v2.edges.begin(); ei != v2.edges.end(); ei++) edges2.insert(*ei); if(!(edges1 == edges2)) return false; } return true; } bool Graph::nucr_find_first_component(const unsigned int level) { cr_component.clear(); cr_component_elements = 0; /* Find first non-discrete cell in the component level */ Partition::Cell* first_cell = p.first_nonsingleton_cell; while(first_cell) { if(p.cr_get_level(first_cell->first) == level) break; first_cell = first_cell->next_nonsingleton; } /* The component is discrete, return false */ if(!first_cell) return false; std::vector component; first_cell->max_ival = 1; component.push_back(first_cell); for(unsigned int i = 0; i < component.size(); i++) { Partition::Cell* const cell = component[i]; const Vertex& v = vertices[p.elements[cell->first]]; std::vector::const_iterator ei = v.edges.begin(); for(unsigned int j = v.nof_edges(); j > 0; j--) { const unsigned int neighbour = *ei++; Partition::Cell* const neighbour_cell = p.get_cell(neighbour); /* Skip unit neighbours */ if(neighbour_cell->is_unit()) continue; /* Already marked to be in the same component? */ if(neighbour_cell->max_ival == 1) continue; /* Is the neighbour at the same component recursion level? */ if(p.cr_get_level(neighbour_cell->first) != level) continue; if(neighbour_cell->max_ival_count == 0) neighbour_heap.insert(neighbour_cell->first); neighbour_cell->max_ival_count++; } while(!neighbour_heap.is_empty()) { const unsigned int start = neighbour_heap.remove(); Partition::Cell* const neighbour_cell = p.get_cell(p.elements[start]); /* Skip saturated neighbour cells */ if(neighbour_cell->max_ival_count == neighbour_cell->length) { neighbour_cell->max_ival_count = 0; continue; } neighbour_cell->max_ival_count = 0; neighbour_cell->max_ival = 1; component.push_back(neighbour_cell); } } for(unsigned int i = 0; i < component.size(); i++) { Partition::Cell* const cell = component[i]; cell->max_ival = 0; cr_component.push_back(cell->first); cr_component_elements += cell->length; } if(verbstr and verbose_level > 2) { fprintf(verbstr, "NU-component with %lu cells and %u vertices\n", (long unsigned)cr_component.size(), cr_component_elements); fflush(verbstr); } return true; } bool Graph::nucr_find_first_component(const unsigned int level, std::vector& component, unsigned int& component_elements, Partition::Cell*& sh_return) { component.clear(); component_elements = 0; sh_return = 0; unsigned int sh_first = 0; unsigned int sh_size = 0; unsigned int sh_nuconn = 0; /* Find first non-discrete cell in the component level */ Partition::Cell* first_cell = p.first_nonsingleton_cell; while(first_cell) { if(p.cr_get_level(first_cell->first) == level) break; first_cell = first_cell->next_nonsingleton; } if(!first_cell) { /* The component is discrete, return false */ return false; } std::vector comp; KStack neighbours; neighbours.init(get_nof_vertices()); first_cell->max_ival = 1; comp.push_back(first_cell); for(unsigned int i = 0; i < comp.size(); i++) { Partition::Cell* const cell = comp[i]; const Vertex& v = vertices[p.elements[cell->first]]; std::vector::const_iterator ei = v.edges.begin(); for(unsigned int j = v.nof_edges(); j > 0; j--) { const unsigned int neighbour = *ei++; Partition::Cell* const neighbour_cell = p.get_cell(neighbour); /* Skip unit neighbours */ if(neighbour_cell->is_unit()) continue; /* Is the neighbour at the same component recursion level? */ //if(p.cr_get_level(neighbour_cell->first) != level) // continue; if(neighbour_cell->max_ival_count == 0) neighbours.push(neighbour_cell); neighbour_cell->max_ival_count++; } unsigned int nuconn = 1; while(!neighbours.is_empty()) { Partition::Cell* const neighbour_cell = neighbours.pop(); //neighbours.pop_back(); /* Skip saturated neighbour cells */ if(neighbour_cell->max_ival_count == neighbour_cell->length) { neighbour_cell->max_ival_count = 0; continue; } nuconn++; neighbour_cell->max_ival_count = 0; if(neighbour_cell->max_ival == 0) { comp.push_back(neighbour_cell); neighbour_cell->max_ival = 1; } } switch(sh) { case shs_f: if(sh_return == 0 or cell->first <= sh_first) { sh_return = cell; sh_first = cell->first; } break; case shs_fs: if(sh_return == 0 or cell->length < sh_size or (cell->length == sh_size and cell->first <= sh_first)) { sh_return = cell; sh_first = cell->first; sh_size = cell->length; } break; case shs_fl: if(sh_return == 0 or cell->length > sh_size or (cell->length == sh_size and cell->first <= sh_first)) { sh_return = cell; sh_first = cell->first; sh_size = cell->length; } break; case shs_fm: if(sh_return == 0 or nuconn > sh_nuconn or (nuconn == sh_nuconn and cell->first <= sh_first)) { sh_return = cell; sh_first = cell->first; sh_nuconn = nuconn; } break; case shs_fsm: if(sh_return == 0 or nuconn > sh_nuconn or (nuconn == sh_nuconn and (cell->length < sh_size or (cell->length == sh_size and cell->first <= sh_first)))) { sh_return = cell; sh_first = cell->first; sh_size = cell->length; sh_nuconn = nuconn; } break; case shs_flm: if(sh_return == 0 or nuconn > sh_nuconn or (nuconn == sh_nuconn and (cell->length > sh_size or (cell->length == sh_size and cell->first <= sh_first)))) { sh_return = cell; sh_first = cell->first; sh_size = cell->length; sh_nuconn = nuconn; } break; default: fatal_error("Internal error - unknown splitting heuristics"); return 0; } } assert(sh_return); for(unsigned int i = 0; i < comp.size(); i++) { Partition::Cell* const cell = comp[i]; cell->max_ival = 0; component.push_back(cell->first); component_elements += cell->length; } if(verbstr and verbose_level > 2) { fprintf(verbstr, "NU-component with %lu cells and %u vertices\n", (long unsigned)component.size(), component_elements); fflush(verbstr); } return true; } } python-igraph-0.8.0/vendor/source/igraph/src/bliss/uintseqhash.cc0000644000076500000240000001052413524616144025365 0ustar tamasstaff00000000000000#include "uintseqhash.hh" /* Copyright (c) 2003-2015 Tommi Junttila Released under the GNU Lesser General Public License version 3. This file is part of bliss. bliss is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, version 3 of the License. bliss is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with bliss. If not, see . */ namespace bliss { /* * Random bits generated by * http://www.fourmilab.ch/hotbits/ */ static unsigned int rtab[256] = { 0xAEAA35B8, 0x65632E16, 0x155EDBA9, 0x01349B39, 0x8EB8BD97, 0x8E4C5367, 0x8EA78B35, 0x2B1B4072, 0xC1163893, 0x269A8642, 0xC79D7F6D, 0x6A32DEA0, 0xD4D2DA56, 0xD96D4F47, 0x47B5F48A, 0x2587C6BF, 0x642B71D8, 0x5DBBAF58, 0x5C178169, 0xA16D9279, 0x75CDA063, 0x291BC48B, 0x01AC2F47, 0x5416DF7C, 0x45307514, 0xB3E1317B, 0xE1C7A8DE, 0x3ACDAC96, 0x11B96831, 0x32DE22DD, 0x6A1DA93B, 0x58B62381, 0x283810E2, 0xBC30E6A6, 0x8EE51705, 0xB06E8DFB, 0x729AB12A, 0xA9634922, 0x1A6E8525, 0x49DD4E19, 0xE5DB3D44, 0x8C5B3A02, 0xEBDE2864, 0xA9146D9F, 0x736D2CB4, 0xF5229F42, 0x712BA846, 0x20631593, 0x89C02603, 0xD5A5BF6A, 0x823F4E18, 0x5BE5DEFF, 0x1C4EBBFA, 0x5FAB8490, 0x6E559B0C, 0x1FE528D6, 0xB3198066, 0x4A965EB5, 0xFE8BB3D5, 0x4D2F6234, 0x5F125AA4, 0xBCC640FA, 0x4F8BC191, 0xA447E537, 0xAC474D3C, 0x703BFA2C, 0x617DC0E7, 0xF26299D7, 0xC90FD835, 0x33B71C7B, 0x6D83E138, 0xCBB1BB14, 0x029CF5FF, 0x7CBD093D, 0x4C9825EF, 0x845C4D6D, 0x124349A5, 0x53942D21, 0x800E60DA, 0x2BA6EB7F, 0xCEBF30D3, 0xEB18D449, 0xE281F724, 0x58B1CB09, 0xD469A13D, 0x9C7495C3, 0xE53A7810, 0xA866C08E, 0x832A038B, 0xDDDCA484, 0xD5FE0DDE, 0x0756002B, 0x2FF51342, 0x60FEC9C8, 0x061A53E3, 0x47B1884E, 0xDC17E461, 0xA17A6A37, 0x3158E7E2, 0xA40D873B, 0x45AE2140, 0xC8F36149, 0x63A4EE2D, 0xD7107447, 0x6F90994F, 0x5006770F, 0xC1F3CA9A, 0x91B317B2, 0xF61B4406, 0xA8C9EE8F, 0xC6939B75, 0xB28BBC3B, 0x36BF4AEF, 0x3B12118D, 0x4D536ECF, 0x9CF4B46B, 0xE8AB1E03, 0x8225A360, 0x7AE4A130, 0xC4EE8B50, 0x50651797, 0x5BB4C59F, 0xD120EE47, 0x24F3A386, 0xBE579B45, 0x3A378EFC, 0xC5AB007B, 0x3668942B, 0x2DBDCC3A, 0x6F37F64C, 0xC24F862A, 0xB6F97FCF, 0x9E4FA23D, 0x551AE769, 0x46A8A5A6, 0xDC1BCFDD, 0x8F684CF9, 0x501D811B, 0x84279F80, 0x2614E0AC, 0x86445276, 0xAEA0CE71, 0x0812250F, 0xB586D18A, 0xC68D721B, 0x44514E1D, 0x37CDB99A, 0x24731F89, 0xFA72E589, 0x81E6EBA2, 0x15452965, 0x55523D9D, 0x2DC47E14, 0x2E7FA107, 0xA7790F23, 0x40EBFDBB, 0x77E7906B, 0x6C1DB960, 0x1A8B9898, 0x65FA0D90, 0xED28B4D8, 0x34C3ED75, 0x768FD2EC, 0xFAB60BCB, 0x962C75F4, 0x304F0498, 0x0A41A36B, 0xF7DE2A4A, 0xF4770FE2, 0x73C93BBB, 0xD21C82C5, 0x6C387447, 0x8CDB4CB9, 0x2CC243E8, 0x41859E3D, 0xB667B9CB, 0x89681E8A, 0x61A0526C, 0x883EDDDC, 0x539DE9A4, 0xC29E1DEC, 0x97C71EC5, 0x4A560A66, 0xBD7ECACF, 0x576AE998, 0x31CE5616, 0x97172A6C, 0x83D047C4, 0x274EA9A8, 0xEB31A9DA, 0x327209B5, 0x14D1F2CB, 0x00FE1D96, 0x817DBE08, 0xD3E55AED, 0xF2D30AFC, 0xFB072660, 0x866687D6, 0x92552EB9, 0xEA8219CD, 0xF7927269, 0xF1948483, 0x694C1DF5, 0xB7D8B7BF, 0xFFBC5D2F, 0x2E88B849, 0x883FD32B, 0xA0331192, 0x8CB244DF, 0x41FAF895, 0x16902220, 0x97FB512A, 0x2BEA3CC4, 0xAF9CAE61, 0x41ACD0D5, 0xFD2F28FF, 0xE780ADFA, 0xB3A3A76E, 0x7112AD87, 0x7C3D6058, 0x69E64FFF, 0xE5F8617C, 0x8580727C, 0x41F54F04, 0xD72BE498, 0x653D1795, 0x1275A327, 0x14B499D4, 0x4E34D553, 0x4687AA39, 0x68B64292, 0x5C18ABC3, 0x41EABFCC, 0x92A85616, 0x82684CF8, 0x5B9F8A4E, 0x35382FFE, 0xFB936318, 0x52C08E15, 0x80918B2E, 0x199EDEE0, 0xA9470163, 0xEC44ACDD, 0x612D6735, 0x8F88EA7D, 0x759F5EA4, 0xE5CC7240, 0x68CFEB8B, 0x04725601, 0x0C22C23E, 0x5BC97174, 0x89965841, 0x5D939479, 0x690F338A, 0x3C2D4380, 0xDAE97F2B }; void UintSeqHash::update(unsigned int i) { i++; while(i > 0) { h ^= rtab[i & 0xff]; #if 1 const unsigned int b = (h & 0x80000000) >> 31; i = i >> 8; h = (h << 1) | b; #else const unsigned int b = h & 0x80000000; h = h << 1; if(b != 0) h++; i = i >> 8; #endif } } } // namespace bliss python-igraph-0.8.0/vendor/source/igraph/src/bliss/orbit.hh0000644000076500000240000000601513524616144024162 0ustar tamasstaff00000000000000#ifndef BLISS_ORBIT_HH #define BLISS_ORBIT_HH /* Copyright (c) 2003-2015 Tommi Junttila Released under the GNU Lesser General Public License version 3. This file is part of bliss. bliss is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, version 3 of the License. bliss is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with bliss. If not, see . */ namespace bliss { /** \internal * \brief A class for representing orbit information. * * Given a set {0,...,N-1} of N elements, represent equivalence * classes (that is, unordered partitions) of the elements. * Supports only equivalence class merging, not splitting. * Merging two classes requires time O(k), where k is the number of * the elements in the smaller of the merged classes. * Getting the smallest representative in a class (and thus testing * whether two elements belong to the same class) is a constant time operation. */ class Orbit { class OrbitEntry { public: unsigned int element; OrbitEntry *next; unsigned int size; }; OrbitEntry *orbits; OrbitEntry **in_orbit; unsigned int nof_elements; unsigned int _nof_orbits; void merge_orbits(OrbitEntry *o1, OrbitEntry *o2); public: /** * Create a new orbit information object. * The init() function must be called next to actually initialize * the object. */ Orbit(); ~Orbit(); /** * Initialize the orbit information to consider sets of \a N elements. * It is required that \a N > 0. * The orbit information is reset so that each element forms * an orbit of its own. * Time complexity is O(N). * \sa reset() */ void init(const unsigned int N); /** * Reset the orbits so that each element forms an orbit of its own. * Time complexity is O(N). */ void reset(); /** * Merge the orbits of the elements \a e1 and \a e2. * Time complexity is O(k), where k is the number of elements in * the smaller of the merged orbits. */ void merge_orbits(unsigned int e1, unsigned int e2); /** * Is the element \a e the smallest element in its orbit? * Time complexity is O(1). */ bool is_minimal_representative(unsigned int e) const; /** * Get the smallest element in the orbit of the element \a e. * Time complexity is O(1). */ unsigned int get_minimal_representative(unsigned int e) const; /** * Get the number of elements in the orbit of the element \a e. * Time complexity is O(1). */ unsigned int orbit_size(unsigned int e) const; /** * Get the number of orbits. * Time complexity is O(1). */ unsigned int nof_orbits() const {return _nof_orbits; } }; } // namespace bliss #endif python-igraph-0.8.0/vendor/source/igraph/src/bliss/partition.hh0000644000076500000240000002033313524616144025053 0ustar tamasstaff00000000000000#ifndef BLISS_PARTITION_HH #define BLISS_PARTITION_HH /* Copyright (c) 2003-2015 Tommi Junttila Released under the GNU Lesser General Public License version 3. This file is part of bliss. bliss is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, version 3 of the License. bliss is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with bliss. If not, see . */ namespace bliss { class Partition; } #include #include #include #include "kstack.hh" #include "kqueue.hh" #include "heap.hh" #include "orbit.hh" #include "graph.hh" namespace bliss { /** \internal * \brief A class for refinable, backtrackable ordered partitions. * * This is rather a data structure with some helper functions than * a proper self-contained class. * That is, for efficiency reasons the fields of this class are directly * manipulated from bliss::AbstractGraph and its subclasses. * Conversely, some methods of this class modify the fields of * bliss::AbstractGraph, too. */ class Partition { public: /** * \brief Data structure for holding information about a cell in a Partition. */ class Cell { friend class Partition; public: unsigned int length; /* Index of the first element of the cell in the Partition::elements array */ unsigned int first; unsigned int max_ival; unsigned int max_ival_count; private: bool in_splitting_queue; public: bool in_neighbour_heap; /* Pointer to the next cell, null if this is the last one. */ Cell* next; Cell* prev; Cell* next_nonsingleton; Cell* prev_nonsingleton; unsigned int split_level; /** Is this a unit cell? */ bool is_unit() const {return(length == 1); } /** Is this cell in splitting queue? */ bool is_in_splitting_queue() const {return(in_splitting_queue); } }; private: /** \internal * Data structure for remembering information about splits in order to * perform efficient backtracking over the splits. */ class RefInfo { public: unsigned int split_cell_first; int prev_nonsingleton_first; int next_nonsingleton_first; }; /** \internal * A stack for remembering the splits, used for backtracking. */ KStack refinement_stack; class BacktrackInfo { public: unsigned int refinement_stack_size; unsigned int cr_backtrack_point; }; /** \internal * The main stack for enabling backtracking. */ std::vector bt_stack; public: AbstractGraph* graph; /* Used during equitable partition refinement */ KQueue splitting_queue; void splitting_queue_add(Cell* const cell); Cell* splitting_queue_pop(); bool splitting_queue_is_empty() const; void splitting_queue_clear(); /** Type for backtracking points. */ typedef unsigned int BacktrackPoint; /** * Get a new backtrack point for the current partition */ BacktrackPoint set_backtrack_point(); /** * Backtrack to the point \a p and remove it. */ void goto_backtrack_point(BacktrackPoint p); /** * Split the non-unit Cell \a cell = {\a element,e1,e2,...,en} containing * the element \a element in two: * \a cell = {e1,...,en} and \a newcell = {\a element}. * @param cell a non-unit Cell * @param element an element in \a cell * @return the new unit Cell \a newcell */ Cell* individualize(Cell* const cell, const unsigned int element); Cell* aux_split_in_two(Cell* const cell, const unsigned int first_half_size); private: unsigned int N; Cell* cells; Cell* free_cells; unsigned int discrete_cell_count; public: Cell* first_cell; Cell* first_nonsingleton_cell; unsigned int *elements; /* invariant_values[e] gives the invariant value of the element e */ unsigned int *invariant_values; /* element_to_cell_map[e] gives the cell of the element e */ Cell **element_to_cell_map; /** Get the cell of the element \a e */ Cell* get_cell(const unsigned int e) const { return element_to_cell_map[e]; } /* in_pos[e] points to the elements array s.t. *in_pos[e] = e */ unsigned int **in_pos; Partition(); ~Partition(); /** * Initialize the partition to the unit partition (all elements in one cell) * over the \a N > 0 elements {0,...,\a N-1}. */ void init(const unsigned int N); /** * Returns true iff the partition is discrete, meaning that all * the elements are in their own cells. */ bool is_discrete() const {return(free_cells == 0); } unsigned int nof_discrete_cells() const {return(discrete_cell_count); } /** * Print the partition into the file stream \a fp. */ size_t print(FILE* const fp, const bool add_newline = true) const; /** * Print the partition cell sizes into the file stream \a fp. */ size_t print_signature(FILE* const fp, const bool add_newline = true) const; /* * Splits the Cell \a cell into [cell_1,...,cell_n] * according to the invariant_values of the elements in \a cell. * After splitting, cell_1 == \a cell. * Returns the pointer to the Cell cell_n; * cell_n != cell iff the Cell \a cell was actually splitted. * The flag \a max_ival_info_ok indicates whether the max_ival and * max_ival_count fields of the Cell \a cell have consistent values * when the method is called. * Clears the invariant values of elements in the Cell \a cell as well as * the max_ival and max_ival_count fields of the Cell \a cell. */ Cell *zplit_cell(Cell * const cell, const bool max_ival_info_ok); /* * Routines for component recursion */ void cr_init(); void cr_free(); unsigned int cr_get_level(const unsigned int cell_index) const; unsigned int cr_split_level(const unsigned int level, const std::vector& cells); /** Clear the invariant_values of the elements in the Cell \a cell. */ void clear_ivs(Cell* const cell); private: /* * Component recursion data structures */ /* Is component recursion support in use? */ bool cr_enabled; class CRCell { public: unsigned int level; CRCell* next; CRCell** prev_next_ptr; void detach() { if(next) next->prev_next_ptr = prev_next_ptr; *(prev_next_ptr) = next; level = UINT_MAX; next = 0; prev_next_ptr = 0; } }; CRCell* cr_cells; CRCell** cr_levels; class CR_BTInfo { public: unsigned int created_trail_index; unsigned int splitted_level_trail_index; }; std::vector cr_created_trail; std::vector cr_splitted_level_trail; std::vector cr_bt_info; unsigned int cr_max_level; void cr_create_at_level(const unsigned int cell_index, unsigned int level); void cr_create_at_level_trailed(const unsigned int cell_index, unsigned int level); unsigned int cr_get_backtrack_point(); void cr_goto_backtrack_point(const unsigned int btpoint); /* * * Auxiliary routines for sorting and splitting cells * */ Cell* sort_and_split_cell1(Cell* cell); Cell* sort_and_split_cell255(Cell* const cell, const unsigned int max_ival); bool shellsort_cell(Cell* cell); Cell* split_cell(Cell* const cell); /* * Some auxiliary stuff needed for distribution count sorting. * To make the code thread-safe (modulo the requirement that each graph is * only accessed in one thread at a time), the arrays are owned by * the partition instance, not statically defined. */ unsigned int dcs_count[256]; unsigned int dcs_start[256]; void dcs_cumulate_count(const unsigned int max); }; inline Partition::Cell* Partition::splitting_queue_pop() { Cell* const cell = splitting_queue.pop_front(); cell->in_splitting_queue = false; return cell; } inline bool Partition::splitting_queue_is_empty() const { return splitting_queue.is_empty(); } inline unsigned int Partition::cr_get_level(const unsigned int cell_index) const { return(cr_cells[cell_index].level); } } // namespace bliss #endif python-igraph-0.8.0/vendor/source/igraph/src/bliss/heap.hh0000644000076500000240000000370313524616144023761 0ustar tamasstaff00000000000000#ifndef BLISS_HEAP_HH #define BLISS_HEAP_HH /* Copyright (c) 2003-2015 Tommi Junttila Released under the GNU Lesser General Public License version 3. This file is part of bliss. bliss is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, version 3 of the License. bliss is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with bliss. If not, see . */ namespace bliss { /** \internal * \brief A capacity bounded heap data structure. */ class Heap { unsigned int N; unsigned int n; unsigned int *array; void upheap(unsigned int k); void downheap(unsigned int k); public: /** * Create a new heap. * init() must be called after this. */ Heap() {array = 0; n = 0; N = 0; } ~Heap(); /** * Initialize the heap to have the capacity to hold \e size elements. */ void init(const unsigned int size); /** * Is the heap empty? * Time complexity is O(1). */ bool is_empty() const {return(n==0); } /** * Remove all the elements in the heap. * Time complexity is O(1). */ void clear() {n = 0;} /** * Insert the element \a e in the heap. * Time complexity is O(log(N)), where N is the number of elements * currently in the heap. */ void insert(const unsigned int e); /** * Remove and return the smallest element in the heap. * Time complexity is O(log(N)), where N is the number of elements * currently in the heap. */ unsigned int remove(); /** * Get the number of elements in the heap. */ unsigned int size() const {return n; } }; } // namespace bliss #endif python-igraph-0.8.0/vendor/source/igraph/src/bliss/defs.hh0000644000076500000240000000700113524616144023760 0ustar tamasstaff00000000000000#ifndef BLISS_DEFS_HH #define BLISS_DEFS_HH #include #include #include "config.h" /* Copyright (c) 2003-2015 Tommi Junttila Released under the GNU Lesser General Public License version 3. This file is part of bliss. bliss is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, version 3 of the License. bliss is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with bliss. If not, see . */ #if HAVE_GMP == 1 # define BLISS_USE_GMP #endif #ifdef USING_R #include #define fatal_error(...) (error(__VA_ARGS__)) #endif namespace bliss { /** * The version number of bliss. */ static const char * const version = "0.73"; /* * If a fatal error (out of memory, internal error) is encountered, * this function is called. * There should not be a return from this function but exit or * a jump to code that deallocates the AbstractGraph instance that called this. */ #ifndef USING_R void fatal_error(const char* fmt, ...); #endif #if defined(BLISS_DEBUG) #define BLISS_CONSISTENCY_CHECKS #define BLISS_EXPENSIVE_CONSISTENCY_CHECKS #endif #if defined(BLISS_CONSISTENCY_CHECKS) /* Force a check that the found automorphisms are valid */ #define BLISS_VERIFY_AUTOMORPHISMS #endif #if defined(BLISS_CONSISTENCY_CHECKS) /* Force a check that the generated partitions are equitable */ #define BLISS_VERIFY_EQUITABLEDNESS #endif } // namespace bliss /*! \mainpage Bliss * * \section intro_sec Introduction * * This is the source code documentation of bliss, * produced by running doxygen in * the source directory. * The algorithms and data structures used in bliss are documented in * the papers found at the * bliss web site. * * * \section compile_sec Compiling * * Compiling bliss in Linux should be easy, just execute * \code * make * \endcode * in the bliss source directory. * This will produce the executable program \c bliss as well as * the library file \c libbliss.a that can be linked in other programs. * If you have the GNU Multiple Precision * Arithmetic Library (GMP) installed in your machine, you can also use * \code * make gmp * \endcode * to enable exact computation of automorphism group sizes. * * When linking the bliss library \c libbliss.a in other programs, * remember to include the standard c++ library * (and the GMP library if you compiled bliss to include it). * For instance, * \code gcc -o test test.c -lstdc++ -lgmp -lbliss\endcode * * \section cppapi_sec The C++ language API * * The C++ language API is the main API to bliss; * all other APIs are just more or less complete variants of it. * The C++ API consists basically of the public methods in * the classes bliss::AbstractGraph, bliss::Graph, and bliss::Digraph. * For an example of its use, * see the \ref executable "source of the bliss executable". * * * \section capi_sec The C language API * * The C language API is given in the file bliss_C.h. * It is currently more restricted than the C++ API so * consider using the C++ API whenever possible. */ #endif python-igraph-0.8.0/vendor/source/igraph/src/bliss/kstack.hh0000644000076500000240000000556413524616144024333 0ustar tamasstaff00000000000000#ifndef BLISS_KSTACK_H #define BLISS_KSTACK_H /* Copyright (c) 2003-2015 Tommi Junttila Released under the GNU Lesser General Public License version 3. This file is part of bliss. bliss is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, version 3 of the License. bliss is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with bliss. If not, see . */ #include #include "defs.hh" namespace bliss { /** \internal * \brief A very simple implementation of a stack with fixed capacity. */ template class KStack { public: /** * Create a new stack with zero capacity. * The function init() should be called next. */ KStack(); /** * Create a new stack with the capacity to hold at most \a N elements. */ KStack(int N); ~KStack(); /** * Initialize the stack to have the capacity to hold at most \a N elements. */ void init(int N); /** * Is the stack empty? */ bool is_empty() const {return(cursor == entries); } /** * Return (but don't remove) the top element of the stack. */ Type top() const {BLISS_ASSERT(cursor > entries); return *cursor; } /** * Pop (remove) the top element of the stack. */ Type pop() { return *cursor--; } /** * Push the element \a e in the stack. */ void push(Type e) { *(++cursor) = e; } /** Remove all the elements in the stack. */ void clean() {cursor = entries; } /** * Get the number of elements in the stack. */ unsigned int size() const {return(cursor - entries); } /** * Return the i:th element in the stack, where \a i is in the range * 0,...,this.size()-1; the 0:th element is the bottom element * in the stack. */ Type element_at(unsigned int i) { assert(i < size()); return entries[i+1]; } /** Return the capacity (NOT the number of elements) of the stack. */ int capacity() {return kapacity; } private: int kapacity; Type *entries; Type *cursor; }; template KStack::KStack() { kapacity = 0; entries = 0; cursor = 0; } template KStack::KStack(int k) { assert(k > 0); kapacity = k; entries = (Type*)malloc((k+1) * sizeof(Type)); cursor = entries; } template void KStack::init(int k) { assert(k > 0); if(entries) free(entries); kapacity = k; entries = (Type*)malloc((k+1) * sizeof(Type)); cursor = entries; } template KStack::~KStack() { free(entries); } } // namespace bliss #endif python-igraph-0.8.0/vendor/source/igraph/src/bliss/defs.cc0000644000076500000240000000202713524616144023751 0ustar tamasstaff00000000000000#include #include #include "defs.hh" /* Copyright (c) 2003-2015 Tommi Junttila Released under the GNU Lesser General Public License version 3. This file is part of bliss. bliss is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, version 3 of the License. bliss is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with bliss. If not, see . */ namespace bliss { #ifndef USING_R void fatal_error(const char* fmt, ...) { va_list ap; va_start(ap, fmt); fprintf(stderr,"Bliss fatal error: "); vfprintf(stderr, fmt, ap); fprintf(stderr, "\nAborting!\n"); va_end(ap); exit(1); } #endif } python-igraph-0.8.0/vendor/source/igraph/src/bliss/igraph-changes.md0000644000076500000240000000147013524616144025724 0ustar tamasstaff00000000000000This file lists changes that were made to the original Bliss package (version 0.73) to integrate it into igraph. Remove `Makefile`, `Doxyfile` Removed `bliss.cc`, `bliss_C.cc`, `bliss_C.h` Remove references to `Timer` class in `graph.cc` Remove `timer.cc` and `timer.hh` Add to `defs.hh`: #include "config.h" #if HAVE_GMP == 1 # define BLISS_USE_GMP #endif In `bignum.hh`: Move `#if defined(BLISS_USE_GMP) ...` below `#include "defs.h"` Add: #include "igraph_memory.h" #include "igraph_error.h" Also add, for the `tostring` method without GMP: #include #include #include Add `tostring` member function to `BigNum` class for both cases (with or without GMP). In `graph.cc`, add IGRAPH_THREAD_LOCAL to the `PathInfo` global variable on line 612. python-igraph-0.8.0/vendor/source/igraph/src/bliss/bliss_heap.cc0000644000076500000240000000402313524616144025137 0ustar tamasstaff00000000000000#include #include #include #include "defs.hh" #include "heap.hh" /* use 'and' instead of '&&' */ #if _MSC_VER #include #endif /* Copyright (c) 2003-2015 Tommi Junttila Released under the GNU Lesser General Public License version 3. This file is part of bliss. bliss is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, version 3 of the License. bliss is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with bliss. If not, see . */ namespace bliss { Heap::~Heap() { if(array) { free(array); array = 0; n = 0; N = 0; } } void Heap::upheap(unsigned int index) { const unsigned int v = array[index]; array[0] = 0; while(array[index/2] > v) { array[index] = array[index/2]; index = index/2; } array[index] = v; } void Heap::downheap(unsigned int index) { const unsigned int v = array[index]; const unsigned int lim = n/2; while(index <= lim) { unsigned int new_index = index + index; if((new_index < n) and (array[new_index] > array[new_index+1])) new_index++; if(v <= array[new_index]) break; array[index] = array[new_index]; index = new_index; } array[index] = v; } void Heap::init(const unsigned int size) { if(size > N) { if(array) free(array); array = (unsigned int*)malloc((size + 1) * sizeof(unsigned int)); N = size; } n = 0; } void Heap::insert(const unsigned int v) { array[++n] = v; upheap(n); } unsigned int Heap::remove() { const unsigned int v = array[1]; array[1] = array[n--]; downheap(1); return v; } } // namespace bliss python-igraph-0.8.0/vendor/source/igraph/src/bliss/uintseqhash.hh0000644000076500000240000000372113524616144025400 0ustar tamasstaff00000000000000#ifndef BLISS_UINTSEQHASH_HH #define BLISS_UINTSEQHASH_HH #include /* Copyright (c) 2003-2015 Tommi Junttila Released under the GNU Lesser General Public License version 3. This file is part of bliss. bliss is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, version 3 of the License. bliss is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with bliss. If not, see . */ namespace bliss { /** \internal * \brief A hash for sequences of unsigned ints. */ class UintSeqHash { protected: unsigned int h; public: UintSeqHash() {h = 0; } UintSeqHash(const UintSeqHash &other) {h = other.h; } UintSeqHash& operator=(const UintSeqHash &other) {h = other.h; return *this; } /** Reset the hash value. */ void reset() {h = 0; } /** Add the unsigned int \a n to the sequence. */ void update(unsigned int n); /** Get the hash value of the sequence seen so far. */ unsigned int get_value() const {return h; } /** Compare the hash values of this and \a other. * Return -1/0/1 if the value of this is smaller/equal/greater than * that of \a other. */ int cmp(const UintSeqHash &other) const { return (h < other.h)?-1:((h == other.h)?0:1); } /** An abbreviation for cmp(other) < 0 */ bool is_lt(const UintSeqHash &other) const {return(cmp(other) < 0); } /** An abbreviation for cmp(other) <= 0 */ bool is_le(const UintSeqHash &other) const {return(cmp(other) <= 0); } /** An abbreviation for cmp(other) == 0 */ bool is_equal(const UintSeqHash &other) const {return(cmp(other) == 0); } }; } // namespace bliss #endif python-igraph-0.8.0/vendor/source/igraph/src/bliss/graph.hh0000644000076500000240000010051013524616144024137 0ustar tamasstaff00000000000000#ifndef BLISS_GRAPH_HH #define BLISS_GRAPH_HH /* Copyright (c) 2003-2015 Tommi Junttila Released under the GNU Lesser General Public License version 3. This file is part of bliss. bliss is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, version 3 of the License. bliss is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with bliss. If not, see . */ /** * \namespace bliss * The namespace bliss contains all the classes and functions of the bliss * tool except for the C programming language API. */ namespace bliss { class AbstractGraph; } #include #include #include "kstack.hh" #include "kqueue.hh" #include "heap.hh" #include "orbit.hh" #include "partition.hh" #include "bignum.hh" #include "uintseqhash.hh" namespace bliss { /** * \brief Statistics returned by the bliss search algorithm. */ class Stats { friend class AbstractGraph; public: /** \internal The size of the automorphism group. */ BigNum group_size; private: /** \internal An approximation (due to possible overflows) of * the size of the automorphism group. */ long double group_size_approx; /** \internal The number of nodes in the search tree. */ long unsigned int nof_nodes; /** \internal The number of leaf nodes in the search tree. */ long unsigned int nof_leaf_nodes; /** \internal The number of bad nodes in the search tree. */ long unsigned int nof_bad_nodes; /** \internal The number of canonical representative updates. */ long unsigned int nof_canupdates; /** \internal The number of generator permutations. */ long unsigned int nof_generators; /** \internal The maximal depth of the search tree. */ unsigned long int max_level; /** */ void reset() { group_size.assign(1); group_size_approx = 1.0; nof_nodes = 0; nof_leaf_nodes = 0; nof_bad_nodes = 0; nof_canupdates = 0; nof_generators = 0; max_level = 0; } public: Stats() { reset(); } /** Print the statistics. */ size_t print(FILE* const fp) const { size_t r = 0; r += fprintf(fp, "Nodes: %lu\n", nof_nodes); r += fprintf(fp, "Leaf nodes: %lu\n", nof_leaf_nodes); r += fprintf(fp, "Bad nodes: %lu\n", nof_bad_nodes); r += fprintf(fp, "Canrep updates: %lu\n", nof_canupdates); r += fprintf(fp, "Generators: %lu\n", nof_generators); r += fprintf(fp, "Max level: %lu\n", max_level); r += fprintf(fp, "|Aut|: ")+group_size.print(fp)+fprintf(fp, "\n"); fflush(fp); return r; } /** An approximation (due to possible overflows/rounding errors) of * the size of the automorphism group. */ long double get_group_size_approx() const {return group_size_approx;} /** The number of nodes in the search tree. */ long unsigned int get_nof_nodes() const {return nof_nodes;} /** The number of leaf nodes in the search tree. */ long unsigned int get_nof_leaf_nodes() const {return nof_leaf_nodes;} /** The number of bad nodes in the search tree. */ long unsigned int get_nof_bad_nodes() const {return nof_bad_nodes;} /** The number of canonical representative updates. */ long unsigned int get_nof_canupdates() const {return nof_canupdates;} /** The number of generator permutations. */ long unsigned int get_nof_generators() const {return nof_generators;} /** The maximal depth of the search tree. */ unsigned long int get_max_level() const {return max_level;} }; /** * \brief An abstract base class for different types of graphs. */ class AbstractGraph { friend class Partition; public: AbstractGraph(); virtual ~AbstractGraph(); /** * Set the verbose output level for the algorithms. * \param level the level of verbose output, 0 means no verbose output */ void set_verbose_level(const unsigned int level); /** * Set the file stream for the verbose output. * \param fp the file stream; if null, no verbose output is written */ void set_verbose_file(FILE * const fp); /** * Add a new vertex with color \a color in the graph and return its index. */ virtual unsigned int add_vertex(const unsigned int color = 0) = 0; /** * Add an edge between vertices \a source and \a target. * Duplicate edges between vertices are ignored but try to avoid introducing * them in the first place as they are not ignored immediately but will * consume memory and computation resources for a while. */ virtual void add_edge(const unsigned int source, const unsigned int target) = 0; /** * Change the color of the vertex \a vertex to \a color. */ virtual void change_color(const unsigned int vertex, const unsigned int color) = 0; /** * Check whether \a perm is an automorphism of this graph. * Unoptimized, mainly for debugging purposes. */ virtual bool is_automorphism(const std::vector& perm) const; /** Activate/deactivate failure recording. * May not be called during the search, i.e. from an automorphism reporting * hook function. * \param active if true, activate failure recording, deactivate otherwise */ void set_failure_recording(const bool active) {assert(!in_search); opt_use_failure_recording = active;} /** Activate/deactivate component recursion. * The choice affects the computed canonical labelings; * therefore, if you want to compare whether two graphs are isomorphic by * computing and comparing (for equality) their canonical versions, * be sure to use the same choice for both graphs. * May not be called during the search, i.e. from an automorphism reporting * hook function. * \param active if true, activate component recursion, deactivate otherwise */ void set_component_recursion(const bool active) {assert(!in_search); opt_use_comprec = active;} /** * Return the number of vertices in the graph. */ virtual unsigned int get_nof_vertices() const = 0; /** * Return a new graph that is the result of applying the permutation \a perm * to this graph. This graph is not modified. * \a perm must contain N=this.get_nof_vertices() elements and be a bijection * on {0,1,...,N-1}, otherwise the result is undefined or a segfault. */ virtual AbstractGraph* permute(const unsigned int* const perm) const = 0; virtual AbstractGraph* permute(const std::vector& perm) const = 0; /** * Find a set of generators for the automorphism group of the graph. * The function \a hook (if non-null) is called each time a new generator * for the automorphism group is found. * The first argument \a user_param for the hook is the * \a hook_user_param given below, * the second argument \a n is the length of the automorphism (equal to * get_nof_vertices()) and * the third argument \a aut is the automorphism * (a bijection on {0,...,get_nof_vertices()-1}). * The memory for the automorphism \a aut will be invalidated immediately * after the return from the hook function; * if you want to use the automorphism later, you have to take a copy of it. * Do not call any member functions in the hook. * The search statistics are copied in \a stats. */ void find_automorphisms(Stats& stats, void (*hook)(void* user_param, unsigned int n, const unsigned int* aut), void* hook_user_param); /** * Otherwise the same as find_automorphisms() except that * a canonical labeling of the graph (a bijection on * {0,...,get_nof_vertices()-1}) is returned. * The memory allocated for the returned canonical labeling will remain * valid only until the next call to a member function with the exception * that constant member functions (for example, bliss::Graph::permute()) can * be called without invalidating the labeling. * To compute the canonical version of an undirected graph, call this * function and then bliss::Graph::permute() with the returned canonical * labeling. * Note that the computed canonical version may depend on the applied version * of bliss as well as on some other options (for instance, the splitting * heuristic selected with bliss::Graph::set_splitting_heuristic()). */ const unsigned int* canonical_form(Stats& stats, void (*hook)(void* user_param, unsigned int n, const unsigned int* aut), void* hook_user_param); /** * Write the graph to a file in a variant of the DIMACS format. * See the bliss website * for the definition of the file format. * Note that in the DIMACS file the vertices are numbered from 1 to N while * in this C++ API they are from 0 to N-1. * Thus the vertex n in the file corresponds to the vertex n-1 in the API. * \param fp the file stream where the graph is written */ virtual void write_dimacs(FILE * const fp) = 0; /** * Write the graph to a file in the graphviz dotty format. * \param fp the file stream where the graph is written */ virtual void write_dot(FILE * const fp) = 0; /** * Write the graph in a file in the graphviz dotty format. * Do nothing if the file cannot be written. * \param file_name the name of the file to which the graph is written */ virtual void write_dot(const char * const file_name) = 0; /** * Get a hash value for the graph. * \return the hash value */ virtual unsigned int get_hash() = 0; /** * Disable/enable the "long prune" method. * The choice affects the computed canonical labelings; * therefore, if you want to compare whether two graphs are isomorphic by * computing and comparing (for equality) their canonical versions, * be sure to use the same choice for both graphs. * May not be called during the search, i.e. from an automorphism reporting * hook function. * \param active if true, activate "long prune", deactivate otherwise */ void set_long_prune_activity(const bool active) { assert(!in_search); opt_use_long_prune = active; } protected: /** \internal * How much verbose output is produced (0 means none) */ unsigned int verbose_level; /** \internal * The output stream for verbose output. */ FILE *verbstr; protected: /** \internal * The ordered partition used in the search algorithm. */ Partition p; /** \internal * Whether the search for automorphisms and a canonical labeling is * in progress. */ bool in_search; /** \internal * Is failure recording in use? */ bool opt_use_failure_recording; /* The "tree-specific" invariant value for the point when current path * got different from the first path */ unsigned int failure_recording_fp_deviation; /** \internal * Is component recursion in use? */ bool opt_use_comprec; unsigned int refine_current_path_certificate_index; bool refine_compare_certificate; bool refine_equal_to_first; unsigned int refine_first_path_subcertificate_end; int refine_cmp_to_best; unsigned int refine_best_path_subcertificate_end; static const unsigned int CERT_SPLIT = 0; //UINT_MAX; static const unsigned int CERT_EDGE = 1; //UINT_MAX-1; /** \internal * Add a triple (v1,v2,v3) in the certificate. * May modify refine_equal_to_first and refine_cmp_to_best. * May also update eqref_hash and failure_recording_fp_deviation. */ void cert_add(const unsigned int v1, const unsigned int v2, const unsigned int v3); /** \internal * Add a redundant triple (v1,v2,v3) in the certificate. * Can also just dicard the triple. * May modify refine_equal_to_first and refine_cmp_to_best. * May also update eqref_hash and failure_recording_fp_deviation. */ void cert_add_redundant(const unsigned int x, const unsigned int y, const unsigned int z); /**\internal * Is the long prune method in use? */ bool opt_use_long_prune; /**\internal * Maximum amount of memory (in megabytes) available for * the long prune method */ static const unsigned int long_prune_options_max_mem = 50; /**\internal * Maximum amount of automorphisms stored for the long prune method; * less than this is stored if the memory limit above is reached first */ static const unsigned int long_prune_options_max_stored_auts = 100; unsigned int long_prune_max_stored_autss; std::vector *> long_prune_fixed; std::vector *> long_prune_mcrs; std::vector long_prune_temp; unsigned int long_prune_begin; unsigned int long_prune_end; /** \internal * Initialize the "long prune" data structures. */ void long_prune_init(); /** \internal * Release the memory allocated for "long prune" data structures. */ void long_prune_deallocate(); void long_prune_add_automorphism(const unsigned int *aut); std::vector& long_prune_get_fixed(const unsigned int index); std::vector& long_prune_allocget_fixed(const unsigned int index); std::vector& long_prune_get_mcrs(const unsigned int index); std::vector& long_prune_allocget_mcrs(const unsigned int index); /** \internal * Swap the i:th and j:th stored automorphism information; * i and j must be "in window, i.e. in [long_prune_begin,long_prune_end[ */ void long_prune_swap(const unsigned int i, const unsigned int j); /* * Data structures and routines for refining the partition p into equitable */ Heap neighbour_heap; virtual bool split_neighbourhood_of_unit_cell(Partition::Cell *) = 0; virtual bool split_neighbourhood_of_cell(Partition::Cell * const) = 0; void refine_to_equitable(); void refine_to_equitable(Partition::Cell * const unit_cell); void refine_to_equitable(Partition::Cell * const unit_cell1, Partition::Cell * const unit_cell2); /** \internal * \return false if it was detected that the current certificate * is different from the first and/or best (whether this is checked * depends on in_search and refine_compare_certificate flags. */ bool do_refine_to_equitable(); unsigned int eqref_max_certificate_index; /** \internal * Whether eqref_hash is updated during equitable refinement process. */ bool compute_eqref_hash; UintSeqHash eqref_hash; /** \internal * Check whether the current partition p is equitable. * Performance: very slow, use only for debugging purposes. */ virtual bool is_equitable() const = 0; unsigned int *first_path_labeling; unsigned int *first_path_labeling_inv; Orbit first_path_orbits; unsigned int *first_path_automorphism; unsigned int *best_path_labeling; unsigned int *best_path_labeling_inv; Orbit best_path_orbits; unsigned int *best_path_automorphism; void update_labeling(unsigned int * const lab); void update_labeling_and_its_inverse(unsigned int * const lab, unsigned int * const lab_inv); void update_orbit_information(Orbit &o, const unsigned int *perm); void reset_permutation(unsigned int *perm); /* Mainly for debugging purposes */ virtual bool is_automorphism(unsigned int* const perm); std::vector certificate_current_path; std::vector certificate_first_path; std::vector certificate_best_path; unsigned int certificate_index; virtual void initialize_certificate() = 0; virtual void remove_duplicate_edges() = 0; virtual void make_initial_equitable_partition() = 0; virtual Partition::Cell* find_next_cell_to_be_splitted(Partition::Cell *cell) = 0; void search(const bool canonical, Stats &stats); void (*report_hook)(void *user_param, unsigned int n, const unsigned int *aut); void *report_user_param; /* * * Nonuniform component recursion (NUCR) * */ /** The currently traversed component */ unsigned int cr_level; /** \internal * The "Component End Point" data structure */ class CR_CEP { public: /** At which level in the search was this CEP created */ unsigned int creation_level; /** The current component has been fully traversed when the partition has * this many discrete cells left */ unsigned int discrete_cell_limit; /** The component to be traversed after the current one */ unsigned int next_cr_level; /** The next component end point */ unsigned int next_cep_index; bool first_checked; bool best_checked; }; /** \internal * A stack for storing Component End Points */ std::vector cr_cep_stack; /** \internal * Find the first non-uniformity component at the component recursion * level \a level. * The component is stored in \a cr_component. * If no component is found, \a cr_component is empty. * Returns false if all the cells in the component recursion level \a level * were discrete. * Modifies the max_ival and max_ival_count fields of Partition:Cell * (assumes that they are 0 when called and * quarantees that they are 0 when returned). */ virtual bool nucr_find_first_component(const unsigned int level) = 0; virtual bool nucr_find_first_component(const unsigned int level, std::vector& component, unsigned int& component_elements, Partition::Cell*& sh_return) = 0; /** \internal * The non-uniformity component found by nucr_find_first_component() * is stored here. */ std::vector cr_component; /** \internal * The number of vertices in the component \a cr_component */ unsigned int cr_component_elements; }; /** * \brief The class for undirected, vertex colored graphs. * * Multiple edges between vertices are not allowed (i.e., are ignored). */ class Graph : public AbstractGraph { public: /** * The possible splitting heuristics. * The selected splitting heuristics affects the computed canonical * labelings; therefore, if you want to compare whether two graphs * are isomorphic by computing and comparing (for equality) their * canonical versions, be sure to use the same splitting heuristics * for both graphs. */ typedef enum { /** First non-unit cell. * Very fast but may result in large search spaces on difficult graphs. * Use for large but easy graphs. */ shs_f = 0, /** First smallest non-unit cell. * Fast, should usually produce smaller search spaces than shs_f. */ shs_fs, /** First largest non-unit cell. * Fast, should usually produce smaller search spaces than shs_f. */ shs_fl, /** First maximally non-trivially connected non-unit cell. * Not so fast, should usually produce smaller search spaces than shs_f, * shs_fs, and shs_fl. */ shs_fm, /** First smallest maximally non-trivially connected non-unit cell. * Not so fast, should usually produce smaller search spaces than shs_f, * shs_fs, and shs_fl. */ shs_fsm, /** First largest maximally non-trivially connected non-unit cell. * Not so fast, should usually produce smaller search spaces than shs_f, * shs_fs, and shs_fl. */ shs_flm } SplittingHeuristic; protected: class Vertex { public: Vertex(); ~Vertex(); void add_edge(const unsigned int other_vertex); void remove_duplicate_edges(std::vector& tmp); void sort_edges(); unsigned int color; std::vector edges; unsigned int nof_edges() const {return edges.size(); } }; std::vector vertices; void sort_edges(); void remove_duplicate_edges(); /** \internal * Partition independent invariant. * Returns the color of the vertex. * Time complexity: O(1). */ static unsigned int vertex_color_invariant(const Graph* const g, const unsigned int v); /** \internal * Partition independent invariant. * Returns the degree of the vertex. * DUPLICATE EDGES MUST HAVE BEEN REMOVED BEFORE. * Time complexity: O(1). */ static unsigned int degree_invariant(const Graph* const g, const unsigned int v); /** \internal * Partition independent invariant. * Returns 1 if there is an edge from the vertex to itself, 0 if not. * Time complexity: O(k), where k is the number of edges leaving the vertex. */ static unsigned int selfloop_invariant(const Graph* const g, const unsigned int v); bool refine_according_to_invariant(unsigned int (*inv)(const Graph* const g, const unsigned int v)); /* * Routines needed when refining the partition p into equitable */ bool split_neighbourhood_of_unit_cell(Partition::Cell *); bool split_neighbourhood_of_cell(Partition::Cell * const); /** \internal * \copydoc AbstractGraph::is_equitable() const */ bool is_equitable() const; /* Splitting heuristics, documented in more detail in graph.cc */ SplittingHeuristic sh; Partition::Cell* find_next_cell_to_be_splitted(Partition::Cell *cell); Partition::Cell* sh_first(); Partition::Cell* sh_first_smallest(); Partition::Cell* sh_first_largest(); Partition::Cell* sh_first_max_neighbours(); Partition::Cell* sh_first_smallest_max_neighbours(); Partition::Cell* sh_first_largest_max_neighbours(); void make_initial_equitable_partition(); void initialize_certificate(); bool is_automorphism(unsigned int* const perm); bool nucr_find_first_component(const unsigned int level); bool nucr_find_first_component(const unsigned int level, std::vector& component, unsigned int& component_elements, Partition::Cell*& sh_return); public: /** * Create a new graph with \a N vertices and no edges. */ Graph(const unsigned int N = 0); /** * Destroy the graph. */ ~Graph(); /** * Read the graph from the file \a fp in a variant of the DIMACS format. * See the bliss website * for the definition of the file format. * Note that in the DIMACS file the vertices are numbered from 1 to N while * in this C++ API they are from 0 to N-1. * Thus the vertex n in the file corresponds to the vertex n-1 in the API. * * \param fp the file stream for the graph file * \param errstr if non-null, the possible error messages are printed * in this file stream * \return a new Graph object or 0 if reading failed for some * reason */ static Graph* read_dimacs(FILE* const fp, FILE* const errstr = stderr); /** * Write the graph to a file in a variant of the DIMACS format. * See the bliss website * for the definition of the file format. */ void write_dimacs(FILE* const fp); /** * \copydoc AbstractGraph::write_dot(FILE * const fp) */ void write_dot(FILE* const fp); /** * \copydoc AbstractGraph::write_dot(const char * const file_name) */ void write_dot(const char* const file_name); /** * \copydoc AbstractGraph::is_automorphism(const std::vector& perm) const */ bool is_automorphism(const std::vector& perm) const; /** * \copydoc AbstractGraph::get_hash() */ virtual unsigned int get_hash(); /** * Return the number of vertices in the graph. */ unsigned int get_nof_vertices() const {return vertices.size(); } /** * \copydoc AbstractGraph::permute(const unsigned int* const perm) const */ Graph* permute(const unsigned int* const perm) const; Graph* permute(const std::vector& perm) const; /** * Add a new vertex with color \a color in the graph and return its index. */ unsigned int add_vertex(const unsigned int color = 0); /** * Add an edge between vertices \a v1 and \a v2. * Duplicate edges between vertices are ignored but try to avoid introducing * them in the first place as they are not ignored immediately but will * consume memory and computation resources for a while. */ void add_edge(const unsigned int v1, const unsigned int v2); /** * Change the color of the vertex \a vertex to \a color. */ void change_color(const unsigned int vertex, const unsigned int color); /** * Compare this graph with the graph \a other. * Returns 0 if the graphs are equal, and a negative (positive) integer * if this graph is "smaller than" ("greater than", resp.) than \a other. */ int cmp(Graph& other); /** * Set the splitting heuristic used by the automorphism and canonical * labeling algorithm. * The selected splitting heuristics affects the computed canonical * labelings; therefore, if you want to compare whether two graphs * are isomorphic by computing and comparing (for equality) their * canonical versions, be sure to use the same splitting heuristics * for both graphs. */ void set_splitting_heuristic(const SplittingHeuristic shs) {sh = shs; } }; /** * \brief The class for directed, vertex colored graphs. * * Multiple edges between vertices are not allowed (i.e., are ignored). */ class Digraph : public AbstractGraph { public: /** * The possible splitting heuristics. * The selected splitting heuristics affects the computed canonical * labelings; therefore, if you want to compare whether two graphs * are isomorphic by computing and comparing (for equality) their * canonical versions, be sure to use the same splitting heuristics * for both graphs. */ typedef enum { /** First non-unit cell. * Very fast but may result in large search spaces on difficult graphs. * Use for large but easy graphs. */ shs_f = 0, /** First smallest non-unit cell. * Fast, should usually produce smaller search spaces than shs_f. */ shs_fs, /** First largest non-unit cell. * Fast, should usually produce smaller search spaces than shs_f. */ shs_fl, /** First maximally non-trivially connected non-unit cell. * Not so fast, should usually produce smaller search spaces than shs_f, * shs_fs, and shs_fl. */ shs_fm, /** First smallest maximally non-trivially connected non-unit cell. * Not so fast, should usually produce smaller search spaces than shs_f, * shs_fs, and shs_fl. */ shs_fsm, /** First largest maximally non-trivially connected non-unit cell. * Not so fast, should usually produce smaller search spaces than shs_f, * shs_fs, and shs_fl. */ shs_flm } SplittingHeuristic; protected: class Vertex { public: Vertex(); ~Vertex(); void add_edge_to(const unsigned int dest_vertex); void add_edge_from(const unsigned int source_vertex); void remove_duplicate_edges(std::vector& tmp); void sort_edges(); unsigned int color; std::vector edges_out; std::vector edges_in; unsigned int nof_edges_in() const {return edges_in.size(); } unsigned int nof_edges_out() const {return edges_out.size(); } }; std::vector vertices; void remove_duplicate_edges(); /** \internal * Partition independent invariant. * Returns the color of the vertex. * Time complexity: O(1). */ static unsigned int vertex_color_invariant(const Digraph* const g, const unsigned int v); /** \internal * Partition independent invariant. * Returns the indegree of the vertex. * DUPLICATE EDGES MUST HAVE BEEN REMOVED BEFORE. * Time complexity: O(1). */ static unsigned int indegree_invariant(const Digraph* const g, const unsigned int v); /** \internal * Partition independent invariant. * Returns the outdegree of the vertex. * DUPLICATE EDGES MUST HAVE BEEN REMOVED BEFORE. * Time complexity: O(1). */ static unsigned int outdegree_invariant(const Digraph* const g, const unsigned int v); /** \internal * Partition independent invariant. * Returns 1 if there is an edge from the vertex to itself, 0 if not. * Time complexity: O(k), where k is the number of edges leaving the vertex. */ static unsigned int selfloop_invariant(const Digraph* const g, const unsigned int v); /** \internal * Refine the partition \a p according to * the partition independent invariant \a inv. */ bool refine_according_to_invariant(unsigned int (*inv)(const Digraph* const g, const unsigned int v)); /* * Routines needed when refining the partition p into equitable */ bool split_neighbourhood_of_unit_cell(Partition::Cell* const); bool split_neighbourhood_of_cell(Partition::Cell* const); /** \internal * \copydoc AbstractGraph::is_equitable() const */ bool is_equitable() const; /* Splitting heuristics, documented in more detail in the cc-file. */ SplittingHeuristic sh; Partition::Cell* find_next_cell_to_be_splitted(Partition::Cell *cell); Partition::Cell* sh_first(); Partition::Cell* sh_first_smallest(); Partition::Cell* sh_first_largest(); Partition::Cell* sh_first_max_neighbours(); Partition::Cell* sh_first_smallest_max_neighbours(); Partition::Cell* sh_first_largest_max_neighbours(); void make_initial_equitable_partition(); void initialize_certificate(); bool is_automorphism(unsigned int* const perm); void sort_edges(); bool nucr_find_first_component(const unsigned int level); bool nucr_find_first_component(const unsigned int level, std::vector& component, unsigned int& component_elements, Partition::Cell*& sh_return); public: /** * Create a new directed graph with \a N vertices and no edges. */ Digraph(const unsigned int N = 0); /** * Destroy the graph. */ ~Digraph(); /** * Read the graph from the file \a fp in a variant of the DIMACS format. * See the bliss website * for the definition of the file format. * Note that in the DIMACS file the vertices are numbered from 1 to N while * in this C++ API they are from 0 to N-1. * Thus the vertex n in the file corresponds to the vertex n-1 in the API. * \param fp the file stream for the graph file * \param errstr if non-null, the possible error messages are printed * in this file stream * \return a new Digraph object or 0 if reading failed for some * reason */ static Digraph* read_dimacs(FILE* const fp, FILE* const errstr = stderr); /** * \copydoc AbstractGraph::write_dimacs(FILE * const fp) */ void write_dimacs(FILE* const fp); /** * \copydoc AbstractGraph::write_dot(FILE *fp) */ void write_dot(FILE * const fp); /** * \copydoc AbstractGraph::write_dot(const char * const file_name) */ void write_dot(const char * const file_name); /** * \copydoc AbstractGraph::is_automorphism(const std::vector& perm) const */ bool is_automorphism(const std::vector& perm) const; /** * \copydoc AbstractGraph::get_hash() */ virtual unsigned int get_hash(); /** * Return the number of vertices in the graph. */ unsigned int get_nof_vertices() const {return vertices.size(); } /** * Add a new vertex with color 'color' in the graph and return its index. */ unsigned int add_vertex(const unsigned int color = 0); /** * Add an edge from the vertex \a source to the vertex \a target. * Duplicate edges are ignored but try to avoid introducing * them in the first place as they are not ignored immediately but will * consume memory and computation resources for a while. */ void add_edge(const unsigned int source, const unsigned int target); /** * Change the color of the vertex 'vertex' to 'color'. */ void change_color(const unsigned int vertex, const unsigned int color); /** * Compare this graph with the graph \a other. * Returns 0 if the graphs are equal, and a negative (positive) integer * if this graph is "smaller than" ("greater than", resp.) than \a other. */ int cmp(Digraph& other); /** * Set the splitting heuristic used by the automorphism and canonical * labeling algorithm. * The selected splitting heuristics affects the computed canonical * labelings; therefore, if you want to compare whether two graphs * are isomorphic by computing and comparing (for equality) their * canonical versions, be sure to use the same splitting heuristics * for both graphs. */ void set_splitting_heuristic(SplittingHeuristic shs) {sh = shs; } /** * \copydoc AbstractGraph::permute(const unsigned int* const perm) const */ Digraph* permute(const unsigned int* const perm) const; Digraph* permute(const std::vector& perm) const; }; } #endif python-igraph-0.8.0/vendor/source/igraph/src/bliss/orbit.cc0000644000076500000240000000564613524616144024161 0ustar tamasstaff00000000000000#include #include #include "defs.hh" #include "orbit.hh" /* Copyright (c) 2003-2015 Tommi Junttila Released under the GNU Lesser General Public License version 3. This file is part of bliss. bliss is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, version 3 of the License. bliss is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with bliss. If not, see . */ namespace bliss { Orbit::Orbit() { orbits = 0; in_orbit = 0; nof_elements = 0; } Orbit::~Orbit() { if(orbits) { free(orbits); orbits = 0; } if(in_orbit) { free(in_orbit); in_orbit = 0; } nof_elements = 0; } void Orbit::init(const unsigned int n) { assert(n > 0); if(orbits) free(orbits); orbits = (OrbitEntry*)malloc(n * sizeof(OrbitEntry)); if(in_orbit) free(in_orbit); in_orbit = (OrbitEntry**)malloc(n * sizeof(OrbitEntry*)); nof_elements = n; reset(); } void Orbit::reset() { assert(orbits); assert(in_orbit); for(unsigned int i = 0; i < nof_elements; i++) { orbits[i].element = i; orbits[i].next = 0; orbits[i].size = 1; in_orbit[i] = &orbits[i]; } _nof_orbits = nof_elements; } void Orbit::merge_orbits(OrbitEntry *orbit1, OrbitEntry *orbit2) { if(orbit1 != orbit2) { _nof_orbits--; /* Only update the elements in the smaller orbit */ if(orbit1->size > orbit2->size) { OrbitEntry * const temp = orbit2; orbit2 = orbit1; orbit1 = temp; } /* Link the elements of orbit1 to the almost beginning of orbit2 */ OrbitEntry *e = orbit1; while(e->next) { in_orbit[e->element] = orbit2; e = e->next; } in_orbit[e->element] = orbit2; e->next = orbit2->next; orbit2->next = orbit1; /* Keep the minimal orbit representative in the beginning */ if(orbit1->element < orbit2->element) { const unsigned int temp = orbit1->element; orbit1->element = orbit2->element; orbit2->element = temp; } orbit2->size += orbit1->size; } } void Orbit::merge_orbits(unsigned int e1, unsigned int e2) { merge_orbits(in_orbit[e1], in_orbit[e2]); } bool Orbit::is_minimal_representative(unsigned int element) const { return(get_minimal_representative(element) == element); } unsigned int Orbit::get_minimal_representative(unsigned int element) const { OrbitEntry * const orbit = in_orbit[element]; return(orbit->element); } unsigned int Orbit::orbit_size(unsigned int element) const { return(in_orbit[element]->size); } } // namespace bliss python-igraph-0.8.0/vendor/source/igraph/src/bliss/partition.cc0000644000076500000240000006655313524616144025057 0ustar tamasstaff00000000000000#include #include #include #include "graph.hh" #include "partition.hh" /* use 'and' instead of '&&' */ #if _MSC_VER #include #endif /* Copyright (c) 2003-2015 Tommi Junttila Released under the GNU Lesser General Public License version 3. This file is part of bliss. bliss is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, version 3 of the License. bliss is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with bliss. If not, see . */ namespace bliss { Partition::Partition() { N = 0; elements = 0; in_pos = 0; invariant_values = 0; cells = 0; free_cells = 0; element_to_cell_map = 0; graph = 0; discrete_cell_count = 0; /* Initialize a distribution count sorting array. */ for(unsigned int i = 0; i < 256; i++) dcs_count[i] = 0; cr_enabled = false; cr_cells = 0; cr_levels = 0; } Partition::~Partition() { if(elements) {free(elements); elements = 0; } if(cells) {free(cells); cells = 0; } if(element_to_cell_map) {free(element_to_cell_map); element_to_cell_map = 0; } if(in_pos) {free(in_pos); in_pos = 0; } if(invariant_values) {free(invariant_values); invariant_values = 0; } N = 0; } void Partition::init(const unsigned int M) { assert(M > 0); N = M; if(elements) free(elements); elements = (unsigned int*)malloc(N * sizeof(unsigned int)); for(unsigned int i = 0; i < N; i++) elements[i] = i; if(in_pos) free(in_pos); in_pos = (unsigned int**)malloc(N * sizeof(unsigned int*)); for(unsigned int i = 0; i < N; i++) in_pos[i] = elements + i; if(invariant_values) free(invariant_values); invariant_values = (unsigned int*)malloc(N * sizeof(unsigned int)); for(unsigned int i = 0; i < N; i++) invariant_values[i] = 0; if(cells) free(cells); cells = (Cell*)malloc(N * sizeof(Cell)); cells[0].first = 0; cells[0].length = N; cells[0].max_ival = 0; cells[0].max_ival_count = 0; cells[0].in_splitting_queue = false; cells[0].in_neighbour_heap = false; cells[0].prev = 0; cells[0].next = 0; cells[0].next_nonsingleton = 0; cells[0].prev_nonsingleton = 0; cells[0].split_level = 0; first_cell = &cells[0]; if(N == 1) { first_nonsingleton_cell = 0; discrete_cell_count = 1; } else { first_nonsingleton_cell = &cells[0]; discrete_cell_count = 0; } for(unsigned int i = 1; i < N; i++) { cells[i].first = 0; cells[i].length = 0; cells[i].max_ival = 0; cells[i].max_ival_count = 0; cells[i].in_splitting_queue = false; cells[i].in_neighbour_heap = false; cells[i].prev = 0; cells[i].next = (i < N-1)?&cells[i+1]:0; cells[i].next_nonsingleton = 0; cells[i].prev_nonsingleton = 0; } if(N > 1) free_cells = &cells[1]; else free_cells = 0; if(element_to_cell_map) free(element_to_cell_map); element_to_cell_map = (Cell **)malloc(N * sizeof(Cell *)); for(unsigned int i = 0; i < N; i++) element_to_cell_map[i] = first_cell; splitting_queue.init(N); refinement_stack.init(N); /* Reset the main backtracking stack */ bt_stack.clear(); } Partition::BacktrackPoint Partition::set_backtrack_point() { BacktrackInfo info; info.refinement_stack_size = refinement_stack.size(); if(cr_enabled) info.cr_backtrack_point = cr_get_backtrack_point(); BacktrackPoint p = bt_stack.size(); bt_stack.push_back(info); return p; } void Partition::goto_backtrack_point(BacktrackPoint p) { BacktrackInfo info = bt_stack[p]; bt_stack.resize(p); if(cr_enabled) cr_goto_backtrack_point(info.cr_backtrack_point); const unsigned int dest_refinement_stack_size = info.refinement_stack_size; assert(refinement_stack.size() >= dest_refinement_stack_size); while(refinement_stack.size() > dest_refinement_stack_size) { RefInfo i = refinement_stack.pop(); const unsigned int first = i.split_cell_first; Cell* cell = get_cell(elements[first]); if(cell->first != first) { assert(cell->first < first); assert(cell->split_level <= dest_refinement_stack_size); goto done; } assert(cell->split_level > dest_refinement_stack_size); while(cell->split_level > dest_refinement_stack_size) { assert(cell->prev); cell = cell->prev; } while(cell->next and cell->next->split_level > dest_refinement_stack_size) { /* Merge next cell */ Cell* const next_cell = cell->next; if(cell->length == 1) discrete_cell_count--; if(next_cell->length == 1) discrete_cell_count--; /* Update element_to_cell_map values of elements added in cell */ unsigned int* ep = elements + next_cell->first; unsigned int* const lp = ep + next_cell->length; for( ; ep < lp; ep++) element_to_cell_map[*ep] = cell; /* Update cell parameters */ cell->length += next_cell->length; if(next_cell->next) next_cell->next->prev = cell; cell->next = next_cell->next; /* (Pseudo)free next_cell */ next_cell->first = 0; next_cell->length = 0; next_cell->prev = 0; next_cell->next = free_cells; free_cells = next_cell; } done: if(i.prev_nonsingleton_first >= 0) { Cell* const prev_cell = get_cell(elements[i.prev_nonsingleton_first]); cell->prev_nonsingleton = prev_cell; prev_cell->next_nonsingleton = cell; } else { //assert(cell->prev_nonsingleton == 0); cell->prev_nonsingleton = 0; first_nonsingleton_cell = cell; } if(i.next_nonsingleton_first >= 0) { Cell* const next_cell = get_cell(elements[i.next_nonsingleton_first]); cell->next_nonsingleton = next_cell; next_cell->prev_nonsingleton = cell; } else { //assert(cell->next_nonsingleton == 0); cell->next_nonsingleton = 0; } } } Partition::Cell* Partition::individualize(Partition::Cell * const cell, const unsigned int element) { unsigned int * const pos = in_pos[element]; const unsigned int last = cell->first + cell->length - 1; *pos = elements[last]; in_pos[*pos] = pos; elements[last] = element; in_pos[element] = elements + last; Partition::Cell * const new_cell = aux_split_in_two(cell, cell->length-1); element_to_cell_map[element] = new_cell; return new_cell; } Partition::Cell* Partition::aux_split_in_two(Partition::Cell* const cell, const unsigned int first_half_size) { RefInfo i; /* (Pseudo)allocate new cell */ Cell * const new_cell = free_cells; free_cells = new_cell->next; /* Update new cell parameters */ new_cell->first = cell->first + first_half_size; new_cell->length = cell->length - first_half_size; new_cell->next = cell->next; if(new_cell->next) new_cell->next->prev = new_cell; new_cell->prev = cell; new_cell->split_level = refinement_stack.size()+1; /* Update old, splitted cell parameters */ cell->length = first_half_size; cell->next = new_cell; /* CR */ if(cr_enabled) cr_create_at_level_trailed(new_cell->first, cr_get_level(cell->first)); /* Add cell in refinement_stack for backtracking */ i.split_cell_first = new_cell->first; if(cell->prev_nonsingleton) i.prev_nonsingleton_first = cell->prev_nonsingleton->first; else i.prev_nonsingleton_first = -1; if(cell->next_nonsingleton) i.next_nonsingleton_first = cell->next_nonsingleton->first; else i.next_nonsingleton_first = -1; refinement_stack.push(i); /* Modify nonsingleton cell list */ if(new_cell->length > 1) { new_cell->prev_nonsingleton = cell; new_cell->next_nonsingleton = cell->next_nonsingleton; if(new_cell->next_nonsingleton) new_cell->next_nonsingleton->prev_nonsingleton = new_cell; cell->next_nonsingleton = new_cell; } else { new_cell->next_nonsingleton = 0; new_cell->prev_nonsingleton = 0; discrete_cell_count++; } if(cell->is_unit()) { if(cell->prev_nonsingleton) cell->prev_nonsingleton->next_nonsingleton = cell->next_nonsingleton; else first_nonsingleton_cell = cell->next_nonsingleton; if(cell->next_nonsingleton) cell->next_nonsingleton->prev_nonsingleton = cell->prev_nonsingleton; cell->next_nonsingleton = 0; cell->prev_nonsingleton = 0; discrete_cell_count++; } return new_cell; } size_t Partition::print(FILE* const fp, const bool add_newline) const { size_t r = 0; const char* cell_sep = ""; r += fprintf(fp, "["); for(Cell* cell = first_cell; cell; cell = cell->next) { /* Print cell */ r += fprintf(fp, "%s{", cell_sep); cell_sep = ","; const char* elem_sep = ""; for(unsigned int i = 0; i < cell->length; i++) { r += fprintf(fp, "%s%u", elem_sep, elements[cell->first + i]); elem_sep = ","; } r += fprintf(fp, "}"); } r += fprintf(fp, "]"); if(add_newline) r += fprintf(fp, "\n"); return r; } size_t Partition::print_signature(FILE* const fp, const bool add_newline) const { size_t r = 0; const char* cell_sep = ""; r += fprintf(fp, "["); for(Cell* cell = first_cell; cell; cell = cell->next) { if(cell->is_unit()) continue; //fprintf(fp, "%s%u", cell_sep, cr_cells[cell->first].level); r += fprintf(fp, "%s%u", cell_sep, cell->length); cell_sep = ","; } r += fprintf(fp, "]"); if(add_newline) r += fprintf(fp, "\n"); return r; } void Partition::splitting_queue_add(Cell* const cell) { static const unsigned int smallish_cell_threshold = 1; cell->in_splitting_queue = true; if(cell->length <= smallish_cell_threshold) splitting_queue.push_front(cell); else splitting_queue.push_back(cell); } void Partition::splitting_queue_clear() { while(!splitting_queue_is_empty()) splitting_queue_pop(); } /* * Assumes that the invariant values are NOT the same * and that the cell contains more than one element */ Partition::Cell* Partition::sort_and_split_cell1(Partition::Cell* const cell) { #if defined(BLISS_EXPENSIVE_CONSISTENCY_CHECKS) assert(cell->length > 1); assert(cell->first + cell->length <= N); unsigned int nof_0_found = 0; unsigned int nof_1_found = 0; for(unsigned int i = cell->first; i < cell->first + cell->length; i++) { const unsigned int ival = invariant_values[elements[i]]; assert(ival == 0 or ival == 1); if(ival == 0) nof_0_found++; else nof_1_found++; } assert(nof_0_found > 0); assert(nof_1_found > 0); assert(nof_1_found == cell->max_ival_count); assert(nof_0_found + nof_1_found == cell->length); assert(cell->max_ival == 1); #endif /* (Pseudo)allocate new cell */ Cell* const new_cell = free_cells; free_cells = new_cell->next; #define NEW_SORT1 #ifdef NEW_SORT1 unsigned int *ep0 = elements + cell->first; unsigned int *ep1 = ep0 + cell->length - cell->max_ival_count; if(cell->max_ival_count > cell->length / 2) { /* There are more ones than zeros, only move zeros */ unsigned int * const end = ep0 + cell->length; while(ep1 < end) { while(invariant_values[*ep1] == 0) { const unsigned int tmp = *ep1; *ep1 = *ep0; *ep0 = tmp; in_pos[tmp] = ep0; in_pos[*ep1] = ep1; ep0++; } element_to_cell_map[*ep1] = new_cell; invariant_values[*ep1] = 0; ep1++; } } else { /* There are more zeros than ones, only move ones */ unsigned int * const end = ep1; while(ep0 < end) { while(invariant_values[*ep0] != 0) { const unsigned int tmp = *ep0; *ep0 = *ep1; *ep1 = tmp; in_pos[tmp] = ep1; in_pos[*ep0] = ep0; ep1++; } ep0++; } ep1 = end; while(ep1 < elements + cell->first + cell->length) { element_to_cell_map[*ep1] = new_cell; invariant_values[*ep1] = 0; ep1++; } } /* Update new cell parameters */ new_cell->first = cell->first + cell->length - cell->max_ival_count; new_cell->length = cell->length - (new_cell->first - cell->first); new_cell->next = cell->next; if(new_cell->next) new_cell->next->prev = new_cell; new_cell->prev = cell; new_cell->split_level = refinement_stack.size()+1; /* Update old, splitted cell parameters */ cell->length = new_cell->first - cell->first; cell->next = new_cell; /* CR */ if(cr_enabled) cr_create_at_level_trailed(new_cell->first, cr_get_level(cell->first)); #else /* Sort vertices in the cell according to the invariant values */ unsigned int *ep0 = elements + cell->first; unsigned int *ep1 = ep0 + cell->length; while(ep1 > ep0) { const unsigned int element = *ep0; const unsigned int ival = invariant_values[element]; invariant_values[element] = 0; if(ival == 0) { ep0++; } else { ep1--; *ep0 = *ep1; *ep1 = element; element_to_cell_map[element] = new_cell; in_pos[element] = ep1; in_pos[*ep0] = ep0; } } /* Update new cell parameters */ new_cell->first = ep1 - elements; new_cell->length = cell->length - (new_cell->first - cell->first); new_cell->next = cell->next; if(new_cell->next) new_cell->next->prev = new_cell; new_cell->prev = cell; new_cell->split_level = cell->split_level; /* Update old, splitted cell parameters */ cell->length = new_cell->first - cell->first; cell->next = new_cell; cell->split_level = refinement_stack.size()+1; /* CR */ if(cr_enabled) cr_create_at_level_trailed(new_cell->first, cr_get_level(cell->first)); #endif /* ifdef NEW_SORT1*/ /* Add cell in refinement stack for backtracking */ { RefInfo i; i.split_cell_first = new_cell->first; if(cell->prev_nonsingleton) i.prev_nonsingleton_first = cell->prev_nonsingleton->first; else i.prev_nonsingleton_first = -1; if(cell->next_nonsingleton) i.next_nonsingleton_first = cell->next_nonsingleton->first; else i.next_nonsingleton_first = -1; /* Modify nonsingleton cell list */ if(new_cell->length > 1) { new_cell->prev_nonsingleton = cell; new_cell->next_nonsingleton = cell->next_nonsingleton; if(new_cell->next_nonsingleton) new_cell->next_nonsingleton->prev_nonsingleton = new_cell; cell->next_nonsingleton = new_cell; } else { new_cell->next_nonsingleton = 0; new_cell->prev_nonsingleton = 0; discrete_cell_count++; } if(cell->is_unit()) { if(cell->prev_nonsingleton) cell->prev_nonsingleton->next_nonsingleton = cell->next_nonsingleton; else first_nonsingleton_cell = cell->next_nonsingleton; if(cell->next_nonsingleton) cell->next_nonsingleton->prev_nonsingleton = cell->prev_nonsingleton; cell->next_nonsingleton = 0; cell->prev_nonsingleton = 0; discrete_cell_count++; } refinement_stack.push(i); } /* Add cells in splitting queue */ if(cell->in_splitting_queue) { /* Both cells must be included in splitting_queue in order to have refinement to equitable partition */ splitting_queue_add(new_cell); } else { Cell *min_cell, *max_cell; if(cell->length <= new_cell->length) { min_cell = cell; max_cell = new_cell; } else { min_cell = new_cell; max_cell = cell; } /* Put the smaller cell in splitting_queue */ splitting_queue_add(min_cell); if(max_cell->is_unit()) { /* Put the "larger" cell also in splitting_queue */ splitting_queue_add(max_cell); } } return new_cell; } /** * An auxiliary function for distribution count sorting. * Build start array so that * dcs_start[0] = 0 and dcs_start[i+1] = dcs_start[i] + dcs_count[i]. */ void Partition::dcs_cumulate_count(const unsigned int max) { unsigned int* count_p = dcs_count; unsigned int* start_p = dcs_start; unsigned int sum = 0; for(unsigned int i = max+1; i > 0; i--) { *start_p = sum; start_p++; sum += *count_p; count_p++; } } /** * Distribution count sorting of cells with invariant values less than 256. */ Partition::Cell* Partition::sort_and_split_cell255(Partition::Cell* const cell, const unsigned int max_ival) { if(cell->is_unit()) { /* Reset invariant value */ invariant_values[elements[cell->first]] = 0; return cell; } #ifdef BLISS_CONSISTENCY_CHECKS for(unsigned int i = 0; i < 256; i++) assert(dcs_count[i] == 0); #endif /* * Compute the distribution of invariant values to the count array */ { const unsigned int *ep = elements + cell->first; const unsigned int ival = invariant_values[*ep]; dcs_count[ival]++; ep++; #if defined(BLISS_CONSISTENCY_CHECKS) bool equal_invariant_values = true; #endif for(unsigned int i = cell->length - 1; i != 0; i--) { const unsigned int ival2 = invariant_values[*ep]; dcs_count[ival2]++; #if defined(BLISS_CONSISTENCY_CHECKS) if(ival2 != ival) { equal_invariant_values = false; } #endif ep++; } #if defined(BLISS_CONSISTENCY_CHECKS) assert(!equal_invariant_values); if(equal_invariant_values) { assert(dcs_count[ival] == cell->length); dcs_count[ival] = 0; clear_ivs(cell); return cell; } #endif } /* Build start array */ dcs_cumulate_count(max_ival); /* Do the sorting */ for(unsigned int i = 0; i <= max_ival; i++) { unsigned int *ep = elements + cell->first + dcs_start[i]; for(unsigned int j = dcs_count[i]; j > 0; j--) { while(true) { const unsigned int element = *ep; const unsigned int ival = invariant_values[element]; if(ival == i) break; *ep = elements[cell->first + dcs_start[ival]]; elements[cell->first + dcs_start[ival]] = element; dcs_start[ival]++; dcs_count[ival]--; } ep++; } dcs_count[i] = 0; } #if defined(BLISS_CONSISTENCY_CHECKS) for(unsigned int i = 0; i < 256; i++) assert(dcs_count[i] == 0); #endif /* split cell */ Cell* const new_cell = split_cell(cell); return new_cell; } /* * Sort the elements in a cell according to their invariant values. * The invariant values are not cleared. * Warning: the in_pos array is left in incorrect state. */ bool Partition::shellsort_cell(Partition::Cell* const cell) { unsigned int h; unsigned int* ep; if(cell->is_unit()) return false; /* Check whether all the elements have the same invariant value */ bool equal_invariant_values = true; { ep = elements + cell->first; const unsigned int ival = invariant_values[*ep]; ep++; for(unsigned int i = cell->length - 1; i > 0; i--) { if(invariant_values[*ep] != ival) { equal_invariant_values = false; break; } ep++; } } if(equal_invariant_values) return false; ep = elements + cell->first; for(h = 1; h <= cell->length/9; h = 3*h + 1) ; for( ; h > 0; h = h/3) { for(unsigned int i = h; i < cell->length; i++) { const unsigned int element = ep[i]; const unsigned int ival = invariant_values[element]; unsigned int j = i; while(j >= h and invariant_values[ep[j-h]] > ival) { ep[j] = ep[j-h]; j -= h; } ep[j] = element; } } return true; } void Partition::clear_ivs(Cell* const cell) { unsigned int* ep = elements + cell->first; for(unsigned int i = cell->length; i > 0; i--, ep++) invariant_values[*ep] = 0; } /* * Assumes that the elements in the cell are sorted according to their * invariant values. */ Partition::Cell* Partition::split_cell(Partition::Cell* const original_cell) { Cell* cell = original_cell; const bool original_cell_was_in_splitting_queue = original_cell->in_splitting_queue; Cell* largest_new_cell = 0; while(true) { unsigned int* ep = elements + cell->first; const unsigned int* const lp = ep + cell->length; const unsigned int ival = invariant_values[*ep]; invariant_values[*ep] = 0; element_to_cell_map[*ep] = cell; in_pos[*ep] = ep; ep++; while(ep < lp) { const unsigned int e = *ep; if(invariant_values[e] != ival) break; invariant_values[e] = 0; in_pos[e] = ep; ep++; element_to_cell_map[e] = cell; } if(ep == lp) break; Cell* const new_cell = aux_split_in_two(cell, (ep - elements) - cell->first); if(graph and graph->compute_eqref_hash) { graph->eqref_hash.update(new_cell->first); graph->eqref_hash.update(new_cell->length); graph->eqref_hash.update(ival); } /* Add cells in splitting_queue */ assert(!new_cell->is_in_splitting_queue()); if(original_cell_was_in_splitting_queue) { /* In this case, all new cells are inserted in splitting_queue */ assert(cell->is_in_splitting_queue()); splitting_queue_add(new_cell); } else { /* Otherwise, we can omit one new cell from splitting_queue */ assert(!cell->is_in_splitting_queue()); if(largest_new_cell == 0) { largest_new_cell = cell; } else { assert(!largest_new_cell->is_in_splitting_queue()); if(cell->length > largest_new_cell->length) { splitting_queue_add(largest_new_cell); largest_new_cell = cell; } else { splitting_queue_add(cell); } } } /* Process the rest of the cell */ cell = new_cell; } if(original_cell == cell) { /* All the elements in cell had the same invariant value */ return cell; } /* Add cells in splitting_queue */ if(!original_cell_was_in_splitting_queue) { /* Also consider the last new cell */ assert(largest_new_cell); if(cell->length > largest_new_cell->length) { splitting_queue_add(largest_new_cell); largest_new_cell = cell; } else { splitting_queue_add(cell); } if(largest_new_cell->is_unit()) { /* Needed in certificate computation */ splitting_queue_add(largest_new_cell); } } return cell; } Partition::Cell* Partition::zplit_cell(Partition::Cell* const cell, const bool max_ival_info_ok) { Cell* last_new_cell = cell; if(!max_ival_info_ok) { /* Compute max_ival info */ assert(cell->max_ival == 0); assert(cell->max_ival_count == 0); unsigned int *ep = elements + cell->first; for(unsigned int i = cell->length; i > 0; i--, ep++) { const unsigned int ival = invariant_values[*ep]; if(ival > cell->max_ival) { cell->max_ival = ival; cell->max_ival_count = 1; } else if(ival == cell->max_ival) { cell->max_ival_count++; } } } #ifdef BLISS_CONSISTENCY_CHECKS /* Verify max_ival info */ { unsigned int nof_zeros = 0; unsigned int max_ival = 0; unsigned int max_ival_count = 0; unsigned int *ep = elements + cell->first; for(unsigned int i = cell->length; i > 0; i--, ep++) { const unsigned int ival = invariant_values[*ep]; if(ival == 0) nof_zeros++; if(ival > max_ival) { max_ival = ival; max_ival_count = 1; } else if(ival == max_ival) max_ival_count++; } assert(max_ival == cell->max_ival); assert(max_ival_count == cell->max_ival_count); } #endif /* max_ival info has been computed */ if(cell->max_ival_count == cell->length) { /* All invariant values are the same, clear 'em */ if(cell->max_ival > 0) clear_ivs(cell); } else { /* All invariant values are not the same */ if(cell->max_ival == 1) { /* Specialized splitting for cells with binary invariant values */ last_new_cell = sort_and_split_cell1(cell); } else if(cell->max_ival < 256) { /* Specialized splitting for cells with invariant values < 256 */ last_new_cell = sort_and_split_cell255(cell, cell->max_ival); } else { /* Generic sorting and splitting */ const bool sorted = shellsort_cell(cell); assert(sorted); last_new_cell = split_cell(cell); } } cell->max_ival = 0; cell->max_ival_count = 0; return last_new_cell; } /* * * Component recursion specific code * */ void Partition::cr_init() { assert(bt_stack.empty()); cr_enabled = true; if(cr_cells) free(cr_cells); cr_cells = (CRCell*)malloc(N * sizeof(CRCell)); if(!cr_cells) {assert(false && "Mem out"); } if(cr_levels) free(cr_levels); cr_levels = (CRCell**)malloc(N * sizeof(CRCell*)); if(!cr_levels) {assert(false && "Mem out"); } for(unsigned int i = 0; i < N; i++) { cr_levels[i] = 0; cr_cells[i].level = UINT_MAX; cr_cells[i].next = 0; cr_cells[i].prev_next_ptr = 0; } for(const Cell *cell = first_cell; cell; cell = cell->next) cr_create_at_level_trailed(cell->first, 0); cr_max_level = 0; } void Partition::cr_free() { if(cr_cells) {free(cr_cells); cr_cells = 0; } if(cr_levels) {free(cr_levels); cr_levels = 0; } cr_created_trail.clear(); cr_splitted_level_trail.clear(); cr_bt_info.clear(); cr_max_level = 0; cr_enabled = false; } unsigned int Partition::cr_split_level(const unsigned int level, const std::vector& splitted_cells) { assert(cr_enabled); assert(level <= cr_max_level); cr_levels[++cr_max_level] = 0; cr_splitted_level_trail.push_back(level); for(unsigned int i = 0; i < splitted_cells.size(); i++) { const unsigned int cell_index = splitted_cells[i]; assert(cell_index < N); CRCell& cr_cell = cr_cells[cell_index]; assert(cr_cell.level == level); cr_cell.detach(); cr_create_at_level(cell_index, cr_max_level); } return cr_max_level; } unsigned int Partition::cr_get_backtrack_point() { assert(cr_enabled); CR_BTInfo info; info.created_trail_index = cr_created_trail.size(); info.splitted_level_trail_index = cr_splitted_level_trail.size(); cr_bt_info.push_back(info); return cr_bt_info.size()-1; } void Partition::cr_goto_backtrack_point(const unsigned int btpoint) { assert(cr_enabled); assert(btpoint < cr_bt_info.size()); while(cr_created_trail.size() > cr_bt_info[btpoint].created_trail_index) { const unsigned int cell_index = cr_created_trail.back(); cr_created_trail.pop_back(); CRCell& cr_cell = cr_cells[cell_index]; assert(cr_cell.level != UINT_MAX); assert(cr_cell.prev_next_ptr); cr_cell.detach(); } while(cr_splitted_level_trail.size() > cr_bt_info[btpoint].splitted_level_trail_index) { const unsigned int dest_level = cr_splitted_level_trail.back(); cr_splitted_level_trail.pop_back(); assert(cr_max_level > 0); assert(dest_level < cr_max_level); while(cr_levels[cr_max_level]) { CRCell *cr_cell = cr_levels[cr_max_level]; cr_cell->detach(); cr_create_at_level(cr_cell - cr_cells, dest_level); } cr_max_level--; } cr_bt_info.resize(btpoint); } void Partition::cr_create_at_level(const unsigned int cell_index, const unsigned int level) { assert(cr_enabled); assert(cell_index < N); assert(level < N); CRCell& cr_cell = cr_cells[cell_index]; assert(cr_cell.level == UINT_MAX); assert(cr_cell.next == 0); assert(cr_cell.prev_next_ptr == 0); if(cr_levels[level]) cr_levels[level]->prev_next_ptr = &(cr_cell.next); cr_cell.next = cr_levels[level]; cr_levels[level] = &cr_cell; cr_cell.prev_next_ptr = &cr_levels[level]; cr_cell.level = level; } void Partition::cr_create_at_level_trailed(const unsigned int cell_index, const unsigned int level) { assert(cr_enabled); cr_create_at_level(cell_index, level); cr_created_trail.push_back(cell_index); } } // namespace bliss python-igraph-0.8.0/vendor/source/igraph/src/array.c0000644000076500000240000000260113614300625022657 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_types.h" #include "igraph_vector.h" #include "igraph_array.h" #define BASE_IGRAPH_REAL #include "igraph_pmt.h" #include "array.pmt" #include "igraph_pmt_off.h" #undef BASE_IGRAPH_REAL #define BASE_LONG #include "igraph_pmt.h" #include "array.pmt" #include "igraph_pmt_off.h" #undef BASE_LONG #define BASE_CHAR #include "igraph_pmt.h" #include "array.pmt" #include "igraph_pmt_off.h" #undef BASE_CHAR #define BASE_BOOL #include "igraph_pmt.h" #include "array.pmt" #include "igraph_pmt_off.h" #undef BASE_BOOL python-igraph-0.8.0/vendor/source/igraph/src/foreign-dl-lexer.l0000644000076500000240000001066613524616145024736 0ustar tamasstaff00000000000000/* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ %{ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "config.h" #include #include #include "foreign-dl-header.h" #include "foreign-dl-parser.h" #define YY_EXTRA_TYPE igraph_i_dl_parsedata_t* #define YY_USER_ACTION yylloc->first_line = yylineno; /* We assume that 'file' is 'stderr' here. */ #ifdef USING_R #define fprintf(file, msg, ...) (1) #endif #ifdef stdout # undef stdout #endif #define stdout 0 #define exit(code) igraph_error("Fatal error in DL parser", __FILE__, \ __LINE__, IGRAPH_PARSEERROR); %} %option noyywrap %option prefix="igraph_dl_yy" %option outfile="lex.yy.c" %option nounput %option noinput %option nodefault %option reentrant %option bison-bridge %option bison-locations digit [0-9] whitespace [ \t\v\f] %x LABELM FULLMATRIX EDGELIST NODELIST %% <*>\n\r|\r\n|\r|\n { return NEWLINE; } [dD][lL]{whitespace}+ { return DL; } [nN]{whitespace}*[=]{whitespace}* { return NEQ; } {digit}+ { return NUM; } [dD][aA][tT][aA][:] { switch (yyextra->mode) { case 0: BEGIN(FULLMATRIX); break; case 1: BEGIN(EDGELIST); break; case 2: BEGIN(NODELIST); break; } return DATA; } [lL][aA][bB][eE][lL][sS]: { BEGIN(LABELM); return LABELS; } [lL][aA][bB][eE][lL][sS]{whitespace}+[eE][mM][bB][eE][dD][dD][eE][dD]:?{whitespace}* { return LABELSEMBEDDED; } [fF][oO][rR][mM][aA][tT]{whitespace}*[=]{whitespace}*[fF][uU][lL][lL][mM][aA][tT][rR][iI][xX]{whitespace}* { yyextra->mode=0; return FORMATFULLMATRIX; } [fF][oO][rR][mM][aA][tT]{whitespace}*[=]{whitespace}*[eE][dD][gG][eE][lL][iI][sS][tT][1]{whitespace}* { yyextra->mode=1; return FORMATEDGELIST1; } [fF][oO][rR][mM][aA][tT]{whitespace}*[=]{whitespace}*[nN][oO][dD][eE][lL][iI][sS][tT][1]{whitespace}* { yyextra->mode=2; return FORMATNODELIST1; } [, ] { /* eaten up */ } [^, \t\n\r\f\v]+{whitespace}* { return LABEL; } {digit}{whitespace}* { return DIGIT; } [^ \t\n\r\v\f,]+ { return LABEL; } {whitespace} { } \-?{digit}+(\.{digit}+)?([eE](\+|\-)?{digit}+)? { return NUM; } [^ \t\n\r\v\f,]+ { return LABEL; } {whitespace}* { } {digit}+ { return NUM; } [^ \t\r\n\v\f,]+ { return LABEL; } {whitespace}* { } {whitespace}+ { /* eaten up */ } <> { if (yyextra->eof) { yyterminate(); } else { yyextra->eof=1; BEGIN(INITIAL); return EOFF; } } <*>. { return 0; } . { return ERROR; } python-igraph-0.8.0/vendor/source/igraph/src/degree_sequence.cpp0000644000076500000240000004020413614300625025225 0ustar tamasstaff00000000000000/* Constructing realizations of degree sequences and bi-degree sequences. Copyright (C) 2018 Szabolcs Horvat This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_constructors.h" #include "igraph_interface.h" #include #include #include #include // (vertex, degree) pair struct vd_pair { long vertex; igraph_integer_t degree; vd_pair(long vertex, igraph_integer_t degree) : vertex(vertex), degree(degree) {} }; // (indegree, outdegree) typedef std::pair bidegree; // (vertex, bidegree) pair struct vbd_pair { long vertex; bidegree degree; vbd_pair(long vertex, bidegree degree) : vertex(vertex), degree(degree) {} }; // Comparison function for vertex-degree pairs. // Also used for lexicographic sorting of bi-degrees. template inline bool degree_greater(const T &a, const T &b) { return a.degree > b.degree; } template inline bool degree_less(const T &a, const T &b) { return a.degree < b.degree; } // Generate undirected realization as edge-list. // If largest=true, always choose the vertex with the largest remaining degree to connect up next. // Otherwise, always choose the one with the smallest remaining degree. static int igraph_i_havel_hakimi(const igraph_vector_t *deg, igraph_vector_t *edges, bool largest) { long n = igraph_vector_size(deg); long ec = 0; // number of edges added so far std::vector vertices; vertices.reserve(n); for (int i = 0; i < n; ++i) { vertices.push_back(vd_pair(i, VECTOR(*deg)[i])); } while (! vertices.empty()) { if (largest) { std::stable_sort(vertices.begin(), vertices.end(), degree_less); } else { std::stable_sort(vertices.begin(), vertices.end(), degree_greater); } // take the next vertex to be connected up vd_pair vd = vertices.back(); vertices.pop_back(); if (vd.degree < 0) { IGRAPH_ERROR("Vertex degrees must be positive", IGRAPH_EINVAL); } if (vd.degree == 0) { continue; } if (vertices.size() < size_t(vd.degree)) { goto fail; } if (largest) { for (int i = 0; i < vd.degree; ++i) { if (--(vertices[vertices.size() - 1 - i].degree) < 0) { goto fail; } VECTOR(*edges)[2 * (ec + i)] = vd.vertex; VECTOR(*edges)[2 * (ec + i) + 1] = vertices[vertices.size() - 1 - i].vertex; } } else { // this loop can only be reached if all zero-degree nodes have already been removed // therefore decrementing remaining degrees is safe for (int i = 0; i < vd.degree; ++i) { vertices[i].degree--; VECTOR(*edges)[2 * (ec + i)] = vd.vertex; VECTOR(*edges)[2 * (ec + i) + 1] = vertices[i].vertex; } } ec += vd.degree; } return IGRAPH_SUCCESS; fail: IGRAPH_ERROR("The given degree sequence is not realizable", IGRAPH_EINVAL); } // Choose vertices in the order of their IDs. static int igraph_i_havel_hakimi_index(const igraph_vector_t *deg, igraph_vector_t *edges) { long n = igraph_vector_size(deg); long ec = 0; // number of edges added so far typedef std::list vlist; vlist vertices; for (int i = 0; i < n; ++i) { vertices.push_back(vd_pair(i, VECTOR(*deg)[i])); } std::vector pointers; pointers.reserve(n); for (vlist::iterator it = vertices.begin(); it != vertices.end(); ++it) { pointers.push_back(it); } for (std::vector::iterator pt = pointers.begin(); pt != pointers.end(); ++pt) { vertices.sort(degree_greater); vd_pair vd = **pt; vertices.erase(*pt); if (vd.degree < 0) { IGRAPH_ERROR("Vertex degrees must be positive", IGRAPH_EINVAL); } if (vd.degree == 0) { continue; } int k; vlist::iterator it; for (it = vertices.begin(), k = 0; k != vd.degree && it != vertices.end(); ++it, ++k) { if (--(it->degree) < 0) { goto fail; } VECTOR(*edges)[2 * (ec + k)] = vd.vertex; VECTOR(*edges)[2 * (ec + k) + 1] = it->vertex; } if (it == vertices.end() && k < vd.degree) { goto fail; } ec += vd.degree; } return IGRAPH_SUCCESS; fail: IGRAPH_ERROR("The given degree sequence is not realizable", IGRAPH_EINVAL); } inline bool is_nonzero_outdeg(const vbd_pair &vd) { return (vd.degree.second != 0); } // The below implementations of the Kleitman-Wang algorithm follow the description in https://arxiv.org/abs/0905.4913 // Realize bi-degree sequence as edge list // If smallest=true, always choose the vertex with "smallest" bi-degree for connecting up next, // otherwise choose the "largest" (based on lexicographic bi-degree ordering). static int igraph_i_kleitman_wang(const igraph_vector_t *outdeg, const igraph_vector_t *indeg, igraph_vector_t *edges, bool smallest) { long n = igraph_vector_size(indeg); // number of vertices long ec = 0; // number of edges added so far std::vector vertices; vertices.reserve(n); for (int i = 0; i < n; ++i) { vertices.push_back(vbd_pair(i, bidegree(VECTOR(*indeg)[i], VECTOR(*outdeg)[i]))); } while (true) { // sort vertices by (in, out) degree pairs in decreasing order std::stable_sort(vertices.begin(), vertices.end(), degree_greater); // remove (0,0)-degree vertices while (!vertices.empty() && vertices.back().degree == bidegree(0, 0)) { vertices.pop_back(); } // if no vertices remain, stop if (vertices.empty()) { break; } // choose a vertex the out-stubs of which will be connected vbd_pair *vdp; if (smallest) { vdp = &*std::find_if(vertices.rbegin(), vertices.rend(), is_nonzero_outdeg); } else { vdp = &*std::find_if(vertices.begin(), vertices.end(), is_nonzero_outdeg); } if (vdp->degree.first < 0 || vdp->degree.second < 0) { IGRAPH_ERROR("Vertex degrees must be positive", IGRAPH_EINVAL); } // are there a sufficient number of other vertices to connect to? if (vertices.size() < vdp->degree.second - 1) { goto fail; } // create the connections int k = 0; for (std::vector::iterator it = vertices.begin(); k < vdp->degree.second; ++it) { if (it->vertex == vdp->vertex) { continue; // do not create a self-loop } if (--(it->degree.first) < 0) { goto fail; } VECTOR(*edges)[2 * (ec + k)] = vdp->vertex; VECTOR(*edges)[2 * (ec + k) + 1] = it->vertex; k++; } ec += vdp->degree.second; vdp->degree.second = 0; } return IGRAPH_SUCCESS; fail: IGRAPH_ERROR("The given directed degree sequence is not realizable", IGRAPH_EINVAL); } // Choose vertices in the order of their IDs. static int igraph_i_kleitman_wang_index(const igraph_vector_t *outdeg, const igraph_vector_t *indeg, igraph_vector_t *edges) { long n = igraph_vector_size(indeg); // number of vertices long ec = 0; // number of edges added so far typedef std::list vlist; vlist vertices; for (int i = 0; i < n; ++i) { vertices.push_back(vbd_pair(i, bidegree(VECTOR(*indeg)[i], VECTOR(*outdeg)[i]))); } std::vector pointers; pointers.reserve(n); for (vlist::iterator it = vertices.begin(); it != vertices.end(); ++it) { pointers.push_back(it); } for (std::vector::iterator pt = pointers.begin(); pt != pointers.end(); ++pt) { // sort vertices by (in, out) degree pairs in decreasing order // note: std::list::sort does a stable sort vertices.sort(degree_greater); // choose a vertex the out-stubs of which will be connected vbd_pair &vd = **pt; if (vd.degree.second == 0) { continue; } if (vd.degree.first < 0 || vd.degree.second < 0) { IGRAPH_ERROR("Vertex degrees must be positive", IGRAPH_EINVAL); } int k = 0; vlist::iterator it; for (it = vertices.begin(); k != vd.degree.second && it != vertices.end(); ++it) { if (it->vertex == vd.vertex) { continue; } if (--(it->degree.first) < 0) { goto fail; } VECTOR(*edges)[2 * (ec + k)] = vd.vertex; VECTOR(*edges)[2 * (ec + k) + 1] = it->vertex; ++k; } if (it == vertices.end() && k < vd.degree.second) { goto fail; } ec += vd.degree.second; vd.degree.second = 0; } return IGRAPH_SUCCESS; fail: IGRAPH_ERROR("The given directed degree sequence is not realizable", IGRAPH_EINVAL); } static int igraph_i_realize_undirected_degree_sequence( igraph_t *graph, const igraph_vector_t *deg, igraph_realize_degseq_t method) { long node_count = igraph_vector_size(deg); long deg_sum = long(igraph_vector_sum(deg)); if (deg_sum % 2 != 0) { IGRAPH_ERROR("The sum of degrees must be even for an undirected graph", IGRAPH_EINVAL); } igraph_vector_t edges; IGRAPH_CHECK(igraph_vector_init(&edges, deg_sum)); IGRAPH_FINALLY(igraph_vector_destroy, &edges); switch (method) { case IGRAPH_REALIZE_DEGSEQ_SMALLEST: IGRAPH_CHECK(igraph_i_havel_hakimi(deg, &edges, false)); break; case IGRAPH_REALIZE_DEGSEQ_LARGEST: IGRAPH_CHECK(igraph_i_havel_hakimi(deg, &edges, true)); break; case IGRAPH_REALIZE_DEGSEQ_INDEX: IGRAPH_CHECK(igraph_i_havel_hakimi_index(deg, &edges)); break; default: IGRAPH_ERROR("Invalid degree sequence realization method", IGRAPH_EINVAL); } igraph_create(graph, &edges, igraph_integer_t(node_count), false); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } static int igraph_i_realize_directed_degree_sequence( igraph_t *graph, const igraph_vector_t *outdeg, const igraph_vector_t *indeg, igraph_realize_degseq_t method) { long node_count = igraph_vector_size(outdeg); long edge_count = long(igraph_vector_sum(outdeg)); if (igraph_vector_size(indeg) != node_count) { IGRAPH_ERROR("In- and out-degree sequences must have the same length", IGRAPH_EINVAL); } if (igraph_vector_sum(indeg) != edge_count) { IGRAPH_ERROR("In- and out-degree sequences do not sum to the same value", IGRAPH_EINVAL); } igraph_vector_t edges; IGRAPH_CHECK(igraph_vector_init(&edges, 2 * edge_count)); IGRAPH_FINALLY(igraph_vector_destroy, &edges); switch (method) { case IGRAPH_REALIZE_DEGSEQ_SMALLEST: IGRAPH_CHECK(igraph_i_kleitman_wang(outdeg, indeg, &edges, true)); break; case IGRAPH_REALIZE_DEGSEQ_LARGEST: IGRAPH_CHECK(igraph_i_kleitman_wang(outdeg, indeg, &edges, false)); break; case IGRAPH_REALIZE_DEGSEQ_INDEX: IGRAPH_CHECK(igraph_i_kleitman_wang_index(outdeg, indeg, &edges)); break; default: IGRAPH_ERROR("Invalid bi-degree sequence realization method", IGRAPH_EINVAL); } igraph_create(graph, &edges, igraph_integer_t(node_count), true); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } /** * \ingroup generators * \function igraph_realize_degree_sequence * \brief Generates a graph with the given degree sequence * * This function constructs a simple graph that realizes the given degree sequence * using the Havel-Hakimi algorithm, or the given (directed) out- and in-degree * sequences using the related Kleitman-Wang algorithm. * * The algorithms work by choosing an arbitrary vertex and connecting all its stubs * to other vertices of highest degree. In the directed case, the "highest" (in, out) degree * pairs are determined based on lexicographic ordering. * * The \c method parameter controls the order in which the vertices to be connected are chosen. * * \param graph Pointer to an uninitialized graph object. * \param outdeg The degree sequence for a simple undirected graph * (if \p indeg is NULL or of length zero), or the out-degree sequence of * a directed graph (if \p indeg is of nonzero size). * \param indeg It is either a zero-length vector or \c NULL (if an undirected graph * is generated), or the in-degree sequence. * \param method The method to generate the graph. Possible values: * \clist * \cli IGRAPH_REALIZE_DEGSEQ_SMALLEST * The vertex with smallest remaining degree is selected first. The result is usually * a graph with high negative degree assortativity. In the undirected case, this method * is guaranteed to generate a connected graph, provided that a connected realization exists. * See http://szhorvat.net/pelican/hh-connected-graphs.html for a proof. * In the directed case it tends to generate weakly connected graphs, but this is not * guaranteed. * \cli IGRAPH_REALIZE_DEGSEQ_LARGEST * The vertex with the largest remaining degree is selected first. The result * is usually a graph with high positive degree assortativity, and is often disconnected. * \cli IGRAPH_REALIZE_DEGSEQ_INDEX * The vertices are selected in order of their index (i.e. their position in the degree vector). * Note that sorting the degree vector and using the \c INDEX method is not equivalent * to the \c SMALLEST method above, as \c SMALLEST uses the smallest \em remaining * degree for selecting vertices, not the smallest \em initial degree. * \endclist * \return Error code: * \clist * \cli IGRAPH_ENOMEM * There is not enough memory to perform the operation. * \cli IGRAPH_EINVAL * Invalid method parameter, or invalid in- and/or out-degree vectors. * The degree vectors should be non-negative, the length * and sum of \p outdeg and \p indeg should match for directed graphs. * \endclist * * \sa \ref igraph_is_graphical_degree_sequence() * \ref igraph_degree_sequence_game() * \ref igraph_k_regular_game() * \ref igraph_rewire() * */ int igraph_realize_degree_sequence( igraph_t *graph, const igraph_vector_t *outdeg, const igraph_vector_t *indeg, igraph_realize_degseq_t method) { long n = igraph_vector_size(outdeg); if (n != igraph_integer_t(n)) { // does the vector size fit into an igraph_integer_t ? IGRAPH_ERROR("Degree sequence vector too long", IGRAPH_EINVAL); } bool directed = bool(indeg) && igraph_vector_size(indeg) != 0; try { if (directed) { return igraph_i_realize_directed_degree_sequence(graph, outdeg, indeg, method); } else { return igraph_i_realize_undirected_degree_sequence(graph, outdeg, method); } } catch (const std::bad_alloc &) { IGRAPH_ERROR("Cannot realize degree sequence due to insufficient memory", IGRAPH_ENOMEM); } } python-igraph-0.8.0/vendor/source/igraph/src/igraph_grid.c0000644000076500000240000004062213614300625024025 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph R package. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_types.h" #include "igraph_types_internal.h" #include "igraph_memory.h" #include "config.h" #include /* internal function */ int igraph_2dgrid_which(igraph_2dgrid_t *grid, igraph_real_t xc, igraph_real_t yc, long int *x, long int *y) { if (xc <= grid->minx) { *x = 0; } else if (xc >= grid->maxx) { *x = grid->stepsx - 1; } else { *x = (long int) floor((xc - (grid->minx)) / (grid->deltax)); } if (yc <= grid->miny) { *y = 0; } else if (yc >= grid->maxy) { *y = grid->stepsy - 1; } else { *y = (long int) floor((yc - (grid->miny)) / (grid->deltay)); } return 0; } int igraph_2dgrid_init(igraph_2dgrid_t *grid, igraph_matrix_t *coords, igraph_real_t minx, igraph_real_t maxx, igraph_real_t deltax, igraph_real_t miny, igraph_real_t maxy, igraph_real_t deltay) { long int i; grid->coords = coords; grid->minx = minx; grid->maxx = maxx; grid->deltax = deltax; grid->miny = miny; grid->maxy = maxy; grid->deltay = deltay; grid->stepsx = (long int) ceil((maxx - minx) / deltax); grid->stepsy = (long int) ceil((maxy - miny) / deltay); IGRAPH_CHECK(igraph_matrix_init(&grid->startidx, grid->stepsx, grid->stepsy)); IGRAPH_FINALLY(igraph_matrix_destroy, &grid->startidx); IGRAPH_VECTOR_INIT_FINALLY(&grid->next, igraph_matrix_nrow(coords)); IGRAPH_VECTOR_INIT_FINALLY(&grid->prev, igraph_matrix_nrow(coords)); for (i = 0; i < igraph_vector_size(&grid->next); i++) { VECTOR(grid->next)[i] = -1; } grid->massx = 0; grid->massy = 0; grid->vertices = 0; IGRAPH_FINALLY_CLEAN(3); return 0; } void igraph_2dgrid_destroy(igraph_2dgrid_t *grid) { igraph_matrix_destroy(&grid->startidx); igraph_vector_destroy(&grid->next); igraph_vector_destroy(&grid->prev); } void igraph_2dgrid_add(igraph_2dgrid_t *grid, long int elem, igraph_real_t xc, igraph_real_t yc) { long int x, y; long int first; MATRIX(*grid->coords, elem, 0) = xc; MATRIX(*grid->coords, elem, 1) = yc; /* add to cell */ igraph_2dgrid_which(grid, xc, yc, &x, &y); first = (long int) MATRIX(grid->startidx, x, y); VECTOR(grid->prev)[elem] = 0; VECTOR(grid->next)[elem] = first; if (first != 0) { VECTOR(grid->prev)[first - 1] = elem + 1; } MATRIX(grid->startidx, x, y) = elem + 1; grid->massx += xc; grid->massy += yc; grid->vertices += 1; } void igraph_2dgrid_add2(igraph_2dgrid_t *grid, long int elem) { long int x, y; long int first; igraph_real_t xc, yc; xc = MATRIX(*grid->coords, elem, 0); yc = MATRIX(*grid->coords, elem, 1); /* add to cell */ igraph_2dgrid_which(grid, xc, yc, &x, &y); first = (long int) MATRIX(grid->startidx, x, y); VECTOR(grid->prev)[elem] = 0; VECTOR(grid->next)[elem] = first; if (first != 0) { VECTOR(grid->prev)[first - 1] = elem + 1; } MATRIX(grid->startidx, x, y) = elem + 1; grid->massx += xc; grid->massy += yc; grid->vertices += 1; } void igraph_2dgrid_move(igraph_2dgrid_t *grid, long int elem, igraph_real_t xc, igraph_real_t yc) { long int oldx, oldy; long int newx, newy; igraph_real_t oldxc = MATRIX(*grid->coords, elem, 0); igraph_real_t oldyc = MATRIX(*grid->coords, elem, 1); long int first; xc = oldxc + xc; yc = oldyc + yc; igraph_2dgrid_which(grid, oldxc, oldyc, &oldx, &oldy); igraph_2dgrid_which(grid, xc, yc, &newx, &newy); if (oldx != newx || oldy != newy) { /* remove from this cell */ if (VECTOR(grid->prev)[elem] != 0) { VECTOR(grid->next) [ (long int) VECTOR(grid->prev)[elem] - 1 ] = VECTOR(grid->next)[elem]; } else { MATRIX(grid->startidx, oldx, oldy) = VECTOR(grid->next)[elem]; } if (VECTOR(grid->next)[elem] != 0) { VECTOR(grid->prev)[ (long int) VECTOR(grid->next)[elem] - 1 ] = VECTOR(grid->prev)[elem]; } /* add to this cell */ first = (long int) MATRIX(grid->startidx, newx, newy); VECTOR(grid->prev)[elem] = 0; VECTOR(grid->next)[elem] = first; if (first != 0) { VECTOR(grid->prev)[first - 1] = elem + 1; } MATRIX(grid->startidx, newx, newy) = elem + 1; } grid->massx += -oldxc + xc; grid->massy += -oldyc + yc; MATRIX(*grid->coords, elem, 0) = xc; MATRIX(*grid->coords, elem, 1) = yc; } void igraph_2dgrid_getcenter(const igraph_2dgrid_t *grid, igraph_real_t *massx, igraph_real_t *massy) { *massx = (grid->massx) / (grid->vertices); *massy = (grid->massy) / (grid->vertices); } igraph_bool_t igraph_2dgrid_in(const igraph_2dgrid_t *grid, long int elem) { return VECTOR(grid->next)[elem] != -1; } igraph_real_t igraph_2dgrid_dist(const igraph_2dgrid_t *grid, long int e1, long int e2) { igraph_real_t x = MATRIX(*grid->coords, e1, 0) - MATRIX(*grid->coords, e2, 0); igraph_real_t y = MATRIX(*grid->coords, e1, 1) - MATRIX(*grid->coords, e2, 1); return sqrt(x * x + y * y); } igraph_real_t igraph_2dgrid_dist2(const igraph_2dgrid_t *grid, long int e1, long int e2) { igraph_real_t x = MATRIX(*grid->coords, e1, 0) - MATRIX(*grid->coords, e2, 0); igraph_real_t y = MATRIX(*grid->coords, e1, 1) - MATRIX(*grid->coords, e2, 1); return x * x + y * y; } int igraph_i_2dgrid_addvertices(igraph_2dgrid_t *grid, igraph_vector_t *eids, igraph_integer_t vid, igraph_real_t r, long int x, long int y) { long int act; igraph_real_t *v = VECTOR(grid->next); r = r * r; act = (long int) MATRIX(grid->startidx, x, y); while (act != 0) { if (igraph_2dgrid_dist2(grid, vid, act - 1) < r) { IGRAPH_CHECK(igraph_vector_push_back(eids, act - 1)); } act = (long int) v[act - 1]; } return 0; } int igraph_2dgrid_neighbors(igraph_2dgrid_t *grid, igraph_vector_t *eids, igraph_integer_t vid, igraph_real_t r) { igraph_real_t xc = MATRIX(*grid->coords, (long int)vid, 0); igraph_real_t yc = MATRIX(*grid->coords, (long int)vid, 1); long int x, y; igraph_vector_clear(eids); igraph_2dgrid_which(grid, xc, yc, &x, &y); /* this cell */ igraph_i_2dgrid_addvertices(grid, eids, vid, r, x, y); /* left */ if (x != 0) { igraph_i_2dgrid_addvertices(grid, eids, vid, r, x - 1, y); } /* right */ if (x != grid->stepsx - 1) { igraph_i_2dgrid_addvertices(grid, eids, vid, r, x + 1, y); } /* up */ if (y != 0) { igraph_i_2dgrid_addvertices(grid, eids, vid, r, x, y - 1); } /* down */ if (y != grid->stepsy - 1) { igraph_i_2dgrid_addvertices(grid, eids, vid, r, x, y + 1); } /* up & left */ if (x != 0 && y != 0) { igraph_i_2dgrid_addvertices(grid, eids, vid, r, x - 1, y - 1); } /* up & right */ if (x != grid->stepsx - 1 && y != 0) { igraph_i_2dgrid_addvertices(grid, eids, vid, r, x + 1, y - 1); } /* down & left */ if (x != 0 && y != grid->stepsy - 1) { igraph_i_2dgrid_addvertices(grid, eids, vid, r, x - 1, y + 1); } /* down & right */ if (x != grid->stepsx - 1 && y != grid->stepsy - 1) { igraph_i_2dgrid_addvertices(grid, eids, vid, r, x - 1, y + 1); } return 0; } void igraph_2dgrid_reset(igraph_2dgrid_t *grid, igraph_2dgrid_iterator_t *it) { /* Search for the first cell containing a vertex */ it->x = 0; it->y = 0; it->vid = (long int) MATRIX(grid->startidx, 0, 0); while ( it->vid == 0 && (it->x < grid->stepsx - 1 || it->y < grid->stepsy - 1)) { it->x += 1; if (it->x == grid->stepsx) { it->x = 0; it->y += 1; } it->vid = (long int) MATRIX(grid->startidx, it->x, it->y); } } igraph_integer_t igraph_2dgrid_next(igraph_2dgrid_t *grid, igraph_2dgrid_iterator_t *it) { long int ret = it->vid; if (ret == 0) { return 0; } /* First neighbor */ it->ncells = -1; if (it->x != grid->stepsx - 1) { it->ncells += 1; it->nx[it->ncells] = it->x + 1; it->ny[it->ncells] = it->y; } if (it->y != grid->stepsy - 1) { it->ncells += 1; it->nx[it->ncells] = it->x; it->ny[it->ncells] = it->y + 1; } if (it->ncells == 1) { it->ncells += 1; it->nx[it->ncells] = it->x + 1; it->ny[it->ncells] = it->y + 1; } it->ncells += 1; it->nx[it->ncells] = it->x; it->ny[it->ncells] = it->y; it->nei = (long int) VECTOR(grid->next) [ ret - 1 ]; while (it->ncells > 0 && it->nei == 0 ) { it->ncells -= 1; it->nei = (long int) MATRIX(grid->startidx, it->nx[it->ncells], it->ny[it->ncells]); } /* Next vertex */ it->vid = (long int) VECTOR(grid->next)[ it->vid - 1 ]; while ( (it->x < grid->stepsx - 1 || it->y < grid->stepsy - 1) && it->vid == 0) { it->x += 1; if (it->x == grid->stepsx) { it->x = 0; it->y += 1; } it->vid = (long int) MATRIX(grid->startidx, it->x, it->y); } return (igraph_integer_t) ret; } igraph_integer_t igraph_2dgrid_next_nei(igraph_2dgrid_t *grid, igraph_2dgrid_iterator_t *it) { long int ret = it->nei; if (it->nei != 0) { it->nei = (long int) VECTOR(grid->next) [ ret - 1 ]; } while (it->ncells > 0 && it->nei == 0 ) { it->ncells -= 1; it->nei = (long int) MATRIX(grid->startidx, it->nx[it->ncells], it->ny[it->ncells]); } return (igraph_integer_t) ret; } /*-----------------------------------------------------------------------*/ int igraph_i_layout_mergegrid_which(igraph_i_layout_mergegrid_t *grid, igraph_real_t xc, igraph_real_t yc, long int *x, long int *y) { if (xc <= grid->minx) { *x = 0; } else if (xc >= grid->maxx) { *x = grid->stepsx - 1; } else { *x = (long int) floor((xc - (grid->minx)) / (grid->deltax)); } if (yc <= grid->miny) { *y = 0; } else if (yc >= grid->maxy) { *y = grid->stepsy - 1; } else { *y = (long int) floor((yc - (grid->miny)) / (grid->deltay)); } return 0; } int igraph_i_layout_mergegrid_init(igraph_i_layout_mergegrid_t *grid, igraph_real_t minx, igraph_real_t maxx, long int stepsx, igraph_real_t miny, igraph_real_t maxy, long int stepsy) { grid->minx = minx; grid->maxx = maxx; grid->stepsx = stepsx; grid->deltax = (maxx - minx) / stepsx; grid->miny = miny; grid->maxy = maxy; grid->stepsy = stepsy; grid->deltay = (maxy - miny) / stepsy; grid->data = igraph_Calloc(stepsx * stepsy, long int); if (grid->data == 0) { IGRAPH_ERROR("Cannot create grid", IGRAPH_ENOMEM); } return 0; } void igraph_i_layout_mergegrid_destroy(igraph_i_layout_mergegrid_t *grid) { igraph_Free(grid->data); } #define MAT(i,j) (grid->data[(grid->stepsy)*(j)+(i)]) #define DIST2(x2,y2) (sqrt(pow(x-(x2),2)+pow(y-(y2), 2))) int igraph_i_layout_merge_place_sphere(igraph_i_layout_mergegrid_t *grid, igraph_real_t x, igraph_real_t y, igraph_real_t r, long int id) { long int cx, cy; long int i, j; igraph_i_layout_mergegrid_which(grid, x, y, &cx, &cy); MAT(cx, cy) = id + 1; #define DIST(i,j) (DIST2(grid->minx+(cx+(i))*grid->deltax, \ grid->miny+(cy+(j))*grid->deltay)) for (i = 0; cx + i < grid->stepsx && DIST(i, 0) < r; i++) { for (j = 0; cy + j < grid->stepsy && DIST(i, j) < r; j++) { MAT(cx + i, cy + j) = id + 1; } } #undef DIST #define DIST(i,j) (DIST2(grid->minx+(cx+(i))*grid->deltax, \ grid->miny+(cy-(j)+1)*grid->deltay)) for (i = 0; cx + i < grid->stepsx && DIST(i, 0) < r; i++) { for (j = 1; cy - j > 0 && DIST(i, j) < r; j++) { MAT(cx + i, cy - j) = id + 1; } } #undef DIST #define DIST(i,j) (DIST2(grid->minx+(cx-(i)+1)*grid->deltax, \ grid->miny+(cy+(j))*grid->deltay)) for (i = 1; cx - i > 0 && DIST(i, 0) < r; i++) { for (j = 0; cy + j < grid->stepsy && DIST(i, j) < r; j++) { MAT(cx - i, cy + j) = id + 1; } } #undef DIST #define DIST(i,j) (DIST2(grid->minx+(cx-(i)+1)*grid->deltax, \ grid->miny+(cy-(j)+1)*grid->deltay)) for (i = 1; cx - i > 0 && DIST(i, 0) < r; i++) { for (j = 1; cy - j > 0 && DIST(i, j) < r; j++) { MAT(cx - i, cy - j) = id + 1; } } #undef DIST #undef DIST2 return 0; } long int igraph_i_layout_mergegrid_get(igraph_i_layout_mergegrid_t *grid, igraph_real_t x, igraph_real_t y) { long int cx, cy; long int res; if (x <= grid->minx || x >= grid->maxx || y <= grid->miny || y >= grid->maxy) { res = -1; } else { igraph_i_layout_mergegrid_which(grid, x, y, &cx, &cy); res = MAT(cx, cy) - 1; } return res; } #define DIST2(x2,y2) (sqrt(pow(x-(x2),2)+pow(y-(y2), 2))) long int igraph_i_layout_mergegrid_get_sphere(igraph_i_layout_mergegrid_t *grid, igraph_real_t x, igraph_real_t y, igraph_real_t r) { long int cx, cy; long int i, j; long int ret; if (x - r <= grid->minx || x + r >= grid->maxx || y - r <= grid->miny || y + r >= grid->maxy) { ret = -1; } else { igraph_i_layout_mergegrid_which(grid, x, y, &cx, &cy); ret = MAT(cx, cy) - 1; #define DIST(i,j) (DIST2(grid->minx+(cx+(i))*grid->deltax, \ grid->miny+(cy+(j))*grid->deltay)) for (i = 0; ret < 0 && cx + i < grid->stepsx && DIST(i, 0) < r; i++) { for (j = 0; ret < 0 && cy + j < grid->stepsy && DIST(i, j) < r; j++) { ret = MAT(cx + i, cy + j) - 1; } } #undef DIST #define DIST(i,j) (DIST2(grid->minx+(cx+(i))*grid->deltax, \ grid->miny+(cy-(j)+1)*grid->deltay)) for (i = 0; ret < 0 && cx + i < grid->stepsx && DIST(i, 0) < r; i++) { for (j = 1; ret < 0 && cy - j > 0 && DIST(i, j) < r; j++) { ret = MAT(cx + i, cy - j) - 1; } } #undef DIST #define DIST(i,j) (DIST2(grid->minx+(cx-(i)+1)*grid->deltax, \ grid->miny+(cy+(j))*grid->deltay)) for (i = 1; ret < 0 && cx - i > 0 && DIST(i, 0) < r; i++) { for (j = 0; ret < 0 && cy + j < grid->stepsy && DIST(i, j) < r; j++) { ret = MAT(cx - i, cy + j) - 1; } } #undef DIST #define DIST(i,j) (DIST2(grid->minx+(cx-(i)+1)*grid->deltax, \ grid->miny+(cy-(j)+1)*grid->deltay)) for (i = 1; ret < 0 && cx + i > 0 && DIST(i, 0) < r; i++) { for (j = 1; ret < 0 && cy + i > 0 && DIST(i, j) < r; j++) { ret = MAT(cx - i, cy - j) - 1; } } #undef DIST } return ret; } /* int print_grid(igraph_i_layout_mergegrid_t *grid) { */ /* long int i,j; */ /* for (i=0; istepsx; i++) { */ /* for (j=0; jstepsy; j++) { */ /* printf("%li ", MAT(i,j)-1); */ /* } */ /* printf("\n"); */ /* } */ /* } */ python-igraph-0.8.0/vendor/source/igraph/src/drl_graph_3d.cpp0000644000076500000240000007071613614300625024445 0ustar tamasstaff00000000000000/* * Copyright 2007 Sandia Corporation. Under the terms of Contract * DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains * certain rights in this software. * * All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are * met: * * * Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * Neither the name of Sandia National Laboratories nor the names of * its contributors may be used to endorse or promote products derived from * this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT * OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED * TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF * LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING * NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. */ // This file contains the member definitions of the master class #include #include #include #include #include #include #include using namespace std; #include "drl_graph_3d.h" #include "igraph_random.h" #include "igraph_interface.h" #include "igraph_progress.h" #include "igraph_interrupt_internal.h" #ifdef MUSE_MPI #include #endif namespace drl3d { graph::graph(const igraph_t *igraph, const igraph_layout_drl_options_t *options, const igraph_vector_t *weights) { myid = 0; num_procs = 1; STAGE = 0; iterations = options->init_iterations; temperature = options->init_temperature; attraction = options->init_attraction; damping_mult = options->init_damping_mult; min_edges = 20; first_add = fine_first_add = true; fineDensity = false; // Brian's original Vx schedule liquid.iterations = options->liquid_iterations; liquid.temperature = options->liquid_temperature; liquid.attraction = options->liquid_attraction; liquid.damping_mult = options->liquid_damping_mult; liquid.time_elapsed = 0; expansion.iterations = options->expansion_iterations; expansion.temperature = options->expansion_temperature; expansion.attraction = options->expansion_attraction; expansion.damping_mult = options->expansion_damping_mult; expansion.time_elapsed = 0; cooldown.iterations = options->cooldown_iterations; cooldown.temperature = options->cooldown_temperature; cooldown.attraction = options->cooldown_attraction; cooldown.damping_mult = options->cooldown_damping_mult; cooldown.time_elapsed = 0; crunch.iterations = options->crunch_iterations; crunch.temperature = options->crunch_temperature; crunch.attraction = options->crunch_attraction; crunch.damping_mult = options->crunch_damping_mult; crunch.time_elapsed = 0; simmer.iterations = options->simmer_iterations; simmer.temperature = options->simmer_temperature; simmer.attraction = options->simmer_attraction; simmer.damping_mult = options->simmer_damping_mult; simmer.time_elapsed = 0; // scan .int file for node info highest_sim = 1.0; num_nodes = igraph_vcount(igraph); long int no_of_edges = igraph_ecount(igraph); for (long int i = 0; i < num_nodes; i++) { id_catalog[i] = 1; } map< int, int>::iterator cat_iter; for ( cat_iter = id_catalog.begin(); cat_iter != id_catalog.end(); cat_iter++) { cat_iter->second = cat_iter->first; } // populate node positions and ids positions.reserve ( num_nodes ); for ( cat_iter = id_catalog.begin(); cat_iter != id_catalog.end(); cat_iter++ ) { positions.push_back ( Node( cat_iter->first ) ); } // read .int file for graph info long int node_1, node_2; double weight; for (long int i = 0; i < no_of_edges; i++) { node_1 = IGRAPH_FROM(igraph, i); node_2 = IGRAPH_TO(igraph, i); weight = weights ? VECTOR(*weights)[i] : 1.0 ; (neighbors[id_catalog[node_1]])[id_catalog[node_2]] = weight; (neighbors[id_catalog[node_2]])[id_catalog[node_1]] = weight; } // initialize density server density_server.Init(); } // init_parms -- this subroutine initializes the edge_cut variables // used in the original VxOrd starting with the edge_cut parameter. // In our version, edge_cut = 0 means no cutting, 1 = maximum cut. // We also set the random seed here. void graph::init_parms ( int rand_seed, float edge_cut, float real_parm ) { IGRAPH_UNUSED(rand_seed); // first we translate edge_cut the former tcl sliding scale //CUT_END = cut_length_end = 39000.0 * (1.0 - edge_cut) + 1000.0; CUT_END = cut_length_end = 40000.0 * (1.0 - edge_cut); // cut_length_end cannot actually be 0 if ( cut_length_end <= 1.0 ) { cut_length_end = 1.0; } float cut_length_start = 4.0 * cut_length_end; // now we set the parameters used by ReCompute cut_off_length = cut_length_start; cut_rate = ( cut_length_start - cut_length_end ) / 400.0; // finally set the number of iterations to leave .real coords fixed int full_comp_iters; full_comp_iters = liquid.iterations + expansion.iterations + cooldown.iterations + crunch.iterations + 3; // adjust real parm to iterations (do not enter simmer halfway) if ( real_parm < 0 ) { real_iterations = (int)real_parm; } else if ( real_parm == 1) { real_iterations = full_comp_iters + simmer.iterations + 100; } else { real_iterations = (int)(real_parm * full_comp_iters); } tot_iterations = 0; if ( real_iterations > 0 ) { real_fixed = true; } else { real_fixed = false; } // calculate total expected iterations (for progress bar display) tot_expected_iterations = liquid.iterations + expansion.iterations + cooldown.iterations + crunch.iterations + simmer.iterations; /* // output edge_cutting parms (for debugging) cout << "Processor " << myid << ": " << "cut_length_end = CUT_END = " << cut_length_end << ", cut_length_start = " << cut_length_start << ", cut_rate = " << cut_rate << endl; */ // set random seed // srand ( rand_seed ); // Don't need this in igraph } void graph::init_parms(const igraph_layout_drl_options_t *options) { double rand_seed = 0.0; double real_in = -1.0; init_parms(rand_seed, options->edge_cut, real_in); } int graph::read_real ( const igraph_matrix_t *real_mat, const igraph_vector_bool_t *fixed) { long int n = igraph_matrix_nrow(real_mat); for (long int i = 0; i < n; i++) { positions[id_catalog[i]].x = MATRIX(*real_mat, i, 0); positions[id_catalog[i]].y = MATRIX(*real_mat, i, 1); positions[id_catalog[i]].z = MATRIX(*real_mat, i, 2); positions[id_catalog[i]].fixed = fixed ? VECTOR(*fixed)[i] : false; if ( real_iterations > 0 ) { density_server.Add ( positions[id_catalog[i]], fineDensity ); } } return 0; } /********************************************* * Function: ReCompute * * Description: Compute the graph locations * * Modified from original code by B. Wylie * ********************************************/ int graph::ReCompute( ) { // carryover from original VxOrd int MIN = 1; /* // output parameters (for debugging) cout << "ReCompute is using the following parameters: "<< endl; cout << "STAGE: " << STAGE << ", iter: " << iterations << ", temp = " << temperature << ", attract = " << attraction << ", damping_mult = " << damping_mult << ", min_edges = " << min_edges << ", cut_off_length = " << cut_off_length << ", fineDensity = " << fineDensity << endl; */ /* igraph progress report */ float progress = (tot_iterations * 100.0 / tot_expected_iterations); switch (STAGE) { case 0: if (iterations == 0) { IGRAPH_PROGRESS("DrL layout (initialization stage)", progress, 0); } else { IGRAPH_PROGRESS("DrL layout (liquid stage)", progress, 0); } break; case 1: IGRAPH_PROGRESS("DrL layout (expansion stage)", progress, 0); break; case 2: IGRAPH_PROGRESS("DrL layout (cooldown and cluster phase)", progress, 0); break; case 3: IGRAPH_PROGRESS("DrL layout (crunch phase)", progress, 0); break; case 5: IGRAPH_PROGRESS("DrL layout (simmer phase)", progress, 0); break; case 6: IGRAPH_PROGRESS("DrL layout (final phase)", 100.0, 0); break; default: IGRAPH_PROGRESS("DrL layout (unknown phase)", 0.0, 0); break; } /* Compute Energies for individual nodes */ update_nodes (); // check to see if we need to free fixed nodes tot_iterations++; if ( tot_iterations >= real_iterations ) { real_fixed = false; } // **************************************** // AUTOMATIC CONTROL SECTION // **************************************** // STAGE 0: LIQUID if (STAGE == 0) { if ( iterations == 0 ) { start_time = time( NULL ); // if ( myid == 0 ) // cout << "Entering liquid stage ..."; } if (iterations < liquid.iterations) { temperature = liquid.temperature; attraction = liquid.attraction; damping_mult = liquid.damping_mult; iterations++; // if ( myid == 0 ) // cout << "." << flush; } else { stop_time = time( NULL ); liquid.time_elapsed = liquid.time_elapsed + (stop_time - start_time); temperature = expansion.temperature; attraction = expansion.attraction; damping_mult = expansion.damping_mult; iterations = 0; // go to next stage STAGE = 1; start_time = time( NULL ); // if ( myid == 0 ) // cout << "Entering expansion stage ..."; } } // STAGE 1: EXPANSION if (STAGE == 1) { if (iterations < expansion.iterations) { // Play with vars if (attraction > 1) { attraction -= .05; } if (min_edges > 12) { min_edges -= .05; } cut_off_length -= cut_rate; if (damping_mult > .1) { damping_mult -= .005; } iterations++; // if ( myid == 0 ) cout << "." << flush; } else { stop_time = time( NULL ); expansion.time_elapsed = expansion.time_elapsed + (stop_time - start_time); min_edges = 12; damping_mult = cooldown.damping_mult; STAGE = 2; attraction = cooldown.attraction; temperature = cooldown.temperature; iterations = 0; start_time = time( NULL ); // if ( myid == 0 ) // cout << "Entering cool-down stage ..."; } } // STAGE 2: Cool down and cluster else if (STAGE == 2) { if (iterations < cooldown.iterations) { // Reduce temperature if (temperature > 50) { temperature -= 10; } // Reduce cut length if (cut_off_length > cut_length_end) { cut_off_length -= cut_rate * 2; } if (min_edges > MIN) { min_edges -= .2; } //min_edges = 99; iterations++; // if ( myid == 0 ) // cout << "." << flush; } else { stop_time = time( NULL ); cooldown.time_elapsed = cooldown.time_elapsed + (stop_time - start_time); cut_off_length = cut_length_end; temperature = crunch.temperature; damping_mult = crunch.damping_mult; min_edges = MIN; //min_edges = 99; // In other words: no more cutting STAGE = 3; iterations = 0; attraction = crunch.attraction; start_time = time( NULL ); // if ( myid == 0 ) // cout << "Entering crunch stage ..."; } } // STAGE 3: Crunch else if (STAGE == 3) { if (iterations < crunch.iterations) { iterations++; // if ( myid == 0 ) cout << "." << flush; } else { stop_time = time( NULL ); crunch.time_elapsed = crunch.time_elapsed + (stop_time - start_time); iterations = 0; temperature = simmer.temperature; attraction = simmer.attraction; damping_mult = simmer.damping_mult; min_edges = 99; fineDensity = true; STAGE = 5; start_time = time( NULL ); // if ( myid == 0 ) // cout << "Entering simmer stage ..."; } } // STAGE 5: Simmer else if ( STAGE == 5 ) { if (iterations < simmer.iterations) { if (temperature > 50) { temperature -= 2; } iterations++; // if ( myid == 0 ) cout << "." << flush; } else { stop_time = time( NULL ); simmer.time_elapsed = simmer.time_elapsed + (stop_time - start_time); STAGE = 6; // if ( myid == 0 ) // cout << "Layout calculation completed in " << // ( liquid.time_elapsed + expansion.time_elapsed + // cooldown.time_elapsed + crunch.time_elapsed + // simmer.time_elapsed ) // << " seconds (not including I/O)." // << endl; } } // STAGE 6: All Done! else if ( STAGE == 6) { /* // output parameters (for debugging) cout << "ReCompute is using the following parameters: "<< endl; cout << "STAGE: " << STAGE << ", iter: " << iterations << ", temp = " << temperature << ", attract = " << attraction << ", damping_mult = " << damping_mult << ", min_edges = " << min_edges << ", cut_off_length = " << cut_off_length << ", fineDensity = " << fineDensity << endl; */ return 0; } // **************************************** // END AUTOMATIC CONTROL SECTION // **************************************** // Still need more recomputation return 1; } // update_nodes -- this function will complete the primary node update // loop in layout's recompute routine. It follows exactly the same // sequence to ensure similarity of parallel layout to the standard layout void graph::update_nodes ( ) { vector node_indices; // node list of nodes currently being updated float old_positions[2 * MAX_PROCS]; // positions before update float new_positions[2 * MAX_PROCS]; // positions after update bool all_fixed; // check if all nodes are fixed // initial node list consists of 0,1,...,num_procs for ( int i = 0; i < num_procs; i++ ) { node_indices.push_back( i ); } // next we calculate the number of nodes there would be if the // num_nodes by num_procs schedule grid were perfectly square int square_num_nodes = (int)(num_procs + num_procs * floor ((float)(num_nodes - 1) / (float)num_procs )); for ( int i = myid; i < square_num_nodes; i += num_procs ) { // get old positions get_positions ( node_indices, old_positions ); // default new position is old position get_positions ( node_indices, new_positions ); if ( i < num_nodes ) { // advance random sequence according to myid for ( int j = 0; j < 2 * myid; j++ ) { RNG_UNIF01(); } // rand(); // calculate node energy possibilities if ( !(positions[i].fixed && real_fixed) ) { update_node_pos ( i, old_positions, new_positions ); } // advance random sequence for next iteration for ( unsigned int j = 2 * myid; j < 2 * (node_indices.size() - 1); j++ ) { RNG_UNIF01(); } // rand(); } else { // advance random sequence according to use by // the other processors for ( unsigned int j = 0; j < 2 * (node_indices.size()); j++ ) { RNG_UNIF01(); } //rand(); } // check if anything was actually updated (e.g. everything was fixed) all_fixed = true; for ( unsigned int j = 0; j < node_indices.size (); j++ ) if ( !(positions [ node_indices[j] ].fixed && real_fixed) ) { all_fixed = false; } // update positions across processors (if not all fixed) if ( !all_fixed ) { #ifdef MUSE_MPI MPI_Allgather ( &new_positions[2 * myid], 2, MPI_FLOAT, new_positions, 2, MPI_FLOAT, MPI_COMM_WORLD ); #endif // update positions (old to new) update_density ( node_indices, old_positions, new_positions ); } /* if ( myid == 0 ) { // output node list (for debugging) for ( unsigned int j = 0; j < node_indices.size(); j++ ) cout << node_indices[j] << " "; cout << endl; } */ // compute node list for next update for ( unsigned int j = 0; j < node_indices.size(); j++ ) { node_indices [j] += num_procs; } while ( !node_indices.empty() && node_indices.back() >= num_nodes ) { node_indices.pop_back ( ); } } // update first_add and fine_first_add first_add = false; if ( fineDensity ) { fine_first_add = false; } } // The get_positions function takes the node_indices list // and returns the corresponding positions in an array. void graph::get_positions ( vector &node_indices, float return_positions[3 * MAX_PROCS] ) { // fill positions for (unsigned int i = 0; i < node_indices.size(); i++) { return_positions[3 * i] = positions[ node_indices[i] ].x; return_positions[3 * i + 1] = positions[ node_indices[i] ].y; return_positions[3 * i + 2] = positions[ node_indices[i] ].z; } } // update_node_pos -- this subroutine does the actual work of computing // the new position of a given node. num_act_proc gives the number // of active processes at this level for use by the random number // generators. void graph::update_node_pos ( int node_ind, float old_positions[3 * MAX_PROCS], float new_positions[3 * MAX_PROCS] ) { float energies[2]; // node energies for possible positions float updated_pos[2][3]; // possible positions float pos_x, pos_y, pos_z; // old VxOrd parameter float jump_length = .010 * temperature; // subtract old node density_server.Subtract ( positions[node_ind], first_add, fine_first_add, fineDensity ); // compute node energy for old solution energies[0] = Compute_Node_Energy ( node_ind ); // move node to centroid position Solve_Analytic ( node_ind, pos_x, pos_y, pos_z ); positions[node_ind].x = updated_pos[0][0] = pos_x; positions[node_ind].y = updated_pos[0][1] = pos_y; positions[node_ind].z = updated_pos[0][2] = pos_z; /* // ouput random numbers (for debugging) int rand_0, rand_1; rand_0 = rand(); rand_1 = rand(); cout << myid << ": " << rand_0 << ", " << rand_1 << endl; */ // Do random method (RAND_MAX is C++ maximum random number) updated_pos[1][0] = updated_pos[0][0] + (.5 - RNG_UNIF01()) * jump_length; updated_pos[1][1] = updated_pos[0][1] + (.5 - RNG_UNIF01()) * jump_length; updated_pos[1][2] = updated_pos[0][2] + (.5 - RNG_UNIF01()) * jump_length; // compute node energy for random position positions[node_ind].x = updated_pos[1][0]; positions[node_ind].y = updated_pos[1][1]; positions[node_ind].z = updated_pos[1][2]; energies[1] = Compute_Node_Energy ( node_ind ); /* // output update possiblities (debugging): cout << node_ind << ": (" << updated_pos[0][0] << "," << updated_pos[0][1] << "), " << energies[0] << "; (" << updated_pos[1][0] << "," << updated_pos[1][1] << "), " << energies[1] << endl; */ // add back old position positions[node_ind].x = old_positions[3 * myid]; positions[node_ind].y = old_positions[3 * myid + 1]; positions[node_ind].z = old_positions[3 * myid + 2]; if ( !fineDensity && !first_add ) { density_server.Add ( positions[node_ind], fineDensity ); } else if ( !fine_first_add ) { density_server.Add ( positions[node_ind], fineDensity ); } // choose updated node position with lowest energy if ( energies[0] < energies[1] ) { new_positions[3 * myid] = updated_pos[0][0]; new_positions[3 * myid + 1] = updated_pos[0][1]; new_positions[3 * myid + 2] = updated_pos[0][2]; positions[node_ind].energy = energies[0]; } else { new_positions[3 * myid] = updated_pos[1][0]; new_positions[3 * myid + 1] = updated_pos[1][1]; new_positions[3 * myid + 2] = updated_pos[1][2]; positions[node_ind].energy = energies[1]; } } // update_density takes a sequence of node_indices and their positions and // updates the positions by subtracting the old positions and adding the // new positions to the density grid. void graph::update_density ( vector &node_indices, float old_positions[3 * MAX_PROCS], float new_positions[3 * MAX_PROCS] ) { // go through each node and subtract old position from // density grid before adding new position for ( unsigned int i = 0; i < node_indices.size(); i++ ) { positions[node_indices[i]].x = old_positions[3 * i]; positions[node_indices[i]].y = old_positions[3 * i + 1]; positions[node_indices[i]].z = old_positions[3 * i + 2]; density_server.Subtract ( positions[node_indices[i]], first_add, fine_first_add, fineDensity ); positions[node_indices[i]].x = new_positions[3 * i]; positions[node_indices[i]].y = new_positions[3 * i + 1]; positions[node_indices[i]].z = new_positions[3 * i + 2]; density_server.Add ( positions[node_indices[i]], fineDensity ); } } /******************************************** * Function: Compute_Node_Energy * * Description: Compute the node energy * * This code has been modified from the * * original code by B. Wylie. * *********************************************/ float graph::Compute_Node_Energy( int node_ind ) { /* Want to expand 4th power range of attraction */ float attraction_factor = attraction * attraction * attraction * attraction * 2e-2; map ::iterator EI; float x_dis, y_dis, z_dis; float energy_distance, weight; float node_energy = 0; // Add up all connection energies for (EI = neighbors[node_ind].begin(); EI != neighbors[node_ind].end(); ++EI) { // Get edge weight weight = EI->second; // Compute x,y distance x_dis = positions[ node_ind ].x - positions[ EI->first ].x; y_dis = positions[ node_ind ].y - positions[ EI->first ].y; z_dis = positions[ node_ind ].z - positions[ EI->first ].z; // Energy Distance energy_distance = x_dis * x_dis + y_dis * y_dis + z_dis * z_dis; if (STAGE < 2) { energy_distance *= energy_distance; } // In the liquid phase we want to discourage long link distances if (STAGE == 0) { energy_distance *= energy_distance; } node_energy += weight * attraction_factor * energy_distance; } // output effect of density (debugging) //cout << "[before: " << node_energy; // add density node_energy += density_server.GetDensity ( positions[ node_ind ].x, positions[ node_ind ].y, positions[ node_ind ].z, fineDensity ); // after calling density server (debugging) //cout << ", after: " << node_energy << "]" << endl; // return computated energy return node_energy; } /********************************************* * Function: Solve_Analytic * * Description: Compute the node position * * This is a modified version of the function * * originally written by B. Wylie * *********************************************/ void graph::Solve_Analytic( int node_ind, float &pos_x, float &pos_y, float &pos_z) { map ::iterator EI; float total_weight = 0; float x_dis, y_dis, z_dis, x_cen = 0, y_cen = 0, z_cen = 0; float x = 0, y = 0, z = 0, dis; float damping, weight; // Sum up all connections for (EI = neighbors[node_ind].begin(); EI != neighbors[node_ind].end(); ++EI) { weight = EI->second; total_weight += weight; x += weight * positions[ EI->first ].x; y += weight * positions[ EI->first ].y; z += weight * positions[ EI->first ].z; } // Now set node position if (total_weight > 0) { // Compute centriod x_cen = x / total_weight; y_cen = y / total_weight; z_cen = z / total_weight; damping = 1.0 - damping_mult; pos_x = damping * positions[ node_ind ].x + (1.0 - damping) * x_cen; pos_y = damping * positions[ node_ind ].y + (1.0 - damping) * y_cen; pos_z = damping * positions[ node_ind ].z + (1.0 - damping) * z_cen; } // No cut edge flag (?) if (min_edges == 99) { return; } // Don't cut at end of scale if ( CUT_END >= 39500 ) { return; } float num_connections = (float)sqrt((float)neighbors[node_ind].size()); float maxLength = 0; map::iterator maxIndex; // Go through nodes edges... cutting if necessary for (EI = maxIndex = neighbors[node_ind].begin(); EI != neighbors[node_ind].end(); ++EI) { // Check for at least min edges if (neighbors[node_ind].size() < min_edges) { continue; } x_dis = x_cen - positions[ EI->first ].x; y_dis = y_cen - positions[ EI->first ].y; z_dis = z_cen - positions[ EI->first ].z; dis = x_dis * x_dis + y_dis * y_dis + z_dis * z_dis; dis *= num_connections; // Store maximum edge if (dis > maxLength) { maxLength = dis; maxIndex = EI; } } // If max length greater than cut_length then cut if (maxLength > cut_off_length) { neighbors[ node_ind ].erase( maxIndex ); } } // get_tot_energy adds up the energy for each node to give an estimate of the // quality of the minimization. float graph::get_tot_energy ( ) { float my_tot_energy, tot_energy; my_tot_energy = 0; for ( int i = myid; i < num_nodes; i += num_procs ) { my_tot_energy += positions[i].energy; } //vector::iterator i; //for ( i = positions.begin(); i != positions.end(); i++ ) // tot_energy += i->energy; #ifdef MUSE_MPI MPI_Reduce ( &my_tot_energy, &tot_energy, 1, MPI_FLOAT, MPI_SUM, 0, MPI_COMM_WORLD ); #else tot_energy = my_tot_energy; #endif return tot_energy; } int graph::draw_graph(igraph_matrix_t *res) { int count_iter = 0; while (ReCompute()) { IGRAPH_ALLOW_INTERRUPTION(); count_iter++; } long int n = positions.size(); IGRAPH_CHECK(igraph_matrix_resize(res, n, 3)); for (long int i = 0; i < n; i++) { MATRIX(*res, i, 0) = positions[i].x; MATRIX(*res, i, 1) = positions[i].y; MATRIX(*res, i, 2) = positions[i].z; } return 0; } } // namespace drl3d python-igraph-0.8.0/vendor/source/igraph/src/paths.c0000644000076500000240000001414013614300625022661 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2014 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_interface.h" #include "igraph_interrupt_internal.h" #include "igraph_vector_ptr.h" #include "igraph_iterators.h" #include "igraph_adjlist.h" #include "igraph_stack.h" /** * \function igraph_get_all_simple_paths * List all simple paths from one source * * A path is simple, if its vertices are unique, no vertex * is visited more than once. * * * Note that potentially there are exponentially many * paths between two vertices of a graph, and you may * run out of memory when using this function, if your * graph is lattice-like. * * * This function currently ignored multiple and loop edges. * \param graph The input graph. * \param res Initialized integer vector, all paths are * returned here, separated by -1 markers. The paths * are included in arbitrary order, as they are found. * \param from The start vertex. * \param to The target vertices. * \param cutoff Maximum length of path that is considered. If * negative, paths of all lengths are considered. * \param mode The type of the paths to consider, it is ignored * for undirected graphs. * \return Error code. * * Time complexity: O(n!) in the worst case, n is the number of * vertices. */ int igraph_get_all_simple_paths(const igraph_t *graph, igraph_vector_int_t *res, igraph_integer_t from, const igraph_vs_t to, igraph_integer_t cutoff, igraph_neimode_t mode) { igraph_integer_t no_nodes = igraph_vcount(graph); igraph_vit_t vit; igraph_bool_t toall = igraph_vs_is_all(&to); igraph_vector_char_t markto; igraph_lazy_adjlist_t adjlist; igraph_vector_int_t stack, dist; igraph_vector_char_t added; igraph_vector_int_t nptr; int iteration; if (from < 0 || from >= no_nodes) { IGRAPH_ERROR("Invalid starting vertex", IGRAPH_EINVAL); } if (!toall) { igraph_vector_char_init(&markto, no_nodes); IGRAPH_FINALLY(igraph_vector_char_destroy, &markto); IGRAPH_CHECK(igraph_vit_create(graph, to, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); for (; !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit)) { VECTOR(markto)[ IGRAPH_VIT_GET(vit) ] = 1; } igraph_vit_destroy(&vit); IGRAPH_FINALLY_CLEAN(1); } IGRAPH_CHECK(igraph_vector_char_init(&added, no_nodes)); IGRAPH_FINALLY(igraph_vector_char_destroy, &added); IGRAPH_CHECK(igraph_vector_int_init(&stack, 100)); IGRAPH_FINALLY(igraph_vector_int_destroy, &stack); IGRAPH_CHECK(igraph_vector_int_init(&dist, 100)); IGRAPH_FINALLY(igraph_vector_int_destroy, &dist); IGRAPH_CHECK(igraph_lazy_adjlist_init(graph, &adjlist, mode, /*simplify=*/ 1)); IGRAPH_FINALLY(igraph_lazy_adjlist_destroy, &adjlist); IGRAPH_CHECK(igraph_vector_int_init(&nptr, no_nodes)); IGRAPH_FINALLY(igraph_vector_int_destroy, &nptr); igraph_vector_int_clear(res); igraph_vector_int_clear(&stack); igraph_vector_int_clear(&dist); igraph_vector_int_push_back(&stack, from); igraph_vector_int_push_back(&dist, 0); VECTOR(added)[from] = 1; while (!igraph_vector_int_empty(&stack)) { int act = igraph_vector_int_tail(&stack); int curdist = igraph_vector_int_tail(&dist); igraph_vector_t *neis = igraph_lazy_adjlist_get(&adjlist, act); int n = igraph_vector_size(neis); int *ptr = igraph_vector_int_e_ptr(&nptr, act); igraph_bool_t any; igraph_bool_t within_dist; int nei; if (iteration == 0) { IGRAPH_ALLOW_INTERRUPTION(); } within_dist = (curdist < cutoff || cutoff < 0); if (within_dist) { /* Search for a neighbor that was not yet visited */ any = 0; while (!any && (*ptr) < n) { nei = (int) VECTOR(*neis)[(*ptr)]; any = !VECTOR(added)[nei]; (*ptr) ++; } } if (within_dist && any) { /* There is such a neighbor, add it */ IGRAPH_CHECK(igraph_vector_int_push_back(&stack, nei)); IGRAPH_CHECK(igraph_vector_int_push_back(&dist, curdist + 1)); VECTOR(added)[nei] = 1; /* Add to results */ if (toall || VECTOR(markto)[nei]) { IGRAPH_CHECK(igraph_vector_int_append(res, &stack)); IGRAPH_CHECK(igraph_vector_int_push_back(res, -1)); } } else { /* There is no such neighbor, finished with the subtree */ int up = igraph_vector_int_pop_back(&stack); igraph_vector_int_pop_back(&dist); VECTOR(added)[up] = 0; VECTOR(nptr)[up] = 0; } iteration++; if (iteration >= 10000) { iteration = 0; } } igraph_vector_int_destroy(&nptr); igraph_lazy_adjlist_destroy(&adjlist); igraph_vector_int_destroy(&dist); igraph_vector_int_destroy(&stack); igraph_vector_char_destroy(&added); IGRAPH_FINALLY_CLEAN(5); if (!toall) { igraph_vector_char_destroy(&markto); IGRAPH_FINALLY_CLEAN(1); } return 0; } python-igraph-0.8.0/vendor/source/igraph/src/igraph_marked_queue.c0000644000076500000240000000651513614300625025552 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_marked_queue.h" #define BATCH_MARKER -1 int igraph_marked_queue_init(igraph_marked_queue_t *q, long int size) { IGRAPH_CHECK(igraph_dqueue_init(&q->Q, 0)); IGRAPH_FINALLY(igraph_dqueue_destroy, &q->Q); IGRAPH_CHECK(igraph_vector_long_init(&q->set, size)); q->mark = 1; q->size = 0; IGRAPH_FINALLY_CLEAN(1); return 0; } void igraph_marked_queue_destroy(igraph_marked_queue_t *q) { igraph_vector_long_destroy(&q->set); igraph_dqueue_destroy(&q->Q); } void igraph_marked_queue_reset(igraph_marked_queue_t *q) { igraph_dqueue_clear(&q->Q); q->size = 0; q->mark += 1; if (q->mark == 0) { igraph_vector_long_null(&q->set); q->mark += 1; } } igraph_bool_t igraph_marked_queue_empty(const igraph_marked_queue_t *q) { return q->size == 0; } long int igraph_marked_queue_size(const igraph_marked_queue_t *q) { return q->size; } igraph_bool_t igraph_marked_queue_iselement(const igraph_marked_queue_t *q, long int elem) { return (VECTOR(q->set)[elem] == q->mark); } int igraph_marked_queue_push(igraph_marked_queue_t *q, long int elem) { if (VECTOR(q->set)[elem] != q->mark) { IGRAPH_CHECK(igraph_dqueue_push(&q->Q, elem)); VECTOR(q->set)[elem] = q->mark; q->size += 1; } return 0; } int igraph_marked_queue_start_batch(igraph_marked_queue_t *q) { IGRAPH_CHECK(igraph_dqueue_push(&q->Q, BATCH_MARKER)); return 0; } void igraph_marked_queue_pop_back_batch(igraph_marked_queue_t *q) { long int size = igraph_dqueue_size(&q->Q); long int elem; while (size > 0 && (elem = (long int) igraph_dqueue_pop_back(&q->Q)) != BATCH_MARKER) { VECTOR(q->set)[elem] = 0; size--; q->size--; } } #ifndef USING_R int igraph_marked_queue_print(const igraph_marked_queue_t *q) { IGRAPH_CHECK(igraph_dqueue_print(&q->Q)); return 0; } #endif int igraph_marked_queue_fprint(const igraph_marked_queue_t *q, FILE *file) { IGRAPH_CHECK(igraph_dqueue_fprint(&q->Q, file)); return 0; } int igraph_marked_queue_as_vector(const igraph_marked_queue_t *q, igraph_vector_t *vec) { long int i, p, n = igraph_dqueue_size(&q->Q); IGRAPH_CHECK(igraph_vector_resize(vec, q->size)); for (i = 0, p = 0; i < n; i++) { igraph_real_t e = igraph_dqueue_e(&q->Q, i); if (e != BATCH_MARKER) { VECTOR(*vec)[p++] = e; } } return 0; } python-igraph-0.8.0/vendor/source/igraph/src/DensityGrid.h0000644000076500000240000000535013614300625023777 0ustar tamasstaff00000000000000/* * Copyright 2007 Sandia Corporation. Under the terms of Contract * DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains * certain rights in this software. * * All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are * met: * * * Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * Neither the name of Sandia National Laboratories nor the names of * its contributors may be used to endorse or promote products derived from * this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT * OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED * TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF * LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING * NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. */ #ifndef __DENSITY_GRID_H__ #define __DENSITY_GRID_H__ // Compile time adjustable parameters #include using namespace std; #include "drl_layout.h" #include "drl_Node.h" #ifdef MUSE_MPI #include #endif namespace drl { class DensityGrid { public: // Methods void Init(); void Subtract(Node &n, bool first_add, bool fine_first_add, bool fineDensity); void Add(Node &n, bool fineDensity ); float GetDensity(float Nx, float Ny, bool fineDensity); // Contructor/Destructor DensityGrid() {}; ~DensityGrid(); private: // Private Members void Subtract( Node &N ); void Add( Node &N ); void fineSubtract( Node &N ); void fineAdd( Node &N ); // new dynamic variables -- SBM float (*fall_off)[RADIUS * 2 + 1]; float (*Density)[GRID_SIZE]; deque* Bins; // old static variables //float fall_off[RADIUS*2+1][RADIUS*2+1]; //float Density[GRID_SIZE][GRID_SIZE]; //deque Bins[GRID_SIZE][GRID_SIZE]; }; } // namespace drl #endif // __DENSITY_GRID_H__ python-igraph-0.8.0/vendor/source/igraph/src/lapack/0000755000076500000240000000000013617375001022634 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/src/lapack/dsortc.c0000644000076500000240000002161413524616145024306 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* ----------------------------------------------------------------------- \BeginDoc \Name: dsortc \Description: Sorts the complex array in XREAL and XIMAG into the order specified by WHICH and optionally applies the permutation to the real array Y. It is assumed that if an element of XIMAG is nonzero, then its negative is also an element. In other words, both members of a complex conjugate pair are to be sorted and the pairs are kept adjacent to each other. \Usage: call dsortc ( WHICH, APPLY, N, XREAL, XIMAG, Y ) \Arguments WHICH Character*2. (Input) 'LM' -> sort XREAL,XIMAG into increasing order of magnitude. 'SM' -> sort XREAL,XIMAG into decreasing order of magnitude. 'LR' -> sort XREAL into increasing order of algebraic. 'SR' -> sort XREAL into decreasing order of algebraic. 'LI' -> sort XIMAG into increasing order of magnitude. 'SI' -> sort XIMAG into decreasing order of magnitude. NOTE: If an element of XIMAG is non-zero, then its negative is also an element. APPLY Logical. (Input) APPLY = .TRUE. -> apply the sorted order to array Y. APPLY = .FALSE. -> do not apply the sorted order to array Y. N Integer. (INPUT) Size of the arrays. XREAL, Double precision array of length N. (INPUT/OUTPUT) XIMAG Real and imaginary part of the array to be sorted. Y Double precision array of length N. (INPUT/OUTPUT) \EndDoc ----------------------------------------------------------------------- \BeginLib \Author Danny Sorensen Phuong Vu Richard Lehoucq CRPC / Rice University Dept. of Computational & Houston, Texas Applied Mathematics Rice University Houston, Texas \Revision history: xx/xx/92: Version ' 2.1' Adapted from the sort routine in LANSO. \SCCS Information: @(#) FILE: sortc.F SID: 2.3 DATE OF SID: 4/20/96 RELEASE: 2 \EndLib ----------------------------------------------------------------------- Subroutine */ int igraphdsortc_(char *which, logical *apply, integer *n, doublereal *xreal, doublereal *ximag, doublereal *y) { /* System generated locals */ integer i__1; doublereal d__1, d__2; /* Builtin functions */ integer s_cmp(char *, char *, ftnlen, ftnlen); /* Local variables */ integer i__, j, igap; doublereal temp, temp1, temp2; extern doublereal igraphdlapy2_(doublereal *, doublereal *); /* %------------------% | Scalar Arguments | %------------------% %-----------------% | Array Arguments | %-----------------% %---------------% | Local Scalars | %---------------% %--------------------% | External Functions | %--------------------% %-----------------------% | Executable Statements | %-----------------------% */ igap = *n / 2; if (s_cmp(which, "LM", (ftnlen)2, (ftnlen)2) == 0) { /* %------------------------------------------------------% | Sort XREAL,XIMAG into increasing order of magnitude. | %------------------------------------------------------% */ L10: if (igap == 0) { goto L9000; } i__1 = *n - 1; for (i__ = igap; i__ <= i__1; ++i__) { j = i__ - igap; L20: if (j < 0) { goto L30; } temp1 = igraphdlapy2_(&xreal[j], &ximag[j]); temp2 = igraphdlapy2_(&xreal[j + igap], &ximag[j + igap]); if (temp1 > temp2) { temp = xreal[j]; xreal[j] = xreal[j + igap]; xreal[j + igap] = temp; temp = ximag[j]; ximag[j] = ximag[j + igap]; ximag[j + igap] = temp; if (*apply) { temp = y[j]; y[j] = y[j + igap]; y[j + igap] = temp; } } else { goto L30; } j -= igap; goto L20; L30: ; } igap /= 2; goto L10; } else if (s_cmp(which, "SM", (ftnlen)2, (ftnlen)2) == 0) { /* %------------------------------------------------------% | Sort XREAL,XIMAG into decreasing order of magnitude. | %------------------------------------------------------% */ L40: if (igap == 0) { goto L9000; } i__1 = *n - 1; for (i__ = igap; i__ <= i__1; ++i__) { j = i__ - igap; L50: if (j < 0) { goto L60; } temp1 = igraphdlapy2_(&xreal[j], &ximag[j]); temp2 = igraphdlapy2_(&xreal[j + igap], &ximag[j + igap]); if (temp1 < temp2) { temp = xreal[j]; xreal[j] = xreal[j + igap]; xreal[j + igap] = temp; temp = ximag[j]; ximag[j] = ximag[j + igap]; ximag[j + igap] = temp; if (*apply) { temp = y[j]; y[j] = y[j + igap]; y[j + igap] = temp; } } else { goto L60; } j -= igap; goto L50; L60: ; } igap /= 2; goto L40; } else if (s_cmp(which, "LR", (ftnlen)2, (ftnlen)2) == 0) { /* %------------------------------------------------% | Sort XREAL into increasing order of algebraic. | %------------------------------------------------% */ L70: if (igap == 0) { goto L9000; } i__1 = *n - 1; for (i__ = igap; i__ <= i__1; ++i__) { j = i__ - igap; L80: if (j < 0) { goto L90; } if (xreal[j] > xreal[j + igap]) { temp = xreal[j]; xreal[j] = xreal[j + igap]; xreal[j + igap] = temp; temp = ximag[j]; ximag[j] = ximag[j + igap]; ximag[j + igap] = temp; if (*apply) { temp = y[j]; y[j] = y[j + igap]; y[j + igap] = temp; } } else { goto L90; } j -= igap; goto L80; L90: ; } igap /= 2; goto L70; } else if (s_cmp(which, "SR", (ftnlen)2, (ftnlen)2) == 0) { /* %------------------------------------------------% | Sort XREAL into decreasing order of algebraic. | %------------------------------------------------% */ L100: if (igap == 0) { goto L9000; } i__1 = *n - 1; for (i__ = igap; i__ <= i__1; ++i__) { j = i__ - igap; L110: if (j < 0) { goto L120; } if (xreal[j] < xreal[j + igap]) { temp = xreal[j]; xreal[j] = xreal[j + igap]; xreal[j + igap] = temp; temp = ximag[j]; ximag[j] = ximag[j + igap]; ximag[j + igap] = temp; if (*apply) { temp = y[j]; y[j] = y[j + igap]; y[j + igap] = temp; } } else { goto L120; } j -= igap; goto L110; L120: ; } igap /= 2; goto L100; } else if (s_cmp(which, "LI", (ftnlen)2, (ftnlen)2) == 0) { /* %------------------------------------------------% | Sort XIMAG into increasing order of magnitude. | %------------------------------------------------% */ L130: if (igap == 0) { goto L9000; } i__1 = *n - 1; for (i__ = igap; i__ <= i__1; ++i__) { j = i__ - igap; L140: if (j < 0) { goto L150; } if ((d__1 = ximag[j], abs(d__1)) > (d__2 = ximag[j + igap], abs( d__2))) { temp = xreal[j]; xreal[j] = xreal[j + igap]; xreal[j + igap] = temp; temp = ximag[j]; ximag[j] = ximag[j + igap]; ximag[j + igap] = temp; if (*apply) { temp = y[j]; y[j] = y[j + igap]; y[j + igap] = temp; } } else { goto L150; } j -= igap; goto L140; L150: ; } igap /= 2; goto L130; } else if (s_cmp(which, "SI", (ftnlen)2, (ftnlen)2) == 0) { /* %------------------------------------------------% | Sort XIMAG into decreasing order of magnitude. | %------------------------------------------------% */ L160: if (igap == 0) { goto L9000; } i__1 = *n - 1; for (i__ = igap; i__ <= i__1; ++i__) { j = i__ - igap; L170: if (j < 0) { goto L180; } if ((d__1 = ximag[j], abs(d__1)) < (d__2 = ximag[j + igap], abs( d__2))) { temp = xreal[j]; xreal[j] = xreal[j + igap]; xreal[j + igap] = temp; temp = ximag[j]; ximag[j] = ximag[j + igap]; ximag[j + igap] = temp; if (*apply) { temp = y[j]; y[j] = y[j + igap]; y[j + igap] = temp; } } else { goto L180; } j -= igap; goto L170; L180: ; } igap /= 2; goto L160; } L9000: return 0; /* %---------------% | End of dsortc | %---------------% */ } /* igraphdsortc_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlaln2.c0000644000076500000240000004544713524616145024176 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLALN2 solves a 1-by-1 or 2-by-2 linear system of equations of the specified form. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLALN2 + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLALN2( LTRANS, NA, NW, SMIN, CA, A, LDA, D1, D2, B, LDB, WR, WI, X, LDX, SCALE, XNORM, INFO ) LOGICAL LTRANS INTEGER INFO, LDA, LDB, LDX, NA, NW DOUBLE PRECISION CA, D1, D2, SCALE, SMIN, WI, WR, XNORM DOUBLE PRECISION A( LDA, * ), B( LDB, * ), X( LDX, * ) > \par Purpose: ============= > > \verbatim > > DLALN2 solves a system of the form (ca A - w D ) X = s B > or (ca A**T - w D) X = s B with possible scaling ("s") and > perturbation of A. (A**T means A-transpose.) > > A is an NA x NA real matrix, ca is a real scalar, D is an NA x NA > real diagonal matrix, w is a real or complex value, and X and B are > NA x 1 matrices -- real if w is real, complex if w is complex. NA > may be 1 or 2. > > If w is complex, X and B are represented as NA x 2 matrices, > the first column of each being the real part and the second > being the imaginary part. > > "s" is a scaling factor (.LE. 1), computed by DLALN2, which is > so chosen that X can be computed without overflow. X is further > scaled if necessary to assure that norm(ca A - w D)*norm(X) is less > than overflow. > > If both singular values of (ca A - w D) are less than SMIN, > SMIN*identity will be used instead of (ca A - w D). If only one > singular value is less than SMIN, one element of (ca A - w D) will be > perturbed enough to make the smallest singular value roughly SMIN. > If both singular values are at least SMIN, (ca A - w D) will not be > perturbed. In any case, the perturbation will be at most some small > multiple of max( SMIN, ulp*norm(ca A - w D) ). The singular values > are computed by infinity-norm approximations, and thus will only be > correct to a factor of 2 or so. > > Note: all input quantities are assumed to be smaller than overflow > by a reasonable factor. (See BIGNUM.) > \endverbatim Arguments: ========== > \param[in] LTRANS > \verbatim > LTRANS is LOGICAL > =.TRUE.: A-transpose will be used. > =.FALSE.: A will be used (not transposed.) > \endverbatim > > \param[in] NA > \verbatim > NA is INTEGER > The size of the matrix A. It may (only) be 1 or 2. > \endverbatim > > \param[in] NW > \verbatim > NW is INTEGER > 1 if "w" is real, 2 if "w" is complex. It may only be 1 > or 2. > \endverbatim > > \param[in] SMIN > \verbatim > SMIN is DOUBLE PRECISION > The desired lower bound on the singular values of A. This > should be a safe distance away from underflow or overflow, > say, between (underflow/machine precision) and (machine > precision * overflow ). (See BIGNUM and ULP.) > \endverbatim > > \param[in] CA > \verbatim > CA is DOUBLE PRECISION > The coefficient c, which A is multiplied by. > \endverbatim > > \param[in] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,NA) > The NA x NA matrix A. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of A. It must be at least NA. > \endverbatim > > \param[in] D1 > \verbatim > D1 is DOUBLE PRECISION > The 1,1 element in the diagonal matrix D. > \endverbatim > > \param[in] D2 > \verbatim > D2 is DOUBLE PRECISION > The 2,2 element in the diagonal matrix D. Not used if NW=1. > \endverbatim > > \param[in] B > \verbatim > B is DOUBLE PRECISION array, dimension (LDB,NW) > The NA x NW matrix B (right-hand side). If NW=2 ("w" is > complex), column 1 contains the real part of B and column 2 > contains the imaginary part. > \endverbatim > > \param[in] LDB > \verbatim > LDB is INTEGER > The leading dimension of B. It must be at least NA. > \endverbatim > > \param[in] WR > \verbatim > WR is DOUBLE PRECISION > The real part of the scalar "w". > \endverbatim > > \param[in] WI > \verbatim > WI is DOUBLE PRECISION > The imaginary part of the scalar "w". Not used if NW=1. > \endverbatim > > \param[out] X > \verbatim > X is DOUBLE PRECISION array, dimension (LDX,NW) > The NA x NW matrix X (unknowns), as computed by DLALN2. > If NW=2 ("w" is complex), on exit, column 1 will contain > the real part of X and column 2 will contain the imaginary > part. > \endverbatim > > \param[in] LDX > \verbatim > LDX is INTEGER > The leading dimension of X. It must be at least NA. > \endverbatim > > \param[out] SCALE > \verbatim > SCALE is DOUBLE PRECISION > The scale factor that B must be multiplied by to insure > that overflow does not occur when computing X. Thus, > (ca A - w D) X will be SCALE*B, not B (ignoring > perturbations of A.) It will be at most 1. > \endverbatim > > \param[out] XNORM > \verbatim > XNORM is DOUBLE PRECISION > The infinity-norm of X, when X is regarded as an NA x NW > real matrix. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > An error flag. It will be set to zero if no error occurs, > a negative number if an argument is in error, or a positive > number if ca A - w D had to be perturbed. > The possible values are: > = 0: No error occurred, and (ca A - w D) did not have to be > perturbed. > = 1: (ca A - w D) had to be perturbed to make its smallest > (or only) singular value greater than SMIN. > NOTE: In the interests of speed, this routine does not > check the inputs for errors. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleOTHERauxiliary ===================================================================== Subroutine */ int igraphdlaln2_(logical *ltrans, integer *na, integer *nw, doublereal *smin, doublereal *ca, doublereal *a, integer *lda, doublereal *d1, doublereal *d2, doublereal *b, integer *ldb, doublereal *wr, doublereal *wi, doublereal *x, integer *ldx, doublereal *scale, doublereal *xnorm, integer *info) { /* Initialized data */ static logical zswap[4] = { FALSE_,FALSE_,TRUE_,TRUE_ }; static logical rswap[4] = { FALSE_,TRUE_,FALSE_,TRUE_ }; static integer ipivot[16] /* was [4][4] */ = { 1,2,3,4,2,1,4,3,3,4,1,2, 4,3,2,1 }; /* System generated locals */ integer a_dim1, a_offset, b_dim1, b_offset, x_dim1, x_offset; doublereal d__1, d__2, d__3, d__4, d__5, d__6; IGRAPH_F77_SAVE doublereal equiv_0[4], equiv_1[4]; /* Local variables */ integer j; #define ci (equiv_0) #define cr (equiv_1) doublereal bi1, bi2, br1, br2, xi1, xi2, xr1, xr2, ci21, ci22, cr21, cr22, li21, csi, ui11, lr21, ui12, ui22; #define civ (equiv_0) doublereal csr, ur11, ur12, ur22; #define crv (equiv_1) doublereal bbnd, cmax, ui11r, ui12s, temp, ur11r, ur12s, u22abs; integer icmax; doublereal bnorm, cnorm, smini; extern doublereal igraphdlamch_(char *); extern /* Subroutine */ int igraphdladiv_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *); doublereal bignum, smlnum; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; b_dim1 = *ldb; b_offset = 1 + b_dim1; b -= b_offset; x_dim1 = *ldx; x_offset = 1 + x_dim1; x -= x_offset; /* Function Body Compute BIGNUM */ smlnum = 2. * igraphdlamch_("Safe minimum"); bignum = 1. / smlnum; smini = max(*smin,smlnum); /* Don't check for input errors */ *info = 0; /* Standard Initializations */ *scale = 1.; if (*na == 1) { /* 1 x 1 (i.e., scalar) system C X = B */ if (*nw == 1) { /* Real 1x1 system. C = ca A - w D */ csr = *ca * a[a_dim1 + 1] - *wr * *d1; cnorm = abs(csr); /* If | C | < SMINI, use C = SMINI */ if (cnorm < smini) { csr = smini; cnorm = smini; *info = 1; } /* Check scaling for X = B / C */ bnorm = (d__1 = b[b_dim1 + 1], abs(d__1)); if (cnorm < 1. && bnorm > 1.) { if (bnorm > bignum * cnorm) { *scale = 1. / bnorm; } } /* Compute X */ x[x_dim1 + 1] = b[b_dim1 + 1] * *scale / csr; *xnorm = (d__1 = x[x_dim1 + 1], abs(d__1)); } else { /* Complex 1x1 system (w is complex) C = ca A - w D */ csr = *ca * a[a_dim1 + 1] - *wr * *d1; csi = -(*wi) * *d1; cnorm = abs(csr) + abs(csi); /* If | C | < SMINI, use C = SMINI */ if (cnorm < smini) { csr = smini; csi = 0.; cnorm = smini; *info = 1; } /* Check scaling for X = B / C */ bnorm = (d__1 = b[b_dim1 + 1], abs(d__1)) + (d__2 = b[(b_dim1 << 1) + 1], abs(d__2)); if (cnorm < 1. && bnorm > 1.) { if (bnorm > bignum * cnorm) { *scale = 1. / bnorm; } } /* Compute X */ d__1 = *scale * b[b_dim1 + 1]; d__2 = *scale * b[(b_dim1 << 1) + 1]; igraphdladiv_(&d__1, &d__2, &csr, &csi, &x[x_dim1 + 1], &x[(x_dim1 << 1) + 1]); *xnorm = (d__1 = x[x_dim1 + 1], abs(d__1)) + (d__2 = x[(x_dim1 << 1) + 1], abs(d__2)); } } else { /* 2x2 System Compute the real part of C = ca A - w D (or ca A**T - w D ) */ cr[0] = *ca * a[a_dim1 + 1] - *wr * *d1; cr[3] = *ca * a[(a_dim1 << 1) + 2] - *wr * *d2; if (*ltrans) { cr[2] = *ca * a[a_dim1 + 2]; cr[1] = *ca * a[(a_dim1 << 1) + 1]; } else { cr[1] = *ca * a[a_dim1 + 2]; cr[2] = *ca * a[(a_dim1 << 1) + 1]; } if (*nw == 1) { /* Real 2x2 system (w is real) Find the largest element in C */ cmax = 0.; icmax = 0; for (j = 1; j <= 4; ++j) { if ((d__1 = crv[j - 1], abs(d__1)) > cmax) { cmax = (d__1 = crv[j - 1], abs(d__1)); icmax = j; } /* L10: */ } /* If norm(C) < SMINI, use SMINI*identity. */ if (cmax < smini) { /* Computing MAX */ d__3 = (d__1 = b[b_dim1 + 1], abs(d__1)), d__4 = (d__2 = b[ b_dim1 + 2], abs(d__2)); bnorm = max(d__3,d__4); if (smini < 1. && bnorm > 1.) { if (bnorm > bignum * smini) { *scale = 1. / bnorm; } } temp = *scale / smini; x[x_dim1 + 1] = temp * b[b_dim1 + 1]; x[x_dim1 + 2] = temp * b[b_dim1 + 2]; *xnorm = temp * bnorm; *info = 1; return 0; } /* Gaussian elimination with complete pivoting. */ ur11 = crv[icmax - 1]; cr21 = crv[ipivot[(icmax << 2) - 3] - 1]; ur12 = crv[ipivot[(icmax << 2) - 2] - 1]; cr22 = crv[ipivot[(icmax << 2) - 1] - 1]; ur11r = 1. / ur11; lr21 = ur11r * cr21; ur22 = cr22 - ur12 * lr21; /* If smaller pivot < SMINI, use SMINI */ if (abs(ur22) < smini) { ur22 = smini; *info = 1; } if (rswap[icmax - 1]) { br1 = b[b_dim1 + 2]; br2 = b[b_dim1 + 1]; } else { br1 = b[b_dim1 + 1]; br2 = b[b_dim1 + 2]; } br2 -= lr21 * br1; /* Computing MAX */ d__2 = (d__1 = br1 * (ur22 * ur11r), abs(d__1)), d__3 = abs(br2); bbnd = max(d__2,d__3); if (bbnd > 1. && abs(ur22) < 1.) { if (bbnd >= bignum * abs(ur22)) { *scale = 1. / bbnd; } } xr2 = br2 * *scale / ur22; xr1 = *scale * br1 * ur11r - xr2 * (ur11r * ur12); if (zswap[icmax - 1]) { x[x_dim1 + 1] = xr2; x[x_dim1 + 2] = xr1; } else { x[x_dim1 + 1] = xr1; x[x_dim1 + 2] = xr2; } /* Computing MAX */ d__1 = abs(xr1), d__2 = abs(xr2); *xnorm = max(d__1,d__2); /* Further scaling if norm(A) norm(X) > overflow */ if (*xnorm > 1. && cmax > 1.) { if (*xnorm > bignum / cmax) { temp = cmax / bignum; x[x_dim1 + 1] = temp * x[x_dim1 + 1]; x[x_dim1 + 2] = temp * x[x_dim1 + 2]; *xnorm = temp * *xnorm; *scale = temp * *scale; } } } else { /* Complex 2x2 system (w is complex) Find the largest element in C */ ci[0] = -(*wi) * *d1; ci[1] = 0.; ci[2] = 0.; ci[3] = -(*wi) * *d2; cmax = 0.; icmax = 0; for (j = 1; j <= 4; ++j) { if ((d__1 = crv[j - 1], abs(d__1)) + (d__2 = civ[j - 1], abs( d__2)) > cmax) { cmax = (d__1 = crv[j - 1], abs(d__1)) + (d__2 = civ[j - 1] , abs(d__2)); icmax = j; } /* L20: */ } /* If norm(C) < SMINI, use SMINI*identity. */ if (cmax < smini) { /* Computing MAX */ d__5 = (d__1 = b[b_dim1 + 1], abs(d__1)) + (d__2 = b[(b_dim1 << 1) + 1], abs(d__2)), d__6 = (d__3 = b[b_dim1 + 2], abs(d__3)) + (d__4 = b[(b_dim1 << 1) + 2], abs(d__4)); bnorm = max(d__5,d__6); if (smini < 1. && bnorm > 1.) { if (bnorm > bignum * smini) { *scale = 1. / bnorm; } } temp = *scale / smini; x[x_dim1 + 1] = temp * b[b_dim1 + 1]; x[x_dim1 + 2] = temp * b[b_dim1 + 2]; x[(x_dim1 << 1) + 1] = temp * b[(b_dim1 << 1) + 1]; x[(x_dim1 << 1) + 2] = temp * b[(b_dim1 << 1) + 2]; *xnorm = temp * bnorm; *info = 1; return 0; } /* Gaussian elimination with complete pivoting. */ ur11 = crv[icmax - 1]; ui11 = civ[icmax - 1]; cr21 = crv[ipivot[(icmax << 2) - 3] - 1]; ci21 = civ[ipivot[(icmax << 2) - 3] - 1]; ur12 = crv[ipivot[(icmax << 2) - 2] - 1]; ui12 = civ[ipivot[(icmax << 2) - 2] - 1]; cr22 = crv[ipivot[(icmax << 2) - 1] - 1]; ci22 = civ[ipivot[(icmax << 2) - 1] - 1]; if (icmax == 1 || icmax == 4) { /* Code when off-diagonals of pivoted C are real */ if (abs(ur11) > abs(ui11)) { temp = ui11 / ur11; /* Computing 2nd power */ d__1 = temp; ur11r = 1. / (ur11 * (d__1 * d__1 + 1.)); ui11r = -temp * ur11r; } else { temp = ur11 / ui11; /* Computing 2nd power */ d__1 = temp; ui11r = -1. / (ui11 * (d__1 * d__1 + 1.)); ur11r = -temp * ui11r; } lr21 = cr21 * ur11r; li21 = cr21 * ui11r; ur12s = ur12 * ur11r; ui12s = ur12 * ui11r; ur22 = cr22 - ur12 * lr21; ui22 = ci22 - ur12 * li21; } else { /* Code when diagonals of pivoted C are real */ ur11r = 1. / ur11; ui11r = 0.; lr21 = cr21 * ur11r; li21 = ci21 * ur11r; ur12s = ur12 * ur11r; ui12s = ui12 * ur11r; ur22 = cr22 - ur12 * lr21 + ui12 * li21; ui22 = -ur12 * li21 - ui12 * lr21; } u22abs = abs(ur22) + abs(ui22); /* If smaller pivot < SMINI, use SMINI */ if (u22abs < smini) { ur22 = smini; ui22 = 0.; *info = 1; } if (rswap[icmax - 1]) { br2 = b[b_dim1 + 1]; br1 = b[b_dim1 + 2]; bi2 = b[(b_dim1 << 1) + 1]; bi1 = b[(b_dim1 << 1) + 2]; } else { br1 = b[b_dim1 + 1]; br2 = b[b_dim1 + 2]; bi1 = b[(b_dim1 << 1) + 1]; bi2 = b[(b_dim1 << 1) + 2]; } br2 = br2 - lr21 * br1 + li21 * bi1; bi2 = bi2 - li21 * br1 - lr21 * bi1; /* Computing MAX */ d__1 = (abs(br1) + abs(bi1)) * (u22abs * (abs(ur11r) + abs(ui11r)) ), d__2 = abs(br2) + abs(bi2); bbnd = max(d__1,d__2); if (bbnd > 1. && u22abs < 1.) { if (bbnd >= bignum * u22abs) { *scale = 1. / bbnd; br1 = *scale * br1; bi1 = *scale * bi1; br2 = *scale * br2; bi2 = *scale * bi2; } } igraphdladiv_(&br2, &bi2, &ur22, &ui22, &xr2, &xi2); xr1 = ur11r * br1 - ui11r * bi1 - ur12s * xr2 + ui12s * xi2; xi1 = ui11r * br1 + ur11r * bi1 - ui12s * xr2 - ur12s * xi2; if (zswap[icmax - 1]) { x[x_dim1 + 1] = xr2; x[x_dim1 + 2] = xr1; x[(x_dim1 << 1) + 1] = xi2; x[(x_dim1 << 1) + 2] = xi1; } else { x[x_dim1 + 1] = xr1; x[x_dim1 + 2] = xr2; x[(x_dim1 << 1) + 1] = xi1; x[(x_dim1 << 1) + 2] = xi2; } /* Computing MAX */ d__1 = abs(xr1) + abs(xi1), d__2 = abs(xr2) + abs(xi2); *xnorm = max(d__1,d__2); /* Further scaling if norm(A) norm(X) > overflow */ if (*xnorm > 1. && cmax > 1.) { if (*xnorm > bignum / cmax) { temp = cmax / bignum; x[x_dim1 + 1] = temp * x[x_dim1 + 1]; x[x_dim1 + 2] = temp * x[x_dim1 + 2]; x[(x_dim1 << 1) + 1] = temp * x[(x_dim1 << 1) + 1]; x[(x_dim1 << 1) + 2] = temp * x[(x_dim1 << 1) + 2]; *xnorm = temp * *xnorm; *scale = temp * *scale; } } } } return 0; /* End of DLALN2 */ } /* igraphdlaln2_ */ #undef crv #undef civ #undef cr #undef ci python-igraph-0.8.0/vendor/source/igraph/src/lapack/dtrsen.c0000644000076500000240000004673013524616145024315 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c_n1 = -1; /* > \brief \b DTRSEN =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DTRSEN + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DTRSEN( JOB, COMPQ, SELECT, N, T, LDT, Q, LDQ, WR, WI, M, S, SEP, WORK, LWORK, IWORK, LIWORK, INFO ) CHARACTER COMPQ, JOB INTEGER INFO, LDQ, LDT, LIWORK, LWORK, M, N DOUBLE PRECISION S, SEP LOGICAL SELECT( * ) INTEGER IWORK( * ) DOUBLE PRECISION Q( LDQ, * ), T( LDT, * ), WI( * ), WORK( * ), $ WR( * ) > \par Purpose: ============= > > \verbatim > > DTRSEN reorders the real Schur factorization of a real matrix > A = Q*T*Q**T, so that a selected cluster of eigenvalues appears in > the leading diagonal blocks of the upper quasi-triangular matrix T, > and the leading columns of Q form an orthonormal basis of the > corresponding right invariant subspace. > > Optionally the routine computes the reciprocal condition numbers of > the cluster of eigenvalues and/or the invariant subspace. > > T must be in Schur canonical form (as returned by DHSEQR), that is, > block upper triangular with 1-by-1 and 2-by-2 diagonal blocks; each > 2-by-2 diagonal block has its diagonal elements equal and its > off-diagonal elements of opposite sign. > \endverbatim Arguments: ========== > \param[in] JOB > \verbatim > JOB is CHARACTER*1 > Specifies whether condition numbers are required for the > cluster of eigenvalues (S) or the invariant subspace (SEP): > = 'N': none; > = 'E': for eigenvalues only (S); > = 'V': for invariant subspace only (SEP); > = 'B': for both eigenvalues and invariant subspace (S and > SEP). > \endverbatim > > \param[in] COMPQ > \verbatim > COMPQ is CHARACTER*1 > = 'V': update the matrix Q of Schur vectors; > = 'N': do not update Q. > \endverbatim > > \param[in] SELECT > \verbatim > SELECT is LOGICAL array, dimension (N) > SELECT specifies the eigenvalues in the selected cluster. To > select a real eigenvalue w(j), SELECT(j) must be set to > .TRUE.. To select a complex conjugate pair of eigenvalues > w(j) and w(j+1), corresponding to a 2-by-2 diagonal block, > either SELECT(j) or SELECT(j+1) or both must be set to > .TRUE.; a complex conjugate pair of eigenvalues must be > either both included in the cluster or both excluded. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix T. N >= 0. > \endverbatim > > \param[in,out] T > \verbatim > T is DOUBLE PRECISION array, dimension (LDT,N) > On entry, the upper quasi-triangular matrix T, in Schur > canonical form. > On exit, T is overwritten by the reordered matrix T, again in > Schur canonical form, with the selected eigenvalues in the > leading diagonal blocks. > \endverbatim > > \param[in] LDT > \verbatim > LDT is INTEGER > The leading dimension of the array T. LDT >= max(1,N). > \endverbatim > > \param[in,out] Q > \verbatim > Q is DOUBLE PRECISION array, dimension (LDQ,N) > On entry, if COMPQ = 'V', the matrix Q of Schur vectors. > On exit, if COMPQ = 'V', Q has been postmultiplied by the > orthogonal transformation matrix which reorders T; the > leading M columns of Q form an orthonormal basis for the > specified invariant subspace. > If COMPQ = 'N', Q is not referenced. > \endverbatim > > \param[in] LDQ > \verbatim > LDQ is INTEGER > The leading dimension of the array Q. > LDQ >= 1; and if COMPQ = 'V', LDQ >= N. > \endverbatim > > \param[out] WR > \verbatim > WR is DOUBLE PRECISION array, dimension (N) > \endverbatim > \param[out] WI > \verbatim > WI is DOUBLE PRECISION array, dimension (N) > > The real and imaginary parts, respectively, of the reordered > eigenvalues of T. The eigenvalues are stored in the same > order as on the diagonal of T, with WR(i) = T(i,i) and, if > T(i:i+1,i:i+1) is a 2-by-2 diagonal block, WI(i) > 0 and > WI(i+1) = -WI(i). Note that if a complex eigenvalue is > sufficiently ill-conditioned, then its value may differ > significantly from its value before reordering. > \endverbatim > > \param[out] M > \verbatim > M is INTEGER > The dimension of the specified invariant subspace. > 0 < = M <= N. > \endverbatim > > \param[out] S > \verbatim > S is DOUBLE PRECISION > If JOB = 'E' or 'B', S is a lower bound on the reciprocal > condition number for the selected cluster of eigenvalues. > S cannot underestimate the true reciprocal condition number > by more than a factor of sqrt(N). If M = 0 or N, S = 1. > If JOB = 'N' or 'V', S is not referenced. > \endverbatim > > \param[out] SEP > \verbatim > SEP is DOUBLE PRECISION > If JOB = 'V' or 'B', SEP is the estimated reciprocal > condition number of the specified invariant subspace. If > M = 0 or N, SEP = norm(T). > If JOB = 'N' or 'E', SEP is not referenced. > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (MAX(1,LWORK)) > On exit, if INFO = 0, WORK(1) returns the optimal LWORK. > \endverbatim > > \param[in] LWORK > \verbatim > LWORK is INTEGER > The dimension of the array WORK. > If JOB = 'N', LWORK >= max(1,N); > if JOB = 'E', LWORK >= max(1,M*(N-M)); > if JOB = 'V' or 'B', LWORK >= max(1,2*M*(N-M)). > > If LWORK = -1, then a workspace query is assumed; the routine > only calculates the optimal size of the WORK array, returns > this value as the first entry of the WORK array, and no error > message related to LWORK is issued by XERBLA. > \endverbatim > > \param[out] IWORK > \verbatim > IWORK is INTEGER array, dimension (MAX(1,LIWORK)) > On exit, if INFO = 0, IWORK(1) returns the optimal LIWORK. > \endverbatim > > \param[in] LIWORK > \verbatim > LIWORK is INTEGER > The dimension of the array IWORK. > If JOB = 'N' or 'E', LIWORK >= 1; > if JOB = 'V' or 'B', LIWORK >= max(1,M*(N-M)). > > If LIWORK = -1, then a workspace query is assumed; the > routine only calculates the optimal size of the IWORK array, > returns this value as the first entry of the IWORK array, and > no error message related to LIWORK is issued by XERBLA. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value > = 1: reordering of T failed because some eigenvalues are too > close to separate (the problem is very ill-conditioned); > T may have been partially reordered, and WR and WI > contain the eigenvalues in the same order as in T; S and > SEP (if requested) are set to zero. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date April 2012 > \ingroup doubleOTHERcomputational > \par Further Details: ===================== > > \verbatim > > DTRSEN first collects the selected eigenvalues by computing an > orthogonal transformation Z to move them to the top left corner of T. > In other words, the selected eigenvalues are the eigenvalues of T11 > in: > > Z**T * T * Z = ( T11 T12 ) n1 > ( 0 T22 ) n2 > n1 n2 > > where N = n1+n2 and Z**T means the transpose of Z. The first n1 columns > of Z span the specified invariant subspace of T. > > If T has been obtained from the real Schur factorization of a matrix > A = Q*T*Q**T, then the reordered real Schur factorization of A is given > by A = (Q*Z)*(Z**T*T*Z)*(Q*Z)**T, and the first n1 columns of Q*Z span > the corresponding invariant subspace of A. > > The reciprocal condition number of the average of the eigenvalues of > T11 may be returned in S. S lies between 0 (very badly conditioned) > and 1 (very well conditioned). It is computed as follows. First we > compute R so that > > P = ( I R ) n1 > ( 0 0 ) n2 > n1 n2 > > is the projector on the invariant subspace associated with T11. > R is the solution of the Sylvester equation: > > T11*R - R*T22 = T12. > > Let F-norm(M) denote the Frobenius-norm of M and 2-norm(M) denote > the two-norm of M. Then S is computed as the lower bound > > (1 + F-norm(R)**2)**(-1/2) > > on the reciprocal of 2-norm(P), the true reciprocal condition number. > S cannot underestimate 1 / 2-norm(P) by more than a factor of > sqrt(N). > > An approximate error bound for the computed average of the > eigenvalues of T11 is > > EPS * norm(T) / S > > where EPS is the machine precision. > > The reciprocal condition number of the right invariant subspace > spanned by the first n1 columns of Z (or of Q*Z) is returned in SEP. > SEP is defined as the separation of T11 and T22: > > sep( T11, T22 ) = sigma-min( C ) > > where sigma-min(C) is the smallest singular value of the > n1*n2-by-n1*n2 matrix > > C = kprod( I(n2), T11 ) - kprod( transpose(T22), I(n1) ) > > I(m) is an m by m identity matrix, and kprod denotes the Kronecker > product. We estimate sigma-min(C) by the reciprocal of an estimate of > the 1-norm of inverse(C). The true reciprocal 1-norm of inverse(C) > cannot differ from sigma-min(C) by more than a factor of sqrt(n1*n2). > > When SEP is small, small changes in T can cause large changes in > the invariant subspace. An approximate bound on the maximum angular > error in the computed right invariant subspace is > > EPS * norm(T) / SEP > \endverbatim > ===================================================================== Subroutine */ int igraphdtrsen_(char *job, char *compq, logical *select, integer *n, doublereal *t, integer *ldt, doublereal *q, integer *ldq, doublereal *wr, doublereal *wi, integer *m, doublereal *s, doublereal *sep, doublereal *work, integer *lwork, integer *iwork, integer * liwork, integer *info) { /* System generated locals */ integer q_dim1, q_offset, t_dim1, t_offset, i__1, i__2; doublereal d__1, d__2; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ integer k, n1, n2, kk, nn, ks; doublereal est; integer kase; logical pair; integer ierr; logical swap; doublereal scale; extern logical igraphlsame_(char *, char *); integer isave[3], lwmin = 0; logical wantq, wants; doublereal rnorm; extern /* Subroutine */ int igraphdlacn2_(integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, integer *); extern doublereal igraphdlange_(char *, integer *, integer *, doublereal *, integer *, doublereal *); extern /* Subroutine */ int igraphdlacpy_(char *, integer *, integer *, doublereal *, integer *, doublereal *, integer *), igraphxerbla_(char *, integer *, ftnlen); logical wantbh; extern /* Subroutine */ int igraphdtrexc_(char *, integer *, doublereal *, integer *, doublereal *, integer *, integer *, integer *, doublereal *, integer *); integer liwmin; logical wantsp, lquery; extern /* Subroutine */ int igraphdtrsyl_(char *, char *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, integer *); /* -- LAPACK computational routine (version 3.4.1) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- April 2012 ===================================================================== Decode and test the input parameters Parameter adjustments */ --select; t_dim1 = *ldt; t_offset = 1 + t_dim1; t -= t_offset; q_dim1 = *ldq; q_offset = 1 + q_dim1; q -= q_offset; --wr; --wi; --work; --iwork; /* Function Body */ wantbh = igraphlsame_(job, "B"); wants = igraphlsame_(job, "E") || wantbh; wantsp = igraphlsame_(job, "V") || wantbh; wantq = igraphlsame_(compq, "V"); *info = 0; lquery = *lwork == -1; if (! igraphlsame_(job, "N") && ! wants && ! wantsp) { *info = -1; } else if (! igraphlsame_(compq, "N") && ! wantq) { *info = -2; } else if (*n < 0) { *info = -4; } else if (*ldt < max(1,*n)) { *info = -6; } else if (*ldq < 1 || wantq && *ldq < *n) { *info = -8; } else { /* Set M to the dimension of the specified invariant subspace, and test LWORK and LIWORK. */ *m = 0; pair = FALSE_; i__1 = *n; for (k = 1; k <= i__1; ++k) { if (pair) { pair = FALSE_; } else { if (k < *n) { if (t[k + 1 + k * t_dim1] == 0.) { if (select[k]) { ++(*m); } } else { pair = TRUE_; if (select[k] || select[k + 1]) { *m += 2; } } } else { if (select[*n]) { ++(*m); } } } /* L10: */ } n1 = *m; n2 = *n - *m; nn = n1 * n2; if (wantsp) { /* Computing MAX */ i__1 = 1, i__2 = nn << 1; lwmin = max(i__1,i__2); liwmin = max(1,nn); } else if (igraphlsame_(job, "N")) { lwmin = max(1,*n); liwmin = 1; } else if (igraphlsame_(job, "E")) { lwmin = max(1,nn); liwmin = 1; } if (*lwork < lwmin && ! lquery) { *info = -15; } else if (*liwork < liwmin && ! lquery) { *info = -17; } } if (*info == 0) { work[1] = (doublereal) lwmin; iwork[1] = liwmin; } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DTRSEN", &i__1, (ftnlen)6); return 0; } else if (lquery) { return 0; } /* Quick return if possible. */ if (*m == *n || *m == 0) { if (wants) { *s = 1.; } if (wantsp) { *sep = igraphdlange_("1", n, n, &t[t_offset], ldt, &work[1]); } goto L40; } /* Collect the selected blocks at the top-left corner of T. */ ks = 0; pair = FALSE_; i__1 = *n; for (k = 1; k <= i__1; ++k) { if (pair) { pair = FALSE_; } else { swap = select[k]; if (k < *n) { if (t[k + 1 + k * t_dim1] != 0.) { pair = TRUE_; swap = swap || select[k + 1]; } } if (swap) { ++ks; /* Swap the K-th block to position KS. */ ierr = 0; kk = k; if (k != ks) { igraphdtrexc_(compq, n, &t[t_offset], ldt, &q[q_offset], ldq, & kk, &ks, &work[1], &ierr); } if (ierr == 1 || ierr == 2) { /* Blocks too close to swap: exit. */ *info = 1; if (wants) { *s = 0.; } if (wantsp) { *sep = 0.; } goto L40; } if (pair) { ++ks; } } } /* L20: */ } if (wants) { /* Solve Sylvester equation for R: T11*R - R*T22 = scale*T12 */ igraphdlacpy_("F", &n1, &n2, &t[(n1 + 1) * t_dim1 + 1], ldt, &work[1], &n1); igraphdtrsyl_("N", "N", &c_n1, &n1, &n2, &t[t_offset], ldt, &t[n1 + 1 + (n1 + 1) * t_dim1], ldt, &work[1], &n1, &scale, &ierr); /* Estimate the reciprocal of the condition number of the cluster of eigenvalues. */ rnorm = igraphdlange_("F", &n1, &n2, &work[1], &n1, &work[1]); if (rnorm == 0.) { *s = 1.; } else { *s = scale / (sqrt(scale * scale / rnorm + rnorm) * sqrt(rnorm)); } } if (wantsp) { /* Estimate sep(T11,T22). */ est = 0.; kase = 0; L30: igraphdlacn2_(&nn, &work[nn + 1], &work[1], &iwork[1], &est, &kase, isave); if (kase != 0) { if (kase == 1) { /* Solve T11*R - R*T22 = scale*X. */ igraphdtrsyl_("N", "N", &c_n1, &n1, &n2, &t[t_offset], ldt, &t[n1 + 1 + (n1 + 1) * t_dim1], ldt, &work[1], &n1, &scale, & ierr); } else { /* Solve T11**T*R - R*T22**T = scale*X. */ igraphdtrsyl_("T", "T", &c_n1, &n1, &n2, &t[t_offset], ldt, &t[n1 + 1 + (n1 + 1) * t_dim1], ldt, &work[1], &n1, &scale, & ierr); } goto L30; } *sep = scale / est; } L40: /* Store the output eigenvalues in WR and WI. */ i__1 = *n; for (k = 1; k <= i__1; ++k) { wr[k] = t[k + k * t_dim1]; wi[k] = 0.; /* L50: */ } i__1 = *n - 1; for (k = 1; k <= i__1; ++k) { if (t[k + 1 + k * t_dim1] != 0.) { wi[k] = sqrt((d__1 = t[k + (k + 1) * t_dim1], abs(d__1))) * sqrt(( d__2 = t[k + 1 + k * t_dim1], abs(d__2))); wi[k + 1] = -wi[k]; } /* L60: */ } work[1] = (doublereal) lwmin; iwork[1] = liwmin; return 0; /* End of DTRSEN */ } /* igraphdtrsen_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/blas.inc0000644000076500000240000000050213524616145024251 0ustar tamasstaff00000000000000BLAS = lapack/dscal.c lapack/dswap.c lapack/lsame.c lapack/dnrm2.c lapack/idamax.c lapack/daxpy.c lapack/dgemv.c lapack/dger.c lapack/dgemm.c lapack/dcopy.c lapack/dtrmm.c lapack/dtrmv.c lapack/drot.c lapack/ddot.c lapack/dasum.c lapack/dsymv.c lapack/dsyr2k.c lapack/dsyr2.c lapack/dtrsm.c lapack/dsyrk.c lapack/dtrsv.c python-igraph-0.8.0/vendor/source/igraph/src/lapack/dgemv.c0000644000076500000240000001664213524616145024117 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Subroutine */ int igraphdgemv_(char *trans, integer *m, integer *n, doublereal * alpha, doublereal *a, integer *lda, doublereal *x, integer *incx, doublereal *beta, doublereal *y, integer *incy) { /* System generated locals */ integer a_dim1, a_offset, i__1, i__2; /* Local variables */ integer i__, j, ix, iy, jx, jy, kx, ky, info; doublereal temp; integer lenx, leny; extern logical igraphlsame_(char *, char *); extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); /* Purpose ======= DGEMV performs one of the matrix-vector operations y := alpha*A*x + beta*y, or y := alpha*A**T*x + beta*y, where alpha and beta are scalars, x and y are vectors and A is an m by n matrix. Arguments ========== TRANS - CHARACTER*1. On entry, TRANS specifies the operation to be performed as follows: TRANS = 'N' or 'n' y := alpha*A*x + beta*y. TRANS = 'T' or 't' y := alpha*A**T*x + beta*y. TRANS = 'C' or 'c' y := alpha*A**T*x + beta*y. Unchanged on exit. M - INTEGER. On entry, M specifies the number of rows of the matrix A. M must be at least zero. Unchanged on exit. N - INTEGER. On entry, N specifies the number of columns of the matrix A. N must be at least zero. Unchanged on exit. ALPHA - DOUBLE PRECISION. On entry, ALPHA specifies the scalar alpha. Unchanged on exit. A - DOUBLE PRECISION array of DIMENSION ( LDA, n ). Before entry, the leading m by n part of the array A must contain the matrix of coefficients. Unchanged on exit. LDA - INTEGER. On entry, LDA specifies the first dimension of A as declared in the calling (sub) program. LDA must be at least max( 1, m ). Unchanged on exit. X - DOUBLE PRECISION array of DIMENSION at least ( 1 + ( n - 1 )*abs( INCX ) ) when TRANS = 'N' or 'n' and at least ( 1 + ( m - 1 )*abs( INCX ) ) otherwise. Before entry, the incremented array X must contain the vector x. Unchanged on exit. INCX - INTEGER. On entry, INCX specifies the increment for the elements of X. INCX must not be zero. Unchanged on exit. BETA - DOUBLE PRECISION. On entry, BETA specifies the scalar beta. When BETA is supplied as zero then Y need not be set on input. Unchanged on exit. Y - DOUBLE PRECISION array of DIMENSION at least ( 1 + ( m - 1 )*abs( INCY ) ) when TRANS = 'N' or 'n' and at least ( 1 + ( n - 1 )*abs( INCY ) ) otherwise. Before entry with BETA non-zero, the incremented array Y must contain the vector y. On exit, Y is overwritten by the updated vector y. INCY - INTEGER. On entry, INCY specifies the increment for the elements of Y. INCY must not be zero. Unchanged on exit. Further Details =============== Level 2 Blas routine. The vector and matrix arguments are not referenced when N = 0, or M = 0 -- Written on 22-October-1986. Jack Dongarra, Argonne National Lab. Jeremy Du Croz, Nag Central Office. Sven Hammarling, Nag Central Office. Richard Hanson, Sandia National Labs. ===================================================================== Test the input parameters. Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --x; --y; /* Function Body */ info = 0; if (! igraphlsame_(trans, "N") && ! igraphlsame_(trans, "T") && ! igraphlsame_(trans, "C") ) { info = 1; } else if (*m < 0) { info = 2; } else if (*n < 0) { info = 3; } else if (*lda < max(1,*m)) { info = 6; } else if (*incx == 0) { info = 8; } else if (*incy == 0) { info = 11; } if (info != 0) { igraphxerbla_("DGEMV ", &info, (ftnlen)6); return 0; } /* Quick return if possible. */ if (*m == 0 || *n == 0 || *alpha == 0. && *beta == 1.) { return 0; } /* Set LENX and LENY, the lengths of the vectors x and y, and set up the start points in X and Y. */ if (igraphlsame_(trans, "N")) { lenx = *n; leny = *m; } else { lenx = *m; leny = *n; } if (*incx > 0) { kx = 1; } else { kx = 1 - (lenx - 1) * *incx; } if (*incy > 0) { ky = 1; } else { ky = 1 - (leny - 1) * *incy; } /* Start the operations. In this version the elements of A are accessed sequentially with one pass through A. First form y := beta*y. */ if (*beta != 1.) { if (*incy == 1) { if (*beta == 0.) { i__1 = leny; for (i__ = 1; i__ <= i__1; ++i__) { y[i__] = 0.; /* L10: */ } } else { i__1 = leny; for (i__ = 1; i__ <= i__1; ++i__) { y[i__] = *beta * y[i__]; /* L20: */ } } } else { iy = ky; if (*beta == 0.) { i__1 = leny; for (i__ = 1; i__ <= i__1; ++i__) { y[iy] = 0.; iy += *incy; /* L30: */ } } else { i__1 = leny; for (i__ = 1; i__ <= i__1; ++i__) { y[iy] = *beta * y[iy]; iy += *incy; /* L40: */ } } } } if (*alpha == 0.) { return 0; } if (igraphlsame_(trans, "N")) { /* Form y := alpha*A*x + y. */ jx = kx; if (*incy == 1) { i__1 = *n; for (j = 1; j <= i__1; ++j) { if (x[jx] != 0.) { temp = *alpha * x[jx]; i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { y[i__] += temp * a[i__ + j * a_dim1]; /* L50: */ } } jx += *incx; /* L60: */ } } else { i__1 = *n; for (j = 1; j <= i__1; ++j) { if (x[jx] != 0.) { temp = *alpha * x[jx]; iy = ky; i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { y[iy] += temp * a[i__ + j * a_dim1]; iy += *incy; /* L70: */ } } jx += *incx; /* L80: */ } } } else { /* Form y := alpha*A**T*x + y. */ jy = ky; if (*incx == 1) { i__1 = *n; for (j = 1; j <= i__1; ++j) { temp = 0.; i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { temp += a[i__ + j * a_dim1] * x[i__]; /* L90: */ } y[jy] += *alpha * temp; jy += *incy; /* L100: */ } } else { i__1 = *n; for (j = 1; j <= i__1; ++j) { temp = 0.; ix = kx; i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { temp += a[i__ + j * a_dim1] * x[ix]; ix += *incx; /* L110: */ } y[jy] += *alpha * temp; jy += *incy; /* L120: */ } } } return 0; /* End of DGEMV . */ } /* igraphdgemv_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlaqr3.c0000644000076500000240000006266013524616145024204 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static integer c_n1 = -1; static logical c_true = TRUE_; static doublereal c_b17 = 0.; static doublereal c_b18 = 1.; static integer c__12 = 12; /* > \brief \b DLAQR3 performs the orthogonal similarity transformation of a Hessenberg matrix to detect and d eflate fully converged eigenvalues from a trailing principal submatrix (aggressive early deflation). =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLAQR3 + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLAQR3( WANTT, WANTZ, N, KTOP, KBOT, NW, H, LDH, ILOZ, IHIZ, Z, LDZ, NS, ND, SR, SI, V, LDV, NH, T, LDT, NV, WV, LDWV, WORK, LWORK ) INTEGER IHIZ, ILOZ, KBOT, KTOP, LDH, LDT, LDV, LDWV, $ LDZ, LWORK, N, ND, NH, NS, NV, NW LOGICAL WANTT, WANTZ DOUBLE PRECISION H( LDH, * ), SI( * ), SR( * ), T( LDT, * ), $ V( LDV, * ), WORK( * ), WV( LDWV, * ), $ Z( LDZ, * ) > \par Purpose: ============= > > \verbatim > > Aggressive early deflation: > > DLAQR3 accepts as input an upper Hessenberg matrix > H and performs an orthogonal similarity transformation > designed to detect and deflate fully converged eigenvalues from > a trailing principal submatrix. On output H has been over- > written by a new Hessenberg matrix that is a perturbation of > an orthogonal similarity transformation of H. It is to be > hoped that the final version of H has many zero subdiagonal > entries. > \endverbatim Arguments: ========== > \param[in] WANTT > \verbatim > WANTT is LOGICAL > If .TRUE., then the Hessenberg matrix H is fully updated > so that the quasi-triangular Schur factor may be > computed (in cooperation with the calling subroutine). > If .FALSE., then only enough of H is updated to preserve > the eigenvalues. > \endverbatim > > \param[in] WANTZ > \verbatim > WANTZ is LOGICAL > If .TRUE., then the orthogonal matrix Z is updated so > so that the orthogonal Schur factor may be computed > (in cooperation with the calling subroutine). > If .FALSE., then Z is not referenced. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix H and (if WANTZ is .TRUE.) the > order of the orthogonal matrix Z. > \endverbatim > > \param[in] KTOP > \verbatim > KTOP is INTEGER > It is assumed that either KTOP = 1 or H(KTOP,KTOP-1)=0. > KBOT and KTOP together determine an isolated block > along the diagonal of the Hessenberg matrix. > \endverbatim > > \param[in] KBOT > \verbatim > KBOT is INTEGER > It is assumed without a check that either > KBOT = N or H(KBOT+1,KBOT)=0. KBOT and KTOP together > determine an isolated block along the diagonal of the > Hessenberg matrix. > \endverbatim > > \param[in] NW > \verbatim > NW is INTEGER > Deflation window size. 1 .LE. NW .LE. (KBOT-KTOP+1). > \endverbatim > > \param[in,out] H > \verbatim > H is DOUBLE PRECISION array, dimension (LDH,N) > On input the initial N-by-N section of H stores the > Hessenberg matrix undergoing aggressive early deflation. > On output H has been transformed by an orthogonal > similarity transformation, perturbed, and the returned > to Hessenberg form that (it is to be hoped) has some > zero subdiagonal entries. > \endverbatim > > \param[in] LDH > \verbatim > LDH is integer > Leading dimension of H just as declared in the calling > subroutine. N .LE. LDH > \endverbatim > > \param[in] ILOZ > \verbatim > ILOZ is INTEGER > \endverbatim > > \param[in] IHIZ > \verbatim > IHIZ is INTEGER > Specify the rows of Z to which transformations must be > applied if WANTZ is .TRUE.. 1 .LE. ILOZ .LE. IHIZ .LE. N. > \endverbatim > > \param[in,out] Z > \verbatim > Z is DOUBLE PRECISION array, dimension (LDZ,N) > IF WANTZ is .TRUE., then on output, the orthogonal > similarity transformation mentioned above has been > accumulated into Z(ILOZ:IHIZ,ILO:IHI) from the right. > If WANTZ is .FALSE., then Z is unreferenced. > \endverbatim > > \param[in] LDZ > \verbatim > LDZ is integer > The leading dimension of Z just as declared in the > calling subroutine. 1 .LE. LDZ. > \endverbatim > > \param[out] NS > \verbatim > NS is integer > The number of unconverged (ie approximate) eigenvalues > returned in SR and SI that may be used as shifts by the > calling subroutine. > \endverbatim > > \param[out] ND > \verbatim > ND is integer > The number of converged eigenvalues uncovered by this > subroutine. > \endverbatim > > \param[out] SR > \verbatim > SR is DOUBLE PRECISION array, dimension (KBOT) > \endverbatim > > \param[out] SI > \verbatim > SI is DOUBLE PRECISION array, dimension (KBOT) > On output, the real and imaginary parts of approximate > eigenvalues that may be used for shifts are stored in > SR(KBOT-ND-NS+1) through SR(KBOT-ND) and > SI(KBOT-ND-NS+1) through SI(KBOT-ND), respectively. > The real and imaginary parts of converged eigenvalues > are stored in SR(KBOT-ND+1) through SR(KBOT) and > SI(KBOT-ND+1) through SI(KBOT), respectively. > \endverbatim > > \param[out] V > \verbatim > V is DOUBLE PRECISION array, dimension (LDV,NW) > An NW-by-NW work array. > \endverbatim > > \param[in] LDV > \verbatim > LDV is integer scalar > The leading dimension of V just as declared in the > calling subroutine. NW .LE. LDV > \endverbatim > > \param[in] NH > \verbatim > NH is integer scalar > The number of columns of T. NH.GE.NW. > \endverbatim > > \param[out] T > \verbatim > T is DOUBLE PRECISION array, dimension (LDT,NW) > \endverbatim > > \param[in] LDT > \verbatim > LDT is integer > The leading dimension of T just as declared in the > calling subroutine. NW .LE. LDT > \endverbatim > > \param[in] NV > \verbatim > NV is integer > The number of rows of work array WV available for > workspace. NV.GE.NW. > \endverbatim > > \param[out] WV > \verbatim > WV is DOUBLE PRECISION array, dimension (LDWV,NW) > \endverbatim > > \param[in] LDWV > \verbatim > LDWV is integer > The leading dimension of W just as declared in the > calling subroutine. NW .LE. LDV > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (LWORK) > On exit, WORK(1) is set to an estimate of the optimal value > of LWORK for the given values of N, NW, KTOP and KBOT. > \endverbatim > > \param[in] LWORK > \verbatim > LWORK is integer > The dimension of the work array WORK. LWORK = 2*NW > suffices, but greater efficiency may result from larger > values of LWORK. > > If LWORK = -1, then a workspace query is assumed; DLAQR3 > only estimates the optimal workspace size for the given > values of N, NW, KTOP and KBOT. The estimate is returned > in WORK(1). No error message related to LWORK is issued > by XERBLA. Neither H nor Z are accessed. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleOTHERauxiliary > \par Contributors: ================== > > Karen Braman and Ralph Byers, Department of Mathematics, > University of Kansas, USA > ===================================================================== Subroutine */ int igraphdlaqr3_(logical *wantt, logical *wantz, integer *n, integer *ktop, integer *kbot, integer *nw, doublereal *h__, integer * ldh, integer *iloz, integer *ihiz, doublereal *z__, integer *ldz, integer *ns, integer *nd, doublereal *sr, doublereal *si, doublereal * v, integer *ldv, integer *nh, doublereal *t, integer *ldt, integer * nv, doublereal *wv, integer *ldwv, doublereal *work, integer *lwork) { /* System generated locals */ integer h_dim1, h_offset, t_dim1, t_offset, v_dim1, v_offset, wv_dim1, wv_offset, z_dim1, z_offset, i__1, i__2, i__3, i__4; doublereal d__1, d__2, d__3, d__4, d__5, d__6; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ integer i__, j, k; doublereal s, aa, bb, cc, dd, cs, sn; integer jw; doublereal evi, evk, foo; integer kln; doublereal tau, ulp; integer lwk1, lwk2, lwk3; doublereal beta; integer kend, kcol, info, nmin, ifst, ilst, ltop, krow; extern /* Subroutine */ int igraphdlarf_(char *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *), igraphdgemm_(char *, char *, integer *, integer * , integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *); logical bulge; extern /* Subroutine */ int igraphdcopy_(integer *, doublereal *, integer *, doublereal *, integer *); integer infqr, kwtop; extern /* Subroutine */ int igraphdlanv2_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *), igraphdlaqr4_( logical *, logical *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, integer *, doublereal *, integer *, integer *), igraphdlabad_(doublereal *, doublereal *); extern doublereal igraphdlamch_(char *); extern /* Subroutine */ int igraphdgehrd_(integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, integer *), igraphdlarfg_(integer *, doublereal *, doublereal *, integer *, doublereal *), igraphdlahqr_(logical *, logical *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, integer *, integer *), igraphdlacpy_(char *, integer *, integer *, doublereal *, integer *, doublereal *, integer *); doublereal safmin; extern integer igraphilaenv_(integer *, char *, char *, integer *, integer *, integer *, integer *, ftnlen, ftnlen); doublereal safmax; extern /* Subroutine */ int igraphdlaset_(char *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *), igraphdtrexc_(char *, integer *, doublereal *, integer *, doublereal *, integer *, integer *, integer *, doublereal *, integer *), igraphdormhr_(char *, char *, integer *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, integer *); logical sorted; doublereal smlnum; integer lwkopt; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ================================================================ ==== Estimate optimal workspace. ==== Parameter adjustments */ h_dim1 = *ldh; h_offset = 1 + h_dim1; h__ -= h_offset; z_dim1 = *ldz; z_offset = 1 + z_dim1; z__ -= z_offset; --sr; --si; v_dim1 = *ldv; v_offset = 1 + v_dim1; v -= v_offset; t_dim1 = *ldt; t_offset = 1 + t_dim1; t -= t_offset; wv_dim1 = *ldwv; wv_offset = 1 + wv_dim1; wv -= wv_offset; --work; /* Function Body Computing MIN */ i__1 = *nw, i__2 = *kbot - *ktop + 1; jw = min(i__1,i__2); if (jw <= 2) { lwkopt = 1; } else { /* ==== Workspace query call to DGEHRD ==== */ i__1 = jw - 1; igraphdgehrd_(&jw, &c__1, &i__1, &t[t_offset], ldt, &work[1], &work[1], & c_n1, &info); lwk1 = (integer) work[1]; /* ==== Workspace query call to DORMHR ==== */ i__1 = jw - 1; igraphdormhr_("R", "N", &jw, &jw, &c__1, &i__1, &t[t_offset], ldt, &work[1], &v[v_offset], ldv, &work[1], &c_n1, &info); lwk2 = (integer) work[1]; /* ==== Workspace query call to DLAQR4 ==== */ igraphdlaqr4_(&c_true, &c_true, &jw, &c__1, &jw, &t[t_offset], ldt, &sr[1], &si[1], &c__1, &jw, &v[v_offset], ldv, &work[1], &c_n1, & infqr); lwk3 = (integer) work[1]; /* ==== Optimal workspace ==== Computing MAX */ i__1 = jw + max(lwk1,lwk2); lwkopt = max(i__1,lwk3); } /* ==== Quick return in case of workspace query. ==== */ if (*lwork == -1) { work[1] = (doublereal) lwkopt; return 0; } /* ==== Nothing to do ... ... for an empty active block ... ==== */ *ns = 0; *nd = 0; work[1] = 1.; if (*ktop > *kbot) { return 0; } /* ... nor for an empty deflation window. ==== */ if (*nw < 1) { return 0; } /* ==== Machine constants ==== */ safmin = igraphdlamch_("SAFE MINIMUM"); safmax = 1. / safmin; igraphdlabad_(&safmin, &safmax); ulp = igraphdlamch_("PRECISION"); smlnum = safmin * ((doublereal) (*n) / ulp); /* ==== Setup deflation window ==== Computing MIN */ i__1 = *nw, i__2 = *kbot - *ktop + 1; jw = min(i__1,i__2); kwtop = *kbot - jw + 1; if (kwtop == *ktop) { s = 0.; } else { s = h__[kwtop + (kwtop - 1) * h_dim1]; } if (*kbot == kwtop) { /* ==== 1-by-1 deflation window: not much to do ==== */ sr[kwtop] = h__[kwtop + kwtop * h_dim1]; si[kwtop] = 0.; *ns = 1; *nd = 0; /* Computing MAX */ d__2 = smlnum, d__3 = ulp * (d__1 = h__[kwtop + kwtop * h_dim1], abs( d__1)); if (abs(s) <= max(d__2,d__3)) { *ns = 0; *nd = 1; if (kwtop > *ktop) { h__[kwtop + (kwtop - 1) * h_dim1] = 0.; } } work[1] = 1.; return 0; } /* ==== Convert to spike-triangular form. (In case of a . rare QR failure, this routine continues to do . aggressive early deflation using that part of . the deflation window that converged using INFQR . here and there to keep track.) ==== */ igraphdlacpy_("U", &jw, &jw, &h__[kwtop + kwtop * h_dim1], ldh, &t[t_offset], ldt); i__1 = jw - 1; i__2 = *ldh + 1; i__3 = *ldt + 1; igraphdcopy_(&i__1, &h__[kwtop + 1 + kwtop * h_dim1], &i__2, &t[t_dim1 + 2], & i__3); igraphdlaset_("A", &jw, &jw, &c_b17, &c_b18, &v[v_offset], ldv); nmin = igraphilaenv_(&c__12, "DLAQR3", "SV", &jw, &c__1, &jw, lwork, (ftnlen)6, (ftnlen)2); if (jw > nmin) { igraphdlaqr4_(&c_true, &c_true, &jw, &c__1, &jw, &t[t_offset], ldt, &sr[ kwtop], &si[kwtop], &c__1, &jw, &v[v_offset], ldv, &work[1], lwork, &infqr); } else { igraphdlahqr_(&c_true, &c_true, &jw, &c__1, &jw, &t[t_offset], ldt, &sr[ kwtop], &si[kwtop], &c__1, &jw, &v[v_offset], ldv, &infqr); } /* ==== DTREXC needs a clean margin near the diagonal ==== */ i__1 = jw - 3; for (j = 1; j <= i__1; ++j) { t[j + 2 + j * t_dim1] = 0.; t[j + 3 + j * t_dim1] = 0.; /* L10: */ } if (jw > 2) { t[jw + (jw - 2) * t_dim1] = 0.; } /* ==== Deflation detection loop ==== */ *ns = jw; ilst = infqr + 1; L20: if (ilst <= *ns) { if (*ns == 1) { bulge = FALSE_; } else { bulge = t[*ns + (*ns - 1) * t_dim1] != 0.; } /* ==== Small spike tip test for deflation ==== */ if (! bulge) { /* ==== Real eigenvalue ==== */ foo = (d__1 = t[*ns + *ns * t_dim1], abs(d__1)); if (foo == 0.) { foo = abs(s); } /* Computing MAX */ d__2 = smlnum, d__3 = ulp * foo; if ((d__1 = s * v[*ns * v_dim1 + 1], abs(d__1)) <= max(d__2,d__3)) { /* ==== Deflatable ==== */ --(*ns); } else { /* ==== Undeflatable. Move it up out of the way. . (DTREXC can not fail in this case.) ==== */ ifst = *ns; igraphdtrexc_("V", &jw, &t[t_offset], ldt, &v[v_offset], ldv, &ifst, &ilst, &work[1], &info); ++ilst; } } else { /* ==== Complex conjugate pair ==== */ foo = (d__3 = t[*ns + *ns * t_dim1], abs(d__3)) + sqrt((d__1 = t[* ns + (*ns - 1) * t_dim1], abs(d__1))) * sqrt((d__2 = t[* ns - 1 + *ns * t_dim1], abs(d__2))); if (foo == 0.) { foo = abs(s); } /* Computing MAX */ d__3 = (d__1 = s * v[*ns * v_dim1 + 1], abs(d__1)), d__4 = (d__2 = s * v[(*ns - 1) * v_dim1 + 1], abs(d__2)); /* Computing MAX */ d__5 = smlnum, d__6 = ulp * foo; if (max(d__3,d__4) <= max(d__5,d__6)) { /* ==== Deflatable ==== */ *ns += -2; } else { /* ==== Undeflatable. Move them up out of the way. . Fortunately, DTREXC does the right thing with . ILST in case of a rare exchange failure. ==== */ ifst = *ns; igraphdtrexc_("V", &jw, &t[t_offset], ldt, &v[v_offset], ldv, &ifst, &ilst, &work[1], &info); ilst += 2; } } /* ==== End deflation detection loop ==== */ goto L20; } /* ==== Return to Hessenberg form ==== */ if (*ns == 0) { s = 0.; } if (*ns < jw) { /* ==== sorting diagonal blocks of T improves accuracy for . graded matrices. Bubble sort deals well with . exchange failures. ==== */ sorted = FALSE_; i__ = *ns + 1; L30: if (sorted) { goto L50; } sorted = TRUE_; kend = i__ - 1; i__ = infqr + 1; if (i__ == *ns) { k = i__ + 1; } else if (t[i__ + 1 + i__ * t_dim1] == 0.) { k = i__ + 1; } else { k = i__ + 2; } L40: if (k <= kend) { if (k == i__ + 1) { evi = (d__1 = t[i__ + i__ * t_dim1], abs(d__1)); } else { evi = (d__3 = t[i__ + i__ * t_dim1], abs(d__3)) + sqrt((d__1 = t[i__ + 1 + i__ * t_dim1], abs(d__1))) * sqrt((d__2 = t[i__ + (i__ + 1) * t_dim1], abs(d__2))); } if (k == kend) { evk = (d__1 = t[k + k * t_dim1], abs(d__1)); } else if (t[k + 1 + k * t_dim1] == 0.) { evk = (d__1 = t[k + k * t_dim1], abs(d__1)); } else { evk = (d__3 = t[k + k * t_dim1], abs(d__3)) + sqrt((d__1 = t[ k + 1 + k * t_dim1], abs(d__1))) * sqrt((d__2 = t[k + (k + 1) * t_dim1], abs(d__2))); } if (evi >= evk) { i__ = k; } else { sorted = FALSE_; ifst = i__; ilst = k; igraphdtrexc_("V", &jw, &t[t_offset], ldt, &v[v_offset], ldv, &ifst, &ilst, &work[1], &info); if (info == 0) { i__ = ilst; } else { i__ = k; } } if (i__ == kend) { k = i__ + 1; } else if (t[i__ + 1 + i__ * t_dim1] == 0.) { k = i__ + 1; } else { k = i__ + 2; } goto L40; } goto L30; L50: ; } /* ==== Restore shift/eigenvalue array from T ==== */ i__ = jw; L60: if (i__ >= infqr + 1) { if (i__ == infqr + 1) { sr[kwtop + i__ - 1] = t[i__ + i__ * t_dim1]; si[kwtop + i__ - 1] = 0.; --i__; } else if (t[i__ + (i__ - 1) * t_dim1] == 0.) { sr[kwtop + i__ - 1] = t[i__ + i__ * t_dim1]; si[kwtop + i__ - 1] = 0.; --i__; } else { aa = t[i__ - 1 + (i__ - 1) * t_dim1]; cc = t[i__ + (i__ - 1) * t_dim1]; bb = t[i__ - 1 + i__ * t_dim1]; dd = t[i__ + i__ * t_dim1]; igraphdlanv2_(&aa, &bb, &cc, &dd, &sr[kwtop + i__ - 2], &si[kwtop + i__ - 2], &sr[kwtop + i__ - 1], &si[kwtop + i__ - 1], &cs, & sn); i__ += -2; } goto L60; } if (*ns < jw || s == 0.) { if (*ns > 1 && s != 0.) { /* ==== Reflect spike back into lower triangle ==== */ igraphdcopy_(ns, &v[v_offset], ldv, &work[1], &c__1); beta = work[1]; igraphdlarfg_(ns, &beta, &work[2], &c__1, &tau); work[1] = 1.; i__1 = jw - 2; i__2 = jw - 2; igraphdlaset_("L", &i__1, &i__2, &c_b17, &c_b17, &t[t_dim1 + 3], ldt); igraphdlarf_("L", ns, &jw, &work[1], &c__1, &tau, &t[t_offset], ldt, & work[jw + 1]); igraphdlarf_("R", ns, ns, &work[1], &c__1, &tau, &t[t_offset], ldt, & work[jw + 1]); igraphdlarf_("R", &jw, ns, &work[1], &c__1, &tau, &v[v_offset], ldv, & work[jw + 1]); i__1 = *lwork - jw; igraphdgehrd_(&jw, &c__1, ns, &t[t_offset], ldt, &work[1], &work[jw + 1] , &i__1, &info); } /* ==== Copy updated reduced window into place ==== */ if (kwtop > 1) { h__[kwtop + (kwtop - 1) * h_dim1] = s * v[v_dim1 + 1]; } igraphdlacpy_("U", &jw, &jw, &t[t_offset], ldt, &h__[kwtop + kwtop * h_dim1] , ldh); i__1 = jw - 1; i__2 = *ldt + 1; i__3 = *ldh + 1; igraphdcopy_(&i__1, &t[t_dim1 + 2], &i__2, &h__[kwtop + 1 + kwtop * h_dim1], &i__3); /* ==== Accumulate orthogonal matrix in order update . H and Z, if requested. ==== */ if (*ns > 1 && s != 0.) { i__1 = *lwork - jw; igraphdormhr_("R", "N", &jw, ns, &c__1, ns, &t[t_offset], ldt, &work[1], &v[v_offset], ldv, &work[jw + 1], &i__1, &info); } /* ==== Update vertical slab in H ==== */ if (*wantt) { ltop = 1; } else { ltop = *ktop; } i__1 = kwtop - 1; i__2 = *nv; for (krow = ltop; i__2 < 0 ? krow >= i__1 : krow <= i__1; krow += i__2) { /* Computing MIN */ i__3 = *nv, i__4 = kwtop - krow; kln = min(i__3,i__4); igraphdgemm_("N", "N", &kln, &jw, &jw, &c_b18, &h__[krow + kwtop * h_dim1], ldh, &v[v_offset], ldv, &c_b17, &wv[wv_offset], ldwv); igraphdlacpy_("A", &kln, &jw, &wv[wv_offset], ldwv, &h__[krow + kwtop * h_dim1], ldh); /* L70: */ } /* ==== Update horizontal slab in H ==== */ if (*wantt) { i__2 = *n; i__1 = *nh; for (kcol = *kbot + 1; i__1 < 0 ? kcol >= i__2 : kcol <= i__2; kcol += i__1) { /* Computing MIN */ i__3 = *nh, i__4 = *n - kcol + 1; kln = min(i__3,i__4); igraphdgemm_("C", "N", &jw, &kln, &jw, &c_b18, &v[v_offset], ldv, & h__[kwtop + kcol * h_dim1], ldh, &c_b17, &t[t_offset], ldt); igraphdlacpy_("A", &jw, &kln, &t[t_offset], ldt, &h__[kwtop + kcol * h_dim1], ldh); /* L80: */ } } /* ==== Update vertical slab in Z ==== */ if (*wantz) { i__1 = *ihiz; i__2 = *nv; for (krow = *iloz; i__2 < 0 ? krow >= i__1 : krow <= i__1; krow += i__2) { /* Computing MIN */ i__3 = *nv, i__4 = *ihiz - krow + 1; kln = min(i__3,i__4); igraphdgemm_("N", "N", &kln, &jw, &jw, &c_b18, &z__[krow + kwtop * z_dim1], ldz, &v[v_offset], ldv, &c_b17, &wv[ wv_offset], ldwv); igraphdlacpy_("A", &kln, &jw, &wv[wv_offset], ldwv, &z__[krow + kwtop * z_dim1], ldz); /* L90: */ } } } /* ==== Return the number of deflations ... ==== */ *nd = jw - *ns; /* ==== ... and the number of shifts. (Subtracting . INFQR from the spike length takes care . of the case of a rare QR failure while . calculating eigenvalues of the deflation . window.) ==== */ *ns -= infqr; /* ==== Return optimal workspace. ==== */ work[1] = (doublereal) lwkopt; /* ==== End of DLAQR3 ==== */ return 0; } /* igraphdlaqr3_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dngets.c0000644000076500000240000002300613524616145024271 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static logical c_true = TRUE_; static integer c__1 = 1; /* ----------------------------------------------------------------------- \BeginDoc \Name: dngets \Description: Given the eigenvalues of the upper Hessenberg matrix H, computes the NP shifts AMU that are zeros of the polynomial of degree NP which filters out components of the unwanted eigenvectors corresponding to the AMU's based on some given criteria. NOTE: call this even in the case of user specified shifts in order to sort the eigenvalues, and error bounds of H for later use. \Usage: call dngets ( ISHIFT, WHICH, KEV, NP, RITZR, RITZI, BOUNDS, SHIFTR, SHIFTI ) \Arguments ISHIFT Integer. (INPUT) Method for selecting the implicit shifts at each iteration. ISHIFT = 0: user specified shifts ISHIFT = 1: exact shift with respect to the matrix H. WHICH Character*2. (INPUT) Shift selection criteria. 'LM' -> want the KEV eigenvalues of largest magnitude. 'SM' -> want the KEV eigenvalues of smallest magnitude. 'LR' -> want the KEV eigenvalues of largest real part. 'SR' -> want the KEV eigenvalues of smallest real part. 'LI' -> want the KEV eigenvalues of largest imaginary part. 'SI' -> want the KEV eigenvalues of smallest imaginary part. KEV Integer. (INPUT/OUTPUT) INPUT: KEV+NP is the size of the matrix H. OUTPUT: Possibly increases KEV by one to keep complex conjugate pairs together. NP Integer. (INPUT/OUTPUT) Number of implicit shifts to be computed. OUTPUT: Possibly decreases NP by one to keep complex conjugate pairs together. RITZR, Double precision array of length KEV+NP. (INPUT/OUTPUT) RITZI On INPUT, RITZR and RITZI contain the real and imaginary parts of the eigenvalues of H. On OUTPUT, RITZR and RITZI are sorted so that the unwanted eigenvalues are in the first NP locations and the wanted portion is in the last KEV locations. When exact shifts are selected, the unwanted part corresponds to the shifts to be applied. Also, if ISHIFT .eq. 1, the unwanted eigenvalues are further sorted so that the ones with largest Ritz values are first. BOUNDS Double precision array of length KEV+NP. (INPUT/OUTPUT) Error bounds corresponding to the ordering in RITZ. SHIFTR, SHIFTI *** USE deprecated as of version 2.1. *** \EndDoc ----------------------------------------------------------------------- \BeginLib \Local variables: xxxxxx real \Routines called: dsortc ARPACK sorting routine. dcopy Level 1 BLAS that copies one vector to another . \Author Danny Sorensen Phuong Vu Richard Lehoucq CRPC / Rice University Dept. of Computational & Houston, Texas Applied Mathematics Rice University Houston, Texas \Revision history: xx/xx/92: Version ' 2.1' \SCCS Information: @(#) FILE: ngets.F SID: 2.3 DATE OF SID: 4/20/96 RELEASE: 2 \Remarks 1. xxxx \EndLib ----------------------------------------------------------------------- Subroutine */ int igraphdngets_(integer *ishift, char *which, integer *kev, integer *np, doublereal *ritzr, doublereal *ritzi, doublereal *bounds, doublereal *shiftr, doublereal *shifti) { /* System generated locals */ integer i__1; /* Builtin functions */ integer s_cmp(char *, char *, ftnlen, ftnlen); /* Local variables */ real t0, t1; extern /* Subroutine */ int igraphdvout_(integer *, integer *, doublereal *, integer *, char *, ftnlen), igraphivout_(integer *, integer *, integer * , integer *, char *, ftnlen), igraphsecond_(real *); integer logfil, ndigit, mngets = 0; extern /* Subroutine */ int igraphdsortc_(char *, logical *, integer *, doublereal *, doublereal *, doublereal *); integer msglvl; real tngets = 0.; /* %----------------------------------------------------% | Include files for debugging and timing information | %----------------------------------------------------% %------------------% | Scalar Arguments | %------------------% %-----------------% | Array Arguments | %-----------------% %------------% | Parameters | %------------% %---------------% | Local Scalars | %---------------% %----------------------% | External Subroutines | %----------------------% %----------------------% | Intrinsics Functions | %----------------------% %-----------------------% | Executable Statements | %-----------------------% %-------------------------------% | Initialize timing statistics | | & message level for debugging | %-------------------------------% Parameter adjustments */ --bounds; --ritzi; --ritzr; --shiftr; --shifti; /* Function Body */ igraphsecond_(&t0); msglvl = mngets; /* %----------------------------------------------------% | LM, SM, LR, SR, LI, SI case. | | Sort the eigenvalues of H into the desired order | | and apply the resulting order to BOUNDS. | | The eigenvalues are sorted so that the wanted part | | are always in the last KEV locations. | | We first do a pre-processing sort in order to keep | | complex conjugate pairs together | %----------------------------------------------------% */ if (s_cmp(which, "LM", (ftnlen)2, (ftnlen)2) == 0) { i__1 = *kev + *np; igraphdsortc_("LR", &c_true, &i__1, &ritzr[1], &ritzi[1], &bounds[1]); } else if (s_cmp(which, "SM", (ftnlen)2, (ftnlen)2) == 0) { i__1 = *kev + *np; igraphdsortc_("SR", &c_true, &i__1, &ritzr[1], &ritzi[1], &bounds[1]); } else if (s_cmp(which, "LR", (ftnlen)2, (ftnlen)2) == 0) { i__1 = *kev + *np; igraphdsortc_("LM", &c_true, &i__1, &ritzr[1], &ritzi[1], &bounds[1]); } else if (s_cmp(which, "SR", (ftnlen)2, (ftnlen)2) == 0) { i__1 = *kev + *np; igraphdsortc_("SM", &c_true, &i__1, &ritzr[1], &ritzi[1], &bounds[1]); } else if (s_cmp(which, "LI", (ftnlen)2, (ftnlen)2) == 0) { i__1 = *kev + *np; igraphdsortc_("LM", &c_true, &i__1, &ritzr[1], &ritzi[1], &bounds[1]); } else if (s_cmp(which, "SI", (ftnlen)2, (ftnlen)2) == 0) { i__1 = *kev + *np; igraphdsortc_("SM", &c_true, &i__1, &ritzr[1], &ritzi[1], &bounds[1]); } i__1 = *kev + *np; igraphdsortc_(which, &c_true, &i__1, &ritzr[1], &ritzi[1], &bounds[1]); /* %-------------------------------------------------------% | Increase KEV by one if the ( ritzr(np),ritzi(np) ) | | = ( ritzr(np+1),-ritzi(np+1) ) and ritz(np) .ne. zero | | Accordingly decrease NP by one. In other words keep | | complex conjugate pairs together. | %-------------------------------------------------------% */ if (ritzr[*np + 1] - ritzr[*np] == 0. && ritzi[*np + 1] + ritzi[*np] == 0.) { --(*np); ++(*kev); } if (*ishift == 1) { /* %-------------------------------------------------------% | Sort the unwanted Ritz values used as shifts so that | | the ones with largest Ritz estimates are first | | This will tend to minimize the effects of the | | forward instability of the iteration when they shifts | | are applied in subroutine dnapps. | | Be careful and use 'SR' since we want to sort BOUNDS! | %-------------------------------------------------------% */ igraphdsortc_("SR", &c_true, np, &bounds[1], &ritzr[1], &ritzi[1]); } igraphsecond_(&t1); tngets += t1 - t0; if (msglvl > 0) { igraphivout_(&logfil, &c__1, kev, &ndigit, "_ngets: KEV is", (ftnlen)14); igraphivout_(&logfil, &c__1, np, &ndigit, "_ngets: NP is", (ftnlen)13); i__1 = *kev + *np; igraphdvout_(&logfil, &i__1, &ritzr[1], &ndigit, "_ngets: Eigenvalues of c" "urrent H matrix -- real part", (ftnlen)52); i__1 = *kev + *np; igraphdvout_(&logfil, &i__1, &ritzi[1], &ndigit, "_ngets: Eigenvalues of c" "urrent H matrix -- imag part", (ftnlen)52); i__1 = *kev + *np; igraphdvout_(&logfil, &i__1, &bounds[1], &ndigit, "_ngets: Ritz estimates " "of the current KEV+NP Ritz values", (ftnlen)56); } return 0; /* %---------------% | End of dngets | %---------------% */ } /* igraphdngets_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dneupd.c0000644000076500000240000013641213524616145024272 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static doublereal c_b3 = .66666666666666663; static integer c__1 = 1; static doublereal c_b44 = 0.; static doublereal c_b45 = 1.; static logical c_true = TRUE_; static doublereal c_b71 = -1.; /* \BeginDoc \Name: dneupd \Description: This subroutine returns the converged approximations to eigenvalues of A*z = lambda*B*z and (optionally): (1) The corresponding approximate eigenvectors; (2) An orthonormal basis for the associated approximate invariant subspace; (3) Both. There is negligible additional cost to obtain eigenvectors. An orthonormal basis is always computed. There is an additional storage cost of n*nev if both are requested (in this case a separate array Z must be supplied). The approximate eigenvalues and eigenvectors of A*z = lambda*B*z are derived from approximate eigenvalues and eigenvectors of of the linear operator OP prescribed by the MODE selection in the call to DNAUPD. DNAUPD must be called before this routine is called. These approximate eigenvalues and vectors are commonly called Ritz values and Ritz vectors respectively. They are referred to as such in the comments that follow. The computed orthonormal basis for the invariant subspace corresponding to these Ritz values is referred to as a Schur basis. See documentation in the header of the subroutine DNAUPD for definition of OP as well as other terms and the relation of computed Ritz values and Ritz vectors of OP with respect to the given problem A*z = lambda*B*z. For a brief description, see definitions of IPARAM(7), MODE and WHICH in the documentation of DNAUPD. \Usage: call dneupd ( RVEC, HOWMNY, SELECT, DR, DI, Z, LDZ, SIGMAR, SIGMAI, WORKEV, BMAT, N, WHICH, NEV, TOL, RESID, NCV, V, LDV, IPARAM, IPNTR, WORKD, WORKL, LWORKL, INFO ) \Arguments: RVEC LOGICAL (INPUT) Specifies whether a basis for the invariant subspace corresponding to the converged Ritz value approximations for the eigenproblem A*z = lambda*B*z is computed. RVEC = .FALSE. Compute Ritz values only. RVEC = .TRUE. Compute the Ritz vectors or Schur vectors. See Remarks below. HOWMNY Character*1 (INPUT) Specifies the form of the basis for the invariant subspace corresponding to the converged Ritz values that is to be computed. = 'A': Compute NEV Ritz vectors; = 'P': Compute NEV Schur vectors; = 'S': compute some of the Ritz vectors, specified by the logical array SELECT. SELECT Logical array of dimension NCV. (INPUT) If HOWMNY = 'S', SELECT specifies the Ritz vectors to be computed. To select the Ritz vector corresponding to a Ritz value (DR(j), DI(j)), SELECT(j) must be set to .TRUE.. If HOWMNY = 'A' or 'P', SELECT is used as internal workspace. DR Double precision array of dimension NEV+1. (OUTPUT) If IPARAM(7) = 1,2 or 3 and SIGMAI=0.0 then on exit: DR contains the real part of the Ritz approximations to the eigenvalues of A*z = lambda*B*z. If IPARAM(7) = 3, 4 and SIGMAI is not equal to zero, then on exit: DR contains the real part of the Ritz values of OP computed by DNAUPD. A further computation must be performed by the user to transform the Ritz values computed for OP by DNAUPD to those of the original system A*z = lambda*B*z. See remark 3 below. DI Double precision array of dimension NEV+1. (OUTPUT) On exit, DI contains the imaginary part of the Ritz value approximations to the eigenvalues of A*z = lambda*B*z associated with DR. NOTE: When Ritz values are complex, they will come in complex conjugate pairs. If eigenvectors are requested, the corresponding Ritz vectors will also come in conjugate pairs and the real and imaginary parts of these are represented in two consecutive columns of the array Z (see below). Z Double precision N by NEV+1 array if RVEC = .TRUE. and HOWMNY = 'A'. (OUTPUT) On exit, if RVEC = .TRUE. and HOWMNY = 'A', then the columns of Z represent approximate eigenvectors (Ritz vectors) corresponding to the NCONV=IPARAM(5) Ritz values for eigensystem A*z = lambda*B*z. The complex Ritz vector associated with the Ritz value with positive imaginary part is stored in two consecutive columns. The first column holds the real part of the Ritz vector and the second column holds the imaginary part. The Ritz vector associated with the Ritz value with negative imaginary part is simply the complex conjugate of the Ritz vector associated with the positive imaginary part. If RVEC = .FALSE. or HOWMNY = 'P', then Z is not referenced. NOTE: If if RVEC = .TRUE. and a Schur basis is not required, the array Z may be set equal to first NEV+1 columns of the Arnoldi basis array V computed by DNAUPD. In this case the Arnoldi basis will be destroyed and overwritten with the eigenvector basis. LDZ Integer. (INPUT) The leading dimension of the array Z. If Ritz vectors are desired, then LDZ >= max( 1, N ). In any case, LDZ >= 1. SIGMAR Double precision (INPUT) If IPARAM(7) = 3 or 4, represents the real part of the shift. Not referenced if IPARAM(7) = 1 or 2. SIGMAI Double precision (INPUT) If IPARAM(7) = 3 or 4, represents the imaginary part of the shift. Not referenced if IPARAM(7) = 1 or 2. See remark 3 below. WORKEV Double precision work array of dimension 3*NCV. (WORKSPACE) **** The remaining arguments MUST be the same as for the **** **** call to DNAUPD that was just completed. **** NOTE: The remaining arguments BMAT, N, WHICH, NEV, TOL, RESID, NCV, V, LDV, IPARAM, IPNTR, WORKD, WORKL, LWORKL, INFO must be passed directly to DNEUPD following the last call to DNAUPD. These arguments MUST NOT BE MODIFIED between the the last call to DNAUPD and the call to DNEUPD. Three of these parameters (V, WORKL, INFO) are also output parameters: V Double precision N by NCV array. (INPUT/OUTPUT) Upon INPUT: the NCV columns of V contain the Arnoldi basis vectors for OP as constructed by DNAUPD . Upon OUTPUT: If RVEC = .TRUE. the first NCONV=IPARAM(5) columns contain approximate Schur vectors that span the desired invariant subspace. See Remark 2 below. NOTE: If the array Z has been set equal to first NEV+1 columns of the array V and RVEC=.TRUE. and HOWMNY= 'A', then the Arnoldi basis held by V has been overwritten by the desired Ritz vectors. If a separate array Z has been passed then the first NCONV=IPARAM(5) columns of V will contain approximate Schur vectors that span the desired invariant subspace. WORKL Double precision work array of length LWORKL. (OUTPUT/WORKSPACE) WORKL(1:ncv*ncv+3*ncv) contains information obtained in dnaupd. They are not changed by dneupd. WORKL(ncv*ncv+3*ncv+1:3*ncv*ncv+6*ncv) holds the real and imaginary part of the untransformed Ritz values, the upper quasi-triangular matrix for H, and the associated matrix representation of the invariant subspace for H. Note: IPNTR(9:13) contains the pointer into WORKL for addresses of the above information computed by dneupd. ------------------------------------------------------------- IPNTR(9): pointer to the real part of the NCV RITZ values of the original system. IPNTR(10): pointer to the imaginary part of the NCV RITZ values of the original system. IPNTR(11): pointer to the NCV corresponding error bounds. IPNTR(12): pointer to the NCV by NCV upper quasi-triangular Schur matrix for H. IPNTR(13): pointer to the NCV by NCV matrix of eigenvectors of the upper Hessenberg matrix H. Only referenced by dneupd if RVEC = .TRUE. See Remark 2 below. ------------------------------------------------------------- INFO Integer. (OUTPUT) Error flag on output. = 0: Normal exit. = 1: The Schur form computed by LAPACK routine dlahqr could not be reordered by LAPACK routine dtrsen. Re-enter subroutine dneupd with IPARAM(5)=NCV and increase the size of the arrays DR and DI to have dimension at least dimension NCV and allocate at least NCV columns for Z. NOTE: Not necessary if Z and V share the same space. Please notify the authors if this error occurs. = -1: N must be positive. = -2: NEV must be positive. = -3: NCV-NEV >= 2 and less than or equal to N. = -5: WHICH must be one of 'LM', 'SM', 'LR', 'SR', 'LI', 'SI' = -6: BMAT must be one of 'I' or 'G'. = -7: Length of private work WORKL array is not sufficient. = -8: Error return from calculation of a real Schur form. Informational error from LAPACK routine dlahqr. = -9: Error return from calculation of eigenvectors. Informational error from LAPACK routine dtrevc. = -10: IPARAM(7) must be 1,2,3,4. = -11: IPARAM(7) = 1 and BMAT = 'G' are incompatible. = -12: HOWMNY = 'S' not yet implemented = -13: HOWMNY must be one of 'A' or 'P' if RVEC = .true. = -14: DNAUPD did not find any eigenvalues to sufficient accuracy. \BeginLib \References: 1. D.C. Sorensen, "Implicit Application of Polynomial Filters in a k-Step Arnoldi Method", SIAM J. Matr. Anal. Apps., 13 (1992), pp 357-385. 2. R.B. Lehoucq, "Analysis and Implementation of an Implicitly Restarted Arnoldi Iteration", Rice University Technical Report TR95-13, Department of Computational and Applied Mathematics. 3. B.N. Parlett & Y. Saad, "Complex Shift and Invert Strategies for Real Matrices", Linear Algebra and its Applications, vol 88/89, pp 575-595, (1987). \Routines called: ivout ARPACK utility routine that prints integers. dmout ARPACK utility routine that prints matrices dvout ARPACK utility routine that prints vectors. dgeqr2 LAPACK routine that computes the QR factorization of a matrix. dlacpy LAPACK matrix copy routine. dlahqr LAPACK routine to compute the real Schur form of an upper Hessenberg matrix. dlamch LAPACK routine that determines machine constants. dlapy2 LAPACK routine to compute sqrt(x**2+y**2) carefully. dlaset LAPACK matrix initialization routine. dorm2r LAPACK routine that applies an orthogonal matrix in factored form. dtrevc LAPACK routine to compute the eigenvectors of a matrix in upper quasi-triangular form. dtrsen LAPACK routine that re-orders the Schur form. dtrmm Level 3 BLAS matrix times an upper triangular matrix. dger Level 2 BLAS rank one update to a matrix. dcopy Level 1 BLAS that copies one vector to another . ddot Level 1 BLAS that computes the scalar product of two vectors. dnrm2 Level 1 BLAS that computes the norm of a vector. dscal Level 1 BLAS that scales a vector. \Remarks 1. Currently only HOWMNY = 'A' and 'P' are implemented. Let X' denote the transpose of X. 2. Schur vectors are an orthogonal representation for the basis of Ritz vectors. Thus, their numerical properties are often superior. If RVEC = .TRUE. then the relationship A * V(:,1:IPARAM(5)) = V(:,1:IPARAM(5)) * T, and V(:,1:IPARAM(5))' * V(:,1:IPARAM(5)) = I are approximately satisfied. Here T is the leading submatrix of order IPARAM(5) of the real upper quasi-triangular matrix stored workl(ipntr(12)). That is, T is block upper triangular with 1-by-1 and 2-by-2 diagonal blocks; each 2-by-2 diagonal block has its diagonal elements equal and its off-diagonal elements of opposite sign. Corresponding to each 2-by-2 diagonal block is a complex conjugate pair of Ritz values. The real Ritz values are stored on the diagonal of T. 3. If IPARAM(7) = 3 or 4 and SIGMAI is not equal zero, then the user must form the IPARAM(5) Rayleigh quotients in order to transform the Ritz values computed by DNAUPD for OP to those of A*z = lambda*B*z. Set RVEC = .true. and HOWMNY = 'A', and compute Z(:,I)' * A * Z(:,I) if DI(I) = 0. If DI(I) is not equal to zero and DI(I+1) = - D(I), then the desired real and imaginary parts of the Ritz value are Z(:,I)' * A * Z(:,I) + Z(:,I+1)' * A * Z(:,I+1), Z(:,I)' * A * Z(:,I+1) - Z(:,I+1)' * A * Z(:,I), respectively. Another possibility is to set RVEC = .true. and HOWMNY = 'P' and compute V(:,1:IPARAM(5))' * A * V(:,1:IPARAM(5)) and then an upper quasi-triangular matrix of order IPARAM(5) is computed. See remark 2 above. \Authors Danny Sorensen Phuong Vu Richard Lehoucq CRPC / Rice University Chao Yang Houston, Texas Dept. of Computational & Applied Mathematics Rice University Houston, Texas \SCCS Information: @(#) FILE: neupd.F SID: 2.5 DATE OF SID: 7/31/96 RELEASE: 2 \EndLib ----------------------------------------------------------------------- Subroutine */ int igraphdneupd_(logical *rvec, char *howmny, logical *select, doublereal *dr, doublereal *di, doublereal *z__, integer *ldz, doublereal *sigmar, doublereal *sigmai, doublereal *workev, char * bmat, integer *n, char *which, integer *nev, doublereal *tol, doublereal *resid, integer *ncv, doublereal *v, integer *ldv, integer *iparam, integer *ipntr, doublereal *workd, doublereal *workl, integer *lworkl, integer *info) { /* System generated locals */ integer v_dim1, v_offset, z_dim1, z_offset, i__1; doublereal d__1, d__2; /* Builtin functions */ double pow_dd(doublereal *, doublereal *); integer s_cmp(char *, char *, ftnlen, ftnlen); /* Subroutine */ int s_copy(char *, char *, ftnlen, ftnlen); /* Local variables */ integer j, k, ih; doublereal vl[1] /* was [1][1] */; integer ibd, ldh, ldq, iri; doublereal sep; integer irr, wri, wrr; extern /* Subroutine */ int igraphdger_(integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, integer *); integer mode; doublereal eps23; integer ierr; doublereal temp; integer iwev; char type__[6]; extern doublereal igraphdnrm2_(integer *, doublereal *, integer *); doublereal temp1; extern /* Subroutine */ int igraphdscal_(integer *, doublereal *, doublereal *, integer *); integer ihbds, iconj; extern /* Subroutine */ int igraphdgemv_(char *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *); doublereal conds; logical reord; extern /* Subroutine */ int igraphdcopy_(integer *, doublereal *, integer *, doublereal *, integer *); integer nconv; extern /* Subroutine */ int igraphdtrmm_(char *, char *, char *, char *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *); doublereal thres; extern /* Subroutine */ int igraphdmout_(integer *, integer *, integer *, doublereal *, integer *, integer *, char *, ftnlen); integer iwork[1]; doublereal rnorm; integer ritzi; extern /* Subroutine */ int igraphdvout_(integer *, integer *, doublereal *, integer *, char *, ftnlen), igraphivout_(integer *, integer *, integer * , integer *, char *, ftnlen); integer ritzr; extern /* Subroutine */ int igraphdgeqr2_(integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *); extern doublereal igraphdlapy2_(doublereal *, doublereal *); extern /* Subroutine */ int igraphdorm2r_(char *, char *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *); extern doublereal igraphdlamch_(char *); integer iheigi, iheigr; extern /* Subroutine */ int igraphdlahqr_(logical *, logical *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, integer *, integer *), igraphdlacpy_(char *, integer *, integer *, doublereal *, integer *, doublereal *, integer *), igraphdlaset_(char *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *); integer logfil, ndigit; extern /* Subroutine */ int igraphdtrevc_(char *, char *, logical *, integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, integer *, integer *, integer *, doublereal *, integer *); integer mneupd = 0, bounds; extern /* Subroutine */ int igraphdtrsen_(char *, char *, logical *, integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, integer *, integer *, integer *, integer *); integer msglvl, ktrord, invsub, iuptri, outncv; /* %----------------------------------------------------% | Include files for debugging and timing information | %----------------------------------------------------% %------------------% | Scalar Arguments | %------------------% %-----------------% | Array Arguments | %-----------------% %------------% | Parameters | %------------% %---------------% | Local Scalars | %---------------% %----------------------% | External Subroutines | %----------------------% %--------------------% | External Functions | %--------------------% %---------------------% | Intrinsic Functions | %---------------------% %-----------------------% | Executable Statements | %-----------------------% %------------------------% | Set default parameters | %------------------------% Parameter adjustments */ z_dim1 = *ldz; z_offset = 1 + z_dim1; z__ -= z_offset; --workd; --resid; --di; --dr; --workev; --select; v_dim1 = *ldv; v_offset = 1 + v_dim1; v -= v_offset; --iparam; --ipntr; --workl; /* Function Body */ msglvl = mneupd; mode = iparam[7]; nconv = iparam[5]; *info = 0; /* %---------------------------------% | Get machine dependent constant. | %---------------------------------% */ eps23 = igraphdlamch_("Epsilon-Machine"); eps23 = pow_dd(&eps23, &c_b3); /* %--------------% | Quick return | %--------------% */ ierr = 0; if (nconv <= 0) { ierr = -14; } else if (*n <= 0) { ierr = -1; } else if (*nev <= 0) { ierr = -2; } else if (*ncv <= *nev + 1 || *ncv > *n) { ierr = -3; } else if (s_cmp(which, "LM", (ftnlen)2, (ftnlen)2) != 0 && s_cmp(which, "SM", (ftnlen)2, (ftnlen)2) != 0 && s_cmp(which, "LR", (ftnlen)2, (ftnlen)2) != 0 && s_cmp(which, "SR", (ftnlen)2, (ftnlen)2) != 0 && s_cmp(which, "LI", (ftnlen)2, (ftnlen)2) != 0 && s_cmp(which, "SI", (ftnlen)2, (ftnlen)2) != 0) { ierr = -5; } else if (*(unsigned char *)bmat != 'I' && *(unsigned char *)bmat != 'G') { ierr = -6; } else /* if(complicated condition) */ { /* Computing 2nd power */ i__1 = *ncv; if (*lworkl < i__1 * i__1 * 3 + *ncv * 6) { ierr = -7; } else if (*(unsigned char *)howmny != 'A' && *(unsigned char *) howmny != 'P' && *(unsigned char *)howmny != 'S' && *rvec) { ierr = -13; } else if (*(unsigned char *)howmny == 'S') { ierr = -12; } } if (mode == 1 || mode == 2) { s_copy(type__, "REGULR", (ftnlen)6, (ftnlen)6); } else if (mode == 3 && *sigmai == 0.) { s_copy(type__, "SHIFTI", (ftnlen)6, (ftnlen)6); } else if (mode == 3) { s_copy(type__, "REALPT", (ftnlen)6, (ftnlen)6); } else if (mode == 4) { s_copy(type__, "IMAGPT", (ftnlen)6, (ftnlen)6); } else { ierr = -10; } if (mode == 1 && *(unsigned char *)bmat == 'G') { ierr = -11; } /* %------------% | Error Exit | %------------% */ if (ierr != 0) { *info = ierr; goto L9000; } /* %--------------------------------------------------------% | Pointer into WORKL for address of H, RITZ, BOUNDS, Q | | etc... and the remaining workspace. | | Also update pointer to be used on output. | | Memory is laid out as follows: | | workl(1:ncv*ncv) := generated Hessenberg matrix | | workl(ncv*ncv+1:ncv*ncv+2*ncv) := real and imaginary | | parts of ritz values | | workl(ncv*ncv+2*ncv+1:ncv*ncv+3*ncv) := error bounds | %--------------------------------------------------------% %-----------------------------------------------------------% | The following is used and set by DNEUPD. | | workl(ncv*ncv+3*ncv+1:ncv*ncv+4*ncv) := The untransformed | | real part of the Ritz values. | | workl(ncv*ncv+4*ncv+1:ncv*ncv+5*ncv) := The untransformed | | imaginary part of the Ritz values. | | workl(ncv*ncv+5*ncv+1:ncv*ncv+6*ncv) := The untransformed | | error bounds of the Ritz values | | workl(ncv*ncv+6*ncv+1:2*ncv*ncv+6*ncv) := Holds the upper | | quasi-triangular matrix for H | | workl(2*ncv*ncv+6*ncv+1: 3*ncv*ncv+6*ncv) := Holds the | | associated matrix representation of the invariant | | subspace for H. | | GRAND total of NCV * ( 3 * NCV + 6 ) locations. | %-----------------------------------------------------------% */ ih = ipntr[5]; ritzr = ipntr[6]; ritzi = ipntr[7]; bounds = ipntr[8]; ldh = *ncv; ldq = *ncv; iheigr = bounds + ldh; iheigi = iheigr + ldh; ihbds = iheigi + ldh; iuptri = ihbds + ldh; invsub = iuptri + ldh * *ncv; ipntr[9] = iheigr; ipntr[10] = iheigi; ipntr[11] = ihbds; ipntr[12] = iuptri; ipntr[13] = invsub; wrr = 1; wri = *ncv + 1; iwev = wri + *ncv; /* %-----------------------------------------% | irr points to the REAL part of the Ritz | | values computed by _neigh before | | exiting _naup2. | | iri points to the IMAGINARY part of the | | Ritz values computed by _neigh | | before exiting _naup2. | | ibd points to the Ritz estimates | | computed by _neigh before exiting | | _naup2. | %-----------------------------------------% */ irr = ipntr[14] + *ncv * *ncv; iri = irr + *ncv; ibd = iri + *ncv; /* %------------------------------------% | RNORM is B-norm of the RESID(1:N). | %------------------------------------% */ rnorm = workl[ih + 2]; workl[ih + 2] = 0.; if (*rvec) { /* %-------------------------------------------% | Get converged Ritz value on the boundary. | | Note: converged Ritz values have been | | placed in the first NCONV locations in | | workl(ritzr) and workl(ritzi). They have | | been sorted (in _naup2) according to the | | WHICH selection criterion. | %-------------------------------------------% */ if (s_cmp(which, "LM", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(which, "SM", (ftnlen)2, (ftnlen)2) == 0) { thres = igraphdlapy2_(&workl[ritzr], &workl[ritzi]); } else if (s_cmp(which, "LR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp( which, "SR", (ftnlen)2, (ftnlen)2) == 0) { thres = workl[ritzr]; } else if (s_cmp(which, "LI", (ftnlen)2, (ftnlen)2) == 0 || s_cmp( which, "SI", (ftnlen)2, (ftnlen)2) == 0) { thres = (d__1 = workl[ritzi], abs(d__1)); } if (msglvl > 2) { igraphdvout_(&logfil, &c__1, &thres, &ndigit, "_neupd: Threshold eigen" "value used for re-ordering", (ftnlen)49); } /* %----------------------------------------------------------% | Check to see if all converged Ritz values appear at the | | top of the upper quasi-triangular matrix computed by | | _neigh in _naup2. This is done in the following way: | | | | 1) For each Ritz value obtained from _neigh, compare it | | with the threshold Ritz value computed above to | | determine whether it is a wanted one. | | | | 2) If it is wanted, then check the corresponding Ritz | | estimate to see if it has converged. If it has, set | | correponding entry in the logical array SELECT to | | .TRUE.. | | | | If SELECT(j) = .TRUE. and j > NCONV, then there is a | | converged Ritz value that does not appear at the top of | | the upper quasi-triangular matrix computed by _neigh in | | _naup2. Reordering is needed. | %----------------------------------------------------------% */ reord = FALSE_; ktrord = 0; i__1 = *ncv - 1; for (j = 0; j <= i__1; ++j) { select[j + 1] = FALSE_; if (s_cmp(which, "LM", (ftnlen)2, (ftnlen)2) == 0) { if (igraphdlapy2_(&workl[irr + j], &workl[iri + j]) >= thres) { /* Computing MAX */ d__1 = eps23, d__2 = igraphdlapy2_(&workl[irr + j], &workl[iri + j]); temp1 = max(d__1,d__2); if (workl[ibd + j] <= *tol * temp1) { select[j + 1] = TRUE_; } } } else if (s_cmp(which, "SM", (ftnlen)2, (ftnlen)2) == 0) { if (igraphdlapy2_(&workl[irr + j], &workl[iri + j]) <= thres) { /* Computing MAX */ d__1 = eps23, d__2 = igraphdlapy2_(&workl[irr + j], &workl[iri + j]); temp1 = max(d__1,d__2); if (workl[ibd + j] <= *tol * temp1) { select[j + 1] = TRUE_; } } } else if (s_cmp(which, "LR", (ftnlen)2, (ftnlen)2) == 0) { if (workl[irr + j] >= thres) { /* Computing MAX */ d__1 = eps23, d__2 = igraphdlapy2_(&workl[irr + j], &workl[iri + j]); temp1 = max(d__1,d__2); if (workl[ibd + j] <= *tol * temp1) { select[j + 1] = TRUE_; } } } else if (s_cmp(which, "SR", (ftnlen)2, (ftnlen)2) == 0) { if (workl[irr + j] <= thres) { /* Computing MAX */ d__1 = eps23, d__2 = igraphdlapy2_(&workl[irr + j], &workl[iri + j]); temp1 = max(d__1,d__2); if (workl[ibd + j] <= *tol * temp1) { select[j + 1] = TRUE_; } } } else if (s_cmp(which, "LI", (ftnlen)2, (ftnlen)2) == 0) { if ((d__1 = workl[iri + j], abs(d__1)) >= thres) { /* Computing MAX */ d__1 = eps23, d__2 = igraphdlapy2_(&workl[irr + j], &workl[iri + j]); temp1 = max(d__1,d__2); if (workl[ibd + j] <= *tol * temp1) { select[j + 1] = TRUE_; } } } else if (s_cmp(which, "SI", (ftnlen)2, (ftnlen)2) == 0) { if ((d__1 = workl[iri + j], abs(d__1)) <= thres) { /* Computing MAX */ d__1 = eps23, d__2 = igraphdlapy2_(&workl[irr + j], &workl[iri + j]); temp1 = max(d__1,d__2); if (workl[ibd + j] <= *tol * temp1) { select[j + 1] = TRUE_; } } } if (j + 1 > nconv) { reord = select[j + 1] || reord; } if (select[j + 1]) { ++ktrord; } /* L10: */ } if (msglvl > 2) { igraphivout_(&logfil, &c__1, &ktrord, &ndigit, "_neupd: Number of spec" "ified eigenvalues", (ftnlen)39); igraphivout_(&logfil, &c__1, &nconv, &ndigit, "_neupd: Number of \"con" "verged\" eigenvalues", (ftnlen)41); } /* %-----------------------------------------------------------% | Call LAPACK routine dlahqr to compute the real Schur form | | of the upper Hessenberg matrix returned by DNAUPD. | | Make a copy of the upper Hessenberg matrix. | | Initialize the Schur vector matrix Q to the identity. | %-----------------------------------------------------------% */ i__1 = ldh * *ncv; igraphdcopy_(&i__1, &workl[ih], &c__1, &workl[iuptri], &c__1); igraphdlaset_("All", ncv, ncv, &c_b44, &c_b45, &workl[invsub], &ldq); igraphdlahqr_(&c_true, &c_true, ncv, &c__1, ncv, &workl[iuptri], &ldh, & workl[iheigr], &workl[iheigi], &c__1, ncv, &workl[invsub], & ldq, &ierr); igraphdcopy_(ncv, &workl[invsub + *ncv - 1], &ldq, &workl[ihbds], &c__1); if (ierr != 0) { *info = -8; goto L9000; } if (msglvl > 1) { igraphdvout_(&logfil, ncv, &workl[iheigr], &ndigit, "_neupd: Real part" " of the eigenvalues of H", (ftnlen)41); igraphdvout_(&logfil, ncv, &workl[iheigi], &ndigit, "_neupd: Imaginary" " part of the Eigenvalues of H", (ftnlen)46); igraphdvout_(&logfil, ncv, &workl[ihbds], &ndigit, "_neupd: Last row o" "f the Schur vector matrix", (ftnlen)43); if (msglvl > 3) { igraphdmout_(&logfil, ncv, ncv, &workl[iuptri], &ldh, &ndigit, "_neupd: The upper quasi-triangular matrix ", (ftnlen) 42); } } if (reord) { /* %-----------------------------------------------------% | Reorder the computed upper quasi-triangular matrix. | %-----------------------------------------------------% */ igraphdtrsen_("None", "V", &select[1], ncv, &workl[iuptri], &ldh, & workl[invsub], &ldq, &workl[iheigr], &workl[iheigi], & nconv, &conds, &sep, &workl[ihbds], ncv, iwork, &c__1, & ierr); if (ierr == 1) { *info = 1; goto L9000; } if (msglvl > 2) { igraphdvout_(&logfil, ncv, &workl[iheigr], &ndigit, "_neupd: Real " "part of the eigenvalues of H--reordered", (ftnlen)52); igraphdvout_(&logfil, ncv, &workl[iheigi], &ndigit, "_neupd: Imag " "part of the eigenvalues of H--reordered", (ftnlen)52); if (msglvl > 3) { igraphdmout_(&logfil, ncv, ncv, &workl[iuptri], &ldq, &ndigit, "_neupd: Quasi-triangular matrix after re-orderi" "ng", (ftnlen)49); } } } /* %---------------------------------------% | Copy the last row of the Schur vector | | into workl(ihbds). This will be used | | to compute the Ritz estimates of | | converged Ritz values. | %---------------------------------------% */ igraphdcopy_(ncv, &workl[invsub + *ncv - 1], &ldq, &workl[ihbds], &c__1); /* %----------------------------------------------------% | Place the computed eigenvalues of H into DR and DI | | if a spectral transformation was not used. | %----------------------------------------------------% */ if (s_cmp(type__, "REGULR", (ftnlen)6, (ftnlen)6) == 0) { igraphdcopy_(&nconv, &workl[iheigr], &c__1, &dr[1], &c__1); igraphdcopy_(&nconv, &workl[iheigi], &c__1, &di[1], &c__1); } /* %----------------------------------------------------------% | Compute the QR factorization of the matrix representing | | the wanted invariant subspace located in the first NCONV | | columns of workl(invsub,ldq). | %----------------------------------------------------------% */ igraphdgeqr2_(ncv, &nconv, &workl[invsub], &ldq, &workev[1], &workev[*ncv + 1], &ierr); /* %---------------------------------------------------------% | * Postmultiply V by Q using dorm2r. | | * Copy the first NCONV columns of VQ into Z. | | * Postmultiply Z by R. | | The N by NCONV matrix Z is now a matrix representation | | of the approximate invariant subspace associated with | | the Ritz values in workl(iheigr) and workl(iheigi) | | The first NCONV columns of V are now approximate Schur | | vectors associated with the real upper quasi-triangular | | matrix of order NCONV in workl(iuptri) | %---------------------------------------------------------% */ igraphdorm2r_("Right", "Notranspose", n, ncv, &nconv, &workl[invsub], &ldq, &workev[1], &v[v_offset], ldv, &workd[*n + 1], &ierr); igraphdlacpy_("All", n, &nconv, &v[v_offset], ldv, &z__[z_offset], ldz); i__1 = nconv; for (j = 1; j <= i__1; ++j) { /* %---------------------------------------------------% | Perform both a column and row scaling if the | | diagonal element of workl(invsub,ldq) is negative | | I'm lazy and don't take advantage of the upper | | quasi-triangular form of workl(iuptri,ldq) | | Note that since Q is orthogonal, R is a diagonal | | matrix consisting of plus or minus ones | %---------------------------------------------------% */ if (workl[invsub + (j - 1) * ldq + j - 1] < 0.) { igraphdscal_(&nconv, &c_b71, &workl[iuptri + j - 1], &ldq); igraphdscal_(&nconv, &c_b71, &workl[iuptri + (j - 1) * ldq], &c__1); } /* L20: */ } if (*(unsigned char *)howmny == 'A') { /* %--------------------------------------------% | Compute the NCONV wanted eigenvectors of T | | located in workl(iuptri,ldq). | %--------------------------------------------% */ i__1 = *ncv; for (j = 1; j <= i__1; ++j) { if (j <= nconv) { select[j] = TRUE_; } else { select[j] = FALSE_; } /* L30: */ } igraphdtrevc_("Right", "Select", &select[1], ncv, &workl[iuptri], &ldq, vl, &c__1, &workl[invsub], &ldq, ncv, &outncv, &workev[1], &ierr); if (ierr != 0) { *info = -9; goto L9000; } /* %------------------------------------------------% | Scale the returning eigenvectors so that their | | Euclidean norms are all one. LAPACK subroutine | | dtrevc returns each eigenvector normalized so | | that the element of largest magnitude has | | magnitude 1; | %------------------------------------------------% */ iconj = 0; i__1 = nconv; for (j = 1; j <= i__1; ++j) { if (workl[iheigi + j - 1] == 0.) { /* %----------------------% | real eigenvalue case | %----------------------% */ temp = igraphdnrm2_(ncv, &workl[invsub + (j - 1) * ldq], &c__1); d__1 = 1. / temp; igraphdscal_(ncv, &d__1, &workl[invsub + (j - 1) * ldq], &c__1); } else { /* %-------------------------------------------% | Complex conjugate pair case. Note that | | since the real and imaginary part of | | the eigenvector are stored in consecutive | | columns, we further normalize by the | | square root of two. | %-------------------------------------------% */ if (iconj == 0) { d__1 = igraphdnrm2_(ncv, &workl[invsub + (j - 1) * ldq], & c__1); d__2 = igraphdnrm2_(ncv, &workl[invsub + j * ldq], &c__1); temp = igraphdlapy2_(&d__1, &d__2); d__1 = 1. / temp; igraphdscal_(ncv, &d__1, &workl[invsub + (j - 1) * ldq], & c__1); d__1 = 1. / temp; igraphdscal_(ncv, &d__1, &workl[invsub + j * ldq], &c__1); iconj = 1; } else { iconj = 0; } } /* L40: */ } igraphdgemv_("T", ncv, &nconv, &c_b45, &workl[invsub], &ldq, &workl[ ihbds], &c__1, &c_b44, &workev[1], &c__1); iconj = 0; i__1 = nconv; for (j = 1; j <= i__1; ++j) { if (workl[iheigi + j - 1] != 0.) { /* %-------------------------------------------% | Complex conjugate pair case. Note that | | since the real and imaginary part of | | the eigenvector are stored in consecutive | %-------------------------------------------% */ if (iconj == 0) { workev[j] = igraphdlapy2_(&workev[j], &workev[j + 1]); workev[j + 1] = workev[j]; iconj = 1; } else { iconj = 0; } } /* L45: */ } if (msglvl > 2) { igraphdcopy_(ncv, &workl[invsub + *ncv - 1], &ldq, &workl[ihbds], & c__1); igraphdvout_(&logfil, ncv, &workl[ihbds], &ndigit, "_neupd: Last r" "ow of the eigenvector matrix for T", (ftnlen)48); if (msglvl > 3) { igraphdmout_(&logfil, ncv, ncv, &workl[invsub], &ldq, &ndigit, "_neupd: The eigenvector matrix for T", (ftnlen) 36); } } /* %---------------------------------------% | Copy Ritz estimates into workl(ihbds) | %---------------------------------------% */ igraphdcopy_(&nconv, &workev[1], &c__1, &workl[ihbds], &c__1); /* %---------------------------------------------------------% | Compute the QR factorization of the eigenvector matrix | | associated with leading portion of T in the first NCONV | | columns of workl(invsub,ldq). | %---------------------------------------------------------% */ igraphdgeqr2_(ncv, &nconv, &workl[invsub], &ldq, &workev[1], &workev[* ncv + 1], &ierr); /* %----------------------------------------------% | * Postmultiply Z by Q. | | * Postmultiply Z by R. | | The N by NCONV matrix Z is now contains the | | Ritz vectors associated with the Ritz values | | in workl(iheigr) and workl(iheigi). | %----------------------------------------------% */ igraphdorm2r_("Right", "Notranspose", n, ncv, &nconv, &workl[invsub], & ldq, &workev[1], &z__[z_offset], ldz, &workd[*n + 1], & ierr); igraphdtrmm_("Right", "Upper", "No transpose", "Non-unit", n, &nconv, & c_b45, &workl[invsub], &ldq, &z__[z_offset], ldz); } } else { /* %------------------------------------------------------% | An approximate invariant subspace is not needed. | | Place the Ritz values computed DNAUPD into DR and DI | %------------------------------------------------------% */ igraphdcopy_(&nconv, &workl[ritzr], &c__1, &dr[1], &c__1); igraphdcopy_(&nconv, &workl[ritzi], &c__1, &di[1], &c__1); igraphdcopy_(&nconv, &workl[ritzr], &c__1, &workl[iheigr], &c__1); igraphdcopy_(&nconv, &workl[ritzi], &c__1, &workl[iheigi], &c__1); igraphdcopy_(&nconv, &workl[bounds], &c__1, &workl[ihbds], &c__1); } /* %------------------------------------------------% | Transform the Ritz values and possibly vectors | | and corresponding error bounds of OP to those | | of A*x = lambda*B*x. | %------------------------------------------------% */ if (s_cmp(type__, "REGULR", (ftnlen)6, (ftnlen)6) == 0) { if (*rvec) { igraphdscal_(ncv, &rnorm, &workl[ihbds], &c__1); } } else { /* %---------------------------------------% | A spectral transformation was used. | | * Determine the Ritz estimates of the | | Ritz values in the original system. | %---------------------------------------% */ if (s_cmp(type__, "SHIFTI", (ftnlen)6, (ftnlen)6) == 0) { if (*rvec) { igraphdscal_(ncv, &rnorm, &workl[ihbds], &c__1); } i__1 = *ncv; for (k = 1; k <= i__1; ++k) { temp = igraphdlapy2_(&workl[iheigr + k - 1], &workl[iheigi + k - 1]) ; workl[ihbds + k - 1] = (d__1 = workl[ihbds + k - 1], abs(d__1) ) / temp / temp; /* L50: */ } } else if (s_cmp(type__, "REALPT", (ftnlen)6, (ftnlen)6) == 0) { i__1 = *ncv; for (k = 1; k <= i__1; ++k) { /* L60: */ } } else if (s_cmp(type__, "IMAGPT", (ftnlen)6, (ftnlen)6) == 0) { i__1 = *ncv; for (k = 1; k <= i__1; ++k) { /* L70: */ } } /* %-----------------------------------------------------------% | * Transform the Ritz values back to the original system. | | For TYPE = 'SHIFTI' the transformation is | | lambda = 1/theta + sigma | | For TYPE = 'REALPT' or 'IMAGPT' the user must from | | Rayleigh quotients or a projection. See remark 3 above.| | NOTES: | | *The Ritz vectors are not affected by the transformation. | %-----------------------------------------------------------% */ if (s_cmp(type__, "SHIFTI", (ftnlen)6, (ftnlen)6) == 0) { i__1 = *ncv; for (k = 1; k <= i__1; ++k) { temp = igraphdlapy2_(&workl[iheigr + k - 1], &workl[iheigi + k - 1]) ; workl[iheigr + k - 1] = workl[iheigr + k - 1] / temp / temp + *sigmar; workl[iheigi + k - 1] = -workl[iheigi + k - 1] / temp / temp + *sigmai; /* L80: */ } igraphdcopy_(&nconv, &workl[iheigr], &c__1, &dr[1], &c__1); igraphdcopy_(&nconv, &workl[iheigi], &c__1, &di[1], &c__1); } else if (s_cmp(type__, "REALPT", (ftnlen)6, (ftnlen)6) == 0 || s_cmp(type__, "IMAGPT", (ftnlen)6, (ftnlen)6) == 0) { igraphdcopy_(&nconv, &workl[iheigr], &c__1, &dr[1], &c__1); igraphdcopy_(&nconv, &workl[iheigi], &c__1, &di[1], &c__1); } } if (s_cmp(type__, "SHIFTI", (ftnlen)6, (ftnlen)6) == 0 && msglvl > 1) { igraphdvout_(&logfil, &nconv, &dr[1], &ndigit, "_neupd: Untransformed real" " part of the Ritz valuess.", (ftnlen)52); igraphdvout_(&logfil, &nconv, &di[1], &ndigit, "_neupd: Untransformed imag" " part of the Ritz valuess.", (ftnlen)52); igraphdvout_(&logfil, &nconv, &workl[ihbds], &ndigit, "_neupd: Ritz estima" "tes of untransformed Ritz values.", (ftnlen)52); } else if (s_cmp(type__, "REGULR", (ftnlen)6, (ftnlen)6) == 0 && msglvl > 1) { igraphdvout_(&logfil, &nconv, &dr[1], &ndigit, "_neupd: Real parts of conv" "erged Ritz values.", (ftnlen)44); igraphdvout_(&logfil, &nconv, &di[1], &ndigit, "_neupd: Imag parts of conv" "erged Ritz values.", (ftnlen)44); igraphdvout_(&logfil, &nconv, &workl[ihbds], &ndigit, "_neupd: Associated " "Ritz estimates.", (ftnlen)34); } /* %-------------------------------------------------% | Eigenvector Purification step. Formally perform | | one of inverse subspace iteration. Only used | | for MODE = 2. | %-------------------------------------------------% */ if (*rvec && *(unsigned char *)howmny == 'A' && s_cmp(type__, "SHIFTI", ( ftnlen)6, (ftnlen)6) == 0) { /* %------------------------------------------------% | Purify the computed Ritz vectors by adding a | | little bit of the residual vector: | | T | | resid(:)*( e s ) / theta | | NCV | | where H s = s theta. Remember that when theta | | has nonzero imaginary part, the corresponding | | Ritz vector is stored across two columns of Z. | %------------------------------------------------% */ iconj = 0; i__1 = nconv; for (j = 1; j <= i__1; ++j) { if (workl[iheigi + j - 1] == 0.) { workev[j] = workl[invsub + (j - 1) * ldq + *ncv - 1] / workl[ iheigr + j - 1]; } else if (iconj == 0) { temp = igraphdlapy2_(&workl[iheigr + j - 1], &workl[iheigi + j - 1]) ; workev[j] = (workl[invsub + (j - 1) * ldq + *ncv - 1] * workl[ iheigr + j - 1] + workl[invsub + j * ldq + *ncv - 1] * workl[iheigi + j - 1]) / temp / temp; workev[j + 1] = (workl[invsub + j * ldq + *ncv - 1] * workl[ iheigr + j - 1] - workl[invsub + (j - 1) * ldq + *ncv - 1] * workl[iheigi + j - 1]) / temp / temp; iconj = 1; } else { iconj = 0; } /* L110: */ } /* %---------------------------------------% | Perform a rank one update to Z and | | purify all the Ritz vectors together. | %---------------------------------------% */ igraphdger_(n, &nconv, &c_b45, &resid[1], &c__1, &workev[1], &c__1, &z__[ z_offset], ldz); } L9000: return 0; /* %---------------% | End of DNEUPD | %---------------% */ } /* igraphdneupd_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlarf.c0000644000076500000240000001645713524616145024111 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static doublereal c_b4 = 1.; static doublereal c_b5 = 0.; static integer c__1 = 1; /* > \brief \b DLARF applies an elementary reflector to a general rectangular matrix. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLARF + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLARF( SIDE, M, N, V, INCV, TAU, C, LDC, WORK ) CHARACTER SIDE INTEGER INCV, LDC, M, N DOUBLE PRECISION TAU DOUBLE PRECISION C( LDC, * ), V( * ), WORK( * ) > \par Purpose: ============= > > \verbatim > > DLARF applies a real elementary reflector H to a real m by n matrix > C, from either the left or the right. H is represented in the form > > H = I - tau * v * v**T > > where tau is a real scalar and v is a real vector. > > If tau = 0, then H is taken to be the unit matrix. > \endverbatim Arguments: ========== > \param[in] SIDE > \verbatim > SIDE is CHARACTER*1 > = 'L': form H * C > = 'R': form C * H > \endverbatim > > \param[in] M > \verbatim > M is INTEGER > The number of rows of the matrix C. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The number of columns of the matrix C. > \endverbatim > > \param[in] V > \verbatim > V is DOUBLE PRECISION array, dimension > (1 + (M-1)*abs(INCV)) if SIDE = 'L' > or (1 + (N-1)*abs(INCV)) if SIDE = 'R' > The vector v in the representation of H. V is not used if > TAU = 0. > \endverbatim > > \param[in] INCV > \verbatim > INCV is INTEGER > The increment between elements of v. INCV <> 0. > \endverbatim > > \param[in] TAU > \verbatim > TAU is DOUBLE PRECISION > The value tau in the representation of H. > \endverbatim > > \param[in,out] C > \verbatim > C is DOUBLE PRECISION array, dimension (LDC,N) > On entry, the m by n matrix C. > On exit, C is overwritten by the matrix H * C if SIDE = 'L', > or C * H if SIDE = 'R'. > \endverbatim > > \param[in] LDC > \verbatim > LDC is INTEGER > The leading dimension of the array C. LDC >= max(1,M). > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension > (N) if SIDE = 'L' > or (M) if SIDE = 'R' > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleOTHERauxiliary ===================================================================== Subroutine */ int igraphdlarf_(char *side, integer *m, integer *n, doublereal *v, integer *incv, doublereal *tau, doublereal *c__, integer *ldc, doublereal *work) { /* System generated locals */ integer c_dim1, c_offset; doublereal d__1; /* Local variables */ integer i__; logical applyleft; extern /* Subroutine */ int igraphdger_(integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, integer *); extern logical igraphlsame_(char *, char *); extern /* Subroutine */ int igraphdgemv_(char *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *); integer lastc, lastv; extern integer igraphiladlc_(integer *, integer *, doublereal *, integer *), igraphiladlr_(integer *, integer *, doublereal *, integer *); /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ --v; c_dim1 = *ldc; c_offset = 1 + c_dim1; c__ -= c_offset; --work; /* Function Body */ applyleft = igraphlsame_(side, "L"); lastv = 0; lastc = 0; if (*tau != 0.) { /* Set up variables for scanning V. LASTV begins pointing to the end of V. */ if (applyleft) { lastv = *m; } else { lastv = *n; } if (*incv > 0) { i__ = (lastv - 1) * *incv + 1; } else { i__ = 1; } /* Look for the last non-zero row in V. */ while(lastv > 0 && v[i__] == 0.) { --lastv; i__ -= *incv; } if (applyleft) { /* Scan for the last non-zero column in C(1:lastv,:). */ lastc = igraphiladlc_(&lastv, n, &c__[c_offset], ldc); } else { /* Scan for the last non-zero row in C(:,1:lastv). */ lastc = igraphiladlr_(m, &lastv, &c__[c_offset], ldc); } } /* Note that lastc.eq.0 renders the BLAS operations null; no special case is needed at this level. */ if (applyleft) { /* Form H * C */ if (lastv > 0) { /* w(1:lastc,1) := C(1:lastv,1:lastc)**T * v(1:lastv,1) */ igraphdgemv_("Transpose", &lastv, &lastc, &c_b4, &c__[c_offset], ldc, & v[1], incv, &c_b5, &work[1], &c__1); /* C(1:lastv,1:lastc) := C(...) - v(1:lastv,1) * w(1:lastc,1)**T */ d__1 = -(*tau); igraphdger_(&lastv, &lastc, &d__1, &v[1], incv, &work[1], &c__1, &c__[ c_offset], ldc); } } else { /* Form C * H */ if (lastv > 0) { /* w(1:lastc,1) := C(1:lastc,1:lastv) * v(1:lastv,1) */ igraphdgemv_("No transpose", &lastc, &lastv, &c_b4, &c__[c_offset], ldc, &v[1], incv, &c_b5, &work[1], &c__1); /* C(1:lastc,1:lastv) := C(...) - w(1:lastc,1) * v(1:lastv,1)**T */ d__1 = -(*tau); igraphdger_(&lastc, &lastv, &d__1, &work[1], &c__1, &v[1], incv, &c__[ c_offset], ldc); } } return 0; /* End of DLARF */ } /* igraphdlarf_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlanv2.c0000644000076500000240000001773513524616145024207 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static doublereal c_b4 = 1.; /* > \brief \b DLANV2 computes the Schur factorization of a real 2-by-2 nonsymmetric matrix in standard form. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLANV2 + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLANV2( A, B, C, D, RT1R, RT1I, RT2R, RT2I, CS, SN ) DOUBLE PRECISION A, B, C, CS, D, RT1I, RT1R, RT2I, RT2R, SN > \par Purpose: ============= > > \verbatim > > DLANV2 computes the Schur factorization of a real 2-by-2 nonsymmetric > matrix in standard form: > > [ A B ] = [ CS -SN ] [ AA BB ] [ CS SN ] > [ C D ] [ SN CS ] [ CC DD ] [-SN CS ] > > where either > 1) CC = 0 so that AA and DD are real eigenvalues of the matrix, or > 2) AA = DD and BB*CC < 0, so that AA + or - sqrt(BB*CC) are complex > conjugate eigenvalues. > \endverbatim Arguments: ========== > \param[in,out] A > \verbatim > A is DOUBLE PRECISION > \endverbatim > > \param[in,out] B > \verbatim > B is DOUBLE PRECISION > \endverbatim > > \param[in,out] C > \verbatim > C is DOUBLE PRECISION > \endverbatim > > \param[in,out] D > \verbatim > D is DOUBLE PRECISION > On entry, the elements of the input matrix. > On exit, they are overwritten by the elements of the > standardised Schur form. > \endverbatim > > \param[out] RT1R > \verbatim > RT1R is DOUBLE PRECISION > \endverbatim > > \param[out] RT1I > \verbatim > RT1I is DOUBLE PRECISION > \endverbatim > > \param[out] RT2R > \verbatim > RT2R is DOUBLE PRECISION > \endverbatim > > \param[out] RT2I > \verbatim > RT2I is DOUBLE PRECISION > The real and imaginary parts of the eigenvalues. If the > eigenvalues are a complex conjugate pair, RT1I > 0. > \endverbatim > > \param[out] CS > \verbatim > CS is DOUBLE PRECISION > \endverbatim > > \param[out] SN > \verbatim > SN is DOUBLE PRECISION > Parameters of the rotation matrix. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleOTHERauxiliary > \par Further Details: ===================== > > \verbatim > > Modified by V. Sima, Research Institute for Informatics, Bucharest, > Romania, to reduce the risk of cancellation errors, > when computing real eigenvalues, and to ensure, if possible, that > abs(RT1R) >= abs(RT2R). > \endverbatim > ===================================================================== Subroutine */ int igraphdlanv2_(doublereal *a, doublereal *b, doublereal *c__, doublereal *d__, doublereal *rt1r, doublereal *rt1i, doublereal *rt2r, doublereal *rt2i, doublereal *cs, doublereal *sn) { /* System generated locals */ doublereal d__1, d__2; /* Builtin functions */ double d_sign(doublereal *, doublereal *), sqrt(doublereal); /* Local variables */ doublereal p, z__, aa, bb, cc, dd, cs1, sn1, sab, sac, eps, tau, temp, scale, bcmax, bcmis, sigma; extern doublereal igraphdlapy2_(doublereal *, doublereal *), igraphdlamch_(char *); /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== */ eps = igraphdlamch_("P"); if (*c__ == 0.) { *cs = 1.; *sn = 0.; goto L10; } else if (*b == 0.) { /* Swap rows and columns */ *cs = 0.; *sn = 1.; temp = *d__; *d__ = *a; *a = temp; *b = -(*c__); *c__ = 0.; goto L10; } else if (*a - *d__ == 0. && d_sign(&c_b4, b) != d_sign(&c_b4, c__)) { *cs = 1.; *sn = 0.; goto L10; } else { temp = *a - *d__; p = temp * .5; /* Computing MAX */ d__1 = abs(*b), d__2 = abs(*c__); bcmax = max(d__1,d__2); /* Computing MIN */ d__1 = abs(*b), d__2 = abs(*c__); bcmis = min(d__1,d__2) * d_sign(&c_b4, b) * d_sign(&c_b4, c__); /* Computing MAX */ d__1 = abs(p); scale = max(d__1,bcmax); z__ = p / scale * p + bcmax / scale * bcmis; /* If Z is of the order of the machine accuracy, postpone the decision on the nature of eigenvalues */ if (z__ >= eps * 4.) { /* Real eigenvalues. Compute A and D. */ d__1 = sqrt(scale) * sqrt(z__); z__ = p + d_sign(&d__1, &p); *a = *d__ + z__; *d__ -= bcmax / z__ * bcmis; /* Compute B and the rotation matrix */ tau = igraphdlapy2_(c__, &z__); *cs = z__ / tau; *sn = *c__ / tau; *b -= *c__; *c__ = 0.; } else { /* Complex eigenvalues, or real (almost) equal eigenvalues. Make diagonal elements equal. */ sigma = *b + *c__; tau = igraphdlapy2_(&sigma, &temp); *cs = sqrt((abs(sigma) / tau + 1.) * .5); *sn = -(p / (tau * *cs)) * d_sign(&c_b4, &sigma); /* Compute [ AA BB ] = [ A B ] [ CS -SN ] [ CC DD ] [ C D ] [ SN CS ] */ aa = *a * *cs + *b * *sn; bb = -(*a) * *sn + *b * *cs; cc = *c__ * *cs + *d__ * *sn; dd = -(*c__) * *sn + *d__ * *cs; /* Compute [ A B ] = [ CS SN ] [ AA BB ] [ C D ] [-SN CS ] [ CC DD ] */ *a = aa * *cs + cc * *sn; *b = bb * *cs + dd * *sn; *c__ = -aa * *sn + cc * *cs; *d__ = -bb * *sn + dd * *cs; temp = (*a + *d__) * .5; *a = temp; *d__ = temp; if (*c__ != 0.) { if (*b != 0.) { if (d_sign(&c_b4, b) == d_sign(&c_b4, c__)) { /* Real eigenvalues: reduce to upper triangular form */ sab = sqrt((abs(*b))); sac = sqrt((abs(*c__))); d__1 = sab * sac; p = d_sign(&d__1, c__); tau = 1. / sqrt((d__1 = *b + *c__, abs(d__1))); *a = temp + p; *d__ = temp - p; *b -= *c__; *c__ = 0.; cs1 = sab * tau; sn1 = sac * tau; temp = *cs * cs1 - *sn * sn1; *sn = *cs * sn1 + *sn * cs1; *cs = temp; } } else { *b = -(*c__); *c__ = 0.; temp = *cs; *cs = -(*sn); *sn = temp; } } } } L10: /* Store eigenvalues in (RT1R,RT1I) and (RT2R,RT2I). */ *rt1r = *a; *rt2r = *d__; if (*c__ == 0.) { *rt1i = 0.; *rt2i = 0.; } else { *rt1i = sqrt((abs(*b))) * sqrt((abs(*c__))); *rt2i = -(*rt1i); } return 0; /* End of DLANV2 */ } /* igraphdlanv2_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/arpack.inc0000644000076500000240000000070713524616145024600 0ustar tamasstaff00000000000000ARPACK = lapack/dnaupd.c lapack/dnaup2.c lapack/dgetv0.c lapack/dvout.c lapack/second.c lapack/dmout.c lapack/dnaitr.c lapack/ivout.c lapack/dnapps.c lapack/dnconv.c lapack/dneigh.c lapack/dlaqrb.c lapack/dngets.c lapack/dsortc.c lapack/dstatn.c lapack/dneupd.c lapack/dsaupd.c lapack/dsaup2.c lapack/dsaitr.c lapack/dsapps.c lapack/dsconv.c lapack/dseigt.c lapack/dstqrb.c lapack/dsgets.c lapack/dsortr.c lapack/dstats.c lapack/dseupd.c lapack/dsesrt.c python-igraph-0.8.0/vendor/source/igraph/src/lapack/dmout.c0000644000076500000240000002515413524616145024143 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static integer c__3 = 3; /* ----------------------------------------------------------------------- Routine: DMOUT Purpose: Real matrix output routine. Usage: CALL DMOUT (LOUT, M, N, A, LDA, IDIGIT, IFMT) Arguments M - Number of rows of A. (Input) N - Number of columns of A. (Input) A - Real M by N matrix to be printed. (Input) LDA - Leading dimension of A exactly as specified in the dimension statement of the calling program. (Input) IFMT - Format to be used in printing matrix A. (Input) IDIGIT - Print up to IABS(IDIGIT) decimal digits per number. (In) If IDIGIT .LT. 0, printing is done with 72 columns. If IDIGIT .GT. 0, printing is done with 132 columns. ----------------------------------------------------------------------- Subroutine */ int igraphdmout_(integer *lout, integer *m, integer *n, doublereal *a, integer *lda, integer *idigit, char *ifmt, ftnlen ifmt_len) { /* Initialized data */ static char icol[1*3] = "C" "o" "l"; /* Format strings */ static char fmt_9999[] = "(/1x,a,/1x,a)"; static char fmt_9998[] = "(10x,10(4x,3a1,i4,1x))"; static char fmt_9994[] = "(1x,\002 Row\002,i4,\002:\002,1x,1p,10d12.3)"; static char fmt_9997[] = "(10x,8(5x,3a1,i4,2x))"; static char fmt_9993[] = "(1x,\002 Row\002,i4,\002:\002,1x,1p,8d14.5)"; static char fmt_9996[] = "(10x,6(7x,3a1,i4,4x))"; static char fmt_9992[] = "(1x,\002 Row\002,i4,\002:\002,1x,1p,6d18.9)"; static char fmt_9995[] = "(10x,5(9x,3a1,i4,6x))"; static char fmt_9991[] = "(1x,\002 Row\002,i4,\002:\002,1x,1p,5d22.13)"; static char fmt_9990[] = "(1x,\002 \002)"; /* System generated locals */ integer a_dim1, a_offset, i__1, i__2, i__3; /* Builtin functions */ integer i_len(char *, ftnlen), s_wsfe(cilist *), do_fio(integer *, char *, ftnlen), e_wsfe(void); /* Local variables */ integer i__, j, k1, k2, lll; char line[80]; integer ndigit; /* Fortran I/O blocks */ static cilist io___5 = { 0, 0, 0, fmt_9999, 0 }; static cilist io___9 = { 0, 0, 0, fmt_9998, 0 }; static cilist io___10 = { 0, 0, 0, fmt_9994, 0 }; static cilist io___12 = { 0, 0, 0, fmt_9997, 0 }; static cilist io___13 = { 0, 0, 0, fmt_9993, 0 }; static cilist io___14 = { 0, 0, 0, fmt_9996, 0 }; static cilist io___15 = { 0, 0, 0, fmt_9992, 0 }; static cilist io___16 = { 0, 0, 0, fmt_9995, 0 }; static cilist io___17 = { 0, 0, 0, fmt_9991, 0 }; static cilist io___18 = { 0, 0, 0, fmt_9998, 0 }; static cilist io___19 = { 0, 0, 0, fmt_9994, 0 }; static cilist io___20 = { 0, 0, 0, fmt_9997, 0 }; static cilist io___21 = { 0, 0, 0, fmt_9993, 0 }; static cilist io___22 = { 0, 0, 0, fmt_9996, 0 }; static cilist io___23 = { 0, 0, 0, fmt_9992, 0 }; static cilist io___24 = { 0, 0, 0, fmt_9995, 0 }; static cilist io___25 = { 0, 0, 0, fmt_9991, 0 }; static cilist io___26 = { 0, 0, 0, fmt_9990, 0 }; /* ... ... SPECIFICATIONS FOR ARGUMENTS ... ... SPECIFICATIONS FOR LOCAL VARIABLES Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; /* Function Body ... ... FIRST EXECUTABLE STATEMENT Computing MIN */ i__1 = i_len(ifmt, ifmt_len); lll = min(i__1,80); i__1 = lll; for (i__ = 1; i__ <= i__1; ++i__) { *(unsigned char *)&line[i__ - 1] = '-'; /* L10: */ } for (i__ = lll + 1; i__ <= 80; ++i__) { *(unsigned char *)&line[i__ - 1] = ' '; /* L20: */ } io___5.ciunit = *lout; s_wsfe(&io___5); do_fio(&c__1, ifmt, ifmt_len); do_fio(&c__1, line, lll); e_wsfe(); if (*m <= 0 || *n <= 0 || *lda <= 0) { return 0; } ndigit = *idigit; if (*idigit == 0) { ndigit = 4; } /* ======================================================================= CODE FOR OUTPUT USING 72 COLUMNS FORMAT ======================================================================= */ if (*idigit < 0) { ndigit = -(*idigit); if (ndigit <= 4) { i__1 = *n; for (k1 = 1; k1 <= i__1; k1 += 5) { /* Computing MIN */ i__2 = *n, i__3 = k1 + 4; k2 = min(i__2,i__3); io___9.ciunit = *lout; s_wsfe(&io___9); i__2 = k2; for (i__ = k1; i__ <= i__2; ++i__) { do_fio(&c__3, icol, (ftnlen)1); do_fio(&c__1, (char *)&i__, (ftnlen)sizeof(integer)); } e_wsfe(); i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { io___10.ciunit = *lout; s_wsfe(&io___10); do_fio(&c__1, (char *)&i__, (ftnlen)sizeof(integer)); i__3 = k2; for (j = k1; j <= i__3; ++j) { do_fio(&c__1, (char *)&a[i__ + j * a_dim1], (ftnlen) sizeof(doublereal)); } e_wsfe(); /* L30: */ } /* L40: */ } } else if (ndigit <= 6) { i__1 = *n; for (k1 = 1; k1 <= i__1; k1 += 4) { /* Computing MIN */ i__2 = *n, i__3 = k1 + 3; k2 = min(i__2,i__3); io___12.ciunit = *lout; s_wsfe(&io___12); i__2 = k2; for (i__ = k1; i__ <= i__2; ++i__) { do_fio(&c__3, icol, (ftnlen)1); do_fio(&c__1, (char *)&i__, (ftnlen)sizeof(integer)); } e_wsfe(); i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { io___13.ciunit = *lout; s_wsfe(&io___13); do_fio(&c__1, (char *)&i__, (ftnlen)sizeof(integer)); i__3 = k2; for (j = k1; j <= i__3; ++j) { do_fio(&c__1, (char *)&a[i__ + j * a_dim1], (ftnlen) sizeof(doublereal)); } e_wsfe(); /* L50: */ } /* L60: */ } } else if (ndigit <= 10) { i__1 = *n; for (k1 = 1; k1 <= i__1; k1 += 3) { /* Computing MIN */ i__2 = *n, i__3 = k1 + 2; k2 = min(i__2,i__3); io___14.ciunit = *lout; s_wsfe(&io___14); i__2 = k2; for (i__ = k1; i__ <= i__2; ++i__) { do_fio(&c__3, icol, (ftnlen)1); do_fio(&c__1, (char *)&i__, (ftnlen)sizeof(integer)); } e_wsfe(); i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { io___15.ciunit = *lout; s_wsfe(&io___15); do_fio(&c__1, (char *)&i__, (ftnlen)sizeof(integer)); i__3 = k2; for (j = k1; j <= i__3; ++j) { do_fio(&c__1, (char *)&a[i__ + j * a_dim1], (ftnlen) sizeof(doublereal)); } e_wsfe(); /* L70: */ } /* L80: */ } } else { i__1 = *n; for (k1 = 1; k1 <= i__1; k1 += 2) { /* Computing MIN */ i__2 = *n, i__3 = k1 + 1; k2 = min(i__2,i__3); io___16.ciunit = *lout; s_wsfe(&io___16); i__2 = k2; for (i__ = k1; i__ <= i__2; ++i__) { do_fio(&c__3, icol, (ftnlen)1); do_fio(&c__1, (char *)&i__, (ftnlen)sizeof(integer)); } e_wsfe(); i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { io___17.ciunit = *lout; s_wsfe(&io___17); do_fio(&c__1, (char *)&i__, (ftnlen)sizeof(integer)); i__3 = k2; for (j = k1; j <= i__3; ++j) { do_fio(&c__1, (char *)&a[i__ + j * a_dim1], (ftnlen) sizeof(doublereal)); } e_wsfe(); /* L90: */ } /* L100: */ } } /* ======================================================================= CODE FOR OUTPUT USING 132 COLUMNS FORMAT ======================================================================= */ } else { if (ndigit <= 4) { i__1 = *n; for (k1 = 1; k1 <= i__1; k1 += 10) { /* Computing MIN */ i__2 = *n, i__3 = k1 + 9; k2 = min(i__2,i__3); io___18.ciunit = *lout; s_wsfe(&io___18); i__2 = k2; for (i__ = k1; i__ <= i__2; ++i__) { do_fio(&c__3, icol, (ftnlen)1); do_fio(&c__1, (char *)&i__, (ftnlen)sizeof(integer)); } e_wsfe(); i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { io___19.ciunit = *lout; s_wsfe(&io___19); do_fio(&c__1, (char *)&i__, (ftnlen)sizeof(integer)); i__3 = k2; for (j = k1; j <= i__3; ++j) { do_fio(&c__1, (char *)&a[i__ + j * a_dim1], (ftnlen) sizeof(doublereal)); } e_wsfe(); /* L110: */ } /* L120: */ } } else if (ndigit <= 6) { i__1 = *n; for (k1 = 1; k1 <= i__1; k1 += 8) { /* Computing MIN */ i__2 = *n, i__3 = k1 + 7; k2 = min(i__2,i__3); io___20.ciunit = *lout; s_wsfe(&io___20); i__2 = k2; for (i__ = k1; i__ <= i__2; ++i__) { do_fio(&c__3, icol, (ftnlen)1); do_fio(&c__1, (char *)&i__, (ftnlen)sizeof(integer)); } e_wsfe(); i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { io___21.ciunit = *lout; s_wsfe(&io___21); do_fio(&c__1, (char *)&i__, (ftnlen)sizeof(integer)); i__3 = k2; for (j = k1; j <= i__3; ++j) { do_fio(&c__1, (char *)&a[i__ + j * a_dim1], (ftnlen) sizeof(doublereal)); } e_wsfe(); /* L130: */ } /* L140: */ } } else if (ndigit <= 10) { i__1 = *n; for (k1 = 1; k1 <= i__1; k1 += 6) { /* Computing MIN */ i__2 = *n, i__3 = k1 + 5; k2 = min(i__2,i__3); io___22.ciunit = *lout; s_wsfe(&io___22); i__2 = k2; for (i__ = k1; i__ <= i__2; ++i__) { do_fio(&c__3, icol, (ftnlen)1); do_fio(&c__1, (char *)&i__, (ftnlen)sizeof(integer)); } e_wsfe(); i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { io___23.ciunit = *lout; s_wsfe(&io___23); do_fio(&c__1, (char *)&i__, (ftnlen)sizeof(integer)); i__3 = k2; for (j = k1; j <= i__3; ++j) { do_fio(&c__1, (char *)&a[i__ + j * a_dim1], (ftnlen) sizeof(doublereal)); } e_wsfe(); /* L150: */ } /* L160: */ } } else { i__1 = *n; for (k1 = 1; k1 <= i__1; k1 += 5) { /* Computing MIN */ i__2 = *n, i__3 = k1 + 4; k2 = min(i__2,i__3); io___24.ciunit = *lout; s_wsfe(&io___24); i__2 = k2; for (i__ = k1; i__ <= i__2; ++i__) { do_fio(&c__3, icol, (ftnlen)1); do_fio(&c__1, (char *)&i__, (ftnlen)sizeof(integer)); } e_wsfe(); i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { io___25.ciunit = *lout; s_wsfe(&io___25); do_fio(&c__1, (char *)&i__, (ftnlen)sizeof(integer)); i__3 = k2; for (j = k1; j <= i__3; ++j) { do_fio(&c__1, (char *)&a[i__ + j * a_dim1], (ftnlen) sizeof(doublereal)); } e_wsfe(); /* L170: */ } /* L180: */ } } } io___26.ciunit = *lout; s_wsfe(&io___26); e_wsfe(); return 0; } /* igraphdmout_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/iladlr.c0000644000076500000240000000710213524616145024253 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b ILADLR scans a matrix for its last non-zero row. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download ILADLR + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== INTEGER FUNCTION ILADLR( M, N, A, LDA ) INTEGER M, N, LDA DOUBLE PRECISION A( LDA, * ) > \par Purpose: ============= > > \verbatim > > ILADLR scans A for its last non-zero row. > \endverbatim Arguments: ========== > \param[in] M > \verbatim > M is INTEGER > The number of rows of the matrix A. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The number of columns of the matrix A. > \endverbatim > > \param[in] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,N) > The m by n matrix A. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. LDA >= max(1,M). > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERauxiliary ===================================================================== */ integer igraphiladlr_(integer *m, integer *n, doublereal *a, integer *lda) { /* System generated locals */ integer a_dim1, a_offset, ret_val, i__1; /* Local variables */ integer i__, j; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Quick test for the common case where one corner is non-zero. Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; /* Function Body */ if (*m == 0) { ret_val = *m; } else if (a[*m + a_dim1] != 0. || a[*m + *n * a_dim1] != 0.) { ret_val = *m; } else { /* Scan up each column tracking the last zero row seen. */ ret_val = 0; i__1 = *n; for (j = 1; j <= i__1; ++j) { i__ = *m; while(a[max(i__,1) + j * a_dim1] == 0. && i__ >= 1) { --i__; } ret_val = max(ret_val,i__); } } return ret_val; } /* igraphiladlr_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dswap.c0000644000076500000240000000427513524616145024132 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Subroutine */ int igraphdswap_(integer *n, doublereal *dx, integer *incx, doublereal *dy, integer *incy) { /* System generated locals */ integer i__1; /* Local variables */ integer i__, m, ix, iy, mp1; doublereal dtemp; /* Purpose ======= interchanges two vectors. uses unrolled loops for increments equal one. Further Details =============== jack dongarra, linpack, 3/11/78. modified 12/3/93, array(1) declarations changed to array(*) ===================================================================== Parameter adjustments */ --dy; --dx; /* Function Body */ if (*n <= 0) { return 0; } if (*incx == 1 && *incy == 1) { /* code for both increments equal to 1 clean-up loop */ m = *n % 3; if (m != 0) { i__1 = m; for (i__ = 1; i__ <= i__1; ++i__) { dtemp = dx[i__]; dx[i__] = dy[i__]; dy[i__] = dtemp; } if (*n < 3) { return 0; } } mp1 = m + 1; i__1 = *n; for (i__ = mp1; i__ <= i__1; i__ += 3) { dtemp = dx[i__]; dx[i__] = dy[i__]; dy[i__] = dtemp; dtemp = dx[i__ + 1]; dx[i__ + 1] = dy[i__ + 1]; dy[i__ + 1] = dtemp; dtemp = dx[i__ + 2]; dx[i__ + 2] = dy[i__ + 2]; dy[i__ + 2] = dtemp; } } else { /* code for unequal increments or equal increments not equal to 1 */ ix = 1; iy = 1; if (*incx < 0) { ix = (-(*n) + 1) * *incx + 1; } if (*incy < 0) { iy = (-(*n) + 1) * *incy + 1; } i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { dtemp = dx[ix]; dx[ix] = dy[iy]; dy[iy] = dtemp; ix += *incx; iy += *incy; } } return 0; } /* igraphdswap_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dsaup2.c0000644000076500000240000010651113524616145024206 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static doublereal c_b3 = .66666666666666663; static integer c__1 = 1; static integer c__0 = 0; static integer c__3 = 3; static logical c_true = TRUE_; static integer c__2 = 2; /* ----------------------------------------------------------------------- \BeginDoc \Name: dsaup2 \Description: Intermediate level interface called by dsaupd. \Usage: call dsaup2 ( IDO, BMAT, N, WHICH, NEV, NP, TOL, RESID, MODE, IUPD, ISHIFT, MXITER, V, LDV, H, LDH, RITZ, BOUNDS, Q, LDQ, WORKL, IPNTR, WORKD, INFO ) \Arguments IDO, BMAT, N, WHICH, NEV, TOL, RESID: same as defined in dsaupd. MODE, ISHIFT, MXITER: see the definition of IPARAM in dsaupd. NP Integer. (INPUT/OUTPUT) Contains the number of implicit shifts to apply during each Arnoldi/Lanczos iteration. If ISHIFT=1, NP is adjusted dynamically at each iteration to accelerate convergence and prevent stagnation. This is also roughly equal to the number of matrix-vector products (involving the operator OP) per Arnoldi iteration. The logic for adjusting is contained within the current subroutine. If ISHIFT=0, NP is the number of shifts the user needs to provide via reverse comunication. 0 < NP < NCV-NEV. NP may be less than NCV-NEV since a leading block of the current upper Tridiagonal matrix has split off and contains "unwanted" Ritz values. Upon termination of the IRA iteration, NP contains the number of "converged" wanted Ritz values. IUPD Integer. (INPUT) IUPD .EQ. 0: use explicit restart instead implicit update. IUPD .NE. 0: use implicit update. V Double precision N by (NEV+NP) array. (INPUT/OUTPUT) The Lanczos basis vectors. LDV Integer. (INPUT) Leading dimension of V exactly as declared in the calling program. H Double precision (NEV+NP) by 2 array. (OUTPUT) H is used to store the generated symmetric tridiagonal matrix The subdiagonal is stored in the first column of H starting at H(2,1). The main diagonal is stored in the second column of H starting at H(1,2). If dsaup2 converges store the B-norm of the final residual vector in H(1,1). LDH Integer. (INPUT) Leading dimension of H exactly as declared in the calling program. RITZ Double precision array of length NEV+NP. (OUTPUT) RITZ(1:NEV) contains the computed Ritz values of OP. BOUNDS Double precision array of length NEV+NP. (OUTPUT) BOUNDS(1:NEV) contain the error bounds corresponding to RITZ. Q Double precision (NEV+NP) by (NEV+NP) array. (WORKSPACE) Private (replicated) work array used to accumulate the rotation in the shift application step. LDQ Integer. (INPUT) Leading dimension of Q exactly as declared in the calling program. WORKL Double precision array of length at least 3*(NEV+NP). (INPUT/WORKSPACE) Private (replicated) array on each PE or array allocated on the front end. It is used in the computation of the tridiagonal eigenvalue problem, the calculation and application of the shifts and convergence checking. If ISHIFT .EQ. O and IDO .EQ. 3, the first NP locations of WORKL are used in reverse communication to hold the user supplied shifts. IPNTR Integer array of length 3. (OUTPUT) Pointer to mark the starting locations in the WORKD for vectors used by the Lanczos iteration. ------------------------------------------------------------- IPNTR(1): pointer to the current operand vector X. IPNTR(2): pointer to the current result vector Y. IPNTR(3): pointer to the vector B * X when used in one of the spectral transformation modes. X is the current operand. ------------------------------------------------------------- WORKD Double precision work array of length 3*N. (REVERSE COMMUNICATION) Distributed array to be used in the basic Lanczos iteration for reverse communication. The user should not use WORKD as temporary workspace during the iteration !!!!!!!!!! See Data Distribution Note in dsaupd. INFO Integer. (INPUT/OUTPUT) If INFO .EQ. 0, a randomly initial residual vector is used. If INFO .NE. 0, RESID contains the initial residual vector, possibly from a previous run. Error flag on output. = 0: Normal return. = 1: All possible eigenvalues of OP has been found. NP returns the size of the invariant subspace spanning the operator OP. = 2: No shifts could be applied. = -8: Error return from trid. eigenvalue calculation; This should never happen. = -9: Starting vector is zero. = -9999: Could not build an Lanczos factorization. Size that was built in returned in NP. \EndDoc ----------------------------------------------------------------------- \BeginLib \References: 1. D.C. Sorensen, "Implicit Application of Polynomial Filters in a k-Step Arnoldi Method", SIAM J. Matr. Anal. Apps., 13 (1992), pp 357-385. 2. R.B. Lehoucq, "Analysis and Implementation of an Implicitly Restarted Arnoldi Iteration", Rice University Technical Report TR95-13, Department of Computational and Applied Mathematics. 3. B.N. Parlett, "The Symmetric Eigenvalue Problem". Prentice-Hall, 1980. 4. B.N. Parlett, B. Nour-Omid, "Towards a Black Box Lanczos Program", Computer Physics Communications, 53 (1989), pp 169-179. 5. B. Nour-Omid, B.N. Parlett, T. Ericson, P.S. Jensen, "How to Implement the Spectral Transformation", Math. Comp., 48 (1987), pp 663-673. 6. R.G. Grimes, J.G. Lewis and H.D. Simon, "A Shifted Block Lanczos Algorithm for Solving Sparse Symmetric Generalized Eigenproblems", SIAM J. Matr. Anal. Apps., January (1993). 7. L. Reichel, W.B. Gragg, "Algorithm 686: FORTRAN Subroutines for Updating the QR decomposition", ACM TOMS, December 1990, Volume 16 Number 4, pp 369-377. \Routines called: dgetv0 ARPACK initial vector generation routine. dsaitr ARPACK Lanczos factorization routine. dsapps ARPACK application of implicit shifts routine. dsconv ARPACK convergence of Ritz values routine. dseigt ARPACK compute Ritz values and error bounds routine. dsgets ARPACK reorder Ritz values and error bounds routine. dsortr ARPACK sorting routine. ivout ARPACK utility routine that prints integers. second ARPACK utility routine for timing. dvout ARPACK utility routine that prints vectors. dlamch LAPACK routine that determines machine constants. dcopy Level 1 BLAS that copies one vector to another. ddot Level 1 BLAS that computes the scalar product of two vectors. dnrm2 Level 1 BLAS that computes the norm of a vector. dscal Level 1 BLAS that scales a vector. dswap Level 1 BLAS that swaps two vectors. \Author Danny Sorensen Phuong Vu Richard Lehoucq CRPC / Rice University Dept. of Computational & Houston, Texas Applied Mathematics Rice University Houston, Texas \Revision history: 12/15/93: Version ' 2.4' xx/xx/95: Version ' 2.4'. (R.B. Lehoucq) \SCCS Information: @(#) FILE: saup2.F SID: 2.6 DATE OF SID: 8/16/96 RELEASE: 2 \EndLib ----------------------------------------------------------------------- Subroutine */ int igraphdsaup2_(integer *ido, char *bmat, integer *n, char * which, integer *nev, integer *np, doublereal *tol, doublereal *resid, integer *mode, integer *iupd, integer *ishift, integer *mxiter, doublereal *v, integer *ldv, doublereal *h__, integer *ldh, doublereal *ritz, doublereal *bounds, doublereal *q, integer *ldq, doublereal *workl, integer *ipntr, doublereal *workd, integer *info) { /* System generated locals */ integer h_dim1, h_offset, q_dim1, q_offset, v_dim1, v_offset, i__1, i__2, i__3; doublereal d__1, d__2, d__3; /* Builtin functions */ double pow_dd(doublereal *, doublereal *); integer s_cmp(char *, char *, ftnlen, ftnlen); /* Subroutine */ int s_copy(char *, char *, ftnlen, ftnlen); double sqrt(doublereal); /* Local variables */ integer j; real t0, t1, t2, t3; integer kp[3]; IGRAPH_F77_SAVE integer np0; integer nbx = 0; IGRAPH_F77_SAVE integer nev0; extern doublereal igraphddot_(integer *, doublereal *, integer *, doublereal *, integer *); IGRAPH_F77_SAVE doublereal eps23; integer ierr; IGRAPH_F77_SAVE integer iter; doublereal temp; integer nevd2; extern doublereal igraphdnrm2_(integer *, doublereal *, integer *); IGRAPH_F77_SAVE logical getv0; integer nevm2; IGRAPH_F77_SAVE logical cnorm; extern /* Subroutine */ int igraphdcopy_(integer *, doublereal *, integer *, doublereal *, integer *), igraphdswap_(integer *, doublereal *, integer *, doublereal *, integer *); IGRAPH_F77_SAVE integer nconv; IGRAPH_F77_SAVE logical initv; IGRAPH_F77_SAVE doublereal rnorm; real tmvbx = 0.0; extern /* Subroutine */ int igraphdvout_(integer *, integer *, doublereal *, integer *, char *, ftnlen), igraphivout_(integer *, integer *, integer * , integer *, char *, ftnlen), igraphdgetv0_(integer *, char *, integer * , logical *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *); integer msaup2 = 0; real tsaup2; extern doublereal igraphdlamch_(char *); integer nevbef; extern /* Subroutine */ int igraphsecond_(real *); integer logfil, ndigit; extern /* Subroutine */ int igraphdseigt_(doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, integer *); IGRAPH_F77_SAVE logical update; extern /* Subroutine */ int igraphdsaitr_(integer *, char *, integer *, integer *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *, doublereal *, integer *, integer *, doublereal *, integer *), igraphdsgets_(integer *, char *, integer *, integer *, doublereal *, doublereal *, doublereal *), igraphdsapps_( integer *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *), igraphdsconv_(integer *, doublereal *, doublereal *, doublereal *, integer *); IGRAPH_F77_SAVE logical ushift; char wprime[2]; IGRAPH_F77_SAVE integer msglvl; integer nptemp; extern /* Subroutine */ int igraphdsortr_(char *, logical *, integer *, doublereal *, doublereal *); IGRAPH_F77_SAVE integer kplusp; /* %----------------------------------------------------% | Include files for debugging and timing information | %----------------------------------------------------% %------------------% | Scalar Arguments | %------------------% %-----------------% | Array Arguments | %-----------------% %------------% | Parameters | %------------% %---------------% | Local Scalars | %---------------% %----------------------% | External Subroutines | %----------------------% %--------------------% | External Functions | %--------------------% %---------------------% | Intrinsic Functions | %---------------------% %-----------------------% | Executable Statements | %-----------------------% Parameter adjustments */ --workd; --resid; --workl; --bounds; --ritz; v_dim1 = *ldv; v_offset = 1 + v_dim1; v -= v_offset; h_dim1 = *ldh; h_offset = 1 + h_dim1; h__ -= h_offset; q_dim1 = *ldq; q_offset = 1 + q_dim1; q -= q_offset; --ipntr; /* Function Body */ if (*ido == 0) { /* %-------------------------------% | Initialize timing statistics | | & message level for debugging | %-------------------------------% */ igraphsecond_(&t0); msglvl = msaup2; /* %---------------------------------% | Set machine dependent constant. | %---------------------------------% */ eps23 = igraphdlamch_("Epsilon-Machine"); eps23 = pow_dd(&eps23, &c_b3); /* %-------------------------------------% | nev0 and np0 are integer variables | | hold the initial values of NEV & NP | %-------------------------------------% */ nev0 = *nev; np0 = *np; /* %-------------------------------------% | kplusp is the bound on the largest | | Lanczos factorization built. | | nconv is the current number of | | "converged" eigenvlues. | | iter is the counter on the current | | iteration step. | %-------------------------------------% */ kplusp = nev0 + np0; nconv = 0; iter = 0; /* %--------------------------------------------% | Set flags for computing the first NEV steps | | of the Lanczos factorization. | %--------------------------------------------% */ getv0 = TRUE_; update = FALSE_; ushift = FALSE_; cnorm = FALSE_; if (*info != 0) { /* %--------------------------------------------% | User provides the initial residual vector. | %--------------------------------------------% */ initv = TRUE_; *info = 0; } else { initv = FALSE_; } } /* %---------------------------------------------% | Get a possibly random starting vector and | | force it into the range of the operator OP. | %---------------------------------------------% L10: */ if (getv0) { igraphdgetv0_(ido, bmat, &c__1, &initv, n, &c__1, &v[v_offset], ldv, &resid[ 1], &rnorm, &ipntr[1], &workd[1], info); if (*ido != 99) { goto L9000; } if (rnorm == 0.) { /* %-----------------------------------------% | The initial vector is zero. Error exit. | %-----------------------------------------% */ *info = -9; goto L1200; } getv0 = FALSE_; *ido = 0; } /* %------------------------------------------------------------% | Back from reverse communication: continue with update step | %------------------------------------------------------------% */ if (update) { goto L20; } /* %-------------------------------------------% | Back from computing user specified shifts | %-------------------------------------------% */ if (ushift) { goto L50; } /* %-------------------------------------% | Back from computing residual norm | | at the end of the current iteration | %-------------------------------------% */ if (cnorm) { goto L100; } /* %----------------------------------------------------------% | Compute the first NEV steps of the Lanczos factorization | %----------------------------------------------------------% */ igraphdsaitr_(ido, bmat, n, &c__0, &nev0, mode, &resid[1], &rnorm, &v[v_offset], ldv, &h__[h_offset], ldh, &ipntr[1], &workd[1], info); /* %---------------------------------------------------% | ido .ne. 99 implies use of reverse communication | | to compute operations involving OP and possibly B | %---------------------------------------------------% */ if (*ido != 99) { goto L9000; } if (*info > 0) { /* %-----------------------------------------------------% | dsaitr was unable to build an Lanczos factorization | | of length NEV0. INFO is returned with the size of | | the factorization built. Exit main loop. | %-----------------------------------------------------% */ *np = *info; *mxiter = iter; *info = -9999; goto L1200; } /* %--------------------------------------------------------------% | | | M A I N LANCZOS I T E R A T I O N L O O P | | Each iteration implicitly restarts the Lanczos | | factorization in place. | | | %--------------------------------------------------------------% */ L1000: ++iter; if (msglvl > 0) { igraphivout_(&logfil, &c__1, &iter, &ndigit, "_saup2: **** Start of major " "iteration number ****", (ftnlen)49); } if (msglvl > 1) { igraphivout_(&logfil, &c__1, nev, &ndigit, "_saup2: The length of the curr" "ent Lanczos factorization", (ftnlen)55); igraphivout_(&logfil, &c__1, np, &ndigit, "_saup2: Extend the Lanczos fact" "orization by", (ftnlen)43); } /* %------------------------------------------------------------% | Compute NP additional steps of the Lanczos factorization. | %------------------------------------------------------------% */ *ido = 0; L20: update = TRUE_; igraphdsaitr_(ido, bmat, n, nev, np, mode, &resid[1], &rnorm, &v[v_offset], ldv, &h__[h_offset], ldh, &ipntr[1], &workd[1], info); /* %---------------------------------------------------% | ido .ne. 99 implies use of reverse communication | | to compute operations involving OP and possibly B | %---------------------------------------------------% */ if (*ido != 99) { goto L9000; } if (*info > 0) { /* %-----------------------------------------------------% | dsaitr was unable to build an Lanczos factorization | | of length NEV0+NP0. INFO is returned with the size | | of the factorization built. Exit main loop. | %-----------------------------------------------------% */ *np = *info; *mxiter = iter; *info = -9999; goto L1200; } update = FALSE_; if (msglvl > 1) { igraphdvout_(&logfil, &c__1, &rnorm, &ndigit, "_saup2: Current B-norm of r" "esidual for factorization", (ftnlen)52); } /* %--------------------------------------------------------% | Compute the eigenvalues and corresponding error bounds | | of the current symmetric tridiagonal matrix. | %--------------------------------------------------------% */ igraphdseigt_(&rnorm, &kplusp, &h__[h_offset], ldh, &ritz[1], &bounds[1], & workl[1], &ierr); if (ierr != 0) { *info = -8; goto L1200; } /* %----------------------------------------------------% | Make a copy of eigenvalues and corresponding error | | bounds obtained from _seigt. | %----------------------------------------------------% */ igraphdcopy_(&kplusp, &ritz[1], &c__1, &workl[kplusp + 1], &c__1); igraphdcopy_(&kplusp, &bounds[1], &c__1, &workl[(kplusp << 1) + 1], &c__1); /* %---------------------------------------------------% | Select the wanted Ritz values and their bounds | | to be used in the convergence test. | | The selection is based on the requested number of | | eigenvalues instead of the current NEV and NP to | | prevent possible misconvergence. | | * Wanted Ritz values := RITZ(NP+1:NEV+NP) | | * Shifts := RITZ(1:NP) := WORKL(1:NP) | %---------------------------------------------------% */ *nev = nev0; *np = np0; igraphdsgets_(ishift, which, nev, np, &ritz[1], &bounds[1], &workl[1]); /* %-------------------% | Convergence test. | %-------------------% */ igraphdcopy_(nev, &bounds[*np + 1], &c__1, &workl[*np + 1], &c__1); igraphdsconv_(nev, &ritz[*np + 1], &workl[*np + 1], tol, &nconv); if (msglvl > 2) { kp[0] = *nev; kp[1] = *np; kp[2] = nconv; igraphivout_(&logfil, &c__3, kp, &ndigit, "_saup2: NEV, NP, NCONV are", ( ftnlen)26); igraphdvout_(&logfil, &kplusp, &ritz[1], &ndigit, "_saup2: The eigenvalues" " of H", (ftnlen)28); igraphdvout_(&logfil, &kplusp, &bounds[1], &ndigit, "_saup2: Ritz estimate" "s of the current NCV Ritz values", (ftnlen)53); } /* %---------------------------------------------------------% | Count the number of unwanted Ritz values that have zero | | Ritz estimates. If any Ritz estimates are equal to zero | | then a leading block of H of order equal to at least | | the number of Ritz values with zero Ritz estimates has | | split off. None of these Ritz values may be removed by | | shifting. Decrease NP the number of shifts to apply. If | | no shifts may be applied, then prepare to exit | %---------------------------------------------------------% */ nptemp = *np; i__1 = nptemp; for (j = 1; j <= i__1; ++j) { if (bounds[j] == 0.) { --(*np); ++(*nev); } /* L30: */ } if (nconv >= nev0 || iter > *mxiter || *np == 0) { /* %------------------------------------------------% | Prepare to exit. Put the converged Ritz values | | and corresponding bounds in RITZ(1:NCONV) and | | BOUNDS(1:NCONV) respectively. Then sort. Be | | careful when NCONV > NP since we don't want to | | swap overlapping locations. | %------------------------------------------------% */ if (s_cmp(which, "BE", (ftnlen)2, (ftnlen)2) == 0) { /* %-----------------------------------------------------% | Both ends of the spectrum are requested. | | Sort the eigenvalues into algebraically decreasing | | order first then swap low end of the spectrum next | | to high end in appropriate locations. | | NOTE: when np < floor(nev/2) be careful not to swap | | overlapping locations. | %-----------------------------------------------------% */ s_copy(wprime, "SA", (ftnlen)2, (ftnlen)2); igraphdsortr_(wprime, &c_true, &kplusp, &ritz[1], &bounds[1]) ; nevd2 = *nev / 2; nevm2 = *nev - nevd2; if (*nev > 1) { i__1 = min(nevd2,*np); /* Computing MAX */ i__2 = kplusp - nevd2 + 1, i__3 = kplusp - *np + 1; igraphdswap_(&i__1, &ritz[nevm2 + 1], &c__1, &ritz[max(i__2,i__3)], &c__1); i__1 = min(nevd2,*np); /* Computing MAX */ i__2 = kplusp - nevd2 + 1, i__3 = kplusp - *np; igraphdswap_(&i__1, &bounds[nevm2 + 1], &c__1, &bounds[max(i__2, i__3) + 1], &c__1); } } else { /* %--------------------------------------------------% | LM, SM, LA, SA case. | | Sort the eigenvalues of H into the an order that | | is opposite to WHICH, and apply the resulting | | order to BOUNDS. The eigenvalues are sorted so | | that the wanted part are always within the first | | NEV locations. | %--------------------------------------------------% */ if (s_cmp(which, "LM", (ftnlen)2, (ftnlen)2) == 0) { s_copy(wprime, "SM", (ftnlen)2, (ftnlen)2); } if (s_cmp(which, "SM", (ftnlen)2, (ftnlen)2) == 0) { s_copy(wprime, "LM", (ftnlen)2, (ftnlen)2); } if (s_cmp(which, "LA", (ftnlen)2, (ftnlen)2) == 0) { s_copy(wprime, "SA", (ftnlen)2, (ftnlen)2); } if (s_cmp(which, "SA", (ftnlen)2, (ftnlen)2) == 0) { s_copy(wprime, "LA", (ftnlen)2, (ftnlen)2); } igraphdsortr_(wprime, &c_true, &kplusp, &ritz[1], &bounds[1]) ; } /* %--------------------------------------------------% | Scale the Ritz estimate of each Ritz value | | by 1 / max(eps23,magnitude of the Ritz value). | %--------------------------------------------------% */ i__1 = nev0; for (j = 1; j <= i__1; ++j) { /* Computing MAX */ d__2 = eps23, d__3 = (d__1 = ritz[j], abs(d__1)); temp = max(d__2,d__3); bounds[j] /= temp; /* L35: */ } /* %----------------------------------------------------% | Sort the Ritz values according to the scaled Ritz | | esitmates. This will push all the converged ones | | towards the front of ritzr, ritzi, bounds | | (in the case when NCONV < NEV.) | %----------------------------------------------------% */ s_copy(wprime, "LA", (ftnlen)2, (ftnlen)2); igraphdsortr_(wprime, &c_true, &nev0, &bounds[1], &ritz[1]); /* %----------------------------------------------% | Scale the Ritz estimate back to its original | | value. | %----------------------------------------------% */ i__1 = nev0; for (j = 1; j <= i__1; ++j) { /* Computing MAX */ d__2 = eps23, d__3 = (d__1 = ritz[j], abs(d__1)); temp = max(d__2,d__3); bounds[j] *= temp; /* L40: */ } /* %--------------------------------------------------% | Sort the "converged" Ritz values again so that | | the "threshold" values and their associated Ritz | | estimates appear at the appropriate position in | | ritz and bound. | %--------------------------------------------------% */ if (s_cmp(which, "BE", (ftnlen)2, (ftnlen)2) == 0) { /* %------------------------------------------------% | Sort the "converged" Ritz values in increasing | | order. The "threshold" values are in the | | middle. | %------------------------------------------------% */ s_copy(wprime, "LA", (ftnlen)2, (ftnlen)2); igraphdsortr_(wprime, &c_true, &nconv, &ritz[1], &bounds[1]); } else { /* %----------------------------------------------% | In LM, SM, LA, SA case, sort the "converged" | | Ritz values according to WHICH so that the | | "threshold" value appears at the front of | | ritz. | %----------------------------------------------% */ igraphdsortr_(which, &c_true, &nconv, &ritz[1], &bounds[1]); } /* %------------------------------------------% | Use h( 1,1 ) as storage to communicate | | rnorm to _seupd if needed | %------------------------------------------% */ h__[h_dim1 + 1] = rnorm; if (msglvl > 1) { igraphdvout_(&logfil, &kplusp, &ritz[1], &ndigit, "_saup2: Sorted Ritz" " values.", (ftnlen)27); igraphdvout_(&logfil, &kplusp, &bounds[1], &ndigit, "_saup2: Sorted ri" "tz estimates.", (ftnlen)30); } /* %------------------------------------% | Max iterations have been exceeded. | %------------------------------------% */ if (iter > *mxiter && nconv < *nev) { *info = 1; } /* %---------------------% | No shifts to apply. | %---------------------% */ if (*np == 0 && nconv < nev0) { *info = 2; } *np = nconv; goto L1100; } else if (nconv < *nev && *ishift == 1) { /* %---------------------------------------------------% | Do not have all the requested eigenvalues yet. | | To prevent possible stagnation, adjust the number | | of Ritz values and the shifts. | %---------------------------------------------------% */ nevbef = *nev; /* Computing MIN */ i__1 = nconv, i__2 = *np / 2; *nev += min(i__1,i__2); if (*nev == 1 && kplusp >= 6) { *nev = kplusp / 2; } else if (*nev == 1 && kplusp > 2) { *nev = 2; } *np = kplusp - *nev; /* %---------------------------------------% | If the size of NEV was just increased | | resort the eigenvalues. | %---------------------------------------% */ if (nevbef < *nev) { igraphdsgets_(ishift, which, nev, np, &ritz[1], &bounds[1], &workl[1]); } } if (msglvl > 0) { igraphivout_(&logfil, &c__1, &nconv, &ndigit, "_saup2: no. of \"converge" "d\" Ritz values at this iter.", (ftnlen)52); if (msglvl > 1) { kp[0] = *nev; kp[1] = *np; igraphivout_(&logfil, &c__2, kp, &ndigit, "_saup2: NEV and NP are", ( ftnlen)22); igraphdvout_(&logfil, nev, &ritz[*np + 1], &ndigit, "_saup2: \"wante" "d\" Ritz values.", (ftnlen)29); igraphdvout_(&logfil, nev, &bounds[*np + 1], &ndigit, "_saup2: Ritz es" "timates of the \"wanted\" values ", (ftnlen)46); } } if (*ishift == 0) { /* %-----------------------------------------------------% | User specified shifts: reverse communication to | | compute the shifts. They are returned in the first | | NP locations of WORKL. | %-----------------------------------------------------% */ ushift = TRUE_; *ido = 3; goto L9000; } L50: /* %------------------------------------% | Back from reverse communication; | | User specified shifts are returned | | in WORKL(1:*NP) | %------------------------------------% */ ushift = FALSE_; /* %---------------------------------------------------------% | Move the NP shifts to the first NP locations of RITZ to | | free up WORKL. This is for the non-exact shift case; | | in the exact shift case, dsgets already handles this. | %---------------------------------------------------------% */ if (*ishift == 0) { igraphdcopy_(np, &workl[1], &c__1, &ritz[1], &c__1); } if (msglvl > 2) { igraphivout_(&logfil, &c__1, np, &ndigit, "_saup2: The number of shifts to" " apply ", (ftnlen)38); igraphdvout_(&logfil, np, &workl[1], &ndigit, "_saup2: shifts selected", ( ftnlen)23); if (*ishift == 1) { igraphdvout_(&logfil, np, &bounds[1], &ndigit, "_saup2: corresponding " "Ritz estimates", (ftnlen)36); } } /* %---------------------------------------------------------% | Apply the NP0 implicit shifts by QR bulge chasing. | | Each shift is applied to the entire tridiagonal matrix. | | The first 2*N locations of WORKD are used as workspace. | | After dsapps is done, we have a Lanczos | | factorization of length NEV. | %---------------------------------------------------------% */ igraphdsapps_(n, nev, np, &ritz[1], &v[v_offset], ldv, &h__[h_offset], ldh, & resid[1], &q[q_offset], ldq, &workd[1]); /* %---------------------------------------------% | Compute the B-norm of the updated residual. | | Keep B*RESID in WORKD(1:N) to be used in | | the first step of the next call to dsaitr. | %---------------------------------------------% */ cnorm = TRUE_; igraphsecond_(&t2); if (*(unsigned char *)bmat == 'G') { ++nbx; igraphdcopy_(n, &resid[1], &c__1, &workd[*n + 1], &c__1); ipntr[1] = *n + 1; ipntr[2] = 1; *ido = 2; /* %----------------------------------% | Exit in order to compute B*RESID | %----------------------------------% */ goto L9000; } else if (*(unsigned char *)bmat == 'I') { igraphdcopy_(n, &resid[1], &c__1, &workd[1], &c__1); } L100: /* %----------------------------------% | Back from reverse communication; | | WORKD(1:N) := B*RESID | %----------------------------------% */ if (*(unsigned char *)bmat == 'G') { igraphsecond_(&t3); tmvbx += t3 - t2; } if (*(unsigned char *)bmat == 'G') { rnorm = igraphddot_(n, &resid[1], &c__1, &workd[1], &c__1); rnorm = sqrt((abs(rnorm))); } else if (*(unsigned char *)bmat == 'I') { rnorm = igraphdnrm2_(n, &resid[1], &c__1); } cnorm = FALSE_; /* L130: */ if (msglvl > 2) { igraphdvout_(&logfil, &c__1, &rnorm, &ndigit, "_saup2: B-norm of residual " "for NEV factorization", (ftnlen)48); igraphdvout_(&logfil, nev, &h__[(h_dim1 << 1) + 1], &ndigit, "_saup2: main" " diagonal of compressed H matrix", (ftnlen)44); i__1 = *nev - 1; igraphdvout_(&logfil, &i__1, &h__[h_dim1 + 2], &ndigit, "_saup2: subdiagon" "al of compressed H matrix", (ftnlen)42); } goto L1000; /* %---------------------------------------------------------------% | | | E N D O F M A I N I T E R A T I O N L O O P | | | %---------------------------------------------------------------% */ L1100: *mxiter = iter; *nev = nconv; L1200: *ido = 99; /* %------------% | Error exit | %------------% */ igraphsecond_(&t1); tsaup2 = t1 - t0; L9000: return 0; /* %---------------% | End of dsaup2 | %---------------% */ } /* igraphdsaup2_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/debug.h0000644000076500000240000000000013524616145024065 0ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/src/lapack/iparmq.c0000644000076500000240000003011513524616145024275 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b IPARMQ =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download IPARMQ + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== INTEGER FUNCTION IPARMQ( ISPEC, NAME, OPTS, N, ILO, IHI, LWORK ) INTEGER IHI, ILO, ISPEC, LWORK, N CHARACTER NAME*( * ), OPTS*( * ) > \par Purpose: ============= > > \verbatim > > This program sets problem and machine dependent parameters > useful for xHSEQR and its subroutines. It is called whenever > ILAENV is called with 12 <= ISPEC <= 16 > \endverbatim Arguments: ========== > \param[in] ISPEC > \verbatim > ISPEC is integer scalar > ISPEC specifies which tunable parameter IPARMQ should > return. > > ISPEC=12: (INMIN) Matrices of order nmin or less > are sent directly to xLAHQR, the implicit > double shift QR algorithm. NMIN must be > at least 11. > > ISPEC=13: (INWIN) Size of the deflation window. > This is best set greater than or equal to > the number of simultaneous shifts NS. > Larger matrices benefit from larger deflation > windows. > > ISPEC=14: (INIBL) Determines when to stop nibbling and > invest in an (expensive) multi-shift QR sweep. > If the aggressive early deflation subroutine > finds LD converged eigenvalues from an order > NW deflation window and LD.GT.(NW*NIBBLE)/100, > then the next QR sweep is skipped and early > deflation is applied immediately to the > remaining active diagonal block. Setting > IPARMQ(ISPEC=14) = 0 causes TTQRE to skip a > multi-shift QR sweep whenever early deflation > finds a converged eigenvalue. Setting > IPARMQ(ISPEC=14) greater than or equal to 100 > prevents TTQRE from skipping a multi-shift > QR sweep. > > ISPEC=15: (NSHFTS) The number of simultaneous shifts in > a multi-shift QR iteration. > > ISPEC=16: (IACC22) IPARMQ is set to 0, 1 or 2 with the > following meanings. > 0: During the multi-shift QR sweep, > xLAQR5 does not accumulate reflections and > does not use matrix-matrix multiply to > update the far-from-diagonal matrix > entries. > 1: During the multi-shift QR sweep, > xLAQR5 and/or xLAQRaccumulates reflections and uses > matrix-matrix multiply to update the > far-from-diagonal matrix entries. > 2: During the multi-shift QR sweep. > xLAQR5 accumulates reflections and takes > advantage of 2-by-2 block structure during > matrix-matrix multiplies. > (If xTRMM is slower than xGEMM, then > IPARMQ(ISPEC=16)=1 may be more efficient than > IPARMQ(ISPEC=16)=2 despite the greater level of > arithmetic work implied by the latter choice.) > \endverbatim > > \param[in] NAME > \verbatim > NAME is character string > Name of the calling subroutine > \endverbatim > > \param[in] OPTS > \verbatim > OPTS is character string > This is a concatenation of the string arguments to > TTQRE. > \endverbatim > > \param[in] N > \verbatim > N is integer scalar > N is the order of the Hessenberg matrix H. > \endverbatim > > \param[in] ILO > \verbatim > ILO is INTEGER > \endverbatim > > \param[in] IHI > \verbatim > IHI is INTEGER > It is assumed that H is already upper triangular > in rows and columns 1:ILO-1 and IHI+1:N. > \endverbatim > > \param[in] LWORK > \verbatim > LWORK is integer scalar > The amount of workspace available. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2011 > \ingroup auxOTHERauxiliary > \par Further Details: ===================== > > \verbatim > > Little is known about how best to choose these parameters. > It is possible to use different values of the parameters > for each of CHSEQR, DHSEQR, SHSEQR and ZHSEQR. > > It is probably best to choose different parameters for > different matrices and different parameters at different > times during the iteration, but this has not been > implemented --- yet. > > > The best choices of most of the parameters depend > in an ill-understood way on the relative execution > rate of xLAQR3 and xLAQR5 and on the nature of each > particular eigenvalue problem. Experiment may be the > only practical way to determine which choices are most > effective. > > Following is a list of default values supplied by IPARMQ. > These defaults may be adjusted in order to attain better > performance in any particular computational environment. > > IPARMQ(ISPEC=12) The xLAHQR vs xLAQR0 crossover point. > Default: 75. (Must be at least 11.) > > IPARMQ(ISPEC=13) Recommended deflation window size. > This depends on ILO, IHI and NS, the > number of simultaneous shifts returned > by IPARMQ(ISPEC=15). The default for > (IHI-ILO+1).LE.500 is NS. The default > for (IHI-ILO+1).GT.500 is 3*NS/2. > > IPARMQ(ISPEC=14) Nibble crossover point. Default: 14. > > IPARMQ(ISPEC=15) Number of simultaneous shifts, NS. > a multi-shift QR iteration. > > If IHI-ILO+1 is ... > > greater than ...but less ... the > or equal to ... than default is > > 0 30 NS = 2+ > 30 60 NS = 4+ > 60 150 NS = 10 > 150 590 NS = ** > 590 3000 NS = 64 > 3000 6000 NS = 128 > 6000 infinity NS = 256 > > (+) By default matrices of this order are > passed to the implicit double shift routine > xLAHQR. See IPARMQ(ISPEC=12) above. These > values of NS are used only in case of a rare > xLAHQR failure. > > (**) The asterisks (**) indicate an ad-hoc > function increasing from 10 to 64. > > IPARMQ(ISPEC=16) Select structured matrix multiply. > (See ISPEC=16 above for details.) > Default: 3. > \endverbatim > ===================================================================== */ integer igraphiparmq_(integer *ispec, char *name__, char *opts, integer *n, integer *ilo, integer *ihi, integer *lwork) { /* System generated locals */ integer ret_val, i__1, i__2; real r__1; /* Builtin functions */ double log(doublereal); integer i_nint(real *); /* Local variables */ integer nh, ns; /* -- LAPACK auxiliary routine (version 3.4.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2011 ================================================================ */ if (*ispec == 15 || *ispec == 13 || *ispec == 16) { /* ==== Set the number simultaneous shifts ==== */ nh = *ihi - *ilo + 1; ns = 2; if (nh >= 30) { ns = 4; } if (nh >= 60) { ns = 10; } if (nh >= 150) { /* Computing MAX */ r__1 = log((real) nh) / log(2.f); i__1 = 10, i__2 = nh / i_nint(&r__1); ns = max(i__1,i__2); } if (nh >= 590) { ns = 64; } if (nh >= 3000) { ns = 128; } if (nh >= 6000) { ns = 256; } /* Computing MAX */ i__1 = 2, i__2 = ns - ns % 2; ns = max(i__1,i__2); } if (*ispec == 12) { /* ===== Matrices of order smaller than NMIN get sent . to xLAHQR, the classic double shift algorithm. . This must be at least 11. ==== */ ret_val = 75; } else if (*ispec == 14) { /* ==== INIBL: skip a multi-shift qr iteration and . whenever aggressive early deflation finds . at least (NIBBLE*(window size)/100) deflations. ==== */ ret_val = 14; } else if (*ispec == 15) { /* ==== NSHFTS: The number of simultaneous shifts ===== */ ret_val = ns; } else if (*ispec == 13) { /* ==== NW: deflation window size. ==== */ if (nh <= 500) { ret_val = ns; } else { ret_val = ns * 3 / 2; } } else if (*ispec == 16) { /* ==== IACC22: Whether to accumulate reflections . before updating the far-from-diagonal elements . and whether to use 2-by-2 block structure while . doing it. A small amount of work could be saved . by making this choice dependent also upon the . NH=IHI-ILO+1. */ ret_val = 0; if (ns >= 14) { ret_val = 1; } if (ns >= 14) { ret_val = 2; } } else { /* ===== invalid value of ispec ===== */ ret_val = -1; } /* ==== End of IPARMQ ==== */ return ret_val; } /* igraphiparmq_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dtrevc.c0000644000076500000240000010642013524616145024276 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static logical c_false = FALSE_; static integer c__1 = 1; static doublereal c_b22 = 1.; static doublereal c_b25 = 0.; static integer c__2 = 2; static logical c_true = TRUE_; /* > \brief \b DTREVC =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DTREVC + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DTREVC( SIDE, HOWMNY, SELECT, N, T, LDT, VL, LDVL, VR, LDVR, MM, M, WORK, INFO ) CHARACTER HOWMNY, SIDE INTEGER INFO, LDT, LDVL, LDVR, M, MM, N LOGICAL SELECT( * ) DOUBLE PRECISION T( LDT, * ), VL( LDVL, * ), VR( LDVR, * ), $ WORK( * ) > \par Purpose: ============= > > \verbatim > > DTREVC computes some or all of the right and/or left eigenvectors of > a real upper quasi-triangular matrix T. > Matrices of this type are produced by the Schur factorization of > a real general matrix: A = Q*T*Q**T, as computed by DHSEQR. > > The right eigenvector x and the left eigenvector y of T corresponding > to an eigenvalue w are defined by: > > T*x = w*x, (y**T)*T = w*(y**T) > > where y**T denotes the transpose of y. > The eigenvalues are not input to this routine, but are read directly > from the diagonal blocks of T. > > This routine returns the matrices X and/or Y of right and left > eigenvectors of T, or the products Q*X and/or Q*Y, where Q is an > input matrix. If Q is the orthogonal factor that reduces a matrix > A to Schur form T, then Q*X and Q*Y are the matrices of right and > left eigenvectors of A. > \endverbatim Arguments: ========== > \param[in] SIDE > \verbatim > SIDE is CHARACTER*1 > = 'R': compute right eigenvectors only; > = 'L': compute left eigenvectors only; > = 'B': compute both right and left eigenvectors. > \endverbatim > > \param[in] HOWMNY > \verbatim > HOWMNY is CHARACTER*1 > = 'A': compute all right and/or left eigenvectors; > = 'B': compute all right and/or left eigenvectors, > backtransformed by the matrices in VR and/or VL; > = 'S': compute selected right and/or left eigenvectors, > as indicated by the logical array SELECT. > \endverbatim > > \param[in,out] SELECT > \verbatim > SELECT is LOGICAL array, dimension (N) > If HOWMNY = 'S', SELECT specifies the eigenvectors to be > computed. > If w(j) is a real eigenvalue, the corresponding real > eigenvector is computed if SELECT(j) is .TRUE.. > If w(j) and w(j+1) are the real and imaginary parts of a > complex eigenvalue, the corresponding complex eigenvector is > computed if either SELECT(j) or SELECT(j+1) is .TRUE., and > on exit SELECT(j) is set to .TRUE. and SELECT(j+1) is set to > .FALSE.. > Not referenced if HOWMNY = 'A' or 'B'. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix T. N >= 0. > \endverbatim > > \param[in] T > \verbatim > T is DOUBLE PRECISION array, dimension (LDT,N) > The upper quasi-triangular matrix T in Schur canonical form. > \endverbatim > > \param[in] LDT > \verbatim > LDT is INTEGER > The leading dimension of the array T. LDT >= max(1,N). > \endverbatim > > \param[in,out] VL > \verbatim > VL is DOUBLE PRECISION array, dimension (LDVL,MM) > On entry, if SIDE = 'L' or 'B' and HOWMNY = 'B', VL must > contain an N-by-N matrix Q (usually the orthogonal matrix Q > of Schur vectors returned by DHSEQR). > On exit, if SIDE = 'L' or 'B', VL contains: > if HOWMNY = 'A', the matrix Y of left eigenvectors of T; > if HOWMNY = 'B', the matrix Q*Y; > if HOWMNY = 'S', the left eigenvectors of T specified by > SELECT, stored consecutively in the columns > of VL, in the same order as their > eigenvalues. > A complex eigenvector corresponding to a complex eigenvalue > is stored in two consecutive columns, the first holding the > real part, and the second the imaginary part. > Not referenced if SIDE = 'R'. > \endverbatim > > \param[in] LDVL > \verbatim > LDVL is INTEGER > The leading dimension of the array VL. LDVL >= 1, and if > SIDE = 'L' or 'B', LDVL >= N. > \endverbatim > > \param[in,out] VR > \verbatim > VR is DOUBLE PRECISION array, dimension (LDVR,MM) > On entry, if SIDE = 'R' or 'B' and HOWMNY = 'B', VR must > contain an N-by-N matrix Q (usually the orthogonal matrix Q > of Schur vectors returned by DHSEQR). > On exit, if SIDE = 'R' or 'B', VR contains: > if HOWMNY = 'A', the matrix X of right eigenvectors of T; > if HOWMNY = 'B', the matrix Q*X; > if HOWMNY = 'S', the right eigenvectors of T specified by > SELECT, stored consecutively in the columns > of VR, in the same order as their > eigenvalues. > A complex eigenvector corresponding to a complex eigenvalue > is stored in two consecutive columns, the first holding the > real part and the second the imaginary part. > Not referenced if SIDE = 'L'. > \endverbatim > > \param[in] LDVR > \verbatim > LDVR is INTEGER > The leading dimension of the array VR. LDVR >= 1, and if > SIDE = 'R' or 'B', LDVR >= N. > \endverbatim > > \param[in] MM > \verbatim > MM is INTEGER > The number of columns in the arrays VL and/or VR. MM >= M. > \endverbatim > > \param[out] M > \verbatim > M is INTEGER > The number of columns in the arrays VL and/or VR actually > used to store the eigenvectors. > If HOWMNY = 'A' or 'B', M is set to N. > Each selected real eigenvector occupies one column and each > selected complex eigenvector occupies two columns. > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (3*N) > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2011 > \ingroup doubleOTHERcomputational > \par Further Details: ===================== > > \verbatim > > The algorithm used in this program is basically backward (forward) > substitution, with scaling to make the the code robust against > possible overflow. > > Each eigenvector is normalized so that the element of largest > magnitude has magnitude 1; here the magnitude of a complex number > (x,y) is taken to be |x| + |y|. > \endverbatim > ===================================================================== Subroutine */ int igraphdtrevc_(char *side, char *howmny, logical *select, integer *n, doublereal *t, integer *ldt, doublereal *vl, integer * ldvl, doublereal *vr, integer *ldvr, integer *mm, integer *m, doublereal *work, integer *info) { /* System generated locals */ integer t_dim1, t_offset, vl_dim1, vl_offset, vr_dim1, vr_offset, i__1, i__2, i__3; doublereal d__1, d__2, d__3, d__4; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ integer i__, j, k; doublereal x[4] /* was [2][2] */; integer j1, j2, n2, ii, ki, ip, is; doublereal wi, wr, rec, ulp, beta, emax; logical pair; extern doublereal igraphddot_(integer *, doublereal *, integer *, doublereal *, integer *); logical allv; integer ierr; doublereal unfl, ovfl, smin; logical over; doublereal vmax; integer jnxt; extern /* Subroutine */ int igraphdscal_(integer *, doublereal *, doublereal *, integer *); doublereal scale; extern logical igraphlsame_(char *, char *); extern /* Subroutine */ int igraphdgemv_(char *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *); doublereal remax; extern /* Subroutine */ int igraphdcopy_(integer *, doublereal *, integer *, doublereal *, integer *); logical leftv, bothv; extern /* Subroutine */ int igraphdaxpy_(integer *, doublereal *, doublereal *, integer *, doublereal *, integer *); doublereal vcrit; logical somev; doublereal xnorm; extern /* Subroutine */ int igraphdlaln2_(logical *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, integer *, doublereal *, doublereal * , doublereal *, integer *, doublereal *, doublereal *, integer *), igraphdlabad_(doublereal *, doublereal *); extern doublereal igraphdlamch_(char *); extern integer igraphidamax_(integer *, doublereal *, integer *); extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); doublereal bignum; logical rightv; doublereal smlnum; /* -- LAPACK computational routine (version 3.4.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2011 ===================================================================== Decode and test the input parameters Parameter adjustments */ --select; t_dim1 = *ldt; t_offset = 1 + t_dim1; t -= t_offset; vl_dim1 = *ldvl; vl_offset = 1 + vl_dim1; vl -= vl_offset; vr_dim1 = *ldvr; vr_offset = 1 + vr_dim1; vr -= vr_offset; --work; /* Function Body */ bothv = igraphlsame_(side, "B"); rightv = igraphlsame_(side, "R") || bothv; leftv = igraphlsame_(side, "L") || bothv; allv = igraphlsame_(howmny, "A"); over = igraphlsame_(howmny, "B"); somev = igraphlsame_(howmny, "S"); *info = 0; if (! rightv && ! leftv) { *info = -1; } else if (! allv && ! over && ! somev) { *info = -2; } else if (*n < 0) { *info = -4; } else if (*ldt < max(1,*n)) { *info = -6; } else if (*ldvl < 1 || leftv && *ldvl < *n) { *info = -8; } else if (*ldvr < 1 || rightv && *ldvr < *n) { *info = -10; } else { /* Set M to the number of columns required to store the selected eigenvectors, standardize the array SELECT if necessary, and test MM. */ if (somev) { *m = 0; pair = FALSE_; i__1 = *n; for (j = 1; j <= i__1; ++j) { if (pair) { pair = FALSE_; select[j] = FALSE_; } else { if (j < *n) { if (t[j + 1 + j * t_dim1] == 0.) { if (select[j]) { ++(*m); } } else { pair = TRUE_; if (select[j] || select[j + 1]) { select[j] = TRUE_; *m += 2; } } } else { if (select[*n]) { ++(*m); } } } /* L10: */ } } else { *m = *n; } if (*mm < *m) { *info = -11; } } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DTREVC", &i__1, (ftnlen)6); return 0; } /* Quick return if possible. */ if (*n == 0) { return 0; } /* Set the constants to control overflow. */ unfl = igraphdlamch_("Safe minimum"); ovfl = 1. / unfl; igraphdlabad_(&unfl, &ovfl); ulp = igraphdlamch_("Precision"); smlnum = unfl * (*n / ulp); bignum = (1. - ulp) / smlnum; /* Compute 1-norm of each column of strictly upper triangular part of T to control overflow in triangular solver. */ work[1] = 0.; i__1 = *n; for (j = 2; j <= i__1; ++j) { work[j] = 0.; i__2 = j - 1; for (i__ = 1; i__ <= i__2; ++i__) { work[j] += (d__1 = t[i__ + j * t_dim1], abs(d__1)); /* L20: */ } /* L30: */ } /* Index IP is used to specify the real or complex eigenvalue: IP = 0, real eigenvalue, 1, first of conjugate complex pair: (wr,wi) -1, second of conjugate complex pair: (wr,wi) */ n2 = *n << 1; if (rightv) { /* Compute right eigenvectors. */ ip = 0; is = *m; for (ki = *n; ki >= 1; --ki) { if (ip == 1) { goto L130; } if (ki == 1) { goto L40; } if (t[ki + (ki - 1) * t_dim1] == 0.) { goto L40; } ip = -1; L40: if (somev) { if (ip == 0) { if (! select[ki]) { goto L130; } } else { if (! select[ki - 1]) { goto L130; } } } /* Compute the KI-th eigenvalue (WR,WI). */ wr = t[ki + ki * t_dim1]; wi = 0.; if (ip != 0) { wi = sqrt((d__1 = t[ki + (ki - 1) * t_dim1], abs(d__1))) * sqrt((d__2 = t[ki - 1 + ki * t_dim1], abs(d__2))); } /* Computing MAX */ d__1 = ulp * (abs(wr) + abs(wi)); smin = max(d__1,smlnum); if (ip == 0) { /* Real right eigenvector */ work[ki + *n] = 1.; /* Form right-hand side */ i__1 = ki - 1; for (k = 1; k <= i__1; ++k) { work[k + *n] = -t[k + ki * t_dim1]; /* L50: */ } /* Solve the upper quasi-triangular system: (T(1:KI-1,1:KI-1) - WR)*X = SCALE*WORK. */ jnxt = ki - 1; for (j = ki - 1; j >= 1; --j) { if (j > jnxt) { goto L60; } j1 = j; j2 = j; jnxt = j - 1; if (j > 1) { if (t[j + (j - 1) * t_dim1] != 0.) { j1 = j - 1; jnxt = j - 2; } } if (j1 == j2) { /* 1-by-1 diagonal block */ igraphdlaln2_(&c_false, &c__1, &c__1, &smin, &c_b22, &t[j + j * t_dim1], ldt, &c_b22, &c_b22, &work[j + * n], n, &wr, &c_b25, x, &c__2, &scale, &xnorm, &ierr); /* Scale X(1,1) to avoid overflow when updating the right-hand side. */ if (xnorm > 1.) { if (work[j] > bignum / xnorm) { x[0] /= xnorm; scale /= xnorm; } } /* Scale if necessary */ if (scale != 1.) { igraphdscal_(&ki, &scale, &work[*n + 1], &c__1); } work[j + *n] = x[0]; /* Update right-hand side */ i__1 = j - 1; d__1 = -x[0]; igraphdaxpy_(&i__1, &d__1, &t[j * t_dim1 + 1], &c__1, &work[ *n + 1], &c__1); } else { /* 2-by-2 diagonal block */ igraphdlaln2_(&c_false, &c__2, &c__1, &smin, &c_b22, &t[j - 1 + (j - 1) * t_dim1], ldt, &c_b22, &c_b22, & work[j - 1 + *n], n, &wr, &c_b25, x, &c__2, & scale, &xnorm, &ierr); /* Scale X(1,1) and X(2,1) to avoid overflow when updating the right-hand side. */ if (xnorm > 1.) { /* Computing MAX */ d__1 = work[j - 1], d__2 = work[j]; beta = max(d__1,d__2); if (beta > bignum / xnorm) { x[0] /= xnorm; x[1] /= xnorm; scale /= xnorm; } } /* Scale if necessary */ if (scale != 1.) { igraphdscal_(&ki, &scale, &work[*n + 1], &c__1); } work[j - 1 + *n] = x[0]; work[j + *n] = x[1]; /* Update right-hand side */ i__1 = j - 2; d__1 = -x[0]; igraphdaxpy_(&i__1, &d__1, &t[(j - 1) * t_dim1 + 1], &c__1, &work[*n + 1], &c__1); i__1 = j - 2; d__1 = -x[1]; igraphdaxpy_(&i__1, &d__1, &t[j * t_dim1 + 1], &c__1, &work[ *n + 1], &c__1); } L60: ; } /* Copy the vector x or Q*x to VR and normalize. */ if (! over) { igraphdcopy_(&ki, &work[*n + 1], &c__1, &vr[is * vr_dim1 + 1], & c__1); ii = igraphidamax_(&ki, &vr[is * vr_dim1 + 1], &c__1); remax = 1. / (d__1 = vr[ii + is * vr_dim1], abs(d__1)); igraphdscal_(&ki, &remax, &vr[is * vr_dim1 + 1], &c__1); i__1 = *n; for (k = ki + 1; k <= i__1; ++k) { vr[k + is * vr_dim1] = 0.; /* L70: */ } } else { if (ki > 1) { i__1 = ki - 1; igraphdgemv_("N", n, &i__1, &c_b22, &vr[vr_offset], ldvr, & work[*n + 1], &c__1, &work[ki + *n], &vr[ki * vr_dim1 + 1], &c__1); } ii = igraphidamax_(n, &vr[ki * vr_dim1 + 1], &c__1); remax = 1. / (d__1 = vr[ii + ki * vr_dim1], abs(d__1)); igraphdscal_(n, &remax, &vr[ki * vr_dim1 + 1], &c__1); } } else { /* Complex right eigenvector. Initial solve [ (T(KI-1,KI-1) T(KI-1,KI) ) - (WR + I* WI)]*X = 0. [ (T(KI,KI-1) T(KI,KI) ) ] */ if ((d__1 = t[ki - 1 + ki * t_dim1], abs(d__1)) >= (d__2 = t[ ki + (ki - 1) * t_dim1], abs(d__2))) { work[ki - 1 + *n] = 1.; work[ki + n2] = wi / t[ki - 1 + ki * t_dim1]; } else { work[ki - 1 + *n] = -wi / t[ki + (ki - 1) * t_dim1]; work[ki + n2] = 1.; } work[ki + *n] = 0.; work[ki - 1 + n2] = 0.; /* Form right-hand side */ i__1 = ki - 2; for (k = 1; k <= i__1; ++k) { work[k + *n] = -work[ki - 1 + *n] * t[k + (ki - 1) * t_dim1]; work[k + n2] = -work[ki + n2] * t[k + ki * t_dim1]; /* L80: */ } /* Solve upper quasi-triangular system: (T(1:KI-2,1:KI-2) - (WR+i*WI))*X = SCALE*(WORK+i*WORK2) */ jnxt = ki - 2; for (j = ki - 2; j >= 1; --j) { if (j > jnxt) { goto L90; } j1 = j; j2 = j; jnxt = j - 1; if (j > 1) { if (t[j + (j - 1) * t_dim1] != 0.) { j1 = j - 1; jnxt = j - 2; } } if (j1 == j2) { /* 1-by-1 diagonal block */ igraphdlaln2_(&c_false, &c__1, &c__2, &smin, &c_b22, &t[j + j * t_dim1], ldt, &c_b22, &c_b22, &work[j + * n], n, &wr, &wi, x, &c__2, &scale, &xnorm, & ierr); /* Scale X(1,1) and X(1,2) to avoid overflow when updating the right-hand side. */ if (xnorm > 1.) { if (work[j] > bignum / xnorm) { x[0] /= xnorm; x[2] /= xnorm; scale /= xnorm; } } /* Scale if necessary */ if (scale != 1.) { igraphdscal_(&ki, &scale, &work[*n + 1], &c__1); igraphdscal_(&ki, &scale, &work[n2 + 1], &c__1); } work[j + *n] = x[0]; work[j + n2] = x[2]; /* Update the right-hand side */ i__1 = j - 1; d__1 = -x[0]; igraphdaxpy_(&i__1, &d__1, &t[j * t_dim1 + 1], &c__1, &work[ *n + 1], &c__1); i__1 = j - 1; d__1 = -x[2]; igraphdaxpy_(&i__1, &d__1, &t[j * t_dim1 + 1], &c__1, &work[ n2 + 1], &c__1); } else { /* 2-by-2 diagonal block */ igraphdlaln2_(&c_false, &c__2, &c__2, &smin, &c_b22, &t[j - 1 + (j - 1) * t_dim1], ldt, &c_b22, &c_b22, & work[j - 1 + *n], n, &wr, &wi, x, &c__2, & scale, &xnorm, &ierr); /* Scale X to avoid overflow when updating the right-hand side. */ if (xnorm > 1.) { /* Computing MAX */ d__1 = work[j - 1], d__2 = work[j]; beta = max(d__1,d__2); if (beta > bignum / xnorm) { rec = 1. / xnorm; x[0] *= rec; x[2] *= rec; x[1] *= rec; x[3] *= rec; scale *= rec; } } /* Scale if necessary */ if (scale != 1.) { igraphdscal_(&ki, &scale, &work[*n + 1], &c__1); igraphdscal_(&ki, &scale, &work[n2 + 1], &c__1); } work[j - 1 + *n] = x[0]; work[j + *n] = x[1]; work[j - 1 + n2] = x[2]; work[j + n2] = x[3]; /* Update the right-hand side */ i__1 = j - 2; d__1 = -x[0]; igraphdaxpy_(&i__1, &d__1, &t[(j - 1) * t_dim1 + 1], &c__1, &work[*n + 1], &c__1); i__1 = j - 2; d__1 = -x[1]; igraphdaxpy_(&i__1, &d__1, &t[j * t_dim1 + 1], &c__1, &work[ *n + 1], &c__1); i__1 = j - 2; d__1 = -x[2]; igraphdaxpy_(&i__1, &d__1, &t[(j - 1) * t_dim1 + 1], &c__1, &work[n2 + 1], &c__1); i__1 = j - 2; d__1 = -x[3]; igraphdaxpy_(&i__1, &d__1, &t[j * t_dim1 + 1], &c__1, &work[ n2 + 1], &c__1); } L90: ; } /* Copy the vector x or Q*x to VR and normalize. */ if (! over) { igraphdcopy_(&ki, &work[*n + 1], &c__1, &vr[(is - 1) * vr_dim1 + 1], &c__1); igraphdcopy_(&ki, &work[n2 + 1], &c__1, &vr[is * vr_dim1 + 1], & c__1); emax = 0.; i__1 = ki; for (k = 1; k <= i__1; ++k) { /* Computing MAX */ d__3 = emax, d__4 = (d__1 = vr[k + (is - 1) * vr_dim1] , abs(d__1)) + (d__2 = vr[k + is * vr_dim1], abs(d__2)); emax = max(d__3,d__4); /* L100: */ } remax = 1. / emax; igraphdscal_(&ki, &remax, &vr[(is - 1) * vr_dim1 + 1], &c__1); igraphdscal_(&ki, &remax, &vr[is * vr_dim1 + 1], &c__1); i__1 = *n; for (k = ki + 1; k <= i__1; ++k) { vr[k + (is - 1) * vr_dim1] = 0.; vr[k + is * vr_dim1] = 0.; /* L110: */ } } else { if (ki > 2) { i__1 = ki - 2; igraphdgemv_("N", n, &i__1, &c_b22, &vr[vr_offset], ldvr, & work[*n + 1], &c__1, &work[ki - 1 + *n], &vr[( ki - 1) * vr_dim1 + 1], &c__1); i__1 = ki - 2; igraphdgemv_("N", n, &i__1, &c_b22, &vr[vr_offset], ldvr, & work[n2 + 1], &c__1, &work[ki + n2], &vr[ki * vr_dim1 + 1], &c__1); } else { igraphdscal_(n, &work[ki - 1 + *n], &vr[(ki - 1) * vr_dim1 + 1], &c__1); igraphdscal_(n, &work[ki + n2], &vr[ki * vr_dim1 + 1], & c__1); } emax = 0.; i__1 = *n; for (k = 1; k <= i__1; ++k) { /* Computing MAX */ d__3 = emax, d__4 = (d__1 = vr[k + (ki - 1) * vr_dim1] , abs(d__1)) + (d__2 = vr[k + ki * vr_dim1], abs(d__2)); emax = max(d__3,d__4); /* L120: */ } remax = 1. / emax; igraphdscal_(n, &remax, &vr[(ki - 1) * vr_dim1 + 1], &c__1); igraphdscal_(n, &remax, &vr[ki * vr_dim1 + 1], &c__1); } } --is; if (ip != 0) { --is; } L130: if (ip == 1) { ip = 0; } if (ip == -1) { ip = 1; } /* L140: */ } } if (leftv) { /* Compute left eigenvectors. */ ip = 0; is = 1; i__1 = *n; for (ki = 1; ki <= i__1; ++ki) { if (ip == -1) { goto L250; } if (ki == *n) { goto L150; } if (t[ki + 1 + ki * t_dim1] == 0.) { goto L150; } ip = 1; L150: if (somev) { if (! select[ki]) { goto L250; } } /* Compute the KI-th eigenvalue (WR,WI). */ wr = t[ki + ki * t_dim1]; wi = 0.; if (ip != 0) { wi = sqrt((d__1 = t[ki + (ki + 1) * t_dim1], abs(d__1))) * sqrt((d__2 = t[ki + 1 + ki * t_dim1], abs(d__2))); } /* Computing MAX */ d__1 = ulp * (abs(wr) + abs(wi)); smin = max(d__1,smlnum); if (ip == 0) { /* Real left eigenvector. */ work[ki + *n] = 1.; /* Form right-hand side */ i__2 = *n; for (k = ki + 1; k <= i__2; ++k) { work[k + *n] = -t[ki + k * t_dim1]; /* L160: */ } /* Solve the quasi-triangular system: (T(KI+1:N,KI+1:N) - WR)**T*X = SCALE*WORK */ vmax = 1.; vcrit = bignum; jnxt = ki + 1; i__2 = *n; for (j = ki + 1; j <= i__2; ++j) { if (j < jnxt) { goto L170; } j1 = j; j2 = j; jnxt = j + 1; if (j < *n) { if (t[j + 1 + j * t_dim1] != 0.) { j2 = j + 1; jnxt = j + 2; } } if (j1 == j2) { /* 1-by-1 diagonal block Scale if necessary to avoid overflow when forming the right-hand side. */ if (work[j] > vcrit) { rec = 1. / vmax; i__3 = *n - ki + 1; igraphdscal_(&i__3, &rec, &work[ki + *n], &c__1); vmax = 1.; vcrit = bignum; } i__3 = j - ki - 1; work[j + *n] -= igraphddot_(&i__3, &t[ki + 1 + j * t_dim1], &c__1, &work[ki + 1 + *n], &c__1); /* Solve (T(J,J)-WR)**T*X = WORK */ igraphdlaln2_(&c_false, &c__1, &c__1, &smin, &c_b22, &t[j + j * t_dim1], ldt, &c_b22, &c_b22, &work[j + * n], n, &wr, &c_b25, x, &c__2, &scale, &xnorm, &ierr); /* Scale if necessary */ if (scale != 1.) { i__3 = *n - ki + 1; igraphdscal_(&i__3, &scale, &work[ki + *n], &c__1); } work[j + *n] = x[0]; /* Computing MAX */ d__2 = (d__1 = work[j + *n], abs(d__1)); vmax = max(d__2,vmax); vcrit = bignum / vmax; } else { /* 2-by-2 diagonal block Scale if necessary to avoid overflow when forming the right-hand side. Computing MAX */ d__1 = work[j], d__2 = work[j + 1]; beta = max(d__1,d__2); if (beta > vcrit) { rec = 1. / vmax; i__3 = *n - ki + 1; igraphdscal_(&i__3, &rec, &work[ki + *n], &c__1); vmax = 1.; vcrit = bignum; } i__3 = j - ki - 1; work[j + *n] -= igraphddot_(&i__3, &t[ki + 1 + j * t_dim1], &c__1, &work[ki + 1 + *n], &c__1); i__3 = j - ki - 1; work[j + 1 + *n] -= igraphddot_(&i__3, &t[ki + 1 + (j + 1) * t_dim1], &c__1, &work[ki + 1 + *n], &c__1); /* Solve [T(J,J)-WR T(J,J+1) ]**T * X = SCALE*( WORK1 ) [T(J+1,J) T(J+1,J+1)-WR] ( WORK2 ) */ igraphdlaln2_(&c_true, &c__2, &c__1, &smin, &c_b22, &t[j + j * t_dim1], ldt, &c_b22, &c_b22, &work[j + * n], n, &wr, &c_b25, x, &c__2, &scale, &xnorm, &ierr); /* Scale if necessary */ if (scale != 1.) { i__3 = *n - ki + 1; igraphdscal_(&i__3, &scale, &work[ki + *n], &c__1); } work[j + *n] = x[0]; work[j + 1 + *n] = x[1]; /* Computing MAX */ d__3 = (d__1 = work[j + *n], abs(d__1)), d__4 = (d__2 = work[j + 1 + *n], abs(d__2)), d__3 = max( d__3,d__4); vmax = max(d__3,vmax); vcrit = bignum / vmax; } L170: ; } /* Copy the vector x or Q*x to VL and normalize. */ if (! over) { i__2 = *n - ki + 1; igraphdcopy_(&i__2, &work[ki + *n], &c__1, &vl[ki + is * vl_dim1], &c__1); i__2 = *n - ki + 1; ii = igraphidamax_(&i__2, &vl[ki + is * vl_dim1], &c__1) + ki - 1; remax = 1. / (d__1 = vl[ii + is * vl_dim1], abs(d__1)); i__2 = *n - ki + 1; igraphdscal_(&i__2, &remax, &vl[ki + is * vl_dim1], &c__1); i__2 = ki - 1; for (k = 1; k <= i__2; ++k) { vl[k + is * vl_dim1] = 0.; /* L180: */ } } else { if (ki < *n) { i__2 = *n - ki; igraphdgemv_("N", n, &i__2, &c_b22, &vl[(ki + 1) * vl_dim1 + 1], ldvl, &work[ki + 1 + *n], &c__1, &work[ ki + *n], &vl[ki * vl_dim1 + 1], &c__1); } ii = igraphidamax_(n, &vl[ki * vl_dim1 + 1], &c__1); remax = 1. / (d__1 = vl[ii + ki * vl_dim1], abs(d__1)); igraphdscal_(n, &remax, &vl[ki * vl_dim1 + 1], &c__1); } } else { /* Complex left eigenvector. Initial solve: ((T(KI,KI) T(KI,KI+1) )**T - (WR - I* WI))*X = 0. ((T(KI+1,KI) T(KI+1,KI+1)) ) */ if ((d__1 = t[ki + (ki + 1) * t_dim1], abs(d__1)) >= (d__2 = t[ki + 1 + ki * t_dim1], abs(d__2))) { work[ki + *n] = wi / t[ki + (ki + 1) * t_dim1]; work[ki + 1 + n2] = 1.; } else { work[ki + *n] = 1.; work[ki + 1 + n2] = -wi / t[ki + 1 + ki * t_dim1]; } work[ki + 1 + *n] = 0.; work[ki + n2] = 0.; /* Form right-hand side */ i__2 = *n; for (k = ki + 2; k <= i__2; ++k) { work[k + *n] = -work[ki + *n] * t[ki + k * t_dim1]; work[k + n2] = -work[ki + 1 + n2] * t[ki + 1 + k * t_dim1] ; /* L190: */ } /* Solve complex quasi-triangular system: ( T(KI+2,N:KI+2,N) - (WR-i*WI) )*X = WORK1+i*WORK2 */ vmax = 1.; vcrit = bignum; jnxt = ki + 2; i__2 = *n; for (j = ki + 2; j <= i__2; ++j) { if (j < jnxt) { goto L200; } j1 = j; j2 = j; jnxt = j + 1; if (j < *n) { if (t[j + 1 + j * t_dim1] != 0.) { j2 = j + 1; jnxt = j + 2; } } if (j1 == j2) { /* 1-by-1 diagonal block Scale if necessary to avoid overflow when forming the right-hand side elements. */ if (work[j] > vcrit) { rec = 1. / vmax; i__3 = *n - ki + 1; igraphdscal_(&i__3, &rec, &work[ki + *n], &c__1); i__3 = *n - ki + 1; igraphdscal_(&i__3, &rec, &work[ki + n2], &c__1); vmax = 1.; vcrit = bignum; } i__3 = j - ki - 2; work[j + *n] -= igraphddot_(&i__3, &t[ki + 2 + j * t_dim1], &c__1, &work[ki + 2 + *n], &c__1); i__3 = j - ki - 2; work[j + n2] -= igraphddot_(&i__3, &t[ki + 2 + j * t_dim1], &c__1, &work[ki + 2 + n2], &c__1); /* Solve (T(J,J)-(WR-i*WI))*(X11+i*X12)= WK+I*WK2 */ d__1 = -wi; igraphdlaln2_(&c_false, &c__1, &c__2, &smin, &c_b22, &t[j + j * t_dim1], ldt, &c_b22, &c_b22, &work[j + * n], n, &wr, &d__1, x, &c__2, &scale, &xnorm, & ierr); /* Scale if necessary */ if (scale != 1.) { i__3 = *n - ki + 1; igraphdscal_(&i__3, &scale, &work[ki + *n], &c__1); i__3 = *n - ki + 1; igraphdscal_(&i__3, &scale, &work[ki + n2], &c__1); } work[j + *n] = x[0]; work[j + n2] = x[2]; /* Computing MAX */ d__3 = (d__1 = work[j + *n], abs(d__1)), d__4 = (d__2 = work[j + n2], abs(d__2)), d__3 = max(d__3, d__4); vmax = max(d__3,vmax); vcrit = bignum / vmax; } else { /* 2-by-2 diagonal block Scale if necessary to avoid overflow when forming the right-hand side elements. Computing MAX */ d__1 = work[j], d__2 = work[j + 1]; beta = max(d__1,d__2); if (beta > vcrit) { rec = 1. / vmax; i__3 = *n - ki + 1; igraphdscal_(&i__3, &rec, &work[ki + *n], &c__1); i__3 = *n - ki + 1; igraphdscal_(&i__3, &rec, &work[ki + n2], &c__1); vmax = 1.; vcrit = bignum; } i__3 = j - ki - 2; work[j + *n] -= igraphddot_(&i__3, &t[ki + 2 + j * t_dim1], &c__1, &work[ki + 2 + *n], &c__1); i__3 = j - ki - 2; work[j + n2] -= igraphddot_(&i__3, &t[ki + 2 + j * t_dim1], &c__1, &work[ki + 2 + n2], &c__1); i__3 = j - ki - 2; work[j + 1 + *n] -= igraphddot_(&i__3, &t[ki + 2 + (j + 1) * t_dim1], &c__1, &work[ki + 2 + *n], &c__1); i__3 = j - ki - 2; work[j + 1 + n2] -= igraphddot_(&i__3, &t[ki + 2 + (j + 1) * t_dim1], &c__1, &work[ki + 2 + n2], &c__1); /* Solve 2-by-2 complex linear equation ([T(j,j) T(j,j+1) ]**T-(wr-i*wi)*I)*X = SCALE*B ([T(j+1,j) T(j+1,j+1)] ) */ d__1 = -wi; igraphdlaln2_(&c_true, &c__2, &c__2, &smin, &c_b22, &t[j + j * t_dim1], ldt, &c_b22, &c_b22, &work[j + * n], n, &wr, &d__1, x, &c__2, &scale, &xnorm, & ierr); /* Scale if necessary */ if (scale != 1.) { i__3 = *n - ki + 1; igraphdscal_(&i__3, &scale, &work[ki + *n], &c__1); i__3 = *n - ki + 1; igraphdscal_(&i__3, &scale, &work[ki + n2], &c__1); } work[j + *n] = x[0]; work[j + n2] = x[2]; work[j + 1 + *n] = x[1]; work[j + 1 + n2] = x[3]; /* Computing MAX */ d__1 = abs(x[0]), d__2 = abs(x[2]), d__1 = max(d__1, d__2), d__2 = abs(x[1]), d__1 = max(d__1,d__2) , d__2 = abs(x[3]), d__1 = max(d__1,d__2); vmax = max(d__1,vmax); vcrit = bignum / vmax; } L200: ; } /* Copy the vector x or Q*x to VL and normalize. */ if (! over) { i__2 = *n - ki + 1; igraphdcopy_(&i__2, &work[ki + *n], &c__1, &vl[ki + is * vl_dim1], &c__1); i__2 = *n - ki + 1; igraphdcopy_(&i__2, &work[ki + n2], &c__1, &vl[ki + (is + 1) * vl_dim1], &c__1); emax = 0.; i__2 = *n; for (k = ki; k <= i__2; ++k) { /* Computing MAX */ d__3 = emax, d__4 = (d__1 = vl[k + is * vl_dim1], abs( d__1)) + (d__2 = vl[k + (is + 1) * vl_dim1], abs(d__2)); emax = max(d__3,d__4); /* L220: */ } remax = 1. / emax; i__2 = *n - ki + 1; igraphdscal_(&i__2, &remax, &vl[ki + is * vl_dim1], &c__1); i__2 = *n - ki + 1; igraphdscal_(&i__2, &remax, &vl[ki + (is + 1) * vl_dim1], &c__1) ; i__2 = ki - 1; for (k = 1; k <= i__2; ++k) { vl[k + is * vl_dim1] = 0.; vl[k + (is + 1) * vl_dim1] = 0.; /* L230: */ } } else { if (ki < *n - 1) { i__2 = *n - ki - 1; igraphdgemv_("N", n, &i__2, &c_b22, &vl[(ki + 2) * vl_dim1 + 1], ldvl, &work[ki + 2 + *n], &c__1, &work[ ki + *n], &vl[ki * vl_dim1 + 1], &c__1); i__2 = *n - ki - 1; igraphdgemv_("N", n, &i__2, &c_b22, &vl[(ki + 2) * vl_dim1 + 1], ldvl, &work[ki + 2 + n2], &c__1, &work[ ki + 1 + n2], &vl[(ki + 1) * vl_dim1 + 1], & c__1); } else { igraphdscal_(n, &work[ki + *n], &vl[ki * vl_dim1 + 1], & c__1); igraphdscal_(n, &work[ki + 1 + n2], &vl[(ki + 1) * vl_dim1 + 1], &c__1); } emax = 0.; i__2 = *n; for (k = 1; k <= i__2; ++k) { /* Computing MAX */ d__3 = emax, d__4 = (d__1 = vl[k + ki * vl_dim1], abs( d__1)) + (d__2 = vl[k + (ki + 1) * vl_dim1], abs(d__2)); emax = max(d__3,d__4); /* L240: */ } remax = 1. / emax; igraphdscal_(n, &remax, &vl[ki * vl_dim1 + 1], &c__1); igraphdscal_(n, &remax, &vl[(ki + 1) * vl_dim1 + 1], &c__1); } } ++is; if (ip != 0) { ++is; } L250: if (ip == -1) { ip = 0; } if (ip == 1) { ip = -1; } /* L260: */ } } return 0; /* End of DTREVC */ } /* igraphdtrevc_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlagtf.c0000644000076500000240000002073413524616145024253 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLAGTF computes an LU factorization of a matrix T-λI, where T is a general tridiagonal matrix, and λ a scalar, using partial pivoting with row interchanges. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLAGTF + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLAGTF( N, A, LAMBDA, B, C, TOL, D, IN, INFO ) INTEGER INFO, N DOUBLE PRECISION LAMBDA, TOL INTEGER IN( * ) DOUBLE PRECISION A( * ), B( * ), C( * ), D( * ) > \par Purpose: ============= > > \verbatim > > DLAGTF factorizes the matrix (T - lambda*I), where T is an n by n > tridiagonal matrix and lambda is a scalar, as > > T - lambda*I = PLU, > > where P is a permutation matrix, L is a unit lower tridiagonal matrix > with at most one non-zero sub-diagonal elements per column and U is > an upper triangular matrix with at most two non-zero super-diagonal > elements per column. > > The factorization is obtained by Gaussian elimination with partial > pivoting and implicit row scaling. > > The parameter LAMBDA is included in the routine so that DLAGTF may > be used, in conjunction with DLAGTS, to obtain eigenvectors of T by > inverse iteration. > \endverbatim Arguments: ========== > \param[in] N > \verbatim > N is INTEGER > The order of the matrix T. > \endverbatim > > \param[in,out] A > \verbatim > A is DOUBLE PRECISION array, dimension (N) > On entry, A must contain the diagonal elements of T. > > On exit, A is overwritten by the n diagonal elements of the > upper triangular matrix U of the factorization of T. > \endverbatim > > \param[in] LAMBDA > \verbatim > LAMBDA is DOUBLE PRECISION > On entry, the scalar lambda. > \endverbatim > > \param[in,out] B > \verbatim > B is DOUBLE PRECISION array, dimension (N-1) > On entry, B must contain the (n-1) super-diagonal elements of > T. > > On exit, B is overwritten by the (n-1) super-diagonal > elements of the matrix U of the factorization of T. > \endverbatim > > \param[in,out] C > \verbatim > C is DOUBLE PRECISION array, dimension (N-1) > On entry, C must contain the (n-1) sub-diagonal elements of > T. > > On exit, C is overwritten by the (n-1) sub-diagonal elements > of the matrix L of the factorization of T. > \endverbatim > > \param[in] TOL > \verbatim > TOL is DOUBLE PRECISION > On entry, a relative tolerance used to indicate whether or > not the matrix (T - lambda*I) is nearly singular. TOL should > normally be chose as approximately the largest relative error > in the elements of T. For example, if the elements of T are > correct to about 4 significant figures, then TOL should be > set to about 5*10**(-4). If TOL is supplied as less than eps, > where eps is the relative machine precision, then the value > eps is used in place of TOL. > \endverbatim > > \param[out] D > \verbatim > D is DOUBLE PRECISION array, dimension (N-2) > On exit, D is overwritten by the (n-2) second super-diagonal > elements of the matrix U of the factorization of T. > \endverbatim > > \param[out] IN > \verbatim > IN is INTEGER array, dimension (N) > On exit, IN contains details of the permutation matrix P. If > an interchange occurred at the kth step of the elimination, > then IN(k) = 1, otherwise IN(k) = 0. The element IN(n) > returns the smallest positive integer j such that > > abs( u(j,j) ).le. norm( (T - lambda*I)(j) )*TOL, > > where norm( A(j) ) denotes the sum of the absolute values of > the jth row of the matrix A. If no such j exists then IN(n) > is returned as zero. If IN(n) is returned as positive, then a > diagonal element of U is small, indicating that > (T - lambda*I) is singular or nearly singular, > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0 : successful exit > .lt. 0: if INFO = -k, the kth argument had an illegal value > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERcomputational ===================================================================== Subroutine */ int igraphdlagtf_(integer *n, doublereal *a, doublereal *lambda, doublereal *b, doublereal *c__, doublereal *tol, doublereal *d__, integer *in, integer *info) { /* System generated locals */ integer i__1; doublereal d__1, d__2; /* Local variables */ integer k; doublereal tl, eps, piv1, piv2, temp, mult, scale1, scale2; extern doublereal igraphdlamch_(char *); extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); /* -- LAPACK computational routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ --in; --d__; --c__; --b; --a; /* Function Body */ *info = 0; if (*n < 0) { *info = -1; i__1 = -(*info); igraphxerbla_("DLAGTF", &i__1, (ftnlen)6); return 0; } if (*n == 0) { return 0; } a[1] -= *lambda; in[*n] = 0; if (*n == 1) { if (a[1] == 0.) { in[1] = 1; } return 0; } eps = igraphdlamch_("Epsilon"); tl = max(*tol,eps); scale1 = abs(a[1]) + abs(b[1]); i__1 = *n - 1; for (k = 1; k <= i__1; ++k) { a[k + 1] -= *lambda; scale2 = (d__1 = c__[k], abs(d__1)) + (d__2 = a[k + 1], abs(d__2)); if (k < *n - 1) { scale2 += (d__1 = b[k + 1], abs(d__1)); } if (a[k] == 0.) { piv1 = 0.; } else { piv1 = (d__1 = a[k], abs(d__1)) / scale1; } if (c__[k] == 0.) { in[k] = 0; piv2 = 0.; scale1 = scale2; if (k < *n - 1) { d__[k] = 0.; } } else { piv2 = (d__1 = c__[k], abs(d__1)) / scale2; if (piv2 <= piv1) { in[k] = 0; scale1 = scale2; c__[k] /= a[k]; a[k + 1] -= c__[k] * b[k]; if (k < *n - 1) { d__[k] = 0.; } } else { in[k] = 1; mult = a[k] / c__[k]; a[k] = c__[k]; temp = a[k + 1]; a[k + 1] = b[k] - mult * temp; if (k < *n - 1) { d__[k] = b[k + 1]; b[k + 1] = -mult * d__[k]; } b[k] = temp; c__[k] = mult; } } if (max(piv1,piv2) <= tl && in[*n] == 0) { in[*n] = k; } /* L10: */ } if ((d__1 = a[*n], abs(d__1)) <= scale1 * tl && in[*n] == 0) { in[*n] = *n; } return 0; /* End of DLAGTF */ } /* igraphdlagtf_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlahr2.c0000644000076500000240000003160213524616145024162 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static doublereal c_b4 = -1.; static doublereal c_b5 = 1.; static integer c__1 = 1; static doublereal c_b38 = 0.; /* > \brief \b DLAHR2 reduces the specified number of first columns of a general rectangular matrix A so that elements below the specified subdiagonal are zero, and returns auxiliary matrices which are needed to apply the transformation to the unreduced part of A. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLAHR2 + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLAHR2( N, K, NB, A, LDA, TAU, T, LDT, Y, LDY ) INTEGER K, LDA, LDT, LDY, N, NB DOUBLE PRECISION A( LDA, * ), T( LDT, NB ), TAU( NB ), $ Y( LDY, NB ) > \par Purpose: ============= > > \verbatim > > DLAHR2 reduces the first NB columns of A real general n-BY-(n-k+1) > matrix A so that elements below the k-th subdiagonal are zero. The > reduction is performed by an orthogonal similarity transformation > Q**T * A * Q. The routine returns the matrices V and T which determine > Q as a block reflector I - V*T*V**T, and also the matrix Y = A * V * T. > > This is an auxiliary routine called by DGEHRD. > \endverbatim Arguments: ========== > \param[in] N > \verbatim > N is INTEGER > The order of the matrix A. > \endverbatim > > \param[in] K > \verbatim > K is INTEGER > The offset for the reduction. Elements below the k-th > subdiagonal in the first NB columns are reduced to zero. > K < N. > \endverbatim > > \param[in] NB > \verbatim > NB is INTEGER > The number of columns to be reduced. > \endverbatim > > \param[in,out] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,N-K+1) > On entry, the n-by-(n-k+1) general matrix A. > On exit, the elements on and above the k-th subdiagonal in > the first NB columns are overwritten with the corresponding > elements of the reduced matrix; the elements below the k-th > subdiagonal, with the array TAU, represent the matrix Q as a > product of elementary reflectors. The other columns of A are > unchanged. See Further Details. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. LDA >= max(1,N). > \endverbatim > > \param[out] TAU > \verbatim > TAU is DOUBLE PRECISION array, dimension (NB) > The scalar factors of the elementary reflectors. See Further > Details. > \endverbatim > > \param[out] T > \verbatim > T is DOUBLE PRECISION array, dimension (LDT,NB) > The upper triangular matrix T. > \endverbatim > > \param[in] LDT > \verbatim > LDT is INTEGER > The leading dimension of the array T. LDT >= NB. > \endverbatim > > \param[out] Y > \verbatim > Y is DOUBLE PRECISION array, dimension (LDY,NB) > The n-by-nb matrix Y. > \endverbatim > > \param[in] LDY > \verbatim > LDY is INTEGER > The leading dimension of the array Y. LDY >= N. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleOTHERauxiliary > \par Further Details: ===================== > > \verbatim > > The matrix Q is represented as a product of nb elementary reflectors > > Q = H(1) H(2) . . . H(nb). > > Each H(i) has the form > > H(i) = I - tau * v * v**T > > where tau is a real scalar, and v is a real vector with > v(1:i+k-1) = 0, v(i+k) = 1; v(i+k+1:n) is stored on exit in > A(i+k+1:n,i), and tau in TAU(i). > > The elements of the vectors v together form the (n-k+1)-by-nb matrix > V which is needed, with T and Y, to apply the transformation to the > unreduced part of the matrix, using an update of the form: > A := (I - V*T*V**T) * (A - Y*V**T). > > The contents of A on exit are illustrated by the following example > with n = 7, k = 3 and nb = 2: > > ( a a a a a ) > ( a a a a a ) > ( a a a a a ) > ( h h a a a ) > ( v1 h a a a ) > ( v1 v2 a a a ) > ( v1 v2 a a a ) > > where a denotes an element of the original matrix A, h denotes a > modified element of the upper Hessenberg matrix H, and vi denotes an > element of the vector defining H(i). > > This subroutine is a slight modification of LAPACK-3.0's DLAHRD > incorporating improvements proposed by Quintana-Orti and Van de > Gejin. Note that the entries of A(1:K,2:NB) differ from those > returned by the original LAPACK-3.0's DLAHRD routine. (This > subroutine is not backward compatible with LAPACK-3.0's DLAHRD.) > \endverbatim > \par References: ================ > > Gregorio Quintana-Orti and Robert van de Geijn, "Improving the > performance of reduction to Hessenberg form," ACM Transactions on > Mathematical Software, 32(2):180-194, June 2006. > ===================================================================== Subroutine */ int igraphdlahr2_(integer *n, integer *k, integer *nb, doublereal * a, integer *lda, doublereal *tau, doublereal *t, integer *ldt, doublereal *y, integer *ldy) { /* System generated locals */ integer a_dim1, a_offset, t_dim1, t_offset, y_dim1, y_offset, i__1, i__2, i__3; doublereal d__1; /* Local variables */ integer i__; doublereal ei; extern /* Subroutine */ int igraphdscal_(integer *, doublereal *, doublereal *, integer *), igraphdgemm_(char *, char *, integer *, integer *, integer * , doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *), igraphdgemv_( char *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *), igraphdcopy_(integer *, doublereal *, integer *, doublereal *, integer *), igraphdtrmm_(char *, char *, char *, char *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *), igraphdaxpy_(integer *, doublereal *, doublereal *, integer *, doublereal *, integer *), igraphdtrmv_(char *, char *, char *, integer *, doublereal *, integer *, doublereal *, integer *), igraphdlarfg_( integer *, doublereal *, doublereal *, integer *, doublereal *), igraphdlacpy_(char *, integer *, integer *, doublereal *, integer *, doublereal *, integer *); /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Quick return if possible Parameter adjustments */ --tau; a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; t_dim1 = *ldt; t_offset = 1 + t_dim1; t -= t_offset; y_dim1 = *ldy; y_offset = 1 + y_dim1; y -= y_offset; /* Function Body */ if (*n <= 1) { return 0; } i__1 = *nb; for (i__ = 1; i__ <= i__1; ++i__) { if (i__ > 1) { /* Update A(K+1:N,I) Update I-th column of A - Y * V**T */ i__2 = *n - *k; i__3 = i__ - 1; igraphdgemv_("NO TRANSPOSE", &i__2, &i__3, &c_b4, &y[*k + 1 + y_dim1], ldy, &a[*k + i__ - 1 + a_dim1], lda, &c_b5, &a[*k + 1 + i__ * a_dim1], &c__1); /* Apply I - V * T**T * V**T to this column (call it b) from the left, using the last column of T as workspace Let V = ( V1 ) and b = ( b1 ) (first I-1 rows) ( V2 ) ( b2 ) where V1 is unit lower triangular w := V1**T * b1 */ i__2 = i__ - 1; igraphdcopy_(&i__2, &a[*k + 1 + i__ * a_dim1], &c__1, &t[*nb * t_dim1 + 1], &c__1); i__2 = i__ - 1; igraphdtrmv_("Lower", "Transpose", "UNIT", &i__2, &a[*k + 1 + a_dim1], lda, &t[*nb * t_dim1 + 1], &c__1); /* w := w + V2**T * b2 */ i__2 = *n - *k - i__ + 1; i__3 = i__ - 1; igraphdgemv_("Transpose", &i__2, &i__3, &c_b5, &a[*k + i__ + a_dim1], lda, &a[*k + i__ + i__ * a_dim1], &c__1, &c_b5, &t[*nb * t_dim1 + 1], &c__1); /* w := T**T * w */ i__2 = i__ - 1; igraphdtrmv_("Upper", "Transpose", "NON-UNIT", &i__2, &t[t_offset], ldt, &t[*nb * t_dim1 + 1], &c__1); /* b2 := b2 - V2*w */ i__2 = *n - *k - i__ + 1; i__3 = i__ - 1; igraphdgemv_("NO TRANSPOSE", &i__2, &i__3, &c_b4, &a[*k + i__ + a_dim1], lda, &t[*nb * t_dim1 + 1], &c__1, &c_b5, &a[*k + i__ + i__ * a_dim1], &c__1); /* b1 := b1 - V1*w */ i__2 = i__ - 1; igraphdtrmv_("Lower", "NO TRANSPOSE", "UNIT", &i__2, &a[*k + 1 + a_dim1] , lda, &t[*nb * t_dim1 + 1], &c__1); i__2 = i__ - 1; igraphdaxpy_(&i__2, &c_b4, &t[*nb * t_dim1 + 1], &c__1, &a[*k + 1 + i__ * a_dim1], &c__1); a[*k + i__ - 1 + (i__ - 1) * a_dim1] = ei; } /* Generate the elementary reflector H(I) to annihilate A(K+I+1:N,I) */ i__2 = *n - *k - i__ + 1; /* Computing MIN */ i__3 = *k + i__ + 1; igraphdlarfg_(&i__2, &a[*k + i__ + i__ * a_dim1], &a[min(i__3,*n) + i__ * a_dim1], &c__1, &tau[i__]); ei = a[*k + i__ + i__ * a_dim1]; a[*k + i__ + i__ * a_dim1] = 1.; /* Compute Y(K+1:N,I) */ i__2 = *n - *k; i__3 = *n - *k - i__ + 1; igraphdgemv_("NO TRANSPOSE", &i__2, &i__3, &c_b5, &a[*k + 1 + (i__ + 1) * a_dim1], lda, &a[*k + i__ + i__ * a_dim1], &c__1, &c_b38, &y[* k + 1 + i__ * y_dim1], &c__1); i__2 = *n - *k - i__ + 1; i__3 = i__ - 1; igraphdgemv_("Transpose", &i__2, &i__3, &c_b5, &a[*k + i__ + a_dim1], lda, & a[*k + i__ + i__ * a_dim1], &c__1, &c_b38, &t[i__ * t_dim1 + 1], &c__1); i__2 = *n - *k; i__3 = i__ - 1; igraphdgemv_("NO TRANSPOSE", &i__2, &i__3, &c_b4, &y[*k + 1 + y_dim1], ldy, &t[i__ * t_dim1 + 1], &c__1, &c_b5, &y[*k + 1 + i__ * y_dim1], &c__1); i__2 = *n - *k; igraphdscal_(&i__2, &tau[i__], &y[*k + 1 + i__ * y_dim1], &c__1); /* Compute T(1:I,I) */ i__2 = i__ - 1; d__1 = -tau[i__]; igraphdscal_(&i__2, &d__1, &t[i__ * t_dim1 + 1], &c__1); i__2 = i__ - 1; igraphdtrmv_("Upper", "No Transpose", "NON-UNIT", &i__2, &t[t_offset], ldt, &t[i__ * t_dim1 + 1], &c__1) ; t[i__ + i__ * t_dim1] = tau[i__]; /* L10: */ } a[*k + *nb + *nb * a_dim1] = ei; /* Compute Y(1:K,1:NB) */ igraphdlacpy_("ALL", k, nb, &a[(a_dim1 << 1) + 1], lda, &y[y_offset], ldy); igraphdtrmm_("RIGHT", "Lower", "NO TRANSPOSE", "UNIT", k, nb, &c_b5, &a[*k + 1 + a_dim1], lda, &y[y_offset], ldy); if (*n > *k + *nb) { i__1 = *n - *k - *nb; igraphdgemm_("NO TRANSPOSE", "NO TRANSPOSE", k, nb, &i__1, &c_b5, &a[(*nb + 2) * a_dim1 + 1], lda, &a[*k + 1 + *nb + a_dim1], lda, &c_b5, &y[y_offset], ldy); } igraphdtrmm_("RIGHT", "Upper", "NO TRANSPOSE", "NON-UNIT", k, nb, &c_b5, &t[ t_offset], ldt, &y[y_offset], ldy); return 0; /* End of DLAHR2 */ } /* igraphdlahr2_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlabad.c0000644000076500000240000000717613524616145024226 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLABAD =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLABAD + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLABAD( SMALL, LARGE ) DOUBLE PRECISION LARGE, SMALL > \par Purpose: ============= > > \verbatim > > DLABAD takes as input the values computed by DLAMCH for underflow and > overflow, and returns the square root of each of these values if the > log of LARGE is sufficiently large. This subroutine is intended to > identify machines with a large exponent range, such as the Crays, and > redefine the underflow and overflow limits to be the square roots of > the values computed by DLAMCH. This subroutine is needed because > DLAMCH does not compensate for poor arithmetic in the upper half of > the exponent range, as is found on a Cray. > \endverbatim Arguments: ========== > \param[in,out] SMALL > \verbatim > SMALL is DOUBLE PRECISION > On entry, the underflow threshold as computed by DLAMCH. > On exit, if LOG10(LARGE) is sufficiently large, the square > root of SMALL, otherwise unchanged. > \endverbatim > > \param[in,out] LARGE > \verbatim > LARGE is DOUBLE PRECISION > On entry, the overflow threshold as computed by DLAMCH. > On exit, if LOG10(LARGE) is sufficiently large, the square > root of LARGE, otherwise unchanged. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2011 > \ingroup auxOTHERauxiliary ===================================================================== Subroutine */ int igraphdlabad_(doublereal *small, doublereal *large) { /* Builtin functions */ double d_lg10(doublereal *), sqrt(doublereal); /* -- LAPACK auxiliary routine (version 3.4.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2011 ===================================================================== If it looks like we're on a Cray, take the square root of SMALL and LARGE to avoid overflow and underflow problems. */ if (d_lg10(large) > 2e3) { *small = sqrt(*small); *large = sqrt(*large); } return 0; /* End of DLABAD */ } /* igraphdlabad_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlarrc.c0000644000076500000240000001526513524616145024264 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLARRC computes the number of eigenvalues of the symmetric tridiagonal matrix. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLARRC + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLARRC( JOBT, N, VL, VU, D, E, PIVMIN, EIGCNT, LCNT, RCNT, INFO ) CHARACTER JOBT INTEGER EIGCNT, INFO, LCNT, N, RCNT DOUBLE PRECISION PIVMIN, VL, VU DOUBLE PRECISION D( * ), E( * ) > \par Purpose: ============= > > \verbatim > > Find the number of eigenvalues of the symmetric tridiagonal matrix T > that are in the interval (VL,VU] if JOBT = 'T', and of L D L^T > if JOBT = 'L'. > \endverbatim Arguments: ========== > \param[in] JOBT > \verbatim > JOBT is CHARACTER*1 > = 'T': Compute Sturm count for matrix T. > = 'L': Compute Sturm count for matrix L D L^T. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix. N > 0. > \endverbatim > > \param[in] VL > \verbatim > VL is DOUBLE PRECISION > \endverbatim > > \param[in] VU > \verbatim > VU is DOUBLE PRECISION > The lower and upper bounds for the eigenvalues. > \endverbatim > > \param[in] D > \verbatim > D is DOUBLE PRECISION array, dimension (N) > JOBT = 'T': The N diagonal elements of the tridiagonal matrix T. > JOBT = 'L': The N diagonal elements of the diagonal matrix D. > \endverbatim > > \param[in] E > \verbatim > E is DOUBLE PRECISION array, dimension (N) > JOBT = 'T': The N-1 offdiagonal elements of the matrix T. > JOBT = 'L': The N-1 offdiagonal elements of the matrix L. > \endverbatim > > \param[in] PIVMIN > \verbatim > PIVMIN is DOUBLE PRECISION > The minimum pivot in the Sturm sequence for T. > \endverbatim > > \param[out] EIGCNT > \verbatim > EIGCNT is INTEGER > The number of eigenvalues of the symmetric tridiagonal matrix T > that are in the interval (VL,VU] > \endverbatim > > \param[out] LCNT > \verbatim > LCNT is INTEGER > \endverbatim > > \param[out] RCNT > \verbatim > RCNT is INTEGER > The left and right negcounts of the interval. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERauxiliary > \par Contributors: ================== > > Beresford Parlett, University of California, Berkeley, USA \n > Jim Demmel, University of California, Berkeley, USA \n > Inderjit Dhillon, University of Texas, Austin, USA \n > Osni Marques, LBNL/NERSC, USA \n > Christof Voemel, University of California, Berkeley, USA ===================================================================== Subroutine */ int igraphdlarrc_(char *jobt, integer *n, doublereal *vl, doublereal *vu, doublereal *d__, doublereal *e, doublereal *pivmin, integer *eigcnt, integer *lcnt, integer *rcnt, integer *info) { /* System generated locals */ integer i__1; doublereal d__1; /* Local variables */ integer i__; doublereal sl, su, tmp, tmp2; logical matt; extern logical igraphlsame_(char *, char *); doublereal lpivot, rpivot; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ --e; --d__; /* Function Body */ *info = 0; *lcnt = 0; *rcnt = 0; *eigcnt = 0; matt = igraphlsame_(jobt, "T"); if (matt) { /* Sturm sequence count on T */ lpivot = d__[1] - *vl; rpivot = d__[1] - *vu; if (lpivot <= 0.) { ++(*lcnt); } if (rpivot <= 0.) { ++(*rcnt); } i__1 = *n - 1; for (i__ = 1; i__ <= i__1; ++i__) { /* Computing 2nd power */ d__1 = e[i__]; tmp = d__1 * d__1; lpivot = d__[i__ + 1] - *vl - tmp / lpivot; rpivot = d__[i__ + 1] - *vu - tmp / rpivot; if (lpivot <= 0.) { ++(*lcnt); } if (rpivot <= 0.) { ++(*rcnt); } /* L10: */ } } else { /* Sturm sequence count on L D L^T */ sl = -(*vl); su = -(*vu); i__1 = *n - 1; for (i__ = 1; i__ <= i__1; ++i__) { lpivot = d__[i__] + sl; rpivot = d__[i__] + su; if (lpivot <= 0.) { ++(*lcnt); } if (rpivot <= 0.) { ++(*rcnt); } tmp = e[i__] * d__[i__] * e[i__]; tmp2 = tmp / lpivot; if (tmp2 == 0.) { sl = tmp - *vl; } else { sl = sl * tmp2 - *vl; } tmp2 = tmp / rpivot; if (tmp2 == 0.) { su = tmp - *vu; } else { su = su * tmp2 - *vu; } /* L20: */ } lpivot = d__[*n] + sl; rpivot = d__[*n] + su; if (lpivot <= 0.) { ++(*lcnt); } if (rpivot <= 0.) { ++(*rcnt); } } *eigcnt = *rcnt - *lcnt; return 0; /* end of DLARRC */ } /* igraphdlarrc_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlasq6.c0000644000076500000240000001616713524616145024211 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLASQ6 computes one dqd transform in ping-pong form. Used by sbdsqr and sstegr. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLASQ6 + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLASQ6( I0, N0, Z, PP, DMIN, DMIN1, DMIN2, DN, DNM1, DNM2 ) INTEGER I0, N0, PP DOUBLE PRECISION DMIN, DMIN1, DMIN2, DN, DNM1, DNM2 DOUBLE PRECISION Z( * ) > \par Purpose: ============= > > \verbatim > > DLASQ6 computes one dqd (shift equal to zero) transform in > ping-pong form, with protection against underflow and overflow. > \endverbatim Arguments: ========== > \param[in] I0 > \verbatim > I0 is INTEGER > First index. > \endverbatim > > \param[in] N0 > \verbatim > N0 is INTEGER > Last index. > \endverbatim > > \param[in] Z > \verbatim > Z is DOUBLE PRECISION array, dimension ( 4*N ) > Z holds the qd array. EMIN is stored in Z(4*N0) to avoid > an extra argument. > \endverbatim > > \param[in] PP > \verbatim > PP is INTEGER > PP=0 for ping, PP=1 for pong. > \endverbatim > > \param[out] DMIN > \verbatim > DMIN is DOUBLE PRECISION > Minimum value of d. > \endverbatim > > \param[out] DMIN1 > \verbatim > DMIN1 is DOUBLE PRECISION > Minimum value of d, excluding D( N0 ). > \endverbatim > > \param[out] DMIN2 > \verbatim > DMIN2 is DOUBLE PRECISION > Minimum value of d, excluding D( N0 ) and D( N0-1 ). > \endverbatim > > \param[out] DN > \verbatim > DN is DOUBLE PRECISION > d(N0), the last value of d. > \endverbatim > > \param[out] DNM1 > \verbatim > DNM1 is DOUBLE PRECISION > d(N0-1). > \endverbatim > > \param[out] DNM2 > \verbatim > DNM2 is DOUBLE PRECISION > d(N0-2). > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERcomputational ===================================================================== Subroutine */ int igraphdlasq6_(integer *i0, integer *n0, doublereal *z__, integer *pp, doublereal *dmin__, doublereal *dmin1, doublereal *dmin2, doublereal *dn, doublereal *dnm1, doublereal *dnm2) { /* System generated locals */ integer i__1; doublereal d__1, d__2; /* Local variables */ doublereal d__; integer j4, j4p2; doublereal emin, temp; extern doublereal igraphdlamch_(char *); doublereal safmin; /* -- LAPACK computational routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ --z__; /* Function Body */ if (*n0 - *i0 - 1 <= 0) { return 0; } safmin = igraphdlamch_("Safe minimum"); j4 = (*i0 << 2) + *pp - 3; emin = z__[j4 + 4]; d__ = z__[j4]; *dmin__ = d__; if (*pp == 0) { i__1 = *n0 - 3 << 2; for (j4 = *i0 << 2; j4 <= i__1; j4 += 4) { z__[j4 - 2] = d__ + z__[j4 - 1]; if (z__[j4 - 2] == 0.) { z__[j4] = 0.; d__ = z__[j4 + 1]; *dmin__ = d__; emin = 0.; } else if (safmin * z__[j4 + 1] < z__[j4 - 2] && safmin * z__[j4 - 2] < z__[j4 + 1]) { temp = z__[j4 + 1] / z__[j4 - 2]; z__[j4] = z__[j4 - 1] * temp; d__ *= temp; } else { z__[j4] = z__[j4 + 1] * (z__[j4 - 1] / z__[j4 - 2]); d__ = z__[j4 + 1] * (d__ / z__[j4 - 2]); } *dmin__ = min(*dmin__,d__); /* Computing MIN */ d__1 = emin, d__2 = z__[j4]; emin = min(d__1,d__2); /* L10: */ } } else { i__1 = *n0 - 3 << 2; for (j4 = *i0 << 2; j4 <= i__1; j4 += 4) { z__[j4 - 3] = d__ + z__[j4]; if (z__[j4 - 3] == 0.) { z__[j4 - 1] = 0.; d__ = z__[j4 + 2]; *dmin__ = d__; emin = 0.; } else if (safmin * z__[j4 + 2] < z__[j4 - 3] && safmin * z__[j4 - 3] < z__[j4 + 2]) { temp = z__[j4 + 2] / z__[j4 - 3]; z__[j4 - 1] = z__[j4] * temp; d__ *= temp; } else { z__[j4 - 1] = z__[j4 + 2] * (z__[j4] / z__[j4 - 3]); d__ = z__[j4 + 2] * (d__ / z__[j4 - 3]); } *dmin__ = min(*dmin__,d__); /* Computing MIN */ d__1 = emin, d__2 = z__[j4 - 1]; emin = min(d__1,d__2); /* L20: */ } } /* Unroll last two steps. */ *dnm2 = d__; *dmin2 = *dmin__; j4 = (*n0 - 2 << 2) - *pp; j4p2 = j4 + (*pp << 1) - 1; z__[j4 - 2] = *dnm2 + z__[j4p2]; if (z__[j4 - 2] == 0.) { z__[j4] = 0.; *dnm1 = z__[j4p2 + 2]; *dmin__ = *dnm1; emin = 0.; } else if (safmin * z__[j4p2 + 2] < z__[j4 - 2] && safmin * z__[j4 - 2] < z__[j4p2 + 2]) { temp = z__[j4p2 + 2] / z__[j4 - 2]; z__[j4] = z__[j4p2] * temp; *dnm1 = *dnm2 * temp; } else { z__[j4] = z__[j4p2 + 2] * (z__[j4p2] / z__[j4 - 2]); *dnm1 = z__[j4p2 + 2] * (*dnm2 / z__[j4 - 2]); } *dmin__ = min(*dmin__,*dnm1); *dmin1 = *dmin__; j4 += 4; j4p2 = j4 + (*pp << 1) - 1; z__[j4 - 2] = *dnm1 + z__[j4p2]; if (z__[j4 - 2] == 0.) { z__[j4] = 0.; *dn = z__[j4p2 + 2]; *dmin__ = *dn; emin = 0.; } else if (safmin * z__[j4p2 + 2] < z__[j4 - 2] && safmin * z__[j4 - 2] < z__[j4p2 + 2]) { temp = z__[j4p2 + 2] / z__[j4 - 2]; z__[j4] = z__[j4p2] * temp; *dn = *dnm1 * temp; } else { z__[j4] = z__[j4p2 + 2] * (z__[j4p2] / z__[j4 - 2]); *dn = z__[j4p2 + 2] * (*dnm1 / z__[j4 - 2]); } *dmin__ = min(*dmin__,*dn); z__[j4 + 2] = *dn; z__[(*n0 << 2) - *pp] = emin; return 0; /* End of DLASQ6 */ } /* igraphdlasq6_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dseupd.c0000644000076500000240000012017613524616145024277 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static doublereal c_b21 = .66666666666666663; static integer c__1 = 1; static integer c__2 = 2; static logical c_true = TRUE_; static doublereal c_b119 = 1.; /* \BeginDoc \Name: dseupd \Description: This subroutine returns the converged approximations to eigenvalues of A*z = lambda*B*z and (optionally): (1) the corresponding approximate eigenvectors, (2) an orthonormal (Lanczos) basis for the associated approximate invariant subspace, (3) Both. There is negligible additional cost to obtain eigenvectors. An orthonormal (Lanczos) basis is always computed. There is an additional storage cost of n*nev if both are requested (in this case a separate array Z must be supplied). These quantities are obtained from the Lanczos factorization computed by DSAUPD for the linear operator OP prescribed by the MODE selection (see IPARAM(7) in DSAUPD documentation.) DSAUPD must be called before this routine is called. These approximate eigenvalues and vectors are commonly called Ritz values and Ritz vectors respectively. They are referred to as such in the comments that follow. The computed orthonormal basis for the invariant subspace corresponding to these Ritz values is referred to as a Lanczos basis. See documentation in the header of the subroutine DSAUPD for a definition of OP as well as other terms and the relation of computed Ritz values and vectors of OP with respect to the given problem A*z = lambda*B*z. The approximate eigenvalues of the original problem are returned in ascending algebraic order. The user may elect to call this routine once for each desired Ritz vector and store it peripherally if desired. There is also the option of computing a selected set of these vectors with a single call. \Usage: call dseupd ( RVEC, HOWMNY, SELECT, D, Z, LDZ, SIGMA, BMAT, N, WHICH, NEV, TOL, RESID, NCV, V, LDV, IPARAM, IPNTR, WORKD, WORKL, LWORKL, INFO ) RVEC LOGICAL (INPUT) Specifies whether Ritz vectors corresponding to the Ritz value approximations to the eigenproblem A*z = lambda*B*z are computed. RVEC = .FALSE. Compute Ritz values only. RVEC = .TRUE. Compute Ritz vectors. HOWMNY Character*1 (INPUT) Specifies how many Ritz vectors are wanted and the form of Z the matrix of Ritz vectors. See remark 1 below. = 'A': compute NEV Ritz vectors; = 'S': compute some of the Ritz vectors, specified by the logical array SELECT. SELECT Logical array of dimension NEV. (INPUT) If HOWMNY = 'S', SELECT specifies the Ritz vectors to be computed. To select the Ritz vector corresponding to a Ritz value D(j), SELECT(j) must be set to .TRUE.. If HOWMNY = 'A' , SELECT is not referenced. D Double precision array of dimension NEV. (OUTPUT) On exit, D contains the Ritz value approximations to the eigenvalues of A*z = lambda*B*z. The values are returned in ascending order. If IPARAM(7) = 3,4,5 then D represents the Ritz values of OP computed by dsaupd transformed to those of the original eigensystem A*z = lambda*B*z. If IPARAM(7) = 1,2 then the Ritz values of OP are the same as the those of A*z = lambda*B*z. Z Double precision N by NEV array if HOWMNY = 'A'. (OUTPUT) On exit, Z contains the B-orthonormal Ritz vectors of the eigensystem A*z = lambda*B*z corresponding to the Ritz value approximations. If RVEC = .FALSE. then Z is not referenced. NOTE: The array Z may be set equal to first NEV columns of the Arnoldi/Lanczos basis array V computed by DSAUPD. LDZ Integer. (INPUT) The leading dimension of the array Z. If Ritz vectors are desired, then LDZ .ge. max( 1, N ). In any case, LDZ .ge. 1. SIGMA Double precision (INPUT) If IPARAM(7) = 3,4,5 represents the shift. Not referenced if IPARAM(7) = 1 or 2. **** The remaining arguments MUST be the same as for the **** **** call to DNAUPD that was just completed. **** NOTE: The remaining arguments BMAT, N, WHICH, NEV, TOL, RESID, NCV, V, LDV, IPARAM, IPNTR, WORKD, WORKL, LWORKL, INFO must be passed directly to DSEUPD following the last call to DSAUPD. These arguments MUST NOT BE MODIFIED between the the last call to DSAUPD and the call to DSEUPD. Two of these parameters (WORKL, INFO) are also output parameters: WORKL Double precision work array of length LWORKL. (OUTPUT/WORKSPACE) WORKL(1:4*ncv) contains information obtained in dsaupd. They are not changed by dseupd. WORKL(4*ncv+1:ncv*ncv+8*ncv) holds the untransformed Ritz values, the computed error estimates, and the associated eigenvector matrix of H. Note: IPNTR(8:10) contains the pointer into WORKL for addresses of the above information computed by dseupd. ------------------------------------------------------------- IPNTR(8): pointer to the NCV RITZ values of the original system. IPNTR(9): pointer to the NCV corresponding error bounds. IPNTR(10): pointer to the NCV by NCV matrix of eigenvectors of the tridiagonal matrix T. Only referenced by dseupd if RVEC = .TRUE. See Remarks. ------------------------------------------------------------- INFO Integer. (OUTPUT) Error flag on output. = 0: Normal exit. = -1: N must be positive. = -2: NEV must be positive. = -3: NCV must be greater than NEV and less than or equal to N. = -5: WHICH must be one of 'LM', 'SM', 'LA', 'SA' or 'BE'. = -6: BMAT must be one of 'I' or 'G'. = -7: Length of private work WORKL array is not sufficient. = -8: Error return from trid. eigenvalue calculation; Information error from LAPACK routine dsteqr. = -9: Starting vector is zero. = -10: IPARAM(7) must be 1,2,3,4,5. = -11: IPARAM(7) = 1 and BMAT = 'G' are incompatible. = -12: NEV and WHICH = 'BE' are incompatible. = -14: DSAUPD did not find any eigenvalues to sufficient accuracy. = -15: HOWMNY must be one of 'A' or 'S' if RVEC = .true. = -16: HOWMNY = 'S' not yet implemented \BeginLib \References: 1. D.C. Sorensen, "Implicit Application of Polynomial Filters in a k-Step Arnoldi Method", SIAM J. Matr. Anal. Apps., 13 (1992), pp 357-385. 2. R.B. Lehoucq, "Analysis and Implementation of an Implicitly Restarted Arnoldi Iteration", Rice University Technical Report TR95-13, Department of Computational and Applied Mathematics. 3. B.N. Parlett, "The Symmetric Eigenvalue Problem". Prentice-Hall, 1980. 4. B.N. Parlett, B. Nour-Omid, "Towards a Black Box Lanczos Program", Computer Physics Communications, 53 (1989), pp 169-179. 5. B. Nour-Omid, B.N. Parlett, T. Ericson, P.S. Jensen, "How to Implement the Spectral Transformation", Math. Comp., 48 (1987), pp 663-673. 6. R.G. Grimes, J.G. Lewis and H.D. Simon, "A Shifted Block Lanczos Algorithm for Solving Sparse Symmetric Generalized Eigenproblems", SIAM J. Matr. Anal. Apps., January (1993). 7. L. Reichel, W.B. Gragg, "Algorithm 686: FORTRAN Subroutines for Updating the QR decomposition", ACM TOMS, December 1990, Volume 16 Number 4, pp 369-377. \Remarks 1. The converged Ritz values are always returned in increasing (algebraic) order. 2. Currently only HOWMNY = 'A' is implemented. It is included at this stage for the user who wants to incorporate it. \Routines called: dsesrt ARPACK routine that sorts an array X, and applies the corresponding permutation to a matrix A. dsortr dsortr ARPACK sorting routine. ivout ARPACK utility routine that prints integers. dvout ARPACK utility routine that prints vectors. dgeqr2 LAPACK routine that computes the QR factorization of a matrix. dlacpy LAPACK matrix copy routine. dlamch LAPACK routine that determines machine constants. dorm2r LAPACK routine that applies an orthogonal matrix in factored form. dsteqr LAPACK routine that computes eigenvalues and eigenvectors of a tridiagonal matrix. dger Level 2 BLAS rank one update to a matrix. dcopy Level 1 BLAS that copies one vector to another . dnrm2 Level 1 BLAS that computes the norm of a vector. dscal Level 1 BLAS that scales a vector. dswap Level 1 BLAS that swaps the contents of two vectors. \Authors Danny Sorensen Phuong Vu Richard Lehoucq CRPC / Rice University Chao Yang Houston, Texas Dept. of Computational & Applied Mathematics Rice University Houston, Texas \Revision history: 12/15/93: Version ' 2.1' \SCCS Information: @(#) FILE: seupd.F SID: 2.7 DATE OF SID: 8/27/96 RELEASE: 2 \EndLib ----------------------------------------------------------------------- Subroutine */ int igraphdseupd_(logical *rvec, char *howmny, logical *select, doublereal *d__, doublereal *z__, integer *ldz, doublereal *sigma, char *bmat, integer *n, char *which, integer *nev, doublereal *tol, doublereal *resid, integer *ncv, doublereal *v, integer *ldv, integer *iparam, integer *ipntr, doublereal *workd, doublereal *workl, integer *lworkl, integer *info) { /* System generated locals */ integer v_dim1, v_offset, z_dim1, z_offset, i__1; doublereal d__1, d__2, d__3; /* Builtin functions */ integer s_cmp(char *, char *, ftnlen, ftnlen); /* Subroutine */ int s_copy(char *, char *, ftnlen, ftnlen); double pow_dd(doublereal *, doublereal *); /* Local variables */ integer j, k, ih, iq, iw; doublereal kv[2]; integer ibd, ihb, ihd, ldh, ilg, ldq, ism, irz; extern /* Subroutine */ int igraphdger_(integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, integer *); integer mode; doublereal eps23; integer ierr; doublereal temp; integer next; char type__[6]; integer ritz; extern doublereal igraphdnrm2_(integer *, doublereal *, integer *); extern /* Subroutine */ int igraphdscal_(integer *, doublereal *, doublereal *, integer *); logical reord; extern /* Subroutine */ int igraphdcopy_(integer *, doublereal *, integer *, doublereal *, integer *); integer nconv; doublereal rnorm; extern /* Subroutine */ int igraphdvout_(integer *, integer *, doublereal *, integer *, char *, ftnlen), igraphivout_(integer *, integer *, integer * , integer *, char *, ftnlen), igraphdgeqr2_(integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *); doublereal bnorm2; extern /* Subroutine */ int igraphdorm2r_(char *, char *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *); doublereal thres1, thres2; extern doublereal igraphdlamch_(char *); extern /* Subroutine */ int igraphdlacpy_(char *, integer *, integer *, doublereal *, integer *, doublereal *, integer *); integer logfil, ndigit, bounds, mseupd = 0; extern /* Subroutine */ int igraphdsteqr_(char *, integer *, doublereal *, doublereal *, doublereal *, integer *, doublereal *, integer *); integer msglvl, ktrord; extern /* Subroutine */ int igraphdsesrt_(char *, logical *, integer *, doublereal *, integer *, doublereal *, integer *), igraphdsortr_(char *, logical *, integer *, doublereal *, doublereal *); doublereal tempbnd; integer leftptr, rghtptr; /* %----------------------------------------------------% | Include files for debugging and timing information | %----------------------------------------------------% %------------------% | Scalar Arguments | %------------------% %-----------------% | Array Arguments | %-----------------% %------------% | Parameters | %------------% %---------------% | Local Scalars | %---------------% %--------------% | Local Arrays | %--------------% %----------------------% | External Subroutines | %----------------------% %--------------------% | External Functions | %--------------------% %---------------------% | Intrinsic Functions | %---------------------% %-----------------------% | Executable Statements | %-----------------------% %------------------------% | Set default parameters | %------------------------% Parameter adjustments */ --workd; --resid; z_dim1 = *ldz; z_offset = 1 + z_dim1; z__ -= z_offset; --d__; --select; v_dim1 = *ldv; v_offset = 1 + v_dim1; v -= v_offset; --iparam; --ipntr; --workl; /* Function Body */ msglvl = mseupd; mode = iparam[7]; nconv = iparam[5]; *info = 0; /* %--------------% | Quick return | %--------------% */ if (nconv == 0) { goto L9000; } ierr = 0; if (nconv <= 0) { ierr = -14; } if (*n <= 0) { ierr = -1; } if (*nev <= 0) { ierr = -2; } if (*ncv <= *nev || *ncv > *n) { ierr = -3; } if (s_cmp(which, "LM", (ftnlen)2, (ftnlen)2) != 0 && s_cmp(which, "SM", ( ftnlen)2, (ftnlen)2) != 0 && s_cmp(which, "LA", (ftnlen)2, ( ftnlen)2) != 0 && s_cmp(which, "SA", (ftnlen)2, (ftnlen)2) != 0 && s_cmp(which, "BE", (ftnlen)2, (ftnlen)2) != 0) { ierr = -5; } if (*(unsigned char *)bmat != 'I' && *(unsigned char *)bmat != 'G') { ierr = -6; } if (*(unsigned char *)howmny != 'A' && *(unsigned char *)howmny != 'P' && *(unsigned char *)howmny != 'S' && *rvec) { ierr = -15; } if (*rvec && *(unsigned char *)howmny == 'S') { ierr = -16; } /* Computing 2nd power */ i__1 = *ncv; if (*rvec && *lworkl < i__1 * i__1 + (*ncv << 3)) { ierr = -7; } if (mode == 1 || mode == 2) { s_copy(type__, "REGULR", (ftnlen)6, (ftnlen)6); } else if (mode == 3) { s_copy(type__, "SHIFTI", (ftnlen)6, (ftnlen)6); } else if (mode == 4) { s_copy(type__, "BUCKLE", (ftnlen)6, (ftnlen)6); } else if (mode == 5) { s_copy(type__, "CAYLEY", (ftnlen)6, (ftnlen)6); } else { ierr = -10; } if (mode == 1 && *(unsigned char *)bmat == 'G') { ierr = -11; } if (*nev == 1 && s_cmp(which, "BE", (ftnlen)2, (ftnlen)2) == 0) { ierr = -12; } /* %------------% | Error Exit | %------------% */ if (ierr != 0) { *info = ierr; goto L9000; } /* %-------------------------------------------------------% | Pointer into WORKL for address of H, RITZ, BOUNDS, Q | | etc... and the remaining workspace. | | Also update pointer to be used on output. | | Memory is laid out as follows: | | workl(1:2*ncv) := generated tridiagonal matrix H | | The subdiagonal is stored in workl(2:ncv). | | The dead spot is workl(1) but upon exiting | | dsaupd stores the B-norm of the last residual | | vector in workl(1). We use this !!! | | workl(2*ncv+1:2*ncv+ncv) := ritz values | | The wanted values are in the first NCONV spots. | | workl(3*ncv+1:3*ncv+ncv) := computed Ritz estimates | | The wanted values are in the first NCONV spots. | | NOTE: workl(1:4*ncv) is set by dsaupd and is not | | modified by dseupd. | %-------------------------------------------------------% %-------------------------------------------------------% | The following is used and set by dseupd. | | workl(4*ncv+1:4*ncv+ncv) := used as workspace during | | computation of the eigenvectors of H. Stores | | the diagonal of H. Upon EXIT contains the NCV | | Ritz values of the original system. The first | | NCONV spots have the wanted values. If MODE = | | 1 or 2 then will equal workl(2*ncv+1:3*ncv). | | workl(5*ncv+1:5*ncv+ncv) := used as workspace during | | computation of the eigenvectors of H. Stores | | the subdiagonal of H. Upon EXIT contains the | | NCV corresponding Ritz estimates of the | | original system. The first NCONV spots have the | | wanted values. If MODE = 1,2 then will equal | | workl(3*ncv+1:4*ncv). | | workl(6*ncv+1:6*ncv+ncv*ncv) := orthogonal Q that is | | the eigenvector matrix for H as returned by | | dsteqr. Not referenced if RVEC = .False. | | Ordering follows that of workl(4*ncv+1:5*ncv) | | workl(6*ncv+ncv*ncv+1:6*ncv+ncv*ncv+2*ncv) := | | Workspace. Needed by dsteqr and by dseupd. | | GRAND total of NCV*(NCV+8) locations. | %-------------------------------------------------------% */ ih = ipntr[5]; ritz = ipntr[6]; bounds = ipntr[7]; ldh = *ncv; ldq = *ncv; ihd = bounds + ldh; ihb = ihd + ldh; iq = ihb + ldh; iw = iq + ldh * *ncv; next = iw + (*ncv << 1); ipntr[4] = next; ipntr[8] = ihd; ipntr[9] = ihb; ipntr[10] = iq; /* %----------------------------------------% | irz points to the Ritz values computed | | by _seigt before exiting _saup2. | | ibd points to the Ritz estimates | | computed by _seigt before exiting | | _saup2. | %----------------------------------------% */ irz = ipntr[11] + *ncv; ibd = irz + *ncv; /* %---------------------------------% | Set machine dependent constant. | %---------------------------------% */ eps23 = igraphdlamch_("Epsilon-Machine"); eps23 = pow_dd(&eps23, &c_b21); /* %---------------------------------------% | RNORM is B-norm of the RESID(1:N). | | BNORM2 is the 2 norm of B*RESID(1:N). | | Upon exit of dsaupd WORKD(1:N) has | | B*RESID(1:N). | %---------------------------------------% */ rnorm = workl[ih]; if (*(unsigned char *)bmat == 'I') { bnorm2 = rnorm; } else if (*(unsigned char *)bmat == 'G') { bnorm2 = igraphdnrm2_(n, &workd[1], &c__1); } if (*rvec) { /* %------------------------------------------------% | Get the converged Ritz value on the boundary. | | This value will be used to dermine whether we | | need to reorder the eigenvalues and | | eigenvectors comupted by _steqr, and is | | referred to as the "threshold" value. | | | | A Ritz value gamma is said to be a wanted | | one, if | | abs(gamma) .ge. threshold, when WHICH = 'LM'; | | abs(gamma) .le. threshold, when WHICH = 'SM'; | | gamma .ge. threshold, when WHICH = 'LA'; | | gamma .le. threshold, when WHICH = 'SA'; | | gamma .le. thres1 .or. gamma .ge. thres2 | | when WHICH = 'BE'; | | | | Note: converged Ritz values and associated | | Ritz estimates have been placed in the first | | NCONV locations in workl(ritz) and | | workl(bounds) respectively. They have been | | sorted (in _saup2) according to the WHICH | | selection criterion. (Except in the case | | WHICH = 'BE', they are sorted in an increasing | | order.) | %------------------------------------------------% */ if (s_cmp(which, "LM", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(which, "SM", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(which, "LA", ( ftnlen)2, (ftnlen)2) == 0 || s_cmp(which, "SA", (ftnlen)2, ( ftnlen)2) == 0) { thres1 = workl[ritz]; if (msglvl > 2) { igraphdvout_(&logfil, &c__1, &thres1, &ndigit, "_seupd: Threshold " "eigenvalue used for re-ordering", (ftnlen)49); } } else if (s_cmp(which, "BE", (ftnlen)2, (ftnlen)2) == 0) { /* %------------------------------------------------% | Ritz values returned from _saup2 have been | | sorted in increasing order. Thus two | | "threshold" values (one for the small end, one | | for the large end) are in the middle. | %------------------------------------------------% */ ism = max(*nev,nconv) / 2; ilg = ism + 1; thres1 = workl[ism]; thres2 = workl[ilg]; if (msglvl > 2) { kv[0] = thres1; kv[1] = thres2; igraphdvout_(&logfil, &c__2, kv, &ndigit, "_seupd: Threshold eigen" "values used for re-ordering", (ftnlen)50); } } /* %----------------------------------------------------------% | Check to see if all converged Ritz values appear within | | the first NCONV diagonal elements returned from _seigt. | | This is done in the following way: | | | | 1) For each Ritz value obtained from _seigt, compare it | | with the threshold Ritz value computed above to | | determine whether it is a wanted one. | | | | 2) If it is wanted, then check the corresponding Ritz | | estimate to see if it has converged. If it has, set | | correponding entry in the logical array SELECT to | | .TRUE.. | | | | If SELECT(j) = .TRUE. and j > NCONV, then there is a | | converged Ritz value that does not appear at the top of | | the diagonal matrix computed by _seigt in _saup2. | | Reordering is needed. | %----------------------------------------------------------% */ reord = FALSE_; ktrord = 0; i__1 = *ncv - 1; for (j = 0; j <= i__1; ++j) { select[j + 1] = FALSE_; if (s_cmp(which, "LM", (ftnlen)2, (ftnlen)2) == 0) { if ((d__1 = workl[irz + j], abs(d__1)) >= abs(thres1)) { /* Computing MAX */ d__2 = eps23, d__3 = (d__1 = workl[irz + j], abs(d__1)); tempbnd = max(d__2,d__3); if (workl[ibd + j] <= *tol * tempbnd) { select[j + 1] = TRUE_; } } } else if (s_cmp(which, "SM", (ftnlen)2, (ftnlen)2) == 0) { if ((d__1 = workl[irz + j], abs(d__1)) <= abs(thres1)) { /* Computing MAX */ d__2 = eps23, d__3 = (d__1 = workl[irz + j], abs(d__1)); tempbnd = max(d__2,d__3); if (workl[ibd + j] <= *tol * tempbnd) { select[j + 1] = TRUE_; } } } else if (s_cmp(which, "LA", (ftnlen)2, (ftnlen)2) == 0) { if (workl[irz + j] >= thres1) { /* Computing MAX */ d__2 = eps23, d__3 = (d__1 = workl[irz + j], abs(d__1)); tempbnd = max(d__2,d__3); if (workl[ibd + j] <= *tol * tempbnd) { select[j + 1] = TRUE_; } } } else if (s_cmp(which, "SA", (ftnlen)2, (ftnlen)2) == 0) { if (workl[irz + j] <= thres1) { /* Computing MAX */ d__2 = eps23, d__3 = (d__1 = workl[irz + j], abs(d__1)); tempbnd = max(d__2,d__3); if (workl[ibd + j] <= *tol * tempbnd) { select[j + 1] = TRUE_; } } } else if (s_cmp(which, "BE", (ftnlen)2, (ftnlen)2) == 0) { if (workl[irz + j] <= thres1 || workl[irz + j] >= thres2) { /* Computing MAX */ d__2 = eps23, d__3 = (d__1 = workl[irz + j], abs(d__1)); tempbnd = max(d__2,d__3); if (workl[ibd + j] <= *tol * tempbnd) { select[j + 1] = TRUE_; } } } if (j + 1 > nconv) { reord = select[j + 1] || reord; } if (select[j + 1]) { ++ktrord; } /* L10: */ } /* %-------------------------------------------% | If KTRORD .ne. NCONV, something is wrong. | %-------------------------------------------% */ if (msglvl > 2) { igraphivout_(&logfil, &c__1, &ktrord, &ndigit, "_seupd: Number of spec" "ified eigenvalues", (ftnlen)39); igraphivout_(&logfil, &c__1, &nconv, &ndigit, "_seupd: Number of \"con" "verged\" eigenvalues", (ftnlen)41); } /* %-----------------------------------------------------------% | Call LAPACK routine _steqr to compute the eigenvalues and | | eigenvectors of the final symmetric tridiagonal matrix H. | | Initialize the eigenvector matrix Q to the identity. | %-----------------------------------------------------------% */ i__1 = *ncv - 1; igraphdcopy_(&i__1, &workl[ih + 1], &c__1, &workl[ihb], &c__1); igraphdcopy_(ncv, &workl[ih + ldh], &c__1, &workl[ihd], &c__1); igraphdsteqr_("Identity", ncv, &workl[ihd], &workl[ihb], &workl[iq], &ldq, & workl[iw], &ierr); if (ierr != 0) { *info = -8; goto L9000; } if (msglvl > 1) { igraphdcopy_(ncv, &workl[iq + *ncv - 1], &ldq, &workl[iw], &c__1); igraphdvout_(&logfil, ncv, &workl[ihd], &ndigit, "_seupd: NCV Ritz val" "ues of the final H matrix", (ftnlen)45); igraphdvout_(&logfil, ncv, &workl[iw], &ndigit, "_seupd: last row of t" "he eigenvector matrix for H", (ftnlen)48); } if (reord) { /* %---------------------------------------------% | Reordered the eigenvalues and eigenvectors | | computed by _steqr so that the "converged" | | eigenvalues appear in the first NCONV | | positions of workl(ihd), and the associated | | eigenvectors appear in the first NCONV | | columns. | %---------------------------------------------% */ leftptr = 1; rghtptr = *ncv; if (*ncv == 1) { goto L30; } L20: if (select[leftptr]) { /* %-------------------------------------------% | Search, from the left, for the first Ritz | | value that has not converged. | %-------------------------------------------% */ ++leftptr; } else if (! select[rghtptr]) { /* %----------------------------------------------% | Search, from the right, the first Ritz value | | that has converged. | %----------------------------------------------% */ --rghtptr; } else { /* %----------------------------------------------% | Swap the Ritz value on the left that has not | | converged with the Ritz value on the right | | that has converged. Swap the associated | | eigenvector of the tridiagonal matrix H as | | well. | %----------------------------------------------% */ temp = workl[ihd + leftptr - 1]; workl[ihd + leftptr - 1] = workl[ihd + rghtptr - 1]; workl[ihd + rghtptr - 1] = temp; igraphdcopy_(ncv, &workl[iq + *ncv * (leftptr - 1)], &c__1, &workl[ iw], &c__1); igraphdcopy_(ncv, &workl[iq + *ncv * (rghtptr - 1)], &c__1, &workl[ iq + *ncv * (leftptr - 1)], &c__1); igraphdcopy_(ncv, &workl[iw], &c__1, &workl[iq + *ncv * (rghtptr - 1)], &c__1); ++leftptr; --rghtptr; } if (leftptr < rghtptr) { goto L20; } L30: ; } if (msglvl > 2) { igraphdvout_(&logfil, ncv, &workl[ihd], &ndigit, "_seupd: The eigenval" "ues of H--reordered", (ftnlen)39); } /* %----------------------------------------% | Load the converged Ritz values into D. | %----------------------------------------% */ igraphdcopy_(&nconv, &workl[ihd], &c__1, &d__[1], &c__1); } else { /* %-----------------------------------------------------% | Ritz vectors not required. Load Ritz values into D. | %-----------------------------------------------------% */ igraphdcopy_(&nconv, &workl[ritz], &c__1, &d__[1], &c__1); igraphdcopy_(ncv, &workl[ritz], &c__1, &workl[ihd], &c__1); } /* %------------------------------------------------------------------% | Transform the Ritz values and possibly vectors and corresponding | | Ritz estimates of OP to those of A*x=lambda*B*x. The Ritz values | | (and corresponding data) are returned in ascending order. | %------------------------------------------------------------------% */ if (s_cmp(type__, "REGULR", (ftnlen)6, (ftnlen)6) == 0) { /* %---------------------------------------------------------% | Ascending sort of wanted Ritz values, vectors and error | | bounds. Not necessary if only Ritz values are desired. | %---------------------------------------------------------% */ if (*rvec) { igraphdsesrt_("LA", rvec, &nconv, &d__[1], ncv, &workl[iq], &ldq); } else { igraphdcopy_(ncv, &workl[bounds], &c__1, &workl[ihb], &c__1); } } else { /* %-------------------------------------------------------------% | * Make a copy of all the Ritz values. | | * Transform the Ritz values back to the original system. | | For TYPE = 'SHIFTI' the transformation is | | lambda = 1/theta + sigma | | For TYPE = 'BUCKLE' the transformation is | | lambda = sigma * theta / ( theta - 1 ) | | For TYPE = 'CAYLEY' the transformation is | | lambda = sigma * (theta + 1) / (theta - 1 ) | | where the theta are the Ritz values returned by dsaupd. | | NOTES: | | *The Ritz vectors are not affected by the transformation. | | They are only reordered. | %-------------------------------------------------------------% */ igraphdcopy_(ncv, &workl[ihd], &c__1, &workl[iw], &c__1); if (s_cmp(type__, "SHIFTI", (ftnlen)6, (ftnlen)6) == 0) { i__1 = *ncv; for (k = 1; k <= i__1; ++k) { workl[ihd + k - 1] = 1. / workl[ihd + k - 1] + *sigma; /* L40: */ } } else if (s_cmp(type__, "BUCKLE", (ftnlen)6, (ftnlen)6) == 0) { i__1 = *ncv; for (k = 1; k <= i__1; ++k) { workl[ihd + k - 1] = *sigma * workl[ihd + k - 1] / (workl[ihd + k - 1] - 1.); /* L50: */ } } else if (s_cmp(type__, "CAYLEY", (ftnlen)6, (ftnlen)6) == 0) { i__1 = *ncv; for (k = 1; k <= i__1; ++k) { workl[ihd + k - 1] = *sigma * (workl[ihd + k - 1] + 1.) / ( workl[ihd + k - 1] - 1.); /* L60: */ } } /* %-------------------------------------------------------------% | * Store the wanted NCONV lambda values into D. | | * Sort the NCONV wanted lambda in WORKL(IHD:IHD+NCONV-1) | | into ascending order and apply sort to the NCONV theta | | values in the transformed system. We'll need this to | | compute Ritz estimates in the original system. | | * Finally sort the lambda's into ascending order and apply | | to Ritz vectors if wanted. Else just sort lambda's into | | ascending order. | | NOTES: | | *workl(iw:iw+ncv-1) contain the theta ordered so that they | | match the ordering of the lambda. We'll use them again for | | Ritz vector purification. | %-------------------------------------------------------------% */ igraphdcopy_(&nconv, &workl[ihd], &c__1, &d__[1], &c__1); igraphdsortr_("LA", &c_true, &nconv, &workl[ihd], &workl[iw]); if (*rvec) { igraphdsesrt_("LA", rvec, &nconv, &d__[1], ncv, &workl[iq], &ldq); } else { igraphdcopy_(ncv, &workl[bounds], &c__1, &workl[ihb], &c__1); d__1 = bnorm2 / rnorm; igraphdscal_(ncv, &d__1, &workl[ihb], &c__1); igraphdsortr_("LA", &c_true, &nconv, &d__[1], &workl[ihb]); } } /* %------------------------------------------------% | Compute the Ritz vectors. Transform the wanted | | eigenvectors of the symmetric tridiagonal H by | | the Lanczos basis matrix V. | %------------------------------------------------% */ if (*rvec && *(unsigned char *)howmny == 'A') { /* %----------------------------------------------------------% | Compute the QR factorization of the matrix representing | | the wanted invariant subspace located in the first NCONV | | columns of workl(iq,ldq). | %----------------------------------------------------------% */ igraphdgeqr2_(ncv, &nconv, &workl[iq], &ldq, &workl[iw + *ncv], &workl[ihb], &ierr); /* %--------------------------------------------------------% | * Postmultiply V by Q. | | * Copy the first NCONV columns of VQ into Z. | | The N by NCONV matrix Z is now a matrix representation | | of the approximate invariant subspace associated with | | the Ritz values in workl(ihd). | %--------------------------------------------------------% */ igraphdorm2r_("Right", "Notranspose", n, ncv, &nconv, &workl[iq], &ldq, & workl[iw + *ncv], &v[v_offset], ldv, &workd[*n + 1], &ierr); igraphdlacpy_("All", n, &nconv, &v[v_offset], ldv, &z__[z_offset], ldz); /* %-----------------------------------------------------% | In order to compute the Ritz estimates for the Ritz | | values in both systems, need the last row of the | | eigenvector matrix. Remember, it's in factored form | %-----------------------------------------------------% */ i__1 = *ncv - 1; for (j = 1; j <= i__1; ++j) { workl[ihb + j - 1] = 0.; /* L65: */ } workl[ihb + *ncv - 1] = 1.; igraphdorm2r_("Left", "Transpose", ncv, &c__1, &nconv, &workl[iq], &ldq, & workl[iw + *ncv], &workl[ihb], ncv, &temp, &ierr); } else if (*rvec && *(unsigned char *)howmny == 'S') { /* Not yet implemented. See remark 2 above. */ } if (s_cmp(type__, "REGULR", (ftnlen)6, (ftnlen)6) == 0 && *rvec) { i__1 = *ncv; for (j = 1; j <= i__1; ++j) { workl[ihb + j - 1] = rnorm * (d__1 = workl[ihb + j - 1], abs(d__1) ); /* L70: */ } } else if (s_cmp(type__, "REGULR", (ftnlen)6, (ftnlen)6) != 0 && *rvec) { /* %-------------------------------------------------% | * Determine Ritz estimates of the theta. | | If RVEC = .true. then compute Ritz estimates | | of the theta. | | If RVEC = .false. then copy Ritz estimates | | as computed by dsaupd. | | * Determine Ritz estimates of the lambda. | %-------------------------------------------------% */ igraphdscal_(ncv, &bnorm2, &workl[ihb], &c__1); if (s_cmp(type__, "SHIFTI", (ftnlen)6, (ftnlen)6) == 0) { i__1 = *ncv; for (k = 1; k <= i__1; ++k) { /* Computing 2nd power */ d__2 = workl[iw + k - 1]; workl[ihb + k - 1] = (d__1 = workl[ihb + k - 1], abs(d__1)) / (d__2 * d__2); /* L80: */ } } else if (s_cmp(type__, "BUCKLE", (ftnlen)6, (ftnlen)6) == 0) { i__1 = *ncv; for (k = 1; k <= i__1; ++k) { /* Computing 2nd power */ d__2 = workl[iw + k - 1] - 1.; workl[ihb + k - 1] = *sigma * (d__1 = workl[ihb + k - 1], abs( d__1)) / (d__2 * d__2); /* L90: */ } } else if (s_cmp(type__, "CAYLEY", (ftnlen)6, (ftnlen)6) == 0) { i__1 = *ncv; for (k = 1; k <= i__1; ++k) { workl[ihb + k - 1] = (d__1 = workl[ihb + k - 1] / workl[iw + k - 1] * (workl[iw + k - 1] - 1.), abs(d__1)); /* L100: */ } } } if (s_cmp(type__, "REGULR", (ftnlen)6, (ftnlen)6) != 0 && msglvl > 1) { igraphdvout_(&logfil, &nconv, &d__[1], &ndigit, "_seupd: Untransformed con" "verged Ritz values", (ftnlen)43); igraphdvout_(&logfil, &nconv, &workl[ihb], &ndigit, "_seupd: Ritz estimate" "s of the untransformed Ritz values", (ftnlen)55); } else if (msglvl > 1) { igraphdvout_(&logfil, &nconv, &d__[1], &ndigit, "_seupd: Converged Ritz va" "lues", (ftnlen)29); igraphdvout_(&logfil, &nconv, &workl[ihb], &ndigit, "_seupd: Associated Ri" "tz estimates", (ftnlen)33); } /* %-------------------------------------------------% | Ritz vector purification step. Formally perform | | one of inverse subspace iteration. Only used | | for MODE = 3,4,5. See reference 7 | %-------------------------------------------------% */ if (*rvec && (s_cmp(type__, "SHIFTI", (ftnlen)6, (ftnlen)6) == 0 || s_cmp( type__, "CAYLEY", (ftnlen)6, (ftnlen)6) == 0)) { i__1 = nconv - 1; for (k = 0; k <= i__1; ++k) { workl[iw + k] = workl[iq + k * ldq + *ncv - 1] / workl[iw + k]; /* L110: */ } } else if (*rvec && s_cmp(type__, "BUCKLE", (ftnlen)6, (ftnlen)6) == 0) { i__1 = nconv - 1; for (k = 0; k <= i__1; ++k) { workl[iw + k] = workl[iq + k * ldq + *ncv - 1] / (workl[iw + k] - 1.); /* L120: */ } } if (s_cmp(type__, "REGULR", (ftnlen)6, (ftnlen)6) != 0) { igraphdger_(n, &nconv, &c_b119, &resid[1], &c__1, &workl[iw], &c__1, &z__[ z_offset], ldz); } L9000: return 0; /* %---------------% | End of dseupd | %---------------% */ } /* igraphdseupd_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dsgets.c0000644000076500000240000002154213524616145024301 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static logical c_true = TRUE_; static integer c__1 = 1; /* ----------------------------------------------------------------------- \BeginDoc \Name: dsgets \Description: Given the eigenvalues of the symmetric tridiagonal matrix H, computes the NP shifts AMU that are zeros of the polynomial of degree NP which filters out components of the unwanted eigenvectors corresponding to the AMU's based on some given criteria. NOTE: This is called even in the case of user specified shifts in order to sort the eigenvalues, and error bounds of H for later use. \Usage: call dsgets ( ISHIFT, WHICH, KEV, NP, RITZ, BOUNDS, SHIFTS ) \Arguments ISHIFT Integer. (INPUT) Method for selecting the implicit shifts at each iteration. ISHIFT = 0: user specified shifts ISHIFT = 1: exact shift with respect to the matrix H. WHICH Character*2. (INPUT) Shift selection criteria. 'LM' -> KEV eigenvalues of largest magnitude are retained. 'SM' -> KEV eigenvalues of smallest magnitude are retained. 'LA' -> KEV eigenvalues of largest value are retained. 'SA' -> KEV eigenvalues of smallest value are retained. 'BE' -> KEV eigenvalues, half from each end of the spectrum. If KEV is odd, compute one more from the high end. KEV Integer. (INPUT) KEV+NP is the size of the matrix H. NP Integer. (INPUT) Number of implicit shifts to be computed. RITZ Double precision array of length KEV+NP. (INPUT/OUTPUT) On INPUT, RITZ contains the eigenvalues of H. On OUTPUT, RITZ are sorted so that the unwanted eigenvalues are in the first NP locations and the wanted part is in the last KEV locations. When exact shifts are selected, the unwanted part corresponds to the shifts to be applied. BOUNDS Double precision array of length KEV+NP. (INPUT/OUTPUT) Error bounds corresponding to the ordering in RITZ. SHIFTS Double precision array of length NP. (INPUT/OUTPUT) On INPUT: contains the user specified shifts if ISHIFT = 0. On OUTPUT: contains the shifts sorted into decreasing order of magnitude with respect to the Ritz estimates contained in BOUNDS. If ISHIFT = 0, SHIFTS is not modified on exit. \EndDoc ----------------------------------------------------------------------- \BeginLib \Local variables: xxxxxx real \Routines called: dsortr ARPACK utility sorting routine. ivout ARPACK utility routine that prints integers. second ARPACK utility routine for timing. dvout ARPACK utility routine that prints vectors. dcopy Level 1 BLAS that copies one vector to another. dswap Level 1 BLAS that swaps the contents of two vectors. \Author Danny Sorensen Phuong Vu Richard Lehoucq CRPC / Rice University Dept. of Computational & Houston, Texas Applied Mathematics Rice University Houston, Texas \Revision history: xx/xx/93: Version ' 2.1' \SCCS Information: @(#) FILE: sgets.F SID: 2.4 DATE OF SID: 4/19/96 RELEASE: 2 \Remarks \EndLib ----------------------------------------------------------------------- Subroutine */ int igraphdsgets_(integer *ishift, char *which, integer *kev, integer *np, doublereal *ritz, doublereal *bounds, doublereal *shifts) { /* System generated locals */ integer i__1; /* Builtin functions */ integer s_cmp(char *, char *, ftnlen, ftnlen); /* Local variables */ real t0, t1; integer kevd2; extern /* Subroutine */ int igraphdswap_(integer *, doublereal *, integer *, doublereal *, integer *), igraphdcopy_(integer *, doublereal *, integer *, doublereal *, integer *), igraphdvout_(integer *, integer *, doublereal *, integer *, char *, ftnlen), igraphivout_(integer *, integer *, integer *, integer *, char *, ftnlen), igraphsecond_(real *); integer logfil, ndigit, msgets = 0, msglvl; real tsgets = 0.0; extern /* Subroutine */ int igraphdsortr_(char *, logical *, integer *, doublereal *, doublereal *); /* %----------------------------------------------------% | Include files for debugging and timing information | %----------------------------------------------------% %------------------% | Scalar Arguments | %------------------% %-----------------% | Array Arguments | %-----------------% %------------% | Parameters | %------------% %---------------% | Local Scalars | %---------------% %----------------------% | External Subroutines | %----------------------% %---------------------% | Intrinsic Functions | %---------------------% %-----------------------% | Executable Statements | %-----------------------% %-------------------------------% | Initialize timing statistics | | & message level for debugging | %-------------------------------% Parameter adjustments */ --shifts; --bounds; --ritz; /* Function Body */ igraphsecond_(&t0); msglvl = msgets; if (s_cmp(which, "BE", (ftnlen)2, (ftnlen)2) == 0) { /* %-----------------------------------------------------% | Both ends of the spectrum are requested. | | Sort the eigenvalues into algebraically increasing | | order first then swap high end of the spectrum next | | to low end in appropriate locations. | | NOTE: when np < floor(kev/2) be careful not to swap | | overlapping locations. | %-----------------------------------------------------% */ i__1 = *kev + *np; igraphdsortr_("LA", &c_true, &i__1, &ritz[1], &bounds[1]); kevd2 = *kev / 2; if (*kev > 1) { i__1 = min(kevd2,*np); igraphdswap_(&i__1, &ritz[1], &c__1, &ritz[max(kevd2,*np) + 1], &c__1); i__1 = min(kevd2,*np); igraphdswap_(&i__1, &bounds[1], &c__1, &bounds[max(kevd2,*np) + 1], & c__1); } } else { /* %----------------------------------------------------% | LM, SM, LA, SA case. | | Sort the eigenvalues of H into the desired order | | and apply the resulting order to BOUNDS. | | The eigenvalues are sorted so that the wanted part | | are always in the last KEV locations. | %----------------------------------------------------% */ i__1 = *kev + *np; igraphdsortr_(which, &c_true, &i__1, &ritz[1], &bounds[1]); } if (*ishift == 1 && *np > 0) { /* %-------------------------------------------------------% | Sort the unwanted Ritz values used as shifts so that | | the ones with largest Ritz estimates are first. | | This will tend to minimize the effects of the | | forward instability of the iteration when the shifts | | are applied in subroutine dsapps. | %-------------------------------------------------------% */ igraphdsortr_("SM", &c_true, np, &bounds[1], &ritz[1]); igraphdcopy_(np, &ritz[1], &c__1, &shifts[1], &c__1); } igraphsecond_(&t1); tsgets += t1 - t0; if (msglvl > 0) { igraphivout_(&logfil, &c__1, kev, &ndigit, "_sgets: KEV is", (ftnlen)14); igraphivout_(&logfil, &c__1, np, &ndigit, "_sgets: NP is", (ftnlen)13); i__1 = *kev + *np; igraphdvout_(&logfil, &i__1, &ritz[1], &ndigit, "_sgets: Eigenvalues of cu" "rrent H matrix", (ftnlen)39); i__1 = *kev + *np; igraphdvout_(&logfil, &i__1, &bounds[1], &ndigit, "_sgets: Associated Ritz" " estimates", (ftnlen)33); } return 0; /* %---------------% | End of dsgets | %---------------% */ } /* igraphdsgets_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dorg2r.c0000644000076500000240000001445113524616145024210 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; /* > \brief \b DORG2R generates all or part of the orthogonal matrix Q from a QR factorization determined by s geqrf (unblocked algorithm). =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DORG2R + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DORG2R( M, N, K, A, LDA, TAU, WORK, INFO ) INTEGER INFO, K, LDA, M, N DOUBLE PRECISION A( LDA, * ), TAU( * ), WORK( * ) > \par Purpose: ============= > > \verbatim > > DORG2R generates an m by n real matrix Q with orthonormal columns, > which is defined as the first n columns of a product of k elementary > reflectors of order m > > Q = H(1) H(2) . . . H(k) > > as returned by DGEQRF. > \endverbatim Arguments: ========== > \param[in] M > \verbatim > M is INTEGER > The number of rows of the matrix Q. M >= 0. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The number of columns of the matrix Q. M >= N >= 0. > \endverbatim > > \param[in] K > \verbatim > K is INTEGER > The number of elementary reflectors whose product defines the > matrix Q. N >= K >= 0. > \endverbatim > > \param[in,out] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,N) > On entry, the i-th column must contain the vector which > defines the elementary reflector H(i), for i = 1,2,...,k, as > returned by DGEQRF in the first k columns of its array > argument A. > On exit, the m-by-n matrix Q. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The first dimension of the array A. LDA >= max(1,M). > \endverbatim > > \param[in] TAU > \verbatim > TAU is DOUBLE PRECISION array, dimension (K) > TAU(i) must contain the scalar factor of the elementary > reflector H(i), as returned by DGEQRF. > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (N) > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument has an illegal value > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleOTHERcomputational ===================================================================== Subroutine */ int igraphdorg2r_(integer *m, integer *n, integer *k, doublereal * a, integer *lda, doublereal *tau, doublereal *work, integer *info) { /* System generated locals */ integer a_dim1, a_offset, i__1, i__2; doublereal d__1; /* Local variables */ integer i__, j, l; extern /* Subroutine */ int igraphdscal_(integer *, doublereal *, doublereal *, integer *), igraphdlarf_(char *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *), igraphxerbla_(char *, integer *, ftnlen); /* -- LAPACK computational routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Test the input arguments Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --tau; --work; /* Function Body */ *info = 0; if (*m < 0) { *info = -1; } else if (*n < 0 || *n > *m) { *info = -2; } else if (*k < 0 || *k > *n) { *info = -3; } else if (*lda < max(1,*m)) { *info = -5; } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DORG2R", &i__1, (ftnlen)6); return 0; } /* Quick return if possible */ if (*n <= 0) { return 0; } /* Initialise columns k+1:n to columns of the unit matrix */ i__1 = *n; for (j = *k + 1; j <= i__1; ++j) { i__2 = *m; for (l = 1; l <= i__2; ++l) { a[l + j * a_dim1] = 0.; /* L10: */ } a[j + j * a_dim1] = 1.; /* L20: */ } for (i__ = *k; i__ >= 1; --i__) { /* Apply H(i) to A(i:m,i:n) from the left */ if (i__ < *n) { a[i__ + i__ * a_dim1] = 1.; i__1 = *m - i__ + 1; i__2 = *n - i__; igraphdlarf_("Left", &i__1, &i__2, &a[i__ + i__ * a_dim1], &c__1, &tau[ i__], &a[i__ + (i__ + 1) * a_dim1], lda, &work[1]); } if (i__ < *m) { i__1 = *m - i__; d__1 = -tau[i__]; igraphdscal_(&i__1, &d__1, &a[i__ + 1 + i__ * a_dim1], &c__1); } a[i__ + i__ * a_dim1] = 1. - tau[i__]; /* Set A(1:i-1,i) to zero */ i__1 = i__ - 1; for (l = 1; l <= i__1; ++l) { a[l + i__ * a_dim1] = 0.; /* L30: */ } /* L40: */ } return 0; /* End of DORG2R */ } /* igraphdorg2r_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dneigh.c0000644000076500000240000003106513524616145024247 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static logical c_true = TRUE_; static integer c__1 = 1; static doublereal c_b18 = 1.; static doublereal c_b20 = 0.; /* ----------------------------------------------------------------------- \BeginDoc \Name: dneigh \Description: Compute the eigenvalues of the current upper Hessenberg matrix and the corresponding Ritz estimates given the current residual norm. \Usage: call dneigh ( RNORM, N, H, LDH, RITZR, RITZI, BOUNDS, Q, LDQ, WORKL, IERR ) \Arguments RNORM Double precision scalar. (INPUT) Residual norm corresponding to the current upper Hessenberg matrix H. N Integer. (INPUT) Size of the matrix H. H Double precision N by N array. (INPUT) H contains the current upper Hessenberg matrix. LDH Integer. (INPUT) Leading dimension of H exactly as declared in the calling program. RITZR, Double precision arrays of length N. (OUTPUT) RITZI On output, RITZR(1:N) (resp. RITZI(1:N)) contains the real (respectively imaginary) parts of the eigenvalues of H. BOUNDS Double precision array of length N. (OUTPUT) On output, BOUNDS contains the Ritz estimates associated with the eigenvalues RITZR and RITZI. This is equal to RNORM times the last components of the eigenvectors corresponding to the eigenvalues in RITZR and RITZI. Q Double precision N by N array. (WORKSPACE) Workspace needed to store the eigenvectors of H. LDQ Integer. (INPUT) Leading dimension of Q exactly as declared in the calling program. WORKL Double precision work array of length N**2 + 3*N. (WORKSPACE) Private (replicated) array on each PE or array allocated on the front end. This is needed to keep the full Schur form of H and also in the calculation of the eigenvectors of H. IERR Integer. (OUTPUT) Error exit flag from dlaqrb or dtrevc. \EndDoc ----------------------------------------------------------------------- \BeginLib \Local variables: xxxxxx real \Routines called: dlaqrb ARPACK routine to compute the real Schur form of an upper Hessenberg matrix and last row of the Schur vectors. second ARPACK utility routine for timing. dmout ARPACK utility routine that prints matrices dvout ARPACK utility routine that prints vectors. dlacpy LAPACK matrix copy routine. dlapy2 LAPACK routine to compute sqrt(x**2+y**2) carefully. dtrevc LAPACK routine to compute the eigenvectors of a matrix in upper quasi-triangular form dgemv Level 2 BLAS routine for matrix vector multiplication. dcopy Level 1 BLAS that copies one vector to another . dnrm2 Level 1 BLAS that computes the norm of a vector. dscal Level 1 BLAS that scales a vector. \Author Danny Sorensen Phuong Vu Richard Lehoucq CRPC / Rice University Dept. of Computational & Houston, Texas Applied Mathematics Rice University Houston, Texas \Revision history: xx/xx/92: Version ' 2.1' \SCCS Information: @(#) FILE: neigh.F SID: 2.3 DATE OF SID: 4/20/96 RELEASE: 2 \Remarks None \EndLib ----------------------------------------------------------------------- Subroutine */ int igraphdneigh_(doublereal *rnorm, integer *n, doublereal *h__, integer *ldh, doublereal *ritzr, doublereal *ritzi, doublereal * bounds, doublereal *q, integer *ldq, doublereal *workl, integer *ierr) { /* System generated locals */ integer h_dim1, h_offset, q_dim1, q_offset, i__1; doublereal d__1, d__2; /* Local variables */ integer i__; real t0, t1; doublereal vl[1], temp; extern doublereal igraphdnrm2_(integer *, doublereal *, integer *); extern /* Subroutine */ int igraphdscal_(integer *, doublereal *, doublereal *, integer *); integer iconj; extern /* Subroutine */ int igraphdgemv_(char *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *), igraphdmout_(integer *, integer *, integer *, doublereal *, integer *, integer *, char *, ftnlen), igraphdvout_(integer *, integer *, doublereal *, integer *, char *, ftnlen); extern doublereal igraphdlapy2_(doublereal *, doublereal *); extern /* Subroutine */ int igraphdlaqrb_(logical *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, integer *); integer mneigh = 0; extern /* Subroutine */ int igraphsecond_(real *), igraphdlacpy_(char *, integer *, integer *, doublereal *, integer *, doublereal *, integer *); integer logfil, ndigit; logical select[1]; real tneigh = 0.; extern /* Subroutine */ int igraphdtrevc_(char *, char *, logical *, integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, integer *, integer *, integer *, doublereal *, integer *); integer msglvl; /* %----------------------------------------------------% | Include files for debugging and timing information | %----------------------------------------------------% %------------------% | Scalar Arguments | %------------------% %-----------------% | Array Arguments | %-----------------% %------------% | Parameters | %------------% %------------------------% | Local Scalars & Arrays | %------------------------% %----------------------% | External Subroutines | %----------------------% %--------------------% | External Functions | %--------------------% %---------------------% | Intrinsic Functions | %---------------------% %-----------------------% | Executable Statements | %-----------------------% %-------------------------------% | Initialize timing statistics | | & message level for debugging | %-------------------------------% Parameter adjustments */ --workl; --bounds; --ritzi; --ritzr; h_dim1 = *ldh; h_offset = 1 + h_dim1; h__ -= h_offset; q_dim1 = *ldq; q_offset = 1 + q_dim1; q -= q_offset; /* Function Body */ igraphsecond_(&t0); msglvl = mneigh; if (msglvl > 2) { igraphdmout_(&logfil, n, n, &h__[h_offset], ldh, &ndigit, "_neigh: Enterin" "g upper Hessenberg matrix H ", (ftnlen)43); } /* %-----------------------------------------------------------% | 1. Compute the eigenvalues, the last components of the | | corresponding Schur vectors and the full Schur form T | | of the current upper Hessenberg matrix H. | | dlaqrb returns the full Schur form of H in WORKL(1:N**2) | | and the last components of the Schur vectors in BOUNDS. | %-----------------------------------------------------------% */ igraphdlacpy_("All", n, n, &h__[h_offset], ldh, &workl[1], n); igraphdlaqrb_(&c_true, n, &c__1, n, &workl[1], n, &ritzr[1], &ritzi[1], &bounds[ 1], ierr); if (*ierr != 0) { goto L9000; } if (msglvl > 1) { igraphdvout_(&logfil, n, &bounds[1], &ndigit, "_neigh: last row of the Sch" "ur matrix for H", (ftnlen)42); } /* %-----------------------------------------------------------% | 2. Compute the eigenvectors of the full Schur form T and | | apply the last components of the Schur vectors to get | | the last components of the corresponding eigenvectors. | | Remember that if the i-th and (i+1)-st eigenvalues are | | complex conjugate pairs, then the real & imaginary part | | of the eigenvector components are split across adjacent | | columns of Q. | %-----------------------------------------------------------% */ igraphdtrevc_("R", "A", select, n, &workl[1], n, vl, n, &q[q_offset], ldq, n, n, &workl[*n * *n + 1], ierr); if (*ierr != 0) { goto L9000; } /* %------------------------------------------------% | Scale the returning eigenvectors so that their | | euclidean norms are all one. LAPACK subroutine | | dtrevc returns each eigenvector normalized so | | that the element of largest magnitude has | | magnitude 1; here the magnitude of a complex | | number (x,y) is taken to be |x| + |y|. | %------------------------------------------------% */ iconj = 0; i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { if ((d__1 = ritzi[i__], abs(d__1)) <= 0.) { /* %----------------------% | Real eigenvalue case | %----------------------% */ temp = igraphdnrm2_(n, &q[i__ * q_dim1 + 1], &c__1); d__1 = 1. / temp; igraphdscal_(n, &d__1, &q[i__ * q_dim1 + 1], &c__1); } else { /* %-------------------------------------------% | Complex conjugate pair case. Note that | | since the real and imaginary part of | | the eigenvector are stored in consecutive | | columns, we further normalize by the | | square root of two. | %-------------------------------------------% */ if (iconj == 0) { d__1 = igraphdnrm2_(n, &q[i__ * q_dim1 + 1], &c__1); d__2 = igraphdnrm2_(n, &q[(i__ + 1) * q_dim1 + 1], &c__1); temp = igraphdlapy2_(&d__1, &d__2); d__1 = 1. / temp; igraphdscal_(n, &d__1, &q[i__ * q_dim1 + 1], &c__1); d__1 = 1. / temp; igraphdscal_(n, &d__1, &q[(i__ + 1) * q_dim1 + 1], &c__1); iconj = 1; } else { iconj = 0; } } /* L10: */ } igraphdgemv_("T", n, n, &c_b18, &q[q_offset], ldq, &bounds[1], &c__1, &c_b20, & workl[1], &c__1); if (msglvl > 1) { igraphdvout_(&logfil, n, &workl[1], &ndigit, "_neigh: Last row of the eige" "nvector matrix for H", (ftnlen)48); } /* %----------------------------% | Compute the Ritz estimates | %----------------------------% */ iconj = 0; i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { if ((d__1 = ritzi[i__], abs(d__1)) <= 0.) { /* %----------------------% | Real eigenvalue case | %----------------------% */ bounds[i__] = *rnorm * (d__1 = workl[i__], abs(d__1)); } else { /* %-------------------------------------------% | Complex conjugate pair case. Note that | | since the real and imaginary part of | | the eigenvector are stored in consecutive | | columns, we need to take the magnitude | | of the last components of the two vectors | %-------------------------------------------% */ if (iconj == 0) { bounds[i__] = *rnorm * igraphdlapy2_(&workl[i__], &workl[i__ + 1]); bounds[i__ + 1] = bounds[i__]; iconj = 1; } else { iconj = 0; } } /* L20: */ } if (msglvl > 2) { igraphdvout_(&logfil, n, &ritzr[1], &ndigit, "_neigh: Real part of the eig" "envalues of H", (ftnlen)41); igraphdvout_(&logfil, n, &ritzi[1], &ndigit, "_neigh: Imaginary part of th" "e eigenvalues of H", (ftnlen)46); igraphdvout_(&logfil, n, &bounds[1], &ndigit, "_neigh: Ritz estimates for " "the eigenvalues of H", (ftnlen)47); } igraphsecond_(&t1); tneigh += t1 - t0; L9000: return 0; /* %---------------% | End of dneigh | %---------------% */ } /* igraphdneigh_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/lsame.c0000644000076500000240000000532713524616145024114 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" logical igraphlsame_(char *ca, char *cb) { /* System generated locals */ logical ret_val; /* Local variables */ integer inta, intb, zcode; /* -- LAPACK auxiliary routine (version 3.1) -- Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. November 2006 Purpose ======= LSAME returns .TRUE. if CA is the same letter as CB regardless of case. Arguments ========= CA (input) CHARACTER*1 CB (input) CHARACTER*1 CA and CB specify the single characters to be compared. ===================================================================== Test if the characters are equal */ ret_val = *(unsigned char *)ca == *(unsigned char *)cb; if (ret_val) { return ret_val; } /* Now test for equivalence if both characters are alphabetic. */ zcode = 'Z'; /* Use 'Z' rather than 'A' so that ASCII can be detected on Prime machines, on which ICHAR returns a value with bit 8 set. ICHAR('A') on Prime machines returns 193 which is the same as ICHAR('A') on an EBCDIC machine. */ inta = *(unsigned char *)ca; intb = *(unsigned char *)cb; if (zcode == 90 || zcode == 122) { /* ASCII is assumed - ZCODE is the ASCII code of either lower or upper case 'Z'. */ if (inta >= 97 && inta <= 122) { inta += -32; } if (intb >= 97 && intb <= 122) { intb += -32; } } else if (zcode == 233 || zcode == 169) { /* EBCDIC is assumed - ZCODE is the EBCDIC code of either lower or upper case 'Z'. */ if (inta >= 129 && inta <= 137 || inta >= 145 && inta <= 153 || inta >= 162 && inta <= 169) { inta += 64; } if (intb >= 129 && intb <= 137 || intb >= 145 && intb <= 153 || intb >= 162 && intb <= 169) { intb += 64; } } else if (zcode == 218 || zcode == 250) { /* ASCII is assumed, on Prime machines - ZCODE is the ASCII code plus 128 of either lower or upper case 'Z'. */ if (inta >= 225 && inta <= 250) { inta += -32; } if (intb >= 225 && intb <= 250) { intb += -32; } } ret_val = inta == intb; /* RETURN End of LSAME */ return ret_val; } /* igraphlsame_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlassq.c0000644000076500000240000001152013524616145024272 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLASSQ updates a sum of squares represented in scaled form. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLASSQ + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLASSQ( N, X, INCX, SCALE, SUMSQ ) INTEGER INCX, N DOUBLE PRECISION SCALE, SUMSQ DOUBLE PRECISION X( * ) > \par Purpose: ============= > > \verbatim > > DLASSQ returns the values scl and smsq such that > > ( scl**2 )*smsq = x( 1 )**2 +...+ x( n )**2 + ( scale**2 )*sumsq, > > where x( i ) = X( 1 + ( i - 1 )*INCX ). The value of sumsq is > assumed to be non-negative and scl returns the value > > scl = max( scale, abs( x( i ) ) ). > > scale and sumsq must be supplied in SCALE and SUMSQ and > scl and smsq are overwritten on SCALE and SUMSQ respectively. > > The routine makes only one pass through the vector x. > \endverbatim Arguments: ========== > \param[in] N > \verbatim > N is INTEGER > The number of elements to be used from the vector X. > \endverbatim > > \param[in] X > \verbatim > X is DOUBLE PRECISION array, dimension (N) > The vector for which a scaled sum of squares is computed. > x( i ) = X( 1 + ( i - 1 )*INCX ), 1 <= i <= n. > \endverbatim > > \param[in] INCX > \verbatim > INCX is INTEGER > The increment between successive values of the vector X. > INCX > 0. > \endverbatim > > \param[in,out] SCALE > \verbatim > SCALE is DOUBLE PRECISION > On entry, the value scale in the equation above. > On exit, SCALE is overwritten with scl , the scaling factor > for the sum of squares. > \endverbatim > > \param[in,out] SUMSQ > \verbatim > SUMSQ is DOUBLE PRECISION > On entry, the value sumsq in the equation above. > On exit, SUMSQ is overwritten with smsq , the basic sum of > squares from which scl has been factored out. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERauxiliary ===================================================================== Subroutine */ int igraphdlassq_(integer *n, doublereal *x, integer *incx, doublereal *scale, doublereal *sumsq) { /* System generated locals */ integer i__1, i__2; doublereal d__1; /* Local variables */ integer ix; doublereal absxi; extern logical igraphdisnan_(doublereal *); /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ --x; /* Function Body */ if (*n > 0) { i__1 = (*n - 1) * *incx + 1; i__2 = *incx; for (ix = 1; i__2 < 0 ? ix >= i__1 : ix <= i__1; ix += i__2) { absxi = (d__1 = x[ix], abs(d__1)); if (absxi > 0. || igraphdisnan_(&absxi)) { if (*scale < absxi) { /* Computing 2nd power */ d__1 = *scale / absxi; *sumsq = *sumsq * (d__1 * d__1) + 1; *scale = absxi; } else { /* Computing 2nd power */ d__1 = absxi / *scale; *sumsq += d__1 * d__1; } } /* L10: */ } } return 0; /* End of DLASSQ */ } /* igraphdlassq_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dtrmm.c0000644000076500000240000002620513524616145024134 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Subroutine */ int igraphdtrmm_(char *side, char *uplo, char *transa, char *diag, integer *m, integer *n, doublereal *alpha, doublereal *a, integer * lda, doublereal *b, integer *ldb) { /* System generated locals */ integer a_dim1, a_offset, b_dim1, b_offset, i__1, i__2, i__3; /* Local variables */ integer i__, j, k, info; doublereal temp; logical lside; extern logical igraphlsame_(char *, char *); integer nrowa; logical upper; extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); logical nounit; /* Purpose ======= DTRMM performs one of the matrix-matrix operations B := alpha*op( A )*B, or B := alpha*B*op( A ), where alpha is a scalar, B is an m by n matrix, A is a unit, or non-unit, upper or lower triangular matrix and op( A ) is one of op( A ) = A or op( A ) = A**T. Arguments ========== SIDE - CHARACTER*1. On entry, SIDE specifies whether op( A ) multiplies B from the left or right as follows: SIDE = 'L' or 'l' B := alpha*op( A )*B. SIDE = 'R' or 'r' B := alpha*B*op( A ). Unchanged on exit. UPLO - CHARACTER*1. On entry, UPLO specifies whether the matrix A is an upper or lower triangular matrix as follows: UPLO = 'U' or 'u' A is an upper triangular matrix. UPLO = 'L' or 'l' A is a lower triangular matrix. Unchanged on exit. TRANSA - CHARACTER*1. On entry, TRANSA specifies the form of op( A ) to be used in the matrix multiplication as follows: TRANSA = 'N' or 'n' op( A ) = A. TRANSA = 'T' or 't' op( A ) = A**T. TRANSA = 'C' or 'c' op( A ) = A**T. Unchanged on exit. DIAG - CHARACTER*1. On entry, DIAG specifies whether or not A is unit triangular as follows: DIAG = 'U' or 'u' A is assumed to be unit triangular. DIAG = 'N' or 'n' A is not assumed to be unit triangular. Unchanged on exit. M - INTEGER. On entry, M specifies the number of rows of B. M must be at least zero. Unchanged on exit. N - INTEGER. On entry, N specifies the number of columns of B. N must be at least zero. Unchanged on exit. ALPHA - DOUBLE PRECISION. On entry, ALPHA specifies the scalar alpha. When alpha is zero then A is not referenced and B need not be set before entry. Unchanged on exit. A - DOUBLE PRECISION array of DIMENSION ( LDA, k ), where k is m when SIDE = 'L' or 'l' and is n when SIDE = 'R' or 'r'. Before entry with UPLO = 'U' or 'u', the leading k by k upper triangular part of the array A must contain the upper triangular matrix and the strictly lower triangular part of A is not referenced. Before entry with UPLO = 'L' or 'l', the leading k by k lower triangular part of the array A must contain the lower triangular matrix and the strictly upper triangular part of A is not referenced. Note that when DIAG = 'U' or 'u', the diagonal elements of A are not referenced either, but are assumed to be unity. Unchanged on exit. LDA - INTEGER. On entry, LDA specifies the first dimension of A as declared in the calling (sub) program. When SIDE = 'L' or 'l' then LDA must be at least max( 1, m ), when SIDE = 'R' or 'r' then LDA must be at least max( 1, n ). Unchanged on exit. B - DOUBLE PRECISION array of DIMENSION ( LDB, n ). Before entry, the leading m by n part of the array B must contain the matrix B, and on exit is overwritten by the transformed matrix. LDB - INTEGER. On entry, LDB specifies the first dimension of B as declared in the calling (sub) program. LDB must be at least max( 1, m ). Unchanged on exit. Further Details =============== Level 3 Blas routine. -- Written on 8-February-1989. Jack Dongarra, Argonne National Laboratory. Iain Duff, AERE Harwell. Jeremy Du Croz, Numerical Algorithms Group Ltd. Sven Hammarling, Numerical Algorithms Group Ltd. ===================================================================== Test the input parameters. Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; b_dim1 = *ldb; b_offset = 1 + b_dim1; b -= b_offset; /* Function Body */ lside = igraphlsame_(side, "L"); if (lside) { nrowa = *m; } else { nrowa = *n; } nounit = igraphlsame_(diag, "N"); upper = igraphlsame_(uplo, "U"); info = 0; if (! lside && ! igraphlsame_(side, "R")) { info = 1; } else if (! upper && ! igraphlsame_(uplo, "L")) { info = 2; } else if (! igraphlsame_(transa, "N") && ! igraphlsame_(transa, "T") && ! igraphlsame_(transa, "C")) { info = 3; } else if (! igraphlsame_(diag, "U") && ! igraphlsame_(diag, "N")) { info = 4; } else if (*m < 0) { info = 5; } else if (*n < 0) { info = 6; } else if (*lda < max(1,nrowa)) { info = 9; } else if (*ldb < max(1,*m)) { info = 11; } if (info != 0) { igraphxerbla_("DTRMM ", &info, (ftnlen)6); return 0; } /* Quick return if possible. */ if (*m == 0 || *n == 0) { return 0; } /* And when alpha.eq.zero. */ if (*alpha == 0.) { i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { b[i__ + j * b_dim1] = 0.; /* L10: */ } /* L20: */ } return 0; } /* Start the operations. */ if (lside) { if (igraphlsame_(transa, "N")) { /* Form B := alpha*A*B. */ if (upper) { i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = *m; for (k = 1; k <= i__2; ++k) { if (b[k + j * b_dim1] != 0.) { temp = *alpha * b[k + j * b_dim1]; i__3 = k - 1; for (i__ = 1; i__ <= i__3; ++i__) { b[i__ + j * b_dim1] += temp * a[i__ + k * a_dim1]; /* L30: */ } if (nounit) { temp *= a[k + k * a_dim1]; } b[k + j * b_dim1] = temp; } /* L40: */ } /* L50: */ } } else { i__1 = *n; for (j = 1; j <= i__1; ++j) { for (k = *m; k >= 1; --k) { if (b[k + j * b_dim1] != 0.) { temp = *alpha * b[k + j * b_dim1]; b[k + j * b_dim1] = temp; if (nounit) { b[k + j * b_dim1] *= a[k + k * a_dim1]; } i__2 = *m; for (i__ = k + 1; i__ <= i__2; ++i__) { b[i__ + j * b_dim1] += temp * a[i__ + k * a_dim1]; /* L60: */ } } /* L70: */ } /* L80: */ } } } else { /* Form B := alpha*A**T*B. */ if (upper) { i__1 = *n; for (j = 1; j <= i__1; ++j) { for (i__ = *m; i__ >= 1; --i__) { temp = b[i__ + j * b_dim1]; if (nounit) { temp *= a[i__ + i__ * a_dim1]; } i__2 = i__ - 1; for (k = 1; k <= i__2; ++k) { temp += a[k + i__ * a_dim1] * b[k + j * b_dim1]; /* L90: */ } b[i__ + j * b_dim1] = *alpha * temp; /* L100: */ } /* L110: */ } } else { i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { temp = b[i__ + j * b_dim1]; if (nounit) { temp *= a[i__ + i__ * a_dim1]; } i__3 = *m; for (k = i__ + 1; k <= i__3; ++k) { temp += a[k + i__ * a_dim1] * b[k + j * b_dim1]; /* L120: */ } b[i__ + j * b_dim1] = *alpha * temp; /* L130: */ } /* L140: */ } } } } else { if (igraphlsame_(transa, "N")) { /* Form B := alpha*B*A. */ if (upper) { for (j = *n; j >= 1; --j) { temp = *alpha; if (nounit) { temp *= a[j + j * a_dim1]; } i__1 = *m; for (i__ = 1; i__ <= i__1; ++i__) { b[i__ + j * b_dim1] = temp * b[i__ + j * b_dim1]; /* L150: */ } i__1 = j - 1; for (k = 1; k <= i__1; ++k) { if (a[k + j * a_dim1] != 0.) { temp = *alpha * a[k + j * a_dim1]; i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { b[i__ + j * b_dim1] += temp * b[i__ + k * b_dim1]; /* L160: */ } } /* L170: */ } /* L180: */ } } else { i__1 = *n; for (j = 1; j <= i__1; ++j) { temp = *alpha; if (nounit) { temp *= a[j + j * a_dim1]; } i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { b[i__ + j * b_dim1] = temp * b[i__ + j * b_dim1]; /* L190: */ } i__2 = *n; for (k = j + 1; k <= i__2; ++k) { if (a[k + j * a_dim1] != 0.) { temp = *alpha * a[k + j * a_dim1]; i__3 = *m; for (i__ = 1; i__ <= i__3; ++i__) { b[i__ + j * b_dim1] += temp * b[i__ + k * b_dim1]; /* L200: */ } } /* L210: */ } /* L220: */ } } } else { /* Form B := alpha*B*A**T. */ if (upper) { i__1 = *n; for (k = 1; k <= i__1; ++k) { i__2 = k - 1; for (j = 1; j <= i__2; ++j) { if (a[j + k * a_dim1] != 0.) { temp = *alpha * a[j + k * a_dim1]; i__3 = *m; for (i__ = 1; i__ <= i__3; ++i__) { b[i__ + j * b_dim1] += temp * b[i__ + k * b_dim1]; /* L230: */ } } /* L240: */ } temp = *alpha; if (nounit) { temp *= a[k + k * a_dim1]; } if (temp != 1.) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { b[i__ + k * b_dim1] = temp * b[i__ + k * b_dim1]; /* L250: */ } } /* L260: */ } } else { for (k = *n; k >= 1; --k) { i__1 = *n; for (j = k + 1; j <= i__1; ++j) { if (a[j + k * a_dim1] != 0.) { temp = *alpha * a[j + k * a_dim1]; i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { b[i__ + j * b_dim1] += temp * b[i__ + k * b_dim1]; /* L270: */ } } /* L280: */ } temp = *alpha; if (nounit) { temp *= a[k + k * a_dim1]; } if (temp != 1.) { i__1 = *m; for (i__ = 1; i__ <= i__1; ++i__) { b[i__ + k * b_dim1] = temp * b[i__ + k * b_dim1]; /* L290: */ } } /* L300: */ } } } } return 0; /* End of DTRMM . */ } /* igraphdtrmm_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlasq2.c0000644000076500000240000004337613524616145024207 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static integer c__2 = 2; static integer c__10 = 10; static integer c__3 = 3; static integer c__4 = 4; static integer c__11 = 11; /* > \brief \b DLASQ2 computes all the eigenvalues of the symmetric positive definite tridiagonal matrix assoc iated with the qd Array Z to high relative accuracy. Used by sbdsqr and sstegr. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLASQ2 + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLASQ2( N, Z, INFO ) INTEGER INFO, N DOUBLE PRECISION Z( * ) > \par Purpose: ============= > > \verbatim > > DLASQ2 computes all the eigenvalues of the symmetric positive > definite tridiagonal matrix associated with the qd array Z to high > relative accuracy are computed to high relative accuracy, in the > absence of denormalization, underflow and overflow. > > To see the relation of Z to the tridiagonal matrix, let L be a > unit lower bidiagonal matrix with subdiagonals Z(2,4,6,,..) and > let U be an upper bidiagonal matrix with 1's above and diagonal > Z(1,3,5,,..). The tridiagonal is L*U or, if you prefer, the > symmetric tridiagonal to which it is similar. > > Note : DLASQ2 defines a logical variable, IEEE, which is true > on machines which follow ieee-754 floating-point standard in their > handling of infinities and NaNs, and false otherwise. This variable > is passed to DLASQ3. > \endverbatim Arguments: ========== > \param[in] N > \verbatim > N is INTEGER > The number of rows and columns in the matrix. N >= 0. > \endverbatim > > \param[in,out] Z > \verbatim > Z is DOUBLE PRECISION array, dimension ( 4*N ) > On entry Z holds the qd array. On exit, entries 1 to N hold > the eigenvalues in decreasing order, Z( 2*N+1 ) holds the > trace, and Z( 2*N+2 ) holds the sum of the eigenvalues. If > N > 2, then Z( 2*N+3 ) holds the iteration count, Z( 2*N+4 ) > holds NDIVS/NIN^2, and Z( 2*N+5 ) holds the percentage of > shifts that failed. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if the i-th argument is a scalar and had an illegal > value, then INFO = -i, if the i-th argument is an > array and the j-entry had an illegal value, then > INFO = -(i*100+j) > > 0: the algorithm failed > = 1, a split was marked by a positive value in E > = 2, current block of Z not diagonalized after 100*N > iterations (in inner while loop). On exit Z holds > a qd array with the same eigenvalues as the given Z. > = 3, termination criterion of outer while loop not met > (program created more than N unreduced blocks) > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERcomputational > \par Further Details: ===================== > > \verbatim > > Local Variables: I0:N0 defines a current unreduced segment of Z. > The shifts are accumulated in SIGMA. Iteration count is in ITER. > Ping-pong is controlled by PP (alternates between 0 and 1). > \endverbatim > ===================================================================== Subroutine */ int igraphdlasq2_(integer *n, doublereal *z__, integer *info) { /* System generated locals */ integer i__1, i__2, i__3; doublereal d__1, d__2; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ doublereal d__, e, g; integer k; doublereal s, t; integer i0, i1, i4, n0, n1; doublereal dn; integer pp; doublereal dn1, dn2, dee, eps, tau, tol; integer ipn4; doublereal tol2; logical ieee; integer nbig; doublereal dmin__, emin, emax; integer kmin, ndiv, iter; doublereal qmin, temp, qmax, zmax; integer splt; doublereal dmin1, dmin2; integer nfail; doublereal desig, trace, sigma; integer iinfo; doublereal tempe, tempq; integer ttype; extern /* Subroutine */ int igraphdlasq3_(integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, integer *, integer *, integer *, logical *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *); extern doublereal igraphdlamch_(char *); doublereal deemin; integer iwhila, iwhilb; doublereal oldemn, safmin; extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); extern integer igraphilaenv_(integer *, char *, char *, integer *, integer *, integer *, integer *, ftnlen, ftnlen); extern /* Subroutine */ int igraphdlasrt_(char *, integer *, doublereal *, integer *); /* -- LAPACK computational routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Test the input arguments. (in case DLASQ2 is not called by DLASQ1) Parameter adjustments */ --z__; /* Function Body */ *info = 0; eps = igraphdlamch_("Precision"); safmin = igraphdlamch_("Safe minimum"); tol = eps * 100.; /* Computing 2nd power */ d__1 = tol; tol2 = d__1 * d__1; if (*n < 0) { *info = -1; igraphxerbla_("DLASQ2", &c__1, (ftnlen)6); return 0; } else if (*n == 0) { return 0; } else if (*n == 1) { /* 1-by-1 case. */ if (z__[1] < 0.) { *info = -201; igraphxerbla_("DLASQ2", &c__2, (ftnlen)6); } return 0; } else if (*n == 2) { /* 2-by-2 case. */ if (z__[2] < 0. || z__[3] < 0.) { *info = -2; igraphxerbla_("DLASQ2", &c__2, (ftnlen)6); return 0; } else if (z__[3] > z__[1]) { d__ = z__[3]; z__[3] = z__[1]; z__[1] = d__; } z__[5] = z__[1] + z__[2] + z__[3]; if (z__[2] > z__[3] * tol2) { t = (z__[1] - z__[3] + z__[2]) * .5; s = z__[3] * (z__[2] / t); if (s <= t) { s = z__[3] * (z__[2] / (t * (sqrt(s / t + 1.) + 1.))); } else { s = z__[3] * (z__[2] / (t + sqrt(t) * sqrt(t + s))); } t = z__[1] + (s + z__[2]); z__[3] *= z__[1] / t; z__[1] = t; } z__[2] = z__[3]; z__[6] = z__[2] + z__[1]; return 0; } /* Check for negative data and compute sums of q's and e's. */ z__[*n * 2] = 0.; emin = z__[2]; qmax = 0.; zmax = 0.; d__ = 0.; e = 0.; i__1 = *n - 1 << 1; for (k = 1; k <= i__1; k += 2) { if (z__[k] < 0.) { *info = -(k + 200); igraphxerbla_("DLASQ2", &c__2, (ftnlen)6); return 0; } else if (z__[k + 1] < 0.) { *info = -(k + 201); igraphxerbla_("DLASQ2", &c__2, (ftnlen)6); return 0; } d__ += z__[k]; e += z__[k + 1]; /* Computing MAX */ d__1 = qmax, d__2 = z__[k]; qmax = max(d__1,d__2); /* Computing MIN */ d__1 = emin, d__2 = z__[k + 1]; emin = min(d__1,d__2); /* Computing MAX */ d__1 = max(qmax,zmax), d__2 = z__[k + 1]; zmax = max(d__1,d__2); /* L10: */ } if (z__[(*n << 1) - 1] < 0.) { *info = -((*n << 1) + 199); igraphxerbla_("DLASQ2", &c__2, (ftnlen)6); return 0; } d__ += z__[(*n << 1) - 1]; /* Computing MAX */ d__1 = qmax, d__2 = z__[(*n << 1) - 1]; qmax = max(d__1,d__2); zmax = max(qmax,zmax); /* Check for diagonality. */ if (e == 0.) { i__1 = *n; for (k = 2; k <= i__1; ++k) { z__[k] = z__[(k << 1) - 1]; /* L20: */ } igraphdlasrt_("D", n, &z__[1], &iinfo); z__[(*n << 1) - 1] = d__; return 0; } trace = d__ + e; /* Check for zero data. */ if (trace == 0.) { z__[(*n << 1) - 1] = 0.; return 0; } /* Check whether the machine is IEEE conformable. */ ieee = igraphilaenv_(&c__10, "DLASQ2", "N", &c__1, &c__2, &c__3, &c__4, (ftnlen) 6, (ftnlen)1) == 1 && igraphilaenv_(&c__11, "DLASQ2", "N", &c__1, &c__2, &c__3, &c__4, (ftnlen)6, (ftnlen)1) == 1; /* Rearrange data for locality: Z=(q1,qq1,e1,ee1,q2,qq2,e2,ee2,...). */ for (k = *n << 1; k >= 2; k += -2) { z__[k * 2] = 0.; z__[(k << 1) - 1] = z__[k]; z__[(k << 1) - 2] = 0.; z__[(k << 1) - 3] = z__[k - 1]; /* L30: */ } i0 = 1; n0 = *n; /* Reverse the qd-array, if warranted. */ if (z__[(i0 << 2) - 3] * 1.5 < z__[(n0 << 2) - 3]) { ipn4 = i0 + n0 << 2; i__1 = i0 + n0 - 1 << 1; for (i4 = i0 << 2; i4 <= i__1; i4 += 4) { temp = z__[i4 - 3]; z__[i4 - 3] = z__[ipn4 - i4 - 3]; z__[ipn4 - i4 - 3] = temp; temp = z__[i4 - 1]; z__[i4 - 1] = z__[ipn4 - i4 - 5]; z__[ipn4 - i4 - 5] = temp; /* L40: */ } } /* Initial split checking via dqd and Li's test. */ pp = 0; for (k = 1; k <= 2; ++k) { d__ = z__[(n0 << 2) + pp - 3]; i__1 = (i0 << 2) + pp; for (i4 = (n0 - 1 << 2) + pp; i4 >= i__1; i4 += -4) { if (z__[i4 - 1] <= tol2 * d__) { z__[i4 - 1] = -0.; d__ = z__[i4 - 3]; } else { d__ = z__[i4 - 3] * (d__ / (d__ + z__[i4 - 1])); } /* L50: */ } /* dqd maps Z to ZZ plus Li's test. */ emin = z__[(i0 << 2) + pp + 1]; d__ = z__[(i0 << 2) + pp - 3]; i__1 = (n0 - 1 << 2) + pp; for (i4 = (i0 << 2) + pp; i4 <= i__1; i4 += 4) { z__[i4 - (pp << 1) - 2] = d__ + z__[i4 - 1]; if (z__[i4 - 1] <= tol2 * d__) { z__[i4 - 1] = -0.; z__[i4 - (pp << 1) - 2] = d__; z__[i4 - (pp << 1)] = 0.; d__ = z__[i4 + 1]; } else if (safmin * z__[i4 + 1] < z__[i4 - (pp << 1) - 2] && safmin * z__[i4 - (pp << 1) - 2] < z__[i4 + 1]) { temp = z__[i4 + 1] / z__[i4 - (pp << 1) - 2]; z__[i4 - (pp << 1)] = z__[i4 - 1] * temp; d__ *= temp; } else { z__[i4 - (pp << 1)] = z__[i4 + 1] * (z__[i4 - 1] / z__[i4 - ( pp << 1) - 2]); d__ = z__[i4 + 1] * (d__ / z__[i4 - (pp << 1) - 2]); } /* Computing MIN */ d__1 = emin, d__2 = z__[i4 - (pp << 1)]; emin = min(d__1,d__2); /* L60: */ } z__[(n0 << 2) - pp - 2] = d__; /* Now find qmax. */ qmax = z__[(i0 << 2) - pp - 2]; i__1 = (n0 << 2) - pp - 2; for (i4 = (i0 << 2) - pp + 2; i4 <= i__1; i4 += 4) { /* Computing MAX */ d__1 = qmax, d__2 = z__[i4]; qmax = max(d__1,d__2); /* L70: */ } /* Prepare for the next iteration on K. */ pp = 1 - pp; /* L80: */ } /* Initialise variables to pass to DLASQ3. */ ttype = 0; dmin1 = 0.; dmin2 = 0.; dn = 0.; dn1 = 0.; dn2 = 0.; g = 0.; tau = 0.; iter = 2; nfail = 0; ndiv = n0 - i0 << 1; i__1 = *n + 1; for (iwhila = 1; iwhila <= i__1; ++iwhila) { if (n0 < 1) { goto L170; } /* While array unfinished do E(N0) holds the value of SIGMA when submatrix in I0:N0 splits from the rest of the array, but is negated. */ desig = 0.; if (n0 == *n) { sigma = 0.; } else { sigma = -z__[(n0 << 2) - 1]; } if (sigma < 0.) { *info = 1; return 0; } /* Find last unreduced submatrix's top index I0, find QMAX and EMIN. Find Gershgorin-type bound if Q's much greater than E's. */ emax = 0.; if (n0 > i0) { emin = (d__1 = z__[(n0 << 2) - 5], abs(d__1)); } else { emin = 0.; } qmin = z__[(n0 << 2) - 3]; qmax = qmin; for (i4 = n0 << 2; i4 >= 8; i4 += -4) { if (z__[i4 - 5] <= 0.) { goto L100; } if (qmin >= emax * 4.) { /* Computing MIN */ d__1 = qmin, d__2 = z__[i4 - 3]; qmin = min(d__1,d__2); /* Computing MAX */ d__1 = emax, d__2 = z__[i4 - 5]; emax = max(d__1,d__2); } /* Computing MAX */ d__1 = qmax, d__2 = z__[i4 - 7] + z__[i4 - 5]; qmax = max(d__1,d__2); /* Computing MIN */ d__1 = emin, d__2 = z__[i4 - 5]; emin = min(d__1,d__2); /* L90: */ } i4 = 4; L100: i0 = i4 / 4; pp = 0; if (n0 - i0 > 1) { dee = z__[(i0 << 2) - 3]; deemin = dee; kmin = i0; i__2 = (n0 << 2) - 3; for (i4 = (i0 << 2) + 1; i4 <= i__2; i4 += 4) { dee = z__[i4] * (dee / (dee + z__[i4 - 2])); if (dee <= deemin) { deemin = dee; kmin = (i4 + 3) / 4; } /* L110: */ } if (kmin - i0 << 1 < n0 - kmin && deemin <= z__[(n0 << 2) - 3] * .5) { ipn4 = i0 + n0 << 2; pp = 2; i__2 = i0 + n0 - 1 << 1; for (i4 = i0 << 2; i4 <= i__2; i4 += 4) { temp = z__[i4 - 3]; z__[i4 - 3] = z__[ipn4 - i4 - 3]; z__[ipn4 - i4 - 3] = temp; temp = z__[i4 - 2]; z__[i4 - 2] = z__[ipn4 - i4 - 2]; z__[ipn4 - i4 - 2] = temp; temp = z__[i4 - 1]; z__[i4 - 1] = z__[ipn4 - i4 - 5]; z__[ipn4 - i4 - 5] = temp; temp = z__[i4]; z__[i4] = z__[ipn4 - i4 - 4]; z__[ipn4 - i4 - 4] = temp; /* L120: */ } } } /* Put -(initial shift) into DMIN. Computing MAX */ d__1 = 0., d__2 = qmin - sqrt(qmin) * 2. * sqrt(emax); dmin__ = -max(d__1,d__2); /* Now I0:N0 is unreduced. PP = 0 for ping, PP = 1 for pong. PP = 2 indicates that flipping was applied to the Z array and and that the tests for deflation upon entry in DLASQ3 should not be performed. */ nbig = (n0 - i0 + 1) * 100; i__2 = nbig; for (iwhilb = 1; iwhilb <= i__2; ++iwhilb) { if (i0 > n0) { goto L150; } /* While submatrix unfinished take a good dqds step. */ igraphdlasq3_(&i0, &n0, &z__[1], &pp, &dmin__, &sigma, &desig, &qmax, & nfail, &iter, &ndiv, &ieee, &ttype, &dmin1, &dmin2, &dn, & dn1, &dn2, &g, &tau); pp = 1 - pp; /* When EMIN is very small check for splits. */ if (pp == 0 && n0 - i0 >= 3) { if (z__[n0 * 4] <= tol2 * qmax || z__[(n0 << 2) - 1] <= tol2 * sigma) { splt = i0 - 1; qmax = z__[(i0 << 2) - 3]; emin = z__[(i0 << 2) - 1]; oldemn = z__[i0 * 4]; i__3 = n0 - 3 << 2; for (i4 = i0 << 2; i4 <= i__3; i4 += 4) { if (z__[i4] <= tol2 * z__[i4 - 3] || z__[i4 - 1] <= tol2 * sigma) { z__[i4 - 1] = -sigma; splt = i4 / 4; qmax = 0.; emin = z__[i4 + 3]; oldemn = z__[i4 + 4]; } else { /* Computing MAX */ d__1 = qmax, d__2 = z__[i4 + 1]; qmax = max(d__1,d__2); /* Computing MIN */ d__1 = emin, d__2 = z__[i4 - 1]; emin = min(d__1,d__2); /* Computing MIN */ d__1 = oldemn, d__2 = z__[i4]; oldemn = min(d__1,d__2); } /* L130: */ } z__[(n0 << 2) - 1] = emin; z__[n0 * 4] = oldemn; i0 = splt + 1; } } /* L140: */ } *info = 2; /* Maximum number of iterations exceeded, restore the shift SIGMA and place the new d's and e's in a qd array. This might need to be done for several blocks */ i1 = i0; n1 = n0; L145: tempq = z__[(i0 << 2) - 3]; z__[(i0 << 2) - 3] += sigma; i__2 = n0; for (k = i0 + 1; k <= i__2; ++k) { tempe = z__[(k << 2) - 5]; z__[(k << 2) - 5] *= tempq / z__[(k << 2) - 7]; tempq = z__[(k << 2) - 3]; z__[(k << 2) - 3] = z__[(k << 2) - 3] + sigma + tempe - z__[(k << 2) - 5]; } /* Prepare to do this on the previous block if there is one */ if (i1 > 1) { n1 = i1 - 1; while(i1 >= 2 && z__[(i1 << 2) - 5] >= 0.) { --i1; } sigma = -z__[(n1 << 2) - 1]; goto L145; } i__2 = *n; for (k = 1; k <= i__2; ++k) { z__[(k << 1) - 1] = z__[(k << 2) - 3]; /* Only the block 1..N0 is unfinished. The rest of the e's must be essentially zero, although sometimes other data has been stored in them. */ if (k < n0) { z__[k * 2] = z__[(k << 2) - 1]; } else { z__[k * 2] = 0.; } } return 0; /* end IWHILB */ L150: /* L160: */ ; } *info = 3; return 0; /* end IWHILA */ L170: /* Move q's to the front. */ i__1 = *n; for (k = 2; k <= i__1; ++k) { z__[k] = z__[(k << 2) - 3]; /* L180: */ } /* Sort and compute sum of eigenvalues. */ igraphdlasrt_("D", n, &z__[1], &iinfo); e = 0.; for (k = *n; k >= 1; --k) { e += z__[k]; /* L190: */ } /* Store trace, sum(eigenvalues) and information on performance. */ z__[(*n << 1) + 1] = trace; z__[(*n << 1) + 2] = e; z__[(*n << 1) + 3] = (doublereal) iter; /* Computing 2nd power */ i__1 = *n; z__[(*n << 1) + 4] = (doublereal) ndiv / (doublereal) (i__1 * i__1); z__[(*n << 1) + 5] = nfail * 100. / (doublereal) iter; return 0; /* End of DLASQ2 */ } /* igraphdlasq2_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dnaup2.c0000644000076500000240000010567313524616145024211 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static doublereal c_b3 = .66666666666666663; static integer c__1 = 1; static integer c__0 = 0; static integer c__4 = 4; static logical c_true = TRUE_; static integer c__2 = 2; /* \BeginDoc \Name: dnaup2 \Description: Intermediate level interface called by dnaupd. \Usage: call dnaup2 ( IDO, BMAT, N, WHICH, NEV, NP, TOL, RESID, MODE, IUPD, ISHIFT, MXITER, V, LDV, H, LDH, RITZR, RITZI, BOUNDS, Q, LDQ, WORKL, IPNTR, WORKD, INFO ) \Arguments IDO, BMAT, N, WHICH, NEV, TOL, RESID: same as defined in dnaupd. MODE, ISHIFT, MXITER: see the definition of IPARAM in dnaupd. NP Integer. (INPUT/OUTPUT) Contains the number of implicit shifts to apply during each Arnoldi iteration. If ISHIFT=1, NP is adjusted dynamically at each iteration to accelerate convergence and prevent stagnation. This is also roughly equal to the number of matrix-vector products (involving the operator OP) per Arnoldi iteration. The logic for adjusting is contained within the current subroutine. If ISHIFT=0, NP is the number of shifts the user needs to provide via reverse comunication. 0 < NP < NCV-NEV. NP may be less than NCV-NEV for two reasons. The first, is to keep complex conjugate pairs of "wanted" Ritz values together. The second, is that a leading block of the current upper Hessenberg matrix has split off and contains "unwanted" Ritz values. Upon termination of the IRA iteration, NP contains the number of "converged" wanted Ritz values. IUPD Integer. (INPUT) IUPD .EQ. 0: use explicit restart instead implicit update. IUPD .NE. 0: use implicit update. V Double precision N by (NEV+NP) array. (INPUT/OUTPUT) The Arnoldi basis vectors are returned in the first NEV columns of V. LDV Integer. (INPUT) Leading dimension of V exactly as declared in the calling program. H Double precision (NEV+NP) by (NEV+NP) array. (OUTPUT) H is used to store the generated upper Hessenberg matrix LDH Integer. (INPUT) Leading dimension of H exactly as declared in the calling program. RITZR, Double precision arrays of length NEV+NP. (OUTPUT) RITZI RITZR(1:NEV) (resp. RITZI(1:NEV)) contains the real (resp. imaginary) part of the computed Ritz values of OP. BOUNDS Double precision array of length NEV+NP. (OUTPUT) BOUNDS(1:NEV) contain the error bounds corresponding to the computed Ritz values. Q Double precision (NEV+NP) by (NEV+NP) array. (WORKSPACE) Private (replicated) work array used to accumulate the rotation in the shift application step. LDQ Integer. (INPUT) Leading dimension of Q exactly as declared in the calling program. WORKL Double precision work array of length at least (NEV+NP)**2 + 3*(NEV+NP). (INPUT/WORKSPACE) Private (replicated) array on each PE or array allocated on the front end. It is used in shifts calculation, shifts application and convergence checking. On exit, the last 3*(NEV+NP) locations of WORKL contain the Ritz values (real,imaginary) and associated Ritz estimates of the current Hessenberg matrix. They are listed in the same order as returned from dneigh. If ISHIFT .EQ. O and IDO .EQ. 3, the first 2*NP locations of WORKL are used in reverse communication to hold the user supplied shifts. IPNTR Integer array of length 3. (OUTPUT) Pointer to mark the starting locations in the WORKD for vectors used by the Arnoldi iteration. ------------------------------------------------------------- IPNTR(1): pointer to the current operand vector X. IPNTR(2): pointer to the current result vector Y. IPNTR(3): pointer to the vector B * X when used in the shift-and-invert mode. X is the current operand. ------------------------------------------------------------- WORKD Double precision work array of length 3*N. (WORKSPACE) Distributed array to be used in the basic Arnoldi iteration for reverse communication. The user should not use WORKD as temporary workspace during the iteration !!!!!!!!!! See Data Distribution Note in DNAUPD. INFO Integer. (INPUT/OUTPUT) If INFO .EQ. 0, a randomly initial residual vector is used. If INFO .NE. 0, RESID contains the initial residual vector, possibly from a previous run. Error flag on output. = 0: Normal return. = 1: Maximum number of iterations taken. All possible eigenvalues of OP has been found. NP returns the number of converged Ritz values. = 2: No shifts could be applied. = -8: Error return from LAPACK eigenvalue calculation; This should never happen. = -9: Starting vector is zero. = -9999: Could not build an Arnoldi factorization. Size that was built in returned in NP. \EndDoc ----------------------------------------------------------------------- \BeginLib \Local variables: xxxxxx real \References: 1. D.C. Sorensen, "Implicit Application of Polynomial Filters in a k-Step Arnoldi Method", SIAM J. Matr. Anal. Apps., 13 (1992), pp 357-385. 2. R.B. Lehoucq, "Analysis and Implementation of an Implicitly Restarted Arnoldi Iteration", Rice University Technical Report TR95-13, Department of Computational and Applied Mathematics. \Routines called: dgetv0 ARPACK initial vector generation routine. dnaitr ARPACK Arnoldi factorization routine. dnapps ARPACK application of implicit shifts routine. dnconv ARPACK convergence of Ritz values routine. dneigh ARPACK compute Ritz values and error bounds routine. dngets ARPACK reorder Ritz values and error bounds routine. dsortc ARPACK sorting routine. ivout ARPACK utility routine that prints integers. second ARPACK utility routine for timing. dmout ARPACK utility routine that prints matrices dvout ARPACK utility routine that prints vectors. dlamch LAPACK routine that determines machine constants. dlapy2 LAPACK routine to compute sqrt(x**2+y**2) carefully. dcopy Level 1 BLAS that copies one vector to another . ddot Level 1 BLAS that computes the scalar product of two vectors. dnrm2 Level 1 BLAS that computes the norm of a vector. dswap Level 1 BLAS that swaps two vectors. \Author Danny Sorensen Phuong Vu Richard Lehoucq CRPC / Rice University Dept. of Computational & Houston, Texas Applied Mathematics Rice University Houston, Texas \SCCS Information: @(#) FILE: naup2.F SID: 2.4 DATE OF SID: 7/30/96 RELEASE: 2 \Remarks 1. None \EndLib ----------------------------------------------------------------------- Subroutine */ int igraphdnaup2_(integer *ido, char *bmat, integer *n, char * which, integer *nev, integer *np, doublereal *tol, doublereal *resid, integer *mode, integer *iupd, integer *ishift, integer *mxiter, doublereal *v, integer *ldv, doublereal *h__, integer *ldh, doublereal *ritzr, doublereal *ritzi, doublereal *bounds, doublereal * q, integer *ldq, doublereal *workl, integer *ipntr, doublereal *workd, integer *info) { /* System generated locals */ integer h_dim1, h_offset, q_dim1, q_offset, v_dim1, v_offset, i__1, i__2; doublereal d__1, d__2; /* Builtin functions */ double pow_dd(doublereal *, doublereal *); integer s_cmp(char *, char *, ftnlen, ftnlen); /* Subroutine */ int s_copy(char *, char *, ftnlen, ftnlen); double sqrt(doublereal); /* Local variables */ IGRAPH_F77_SAVE integer j; IGRAPH_F77_SAVE real t0, t1, t2, t3; IGRAPH_F77_SAVE integer kp[4], np0, nbx, nev0; extern doublereal igraphddot_(integer *, doublereal *, integer *, doublereal *, integer *); IGRAPH_F77_SAVE doublereal eps23; IGRAPH_F77_SAVE integer ierr, iter; IGRAPH_F77_SAVE doublereal temp; extern doublereal igraphdnrm2_(integer *, doublereal *, integer *); IGRAPH_F77_SAVE logical getv0, cnorm; extern /* Subroutine */ int igraphdcopy_(integer *, doublereal *, integer *, doublereal *, integer *); IGRAPH_F77_SAVE integer nconv; extern /* Subroutine */ int igraphdmout_(integer *, integer *, integer *, doublereal *, integer *, integer *, char *, ftnlen); IGRAPH_F77_SAVE logical initv; IGRAPH_F77_SAVE doublereal rnorm; IGRAPH_F77_SAVE real tmvbx; extern /* Subroutine */ int igraphdvout_(integer *, integer *, doublereal *, integer *, char *, ftnlen), igraphivout_(integer *, integer *, integer * , integer *, char *, ftnlen), igraphdgetv0_(integer *, char *, integer * , logical *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *); extern doublereal igraphdlapy2_(doublereal *, doublereal *); IGRAPH_F77_SAVE integer mnaup2; IGRAPH_F77_SAVE real tnaup2; extern doublereal igraphdlamch_(char *); extern /* Subroutine */ int igraphdneigh_(doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, doublereal * , integer *, doublereal *, integer *); IGRAPH_F77_SAVE integer nevbef; extern /* Subroutine */ int igraphsecond_(real *); IGRAPH_F77_SAVE integer logfil, ndigit; extern /* Subroutine */ int igraphdnaitr_(integer *, char *, integer *, integer *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *, doublereal *, integer *, integer *, doublereal *, integer *); IGRAPH_F77_SAVE logical update; extern /* Subroutine */ int igraphdngets_(integer *, char *, integer *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *), igraphdnapps_(integer *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *, doublereal *), igraphdnconv_(integer *, doublereal *, doublereal *, doublereal *, doublereal *, integer *), igraphdsortc_(char *, logical *, integer *, doublereal *, doublereal *, doublereal *); IGRAPH_F77_SAVE logical ushift; IGRAPH_F77_SAVE char wprime[2]; IGRAPH_F77_SAVE integer msglvl, nptemp, numcnv, kplusp; /* %----------------------------------------------------% | Include files for debugging and timing information | %----------------------------------------------------% %------------------% | Scalar Arguments | %------------------% %-----------------% | Array Arguments | %-----------------% %------------% | Parameters | %------------% %---------------% | Local Scalars | %---------------% %-----------------------% | Local array arguments | %-----------------------% %----------------------% | External Subroutines | %----------------------% %--------------------% | External Functions | %--------------------% %---------------------% | Intrinsic Functions | %---------------------% %-----------------------% | Executable Statements | %-----------------------% Parameter adjustments */ --workd; --resid; --workl; --bounds; --ritzi; --ritzr; v_dim1 = *ldv; v_offset = 1 + v_dim1; v -= v_offset; h_dim1 = *ldh; h_offset = 1 + h_dim1; h__ -= h_offset; q_dim1 = *ldq; q_offset = 1 + q_dim1; q -= q_offset; --ipntr; /* Function Body */ if (*ido == 0) { igraphsecond_(&t0); msglvl = mnaup2; /* %-------------------------------------% | Get the machine dependent constant. | %-------------------------------------% */ eps23 = igraphdlamch_("Epsilon-Machine"); eps23 = pow_dd(&eps23, &c_b3); nev0 = *nev; np0 = *np; /* %-------------------------------------% | kplusp is the bound on the largest | | Lanczos factorization built. | | nconv is the current number of | | "converged" eigenvlues. | | iter is the counter on the current | | iteration step. | %-------------------------------------% */ kplusp = *nev + *np; nconv = 0; iter = 0; /* %---------------------------------------% | Set flags for computing the first NEV | | steps of the Arnoldi factorization. | %---------------------------------------% */ getv0 = TRUE_; update = FALSE_; ushift = FALSE_; cnorm = FALSE_; if (*info != 0) { /* %--------------------------------------------% | User provides the initial residual vector. | %--------------------------------------------% */ initv = TRUE_; *info = 0; } else { initv = FALSE_; } } /* %---------------------------------------------% | Get a possibly random starting vector and | | force it into the range of the operator OP. | %---------------------------------------------% L10: */ if (getv0) { igraphdgetv0_(ido, bmat, &c__1, &initv, n, &c__1, &v[v_offset], ldv, &resid[ 1], &rnorm, &ipntr[1], &workd[1], info); if (*ido != 99) { goto L9000; } if (rnorm == 0.) { /* %-----------------------------------------% | The initial vector is zero. Error exit. | %-----------------------------------------% */ *info = -9; goto L1100; } getv0 = FALSE_; *ido = 0; } /* %-----------------------------------% | Back from reverse communication : | | continue with update step | %-----------------------------------% */ if (update) { goto L20; } /* %-------------------------------------------% | Back from computing user specified shifts | %-------------------------------------------% */ if (ushift) { goto L50; } /* %-------------------------------------% | Back from computing residual norm | | at the end of the current iteration | %-------------------------------------% */ if (cnorm) { goto L100; } /* %----------------------------------------------------------% | Compute the first NEV steps of the Arnoldi factorization | %----------------------------------------------------------% */ igraphdnaitr_(ido, bmat, n, &c__0, nev, mode, &resid[1], &rnorm, &v[v_offset], ldv, &h__[h_offset], ldh, &ipntr[1], &workd[1], info); /* %---------------------------------------------------% | ido .ne. 99 implies use of reverse communication | | to compute operations involving OP and possibly B | %---------------------------------------------------% */ if (*ido != 99) { goto L9000; } if (*info > 0) { *np = *info; *mxiter = iter; *info = -9999; goto L1200; } /* %--------------------------------------------------------------% | | | M A I N ARNOLDI I T E R A T I O N L O O P | | Each iteration implicitly restarts the Arnoldi | | factorization in place. | | | %--------------------------------------------------------------% */ L1000: ++iter; if (msglvl > 0) { igraphivout_(&logfil, &c__1, &iter, &ndigit, "_naup2: **** Start of major " "iteration number ****", (ftnlen)49); } /* %-----------------------------------------------------------% | Compute NP additional steps of the Arnoldi factorization. | | Adjust NP since NEV might have been updated by last call | | to the shift application routine dnapps. | %-----------------------------------------------------------% */ *np = kplusp - *nev; if (msglvl > 1) { igraphivout_(&logfil, &c__1, nev, &ndigit, "_naup2: The length of the curr" "ent Arnoldi factorization", (ftnlen)55); igraphivout_(&logfil, &c__1, np, &ndigit, "_naup2: Extend the Arnoldi fact" "orization by", (ftnlen)43); } /* %-----------------------------------------------------------% | Compute NP additional steps of the Arnoldi factorization. | %-----------------------------------------------------------% */ *ido = 0; L20: update = TRUE_; igraphdnaitr_(ido, bmat, n, nev, np, mode, &resid[1], &rnorm, &v[v_offset], ldv, &h__[h_offset], ldh, &ipntr[1], &workd[1], info); /* %---------------------------------------------------% | ido .ne. 99 implies use of reverse communication | | to compute operations involving OP and possibly B | %---------------------------------------------------% */ if (*ido != 99) { goto L9000; } if (*info > 0) { *np = *info; *mxiter = iter; *info = -9999; goto L1200; } update = FALSE_; if (msglvl > 1) { igraphdvout_(&logfil, &c__1, &rnorm, &ndigit, "_naup2: Corresponding B-nor" "m of the residual", (ftnlen)44); } /* %--------------------------------------------------------% | Compute the eigenvalues and corresponding error bounds | | of the current upper Hessenberg matrix. | %--------------------------------------------------------% */ igraphdneigh_(&rnorm, &kplusp, &h__[h_offset], ldh, &ritzr[1], &ritzi[1], & bounds[1], &q[q_offset], ldq, &workl[1], &ierr); if (ierr != 0) { *info = -8; goto L1200; } /* %----------------------------------------------------% | Make a copy of eigenvalues and corresponding error | | bounds obtained from dneigh. | %----------------------------------------------------% Computing 2nd power */ i__1 = kplusp; igraphdcopy_(&kplusp, &ritzr[1], &c__1, &workl[i__1 * i__1 + 1], &c__1); /* Computing 2nd power */ i__1 = kplusp; igraphdcopy_(&kplusp, &ritzi[1], &c__1, &workl[i__1 * i__1 + kplusp + 1], &c__1) ; /* Computing 2nd power */ i__1 = kplusp; igraphdcopy_(&kplusp, &bounds[1], &c__1, &workl[i__1 * i__1 + (kplusp << 1) + 1] , &c__1); /* %---------------------------------------------------% | Select the wanted Ritz values and their bounds | | to be used in the convergence test. | | The wanted part of the spectrum and corresponding | | error bounds are in the last NEV loc. of RITZR, | | RITZI and BOUNDS respectively. The variables NEV | | and NP may be updated if the NEV-th wanted Ritz | | value has a non zero imaginary part. In this case | | NEV is increased by one and NP decreased by one. | | NOTE: The last two arguments of dngets are no | | longer used as of version 2.1. | %---------------------------------------------------% */ *nev = nev0; *np = np0; numcnv = *nev; igraphdngets_(ishift, which, nev, np, &ritzr[1], &ritzi[1], &bounds[1], &workl[ 1], &workl[*np + 1]); if (*nev == nev0 + 1) { numcnv = nev0 + 1; } /* %-------------------% | Convergence test. | %-------------------% */ igraphdcopy_(nev, &bounds[*np + 1], &c__1, &workl[(*np << 1) + 1], &c__1); igraphdnconv_(nev, &ritzr[*np + 1], &ritzi[*np + 1], &workl[(*np << 1) + 1], tol, &nconv); if (msglvl > 2) { kp[0] = *nev; kp[1] = *np; kp[2] = numcnv; kp[3] = nconv; igraphivout_(&logfil, &c__4, kp, &ndigit, "_naup2: NEV, NP, NUMCNV, NCONV " "are", (ftnlen)34); igraphdvout_(&logfil, &kplusp, &ritzr[1], &ndigit, "_naup2: Real part of t" "he eigenvalues of H", (ftnlen)41); igraphdvout_(&logfil, &kplusp, &ritzi[1], &ndigit, "_naup2: Imaginary part" " of the eigenvalues of H", (ftnlen)46); igraphdvout_(&logfil, &kplusp, &bounds[1], &ndigit, "_naup2: Ritz estimate" "s of the current NCV Ritz values", (ftnlen)53); } /* %---------------------------------------------------------% | Count the number of unwanted Ritz values that have zero | | Ritz estimates. If any Ritz estimates are equal to zero | | then a leading block of H of order equal to at least | | the number of Ritz values with zero Ritz estimates has | | split off. None of these Ritz values may be removed by | | shifting. Decrease NP the number of shifts to apply. If | | no shifts may be applied, then prepare to exit | %---------------------------------------------------------% */ nptemp = *np; i__1 = nptemp; for (j = 1; j <= i__1; ++j) { if (bounds[j] == 0.) { --(*np); ++(*nev); } /* L30: */ } if (nconv >= numcnv || iter > *mxiter || *np == 0) { if (msglvl > 4) { /* Computing 2nd power */ i__1 = kplusp; igraphdvout_(&logfil, &kplusp, &workl[i__1 * i__1 + 1], &ndigit, "_nau" "p2: Real part of the eig computed by _neigh:", (ftnlen)48) ; /* Computing 2nd power */ i__1 = kplusp; igraphdvout_(&logfil, &kplusp, &workl[i__1 * i__1 + kplusp + 1], & ndigit, "_naup2: Imag part of the eig computed by _neigh:" , (ftnlen)48); /* Computing 2nd power */ i__1 = kplusp; igraphdvout_(&logfil, &kplusp, &workl[i__1 * i__1 + (kplusp << 1) + 1], &ndigit, "_naup2: Ritz eistmates computed by _neigh:", ( ftnlen)42); } /* %------------------------------------------------% | Prepare to exit. Put the converged Ritz values | | and corresponding bounds in RITZ(1:NCONV) and | | BOUNDS(1:NCONV) respectively. Then sort. Be | | careful when NCONV > NP | %------------------------------------------------% %------------------------------------------% | Use h( 3,1 ) as storage to communicate | | rnorm to _neupd if needed | %------------------------------------------% */ h__[h_dim1 + 3] = rnorm; /* %----------------------------------------------% | To be consistent with dngets, we first do a | | pre-processing sort in order to keep complex | | conjugate pairs together. This is similar | | to the pre-processing sort used in dngets | | except that the sort is done in the opposite | | order. | %----------------------------------------------% */ if (s_cmp(which, "LM", (ftnlen)2, (ftnlen)2) == 0) { s_copy(wprime, "SR", (ftnlen)2, (ftnlen)2); } if (s_cmp(which, "SM", (ftnlen)2, (ftnlen)2) == 0) { s_copy(wprime, "LR", (ftnlen)2, (ftnlen)2); } if (s_cmp(which, "LR", (ftnlen)2, (ftnlen)2) == 0) { s_copy(wprime, "SM", (ftnlen)2, (ftnlen)2); } if (s_cmp(which, "SR", (ftnlen)2, (ftnlen)2) == 0) { s_copy(wprime, "LM", (ftnlen)2, (ftnlen)2); } if (s_cmp(which, "LI", (ftnlen)2, (ftnlen)2) == 0) { s_copy(wprime, "SM", (ftnlen)2, (ftnlen)2); } if (s_cmp(which, "SI", (ftnlen)2, (ftnlen)2) == 0) { s_copy(wprime, "LM", (ftnlen)2, (ftnlen)2); } igraphdsortc_(wprime, &c_true, &kplusp, &ritzr[1], &ritzi[1], &bounds[1]); /* %----------------------------------------------% | Now sort Ritz values so that converged Ritz | | values appear within the first NEV locations | | of ritzr, ritzi and bounds, and the most | | desired one appears at the front. | %----------------------------------------------% */ if (s_cmp(which, "LM", (ftnlen)2, (ftnlen)2) == 0) { s_copy(wprime, "SM", (ftnlen)2, (ftnlen)2); } if (s_cmp(which, "SM", (ftnlen)2, (ftnlen)2) == 0) { s_copy(wprime, "LM", (ftnlen)2, (ftnlen)2); } if (s_cmp(which, "LR", (ftnlen)2, (ftnlen)2) == 0) { s_copy(wprime, "SR", (ftnlen)2, (ftnlen)2); } if (s_cmp(which, "SR", (ftnlen)2, (ftnlen)2) == 0) { s_copy(wprime, "LR", (ftnlen)2, (ftnlen)2); } if (s_cmp(which, "LI", (ftnlen)2, (ftnlen)2) == 0) { s_copy(wprime, "SI", (ftnlen)2, (ftnlen)2); } if (s_cmp(which, "SI", (ftnlen)2, (ftnlen)2) == 0) { s_copy(wprime, "LI", (ftnlen)2, (ftnlen)2); } igraphdsortc_(wprime, &c_true, &kplusp, &ritzr[1], &ritzi[1], &bounds[1]); /* %--------------------------------------------------% | Scale the Ritz estimate of each Ritz value | | by 1 / max(eps23,magnitude of the Ritz value). | %--------------------------------------------------% */ i__1 = nev0; for (j = 1; j <= i__1; ++j) { /* Computing MAX */ d__1 = eps23, d__2 = igraphdlapy2_(&ritzr[j], &ritzi[j]); temp = max(d__1,d__2); bounds[j] /= temp; /* L35: */ } /* %----------------------------------------------------% | Sort the Ritz values according to the scaled Ritz | | esitmates. This will push all the converged ones | | towards the front of ritzr, ritzi, bounds | | (in the case when NCONV < NEV.) | %----------------------------------------------------% */ s_copy(wprime, "LR", (ftnlen)2, (ftnlen)2); igraphdsortc_(wprime, &c_true, &nev0, &bounds[1], &ritzr[1], &ritzi[1]); /* %----------------------------------------------% | Scale the Ritz estimate back to its original | | value. | %----------------------------------------------% */ i__1 = nev0; for (j = 1; j <= i__1; ++j) { /* Computing MAX */ d__1 = eps23, d__2 = igraphdlapy2_(&ritzr[j], &ritzi[j]); temp = max(d__1,d__2); bounds[j] *= temp; /* L40: */ } /* %------------------------------------------------% | Sort the converged Ritz values again so that | | the "threshold" value appears at the front of | | ritzr, ritzi and bound. | %------------------------------------------------% */ igraphdsortc_(which, &c_true, &nconv, &ritzr[1], &ritzi[1], &bounds[1]); if (msglvl > 1) { igraphdvout_(&logfil, &kplusp, &ritzr[1], &ndigit, "_naup2: Sorted rea" "l part of the eigenvalues", (ftnlen)43); igraphdvout_(&logfil, &kplusp, &ritzi[1], &ndigit, "_naup2: Sorted ima" "ginary part of the eigenvalues", (ftnlen)48); igraphdvout_(&logfil, &kplusp, &bounds[1], &ndigit, "_naup2: Sorted ri" "tz estimates.", (ftnlen)30); } /* %------------------------------------% | Max iterations have been exceeded. | %------------------------------------% */ if (iter > *mxiter && nconv < numcnv) { *info = 1; } /* %---------------------% | No shifts to apply. | %---------------------% */ if (*np == 0 && nconv < numcnv) { *info = 2; } *np = nconv; goto L1100; } else if (nconv < numcnv && *ishift == 1) { /* %-------------------------------------------------% | Do not have all the requested eigenvalues yet. | | To prevent possible stagnation, adjust the size | | of NEV. | %-------------------------------------------------% */ nevbef = *nev; /* Computing MIN */ i__1 = nconv, i__2 = *np / 2; *nev += min(i__1,i__2); if (*nev == 1 && kplusp >= 6) { *nev = kplusp / 2; } else if (*nev == 1 && kplusp > 3) { *nev = 2; } *np = kplusp - *nev; /* %---------------------------------------% | If the size of NEV was just increased | | resort the eigenvalues. | %---------------------------------------% */ if (nevbef < *nev) { igraphdngets_(ishift, which, nev, np, &ritzr[1], &ritzi[1], &bounds[1], &workl[1], &workl[*np + 1]); } } if (msglvl > 0) { igraphivout_(&logfil, &c__1, &nconv, &ndigit, "_naup2: no. of \"converge" "d\" Ritz values at this iter.", (ftnlen)52); if (msglvl > 1) { kp[0] = *nev; kp[1] = *np; igraphivout_(&logfil, &c__2, kp, &ndigit, "_naup2: NEV and NP are", ( ftnlen)22); igraphdvout_(&logfil, nev, &ritzr[*np + 1], &ndigit, "_naup2: \"wante" "d\" Ritz values -- real part", (ftnlen)41); igraphdvout_(&logfil, nev, &ritzi[*np + 1], &ndigit, "_naup2: \"wante" "d\" Ritz values -- imag part", (ftnlen)41); igraphdvout_(&logfil, nev, &bounds[*np + 1], &ndigit, "_naup2: Ritz es" "timates of the \"wanted\" values ", (ftnlen)46); } } if (*ishift == 0) { /* %-------------------------------------------------------% | User specified shifts: reverse comminucation to | | compute the shifts. They are returned in the first | | 2*NP locations of WORKL. | %-------------------------------------------------------% */ ushift = TRUE_; *ido = 3; goto L9000; } L50: /* %------------------------------------% | Back from reverse communication; | | User specified shifts are returned | | in WORKL(1:2*NP) | %------------------------------------% */ ushift = FALSE_; if (*ishift == 0) { /* %----------------------------------% | Move the NP shifts from WORKL to | | RITZR, RITZI to free up WORKL | | for non-exact shift case. | %----------------------------------% */ igraphdcopy_(np, &workl[1], &c__1, &ritzr[1], &c__1); igraphdcopy_(np, &workl[*np + 1], &c__1, &ritzi[1], &c__1); } if (msglvl > 2) { igraphivout_(&logfil, &c__1, np, &ndigit, "_naup2: The number of shifts to" " apply ", (ftnlen)38); igraphdvout_(&logfil, np, &ritzr[1], &ndigit, "_naup2: Real part of the sh" "ifts", (ftnlen)31); igraphdvout_(&logfil, np, &ritzi[1], &ndigit, "_naup2: Imaginary part of t" "he shifts", (ftnlen)36); if (*ishift == 1) { igraphdvout_(&logfil, np, &bounds[1], &ndigit, "_naup2: Ritz estimates" " of the shifts", (ftnlen)36); } } /* %---------------------------------------------------------% | Apply the NP implicit shifts by QR bulge chasing. | | Each shift is applied to the whole upper Hessenberg | | matrix H. | | The first 2*N locations of WORKD are used as workspace. | %---------------------------------------------------------% */ igraphdnapps_(n, nev, np, &ritzr[1], &ritzi[1], &v[v_offset], ldv, &h__[ h_offset], ldh, &resid[1], &q[q_offset], ldq, &workl[1], &workd[1] ); /* %---------------------------------------------% | Compute the B-norm of the updated residual. | | Keep B*RESID in WORKD(1:N) to be used in | | the first step of the next call to dnaitr. | %---------------------------------------------% */ cnorm = TRUE_; igraphsecond_(&t2); if (*(unsigned char *)bmat == 'G') { ++nbx; igraphdcopy_(n, &resid[1], &c__1, &workd[*n + 1], &c__1); ipntr[1] = *n + 1; ipntr[2] = 1; *ido = 2; /* %----------------------------------% | Exit in order to compute B*RESID | %----------------------------------% */ goto L9000; } else if (*(unsigned char *)bmat == 'I') { igraphdcopy_(n, &resid[1], &c__1, &workd[1], &c__1); } L100: /* %----------------------------------% | Back from reverse communication; | | WORKD(1:N) := B*RESID | %----------------------------------% */ if (*(unsigned char *)bmat == 'G') { igraphsecond_(&t3); tmvbx += t3 - t2; } if (*(unsigned char *)bmat == 'G') { rnorm = igraphddot_(n, &resid[1], &c__1, &workd[1], &c__1); rnorm = sqrt((abs(rnorm))); } else if (*(unsigned char *)bmat == 'I') { rnorm = igraphdnrm2_(n, &resid[1], &c__1); } cnorm = FALSE_; if (msglvl > 2) { igraphdvout_(&logfil, &c__1, &rnorm, &ndigit, "_naup2: B-norm of residual " "for compressed factorization", (ftnlen)55); igraphdmout_(&logfil, nev, nev, &h__[h_offset], ldh, &ndigit, "_naup2: Com" "pressed upper Hessenberg matrix H", (ftnlen)44); } goto L1000; /* %---------------------------------------------------------------% | | | E N D O F M A I N I T E R A T I O N L O O P | | | %---------------------------------------------------------------% */ L1100: *mxiter = iter; *nev = numcnv; L1200: *ido = 99; /* %------------% | Error Exit | %------------% */ igraphsecond_(&t1); tnaup2 = t1 - t0; L9000: /* %---------------% | End of dnaup2 | %---------------% */ return 0; } /* igraphdnaup2_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dseigt.c0000644000076500000240000001475713524616145024301 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; /* ----------------------------------------------------------------------- \BeginDoc \Name: dseigt \Description: Compute the eigenvalues of the current symmetric tridiagonal matrix and the corresponding error bounds given the current residual norm. \Usage: call dseigt ( RNORM, N, H, LDH, EIG, BOUNDS, WORKL, IERR ) \Arguments RNORM Double precision scalar. (INPUT) RNORM contains the residual norm corresponding to the current symmetric tridiagonal matrix H. N Integer. (INPUT) Size of the symmetric tridiagonal matrix H. H Double precision N by 2 array. (INPUT) H contains the symmetric tridiagonal matrix with the subdiagonal in the first column starting at H(2,1) and the main diagonal in second column. LDH Integer. (INPUT) Leading dimension of H exactly as declared in the calling program. EIG Double precision array of length N. (OUTPUT) On output, EIG contains the N eigenvalues of H possibly unsorted. The BOUNDS arrays are returned in the same sorted order as EIG. BOUNDS Double precision array of length N. (OUTPUT) On output, BOUNDS contains the error estimates corresponding to the eigenvalues EIG. This is equal to RNORM times the last components of the eigenvectors corresponding to the eigenvalues in EIG. WORKL Double precision work array of length 3*N. (WORKSPACE) Private (replicated) array on each PE or array allocated on the front end. IERR Integer. (OUTPUT) Error exit flag from dstqrb. \EndDoc ----------------------------------------------------------------------- \BeginLib \Local variables: xxxxxx real \Routines called: dstqrb ARPACK routine that computes the eigenvalues and the last components of the eigenvectors of a symmetric and tridiagonal matrix. second ARPACK utility routine for timing. dvout ARPACK utility routine that prints vectors. dcopy Level 1 BLAS that copies one vector to another. \Author Danny Sorensen Phuong Vu Richard Lehoucq CRPC / Rice University Dept. of Computational & Houston, Texas Applied Mathematics Rice University Houston, Texas \Revision history: xx/xx/92: Version ' 2.4' \SCCS Information: @(#) FILE: seigt.F SID: 2.4 DATE OF SID: 8/27/96 RELEASE: 2 \Remarks None \EndLib ----------------------------------------------------------------------- Subroutine */ int igraphdseigt_(doublereal *rnorm, integer *n, doublereal *h__, integer *ldh, doublereal *eig, doublereal *bounds, doublereal *workl, integer *ierr) { /* System generated locals */ integer h_dim1, h_offset, i__1; doublereal d__1; /* Local variables */ integer k; real t0, t1; extern /* Subroutine */ int igraphdcopy_(integer *, doublereal *, integer *, doublereal *, integer *), igraphdvout_(integer *, integer *, doublereal *, integer *, char *, ftnlen), igraphsecond_(real *); integer logfil, ndigit, mseigt = 0; extern /* Subroutine */ int igraphdstqrb_(integer *, doublereal *, doublereal *, doublereal *, doublereal *, integer *); real tseigt = 0.0; integer msglvl; /* %----------------------------------------------------% | Include files for debugging and timing information | %----------------------------------------------------% %------------------% | Scalar Arguments | %------------------% %-----------------% | Array Arguments | %-----------------% %------------% | Parameters | %------------% %---------------% | Local Scalars | %---------------% %----------------------% | External Subroutines | %----------------------% %-----------------------% | Executable Statements | %-----------------------% %-------------------------------% | Initialize timing statistics | | & message level for debugging | %-------------------------------% Parameter adjustments */ --workl; --bounds; --eig; h_dim1 = *ldh; h_offset = 1 + h_dim1; h__ -= h_offset; /* Function Body */ igraphsecond_(&t0); msglvl = mseigt; if (msglvl > 0) { igraphdvout_(&logfil, n, &h__[(h_dim1 << 1) + 1], &ndigit, "_seigt: main d" "iagonal of matrix H", (ftnlen)33); if (*n > 1) { i__1 = *n - 1; igraphdvout_(&logfil, &i__1, &h__[h_dim1 + 2], &ndigit, "_seigt: sub d" "iagonal of matrix H", (ftnlen)32); } } igraphdcopy_(n, &h__[(h_dim1 << 1) + 1], &c__1, &eig[1], &c__1); i__1 = *n - 1; igraphdcopy_(&i__1, &h__[h_dim1 + 2], &c__1, &workl[1], &c__1); igraphdstqrb_(n, &eig[1], &workl[1], &bounds[1], &workl[*n + 1], ierr); if (*ierr != 0) { goto L9000; } if (msglvl > 1) { igraphdvout_(&logfil, n, &bounds[1], &ndigit, "_seigt: last row of the eig" "envector matrix for H", (ftnlen)48); } /* %-----------------------------------------------% | Finally determine the error bounds associated | | with the n Ritz values of H. | %-----------------------------------------------% */ i__1 = *n; for (k = 1; k <= i__1; ++k) { bounds[k] = *rnorm * (d__1 = bounds[k], abs(d__1)); /* L30: */ } igraphsecond_(&t1); tseigt += t1 - t0; L9000: return 0; /* %---------------% | End of dseigt | %---------------% */ } /* igraphdseigt_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlanst.c0000644000076500000240000001376713524616145024307 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; /* > \brief \b DLANST returns the value of the 1-norm, or the Frobenius norm, or the infinity norm, or the ele ment of largest absolute value of a real symmetric tridiagonal matrix. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLANST + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== DOUBLE PRECISION FUNCTION DLANST( NORM, N, D, E ) CHARACTER NORM INTEGER N DOUBLE PRECISION D( * ), E( * ) > \par Purpose: ============= > > \verbatim > > DLANST returns the value of the one norm, or the Frobenius norm, or > the infinity norm, or the element of largest absolute value of a > real symmetric tridiagonal matrix A. > \endverbatim > > \return DLANST > \verbatim > > DLANST = ( max(abs(A(i,j))), NORM = 'M' or 'm' > ( > ( norm1(A), NORM = '1', 'O' or 'o' > ( > ( normI(A), NORM = 'I' or 'i' > ( > ( normF(A), NORM = 'F', 'f', 'E' or 'e' > > where norm1 denotes the one norm of a matrix (maximum column sum), > normI denotes the infinity norm of a matrix (maximum row sum) and > normF denotes the Frobenius norm of a matrix (square root of sum of > squares). Note that max(abs(A(i,j))) is not a consistent matrix norm. > \endverbatim Arguments: ========== > \param[in] NORM > \verbatim > NORM is CHARACTER*1 > Specifies the value to be returned in DLANST as described > above. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix A. N >= 0. When N = 0, DLANST is > set to zero. > \endverbatim > > \param[in] D > \verbatim > D is DOUBLE PRECISION array, dimension (N) > The diagonal elements of A. > \endverbatim > > \param[in] E > \verbatim > E is DOUBLE PRECISION array, dimension (N-1) > The (n-1) sub-diagonal or super-diagonal elements of A. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERauxiliary ===================================================================== */ doublereal igraphdlanst_(char *norm, integer *n, doublereal *d__, doublereal *e) { /* System generated locals */ integer i__1; doublereal ret_val, d__1, d__2, d__3; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ integer i__; doublereal sum, scale; extern logical igraphlsame_(char *, char *); doublereal anorm = 0.; extern logical igraphdisnan_(doublereal *); extern /* Subroutine */ int igraphdlassq_(integer *, doublereal *, integer *, doublereal *, doublereal *); /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ --e; --d__; /* Function Body */ if (*n <= 0) { anorm = 0.; } else if (igraphlsame_(norm, "M")) { /* Find max(abs(A(i,j))). */ anorm = (d__1 = d__[*n], abs(d__1)); i__1 = *n - 1; for (i__ = 1; i__ <= i__1; ++i__) { sum = (d__1 = d__[i__], abs(d__1)); if (anorm < sum || igraphdisnan_(&sum)) { anorm = sum; } sum = (d__1 = e[i__], abs(d__1)); if (anorm < sum || igraphdisnan_(&sum)) { anorm = sum; } /* L10: */ } } else if (igraphlsame_(norm, "O") || *(unsigned char *) norm == '1' || igraphlsame_(norm, "I")) { /* Find norm1(A). */ if (*n == 1) { anorm = abs(d__[1]); } else { anorm = abs(d__[1]) + abs(e[1]); sum = (d__1 = e[*n - 1], abs(d__1)) + (d__2 = d__[*n], abs(d__2)); if (anorm < sum || igraphdisnan_(&sum)) { anorm = sum; } i__1 = *n - 1; for (i__ = 2; i__ <= i__1; ++i__) { sum = (d__1 = d__[i__], abs(d__1)) + (d__2 = e[i__], abs(d__2) ) + (d__3 = e[i__ - 1], abs(d__3)); if (anorm < sum || igraphdisnan_(&sum)) { anorm = sum; } /* L20: */ } } } else if (igraphlsame_(norm, "F") || igraphlsame_(norm, "E")) { /* Find normF(A). */ scale = 0.; sum = 1.; if (*n > 1) { i__1 = *n - 1; igraphdlassq_(&i__1, &e[1], &c__1, &scale, &sum); sum *= 2; } igraphdlassq_(n, &d__[1], &c__1, &scale, &sum); anorm = scale * sqrt(sum); } ret_val = anorm; return ret_val; /* End of DLANST */ } /* igraphdlanst_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dnrm2.c0000644000076500000240000000406413524616145024032 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" doublereal igraphdnrm2_(integer *n, doublereal *x, integer *incx) { /* System generated locals */ integer i__1, i__2; doublereal ret_val, d__1; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ integer ix; doublereal ssq, norm, scale, absxi; /* Purpose ======= DNRM2 returns the euclidean norm of a vector via the function name, so that DNRM2 := sqrt( x'*x ) Further Details =============== -- This version written on 25-October-1982. Modified on 14-October-1993 to inline the call to DLASSQ. Sven Hammarling, Nag Ltd. ===================================================================== Parameter adjustments */ --x; /* Function Body */ if (*n < 1 || *incx < 1) { norm = 0.; } else if (*n == 1) { norm = abs(x[1]); } else { scale = 0.; ssq = 1.; /* The following loop is equivalent to this call to the LAPACK auxiliary routine: CALL DLASSQ( N, X, INCX, SCALE, SSQ ) */ i__1 = (*n - 1) * *incx + 1; i__2 = *incx; for (ix = 1; i__2 < 0 ? ix >= i__1 : ix <= i__1; ix += i__2) { if (x[ix] != 0.) { absxi = (d__1 = x[ix], abs(d__1)); if (scale < absxi) { /* Computing 2nd power */ d__1 = scale / absxi; ssq = ssq * (d__1 * d__1) + 1.; scale = absxi; } else { /* Computing 2nd power */ d__1 = absxi / scale; ssq += d__1 * d__1; } } /* L10: */ } norm = scale * sqrt(ssq); } ret_val = norm; return ret_val; /* End of DNRM2. */ } /* igraphdnrm2_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dasum.c0000644000076500000240000000421313524616145024115 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" doublereal igraphdasum_(integer *n, doublereal *dx, integer *incx) { /* System generated locals */ integer i__1, i__2; doublereal ret_val, d__1, d__2, d__3, d__4, d__5, d__6; /* Local variables */ integer i__, m, mp1; doublereal dtemp; integer nincx; /* Purpose ======= DASUM takes the sum of the absolute values. Further Details =============== jack dongarra, linpack, 3/11/78. modified 3/93 to return if incx .le. 0. modified 12/3/93, array(1) declarations changed to array(*) ===================================================================== Parameter adjustments */ --dx; /* Function Body */ ret_val = 0.; dtemp = 0.; if (*n <= 0 || *incx <= 0) { return ret_val; } if (*incx == 1) { /* code for increment equal to 1 clean-up loop */ m = *n % 6; if (m != 0) { i__1 = m; for (i__ = 1; i__ <= i__1; ++i__) { dtemp += (d__1 = dx[i__], abs(d__1)); } if (*n < 6) { ret_val = dtemp; return ret_val; } } mp1 = m + 1; i__1 = *n; for (i__ = mp1; i__ <= i__1; i__ += 6) { dtemp = dtemp + (d__1 = dx[i__], abs(d__1)) + (d__2 = dx[i__ + 1], abs(d__2)) + (d__3 = dx[i__ + 2], abs(d__3)) + (d__4 = dx[i__ + 3], abs(d__4)) + (d__5 = dx[i__ + 4], abs(d__5)) + (d__6 = dx[i__ + 5], abs(d__6)); } } else { /* code for increment not equal to 1 */ nincx = *n * *incx; i__1 = nincx; i__2 = *incx; for (i__ = 1; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ += i__2) { dtemp += (d__1 = dx[i__], abs(d__1)); } } ret_val = dtemp; return ret_val; } /* igraphdasum_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dscal.c0000644000076500000240000000371413524616145024077 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Subroutine */ int igraphdscal_(integer *n, doublereal *da, doublereal *dx, integer *incx) { /* System generated locals */ integer i__1, i__2; /* Local variables */ integer i__, m, mp1, nincx; /* Purpose ======= DSCAL scales a vector by a constant. uses unrolled loops for increment equal to one. Further Details =============== jack dongarra, linpack, 3/11/78. modified 3/93 to return if incx .le. 0. modified 12/3/93, array(1) declarations changed to array(*) ===================================================================== Parameter adjustments */ --dx; /* Function Body */ if (*n <= 0 || *incx <= 0) { return 0; } if (*incx == 1) { /* code for increment equal to 1 clean-up loop */ m = *n % 5; if (m != 0) { i__1 = m; for (i__ = 1; i__ <= i__1; ++i__) { dx[i__] = *da * dx[i__]; } if (*n < 5) { return 0; } } mp1 = m + 1; i__1 = *n; for (i__ = mp1; i__ <= i__1; i__ += 5) { dx[i__] = *da * dx[i__]; dx[i__ + 1] = *da * dx[i__ + 1]; dx[i__ + 2] = *da * dx[i__ + 2]; dx[i__ + 3] = *da * dx[i__ + 3]; dx[i__ + 4] = *da * dx[i__ + 4]; } } else { /* code for increment not equal to 1 */ nincx = *n * *incx; i__1 = nincx; i__2 = *incx; for (i__ = 1; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ += i__2) { dx[i__] = *da * dx[i__]; } } return 0; } /* igraphdscal_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dorm2l.c0000644000076500000240000002031413524616145024203 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; /* > \brief \b DORM2L multiplies a general matrix by the orthogonal matrix from a QL factorization determined by sgeqlf (unblocked algorithm). =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DORM2L + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DORM2L( SIDE, TRANS, M, N, K, A, LDA, TAU, C, LDC, WORK, INFO ) CHARACTER SIDE, TRANS INTEGER INFO, K, LDA, LDC, M, N DOUBLE PRECISION A( LDA, * ), C( LDC, * ), TAU( * ), WORK( * ) > \par Purpose: ============= > > \verbatim > > DORM2L overwrites the general real m by n matrix C with > > Q * C if SIDE = 'L' and TRANS = 'N', or > > Q**T * C if SIDE = 'L' and TRANS = 'T', or > > C * Q if SIDE = 'R' and TRANS = 'N', or > > C * Q**T if SIDE = 'R' and TRANS = 'T', > > where Q is a real orthogonal matrix defined as the product of k > elementary reflectors > > Q = H(k) . . . H(2) H(1) > > as returned by DGEQLF. Q is of order m if SIDE = 'L' and of order n > if SIDE = 'R'. > \endverbatim Arguments: ========== > \param[in] SIDE > \verbatim > SIDE is CHARACTER*1 > = 'L': apply Q or Q**T from the Left > = 'R': apply Q or Q**T from the Right > \endverbatim > > \param[in] TRANS > \verbatim > TRANS is CHARACTER*1 > = 'N': apply Q (No transpose) > = 'T': apply Q**T (Transpose) > \endverbatim > > \param[in] M > \verbatim > M is INTEGER > The number of rows of the matrix C. M >= 0. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The number of columns of the matrix C. N >= 0. > \endverbatim > > \param[in] K > \verbatim > K is INTEGER > The number of elementary reflectors whose product defines > the matrix Q. > If SIDE = 'L', M >= K >= 0; > if SIDE = 'R', N >= K >= 0. > \endverbatim > > \param[in] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,K) > The i-th column must contain the vector which defines the > elementary reflector H(i), for i = 1,2,...,k, as returned by > DGEQLF in the last k columns of its array argument A. > A is modified by the routine but restored on exit. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. > If SIDE = 'L', LDA >= max(1,M); > if SIDE = 'R', LDA >= max(1,N). > \endverbatim > > \param[in] TAU > \verbatim > TAU is DOUBLE PRECISION array, dimension (K) > TAU(i) must contain the scalar factor of the elementary > reflector H(i), as returned by DGEQLF. > \endverbatim > > \param[in,out] C > \verbatim > C is DOUBLE PRECISION array, dimension (LDC,N) > On entry, the m by n matrix C. > On exit, C is overwritten by Q*C or Q**T*C or C*Q**T or C*Q. > \endverbatim > > \param[in] LDC > \verbatim > LDC is INTEGER > The leading dimension of the array C. LDC >= max(1,M). > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension > (N) if SIDE = 'L', > (M) if SIDE = 'R' > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleOTHERcomputational ===================================================================== Subroutine */ int igraphdorm2l_(char *side, char *trans, integer *m, integer *n, integer *k, doublereal *a, integer *lda, doublereal *tau, doublereal * c__, integer *ldc, doublereal *work, integer *info) { /* System generated locals */ integer a_dim1, a_offset, c_dim1, c_offset, i__1, i__2; /* Local variables */ integer i__, i1, i2, i3, mi, ni, nq; doublereal aii; logical left; extern /* Subroutine */ int igraphdlarf_(char *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *); extern logical igraphlsame_(char *, char *); extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); logical notran; /* -- LAPACK computational routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Test the input arguments Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --tau; c_dim1 = *ldc; c_offset = 1 + c_dim1; c__ -= c_offset; --work; /* Function Body */ *info = 0; left = igraphlsame_(side, "L"); notran = igraphlsame_(trans, "N"); /* NQ is the order of Q */ if (left) { nq = *m; } else { nq = *n; } if (! left && ! igraphlsame_(side, "R")) { *info = -1; } else if (! notran && ! igraphlsame_(trans, "T")) { *info = -2; } else if (*m < 0) { *info = -3; } else if (*n < 0) { *info = -4; } else if (*k < 0 || *k > nq) { *info = -5; } else if (*lda < max(1,nq)) { *info = -7; } else if (*ldc < max(1,*m)) { *info = -10; } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DORM2L", &i__1, (ftnlen)6); return 0; } /* Quick return if possible */ if (*m == 0 || *n == 0 || *k == 0) { return 0; } if (left && notran || ! left && ! notran) { i1 = 1; i2 = *k; i3 = 1; } else { i1 = *k; i2 = 1; i3 = -1; } if (left) { ni = *n; } else { mi = *m; } i__1 = i2; i__2 = i3; for (i__ = i1; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ += i__2) { if (left) { /* H(i) is applied to C(1:m-k+i,1:n) */ mi = *m - *k + i__; } else { /* H(i) is applied to C(1:m,1:n-k+i) */ ni = *n - *k + i__; } /* Apply H(i) */ aii = a[nq - *k + i__ + i__ * a_dim1]; a[nq - *k + i__ + i__ * a_dim1] = 1.; igraphdlarf_(side, &mi, &ni, &a[i__ * a_dim1 + 1], &c__1, &tau[i__], &c__[ c_offset], ldc, &work[1]); a[nq - *k + i__ + i__ * a_dim1] = aii; /* L10: */ } return 0; /* End of DORM2L */ } /* igraphdorm2l_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dormhr.c0000644000076500000240000002372613524616145024311 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static integer c_n1 = -1; static integer c__2 = 2; /* > \brief \b DORMHR =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DORMHR + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DORMHR( SIDE, TRANS, M, N, ILO, IHI, A, LDA, TAU, C, LDC, WORK, LWORK, INFO ) CHARACTER SIDE, TRANS INTEGER IHI, ILO, INFO, LDA, LDC, LWORK, M, N DOUBLE PRECISION A( LDA, * ), C( LDC, * ), TAU( * ), WORK( * ) > \par Purpose: ============= > > \verbatim > > DORMHR overwrites the general real M-by-N matrix C with > > SIDE = 'L' SIDE = 'R' > TRANS = 'N': Q * C C * Q > TRANS = 'T': Q**T * C C * Q**T > > where Q is a real orthogonal matrix of order nq, with nq = m if > SIDE = 'L' and nq = n if SIDE = 'R'. Q is defined as the product of > IHI-ILO elementary reflectors, as returned by DGEHRD: > > Q = H(ilo) H(ilo+1) . . . H(ihi-1). > \endverbatim Arguments: ========== > \param[in] SIDE > \verbatim > SIDE is CHARACTER*1 > = 'L': apply Q or Q**T from the Left; > = 'R': apply Q or Q**T from the Right. > \endverbatim > > \param[in] TRANS > \verbatim > TRANS is CHARACTER*1 > = 'N': No transpose, apply Q; > = 'T': Transpose, apply Q**T. > \endverbatim > > \param[in] M > \verbatim > M is INTEGER > The number of rows of the matrix C. M >= 0. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The number of columns of the matrix C. N >= 0. > \endverbatim > > \param[in] ILO > \verbatim > ILO is INTEGER > \endverbatim > > \param[in] IHI > \verbatim > IHI is INTEGER > > ILO and IHI must have the same values as in the previous call > of DGEHRD. Q is equal to the unit matrix except in the > submatrix Q(ilo+1:ihi,ilo+1:ihi). > If SIDE = 'L', then 1 <= ILO <= IHI <= M, if M > 0, and > ILO = 1 and IHI = 0, if M = 0; > if SIDE = 'R', then 1 <= ILO <= IHI <= N, if N > 0, and > ILO = 1 and IHI = 0, if N = 0. > \endverbatim > > \param[in] A > \verbatim > A is DOUBLE PRECISION array, dimension > (LDA,M) if SIDE = 'L' > (LDA,N) if SIDE = 'R' > The vectors which define the elementary reflectors, as > returned by DGEHRD. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. > LDA >= max(1,M) if SIDE = 'L'; LDA >= max(1,N) if SIDE = 'R'. > \endverbatim > > \param[in] TAU > \verbatim > TAU is DOUBLE PRECISION array, dimension > (M-1) if SIDE = 'L' > (N-1) if SIDE = 'R' > TAU(i) must contain the scalar factor of the elementary > reflector H(i), as returned by DGEHRD. > \endverbatim > > \param[in,out] C > \verbatim > C is DOUBLE PRECISION array, dimension (LDC,N) > On entry, the M-by-N matrix C. > On exit, C is overwritten by Q*C or Q**T*C or C*Q**T or C*Q. > \endverbatim > > \param[in] LDC > \verbatim > LDC is INTEGER > The leading dimension of the array C. LDC >= max(1,M). > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (MAX(1,LWORK)) > On exit, if INFO = 0, WORK(1) returns the optimal LWORK. > \endverbatim > > \param[in] LWORK > \verbatim > LWORK is INTEGER > The dimension of the array WORK. > If SIDE = 'L', LWORK >= max(1,N); > if SIDE = 'R', LWORK >= max(1,M). > For optimum performance LWORK >= N*NB if SIDE = 'L', and > LWORK >= M*NB if SIDE = 'R', where NB is the optimal > blocksize. > > If LWORK = -1, then a workspace query is assumed; the routine > only calculates the optimal size of the WORK array, returns > this value as the first entry of the WORK array, and no error > message related to LWORK is issued by XERBLA. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2011 > \ingroup doubleOTHERcomputational ===================================================================== Subroutine */ int igraphdormhr_(char *side, char *trans, integer *m, integer *n, integer *ilo, integer *ihi, doublereal *a, integer *lda, doublereal * tau, doublereal *c__, integer *ldc, doublereal *work, integer *lwork, integer *info) { /* System generated locals */ address a__1[2]; integer a_dim1, a_offset, c_dim1, c_offset, i__1[2], i__2; char ch__1[2]; /* Builtin functions Subroutine */ int s_cat(char *, char **, integer *, integer *, ftnlen); /* Local variables */ integer i1, i2, nb, mi, nh, ni, nq, nw; logical left; extern logical igraphlsame_(char *, char *); integer iinfo; extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); extern integer igraphilaenv_(integer *, char *, char *, integer *, integer *, integer *, integer *, ftnlen, ftnlen); extern /* Subroutine */ int igraphdormqr_(char *, char *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, integer *); integer lwkopt; logical lquery; /* -- LAPACK computational routine (version 3.4.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2011 ===================================================================== Test the input arguments Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --tau; c_dim1 = *ldc; c_offset = 1 + c_dim1; c__ -= c_offset; --work; /* Function Body */ *info = 0; nh = *ihi - *ilo; left = igraphlsame_(side, "L"); lquery = *lwork == -1; /* NQ is the order of Q and NW is the minimum dimension of WORK */ if (left) { nq = *m; nw = *n; } else { nq = *n; nw = *m; } if (! left && ! igraphlsame_(side, "R")) { *info = -1; } else if (! igraphlsame_(trans, "N") && ! igraphlsame_(trans, "T")) { *info = -2; } else if (*m < 0) { *info = -3; } else if (*n < 0) { *info = -4; } else if (*ilo < 1 || *ilo > max(1,nq)) { *info = -5; } else if (*ihi < min(*ilo,nq) || *ihi > nq) { *info = -6; } else if (*lda < max(1,nq)) { *info = -8; } else if (*ldc < max(1,*m)) { *info = -11; } else if (*lwork < max(1,nw) && ! lquery) { *info = -13; } if (*info == 0) { if (left) { /* Writing concatenation */ i__1[0] = 1, a__1[0] = side; i__1[1] = 1, a__1[1] = trans; s_cat(ch__1, a__1, i__1, &c__2, (ftnlen)2); nb = igraphilaenv_(&c__1, "DORMQR", ch__1, &nh, n, &nh, &c_n1, (ftnlen) 6, (ftnlen)2); } else { /* Writing concatenation */ i__1[0] = 1, a__1[0] = side; i__1[1] = 1, a__1[1] = trans; s_cat(ch__1, a__1, i__1, &c__2, (ftnlen)2); nb = igraphilaenv_(&c__1, "DORMQR", ch__1, m, &nh, &nh, &c_n1, (ftnlen) 6, (ftnlen)2); } lwkopt = max(1,nw) * nb; work[1] = (doublereal) lwkopt; } if (*info != 0) { i__2 = -(*info); igraphxerbla_("DORMHR", &i__2, (ftnlen)6); return 0; } else if (lquery) { return 0; } /* Quick return if possible */ if (*m == 0 || *n == 0 || nh == 0) { work[1] = 1.; return 0; } if (left) { mi = nh; ni = *n; i1 = *ilo + 1; i2 = 1; } else { mi = *m; ni = nh; i1 = 1; i2 = *ilo + 1; } igraphdormqr_(side, trans, &mi, &ni, &nh, &a[*ilo + 1 + *ilo * a_dim1], lda, & tau[*ilo], &c__[i1 + i2 * c_dim1], ldc, &work[1], lwork, &iinfo); work[1] = (doublereal) lwkopt; return 0; /* End of DORMHR */ } /* igraphdormhr_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dgeevx.c0000644000076500000240000006675113524616145024305 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static integer c__0 = 0; static integer c_n1 = -1; /* > \brief DGEEVX computes the eigenvalues and, optionally, the left and/or right eigenvectors for GE mat rices =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DGEEVX + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DGEEVX( BALANC, JOBVL, JOBVR, SENSE, N, A, LDA, WR, WI, VL, LDVL, VR, LDVR, ILO, IHI, SCALE, ABNRM, RCONDE, RCONDV, WORK, LWORK, IWORK, INFO ) CHARACTER BALANC, JOBVL, JOBVR, SENSE INTEGER IHI, ILO, INFO, LDA, LDVL, LDVR, LWORK, N DOUBLE PRECISION ABNRM INTEGER IWORK( * ) DOUBLE PRECISION A( LDA, * ), RCONDE( * ), RCONDV( * ), $ SCALE( * ), VL( LDVL, * ), VR( LDVR, * ), $ WI( * ), WORK( * ), WR( * ) > \par Purpose: ============= > > \verbatim > > DGEEVX computes for an N-by-N real nonsymmetric matrix A, the > eigenvalues and, optionally, the left and/or right eigenvectors. > > Optionally also, it computes a balancing transformation to improve > the conditioning of the eigenvalues and eigenvectors (ILO, IHI, > SCALE, and ABNRM), reciprocal condition numbers for the eigenvalues > (RCONDE), and reciprocal condition numbers for the right > eigenvectors (RCONDV). > > The right eigenvector v(j) of A satisfies > A * v(j) = lambda(j) * v(j) > where lambda(j) is its eigenvalue. > The left eigenvector u(j) of A satisfies > u(j)**H * A = lambda(j) * u(j)**H > where u(j)**H denotes the conjugate-transpose of u(j). > > The computed eigenvectors are normalized to have Euclidean norm > equal to 1 and largest component real. > > Balancing a matrix means permuting the rows and columns to make it > more nearly upper triangular, and applying a diagonal similarity > transformation D * A * D**(-1), where D is a diagonal matrix, to > make its rows and columns closer in norm and the condition numbers > of its eigenvalues and eigenvectors smaller. The computed > reciprocal condition numbers correspond to the balanced matrix. > Permuting rows and columns will not change the condition numbers > (in exact arithmetic) but diagonal scaling will. For further > explanation of balancing, see section 4.10.2 of the LAPACK > Users' Guide. > \endverbatim Arguments: ========== > \param[in] BALANC > \verbatim > BALANC is CHARACTER*1 > Indicates how the input matrix should be diagonally scaled > and/or permuted to improve the conditioning of its > eigenvalues. > = 'N': Do not diagonally scale or permute; > = 'P': Perform permutations to make the matrix more nearly > upper triangular. Do not diagonally scale; > = 'S': Diagonally scale the matrix, i.e. replace A by > D*A*D**(-1), where D is a diagonal matrix chosen > to make the rows and columns of A more equal in > norm. Do not permute; > = 'B': Both diagonally scale and permute A. > > Computed reciprocal condition numbers will be for the matrix > after balancing and/or permuting. Permuting does not change > condition numbers (in exact arithmetic), but balancing does. > \endverbatim > > \param[in] JOBVL > \verbatim > JOBVL is CHARACTER*1 > = 'N': left eigenvectors of A are not computed; > = 'V': left eigenvectors of A are computed. > If SENSE = 'E' or 'B', JOBVL must = 'V'. > \endverbatim > > \param[in] JOBVR > \verbatim > JOBVR is CHARACTER*1 > = 'N': right eigenvectors of A are not computed; > = 'V': right eigenvectors of A are computed. > If SENSE = 'E' or 'B', JOBVR must = 'V'. > \endverbatim > > \param[in] SENSE > \verbatim > SENSE is CHARACTER*1 > Determines which reciprocal condition numbers are computed. > = 'N': None are computed; > = 'E': Computed for eigenvalues only; > = 'V': Computed for right eigenvectors only; > = 'B': Computed for eigenvalues and right eigenvectors. > > If SENSE = 'E' or 'B', both left and right eigenvectors > must also be computed (JOBVL = 'V' and JOBVR = 'V'). > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix A. N >= 0. > \endverbatim > > \param[in,out] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,N) > On entry, the N-by-N matrix A. > On exit, A has been overwritten. If JOBVL = 'V' or > JOBVR = 'V', A contains the real Schur form of the balanced > version of the input matrix A. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. LDA >= max(1,N). > \endverbatim > > \param[out] WR > \verbatim > WR is DOUBLE PRECISION array, dimension (N) > \endverbatim > > \param[out] WI > \verbatim > WI is DOUBLE PRECISION array, dimension (N) > WR and WI contain the real and imaginary parts, > respectively, of the computed eigenvalues. Complex > conjugate pairs of eigenvalues will appear consecutively > with the eigenvalue having the positive imaginary part > first. > \endverbatim > > \param[out] VL > \verbatim > VL is DOUBLE PRECISION array, dimension (LDVL,N) > If JOBVL = 'V', the left eigenvectors u(j) are stored one > after another in the columns of VL, in the same order > as their eigenvalues. > If JOBVL = 'N', VL is not referenced. > If the j-th eigenvalue is real, then u(j) = VL(:,j), > the j-th column of VL. > If the j-th and (j+1)-st eigenvalues form a complex > conjugate pair, then u(j) = VL(:,j) + i*VL(:,j+1) and > u(j+1) = VL(:,j) - i*VL(:,j+1). > \endverbatim > > \param[in] LDVL > \verbatim > LDVL is INTEGER > The leading dimension of the array VL. LDVL >= 1; if > JOBVL = 'V', LDVL >= N. > \endverbatim > > \param[out] VR > \verbatim > VR is DOUBLE PRECISION array, dimension (LDVR,N) > If JOBVR = 'V', the right eigenvectors v(j) are stored one > after another in the columns of VR, in the same order > as their eigenvalues. > If JOBVR = 'N', VR is not referenced. > If the j-th eigenvalue is real, then v(j) = VR(:,j), > the j-th column of VR. > If the j-th and (j+1)-st eigenvalues form a complex > conjugate pair, then v(j) = VR(:,j) + i*VR(:,j+1) and > v(j+1) = VR(:,j) - i*VR(:,j+1). > \endverbatim > > \param[in] LDVR > \verbatim > LDVR is INTEGER > The leading dimension of the array VR. LDVR >= 1, and if > JOBVR = 'V', LDVR >= N. > \endverbatim > > \param[out] ILO > \verbatim > ILO is INTEGER > \endverbatim > > \param[out] IHI > \verbatim > IHI is INTEGER > ILO and IHI are integer values determined when A was > balanced. The balanced A(i,j) = 0 if I > J and > J = 1,...,ILO-1 or I = IHI+1,...,N. > \endverbatim > > \param[out] SCALE > \verbatim > SCALE is DOUBLE PRECISION array, dimension (N) > Details of the permutations and scaling factors applied > when balancing A. If P(j) is the index of the row and column > interchanged with row and column j, and D(j) is the scaling > factor applied to row and column j, then > SCALE(J) = P(J), for J = 1,...,ILO-1 > = D(J), for J = ILO,...,IHI > = P(J) for J = IHI+1,...,N. > The order in which the interchanges are made is N to IHI+1, > then 1 to ILO-1. > \endverbatim > > \param[out] ABNRM > \verbatim > ABNRM is DOUBLE PRECISION > The one-norm of the balanced matrix (the maximum > of the sum of absolute values of elements of any column). > \endverbatim > > \param[out] RCONDE > \verbatim > RCONDE is DOUBLE PRECISION array, dimension (N) > RCONDE(j) is the reciprocal condition number of the j-th > eigenvalue. > \endverbatim > > \param[out] RCONDV > \verbatim > RCONDV is DOUBLE PRECISION array, dimension (N) > RCONDV(j) is the reciprocal condition number of the j-th > right eigenvector. > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (MAX(1,LWORK)) > On exit, if INFO = 0, WORK(1) returns the optimal LWORK. > \endverbatim > > \param[in] LWORK > \verbatim > LWORK is INTEGER > The dimension of the array WORK. If SENSE = 'N' or 'E', > LWORK >= max(1,2*N), and if JOBVL = 'V' or JOBVR = 'V', > LWORK >= 3*N. If SENSE = 'V' or 'B', LWORK >= N*(N+6). > For good performance, LWORK must generally be larger. > > If LWORK = -1, then a workspace query is assumed; the routine > only calculates the optimal size of the WORK array, returns > this value as the first entry of the WORK array, and no error > message related to LWORK is issued by XERBLA. > \endverbatim > > \param[out] IWORK > \verbatim > IWORK is INTEGER array, dimension (2*N-2) > If SENSE = 'N' or 'E', not referenced. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value. > > 0: if INFO = i, the QR algorithm failed to compute all the > eigenvalues, and no eigenvectors or condition numbers > have been computed; elements 1:ILO-1 and i+1:N of WR > and WI contain eigenvalues which have converged. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleGEeigen ===================================================================== Subroutine */ int igraphdgeevx_(char *balanc, char *jobvl, char *jobvr, char * sense, integer *n, doublereal *a, integer *lda, doublereal *wr, doublereal *wi, doublereal *vl, integer *ldvl, doublereal *vr, integer *ldvr, integer *ilo, integer *ihi, doublereal *scale, doublereal *abnrm, doublereal *rconde, doublereal *rcondv, doublereal *work, integer *lwork, integer *iwork, integer *info) { /* System generated locals */ integer a_dim1, a_offset, vl_dim1, vl_offset, vr_dim1, vr_offset, i__1, i__2, i__3; doublereal d__1, d__2; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ integer i__, k; doublereal r__, cs, sn; char job[1]; doublereal scl, dum[1], eps; char side[1]; doublereal anrm; integer ierr, itau; extern /* Subroutine */ int igraphdrot_(integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *); integer iwrk, nout; extern doublereal igraphdnrm2_(integer *, doublereal *, integer *); extern /* Subroutine */ int igraphdscal_(integer *, doublereal *, doublereal *, integer *); integer icond; extern logical igraphlsame_(char *, char *); extern doublereal igraphdlapy2_(doublereal *, doublereal *); extern /* Subroutine */ int igraphdlabad_(doublereal *, doublereal *), igraphdgebak_( char *, char *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, integer *, integer *), igraphdgebal_(char *, integer *, doublereal *, integer *, integer *, integer *, doublereal *, integer *); logical scalea; extern doublereal igraphdlamch_(char *); doublereal cscale; extern doublereal igraphdlange_(char *, integer *, integer *, doublereal *, integer *, doublereal *); extern /* Subroutine */ int igraphdgehrd_(integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, integer *), igraphdlascl_(char *, integer *, integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, integer *, integer *); extern integer igraphidamax_(integer *, doublereal *, integer *); extern /* Subroutine */ int igraphdlacpy_(char *, integer *, integer *, doublereal *, integer *, doublereal *, integer *), igraphdlartg_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *), igraphxerbla_(char *, integer *, ftnlen); logical select[1]; extern integer igraphilaenv_(integer *, char *, char *, integer *, integer *, integer *, integer *, ftnlen, ftnlen); doublereal bignum; extern /* Subroutine */ int igraphdorghr_(integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, integer *), igraphdhseqr_(char *, char *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, integer *, doublereal *, integer *, integer *), igraphdtrevc_(char *, char *, logical *, integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, integer *, integer *, integer *, doublereal *, integer *), igraphdtrsna_(char *, char *, logical *, integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, integer *, integer *, integer *); integer minwrk, maxwrk; logical wantvl, wntsnb; integer hswork; logical wntsne; doublereal smlnum; logical lquery, wantvr, wntsnn, wntsnv; /* -- LAPACK driver routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Test the input arguments Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --wr; --wi; vl_dim1 = *ldvl; vl_offset = 1 + vl_dim1; vl -= vl_offset; vr_dim1 = *ldvr; vr_offset = 1 + vr_dim1; vr -= vr_offset; --scale; --rconde; --rcondv; --work; --iwork; /* Function Body */ *info = 0; lquery = *lwork == -1; wantvl = igraphlsame_(jobvl, "V"); wantvr = igraphlsame_(jobvr, "V"); wntsnn = igraphlsame_(sense, "N"); wntsne = igraphlsame_(sense, "E"); wntsnv = igraphlsame_(sense, "V"); wntsnb = igraphlsame_(sense, "B"); if (! (igraphlsame_(balanc, "N") || igraphlsame_(balanc, "S") || igraphlsame_(balanc, "P") || igraphlsame_(balanc, "B"))) { *info = -1; } else if (! wantvl && ! igraphlsame_(jobvl, "N")) { *info = -2; } else if (! wantvr && ! igraphlsame_(jobvr, "N")) { *info = -3; } else if (! (wntsnn || wntsne || wntsnb || wntsnv) || (wntsne || wntsnb) && ! (wantvl && wantvr)) { *info = -4; } else if (*n < 0) { *info = -5; } else if (*lda < max(1,*n)) { *info = -7; } else if (*ldvl < 1 || wantvl && *ldvl < *n) { *info = -11; } else if (*ldvr < 1 || wantvr && *ldvr < *n) { *info = -13; } /* Compute workspace (Note: Comments in the code beginning "Workspace:" describe the minimal amount of workspace needed at that point in the code, as well as the preferred amount for good performance. NB refers to the optimal block size for the immediately following subroutine, as returned by ILAENV. HSWORK refers to the workspace preferred by DHSEQR, as calculated below. HSWORK is computed assuming ILO=1 and IHI=N, the worst case.) */ if (*info == 0) { if (*n == 0) { minwrk = 1; maxwrk = 1; } else { maxwrk = *n + *n * igraphilaenv_(&c__1, "DGEHRD", " ", n, &c__1, n, & c__0, (ftnlen)6, (ftnlen)1); if (wantvl) { igraphdhseqr_("S", "V", n, &c__1, n, &a[a_offset], lda, &wr[1], &wi[ 1], &vl[vl_offset], ldvl, &work[1], &c_n1, info); } else if (wantvr) { igraphdhseqr_("S", "V", n, &c__1, n, &a[a_offset], lda, &wr[1], &wi[ 1], &vr[vr_offset], ldvr, &work[1], &c_n1, info); } else { if (wntsnn) { igraphdhseqr_("E", "N", n, &c__1, n, &a[a_offset], lda, &wr[1], &wi[1], &vr[vr_offset], ldvr, &work[1], &c_n1, info); } else { igraphdhseqr_("S", "N", n, &c__1, n, &a[a_offset], lda, &wr[1], &wi[1], &vr[vr_offset], ldvr, &work[1], &c_n1, info); } } hswork = (integer) work[1]; if (! wantvl && ! wantvr) { minwrk = *n << 1; if (! wntsnn) { /* Computing MAX */ i__1 = minwrk, i__2 = *n * *n + *n * 6; minwrk = max(i__1,i__2); } maxwrk = max(maxwrk,hswork); if (! wntsnn) { /* Computing MAX */ i__1 = maxwrk, i__2 = *n * *n + *n * 6; maxwrk = max(i__1,i__2); } } else { minwrk = *n * 3; if (! wntsnn && ! wntsne) { /* Computing MAX */ i__1 = minwrk, i__2 = *n * *n + *n * 6; minwrk = max(i__1,i__2); } maxwrk = max(maxwrk,hswork); /* Computing MAX */ i__1 = maxwrk, i__2 = *n + (*n - 1) * igraphilaenv_(&c__1, "DORGHR", " ", n, &c__1, n, &c_n1, (ftnlen)6, (ftnlen)1); maxwrk = max(i__1,i__2); if (! wntsnn && ! wntsne) { /* Computing MAX */ i__1 = maxwrk, i__2 = *n * *n + *n * 6; maxwrk = max(i__1,i__2); } /* Computing MAX */ i__1 = maxwrk, i__2 = *n * 3; maxwrk = max(i__1,i__2); } maxwrk = max(maxwrk,minwrk); } work[1] = (doublereal) maxwrk; if (*lwork < minwrk && ! lquery) { *info = -21; } } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DGEEVX", &i__1, (ftnlen)6); return 0; } else if (lquery) { return 0; } /* Quick return if possible */ if (*n == 0) { return 0; } /* Get machine constants */ eps = igraphdlamch_("P"); smlnum = igraphdlamch_("S"); bignum = 1. / smlnum; igraphdlabad_(&smlnum, &bignum); smlnum = sqrt(smlnum) / eps; bignum = 1. / smlnum; /* Scale A if max element outside range [SMLNUM,BIGNUM] */ icond = 0; anrm = igraphdlange_("M", n, n, &a[a_offset], lda, dum); scalea = FALSE_; if (anrm > 0. && anrm < smlnum) { scalea = TRUE_; cscale = smlnum; } else if (anrm > bignum) { scalea = TRUE_; cscale = bignum; } if (scalea) { igraphdlascl_("G", &c__0, &c__0, &anrm, &cscale, n, n, &a[a_offset], lda, & ierr); } /* Balance the matrix and compute ABNRM */ igraphdgebal_(balanc, n, &a[a_offset], lda, ilo, ihi, &scale[1], &ierr); *abnrm = igraphdlange_("1", n, n, &a[a_offset], lda, dum); if (scalea) { dum[0] = *abnrm; igraphdlascl_("G", &c__0, &c__0, &cscale, &anrm, &c__1, &c__1, dum, &c__1, & ierr); *abnrm = dum[0]; } /* Reduce to upper Hessenberg form (Workspace: need 2*N, prefer N+N*NB) */ itau = 1; iwrk = itau + *n; i__1 = *lwork - iwrk + 1; igraphdgehrd_(n, ilo, ihi, &a[a_offset], lda, &work[itau], &work[iwrk], &i__1, & ierr); if (wantvl) { /* Want left eigenvectors Copy Householder vectors to VL */ *(unsigned char *)side = 'L'; igraphdlacpy_("L", n, n, &a[a_offset], lda, &vl[vl_offset], ldvl) ; /* Generate orthogonal matrix in VL (Workspace: need 2*N-1, prefer N+(N-1)*NB) */ i__1 = *lwork - iwrk + 1; igraphdorghr_(n, ilo, ihi, &vl[vl_offset], ldvl, &work[itau], &work[iwrk], & i__1, &ierr); /* Perform QR iteration, accumulating Schur vectors in VL (Workspace: need 1, prefer HSWORK (see comments) ) */ iwrk = itau; i__1 = *lwork - iwrk + 1; igraphdhseqr_("S", "V", n, ilo, ihi, &a[a_offset], lda, &wr[1], &wi[1], &vl[ vl_offset], ldvl, &work[iwrk], &i__1, info); if (wantvr) { /* Want left and right eigenvectors Copy Schur vectors to VR */ *(unsigned char *)side = 'B'; igraphdlacpy_("F", n, n, &vl[vl_offset], ldvl, &vr[vr_offset], ldvr); } } else if (wantvr) { /* Want right eigenvectors Copy Householder vectors to VR */ *(unsigned char *)side = 'R'; igraphdlacpy_("L", n, n, &a[a_offset], lda, &vr[vr_offset], ldvr) ; /* Generate orthogonal matrix in VR (Workspace: need 2*N-1, prefer N+(N-1)*NB) */ i__1 = *lwork - iwrk + 1; igraphdorghr_(n, ilo, ihi, &vr[vr_offset], ldvr, &work[itau], &work[iwrk], & i__1, &ierr); /* Perform QR iteration, accumulating Schur vectors in VR (Workspace: need 1, prefer HSWORK (see comments) ) */ iwrk = itau; i__1 = *lwork - iwrk + 1; igraphdhseqr_("S", "V", n, ilo, ihi, &a[a_offset], lda, &wr[1], &wi[1], &vr[ vr_offset], ldvr, &work[iwrk], &i__1, info); } else { /* Compute eigenvalues only If condition numbers desired, compute Schur form */ if (wntsnn) { *(unsigned char *)job = 'E'; } else { *(unsigned char *)job = 'S'; } /* (Workspace: need 1, prefer HSWORK (see comments) ) */ iwrk = itau; i__1 = *lwork - iwrk + 1; igraphdhseqr_(job, "N", n, ilo, ihi, &a[a_offset], lda, &wr[1], &wi[1], &vr[ vr_offset], ldvr, &work[iwrk], &i__1, info); } /* If INFO > 0 from DHSEQR, then quit */ if (*info > 0) { goto L50; } if (wantvl || wantvr) { /* Compute left and/or right eigenvectors (Workspace: need 3*N) */ igraphdtrevc_(side, "B", select, n, &a[a_offset], lda, &vl[vl_offset], ldvl, &vr[vr_offset], ldvr, n, &nout, &work[iwrk], &ierr); } /* Compute condition numbers if desired (Workspace: need N*N+6*N unless SENSE = 'E') */ if (! wntsnn) { igraphdtrsna_(sense, "A", select, n, &a[a_offset], lda, &vl[vl_offset], ldvl, &vr[vr_offset], ldvr, &rconde[1], &rcondv[1], n, &nout, &work[iwrk], n, &iwork[1], &icond); } if (wantvl) { /* Undo balancing of left eigenvectors */ igraphdgebak_(balanc, "L", n, ilo, ihi, &scale[1], n, &vl[vl_offset], ldvl, &ierr); /* Normalize left eigenvectors and make largest component real */ i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { if (wi[i__] == 0.) { scl = 1. / igraphdnrm2_(n, &vl[i__ * vl_dim1 + 1], &c__1); igraphdscal_(n, &scl, &vl[i__ * vl_dim1 + 1], &c__1); } else if (wi[i__] > 0.) { d__1 = igraphdnrm2_(n, &vl[i__ * vl_dim1 + 1], &c__1); d__2 = igraphdnrm2_(n, &vl[(i__ + 1) * vl_dim1 + 1], &c__1); scl = 1. / igraphdlapy2_(&d__1, &d__2); igraphdscal_(n, &scl, &vl[i__ * vl_dim1 + 1], &c__1); igraphdscal_(n, &scl, &vl[(i__ + 1) * vl_dim1 + 1], &c__1); i__2 = *n; for (k = 1; k <= i__2; ++k) { /* Computing 2nd power */ d__1 = vl[k + i__ * vl_dim1]; /* Computing 2nd power */ d__2 = vl[k + (i__ + 1) * vl_dim1]; work[k] = d__1 * d__1 + d__2 * d__2; /* L10: */ } k = igraphidamax_(n, &work[1], &c__1); igraphdlartg_(&vl[k + i__ * vl_dim1], &vl[k + (i__ + 1) * vl_dim1], &cs, &sn, &r__); igraphdrot_(n, &vl[i__ * vl_dim1 + 1], &c__1, &vl[(i__ + 1) * vl_dim1 + 1], &c__1, &cs, &sn); vl[k + (i__ + 1) * vl_dim1] = 0.; } /* L20: */ } } if (wantvr) { /* Undo balancing of right eigenvectors */ igraphdgebak_(balanc, "R", n, ilo, ihi, &scale[1], n, &vr[vr_offset], ldvr, &ierr); /* Normalize right eigenvectors and make largest component real */ i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { if (wi[i__] == 0.) { scl = 1. / igraphdnrm2_(n, &vr[i__ * vr_dim1 + 1], &c__1); igraphdscal_(n, &scl, &vr[i__ * vr_dim1 + 1], &c__1); } else if (wi[i__] > 0.) { d__1 = igraphdnrm2_(n, &vr[i__ * vr_dim1 + 1], &c__1); d__2 = igraphdnrm2_(n, &vr[(i__ + 1) * vr_dim1 + 1], &c__1); scl = 1. / igraphdlapy2_(&d__1, &d__2); igraphdscal_(n, &scl, &vr[i__ * vr_dim1 + 1], &c__1); igraphdscal_(n, &scl, &vr[(i__ + 1) * vr_dim1 + 1], &c__1); i__2 = *n; for (k = 1; k <= i__2; ++k) { /* Computing 2nd power */ d__1 = vr[k + i__ * vr_dim1]; /* Computing 2nd power */ d__2 = vr[k + (i__ + 1) * vr_dim1]; work[k] = d__1 * d__1 + d__2 * d__2; /* L30: */ } k = igraphidamax_(n, &work[1], &c__1); igraphdlartg_(&vr[k + i__ * vr_dim1], &vr[k + (i__ + 1) * vr_dim1], &cs, &sn, &r__); igraphdrot_(n, &vr[i__ * vr_dim1 + 1], &c__1, &vr[(i__ + 1) * vr_dim1 + 1], &c__1, &cs, &sn); vr[k + (i__ + 1) * vr_dim1] = 0.; } /* L40: */ } } /* Undo scaling if necessary */ L50: if (scalea) { i__1 = *n - *info; /* Computing MAX */ i__3 = *n - *info; i__2 = max(i__3,1); igraphdlascl_("G", &c__0, &c__0, &cscale, &anrm, &i__1, &c__1, &wr[*info + 1], &i__2, &ierr); i__1 = *n - *info; /* Computing MAX */ i__3 = *n - *info; i__2 = max(i__3,1); igraphdlascl_("G", &c__0, &c__0, &cscale, &anrm, &i__1, &c__1, &wi[*info + 1], &i__2, &ierr); if (*info == 0) { if ((wntsnv || wntsnb) && icond == 0) { igraphdlascl_("G", &c__0, &c__0, &cscale, &anrm, n, &c__1, &rcondv[ 1], n, &ierr); } } else { i__1 = *ilo - 1; igraphdlascl_("G", &c__0, &c__0, &cscale, &anrm, &i__1, &c__1, &wr[1], n, &ierr); i__1 = *ilo - 1; igraphdlascl_("G", &c__0, &c__0, &cscale, &anrm, &i__1, &c__1, &wi[1], n, &ierr); } } work[1] = (doublereal) maxwrk; return 0; /* End of DGEEVX */ } /* igraphdgeevx_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlarnv.c0000644000076500000240000001227213524616145024276 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLARNV returns a vector of random numbers from a uniform or normal distribution. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLARNV + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLARNV( IDIST, ISEED, N, X ) INTEGER IDIST, N INTEGER ISEED( 4 ) DOUBLE PRECISION X( * ) > \par Purpose: ============= > > \verbatim > > DLARNV returns a vector of n random real numbers from a uniform or > normal distribution. > \endverbatim Arguments: ========== > \param[in] IDIST > \verbatim > IDIST is INTEGER > Specifies the distribution of the random numbers: > = 1: uniform (0,1) > = 2: uniform (-1,1) > = 3: normal (0,1) > \endverbatim > > \param[in,out] ISEED > \verbatim > ISEED is INTEGER array, dimension (4) > On entry, the seed of the random number generator; the array > elements must be between 0 and 4095, and ISEED(4) must be > odd. > On exit, the seed is updated. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The number of random numbers to be generated. > \endverbatim > > \param[out] X > \verbatim > X is DOUBLE PRECISION array, dimension (N) > The generated random numbers. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERauxiliary > \par Further Details: ===================== > > \verbatim > > This routine calls the auxiliary routine DLARUV to generate random > real numbers from a uniform (0,1) distribution, in batches of up to > 128 using vectorisable code. The Box-Muller method is used to > transform numbers from a uniform to a normal distribution. > \endverbatim > ===================================================================== Subroutine */ int igraphdlarnv_(integer *idist, integer *iseed, integer *n, doublereal *x) { /* System generated locals */ integer i__1, i__2, i__3; /* Builtin functions */ double log(doublereal), sqrt(doublereal), cos(doublereal); /* Local variables */ integer i__; doublereal u[128]; integer il, iv, il2; extern /* Subroutine */ int igraphdlaruv_(integer *, integer *, doublereal *); /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ --x; --iseed; /* Function Body */ i__1 = *n; for (iv = 1; iv <= i__1; iv += 64) { /* Computing MIN */ i__2 = 64, i__3 = *n - iv + 1; il = min(i__2,i__3); if (*idist == 3) { il2 = il << 1; } else { il2 = il; } /* Call DLARUV to generate IL2 numbers from a uniform (0,1) distribution (IL2 <= LV) */ igraphdlaruv_(&iseed[1], &il2, u); if (*idist == 1) { /* Copy generated numbers */ i__2 = il; for (i__ = 1; i__ <= i__2; ++i__) { x[iv + i__ - 1] = u[i__ - 1]; /* L10: */ } } else if (*idist == 2) { /* Convert generated numbers to uniform (-1,1) distribution */ i__2 = il; for (i__ = 1; i__ <= i__2; ++i__) { x[iv + i__ - 1] = u[i__ - 1] * 2. - 1.; /* L20: */ } } else if (*idist == 3) { /* Convert generated numbers to normal (0,1) distribution */ i__2 = il; for (i__ = 1; i__ <= i__2; ++i__) { x[iv + i__ - 1] = sqrt(log(u[(i__ << 1) - 2]) * -2.) * cos(u[( i__ << 1) - 1] * 6.2831853071795864769252867663); /* L30: */ } } /* L40: */ } return 0; /* End of DLARNV */ } /* igraphdlarnv_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlaqr0.c0000644000076500000240000007054713524616145024204 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__13 = 13; static integer c__15 = 15; static integer c_n1 = -1; static integer c__12 = 12; static integer c__14 = 14; static integer c__16 = 16; static logical c_false = FALSE_; static integer c__1 = 1; static integer c__3 = 3; /* > \brief \b DLAQR0 computes the eigenvalues of a Hessenberg matrix, and optionally the matrices from the Sc hur decomposition. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLAQR0 + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLAQR0( WANTT, WANTZ, N, ILO, IHI, H, LDH, WR, WI, ILOZ, IHIZ, Z, LDZ, WORK, LWORK, INFO ) INTEGER IHI, IHIZ, ILO, ILOZ, INFO, LDH, LDZ, LWORK, N LOGICAL WANTT, WANTZ DOUBLE PRECISION H( LDH, * ), WI( * ), WORK( * ), WR( * ), $ Z( LDZ, * ) > \par Purpose: ============= > > \verbatim > > DLAQR0 computes the eigenvalues of a Hessenberg matrix H > and, optionally, the matrices T and Z from the Schur decomposition > H = Z T Z**T, where T is an upper quasi-triangular matrix (the > Schur form), and Z is the orthogonal matrix of Schur vectors. > > Optionally Z may be postmultiplied into an input orthogonal > matrix Q so that this routine can give the Schur factorization > of a matrix A which has been reduced to the Hessenberg form H > by the orthogonal matrix Q: A = Q*H*Q**T = (QZ)*T*(QZ)**T. > \endverbatim Arguments: ========== > \param[in] WANTT > \verbatim > WANTT is LOGICAL > = .TRUE. : the full Schur form T is required; > = .FALSE.: only eigenvalues are required. > \endverbatim > > \param[in] WANTZ > \verbatim > WANTZ is LOGICAL > = .TRUE. : the matrix of Schur vectors Z is required; > = .FALSE.: Schur vectors are not required. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix H. N .GE. 0. > \endverbatim > > \param[in] ILO > \verbatim > ILO is INTEGER > \endverbatim > > \param[in] IHI > \verbatim > IHI is INTEGER > It is assumed that H is already upper triangular in rows > and columns 1:ILO-1 and IHI+1:N and, if ILO.GT.1, > H(ILO,ILO-1) is zero. ILO and IHI are normally set by a > previous call to DGEBAL, and then passed to DGEHRD when the > matrix output by DGEBAL is reduced to Hessenberg form. > Otherwise, ILO and IHI should be set to 1 and N, > respectively. If N.GT.0, then 1.LE.ILO.LE.IHI.LE.N. > If N = 0, then ILO = 1 and IHI = 0. > \endverbatim > > \param[in,out] H > \verbatim > H is DOUBLE PRECISION array, dimension (LDH,N) > On entry, the upper Hessenberg matrix H. > On exit, if INFO = 0 and WANTT is .TRUE., then H contains > the upper quasi-triangular matrix T from the Schur > decomposition (the Schur form); 2-by-2 diagonal blocks > (corresponding to complex conjugate pairs of eigenvalues) > are returned in standard form, with H(i,i) = H(i+1,i+1) > and H(i+1,i)*H(i,i+1).LT.0. If INFO = 0 and WANTT is > .FALSE., then the contents of H are unspecified on exit. > (The output value of H when INFO.GT.0 is given under the > description of INFO below.) > > This subroutine may explicitly set H(i,j) = 0 for i.GT.j and > j = 1, 2, ... ILO-1 or j = IHI+1, IHI+2, ... N. > \endverbatim > > \param[in] LDH > \verbatim > LDH is INTEGER > The leading dimension of the array H. LDH .GE. max(1,N). > \endverbatim > > \param[out] WR > \verbatim > WR is DOUBLE PRECISION array, dimension (IHI) > \endverbatim > > \param[out] WI > \verbatim > WI is DOUBLE PRECISION array, dimension (IHI) > The real and imaginary parts, respectively, of the computed > eigenvalues of H(ILO:IHI,ILO:IHI) are stored in WR(ILO:IHI) > and WI(ILO:IHI). If two eigenvalues are computed as a > complex conjugate pair, they are stored in consecutive > elements of WR and WI, say the i-th and (i+1)th, with > WI(i) .GT. 0 and WI(i+1) .LT. 0. If WANTT is .TRUE., then > the eigenvalues are stored in the same order as on the > diagonal of the Schur form returned in H, with > WR(i) = H(i,i) and, if H(i:i+1,i:i+1) is a 2-by-2 diagonal > block, WI(i) = sqrt(-H(i+1,i)*H(i,i+1)) and > WI(i+1) = -WI(i). > \endverbatim > > \param[in] ILOZ > \verbatim > ILOZ is INTEGER > \endverbatim > > \param[in] IHIZ > \verbatim > IHIZ is INTEGER > Specify the rows of Z to which transformations must be > applied if WANTZ is .TRUE.. > 1 .LE. ILOZ .LE. ILO; IHI .LE. IHIZ .LE. N. > \endverbatim > > \param[in,out] Z > \verbatim > Z is DOUBLE PRECISION array, dimension (LDZ,IHI) > If WANTZ is .FALSE., then Z is not referenced. > If WANTZ is .TRUE., then Z(ILO:IHI,ILOZ:IHIZ) is > replaced by Z(ILO:IHI,ILOZ:IHIZ)*U where U is the > orthogonal Schur factor of H(ILO:IHI,ILO:IHI). > (The output value of Z when INFO.GT.0 is given under > the description of INFO below.) > \endverbatim > > \param[in] LDZ > \verbatim > LDZ is INTEGER > The leading dimension of the array Z. if WANTZ is .TRUE. > then LDZ.GE.MAX(1,IHIZ). Otherwize, LDZ.GE.1. > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension LWORK > On exit, if LWORK = -1, WORK(1) returns an estimate of > the optimal value for LWORK. > \endverbatim > > \param[in] LWORK > \verbatim > LWORK is INTEGER > The dimension of the array WORK. LWORK .GE. max(1,N) > is sufficient, but LWORK typically as large as 6*N may > be required for optimal performance. A workspace query > to determine the optimal workspace size is recommended. > > If LWORK = -1, then DLAQR0 does a workspace query. > In this case, DLAQR0 checks the input parameters and > estimates the optimal workspace size for the given > values of N, ILO and IHI. The estimate is returned > in WORK(1). No error message related to LWORK is > issued by XERBLA. Neither H nor Z are accessed. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > .GT. 0: if INFO = i, DLAQR0 failed to compute all of > the eigenvalues. Elements 1:ilo-1 and i+1:n of WR > and WI contain those eigenvalues which have been > successfully computed. (Failures are rare.) > > If INFO .GT. 0 and WANT is .FALSE., then on exit, > the remaining unconverged eigenvalues are the eigen- > values of the upper Hessenberg matrix rows and > columns ILO through INFO of the final, output > value of H. > > If INFO .GT. 0 and WANTT is .TRUE., then on exit > > (*) (initial value of H)*U = U*(final value of H) > > where U is an orthogonal matrix. The final > value of H is upper Hessenberg and quasi-triangular > in rows and columns INFO+1 through IHI. > > If INFO .GT. 0 and WANTZ is .TRUE., then on exit > > (final value of Z(ILO:IHI,ILOZ:IHIZ) > = (initial value of Z(ILO:IHI,ILOZ:IHIZ)*U > > where U is the orthogonal matrix in (*) (regard- > less of the value of WANTT.) > > If INFO .GT. 0 and WANTZ is .FALSE., then Z is not > accessed. > \endverbatim > \par Contributors: ================== > > Karen Braman and Ralph Byers, Department of Mathematics, > University of Kansas, USA > \par References: ================ > > K. Braman, R. Byers and R. Mathias, The Multi-Shift QR > Algorithm Part I: Maintaining Well Focused Shifts, and Level 3 > Performance, SIAM Journal of Matrix Analysis, volume 23, pages > 929--947, 2002. > \n > K. Braman, R. Byers and R. Mathias, The Multi-Shift QR > Algorithm Part II: Aggressive Early Deflation, SIAM Journal > of Matrix Analysis, volume 23, pages 948--973, 2002. Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleOTHERauxiliary ===================================================================== Subroutine */ int igraphdlaqr0_(logical *wantt, logical *wantz, integer *n, integer *ilo, integer *ihi, doublereal *h__, integer *ldh, doublereal *wr, doublereal *wi, integer *iloz, integer *ihiz, doublereal *z__, integer *ldz, doublereal *work, integer *lwork, integer *info) { /* System generated locals */ integer h_dim1, h_offset, z_dim1, z_offset, i__1, i__2, i__3, i__4, i__5; doublereal d__1, d__2, d__3, d__4; /* Local variables */ integer i__, k; doublereal aa, bb, cc, dd; integer ld; doublereal cs; integer nh, it, ks, kt; doublereal sn; integer ku, kv, ls, ns; doublereal ss; integer nw, inf, kdu, nho, nve, kwh, nsr, nwr, kwv, ndec, ndfl, kbot, nmin; doublereal swap; integer ktop; doublereal zdum[1] /* was [1][1] */; integer kacc22, itmax, nsmax, nwmax, kwtop; extern /* Subroutine */ int igraphdlanv2_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *), igraphdlaqr3_( logical *, logical *, integer *, integer *, integer *, integer *, doublereal *, integer *, integer *, integer *, doublereal *, integer *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *, integer *, doublereal *, integer *, integer *, doublereal *, integer *, doublereal *, integer *), igraphdlaqr4_(logical *, logical *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, integer *, doublereal *, integer *, integer *), igraphdlaqr5_(logical *, logical *, integer *, integer *, integer *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, integer *, integer *, doublereal *, integer *, integer *, doublereal *, integer *); integer nibble; extern /* Subroutine */ int igraphdlahqr_(logical *, logical *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, integer *, integer *), igraphdlacpy_(char *, integer *, integer *, doublereal *, integer *, doublereal *, integer *); extern integer igraphilaenv_(integer *, char *, char *, integer *, integer *, integer *, integer *, ftnlen, ftnlen); char jbcmpz[2]; integer nwupbd; logical sorted; integer lwkopt; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ================================================================ ==== Matrices of order NTINY or smaller must be processed by . DLAHQR because of insufficient subdiagonal scratch space. . (This is a hard limit.) ==== ==== Exceptional deflation windows: try to cure rare . slow convergence by varying the size of the . deflation window after KEXNW iterations. ==== ==== Exceptional shifts: try to cure rare slow convergence . with ad-hoc exceptional shifts every KEXSH iterations. . ==== ==== The constants WILK1 and WILK2 are used to form the . exceptional shifts. ==== Parameter adjustments */ h_dim1 = *ldh; h_offset = 1 + h_dim1; h__ -= h_offset; --wr; --wi; z_dim1 = *ldz; z_offset = 1 + z_dim1; z__ -= z_offset; --work; /* Function Body */ *info = 0; /* ==== Quick return for N = 0: nothing to do. ==== */ if (*n == 0) { work[1] = 1.; return 0; } if (*n <= 11) { /* ==== Tiny matrices must use DLAHQR. ==== */ lwkopt = 1; if (*lwork != -1) { igraphdlahqr_(wantt, wantz, n, ilo, ihi, &h__[h_offset], ldh, &wr[1], & wi[1], iloz, ihiz, &z__[z_offset], ldz, info); } } else { /* ==== Use small bulge multi-shift QR with aggressive early . deflation on larger-than-tiny matrices. ==== ==== Hope for the best. ==== */ *info = 0; /* ==== Set up job flags for ILAENV. ==== */ if (*wantt) { *(unsigned char *)jbcmpz = 'S'; } else { *(unsigned char *)jbcmpz = 'E'; } if (*wantz) { *(unsigned char *)&jbcmpz[1] = 'V'; } else { *(unsigned char *)&jbcmpz[1] = 'N'; } /* ==== NWR = recommended deflation window size. At this . point, N .GT. NTINY = 11, so there is enough . subdiagonal workspace for NWR.GE.2 as required. . (In fact, there is enough subdiagonal space for . NWR.GE.3.) ==== */ nwr = igraphilaenv_(&c__13, "DLAQR0", jbcmpz, n, ilo, ihi, lwork, (ftnlen)6, (ftnlen)2); nwr = max(2,nwr); /* Computing MIN */ i__1 = *ihi - *ilo + 1, i__2 = (*n - 1) / 3, i__1 = min(i__1,i__2); nwr = min(i__1,nwr); /* ==== NSR = recommended number of simultaneous shifts. . At this point N .GT. NTINY = 11, so there is at . enough subdiagonal workspace for NSR to be even . and greater than or equal to two as required. ==== */ nsr = igraphilaenv_(&c__15, "DLAQR0", jbcmpz, n, ilo, ihi, lwork, (ftnlen)6, (ftnlen)2); /* Computing MIN */ i__1 = nsr, i__2 = (*n + 6) / 9, i__1 = min(i__1,i__2), i__2 = *ihi - *ilo; nsr = min(i__1,i__2); /* Computing MAX */ i__1 = 2, i__2 = nsr - nsr % 2; nsr = max(i__1,i__2); /* ==== Estimate optimal workspace ==== ==== Workspace query call to DLAQR3 ==== */ i__1 = nwr + 1; igraphdlaqr3_(wantt, wantz, n, ilo, ihi, &i__1, &h__[h_offset], ldh, iloz, ihiz, &z__[z_offset], ldz, &ls, &ld, &wr[1], &wi[1], &h__[ h_offset], ldh, n, &h__[h_offset], ldh, n, &h__[h_offset], ldh, &work[1], &c_n1); /* ==== Optimal workspace = MAX(DLAQR5, DLAQR3) ==== Computing MAX */ i__1 = nsr * 3 / 2, i__2 = (integer) work[1]; lwkopt = max(i__1,i__2); /* ==== Quick return in case of workspace query. ==== */ if (*lwork == -1) { work[1] = (doublereal) lwkopt; return 0; } /* ==== DLAHQR/DLAQR0 crossover point ==== */ nmin = igraphilaenv_(&c__12, "DLAQR0", jbcmpz, n, ilo, ihi, lwork, (ftnlen) 6, (ftnlen)2); nmin = max(11,nmin); /* ==== Nibble crossover point ==== */ nibble = igraphilaenv_(&c__14, "DLAQR0", jbcmpz, n, ilo, ihi, lwork, ( ftnlen)6, (ftnlen)2); nibble = max(0,nibble); /* ==== Accumulate reflections during ttswp? Use block . 2-by-2 structure during matrix-matrix multiply? ==== */ kacc22 = igraphilaenv_(&c__16, "DLAQR0", jbcmpz, n, ilo, ihi, lwork, ( ftnlen)6, (ftnlen)2); kacc22 = max(0,kacc22); kacc22 = min(2,kacc22); /* ==== NWMAX = the largest possible deflation window for . which there is sufficient workspace. ==== Computing MIN */ i__1 = (*n - 1) / 3, i__2 = *lwork / 2; nwmax = min(i__1,i__2); nw = nwmax; /* ==== NSMAX = the Largest number of simultaneous shifts . for which there is sufficient workspace. ==== Computing MIN */ i__1 = (*n + 6) / 9, i__2 = (*lwork << 1) / 3; nsmax = min(i__1,i__2); nsmax -= nsmax % 2; /* ==== NDFL: an iteration count restarted at deflation. ==== */ ndfl = 1; /* ==== ITMAX = iteration limit ==== Computing MAX */ i__1 = 10, i__2 = *ihi - *ilo + 1; itmax = max(i__1,i__2) * 30; /* ==== Last row and column in the active block ==== */ kbot = *ihi; /* ==== Main Loop ==== */ i__1 = itmax; for (it = 1; it <= i__1; ++it) { /* ==== Done when KBOT falls below ILO ==== */ if (kbot < *ilo) { goto L90; } /* ==== Locate active block ==== */ i__2 = *ilo + 1; for (k = kbot; k >= i__2; --k) { if (h__[k + (k - 1) * h_dim1] == 0.) { goto L20; } /* L10: */ } k = *ilo; L20: ktop = k; /* ==== Select deflation window size: . Typical Case: . If possible and advisable, nibble the entire . active block. If not, use size MIN(NWR,NWMAX) . or MIN(NWR+1,NWMAX) depending upon which has . the smaller corresponding subdiagonal entry . (a heuristic). . . Exceptional Case: . If there have been no deflations in KEXNW or . more iterations, then vary the deflation window . size. At first, because, larger windows are, . in general, more powerful than smaller ones, . rapidly increase the window to the maximum possible. . Then, gradually reduce the window size. ==== */ nh = kbot - ktop + 1; nwupbd = min(nh,nwmax); if (ndfl < 5) { nw = min(nwupbd,nwr); } else { /* Computing MIN */ i__2 = nwupbd, i__3 = nw << 1; nw = min(i__2,i__3); } if (nw < nwmax) { if (nw >= nh - 1) { nw = nh; } else { kwtop = kbot - nw + 1; if ((d__1 = h__[kwtop + (kwtop - 1) * h_dim1], abs(d__1)) > (d__2 = h__[kwtop - 1 + (kwtop - 2) * h_dim1], abs(d__2))) { ++nw; } } } if (ndfl < 5) { ndec = -1; } else if (ndec >= 0 || nw >= nwupbd) { ++ndec; if (nw - ndec < 2) { ndec = 0; } nw -= ndec; } /* ==== Aggressive early deflation: . split workspace under the subdiagonal into . - an nw-by-nw work array V in the lower . left-hand-corner, . - an NW-by-at-least-NW-but-more-is-better . (NW-by-NHO) horizontal work array along . the bottom edge, . - an at-least-NW-but-more-is-better (NHV-by-NW) . vertical work array along the left-hand-edge. . ==== */ kv = *n - nw + 1; kt = nw + 1; nho = *n - nw - 1 - kt + 1; kwv = nw + 2; nve = *n - nw - kwv + 1; /* ==== Aggressive early deflation ==== */ igraphdlaqr3_(wantt, wantz, n, &ktop, &kbot, &nw, &h__[h_offset], ldh, iloz, ihiz, &z__[z_offset], ldz, &ls, &ld, &wr[1], &wi[1], &h__[kv + h_dim1], ldh, &nho, &h__[kv + kt * h_dim1], ldh, &nve, &h__[kwv + h_dim1], ldh, &work[1], lwork); /* ==== Adjust KBOT accounting for new deflations. ==== */ kbot -= ld; /* ==== KS points to the shifts. ==== */ ks = kbot - ls + 1; /* ==== Skip an expensive QR sweep if there is a (partly . heuristic) reason to expect that many eigenvalues . will deflate without it. Here, the QR sweep is . skipped if many eigenvalues have just been deflated . or if the remaining active block is small. */ if (ld == 0 || ld * 100 <= nw * nibble && kbot - ktop + 1 > min( nmin,nwmax)) { /* ==== NS = nominal number of simultaneous shifts. . This may be lowered (slightly) if DLAQR3 . did not provide that many shifts. ==== Computing MIN Computing MAX */ i__4 = 2, i__5 = kbot - ktop; i__2 = min(nsmax,nsr), i__3 = max(i__4,i__5); ns = min(i__2,i__3); ns -= ns % 2; /* ==== If there have been no deflations . in a multiple of KEXSH iterations, . then try exceptional shifts. . Otherwise use shifts provided by . DLAQR3 above or from the eigenvalues . of a trailing principal submatrix. ==== */ if (ndfl % 6 == 0) { ks = kbot - ns + 1; /* Computing MAX */ i__3 = ks + 1, i__4 = ktop + 2; i__2 = max(i__3,i__4); for (i__ = kbot; i__ >= i__2; i__ += -2) { ss = (d__1 = h__[i__ + (i__ - 1) * h_dim1], abs(d__1)) + (d__2 = h__[i__ - 1 + (i__ - 2) * h_dim1], abs(d__2)); aa = ss * .75 + h__[i__ + i__ * h_dim1]; bb = ss; cc = ss * -.4375; dd = aa; igraphdlanv2_(&aa, &bb, &cc, &dd, &wr[i__ - 1], &wi[i__ - 1] , &wr[i__], &wi[i__], &cs, &sn); /* L30: */ } if (ks == ktop) { wr[ks + 1] = h__[ks + 1 + (ks + 1) * h_dim1]; wi[ks + 1] = 0.; wr[ks] = wr[ks + 1]; wi[ks] = wi[ks + 1]; } } else { /* ==== Got NS/2 or fewer shifts? Use DLAQR4 or . DLAHQR on a trailing principal submatrix to . get more. (Since NS.LE.NSMAX.LE.(N+6)/9, . there is enough space below the subdiagonal . to fit an NS-by-NS scratch array.) ==== */ if (kbot - ks + 1 <= ns / 2) { ks = kbot - ns + 1; kt = *n - ns + 1; igraphdlacpy_("A", &ns, &ns, &h__[ks + ks * h_dim1], ldh, & h__[kt + h_dim1], ldh); if (ns > nmin) { igraphdlaqr4_(&c_false, &c_false, &ns, &c__1, &ns, &h__[ kt + h_dim1], ldh, &wr[ks], &wi[ks], & c__1, &c__1, zdum, &c__1, &work[1], lwork, &inf); } else { igraphdlahqr_(&c_false, &c_false, &ns, &c__1, &ns, &h__[ kt + h_dim1], ldh, &wr[ks], &wi[ks], & c__1, &c__1, zdum, &c__1, &inf); } ks += inf; /* ==== In case of a rare QR failure use . eigenvalues of the trailing 2-by-2 . principal submatrix. ==== */ if (ks >= kbot) { aa = h__[kbot - 1 + (kbot - 1) * h_dim1]; cc = h__[kbot + (kbot - 1) * h_dim1]; bb = h__[kbot - 1 + kbot * h_dim1]; dd = h__[kbot + kbot * h_dim1]; igraphdlanv2_(&aa, &bb, &cc, &dd, &wr[kbot - 1], &wi[ kbot - 1], &wr[kbot], &wi[kbot], &cs, &sn) ; ks = kbot - 1; } } if (kbot - ks + 1 > ns) { /* ==== Sort the shifts (Helps a little) . Bubble sort keeps complex conjugate . pairs together. ==== */ sorted = FALSE_; i__2 = ks + 1; for (k = kbot; k >= i__2; --k) { if (sorted) { goto L60; } sorted = TRUE_; i__3 = k - 1; for (i__ = ks; i__ <= i__3; ++i__) { if ((d__1 = wr[i__], abs(d__1)) + (d__2 = wi[ i__], abs(d__2)) < (d__3 = wr[i__ + 1] , abs(d__3)) + (d__4 = wi[i__ + 1], abs(d__4))) { sorted = FALSE_; swap = wr[i__]; wr[i__] = wr[i__ + 1]; wr[i__ + 1] = swap; swap = wi[i__]; wi[i__] = wi[i__ + 1]; wi[i__ + 1] = swap; } /* L40: */ } /* L50: */ } L60: ; } /* ==== Shuffle shifts into pairs of real shifts . and pairs of complex conjugate shifts . assuming complex conjugate shifts are . already adjacent to one another. (Yes, . they are.) ==== */ i__2 = ks + 2; for (i__ = kbot; i__ >= i__2; i__ += -2) { if (wi[i__] != -wi[i__ - 1]) { swap = wr[i__]; wr[i__] = wr[i__ - 1]; wr[i__ - 1] = wr[i__ - 2]; wr[i__ - 2] = swap; swap = wi[i__]; wi[i__] = wi[i__ - 1]; wi[i__ - 1] = wi[i__ - 2]; wi[i__ - 2] = swap; } /* L70: */ } } /* ==== If there are only two shifts and both are . real, then use only one. ==== */ if (kbot - ks + 1 == 2) { if (wi[kbot] == 0.) { if ((d__1 = wr[kbot] - h__[kbot + kbot * h_dim1], abs( d__1)) < (d__2 = wr[kbot - 1] - h__[kbot + kbot * h_dim1], abs(d__2))) { wr[kbot - 1] = wr[kbot]; } else { wr[kbot] = wr[kbot - 1]; } } } /* ==== Use up to NS of the the smallest magnatiude . shifts. If there aren't NS shifts available, . then use them all, possibly dropping one to . make the number of shifts even. ==== Computing MIN */ i__2 = ns, i__3 = kbot - ks + 1; ns = min(i__2,i__3); ns -= ns % 2; ks = kbot - ns + 1; /* ==== Small-bulge multi-shift QR sweep: . split workspace under the subdiagonal into . - a KDU-by-KDU work array U in the lower . left-hand-corner, . - a KDU-by-at-least-KDU-but-more-is-better . (KDU-by-NHo) horizontal work array WH along . the bottom edge, . - and an at-least-KDU-but-more-is-better-by-KDU . (NVE-by-KDU) vertical work WV arrow along . the left-hand-edge. ==== */ kdu = ns * 3 - 3; ku = *n - kdu + 1; kwh = kdu + 1; nho = *n - kdu - 3 - (kdu + 1) + 1; kwv = kdu + 4; nve = *n - kdu - kwv + 1; /* ==== Small-bulge multi-shift QR sweep ==== */ igraphdlaqr5_(wantt, wantz, &kacc22, n, &ktop, &kbot, &ns, &wr[ks], &wi[ks], &h__[h_offset], ldh, iloz, ihiz, &z__[ z_offset], ldz, &work[1], &c__3, &h__[ku + h_dim1], ldh, &nve, &h__[kwv + h_dim1], ldh, &nho, &h__[ku + kwh * h_dim1], ldh); } /* ==== Note progress (or the lack of it). ==== */ if (ld > 0) { ndfl = 1; } else { ++ndfl; } /* ==== End of main loop ==== L80: */ } /* ==== Iteration limit exceeded. Set INFO to show where . the problem occurred and exit. ==== */ *info = kbot; L90: ; } /* ==== Return the optimal value of LWORK. ==== */ work[1] = (doublereal) lwkopt; /* ==== End of DLAQR0 ==== */ return 0; } /* igraphdlaqr0_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/second.c0000644000076500000240000000210013524616145024250 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Subroutine */ int igraphsecond_(real *t) { real t1; extern doublereal etime_(real *); real tarray[2]; /* -- LAPACK auxiliary routine (preliminary version) -- Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., Courant Institute, Argonne National Lab, and Rice University July 26, 1991 Purpose ======= SECOND returns the user time for a process in seconds. This version gets the time from the system function ETIME. */ t1 = etime_(tarray); *t = tarray[0]; return 0; /* End of SECOND */ } /* igraphsecond_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dnconv.c0000644000076500000240000001216413524616145024277 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static doublereal c_b3 = .66666666666666663; /* ----------------------------------------------------------------------- \BeginDoc \Name: dnconv \Description: Convergence testing for the nonsymmetric Arnoldi eigenvalue routine. \Usage: call dnconv ( N, RITZR, RITZI, BOUNDS, TOL, NCONV ) \Arguments N Integer. (INPUT) Number of Ritz values to check for convergence. RITZR, Double precision arrays of length N. (INPUT) RITZI Real and imaginary parts of the Ritz values to be checked for convergence. BOUNDS Double precision array of length N. (INPUT) Ritz estimates for the Ritz values in RITZR and RITZI. TOL Double precision scalar. (INPUT) Desired backward error for a Ritz value to be considered "converged". NCONV Integer scalar. (OUTPUT) Number of "converged" Ritz values. \EndDoc ----------------------------------------------------------------------- \BeginLib \Local variables: xxxxxx real \Routines called: second ARPACK utility routine for timing. dlamch LAPACK routine that determines machine constants. dlapy2 LAPACK routine to compute sqrt(x**2+y**2) carefully. \Author Danny Sorensen Phuong Vu Richard Lehoucq CRPC / Rice University Dept. of Computational & Houston, Texas Applied Mathematics Rice University Houston, Texas \Revision history: xx/xx/92: Version ' 2.1' \SCCS Information: @(#) FILE: nconv.F SID: 2.3 DATE OF SID: 4/20/96 RELEASE: 2 \Remarks 1. xxxx \EndLib ----------------------------------------------------------------------- Subroutine */ int igraphdnconv_(integer *n, doublereal *ritzr, doublereal *ritzi, doublereal *bounds, doublereal *tol, integer *nconv) { /* System generated locals */ integer i__1; doublereal d__1, d__2; /* Builtin functions */ double pow_dd(doublereal *, doublereal *); /* Local variables */ integer i__; real t0, t1; doublereal eps23, temp; extern doublereal igraphdlapy2_(doublereal *, doublereal *), igraphdlamch_(char *); extern /* Subroutine */ int igraphsecond_(real *); real tnconv = 0.; /* %----------------------------------------------------% | Include files for debugging and timing information | %----------------------------------------------------% %------------------% | Scalar Arguments | %------------------% %-----------------% | Array Arguments | %-----------------% %---------------% | Local Scalars | %---------------% %--------------------% | External Functions | %--------------------% %-----------------------% | Executable Statements | %-----------------------% %-------------------------------------------------------------% | Convergence test: unlike in the symmetric code, I am not | | using things like refined error bounds and gap condition | | because I don't know the exact equivalent concept. | | | | Instead the i-th Ritz value is considered "converged" when: | | | | bounds(i) .le. ( TOL * | ritz | ) | | | | for some appropriate choice of norm. | %-------------------------------------------------------------% Parameter adjustments */ --bounds; --ritzi; --ritzr; /* Function Body */ igraphsecond_(&t0); /* %---------------------------------% | Get machine dependent constant. | %---------------------------------% */ eps23 = igraphdlamch_("Epsilon-Machine"); eps23 = pow_dd(&eps23, &c_b3); *nconv = 0; i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { /* Computing MAX */ d__1 = eps23, d__2 = igraphdlapy2_(&ritzr[i__], &ritzi[i__]); temp = max(d__1,d__2); if (bounds[i__] <= *tol * temp) { ++(*nconv); } /* L20: */ } igraphsecond_(&t1); tnconv += t1 - t0; return 0; /* %---------------% | End of dnconv | %---------------% */ } /* igraphdnconv_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlarrr.c0000644000076500000240000001471613524616145024303 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLARRR performs tests to decide whether the symmetric tridiagonal matrix T warrants expensive c omputations which guarantee high relative accuracy in the eigenvalues. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLARRR + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLARRR( N, D, E, INFO ) INTEGER N, INFO DOUBLE PRECISION D( * ), E( * ) > \par Purpose: ============= > > \verbatim > > Perform tests to decide whether the symmetric tridiagonal matrix T > warrants expensive computations which guarantee high relative accuracy > in the eigenvalues. > \endverbatim Arguments: ========== > \param[in] N > \verbatim > N is INTEGER > The order of the matrix. N > 0. > \endverbatim > > \param[in] D > \verbatim > D is DOUBLE PRECISION array, dimension (N) > The N diagonal elements of the tridiagonal matrix T. > \endverbatim > > \param[in,out] E > \verbatim > E is DOUBLE PRECISION array, dimension (N) > On entry, the first (N-1) entries contain the subdiagonal > elements of the tridiagonal matrix T; E(N) is set to ZERO. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > INFO = 0(default) : the matrix warrants computations preserving > relative accuracy. > INFO = 1 : the matrix warrants computations guaranteeing > only absolute accuracy. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERauxiliary > \par Contributors: ================== > > Beresford Parlett, University of California, Berkeley, USA \n > Jim Demmel, University of California, Berkeley, USA \n > Inderjit Dhillon, University of Texas, Austin, USA \n > Osni Marques, LBNL/NERSC, USA \n > Christof Voemel, University of California, Berkeley, USA ===================================================================== Subroutine */ int igraphdlarrr_(integer *n, doublereal *d__, doublereal *e, integer *info) { /* System generated locals */ integer i__1; doublereal d__1; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ integer i__; doublereal eps, tmp, tmp2, rmin; extern doublereal igraphdlamch_(char *); doublereal offdig, safmin; logical yesrel; doublereal smlnum, offdig2; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== As a default, do NOT go for relative-accuracy preserving computations. Parameter adjustments */ --e; --d__; /* Function Body */ *info = 1; safmin = igraphdlamch_("Safe minimum"); eps = igraphdlamch_("Precision"); smlnum = safmin / eps; rmin = sqrt(smlnum); /* Tests for relative accuracy Test for scaled diagonal dominance Scale the diagonal entries to one and check whether the sum of the off-diagonals is less than one The sdd relative error bounds have a 1/(1- 2*x) factor in them, x = max(OFFDIG + OFFDIG2), so when x is close to 1/2, no relative accuracy is promised. In the notation of the code fragment below, 1/(1 - (OFFDIG + OFFDIG2)) is the condition number. We don't think it is worth going into "sdd mode" unless the relative condition number is reasonable, not 1/macheps. The threshold should be compatible with other thresholds used in the code. We set OFFDIG + OFFDIG2 <= .999 =: RELCOND, it corresponds to losing at most 3 decimal digits: 1 / (1 - (OFFDIG + OFFDIG2)) <= 1000 instead of the current OFFDIG + OFFDIG2 < 1 */ yesrel = TRUE_; offdig = 0.; tmp = sqrt((abs(d__[1]))); if (tmp < rmin) { yesrel = FALSE_; } if (! yesrel) { goto L11; } i__1 = *n; for (i__ = 2; i__ <= i__1; ++i__) { tmp2 = sqrt((d__1 = d__[i__], abs(d__1))); if (tmp2 < rmin) { yesrel = FALSE_; } if (! yesrel) { goto L11; } offdig2 = (d__1 = e[i__ - 1], abs(d__1)) / (tmp * tmp2); if (offdig + offdig2 >= .999) { yesrel = FALSE_; } if (! yesrel) { goto L11; } tmp = tmp2; offdig = offdig2; /* L10: */ } L11: if (yesrel) { *info = 0; return 0; } else { } /* *** MORE TO BE IMPLEMENTED *** Test if the lower bidiagonal matrix L from T = L D L^T (zero shift facto) is well conditioned Test if the upper bidiagonal matrix U from T = U D U^T (zero shift facto) is well conditioned. In this case, the matrix needs to be flipped and, at the end of the eigenvector computation, the flip needs to be applied to the computed eigenvectors (and the support) */ return 0; /* END OF DLARRR */ } /* igraphdlarrr_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dstats.c0000644000076500000240000000347213524616145024314 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* \SCCS Information: @(#) FILE: stats.F SID: 2.1 DATE OF SID: 4/19/96 RELEASE: 2 %---------------------------------------------% | Initialize statistic and timing information | | for symmetric Arnoldi code. | %---------------------------------------------% Subroutine */ int igraphdstats_(void) { integer nbx, nopx; real trvec, tmvbx, tgetv0, tsaup2; integer nitref; real titref, tseigt, tsaupd, tsaitr, tsgets, tsapps; integer nrorth; real tsconv; integer nrstrt; real tmvopx; /* %--------------------------------% | See stat.doc for documentation | %--------------------------------% %-----------------------% | Executable Statements | %-----------------------% */ nopx = 0; nbx = 0; nrorth = 0; nitref = 0; nrstrt = 0; tsaupd = 0.f; tsaup2 = 0.f; tsaitr = 0.f; tseigt = 0.f; tsgets = 0.f; tsapps = 0.f; tsconv = 0.f; titref = 0.f; tgetv0 = 0.f; trvec = 0.f; /* %----------------------------------------------------% | User time including reverse communication overhead | %----------------------------------------------------% */ tmvopx = 0.f; tmvbx = 0.f; return 0; /* End of dstats */ } /* igraphdstats_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dsytrd.c0000644000076500000240000003244713524616145024327 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static integer c_n1 = -1; static integer c__3 = 3; static integer c__2 = 2; static doublereal c_b22 = -1.; static doublereal c_b23 = 1.; /* > \brief \b DSYTRD =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DSYTRD + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DSYTRD( UPLO, N, A, LDA, D, E, TAU, WORK, LWORK, INFO ) CHARACTER UPLO INTEGER INFO, LDA, LWORK, N DOUBLE PRECISION A( LDA, * ), D( * ), E( * ), TAU( * ), $ WORK( * ) > \par Purpose: ============= > > \verbatim > > DSYTRD reduces a real symmetric matrix A to real symmetric > tridiagonal form T by an orthogonal similarity transformation: > Q**T * A * Q = T. > \endverbatim Arguments: ========== > \param[in] UPLO > \verbatim > UPLO is CHARACTER*1 > = 'U': Upper triangle of A is stored; > = 'L': Lower triangle of A is stored. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix A. N >= 0. > \endverbatim > > \param[in,out] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,N) > On entry, the symmetric matrix A. If UPLO = 'U', the leading > N-by-N upper triangular part of A contains the upper > triangular part of the matrix A, and the strictly lower > triangular part of A is not referenced. If UPLO = 'L', the > leading N-by-N lower triangular part of A contains the lower > triangular part of the matrix A, and the strictly upper > triangular part of A is not referenced. > On exit, if UPLO = 'U', the diagonal and first superdiagonal > of A are overwritten by the corresponding elements of the > tridiagonal matrix T, and the elements above the first > superdiagonal, with the array TAU, represent the orthogonal > matrix Q as a product of elementary reflectors; if UPLO > = 'L', the diagonal and first subdiagonal of A are over- > written by the corresponding elements of the tridiagonal > matrix T, and the elements below the first subdiagonal, with > the array TAU, represent the orthogonal matrix Q as a product > of elementary reflectors. See Further Details. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. LDA >= max(1,N). > \endverbatim > > \param[out] D > \verbatim > D is DOUBLE PRECISION array, dimension (N) > The diagonal elements of the tridiagonal matrix T: > D(i) = A(i,i). > \endverbatim > > \param[out] E > \verbatim > E is DOUBLE PRECISION array, dimension (N-1) > The off-diagonal elements of the tridiagonal matrix T: > E(i) = A(i,i+1) if UPLO = 'U', E(i) = A(i+1,i) if UPLO = 'L'. > \endverbatim > > \param[out] TAU > \verbatim > TAU is DOUBLE PRECISION array, dimension (N-1) > The scalar factors of the elementary reflectors (see Further > Details). > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (MAX(1,LWORK)) > On exit, if INFO = 0, WORK(1) returns the optimal LWORK. > \endverbatim > > \param[in] LWORK > \verbatim > LWORK is INTEGER > The dimension of the array WORK. LWORK >= 1. > For optimum performance LWORK >= N*NB, where NB is the > optimal blocksize. > > If LWORK = -1, then a workspace query is assumed; the routine > only calculates the optimal size of the WORK array, returns > this value as the first entry of the WORK array, and no error > message related to LWORK is issued by XERBLA. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2011 > \ingroup doubleSYcomputational > \par Further Details: ===================== > > \verbatim > > If UPLO = 'U', the matrix Q is represented as a product of elementary > reflectors > > Q = H(n-1) . . . H(2) H(1). > > Each H(i) has the form > > H(i) = I - tau * v * v**T > > where tau is a real scalar, and v is a real vector with > v(i+1:n) = 0 and v(i) = 1; v(1:i-1) is stored on exit in > A(1:i-1,i+1), and tau in TAU(i). > > If UPLO = 'L', the matrix Q is represented as a product of elementary > reflectors > > Q = H(1) H(2) . . . H(n-1). > > Each H(i) has the form > > H(i) = I - tau * v * v**T > > where tau is a real scalar, and v is a real vector with > v(1:i) = 0 and v(i+1) = 1; v(i+2:n) is stored on exit in A(i+2:n,i), > and tau in TAU(i). > > The contents of A on exit are illustrated by the following examples > with n = 5: > > if UPLO = 'U': if UPLO = 'L': > > ( d e v2 v3 v4 ) ( d ) > ( d e v3 v4 ) ( e d ) > ( d e v4 ) ( v1 e d ) > ( d e ) ( v1 v2 e d ) > ( d ) ( v1 v2 v3 e d ) > > where d and e denote diagonal and off-diagonal elements of T, and vi > denotes an element of the vector defining H(i). > \endverbatim > ===================================================================== Subroutine */ int igraphdsytrd_(char *uplo, integer *n, doublereal *a, integer * lda, doublereal *d__, doublereal *e, doublereal *tau, doublereal * work, integer *lwork, integer *info) { /* System generated locals */ integer a_dim1, a_offset, i__1, i__2, i__3; /* Local variables */ integer i__, j, nb, kk, nx, iws; extern logical igraphlsame_(char *, char *); integer nbmin, iinfo; logical upper; extern /* Subroutine */ int igraphdsytd2_(char *, integer *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, integer *), igraphdsyr2k_(char *, char *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *), igraphdlatrd_(char *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, integer *), igraphxerbla_(char *, integer *, ftnlen); extern integer igraphilaenv_(integer *, char *, char *, integer *, integer *, integer *, integer *, ftnlen, ftnlen); integer ldwork, lwkopt; logical lquery; /* -- LAPACK computational routine (version 3.4.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2011 ===================================================================== Test the input parameters Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --d__; --e; --tau; --work; /* Function Body */ *info = 0; upper = igraphlsame_(uplo, "U"); lquery = *lwork == -1; if (! upper && ! igraphlsame_(uplo, "L")) { *info = -1; } else if (*n < 0) { *info = -2; } else if (*lda < max(1,*n)) { *info = -4; } else if (*lwork < 1 && ! lquery) { *info = -9; } if (*info == 0) { /* Determine the block size. */ nb = igraphilaenv_(&c__1, "DSYTRD", uplo, n, &c_n1, &c_n1, &c_n1, (ftnlen)6, (ftnlen)1); lwkopt = *n * nb; work[1] = (doublereal) lwkopt; } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DSYTRD", &i__1, (ftnlen)6); return 0; } else if (lquery) { return 0; } /* Quick return if possible */ if (*n == 0) { work[1] = 1.; return 0; } nx = *n; iws = 1; if (nb > 1 && nb < *n) { /* Determine when to cross over from blocked to unblocked code (last block is always handled by unblocked code). Computing MAX */ i__1 = nb, i__2 = igraphilaenv_(&c__3, "DSYTRD", uplo, n, &c_n1, &c_n1, & c_n1, (ftnlen)6, (ftnlen)1); nx = max(i__1,i__2); if (nx < *n) { /* Determine if workspace is large enough for blocked code. */ ldwork = *n; iws = ldwork * nb; if (*lwork < iws) { /* Not enough workspace to use optimal NB: determine the minimum value of NB, and reduce NB or force use of unblocked code by setting NX = N. Computing MAX */ i__1 = *lwork / ldwork; nb = max(i__1,1); nbmin = igraphilaenv_(&c__2, "DSYTRD", uplo, n, &c_n1, &c_n1, &c_n1, (ftnlen)6, (ftnlen)1); if (nb < nbmin) { nx = *n; } } } else { nx = *n; } } else { nb = 1; } if (upper) { /* Reduce the upper triangle of A. Columns 1:kk are handled by the unblocked method. */ kk = *n - (*n - nx + nb - 1) / nb * nb; i__1 = kk + 1; i__2 = -nb; for (i__ = *n - nb + 1; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ += i__2) { /* Reduce columns i:i+nb-1 to tridiagonal form and form the matrix W which is needed to update the unreduced part of the matrix */ i__3 = i__ + nb - 1; igraphdlatrd_(uplo, &i__3, &nb, &a[a_offset], lda, &e[1], &tau[1], & work[1], &ldwork); /* Update the unreduced submatrix A(1:i-1,1:i-1), using an update of the form: A := A - V*W**T - W*V**T */ i__3 = i__ - 1; igraphdsyr2k_(uplo, "No transpose", &i__3, &nb, &c_b22, &a[i__ * a_dim1 + 1], lda, &work[1], &ldwork, &c_b23, &a[a_offset], lda); /* Copy superdiagonal elements back into A, and diagonal elements into D */ i__3 = i__ + nb - 1; for (j = i__; j <= i__3; ++j) { a[j - 1 + j * a_dim1] = e[j - 1]; d__[j] = a[j + j * a_dim1]; /* L10: */ } /* L20: */ } /* Use unblocked code to reduce the last or only block */ igraphdsytd2_(uplo, &kk, &a[a_offset], lda, &d__[1], &e[1], &tau[1], &iinfo); } else { /* Reduce the lower triangle of A */ i__2 = *n - nx; i__1 = nb; for (i__ = 1; i__1 < 0 ? i__ >= i__2 : i__ <= i__2; i__ += i__1) { /* Reduce columns i:i+nb-1 to tridiagonal form and form the matrix W which is needed to update the unreduced part of the matrix */ i__3 = *n - i__ + 1; igraphdlatrd_(uplo, &i__3, &nb, &a[i__ + i__ * a_dim1], lda, &e[i__], & tau[i__], &work[1], &ldwork); /* Update the unreduced submatrix A(i+ib:n,i+ib:n), using an update of the form: A := A - V*W**T - W*V**T */ i__3 = *n - i__ - nb + 1; igraphdsyr2k_(uplo, "No transpose", &i__3, &nb, &c_b22, &a[i__ + nb + i__ * a_dim1], lda, &work[nb + 1], &ldwork, &c_b23, &a[ i__ + nb + (i__ + nb) * a_dim1], lda); /* Copy subdiagonal elements back into A, and diagonal elements into D */ i__3 = i__ + nb - 1; for (j = i__; j <= i__3; ++j) { a[j + 1 + j * a_dim1] = e[j]; d__[j] = a[j + j * a_dim1]; /* L30: */ } /* L40: */ } /* Use unblocked code to reduce the last or only block */ i__1 = *n - i__ + 1; igraphdsytd2_(uplo, &i__1, &a[i__ + i__ * a_dim1], lda, &d__[i__], &e[i__], &tau[i__], &iinfo); } work[1] = (doublereal) lwkopt; return 0; /* End of DSYTRD */ } /* igraphdsytrd_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlaisnan.c0000644000076500000240000000633113524616145024600 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLAISNAN tests input for NaN by comparing two arguments for inequality. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLAISNAN + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== LOGICAL FUNCTION DLAISNAN( DIN1, DIN2 ) DOUBLE PRECISION DIN1, DIN2 > \par Purpose: ============= > > \verbatim > > This routine is not for general use. It exists solely to avoid > over-optimization in DISNAN. > > DLAISNAN checks for NaNs by comparing its two arguments for > inequality. NaN is the only floating-point value where NaN != NaN > returns .TRUE. To check for NaNs, pass the same variable as both > arguments. > > A compiler must assume that the two arguments are > not the same variable, and the test will not be optimized away. > Interprocedural or whole-program optimization may delete this > test. The ISNAN functions will be replaced by the correct > Fortran 03 intrinsic once the intrinsic is widely available. > \endverbatim Arguments: ========== > \param[in] DIN1 > \verbatim > DIN1 is DOUBLE PRECISION > \endverbatim > > \param[in] DIN2 > \verbatim > DIN2 is DOUBLE PRECISION > Two numbers to compare for inequality. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERauxiliary ===================================================================== */ logical igraphdlaisnan_(doublereal *din1, doublereal *din2) { /* System generated locals */ logical ret_val; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== */ ret_val = *din1 != *din2; return ret_val; } /* igraphdlaisnan_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dsaitr.c0000644000076500000240000010105313524616145024272 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static logical c_false = FALSE_; static doublereal c_b24 = 1.; static doublereal c_b49 = 0.; static doublereal c_b57 = -1.; static integer c__2 = 2; /* ----------------------------------------------------------------------- \BeginDoc \Name: dsaitr \Description: Reverse communication interface for applying NP additional steps to a K step symmetric Arnoldi factorization. Input: OP*V_{k} - V_{k}*H = r_{k}*e_{k}^T with (V_{k}^T)*B*V_{k} = I, (V_{k}^T)*B*r_{k} = 0. Output: OP*V_{k+p} - V_{k+p}*H = r_{k+p}*e_{k+p}^T with (V_{k+p}^T)*B*V_{k+p} = I, (V_{k+p}^T)*B*r_{k+p} = 0. where OP and B are as in dsaupd. The B-norm of r_{k+p} is also computed and returned. \Usage: call dsaitr ( IDO, BMAT, N, K, NP, MODE, RESID, RNORM, V, LDV, H, LDH, IPNTR, WORKD, INFO ) \Arguments IDO Integer. (INPUT/OUTPUT) Reverse communication flag. ------------------------------------------------------------- IDO = 0: first call to the reverse communication interface IDO = -1: compute Y = OP * X where IPNTR(1) is the pointer into WORK for X, IPNTR(2) is the pointer into WORK for Y. This is for the restart phase to force the new starting vector into the range of OP. IDO = 1: compute Y = OP * X where IPNTR(1) is the pointer into WORK for X, IPNTR(2) is the pointer into WORK for Y, IPNTR(3) is the pointer into WORK for B * X. IDO = 2: compute Y = B * X where IPNTR(1) is the pointer into WORK for X, IPNTR(2) is the pointer into WORK for Y. IDO = 99: done ------------------------------------------------------------- When the routine is used in the "shift-and-invert" mode, the vector B * Q is already available and does not need to be recomputed in forming OP * Q. BMAT Character*1. (INPUT) BMAT specifies the type of matrix B that defines the semi-inner product for the operator OP. See dsaupd. B = 'I' -> standard eigenvalue problem A*x = lambda*x B = 'G' -> generalized eigenvalue problem A*x = lambda*M*x N Integer. (INPUT) Dimension of the eigenproblem. K Integer. (INPUT) Current order of H and the number of columns of V. NP Integer. (INPUT) Number of additional Arnoldi steps to take. MODE Integer. (INPUT) Signifies which form for "OP". If MODE=2 then a reduction in the number of B matrix vector multiplies is possible since the B-norm of OP*x is equivalent to the inv(B)-norm of A*x. RESID Double precision array of length N. (INPUT/OUTPUT) On INPUT: RESID contains the residual vector r_{k}. On OUTPUT: RESID contains the residual vector r_{k+p}. RNORM Double precision scalar. (INPUT/OUTPUT) On INPUT the B-norm of r_{k}. On OUTPUT the B-norm of the updated residual r_{k+p}. V Double precision N by K+NP array. (INPUT/OUTPUT) On INPUT: V contains the Arnoldi vectors in the first K columns. On OUTPUT: V contains the new NP Arnoldi vectors in the next NP columns. The first K columns are unchanged. LDV Integer. (INPUT) Leading dimension of V exactly as declared in the calling program. H Double precision (K+NP) by 2 array. (INPUT/OUTPUT) H is used to store the generated symmetric tridiagonal matrix with the subdiagonal in the first column starting at H(2,1) and the main diagonal in the second column. LDH Integer. (INPUT) Leading dimension of H exactly as declared in the calling program. IPNTR Integer array of length 3. (OUTPUT) Pointer to mark the starting locations in the WORK for vectors used by the Arnoldi iteration. ------------------------------------------------------------- IPNTR(1): pointer to the current operand vector X. IPNTR(2): pointer to the current result vector Y. IPNTR(3): pointer to the vector B * X when used in the shift-and-invert mode. X is the current operand. ------------------------------------------------------------- WORKD Double precision work array of length 3*N. (REVERSE COMMUNICATION) Distributed array to be used in the basic Arnoldi iteration for reverse communication. The calling program should not use WORKD as temporary workspace during the iteration !!!!!! On INPUT, WORKD(1:N) = B*RESID where RESID is associated with the K step Arnoldi factorization. Used to save some computation at the first step. On OUTPUT, WORKD(1:N) = B*RESID where RESID is associated with the K+NP step Arnoldi factorization. INFO Integer. (OUTPUT) = 0: Normal exit. > 0: Size of an invariant subspace of OP is found that is less than K + NP. \EndDoc ----------------------------------------------------------------------- \BeginLib \Local variables: xxxxxx real \Routines called: dgetv0 ARPACK routine to generate the initial vector. ivout ARPACK utility routine that prints integers. dmout ARPACK utility routine that prints matrices. dvout ARPACK utility routine that prints vectors. dlamch LAPACK routine that determines machine constants. dlascl LAPACK routine for careful scaling of a matrix. dgemv Level 2 BLAS routine for matrix vector multiplication. daxpy Level 1 BLAS that computes a vector triad. dscal Level 1 BLAS that scales a vector. dcopy Level 1 BLAS that copies one vector to another . ddot Level 1 BLAS that computes the scalar product of two vectors. dnrm2 Level 1 BLAS that computes the norm of a vector. \Author Danny Sorensen Phuong Vu Richard Lehoucq CRPC / Rice University Dept. of Computational & Houston, Texas Applied Mathematics Rice University Houston, Texas \Revision history: xx/xx/93: Version ' 2.4' \SCCS Information: @(#) FILE: saitr.F SID: 2.6 DATE OF SID: 8/28/96 RELEASE: 2 \Remarks The algorithm implemented is: restart = .false. Given V_{k} = [v_{1}, ..., v_{k}], r_{k}; r_{k} contains the initial residual vector even for k = 0; Also assume that rnorm = || B*r_{k} || and B*r_{k} are already computed by the calling program. betaj = rnorm ; p_{k+1} = B*r_{k} ; For j = k+1, ..., k+np Do 1) if ( betaj < tol ) stop or restart depending on j. if ( restart ) generate a new starting vector. 2) v_{j} = r(j-1)/betaj; V_{j} = [V_{j-1}, v_{j}]; p_{j} = p_{j}/betaj 3) r_{j} = OP*v_{j} where OP is defined as in dsaupd For shift-invert mode p_{j} = B*v_{j} is already available. wnorm = || OP*v_{j} || 4) Compute the j-th step residual vector. w_{j} = V_{j}^T * B * OP * v_{j} r_{j} = OP*v_{j} - V_{j} * w_{j} alphaj <- j-th component of w_{j} rnorm = || r_{j} || betaj+1 = rnorm If (rnorm > 0.717*wnorm) accept step and go back to 1) 5) Re-orthogonalization step: s = V_{j}'*B*r_{j} r_{j} = r_{j} - V_{j}*s; rnorm1 = || r_{j} || alphaj = alphaj + s_{j}; 6) Iterative refinement step: If (rnorm1 > 0.717*rnorm) then rnorm = rnorm1 accept step and go back to 1) Else rnorm = rnorm1 If this is the first time in step 6), go to 5) Else r_{j} lies in the span of V_{j} numerically. Set r_{j} = 0 and rnorm = 0; go to 1) EndIf End Do \EndLib ----------------------------------------------------------------------- Subroutine */ int igraphdsaitr_(integer *ido, char *bmat, integer *n, integer *k, integer *np, integer *mode, doublereal *resid, doublereal *rnorm, doublereal *v, integer *ldv, doublereal *h__, integer *ldh, integer * ipntr, doublereal *workd, integer *info) { /* Initialized data */ IGRAPH_F77_SAVE logical first = TRUE_; /* System generated locals */ integer h_dim1, h_offset, v_dim1, v_offset, i__1; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ integer i__; IGRAPH_F77_SAVE integer j; real t0, t1, t2 = 0.0, t3, t4, t5; integer jj; IGRAPH_F77_SAVE integer ipj, irj; integer nbx = 0; IGRAPH_F77_SAVE integer ivj; extern doublereal igraphddot_(integer *, doublereal *, integer *, doublereal *, integer *); IGRAPH_F77_SAVE integer ierr, iter; integer nopx = 0; IGRAPH_F77_SAVE integer itry; extern doublereal igraphdnrm2_(integer *, doublereal *, integer *); doublereal temp1; IGRAPH_F77_SAVE logical orth1, orth2, step3, step4; extern /* Subroutine */ int igraphdscal_(integer *, doublereal *, doublereal *, integer *), igraphdgemv_(char *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *); integer infol; extern /* Subroutine */ int igraphdcopy_(integer *, doublereal *, integer *, doublereal *, integer *); doublereal xtemp[2]; real tmvbx = 0; extern /* Subroutine */ int igraphdvout_(integer *, integer *, doublereal *, integer *, char *, ftnlen); IGRAPH_F77_SAVE doublereal wnorm; extern /* Subroutine */ int igraphivout_(integer *, integer *, integer *, integer *, char *, ftnlen), igraphdgetv0_(integer *, char *, integer *, logical *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *); IGRAPH_F77_SAVE doublereal rnorm1; extern doublereal igraphdlamch_(char *); extern /* Subroutine */ int igraphdlascl_(char *, integer *, integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, integer *, integer *), igraphsecond_(real *); integer logfil; IGRAPH_F77_SAVE doublereal safmin; integer ndigit = 0, nitref = 0; real titref = 0; integer msaitr = 0; IGRAPH_F77_SAVE integer msglvl; real tsaitr = 0; integer nrorth = 0; IGRAPH_F77_SAVE logical rstart; integer nrstrt = 0; real tmvopx = 0; /* %----------------------------------------------------% | Include files for debugging and timing information | %----------------------------------------------------% %------------------% | Scalar Arguments | %------------------% %-----------------% | Array Arguments | %-----------------% %------------% | Parameters | %------------% %---------------% | Local Scalars | %---------------% %-----------------------% | Local Array Arguments | %-----------------------% %----------------------% | External Subroutines | %----------------------% %--------------------% | External Functions | %--------------------% %-----------------% | Data statements | %-----------------% Parameter adjustments */ --workd; --resid; v_dim1 = *ldv; v_offset = 1 + v_dim1; v -= v_offset; h_dim1 = *ldh; h_offset = 1 + h_dim1; h__ -= h_offset; --ipntr; /* Function Body %-----------------------% | Executable Statements | %-----------------------% */ if (first) { first = FALSE_; /* %--------------------------------% | safmin = safe minimum is such | | that 1/sfmin does not overflow | %--------------------------------% */ safmin = igraphdlamch_("safmin"); } if (*ido == 0) { /* %-------------------------------% | Initialize timing statistics | | & message level for debugging | %-------------------------------% */ igraphsecond_(&t0); msglvl = msaitr; /* %------------------------------% | Initial call to this routine | %------------------------------% */ *info = 0; step3 = FALSE_; step4 = FALSE_; rstart = FALSE_; orth1 = FALSE_; orth2 = FALSE_; /* %--------------------------------% | Pointer to the current step of | | the factorization to build | %--------------------------------% */ j = *k + 1; /* %------------------------------------------% | Pointers used for reverse communication | | when using WORKD. | %------------------------------------------% */ ipj = 1; irj = ipj + *n; ivj = irj + *n; } /* %-------------------------------------------------% | When in reverse communication mode one of: | | STEP3, STEP4, ORTH1, ORTH2, RSTART | | will be .true. | | STEP3: return from computing OP*v_{j}. | | STEP4: return from computing B-norm of OP*v_{j} | | ORTH1: return from computing B-norm of r_{j+1} | | ORTH2: return from computing B-norm of | | correction to the residual vector. | | RSTART: return from OP computations needed by | | dgetv0. | %-------------------------------------------------% */ if (step3) { goto L50; } if (step4) { goto L60; } if (orth1) { goto L70; } if (orth2) { goto L90; } if (rstart) { goto L30; } /* %------------------------------% | Else this is the first step. | %------------------------------% %--------------------------------------------------------------% | | | A R N O L D I I T E R A T I O N L O O P | | | | Note: B*r_{j-1} is already in WORKD(1:N)=WORKD(IPJ:IPJ+N-1) | %--------------------------------------------------------------% */ L1000: if (msglvl > 2) { igraphivout_(&logfil, &c__1, &j, &ndigit, "_saitr: generating Arnoldi vect" "or no.", (ftnlen)37); igraphdvout_(&logfil, &c__1, rnorm, &ndigit, "_saitr: B-norm of the curren" "t residual =", (ftnlen)40); } /* %---------------------------------------------------------% | Check for exact zero. Equivalent to determing whether a | | j-step Arnoldi factorization is present. | %---------------------------------------------------------% */ if (*rnorm > 0.) { goto L40; } /* %---------------------------------------------------% | Invariant subspace found, generate a new starting | | vector which is orthogonal to the current Arnoldi | | basis and continue the iteration. | %---------------------------------------------------% */ if (msglvl > 0) { igraphivout_(&logfil, &c__1, &j, &ndigit, "_saitr: ****** restart at step " "******", (ftnlen)37); } /* %---------------------------------------------% | ITRY is the loop variable that controls the | | maximum amount of times that a restart is | | attempted. NRSTRT is used by stat.h | %---------------------------------------------% */ ++nrstrt; itry = 1; L20: rstart = TRUE_; *ido = 0; L30: /* %--------------------------------------% | If in reverse communication mode and | | RSTART = .true. flow returns here. | %--------------------------------------% */ igraphdgetv0_(ido, bmat, &itry, &c_false, n, &j, &v[v_offset], ldv, &resid[1], rnorm, &ipntr[1], &workd[1], &ierr); if (*ido != 99) { goto L9000; } if (ierr < 0) { ++itry; if (itry <= 3) { goto L20; } /* %------------------------------------------------% | Give up after several restart attempts. | | Set INFO to the size of the invariant subspace | | which spans OP and exit. | %------------------------------------------------% */ *info = j - 1; igraphsecond_(&t1); tsaitr += t1 - t0; *ido = 99; goto L9000; } L40: /* %---------------------------------------------------------% | STEP 2: v_{j} = r_{j-1}/rnorm and p_{j} = p_{j}/rnorm | | Note that p_{j} = B*r_{j-1}. In order to avoid overflow | | when reciprocating a small RNORM, test against lower | | machine bound. | %---------------------------------------------------------% */ igraphdcopy_(n, &resid[1], &c__1, &v[j * v_dim1 + 1], &c__1); if (*rnorm >= safmin) { temp1 = 1. / *rnorm; igraphdscal_(n, &temp1, &v[j * v_dim1 + 1], &c__1); igraphdscal_(n, &temp1, &workd[ipj], &c__1); } else { /* %-----------------------------------------% | To scale both v_{j} and p_{j} carefully | | use LAPACK routine SLASCL | %-----------------------------------------% */ igraphdlascl_("General", &i__, &i__, rnorm, &c_b24, n, &c__1, &v[j * v_dim1 + 1], n, &infol); igraphdlascl_("General", &i__, &i__, rnorm, &c_b24, n, &c__1, &workd[ipj], n, &infol); } /* %------------------------------------------------------% | STEP 3: r_{j} = OP*v_{j}; Note that p_{j} = B*v_{j} | | Note that this is not quite yet r_{j}. See STEP 4 | %------------------------------------------------------% */ step3 = TRUE_; ++nopx; igraphsecond_(&t2); igraphdcopy_(n, &v[j * v_dim1 + 1], &c__1, &workd[ivj], &c__1); ipntr[1] = ivj; ipntr[2] = irj; ipntr[3] = ipj; *ido = 1; /* %-----------------------------------% | Exit in order to compute OP*v_{j} | %-----------------------------------% */ goto L9000; L50: /* %-----------------------------------% | Back from reverse communication; | | WORKD(IRJ:IRJ+N-1) := OP*v_{j}. | %-----------------------------------% */ igraphsecond_(&t3); tmvopx += t3 - t2; step3 = FALSE_; /* %------------------------------------------% | Put another copy of OP*v_{j} into RESID. | %------------------------------------------% */ igraphdcopy_(n, &workd[irj], &c__1, &resid[1], &c__1); /* %-------------------------------------------% | STEP 4: Finish extending the symmetric | | Arnoldi to length j. If MODE = 2 | | then B*OP = B*inv(B)*A = A and | | we don't need to compute B*OP. | | NOTE: If MODE = 2 WORKD(IVJ:IVJ+N-1) is | | assumed to have A*v_{j}. | %-------------------------------------------% */ if (*mode == 2) { goto L65; } igraphsecond_(&t2); if (*(unsigned char *)bmat == 'G') { ++nbx; step4 = TRUE_; ipntr[1] = irj; ipntr[2] = ipj; *ido = 2; /* %-------------------------------------% | Exit in order to compute B*OP*v_{j} | %-------------------------------------% */ goto L9000; } else if (*(unsigned char *)bmat == 'I') { igraphdcopy_(n, &resid[1], &c__1, &workd[ipj], &c__1); } L60: /* %-----------------------------------% | Back from reverse communication; | | WORKD(IPJ:IPJ+N-1) := B*OP*v_{j}. | %-----------------------------------% */ if (*(unsigned char *)bmat == 'G') { igraphsecond_(&t3); tmvbx += t3 - t2; } step4 = FALSE_; /* %-------------------------------------% | The following is needed for STEP 5. | | Compute the B-norm of OP*v_{j}. | %-------------------------------------% */ L65: if (*mode == 2) { /* %----------------------------------% | Note that the B-norm of OP*v_{j} | | is the inv(B)-norm of A*v_{j}. | %----------------------------------% */ wnorm = igraphddot_(n, &resid[1], &c__1, &workd[ivj], &c__1); wnorm = sqrt((abs(wnorm))); } else if (*(unsigned char *)bmat == 'G') { wnorm = igraphddot_(n, &resid[1], &c__1, &workd[ipj], &c__1); wnorm = sqrt((abs(wnorm))); } else if (*(unsigned char *)bmat == 'I') { wnorm = igraphdnrm2_(n, &resid[1], &c__1); } /* %-----------------------------------------% | Compute the j-th residual corresponding | | to the j step factorization. | | Use Classical Gram Schmidt and compute: | | w_{j} <- V_{j}^T * B * OP * v_{j} | | r_{j} <- OP*v_{j} - V_{j} * w_{j} | %-----------------------------------------% %------------------------------------------% | Compute the j Fourier coefficients w_{j} | | WORKD(IPJ:IPJ+N-1) contains B*OP*v_{j}. | %------------------------------------------% */ if (*mode != 2) { igraphdgemv_("T", n, &j, &c_b24, &v[v_offset], ldv, &workd[ipj], &c__1, & c_b49, &workd[irj], &c__1); } else if (*mode == 2) { igraphdgemv_("T", n, &j, &c_b24, &v[v_offset], ldv, &workd[ivj], &c__1, & c_b49, &workd[irj], &c__1); } /* %--------------------------------------% | Orthgonalize r_{j} against V_{j}. | | RESID contains OP*v_{j}. See STEP 3. | %--------------------------------------% */ igraphdgemv_("N", n, &j, &c_b57, &v[v_offset], ldv, &workd[irj], &c__1, &c_b24, &resid[1], &c__1); /* %--------------------------------------% | Extend H to have j rows and columns. | %--------------------------------------% */ h__[j + (h_dim1 << 1)] = workd[irj + j - 1]; if (j == 1 || rstart) { h__[j + h_dim1] = 0.; } else { h__[j + h_dim1] = *rnorm; } igraphsecond_(&t4); orth1 = TRUE_; iter = 0; igraphsecond_(&t2); if (*(unsigned char *)bmat == 'G') { ++nbx; igraphdcopy_(n, &resid[1], &c__1, &workd[irj], &c__1); ipntr[1] = irj; ipntr[2] = ipj; *ido = 2; /* %----------------------------------% | Exit in order to compute B*r_{j} | %----------------------------------% */ goto L9000; } else if (*(unsigned char *)bmat == 'I') { igraphdcopy_(n, &resid[1], &c__1, &workd[ipj], &c__1); } L70: /* %---------------------------------------------------% | Back from reverse communication if ORTH1 = .true. | | WORKD(IPJ:IPJ+N-1) := B*r_{j}. | %---------------------------------------------------% */ if (*(unsigned char *)bmat == 'G') { igraphsecond_(&t3); tmvbx += t3 - t2; } orth1 = FALSE_; /* %------------------------------% | Compute the B-norm of r_{j}. | %------------------------------% */ if (*(unsigned char *)bmat == 'G') { *rnorm = igraphddot_(n, &resid[1], &c__1, &workd[ipj], &c__1); *rnorm = sqrt((abs(*rnorm))); } else if (*(unsigned char *)bmat == 'I') { *rnorm = igraphdnrm2_(n, &resid[1], &c__1); } /* %-----------------------------------------------------------% | STEP 5: Re-orthogonalization / Iterative refinement phase | | Maximum NITER_ITREF tries. | | | | s = V_{j}^T * B * r_{j} | | r_{j} = r_{j} - V_{j}*s | | alphaj = alphaj + s_{j} | | | | The stopping criteria used for iterative refinement is | | discussed in Parlett's book SEP, page 107 and in Gragg & | | Reichel ACM TOMS paper; Algorithm 686, Dec. 1990. | | Determine if we need to correct the residual. The goal is | | to enforce ||v(:,1:j)^T * r_{j}|| .le. eps * || r_{j} || | %-----------------------------------------------------------% */ if (*rnorm > wnorm * .717f) { goto L100; } ++nrorth; /* %---------------------------------------------------% | Enter the Iterative refinement phase. If further | | refinement is necessary, loop back here. The loop | | variable is ITER. Perform a step of Classical | | Gram-Schmidt using all the Arnoldi vectors V_{j} | %---------------------------------------------------% */ L80: if (msglvl > 2) { xtemp[0] = wnorm; xtemp[1] = *rnorm; igraphdvout_(&logfil, &c__2, xtemp, &ndigit, "_saitr: re-orthonalization ;" " wnorm and rnorm are", (ftnlen)48); } /* %----------------------------------------------------% | Compute V_{j}^T * B * r_{j}. | | WORKD(IRJ:IRJ+J-1) = v(:,1:J)'*WORKD(IPJ:IPJ+N-1). | %----------------------------------------------------% */ igraphdgemv_("T", n, &j, &c_b24, &v[v_offset], ldv, &workd[ipj], &c__1, &c_b49, &workd[irj], &c__1); /* %----------------------------------------------% | Compute the correction to the residual: | | r_{j} = r_{j} - V_{j} * WORKD(IRJ:IRJ+J-1). | | The correction to H is v(:,1:J)*H(1:J,1:J) + | | v(:,1:J)*WORKD(IRJ:IRJ+J-1)*e'_j, but only | | H(j,j) is updated. | %----------------------------------------------% */ igraphdgemv_("N", n, &j, &c_b57, &v[v_offset], ldv, &workd[irj], &c__1, &c_b24, &resid[1], &c__1); if (j == 1 || rstart) { h__[j + h_dim1] = 0.; } h__[j + (h_dim1 << 1)] += workd[irj + j - 1]; orth2 = TRUE_; igraphsecond_(&t2); if (*(unsigned char *)bmat == 'G') { ++nbx; igraphdcopy_(n, &resid[1], &c__1, &workd[irj], &c__1); ipntr[1] = irj; ipntr[2] = ipj; *ido = 2; /* %-----------------------------------% | Exit in order to compute B*r_{j}. | | r_{j} is the corrected residual. | %-----------------------------------% */ goto L9000; } else if (*(unsigned char *)bmat == 'I') { igraphdcopy_(n, &resid[1], &c__1, &workd[ipj], &c__1); } L90: /* %---------------------------------------------------% | Back from reverse communication if ORTH2 = .true. | %---------------------------------------------------% */ if (*(unsigned char *)bmat == 'G') { igraphsecond_(&t3); tmvbx += t3 - t2; } /* %-----------------------------------------------------% | Compute the B-norm of the corrected residual r_{j}. | %-----------------------------------------------------% */ if (*(unsigned char *)bmat == 'G') { rnorm1 = igraphddot_(n, &resid[1], &c__1, &workd[ipj], &c__1); rnorm1 = sqrt((abs(rnorm1))); } else if (*(unsigned char *)bmat == 'I') { rnorm1 = igraphdnrm2_(n, &resid[1], &c__1); } if (msglvl > 0 && iter > 0) { igraphivout_(&logfil, &c__1, &j, &ndigit, "_saitr: Iterative refinement fo" "r Arnoldi residual", (ftnlen)49); if (msglvl > 2) { xtemp[0] = *rnorm; xtemp[1] = rnorm1; igraphdvout_(&logfil, &c__2, xtemp, &ndigit, "_saitr: iterative refine" "ment ; rnorm and rnorm1 are", (ftnlen)51); } } /* %-----------------------------------------% | Determine if we need to perform another | | step of re-orthogonalization. | %-----------------------------------------% */ if (rnorm1 > *rnorm * .717f) { /* %--------------------------------% | No need for further refinement | %--------------------------------% */ *rnorm = rnorm1; } else { /* %-------------------------------------------% | Another step of iterative refinement step | | is required. NITREF is used by stat.h | %-------------------------------------------% */ ++nitref; *rnorm = rnorm1; ++iter; if (iter <= 1) { goto L80; } /* %-------------------------------------------------% | Otherwise RESID is numerically in the span of V | %-------------------------------------------------% */ i__1 = *n; for (jj = 1; jj <= i__1; ++jj) { resid[jj] = 0.; /* L95: */ } *rnorm = 0.; } /* %----------------------------------------------% | Branch here directly if iterative refinement | | wasn't necessary or after at most NITER_REF | | steps of iterative refinement. | %----------------------------------------------% */ L100: rstart = FALSE_; orth2 = FALSE_; igraphsecond_(&t5); titref += t5 - t4; /* %----------------------------------------------------------% | Make sure the last off-diagonal element is non negative | | If not perform a similarity transformation on H(1:j,1:j) | | and scale v(:,j) by -1. | %----------------------------------------------------------% */ if (h__[j + h_dim1] < 0.) { h__[j + h_dim1] = -h__[j + h_dim1]; if (j < *k + *np) { igraphdscal_(n, &c_b57, &v[(j + 1) * v_dim1 + 1], &c__1); } else { igraphdscal_(n, &c_b57, &resid[1], &c__1); } } /* %------------------------------------% | STEP 6: Update j = j+1; Continue | %------------------------------------% */ ++j; if (j > *k + *np) { igraphsecond_(&t1); tsaitr += t1 - t0; *ido = 99; if (msglvl > 1) { i__1 = *k + *np; igraphdvout_(&logfil, &i__1, &h__[(h_dim1 << 1) + 1], &ndigit, "_saitr" ": main diagonal of matrix H of step K+NP.", (ftnlen)47); if (*k + *np > 1) { i__1 = *k + *np - 1; igraphdvout_(&logfil, &i__1, &h__[h_dim1 + 2], &ndigit, "_saitr: s" "ub diagonal of matrix H of step K+NP.", (ftnlen)46); } } goto L9000; } /* %--------------------------------------------------------% | Loop back to extend the factorization by another step. | %--------------------------------------------------------% */ goto L1000; /* %---------------------------------------------------------------% | | | E N D O F M A I N I T E R A T I O N L O O P | | | %---------------------------------------------------------------% */ L9000: return 0; /* %---------------% | End of dsaitr | %---------------% */ } /* igraphdsaitr_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dsyevr.c0000644000076500000240000006416513524616145024334 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__10 = 10; static integer c__1 = 1; static integer c__2 = 2; static integer c__3 = 3; static integer c__4 = 4; static integer c_n1 = -1; /* > \brief DSYEVR computes the eigenvalues and, optionally, the left and/or right eigenvectors for SY mat rices =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DSYEVR + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DSYEVR( JOBZ, RANGE, UPLO, N, A, LDA, VL, VU, IL, IU, ABSTOL, M, W, Z, LDZ, ISUPPZ, WORK, LWORK, IWORK, LIWORK, INFO ) CHARACTER JOBZ, RANGE, UPLO INTEGER IL, INFO, IU, LDA, LDZ, LIWORK, LWORK, M, N DOUBLE PRECISION ABSTOL, VL, VU INTEGER ISUPPZ( * ), IWORK( * ) DOUBLE PRECISION A( LDA, * ), W( * ), WORK( * ), Z( LDZ, * ) > \par Purpose: ============= > > \verbatim > > DSYEVR computes selected eigenvalues and, optionally, eigenvectors > of a real symmetric matrix A. Eigenvalues and eigenvectors can be > selected by specifying either a range of values or a range of > indices for the desired eigenvalues. > > DSYEVR first reduces the matrix A to tridiagonal form T with a call > to DSYTRD. Then, whenever possible, DSYEVR calls DSTEMR to compute > the eigenspectrum using Relatively Robust Representations. DSTEMR > computes eigenvalues by the dqds algorithm, while orthogonal > eigenvectors are computed from various "good" L D L^T representations > (also known as Relatively Robust Representations). Gram-Schmidt > orthogonalization is avoided as far as possible. More specifically, > the various steps of the algorithm are as follows. > > For each unreduced block (submatrix) of T, > (a) Compute T - sigma I = L D L^T, so that L and D > define all the wanted eigenvalues to high relative accuracy. > This means that small relative changes in the entries of D and L > cause only small relative changes in the eigenvalues and > eigenvectors. The standard (unfactored) representation of the > tridiagonal matrix T does not have this property in general. > (b) Compute the eigenvalues to suitable accuracy. > If the eigenvectors are desired, the algorithm attains full > accuracy of the computed eigenvalues only right before > the corresponding vectors have to be computed, see steps c) and d). > (c) For each cluster of close eigenvalues, select a new > shift close to the cluster, find a new factorization, and refine > the shifted eigenvalues to suitable accuracy. > (d) For each eigenvalue with a large enough relative separation compute > the corresponding eigenvector by forming a rank revealing twisted > factorization. Go back to (c) for any clusters that remain. > > The desired accuracy of the output can be specified by the input > parameter ABSTOL. > > For more details, see DSTEMR's documentation and: > - Inderjit S. Dhillon and Beresford N. Parlett: "Multiple representations > to compute orthogonal eigenvectors of symmetric tridiagonal matrices," > Linear Algebra and its Applications, 387(1), pp. 1-28, August 2004. > - Inderjit Dhillon and Beresford Parlett: "Orthogonal Eigenvectors and > Relative Gaps," SIAM Journal on Matrix Analysis and Applications, Vol. 25, > 2004. Also LAPACK Working Note 154. > - Inderjit Dhillon: "A new O(n^2) algorithm for the symmetric > tridiagonal eigenvalue/eigenvector problem", > Computer Science Division Technical Report No. UCB/CSD-97-971, > UC Berkeley, May 1997. > > > Note 1 : DSYEVR calls DSTEMR when the full spectrum is requested > on machines which conform to the ieee-754 floating point standard. > DSYEVR calls DSTEBZ and SSTEIN on non-ieee machines and > when partial spectrum requests are made. > > Normal execution of DSTEMR may create NaNs and infinities and > hence may abort due to a floating point exception in environments > which do not handle NaNs and infinities in the ieee standard default > manner. > \endverbatim Arguments: ========== > \param[in] JOBZ > \verbatim > JOBZ is CHARACTER*1 > = 'N': Compute eigenvalues only; > = 'V': Compute eigenvalues and eigenvectors. > \endverbatim > > \param[in] RANGE > \verbatim > RANGE is CHARACTER*1 > = 'A': all eigenvalues will be found. > = 'V': all eigenvalues in the half-open interval (VL,VU] > will be found. > = 'I': the IL-th through IU-th eigenvalues will be found. > For RANGE = 'V' or 'I' and IU - IL < N - 1, DSTEBZ and > DSTEIN are called > \endverbatim > > \param[in] UPLO > \verbatim > UPLO is CHARACTER*1 > = 'U': Upper triangle of A is stored; > = 'L': Lower triangle of A is stored. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix A. N >= 0. > \endverbatim > > \param[in,out] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA, N) > On entry, the symmetric matrix A. If UPLO = 'U', the > leading N-by-N upper triangular part of A contains the > upper triangular part of the matrix A. If UPLO = 'L', > the leading N-by-N lower triangular part of A contains > the lower triangular part of the matrix A. > On exit, the lower triangle (if UPLO='L') or the upper > triangle (if UPLO='U') of A, including the diagonal, is > destroyed. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. LDA >= max(1,N). > \endverbatim > > \param[in] VL > \verbatim > VL is DOUBLE PRECISION > \endverbatim > > \param[in] VU > \verbatim > VU is DOUBLE PRECISION > If RANGE='V', the lower and upper bounds of the interval to > be searched for eigenvalues. VL < VU. > Not referenced if RANGE = 'A' or 'I'. > \endverbatim > > \param[in] IL > \verbatim > IL is INTEGER > \endverbatim > > \param[in] IU > \verbatim > IU is INTEGER > If RANGE='I', the indices (in ascending order) of the > smallest and largest eigenvalues to be returned. > 1 <= IL <= IU <= N, if N > 0; IL = 1 and IU = 0 if N = 0. > Not referenced if RANGE = 'A' or 'V'. > \endverbatim > > \param[in] ABSTOL > \verbatim > ABSTOL is DOUBLE PRECISION > The absolute error tolerance for the eigenvalues. > An approximate eigenvalue is accepted as converged > when it is determined to lie in an interval [a,b] > of width less than or equal to > > ABSTOL + EPS * max( |a|,|b| ) , > > where EPS is the machine precision. If ABSTOL is less than > or equal to zero, then EPS*|T| will be used in its place, > where |T| is the 1-norm of the tridiagonal matrix obtained > by reducing A to tridiagonal form. > > See "Computing Small Singular Values of Bidiagonal Matrices > with Guaranteed High Relative Accuracy," by Demmel and > Kahan, LAPACK Working Note #3. > > If high relative accuracy is important, set ABSTOL to > DLAMCH( 'Safe minimum' ). Doing so will guarantee that > eigenvalues are computed to high relative accuracy when > possible in future releases. The current code does not > make any guarantees about high relative accuracy, but > future releases will. See J. Barlow and J. Demmel, > "Computing Accurate Eigensystems of Scaled Diagonally > Dominant Matrices", LAPACK Working Note #7, for a discussion > of which matrices define their eigenvalues to high relative > accuracy. > \endverbatim > > \param[out] M > \verbatim > M is INTEGER > The total number of eigenvalues found. 0 <= M <= N. > If RANGE = 'A', M = N, and if RANGE = 'I', M = IU-IL+1. > \endverbatim > > \param[out] W > \verbatim > W is DOUBLE PRECISION array, dimension (N) > The first M elements contain the selected eigenvalues in > ascending order. > \endverbatim > > \param[out] Z > \verbatim > Z is DOUBLE PRECISION array, dimension (LDZ, max(1,M)) > If JOBZ = 'V', then if INFO = 0, the first M columns of Z > contain the orthonormal eigenvectors of the matrix A > corresponding to the selected eigenvalues, with the i-th > column of Z holding the eigenvector associated with W(i). > If JOBZ = 'N', then Z is not referenced. > Note: the user must ensure that at least max(1,M) columns are > supplied in the array Z; if RANGE = 'V', the exact value of M > is not known in advance and an upper bound must be used. > Supplying N columns is always safe. > \endverbatim > > \param[in] LDZ > \verbatim > LDZ is INTEGER > The leading dimension of the array Z. LDZ >= 1, and if > JOBZ = 'V', LDZ >= max(1,N). > \endverbatim > > \param[out] ISUPPZ > \verbatim > ISUPPZ is INTEGER array, dimension ( 2*max(1,M) ) > The support of the eigenvectors in Z, i.e., the indices > indicating the nonzero elements in Z. The i-th eigenvector > is nonzero only in elements ISUPPZ( 2*i-1 ) through > ISUPPZ( 2*i ). > Implemented only for RANGE = 'A' or 'I' and IU - IL = N - 1 > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (MAX(1,LWORK)) > On exit, if INFO = 0, WORK(1) returns the optimal LWORK. > \endverbatim > > \param[in] LWORK > \verbatim > LWORK is INTEGER > The dimension of the array WORK. LWORK >= max(1,26*N). > For optimal efficiency, LWORK >= (NB+6)*N, > where NB is the max of the blocksize for DSYTRD and DORMTR > returned by ILAENV. > > If LWORK = -1, then a workspace query is assumed; the routine > only calculates the optimal size of the WORK array, returns > this value as the first entry of the WORK array, and no error > message related to LWORK is issued by XERBLA. > \endverbatim > > \param[out] IWORK > \verbatim > IWORK is INTEGER array, dimension (MAX(1,LIWORK)) > On exit, if INFO = 0, IWORK(1) returns the optimal LWORK. > \endverbatim > > \param[in] LIWORK > \verbatim > LIWORK is INTEGER > The dimension of the array IWORK. LIWORK >= max(1,10*N). > > If LIWORK = -1, then a workspace query is assumed; the > routine only calculates the optimal size of the IWORK array, > returns this value as the first entry of the IWORK array, and > no error message related to LIWORK is issued by XERBLA. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value > > 0: Internal error > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleSYeigen > \par Contributors: ================== > > Inderjit Dhillon, IBM Almaden, USA \n > Osni Marques, LBNL/NERSC, USA \n > Ken Stanley, Computer Science Division, University of > California at Berkeley, USA \n > Jason Riedy, Computer Science Division, University of > California at Berkeley, USA \n > ===================================================================== Subroutine */ int igraphdsyevr_(char *jobz, char *range, char *uplo, integer *n, doublereal *a, integer *lda, doublereal *vl, doublereal *vu, integer * il, integer *iu, doublereal *abstol, integer *m, doublereal *w, doublereal *z__, integer *ldz, integer *isuppz, doublereal *work, integer *lwork, integer *iwork, integer *liwork, integer *info) { /* System generated locals */ integer a_dim1, a_offset, z_dim1, z_offset, i__1, i__2; doublereal d__1, d__2; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ integer i__, j, nb, jj; doublereal eps, vll, vuu, tmp1; integer indd, inde; doublereal anrm; integer imax; doublereal rmin, rmax; integer inddd, indee; extern /* Subroutine */ int igraphdscal_(integer *, doublereal *, doublereal *, integer *); doublereal sigma; extern logical igraphlsame_(char *, char *); integer iinfo; char order[1]; integer indwk; extern /* Subroutine */ int igraphdcopy_(integer *, doublereal *, integer *, doublereal *, integer *), igraphdswap_(integer *, doublereal *, integer *, doublereal *, integer *); integer lwmin; logical lower, wantz; extern doublereal igraphdlamch_(char *); logical alleig, indeig; integer iscale, ieeeok, indibl, indifl; logical valeig; doublereal safmin; extern integer igraphilaenv_(integer *, char *, char *, integer *, integer *, integer *, integer *, ftnlen, ftnlen); extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); doublereal abstll, bignum; integer indtau, indisp; extern /* Subroutine */ int igraphdstein_(integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, integer *, doublereal *, integer *, doublereal *, integer *, integer *, integer *), igraphdsterf_(integer *, doublereal *, doublereal *, integer *); integer indiwo, indwkn; extern doublereal igraphdlansy_(char *, char *, integer *, doublereal *, integer *, doublereal *); extern /* Subroutine */ int igraphdstebz_(char *, char *, integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *, integer *, doublereal *, integer *, integer *, doublereal *, integer *, integer *), igraphdstemr_(char *, char *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, integer *, integer *, integer *, doublereal *, doublereal *, integer *, integer *, integer *, logical *, doublereal *, integer *, integer *, integer *, integer *); integer liwmin; logical tryrac; extern /* Subroutine */ int igraphdormtr_(char *, char *, char *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, integer *); integer llwrkn, llwork, nsplit; doublereal smlnum; extern /* Subroutine */ int igraphdsytrd_(char *, integer *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, integer *, integer *); integer lwkopt; logical lquery; /* -- LAPACK driver routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Test the input parameters. Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --w; z_dim1 = *ldz; z_offset = 1 + z_dim1; z__ -= z_offset; --isuppz; --work; --iwork; /* Function Body */ ieeeok = igraphilaenv_(&c__10, "DSYEVR", "N", &c__1, &c__2, &c__3, &c__4, ( ftnlen)6, (ftnlen)1); lower = igraphlsame_(uplo, "L"); wantz = igraphlsame_(jobz, "V"); alleig = igraphlsame_(range, "A"); valeig = igraphlsame_(range, "V"); indeig = igraphlsame_(range, "I"); lquery = *lwork == -1 || *liwork == -1; /* Computing MAX */ i__1 = 1, i__2 = *n * 26; lwmin = max(i__1,i__2); /* Computing MAX */ i__1 = 1, i__2 = *n * 10; liwmin = max(i__1,i__2); *info = 0; if (! (wantz || igraphlsame_(jobz, "N"))) { *info = -1; } else if (! (alleig || valeig || indeig)) { *info = -2; } else if (! (lower || igraphlsame_(uplo, "U"))) { *info = -3; } else if (*n < 0) { *info = -4; } else if (*lda < max(1,*n)) { *info = -6; } else { if (valeig) { if (*n > 0 && *vu <= *vl) { *info = -8; } } else if (indeig) { if (*il < 1 || *il > max(1,*n)) { *info = -9; } else if (*iu < min(*n,*il) || *iu > *n) { *info = -10; } } } if (*info == 0) { if (*ldz < 1 || wantz && *ldz < *n) { *info = -15; } else if (*lwork < lwmin && ! lquery) { *info = -18; } else if (*liwork < liwmin && ! lquery) { *info = -20; } } if (*info == 0) { nb = igraphilaenv_(&c__1, "DSYTRD", uplo, n, &c_n1, &c_n1, &c_n1, (ftnlen)6, (ftnlen)1); /* Computing MAX */ i__1 = nb, i__2 = igraphilaenv_(&c__1, "DORMTR", uplo, n, &c_n1, &c_n1, & c_n1, (ftnlen)6, (ftnlen)1); nb = max(i__1,i__2); /* Computing MAX */ i__1 = (nb + 1) * *n; lwkopt = max(i__1,lwmin); work[1] = (doublereal) lwkopt; iwork[1] = liwmin; } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DSYEVR", &i__1, (ftnlen)6); return 0; } else if (lquery) { return 0; } /* Quick return if possible */ *m = 0; if (*n == 0) { work[1] = 1.; return 0; } if (*n == 1) { work[1] = 7.; if (alleig || indeig) { *m = 1; w[1] = a[a_dim1 + 1]; } else { if (*vl < a[a_dim1 + 1] && *vu >= a[a_dim1 + 1]) { *m = 1; w[1] = a[a_dim1 + 1]; } } if (wantz) { z__[z_dim1 + 1] = 1.; isuppz[1] = 1; isuppz[2] = 1; } return 0; } /* Get machine constants. */ safmin = igraphdlamch_("Safe minimum"); eps = igraphdlamch_("Precision"); smlnum = safmin / eps; bignum = 1. / smlnum; rmin = sqrt(smlnum); /* Computing MIN */ d__1 = sqrt(bignum), d__2 = 1. / sqrt(sqrt(safmin)); rmax = min(d__1,d__2); /* Scale matrix to allowable range, if necessary. */ iscale = 0; abstll = *abstol; if (valeig) { vll = *vl; vuu = *vu; } anrm = igraphdlansy_("M", uplo, n, &a[a_offset], lda, &work[1]); if (anrm > 0. && anrm < rmin) { iscale = 1; sigma = rmin / anrm; } else if (anrm > rmax) { iscale = 1; sigma = rmax / anrm; } if (iscale == 1) { if (lower) { i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = *n - j + 1; igraphdscal_(&i__2, &sigma, &a[j + j * a_dim1], &c__1); /* L10: */ } } else { i__1 = *n; for (j = 1; j <= i__1; ++j) { igraphdscal_(&j, &sigma, &a[j * a_dim1 + 1], &c__1); /* L20: */ } } if (*abstol > 0.) { abstll = *abstol * sigma; } if (valeig) { vll = *vl * sigma; vuu = *vu * sigma; } } /* Initialize indices into workspaces. Note: The IWORK indices are used only if DSTERF or DSTEMR fail. WORK(INDTAU:INDTAU+N-1) stores the scalar factors of the elementary reflectors used in DSYTRD. */ indtau = 1; /* WORK(INDD:INDD+N-1) stores the tridiagonal's diagonal entries. */ indd = indtau + *n; /* WORK(INDE:INDE+N-1) stores the off-diagonal entries of the tridiagonal matrix from DSYTRD. */ inde = indd + *n; /* WORK(INDDD:INDDD+N-1) is a copy of the diagonal entries over -written by DSTEMR (the DSTERF path copies the diagonal to W). */ inddd = inde + *n; /* WORK(INDEE:INDEE+N-1) is a copy of the off-diagonal entries over -written while computing the eigenvalues in DSTERF and DSTEMR. */ indee = inddd + *n; /* INDWK is the starting offset of the left-over workspace, and LLWORK is the remaining workspace size. */ indwk = indee + *n; llwork = *lwork - indwk + 1; /* IWORK(INDIBL:INDIBL+M-1) corresponds to IBLOCK in DSTEBZ and stores the block indices of each of the M<=N eigenvalues. */ indibl = 1; /* IWORK(INDISP:INDISP+NSPLIT-1) corresponds to ISPLIT in DSTEBZ and stores the starting and finishing indices of each block. */ indisp = indibl + *n; /* IWORK(INDIFL:INDIFL+N-1) stores the indices of eigenvectors that corresponding to eigenvectors that fail to converge in DSTEIN. This information is discarded; if any fail, the driver returns INFO > 0. */ indifl = indisp + *n; /* INDIWO is the offset of the remaining integer workspace. */ indiwo = indifl + *n; /* Call DSYTRD to reduce symmetric matrix to tridiagonal form. */ igraphdsytrd_(uplo, n, &a[a_offset], lda, &work[indd], &work[inde], &work[ indtau], &work[indwk], &llwork, &iinfo); /* If all eigenvalues are desired then call DSTERF or DSTEMR and DORMTR. */ if ((alleig || indeig && *il == 1 && *iu == *n) && ieeeok == 1) { if (! wantz) { igraphdcopy_(n, &work[indd], &c__1, &w[1], &c__1); i__1 = *n - 1; igraphdcopy_(&i__1, &work[inde], &c__1, &work[indee], &c__1); igraphdsterf_(n, &w[1], &work[indee], info); } else { i__1 = *n - 1; igraphdcopy_(&i__1, &work[inde], &c__1, &work[indee], &c__1); igraphdcopy_(n, &work[indd], &c__1, &work[inddd], &c__1); if (*abstol <= *n * 2. * eps) { tryrac = TRUE_; } else { tryrac = FALSE_; } igraphdstemr_(jobz, "A", n, &work[inddd], &work[indee], vl, vu, il, iu, m, &w[1], &z__[z_offset], ldz, n, &isuppz[1], &tryrac, & work[indwk], lwork, &iwork[1], liwork, info); /* Apply orthogonal matrix used in reduction to tridiagonal form to eigenvectors returned by DSTEIN. */ if (wantz && *info == 0) { indwkn = inde; llwrkn = *lwork - indwkn + 1; igraphdormtr_("L", uplo, "N", n, m, &a[a_offset], lda, &work[indtau] , &z__[z_offset], ldz, &work[indwkn], &llwrkn, &iinfo); } } if (*info == 0) { /* Everything worked. Skip DSTEBZ/DSTEIN. IWORK(:) are undefined. */ *m = *n; goto L30; } *info = 0; } /* Otherwise, call DSTEBZ and, if eigenvectors are desired, DSTEIN. Also call DSTEBZ and DSTEIN if DSTEMR fails. */ if (wantz) { *(unsigned char *)order = 'B'; } else { *(unsigned char *)order = 'E'; } igraphdstebz_(range, order, n, &vll, &vuu, il, iu, &abstll, &work[indd], &work[ inde], m, &nsplit, &w[1], &iwork[indibl], &iwork[indisp], &work[ indwk], &iwork[indiwo], info); if (wantz) { igraphdstein_(n, &work[indd], &work[inde], m, &w[1], &iwork[indibl], &iwork[ indisp], &z__[z_offset], ldz, &work[indwk], &iwork[indiwo], & iwork[indifl], info); /* Apply orthogonal matrix used in reduction to tridiagonal form to eigenvectors returned by DSTEIN. */ indwkn = inde; llwrkn = *lwork - indwkn + 1; igraphdormtr_("L", uplo, "N", n, m, &a[a_offset], lda, &work[indtau], &z__[ z_offset], ldz, &work[indwkn], &llwrkn, &iinfo); } /* If matrix was scaled, then rescale eigenvalues appropriately. Jump here if DSTEMR/DSTEIN succeeded. */ L30: if (iscale == 1) { if (*info == 0) { imax = *m; } else { imax = *info - 1; } d__1 = 1. / sigma; igraphdscal_(&imax, &d__1, &w[1], &c__1); } /* If eigenvalues are not in order, then sort them, along with eigenvectors. Note: We do not sort the IFAIL portion of IWORK. It may not be initialized (if DSTEMR/DSTEIN succeeded), and we do not return this detailed information to the user. */ if (wantz) { i__1 = *m - 1; for (j = 1; j <= i__1; ++j) { i__ = 0; tmp1 = w[j]; i__2 = *m; for (jj = j + 1; jj <= i__2; ++jj) { if (w[jj] < tmp1) { i__ = jj; tmp1 = w[jj]; } /* L40: */ } if (i__ != 0) { w[i__] = w[j]; w[j] = tmp1; igraphdswap_(n, &z__[i__ * z_dim1 + 1], &c__1, &z__[j * z_dim1 + 1], &c__1); } /* L50: */ } } /* Set WORK(1) to optimal workspace size. */ work[1] = (doublereal) lwkopt; iwork[1] = liwmin; return 0; /* End of DSYEVR */ } /* igraphdsyevr_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dnapps.c0000644000076500000240000006640713524616145024306 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static doublereal c_b5 = 0.; static doublereal c_b6 = 1.; static integer c__1 = 1; static doublereal c_b43 = -1.; /* ----------------------------------------------------------------------- \BeginDoc \Name: dnapps \Description: Given the Arnoldi factorization A*V_{k} - V_{k}*H_{k} = r_{k+p}*e_{k+p}^T, apply NP implicit shifts resulting in A*(V_{k}*Q) - (V_{k}*Q)*(Q^T* H_{k}*Q) = r_{k+p}*e_{k+p}^T * Q where Q is an orthogonal matrix which is the product of rotations and reflections resulting from the NP bulge chage sweeps. The updated Arnoldi factorization becomes: A*VNEW_{k} - VNEW_{k}*HNEW_{k} = rnew_{k}*e_{k}^T. \Usage: call dnapps ( N, KEV, NP, SHIFTR, SHIFTI, V, LDV, H, LDH, RESID, Q, LDQ, WORKL, WORKD ) \Arguments N Integer. (INPUT) Problem size, i.e. size of matrix A. KEV Integer. (INPUT/OUTPUT) KEV+NP is the size of the input matrix H. KEV is the size of the updated matrix HNEW. KEV is only updated on ouput when fewer than NP shifts are applied in order to keep the conjugate pair together. NP Integer. (INPUT) Number of implicit shifts to be applied. SHIFTR, Double precision array of length NP. (INPUT) SHIFTI Real and imaginary part of the shifts to be applied. Upon, entry to dnapps, the shifts must be sorted so that the conjugate pairs are in consecutive locations. V Double precision N by (KEV+NP) array. (INPUT/OUTPUT) On INPUT, V contains the current KEV+NP Arnoldi vectors. On OUTPUT, V contains the updated KEV Arnoldi vectors in the first KEV columns of V. LDV Integer. (INPUT) Leading dimension of V exactly as declared in the calling program. H Double precision (KEV+NP) by (KEV+NP) array. (INPUT/OUTPUT) On INPUT, H contains the current KEV+NP by KEV+NP upper Hessenber matrix of the Arnoldi factorization. On OUTPUT, H contains the updated KEV by KEV upper Hessenberg matrix in the KEV leading submatrix. LDH Integer. (INPUT) Leading dimension of H exactly as declared in the calling program. RESID Double precision array of length N. (INPUT/OUTPUT) On INPUT, RESID contains the the residual vector r_{k+p}. On OUTPUT, RESID is the update residual vector rnew_{k} in the first KEV locations. Q Double precision KEV+NP by KEV+NP work array. (WORKSPACE) Work array used to accumulate the rotations and reflections during the bulge chase sweep. LDQ Integer. (INPUT) Leading dimension of Q exactly as declared in the calling program. WORKL Double precision work array of length (KEV+NP). (WORKSPACE) Private (replicated) array on each PE or array allocated on the front end. WORKD Double precision work array of length 2*N. (WORKSPACE) Distributed array used in the application of the accumulated orthogonal matrix Q. \EndDoc ----------------------------------------------------------------------- \BeginLib \Local variables: xxxxxx real \References: 1. D.C. Sorensen, "Implicit Application of Polynomial Filters in a k-Step Arnoldi Method", SIAM J. Matr. Anal. Apps., 13 (1992), pp 357-385. \Routines called: ivout ARPACK utility routine that prints integers. second ARPACK utility routine for timing. dmout ARPACK utility routine that prints matrices. dvout ARPACK utility routine that prints vectors. dlabad LAPACK routine that computes machine constants. dlacpy LAPACK matrix copy routine. dlamch LAPACK routine that determines machine constants. dlanhs LAPACK routine that computes various norms of a matrix. dlapy2 LAPACK routine to compute sqrt(x**2+y**2) carefully. dlarf LAPACK routine that applies Householder reflection to a matrix. dlarfg LAPACK Householder reflection construction routine. dlartg LAPACK Givens rotation construction routine. dlaset LAPACK matrix initialization routine. dgemv Level 2 BLAS routine for matrix vector multiplication. daxpy Level 1 BLAS that computes a vector triad. dcopy Level 1 BLAS that copies one vector to another . dscal Level 1 BLAS that scales a vector. \Author Danny Sorensen Phuong Vu Richard Lehoucq CRPC / Rice University Dept. of Computational & Houston, Texas Applied Mathematics Rice University Houston, Texas \Revision history: xx/xx/92: Version ' 2.1' \SCCS Information: @(#) FILE: napps.F SID: 2.3 DATE OF SID: 4/20/96 RELEASE: 2 \Remarks 1. In this version, each shift is applied to all the sublocks of the Hessenberg matrix H and not just to the submatrix that it comes from. Deflation as in LAPACK routine dlahqr (QR algorithm for upper Hessenberg matrices ) is used. The subdiagonals of H are enforced to be non-negative. \EndLib ----------------------------------------------------------------------- Subroutine */ int igraphdnapps_(integer *n, integer *kev, integer *np, doublereal *shiftr, doublereal *shifti, doublereal *v, integer *ldv, doublereal *h__, integer *ldh, doublereal *resid, doublereal *q, integer *ldq, doublereal *workl, doublereal *workd) { /* Initialized data */ IGRAPH_F77_SAVE logical first = TRUE_; /* System generated locals */ integer h_dim1, h_offset, v_dim1, v_offset, q_dim1, q_offset, i__1, i__2, i__3, i__4; doublereal d__1, d__2; /* Local variables */ doublereal c__, f, g; integer i__, j; doublereal r__, s, t, u[3]; real t0, t1; doublereal h11, h12, h21, h22, h32; integer jj, ir, nr; doublereal tau; IGRAPH_F77_SAVE doublereal ulp; doublereal tst1; integer iend; IGRAPH_F77_SAVE doublereal unfl, ovfl; extern /* Subroutine */ int igraphdscal_(integer *, doublereal *, doublereal *, integer *), igraphdlarf_(char *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *); logical cconj; extern /* Subroutine */ int igraphdgemv_(char *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *), igraphdcopy_(integer *, doublereal *, integer *, doublereal *, integer *), igraphdaxpy_(integer *, doublereal *, doublereal *, integer *, doublereal *, integer *) , igraphdmout_(integer *, integer *, integer *, doublereal *, integer *, integer *, char *, ftnlen), igraphdvout_(integer *, integer *, doublereal *, integer *, char *, ftnlen), igraphivout_(integer *, integer *, integer *, integer *, char *, ftnlen); extern doublereal igraphdlapy2_(doublereal *, doublereal *); extern /* Subroutine */ int igraphdlabad_(doublereal *, doublereal *); extern doublereal igraphdlamch_(char *); extern /* Subroutine */ int igraphdlarfg_(integer *, doublereal *, doublereal *, integer *, doublereal *); doublereal sigmai; extern doublereal igraphdlanhs_(char *, integer *, doublereal *, integer *, doublereal *); extern /* Subroutine */ int igraphsecond_(real *), igraphdlacpy_(char *, integer *, integer *, doublereal *, integer *, doublereal *, integer *), igraphdlaset_(char *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *), igraphdlartg_( doublereal *, doublereal *, doublereal *, doublereal *, doublereal *); integer logfil, ndigit; doublereal sigmar; integer mnapps = 0, msglvl; real tnapps = 0.; integer istart; IGRAPH_F77_SAVE doublereal smlnum; integer kplusp; /* %----------------------------------------------------% | Include files for debugging and timing information | %----------------------------------------------------% %------------------% | Scalar Arguments | %------------------% %-----------------% | Array Arguments | %-----------------% %------------% | Parameters | %------------% %------------------------% | Local Scalars & Arrays | %------------------------% %----------------------% | External Subroutines | %----------------------% %--------------------% | External Functions | %--------------------% %----------------------% | Intrinsics Functions | %----------------------% %----------------% | Data statments | %----------------% Parameter adjustments */ --workd; --resid; --workl; --shifti; --shiftr; v_dim1 = *ldv; v_offset = 1 + v_dim1; v -= v_offset; h_dim1 = *ldh; h_offset = 1 + h_dim1; h__ -= h_offset; q_dim1 = *ldq; q_offset = 1 + q_dim1; q -= q_offset; /* Function Body %-----------------------% | Executable Statements | %-----------------------% */ if (first) { /* %-----------------------------------------------% | Set machine-dependent constants for the | | stopping criterion. If norm(H) <= sqrt(OVFL), | | overflow should not occur. | | REFERENCE: LAPACK subroutine dlahqr | %-----------------------------------------------% */ unfl = igraphdlamch_("safe minimum"); ovfl = 1. / unfl; igraphdlabad_(&unfl, &ovfl); ulp = igraphdlamch_("precision"); smlnum = unfl * (*n / ulp); first = FALSE_; } /* %-------------------------------% | Initialize timing statistics | | & message level for debugging | %-------------------------------% */ igraphsecond_(&t0); msglvl = mnapps; kplusp = *kev + *np; /* %--------------------------------------------% | Initialize Q to the identity to accumulate | | the rotations and reflections | %--------------------------------------------% */ igraphdlaset_("All", &kplusp, &kplusp, &c_b5, &c_b6, &q[q_offset], ldq); /* %----------------------------------------------% | Quick return if there are no shifts to apply | %----------------------------------------------% */ if (*np == 0) { goto L9000; } /* %----------------------------------------------% | Chase the bulge with the application of each | | implicit shift. Each shift is applied to the | | whole matrix including each block. | %----------------------------------------------% */ cconj = FALSE_; i__1 = *np; for (jj = 1; jj <= i__1; ++jj) { sigmar = shiftr[jj]; sigmai = shifti[jj]; if (msglvl > 2) { igraphivout_(&logfil, &c__1, &jj, &ndigit, "_napps: shift number.", ( ftnlen)21); igraphdvout_(&logfil, &c__1, &sigmar, &ndigit, "_napps: The real part " "of the shift ", (ftnlen)35); igraphdvout_(&logfil, &c__1, &sigmai, &ndigit, "_napps: The imaginary " "part of the shift ", (ftnlen)40); } /* %-------------------------------------------------% | The following set of conditionals is necessary | | in order that complex conjugate pairs of shifts | | are applied together or not at all. | %-------------------------------------------------% */ if (cconj) { /* %-----------------------------------------% | cconj = .true. means the previous shift | | had non-zero imaginary part. | %-----------------------------------------% */ cconj = FALSE_; goto L110; } else if (jj < *np && abs(sigmai) > 0.) { /* %------------------------------------% | Start of a complex conjugate pair. | %------------------------------------% */ cconj = TRUE_; } else if (jj == *np && abs(sigmai) > 0.) { /* %----------------------------------------------% | The last shift has a nonzero imaginary part. | | Don't apply it; thus the order of the | | compressed H is order KEV+1 since only np-1 | | were applied. | %----------------------------------------------% */ ++(*kev); goto L110; } istart = 1; L20: /* %--------------------------------------------------% | if sigmai = 0 then | | Apply the jj-th shift ... | | else | | Apply the jj-th and (jj+1)-th together ... | | (Note that jj < np at this point in the code) | | end | | to the current block of H. The next do loop | | determines the current block ; | %--------------------------------------------------% */ i__2 = kplusp - 1; for (i__ = istart; i__ <= i__2; ++i__) { /* %----------------------------------------% | Check for splitting and deflation. Use | | a standard test as in the QR algorithm | | REFERENCE: LAPACK subroutine dlahqr | %----------------------------------------% */ tst1 = (d__1 = h__[i__ + i__ * h_dim1], abs(d__1)) + (d__2 = h__[ i__ + 1 + (i__ + 1) * h_dim1], abs(d__2)); if (tst1 == 0.) { i__3 = kplusp - jj + 1; tst1 = igraphdlanhs_("1", &i__3, &h__[h_offset], ldh, &workl[1]); } /* Computing MAX */ d__2 = ulp * tst1; if ((d__1 = h__[i__ + 1 + i__ * h_dim1], abs(d__1)) <= max(d__2, smlnum)) { if (msglvl > 0) { igraphivout_(&logfil, &c__1, &i__, &ndigit, "_napps: matrix sp" "litting at row/column no.", (ftnlen)42); igraphivout_(&logfil, &c__1, &jj, &ndigit, "_napps: matrix spl" "itting with shift number.", (ftnlen)43); igraphdvout_(&logfil, &c__1, &h__[i__ + 1 + i__ * h_dim1], & ndigit, "_napps: off diagonal element.", (ftnlen) 29); } iend = i__; h__[i__ + 1 + i__ * h_dim1] = 0.; goto L40; } /* L30: */ } iend = kplusp; L40: if (msglvl > 2) { igraphivout_(&logfil, &c__1, &istart, &ndigit, "_napps: Start of curre" "nt block ", (ftnlen)31); igraphivout_(&logfil, &c__1, &iend, &ndigit, "_napps: End of current b" "lock ", (ftnlen)29); } /* %------------------------------------------------% | No reason to apply a shift to block of order 1 | %------------------------------------------------% */ if (istart == iend) { goto L100; } /* %------------------------------------------------------% | If istart + 1 = iend then no reason to apply a | | complex conjugate pair of shifts on a 2 by 2 matrix. | %------------------------------------------------------% */ if (istart + 1 == iend && abs(sigmai) > 0.) { goto L100; } h11 = h__[istart + istart * h_dim1]; h21 = h__[istart + 1 + istart * h_dim1]; if (abs(sigmai) <= 0.) { /* %---------------------------------------------% | Real-valued shift ==> apply single shift QR | %---------------------------------------------% */ f = h11 - sigmar; g = h21; i__2 = iend - 1; for (i__ = istart; i__ <= i__2; ++i__) { /* %-----------------------------------------------------% | Contruct the plane rotation G to zero out the bulge | %-----------------------------------------------------% */ igraphdlartg_(&f, &g, &c__, &s, &r__); if (i__ > istart) { /* %-------------------------------------------% | The following ensures that h(1:iend-1,1), | | the first iend-2 off diagonal of elements | | H, remain non negative. | %-------------------------------------------% */ if (r__ < 0.) { r__ = -r__; c__ = -c__; s = -s; } h__[i__ + (i__ - 1) * h_dim1] = r__; h__[i__ + 1 + (i__ - 1) * h_dim1] = 0.; } /* %---------------------------------------------% | Apply rotation to the left of H; H <- G'*H | %---------------------------------------------% */ i__3 = kplusp; for (j = i__; j <= i__3; ++j) { t = c__ * h__[i__ + j * h_dim1] + s * h__[i__ + 1 + j * h_dim1]; h__[i__ + 1 + j * h_dim1] = -s * h__[i__ + j * h_dim1] + c__ * h__[i__ + 1 + j * h_dim1]; h__[i__ + j * h_dim1] = t; /* L50: */ } /* %---------------------------------------------% | Apply rotation to the right of H; H <- H*G | %---------------------------------------------% Computing MIN */ i__4 = i__ + 2; i__3 = min(i__4,iend); for (j = 1; j <= i__3; ++j) { t = c__ * h__[j + i__ * h_dim1] + s * h__[j + (i__ + 1) * h_dim1]; h__[j + (i__ + 1) * h_dim1] = -s * h__[j + i__ * h_dim1] + c__ * h__[j + (i__ + 1) * h_dim1]; h__[j + i__ * h_dim1] = t; /* L60: */ } /* %----------------------------------------------------% | Accumulate the rotation in the matrix Q; Q <- Q*G | %----------------------------------------------------% Computing MIN */ i__4 = j + jj; i__3 = min(i__4,kplusp); for (j = 1; j <= i__3; ++j) { t = c__ * q[j + i__ * q_dim1] + s * q[j + (i__ + 1) * q_dim1]; q[j + (i__ + 1) * q_dim1] = -s * q[j + i__ * q_dim1] + c__ * q[j + (i__ + 1) * q_dim1]; q[j + i__ * q_dim1] = t; /* L70: */ } /* %---------------------------% | Prepare for next rotation | %---------------------------% */ if (i__ < iend - 1) { f = h__[i__ + 1 + i__ * h_dim1]; g = h__[i__ + 2 + i__ * h_dim1]; } /* L80: */ } /* %-----------------------------------% | Finished applying the real shift. | %-----------------------------------% */ } else { /* %----------------------------------------------------% | Complex conjugate shifts ==> apply double shift QR | %----------------------------------------------------% */ h12 = h__[istart + (istart + 1) * h_dim1]; h22 = h__[istart + 1 + (istart + 1) * h_dim1]; h32 = h__[istart + 2 + (istart + 1) * h_dim1]; /* %---------------------------------------------------------% | Compute 1st column of (H - shift*I)*(H - conj(shift)*I) | %---------------------------------------------------------% */ s = sigmar * 2.f; t = igraphdlapy2_(&sigmar, &sigmai); u[0] = (h11 * (h11 - s) + t * t) / h21 + h12; u[1] = h11 + h22 - s; u[2] = h32; i__2 = iend - 1; for (i__ = istart; i__ <= i__2; ++i__) { /* Computing MIN */ i__3 = 3, i__4 = iend - i__ + 1; nr = min(i__3,i__4); /* %-----------------------------------------------------% | Construct Householder reflector G to zero out u(1). | | G is of the form I - tau*( 1 u )' * ( 1 u' ). | %-----------------------------------------------------% */ igraphdlarfg_(&nr, u, &u[1], &c__1, &tau); if (i__ > istart) { h__[i__ + (i__ - 1) * h_dim1] = u[0]; h__[i__ + 1 + (i__ - 1) * h_dim1] = 0.; if (i__ < iend - 1) { h__[i__ + 2 + (i__ - 1) * h_dim1] = 0.; } } u[0] = 1.; /* %--------------------------------------% | Apply the reflector to the left of H | %--------------------------------------% */ i__3 = kplusp - i__ + 1; igraphdlarf_("Left", &nr, &i__3, u, &c__1, &tau, &h__[i__ + i__ * h_dim1], ldh, &workl[1]); /* %---------------------------------------% | Apply the reflector to the right of H | %---------------------------------------% Computing MIN */ i__3 = i__ + 3; ir = min(i__3,iend); igraphdlarf_("Right", &ir, &nr, u, &c__1, &tau, &h__[i__ * h_dim1 + 1], ldh, &workl[1]); /* %-----------------------------------------------------% | Accumulate the reflector in the matrix Q; Q <- Q*G | %-----------------------------------------------------% */ igraphdlarf_("Right", &kplusp, &nr, u, &c__1, &tau, &q[i__ * q_dim1 + 1], ldq, &workl[1]); /* %----------------------------% | Prepare for next reflector | %----------------------------% */ if (i__ < iend - 1) { u[0] = h__[i__ + 1 + i__ * h_dim1]; u[1] = h__[i__ + 2 + i__ * h_dim1]; if (i__ < iend - 2) { u[2] = h__[i__ + 3 + i__ * h_dim1]; } } /* L90: */ } /* %--------------------------------------------% | Finished applying a complex pair of shifts | | to the current block | %--------------------------------------------% */ } L100: /* %---------------------------------------------------------% | Apply the same shift to the next block if there is any. | %---------------------------------------------------------% */ istart = iend + 1; if (iend < kplusp) { goto L20; } /* %---------------------------------------------% | Loop back to the top to get the next shift. | %---------------------------------------------% */ L110: ; } /* %--------------------------------------------------% | Perform a similarity transformation that makes | | sure that H will have non negative sub diagonals | %--------------------------------------------------% */ i__1 = *kev; for (j = 1; j <= i__1; ++j) { if (h__[j + 1 + j * h_dim1] < 0.) { i__2 = kplusp - j + 1; igraphdscal_(&i__2, &c_b43, &h__[j + 1 + j * h_dim1], ldh); /* Computing MIN */ i__3 = j + 2; i__2 = min(i__3,kplusp); igraphdscal_(&i__2, &c_b43, &h__[(j + 1) * h_dim1 + 1], &c__1); /* Computing MIN */ i__3 = j + *np + 1; i__2 = min(i__3,kplusp); igraphdscal_(&i__2, &c_b43, &q[(j + 1) * q_dim1 + 1], &c__1); } /* L120: */ } i__1 = *kev; for (i__ = 1; i__ <= i__1; ++i__) { /* %--------------------------------------------% | Final check for splitting and deflation. | | Use a standard test as in the QR algorithm | | REFERENCE: LAPACK subroutine dlahqr | %--------------------------------------------% */ tst1 = (d__1 = h__[i__ + i__ * h_dim1], abs(d__1)) + (d__2 = h__[i__ + 1 + (i__ + 1) * h_dim1], abs(d__2)); if (tst1 == 0.) { tst1 = igraphdlanhs_("1", kev, &h__[h_offset], ldh, &workl[1]); } /* Computing MAX */ d__1 = ulp * tst1; if (h__[i__ + 1 + i__ * h_dim1] <= max(d__1,smlnum)) { h__[i__ + 1 + i__ * h_dim1] = 0.; } /* L130: */ } /* %-------------------------------------------------% | Compute the (kev+1)-st column of (V*Q) and | | temporarily store the result in WORKD(N+1:2*N). | | This is needed in the residual update since we | | cannot GUARANTEE that the corresponding entry | | of H would be zero as in exact arithmetic. | %-------------------------------------------------% */ if (h__[*kev + 1 + *kev * h_dim1] > 0.) { igraphdgemv_("N", n, &kplusp, &c_b6, &v[v_offset], ldv, &q[(*kev + 1) * q_dim1 + 1], &c__1, &c_b5, &workd[*n + 1], &c__1); } /* %----------------------------------------------------------% | Compute column 1 to kev of (V*Q) in backward order | | taking advantage of the upper Hessenberg structure of Q. | %----------------------------------------------------------% */ i__1 = *kev; for (i__ = 1; i__ <= i__1; ++i__) { i__2 = kplusp - i__ + 1; igraphdgemv_("N", n, &i__2, &c_b6, &v[v_offset], ldv, &q[(*kev - i__ + 1) * q_dim1 + 1], &c__1, &c_b5, &workd[1], &c__1); igraphdcopy_(n, &workd[1], &c__1, &v[(kplusp - i__ + 1) * v_dim1 + 1], & c__1); /* L140: */ } /* %-------------------------------------------------% | Move v(:,kplusp-kev+1:kplusp) into v(:,1:kev). | %-------------------------------------------------% */ igraphdlacpy_("A", n, kev, &v[(kplusp - *kev + 1) * v_dim1 + 1], ldv, &v[ v_offset], ldv); /* %--------------------------------------------------------------% | Copy the (kev+1)-st column of (V*Q) in the appropriate place | %--------------------------------------------------------------% */ if (h__[*kev + 1 + *kev * h_dim1] > 0.) { igraphdcopy_(n, &workd[*n + 1], &c__1, &v[(*kev + 1) * v_dim1 + 1], &c__1); } /* %-------------------------------------% | Update the residual vector: | | r <- sigmak*r + betak*v(:,kev+1) | | where | | sigmak = (e_{kplusp}'*Q)*e_{kev} | | betak = e_{kev+1}'*H*e_{kev} | %-------------------------------------% */ igraphdscal_(n, &q[kplusp + *kev * q_dim1], &resid[1], &c__1); if (h__[*kev + 1 + *kev * h_dim1] > 0.) { igraphdaxpy_(n, &h__[*kev + 1 + *kev * h_dim1], &v[(*kev + 1) * v_dim1 + 1], &c__1, &resid[1], &c__1); } if (msglvl > 1) { igraphdvout_(&logfil, &c__1, &q[kplusp + *kev * q_dim1], &ndigit, "_napps:" " sigmak = (e_{kev+p}^T*Q)*e_{kev}", (ftnlen)40); igraphdvout_(&logfil, &c__1, &h__[*kev + 1 + *kev * h_dim1], &ndigit, "_na" "pps: betak = e_{kev+1}^T*H*e_{kev}", (ftnlen)37); igraphivout_(&logfil, &c__1, kev, &ndigit, "_napps: Order of the final Hes" "senberg matrix ", (ftnlen)45); if (msglvl > 2) { igraphdmout_(&logfil, kev, kev, &h__[h_offset], ldh, &ndigit, "_napps:" " updated Hessenberg matrix H for next iteration", (ftnlen) 54); } } L9000: igraphsecond_(&t1); tnapps += t1 - t0; return 0; /* %---------------% | End of dnapps | %---------------% */ } /* igraphdnapps_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlatrd.c0000644000076500000240000003433013524616145024261 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static doublereal c_b5 = -1.; static doublereal c_b6 = 1.; static integer c__1 = 1; static doublereal c_b16 = 0.; /* > \brief \b DLATRD reduces the first nb rows and columns of a symmetric/Hermitian matrix A to real tridiago nal form by an orthogonal similarity transformation. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLATRD + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLATRD( UPLO, N, NB, A, LDA, E, TAU, W, LDW ) CHARACTER UPLO INTEGER LDA, LDW, N, NB DOUBLE PRECISION A( LDA, * ), E( * ), TAU( * ), W( LDW, * ) > \par Purpose: ============= > > \verbatim > > DLATRD reduces NB rows and columns of a real symmetric matrix A to > symmetric tridiagonal form by an orthogonal similarity > transformation Q**T * A * Q, and returns the matrices V and W which are > needed to apply the transformation to the unreduced part of A. > > If UPLO = 'U', DLATRD reduces the last NB rows and columns of a > matrix, of which the upper triangle is supplied; > if UPLO = 'L', DLATRD reduces the first NB rows and columns of a > matrix, of which the lower triangle is supplied. > > This is an auxiliary routine called by DSYTRD. > \endverbatim Arguments: ========== > \param[in] UPLO > \verbatim > UPLO is CHARACTER*1 > Specifies whether the upper or lower triangular part of the > symmetric matrix A is stored: > = 'U': Upper triangular > = 'L': Lower triangular > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix A. > \endverbatim > > \param[in] NB > \verbatim > NB is INTEGER > The number of rows and columns to be reduced. > \endverbatim > > \param[in,out] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,N) > On entry, the symmetric matrix A. If UPLO = 'U', the leading > n-by-n upper triangular part of A contains the upper > triangular part of the matrix A, and the strictly lower > triangular part of A is not referenced. If UPLO = 'L', the > leading n-by-n lower triangular part of A contains the lower > triangular part of the matrix A, and the strictly upper > triangular part of A is not referenced. > On exit: > if UPLO = 'U', the last NB columns have been reduced to > tridiagonal form, with the diagonal elements overwriting > the diagonal elements of A; the elements above the diagonal > with the array TAU, represent the orthogonal matrix Q as a > product of elementary reflectors; > if UPLO = 'L', the first NB columns have been reduced to > tridiagonal form, with the diagonal elements overwriting > the diagonal elements of A; the elements below the diagonal > with the array TAU, represent the orthogonal matrix Q as a > product of elementary reflectors. > See Further Details. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. LDA >= (1,N). > \endverbatim > > \param[out] E > \verbatim > E is DOUBLE PRECISION array, dimension (N-1) > If UPLO = 'U', E(n-nb:n-1) contains the superdiagonal > elements of the last NB columns of the reduced matrix; > if UPLO = 'L', E(1:nb) contains the subdiagonal elements of > the first NB columns of the reduced matrix. > \endverbatim > > \param[out] TAU > \verbatim > TAU is DOUBLE PRECISION array, dimension (N-1) > The scalar factors of the elementary reflectors, stored in > TAU(n-nb:n-1) if UPLO = 'U', and in TAU(1:nb) if UPLO = 'L'. > See Further Details. > \endverbatim > > \param[out] W > \verbatim > W is DOUBLE PRECISION array, dimension (LDW,NB) > The n-by-nb matrix W required to update the unreduced part > of A. > \endverbatim > > \param[in] LDW > \verbatim > LDW is INTEGER > The leading dimension of the array W. LDW >= max(1,N). > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleOTHERauxiliary > \par Further Details: ===================== > > \verbatim > > If UPLO = 'U', the matrix Q is represented as a product of elementary > reflectors > > Q = H(n) H(n-1) . . . H(n-nb+1). > > Each H(i) has the form > > H(i) = I - tau * v * v**T > > where tau is a real scalar, and v is a real vector with > v(i:n) = 0 and v(i-1) = 1; v(1:i-1) is stored on exit in A(1:i-1,i), > and tau in TAU(i-1). > > If UPLO = 'L', the matrix Q is represented as a product of elementary > reflectors > > Q = H(1) H(2) . . . H(nb). > > Each H(i) has the form > > H(i) = I - tau * v * v**T > > where tau is a real scalar, and v is a real vector with > v(1:i) = 0 and v(i+1) = 1; v(i+1:n) is stored on exit in A(i+1:n,i), > and tau in TAU(i). > > The elements of the vectors v together form the n-by-nb matrix V > which is needed, with W, to apply the transformation to the unreduced > part of the matrix, using a symmetric rank-2k update of the form: > A := A - V*W**T - W*V**T. > > The contents of A on exit are illustrated by the following examples > with n = 5 and nb = 2: > > if UPLO = 'U': if UPLO = 'L': > > ( a a a v4 v5 ) ( d ) > ( a a v4 v5 ) ( 1 d ) > ( a 1 v5 ) ( v1 1 a ) > ( d 1 ) ( v1 v2 a a ) > ( d ) ( v1 v2 a a a ) > > where d denotes a diagonal element of the reduced matrix, a denotes > an element of the original matrix that is unchanged, and vi denotes > an element of the vector defining H(i). > \endverbatim > ===================================================================== Subroutine */ int igraphdlatrd_(char *uplo, integer *n, integer *nb, doublereal * a, integer *lda, doublereal *e, doublereal *tau, doublereal *w, integer *ldw) { /* System generated locals */ integer a_dim1, a_offset, w_dim1, w_offset, i__1, i__2, i__3; /* Local variables */ integer i__, iw; extern doublereal igraphddot_(integer *, doublereal *, integer *, doublereal *, integer *); doublereal alpha; extern /* Subroutine */ int igraphdscal_(integer *, doublereal *, doublereal *, integer *); extern logical igraphlsame_(char *, char *); extern /* Subroutine */ int igraphdgemv_(char *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *), igraphdaxpy_(integer *, doublereal *, doublereal *, integer *, doublereal *, integer *), igraphdsymv_(char *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *), igraphdlarfg_(integer *, doublereal *, doublereal *, integer *, doublereal *); /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Quick return if possible Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --e; --tau; w_dim1 = *ldw; w_offset = 1 + w_dim1; w -= w_offset; /* Function Body */ if (*n <= 0) { return 0; } if (igraphlsame_(uplo, "U")) { /* Reduce last NB columns of upper triangle */ i__1 = *n - *nb + 1; for (i__ = *n; i__ >= i__1; --i__) { iw = i__ - *n + *nb; if (i__ < *n) { /* Update A(1:i,i) */ i__2 = *n - i__; igraphdgemv_("No transpose", &i__, &i__2, &c_b5, &a[(i__ + 1) * a_dim1 + 1], lda, &w[i__ + (iw + 1) * w_dim1], ldw, & c_b6, &a[i__ * a_dim1 + 1], &c__1); i__2 = *n - i__; igraphdgemv_("No transpose", &i__, &i__2, &c_b5, &w[(iw + 1) * w_dim1 + 1], ldw, &a[i__ + (i__ + 1) * a_dim1], lda, & c_b6, &a[i__ * a_dim1 + 1], &c__1); } if (i__ > 1) { /* Generate elementary reflector H(i) to annihilate A(1:i-2,i) */ i__2 = i__ - 1; igraphdlarfg_(&i__2, &a[i__ - 1 + i__ * a_dim1], &a[i__ * a_dim1 + 1], &c__1, &tau[i__ - 1]); e[i__ - 1] = a[i__ - 1 + i__ * a_dim1]; a[i__ - 1 + i__ * a_dim1] = 1.; /* Compute W(1:i-1,i) */ i__2 = i__ - 1; igraphdsymv_("Upper", &i__2, &c_b6, &a[a_offset], lda, &a[i__ * a_dim1 + 1], &c__1, &c_b16, &w[iw * w_dim1 + 1], & c__1); if (i__ < *n) { i__2 = i__ - 1; i__3 = *n - i__; igraphdgemv_("Transpose", &i__2, &i__3, &c_b6, &w[(iw + 1) * w_dim1 + 1], ldw, &a[i__ * a_dim1 + 1], &c__1, & c_b16, &w[i__ + 1 + iw * w_dim1], &c__1); i__2 = i__ - 1; i__3 = *n - i__; igraphdgemv_("No transpose", &i__2, &i__3, &c_b5, &a[(i__ + 1) * a_dim1 + 1], lda, &w[i__ + 1 + iw * w_dim1], & c__1, &c_b6, &w[iw * w_dim1 + 1], &c__1); i__2 = i__ - 1; i__3 = *n - i__; igraphdgemv_("Transpose", &i__2, &i__3, &c_b6, &a[(i__ + 1) * a_dim1 + 1], lda, &a[i__ * a_dim1 + 1], &c__1, & c_b16, &w[i__ + 1 + iw * w_dim1], &c__1); i__2 = i__ - 1; i__3 = *n - i__; igraphdgemv_("No transpose", &i__2, &i__3, &c_b5, &w[(iw + 1) * w_dim1 + 1], ldw, &w[i__ + 1 + iw * w_dim1], & c__1, &c_b6, &w[iw * w_dim1 + 1], &c__1); } i__2 = i__ - 1; igraphdscal_(&i__2, &tau[i__ - 1], &w[iw * w_dim1 + 1], &c__1); i__2 = i__ - 1; alpha = tau[i__ - 1] * -.5 * igraphddot_(&i__2, &w[iw * w_dim1 + 1], &c__1, &a[i__ * a_dim1 + 1], &c__1); i__2 = i__ - 1; igraphdaxpy_(&i__2, &alpha, &a[i__ * a_dim1 + 1], &c__1, &w[iw * w_dim1 + 1], &c__1); } /* L10: */ } } else { /* Reduce first NB columns of lower triangle */ i__1 = *nb; for (i__ = 1; i__ <= i__1; ++i__) { /* Update A(i:n,i) */ i__2 = *n - i__ + 1; i__3 = i__ - 1; igraphdgemv_("No transpose", &i__2, &i__3, &c_b5, &a[i__ + a_dim1], lda, &w[i__ + w_dim1], ldw, &c_b6, &a[i__ + i__ * a_dim1], & c__1); i__2 = *n - i__ + 1; i__3 = i__ - 1; igraphdgemv_("No transpose", &i__2, &i__3, &c_b5, &w[i__ + w_dim1], ldw, &a[i__ + a_dim1], lda, &c_b6, &a[i__ + i__ * a_dim1], & c__1); if (i__ < *n) { /* Generate elementary reflector H(i) to annihilate A(i+2:n,i) */ i__2 = *n - i__; /* Computing MIN */ i__3 = i__ + 2; igraphdlarfg_(&i__2, &a[i__ + 1 + i__ * a_dim1], &a[min(i__3,*n) + i__ * a_dim1], &c__1, &tau[i__]); e[i__] = a[i__ + 1 + i__ * a_dim1]; a[i__ + 1 + i__ * a_dim1] = 1.; /* Compute W(i+1:n,i) */ i__2 = *n - i__; igraphdsymv_("Lower", &i__2, &c_b6, &a[i__ + 1 + (i__ + 1) * a_dim1] , lda, &a[i__ + 1 + i__ * a_dim1], &c__1, &c_b16, &w[ i__ + 1 + i__ * w_dim1], &c__1); i__2 = *n - i__; i__3 = i__ - 1; igraphdgemv_("Transpose", &i__2, &i__3, &c_b6, &w[i__ + 1 + w_dim1], ldw, &a[i__ + 1 + i__ * a_dim1], &c__1, &c_b16, &w[ i__ * w_dim1 + 1], &c__1); i__2 = *n - i__; i__3 = i__ - 1; igraphdgemv_("No transpose", &i__2, &i__3, &c_b5, &a[i__ + 1 + a_dim1], lda, &w[i__ * w_dim1 + 1], &c__1, &c_b6, &w[ i__ + 1 + i__ * w_dim1], &c__1); i__2 = *n - i__; i__3 = i__ - 1; igraphdgemv_("Transpose", &i__2, &i__3, &c_b6, &a[i__ + 1 + a_dim1], lda, &a[i__ + 1 + i__ * a_dim1], &c__1, &c_b16, &w[ i__ * w_dim1 + 1], &c__1); i__2 = *n - i__; i__3 = i__ - 1; igraphdgemv_("No transpose", &i__2, &i__3, &c_b5, &w[i__ + 1 + w_dim1], ldw, &w[i__ * w_dim1 + 1], &c__1, &c_b6, &w[ i__ + 1 + i__ * w_dim1], &c__1); i__2 = *n - i__; igraphdscal_(&i__2, &tau[i__], &w[i__ + 1 + i__ * w_dim1], &c__1); i__2 = *n - i__; alpha = tau[i__] * -.5 * igraphddot_(&i__2, &w[i__ + 1 + i__ * w_dim1], &c__1, &a[i__ + 1 + i__ * a_dim1], &c__1); i__2 = *n - i__; igraphdaxpy_(&i__2, &alpha, &a[i__ + 1 + i__ * a_dim1], &c__1, &w[ i__ + 1 + i__ * w_dim1], &c__1); } /* L20: */ } } return 0; /* End of DLATRD */ } /* igraphdlatrd_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlaebz.c0000644000076500000240000005653213524616145024260 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLAEBZ computes the number of eigenvalues of a real symmetric tridiagonal matrix which are less than or equal to a given value, and performs other tasks required by the routine sstebz. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLAEBZ + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLAEBZ( IJOB, NITMAX, N, MMAX, MINP, NBMIN, ABSTOL, RELTOL, PIVMIN, D, E, E2, NVAL, AB, C, MOUT, NAB, WORK, IWORK, INFO ) INTEGER IJOB, INFO, MINP, MMAX, MOUT, N, NBMIN, NITMAX DOUBLE PRECISION ABSTOL, PIVMIN, RELTOL INTEGER IWORK( * ), NAB( MMAX, * ), NVAL( * ) DOUBLE PRECISION AB( MMAX, * ), C( * ), D( * ), E( * ), E2( * ), $ WORK( * ) > \par Purpose: ============= > > \verbatim > > DLAEBZ contains the iteration loops which compute and use the > function N(w), which is the count of eigenvalues of a symmetric > tridiagonal matrix T less than or equal to its argument w. It > performs a choice of two types of loops: > > IJOB=1, followed by > IJOB=2: It takes as input a list of intervals and returns a list of > sufficiently small intervals whose union contains the same > eigenvalues as the union of the original intervals. > The input intervals are (AB(j,1),AB(j,2)], j=1,...,MINP. > The output interval (AB(j,1),AB(j,2)] will contain > eigenvalues NAB(j,1)+1,...,NAB(j,2), where 1 <= j <= MOUT. > > IJOB=3: It performs a binary search in each input interval > (AB(j,1),AB(j,2)] for a point w(j) such that > N(w(j))=NVAL(j), and uses C(j) as the starting point of > the search. If such a w(j) is found, then on output > AB(j,1)=AB(j,2)=w. If no such w(j) is found, then on output > (AB(j,1),AB(j,2)] will be a small interval containing the > point where N(w) jumps through NVAL(j), unless that point > lies outside the initial interval. > > Note that the intervals are in all cases half-open intervals, > i.e., of the form (a,b] , which includes b but not a . > > To avoid underflow, the matrix should be scaled so that its largest > element is no greater than overflow**(1/2) * underflow**(1/4) > in absolute value. To assure the most accurate computation > of small eigenvalues, the matrix should be scaled to be > not much smaller than that, either. > > See W. Kahan "Accurate Eigenvalues of a Symmetric Tridiagonal > Matrix", Report CS41, Computer Science Dept., Stanford > University, July 21, 1966 > > Note: the arguments are, in general, *not* checked for unreasonable > values. > \endverbatim Arguments: ========== > \param[in] IJOB > \verbatim > IJOB is INTEGER > Specifies what is to be done: > = 1: Compute NAB for the initial intervals. > = 2: Perform bisection iteration to find eigenvalues of T. > = 3: Perform bisection iteration to invert N(w), i.e., > to find a point which has a specified number of > eigenvalues of T to its left. > Other values will cause DLAEBZ to return with INFO=-1. > \endverbatim > > \param[in] NITMAX > \verbatim > NITMAX is INTEGER > The maximum number of "levels" of bisection to be > performed, i.e., an interval of width W will not be made > smaller than 2^(-NITMAX) * W. If not all intervals > have converged after NITMAX iterations, then INFO is set > to the number of non-converged intervals. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The dimension n of the tridiagonal matrix T. It must be at > least 1. > \endverbatim > > \param[in] MMAX > \verbatim > MMAX is INTEGER > The maximum number of intervals. If more than MMAX intervals > are generated, then DLAEBZ will quit with INFO=MMAX+1. > \endverbatim > > \param[in] MINP > \verbatim > MINP is INTEGER > The initial number of intervals. It may not be greater than > MMAX. > \endverbatim > > \param[in] NBMIN > \verbatim > NBMIN is INTEGER > The smallest number of intervals that should be processed > using a vector loop. If zero, then only the scalar loop > will be used. > \endverbatim > > \param[in] ABSTOL > \verbatim > ABSTOL is DOUBLE PRECISION > The minimum (absolute) width of an interval. When an > interval is narrower than ABSTOL, or than RELTOL times the > larger (in magnitude) endpoint, then it is considered to be > sufficiently small, i.e., converged. This must be at least > zero. > \endverbatim > > \param[in] RELTOL > \verbatim > RELTOL is DOUBLE PRECISION > The minimum relative width of an interval. When an interval > is narrower than ABSTOL, or than RELTOL times the larger (in > magnitude) endpoint, then it is considered to be > sufficiently small, i.e., converged. Note: this should > always be at least radix*machine epsilon. > \endverbatim > > \param[in] PIVMIN > \verbatim > PIVMIN is DOUBLE PRECISION > The minimum absolute value of a "pivot" in the Sturm > sequence loop. > This must be at least max |e(j)**2|*safe_min and at > least safe_min, where safe_min is at least > the smallest number that can divide one without overflow. > \endverbatim > > \param[in] D > \verbatim > D is DOUBLE PRECISION array, dimension (N) > The diagonal elements of the tridiagonal matrix T. > \endverbatim > > \param[in] E > \verbatim > E is DOUBLE PRECISION array, dimension (N) > The offdiagonal elements of the tridiagonal matrix T in > positions 1 through N-1. E(N) is arbitrary. > \endverbatim > > \param[in] E2 > \verbatim > E2 is DOUBLE PRECISION array, dimension (N) > The squares of the offdiagonal elements of the tridiagonal > matrix T. E2(N) is ignored. > \endverbatim > > \param[in,out] NVAL > \verbatim > NVAL is INTEGER array, dimension (MINP) > If IJOB=1 or 2, not referenced. > If IJOB=3, the desired values of N(w). The elements of NVAL > will be reordered to correspond with the intervals in AB. > Thus, NVAL(j) on output will not, in general be the same as > NVAL(j) on input, but it will correspond with the interval > (AB(j,1),AB(j,2)] on output. > \endverbatim > > \param[in,out] AB > \verbatim > AB is DOUBLE PRECISION array, dimension (MMAX,2) > The endpoints of the intervals. AB(j,1) is a(j), the left > endpoint of the j-th interval, and AB(j,2) is b(j), the > right endpoint of the j-th interval. The input intervals > will, in general, be modified, split, and reordered by the > calculation. > \endverbatim > > \param[in,out] C > \verbatim > C is DOUBLE PRECISION array, dimension (MMAX) > If IJOB=1, ignored. > If IJOB=2, workspace. > If IJOB=3, then on input C(j) should be initialized to the > first search point in the binary search. > \endverbatim > > \param[out] MOUT > \verbatim > MOUT is INTEGER > If IJOB=1, the number of eigenvalues in the intervals. > If IJOB=2 or 3, the number of intervals output. > If IJOB=3, MOUT will equal MINP. > \endverbatim > > \param[in,out] NAB > \verbatim > NAB is INTEGER array, dimension (MMAX,2) > If IJOB=1, then on output NAB(i,j) will be set to N(AB(i,j)). > If IJOB=2, then on input, NAB(i,j) should be set. It must > satisfy the condition: > N(AB(i,1)) <= NAB(i,1) <= NAB(i,2) <= N(AB(i,2)), > which means that in interval i only eigenvalues > NAB(i,1)+1,...,NAB(i,2) will be considered. Usually, > NAB(i,j)=N(AB(i,j)), from a previous call to DLAEBZ with > IJOB=1. > On output, NAB(i,j) will contain > max(na(k),min(nb(k),N(AB(i,j)))), where k is the index of > the input interval that the output interval > (AB(j,1),AB(j,2)] came from, and na(k) and nb(k) are the > the input values of NAB(k,1) and NAB(k,2). > If IJOB=3, then on output, NAB(i,j) contains N(AB(i,j)), > unless N(w) > NVAL(i) for all search points w , in which > case NAB(i,1) will not be modified, i.e., the output > value will be the same as the input value (modulo > reorderings -- see NVAL and AB), or unless N(w) < NVAL(i) > for all search points w , in which case NAB(i,2) will > not be modified. Normally, NAB should be set to some > distinctive value(s) before DLAEBZ is called. > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (MMAX) > Workspace. > \endverbatim > > \param[out] IWORK > \verbatim > IWORK is INTEGER array, dimension (MMAX) > Workspace. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: All intervals converged. > = 1--MMAX: The last INFO intervals did not converge. > = MMAX+1: More than MMAX intervals were generated. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERauxiliary > \par Further Details: ===================== > > \verbatim > > This routine is intended to be called only by other LAPACK > routines, thus the interface is less user-friendly. It is intended > for two purposes: > > (a) finding eigenvalues. In this case, DLAEBZ should have one or > more initial intervals set up in AB, and DLAEBZ should be called > with IJOB=1. This sets up NAB, and also counts the eigenvalues. > Intervals with no eigenvalues would usually be thrown out at > this point. Also, if not all the eigenvalues in an interval i > are desired, NAB(i,1) can be increased or NAB(i,2) decreased. > For example, set NAB(i,1)=NAB(i,2)-1 to get the largest > eigenvalue. DLAEBZ is then called with IJOB=2 and MMAX > no smaller than the value of MOUT returned by the call with > IJOB=1. After this (IJOB=2) call, eigenvalues NAB(i,1)+1 > through NAB(i,2) are approximately AB(i,1) (or AB(i,2)) to the > tolerance specified by ABSTOL and RELTOL. > > (b) finding an interval (a',b'] containing eigenvalues w(f),...,w(l). > In this case, start with a Gershgorin interval (a,b). Set up > AB to contain 2 search intervals, both initially (a,b). One > NVAL element should contain f-1 and the other should contain l > , while C should contain a and b, resp. NAB(i,1) should be -1 > and NAB(i,2) should be N+1, to flag an error if the desired > interval does not lie in (a,b). DLAEBZ is then called with > IJOB=3. On exit, if w(f-1) < w(f), then one of the intervals -- > j -- will have AB(j,1)=AB(j,2) and NAB(j,1)=NAB(j,2)=f-1, while > if, to the specified tolerance, w(f-k)=...=w(f+r), k > 0 and r > >= 0, then the interval will have N(AB(j,1))=NAB(j,1)=f-k and > N(AB(j,2))=NAB(j,2)=f+r. The cases w(l) < w(l+1) and > w(l-r)=...=w(l+k) are handled similarly. > \endverbatim > ===================================================================== Subroutine */ int igraphdlaebz_(integer *ijob, integer *nitmax, integer *n, integer *mmax, integer *minp, integer *nbmin, doublereal *abstol, doublereal *reltol, doublereal *pivmin, doublereal *d__, doublereal * e, doublereal *e2, integer *nval, doublereal *ab, doublereal *c__, integer *mout, integer *nab, doublereal *work, integer *iwork, integer *info) { /* System generated locals */ integer nab_dim1, nab_offset, ab_dim1, ab_offset, i__1, i__2, i__3, i__4, i__5, i__6; doublereal d__1, d__2, d__3, d__4; /* Local variables */ integer j, kf, ji, kl, jp, jit; doublereal tmp1, tmp2; integer itmp1, itmp2, kfnew, klnew; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Check for Errors Parameter adjustments */ nab_dim1 = *mmax; nab_offset = 1 + nab_dim1; nab -= nab_offset; ab_dim1 = *mmax; ab_offset = 1 + ab_dim1; ab -= ab_offset; --d__; --e; --e2; --nval; --c__; --work; --iwork; /* Function Body */ *info = 0; if (*ijob < 1 || *ijob > 3) { *info = -1; return 0; } /* Initialize NAB */ if (*ijob == 1) { /* Compute the number of eigenvalues in the initial intervals. */ *mout = 0; i__1 = *minp; for (ji = 1; ji <= i__1; ++ji) { for (jp = 1; jp <= 2; ++jp) { tmp1 = d__[1] - ab[ji + jp * ab_dim1]; if (abs(tmp1) < *pivmin) { tmp1 = -(*pivmin); } nab[ji + jp * nab_dim1] = 0; if (tmp1 <= 0.) { nab[ji + jp * nab_dim1] = 1; } i__2 = *n; for (j = 2; j <= i__2; ++j) { tmp1 = d__[j] - e2[j - 1] / tmp1 - ab[ji + jp * ab_dim1]; if (abs(tmp1) < *pivmin) { tmp1 = -(*pivmin); } if (tmp1 <= 0.) { ++nab[ji + jp * nab_dim1]; } /* L10: */ } /* L20: */ } *mout = *mout + nab[ji + (nab_dim1 << 1)] - nab[ji + nab_dim1]; /* L30: */ } return 0; } /* Initialize for loop KF and KL have the following meaning: Intervals 1,...,KF-1 have converged. Intervals KF,...,KL still need to be refined. */ kf = 1; kl = *minp; /* If IJOB=2, initialize C. If IJOB=3, use the user-supplied starting point. */ if (*ijob == 2) { i__1 = *minp; for (ji = 1; ji <= i__1; ++ji) { c__[ji] = (ab[ji + ab_dim1] + ab[ji + (ab_dim1 << 1)]) * .5; /* L40: */ } } /* Iteration loop */ i__1 = *nitmax; for (jit = 1; jit <= i__1; ++jit) { /* Loop over intervals */ if (kl - kf + 1 >= *nbmin && *nbmin > 0) { /* Begin of Parallel Version of the loop */ i__2 = kl; for (ji = kf; ji <= i__2; ++ji) { /* Compute N(c), the number of eigenvalues less than c */ work[ji] = d__[1] - c__[ji]; iwork[ji] = 0; if (work[ji] <= *pivmin) { iwork[ji] = 1; /* Computing MIN */ d__1 = work[ji], d__2 = -(*pivmin); work[ji] = min(d__1,d__2); } i__3 = *n; for (j = 2; j <= i__3; ++j) { work[ji] = d__[j] - e2[j - 1] / work[ji] - c__[ji]; if (work[ji] <= *pivmin) { ++iwork[ji]; /* Computing MIN */ d__1 = work[ji], d__2 = -(*pivmin); work[ji] = min(d__1,d__2); } /* L50: */ } /* L60: */ } if (*ijob <= 2) { /* IJOB=2: Choose all intervals containing eigenvalues. */ klnew = kl; i__2 = kl; for (ji = kf; ji <= i__2; ++ji) { /* Insure that N(w) is monotone Computing MIN Computing MAX */ i__5 = nab[ji + nab_dim1], i__6 = iwork[ji]; i__3 = nab[ji + (nab_dim1 << 1)], i__4 = max(i__5,i__6); iwork[ji] = min(i__3,i__4); /* Update the Queue -- add intervals if both halves contain eigenvalues. */ if (iwork[ji] == nab[ji + (nab_dim1 << 1)]) { /* No eigenvalue in the upper interval: just use the lower interval. */ ab[ji + (ab_dim1 << 1)] = c__[ji]; } else if (iwork[ji] == nab[ji + nab_dim1]) { /* No eigenvalue in the lower interval: just use the upper interval. */ ab[ji + ab_dim1] = c__[ji]; } else { ++klnew; if (klnew <= *mmax) { /* Eigenvalue in both intervals -- add upper to queue. */ ab[klnew + (ab_dim1 << 1)] = ab[ji + (ab_dim1 << 1)]; nab[klnew + (nab_dim1 << 1)] = nab[ji + (nab_dim1 << 1)]; ab[klnew + ab_dim1] = c__[ji]; nab[klnew + nab_dim1] = iwork[ji]; ab[ji + (ab_dim1 << 1)] = c__[ji]; nab[ji + (nab_dim1 << 1)] = iwork[ji]; } else { *info = *mmax + 1; } } /* L70: */ } if (*info != 0) { return 0; } kl = klnew; } else { /* IJOB=3: Binary search. Keep only the interval containing w s.t. N(w) = NVAL */ i__2 = kl; for (ji = kf; ji <= i__2; ++ji) { if (iwork[ji] <= nval[ji]) { ab[ji + ab_dim1] = c__[ji]; nab[ji + nab_dim1] = iwork[ji]; } if (iwork[ji] >= nval[ji]) { ab[ji + (ab_dim1 << 1)] = c__[ji]; nab[ji + (nab_dim1 << 1)] = iwork[ji]; } /* L80: */ } } } else { /* End of Parallel Version of the loop Begin of Serial Version of the loop */ klnew = kl; i__2 = kl; for (ji = kf; ji <= i__2; ++ji) { /* Compute N(w), the number of eigenvalues less than w */ tmp1 = c__[ji]; tmp2 = d__[1] - tmp1; itmp1 = 0; if (tmp2 <= *pivmin) { itmp1 = 1; /* Computing MIN */ d__1 = tmp2, d__2 = -(*pivmin); tmp2 = min(d__1,d__2); } i__3 = *n; for (j = 2; j <= i__3; ++j) { tmp2 = d__[j] - e2[j - 1] / tmp2 - tmp1; if (tmp2 <= *pivmin) { ++itmp1; /* Computing MIN */ d__1 = tmp2, d__2 = -(*pivmin); tmp2 = min(d__1,d__2); } /* L90: */ } if (*ijob <= 2) { /* IJOB=2: Choose all intervals containing eigenvalues. Insure that N(w) is monotone Computing MIN Computing MAX */ i__5 = nab[ji + nab_dim1]; i__3 = nab[ji + (nab_dim1 << 1)], i__4 = max(i__5,itmp1); itmp1 = min(i__3,i__4); /* Update the Queue -- add intervals if both halves contain eigenvalues. */ if (itmp1 == nab[ji + (nab_dim1 << 1)]) { /* No eigenvalue in the upper interval: just use the lower interval. */ ab[ji + (ab_dim1 << 1)] = tmp1; } else if (itmp1 == nab[ji + nab_dim1]) { /* No eigenvalue in the lower interval: just use the upper interval. */ ab[ji + ab_dim1] = tmp1; } else if (klnew < *mmax) { /* Eigenvalue in both intervals -- add upper to queue. */ ++klnew; ab[klnew + (ab_dim1 << 1)] = ab[ji + (ab_dim1 << 1)]; nab[klnew + (nab_dim1 << 1)] = nab[ji + (nab_dim1 << 1)]; ab[klnew + ab_dim1] = tmp1; nab[klnew + nab_dim1] = itmp1; ab[ji + (ab_dim1 << 1)] = tmp1; nab[ji + (nab_dim1 << 1)] = itmp1; } else { *info = *mmax + 1; return 0; } } else { /* IJOB=3: Binary search. Keep only the interval containing w s.t. N(w) = NVAL */ if (itmp1 <= nval[ji]) { ab[ji + ab_dim1] = tmp1; nab[ji + nab_dim1] = itmp1; } if (itmp1 >= nval[ji]) { ab[ji + (ab_dim1 << 1)] = tmp1; nab[ji + (nab_dim1 << 1)] = itmp1; } } /* L100: */ } kl = klnew; } /* Check for convergence */ kfnew = kf; i__2 = kl; for (ji = kf; ji <= i__2; ++ji) { tmp1 = (d__1 = ab[ji + (ab_dim1 << 1)] - ab[ji + ab_dim1], abs( d__1)); /* Computing MAX */ d__3 = (d__1 = ab[ji + (ab_dim1 << 1)], abs(d__1)), d__4 = (d__2 = ab[ji + ab_dim1], abs(d__2)); tmp2 = max(d__3,d__4); /* Computing MAX */ d__1 = max(*abstol,*pivmin), d__2 = *reltol * tmp2; if (tmp1 < max(d__1,d__2) || nab[ji + nab_dim1] >= nab[ji + ( nab_dim1 << 1)]) { /* Converged -- Swap with position KFNEW, then increment KFNEW */ if (ji > kfnew) { tmp1 = ab[ji + ab_dim1]; tmp2 = ab[ji + (ab_dim1 << 1)]; itmp1 = nab[ji + nab_dim1]; itmp2 = nab[ji + (nab_dim1 << 1)]; ab[ji + ab_dim1] = ab[kfnew + ab_dim1]; ab[ji + (ab_dim1 << 1)] = ab[kfnew + (ab_dim1 << 1)]; nab[ji + nab_dim1] = nab[kfnew + nab_dim1]; nab[ji + (nab_dim1 << 1)] = nab[kfnew + (nab_dim1 << 1)]; ab[kfnew + ab_dim1] = tmp1; ab[kfnew + (ab_dim1 << 1)] = tmp2; nab[kfnew + nab_dim1] = itmp1; nab[kfnew + (nab_dim1 << 1)] = itmp2; if (*ijob == 3) { itmp1 = nval[ji]; nval[ji] = nval[kfnew]; nval[kfnew] = itmp1; } } ++kfnew; } /* L110: */ } kf = kfnew; /* Choose Midpoints */ i__2 = kl; for (ji = kf; ji <= i__2; ++ji) { c__[ji] = (ab[ji + ab_dim1] + ab[ji + (ab_dim1 << 1)]) * .5; /* L120: */ } /* If no more intervals to refine, quit. */ if (kf > kl) { goto L140; } /* L130: */ } /* Converged */ L140: /* Computing MAX */ i__1 = kl + 1 - kf; *info = max(i__1,0); *mout = kl; return 0; /* End of DLAEBZ */ } /* igraphdlaebz_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dtrmv.c0000644000076500000240000002032113524616145024136 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Subroutine */ int igraphdtrmv_(char *uplo, char *trans, char *diag, integer *n, doublereal *a, integer *lda, doublereal *x, integer *incx) { /* System generated locals */ integer a_dim1, a_offset, i__1, i__2; /* Local variables */ integer i__, j, ix, jx, kx, info; doublereal temp; extern logical igraphlsame_(char *, char *); extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); logical nounit; /* Purpose ======= DTRMV performs one of the matrix-vector operations x := A*x, or x := A**T*x, where x is an n element vector and A is an n by n unit, or non-unit, upper or lower triangular matrix. Arguments ========== UPLO - CHARACTER*1. On entry, UPLO specifies whether the matrix is an upper or lower triangular matrix as follows: UPLO = 'U' or 'u' A is an upper triangular matrix. UPLO = 'L' or 'l' A is a lower triangular matrix. Unchanged on exit. TRANS - CHARACTER*1. On entry, TRANS specifies the operation to be performed as follows: TRANS = 'N' or 'n' x := A*x. TRANS = 'T' or 't' x := A**T*x. TRANS = 'C' or 'c' x := A**T*x. Unchanged on exit. DIAG - CHARACTER*1. On entry, DIAG specifies whether or not A is unit triangular as follows: DIAG = 'U' or 'u' A is assumed to be unit triangular. DIAG = 'N' or 'n' A is not assumed to be unit triangular. Unchanged on exit. N - INTEGER. On entry, N specifies the order of the matrix A. N must be at least zero. Unchanged on exit. A - DOUBLE PRECISION array of DIMENSION ( LDA, n ). Before entry with UPLO = 'U' or 'u', the leading n by n upper triangular part of the array A must contain the upper triangular matrix and the strictly lower triangular part of A is not referenced. Before entry with UPLO = 'L' or 'l', the leading n by n lower triangular part of the array A must contain the lower triangular matrix and the strictly upper triangular part of A is not referenced. Note that when DIAG = 'U' or 'u', the diagonal elements of A are not referenced either, but are assumed to be unity. Unchanged on exit. LDA - INTEGER. On entry, LDA specifies the first dimension of A as declared in the calling (sub) program. LDA must be at least max( 1, n ). Unchanged on exit. X - DOUBLE PRECISION array of dimension at least ( 1 + ( n - 1 )*abs( INCX ) ). Before entry, the incremented array X must contain the n element vector x. On exit, X is overwritten with the tranformed vector x. INCX - INTEGER. On entry, INCX specifies the increment for the elements of X. INCX must not be zero. Unchanged on exit. Further Details =============== Level 2 Blas routine. The vector and matrix arguments are not referenced when N = 0, or M = 0 -- Written on 22-October-1986. Jack Dongarra, Argonne National Lab. Jeremy Du Croz, Nag Central Office. Sven Hammarling, Nag Central Office. Richard Hanson, Sandia National Labs. ===================================================================== Test the input parameters. Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --x; /* Function Body */ info = 0; if (! igraphlsame_(uplo, "U") && ! igraphlsame_(uplo, "L")) { info = 1; } else if (! igraphlsame_(trans, "N") && ! igraphlsame_(trans, "T") && ! igraphlsame_(trans, "C")) { info = 2; } else if (! igraphlsame_(diag, "U") && ! igraphlsame_(diag, "N")) { info = 3; } else if (*n < 0) { info = 4; } else if (*lda < max(1,*n)) { info = 6; } else if (*incx == 0) { info = 8; } if (info != 0) { igraphxerbla_("DTRMV ", &info, (ftnlen)6); return 0; } /* Quick return if possible. */ if (*n == 0) { return 0; } nounit = igraphlsame_(diag, "N"); /* Set up the start point in X if the increment is not unity. This will be ( N - 1 )*INCX too small for descending loops. */ if (*incx <= 0) { kx = 1 - (*n - 1) * *incx; } else if (*incx != 1) { kx = 1; } /* Start the operations. In this version the elements of A are accessed sequentially with one pass through A. */ if (igraphlsame_(trans, "N")) { /* Form x := A*x. */ if (igraphlsame_(uplo, "U")) { if (*incx == 1) { i__1 = *n; for (j = 1; j <= i__1; ++j) { if (x[j] != 0.) { temp = x[j]; i__2 = j - 1; for (i__ = 1; i__ <= i__2; ++i__) { x[i__] += temp * a[i__ + j * a_dim1]; /* L10: */ } if (nounit) { x[j] *= a[j + j * a_dim1]; } } /* L20: */ } } else { jx = kx; i__1 = *n; for (j = 1; j <= i__1; ++j) { if (x[jx] != 0.) { temp = x[jx]; ix = kx; i__2 = j - 1; for (i__ = 1; i__ <= i__2; ++i__) { x[ix] += temp * a[i__ + j * a_dim1]; ix += *incx; /* L30: */ } if (nounit) { x[jx] *= a[j + j * a_dim1]; } } jx += *incx; /* L40: */ } } } else { if (*incx == 1) { for (j = *n; j >= 1; --j) { if (x[j] != 0.) { temp = x[j]; i__1 = j + 1; for (i__ = *n; i__ >= i__1; --i__) { x[i__] += temp * a[i__ + j * a_dim1]; /* L50: */ } if (nounit) { x[j] *= a[j + j * a_dim1]; } } /* L60: */ } } else { kx += (*n - 1) * *incx; jx = kx; for (j = *n; j >= 1; --j) { if (x[jx] != 0.) { temp = x[jx]; ix = kx; i__1 = j + 1; for (i__ = *n; i__ >= i__1; --i__) { x[ix] += temp * a[i__ + j * a_dim1]; ix -= *incx; /* L70: */ } if (nounit) { x[jx] *= a[j + j * a_dim1]; } } jx -= *incx; /* L80: */ } } } } else { /* Form x := A**T*x. */ if (igraphlsame_(uplo, "U")) { if (*incx == 1) { for (j = *n; j >= 1; --j) { temp = x[j]; if (nounit) { temp *= a[j + j * a_dim1]; } for (i__ = j - 1; i__ >= 1; --i__) { temp += a[i__ + j * a_dim1] * x[i__]; /* L90: */ } x[j] = temp; /* L100: */ } } else { jx = kx + (*n - 1) * *incx; for (j = *n; j >= 1; --j) { temp = x[jx]; ix = jx; if (nounit) { temp *= a[j + j * a_dim1]; } for (i__ = j - 1; i__ >= 1; --i__) { ix -= *incx; temp += a[i__ + j * a_dim1] * x[ix]; /* L110: */ } x[jx] = temp; jx -= *incx; /* L120: */ } } } else { if (*incx == 1) { i__1 = *n; for (j = 1; j <= i__1; ++j) { temp = x[j]; if (nounit) { temp *= a[j + j * a_dim1]; } i__2 = *n; for (i__ = j + 1; i__ <= i__2; ++i__) { temp += a[i__ + j * a_dim1] * x[i__]; /* L130: */ } x[j] = temp; /* L140: */ } } else { jx = kx; i__1 = *n; for (j = 1; j <= i__1; ++j) { temp = x[jx]; ix = jx; if (nounit) { temp *= a[j + j * a_dim1]; } i__2 = *n; for (i__ = j + 1; i__ <= i__2; ++i__) { ix += *incx; temp += a[i__ + j * a_dim1] * x[ix]; /* L150: */ } x[jx] = temp; jx += *incx; /* L160: */ } } } } return 0; /* End of DTRMV . */ } /* igraphdtrmv_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/stat.h0000644000076500000240000000000013524616145023752 0ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlahqr.c0000644000076500000240000005332013524616145024262 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; /* > \brief \b DLAHQR computes the eigenvalues and Schur factorization of an upper Hessenberg matrix, using th e double-shift/single-shift QR algorithm. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLAHQR + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLAHQR( WANTT, WANTZ, N, ILO, IHI, H, LDH, WR, WI, ILOZ, IHIZ, Z, LDZ, INFO ) INTEGER IHI, IHIZ, ILO, ILOZ, INFO, LDH, LDZ, N LOGICAL WANTT, WANTZ DOUBLE PRECISION H( LDH, * ), WI( * ), WR( * ), Z( LDZ, * ) > \par Purpose: ============= > > \verbatim > > DLAHQR is an auxiliary routine called by DHSEQR to update the > eigenvalues and Schur decomposition already computed by DHSEQR, by > dealing with the Hessenberg submatrix in rows and columns ILO to > IHI. > \endverbatim Arguments: ========== > \param[in] WANTT > \verbatim > WANTT is LOGICAL > = .TRUE. : the full Schur form T is required; > = .FALSE.: only eigenvalues are required. > \endverbatim > > \param[in] WANTZ > \verbatim > WANTZ is LOGICAL > = .TRUE. : the matrix of Schur vectors Z is required; > = .FALSE.: Schur vectors are not required. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix H. N >= 0. > \endverbatim > > \param[in] ILO > \verbatim > ILO is INTEGER > \endverbatim > > \param[in] IHI > \verbatim > IHI is INTEGER > It is assumed that H is already upper quasi-triangular in > rows and columns IHI+1:N, and that H(ILO,ILO-1) = 0 (unless > ILO = 1). DLAHQR works primarily with the Hessenberg > submatrix in rows and columns ILO to IHI, but applies > transformations to all of H if WANTT is .TRUE.. > 1 <= ILO <= max(1,IHI); IHI <= N. > \endverbatim > > \param[in,out] H > \verbatim > H is DOUBLE PRECISION array, dimension (LDH,N) > On entry, the upper Hessenberg matrix H. > On exit, if INFO is zero and if WANTT is .TRUE., H is upper > quasi-triangular in rows and columns ILO:IHI, with any > 2-by-2 diagonal blocks in standard form. If INFO is zero > and WANTT is .FALSE., the contents of H are unspecified on > exit. The output state of H if INFO is nonzero is given > below under the description of INFO. > \endverbatim > > \param[in] LDH > \verbatim > LDH is INTEGER > The leading dimension of the array H. LDH >= max(1,N). > \endverbatim > > \param[out] WR > \verbatim > WR is DOUBLE PRECISION array, dimension (N) > \endverbatim > > \param[out] WI > \verbatim > WI is DOUBLE PRECISION array, dimension (N) > The real and imaginary parts, respectively, of the computed > eigenvalues ILO to IHI are stored in the corresponding > elements of WR and WI. If two eigenvalues are computed as a > complex conjugate pair, they are stored in consecutive > elements of WR and WI, say the i-th and (i+1)th, with > WI(i) > 0 and WI(i+1) < 0. If WANTT is .TRUE., the > eigenvalues are stored in the same order as on the diagonal > of the Schur form returned in H, with WR(i) = H(i,i), and, if > H(i:i+1,i:i+1) is a 2-by-2 diagonal block, > WI(i) = sqrt(H(i+1,i)*H(i,i+1)) and WI(i+1) = -WI(i). > \endverbatim > > \param[in] ILOZ > \verbatim > ILOZ is INTEGER > \endverbatim > > \param[in] IHIZ > \verbatim > IHIZ is INTEGER > Specify the rows of Z to which transformations must be > applied if WANTZ is .TRUE.. > 1 <= ILOZ <= ILO; IHI <= IHIZ <= N. > \endverbatim > > \param[in,out] Z > \verbatim > Z is DOUBLE PRECISION array, dimension (LDZ,N) > If WANTZ is .TRUE., on entry Z must contain the current > matrix Z of transformations accumulated by DHSEQR, and on > exit Z has been updated; transformations are applied only to > the submatrix Z(ILOZ:IHIZ,ILO:IHI). > If WANTZ is .FALSE., Z is not referenced. > \endverbatim > > \param[in] LDZ > \verbatim > LDZ is INTEGER > The leading dimension of the array Z. LDZ >= max(1,N). > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > .GT. 0: If INFO = i, DLAHQR failed to compute all the > eigenvalues ILO to IHI in a total of 30 iterations > per eigenvalue; elements i+1:ihi of WR and WI > contain those eigenvalues which have been > successfully computed. > > If INFO .GT. 0 and WANTT is .FALSE., then on exit, > the remaining unconverged eigenvalues are the > eigenvalues of the upper Hessenberg matrix rows > and columns ILO thorugh INFO of the final, output > value of H. > > If INFO .GT. 0 and WANTT is .TRUE., then on exit > (*) (initial value of H)*U = U*(final value of H) > where U is an orthognal matrix. The final > value of H is upper Hessenberg and triangular in > rows and columns INFO+1 through IHI. > > If INFO .GT. 0 and WANTZ is .TRUE., then on exit > (final value of Z) = (initial value of Z)*U > where U is the orthogonal matrix in (*) > (regardless of the value of WANTT.) > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleOTHERauxiliary > \par Further Details: ===================== > > \verbatim > > 02-96 Based on modifications by > David Day, Sandia National Laboratory, USA > > 12-04 Further modifications by > Ralph Byers, University of Kansas, USA > This is a modified version of DLAHQR from LAPACK version 3.0. > It is (1) more robust against overflow and underflow and > (2) adopts the more conservative Ahues & Tisseur stopping > criterion (LAWN 122, 1997). > \endverbatim > ===================================================================== Subroutine */ int igraphdlahqr_(logical *wantt, logical *wantz, integer *n, integer *ilo, integer *ihi, doublereal *h__, integer *ldh, doublereal *wr, doublereal *wi, integer *iloz, integer *ihiz, doublereal *z__, integer *ldz, integer *info) { /* System generated locals */ integer h_dim1, h_offset, z_dim1, z_offset, i__1, i__2, i__3; doublereal d__1, d__2, d__3, d__4; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ integer i__, j, k, l, m; doublereal s, v[3]; integer i1, i2; doublereal t1, t2, t3, v2, v3, aa, ab, ba, bb, h11, h12, h21, h22, cs; integer nh; doublereal sn; integer nr; doublereal tr; integer nz; doublereal det, h21s; integer its; doublereal ulp, sum, tst, rt1i, rt2i, rt1r, rt2r; extern /* Subroutine */ int igraphdrot_(integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *), igraphdcopy_( integer *, doublereal *, integer *, doublereal *, integer *), igraphdlanv2_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *), igraphdlabad_(doublereal *, doublereal *); extern doublereal igraphdlamch_(char *); extern /* Subroutine */ int igraphdlarfg_(integer *, doublereal *, doublereal *, integer *, doublereal *); doublereal safmin, safmax, rtdisc, smlnum; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ========================================================= Parameter adjustments */ h_dim1 = *ldh; h_offset = 1 + h_dim1; h__ -= h_offset; --wr; --wi; z_dim1 = *ldz; z_offset = 1 + z_dim1; z__ -= z_offset; /* Function Body */ *info = 0; /* Quick return if possible */ if (*n == 0) { return 0; } if (*ilo == *ihi) { wr[*ilo] = h__[*ilo + *ilo * h_dim1]; wi[*ilo] = 0.; return 0; } /* ==== clear out the trash ==== */ i__1 = *ihi - 3; for (j = *ilo; j <= i__1; ++j) { h__[j + 2 + j * h_dim1] = 0.; h__[j + 3 + j * h_dim1] = 0.; /* L10: */ } if (*ilo <= *ihi - 2) { h__[*ihi + (*ihi - 2) * h_dim1] = 0.; } nh = *ihi - *ilo + 1; nz = *ihiz - *iloz + 1; /* Set machine-dependent constants for the stopping criterion. */ safmin = igraphdlamch_("SAFE MINIMUM"); safmax = 1. / safmin; igraphdlabad_(&safmin, &safmax); ulp = igraphdlamch_("PRECISION"); smlnum = safmin * ((doublereal) nh / ulp); /* I1 and I2 are the indices of the first row and last column of H to which transformations must be applied. If eigenvalues only are being computed, I1 and I2 are set inside the main loop. */ if (*wantt) { i1 = 1; i2 = *n; } /* The main loop begins here. I is the loop index and decreases from IHI to ILO in steps of 1 or 2. Each iteration of the loop works with the active submatrix in rows and columns L to I. Eigenvalues I+1 to IHI have already converged. Either L = ILO or H(L,L-1) is negligible so that the matrix splits. */ i__ = *ihi; L20: l = *ilo; if (i__ < *ilo) { goto L160; } /* Perform QR iterations on rows and columns ILO to I until a submatrix of order 1 or 2 splits off at the bottom because a subdiagonal element has become negligible. */ for (its = 0; its <= 30; ++its) { /* Look for a single small subdiagonal element. */ i__1 = l + 1; for (k = i__; k >= i__1; --k) { if ((d__1 = h__[k + (k - 1) * h_dim1], abs(d__1)) <= smlnum) { goto L40; } tst = (d__1 = h__[k - 1 + (k - 1) * h_dim1], abs(d__1)) + (d__2 = h__[k + k * h_dim1], abs(d__2)); if (tst == 0.) { if (k - 2 >= *ilo) { tst += (d__1 = h__[k - 1 + (k - 2) * h_dim1], abs(d__1)); } if (k + 1 <= *ihi) { tst += (d__1 = h__[k + 1 + k * h_dim1], abs(d__1)); } } /* ==== The following is a conservative small subdiagonal . deflation criterion due to Ahues & Tisseur (LAWN 122, . 1997). It has better mathematical foundation and . improves accuracy in some cases. ==== */ if ((d__1 = h__[k + (k - 1) * h_dim1], abs(d__1)) <= ulp * tst) { /* Computing MAX */ d__3 = (d__1 = h__[k + (k - 1) * h_dim1], abs(d__1)), d__4 = ( d__2 = h__[k - 1 + k * h_dim1], abs(d__2)); ab = max(d__3,d__4); /* Computing MIN */ d__3 = (d__1 = h__[k + (k - 1) * h_dim1], abs(d__1)), d__4 = ( d__2 = h__[k - 1 + k * h_dim1], abs(d__2)); ba = min(d__3,d__4); /* Computing MAX */ d__3 = (d__1 = h__[k + k * h_dim1], abs(d__1)), d__4 = (d__2 = h__[k - 1 + (k - 1) * h_dim1] - h__[k + k * h_dim1], abs(d__2)); aa = max(d__3,d__4); /* Computing MIN */ d__3 = (d__1 = h__[k + k * h_dim1], abs(d__1)), d__4 = (d__2 = h__[k - 1 + (k - 1) * h_dim1] - h__[k + k * h_dim1], abs(d__2)); bb = min(d__3,d__4); s = aa + ab; /* Computing MAX */ d__1 = smlnum, d__2 = ulp * (bb * (aa / s)); if (ba * (ab / s) <= max(d__1,d__2)) { goto L40; } } /* L30: */ } L40: l = k; if (l > *ilo) { /* H(L,L-1) is negligible */ h__[l + (l - 1) * h_dim1] = 0.; } /* Exit from loop if a submatrix of order 1 or 2 has split off. */ if (l >= i__ - 1) { goto L150; } /* Now the active submatrix is in rows and columns L to I. If eigenvalues only are being computed, only the active submatrix need be transformed. */ if (! (*wantt)) { i1 = l; i2 = i__; } if (its == 10) { /* Exceptional shift. */ s = (d__1 = h__[l + 1 + l * h_dim1], abs(d__1)) + (d__2 = h__[l + 2 + (l + 1) * h_dim1], abs(d__2)); h11 = s * .75 + h__[l + l * h_dim1]; h12 = s * -.4375; h21 = s; h22 = h11; } else if (its == 20) { /* Exceptional shift. */ s = (d__1 = h__[i__ + (i__ - 1) * h_dim1], abs(d__1)) + (d__2 = h__[i__ - 1 + (i__ - 2) * h_dim1], abs(d__2)); h11 = s * .75 + h__[i__ + i__ * h_dim1]; h12 = s * -.4375; h21 = s; h22 = h11; } else { /* Prepare to use Francis' double shift (i.e. 2nd degree generalized Rayleigh quotient) */ h11 = h__[i__ - 1 + (i__ - 1) * h_dim1]; h21 = h__[i__ + (i__ - 1) * h_dim1]; h12 = h__[i__ - 1 + i__ * h_dim1]; h22 = h__[i__ + i__ * h_dim1]; } s = abs(h11) + abs(h12) + abs(h21) + abs(h22); if (s == 0.) { rt1r = 0.; rt1i = 0.; rt2r = 0.; rt2i = 0.; } else { h11 /= s; h21 /= s; h12 /= s; h22 /= s; tr = (h11 + h22) / 2.; det = (h11 - tr) * (h22 - tr) - h12 * h21; rtdisc = sqrt((abs(det))); if (det >= 0.) { /* ==== complex conjugate shifts ==== */ rt1r = tr * s; rt2r = rt1r; rt1i = rtdisc * s; rt2i = -rt1i; } else { /* ==== real shifts (use only one of them) ==== */ rt1r = tr + rtdisc; rt2r = tr - rtdisc; if ((d__1 = rt1r - h22, abs(d__1)) <= (d__2 = rt2r - h22, abs( d__2))) { rt1r *= s; rt2r = rt1r; } else { rt2r *= s; rt1r = rt2r; } rt1i = 0.; rt2i = 0.; } } /* Look for two consecutive small subdiagonal elements. */ i__1 = l; for (m = i__ - 2; m >= i__1; --m) { /* Determine the effect of starting the double-shift QR iteration at row M, and see if this would make H(M,M-1) negligible. (The following uses scaling to avoid overflows and most underflows.) */ h21s = h__[m + 1 + m * h_dim1]; s = (d__1 = h__[m + m * h_dim1] - rt2r, abs(d__1)) + abs(rt2i) + abs(h21s); h21s = h__[m + 1 + m * h_dim1] / s; v[0] = h21s * h__[m + (m + 1) * h_dim1] + (h__[m + m * h_dim1] - rt1r) * ((h__[m + m * h_dim1] - rt2r) / s) - rt1i * (rt2i / s); v[1] = h21s * (h__[m + m * h_dim1] + h__[m + 1 + (m + 1) * h_dim1] - rt1r - rt2r); v[2] = h21s * h__[m + 2 + (m + 1) * h_dim1]; s = abs(v[0]) + abs(v[1]) + abs(v[2]); v[0] /= s; v[1] /= s; v[2] /= s; if (m == l) { goto L60; } if ((d__1 = h__[m + (m - 1) * h_dim1], abs(d__1)) * (abs(v[1]) + abs(v[2])) <= ulp * abs(v[0]) * ((d__2 = h__[m - 1 + (m - 1) * h_dim1], abs(d__2)) + (d__3 = h__[m + m * h_dim1], abs(d__3)) + (d__4 = h__[m + 1 + (m + 1) * h_dim1], abs( d__4)))) { goto L60; } /* L50: */ } L60: /* Double-shift QR step */ i__1 = i__ - 1; for (k = m; k <= i__1; ++k) { /* The first iteration of this loop determines a reflection G from the vector V and applies it from left and right to H, thus creating a nonzero bulge below the subdiagonal. Each subsequent iteration determines a reflection G to restore the Hessenberg form in the (K-1)th column, and thus chases the bulge one step toward the bottom of the active submatrix. NR is the order of G. Computing MIN */ i__2 = 3, i__3 = i__ - k + 1; nr = min(i__2,i__3); if (k > m) { igraphdcopy_(&nr, &h__[k + (k - 1) * h_dim1], &c__1, v, &c__1); } igraphdlarfg_(&nr, v, &v[1], &c__1, &t1); if (k > m) { h__[k + (k - 1) * h_dim1] = v[0]; h__[k + 1 + (k - 1) * h_dim1] = 0.; if (k < i__ - 1) { h__[k + 2 + (k - 1) * h_dim1] = 0.; } } else if (m > l) { /* ==== Use the following instead of . H( K, K-1 ) = -H( K, K-1 ) to . avoid a bug when v(2) and v(3) . underflow. ==== */ h__[k + (k - 1) * h_dim1] *= 1. - t1; } v2 = v[1]; t2 = t1 * v2; if (nr == 3) { v3 = v[2]; t3 = t1 * v3; /* Apply G from the left to transform the rows of the matrix in columns K to I2. */ i__2 = i2; for (j = k; j <= i__2; ++j) { sum = h__[k + j * h_dim1] + v2 * h__[k + 1 + j * h_dim1] + v3 * h__[k + 2 + j * h_dim1]; h__[k + j * h_dim1] -= sum * t1; h__[k + 1 + j * h_dim1] -= sum * t2; h__[k + 2 + j * h_dim1] -= sum * t3; /* L70: */ } /* Apply G from the right to transform the columns of the matrix in rows I1 to min(K+3,I). Computing MIN */ i__3 = k + 3; i__2 = min(i__3,i__); for (j = i1; j <= i__2; ++j) { sum = h__[j + k * h_dim1] + v2 * h__[j + (k + 1) * h_dim1] + v3 * h__[j + (k + 2) * h_dim1]; h__[j + k * h_dim1] -= sum * t1; h__[j + (k + 1) * h_dim1] -= sum * t2; h__[j + (k + 2) * h_dim1] -= sum * t3; /* L80: */ } if (*wantz) { /* Accumulate transformations in the matrix Z */ i__2 = *ihiz; for (j = *iloz; j <= i__2; ++j) { sum = z__[j + k * z_dim1] + v2 * z__[j + (k + 1) * z_dim1] + v3 * z__[j + (k + 2) * z_dim1]; z__[j + k * z_dim1] -= sum * t1; z__[j + (k + 1) * z_dim1] -= sum * t2; z__[j + (k + 2) * z_dim1] -= sum * t3; /* L90: */ } } } else if (nr == 2) { /* Apply G from the left to transform the rows of the matrix in columns K to I2. */ i__2 = i2; for (j = k; j <= i__2; ++j) { sum = h__[k + j * h_dim1] + v2 * h__[k + 1 + j * h_dim1]; h__[k + j * h_dim1] -= sum * t1; h__[k + 1 + j * h_dim1] -= sum * t2; /* L100: */ } /* Apply G from the right to transform the columns of the matrix in rows I1 to min(K+3,I). */ i__2 = i__; for (j = i1; j <= i__2; ++j) { sum = h__[j + k * h_dim1] + v2 * h__[j + (k + 1) * h_dim1] ; h__[j + k * h_dim1] -= sum * t1; h__[j + (k + 1) * h_dim1] -= sum * t2; /* L110: */ } if (*wantz) { /* Accumulate transformations in the matrix Z */ i__2 = *ihiz; for (j = *iloz; j <= i__2; ++j) { sum = z__[j + k * z_dim1] + v2 * z__[j + (k + 1) * z_dim1]; z__[j + k * z_dim1] -= sum * t1; z__[j + (k + 1) * z_dim1] -= sum * t2; /* L120: */ } } } /* L130: */ } /* L140: */ } /* Failure to converge in remaining number of iterations */ *info = i__; return 0; L150: if (l == i__) { /* H(I,I-1) is negligible: one eigenvalue has converged. */ wr[i__] = h__[i__ + i__ * h_dim1]; wi[i__] = 0.; } else if (l == i__ - 1) { /* H(I-1,I-2) is negligible: a pair of eigenvalues have converged. Transform the 2-by-2 submatrix to standard Schur form, and compute and store the eigenvalues. */ igraphdlanv2_(&h__[i__ - 1 + (i__ - 1) * h_dim1], &h__[i__ - 1 + i__ * h_dim1], &h__[i__ + (i__ - 1) * h_dim1], &h__[i__ + i__ * h_dim1], &wr[i__ - 1], &wi[i__ - 1], &wr[i__], &wi[i__], &cs, &sn); if (*wantt) { /* Apply the transformation to the rest of H. */ if (i2 > i__) { i__1 = i2 - i__; igraphdrot_(&i__1, &h__[i__ - 1 + (i__ + 1) * h_dim1], ldh, &h__[ i__ + (i__ + 1) * h_dim1], ldh, &cs, &sn); } i__1 = i__ - i1 - 1; igraphdrot_(&i__1, &h__[i1 + (i__ - 1) * h_dim1], &c__1, &h__[i1 + i__ * h_dim1], &c__1, &cs, &sn); } if (*wantz) { /* Apply the transformation to Z. */ igraphdrot_(&nz, &z__[*iloz + (i__ - 1) * z_dim1], &c__1, &z__[*iloz + i__ * z_dim1], &c__1, &cs, &sn); } } /* return to start of the main loop with new value of I. */ i__ = l - 1; goto L20; L160: return 0; /* End of DLAHQR */ } /* igraphdlahqr_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlaqr4.c0000644000076500000240000007043413524616145024203 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__13 = 13; static integer c__15 = 15; static integer c_n1 = -1; static integer c__12 = 12; static integer c__14 = 14; static integer c__16 = 16; static logical c_false = FALSE_; static integer c__1 = 1; static integer c__3 = 3; /* > \brief \b DLAQR4 computes the eigenvalues of a Hessenberg matrix, and optionally the matrices from the Sc hur decomposition. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLAQR4 + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLAQR4( WANTT, WANTZ, N, ILO, IHI, H, LDH, WR, WI, ILOZ, IHIZ, Z, LDZ, WORK, LWORK, INFO ) INTEGER IHI, IHIZ, ILO, ILOZ, INFO, LDH, LDZ, LWORK, N LOGICAL WANTT, WANTZ DOUBLE PRECISION H( LDH, * ), WI( * ), WORK( * ), WR( * ), $ Z( LDZ, * ) > \par Purpose: ============= > > \verbatim > > DLAQR4 implements one level of recursion for DLAQR0. > It is a complete implementation of the small bulge multi-shift > QR algorithm. It may be called by DLAQR0 and, for large enough > deflation window size, it may be called by DLAQR3. This > subroutine is identical to DLAQR0 except that it calls DLAQR2 > instead of DLAQR3. > > DLAQR4 computes the eigenvalues of a Hessenberg matrix H > and, optionally, the matrices T and Z from the Schur decomposition > H = Z T Z**T, where T is an upper quasi-triangular matrix (the > Schur form), and Z is the orthogonal matrix of Schur vectors. > > Optionally Z may be postmultiplied into an input orthogonal > matrix Q so that this routine can give the Schur factorization > of a matrix A which has been reduced to the Hessenberg form H > by the orthogonal matrix Q: A = Q*H*Q**T = (QZ)*T*(QZ)**T. > \endverbatim Arguments: ========== > \param[in] WANTT > \verbatim > WANTT is LOGICAL > = .TRUE. : the full Schur form T is required; > = .FALSE.: only eigenvalues are required. > \endverbatim > > \param[in] WANTZ > \verbatim > WANTZ is LOGICAL > = .TRUE. : the matrix of Schur vectors Z is required; > = .FALSE.: Schur vectors are not required. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix H. N .GE. 0. > \endverbatim > > \param[in] ILO > \verbatim > ILO is INTEGER > \endverbatim > > \param[in] IHI > \verbatim > IHI is INTEGER > It is assumed that H is already upper triangular in rows > and columns 1:ILO-1 and IHI+1:N and, if ILO.GT.1, > H(ILO,ILO-1) is zero. ILO and IHI are normally set by a > previous call to DGEBAL, and then passed to DGEHRD when the > matrix output by DGEBAL is reduced to Hessenberg form. > Otherwise, ILO and IHI should be set to 1 and N, > respectively. If N.GT.0, then 1.LE.ILO.LE.IHI.LE.N. > If N = 0, then ILO = 1 and IHI = 0. > \endverbatim > > \param[in,out] H > \verbatim > H is DOUBLE PRECISION array, dimension (LDH,N) > On entry, the upper Hessenberg matrix H. > On exit, if INFO = 0 and WANTT is .TRUE., then H contains > the upper quasi-triangular matrix T from the Schur > decomposition (the Schur form); 2-by-2 diagonal blocks > (corresponding to complex conjugate pairs of eigenvalues) > are returned in standard form, with H(i,i) = H(i+1,i+1) > and H(i+1,i)*H(i,i+1).LT.0. If INFO = 0 and WANTT is > .FALSE., then the contents of H are unspecified on exit. > (The output value of H when INFO.GT.0 is given under the > description of INFO below.) > > This subroutine may explicitly set H(i,j) = 0 for i.GT.j and > j = 1, 2, ... ILO-1 or j = IHI+1, IHI+2, ... N. > \endverbatim > > \param[in] LDH > \verbatim > LDH is INTEGER > The leading dimension of the array H. LDH .GE. max(1,N). > \endverbatim > > \param[out] WR > \verbatim > WR is DOUBLE PRECISION array, dimension (IHI) > \endverbatim > > \param[out] WI > \verbatim > WI is DOUBLE PRECISION array, dimension (IHI) > The real and imaginary parts, respectively, of the computed > eigenvalues of H(ILO:IHI,ILO:IHI) are stored in WR(ILO:IHI) > and WI(ILO:IHI). If two eigenvalues are computed as a > complex conjugate pair, they are stored in consecutive > elements of WR and WI, say the i-th and (i+1)th, with > WI(i) .GT. 0 and WI(i+1) .LT. 0. If WANTT is .TRUE., then > the eigenvalues are stored in the same order as on the > diagonal of the Schur form returned in H, with > WR(i) = H(i,i) and, if H(i:i+1,i:i+1) is a 2-by-2 diagonal > block, WI(i) = sqrt(-H(i+1,i)*H(i,i+1)) and > WI(i+1) = -WI(i). > \endverbatim > > \param[in] ILOZ > \verbatim > ILOZ is INTEGER > \endverbatim > > \param[in] IHIZ > \verbatim > IHIZ is INTEGER > Specify the rows of Z to which transformations must be > applied if WANTZ is .TRUE.. > 1 .LE. ILOZ .LE. ILO; IHI .LE. IHIZ .LE. N. > \endverbatim > > \param[in,out] Z > \verbatim > Z is DOUBLE PRECISION array, dimension (LDZ,IHI) > If WANTZ is .FALSE., then Z is not referenced. > If WANTZ is .TRUE., then Z(ILO:IHI,ILOZ:IHIZ) is > replaced by Z(ILO:IHI,ILOZ:IHIZ)*U where U is the > orthogonal Schur factor of H(ILO:IHI,ILO:IHI). > (The output value of Z when INFO.GT.0 is given under > the description of INFO below.) > \endverbatim > > \param[in] LDZ > \verbatim > LDZ is INTEGER > The leading dimension of the array Z. if WANTZ is .TRUE. > then LDZ.GE.MAX(1,IHIZ). Otherwize, LDZ.GE.1. > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension LWORK > On exit, if LWORK = -1, WORK(1) returns an estimate of > the optimal value for LWORK. > \endverbatim > > \param[in] LWORK > \verbatim > LWORK is INTEGER > The dimension of the array WORK. LWORK .GE. max(1,N) > is sufficient, but LWORK typically as large as 6*N may > be required for optimal performance. A workspace query > to determine the optimal workspace size is recommended. > > If LWORK = -1, then DLAQR4 does a workspace query. > In this case, DLAQR4 checks the input parameters and > estimates the optimal workspace size for the given > values of N, ILO and IHI. The estimate is returned > in WORK(1). No error message related to LWORK is > issued by XERBLA. Neither H nor Z are accessed. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > .GT. 0: if INFO = i, DLAQR4 failed to compute all of > the eigenvalues. Elements 1:ilo-1 and i+1:n of WR > and WI contain those eigenvalues which have been > successfully computed. (Failures are rare.) > > If INFO .GT. 0 and WANT is .FALSE., then on exit, > the remaining unconverged eigenvalues are the eigen- > values of the upper Hessenberg matrix rows and > columns ILO through INFO of the final, output > value of H. > > If INFO .GT. 0 and WANTT is .TRUE., then on exit > > (*) (initial value of H)*U = U*(final value of H) > > where U is a orthogonal matrix. The final > value of H is upper Hessenberg and triangular in > rows and columns INFO+1 through IHI. > > If INFO .GT. 0 and WANTZ is .TRUE., then on exit > > (final value of Z(ILO:IHI,ILOZ:IHIZ) > = (initial value of Z(ILO:IHI,ILOZ:IHIZ)*U > > where U is the orthogonal matrix in (*) (regard- > less of the value of WANTT.) > > If INFO .GT. 0 and WANTZ is .FALSE., then Z is not > accessed. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleOTHERauxiliary > \par Contributors: ================== > > Karen Braman and Ralph Byers, Department of Mathematics, > University of Kansas, USA > \par References: ================ > > K. Braman, R. Byers and R. Mathias, The Multi-Shift QR > Algorithm Part I: Maintaining Well Focused Shifts, and Level 3 > Performance, SIAM Journal of Matrix Analysis, volume 23, pages > 929--947, 2002. > \n > K. Braman, R. Byers and R. Mathias, The Multi-Shift QR > Algorithm Part II: Aggressive Early Deflation, SIAM Journal > of Matrix Analysis, volume 23, pages 948--973, 2002. > ===================================================================== Subroutine */ int igraphdlaqr4_(logical *wantt, logical *wantz, integer *n, integer *ilo, integer *ihi, doublereal *h__, integer *ldh, doublereal *wr, doublereal *wi, integer *iloz, integer *ihiz, doublereal *z__, integer *ldz, doublereal *work, integer *lwork, integer *info) { /* System generated locals */ integer h_dim1, h_offset, z_dim1, z_offset, i__1, i__2, i__3, i__4, i__5; doublereal d__1, d__2, d__3, d__4; /* Local variables */ integer i__, k; doublereal aa, bb, cc, dd; integer ld; doublereal cs; integer nh, it, ks, kt; doublereal sn; integer ku, kv, ls, ns; doublereal ss; integer nw, inf, kdu, nho, nve, kwh, nsr, nwr, kwv, ndec, ndfl, kbot, nmin; doublereal swap; integer ktop; doublereal zdum[1] /* was [1][1] */; integer kacc22, itmax, nsmax, nwmax, kwtop; extern /* Subroutine */ int igraphdlaqr2_(logical *, logical *, integer *, integer *, integer *, integer *, doublereal *, integer *, integer *, integer *, doublereal *, integer *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *, integer *, doublereal *, integer *, integer *, doublereal *, integer *, doublereal *, integer *), igraphdlanv2_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *), igraphdlaqr5_( logical *, logical *, integer *, integer *, integer *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, integer *, integer *, doublereal *, integer *, integer *, doublereal *, integer *); integer nibble; extern /* Subroutine */ int igraphdlahqr_(logical *, logical *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, integer *, integer *), igraphdlacpy_(char *, integer *, integer *, doublereal *, integer *, doublereal *, integer *); extern integer igraphilaenv_(integer *, char *, char *, integer *, integer *, integer *, integer *, ftnlen, ftnlen); char jbcmpz[2]; integer nwupbd; logical sorted; integer lwkopt; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ================================================================ ==== Matrices of order NTINY or smaller must be processed by . DLAHQR because of insufficient subdiagonal scratch space. . (This is a hard limit.) ==== ==== Exceptional deflation windows: try to cure rare . slow convergence by varying the size of the . deflation window after KEXNW iterations. ==== ==== Exceptional shifts: try to cure rare slow convergence . with ad-hoc exceptional shifts every KEXSH iterations. . ==== ==== The constants WILK1 and WILK2 are used to form the . exceptional shifts. ==== Parameter adjustments */ h_dim1 = *ldh; h_offset = 1 + h_dim1; h__ -= h_offset; --wr; --wi; z_dim1 = *ldz; z_offset = 1 + z_dim1; z__ -= z_offset; --work; /* Function Body */ *info = 0; /* ==== Quick return for N = 0: nothing to do. ==== */ if (*n == 0) { work[1] = 1.; return 0; } if (*n <= 11) { /* ==== Tiny matrices must use DLAHQR. ==== */ lwkopt = 1; if (*lwork != -1) { igraphdlahqr_(wantt, wantz, n, ilo, ihi, &h__[h_offset], ldh, &wr[1], & wi[1], iloz, ihiz, &z__[z_offset], ldz, info); } } else { /* ==== Use small bulge multi-shift QR with aggressive early . deflation on larger-than-tiny matrices. ==== ==== Hope for the best. ==== */ *info = 0; /* ==== Set up job flags for ILAENV. ==== */ if (*wantt) { *(unsigned char *)jbcmpz = 'S'; } else { *(unsigned char *)jbcmpz = 'E'; } if (*wantz) { *(unsigned char *)&jbcmpz[1] = 'V'; } else { *(unsigned char *)&jbcmpz[1] = 'N'; } /* ==== NWR = recommended deflation window size. At this . point, N .GT. NTINY = 11, so there is enough . subdiagonal workspace for NWR.GE.2 as required. . (In fact, there is enough subdiagonal space for . NWR.GE.3.) ==== */ nwr = igraphilaenv_(&c__13, "DLAQR4", jbcmpz, n, ilo, ihi, lwork, (ftnlen)6, (ftnlen)2); nwr = max(2,nwr); /* Computing MIN */ i__1 = *ihi - *ilo + 1, i__2 = (*n - 1) / 3, i__1 = min(i__1,i__2); nwr = min(i__1,nwr); /* ==== NSR = recommended number of simultaneous shifts. . At this point N .GT. NTINY = 11, so there is at . enough subdiagonal workspace for NSR to be even . and greater than or equal to two as required. ==== */ nsr = igraphilaenv_(&c__15, "DLAQR4", jbcmpz, n, ilo, ihi, lwork, (ftnlen)6, (ftnlen)2); /* Computing MIN */ i__1 = nsr, i__2 = (*n + 6) / 9, i__1 = min(i__1,i__2), i__2 = *ihi - *ilo; nsr = min(i__1,i__2); /* Computing MAX */ i__1 = 2, i__2 = nsr - nsr % 2; nsr = max(i__1,i__2); /* ==== Estimate optimal workspace ==== ==== Workspace query call to DLAQR2 ==== */ i__1 = nwr + 1; igraphdlaqr2_(wantt, wantz, n, ilo, ihi, &i__1, &h__[h_offset], ldh, iloz, ihiz, &z__[z_offset], ldz, &ls, &ld, &wr[1], &wi[1], &h__[ h_offset], ldh, n, &h__[h_offset], ldh, n, &h__[h_offset], ldh, &work[1], &c_n1); /* ==== Optimal workspace = MAX(DLAQR5, DLAQR2) ==== Computing MAX */ i__1 = nsr * 3 / 2, i__2 = (integer) work[1]; lwkopt = max(i__1,i__2); /* ==== Quick return in case of workspace query. ==== */ if (*lwork == -1) { work[1] = (doublereal) lwkopt; return 0; } /* ==== DLAHQR/DLAQR0 crossover point ==== */ nmin = igraphilaenv_(&c__12, "DLAQR4", jbcmpz, n, ilo, ihi, lwork, (ftnlen) 6, (ftnlen)2); nmin = max(11,nmin); /* ==== Nibble crossover point ==== */ nibble = igraphilaenv_(&c__14, "DLAQR4", jbcmpz, n, ilo, ihi, lwork, ( ftnlen)6, (ftnlen)2); nibble = max(0,nibble); /* ==== Accumulate reflections during ttswp? Use block . 2-by-2 structure during matrix-matrix multiply? ==== */ kacc22 = igraphilaenv_(&c__16, "DLAQR4", jbcmpz, n, ilo, ihi, lwork, ( ftnlen)6, (ftnlen)2); kacc22 = max(0,kacc22); kacc22 = min(2,kacc22); /* ==== NWMAX = the largest possible deflation window for . which there is sufficient workspace. ==== Computing MIN */ i__1 = (*n - 1) / 3, i__2 = *lwork / 2; nwmax = min(i__1,i__2); nw = nwmax; /* ==== NSMAX = the Largest number of simultaneous shifts . for which there is sufficient workspace. ==== Computing MIN */ i__1 = (*n + 6) / 9, i__2 = (*lwork << 1) / 3; nsmax = min(i__1,i__2); nsmax -= nsmax % 2; /* ==== NDFL: an iteration count restarted at deflation. ==== */ ndfl = 1; /* ==== ITMAX = iteration limit ==== Computing MAX */ i__1 = 10, i__2 = *ihi - *ilo + 1; itmax = max(i__1,i__2) * 30; /* ==== Last row and column in the active block ==== */ kbot = *ihi; /* ==== Main Loop ==== */ i__1 = itmax; for (it = 1; it <= i__1; ++it) { /* ==== Done when KBOT falls below ILO ==== */ if (kbot < *ilo) { goto L90; } /* ==== Locate active block ==== */ i__2 = *ilo + 1; for (k = kbot; k >= i__2; --k) { if (h__[k + (k - 1) * h_dim1] == 0.) { goto L20; } /* L10: */ } k = *ilo; L20: ktop = k; /* ==== Select deflation window size: . Typical Case: . If possible and advisable, nibble the entire . active block. If not, use size MIN(NWR,NWMAX) . or MIN(NWR+1,NWMAX) depending upon which has . the smaller corresponding subdiagonal entry . (a heuristic). . . Exceptional Case: . If there have been no deflations in KEXNW or . more iterations, then vary the deflation window . size. At first, because, larger windows are, . in general, more powerful than smaller ones, . rapidly increase the window to the maximum possible. . Then, gradually reduce the window size. ==== */ nh = kbot - ktop + 1; nwupbd = min(nh,nwmax); if (ndfl < 5) { nw = min(nwupbd,nwr); } else { /* Computing MIN */ i__2 = nwupbd, i__3 = nw << 1; nw = min(i__2,i__3); } if (nw < nwmax) { if (nw >= nh - 1) { nw = nh; } else { kwtop = kbot - nw + 1; if ((d__1 = h__[kwtop + (kwtop - 1) * h_dim1], abs(d__1)) > (d__2 = h__[kwtop - 1 + (kwtop - 2) * h_dim1], abs(d__2))) { ++nw; } } } if (ndfl < 5) { ndec = -1; } else if (ndec >= 0 || nw >= nwupbd) { ++ndec; if (nw - ndec < 2) { ndec = 0; } nw -= ndec; } /* ==== Aggressive early deflation: . split workspace under the subdiagonal into . - an nw-by-nw work array V in the lower . left-hand-corner, . - an NW-by-at-least-NW-but-more-is-better . (NW-by-NHO) horizontal work array along . the bottom edge, . - an at-least-NW-but-more-is-better (NHV-by-NW) . vertical work array along the left-hand-edge. . ==== */ kv = *n - nw + 1; kt = nw + 1; nho = *n - nw - 1 - kt + 1; kwv = nw + 2; nve = *n - nw - kwv + 1; /* ==== Aggressive early deflation ==== */ igraphdlaqr2_(wantt, wantz, n, &ktop, &kbot, &nw, &h__[h_offset], ldh, iloz, ihiz, &z__[z_offset], ldz, &ls, &ld, &wr[1], &wi[1], &h__[kv + h_dim1], ldh, &nho, &h__[kv + kt * h_dim1], ldh, &nve, &h__[kwv + h_dim1], ldh, &work[1], lwork); /* ==== Adjust KBOT accounting for new deflations. ==== */ kbot -= ld; /* ==== KS points to the shifts. ==== */ ks = kbot - ls + 1; /* ==== Skip an expensive QR sweep if there is a (partly . heuristic) reason to expect that many eigenvalues . will deflate without it. Here, the QR sweep is . skipped if many eigenvalues have just been deflated . or if the remaining active block is small. */ if (ld == 0 || ld * 100 <= nw * nibble && kbot - ktop + 1 > min( nmin,nwmax)) { /* ==== NS = nominal number of simultaneous shifts. . This may be lowered (slightly) if DLAQR2 . did not provide that many shifts. ==== Computing MIN Computing MAX */ i__4 = 2, i__5 = kbot - ktop; i__2 = min(nsmax,nsr), i__3 = max(i__4,i__5); ns = min(i__2,i__3); ns -= ns % 2; /* ==== If there have been no deflations . in a multiple of KEXSH iterations, . then try exceptional shifts. . Otherwise use shifts provided by . DLAQR2 above or from the eigenvalues . of a trailing principal submatrix. ==== */ if (ndfl % 6 == 0) { ks = kbot - ns + 1; /* Computing MAX */ i__3 = ks + 1, i__4 = ktop + 2; i__2 = max(i__3,i__4); for (i__ = kbot; i__ >= i__2; i__ += -2) { ss = (d__1 = h__[i__ + (i__ - 1) * h_dim1], abs(d__1)) + (d__2 = h__[i__ - 1 + (i__ - 2) * h_dim1], abs(d__2)); aa = ss * .75 + h__[i__ + i__ * h_dim1]; bb = ss; cc = ss * -.4375; dd = aa; igraphdlanv2_(&aa, &bb, &cc, &dd, &wr[i__ - 1], &wi[i__ - 1] , &wr[i__], &wi[i__], &cs, &sn); /* L30: */ } if (ks == ktop) { wr[ks + 1] = h__[ks + 1 + (ks + 1) * h_dim1]; wi[ks + 1] = 0.; wr[ks] = wr[ks + 1]; wi[ks] = wi[ks + 1]; } } else { /* ==== Got NS/2 or fewer shifts? Use DLAHQR . on a trailing principal submatrix to . get more. (Since NS.LE.NSMAX.LE.(N+6)/9, . there is enough space below the subdiagonal . to fit an NS-by-NS scratch array.) ==== */ if (kbot - ks + 1 <= ns / 2) { ks = kbot - ns + 1; kt = *n - ns + 1; igraphdlacpy_("A", &ns, &ns, &h__[ks + ks * h_dim1], ldh, & h__[kt + h_dim1], ldh); igraphdlahqr_(&c_false, &c_false, &ns, &c__1, &ns, &h__[kt + h_dim1], ldh, &wr[ks], &wi[ks], &c__1, & c__1, zdum, &c__1, &inf); ks += inf; /* ==== In case of a rare QR failure use . eigenvalues of the trailing 2-by-2 . principal submatrix. ==== */ if (ks >= kbot) { aa = h__[kbot - 1 + (kbot - 1) * h_dim1]; cc = h__[kbot + (kbot - 1) * h_dim1]; bb = h__[kbot - 1 + kbot * h_dim1]; dd = h__[kbot + kbot * h_dim1]; igraphdlanv2_(&aa, &bb, &cc, &dd, &wr[kbot - 1], &wi[ kbot - 1], &wr[kbot], &wi[kbot], &cs, &sn) ; ks = kbot - 1; } } if (kbot - ks + 1 > ns) { /* ==== Sort the shifts (Helps a little) . Bubble sort keeps complex conjugate . pairs together. ==== */ sorted = FALSE_; i__2 = ks + 1; for (k = kbot; k >= i__2; --k) { if (sorted) { goto L60; } sorted = TRUE_; i__3 = k - 1; for (i__ = ks; i__ <= i__3; ++i__) { if ((d__1 = wr[i__], abs(d__1)) + (d__2 = wi[ i__], abs(d__2)) < (d__3 = wr[i__ + 1] , abs(d__3)) + (d__4 = wi[i__ + 1], abs(d__4))) { sorted = FALSE_; swap = wr[i__]; wr[i__] = wr[i__ + 1]; wr[i__ + 1] = swap; swap = wi[i__]; wi[i__] = wi[i__ + 1]; wi[i__ + 1] = swap; } /* L40: */ } /* L50: */ } L60: ; } /* ==== Shuffle shifts into pairs of real shifts . and pairs of complex conjugate shifts . assuming complex conjugate shifts are . already adjacent to one another. (Yes, . they are.) ==== */ i__2 = ks + 2; for (i__ = kbot; i__ >= i__2; i__ += -2) { if (wi[i__] != -wi[i__ - 1]) { swap = wr[i__]; wr[i__] = wr[i__ - 1]; wr[i__ - 1] = wr[i__ - 2]; wr[i__ - 2] = swap; swap = wi[i__]; wi[i__] = wi[i__ - 1]; wi[i__ - 1] = wi[i__ - 2]; wi[i__ - 2] = swap; } /* L70: */ } } /* ==== If there are only two shifts and both are . real, then use only one. ==== */ if (kbot - ks + 1 == 2) { if (wi[kbot] == 0.) { if ((d__1 = wr[kbot] - h__[kbot + kbot * h_dim1], abs( d__1)) < (d__2 = wr[kbot - 1] - h__[kbot + kbot * h_dim1], abs(d__2))) { wr[kbot - 1] = wr[kbot]; } else { wr[kbot] = wr[kbot - 1]; } } } /* ==== Use up to NS of the the smallest magnatiude . shifts. If there aren't NS shifts available, . then use them all, possibly dropping one to . make the number of shifts even. ==== Computing MIN */ i__2 = ns, i__3 = kbot - ks + 1; ns = min(i__2,i__3); ns -= ns % 2; ks = kbot - ns + 1; /* ==== Small-bulge multi-shift QR sweep: . split workspace under the subdiagonal into . - a KDU-by-KDU work array U in the lower . left-hand-corner, . - a KDU-by-at-least-KDU-but-more-is-better . (KDU-by-NHo) horizontal work array WH along . the bottom edge, . - and an at-least-KDU-but-more-is-better-by-KDU . (NVE-by-KDU) vertical work WV arrow along . the left-hand-edge. ==== */ kdu = ns * 3 - 3; ku = *n - kdu + 1; kwh = kdu + 1; nho = *n - kdu - 3 - (kdu + 1) + 1; kwv = kdu + 4; nve = *n - kdu - kwv + 1; /* ==== Small-bulge multi-shift QR sweep ==== */ igraphdlaqr5_(wantt, wantz, &kacc22, n, &ktop, &kbot, &ns, &wr[ks], &wi[ks], &h__[h_offset], ldh, iloz, ihiz, &z__[ z_offset], ldz, &work[1], &c__3, &h__[ku + h_dim1], ldh, &nve, &h__[kwv + h_dim1], ldh, &nho, &h__[ku + kwh * h_dim1], ldh); } /* ==== Note progress (or the lack of it). ==== */ if (ld > 0) { ndfl = 1; } else { ++ndfl; } /* ==== End of main loop ==== L80: */ } /* ==== Iteration limit exceeded. Set INFO to show where . the problem occurred and exit. ==== */ *info = kbot; L90: ; } /* ==== Return the optimal value of LWORK. ==== */ work[1] = (doublereal) lwkopt; /* ==== End of DLAQR4 ==== */ return 0; } /* igraphdlaqr4_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlarrv.c0000644000076500000240000012031713524616145024302 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static doublereal c_b5 = 0.; static integer c__1 = 1; static integer c__2 = 2; /* > \brief \b DLARRV computes the eigenvectors of the tridiagonal matrix T = L D LT given L, D and the eigenv alues of L D LT. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLARRV + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLARRV( N, VL, VU, D, L, PIVMIN, ISPLIT, M, DOL, DOU, MINRGP, RTOL1, RTOL2, W, WERR, WGAP, IBLOCK, INDEXW, GERS, Z, LDZ, ISUPPZ, WORK, IWORK, INFO ) INTEGER DOL, DOU, INFO, LDZ, M, N DOUBLE PRECISION MINRGP, PIVMIN, RTOL1, RTOL2, VL, VU INTEGER IBLOCK( * ), INDEXW( * ), ISPLIT( * ), $ ISUPPZ( * ), IWORK( * ) DOUBLE PRECISION D( * ), GERS( * ), L( * ), W( * ), WERR( * ), $ WGAP( * ), WORK( * ) DOUBLE PRECISION Z( LDZ, * ) > \par Purpose: ============= > > \verbatim > > DLARRV computes the eigenvectors of the tridiagonal matrix > T = L D L**T given L, D and APPROXIMATIONS to the eigenvalues of L D L**T. > The input eigenvalues should have been computed by DLARRE. > \endverbatim Arguments: ========== > \param[in] N > \verbatim > N is INTEGER > The order of the matrix. N >= 0. > \endverbatim > > \param[in] VL > \verbatim > VL is DOUBLE PRECISION > \endverbatim > > \param[in] VU > \verbatim > VU is DOUBLE PRECISION > Lower and upper bounds of the interval that contains the desired > eigenvalues. VL < VU. Needed to compute gaps on the left or right > end of the extremal eigenvalues in the desired RANGE. > \endverbatim > > \param[in,out] D > \verbatim > D is DOUBLE PRECISION array, dimension (N) > On entry, the N diagonal elements of the diagonal matrix D. > On exit, D may be overwritten. > \endverbatim > > \param[in,out] L > \verbatim > L is DOUBLE PRECISION array, dimension (N) > On entry, the (N-1) subdiagonal elements of the unit > bidiagonal matrix L are in elements 1 to N-1 of L > (if the matrix is not splitted.) At the end of each block > is stored the corresponding shift as given by DLARRE. > On exit, L is overwritten. > \endverbatim > > \param[in] PIVMIN > \verbatim > PIVMIN is DOUBLE PRECISION > The minimum pivot allowed in the Sturm sequence. > \endverbatim > > \param[in] ISPLIT > \verbatim > ISPLIT is INTEGER array, dimension (N) > The splitting points, at which T breaks up into blocks. > The first block consists of rows/columns 1 to > ISPLIT( 1 ), the second of rows/columns ISPLIT( 1 )+1 > through ISPLIT( 2 ), etc. > \endverbatim > > \param[in] M > \verbatim > M is INTEGER > The total number of input eigenvalues. 0 <= M <= N. > \endverbatim > > \param[in] DOL > \verbatim > DOL is INTEGER > \endverbatim > > \param[in] DOU > \verbatim > DOU is INTEGER > If the user wants to compute only selected eigenvectors from all > the eigenvalues supplied, he can specify an index range DOL:DOU. > Or else the setting DOL=1, DOU=M should be applied. > Note that DOL and DOU refer to the order in which the eigenvalues > are stored in W. > If the user wants to compute only selected eigenpairs, then > the columns DOL-1 to DOU+1 of the eigenvector space Z contain the > computed eigenvectors. All other columns of Z are set to zero. > \endverbatim > > \param[in] MINRGP > \verbatim > MINRGP is DOUBLE PRECISION > \endverbatim > > \param[in] RTOL1 > \verbatim > RTOL1 is DOUBLE PRECISION > \endverbatim > > \param[in] RTOL2 > \verbatim > RTOL2 is DOUBLE PRECISION > Parameters for bisection. > An interval [LEFT,RIGHT] has converged if > RIGHT-LEFT.LT.MAX( RTOL1*GAP, RTOL2*MAX(|LEFT|,|RIGHT|) ) > \endverbatim > > \param[in,out] W > \verbatim > W is DOUBLE PRECISION array, dimension (N) > The first M elements of W contain the APPROXIMATE eigenvalues for > which eigenvectors are to be computed. The eigenvalues > should be grouped by split-off block and ordered from > smallest to largest within the block ( The output array > W from DLARRE is expected here ). Furthermore, they are with > respect to the shift of the corresponding root representation > for their block. On exit, W holds the eigenvalues of the > UNshifted matrix. > \endverbatim > > \param[in,out] WERR > \verbatim > WERR is DOUBLE PRECISION array, dimension (N) > The first M elements contain the semiwidth of the uncertainty > interval of the corresponding eigenvalue in W > \endverbatim > > \param[in,out] WGAP > \verbatim > WGAP is DOUBLE PRECISION array, dimension (N) > The separation from the right neighbor eigenvalue in W. > \endverbatim > > \param[in] IBLOCK > \verbatim > IBLOCK is INTEGER array, dimension (N) > The indices of the blocks (submatrices) associated with the > corresponding eigenvalues in W; IBLOCK(i)=1 if eigenvalue > W(i) belongs to the first block from the top, =2 if W(i) > belongs to the second block, etc. > \endverbatim > > \param[in] INDEXW > \verbatim > INDEXW is INTEGER array, dimension (N) > The indices of the eigenvalues within each block (submatrix); > for example, INDEXW(i)= 10 and IBLOCK(i)=2 imply that the > i-th eigenvalue W(i) is the 10-th eigenvalue in the second block. > \endverbatim > > \param[in] GERS > \verbatim > GERS is DOUBLE PRECISION array, dimension (2*N) > The N Gerschgorin intervals (the i-th Gerschgorin interval > is (GERS(2*i-1), GERS(2*i)). The Gerschgorin intervals should > be computed from the original UNshifted matrix. > \endverbatim > > \param[out] Z > \verbatim > Z is DOUBLE PRECISION array, dimension (LDZ, max(1,M) ) > If INFO = 0, the first M columns of Z contain the > orthonormal eigenvectors of the matrix T > corresponding to the input eigenvalues, with the i-th > column of Z holding the eigenvector associated with W(i). > Note: the user must ensure that at least max(1,M) columns are > supplied in the array Z. > \endverbatim > > \param[in] LDZ > \verbatim > LDZ is INTEGER > The leading dimension of the array Z. LDZ >= 1, and if > JOBZ = 'V', LDZ >= max(1,N). > \endverbatim > > \param[out] ISUPPZ > \verbatim > ISUPPZ is INTEGER array, dimension ( 2*max(1,M) ) > The support of the eigenvectors in Z, i.e., the indices > indicating the nonzero elements in Z. The I-th eigenvector > is nonzero only in elements ISUPPZ( 2*I-1 ) through > ISUPPZ( 2*I ). > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (12*N) > \endverbatim > > \param[out] IWORK > \verbatim > IWORK is INTEGER array, dimension (7*N) > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > > > 0: A problem occured in DLARRV. > < 0: One of the called subroutines signaled an internal problem. > Needs inspection of the corresponding parameter IINFO > for further information. > > =-1: Problem in DLARRB when refining a child's eigenvalues. > =-2: Problem in DLARRF when computing the RRR of a child. > When a child is inside a tight cluster, it can be difficult > to find an RRR. A partial remedy from the user's point of > view is to make the parameter MINRGP smaller and recompile. > However, as the orthogonality of the computed vectors is > proportional to 1/MINRGP, the user should be aware that > he might be trading in precision when he decreases MINRGP. > =-3: Problem in DLARRB when refining a single eigenvalue > after the Rayleigh correction was rejected. > = 5: The Rayleigh Quotient Iteration failed to converge to > full accuracy in MAXITR steps. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleOTHERauxiliary > \par Contributors: ================== > > Beresford Parlett, University of California, Berkeley, USA \n > Jim Demmel, University of California, Berkeley, USA \n > Inderjit Dhillon, University of Texas, Austin, USA \n > Osni Marques, LBNL/NERSC, USA \n > Christof Voemel, University of California, Berkeley, USA ===================================================================== Subroutine */ int igraphdlarrv_(integer *n, doublereal *vl, doublereal *vu, doublereal *d__, doublereal *l, doublereal *pivmin, integer *isplit, integer *m, integer *dol, integer *dou, doublereal *minrgp, doublereal *rtol1, doublereal *rtol2, doublereal *w, doublereal *werr, doublereal *wgap, integer *iblock, integer *indexw, doublereal *gers, doublereal *z__, integer *ldz, integer *isuppz, doublereal *work, integer *iwork, integer *info) { /* System generated locals */ integer z_dim1, z_offset, i__1, i__2, i__3, i__4, i__5; doublereal d__1, d__2; logical L__1; /* Builtin functions */ double log(doublereal); /* Local variables */ integer minwsize, i__, j, k, p, q, miniwsize, ii; doublereal gl; integer im, in; doublereal gu, gap, eps, tau, tol, tmp; integer zto; doublereal ztz; integer iend, jblk; doublereal lgap; integer done; doublereal rgap, left; integer wend, iter; doublereal bstw; integer itmp1; extern /* Subroutine */ int igraphdscal_(integer *, doublereal *, doublereal *, integer *); integer indld; doublereal fudge; integer idone; doublereal sigma; integer iinfo, iindr; doublereal resid; logical eskip; doublereal right; extern /* Subroutine */ int igraphdcopy_(integer *, doublereal *, integer *, doublereal *, integer *); integer nclus, zfrom; doublereal rqtol; integer iindc1, iindc2; extern /* Subroutine */ int igraphdlar1v_(integer *, integer *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, logical *, integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, doublereal *, doublereal *, doublereal *); logical stp2ii; doublereal lambda; extern doublereal igraphdlamch_(char *); integer ibegin, indeig; logical needbs; integer indlld; doublereal sgndef, mingma; extern /* Subroutine */ int igraphdlarrb_(integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, integer *, doublereal *, doublereal *, integer *, integer *); integer oldien, oldncl, wbegin; doublereal spdiam; integer negcnt; extern /* Subroutine */ int igraphdlarrf_(integer *, doublereal *, doublereal *, doublereal *, integer *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, integer *); integer oldcls; doublereal savgap; integer ndepth; doublereal ssigma; extern /* Subroutine */ int igraphdlaset_(char *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *); logical usedbs; integer iindwk, offset; doublereal gaptol; integer newcls, oldfst, indwrk, windex, oldlst; logical usedrq; integer newfst, newftt, parity, windmn, windpl, isupmn, newlst, zusedl; doublereal bstres; integer newsiz, zusedu, zusedw; doublereal nrminv, rqcorr; logical tryrqc; integer isupmx; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== The first N entries of WORK are reserved for the eigenvalues Parameter adjustments */ --d__; --l; --isplit; --w; --werr; --wgap; --iblock; --indexw; --gers; z_dim1 = *ldz; z_offset = 1 + z_dim1; z__ -= z_offset; --isuppz; --work; --iwork; /* Function Body */ indld = *n + 1; indlld = (*n << 1) + 1; indwrk = *n * 3 + 1; minwsize = *n * 12; i__1 = minwsize; for (i__ = 1; i__ <= i__1; ++i__) { work[i__] = 0.; /* L5: */ } /* IWORK(IINDR+1:IINDR+N) hold the twist indices R for the factorization used to compute the FP vector */ iindr = 0; /* IWORK(IINDC1+1:IINC2+N) are used to store the clusters of the current layer and the one above. */ iindc1 = *n; iindc2 = *n << 1; iindwk = *n * 3 + 1; miniwsize = *n * 7; i__1 = miniwsize; for (i__ = 1; i__ <= i__1; ++i__) { iwork[i__] = 0; /* L10: */ } zusedl = 1; if (*dol > 1) { /* Set lower bound for use of Z */ zusedl = *dol - 1; } zusedu = *m; if (*dou < *m) { /* Set lower bound for use of Z */ zusedu = *dou + 1; } /* The width of the part of Z that is used */ zusedw = zusedu - zusedl + 1; igraphdlaset_("Full", n, &zusedw, &c_b5, &c_b5, &z__[zusedl * z_dim1 + 1], ldz); eps = igraphdlamch_("Precision"); rqtol = eps * 2.; /* Set expert flags for standard code. */ tryrqc = TRUE_; if (*dol == 1 && *dou == *m) { } else { /* Only selected eigenpairs are computed. Since the other evalues are not refined by RQ iteration, bisection has to compute to full accuracy. */ *rtol1 = eps * 4.; *rtol2 = eps * 4.; } /* The entries WBEGIN:WEND in W, WERR, WGAP correspond to the desired eigenvalues. The support of the nonzero eigenvector entries is contained in the interval IBEGIN:IEND. Remark that if k eigenpairs are desired, then the eigenvectors are stored in k contiguous columns of Z. DONE is the number of eigenvectors already computed */ done = 0; ibegin = 1; wbegin = 1; i__1 = iblock[*m]; for (jblk = 1; jblk <= i__1; ++jblk) { iend = isplit[jblk]; sigma = l[iend]; /* Find the eigenvectors of the submatrix indexed IBEGIN through IEND. */ wend = wbegin - 1; L15: if (wend < *m) { if (iblock[wend + 1] == jblk) { ++wend; goto L15; } } if (wend < wbegin) { ibegin = iend + 1; goto L170; } else if (wend < *dol || wbegin > *dou) { ibegin = iend + 1; wbegin = wend + 1; goto L170; } /* Find local spectral diameter of the block */ gl = gers[(ibegin << 1) - 1]; gu = gers[ibegin * 2]; i__2 = iend; for (i__ = ibegin + 1; i__ <= i__2; ++i__) { /* Computing MIN */ d__1 = gers[(i__ << 1) - 1]; gl = min(d__1,gl); /* Computing MAX */ d__1 = gers[i__ * 2]; gu = max(d__1,gu); /* L20: */ } spdiam = gu - gl; /* OLDIEN is the last index of the previous block */ oldien = ibegin - 1; /* Calculate the size of the current block */ in = iend - ibegin + 1; /* The number of eigenvalues in the current block */ im = wend - wbegin + 1; /* This is for a 1x1 block */ if (ibegin == iend) { ++done; z__[ibegin + wbegin * z_dim1] = 1.; isuppz[(wbegin << 1) - 1] = ibegin; isuppz[wbegin * 2] = ibegin; w[wbegin] += sigma; work[wbegin] = w[wbegin]; ibegin = iend + 1; ++wbegin; goto L170; } /* The desired (shifted) eigenvalues are stored in W(WBEGIN:WEND) Note that these can be approximations, in this case, the corresp. entries of WERR give the size of the uncertainty interval. The eigenvalue approximations will be refined when necessary as high relative accuracy is required for the computation of the corresponding eigenvectors. */ igraphdcopy_(&im, &w[wbegin], &c__1, &work[wbegin], &c__1); /* We store in W the eigenvalue approximations w.r.t. the original matrix T. */ i__2 = im; for (i__ = 1; i__ <= i__2; ++i__) { w[wbegin + i__ - 1] += sigma; /* L30: */ } /* NDEPTH is the current depth of the representation tree */ ndepth = 0; /* PARITY is either 1 or 0 */ parity = 1; /* NCLUS is the number of clusters for the next level of the representation tree, we start with NCLUS = 1 for the root */ nclus = 1; iwork[iindc1 + 1] = 1; iwork[iindc1 + 2] = im; /* IDONE is the number of eigenvectors already computed in the current block */ idone = 0; /* loop while( IDONE.LT.IM ) generate the representation tree for the current block and compute the eigenvectors */ L40: if (idone < im) { /* This is a crude protection against infinitely deep trees */ if (ndepth > *m) { *info = -2; return 0; } /* breadth first processing of the current level of the representation tree: OLDNCL = number of clusters on current level */ oldncl = nclus; /* reset NCLUS to count the number of child clusters */ nclus = 0; parity = 1 - parity; if (parity == 0) { oldcls = iindc1; newcls = iindc2; } else { oldcls = iindc2; newcls = iindc1; } /* Process the clusters on the current level */ i__2 = oldncl; for (i__ = 1; i__ <= i__2; ++i__) { j = oldcls + (i__ << 1); /* OLDFST, OLDLST = first, last index of current cluster. cluster indices start with 1 and are relative to WBEGIN when accessing W, WGAP, WERR, Z */ oldfst = iwork[j - 1]; oldlst = iwork[j]; if (ndepth > 0) { /* Retrieve relatively robust representation (RRR) of cluster that has been computed at the previous level The RRR is stored in Z and overwritten once the eigenvectors have been computed or when the cluster is refined */ if (*dol == 1 && *dou == *m) { /* Get representation from location of the leftmost evalue of the cluster */ j = wbegin + oldfst - 1; } else { if (wbegin + oldfst - 1 < *dol) { /* Get representation from the left end of Z array */ j = *dol - 1; } else if (wbegin + oldfst - 1 > *dou) { /* Get representation from the right end of Z array */ j = *dou; } else { j = wbegin + oldfst - 1; } } igraphdcopy_(&in, &z__[ibegin + j * z_dim1], &c__1, &d__[ibegin] , &c__1); i__3 = in - 1; igraphdcopy_(&i__3, &z__[ibegin + (j + 1) * z_dim1], &c__1, &l[ ibegin], &c__1); sigma = z__[iend + (j + 1) * z_dim1]; /* Set the corresponding entries in Z to zero */ igraphdlaset_("Full", &in, &c__2, &c_b5, &c_b5, &z__[ibegin + j * z_dim1], ldz); } /* Compute DL and DLL of current RRR */ i__3 = iend - 1; for (j = ibegin; j <= i__3; ++j) { tmp = d__[j] * l[j]; work[indld - 1 + j] = tmp; work[indlld - 1 + j] = tmp * l[j]; /* L50: */ } if (ndepth > 0) { /* P and Q are index of the first and last eigenvalue to compute within the current block */ p = indexw[wbegin - 1 + oldfst]; q = indexw[wbegin - 1 + oldlst]; /* Offset for the arrays WORK, WGAP and WERR, i.e., the P-OFFSET through the Q-OFFSET elements of these arrays are to be used. OFFSET = P-OLDFST */ offset = indexw[wbegin] - 1; /* perform limited bisection (if necessary) to get approximate eigenvalues to the precision needed. */ igraphdlarrb_(&in, &d__[ibegin], &work[indlld + ibegin - 1], &p, &q, rtol1, rtol2, &offset, &work[wbegin], &wgap[ wbegin], &werr[wbegin], &work[indwrk], &iwork[ iindwk], pivmin, &spdiam, &in, &iinfo); if (iinfo != 0) { *info = -1; return 0; } /* We also recompute the extremal gaps. W holds all eigenvalues of the unshifted matrix and must be used for computation of WGAP, the entries of WORK might stem from RRRs with different shifts. The gaps from WBEGIN-1+OLDFST to WBEGIN-1+OLDLST are correctly computed in DLARRB. However, we only allow the gaps to become greater since this is what should happen when we decrease WERR */ if (oldfst > 1) { /* Computing MAX */ d__1 = wgap[wbegin + oldfst - 2], d__2 = w[wbegin + oldfst - 1] - werr[wbegin + oldfst - 1] - w[ wbegin + oldfst - 2] - werr[wbegin + oldfst - 2]; wgap[wbegin + oldfst - 2] = max(d__1,d__2); } if (wbegin + oldlst - 1 < wend) { /* Computing MAX */ d__1 = wgap[wbegin + oldlst - 1], d__2 = w[wbegin + oldlst] - werr[wbegin + oldlst] - w[wbegin + oldlst - 1] - werr[wbegin + oldlst - 1]; wgap[wbegin + oldlst - 1] = max(d__1,d__2); } /* Each time the eigenvalues in WORK get refined, we store the newly found approximation with all shifts applied in W */ i__3 = oldlst; for (j = oldfst; j <= i__3; ++j) { w[wbegin + j - 1] = work[wbegin + j - 1] + sigma; /* L53: */ } } /* Process the current node. */ newfst = oldfst; i__3 = oldlst; for (j = oldfst; j <= i__3; ++j) { if (j == oldlst) { /* we are at the right end of the cluster, this is also the boundary of the child cluster */ newlst = j; } else if (wgap[wbegin + j - 1] >= *minrgp * (d__1 = work[ wbegin + j - 1], abs(d__1))) { /* the right relative gap is big enough, the child cluster (NEWFST,..,NEWLST) is well separated from the following */ newlst = j; } else { /* inside a child cluster, the relative gap is not big enough. */ goto L140; } /* Compute size of child cluster found */ newsiz = newlst - newfst + 1; /* NEWFTT is the place in Z where the new RRR or the computed eigenvector is to be stored */ if (*dol == 1 && *dou == *m) { /* Store representation at location of the leftmost evalue of the cluster */ newftt = wbegin + newfst - 1; } else { if (wbegin + newfst - 1 < *dol) { /* Store representation at the left end of Z array */ newftt = *dol - 1; } else if (wbegin + newfst - 1 > *dou) { /* Store representation at the right end of Z array */ newftt = *dou; } else { newftt = wbegin + newfst - 1; } } if (newsiz > 1) { /* Current child is not a singleton but a cluster. Compute and store new representation of child. Compute left and right cluster gap. LGAP and RGAP are not computed from WORK because the eigenvalue approximations may stem from RRRs different shifts. However, W hold all eigenvalues of the unshifted matrix. Still, the entries in WGAP have to be computed from WORK since the entries in W might be of the same order so that gaps are not exhibited correctly for very close eigenvalues. */ if (newfst == 1) { /* Computing MAX */ d__1 = 0., d__2 = w[wbegin] - werr[wbegin] - *vl; lgap = max(d__1,d__2); } else { lgap = wgap[wbegin + newfst - 2]; } rgap = wgap[wbegin + newlst - 1]; /* Compute left- and rightmost eigenvalue of child to high precision in order to shift as close as possible and obtain as large relative gaps as possible */ for (k = 1; k <= 2; ++k) { if (k == 1) { p = indexw[wbegin - 1 + newfst]; } else { p = indexw[wbegin - 1 + newlst]; } offset = indexw[wbegin] - 1; igraphdlarrb_(&in, &d__[ibegin], &work[indlld + ibegin - 1], &p, &p, &rqtol, &rqtol, &offset, & work[wbegin], &wgap[wbegin], &werr[wbegin] , &work[indwrk], &iwork[iindwk], pivmin, & spdiam, &in, &iinfo); /* L55: */ } if (wbegin + newlst - 1 < *dol || wbegin + newfst - 1 > *dou) { /* if the cluster contains no desired eigenvalues skip the computation of that branch of the rep. tree We could skip before the refinement of the extremal eigenvalues of the child, but then the representation tree could be different from the one when nothing is skipped. For this reason we skip at this place. */ idone = idone + newlst - newfst + 1; goto L139; } /* Compute RRR of child cluster. Note that the new RRR is stored in Z DLARRF needs LWORK = 2*N */ igraphdlarrf_(&in, &d__[ibegin], &l[ibegin], &work[indld + ibegin - 1], &newfst, &newlst, &work[wbegin], &wgap[wbegin], &werr[wbegin], &spdiam, &lgap, &rgap, pivmin, &tau, &z__[ibegin + newftt * z_dim1], &z__[ibegin + (newftt + 1) * z_dim1], &work[indwrk], &iinfo); if (iinfo == 0) { /* a new RRR for the cluster was found by DLARRF update shift and store it */ ssigma = sigma + tau; z__[iend + (newftt + 1) * z_dim1] = ssigma; /* WORK() are the midpoints and WERR() the semi-width Note that the entries in W are unchanged. */ i__4 = newlst; for (k = newfst; k <= i__4; ++k) { fudge = eps * 3. * (d__1 = work[wbegin + k - 1], abs(d__1)); work[wbegin + k - 1] -= tau; fudge += eps * 4. * (d__1 = work[wbegin + k - 1], abs(d__1)); /* Fudge errors */ werr[wbegin + k - 1] += fudge; /* Gaps are not fudged. Provided that WERR is small when eigenvalues are close, a zero gap indicates that a new representation is needed for resolving the cluster. A fudge could lead to a wrong decision of judging eigenvalues 'separated' which in reality are not. This could have a negative impact on the orthogonality of the computed eigenvectors. L116: */ } ++nclus; k = newcls + (nclus << 1); iwork[k - 1] = newfst; iwork[k] = newlst; } else { *info = -2; return 0; } } else { /* Compute eigenvector of singleton */ iter = 0; tol = log((doublereal) in) * 4. * eps; k = newfst; windex = wbegin + k - 1; /* Computing MAX */ i__4 = windex - 1; windmn = max(i__4,1); /* Computing MIN */ i__4 = windex + 1; windpl = min(i__4,*m); lambda = work[windex]; ++done; /* Check if eigenvector computation is to be skipped */ if (windex < *dol || windex > *dou) { eskip = TRUE_; goto L125; } else { eskip = FALSE_; } left = work[windex] - werr[windex]; right = work[windex] + werr[windex]; indeig = indexw[windex]; /* Note that since we compute the eigenpairs for a child, all eigenvalue approximations are w.r.t the same shift. In this case, the entries in WORK should be used for computing the gaps since they exhibit even very small differences in the eigenvalues, as opposed to the entries in W which might "look" the same. */ if (k == 1) { /* In the case RANGE='I' and with not much initial accuracy in LAMBDA and VL, the formula LGAP = MAX( ZERO, (SIGMA - VL) + LAMBDA ) can lead to an overestimation of the left gap and thus to inadequately early RQI 'convergence'. Prevent this by forcing a small left gap. Computing MAX */ d__1 = abs(left), d__2 = abs(right); lgap = eps * max(d__1,d__2); } else { lgap = wgap[windmn]; } if (k == im) { /* In the case RANGE='I' and with not much initial accuracy in LAMBDA and VU, the formula can lead to an overestimation of the right gap and thus to inadequately early RQI 'convergence'. Prevent this by forcing a small right gap. Computing MAX */ d__1 = abs(left), d__2 = abs(right); rgap = eps * max(d__1,d__2); } else { rgap = wgap[windex]; } gap = min(lgap,rgap); if (k == 1 || k == im) { /* The eigenvector support can become wrong because significant entries could be cut off due to a large GAPTOL parameter in LAR1V. Prevent this. */ gaptol = 0.; } else { gaptol = gap * eps; } isupmn = in; isupmx = 1; /* Update WGAP so that it holds the minimum gap to the left or the right. This is crucial in the case where bisection is used to ensure that the eigenvalue is refined up to the required precision. The correct value is restored afterwards. */ savgap = wgap[windex]; wgap[windex] = gap; /* We want to use the Rayleigh Quotient Correction as often as possible since it converges quadratically when we are close enough to the desired eigenvalue. However, the Rayleigh Quotient can have the wrong sign and lead us away from the desired eigenvalue. In this case, the best we can do is to use bisection. */ usedbs = FALSE_; usedrq = FALSE_; /* Bisection is initially turned off unless it is forced */ needbs = ! tryrqc; L120: /* Check if bisection should be used to refine eigenvalue */ if (needbs) { /* Take the bisection as new iterate */ usedbs = TRUE_; itmp1 = iwork[iindr + windex]; offset = indexw[wbegin] - 1; d__1 = eps * 2.; igraphdlarrb_(&in, &d__[ibegin], &work[indlld + ibegin - 1], &indeig, &indeig, &c_b5, &d__1, & offset, &work[wbegin], &wgap[wbegin], & werr[wbegin], &work[indwrk], &iwork[ iindwk], pivmin, &spdiam, &itmp1, &iinfo); if (iinfo != 0) { *info = -3; return 0; } lambda = work[windex]; /* Reset twist index from inaccurate LAMBDA to force computation of true MINGMA */ iwork[iindr + windex] = 0; } /* Given LAMBDA, compute the eigenvector. */ L__1 = ! usedbs; igraphdlar1v_(&in, &c__1, &in, &lambda, &d__[ibegin], &l[ ibegin], &work[indld + ibegin - 1], &work[ indlld + ibegin - 1], pivmin, &gaptol, &z__[ ibegin + windex * z_dim1], &L__1, &negcnt, & ztz, &mingma, &iwork[iindr + windex], &isuppz[ (windex << 1) - 1], &nrminv, &resid, &rqcorr, &work[indwrk]); if (iter == 0) { bstres = resid; bstw = lambda; } else if (resid < bstres) { bstres = resid; bstw = lambda; } /* Computing MIN */ i__4 = isupmn, i__5 = isuppz[(windex << 1) - 1]; isupmn = min(i__4,i__5); /* Computing MAX */ i__4 = isupmx, i__5 = isuppz[windex * 2]; isupmx = max(i__4,i__5); ++iter; /* sin alpha <= |resid|/gap Note that both the residual and the gap are proportional to the matrix, so ||T|| doesn't play a role in the quotient Convergence test for Rayleigh-Quotient iteration (omitted when Bisection has been used) */ if (resid > tol * gap && abs(rqcorr) > rqtol * abs( lambda) && ! usedbs) { /* We need to check that the RQCORR update doesn't move the eigenvalue away from the desired one and towards a neighbor. -> protection with bisection */ if (indeig <= negcnt) { /* The wanted eigenvalue lies to the left */ sgndef = -1.; } else { /* The wanted eigenvalue lies to the right */ sgndef = 1.; } /* We only use the RQCORR if it improves the the iterate reasonably. */ if (rqcorr * sgndef >= 0. && lambda + rqcorr <= right && lambda + rqcorr >= left) { usedrq = TRUE_; /* Store new midpoint of bisection interval in WORK */ if (sgndef == 1.) { /* The current LAMBDA is on the left of the true eigenvalue */ left = lambda; /* We prefer to assume that the error estimate is correct. We could make the interval not as a bracket but to be modified if the RQCORR chooses to. In this case, the RIGHT side should be modified as follows: RIGHT = MAX(RIGHT, LAMBDA + RQCORR) */ } else { /* The current LAMBDA is on the right of the true eigenvalue */ right = lambda; /* See comment about assuming the error estimate is correct above. LEFT = MIN(LEFT, LAMBDA + RQCORR) */ } work[windex] = (right + left) * .5; /* Take RQCORR since it has the correct sign and improves the iterate reasonably */ lambda += rqcorr; /* Update width of error interval */ werr[windex] = (right - left) * .5; } else { needbs = TRUE_; } if (right - left < rqtol * abs(lambda)) { /* The eigenvalue is computed to bisection accuracy compute eigenvector and stop */ usedbs = TRUE_; goto L120; } else if (iter < 10) { goto L120; } else if (iter == 10) { needbs = TRUE_; goto L120; } else { *info = 5; return 0; } } else { stp2ii = FALSE_; if (usedrq && usedbs && bstres <= resid) { lambda = bstw; stp2ii = TRUE_; } if (stp2ii) { /* improve error angle by second step */ L__1 = ! usedbs; igraphdlar1v_(&in, &c__1, &in, &lambda, &d__[ibegin] , &l[ibegin], &work[indld + ibegin - 1], &work[indlld + ibegin - 1], pivmin, &gaptol, &z__[ibegin + windex * z_dim1], &L__1, &negcnt, &ztz, & mingma, &iwork[iindr + windex], & isuppz[(windex << 1) - 1], &nrminv, & resid, &rqcorr, &work[indwrk]); } work[windex] = lambda; } /* Compute FP-vector support w.r.t. whole matrix */ isuppz[(windex << 1) - 1] += oldien; isuppz[windex * 2] += oldien; zfrom = isuppz[(windex << 1) - 1]; zto = isuppz[windex * 2]; isupmn += oldien; isupmx += oldien; /* Ensure vector is ok if support in the RQI has changed */ if (isupmn < zfrom) { i__4 = zfrom - 1; for (ii = isupmn; ii <= i__4; ++ii) { z__[ii + windex * z_dim1] = 0.; /* L122: */ } } if (isupmx > zto) { i__4 = isupmx; for (ii = zto + 1; ii <= i__4; ++ii) { z__[ii + windex * z_dim1] = 0.; /* L123: */ } } i__4 = zto - zfrom + 1; igraphdscal_(&i__4, &nrminv, &z__[zfrom + windex * z_dim1], &c__1); L125: /* Update W */ w[windex] = lambda + sigma; /* Recompute the gaps on the left and right But only allow them to become larger and not smaller (which can only happen through "bad" cancellation and doesn't reflect the theory where the initial gaps are underestimated due to WERR being too crude.) */ if (! eskip) { if (k > 1) { /* Computing MAX */ d__1 = wgap[windmn], d__2 = w[windex] - werr[ windex] - w[windmn] - werr[windmn]; wgap[windmn] = max(d__1,d__2); } if (windex < wend) { /* Computing MAX */ d__1 = savgap, d__2 = w[windpl] - werr[windpl] - w[windex] - werr[windex]; wgap[windex] = max(d__1,d__2); } } ++idone; } /* here ends the code for the current child */ L139: /* Proceed to any remaining child nodes */ newfst = j + 1; L140: ; } /* L150: */ } ++ndepth; goto L40; } ibegin = iend + 1; wbegin = wend + 1; L170: ; } return 0; /* End of DLARRV */ } /* igraphdlarrv_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dormtr.c0000644000076500000240000002551213524616145024320 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static integer c_n1 = -1; static integer c__2 = 2; /* > \brief \b DORMTR =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DORMTR + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DORMTR( SIDE, UPLO, TRANS, M, N, A, LDA, TAU, C, LDC, WORK, LWORK, INFO ) CHARACTER SIDE, TRANS, UPLO INTEGER INFO, LDA, LDC, LWORK, M, N DOUBLE PRECISION A( LDA, * ), C( LDC, * ), TAU( * ), WORK( * ) > \par Purpose: ============= > > \verbatim > > DORMTR overwrites the general real M-by-N matrix C with > > SIDE = 'L' SIDE = 'R' > TRANS = 'N': Q * C C * Q > TRANS = 'T': Q**T * C C * Q**T > > where Q is a real orthogonal matrix of order nq, with nq = m if > SIDE = 'L' and nq = n if SIDE = 'R'. Q is defined as the product of > nq-1 elementary reflectors, as returned by DSYTRD: > > if UPLO = 'U', Q = H(nq-1) . . . H(2) H(1); > > if UPLO = 'L', Q = H(1) H(2) . . . H(nq-1). > \endverbatim Arguments: ========== > \param[in] SIDE > \verbatim > SIDE is CHARACTER*1 > = 'L': apply Q or Q**T from the Left; > = 'R': apply Q or Q**T from the Right. > \endverbatim > > \param[in] UPLO > \verbatim > UPLO is CHARACTER*1 > = 'U': Upper triangle of A contains elementary reflectors > from DSYTRD; > = 'L': Lower triangle of A contains elementary reflectors > from DSYTRD. > \endverbatim > > \param[in] TRANS > \verbatim > TRANS is CHARACTER*1 > = 'N': No transpose, apply Q; > = 'T': Transpose, apply Q**T. > \endverbatim > > \param[in] M > \verbatim > M is INTEGER > The number of rows of the matrix C. M >= 0. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The number of columns of the matrix C. N >= 0. > \endverbatim > > \param[in] A > \verbatim > A is DOUBLE PRECISION array, dimension > (LDA,M) if SIDE = 'L' > (LDA,N) if SIDE = 'R' > The vectors which define the elementary reflectors, as > returned by DSYTRD. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. > LDA >= max(1,M) if SIDE = 'L'; LDA >= max(1,N) if SIDE = 'R'. > \endverbatim > > \param[in] TAU > \verbatim > TAU is DOUBLE PRECISION array, dimension > (M-1) if SIDE = 'L' > (N-1) if SIDE = 'R' > TAU(i) must contain the scalar factor of the elementary > reflector H(i), as returned by DSYTRD. > \endverbatim > > \param[in,out] C > \verbatim > C is DOUBLE PRECISION array, dimension (LDC,N) > On entry, the M-by-N matrix C. > On exit, C is overwritten by Q*C or Q**T*C or C*Q**T or C*Q. > \endverbatim > > \param[in] LDC > \verbatim > LDC is INTEGER > The leading dimension of the array C. LDC >= max(1,M). > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (MAX(1,LWORK)) > On exit, if INFO = 0, WORK(1) returns the optimal LWORK. > \endverbatim > > \param[in] LWORK > \verbatim > LWORK is INTEGER > The dimension of the array WORK. > If SIDE = 'L', LWORK >= max(1,N); > if SIDE = 'R', LWORK >= max(1,M). > For optimum performance LWORK >= N*NB if SIDE = 'L', and > LWORK >= M*NB if SIDE = 'R', where NB is the optimal > blocksize. > > If LWORK = -1, then a workspace query is assumed; the routine > only calculates the optimal size of the WORK array, returns > this value as the first entry of the WORK array, and no error > message related to LWORK is issued by XERBLA. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2011 > \ingroup doubleOTHERcomputational ===================================================================== Subroutine */ int igraphdormtr_(char *side, char *uplo, char *trans, integer *m, integer *n, doublereal *a, integer *lda, doublereal *tau, doublereal * c__, integer *ldc, doublereal *work, integer *lwork, integer *info) { /* System generated locals */ address a__1[2]; integer a_dim1, a_offset, c_dim1, c_offset, i__1[2], i__2, i__3; char ch__1[2]; /* Builtin functions Subroutine */ int s_cat(char *, char **, integer *, integer *, ftnlen); /* Local variables */ integer i1, i2, nb, mi, ni, nq, nw; logical left; extern logical igraphlsame_(char *, char *); integer iinfo; logical upper; extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); extern integer igraphilaenv_(integer *, char *, char *, integer *, integer *, integer *, integer *, ftnlen, ftnlen); extern /* Subroutine */ int igraphdormql_(char *, char *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, integer *), igraphdormqr_(char *, char *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, integer *); integer lwkopt; logical lquery; /* -- LAPACK computational routine (version 3.4.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2011 ===================================================================== Test the input arguments Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --tau; c_dim1 = *ldc; c_offset = 1 + c_dim1; c__ -= c_offset; --work; /* Function Body */ *info = 0; left = igraphlsame_(side, "L"); upper = igraphlsame_(uplo, "U"); lquery = *lwork == -1; /* NQ is the order of Q and NW is the minimum dimension of WORK */ if (left) { nq = *m; nw = *n; } else { nq = *n; nw = *m; } if (! left && ! igraphlsame_(side, "R")) { *info = -1; } else if (! upper && ! igraphlsame_(uplo, "L")) { *info = -2; } else if (! igraphlsame_(trans, "N") && ! igraphlsame_(trans, "T")) { *info = -3; } else if (*m < 0) { *info = -4; } else if (*n < 0) { *info = -5; } else if (*lda < max(1,nq)) { *info = -7; } else if (*ldc < max(1,*m)) { *info = -10; } else if (*lwork < max(1,nw) && ! lquery) { *info = -12; } if (*info == 0) { if (upper) { if (left) { /* Writing concatenation */ i__1[0] = 1, a__1[0] = side; i__1[1] = 1, a__1[1] = trans; s_cat(ch__1, a__1, i__1, &c__2, (ftnlen)2); i__2 = *m - 1; i__3 = *m - 1; nb = igraphilaenv_(&c__1, "DORMQL", ch__1, &i__2, n, &i__3, &c_n1, ( ftnlen)6, (ftnlen)2); } else { /* Writing concatenation */ i__1[0] = 1, a__1[0] = side; i__1[1] = 1, a__1[1] = trans; s_cat(ch__1, a__1, i__1, &c__2, (ftnlen)2); i__2 = *n - 1; i__3 = *n - 1; nb = igraphilaenv_(&c__1, "DORMQL", ch__1, m, &i__2, &i__3, &c_n1, ( ftnlen)6, (ftnlen)2); } } else { if (left) { /* Writing concatenation */ i__1[0] = 1, a__1[0] = side; i__1[1] = 1, a__1[1] = trans; s_cat(ch__1, a__1, i__1, &c__2, (ftnlen)2); i__2 = *m - 1; i__3 = *m - 1; nb = igraphilaenv_(&c__1, "DORMQR", ch__1, &i__2, n, &i__3, &c_n1, ( ftnlen)6, (ftnlen)2); } else { /* Writing concatenation */ i__1[0] = 1, a__1[0] = side; i__1[1] = 1, a__1[1] = trans; s_cat(ch__1, a__1, i__1, &c__2, (ftnlen)2); i__2 = *n - 1; i__3 = *n - 1; nb = igraphilaenv_(&c__1, "DORMQR", ch__1, m, &i__2, &i__3, &c_n1, ( ftnlen)6, (ftnlen)2); } } lwkopt = max(1,nw) * nb; work[1] = (doublereal) lwkopt; } if (*info != 0) { i__2 = -(*info); igraphxerbla_("DORMTR", &i__2, (ftnlen)6); return 0; } else if (lquery) { return 0; } /* Quick return if possible */ if (*m == 0 || *n == 0 || nq == 1) { work[1] = 1.; return 0; } if (left) { mi = *m - 1; ni = *n; } else { mi = *m; ni = *n - 1; } if (upper) { /* Q was determined by a call to DSYTRD with UPLO = 'U' */ i__2 = nq - 1; igraphdormql_(side, trans, &mi, &ni, &i__2, &a[(a_dim1 << 1) + 1], lda, & tau[1], &c__[c_offset], ldc, &work[1], lwork, &iinfo); } else { /* Q was determined by a call to DSYTRD with UPLO = 'L' */ if (left) { i1 = 2; i2 = 1; } else { i1 = 1; i2 = 2; } i__2 = nq - 1; igraphdormqr_(side, trans, &mi, &ni, &i__2, &a[a_dim1 + 2], lda, &tau[1], & c__[i1 + i2 * c_dim1], ldc, &work[1], lwork, &iinfo); } work[1] = (doublereal) lwkopt; return 0; /* End of DORMTR */ } /* igraphdormtr_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlagts.c0000644000076500000240000002655713524616145024301 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLAGTS solves the system of equations (T-λI)x = y or (T-λI)Tx = y,where T is a general tridia gonal matrix and λ a scalar, using the LU factorization computed by slagtf. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLAGTS + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLAGTS( JOB, N, A, B, C, D, IN, Y, TOL, INFO ) INTEGER INFO, JOB, N DOUBLE PRECISION TOL INTEGER IN( * ) DOUBLE PRECISION A( * ), B( * ), C( * ), D( * ), Y( * ) > \par Purpose: ============= > > \verbatim > > DLAGTS may be used to solve one of the systems of equations > > (T - lambda*I)*x = y or (T - lambda*I)**T*x = y, > > where T is an n by n tridiagonal matrix, for x, following the > factorization of (T - lambda*I) as > > (T - lambda*I) = P*L*U , > > by routine DLAGTF. The choice of equation to be solved is > controlled by the argument JOB, and in each case there is an option > to perturb zero or very small diagonal elements of U, this option > being intended for use in applications such as inverse iteration. > \endverbatim Arguments: ========== > \param[in] JOB > \verbatim > JOB is INTEGER > Specifies the job to be performed by DLAGTS as follows: > = 1: The equations (T - lambda*I)x = y are to be solved, > but diagonal elements of U are not to be perturbed. > = -1: The equations (T - lambda*I)x = y are to be solved > and, if overflow would otherwise occur, the diagonal > elements of U are to be perturbed. See argument TOL > below. > = 2: The equations (T - lambda*I)**Tx = y are to be solved, > but diagonal elements of U are not to be perturbed. > = -2: The equations (T - lambda*I)**Tx = y are to be solved > and, if overflow would otherwise occur, the diagonal > elements of U are to be perturbed. See argument TOL > below. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix T. > \endverbatim > > \param[in] A > \verbatim > A is DOUBLE PRECISION array, dimension (N) > On entry, A must contain the diagonal elements of U as > returned from DLAGTF. > \endverbatim > > \param[in] B > \verbatim > B is DOUBLE PRECISION array, dimension (N-1) > On entry, B must contain the first super-diagonal elements of > U as returned from DLAGTF. > \endverbatim > > \param[in] C > \verbatim > C is DOUBLE PRECISION array, dimension (N-1) > On entry, C must contain the sub-diagonal elements of L as > returned from DLAGTF. > \endverbatim > > \param[in] D > \verbatim > D is DOUBLE PRECISION array, dimension (N-2) > On entry, D must contain the second super-diagonal elements > of U as returned from DLAGTF. > \endverbatim > > \param[in] IN > \verbatim > IN is INTEGER array, dimension (N) > On entry, IN must contain details of the matrix P as returned > from DLAGTF. > \endverbatim > > \param[in,out] Y > \verbatim > Y is DOUBLE PRECISION array, dimension (N) > On entry, the right hand side vector y. > On exit, Y is overwritten by the solution vector x. > \endverbatim > > \param[in,out] TOL > \verbatim > TOL is DOUBLE PRECISION > On entry, with JOB .lt. 0, TOL should be the minimum > perturbation to be made to very small diagonal elements of U. > TOL should normally be chosen as about eps*norm(U), where eps > is the relative machine precision, but if TOL is supplied as > non-positive, then it is reset to eps*max( abs( u(i,j) ) ). > If JOB .gt. 0 then TOL is not referenced. > > On exit, TOL is changed as described above, only if TOL is > non-positive on entry. Otherwise TOL is unchanged. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0 : successful exit > .lt. 0: if INFO = -i, the i-th argument had an illegal value > .gt. 0: overflow would occur when computing the INFO(th) > element of the solution vector x. This can only occur > when JOB is supplied as positive and either means > that a diagonal element of U is very small, or that > the elements of the right-hand side vector y are very > large. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERauxiliary ===================================================================== Subroutine */ int igraphdlagts_(integer *job, integer *n, doublereal *a, doublereal *b, doublereal *c__, doublereal *d__, integer *in, doublereal *y, doublereal *tol, integer *info) { /* System generated locals */ integer i__1; doublereal d__1, d__2, d__3, d__4, d__5; /* Builtin functions */ double d_sign(doublereal *, doublereal *); /* Local variables */ integer k; doublereal ak, eps, temp, pert, absak, sfmin; extern doublereal igraphdlamch_(char *); extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); doublereal bignum; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ --y; --in; --d__; --c__; --b; --a; /* Function Body */ *info = 0; if (abs(*job) > 2 || *job == 0) { *info = -1; } else if (*n < 0) { *info = -2; } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DLAGTS", &i__1, (ftnlen)6); return 0; } if (*n == 0) { return 0; } eps = igraphdlamch_("Epsilon"); sfmin = igraphdlamch_("Safe minimum"); bignum = 1. / sfmin; if (*job < 0) { if (*tol <= 0.) { *tol = abs(a[1]); if (*n > 1) { /* Computing MAX */ d__1 = *tol, d__2 = abs(a[2]), d__1 = max(d__1,d__2), d__2 = abs(b[1]); *tol = max(d__1,d__2); } i__1 = *n; for (k = 3; k <= i__1; ++k) { /* Computing MAX */ d__4 = *tol, d__5 = (d__1 = a[k], abs(d__1)), d__4 = max(d__4, d__5), d__5 = (d__2 = b[k - 1], abs(d__2)), d__4 = max(d__4,d__5), d__5 = (d__3 = d__[k - 2], abs(d__3)); *tol = max(d__4,d__5); /* L10: */ } *tol *= eps; if (*tol == 0.) { *tol = eps; } } } if (abs(*job) == 1) { i__1 = *n; for (k = 2; k <= i__1; ++k) { if (in[k - 1] == 0) { y[k] -= c__[k - 1] * y[k - 1]; } else { temp = y[k - 1]; y[k - 1] = y[k]; y[k] = temp - c__[k - 1] * y[k]; } /* L20: */ } if (*job == 1) { for (k = *n; k >= 1; --k) { if (k <= *n - 2) { temp = y[k] - b[k] * y[k + 1] - d__[k] * y[k + 2]; } else if (k == *n - 1) { temp = y[k] - b[k] * y[k + 1]; } else { temp = y[k]; } ak = a[k]; absak = abs(ak); if (absak < 1.) { if (absak < sfmin) { if (absak == 0. || abs(temp) * sfmin > absak) { *info = k; return 0; } else { temp *= bignum; ak *= bignum; } } else if (abs(temp) > absak * bignum) { *info = k; return 0; } } y[k] = temp / ak; /* L30: */ } } else { for (k = *n; k >= 1; --k) { if (k <= *n - 2) { temp = y[k] - b[k] * y[k + 1] - d__[k] * y[k + 2]; } else if (k == *n - 1) { temp = y[k] - b[k] * y[k + 1]; } else { temp = y[k]; } ak = a[k]; pert = d_sign(tol, &ak); L40: absak = abs(ak); if (absak < 1.) { if (absak < sfmin) { if (absak == 0. || abs(temp) * sfmin > absak) { ak += pert; pert *= 2; goto L40; } else { temp *= bignum; ak *= bignum; } } else if (abs(temp) > absak * bignum) { ak += pert; pert *= 2; goto L40; } } y[k] = temp / ak; /* L50: */ } } } else { /* Come to here if JOB = 2 or -2 */ if (*job == 2) { i__1 = *n; for (k = 1; k <= i__1; ++k) { if (k >= 3) { temp = y[k] - b[k - 1] * y[k - 1] - d__[k - 2] * y[k - 2]; } else if (k == 2) { temp = y[k] - b[k - 1] * y[k - 1]; } else { temp = y[k]; } ak = a[k]; absak = abs(ak); if (absak < 1.) { if (absak < sfmin) { if (absak == 0. || abs(temp) * sfmin > absak) { *info = k; return 0; } else { temp *= bignum; ak *= bignum; } } else if (abs(temp) > absak * bignum) { *info = k; return 0; } } y[k] = temp / ak; /* L60: */ } } else { i__1 = *n; for (k = 1; k <= i__1; ++k) { if (k >= 3) { temp = y[k] - b[k - 1] * y[k - 1] - d__[k - 2] * y[k - 2]; } else if (k == 2) { temp = y[k] - b[k - 1] * y[k - 1]; } else { temp = y[k]; } ak = a[k]; pert = d_sign(tol, &ak); L70: absak = abs(ak); if (absak < 1.) { if (absak < sfmin) { if (absak == 0. || abs(temp) * sfmin > absak) { ak += pert; pert *= 2; goto L70; } else { temp *= bignum; ak *= bignum; } } else if (abs(temp) > absak * bignum) { ak += pert; pert *= 2; goto L70; } } y[k] = temp / ak; /* L80: */ } } for (k = *n; k >= 2; --k) { if (in[k - 1] == 0) { y[k - 1] -= c__[k - 1] * y[k]; } else { temp = y[k - 1]; y[k - 1] = y[k]; y[k] = temp - c__[k - 1] * y[k]; } /* L90: */ } } /* End of DLAGTS */ return 0; } /* igraphdlagts_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlarft.c0000644000076500000240000003077713524616145024276 0ustar tamasstaff00000000000000/* dlarft.f -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static doublereal c_b8 = 1.; /* > \brief \b DLARFT forms the triangular factor T of a block reflector H = I - vtvH */ /* =========== DOCUMENTATION =========== */ /* Online html documentation available at */ /* http://www.netlib.org/lapack/explore-html/ */ /* > \htmlonly */ /* > Download DLARFT + dependencies */ /* > */ /* > [TGZ] */ /* > */ /* > [ZIP] */ /* > */ /* > [TXT] */ /* > \endhtmlonly */ /* Definition: */ /* =========== */ /* SUBROUTINE DLARFT( DIRECT, STOREV, N, K, V, LDV, TAU, T, LDT ) */ /* .. Scalar Arguments .. */ /* CHARACTER DIRECT, STOREV */ /* INTEGER K, LDT, LDV, N */ /* .. */ /* .. Array Arguments .. */ /* DOUBLE PRECISION T( LDT, * ), TAU( * ), V( LDV, * ) */ /* .. */ /* > \par Purpose: */ /* ============= */ /* > */ /* > \verbatim */ /* > */ /* > DLARFT forms the triangular factor T of a real block reflector H */ /* > of order n, which is defined as a product of k elementary reflectors. */ /* > */ /* > If DIRECT = 'F', H = H(1) H(2) . . . H(k) and T is upper triangular; */ /* > */ /* > If DIRECT = 'B', H = H(k) . . . H(2) H(1) and T is lower triangular. */ /* > */ /* > If STOREV = 'C', the vector which defines the elementary reflector */ /* > H(i) is stored in the i-th column of the array V, and */ /* > */ /* > H = I - V * T * V**T */ /* > */ /* > If STOREV = 'R', the vector which defines the elementary reflector */ /* > H(i) is stored in the i-th row of the array V, and */ /* > */ /* > H = I - V**T * T * V */ /* > \endverbatim */ /* Arguments: */ /* ========== */ /* > \param[in] DIRECT */ /* > \verbatim */ /* > DIRECT is CHARACTER*1 */ /* > Specifies the order in which the elementary reflectors are */ /* > multiplied to form the block reflector: */ /* > = 'F': H = H(1) H(2) . . . H(k) (Forward) */ /* > = 'B': H = H(k) . . . H(2) H(1) (Backward) */ /* > \endverbatim */ /* > */ /* > \param[in] STOREV */ /* > \verbatim */ /* > STOREV is CHARACTER*1 */ /* > Specifies how the vectors which define the elementary */ /* > reflectors are stored (see also Further Details): */ /* > = 'C': columnwise */ /* > = 'R': rowwise */ /* > \endverbatim */ /* > */ /* > \param[in] N */ /* > \verbatim */ /* > N is INTEGER */ /* > The order of the block reflector H. N >= 0. */ /* > \endverbatim */ /* > */ /* > \param[in] K */ /* > \verbatim */ /* > K is INTEGER */ /* > The order of the triangular factor T (= the number of */ /* > elementary reflectors). K >= 1. */ /* > \endverbatim */ /* > */ /* > \param[in] V */ /* > \verbatim */ /* > V is DOUBLE PRECISION array, dimension */ /* > (LDV,K) if STOREV = 'C' */ /* > (LDV,N) if STOREV = 'R' */ /* > The matrix V. See further details. */ /* > \endverbatim */ /* > */ /* > \param[in] LDV */ /* > \verbatim */ /* > LDV is INTEGER */ /* > The leading dimension of the array V. */ /* > If STOREV = 'C', LDV >= max(1,N); if STOREV = 'R', LDV >= K. */ /* > \endverbatim */ /* > */ /* > \param[in] TAU */ /* > \verbatim */ /* > TAU is DOUBLE PRECISION array, dimension (K) */ /* > TAU(i) must contain the scalar factor of the elementary */ /* > reflector H(i). */ /* > \endverbatim */ /* > */ /* > \param[out] T */ /* > \verbatim */ /* > T is DOUBLE PRECISION array, dimension (LDT,K) */ /* > The k by k triangular factor T of the block reflector. */ /* > If DIRECT = 'F', T is upper triangular; if DIRECT = 'B', T is */ /* > lower triangular. The rest of the array is not used. */ /* > \endverbatim */ /* > */ /* > \param[in] LDT */ /* > \verbatim */ /* > LDT is INTEGER */ /* > The leading dimension of the array T. LDT >= K. */ /* > \endverbatim */ /* Authors: */ /* ======== */ /* > \author Univ. of Tennessee */ /* > \author Univ. of California Berkeley */ /* > \author Univ. of Colorado Denver */ /* > \author NAG Ltd. */ /* > \date September 2012 */ /* > \ingroup doubleOTHERauxiliary */ /* > \par Further Details: */ /* ===================== */ /* > */ /* > \verbatim */ /* > */ /* > The shape of the matrix V and the storage of the vectors which define */ /* > the H(i) is best illustrated by the following example with n = 5 and */ /* > k = 3. The elements equal to 1 are not stored. */ /* > */ /* > DIRECT = 'F' and STOREV = 'C': DIRECT = 'F' and STOREV = 'R': */ /* > */ /* > V = ( 1 ) V = ( 1 v1 v1 v1 v1 ) */ /* > ( v1 1 ) ( 1 v2 v2 v2 ) */ /* > ( v1 v2 1 ) ( 1 v3 v3 ) */ /* > ( v1 v2 v3 ) */ /* > ( v1 v2 v3 ) */ /* > */ /* > DIRECT = 'B' and STOREV = 'C': DIRECT = 'B' and STOREV = 'R': */ /* > */ /* > V = ( v1 v2 v3 ) V = ( v1 v1 1 ) */ /* > ( v1 v2 v3 ) ( v2 v2 v2 1 ) */ /* > ( 1 v2 v3 ) ( v3 v3 v3 v3 1 ) */ /* > ( 1 v3 ) */ /* > ( 1 ) */ /* > \endverbatim */ /* > */ /* ===================================================================== */ /* Subroutine */ int igraphdlarft_(char *direct, char *storev, integer *n, integer * k, doublereal *v, integer *ldv, doublereal *tau, doublereal *t, integer *ldt) { /* System generated locals */ integer t_dim1, t_offset, v_dim1, v_offset, i__1, i__2, i__3; doublereal d__1; /* Local variables */ integer i__, j, prevlastv; extern logical igraphlsame_(char *, char *); extern /* Subroutine */ int igraphdgemv_(char *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *); integer lastv; extern /* Subroutine */ int igraphdtrmv_(char *, char *, char *, integer *, doublereal *, integer *, doublereal *, integer *); /* -- LAPACK auxiliary routine (version 3.4.2) -- */ /* -- LAPACK is a software package provided by Univ. of Tennessee, -- */ /* -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- */ /* September 2012 */ /* .. Scalar Arguments .. */ /* .. */ /* .. Array Arguments .. */ /* .. */ /* ===================================================================== */ /* .. Parameters .. */ /* .. */ /* .. Local Scalars .. */ /* .. */ /* .. External Subroutines .. */ /* .. */ /* .. External Functions .. */ /* .. */ /* .. Executable Statements .. */ /* Quick return if possible */ /* Parameter adjustments */ v_dim1 = *ldv; v_offset = 1 + v_dim1; v -= v_offset; --tau; t_dim1 = *ldt; t_offset = 1 + t_dim1; t -= t_offset; /* Function Body */ if (*n == 0) { return 0; } if (igraphlsame_(direct, "F")) { prevlastv = *n; i__1 = *k; for (i__ = 1; i__ <= i__1; ++i__) { prevlastv = max(i__,prevlastv); if (tau[i__] == 0.) { /* H(i) = I */ i__2 = i__; for (j = 1; j <= i__2; ++j) { t[j + i__ * t_dim1] = 0.; } } else { /* general case */ if (igraphlsame_(storev, "C")) { /* Skip any trailing zeros. */ lastv = *n; L14: if (v[lastv + i__ * v_dim1] != 0.) { goto L15; } if (lastv == i__ + 1) { goto L15; } --lastv; goto L14; L15: /* DO LASTV = N, I+1, -1 */ /* IF( V( LASTV, I ).NE.ZERO ) EXIT */ /* END DO */ i__2 = i__ - 1; for (j = 1; j <= i__2; ++j) { t[j + i__ * t_dim1] = -tau[i__] * v[i__ + j * v_dim1]; } j = min(lastv,prevlastv); /* T(1:i-1,i) := - tau(i) * V(i:j,1:i-1)**T * V(i:j,i) */ i__2 = j - i__; i__3 = i__ - 1; d__1 = -tau[i__]; igraphdgemv_("Transpose", &i__2, &i__3, &d__1, &v[i__ + 1 + v_dim1], ldv, &v[i__ + 1 + i__ * v_dim1], &c__1, & c_b8, &t[i__ * t_dim1 + 1], &c__1); } else { /* Skip any trailing zeros. */ lastv = *n; L16: if (v[i__ + lastv * v_dim1] != 0.) { goto L17; } if (lastv == i__ + 1) { goto L17; } --lastv; goto L16; L17: /* DO LASTV = N, I+1, -1 */ /* IF( V( I, LASTV ).NE.ZERO ) EXIT */ /* END DO */ i__2 = i__ - 1; for (j = 1; j <= i__2; ++j) { t[j + i__ * t_dim1] = -tau[i__] * v[j + i__ * v_dim1]; } j = min(lastv,prevlastv); /* T(1:i-1,i) := - tau(i) * V(1:i-1,i:j) * V(i,i:j)**T */ i__2 = i__ - 1; i__3 = j - i__; d__1 = -tau[i__]; igraphdgemv_("No transpose", &i__2, &i__3, &d__1, &v[(i__ + 1) * v_dim1 + 1], ldv, &v[i__ + (i__ + 1) * v_dim1], ldv, &c_b8, &t[i__ * t_dim1 + 1], &c__1); } /* T(1:i-1,i) := T(1:i-1,1:i-1) * T(1:i-1,i) */ i__2 = i__ - 1; igraphdtrmv_("Upper", "No transpose", "Non-unit", &i__2, &t[ t_offset], ldt, &t[i__ * t_dim1 + 1], &c__1); t[i__ + i__ * t_dim1] = tau[i__]; if (i__ > 1) { prevlastv = max(prevlastv,lastv); } else { prevlastv = lastv; } } } } else { prevlastv = 1; for (i__ = *k; i__ >= 1; --i__) { if (tau[i__] == 0.) { /* H(i) = I */ i__1 = *k; for (j = i__; j <= i__1; ++j) { t[j + i__ * t_dim1] = 0.; } } else { /* general case */ if (i__ < *k) { if (igraphlsame_(storev, "C")) { /* Skip any leading zeros. */ lastv = 1; L34: if (v[lastv + i__ * v_dim1] != 0.) { goto L35; } if (lastv == i__ - 1) { goto L35; } ++lastv; goto L34; L35: /* DO LASTV = 1, I-1 */ /* IF( V( LASTV, I ).NE.ZERO ) EXIT */ /* END DO */ i__1 = *k; for (j = i__ + 1; j <= i__1; ++j) { t[j + i__ * t_dim1] = -tau[i__] * v[*n - *k + i__ + j * v_dim1]; } j = max(lastv,prevlastv); /* T(i+1:k,i) = -tau(i) * V(j:n-k+i,i+1:k)**T * V(j:n-k+i,i) */ i__1 = *n - *k + i__ - j; i__2 = *k - i__; d__1 = -tau[i__]; igraphdgemv_("Transpose", &i__1, &i__2, &d__1, &v[j + (i__ + 1) * v_dim1], ldv, &v[j + i__ * v_dim1], & c__1, &c_b8, &t[i__ + 1 + i__ * t_dim1], & c__1); } else { /* Skip any leading zeros. */ lastv = 1; /* L36: */ if (v[i__ + lastv * v_dim1] != 0.) { goto L37; } if (lastv == i__ - 1) { goto L37; } ++lastv; L37: /* DO LASTV = 1, I-1 */ /* IF( V( I, LASTV ).NE.ZERO ) EXIT */ /* END DO */ i__1 = *k; for (j = i__ + 1; j <= i__1; ++j) { t[j + i__ * t_dim1] = -tau[i__] * v[j + (*n - *k + i__) * v_dim1]; } j = max(lastv,prevlastv); /* T(i+1:k,i) = -tau(i) * V(i+1:k,j:n-k+i) * V(i,j:n-k+i)**T */ i__1 = *k - i__; i__2 = *n - *k + i__ - j; d__1 = -tau[i__]; igraphdgemv_("No transpose", &i__1, &i__2, &d__1, &v[i__ + 1 + j * v_dim1], ldv, &v[i__ + j * v_dim1], ldv, &c_b8, &t[i__ + 1 + i__ * t_dim1], &c__1 ); } /* T(i+1:k,i) := T(i+1:k,i+1:k) * T(i+1:k,i) */ i__1 = *k - i__; igraphdtrmv_("Lower", "No transpose", "Non-unit", &i__1, &t[i__ + 1 + (i__ + 1) * t_dim1], ldt, &t[i__ + 1 + i__ * t_dim1], &c__1) ; if (i__ > 1) { prevlastv = min(prevlastv,lastv); } else { prevlastv = lastv; } } t[i__ + i__ * t_dim1] = tau[i__]; } } } return 0; /* End of DLARFT */ } /* dlarft_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlascl.c0000644000076500000240000002500113524616145024244 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLASCL multiplies a general rectangular matrix by a real scalar defined as cto/cfrom. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLASCL + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLASCL( TYPE, KL, KU, CFROM, CTO, M, N, A, LDA, INFO ) CHARACTER TYPE INTEGER INFO, KL, KU, LDA, M, N DOUBLE PRECISION CFROM, CTO DOUBLE PRECISION A( LDA, * ) > \par Purpose: ============= > > \verbatim > > DLASCL multiplies the M by N real matrix A by the real scalar > CTO/CFROM. This is done without over/underflow as long as the final > result CTO*A(I,J)/CFROM does not over/underflow. TYPE specifies that > A may be full, upper triangular, lower triangular, upper Hessenberg, > or banded. > \endverbatim Arguments: ========== > \param[in] TYPE > \verbatim > TYPE is CHARACTER*1 > TYPE indices the storage type of the input matrix. > = 'G': A is a full matrix. > = 'L': A is a lower triangular matrix. > = 'U': A is an upper triangular matrix. > = 'H': A is an upper Hessenberg matrix. > = 'B': A is a symmetric band matrix with lower bandwidth KL > and upper bandwidth KU and with the only the lower > half stored. > = 'Q': A is a symmetric band matrix with lower bandwidth KL > and upper bandwidth KU and with the only the upper > half stored. > = 'Z': A is a band matrix with lower bandwidth KL and upper > bandwidth KU. See DGBTRF for storage details. > \endverbatim > > \param[in] KL > \verbatim > KL is INTEGER > The lower bandwidth of A. Referenced only if TYPE = 'B', > 'Q' or 'Z'. > \endverbatim > > \param[in] KU > \verbatim > KU is INTEGER > The upper bandwidth of A. Referenced only if TYPE = 'B', > 'Q' or 'Z'. > \endverbatim > > \param[in] CFROM > \verbatim > CFROM is DOUBLE PRECISION > \endverbatim > > \param[in] CTO > \verbatim > CTO is DOUBLE PRECISION > > The matrix A is multiplied by CTO/CFROM. A(I,J) is computed > without over/underflow if the final result CTO*A(I,J)/CFROM > can be represented without over/underflow. CFROM must be > nonzero. > \endverbatim > > \param[in] M > \verbatim > M is INTEGER > The number of rows of the matrix A. M >= 0. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The number of columns of the matrix A. N >= 0. > \endverbatim > > \param[in,out] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,N) > The matrix to be multiplied by CTO/CFROM. See TYPE for the > storage type. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. LDA >= max(1,M). > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > 0 - successful exit > <0 - if INFO = -i, the i-th argument had an illegal value. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERauxiliary ===================================================================== Subroutine */ int igraphdlascl_(char *type__, integer *kl, integer *ku, doublereal *cfrom, doublereal *cto, integer *m, integer *n, doublereal *a, integer *lda, integer *info) { /* System generated locals */ integer a_dim1, a_offset, i__1, i__2, i__3, i__4, i__5; /* Local variables */ integer i__, j, k1, k2, k3, k4; doublereal mul, cto1; logical done; doublereal ctoc; extern logical igraphlsame_(char *, char *); integer itype; doublereal cfrom1; extern doublereal igraphdlamch_(char *); doublereal cfromc; extern logical igraphdisnan_(doublereal *); extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); doublereal bignum, smlnum; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Test the input arguments Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; /* Function Body */ *info = 0; if (igraphlsame_(type__, "G")) { itype = 0; } else if (igraphlsame_(type__, "L")) { itype = 1; } else if (igraphlsame_(type__, "U")) { itype = 2; } else if (igraphlsame_(type__, "H")) { itype = 3; } else if (igraphlsame_(type__, "B")) { itype = 4; } else if (igraphlsame_(type__, "Q")) { itype = 5; } else if (igraphlsame_(type__, "Z")) { itype = 6; } else { itype = -1; } if (itype == -1) { *info = -1; } else if (*cfrom == 0. || igraphdisnan_(cfrom)) { *info = -4; } else if (igraphdisnan_(cto)) { *info = -5; } else if (*m < 0) { *info = -6; } else if (*n < 0 || itype == 4 && *n != *m || itype == 5 && *n != *m) { *info = -7; } else if (itype <= 3 && *lda < max(1,*m)) { *info = -9; } else if (itype >= 4) { /* Computing MAX */ i__1 = *m - 1; if (*kl < 0 || *kl > max(i__1,0)) { *info = -2; } else /* if(complicated condition) */ { /* Computing MAX */ i__1 = *n - 1; if (*ku < 0 || *ku > max(i__1,0) || (itype == 4 || itype == 5) && *kl != *ku) { *info = -3; } else if (itype == 4 && *lda < *kl + 1 || itype == 5 && *lda < * ku + 1 || itype == 6 && *lda < (*kl << 1) + *ku + 1) { *info = -9; } } } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DLASCL", &i__1, (ftnlen)6); return 0; } /* Quick return if possible */ if (*n == 0 || *m == 0) { return 0; } /* Get machine parameters */ smlnum = igraphdlamch_("S"); bignum = 1. / smlnum; cfromc = *cfrom; ctoc = *cto; L10: cfrom1 = cfromc * smlnum; if (cfrom1 == cfromc) { /* CFROMC is an inf. Multiply by a correctly signed zero for finite CTOC, or a NaN if CTOC is infinite. */ mul = ctoc / cfromc; done = TRUE_; cto1 = ctoc; } else { cto1 = ctoc / bignum; if (cto1 == ctoc) { /* CTOC is either 0 or an inf. In both cases, CTOC itself serves as the correct multiplication factor. */ mul = ctoc; done = TRUE_; cfromc = 1.; } else if (abs(cfrom1) > abs(ctoc) && ctoc != 0.) { mul = smlnum; done = FALSE_; cfromc = cfrom1; } else if (abs(cto1) > abs(cfromc)) { mul = bignum; done = FALSE_; ctoc = cto1; } else { mul = ctoc / cfromc; done = TRUE_; } } if (itype == 0) { /* Full matrix */ i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { a[i__ + j * a_dim1] *= mul; /* L20: */ } /* L30: */ } } else if (itype == 1) { /* Lower triangular matrix */ i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = *m; for (i__ = j; i__ <= i__2; ++i__) { a[i__ + j * a_dim1] *= mul; /* L40: */ } /* L50: */ } } else if (itype == 2) { /* Upper triangular matrix */ i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = min(j,*m); for (i__ = 1; i__ <= i__2; ++i__) { a[i__ + j * a_dim1] *= mul; /* L60: */ } /* L70: */ } } else if (itype == 3) { /* Upper Hessenberg matrix */ i__1 = *n; for (j = 1; j <= i__1; ++j) { /* Computing MIN */ i__3 = j + 1; i__2 = min(i__3,*m); for (i__ = 1; i__ <= i__2; ++i__) { a[i__ + j * a_dim1] *= mul; /* L80: */ } /* L90: */ } } else if (itype == 4) { /* Lower half of a symmetric band matrix */ k3 = *kl + 1; k4 = *n + 1; i__1 = *n; for (j = 1; j <= i__1; ++j) { /* Computing MIN */ i__3 = k3, i__4 = k4 - j; i__2 = min(i__3,i__4); for (i__ = 1; i__ <= i__2; ++i__) { a[i__ + j * a_dim1] *= mul; /* L100: */ } /* L110: */ } } else if (itype == 5) { /* Upper half of a symmetric band matrix */ k1 = *ku + 2; k3 = *ku + 1; i__1 = *n; for (j = 1; j <= i__1; ++j) { /* Computing MAX */ i__2 = k1 - j; i__3 = k3; for (i__ = max(i__2,1); i__ <= i__3; ++i__) { a[i__ + j * a_dim1] *= mul; /* L120: */ } /* L130: */ } } else if (itype == 6) { /* Band matrix */ k1 = *kl + *ku + 2; k2 = *kl + 1; k3 = (*kl << 1) + *ku + 1; k4 = *kl + *ku + 1 + *m; i__1 = *n; for (j = 1; j <= i__1; ++j) { /* Computing MAX */ i__3 = k1 - j; /* Computing MIN */ i__4 = k3, i__5 = k4 - j; i__2 = min(i__4,i__5); for (i__ = max(i__3,k2); i__ <= i__2; ++i__) { a[i__ + j * a_dim1] *= mul; /* L140: */ } /* L150: */ } } if (! done) { goto L10; } return 0; /* End of DLASCL */ } /* igraphdlascl_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlae2.c0000644000076500000240000001231113524616145023771 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLAE2 computes the eigenvalues of a 2-by-2 symmetric matrix. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLAE2 + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLAE2( A, B, C, RT1, RT2 ) DOUBLE PRECISION A, B, C, RT1, RT2 > \par Purpose: ============= > > \verbatim > > DLAE2 computes the eigenvalues of a 2-by-2 symmetric matrix > [ A B ] > [ B C ]. > On return, RT1 is the eigenvalue of larger absolute value, and RT2 > is the eigenvalue of smaller absolute value. > \endverbatim Arguments: ========== > \param[in] A > \verbatim > A is DOUBLE PRECISION > The (1,1) element of the 2-by-2 matrix. > \endverbatim > > \param[in] B > \verbatim > B is DOUBLE PRECISION > The (1,2) and (2,1) elements of the 2-by-2 matrix. > \endverbatim > > \param[in] C > \verbatim > C is DOUBLE PRECISION > The (2,2) element of the 2-by-2 matrix. > \endverbatim > > \param[out] RT1 > \verbatim > RT1 is DOUBLE PRECISION > The eigenvalue of larger absolute value. > \endverbatim > > \param[out] RT2 > \verbatim > RT2 is DOUBLE PRECISION > The eigenvalue of smaller absolute value. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERauxiliary > \par Further Details: ===================== > > \verbatim > > RT1 is accurate to a few ulps barring over/underflow. > > RT2 may be inaccurate if there is massive cancellation in the > determinant A*C-B*B; higher precision or correctly rounded or > correctly truncated arithmetic would be needed to compute RT2 > accurately in all cases. > > Overflow is possible only if RT1 is within a factor of 5 of overflow. > Underflow is harmless if the input data is 0 or exceeds > underflow_threshold / macheps. > \endverbatim > ===================================================================== Subroutine */ int igraphdlae2_(doublereal *a, doublereal *b, doublereal *c__, doublereal *rt1, doublereal *rt2) { /* System generated locals */ doublereal d__1; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ doublereal ab, df, tb, sm, rt, adf, acmn, acmx; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Compute the eigenvalues */ sm = *a + *c__; df = *a - *c__; adf = abs(df); tb = *b + *b; ab = abs(tb); if (abs(*a) > abs(*c__)) { acmx = *a; acmn = *c__; } else { acmx = *c__; acmn = *a; } if (adf > ab) { /* Computing 2nd power */ d__1 = ab / adf; rt = adf * sqrt(d__1 * d__1 + 1.); } else if (adf < ab) { /* Computing 2nd power */ d__1 = adf / ab; rt = ab * sqrt(d__1 * d__1 + 1.); } else { /* Includes case AB=ADF=0 */ rt = ab * sqrt(2.); } if (sm < 0.) { *rt1 = (sm - rt) * .5; /* Order of execution important. To get fully accurate smaller eigenvalue, next line needs to be executed in higher precision. */ *rt2 = acmx / *rt1 * acmn - *b / *rt1 * *b; } else if (sm > 0.) { *rt1 = (sm + rt) * .5; /* Order of execution important. To get fully accurate smaller eigenvalue, next line needs to be executed in higher precision. */ *rt2 = acmx / *rt1 * acmn - *b / *rt1 * *b; } else { /* Includes case RT1 = RT2 = 0 */ *rt1 = rt * .5; *rt2 = rt * -.5; } return 0; /* End of DLAE2 */ } /* igraphdlae2_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dstebz.c0000644000076500000240000005747513524616145024321 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static integer c_n1 = -1; static integer c__3 = 3; static integer c__2 = 2; static integer c__0 = 0; /* > \brief \b DSTEBZ =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DSTEBZ + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DSTEBZ( RANGE, ORDER, N, VL, VU, IL, IU, ABSTOL, D, E, M, NSPLIT, W, IBLOCK, ISPLIT, WORK, IWORK, INFO ) CHARACTER ORDER, RANGE INTEGER IL, INFO, IU, M, N, NSPLIT DOUBLE PRECISION ABSTOL, VL, VU INTEGER IBLOCK( * ), ISPLIT( * ), IWORK( * ) DOUBLE PRECISION D( * ), E( * ), W( * ), WORK( * ) > \par Purpose: ============= > > \verbatim > > DSTEBZ computes the eigenvalues of a symmetric tridiagonal > matrix T. The user may ask for all eigenvalues, all eigenvalues > in the half-open interval (VL, VU], or the IL-th through IU-th > eigenvalues. > > To avoid overflow, the matrix must be scaled so that its > largest element is no greater than overflow**(1/2) * underflow**(1/4) in absolute value, and for greatest > accuracy, it should not be much smaller than that. > > See W. Kahan "Accurate Eigenvalues of a Symmetric Tridiagonal > Matrix", Report CS41, Computer Science Dept., Stanford > University, July 21, 1966. > \endverbatim Arguments: ========== > \param[in] RANGE > \verbatim > RANGE is CHARACTER*1 > = 'A': ("All") all eigenvalues will be found. > = 'V': ("Value") all eigenvalues in the half-open interval > (VL, VU] will be found. > = 'I': ("Index") the IL-th through IU-th eigenvalues (of the > entire matrix) will be found. > \endverbatim > > \param[in] ORDER > \verbatim > ORDER is CHARACTER*1 > = 'B': ("By Block") the eigenvalues will be grouped by > split-off block (see IBLOCK, ISPLIT) and > ordered from smallest to largest within > the block. > = 'E': ("Entire matrix") > the eigenvalues for the entire matrix > will be ordered from smallest to > largest. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the tridiagonal matrix T. N >= 0. > \endverbatim > > \param[in] VL > \verbatim > VL is DOUBLE PRECISION > \endverbatim > > \param[in] VU > \verbatim > VU is DOUBLE PRECISION > > If RANGE='V', the lower and upper bounds of the interval to > be searched for eigenvalues. Eigenvalues less than or equal > to VL, or greater than VU, will not be returned. VL < VU. > Not referenced if RANGE = 'A' or 'I'. > \endverbatim > > \param[in] IL > \verbatim > IL is INTEGER > \endverbatim > > \param[in] IU > \verbatim > IU is INTEGER > > If RANGE='I', the indices (in ascending order) of the > smallest and largest eigenvalues to be returned. > 1 <= IL <= IU <= N, if N > 0; IL = 1 and IU = 0 if N = 0. > Not referenced if RANGE = 'A' or 'V'. > \endverbatim > > \param[in] ABSTOL > \verbatim > ABSTOL is DOUBLE PRECISION > The absolute tolerance for the eigenvalues. An eigenvalue > (or cluster) is considered to be located if it has been > determined to lie in an interval whose width is ABSTOL or > less. If ABSTOL is less than or equal to zero, then ULP*|T| > will be used, where |T| means the 1-norm of T. > > Eigenvalues will be computed most accurately when ABSTOL is > set to twice the underflow threshold 2*DLAMCH('S'), not zero. > \endverbatim > > \param[in] D > \verbatim > D is DOUBLE PRECISION array, dimension (N) > The n diagonal elements of the tridiagonal matrix T. > \endverbatim > > \param[in] E > \verbatim > E is DOUBLE PRECISION array, dimension (N-1) > The (n-1) off-diagonal elements of the tridiagonal matrix T. > \endverbatim > > \param[out] M > \verbatim > M is INTEGER > The actual number of eigenvalues found. 0 <= M <= N. > (See also the description of INFO=2,3.) > \endverbatim > > \param[out] NSPLIT > \verbatim > NSPLIT is INTEGER > The number of diagonal blocks in the matrix T. > 1 <= NSPLIT <= N. > \endverbatim > > \param[out] W > \verbatim > W is DOUBLE PRECISION array, dimension (N) > On exit, the first M elements of W will contain the > eigenvalues. (DSTEBZ may use the remaining N-M elements as > workspace.) > \endverbatim > > \param[out] IBLOCK > \verbatim > IBLOCK is INTEGER array, dimension (N) > At each row/column j where E(j) is zero or small, the > matrix T is considered to split into a block diagonal > matrix. On exit, if INFO = 0, IBLOCK(i) specifies to which > block (from 1 to the number of blocks) the eigenvalue W(i) > belongs. (DSTEBZ may use the remaining N-M elements as > workspace.) > \endverbatim > > \param[out] ISPLIT > \verbatim > ISPLIT is INTEGER array, dimension (N) > The splitting points, at which T breaks up into submatrices. > The first submatrix consists of rows/columns 1 to ISPLIT(1), > the second of rows/columns ISPLIT(1)+1 through ISPLIT(2), > etc., and the NSPLIT-th consists of rows/columns > ISPLIT(NSPLIT-1)+1 through ISPLIT(NSPLIT)=N. > (Only the first NSPLIT elements will actually be used, but > since the user cannot know a priori what value NSPLIT will > have, N words must be reserved for ISPLIT.) > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (4*N) > \endverbatim > > \param[out] IWORK > \verbatim > IWORK is INTEGER array, dimension (3*N) > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value > > 0: some or all of the eigenvalues failed to converge or > were not computed: > =1 or 3: Bisection failed to converge for some > eigenvalues; these eigenvalues are flagged by a > negative block number. The effect is that the > eigenvalues may not be as accurate as the > absolute and relative tolerances. This is > generally caused by unexpectedly inaccurate > arithmetic. > =2 or 3: RANGE='I' only: Not all of the eigenvalues > IL:IU were found. > Effect: M < IU+1-IL > Cause: non-monotonic arithmetic, causing the > Sturm sequence to be non-monotonic. > Cure: recalculate, using RANGE='A', and pick > out eigenvalues IL:IU. In some cases, > increasing the PARAMETER "FUDGE" may > make things work. > = 4: RANGE='I', and the Gershgorin interval > initially used was too small. No eigenvalues > were computed. > Probable cause: your machine has sloppy > floating-point arithmetic. > Cure: Increase the PARAMETER "FUDGE", > recompile, and try again. > \endverbatim > \par Internal Parameters: ========================= > > \verbatim > RELFAC DOUBLE PRECISION, default = 2.0e0 > The relative tolerance. An interval (a,b] lies within > "relative tolerance" if b-a < RELFAC*ulp*max(|a|,|b|), > where "ulp" is the machine precision (distance from 1 to > the next larger floating point number.) > > FUDGE DOUBLE PRECISION, default = 2 > A "fudge factor" to widen the Gershgorin intervals. Ideally, > a value of 1 should work, but on machines with sloppy > arithmetic, this needs to be larger. The default for > publicly released versions should be large enough to handle > the worst machine around. Note that this has no effect > on accuracy of the solution. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2011 > \ingroup auxOTHERcomputational ===================================================================== Subroutine */ int igraphdstebz_(char *range, char *order, integer *n, doublereal *vl, doublereal *vu, integer *il, integer *iu, doublereal *abstol, doublereal *d__, doublereal *e, integer *m, integer *nsplit, doublereal *w, integer *iblock, integer *isplit, doublereal *work, integer *iwork, integer *info) { /* System generated locals */ integer i__1, i__2, i__3; doublereal d__1, d__2, d__3, d__4, d__5; /* Builtin functions */ double sqrt(doublereal), log(doublereal); /* Local variables */ integer j, ib, jb, ie, je, nb; doublereal gl; integer im, in; doublereal gu; integer iw; doublereal wl, wu; integer nwl; doublereal ulp, wlu, wul; integer nwu; doublereal tmp1, tmp2; integer iend, ioff, iout, itmp1, jdisc; extern logical igraphlsame_(char *, char *); integer iinfo; doublereal atoli; integer iwoff; doublereal bnorm; integer itmax; doublereal wkill, rtoli, tnorm; extern doublereal igraphdlamch_(char *); integer ibegin; extern /* Subroutine */ int igraphdlaebz_(integer *, integer *, integer *, integer *, integer *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, integer *, integer *); integer irange, idiscl; doublereal safemn; integer idumma[1]; extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); extern integer igraphilaenv_(integer *, char *, char *, integer *, integer *, integer *, integer *, ftnlen, ftnlen); integer idiscu, iorder; logical ncnvrg; doublereal pivmin; logical toofew; /* -- LAPACK computational routine (version 3.4.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2011 ===================================================================== Parameter adjustments */ --iwork; --work; --isplit; --iblock; --w; --e; --d__; /* Function Body */ *info = 0; /* Decode RANGE */ if (igraphlsame_(range, "A")) { irange = 1; } else if (igraphlsame_(range, "V")) { irange = 2; } else if (igraphlsame_(range, "I")) { irange = 3; } else { irange = 0; } /* Decode ORDER */ if (igraphlsame_(order, "B")) { iorder = 2; } else if (igraphlsame_(order, "E")) { iorder = 1; } else { iorder = 0; } /* Check for Errors */ if (irange <= 0) { *info = -1; } else if (iorder <= 0) { *info = -2; } else if (*n < 0) { *info = -3; } else if (irange == 2) { if (*vl >= *vu) { *info = -5; } } else if (irange == 3 && (*il < 1 || *il > max(1,*n))) { *info = -6; } else if (irange == 3 && (*iu < min(*n,*il) || *iu > *n)) { *info = -7; } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DSTEBZ", &i__1, (ftnlen)6); return 0; } /* Initialize error flags */ *info = 0; ncnvrg = FALSE_; toofew = FALSE_; /* Quick return if possible */ *m = 0; if (*n == 0) { return 0; } /* Simplifications: */ if (irange == 3 && *il == 1 && *iu == *n) { irange = 1; } /* Get machine constants NB is the minimum vector length for vector bisection, or 0 if only scalar is to be done. */ safemn = igraphdlamch_("S"); ulp = igraphdlamch_("P"); rtoli = ulp * 2.; nb = igraphilaenv_(&c__1, "DSTEBZ", " ", n, &c_n1, &c_n1, &c_n1, (ftnlen)6, ( ftnlen)1); if (nb <= 1) { nb = 0; } /* Special Case when N=1 */ if (*n == 1) { *nsplit = 1; isplit[1] = 1; if (irange == 2 && (*vl >= d__[1] || *vu < d__[1])) { *m = 0; } else { w[1] = d__[1]; iblock[1] = 1; *m = 1; } return 0; } /* Compute Splitting Points */ *nsplit = 1; work[*n] = 0.; pivmin = 1.; i__1 = *n; for (j = 2; j <= i__1; ++j) { /* Computing 2nd power */ d__1 = e[j - 1]; tmp1 = d__1 * d__1; /* Computing 2nd power */ d__2 = ulp; if ((d__1 = d__[j] * d__[j - 1], abs(d__1)) * (d__2 * d__2) + safemn > tmp1) { isplit[*nsplit] = j - 1; ++(*nsplit); work[j - 1] = 0.; } else { work[j - 1] = tmp1; pivmin = max(pivmin,tmp1); } /* L10: */ } isplit[*nsplit] = *n; pivmin *= safemn; /* Compute Interval and ATOLI */ if (irange == 3) { /* RANGE='I': Compute the interval containing eigenvalues IL through IU. Compute Gershgorin interval for entire (split) matrix and use it as the initial interval */ gu = d__[1]; gl = d__[1]; tmp1 = 0.; i__1 = *n - 1; for (j = 1; j <= i__1; ++j) { tmp2 = sqrt(work[j]); /* Computing MAX */ d__1 = gu, d__2 = d__[j] + tmp1 + tmp2; gu = max(d__1,d__2); /* Computing MIN */ d__1 = gl, d__2 = d__[j] - tmp1 - tmp2; gl = min(d__1,d__2); tmp1 = tmp2; /* L20: */ } /* Computing MAX */ d__1 = gu, d__2 = d__[*n] + tmp1; gu = max(d__1,d__2); /* Computing MIN */ d__1 = gl, d__2 = d__[*n] - tmp1; gl = min(d__1,d__2); /* Computing MAX */ d__1 = abs(gl), d__2 = abs(gu); tnorm = max(d__1,d__2); gl = gl - tnorm * 2.1 * ulp * *n - pivmin * 4.2000000000000002; gu = gu + tnorm * 2.1 * ulp * *n + pivmin * 2.1; /* Compute Iteration parameters */ itmax = (integer) ((log(tnorm + pivmin) - log(pivmin)) / log(2.)) + 2; if (*abstol <= 0.) { atoli = ulp * tnorm; } else { atoli = *abstol; } work[*n + 1] = gl; work[*n + 2] = gl; work[*n + 3] = gu; work[*n + 4] = gu; work[*n + 5] = gl; work[*n + 6] = gu; iwork[1] = -1; iwork[2] = -1; iwork[3] = *n + 1; iwork[4] = *n + 1; iwork[5] = *il - 1; iwork[6] = *iu; igraphdlaebz_(&c__3, &itmax, n, &c__2, &c__2, &nb, &atoli, &rtoli, &pivmin, &d__[1], &e[1], &work[1], &iwork[5], &work[*n + 1], &work[*n + 5], &iout, &iwork[1], &w[1], &iblock[1], &iinfo); if (iwork[6] == *iu) { wl = work[*n + 1]; wlu = work[*n + 3]; nwl = iwork[1]; wu = work[*n + 4]; wul = work[*n + 2]; nwu = iwork[4]; } else { wl = work[*n + 2]; wlu = work[*n + 4]; nwl = iwork[2]; wu = work[*n + 3]; wul = work[*n + 1]; nwu = iwork[3]; } if (nwl < 0 || nwl >= *n || nwu < 1 || nwu > *n) { *info = 4; return 0; } } else { /* RANGE='A' or 'V' -- Set ATOLI Computing MAX */ d__3 = abs(d__[1]) + abs(e[1]), d__4 = (d__1 = d__[*n], abs(d__1)) + ( d__2 = e[*n - 1], abs(d__2)); tnorm = max(d__3,d__4); i__1 = *n - 1; for (j = 2; j <= i__1; ++j) { /* Computing MAX */ d__4 = tnorm, d__5 = (d__1 = d__[j], abs(d__1)) + (d__2 = e[j - 1] , abs(d__2)) + (d__3 = e[j], abs(d__3)); tnorm = max(d__4,d__5); /* L30: */ } if (*abstol <= 0.) { atoli = ulp * tnorm; } else { atoli = *abstol; } if (irange == 2) { wl = *vl; wu = *vu; } else { wl = 0.; wu = 0.; } } /* Find Eigenvalues -- Loop Over Blocks and recompute NWL and NWU. NWL accumulates the number of eigenvalues .le. WL, NWU accumulates the number of eigenvalues .le. WU */ *m = 0; iend = 0; *info = 0; nwl = 0; nwu = 0; i__1 = *nsplit; for (jb = 1; jb <= i__1; ++jb) { ioff = iend; ibegin = ioff + 1; iend = isplit[jb]; in = iend - ioff; if (in == 1) { /* Special Case -- IN=1 */ if (irange == 1 || wl >= d__[ibegin] - pivmin) { ++nwl; } if (irange == 1 || wu >= d__[ibegin] - pivmin) { ++nwu; } if (irange == 1 || wl < d__[ibegin] - pivmin && wu >= d__[ibegin] - pivmin) { ++(*m); w[*m] = d__[ibegin]; iblock[*m] = jb; } } else { /* General Case -- IN > 1 Compute Gershgorin Interval and use it as the initial interval */ gu = d__[ibegin]; gl = d__[ibegin]; tmp1 = 0.; i__2 = iend - 1; for (j = ibegin; j <= i__2; ++j) { tmp2 = (d__1 = e[j], abs(d__1)); /* Computing MAX */ d__1 = gu, d__2 = d__[j] + tmp1 + tmp2; gu = max(d__1,d__2); /* Computing MIN */ d__1 = gl, d__2 = d__[j] - tmp1 - tmp2; gl = min(d__1,d__2); tmp1 = tmp2; /* L40: */ } /* Computing MAX */ d__1 = gu, d__2 = d__[iend] + tmp1; gu = max(d__1,d__2); /* Computing MIN */ d__1 = gl, d__2 = d__[iend] - tmp1; gl = min(d__1,d__2); /* Computing MAX */ d__1 = abs(gl), d__2 = abs(gu); bnorm = max(d__1,d__2); gl = gl - bnorm * 2.1 * ulp * in - pivmin * 2.1; gu = gu + bnorm * 2.1 * ulp * in + pivmin * 2.1; /* Compute ATOLI for the current submatrix */ if (*abstol <= 0.) { /* Computing MAX */ d__1 = abs(gl), d__2 = abs(gu); atoli = ulp * max(d__1,d__2); } else { atoli = *abstol; } if (irange > 1) { if (gu < wl) { nwl += in; nwu += in; goto L70; } gl = max(gl,wl); gu = min(gu,wu); if (gl >= gu) { goto L70; } } /* Set Up Initial Interval */ work[*n + 1] = gl; work[*n + in + 1] = gu; igraphdlaebz_(&c__1, &c__0, &in, &in, &c__1, &nb, &atoli, &rtoli, & pivmin, &d__[ibegin], &e[ibegin], &work[ibegin], idumma, & work[*n + 1], &work[*n + (in << 1) + 1], &im, &iwork[1], & w[*m + 1], &iblock[*m + 1], &iinfo); nwl += iwork[1]; nwu += iwork[in + 1]; iwoff = *m - iwork[1]; /* Compute Eigenvalues */ itmax = (integer) ((log(gu - gl + pivmin) - log(pivmin)) / log(2.) ) + 2; igraphdlaebz_(&c__2, &itmax, &in, &in, &c__1, &nb, &atoli, &rtoli, & pivmin, &d__[ibegin], &e[ibegin], &work[ibegin], idumma, & work[*n + 1], &work[*n + (in << 1) + 1], &iout, &iwork[1], &w[*m + 1], &iblock[*m + 1], &iinfo); /* Copy Eigenvalues Into W and IBLOCK Use -JB for block number for unconverged eigenvalues. */ i__2 = iout; for (j = 1; j <= i__2; ++j) { tmp1 = (work[j + *n] + work[j + in + *n]) * .5; /* Flag non-convergence. */ if (j > iout - iinfo) { ncnvrg = TRUE_; ib = -jb; } else { ib = jb; } i__3 = iwork[j + in] + iwoff; for (je = iwork[j] + 1 + iwoff; je <= i__3; ++je) { w[je] = tmp1; iblock[je] = ib; /* L50: */ } /* L60: */ } *m += im; } L70: ; } /* If RANGE='I', then (WL,WU) contains eigenvalues NWL+1,...,NWU If NWL+1 < IL or NWU > IU, discard extra eigenvalues. */ if (irange == 3) { im = 0; idiscl = *il - 1 - nwl; idiscu = nwu - *iu; if (idiscl > 0 || idiscu > 0) { i__1 = *m; for (je = 1; je <= i__1; ++je) { if (w[je] <= wlu && idiscl > 0) { --idiscl; } else if (w[je] >= wul && idiscu > 0) { --idiscu; } else { ++im; w[im] = w[je]; iblock[im] = iblock[je]; } /* L80: */ } *m = im; } if (idiscl > 0 || idiscu > 0) { /* Code to deal with effects of bad arithmetic: Some low eigenvalues to be discarded are not in (WL,WLU], or high eigenvalues to be discarded are not in (WUL,WU] so just kill off the smallest IDISCL/largest IDISCU eigenvalues, by simply finding the smallest/largest eigenvalue(s). (If N(w) is monotone non-decreasing, this should never happen.) */ if (idiscl > 0) { wkill = wu; i__1 = idiscl; for (jdisc = 1; jdisc <= i__1; ++jdisc) { iw = 0; i__2 = *m; for (je = 1; je <= i__2; ++je) { if (iblock[je] != 0 && (w[je] < wkill || iw == 0)) { iw = je; wkill = w[je]; } /* L90: */ } iblock[iw] = 0; /* L100: */ } } if (idiscu > 0) { wkill = wl; i__1 = idiscu; for (jdisc = 1; jdisc <= i__1; ++jdisc) { iw = 0; i__2 = *m; for (je = 1; je <= i__2; ++je) { if (iblock[je] != 0 && (w[je] > wkill || iw == 0)) { iw = je; wkill = w[je]; } /* L110: */ } iblock[iw] = 0; /* L120: */ } } im = 0; i__1 = *m; for (je = 1; je <= i__1; ++je) { if (iblock[je] != 0) { ++im; w[im] = w[je]; iblock[im] = iblock[je]; } /* L130: */ } *m = im; } if (idiscl < 0 || idiscu < 0) { toofew = TRUE_; } } /* If ORDER='B', do nothing -- the eigenvalues are already sorted by block. If ORDER='E', sort the eigenvalues from smallest to largest */ if (iorder == 1 && *nsplit > 1) { i__1 = *m - 1; for (je = 1; je <= i__1; ++je) { ie = 0; tmp1 = w[je]; i__2 = *m; for (j = je + 1; j <= i__2; ++j) { if (w[j] < tmp1) { ie = j; tmp1 = w[j]; } /* L140: */ } if (ie != 0) { itmp1 = iblock[ie]; w[ie] = w[je]; iblock[ie] = iblock[je]; w[je] = tmp1; iblock[je] = itmp1; } /* L150: */ } } *info = 0; if (ncnvrg) { ++(*info); } if (toofew) { *info += 2; } return 0; /* End of DSTEBZ */ } /* igraphdstebz_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlasq5.c0000644000076500000240000002723113524616145024202 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLASQ5 computes one dqds transform in ping-pong form. Used by sbdsqr and sstegr. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLASQ5 + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLASQ5( I0, N0, Z, PP, TAU, SIGMA, DMIN, DMIN1, DMIN2, DN, DNM1, DNM2, IEEE, EPS ) LOGICAL IEEE INTEGER I0, N0, PP DOUBLE PRECISION DMIN, DMIN1, DMIN2, DN, DNM1, DNM2, TAU, SIGMA, EPS DOUBLE PRECISION Z( * ) > \par Purpose: ============= > > \verbatim > > DLASQ5 computes one dqds transform in ping-pong form, one > version for IEEE machines another for non IEEE machines. > \endverbatim Arguments: ========== > \param[in] I0 > \verbatim > I0 is INTEGER > First index. > \endverbatim > > \param[in] N0 > \verbatim > N0 is INTEGER > Last index. > \endverbatim > > \param[in] Z > \verbatim > Z is DOUBLE PRECISION array, dimension ( 4*N ) > Z holds the qd array. EMIN is stored in Z(4*N0) to avoid > an extra argument. > \endverbatim > > \param[in] PP > \verbatim > PP is INTEGER > PP=0 for ping, PP=1 for pong. > \endverbatim > > \param[in] TAU > \verbatim > TAU is DOUBLE PRECISION > This is the shift. > \endverbatim > > \param[in] SIGMA > \verbatim > SIGMA is DOUBLE PRECISION > This is the accumulated shift up to this step. > \endverbatim > > \param[out] DMIN > \verbatim > DMIN is DOUBLE PRECISION > Minimum value of d. > \endverbatim > > \param[out] DMIN1 > \verbatim > DMIN1 is DOUBLE PRECISION > Minimum value of d, excluding D( N0 ). > \endverbatim > > \param[out] DMIN2 > \verbatim > DMIN2 is DOUBLE PRECISION > Minimum value of d, excluding D( N0 ) and D( N0-1 ). > \endverbatim > > \param[out] DN > \verbatim > DN is DOUBLE PRECISION > d(N0), the last value of d. > \endverbatim > > \param[out] DNM1 > \verbatim > DNM1 is DOUBLE PRECISION > d(N0-1). > \endverbatim > > \param[out] DNM2 > \verbatim > DNM2 is DOUBLE PRECISION > d(N0-2). > \endverbatim > > \param[in] IEEE > \verbatim > IEEE is LOGICAL > Flag for IEEE or non IEEE arithmetic. > \endverbatim > \param[in] EPS > \verbatim > EPS is DOUBLE PRECISION > This is the value of epsilon used. > \endverbatim > Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERcomputational ===================================================================== Subroutine */ int igraphdlasq5_(integer *i0, integer *n0, doublereal *z__, integer *pp, doublereal *tau, doublereal *sigma, doublereal *dmin__, doublereal *dmin1, doublereal *dmin2, doublereal *dn, doublereal * dnm1, doublereal *dnm2, logical *ieee, doublereal *eps) { /* System generated locals */ integer i__1; doublereal d__1, d__2; /* Local variables */ doublereal d__; integer j4, j4p2; doublereal emin, temp, dthresh; /* -- LAPACK computational routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ --z__; /* Function Body */ if (*n0 - *i0 - 1 <= 0) { return 0; } dthresh = *eps * (*sigma + *tau); if (*tau < dthresh * .5) { *tau = 0.; } if (*tau != 0.) { j4 = (*i0 << 2) + *pp - 3; emin = z__[j4 + 4]; d__ = z__[j4] - *tau; *dmin__ = d__; *dmin1 = -z__[j4]; if (*ieee) { /* Code for IEEE arithmetic. */ if (*pp == 0) { i__1 = *n0 - 3 << 2; for (j4 = *i0 << 2; j4 <= i__1; j4 += 4) { z__[j4 - 2] = d__ + z__[j4 - 1]; temp = z__[j4 + 1] / z__[j4 - 2]; d__ = d__ * temp - *tau; *dmin__ = min(*dmin__,d__); z__[j4] = z__[j4 - 1] * temp; /* Computing MIN */ d__1 = z__[j4]; emin = min(d__1,emin); /* L10: */ } } else { i__1 = *n0 - 3 << 2; for (j4 = *i0 << 2; j4 <= i__1; j4 += 4) { z__[j4 - 3] = d__ + z__[j4]; temp = z__[j4 + 2] / z__[j4 - 3]; d__ = d__ * temp - *tau; *dmin__ = min(*dmin__,d__); z__[j4 - 1] = z__[j4] * temp; /* Computing MIN */ d__1 = z__[j4 - 1]; emin = min(d__1,emin); /* L20: */ } } /* Unroll last two steps. */ *dnm2 = d__; *dmin2 = *dmin__; j4 = (*n0 - 2 << 2) - *pp; j4p2 = j4 + (*pp << 1) - 1; z__[j4 - 2] = *dnm2 + z__[j4p2]; z__[j4] = z__[j4p2 + 2] * (z__[j4p2] / z__[j4 - 2]); *dnm1 = z__[j4p2 + 2] * (*dnm2 / z__[j4 - 2]) - *tau; *dmin__ = min(*dmin__,*dnm1); *dmin1 = *dmin__; j4 += 4; j4p2 = j4 + (*pp << 1) - 1; z__[j4 - 2] = *dnm1 + z__[j4p2]; z__[j4] = z__[j4p2 + 2] * (z__[j4p2] / z__[j4 - 2]); *dn = z__[j4p2 + 2] * (*dnm1 / z__[j4 - 2]) - *tau; *dmin__ = min(*dmin__,*dn); } else { /* Code for non IEEE arithmetic. */ if (*pp == 0) { i__1 = *n0 - 3 << 2; for (j4 = *i0 << 2; j4 <= i__1; j4 += 4) { z__[j4 - 2] = d__ + z__[j4 - 1]; if (d__ < 0.) { return 0; } else { z__[j4] = z__[j4 + 1] * (z__[j4 - 1] / z__[j4 - 2]); d__ = z__[j4 + 1] * (d__ / z__[j4 - 2]) - *tau; } *dmin__ = min(*dmin__,d__); /* Computing MIN */ d__1 = emin, d__2 = z__[j4]; emin = min(d__1,d__2); /* L30: */ } } else { i__1 = *n0 - 3 << 2; for (j4 = *i0 << 2; j4 <= i__1; j4 += 4) { z__[j4 - 3] = d__ + z__[j4]; if (d__ < 0.) { return 0; } else { z__[j4 - 1] = z__[j4 + 2] * (z__[j4] / z__[j4 - 3]); d__ = z__[j4 + 2] * (d__ / z__[j4 - 3]) - *tau; } *dmin__ = min(*dmin__,d__); /* Computing MIN */ d__1 = emin, d__2 = z__[j4 - 1]; emin = min(d__1,d__2); /* L40: */ } } /* Unroll last two steps. */ *dnm2 = d__; *dmin2 = *dmin__; j4 = (*n0 - 2 << 2) - *pp; j4p2 = j4 + (*pp << 1) - 1; z__[j4 - 2] = *dnm2 + z__[j4p2]; if (*dnm2 < 0.) { return 0; } else { z__[j4] = z__[j4p2 + 2] * (z__[j4p2] / z__[j4 - 2]); *dnm1 = z__[j4p2 + 2] * (*dnm2 / z__[j4 - 2]) - *tau; } *dmin__ = min(*dmin__,*dnm1); *dmin1 = *dmin__; j4 += 4; j4p2 = j4 + (*pp << 1) - 1; z__[j4 - 2] = *dnm1 + z__[j4p2]; if (*dnm1 < 0.) { return 0; } else { z__[j4] = z__[j4p2 + 2] * (z__[j4p2] / z__[j4 - 2]); *dn = z__[j4p2 + 2] * (*dnm1 / z__[j4 - 2]) - *tau; } *dmin__ = min(*dmin__,*dn); } } else { /* This is the version that sets d's to zero if they are small enough */ j4 = (*i0 << 2) + *pp - 3; emin = z__[j4 + 4]; d__ = z__[j4] - *tau; *dmin__ = d__; *dmin1 = -z__[j4]; if (*ieee) { /* Code for IEEE arithmetic. */ if (*pp == 0) { i__1 = *n0 - 3 << 2; for (j4 = *i0 << 2; j4 <= i__1; j4 += 4) { z__[j4 - 2] = d__ + z__[j4 - 1]; temp = z__[j4 + 1] / z__[j4 - 2]; d__ = d__ * temp - *tau; if (d__ < dthresh) { d__ = 0.; } *dmin__ = min(*dmin__,d__); z__[j4] = z__[j4 - 1] * temp; /* Computing MIN */ d__1 = z__[j4]; emin = min(d__1,emin); /* L50: */ } } else { i__1 = *n0 - 3 << 2; for (j4 = *i0 << 2; j4 <= i__1; j4 += 4) { z__[j4 - 3] = d__ + z__[j4]; temp = z__[j4 + 2] / z__[j4 - 3]; d__ = d__ * temp - *tau; if (d__ < dthresh) { d__ = 0.; } *dmin__ = min(*dmin__,d__); z__[j4 - 1] = z__[j4] * temp; /* Computing MIN */ d__1 = z__[j4 - 1]; emin = min(d__1,emin); /* L60: */ } } /* Unroll last two steps. */ *dnm2 = d__; *dmin2 = *dmin__; j4 = (*n0 - 2 << 2) - *pp; j4p2 = j4 + (*pp << 1) - 1; z__[j4 - 2] = *dnm2 + z__[j4p2]; z__[j4] = z__[j4p2 + 2] * (z__[j4p2] / z__[j4 - 2]); *dnm1 = z__[j4p2 + 2] * (*dnm2 / z__[j4 - 2]) - *tau; *dmin__ = min(*dmin__,*dnm1); *dmin1 = *dmin__; j4 += 4; j4p2 = j4 + (*pp << 1) - 1; z__[j4 - 2] = *dnm1 + z__[j4p2]; z__[j4] = z__[j4p2 + 2] * (z__[j4p2] / z__[j4 - 2]); *dn = z__[j4p2 + 2] * (*dnm1 / z__[j4 - 2]) - *tau; *dmin__ = min(*dmin__,*dn); } else { /* Code for non IEEE arithmetic. */ if (*pp == 0) { i__1 = *n0 - 3 << 2; for (j4 = *i0 << 2; j4 <= i__1; j4 += 4) { z__[j4 - 2] = d__ + z__[j4 - 1]; if (d__ < 0.) { return 0; } else { z__[j4] = z__[j4 + 1] * (z__[j4 - 1] / z__[j4 - 2]); d__ = z__[j4 + 1] * (d__ / z__[j4 - 2]) - *tau; } if (d__ < dthresh) { d__ = 0.; } *dmin__ = min(*dmin__,d__); /* Computing MIN */ d__1 = emin, d__2 = z__[j4]; emin = min(d__1,d__2); /* L70: */ } } else { i__1 = *n0 - 3 << 2; for (j4 = *i0 << 2; j4 <= i__1; j4 += 4) { z__[j4 - 3] = d__ + z__[j4]; if (d__ < 0.) { return 0; } else { z__[j4 - 1] = z__[j4 + 2] * (z__[j4] / z__[j4 - 3]); d__ = z__[j4 + 2] * (d__ / z__[j4 - 3]) - *tau; } if (d__ < dthresh) { d__ = 0.; } *dmin__ = min(*dmin__,d__); /* Computing MIN */ d__1 = emin, d__2 = z__[j4 - 1]; emin = min(d__1,d__2); /* L80: */ } } /* Unroll last two steps. */ *dnm2 = d__; *dmin2 = *dmin__; j4 = (*n0 - 2 << 2) - *pp; j4p2 = j4 + (*pp << 1) - 1; z__[j4 - 2] = *dnm2 + z__[j4p2]; if (*dnm2 < 0.) { return 0; } else { z__[j4] = z__[j4p2 + 2] * (z__[j4p2] / z__[j4 - 2]); *dnm1 = z__[j4p2 + 2] * (*dnm2 / z__[j4 - 2]) - *tau; } *dmin__ = min(*dmin__,*dnm1); *dmin1 = *dmin__; j4 += 4; j4p2 = j4 + (*pp << 1) - 1; z__[j4 - 2] = *dnm1 + z__[j4p2]; if (*dnm1 < 0.) { return 0; } else { z__[j4] = z__[j4p2 + 2] * (z__[j4p2] / z__[j4 - 2]); *dn = z__[j4p2 + 2] * (*dnm1 / z__[j4 - 2]) - *tau; } *dmin__ = min(*dmin__,*dn); } } z__[j4 + 2] = *dn; z__[(*n0 << 2) - *pp] = emin; return 0; /* End of DLASQ5 */ } /* igraphdlasq5_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/ivout.c0000644000076500000240000001676213524616145024166 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; /* ----------------------------------------------------------------------- Routine: IVOUT Purpose: Integer vector output routine. Usage: CALL IVOUT (LOUT, N, IX, IDIGIT, IFMT) Arguments N - Length of array IX. (Input) IX - Integer array to be printed. (Input) IFMT - Format to be used in printing array IX. (Input) IDIGIT - Print up to ABS(IDIGIT) decimal digits / number. (Input) If IDIGIT .LT. 0, printing is done with 72 columns. If IDIGIT .GT. 0, printing is done with 132 columns. ----------------------------------------------------------------------- Subroutine */ int igraphivout_(integer *lout, integer *n, integer *ix, integer * idigit, char *ifmt, ftnlen ifmt_len) { /* Format strings */ static char fmt_2000[] = "(/1x,a/1x,a)"; static char fmt_1000[] = "(1x,i4,\002 - \002,i4,\002:\002,20(1x,i5))"; static char fmt_1001[] = "(1x,i4,\002 - \002,i4,\002:\002,15(1x,i7))"; static char fmt_1002[] = "(1x,i4,\002 - \002,i4,\002:\002,10(1x,i11))"; static char fmt_1003[] = "(1x,i4,\002 - \002,i4,\002:\002,7(1x,i15))"; static char fmt_1004[] = "(1x,\002 \002)"; /* System generated locals */ integer i__1, i__2, i__3; /* Builtin functions */ integer i_len(char *, ftnlen), s_wsfe(cilist *), do_fio(integer *, char *, ftnlen), e_wsfe(void); /* Local variables */ integer i__, k1, k2, lll; char line[80]; integer ndigit; /* Fortran I/O blocks */ static cilist io___4 = { 0, 0, 0, fmt_2000, 0 }; static cilist io___8 = { 0, 0, 0, fmt_1000, 0 }; static cilist io___9 = { 0, 0, 0, fmt_1001, 0 }; static cilist io___10 = { 0, 0, 0, fmt_1002, 0 }; static cilist io___11 = { 0, 0, 0, fmt_1003, 0 }; static cilist io___12 = { 0, 0, 0, fmt_1000, 0 }; static cilist io___13 = { 0, 0, 0, fmt_1001, 0 }; static cilist io___14 = { 0, 0, 0, fmt_1002, 0 }; static cilist io___15 = { 0, 0, 0, fmt_1003, 0 }; static cilist io___16 = { 0, 0, 0, fmt_1004, 0 }; /* ... ... SPECIFICATIONS FOR ARGUMENTS ... ... SPECIFICATIONS FOR LOCAL VARIABLES ... ... SPECIFICATIONS INTRINSICS Parameter adjustments */ --ix; /* Function Body Computing MIN */ i__1 = i_len(ifmt, ifmt_len); lll = min(i__1,80); i__1 = lll; for (i__ = 1; i__ <= i__1; ++i__) { *(unsigned char *)&line[i__ - 1] = '-'; /* L1: */ } for (i__ = lll + 1; i__ <= 80; ++i__) { *(unsigned char *)&line[i__ - 1] = ' '; /* L2: */ } io___4.ciunit = *lout; s_wsfe(&io___4); do_fio(&c__1, ifmt, ifmt_len); do_fio(&c__1, line, lll); e_wsfe(); if (*n <= 0) { return 0; } ndigit = *idigit; if (*idigit == 0) { ndigit = 4; } /* ======================================================================= CODE FOR OUTPUT USING 72 COLUMNS FORMAT ======================================================================= */ if (*idigit < 0) { ndigit = -(*idigit); if (ndigit <= 4) { i__1 = *n; for (k1 = 1; k1 <= i__1; k1 += 10) { /* Computing MIN */ i__2 = *n, i__3 = k1 + 9; k2 = min(i__2,i__3); io___8.ciunit = *lout; s_wsfe(&io___8); do_fio(&c__1, (char *)&k1, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&k2, (ftnlen)sizeof(integer)); i__2 = k2; for (i__ = k1; i__ <= i__2; ++i__) { do_fio(&c__1, (char *)&ix[i__], (ftnlen)sizeof(integer)); } e_wsfe(); /* L10: */ } } else if (ndigit <= 6) { i__1 = *n; for (k1 = 1; k1 <= i__1; k1 += 7) { /* Computing MIN */ i__2 = *n, i__3 = k1 + 6; k2 = min(i__2,i__3); io___9.ciunit = *lout; s_wsfe(&io___9); do_fio(&c__1, (char *)&k1, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&k2, (ftnlen)sizeof(integer)); i__2 = k2; for (i__ = k1; i__ <= i__2; ++i__) { do_fio(&c__1, (char *)&ix[i__], (ftnlen)sizeof(integer)); } e_wsfe(); /* L30: */ } } else if (ndigit <= 10) { i__1 = *n; for (k1 = 1; k1 <= i__1; k1 += 5) { /* Computing MIN */ i__2 = *n, i__3 = k1 + 4; k2 = min(i__2,i__3); io___10.ciunit = *lout; s_wsfe(&io___10); do_fio(&c__1, (char *)&k1, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&k2, (ftnlen)sizeof(integer)); i__2 = k2; for (i__ = k1; i__ <= i__2; ++i__) { do_fio(&c__1, (char *)&ix[i__], (ftnlen)sizeof(integer)); } e_wsfe(); /* L50: */ } } else { i__1 = *n; for (k1 = 1; k1 <= i__1; k1 += 3) { /* Computing MIN */ i__2 = *n, i__3 = k1 + 2; k2 = min(i__2,i__3); io___11.ciunit = *lout; s_wsfe(&io___11); do_fio(&c__1, (char *)&k1, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&k2, (ftnlen)sizeof(integer)); i__2 = k2; for (i__ = k1; i__ <= i__2; ++i__) { do_fio(&c__1, (char *)&ix[i__], (ftnlen)sizeof(integer)); } e_wsfe(); /* L70: */ } } /* ======================================================================= CODE FOR OUTPUT USING 132 COLUMNS FORMAT ======================================================================= */ } else { if (ndigit <= 4) { i__1 = *n; for (k1 = 1; k1 <= i__1; k1 += 20) { /* Computing MIN */ i__2 = *n, i__3 = k1 + 19; k2 = min(i__2,i__3); io___12.ciunit = *lout; s_wsfe(&io___12); do_fio(&c__1, (char *)&k1, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&k2, (ftnlen)sizeof(integer)); i__2 = k2; for (i__ = k1; i__ <= i__2; ++i__) { do_fio(&c__1, (char *)&ix[i__], (ftnlen)sizeof(integer)); } e_wsfe(); /* L90: */ } } else if (ndigit <= 6) { i__1 = *n; for (k1 = 1; k1 <= i__1; k1 += 15) { /* Computing MIN */ i__2 = *n, i__3 = k1 + 14; k2 = min(i__2,i__3); io___13.ciunit = *lout; s_wsfe(&io___13); do_fio(&c__1, (char *)&k1, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&k2, (ftnlen)sizeof(integer)); i__2 = k2; for (i__ = k1; i__ <= i__2; ++i__) { do_fio(&c__1, (char *)&ix[i__], (ftnlen)sizeof(integer)); } e_wsfe(); /* L110: */ } } else if (ndigit <= 10) { i__1 = *n; for (k1 = 1; k1 <= i__1; k1 += 10) { /* Computing MIN */ i__2 = *n, i__3 = k1 + 9; k2 = min(i__2,i__3); io___14.ciunit = *lout; s_wsfe(&io___14); do_fio(&c__1, (char *)&k1, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&k2, (ftnlen)sizeof(integer)); i__2 = k2; for (i__ = k1; i__ <= i__2; ++i__) { do_fio(&c__1, (char *)&ix[i__], (ftnlen)sizeof(integer)); } e_wsfe(); /* L130: */ } } else { i__1 = *n; for (k1 = 1; k1 <= i__1; k1 += 7) { /* Computing MIN */ i__2 = *n, i__3 = k1 + 6; k2 = min(i__2,i__3); io___15.ciunit = *lout; s_wsfe(&io___15); do_fio(&c__1, (char *)&k1, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&k2, (ftnlen)sizeof(integer)); i__2 = k2; for (i__ = k1; i__ <= i__2; ++i__) { do_fio(&c__1, (char *)&ix[i__], (ftnlen)sizeof(integer)); } e_wsfe(); /* L150: */ } } } io___16.ciunit = *lout; s_wsfe(&io___16); e_wsfe(); return 0; } /* igraphivout_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlaexc.c0000644000076500000240000003573713524616145024263 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static integer c__4 = 4; static logical c_false = FALSE_; static integer c_n1 = -1; static integer c__2 = 2; static integer c__3 = 3; /* > \brief \b DLAEXC swaps adjacent diagonal blocks of a real upper quasi-triangular matrix in Schur canonica l form, by an orthogonal similarity transformation. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLAEXC + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLAEXC( WANTQ, N, T, LDT, Q, LDQ, J1, N1, N2, WORK, INFO ) LOGICAL WANTQ INTEGER INFO, J1, LDQ, LDT, N, N1, N2 DOUBLE PRECISION Q( LDQ, * ), T( LDT, * ), WORK( * ) > \par Purpose: ============= > > \verbatim > > DLAEXC swaps adjacent diagonal blocks T11 and T22 of order 1 or 2 in > an upper quasi-triangular matrix T by an orthogonal similarity > transformation. > > T must be in Schur canonical form, that is, block upper triangular > with 1-by-1 and 2-by-2 diagonal blocks; each 2-by-2 diagonal block > has its diagonal elemnts equal and its off-diagonal elements of > opposite sign. > \endverbatim Arguments: ========== > \param[in] WANTQ > \verbatim > WANTQ is LOGICAL > = .TRUE. : accumulate the transformation in the matrix Q; > = .FALSE.: do not accumulate the transformation. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix T. N >= 0. > \endverbatim > > \param[in,out] T > \verbatim > T is DOUBLE PRECISION array, dimension (LDT,N) > On entry, the upper quasi-triangular matrix T, in Schur > canonical form. > On exit, the updated matrix T, again in Schur canonical form. > \endverbatim > > \param[in] LDT > \verbatim > LDT is INTEGER > The leading dimension of the array T. LDT >= max(1,N). > \endverbatim > > \param[in,out] Q > \verbatim > Q is DOUBLE PRECISION array, dimension (LDQ,N) > On entry, if WANTQ is .TRUE., the orthogonal matrix Q. > On exit, if WANTQ is .TRUE., the updated matrix Q. > If WANTQ is .FALSE., Q is not referenced. > \endverbatim > > \param[in] LDQ > \verbatim > LDQ is INTEGER > The leading dimension of the array Q. > LDQ >= 1; and if WANTQ is .TRUE., LDQ >= N. > \endverbatim > > \param[in] J1 > \verbatim > J1 is INTEGER > The index of the first row of the first block T11. > \endverbatim > > \param[in] N1 > \verbatim > N1 is INTEGER > The order of the first block T11. N1 = 0, 1 or 2. > \endverbatim > > \param[in] N2 > \verbatim > N2 is INTEGER > The order of the second block T22. N2 = 0, 1 or 2. > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (N) > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > = 1: the transformed matrix T would be too far from Schur > form; the blocks are not swapped and T and Q are > unchanged. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleOTHERauxiliary ===================================================================== Subroutine */ int igraphdlaexc_(logical *wantq, integer *n, doublereal *t, integer *ldt, doublereal *q, integer *ldq, integer *j1, integer *n1, integer *n2, doublereal *work, integer *info) { /* System generated locals */ integer q_dim1, q_offset, t_dim1, t_offset, i__1; doublereal d__1, d__2, d__3; /* Local variables */ doublereal d__[16] /* was [4][4] */; integer k; doublereal u[3], x[4] /* was [2][2] */; integer j2, j3, j4; doublereal u1[3], u2[3]; integer nd; doublereal cs, t11, t22, t33, sn, wi1, wi2, wr1, wr2, eps, tau, tau1, tau2; integer ierr; doublereal temp; extern /* Subroutine */ int igraphdrot_(integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *); doublereal scale, dnorm, xnorm; extern /* Subroutine */ int igraphdlanv2_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *), igraphdlasy2_( logical *, logical *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *); extern doublereal igraphdlamch_(char *), igraphdlange_(char *, integer *, integer *, doublereal *, integer *, doublereal *); extern /* Subroutine */ int igraphdlarfg_(integer *, doublereal *, doublereal *, integer *, doublereal *), igraphdlacpy_(char *, integer *, integer *, doublereal *, integer *, doublereal *, integer *), igraphdlartg_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *), igraphdlarfx_(char *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *, doublereal *); doublereal thresh, smlnum; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ t_dim1 = *ldt; t_offset = 1 + t_dim1; t -= t_offset; q_dim1 = *ldq; q_offset = 1 + q_dim1; q -= q_offset; --work; /* Function Body */ *info = 0; /* Quick return if possible */ if (*n == 0 || *n1 == 0 || *n2 == 0) { return 0; } if (*j1 + *n1 > *n) { return 0; } j2 = *j1 + 1; j3 = *j1 + 2; j4 = *j1 + 3; if (*n1 == 1 && *n2 == 1) { /* Swap two 1-by-1 blocks. */ t11 = t[*j1 + *j1 * t_dim1]; t22 = t[j2 + j2 * t_dim1]; /* Determine the transformation to perform the interchange. */ d__1 = t22 - t11; igraphdlartg_(&t[*j1 + j2 * t_dim1], &d__1, &cs, &sn, &temp); /* Apply transformation to the matrix T. */ if (j3 <= *n) { i__1 = *n - *j1 - 1; igraphdrot_(&i__1, &t[*j1 + j3 * t_dim1], ldt, &t[j2 + j3 * t_dim1], ldt, &cs, &sn); } i__1 = *j1 - 1; igraphdrot_(&i__1, &t[*j1 * t_dim1 + 1], &c__1, &t[j2 * t_dim1 + 1], &c__1, &cs, &sn); t[*j1 + *j1 * t_dim1] = t22; t[j2 + j2 * t_dim1] = t11; if (*wantq) { /* Accumulate transformation in the matrix Q. */ igraphdrot_(n, &q[*j1 * q_dim1 + 1], &c__1, &q[j2 * q_dim1 + 1], &c__1, &cs, &sn); } } else { /* Swapping involves at least one 2-by-2 block. Copy the diagonal block of order N1+N2 to the local array D and compute its norm. */ nd = *n1 + *n2; igraphdlacpy_("Full", &nd, &nd, &t[*j1 + *j1 * t_dim1], ldt, d__, &c__4); dnorm = igraphdlange_("Max", &nd, &nd, d__, &c__4, &work[1]); /* Compute machine-dependent threshold for test for accepting swap. */ eps = igraphdlamch_("P"); smlnum = igraphdlamch_("S") / eps; /* Computing MAX */ d__1 = eps * 10. * dnorm; thresh = max(d__1,smlnum); /* Solve T11*X - X*T22 = scale*T12 for X. */ igraphdlasy2_(&c_false, &c_false, &c_n1, n1, n2, d__, &c__4, &d__[*n1 + 1 + (*n1 + 1 << 2) - 5], &c__4, &d__[(*n1 + 1 << 2) - 4], &c__4, & scale, x, &c__2, &xnorm, &ierr); /* Swap the adjacent diagonal blocks. */ k = *n1 + *n1 + *n2 - 3; switch (k) { case 1: goto L10; case 2: goto L20; case 3: goto L30; } L10: /* N1 = 1, N2 = 2: generate elementary reflector H so that: ( scale, X11, X12 ) H = ( 0, 0, * ) */ u[0] = scale; u[1] = x[0]; u[2] = x[2]; igraphdlarfg_(&c__3, &u[2], u, &c__1, &tau); u[2] = 1.; t11 = t[*j1 + *j1 * t_dim1]; /* Perform swap provisionally on diagonal block in D. */ igraphdlarfx_("L", &c__3, &c__3, u, &tau, d__, &c__4, &work[1]); igraphdlarfx_("R", &c__3, &c__3, u, &tau, d__, &c__4, &work[1]); /* Test whether to reject swap. Computing MAX */ d__2 = abs(d__[2]), d__3 = abs(d__[6]), d__2 = max(d__2,d__3), d__3 = (d__1 = d__[10] - t11, abs(d__1)); if (max(d__2,d__3) > thresh) { goto L50; } /* Accept swap: apply transformation to the entire matrix T. */ i__1 = *n - *j1 + 1; igraphdlarfx_("L", &c__3, &i__1, u, &tau, &t[*j1 + *j1 * t_dim1], ldt, & work[1]); igraphdlarfx_("R", &j2, &c__3, u, &tau, &t[*j1 * t_dim1 + 1], ldt, &work[1]); t[j3 + *j1 * t_dim1] = 0.; t[j3 + j2 * t_dim1] = 0.; t[j3 + j3 * t_dim1] = t11; if (*wantq) { /* Accumulate transformation in the matrix Q. */ igraphdlarfx_("R", n, &c__3, u, &tau, &q[*j1 * q_dim1 + 1], ldq, &work[ 1]); } goto L40; L20: /* N1 = 2, N2 = 1: generate elementary reflector H so that: H ( -X11 ) = ( * ) ( -X21 ) = ( 0 ) ( scale ) = ( 0 ) */ u[0] = -x[0]; u[1] = -x[1]; u[2] = scale; igraphdlarfg_(&c__3, u, &u[1], &c__1, &tau); u[0] = 1.; t33 = t[j3 + j3 * t_dim1]; /* Perform swap provisionally on diagonal block in D. */ igraphdlarfx_("L", &c__3, &c__3, u, &tau, d__, &c__4, &work[1]); igraphdlarfx_("R", &c__3, &c__3, u, &tau, d__, &c__4, &work[1]); /* Test whether to reject swap. Computing MAX */ d__2 = abs(d__[1]), d__3 = abs(d__[2]), d__2 = max(d__2,d__3), d__3 = (d__1 = d__[0] - t33, abs(d__1)); if (max(d__2,d__3) > thresh) { goto L50; } /* Accept swap: apply transformation to the entire matrix T. */ igraphdlarfx_("R", &j3, &c__3, u, &tau, &t[*j1 * t_dim1 + 1], ldt, &work[1]); i__1 = *n - *j1; igraphdlarfx_("L", &c__3, &i__1, u, &tau, &t[*j1 + j2 * t_dim1], ldt, &work[ 1]); t[*j1 + *j1 * t_dim1] = t33; t[j2 + *j1 * t_dim1] = 0.; t[j3 + *j1 * t_dim1] = 0.; if (*wantq) { /* Accumulate transformation in the matrix Q. */ igraphdlarfx_("R", n, &c__3, u, &tau, &q[*j1 * q_dim1 + 1], ldq, &work[ 1]); } goto L40; L30: /* N1 = 2, N2 = 2: generate elementary reflectors H(1) and H(2) so that: H(2) H(1) ( -X11 -X12 ) = ( * * ) ( -X21 -X22 ) ( 0 * ) ( scale 0 ) ( 0 0 ) ( 0 scale ) ( 0 0 ) */ u1[0] = -x[0]; u1[1] = -x[1]; u1[2] = scale; igraphdlarfg_(&c__3, u1, &u1[1], &c__1, &tau1); u1[0] = 1.; temp = -tau1 * (x[2] + u1[1] * x[3]); u2[0] = -temp * u1[1] - x[3]; u2[1] = -temp * u1[2]; u2[2] = scale; igraphdlarfg_(&c__3, u2, &u2[1], &c__1, &tau2); u2[0] = 1.; /* Perform swap provisionally on diagonal block in D. */ igraphdlarfx_("L", &c__3, &c__4, u1, &tau1, d__, &c__4, &work[1]) ; igraphdlarfx_("R", &c__4, &c__3, u1, &tau1, d__, &c__4, &work[1]) ; igraphdlarfx_("L", &c__3, &c__4, u2, &tau2, &d__[1], &c__4, &work[1]); igraphdlarfx_("R", &c__4, &c__3, u2, &tau2, &d__[4], &c__4, &work[1]); /* Test whether to reject swap. Computing MAX */ d__1 = abs(d__[2]), d__2 = abs(d__[6]), d__1 = max(d__1,d__2), d__2 = abs(d__[3]), d__1 = max(d__1,d__2), d__2 = abs(d__[7]); if (max(d__1,d__2) > thresh) { goto L50; } /* Accept swap: apply transformation to the entire matrix T. */ i__1 = *n - *j1 + 1; igraphdlarfx_("L", &c__3, &i__1, u1, &tau1, &t[*j1 + *j1 * t_dim1], ldt, & work[1]); igraphdlarfx_("R", &j4, &c__3, u1, &tau1, &t[*j1 * t_dim1 + 1], ldt, &work[ 1]); i__1 = *n - *j1 + 1; igraphdlarfx_("L", &c__3, &i__1, u2, &tau2, &t[j2 + *j1 * t_dim1], ldt, & work[1]); igraphdlarfx_("R", &j4, &c__3, u2, &tau2, &t[j2 * t_dim1 + 1], ldt, &work[1] ); t[j3 + *j1 * t_dim1] = 0.; t[j3 + j2 * t_dim1] = 0.; t[j4 + *j1 * t_dim1] = 0.; t[j4 + j2 * t_dim1] = 0.; if (*wantq) { /* Accumulate transformation in the matrix Q. */ igraphdlarfx_("R", n, &c__3, u1, &tau1, &q[*j1 * q_dim1 + 1], ldq, & work[1]); igraphdlarfx_("R", n, &c__3, u2, &tau2, &q[j2 * q_dim1 + 1], ldq, &work[ 1]); } L40: if (*n2 == 2) { /* Standardize new 2-by-2 block T11 */ igraphdlanv2_(&t[*j1 + *j1 * t_dim1], &t[*j1 + j2 * t_dim1], &t[j2 + * j1 * t_dim1], &t[j2 + j2 * t_dim1], &wr1, &wi1, &wr2, & wi2, &cs, &sn); i__1 = *n - *j1 - 1; igraphdrot_(&i__1, &t[*j1 + (*j1 + 2) * t_dim1], ldt, &t[j2 + (*j1 + 2) * t_dim1], ldt, &cs, &sn); i__1 = *j1 - 1; igraphdrot_(&i__1, &t[*j1 * t_dim1 + 1], &c__1, &t[j2 * t_dim1 + 1], & c__1, &cs, &sn); if (*wantq) { igraphdrot_(n, &q[*j1 * q_dim1 + 1], &c__1, &q[j2 * q_dim1 + 1], & c__1, &cs, &sn); } } if (*n1 == 2) { /* Standardize new 2-by-2 block T22 */ j3 = *j1 + *n2; j4 = j3 + 1; igraphdlanv2_(&t[j3 + j3 * t_dim1], &t[j3 + j4 * t_dim1], &t[j4 + j3 * t_dim1], &t[j4 + j4 * t_dim1], &wr1, &wi1, &wr2, &wi2, & cs, &sn); if (j3 + 2 <= *n) { i__1 = *n - j3 - 1; igraphdrot_(&i__1, &t[j3 + (j3 + 2) * t_dim1], ldt, &t[j4 + (j3 + 2) * t_dim1], ldt, &cs, &sn); } i__1 = j3 - 1; igraphdrot_(&i__1, &t[j3 * t_dim1 + 1], &c__1, &t[j4 * t_dim1 + 1], & c__1, &cs, &sn); if (*wantq) { igraphdrot_(n, &q[j3 * q_dim1 + 1], &c__1, &q[j4 * q_dim1 + 1], & c__1, &cs, &sn); } } } return 0; /* Exit with INFO = 1 if swap was rejected. */ L50: *info = 1; return 0; /* End of DLAEXC */ } /* igraphdlaexc_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dsortr.c0000644000076500000240000001276013524616145024327 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* ----------------------------------------------------------------------- \BeginDoc \Name: dsortr \Description: Sort the array X1 in the order specified by WHICH and optionally applies the permutation to the array X2. \Usage: call dsortr ( WHICH, APPLY, N, X1, X2 ) \Arguments WHICH Character*2. (Input) 'LM' -> X1 is sorted into increasing order of magnitude. 'SM' -> X1 is sorted into decreasing order of magnitude. 'LA' -> X1 is sorted into increasing order of algebraic. 'SA' -> X1 is sorted into decreasing order of algebraic. APPLY Logical. (Input) APPLY = .TRUE. -> apply the sorted order to X2. APPLY = .FALSE. -> do not apply the sorted order to X2. N Integer. (INPUT) Size of the arrays. X1 Double precision array of length N. (INPUT/OUTPUT) The array to be sorted. X2 Double precision array of length N. (INPUT/OUTPUT) Only referenced if APPLY = .TRUE. \EndDoc ----------------------------------------------------------------------- \BeginLib \Author Danny Sorensen Phuong Vu Richard Lehoucq CRPC / Rice University Dept. of Computational & Houston, Texas Applied Mathematics Rice University Houston, Texas \Revision history: 12/16/93: Version ' 2.1'. Adapted from the sort routine in LANSO. \SCCS Information: @(#) FILE: sortr.F SID: 2.3 DATE OF SID: 4/19/96 RELEASE: 2 \EndLib ----------------------------------------------------------------------- Subroutine */ int igraphdsortr_(char *which, logical *apply, integer *n, doublereal *x1, doublereal *x2) { /* System generated locals */ integer i__1; doublereal d__1, d__2; /* Builtin functions */ integer s_cmp(char *, char *, ftnlen, ftnlen); /* Local variables */ integer i__, j, igap; doublereal temp; /* %------------------% | Scalar Arguments | %------------------% %-----------------% | Array Arguments | %-----------------% %---------------% | Local Scalars | %---------------% %-----------------------% | Executable Statements | %-----------------------% */ igap = *n / 2; if (s_cmp(which, "SA", (ftnlen)2, (ftnlen)2) == 0) { /* X1 is sorted into decreasing order of algebraic. */ L10: if (igap == 0) { goto L9000; } i__1 = *n - 1; for (i__ = igap; i__ <= i__1; ++i__) { j = i__ - igap; L20: if (j < 0) { goto L30; } if (x1[j] < x1[j + igap]) { temp = x1[j]; x1[j] = x1[j + igap]; x1[j + igap] = temp; if (*apply) { temp = x2[j]; x2[j] = x2[j + igap]; x2[j + igap] = temp; } } else { goto L30; } j -= igap; goto L20; L30: ; } igap /= 2; goto L10; } else if (s_cmp(which, "SM", (ftnlen)2, (ftnlen)2) == 0) { /* X1 is sorted into decreasing order of magnitude. */ L40: if (igap == 0) { goto L9000; } i__1 = *n - 1; for (i__ = igap; i__ <= i__1; ++i__) { j = i__ - igap; L50: if (j < 0) { goto L60; } if ((d__1 = x1[j], abs(d__1)) < (d__2 = x1[j + igap], abs(d__2))) { temp = x1[j]; x1[j] = x1[j + igap]; x1[j + igap] = temp; if (*apply) { temp = x2[j]; x2[j] = x2[j + igap]; x2[j + igap] = temp; } } else { goto L60; } j -= igap; goto L50; L60: ; } igap /= 2; goto L40; } else if (s_cmp(which, "LA", (ftnlen)2, (ftnlen)2) == 0) { /* X1 is sorted into increasing order of algebraic. */ L70: if (igap == 0) { goto L9000; } i__1 = *n - 1; for (i__ = igap; i__ <= i__1; ++i__) { j = i__ - igap; L80: if (j < 0) { goto L90; } if (x1[j] > x1[j + igap]) { temp = x1[j]; x1[j] = x1[j + igap]; x1[j + igap] = temp; if (*apply) { temp = x2[j]; x2[j] = x2[j + igap]; x2[j + igap] = temp; } } else { goto L90; } j -= igap; goto L80; L90: ; } igap /= 2; goto L70; } else if (s_cmp(which, "LM", (ftnlen)2, (ftnlen)2) == 0) { /* X1 is sorted into increasing order of magnitude. */ L100: if (igap == 0) { goto L9000; } i__1 = *n - 1; for (i__ = igap; i__ <= i__1; ++i__) { j = i__ - igap; L110: if (j < 0) { goto L120; } if ((d__1 = x1[j], abs(d__1)) > (d__2 = x1[j + igap], abs(d__2))) { temp = x1[j]; x1[j] = x1[j + igap]; x1[j + igap] = temp; if (*apply) { temp = x2[j]; x2[j] = x2[j + igap]; x2[j + igap] = temp; } } else { goto L120; } j -= igap; goto L110; L120: ; } igap /= 2; goto L100; } L9000: return 0; /* %---------------% | End of dsortr | %---------------% */ } /* igraphdsortr_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dgetf2.c0000644000076500000240000001555413524616145024171 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static doublereal c_b8 = -1.; /* > \brief \b DGETF2 computes the LU factorization of a general m-by-n matrix using partial pivoting with row interchanges (unblocked algorithm). =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DGETF2 + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DGETF2( M, N, A, LDA, IPIV, INFO ) INTEGER INFO, LDA, M, N INTEGER IPIV( * ) DOUBLE PRECISION A( LDA, * ) > \par Purpose: ============= > > \verbatim > > DGETF2 computes an LU factorization of a general m-by-n matrix A > using partial pivoting with row interchanges. > > The factorization has the form > A = P * L * U > where P is a permutation matrix, L is lower triangular with unit > diagonal elements (lower trapezoidal if m > n), and U is upper > triangular (upper trapezoidal if m < n). > > This is the right-looking Level 2 BLAS version of the algorithm. > \endverbatim Arguments: ========== > \param[in] M > \verbatim > M is INTEGER > The number of rows of the matrix A. M >= 0. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The number of columns of the matrix A. N >= 0. > \endverbatim > > \param[in,out] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,N) > On entry, the m by n matrix to be factored. > On exit, the factors L and U from the factorization > A = P*L*U; the unit diagonal elements of L are not stored. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. LDA >= max(1,M). > \endverbatim > > \param[out] IPIV > \verbatim > IPIV is INTEGER array, dimension (min(M,N)) > The pivot indices; for 1 <= i <= min(M,N), row i of the > matrix was interchanged with row IPIV(i). > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -k, the k-th argument had an illegal value > > 0: if INFO = k, U(k,k) is exactly zero. The factorization > has been completed, but the factor U is exactly > singular, and division by zero will occur if it is used > to solve a system of equations. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleGEcomputational ===================================================================== Subroutine */ int igraphdgetf2_(integer *m, integer *n, doublereal *a, integer * lda, integer *ipiv, integer *info) { /* System generated locals */ integer a_dim1, a_offset, i__1, i__2, i__3; doublereal d__1; /* Local variables */ integer i__, j, jp; extern /* Subroutine */ int igraphdger_(integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, integer *), igraphdscal_(integer *, doublereal *, doublereal *, integer *); doublereal sfmin; extern /* Subroutine */ int igraphdswap_(integer *, doublereal *, integer *, doublereal *, integer *); extern doublereal igraphdlamch_(char *); extern integer igraphidamax_(integer *, doublereal *, integer *); extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); /* -- LAPACK computational routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Test the input parameters. Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --ipiv; /* Function Body */ *info = 0; if (*m < 0) { *info = -1; } else if (*n < 0) { *info = -2; } else if (*lda < max(1,*m)) { *info = -4; } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DGETF2", &i__1, (ftnlen)6); return 0; } /* Quick return if possible */ if (*m == 0 || *n == 0) { return 0; } /* Compute machine safe minimum */ sfmin = igraphdlamch_("S"); i__1 = min(*m,*n); for (j = 1; j <= i__1; ++j) { /* Find pivot and test for singularity. */ i__2 = *m - j + 1; jp = j - 1 + igraphidamax_(&i__2, &a[j + j * a_dim1], &c__1); ipiv[j] = jp; if (a[jp + j * a_dim1] != 0.) { /* Apply the interchange to columns 1:N. */ if (jp != j) { igraphdswap_(n, &a[j + a_dim1], lda, &a[jp + a_dim1], lda); } /* Compute elements J+1:M of J-th column. */ if (j < *m) { if ((d__1 = a[j + j * a_dim1], abs(d__1)) >= sfmin) { i__2 = *m - j; d__1 = 1. / a[j + j * a_dim1]; igraphdscal_(&i__2, &d__1, &a[j + 1 + j * a_dim1], &c__1); } else { i__2 = *m - j; for (i__ = 1; i__ <= i__2; ++i__) { a[j + i__ + j * a_dim1] /= a[j + j * a_dim1]; /* L20: */ } } } } else if (*info == 0) { *info = j; } if (j < min(*m,*n)) { /* Update trailing submatrix. */ i__2 = *m - j; i__3 = *n - j; igraphdger_(&i__2, &i__3, &c_b8, &a[j + 1 + j * a_dim1], &c__1, &a[j + ( j + 1) * a_dim1], lda, &a[j + 1 + (j + 1) * a_dim1], lda); } /* L10: */ } return 0; /* End of DGETF2 */ } /* igraphdgetf2_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dsconv.c0000644000076500000240000001055513524616145024306 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static doublereal c_b3 = .66666666666666663; /* ----------------------------------------------------------------------- \BeginDoc \Name: dsconv \Description: Convergence testing for the symmetric Arnoldi eigenvalue routine. \Usage: call dsconv ( N, RITZ, BOUNDS, TOL, NCONV ) \Arguments N Integer. (INPUT) Number of Ritz values to check for convergence. RITZ Double precision array of length N. (INPUT) The Ritz values to be checked for convergence. BOUNDS Double precision array of length N. (INPUT) Ritz estimates associated with the Ritz values in RITZ. TOL Double precision scalar. (INPUT) Desired relative accuracy for a Ritz value to be considered "converged". NCONV Integer scalar. (OUTPUT) Number of "converged" Ritz values. \EndDoc ----------------------------------------------------------------------- \BeginLib \Routines called: second ARPACK utility routine for timing. dlamch LAPACK routine that determines machine constants. \Author Danny Sorensen Phuong Vu Richard Lehoucq CRPC / Rice University Dept. of Computational & Houston, Texas Applied Mathematics Rice University Houston, Texas \SCCS Information: @(#) FILE: sconv.F SID: 2.4 DATE OF SID: 4/19/96 RELEASE: 2 \Remarks 1. Starting with version 2.4, this routine no longer uses the Parlett strategy using the gap conditions. \EndLib ----------------------------------------------------------------------- Subroutine */ int igraphdsconv_(integer *n, doublereal *ritz, doublereal *bounds, doublereal *tol, integer *nconv) { /* System generated locals */ integer i__1; doublereal d__1, d__2, d__3; /* Builtin functions */ double pow_dd(doublereal *, doublereal *); /* Local variables */ integer i__; real t0, t1; doublereal eps23, temp; extern doublereal igraphdlamch_(char *); extern /* Subroutine */ int igraphsecond_(real *); real tsconv = 0; /* %----------------------------------------------------% | Include files for debugging and timing information | %----------------------------------------------------% %------------------% | Scalar Arguments | %------------------% %-----------------% | Array Arguments | %-----------------% %---------------% | Local Scalars | %---------------% %-------------------% | External routines | %-------------------% %---------------------% | Intrinsic Functions | %---------------------% %-----------------------% | Executable Statements | %-----------------------% Parameter adjustments */ --bounds; --ritz; /* Function Body */ igraphsecond_(&t0); eps23 = igraphdlamch_("Epsilon-Machine"); eps23 = pow_dd(&eps23, &c_b3); *nconv = 0; i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { /* %-----------------------------------------------------% | The i-th Ritz value is considered "converged" | | when: bounds(i) .le. TOL*max(eps23, abs(ritz(i))) | %-----------------------------------------------------% Computing MAX */ d__2 = eps23, d__3 = (d__1 = ritz[i__], abs(d__1)); temp = max(d__2,d__3); if (bounds[i__] <= *tol * temp) { ++(*nconv); } /* L10: */ } igraphsecond_(&t1); tsconv += t1 - t0; return 0; /* %---------------% | End of dsconv | %---------------% */ } /* igraphdsconv_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dnaitr.c0000644000076500000240000010212013524616145024261 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static logical c_false = FALSE_; static doublereal c_b25 = 1.; static doublereal c_b47 = 0.; static doublereal c_b50 = -1.; static integer c__2 = 2; /* ----------------------------------------------------------------------- \BeginDoc \Name: dnaitr \Description: Reverse communication interface for applying NP additional steps to a K step nonsymmetric Arnoldi factorization. Input: OP*V_{k} - V_{k}*H = r_{k}*e_{k}^T with (V_{k}^T)*B*V_{k} = I, (V_{k}^T)*B*r_{k} = 0. Output: OP*V_{k+p} - V_{k+p}*H = r_{k+p}*e_{k+p}^T with (V_{k+p}^T)*B*V_{k+p} = I, (V_{k+p}^T)*B*r_{k+p} = 0. where OP and B are as in dnaupd. The B-norm of r_{k+p} is also computed and returned. \Usage: call dnaitr ( IDO, BMAT, N, K, NP, NB, RESID, RNORM, V, LDV, H, LDH, IPNTR, WORKD, INFO ) \Arguments IDO Integer. (INPUT/OUTPUT) Reverse communication flag. ------------------------------------------------------------- IDO = 0: first call to the reverse communication interface IDO = -1: compute Y = OP * X where IPNTR(1) is the pointer into WORK for X, IPNTR(2) is the pointer into WORK for Y. This is for the restart phase to force the new starting vector into the range of OP. IDO = 1: compute Y = OP * X where IPNTR(1) is the pointer into WORK for X, IPNTR(2) is the pointer into WORK for Y, IPNTR(3) is the pointer into WORK for B * X. IDO = 2: compute Y = B * X where IPNTR(1) is the pointer into WORK for X, IPNTR(2) is the pointer into WORK for Y. IDO = 99: done ------------------------------------------------------------- When the routine is used in the "shift-and-invert" mode, the vector B * Q is already available and do not need to be recompute in forming OP * Q. BMAT Character*1. (INPUT) BMAT specifies the type of the matrix B that defines the semi-inner product for the operator OP. See dnaupd. B = 'I' -> standard eigenvalue problem A*x = lambda*x B = 'G' -> generalized eigenvalue problem A*x = lambda*M**x N Integer. (INPUT) Dimension of the eigenproblem. K Integer. (INPUT) Current size of V and H. NP Integer. (INPUT) Number of additional Arnoldi steps to take. NB Integer. (INPUT) Blocksize to be used in the recurrence. Only work for NB = 1 right now. The goal is to have a program that implement both the block and non-block method. RESID Double precision array of length N. (INPUT/OUTPUT) On INPUT: RESID contains the residual vector r_{k}. On OUTPUT: RESID contains the residual vector r_{k+p}. RNORM Double precision scalar. (INPUT/OUTPUT) B-norm of the starting residual on input. B-norm of the updated residual r_{k+p} on output. V Double precision N by K+NP array. (INPUT/OUTPUT) On INPUT: V contains the Arnoldi vectors in the first K columns. On OUTPUT: V contains the new NP Arnoldi vectors in the next NP columns. The first K columns are unchanged. LDV Integer. (INPUT) Leading dimension of V exactly as declared in the calling program. H Double precision (K+NP) by (K+NP) array. (INPUT/OUTPUT) H is used to store the generated upper Hessenberg matrix. LDH Integer. (INPUT) Leading dimension of H exactly as declared in the calling program. IPNTR Integer array of length 3. (OUTPUT) Pointer to mark the starting locations in the WORK for vectors used by the Arnoldi iteration. ------------------------------------------------------------- IPNTR(1): pointer to the current operand vector X. IPNTR(2): pointer to the current result vector Y. IPNTR(3): pointer to the vector B * X when used in the shift-and-invert mode. X is the current operand. ------------------------------------------------------------- WORKD Double precision work array of length 3*N. (REVERSE COMMUNICATION) Distributed array to be used in the basic Arnoldi iteration for reverse communication. The calling program should not use WORKD as temporary workspace during the iteration !!!!!! On input, WORKD(1:N) = B*RESID and is used to save some computation at the first step. INFO Integer. (OUTPUT) = 0: Normal exit. > 0: Size of the spanning invariant subspace of OP found. \EndDoc ----------------------------------------------------------------------- \BeginLib \Local variables: xxxxxx real \References: 1. D.C. Sorensen, "Implicit Application of Polynomial Filters in a k-Step Arnoldi Method", SIAM J. Matr. Anal. Apps., 13 (1992), pp 357-385. 2. R.B. Lehoucq, "Analysis and Implementation of an Implicitly Restarted Arnoldi Iteration", Rice University Technical Report TR95-13, Department of Computational and Applied Mathematics. \Routines called: dgetv0 ARPACK routine to generate the initial vector. ivout ARPACK utility routine that prints integers. second ARPACK utility routine for timing. dmout ARPACK utility routine that prints matrices dvout ARPACK utility routine that prints vectors. dlabad LAPACK routine that computes machine constants. dlamch LAPACK routine that determines machine constants. dlascl LAPACK routine for careful scaling of a matrix. dlanhs LAPACK routine that computes various norms of a matrix. dgemv Level 2 BLAS routine for matrix vector multiplication. daxpy Level 1 BLAS that computes a vector triad. dscal Level 1 BLAS that scales a vector. dcopy Level 1 BLAS that copies one vector to another . ddot Level 1 BLAS that computes the scalar product of two vectors. dnrm2 Level 1 BLAS that computes the norm of a vector. \Author Danny Sorensen Phuong Vu Richard Lehoucq CRPC / Rice University Dept. of Computational & Houston, Texas Applied Mathematics Rice University Houston, Texas \Revision history: xx/xx/92: Version ' 2.4' \SCCS Information: @(#) FILE: naitr.F SID: 2.4 DATE OF SID: 8/27/96 RELEASE: 2 \Remarks The algorithm implemented is: restart = .false. Given V_{k} = [v_{1}, ..., v_{k}], r_{k}; r_{k} contains the initial residual vector even for k = 0; Also assume that rnorm = || B*r_{k} || and B*r_{k} are already computed by the calling program. betaj = rnorm ; p_{k+1} = B*r_{k} ; For j = k+1, ..., k+np Do 1) if ( betaj < tol ) stop or restart depending on j. ( At present tol is zero ) if ( restart ) generate a new starting vector. 2) v_{j} = r(j-1)/betaj; V_{j} = [V_{j-1}, v_{j}]; p_{j} = p_{j}/betaj 3) r_{j} = OP*v_{j} where OP is defined as in dnaupd For shift-invert mode p_{j} = B*v_{j} is already available. wnorm = || OP*v_{j} || 4) Compute the j-th step residual vector. w_{j} = V_{j}^T * B * OP * v_{j} r_{j} = OP*v_{j} - V_{j} * w_{j} H(:,j) = w_{j}; H(j,j-1) = rnorm rnorm = || r_(j) || If (rnorm > 0.717*wnorm) accept step and go back to 1) 5) Re-orthogonalization step: s = V_{j}'*B*r_{j} r_{j} = r_{j} - V_{j}*s; rnorm1 = || r_{j} || alphaj = alphaj + s_{j}; 6) Iterative refinement step: If (rnorm1 > 0.717*rnorm) then rnorm = rnorm1 accept step and go back to 1) Else rnorm = rnorm1 If this is the first time in step 6), go to 5) Else r_{j} lies in the span of V_{j} numerically. Set r_{j} = 0 and rnorm = 0; go to 1) EndIf End Do \EndLib ----------------------------------------------------------------------- Subroutine */ int igraphdnaitr_(integer *ido, char *bmat, integer *n, integer *k, integer *np, integer *nb, doublereal *resid, doublereal *rnorm, doublereal *v, integer *ldv, doublereal *h__, integer *ldh, integer * ipntr, doublereal *workd, integer *info) { /* Initialized data */ IGRAPH_F77_SAVE logical first = TRUE_; /* System generated locals */ integer h_dim1, h_offset, v_dim1, v_offset, i__1, i__2; doublereal d__1, d__2; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ integer i__; IGRAPH_F77_SAVE integer j; real t0, t1, t2 = 0, t3, t4, t5; integer jj; IGRAPH_F77_SAVE integer ipj, irj; integer nbx = 0; IGRAPH_F77_SAVE integer ivj; IGRAPH_F77_SAVE doublereal ulp; doublereal tst1; extern doublereal igraphddot_(integer *, doublereal *, integer *, doublereal *, integer *); IGRAPH_F77_SAVE integer ierr, iter; IGRAPH_F77_SAVE doublereal unfl, ovfl; integer nopx = 0; IGRAPH_F77_SAVE integer itry; extern doublereal igraphdnrm2_(integer *, doublereal *, integer *); doublereal temp1; IGRAPH_F77_SAVE logical orth1, orth2, step3, step4; IGRAPH_F77_SAVE doublereal betaj; extern /* Subroutine */ int igraphdscal_(integer *, doublereal *, doublereal *, integer *), igraphdgemv_(char *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *); integer infol; extern /* Subroutine */ int igraphdcopy_(integer *, doublereal *, integer *, doublereal *, integer *), igraphdaxpy_(integer *, doublereal *, doublereal *, integer *, doublereal *, integer *), igraphdmout_(integer *, integer *, integer *, doublereal *, integer *, integer *, char *, ftnlen); doublereal xtemp[2]; real tmvbx = 0; extern /* Subroutine */ int igraphdvout_(integer *, integer *, doublereal *, integer *, char *, ftnlen); IGRAPH_F77_SAVE doublereal wnorm; extern /* Subroutine */ int igraphivout_(integer *, integer *, integer *, integer *, char *, ftnlen), igraphdgetv0_(integer *, char *, integer *, logical *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *), igraphdlabad_(doublereal *, doublereal *); IGRAPH_F77_SAVE doublereal rnorm1; extern doublereal igraphdlamch_(char *); extern /* Subroutine */ int igraphdlascl_(char *, integer *, integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, integer *, integer *); extern doublereal igraphdlanhs_(char *, integer *, doublereal *, integer *, doublereal *); extern /* Subroutine */ int igraphsecond_(real *); integer logfil, ndigit, nitref = 0, mnaitr = 0; real titref = 0, tnaitr = 0; IGRAPH_F77_SAVE integer msglvl; IGRAPH_F77_SAVE doublereal smlnum; integer nrorth = 0; IGRAPH_F77_SAVE logical rstart; integer nrstrt = 0; real tmvopx = 0; /* %----------------------------------------------------% | Include files for debugging and timing information | %----------------------------------------------------% %------------------% | Scalar Arguments | %------------------% %-----------------% | Array Arguments | %-----------------% %------------% | Parameters | %------------% %---------------% | Local Scalars | %---------------% %-----------------------% | Local Array Arguments | %-----------------------% %----------------------% | External Subroutines | %----------------------% %--------------------% | External Functions | %--------------------% %---------------------% | Intrinsic Functions | %---------------------% %-----------------% | Data statements | %-----------------% Parameter adjustments */ --workd; --resid; v_dim1 = *ldv; v_offset = 1 + v_dim1; v -= v_offset; h_dim1 = *ldh; h_offset = 1 + h_dim1; h__ -= h_offset; --ipntr; /* Function Body %-----------------------% | Executable Statements | %-----------------------% */ if (first) { /* %-----------------------------------------% | Set machine-dependent constants for the | | the splitting and deflation criterion. | | If norm(H) <= sqrt(OVFL), | | overflow should not occur. | | REFERENCE: LAPACK subroutine dlahqr | %-----------------------------------------% */ unfl = igraphdlamch_("safe minimum"); ovfl = 1. / unfl; igraphdlabad_(&unfl, &ovfl); ulp = igraphdlamch_("precision"); smlnum = unfl * (*n / ulp); first = FALSE_; } if (*ido == 0) { /* %-------------------------------% | Initialize timing statistics | | & message level for debugging | %-------------------------------% */ igraphsecond_(&t0); msglvl = mnaitr; /* %------------------------------% | Initial call to this routine | %------------------------------% */ *info = 0; step3 = FALSE_; step4 = FALSE_; rstart = FALSE_; orth1 = FALSE_; orth2 = FALSE_; j = *k + 1; ipj = 1; irj = ipj + *n; ivj = irj + *n; } /* %-------------------------------------------------% | When in reverse communication mode one of: | | STEP3, STEP4, ORTH1, ORTH2, RSTART | | will be .true. when .... | | STEP3: return from computing OP*v_{j}. | | STEP4: return from computing B-norm of OP*v_{j} | | ORTH1: return from computing B-norm of r_{j+1} | | ORTH2: return from computing B-norm of | | correction to the residual vector. | | RSTART: return from OP computations needed by | | dgetv0. | %-------------------------------------------------% */ if (step3) { goto L50; } if (step4) { goto L60; } if (orth1) { goto L70; } if (orth2) { goto L90; } if (rstart) { goto L30; } /* %-----------------------------% | Else this is the first step | %-----------------------------% %--------------------------------------------------------------% | | | A R N O L D I I T E R A T I O N L O O P | | | | Note: B*r_{j-1} is already in WORKD(1:N)=WORKD(IPJ:IPJ+N-1) | %--------------------------------------------------------------% */ L1000: if (msglvl > 1) { igraphivout_(&logfil, &c__1, &j, &ndigit, "_naitr: generating Arnoldi vect" "or number", (ftnlen)40); igraphdvout_(&logfil, &c__1, rnorm, &ndigit, "_naitr: B-norm of the curren" "t residual is", (ftnlen)41); } /* %---------------------------------------------------% | STEP 1: Check if the B norm of j-th residual | | vector is zero. Equivalent to determing whether | | an exact j-step Arnoldi factorization is present. | %---------------------------------------------------% */ betaj = *rnorm; if (*rnorm > 0.) { goto L40; } /* %---------------------------------------------------% | Invariant subspace found, generate a new starting | | vector which is orthogonal to the current Arnoldi | | basis and continue the iteration. | %---------------------------------------------------% */ if (msglvl > 0) { igraphivout_(&logfil, &c__1, &j, &ndigit, "_naitr: ****** RESTART AT STEP " "******", (ftnlen)37); } /* %---------------------------------------------% | ITRY is the loop variable that controls the | | maximum amount of times that a restart is | | attempted. NRSTRT is used by stat.h | %---------------------------------------------% */ betaj = 0.; ++nrstrt; itry = 1; L20: rstart = TRUE_; *ido = 0; L30: /* %--------------------------------------% | If in reverse communication mode and | | RSTART = .true. flow returns here. | %--------------------------------------% */ igraphdgetv0_(ido, bmat, &itry, &c_false, n, &j, &v[v_offset], ldv, &resid[1], rnorm, &ipntr[1], &workd[1], &ierr); if (*ido != 99) { goto L9000; } if (ierr < 0) { ++itry; if (itry <= 3) { goto L20; } /* %------------------------------------------------% | Give up after several restart attempts. | | Set INFO to the size of the invariant subspace | | which spans OP and exit. | %------------------------------------------------% */ *info = j - 1; igraphsecond_(&t1); tnaitr += t1 - t0; *ido = 99; goto L9000; } L40: /* %---------------------------------------------------------% | STEP 2: v_{j} = r_{j-1}/rnorm and p_{j} = p_{j}/rnorm | | Note that p_{j} = B*r_{j-1}. In order to avoid overflow | | when reciprocating a small RNORM, test against lower | | machine bound. | %---------------------------------------------------------% */ igraphdcopy_(n, &resid[1], &c__1, &v[j * v_dim1 + 1], &c__1); if (*rnorm >= unfl) { temp1 = 1. / *rnorm; igraphdscal_(n, &temp1, &v[j * v_dim1 + 1], &c__1); igraphdscal_(n, &temp1, &workd[ipj], &c__1); } else { /* %-----------------------------------------% | To scale both v_{j} and p_{j} carefully | | use LAPACK routine SLASCL | %-----------------------------------------% */ igraphdlascl_("General", &i__, &i__, rnorm, &c_b25, n, &c__1, &v[j * v_dim1 + 1], n, &infol); igraphdlascl_("General", &i__, &i__, rnorm, &c_b25, n, &c__1, &workd[ipj], n, &infol); } /* %------------------------------------------------------% | STEP 3: r_{j} = OP*v_{j}; Note that p_{j} = B*v_{j} | | Note that this is not quite yet r_{j}. See STEP 4 | %------------------------------------------------------% */ step3 = TRUE_; ++nopx; igraphsecond_(&t2); igraphdcopy_(n, &v[j * v_dim1 + 1], &c__1, &workd[ivj], &c__1); ipntr[1] = ivj; ipntr[2] = irj; ipntr[3] = ipj; *ido = 1; /* %-----------------------------------% | Exit in order to compute OP*v_{j} | %-----------------------------------% */ goto L9000; L50: /* %----------------------------------% | Back from reverse communication; | | WORKD(IRJ:IRJ+N-1) := OP*v_{j} | | if step3 = .true. | %----------------------------------% */ igraphsecond_(&t3); tmvopx += t3 - t2; step3 = FALSE_; /* %------------------------------------------% | Put another copy of OP*v_{j} into RESID. | %------------------------------------------% */ igraphdcopy_(n, &workd[irj], &c__1, &resid[1], &c__1); /* %---------------------------------------% | STEP 4: Finish extending the Arnoldi | | factorization to length j. | %---------------------------------------% */ igraphsecond_(&t2); if (*(unsigned char *)bmat == 'G') { ++nbx; step4 = TRUE_; ipntr[1] = irj; ipntr[2] = ipj; *ido = 2; /* %-------------------------------------% | Exit in order to compute B*OP*v_{j} | %-------------------------------------% */ goto L9000; } else if (*(unsigned char *)bmat == 'I') { igraphdcopy_(n, &resid[1], &c__1, &workd[ipj], &c__1); } L60: /* %----------------------------------% | Back from reverse communication; | | WORKD(IPJ:IPJ+N-1) := B*OP*v_{j} | | if step4 = .true. | %----------------------------------% */ if (*(unsigned char *)bmat == 'G') { igraphsecond_(&t3); tmvbx += t3 - t2; } step4 = FALSE_; /* %-------------------------------------% | The following is needed for STEP 5. | | Compute the B-norm of OP*v_{j}. | %-------------------------------------% */ if (*(unsigned char *)bmat == 'G') { wnorm = igraphddot_(n, &resid[1], &c__1, &workd[ipj], &c__1); wnorm = sqrt((abs(wnorm))); } else if (*(unsigned char *)bmat == 'I') { wnorm = igraphdnrm2_(n, &resid[1], &c__1); } /* %-----------------------------------------% | Compute the j-th residual corresponding | | to the j step factorization. | | Use Classical Gram Schmidt and compute: | | w_{j} <- V_{j}^T * B * OP * v_{j} | | r_{j} <- OP*v_{j} - V_{j} * w_{j} | %-----------------------------------------% %------------------------------------------% | Compute the j Fourier coefficients w_{j} | | WORKD(IPJ:IPJ+N-1) contains B*OP*v_{j}. | %------------------------------------------% */ igraphdgemv_("T", n, &j, &c_b25, &v[v_offset], ldv, &workd[ipj], &c__1, &c_b47, &h__[j * h_dim1 + 1], &c__1); /* %--------------------------------------% | Orthogonalize r_{j} against V_{j}. | | RESID contains OP*v_{j}. See STEP 3. | %--------------------------------------% */ igraphdgemv_("N", n, &j, &c_b50, &v[v_offset], ldv, &h__[j * h_dim1 + 1], &c__1, &c_b25, &resid[1], &c__1); if (j > 1) { h__[j + (j - 1) * h_dim1] = betaj; } igraphsecond_(&t4); orth1 = TRUE_; igraphsecond_(&t2); if (*(unsigned char *)bmat == 'G') { ++nbx; igraphdcopy_(n, &resid[1], &c__1, &workd[irj], &c__1); ipntr[1] = irj; ipntr[2] = ipj; *ido = 2; /* %----------------------------------% | Exit in order to compute B*r_{j} | %----------------------------------% */ goto L9000; } else if (*(unsigned char *)bmat == 'I') { igraphdcopy_(n, &resid[1], &c__1, &workd[ipj], &c__1); } L70: /* %---------------------------------------------------% | Back from reverse communication if ORTH1 = .true. | | WORKD(IPJ:IPJ+N-1) := B*r_{j}. | %---------------------------------------------------% */ if (*(unsigned char *)bmat == 'G') { igraphsecond_(&t3); tmvbx += t3 - t2; } orth1 = FALSE_; /* %------------------------------% | Compute the B-norm of r_{j}. | %------------------------------% */ if (*(unsigned char *)bmat == 'G') { *rnorm = igraphddot_(n, &resid[1], &c__1, &workd[ipj], &c__1); *rnorm = sqrt((abs(*rnorm))); } else if (*(unsigned char *)bmat == 'I') { *rnorm = igraphdnrm2_(n, &resid[1], &c__1); } /* %-----------------------------------------------------------% | STEP 5: Re-orthogonalization / Iterative refinement phase | | Maximum NITER_ITREF tries. | | | | s = V_{j}^T * B * r_{j} | | r_{j} = r_{j} - V_{j}*s | | alphaj = alphaj + s_{j} | | | | The stopping criteria used for iterative refinement is | | discussed in Parlett's book SEP, page 107 and in Gragg & | | Reichel ACM TOMS paper; Algorithm 686, Dec. 1990. | | Determine if we need to correct the residual. The goal is | | to enforce ||v(:,1:j)^T * r_{j}|| .le. eps * || r_{j} || | | The following test determines whether the sine of the | | angle between OP*x and the computed residual is less | | than or equal to 0.717. | %-----------------------------------------------------------% */ if (*rnorm > wnorm * .717f) { goto L100; } iter = 0; ++nrorth; /* %---------------------------------------------------% | Enter the Iterative refinement phase. If further | | refinement is necessary, loop back here. The loop | | variable is ITER. Perform a step of Classical | | Gram-Schmidt using all the Arnoldi vectors V_{j} | %---------------------------------------------------% */ L80: if (msglvl > 2) { xtemp[0] = wnorm; xtemp[1] = *rnorm; igraphdvout_(&logfil, &c__2, xtemp, &ndigit, "_naitr: re-orthonalization; " "wnorm and rnorm are", (ftnlen)47); igraphdvout_(&logfil, &j, &h__[j * h_dim1 + 1], &ndigit, "_naitr: j-th col" "umn of H", (ftnlen)24); } /* %----------------------------------------------------% | Compute V_{j}^T * B * r_{j}. | | WORKD(IRJ:IRJ+J-1) = v(:,1:J)'*WORKD(IPJ:IPJ+N-1). | %----------------------------------------------------% */ igraphdgemv_("T", n, &j, &c_b25, &v[v_offset], ldv, &workd[ipj], &c__1, &c_b47, &workd[irj], &c__1); /* %---------------------------------------------% | Compute the correction to the residual: | | r_{j} = r_{j} - V_{j} * WORKD(IRJ:IRJ+J-1). | | The correction to H is v(:,1:J)*H(1:J,1:J) | | + v(:,1:J)*WORKD(IRJ:IRJ+J-1)*e'_j. | %---------------------------------------------% */ igraphdgemv_("N", n, &j, &c_b50, &v[v_offset], ldv, &workd[irj], &c__1, &c_b25, &resid[1], &c__1); igraphdaxpy_(&j, &c_b25, &workd[irj], &c__1, &h__[j * h_dim1 + 1], &c__1); orth2 = TRUE_; igraphsecond_(&t2); if (*(unsigned char *)bmat == 'G') { ++nbx; igraphdcopy_(n, &resid[1], &c__1, &workd[irj], &c__1); ipntr[1] = irj; ipntr[2] = ipj; *ido = 2; /* %-----------------------------------% | Exit in order to compute B*r_{j}. | | r_{j} is the corrected residual. | %-----------------------------------% */ goto L9000; } else if (*(unsigned char *)bmat == 'I') { igraphdcopy_(n, &resid[1], &c__1, &workd[ipj], &c__1); } L90: /* %---------------------------------------------------% | Back from reverse communication if ORTH2 = .true. | %---------------------------------------------------% */ if (*(unsigned char *)bmat == 'G') { igraphsecond_(&t3); tmvbx += t3 - t2; } /* %-----------------------------------------------------% | Compute the B-norm of the corrected residual r_{j}. | %-----------------------------------------------------% */ if (*(unsigned char *)bmat == 'G') { rnorm1 = igraphddot_(n, &resid[1], &c__1, &workd[ipj], &c__1); rnorm1 = sqrt((abs(rnorm1))); } else if (*(unsigned char *)bmat == 'I') { rnorm1 = igraphdnrm2_(n, &resid[1], &c__1); } if (msglvl > 0 && iter > 0) { igraphivout_(&logfil, &c__1, &j, &ndigit, "_naitr: Iterative refinement fo" "r Arnoldi residual", (ftnlen)49); if (msglvl > 2) { xtemp[0] = *rnorm; xtemp[1] = rnorm1; igraphdvout_(&logfil, &c__2, xtemp, &ndigit, "_naitr: iterative refine" "ment ; rnorm and rnorm1 are", (ftnlen)51); } } /* %-----------------------------------------% | Determine if we need to perform another | | step of re-orthogonalization. | %-----------------------------------------% */ if (rnorm1 > *rnorm * .717f) { /* %---------------------------------------% | No need for further refinement. | | The cosine of the angle between the | | corrected residual vector and the old | | residual vector is greater than 0.717 | | In other words the corrected residual | | and the old residual vector share an | | angle of less than arcCOS(0.717) | %---------------------------------------% */ *rnorm = rnorm1; } else { /* %-------------------------------------------% | Another step of iterative refinement step | | is required. NITREF is used by stat.h | %-------------------------------------------% */ ++nitref; *rnorm = rnorm1; ++iter; if (iter <= 1) { goto L80; } /* %-------------------------------------------------% | Otherwise RESID is numerically in the span of V | %-------------------------------------------------% */ i__1 = *n; for (jj = 1; jj <= i__1; ++jj) { resid[jj] = 0.; /* L95: */ } *rnorm = 0.; } /* %----------------------------------------------% | Branch here directly if iterative refinement | | wasn't necessary or after at most NITER_REF | | steps of iterative refinement. | %----------------------------------------------% */ L100: rstart = FALSE_; orth2 = FALSE_; igraphsecond_(&t5); titref += t5 - t4; /* %------------------------------------% | STEP 6: Update j = j+1; Continue | %------------------------------------% */ ++j; if (j > *k + *np) { igraphsecond_(&t1); tnaitr += t1 - t0; *ido = 99; i__1 = *k + *np - 1; for (i__ = max(1,*k); i__ <= i__1; ++i__) { /* %--------------------------------------------% | Check for splitting and deflation. | | Use a standard test as in the QR algorithm | | REFERENCE: LAPACK subroutine dlahqr | %--------------------------------------------% */ tst1 = (d__1 = h__[i__ + i__ * h_dim1], abs(d__1)) + (d__2 = h__[ i__ + 1 + (i__ + 1) * h_dim1], abs(d__2)); if (tst1 == 0.) { i__2 = *k + *np; tst1 = igraphdlanhs_("1", &i__2, &h__[h_offset], ldh, &workd[*n + 1] ); } /* Computing MAX */ d__2 = ulp * tst1; if ((d__1 = h__[i__ + 1 + i__ * h_dim1], abs(d__1)) <= max(d__2, smlnum)) { h__[i__ + 1 + i__ * h_dim1] = 0.; } /* L110: */ } if (msglvl > 2) { i__1 = *k + *np; i__2 = *k + *np; igraphdmout_(&logfil, &i__1, &i__2, &h__[h_offset], ldh, &ndigit, "_na" "itr: Final upper Hessenberg matrix H of order K+NP", ( ftnlen)53); } goto L9000; } /* %--------------------------------------------------------% | Loop back to extend the factorization by another step. | %--------------------------------------------------------% */ goto L1000; /* %---------------------------------------------------------------% | | | E N D O F M A I N I T E R A T I O N L O O P | | | %---------------------------------------------------------------% */ L9000: return 0; /* %---------------% | End of dnaitr | %---------------% */ } /* igraphdnaitr_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlansy.c0000644000076500000240000002027113524616145024300 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; /* > \brief \b DLANSY returns the value of the 1-norm, or the Frobenius norm, or the infinity norm, or the ele ment of largest absolute value of a real symmetric matrix. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLANSY + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== DOUBLE PRECISION FUNCTION DLANSY( NORM, UPLO, N, A, LDA, WORK ) CHARACTER NORM, UPLO INTEGER LDA, N DOUBLE PRECISION A( LDA, * ), WORK( * ) > \par Purpose: ============= > > \verbatim > > DLANSY returns the value of the one norm, or the Frobenius norm, or > the infinity norm, or the element of largest absolute value of a > real symmetric matrix A. > \endverbatim > > \return DLANSY > \verbatim > > DLANSY = ( max(abs(A(i,j))), NORM = 'M' or 'm' > ( > ( norm1(A), NORM = '1', 'O' or 'o' > ( > ( normI(A), NORM = 'I' or 'i' > ( > ( normF(A), NORM = 'F', 'f', 'E' or 'e' > > where norm1 denotes the one norm of a matrix (maximum column sum), > normI denotes the infinity norm of a matrix (maximum row sum) and > normF denotes the Frobenius norm of a matrix (square root of sum of > squares). Note that max(abs(A(i,j))) is not a consistent matrix norm. > \endverbatim Arguments: ========== > \param[in] NORM > \verbatim > NORM is CHARACTER*1 > Specifies the value to be returned in DLANSY as described > above. > \endverbatim > > \param[in] UPLO > \verbatim > UPLO is CHARACTER*1 > Specifies whether the upper or lower triangular part of the > symmetric matrix A is to be referenced. > = 'U': Upper triangular part of A is referenced > = 'L': Lower triangular part of A is referenced > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix A. N >= 0. When N = 0, DLANSY is > set to zero. > \endverbatim > > \param[in] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,N) > The symmetric matrix A. If UPLO = 'U', the leading n by n > upper triangular part of A contains the upper triangular part > of the matrix A, and the strictly lower triangular part of A > is not referenced. If UPLO = 'L', the leading n by n lower > triangular part of A contains the lower triangular part of > the matrix A, and the strictly upper triangular part of A is > not referenced. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. LDA >= max(N,1). > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (MAX(1,LWORK)), > where LWORK >= N when NORM = 'I' or '1' or 'O'; otherwise, > WORK is not referenced. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleSYauxiliary ===================================================================== */ doublereal igraphdlansy_(char *norm, char *uplo, integer *n, doublereal *a, integer *lda, doublereal *work) { /* System generated locals */ integer a_dim1, a_offset, i__1, i__2; doublereal ret_val, d__1; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ integer i__, j; doublereal sum, absa, scale; extern logical igraphlsame_(char *, char *); doublereal value = 0.; extern logical igraphdisnan_(doublereal *); extern /* Subroutine */ int igraphdlassq_(integer *, doublereal *, integer *, doublereal *, doublereal *); /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --work; /* Function Body */ if (*n == 0) { value = 0.; } else if (igraphlsame_(norm, "M")) { /* Find max(abs(A(i,j))). */ value = 0.; if (igraphlsame_(uplo, "U")) { i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = j; for (i__ = 1; i__ <= i__2; ++i__) { sum = (d__1 = a[i__ + j * a_dim1], abs(d__1)); if (value < sum || igraphdisnan_(&sum)) { value = sum; } /* L10: */ } /* L20: */ } } else { i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = *n; for (i__ = j; i__ <= i__2; ++i__) { sum = (d__1 = a[i__ + j * a_dim1], abs(d__1)); if (value < sum || igraphdisnan_(&sum)) { value = sum; } /* L30: */ } /* L40: */ } } } else if (igraphlsame_(norm, "I") || igraphlsame_(norm, "O") || *(unsigned char *)norm == '1') { /* Find normI(A) ( = norm1(A), since A is symmetric). */ value = 0.; if (igraphlsame_(uplo, "U")) { i__1 = *n; for (j = 1; j <= i__1; ++j) { sum = 0.; i__2 = j - 1; for (i__ = 1; i__ <= i__2; ++i__) { absa = (d__1 = a[i__ + j * a_dim1], abs(d__1)); sum += absa; work[i__] += absa; /* L50: */ } work[j] = sum + (d__1 = a[j + j * a_dim1], abs(d__1)); /* L60: */ } i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { sum = work[i__]; if (value < sum || igraphdisnan_(&sum)) { value = sum; } /* L70: */ } } else { i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { work[i__] = 0.; /* L80: */ } i__1 = *n; for (j = 1; j <= i__1; ++j) { sum = work[j] + (d__1 = a[j + j * a_dim1], abs(d__1)); i__2 = *n; for (i__ = j + 1; i__ <= i__2; ++i__) { absa = (d__1 = a[i__ + j * a_dim1], abs(d__1)); sum += absa; work[i__] += absa; /* L90: */ } if (value < sum || igraphdisnan_(&sum)) { value = sum; } /* L100: */ } } } else if (igraphlsame_(norm, "F") || igraphlsame_(norm, "E")) { /* Find normF(A). */ scale = 0.; sum = 1.; if (igraphlsame_(uplo, "U")) { i__1 = *n; for (j = 2; j <= i__1; ++j) { i__2 = j - 1; igraphdlassq_(&i__2, &a[j * a_dim1 + 1], &c__1, &scale, &sum); /* L110: */ } } else { i__1 = *n - 1; for (j = 1; j <= i__1; ++j) { i__2 = *n - j; igraphdlassq_(&i__2, &a[j + 1 + j * a_dim1], &c__1, &scale, &sum); /* L120: */ } } sum *= 2; i__1 = *lda + 1; igraphdlassq_(n, &a[a_offset], &i__1, &scale, &sum); value = scale * sqrt(sum); } ret_val = value; return ret_val; /* End of DLANSY */ } /* igraphdlansy_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlarfb.c0000644000076500000240000005560513524616145024251 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static doublereal c_b14 = 1.; static doublereal c_b25 = -1.; /* > \brief \b DLARFB applies a block reflector or its transpose to a general rectangular matrix. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLARFB + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLARFB( SIDE, TRANS, DIRECT, STOREV, M, N, K, V, LDV, T, LDT, C, LDC, WORK, LDWORK ) CHARACTER DIRECT, SIDE, STOREV, TRANS INTEGER K, LDC, LDT, LDV, LDWORK, M, N DOUBLE PRECISION C( LDC, * ), T( LDT, * ), V( LDV, * ), $ WORK( LDWORK, * ) > \par Purpose: ============= > > \verbatim > > DLARFB applies a real block reflector H or its transpose H**T to a > real m by n matrix C, from either the left or the right. > \endverbatim Arguments: ========== > \param[in] SIDE > \verbatim > SIDE is CHARACTER*1 > = 'L': apply H or H**T from the Left > = 'R': apply H or H**T from the Right > \endverbatim > > \param[in] TRANS > \verbatim > TRANS is CHARACTER*1 > = 'N': apply H (No transpose) > = 'T': apply H**T (Transpose) > \endverbatim > > \param[in] DIRECT > \verbatim > DIRECT is CHARACTER*1 > Indicates how H is formed from a product of elementary > reflectors > = 'F': H = H(1) H(2) . . . H(k) (Forward) > = 'B': H = H(k) . . . H(2) H(1) (Backward) > \endverbatim > > \param[in] STOREV > \verbatim > STOREV is CHARACTER*1 > Indicates how the vectors which define the elementary > reflectors are stored: > = 'C': Columnwise > = 'R': Rowwise > \endverbatim > > \param[in] M > \verbatim > M is INTEGER > The number of rows of the matrix C. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The number of columns of the matrix C. > \endverbatim > > \param[in] K > \verbatim > K is INTEGER > The order of the matrix T (= the number of elementary > reflectors whose product defines the block reflector). > \endverbatim > > \param[in] V > \verbatim > V is DOUBLE PRECISION array, dimension > (LDV,K) if STOREV = 'C' > (LDV,M) if STOREV = 'R' and SIDE = 'L' > (LDV,N) if STOREV = 'R' and SIDE = 'R' > The matrix V. See Further Details. > \endverbatim > > \param[in] LDV > \verbatim > LDV is INTEGER > The leading dimension of the array V. > If STOREV = 'C' and SIDE = 'L', LDV >= max(1,M); > if STOREV = 'C' and SIDE = 'R', LDV >= max(1,N); > if STOREV = 'R', LDV >= K. > \endverbatim > > \param[in] T > \verbatim > T is DOUBLE PRECISION array, dimension (LDT,K) > The triangular k by k matrix T in the representation of the > block reflector. > \endverbatim > > \param[in] LDT > \verbatim > LDT is INTEGER > The leading dimension of the array T. LDT >= K. > \endverbatim > > \param[in,out] C > \verbatim > C is DOUBLE PRECISION array, dimension (LDC,N) > On entry, the m by n matrix C. > On exit, C is overwritten by H*C or H**T*C or C*H or C*H**T. > \endverbatim > > \param[in] LDC > \verbatim > LDC is INTEGER > The leading dimension of the array C. LDC >= max(1,M). > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (LDWORK,K) > \endverbatim > > \param[in] LDWORK > \verbatim > LDWORK is INTEGER > The leading dimension of the array WORK. > If SIDE = 'L', LDWORK >= max(1,N); > if SIDE = 'R', LDWORK >= max(1,M). > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date June 2013 > \ingroup doubleOTHERauxiliary > \par Further Details: ===================== > > \verbatim > > The shape of the matrix V and the storage of the vectors which define > the H(i) is best illustrated by the following example with n = 5 and > k = 3. The elements equal to 1 are not stored; the corresponding > array elements are modified but restored on exit. The rest of the > array is not used. > > DIRECT = 'F' and STOREV = 'C': DIRECT = 'F' and STOREV = 'R': > > V = ( 1 ) V = ( 1 v1 v1 v1 v1 ) > ( v1 1 ) ( 1 v2 v2 v2 ) > ( v1 v2 1 ) ( 1 v3 v3 ) > ( v1 v2 v3 ) > ( v1 v2 v3 ) > > DIRECT = 'B' and STOREV = 'C': DIRECT = 'B' and STOREV = 'R': > > V = ( v1 v2 v3 ) V = ( v1 v1 1 ) > ( v1 v2 v3 ) ( v2 v2 v2 1 ) > ( 1 v2 v3 ) ( v3 v3 v3 v3 1 ) > ( 1 v3 ) > ( 1 ) > \endverbatim > ===================================================================== Subroutine */ int igraphdlarfb_(char *side, char *trans, char *direct, char * storev, integer *m, integer *n, integer *k, doublereal *v, integer * ldv, doublereal *t, integer *ldt, doublereal *c__, integer *ldc, doublereal *work, integer *ldwork) { /* System generated locals */ integer c_dim1, c_offset, t_dim1, t_offset, v_dim1, v_offset, work_dim1, work_offset, i__1, i__2; /* Local variables */ integer i__, j; extern /* Subroutine */ int igraphdgemm_(char *, char *, integer *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *); extern logical igraphlsame_(char *, char *); extern /* Subroutine */ int igraphdcopy_(integer *, doublereal *, integer *, doublereal *, integer *), igraphdtrmm_(char *, char *, char *, char *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *); char transt[1]; /* -- LAPACK auxiliary routine (version 3.5.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- June 2013 ===================================================================== Quick return if possible Parameter adjustments */ v_dim1 = *ldv; v_offset = 1 + v_dim1; v -= v_offset; t_dim1 = *ldt; t_offset = 1 + t_dim1; t -= t_offset; c_dim1 = *ldc; c_offset = 1 + c_dim1; c__ -= c_offset; work_dim1 = *ldwork; work_offset = 1 + work_dim1; work -= work_offset; /* Function Body */ if (*m <= 0 || *n <= 0) { return 0; } if (igraphlsame_(trans, "N")) { *(unsigned char *)transt = 'T'; } else { *(unsigned char *)transt = 'N'; } if (igraphlsame_(storev, "C")) { if (igraphlsame_(direct, "F")) { /* Let V = ( V1 ) (first K rows) ( V2 ) where V1 is unit lower triangular. */ if (igraphlsame_(side, "L")) { /* Form H * C or H**T * C where C = ( C1 ) ( C2 ) W := C**T * V = (C1**T * V1 + C2**T * V2) (stored in WORK) W := C1**T */ i__1 = *k; for (j = 1; j <= i__1; ++j) { igraphdcopy_(n, &c__[j + c_dim1], ldc, &work[j * work_dim1 + 1], &c__1); /* L10: */ } /* W := W * V1 */ igraphdtrmm_("Right", "Lower", "No transpose", "Unit", n, k, &c_b14, &v[v_offset], ldv, &work[work_offset], ldwork); if (*m > *k) { /* W := W + C2**T * V2 */ i__1 = *m - *k; igraphdgemm_("Transpose", "No transpose", n, k, &i__1, &c_b14, & c__[*k + 1 + c_dim1], ldc, &v[*k + 1 + v_dim1], ldv, &c_b14, &work[work_offset], ldwork); } /* W := W * T**T or W * T */ igraphdtrmm_("Right", "Upper", transt, "Non-unit", n, k, &c_b14, &t[ t_offset], ldt, &work[work_offset], ldwork); /* C := C - V * W**T */ if (*m > *k) { /* C2 := C2 - V2 * W**T */ i__1 = *m - *k; igraphdgemm_("No transpose", "Transpose", &i__1, n, k, &c_b25, & v[*k + 1 + v_dim1], ldv, &work[work_offset], ldwork, &c_b14, &c__[*k + 1 + c_dim1], ldc); } /* W := W * V1**T */ igraphdtrmm_("Right", "Lower", "Transpose", "Unit", n, k, &c_b14, & v[v_offset], ldv, &work[work_offset], ldwork); /* C1 := C1 - W**T */ i__1 = *k; for (j = 1; j <= i__1; ++j) { i__2 = *n; for (i__ = 1; i__ <= i__2; ++i__) { c__[j + i__ * c_dim1] -= work[i__ + j * work_dim1]; /* L20: */ } /* L30: */ } } else if (igraphlsame_(side, "R")) { /* Form C * H or C * H**T where C = ( C1 C2 ) W := C * V = (C1*V1 + C2*V2) (stored in WORK) W := C1 */ i__1 = *k; for (j = 1; j <= i__1; ++j) { igraphdcopy_(m, &c__[j * c_dim1 + 1], &c__1, &work[j * work_dim1 + 1], &c__1); /* L40: */ } /* W := W * V1 */ igraphdtrmm_("Right", "Lower", "No transpose", "Unit", m, k, &c_b14, &v[v_offset], ldv, &work[work_offset], ldwork); if (*n > *k) { /* W := W + C2 * V2 */ i__1 = *n - *k; igraphdgemm_("No transpose", "No transpose", m, k, &i__1, & c_b14, &c__[(*k + 1) * c_dim1 + 1], ldc, &v[*k + 1 + v_dim1], ldv, &c_b14, &work[work_offset], ldwork); } /* W := W * T or W * T**T */ igraphdtrmm_("Right", "Upper", trans, "Non-unit", m, k, &c_b14, &t[ t_offset], ldt, &work[work_offset], ldwork); /* C := C - W * V**T */ if (*n > *k) { /* C2 := C2 - W * V2**T */ i__1 = *n - *k; igraphdgemm_("No transpose", "Transpose", m, &i__1, k, &c_b25, & work[work_offset], ldwork, &v[*k + 1 + v_dim1], ldv, &c_b14, &c__[(*k + 1) * c_dim1 + 1], ldc); } /* W := W * V1**T */ igraphdtrmm_("Right", "Lower", "Transpose", "Unit", m, k, &c_b14, & v[v_offset], ldv, &work[work_offset], ldwork); /* C1 := C1 - W */ i__1 = *k; for (j = 1; j <= i__1; ++j) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { c__[i__ + j * c_dim1] -= work[i__ + j * work_dim1]; /* L50: */ } /* L60: */ } } } else { /* Let V = ( V1 ) ( V2 ) (last K rows) where V2 is unit upper triangular. */ if (igraphlsame_(side, "L")) { /* Form H * C or H**T * C where C = ( C1 ) ( C2 ) W := C**T * V = (C1**T * V1 + C2**T * V2) (stored in WORK) W := C2**T */ i__1 = *k; for (j = 1; j <= i__1; ++j) { igraphdcopy_(n, &c__[*m - *k + j + c_dim1], ldc, &work[j * work_dim1 + 1], &c__1); /* L70: */ } /* W := W * V2 */ igraphdtrmm_("Right", "Upper", "No transpose", "Unit", n, k, &c_b14, &v[*m - *k + 1 + v_dim1], ldv, &work[work_offset], ldwork); if (*m > *k) { /* W := W + C1**T * V1 */ i__1 = *m - *k; igraphdgemm_("Transpose", "No transpose", n, k, &i__1, &c_b14, & c__[c_offset], ldc, &v[v_offset], ldv, &c_b14, & work[work_offset], ldwork); } /* W := W * T**T or W * T */ igraphdtrmm_("Right", "Lower", transt, "Non-unit", n, k, &c_b14, &t[ t_offset], ldt, &work[work_offset], ldwork); /* C := C - V * W**T */ if (*m > *k) { /* C1 := C1 - V1 * W**T */ i__1 = *m - *k; igraphdgemm_("No transpose", "Transpose", &i__1, n, k, &c_b25, & v[v_offset], ldv, &work[work_offset], ldwork, & c_b14, &c__[c_offset], ldc) ; } /* W := W * V2**T */ igraphdtrmm_("Right", "Upper", "Transpose", "Unit", n, k, &c_b14, & v[*m - *k + 1 + v_dim1], ldv, &work[work_offset], ldwork); /* C2 := C2 - W**T */ i__1 = *k; for (j = 1; j <= i__1; ++j) { i__2 = *n; for (i__ = 1; i__ <= i__2; ++i__) { c__[*m - *k + j + i__ * c_dim1] -= work[i__ + j * work_dim1]; /* L80: */ } /* L90: */ } } else if (igraphlsame_(side, "R")) { /* Form C * H or C * H**T where C = ( C1 C2 ) W := C * V = (C1*V1 + C2*V2) (stored in WORK) W := C2 */ i__1 = *k; for (j = 1; j <= i__1; ++j) { igraphdcopy_(m, &c__[(*n - *k + j) * c_dim1 + 1], &c__1, &work[ j * work_dim1 + 1], &c__1); /* L100: */ } /* W := W * V2 */ igraphdtrmm_("Right", "Upper", "No transpose", "Unit", m, k, &c_b14, &v[*n - *k + 1 + v_dim1], ldv, &work[work_offset], ldwork); if (*n > *k) { /* W := W + C1 * V1 */ i__1 = *n - *k; igraphdgemm_("No transpose", "No transpose", m, k, &i__1, & c_b14, &c__[c_offset], ldc, &v[v_offset], ldv, & c_b14, &work[work_offset], ldwork); } /* W := W * T or W * T**T */ igraphdtrmm_("Right", "Lower", trans, "Non-unit", m, k, &c_b14, &t[ t_offset], ldt, &work[work_offset], ldwork); /* C := C - W * V**T */ if (*n > *k) { /* C1 := C1 - W * V1**T */ i__1 = *n - *k; igraphdgemm_("No transpose", "Transpose", m, &i__1, k, &c_b25, & work[work_offset], ldwork, &v[v_offset], ldv, & c_b14, &c__[c_offset], ldc) ; } /* W := W * V2**T */ igraphdtrmm_("Right", "Upper", "Transpose", "Unit", m, k, &c_b14, & v[*n - *k + 1 + v_dim1], ldv, &work[work_offset], ldwork); /* C2 := C2 - W */ i__1 = *k; for (j = 1; j <= i__1; ++j) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { c__[i__ + (*n - *k + j) * c_dim1] -= work[i__ + j * work_dim1]; /* L110: */ } /* L120: */ } } } } else if (igraphlsame_(storev, "R")) { if (igraphlsame_(direct, "F")) { /* Let V = ( V1 V2 ) (V1: first K columns) where V1 is unit upper triangular. */ if (igraphlsame_(side, "L")) { /* Form H * C or H**T * C where C = ( C1 ) ( C2 ) W := C**T * V**T = (C1**T * V1**T + C2**T * V2**T) (stored in WORK) W := C1**T */ i__1 = *k; for (j = 1; j <= i__1; ++j) { igraphdcopy_(n, &c__[j + c_dim1], ldc, &work[j * work_dim1 + 1], &c__1); /* L130: */ } /* W := W * V1**T */ igraphdtrmm_("Right", "Upper", "Transpose", "Unit", n, k, &c_b14, & v[v_offset], ldv, &work[work_offset], ldwork); if (*m > *k) { /* W := W + C2**T * V2**T */ i__1 = *m - *k; igraphdgemm_("Transpose", "Transpose", n, k, &i__1, &c_b14, & c__[*k + 1 + c_dim1], ldc, &v[(*k + 1) * v_dim1 + 1], ldv, &c_b14, &work[work_offset], ldwork); } /* W := W * T**T or W * T */ igraphdtrmm_("Right", "Upper", transt, "Non-unit", n, k, &c_b14, &t[ t_offset], ldt, &work[work_offset], ldwork); /* C := C - V**T * W**T */ if (*m > *k) { /* C2 := C2 - V2**T * W**T */ i__1 = *m - *k; igraphdgemm_("Transpose", "Transpose", &i__1, n, k, &c_b25, &v[( *k + 1) * v_dim1 + 1], ldv, &work[work_offset], ldwork, &c_b14, &c__[*k + 1 + c_dim1], ldc); } /* W := W * V1 */ igraphdtrmm_("Right", "Upper", "No transpose", "Unit", n, k, &c_b14, &v[v_offset], ldv, &work[work_offset], ldwork); /* C1 := C1 - W**T */ i__1 = *k; for (j = 1; j <= i__1; ++j) { i__2 = *n; for (i__ = 1; i__ <= i__2; ++i__) { c__[j + i__ * c_dim1] -= work[i__ + j * work_dim1]; /* L140: */ } /* L150: */ } } else if (igraphlsame_(side, "R")) { /* Form C * H or C * H**T where C = ( C1 C2 ) W := C * V**T = (C1*V1**T + C2*V2**T) (stored in WORK) W := C1 */ i__1 = *k; for (j = 1; j <= i__1; ++j) { igraphdcopy_(m, &c__[j * c_dim1 + 1], &c__1, &work[j * work_dim1 + 1], &c__1); /* L160: */ } /* W := W * V1**T */ igraphdtrmm_("Right", "Upper", "Transpose", "Unit", m, k, &c_b14, & v[v_offset], ldv, &work[work_offset], ldwork); if (*n > *k) { /* W := W + C2 * V2**T */ i__1 = *n - *k; igraphdgemm_("No transpose", "Transpose", m, k, &i__1, &c_b14, & c__[(*k + 1) * c_dim1 + 1], ldc, &v[(*k + 1) * v_dim1 + 1], ldv, &c_b14, &work[work_offset], ldwork); } /* W := W * T or W * T**T */ igraphdtrmm_("Right", "Upper", trans, "Non-unit", m, k, &c_b14, &t[ t_offset], ldt, &work[work_offset], ldwork); /* C := C - W * V */ if (*n > *k) { /* C2 := C2 - W * V2 */ i__1 = *n - *k; igraphdgemm_("No transpose", "No transpose", m, &i__1, k, & c_b25, &work[work_offset], ldwork, &v[(*k + 1) * v_dim1 + 1], ldv, &c_b14, &c__[(*k + 1) * c_dim1 + 1], ldc); } /* W := W * V1 */ igraphdtrmm_("Right", "Upper", "No transpose", "Unit", m, k, &c_b14, &v[v_offset], ldv, &work[work_offset], ldwork); /* C1 := C1 - W */ i__1 = *k; for (j = 1; j <= i__1; ++j) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { c__[i__ + j * c_dim1] -= work[i__ + j * work_dim1]; /* L170: */ } /* L180: */ } } } else { /* Let V = ( V1 V2 ) (V2: last K columns) where V2 is unit lower triangular. */ if (igraphlsame_(side, "L")) { /* Form H * C or H**T * C where C = ( C1 ) ( C2 ) W := C**T * V**T = (C1**T * V1**T + C2**T * V2**T) (stored in WORK) W := C2**T */ i__1 = *k; for (j = 1; j <= i__1; ++j) { igraphdcopy_(n, &c__[*m - *k + j + c_dim1], ldc, &work[j * work_dim1 + 1], &c__1); /* L190: */ } /* W := W * V2**T */ igraphdtrmm_("Right", "Lower", "Transpose", "Unit", n, k, &c_b14, & v[(*m - *k + 1) * v_dim1 + 1], ldv, &work[work_offset] , ldwork); if (*m > *k) { /* W := W + C1**T * V1**T */ i__1 = *m - *k; igraphdgemm_("Transpose", "Transpose", n, k, &i__1, &c_b14, & c__[c_offset], ldc, &v[v_offset], ldv, &c_b14, & work[work_offset], ldwork); } /* W := W * T**T or W * T */ igraphdtrmm_("Right", "Lower", transt, "Non-unit", n, k, &c_b14, &t[ t_offset], ldt, &work[work_offset], ldwork); /* C := C - V**T * W**T */ if (*m > *k) { /* C1 := C1 - V1**T * W**T */ i__1 = *m - *k; igraphdgemm_("Transpose", "Transpose", &i__1, n, k, &c_b25, &v[ v_offset], ldv, &work[work_offset], ldwork, & c_b14, &c__[c_offset], ldc); } /* W := W * V2 */ igraphdtrmm_("Right", "Lower", "No transpose", "Unit", n, k, &c_b14, &v[(*m - *k + 1) * v_dim1 + 1], ldv, &work[ work_offset], ldwork); /* C2 := C2 - W**T */ i__1 = *k; for (j = 1; j <= i__1; ++j) { i__2 = *n; for (i__ = 1; i__ <= i__2; ++i__) { c__[*m - *k + j + i__ * c_dim1] -= work[i__ + j * work_dim1]; /* L200: */ } /* L210: */ } } else if (igraphlsame_(side, "R")) { /* Form C * H or C * H' where C = ( C1 C2 ) W := C * V**T = (C1*V1**T + C2*V2**T) (stored in WORK) W := C2 */ i__1 = *k; for (j = 1; j <= i__1; ++j) { igraphdcopy_(m, &c__[(*n - *k + j) * c_dim1 + 1], &c__1, &work[ j * work_dim1 + 1], &c__1); /* L220: */ } /* W := W * V2**T */ igraphdtrmm_("Right", "Lower", "Transpose", "Unit", m, k, &c_b14, & v[(*n - *k + 1) * v_dim1 + 1], ldv, &work[work_offset] , ldwork); if (*n > *k) { /* W := W + C1 * V1**T */ i__1 = *n - *k; igraphdgemm_("No transpose", "Transpose", m, k, &i__1, &c_b14, & c__[c_offset], ldc, &v[v_offset], ldv, &c_b14, & work[work_offset], ldwork); } /* W := W * T or W * T**T */ igraphdtrmm_("Right", "Lower", trans, "Non-unit", m, k, &c_b14, &t[ t_offset], ldt, &work[work_offset], ldwork); /* C := C - W * V */ if (*n > *k) { /* C1 := C1 - W * V1 */ i__1 = *n - *k; igraphdgemm_("No transpose", "No transpose", m, &i__1, k, & c_b25, &work[work_offset], ldwork, &v[v_offset], ldv, &c_b14, &c__[c_offset], ldc); } /* W := W * V2 */ igraphdtrmm_("Right", "Lower", "No transpose", "Unit", m, k, &c_b14, &v[(*n - *k + 1) * v_dim1 + 1], ldv, &work[ work_offset], ldwork); /* C1 := C1 - W */ i__1 = *k; for (j = 1; j <= i__1; ++j) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { c__[i__ + (*n - *k + j) * c_dim1] -= work[i__ + j * work_dim1]; /* L230: */ } /* L240: */ } } } } return 0; /* End of DLARFB */ } /* igraphdlarfb_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlarrj.c0000644000076500000240000002662413524616145024274 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLARRJ performs refinement of the initial estimates of the eigenvalues of the matrix T. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLARRJ + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLARRJ( N, D, E2, IFIRST, ILAST, RTOL, OFFSET, W, WERR, WORK, IWORK, PIVMIN, SPDIAM, INFO ) INTEGER IFIRST, ILAST, INFO, N, OFFSET DOUBLE PRECISION PIVMIN, RTOL, SPDIAM INTEGER IWORK( * ) DOUBLE PRECISION D( * ), E2( * ), W( * ), $ WERR( * ), WORK( * ) > \par Purpose: ============= > > \verbatim > > Given the initial eigenvalue approximations of T, DLARRJ > does bisection to refine the eigenvalues of T, > W( IFIRST-OFFSET ) through W( ILAST-OFFSET ), to more accuracy. Initial > guesses for these eigenvalues are input in W, the corresponding estimate > of the error in these guesses in WERR. During bisection, intervals > [left, right] are maintained by storing their mid-points and > semi-widths in the arrays W and WERR respectively. > \endverbatim Arguments: ========== > \param[in] N > \verbatim > N is INTEGER > The order of the matrix. > \endverbatim > > \param[in] D > \verbatim > D is DOUBLE PRECISION array, dimension (N) > The N diagonal elements of T. > \endverbatim > > \param[in] E2 > \verbatim > E2 is DOUBLE PRECISION array, dimension (N-1) > The Squares of the (N-1) subdiagonal elements of T. > \endverbatim > > \param[in] IFIRST > \verbatim > IFIRST is INTEGER > The index of the first eigenvalue to be computed. > \endverbatim > > \param[in] ILAST > \verbatim > ILAST is INTEGER > The index of the last eigenvalue to be computed. > \endverbatim > > \param[in] RTOL > \verbatim > RTOL is DOUBLE PRECISION > Tolerance for the convergence of the bisection intervals. > An interval [LEFT,RIGHT] has converged if > RIGHT-LEFT.LT.RTOL*MAX(|LEFT|,|RIGHT|). > \endverbatim > > \param[in] OFFSET > \verbatim > OFFSET is INTEGER > Offset for the arrays W and WERR, i.e., the IFIRST-OFFSET > through ILAST-OFFSET elements of these arrays are to be used. > \endverbatim > > \param[in,out] W > \verbatim > W is DOUBLE PRECISION array, dimension (N) > On input, W( IFIRST-OFFSET ) through W( ILAST-OFFSET ) are > estimates of the eigenvalues of L D L^T indexed IFIRST through > ILAST. > On output, these estimates are refined. > \endverbatim > > \param[in,out] WERR > \verbatim > WERR is DOUBLE PRECISION array, dimension (N) > On input, WERR( IFIRST-OFFSET ) through WERR( ILAST-OFFSET ) are > the errors in the estimates of the corresponding elements in W. > On output, these errors are refined. > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (2*N) > Workspace. > \endverbatim > > \param[out] IWORK > \verbatim > IWORK is INTEGER array, dimension (2*N) > Workspace. > \endverbatim > > \param[in] PIVMIN > \verbatim > PIVMIN is DOUBLE PRECISION > The minimum pivot in the Sturm sequence for T. > \endverbatim > > \param[in] SPDIAM > \verbatim > SPDIAM is DOUBLE PRECISION > The spectral diameter of T. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > Error flag. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERauxiliary > \par Contributors: ================== > > Beresford Parlett, University of California, Berkeley, USA \n > Jim Demmel, University of California, Berkeley, USA \n > Inderjit Dhillon, University of Texas, Austin, USA \n > Osni Marques, LBNL/NERSC, USA \n > Christof Voemel, University of California, Berkeley, USA ===================================================================== Subroutine */ int igraphdlarrj_(integer *n, doublereal *d__, doublereal *e2, integer *ifirst, integer *ilast, doublereal *rtol, integer *offset, doublereal *w, doublereal *werr, doublereal *work, integer *iwork, doublereal *pivmin, doublereal *spdiam, integer *info) { /* System generated locals */ integer i__1, i__2; doublereal d__1, d__2; /* Builtin functions */ double log(doublereal); /* Local variables */ integer i__, j, k, p; doublereal s; integer i1, i2, ii; doublereal fac, mid; integer cnt; doublereal tmp, left; integer iter, nint, prev, next, savi1; doublereal right, width, dplus; integer olnint, maxitr; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ --iwork; --work; --werr; --w; --e2; --d__; /* Function Body */ *info = 0; maxitr = (integer) ((log(*spdiam + *pivmin) - log(*pivmin)) / log(2.)) + 2; /* Initialize unconverged intervals in [ WORK(2*I-1), WORK(2*I) ]. The Sturm Count, Count( WORK(2*I-1) ) is arranged to be I-1, while Count( WORK(2*I) ) is stored in IWORK( 2*I ). The integer IWORK( 2*I-1 ) for an unconverged interval is set to the index of the next unconverged interval, and is -1 or 0 for a converged interval. Thus a linked list of unconverged intervals is set up. */ i1 = *ifirst; i2 = *ilast; /* The number of unconverged intervals */ nint = 0; /* The last unconverged interval found */ prev = 0; i__1 = i2; for (i__ = i1; i__ <= i__1; ++i__) { k = i__ << 1; ii = i__ - *offset; left = w[ii] - werr[ii]; mid = w[ii]; right = w[ii] + werr[ii]; width = right - mid; /* Computing MAX */ d__1 = abs(left), d__2 = abs(right); tmp = max(d__1,d__2); /* The following test prevents the test of converged intervals */ if (width < *rtol * tmp) { /* This interval has already converged and does not need refinement. (Note that the gaps might change through refining the eigenvalues, however, they can only get bigger.) Remove it from the list. */ iwork[k - 1] = -1; /* Make sure that I1 always points to the first unconverged interval */ if (i__ == i1 && i__ < i2) { i1 = i__ + 1; } if (prev >= i1 && i__ <= i2) { iwork[(prev << 1) - 1] = i__ + 1; } } else { /* unconverged interval found */ prev = i__; /* Make sure that [LEFT,RIGHT] contains the desired eigenvalue Do while( CNT(LEFT).GT.I-1 ) */ fac = 1.; L20: cnt = 0; s = left; dplus = d__[1] - s; if (dplus < 0.) { ++cnt; } i__2 = *n; for (j = 2; j <= i__2; ++j) { dplus = d__[j] - s - e2[j - 1] / dplus; if (dplus < 0.) { ++cnt; } /* L30: */ } if (cnt > i__ - 1) { left -= werr[ii] * fac; fac *= 2.; goto L20; } /* Do while( CNT(RIGHT).LT.I ) */ fac = 1.; L50: cnt = 0; s = right; dplus = d__[1] - s; if (dplus < 0.) { ++cnt; } i__2 = *n; for (j = 2; j <= i__2; ++j) { dplus = d__[j] - s - e2[j - 1] / dplus; if (dplus < 0.) { ++cnt; } /* L60: */ } if (cnt < i__) { right += werr[ii] * fac; fac *= 2.; goto L50; } ++nint; iwork[k - 1] = i__ + 1; iwork[k] = cnt; } work[k - 1] = left; work[k] = right; /* L75: */ } savi1 = i1; /* Do while( NINT.GT.0 ), i.e. there are still unconverged intervals and while (ITER.LT.MAXITR) */ iter = 0; L80: prev = i1 - 1; i__ = i1; olnint = nint; i__1 = olnint; for (p = 1; p <= i__1; ++p) { k = i__ << 1; ii = i__ - *offset; next = iwork[k - 1]; left = work[k - 1]; right = work[k]; mid = (left + right) * .5; /* semiwidth of interval */ width = right - mid; /* Computing MAX */ d__1 = abs(left), d__2 = abs(right); tmp = max(d__1,d__2); if (width < *rtol * tmp || iter == maxitr) { /* reduce number of unconverged intervals */ --nint; /* Mark interval as converged. */ iwork[k - 1] = 0; if (i1 == i__) { i1 = next; } else { /* Prev holds the last unconverged interval previously examined */ if (prev >= i1) { iwork[(prev << 1) - 1] = next; } } i__ = next; goto L100; } prev = i__; /* Perform one bisection step */ cnt = 0; s = mid; dplus = d__[1] - s; if (dplus < 0.) { ++cnt; } i__2 = *n; for (j = 2; j <= i__2; ++j) { dplus = d__[j] - s - e2[j - 1] / dplus; if (dplus < 0.) { ++cnt; } /* L90: */ } if (cnt <= i__ - 1) { work[k - 1] = mid; } else { work[k] = mid; } i__ = next; L100: ; } ++iter; /* do another loop if there are still unconverged intervals However, in the last iteration, all intervals are accepted since this is the best we can do. */ if (nint > 0 && iter <= maxitr) { goto L80; } /* At this point, all the intervals have converged */ i__1 = *ilast; for (i__ = savi1; i__ <= i__1; ++i__) { k = i__ << 1; ii = i__ - *offset; /* All intervals marked by '0' have been refined. */ if (iwork[k - 1] == 0) { w[ii] = (work[k - 1] + work[k]) * .5; werr[ii] = work[k] - w[ii]; } /* L110: */ } return 0; /* End of DLARRJ */ } /* igraphdlarrj_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dgehd2.c0000644000076500000240000001744513524616145024154 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; /* > \brief \b DGEHD2 reduces a general square matrix to upper Hessenberg form using an unblocked algorithm. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DGEHD2 + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DGEHD2( N, ILO, IHI, A, LDA, TAU, WORK, INFO ) INTEGER IHI, ILO, INFO, LDA, N DOUBLE PRECISION A( LDA, * ), TAU( * ), WORK( * ) > \par Purpose: ============= > > \verbatim > > DGEHD2 reduces a real general matrix A to upper Hessenberg form H by > an orthogonal similarity transformation: Q**T * A * Q = H . > \endverbatim Arguments: ========== > \param[in] N > \verbatim > N is INTEGER > The order of the matrix A. N >= 0. > \endverbatim > > \param[in] ILO > \verbatim > ILO is INTEGER > \endverbatim > > \param[in] IHI > \verbatim > IHI is INTEGER > > It is assumed that A is already upper triangular in rows > and columns 1:ILO-1 and IHI+1:N. ILO and IHI are normally > set by a previous call to DGEBAL; otherwise they should be > set to 1 and N respectively. See Further Details. > 1 <= ILO <= IHI <= max(1,N). > \endverbatim > > \param[in,out] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,N) > On entry, the n by n general matrix to be reduced. > On exit, the upper triangle and the first subdiagonal of A > are overwritten with the upper Hessenberg matrix H, and the > elements below the first subdiagonal, with the array TAU, > represent the orthogonal matrix Q as a product of elementary > reflectors. See Further Details. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. LDA >= max(1,N). > \endverbatim > > \param[out] TAU > \verbatim > TAU is DOUBLE PRECISION array, dimension (N-1) > The scalar factors of the elementary reflectors (see Further > Details). > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (N) > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit. > < 0: if INFO = -i, the i-th argument had an illegal value. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleGEcomputational > \par Further Details: ===================== > > \verbatim > > The matrix Q is represented as a product of (ihi-ilo) elementary > reflectors > > Q = H(ilo) H(ilo+1) . . . H(ihi-1). > > Each H(i) has the form > > H(i) = I - tau * v * v**T > > where tau is a real scalar, and v is a real vector with > v(1:i) = 0, v(i+1) = 1 and v(ihi+1:n) = 0; v(i+2:ihi) is stored on > exit in A(i+2:ihi,i), and tau in TAU(i). > > The contents of A are illustrated by the following example, with > n = 7, ilo = 2 and ihi = 6: > > on entry, on exit, > > ( a a a a a a a ) ( a a h h h h a ) > ( a a a a a a ) ( a h h h h a ) > ( a a a a a a ) ( h h h h h h ) > ( a a a a a a ) ( v2 h h h h h ) > ( a a a a a a ) ( v2 v3 h h h h ) > ( a a a a a a ) ( v2 v3 v4 h h h ) > ( a ) ( a ) > > where a denotes an element of the original matrix A, h denotes a > modified element of the upper Hessenberg matrix H, and vi denotes an > element of the vector defining H(i). > \endverbatim > ===================================================================== Subroutine */ int igraphdgehd2_(integer *n, integer *ilo, integer *ihi, doublereal *a, integer *lda, doublereal *tau, doublereal *work, integer *info) { /* System generated locals */ integer a_dim1, a_offset, i__1, i__2, i__3; /* Local variables */ integer i__; doublereal aii; extern /* Subroutine */ int igraphdlarf_(char *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *), igraphdlarfg_(integer *, doublereal *, doublereal *, integer *, doublereal *), igraphxerbla_(char *, integer *, ftnlen); /* -- LAPACK computational routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Test the input parameters Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --tau; --work; /* Function Body */ *info = 0; if (*n < 0) { *info = -1; } else if (*ilo < 1 || *ilo > max(1,*n)) { *info = -2; } else if (*ihi < min(*ilo,*n) || *ihi > *n) { *info = -3; } else if (*lda < max(1,*n)) { *info = -5; } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DGEHD2", &i__1, (ftnlen)6); return 0; } i__1 = *ihi - 1; for (i__ = *ilo; i__ <= i__1; ++i__) { /* Compute elementary reflector H(i) to annihilate A(i+2:ihi,i) */ i__2 = *ihi - i__; /* Computing MIN */ i__3 = i__ + 2; igraphdlarfg_(&i__2, &a[i__ + 1 + i__ * a_dim1], &a[min(i__3,*n) + i__ * a_dim1], &c__1, &tau[i__]); aii = a[i__ + 1 + i__ * a_dim1]; a[i__ + 1 + i__ * a_dim1] = 1.; /* Apply H(i) to A(1:ihi,i+1:ihi) from the right */ i__2 = *ihi - i__; igraphdlarf_("Right", ihi, &i__2, &a[i__ + 1 + i__ * a_dim1], &c__1, &tau[ i__], &a[(i__ + 1) * a_dim1 + 1], lda, &work[1]); /* Apply H(i) to A(i+1:ihi,i+1:n) from the left */ i__2 = *ihi - i__; i__3 = *n - i__; igraphdlarf_("Left", &i__2, &i__3, &a[i__ + 1 + i__ * a_dim1], &c__1, &tau[ i__], &a[i__ + 1 + (i__ + 1) * a_dim1], lda, &work[1]); a[i__ + 1 + i__ * a_dim1] = aii; /* L10: */ } return 0; /* End of DGEHD2 */ } /* igraphdgehd2_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dgemm.c0000644000076500000240000002420313524616145024076 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Subroutine */ int igraphdgemm_(char *transa, char *transb, integer *m, integer * n, integer *k, doublereal *alpha, doublereal *a, integer *lda, doublereal *b, integer *ldb, doublereal *beta, doublereal *c__, integer *ldc) { /* System generated locals */ integer a_dim1, a_offset, b_dim1, b_offset, c_dim1, c_offset, i__1, i__2, i__3; /* Local variables */ integer i__, j, l, info; logical nota, notb; doublereal temp; integer ncola; extern logical igraphlsame_(char *, char *); integer nrowa, nrowb; extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); /* Purpose ======= DGEMM performs one of the matrix-matrix operations C := alpha*op( A )*op( B ) + beta*C, where op( X ) is one of op( X ) = X or op( X ) = X**T, alpha and beta are scalars, and A, B and C are matrices, with op( A ) an m by k matrix, op( B ) a k by n matrix and C an m by n matrix. Arguments ========== TRANSA - CHARACTER*1. On entry, TRANSA specifies the form of op( A ) to be used in the matrix multiplication as follows: TRANSA = 'N' or 'n', op( A ) = A. TRANSA = 'T' or 't', op( A ) = A**T. TRANSA = 'C' or 'c', op( A ) = A**T. Unchanged on exit. TRANSB - CHARACTER*1. On entry, TRANSB specifies the form of op( B ) to be used in the matrix multiplication as follows: TRANSB = 'N' or 'n', op( B ) = B. TRANSB = 'T' or 't', op( B ) = B**T. TRANSB = 'C' or 'c', op( B ) = B**T. Unchanged on exit. M - INTEGER. On entry, M specifies the number of rows of the matrix op( A ) and of the matrix C. M must be at least zero. Unchanged on exit. N - INTEGER. On entry, N specifies the number of columns of the matrix op( B ) and the number of columns of the matrix C. N must be at least zero. Unchanged on exit. K - INTEGER. On entry, K specifies the number of columns of the matrix op( A ) and the number of rows of the matrix op( B ). K must be at least zero. Unchanged on exit. ALPHA - DOUBLE PRECISION. On entry, ALPHA specifies the scalar alpha. Unchanged on exit. A - DOUBLE PRECISION array of DIMENSION ( LDA, ka ), where ka is k when TRANSA = 'N' or 'n', and is m otherwise. Before entry with TRANSA = 'N' or 'n', the leading m by k part of the array A must contain the matrix A, otherwise the leading k by m part of the array A must contain the matrix A. Unchanged on exit. LDA - INTEGER. On entry, LDA specifies the first dimension of A as declared in the calling (sub) program. When TRANSA = 'N' or 'n' then LDA must be at least max( 1, m ), otherwise LDA must be at least max( 1, k ). Unchanged on exit. B - DOUBLE PRECISION array of DIMENSION ( LDB, kb ), where kb is n when TRANSB = 'N' or 'n', and is k otherwise. Before entry with TRANSB = 'N' or 'n', the leading k by n part of the array B must contain the matrix B, otherwise the leading n by k part of the array B must contain the matrix B. Unchanged on exit. LDB - INTEGER. On entry, LDB specifies the first dimension of B as declared in the calling (sub) program. When TRANSB = 'N' or 'n' then LDB must be at least max( 1, k ), otherwise LDB must be at least max( 1, n ). Unchanged on exit. BETA - DOUBLE PRECISION. On entry, BETA specifies the scalar beta. When BETA is supplied as zero then C need not be set on input. Unchanged on exit. C - DOUBLE PRECISION array of DIMENSION ( LDC, n ). Before entry, the leading m by n part of the array C must contain the matrix C, except when beta is zero, in which case C need not be set on entry. On exit, the array C is overwritten by the m by n matrix ( alpha*op( A )*op( B ) + beta*C ). LDC - INTEGER. On entry, LDC specifies the first dimension of C as declared in the calling (sub) program. LDC must be at least max( 1, m ). Unchanged on exit. Further Details =============== Level 3 Blas routine. -- Written on 8-February-1989. Jack Dongarra, Argonne National Laboratory. Iain Duff, AERE Harwell. Jeremy Du Croz, Numerical Algorithms Group Ltd. Sven Hammarling, Numerical Algorithms Group Ltd. ===================================================================== Set NOTA and NOTB as true if A and B respectively are not transposed and set NROWA, NCOLA and NROWB as the number of rows and columns of A and the number of rows of B respectively. Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; b_dim1 = *ldb; b_offset = 1 + b_dim1; b -= b_offset; c_dim1 = *ldc; c_offset = 1 + c_dim1; c__ -= c_offset; /* Function Body */ nota = igraphlsame_(transa, "N"); notb = igraphlsame_(transb, "N"); if (nota) { nrowa = *m; ncola = *k; } else { nrowa = *k; ncola = *m; } if (notb) { nrowb = *k; } else { nrowb = *n; } /* Test the input parameters. */ info = 0; if (! nota && ! igraphlsame_(transa, "C") && ! igraphlsame_( transa, "T")) { info = 1; } else if (! notb && ! igraphlsame_(transb, "C") && ! igraphlsame_(transb, "T")) { info = 2; } else if (*m < 0) { info = 3; } else if (*n < 0) { info = 4; } else if (*k < 0) { info = 5; } else if (*lda < max(1,nrowa)) { info = 8; } else if (*ldb < max(1,nrowb)) { info = 10; } else if (*ldc < max(1,*m)) { info = 13; } if (info != 0) { igraphxerbla_("DGEMM ", &info, (ftnlen)6); return 0; } /* Quick return if possible. */ if (*m == 0 || *n == 0 || (*alpha == 0. || *k == 0) && *beta == 1.) { return 0; } /* And if alpha.eq.zero. */ if (*alpha == 0.) { if (*beta == 0.) { i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { c__[i__ + j * c_dim1] = 0.; /* L10: */ } /* L20: */ } } else { i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { c__[i__ + j * c_dim1] = *beta * c__[i__ + j * c_dim1]; /* L30: */ } /* L40: */ } } return 0; } /* Start the operations. */ if (notb) { if (nota) { /* Form C := alpha*A*B + beta*C. */ i__1 = *n; for (j = 1; j <= i__1; ++j) { if (*beta == 0.) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { c__[i__ + j * c_dim1] = 0.; /* L50: */ } } else if (*beta != 1.) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { c__[i__ + j * c_dim1] = *beta * c__[i__ + j * c_dim1]; /* L60: */ } } i__2 = *k; for (l = 1; l <= i__2; ++l) { if (b[l + j * b_dim1] != 0.) { temp = *alpha * b[l + j * b_dim1]; i__3 = *m; for (i__ = 1; i__ <= i__3; ++i__) { c__[i__ + j * c_dim1] += temp * a[i__ + l * a_dim1]; /* L70: */ } } /* L80: */ } /* L90: */ } } else { /* Form C := alpha*A**T*B + beta*C */ i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { temp = 0.; i__3 = *k; for (l = 1; l <= i__3; ++l) { temp += a[l + i__ * a_dim1] * b[l + j * b_dim1]; /* L100: */ } if (*beta == 0.) { c__[i__ + j * c_dim1] = *alpha * temp; } else { c__[i__ + j * c_dim1] = *alpha * temp + *beta * c__[ i__ + j * c_dim1]; } /* L110: */ } /* L120: */ } } } else { if (nota) { /* Form C := alpha*A*B**T + beta*C */ i__1 = *n; for (j = 1; j <= i__1; ++j) { if (*beta == 0.) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { c__[i__ + j * c_dim1] = 0.; /* L130: */ } } else if (*beta != 1.) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { c__[i__ + j * c_dim1] = *beta * c__[i__ + j * c_dim1]; /* L140: */ } } i__2 = *k; for (l = 1; l <= i__2; ++l) { if (b[j + l * b_dim1] != 0.) { temp = *alpha * b[j + l * b_dim1]; i__3 = *m; for (i__ = 1; i__ <= i__3; ++i__) { c__[i__ + j * c_dim1] += temp * a[i__ + l * a_dim1]; /* L150: */ } } /* L160: */ } /* L170: */ } } else { /* Form C := alpha*A**T*B**T + beta*C */ i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { temp = 0.; i__3 = *k; for (l = 1; l <= i__3; ++l) { temp += a[l + i__ * a_dim1] * b[j + l * b_dim1]; /* L180: */ } if (*beta == 0.) { c__[i__ + j * c_dim1] = *alpha * temp; } else { c__[i__ + j * c_dim1] = *alpha * temp + *beta * c__[ i__ + j * c_dim1]; } /* L190: */ } /* L200: */ } } } return 0; /* End of DGEMM . */ } /* igraphdgemm_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dpotrf.c0000644000076500000240000002112413524616145024302 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static integer c_n1 = -1; static doublereal c_b13 = -1.; static doublereal c_b14 = 1.; /* > \brief \b DPOTRF =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DPOTRF + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DPOTRF( UPLO, N, A, LDA, INFO ) CHARACTER UPLO INTEGER INFO, LDA, N DOUBLE PRECISION A( LDA, * ) > \par Purpose: ============= > > \verbatim > > DPOTRF computes the Cholesky factorization of a real symmetric > positive definite matrix A. > > The factorization has the form > A = U**T * U, if UPLO = 'U', or > A = L * L**T, if UPLO = 'L', > where U is an upper triangular matrix and L is lower triangular. > > This is the block version of the algorithm, calling Level 3 BLAS. > \endverbatim Arguments: ========== > \param[in] UPLO > \verbatim > UPLO is CHARACTER*1 > = 'U': Upper triangle of A is stored; > = 'L': Lower triangle of A is stored. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix A. N >= 0. > \endverbatim > > \param[in,out] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,N) > On entry, the symmetric matrix A. If UPLO = 'U', the leading > N-by-N upper triangular part of A contains the upper > triangular part of the matrix A, and the strictly lower > triangular part of A is not referenced. If UPLO = 'L', the > leading N-by-N lower triangular part of A contains the lower > triangular part of the matrix A, and the strictly upper > triangular part of A is not referenced. > > On exit, if INFO = 0, the factor U or L from the Cholesky > factorization A = U**T*U or A = L*L**T. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. LDA >= max(1,N). > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value > > 0: if INFO = i, the leading minor of order i is not > positive definite, and the factorization could not be > completed. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2011 > \ingroup doublePOcomputational ===================================================================== Subroutine */ int igraphdpotrf_(char *uplo, integer *n, doublereal *a, integer * lda, integer *info) { /* System generated locals */ integer a_dim1, a_offset, i__1, i__2, i__3, i__4; /* Local variables */ integer j, jb, nb; extern /* Subroutine */ int igraphdgemm_(char *, char *, integer *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *); extern logical igraphlsame_(char *, char *); extern /* Subroutine */ int igraphdtrsm_(char *, char *, char *, char *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *); logical upper; extern /* Subroutine */ int igraphdsyrk_(char *, char *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, doublereal *, integer *), igraphdpotf2_(char *, integer *, doublereal *, integer *, integer *), igraphxerbla_(char *, integer *, ftnlen); extern integer igraphilaenv_(integer *, char *, char *, integer *, integer *, integer *, integer *, ftnlen, ftnlen); /* -- LAPACK computational routine (version 3.4.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2011 ===================================================================== Test the input parameters. Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; /* Function Body */ *info = 0; upper = igraphlsame_(uplo, "U"); if (! upper && ! igraphlsame_(uplo, "L")) { *info = -1; } else if (*n < 0) { *info = -2; } else if (*lda < max(1,*n)) { *info = -4; } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DPOTRF", &i__1, (ftnlen)6); return 0; } /* Quick return if possible */ if (*n == 0) { return 0; } /* Determine the block size for this environment. */ nb = igraphilaenv_(&c__1, "DPOTRF", uplo, n, &c_n1, &c_n1, &c_n1, (ftnlen)6, ( ftnlen)1); if (nb <= 1 || nb >= *n) { /* Use unblocked code. */ igraphdpotf2_(uplo, n, &a[a_offset], lda, info); } else { /* Use blocked code. */ if (upper) { /* Compute the Cholesky factorization A = U**T*U. */ i__1 = *n; i__2 = nb; for (j = 1; i__2 < 0 ? j >= i__1 : j <= i__1; j += i__2) { /* Update and factorize the current diagonal block and test for non-positive-definiteness. Computing MIN */ i__3 = nb, i__4 = *n - j + 1; jb = min(i__3,i__4); i__3 = j - 1; igraphdsyrk_("Upper", "Transpose", &jb, &i__3, &c_b13, &a[j * a_dim1 + 1], lda, &c_b14, &a[j + j * a_dim1], lda); igraphdpotf2_("Upper", &jb, &a[j + j * a_dim1], lda, info); if (*info != 0) { goto L30; } if (j + jb <= *n) { /* Compute the current block row. */ i__3 = *n - j - jb + 1; i__4 = j - 1; igraphdgemm_("Transpose", "No transpose", &jb, &i__3, &i__4, & c_b13, &a[j * a_dim1 + 1], lda, &a[(j + jb) * a_dim1 + 1], lda, &c_b14, &a[j + (j + jb) * a_dim1], lda); i__3 = *n - j - jb + 1; igraphdtrsm_("Left", "Upper", "Transpose", "Non-unit", &jb, & i__3, &c_b14, &a[j + j * a_dim1], lda, &a[j + (j + jb) * a_dim1], lda); } /* L10: */ } } else { /* Compute the Cholesky factorization A = L*L**T. */ i__2 = *n; i__1 = nb; for (j = 1; i__1 < 0 ? j >= i__2 : j <= i__2; j += i__1) { /* Update and factorize the current diagonal block and test for non-positive-definiteness. Computing MIN */ i__3 = nb, i__4 = *n - j + 1; jb = min(i__3,i__4); i__3 = j - 1; igraphdsyrk_("Lower", "No transpose", &jb, &i__3, &c_b13, &a[j + a_dim1], lda, &c_b14, &a[j + j * a_dim1], lda); igraphdpotf2_("Lower", &jb, &a[j + j * a_dim1], lda, info); if (*info != 0) { goto L30; } if (j + jb <= *n) { /* Compute the current block column. */ i__3 = *n - j - jb + 1; i__4 = j - 1; igraphdgemm_("No transpose", "Transpose", &i__3, &jb, &i__4, & c_b13, &a[j + jb + a_dim1], lda, &a[j + a_dim1], lda, &c_b14, &a[j + jb + j * a_dim1], lda); i__3 = *n - j - jb + 1; igraphdtrsm_("Right", "Lower", "Transpose", "Non-unit", &i__3, & jb, &c_b14, &a[j + j * a_dim1], lda, &a[j + jb + j * a_dim1], lda); } /* L20: */ } } } goto L40; L30: *info = *info + j - 1; L40: return 0; /* End of DPOTRF */ } /* igraphdpotrf_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlarrd.c0000644000076500000240000007233413524616145024265 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static integer c_n1 = -1; static integer c__3 = 3; static integer c__2 = 2; static integer c__0 = 0; /* > \brief \b DLARRD computes the eigenvalues of a symmetric tridiagonal matrix to suitable accuracy. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLARRD + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLARRD( RANGE, ORDER, N, VL, VU, IL, IU, GERS, RELTOL, D, E, E2, PIVMIN, NSPLIT, ISPLIT, M, W, WERR, WL, WU, IBLOCK, INDEXW, WORK, IWORK, INFO ) CHARACTER ORDER, RANGE INTEGER IL, INFO, IU, M, N, NSPLIT DOUBLE PRECISION PIVMIN, RELTOL, VL, VU, WL, WU INTEGER IBLOCK( * ), INDEXW( * ), $ ISPLIT( * ), IWORK( * ) DOUBLE PRECISION D( * ), E( * ), E2( * ), $ GERS( * ), W( * ), WERR( * ), WORK( * ) > \par Purpose: ============= > > \verbatim > > DLARRD computes the eigenvalues of a symmetric tridiagonal > matrix T to suitable accuracy. This is an auxiliary code to be > called from DSTEMR. > The user may ask for all eigenvalues, all eigenvalues > in the half-open interval (VL, VU], or the IL-th through IU-th > eigenvalues. > > To avoid overflow, the matrix must be scaled so that its > largest element is no greater than overflow**(1/2) * underflow**(1/4) in absolute value, and for greatest > accuracy, it should not be much smaller than that. > > See W. Kahan "Accurate Eigenvalues of a Symmetric Tridiagonal > Matrix", Report CS41, Computer Science Dept., Stanford > University, July 21, 1966. > \endverbatim Arguments: ========== > \param[in] RANGE > \verbatim > RANGE is CHARACTER*1 > = 'A': ("All") all eigenvalues will be found. > = 'V': ("Value") all eigenvalues in the half-open interval > (VL, VU] will be found. > = 'I': ("Index") the IL-th through IU-th eigenvalues (of the > entire matrix) will be found. > \endverbatim > > \param[in] ORDER > \verbatim > ORDER is CHARACTER*1 > = 'B': ("By Block") the eigenvalues will be grouped by > split-off block (see IBLOCK, ISPLIT) and > ordered from smallest to largest within > the block. > = 'E': ("Entire matrix") > the eigenvalues for the entire matrix > will be ordered from smallest to > largest. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the tridiagonal matrix T. N >= 0. > \endverbatim > > \param[in] VL > \verbatim > VL is DOUBLE PRECISION > \endverbatim > > \param[in] VU > \verbatim > VU is DOUBLE PRECISION > If RANGE='V', the lower and upper bounds of the interval to > be searched for eigenvalues. Eigenvalues less than or equal > to VL, or greater than VU, will not be returned. VL < VU. > Not referenced if RANGE = 'A' or 'I'. > \endverbatim > > \param[in] IL > \verbatim > IL is INTEGER > \endverbatim > > \param[in] IU > \verbatim > IU is INTEGER > If RANGE='I', the indices (in ascending order) of the > smallest and largest eigenvalues to be returned. > 1 <= IL <= IU <= N, if N > 0; IL = 1 and IU = 0 if N = 0. > Not referenced if RANGE = 'A' or 'V'. > \endverbatim > > \param[in] GERS > \verbatim > GERS is DOUBLE PRECISION array, dimension (2*N) > The N Gerschgorin intervals (the i-th Gerschgorin interval > is (GERS(2*i-1), GERS(2*i)). > \endverbatim > > \param[in] RELTOL > \verbatim > RELTOL is DOUBLE PRECISION > The minimum relative width of an interval. When an interval > is narrower than RELTOL times the larger (in > magnitude) endpoint, then it is considered to be > sufficiently small, i.e., converged. Note: this should > always be at least radix*machine epsilon. > \endverbatim > > \param[in] D > \verbatim > D is DOUBLE PRECISION array, dimension (N) > The n diagonal elements of the tridiagonal matrix T. > \endverbatim > > \param[in] E > \verbatim > E is DOUBLE PRECISION array, dimension (N-1) > The (n-1) off-diagonal elements of the tridiagonal matrix T. > \endverbatim > > \param[in] E2 > \verbatim > E2 is DOUBLE PRECISION array, dimension (N-1) > The (n-1) squared off-diagonal elements of the tridiagonal matrix T. > \endverbatim > > \param[in] PIVMIN > \verbatim > PIVMIN is DOUBLE PRECISION > The minimum pivot allowed in the Sturm sequence for T. > \endverbatim > > \param[in] NSPLIT > \verbatim > NSPLIT is INTEGER > The number of diagonal blocks in the matrix T. > 1 <= NSPLIT <= N. > \endverbatim > > \param[in] ISPLIT > \verbatim > ISPLIT is INTEGER array, dimension (N) > The splitting points, at which T breaks up into submatrices. > The first submatrix consists of rows/columns 1 to ISPLIT(1), > the second of rows/columns ISPLIT(1)+1 through ISPLIT(2), > etc., and the NSPLIT-th consists of rows/columns > ISPLIT(NSPLIT-1)+1 through ISPLIT(NSPLIT)=N. > (Only the first NSPLIT elements will actually be used, but > since the user cannot know a priori what value NSPLIT will > have, N words must be reserved for ISPLIT.) > \endverbatim > > \param[out] M > \verbatim > M is INTEGER > The actual number of eigenvalues found. 0 <= M <= N. > (See also the description of INFO=2,3.) > \endverbatim > > \param[out] W > \verbatim > W is DOUBLE PRECISION array, dimension (N) > On exit, the first M elements of W will contain the > eigenvalue approximations. DLARRD computes an interval > I_j = (a_j, b_j] that includes eigenvalue j. The eigenvalue > approximation is given as the interval midpoint > W(j)= ( a_j + b_j)/2. The corresponding error is bounded by > WERR(j) = abs( a_j - b_j)/2 > \endverbatim > > \param[out] WERR > \verbatim > WERR is DOUBLE PRECISION array, dimension (N) > The error bound on the corresponding eigenvalue approximation > in W. > \endverbatim > > \param[out] WL > \verbatim > WL is DOUBLE PRECISION > \endverbatim > > \param[out] WU > \verbatim > WU is DOUBLE PRECISION > The interval (WL, WU] contains all the wanted eigenvalues. > If RANGE='V', then WL=VL and WU=VU. > If RANGE='A', then WL and WU are the global Gerschgorin bounds > on the spectrum. > If RANGE='I', then WL and WU are computed by DLAEBZ from the > index range specified. > \endverbatim > > \param[out] IBLOCK > \verbatim > IBLOCK is INTEGER array, dimension (N) > At each row/column j where E(j) is zero or small, the > matrix T is considered to split into a block diagonal > matrix. On exit, if INFO = 0, IBLOCK(i) specifies to which > block (from 1 to the number of blocks) the eigenvalue W(i) > belongs. (DLARRD may use the remaining N-M elements as > workspace.) > \endverbatim > > \param[out] INDEXW > \verbatim > INDEXW is INTEGER array, dimension (N) > The indices of the eigenvalues within each block (submatrix); > for example, INDEXW(i)= j and IBLOCK(i)=k imply that the > i-th eigenvalue W(i) is the j-th eigenvalue in block k. > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (4*N) > \endverbatim > > \param[out] IWORK > \verbatim > IWORK is INTEGER array, dimension (3*N) > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value > > 0: some or all of the eigenvalues failed to converge or > were not computed: > =1 or 3: Bisection failed to converge for some > eigenvalues; these eigenvalues are flagged by a > negative block number. The effect is that the > eigenvalues may not be as accurate as the > absolute and relative tolerances. This is > generally caused by unexpectedly inaccurate > arithmetic. > =2 or 3: RANGE='I' only: Not all of the eigenvalues > IL:IU were found. > Effect: M < IU+1-IL > Cause: non-monotonic arithmetic, causing the > Sturm sequence to be non-monotonic. > Cure: recalculate, using RANGE='A', and pick > out eigenvalues IL:IU. In some cases, > increasing the PARAMETER "FUDGE" may > make things work. > = 4: RANGE='I', and the Gershgorin interval > initially used was too small. No eigenvalues > were computed. > Probable cause: your machine has sloppy > floating-point arithmetic. > Cure: Increase the PARAMETER "FUDGE", > recompile, and try again. > \endverbatim > \par Internal Parameters: ========================= > > \verbatim > FUDGE DOUBLE PRECISION, default = 2 > A "fudge factor" to widen the Gershgorin intervals. Ideally, > a value of 1 should work, but on machines with sloppy > arithmetic, this needs to be larger. The default for > publicly released versions should be large enough to handle > the worst machine around. Note that this has no effect > on accuracy of the solution. > \endverbatim > > \par Contributors: ================== > > W. Kahan, University of California, Berkeley, USA \n > Beresford Parlett, University of California, Berkeley, USA \n > Jim Demmel, University of California, Berkeley, USA \n > Inderjit Dhillon, University of Texas, Austin, USA \n > Osni Marques, LBNL/NERSC, USA \n > Christof Voemel, University of California, Berkeley, USA \n Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERauxiliary ===================================================================== Subroutine */ int igraphdlarrd_(char *range, char *order, integer *n, doublereal *vl, doublereal *vu, integer *il, integer *iu, doublereal *gers, doublereal *reltol, doublereal *d__, doublereal *e, doublereal *e2, doublereal *pivmin, integer *nsplit, integer *isplit, integer *m, doublereal *w, doublereal *werr, doublereal *wl, doublereal *wu, integer *iblock, integer *indexw, doublereal *work, integer *iwork, integer *info) { /* System generated locals */ integer i__1, i__2, i__3; doublereal d__1, d__2; /* Builtin functions */ double log(doublereal); /* Local variables */ integer i__, j, ib, ie, je, nb; doublereal gl; integer im, in; doublereal gu; integer iw, jee; doublereal eps; integer nwl; doublereal wlu, wul; integer nwu; doublereal tmp1, tmp2; integer iend, jblk, ioff, iout, itmp1, itmp2, jdisc; extern logical igraphlsame_(char *, char *); integer iinfo; doublereal atoli; integer iwoff, itmax; doublereal wkill, rtoli, uflow, tnorm; extern doublereal igraphdlamch_(char *); integer ibegin; extern /* Subroutine */ int igraphdlaebz_(integer *, integer *, integer *, integer *, integer *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, integer *, integer *); integer irange, idiscl, idumma[1]; extern integer igraphilaenv_(integer *, char *, char *, integer *, integer *, integer *, integer *, ftnlen, ftnlen); integer idiscu; logical ncnvrg, toofew; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ --iwork; --work; --indexw; --iblock; --werr; --w; --isplit; --e2; --e; --d__; --gers; /* Function Body */ *info = 0; /* Decode RANGE */ if (igraphlsame_(range, "A")) { irange = 1; } else if (igraphlsame_(range, "V")) { irange = 2; } else if (igraphlsame_(range, "I")) { irange = 3; } else { irange = 0; } /* Check for Errors */ if (irange <= 0) { *info = -1; } else if (! (igraphlsame_(order, "B") || igraphlsame_(order, "E"))) { *info = -2; } else if (*n < 0) { *info = -3; } else if (irange == 2) { if (*vl >= *vu) { *info = -5; } } else if (irange == 3 && (*il < 1 || *il > max(1,*n))) { *info = -6; } else if (irange == 3 && (*iu < min(*n,*il) || *iu > *n)) { *info = -7; } if (*info != 0) { return 0; } /* Initialize error flags */ *info = 0; ncnvrg = FALSE_; toofew = FALSE_; /* Quick return if possible */ *m = 0; if (*n == 0) { return 0; } /* Simplification: */ if (irange == 3 && *il == 1 && *iu == *n) { irange = 1; } /* Get machine constants */ eps = igraphdlamch_("P"); uflow = igraphdlamch_("U"); /* Special Case when N=1 Treat case of 1x1 matrix for quick return */ if (*n == 1) { if (irange == 1 || irange == 2 && d__[1] > *vl && d__[1] <= *vu || irange == 3 && *il == 1 && *iu == 1) { *m = 1; w[1] = d__[1]; /* The computation error of the eigenvalue is zero */ werr[1] = 0.; iblock[1] = 1; indexw[1] = 1; } return 0; } /* NB is the minimum vector length for vector bisection, or 0 if only scalar is to be done. */ nb = igraphilaenv_(&c__1, "DSTEBZ", " ", n, &c_n1, &c_n1, &c_n1, (ftnlen)6, ( ftnlen)1); if (nb <= 1) { nb = 0; } /* Find global spectral radius */ gl = d__[1]; gu = d__[1]; i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { /* Computing MIN */ d__1 = gl, d__2 = gers[(i__ << 1) - 1]; gl = min(d__1,d__2); /* Computing MAX */ d__1 = gu, d__2 = gers[i__ * 2]; gu = max(d__1,d__2); /* L5: */ } /* Compute global Gerschgorin bounds and spectral diameter Computing MAX */ d__1 = abs(gl), d__2 = abs(gu); tnorm = max(d__1,d__2); gl = gl - tnorm * 2. * eps * *n - *pivmin * 4.; gu = gu + tnorm * 2. * eps * *n + *pivmin * 4.; /* [JAN/28/2009] remove the line below since SPDIAM variable not use SPDIAM = GU - GL Input arguments for DLAEBZ: The relative tolerance. An interval (a,b] lies within "relative tolerance" if b-a < RELTOL*max(|a|,|b|), */ rtoli = *reltol; /* Set the absolute tolerance for interval convergence to zero to force interval convergence based on relative size of the interval. This is dangerous because intervals might not converge when RELTOL is small. But at least a very small number should be selected so that for strongly graded matrices, the code can get relatively accurate eigenvalues. */ atoli = uflow * 4. + *pivmin * 4.; if (irange == 3) { /* RANGE='I': Compute an interval containing eigenvalues IL through IU. The initial interval [GL,GU] from the global Gerschgorin bounds GL and GU is refined by DLAEBZ. */ itmax = (integer) ((log(tnorm + *pivmin) - log(*pivmin)) / log(2.)) + 2; work[*n + 1] = gl; work[*n + 2] = gl; work[*n + 3] = gu; work[*n + 4] = gu; work[*n + 5] = gl; work[*n + 6] = gu; iwork[1] = -1; iwork[2] = -1; iwork[3] = *n + 1; iwork[4] = *n + 1; iwork[5] = *il - 1; iwork[6] = *iu; igraphdlaebz_(&c__3, &itmax, n, &c__2, &c__2, &nb, &atoli, &rtoli, pivmin, & d__[1], &e[1], &e2[1], &iwork[5], &work[*n + 1], &work[*n + 5] , &iout, &iwork[1], &w[1], &iblock[1], &iinfo); if (iinfo != 0) { *info = iinfo; return 0; } /* On exit, output intervals may not be ordered by ascending negcount */ if (iwork[6] == *iu) { *wl = work[*n + 1]; wlu = work[*n + 3]; nwl = iwork[1]; *wu = work[*n + 4]; wul = work[*n + 2]; nwu = iwork[4]; } else { *wl = work[*n + 2]; wlu = work[*n + 4]; nwl = iwork[2]; *wu = work[*n + 3]; wul = work[*n + 1]; nwu = iwork[3]; } /* On exit, the interval [WL, WLU] contains a value with negcount NWL, and [WUL, WU] contains a value with negcount NWU. */ if (nwl < 0 || nwl >= *n || nwu < 1 || nwu > *n) { *info = 4; return 0; } } else if (irange == 2) { *wl = *vl; *wu = *vu; } else if (irange == 1) { *wl = gl; *wu = gu; } /* Find Eigenvalues -- Loop Over blocks and recompute NWL and NWU. NWL accumulates the number of eigenvalues .le. WL, NWU accumulates the number of eigenvalues .le. WU */ *m = 0; iend = 0; *info = 0; nwl = 0; nwu = 0; i__1 = *nsplit; for (jblk = 1; jblk <= i__1; ++jblk) { ioff = iend; ibegin = ioff + 1; iend = isplit[jblk]; in = iend - ioff; if (in == 1) { /* 1x1 block */ if (*wl >= d__[ibegin] - *pivmin) { ++nwl; } if (*wu >= d__[ibegin] - *pivmin) { ++nwu; } if (irange == 1 || *wl < d__[ibegin] - *pivmin && *wu >= d__[ ibegin] - *pivmin) { ++(*m); w[*m] = d__[ibegin]; werr[*m] = 0.; /* The gap for a single block doesn't matter for the later algorithm and is assigned an arbitrary large value */ iblock[*m] = jblk; indexw[*m] = 1; } /* Disabled 2x2 case because of a failure on the following matrix RANGE = 'I', IL = IU = 4 Original Tridiagonal, d = [ -0.150102010615740E+00 -0.849897989384260E+00 -0.128208148052635E-15 0.128257718286320E-15 ]; e = [ -0.357171383266986E+00 -0.180411241501588E-15 -0.175152352710251E-15 ]; ELSE IF( IN.EQ.2 ) THEN * 2x2 block DISC = SQRT( (HALF*(D(IBEGIN)-D(IEND)))**2 + E(IBEGIN)**2 ) TMP1 = HALF*(D(IBEGIN)+D(IEND)) L1 = TMP1 - DISC IF( WL.GE. L1-PIVMIN ) $ NWL = NWL + 1 IF( WU.GE. L1-PIVMIN ) $ NWU = NWU + 1 IF( IRANGE.EQ.ALLRNG .OR. ( WL.LT.L1-PIVMIN .AND. WU.GE. $ L1-PIVMIN ) ) THEN M = M + 1 W( M ) = L1 * The uncertainty of eigenvalues of a 2x2 matrix is very small WERR( M ) = EPS * ABS( W( M ) ) * TWO IBLOCK( M ) = JBLK INDEXW( M ) = 1 ENDIF L2 = TMP1 + DISC IF( WL.GE. L2-PIVMIN ) $ NWL = NWL + 1 IF( WU.GE. L2-PIVMIN ) $ NWU = NWU + 1 IF( IRANGE.EQ.ALLRNG .OR. ( WL.LT.L2-PIVMIN .AND. WU.GE. $ L2-PIVMIN ) ) THEN M = M + 1 W( M ) = L2 * The uncertainty of eigenvalues of a 2x2 matrix is very small WERR( M ) = EPS * ABS( W( M ) ) * TWO IBLOCK( M ) = JBLK INDEXW( M ) = 2 ENDIF */ } else { /* General Case - block of size IN >= 2 Compute local Gerschgorin interval and use it as the initial interval for DLAEBZ */ gu = d__[ibegin]; gl = d__[ibegin]; tmp1 = 0.; i__2 = iend; for (j = ibegin; j <= i__2; ++j) { /* Computing MIN */ d__1 = gl, d__2 = gers[(j << 1) - 1]; gl = min(d__1,d__2); /* Computing MAX */ d__1 = gu, d__2 = gers[j * 2]; gu = max(d__1,d__2); /* L40: */ } /* [JAN/28/2009] change SPDIAM by TNORM in lines 2 and 3 thereafter line 1: remove computation of SPDIAM (not useful anymore) SPDIAM = GU - GL GL = GL - FUDGE*SPDIAM*EPS*IN - FUDGE*PIVMIN GU = GU + FUDGE*SPDIAM*EPS*IN + FUDGE*PIVMIN */ gl = gl - tnorm * 2. * eps * in - *pivmin * 2.; gu = gu + tnorm * 2. * eps * in + *pivmin * 2.; if (irange > 1) { if (gu < *wl) { /* the local block contains none of the wanted eigenvalues */ nwl += in; nwu += in; goto L70; } /* refine search interval if possible, only range (WL,WU] matters */ gl = max(gl,*wl); gu = min(gu,*wu); if (gl >= gu) { goto L70; } } /* Find negcount of initial interval boundaries GL and GU */ work[*n + 1] = gl; work[*n + in + 1] = gu; igraphdlaebz_(&c__1, &c__0, &in, &in, &c__1, &nb, &atoli, &rtoli, pivmin, &d__[ibegin], &e[ibegin], &e2[ibegin], idumma, & work[*n + 1], &work[*n + (in << 1) + 1], &im, &iwork[1], & w[*m + 1], &iblock[*m + 1], &iinfo); if (iinfo != 0) { *info = iinfo; return 0; } nwl += iwork[1]; nwu += iwork[in + 1]; iwoff = *m - iwork[1]; /* Compute Eigenvalues */ itmax = (integer) ((log(gu - gl + *pivmin) - log(*pivmin)) / log( 2.)) + 2; igraphdlaebz_(&c__2, &itmax, &in, &in, &c__1, &nb, &atoli, &rtoli, pivmin, &d__[ibegin], &e[ibegin], &e2[ibegin], idumma, & work[*n + 1], &work[*n + (in << 1) + 1], &iout, &iwork[1], &w[*m + 1], &iblock[*m + 1], &iinfo); if (iinfo != 0) { *info = iinfo; return 0; } /* Copy eigenvalues into W and IBLOCK Use -JBLK for block number for unconverged eigenvalues. Loop over the number of output intervals from DLAEBZ */ i__2 = iout; for (j = 1; j <= i__2; ++j) { /* eigenvalue approximation is middle point of interval */ tmp1 = (work[j + *n] + work[j + in + *n]) * .5; /* semi length of error interval */ tmp2 = (d__1 = work[j + *n] - work[j + in + *n], abs(d__1)) * .5; if (j > iout - iinfo) { /* Flag non-convergence. */ ncnvrg = TRUE_; ib = -jblk; } else { ib = jblk; } i__3 = iwork[j + in] + iwoff; for (je = iwork[j] + 1 + iwoff; je <= i__3; ++je) { w[je] = tmp1; werr[je] = tmp2; indexw[je] = je - iwoff; iblock[je] = ib; /* L50: */ } /* L60: */ } *m += im; } L70: ; } /* If RANGE='I', then (WL,WU) contains eigenvalues NWL+1,...,NWU If NWL+1 < IL or NWU > IU, discard extra eigenvalues. */ if (irange == 3) { idiscl = *il - 1 - nwl; idiscu = nwu - *iu; if (idiscl > 0) { im = 0; i__1 = *m; for (je = 1; je <= i__1; ++je) { /* Remove some of the smallest eigenvalues from the left so that at the end IDISCL =0. Move all eigenvalues up to the left. */ if (w[je] <= wlu && idiscl > 0) { --idiscl; } else { ++im; w[im] = w[je]; werr[im] = werr[je]; indexw[im] = indexw[je]; iblock[im] = iblock[je]; } /* L80: */ } *m = im; } if (idiscu > 0) { /* Remove some of the largest eigenvalues from the right so that at the end IDISCU =0. Move all eigenvalues up to the left. */ im = *m + 1; for (je = *m; je >= 1; --je) { if (w[je] >= wul && idiscu > 0) { --idiscu; } else { --im; w[im] = w[je]; werr[im] = werr[je]; indexw[im] = indexw[je]; iblock[im] = iblock[je]; } /* L81: */ } jee = 0; i__1 = *m; for (je = im; je <= i__1; ++je) { ++jee; w[jee] = w[je]; werr[jee] = werr[je]; indexw[jee] = indexw[je]; iblock[jee] = iblock[je]; /* L82: */ } *m = *m - im + 1; } if (idiscl > 0 || idiscu > 0) { /* Code to deal with effects of bad arithmetic. (If N(w) is monotone non-decreasing, this should never happen.) Some low eigenvalues to be discarded are not in (WL,WLU], or high eigenvalues to be discarded are not in (WUL,WU] so just kill off the smallest IDISCL/largest IDISCU eigenvalues, by marking the corresponding IBLOCK = 0 */ if (idiscl > 0) { wkill = *wu; i__1 = idiscl; for (jdisc = 1; jdisc <= i__1; ++jdisc) { iw = 0; i__2 = *m; for (je = 1; je <= i__2; ++je) { if (iblock[je] != 0 && (w[je] < wkill || iw == 0)) { iw = je; wkill = w[je]; } /* L90: */ } iblock[iw] = 0; /* L100: */ } } if (idiscu > 0) { wkill = *wl; i__1 = idiscu; for (jdisc = 1; jdisc <= i__1; ++jdisc) { iw = 0; i__2 = *m; for (je = 1; je <= i__2; ++je) { if (iblock[je] != 0 && (w[je] >= wkill || iw == 0)) { iw = je; wkill = w[je]; } /* L110: */ } iblock[iw] = 0; /* L120: */ } } /* Now erase all eigenvalues with IBLOCK set to zero */ im = 0; i__1 = *m; for (je = 1; je <= i__1; ++je) { if (iblock[je] != 0) { ++im; w[im] = w[je]; werr[im] = werr[je]; indexw[im] = indexw[je]; iblock[im] = iblock[je]; } /* L130: */ } *m = im; } if (idiscl < 0 || idiscu < 0) { toofew = TRUE_; } } if (irange == 1 && *m != *n || irange == 3 && *m != *iu - *il + 1) { toofew = TRUE_; } /* If ORDER='B', do nothing the eigenvalues are already sorted by block. If ORDER='E', sort the eigenvalues from smallest to largest */ if (igraphlsame_(order, "E") && *nsplit > 1) { i__1 = *m - 1; for (je = 1; je <= i__1; ++je) { ie = 0; tmp1 = w[je]; i__2 = *m; for (j = je + 1; j <= i__2; ++j) { if (w[j] < tmp1) { ie = j; tmp1 = w[j]; } /* L140: */ } if (ie != 0) { tmp2 = werr[ie]; itmp1 = iblock[ie]; itmp2 = indexw[ie]; w[ie] = w[je]; werr[ie] = werr[je]; iblock[ie] = iblock[je]; indexw[ie] = indexw[je]; w[je] = tmp1; werr[je] = tmp2; iblock[je] = itmp1; indexw[je] = itmp2; } /* L150: */ } } *info = 0; if (ncnvrg) { ++(*info); } if (toofew) { *info += 2; } return 0; /* End of DLARRD */ } /* igraphdlarrd_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlacpy.c0000644000076500000240000001167113524616145024266 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLACPY copies all or part of one two-dimensional array to another. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLACPY + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLACPY( UPLO, M, N, A, LDA, B, LDB ) CHARACTER UPLO INTEGER LDA, LDB, M, N DOUBLE PRECISION A( LDA, * ), B( LDB, * ) > \par Purpose: ============= > > \verbatim > > DLACPY copies all or part of a two-dimensional matrix A to another > matrix B. > \endverbatim Arguments: ========== > \param[in] UPLO > \verbatim > UPLO is CHARACTER*1 > Specifies the part of the matrix A to be copied to B. > = 'U': Upper triangular part > = 'L': Lower triangular part > Otherwise: All of the matrix A > \endverbatim > > \param[in] M > \verbatim > M is INTEGER > The number of rows of the matrix A. M >= 0. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The number of columns of the matrix A. N >= 0. > \endverbatim > > \param[in] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,N) > The m by n matrix A. If UPLO = 'U', only the upper triangle > or trapezoid is accessed; if UPLO = 'L', only the lower > triangle or trapezoid is accessed. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. LDA >= max(1,M). > \endverbatim > > \param[out] B > \verbatim > B is DOUBLE PRECISION array, dimension (LDB,N) > On exit, B = A in the locations specified by UPLO. > \endverbatim > > \param[in] LDB > \verbatim > LDB is INTEGER > The leading dimension of the array B. LDB >= max(1,M). > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERauxiliary ===================================================================== Subroutine */ int igraphdlacpy_(char *uplo, integer *m, integer *n, doublereal * a, integer *lda, doublereal *b, integer *ldb) { /* System generated locals */ integer a_dim1, a_offset, b_dim1, b_offset, i__1, i__2; /* Local variables */ integer i__, j; extern logical igraphlsame_(char *, char *); /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; b_dim1 = *ldb; b_offset = 1 + b_dim1; b -= b_offset; /* Function Body */ if (igraphlsame_(uplo, "U")) { i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = min(j,*m); for (i__ = 1; i__ <= i__2; ++i__) { b[i__ + j * b_dim1] = a[i__ + j * a_dim1]; /* L10: */ } /* L20: */ } } else if (igraphlsame_(uplo, "L")) { i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = *m; for (i__ = j; i__ <= i__2; ++i__) { b[i__ + j * b_dim1] = a[i__ + j * a_dim1]; /* L30: */ } /* L40: */ } } else { i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { b[i__ + j * b_dim1] = a[i__ + j * a_dim1]; /* L50: */ } /* L60: */ } } return 0; /* End of DLACPY */ } /* igraphdlacpy_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dgetv0.c0000644000076500000240000003543313524616145024205 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static doublereal c_b24 = 1.; static doublereal c_b26 = 0.; static doublereal c_b29 = -1.; /* ----------------------------------------------------------------------- \BeginDoc \Name: dgetv0 \Description: Generate a random initial residual vector for the Arnoldi process. Force the residual vector to be in the range of the operator OP. \Usage: call dgetv0 ( IDO, BMAT, ITRY, INITV, N, J, V, LDV, RESID, RNORM, IPNTR, WORKD, IERR ) \Arguments IDO Integer. (INPUT/OUTPUT) Reverse communication flag. IDO must be zero on the first call to dgetv0. ------------------------------------------------------------- IDO = 0: first call to the reverse communication interface IDO = -1: compute Y = OP * X where IPNTR(1) is the pointer into WORKD for X, IPNTR(2) is the pointer into WORKD for Y. This is for the initialization phase to force the starting vector into the range of OP. IDO = 2: compute Y = B * X where IPNTR(1) is the pointer into WORKD for X, IPNTR(2) is the pointer into WORKD for Y. IDO = 99: done ------------------------------------------------------------- BMAT Character*1. (INPUT) BMAT specifies the type of the matrix B in the (generalized) eigenvalue problem A*x = lambda*B*x. B = 'I' -> standard eigenvalue problem A*x = lambda*x B = 'G' -> generalized eigenvalue problem A*x = lambda*B*x ITRY Integer. (INPUT) ITRY counts the number of times that dgetv0 is called. It should be set to 1 on the initial call to dgetv0. INITV Logical variable. (INPUT) .TRUE. => the initial residual vector is given in RESID. .FALSE. => generate a random initial residual vector. N Integer. (INPUT) Dimension of the problem. J Integer. (INPUT) Index of the residual vector to be generated, with respect to the Arnoldi process. J > 1 in case of a "restart". V Double precision N by J array. (INPUT) The first J-1 columns of V contain the current Arnoldi basis if this is a "restart". LDV Integer. (INPUT) Leading dimension of V exactly as declared in the calling program. RESID Double precision array of length N. (INPUT/OUTPUT) Initial residual vector to be generated. If RESID is provided, force RESID into the range of the operator OP. RNORM Double precision scalar. (OUTPUT) B-norm of the generated residual. IPNTR Integer array of length 3. (OUTPUT) WORKD Double precision work array of length 2*N. (REVERSE COMMUNICATION). On exit, WORK(1:N) = B*RESID to be used in SSAITR. IERR Integer. (OUTPUT) = 0: Normal exit. = -1: Cannot generate a nontrivial restarted residual vector in the range of the operator OP. \EndDoc ----------------------------------------------------------------------- \BeginLib \Local variables: xxxxxx real \References: 1. D.C. Sorensen, "Implicit Application of Polynomial Filters in a k-Step Arnoldi Method", SIAM J. Matr. Anal. Apps., 13 (1992), pp 357-385. 2. R.B. Lehoucq, "Analysis and Implementation of an Implicitly Restarted Arnoldi Iteration", Rice University Technical Report TR95-13, Department of Computational and Applied Mathematics. \Routines called: second ARPACK utility routine for timing. dvout ARPACK utility routine for vector output. dlarnv LAPACK routine for generating a random vector. dgemv Level 2 BLAS routine for matrix vector multiplication. dcopy Level 1 BLAS that copies one vector to another. ddot Level 1 BLAS that computes the scalar product of two vectors. dnrm2 Level 1 BLAS that computes the norm of a vector. \Author Danny Sorensen Phuong Vu Richard Lehoucq CRPC / Rice University Dept. of Computational & Houston, Texas Applied Mathematics Rice University Houston, Texas \SCCS Information: @(#) FILE: getv0.F SID: 2.6 DATE OF SID: 8/27/96 RELEASE: 2 \EndLib ----------------------------------------------------------------------- Subroutine */ int igraphdgetv0_(integer *ido, char *bmat, integer *itry, logical *initv, integer *n, integer *j, doublereal *v, integer *ldv, doublereal *resid, doublereal *rnorm, integer *ipntr, doublereal * workd, integer *ierr) { /* Initialized data */ IGRAPH_F77_SAVE logical inits = TRUE_; /* System generated locals */ integer v_dim1, v_offset, i__1; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ real t0, t1, t2, t3; integer jj, nbx = 0; extern doublereal igraphddot_(integer *, doublereal *, integer *, doublereal *, integer *); IGRAPH_F77_SAVE integer iter; IGRAPH_F77_SAVE logical orth; integer nopx = 0; extern doublereal igraphdnrm2_(integer *, doublereal *, integer *); IGRAPH_F77_SAVE integer iseed[4]; extern /* Subroutine */ int igraphdgemv_(char *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *); integer idist; extern /* Subroutine */ int igraphdcopy_(integer *, doublereal *, integer *, doublereal *, integer *); IGRAPH_F77_SAVE logical first; real tmvbx = 0; extern /* Subroutine */ int igraphdvout_(integer *, integer *, doublereal *, integer *, char *, ftnlen); integer mgetv0 = 0; real tgetv0 = 0; IGRAPH_F77_SAVE doublereal rnorm0; extern /* Subroutine */ int igraphsecond_(real *); integer logfil, ndigit; extern /* Subroutine */ int igraphdlarnv_(integer *, integer *, integer *, doublereal *); IGRAPH_F77_SAVE integer msglvl; real tmvopx = 0; /* %----------------------------------------------------% | Include files for debugging and timing information | %----------------------------------------------------% %------------------% | Scalar Arguments | %------------------% %-----------------% | Array Arguments | %-----------------% %------------% | Parameters | %------------% %------------------------% | Local Scalars & Arrays | %------------------------% %----------------------% | External Subroutines | %----------------------% %--------------------% | External Functions | %--------------------% %---------------------% | Intrinsic Functions | %---------------------% %-----------------% | Data Statements | %-----------------% Parameter adjustments */ --workd; --resid; v_dim1 = *ldv; v_offset = 1 + v_dim1; v -= v_offset; --ipntr; /* Function Body %-----------------------% | Executable Statements | %-----------------------% %-----------------------------------% | Initialize the seed of the LAPACK | | random number generator | %-----------------------------------% */ if (inits) { iseed[0] = 1; iseed[1] = 3; iseed[2] = 5; iseed[3] = 7; inits = FALSE_; } if (*ido == 0) { /* %-------------------------------% | Initialize timing statistics | | & message level for debugging | %-------------------------------% */ igraphsecond_(&t0); msglvl = mgetv0; *ierr = 0; iter = 0; first = FALSE_; orth = FALSE_; /* %-----------------------------------------------------% | Possibly generate a random starting vector in RESID | | Use a LAPACK random number generator used by the | | matrix generation routines. | | idist = 1: uniform (0,1) distribution; | | idist = 2: uniform (-1,1) distribution; | | idist = 3: normal (0,1) distribution; | %-----------------------------------------------------% */ if (! (*initv)) { idist = 2; igraphdlarnv_(&idist, iseed, n, &resid[1]); } /* %----------------------------------------------------------% | Force the starting vector into the range of OP to handle | | the generalized problem when B is possibly (singular). | %----------------------------------------------------------% */ igraphsecond_(&t2); if (*(unsigned char *)bmat == 'G') { ++nopx; ipntr[1] = 1; ipntr[2] = *n + 1; igraphdcopy_(n, &resid[1], &c__1, &workd[1], &c__1); *ido = -1; goto L9000; } } /* %-----------------------------------------% | Back from computing OP*(initial-vector) | %-----------------------------------------% */ if (first) { goto L20; } /* %-----------------------------------------------% | Back from computing B*(orthogonalized-vector) | %-----------------------------------------------% */ if (orth) { goto L40; } if (*(unsigned char *)bmat == 'G') { igraphsecond_(&t3); tmvopx += t3 - t2; } /* %------------------------------------------------------% | Starting vector is now in the range of OP; r = OP*r; | | Compute B-norm of starting vector. | %------------------------------------------------------% */ igraphsecond_(&t2); first = TRUE_; if (*(unsigned char *)bmat == 'G') { ++nbx; igraphdcopy_(n, &workd[*n + 1], &c__1, &resid[1], &c__1); ipntr[1] = *n + 1; ipntr[2] = 1; *ido = 2; goto L9000; } else if (*(unsigned char *)bmat == 'I') { igraphdcopy_(n, &resid[1], &c__1, &workd[1], &c__1); } L20: if (*(unsigned char *)bmat == 'G') { igraphsecond_(&t3); tmvbx += t3 - t2; } first = FALSE_; if (*(unsigned char *)bmat == 'G') { rnorm0 = igraphddot_(n, &resid[1], &c__1, &workd[1], &c__1); rnorm0 = sqrt((abs(rnorm0))); } else if (*(unsigned char *)bmat == 'I') { rnorm0 = igraphdnrm2_(n, &resid[1], &c__1); } *rnorm = rnorm0; /* %---------------------------------------------% | Exit if this is the very first Arnoldi step | %---------------------------------------------% */ if (*j == 1) { goto L50; } /* %---------------------------------------------------------------- | Otherwise need to B-orthogonalize the starting vector against | | the current Arnoldi basis using Gram-Schmidt with iter. ref. | | This is the case where an invariant subspace is encountered | | in the middle of the Arnoldi factorization. | | | | s = V^{T}*B*r; r = r - V*s; | | | | Stopping criteria used for iter. ref. is discussed in | | Parlett's book, page 107 and in Gragg & Reichel TOMS paper. | %---------------------------------------------------------------% */ orth = TRUE_; L30: i__1 = *j - 1; igraphdgemv_("T", n, &i__1, &c_b24, &v[v_offset], ldv, &workd[1], &c__1, &c_b26, &workd[*n + 1], &c__1); i__1 = *j - 1; igraphdgemv_("N", n, &i__1, &c_b29, &v[v_offset], ldv, &workd[*n + 1], &c__1, & c_b24, &resid[1], &c__1); /* %----------------------------------------------------------% | Compute the B-norm of the orthogonalized starting vector | %----------------------------------------------------------% */ igraphsecond_(&t2); if (*(unsigned char *)bmat == 'G') { ++nbx; igraphdcopy_(n, &resid[1], &c__1, &workd[*n + 1], &c__1); ipntr[1] = *n + 1; ipntr[2] = 1; *ido = 2; goto L9000; } else if (*(unsigned char *)bmat == 'I') { igraphdcopy_(n, &resid[1], &c__1, &workd[1], &c__1); } L40: if (*(unsigned char *)bmat == 'G') { igraphsecond_(&t3); tmvbx += t3 - t2; } if (*(unsigned char *)bmat == 'G') { *rnorm = igraphddot_(n, &resid[1], &c__1, &workd[1], &c__1); *rnorm = sqrt((abs(*rnorm))); } else if (*(unsigned char *)bmat == 'I') { *rnorm = igraphdnrm2_(n, &resid[1], &c__1); } /* %--------------------------------------% | Check for further orthogonalization. | %--------------------------------------% */ if (msglvl > 2) { igraphdvout_(&logfil, &c__1, &rnorm0, &ndigit, "_getv0: re-orthonalization" " ; rnorm0 is", (ftnlen)38); igraphdvout_(&logfil, &c__1, rnorm, &ndigit, "_getv0: re-orthonalization ;" " rnorm is", (ftnlen)37); } if (*rnorm > rnorm0 * .717f) { goto L50; } ++iter; if (iter <= 1) { /* %-----------------------------------% | Perform iterative refinement step | %-----------------------------------% */ rnorm0 = *rnorm; goto L30; } else { /* %------------------------------------% | Iterative refinement step "failed" | %------------------------------------% */ i__1 = *n; for (jj = 1; jj <= i__1; ++jj) { resid[jj] = 0.; /* L45: */ } *rnorm = 0.; *ierr = -1; } L50: if (msglvl > 0) { igraphdvout_(&logfil, &c__1, rnorm, &ndigit, "_getv0: B-norm of initial / " "restarted starting vector", (ftnlen)53); } if (msglvl > 2) { igraphdvout_(&logfil, n, &resid[1], &ndigit, "_getv0: initial / restarted " "starting vector", (ftnlen)43); } *ido = 99; igraphsecond_(&t1); tgetv0 += t1 - t0; L9000: return 0; /* %---------------% | End of dgetv0 | %---------------% */ } /* igraphdgetv0_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dsapps.c0000644000076500000240000005310413524616145024301 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static doublereal c_b4 = 0.; static doublereal c_b5 = 1.; static integer c__1 = 1; static doublereal c_b20 = -1.; /* ----------------------------------------------------------------------- \BeginDoc \Name: dsapps \Description: Given the Arnoldi factorization A*V_{k} - V_{k}*H_{k} = r_{k+p}*e_{k+p}^T, apply NP shifts implicitly resulting in A*(V_{k}*Q) - (V_{k}*Q)*(Q^T* H_{k}*Q) = r_{k+p}*e_{k+p}^T * Q where Q is an orthogonal matrix of order KEV+NP. Q is the product of rotations resulting from the NP bulge chasing sweeps. The updated Arnoldi factorization becomes: A*VNEW_{k} - VNEW_{k}*HNEW_{k} = rnew_{k}*e_{k}^T. \Usage: call dsapps ( N, KEV, NP, SHIFT, V, LDV, H, LDH, RESID, Q, LDQ, WORKD ) \Arguments N Integer. (INPUT) Problem size, i.e. dimension of matrix A. KEV Integer. (INPUT) INPUT: KEV+NP is the size of the input matrix H. OUTPUT: KEV is the size of the updated matrix HNEW. NP Integer. (INPUT) Number of implicit shifts to be applied. SHIFT Double precision array of length NP. (INPUT) The shifts to be applied. V Double precision N by (KEV+NP) array. (INPUT/OUTPUT) INPUT: V contains the current KEV+NP Arnoldi vectors. OUTPUT: VNEW = V(1:n,1:KEV); the updated Arnoldi vectors are in the first KEV columns of V. LDV Integer. (INPUT) Leading dimension of V exactly as declared in the calling program. H Double precision (KEV+NP) by 2 array. (INPUT/OUTPUT) INPUT: H contains the symmetric tridiagonal matrix of the Arnoldi factorization with the subdiagonal in the 1st column starting at H(2,1) and the main diagonal in the 2nd column. OUTPUT: H contains the updated tridiagonal matrix in the KEV leading submatrix. LDH Integer. (INPUT) Leading dimension of H exactly as declared in the calling program. RESID Double precision array of length (N). (INPUT/OUTPUT) INPUT: RESID contains the the residual vector r_{k+p}. OUTPUT: RESID is the updated residual vector rnew_{k}. Q Double precision KEV+NP by KEV+NP work array. (WORKSPACE) Work array used to accumulate the rotations during the bulge chase sweep. LDQ Integer. (INPUT) Leading dimension of Q exactly as declared in the calling program. WORKD Double precision work array of length 2*N. (WORKSPACE) Distributed array used in the application of the accumulated orthogonal matrix Q. \EndDoc ----------------------------------------------------------------------- \BeginLib \Local variables: xxxxxx real \References: 1. D.C. Sorensen, "Implicit Application of Polynomial Filters in a k-Step Arnoldi Method", SIAM J. Matr. Anal. Apps., 13 (1992), pp 357-385. 2. R.B. Lehoucq, "Analysis and Implementation of an Implicitly Restarted Arnoldi Iteration", Rice University Technical Report TR95-13, Department of Computational and Applied Mathematics. \Routines called: ivout ARPACK utility routine that prints integers. second ARPACK utility routine for timing. dvout ARPACK utility routine that prints vectors. dlamch LAPACK routine that determines machine constants. dlartg LAPACK Givens rotation construction routine. dlacpy LAPACK matrix copy routine. dlaset LAPACK matrix initialization routine. dgemv Level 2 BLAS routine for matrix vector multiplication. daxpy Level 1 BLAS that computes a vector triad. dcopy Level 1 BLAS that copies one vector to another. dscal Level 1 BLAS that scales a vector. \Author Danny Sorensen Phuong Vu Richard Lehoucq CRPC / Rice University Dept. of Computational & Houston, Texas Applied Mathematics Rice University Houston, Texas \Revision history: 12/16/93: Version ' 2.1' \SCCS Information: @(#) FILE: sapps.F SID: 2.5 DATE OF SID: 4/19/96 RELEASE: 2 \Remarks 1. In this version, each shift is applied to all the subblocks of the tridiagonal matrix H and not just to the submatrix that it comes from. This routine assumes that the subdiagonal elements of H that are stored in h(1:kev+np,1) are nonegative upon input and enforce this condition upon output. This version incorporates deflation. See code for documentation. \EndLib ----------------------------------------------------------------------- Subroutine */ int igraphdsapps_(integer *n, integer *kev, integer *np, doublereal *shift, doublereal *v, integer *ldv, doublereal *h__, integer *ldh, doublereal *resid, doublereal *q, integer *ldq, doublereal *workd) { /* Initialized data */ IGRAPH_F77_SAVE logical first = TRUE_; /* System generated locals */ integer h_dim1, h_offset, q_dim1, q_offset, v_dim1, v_offset, i__1, i__2, i__3, i__4; doublereal d__1, d__2; /* Local variables */ doublereal c__, f, g; integer i__, j; doublereal r__, s, a1, a2, a3, a4; real t0, t1; integer jj; doublereal big; integer iend, itop; extern /* Subroutine */ int igraphdscal_(integer *, doublereal *, doublereal *, integer *), igraphdgemv_(char *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *), igraphdcopy_(integer *, doublereal *, integer *, doublereal *, integer *), igraphdaxpy_(integer *, doublereal *, doublereal *, integer *, doublereal *, integer *), igraphdvout_( integer *, integer *, doublereal *, integer *, char *, ftnlen), igraphivout_(integer *, integer *, integer *, integer *, char *, ftnlen) ; extern doublereal igraphdlamch_(char *); extern /* Subroutine */ int igraphsecond_(real *), igraphdlacpy_(char *, integer *, integer *, doublereal *, integer *, doublereal *, integer *), igraphdlartg_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *), igraphdlaset_(char *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *); IGRAPH_F77_SAVE doublereal epsmch; integer logfil, ndigit, msapps = 0, msglvl, istart; real tsapps = 0; integer kplusp; /* %----------------------------------------------------% | Include files for debugging and timing information | %----------------------------------------------------% %------------------% | Scalar Arguments | %------------------% %-----------------% | Array Arguments | %-----------------% %------------% | Parameters | %------------% %---------------% | Local Scalars | %---------------% %----------------------% | External Subroutines | %----------------------% %--------------------% | External Functions | %--------------------% %----------------------% | Intrinsics Functions | %----------------------% %----------------% | Data statments | %----------------% Parameter adjustments */ --workd; --resid; --shift; v_dim1 = *ldv; v_offset = 1 + v_dim1; v -= v_offset; h_dim1 = *ldh; h_offset = 1 + h_dim1; h__ -= h_offset; q_dim1 = *ldq; q_offset = 1 + q_dim1; q -= q_offset; /* Function Body %-----------------------% | Executable Statements | %-----------------------% */ if (first) { epsmch = igraphdlamch_("Epsilon-Machine"); first = FALSE_; } itop = 1; /* %-------------------------------% | Initialize timing statistics | | & message level for debugging | %-------------------------------% */ igraphsecond_(&t0); msglvl = msapps; kplusp = *kev + *np; /* %----------------------------------------------% | Initialize Q to the identity matrix of order | | kplusp used to accumulate the rotations. | %----------------------------------------------% */ igraphdlaset_("All", &kplusp, &kplusp, &c_b4, &c_b5, &q[q_offset], ldq); /* %----------------------------------------------% | Quick return if there are no shifts to apply | %----------------------------------------------% */ if (*np == 0) { goto L9000; } /* %----------------------------------------------------------% | Apply the np shifts implicitly. Apply each shift to the | | whole matrix and not just to the submatrix from which it | | comes. | %----------------------------------------------------------% */ i__1 = *np; for (jj = 1; jj <= i__1; ++jj) { istart = itop; /* %----------------------------------------------------------% | Check for splitting and deflation. Currently we consider | | an off-diagonal element h(i+1,1) negligible if | | h(i+1,1) .le. epsmch*( |h(i,2)| + |h(i+1,2)| ) | | for i=1:KEV+NP-1. | | If above condition tests true then we set h(i+1,1) = 0. | | Note that h(1:KEV+NP,1) are assumed to be non negative. | %----------------------------------------------------------% */ L20: /* %------------------------------------------------% | The following loop exits early if we encounter | | a negligible off diagonal element. | %------------------------------------------------% */ i__2 = kplusp - 1; for (i__ = istart; i__ <= i__2; ++i__) { big = (d__1 = h__[i__ + (h_dim1 << 1)], abs(d__1)) + (d__2 = h__[ i__ + 1 + (h_dim1 << 1)], abs(d__2)); if (h__[i__ + 1 + h_dim1] <= epsmch * big) { if (msglvl > 0) { igraphivout_(&logfil, &c__1, &i__, &ndigit, "_sapps: deflation" " at row/column no.", (ftnlen)35); igraphivout_(&logfil, &c__1, &jj, &ndigit, "_sapps: occured be" "fore shift number.", (ftnlen)36); igraphdvout_(&logfil, &c__1, &h__[i__ + 1 + h_dim1], &ndigit, "_sapps: the corresponding off diagonal element", (ftnlen)46); } h__[i__ + 1 + h_dim1] = 0.; iend = i__; goto L40; } /* L30: */ } iend = kplusp; L40: if (istart < iend) { /* %--------------------------------------------------------% | Construct the plane rotation G'(istart,istart+1,theta) | | that attempts to drive h(istart+1,1) to zero. | %--------------------------------------------------------% */ f = h__[istart + (h_dim1 << 1)] - shift[jj]; g = h__[istart + 1 + h_dim1]; igraphdlartg_(&f, &g, &c__, &s, &r__); /* %-------------------------------------------------------% | Apply rotation to the left and right of H; | | H <- G' * H * G, where G = G(istart,istart+1,theta). | | This will create a "bulge". | %-------------------------------------------------------% */ a1 = c__ * h__[istart + (h_dim1 << 1)] + s * h__[istart + 1 + h_dim1]; a2 = c__ * h__[istart + 1 + h_dim1] + s * h__[istart + 1 + ( h_dim1 << 1)]; a4 = c__ * h__[istart + 1 + (h_dim1 << 1)] - s * h__[istart + 1 + h_dim1]; a3 = c__ * h__[istart + 1 + h_dim1] - s * h__[istart + (h_dim1 << 1)]; h__[istart + (h_dim1 << 1)] = c__ * a1 + s * a2; h__[istart + 1 + (h_dim1 << 1)] = c__ * a4 - s * a3; h__[istart + 1 + h_dim1] = c__ * a3 + s * a4; /* %----------------------------------------------------% | Accumulate the rotation in the matrix Q; Q <- Q*G | %----------------------------------------------------% Computing MIN */ i__3 = istart + jj; i__2 = min(i__3,kplusp); for (j = 1; j <= i__2; ++j) { a1 = c__ * q[j + istart * q_dim1] + s * q[j + (istart + 1) * q_dim1]; q[j + (istart + 1) * q_dim1] = -s * q[j + istart * q_dim1] + c__ * q[j + (istart + 1) * q_dim1]; q[j + istart * q_dim1] = a1; /* L60: */ } /* %----------------------------------------------% | The following loop chases the bulge created. | | Note that the previous rotation may also be | | done within the following loop. But it is | | kept separate to make the distinction among | | the bulge chasing sweeps and the first plane | | rotation designed to drive h(istart+1,1) to | | zero. | %----------------------------------------------% */ i__2 = iend - 1; for (i__ = istart + 1; i__ <= i__2; ++i__) { /* %----------------------------------------------% | Construct the plane rotation G'(i,i+1,theta) | | that zeros the i-th bulge that was created | | by G(i-1,i,theta). g represents the bulge. | %----------------------------------------------% */ f = h__[i__ + h_dim1]; g = s * h__[i__ + 1 + h_dim1]; /* %----------------------------------% | Final update with G(i-1,i,theta) | %----------------------------------% */ h__[i__ + 1 + h_dim1] = c__ * h__[i__ + 1 + h_dim1]; igraphdlartg_(&f, &g, &c__, &s, &r__); /* %-------------------------------------------% | The following ensures that h(1:iend-1,1), | | the first iend-2 off diagonal of elements | | H, remain non negative. | %-------------------------------------------% */ if (r__ < 0.) { r__ = -r__; c__ = -c__; s = -s; } /* %--------------------------------------------% | Apply rotation to the left and right of H; | | H <- G * H * G', where G = G(i,i+1,theta) | %--------------------------------------------% */ h__[i__ + h_dim1] = r__; a1 = c__ * h__[i__ + (h_dim1 << 1)] + s * h__[i__ + 1 + h_dim1]; a2 = c__ * h__[i__ + 1 + h_dim1] + s * h__[i__ + 1 + (h_dim1 << 1)]; a3 = c__ * h__[i__ + 1 + h_dim1] - s * h__[i__ + (h_dim1 << 1) ]; a4 = c__ * h__[i__ + 1 + (h_dim1 << 1)] - s * h__[i__ + 1 + h_dim1]; h__[i__ + (h_dim1 << 1)] = c__ * a1 + s * a2; h__[i__ + 1 + (h_dim1 << 1)] = c__ * a4 - s * a3; h__[i__ + 1 + h_dim1] = c__ * a3 + s * a4; /* %----------------------------------------------------% | Accumulate the rotation in the matrix Q; Q <- Q*G | %----------------------------------------------------% Computing MIN */ i__4 = j + jj; i__3 = min(i__4,kplusp); for (j = 1; j <= i__3; ++j) { a1 = c__ * q[j + i__ * q_dim1] + s * q[j + (i__ + 1) * q_dim1]; q[j + (i__ + 1) * q_dim1] = -s * q[j + i__ * q_dim1] + c__ * q[j + (i__ + 1) * q_dim1]; q[j + i__ * q_dim1] = a1; /* L50: */ } /* L70: */ } } /* %--------------------------% | Update the block pointer | %--------------------------% */ istart = iend + 1; /* %------------------------------------------% | Make sure that h(iend,1) is non-negative | | If not then set h(iend,1) <-- -h(iend,1) | | and negate the last column of Q. | | We have effectively carried out a | | similarity on transformation H | %------------------------------------------% */ if (h__[iend + h_dim1] < 0.) { h__[iend + h_dim1] = -h__[iend + h_dim1]; igraphdscal_(&kplusp, &c_b20, &q[iend * q_dim1 + 1], &c__1); } /* %--------------------------------------------------------% | Apply the same shift to the next block if there is any | %--------------------------------------------------------% */ if (iend < kplusp) { goto L20; } /* %-----------------------------------------------------% | Check if we can increase the the start of the block | %-----------------------------------------------------% */ i__2 = kplusp - 1; for (i__ = itop; i__ <= i__2; ++i__) { if (h__[i__ + 1 + h_dim1] > 0.) { goto L90; } ++itop; /* L80: */ } /* %-----------------------------------% | Finished applying the jj-th shift | %-----------------------------------% */ L90: ; } /* %------------------------------------------% | All shifts have been applied. Check for | | more possible deflation that might occur | | after the last shift is applied. | %------------------------------------------% */ i__1 = kplusp - 1; for (i__ = itop; i__ <= i__1; ++i__) { big = (d__1 = h__[i__ + (h_dim1 << 1)], abs(d__1)) + (d__2 = h__[i__ + 1 + (h_dim1 << 1)], abs(d__2)); if (h__[i__ + 1 + h_dim1] <= epsmch * big) { if (msglvl > 0) { igraphivout_(&logfil, &c__1, &i__, &ndigit, "_sapps: deflation at " "row/column no.", (ftnlen)35); igraphdvout_(&logfil, &c__1, &h__[i__ + 1 + h_dim1], &ndigit, "_sa" "pps: the corresponding off diagonal element", (ftnlen) 46); } h__[i__ + 1 + h_dim1] = 0.; } /* L100: */ } /* %-------------------------------------------------% | Compute the (kev+1)-st column of (V*Q) and | | temporarily store the result in WORKD(N+1:2*N). | | This is not necessary if h(kev+1,1) = 0. | %-------------------------------------------------% */ if (h__[*kev + 1 + h_dim1] > 0.) { igraphdgemv_("N", n, &kplusp, &c_b5, &v[v_offset], ldv, &q[(*kev + 1) * q_dim1 + 1], &c__1, &c_b4, &workd[*n + 1], &c__1); } /* %-------------------------------------------------------% | Compute column 1 to kev of (V*Q) in backward order | | taking advantage that Q is an upper triangular matrix | | with lower bandwidth np. | | Place results in v(:,kplusp-kev:kplusp) temporarily. | %-------------------------------------------------------% */ i__1 = *kev; for (i__ = 1; i__ <= i__1; ++i__) { i__2 = kplusp - i__ + 1; igraphdgemv_("N", n, &i__2, &c_b5, &v[v_offset], ldv, &q[(*kev - i__ + 1) * q_dim1 + 1], &c__1, &c_b4, &workd[1], &c__1); igraphdcopy_(n, &workd[1], &c__1, &v[(kplusp - i__ + 1) * v_dim1 + 1], & c__1); /* L130: */ } /* %-------------------------------------------------% | Move v(:,kplusp-kev+1:kplusp) into v(:,1:kev). | %-------------------------------------------------% */ igraphdlacpy_("All", n, kev, &v[(*np + 1) * v_dim1 + 1], ldv, &v[v_offset], ldv); /* %--------------------------------------------% | Copy the (kev+1)-st column of (V*Q) in the | | appropriate place if h(kev+1,1) .ne. zero. | %--------------------------------------------% */ if (h__[*kev + 1 + h_dim1] > 0.) { igraphdcopy_(n, &workd[*n + 1], &c__1, &v[(*kev + 1) * v_dim1 + 1], &c__1); } /* %-------------------------------------% | Update the residual vector: | | r <- sigmak*r + betak*v(:,kev+1) | | where | | sigmak = (e_{kev+p}'*Q)*e_{kev} | | betak = e_{kev+1}'*H*e_{kev} | %-------------------------------------% */ igraphdscal_(n, &q[kplusp + *kev * q_dim1], &resid[1], &c__1); if (h__[*kev + 1 + h_dim1] > 0.) { igraphdaxpy_(n, &h__[*kev + 1 + h_dim1], &v[(*kev + 1) * v_dim1 + 1], &c__1, &resid[1], &c__1); } if (msglvl > 1) { igraphdvout_(&logfil, &c__1, &q[kplusp + *kev * q_dim1], &ndigit, "_sapps:" " sigmak of the updated residual vector", (ftnlen)45); igraphdvout_(&logfil, &c__1, &h__[*kev + 1 + h_dim1], &ndigit, "_sapps: be" "tak of the updated residual vector", (ftnlen)44); igraphdvout_(&logfil, kev, &h__[(h_dim1 << 1) + 1], &ndigit, "_sapps: upda" "ted main diagonal of H for next iteration", (ftnlen)53); if (*kev > 1) { i__1 = *kev - 1; igraphdvout_(&logfil, &i__1, &h__[h_dim1 + 2], &ndigit, "_sapps: updat" "ed sub diagonal of H for next iteration", (ftnlen)52); } } igraphsecond_(&t1); tsapps += t1 - t0; L9000: return 0; /* %---------------% | End of dsapps | %---------------% */ } /* igraphdsapps_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dtrexc.c0000644000076500000240000003025513524616145024302 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static integer c__2 = 2; /* > \brief \b DTREXC =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DTREXC + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DTREXC( COMPQ, N, T, LDT, Q, LDQ, IFST, ILST, WORK, INFO ) CHARACTER COMPQ INTEGER IFST, ILST, INFO, LDQ, LDT, N DOUBLE PRECISION Q( LDQ, * ), T( LDT, * ), WORK( * ) > \par Purpose: ============= > > \verbatim > > DTREXC reorders the real Schur factorization of a real matrix > A = Q*T*Q**T, so that the diagonal block of T with row index IFST is > moved to row ILST. > > The real Schur form T is reordered by an orthogonal similarity > transformation Z**T*T*Z, and optionally the matrix Q of Schur vectors > is updated by postmultiplying it with Z. > > T must be in Schur canonical form (as returned by DHSEQR), that is, > block upper triangular with 1-by-1 and 2-by-2 diagonal blocks; each > 2-by-2 diagonal block has its diagonal elements equal and its > off-diagonal elements of opposite sign. > \endverbatim Arguments: ========== > \param[in] COMPQ > \verbatim > COMPQ is CHARACTER*1 > = 'V': update the matrix Q of Schur vectors; > = 'N': do not update Q. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix T. N >= 0. > \endverbatim > > \param[in,out] T > \verbatim > T is DOUBLE PRECISION array, dimension (LDT,N) > On entry, the upper quasi-triangular matrix T, in Schur > Schur canonical form. > On exit, the reordered upper quasi-triangular matrix, again > in Schur canonical form. > \endverbatim > > \param[in] LDT > \verbatim > LDT is INTEGER > The leading dimension of the array T. LDT >= max(1,N). > \endverbatim > > \param[in,out] Q > \verbatim > Q is DOUBLE PRECISION array, dimension (LDQ,N) > On entry, if COMPQ = 'V', the matrix Q of Schur vectors. > On exit, if COMPQ = 'V', Q has been postmultiplied by the > orthogonal transformation matrix Z which reorders T. > If COMPQ = 'N', Q is not referenced. > \endverbatim > > \param[in] LDQ > \verbatim > LDQ is INTEGER > The leading dimension of the array Q. LDQ >= max(1,N). > \endverbatim > > \param[in,out] IFST > \verbatim > IFST is INTEGER > \endverbatim > > \param[in,out] ILST > \verbatim > ILST is INTEGER > > Specify the reordering of the diagonal blocks of T. > The block with row index IFST is moved to row ILST, by a > sequence of transpositions between adjacent blocks. > On exit, if IFST pointed on entry to the second row of a > 2-by-2 block, it is changed to point to the first row; ILST > always points to the first row of the block in its final > position (which may differ from its input value by +1 or -1). > 1 <= IFST <= N; 1 <= ILST <= N. > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (N) > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value > = 1: two adjacent blocks were too close to swap (the problem > is very ill-conditioned); T may have been partially > reordered, and ILST points to the first row of the > current position of the block being moved. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2011 > \ingroup doubleOTHERcomputational ===================================================================== Subroutine */ int igraphdtrexc_(char *compq, integer *n, doublereal *t, integer * ldt, doublereal *q, integer *ldq, integer *ifst, integer *ilst, doublereal *work, integer *info) { /* System generated locals */ integer q_dim1, q_offset, t_dim1, t_offset, i__1; /* Local variables */ integer nbf, nbl, here; extern logical igraphlsame_(char *, char *); logical wantq; extern /* Subroutine */ int igraphdlaexc_(logical *, integer *, doublereal *, integer *, doublereal *, integer *, integer *, integer *, integer *, doublereal *, integer *), igraphxerbla_(char *, integer *, ftnlen); integer nbnext; /* -- LAPACK computational routine (version 3.4.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2011 ===================================================================== Decode and test the input arguments. Parameter adjustments */ t_dim1 = *ldt; t_offset = 1 + t_dim1; t -= t_offset; q_dim1 = *ldq; q_offset = 1 + q_dim1; q -= q_offset; --work; /* Function Body */ *info = 0; wantq = igraphlsame_(compq, "V"); if (! wantq && ! igraphlsame_(compq, "N")) { *info = -1; } else if (*n < 0) { *info = -2; } else if (*ldt < max(1,*n)) { *info = -4; } else if (*ldq < 1 || wantq && *ldq < max(1,*n)) { *info = -6; } else if (*ifst < 1 || *ifst > *n) { *info = -7; } else if (*ilst < 1 || *ilst > *n) { *info = -8; } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DTREXC", &i__1, (ftnlen)6); return 0; } /* Quick return if possible */ if (*n <= 1) { return 0; } /* Determine the first row of specified block and find out it is 1 by 1 or 2 by 2. */ if (*ifst > 1) { if (t[*ifst + (*ifst - 1) * t_dim1] != 0.) { --(*ifst); } } nbf = 1; if (*ifst < *n) { if (t[*ifst + 1 + *ifst * t_dim1] != 0.) { nbf = 2; } } /* Determine the first row of the final block and find out it is 1 by 1 or 2 by 2. */ if (*ilst > 1) { if (t[*ilst + (*ilst - 1) * t_dim1] != 0.) { --(*ilst); } } nbl = 1; if (*ilst < *n) { if (t[*ilst + 1 + *ilst * t_dim1] != 0.) { nbl = 2; } } if (*ifst == *ilst) { return 0; } if (*ifst < *ilst) { /* Update ILST */ if (nbf == 2 && nbl == 1) { --(*ilst); } if (nbf == 1 && nbl == 2) { ++(*ilst); } here = *ifst; L10: /* Swap block with next one below */ if (nbf == 1 || nbf == 2) { /* Current block either 1 by 1 or 2 by 2 */ nbnext = 1; if (here + nbf + 1 <= *n) { if (t[here + nbf + 1 + (here + nbf) * t_dim1] != 0.) { nbnext = 2; } } igraphdlaexc_(&wantq, n, &t[t_offset], ldt, &q[q_offset], ldq, &here, & nbf, &nbnext, &work[1], info); if (*info != 0) { *ilst = here; return 0; } here += nbnext; /* Test if 2 by 2 block breaks into two 1 by 1 blocks */ if (nbf == 2) { if (t[here + 1 + here * t_dim1] == 0.) { nbf = 3; } } } else { /* Current block consists of two 1 by 1 blocks each of which must be swapped individually */ nbnext = 1; if (here + 3 <= *n) { if (t[here + 3 + (here + 2) * t_dim1] != 0.) { nbnext = 2; } } i__1 = here + 1; igraphdlaexc_(&wantq, n, &t[t_offset], ldt, &q[q_offset], ldq, &i__1, & c__1, &nbnext, &work[1], info); if (*info != 0) { *ilst = here; return 0; } if (nbnext == 1) { /* Swap two 1 by 1 blocks, no problems possible */ igraphdlaexc_(&wantq, n, &t[t_offset], ldt, &q[q_offset], ldq, & here, &c__1, &nbnext, &work[1], info); ++here; } else { /* Recompute NBNEXT in case 2 by 2 split */ if (t[here + 2 + (here + 1) * t_dim1] == 0.) { nbnext = 1; } if (nbnext == 2) { /* 2 by 2 Block did not split */ igraphdlaexc_(&wantq, n, &t[t_offset], ldt, &q[q_offset], ldq, & here, &c__1, &nbnext, &work[1], info); if (*info != 0) { *ilst = here; return 0; } here += 2; } else { /* 2 by 2 Block did split */ igraphdlaexc_(&wantq, n, &t[t_offset], ldt, &q[q_offset], ldq, & here, &c__1, &c__1, &work[1], info); i__1 = here + 1; igraphdlaexc_(&wantq, n, &t[t_offset], ldt, &q[q_offset], ldq, & i__1, &c__1, &c__1, &work[1], info); here += 2; } } } if (here < *ilst) { goto L10; } } else { here = *ifst; L20: /* Swap block with next one above */ if (nbf == 1 || nbf == 2) { /* Current block either 1 by 1 or 2 by 2 */ nbnext = 1; if (here >= 3) { if (t[here - 1 + (here - 2) * t_dim1] != 0.) { nbnext = 2; } } i__1 = here - nbnext; igraphdlaexc_(&wantq, n, &t[t_offset], ldt, &q[q_offset], ldq, &i__1, & nbnext, &nbf, &work[1], info); if (*info != 0) { *ilst = here; return 0; } here -= nbnext; /* Test if 2 by 2 block breaks into two 1 by 1 blocks */ if (nbf == 2) { if (t[here + 1 + here * t_dim1] == 0.) { nbf = 3; } } } else { /* Current block consists of two 1 by 1 blocks each of which must be swapped individually */ nbnext = 1; if (here >= 3) { if (t[here - 1 + (here - 2) * t_dim1] != 0.) { nbnext = 2; } } i__1 = here - nbnext; igraphdlaexc_(&wantq, n, &t[t_offset], ldt, &q[q_offset], ldq, &i__1, & nbnext, &c__1, &work[1], info); if (*info != 0) { *ilst = here; return 0; } if (nbnext == 1) { /* Swap two 1 by 1 blocks, no problems possible */ igraphdlaexc_(&wantq, n, &t[t_offset], ldt, &q[q_offset], ldq, & here, &nbnext, &c__1, &work[1], info); --here; } else { /* Recompute NBNEXT in case 2 by 2 split */ if (t[here + (here - 1) * t_dim1] == 0.) { nbnext = 1; } if (nbnext == 2) { /* 2 by 2 Block did not split */ i__1 = here - 1; igraphdlaexc_(&wantq, n, &t[t_offset], ldt, &q[q_offset], ldq, & i__1, &c__2, &c__1, &work[1], info); if (*info != 0) { *ilst = here; return 0; } here += -2; } else { /* 2 by 2 Block did split */ igraphdlaexc_(&wantq, n, &t[t_offset], ldt, &q[q_offset], ldq, & here, &c__1, &c__1, &work[1], info); i__1 = here - 1; igraphdlaexc_(&wantq, n, &t[t_offset], ldt, &q[q_offset], ldq, & i__1, &c__1, &c__1, &work[1], info); here += -2; } } } if (here > *ilst) { goto L20; } } *ilst = here; return 0; /* End of DTREXC */ } /* igraphdtrexc_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/drot.c0000644000076500000240000000354013524616145023756 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Subroutine */ int igraphdrot_(integer *n, doublereal *dx, integer *incx, doublereal *dy, integer *incy, doublereal *c__, doublereal *s) { /* System generated locals */ integer i__1; /* Local variables */ integer i__, ix, iy; doublereal dtemp; /* Purpose ======= DROT applies a plane rotation. Further Details =============== jack dongarra, linpack, 3/11/78. modified 12/3/93, array(1) declarations changed to array(*) ===================================================================== Parameter adjustments */ --dy; --dx; /* Function Body */ if (*n <= 0) { return 0; } if (*incx == 1 && *incy == 1) { /* code for both increments equal to 1 */ i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { dtemp = *c__ * dx[i__] + *s * dy[i__]; dy[i__] = *c__ * dy[i__] - *s * dx[i__]; dx[i__] = dtemp; } } else { /* code for unequal increments or equal increments not equal to 1 */ ix = 1; iy = 1; if (*incx < 0) { ix = (-(*n) + 1) * *incx + 1; } if (*incy < 0) { iy = (-(*n) + 1) * *incy + 1; } i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { dtemp = *c__ * dx[ix] + *s * dy[iy]; dy[iy] = *c__ * dy[iy] - *s * dx[ix]; dx[ix] = dtemp; ix += *incx; iy += *incy; } } return 0; } /* igraphdrot_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/ddot.c0000644000076500000240000000427113524616145023742 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" doublereal igraphddot_(integer *n, doublereal *dx, integer *incx, doublereal *dy, integer *incy) { /* System generated locals */ integer i__1; doublereal ret_val; /* Local variables */ integer i__, m, ix, iy, mp1; doublereal dtemp; /* Purpose ======= DDOT forms the dot product of two vectors. uses unrolled loops for increments equal to one. Further Details =============== jack dongarra, linpack, 3/11/78. modified 12/3/93, array(1) declarations changed to array(*) ===================================================================== Parameter adjustments */ --dy; --dx; /* Function Body */ ret_val = 0.; dtemp = 0.; if (*n <= 0) { return ret_val; } if (*incx == 1 && *incy == 1) { /* code for both increments equal to 1 clean-up loop */ m = *n % 5; if (m != 0) { i__1 = m; for (i__ = 1; i__ <= i__1; ++i__) { dtemp += dx[i__] * dy[i__]; } if (*n < 5) { ret_val = dtemp; return ret_val; } } mp1 = m + 1; i__1 = *n; for (i__ = mp1; i__ <= i__1; i__ += 5) { dtemp = dtemp + dx[i__] * dy[i__] + dx[i__ + 1] * dy[i__ + 1] + dx[i__ + 2] * dy[i__ + 2] + dx[i__ + 3] * dy[i__ + 3] + dx[i__ + 4] * dy[i__ + 4]; } } else { /* code for unequal increments or equal increments not equal to 1 */ ix = 1; iy = 1; if (*incx < 0) { ix = (-(*n) + 1) * *incx + 1; } if (*incy < 0) { iy = (-(*n) + 1) * *incy + 1; } i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { dtemp += dx[ix] * dy[iy]; ix += *incx; iy += *incy; } } ret_val = dtemp; return ret_val; } /* igraphddot_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/iladlc.c0000644000076500000240000000713013524616145024235 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b ILADLC scans a matrix for its last non-zero column. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download ILADLC + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== INTEGER FUNCTION ILADLC( M, N, A, LDA ) INTEGER M, N, LDA DOUBLE PRECISION A( LDA, * ) > \par Purpose: ============= > > \verbatim > > ILADLC scans A for its last non-zero column. > \endverbatim Arguments: ========== > \param[in] M > \verbatim > M is INTEGER > The number of rows of the matrix A. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The number of columns of the matrix A. > \endverbatim > > \param[in] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,N) > The m by n matrix A. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. LDA >= max(1,M). > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERauxiliary ===================================================================== */ integer igraphiladlc_(integer *m, integer *n, doublereal *a, integer *lda) { /* System generated locals */ integer a_dim1, a_offset, ret_val, i__1; /* Local variables */ integer i__; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Quick test for the common case where one corner is non-zero. Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; /* Function Body */ if (*n == 0) { ret_val = *n; } else if (a[*n * a_dim1 + 1] != 0. || a[*m + *n * a_dim1] != 0.) { ret_val = *n; } else { /* Now scan each column from the end, returning with the first non-zero. */ for (ret_val = *n; ret_val >= 1; --ret_val) { i__1 = *m; for (i__ = 1; i__ <= i__1; ++i__) { if (a[i__ + ret_val * a_dim1] != 0.) { return ret_val; } } } } return ret_val; } /* igraphiladlc_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/daxpy.c0000644000076500000240000000413013524616145024127 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Subroutine */ int igraphdaxpy_(integer *n, doublereal *da, doublereal *dx, integer *incx, doublereal *dy, integer *incy) { /* System generated locals */ integer i__1; /* Local variables */ integer i__, m, ix, iy, mp1; /* Purpose ======= DAXPY constant times a vector plus a vector. uses unrolled loops for increments equal to one. Further Details =============== jack dongarra, linpack, 3/11/78. modified 12/3/93, array(1) declarations changed to array(*) ===================================================================== Parameter adjustments */ --dy; --dx; /* Function Body */ if (*n <= 0) { return 0; } if (*da == 0.) { return 0; } if (*incx == 1 && *incy == 1) { /* code for both increments equal to 1 clean-up loop */ m = *n % 4; if (m != 0) { i__1 = m; for (i__ = 1; i__ <= i__1; ++i__) { dy[i__] += *da * dx[i__]; } } if (*n < 4) { return 0; } mp1 = m + 1; i__1 = *n; for (i__ = mp1; i__ <= i__1; i__ += 4) { dy[i__] += *da * dx[i__]; dy[i__ + 1] += *da * dx[i__ + 1]; dy[i__ + 2] += *da * dx[i__ + 2]; dy[i__ + 3] += *da * dx[i__ + 3]; } } else { /* code for unequal increments or equal increments not equal to 1 */ ix = 1; iy = 1; if (*incx < 0) { ix = (-(*n) + 1) * *incx + 1; } if (*incy < 0) { iy = (-(*n) + 1) * *incy + 1; } i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { dy[iy] += *da * dx[ix]; ix += *incx; iy += *incy; } } return 0; } /* igraphdaxpy_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dsesrt.c0000644000076500000240000001433213524616145024313 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; /* ----------------------------------------------------------------------- \BeginDoc \Name: dsesrt \Description: Sort the array X in the order specified by WHICH and optionally apply the permutation to the columns of the matrix A. \Usage: call dsesrt ( WHICH, APPLY, N, X, NA, A, LDA) \Arguments WHICH Character*2. (Input) 'LM' -> X is sorted into increasing order of magnitude. 'SM' -> X is sorted into decreasing order of magnitude. 'LA' -> X is sorted into increasing order of algebraic. 'SA' -> X is sorted into decreasing order of algebraic. APPLY Logical. (Input) APPLY = .TRUE. -> apply the sorted order to A. APPLY = .FALSE. -> do not apply the sorted order to A. N Integer. (INPUT) Dimension of the array X. X Double precision array of length N. (INPUT/OUTPUT) The array to be sorted. NA Integer. (INPUT) Number of rows of the matrix A. A Double precision array of length NA by N. (INPUT/OUTPUT) LDA Integer. (INPUT) Leading dimension of A. \EndDoc ----------------------------------------------------------------------- \BeginLib \Routines dswap Level 1 BLAS that swaps the contents of two vectors. \Authors Danny Sorensen Phuong Vu Richard Lehoucq CRPC / Rice University Dept. of Computational & Houston, Texas Applied Mathematics Rice University Houston, Texas \Revision history: 12/15/93: Version ' 2.1'. Adapted from the sort routine in LANSO and the ARPACK code dsortr \SCCS Information: @(#) FILE: sesrt.F SID: 2.3 DATE OF SID: 4/19/96 RELEASE: 2 \EndLib ----------------------------------------------------------------------- Subroutine */ int igraphdsesrt_(char *which, logical *apply, integer *n, doublereal *x, integer *na, doublereal *a, integer *lda) { /* System generated locals */ integer a_dim1, a_offset, i__1; doublereal d__1, d__2; /* Builtin functions */ integer s_cmp(char *, char *, ftnlen, ftnlen); /* Local variables */ integer i__, j, igap; doublereal temp; extern /* Subroutine */ int igraphdswap_(integer *, doublereal *, integer *, doublereal *, integer *); /* %------------------% | Scalar Arguments | %------------------% %-----------------% | Array Arguments | %-----------------% %---------------% | Local Scalars | %---------------% %----------------------% | External Subroutines | %----------------------% %-----------------------% | Executable Statements | %-----------------------% Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1 * 0; a -= a_offset; /* Function Body */ igap = *n / 2; if (s_cmp(which, "SA", (ftnlen)2, (ftnlen)2) == 0) { /* X is sorted into decreasing order of algebraic. */ L10: if (igap == 0) { goto L9000; } i__1 = *n - 1; for (i__ = igap; i__ <= i__1; ++i__) { j = i__ - igap; L20: if (j < 0) { goto L30; } if (x[j] < x[j + igap]) { temp = x[j]; x[j] = x[j + igap]; x[j + igap] = temp; if (*apply) { igraphdswap_(na, &a[j * a_dim1 + 1], &c__1, &a[(j + igap) * a_dim1 + 1], &c__1); } } else { goto L30; } j -= igap; goto L20; L30: ; } igap /= 2; goto L10; } else if (s_cmp(which, "SM", (ftnlen)2, (ftnlen)2) == 0) { /* X is sorted into decreasing order of magnitude. */ L40: if (igap == 0) { goto L9000; } i__1 = *n - 1; for (i__ = igap; i__ <= i__1; ++i__) { j = i__ - igap; L50: if (j < 0) { goto L60; } if ((d__1 = x[j], abs(d__1)) < (d__2 = x[j + igap], abs(d__2))) { temp = x[j]; x[j] = x[j + igap]; x[j + igap] = temp; if (*apply) { igraphdswap_(na, &a[j * a_dim1 + 1], &c__1, &a[(j + igap) * a_dim1 + 1], &c__1); } } else { goto L60; } j -= igap; goto L50; L60: ; } igap /= 2; goto L40; } else if (s_cmp(which, "LA", (ftnlen)2, (ftnlen)2) == 0) { /* X is sorted into increasing order of algebraic. */ L70: if (igap == 0) { goto L9000; } i__1 = *n - 1; for (i__ = igap; i__ <= i__1; ++i__) { j = i__ - igap; L80: if (j < 0) { goto L90; } if (x[j] > x[j + igap]) { temp = x[j]; x[j] = x[j + igap]; x[j + igap] = temp; if (*apply) { igraphdswap_(na, &a[j * a_dim1 + 1], &c__1, &a[(j + igap) * a_dim1 + 1], &c__1); } } else { goto L90; } j -= igap; goto L80; L90: ; } igap /= 2; goto L70; } else if (s_cmp(which, "LM", (ftnlen)2, (ftnlen)2) == 0) { /* X is sorted into increasing order of magnitude. */ L100: if (igap == 0) { goto L9000; } i__1 = *n - 1; for (i__ = igap; i__ <= i__1; ++i__) { j = i__ - igap; L110: if (j < 0) { goto L120; } if ((d__1 = x[j], abs(d__1)) > (d__2 = x[j + igap], abs(d__2))) { temp = x[j]; x[j] = x[j + igap]; x[j + igap] = temp; if (*apply) { igraphdswap_(na, &a[j * a_dim1 + 1], &c__1, &a[(j + igap) * a_dim1 + 1], &c__1); } } else { goto L120; } j -= igap; goto L110; L120: ; } igap /= 2; goto L100; } L9000: return 0; /* %---------------% | End of dsesrt | %---------------% */ } /* igraphdsesrt_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dormqr.c0000644000076500000240000002633613524616145024322 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static integer c_n1 = -1; static integer c__2 = 2; static integer c__65 = 65; /* > \brief \b DORMQR =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DORMQR + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DORMQR( SIDE, TRANS, M, N, K, A, LDA, TAU, C, LDC, WORK, LWORK, INFO ) CHARACTER SIDE, TRANS INTEGER INFO, K, LDA, LDC, LWORK, M, N DOUBLE PRECISION A( LDA, * ), C( LDC, * ), TAU( * ), WORK( * ) > \par Purpose: ============= > > \verbatim > > DORMQR overwrites the general real M-by-N matrix C with > > SIDE = 'L' SIDE = 'R' > TRANS = 'N': Q * C C * Q > TRANS = 'T': Q**T * C C * Q**T > > where Q is a real orthogonal matrix defined as the product of k > elementary reflectors > > Q = H(1) H(2) . . . H(k) > > as returned by DGEQRF. Q is of order M if SIDE = 'L' and of order N > if SIDE = 'R'. > \endverbatim Arguments: ========== > \param[in] SIDE > \verbatim > SIDE is CHARACTER*1 > = 'L': apply Q or Q**T from the Left; > = 'R': apply Q or Q**T from the Right. > \endverbatim > > \param[in] TRANS > \verbatim > TRANS is CHARACTER*1 > = 'N': No transpose, apply Q; > = 'T': Transpose, apply Q**T. > \endverbatim > > \param[in] M > \verbatim > M is INTEGER > The number of rows of the matrix C. M >= 0. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The number of columns of the matrix C. N >= 0. > \endverbatim > > \param[in] K > \verbatim > K is INTEGER > The number of elementary reflectors whose product defines > the matrix Q. > If SIDE = 'L', M >= K >= 0; > if SIDE = 'R', N >= K >= 0. > \endverbatim > > \param[in] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,K) > The i-th column must contain the vector which defines the > elementary reflector H(i), for i = 1,2,...,k, as returned by > DGEQRF in the first k columns of its array argument A. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. > If SIDE = 'L', LDA >= max(1,M); > if SIDE = 'R', LDA >= max(1,N). > \endverbatim > > \param[in] TAU > \verbatim > TAU is DOUBLE PRECISION array, dimension (K) > TAU(i) must contain the scalar factor of the elementary > reflector H(i), as returned by DGEQRF. > \endverbatim > > \param[in,out] C > \verbatim > C is DOUBLE PRECISION array, dimension (LDC,N) > On entry, the M-by-N matrix C. > On exit, C is overwritten by Q*C or Q**T*C or C*Q**T or C*Q. > \endverbatim > > \param[in] LDC > \verbatim > LDC is INTEGER > The leading dimension of the array C. LDC >= max(1,M). > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (MAX(1,LWORK)) > On exit, if INFO = 0, WORK(1) returns the optimal LWORK. > \endverbatim > > \param[in] LWORK > \verbatim > LWORK is INTEGER > The dimension of the array WORK. > If SIDE = 'L', LWORK >= max(1,N); > if SIDE = 'R', LWORK >= max(1,M). > For optimum performance LWORK >= N*NB if SIDE = 'L', and > LWORK >= M*NB if SIDE = 'R', where NB is the optimal > blocksize. > > If LWORK = -1, then a workspace query is assumed; the routine > only calculates the optimal size of the WORK array, returns > this value as the first entry of the WORK array, and no error > message related to LWORK is issued by XERBLA. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2011 > \ingroup doubleOTHERcomputational ===================================================================== Subroutine */ int igraphdormqr_(char *side, char *trans, integer *m, integer *n, integer *k, doublereal *a, integer *lda, doublereal *tau, doublereal * c__, integer *ldc, doublereal *work, integer *lwork, integer *info) { /* System generated locals */ address a__1[2]; integer a_dim1, a_offset, c_dim1, c_offset, i__1, i__2, i__3[2], i__4, i__5; char ch__1[2]; /* Builtin functions Subroutine */ int s_cat(char *, char **, integer *, integer *, ftnlen); /* Local variables */ integer i__; doublereal t[4160] /* was [65][64] */; integer i1, i2, i3, ib, ic, jc, nb, mi, ni, nq, nw, iws; logical left; extern logical igraphlsame_(char *, char *); integer nbmin, iinfo; extern /* Subroutine */ int igraphdorm2r_(char *, char *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *), igraphdlarfb_(char *, char *, char *, char *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, integer *), igraphdlarft_(char *, char *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *), igraphxerbla_(char *, integer *, ftnlen); extern integer igraphilaenv_(integer *, char *, char *, integer *, integer *, integer *, integer *, ftnlen, ftnlen); logical notran; integer ldwork, lwkopt; logical lquery; /* -- LAPACK computational routine (version 3.4.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2011 ===================================================================== Test the input arguments Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --tau; c_dim1 = *ldc; c_offset = 1 + c_dim1; c__ -= c_offset; --work; /* Function Body */ *info = 0; left = igraphlsame_(side, "L"); notran = igraphlsame_(trans, "N"); lquery = *lwork == -1; /* NQ is the order of Q and NW is the minimum dimension of WORK */ if (left) { nq = *m; nw = *n; } else { nq = *n; nw = *m; } if (! left && ! igraphlsame_(side, "R")) { *info = -1; } else if (! notran && ! igraphlsame_(trans, "T")) { *info = -2; } else if (*m < 0) { *info = -3; } else if (*n < 0) { *info = -4; } else if (*k < 0 || *k > nq) { *info = -5; } else if (*lda < max(1,nq)) { *info = -7; } else if (*ldc < max(1,*m)) { *info = -10; } else if (*lwork < max(1,nw) && ! lquery) { *info = -12; } if (*info == 0) { /* Determine the block size. NB may be at most NBMAX, where NBMAX is used to define the local array T. Computing MIN Writing concatenation */ i__3[0] = 1, a__1[0] = side; i__3[1] = 1, a__1[1] = trans; s_cat(ch__1, a__1, i__3, &c__2, (ftnlen)2); i__1 = 64, i__2 = igraphilaenv_(&c__1, "DORMQR", ch__1, m, n, k, &c_n1, ( ftnlen)6, (ftnlen)2); nb = min(i__1,i__2); lwkopt = max(1,nw) * nb; work[1] = (doublereal) lwkopt; } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DORMQR", &i__1, (ftnlen)6); return 0; } else if (lquery) { return 0; } /* Quick return if possible */ if (*m == 0 || *n == 0 || *k == 0) { work[1] = 1.; return 0; } nbmin = 2; ldwork = nw; if (nb > 1 && nb < *k) { iws = nw * nb; if (*lwork < iws) { nb = *lwork / ldwork; /* Computing MAX Writing concatenation */ i__3[0] = 1, a__1[0] = side; i__3[1] = 1, a__1[1] = trans; s_cat(ch__1, a__1, i__3, &c__2, (ftnlen)2); i__1 = 2, i__2 = igraphilaenv_(&c__2, "DORMQR", ch__1, m, n, k, &c_n1, ( ftnlen)6, (ftnlen)2); nbmin = max(i__1,i__2); } } else { iws = nw; } if (nb < nbmin || nb >= *k) { /* Use unblocked code */ igraphdorm2r_(side, trans, m, n, k, &a[a_offset], lda, &tau[1], &c__[ c_offset], ldc, &work[1], &iinfo); } else { /* Use blocked code */ if (left && ! notran || ! left && notran) { i1 = 1; i2 = *k; i3 = nb; } else { i1 = (*k - 1) / nb * nb + 1; i2 = 1; i3 = -nb; } if (left) { ni = *n; jc = 1; } else { mi = *m; ic = 1; } i__1 = i2; i__2 = i3; for (i__ = i1; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ += i__2) { /* Computing MIN */ i__4 = nb, i__5 = *k - i__ + 1; ib = min(i__4,i__5); /* Form the triangular factor of the block reflector H = H(i) H(i+1) . . . H(i+ib-1) */ i__4 = nq - i__ + 1; igraphdlarft_("Forward", "Columnwise", &i__4, &ib, &a[i__ + i__ * a_dim1], lda, &tau[i__], t, &c__65) ; if (left) { /* H or H**T is applied to C(i:m,1:n) */ mi = *m - i__ + 1; ic = i__; } else { /* H or H**T is applied to C(1:m,i:n) */ ni = *n - i__ + 1; jc = i__; } /* Apply H or H**T */ igraphdlarfb_(side, trans, "Forward", "Columnwise", &mi, &ni, &ib, &a[ i__ + i__ * a_dim1], lda, t, &c__65, &c__[ic + jc * c_dim1], ldc, &work[1], &ldwork); /* L10: */ } } work[1] = (doublereal) lwkopt; return 0; /* End of DORMQR */ } /* igraphdormqr_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlamch.c0000644000076500000240000001343213524616145024237 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static doublereal c_b2 = 0.; /* > \brief \b DLAMCH =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ Definition: =========== DOUBLE PRECISION FUNCTION DLAMCH( CMACH ) > \par Purpose: ============= > > \verbatim > > DLAMCH determines double precision machine parameters. > \endverbatim Arguments: ========== > \param[in] CMACH > \verbatim > Specifies the value to be returned by DLAMCH: > = 'E' or 'e', DLAMCH := eps > = 'S' or 's , DLAMCH := sfmin > = 'B' or 'b', DLAMCH := base > = 'P' or 'p', DLAMCH := eps*base > = 'N' or 'n', DLAMCH := t > = 'R' or 'r', DLAMCH := rnd > = 'M' or 'm', DLAMCH := emin > = 'U' or 'u', DLAMCH := rmin > = 'L' or 'l', DLAMCH := emax > = 'O' or 'o', DLAMCH := rmax > where > eps = relative machine precision > sfmin = safe minimum, such that 1/sfmin does not overflow > base = base of the machine > prec = eps*base > t = number of (base) digits in the mantissa > rnd = 1.0 when rounding occurs in addition, 0.0 otherwise > emin = minimum exponent before (gradual) underflow > rmin = underflow threshold - base**(emin-1) > emax = largest exponent before overflow > rmax = overflow threshold - (base**emax)*(1-eps) > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2011 > \ingroup auxOTHERauxiliary ===================================================================== */ doublereal igraphdlamch_(char *cmach) { /* System generated locals */ doublereal ret_val; /* Local variables */ extern doublereal radixdbl_(doublereal *), digitsdbl_(doublereal *), epsilondbl_(doublereal *); doublereal rnd, eps, rmach; extern logical igraphlsame_(char *, char *); doublereal small, sfmin; extern integer minexponentdbl_(doublereal *), maxexponentdbl_(doublereal * ); extern doublereal hugedbl_(doublereal *), tinydbl_(doublereal *); /* -- LAPACK auxiliary routine (version 3.4.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2011 ===================================================================== Assume rounding, not chopping. Always. */ rnd = 1.; if (1. == rnd) { eps = epsilondbl_(&c_b2) * .5f; } else { eps = epsilondbl_(&c_b2); } if (igraphlsame_(cmach, "E")) { rmach = eps; } else if (igraphlsame_(cmach, "S")) { sfmin = tinydbl_(&c_b2); small = 1. / hugedbl_(&c_b2); if (small >= sfmin) { /* Use SMALL plus a bit, to avoid the possibility of rounding causing overflow when computing 1/sfmin. */ sfmin = small * (eps + 1.); } rmach = sfmin; } else if (igraphlsame_(cmach, "B")) { rmach = radixdbl_(&c_b2); } else if (igraphlsame_(cmach, "P")) { rmach = eps * radixdbl_(&c_b2); } else if (igraphlsame_(cmach, "N")) { rmach = digitsdbl_(&c_b2); } else if (igraphlsame_(cmach, "R")) { rmach = rnd; } else if (igraphlsame_(cmach, "M")) { rmach = (doublereal) minexponentdbl_(&c_b2); } else if (igraphlsame_(cmach, "U")) { rmach = tinydbl_(&c_b2); } else if (igraphlsame_(cmach, "L")) { rmach = (doublereal) maxexponentdbl_(&c_b2); } else if (igraphlsame_(cmach, "O")) { rmach = hugedbl_(&c_b2); } else { rmach = 0.; } ret_val = rmach; return ret_val; /* End of DLAMCH */ } /* igraphdlamch_ *********************************************************************** > \brief \b DLAMC3 > \details > \b Purpose: > \verbatim > DLAMC3 is intended to force A and B to be stored prior to doing > the addition of A and B , for use in situations where optimizers > might hold one of these in a register. > \endverbatim > \author LAPACK is a software package provided by Univ. of Tennessee, Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd.. > \date November 2011 > \ingroup auxOTHERauxiliary > > \param[in] A > \verbatim > A is a DOUBLE PRECISION > \endverbatim > > \param[in] B > \verbatim > B is a DOUBLE PRECISION > The values A and B. > \endverbatim > */ doublereal igraphdlamc3_(doublereal *a, doublereal *b) { /* System generated locals */ doublereal ret_val; /* -- LAPACK auxiliary routine (version 3.4.0) -- Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. November 2010 ===================================================================== */ ret_val = *a + *b; return ret_val; /* End of DLAMC3 */ } /* igraphdlamc3_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlanhs.c0000644000076500000240000001551413524616145024263 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; /* > \brief \b DLANHS returns the value of the 1-norm, Frobenius norm, infinity-norm, or the largest absolute value of any element of an upper Hessenberg matrix. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLANHS + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== DOUBLE PRECISION FUNCTION DLANHS( NORM, N, A, LDA, WORK ) CHARACTER NORM INTEGER LDA, N DOUBLE PRECISION A( LDA, * ), WORK( * ) > \par Purpose: ============= > > \verbatim > > DLANHS returns the value of the one norm, or the Frobenius norm, or > the infinity norm, or the element of largest absolute value of a > Hessenberg matrix A. > \endverbatim > > \return DLANHS > \verbatim > > DLANHS = ( max(abs(A(i,j))), NORM = 'M' or 'm' > ( > ( norm1(A), NORM = '1', 'O' or 'o' > ( > ( normI(A), NORM = 'I' or 'i' > ( > ( normF(A), NORM = 'F', 'f', 'E' or 'e' > > where norm1 denotes the one norm of a matrix (maximum column sum), > normI denotes the infinity norm of a matrix (maximum row sum) and > normF denotes the Frobenius norm of a matrix (square root of sum of > squares). Note that max(abs(A(i,j))) is not a consistent matrix norm. > \endverbatim Arguments: ========== > \param[in] NORM > \verbatim > NORM is CHARACTER*1 > Specifies the value to be returned in DLANHS as described > above. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix A. N >= 0. When N = 0, DLANHS is > set to zero. > \endverbatim > > \param[in] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,N) > The n by n upper Hessenberg matrix A; the part of A below the > first sub-diagonal is not referenced. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. LDA >= max(N,1). > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (MAX(1,LWORK)), > where LWORK >= N when NORM = 'I'; otherwise, WORK is not > referenced. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleOTHERauxiliary ===================================================================== */ doublereal igraphdlanhs_(char *norm, integer *n, doublereal *a, integer *lda, doublereal *work) { /* System generated locals */ integer a_dim1, a_offset, i__1, i__2, i__3, i__4; doublereal ret_val, d__1; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ integer i__, j; doublereal sum, scale; extern logical igraphlsame_(char *, char *); doublereal value = 0.; extern logical igraphdisnan_(doublereal *); extern /* Subroutine */ int igraphdlassq_(integer *, doublereal *, integer *, doublereal *, doublereal *); /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --work; /* Function Body */ if (*n == 0) { value = 0.; } else if (igraphlsame_(norm, "M")) { /* Find max(abs(A(i,j))). */ value = 0.; i__1 = *n; for (j = 1; j <= i__1; ++j) { /* Computing MIN */ i__3 = *n, i__4 = j + 1; i__2 = min(i__3,i__4); for (i__ = 1; i__ <= i__2; ++i__) { sum = (d__1 = a[i__ + j * a_dim1], abs(d__1)); if (value < sum || igraphdisnan_(&sum)) { value = sum; } /* L10: */ } /* L20: */ } } else if (igraphlsame_(norm, "O") || *(unsigned char *) norm == '1') { /* Find norm1(A). */ value = 0.; i__1 = *n; for (j = 1; j <= i__1; ++j) { sum = 0.; /* Computing MIN */ i__3 = *n, i__4 = j + 1; i__2 = min(i__3,i__4); for (i__ = 1; i__ <= i__2; ++i__) { sum += (d__1 = a[i__ + j * a_dim1], abs(d__1)); /* L30: */ } if (value < sum || igraphdisnan_(&sum)) { value = sum; } /* L40: */ } } else if (igraphlsame_(norm, "I")) { /* Find normI(A). */ i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { work[i__] = 0.; /* L50: */ } i__1 = *n; for (j = 1; j <= i__1; ++j) { /* Computing MIN */ i__3 = *n, i__4 = j + 1; i__2 = min(i__3,i__4); for (i__ = 1; i__ <= i__2; ++i__) { work[i__] += (d__1 = a[i__ + j * a_dim1], abs(d__1)); /* L60: */ } /* L70: */ } value = 0.; i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { sum = work[i__]; if (value < sum || igraphdisnan_(&sum)) { value = sum; } /* L80: */ } } else if (igraphlsame_(norm, "F") || igraphlsame_(norm, "E")) { /* Find normF(A). */ scale = 0.; sum = 1.; i__1 = *n; for (j = 1; j <= i__1; ++j) { /* Computing MIN */ i__3 = *n, i__4 = j + 1; i__2 = min(i__3,i__4); igraphdlassq_(&i__2, &a[j * a_dim1 + 1], &c__1, &scale, &sum); /* L90: */ } value = scale * sqrt(sum); } ret_val = value; return ret_val; /* End of DLANHS */ } /* igraphdlanhs_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlaqr1.c0000644000076500000240000001341213524616145024171 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLAQR1 sets a scalar multiple of the first column of the product of 2-by-2 or 3-by-3 matrix H a nd specified shifts. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLAQR1 + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLAQR1( N, H, LDH, SR1, SI1, SR2, SI2, V ) DOUBLE PRECISION SI1, SI2, SR1, SR2 INTEGER LDH, N DOUBLE PRECISION H( LDH, * ), V( * ) > \par Purpose: ============= > > \verbatim > > Given a 2-by-2 or 3-by-3 matrix H, DLAQR1 sets v to a > scalar multiple of the first column of the product > > (*) K = (H - (sr1 + i*si1)*I)*(H - (sr2 + i*si2)*I) > > scaling to avoid overflows and most underflows. It > is assumed that either > > 1) sr1 = sr2 and si1 = -si2 > or > 2) si1 = si2 = 0. > > This is useful for starting double implicit shift bulges > in the QR algorithm. > \endverbatim Arguments: ========== > \param[in] N > \verbatim > N is integer > Order of the matrix H. N must be either 2 or 3. > \endverbatim > > \param[in] H > \verbatim > H is DOUBLE PRECISION array of dimension (LDH,N) > The 2-by-2 or 3-by-3 matrix H in (*). > \endverbatim > > \param[in] LDH > \verbatim > LDH is integer > The leading dimension of H as declared in > the calling procedure. LDH.GE.N > \endverbatim > > \param[in] SR1 > \verbatim > SR1 is DOUBLE PRECISION > \endverbatim > > \param[in] SI1 > \verbatim > SI1 is DOUBLE PRECISION > \endverbatim > > \param[in] SR2 > \verbatim > SR2 is DOUBLE PRECISION > \endverbatim > > \param[in] SI2 > \verbatim > SI2 is DOUBLE PRECISION > The shifts in (*). > \endverbatim > > \param[out] V > \verbatim > V is DOUBLE PRECISION array of dimension N > A scalar multiple of the first column of the > matrix K in (*). > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleOTHERauxiliary > \par Contributors: ================== > > Karen Braman and Ralph Byers, Department of Mathematics, > University of Kansas, USA > ===================================================================== Subroutine */ int igraphdlaqr1_(integer *n, doublereal *h__, integer *ldh, doublereal *sr1, doublereal *si1, doublereal *sr2, doublereal *si2, doublereal *v) { /* System generated locals */ integer h_dim1, h_offset; doublereal d__1, d__2, d__3; /* Local variables */ doublereal s, h21s, h31s; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ================================================================ Parameter adjustments */ h_dim1 = *ldh; h_offset = 1 + h_dim1; h__ -= h_offset; --v; /* Function Body */ if (*n == 2) { s = (d__1 = h__[h_dim1 + 1] - *sr2, abs(d__1)) + abs(*si2) + (d__2 = h__[h_dim1 + 2], abs(d__2)); if (s == 0.) { v[1] = 0.; v[2] = 0.; } else { h21s = h__[h_dim1 + 2] / s; v[1] = h21s * h__[(h_dim1 << 1) + 1] + (h__[h_dim1 + 1] - *sr1) * ((h__[h_dim1 + 1] - *sr2) / s) - *si1 * (*si2 / s); v[2] = h21s * (h__[h_dim1 + 1] + h__[(h_dim1 << 1) + 2] - *sr1 - * sr2); } } else { s = (d__1 = h__[h_dim1 + 1] - *sr2, abs(d__1)) + abs(*si2) + (d__2 = h__[h_dim1 + 2], abs(d__2)) + (d__3 = h__[h_dim1 + 3], abs( d__3)); if (s == 0.) { v[1] = 0.; v[2] = 0.; v[3] = 0.; } else { h21s = h__[h_dim1 + 2] / s; h31s = h__[h_dim1 + 3] / s; v[1] = (h__[h_dim1 + 1] - *sr1) * ((h__[h_dim1 + 1] - *sr2) / s) - *si1 * (*si2 / s) + h__[(h_dim1 << 1) + 1] * h21s + h__[ h_dim1 * 3 + 1] * h31s; v[2] = h21s * (h__[h_dim1 + 1] + h__[(h_dim1 << 1) + 2] - *sr1 - * sr2) + h__[h_dim1 * 3 + 2] * h31s; v[3] = h31s * (h__[h_dim1 + 1] + h__[h_dim1 * 3 + 3] - *sr1 - * sr2) + h21s * h__[(h_dim1 << 1) + 3]; } } return 0; } /* igraphdlaqr1_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/len_trim.c0000644000076500000240000000160313524616145024615 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* -- LEN_TRIM is Fortran 95, so we use a replacement here */ integer igraphlen_trim__(char *s, ftnlen s_len) { /* System generated locals */ integer ret_val; /* Builtin functions */ integer i_len(char *, ftnlen); for (ret_val = i_len(s, s_len); ret_val >= 1; --ret_val) { if (*(unsigned char *)&s[ret_val - 1] != ' ') { return ret_val; } } return ret_val; } /* igraphlen_trim__ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dstemr.c0000644000076500000240000007000513524616145024304 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static doublereal c_b18 = .001; /* > \brief \b DSTEMR =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DSTEMR + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DSTEMR( JOBZ, RANGE, N, D, E, VL, VU, IL, IU, M, W, Z, LDZ, NZC, ISUPPZ, TRYRAC, WORK, LWORK, IWORK, LIWORK, INFO ) CHARACTER JOBZ, RANGE LOGICAL TRYRAC INTEGER IL, INFO, IU, LDZ, NZC, LIWORK, LWORK, M, N DOUBLE PRECISION VL, VU INTEGER ISUPPZ( * ), IWORK( * ) DOUBLE PRECISION D( * ), E( * ), W( * ), WORK( * ) DOUBLE PRECISION Z( LDZ, * ) > \par Purpose: ============= > > \verbatim > > DSTEMR computes selected eigenvalues and, optionally, eigenvectors > of a real symmetric tridiagonal matrix T. Any such unreduced matrix has > a well defined set of pairwise different real eigenvalues, the corresponding > real eigenvectors are pairwise orthogonal. > > The spectrum may be computed either completely or partially by specifying > either an interval (VL,VU] or a range of indices IL:IU for the desired > eigenvalues. > > Depending on the number of desired eigenvalues, these are computed either > by bisection or the dqds algorithm. Numerically orthogonal eigenvectors are > computed by the use of various suitable L D L^T factorizations near clusters > of close eigenvalues (referred to as RRRs, Relatively Robust > Representations). An informal sketch of the algorithm follows. > > For each unreduced block (submatrix) of T, > (a) Compute T - sigma I = L D L^T, so that L and D > define all the wanted eigenvalues to high relative accuracy. > This means that small relative changes in the entries of D and L > cause only small relative changes in the eigenvalues and > eigenvectors. The standard (unfactored) representation of the > tridiagonal matrix T does not have this property in general. > (b) Compute the eigenvalues to suitable accuracy. > If the eigenvectors are desired, the algorithm attains full > accuracy of the computed eigenvalues only right before > the corresponding vectors have to be computed, see steps c) and d). > (c) For each cluster of close eigenvalues, select a new > shift close to the cluster, find a new factorization, and refine > the shifted eigenvalues to suitable accuracy. > (d) For each eigenvalue with a large enough relative separation compute > the corresponding eigenvector by forming a rank revealing twisted > factorization. Go back to (c) for any clusters that remain. > > For more details, see: > - Inderjit S. Dhillon and Beresford N. Parlett: "Multiple representations > to compute orthogonal eigenvectors of symmetric tridiagonal matrices," > Linear Algebra and its Applications, 387(1), pp. 1-28, August 2004. > - Inderjit Dhillon and Beresford Parlett: "Orthogonal Eigenvectors and > Relative Gaps," SIAM Journal on Matrix Analysis and Applications, Vol. 25, > 2004. Also LAPACK Working Note 154. > - Inderjit Dhillon: "A new O(n^2) algorithm for the symmetric > tridiagonal eigenvalue/eigenvector problem", > Computer Science Division Technical Report No. UCB/CSD-97-971, > UC Berkeley, May 1997. > > Further Details > 1.DSTEMR works only on machines which follow IEEE-754 > floating-point standard in their handling of infinities and NaNs. > This permits the use of efficient inner loops avoiding a check for > zero divisors. > \endverbatim Arguments: ========== > \param[in] JOBZ > \verbatim > JOBZ is CHARACTER*1 > = 'N': Compute eigenvalues only; > = 'V': Compute eigenvalues and eigenvectors. > \endverbatim > > \param[in] RANGE > \verbatim > RANGE is CHARACTER*1 > = 'A': all eigenvalues will be found. > = 'V': all eigenvalues in the half-open interval (VL,VU] > will be found. > = 'I': the IL-th through IU-th eigenvalues will be found. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix. N >= 0. > \endverbatim > > \param[in,out] D > \verbatim > D is DOUBLE PRECISION array, dimension (N) > On entry, the N diagonal elements of the tridiagonal matrix > T. On exit, D is overwritten. > \endverbatim > > \param[in,out] E > \verbatim > E is DOUBLE PRECISION array, dimension (N) > On entry, the (N-1) subdiagonal elements of the tridiagonal > matrix T in elements 1 to N-1 of E. E(N) need not be set on > input, but is used internally as workspace. > On exit, E is overwritten. > \endverbatim > > \param[in] VL > \verbatim > VL is DOUBLE PRECISION > \endverbatim > > \param[in] VU > \verbatim > VU is DOUBLE PRECISION > > If RANGE='V', the lower and upper bounds of the interval to > be searched for eigenvalues. VL < VU. > Not referenced if RANGE = 'A' or 'I'. > \endverbatim > > \param[in] IL > \verbatim > IL is INTEGER > \endverbatim > > \param[in] IU > \verbatim > IU is INTEGER > > If RANGE='I', the indices (in ascending order) of the > smallest and largest eigenvalues to be returned. > 1 <= IL <= IU <= N, if N > 0. > Not referenced if RANGE = 'A' or 'V'. > \endverbatim > > \param[out] M > \verbatim > M is INTEGER > The total number of eigenvalues found. 0 <= M <= N. > If RANGE = 'A', M = N, and if RANGE = 'I', M = IU-IL+1. > \endverbatim > > \param[out] W > \verbatim > W is DOUBLE PRECISION array, dimension (N) > The first M elements contain the selected eigenvalues in > ascending order. > \endverbatim > > \param[out] Z > \verbatim > Z is DOUBLE PRECISION array, dimension (LDZ, max(1,M) ) > If JOBZ = 'V', and if INFO = 0, then the first M columns of Z > contain the orthonormal eigenvectors of the matrix T > corresponding to the selected eigenvalues, with the i-th > column of Z holding the eigenvector associated with W(i). > If JOBZ = 'N', then Z is not referenced. > Note: the user must ensure that at least max(1,M) columns are > supplied in the array Z; if RANGE = 'V', the exact value of M > is not known in advance and can be computed with a workspace > query by setting NZC = -1, see below. > \endverbatim > > \param[in] LDZ > \verbatim > LDZ is INTEGER > The leading dimension of the array Z. LDZ >= 1, and if > JOBZ = 'V', then LDZ >= max(1,N). > \endverbatim > > \param[in] NZC > \verbatim > NZC is INTEGER > The number of eigenvectors to be held in the array Z. > If RANGE = 'A', then NZC >= max(1,N). > If RANGE = 'V', then NZC >= the number of eigenvalues in (VL,VU]. > If RANGE = 'I', then NZC >= IU-IL+1. > If NZC = -1, then a workspace query is assumed; the > routine calculates the number of columns of the array Z that > are needed to hold the eigenvectors. > This value is returned as the first entry of the Z array, and > no error message related to NZC is issued by XERBLA. > \endverbatim > > \param[out] ISUPPZ > \verbatim > ISUPPZ is INTEGER ARRAY, dimension ( 2*max(1,M) ) > The support of the eigenvectors in Z, i.e., the indices > indicating the nonzero elements in Z. The i-th computed eigenvector > is nonzero only in elements ISUPPZ( 2*i-1 ) through > ISUPPZ( 2*i ). This is relevant in the case when the matrix > is split. ISUPPZ is only accessed when JOBZ is 'V' and N > 0. > \endverbatim > > \param[in,out] TRYRAC > \verbatim > TRYRAC is LOGICAL > If TRYRAC.EQ..TRUE., indicates that the code should check whether > the tridiagonal matrix defines its eigenvalues to high relative > accuracy. If so, the code uses relative-accuracy preserving > algorithms that might be (a bit) slower depending on the matrix. > If the matrix does not define its eigenvalues to high relative > accuracy, the code can uses possibly faster algorithms. > If TRYRAC.EQ..FALSE., the code is not required to guarantee > relatively accurate eigenvalues and can use the fastest possible > techniques. > On exit, a .TRUE. TRYRAC will be set to .FALSE. if the matrix > does not define its eigenvalues to high relative accuracy. > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (LWORK) > On exit, if INFO = 0, WORK(1) returns the optimal > (and minimal) LWORK. > \endverbatim > > \param[in] LWORK > \verbatim > LWORK is INTEGER > The dimension of the array WORK. LWORK >= max(1,18*N) > if JOBZ = 'V', and LWORK >= max(1,12*N) if JOBZ = 'N'. > If LWORK = -1, then a workspace query is assumed; the routine > only calculates the optimal size of the WORK array, returns > this value as the first entry of the WORK array, and no error > message related to LWORK is issued by XERBLA. > \endverbatim > > \param[out] IWORK > \verbatim > IWORK is INTEGER array, dimension (LIWORK) > On exit, if INFO = 0, IWORK(1) returns the optimal LIWORK. > \endverbatim > > \param[in] LIWORK > \verbatim > LIWORK is INTEGER > The dimension of the array IWORK. LIWORK >= max(1,10*N) > if the eigenvectors are desired, and LIWORK >= max(1,8*N) > if only the eigenvalues are to be computed. > If LIWORK = -1, then a workspace query is assumed; the > routine only calculates the optimal size of the IWORK array, > returns this value as the first entry of the IWORK array, and > no error message related to LIWORK is issued by XERBLA. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > On exit, INFO > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value > > 0: if INFO = 1X, internal error in DLARRE, > if INFO = 2X, internal error in DLARRV. > Here, the digit X = ABS( IINFO ) < 10, where IINFO is > the nonzero error code returned by DLARRE or > DLARRV, respectively. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2013 > \ingroup doubleOTHERcomputational > \par Contributors: ================== > > Beresford Parlett, University of California, Berkeley, USA \n > Jim Demmel, University of California, Berkeley, USA \n > Inderjit Dhillon, University of Texas, Austin, USA \n > Osni Marques, LBNL/NERSC, USA \n > Christof Voemel, University of California, Berkeley, USA ===================================================================== Subroutine */ int igraphdstemr_(char *jobz, char *range, integer *n, doublereal * d__, doublereal *e, doublereal *vl, doublereal *vu, integer *il, integer *iu, integer *m, doublereal *w, doublereal *z__, integer *ldz, integer *nzc, integer *isuppz, logical *tryrac, doublereal *work, integer *lwork, integer *iwork, integer *liwork, integer *info) { /* System generated locals */ integer z_dim1, z_offset, i__1, i__2; doublereal d__1, d__2; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ integer i__, j; doublereal r1, r2; integer jj; doublereal cs; integer in; doublereal sn, wl, wu; integer iil, iiu; doublereal eps, tmp; integer indd, iend, jblk, wend; doublereal rmin, rmax; integer itmp; doublereal tnrm; extern /* Subroutine */ int igraphdlae2_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *); integer inde2, itmp2; doublereal rtol1, rtol2; extern /* Subroutine */ int igraphdscal_(integer *, doublereal *, doublereal *, integer *); doublereal scale; integer indgp; extern logical igraphlsame_(char *, char *); integer iinfo, iindw, ilast; extern /* Subroutine */ int igraphdcopy_(integer *, doublereal *, integer *, doublereal *, integer *), igraphdswap_(integer *, doublereal *, integer *, doublereal *, integer *); integer lwmin; logical wantz; extern /* Subroutine */ int igraphdlaev2_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *); extern doublereal igraphdlamch_(char *); logical alleig; integer ibegin; logical indeig; integer iindbl; logical valeig; extern /* Subroutine */ int igraphdlarrc_(char *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, integer *, integer *, integer *, integer *), igraphdlarre_(char *, integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, integer *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *, integer *); integer wbegin; doublereal safmin; extern /* Subroutine */ int igraphdlarrj_(integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, integer *, doublereal *, doublereal *, integer *), igraphxerbla_(char *, integer *, ftnlen); doublereal bignum; integer inderr, iindwk, indgrs, offset; extern doublereal igraphdlanst_(char *, integer *, doublereal *, doublereal *); extern /* Subroutine */ int igraphdlarrr_(integer *, doublereal *, doublereal *, integer *), igraphdlarrv_(integer *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, integer *, integer *, integer *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, integer *, integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, integer *, integer *), igraphdlasrt_(char *, integer *, doublereal *, integer *); doublereal thresh; integer iinspl, ifirst, indwrk, liwmin, nzcmin; doublereal pivmin; integer nsplit; doublereal smlnum; logical lquery, zquery; /* -- LAPACK computational routine (version 3.5.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2013 ===================================================================== Test the input parameters. Parameter adjustments */ --d__; --e; --w; z_dim1 = *ldz; z_offset = 1 + z_dim1; z__ -= z_offset; --isuppz; --work; --iwork; /* Function Body */ wantz = igraphlsame_(jobz, "V"); alleig = igraphlsame_(range, "A"); valeig = igraphlsame_(range, "V"); indeig = igraphlsame_(range, "I"); lquery = *lwork == -1 || *liwork == -1; zquery = *nzc == -1; /* DSTEMR needs WORK of size 6*N, IWORK of size 3*N. In addition, DLARRE needs WORK of size 6*N, IWORK of size 5*N. Furthermore, DLARRV needs WORK of size 12*N, IWORK of size 7*N. */ if (wantz) { lwmin = *n * 18; liwmin = *n * 10; } else { /* need less workspace if only the eigenvalues are wanted */ lwmin = *n * 12; liwmin = *n << 3; } wl = 0.; wu = 0.; iil = 0; iiu = 0; nsplit = 0; if (valeig) { /* We do not reference VL, VU in the cases RANGE = 'I','A' The interval (WL, WU] contains all the wanted eigenvalues. It is either given by the user or computed in DLARRE. */ wl = *vl; wu = *vu; } else if (indeig) { /* We do not reference IL, IU in the cases RANGE = 'V','A' */ iil = *il; iiu = *iu; } *info = 0; if (! (wantz || igraphlsame_(jobz, "N"))) { *info = -1; } else if (! (alleig || valeig || indeig)) { *info = -2; } else if (*n < 0) { *info = -3; } else if (valeig && *n > 0 && wu <= wl) { *info = -7; } else if (indeig && (iil < 1 || iil > *n)) { *info = -8; } else if (indeig && (iiu < iil || iiu > *n)) { *info = -9; } else if (*ldz < 1 || wantz && *ldz < *n) { *info = -13; } else if (*lwork < lwmin && ! lquery) { *info = -17; } else if (*liwork < liwmin && ! lquery) { *info = -19; } /* Get machine constants. */ safmin = igraphdlamch_("Safe minimum"); eps = igraphdlamch_("Precision"); smlnum = safmin / eps; bignum = 1. / smlnum; rmin = sqrt(smlnum); /* Computing MIN */ d__1 = sqrt(bignum), d__2 = 1. / sqrt(sqrt(safmin)); rmax = min(d__1,d__2); if (*info == 0) { work[1] = (doublereal) lwmin; iwork[1] = liwmin; if (wantz && alleig) { nzcmin = *n; } else if (wantz && valeig) { igraphdlarrc_("T", n, vl, vu, &d__[1], &e[1], &safmin, &nzcmin, &itmp, & itmp2, info); } else if (wantz && indeig) { nzcmin = iiu - iil + 1; } else { /* WANTZ .EQ. FALSE. */ nzcmin = 0; } if (zquery && *info == 0) { z__[z_dim1 + 1] = (doublereal) nzcmin; } else if (*nzc < nzcmin && ! zquery) { *info = -14; } } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DSTEMR", &i__1, (ftnlen)6); return 0; } else if (lquery || zquery) { return 0; } /* Handle N = 0, 1, and 2 cases immediately */ *m = 0; if (*n == 0) { return 0; } if (*n == 1) { if (alleig || indeig) { *m = 1; w[1] = d__[1]; } else { if (wl < d__[1] && wu >= d__[1]) { *m = 1; w[1] = d__[1]; } } if (wantz && ! zquery) { z__[z_dim1 + 1] = 1.; isuppz[1] = 1; isuppz[2] = 1; } return 0; } if (*n == 2) { if (! wantz) { igraphdlae2_(&d__[1], &e[1], &d__[2], &r1, &r2); } else if (wantz && ! zquery) { igraphdlaev2_(&d__[1], &e[1], &d__[2], &r1, &r2, &cs, &sn); } if (alleig || valeig && r2 > wl && r2 <= wu || indeig && iil == 1) { ++(*m); w[*m] = r2; if (wantz && ! zquery) { z__[*m * z_dim1 + 1] = -sn; z__[*m * z_dim1 + 2] = cs; /* Note: At most one of SN and CS can be zero. */ if (sn != 0.) { if (cs != 0.) { isuppz[(*m << 1) - 1] = 1; isuppz[*m * 2] = 2; } else { isuppz[(*m << 1) - 1] = 1; isuppz[*m * 2] = 1; } } else { isuppz[(*m << 1) - 1] = 2; isuppz[*m * 2] = 2; } } } if (alleig || valeig && r1 > wl && r1 <= wu || indeig && iiu == 2) { ++(*m); w[*m] = r1; if (wantz && ! zquery) { z__[*m * z_dim1 + 1] = cs; z__[*m * z_dim1 + 2] = sn; /* Note: At most one of SN and CS can be zero. */ if (sn != 0.) { if (cs != 0.) { isuppz[(*m << 1) - 1] = 1; isuppz[*m * 2] = 2; } else { isuppz[(*m << 1) - 1] = 1; isuppz[*m * 2] = 1; } } else { isuppz[(*m << 1) - 1] = 2; isuppz[*m * 2] = 2; } } } } else { /* Continue with general N */ indgrs = 1; inderr = (*n << 1) + 1; indgp = *n * 3 + 1; indd = (*n << 2) + 1; inde2 = *n * 5 + 1; indwrk = *n * 6 + 1; iinspl = 1; iindbl = *n + 1; iindw = (*n << 1) + 1; iindwk = *n * 3 + 1; /* Scale matrix to allowable range, if necessary. The allowable range is related to the PIVMIN parameter; see the comments in DLARRD. The preference for scaling small values up is heuristic; we expect users' matrices not to be close to the RMAX threshold. */ scale = 1.; tnrm = igraphdlanst_("M", n, &d__[1], &e[1]); if (tnrm > 0. && tnrm < rmin) { scale = rmin / tnrm; } else if (tnrm > rmax) { scale = rmax / tnrm; } if (scale != 1.) { igraphdscal_(n, &scale, &d__[1], &c__1); i__1 = *n - 1; igraphdscal_(&i__1, &scale, &e[1], &c__1); tnrm *= scale; if (valeig) { /* If eigenvalues in interval have to be found, scale (WL, WU] accordingly */ wl *= scale; wu *= scale; } } /* Compute the desired eigenvalues of the tridiagonal after splitting into smaller subblocks if the corresponding off-diagonal elements are small THRESH is the splitting parameter for DLARRE A negative THRESH forces the old splitting criterion based on the size of the off-diagonal. A positive THRESH switches to splitting which preserves relative accuracy. */ if (*tryrac) { /* Test whether the matrix warrants the more expensive relative approach. */ igraphdlarrr_(n, &d__[1], &e[1], &iinfo); } else { /* The user does not care about relative accurately eigenvalues */ iinfo = -1; } /* Set the splitting criterion */ if (iinfo == 0) { thresh = eps; } else { thresh = -eps; /* relative accuracy is desired but T does not guarantee it */ *tryrac = FALSE_; } if (*tryrac) { /* Copy original diagonal, needed to guarantee relative accuracy */ igraphdcopy_(n, &d__[1], &c__1, &work[indd], &c__1); } /* Store the squares of the offdiagonal values of T */ i__1 = *n - 1; for (j = 1; j <= i__1; ++j) { /* Computing 2nd power */ d__1 = e[j]; work[inde2 + j - 1] = d__1 * d__1; /* L5: */ } /* Set the tolerance parameters for bisection */ if (! wantz) { /* DLARRE computes the eigenvalues to full precision. */ rtol1 = eps * 4.; rtol2 = eps * 4.; } else { /* DLARRE computes the eigenvalues to less than full precision. DLARRV will refine the eigenvalue approximations, and we can need less accurate initial bisection in DLARRE. Note: these settings do only affect the subset case and DLARRE */ rtol1 = sqrt(eps); /* Computing MAX */ d__1 = sqrt(eps) * .005, d__2 = eps * 4.; rtol2 = max(d__1,d__2); } igraphdlarre_(range, n, &wl, &wu, &iil, &iiu, &d__[1], &e[1], &work[inde2], &rtol1, &rtol2, &thresh, &nsplit, &iwork[iinspl], m, &w[1], & work[inderr], &work[indgp], &iwork[iindbl], &iwork[iindw], & work[indgrs], &pivmin, &work[indwrk], &iwork[iindwk], &iinfo); if (iinfo != 0) { *info = abs(iinfo) + 10; return 0; } /* Note that if RANGE .NE. 'V', DLARRE computes bounds on the desired part of the spectrum. All desired eigenvalues are contained in (WL,WU] */ if (wantz) { /* Compute the desired eigenvectors corresponding to the computed eigenvalues */ igraphdlarrv_(n, &wl, &wu, &d__[1], &e[1], &pivmin, &iwork[iinspl], m, & c__1, m, &c_b18, &rtol1, &rtol2, &w[1], &work[inderr], & work[indgp], &iwork[iindbl], &iwork[iindw], &work[indgrs], &z__[z_offset], ldz, &isuppz[1], &work[indwrk], &iwork[ iindwk], &iinfo); if (iinfo != 0) { *info = abs(iinfo) + 20; return 0; } } else { /* DLARRE computes eigenvalues of the (shifted) root representation DLARRV returns the eigenvalues of the unshifted matrix. However, if the eigenvectors are not desired by the user, we need to apply the corresponding shifts from DLARRE to obtain the eigenvalues of the original matrix. */ i__1 = *m; for (j = 1; j <= i__1; ++j) { itmp = iwork[iindbl + j - 1]; w[j] += e[iwork[iinspl + itmp - 1]]; /* L20: */ } } if (*tryrac) { /* Refine computed eigenvalues so that they are relatively accurate with respect to the original matrix T. */ ibegin = 1; wbegin = 1; i__1 = iwork[iindbl + *m - 1]; for (jblk = 1; jblk <= i__1; ++jblk) { iend = iwork[iinspl + jblk - 1]; in = iend - ibegin + 1; wend = wbegin - 1; /* check if any eigenvalues have to be refined in this block */ L36: if (wend < *m) { if (iwork[iindbl + wend] == jblk) { ++wend; goto L36; } } if (wend < wbegin) { ibegin = iend + 1; goto L39; } offset = iwork[iindw + wbegin - 1] - 1; ifirst = iwork[iindw + wbegin - 1]; ilast = iwork[iindw + wend - 1]; rtol2 = eps * 4.; igraphdlarrj_(&in, &work[indd + ibegin - 1], &work[inde2 + ibegin - 1], &ifirst, &ilast, &rtol2, &offset, &w[wbegin], & work[inderr + wbegin - 1], &work[indwrk], &iwork[ iindwk], &pivmin, &tnrm, &iinfo); ibegin = iend + 1; wbegin = wend + 1; L39: ; } } /* If matrix was scaled, then rescale eigenvalues appropriately. */ if (scale != 1.) { d__1 = 1. / scale; igraphdscal_(m, &d__1, &w[1], &c__1); } } /* If eigenvalues are not in increasing order, then sort them, possibly along with eigenvectors. */ if (nsplit > 1 || *n == 2) { if (! wantz) { igraphdlasrt_("I", m, &w[1], &iinfo); if (iinfo != 0) { *info = 3; return 0; } } else { i__1 = *m - 1; for (j = 1; j <= i__1; ++j) { i__ = 0; tmp = w[j]; i__2 = *m; for (jj = j + 1; jj <= i__2; ++jj) { if (w[jj] < tmp) { i__ = jj; tmp = w[jj]; } /* L50: */ } if (i__ != 0) { w[i__] = w[j]; w[j] = tmp; if (wantz) { igraphdswap_(n, &z__[i__ * z_dim1 + 1], &c__1, &z__[j * z_dim1 + 1], &c__1); itmp = isuppz[(i__ << 1) - 1]; isuppz[(i__ << 1) - 1] = isuppz[(j << 1) - 1]; isuppz[(j << 1) - 1] = itmp; itmp = isuppz[i__ * 2]; isuppz[i__ * 2] = isuppz[j * 2]; isuppz[j * 2] = itmp; } } /* L60: */ } } } work[1] = (doublereal) lwmin; iwork[1] = liwmin; return 0; /* End of DSTEMR */ } /* igraphdstemr_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlaneg.c0000644000076500000240000001701013524616145024235 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLANEG computes the Sturm count. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLANEG + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== INTEGER FUNCTION DLANEG( N, D, LLD, SIGMA, PIVMIN, R ) INTEGER N, R DOUBLE PRECISION PIVMIN, SIGMA DOUBLE PRECISION D( * ), LLD( * ) > \par Purpose: ============= > > \verbatim > > DLANEG computes the Sturm count, the number of negative pivots > encountered while factoring tridiagonal T - sigma I = L D L^T. > This implementation works directly on the factors without forming > the tridiagonal matrix T. The Sturm count is also the number of > eigenvalues of T less than sigma. > > This routine is called from DLARRB. > > The current routine does not use the PIVMIN parameter but rather > requires IEEE-754 propagation of Infinities and NaNs. This > routine also has no input range restrictions but does require > default exception handling such that x/0 produces Inf when x is > non-zero, and Inf/Inf produces NaN. For more information, see: > > Marques, Riedy, and Voemel, "Benefits of IEEE-754 Features in > Modern Symmetric Tridiagonal Eigensolvers," SIAM Journal on > Scientific Computing, v28, n5, 2006. DOI 10.1137/050641624 > (Tech report version in LAWN 172 with the same title.) > \endverbatim Arguments: ========== > \param[in] N > \verbatim > N is INTEGER > The order of the matrix. > \endverbatim > > \param[in] D > \verbatim > D is DOUBLE PRECISION array, dimension (N) > The N diagonal elements of the diagonal matrix D. > \endverbatim > > \param[in] LLD > \verbatim > LLD is DOUBLE PRECISION array, dimension (N-1) > The (N-1) elements L(i)*L(i)*D(i). > \endverbatim > > \param[in] SIGMA > \verbatim > SIGMA is DOUBLE PRECISION > Shift amount in T - sigma I = L D L^T. > \endverbatim > > \param[in] PIVMIN > \verbatim > PIVMIN is DOUBLE PRECISION > The minimum pivot in the Sturm sequence. May be used > when zero pivots are encountered on non-IEEE-754 > architectures. > \endverbatim > > \param[in] R > \verbatim > R is INTEGER > The twist index for the twisted factorization that is used > for the negcount. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERauxiliary > \par Contributors: ================== > > Osni Marques, LBNL/NERSC, USA \n > Christof Voemel, University of California, Berkeley, USA \n > Jason Riedy, University of California, Berkeley, USA \n > ===================================================================== */ integer igraphdlaneg_(integer *n, doublereal *d__, doublereal *lld, doublereal * sigma, doublereal *pivmin, integer *r__) { /* System generated locals */ integer ret_val, i__1, i__2, i__3, i__4; /* Local variables */ integer j; doublereal p, t; integer bj; doublereal tmp; integer neg1, neg2; doublereal bsav, gamma, dplus; extern logical igraphdisnan_(doublereal *); integer negcnt; logical sawnan; doublereal dminus; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Some architectures propagate Infinities and NaNs very slowly, so the code computes counts in BLKLEN chunks. Then a NaN can propagate at most BLKLEN columns before being detected. This is not a general tuning parameter; it needs only to be just large enough that the overhead is tiny in common cases. Parameter adjustments */ --lld; --d__; /* Function Body */ negcnt = 0; /* I) upper part: L D L^T - SIGMA I = L+ D+ L+^T */ t = -(*sigma); i__1 = *r__ - 1; for (bj = 1; bj <= i__1; bj += 128) { neg1 = 0; bsav = t; /* Computing MIN */ i__3 = bj + 127, i__4 = *r__ - 1; i__2 = min(i__3,i__4); for (j = bj; j <= i__2; ++j) { dplus = d__[j] + t; if (dplus < 0.) { ++neg1; } tmp = t / dplus; t = tmp * lld[j] - *sigma; /* L21: */ } sawnan = igraphdisnan_(&t); /* Run a slower version of the above loop if a NaN is detected. A NaN should occur only with a zero pivot after an infinite pivot. In that case, substituting 1 for T/DPLUS is the correct limit. */ if (sawnan) { neg1 = 0; t = bsav; /* Computing MIN */ i__3 = bj + 127, i__4 = *r__ - 1; i__2 = min(i__3,i__4); for (j = bj; j <= i__2; ++j) { dplus = d__[j] + t; if (dplus < 0.) { ++neg1; } tmp = t / dplus; if (igraphdisnan_(&tmp)) { tmp = 1.; } t = tmp * lld[j] - *sigma; /* L22: */ } } negcnt += neg1; /* L210: */ } /* II) lower part: L D L^T - SIGMA I = U- D- U-^T */ p = d__[*n] - *sigma; i__1 = *r__; for (bj = *n - 1; bj >= i__1; bj += -128) { neg2 = 0; bsav = p; /* Computing MAX */ i__3 = bj - 127; i__2 = max(i__3,*r__); for (j = bj; j >= i__2; --j) { dminus = lld[j] + p; if (dminus < 0.) { ++neg2; } tmp = p / dminus; p = tmp * d__[j] - *sigma; /* L23: */ } sawnan = igraphdisnan_(&p); /* As above, run a slower version that substitutes 1 for Inf/Inf. */ if (sawnan) { neg2 = 0; p = bsav; /* Computing MAX */ i__3 = bj - 127; i__2 = max(i__3,*r__); for (j = bj; j >= i__2; --j) { dminus = lld[j] + p; if (dminus < 0.) { ++neg2; } tmp = p / dminus; if (igraphdisnan_(&tmp)) { tmp = 1.; } p = tmp * d__[j] - *sigma; /* L24: */ } } negcnt += neg2; /* L230: */ } /* III) Twist index T was shifted by SIGMA initially. */ gamma = t + *sigma + p; if (gamma < 0.) { ++negcnt; } ret_val = negcnt; return ret_val; } /* igraphdlaneg_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dnaupd.c0000644000076500000240000010175313524616145024266 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; /* \BeginDoc \Name: dnaupd \Description: Reverse communication interface for the Implicitly Restarted Arnoldi iteration. This subroutine computes approximations to a few eigenpairs of a linear operator "OP" with respect to a semi-inner product defined by a symmetric positive semi-definite real matrix B. B may be the identity matrix. NOTE: If the linear operator "OP" is real and symmetric with respect to the real positive semi-definite symmetric matrix B, i.e. B*OP = (OP')*B, then subroutine ssaupd should be used instead. The computed approximate eigenvalues are called Ritz values and the corresponding approximate eigenvectors are called Ritz vectors. dnaupd is usually called iteratively to solve one of the following problems: Mode 1: A*x = lambda*x. ===> OP = A and B = I. Mode 2: A*x = lambda*M*x, M symmetric positive definite ===> OP = inv[M]*A and B = M. ===> (If M can be factored see remark 3 below) Mode 3: A*x = lambda*M*x, M symmetric semi-definite ===> OP = Real_Part{ inv[A - sigma*M]*M } and B = M. ===> shift-and-invert mode (in real arithmetic) If OP*x = amu*x, then amu = 1/2 * [ 1/(lambda-sigma) + 1/(lambda-conjg(sigma)) ]. Note: If sigma is real, i.e. imaginary part of sigma is zero; Real_Part{ inv[A - sigma*M]*M } == inv[A - sigma*M]*M amu == 1/(lambda-sigma). Mode 4: A*x = lambda*M*x, M symmetric semi-definite ===> OP = Imaginary_Part{ inv[A - sigma*M]*M } and B = M. ===> shift-and-invert mode (in real arithmetic) If OP*x = amu*x, then amu = 1/2i * [ 1/(lambda-sigma) - 1/(lambda-conjg(sigma)) ]. Both mode 3 and 4 give the same enhancement to eigenvalues close to the (complex) shift sigma. However, as lambda goes to infinity, the operator OP in mode 4 dampens the eigenvalues more strongly than does OP defined in mode 3. NOTE: The action of w <- inv[A - sigma*M]*v or w <- inv[M]*v should be accomplished either by a direct method using a sparse matrix factorization and solving [A - sigma*M]*w = v or M*w = v, or through an iterative method for solving these systems. If an iterative method is used, the convergence test must be more stringent than the accuracy requirements for the eigenvalue approximations. \Usage: call dnaupd ( IDO, BMAT, N, WHICH, NEV, TOL, RESID, NCV, V, LDV, IPARAM, IPNTR, WORKD, WORKL, LWORKL, INFO ) \Arguments IDO Integer. (INPUT/OUTPUT) Reverse communication flag. IDO must be zero on the first call to dnaupd. IDO will be set internally to indicate the type of operation to be performed. Control is then given back to the calling routine which has the responsibility to carry out the requested operation and call dnaupd with the result. The operand is given in WORKD(IPNTR(1)), the result must be put in WORKD(IPNTR(2)). ------------------------------------------------------------- IDO = 0: first call to the reverse communication interface IDO = -1: compute Y = OP * X where IPNTR(1) is the pointer into WORKD for X, IPNTR(2) is the pointer into WORKD for Y. This is for the initialization phase to force the starting vector into the range of OP. IDO = 1: compute Y = OP * X where IPNTR(1) is the pointer into WORKD for X, IPNTR(2) is the pointer into WORKD for Y. In mode 3 and 4, the vector B * X is already available in WORKD(ipntr(3)). It does not need to be recomputed in forming OP * X. IDO = 2: compute Y = B * X where IPNTR(1) is the pointer into WORKD for X, IPNTR(2) is the pointer into WORKD for Y. IDO = 3: compute the IPARAM(8) real and imaginary parts of the shifts where INPTR(14) is the pointer into WORKL for placing the shifts. See Remark 5 below. IDO = 99: done ------------------------------------------------------------- BMAT Character*1. (INPUT) BMAT specifies the type of the matrix B that defines the semi-inner product for the operator OP. BMAT = 'I' -> standard eigenvalue problem A*x = lambda*x BMAT = 'G' -> generalized eigenvalue problem A*x = lambda*B*x N Integer. (INPUT) Dimension of the eigenproblem. WHICH Character*2. (INPUT) 'LM' -> want the NEV eigenvalues of largest magnitude. 'SM' -> want the NEV eigenvalues of smallest magnitude. 'LR' -> want the NEV eigenvalues of largest real part. 'SR' -> want the NEV eigenvalues of smallest real part. 'LI' -> want the NEV eigenvalues of largest imaginary part. 'SI' -> want the NEV eigenvalues of smallest imaginary part. NEV Integer. (INPUT) Number of eigenvalues of OP to be computed. 0 < NEV < N-1. TOL Double precision scalar. (INPUT) Stopping criterion: the relative accuracy of the Ritz value is considered acceptable if BOUNDS(I) .LE. TOL*ABS(RITZ(I)) where ABS(RITZ(I)) is the magnitude when RITZ(I) is complex. DEFAULT = DLAMCH('EPS') (machine precision as computed by the LAPACK auxiliary subroutine DLAMCH). RESID Double precision array of length N. (INPUT/OUTPUT) On INPUT: If INFO .EQ. 0, a random initial residual vector is used. If INFO .NE. 0, RESID contains the initial residual vector, possibly from a previous run. On OUTPUT: RESID contains the final residual vector. NCV Integer. (INPUT) Number of columns of the matrix V. NCV must satisfy the two inequalities 2 <= NCV-NEV and NCV <= N. This will indicate how many Arnoldi vectors are generated at each iteration. After the startup phase in which NEV Arnoldi vectors are generated, the algorithm generates approximately NCV-NEV Arnoldi vectors at each subsequent update iteration. Most of the cost in generating each Arnoldi vector is in the matrix-vector operation OP*x. NOTE: 2 <= NCV-NEV in order that complex conjugate pairs of Ritz values are kept together. (See remark 4 below) V Double precision array N by NCV. (OUTPUT) Contains the final set of Arnoldi basis vectors. LDV Integer. (INPUT) Leading dimension of V exactly as declared in the calling program. IPARAM Integer array of length 11. (INPUT/OUTPUT) IPARAM(1) = ISHIFT: method for selecting the implicit shifts. The shifts selected at each iteration are used to restart the Arnoldi iteration in an implicit fashion. ------------------------------------------------------------- ISHIFT = 0: the shifts are provided by the user via reverse communication. The real and imaginary parts of the NCV eigenvalues of the Hessenberg matrix H are returned in the part of the WORKL array corresponding to RITZR and RITZI. See remark 5 below. ISHIFT = 1: exact shifts with respect to the current Hessenberg matrix H. This is equivalent to restarting the iteration with a starting vector that is a linear combination of approximate Schur vectors associated with the "wanted" Ritz values. ------------------------------------------------------------- IPARAM(2) = No longer referenced. IPARAM(3) = MXITER On INPUT: maximum number of Arnoldi update iterations allowed. On OUTPUT: actual number of Arnoldi update iterations taken. IPARAM(4) = NB: blocksize to be used in the recurrence. The code currently works only for NB = 1. IPARAM(5) = NCONV: number of "converged" Ritz values. This represents the number of Ritz values that satisfy the convergence criterion. IPARAM(6) = IUPD No longer referenced. Implicit restarting is ALWAYS used. IPARAM(7) = MODE On INPUT determines what type of eigenproblem is being solved. Must be 1,2,3,4; See under \Description of dnaupd for the four modes available. IPARAM(8) = NP When ido = 3 and the user provides shifts through reverse communication (IPARAM(1)=0), dnaupd returns NP, the number of shifts the user is to provide. 0 < NP <=NCV-NEV. See Remark 5 below. IPARAM(9) = NUMOP, IPARAM(10) = NUMOPB, IPARAM(11) = NUMREO, OUTPUT: NUMOP = total number of OP*x operations, NUMOPB = total number of B*x operations if BMAT='G', NUMREO = total number of steps of re-orthogonalization. IPNTR Integer array of length 14. (OUTPUT) Pointer to mark the starting locations in the WORKD and WORKL arrays for matrices/vectors used by the Arnoldi iteration. ------------------------------------------------------------- IPNTR(1): pointer to the current operand vector X in WORKD. IPNTR(2): pointer to the current result vector Y in WORKD. IPNTR(3): pointer to the vector B * X in WORKD when used in the shift-and-invert mode. IPNTR(4): pointer to the next available location in WORKL that is untouched by the program. IPNTR(5): pointer to the NCV by NCV upper Hessenberg matrix H in WORKL. IPNTR(6): pointer to the real part of the ritz value array RITZR in WORKL. IPNTR(7): pointer to the imaginary part of the ritz value array RITZI in WORKL. IPNTR(8): pointer to the Ritz estimates in array WORKL associated with the Ritz values located in RITZR and RITZI in WORKL. IPNTR(14): pointer to the NP shifts in WORKL. See Remark 5 below. Note: IPNTR(9:13) is only referenced by dneupd. See Remark 2 below. IPNTR(9): pointer to the real part of the NCV RITZ values of the original system. IPNTR(10): pointer to the imaginary part of the NCV RITZ values of the original system. IPNTR(11): pointer to the NCV corresponding error bounds. IPNTR(12): pointer to the NCV by NCV upper quasi-triangular Schur matrix for H. IPNTR(13): pointer to the NCV by NCV matrix of eigenvectors of the upper Hessenberg matrix H. Only referenced by dneupd if RVEC = .TRUE. See Remark 2 below. ------------------------------------------------------------- WORKD Double precision work array of length 3*N. (REVERSE COMMUNICATION) Distributed array to be used in the basic Arnoldi iteration for reverse communication. The user should not use WORKD as temporary workspace during the iteration. Upon termination WORKD(1:N) contains B*RESID(1:N). If an invariant subspace associated with the converged Ritz values is desired, see remark 2 below, subroutine dneupd uses this output. See Data Distribution Note below. WORKL Double precision work array of length LWORKL. (OUTPUT/WORKSPACE) Private (replicated) array on each PE or array allocated on the front end. See Data Distribution Note below. LWORKL Integer. (INPUT) LWORKL must be at least 3*NCV**2 + 6*NCV. INFO Integer. (INPUT/OUTPUT) If INFO .EQ. 0, a randomly initial residual vector is used. If INFO .NE. 0, RESID contains the initial residual vector, possibly from a previous run. Error flag on output. = 0: Normal exit. = 1: Maximum number of iterations taken. All possible eigenvalues of OP has been found. IPARAM(5) returns the number of wanted converged Ritz values. = 2: No longer an informational error. Deprecated starting with release 2 of ARPACK. = 3: No shifts could be applied during a cycle of the Implicitly restarted Arnoldi iteration. One possibility is to increase the size of NCV relative to NEV. See remark 4 below. = -1: N must be positive. = -2: NEV must be positive. = -3: NCV-NEV >= 2 and less than or equal to N. = -4: The maximum number of Arnoldi update iteration must be greater than zero. = -5: WHICH must be one of 'LM', 'SM', 'LR', 'SR', 'LI', 'SI' = -6: BMAT must be one of 'I' or 'G'. = -7: Length of private work array is not sufficient. = -8: Error return from LAPACK eigenvalue calculation; = -9: Starting vector is zero. = -10: IPARAM(7) must be 1,2,3,4. = -11: IPARAM(7) = 1 and BMAT = 'G' are incompatable. = -12: IPARAM(1) must be equal to 0 or 1. = -9999: Could not build an Arnoldi factorization. IPARAM(5) returns the size of the current Arnoldi factorization. \Remarks 1. The computed Ritz values are approximate eigenvalues of OP. The selection of WHICH should be made with this in mind when Mode = 3 and 4. After convergence, approximate eigenvalues of the original problem may be obtained with the ARPACK subroutine dneupd. 2. If a basis for the invariant subspace corresponding to the converged Ritz values is needed, the user must call dneupd immediately following completion of dnaupd. This is new starting with release 2 of ARPACK. 3. If M can be factored into a Cholesky factorization M = LL' then Mode = 2 should not be selected. Instead one should use Mode = 1 with OP = inv(L)*A*inv(L'). Appropriate triangular linear systems should be solved with L and L' rather than computing inverses. After convergence, an approximate eigenvector z of the original problem is recovered by solving L'z = x where x is a Ritz vector of OP. 4. At present there is no a-priori analysis to guide the selection of NCV relative to NEV. The only formal requrement is that NCV > NEV + 2. However, it is recommended that NCV .ge. 2*NEV+1. If many problems of the same type are to be solved, one should experiment with increasing NCV while keeping NEV fixed for a given test problem. This will usually decrease the required number of OP*x operations but it also increases the work and storage required to maintain the orthogonal basis vectors. The optimal "cross-over" with respect to CPU time is problem dependent and must be determined empirically. See Chapter 8 of Reference 2 for further information. 5. When IPARAM(1) = 0, and IDO = 3, the user needs to provide the NP = IPARAM(8) real and imaginary parts of the shifts in locations real part imaginary part ----------------------- -------------- 1 WORKL(IPNTR(14)) WORKL(IPNTR(14)+NP) 2 WORKL(IPNTR(14)+1) WORKL(IPNTR(14)+NP+1) . . . . . . NP WORKL(IPNTR(14)+NP-1) WORKL(IPNTR(14)+2*NP-1). Only complex conjugate pairs of shifts may be applied and the pairs must be placed in consecutive locations. The real part of the eigenvalues of the current upper Hessenberg matrix are located in WORKL(IPNTR(6)) through WORKL(IPNTR(6)+NCV-1) and the imaginary part in WORKL(IPNTR(7)) through WORKL(IPNTR(7)+NCV-1). They are ordered according to the order defined by WHICH. The complex conjugate pairs are kept together and the associated Ritz estimates are located in WORKL(IPNTR(8)), WORKL(IPNTR(8)+1), ... , WORKL(IPNTR(8)+NCV-1). ----------------------------------------------------------------------- \Data Distribution Note: Fortran-D syntax: ================ Double precision resid(n), v(ldv,ncv), workd(3*n), workl(lworkl) decompose d1(n), d2(n,ncv) align resid(i) with d1(i) align v(i,j) with d2(i,j) align workd(i) with d1(i) range (1:n) align workd(i) with d1(i-n) range (n+1:2*n) align workd(i) with d1(i-2*n) range (2*n+1:3*n) distribute d1(block), d2(block,:) replicated workl(lworkl) Cray MPP syntax: =============== Double precision resid(n), v(ldv,ncv), workd(n,3), workl(lworkl) shared resid(block), v(block,:), workd(block,:) replicated workl(lworkl) CM2/CM5 syntax: ============== ----------------------------------------------------------------------- include 'ex-nonsym.doc' ----------------------------------------------------------------------- \BeginLib \Local variables: xxxxxx real \References: 1. D.C. Sorensen, "Implicit Application of Polynomial Filters in a k-Step Arnoldi Method", SIAM J. Matr. Anal. Apps., 13 (1992), pp 357-385. 2. R.B. Lehoucq, "Analysis and Implementation of an Implicitly Restarted Arnoldi Iteration", Rice University Technical Report TR95-13, Department of Computational and Applied Mathematics. 3. B.N. Parlett & Y. Saad, "Complex Shift and Invert Strategies for Real Matrices", Linear Algebra and its Applications, vol 88/89, pp 575-595, (1987). \Routines called: dnaup2 ARPACK routine that implements the Implicitly Restarted Arnoldi Iteration. ivout ARPACK utility routine that prints integers. second ARPACK utility routine for timing. dvout ARPACK utility routine that prints vectors. dlamch LAPACK routine that determines machine constants. \Author Danny Sorensen Phuong Vu Richard Lehoucq CRPC / Rice University Dept. of Computational & Houston, Texas Applied Mathematics Rice University Houston, Texas \Revision history: 12/16/93: Version '1.1' \SCCS Information: @(#) FILE: naupd.F SID: 2.5 DATE OF SID: 8/27/96 RELEASE: 2 \Remarks \EndLib ----------------------------------------------------------------------- Subroutine */ int igraphdnaupd_(integer *ido, char *bmat, integer *n, char * which, integer *nev, doublereal *tol, doublereal *resid, integer *ncv, doublereal *v, integer *ldv, integer *iparam, integer *ipntr, doublereal *workd, doublereal *workl, integer *lworkl, integer *info) { /* Format strings */ static char fmt_1000[] = "(//,5x,\002===================================" "==========\002,/5x,\002= Nonsymmetric implicit Arnoldi update co" "de =\002,/5x,\002= Version Number: \002,\002 2.4\002,21x,\002 " "=\002,/5x,\002= Version Date: \002,\002 07/31/96\002,16x,\002 =" "\002,/5x,\002=============================================\002,/" "5x,\002= Summary of timing statistics =\002,/5x," "\002=============================================\002,//)"; static char fmt_1100[] = "(5x,\002Total number update iterations " " = \002,i5,/5x,\002Total number of OP*x operations " " = \002,i5,/5x,\002Total number of B*x operations = " "\002,i5,/5x,\002Total number of reorthogonalization steps = " "\002,i5,/5x,\002Total number of iterative refinement steps = " "\002,i5,/5x,\002Total number of restart steps = " "\002,i5,/5x,\002Total time in user OP*x operation = " "\002,f12.6,/5x,\002Total time in user B*x operation =" " \002,f12.6,/5x,\002Total time in Arnoldi update routine = " "\002,f12.6,/5x,\002Total time in naup2 routine =" " \002,f12.6,/5x,\002Total time in basic Arnoldi iteration loop = " "\002,f12.6,/5x,\002Total time in reorthogonalization phase =" " \002,f12.6,/5x,\002Total time in (re)start vector generation = " "\002,f12.6,/5x,\002Total time in Hessenberg eig. subproblem =" " \002,f12.6,/5x,\002Total time in getting the shifts = " "\002,f12.6,/5x,\002Total time in applying the shifts =" " \002,f12.6,/5x,\002Total time in convergence testing = " "\002,f12.6,/5x,\002Total time in computing final Ritz vectors =" " \002,f12.6/)"; /* System generated locals */ integer v_dim1, v_offset, i__1, i__2; /* Builtin functions */ integer s_cmp(char *, char *, ftnlen, ftnlen), s_wsfe(cilist *), e_wsfe( void), do_fio(integer *, char *, ftnlen); /* Local variables */ integer j; real t0, t1; IGRAPH_F77_SAVE integer nb, ih, iq, np, iw, ldh, ldq; integer nbx = 0; IGRAPH_F77_SAVE integer nev0, mode; integer ierr; IGRAPH_F77_SAVE integer iupd, next; integer nopx = 0; IGRAPH_F77_SAVE integer levec; real trvec, tmvbx; IGRAPH_F77_SAVE integer ritzi; extern /* Subroutine */ int igraphdvout_(integer *, integer *, doublereal *, integer *, char *, ftnlen), igraphivout_(integer *, integer *, integer * , integer *, char *, ftnlen); IGRAPH_F77_SAVE integer ritzr; extern /* Subroutine */ int igraphdnaup2_(integer *, char *, integer *, char *, integer *, integer *, doublereal *, doublereal *, integer *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, integer *); real tnaup2, tgetv0; extern doublereal igraphdlamch_(char *); extern /* Subroutine */ int igraphsecond_(real *); integer logfil, ndigit; real tneigh; integer mnaupd = 0; IGRAPH_F77_SAVE integer ishift; integer nitref; IGRAPH_F77_SAVE integer bounds; real tnaupd; extern /* Subroutine */ int igraphdstatn_(void); real titref, tnaitr; IGRAPH_F77_SAVE integer msglvl; real tngets, tnapps, tnconv; IGRAPH_F77_SAVE integer mxiter; integer nrorth = 0, nrstrt = 0; real tmvopx; /* Fortran I/O blocks */ static cilist io___30 = { 0, 6, 0, fmt_1000, 0 }; static cilist io___31 = { 0, 6, 0, fmt_1100, 0 }; /* %----------------------------------------------------% | Include files for debugging and timing information | %----------------------------------------------------% %------------------% | Scalar Arguments | %------------------% %-----------------% | Array Arguments | %-----------------% %------------% | Parameters | %------------% %---------------% | Local Scalars | %---------------% %----------------------% | External Subroutines | %----------------------% %--------------------% | External Functions | %--------------------% %-----------------------% | Executable Statements | %-----------------------% Parameter adjustments */ --workd; --resid; v_dim1 = *ldv; v_offset = 1 + v_dim1; v -= v_offset; --iparam; --ipntr; --workl; /* Function Body */ if (*ido == 0) { /* %-------------------------------% | Initialize timing statistics | | & message level for debugging | %-------------------------------% */ igraphdstatn_(); igraphsecond_(&t0); msglvl = mnaupd; /* %----------------% | Error checking | %----------------% */ ierr = 0; ishift = iparam[1]; levec = iparam[2]; mxiter = iparam[3]; nb = iparam[4]; /* %--------------------------------------------% | Revision 2 performs only implicit restart. | %--------------------------------------------% */ iupd = 1; mode = iparam[7]; if (*n <= 0) { ierr = -1; } else if (*nev <= 0) { ierr = -2; } else if (*ncv <= *nev + 1 || *ncv > *n) { ierr = -3; } else if (mxiter <= 0) { ierr = -4; } else if (s_cmp(which, "LM", (ftnlen)2, (ftnlen)2) != 0 && s_cmp( which, "SM", (ftnlen)2, (ftnlen)2) != 0 && s_cmp(which, "LR", (ftnlen)2, (ftnlen)2) != 0 && s_cmp(which, "SR", (ftnlen)2, ( ftnlen)2) != 0 && s_cmp(which, "LI", (ftnlen)2, (ftnlen)2) != 0 && s_cmp(which, "SI", (ftnlen)2, (ftnlen)2) != 0) { ierr = -5; } else if (*(unsigned char *)bmat != 'I' && *(unsigned char *)bmat != 'G') { ierr = -6; } else /* if(complicated condition) */ { /* Computing 2nd power */ i__1 = *ncv; if (*lworkl < i__1 * i__1 * 3 + *ncv * 6) { ierr = -7; } else if (mode < 1 || mode > 5) { ierr = -10; } else if (mode == 1 && *(unsigned char *)bmat == 'G') { ierr = -11; } else if (ishift < 0 || ishift > 1) { ierr = -12; } } /* %------------% | Error Exit | %------------% */ if (ierr != 0) { *info = ierr; *ido = 99; goto L9000; } /* %------------------------% | Set default parameters | %------------------------% */ if (nb <= 0) { nb = 1; } if (*tol <= 0.) { *tol = igraphdlamch_("EpsMach"); } /* %----------------------------------------------% | NP is the number of additional steps to | | extend the length NEV Lanczos factorization. | | NEV0 is the local variable designating the | | size of the invariant subspace desired. | %----------------------------------------------% */ np = *ncv - *nev; nev0 = *nev; /* %-----------------------------% | Zero out internal workspace | %-----------------------------% Computing 2nd power */ i__2 = *ncv; i__1 = i__2 * i__2 * 3 + *ncv * 6; for (j = 1; j <= i__1; ++j) { workl[j] = 0.; /* L10: */ } /* %-------------------------------------------------------------% | Pointer into WORKL for address of H, RITZ, BOUNDS, Q | | etc... and the remaining workspace. | | Also update pointer to be used on output. | | Memory is laid out as follows: | | workl(1:ncv*ncv) := generated Hessenberg matrix | | workl(ncv*ncv+1:ncv*ncv+2*ncv) := real and imaginary | | parts of ritz values | | workl(ncv*ncv+2*ncv+1:ncv*ncv+3*ncv) := error bounds | | workl(ncv*ncv+3*ncv+1:2*ncv*ncv+3*ncv) := rotation matrix Q | | workl(2*ncv*ncv+3*ncv+1:3*ncv*ncv+6*ncv) := workspace | | The final workspace is needed by subroutine dneigh called | | by dnaup2. Subroutine dneigh calls LAPACK routines for | | calculating eigenvalues and the last row of the eigenvector | | matrix. | %-------------------------------------------------------------% */ ldh = *ncv; ldq = *ncv; ih = 1; ritzr = ih + ldh * *ncv; ritzi = ritzr + *ncv; bounds = ritzi + *ncv; iq = bounds + *ncv; iw = iq + ldq * *ncv; /* Computing 2nd power */ i__1 = *ncv; next = iw + i__1 * i__1 + *ncv * 3; ipntr[4] = next; ipntr[5] = ih; ipntr[6] = ritzr; ipntr[7] = ritzi; ipntr[8] = bounds; ipntr[14] = iw; } /* %-------------------------------------------------------% | Carry out the Implicitly restarted Arnoldi Iteration. | %-------------------------------------------------------% */ igraphdnaup2_(ido, bmat, n, which, &nev0, &np, tol, &resid[1], &mode, &iupd, & ishift, &mxiter, &v[v_offset], ldv, &workl[ih], &ldh, &workl[ ritzr], &workl[ritzi], &workl[bounds], &workl[iq], &ldq, &workl[ iw], &ipntr[1], &workd[1], info); /* %--------------------------------------------------% | ido .ne. 99 implies use of reverse communication | | to compute operations involving OP or shifts. | %--------------------------------------------------% */ if (*ido == 3) { iparam[8] = np; } if (*ido != 99) { goto L9000; } iparam[3] = mxiter; iparam[5] = np; iparam[9] = nopx; iparam[10] = nbx; iparam[11] = nrorth; /* %------------------------------------% | Exit if there was an informational | | error within dnaup2. | %------------------------------------% */ if (*info < 0) { goto L9000; } if (*info == 2) { *info = 3; } if (msglvl > 0) { igraphivout_(&logfil, &c__1, &mxiter, &ndigit, "_naupd: Number of update i" "terations taken", (ftnlen)41); igraphivout_(&logfil, &c__1, &np, &ndigit, "_naupd: Number of wanted \"con" "verged\" Ritz values", (ftnlen)48); igraphdvout_(&logfil, &np, &workl[ritzr], &ndigit, "_naupd: Real part of t" "he final Ritz values", (ftnlen)42); igraphdvout_(&logfil, &np, &workl[ritzi], &ndigit, "_naupd: Imaginary part" " of the final Ritz values", (ftnlen)47); igraphdvout_(&logfil, &np, &workl[bounds], &ndigit, "_naupd: Associated Ri" "tz estimates", (ftnlen)33); } igraphsecond_(&t1); tnaupd = t1 - t0; if (msglvl > 0) { /* %--------------------------------------------------------% | Version Number & Version Date are defined in version.h | %--------------------------------------------------------% */ s_wsfe(&io___30); e_wsfe(); s_wsfe(&io___31); do_fio(&c__1, (char *)&mxiter, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&nopx, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&nbx, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&nrorth, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&nitref, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&nrstrt, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&tmvopx, (ftnlen)sizeof(real)); do_fio(&c__1, (char *)&tmvbx, (ftnlen)sizeof(real)); do_fio(&c__1, (char *)&tnaupd, (ftnlen)sizeof(real)); do_fio(&c__1, (char *)&tnaup2, (ftnlen)sizeof(real)); do_fio(&c__1, (char *)&tnaitr, (ftnlen)sizeof(real)); do_fio(&c__1, (char *)&titref, (ftnlen)sizeof(real)); do_fio(&c__1, (char *)&tgetv0, (ftnlen)sizeof(real)); do_fio(&c__1, (char *)&tneigh, (ftnlen)sizeof(real)); do_fio(&c__1, (char *)&tngets, (ftnlen)sizeof(real)); do_fio(&c__1, (char *)&tnapps, (ftnlen)sizeof(real)); do_fio(&c__1, (char *)&tnconv, (ftnlen)sizeof(real)); do_fio(&c__1, (char *)&trvec, (ftnlen)sizeof(real)); e_wsfe(); } L9000: return 0; /* %---------------% | End of dnaupd | %---------------% */ } /* igraphdnaupd_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dorghr.c0000644000076500000240000001715513524616145024302 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static integer c_n1 = -1; /* > \brief \b DORGHR =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DORGHR + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DORGHR( N, ILO, IHI, A, LDA, TAU, WORK, LWORK, INFO ) INTEGER IHI, ILO, INFO, LDA, LWORK, N DOUBLE PRECISION A( LDA, * ), TAU( * ), WORK( * ) > \par Purpose: ============= > > \verbatim > > DORGHR generates a real orthogonal matrix Q which is defined as the > product of IHI-ILO elementary reflectors of order N, as returned by > DGEHRD: > > Q = H(ilo) H(ilo+1) . . . H(ihi-1). > \endverbatim Arguments: ========== > \param[in] N > \verbatim > N is INTEGER > The order of the matrix Q. N >= 0. > \endverbatim > > \param[in] ILO > \verbatim > ILO is INTEGER > \endverbatim > > \param[in] IHI > \verbatim > IHI is INTEGER > > ILO and IHI must have the same values as in the previous call > of DGEHRD. Q is equal to the unit matrix except in the > submatrix Q(ilo+1:ihi,ilo+1:ihi). > 1 <= ILO <= IHI <= N, if N > 0; ILO=1 and IHI=0, if N=0. > \endverbatim > > \param[in,out] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,N) > On entry, the vectors which define the elementary reflectors, > as returned by DGEHRD. > On exit, the N-by-N orthogonal matrix Q. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. LDA >= max(1,N). > \endverbatim > > \param[in] TAU > \verbatim > TAU is DOUBLE PRECISION array, dimension (N-1) > TAU(i) must contain the scalar factor of the elementary > reflector H(i), as returned by DGEHRD. > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (MAX(1,LWORK)) > On exit, if INFO = 0, WORK(1) returns the optimal LWORK. > \endverbatim > > \param[in] LWORK > \verbatim > LWORK is INTEGER > The dimension of the array WORK. LWORK >= IHI-ILO. > For optimum performance LWORK >= (IHI-ILO)*NB, where NB is > the optimal blocksize. > > If LWORK = -1, then a workspace query is assumed; the routine > only calculates the optimal size of the WORK array, returns > this value as the first entry of the WORK array, and no error > message related to LWORK is issued by XERBLA. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2011 > \ingroup doubleOTHERcomputational ===================================================================== Subroutine */ int igraphdorghr_(integer *n, integer *ilo, integer *ihi, doublereal *a, integer *lda, doublereal *tau, doublereal *work, integer *lwork, integer *info) { /* System generated locals */ integer a_dim1, a_offset, i__1, i__2; /* Local variables */ integer i__, j, nb, nh, iinfo; extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); extern integer igraphilaenv_(integer *, char *, char *, integer *, integer *, integer *, integer *, ftnlen, ftnlen); extern /* Subroutine */ int igraphdorgqr_(integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, integer *); integer lwkopt; logical lquery; /* -- LAPACK computational routine (version 3.4.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2011 ===================================================================== Test the input arguments Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --tau; --work; /* Function Body */ *info = 0; nh = *ihi - *ilo; lquery = *lwork == -1; if (*n < 0) { *info = -1; } else if (*ilo < 1 || *ilo > max(1,*n)) { *info = -2; } else if (*ihi < min(*ilo,*n) || *ihi > *n) { *info = -3; } else if (*lda < max(1,*n)) { *info = -5; } else if (*lwork < max(1,nh) && ! lquery) { *info = -8; } if (*info == 0) { nb = igraphilaenv_(&c__1, "DORGQR", " ", &nh, &nh, &nh, &c_n1, (ftnlen)6, ( ftnlen)1); lwkopt = max(1,nh) * nb; work[1] = (doublereal) lwkopt; } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DORGHR", &i__1, (ftnlen)6); return 0; } else if (lquery) { return 0; } /* Quick return if possible */ if (*n == 0) { work[1] = 1.; return 0; } /* Shift the vectors which define the elementary reflectors one column to the right, and set the first ilo and the last n-ihi rows and columns to those of the unit matrix */ i__1 = *ilo + 1; for (j = *ihi; j >= i__1; --j) { i__2 = j - 1; for (i__ = 1; i__ <= i__2; ++i__) { a[i__ + j * a_dim1] = 0.; /* L10: */ } i__2 = *ihi; for (i__ = j + 1; i__ <= i__2; ++i__) { a[i__ + j * a_dim1] = a[i__ + (j - 1) * a_dim1]; /* L20: */ } i__2 = *n; for (i__ = *ihi + 1; i__ <= i__2; ++i__) { a[i__ + j * a_dim1] = 0.; /* L30: */ } /* L40: */ } i__1 = *ilo; for (j = 1; j <= i__1; ++j) { i__2 = *n; for (i__ = 1; i__ <= i__2; ++i__) { a[i__ + j * a_dim1] = 0.; /* L50: */ } a[j + j * a_dim1] = 1.; /* L60: */ } i__1 = *n; for (j = *ihi + 1; j <= i__1; ++j) { i__2 = *n; for (i__ = 1; i__ <= i__2; ++i__) { a[i__ + j * a_dim1] = 0.; /* L70: */ } a[j + j * a_dim1] = 1.; /* L80: */ } if (nh > 0) { /* Generate Q(ilo+1:ihi,ilo+1:ihi) */ igraphdorgqr_(&nh, &nh, &nh, &a[*ilo + 1 + (*ilo + 1) * a_dim1], lda, &tau[* ilo], &work[1], lwork, &iinfo); } work[1] = (doublereal) lwkopt; return 0; /* End of DORGHR */ } /* igraphdorghr_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dsteqr.c0000644000076500000240000004051413524616145024312 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static doublereal c_b9 = 0.; static doublereal c_b10 = 1.; static integer c__0 = 0; static integer c__1 = 1; static integer c__2 = 2; /* > \brief \b DSTEQR =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DSTEQR + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DSTEQR( COMPZ, N, D, E, Z, LDZ, WORK, INFO ) CHARACTER COMPZ INTEGER INFO, LDZ, N DOUBLE PRECISION D( * ), E( * ), WORK( * ), Z( LDZ, * ) > \par Purpose: ============= > > \verbatim > > DSTEQR computes all eigenvalues and, optionally, eigenvectors of a > symmetric tridiagonal matrix using the implicit QL or QR method. > The eigenvectors of a full or band symmetric matrix can also be found > if DSYTRD or DSPTRD or DSBTRD has been used to reduce this matrix to > tridiagonal form. > \endverbatim Arguments: ========== > \param[in] COMPZ > \verbatim > COMPZ is CHARACTER*1 > = 'N': Compute eigenvalues only. > = 'V': Compute eigenvalues and eigenvectors of the original > symmetric matrix. On entry, Z must contain the > orthogonal matrix used to reduce the original matrix > to tridiagonal form. > = 'I': Compute eigenvalues and eigenvectors of the > tridiagonal matrix. Z is initialized to the identity > matrix. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix. N >= 0. > \endverbatim > > \param[in,out] D > \verbatim > D is DOUBLE PRECISION array, dimension (N) > On entry, the diagonal elements of the tridiagonal matrix. > On exit, if INFO = 0, the eigenvalues in ascending order. > \endverbatim > > \param[in,out] E > \verbatim > E is DOUBLE PRECISION array, dimension (N-1) > On entry, the (n-1) subdiagonal elements of the tridiagonal > matrix. > On exit, E has been destroyed. > \endverbatim > > \param[in,out] Z > \verbatim > Z is DOUBLE PRECISION array, dimension (LDZ, N) > On entry, if COMPZ = 'V', then Z contains the orthogonal > matrix used in the reduction to tridiagonal form. > On exit, if INFO = 0, then if COMPZ = 'V', Z contains the > orthonormal eigenvectors of the original symmetric matrix, > and if COMPZ = 'I', Z contains the orthonormal eigenvectors > of the symmetric tridiagonal matrix. > If COMPZ = 'N', then Z is not referenced. > \endverbatim > > \param[in] LDZ > \verbatim > LDZ is INTEGER > The leading dimension of the array Z. LDZ >= 1, and if > eigenvectors are desired, then LDZ >= max(1,N). > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (max(1,2*N-2)) > If COMPZ = 'N', then WORK is not referenced. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value > > 0: the algorithm has failed to find all the eigenvalues in > a total of 30*N iterations; if INFO = i, then i > elements of E have not converged to zero; on exit, D > and E contain the elements of a symmetric tridiagonal > matrix which is orthogonally similar to the original > matrix. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2011 > \ingroup auxOTHERcomputational ===================================================================== Subroutine */ int igraphdsteqr_(char *compz, integer *n, doublereal *d__, doublereal *e, doublereal *z__, integer *ldz, doublereal *work, integer *info) { /* System generated locals */ integer z_dim1, z_offset, i__1, i__2; doublereal d__1, d__2; /* Builtin functions */ double sqrt(doublereal), d_sign(doublereal *, doublereal *); /* Local variables */ doublereal b, c__, f, g; integer i__, j, k, l, m; doublereal p, r__, s; integer l1, ii, mm, lm1, mm1, nm1; doublereal rt1, rt2, eps; integer lsv; doublereal tst, eps2; integer lend, jtot; extern /* Subroutine */ int igraphdlae2_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *); extern logical igraphlsame_(char *, char *); extern /* Subroutine */ int igraphdlasr_(char *, char *, char *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *); doublereal anorm; extern /* Subroutine */ int igraphdswap_(integer *, doublereal *, integer *, doublereal *, integer *), igraphdlaev2_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *); integer lendm1, lendp1; extern doublereal igraphdlapy2_(doublereal *, doublereal *), igraphdlamch_(char *); integer iscale; extern /* Subroutine */ int igraphdlascl_(char *, integer *, integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, integer *, integer *), igraphdlaset_(char *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *); doublereal safmin; extern /* Subroutine */ int igraphdlartg_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *); doublereal safmax; extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); extern doublereal igraphdlanst_(char *, integer *, doublereal *, doublereal *); extern /* Subroutine */ int igraphdlasrt_(char *, integer *, doublereal *, integer *); integer lendsv; doublereal ssfmin; integer nmaxit, icompz; doublereal ssfmax; /* -- LAPACK computational routine (version 3.4.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2011 ===================================================================== Test the input parameters. Parameter adjustments */ --d__; --e; z_dim1 = *ldz; z_offset = 1 + z_dim1; z__ -= z_offset; --work; /* Function Body */ *info = 0; if (igraphlsame_(compz, "N")) { icompz = 0; } else if (igraphlsame_(compz, "V")) { icompz = 1; } else if (igraphlsame_(compz, "I")) { icompz = 2; } else { icompz = -1; } if (icompz < 0) { *info = -1; } else if (*n < 0) { *info = -2; } else if (*ldz < 1 || icompz > 0 && *ldz < max(1,*n)) { *info = -6; } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DSTEQR", &i__1, (ftnlen)6); return 0; } /* Quick return if possible */ if (*n == 0) { return 0; } if (*n == 1) { if (icompz == 2) { z__[z_dim1 + 1] = 1.; } return 0; } /* Determine the unit roundoff and over/underflow thresholds. */ eps = igraphdlamch_("E"); /* Computing 2nd power */ d__1 = eps; eps2 = d__1 * d__1; safmin = igraphdlamch_("S"); safmax = 1. / safmin; ssfmax = sqrt(safmax) / 3.; ssfmin = sqrt(safmin) / eps2; /* Compute the eigenvalues and eigenvectors of the tridiagonal matrix. */ if (icompz == 2) { igraphdlaset_("Full", n, n, &c_b9, &c_b10, &z__[z_offset], ldz); } nmaxit = *n * 30; jtot = 0; /* Determine where the matrix splits and choose QL or QR iteration for each block, according to whether top or bottom diagonal element is smaller. */ l1 = 1; nm1 = *n - 1; L10: if (l1 > *n) { goto L160; } if (l1 > 1) { e[l1 - 1] = 0.; } if (l1 <= nm1) { i__1 = nm1; for (m = l1; m <= i__1; ++m) { tst = (d__1 = e[m], abs(d__1)); if (tst == 0.) { goto L30; } if (tst <= sqrt((d__1 = d__[m], abs(d__1))) * sqrt((d__2 = d__[m + 1], abs(d__2))) * eps) { e[m] = 0.; goto L30; } /* L20: */ } } m = *n; L30: l = l1; lsv = l; lend = m; lendsv = lend; l1 = m + 1; if (lend == l) { goto L10; } /* Scale submatrix in rows and columns L to LEND */ i__1 = lend - l + 1; anorm = igraphdlanst_("M", &i__1, &d__[l], &e[l]); iscale = 0; if (anorm == 0.) { goto L10; } if (anorm > ssfmax) { iscale = 1; i__1 = lend - l + 1; igraphdlascl_("G", &c__0, &c__0, &anorm, &ssfmax, &i__1, &c__1, &d__[l], n, info); i__1 = lend - l; igraphdlascl_("G", &c__0, &c__0, &anorm, &ssfmax, &i__1, &c__1, &e[l], n, info); } else if (anorm < ssfmin) { iscale = 2; i__1 = lend - l + 1; igraphdlascl_("G", &c__0, &c__0, &anorm, &ssfmin, &i__1, &c__1, &d__[l], n, info); i__1 = lend - l; igraphdlascl_("G", &c__0, &c__0, &anorm, &ssfmin, &i__1, &c__1, &e[l], n, info); } /* Choose between QL and QR iteration */ if ((d__1 = d__[lend], abs(d__1)) < (d__2 = d__[l], abs(d__2))) { lend = lsv; l = lendsv; } if (lend > l) { /* QL Iteration Look for small subdiagonal element. */ L40: if (l != lend) { lendm1 = lend - 1; i__1 = lendm1; for (m = l; m <= i__1; ++m) { /* Computing 2nd power */ d__2 = (d__1 = e[m], abs(d__1)); tst = d__2 * d__2; if (tst <= eps2 * (d__1 = d__[m], abs(d__1)) * (d__2 = d__[m + 1], abs(d__2)) + safmin) { goto L60; } /* L50: */ } } m = lend; L60: if (m < lend) { e[m] = 0.; } p = d__[l]; if (m == l) { goto L80; } /* If remaining matrix is 2-by-2, use DLAE2 or SLAEV2 to compute its eigensystem. */ if (m == l + 1) { if (icompz > 0) { igraphdlaev2_(&d__[l], &e[l], &d__[l + 1], &rt1, &rt2, &c__, &s); work[l] = c__; work[*n - 1 + l] = s; igraphdlasr_("R", "V", "B", n, &c__2, &work[l], &work[*n - 1 + l], & z__[l * z_dim1 + 1], ldz); } else { igraphdlae2_(&d__[l], &e[l], &d__[l + 1], &rt1, &rt2); } d__[l] = rt1; d__[l + 1] = rt2; e[l] = 0.; l += 2; if (l <= lend) { goto L40; } goto L140; } if (jtot == nmaxit) { goto L140; } ++jtot; /* Form shift. */ g = (d__[l + 1] - p) / (e[l] * 2.); r__ = igraphdlapy2_(&g, &c_b10); g = d__[m] - p + e[l] / (g + d_sign(&r__, &g)); s = 1.; c__ = 1.; p = 0.; /* Inner loop */ mm1 = m - 1; i__1 = l; for (i__ = mm1; i__ >= i__1; --i__) { f = s * e[i__]; b = c__ * e[i__]; igraphdlartg_(&g, &f, &c__, &s, &r__); if (i__ != m - 1) { e[i__ + 1] = r__; } g = d__[i__ + 1] - p; r__ = (d__[i__] - g) * s + c__ * 2. * b; p = s * r__; d__[i__ + 1] = g + p; g = c__ * r__ - b; /* If eigenvectors are desired, then save rotations. */ if (icompz > 0) { work[i__] = c__; work[*n - 1 + i__] = -s; } /* L70: */ } /* If eigenvectors are desired, then apply saved rotations. */ if (icompz > 0) { mm = m - l + 1; igraphdlasr_("R", "V", "B", n, &mm, &work[l], &work[*n - 1 + l], &z__[l * z_dim1 + 1], ldz); } d__[l] -= p; e[l] = g; goto L40; /* Eigenvalue found. */ L80: d__[l] = p; ++l; if (l <= lend) { goto L40; } goto L140; } else { /* QR Iteration Look for small superdiagonal element. */ L90: if (l != lend) { lendp1 = lend + 1; i__1 = lendp1; for (m = l; m >= i__1; --m) { /* Computing 2nd power */ d__2 = (d__1 = e[m - 1], abs(d__1)); tst = d__2 * d__2; if (tst <= eps2 * (d__1 = d__[m], abs(d__1)) * (d__2 = d__[m - 1], abs(d__2)) + safmin) { goto L110; } /* L100: */ } } m = lend; L110: if (m > lend) { e[m - 1] = 0.; } p = d__[l]; if (m == l) { goto L130; } /* If remaining matrix is 2-by-2, use DLAE2 or SLAEV2 to compute its eigensystem. */ if (m == l - 1) { if (icompz > 0) { igraphdlaev2_(&d__[l - 1], &e[l - 1], &d__[l], &rt1, &rt2, &c__, &s) ; work[m] = c__; work[*n - 1 + m] = s; igraphdlasr_("R", "V", "F", n, &c__2, &work[m], &work[*n - 1 + m], & z__[(l - 1) * z_dim1 + 1], ldz); } else { igraphdlae2_(&d__[l - 1], &e[l - 1], &d__[l], &rt1, &rt2); } d__[l - 1] = rt1; d__[l] = rt2; e[l - 1] = 0.; l += -2; if (l >= lend) { goto L90; } goto L140; } if (jtot == nmaxit) { goto L140; } ++jtot; /* Form shift. */ g = (d__[l - 1] - p) / (e[l - 1] * 2.); r__ = igraphdlapy2_(&g, &c_b10); g = d__[m] - p + e[l - 1] / (g + d_sign(&r__, &g)); s = 1.; c__ = 1.; p = 0.; /* Inner loop */ lm1 = l - 1; i__1 = lm1; for (i__ = m; i__ <= i__1; ++i__) { f = s * e[i__]; b = c__ * e[i__]; igraphdlartg_(&g, &f, &c__, &s, &r__); if (i__ != m) { e[i__ - 1] = r__; } g = d__[i__] - p; r__ = (d__[i__ + 1] - g) * s + c__ * 2. * b; p = s * r__; d__[i__] = g + p; g = c__ * r__ - b; /* If eigenvectors are desired, then save rotations. */ if (icompz > 0) { work[i__] = c__; work[*n - 1 + i__] = s; } /* L120: */ } /* If eigenvectors are desired, then apply saved rotations. */ if (icompz > 0) { mm = l - m + 1; igraphdlasr_("R", "V", "F", n, &mm, &work[m], &work[*n - 1 + m], &z__[m * z_dim1 + 1], ldz); } d__[l] -= p; e[lm1] = g; goto L90; /* Eigenvalue found. */ L130: d__[l] = p; --l; if (l >= lend) { goto L90; } goto L140; } /* Undo scaling if necessary */ L140: if (iscale == 1) { i__1 = lendsv - lsv + 1; igraphdlascl_("G", &c__0, &c__0, &ssfmax, &anorm, &i__1, &c__1, &d__[lsv], n, info); i__1 = lendsv - lsv; igraphdlascl_("G", &c__0, &c__0, &ssfmax, &anorm, &i__1, &c__1, &e[lsv], n, info); } else if (iscale == 2) { i__1 = lendsv - lsv + 1; igraphdlascl_("G", &c__0, &c__0, &ssfmin, &anorm, &i__1, &c__1, &d__[lsv], n, info); i__1 = lendsv - lsv; igraphdlascl_("G", &c__0, &c__0, &ssfmin, &anorm, &i__1, &c__1, &e[lsv], n, info); } /* Check for no convergence to an eigenvalue after a total of N*MAXIT iterations. */ if (jtot < nmaxit) { goto L10; } i__1 = *n - 1; for (i__ = 1; i__ <= i__1; ++i__) { if (e[i__] != 0.) { ++(*info); } /* L150: */ } goto L190; /* Order eigenvalues and eigenvectors. */ L160: if (icompz == 0) { /* Use Quick Sort */ igraphdlasrt_("I", n, &d__[1], info); } else { /* Use Selection Sort to minimize swaps of eigenvectors */ i__1 = *n; for (ii = 2; ii <= i__1; ++ii) { i__ = ii - 1; k = i__; p = d__[i__]; i__2 = *n; for (j = ii; j <= i__2; ++j) { if (d__[j] < p) { k = j; p = d__[j]; } /* L170: */ } if (k != i__) { d__[k] = d__[i__]; d__[i__] = p; igraphdswap_(n, &z__[i__ * z_dim1 + 1], &c__1, &z__[k * z_dim1 + 1], &c__1); } /* L180: */ } } L190: return 0; /* End of DSTEQR */ } /* igraphdsteqr_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlaqtr.c0000644000076500000240000005565613524616145024314 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static logical c_false = FALSE_; static integer c__2 = 2; static doublereal c_b21 = 1.; static doublereal c_b25 = 0.; static logical c_true = TRUE_; /* > \brief \b DLAQTR solves a real quasi-triangular system of equations, or a complex quasi-triangular system of special form, in real arithmetic. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLAQTR + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLAQTR( LTRAN, LREAL, N, T, LDT, B, W, SCALE, X, WORK, INFO ) LOGICAL LREAL, LTRAN INTEGER INFO, LDT, N DOUBLE PRECISION SCALE, W DOUBLE PRECISION B( * ), T( LDT, * ), WORK( * ), X( * ) > \par Purpose: ============= > > \verbatim > > DLAQTR solves the real quasi-triangular system > > op(T)*p = scale*c, if LREAL = .TRUE. > > or the complex quasi-triangular systems > > op(T + iB)*(p+iq) = scale*(c+id), if LREAL = .FALSE. > > in real arithmetic, where T is upper quasi-triangular. > If LREAL = .FALSE., then the first diagonal block of T must be > 1 by 1, B is the specially structured matrix > > B = [ b(1) b(2) ... b(n) ] > [ w ] > [ w ] > [ . ] > [ w ] > > op(A) = A or A**T, A**T denotes the transpose of > matrix A. > > On input, X = [ c ]. On output, X = [ p ]. > [ d ] [ q ] > > This subroutine is designed for the condition number estimation > in routine DTRSNA. > \endverbatim Arguments: ========== > \param[in] LTRAN > \verbatim > LTRAN is LOGICAL > On entry, LTRAN specifies the option of conjugate transpose: > = .FALSE., op(T+i*B) = T+i*B, > = .TRUE., op(T+i*B) = (T+i*B)**T. > \endverbatim > > \param[in] LREAL > \verbatim > LREAL is LOGICAL > On entry, LREAL specifies the input matrix structure: > = .FALSE., the input is complex > = .TRUE., the input is real > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > On entry, N specifies the order of T+i*B. N >= 0. > \endverbatim > > \param[in] T > \verbatim > T is DOUBLE PRECISION array, dimension (LDT,N) > On entry, T contains a matrix in Schur canonical form. > If LREAL = .FALSE., then the first diagonal block of T mu > be 1 by 1. > \endverbatim > > \param[in] LDT > \verbatim > LDT is INTEGER > The leading dimension of the matrix T. LDT >= max(1,N). > \endverbatim > > \param[in] B > \verbatim > B is DOUBLE PRECISION array, dimension (N) > On entry, B contains the elements to form the matrix > B as described above. > If LREAL = .TRUE., B is not referenced. > \endverbatim > > \param[in] W > \verbatim > W is DOUBLE PRECISION > On entry, W is the diagonal element of the matrix B. > If LREAL = .TRUE., W is not referenced. > \endverbatim > > \param[out] SCALE > \verbatim > SCALE is DOUBLE PRECISION > On exit, SCALE is the scale factor. > \endverbatim > > \param[in,out] X > \verbatim > X is DOUBLE PRECISION array, dimension (2*N) > On entry, X contains the right hand side of the system. > On exit, X is overwritten by the solution. > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (N) > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > On exit, INFO is set to > 0: successful exit. > 1: the some diagonal 1 by 1 block has been perturbed by > a small number SMIN to keep nonsingularity. > 2: the some diagonal 2 by 2 block has been perturbed by > a small number in DLALN2 to keep nonsingularity. > NOTE: In the interests of speed, this routine does not > check the inputs for errors. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleOTHERauxiliary ===================================================================== Subroutine */ int igraphdlaqtr_(logical *ltran, logical *lreal, integer *n, doublereal *t, integer *ldt, doublereal *b, doublereal *w, doublereal *scale, doublereal *x, doublereal *work, integer *info) { /* System generated locals */ integer t_dim1, t_offset, i__1, i__2; doublereal d__1, d__2, d__3, d__4, d__5, d__6; /* Local variables */ doublereal d__[4] /* was [2][2] */; integer i__, j, k; doublereal v[4] /* was [2][2] */, z__; integer j1, j2, n1, n2; doublereal si, xj, sr, rec, eps, tjj, tmp; extern doublereal igraphddot_(integer *, doublereal *, integer *, doublereal *, integer *); integer ierr; doublereal smin, xmax; extern /* Subroutine */ int igraphdscal_(integer *, doublereal *, doublereal *, integer *); extern doublereal igraphdasum_(integer *, doublereal *, integer *); extern /* Subroutine */ int igraphdaxpy_(integer *, doublereal *, doublereal *, integer *, doublereal *, integer *); integer jnext; doublereal sminw, xnorm; extern /* Subroutine */ int igraphdlaln2_(logical *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, integer *, doublereal *, doublereal * , doublereal *, integer *, doublereal *, doublereal *, integer *); extern doublereal igraphdlamch_(char *), igraphdlange_(char *, integer *, integer *, doublereal *, integer *, doublereal *); extern integer igraphidamax_(integer *, doublereal *, integer *); doublereal scaloc; extern /* Subroutine */ int igraphdladiv_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *); doublereal bignum; logical notran; doublereal smlnum; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Do not test the input parameters for errors Parameter adjustments */ t_dim1 = *ldt; t_offset = 1 + t_dim1; t -= t_offset; --b; --x; --work; /* Function Body */ notran = ! (*ltran); *info = 0; /* Quick return if possible */ if (*n == 0) { return 0; } /* Set constants to control overflow */ eps = igraphdlamch_("P"); smlnum = igraphdlamch_("S") / eps; bignum = 1. / smlnum; xnorm = igraphdlange_("M", n, n, &t[t_offset], ldt, d__); if (! (*lreal)) { /* Computing MAX */ d__1 = xnorm, d__2 = abs(*w), d__1 = max(d__1,d__2), d__2 = igraphdlange_( "M", n, &c__1, &b[1], n, d__); xnorm = max(d__1,d__2); } /* Computing MAX */ d__1 = smlnum, d__2 = eps * xnorm; smin = max(d__1,d__2); /* Compute 1-norm of each column of strictly upper triangular part of T to control overflow in triangular solver. */ work[1] = 0.; i__1 = *n; for (j = 2; j <= i__1; ++j) { i__2 = j - 1; work[j] = igraphdasum_(&i__2, &t[j * t_dim1 + 1], &c__1); /* L10: */ } if (! (*lreal)) { i__1 = *n; for (i__ = 2; i__ <= i__1; ++i__) { work[i__] += (d__1 = b[i__], abs(d__1)); /* L20: */ } } n2 = *n << 1; n1 = *n; if (! (*lreal)) { n1 = n2; } k = igraphidamax_(&n1, &x[1], &c__1); xmax = (d__1 = x[k], abs(d__1)); *scale = 1.; if (xmax > bignum) { *scale = bignum / xmax; igraphdscal_(&n1, scale, &x[1], &c__1); xmax = bignum; } if (*lreal) { if (notran) { /* Solve T*p = scale*c */ jnext = *n; for (j = *n; j >= 1; --j) { if (j > jnext) { goto L30; } j1 = j; j2 = j; jnext = j - 1; if (j > 1) { if (t[j + (j - 1) * t_dim1] != 0.) { j1 = j - 1; jnext = j - 2; } } if (j1 == j2) { /* Meet 1 by 1 diagonal block Scale to avoid overflow when computing x(j) = b(j)/T(j,j) */ xj = (d__1 = x[j1], abs(d__1)); tjj = (d__1 = t[j1 + j1 * t_dim1], abs(d__1)); tmp = t[j1 + j1 * t_dim1]; if (tjj < smin) { tmp = smin; tjj = smin; *info = 1; } if (xj == 0.) { goto L30; } if (tjj < 1.) { if (xj > bignum * tjj) { rec = 1. / xj; igraphdscal_(n, &rec, &x[1], &c__1); *scale *= rec; xmax *= rec; } } x[j1] /= tmp; xj = (d__1 = x[j1], abs(d__1)); /* Scale x if necessary to avoid overflow when adding a multiple of column j1 of T. */ if (xj > 1.) { rec = 1. / xj; if (work[j1] > (bignum - xmax) * rec) { igraphdscal_(n, &rec, &x[1], &c__1); *scale *= rec; } } if (j1 > 1) { i__1 = j1 - 1; d__1 = -x[j1]; igraphdaxpy_(&i__1, &d__1, &t[j1 * t_dim1 + 1], &c__1, &x[1] , &c__1); i__1 = j1 - 1; k = igraphidamax_(&i__1, &x[1], &c__1); xmax = (d__1 = x[k], abs(d__1)); } } else { /* Meet 2 by 2 diagonal block Call 2 by 2 linear system solve, to take care of possible overflow by scaling factor. */ d__[0] = x[j1]; d__[1] = x[j2]; igraphdlaln2_(&c_false, &c__2, &c__1, &smin, &c_b21, &t[j1 + j1 * t_dim1], ldt, &c_b21, &c_b21, d__, &c__2, & c_b25, &c_b25, v, &c__2, &scaloc, &xnorm, &ierr); if (ierr != 0) { *info = 2; } if (scaloc != 1.) { igraphdscal_(n, &scaloc, &x[1], &c__1); *scale *= scaloc; } x[j1] = v[0]; x[j2] = v[1]; /* Scale V(1,1) (= X(J1)) and/or V(2,1) (=X(J2)) to avoid overflow in updating right-hand side. Computing MAX */ d__1 = abs(v[0]), d__2 = abs(v[1]); xj = max(d__1,d__2); if (xj > 1.) { rec = 1. / xj; /* Computing MAX */ d__1 = work[j1], d__2 = work[j2]; if (max(d__1,d__2) > (bignum - xmax) * rec) { igraphdscal_(n, &rec, &x[1], &c__1); *scale *= rec; } } /* Update right-hand side */ if (j1 > 1) { i__1 = j1 - 1; d__1 = -x[j1]; igraphdaxpy_(&i__1, &d__1, &t[j1 * t_dim1 + 1], &c__1, &x[1] , &c__1); i__1 = j1 - 1; d__1 = -x[j2]; igraphdaxpy_(&i__1, &d__1, &t[j2 * t_dim1 + 1], &c__1, &x[1] , &c__1); i__1 = j1 - 1; k = igraphidamax_(&i__1, &x[1], &c__1); xmax = (d__1 = x[k], abs(d__1)); } } L30: ; } } else { /* Solve T**T*p = scale*c */ jnext = 1; i__1 = *n; for (j = 1; j <= i__1; ++j) { if (j < jnext) { goto L40; } j1 = j; j2 = j; jnext = j + 1; if (j < *n) { if (t[j + 1 + j * t_dim1] != 0.) { j2 = j + 1; jnext = j + 2; } } if (j1 == j2) { /* 1 by 1 diagonal block Scale if necessary to avoid overflow in forming the right-hand side element by inner product. */ xj = (d__1 = x[j1], abs(d__1)); if (xmax > 1.) { rec = 1. / xmax; if (work[j1] > (bignum - xj) * rec) { igraphdscal_(n, &rec, &x[1], &c__1); *scale *= rec; xmax *= rec; } } i__2 = j1 - 1; x[j1] -= igraphddot_(&i__2, &t[j1 * t_dim1 + 1], &c__1, &x[1], & c__1); xj = (d__1 = x[j1], abs(d__1)); tjj = (d__1 = t[j1 + j1 * t_dim1], abs(d__1)); tmp = t[j1 + j1 * t_dim1]; if (tjj < smin) { tmp = smin; tjj = smin; *info = 1; } if (tjj < 1.) { if (xj > bignum * tjj) { rec = 1. / xj; igraphdscal_(n, &rec, &x[1], &c__1); *scale *= rec; xmax *= rec; } } x[j1] /= tmp; /* Computing MAX */ d__2 = xmax, d__3 = (d__1 = x[j1], abs(d__1)); xmax = max(d__2,d__3); } else { /* 2 by 2 diagonal block Scale if necessary to avoid overflow in forming the right-hand side elements by inner product. Computing MAX */ d__3 = (d__1 = x[j1], abs(d__1)), d__4 = (d__2 = x[j2], abs(d__2)); xj = max(d__3,d__4); if (xmax > 1.) { rec = 1. / xmax; /* Computing MAX */ d__1 = work[j2], d__2 = work[j1]; if (max(d__1,d__2) > (bignum - xj) * rec) { igraphdscal_(n, &rec, &x[1], &c__1); *scale *= rec; xmax *= rec; } } i__2 = j1 - 1; d__[0] = x[j1] - igraphddot_(&i__2, &t[j1 * t_dim1 + 1], &c__1, &x[1], &c__1); i__2 = j1 - 1; d__[1] = x[j2] - igraphddot_(&i__2, &t[j2 * t_dim1 + 1], &c__1, &x[1], &c__1); igraphdlaln2_(&c_true, &c__2, &c__1, &smin, &c_b21, &t[j1 + j1 * t_dim1], ldt, &c_b21, &c_b21, d__, &c__2, &c_b25, &c_b25, v, &c__2, &scaloc, &xnorm, &ierr); if (ierr != 0) { *info = 2; } if (scaloc != 1.) { igraphdscal_(n, &scaloc, &x[1], &c__1); *scale *= scaloc; } x[j1] = v[0]; x[j2] = v[1]; /* Computing MAX */ d__3 = (d__1 = x[j1], abs(d__1)), d__4 = (d__2 = x[j2], abs(d__2)), d__3 = max(d__3,d__4); xmax = max(d__3,xmax); } L40: ; } } } else { /* Computing MAX */ d__1 = eps * abs(*w); sminw = max(d__1,smin); if (notran) { /* Solve (T + iB)*(p+iq) = c+id */ jnext = *n; for (j = *n; j >= 1; --j) { if (j > jnext) { goto L70; } j1 = j; j2 = j; jnext = j - 1; if (j > 1) { if (t[j + (j - 1) * t_dim1] != 0.) { j1 = j - 1; jnext = j - 2; } } if (j1 == j2) { /* 1 by 1 diagonal block Scale if necessary to avoid overflow in division */ z__ = *w; if (j1 == 1) { z__ = b[1]; } xj = (d__1 = x[j1], abs(d__1)) + (d__2 = x[*n + j1], abs( d__2)); tjj = (d__1 = t[j1 + j1 * t_dim1], abs(d__1)) + abs(z__); tmp = t[j1 + j1 * t_dim1]; if (tjj < sminw) { tmp = sminw; tjj = sminw; *info = 1; } if (xj == 0.) { goto L70; } if (tjj < 1.) { if (xj > bignum * tjj) { rec = 1. / xj; igraphdscal_(&n2, &rec, &x[1], &c__1); *scale *= rec; xmax *= rec; } } igraphdladiv_(&x[j1], &x[*n + j1], &tmp, &z__, &sr, &si); x[j1] = sr; x[*n + j1] = si; xj = (d__1 = x[j1], abs(d__1)) + (d__2 = x[*n + j1], abs( d__2)); /* Scale x if necessary to avoid overflow when adding a multiple of column j1 of T. */ if (xj > 1.) { rec = 1. / xj; if (work[j1] > (bignum - xmax) * rec) { igraphdscal_(&n2, &rec, &x[1], &c__1); *scale *= rec; } } if (j1 > 1) { i__1 = j1 - 1; d__1 = -x[j1]; igraphdaxpy_(&i__1, &d__1, &t[j1 * t_dim1 + 1], &c__1, &x[1] , &c__1); i__1 = j1 - 1; d__1 = -x[*n + j1]; igraphdaxpy_(&i__1, &d__1, &t[j1 * t_dim1 + 1], &c__1, &x[* n + 1], &c__1); x[1] += b[j1] * x[*n + j1]; x[*n + 1] -= b[j1] * x[j1]; xmax = 0.; i__1 = j1 - 1; for (k = 1; k <= i__1; ++k) { /* Computing MAX */ d__3 = xmax, d__4 = (d__1 = x[k], abs(d__1)) + ( d__2 = x[k + *n], abs(d__2)); xmax = max(d__3,d__4); /* L50: */ } } } else { /* Meet 2 by 2 diagonal block */ d__[0] = x[j1]; d__[1] = x[j2]; d__[2] = x[*n + j1]; d__[3] = x[*n + j2]; d__1 = -(*w); igraphdlaln2_(&c_false, &c__2, &c__2, &sminw, &c_b21, &t[j1 + j1 * t_dim1], ldt, &c_b21, &c_b21, d__, &c__2, & c_b25, &d__1, v, &c__2, &scaloc, &xnorm, &ierr); if (ierr != 0) { *info = 2; } if (scaloc != 1.) { i__1 = *n << 1; igraphdscal_(&i__1, &scaloc, &x[1], &c__1); *scale = scaloc * *scale; } x[j1] = v[0]; x[j2] = v[1]; x[*n + j1] = v[2]; x[*n + j2] = v[3]; /* Scale X(J1), .... to avoid overflow in updating right hand side. Computing MAX */ d__1 = abs(v[0]) + abs(v[2]), d__2 = abs(v[1]) + abs(v[3]) ; xj = max(d__1,d__2); if (xj > 1.) { rec = 1. / xj; /* Computing MAX */ d__1 = work[j1], d__2 = work[j2]; if (max(d__1,d__2) > (bignum - xmax) * rec) { igraphdscal_(&n2, &rec, &x[1], &c__1); *scale *= rec; } } /* Update the right-hand side. */ if (j1 > 1) { i__1 = j1 - 1; d__1 = -x[j1]; igraphdaxpy_(&i__1, &d__1, &t[j1 * t_dim1 + 1], &c__1, &x[1] , &c__1); i__1 = j1 - 1; d__1 = -x[j2]; igraphdaxpy_(&i__1, &d__1, &t[j2 * t_dim1 + 1], &c__1, &x[1] , &c__1); i__1 = j1 - 1; d__1 = -x[*n + j1]; igraphdaxpy_(&i__1, &d__1, &t[j1 * t_dim1 + 1], &c__1, &x[* n + 1], &c__1); i__1 = j1 - 1; d__1 = -x[*n + j2]; igraphdaxpy_(&i__1, &d__1, &t[j2 * t_dim1 + 1], &c__1, &x[* n + 1], &c__1); x[1] = x[1] + b[j1] * x[*n + j1] + b[j2] * x[*n + j2]; x[*n + 1] = x[*n + 1] - b[j1] * x[j1] - b[j2] * x[j2]; xmax = 0.; i__1 = j1 - 1; for (k = 1; k <= i__1; ++k) { /* Computing MAX */ d__3 = (d__1 = x[k], abs(d__1)) + (d__2 = x[k + * n], abs(d__2)); xmax = max(d__3,xmax); /* L60: */ } } } L70: ; } } else { /* Solve (T + iB)**T*(p+iq) = c+id */ jnext = 1; i__1 = *n; for (j = 1; j <= i__1; ++j) { if (j < jnext) { goto L80; } j1 = j; j2 = j; jnext = j + 1; if (j < *n) { if (t[j + 1 + j * t_dim1] != 0.) { j2 = j + 1; jnext = j + 2; } } if (j1 == j2) { /* 1 by 1 diagonal block Scale if necessary to avoid overflow in forming the right-hand side element by inner product. */ xj = (d__1 = x[j1], abs(d__1)) + (d__2 = x[j1 + *n], abs( d__2)); if (xmax > 1.) { rec = 1. / xmax; if (work[j1] > (bignum - xj) * rec) { igraphdscal_(&n2, &rec, &x[1], &c__1); *scale *= rec; xmax *= rec; } } i__2 = j1 - 1; x[j1] -= igraphddot_(&i__2, &t[j1 * t_dim1 + 1], &c__1, &x[1], & c__1); i__2 = j1 - 1; x[*n + j1] -= igraphddot_(&i__2, &t[j1 * t_dim1 + 1], &c__1, &x[ *n + 1], &c__1); if (j1 > 1) { x[j1] -= b[j1] * x[*n + 1]; x[*n + j1] += b[j1] * x[1]; } xj = (d__1 = x[j1], abs(d__1)) + (d__2 = x[j1 + *n], abs( d__2)); z__ = *w; if (j1 == 1) { z__ = b[1]; } /* Scale if necessary to avoid overflow in complex division */ tjj = (d__1 = t[j1 + j1 * t_dim1], abs(d__1)) + abs(z__); tmp = t[j1 + j1 * t_dim1]; if (tjj < sminw) { tmp = sminw; tjj = sminw; *info = 1; } if (tjj < 1.) { if (xj > bignum * tjj) { rec = 1. / xj; igraphdscal_(&n2, &rec, &x[1], &c__1); *scale *= rec; xmax *= rec; } } d__1 = -z__; igraphdladiv_(&x[j1], &x[*n + j1], &tmp, &d__1, &sr, &si); x[j1] = sr; x[j1 + *n] = si; /* Computing MAX */ d__3 = (d__1 = x[j1], abs(d__1)) + (d__2 = x[j1 + *n], abs(d__2)); xmax = max(d__3,xmax); } else { /* 2 by 2 diagonal block Scale if necessary to avoid overflow in forming the right-hand side element by inner product. Computing MAX */ d__5 = (d__1 = x[j1], abs(d__1)) + (d__2 = x[*n + j1], abs(d__2)), d__6 = (d__3 = x[j2], abs(d__3)) + ( d__4 = x[*n + j2], abs(d__4)); xj = max(d__5,d__6); if (xmax > 1.) { rec = 1. / xmax; /* Computing MAX */ d__1 = work[j1], d__2 = work[j2]; if (max(d__1,d__2) > (bignum - xj) / xmax) { igraphdscal_(&n2, &rec, &x[1], &c__1); *scale *= rec; xmax *= rec; } } i__2 = j1 - 1; d__[0] = x[j1] - igraphddot_(&i__2, &t[j1 * t_dim1 + 1], &c__1, &x[1], &c__1); i__2 = j1 - 1; d__[1] = x[j2] - igraphddot_(&i__2, &t[j2 * t_dim1 + 1], &c__1, &x[1], &c__1); i__2 = j1 - 1; d__[2] = x[*n + j1] - igraphddot_(&i__2, &t[j1 * t_dim1 + 1], & c__1, &x[*n + 1], &c__1); i__2 = j1 - 1; d__[3] = x[*n + j2] - igraphddot_(&i__2, &t[j2 * t_dim1 + 1], & c__1, &x[*n + 1], &c__1); d__[0] -= b[j1] * x[*n + 1]; d__[1] -= b[j2] * x[*n + 1]; d__[2] += b[j1] * x[1]; d__[3] += b[j2] * x[1]; igraphdlaln2_(&c_true, &c__2, &c__2, &sminw, &c_b21, &t[j1 + j1 * t_dim1], ldt, &c_b21, &c_b21, d__, &c__2, & c_b25, w, v, &c__2, &scaloc, &xnorm, &ierr); if (ierr != 0) { *info = 2; } if (scaloc != 1.) { igraphdscal_(&n2, &scaloc, &x[1], &c__1); *scale = scaloc * *scale; } x[j1] = v[0]; x[j2] = v[1]; x[*n + j1] = v[2]; x[*n + j2] = v[3]; /* Computing MAX */ d__5 = (d__1 = x[j1], abs(d__1)) + (d__2 = x[*n + j1], abs(d__2)), d__6 = (d__3 = x[j2], abs(d__3)) + ( d__4 = x[*n + j2], abs(d__4)), d__5 = max(d__5, d__6); xmax = max(d__5,xmax); } L80: ; } } } return 0; /* End of DLAQTR */ } /* igraphdlaqtr_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dtrsyl.c0000644000076500000240000011414213524616145024330 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static logical c_false = FALSE_; static integer c__2 = 2; static doublereal c_b26 = 1.; static doublereal c_b30 = 0.; static logical c_true = TRUE_; /* > \brief \b DTRSYL =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DTRSYL + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DTRSYL( TRANA, TRANB, ISGN, M, N, A, LDA, B, LDB, C, LDC, SCALE, INFO ) CHARACTER TRANA, TRANB INTEGER INFO, ISGN, LDA, LDB, LDC, M, N DOUBLE PRECISION SCALE DOUBLE PRECISION A( LDA, * ), B( LDB, * ), C( LDC, * ) > \par Purpose: ============= > > \verbatim > > DTRSYL solves the real Sylvester matrix equation: > > op(A)*X + X*op(B) = scale*C or > op(A)*X - X*op(B) = scale*C, > > where op(A) = A or A**T, and A and B are both upper quasi- > triangular. A is M-by-M and B is N-by-N; the right hand side C and > the solution X are M-by-N; and scale is an output scale factor, set > <= 1 to avoid overflow in X. > > A and B must be in Schur canonical form (as returned by DHSEQR), that > is, block upper triangular with 1-by-1 and 2-by-2 diagonal blocks; > each 2-by-2 diagonal block has its diagonal elements equal and its > off-diagonal elements of opposite sign. > \endverbatim Arguments: ========== > \param[in] TRANA > \verbatim > TRANA is CHARACTER*1 > Specifies the option op(A): > = 'N': op(A) = A (No transpose) > = 'T': op(A) = A**T (Transpose) > = 'C': op(A) = A**H (Conjugate transpose = Transpose) > \endverbatim > > \param[in] TRANB > \verbatim > TRANB is CHARACTER*1 > Specifies the option op(B): > = 'N': op(B) = B (No transpose) > = 'T': op(B) = B**T (Transpose) > = 'C': op(B) = B**H (Conjugate transpose = Transpose) > \endverbatim > > \param[in] ISGN > \verbatim > ISGN is INTEGER > Specifies the sign in the equation: > = +1: solve op(A)*X + X*op(B) = scale*C > = -1: solve op(A)*X - X*op(B) = scale*C > \endverbatim > > \param[in] M > \verbatim > M is INTEGER > The order of the matrix A, and the number of rows in the > matrices X and C. M >= 0. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix B, and the number of columns in the > matrices X and C. N >= 0. > \endverbatim > > \param[in] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,M) > The upper quasi-triangular matrix A, in Schur canonical form. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. LDA >= max(1,M). > \endverbatim > > \param[in] B > \verbatim > B is DOUBLE PRECISION array, dimension (LDB,N) > The upper quasi-triangular matrix B, in Schur canonical form. > \endverbatim > > \param[in] LDB > \verbatim > LDB is INTEGER > The leading dimension of the array B. LDB >= max(1,N). > \endverbatim > > \param[in,out] C > \verbatim > C is DOUBLE PRECISION array, dimension (LDC,N) > On entry, the M-by-N right hand side matrix C. > On exit, C is overwritten by the solution matrix X. > \endverbatim > > \param[in] LDC > \verbatim > LDC is INTEGER > The leading dimension of the array C. LDC >= max(1,M) > \endverbatim > > \param[out] SCALE > \verbatim > SCALE is DOUBLE PRECISION > The scale factor, scale, set <= 1 to avoid overflow in X. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value > = 1: A and B have common or very close eigenvalues; perturbed > values were used to solve the equation (but the matrices > A and B are unchanged). > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2011 > \ingroup doubleSYcomputational ===================================================================== Subroutine */ int igraphdtrsyl_(char *trana, char *tranb, integer *isgn, integer *m, integer *n, doublereal *a, integer *lda, doublereal *b, integer * ldb, doublereal *c__, integer *ldc, doublereal *scale, integer *info) { /* System generated locals */ integer a_dim1, a_offset, b_dim1, b_offset, c_dim1, c_offset, i__1, i__2, i__3, i__4; doublereal d__1, d__2; /* Local variables */ integer j, k, l; doublereal x[4] /* was [2][2] */; integer k1, k2, l1, l2; doublereal a11, db, da11, vec[4] /* was [2][2] */, dum[1], eps, sgn; extern doublereal igraphddot_(integer *, doublereal *, integer *, doublereal *, integer *); integer ierr; doublereal smin, suml, sumr; extern /* Subroutine */ int igraphdscal_(integer *, doublereal *, doublereal *, integer *); extern logical igraphlsame_(char *, char *); integer knext, lnext; doublereal xnorm; extern /* Subroutine */ int igraphdlaln2_(logical *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, integer *, doublereal *, doublereal * , doublereal *, integer *, doublereal *, doublereal *, integer *), igraphdlasy2_(logical *, logical *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *), igraphdlabad_(doublereal *, doublereal *); extern doublereal igraphdlamch_(char *), igraphdlange_(char *, integer *, integer *, doublereal *, integer *, doublereal *); doublereal scaloc; extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); doublereal bignum; logical notrna, notrnb; doublereal smlnum; /* -- LAPACK computational routine (version 3.4.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2011 ===================================================================== Decode and Test input parameters Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; b_dim1 = *ldb; b_offset = 1 + b_dim1; b -= b_offset; c_dim1 = *ldc; c_offset = 1 + c_dim1; c__ -= c_offset; /* Function Body */ notrna = igraphlsame_(trana, "N"); notrnb = igraphlsame_(tranb, "N"); *info = 0; if (! notrna && ! igraphlsame_(trana, "T") && ! igraphlsame_( trana, "C")) { *info = -1; } else if (! notrnb && ! igraphlsame_(tranb, "T") && ! igraphlsame_(tranb, "C")) { *info = -2; } else if (*isgn != 1 && *isgn != -1) { *info = -3; } else if (*m < 0) { *info = -4; } else if (*n < 0) { *info = -5; } else if (*lda < max(1,*m)) { *info = -7; } else if (*ldb < max(1,*n)) { *info = -9; } else if (*ldc < max(1,*m)) { *info = -11; } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DTRSYL", &i__1, (ftnlen)6); return 0; } /* Quick return if possible */ *scale = 1.; if (*m == 0 || *n == 0) { return 0; } /* Set constants to control overflow */ eps = igraphdlamch_("P"); smlnum = igraphdlamch_("S"); bignum = 1. / smlnum; igraphdlabad_(&smlnum, &bignum); smlnum = smlnum * (doublereal) (*m * *n) / eps; bignum = 1. / smlnum; /* Computing MAX */ d__1 = smlnum, d__2 = eps * igraphdlange_("M", m, m, &a[a_offset], lda, dum), d__1 = max(d__1,d__2), d__2 = eps * igraphdlange_("M", n, n, &b[b_offset], ldb, dum); smin = max(d__1,d__2); sgn = (doublereal) (*isgn); if (notrna && notrnb) { /* Solve A*X + ISGN*X*B = scale*C. The (K,L)th block of X is determined starting from bottom-left corner column by column by A(K,K)*X(K,L) + ISGN*X(K,L)*B(L,L) = C(K,L) - R(K,L) Where M L-1 R(K,L) = SUM [A(K,I)*X(I,L)] + ISGN*SUM [X(K,J)*B(J,L)]. I=K+1 J=1 Start column loop (index = L) L1 (L2) : column index of the first (first) row of X(K,L). */ lnext = 1; i__1 = *n; for (l = 1; l <= i__1; ++l) { if (l < lnext) { goto L60; } if (l == *n) { l1 = l; l2 = l; } else { if (b[l + 1 + l * b_dim1] != 0.) { l1 = l; l2 = l + 1; lnext = l + 2; } else { l1 = l; l2 = l; lnext = l + 1; } } /* Start row loop (index = K) K1 (K2): row index of the first (last) row of X(K,L). */ knext = *m; for (k = *m; k >= 1; --k) { if (k > knext) { goto L50; } if (k == 1) { k1 = k; k2 = k; } else { if (a[k + (k - 1) * a_dim1] != 0.) { k1 = k - 1; k2 = k; knext = k - 2; } else { k1 = k; k2 = k; knext = k - 1; } } if (l1 == l2 && k1 == k2) { i__2 = *m - k1; /* Computing MIN */ i__3 = k1 + 1; /* Computing MIN */ i__4 = k1 + 1; suml = igraphddot_(&i__2, &a[k1 + min(i__3,*m) * a_dim1], lda, & c__[min(i__4,*m) + l1 * c_dim1], &c__1); i__2 = l1 - 1; sumr = igraphddot_(&i__2, &c__[k1 + c_dim1], ldc, &b[l1 * b_dim1 + 1], &c__1); vec[0] = c__[k1 + l1 * c_dim1] - (suml + sgn * sumr); scaloc = 1.; a11 = a[k1 + k1 * a_dim1] + sgn * b[l1 + l1 * b_dim1]; da11 = abs(a11); if (da11 <= smin) { a11 = smin; da11 = smin; *info = 1; } db = abs(vec[0]); if (da11 < 1. && db > 1.) { if (db > bignum * da11) { scaloc = 1. / db; } } x[0] = vec[0] * scaloc / a11; if (scaloc != 1.) { i__2 = *n; for (j = 1; j <= i__2; ++j) { igraphdscal_(m, &scaloc, &c__[j * c_dim1 + 1], &c__1); /* L10: */ } *scale *= scaloc; } c__[k1 + l1 * c_dim1] = x[0]; } else if (l1 == l2 && k1 != k2) { i__2 = *m - k2; /* Computing MIN */ i__3 = k2 + 1; /* Computing MIN */ i__4 = k2 + 1; suml = igraphddot_(&i__2, &a[k1 + min(i__3,*m) * a_dim1], lda, & c__[min(i__4,*m) + l1 * c_dim1], &c__1); i__2 = l1 - 1; sumr = igraphddot_(&i__2, &c__[k1 + c_dim1], ldc, &b[l1 * b_dim1 + 1], &c__1); vec[0] = c__[k1 + l1 * c_dim1] - (suml + sgn * sumr); i__2 = *m - k2; /* Computing MIN */ i__3 = k2 + 1; /* Computing MIN */ i__4 = k2 + 1; suml = igraphddot_(&i__2, &a[k2 + min(i__3,*m) * a_dim1], lda, & c__[min(i__4,*m) + l1 * c_dim1], &c__1); i__2 = l1 - 1; sumr = igraphddot_(&i__2, &c__[k2 + c_dim1], ldc, &b[l1 * b_dim1 + 1], &c__1); vec[1] = c__[k2 + l1 * c_dim1] - (suml + sgn * sumr); d__1 = -sgn * b[l1 + l1 * b_dim1]; igraphdlaln2_(&c_false, &c__2, &c__1, &smin, &c_b26, &a[k1 + k1 * a_dim1], lda, &c_b26, &c_b26, vec, &c__2, &d__1, &c_b30, x, &c__2, &scaloc, &xnorm, &ierr); if (ierr != 0) { *info = 1; } if (scaloc != 1.) { i__2 = *n; for (j = 1; j <= i__2; ++j) { igraphdscal_(m, &scaloc, &c__[j * c_dim1 + 1], &c__1); /* L20: */ } *scale *= scaloc; } c__[k1 + l1 * c_dim1] = x[0]; c__[k2 + l1 * c_dim1] = x[1]; } else if (l1 != l2 && k1 == k2) { i__2 = *m - k1; /* Computing MIN */ i__3 = k1 + 1; /* Computing MIN */ i__4 = k1 + 1; suml = igraphddot_(&i__2, &a[k1 + min(i__3,*m) * a_dim1], lda, & c__[min(i__4,*m) + l1 * c_dim1], &c__1); i__2 = l1 - 1; sumr = igraphddot_(&i__2, &c__[k1 + c_dim1], ldc, &b[l1 * b_dim1 + 1], &c__1); vec[0] = sgn * (c__[k1 + l1 * c_dim1] - (suml + sgn * sumr)); i__2 = *m - k1; /* Computing MIN */ i__3 = k1 + 1; /* Computing MIN */ i__4 = k1 + 1; suml = igraphddot_(&i__2, &a[k1 + min(i__3,*m) * a_dim1], lda, & c__[min(i__4,*m) + l2 * c_dim1], &c__1); i__2 = l1 - 1; sumr = igraphddot_(&i__2, &c__[k1 + c_dim1], ldc, &b[l2 * b_dim1 + 1], &c__1); vec[1] = sgn * (c__[k1 + l2 * c_dim1] - (suml + sgn * sumr)); d__1 = -sgn * a[k1 + k1 * a_dim1]; igraphdlaln2_(&c_true, &c__2, &c__1, &smin, &c_b26, &b[l1 + l1 * b_dim1], ldb, &c_b26, &c_b26, vec, &c__2, &d__1, &c_b30, x, &c__2, &scaloc, &xnorm, &ierr); if (ierr != 0) { *info = 1; } if (scaloc != 1.) { i__2 = *n; for (j = 1; j <= i__2; ++j) { igraphdscal_(m, &scaloc, &c__[j * c_dim1 + 1], &c__1); /* L30: */ } *scale *= scaloc; } c__[k1 + l1 * c_dim1] = x[0]; c__[k1 + l2 * c_dim1] = x[1]; } else if (l1 != l2 && k1 != k2) { i__2 = *m - k2; /* Computing MIN */ i__3 = k2 + 1; /* Computing MIN */ i__4 = k2 + 1; suml = igraphddot_(&i__2, &a[k1 + min(i__3,*m) * a_dim1], lda, & c__[min(i__4,*m) + l1 * c_dim1], &c__1); i__2 = l1 - 1; sumr = igraphddot_(&i__2, &c__[k1 + c_dim1], ldc, &b[l1 * b_dim1 + 1], &c__1); vec[0] = c__[k1 + l1 * c_dim1] - (suml + sgn * sumr); i__2 = *m - k2; /* Computing MIN */ i__3 = k2 + 1; /* Computing MIN */ i__4 = k2 + 1; suml = igraphddot_(&i__2, &a[k1 + min(i__3,*m) * a_dim1], lda, & c__[min(i__4,*m) + l2 * c_dim1], &c__1); i__2 = l1 - 1; sumr = igraphddot_(&i__2, &c__[k1 + c_dim1], ldc, &b[l2 * b_dim1 + 1], &c__1); vec[2] = c__[k1 + l2 * c_dim1] - (suml + sgn * sumr); i__2 = *m - k2; /* Computing MIN */ i__3 = k2 + 1; /* Computing MIN */ i__4 = k2 + 1; suml = igraphddot_(&i__2, &a[k2 + min(i__3,*m) * a_dim1], lda, & c__[min(i__4,*m) + l1 * c_dim1], &c__1); i__2 = l1 - 1; sumr = igraphddot_(&i__2, &c__[k2 + c_dim1], ldc, &b[l1 * b_dim1 + 1], &c__1); vec[1] = c__[k2 + l1 * c_dim1] - (suml + sgn * sumr); i__2 = *m - k2; /* Computing MIN */ i__3 = k2 + 1; /* Computing MIN */ i__4 = k2 + 1; suml = igraphddot_(&i__2, &a[k2 + min(i__3,*m) * a_dim1], lda, & c__[min(i__4,*m) + l2 * c_dim1], &c__1); i__2 = l1 - 1; sumr = igraphddot_(&i__2, &c__[k2 + c_dim1], ldc, &b[l2 * b_dim1 + 1], &c__1); vec[3] = c__[k2 + l2 * c_dim1] - (suml + sgn * sumr); igraphdlasy2_(&c_false, &c_false, isgn, &c__2, &c__2, &a[k1 + k1 * a_dim1], lda, &b[l1 + l1 * b_dim1], ldb, vec, &c__2, &scaloc, x, &c__2, &xnorm, &ierr); if (ierr != 0) { *info = 1; } if (scaloc != 1.) { i__2 = *n; for (j = 1; j <= i__2; ++j) { igraphdscal_(m, &scaloc, &c__[j * c_dim1 + 1], &c__1); /* L40: */ } *scale *= scaloc; } c__[k1 + l1 * c_dim1] = x[0]; c__[k1 + l2 * c_dim1] = x[2]; c__[k2 + l1 * c_dim1] = x[1]; c__[k2 + l2 * c_dim1] = x[3]; } L50: ; } L60: ; } } else if (! notrna && notrnb) { /* Solve A**T *X + ISGN*X*B = scale*C. The (K,L)th block of X is determined starting from upper-left corner column by column by A(K,K)**T*X(K,L) + ISGN*X(K,L)*B(L,L) = C(K,L) - R(K,L) Where K-1 T L-1 R(K,L) = SUM [A(I,K)**T*X(I,L)] +ISGN*SUM [X(K,J)*B(J,L)] I=1 J=1 Start column loop (index = L) L1 (L2): column index of the first (last) row of X(K,L) */ lnext = 1; i__1 = *n; for (l = 1; l <= i__1; ++l) { if (l < lnext) { goto L120; } if (l == *n) { l1 = l; l2 = l; } else { if (b[l + 1 + l * b_dim1] != 0.) { l1 = l; l2 = l + 1; lnext = l + 2; } else { l1 = l; l2 = l; lnext = l + 1; } } /* Start row loop (index = K) K1 (K2): row index of the first (last) row of X(K,L) */ knext = 1; i__2 = *m; for (k = 1; k <= i__2; ++k) { if (k < knext) { goto L110; } if (k == *m) { k1 = k; k2 = k; } else { if (a[k + 1 + k * a_dim1] != 0.) { k1 = k; k2 = k + 1; knext = k + 2; } else { k1 = k; k2 = k; knext = k + 1; } } if (l1 == l2 && k1 == k2) { i__3 = k1 - 1; suml = igraphddot_(&i__3, &a[k1 * a_dim1 + 1], &c__1, &c__[l1 * c_dim1 + 1], &c__1); i__3 = l1 - 1; sumr = igraphddot_(&i__3, &c__[k1 + c_dim1], ldc, &b[l1 * b_dim1 + 1], &c__1); vec[0] = c__[k1 + l1 * c_dim1] - (suml + sgn * sumr); scaloc = 1.; a11 = a[k1 + k1 * a_dim1] + sgn * b[l1 + l1 * b_dim1]; da11 = abs(a11); if (da11 <= smin) { a11 = smin; da11 = smin; *info = 1; } db = abs(vec[0]); if (da11 < 1. && db > 1.) { if (db > bignum * da11) { scaloc = 1. / db; } } x[0] = vec[0] * scaloc / a11; if (scaloc != 1.) { i__3 = *n; for (j = 1; j <= i__3; ++j) { igraphdscal_(m, &scaloc, &c__[j * c_dim1 + 1], &c__1); /* L70: */ } *scale *= scaloc; } c__[k1 + l1 * c_dim1] = x[0]; } else if (l1 == l2 && k1 != k2) { i__3 = k1 - 1; suml = igraphddot_(&i__3, &a[k1 * a_dim1 + 1], &c__1, &c__[l1 * c_dim1 + 1], &c__1); i__3 = l1 - 1; sumr = igraphddot_(&i__3, &c__[k1 + c_dim1], ldc, &b[l1 * b_dim1 + 1], &c__1); vec[0] = c__[k1 + l1 * c_dim1] - (suml + sgn * sumr); i__3 = k1 - 1; suml = igraphddot_(&i__3, &a[k2 * a_dim1 + 1], &c__1, &c__[l1 * c_dim1 + 1], &c__1); i__3 = l1 - 1; sumr = igraphddot_(&i__3, &c__[k2 + c_dim1], ldc, &b[l1 * b_dim1 + 1], &c__1); vec[1] = c__[k2 + l1 * c_dim1] - (suml + sgn * sumr); d__1 = -sgn * b[l1 + l1 * b_dim1]; igraphdlaln2_(&c_true, &c__2, &c__1, &smin, &c_b26, &a[k1 + k1 * a_dim1], lda, &c_b26, &c_b26, vec, &c__2, &d__1, &c_b30, x, &c__2, &scaloc, &xnorm, &ierr); if (ierr != 0) { *info = 1; } if (scaloc != 1.) { i__3 = *n; for (j = 1; j <= i__3; ++j) { igraphdscal_(m, &scaloc, &c__[j * c_dim1 + 1], &c__1); /* L80: */ } *scale *= scaloc; } c__[k1 + l1 * c_dim1] = x[0]; c__[k2 + l1 * c_dim1] = x[1]; } else if (l1 != l2 && k1 == k2) { i__3 = k1 - 1; suml = igraphddot_(&i__3, &a[k1 * a_dim1 + 1], &c__1, &c__[l1 * c_dim1 + 1], &c__1); i__3 = l1 - 1; sumr = igraphddot_(&i__3, &c__[k1 + c_dim1], ldc, &b[l1 * b_dim1 + 1], &c__1); vec[0] = sgn * (c__[k1 + l1 * c_dim1] - (suml + sgn * sumr)); i__3 = k1 - 1; suml = igraphddot_(&i__3, &a[k1 * a_dim1 + 1], &c__1, &c__[l2 * c_dim1 + 1], &c__1); i__3 = l1 - 1; sumr = igraphddot_(&i__3, &c__[k1 + c_dim1], ldc, &b[l2 * b_dim1 + 1], &c__1); vec[1] = sgn * (c__[k1 + l2 * c_dim1] - (suml + sgn * sumr)); d__1 = -sgn * a[k1 + k1 * a_dim1]; igraphdlaln2_(&c_true, &c__2, &c__1, &smin, &c_b26, &b[l1 + l1 * b_dim1], ldb, &c_b26, &c_b26, vec, &c__2, &d__1, &c_b30, x, &c__2, &scaloc, &xnorm, &ierr); if (ierr != 0) { *info = 1; } if (scaloc != 1.) { i__3 = *n; for (j = 1; j <= i__3; ++j) { igraphdscal_(m, &scaloc, &c__[j * c_dim1 + 1], &c__1); /* L90: */ } *scale *= scaloc; } c__[k1 + l1 * c_dim1] = x[0]; c__[k1 + l2 * c_dim1] = x[1]; } else if (l1 != l2 && k1 != k2) { i__3 = k1 - 1; suml = igraphddot_(&i__3, &a[k1 * a_dim1 + 1], &c__1, &c__[l1 * c_dim1 + 1], &c__1); i__3 = l1 - 1; sumr = igraphddot_(&i__3, &c__[k1 + c_dim1], ldc, &b[l1 * b_dim1 + 1], &c__1); vec[0] = c__[k1 + l1 * c_dim1] - (suml + sgn * sumr); i__3 = k1 - 1; suml = igraphddot_(&i__3, &a[k1 * a_dim1 + 1], &c__1, &c__[l2 * c_dim1 + 1], &c__1); i__3 = l1 - 1; sumr = igraphddot_(&i__3, &c__[k1 + c_dim1], ldc, &b[l2 * b_dim1 + 1], &c__1); vec[2] = c__[k1 + l2 * c_dim1] - (suml + sgn * sumr); i__3 = k1 - 1; suml = igraphddot_(&i__3, &a[k2 * a_dim1 + 1], &c__1, &c__[l1 * c_dim1 + 1], &c__1); i__3 = l1 - 1; sumr = igraphddot_(&i__3, &c__[k2 + c_dim1], ldc, &b[l1 * b_dim1 + 1], &c__1); vec[1] = c__[k2 + l1 * c_dim1] - (suml + sgn * sumr); i__3 = k1 - 1; suml = igraphddot_(&i__3, &a[k2 * a_dim1 + 1], &c__1, &c__[l2 * c_dim1 + 1], &c__1); i__3 = l1 - 1; sumr = igraphddot_(&i__3, &c__[k2 + c_dim1], ldc, &b[l2 * b_dim1 + 1], &c__1); vec[3] = c__[k2 + l2 * c_dim1] - (suml + sgn * sumr); igraphdlasy2_(&c_true, &c_false, isgn, &c__2, &c__2, &a[k1 + k1 * a_dim1], lda, &b[l1 + l1 * b_dim1], ldb, vec, & c__2, &scaloc, x, &c__2, &xnorm, &ierr); if (ierr != 0) { *info = 1; } if (scaloc != 1.) { i__3 = *n; for (j = 1; j <= i__3; ++j) { igraphdscal_(m, &scaloc, &c__[j * c_dim1 + 1], &c__1); /* L100: */ } *scale *= scaloc; } c__[k1 + l1 * c_dim1] = x[0]; c__[k1 + l2 * c_dim1] = x[2]; c__[k2 + l1 * c_dim1] = x[1]; c__[k2 + l2 * c_dim1] = x[3]; } L110: ; } L120: ; } } else if (! notrna && ! notrnb) { /* Solve A**T*X + ISGN*X*B**T = scale*C. The (K,L)th block of X is determined starting from top-right corner column by column by A(K,K)**T*X(K,L) + ISGN*X(K,L)*B(L,L)**T = C(K,L) - R(K,L) Where K-1 N R(K,L) = SUM [A(I,K)**T*X(I,L)] + ISGN*SUM [X(K,J)*B(L,J)**T]. I=1 J=L+1 Start column loop (index = L) L1 (L2): column index of the first (last) row of X(K,L) */ lnext = *n; for (l = *n; l >= 1; --l) { if (l > lnext) { goto L180; } if (l == 1) { l1 = l; l2 = l; } else { if (b[l + (l - 1) * b_dim1] != 0.) { l1 = l - 1; l2 = l; lnext = l - 2; } else { l1 = l; l2 = l; lnext = l - 1; } } /* Start row loop (index = K) K1 (K2): row index of the first (last) row of X(K,L) */ knext = 1; i__1 = *m; for (k = 1; k <= i__1; ++k) { if (k < knext) { goto L170; } if (k == *m) { k1 = k; k2 = k; } else { if (a[k + 1 + k * a_dim1] != 0.) { k1 = k; k2 = k + 1; knext = k + 2; } else { k1 = k; k2 = k; knext = k + 1; } } if (l1 == l2 && k1 == k2) { i__2 = k1 - 1; suml = igraphddot_(&i__2, &a[k1 * a_dim1 + 1], &c__1, &c__[l1 * c_dim1 + 1], &c__1); i__2 = *n - l1; /* Computing MIN */ i__3 = l1 + 1; /* Computing MIN */ i__4 = l1 + 1; sumr = igraphddot_(&i__2, &c__[k1 + min(i__3,*n) * c_dim1], ldc, &b[l1 + min(i__4,*n) * b_dim1], ldb); vec[0] = c__[k1 + l1 * c_dim1] - (suml + sgn * sumr); scaloc = 1.; a11 = a[k1 + k1 * a_dim1] + sgn * b[l1 + l1 * b_dim1]; da11 = abs(a11); if (da11 <= smin) { a11 = smin; da11 = smin; *info = 1; } db = abs(vec[0]); if (da11 < 1. && db > 1.) { if (db > bignum * da11) { scaloc = 1. / db; } } x[0] = vec[0] * scaloc / a11; if (scaloc != 1.) { i__2 = *n; for (j = 1; j <= i__2; ++j) { igraphdscal_(m, &scaloc, &c__[j * c_dim1 + 1], &c__1); /* L130: */ } *scale *= scaloc; } c__[k1 + l1 * c_dim1] = x[0]; } else if (l1 == l2 && k1 != k2) { i__2 = k1 - 1; suml = igraphddot_(&i__2, &a[k1 * a_dim1 + 1], &c__1, &c__[l1 * c_dim1 + 1], &c__1); i__2 = *n - l2; /* Computing MIN */ i__3 = l2 + 1; /* Computing MIN */ i__4 = l2 + 1; sumr = igraphddot_(&i__2, &c__[k1 + min(i__3,*n) * c_dim1], ldc, &b[l1 + min(i__4,*n) * b_dim1], ldb); vec[0] = c__[k1 + l1 * c_dim1] - (suml + sgn * sumr); i__2 = k1 - 1; suml = igraphddot_(&i__2, &a[k2 * a_dim1 + 1], &c__1, &c__[l1 * c_dim1 + 1], &c__1); i__2 = *n - l2; /* Computing MIN */ i__3 = l2 + 1; /* Computing MIN */ i__4 = l2 + 1; sumr = igraphddot_(&i__2, &c__[k2 + min(i__3,*n) * c_dim1], ldc, &b[l1 + min(i__4,*n) * b_dim1], ldb); vec[1] = c__[k2 + l1 * c_dim1] - (suml + sgn * sumr); d__1 = -sgn * b[l1 + l1 * b_dim1]; igraphdlaln2_(&c_true, &c__2, &c__1, &smin, &c_b26, &a[k1 + k1 * a_dim1], lda, &c_b26, &c_b26, vec, &c__2, &d__1, &c_b30, x, &c__2, &scaloc, &xnorm, &ierr); if (ierr != 0) { *info = 1; } if (scaloc != 1.) { i__2 = *n; for (j = 1; j <= i__2; ++j) { igraphdscal_(m, &scaloc, &c__[j * c_dim1 + 1], &c__1); /* L140: */ } *scale *= scaloc; } c__[k1 + l1 * c_dim1] = x[0]; c__[k2 + l1 * c_dim1] = x[1]; } else if (l1 != l2 && k1 == k2) { i__2 = k1 - 1; suml = igraphddot_(&i__2, &a[k1 * a_dim1 + 1], &c__1, &c__[l1 * c_dim1 + 1], &c__1); i__2 = *n - l2; /* Computing MIN */ i__3 = l2 + 1; /* Computing MIN */ i__4 = l2 + 1; sumr = igraphddot_(&i__2, &c__[k1 + min(i__3,*n) * c_dim1], ldc, &b[l1 + min(i__4,*n) * b_dim1], ldb); vec[0] = sgn * (c__[k1 + l1 * c_dim1] - (suml + sgn * sumr)); i__2 = k1 - 1; suml = igraphddot_(&i__2, &a[k1 * a_dim1 + 1], &c__1, &c__[l2 * c_dim1 + 1], &c__1); i__2 = *n - l2; /* Computing MIN */ i__3 = l2 + 1; /* Computing MIN */ i__4 = l2 + 1; sumr = igraphddot_(&i__2, &c__[k1 + min(i__3,*n) * c_dim1], ldc, &b[l2 + min(i__4,*n) * b_dim1], ldb); vec[1] = sgn * (c__[k1 + l2 * c_dim1] - (suml + sgn * sumr)); d__1 = -sgn * a[k1 + k1 * a_dim1]; igraphdlaln2_(&c_false, &c__2, &c__1, &smin, &c_b26, &b[l1 + l1 * b_dim1], ldb, &c_b26, &c_b26, vec, &c__2, &d__1, &c_b30, x, &c__2, &scaloc, &xnorm, &ierr); if (ierr != 0) { *info = 1; } if (scaloc != 1.) { i__2 = *n; for (j = 1; j <= i__2; ++j) { igraphdscal_(m, &scaloc, &c__[j * c_dim1 + 1], &c__1); /* L150: */ } *scale *= scaloc; } c__[k1 + l1 * c_dim1] = x[0]; c__[k1 + l2 * c_dim1] = x[1]; } else if (l1 != l2 && k1 != k2) { i__2 = k1 - 1; suml = igraphddot_(&i__2, &a[k1 * a_dim1 + 1], &c__1, &c__[l1 * c_dim1 + 1], &c__1); i__2 = *n - l2; /* Computing MIN */ i__3 = l2 + 1; /* Computing MIN */ i__4 = l2 + 1; sumr = igraphddot_(&i__2, &c__[k1 + min(i__3,*n) * c_dim1], ldc, &b[l1 + min(i__4,*n) * b_dim1], ldb); vec[0] = c__[k1 + l1 * c_dim1] - (suml + sgn * sumr); i__2 = k1 - 1; suml = igraphddot_(&i__2, &a[k1 * a_dim1 + 1], &c__1, &c__[l2 * c_dim1 + 1], &c__1); i__2 = *n - l2; /* Computing MIN */ i__3 = l2 + 1; /* Computing MIN */ i__4 = l2 + 1; sumr = igraphddot_(&i__2, &c__[k1 + min(i__3,*n) * c_dim1], ldc, &b[l2 + min(i__4,*n) * b_dim1], ldb); vec[2] = c__[k1 + l2 * c_dim1] - (suml + sgn * sumr); i__2 = k1 - 1; suml = igraphddot_(&i__2, &a[k2 * a_dim1 + 1], &c__1, &c__[l1 * c_dim1 + 1], &c__1); i__2 = *n - l2; /* Computing MIN */ i__3 = l2 + 1; /* Computing MIN */ i__4 = l2 + 1; sumr = igraphddot_(&i__2, &c__[k2 + min(i__3,*n) * c_dim1], ldc, &b[l1 + min(i__4,*n) * b_dim1], ldb); vec[1] = c__[k2 + l1 * c_dim1] - (suml + sgn * sumr); i__2 = k1 - 1; suml = igraphddot_(&i__2, &a[k2 * a_dim1 + 1], &c__1, &c__[l2 * c_dim1 + 1], &c__1); i__2 = *n - l2; /* Computing MIN */ i__3 = l2 + 1; /* Computing MIN */ i__4 = l2 + 1; sumr = igraphddot_(&i__2, &c__[k2 + min(i__3,*n) * c_dim1], ldc, &b[l2 + min(i__4,*n) * b_dim1], ldb); vec[3] = c__[k2 + l2 * c_dim1] - (suml + sgn * sumr); igraphdlasy2_(&c_true, &c_true, isgn, &c__2, &c__2, &a[k1 + k1 * a_dim1], lda, &b[l1 + l1 * b_dim1], ldb, vec, & c__2, &scaloc, x, &c__2, &xnorm, &ierr); if (ierr != 0) { *info = 1; } if (scaloc != 1.) { i__2 = *n; for (j = 1; j <= i__2; ++j) { igraphdscal_(m, &scaloc, &c__[j * c_dim1 + 1], &c__1); /* L160: */ } *scale *= scaloc; } c__[k1 + l1 * c_dim1] = x[0]; c__[k1 + l2 * c_dim1] = x[2]; c__[k2 + l1 * c_dim1] = x[1]; c__[k2 + l2 * c_dim1] = x[3]; } L170: ; } L180: ; } } else if (notrna && ! notrnb) { /* Solve A*X + ISGN*X*B**T = scale*C. The (K,L)th block of X is determined starting from bottom-right corner column by column by A(K,K)*X(K,L) + ISGN*X(K,L)*B(L,L)**T = C(K,L) - R(K,L) Where M N R(K,L) = SUM [A(K,I)*X(I,L)] + ISGN*SUM [X(K,J)*B(L,J)**T]. I=K+1 J=L+1 Start column loop (index = L) L1 (L2): column index of the first (last) row of X(K,L) */ lnext = *n; for (l = *n; l >= 1; --l) { if (l > lnext) { goto L240; } if (l == 1) { l1 = l; l2 = l; } else { if (b[l + (l - 1) * b_dim1] != 0.) { l1 = l - 1; l2 = l; lnext = l - 2; } else { l1 = l; l2 = l; lnext = l - 1; } } /* Start row loop (index = K) K1 (K2): row index of the first (last) row of X(K,L) */ knext = *m; for (k = *m; k >= 1; --k) { if (k > knext) { goto L230; } if (k == 1) { k1 = k; k2 = k; } else { if (a[k + (k - 1) * a_dim1] != 0.) { k1 = k - 1; k2 = k; knext = k - 2; } else { k1 = k; k2 = k; knext = k - 1; } } if (l1 == l2 && k1 == k2) { i__1 = *m - k1; /* Computing MIN */ i__2 = k1 + 1; /* Computing MIN */ i__3 = k1 + 1; suml = igraphddot_(&i__1, &a[k1 + min(i__2,*m) * a_dim1], lda, & c__[min(i__3,*m) + l1 * c_dim1], &c__1); i__1 = *n - l1; /* Computing MIN */ i__2 = l1 + 1; /* Computing MIN */ i__3 = l1 + 1; sumr = igraphddot_(&i__1, &c__[k1 + min(i__2,*n) * c_dim1], ldc, &b[l1 + min(i__3,*n) * b_dim1], ldb); vec[0] = c__[k1 + l1 * c_dim1] - (suml + sgn * sumr); scaloc = 1.; a11 = a[k1 + k1 * a_dim1] + sgn * b[l1 + l1 * b_dim1]; da11 = abs(a11); if (da11 <= smin) { a11 = smin; da11 = smin; *info = 1; } db = abs(vec[0]); if (da11 < 1. && db > 1.) { if (db > bignum * da11) { scaloc = 1. / db; } } x[0] = vec[0] * scaloc / a11; if (scaloc != 1.) { i__1 = *n; for (j = 1; j <= i__1; ++j) { igraphdscal_(m, &scaloc, &c__[j * c_dim1 + 1], &c__1); /* L190: */ } *scale *= scaloc; } c__[k1 + l1 * c_dim1] = x[0]; } else if (l1 == l2 && k1 != k2) { i__1 = *m - k2; /* Computing MIN */ i__2 = k2 + 1; /* Computing MIN */ i__3 = k2 + 1; suml = igraphddot_(&i__1, &a[k1 + min(i__2,*m) * a_dim1], lda, & c__[min(i__3,*m) + l1 * c_dim1], &c__1); i__1 = *n - l2; /* Computing MIN */ i__2 = l2 + 1; /* Computing MIN */ i__3 = l2 + 1; sumr = igraphddot_(&i__1, &c__[k1 + min(i__2,*n) * c_dim1], ldc, &b[l1 + min(i__3,*n) * b_dim1], ldb); vec[0] = c__[k1 + l1 * c_dim1] - (suml + sgn * sumr); i__1 = *m - k2; /* Computing MIN */ i__2 = k2 + 1; /* Computing MIN */ i__3 = k2 + 1; suml = igraphddot_(&i__1, &a[k2 + min(i__2,*m) * a_dim1], lda, & c__[min(i__3,*m) + l1 * c_dim1], &c__1); i__1 = *n - l2; /* Computing MIN */ i__2 = l2 + 1; /* Computing MIN */ i__3 = l2 + 1; sumr = igraphddot_(&i__1, &c__[k2 + min(i__2,*n) * c_dim1], ldc, &b[l1 + min(i__3,*n) * b_dim1], ldb); vec[1] = c__[k2 + l1 * c_dim1] - (suml + sgn * sumr); d__1 = -sgn * b[l1 + l1 * b_dim1]; igraphdlaln2_(&c_false, &c__2, &c__1, &smin, &c_b26, &a[k1 + k1 * a_dim1], lda, &c_b26, &c_b26, vec, &c__2, &d__1, &c_b30, x, &c__2, &scaloc, &xnorm, &ierr); if (ierr != 0) { *info = 1; } if (scaloc != 1.) { i__1 = *n; for (j = 1; j <= i__1; ++j) { igraphdscal_(m, &scaloc, &c__[j * c_dim1 + 1], &c__1); /* L200: */ } *scale *= scaloc; } c__[k1 + l1 * c_dim1] = x[0]; c__[k2 + l1 * c_dim1] = x[1]; } else if (l1 != l2 && k1 == k2) { i__1 = *m - k1; /* Computing MIN */ i__2 = k1 + 1; /* Computing MIN */ i__3 = k1 + 1; suml = igraphddot_(&i__1, &a[k1 + min(i__2,*m) * a_dim1], lda, & c__[min(i__3,*m) + l1 * c_dim1], &c__1); i__1 = *n - l2; /* Computing MIN */ i__2 = l2 + 1; /* Computing MIN */ i__3 = l2 + 1; sumr = igraphddot_(&i__1, &c__[k1 + min(i__2,*n) * c_dim1], ldc, &b[l1 + min(i__3,*n) * b_dim1], ldb); vec[0] = sgn * (c__[k1 + l1 * c_dim1] - (suml + sgn * sumr)); i__1 = *m - k1; /* Computing MIN */ i__2 = k1 + 1; /* Computing MIN */ i__3 = k1 + 1; suml = igraphddot_(&i__1, &a[k1 + min(i__2,*m) * a_dim1], lda, & c__[min(i__3,*m) + l2 * c_dim1], &c__1); i__1 = *n - l2; /* Computing MIN */ i__2 = l2 + 1; /* Computing MIN */ i__3 = l2 + 1; sumr = igraphddot_(&i__1, &c__[k1 + min(i__2,*n) * c_dim1], ldc, &b[l2 + min(i__3,*n) * b_dim1], ldb); vec[1] = sgn * (c__[k1 + l2 * c_dim1] - (suml + sgn * sumr)); d__1 = -sgn * a[k1 + k1 * a_dim1]; igraphdlaln2_(&c_false, &c__2, &c__1, &smin, &c_b26, &b[l1 + l1 * b_dim1], ldb, &c_b26, &c_b26, vec, &c__2, &d__1, &c_b30, x, &c__2, &scaloc, &xnorm, &ierr); if (ierr != 0) { *info = 1; } if (scaloc != 1.) { i__1 = *n; for (j = 1; j <= i__1; ++j) { igraphdscal_(m, &scaloc, &c__[j * c_dim1 + 1], &c__1); /* L210: */ } *scale *= scaloc; } c__[k1 + l1 * c_dim1] = x[0]; c__[k1 + l2 * c_dim1] = x[1]; } else if (l1 != l2 && k1 != k2) { i__1 = *m - k2; /* Computing MIN */ i__2 = k2 + 1; /* Computing MIN */ i__3 = k2 + 1; suml = igraphddot_(&i__1, &a[k1 + min(i__2,*m) * a_dim1], lda, & c__[min(i__3,*m) + l1 * c_dim1], &c__1); i__1 = *n - l2; /* Computing MIN */ i__2 = l2 + 1; /* Computing MIN */ i__3 = l2 + 1; sumr = igraphddot_(&i__1, &c__[k1 + min(i__2,*n) * c_dim1], ldc, &b[l1 + min(i__3,*n) * b_dim1], ldb); vec[0] = c__[k1 + l1 * c_dim1] - (suml + sgn * sumr); i__1 = *m - k2; /* Computing MIN */ i__2 = k2 + 1; /* Computing MIN */ i__3 = k2 + 1; suml = igraphddot_(&i__1, &a[k1 + min(i__2,*m) * a_dim1], lda, & c__[min(i__3,*m) + l2 * c_dim1], &c__1); i__1 = *n - l2; /* Computing MIN */ i__2 = l2 + 1; /* Computing MIN */ i__3 = l2 + 1; sumr = igraphddot_(&i__1, &c__[k1 + min(i__2,*n) * c_dim1], ldc, &b[l2 + min(i__3,*n) * b_dim1], ldb); vec[2] = c__[k1 + l2 * c_dim1] - (suml + sgn * sumr); i__1 = *m - k2; /* Computing MIN */ i__2 = k2 + 1; /* Computing MIN */ i__3 = k2 + 1; suml = igraphddot_(&i__1, &a[k2 + min(i__2,*m) * a_dim1], lda, & c__[min(i__3,*m) + l1 * c_dim1], &c__1); i__1 = *n - l2; /* Computing MIN */ i__2 = l2 + 1; /* Computing MIN */ i__3 = l2 + 1; sumr = igraphddot_(&i__1, &c__[k2 + min(i__2,*n) * c_dim1], ldc, &b[l1 + min(i__3,*n) * b_dim1], ldb); vec[1] = c__[k2 + l1 * c_dim1] - (suml + sgn * sumr); i__1 = *m - k2; /* Computing MIN */ i__2 = k2 + 1; /* Computing MIN */ i__3 = k2 + 1; suml = igraphddot_(&i__1, &a[k2 + min(i__2,*m) * a_dim1], lda, & c__[min(i__3,*m) + l2 * c_dim1], &c__1); i__1 = *n - l2; /* Computing MIN */ i__2 = l2 + 1; /* Computing MIN */ i__3 = l2 + 1; sumr = igraphddot_(&i__1, &c__[k2 + min(i__2,*n) * c_dim1], ldc, &b[l2 + min(i__3,*n) * b_dim1], ldb); vec[3] = c__[k2 + l2 * c_dim1] - (suml + sgn * sumr); igraphdlasy2_(&c_false, &c_true, isgn, &c__2, &c__2, &a[k1 + k1 * a_dim1], lda, &b[l1 + l1 * b_dim1], ldb, vec, & c__2, &scaloc, x, &c__2, &xnorm, &ierr); if (ierr != 0) { *info = 1; } if (scaloc != 1.) { i__1 = *n; for (j = 1; j <= i__1; ++j) { igraphdscal_(m, &scaloc, &c__[j * c_dim1 + 1], &c__1); /* L220: */ } *scale *= scaloc; } c__[k1 + l1 * c_dim1] = x[0]; c__[k1 + l2 * c_dim1] = x[2]; c__[k2 + l1 * c_dim1] = x[1]; c__[k2 + l2 * c_dim1] = x[3]; } L230: ; } L240: ; } } return 0; /* End of DTRSYL */ } /* igraphdtrsyl_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/ieeeck.c0000644000076500000240000001151513524616145024234 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b IEEECK =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download IEEECK + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== INTEGER FUNCTION IEEECK( ISPEC, ZERO, ONE ) INTEGER ISPEC REAL ONE, ZERO > \par Purpose: ============= > > \verbatim > > IEEECK is called from the ILAENV to verify that Infinity and > possibly NaN arithmetic is safe (i.e. will not trap). > \endverbatim Arguments: ========== > \param[in] ISPEC > \verbatim > ISPEC is INTEGER > Specifies whether to test just for inifinity arithmetic > or whether to test for infinity and NaN arithmetic. > = 0: Verify infinity arithmetic only. > = 1: Verify infinity and NaN arithmetic. > \endverbatim > > \param[in] ZERO > \verbatim > ZERO is REAL > Must contain the value 0.0 > This is passed to prevent the compiler from optimizing > away this code. > \endverbatim > > \param[in] ONE > \verbatim > ONE is REAL > Must contain the value 1.0 > This is passed to prevent the compiler from optimizing > away this code. > > RETURN VALUE: INTEGER > = 0: Arithmetic failed to produce the correct answers > = 1: Arithmetic produced the correct answers > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2011 > \ingroup auxOTHERauxiliary ===================================================================== */ integer igraphieeeck_(integer *ispec, real *zero, real *one) { /* System generated locals */ integer ret_val; /* Local variables */ real nan1, nan2, nan3, nan4, nan5, nan6, neginf, posinf, negzro, newzro; /* -- LAPACK auxiliary routine (version 3.4.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2011 ===================================================================== */ ret_val = 1; posinf = *one / *zero; if (posinf <= *one) { ret_val = 0; return ret_val; } neginf = -(*one) / *zero; if (neginf >= *zero) { ret_val = 0; return ret_val; } negzro = *one / (neginf + *one); if (negzro != *zero) { ret_val = 0; return ret_val; } neginf = *one / negzro; if (neginf >= *zero) { ret_val = 0; return ret_val; } newzro = negzro + *zero; if (newzro != *zero) { ret_val = 0; return ret_val; } posinf = *one / newzro; if (posinf <= *one) { ret_val = 0; return ret_val; } neginf *= posinf; if (neginf >= *zero) { ret_val = 0; return ret_val; } posinf *= posinf; if (posinf <= *one) { ret_val = 0; return ret_val; } /* Return if we were only asked to check infinity arithmetic */ if (*ispec == 0) { return ret_val; } nan1 = posinf + neginf; nan2 = posinf / neginf; nan3 = posinf / posinf; nan4 = posinf * *zero; nan5 = neginf * negzro; nan6 = nan5 * *zero; if (nan1 == nan1) { ret_val = 0; return ret_val; } if (nan2 == nan2) { ret_val = 0; return ret_val; } if (nan3 == nan3) { ret_val = 0; return ret_val; } if (nan4 == nan4) { ret_val = 0; return ret_val; } if (nan5 == nan5) { ret_val = 0; return ret_val; } if (nan6 == nan6) { ret_val = 0; return ret_val; } return ret_val; } /* igraphieeeck_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dtrsv.c0000644000076500000240000002037613524616145024156 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Subroutine */ int igraphdtrsv_(char *uplo, char *trans, char *diag, integer *n, doublereal *a, integer *lda, doublereal *x, integer *incx) { /* System generated locals */ integer a_dim1, a_offset, i__1, i__2; /* Local variables */ integer i__, j, ix, jx, kx, info; doublereal temp; extern logical igraphlsame_(char *, char *); extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); logical nounit; /* Purpose ======= DTRSV solves one of the systems of equations A*x = b, or A**T*x = b, where b and x are n element vectors and A is an n by n unit, or non-unit, upper or lower triangular matrix. No test for singularity or near-singularity is included in this routine. Such tests must be performed before calling this routine. Arguments ========== UPLO - CHARACTER*1. On entry, UPLO specifies whether the matrix is an upper or lower triangular matrix as follows: UPLO = 'U' or 'u' A is an upper triangular matrix. UPLO = 'L' or 'l' A is a lower triangular matrix. Unchanged on exit. TRANS - CHARACTER*1. On entry, TRANS specifies the equations to be solved as follows: TRANS = 'N' or 'n' A*x = b. TRANS = 'T' or 't' A**T*x = b. TRANS = 'C' or 'c' A**T*x = b. Unchanged on exit. DIAG - CHARACTER*1. On entry, DIAG specifies whether or not A is unit triangular as follows: DIAG = 'U' or 'u' A is assumed to be unit triangular. DIAG = 'N' or 'n' A is not assumed to be unit triangular. Unchanged on exit. N - INTEGER. On entry, N specifies the order of the matrix A. N must be at least zero. Unchanged on exit. A - DOUBLE PRECISION array of DIMENSION ( LDA, n ). Before entry with UPLO = 'U' or 'u', the leading n by n upper triangular part of the array A must contain the upper triangular matrix and the strictly lower triangular part of A is not referenced. Before entry with UPLO = 'L' or 'l', the leading n by n lower triangular part of the array A must contain the lower triangular matrix and the strictly upper triangular part of A is not referenced. Note that when DIAG = 'U' or 'u', the diagonal elements of A are not referenced either, but are assumed to be unity. Unchanged on exit. LDA - INTEGER. On entry, LDA specifies the first dimension of A as declared in the calling (sub) program. LDA must be at least max( 1, n ). Unchanged on exit. X - DOUBLE PRECISION array of dimension at least ( 1 + ( n - 1 )*abs( INCX ) ). Before entry, the incremented array X must contain the n element right-hand side vector b. On exit, X is overwritten with the solution vector x. INCX - INTEGER. On entry, INCX specifies the increment for the elements of X. INCX must not be zero. Unchanged on exit. Level 2 Blas routine. -- Written on 22-October-1986. Jack Dongarra, Argonne National Lab. Jeremy Du Croz, Nag Central Office. Sven Hammarling, Nag Central Office. Richard Hanson, Sandia National Labs. ===================================================================== Test the input parameters. Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --x; /* Function Body */ info = 0; if (! igraphlsame_(uplo, "U") && ! igraphlsame_(uplo, "L")) { info = 1; } else if (! igraphlsame_(trans, "N") && ! igraphlsame_(trans, "T") && ! igraphlsame_(trans, "C")) { info = 2; } else if (! igraphlsame_(diag, "U") && ! igraphlsame_(diag, "N")) { info = 3; } else if (*n < 0) { info = 4; } else if (*lda < max(1,*n)) { info = 6; } else if (*incx == 0) { info = 8; } if (info != 0) { igraphxerbla_("DTRSV ", &info, (ftnlen)6); return 0; } /* Quick return if possible. */ if (*n == 0) { return 0; } nounit = igraphlsame_(diag, "N"); /* Set up the start point in X if the increment is not unity. This will be ( N - 1 )*INCX too small for descending loops. */ if (*incx <= 0) { kx = 1 - (*n - 1) * *incx; } else if (*incx != 1) { kx = 1; } /* Start the operations. In this version the elements of A are accessed sequentially with one pass through A. */ if (igraphlsame_(trans, "N")) { /* Form x := inv( A )*x. */ if (igraphlsame_(uplo, "U")) { if (*incx == 1) { for (j = *n; j >= 1; --j) { if (x[j] != 0.) { if (nounit) { x[j] /= a[j + j * a_dim1]; } temp = x[j]; for (i__ = j - 1; i__ >= 1; --i__) { x[i__] -= temp * a[i__ + j * a_dim1]; /* L10: */ } } /* L20: */ } } else { jx = kx + (*n - 1) * *incx; for (j = *n; j >= 1; --j) { if (x[jx] != 0.) { if (nounit) { x[jx] /= a[j + j * a_dim1]; } temp = x[jx]; ix = jx; for (i__ = j - 1; i__ >= 1; --i__) { ix -= *incx; x[ix] -= temp * a[i__ + j * a_dim1]; /* L30: */ } } jx -= *incx; /* L40: */ } } } else { if (*incx == 1) { i__1 = *n; for (j = 1; j <= i__1; ++j) { if (x[j] != 0.) { if (nounit) { x[j] /= a[j + j * a_dim1]; } temp = x[j]; i__2 = *n; for (i__ = j + 1; i__ <= i__2; ++i__) { x[i__] -= temp * a[i__ + j * a_dim1]; /* L50: */ } } /* L60: */ } } else { jx = kx; i__1 = *n; for (j = 1; j <= i__1; ++j) { if (x[jx] != 0.) { if (nounit) { x[jx] /= a[j + j * a_dim1]; } temp = x[jx]; ix = jx; i__2 = *n; for (i__ = j + 1; i__ <= i__2; ++i__) { ix += *incx; x[ix] -= temp * a[i__ + j * a_dim1]; /* L70: */ } } jx += *incx; /* L80: */ } } } } else { /* Form x := inv( A**T )*x. */ if (igraphlsame_(uplo, "U")) { if (*incx == 1) { i__1 = *n; for (j = 1; j <= i__1; ++j) { temp = x[j]; i__2 = j - 1; for (i__ = 1; i__ <= i__2; ++i__) { temp -= a[i__ + j * a_dim1] * x[i__]; /* L90: */ } if (nounit) { temp /= a[j + j * a_dim1]; } x[j] = temp; /* L100: */ } } else { jx = kx; i__1 = *n; for (j = 1; j <= i__1; ++j) { temp = x[jx]; ix = kx; i__2 = j - 1; for (i__ = 1; i__ <= i__2; ++i__) { temp -= a[i__ + j * a_dim1] * x[ix]; ix += *incx; /* L110: */ } if (nounit) { temp /= a[j + j * a_dim1]; } x[jx] = temp; jx += *incx; /* L120: */ } } } else { if (*incx == 1) { for (j = *n; j >= 1; --j) { temp = x[j]; i__1 = j + 1; for (i__ = *n; i__ >= i__1; --i__) { temp -= a[i__ + j * a_dim1] * x[i__]; /* L130: */ } if (nounit) { temp /= a[j + j * a_dim1]; } x[j] = temp; /* L140: */ } } else { kx += (*n - 1) * *incx; jx = kx; for (j = *n; j >= 1; --j) { temp = x[jx]; ix = kx; i__1 = j + 1; for (i__ = *n; i__ >= i__1; --i__) { temp -= a[i__ + j * a_dim1] * x[ix]; ix -= *incx; /* L150: */ } if (nounit) { temp /= a[j + j * a_dim1]; } x[jx] = temp; jx -= *incx; /* L160: */ } } } } return 0; /* End of DTRSV . */ } /* igraphdtrsv_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlasr.c0000644000076500000240000003602513524616145024117 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLASR applies a sequence of plane rotations to a general rectangular matrix. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLASR + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLASR( SIDE, PIVOT, DIRECT, M, N, C, S, A, LDA ) CHARACTER DIRECT, PIVOT, SIDE INTEGER LDA, M, N DOUBLE PRECISION A( LDA, * ), C( * ), S( * ) > \par Purpose: ============= > > \verbatim > > DLASR applies a sequence of plane rotations to a real matrix A, > from either the left or the right. > > When SIDE = 'L', the transformation takes the form > > A := P*A > > and when SIDE = 'R', the transformation takes the form > > A := A*P**T > > where P is an orthogonal matrix consisting of a sequence of z plane > rotations, with z = M when SIDE = 'L' and z = N when SIDE = 'R', > and P**T is the transpose of P. > > When DIRECT = 'F' (Forward sequence), then > > P = P(z-1) * ... * P(2) * P(1) > > and when DIRECT = 'B' (Backward sequence), then > > P = P(1) * P(2) * ... * P(z-1) > > where P(k) is a plane rotation matrix defined by the 2-by-2 rotation > > R(k) = ( c(k) s(k) ) > = ( -s(k) c(k) ). > > When PIVOT = 'V' (Variable pivot), the rotation is performed > for the plane (k,k+1), i.e., P(k) has the form > > P(k) = ( 1 ) > ( ... ) > ( 1 ) > ( c(k) s(k) ) > ( -s(k) c(k) ) > ( 1 ) > ( ... ) > ( 1 ) > > where R(k) appears as a rank-2 modification to the identity matrix in > rows and columns k and k+1. > > When PIVOT = 'T' (Top pivot), the rotation is performed for the > plane (1,k+1), so P(k) has the form > > P(k) = ( c(k) s(k) ) > ( 1 ) > ( ... ) > ( 1 ) > ( -s(k) c(k) ) > ( 1 ) > ( ... ) > ( 1 ) > > where R(k) appears in rows and columns 1 and k+1. > > Similarly, when PIVOT = 'B' (Bottom pivot), the rotation is > performed for the plane (k,z), giving P(k) the form > > P(k) = ( 1 ) > ( ... ) > ( 1 ) > ( c(k) s(k) ) > ( 1 ) > ( ... ) > ( 1 ) > ( -s(k) c(k) ) > > where R(k) appears in rows and columns k and z. The rotations are > performed without ever forming P(k) explicitly. > \endverbatim Arguments: ========== > \param[in] SIDE > \verbatim > SIDE is CHARACTER*1 > Specifies whether the plane rotation matrix P is applied to > A on the left or the right. > = 'L': Left, compute A := P*A > = 'R': Right, compute A:= A*P**T > \endverbatim > > \param[in] PIVOT > \verbatim > PIVOT is CHARACTER*1 > Specifies the plane for which P(k) is a plane rotation > matrix. > = 'V': Variable pivot, the plane (k,k+1) > = 'T': Top pivot, the plane (1,k+1) > = 'B': Bottom pivot, the plane (k,z) > \endverbatim > > \param[in] DIRECT > \verbatim > DIRECT is CHARACTER*1 > Specifies whether P is a forward or backward sequence of > plane rotations. > = 'F': Forward, P = P(z-1)*...*P(2)*P(1) > = 'B': Backward, P = P(1)*P(2)*...*P(z-1) > \endverbatim > > \param[in] M > \verbatim > M is INTEGER > The number of rows of the matrix A. If m <= 1, an immediate > return is effected. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The number of columns of the matrix A. If n <= 1, an > immediate return is effected. > \endverbatim > > \param[in] C > \verbatim > C is DOUBLE PRECISION array, dimension > (M-1) if SIDE = 'L' > (N-1) if SIDE = 'R' > The cosines c(k) of the plane rotations. > \endverbatim > > \param[in] S > \verbatim > S is DOUBLE PRECISION array, dimension > (M-1) if SIDE = 'L' > (N-1) if SIDE = 'R' > The sines s(k) of the plane rotations. The 2-by-2 plane > rotation part of the matrix P(k), R(k), has the form > R(k) = ( c(k) s(k) ) > ( -s(k) c(k) ). > \endverbatim > > \param[in,out] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,N) > The M-by-N matrix A. On exit, A is overwritten by P*A if > SIDE = 'R' or by A*P**T if SIDE = 'L'. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. LDA >= max(1,M). > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERauxiliary ===================================================================== Subroutine */ int igraphdlasr_(char *side, char *pivot, char *direct, integer *m, integer *n, doublereal *c__, doublereal *s, doublereal *a, integer * lda) { /* System generated locals */ integer a_dim1, a_offset, i__1, i__2; /* Local variables */ integer i__, j, info; doublereal temp; extern logical igraphlsame_(char *, char *); doublereal ctemp, stemp; extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Test the input parameters Parameter adjustments */ --c__; --s; a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; /* Function Body */ info = 0; if (! (igraphlsame_(side, "L") || igraphlsame_(side, "R"))) { info = 1; } else if (! (igraphlsame_(pivot, "V") || igraphlsame_(pivot, "T") || igraphlsame_(pivot, "B"))) { info = 2; } else if (! (igraphlsame_(direct, "F") || igraphlsame_(direct, "B"))) { info = 3; } else if (*m < 0) { info = 4; } else if (*n < 0) { info = 5; } else if (*lda < max(1,*m)) { info = 9; } if (info != 0) { igraphxerbla_("DLASR ", &info, (ftnlen)6); return 0; } /* Quick return if possible */ if (*m == 0 || *n == 0) { return 0; } if (igraphlsame_(side, "L")) { /* Form P * A */ if (igraphlsame_(pivot, "V")) { if (igraphlsame_(direct, "F")) { i__1 = *m - 1; for (j = 1; j <= i__1; ++j) { ctemp = c__[j]; stemp = s[j]; if (ctemp != 1. || stemp != 0.) { i__2 = *n; for (i__ = 1; i__ <= i__2; ++i__) { temp = a[j + 1 + i__ * a_dim1]; a[j + 1 + i__ * a_dim1] = ctemp * temp - stemp * a[j + i__ * a_dim1]; a[j + i__ * a_dim1] = stemp * temp + ctemp * a[j + i__ * a_dim1]; /* L10: */ } } /* L20: */ } } else if (igraphlsame_(direct, "B")) { for (j = *m - 1; j >= 1; --j) { ctemp = c__[j]; stemp = s[j]; if (ctemp != 1. || stemp != 0.) { i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { temp = a[j + 1 + i__ * a_dim1]; a[j + 1 + i__ * a_dim1] = ctemp * temp - stemp * a[j + i__ * a_dim1]; a[j + i__ * a_dim1] = stemp * temp + ctemp * a[j + i__ * a_dim1]; /* L30: */ } } /* L40: */ } } } else if (igraphlsame_(pivot, "T")) { if (igraphlsame_(direct, "F")) { i__1 = *m; for (j = 2; j <= i__1; ++j) { ctemp = c__[j - 1]; stemp = s[j - 1]; if (ctemp != 1. || stemp != 0.) { i__2 = *n; for (i__ = 1; i__ <= i__2; ++i__) { temp = a[j + i__ * a_dim1]; a[j + i__ * a_dim1] = ctemp * temp - stemp * a[ i__ * a_dim1 + 1]; a[i__ * a_dim1 + 1] = stemp * temp + ctemp * a[ i__ * a_dim1 + 1]; /* L50: */ } } /* L60: */ } } else if (igraphlsame_(direct, "B")) { for (j = *m; j >= 2; --j) { ctemp = c__[j - 1]; stemp = s[j - 1]; if (ctemp != 1. || stemp != 0.) { i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { temp = a[j + i__ * a_dim1]; a[j + i__ * a_dim1] = ctemp * temp - stemp * a[ i__ * a_dim1 + 1]; a[i__ * a_dim1 + 1] = stemp * temp + ctemp * a[ i__ * a_dim1 + 1]; /* L70: */ } } /* L80: */ } } } else if (igraphlsame_(pivot, "B")) { if (igraphlsame_(direct, "F")) { i__1 = *m - 1; for (j = 1; j <= i__1; ++j) { ctemp = c__[j]; stemp = s[j]; if (ctemp != 1. || stemp != 0.) { i__2 = *n; for (i__ = 1; i__ <= i__2; ++i__) { temp = a[j + i__ * a_dim1]; a[j + i__ * a_dim1] = stemp * a[*m + i__ * a_dim1] + ctemp * temp; a[*m + i__ * a_dim1] = ctemp * a[*m + i__ * a_dim1] - stemp * temp; /* L90: */ } } /* L100: */ } } else if (igraphlsame_(direct, "B")) { for (j = *m - 1; j >= 1; --j) { ctemp = c__[j]; stemp = s[j]; if (ctemp != 1. || stemp != 0.) { i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { temp = a[j + i__ * a_dim1]; a[j + i__ * a_dim1] = stemp * a[*m + i__ * a_dim1] + ctemp * temp; a[*m + i__ * a_dim1] = ctemp * a[*m + i__ * a_dim1] - stemp * temp; /* L110: */ } } /* L120: */ } } } } else if (igraphlsame_(side, "R")) { /* Form A * P**T */ if (igraphlsame_(pivot, "V")) { if (igraphlsame_(direct, "F")) { i__1 = *n - 1; for (j = 1; j <= i__1; ++j) { ctemp = c__[j]; stemp = s[j]; if (ctemp != 1. || stemp != 0.) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { temp = a[i__ + (j + 1) * a_dim1]; a[i__ + (j + 1) * a_dim1] = ctemp * temp - stemp * a[i__ + j * a_dim1]; a[i__ + j * a_dim1] = stemp * temp + ctemp * a[ i__ + j * a_dim1]; /* L130: */ } } /* L140: */ } } else if (igraphlsame_(direct, "B")) { for (j = *n - 1; j >= 1; --j) { ctemp = c__[j]; stemp = s[j]; if (ctemp != 1. || stemp != 0.) { i__1 = *m; for (i__ = 1; i__ <= i__1; ++i__) { temp = a[i__ + (j + 1) * a_dim1]; a[i__ + (j + 1) * a_dim1] = ctemp * temp - stemp * a[i__ + j * a_dim1]; a[i__ + j * a_dim1] = stemp * temp + ctemp * a[ i__ + j * a_dim1]; /* L150: */ } } /* L160: */ } } } else if (igraphlsame_(pivot, "T")) { if (igraphlsame_(direct, "F")) { i__1 = *n; for (j = 2; j <= i__1; ++j) { ctemp = c__[j - 1]; stemp = s[j - 1]; if (ctemp != 1. || stemp != 0.) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { temp = a[i__ + j * a_dim1]; a[i__ + j * a_dim1] = ctemp * temp - stemp * a[ i__ + a_dim1]; a[i__ + a_dim1] = stemp * temp + ctemp * a[i__ + a_dim1]; /* L170: */ } } /* L180: */ } } else if (igraphlsame_(direct, "B")) { for (j = *n; j >= 2; --j) { ctemp = c__[j - 1]; stemp = s[j - 1]; if (ctemp != 1. || stemp != 0.) { i__1 = *m; for (i__ = 1; i__ <= i__1; ++i__) { temp = a[i__ + j * a_dim1]; a[i__ + j * a_dim1] = ctemp * temp - stemp * a[ i__ + a_dim1]; a[i__ + a_dim1] = stemp * temp + ctemp * a[i__ + a_dim1]; /* L190: */ } } /* L200: */ } } } else if (igraphlsame_(pivot, "B")) { if (igraphlsame_(direct, "F")) { i__1 = *n - 1; for (j = 1; j <= i__1; ++j) { ctemp = c__[j]; stemp = s[j]; if (ctemp != 1. || stemp != 0.) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { temp = a[i__ + j * a_dim1]; a[i__ + j * a_dim1] = stemp * a[i__ + *n * a_dim1] + ctemp * temp; a[i__ + *n * a_dim1] = ctemp * a[i__ + *n * a_dim1] - stemp * temp; /* L210: */ } } /* L220: */ } } else if (igraphlsame_(direct, "B")) { for (j = *n - 1; j >= 1; --j) { ctemp = c__[j]; stemp = s[j]; if (ctemp != 1. || stemp != 0.) { i__1 = *m; for (i__ = 1; i__ <= i__1; ++i__) { temp = a[i__ + j * a_dim1]; a[i__ + j * a_dim1] = stemp * a[i__ + *n * a_dim1] + ctemp * temp; a[i__ + *n * a_dim1] = ctemp * a[i__ + *n * a_dim1] - stemp * temp; /* L230: */ } } /* L240: */ } } } } return 0; /* End of DLASR */ } /* igraphdlasr_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dsyr2.c0000644000076500000240000001626513524616145024061 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Subroutine */ int igraphdsyr2_(char *uplo, integer *n, doublereal *alpha, doublereal *x, integer *incx, doublereal *y, integer *incy, doublereal *a, integer *lda) { /* System generated locals */ integer a_dim1, a_offset, i__1, i__2; /* Local variables */ integer i__, j, ix, iy, jx, jy, kx, ky, info; doublereal temp1, temp2; extern logical igraphlsame_(char *, char *); extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); /* Purpose ======= DSYR2 performs the symmetric rank 2 operation A := alpha*x*y**T + alpha*y*x**T + A, where alpha is a scalar, x and y are n element vectors and A is an n by n symmetric matrix. Arguments ========== UPLO - CHARACTER*1. On entry, UPLO specifies whether the upper or lower triangular part of the array A is to be referenced as follows: UPLO = 'U' or 'u' Only the upper triangular part of A is to be referenced. UPLO = 'L' or 'l' Only the lower triangular part of A is to be referenced. Unchanged on exit. N - INTEGER. On entry, N specifies the order of the matrix A. N must be at least zero. Unchanged on exit. ALPHA - DOUBLE PRECISION. On entry, ALPHA specifies the scalar alpha. Unchanged on exit. X - DOUBLE PRECISION array of dimension at least ( 1 + ( n - 1 )*abs( INCX ) ). Before entry, the incremented array X must contain the n element vector x. Unchanged on exit. INCX - INTEGER. On entry, INCX specifies the increment for the elements of X. INCX must not be zero. Unchanged on exit. Y - DOUBLE PRECISION array of dimension at least ( 1 + ( n - 1 )*abs( INCY ) ). Before entry, the incremented array Y must contain the n element vector y. Unchanged on exit. INCY - INTEGER. On entry, INCY specifies the increment for the elements of Y. INCY must not be zero. Unchanged on exit. A - DOUBLE PRECISION array of DIMENSION ( LDA, n ). Before entry with UPLO = 'U' or 'u', the leading n by n upper triangular part of the array A must contain the upper triangular part of the symmetric matrix and the strictly lower triangular part of A is not referenced. On exit, the upper triangular part of the array A is overwritten by the upper triangular part of the updated matrix. Before entry with UPLO = 'L' or 'l', the leading n by n lower triangular part of the array A must contain the lower triangular part of the symmetric matrix and the strictly upper triangular part of A is not referenced. On exit, the lower triangular part of the array A is overwritten by the lower triangular part of the updated matrix. LDA - INTEGER. On entry, LDA specifies the first dimension of A as declared in the calling (sub) program. LDA must be at least max( 1, n ). Unchanged on exit. Further Details =============== Level 2 Blas routine. -- Written on 22-October-1986. Jack Dongarra, Argonne National Lab. Jeremy Du Croz, Nag Central Office. Sven Hammarling, Nag Central Office. Richard Hanson, Sandia National Labs. ===================================================================== Test the input parameters. Parameter adjustments */ --x; --y; a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; /* Function Body */ info = 0; if (! igraphlsame_(uplo, "U") && ! igraphlsame_(uplo, "L")) { info = 1; } else if (*n < 0) { info = 2; } else if (*incx == 0) { info = 5; } else if (*incy == 0) { info = 7; } else if (*lda < max(1,*n)) { info = 9; } if (info != 0) { igraphxerbla_("DSYR2 ", &info, (ftnlen)6); return 0; } /* Quick return if possible. */ if (*n == 0 || *alpha == 0.) { return 0; } /* Set up the start points in X and Y if the increments are not both unity. */ if (*incx != 1 || *incy != 1) { if (*incx > 0) { kx = 1; } else { kx = 1 - (*n - 1) * *incx; } if (*incy > 0) { ky = 1; } else { ky = 1 - (*n - 1) * *incy; } jx = kx; jy = ky; } /* Start the operations. In this version the elements of A are accessed sequentially with one pass through the triangular part of A. */ if (igraphlsame_(uplo, "U")) { /* Form A when A is stored in the upper triangle. */ if (*incx == 1 && *incy == 1) { i__1 = *n; for (j = 1; j <= i__1; ++j) { if (x[j] != 0. || y[j] != 0.) { temp1 = *alpha * y[j]; temp2 = *alpha * x[j]; i__2 = j; for (i__ = 1; i__ <= i__2; ++i__) { a[i__ + j * a_dim1] = a[i__ + j * a_dim1] + x[i__] * temp1 + y[i__] * temp2; /* L10: */ } } /* L20: */ } } else { i__1 = *n; for (j = 1; j <= i__1; ++j) { if (x[jx] != 0. || y[jy] != 0.) { temp1 = *alpha * y[jy]; temp2 = *alpha * x[jx]; ix = kx; iy = ky; i__2 = j; for (i__ = 1; i__ <= i__2; ++i__) { a[i__ + j * a_dim1] = a[i__ + j * a_dim1] + x[ix] * temp1 + y[iy] * temp2; ix += *incx; iy += *incy; /* L30: */ } } jx += *incx; jy += *incy; /* L40: */ } } } else { /* Form A when A is stored in the lower triangle. */ if (*incx == 1 && *incy == 1) { i__1 = *n; for (j = 1; j <= i__1; ++j) { if (x[j] != 0. || y[j] != 0.) { temp1 = *alpha * y[j]; temp2 = *alpha * x[j]; i__2 = *n; for (i__ = j; i__ <= i__2; ++i__) { a[i__ + j * a_dim1] = a[i__ + j * a_dim1] + x[i__] * temp1 + y[i__] * temp2; /* L50: */ } } /* L60: */ } } else { i__1 = *n; for (j = 1; j <= i__1; ++j) { if (x[jx] != 0. || y[jy] != 0.) { temp1 = *alpha * y[jy]; temp2 = *alpha * x[jx]; ix = jx; iy = jy; i__2 = *n; for (i__ = j; i__ <= i__2; ++i__) { a[i__ + j * a_dim1] = a[i__ + j * a_dim1] + x[ix] * temp1 + y[iy] * temp2; ix += *incx; iy += *incy; /* L70: */ } } jx += *incx; jy += *incy; /* L80: */ } } } return 0; /* End of DSYR2 . */ } /* igraphdsyr2_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlaqr5.c0000644000076500000240000011126613524616145024203 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static doublereal c_b7 = 0.; static doublereal c_b8 = 1.; static integer c__3 = 3; static integer c__1 = 1; static integer c__2 = 2; /* > \brief \b DLAQR5 performs a single small-bulge multi-shift QR sweep. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLAQR5 + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLAQR5( WANTT, WANTZ, KACC22, N, KTOP, KBOT, NSHFTS, SR, SI, H, LDH, ILOZ, IHIZ, Z, LDZ, V, LDV, U, LDU, NV, WV, LDWV, NH, WH, LDWH ) INTEGER IHIZ, ILOZ, KACC22, KBOT, KTOP, LDH, LDU, LDV, $ LDWH, LDWV, LDZ, N, NH, NSHFTS, NV LOGICAL WANTT, WANTZ DOUBLE PRECISION H( LDH, * ), SI( * ), SR( * ), U( LDU, * ), $ V( LDV, * ), WH( LDWH, * ), WV( LDWV, * ), $ Z( LDZ, * ) > \par Purpose: ============= > > \verbatim > > DLAQR5, called by DLAQR0, performs a > single small-bulge multi-shift QR sweep. > \endverbatim Arguments: ========== > \param[in] WANTT > \verbatim > WANTT is logical scalar > WANTT = .true. if the quasi-triangular Schur factor > is being computed. WANTT is set to .false. otherwise. > \endverbatim > > \param[in] WANTZ > \verbatim > WANTZ is logical scalar > WANTZ = .true. if the orthogonal Schur factor is being > computed. WANTZ is set to .false. otherwise. > \endverbatim > > \param[in] KACC22 > \verbatim > KACC22 is integer with value 0, 1, or 2. > Specifies the computation mode of far-from-diagonal > orthogonal updates. > = 0: DLAQR5 does not accumulate reflections and does not > use matrix-matrix multiply to update far-from-diagonal > matrix entries. > = 1: DLAQR5 accumulates reflections and uses matrix-matrix > multiply to update the far-from-diagonal matrix entries. > = 2: DLAQR5 accumulates reflections, uses matrix-matrix > multiply to update the far-from-diagonal matrix entries, > and takes advantage of 2-by-2 block structure during > matrix multiplies. > \endverbatim > > \param[in] N > \verbatim > N is integer scalar > N is the order of the Hessenberg matrix H upon which this > subroutine operates. > \endverbatim > > \param[in] KTOP > \verbatim > KTOP is integer scalar > \endverbatim > > \param[in] KBOT > \verbatim > KBOT is integer scalar > These are the first and last rows and columns of an > isolated diagonal block upon which the QR sweep is to be > applied. It is assumed without a check that > either KTOP = 1 or H(KTOP,KTOP-1) = 0 > and > either KBOT = N or H(KBOT+1,KBOT) = 0. > \endverbatim > > \param[in] NSHFTS > \verbatim > NSHFTS is integer scalar > NSHFTS gives the number of simultaneous shifts. NSHFTS > must be positive and even. > \endverbatim > > \param[in,out] SR > \verbatim > SR is DOUBLE PRECISION array of size (NSHFTS) > \endverbatim > > \param[in,out] SI > \verbatim > SI is DOUBLE PRECISION array of size (NSHFTS) > SR contains the real parts and SI contains the imaginary > parts of the NSHFTS shifts of origin that define the > multi-shift QR sweep. On output SR and SI may be > reordered. > \endverbatim > > \param[in,out] H > \verbatim > H is DOUBLE PRECISION array of size (LDH,N) > On input H contains a Hessenberg matrix. On output a > multi-shift QR sweep with shifts SR(J)+i*SI(J) is applied > to the isolated diagonal block in rows and columns KTOP > through KBOT. > \endverbatim > > \param[in] LDH > \verbatim > LDH is integer scalar > LDH is the leading dimension of H just as declared in the > calling procedure. LDH.GE.MAX(1,N). > \endverbatim > > \param[in] ILOZ > \verbatim > ILOZ is INTEGER > \endverbatim > > \param[in] IHIZ > \verbatim > IHIZ is INTEGER > Specify the rows of Z to which transformations must be > applied if WANTZ is .TRUE.. 1 .LE. ILOZ .LE. IHIZ .LE. N > \endverbatim > > \param[in,out] Z > \verbatim > Z is DOUBLE PRECISION array of size (LDZ,IHI) > If WANTZ = .TRUE., then the QR Sweep orthogonal > similarity transformation is accumulated into > Z(ILOZ:IHIZ,ILO:IHI) from the right. > If WANTZ = .FALSE., then Z is unreferenced. > \endverbatim > > \param[in] LDZ > \verbatim > LDZ is integer scalar > LDA is the leading dimension of Z just as declared in > the calling procedure. LDZ.GE.N. > \endverbatim > > \param[out] V > \verbatim > V is DOUBLE PRECISION array of size (LDV,NSHFTS/2) > \endverbatim > > \param[in] LDV > \verbatim > LDV is integer scalar > LDV is the leading dimension of V as declared in the > calling procedure. LDV.GE.3. > \endverbatim > > \param[out] U > \verbatim > U is DOUBLE PRECISION array of size > (LDU,3*NSHFTS-3) > \endverbatim > > \param[in] LDU > \verbatim > LDU is integer scalar > LDU is the leading dimension of U just as declared in the > in the calling subroutine. LDU.GE.3*NSHFTS-3. > \endverbatim > > \param[in] NH > \verbatim > NH is integer scalar > NH is the number of columns in array WH available for > workspace. NH.GE.1. > \endverbatim > > \param[out] WH > \verbatim > WH is DOUBLE PRECISION array of size (LDWH,NH) > \endverbatim > > \param[in] LDWH > \verbatim > LDWH is integer scalar > Leading dimension of WH just as declared in the > calling procedure. LDWH.GE.3*NSHFTS-3. > \endverbatim > > \param[in] NV > \verbatim > NV is integer scalar > NV is the number of rows in WV agailable for workspace. > NV.GE.1. > \endverbatim > > \param[out] WV > \verbatim > WV is DOUBLE PRECISION array of size > (LDWV,3*NSHFTS-3) > \endverbatim > > \param[in] LDWV > \verbatim > LDWV is integer scalar > LDWV is the leading dimension of WV as declared in the > in the calling subroutine. LDWV.GE.NV. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleOTHERauxiliary > \par Contributors: ================== > > Karen Braman and Ralph Byers, Department of Mathematics, > University of Kansas, USA > \par References: ================ > > K. Braman, R. Byers and R. Mathias, The Multi-Shift QR > Algorithm Part I: Maintaining Well Focused Shifts, and Level 3 > Performance, SIAM Journal of Matrix Analysis, volume 23, pages > 929--947, 2002. > ===================================================================== Subroutine */ int igraphdlaqr5_(logical *wantt, logical *wantz, integer *kacc22, integer *n, integer *ktop, integer *kbot, integer *nshfts, doublereal *sr, doublereal *si, doublereal *h__, integer *ldh, integer *iloz, integer *ihiz, doublereal *z__, integer *ldz, doublereal *v, integer * ldv, doublereal *u, integer *ldu, integer *nv, doublereal *wv, integer *ldwv, integer *nh, doublereal *wh, integer *ldwh) { /* System generated locals */ integer h_dim1, h_offset, u_dim1, u_offset, v_dim1, v_offset, wh_dim1, wh_offset, wv_dim1, wv_offset, z_dim1, z_offset, i__1, i__2, i__3, i__4, i__5, i__6, i__7; doublereal d__1, d__2, d__3, d__4, d__5; /* Local variables */ integer i__, j, k, m, i2, j2, i4, j4, k1; doublereal h11, h12, h21, h22; integer m22, ns, nu; doublereal vt[3], scl; integer kdu, kms; doublereal ulp; integer knz, kzs; doublereal tst1, tst2, beta; logical blk22, bmp22; integer mend, jcol, jlen, jbot, mbot; doublereal swap; integer jtop, jrow, mtop; doublereal alpha; logical accum; extern /* Subroutine */ int igraphdgemm_(char *, char *, integer *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *); integer ndcol, incol, krcol, nbmps; extern /* Subroutine */ int igraphdtrmm_(char *, char *, char *, char *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *), igraphdlaqr1_( integer *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *), igraphdlabad_(doublereal *, doublereal *); extern doublereal igraphdlamch_(char *); extern /* Subroutine */ int igraphdlarfg_(integer *, doublereal *, doublereal *, integer *, doublereal *), igraphdlacpy_(char *, integer *, integer *, doublereal *, integer *, doublereal *, integer *); doublereal safmin; extern /* Subroutine */ int igraphdlaset_(char *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *); doublereal safmax, refsum; integer mstart; doublereal smlnum; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ================================================================ ==== If there are no shifts, then there is nothing to do. ==== Parameter adjustments */ --sr; --si; h_dim1 = *ldh; h_offset = 1 + h_dim1; h__ -= h_offset; z_dim1 = *ldz; z_offset = 1 + z_dim1; z__ -= z_offset; v_dim1 = *ldv; v_offset = 1 + v_dim1; v -= v_offset; u_dim1 = *ldu; u_offset = 1 + u_dim1; u -= u_offset; wv_dim1 = *ldwv; wv_offset = 1 + wv_dim1; wv -= wv_offset; wh_dim1 = *ldwh; wh_offset = 1 + wh_dim1; wh -= wh_offset; /* Function Body */ if (*nshfts < 2) { return 0; } /* ==== If the active block is empty or 1-by-1, then there . is nothing to do. ==== */ if (*ktop >= *kbot) { return 0; } /* ==== Shuffle shifts into pairs of real shifts and pairs . of complex conjugate shifts assuming complex . conjugate shifts are already adjacent to one . another. ==== */ i__1 = *nshfts - 2; for (i__ = 1; i__ <= i__1; i__ += 2) { if (si[i__] != -si[i__ + 1]) { swap = sr[i__]; sr[i__] = sr[i__ + 1]; sr[i__ + 1] = sr[i__ + 2]; sr[i__ + 2] = swap; swap = si[i__]; si[i__] = si[i__ + 1]; si[i__ + 1] = si[i__ + 2]; si[i__ + 2] = swap; } /* L10: */ } /* ==== NSHFTS is supposed to be even, but if it is odd, . then simply reduce it by one. The shuffle above . ensures that the dropped shift is real and that . the remaining shifts are paired. ==== */ ns = *nshfts - *nshfts % 2; /* ==== Machine constants for deflation ==== */ safmin = igraphdlamch_("SAFE MINIMUM"); safmax = 1. / safmin; igraphdlabad_(&safmin, &safmax); ulp = igraphdlamch_("PRECISION"); smlnum = safmin * ((doublereal) (*n) / ulp); /* ==== Use accumulated reflections to update far-from-diagonal . entries ? ==== */ accum = *kacc22 == 1 || *kacc22 == 2; /* ==== If so, exploit the 2-by-2 block structure? ==== */ blk22 = ns > 2 && *kacc22 == 2; /* ==== clear trash ==== */ if (*ktop + 2 <= *kbot) { h__[*ktop + 2 + *ktop * h_dim1] = 0.; } /* ==== NBMPS = number of 2-shift bulges in the chain ==== */ nbmps = ns / 2; /* ==== KDU = width of slab ==== */ kdu = nbmps * 6 - 3; /* ==== Create and chase chains of NBMPS bulges ==== */ i__1 = *kbot - 2; i__2 = nbmps * 3 - 2; for (incol = (1 - nbmps) * 3 + *ktop - 1; i__2 < 0 ? incol >= i__1 : incol <= i__1; incol += i__2) { ndcol = incol + kdu; if (accum) { igraphdlaset_("ALL", &kdu, &kdu, &c_b7, &c_b8, &u[u_offset], ldu); } /* ==== Near-the-diagonal bulge chase. The following loop . performs the near-the-diagonal part of a small bulge . multi-shift QR sweep. Each 6*NBMPS-2 column diagonal . chunk extends from column INCOL to column NDCOL . (including both column INCOL and column NDCOL). The . following loop chases a 3*NBMPS column long chain of . NBMPS bulges 3*NBMPS-2 columns to the right. (INCOL . may be less than KTOP and and NDCOL may be greater than . KBOT indicating phantom columns from which to chase . bulges before they are actually introduced or to which . to chase bulges beyond column KBOT.) ==== Computing MIN */ i__4 = incol + nbmps * 3 - 3, i__5 = *kbot - 2; i__3 = min(i__4,i__5); for (krcol = incol; krcol <= i__3; ++krcol) { /* ==== Bulges number MTOP to MBOT are active double implicit . shift bulges. There may or may not also be small . 2-by-2 bulge, if there is room. The inactive bulges . (if any) must wait until the active bulges have moved . down the diagonal to make room. The phantom matrix . paradigm described above helps keep track. ==== Computing MAX */ i__4 = 1, i__5 = (*ktop - 1 - krcol + 2) / 3 + 1; mtop = max(i__4,i__5); /* Computing MIN */ i__4 = nbmps, i__5 = (*kbot - krcol) / 3; mbot = min(i__4,i__5); m22 = mbot + 1; bmp22 = mbot < nbmps && krcol + (m22 - 1) * 3 == *kbot - 2; /* ==== Generate reflections to chase the chain right . one column. (The minimum value of K is KTOP-1.) ==== */ i__4 = mbot; for (m = mtop; m <= i__4; ++m) { k = krcol + (m - 1) * 3; if (k == *ktop - 1) { igraphdlaqr1_(&c__3, &h__[*ktop + *ktop * h_dim1], ldh, &sr[(m << 1) - 1], &si[(m << 1) - 1], &sr[m * 2], &si[m * 2], &v[m * v_dim1 + 1]); alpha = v[m * v_dim1 + 1]; igraphdlarfg_(&c__3, &alpha, &v[m * v_dim1 + 2], &c__1, &v[m * v_dim1 + 1]); } else { beta = h__[k + 1 + k * h_dim1]; v[m * v_dim1 + 2] = h__[k + 2 + k * h_dim1]; v[m * v_dim1 + 3] = h__[k + 3 + k * h_dim1]; igraphdlarfg_(&c__3, &beta, &v[m * v_dim1 + 2], &c__1, &v[m * v_dim1 + 1]); /* ==== A Bulge may collapse because of vigilant . deflation or destructive underflow. In the . underflow case, try the two-small-subdiagonals . trick to try to reinflate the bulge. ==== */ if (h__[k + 3 + k * h_dim1] != 0. || h__[k + 3 + (k + 1) * h_dim1] != 0. || h__[k + 3 + (k + 2) * h_dim1] == 0.) { /* ==== Typical case: not collapsed (yet). ==== */ h__[k + 1 + k * h_dim1] = beta; h__[k + 2 + k * h_dim1] = 0.; h__[k + 3 + k * h_dim1] = 0.; } else { /* ==== Atypical case: collapsed. Attempt to . reintroduce ignoring H(K+1,K) and H(K+2,K). . If the fill resulting from the new . reflector is too large, then abandon it. . Otherwise, use the new one. ==== */ igraphdlaqr1_(&c__3, &h__[k + 1 + (k + 1) * h_dim1], ldh, & sr[(m << 1) - 1], &si[(m << 1) - 1], &sr[m * 2], &si[m * 2], vt); alpha = vt[0]; igraphdlarfg_(&c__3, &alpha, &vt[1], &c__1, vt); refsum = vt[0] * (h__[k + 1 + k * h_dim1] + vt[1] * h__[k + 2 + k * h_dim1]); if ((d__1 = h__[k + 2 + k * h_dim1] - refsum * vt[1], abs(d__1)) + (d__2 = refsum * vt[2], abs(d__2) ) > ulp * ((d__3 = h__[k + k * h_dim1], abs( d__3)) + (d__4 = h__[k + 1 + (k + 1) * h_dim1] , abs(d__4)) + (d__5 = h__[k + 2 + (k + 2) * h_dim1], abs(d__5)))) { /* ==== Starting a new bulge here would . create non-negligible fill. Use . the old one with trepidation. ==== */ h__[k + 1 + k * h_dim1] = beta; h__[k + 2 + k * h_dim1] = 0.; h__[k + 3 + k * h_dim1] = 0.; } else { /* ==== Stating a new bulge here would . create only negligible fill. . Replace the old reflector with . the new one. ==== */ h__[k + 1 + k * h_dim1] -= refsum; h__[k + 2 + k * h_dim1] = 0.; h__[k + 3 + k * h_dim1] = 0.; v[m * v_dim1 + 1] = vt[0]; v[m * v_dim1 + 2] = vt[1]; v[m * v_dim1 + 3] = vt[2]; } } } /* L20: */ } /* ==== Generate a 2-by-2 reflection, if needed. ==== */ k = krcol + (m22 - 1) * 3; if (bmp22) { if (k == *ktop - 1) { igraphdlaqr1_(&c__2, &h__[k + 1 + (k + 1) * h_dim1], ldh, &sr[( m22 << 1) - 1], &si[(m22 << 1) - 1], &sr[m22 * 2], &si[m22 * 2], &v[m22 * v_dim1 + 1]); beta = v[m22 * v_dim1 + 1]; igraphdlarfg_(&c__2, &beta, &v[m22 * v_dim1 + 2], &c__1, &v[m22 * v_dim1 + 1]); } else { beta = h__[k + 1 + k * h_dim1]; v[m22 * v_dim1 + 2] = h__[k + 2 + k * h_dim1]; igraphdlarfg_(&c__2, &beta, &v[m22 * v_dim1 + 2], &c__1, &v[m22 * v_dim1 + 1]); h__[k + 1 + k * h_dim1] = beta; h__[k + 2 + k * h_dim1] = 0.; } } /* ==== Multiply H by reflections from the left ==== */ if (accum) { jbot = min(ndcol,*kbot); } else if (*wantt) { jbot = *n; } else { jbot = *kbot; } i__4 = jbot; for (j = max(*ktop,krcol); j <= i__4; ++j) { /* Computing MIN */ i__5 = mbot, i__6 = (j - krcol + 2) / 3; mend = min(i__5,i__6); i__5 = mend; for (m = mtop; m <= i__5; ++m) { k = krcol + (m - 1) * 3; refsum = v[m * v_dim1 + 1] * (h__[k + 1 + j * h_dim1] + v[ m * v_dim1 + 2] * h__[k + 2 + j * h_dim1] + v[m * v_dim1 + 3] * h__[k + 3 + j * h_dim1]); h__[k + 1 + j * h_dim1] -= refsum; h__[k + 2 + j * h_dim1] -= refsum * v[m * v_dim1 + 2]; h__[k + 3 + j * h_dim1] -= refsum * v[m * v_dim1 + 3]; /* L30: */ } /* L40: */ } if (bmp22) { k = krcol + (m22 - 1) * 3; /* Computing MAX */ i__4 = k + 1; i__5 = jbot; for (j = max(i__4,*ktop); j <= i__5; ++j) { refsum = v[m22 * v_dim1 + 1] * (h__[k + 1 + j * h_dim1] + v[m22 * v_dim1 + 2] * h__[k + 2 + j * h_dim1]); h__[k + 1 + j * h_dim1] -= refsum; h__[k + 2 + j * h_dim1] -= refsum * v[m22 * v_dim1 + 2]; /* L50: */ } } /* ==== Multiply H by reflections from the right. . Delay filling in the last row until the . vigilant deflation check is complete. ==== */ if (accum) { jtop = max(*ktop,incol); } else if (*wantt) { jtop = 1; } else { jtop = *ktop; } i__5 = mbot; for (m = mtop; m <= i__5; ++m) { if (v[m * v_dim1 + 1] != 0.) { k = krcol + (m - 1) * 3; /* Computing MIN */ i__6 = *kbot, i__7 = k + 3; i__4 = min(i__6,i__7); for (j = jtop; j <= i__4; ++j) { refsum = v[m * v_dim1 + 1] * (h__[j + (k + 1) * h_dim1] + v[m * v_dim1 + 2] * h__[j + (k + 2) * h_dim1] + v[m * v_dim1 + 3] * h__[j + (k + 3) * h_dim1]); h__[j + (k + 1) * h_dim1] -= refsum; h__[j + (k + 2) * h_dim1] -= refsum * v[m * v_dim1 + 2]; h__[j + (k + 3) * h_dim1] -= refsum * v[m * v_dim1 + 3]; /* L60: */ } if (accum) { /* ==== Accumulate U. (If necessary, update Z later . with with an efficient matrix-matrix . multiply.) ==== */ kms = k - incol; /* Computing MAX */ i__4 = 1, i__6 = *ktop - incol; i__7 = kdu; for (j = max(i__4,i__6); j <= i__7; ++j) { refsum = v[m * v_dim1 + 1] * (u[j + (kms + 1) * u_dim1] + v[m * v_dim1 + 2] * u[j + (kms + 2) * u_dim1] + v[m * v_dim1 + 3] * u[j + (kms + 3) * u_dim1]); u[j + (kms + 1) * u_dim1] -= refsum; u[j + (kms + 2) * u_dim1] -= refsum * v[m * v_dim1 + 2]; u[j + (kms + 3) * u_dim1] -= refsum * v[m * v_dim1 + 3]; /* L70: */ } } else if (*wantz) { /* ==== U is not accumulated, so update Z . now by multiplying by reflections . from the right. ==== */ i__7 = *ihiz; for (j = *iloz; j <= i__7; ++j) { refsum = v[m * v_dim1 + 1] * (z__[j + (k + 1) * z_dim1] + v[m * v_dim1 + 2] * z__[j + (k + 2) * z_dim1] + v[m * v_dim1 + 3] * z__[ j + (k + 3) * z_dim1]); z__[j + (k + 1) * z_dim1] -= refsum; z__[j + (k + 2) * z_dim1] -= refsum * v[m * v_dim1 + 2]; z__[j + (k + 3) * z_dim1] -= refsum * v[m * v_dim1 + 3]; /* L80: */ } } } /* L90: */ } /* ==== Special case: 2-by-2 reflection (if needed) ==== */ k = krcol + (m22 - 1) * 3; if (bmp22) { if (v[m22 * v_dim1 + 1] != 0.) { /* Computing MIN */ i__7 = *kbot, i__4 = k + 3; i__5 = min(i__7,i__4); for (j = jtop; j <= i__5; ++j) { refsum = v[m22 * v_dim1 + 1] * (h__[j + (k + 1) * h_dim1] + v[m22 * v_dim1 + 2] * h__[j + (k + 2) * h_dim1]); h__[j + (k + 1) * h_dim1] -= refsum; h__[j + (k + 2) * h_dim1] -= refsum * v[m22 * v_dim1 + 2]; /* L100: */ } if (accum) { kms = k - incol; /* Computing MAX */ i__5 = 1, i__7 = *ktop - incol; i__4 = kdu; for (j = max(i__5,i__7); j <= i__4; ++j) { refsum = v[m22 * v_dim1 + 1] * (u[j + (kms + 1) * u_dim1] + v[m22 * v_dim1 + 2] * u[j + ( kms + 2) * u_dim1]); u[j + (kms + 1) * u_dim1] -= refsum; u[j + (kms + 2) * u_dim1] -= refsum * v[m22 * v_dim1 + 2]; /* L110: */ } } else if (*wantz) { i__4 = *ihiz; for (j = *iloz; j <= i__4; ++j) { refsum = v[m22 * v_dim1 + 1] * (z__[j + (k + 1) * z_dim1] + v[m22 * v_dim1 + 2] * z__[j + ( k + 2) * z_dim1]); z__[j + (k + 1) * z_dim1] -= refsum; z__[j + (k + 2) * z_dim1] -= refsum * v[m22 * v_dim1 + 2]; /* L120: */ } } } } /* ==== Vigilant deflation check ==== */ mstart = mtop; if (krcol + (mstart - 1) * 3 < *ktop) { ++mstart; } mend = mbot; if (bmp22) { ++mend; } if (krcol == *kbot - 2) { ++mend; } i__4 = mend; for (m = mstart; m <= i__4; ++m) { /* Computing MIN */ i__5 = *kbot - 1, i__7 = krcol + (m - 1) * 3; k = min(i__5,i__7); /* ==== The following convergence test requires that . the tradition small-compared-to-nearby-diagonals . criterion and the Ahues & Tisseur (LAWN 122, 1997) . criteria both be satisfied. The latter improves . accuracy in some examples. Falling back on an . alternate convergence criterion when TST1 or TST2 . is zero (as done here) is traditional but probably . unnecessary. ==== */ if (h__[k + 1 + k * h_dim1] != 0.) { tst1 = (d__1 = h__[k + k * h_dim1], abs(d__1)) + (d__2 = h__[k + 1 + (k + 1) * h_dim1], abs(d__2)); if (tst1 == 0.) { if (k >= *ktop + 1) { tst1 += (d__1 = h__[k + (k - 1) * h_dim1], abs( d__1)); } if (k >= *ktop + 2) { tst1 += (d__1 = h__[k + (k - 2) * h_dim1], abs( d__1)); } if (k >= *ktop + 3) { tst1 += (d__1 = h__[k + (k - 3) * h_dim1], abs( d__1)); } if (k <= *kbot - 2) { tst1 += (d__1 = h__[k + 2 + (k + 1) * h_dim1], abs(d__1)); } if (k <= *kbot - 3) { tst1 += (d__1 = h__[k + 3 + (k + 1) * h_dim1], abs(d__1)); } if (k <= *kbot - 4) { tst1 += (d__1 = h__[k + 4 + (k + 1) * h_dim1], abs(d__1)); } } /* Computing MAX */ d__2 = smlnum, d__3 = ulp * tst1; if ((d__1 = h__[k + 1 + k * h_dim1], abs(d__1)) <= max( d__2,d__3)) { /* Computing MAX */ d__3 = (d__1 = h__[k + 1 + k * h_dim1], abs(d__1)), d__4 = (d__2 = h__[k + (k + 1) * h_dim1], abs( d__2)); h12 = max(d__3,d__4); /* Computing MIN */ d__3 = (d__1 = h__[k + 1 + k * h_dim1], abs(d__1)), d__4 = (d__2 = h__[k + (k + 1) * h_dim1], abs( d__2)); h21 = min(d__3,d__4); /* Computing MAX */ d__3 = (d__1 = h__[k + 1 + (k + 1) * h_dim1], abs( d__1)), d__4 = (d__2 = h__[k + k * h_dim1] - h__[k + 1 + (k + 1) * h_dim1], abs(d__2)); h11 = max(d__3,d__4); /* Computing MIN */ d__3 = (d__1 = h__[k + 1 + (k + 1) * h_dim1], abs( d__1)), d__4 = (d__2 = h__[k + k * h_dim1] - h__[k + 1 + (k + 1) * h_dim1], abs(d__2)); h22 = min(d__3,d__4); scl = h11 + h12; tst2 = h22 * (h11 / scl); /* Computing MAX */ d__1 = smlnum, d__2 = ulp * tst2; if (tst2 == 0. || h21 * (h12 / scl) <= max(d__1,d__2)) { h__[k + 1 + k * h_dim1] = 0.; } } } /* L130: */ } /* ==== Fill in the last row of each bulge. ==== Computing MIN */ i__4 = nbmps, i__5 = (*kbot - krcol - 1) / 3; mend = min(i__4,i__5); i__4 = mend; for (m = mtop; m <= i__4; ++m) { k = krcol + (m - 1) * 3; refsum = v[m * v_dim1 + 1] * v[m * v_dim1 + 3] * h__[k + 4 + ( k + 3) * h_dim1]; h__[k + 4 + (k + 1) * h_dim1] = -refsum; h__[k + 4 + (k + 2) * h_dim1] = -refsum * v[m * v_dim1 + 2]; h__[k + 4 + (k + 3) * h_dim1] -= refsum * v[m * v_dim1 + 3]; /* L140: */ } /* ==== End of near-the-diagonal bulge chase. ==== L150: */ } /* ==== Use U (if accumulated) to update far-from-diagonal . entries in H. If required, use U to update Z as . well. ==== */ if (accum) { if (*wantt) { jtop = 1; jbot = *n; } else { jtop = *ktop; jbot = *kbot; } if (! blk22 || incol < *ktop || ndcol > *kbot || ns <= 2) { /* ==== Updates not exploiting the 2-by-2 block . structure of U. K1 and NU keep track of . the location and size of U in the special . cases of introducing bulges and chasing . bulges off the bottom. In these special . cases and in case the number of shifts . is NS = 2, there is no 2-by-2 block . structure to exploit. ==== Computing MAX */ i__3 = 1, i__4 = *ktop - incol; k1 = max(i__3,i__4); /* Computing MAX */ i__3 = 0, i__4 = ndcol - *kbot; nu = kdu - max(i__3,i__4) - k1 + 1; /* ==== Horizontal Multiply ==== */ i__3 = jbot; i__4 = *nh; for (jcol = min(ndcol,*kbot) + 1; i__4 < 0 ? jcol >= i__3 : jcol <= i__3; jcol += i__4) { /* Computing MIN */ i__5 = *nh, i__7 = jbot - jcol + 1; jlen = min(i__5,i__7); igraphdgemm_("C", "N", &nu, &jlen, &nu, &c_b8, &u[k1 + k1 * u_dim1], ldu, &h__[incol + k1 + jcol * h_dim1], ldh, &c_b7, &wh[wh_offset], ldwh); igraphdlacpy_("ALL", &nu, &jlen, &wh[wh_offset], ldwh, &h__[ incol + k1 + jcol * h_dim1], ldh); /* L160: */ } /* ==== Vertical multiply ==== */ i__4 = max(*ktop,incol) - 1; i__3 = *nv; for (jrow = jtop; i__3 < 0 ? jrow >= i__4 : jrow <= i__4; jrow += i__3) { /* Computing MIN */ i__5 = *nv, i__7 = max(*ktop,incol) - jrow; jlen = min(i__5,i__7); igraphdgemm_("N", "N", &jlen, &nu, &nu, &c_b8, &h__[jrow + ( incol + k1) * h_dim1], ldh, &u[k1 + k1 * u_dim1], ldu, &c_b7, &wv[wv_offset], ldwv); igraphdlacpy_("ALL", &jlen, &nu, &wv[wv_offset], ldwv, &h__[ jrow + (incol + k1) * h_dim1], ldh); /* L170: */ } /* ==== Z multiply (also vertical) ==== */ if (*wantz) { i__3 = *ihiz; i__4 = *nv; for (jrow = *iloz; i__4 < 0 ? jrow >= i__3 : jrow <= i__3; jrow += i__4) { /* Computing MIN */ i__5 = *nv, i__7 = *ihiz - jrow + 1; jlen = min(i__5,i__7); igraphdgemm_("N", "N", &jlen, &nu, &nu, &c_b8, &z__[jrow + ( incol + k1) * z_dim1], ldz, &u[k1 + k1 * u_dim1], ldu, &c_b7, &wv[wv_offset], ldwv); igraphdlacpy_("ALL", &jlen, &nu, &wv[wv_offset], ldwv, &z__[ jrow + (incol + k1) * z_dim1], ldz) ; /* L180: */ } } } else { /* ==== Updates exploiting U's 2-by-2 block structure. . (I2, I4, J2, J4 are the last rows and columns . of the blocks.) ==== */ i2 = (kdu + 1) / 2; i4 = kdu; j2 = i4 - i2; j4 = kdu; /* ==== KZS and KNZ deal with the band of zeros . along the diagonal of one of the triangular . blocks. ==== */ kzs = j4 - j2 - (ns + 1); knz = ns + 1; /* ==== Horizontal multiply ==== */ i__4 = jbot; i__3 = *nh; for (jcol = min(ndcol,*kbot) + 1; i__3 < 0 ? jcol >= i__4 : jcol <= i__4; jcol += i__3) { /* Computing MIN */ i__5 = *nh, i__7 = jbot - jcol + 1; jlen = min(i__5,i__7); /* ==== Copy bottom of H to top+KZS of scratch ==== (The first KZS rows get multiplied by zero.) ==== */ igraphdlacpy_("ALL", &knz, &jlen, &h__[incol + 1 + j2 + jcol * h_dim1], ldh, &wh[kzs + 1 + wh_dim1], ldwh); /* ==== Multiply by U21**T ==== */ igraphdlaset_("ALL", &kzs, &jlen, &c_b7, &c_b7, &wh[wh_offset], ldwh); igraphdtrmm_("L", "U", "C", "N", &knz, &jlen, &c_b8, &u[j2 + 1 + (kzs + 1) * u_dim1], ldu, &wh[kzs + 1 + wh_dim1] , ldwh); /* ==== Multiply top of H by U11**T ==== */ igraphdgemm_("C", "N", &i2, &jlen, &j2, &c_b8, &u[u_offset], ldu, &h__[incol + 1 + jcol * h_dim1], ldh, &c_b8, &wh[wh_offset], ldwh); /* ==== Copy top of H to bottom of WH ==== */ igraphdlacpy_("ALL", &j2, &jlen, &h__[incol + 1 + jcol * h_dim1] , ldh, &wh[i2 + 1 + wh_dim1], ldwh); /* ==== Multiply by U21**T ==== */ igraphdtrmm_("L", "L", "C", "N", &j2, &jlen, &c_b8, &u[(i2 + 1) * u_dim1 + 1], ldu, &wh[i2 + 1 + wh_dim1], ldwh); /* ==== Multiply by U22 ==== */ i__5 = i4 - i2; i__7 = j4 - j2; igraphdgemm_("C", "N", &i__5, &jlen, &i__7, &c_b8, &u[j2 + 1 + ( i2 + 1) * u_dim1], ldu, &h__[incol + 1 + j2 + jcol * h_dim1], ldh, &c_b8, &wh[i2 + 1 + wh_dim1], ldwh); /* ==== Copy it back ==== */ igraphdlacpy_("ALL", &kdu, &jlen, &wh[wh_offset], ldwh, &h__[ incol + 1 + jcol * h_dim1], ldh); /* L190: */ } /* ==== Vertical multiply ==== */ i__3 = max(incol,*ktop) - 1; i__4 = *nv; for (jrow = jtop; i__4 < 0 ? jrow >= i__3 : jrow <= i__3; jrow += i__4) { /* Computing MIN */ i__5 = *nv, i__7 = max(incol,*ktop) - jrow; jlen = min(i__5,i__7); /* ==== Copy right of H to scratch (the first KZS . columns get multiplied by zero) ==== */ igraphdlacpy_("ALL", &jlen, &knz, &h__[jrow + (incol + 1 + j2) * h_dim1], ldh, &wv[(kzs + 1) * wv_dim1 + 1], ldwv); /* ==== Multiply by U21 ==== */ igraphdlaset_("ALL", &jlen, &kzs, &c_b7, &c_b7, &wv[wv_offset], ldwv); igraphdtrmm_("R", "U", "N", "N", &jlen, &knz, &c_b8, &u[j2 + 1 + (kzs + 1) * u_dim1], ldu, &wv[(kzs + 1) * wv_dim1 + 1], ldwv); /* ==== Multiply by U11 ==== */ igraphdgemm_("N", "N", &jlen, &i2, &j2, &c_b8, &h__[jrow + ( incol + 1) * h_dim1], ldh, &u[u_offset], ldu, & c_b8, &wv[wv_offset], ldwv); /* ==== Copy left of H to right of scratch ==== */ igraphdlacpy_("ALL", &jlen, &j2, &h__[jrow + (incol + 1) * h_dim1], ldh, &wv[(i2 + 1) * wv_dim1 + 1], ldwv); /* ==== Multiply by U21 ==== */ i__5 = i4 - i2; igraphdtrmm_("R", "L", "N", "N", &jlen, &i__5, &c_b8, &u[(i2 + 1) * u_dim1 + 1], ldu, &wv[(i2 + 1) * wv_dim1 + 1] , ldwv); /* ==== Multiply by U22 ==== */ i__5 = i4 - i2; i__7 = j4 - j2; igraphdgemm_("N", "N", &jlen, &i__5, &i__7, &c_b8, &h__[jrow + ( incol + 1 + j2) * h_dim1], ldh, &u[j2 + 1 + (i2 + 1) * u_dim1], ldu, &c_b8, &wv[(i2 + 1) * wv_dim1 + 1], ldwv); /* ==== Copy it back ==== */ igraphdlacpy_("ALL", &jlen, &kdu, &wv[wv_offset], ldwv, &h__[ jrow + (incol + 1) * h_dim1], ldh); /* L200: */ } /* ==== Multiply Z (also vertical) ==== */ if (*wantz) { i__4 = *ihiz; i__3 = *nv; for (jrow = *iloz; i__3 < 0 ? jrow >= i__4 : jrow <= i__4; jrow += i__3) { /* Computing MIN */ i__5 = *nv, i__7 = *ihiz - jrow + 1; jlen = min(i__5,i__7); /* ==== Copy right of Z to left of scratch (first . KZS columns get multiplied by zero) ==== */ igraphdlacpy_("ALL", &jlen, &knz, &z__[jrow + (incol + 1 + j2) * z_dim1], ldz, &wv[(kzs + 1) * wv_dim1 + 1], ldwv); /* ==== Multiply by U12 ==== */ igraphdlaset_("ALL", &jlen, &kzs, &c_b7, &c_b7, &wv[ wv_offset], ldwv); igraphdtrmm_("R", "U", "N", "N", &jlen, &knz, &c_b8, &u[j2 + 1 + (kzs + 1) * u_dim1], ldu, &wv[(kzs + 1) * wv_dim1 + 1], ldwv); /* ==== Multiply by U11 ==== */ igraphdgemm_("N", "N", &jlen, &i2, &j2, &c_b8, &z__[jrow + ( incol + 1) * z_dim1], ldz, &u[u_offset], ldu, &c_b8, &wv[wv_offset], ldwv); /* ==== Copy left of Z to right of scratch ==== */ igraphdlacpy_("ALL", &jlen, &j2, &z__[jrow + (incol + 1) * z_dim1], ldz, &wv[(i2 + 1) * wv_dim1 + 1], ldwv); /* ==== Multiply by U21 ==== */ i__5 = i4 - i2; igraphdtrmm_("R", "L", "N", "N", &jlen, &i__5, &c_b8, &u[( i2 + 1) * u_dim1 + 1], ldu, &wv[(i2 + 1) * wv_dim1 + 1], ldwv); /* ==== Multiply by U22 ==== */ i__5 = i4 - i2; i__7 = j4 - j2; igraphdgemm_("N", "N", &jlen, &i__5, &i__7, &c_b8, &z__[ jrow + (incol + 1 + j2) * z_dim1], ldz, &u[j2 + 1 + (i2 + 1) * u_dim1], ldu, &c_b8, &wv[(i2 + 1) * wv_dim1 + 1], ldwv); /* ==== Copy the result back to Z ==== */ igraphdlacpy_("ALL", &jlen, &kdu, &wv[wv_offset], ldwv, & z__[jrow + (incol + 1) * z_dim1], ldz); /* L210: */ } } } } /* L220: */ } /* ==== End of DLAQR5 ==== */ return 0; } /* igraphdlaqr5_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dgeev.c0000644000076500000240000005125113524616145024102 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static integer c__0 = 0; static integer c_n1 = -1; /* > \brief DGEEV computes the eigenvalues and, optionally, the left and/or right eigenvectors for GE matr ices =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DGEEV + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DGEEV( JOBVL, JOBVR, N, A, LDA, WR, WI, VL, LDVL, VR, LDVR, WORK, LWORK, INFO ) CHARACTER JOBVL, JOBVR INTEGER INFO, LDA, LDVL, LDVR, LWORK, N DOUBLE PRECISION A( LDA, * ), VL( LDVL, * ), VR( LDVR, * ), $ WI( * ), WORK( * ), WR( * ) > \par Purpose: ============= > > \verbatim > > DGEEV computes for an N-by-N real nonsymmetric matrix A, the > eigenvalues and, optionally, the left and/or right eigenvectors. > > The right eigenvector v(j) of A satisfies > A * v(j) = lambda(j) * v(j) > where lambda(j) is its eigenvalue. > The left eigenvector u(j) of A satisfies > u(j)**H * A = lambda(j) * u(j)**H > where u(j)**H denotes the conjugate-transpose of u(j). > > The computed eigenvectors are normalized to have Euclidean norm > equal to 1 and largest component real. > \endverbatim Arguments: ========== > \param[in] JOBVL > \verbatim > JOBVL is CHARACTER*1 > = 'N': left eigenvectors of A are not computed; > = 'V': left eigenvectors of A are computed. > \endverbatim > > \param[in] JOBVR > \verbatim > JOBVR is CHARACTER*1 > = 'N': right eigenvectors of A are not computed; > = 'V': right eigenvectors of A are computed. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix A. N >= 0. > \endverbatim > > \param[in,out] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,N) > On entry, the N-by-N matrix A. > On exit, A has been overwritten. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. LDA >= max(1,N). > \endverbatim > > \param[out] WR > \verbatim > WR is DOUBLE PRECISION array, dimension (N) > \endverbatim > > \param[out] WI > \verbatim > WI is DOUBLE PRECISION array, dimension (N) > WR and WI contain the real and imaginary parts, > respectively, of the computed eigenvalues. Complex > conjugate pairs of eigenvalues appear consecutively > with the eigenvalue having the positive imaginary part > first. > \endverbatim > > \param[out] VL > \verbatim > VL is DOUBLE PRECISION array, dimension (LDVL,N) > If JOBVL = 'V', the left eigenvectors u(j) are stored one > after another in the columns of VL, in the same order > as their eigenvalues. > If JOBVL = 'N', VL is not referenced. > If the j-th eigenvalue is real, then u(j) = VL(:,j), > the j-th column of VL. > If the j-th and (j+1)-st eigenvalues form a complex > conjugate pair, then u(j) = VL(:,j) + i*VL(:,j+1) and > u(j+1) = VL(:,j) - i*VL(:,j+1). > \endverbatim > > \param[in] LDVL > \verbatim > LDVL is INTEGER > The leading dimension of the array VL. LDVL >= 1; if > JOBVL = 'V', LDVL >= N. > \endverbatim > > \param[out] VR > \verbatim > VR is DOUBLE PRECISION array, dimension (LDVR,N) > If JOBVR = 'V', the right eigenvectors v(j) are stored one > after another in the columns of VR, in the same order > as their eigenvalues. > If JOBVR = 'N', VR is not referenced. > If the j-th eigenvalue is real, then v(j) = VR(:,j), > the j-th column of VR. > If the j-th and (j+1)-st eigenvalues form a complex > conjugate pair, then v(j) = VR(:,j) + i*VR(:,j+1) and > v(j+1) = VR(:,j) - i*VR(:,j+1). > \endverbatim > > \param[in] LDVR > \verbatim > LDVR is INTEGER > The leading dimension of the array VR. LDVR >= 1; if > JOBVR = 'V', LDVR >= N. > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (MAX(1,LWORK)) > On exit, if INFO = 0, WORK(1) returns the optimal LWORK. > \endverbatim > > \param[in] LWORK > \verbatim > LWORK is INTEGER > The dimension of the array WORK. LWORK >= max(1,3*N), and > if JOBVL = 'V' or JOBVR = 'V', LWORK >= 4*N. For good > performance, LWORK must generally be larger. > > If LWORK = -1, then a workspace query is assumed; the routine > only calculates the optimal size of the WORK array, returns > this value as the first entry of the WORK array, and no error > message related to LWORK is issued by XERBLA. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value. > > 0: if INFO = i, the QR algorithm failed to compute all the > eigenvalues, and no eigenvectors have been computed; > elements i+1:N of WR and WI contain eigenvalues which > have converged. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleGEeigen ===================================================================== Subroutine */ int igraphdgeev_(char *jobvl, char *jobvr, integer *n, doublereal * a, integer *lda, doublereal *wr, doublereal *wi, doublereal *vl, integer *ldvl, doublereal *vr, integer *ldvr, doublereal *work, integer *lwork, integer *info) { /* System generated locals */ integer a_dim1, a_offset, vl_dim1, vl_offset, vr_dim1, vr_offset, i__1, i__2, i__3; doublereal d__1, d__2; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ integer i__, k; doublereal r__, cs, sn; integer ihi; doublereal scl; integer ilo; doublereal dum[1], eps; integer ibal; char side[1]; doublereal anrm; integer ierr, itau; extern /* Subroutine */ int igraphdrot_(integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *); integer iwrk, nout; extern doublereal igraphdnrm2_(integer *, doublereal *, integer *); extern /* Subroutine */ int igraphdscal_(integer *, doublereal *, doublereal *, integer *); extern logical igraphlsame_(char *, char *); extern doublereal igraphdlapy2_(doublereal *, doublereal *); extern /* Subroutine */ int igraphdlabad_(doublereal *, doublereal *), igraphdgebak_( char *, char *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, integer *, integer *), igraphdgebal_(char *, integer *, doublereal *, integer *, integer *, integer *, doublereal *, integer *); logical scalea; extern doublereal igraphdlamch_(char *); doublereal cscale; extern doublereal igraphdlange_(char *, integer *, integer *, doublereal *, integer *, doublereal *); extern /* Subroutine */ int igraphdgehrd_(integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, integer *), igraphdlascl_(char *, integer *, integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, integer *, integer *); extern integer igraphidamax_(integer *, doublereal *, integer *); extern /* Subroutine */ int igraphdlacpy_(char *, integer *, integer *, doublereal *, integer *, doublereal *, integer *), igraphdlartg_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *), igraphxerbla_(char *, integer *, ftnlen); logical select[1]; extern integer igraphilaenv_(integer *, char *, char *, integer *, integer *, integer *, integer *, ftnlen, ftnlen); doublereal bignum; extern /* Subroutine */ int igraphdorghr_(integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, integer *), igraphdhseqr_(char *, char *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, integer *, doublereal *, integer *, integer *), igraphdtrevc_(char *, char *, logical *, integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, integer *, integer *, integer *, doublereal *, integer *); integer minwrk, maxwrk; logical wantvl; doublereal smlnum; integer hswork; logical lquery, wantvr; /* -- LAPACK driver routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Test the input arguments Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --wr; --wi; vl_dim1 = *ldvl; vl_offset = 1 + vl_dim1; vl -= vl_offset; vr_dim1 = *ldvr; vr_offset = 1 + vr_dim1; vr -= vr_offset; --work; /* Function Body */ *info = 0; lquery = *lwork == -1; wantvl = igraphlsame_(jobvl, "V"); wantvr = igraphlsame_(jobvr, "V"); if (! wantvl && ! igraphlsame_(jobvl, "N")) { *info = -1; } else if (! wantvr && ! igraphlsame_(jobvr, "N")) { *info = -2; } else if (*n < 0) { *info = -3; } else if (*lda < max(1,*n)) { *info = -5; } else if (*ldvl < 1 || wantvl && *ldvl < *n) { *info = -9; } else if (*ldvr < 1 || wantvr && *ldvr < *n) { *info = -11; } /* Compute workspace (Note: Comments in the code beginning "Workspace:" describe the minimal amount of workspace needed at that point in the code, as well as the preferred amount for good performance. NB refers to the optimal block size for the immediately following subroutine, as returned by ILAENV. HSWORK refers to the workspace preferred by DHSEQR, as calculated below. HSWORK is computed assuming ILO=1 and IHI=N, the worst case.) */ if (*info == 0) { if (*n == 0) { minwrk = 1; maxwrk = 1; } else { maxwrk = (*n << 1) + *n * igraphilaenv_(&c__1, "DGEHRD", " ", n, &c__1, n, &c__0, (ftnlen)6, (ftnlen)1); if (wantvl) { minwrk = *n << 2; /* Computing MAX */ i__1 = maxwrk, i__2 = (*n << 1) + (*n - 1) * igraphilaenv_(&c__1, "DORGHR", " ", n, &c__1, n, &c_n1, (ftnlen)6, (ftnlen) 1); maxwrk = max(i__1,i__2); igraphdhseqr_("S", "V", n, &c__1, n, &a[a_offset], lda, &wr[1], &wi[ 1], &vl[vl_offset], ldvl, &work[1], &c_n1, info); hswork = (integer) work[1]; /* Computing MAX */ i__1 = maxwrk, i__2 = *n + 1, i__1 = max(i__1,i__2), i__2 = * n + hswork; maxwrk = max(i__1,i__2); /* Computing MAX */ i__1 = maxwrk, i__2 = *n << 2; maxwrk = max(i__1,i__2); } else if (wantvr) { minwrk = *n << 2; /* Computing MAX */ i__1 = maxwrk, i__2 = (*n << 1) + (*n - 1) * igraphilaenv_(&c__1, "DORGHR", " ", n, &c__1, n, &c_n1, (ftnlen)6, (ftnlen) 1); maxwrk = max(i__1,i__2); igraphdhseqr_("S", "V", n, &c__1, n, &a[a_offset], lda, &wr[1], &wi[ 1], &vr[vr_offset], ldvr, &work[1], &c_n1, info); hswork = (integer) work[1]; /* Computing MAX */ i__1 = maxwrk, i__2 = *n + 1, i__1 = max(i__1,i__2), i__2 = * n + hswork; maxwrk = max(i__1,i__2); /* Computing MAX */ i__1 = maxwrk, i__2 = *n << 2; maxwrk = max(i__1,i__2); } else { minwrk = *n * 3; igraphdhseqr_("E", "N", n, &c__1, n, &a[a_offset], lda, &wr[1], &wi[ 1], &vr[vr_offset], ldvr, &work[1], &c_n1, info); hswork = (integer) work[1]; /* Computing MAX */ i__1 = maxwrk, i__2 = *n + 1, i__1 = max(i__1,i__2), i__2 = * n + hswork; maxwrk = max(i__1,i__2); } maxwrk = max(maxwrk,minwrk); } work[1] = (doublereal) maxwrk; if (*lwork < minwrk && ! lquery) { *info = -13; } } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DGEEV ", &i__1, (ftnlen)6); return 0; } else if (lquery) { return 0; } /* Quick return if possible */ if (*n == 0) { return 0; } /* Get machine constants */ eps = igraphdlamch_("P"); smlnum = igraphdlamch_("S"); bignum = 1. / smlnum; igraphdlabad_(&smlnum, &bignum); smlnum = sqrt(smlnum) / eps; bignum = 1. / smlnum; /* Scale A if max element outside range [SMLNUM,BIGNUM] */ anrm = igraphdlange_("M", n, n, &a[a_offset], lda, dum); scalea = FALSE_; if (anrm > 0. && anrm < smlnum) { scalea = TRUE_; cscale = smlnum; } else if (anrm > bignum) { scalea = TRUE_; cscale = bignum; } if (scalea) { igraphdlascl_("G", &c__0, &c__0, &anrm, &cscale, n, n, &a[a_offset], lda, & ierr); } /* Balance the matrix (Workspace: need N) */ ibal = 1; igraphdgebal_("B", n, &a[a_offset], lda, &ilo, &ihi, &work[ibal], &ierr); /* Reduce to upper Hessenberg form (Workspace: need 3*N, prefer 2*N+N*NB) */ itau = ibal + *n; iwrk = itau + *n; i__1 = *lwork - iwrk + 1; igraphdgehrd_(n, &ilo, &ihi, &a[a_offset], lda, &work[itau], &work[iwrk], &i__1, &ierr); if (wantvl) { /* Want left eigenvectors Copy Householder vectors to VL */ *(unsigned char *)side = 'L'; igraphdlacpy_("L", n, n, &a[a_offset], lda, &vl[vl_offset], ldvl) ; /* Generate orthogonal matrix in VL (Workspace: need 3*N-1, prefer 2*N+(N-1)*NB) */ i__1 = *lwork - iwrk + 1; igraphdorghr_(n, &ilo, &ihi, &vl[vl_offset], ldvl, &work[itau], &work[iwrk], &i__1, &ierr); /* Perform QR iteration, accumulating Schur vectors in VL (Workspace: need N+1, prefer N+HSWORK (see comments) ) */ iwrk = itau; i__1 = *lwork - iwrk + 1; igraphdhseqr_("S", "V", n, &ilo, &ihi, &a[a_offset], lda, &wr[1], &wi[1], & vl[vl_offset], ldvl, &work[iwrk], &i__1, info); if (wantvr) { /* Want left and right eigenvectors Copy Schur vectors to VR */ *(unsigned char *)side = 'B'; igraphdlacpy_("F", n, n, &vl[vl_offset], ldvl, &vr[vr_offset], ldvr); } } else if (wantvr) { /* Want right eigenvectors Copy Householder vectors to VR */ *(unsigned char *)side = 'R'; igraphdlacpy_("L", n, n, &a[a_offset], lda, &vr[vr_offset], ldvr) ; /* Generate orthogonal matrix in VR (Workspace: need 3*N-1, prefer 2*N+(N-1)*NB) */ i__1 = *lwork - iwrk + 1; igraphdorghr_(n, &ilo, &ihi, &vr[vr_offset], ldvr, &work[itau], &work[iwrk], &i__1, &ierr); /* Perform QR iteration, accumulating Schur vectors in VR (Workspace: need N+1, prefer N+HSWORK (see comments) ) */ iwrk = itau; i__1 = *lwork - iwrk + 1; igraphdhseqr_("S", "V", n, &ilo, &ihi, &a[a_offset], lda, &wr[1], &wi[1], & vr[vr_offset], ldvr, &work[iwrk], &i__1, info); } else { /* Compute eigenvalues only (Workspace: need N+1, prefer N+HSWORK (see comments) ) */ iwrk = itau; i__1 = *lwork - iwrk + 1; igraphdhseqr_("E", "N", n, &ilo, &ihi, &a[a_offset], lda, &wr[1], &wi[1], & vr[vr_offset], ldvr, &work[iwrk], &i__1, info); } /* If INFO > 0 from DHSEQR, then quit */ if (*info > 0) { goto L50; } if (wantvl || wantvr) { /* Compute left and/or right eigenvectors (Workspace: need 4*N) */ igraphdtrevc_(side, "B", select, n, &a[a_offset], lda, &vl[vl_offset], ldvl, &vr[vr_offset], ldvr, n, &nout, &work[iwrk], &ierr); } if (wantvl) { /* Undo balancing of left eigenvectors (Workspace: need N) */ igraphdgebak_("B", "L", n, &ilo, &ihi, &work[ibal], n, &vl[vl_offset], ldvl, &ierr); /* Normalize left eigenvectors and make largest component real */ i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { if (wi[i__] == 0.) { scl = 1. / igraphdnrm2_(n, &vl[i__ * vl_dim1 + 1], &c__1); igraphdscal_(n, &scl, &vl[i__ * vl_dim1 + 1], &c__1); } else if (wi[i__] > 0.) { d__1 = igraphdnrm2_(n, &vl[i__ * vl_dim1 + 1], &c__1); d__2 = igraphdnrm2_(n, &vl[(i__ + 1) * vl_dim1 + 1], &c__1); scl = 1. / igraphdlapy2_(&d__1, &d__2); igraphdscal_(n, &scl, &vl[i__ * vl_dim1 + 1], &c__1); igraphdscal_(n, &scl, &vl[(i__ + 1) * vl_dim1 + 1], &c__1); i__2 = *n; for (k = 1; k <= i__2; ++k) { /* Computing 2nd power */ d__1 = vl[k + i__ * vl_dim1]; /* Computing 2nd power */ d__2 = vl[k + (i__ + 1) * vl_dim1]; work[iwrk + k - 1] = d__1 * d__1 + d__2 * d__2; /* L10: */ } k = igraphidamax_(n, &work[iwrk], &c__1); igraphdlartg_(&vl[k + i__ * vl_dim1], &vl[k + (i__ + 1) * vl_dim1], &cs, &sn, &r__); igraphdrot_(n, &vl[i__ * vl_dim1 + 1], &c__1, &vl[(i__ + 1) * vl_dim1 + 1], &c__1, &cs, &sn); vl[k + (i__ + 1) * vl_dim1] = 0.; } /* L20: */ } } if (wantvr) { /* Undo balancing of right eigenvectors (Workspace: need N) */ igraphdgebak_("B", "R", n, &ilo, &ihi, &work[ibal], n, &vr[vr_offset], ldvr, &ierr); /* Normalize right eigenvectors and make largest component real */ i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { if (wi[i__] == 0.) { scl = 1. / igraphdnrm2_(n, &vr[i__ * vr_dim1 + 1], &c__1); igraphdscal_(n, &scl, &vr[i__ * vr_dim1 + 1], &c__1); } else if (wi[i__] > 0.) { d__1 = igraphdnrm2_(n, &vr[i__ * vr_dim1 + 1], &c__1); d__2 = igraphdnrm2_(n, &vr[(i__ + 1) * vr_dim1 + 1], &c__1); scl = 1. / igraphdlapy2_(&d__1, &d__2); igraphdscal_(n, &scl, &vr[i__ * vr_dim1 + 1], &c__1); igraphdscal_(n, &scl, &vr[(i__ + 1) * vr_dim1 + 1], &c__1); i__2 = *n; for (k = 1; k <= i__2; ++k) { /* Computing 2nd power */ d__1 = vr[k + i__ * vr_dim1]; /* Computing 2nd power */ d__2 = vr[k + (i__ + 1) * vr_dim1]; work[iwrk + k - 1] = d__1 * d__1 + d__2 * d__2; /* L30: */ } k = igraphidamax_(n, &work[iwrk], &c__1); igraphdlartg_(&vr[k + i__ * vr_dim1], &vr[k + (i__ + 1) * vr_dim1], &cs, &sn, &r__); igraphdrot_(n, &vr[i__ * vr_dim1 + 1], &c__1, &vr[(i__ + 1) * vr_dim1 + 1], &c__1, &cs, &sn); vr[k + (i__ + 1) * vr_dim1] = 0.; } /* L40: */ } } /* Undo scaling if necessary */ L50: if (scalea) { i__1 = *n - *info; /* Computing MAX */ i__3 = *n - *info; i__2 = max(i__3,1); igraphdlascl_("G", &c__0, &c__0, &cscale, &anrm, &i__1, &c__1, &wr[*info + 1], &i__2, &ierr); i__1 = *n - *info; /* Computing MAX */ i__3 = *n - *info; i__2 = max(i__3,1); igraphdlascl_("G", &c__0, &c__0, &cscale, &anrm, &i__1, &c__1, &wi[*info + 1], &i__2, &ierr); if (*info > 0) { i__1 = ilo - 1; igraphdlascl_("G", &c__0, &c__0, &cscale, &anrm, &i__1, &c__1, &wr[1], n, &ierr); i__1 = ilo - 1; igraphdlascl_("G", &c__0, &c__0, &cscale, &anrm, &i__1, &c__1, &wi[1], n, &ierr); } } work[1] = (doublereal) maxwrk; return 0; /* End of DGEEV */ } /* igraphdgeev_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dgehrd.c0000644000076500000240000003153213524616145024245 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static integer c_n1 = -1; static integer c__3 = 3; static integer c__2 = 2; static integer c__65 = 65; static doublereal c_b25 = -1.; static doublereal c_b26 = 1.; /* > \brief \b DGEHRD =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DGEHRD + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DGEHRD( N, ILO, IHI, A, LDA, TAU, WORK, LWORK, INFO ) INTEGER IHI, ILO, INFO, LDA, LWORK, N DOUBLE PRECISION A( LDA, * ), TAU( * ), WORK( * ) > \par Purpose: ============= > > \verbatim > > DGEHRD reduces a real general matrix A to upper Hessenberg form H by > an orthogonal similarity transformation: Q**T * A * Q = H . > \endverbatim Arguments: ========== > \param[in] N > \verbatim > N is INTEGER > The order of the matrix A. N >= 0. > \endverbatim > > \param[in] ILO > \verbatim > ILO is INTEGER > \endverbatim > > \param[in] IHI > \verbatim > IHI is INTEGER > > It is assumed that A is already upper triangular in rows > and columns 1:ILO-1 and IHI+1:N. ILO and IHI are normally > set by a previous call to DGEBAL; otherwise they should be > set to 1 and N respectively. See Further Details. > 1 <= ILO <= IHI <= N, if N > 0; ILO=1 and IHI=0, if N=0. > \endverbatim > > \param[in,out] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,N) > On entry, the N-by-N general matrix to be reduced. > On exit, the upper triangle and the first subdiagonal of A > are overwritten with the upper Hessenberg matrix H, and the > elements below the first subdiagonal, with the array TAU, > represent the orthogonal matrix Q as a product of elementary > reflectors. See Further Details. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. LDA >= max(1,N). > \endverbatim > > \param[out] TAU > \verbatim > TAU is DOUBLE PRECISION array, dimension (N-1) > The scalar factors of the elementary reflectors (see Further > Details). Elements 1:ILO-1 and IHI:N-1 of TAU are set to > zero. > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (LWORK) > On exit, if INFO = 0, WORK(1) returns the optimal LWORK. > \endverbatim > > \param[in] LWORK > \verbatim > LWORK is INTEGER > The length of the array WORK. LWORK >= max(1,N). > For optimum performance LWORK >= N*NB, where NB is the > optimal blocksize. > > If LWORK = -1, then a workspace query is assumed; the routine > only calculates the optimal size of the WORK array, returns > this value as the first entry of the WORK array, and no error > message related to LWORK is issued by XERBLA. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2011 > \ingroup doubleGEcomputational > \par Further Details: ===================== > > \verbatim > > The matrix Q is represented as a product of (ihi-ilo) elementary > reflectors > > Q = H(ilo) H(ilo+1) . . . H(ihi-1). > > Each H(i) has the form > > H(i) = I - tau * v * v**T > > where tau is a real scalar, and v is a real vector with > v(1:i) = 0, v(i+1) = 1 and v(ihi+1:n) = 0; v(i+2:ihi) is stored on > exit in A(i+2:ihi,i), and tau in TAU(i). > > The contents of A are illustrated by the following example, with > n = 7, ilo = 2 and ihi = 6: > > on entry, on exit, > > ( a a a a a a a ) ( a a h h h h a ) > ( a a a a a a ) ( a h h h h a ) > ( a a a a a a ) ( h h h h h h ) > ( a a a a a a ) ( v2 h h h h h ) > ( a a a a a a ) ( v2 v3 h h h h ) > ( a a a a a a ) ( v2 v3 v4 h h h ) > ( a ) ( a ) > > where a denotes an element of the original matrix A, h denotes a > modified element of the upper Hessenberg matrix H, and vi denotes an > element of the vector defining H(i). > > This file is a slight modification of LAPACK-3.0's DGEHRD > subroutine incorporating improvements proposed by Quintana-Orti and > Van de Geijn (2006). (See DLAHR2.) > \endverbatim > ===================================================================== Subroutine */ int igraphdgehrd_(integer *n, integer *ilo, integer *ihi, doublereal *a, integer *lda, doublereal *tau, doublereal *work, integer *lwork, integer *info) { /* System generated locals */ integer a_dim1, a_offset, i__1, i__2, i__3, i__4; /* Local variables */ integer i__, j; doublereal t[4160] /* was [65][64] */; integer ib; doublereal ei; integer nb, nh, nx, iws; extern /* Subroutine */ int igraphdgemm_(char *, char *, integer *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *); integer nbmin, iinfo; extern /* Subroutine */ int igraphdtrmm_(char *, char *, char *, char *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *), igraphdaxpy_( integer *, doublereal *, doublereal *, integer *, doublereal *, integer *), igraphdgehd2_(integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *), igraphdlahr2_( integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *), igraphdlarfb_(char *, char *, char *, char *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, integer *), igraphxerbla_(char *, integer *, ftnlen); extern integer igraphilaenv_(integer *, char *, char *, integer *, integer *, integer *, integer *, ftnlen, ftnlen); integer ldwork, lwkopt; logical lquery; /* -- LAPACK computational routine (version 3.4.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2011 ===================================================================== Test the input parameters Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --tau; --work; /* Function Body */ *info = 0; /* Computing MIN */ i__1 = 64, i__2 = igraphilaenv_(&c__1, "DGEHRD", " ", n, ilo, ihi, &c_n1, ( ftnlen)6, (ftnlen)1); nb = min(i__1,i__2); lwkopt = *n * nb; work[1] = (doublereal) lwkopt; lquery = *lwork == -1; if (*n < 0) { *info = -1; } else if (*ilo < 1 || *ilo > max(1,*n)) { *info = -2; } else if (*ihi < min(*ilo,*n) || *ihi > *n) { *info = -3; } else if (*lda < max(1,*n)) { *info = -5; } else if (*lwork < max(1,*n) && ! lquery) { *info = -8; } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DGEHRD", &i__1, (ftnlen)6); return 0; } else if (lquery) { return 0; } /* Set elements 1:ILO-1 and IHI:N-1 of TAU to zero */ i__1 = *ilo - 1; for (i__ = 1; i__ <= i__1; ++i__) { tau[i__] = 0.; /* L10: */ } i__1 = *n - 1; for (i__ = max(1,*ihi); i__ <= i__1; ++i__) { tau[i__] = 0.; /* L20: */ } /* Quick return if possible */ nh = *ihi - *ilo + 1; if (nh <= 1) { work[1] = 1.; return 0; } /* Determine the block size Computing MIN */ i__1 = 64, i__2 = igraphilaenv_(&c__1, "DGEHRD", " ", n, ilo, ihi, &c_n1, ( ftnlen)6, (ftnlen)1); nb = min(i__1,i__2); nbmin = 2; iws = 1; if (nb > 1 && nb < nh) { /* Determine when to cross over from blocked to unblocked code (last block is always handled by unblocked code) Computing MAX */ i__1 = nb, i__2 = igraphilaenv_(&c__3, "DGEHRD", " ", n, ilo, ihi, &c_n1, ( ftnlen)6, (ftnlen)1); nx = max(i__1,i__2); if (nx < nh) { /* Determine if workspace is large enough for blocked code */ iws = *n * nb; if (*lwork < iws) { /* Not enough workspace to use optimal NB: determine the minimum value of NB, and reduce NB or force use of unblocked code Computing MAX */ i__1 = 2, i__2 = igraphilaenv_(&c__2, "DGEHRD", " ", n, ilo, ihi, & c_n1, (ftnlen)6, (ftnlen)1); nbmin = max(i__1,i__2); if (*lwork >= *n * nbmin) { nb = *lwork / *n; } else { nb = 1; } } } } ldwork = *n; if (nb < nbmin || nb >= nh) { /* Use unblocked code below */ i__ = *ilo; } else { /* Use blocked code */ i__1 = *ihi - 1 - nx; i__2 = nb; for (i__ = *ilo; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ += i__2) { /* Computing MIN */ i__3 = nb, i__4 = *ihi - i__; ib = min(i__3,i__4); /* Reduce columns i:i+ib-1 to Hessenberg form, returning the matrices V and T of the block reflector H = I - V*T*V**T which performs the reduction, and also the matrix Y = A*V*T */ igraphdlahr2_(ihi, &i__, &ib, &a[i__ * a_dim1 + 1], lda, &tau[i__], t, & c__65, &work[1], &ldwork); /* Apply the block reflector H to A(1:ihi,i+ib:ihi) from the right, computing A := A - Y * V**T. V(i+ib,ib-1) must be set to 1 */ ei = a[i__ + ib + (i__ + ib - 1) * a_dim1]; a[i__ + ib + (i__ + ib - 1) * a_dim1] = 1.; i__3 = *ihi - i__ - ib + 1; igraphdgemm_("No transpose", "Transpose", ihi, &i__3, &ib, &c_b25, & work[1], &ldwork, &a[i__ + ib + i__ * a_dim1], lda, & c_b26, &a[(i__ + ib) * a_dim1 + 1], lda); a[i__ + ib + (i__ + ib - 1) * a_dim1] = ei; /* Apply the block reflector H to A(1:i,i+1:i+ib-1) from the right */ i__3 = ib - 1; igraphdtrmm_("Right", "Lower", "Transpose", "Unit", &i__, &i__3, &c_b26, &a[i__ + 1 + i__ * a_dim1], lda, &work[1], &ldwork); i__3 = ib - 2; for (j = 0; j <= i__3; ++j) { igraphdaxpy_(&i__, &c_b25, &work[ldwork * j + 1], &c__1, &a[(i__ + j + 1) * a_dim1 + 1], &c__1); /* L30: */ } /* Apply the block reflector H to A(i+1:ihi,i+ib:n) from the left */ i__3 = *ihi - i__; i__4 = *n - i__ - ib + 1; igraphdlarfb_("Left", "Transpose", "Forward", "Columnwise", &i__3, & i__4, &ib, &a[i__ + 1 + i__ * a_dim1], lda, t, &c__65, &a[ i__ + 1 + (i__ + ib) * a_dim1], lda, &work[1], &ldwork); /* L40: */ } } /* Use unblocked code to reduce the rest of the matrix */ igraphdgehd2_(n, &i__, ihi, &a[a_offset], lda, &tau[1], &work[1], &iinfo); work[1] = (doublereal) iws; return 0; /* End of DGEHRD */ } /* igraphdgehrd_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlasy2.c0000644000076500000240000004074613524616145024215 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__4 = 4; static integer c__1 = 1; static integer c__16 = 16; static integer c__0 = 0; /* > \brief \b DLASY2 solves the Sylvester matrix equation where the matrices are of order 1 or 2. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLASY2 + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLASY2( LTRANL, LTRANR, ISGN, N1, N2, TL, LDTL, TR, LDTR, B, LDB, SCALE, X, LDX, XNORM, INFO ) LOGICAL LTRANL, LTRANR INTEGER INFO, ISGN, LDB, LDTL, LDTR, LDX, N1, N2 DOUBLE PRECISION SCALE, XNORM DOUBLE PRECISION B( LDB, * ), TL( LDTL, * ), TR( LDTR, * ), $ X( LDX, * ) > \par Purpose: ============= > > \verbatim > > DLASY2 solves for the N1 by N2 matrix X, 1 <= N1,N2 <= 2, in > > op(TL)*X + ISGN*X*op(TR) = SCALE*B, > > where TL is N1 by N1, TR is N2 by N2, B is N1 by N2, and ISGN = 1 or > -1. op(T) = T or T**T, where T**T denotes the transpose of T. > \endverbatim Arguments: ========== > \param[in] LTRANL > \verbatim > LTRANL is LOGICAL > On entry, LTRANL specifies the op(TL): > = .FALSE., op(TL) = TL, > = .TRUE., op(TL) = TL**T. > \endverbatim > > \param[in] LTRANR > \verbatim > LTRANR is LOGICAL > On entry, LTRANR specifies the op(TR): > = .FALSE., op(TR) = TR, > = .TRUE., op(TR) = TR**T. > \endverbatim > > \param[in] ISGN > \verbatim > ISGN is INTEGER > On entry, ISGN specifies the sign of the equation > as described before. ISGN may only be 1 or -1. > \endverbatim > > \param[in] N1 > \verbatim > N1 is INTEGER > On entry, N1 specifies the order of matrix TL. > N1 may only be 0, 1 or 2. > \endverbatim > > \param[in] N2 > \verbatim > N2 is INTEGER > On entry, N2 specifies the order of matrix TR. > N2 may only be 0, 1 or 2. > \endverbatim > > \param[in] TL > \verbatim > TL is DOUBLE PRECISION array, dimension (LDTL,2) > On entry, TL contains an N1 by N1 matrix. > \endverbatim > > \param[in] LDTL > \verbatim > LDTL is INTEGER > The leading dimension of the matrix TL. LDTL >= max(1,N1). > \endverbatim > > \param[in] TR > \verbatim > TR is DOUBLE PRECISION array, dimension (LDTR,2) > On entry, TR contains an N2 by N2 matrix. > \endverbatim > > \param[in] LDTR > \verbatim > LDTR is INTEGER > The leading dimension of the matrix TR. LDTR >= max(1,N2). > \endverbatim > > \param[in] B > \verbatim > B is DOUBLE PRECISION array, dimension (LDB,2) > On entry, the N1 by N2 matrix B contains the right-hand > side of the equation. > \endverbatim > > \param[in] LDB > \verbatim > LDB is INTEGER > The leading dimension of the matrix B. LDB >= max(1,N1). > \endverbatim > > \param[out] SCALE > \verbatim > SCALE is DOUBLE PRECISION > On exit, SCALE contains the scale factor. SCALE is chosen > less than or equal to 1 to prevent the solution overflowing. > \endverbatim > > \param[out] X > \verbatim > X is DOUBLE PRECISION array, dimension (LDX,2) > On exit, X contains the N1 by N2 solution. > \endverbatim > > \param[in] LDX > \verbatim > LDX is INTEGER > The leading dimension of the matrix X. LDX >= max(1,N1). > \endverbatim > > \param[out] XNORM > \verbatim > XNORM is DOUBLE PRECISION > On exit, XNORM is the infinity-norm of the solution. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > On exit, INFO is set to > 0: successful exit. > 1: TL and TR have too close eigenvalues, so TL or > TR is perturbed to get a nonsingular equation. > NOTE: In the interests of speed, this routine does not > check the inputs for errors. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleSYauxiliary ===================================================================== Subroutine */ int igraphdlasy2_(logical *ltranl, logical *ltranr, integer *isgn, integer *n1, integer *n2, doublereal *tl, integer *ldtl, doublereal * tr, integer *ldtr, doublereal *b, integer *ldb, doublereal *scale, doublereal *x, integer *ldx, doublereal *xnorm, integer *info) { /* Initialized data */ static integer locu12[4] = { 3,4,1,2 }; static integer locl21[4] = { 2,1,4,3 }; static integer locu22[4] = { 4,3,2,1 }; static logical xswpiv[4] = { FALSE_,FALSE_,TRUE_,TRUE_ }; static logical bswpiv[4] = { FALSE_,TRUE_,FALSE_,TRUE_ }; /* System generated locals */ integer b_dim1, b_offset, tl_dim1, tl_offset, tr_dim1, tr_offset, x_dim1, x_offset; doublereal d__1, d__2, d__3, d__4, d__5, d__6, d__7, d__8; /* Local variables */ integer i__, j, k; doublereal x2[2], l21, u11, u12; integer ip, jp; doublereal u22, t16[16] /* was [4][4] */, gam, bet, eps, sgn, tmp[4], tau1, btmp[4], smin; integer ipiv; doublereal temp; integer jpiv[4]; doublereal xmax; integer ipsv, jpsv; logical bswap; extern /* Subroutine */ int igraphdcopy_(integer *, doublereal *, integer *, doublereal *, integer *), igraphdswap_(integer *, doublereal *, integer *, doublereal *, integer *); logical xswap; extern doublereal igraphdlamch_(char *); extern integer igraphidamax_(integer *, doublereal *, integer *); doublereal smlnum; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ tl_dim1 = *ldtl; tl_offset = 1 + tl_dim1; tl -= tl_offset; tr_dim1 = *ldtr; tr_offset = 1 + tr_dim1; tr -= tr_offset; b_dim1 = *ldb; b_offset = 1 + b_dim1; b -= b_offset; x_dim1 = *ldx; x_offset = 1 + x_dim1; x -= x_offset; /* Function Body Do not check the input parameters for errors */ *info = 0; /* Quick return if possible */ if (*n1 == 0 || *n2 == 0) { return 0; } /* Set constants to control overflow */ eps = igraphdlamch_("P"); smlnum = igraphdlamch_("S") / eps; sgn = (doublereal) (*isgn); k = *n1 + *n1 + *n2 - 2; switch (k) { case 1: goto L10; case 2: goto L20; case 3: goto L30; case 4: goto L50; } /* 1 by 1: TL11*X + SGN*X*TR11 = B11 */ L10: tau1 = tl[tl_dim1 + 1] + sgn * tr[tr_dim1 + 1]; bet = abs(tau1); if (bet <= smlnum) { tau1 = smlnum; bet = smlnum; *info = 1; } *scale = 1.; gam = (d__1 = b[b_dim1 + 1], abs(d__1)); if (smlnum * gam > bet) { *scale = 1. / gam; } x[x_dim1 + 1] = b[b_dim1 + 1] * *scale / tau1; *xnorm = (d__1 = x[x_dim1 + 1], abs(d__1)); return 0; /* 1 by 2: TL11*[X11 X12] + ISGN*[X11 X12]*op[TR11 TR12] = [B11 B12] [TR21 TR22] */ L20: /* Computing MAX Computing MAX */ d__7 = (d__1 = tl[tl_dim1 + 1], abs(d__1)), d__8 = (d__2 = tr[tr_dim1 + 1] , abs(d__2)), d__7 = max(d__7,d__8), d__8 = (d__3 = tr[(tr_dim1 << 1) + 1], abs(d__3)), d__7 = max(d__7,d__8), d__8 = (d__4 = tr[ tr_dim1 + 2], abs(d__4)), d__7 = max(d__7,d__8), d__8 = (d__5 = tr[(tr_dim1 << 1) + 2], abs(d__5)); d__6 = eps * max(d__7,d__8); smin = max(d__6,smlnum); tmp[0] = tl[tl_dim1 + 1] + sgn * tr[tr_dim1 + 1]; tmp[3] = tl[tl_dim1 + 1] + sgn * tr[(tr_dim1 << 1) + 2]; if (*ltranr) { tmp[1] = sgn * tr[tr_dim1 + 2]; tmp[2] = sgn * tr[(tr_dim1 << 1) + 1]; } else { tmp[1] = sgn * tr[(tr_dim1 << 1) + 1]; tmp[2] = sgn * tr[tr_dim1 + 2]; } btmp[0] = b[b_dim1 + 1]; btmp[1] = b[(b_dim1 << 1) + 1]; goto L40; /* 2 by 1: op[TL11 TL12]*[X11] + ISGN* [X11]*TR11 = [B11] [TL21 TL22] [X21] [X21] [B21] */ L30: /* Computing MAX Computing MAX */ d__7 = (d__1 = tr[tr_dim1 + 1], abs(d__1)), d__8 = (d__2 = tl[tl_dim1 + 1] , abs(d__2)), d__7 = max(d__7,d__8), d__8 = (d__3 = tl[(tl_dim1 << 1) + 1], abs(d__3)), d__7 = max(d__7,d__8), d__8 = (d__4 = tl[ tl_dim1 + 2], abs(d__4)), d__7 = max(d__7,d__8), d__8 = (d__5 = tl[(tl_dim1 << 1) + 2], abs(d__5)); d__6 = eps * max(d__7,d__8); smin = max(d__6,smlnum); tmp[0] = tl[tl_dim1 + 1] + sgn * tr[tr_dim1 + 1]; tmp[3] = tl[(tl_dim1 << 1) + 2] + sgn * tr[tr_dim1 + 1]; if (*ltranl) { tmp[1] = tl[(tl_dim1 << 1) + 1]; tmp[2] = tl[tl_dim1 + 2]; } else { tmp[1] = tl[tl_dim1 + 2]; tmp[2] = tl[(tl_dim1 << 1) + 1]; } btmp[0] = b[b_dim1 + 1]; btmp[1] = b[b_dim1 + 2]; L40: /* Solve 2 by 2 system using complete pivoting. Set pivots less than SMIN to SMIN. */ ipiv = igraphidamax_(&c__4, tmp, &c__1); u11 = tmp[ipiv - 1]; if (abs(u11) <= smin) { *info = 1; u11 = smin; } u12 = tmp[locu12[ipiv - 1] - 1]; l21 = tmp[locl21[ipiv - 1] - 1] / u11; u22 = tmp[locu22[ipiv - 1] - 1] - u12 * l21; xswap = xswpiv[ipiv - 1]; bswap = bswpiv[ipiv - 1]; if (abs(u22) <= smin) { *info = 1; u22 = smin; } if (bswap) { temp = btmp[1]; btmp[1] = btmp[0] - l21 * temp; btmp[0] = temp; } else { btmp[1] -= l21 * btmp[0]; } *scale = 1.; if (smlnum * 2. * abs(btmp[1]) > abs(u22) || smlnum * 2. * abs(btmp[0]) > abs(u11)) { /* Computing MAX */ d__1 = abs(btmp[0]), d__2 = abs(btmp[1]); *scale = .5 / max(d__1,d__2); btmp[0] *= *scale; btmp[1] *= *scale; } x2[1] = btmp[1] / u22; x2[0] = btmp[0] / u11 - u12 / u11 * x2[1]; if (xswap) { temp = x2[1]; x2[1] = x2[0]; x2[0] = temp; } x[x_dim1 + 1] = x2[0]; if (*n1 == 1) { x[(x_dim1 << 1) + 1] = x2[1]; *xnorm = (d__1 = x[x_dim1 + 1], abs(d__1)) + (d__2 = x[(x_dim1 << 1) + 1], abs(d__2)); } else { x[x_dim1 + 2] = x2[1]; /* Computing MAX */ d__3 = (d__1 = x[x_dim1 + 1], abs(d__1)), d__4 = (d__2 = x[x_dim1 + 2] , abs(d__2)); *xnorm = max(d__3,d__4); } return 0; /* 2 by 2: op[TL11 TL12]*[X11 X12] +ISGN* [X11 X12]*op[TR11 TR12] = [B11 B12] [TL21 TL22] [X21 X22] [X21 X22] [TR21 TR22] [B21 B22] Solve equivalent 4 by 4 system using complete pivoting. Set pivots less than SMIN to SMIN. */ L50: /* Computing MAX */ d__5 = (d__1 = tr[tr_dim1 + 1], abs(d__1)), d__6 = (d__2 = tr[(tr_dim1 << 1) + 1], abs(d__2)), d__5 = max(d__5,d__6), d__6 = (d__3 = tr[ tr_dim1 + 2], abs(d__3)), d__5 = max(d__5,d__6), d__6 = (d__4 = tr[(tr_dim1 << 1) + 2], abs(d__4)); smin = max(d__5,d__6); /* Computing MAX */ d__5 = smin, d__6 = (d__1 = tl[tl_dim1 + 1], abs(d__1)), d__5 = max(d__5, d__6), d__6 = (d__2 = tl[(tl_dim1 << 1) + 1], abs(d__2)), d__5 = max(d__5,d__6), d__6 = (d__3 = tl[tl_dim1 + 2], abs(d__3)), d__5 = max(d__5,d__6), d__6 = (d__4 = tl[(tl_dim1 << 1) + 2], abs(d__4)) ; smin = max(d__5,d__6); /* Computing MAX */ d__1 = eps * smin; smin = max(d__1,smlnum); btmp[0] = 0.; igraphdcopy_(&c__16, btmp, &c__0, t16, &c__1); t16[0] = tl[tl_dim1 + 1] + sgn * tr[tr_dim1 + 1]; t16[5] = tl[(tl_dim1 << 1) + 2] + sgn * tr[tr_dim1 + 1]; t16[10] = tl[tl_dim1 + 1] + sgn * tr[(tr_dim1 << 1) + 2]; t16[15] = tl[(tl_dim1 << 1) + 2] + sgn * tr[(tr_dim1 << 1) + 2]; if (*ltranl) { t16[4] = tl[tl_dim1 + 2]; t16[1] = tl[(tl_dim1 << 1) + 1]; t16[14] = tl[tl_dim1 + 2]; t16[11] = tl[(tl_dim1 << 1) + 1]; } else { t16[4] = tl[(tl_dim1 << 1) + 1]; t16[1] = tl[tl_dim1 + 2]; t16[14] = tl[(tl_dim1 << 1) + 1]; t16[11] = tl[tl_dim1 + 2]; } if (*ltranr) { t16[8] = sgn * tr[(tr_dim1 << 1) + 1]; t16[13] = sgn * tr[(tr_dim1 << 1) + 1]; t16[2] = sgn * tr[tr_dim1 + 2]; t16[7] = sgn * tr[tr_dim1 + 2]; } else { t16[8] = sgn * tr[tr_dim1 + 2]; t16[13] = sgn * tr[tr_dim1 + 2]; t16[2] = sgn * tr[(tr_dim1 << 1) + 1]; t16[7] = sgn * tr[(tr_dim1 << 1) + 1]; } btmp[0] = b[b_dim1 + 1]; btmp[1] = b[b_dim1 + 2]; btmp[2] = b[(b_dim1 << 1) + 1]; btmp[3] = b[(b_dim1 << 1) + 2]; /* Perform elimination */ for (i__ = 1; i__ <= 3; ++i__) { xmax = 0.; for (ip = i__; ip <= 4; ++ip) { for (jp = i__; jp <= 4; ++jp) { if ((d__1 = t16[ip + (jp << 2) - 5], abs(d__1)) >= xmax) { xmax = (d__1 = t16[ip + (jp << 2) - 5], abs(d__1)); ipsv = ip; jpsv = jp; } /* L60: */ } /* L70: */ } if (ipsv != i__) { igraphdswap_(&c__4, &t16[ipsv - 1], &c__4, &t16[i__ - 1], &c__4); temp = btmp[i__ - 1]; btmp[i__ - 1] = btmp[ipsv - 1]; btmp[ipsv - 1] = temp; } if (jpsv != i__) { igraphdswap_(&c__4, &t16[(jpsv << 2) - 4], &c__1, &t16[(i__ << 2) - 4], &c__1); } jpiv[i__ - 1] = jpsv; if ((d__1 = t16[i__ + (i__ << 2) - 5], abs(d__1)) < smin) { *info = 1; t16[i__ + (i__ << 2) - 5] = smin; } for (j = i__ + 1; j <= 4; ++j) { t16[j + (i__ << 2) - 5] /= t16[i__ + (i__ << 2) - 5]; btmp[j - 1] -= t16[j + (i__ << 2) - 5] * btmp[i__ - 1]; for (k = i__ + 1; k <= 4; ++k) { t16[j + (k << 2) - 5] -= t16[j + (i__ << 2) - 5] * t16[i__ + ( k << 2) - 5]; /* L80: */ } /* L90: */ } /* L100: */ } if (abs(t16[15]) < smin) { t16[15] = smin; } *scale = 1.; if (smlnum * 8. * abs(btmp[0]) > abs(t16[0]) || smlnum * 8. * abs(btmp[1]) > abs(t16[5]) || smlnum * 8. * abs(btmp[2]) > abs(t16[10]) || smlnum * 8. * abs(btmp[3]) > abs(t16[15])) { /* Computing MAX */ d__1 = abs(btmp[0]), d__2 = abs(btmp[1]), d__1 = max(d__1,d__2), d__2 = abs(btmp[2]), d__1 = max(d__1,d__2), d__2 = abs(btmp[3]); *scale = .125 / max(d__1,d__2); btmp[0] *= *scale; btmp[1] *= *scale; btmp[2] *= *scale; btmp[3] *= *scale; } for (i__ = 1; i__ <= 4; ++i__) { k = 5 - i__; temp = 1. / t16[k + (k << 2) - 5]; tmp[k - 1] = btmp[k - 1] * temp; for (j = k + 1; j <= 4; ++j) { tmp[k - 1] -= temp * t16[k + (j << 2) - 5] * tmp[j - 1]; /* L110: */ } /* L120: */ } for (i__ = 1; i__ <= 3; ++i__) { if (jpiv[4 - i__ - 1] != 4 - i__) { temp = tmp[4 - i__ - 1]; tmp[4 - i__ - 1] = tmp[jpiv[4 - i__ - 1] - 1]; tmp[jpiv[4 - i__ - 1] - 1] = temp; } /* L130: */ } x[x_dim1 + 1] = tmp[0]; x[x_dim1 + 2] = tmp[1]; x[(x_dim1 << 1) + 1] = tmp[2]; x[(x_dim1 << 1) + 2] = tmp[3]; /* Computing MAX */ d__1 = abs(tmp[0]) + abs(tmp[2]), d__2 = abs(tmp[1]) + abs(tmp[3]); *xnorm = max(d__1,d__2); return 0; /* End of DLASY2 */ } /* igraphdlasy2_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlasq4.c0000644000076500000240000002614113524616145024200 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLASQ4 computes an approximation to the smallest eigenvalue using values of d from the previous transform. Used by sbdsqr. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLASQ4 + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLASQ4( I0, N0, Z, PP, N0IN, DMIN, DMIN1, DMIN2, DN, DN1, DN2, TAU, TTYPE, G ) INTEGER I0, N0, N0IN, PP, TTYPE DOUBLE PRECISION DMIN, DMIN1, DMIN2, DN, DN1, DN2, G, TAU DOUBLE PRECISION Z( * ) > \par Purpose: ============= > > \verbatim > > DLASQ4 computes an approximation TAU to the smallest eigenvalue > using values of d from the previous transform. > \endverbatim Arguments: ========== > \param[in] I0 > \verbatim > I0 is INTEGER > First index. > \endverbatim > > \param[in] N0 > \verbatim > N0 is INTEGER > Last index. > \endverbatim > > \param[in] Z > \verbatim > Z is DOUBLE PRECISION array, dimension ( 4*N ) > Z holds the qd array. > \endverbatim > > \param[in] PP > \verbatim > PP is INTEGER > PP=0 for ping, PP=1 for pong. > \endverbatim > > \param[in] N0IN > \verbatim > N0IN is INTEGER > The value of N0 at start of EIGTEST. > \endverbatim > > \param[in] DMIN > \verbatim > DMIN is DOUBLE PRECISION > Minimum value of d. > \endverbatim > > \param[in] DMIN1 > \verbatim > DMIN1 is DOUBLE PRECISION > Minimum value of d, excluding D( N0 ). > \endverbatim > > \param[in] DMIN2 > \verbatim > DMIN2 is DOUBLE PRECISION > Minimum value of d, excluding D( N0 ) and D( N0-1 ). > \endverbatim > > \param[in] DN > \verbatim > DN is DOUBLE PRECISION > d(N) > \endverbatim > > \param[in] DN1 > \verbatim > DN1 is DOUBLE PRECISION > d(N-1) > \endverbatim > > \param[in] DN2 > \verbatim > DN2 is DOUBLE PRECISION > d(N-2) > \endverbatim > > \param[out] TAU > \verbatim > TAU is DOUBLE PRECISION > This is the shift. > \endverbatim > > \param[out] TTYPE > \verbatim > TTYPE is INTEGER > Shift type. > \endverbatim > > \param[in,out] G > \verbatim > G is REAL > G is passed as an argument in order to save its value between > calls to DLASQ4. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERcomputational > \par Further Details: ===================== > > \verbatim > > CNST1 = 9/16 > \endverbatim > ===================================================================== Subroutine */ int igraphdlasq4_(integer *i0, integer *n0, doublereal *z__, integer *pp, integer *n0in, doublereal *dmin__, doublereal *dmin1, doublereal *dmin2, doublereal *dn, doublereal *dn1, doublereal *dn2, doublereal *tau, integer *ttype, doublereal *g) { /* System generated locals */ integer i__1; doublereal d__1, d__2; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ doublereal s = 0., a2, b1, b2; integer i4, nn, np; doublereal gam, gap1, gap2; /* -- LAPACK computational routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== A negative DMIN forces the shift to take that absolute value TTYPE records the type of shift. Parameter adjustments */ --z__; /* Function Body */ if (*dmin__ <= 0.) { *tau = -(*dmin__); *ttype = -1; return 0; } nn = (*n0 << 2) + *pp; if (*n0in == *n0) { /* No eigenvalues deflated. */ if (*dmin__ == *dn || *dmin__ == *dn1) { b1 = sqrt(z__[nn - 3]) * sqrt(z__[nn - 5]); b2 = sqrt(z__[nn - 7]) * sqrt(z__[nn - 9]); a2 = z__[nn - 7] + z__[nn - 5]; /* Cases 2 and 3. */ if (*dmin__ == *dn && *dmin1 == *dn1) { gap2 = *dmin2 - a2 - *dmin2 * .25; if (gap2 > 0. && gap2 > b2) { gap1 = a2 - *dn - b2 / gap2 * b2; } else { gap1 = a2 - *dn - (b1 + b2); } if (gap1 > 0. && gap1 > b1) { /* Computing MAX */ d__1 = *dn - b1 / gap1 * b1, d__2 = *dmin__ * .5; s = max(d__1,d__2); *ttype = -2; } else { s = 0.; if (*dn > b1) { s = *dn - b1; } if (a2 > b1 + b2) { /* Computing MIN */ d__1 = s, d__2 = a2 - (b1 + b2); s = min(d__1,d__2); } /* Computing MAX */ d__1 = s, d__2 = *dmin__ * .333; s = max(d__1,d__2); *ttype = -3; } } else { /* Case 4. */ *ttype = -4; s = *dmin__ * .25; if (*dmin__ == *dn) { gam = *dn; a2 = 0.; if (z__[nn - 5] > z__[nn - 7]) { return 0; } b2 = z__[nn - 5] / z__[nn - 7]; np = nn - 9; } else { np = nn - (*pp << 1); b2 = z__[np - 2]; gam = *dn1; if (z__[np - 4] > z__[np - 2]) { return 0; } a2 = z__[np - 4] / z__[np - 2]; if (z__[nn - 9] > z__[nn - 11]) { return 0; } b2 = z__[nn - 9] / z__[nn - 11]; np = nn - 13; } /* Approximate contribution to norm squared from I < NN-1. */ a2 += b2; i__1 = (*i0 << 2) - 1 + *pp; for (i4 = np; i4 >= i__1; i4 += -4) { if (b2 == 0.) { goto L20; } b1 = b2; if (z__[i4] > z__[i4 - 2]) { return 0; } b2 *= z__[i4] / z__[i4 - 2]; a2 += b2; if (max(b2,b1) * 100. < a2 || .563 < a2) { goto L20; } /* L10: */ } L20: a2 *= 1.05; /* Rayleigh quotient residual bound. */ if (a2 < .563) { s = gam * (1. - sqrt(a2)) / (a2 + 1.); } } } else if (*dmin__ == *dn2) { /* Case 5. */ *ttype = -5; s = *dmin__ * .25; /* Compute contribution to norm squared from I > NN-2. */ np = nn - (*pp << 1); b1 = z__[np - 2]; b2 = z__[np - 6]; gam = *dn2; if (z__[np - 8] > b2 || z__[np - 4] > b1) { return 0; } a2 = z__[np - 8] / b2 * (z__[np - 4] / b1 + 1.); /* Approximate contribution to norm squared from I < NN-2. */ if (*n0 - *i0 > 2) { b2 = z__[nn - 13] / z__[nn - 15]; a2 += b2; i__1 = (*i0 << 2) - 1 + *pp; for (i4 = nn - 17; i4 >= i__1; i4 += -4) { if (b2 == 0.) { goto L40; } b1 = b2; if (z__[i4] > z__[i4 - 2]) { return 0; } b2 *= z__[i4] / z__[i4 - 2]; a2 += b2; if (max(b2,b1) * 100. < a2 || .563 < a2) { goto L40; } /* L30: */ } L40: a2 *= 1.05; } if (a2 < .563) { s = gam * (1. - sqrt(a2)) / (a2 + 1.); } } else { /* Case 6, no information to guide us. */ if (*ttype == -6) { *g += (1. - *g) * .333; } else if (*ttype == -18) { *g = .083250000000000005; } else { *g = .25; } s = *g * *dmin__; *ttype = -6; } } else if (*n0in == *n0 + 1) { /* One eigenvalue just deflated. Use DMIN1, DN1 for DMIN and DN. */ if (*dmin1 == *dn1 && *dmin2 == *dn2) { /* Cases 7 and 8. */ *ttype = -7; s = *dmin1 * .333; if (z__[nn - 5] > z__[nn - 7]) { return 0; } b1 = z__[nn - 5] / z__[nn - 7]; b2 = b1; if (b2 == 0.) { goto L60; } i__1 = (*i0 << 2) - 1 + *pp; for (i4 = (*n0 << 2) - 9 + *pp; i4 >= i__1; i4 += -4) { a2 = b1; if (z__[i4] > z__[i4 - 2]) { return 0; } b1 *= z__[i4] / z__[i4 - 2]; b2 += b1; if (max(b1,a2) * 100. < b2) { goto L60; } /* L50: */ } L60: b2 = sqrt(b2 * 1.05); /* Computing 2nd power */ d__1 = b2; a2 = *dmin1 / (d__1 * d__1 + 1.); gap2 = *dmin2 * .5 - a2; if (gap2 > 0. && gap2 > b2 * a2) { /* Computing MAX */ d__1 = s, d__2 = a2 * (1. - a2 * 1.01 * (b2 / gap2) * b2); s = max(d__1,d__2); } else { /* Computing MAX */ d__1 = s, d__2 = a2 * (1. - b2 * 1.01); s = max(d__1,d__2); *ttype = -8; } } else { /* Case 9. */ s = *dmin1 * .25; if (*dmin1 == *dn1) { s = *dmin1 * .5; } *ttype = -9; } } else if (*n0in == *n0 + 2) { /* Two eigenvalues deflated. Use DMIN2, DN2 for DMIN and DN. Cases 10 and 11. */ if (*dmin2 == *dn2 && z__[nn - 5] * 2. < z__[nn - 7]) { *ttype = -10; s = *dmin2 * .333; if (z__[nn - 5] > z__[nn - 7]) { return 0; } b1 = z__[nn - 5] / z__[nn - 7]; b2 = b1; if (b2 == 0.) { goto L80; } i__1 = (*i0 << 2) - 1 + *pp; for (i4 = (*n0 << 2) - 9 + *pp; i4 >= i__1; i4 += -4) { if (z__[i4] > z__[i4 - 2]) { return 0; } b1 *= z__[i4] / z__[i4 - 2]; b2 += b1; if (b1 * 100. < b2) { goto L80; } /* L70: */ } L80: b2 = sqrt(b2 * 1.05); /* Computing 2nd power */ d__1 = b2; a2 = *dmin2 / (d__1 * d__1 + 1.); gap2 = z__[nn - 7] + z__[nn - 9] - sqrt(z__[nn - 11]) * sqrt(z__[ nn - 9]) - a2; if (gap2 > 0. && gap2 > b2 * a2) { /* Computing MAX */ d__1 = s, d__2 = a2 * (1. - a2 * 1.01 * (b2 / gap2) * b2); s = max(d__1,d__2); } else { /* Computing MAX */ d__1 = s, d__2 = a2 * (1. - b2 * 1.01); s = max(d__1,d__2); } } else { s = *dmin2 * .25; *ttype = -11; } } else if (*n0in > *n0 + 2) { /* Case 12, more than two eigenvalues deflated. No information. */ s = 0.; *ttype = -12; } *tau = s; return 0; /* End of DLASQ4 */ } /* igraphdlasq4_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlarra.c0000644000076500000240000001502713524616145024256 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLARRA computes the splitting points with the specified threshold. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLARRA + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLARRA( N, D, E, E2, SPLTOL, TNRM, NSPLIT, ISPLIT, INFO ) INTEGER INFO, N, NSPLIT DOUBLE PRECISION SPLTOL, TNRM INTEGER ISPLIT( * ) DOUBLE PRECISION D( * ), E( * ), E2( * ) > \par Purpose: ============= > > \verbatim > > Compute the splitting points with threshold SPLTOL. > DLARRA sets any "small" off-diagonal elements to zero. > \endverbatim Arguments: ========== > \param[in] N > \verbatim > N is INTEGER > The order of the matrix. N > 0. > \endverbatim > > \param[in] D > \verbatim > D is DOUBLE PRECISION array, dimension (N) > On entry, the N diagonal elements of the tridiagonal > matrix T. > \endverbatim > > \param[in,out] E > \verbatim > E is DOUBLE PRECISION array, dimension (N) > On entry, the first (N-1) entries contain the subdiagonal > elements of the tridiagonal matrix T; E(N) need not be set. > On exit, the entries E( ISPLIT( I ) ), 1 <= I <= NSPLIT, > are set to zero, the other entries of E are untouched. > \endverbatim > > \param[in,out] E2 > \verbatim > E2 is DOUBLE PRECISION array, dimension (N) > On entry, the first (N-1) entries contain the SQUARES of the > subdiagonal elements of the tridiagonal matrix T; > E2(N) need not be set. > On exit, the entries E2( ISPLIT( I ) ), > 1 <= I <= NSPLIT, have been set to zero > \endverbatim > > \param[in] SPLTOL > \verbatim > SPLTOL is DOUBLE PRECISION > The threshold for splitting. Two criteria can be used: > SPLTOL<0 : criterion based on absolute off-diagonal value > SPLTOL>0 : criterion that preserves relative accuracy > \endverbatim > > \param[in] TNRM > \verbatim > TNRM is DOUBLE PRECISION > The norm of the matrix. > \endverbatim > > \param[out] NSPLIT > \verbatim > NSPLIT is INTEGER > The number of blocks T splits into. 1 <= NSPLIT <= N. > \endverbatim > > \param[out] ISPLIT > \verbatim > ISPLIT is INTEGER array, dimension (N) > The splitting points, at which T breaks up into blocks. > The first block consists of rows/columns 1 to ISPLIT(1), > the second of rows/columns ISPLIT(1)+1 through ISPLIT(2), > etc., and the NSPLIT-th consists of rows/columns > ISPLIT(NSPLIT-1)+1 through ISPLIT(NSPLIT)=N. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERauxiliary > \par Contributors: ================== > > Beresford Parlett, University of California, Berkeley, USA \n > Jim Demmel, University of California, Berkeley, USA \n > Inderjit Dhillon, University of Texas, Austin, USA \n > Osni Marques, LBNL/NERSC, USA \n > Christof Voemel, University of California, Berkeley, USA ===================================================================== Subroutine */ int igraphdlarra_(integer *n, doublereal *d__, doublereal *e, doublereal *e2, doublereal *spltol, doublereal *tnrm, integer *nsplit, integer *isplit, integer *info) { /* System generated locals */ integer i__1; doublereal d__1, d__2; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ integer i__; doublereal tmp1, eabs; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ --isplit; --e2; --e; --d__; /* Function Body */ *info = 0; /* Compute splitting points */ *nsplit = 1; if (*spltol < 0.) { /* Criterion based on absolute off-diagonal value */ tmp1 = abs(*spltol) * *tnrm; i__1 = *n - 1; for (i__ = 1; i__ <= i__1; ++i__) { eabs = (d__1 = e[i__], abs(d__1)); if (eabs <= tmp1) { e[i__] = 0.; e2[i__] = 0.; isplit[*nsplit] = i__; ++(*nsplit); } /* L9: */ } } else { /* Criterion that guarantees relative accuracy */ i__1 = *n - 1; for (i__ = 1; i__ <= i__1; ++i__) { eabs = (d__1 = e[i__], abs(d__1)); if (eabs <= *spltol * sqrt((d__1 = d__[i__], abs(d__1))) * sqrt(( d__2 = d__[i__ + 1], abs(d__2)))) { e[i__] = 0.; e2[i__] = 0.; isplit[*nsplit] = i__; ++(*nsplit); } /* L10: */ } } isplit[*nsplit] = *n; return 0; /* End of DLARRA */ } /* igraphdlarra_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlaruv.c0000644000076500000240000002034113524616145024301 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLARUV returns a vector of n random real numbers from a uniform distribution. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLARUV + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLARUV( ISEED, N, X ) INTEGER N INTEGER ISEED( 4 ) DOUBLE PRECISION X( N ) > \par Purpose: ============= > > \verbatim > > DLARUV returns a vector of n random real numbers from a uniform (0,1) > distribution (n <= 128). > > This is an auxiliary routine called by DLARNV and ZLARNV. > \endverbatim Arguments: ========== > \param[in,out] ISEED > \verbatim > ISEED is INTEGER array, dimension (4) > On entry, the seed of the random number generator; the array > elements must be between 0 and 4095, and ISEED(4) must be > odd. > On exit, the seed is updated. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The number of random numbers to be generated. N <= 128. > \endverbatim > > \param[out] X > \verbatim > X is DOUBLE PRECISION array, dimension (N) > The generated random numbers. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERauxiliary > \par Further Details: ===================== > > \verbatim > > This routine uses a multiplicative congruential method with modulus > 2**48 and multiplier 33952834046453 (see G.S.Fishman, > 'Multiplicative congruential random number generators with modulus > 2**b: an exhaustive analysis for b = 32 and a partial analysis for > b = 48', Math. Comp. 189, pp 331-344, 1990). > > 48-bit integers are stored in 4 integer array elements with 12 bits > per element. Hence the routine is portable across machines with > integers of 32 bits or more. > \endverbatim > ===================================================================== Subroutine */ int igraphdlaruv_(integer *iseed, integer *n, doublereal *x) { /* Initialized data */ static integer mm[512] /* was [128][4] */ = { 494,2637,255,2008,1253, 3344,4084,1739,3143,3468,688,1657,1238,3166,1292,3422,1270,2016, 154,2862,697,1706,491,931,1444,444,3577,3944,2184,1661,3482,657, 3023,3618,1267,1828,164,3798,3087,2400,2870,3876,1905,1593,1797, 1234,3460,328,2861,1950,617,2070,3331,769,1558,2412,2800,189,287, 2045,1227,2838,209,2770,3654,3993,192,2253,3491,2889,2857,2094, 1818,688,1407,634,3231,815,3524,1914,516,164,303,2144,3480,119, 3357,837,2826,2332,2089,3780,1700,3712,150,2000,3375,1621,3090, 3765,1149,3146,33,3082,2741,359,3316,1749,185,2784,2202,2199,1364, 1244,2020,3160,2785,2772,1217,1822,1245,2252,3904,2774,997,2573, 1148,545,322,789,1440,752,2859,123,1848,643,2405,2638,2344,46, 3814,913,3649,339,3808,822,2832,3078,3633,2970,637,2249,2081,4019, 1478,242,481,2075,4058,622,3376,812,234,641,4005,1122,3135,2640, 2302,40,1832,2247,2034,2637,1287,1691,496,1597,2394,2584,1843,336, 1472,2407,433,2096,1761,2810,566,442,41,1238,1086,603,840,3168, 1499,1084,3438,2408,1589,2391,288,26,512,1456,171,1677,2657,2270, 2587,2961,1970,1817,676,1410,3723,2803,3185,184,663,499,3784,1631, 1925,3912,1398,1349,1441,2224,2411,1907,3192,2786,382,37,759,2948, 1862,3802,2423,2051,2295,1332,1832,2405,3638,3661,327,3660,716, 1842,3987,1368,1848,2366,2508,3754,1766,3572,2893,307,1297,3966, 758,2598,3406,2922,1038,2934,2091,2451,1580,1958,2055,1507,1078, 3273,17,854,2916,3971,2889,3831,2621,1541,893,736,3992,787,2125, 2364,2460,257,1574,3912,1216,3248,3401,2124,2762,149,2245,166,466, 4018,1399,190,2879,153,2320,18,712,2159,2318,2091,3443,1510,449, 1956,2201,3137,3399,1321,2271,3667,2703,629,2365,2431,1113,3922, 2554,184,2099,3228,4012,1921,3452,3901,572,3309,3171,817,3039, 1696,1256,3715,2077,3019,1497,1101,717,51,981,1978,1813,3881,76, 3846,3694,1682,124,1660,3997,479,1141,886,3514,1301,3604,1888, 1836,1990,2058,692,1194,20,3285,2046,2107,3508,3525,3801,2549, 1145,2253,305,3301,1065,3133,2913,3285,1241,1197,3729,2501,1673, 541,2753,949,2361,1165,4081,2725,3305,3069,3617,3733,409,2157, 1361,3973,1865,2525,1409,3445,3577,77,3761,2149,1449,3005,225,85, 3673,3117,3089,1349,2057,413,65,1845,697,3085,3441,1573,3689,2941, 929,533,2841,4077,721,2821,2249,2397,2817,245,1913,1997,3121,997, 1833,2877,1633,981,2009,941,2449,197,2441,285,1473,2741,3129,909, 2801,421,4073,2813,2337,1429,1177,1901,81,1669,2633,2269,129,1141, 249,3917,2481,3941,2217,2749,3041,1877,345,2861,1809,3141,2825, 157,2881,3637,1465,2829,2161,3365,361,2685,3745,2325,3609,3821, 3537,517,3017,2141,1537 }; /* System generated locals */ integer i__1; /* Local variables */ integer i__, i1, i2, i3, i4, it1, it2, it3, it4; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ --iseed; --x; /* Function Body */ i1 = iseed[1]; i2 = iseed[2]; i3 = iseed[3]; i4 = iseed[4]; i__1 = min(*n,128); for (i__ = 1; i__ <= i__1; ++i__) { L20: /* Multiply the seed by i-th power of the multiplier modulo 2**48 */ it4 = i4 * mm[i__ + 383]; it3 = it4 / 4096; it4 -= it3 << 12; it3 = it3 + i3 * mm[i__ + 383] + i4 * mm[i__ + 255]; it2 = it3 / 4096; it3 -= it2 << 12; it2 = it2 + i2 * mm[i__ + 383] + i3 * mm[i__ + 255] + i4 * mm[i__ + 127]; it1 = it2 / 4096; it2 -= it1 << 12; it1 = it1 + i1 * mm[i__ + 383] + i2 * mm[i__ + 255] + i3 * mm[i__ + 127] + i4 * mm[i__ - 1]; it1 %= 4096; /* Convert 48-bit integer to a real number in the interval (0,1) */ x[i__] = ((doublereal) it1 + ((doublereal) it2 + ((doublereal) it3 + ( doublereal) it4 * 2.44140625e-4) * 2.44140625e-4) * 2.44140625e-4) * 2.44140625e-4; if (x[i__] == 1.) { /* If a real number has n bits of precision, and the first n bits of the 48-bit integer above happen to be all 1 (which will occur about once every 2**n calls), then X( I ) will be rounded to exactly 1.0. Since X( I ) is not supposed to return exactly 0.0 or 1.0, the statistically correct thing to do in this situation is simply to iterate again. N.B. the case X( I ) = 0.0 should not be possible. */ i1 += 2; i2 += 2; i3 += 2; i4 += 2; goto L20; } /* L10: */ } /* Return final value of seed */ iseed[1] = it1; iseed[2] = it2; iseed[3] = it3; iseed[4] = it4; return 0; /* End of DLARUV */ } /* igraphdlaruv_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dtrsna.c0000644000076500000240000005240713524616145024307 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static logical c_true = TRUE_; static logical c_false = FALSE_; /* > \brief \b DTRSNA =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DTRSNA + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DTRSNA( JOB, HOWMNY, SELECT, N, T, LDT, VL, LDVL, VR, LDVR, S, SEP, MM, M, WORK, LDWORK, IWORK, INFO ) CHARACTER HOWMNY, JOB INTEGER INFO, LDT, LDVL, LDVR, LDWORK, M, MM, N LOGICAL SELECT( * ) INTEGER IWORK( * ) DOUBLE PRECISION S( * ), SEP( * ), T( LDT, * ), VL( LDVL, * ), $ VR( LDVR, * ), WORK( LDWORK, * ) > \par Purpose: ============= > > \verbatim > > DTRSNA estimates reciprocal condition numbers for specified > eigenvalues and/or right eigenvectors of a real upper > quasi-triangular matrix T (or of any matrix Q*T*Q**T with Q > orthogonal). > > T must be in Schur canonical form (as returned by DHSEQR), that is, > block upper triangular with 1-by-1 and 2-by-2 diagonal blocks; each > 2-by-2 diagonal block has its diagonal elements equal and its > off-diagonal elements of opposite sign. > \endverbatim Arguments: ========== > \param[in] JOB > \verbatim > JOB is CHARACTER*1 > Specifies whether condition numbers are required for > eigenvalues (S) or eigenvectors (SEP): > = 'E': for eigenvalues only (S); > = 'V': for eigenvectors only (SEP); > = 'B': for both eigenvalues and eigenvectors (S and SEP). > \endverbatim > > \param[in] HOWMNY > \verbatim > HOWMNY is CHARACTER*1 > = 'A': compute condition numbers for all eigenpairs; > = 'S': compute condition numbers for selected eigenpairs > specified by the array SELECT. > \endverbatim > > \param[in] SELECT > \verbatim > SELECT is LOGICAL array, dimension (N) > If HOWMNY = 'S', SELECT specifies the eigenpairs for which > condition numbers are required. To select condition numbers > for the eigenpair corresponding to a real eigenvalue w(j), > SELECT(j) must be set to .TRUE.. To select condition numbers > corresponding to a complex conjugate pair of eigenvalues w(j) > and w(j+1), either SELECT(j) or SELECT(j+1) or both, must be > set to .TRUE.. > If HOWMNY = 'A', SELECT is not referenced. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix T. N >= 0. > \endverbatim > > \param[in] T > \verbatim > T is DOUBLE PRECISION array, dimension (LDT,N) > The upper quasi-triangular matrix T, in Schur canonical form. > \endverbatim > > \param[in] LDT > \verbatim > LDT is INTEGER > The leading dimension of the array T. LDT >= max(1,N). > \endverbatim > > \param[in] VL > \verbatim > VL is DOUBLE PRECISION array, dimension (LDVL,M) > If JOB = 'E' or 'B', VL must contain left eigenvectors of T > (or of any Q*T*Q**T with Q orthogonal), corresponding to the > eigenpairs specified by HOWMNY and SELECT. The eigenvectors > must be stored in consecutive columns of VL, as returned by > DHSEIN or DTREVC. > If JOB = 'V', VL is not referenced. > \endverbatim > > \param[in] LDVL > \verbatim > LDVL is INTEGER > The leading dimension of the array VL. > LDVL >= 1; and if JOB = 'E' or 'B', LDVL >= N. > \endverbatim > > \param[in] VR > \verbatim > VR is DOUBLE PRECISION array, dimension (LDVR,M) > If JOB = 'E' or 'B', VR must contain right eigenvectors of T > (or of any Q*T*Q**T with Q orthogonal), corresponding to the > eigenpairs specified by HOWMNY and SELECT. The eigenvectors > must be stored in consecutive columns of VR, as returned by > DHSEIN or DTREVC. > If JOB = 'V', VR is not referenced. > \endverbatim > > \param[in] LDVR > \verbatim > LDVR is INTEGER > The leading dimension of the array VR. > LDVR >= 1; and if JOB = 'E' or 'B', LDVR >= N. > \endverbatim > > \param[out] S > \verbatim > S is DOUBLE PRECISION array, dimension (MM) > If JOB = 'E' or 'B', the reciprocal condition numbers of the > selected eigenvalues, stored in consecutive elements of the > array. For a complex conjugate pair of eigenvalues two > consecutive elements of S are set to the same value. Thus > S(j), SEP(j), and the j-th columns of VL and VR all > correspond to the same eigenpair (but not in general the > j-th eigenpair, unless all eigenpairs are selected). > If JOB = 'V', S is not referenced. > \endverbatim > > \param[out] SEP > \verbatim > SEP is DOUBLE PRECISION array, dimension (MM) > If JOB = 'V' or 'B', the estimated reciprocal condition > numbers of the selected eigenvectors, stored in consecutive > elements of the array. For a complex eigenvector two > consecutive elements of SEP are set to the same value. If > the eigenvalues cannot be reordered to compute SEP(j), SEP(j) > is set to 0; this can only occur when the true value would be > very small anyway. > If JOB = 'E', SEP is not referenced. > \endverbatim > > \param[in] MM > \verbatim > MM is INTEGER > The number of elements in the arrays S (if JOB = 'E' or 'B') > and/or SEP (if JOB = 'V' or 'B'). MM >= M. > \endverbatim > > \param[out] M > \verbatim > M is INTEGER > The number of elements of the arrays S and/or SEP actually > used to store the estimated condition numbers. > If HOWMNY = 'A', M is set to N. > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (LDWORK,N+6) > If JOB = 'E', WORK is not referenced. > \endverbatim > > \param[in] LDWORK > \verbatim > LDWORK is INTEGER > The leading dimension of the array WORK. > LDWORK >= 1; and if JOB = 'V' or 'B', LDWORK >= N. > \endverbatim > > \param[out] IWORK > \verbatim > IWORK is INTEGER array, dimension (2*(N-1)) > If JOB = 'E', IWORK is not referenced. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2011 > \ingroup doubleOTHERcomputational > \par Further Details: ===================== > > \verbatim > > The reciprocal of the condition number of an eigenvalue lambda is > defined as > > S(lambda) = |v**T*u| / (norm(u)*norm(v)) > > where u and v are the right and left eigenvectors of T corresponding > to lambda; v**T denotes the transpose of v, and norm(u) > denotes the Euclidean norm. These reciprocal condition numbers always > lie between zero (very badly conditioned) and one (very well > conditioned). If n = 1, S(lambda) is defined to be 1. > > An approximate error bound for a computed eigenvalue W(i) is given by > > EPS * norm(T) / S(i) > > where EPS is the machine precision. > > The reciprocal of the condition number of the right eigenvector u > corresponding to lambda is defined as follows. Suppose > > T = ( lambda c ) > ( 0 T22 ) > > Then the reciprocal condition number is > > SEP( lambda, T22 ) = sigma-min( T22 - lambda*I ) > > where sigma-min denotes the smallest singular value. We approximate > the smallest singular value by the reciprocal of an estimate of the > one-norm of the inverse of T22 - lambda*I. If n = 1, SEP(1) is > defined to be abs(T(1,1)). > > An approximate error bound for a computed right eigenvector VR(i) > is given by > > EPS * norm(T) / SEP(i) > \endverbatim > ===================================================================== Subroutine */ int igraphdtrsna_(char *job, char *howmny, logical *select, integer *n, doublereal *t, integer *ldt, doublereal *vl, integer * ldvl, doublereal *vr, integer *ldvr, doublereal *s, doublereal *sep, integer *mm, integer *m, doublereal *work, integer *ldwork, integer * iwork, integer *info) { /* System generated locals */ integer t_dim1, t_offset, vl_dim1, vl_offset, vr_dim1, vr_offset, work_dim1, work_offset, i__1, i__2; doublereal d__1, d__2; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ integer i__, j, k, n2; doublereal cs; integer nn, ks; doublereal sn, mu, eps, est; integer kase; doublereal cond; extern doublereal igraphddot_(integer *, doublereal *, integer *, doublereal *, integer *); logical pair; integer ierr; doublereal dumm, prod; integer ifst; doublereal lnrm; integer ilst; doublereal rnrm; extern doublereal igraphdnrm2_(integer *, doublereal *, integer *); doublereal prod1, prod2, scale, delta; extern logical igraphlsame_(char *, char *); integer isave[3]; logical wants; doublereal dummy[1]; extern /* Subroutine */ int igraphdlacn2_(integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, integer *); extern doublereal igraphdlapy2_(doublereal *, doublereal *); extern /* Subroutine */ int igraphdlabad_(doublereal *, doublereal *); extern doublereal igraphdlamch_(char *); extern /* Subroutine */ int igraphdlacpy_(char *, integer *, integer *, doublereal *, integer *, doublereal *, integer *), igraphxerbla_(char *, integer *, ftnlen); doublereal bignum; logical wantbh; extern /* Subroutine */ int igraphdlaqtr_(logical *, logical *, integer *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, integer *), igraphdtrexc_(char *, integer * , doublereal *, integer *, doublereal *, integer *, integer *, integer *, doublereal *, integer *); logical somcon; doublereal smlnum; logical wantsp; /* -- LAPACK computational routine (version 3.4.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2011 ===================================================================== Decode and test the input parameters Parameter adjustments */ --select; t_dim1 = *ldt; t_offset = 1 + t_dim1; t -= t_offset; vl_dim1 = *ldvl; vl_offset = 1 + vl_dim1; vl -= vl_offset; vr_dim1 = *ldvr; vr_offset = 1 + vr_dim1; vr -= vr_offset; --s; --sep; work_dim1 = *ldwork; work_offset = 1 + work_dim1; work -= work_offset; --iwork; /* Function Body */ wantbh = igraphlsame_(job, "B"); wants = igraphlsame_(job, "E") || wantbh; wantsp = igraphlsame_(job, "V") || wantbh; somcon = igraphlsame_(howmny, "S"); *info = 0; if (! wants && ! wantsp) { *info = -1; } else if (! igraphlsame_(howmny, "A") && ! somcon) { *info = -2; } else if (*n < 0) { *info = -4; } else if (*ldt < max(1,*n)) { *info = -6; } else if (*ldvl < 1 || wants && *ldvl < *n) { *info = -8; } else if (*ldvr < 1 || wants && *ldvr < *n) { *info = -10; } else { /* Set M to the number of eigenpairs for which condition numbers are required, and test MM. */ if (somcon) { *m = 0; pair = FALSE_; i__1 = *n; for (k = 1; k <= i__1; ++k) { if (pair) { pair = FALSE_; } else { if (k < *n) { if (t[k + 1 + k * t_dim1] == 0.) { if (select[k]) { ++(*m); } } else { pair = TRUE_; if (select[k] || select[k + 1]) { *m += 2; } } } else { if (select[*n]) { ++(*m); } } } /* L10: */ } } else { *m = *n; } if (*mm < *m) { *info = -13; } else if (*ldwork < 1 || wantsp && *ldwork < *n) { *info = -16; } } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DTRSNA", &i__1, (ftnlen)6); return 0; } /* Quick return if possible */ if (*n == 0) { return 0; } if (*n == 1) { if (somcon) { if (! select[1]) { return 0; } } if (wants) { s[1] = 1.; } if (wantsp) { sep[1] = (d__1 = t[t_dim1 + 1], abs(d__1)); } return 0; } /* Get machine constants */ eps = igraphdlamch_("P"); smlnum = igraphdlamch_("S") / eps; bignum = 1. / smlnum; igraphdlabad_(&smlnum, &bignum); ks = 0; pair = FALSE_; i__1 = *n; for (k = 1; k <= i__1; ++k) { /* Determine whether T(k,k) begins a 1-by-1 or 2-by-2 block. */ if (pair) { pair = FALSE_; goto L60; } else { if (k < *n) { pair = t[k + 1 + k * t_dim1] != 0.; } } /* Determine whether condition numbers are required for the k-th eigenpair. */ if (somcon) { if (pair) { if (! select[k] && ! select[k + 1]) { goto L60; } } else { if (! select[k]) { goto L60; } } } ++ks; if (wants) { /* Compute the reciprocal condition number of the k-th eigenvalue. */ if (! pair) { /* Real eigenvalue. */ prod = igraphddot_(n, &vr[ks * vr_dim1 + 1], &c__1, &vl[ks * vl_dim1 + 1], &c__1); rnrm = igraphdnrm2_(n, &vr[ks * vr_dim1 + 1], &c__1); lnrm = igraphdnrm2_(n, &vl[ks * vl_dim1 + 1], &c__1); s[ks] = abs(prod) / (rnrm * lnrm); } else { /* Complex eigenvalue. */ prod1 = igraphddot_(n, &vr[ks * vr_dim1 + 1], &c__1, &vl[ks * vl_dim1 + 1], &c__1); prod1 += igraphddot_(n, &vr[(ks + 1) * vr_dim1 + 1], &c__1, &vl[(ks + 1) * vl_dim1 + 1], &c__1); prod2 = igraphddot_(n, &vl[ks * vl_dim1 + 1], &c__1, &vr[(ks + 1) * vr_dim1 + 1], &c__1); prod2 -= igraphddot_(n, &vl[(ks + 1) * vl_dim1 + 1], &c__1, &vr[ks * vr_dim1 + 1], &c__1); d__1 = igraphdnrm2_(n, &vr[ks * vr_dim1 + 1], &c__1); d__2 = igraphdnrm2_(n, &vr[(ks + 1) * vr_dim1 + 1], &c__1); rnrm = igraphdlapy2_(&d__1, &d__2); d__1 = igraphdnrm2_(n, &vl[ks * vl_dim1 + 1], &c__1); d__2 = igraphdnrm2_(n, &vl[(ks + 1) * vl_dim1 + 1], &c__1); lnrm = igraphdlapy2_(&d__1, &d__2); cond = igraphdlapy2_(&prod1, &prod2) / (rnrm * lnrm); s[ks] = cond; s[ks + 1] = cond; } } if (wantsp) { /* Estimate the reciprocal condition number of the k-th eigenvector. Copy the matrix T to the array WORK and swap the diagonal block beginning at T(k,k) to the (1,1) position. */ igraphdlacpy_("Full", n, n, &t[t_offset], ldt, &work[work_offset], ldwork); ifst = k; ilst = 1; igraphdtrexc_("No Q", n, &work[work_offset], ldwork, dummy, &c__1, & ifst, &ilst, &work[(*n + 1) * work_dim1 + 1], &ierr); if (ierr == 1 || ierr == 2) { /* Could not swap because blocks not well separated */ scale = 1.; est = bignum; } else { /* Reordering successful */ if (work[work_dim1 + 2] == 0.) { /* Form C = T22 - lambda*I in WORK(2:N,2:N). */ i__2 = *n; for (i__ = 2; i__ <= i__2; ++i__) { work[i__ + i__ * work_dim1] -= work[work_dim1 + 1]; /* L20: */ } n2 = 1; nn = *n - 1; } else { /* Triangularize the 2 by 2 block by unitary transformation U = [ cs i*ss ] [ i*ss cs ]. such that the (1,1) position of WORK is complex eigenvalue lambda with positive imaginary part. (2,2) position of WORK is the complex eigenvalue lambda with negative imaginary part. */ mu = sqrt((d__1 = work[(work_dim1 << 1) + 1], abs(d__1))) * sqrt((d__2 = work[work_dim1 + 2], abs(d__2))); delta = igraphdlapy2_(&mu, &work[work_dim1 + 2]); cs = mu / delta; sn = -work[work_dim1 + 2] / delta; /* Form C**T = WORK(2:N,2:N) + i*[rwork(1) ..... rwork(n-1) ] [ mu ] [ .. ] [ .. ] [ mu ] where C**T is transpose of matrix C, and RWORK is stored starting in the N+1-st column of WORK. */ i__2 = *n; for (j = 3; j <= i__2; ++j) { work[j * work_dim1 + 2] = cs * work[j * work_dim1 + 2] ; work[j + j * work_dim1] -= work[work_dim1 + 1]; /* L30: */ } work[(work_dim1 << 1) + 2] = 0.; work[(*n + 1) * work_dim1 + 1] = mu * 2.; i__2 = *n - 1; for (i__ = 2; i__ <= i__2; ++i__) { work[i__ + (*n + 1) * work_dim1] = sn * work[(i__ + 1) * work_dim1 + 1]; /* L40: */ } n2 = 2; nn = *n - 1 << 1; } /* Estimate norm(inv(C**T)) */ est = 0.; kase = 0; L50: igraphdlacn2_(&nn, &work[(*n + 2) * work_dim1 + 1], &work[(*n + 4) * work_dim1 + 1], &iwork[1], &est, &kase, isave); if (kase != 0) { if (kase == 1) { if (n2 == 1) { /* Real eigenvalue: solve C**T*x = scale*c. */ i__2 = *n - 1; igraphdlaqtr_(&c_true, &c_true, &i__2, &work[(work_dim1 << 1) + 2], ldwork, dummy, &dumm, &scale, &work[(*n + 4) * work_dim1 + 1], &work[(* n + 6) * work_dim1 + 1], &ierr); } else { /* Complex eigenvalue: solve C**T*(p+iq) = scale*(c+id) in real arithmetic. */ i__2 = *n - 1; igraphdlaqtr_(&c_true, &c_false, &i__2, &work[( work_dim1 << 1) + 2], ldwork, &work[(*n + 1) * work_dim1 + 1], &mu, &scale, &work[(* n + 4) * work_dim1 + 1], &work[(*n + 6) * work_dim1 + 1], &ierr); } } else { if (n2 == 1) { /* Real eigenvalue: solve C*x = scale*c. */ i__2 = *n - 1; igraphdlaqtr_(&c_false, &c_true, &i__2, &work[( work_dim1 << 1) + 2], ldwork, dummy, & dumm, &scale, &work[(*n + 4) * work_dim1 + 1], &work[(*n + 6) * work_dim1 + 1], & ierr); } else { /* Complex eigenvalue: solve C*(p+iq) = scale*(c+id) in real arithmetic. */ i__2 = *n - 1; igraphdlaqtr_(&c_false, &c_false, &i__2, &work[( work_dim1 << 1) + 2], ldwork, &work[(*n + 1) * work_dim1 + 1], &mu, &scale, &work[(* n + 4) * work_dim1 + 1], &work[(*n + 6) * work_dim1 + 1], &ierr); } } goto L50; } } sep[ks] = scale / max(est,smlnum); if (pair) { sep[ks + 1] = sep[ks]; } } if (pair) { ++ks; } L60: ; } return 0; /* End of DTRSNA */ } /* igraphdtrsna_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlarrk.c0000644000076500000240000001652513524616145024274 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLARRK computes one eigenvalue of a symmetric tridiagonal matrix T to suitable accuracy. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLARRK + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLARRK( N, IW, GL, GU, D, E2, PIVMIN, RELTOL, W, WERR, INFO) INTEGER INFO, IW, N DOUBLE PRECISION PIVMIN, RELTOL, GL, GU, W, WERR DOUBLE PRECISION D( * ), E2( * ) > \par Purpose: ============= > > \verbatim > > DLARRK computes one eigenvalue of a symmetric tridiagonal > matrix T to suitable accuracy. This is an auxiliary code to be > called from DSTEMR. > > To avoid overflow, the matrix must be scaled so that its > largest element is no greater than overflow**(1/2) * underflow**(1/4) in absolute value, and for greatest > accuracy, it should not be much smaller than that. > > See W. Kahan "Accurate Eigenvalues of a Symmetric Tridiagonal > Matrix", Report CS41, Computer Science Dept., Stanford > University, July 21, 1966. > \endverbatim Arguments: ========== > \param[in] N > \verbatim > N is INTEGER > The order of the tridiagonal matrix T. N >= 0. > \endverbatim > > \param[in] IW > \verbatim > IW is INTEGER > The index of the eigenvalues to be returned. > \endverbatim > > \param[in] GL > \verbatim > GL is DOUBLE PRECISION > \endverbatim > > \param[in] GU > \verbatim > GU is DOUBLE PRECISION > An upper and a lower bound on the eigenvalue. > \endverbatim > > \param[in] D > \verbatim > D is DOUBLE PRECISION array, dimension (N) > The n diagonal elements of the tridiagonal matrix T. > \endverbatim > > \param[in] E2 > \verbatim > E2 is DOUBLE PRECISION array, dimension (N-1) > The (n-1) squared off-diagonal elements of the tridiagonal matrix T. > \endverbatim > > \param[in] PIVMIN > \verbatim > PIVMIN is DOUBLE PRECISION > The minimum pivot allowed in the Sturm sequence for T. > \endverbatim > > \param[in] RELTOL > \verbatim > RELTOL is DOUBLE PRECISION > The minimum relative width of an interval. When an interval > is narrower than RELTOL times the larger (in > magnitude) endpoint, then it is considered to be > sufficiently small, i.e., converged. Note: this should > always be at least radix*machine epsilon. > \endverbatim > > \param[out] W > \verbatim > W is DOUBLE PRECISION > \endverbatim > > \param[out] WERR > \verbatim > WERR is DOUBLE PRECISION > The error bound on the corresponding eigenvalue approximation > in W. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: Eigenvalue converged > = -1: Eigenvalue did NOT converge > \endverbatim > \par Internal Parameters: ========================= > > \verbatim > FUDGE DOUBLE PRECISION, default = 2 > A "fudge factor" to widen the Gershgorin intervals. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERauxiliary ===================================================================== Subroutine */ int igraphdlarrk_(integer *n, integer *iw, doublereal *gl, doublereal *gu, doublereal *d__, doublereal *e2, doublereal *pivmin, doublereal *reltol, doublereal *w, doublereal *werr, integer *info) { /* System generated locals */ integer i__1; doublereal d__1, d__2; /* Builtin functions */ double log(doublereal); /* Local variables */ integer i__, it; doublereal mid, eps, tmp1, tmp2, left, atoli, right; integer itmax; doublereal rtoli, tnorm; extern doublereal igraphdlamch_(char *); integer negcnt; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Get machine constants Parameter adjustments */ --e2; --d__; /* Function Body */ eps = igraphdlamch_("P"); /* Computing MAX */ d__1 = abs(*gl), d__2 = abs(*gu); tnorm = max(d__1,d__2); rtoli = *reltol; atoli = *pivmin * 4.; itmax = (integer) ((log(tnorm + *pivmin) - log(*pivmin)) / log(2.)) + 2; *info = -1; left = *gl - tnorm * 2. * eps * *n - *pivmin * 4.; right = *gu + tnorm * 2. * eps * *n + *pivmin * 4.; it = 0; L10: /* Check if interval converged or maximum number of iterations reached */ tmp1 = (d__1 = right - left, abs(d__1)); /* Computing MAX */ d__1 = abs(right), d__2 = abs(left); tmp2 = max(d__1,d__2); /* Computing MAX */ d__1 = max(atoli,*pivmin), d__2 = rtoli * tmp2; if (tmp1 < max(d__1,d__2)) { *info = 0; goto L30; } if (it > itmax) { goto L30; } /* Count number of negative pivots for mid-point */ ++it; mid = (left + right) * .5; negcnt = 0; tmp1 = d__[1] - mid; if (abs(tmp1) < *pivmin) { tmp1 = -(*pivmin); } if (tmp1 <= 0.) { ++negcnt; } i__1 = *n; for (i__ = 2; i__ <= i__1; ++i__) { tmp1 = d__[i__] - e2[i__ - 1] / tmp1 - mid; if (abs(tmp1) < *pivmin) { tmp1 = -(*pivmin); } if (tmp1 <= 0.) { ++negcnt; } /* L20: */ } if (negcnt >= *iw) { right = mid; } else { left = mid; } goto L10; L30: /* Converged or maximum number of iterations reached */ *w = (left + right) * .5; *werr = (d__1 = right - left, abs(d__1)) * .5; return 0; /* End of DLARRK */ } /* igraphdlarrk_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dorgqr.c0000644000076500000240000002300713524616145024304 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static integer c_n1 = -1; static integer c__3 = 3; static integer c__2 = 2; /* > \brief \b DORGQR =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DORGQR + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DORGQR( M, N, K, A, LDA, TAU, WORK, LWORK, INFO ) INTEGER INFO, K, LDA, LWORK, M, N DOUBLE PRECISION A( LDA, * ), TAU( * ), WORK( * ) > \par Purpose: ============= > > \verbatim > > DORGQR generates an M-by-N real matrix Q with orthonormal columns, > which is defined as the first N columns of a product of K elementary > reflectors of order M > > Q = H(1) H(2) . . . H(k) > > as returned by DGEQRF. > \endverbatim Arguments: ========== > \param[in] M > \verbatim > M is INTEGER > The number of rows of the matrix Q. M >= 0. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The number of columns of the matrix Q. M >= N >= 0. > \endverbatim > > \param[in] K > \verbatim > K is INTEGER > The number of elementary reflectors whose product defines the > matrix Q. N >= K >= 0. > \endverbatim > > \param[in,out] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,N) > On entry, the i-th column must contain the vector which > defines the elementary reflector H(i), for i = 1,2,...,k, as > returned by DGEQRF in the first k columns of its array > argument A. > On exit, the M-by-N matrix Q. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The first dimension of the array A. LDA >= max(1,M). > \endverbatim > > \param[in] TAU > \verbatim > TAU is DOUBLE PRECISION array, dimension (K) > TAU(i) must contain the scalar factor of the elementary > reflector H(i), as returned by DGEQRF. > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (MAX(1,LWORK)) > On exit, if INFO = 0, WORK(1) returns the optimal LWORK. > \endverbatim > > \param[in] LWORK > \verbatim > LWORK is INTEGER > The dimension of the array WORK. LWORK >= max(1,N). > For optimum performance LWORK >= N*NB, where NB is the > optimal blocksize. > > If LWORK = -1, then a workspace query is assumed; the routine > only calculates the optimal size of the WORK array, returns > this value as the first entry of the WORK array, and no error > message related to LWORK is issued by XERBLA. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument has an illegal value > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2011 > \ingroup doubleOTHERcomputational ===================================================================== Subroutine */ int igraphdorgqr_(integer *m, integer *n, integer *k, doublereal * a, integer *lda, doublereal *tau, doublereal *work, integer *lwork, integer *info) { /* System generated locals */ integer a_dim1, a_offset, i__1, i__2, i__3; /* Local variables */ integer i__, j, l, ib, nb, ki, kk, nx, iws, nbmin, iinfo; extern /* Subroutine */ int igraphdorg2r_(integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *), igraphdlarfb_(char *, char *, char *, char *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, integer *), igraphdlarft_(char *, char *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *), igraphxerbla_(char *, integer *, ftnlen); extern integer igraphilaenv_(integer *, char *, char *, integer *, integer *, integer *, integer *, ftnlen, ftnlen); integer ldwork, lwkopt; logical lquery; /* -- LAPACK computational routine (version 3.4.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2011 ===================================================================== Test the input arguments Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --tau; --work; /* Function Body */ *info = 0; nb = igraphilaenv_(&c__1, "DORGQR", " ", m, n, k, &c_n1, (ftnlen)6, (ftnlen)1); lwkopt = max(1,*n) * nb; work[1] = (doublereal) lwkopt; lquery = *lwork == -1; if (*m < 0) { *info = -1; } else if (*n < 0 || *n > *m) { *info = -2; } else if (*k < 0 || *k > *n) { *info = -3; } else if (*lda < max(1,*m)) { *info = -5; } else if (*lwork < max(1,*n) && ! lquery) { *info = -8; } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DORGQR", &i__1, (ftnlen)6); return 0; } else if (lquery) { return 0; } /* Quick return if possible */ if (*n <= 0) { work[1] = 1.; return 0; } nbmin = 2; nx = 0; iws = *n; if (nb > 1 && nb < *k) { /* Determine when to cross over from blocked to unblocked code. Computing MAX */ i__1 = 0, i__2 = igraphilaenv_(&c__3, "DORGQR", " ", m, n, k, &c_n1, ( ftnlen)6, (ftnlen)1); nx = max(i__1,i__2); if (nx < *k) { /* Determine if workspace is large enough for blocked code. */ ldwork = *n; iws = ldwork * nb; if (*lwork < iws) { /* Not enough workspace to use optimal NB: reduce NB and determine the minimum value of NB. */ nb = *lwork / ldwork; /* Computing MAX */ i__1 = 2, i__2 = igraphilaenv_(&c__2, "DORGQR", " ", m, n, k, &c_n1, (ftnlen)6, (ftnlen)1); nbmin = max(i__1,i__2); } } } if (nb >= nbmin && nb < *k && nx < *k) { /* Use blocked code after the last block. The first kk columns are handled by the block method. */ ki = (*k - nx - 1) / nb * nb; /* Computing MIN */ i__1 = *k, i__2 = ki + nb; kk = min(i__1,i__2); /* Set A(1:kk,kk+1:n) to zero. */ i__1 = *n; for (j = kk + 1; j <= i__1; ++j) { i__2 = kk; for (i__ = 1; i__ <= i__2; ++i__) { a[i__ + j * a_dim1] = 0.; /* L10: */ } /* L20: */ } } else { kk = 0; } /* Use unblocked code for the last or only block. */ if (kk < *n) { i__1 = *m - kk; i__2 = *n - kk; i__3 = *k - kk; igraphdorg2r_(&i__1, &i__2, &i__3, &a[kk + 1 + (kk + 1) * a_dim1], lda, & tau[kk + 1], &work[1], &iinfo); } if (kk > 0) { /* Use blocked code */ i__1 = -nb; for (i__ = ki + 1; i__1 < 0 ? i__ >= 1 : i__ <= 1; i__ += i__1) { /* Computing MIN */ i__2 = nb, i__3 = *k - i__ + 1; ib = min(i__2,i__3); if (i__ + ib <= *n) { /* Form the triangular factor of the block reflector H = H(i) H(i+1) . . . H(i+ib-1) */ i__2 = *m - i__ + 1; igraphdlarft_("Forward", "Columnwise", &i__2, &ib, &a[i__ + i__ * a_dim1], lda, &tau[i__], &work[1], &ldwork); /* Apply H to A(i:m,i+ib:n) from the left */ i__2 = *m - i__ + 1; i__3 = *n - i__ - ib + 1; igraphdlarfb_("Left", "No transpose", "Forward", "Columnwise", & i__2, &i__3, &ib, &a[i__ + i__ * a_dim1], lda, &work[ 1], &ldwork, &a[i__ + (i__ + ib) * a_dim1], lda, & work[ib + 1], &ldwork); } /* Apply H to rows i:m of current block */ i__2 = *m - i__ + 1; igraphdorg2r_(&i__2, &ib, &ib, &a[i__ + i__ * a_dim1], lda, &tau[i__], & work[1], &iinfo); /* Set rows 1:i-1 of current block to zero */ i__2 = i__ + ib - 1; for (j = i__; j <= i__2; ++j) { i__3 = i__ - 1; for (l = 1; l <= i__3; ++l) { a[l + j * a_dim1] = 0.; /* L30: */ } /* L40: */ } /* L50: */ } } work[1] = (doublereal) iws; return 0; /* End of DORGQR */ } /* igraphdorgqr_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/idamax.c0000644000076500000240000000352513524616145024254 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" integer igraphidamax_(integer *n, doublereal *dx, integer *incx) { /* System generated locals */ integer ret_val, i__1; doublereal d__1; /* Local variables */ integer i__, ix; doublereal dmax__; /* Purpose ======= IDAMAX finds the index of element having max. absolute value. Further Details =============== jack dongarra, linpack, 3/11/78. modified 3/93 to return if incx .le. 0. modified 12/3/93, array(1) declarations changed to array(*) ===================================================================== Parameter adjustments */ --dx; /* Function Body */ ret_val = 0; if (*n < 1 || *incx <= 0) { return ret_val; } ret_val = 1; if (*n == 1) { return ret_val; } if (*incx == 1) { /* code for increment equal to 1 */ dmax__ = abs(dx[1]); i__1 = *n; for (i__ = 2; i__ <= i__1; ++i__) { if ((d__1 = dx[i__], abs(d__1)) > dmax__) { ret_val = i__; dmax__ = (d__1 = dx[i__], abs(d__1)); } } } else { /* code for increment not equal to 1 */ ix = 1; dmax__ = abs(dx[1]); ix += *incx; i__1 = *n; for (i__ = 2; i__ <= i__1; ++i__) { if ((d__1 = dx[ix], abs(d__1)) > dmax__) { ret_val = i__; dmax__ = (d__1 = dx[ix], abs(d__1)); } ix += *incx; } } return ret_val; } /* igraphidamax_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dstein.c0000644000076500000240000003523613524616145024303 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__2 = 2; static integer c__1 = 1; static integer c_n1 = -1; /* > \brief \b DSTEIN =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DSTEIN + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DSTEIN( N, D, E, M, W, IBLOCK, ISPLIT, Z, LDZ, WORK, IWORK, IFAIL, INFO ) INTEGER INFO, LDZ, M, N INTEGER IBLOCK( * ), IFAIL( * ), ISPLIT( * ), $ IWORK( * ) DOUBLE PRECISION D( * ), E( * ), W( * ), WORK( * ), Z( LDZ, * ) > \par Purpose: ============= > > \verbatim > > DSTEIN computes the eigenvectors of a real symmetric tridiagonal > matrix T corresponding to specified eigenvalues, using inverse > iteration. > > The maximum number of iterations allowed for each eigenvector is > specified by an internal parameter MAXITS (currently set to 5). > \endverbatim Arguments: ========== > \param[in] N > \verbatim > N is INTEGER > The order of the matrix. N >= 0. > \endverbatim > > \param[in] D > \verbatim > D is DOUBLE PRECISION array, dimension (N) > The n diagonal elements of the tridiagonal matrix T. > \endverbatim > > \param[in] E > \verbatim > E is DOUBLE PRECISION array, dimension (N-1) > The (n-1) subdiagonal elements of the tridiagonal matrix > T, in elements 1 to N-1. > \endverbatim > > \param[in] M > \verbatim > M is INTEGER > The number of eigenvectors to be found. 0 <= M <= N. > \endverbatim > > \param[in] W > \verbatim > W is DOUBLE PRECISION array, dimension (N) > The first M elements of W contain the eigenvalues for > which eigenvectors are to be computed. The eigenvalues > should be grouped by split-off block and ordered from > smallest to largest within the block. ( The output array > W from DSTEBZ with ORDER = 'B' is expected here. ) > \endverbatim > > \param[in] IBLOCK > \verbatim > IBLOCK is INTEGER array, dimension (N) > The submatrix indices associated with the corresponding > eigenvalues in W; IBLOCK(i)=1 if eigenvalue W(i) belongs to > the first submatrix from the top, =2 if W(i) belongs to > the second submatrix, etc. ( The output array IBLOCK > from DSTEBZ is expected here. ) > \endverbatim > > \param[in] ISPLIT > \verbatim > ISPLIT is INTEGER array, dimension (N) > The splitting points, at which T breaks up into submatrices. > The first submatrix consists of rows/columns 1 to > ISPLIT( 1 ), the second of rows/columns ISPLIT( 1 )+1 > through ISPLIT( 2 ), etc. > ( The output array ISPLIT from DSTEBZ is expected here. ) > \endverbatim > > \param[out] Z > \verbatim > Z is DOUBLE PRECISION array, dimension (LDZ, M) > The computed eigenvectors. The eigenvector associated > with the eigenvalue W(i) is stored in the i-th column of > Z. Any vector which fails to converge is set to its current > iterate after MAXITS iterations. > \endverbatim > > \param[in] LDZ > \verbatim > LDZ is INTEGER > The leading dimension of the array Z. LDZ >= max(1,N). > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (5*N) > \endverbatim > > \param[out] IWORK > \verbatim > IWORK is INTEGER array, dimension (N) > \endverbatim > > \param[out] IFAIL > \verbatim > IFAIL is INTEGER array, dimension (M) > On normal exit, all elements of IFAIL are zero. > If one or more eigenvectors fail to converge after > MAXITS iterations, then their indices are stored in > array IFAIL. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit. > < 0: if INFO = -i, the i-th argument had an illegal value > > 0: if INFO = i, then i eigenvectors failed to converge > in MAXITS iterations. Their indices are stored in > array IFAIL. > \endverbatim > \par Internal Parameters: ========================= > > \verbatim > MAXITS INTEGER, default = 5 > The maximum number of iterations performed. > > EXTRA INTEGER, default = 2 > The number of iterations performed after norm growth > criterion is satisfied, should be at least 1. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2011 > \ingroup doubleOTHERcomputational ===================================================================== Subroutine */ int igraphdstein_(integer *n, doublereal *d__, doublereal *e, integer *m, doublereal *w, integer *iblock, integer *isplit, doublereal *z__, integer *ldz, doublereal *work, integer *iwork, integer *ifail, integer *info) { /* System generated locals */ integer z_dim1, z_offset, i__1, i__2, i__3; doublereal d__1, d__2, d__3, d__4, d__5; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ integer i__, j, b1, j1, bn; doublereal xj, scl, eps, sep, nrm, tol; integer its; doublereal xjm, ztr, eps1; integer jblk, nblk; extern doublereal igraphddot_(integer *, doublereal *, integer *, doublereal *, integer *); integer jmax; extern doublereal igraphdnrm2_(integer *, doublereal *, integer *); extern /* Subroutine */ int igraphdscal_(integer *, doublereal *, doublereal *, integer *); integer iseed[4], gpind, iinfo; extern doublereal igraphdasum_(integer *, doublereal *, integer *); extern /* Subroutine */ int igraphdcopy_(integer *, doublereal *, integer *, doublereal *, integer *), igraphdaxpy_(integer *, doublereal *, doublereal *, integer *, doublereal *, integer *); doublereal ortol; integer indrv1, indrv2, indrv3, indrv4, indrv5; extern doublereal igraphdlamch_(char *); extern /* Subroutine */ int igraphdlagtf_(integer *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, integer * , integer *); extern integer igraphidamax_(integer *, doublereal *, integer *); extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen), igraphdlagts_( integer *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, integer *, doublereal *, doublereal *, integer *); integer nrmchk; extern /* Subroutine */ int igraphdlarnv_(integer *, integer *, integer *, doublereal *); integer blksiz; doublereal onenrm, dtpcrt, pertol; /* -- LAPACK computational routine (version 3.4.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2011 ===================================================================== Test the input parameters. Parameter adjustments */ --d__; --e; --w; --iblock; --isplit; z_dim1 = *ldz; z_offset = 1 + z_dim1; z__ -= z_offset; --work; --iwork; --ifail; /* Function Body */ *info = 0; i__1 = *m; for (i__ = 1; i__ <= i__1; ++i__) { ifail[i__] = 0; /* L10: */ } if (*n < 0) { *info = -1; } else if (*m < 0 || *m > *n) { *info = -4; } else if (*ldz < max(1,*n)) { *info = -9; } else { i__1 = *m; for (j = 2; j <= i__1; ++j) { if (iblock[j] < iblock[j - 1]) { *info = -6; goto L30; } if (iblock[j] == iblock[j - 1] && w[j] < w[j - 1]) { *info = -5; goto L30; } /* L20: */ } L30: ; } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DSTEIN", &i__1, (ftnlen)6); return 0; } /* Quick return if possible */ if (*n == 0 || *m == 0) { return 0; } else if (*n == 1) { z__[z_dim1 + 1] = 1.; return 0; } /* Get machine constants. */ eps = igraphdlamch_("Precision"); /* Initialize seed for random number generator DLARNV. */ for (i__ = 1; i__ <= 4; ++i__) { iseed[i__ - 1] = 1; /* L40: */ } /* Initialize pointers. */ indrv1 = 0; indrv2 = indrv1 + *n; indrv3 = indrv2 + *n; indrv4 = indrv3 + *n; indrv5 = indrv4 + *n; /* Compute eigenvectors of matrix blocks. */ j1 = 1; i__1 = iblock[*m]; for (nblk = 1; nblk <= i__1; ++nblk) { /* Find starting and ending indices of block nblk. */ if (nblk == 1) { b1 = 1; } else { b1 = isplit[nblk - 1] + 1; } bn = isplit[nblk]; blksiz = bn - b1 + 1; if (blksiz == 1) { goto L60; } gpind = b1; /* Compute reorthogonalization criterion and stopping criterion. */ onenrm = (d__1 = d__[b1], abs(d__1)) + (d__2 = e[b1], abs(d__2)); /* Computing MAX */ d__3 = onenrm, d__4 = (d__1 = d__[bn], abs(d__1)) + (d__2 = e[bn - 1], abs(d__2)); onenrm = max(d__3,d__4); i__2 = bn - 1; for (i__ = b1 + 1; i__ <= i__2; ++i__) { /* Computing MAX */ d__4 = onenrm, d__5 = (d__1 = d__[i__], abs(d__1)) + (d__2 = e[ i__ - 1], abs(d__2)) + (d__3 = e[i__], abs(d__3)); onenrm = max(d__4,d__5); /* L50: */ } ortol = onenrm * .001; dtpcrt = sqrt(.1 / blksiz); /* Loop through eigenvalues of block nblk. */ L60: jblk = 0; i__2 = *m; for (j = j1; j <= i__2; ++j) { if (iblock[j] != nblk) { j1 = j; goto L160; } ++jblk; xj = w[j]; /* Skip all the work if the block size is one. */ if (blksiz == 1) { work[indrv1 + 1] = 1.; goto L120; } /* If eigenvalues j and j-1 are too close, add a relatively small perturbation. */ if (jblk > 1) { eps1 = (d__1 = eps * xj, abs(d__1)); pertol = eps1 * 10.; sep = xj - xjm; if (sep < pertol) { xj = xjm + pertol; } } its = 0; nrmchk = 0; /* Get random starting vector. */ igraphdlarnv_(&c__2, iseed, &blksiz, &work[indrv1 + 1]); /* Copy the matrix T so it won't be destroyed in factorization. */ igraphdcopy_(&blksiz, &d__[b1], &c__1, &work[indrv4 + 1], &c__1); i__3 = blksiz - 1; igraphdcopy_(&i__3, &e[b1], &c__1, &work[indrv2 + 2], &c__1); i__3 = blksiz - 1; igraphdcopy_(&i__3, &e[b1], &c__1, &work[indrv3 + 1], &c__1); /* Compute LU factors with partial pivoting ( PT = LU ) */ tol = 0.; igraphdlagtf_(&blksiz, &work[indrv4 + 1], &xj, &work[indrv2 + 2], &work[ indrv3 + 1], &tol, &work[indrv5 + 1], &iwork[1], &iinfo); /* Update iteration count. */ L70: ++its; if (its > 5) { goto L100; } /* Normalize and scale the righthand side vector Pb. Computing MAX */ d__2 = eps, d__3 = (d__1 = work[indrv4 + blksiz], abs(d__1)); scl = blksiz * onenrm * max(d__2,d__3) / igraphdasum_(&blksiz, &work[ indrv1 + 1], &c__1); igraphdscal_(&blksiz, &scl, &work[indrv1 + 1], &c__1); /* Solve the system LU = Pb. */ igraphdlagts_(&c_n1, &blksiz, &work[indrv4 + 1], &work[indrv2 + 2], & work[indrv3 + 1], &work[indrv5 + 1], &iwork[1], &work[ indrv1 + 1], &tol, &iinfo); /* Reorthogonalize by modified Gram-Schmidt if eigenvalues are close enough. */ if (jblk == 1) { goto L90; } if ((d__1 = xj - xjm, abs(d__1)) > ortol) { gpind = j; } if (gpind != j) { i__3 = j - 1; for (i__ = gpind; i__ <= i__3; ++i__) { ztr = -igraphddot_(&blksiz, &work[indrv1 + 1], &c__1, &z__[b1 + i__ * z_dim1], &c__1); igraphdaxpy_(&blksiz, &ztr, &z__[b1 + i__ * z_dim1], &c__1, & work[indrv1 + 1], &c__1); /* L80: */ } } /* Check the infinity norm of the iterate. */ L90: jmax = igraphidamax_(&blksiz, &work[indrv1 + 1], &c__1); nrm = (d__1 = work[indrv1 + jmax], abs(d__1)); /* Continue for additional iterations after norm reaches stopping criterion. */ if (nrm < dtpcrt) { goto L70; } ++nrmchk; if (nrmchk < 3) { goto L70; } goto L110; /* If stopping criterion was not satisfied, update info and store eigenvector number in array ifail. */ L100: ++(*info); ifail[*info] = j; /* Accept iterate as jth eigenvector. */ L110: scl = 1. / igraphdnrm2_(&blksiz, &work[indrv1 + 1], &c__1); jmax = igraphidamax_(&blksiz, &work[indrv1 + 1], &c__1); if (work[indrv1 + jmax] < 0.) { scl = -scl; } igraphdscal_(&blksiz, &scl, &work[indrv1 + 1], &c__1); L120: i__3 = *n; for (i__ = 1; i__ <= i__3; ++i__) { z__[i__ + j * z_dim1] = 0.; /* L130: */ } i__3 = blksiz; for (i__ = 1; i__ <= i__3; ++i__) { z__[b1 + i__ - 1 + j * z_dim1] = work[indrv1 + i__]; /* L140: */ } /* Save the shift to check eigenvalue spacing at next iteration. */ xjm = xj; /* L150: */ } L160: ; } return 0; /* End of DSTEIN */ } /* igraphdstein_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlaset.c0000644000076500000240000001337513524616145024271 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLASET initializes the off-diagonal elements and the diagonal elements of a matrix to given val ues. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLASET + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLASET( UPLO, M, N, ALPHA, BETA, A, LDA ) CHARACTER UPLO INTEGER LDA, M, N DOUBLE PRECISION ALPHA, BETA DOUBLE PRECISION A( LDA, * ) > \par Purpose: ============= > > \verbatim > > DLASET initializes an m-by-n matrix A to BETA on the diagonal and > ALPHA on the offdiagonals. > \endverbatim Arguments: ========== > \param[in] UPLO > \verbatim > UPLO is CHARACTER*1 > Specifies the part of the matrix A to be set. > = 'U': Upper triangular part is set; the strictly lower > triangular part of A is not changed. > = 'L': Lower triangular part is set; the strictly upper > triangular part of A is not changed. > Otherwise: All of the matrix A is set. > \endverbatim > > \param[in] M > \verbatim > M is INTEGER > The number of rows of the matrix A. M >= 0. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The number of columns of the matrix A. N >= 0. > \endverbatim > > \param[in] ALPHA > \verbatim > ALPHA is DOUBLE PRECISION > The constant to which the offdiagonal elements are to be set. > \endverbatim > > \param[in] BETA > \verbatim > BETA is DOUBLE PRECISION > The constant to which the diagonal elements are to be set. > \endverbatim > > \param[in,out] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,N) > On exit, the leading m-by-n submatrix of A is set as follows: > > if UPLO = 'U', A(i,j) = ALPHA, 1<=i<=j-1, 1<=j<=n, > if UPLO = 'L', A(i,j) = ALPHA, j+1<=i<=m, 1<=j<=n, > otherwise, A(i,j) = ALPHA, 1<=i<=m, 1<=j<=n, i.ne.j, > > and, for all UPLO, A(i,i) = BETA, 1<=i<=min(m,n). > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. LDA >= max(1,M). > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERauxiliary ===================================================================== Subroutine */ int igraphdlaset_(char *uplo, integer *m, integer *n, doublereal * alpha, doublereal *beta, doublereal *a, integer *lda) { /* System generated locals */ integer a_dim1, a_offset, i__1, i__2, i__3; /* Local variables */ integer i__, j; extern logical igraphlsame_(char *, char *); /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; /* Function Body */ if (igraphlsame_(uplo, "U")) { /* Set the strictly upper triangular or trapezoidal part of the array to ALPHA. */ i__1 = *n; for (j = 2; j <= i__1; ++j) { /* Computing MIN */ i__3 = j - 1; i__2 = min(i__3,*m); for (i__ = 1; i__ <= i__2; ++i__) { a[i__ + j * a_dim1] = *alpha; /* L10: */ } /* L20: */ } } else if (igraphlsame_(uplo, "L")) { /* Set the strictly lower triangular or trapezoidal part of the array to ALPHA. */ i__1 = min(*m,*n); for (j = 1; j <= i__1; ++j) { i__2 = *m; for (i__ = j + 1; i__ <= i__2; ++i__) { a[i__ + j * a_dim1] = *alpha; /* L30: */ } /* L40: */ } } else { /* Set the leading m-by-n submatrix to ALPHA. */ i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { a[i__ + j * a_dim1] = *alpha; /* L50: */ } /* L60: */ } } /* Set the first min(M,N) diagonal elements to BETA. */ i__1 = min(*m,*n); for (i__ = 1; i__ <= i__1; ++i__) { a[i__ + i__ * a_dim1] = *beta; /* L70: */ } return 0; /* End of DLASET */ } /* igraphdlaset_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlapy2.c0000644000076500000240000000562013524616145024202 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLAPY2 returns sqrt(x2+y2). =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLAPY2 + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== DOUBLE PRECISION FUNCTION DLAPY2( X, Y ) DOUBLE PRECISION X, Y > \par Purpose: ============= > > \verbatim > > DLAPY2 returns sqrt(x**2+y**2), taking care not to cause unnecessary > overflow. > \endverbatim Arguments: ========== > \param[in] X > \verbatim > X is DOUBLE PRECISION > \endverbatim > > \param[in] Y > \verbatim > Y is DOUBLE PRECISION > X and Y specify the values x and y. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERauxiliary ===================================================================== */ doublereal igraphdlapy2_(doublereal *x, doublereal *y) { /* System generated locals */ doublereal ret_val, d__1; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ doublereal w, z__, xabs, yabs; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== */ xabs = abs(*x); yabs = abs(*y); w = max(xabs,yabs); z__ = min(xabs,yabs); if (z__ == 0.) { ret_val = w; } else { /* Computing 2nd power */ d__1 = z__ / w; ret_val = w * sqrt(d__1 * d__1 + 1.); } return ret_val; /* End of DLAPY2 */ } /* igraphdlapy2_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlarfg.c0000644000076500000240000001314713524616145024251 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLARFG generates an elementary reflector (Householder matrix). =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLARFG + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLARFG( N, ALPHA, X, INCX, TAU ) INTEGER INCX, N DOUBLE PRECISION ALPHA, TAU DOUBLE PRECISION X( * ) > \par Purpose: ============= > > \verbatim > > DLARFG generates a real elementary reflector H of order n, such > that > > H * ( alpha ) = ( beta ), H**T * H = I. > ( x ) ( 0 ) > > where alpha and beta are scalars, and x is an (n-1)-element real > vector. H is represented in the form > > H = I - tau * ( 1 ) * ( 1 v**T ) , > ( v ) > > where tau is a real scalar and v is a real (n-1)-element > vector. > > If the elements of x are all zero, then tau = 0 and H is taken to be > the unit matrix. > > Otherwise 1 <= tau <= 2. > \endverbatim Arguments: ========== > \param[in] N > \verbatim > N is INTEGER > The order of the elementary reflector. > \endverbatim > > \param[in,out] ALPHA > \verbatim > ALPHA is DOUBLE PRECISION > On entry, the value alpha. > On exit, it is overwritten with the value beta. > \endverbatim > > \param[in,out] X > \verbatim > X is DOUBLE PRECISION array, dimension > (1+(N-2)*abs(INCX)) > On entry, the vector x. > On exit, it is overwritten with the vector v. > \endverbatim > > \param[in] INCX > \verbatim > INCX is INTEGER > The increment between elements of X. INCX > 0. > \endverbatim > > \param[out] TAU > \verbatim > TAU is DOUBLE PRECISION > The value tau. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleOTHERauxiliary ===================================================================== Subroutine */ int igraphdlarfg_(integer *n, doublereal *alpha, doublereal *x, integer *incx, doublereal *tau) { /* System generated locals */ integer i__1; doublereal d__1; /* Builtin functions */ double d_sign(doublereal *, doublereal *); /* Local variables */ integer j, knt; doublereal beta; extern doublereal igraphdnrm2_(integer *, doublereal *, integer *); extern /* Subroutine */ int igraphdscal_(integer *, doublereal *, doublereal *, integer *); doublereal xnorm; extern doublereal igraphdlapy2_(doublereal *, doublereal *), igraphdlamch_(char *); doublereal safmin, rsafmn; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ --x; /* Function Body */ if (*n <= 1) { *tau = 0.; return 0; } i__1 = *n - 1; xnorm = igraphdnrm2_(&i__1, &x[1], incx); if (xnorm == 0.) { /* H = I */ *tau = 0.; } else { /* general case */ d__1 = igraphdlapy2_(alpha, &xnorm); beta = -d_sign(&d__1, alpha); safmin = igraphdlamch_("S") / igraphdlamch_("E"); knt = 0; if (abs(beta) < safmin) { /* XNORM, BETA may be inaccurate; scale X and recompute them */ rsafmn = 1. / safmin; L10: ++knt; i__1 = *n - 1; igraphdscal_(&i__1, &rsafmn, &x[1], incx); beta *= rsafmn; *alpha *= rsafmn; if (abs(beta) < safmin) { goto L10; } /* New BETA is at most 1, at least SAFMIN */ i__1 = *n - 1; xnorm = igraphdnrm2_(&i__1, &x[1], incx); d__1 = igraphdlapy2_(alpha, &xnorm); beta = -d_sign(&d__1, alpha); } *tau = (beta - *alpha) / beta; i__1 = *n - 1; d__1 = 1. / (*alpha - beta); igraphdscal_(&i__1, &d__1, &x[1], incx); /* If ALPHA is subnormal, it may lose relative accuracy */ i__1 = knt; for (j = 1; j <= i__1; ++j) { beta *= safmin; /* L20: */ } *alpha = beta; } return 0; /* End of DLARFG */ } /* igraphdlarfg_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dgetrs.c0000644000076500000240000001567513524616145024312 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static doublereal c_b12 = 1.; static integer c_n1 = -1; /* > \brief \b DGETRS =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DGETRS + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DGETRS( TRANS, N, NRHS, A, LDA, IPIV, B, LDB, INFO ) CHARACTER TRANS INTEGER INFO, LDA, LDB, N, NRHS INTEGER IPIV( * ) DOUBLE PRECISION A( LDA, * ), B( LDB, * ) > \par Purpose: ============= > > \verbatim > > DGETRS solves a system of linear equations > A * X = B or A**T * X = B > with a general N-by-N matrix A using the LU factorization computed > by DGETRF. > \endverbatim Arguments: ========== > \param[in] TRANS > \verbatim > TRANS is CHARACTER*1 > Specifies the form of the system of equations: > = 'N': A * X = B (No transpose) > = 'T': A**T* X = B (Transpose) > = 'C': A**T* X = B (Conjugate transpose = Transpose) > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix A. N >= 0. > \endverbatim > > \param[in] NRHS > \verbatim > NRHS is INTEGER > The number of right hand sides, i.e., the number of columns > of the matrix B. NRHS >= 0. > \endverbatim > > \param[in] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,N) > The factors L and U from the factorization A = P*L*U > as computed by DGETRF. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. LDA >= max(1,N). > \endverbatim > > \param[in] IPIV > \verbatim > IPIV is INTEGER array, dimension (N) > The pivot indices from DGETRF; for 1<=i<=N, row i of the > matrix was interchanged with row IPIV(i). > \endverbatim > > \param[in,out] B > \verbatim > B is DOUBLE PRECISION array, dimension (LDB,NRHS) > On entry, the right hand side matrix B. > On exit, the solution matrix X. > \endverbatim > > \param[in] LDB > \verbatim > LDB is INTEGER > The leading dimension of the array B. LDB >= max(1,N). > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2011 > \ingroup doubleGEcomputational ===================================================================== Subroutine */ int igraphdgetrs_(char *trans, integer *n, integer *nrhs, doublereal *a, integer *lda, integer *ipiv, doublereal *b, integer * ldb, integer *info) { /* System generated locals */ integer a_dim1, a_offset, b_dim1, b_offset, i__1; /* Local variables */ extern logical igraphlsame_(char *, char *); extern /* Subroutine */ int igraphdtrsm_(char *, char *, char *, char *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *), igraphxerbla_( char *, integer *, ftnlen), igraphdlaswp_(integer *, doublereal *, integer *, integer *, integer *, integer *, integer *); logical notran; /* -- LAPACK computational routine (version 3.4.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2011 ===================================================================== Test the input parameters. Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --ipiv; b_dim1 = *ldb; b_offset = 1 + b_dim1; b -= b_offset; /* Function Body */ *info = 0; notran = igraphlsame_(trans, "N"); if (! notran && ! igraphlsame_(trans, "T") && ! igraphlsame_( trans, "C")) { *info = -1; } else if (*n < 0) { *info = -2; } else if (*nrhs < 0) { *info = -3; } else if (*lda < max(1,*n)) { *info = -5; } else if (*ldb < max(1,*n)) { *info = -8; } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DGETRS", &i__1, (ftnlen)6); return 0; } /* Quick return if possible */ if (*n == 0 || *nrhs == 0) { return 0; } if (notran) { /* Solve A * X = B. Apply row interchanges to the right hand sides. */ igraphdlaswp_(nrhs, &b[b_offset], ldb, &c__1, n, &ipiv[1], &c__1); /* Solve L*X = B, overwriting B with X. */ igraphdtrsm_("Left", "Lower", "No transpose", "Unit", n, nrhs, &c_b12, &a[ a_offset], lda, &b[b_offset], ldb); /* Solve U*X = B, overwriting B with X. */ igraphdtrsm_("Left", "Upper", "No transpose", "Non-unit", n, nrhs, &c_b12, & a[a_offset], lda, &b[b_offset], ldb); } else { /* Solve A**T * X = B. Solve U**T *X = B, overwriting B with X. */ igraphdtrsm_("Left", "Upper", "Transpose", "Non-unit", n, nrhs, &c_b12, &a[ a_offset], lda, &b[b_offset], ldb); /* Solve L**T *X = B, overwriting B with X. */ igraphdtrsm_("Left", "Lower", "Transpose", "Unit", n, nrhs, &c_b12, &a[ a_offset], lda, &b[b_offset], ldb); /* Apply row interchanges to the solution vectors. */ igraphdlaswp_(nrhs, &b[b_offset], ldb, &c__1, n, &ipiv[1], &c_n1); } return 0; /* End of DGETRS */ } /* igraphdgetrs_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dcopy.c0000644000076500000240000000413213524616145024122 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Subroutine */ int igraphdcopy_(integer *n, doublereal *dx, integer *incx, doublereal *dy, integer *incy) { /* System generated locals */ integer i__1; /* Local variables */ integer i__, m, ix, iy, mp1; /* Purpose ======= DCOPY copies a vector, x, to a vector, y. uses unrolled loops for increments equal to one. Further Details =============== jack dongarra, linpack, 3/11/78. modified 12/3/93, array(1) declarations changed to array(*) ===================================================================== Parameter adjustments */ --dy; --dx; /* Function Body */ if (*n <= 0) { return 0; } if (*incx == 1 && *incy == 1) { /* code for both increments equal to 1 clean-up loop */ m = *n % 7; if (m != 0) { i__1 = m; for (i__ = 1; i__ <= i__1; ++i__) { dy[i__] = dx[i__]; } if (*n < 7) { return 0; } } mp1 = m + 1; i__1 = *n; for (i__ = mp1; i__ <= i__1; i__ += 7) { dy[i__] = dx[i__]; dy[i__ + 1] = dx[i__ + 1]; dy[i__ + 2] = dx[i__ + 2]; dy[i__ + 3] = dx[i__ + 3]; dy[i__ + 4] = dx[i__ + 4]; dy[i__ + 5] = dx[i__ + 5]; dy[i__ + 6] = dx[i__ + 6]; } } else { /* code for unequal increments or equal increments not equal to 1 */ ix = 1; iy = 1; if (*incx < 0) { ix = (-(*n) + 1) * *incx + 1; } if (*incy < 0) { iy = (-(*n) + 1) * *incy + 1; } i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { dy[iy] = dx[ix]; ix += *incx; iy += *incy; } } return 0; } /* igraphdcopy_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlarre.c0000644000076500000240000010140613524616145024257 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static integer c__2 = 2; /* > \brief \b DLARRE given the tridiagonal matrix T, sets small off-diagonal elements to zero and for each un reduced block Ti, finds base representations and eigenvalues. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLARRE + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLARRE( RANGE, N, VL, VU, IL, IU, D, E, E2, RTOL1, RTOL2, SPLTOL, NSPLIT, ISPLIT, M, W, WERR, WGAP, IBLOCK, INDEXW, GERS, PIVMIN, WORK, IWORK, INFO ) CHARACTER RANGE INTEGER IL, INFO, IU, M, N, NSPLIT DOUBLE PRECISION PIVMIN, RTOL1, RTOL2, SPLTOL, VL, VU INTEGER IBLOCK( * ), ISPLIT( * ), IWORK( * ), $ INDEXW( * ) DOUBLE PRECISION D( * ), E( * ), E2( * ), GERS( * ), $ W( * ),WERR( * ), WGAP( * ), WORK( * ) > \par Purpose: ============= > > \verbatim > > To find the desired eigenvalues of a given real symmetric > tridiagonal matrix T, DLARRE sets any "small" off-diagonal > elements to zero, and for each unreduced block T_i, it finds > (a) a suitable shift at one end of the block's spectrum, > (b) the base representation, T_i - sigma_i I = L_i D_i L_i^T, and > (c) eigenvalues of each L_i D_i L_i^T. > The representations and eigenvalues found are then used by > DSTEMR to compute the eigenvectors of T. > The accuracy varies depending on whether bisection is used to > find a few eigenvalues or the dqds algorithm (subroutine DLASQ2) to > conpute all and then discard any unwanted one. > As an added benefit, DLARRE also outputs the n > Gerschgorin intervals for the matrices L_i D_i L_i^T. > \endverbatim Arguments: ========== > \param[in] RANGE > \verbatim > RANGE is CHARACTER*1 > = 'A': ("All") all eigenvalues will be found. > = 'V': ("Value") all eigenvalues in the half-open interval > (VL, VU] will be found. > = 'I': ("Index") the IL-th through IU-th eigenvalues (of the > entire matrix) will be found. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix. N > 0. > \endverbatim > > \param[in,out] VL > \verbatim > VL is DOUBLE PRECISION > \endverbatim > > \param[in,out] VU > \verbatim > VU is DOUBLE PRECISION > If RANGE='V', the lower and upper bounds for the eigenvalues. > Eigenvalues less than or equal to VL, or greater than VU, > will not be returned. VL < VU. > If RANGE='I' or ='A', DLARRE computes bounds on the desired > part of the spectrum. > \endverbatim > > \param[in] IL > \verbatim > IL is INTEGER > \endverbatim > > \param[in] IU > \verbatim > IU is INTEGER > If RANGE='I', the indices (in ascending order) of the > smallest and largest eigenvalues to be returned. > 1 <= IL <= IU <= N. > \endverbatim > > \param[in,out] D > \verbatim > D is DOUBLE PRECISION array, dimension (N) > On entry, the N diagonal elements of the tridiagonal > matrix T. > On exit, the N diagonal elements of the diagonal > matrices D_i. > \endverbatim > > \param[in,out] E > \verbatim > E is DOUBLE PRECISION array, dimension (N) > On entry, the first (N-1) entries contain the subdiagonal > elements of the tridiagonal matrix T; E(N) need not be set. > On exit, E contains the subdiagonal elements of the unit > bidiagonal matrices L_i. The entries E( ISPLIT( I ) ), > 1 <= I <= NSPLIT, contain the base points sigma_i on output. > \endverbatim > > \param[in,out] E2 > \verbatim > E2 is DOUBLE PRECISION array, dimension (N) > On entry, the first (N-1) entries contain the SQUARES of the > subdiagonal elements of the tridiagonal matrix T; > E2(N) need not be set. > On exit, the entries E2( ISPLIT( I ) ), > 1 <= I <= NSPLIT, have been set to zero > \endverbatim > > \param[in] RTOL1 > \verbatim > RTOL1 is DOUBLE PRECISION > \endverbatim > > \param[in] RTOL2 > \verbatim > RTOL2 is DOUBLE PRECISION > Parameters for bisection. > An interval [LEFT,RIGHT] has converged if > RIGHT-LEFT.LT.MAX( RTOL1*GAP, RTOL2*MAX(|LEFT|,|RIGHT|) ) > \endverbatim > > \param[in] SPLTOL > \verbatim > SPLTOL is DOUBLE PRECISION > The threshold for splitting. > \endverbatim > > \param[out] NSPLIT > \verbatim > NSPLIT is INTEGER > The number of blocks T splits into. 1 <= NSPLIT <= N. > \endverbatim > > \param[out] ISPLIT > \verbatim > ISPLIT is INTEGER array, dimension (N) > The splitting points, at which T breaks up into blocks. > The first block consists of rows/columns 1 to ISPLIT(1), > the second of rows/columns ISPLIT(1)+1 through ISPLIT(2), > etc., and the NSPLIT-th consists of rows/columns > ISPLIT(NSPLIT-1)+1 through ISPLIT(NSPLIT)=N. > \endverbatim > > \param[out] M > \verbatim > M is INTEGER > The total number of eigenvalues (of all L_i D_i L_i^T) > found. > \endverbatim > > \param[out] W > \verbatim > W is DOUBLE PRECISION array, dimension (N) > The first M elements contain the eigenvalues. The > eigenvalues of each of the blocks, L_i D_i L_i^T, are > sorted in ascending order ( DLARRE may use the > remaining N-M elements as workspace). > \endverbatim > > \param[out] WERR > \verbatim > WERR is DOUBLE PRECISION array, dimension (N) > The error bound on the corresponding eigenvalue in W. > \endverbatim > > \param[out] WGAP > \verbatim > WGAP is DOUBLE PRECISION array, dimension (N) > The separation from the right neighbor eigenvalue in W. > The gap is only with respect to the eigenvalues of the same block > as each block has its own representation tree. > Exception: at the right end of a block we store the left gap > \endverbatim > > \param[out] IBLOCK > \verbatim > IBLOCK is INTEGER array, dimension (N) > The indices of the blocks (submatrices) associated with the > corresponding eigenvalues in W; IBLOCK(i)=1 if eigenvalue > W(i) belongs to the first block from the top, =2 if W(i) > belongs to the second block, etc. > \endverbatim > > \param[out] INDEXW > \verbatim > INDEXW is INTEGER array, dimension (N) > The indices of the eigenvalues within each block (submatrix); > for example, INDEXW(i)= 10 and IBLOCK(i)=2 imply that the > i-th eigenvalue W(i) is the 10-th eigenvalue in block 2 > \endverbatim > > \param[out] GERS > \verbatim > GERS is DOUBLE PRECISION array, dimension (2*N) > The N Gerschgorin intervals (the i-th Gerschgorin interval > is (GERS(2*i-1), GERS(2*i)). > \endverbatim > > \param[out] PIVMIN > \verbatim > PIVMIN is DOUBLE PRECISION > The minimum pivot in the Sturm sequence for T. > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (6*N) > Workspace. > \endverbatim > > \param[out] IWORK > \verbatim > IWORK is INTEGER array, dimension (5*N) > Workspace. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > > 0: A problem occured in DLARRE. > < 0: One of the called subroutines signaled an internal problem. > Needs inspection of the corresponding parameter IINFO > for further information. > > =-1: Problem in DLARRD. > = 2: No base representation could be found in MAXTRY iterations. > Increasing MAXTRY and recompilation might be a remedy. > =-3: Problem in DLARRB when computing the refined root > representation for DLASQ2. > =-4: Problem in DLARRB when preforming bisection on the > desired part of the spectrum. > =-5: Problem in DLASQ2. > =-6: Problem in DLASQ2. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERauxiliary > \par Further Details: ===================== > > \verbatim > > The base representations are required to suffer very little > element growth and consequently define all their eigenvalues to > high relative accuracy. > \endverbatim > \par Contributors: ================== > > Beresford Parlett, University of California, Berkeley, USA \n > Jim Demmel, University of California, Berkeley, USA \n > Inderjit Dhillon, University of Texas, Austin, USA \n > Osni Marques, LBNL/NERSC, USA \n > Christof Voemel, University of California, Berkeley, USA \n > ===================================================================== Subroutine */ int igraphdlarre_(char *range, integer *n, doublereal *vl, doublereal *vu, integer *il, integer *iu, doublereal *d__, doublereal *e, doublereal *e2, doublereal *rtol1, doublereal *rtol2, doublereal * spltol, integer *nsplit, integer *isplit, integer *m, doublereal *w, doublereal *werr, doublereal *wgap, integer *iblock, integer *indexw, doublereal *gers, doublereal *pivmin, doublereal *work, integer * iwork, integer *info) { /* System generated locals */ integer i__1, i__2; doublereal d__1, d__2, d__3; /* Builtin functions */ double sqrt(doublereal), log(doublereal); /* Local variables */ integer i__, j; doublereal s1, s2; integer mb; doublereal gl; integer in, mm; doublereal gu; integer cnt; doublereal eps, tau, tmp, rtl; integer cnt1, cnt2; doublereal tmp1, eabs; integer iend, jblk; doublereal eold; integer indl; doublereal dmax__, emax; integer wend, idum, indu; doublereal rtol; integer iseed[4]; doublereal avgap, sigma; extern logical igraphlsame_(char *, char *); integer iinfo; extern /* Subroutine */ int igraphdcopy_(integer *, doublereal *, integer *, doublereal *, integer *); logical norep; extern /* Subroutine */ int igraphdlasq2_(integer *, doublereal *, integer *); extern doublereal igraphdlamch_(char *); integer ibegin; logical forceb; integer irange; doublereal sgndef; extern /* Subroutine */ int igraphdlarra_(integer *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, integer *, integer *, integer *), igraphdlarrb_(integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, integer *, doublereal *, doublereal *, integer *, integer *), igraphdlarrc_(char * , integer *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, integer *, integer *, integer *, integer *); integer wbegin; extern /* Subroutine */ int igraphdlarrd_(char *, char *, integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, integer * , integer *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, integer *, integer *, doublereal *, integer *, integer *); doublereal safmin, spdiam; extern /* Subroutine */ int igraphdlarrk_(integer *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, integer *); logical usedqd; doublereal clwdth, isleft; extern /* Subroutine */ int igraphdlarnv_(integer *, integer *, integer *, doublereal *); doublereal isrght, bsrtol, dpivot; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ --iwork; --work; --gers; --indexw; --iblock; --wgap; --werr; --w; --isplit; --e2; --e; --d__; /* Function Body */ *info = 0; /* Decode RANGE */ if (igraphlsame_(range, "A")) { irange = 1; } else if (igraphlsame_(range, "V")) { irange = 3; } else if (igraphlsame_(range, "I")) { irange = 2; } *m = 0; /* Get machine constants */ safmin = igraphdlamch_("S"); eps = igraphdlamch_("P"); /* Set parameters */ rtl = sqrt(eps); bsrtol = sqrt(eps); /* Treat case of 1x1 matrix for quick return */ if (*n == 1) { if (irange == 1 || irange == 3 && d__[1] > *vl && d__[1] <= *vu || irange == 2 && *il == 1 && *iu == 1) { *m = 1; w[1] = d__[1]; /* The computation error of the eigenvalue is zero */ werr[1] = 0.; wgap[1] = 0.; iblock[1] = 1; indexw[1] = 1; gers[1] = d__[1]; gers[2] = d__[1]; } /* store the shift for the initial RRR, which is zero in this case */ e[1] = 0.; return 0; } /* General case: tridiagonal matrix of order > 1 Init WERR, WGAP. Compute Gerschgorin intervals and spectral diameter. Compute maximum off-diagonal entry and pivmin. */ gl = d__[1]; gu = d__[1]; eold = 0.; emax = 0.; e[*n] = 0.; i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { werr[i__] = 0.; wgap[i__] = 0.; eabs = (d__1 = e[i__], abs(d__1)); if (eabs >= emax) { emax = eabs; } tmp1 = eabs + eold; gers[(i__ << 1) - 1] = d__[i__] - tmp1; /* Computing MIN */ d__1 = gl, d__2 = gers[(i__ << 1) - 1]; gl = min(d__1,d__2); gers[i__ * 2] = d__[i__] + tmp1; /* Computing MAX */ d__1 = gu, d__2 = gers[i__ * 2]; gu = max(d__1,d__2); eold = eabs; /* L5: */ } /* The minimum pivot allowed in the Sturm sequence for T Computing MAX Computing 2nd power */ d__3 = emax; d__1 = 1., d__2 = d__3 * d__3; *pivmin = safmin * max(d__1,d__2); /* Compute spectral diameter. The Gerschgorin bounds give an estimate that is wrong by at most a factor of SQRT(2) */ spdiam = gu - gl; /* Compute splitting points */ igraphdlarra_(n, &d__[1], &e[1], &e2[1], spltol, &spdiam, nsplit, &isplit[1], & iinfo); /* Can force use of bisection instead of faster DQDS. Option left in the code for future multisection work. */ forceb = FALSE_; /* Initialize USEDQD, DQDS should be used for ALLRNG unless someone explicitly wants bisection. */ usedqd = irange == 1 && ! forceb; if (irange == 1 && ! forceb) { /* Set interval [VL,VU] that contains all eigenvalues */ *vl = gl; *vu = gu; } else { /* We call DLARRD to find crude approximations to the eigenvalues in the desired range. In case IRANGE = INDRNG, we also obtain the interval (VL,VU] that contains all the wanted eigenvalues. An interval [LEFT,RIGHT] has converged if RIGHT-LEFT.LT.RTOL*MAX(ABS(LEFT),ABS(RIGHT)) DLARRD needs a WORK of size 4*N, IWORK of size 3*N */ igraphdlarrd_(range, "B", n, vl, vu, il, iu, &gers[1], &bsrtol, &d__[1], &e[ 1], &e2[1], pivmin, nsplit, &isplit[1], &mm, &w[1], &werr[1], vl, vu, &iblock[1], &indexw[1], &work[1], &iwork[1], &iinfo); if (iinfo != 0) { *info = -1; return 0; } /* Make sure that the entries M+1 to N in W, WERR, IBLOCK, INDEXW are 0 */ i__1 = *n; for (i__ = mm + 1; i__ <= i__1; ++i__) { w[i__] = 0.; werr[i__] = 0.; iblock[i__] = 0; indexw[i__] = 0; /* L14: */ } } /* ** Loop over unreduced blocks */ ibegin = 1; wbegin = 1; i__1 = *nsplit; for (jblk = 1; jblk <= i__1; ++jblk) { iend = isplit[jblk]; in = iend - ibegin + 1; /* 1 X 1 block */ if (in == 1) { if (irange == 1 || irange == 3 && d__[ibegin] > *vl && d__[ibegin] <= *vu || irange == 2 && iblock[wbegin] == jblk) { ++(*m); w[*m] = d__[ibegin]; werr[*m] = 0.; /* The gap for a single block doesn't matter for the later algorithm and is assigned an arbitrary large value */ wgap[*m] = 0.; iblock[*m] = jblk; indexw[*m] = 1; ++wbegin; } /* E( IEND ) holds the shift for the initial RRR */ e[iend] = 0.; ibegin = iend + 1; goto L170; } /* Blocks of size larger than 1x1 E( IEND ) will hold the shift for the initial RRR, for now set it =0 */ e[iend] = 0.; /* Find local outer bounds GL,GU for the block */ gl = d__[ibegin]; gu = d__[ibegin]; i__2 = iend; for (i__ = ibegin; i__ <= i__2; ++i__) { /* Computing MIN */ d__1 = gers[(i__ << 1) - 1]; gl = min(d__1,gl); /* Computing MAX */ d__1 = gers[i__ * 2]; gu = max(d__1,gu); /* L15: */ } spdiam = gu - gl; if (! (irange == 1 && ! forceb)) { /* Count the number of eigenvalues in the current block. */ mb = 0; i__2 = mm; for (i__ = wbegin; i__ <= i__2; ++i__) { if (iblock[i__] == jblk) { ++mb; } else { goto L21; } /* L20: */ } L21: if (mb == 0) { /* No eigenvalue in the current block lies in the desired range E( IEND ) holds the shift for the initial RRR */ e[iend] = 0.; ibegin = iend + 1; goto L170; } else { /* Decide whether dqds or bisection is more efficient */ usedqd = (doublereal) mb > in * .5 && ! forceb; wend = wbegin + mb - 1; /* Calculate gaps for the current block In later stages, when representations for individual eigenvalues are different, we use SIGMA = E( IEND ). */ sigma = 0.; i__2 = wend - 1; for (i__ = wbegin; i__ <= i__2; ++i__) { /* Computing MAX */ d__1 = 0., d__2 = w[i__ + 1] - werr[i__ + 1] - (w[i__] + werr[i__]); wgap[i__] = max(d__1,d__2); /* L30: */ } /* Computing MAX */ d__1 = 0., d__2 = *vu - sigma - (w[wend] + werr[wend]); wgap[wend] = max(d__1,d__2); /* Find local index of the first and last desired evalue. */ indl = indexw[wbegin]; indu = indexw[wend]; } } if (irange == 1 && ! forceb || usedqd) { /* Case of DQDS Find approximations to the extremal eigenvalues of the block */ igraphdlarrk_(&in, &c__1, &gl, &gu, &d__[ibegin], &e2[ibegin], pivmin, & rtl, &tmp, &tmp1, &iinfo); if (iinfo != 0) { *info = -1; return 0; } /* Computing MAX */ d__2 = gl, d__3 = tmp - tmp1 - eps * 100. * (d__1 = tmp - tmp1, abs(d__1)); isleft = max(d__2,d__3); igraphdlarrk_(&in, &in, &gl, &gu, &d__[ibegin], &e2[ibegin], pivmin, & rtl, &tmp, &tmp1, &iinfo); if (iinfo != 0) { *info = -1; return 0; } /* Computing MIN */ d__2 = gu, d__3 = tmp + tmp1 + eps * 100. * (d__1 = tmp + tmp1, abs(d__1)); isrght = min(d__2,d__3); /* Improve the estimate of the spectral diameter */ spdiam = isrght - isleft; } else { /* Case of bisection Find approximations to the wanted extremal eigenvalues Computing MAX */ d__2 = gl, d__3 = w[wbegin] - werr[wbegin] - eps * 100. * (d__1 = w[wbegin] - werr[wbegin], abs(d__1)); isleft = max(d__2,d__3); /* Computing MIN */ d__2 = gu, d__3 = w[wend] + werr[wend] + eps * 100. * (d__1 = w[ wend] + werr[wend], abs(d__1)); isrght = min(d__2,d__3); } /* Decide whether the base representation for the current block L_JBLK D_JBLK L_JBLK^T = T_JBLK - sigma_JBLK I should be on the left or the right end of the current block. The strategy is to shift to the end which is "more populated" Furthermore, decide whether to use DQDS for the computation of the eigenvalue approximations at the end of DLARRE or bisection. dqds is chosen if all eigenvalues are desired or the number of eigenvalues to be computed is large compared to the blocksize. */ if (irange == 1 && ! forceb) { /* If all the eigenvalues have to be computed, we use dqd */ usedqd = TRUE_; /* INDL is the local index of the first eigenvalue to compute */ indl = 1; indu = in; /* MB = number of eigenvalues to compute */ mb = in; wend = wbegin + mb - 1; /* Define 1/4 and 3/4 points of the spectrum */ s1 = isleft + spdiam * .25; s2 = isrght - spdiam * .25; } else { /* DLARRD has computed IBLOCK and INDEXW for each eigenvalue approximation. choose sigma */ if (usedqd) { s1 = isleft + spdiam * .25; s2 = isrght - spdiam * .25; } else { tmp = min(isrght,*vu) - max(isleft,*vl); s1 = max(isleft,*vl) + tmp * .25; s2 = min(isrght,*vu) - tmp * .25; } } /* Compute the negcount at the 1/4 and 3/4 points */ if (mb > 1) { igraphdlarrc_("T", &in, &s1, &s2, &d__[ibegin], &e[ibegin], pivmin, & cnt, &cnt1, &cnt2, &iinfo); } if (mb == 1) { sigma = gl; sgndef = 1.; } else if (cnt1 - indl >= indu - cnt2) { if (irange == 1 && ! forceb) { sigma = max(isleft,gl); } else if (usedqd) { /* use Gerschgorin bound as shift to get pos def matrix for dqds */ sigma = isleft; } else { /* use approximation of the first desired eigenvalue of the block as shift */ sigma = max(isleft,*vl); } sgndef = 1.; } else { if (irange == 1 && ! forceb) { sigma = min(isrght,gu); } else if (usedqd) { /* use Gerschgorin bound as shift to get neg def matrix for dqds */ sigma = isrght; } else { /* use approximation of the first desired eigenvalue of the block as shift */ sigma = min(isrght,*vu); } sgndef = -1.; } /* An initial SIGMA has been chosen that will be used for computing T - SIGMA I = L D L^T Define the increment TAU of the shift in case the initial shift needs to be refined to obtain a factorization with not too much element growth. */ if (usedqd) { /* The initial SIGMA was to the outer end of the spectrum the matrix is definite and we need not retreat. */ tau = spdiam * eps * *n + *pivmin * 2.; /* Computing MAX */ d__1 = tau, d__2 = eps * 2. * abs(sigma); tau = max(d__1,d__2); } else { if (mb > 1) { clwdth = w[wend] + werr[wend] - w[wbegin] - werr[wbegin]; avgap = (d__1 = clwdth / (doublereal) (wend - wbegin), abs( d__1)); if (sgndef == 1.) { /* Computing MAX */ d__1 = wgap[wbegin]; tau = max(d__1,avgap) * .5; /* Computing MAX */ d__1 = tau, d__2 = werr[wbegin]; tau = max(d__1,d__2); } else { /* Computing MAX */ d__1 = wgap[wend - 1]; tau = max(d__1,avgap) * .5; /* Computing MAX */ d__1 = tau, d__2 = werr[wend]; tau = max(d__1,d__2); } } else { tau = werr[wbegin]; } } for (idum = 1; idum <= 6; ++idum) { /* Compute L D L^T factorization of tridiagonal matrix T - sigma I. Store D in WORK(1:IN), L in WORK(IN+1:2*IN), and reciprocals of pivots in WORK(2*IN+1:3*IN) */ dpivot = d__[ibegin] - sigma; work[1] = dpivot; dmax__ = abs(work[1]); j = ibegin; i__2 = in - 1; for (i__ = 1; i__ <= i__2; ++i__) { work[(in << 1) + i__] = 1. / work[i__]; tmp = e[j] * work[(in << 1) + i__]; work[in + i__] = tmp; dpivot = d__[j + 1] - sigma - tmp * e[j]; work[i__ + 1] = dpivot; /* Computing MAX */ d__1 = dmax__, d__2 = abs(dpivot); dmax__ = max(d__1,d__2); ++j; /* L70: */ } /* check for element growth */ if (dmax__ > spdiam * 64.) { norep = TRUE_; } else { norep = FALSE_; } if (usedqd && ! norep) { /* Ensure the definiteness of the representation All entries of D (of L D L^T) must have the same sign */ i__2 = in; for (i__ = 1; i__ <= i__2; ++i__) { tmp = sgndef * work[i__]; if (tmp < 0.) { norep = TRUE_; } /* L71: */ } } if (norep) { /* Note that in the case of IRANGE=ALLRNG, we use the Gerschgorin shift which makes the matrix definite. So we should end up here really only in the case of IRANGE = VALRNG or INDRNG. */ if (idum == 5) { if (sgndef == 1.) { /* The fudged Gerschgorin shift should succeed */ sigma = gl - spdiam * 2. * eps * *n - *pivmin * 4.; } else { sigma = gu + spdiam * 2. * eps * *n + *pivmin * 4.; } } else { sigma -= sgndef * tau; tau *= 2.; } } else { /* an initial RRR is found */ goto L83; } /* L80: */ } /* if the program reaches this point, no base representation could be found in MAXTRY iterations. */ *info = 2; return 0; L83: /* At this point, we have found an initial base representation T - SIGMA I = L D L^T with not too much element growth. Store the shift. */ e[iend] = sigma; /* Store D and L. */ igraphdcopy_(&in, &work[1], &c__1, &d__[ibegin], &c__1); i__2 = in - 1; igraphdcopy_(&i__2, &work[in + 1], &c__1, &e[ibegin], &c__1); if (mb > 1) { /* Perturb each entry of the base representation by a small (but random) relative amount to overcome difficulties with glued matrices. */ for (i__ = 1; i__ <= 4; ++i__) { iseed[i__ - 1] = 1; /* L122: */ } i__2 = (in << 1) - 1; igraphdlarnv_(&c__2, iseed, &i__2, &work[1]); i__2 = in - 1; for (i__ = 1; i__ <= i__2; ++i__) { d__[ibegin + i__ - 1] *= eps * 8. * work[i__] + 1.; e[ibegin + i__ - 1] *= eps * 8. * work[in + i__] + 1.; /* L125: */ } d__[iend] *= eps * 4. * work[in] + 1.; } /* Don't update the Gerschgorin intervals because keeping track of the updates would be too much work in DLARRV. We update W instead and use it to locate the proper Gerschgorin intervals. Compute the required eigenvalues of L D L' by bisection or dqds */ if (! usedqd) { /* If DLARRD has been used, shift the eigenvalue approximations according to their representation. This is necessary for a uniform DLARRV since dqds computes eigenvalues of the shifted representation. In DLARRV, W will always hold the UNshifted eigenvalue approximation. */ i__2 = wend; for (j = wbegin; j <= i__2; ++j) { w[j] -= sigma; werr[j] += (d__1 = w[j], abs(d__1)) * eps; /* L134: */ } /* call DLARRB to reduce eigenvalue error of the approximations from DLARRD */ i__2 = iend - 1; for (i__ = ibegin; i__ <= i__2; ++i__) { /* Computing 2nd power */ d__1 = e[i__]; work[i__] = d__[i__] * (d__1 * d__1); /* L135: */ } /* use bisection to find EV from INDL to INDU */ i__2 = indl - 1; igraphdlarrb_(&in, &d__[ibegin], &work[ibegin], &indl, &indu, rtol1, rtol2, &i__2, &w[wbegin], &wgap[wbegin], &werr[wbegin], & work[(*n << 1) + 1], &iwork[1], pivmin, &spdiam, &in, & iinfo); if (iinfo != 0) { *info = -4; return 0; } /* DLARRB computes all gaps correctly except for the last one Record distance to VU/GU Computing MAX */ d__1 = 0., d__2 = *vu - sigma - (w[wend] + werr[wend]); wgap[wend] = max(d__1,d__2); i__2 = indu; for (i__ = indl; i__ <= i__2; ++i__) { ++(*m); iblock[*m] = jblk; indexw[*m] = i__; /* L138: */ } } else { /* Call dqds to get all eigs (and then possibly delete unwanted eigenvalues). Note that dqds finds the eigenvalues of the L D L^T representation of T to high relative accuracy. High relative accuracy might be lost when the shift of the RRR is subtracted to obtain the eigenvalues of T. However, T is not guaranteed to define its eigenvalues to high relative accuracy anyway. Set RTOL to the order of the tolerance used in DLASQ2 This is an ESTIMATED error, the worst case bound is 4*N*EPS which is usually too large and requires unnecessary work to be done by bisection when computing the eigenvectors */ rtol = log((doublereal) in) * 4. * eps; j = ibegin; i__2 = in - 1; for (i__ = 1; i__ <= i__2; ++i__) { work[(i__ << 1) - 1] = (d__1 = d__[j], abs(d__1)); work[i__ * 2] = e[j] * e[j] * work[(i__ << 1) - 1]; ++j; /* L140: */ } work[(in << 1) - 1] = (d__1 = d__[iend], abs(d__1)); work[in * 2] = 0.; igraphdlasq2_(&in, &work[1], &iinfo); if (iinfo != 0) { /* If IINFO = -5 then an index is part of a tight cluster and should be changed. The index is in IWORK(1) and the gap is in WORK(N+1) */ *info = -5; return 0; } else { /* Test that all eigenvalues are positive as expected */ i__2 = in; for (i__ = 1; i__ <= i__2; ++i__) { if (work[i__] < 0.) { *info = -6; return 0; } /* L149: */ } } if (sgndef > 0.) { i__2 = indu; for (i__ = indl; i__ <= i__2; ++i__) { ++(*m); w[*m] = work[in - i__ + 1]; iblock[*m] = jblk; indexw[*m] = i__; /* L150: */ } } else { i__2 = indu; for (i__ = indl; i__ <= i__2; ++i__) { ++(*m); w[*m] = -work[i__]; iblock[*m] = jblk; indexw[*m] = i__; /* L160: */ } } i__2 = *m; for (i__ = *m - mb + 1; i__ <= i__2; ++i__) { /* the value of RTOL below should be the tolerance in DLASQ2 */ werr[i__] = rtol * (d__1 = w[i__], abs(d__1)); /* L165: */ } i__2 = *m - 1; for (i__ = *m - mb + 1; i__ <= i__2; ++i__) { /* compute the right gap between the intervals Computing MAX */ d__1 = 0., d__2 = w[i__ + 1] - werr[i__ + 1] - (w[i__] + werr[ i__]); wgap[i__] = max(d__1,d__2); /* L166: */ } /* Computing MAX */ d__1 = 0., d__2 = *vu - sigma - (w[*m] + werr[*m]); wgap[*m] = max(d__1,d__2); } /* proceed with next block */ ibegin = iend + 1; wbegin = wend + 1; L170: ; } return 0; /* end of DLARRE */ } /* igraphdlarre_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dsaupd.c0000644000076500000240000007760213524616145024300 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; /* ----------------------------------------------------------------------- \BeginDoc \Name: dsaupd \Description: Reverse communication interface for the Implicitly Restarted Arnoldi Iteration. For symmetric problems this reduces to a variant of the Lanczos method. This method has been designed to compute approximations to a few eigenpairs of a linear operator OP that is real and symmetric with respect to a real positive semi-definite symmetric matrix B, i.e. B*OP = (OP')*B. Another way to express this condition is < x,OPy > = < OPx,y > where < z,w > = z'Bw . In the standard eigenproblem B is the identity matrix. ( A' denotes transpose of A) The computed approximate eigenvalues are called Ritz values and the corresponding approximate eigenvectors are called Ritz vectors. dsaupd is usually called iteratively to solve one of the following problems: Mode 1: A*x = lambda*x, A symmetric ===> OP = A and B = I. Mode 2: A*x = lambda*M*x, A symmetric, M symmetric positive definite ===> OP = inv[M]*A and B = M. ===> (If M can be factored see remark 3 below) Mode 3: K*x = lambda*M*x, K symmetric, M symmetric positive semi-definite ===> OP = (inv[K - sigma*M])*M and B = M. ===> Shift-and-Invert mode Mode 4: K*x = lambda*KG*x, K symmetric positive semi-definite, KG symmetric indefinite ===> OP = (inv[K - sigma*KG])*K and B = K. ===> Buckling mode Mode 5: A*x = lambda*M*x, A symmetric, M symmetric positive semi-definite ===> OP = inv[A - sigma*M]*[A + sigma*M] and B = M. ===> Cayley transformed mode NOTE: The action of w <- inv[A - sigma*M]*v or w <- inv[M]*v should be accomplished either by a direct method using a sparse matrix factorization and solving [A - sigma*M]*w = v or M*w = v, or through an iterative method for solving these systems. If an iterative method is used, the convergence test must be more stringent than the accuracy requirements for the eigenvalue approximations. \Usage: call dsaupd ( IDO, BMAT, N, WHICH, NEV, TOL, RESID, NCV, V, LDV, IPARAM, IPNTR, WORKD, WORKL, LWORKL, INFO ) \Arguments IDO Integer. (INPUT/OUTPUT) Reverse communication flag. IDO must be zero on the first call to dsaupd. IDO will be set internally to indicate the type of operation to be performed. Control is then given back to the calling routine which has the responsibility to carry out the requested operation and call dsaupd with the result. The operand is given in WORKD(IPNTR(1)), the result must be put in WORKD(IPNTR(2)). (If Mode = 2 see remark 5 below) ------------------------------------------------------------- IDO = 0: first call to the reverse communication interface IDO = -1: compute Y = OP * X where IPNTR(1) is the pointer into WORKD for X, IPNTR(2) is the pointer into WORKD for Y. This is for the initialization phase to force the starting vector into the range of OP. IDO = 1: compute Y = OP * X where IPNTR(1) is the pointer into WORKD for X, IPNTR(2) is the pointer into WORKD for Y. In mode 3,4 and 5, the vector B * X is already available in WORKD(ipntr(3)). It does not need to be recomputed in forming OP * X. IDO = 2: compute Y = B * X where IPNTR(1) is the pointer into WORKD for X, IPNTR(2) is the pointer into WORKD for Y. IDO = 3: compute the IPARAM(8) shifts where IPNTR(11) is the pointer into WORKL for placing the shifts. See remark 6 below. IDO = 99: done ------------------------------------------------------------- BMAT Character*1. (INPUT) BMAT specifies the type of the matrix B that defines the semi-inner product for the operator OP. B = 'I' -> standard eigenvalue problem A*x = lambda*x B = 'G' -> generalized eigenvalue problem A*x = lambda*B*x N Integer. (INPUT) Dimension of the eigenproblem. WHICH Character*2. (INPUT) Specify which of the Ritz values of OP to compute. 'LA' - compute the NEV largest (algebraic) eigenvalues. 'SA' - compute the NEV smallest (algebraic) eigenvalues. 'LM' - compute the NEV largest (in magnitude) eigenvalues. 'SM' - compute the NEV smallest (in magnitude) eigenvalues. 'BE' - compute NEV eigenvalues, half from each end of the spectrum. When NEV is odd, compute one more from the high end than from the low end. (see remark 1 below) NEV Integer. (INPUT) Number of eigenvalues of OP to be computed. 0 < NEV < N. TOL Double precision scalar. (INPUT) Stopping criterion: the relative accuracy of the Ritz value is considered acceptable if BOUNDS(I) .LE. TOL*ABS(RITZ(I)). If TOL .LE. 0. is passed a default is set: DEFAULT = DLAMCH('EPS') (machine precision as computed by the LAPACK auxiliary subroutine DLAMCH). RESID Double precision array of length N. (INPUT/OUTPUT) On INPUT: If INFO .EQ. 0, a random initial residual vector is used. If INFO .NE. 0, RESID contains the initial residual vector, possibly from a previous run. On OUTPUT: RESID contains the final residual vector. NCV Integer. (INPUT) Number of columns of the matrix V (less than or equal to N). This will indicate how many Lanczos vectors are generated at each iteration. After the startup phase in which NEV Lanczos vectors are generated, the algorithm generates NCV-NEV Lanczos vectors at each subsequent update iteration. Most of the cost in generating each Lanczos vector is in the matrix-vector product OP*x. (See remark 4 below). V Double precision N by NCV array. (OUTPUT) The NCV columns of V contain the Lanczos basis vectors. LDV Integer. (INPUT) Leading dimension of V exactly as declared in the calling program. IPARAM Integer array of length 11. (INPUT/OUTPUT) IPARAM(1) = ISHIFT: method for selecting the implicit shifts. The shifts selected at each iteration are used to restart the Arnoldi iteration in an implicit fashion. ------------------------------------------------------------- ISHIFT = 0: the shifts are provided by the user via reverse communication. The NCV eigenvalues of the current tridiagonal matrix T are returned in the part of WORKL array corresponding to RITZ. See remark 6 below. ISHIFT = 1: exact shifts with respect to the reduced tridiagonal matrix T. This is equivalent to restarting the iteration with a starting vector that is a linear combination of Ritz vectors associated with the "wanted" Ritz values. ------------------------------------------------------------- IPARAM(2) = LEVEC No longer referenced. See remark 2 below. IPARAM(3) = MXITER On INPUT: maximum number of Arnoldi update iterations allowed. On OUTPUT: actual number of Arnoldi update iterations taken. IPARAM(4) = NB: blocksize to be used in the recurrence. The code currently works only for NB = 1. IPARAM(5) = NCONV: number of "converged" Ritz values. This represents the number of Ritz values that satisfy the convergence criterion. IPARAM(6) = IUPD No longer referenced. Implicit restarting is ALWAYS used. IPARAM(7) = MODE On INPUT determines what type of eigenproblem is being solved. Must be 1,2,3,4,5; See under \Description of dsaupd for the five modes available. IPARAM(8) = NP When ido = 3 and the user provides shifts through reverse communication (IPARAM(1)=0), dsaupd returns NP, the number of shifts the user is to provide. 0 < NP <=NCV-NEV. See Remark 6 below. IPARAM(9) = NUMOP, IPARAM(10) = NUMOPB, IPARAM(11) = NUMREO, OUTPUT: NUMOP = total number of OP*x operations, NUMOPB = total number of B*x operations if BMAT='G', NUMREO = total number of steps of re-orthogonalization. IPNTR Integer array of length 11. (OUTPUT) Pointer to mark the starting locations in the WORKD and WORKL arrays for matrices/vectors used by the Lanczos iteration. ------------------------------------------------------------- IPNTR(1): pointer to the current operand vector X in WORKD. IPNTR(2): pointer to the current result vector Y in WORKD. IPNTR(3): pointer to the vector B * X in WORKD when used in the shift-and-invert mode. IPNTR(4): pointer to the next available location in WORKL that is untouched by the program. IPNTR(5): pointer to the NCV by 2 tridiagonal matrix T in WORKL. IPNTR(6): pointer to the NCV RITZ values array in WORKL. IPNTR(7): pointer to the Ritz estimates in array WORKL associated with the Ritz values located in RITZ in WORKL. IPNTR(11): pointer to the NP shifts in WORKL. See Remark 6 below. Note: IPNTR(8:10) is only referenced by dseupd. See Remark 2. IPNTR(8): pointer to the NCV RITZ values of the original system. IPNTR(9): pointer to the NCV corresponding error bounds. IPNTR(10): pointer to the NCV by NCV matrix of eigenvectors of the tridiagonal matrix T. Only referenced by dseupd if RVEC = .TRUE. See Remarks. ------------------------------------------------------------- WORKD Double precision work array of length 3*N. (REVERSE COMMUNICATION) Distributed array to be used in the basic Arnoldi iteration for reverse communication. The user should not use WORKD as temporary workspace during the iteration. Upon termination WORKD(1:N) contains B*RESID(1:N). If the Ritz vectors are desired subroutine dseupd uses this output. See Data Distribution Note below. WORKL Double precision work array of length LWORKL. (OUTPUT/WORKSPACE) Private (replicated) array on each PE or array allocated on the front end. See Data Distribution Note below. LWORKL Integer. (INPUT) LWORKL must be at least NCV**2 + 8*NCV . INFO Integer. (INPUT/OUTPUT) If INFO .EQ. 0, a randomly initial residual vector is used. If INFO .NE. 0, RESID contains the initial residual vector, possibly from a previous run. Error flag on output. = 0: Normal exit. = 1: Maximum number of iterations taken. All possible eigenvalues of OP has been found. IPARAM(5) returns the number of wanted converged Ritz values. = 2: No longer an informational error. Deprecated starting with release 2 of ARPACK. = 3: No shifts could be applied during a cycle of the Implicitly restarted Arnoldi iteration. One possibility is to increase the size of NCV relative to NEV. See remark 4 below. = -1: N must be positive. = -2: NEV must be positive. = -3: NCV must be greater than NEV and less than or equal to N. = -4: The maximum number of Arnoldi update iterations allowed must be greater than zero. = -5: WHICH must be one of 'LM', 'SM', 'LA', 'SA' or 'BE'. = -6: BMAT must be one of 'I' or 'G'. = -7: Length of private work array WORKL is not sufficient. = -8: Error return from trid. eigenvalue calculation; Informatinal error from LAPACK routine dsteqr. = -9: Starting vector is zero. = -10: IPARAM(7) must be 1,2,3,4,5. = -11: IPARAM(7) = 1 and BMAT = 'G' are incompatable. = -12: IPARAM(1) must be equal to 0 or 1. = -13: NEV and WHICH = 'BE' are incompatable. = -9999: Could not build an Arnoldi factorization. IPARAM(5) returns the size of the current Arnoldi factorization. The user is advised to check that enough workspace and array storage has been allocated. \Remarks 1. The converged Ritz values are always returned in ascending algebraic order. The computed Ritz values are approximate eigenvalues of OP. The selection of WHICH should be made with this in mind when Mode = 3,4,5. After convergence, approximate eigenvalues of the original problem may be obtained with the ARPACK subroutine dseupd. 2. If the Ritz vectors corresponding to the converged Ritz values are needed, the user must call dseupd immediately following completion of dsaupd. This is new starting with version 2.1 of ARPACK. 3. If M can be factored into a Cholesky factorization M = LL' then Mode = 2 should not be selected. Instead one should use Mode = 1 with OP = inv(L)*A*inv(L'). Appropriate triangular linear systems should be solved with L and L' rather than computing inverses. After convergence, an approximate eigenvector z of the original problem is recovered by solving L'z = x where x is a Ritz vector of OP. 4. At present there is no a-priori analysis to guide the selection of NCV relative to NEV. The only formal requrement is that NCV > NEV. However, it is recommended that NCV .ge. 2*NEV. If many problems of the same type are to be solved, one should experiment with increasing NCV while keeping NEV fixed for a given test problem. This will usually decrease the required number of OP*x operations but it also increases the work and storage required to maintain the orthogonal basis vectors. The optimal "cross-over" with respect to CPU time is problem dependent and must be determined empirically. 5. If IPARAM(7) = 2 then in the Reverse commuication interface the user must do the following. When IDO = 1, Y = OP * X is to be computed. When IPARAM(7) = 2 OP = inv(B)*A. After computing A*X the user must overwrite X with A*X. Y is then the solution to the linear set of equations B*Y = A*X. 6. When IPARAM(1) = 0, and IDO = 3, the user needs to provide the NP = IPARAM(8) shifts in locations: 1 WORKL(IPNTR(11)) 2 WORKL(IPNTR(11)+1) . . . NP WORKL(IPNTR(11)+NP-1). The eigenvalues of the current tridiagonal matrix are located in WORKL(IPNTR(6)) through WORKL(IPNTR(6)+NCV-1). They are in the order defined by WHICH. The associated Ritz estimates are located in WORKL(IPNTR(8)), WORKL(IPNTR(8)+1), ... , WORKL(IPNTR(8)+NCV-1). ----------------------------------------------------------------------- \Data Distribution Note: Fortran-D syntax: ================ REAL RESID(N), V(LDV,NCV), WORKD(3*N), WORKL(LWORKL) DECOMPOSE D1(N), D2(N,NCV) ALIGN RESID(I) with D1(I) ALIGN V(I,J) with D2(I,J) ALIGN WORKD(I) with D1(I) range (1:N) ALIGN WORKD(I) with D1(I-N) range (N+1:2*N) ALIGN WORKD(I) with D1(I-2*N) range (2*N+1:3*N) DISTRIBUTE D1(BLOCK), D2(BLOCK,:) REPLICATED WORKL(LWORKL) Cray MPP syntax: =============== REAL RESID(N), V(LDV,NCV), WORKD(N,3), WORKL(LWORKL) SHARED RESID(BLOCK), V(BLOCK,:), WORKD(BLOCK,:) REPLICATED WORKL(LWORKL) \BeginLib \References: 1. D.C. Sorensen, "Implicit Application of Polynomial Filters in a k-Step Arnoldi Method", SIAM J. Matr. Anal. Apps., 13 (1992), pp 357-385. 2. R.B. Lehoucq, "Analysis and Implementation of an Implicitly Restarted Arnoldi Iteration", Rice University Technical Report TR95-13, Department of Computational and Applied Mathematics. 3. B.N. Parlett, "The Symmetric Eigenvalue Problem". Prentice-Hall, 1980. 4. B.N. Parlett, B. Nour-Omid, "Towards a Black Box Lanczos Program", Computer Physics Communications, 53 (1989), pp 169-179. 5. B. Nour-Omid, B.N. Parlett, T. Ericson, P.S. Jensen, "How to Implement the Spectral Transformation", Math. Comp., 48 (1987), pp 663-673. 6. R.G. Grimes, J.G. Lewis and H.D. Simon, "A Shifted Block Lanczos Algorithm for Solving Sparse Symmetric Generalized Eigenproblems", SIAM J. Matr. Anal. Apps., January (1993). 7. L. Reichel, W.B. Gragg, "Algorithm 686: FORTRAN Subroutines for Updating the QR decomposition", ACM TOMS, December 1990, Volume 16 Number 4, pp 369-377. 8. R.B. Lehoucq, D.C. Sorensen, "Implementation of Some Spectral Transformations in a k-Step Arnoldi Method". In Preparation. \Routines called: dsaup2 ARPACK routine that implements the Implicitly Restarted Arnoldi Iteration. dstats ARPACK routine that initialize timing and other statistics variables. ivout ARPACK utility routine that prints integers. second ARPACK utility routine for timing. dvout ARPACK utility routine that prints vectors. dlamch LAPACK routine that determines machine constants. \Authors Danny Sorensen Phuong Vu Richard Lehoucq CRPC / Rice University Dept. of Computational & Houston, Texas Applied Mathematics Rice University Houston, Texas \Revision history: 12/15/93: Version ' 2.4' \SCCS Information: @(#) FILE: saupd.F SID: 2.7 DATE OF SID: 8/27/96 RELEASE: 2 \Remarks 1. None \EndLib ----------------------------------------------------------------------- Subroutine */ int igraphdsaupd_(integer *ido, char *bmat, integer *n, char * which, integer *nev, doublereal *tol, doublereal *resid, integer *ncv, doublereal *v, integer *ldv, integer *iparam, integer *ipntr, doublereal *workd, doublereal *workl, integer *lworkl, integer *info) { /* Format strings */ static char fmt_1000[] = "(//,5x,\002===================================" "=======\002,/5x,\002= Symmetric implicit Arnoldi update code " "=\002,/5x,\002= Version Number:\002,\002 2.4\002,19x,\002 =\002," "/5x,\002= Version Date: \002,\002 07/31/96\002,14x,\002 =\002,/" "5x,\002==========================================\002,/5x,\002= " "Summary of timing statistics =\002,/5x,\002===========" "===============================\002,//)"; static char fmt_1100[] = "(5x,\002Total number update iterations " " = \002,i5,/5x,\002Total number of OP*x operations " " = \002,i5,/5x,\002Total number of B*x operations = " "\002,i5,/5x,\002Total number of reorthogonalization steps = " "\002,i5,/5x,\002Total number of iterative refinement steps = " "\002,i5,/5x,\002Total number of restart steps = " "\002,i5,/5x,\002Total time in user OP*x operation = " "\002,f12.6,/5x,\002Total time in user B*x operation =" " \002,f12.6,/5x,\002Total time in Arnoldi update routine = " "\002,f12.6,/5x,\002Total time in saup2 routine =" " \002,f12.6,/5x,\002Total time in basic Arnoldi iteration loop = " "\002,f12.6,/5x,\002Total time in reorthogonalization phase =" " \002,f12.6,/5x,\002Total time in (re)start vector generation = " "\002,f12.6,/5x,\002Total time in trid eigenvalue subproblem =" " \002,f12.6,/5x,\002Total time in getting the shifts = " "\002,f12.6,/5x,\002Total time in applying the shifts =" " \002,f12.6,/5x,\002Total time in convergence testing = " "\002,f12.6)"; /* System generated locals */ integer v_dim1, v_offset, i__1, i__2; /* Builtin functions */ integer s_cmp(char *, char *, ftnlen, ftnlen), s_wsfe(cilist *), e_wsfe( void), do_fio(integer *, char *, ftnlen); /* Local variables */ integer j; real t0, t1; IGRAPH_F77_SAVE integer nb, ih, iq, np, iw, ldh, ldq; integer nbx = 0; IGRAPH_F77_SAVE integer nev0, mode, ierr, iupd, next; integer nopx = 0; IGRAPH_F77_SAVE integer ritz; real tmvbx; extern /* Subroutine */ int igraphdvout_(integer *, integer *, doublereal *, integer *, char *, ftnlen), igraphivout_(integer *, integer *, integer * , integer *, char *, ftnlen), igraphdsaup2_(integer *, char *, integer * , char *, integer *, integer *, doublereal *, doublereal *, integer *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, integer *); real tgetv0, tsaup2; extern doublereal igraphdlamch_(char *); extern /* Subroutine */ int igraphsecond_(real *); integer logfil, ndigit; IGRAPH_F77_SAVE integer ishift; integer nitref, msaupd = 0; IGRAPH_F77_SAVE integer bounds; real titref, tseigt, tsaupd; extern /* Subroutine */ int igraphdstats_(void); IGRAPH_F77_SAVE integer msglvl; real tsaitr = 0.0; IGRAPH_F77_SAVE integer mxiter; real tsgets, tsapps; integer nrorth = 0; real tsconv = 0.0; integer nrstrt = 0; real tmvopx = 0.0; /* Fortran I/O blocks */ static cilist io___28 = { 0, 6, 0, fmt_1000, 0 }; static cilist io___29 = { 0, 6, 0, fmt_1100, 0 }; /* %----------------------------------------------------% | Include files for debugging and timing information | %----------------------------------------------------% %------------------% | Scalar Arguments | %------------------% %-----------------% | Array Arguments | %-----------------% %------------% | Parameters | %------------% %---------------% | Local Scalars | %---------------% %----------------------% | External Subroutines | %----------------------% %--------------------% | External Functions | %--------------------% %-----------------------% | Executable Statements | %-----------------------% Parameter adjustments */ --workd; --resid; v_dim1 = *ldv; v_offset = 1 + v_dim1; v -= v_offset; --iparam; --ipntr; --workl; /* Function Body */ if (*ido == 0) { /* %-------------------------------% | Initialize timing statistics | | & message level for debugging | %-------------------------------% */ igraphdstats_(); igraphsecond_(&t0); msglvl = msaupd; ierr = 0; ishift = iparam[1]; mxiter = iparam[3]; nb = iparam[4]; /* %--------------------------------------------% | Revision 2 performs only implicit restart. | %--------------------------------------------% */ iupd = 1; mode = iparam[7]; /* %----------------% | Error checking | %----------------% */ if (*n <= 0) { ierr = -1; } else if (*nev <= 0) { ierr = -2; } else if (*ncv <= *nev || *ncv > *n) { ierr = -3; } /* %----------------------------------------------% | NP is the number of additional steps to | | extend the length NEV Lanczos factorization. | %----------------------------------------------% */ np = *ncv - *nev; if (mxiter <= 0) { ierr = -4; } if (s_cmp(which, "LM", (ftnlen)2, (ftnlen)2) != 0 && s_cmp(which, "SM", (ftnlen)2, (ftnlen)2) != 0 && s_cmp(which, "LA", ( ftnlen)2, (ftnlen)2) != 0 && s_cmp(which, "SA", (ftnlen)2, ( ftnlen)2) != 0 && s_cmp(which, "BE", (ftnlen)2, (ftnlen)2) != 0) { ierr = -5; } if (*(unsigned char *)bmat != 'I' && *(unsigned char *)bmat != 'G') { ierr = -6; } /* Computing 2nd power */ i__1 = *ncv; if (*lworkl < i__1 * i__1 + (*ncv << 3)) { ierr = -7; } if (mode < 1 || mode > 5) { ierr = -10; } else if (mode == 1 && *(unsigned char *)bmat == 'G') { ierr = -11; } else if (ishift < 0 || ishift > 1) { ierr = -12; } else if (*nev == 1 && s_cmp(which, "BE", (ftnlen)2, (ftnlen)2) == 0) { ierr = -13; } /* %------------% | Error Exit | %------------% */ if (ierr != 0) { *info = ierr; *ido = 99; goto L9000; } /* %------------------------% | Set default parameters | %------------------------% */ if (nb <= 0) { nb = 1; } if (*tol <= 0.) { *tol = igraphdlamch_("EpsMach"); } /* %----------------------------------------------% | NP is the number of additional steps to | | extend the length NEV Lanczos factorization. | | NEV0 is the local variable designating the | | size of the invariant subspace desired. | %----------------------------------------------% */ np = *ncv - *nev; nev0 = *nev; /* %-----------------------------% | Zero out internal workspace | %-----------------------------% Computing 2nd power */ i__2 = *ncv; i__1 = i__2 * i__2 + (*ncv << 3); for (j = 1; j <= i__1; ++j) { workl[j] = 0.; /* L10: */ } /* %-------------------------------------------------------% | Pointer into WORKL for address of H, RITZ, BOUNDS, Q | | etc... and the remaining workspace. | | Also update pointer to be used on output. | | Memory is laid out as follows: | | workl(1:2*ncv) := generated tridiagonal matrix | | workl(2*ncv+1:2*ncv+ncv) := ritz values | | workl(3*ncv+1:3*ncv+ncv) := computed error bounds | | workl(4*ncv+1:4*ncv+ncv*ncv) := rotation matrix Q | | workl(4*ncv+ncv*ncv+1:7*ncv+ncv*ncv) := workspace | %-------------------------------------------------------% */ ldh = *ncv; ldq = *ncv; ih = 1; ritz = ih + (ldh << 1); bounds = ritz + *ncv; iq = bounds + *ncv; /* Computing 2nd power */ i__1 = *ncv; iw = iq + i__1 * i__1; next = iw + *ncv * 3; ipntr[4] = next; ipntr[5] = ih; ipntr[6] = ritz; ipntr[7] = bounds; ipntr[11] = iw; } /* %-------------------------------------------------------% | Carry out the Implicitly restarted Lanczos Iteration. | %-------------------------------------------------------% */ igraphdsaup2_(ido, bmat, n, which, &nev0, &np, tol, &resid[1], &mode, &iupd, & ishift, &mxiter, &v[v_offset], ldv, &workl[ih], &ldh, &workl[ritz] , &workl[bounds], &workl[iq], &ldq, &workl[iw], &ipntr[1], &workd[ 1], info); /* %--------------------------------------------------% | ido .ne. 99 implies use of reverse communication | | to compute operations involving OP or shifts. | %--------------------------------------------------% */ if (*ido == 3) { iparam[8] = np; } if (*ido != 99) { goto L9000; } iparam[3] = mxiter; iparam[5] = np; iparam[9] = nopx; iparam[10] = nbx; iparam[11] = nrorth; /* %------------------------------------% | Exit if there was an informational | | error within dsaup2. | %------------------------------------% */ if (*info < 0) { goto L9000; } if (*info == 2) { *info = 3; } if (msglvl > 0) { igraphivout_(&logfil, &c__1, &mxiter, &ndigit, "_saupd: number of update i" "terations taken", (ftnlen)41); igraphivout_(&logfil, &c__1, &np, &ndigit, "_saupd: number of \"converge" "d\" Ritz values", (ftnlen)41); igraphdvout_(&logfil, &np, &workl[ritz], &ndigit, "_saupd: final Ritz valu" "es", (ftnlen)25); igraphdvout_(&logfil, &np, &workl[bounds], &ndigit, "_saupd: corresponding" " error bounds", (ftnlen)34); } igraphsecond_(&t1); tsaupd = t1 - t0; if (msglvl > 0) { /* %--------------------------------------------------------% | Version Number & Version Date are defined in version.h | %--------------------------------------------------------% */ s_wsfe(&io___28); e_wsfe(); s_wsfe(&io___29); do_fio(&c__1, (char *)&mxiter, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&nopx, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&nbx, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&nrorth, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&nitref, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&nrstrt, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&tmvopx, (ftnlen)sizeof(real)); do_fio(&c__1, (char *)&tmvbx, (ftnlen)sizeof(real)); do_fio(&c__1, (char *)&tsaupd, (ftnlen)sizeof(real)); do_fio(&c__1, (char *)&tsaup2, (ftnlen)sizeof(real)); do_fio(&c__1, (char *)&tsaitr, (ftnlen)sizeof(real)); do_fio(&c__1, (char *)&titref, (ftnlen)sizeof(real)); do_fio(&c__1, (char *)&tgetv0, (ftnlen)sizeof(real)); do_fio(&c__1, (char *)&tseigt, (ftnlen)sizeof(real)); do_fio(&c__1, (char *)&tsgets, (ftnlen)sizeof(real)); do_fio(&c__1, (char *)&tsapps, (ftnlen)sizeof(real)); do_fio(&c__1, (char *)&tsconv, (ftnlen)sizeof(real)); e_wsfe(); } L9000: return 0; /* %---------------% | End of dsaupd | %---------------% */ } /* igraphdsaupd_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dladiv.c0000644000076500000240000001407413524616145024255 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLADIV performs complex division in real arithmetic, avoiding unnecessary overflow. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLADIV + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLADIV( A, B, C, D, P, Q ) DOUBLE PRECISION A, B, C, D, P, Q > \par Purpose: ============= > > \verbatim > > DLADIV performs complex division in real arithmetic > > a + i*b > p + i*q = --------- > c + i*d > > The algorithm is due to Michael Baudin and Robert L. Smith > and can be found in the paper > "A Robust Complex Division in Scilab" > \endverbatim Arguments: ========== > \param[in] A > \verbatim > A is DOUBLE PRECISION > \endverbatim > > \param[in] B > \verbatim > B is DOUBLE PRECISION > \endverbatim > > \param[in] C > \verbatim > C is DOUBLE PRECISION > \endverbatim > > \param[in] D > \verbatim > D is DOUBLE PRECISION > The scalars a, b, c, and d in the above expression. > \endverbatim > > \param[out] P > \verbatim > P is DOUBLE PRECISION > \endverbatim > > \param[out] Q > \verbatim > Q is DOUBLE PRECISION > The scalars p and q in the above expression. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date January 2013 > \ingroup auxOTHERauxiliary ===================================================================== Subroutine */ int igraphdladiv_(doublereal *a, doublereal *b, doublereal *c__, doublereal *d__, doublereal *p, doublereal *q) { /* System generated locals */ doublereal d__1, d__2; /* Local variables */ doublereal s, aa, ab, bb, cc, cd, dd, be, un, ov, eps; extern doublereal igraphdlamch_(char *); extern /* Subroutine */ int dladiv1_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *); /* -- LAPACK auxiliary routine (version 3.5.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- January 2013 ===================================================================== */ aa = *a; bb = *b; cc = *c__; dd = *d__; /* Computing MAX */ d__1 = abs(*a), d__2 = abs(*b); ab = max(d__1,d__2); /* Computing MAX */ d__1 = abs(*c__), d__2 = abs(*d__); cd = max(d__1,d__2); s = 1.; ov = igraphdlamch_("Overflow threshold"); un = igraphdlamch_("Safe minimum"); eps = igraphdlamch_("Epsilon"); be = 2. / (eps * eps); if (ab >= ov * .5) { aa *= .5; bb *= .5; s *= 2.; } if (cd >= ov * .5) { cc *= .5; dd *= .5; s *= .5; } if (ab <= un * 2. / eps) { aa *= be; bb *= be; s /= be; } if (cd <= un * 2. / eps) { cc *= be; dd *= be; s *= be; } if (abs(*d__) <= abs(*c__)) { dladiv1_(&aa, &bb, &cc, &dd, p, q); } else { dladiv1_(&bb, &aa, &dd, &cc, p, q); *q = -(*q); } *p *= s; *q *= s; return 0; /* End of DLADIV */ } /* igraphdladiv_ Subroutine */ int dladiv1_(doublereal *a, doublereal *b, doublereal *c__, doublereal *d__, doublereal *p, doublereal *q) { doublereal r__, t; extern doublereal dladiv2_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *); /* -- LAPACK auxiliary routine (version 3.5.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- January 2013 ===================================================================== */ r__ = *d__ / *c__; t = 1. / (*c__ + *d__ * r__); *p = dladiv2_(a, b, c__, d__, &r__, &t); *a = -(*a); *q = dladiv2_(b, a, c__, d__, &r__, &t); return 0; /* End of DLADIV1 */ } /* dladiv1_ */ doublereal dladiv2_(doublereal *a, doublereal *b, doublereal *c__, doublereal *d__, doublereal *r__, doublereal *t) { /* System generated locals */ doublereal ret_val; /* Local variables */ doublereal br; /* -- LAPACK auxiliary routine (version 3.5.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- January 2013 ===================================================================== */ if (*r__ != 0.) { br = *b * *r__; if (br != 0.) { ret_val = (*a + br) * *t; } else { ret_val = *a * *t + *b * *t * *r__; } } else { ret_val = (*a + *d__ * (*b / *c__)) * *t; } return ret_val; /* End of DLADIV12 */ } /* dladiv2_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dsytd2.c0000644000076500000240000002701113524616145024216 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static doublereal c_b8 = 0.; static doublereal c_b14 = -1.; /* > \brief \b DSYTD2 reduces a symmetric matrix to real symmetric tridiagonal form by an orthogonal similarit y transformation (unblocked algorithm). =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DSYTD2 + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DSYTD2( UPLO, N, A, LDA, D, E, TAU, INFO ) CHARACTER UPLO INTEGER INFO, LDA, N DOUBLE PRECISION A( LDA, * ), D( * ), E( * ), TAU( * ) > \par Purpose: ============= > > \verbatim > > DSYTD2 reduces a real symmetric matrix A to symmetric tridiagonal > form T by an orthogonal similarity transformation: Q**T * A * Q = T. > \endverbatim Arguments: ========== > \param[in] UPLO > \verbatim > UPLO is CHARACTER*1 > Specifies whether the upper or lower triangular part of the > symmetric matrix A is stored: > = 'U': Upper triangular > = 'L': Lower triangular > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix A. N >= 0. > \endverbatim > > \param[in,out] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,N) > On entry, the symmetric matrix A. If UPLO = 'U', the leading > n-by-n upper triangular part of A contains the upper > triangular part of the matrix A, and the strictly lower > triangular part of A is not referenced. If UPLO = 'L', the > leading n-by-n lower triangular part of A contains the lower > triangular part of the matrix A, and the strictly upper > triangular part of A is not referenced. > On exit, if UPLO = 'U', the diagonal and first superdiagonal > of A are overwritten by the corresponding elements of the > tridiagonal matrix T, and the elements above the first > superdiagonal, with the array TAU, represent the orthogonal > matrix Q as a product of elementary reflectors; if UPLO > = 'L', the diagonal and first subdiagonal of A are over- > written by the corresponding elements of the tridiagonal > matrix T, and the elements below the first subdiagonal, with > the array TAU, represent the orthogonal matrix Q as a product > of elementary reflectors. See Further Details. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. LDA >= max(1,N). > \endverbatim > > \param[out] D > \verbatim > D is DOUBLE PRECISION array, dimension (N) > The diagonal elements of the tridiagonal matrix T: > D(i) = A(i,i). > \endverbatim > > \param[out] E > \verbatim > E is DOUBLE PRECISION array, dimension (N-1) > The off-diagonal elements of the tridiagonal matrix T: > E(i) = A(i,i+1) if UPLO = 'U', E(i) = A(i+1,i) if UPLO = 'L'. > \endverbatim > > \param[out] TAU > \verbatim > TAU is DOUBLE PRECISION array, dimension (N-1) > The scalar factors of the elementary reflectors (see Further > Details). > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleSYcomputational > \par Further Details: ===================== > > \verbatim > > If UPLO = 'U', the matrix Q is represented as a product of elementary > reflectors > > Q = H(n-1) . . . H(2) H(1). > > Each H(i) has the form > > H(i) = I - tau * v * v**T > > where tau is a real scalar, and v is a real vector with > v(i+1:n) = 0 and v(i) = 1; v(1:i-1) is stored on exit in > A(1:i-1,i+1), and tau in TAU(i). > > If UPLO = 'L', the matrix Q is represented as a product of elementary > reflectors > > Q = H(1) H(2) . . . H(n-1). > > Each H(i) has the form > > H(i) = I - tau * v * v**T > > where tau is a real scalar, and v is a real vector with > v(1:i) = 0 and v(i+1) = 1; v(i+2:n) is stored on exit in A(i+2:n,i), > and tau in TAU(i). > > The contents of A on exit are illustrated by the following examples > with n = 5: > > if UPLO = 'U': if UPLO = 'L': > > ( d e v2 v3 v4 ) ( d ) > ( d e v3 v4 ) ( e d ) > ( d e v4 ) ( v1 e d ) > ( d e ) ( v1 v2 e d ) > ( d ) ( v1 v2 v3 e d ) > > where d and e denote diagonal and off-diagonal elements of T, and vi > denotes an element of the vector defining H(i). > \endverbatim > ===================================================================== Subroutine */ int igraphdsytd2_(char *uplo, integer *n, doublereal *a, integer * lda, doublereal *d__, doublereal *e, doublereal *tau, integer *info) { /* System generated locals */ integer a_dim1, a_offset, i__1, i__2, i__3; /* Local variables */ integer i__; extern doublereal igraphddot_(integer *, doublereal *, integer *, doublereal *, integer *); doublereal taui; extern /* Subroutine */ int igraphdsyr2_(char *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, integer *); doublereal alpha; extern logical igraphlsame_(char *, char *); extern /* Subroutine */ int igraphdaxpy_(integer *, doublereal *, doublereal *, integer *, doublereal *, integer *); logical upper; extern /* Subroutine */ int igraphdsymv_(char *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *), igraphdlarfg_(integer *, doublereal *, doublereal *, integer *, doublereal *), igraphxerbla_(char *, integer * , ftnlen); /* -- LAPACK computational routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Test the input parameters Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --d__; --e; --tau; /* Function Body */ *info = 0; upper = igraphlsame_(uplo, "U"); if (! upper && ! igraphlsame_(uplo, "L")) { *info = -1; } else if (*n < 0) { *info = -2; } else if (*lda < max(1,*n)) { *info = -4; } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DSYTD2", &i__1, (ftnlen)6); return 0; } /* Quick return if possible */ if (*n <= 0) { return 0; } if (upper) { /* Reduce the upper triangle of A */ for (i__ = *n - 1; i__ >= 1; --i__) { /* Generate elementary reflector H(i) = I - tau * v * v**T to annihilate A(1:i-1,i+1) */ igraphdlarfg_(&i__, &a[i__ + (i__ + 1) * a_dim1], &a[(i__ + 1) * a_dim1 + 1], &c__1, &taui); e[i__] = a[i__ + (i__ + 1) * a_dim1]; if (taui != 0.) { /* Apply H(i) from both sides to A(1:i,1:i) */ a[i__ + (i__ + 1) * a_dim1] = 1.; /* Compute x := tau * A * v storing x in TAU(1:i) */ igraphdsymv_(uplo, &i__, &taui, &a[a_offset], lda, &a[(i__ + 1) * a_dim1 + 1], &c__1, &c_b8, &tau[1], &c__1); /* Compute w := x - 1/2 * tau * (x**T * v) * v */ alpha = taui * -.5 * igraphddot_(&i__, &tau[1], &c__1, &a[(i__ + 1) * a_dim1 + 1], &c__1); igraphdaxpy_(&i__, &alpha, &a[(i__ + 1) * a_dim1 + 1], &c__1, &tau[ 1], &c__1); /* Apply the transformation as a rank-2 update: A := A - v * w**T - w * v**T */ igraphdsyr2_(uplo, &i__, &c_b14, &a[(i__ + 1) * a_dim1 + 1], &c__1, &tau[1], &c__1, &a[a_offset], lda); a[i__ + (i__ + 1) * a_dim1] = e[i__]; } d__[i__ + 1] = a[i__ + 1 + (i__ + 1) * a_dim1]; tau[i__] = taui; /* L10: */ } d__[1] = a[a_dim1 + 1]; } else { /* Reduce the lower triangle of A */ i__1 = *n - 1; for (i__ = 1; i__ <= i__1; ++i__) { /* Generate elementary reflector H(i) = I - tau * v * v**T to annihilate A(i+2:n,i) */ i__2 = *n - i__; /* Computing MIN */ i__3 = i__ + 2; igraphdlarfg_(&i__2, &a[i__ + 1 + i__ * a_dim1], &a[min(i__3,*n) + i__ * a_dim1], &c__1, &taui); e[i__] = a[i__ + 1 + i__ * a_dim1]; if (taui != 0.) { /* Apply H(i) from both sides to A(i+1:n,i+1:n) */ a[i__ + 1 + i__ * a_dim1] = 1.; /* Compute x := tau * A * v storing y in TAU(i:n-1) */ i__2 = *n - i__; igraphdsymv_(uplo, &i__2, &taui, &a[i__ + 1 + (i__ + 1) * a_dim1], lda, &a[i__ + 1 + i__ * a_dim1], &c__1, &c_b8, &tau[ i__], &c__1); /* Compute w := x - 1/2 * tau * (x**T * v) * v */ i__2 = *n - i__; alpha = taui * -.5 * igraphddot_(&i__2, &tau[i__], &c__1, &a[i__ + 1 + i__ * a_dim1], &c__1); i__2 = *n - i__; igraphdaxpy_(&i__2, &alpha, &a[i__ + 1 + i__ * a_dim1], &c__1, &tau[ i__], &c__1); /* Apply the transformation as a rank-2 update: A := A - v * w**T - w * v**T */ i__2 = *n - i__; igraphdsyr2_(uplo, &i__2, &c_b14, &a[i__ + 1 + i__ * a_dim1], &c__1, &tau[i__], &c__1, &a[i__ + 1 + (i__ + 1) * a_dim1], lda); a[i__ + 1 + i__ * a_dim1] = e[i__]; } d__[i__] = a[i__ + i__ * a_dim1]; tau[i__] = taui; /* L20: */ } d__[*n] = a[*n + *n * a_dim1]; } return 0; /* End of DSYTD2 */ } /* igraphdsytd2_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dgebal.c0000644000076500000240000002664213524616145024234 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; /* > \brief \b DGEBAL =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DGEBAL + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DGEBAL( JOB, N, A, LDA, ILO, IHI, SCALE, INFO ) CHARACTER JOB INTEGER IHI, ILO, INFO, LDA, N DOUBLE PRECISION A( LDA, * ), SCALE( * ) > \par Purpose: ============= > > \verbatim > > DGEBAL balances a general real matrix A. This involves, first, > permuting A by a similarity transformation to isolate eigenvalues > in the first 1 to ILO-1 and last IHI+1 to N elements on the > diagonal; and second, applying a diagonal similarity transformation > to rows and columns ILO to IHI to make the rows and columns as > close in norm as possible. Both steps are optional. > > Balancing may reduce the 1-norm of the matrix, and improve the > accuracy of the computed eigenvalues and/or eigenvectors. > \endverbatim Arguments: ========== > \param[in] JOB > \verbatim > JOB is CHARACTER*1 > Specifies the operations to be performed on A: > = 'N': none: simply set ILO = 1, IHI = N, SCALE(I) = 1.0 > for i = 1,...,N; > = 'P': permute only; > = 'S': scale only; > = 'B': both permute and scale. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix A. N >= 0. > \endverbatim > > \param[in,out] A > \verbatim > A is DOUBLE array, dimension (LDA,N) > On entry, the input matrix A. > On exit, A is overwritten by the balanced matrix. > If JOB = 'N', A is not referenced. > See Further Details. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. LDA >= max(1,N). > \endverbatim > > \param[out] ILO > \verbatim > ILO is INTEGER > \endverbatim > \param[out] IHI > \verbatim > IHI is INTEGER > ILO and IHI are set to integers such that on exit > A(i,j) = 0 if i > j and j = 1,...,ILO-1 or I = IHI+1,...,N. > If JOB = 'N' or 'S', ILO = 1 and IHI = N. > \endverbatim > > \param[out] SCALE > \verbatim > SCALE is DOUBLE array, dimension (N) > Details of the permutations and scaling factors applied to > A. If P(j) is the index of the row and column interchanged > with row and column j and D(j) is the scaling factor > applied to row and column j, then > SCALE(j) = P(j) for j = 1,...,ILO-1 > = D(j) for j = ILO,...,IHI > = P(j) for j = IHI+1,...,N. > The order in which the interchanges are made is N to IHI+1, > then 1 to ILO-1. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit. > < 0: if INFO = -i, the i-th argument had an illegal value. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2013 > \ingroup doubleGEcomputational > \par Further Details: ===================== > > \verbatim > > The permutations consist of row and column interchanges which put > the matrix in the form > > ( T1 X Y ) > P A P = ( 0 B Z ) > ( 0 0 T2 ) > > where T1 and T2 are upper triangular matrices whose eigenvalues lie > along the diagonal. The column indices ILO and IHI mark the starting > and ending columns of the submatrix B. Balancing consists of applying > a diagonal similarity transformation inv(D) * B * D to make the > 1-norms of each row of B and its corresponding column nearly equal. > The output matrix is > > ( T1 X*D Y ) > ( 0 inv(D)*B*D inv(D)*Z ). > ( 0 0 T2 ) > > Information about the permutations P and the diagonal matrix D is > returned in the vector SCALE. > > This subroutine is based on the EISPACK routine BALANC. > > Modified by Tzu-Yi Chen, Computer Science Division, University of > California at Berkeley, USA > \endverbatim > ===================================================================== Subroutine */ int igraphdgebal_(char *job, integer *n, doublereal *a, integer * lda, integer *ilo, integer *ihi, doublereal *scale, integer *info) { /* System generated locals */ integer a_dim1, a_offset, i__1, i__2; doublereal d__1, d__2; /* Local variables */ doublereal c__, f, g; integer i__, j, k, l, m; doublereal r__, s, ca, ra; integer ica, ira, iexc; extern doublereal igraphdnrm2_(integer *, doublereal *, integer *); extern /* Subroutine */ int igraphdscal_(integer *, doublereal *, doublereal *, integer *); extern logical igraphlsame_(char *, char *); extern /* Subroutine */ int igraphdswap_(integer *, doublereal *, integer *, doublereal *, integer *); doublereal sfmin1, sfmin2, sfmax1, sfmax2; extern doublereal igraphdlamch_(char *); extern integer igraphidamax_(integer *, doublereal *, integer *); extern logical igraphdisnan_(doublereal *); extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); logical noconv; /* -- LAPACK computational routine (version 3.5.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2013 ===================================================================== Test the input parameters Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --scale; /* Function Body */ *info = 0; if (! igraphlsame_(job, "N") && ! igraphlsame_(job, "P") && ! igraphlsame_(job, "S") && ! igraphlsame_(job, "B")) { *info = -1; } else if (*n < 0) { *info = -2; } else if (*lda < max(1,*n)) { *info = -4; } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DGEBAL", &i__1, (ftnlen)6); return 0; } k = 1; l = *n; if (*n == 0) { goto L210; } if (igraphlsame_(job, "N")) { i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { scale[i__] = 1.; /* L10: */ } goto L210; } if (igraphlsame_(job, "S")) { goto L120; } /* Permutation to isolate eigenvalues if possible */ goto L50; /* Row and column exchange. */ L20: scale[m] = (doublereal) j; if (j == m) { goto L30; } igraphdswap_(&l, &a[j * a_dim1 + 1], &c__1, &a[m * a_dim1 + 1], &c__1); i__1 = *n - k + 1; igraphdswap_(&i__1, &a[j + k * a_dim1], lda, &a[m + k * a_dim1], lda); L30: switch (iexc) { case 1: goto L40; case 2: goto L80; } /* Search for rows isolating an eigenvalue and push them down. */ L40: if (l == 1) { goto L210; } --l; L50: for (j = l; j >= 1; --j) { i__1 = l; for (i__ = 1; i__ <= i__1; ++i__) { if (i__ == j) { goto L60; } if (a[j + i__ * a_dim1] != 0.) { goto L70; } L60: ; } m = l; iexc = 1; goto L20; L70: ; } goto L90; /* Search for columns isolating an eigenvalue and push them left. */ L80: ++k; L90: i__1 = l; for (j = k; j <= i__1; ++j) { i__2 = l; for (i__ = k; i__ <= i__2; ++i__) { if (i__ == j) { goto L100; } if (a[i__ + j * a_dim1] != 0.) { goto L110; } L100: ; } m = k; iexc = 2; goto L20; L110: ; } L120: i__1 = l; for (i__ = k; i__ <= i__1; ++i__) { scale[i__] = 1.; /* L130: */ } if (igraphlsame_(job, "P")) { goto L210; } /* Balance the submatrix in rows K to L. Iterative loop for norm reduction */ sfmin1 = igraphdlamch_("S") / igraphdlamch_("P"); sfmax1 = 1. / sfmin1; sfmin2 = sfmin1 * 2.; sfmax2 = 1. / sfmin2; L140: noconv = FALSE_; i__1 = l; for (i__ = k; i__ <= i__1; ++i__) { i__2 = l - k + 1; c__ = igraphdnrm2_(&i__2, &a[k + i__ * a_dim1], &c__1); i__2 = l - k + 1; r__ = igraphdnrm2_(&i__2, &a[i__ + k * a_dim1], lda); ica = igraphidamax_(&l, &a[i__ * a_dim1 + 1], &c__1); ca = (d__1 = a[ica + i__ * a_dim1], abs(d__1)); i__2 = *n - k + 1; ira = igraphidamax_(&i__2, &a[i__ + k * a_dim1], lda); ra = (d__1 = a[i__ + (ira + k - 1) * a_dim1], abs(d__1)); /* Guard against zero C or R due to underflow. */ if (c__ == 0. || r__ == 0.) { goto L200; } g = r__ / 2.; f = 1.; s = c__ + r__; L160: /* Computing MAX */ d__1 = max(f,c__); /* Computing MIN */ d__2 = min(r__,g); if (c__ >= g || max(d__1,ca) >= sfmax2 || min(d__2,ra) <= sfmin2) { goto L170; } d__1 = c__ + f + ca + r__ + g + ra; if (igraphdisnan_(&d__1)) { /* Exit if NaN to avoid infinite loop */ *info = -3; i__2 = -(*info); igraphxerbla_("DGEBAL", &i__2, (ftnlen)6); return 0; } f *= 2.; c__ *= 2.; ca *= 2.; r__ /= 2.; g /= 2.; ra /= 2.; goto L160; L170: g = c__ / 2.; L180: /* Computing MIN */ d__1 = min(f,c__), d__1 = min(d__1,g); if (g < r__ || max(r__,ra) >= sfmax2 || min(d__1,ca) <= sfmin2) { goto L190; } f /= 2.; c__ /= 2.; g /= 2.; ca /= 2.; r__ *= 2.; ra *= 2.; goto L180; /* Now balance. */ L190: if (c__ + r__ >= s * .95) { goto L200; } if (f < 1. && scale[i__] < 1.) { if (f * scale[i__] <= sfmin1) { goto L200; } } if (f > 1. && scale[i__] > 1.) { if (scale[i__] >= sfmax1 / f) { goto L200; } } g = 1. / f; scale[i__] *= f; noconv = TRUE_; i__2 = *n - k + 1; igraphdscal_(&i__2, &g, &a[i__ + k * a_dim1], lda); igraphdscal_(&l, &f, &a[i__ * a_dim1 + 1], &c__1); L200: ; } if (noconv) { goto L140; } L210: *ilo = k; *ihi = l; return 0; /* End of DGEBAL */ } /* igraphdgebal_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dstatn.c0000644000076500000240000000416113524616145024303 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* %---------------------------------------------% | Initialize statistic and timing information | | for nonsymmetric Arnoldi code. | %---------------------------------------------% \Author Danny Sorensen Phuong Vu Richard Lehoucq CRPC / Rice University Dept. of Computational & Houston, Texas Applied Mathematics Rice University Houston, Texas \SCCS Information: @(#) FILE: statn.F SID: 2.4 DATE OF SID: 4/20/96 RELEASE: 2 Subroutine */ int igraphdstatn_(void) { integer nbx, nopx; real trvec, tmvbx, tnaup2, tgetv0, tneigh; integer nitref; real tnaupd, titref, tnaitr, tngets, tnapps, tnconv; integer nrorth, nrstrt; real tmvopx; /* %--------------------------------% | See stat.doc for documentation | %--------------------------------% %-----------------------% | Executable Statements | %-----------------------% */ nopx = 0; nbx = 0; nrorth = 0; nitref = 0; nrstrt = 0; tnaupd = 0.f; tnaup2 = 0.f; tnaitr = 0.f; tneigh = 0.f; tngets = 0.f; tnapps = 0.f; tnconv = 0.f; titref = 0.f; tgetv0 = 0.f; trvec = 0.f; /* %----------------------------------------------------% | User time including reverse communication overhead | %----------------------------------------------------% */ tmvopx = 0.f; tmvbx = 0.f; return 0; /* %---------------% | End of dstatn | %---------------% */ } /* igraphdstatn_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dger.c0000644000076500000240000001133713524616145023732 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Subroutine */ int igraphdger_(integer *m, integer *n, doublereal *alpha, doublereal *x, integer *incx, doublereal *y, integer *incy, doublereal *a, integer *lda) { /* System generated locals */ integer a_dim1, a_offset, i__1, i__2; /* Local variables */ integer i__, j, ix, jy, kx, info; doublereal temp; extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); /* Purpose ======= DGER performs the rank 1 operation A := alpha*x*y**T + A, where alpha is a scalar, x is an m element vector, y is an n element vector and A is an m by n matrix. Arguments ========== M - INTEGER. On entry, M specifies the number of rows of the matrix A. M must be at least zero. Unchanged on exit. N - INTEGER. On entry, N specifies the number of columns of the matrix A. N must be at least zero. Unchanged on exit. ALPHA - DOUBLE PRECISION. On entry, ALPHA specifies the scalar alpha. Unchanged on exit. X - DOUBLE PRECISION array of dimension at least ( 1 + ( m - 1 )*abs( INCX ) ). Before entry, the incremented array X must contain the m element vector x. Unchanged on exit. INCX - INTEGER. On entry, INCX specifies the increment for the elements of X. INCX must not be zero. Unchanged on exit. Y - DOUBLE PRECISION array of dimension at least ( 1 + ( n - 1 )*abs( INCY ) ). Before entry, the incremented array Y must contain the n element vector y. Unchanged on exit. INCY - INTEGER. On entry, INCY specifies the increment for the elements of Y. INCY must not be zero. Unchanged on exit. A - DOUBLE PRECISION array of DIMENSION ( LDA, n ). Before entry, the leading m by n part of the array A must contain the matrix of coefficients. On exit, A is overwritten by the updated matrix. LDA - INTEGER. On entry, LDA specifies the first dimension of A as declared in the calling (sub) program. LDA must be at least max( 1, m ). Unchanged on exit. Further Details =============== Level 2 Blas routine. -- Written on 22-October-1986. Jack Dongarra, Argonne National Lab. Jeremy Du Croz, Nag Central Office. Sven Hammarling, Nag Central Office. Richard Hanson, Sandia National Labs. ===================================================================== Test the input parameters. Parameter adjustments */ --x; --y; a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; /* Function Body */ info = 0; if (*m < 0) { info = 1; } else if (*n < 0) { info = 2; } else if (*incx == 0) { info = 5; } else if (*incy == 0) { info = 7; } else if (*lda < max(1,*m)) { info = 9; } if (info != 0) { igraphxerbla_("DGER ", &info, (ftnlen)6); return 0; } /* Quick return if possible. */ if (*m == 0 || *n == 0 || *alpha == 0.) { return 0; } /* Start the operations. In this version the elements of A are accessed sequentially with one pass through A. */ if (*incy > 0) { jy = 1; } else { jy = 1 - (*n - 1) * *incy; } if (*incx == 1) { i__1 = *n; for (j = 1; j <= i__1; ++j) { if (y[jy] != 0.) { temp = *alpha * y[jy]; i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { a[i__ + j * a_dim1] += x[i__] * temp; /* L10: */ } } jy += *incy; /* L20: */ } } else { if (*incx > 0) { kx = 1; } else { kx = 1 - (*m - 1) * *incx; } i__1 = *n; for (j = 1; j <= i__1; ++j) { if (y[jy] != 0.) { temp = *alpha * y[jy]; ix = kx; i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { a[i__ + j * a_dim1] += x[ix] * temp; ix += *incx; /* L30: */ } } jy += *incy; /* L40: */ } } return 0; /* End of DGER . */ } /* igraphdger_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dormql.c0000644000076500000240000002640113524616145024305 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static integer c_n1 = -1; static integer c__2 = 2; static integer c__65 = 65; /* > \brief \b DORMQL =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DORMQL + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DORMQL( SIDE, TRANS, M, N, K, A, LDA, TAU, C, LDC, WORK, LWORK, INFO ) CHARACTER SIDE, TRANS INTEGER INFO, K, LDA, LDC, LWORK, M, N DOUBLE PRECISION A( LDA, * ), C( LDC, * ), TAU( * ), WORK( * ) > \par Purpose: ============= > > \verbatim > > DORMQL overwrites the general real M-by-N matrix C with > > SIDE = 'L' SIDE = 'R' > TRANS = 'N': Q * C C * Q > TRANS = 'T': Q**T * C C * Q**T > > where Q is a real orthogonal matrix defined as the product of k > elementary reflectors > > Q = H(k) . . . H(2) H(1) > > as returned by DGEQLF. Q is of order M if SIDE = 'L' and of order N > if SIDE = 'R'. > \endverbatim Arguments: ========== > \param[in] SIDE > \verbatim > SIDE is CHARACTER*1 > = 'L': apply Q or Q**T from the Left; > = 'R': apply Q or Q**T from the Right. > \endverbatim > > \param[in] TRANS > \verbatim > TRANS is CHARACTER*1 > = 'N': No transpose, apply Q; > = 'T': Transpose, apply Q**T. > \endverbatim > > \param[in] M > \verbatim > M is INTEGER > The number of rows of the matrix C. M >= 0. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The number of columns of the matrix C. N >= 0. > \endverbatim > > \param[in] K > \verbatim > K is INTEGER > The number of elementary reflectors whose product defines > the matrix Q. > If SIDE = 'L', M >= K >= 0; > if SIDE = 'R', N >= K >= 0. > \endverbatim > > \param[in] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,K) > The i-th column must contain the vector which defines the > elementary reflector H(i), for i = 1,2,...,k, as returned by > DGEQLF in the last k columns of its array argument A. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. > If SIDE = 'L', LDA >= max(1,M); > if SIDE = 'R', LDA >= max(1,N). > \endverbatim > > \param[in] TAU > \verbatim > TAU is DOUBLE PRECISION array, dimension (K) > TAU(i) must contain the scalar factor of the elementary > reflector H(i), as returned by DGEQLF. > \endverbatim > > \param[in,out] C > \verbatim > C is DOUBLE PRECISION array, dimension (LDC,N) > On entry, the M-by-N matrix C. > On exit, C is overwritten by Q*C or Q**T*C or C*Q**T or C*Q. > \endverbatim > > \param[in] LDC > \verbatim > LDC is INTEGER > The leading dimension of the array C. LDC >= max(1,M). > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (MAX(1,LWORK)) > On exit, if INFO = 0, WORK(1) returns the optimal LWORK. > \endverbatim > > \param[in] LWORK > \verbatim > LWORK is INTEGER > The dimension of the array WORK. > If SIDE = 'L', LWORK >= max(1,N); > if SIDE = 'R', LWORK >= max(1,M). > For optimum performance LWORK >= N*NB if SIDE = 'L', and > LWORK >= M*NB if SIDE = 'R', where NB is the optimal > blocksize. > > If LWORK = -1, then a workspace query is assumed; the routine > only calculates the optimal size of the WORK array, returns > this value as the first entry of the WORK array, and no error > message related to LWORK is issued by XERBLA. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2011 > \ingroup doubleOTHERcomputational ===================================================================== Subroutine */ int igraphdormql_(char *side, char *trans, integer *m, integer *n, integer *k, doublereal *a, integer *lda, doublereal *tau, doublereal * c__, integer *ldc, doublereal *work, integer *lwork, integer *info) { /* System generated locals */ address a__1[2]; integer a_dim1, a_offset, c_dim1, c_offset, i__1, i__2, i__3[2], i__4, i__5; char ch__1[2]; /* Builtin functions Subroutine */ int s_cat(char *, char **, integer *, integer *, ftnlen); /* Local variables */ integer i__; doublereal t[4160] /* was [65][64] */; integer i1, i2, i3, ib, nb, mi, ni, nq, nw, iws; logical left; extern logical igraphlsame_(char *, char *); integer nbmin, iinfo; extern /* Subroutine */ int igraphdorm2l_(char *, char *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *), igraphdlarfb_(char *, char *, char *, char *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, integer *), igraphdlarft_(char *, char *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *), igraphxerbla_(char *, integer *, ftnlen); extern integer igraphilaenv_(integer *, char *, char *, integer *, integer *, integer *, integer *, ftnlen, ftnlen); logical notran; integer ldwork, lwkopt; logical lquery; /* -- LAPACK computational routine (version 3.4.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2011 ===================================================================== Test the input arguments Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --tau; c_dim1 = *ldc; c_offset = 1 + c_dim1; c__ -= c_offset; --work; /* Function Body */ *info = 0; left = igraphlsame_(side, "L"); notran = igraphlsame_(trans, "N"); lquery = *lwork == -1; /* NQ is the order of Q and NW is the minimum dimension of WORK */ if (left) { nq = *m; nw = max(1,*n); } else { nq = *n; nw = max(1,*m); } if (! left && ! igraphlsame_(side, "R")) { *info = -1; } else if (! notran && ! igraphlsame_(trans, "T")) { *info = -2; } else if (*m < 0) { *info = -3; } else if (*n < 0) { *info = -4; } else if (*k < 0 || *k > nq) { *info = -5; } else if (*lda < max(1,nq)) { *info = -7; } else if (*ldc < max(1,*m)) { *info = -10; } if (*info == 0) { if (*m == 0 || *n == 0) { lwkopt = 1; } else { /* Determine the block size. NB may be at most NBMAX, where NBMAX is used to define the local array T. Computing MIN Writing concatenation */ i__3[0] = 1, a__1[0] = side; i__3[1] = 1, a__1[1] = trans; s_cat(ch__1, a__1, i__3, &c__2, (ftnlen)2); i__1 = 64, i__2 = igraphilaenv_(&c__1, "DORMQL", ch__1, m, n, k, &c_n1, (ftnlen)6, (ftnlen)2); nb = min(i__1,i__2); lwkopt = nw * nb; } work[1] = (doublereal) lwkopt; if (*lwork < nw && ! lquery) { *info = -12; } } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DORMQL", &i__1, (ftnlen)6); return 0; } else if (lquery) { return 0; } /* Quick return if possible */ if (*m == 0 || *n == 0) { return 0; } nbmin = 2; ldwork = nw; if (nb > 1 && nb < *k) { iws = nw * nb; if (*lwork < iws) { nb = *lwork / ldwork; /* Computing MAX Writing concatenation */ i__3[0] = 1, a__1[0] = side; i__3[1] = 1, a__1[1] = trans; s_cat(ch__1, a__1, i__3, &c__2, (ftnlen)2); i__1 = 2, i__2 = igraphilaenv_(&c__2, "DORMQL", ch__1, m, n, k, &c_n1, ( ftnlen)6, (ftnlen)2); nbmin = max(i__1,i__2); } } else { iws = nw; } if (nb < nbmin || nb >= *k) { /* Use unblocked code */ igraphdorm2l_(side, trans, m, n, k, &a[a_offset], lda, &tau[1], &c__[ c_offset], ldc, &work[1], &iinfo); } else { /* Use blocked code */ if (left && notran || ! left && ! notran) { i1 = 1; i2 = *k; i3 = nb; } else { i1 = (*k - 1) / nb * nb + 1; i2 = 1; i3 = -nb; } if (left) { ni = *n; } else { mi = *m; } i__1 = i2; i__2 = i3; for (i__ = i1; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ += i__2) { /* Computing MIN */ i__4 = nb, i__5 = *k - i__ + 1; ib = min(i__4,i__5); /* Form the triangular factor of the block reflector H = H(i+ib-1) . . . H(i+1) H(i) */ i__4 = nq - *k + i__ + ib - 1; igraphdlarft_("Backward", "Columnwise", &i__4, &ib, &a[i__ * a_dim1 + 1] , lda, &tau[i__], t, &c__65); if (left) { /* H or H**T is applied to C(1:m-k+i+ib-1,1:n) */ mi = *m - *k + i__ + ib - 1; } else { /* H or H**T is applied to C(1:m,1:n-k+i+ib-1) */ ni = *n - *k + i__ + ib - 1; } /* Apply H or H**T */ igraphdlarfb_(side, trans, "Backward", "Columnwise", &mi, &ni, &ib, &a[ i__ * a_dim1 + 1], lda, t, &c__65, &c__[c_offset], ldc, & work[1], &ldwork); /* L10: */ } } work[1] = (doublereal) lwkopt; return 0; /* End of DORMQL */ } /* igraphdormql_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dstqrb.c0000644000076500000240000004211513524616145024306 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__0 = 0; static integer c__1 = 1; static doublereal c_b31 = 1.; /* ----------------------------------------------------------------------- \BeginDoc \Name: dstqrb \Description: Computes all eigenvalues and the last component of the eigenvectors of a symmetric tridiagonal matrix using the implicit QL or QR method. This is mostly a modification of the LAPACK routine dsteqr. See Remarks. \Usage: call dstqrb ( N, D, E, Z, WORK, INFO ) \Arguments N Integer. (INPUT) The number of rows and columns in the matrix. N >= 0. D Double precision array, dimension (N). (INPUT/OUTPUT) On entry, D contains the diagonal elements of the tridiagonal matrix. On exit, D contains the eigenvalues, in ascending order. If an error exit is made, the eigenvalues are correct for indices 1,2,...,INFO-1, but they are unordered and may not be the smallest eigenvalues of the matrix. E Double precision array, dimension (N-1). (INPUT/OUTPUT) On entry, E contains the subdiagonal elements of the tridiagonal matrix in positions 1 through N-1. On exit, E has been destroyed. Z Double precision array, dimension (N). (OUTPUT) On exit, Z contains the last row of the orthonormal eigenvector matrix of the symmetric tridiagonal matrix. If an error exit is made, Z contains the last row of the eigenvector matrix associated with the stored eigenvalues. WORK Double precision array, dimension (max(1,2*N-2)). (WORKSPACE) Workspace used in accumulating the transformation for computing the last components of the eigenvectors. INFO Integer. (OUTPUT) = 0: normal return. < 0: if INFO = -i, the i-th argument had an illegal value. > 0: if INFO = +i, the i-th eigenvalue has not converged after a total of 30*N iterations. \Remarks 1. None. ----------------------------------------------------------------------- \BeginLib \Local variables: xxxxxx real \Routines called: daxpy Level 1 BLAS that computes a vector triad. dcopy Level 1 BLAS that copies one vector to another. dswap Level 1 BLAS that swaps the contents of two vectors. lsame LAPACK character comparison routine. dlae2 LAPACK routine that computes the eigenvalues of a 2-by-2 symmetric matrix. dlaev2 LAPACK routine that eigendecomposition of a 2-by-2 symmetric matrix. dlamch LAPACK routine that determines machine constants. dlanst LAPACK routine that computes the norm of a matrix. dlapy2 LAPACK routine to compute sqrt(x**2+y**2) carefully. dlartg LAPACK Givens rotation construction routine. dlascl LAPACK routine for careful scaling of a matrix. dlaset LAPACK matrix initialization routine. dlasr LAPACK routine that applies an orthogonal transformation to a matrix. dlasrt LAPACK sorting routine. dsteqr LAPACK routine that computes eigenvalues and eigenvectors of a symmetric tridiagonal matrix. xerbla LAPACK error handler routine. \Authors Danny Sorensen Phuong Vu Richard Lehoucq CRPC / Rice University Dept. of Computational & Houston, Texas Applied Mathematics Rice University Houston, Texas \SCCS Information: @(#) FILE: stqrb.F SID: 2.5 DATE OF SID: 8/27/96 RELEASE: 2 \Remarks 1. Starting with version 2.5, this routine is a modified version of LAPACK version 2.0 subroutine SSTEQR. No lines are deleted, only commeted out and new lines inserted. All lines commented out have "c$$$" at the beginning. Note that the LAPACK version 1.0 subroutine SSTEQR contained bugs. \EndLib ----------------------------------------------------------------------- Subroutine */ int igraphdstqrb_(integer *n, doublereal *d__, doublereal *e, doublereal *z__, doublereal *work, integer *info) { /* System generated locals */ integer i__1, i__2; doublereal d__1, d__2; /* Builtin functions */ double sqrt(doublereal), d_sign(doublereal *, doublereal *); /* Local variables */ doublereal b, c__, f, g; integer i__, j, k, l, m; doublereal p, r__, s; integer l1, ii, mm, lm1, mm1, nm1; doublereal rt1, rt2, eps; integer lsv; doublereal tst, eps2; integer lend, jtot; extern /* Subroutine */ int igraphdlae2_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *), igraphdlasr_(char *, char *, char *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *); doublereal anorm; extern /* Subroutine */ int igraphdlaev2_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *); integer lendm1, lendp1; extern doublereal igraphdlapy2_(doublereal *, doublereal *), igraphdlamch_(char *); integer iscale; extern /* Subroutine */ int igraphdlascl_(char *, integer *, integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, integer *, integer *); doublereal safmin; extern /* Subroutine */ int igraphdlartg_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *); doublereal safmax; extern doublereal igraphdlanst_(char *, integer *, doublereal *, doublereal *); extern /* Subroutine */ int igraphdlasrt_(char *, integer *, doublereal *, integer *); integer lendsv, nmaxit, icompz; doublereal ssfmax, ssfmin; /* %------------------% | Scalar Arguments | %------------------% %-----------------% | Array Arguments | %-----------------% test the input parameters. Parameter adjustments */ --work; --z__; --e; --d__; /* Function Body */ *info = 0; /* $$$ IF( LSAME( COMPZ, 'N' ) ) THEN $$$ ICOMPZ = 0 $$$ ELSE IF( LSAME( COMPZ, 'V' ) ) THEN $$$ ICOMPZ = 1 $$$ ELSE IF( LSAME( COMPZ, 'I' ) ) THEN $$$ ICOMPZ = 2 $$$ ELSE $$$ ICOMPZ = -1 $$$ END IF $$$ IF( ICOMPZ.LT.0 ) THEN $$$ INFO = -1 $$$ ELSE IF( N.LT.0 ) THEN $$$ INFO = -2 $$$ ELSE IF( ( LDZ.LT.1 ) .OR. ( ICOMPZ.GT.0 .AND. LDZ.LT.MAX( 1, $$$ $ N ) ) ) THEN $$$ INFO = -6 $$$ END IF $$$ IF( INFO.NE.0 ) THEN $$$ CALL XERBLA( 'SSTEQR', -INFO ) $$$ RETURN $$$ END IF *** New starting with version 2.5 *** */ icompz = 2; /* ************************************* quick return if possible */ if (*n == 0) { return 0; } if (*n == 1) { if (icompz == 2) { z__[1] = 1.; } return 0; } /* determine the unit roundoff and over/underflow thresholds. */ eps = igraphdlamch_("e"); /* Computing 2nd power */ d__1 = eps; eps2 = d__1 * d__1; safmin = igraphdlamch_("s"); safmax = 1. / safmin; ssfmax = sqrt(safmax) / 3.; ssfmin = sqrt(safmin) / eps2; /* compute the eigenvalues and eigenvectors of the tridiagonal matrix. $$ if( icompz.eq.2 ) $$$ $ call dlaset( 'full', n, n, zero, one, z, ldz ) *** New starting with version 2.5 *** */ if (icompz == 2) { i__1 = *n - 1; for (j = 1; j <= i__1; ++j) { z__[j] = 0.; /* L5: */ } z__[*n] = 1.; } /* ************************************* */ nmaxit = *n * 30; jtot = 0; /* determine where the matrix splits and choose ql or qr iteration for each block, according to whether top or bottom diagonal element is smaller. */ l1 = 1; nm1 = *n - 1; L10: if (l1 > *n) { goto L160; } if (l1 > 1) { e[l1 - 1] = 0.; } if (l1 <= nm1) { i__1 = nm1; for (m = l1; m <= i__1; ++m) { tst = (d__1 = e[m], abs(d__1)); if (tst == 0.) { goto L30; } if (tst <= sqrt((d__1 = d__[m], abs(d__1))) * sqrt((d__2 = d__[m + 1], abs(d__2))) * eps) { e[m] = 0.; goto L30; } /* L20: */ } } m = *n; L30: l = l1; lsv = l; lend = m; lendsv = lend; l1 = m + 1; if (lend == l) { goto L10; } /* scale submatrix in rows and columns l to lend */ i__1 = lend - l + 1; anorm = igraphdlanst_("i", &i__1, &d__[l], &e[l]); iscale = 0; if (anorm == 0.) { goto L10; } if (anorm > ssfmax) { iscale = 1; i__1 = lend - l + 1; igraphdlascl_("g", &c__0, &c__0, &anorm, &ssfmax, &i__1, &c__1, &d__[l], n, info); i__1 = lend - l; igraphdlascl_("g", &c__0, &c__0, &anorm, &ssfmax, &i__1, &c__1, &e[l], n, info); } else if (anorm < ssfmin) { iscale = 2; i__1 = lend - l + 1; igraphdlascl_("g", &c__0, &c__0, &anorm, &ssfmin, &i__1, &c__1, &d__[l], n, info); i__1 = lend - l; igraphdlascl_("g", &c__0, &c__0, &anorm, &ssfmin, &i__1, &c__1, &e[l], n, info); } /* choose between ql and qr iteration */ if ((d__1 = d__[lend], abs(d__1)) < (d__2 = d__[l], abs(d__2))) { lend = lsv; l = lendsv; } if (lend > l) { /* ql iteration look for small subdiagonal element. */ L40: if (l != lend) { lendm1 = lend - 1; i__1 = lendm1; for (m = l; m <= i__1; ++m) { /* Computing 2nd power */ d__2 = (d__1 = e[m], abs(d__1)); tst = d__2 * d__2; if (tst <= eps2 * (d__1 = d__[m], abs(d__1)) * (d__2 = d__[m + 1], abs(d__2)) + safmin) { goto L60; } /* L50: */ } } m = lend; L60: if (m < lend) { e[m] = 0.; } p = d__[l]; if (m == l) { goto L80; } /* if remaining matrix is 2-by-2, use dlae2 or dlaev2 to compute its eigensystem. */ if (m == l + 1) { if (icompz > 0) { igraphdlaev2_(&d__[l], &e[l], &d__[l + 1], &rt1, &rt2, &c__, &s); work[l] = c__; work[*n - 1 + l] = s; /* $$$ call dlasr( 'r', 'v', 'b', n, 2, work( l ), $$$ $ work( n-1+l ), z( 1, l ), ldz ) *** New starting with version 2.5 *** */ tst = z__[l + 1]; z__[l + 1] = c__ * tst - s * z__[l]; z__[l] = s * tst + c__ * z__[l]; /* ************************************* */ } else { igraphdlae2_(&d__[l], &e[l], &d__[l + 1], &rt1, &rt2); } d__[l] = rt1; d__[l + 1] = rt2; e[l] = 0.; l += 2; if (l <= lend) { goto L40; } goto L140; } if (jtot == nmaxit) { goto L140; } ++jtot; /* form shift. */ g = (d__[l + 1] - p) / (e[l] * 2.); r__ = igraphdlapy2_(&g, &c_b31); g = d__[m] - p + e[l] / (g + d_sign(&r__, &g)); s = 1.; c__ = 1.; p = 0.; /* inner loop */ mm1 = m - 1; i__1 = l; for (i__ = mm1; i__ >= i__1; --i__) { f = s * e[i__]; b = c__ * e[i__]; igraphdlartg_(&g, &f, &c__, &s, &r__); if (i__ != m - 1) { e[i__ + 1] = r__; } g = d__[i__ + 1] - p; r__ = (d__[i__] - g) * s + c__ * 2. * b; p = s * r__; d__[i__ + 1] = g + p; g = c__ * r__ - b; /* if eigenvectors are desired, then save rotations. */ if (icompz > 0) { work[i__] = c__; work[*n - 1 + i__] = -s; } /* L70: */ } /* if eigenvectors are desired, then apply saved rotations. */ if (icompz > 0) { mm = m - l + 1; /* $$$ call dlasr( 'r', 'v', 'b', n, mm, work( l ), work( n-1+l ), $$$ $ z( 1, l ), ldz ) *** New starting with version 2.5 *** */ igraphdlasr_("r", "v", "b", &c__1, &mm, &work[l], &work[*n - 1 + l], & z__[l], &c__1); /* ************************************* */ } d__[l] -= p; e[l] = g; goto L40; /* eigenvalue found. */ L80: d__[l] = p; ++l; if (l <= lend) { goto L40; } goto L140; } else { /* qr iteration look for small superdiagonal element. */ L90: if (l != lend) { lendp1 = lend + 1; i__1 = lendp1; for (m = l; m >= i__1; --m) { /* Computing 2nd power */ d__2 = (d__1 = e[m - 1], abs(d__1)); tst = d__2 * d__2; if (tst <= eps2 * (d__1 = d__[m], abs(d__1)) * (d__2 = d__[m - 1], abs(d__2)) + safmin) { goto L110; } /* L100: */ } } m = lend; L110: if (m > lend) { e[m - 1] = 0.; } p = d__[l]; if (m == l) { goto L130; } /* if remaining matrix is 2-by-2, use dlae2 or dlaev2 to compute its eigensystem. */ if (m == l - 1) { if (icompz > 0) { igraphdlaev2_(&d__[l - 1], &e[l - 1], &d__[l], &rt1, &rt2, &c__, &s) ; /* $$$ work( m ) = c $$$ work( n-1+m ) = s $$$ call dlasr( 'r', 'v', 'f', n, 2, work( m ), $$$ $ work( n-1+m ), z( 1, l-1 ), ldz ) *** New starting with version 2.5 *** */ tst = z__[l]; z__[l] = c__ * tst - s * z__[l - 1]; z__[l - 1] = s * tst + c__ * z__[l - 1]; /* ************************************* */ } else { igraphdlae2_(&d__[l - 1], &e[l - 1], &d__[l], &rt1, &rt2); } d__[l - 1] = rt1; d__[l] = rt2; e[l - 1] = 0.; l += -2; if (l >= lend) { goto L90; } goto L140; } if (jtot == nmaxit) { goto L140; } ++jtot; /* form shift. */ g = (d__[l - 1] - p) / (e[l - 1] * 2.); r__ = igraphdlapy2_(&g, &c_b31); g = d__[m] - p + e[l - 1] / (g + d_sign(&r__, &g)); s = 1.; c__ = 1.; p = 0.; /* inner loop */ lm1 = l - 1; i__1 = lm1; for (i__ = m; i__ <= i__1; ++i__) { f = s * e[i__]; b = c__ * e[i__]; igraphdlartg_(&g, &f, &c__, &s, &r__); if (i__ != m) { e[i__ - 1] = r__; } g = d__[i__] - p; r__ = (d__[i__ + 1] - g) * s + c__ * 2. * b; p = s * r__; d__[i__] = g + p; g = c__ * r__ - b; /* if eigenvectors are desired, then save rotations. */ if (icompz > 0) { work[i__] = c__; work[*n - 1 + i__] = s; } /* L120: */ } /* if eigenvectors are desired, then apply saved rotations. */ if (icompz > 0) { mm = l - m + 1; /* $$$ call dlasr( 'r', 'v', 'f', n, mm, work( m ), work( n-1+m ), $$$ $ z( 1, m ), ldz ) *** New starting with version 2.5 *** */ igraphdlasr_("r", "v", "f", &c__1, &mm, &work[m], &work[*n - 1 + m], & z__[m], &c__1); /* ************************************* */ } d__[l] -= p; e[lm1] = g; goto L90; /* eigenvalue found. */ L130: d__[l] = p; --l; if (l >= lend) { goto L90; } goto L140; } /* undo scaling if necessary */ L140: if (iscale == 1) { i__1 = lendsv - lsv + 1; igraphdlascl_("g", &c__0, &c__0, &ssfmax, &anorm, &i__1, &c__1, &d__[lsv], n, info); i__1 = lendsv - lsv; igraphdlascl_("g", &c__0, &c__0, &ssfmax, &anorm, &i__1, &c__1, &e[lsv], n, info); } else if (iscale == 2) { i__1 = lendsv - lsv + 1; igraphdlascl_("g", &c__0, &c__0, &ssfmin, &anorm, &i__1, &c__1, &d__[lsv], n, info); i__1 = lendsv - lsv; igraphdlascl_("g", &c__0, &c__0, &ssfmin, &anorm, &i__1, &c__1, &e[lsv], n, info); } /* check for no convergence to an eigenvalue after a total of n*maxit iterations. */ if (jtot < nmaxit) { goto L10; } i__1 = *n - 1; for (i__ = 1; i__ <= i__1; ++i__) { if (e[i__] != 0.) { ++(*info); } /* L150: */ } goto L190; /* order eigenvalues and eigenvectors. */ L160: if (icompz == 0) { /* use quick sort */ igraphdlasrt_("i", n, &d__[1], info); } else { /* use selection sort to minimize swaps of eigenvectors */ i__1 = *n; for (ii = 2; ii <= i__1; ++ii) { i__ = ii - 1; k = i__; p = d__[i__]; i__2 = *n; for (j = ii; j <= i__2; ++j) { if (d__[j] < p) { k = j; p = d__[j]; } /* L170: */ } if (k != i__) { d__[k] = d__[i__]; d__[i__] = p; /* $$$ call dswap( n, z( 1, i ), 1, z( 1, k ), 1 ) *** New starting with version 2.5 *** */ p = z__[k]; z__[k] = z__[i__]; z__[i__] = p; /* ************************************* */ } /* L180: */ } } L190: return 0; /* %---------------% | End of dstqrb | %---------------% */ } /* igraphdstqrb_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dgesv.c0000644000076500000240000001424413524616145024121 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief DGESV computes the solution to system of linear equations A * X = B for GE matrices =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DGESV + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DGESV( N, NRHS, A, LDA, IPIV, B, LDB, INFO ) INTEGER INFO, LDA, LDB, N, NRHS INTEGER IPIV( * ) DOUBLE PRECISION A( LDA, * ), B( LDB, * ) > \par Purpose: ============= > > \verbatim > > DGESV computes the solution to a real system of linear equations > A * X = B, > where A is an N-by-N matrix and X and B are N-by-NRHS matrices. > > The LU decomposition with partial pivoting and row interchanges is > used to factor A as > A = P * L * U, > where P is a permutation matrix, L is unit lower triangular, and U is > upper triangular. The factored form of A is then used to solve the > system of equations A * X = B. > \endverbatim Arguments: ========== > \param[in] N > \verbatim > N is INTEGER > The number of linear equations, i.e., the order of the > matrix A. N >= 0. > \endverbatim > > \param[in] NRHS > \verbatim > NRHS is INTEGER > The number of right hand sides, i.e., the number of columns > of the matrix B. NRHS >= 0. > \endverbatim > > \param[in,out] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,N) > On entry, the N-by-N coefficient matrix A. > On exit, the factors L and U from the factorization > A = P*L*U; the unit diagonal elements of L are not stored. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. LDA >= max(1,N). > \endverbatim > > \param[out] IPIV > \verbatim > IPIV is INTEGER array, dimension (N) > The pivot indices that define the permutation matrix P; > row i of the matrix was interchanged with row IPIV(i). > \endverbatim > > \param[in,out] B > \verbatim > B is DOUBLE PRECISION array, dimension (LDB,NRHS) > On entry, the N-by-NRHS matrix of right hand side matrix B. > On exit, if INFO = 0, the N-by-NRHS solution matrix X. > \endverbatim > > \param[in] LDB > \verbatim > LDB is INTEGER > The leading dimension of the array B. LDB >= max(1,N). > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value > > 0: if INFO = i, U(i,i) is exactly zero. The factorization > has been completed, but the factor U is exactly > singular, so the solution could not be computed. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2011 > \ingroup doubleGEsolve ===================================================================== Subroutine */ int igraphdgesv_(integer *n, integer *nrhs, doublereal *a, integer *lda, integer *ipiv, doublereal *b, integer *ldb, integer *info) { /* System generated locals */ integer a_dim1, a_offset, b_dim1, b_offset, i__1; /* Local variables */ extern /* Subroutine */ int igraphdgetrf_(integer *, integer *, doublereal *, integer *, integer *, integer *), igraphxerbla_(char *, integer *, ftnlen), igraphdgetrs_(char *, integer *, integer *, doublereal *, integer *, integer *, doublereal *, integer *, integer *); /* -- LAPACK driver routine (version 3.4.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2011 ===================================================================== Test the input parameters. Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --ipiv; b_dim1 = *ldb; b_offset = 1 + b_dim1; b -= b_offset; /* Function Body */ *info = 0; if (*n < 0) { *info = -1; } else if (*nrhs < 0) { *info = -2; } else if (*lda < max(1,*n)) { *info = -4; } else if (*ldb < max(1,*n)) { *info = -7; } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DGESV ", &i__1, (ftnlen)6); return 0; } /* Compute the LU factorization of A. */ igraphdgetrf_(n, n, &a[a_offset], lda, &ipiv[1], info); if (*info == 0) { /* Solve the system A*X = B, overwriting B with X. */ igraphdgetrs_("No transpose", n, nrhs, &a[a_offset], lda, &ipiv[1], &b[ b_offset], ldb, info); } return 0; /* End of DGESV */ } /* igraphdgesv_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/lapack.inc0000644000076500000240000000321313524616145024565 0ustar tamasstaff00000000000000LAPACK = lapack/dgeev.c lapack/dgebak.c lapack/xerbla.c lapack/dgebal.c lapack/disnan.c lapack/dlaisnan.c lapack/dgehrd.c lapack/dgehd2.c lapack/dlarf.c lapack/iladlc.c lapack/iladlr.c lapack/dlarfg.c lapack/dlapy2.c lapack/dlahr2.c lapack/dlacpy.c lapack/dlarfb.c lapack/ilaenv.c lapack/ieeeck.c lapack/iparmq.c lapack/dhseqr.c lapack/dlahqr.c lapack/dlabad.c lapack/dlanv2.c lapack/dlaqr0.c lapack/dlaqr3.c lapack/dlaqr4.c lapack/dlaqr2.c lapack/dlaset.c lapack/dormhr.c lapack/dormqr.c lapack/dlarft.c lapack/dorm2r.c lapack/dtrexc.c lapack/dlaexc.c lapack/dlange.c lapack/dlassq.c lapack/dlarfx.c lapack/dlartg.c lapack/dlasy2.c lapack/dlaqr5.c lapack/dlaqr1.c lapack/dlascl.c lapack/dorghr.c lapack/dorgqr.c lapack/dorg2r.c lapack/dtrevc.c lapack/dlaln2.c lapack/dladiv.c lapack/dsyevr.c lapack/dlansy.c lapack/dormtr.c lapack/dormql.c lapack/dorm2l.c lapack/dstebz.c lapack/dlaebz.c lapack/dstein.c lapack/dlagtf.c lapack/dlagts.c lapack/dlarnv.c lapack/dlaruv.c lapack/dstemr.c lapack/dlae2.c lapack/dlaev2.c lapack/dlanst.c lapack/dlarrc.c lapack/dlarre.c lapack/dlarra.c lapack/dlarrb.c lapack/dlaneg.c lapack/dlarrd.c lapack/dlarrk.c lapack/dlasq2.c lapack/dlasq3.c lapack/dlasq4.c lapack/dlasq5.c lapack/dlasq6.c lapack/dlasrt.c lapack/dlarrj.c lapack/dlarrr.c lapack/dlarrv.c lapack/dlar1v.c lapack/dlarrf.c lapack/dsterf.c lapack/dsytrd.c lapack/dlatrd.c lapack/dsytd2.c lapack/dlanhs.c lapack/dgeqr2.c lapack/dtrsen.c lapack/dlacn2.c lapack/dtrsyl.c lapack/dlasr.c lapack/dsteqr.c lapack/dgeevx.c lapack/dtrsna.c lapack/dlaqtr.c lapack/dgetrf.c lapack/dgetf2.c lapack/dlaswp.c lapack/dgetrs.c lapack/dgesv.c lapack/dpotrf.c lapack/dpotf2.c lapack/len_trim.c python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlaev2.c0000644000076500000240000001473513524616145024173 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLAEV2 computes the eigenvalues and eigenvectors of a 2-by-2 symmetric/Hermitian matrix. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLAEV2 + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLAEV2( A, B, C, RT1, RT2, CS1, SN1 ) DOUBLE PRECISION A, B, C, CS1, RT1, RT2, SN1 > \par Purpose: ============= > > \verbatim > > DLAEV2 computes the eigendecomposition of a 2-by-2 symmetric matrix > [ A B ] > [ B C ]. > On return, RT1 is the eigenvalue of larger absolute value, RT2 is the > eigenvalue of smaller absolute value, and (CS1,SN1) is the unit right > eigenvector for RT1, giving the decomposition > > [ CS1 SN1 ] [ A B ] [ CS1 -SN1 ] = [ RT1 0 ] > [-SN1 CS1 ] [ B C ] [ SN1 CS1 ] [ 0 RT2 ]. > \endverbatim Arguments: ========== > \param[in] A > \verbatim > A is DOUBLE PRECISION > The (1,1) element of the 2-by-2 matrix. > \endverbatim > > \param[in] B > \verbatim > B is DOUBLE PRECISION > The (1,2) element and the conjugate of the (2,1) element of > the 2-by-2 matrix. > \endverbatim > > \param[in] C > \verbatim > C is DOUBLE PRECISION > The (2,2) element of the 2-by-2 matrix. > \endverbatim > > \param[out] RT1 > \verbatim > RT1 is DOUBLE PRECISION > The eigenvalue of larger absolute value. > \endverbatim > > \param[out] RT2 > \verbatim > RT2 is DOUBLE PRECISION > The eigenvalue of smaller absolute value. > \endverbatim > > \param[out] CS1 > \verbatim > CS1 is DOUBLE PRECISION > \endverbatim > > \param[out] SN1 > \verbatim > SN1 is DOUBLE PRECISION > The vector (CS1, SN1) is a unit right eigenvector for RT1. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERauxiliary > \par Further Details: ===================== > > \verbatim > > RT1 is accurate to a few ulps barring over/underflow. > > RT2 may be inaccurate if there is massive cancellation in the > determinant A*C-B*B; higher precision or correctly rounded or > correctly truncated arithmetic would be needed to compute RT2 > accurately in all cases. > > CS1 and SN1 are accurate to a few ulps barring over/underflow. > > Overflow is possible only if RT1 is within a factor of 5 of overflow. > Underflow is harmless if the input data is 0 or exceeds > underflow_threshold / macheps. > \endverbatim > ===================================================================== Subroutine */ int igraphdlaev2_(doublereal *a, doublereal *b, doublereal *c__, doublereal *rt1, doublereal *rt2, doublereal *cs1, doublereal *sn1) { /* System generated locals */ doublereal d__1; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ doublereal ab, df, cs, ct, tb, sm, tn, rt, adf, acs; integer sgn1, sgn2; doublereal acmn, acmx; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Compute the eigenvalues */ sm = *a + *c__; df = *a - *c__; adf = abs(df); tb = *b + *b; ab = abs(tb); if (abs(*a) > abs(*c__)) { acmx = *a; acmn = *c__; } else { acmx = *c__; acmn = *a; } if (adf > ab) { /* Computing 2nd power */ d__1 = ab / adf; rt = adf * sqrt(d__1 * d__1 + 1.); } else if (adf < ab) { /* Computing 2nd power */ d__1 = adf / ab; rt = ab * sqrt(d__1 * d__1 + 1.); } else { /* Includes case AB=ADF=0 */ rt = ab * sqrt(2.); } if (sm < 0.) { *rt1 = (sm - rt) * .5; sgn1 = -1; /* Order of execution important. To get fully accurate smaller eigenvalue, next line needs to be executed in higher precision. */ *rt2 = acmx / *rt1 * acmn - *b / *rt1 * *b; } else if (sm > 0.) { *rt1 = (sm + rt) * .5; sgn1 = 1; /* Order of execution important. To get fully accurate smaller eigenvalue, next line needs to be executed in higher precision. */ *rt2 = acmx / *rt1 * acmn - *b / *rt1 * *b; } else { /* Includes case RT1 = RT2 = 0 */ *rt1 = rt * .5; *rt2 = rt * -.5; sgn1 = 1; } /* Compute the eigenvector */ if (df >= 0.) { cs = df + rt; sgn2 = 1; } else { cs = df - rt; sgn2 = -1; } acs = abs(cs); if (acs > ab) { ct = -tb / cs; *sn1 = 1. / sqrt(ct * ct + 1.); *cs1 = ct * *sn1; } else { if (ab == 0.) { *cs1 = 1.; *sn1 = 0.; } else { tn = -cs / tb; *cs1 = 1. / sqrt(tn * tn + 1.); *sn1 = tn * *cs1; } } if (sgn1 == sgn2) { tn = *cs1; *cs1 = -(*sn1); *sn1 = tn; } return 0; /* End of DLAEV2 */ } /* igraphdlaev2_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlarfx.c0000644000076500000240000004620013524616145024266 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; /* > \brief \b DLARFX applies an elementary reflector to a general rectangular matrix, with loop unrolling whe n the reflector has order ≤ 10. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLARFX + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLARFX( SIDE, M, N, V, TAU, C, LDC, WORK ) CHARACTER SIDE INTEGER LDC, M, N DOUBLE PRECISION TAU DOUBLE PRECISION C( LDC, * ), V( * ), WORK( * ) > \par Purpose: ============= > > \verbatim > > DLARFX applies a real elementary reflector H to a real m by n > matrix C, from either the left or the right. H is represented in the > form > > H = I - tau * v * v**T > > where tau is a real scalar and v is a real vector. > > If tau = 0, then H is taken to be the unit matrix > > This version uses inline code if H has order < 11. > \endverbatim Arguments: ========== > \param[in] SIDE > \verbatim > SIDE is CHARACTER*1 > = 'L': form H * C > = 'R': form C * H > \endverbatim > > \param[in] M > \verbatim > M is INTEGER > The number of rows of the matrix C. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The number of columns of the matrix C. > \endverbatim > > \param[in] V > \verbatim > V is DOUBLE PRECISION array, dimension (M) if SIDE = 'L' > or (N) if SIDE = 'R' > The vector v in the representation of H. > \endverbatim > > \param[in] TAU > \verbatim > TAU is DOUBLE PRECISION > The value tau in the representation of H. > \endverbatim > > \param[in,out] C > \verbatim > C is DOUBLE PRECISION array, dimension (LDC,N) > On entry, the m by n matrix C. > On exit, C is overwritten by the matrix H * C if SIDE = 'L', > or C * H if SIDE = 'R'. > \endverbatim > > \param[in] LDC > \verbatim > LDC is INTEGER > The leading dimension of the array C. LDA >= (1,M). > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension > (N) if SIDE = 'L' > or (M) if SIDE = 'R' > WORK is not referenced if H has order < 11. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleOTHERauxiliary ===================================================================== Subroutine */ int igraphdlarfx_(char *side, integer *m, integer *n, doublereal * v, doublereal *tau, doublereal *c__, integer *ldc, doublereal *work) { /* System generated locals */ integer c_dim1, c_offset, i__1; /* Local variables */ integer j; doublereal t1, t2, t3, t4, t5, t6, t7, t8, t9, v1, v2, v3, v4, v5, v6, v7, v8, v9, t10, v10, sum; extern /* Subroutine */ int igraphdlarf_(char *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *); extern logical igraphlsame_(char *, char *); /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ --v; c_dim1 = *ldc; c_offset = 1 + c_dim1; c__ -= c_offset; --work; /* Function Body */ if (*tau == 0.) { return 0; } if (igraphlsame_(side, "L")) { /* Form H * C, where H has order m. */ switch (*m) { case 1: goto L10; case 2: goto L30; case 3: goto L50; case 4: goto L70; case 5: goto L90; case 6: goto L110; case 7: goto L130; case 8: goto L150; case 9: goto L170; case 10: goto L190; } /* Code for general M */ igraphdlarf_(side, m, n, &v[1], &c__1, tau, &c__[c_offset], ldc, &work[1]); goto L410; L10: /* Special code for 1 x 1 Householder */ t1 = 1. - *tau * v[1] * v[1]; i__1 = *n; for (j = 1; j <= i__1; ++j) { c__[j * c_dim1 + 1] = t1 * c__[j * c_dim1 + 1]; /* L20: */ } goto L410; L30: /* Special code for 2 x 2 Householder */ v1 = v[1]; t1 = *tau * v1; v2 = v[2]; t2 = *tau * v2; i__1 = *n; for (j = 1; j <= i__1; ++j) { sum = v1 * c__[j * c_dim1 + 1] + v2 * c__[j * c_dim1 + 2]; c__[j * c_dim1 + 1] -= sum * t1; c__[j * c_dim1 + 2] -= sum * t2; /* L40: */ } goto L410; L50: /* Special code for 3 x 3 Householder */ v1 = v[1]; t1 = *tau * v1; v2 = v[2]; t2 = *tau * v2; v3 = v[3]; t3 = *tau * v3; i__1 = *n; for (j = 1; j <= i__1; ++j) { sum = v1 * c__[j * c_dim1 + 1] + v2 * c__[j * c_dim1 + 2] + v3 * c__[j * c_dim1 + 3]; c__[j * c_dim1 + 1] -= sum * t1; c__[j * c_dim1 + 2] -= sum * t2; c__[j * c_dim1 + 3] -= sum * t3; /* L60: */ } goto L410; L70: /* Special code for 4 x 4 Householder */ v1 = v[1]; t1 = *tau * v1; v2 = v[2]; t2 = *tau * v2; v3 = v[3]; t3 = *tau * v3; v4 = v[4]; t4 = *tau * v4; i__1 = *n; for (j = 1; j <= i__1; ++j) { sum = v1 * c__[j * c_dim1 + 1] + v2 * c__[j * c_dim1 + 2] + v3 * c__[j * c_dim1 + 3] + v4 * c__[j * c_dim1 + 4]; c__[j * c_dim1 + 1] -= sum * t1; c__[j * c_dim1 + 2] -= sum * t2; c__[j * c_dim1 + 3] -= sum * t3; c__[j * c_dim1 + 4] -= sum * t4; /* L80: */ } goto L410; L90: /* Special code for 5 x 5 Householder */ v1 = v[1]; t1 = *tau * v1; v2 = v[2]; t2 = *tau * v2; v3 = v[3]; t3 = *tau * v3; v4 = v[4]; t4 = *tau * v4; v5 = v[5]; t5 = *tau * v5; i__1 = *n; for (j = 1; j <= i__1; ++j) { sum = v1 * c__[j * c_dim1 + 1] + v2 * c__[j * c_dim1 + 2] + v3 * c__[j * c_dim1 + 3] + v4 * c__[j * c_dim1 + 4] + v5 * c__[ j * c_dim1 + 5]; c__[j * c_dim1 + 1] -= sum * t1; c__[j * c_dim1 + 2] -= sum * t2; c__[j * c_dim1 + 3] -= sum * t3; c__[j * c_dim1 + 4] -= sum * t4; c__[j * c_dim1 + 5] -= sum * t5; /* L100: */ } goto L410; L110: /* Special code for 6 x 6 Householder */ v1 = v[1]; t1 = *tau * v1; v2 = v[2]; t2 = *tau * v2; v3 = v[3]; t3 = *tau * v3; v4 = v[4]; t4 = *tau * v4; v5 = v[5]; t5 = *tau * v5; v6 = v[6]; t6 = *tau * v6; i__1 = *n; for (j = 1; j <= i__1; ++j) { sum = v1 * c__[j * c_dim1 + 1] + v2 * c__[j * c_dim1 + 2] + v3 * c__[j * c_dim1 + 3] + v4 * c__[j * c_dim1 + 4] + v5 * c__[ j * c_dim1 + 5] + v6 * c__[j * c_dim1 + 6]; c__[j * c_dim1 + 1] -= sum * t1; c__[j * c_dim1 + 2] -= sum * t2; c__[j * c_dim1 + 3] -= sum * t3; c__[j * c_dim1 + 4] -= sum * t4; c__[j * c_dim1 + 5] -= sum * t5; c__[j * c_dim1 + 6] -= sum * t6; /* L120: */ } goto L410; L130: /* Special code for 7 x 7 Householder */ v1 = v[1]; t1 = *tau * v1; v2 = v[2]; t2 = *tau * v2; v3 = v[3]; t3 = *tau * v3; v4 = v[4]; t4 = *tau * v4; v5 = v[5]; t5 = *tau * v5; v6 = v[6]; t6 = *tau * v6; v7 = v[7]; t7 = *tau * v7; i__1 = *n; for (j = 1; j <= i__1; ++j) { sum = v1 * c__[j * c_dim1 + 1] + v2 * c__[j * c_dim1 + 2] + v3 * c__[j * c_dim1 + 3] + v4 * c__[j * c_dim1 + 4] + v5 * c__[ j * c_dim1 + 5] + v6 * c__[j * c_dim1 + 6] + v7 * c__[j * c_dim1 + 7]; c__[j * c_dim1 + 1] -= sum * t1; c__[j * c_dim1 + 2] -= sum * t2; c__[j * c_dim1 + 3] -= sum * t3; c__[j * c_dim1 + 4] -= sum * t4; c__[j * c_dim1 + 5] -= sum * t5; c__[j * c_dim1 + 6] -= sum * t6; c__[j * c_dim1 + 7] -= sum * t7; /* L140: */ } goto L410; L150: /* Special code for 8 x 8 Householder */ v1 = v[1]; t1 = *tau * v1; v2 = v[2]; t2 = *tau * v2; v3 = v[3]; t3 = *tau * v3; v4 = v[4]; t4 = *tau * v4; v5 = v[5]; t5 = *tau * v5; v6 = v[6]; t6 = *tau * v6; v7 = v[7]; t7 = *tau * v7; v8 = v[8]; t8 = *tau * v8; i__1 = *n; for (j = 1; j <= i__1; ++j) { sum = v1 * c__[j * c_dim1 + 1] + v2 * c__[j * c_dim1 + 2] + v3 * c__[j * c_dim1 + 3] + v4 * c__[j * c_dim1 + 4] + v5 * c__[ j * c_dim1 + 5] + v6 * c__[j * c_dim1 + 6] + v7 * c__[j * c_dim1 + 7] + v8 * c__[j * c_dim1 + 8]; c__[j * c_dim1 + 1] -= sum * t1; c__[j * c_dim1 + 2] -= sum * t2; c__[j * c_dim1 + 3] -= sum * t3; c__[j * c_dim1 + 4] -= sum * t4; c__[j * c_dim1 + 5] -= sum * t5; c__[j * c_dim1 + 6] -= sum * t6; c__[j * c_dim1 + 7] -= sum * t7; c__[j * c_dim1 + 8] -= sum * t8; /* L160: */ } goto L410; L170: /* Special code for 9 x 9 Householder */ v1 = v[1]; t1 = *tau * v1; v2 = v[2]; t2 = *tau * v2; v3 = v[3]; t3 = *tau * v3; v4 = v[4]; t4 = *tau * v4; v5 = v[5]; t5 = *tau * v5; v6 = v[6]; t6 = *tau * v6; v7 = v[7]; t7 = *tau * v7; v8 = v[8]; t8 = *tau * v8; v9 = v[9]; t9 = *tau * v9; i__1 = *n; for (j = 1; j <= i__1; ++j) { sum = v1 * c__[j * c_dim1 + 1] + v2 * c__[j * c_dim1 + 2] + v3 * c__[j * c_dim1 + 3] + v4 * c__[j * c_dim1 + 4] + v5 * c__[ j * c_dim1 + 5] + v6 * c__[j * c_dim1 + 6] + v7 * c__[j * c_dim1 + 7] + v8 * c__[j * c_dim1 + 8] + v9 * c__[j * c_dim1 + 9]; c__[j * c_dim1 + 1] -= sum * t1; c__[j * c_dim1 + 2] -= sum * t2; c__[j * c_dim1 + 3] -= sum * t3; c__[j * c_dim1 + 4] -= sum * t4; c__[j * c_dim1 + 5] -= sum * t5; c__[j * c_dim1 + 6] -= sum * t6; c__[j * c_dim1 + 7] -= sum * t7; c__[j * c_dim1 + 8] -= sum * t8; c__[j * c_dim1 + 9] -= sum * t9; /* L180: */ } goto L410; L190: /* Special code for 10 x 10 Householder */ v1 = v[1]; t1 = *tau * v1; v2 = v[2]; t2 = *tau * v2; v3 = v[3]; t3 = *tau * v3; v4 = v[4]; t4 = *tau * v4; v5 = v[5]; t5 = *tau * v5; v6 = v[6]; t6 = *tau * v6; v7 = v[7]; t7 = *tau * v7; v8 = v[8]; t8 = *tau * v8; v9 = v[9]; t9 = *tau * v9; v10 = v[10]; t10 = *tau * v10; i__1 = *n; for (j = 1; j <= i__1; ++j) { sum = v1 * c__[j * c_dim1 + 1] + v2 * c__[j * c_dim1 + 2] + v3 * c__[j * c_dim1 + 3] + v4 * c__[j * c_dim1 + 4] + v5 * c__[ j * c_dim1 + 5] + v6 * c__[j * c_dim1 + 6] + v7 * c__[j * c_dim1 + 7] + v8 * c__[j * c_dim1 + 8] + v9 * c__[j * c_dim1 + 9] + v10 * c__[j * c_dim1 + 10]; c__[j * c_dim1 + 1] -= sum * t1; c__[j * c_dim1 + 2] -= sum * t2; c__[j * c_dim1 + 3] -= sum * t3; c__[j * c_dim1 + 4] -= sum * t4; c__[j * c_dim1 + 5] -= sum * t5; c__[j * c_dim1 + 6] -= sum * t6; c__[j * c_dim1 + 7] -= sum * t7; c__[j * c_dim1 + 8] -= sum * t8; c__[j * c_dim1 + 9] -= sum * t9; c__[j * c_dim1 + 10] -= sum * t10; /* L200: */ } goto L410; } else { /* Form C * H, where H has order n. */ switch (*n) { case 1: goto L210; case 2: goto L230; case 3: goto L250; case 4: goto L270; case 5: goto L290; case 6: goto L310; case 7: goto L330; case 8: goto L350; case 9: goto L370; case 10: goto L390; } /* Code for general N */ igraphdlarf_(side, m, n, &v[1], &c__1, tau, &c__[c_offset], ldc, &work[1]); goto L410; L210: /* Special code for 1 x 1 Householder */ t1 = 1. - *tau * v[1] * v[1]; i__1 = *m; for (j = 1; j <= i__1; ++j) { c__[j + c_dim1] = t1 * c__[j + c_dim1]; /* L220: */ } goto L410; L230: /* Special code for 2 x 2 Householder */ v1 = v[1]; t1 = *tau * v1; v2 = v[2]; t2 = *tau * v2; i__1 = *m; for (j = 1; j <= i__1; ++j) { sum = v1 * c__[j + c_dim1] + v2 * c__[j + (c_dim1 << 1)]; c__[j + c_dim1] -= sum * t1; c__[j + (c_dim1 << 1)] -= sum * t2; /* L240: */ } goto L410; L250: /* Special code for 3 x 3 Householder */ v1 = v[1]; t1 = *tau * v1; v2 = v[2]; t2 = *tau * v2; v3 = v[3]; t3 = *tau * v3; i__1 = *m; for (j = 1; j <= i__1; ++j) { sum = v1 * c__[j + c_dim1] + v2 * c__[j + (c_dim1 << 1)] + v3 * c__[j + c_dim1 * 3]; c__[j + c_dim1] -= sum * t1; c__[j + (c_dim1 << 1)] -= sum * t2; c__[j + c_dim1 * 3] -= sum * t3; /* L260: */ } goto L410; L270: /* Special code for 4 x 4 Householder */ v1 = v[1]; t1 = *tau * v1; v2 = v[2]; t2 = *tau * v2; v3 = v[3]; t3 = *tau * v3; v4 = v[4]; t4 = *tau * v4; i__1 = *m; for (j = 1; j <= i__1; ++j) { sum = v1 * c__[j + c_dim1] + v2 * c__[j + (c_dim1 << 1)] + v3 * c__[j + c_dim1 * 3] + v4 * c__[j + (c_dim1 << 2)]; c__[j + c_dim1] -= sum * t1; c__[j + (c_dim1 << 1)] -= sum * t2; c__[j + c_dim1 * 3] -= sum * t3; c__[j + (c_dim1 << 2)] -= sum * t4; /* L280: */ } goto L410; L290: /* Special code for 5 x 5 Householder */ v1 = v[1]; t1 = *tau * v1; v2 = v[2]; t2 = *tau * v2; v3 = v[3]; t3 = *tau * v3; v4 = v[4]; t4 = *tau * v4; v5 = v[5]; t5 = *tau * v5; i__1 = *m; for (j = 1; j <= i__1; ++j) { sum = v1 * c__[j + c_dim1] + v2 * c__[j + (c_dim1 << 1)] + v3 * c__[j + c_dim1 * 3] + v4 * c__[j + (c_dim1 << 2)] + v5 * c__[j + c_dim1 * 5]; c__[j + c_dim1] -= sum * t1; c__[j + (c_dim1 << 1)] -= sum * t2; c__[j + c_dim1 * 3] -= sum * t3; c__[j + (c_dim1 << 2)] -= sum * t4; c__[j + c_dim1 * 5] -= sum * t5; /* L300: */ } goto L410; L310: /* Special code for 6 x 6 Householder */ v1 = v[1]; t1 = *tau * v1; v2 = v[2]; t2 = *tau * v2; v3 = v[3]; t3 = *tau * v3; v4 = v[4]; t4 = *tau * v4; v5 = v[5]; t5 = *tau * v5; v6 = v[6]; t6 = *tau * v6; i__1 = *m; for (j = 1; j <= i__1; ++j) { sum = v1 * c__[j + c_dim1] + v2 * c__[j + (c_dim1 << 1)] + v3 * c__[j + c_dim1 * 3] + v4 * c__[j + (c_dim1 << 2)] + v5 * c__[j + c_dim1 * 5] + v6 * c__[j + c_dim1 * 6]; c__[j + c_dim1] -= sum * t1; c__[j + (c_dim1 << 1)] -= sum * t2; c__[j + c_dim1 * 3] -= sum * t3; c__[j + (c_dim1 << 2)] -= sum * t4; c__[j + c_dim1 * 5] -= sum * t5; c__[j + c_dim1 * 6] -= sum * t6; /* L320: */ } goto L410; L330: /* Special code for 7 x 7 Householder */ v1 = v[1]; t1 = *tau * v1; v2 = v[2]; t2 = *tau * v2; v3 = v[3]; t3 = *tau * v3; v4 = v[4]; t4 = *tau * v4; v5 = v[5]; t5 = *tau * v5; v6 = v[6]; t6 = *tau * v6; v7 = v[7]; t7 = *tau * v7; i__1 = *m; for (j = 1; j <= i__1; ++j) { sum = v1 * c__[j + c_dim1] + v2 * c__[j + (c_dim1 << 1)] + v3 * c__[j + c_dim1 * 3] + v4 * c__[j + (c_dim1 << 2)] + v5 * c__[j + c_dim1 * 5] + v6 * c__[j + c_dim1 * 6] + v7 * c__[ j + c_dim1 * 7]; c__[j + c_dim1] -= sum * t1; c__[j + (c_dim1 << 1)] -= sum * t2; c__[j + c_dim1 * 3] -= sum * t3; c__[j + (c_dim1 << 2)] -= sum * t4; c__[j + c_dim1 * 5] -= sum * t5; c__[j + c_dim1 * 6] -= sum * t6; c__[j + c_dim1 * 7] -= sum * t7; /* L340: */ } goto L410; L350: /* Special code for 8 x 8 Householder */ v1 = v[1]; t1 = *tau * v1; v2 = v[2]; t2 = *tau * v2; v3 = v[3]; t3 = *tau * v3; v4 = v[4]; t4 = *tau * v4; v5 = v[5]; t5 = *tau * v5; v6 = v[6]; t6 = *tau * v6; v7 = v[7]; t7 = *tau * v7; v8 = v[8]; t8 = *tau * v8; i__1 = *m; for (j = 1; j <= i__1; ++j) { sum = v1 * c__[j + c_dim1] + v2 * c__[j + (c_dim1 << 1)] + v3 * c__[j + c_dim1 * 3] + v4 * c__[j + (c_dim1 << 2)] + v5 * c__[j + c_dim1 * 5] + v6 * c__[j + c_dim1 * 6] + v7 * c__[ j + c_dim1 * 7] + v8 * c__[j + (c_dim1 << 3)]; c__[j + c_dim1] -= sum * t1; c__[j + (c_dim1 << 1)] -= sum * t2; c__[j + c_dim1 * 3] -= sum * t3; c__[j + (c_dim1 << 2)] -= sum * t4; c__[j + c_dim1 * 5] -= sum * t5; c__[j + c_dim1 * 6] -= sum * t6; c__[j + c_dim1 * 7] -= sum * t7; c__[j + (c_dim1 << 3)] -= sum * t8; /* L360: */ } goto L410; L370: /* Special code for 9 x 9 Householder */ v1 = v[1]; t1 = *tau * v1; v2 = v[2]; t2 = *tau * v2; v3 = v[3]; t3 = *tau * v3; v4 = v[4]; t4 = *tau * v4; v5 = v[5]; t5 = *tau * v5; v6 = v[6]; t6 = *tau * v6; v7 = v[7]; t7 = *tau * v7; v8 = v[8]; t8 = *tau * v8; v9 = v[9]; t9 = *tau * v9; i__1 = *m; for (j = 1; j <= i__1; ++j) { sum = v1 * c__[j + c_dim1] + v2 * c__[j + (c_dim1 << 1)] + v3 * c__[j + c_dim1 * 3] + v4 * c__[j + (c_dim1 << 2)] + v5 * c__[j + c_dim1 * 5] + v6 * c__[j + c_dim1 * 6] + v7 * c__[ j + c_dim1 * 7] + v8 * c__[j + (c_dim1 << 3)] + v9 * c__[ j + c_dim1 * 9]; c__[j + c_dim1] -= sum * t1; c__[j + (c_dim1 << 1)] -= sum * t2; c__[j + c_dim1 * 3] -= sum * t3; c__[j + (c_dim1 << 2)] -= sum * t4; c__[j + c_dim1 * 5] -= sum * t5; c__[j + c_dim1 * 6] -= sum * t6; c__[j + c_dim1 * 7] -= sum * t7; c__[j + (c_dim1 << 3)] -= sum * t8; c__[j + c_dim1 * 9] -= sum * t9; /* L380: */ } goto L410; L390: /* Special code for 10 x 10 Householder */ v1 = v[1]; t1 = *tau * v1; v2 = v[2]; t2 = *tau * v2; v3 = v[3]; t3 = *tau * v3; v4 = v[4]; t4 = *tau * v4; v5 = v[5]; t5 = *tau * v5; v6 = v[6]; t6 = *tau * v6; v7 = v[7]; t7 = *tau * v7; v8 = v[8]; t8 = *tau * v8; v9 = v[9]; t9 = *tau * v9; v10 = v[10]; t10 = *tau * v10; i__1 = *m; for (j = 1; j <= i__1; ++j) { sum = v1 * c__[j + c_dim1] + v2 * c__[j + (c_dim1 << 1)] + v3 * c__[j + c_dim1 * 3] + v4 * c__[j + (c_dim1 << 2)] + v5 * c__[j + c_dim1 * 5] + v6 * c__[j + c_dim1 * 6] + v7 * c__[ j + c_dim1 * 7] + v8 * c__[j + (c_dim1 << 3)] + v9 * c__[ j + c_dim1 * 9] + v10 * c__[j + c_dim1 * 10]; c__[j + c_dim1] -= sum * t1; c__[j + (c_dim1 << 1)] -= sum * t2; c__[j + c_dim1 * 3] -= sum * t3; c__[j + (c_dim1 << 2)] -= sum * t4; c__[j + c_dim1 * 5] -= sum * t5; c__[j + c_dim1 * 6] -= sum * t6; c__[j + c_dim1 * 7] -= sum * t7; c__[j + (c_dim1 << 3)] -= sum * t8; c__[j + c_dim1 * 9] -= sum * t9; c__[j + c_dim1 * 10] -= sum * t10; /* L400: */ } goto L410; } L410: return 0; /* End of DLARFX */ } /* igraphdlarfx_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dsterf.c0000644000076500000240000002610013524616145024272 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__0 = 0; static integer c__1 = 1; static doublereal c_b33 = 1.; /* > \brief \b DSTERF =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DSTERF + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DSTERF( N, D, E, INFO ) INTEGER INFO, N DOUBLE PRECISION D( * ), E( * ) > \par Purpose: ============= > > \verbatim > > DSTERF computes all eigenvalues of a symmetric tridiagonal matrix > using the Pal-Walker-Kahan variant of the QL or QR algorithm. > \endverbatim Arguments: ========== > \param[in] N > \verbatim > N is INTEGER > The order of the matrix. N >= 0. > \endverbatim > > \param[in,out] D > \verbatim > D is DOUBLE PRECISION array, dimension (N) > On entry, the n diagonal elements of the tridiagonal matrix. > On exit, if INFO = 0, the eigenvalues in ascending order. > \endverbatim > > \param[in,out] E > \verbatim > E is DOUBLE PRECISION array, dimension (N-1) > On entry, the (n-1) subdiagonal elements of the tridiagonal > matrix. > On exit, E has been destroyed. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value > > 0: the algorithm failed to find all of the eigenvalues in > a total of 30*N iterations; if INFO = i, then i > elements of E have not converged to zero. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2011 > \ingroup auxOTHERcomputational ===================================================================== Subroutine */ int igraphdsterf_(integer *n, doublereal *d__, doublereal *e, integer *info) { /* System generated locals */ integer i__1; doublereal d__1, d__2, d__3; /* Builtin functions */ double sqrt(doublereal), d_sign(doublereal *, doublereal *); /* Local variables */ doublereal c__; integer i__, l, m; doublereal p, r__, s; integer l1; doublereal bb, rt1, rt2, eps, rte; integer lsv; doublereal eps2, oldc; integer lend; doublereal rmax; integer jtot; extern /* Subroutine */ int igraphdlae2_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *); doublereal gamma, alpha, sigma, anorm; extern doublereal igraphdlapy2_(doublereal *, doublereal *), igraphdlamch_(char *); integer iscale; extern /* Subroutine */ int igraphdlascl_(char *, integer *, integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, integer *, integer *); doublereal oldgam, safmin; extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); doublereal safmax; extern doublereal igraphdlanst_(char *, integer *, doublereal *, doublereal *); extern /* Subroutine */ int igraphdlasrt_(char *, integer *, doublereal *, integer *); integer lendsv; doublereal ssfmin; integer nmaxit; doublereal ssfmax; /* -- LAPACK computational routine (version 3.4.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2011 ===================================================================== Test the input parameters. Parameter adjustments */ --e; --d__; /* Function Body */ *info = 0; /* Quick return if possible */ if (*n < 0) { *info = -1; i__1 = -(*info); igraphxerbla_("DSTERF", &i__1, (ftnlen)6); return 0; } if (*n <= 1) { return 0; } /* Determine the unit roundoff for this environment. */ eps = igraphdlamch_("E"); /* Computing 2nd power */ d__1 = eps; eps2 = d__1 * d__1; safmin = igraphdlamch_("S"); safmax = 1. / safmin; ssfmax = sqrt(safmax) / 3.; ssfmin = sqrt(safmin) / eps2; rmax = igraphdlamch_("O"); /* Compute the eigenvalues of the tridiagonal matrix. */ nmaxit = *n * 30; sigma = 0.; jtot = 0; /* Determine where the matrix splits and choose QL or QR iteration for each block, according to whether top or bottom diagonal element is smaller. */ l1 = 1; L10: if (l1 > *n) { goto L170; } if (l1 > 1) { e[l1 - 1] = 0.; } i__1 = *n - 1; for (m = l1; m <= i__1; ++m) { if ((d__3 = e[m], abs(d__3)) <= sqrt((d__1 = d__[m], abs(d__1))) * sqrt((d__2 = d__[m + 1], abs(d__2))) * eps) { e[m] = 0.; goto L30; } /* L20: */ } m = *n; L30: l = l1; lsv = l; lend = m; lendsv = lend; l1 = m + 1; if (lend == l) { goto L10; } /* Scale submatrix in rows and columns L to LEND */ i__1 = lend - l + 1; anorm = igraphdlanst_("M", &i__1, &d__[l], &e[l]); iscale = 0; if (anorm == 0.) { goto L10; } if (anorm > ssfmax) { iscale = 1; i__1 = lend - l + 1; igraphdlascl_("G", &c__0, &c__0, &anorm, &ssfmax, &i__1, &c__1, &d__[l], n, info); i__1 = lend - l; igraphdlascl_("G", &c__0, &c__0, &anorm, &ssfmax, &i__1, &c__1, &e[l], n, info); } else if (anorm < ssfmin) { iscale = 2; i__1 = lend - l + 1; igraphdlascl_("G", &c__0, &c__0, &anorm, &ssfmin, &i__1, &c__1, &d__[l], n, info); i__1 = lend - l; igraphdlascl_("G", &c__0, &c__0, &anorm, &ssfmin, &i__1, &c__1, &e[l], n, info); } i__1 = lend - 1; for (i__ = l; i__ <= i__1; ++i__) { /* Computing 2nd power */ d__1 = e[i__]; e[i__] = d__1 * d__1; /* L40: */ } /* Choose between QL and QR iteration */ if ((d__1 = d__[lend], abs(d__1)) < (d__2 = d__[l], abs(d__2))) { lend = lsv; l = lendsv; } if (lend >= l) { /* QL Iteration Look for small subdiagonal element. */ L50: if (l != lend) { i__1 = lend - 1; for (m = l; m <= i__1; ++m) { if ((d__2 = e[m], abs(d__2)) <= eps2 * (d__1 = d__[m] * d__[m + 1], abs(d__1))) { goto L70; } /* L60: */ } } m = lend; L70: if (m < lend) { e[m] = 0.; } p = d__[l]; if (m == l) { goto L90; } /* If remaining matrix is 2 by 2, use DLAE2 to compute its eigenvalues. */ if (m == l + 1) { rte = sqrt(e[l]); igraphdlae2_(&d__[l], &rte, &d__[l + 1], &rt1, &rt2); d__[l] = rt1; d__[l + 1] = rt2; e[l] = 0.; l += 2; if (l <= lend) { goto L50; } goto L150; } if (jtot == nmaxit) { goto L150; } ++jtot; /* Form shift. */ rte = sqrt(e[l]); sigma = (d__[l + 1] - p) / (rte * 2.); r__ = igraphdlapy2_(&sigma, &c_b33); sigma = p - rte / (sigma + d_sign(&r__, &sigma)); c__ = 1.; s = 0.; gamma = d__[m] - sigma; p = gamma * gamma; /* Inner loop */ i__1 = l; for (i__ = m - 1; i__ >= i__1; --i__) { bb = e[i__]; r__ = p + bb; if (i__ != m - 1) { e[i__ + 1] = s * r__; } oldc = c__; c__ = p / r__; s = bb / r__; oldgam = gamma; alpha = d__[i__]; gamma = c__ * (alpha - sigma) - s * oldgam; d__[i__ + 1] = oldgam + (alpha - gamma); if (c__ != 0.) { p = gamma * gamma / c__; } else { p = oldc * bb; } /* L80: */ } e[l] = s * p; d__[l] = sigma + gamma; goto L50; /* Eigenvalue found. */ L90: d__[l] = p; ++l; if (l <= lend) { goto L50; } goto L150; } else { /* QR Iteration Look for small superdiagonal element. */ L100: i__1 = lend + 1; for (m = l; m >= i__1; --m) { if ((d__2 = e[m - 1], abs(d__2)) <= eps2 * (d__1 = d__[m] * d__[m - 1], abs(d__1))) { goto L120; } /* L110: */ } m = lend; L120: if (m > lend) { e[m - 1] = 0.; } p = d__[l]; if (m == l) { goto L140; } /* If remaining matrix is 2 by 2, use DLAE2 to compute its eigenvalues. */ if (m == l - 1) { rte = sqrt(e[l - 1]); igraphdlae2_(&d__[l], &rte, &d__[l - 1], &rt1, &rt2); d__[l] = rt1; d__[l - 1] = rt2; e[l - 1] = 0.; l += -2; if (l >= lend) { goto L100; } goto L150; } if (jtot == nmaxit) { goto L150; } ++jtot; /* Form shift. */ rte = sqrt(e[l - 1]); sigma = (d__[l - 1] - p) / (rte * 2.); r__ = igraphdlapy2_(&sigma, &c_b33); sigma = p - rte / (sigma + d_sign(&r__, &sigma)); c__ = 1.; s = 0.; gamma = d__[m] - sigma; p = gamma * gamma; /* Inner loop */ i__1 = l - 1; for (i__ = m; i__ <= i__1; ++i__) { bb = e[i__]; r__ = p + bb; if (i__ != m) { e[i__ - 1] = s * r__; } oldc = c__; c__ = p / r__; s = bb / r__; oldgam = gamma; alpha = d__[i__ + 1]; gamma = c__ * (alpha - sigma) - s * oldgam; d__[i__] = oldgam + (alpha - gamma); if (c__ != 0.) { p = gamma * gamma / c__; } else { p = oldc * bb; } /* L130: */ } e[l - 1] = s * p; d__[l] = sigma + gamma; goto L100; /* Eigenvalue found. */ L140: d__[l] = p; --l; if (l >= lend) { goto L100; } goto L150; } /* Undo scaling if necessary */ L150: if (iscale == 1) { i__1 = lendsv - lsv + 1; igraphdlascl_("G", &c__0, &c__0, &ssfmax, &anorm, &i__1, &c__1, &d__[lsv], n, info); } if (iscale == 2) { i__1 = lendsv - lsv + 1; igraphdlascl_("G", &c__0, &c__0, &ssfmin, &anorm, &i__1, &c__1, &d__[lsv], n, info); } /* Check for no convergence to an eigenvalue after a total of N*MAXIT iterations. */ if (jtot < nmaxit) { goto L10; } i__1 = *n - 1; for (i__ = 1; i__ <= i__1; ++i__) { if (e[i__] != 0.) { ++(*info); } /* L160: */ } goto L180; /* Sort eigenvalues in increasing order. */ L170: igraphdlasrt_("I", n, &d__[1], info); L180: return 0; /* End of DSTERF */ } /* igraphdsterf_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlaqr2.c0000644000076500000240000006123513524616145024200 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static integer c_n1 = -1; static doublereal c_b12 = 0.; static doublereal c_b13 = 1.; static logical c_true = TRUE_; /* > \brief \b DLAQR2 performs the orthogonal similarity transformation of a Hessenberg matrix to detect and d eflate fully converged eigenvalues from a trailing principal submatrix (aggressive early deflation). =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLAQR2 + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLAQR2( WANTT, WANTZ, N, KTOP, KBOT, NW, H, LDH, ILOZ, IHIZ, Z, LDZ, NS, ND, SR, SI, V, LDV, NH, T, LDT, NV, WV, LDWV, WORK, LWORK ) INTEGER IHIZ, ILOZ, KBOT, KTOP, LDH, LDT, LDV, LDWV, $ LDZ, LWORK, N, ND, NH, NS, NV, NW LOGICAL WANTT, WANTZ DOUBLE PRECISION H( LDH, * ), SI( * ), SR( * ), T( LDT, * ), $ V( LDV, * ), WORK( * ), WV( LDWV, * ), $ Z( LDZ, * ) > \par Purpose: ============= > > \verbatim > > DLAQR2 is identical to DLAQR3 except that it avoids > recursion by calling DLAHQR instead of DLAQR4. > > Aggressive early deflation: > > This subroutine accepts as input an upper Hessenberg matrix > H and performs an orthogonal similarity transformation > designed to detect and deflate fully converged eigenvalues from > a trailing principal submatrix. On output H has been over- > written by a new Hessenberg matrix that is a perturbation of > an orthogonal similarity transformation of H. It is to be > hoped that the final version of H has many zero subdiagonal > entries. > \endverbatim Arguments: ========== > \param[in] WANTT > \verbatim > WANTT is LOGICAL > If .TRUE., then the Hessenberg matrix H is fully updated > so that the quasi-triangular Schur factor may be > computed (in cooperation with the calling subroutine). > If .FALSE., then only enough of H is updated to preserve > the eigenvalues. > \endverbatim > > \param[in] WANTZ > \verbatim > WANTZ is LOGICAL > If .TRUE., then the orthogonal matrix Z is updated so > so that the orthogonal Schur factor may be computed > (in cooperation with the calling subroutine). > If .FALSE., then Z is not referenced. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix H and (if WANTZ is .TRUE.) the > order of the orthogonal matrix Z. > \endverbatim > > \param[in] KTOP > \verbatim > KTOP is INTEGER > It is assumed that either KTOP = 1 or H(KTOP,KTOP-1)=0. > KBOT and KTOP together determine an isolated block > along the diagonal of the Hessenberg matrix. > \endverbatim > > \param[in] KBOT > \verbatim > KBOT is INTEGER > It is assumed without a check that either > KBOT = N or H(KBOT+1,KBOT)=0. KBOT and KTOP together > determine an isolated block along the diagonal of the > Hessenberg matrix. > \endverbatim > > \param[in] NW > \verbatim > NW is INTEGER > Deflation window size. 1 .LE. NW .LE. (KBOT-KTOP+1). > \endverbatim > > \param[in,out] H > \verbatim > H is DOUBLE PRECISION array, dimension (LDH,N) > On input the initial N-by-N section of H stores the > Hessenberg matrix undergoing aggressive early deflation. > On output H has been transformed by an orthogonal > similarity transformation, perturbed, and the returned > to Hessenberg form that (it is to be hoped) has some > zero subdiagonal entries. > \endverbatim > > \param[in] LDH > \verbatim > LDH is integer > Leading dimension of H just as declared in the calling > subroutine. N .LE. LDH > \endverbatim > > \param[in] ILOZ > \verbatim > ILOZ is INTEGER > \endverbatim > > \param[in] IHIZ > \verbatim > IHIZ is INTEGER > Specify the rows of Z to which transformations must be > applied if WANTZ is .TRUE.. 1 .LE. ILOZ .LE. IHIZ .LE. N. > \endverbatim > > \param[in,out] Z > \verbatim > Z is DOUBLE PRECISION array, dimension (LDZ,N) > IF WANTZ is .TRUE., then on output, the orthogonal > similarity transformation mentioned above has been > accumulated into Z(ILOZ:IHIZ,ILO:IHI) from the right. > If WANTZ is .FALSE., then Z is unreferenced. > \endverbatim > > \param[in] LDZ > \verbatim > LDZ is integer > The leading dimension of Z just as declared in the > calling subroutine. 1 .LE. LDZ. > \endverbatim > > \param[out] NS > \verbatim > NS is integer > The number of unconverged (ie approximate) eigenvalues > returned in SR and SI that may be used as shifts by the > calling subroutine. > \endverbatim > > \param[out] ND > \verbatim > ND is integer > The number of converged eigenvalues uncovered by this > subroutine. > \endverbatim > > \param[out] SR > \verbatim > SR is DOUBLE PRECISION array, dimension (KBOT) > \endverbatim > > \param[out] SI > \verbatim > SI is DOUBLE PRECISION array, dimension (KBOT) > On output, the real and imaginary parts of approximate > eigenvalues that may be used for shifts are stored in > SR(KBOT-ND-NS+1) through SR(KBOT-ND) and > SI(KBOT-ND-NS+1) through SI(KBOT-ND), respectively. > The real and imaginary parts of converged eigenvalues > are stored in SR(KBOT-ND+1) through SR(KBOT) and > SI(KBOT-ND+1) through SI(KBOT), respectively. > \endverbatim > > \param[out] V > \verbatim > V is DOUBLE PRECISION array, dimension (LDV,NW) > An NW-by-NW work array. > \endverbatim > > \param[in] LDV > \verbatim > LDV is integer scalar > The leading dimension of V just as declared in the > calling subroutine. NW .LE. LDV > \endverbatim > > \param[in] NH > \verbatim > NH is integer scalar > The number of columns of T. NH.GE.NW. > \endverbatim > > \param[out] T > \verbatim > T is DOUBLE PRECISION array, dimension (LDT,NW) > \endverbatim > > \param[in] LDT > \verbatim > LDT is integer > The leading dimension of T just as declared in the > calling subroutine. NW .LE. LDT > \endverbatim > > \param[in] NV > \verbatim > NV is integer > The number of rows of work array WV available for > workspace. NV.GE.NW. > \endverbatim > > \param[out] WV > \verbatim > WV is DOUBLE PRECISION array, dimension (LDWV,NW) > \endverbatim > > \param[in] LDWV > \verbatim > LDWV is integer > The leading dimension of W just as declared in the > calling subroutine. NW .LE. LDV > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (LWORK) > On exit, WORK(1) is set to an estimate of the optimal value > of LWORK for the given values of N, NW, KTOP and KBOT. > \endverbatim > > \param[in] LWORK > \verbatim > LWORK is integer > The dimension of the work array WORK. LWORK = 2*NW > suffices, but greater efficiency may result from larger > values of LWORK. > > If LWORK = -1, then a workspace query is assumed; DLAQR2 > only estimates the optimal workspace size for the given > values of N, NW, KTOP and KBOT. The estimate is returned > in WORK(1). No error message related to LWORK is issued > by XERBLA. Neither H nor Z are accessed. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleOTHERauxiliary > \par Contributors: ================== > > Karen Braman and Ralph Byers, Department of Mathematics, > University of Kansas, USA > ===================================================================== Subroutine */ int igraphdlaqr2_(logical *wantt, logical *wantz, integer *n, integer *ktop, integer *kbot, integer *nw, doublereal *h__, integer * ldh, integer *iloz, integer *ihiz, doublereal *z__, integer *ldz, integer *ns, integer *nd, doublereal *sr, doublereal *si, doublereal * v, integer *ldv, integer *nh, doublereal *t, integer *ldt, integer * nv, doublereal *wv, integer *ldwv, doublereal *work, integer *lwork) { /* System generated locals */ integer h_dim1, h_offset, t_dim1, t_offset, v_dim1, v_offset, wv_dim1, wv_offset, z_dim1, z_offset, i__1, i__2, i__3, i__4; doublereal d__1, d__2, d__3, d__4, d__5, d__6; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ integer i__, j, k; doublereal s, aa, bb, cc, dd, cs, sn; integer jw; doublereal evi, evk, foo; integer kln; doublereal tau, ulp; integer lwk1, lwk2; doublereal beta; integer kend, kcol, info, ifst, ilst, ltop, krow; extern /* Subroutine */ int igraphdlarf_(char *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *), igraphdgemm_(char *, char *, integer *, integer * , integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *); logical bulge; extern /* Subroutine */ int igraphdcopy_(integer *, doublereal *, integer *, doublereal *, integer *); integer infqr, kwtop; extern /* Subroutine */ int igraphdlanv2_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *), igraphdlabad_( doublereal *, doublereal *); extern doublereal igraphdlamch_(char *); extern /* Subroutine */ int igraphdgehrd_(integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, integer *), igraphdlarfg_(integer *, doublereal *, doublereal *, integer *, doublereal *), igraphdlahqr_(logical *, logical *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, integer *, integer *), igraphdlacpy_(char *, integer *, integer *, doublereal *, integer *, doublereal *, integer *); doublereal safmin; extern /* Subroutine */ int igraphdlaset_(char *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *); doublereal safmax; extern /* Subroutine */ int igraphdtrexc_(char *, integer *, doublereal *, integer *, doublereal *, integer *, integer *, integer *, doublereal *, integer *), igraphdormhr_(char *, char *, integer *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, integer *); logical sorted; doublereal smlnum; integer lwkopt; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ================================================================ ==== Estimate optimal workspace. ==== Parameter adjustments */ h_dim1 = *ldh; h_offset = 1 + h_dim1; h__ -= h_offset; z_dim1 = *ldz; z_offset = 1 + z_dim1; z__ -= z_offset; --sr; --si; v_dim1 = *ldv; v_offset = 1 + v_dim1; v -= v_offset; t_dim1 = *ldt; t_offset = 1 + t_dim1; t -= t_offset; wv_dim1 = *ldwv; wv_offset = 1 + wv_dim1; wv -= wv_offset; --work; /* Function Body Computing MIN */ i__1 = *nw, i__2 = *kbot - *ktop + 1; jw = min(i__1,i__2); if (jw <= 2) { lwkopt = 1; } else { /* ==== Workspace query call to DGEHRD ==== */ i__1 = jw - 1; igraphdgehrd_(&jw, &c__1, &i__1, &t[t_offset], ldt, &work[1], &work[1], & c_n1, &info); lwk1 = (integer) work[1]; /* ==== Workspace query call to DORMHR ==== */ i__1 = jw - 1; igraphdormhr_("R", "N", &jw, &jw, &c__1, &i__1, &t[t_offset], ldt, &work[1], &v[v_offset], ldv, &work[1], &c_n1, &info); lwk2 = (integer) work[1]; /* ==== Optimal workspace ==== */ lwkopt = jw + max(lwk1,lwk2); } /* ==== Quick return in case of workspace query. ==== */ if (*lwork == -1) { work[1] = (doublereal) lwkopt; return 0; } /* ==== Nothing to do ... ... for an empty active block ... ==== */ *ns = 0; *nd = 0; work[1] = 1.; if (*ktop > *kbot) { return 0; } /* ... nor for an empty deflation window. ==== */ if (*nw < 1) { return 0; } /* ==== Machine constants ==== */ safmin = igraphdlamch_("SAFE MINIMUM"); safmax = 1. / safmin; igraphdlabad_(&safmin, &safmax); ulp = igraphdlamch_("PRECISION"); smlnum = safmin * ((doublereal) (*n) / ulp); /* ==== Setup deflation window ==== Computing MIN */ i__1 = *nw, i__2 = *kbot - *ktop + 1; jw = min(i__1,i__2); kwtop = *kbot - jw + 1; if (kwtop == *ktop) { s = 0.; } else { s = h__[kwtop + (kwtop - 1) * h_dim1]; } if (*kbot == kwtop) { /* ==== 1-by-1 deflation window: not much to do ==== */ sr[kwtop] = h__[kwtop + kwtop * h_dim1]; si[kwtop] = 0.; *ns = 1; *nd = 0; /* Computing MAX */ d__2 = smlnum, d__3 = ulp * (d__1 = h__[kwtop + kwtop * h_dim1], abs( d__1)); if (abs(s) <= max(d__2,d__3)) { *ns = 0; *nd = 1; if (kwtop > *ktop) { h__[kwtop + (kwtop - 1) * h_dim1] = 0.; } } work[1] = 1.; return 0; } /* ==== Convert to spike-triangular form. (In case of a . rare QR failure, this routine continues to do . aggressive early deflation using that part of . the deflation window that converged using INFQR . here and there to keep track.) ==== */ igraphdlacpy_("U", &jw, &jw, &h__[kwtop + kwtop * h_dim1], ldh, &t[t_offset], ldt); i__1 = jw - 1; i__2 = *ldh + 1; i__3 = *ldt + 1; igraphdcopy_(&i__1, &h__[kwtop + 1 + kwtop * h_dim1], &i__2, &t[t_dim1 + 2], & i__3); igraphdlaset_("A", &jw, &jw, &c_b12, &c_b13, &v[v_offset], ldv); igraphdlahqr_(&c_true, &c_true, &jw, &c__1, &jw, &t[t_offset], ldt, &sr[kwtop], &si[kwtop], &c__1, &jw, &v[v_offset], ldv, &infqr); /* ==== DTREXC needs a clean margin near the diagonal ==== */ i__1 = jw - 3; for (j = 1; j <= i__1; ++j) { t[j + 2 + j * t_dim1] = 0.; t[j + 3 + j * t_dim1] = 0.; /* L10: */ } if (jw > 2) { t[jw + (jw - 2) * t_dim1] = 0.; } /* ==== Deflation detection loop ==== */ *ns = jw; ilst = infqr + 1; L20: if (ilst <= *ns) { if (*ns == 1) { bulge = FALSE_; } else { bulge = t[*ns + (*ns - 1) * t_dim1] != 0.; } /* ==== Small spike tip test for deflation ==== */ if (! bulge) { /* ==== Real eigenvalue ==== */ foo = (d__1 = t[*ns + *ns * t_dim1], abs(d__1)); if (foo == 0.) { foo = abs(s); } /* Computing MAX */ d__2 = smlnum, d__3 = ulp * foo; if ((d__1 = s * v[*ns * v_dim1 + 1], abs(d__1)) <= max(d__2,d__3)) { /* ==== Deflatable ==== */ --(*ns); } else { /* ==== Undeflatable. Move it up out of the way. . (DTREXC can not fail in this case.) ==== */ ifst = *ns; igraphdtrexc_("V", &jw, &t[t_offset], ldt, &v[v_offset], ldv, &ifst, &ilst, &work[1], &info); ++ilst; } } else { /* ==== Complex conjugate pair ==== */ foo = (d__3 = t[*ns + *ns * t_dim1], abs(d__3)) + sqrt((d__1 = t[* ns + (*ns - 1) * t_dim1], abs(d__1))) * sqrt((d__2 = t[* ns - 1 + *ns * t_dim1], abs(d__2))); if (foo == 0.) { foo = abs(s); } /* Computing MAX */ d__3 = (d__1 = s * v[*ns * v_dim1 + 1], abs(d__1)), d__4 = (d__2 = s * v[(*ns - 1) * v_dim1 + 1], abs(d__2)); /* Computing MAX */ d__5 = smlnum, d__6 = ulp * foo; if (max(d__3,d__4) <= max(d__5,d__6)) { /* ==== Deflatable ==== */ *ns += -2; } else { /* ==== Undeflatable. Move them up out of the way. . Fortunately, DTREXC does the right thing with . ILST in case of a rare exchange failure. ==== */ ifst = *ns; igraphdtrexc_("V", &jw, &t[t_offset], ldt, &v[v_offset], ldv, &ifst, &ilst, &work[1], &info); ilst += 2; } } /* ==== End deflation detection loop ==== */ goto L20; } /* ==== Return to Hessenberg form ==== */ if (*ns == 0) { s = 0.; } if (*ns < jw) { /* ==== sorting diagonal blocks of T improves accuracy for . graded matrices. Bubble sort deals well with . exchange failures. ==== */ sorted = FALSE_; i__ = *ns + 1; L30: if (sorted) { goto L50; } sorted = TRUE_; kend = i__ - 1; i__ = infqr + 1; if (i__ == *ns) { k = i__ + 1; } else if (t[i__ + 1 + i__ * t_dim1] == 0.) { k = i__ + 1; } else { k = i__ + 2; } L40: if (k <= kend) { if (k == i__ + 1) { evi = (d__1 = t[i__ + i__ * t_dim1], abs(d__1)); } else { evi = (d__3 = t[i__ + i__ * t_dim1], abs(d__3)) + sqrt((d__1 = t[i__ + 1 + i__ * t_dim1], abs(d__1))) * sqrt((d__2 = t[i__ + (i__ + 1) * t_dim1], abs(d__2))); } if (k == kend) { evk = (d__1 = t[k + k * t_dim1], abs(d__1)); } else if (t[k + 1 + k * t_dim1] == 0.) { evk = (d__1 = t[k + k * t_dim1], abs(d__1)); } else { evk = (d__3 = t[k + k * t_dim1], abs(d__3)) + sqrt((d__1 = t[ k + 1 + k * t_dim1], abs(d__1))) * sqrt((d__2 = t[k + (k + 1) * t_dim1], abs(d__2))); } if (evi >= evk) { i__ = k; } else { sorted = FALSE_; ifst = i__; ilst = k; igraphdtrexc_("V", &jw, &t[t_offset], ldt, &v[v_offset], ldv, &ifst, &ilst, &work[1], &info); if (info == 0) { i__ = ilst; } else { i__ = k; } } if (i__ == kend) { k = i__ + 1; } else if (t[i__ + 1 + i__ * t_dim1] == 0.) { k = i__ + 1; } else { k = i__ + 2; } goto L40; } goto L30; L50: ; } /* ==== Restore shift/eigenvalue array from T ==== */ i__ = jw; L60: if (i__ >= infqr + 1) { if (i__ == infqr + 1) { sr[kwtop + i__ - 1] = t[i__ + i__ * t_dim1]; si[kwtop + i__ - 1] = 0.; --i__; } else if (t[i__ + (i__ - 1) * t_dim1] == 0.) { sr[kwtop + i__ - 1] = t[i__ + i__ * t_dim1]; si[kwtop + i__ - 1] = 0.; --i__; } else { aa = t[i__ - 1 + (i__ - 1) * t_dim1]; cc = t[i__ + (i__ - 1) * t_dim1]; bb = t[i__ - 1 + i__ * t_dim1]; dd = t[i__ + i__ * t_dim1]; igraphdlanv2_(&aa, &bb, &cc, &dd, &sr[kwtop + i__ - 2], &si[kwtop + i__ - 2], &sr[kwtop + i__ - 1], &si[kwtop + i__ - 1], &cs, & sn); i__ += -2; } goto L60; } if (*ns < jw || s == 0.) { if (*ns > 1 && s != 0.) { /* ==== Reflect spike back into lower triangle ==== */ igraphdcopy_(ns, &v[v_offset], ldv, &work[1], &c__1); beta = work[1]; igraphdlarfg_(ns, &beta, &work[2], &c__1, &tau); work[1] = 1.; i__1 = jw - 2; i__2 = jw - 2; igraphdlaset_("L", &i__1, &i__2, &c_b12, &c_b12, &t[t_dim1 + 3], ldt); igraphdlarf_("L", ns, &jw, &work[1], &c__1, &tau, &t[t_offset], ldt, & work[jw + 1]); igraphdlarf_("R", ns, ns, &work[1], &c__1, &tau, &t[t_offset], ldt, & work[jw + 1]); igraphdlarf_("R", &jw, ns, &work[1], &c__1, &tau, &v[v_offset], ldv, & work[jw + 1]); i__1 = *lwork - jw; igraphdgehrd_(&jw, &c__1, ns, &t[t_offset], ldt, &work[1], &work[jw + 1] , &i__1, &info); } /* ==== Copy updated reduced window into place ==== */ if (kwtop > 1) { h__[kwtop + (kwtop - 1) * h_dim1] = s * v[v_dim1 + 1]; } igraphdlacpy_("U", &jw, &jw, &t[t_offset], ldt, &h__[kwtop + kwtop * h_dim1] , ldh); i__1 = jw - 1; i__2 = *ldt + 1; i__3 = *ldh + 1; igraphdcopy_(&i__1, &t[t_dim1 + 2], &i__2, &h__[kwtop + 1 + kwtop * h_dim1], &i__3); /* ==== Accumulate orthogonal matrix in order update . H and Z, if requested. ==== */ if (*ns > 1 && s != 0.) { i__1 = *lwork - jw; igraphdormhr_("R", "N", &jw, ns, &c__1, ns, &t[t_offset], ldt, &work[1], &v[v_offset], ldv, &work[jw + 1], &i__1, &info); } /* ==== Update vertical slab in H ==== */ if (*wantt) { ltop = 1; } else { ltop = *ktop; } i__1 = kwtop - 1; i__2 = *nv; for (krow = ltop; i__2 < 0 ? krow >= i__1 : krow <= i__1; krow += i__2) { /* Computing MIN */ i__3 = *nv, i__4 = kwtop - krow; kln = min(i__3,i__4); igraphdgemm_("N", "N", &kln, &jw, &jw, &c_b13, &h__[krow + kwtop * h_dim1], ldh, &v[v_offset], ldv, &c_b12, &wv[wv_offset], ldwv); igraphdlacpy_("A", &kln, &jw, &wv[wv_offset], ldwv, &h__[krow + kwtop * h_dim1], ldh); /* L70: */ } /* ==== Update horizontal slab in H ==== */ if (*wantt) { i__2 = *n; i__1 = *nh; for (kcol = *kbot + 1; i__1 < 0 ? kcol >= i__2 : kcol <= i__2; kcol += i__1) { /* Computing MIN */ i__3 = *nh, i__4 = *n - kcol + 1; kln = min(i__3,i__4); igraphdgemm_("C", "N", &jw, &kln, &jw, &c_b13, &v[v_offset], ldv, & h__[kwtop + kcol * h_dim1], ldh, &c_b12, &t[t_offset], ldt); igraphdlacpy_("A", &jw, &kln, &t[t_offset], ldt, &h__[kwtop + kcol * h_dim1], ldh); /* L80: */ } } /* ==== Update vertical slab in Z ==== */ if (*wantz) { i__1 = *ihiz; i__2 = *nv; for (krow = *iloz; i__2 < 0 ? krow >= i__1 : krow <= i__1; krow += i__2) { /* Computing MIN */ i__3 = *nv, i__4 = *ihiz - krow + 1; kln = min(i__3,i__4); igraphdgemm_("N", "N", &kln, &jw, &jw, &c_b13, &z__[krow + kwtop * z_dim1], ldz, &v[v_offset], ldv, &c_b12, &wv[ wv_offset], ldwv); igraphdlacpy_("A", &kln, &jw, &wv[wv_offset], ldwv, &z__[krow + kwtop * z_dim1], ldz); /* L90: */ } } } /* ==== Return the number of deflations ... ==== */ *nd = jw - *ns; /* ==== ... and the number of shifts. (Subtracting . INFQR from the spike length takes care . of the case of a rare QR failure while . calculating eigenvalues of the deflation . window.) ==== */ *ns -= infqr; /* ==== Return optimal workspace. ==== */ work[1] = (doublereal) lwkopt; /* ==== End of DLAQR2 ==== */ return 0; } /* igraphdlaqr2_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dvout.c0000644000076500000240000001711013524616145024145 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; /* ----------------------------------------------------------------------- Routine: DVOUT Purpose: Real vector output routine. Usage: CALL DVOUT (LOUT, N, SX, IDIGIT, IFMT) Arguments N - Length of array SX. (Input) SX - Real array to be printed. (Input) IFMT - Format to be used in printing array SX. (Input) IDIGIT - Print up to IABS(IDIGIT) decimal digits per number. (In) If IDIGIT .LT. 0, printing is done with 72 columns. If IDIGIT .GT. 0, printing is done with 132 columns. ----------------------------------------------------------------------- Subroutine */ int igraphdvout_(integer *lout, integer *n, doublereal *sx, integer *idigit, char *ifmt, ftnlen ifmt_len) { /* Format strings */ static char fmt_9999[] = "(/1x,a,/1x,a)"; static char fmt_9998[] = "(1x,i4,\002 - \002,i4,\002:\002,1p,10d12.3)"; static char fmt_9997[] = "(1x,i4,\002 - \002,i4,\002:\002,1x,1p,8d14.5)"; static char fmt_9996[] = "(1x,i4,\002 - \002,i4,\002:\002,1x,1p,6d18.9)"; static char fmt_9995[] = "(1x,i4,\002 - \002,i4,\002:\002,1x,1p,5d24.13)"; static char fmt_9994[] = "(1x,\002 \002)"; /* System generated locals */ integer i__1, i__2, i__3; /* Builtin functions */ integer i_len(char *, ftnlen), s_wsfe(cilist *), do_fio(integer *, char *, ftnlen), e_wsfe(void); /* Local variables */ integer i__, k1, k2, lll; char line[80]; integer ndigit; /* Fortran I/O blocks */ static cilist io___4 = { 0, 0, 0, fmt_9999, 0 }; static cilist io___8 = { 0, 0, 0, fmt_9998, 0 }; static cilist io___9 = { 0, 0, 0, fmt_9997, 0 }; static cilist io___10 = { 0, 0, 0, fmt_9996, 0 }; static cilist io___11 = { 0, 0, 0, fmt_9995, 0 }; static cilist io___12 = { 0, 0, 0, fmt_9998, 0 }; static cilist io___13 = { 0, 0, 0, fmt_9997, 0 }; static cilist io___14 = { 0, 0, 0, fmt_9996, 0 }; static cilist io___15 = { 0, 0, 0, fmt_9995, 0 }; static cilist io___16 = { 0, 0, 0, fmt_9994, 0 }; /* ... ... SPECIFICATIONS FOR ARGUMENTS ... ... SPECIFICATIONS FOR LOCAL VARIABLES ... ... FIRST EXECUTABLE STATEMENT Parameter adjustments */ --sx; /* Function Body Computing MIN */ i__1 = i_len(ifmt, ifmt_len); lll = min(i__1,80); i__1 = lll; for (i__ = 1; i__ <= i__1; ++i__) { *(unsigned char *)&line[i__ - 1] = '-'; /* L10: */ } for (i__ = lll + 1; i__ <= 80; ++i__) { *(unsigned char *)&line[i__ - 1] = ' '; /* L20: */ } io___4.ciunit = *lout; s_wsfe(&io___4); do_fio(&c__1, ifmt, ifmt_len); do_fio(&c__1, line, lll); e_wsfe(); if (*n <= 0) { return 0; } ndigit = *idigit; if (*idigit == 0) { ndigit = 4; } /* ======================================================================= CODE FOR OUTPUT USING 72 COLUMNS FORMAT ======================================================================= */ if (*idigit < 0) { ndigit = -(*idigit); if (ndigit <= 4) { i__1 = *n; for (k1 = 1; k1 <= i__1; k1 += 5) { /* Computing MIN */ i__2 = *n, i__3 = k1 + 4; k2 = min(i__2,i__3); io___8.ciunit = *lout; s_wsfe(&io___8); do_fio(&c__1, (char *)&k1, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&k2, (ftnlen)sizeof(integer)); i__2 = k2; for (i__ = k1; i__ <= i__2; ++i__) { do_fio(&c__1, (char *)&sx[i__], (ftnlen)sizeof(doublereal) ); } e_wsfe(); /* L30: */ } } else if (ndigit <= 6) { i__1 = *n; for (k1 = 1; k1 <= i__1; k1 += 4) { /* Computing MIN */ i__2 = *n, i__3 = k1 + 3; k2 = min(i__2,i__3); io___9.ciunit = *lout; s_wsfe(&io___9); do_fio(&c__1, (char *)&k1, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&k2, (ftnlen)sizeof(integer)); i__2 = k2; for (i__ = k1; i__ <= i__2; ++i__) { do_fio(&c__1, (char *)&sx[i__], (ftnlen)sizeof(doublereal) ); } e_wsfe(); /* L40: */ } } else if (ndigit <= 10) { i__1 = *n; for (k1 = 1; k1 <= i__1; k1 += 3) { /* Computing MIN */ i__2 = *n, i__3 = k1 + 2; k2 = min(i__2,i__3); io___10.ciunit = *lout; s_wsfe(&io___10); do_fio(&c__1, (char *)&k1, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&k2, (ftnlen)sizeof(integer)); i__2 = k2; for (i__ = k1; i__ <= i__2; ++i__) { do_fio(&c__1, (char *)&sx[i__], (ftnlen)sizeof(doublereal) ); } e_wsfe(); /* L50: */ } } else { i__1 = *n; for (k1 = 1; k1 <= i__1; k1 += 2) { /* Computing MIN */ i__2 = *n, i__3 = k1 + 1; k2 = min(i__2,i__3); io___11.ciunit = *lout; s_wsfe(&io___11); do_fio(&c__1, (char *)&k1, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&k2, (ftnlen)sizeof(integer)); i__2 = k2; for (i__ = k1; i__ <= i__2; ++i__) { do_fio(&c__1, (char *)&sx[i__], (ftnlen)sizeof(doublereal) ); } e_wsfe(); /* L60: */ } } /* ======================================================================= CODE FOR OUTPUT USING 132 COLUMNS FORMAT ======================================================================= */ } else { if (ndigit <= 4) { i__1 = *n; for (k1 = 1; k1 <= i__1; k1 += 10) { /* Computing MIN */ i__2 = *n, i__3 = k1 + 9; k2 = min(i__2,i__3); io___12.ciunit = *lout; s_wsfe(&io___12); do_fio(&c__1, (char *)&k1, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&k2, (ftnlen)sizeof(integer)); i__2 = k2; for (i__ = k1; i__ <= i__2; ++i__) { do_fio(&c__1, (char *)&sx[i__], (ftnlen)sizeof(doublereal) ); } e_wsfe(); /* L70: */ } } else if (ndigit <= 6) { i__1 = *n; for (k1 = 1; k1 <= i__1; k1 += 8) { /* Computing MIN */ i__2 = *n, i__3 = k1 + 7; k2 = min(i__2,i__3); io___13.ciunit = *lout; s_wsfe(&io___13); do_fio(&c__1, (char *)&k1, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&k2, (ftnlen)sizeof(integer)); i__2 = k2; for (i__ = k1; i__ <= i__2; ++i__) { do_fio(&c__1, (char *)&sx[i__], (ftnlen)sizeof(doublereal) ); } e_wsfe(); /* L80: */ } } else if (ndigit <= 10) { i__1 = *n; for (k1 = 1; k1 <= i__1; k1 += 6) { /* Computing MIN */ i__2 = *n, i__3 = k1 + 5; k2 = min(i__2,i__3); io___14.ciunit = *lout; s_wsfe(&io___14); do_fio(&c__1, (char *)&k1, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&k2, (ftnlen)sizeof(integer)); i__2 = k2; for (i__ = k1; i__ <= i__2; ++i__) { do_fio(&c__1, (char *)&sx[i__], (ftnlen)sizeof(doublereal) ); } e_wsfe(); /* L90: */ } } else { i__1 = *n; for (k1 = 1; k1 <= i__1; k1 += 5) { /* Computing MIN */ i__2 = *n, i__3 = k1 + 4; k2 = min(i__2,i__3); io___15.ciunit = *lout; s_wsfe(&io___15); do_fio(&c__1, (char *)&k1, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&k2, (ftnlen)sizeof(integer)); i__2 = k2; for (i__ = k1; i__ <= i__2; ++i__) { do_fio(&c__1, (char *)&sx[i__], (ftnlen)sizeof(doublereal) ); } e_wsfe(); /* L100: */ } } } io___16.ciunit = *lout; s_wsfe(&io___16); e_wsfe(); return 0; } /* igraphdvout_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dgetrf.c0000644000076500000240000001745613524616145024274 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static integer c_n1 = -1; static doublereal c_b16 = 1.; static doublereal c_b19 = -1.; /* > \brief \b DGETRF =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DGETRF + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DGETRF( M, N, A, LDA, IPIV, INFO ) INTEGER INFO, LDA, M, N INTEGER IPIV( * ) DOUBLE PRECISION A( LDA, * ) > \par Purpose: ============= > > \verbatim > > DGETRF computes an LU factorization of a general M-by-N matrix A > using partial pivoting with row interchanges. > > The factorization has the form > A = P * L * U > where P is a permutation matrix, L is lower triangular with unit > diagonal elements (lower trapezoidal if m > n), and U is upper > triangular (upper trapezoidal if m < n). > > This is the right-looking Level 3 BLAS version of the algorithm. > \endverbatim Arguments: ========== > \param[in] M > \verbatim > M is INTEGER > The number of rows of the matrix A. M >= 0. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The number of columns of the matrix A. N >= 0. > \endverbatim > > \param[in,out] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,N) > On entry, the M-by-N matrix to be factored. > On exit, the factors L and U from the factorization > A = P*L*U; the unit diagonal elements of L are not stored. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. LDA >= max(1,M). > \endverbatim > > \param[out] IPIV > \verbatim > IPIV is INTEGER array, dimension (min(M,N)) > The pivot indices; for 1 <= i <= min(M,N), row i of the > matrix was interchanged with row IPIV(i). > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value > > 0: if INFO = i, U(i,i) is exactly zero. The factorization > has been completed, but the factor U is exactly > singular, and division by zero will occur if it is used > to solve a system of equations. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2011 > \ingroup doubleGEcomputational ===================================================================== Subroutine */ int igraphdgetrf_(integer *m, integer *n, doublereal *a, integer * lda, integer *ipiv, integer *info) { /* System generated locals */ integer a_dim1, a_offset, i__1, i__2, i__3, i__4, i__5; /* Local variables */ integer i__, j, jb, nb; extern /* Subroutine */ int igraphdgemm_(char *, char *, integer *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *); integer iinfo; extern /* Subroutine */ int igraphdtrsm_(char *, char *, char *, char *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *), igraphdgetf2_( integer *, integer *, doublereal *, integer *, integer *, integer *), igraphxerbla_(char *, integer *, ftnlen); extern integer igraphilaenv_(integer *, char *, char *, integer *, integer *, integer *, integer *, ftnlen, ftnlen); extern /* Subroutine */ int igraphdlaswp_(integer *, doublereal *, integer *, integer *, integer *, integer *, integer *); /* -- LAPACK computational routine (version 3.4.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2011 ===================================================================== Test the input parameters. Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --ipiv; /* Function Body */ *info = 0; if (*m < 0) { *info = -1; } else if (*n < 0) { *info = -2; } else if (*lda < max(1,*m)) { *info = -4; } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DGETRF", &i__1, (ftnlen)6); return 0; } /* Quick return if possible */ if (*m == 0 || *n == 0) { return 0; } /* Determine the block size for this environment. */ nb = igraphilaenv_(&c__1, "DGETRF", " ", m, n, &c_n1, &c_n1, (ftnlen)6, (ftnlen) 1); if (nb <= 1 || nb >= min(*m,*n)) { /* Use unblocked code. */ igraphdgetf2_(m, n, &a[a_offset], lda, &ipiv[1], info); } else { /* Use blocked code. */ i__1 = min(*m,*n); i__2 = nb; for (j = 1; i__2 < 0 ? j >= i__1 : j <= i__1; j += i__2) { /* Computing MIN */ i__3 = min(*m,*n) - j + 1; jb = min(i__3,nb); /* Factor diagonal and subdiagonal blocks and test for exact singularity. */ i__3 = *m - j + 1; igraphdgetf2_(&i__3, &jb, &a[j + j * a_dim1], lda, &ipiv[j], &iinfo); /* Adjust INFO and the pivot indices. */ if (*info == 0 && iinfo > 0) { *info = iinfo + j - 1; } /* Computing MIN */ i__4 = *m, i__5 = j + jb - 1; i__3 = min(i__4,i__5); for (i__ = j; i__ <= i__3; ++i__) { ipiv[i__] = j - 1 + ipiv[i__]; /* L10: */ } /* Apply interchanges to columns 1:J-1. */ i__3 = j - 1; i__4 = j + jb - 1; igraphdlaswp_(&i__3, &a[a_offset], lda, &j, &i__4, &ipiv[1], &c__1); if (j + jb <= *n) { /* Apply interchanges to columns J+JB:N. */ i__3 = *n - j - jb + 1; i__4 = j + jb - 1; igraphdlaswp_(&i__3, &a[(j + jb) * a_dim1 + 1], lda, &j, &i__4, & ipiv[1], &c__1); /* Compute block row of U. */ i__3 = *n - j - jb + 1; igraphdtrsm_("Left", "Lower", "No transpose", "Unit", &jb, &i__3, & c_b16, &a[j + j * a_dim1], lda, &a[j + (j + jb) * a_dim1], lda); if (j + jb <= *m) { /* Update trailing submatrix. */ i__3 = *m - j - jb + 1; i__4 = *n - j - jb + 1; igraphdgemm_("No transpose", "No transpose", &i__3, &i__4, &jb, &c_b19, &a[j + jb + j * a_dim1], lda, &a[j + (j + jb) * a_dim1], lda, &c_b16, &a[j + jb + (j + jb) * a_dim1], lda); } } /* L20: */ } } return 0; /* End of DGETRF */ } /* igraphdgetrf_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlange.c0000644000076500000240000001532613524616145024245 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; /* > \brief \b DLANGE returns the value of the 1-norm, Frobenius norm, infinity-norm, or the largest absolute value of any element of a general rectangular matrix. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLANGE + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== DOUBLE PRECISION FUNCTION DLANGE( NORM, M, N, A, LDA, WORK ) CHARACTER NORM INTEGER LDA, M, N DOUBLE PRECISION A( LDA, * ), WORK( * ) > \par Purpose: ============= > > \verbatim > > DLANGE returns the value of the one norm, or the Frobenius norm, or > the infinity norm, or the element of largest absolute value of a > real matrix A. > \endverbatim > > \return DLANGE > \verbatim > > DLANGE = ( max(abs(A(i,j))), NORM = 'M' or 'm' > ( > ( norm1(A), NORM = '1', 'O' or 'o' > ( > ( normI(A), NORM = 'I' or 'i' > ( > ( normF(A), NORM = 'F', 'f', 'E' or 'e' > > where norm1 denotes the one norm of a matrix (maximum column sum), > normI denotes the infinity norm of a matrix (maximum row sum) and > normF denotes the Frobenius norm of a matrix (square root of sum of > squares). Note that max(abs(A(i,j))) is not a consistent matrix norm. > \endverbatim Arguments: ========== > \param[in] NORM > \verbatim > NORM is CHARACTER*1 > Specifies the value to be returned in DLANGE as described > above. > \endverbatim > > \param[in] M > \verbatim > M is INTEGER > The number of rows of the matrix A. M >= 0. When M = 0, > DLANGE is set to zero. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The number of columns of the matrix A. N >= 0. When N = 0, > DLANGE is set to zero. > \endverbatim > > \param[in] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,N) > The m by n matrix A. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. LDA >= max(M,1). > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (MAX(1,LWORK)), > where LWORK >= M when NORM = 'I'; otherwise, WORK is not > referenced. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleGEauxiliary ===================================================================== */ doublereal igraphdlange_(char *norm, integer *m, integer *n, doublereal *a, integer *lda, doublereal *work) { /* System generated locals */ integer a_dim1, a_offset, i__1, i__2; doublereal ret_val, d__1; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ integer i__, j; doublereal sum, temp, scale; extern logical igraphlsame_(char *, char *); doublereal value = 0.; extern logical igraphdisnan_(doublereal *); extern /* Subroutine */ int igraphdlassq_(integer *, doublereal *, integer *, doublereal *, doublereal *); /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --work; /* Function Body */ if (min(*m,*n) == 0) { value = 0.; } else if (igraphlsame_(norm, "M")) { /* Find max(abs(A(i,j))). */ value = 0.; i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { temp = (d__1 = a[i__ + j * a_dim1], abs(d__1)); if (value < temp || igraphdisnan_(&temp)) { value = temp; } /* L10: */ } /* L20: */ } } else if (igraphlsame_(norm, "O") || *(unsigned char *) norm == '1') { /* Find norm1(A). */ value = 0.; i__1 = *n; for (j = 1; j <= i__1; ++j) { sum = 0.; i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { sum += (d__1 = a[i__ + j * a_dim1], abs(d__1)); /* L30: */ } if (value < sum || igraphdisnan_(&sum)) { value = sum; } /* L40: */ } } else if (igraphlsame_(norm, "I")) { /* Find normI(A). */ i__1 = *m; for (i__ = 1; i__ <= i__1; ++i__) { work[i__] = 0.; /* L50: */ } i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { work[i__] += (d__1 = a[i__ + j * a_dim1], abs(d__1)); /* L60: */ } /* L70: */ } value = 0.; i__1 = *m; for (i__ = 1; i__ <= i__1; ++i__) { temp = work[i__]; if (value < temp || igraphdisnan_(&temp)) { value = temp; } /* L80: */ } } else if (igraphlsame_(norm, "F") || igraphlsame_(norm, "E")) { /* Find normF(A). */ scale = 0.; sum = 1.; i__1 = *n; for (j = 1; j <= i__1; ++j) { igraphdlassq_(m, &a[j * a_dim1 + 1], &c__1, &scale, &sum); /* L90: */ } value = scale * sqrt(sum); } ret_val = value; return ret_val; /* End of DLANGE */ } /* igraphdlange_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dsyr2k.c0000644000076500000240000002632313524616145024230 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Subroutine */ int igraphdsyr2k_(char *uplo, char *trans, integer *n, integer *k, doublereal *alpha, doublereal *a, integer *lda, doublereal *b, integer *ldb, doublereal *beta, doublereal *c__, integer *ldc) { /* System generated locals */ integer a_dim1, a_offset, b_dim1, b_offset, c_dim1, c_offset, i__1, i__2, i__3; /* Local variables */ integer i__, j, l, info; doublereal temp1, temp2; extern logical igraphlsame_(char *, char *); integer nrowa; logical upper; extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); /* Purpose ======= DSYR2K performs one of the symmetric rank 2k operations C := alpha*A*B**T + alpha*B*A**T + beta*C, or C := alpha*A**T*B + alpha*B**T*A + beta*C, where alpha and beta are scalars, C is an n by n symmetric matrix and A and B are n by k matrices in the first case and k by n matrices in the second case. Arguments ========== UPLO - CHARACTER*1. On entry, UPLO specifies whether the upper or lower triangular part of the array C is to be referenced as follows: UPLO = 'U' or 'u' Only the upper triangular part of C is to be referenced. UPLO = 'L' or 'l' Only the lower triangular part of C is to be referenced. Unchanged on exit. TRANS - CHARACTER*1. On entry, TRANS specifies the operation to be performed as follows: TRANS = 'N' or 'n' C := alpha*A*B**T + alpha*B*A**T + beta*C. TRANS = 'T' or 't' C := alpha*A**T*B + alpha*B**T*A + beta*C. TRANS = 'C' or 'c' C := alpha*A**T*B + alpha*B**T*A + beta*C. Unchanged on exit. N - INTEGER. On entry, N specifies the order of the matrix C. N must be at least zero. Unchanged on exit. K - INTEGER. On entry with TRANS = 'N' or 'n', K specifies the number of columns of the matrices A and B, and on entry with TRANS = 'T' or 't' or 'C' or 'c', K specifies the number of rows of the matrices A and B. K must be at least zero. Unchanged on exit. ALPHA - DOUBLE PRECISION. On entry, ALPHA specifies the scalar alpha. Unchanged on exit. A - DOUBLE PRECISION array of DIMENSION ( LDA, ka ), where ka is k when TRANS = 'N' or 'n', and is n otherwise. Before entry with TRANS = 'N' or 'n', the leading n by k part of the array A must contain the matrix A, otherwise the leading k by n part of the array A must contain the matrix A. Unchanged on exit. LDA - INTEGER. On entry, LDA specifies the first dimension of A as declared in the calling (sub) program. When TRANS = 'N' or 'n' then LDA must be at least max( 1, n ), otherwise LDA must be at least max( 1, k ). Unchanged on exit. B - DOUBLE PRECISION array of DIMENSION ( LDB, kb ), where kb is k when TRANS = 'N' or 'n', and is n otherwise. Before entry with TRANS = 'N' or 'n', the leading n by k part of the array B must contain the matrix B, otherwise the leading k by n part of the array B must contain the matrix B. Unchanged on exit. LDB - INTEGER. On entry, LDB specifies the first dimension of B as declared in the calling (sub) program. When TRANS = 'N' or 'n' then LDB must be at least max( 1, n ), otherwise LDB must be at least max( 1, k ). Unchanged on exit. BETA - DOUBLE PRECISION. On entry, BETA specifies the scalar beta. Unchanged on exit. C - DOUBLE PRECISION array of DIMENSION ( LDC, n ). Before entry with UPLO = 'U' or 'u', the leading n by n upper triangular part of the array C must contain the upper triangular part of the symmetric matrix and the strictly lower triangular part of C is not referenced. On exit, the upper triangular part of the array C is overwritten by the upper triangular part of the updated matrix. Before entry with UPLO = 'L' or 'l', the leading n by n lower triangular part of the array C must contain the lower triangular part of the symmetric matrix and the strictly upper triangular part of C is not referenced. On exit, the lower triangular part of the array C is overwritten by the lower triangular part of the updated matrix. LDC - INTEGER. On entry, LDC specifies the first dimension of C as declared in the calling (sub) program. LDC must be at least max( 1, n ). Unchanged on exit. Further Details =============== Level 3 Blas routine. -- Written on 8-February-1989. Jack Dongarra, Argonne National Laboratory. Iain Duff, AERE Harwell. Jeremy Du Croz, Numerical Algorithms Group Ltd. Sven Hammarling, Numerical Algorithms Group Ltd. ===================================================================== Test the input parameters. Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; b_dim1 = *ldb; b_offset = 1 + b_dim1; b -= b_offset; c_dim1 = *ldc; c_offset = 1 + c_dim1; c__ -= c_offset; /* Function Body */ if (igraphlsame_(trans, "N")) { nrowa = *n; } else { nrowa = *k; } upper = igraphlsame_(uplo, "U"); info = 0; if (! upper && ! igraphlsame_(uplo, "L")) { info = 1; } else if (! igraphlsame_(trans, "N") && ! igraphlsame_(trans, "T") && ! igraphlsame_(trans, "C")) { info = 2; } else if (*n < 0) { info = 3; } else if (*k < 0) { info = 4; } else if (*lda < max(1,nrowa)) { info = 7; } else if (*ldb < max(1,nrowa)) { info = 9; } else if (*ldc < max(1,*n)) { info = 12; } if (info != 0) { igraphxerbla_("DSYR2K", &info, (ftnlen)6); return 0; } /* Quick return if possible. */ if (*n == 0 || (*alpha == 0. || *k == 0) && *beta == 1.) { return 0; } /* And when alpha.eq.zero. */ if (*alpha == 0.) { if (upper) { if (*beta == 0.) { i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = j; for (i__ = 1; i__ <= i__2; ++i__) { c__[i__ + j * c_dim1] = 0.; /* L10: */ } /* L20: */ } } else { i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = j; for (i__ = 1; i__ <= i__2; ++i__) { c__[i__ + j * c_dim1] = *beta * c__[i__ + j * c_dim1]; /* L30: */ } /* L40: */ } } } else { if (*beta == 0.) { i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = *n; for (i__ = j; i__ <= i__2; ++i__) { c__[i__ + j * c_dim1] = 0.; /* L50: */ } /* L60: */ } } else { i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = *n; for (i__ = j; i__ <= i__2; ++i__) { c__[i__ + j * c_dim1] = *beta * c__[i__ + j * c_dim1]; /* L70: */ } /* L80: */ } } } return 0; } /* Start the operations. */ if (igraphlsame_(trans, "N")) { /* Form C := alpha*A*B**T + alpha*B*A**T + C. */ if (upper) { i__1 = *n; for (j = 1; j <= i__1; ++j) { if (*beta == 0.) { i__2 = j; for (i__ = 1; i__ <= i__2; ++i__) { c__[i__ + j * c_dim1] = 0.; /* L90: */ } } else if (*beta != 1.) { i__2 = j; for (i__ = 1; i__ <= i__2; ++i__) { c__[i__ + j * c_dim1] = *beta * c__[i__ + j * c_dim1]; /* L100: */ } } i__2 = *k; for (l = 1; l <= i__2; ++l) { if (a[j + l * a_dim1] != 0. || b[j + l * b_dim1] != 0.) { temp1 = *alpha * b[j + l * b_dim1]; temp2 = *alpha * a[j + l * a_dim1]; i__3 = j; for (i__ = 1; i__ <= i__3; ++i__) { c__[i__ + j * c_dim1] = c__[i__ + j * c_dim1] + a[ i__ + l * a_dim1] * temp1 + b[i__ + l * b_dim1] * temp2; /* L110: */ } } /* L120: */ } /* L130: */ } } else { i__1 = *n; for (j = 1; j <= i__1; ++j) { if (*beta == 0.) { i__2 = *n; for (i__ = j; i__ <= i__2; ++i__) { c__[i__ + j * c_dim1] = 0.; /* L140: */ } } else if (*beta != 1.) { i__2 = *n; for (i__ = j; i__ <= i__2; ++i__) { c__[i__ + j * c_dim1] = *beta * c__[i__ + j * c_dim1]; /* L150: */ } } i__2 = *k; for (l = 1; l <= i__2; ++l) { if (a[j + l * a_dim1] != 0. || b[j + l * b_dim1] != 0.) { temp1 = *alpha * b[j + l * b_dim1]; temp2 = *alpha * a[j + l * a_dim1]; i__3 = *n; for (i__ = j; i__ <= i__3; ++i__) { c__[i__ + j * c_dim1] = c__[i__ + j * c_dim1] + a[ i__ + l * a_dim1] * temp1 + b[i__ + l * b_dim1] * temp2; /* L160: */ } } /* L170: */ } /* L180: */ } } } else { /* Form C := alpha*A**T*B + alpha*B**T*A + C. */ if (upper) { i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = j; for (i__ = 1; i__ <= i__2; ++i__) { temp1 = 0.; temp2 = 0.; i__3 = *k; for (l = 1; l <= i__3; ++l) { temp1 += a[l + i__ * a_dim1] * b[l + j * b_dim1]; temp2 += b[l + i__ * b_dim1] * a[l + j * a_dim1]; /* L190: */ } if (*beta == 0.) { c__[i__ + j * c_dim1] = *alpha * temp1 + *alpha * temp2; } else { c__[i__ + j * c_dim1] = *beta * c__[i__ + j * c_dim1] + *alpha * temp1 + *alpha * temp2; } /* L200: */ } /* L210: */ } } else { i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = *n; for (i__ = j; i__ <= i__2; ++i__) { temp1 = 0.; temp2 = 0.; i__3 = *k; for (l = 1; l <= i__3; ++l) { temp1 += a[l + i__ * a_dim1] * b[l + j * b_dim1]; temp2 += b[l + i__ * b_dim1] * a[l + j * a_dim1]; /* L220: */ } if (*beta == 0.) { c__[i__ + j * c_dim1] = *alpha * temp1 + *alpha * temp2; } else { c__[i__ + j * c_dim1] = *beta * c__[i__ + j * c_dim1] + *alpha * temp1 + *alpha * temp2; } /* L230: */ } /* L240: */ } } } return 0; /* End of DSYR2K. */ } /* igraphdsyr2k_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/ilaenv.c0000644000076500000240000005225413524616145024272 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static real c_b163 = 0.f; static real c_b164 = 1.f; static integer c__0 = 0; /* > \brief \b ILAENV =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download ILAENV + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== INTEGER FUNCTION ILAENV( ISPEC, NAME, OPTS, N1, N2, N3, N4 ) CHARACTER*( * ) NAME, OPTS INTEGER ISPEC, N1, N2, N3, N4 > \par Purpose: ============= > > \verbatim > > ILAENV is called from the LAPACK routines to choose problem-dependent > parameters for the local environment. See ISPEC for a description of > the parameters. > > ILAENV returns an INTEGER > if ILAENV >= 0: ILAENV returns the value of the parameter specified by ISPEC > if ILAENV < 0: if ILAENV = -k, the k-th argument had an illegal value. > > This version provides a set of parameters which should give good, > but not optimal, performance on many of the currently available > computers. Users are encouraged to modify this subroutine to set > the tuning parameters for their particular machine using the option > and problem size information in the arguments. > > This routine will not function correctly if it is converted to all > lower case. Converting it to all upper case is allowed. > \endverbatim Arguments: ========== > \param[in] ISPEC > \verbatim > ISPEC is INTEGER > Specifies the parameter to be returned as the value of > ILAENV. > = 1: the optimal blocksize; if this value is 1, an unblocked > algorithm will give the best performance. > = 2: the minimum block size for which the block routine > should be used; if the usable block size is less than > this value, an unblocked routine should be used. > = 3: the crossover point (in a block routine, for N less > than this value, an unblocked routine should be used) > = 4: the number of shifts, used in the nonsymmetric > eigenvalue routines (DEPRECATED) > = 5: the minimum column dimension for blocking to be used; > rectangular blocks must have dimension at least k by m, > where k is given by ILAENV(2,...) and m by ILAENV(5,...) > = 6: the crossover point for the SVD (when reducing an m by n > matrix to bidiagonal form, if max(m,n)/min(m,n) exceeds > this value, a QR factorization is used first to reduce > the matrix to a triangular form.) > = 7: the number of processors > = 8: the crossover point for the multishift QR method > for nonsymmetric eigenvalue problems (DEPRECATED) > = 9: maximum size of the subproblems at the bottom of the > computation tree in the divide-and-conquer algorithm > (used by xGELSD and xGESDD) > =10: ieee NaN arithmetic can be trusted not to trap > =11: infinity arithmetic can be trusted not to trap > 12 <= ISPEC <= 16: > xHSEQR or one of its subroutines, > see IPARMQ for detailed explanation > \endverbatim > > \param[in] NAME > \verbatim > NAME is CHARACTER*(*) > The name of the calling subroutine, in either upper case or > lower case. > \endverbatim > > \param[in] OPTS > \verbatim > OPTS is CHARACTER*(*) > The character options to the subroutine NAME, concatenated > into a single character string. For example, UPLO = 'U', > TRANS = 'T', and DIAG = 'N' for a triangular routine would > be specified as OPTS = 'UTN'. > \endverbatim > > \param[in] N1 > \verbatim > N1 is INTEGER > \endverbatim > > \param[in] N2 > \verbatim > N2 is INTEGER > \endverbatim > > \param[in] N3 > \verbatim > N3 is INTEGER > \endverbatim > > \param[in] N4 > \verbatim > N4 is INTEGER > Problem dimensions for the subroutine NAME; these may not all > be required. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2011 > \ingroup auxOTHERauxiliary > \par Further Details: ===================== > > \verbatim > > The following conventions have been used when calling ILAENV from the > LAPACK routines: > 1) OPTS is a concatenation of all of the character options to > subroutine NAME, in the same order that they appear in the > argument list for NAME, even if they are not used in determining > the value of the parameter specified by ISPEC. > 2) The problem dimensions N1, N2, N3, N4 are specified in the order > that they appear in the argument list for NAME. N1 is used > first, N2 second, and so on, and unused problem dimensions are > passed a value of -1. > 3) The parameter value returned by ILAENV is checked for validity in > the calling subroutine. For example, ILAENV is used to retrieve > the optimal blocksize for STRTRI as follows: > > NB = ILAENV( 1, 'STRTRI', UPLO // DIAG, N, -1, -1, -1 ) > IF( NB.LE.1 ) NB = MAX( 1, N ) > \endverbatim > ===================================================================== */ integer igraphilaenv_(integer *ispec, char *name__, char *opts, integer *n1, integer *n2, integer *n3, integer *n4, ftnlen name_len, ftnlen opts_len) { /* System generated locals */ integer ret_val; /* Builtin functions Subroutine */ int s_copy(char *, char *, ftnlen, ftnlen); integer s_cmp(char *, char *, ftnlen, ftnlen); /* Local variables */ integer i__; char c1[1], c2[2], c3[3], c4[2]; integer ic, nb, iz, nx; logical cname; integer nbmin; logical sname; extern integer igraphieeeck_(integer *, real *, real *); char subnam[6]; extern integer igraphiparmq_(integer *, char *, char *, integer *, integer *, integer *, integer *); /* -- LAPACK auxiliary routine (version 3.4.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2011 ===================================================================== */ switch (*ispec) { case 1: goto L10; case 2: goto L10; case 3: goto L10; case 4: goto L80; case 5: goto L90; case 6: goto L100; case 7: goto L110; case 8: goto L120; case 9: goto L130; case 10: goto L140; case 11: goto L150; case 12: goto L160; case 13: goto L160; case 14: goto L160; case 15: goto L160; case 16: goto L160; } /* Invalid value for ISPEC */ ret_val = -1; return ret_val; L10: /* Convert NAME to upper case if the first character is lower case. */ ret_val = 1; s_copy(subnam, name__, (ftnlen)6, name_len); ic = *(unsigned char *)subnam; iz = 'Z'; if (iz == 90 || iz == 122) { /* ASCII character set */ if (ic >= 97 && ic <= 122) { *(unsigned char *)subnam = (char) (ic - 32); for (i__ = 2; i__ <= 6; ++i__) { ic = *(unsigned char *)&subnam[i__ - 1]; if (ic >= 97 && ic <= 122) { *(unsigned char *)&subnam[i__ - 1] = (char) (ic - 32); } /* L20: */ } } } else if (iz == 233 || iz == 169) { /* EBCDIC character set */ if (ic >= 129 && ic <= 137 || ic >= 145 && ic <= 153 || ic >= 162 && ic <= 169) { *(unsigned char *)subnam = (char) (ic + 64); for (i__ = 2; i__ <= 6; ++i__) { ic = *(unsigned char *)&subnam[i__ - 1]; if (ic >= 129 && ic <= 137 || ic >= 145 && ic <= 153 || ic >= 162 && ic <= 169) { *(unsigned char *)&subnam[i__ - 1] = (char) (ic + 64); } /* L30: */ } } } else if (iz == 218 || iz == 250) { /* Prime machines: ASCII+128 */ if (ic >= 225 && ic <= 250) { *(unsigned char *)subnam = (char) (ic - 32); for (i__ = 2; i__ <= 6; ++i__) { ic = *(unsigned char *)&subnam[i__ - 1]; if (ic >= 225 && ic <= 250) { *(unsigned char *)&subnam[i__ - 1] = (char) (ic - 32); } /* L40: */ } } } *(unsigned char *)c1 = *(unsigned char *)subnam; sname = *(unsigned char *)c1 == 'S' || *(unsigned char *)c1 == 'D'; cname = *(unsigned char *)c1 == 'C' || *(unsigned char *)c1 == 'Z'; if (! (cname || sname)) { return ret_val; } s_copy(c2, subnam + 1, (ftnlen)2, (ftnlen)2); s_copy(c3, subnam + 3, (ftnlen)3, (ftnlen)3); s_copy(c4, c3 + 1, (ftnlen)2, (ftnlen)2); switch (*ispec) { case 1: goto L50; case 2: goto L60; case 3: goto L70; } L50: /* ISPEC = 1: block size In these examples, separate code is provided for setting NB for real and complex. We assume that NB will take the same value in single or double precision. */ nb = 1; if (s_cmp(c2, "GE", (ftnlen)2, (ftnlen)2) == 0) { if (s_cmp(c3, "TRF", (ftnlen)3, (ftnlen)3) == 0) { if (sname) { nb = 64; } else { nb = 64; } } else if (s_cmp(c3, "QRF", (ftnlen)3, (ftnlen)3) == 0 || s_cmp(c3, "RQF", (ftnlen)3, (ftnlen)3) == 0 || s_cmp(c3, "LQF", (ftnlen) 3, (ftnlen)3) == 0 || s_cmp(c3, "QLF", (ftnlen)3, (ftnlen)3) == 0) { if (sname) { nb = 32; } else { nb = 32; } } else if (s_cmp(c3, "HRD", (ftnlen)3, (ftnlen)3) == 0) { if (sname) { nb = 32; } else { nb = 32; } } else if (s_cmp(c3, "BRD", (ftnlen)3, (ftnlen)3) == 0) { if (sname) { nb = 32; } else { nb = 32; } } else if (s_cmp(c3, "TRI", (ftnlen)3, (ftnlen)3) == 0) { if (sname) { nb = 64; } else { nb = 64; } } } else if (s_cmp(c2, "PO", (ftnlen)2, (ftnlen)2) == 0) { if (s_cmp(c3, "TRF", (ftnlen)3, (ftnlen)3) == 0) { if (sname) { nb = 64; } else { nb = 64; } } } else if (s_cmp(c2, "SY", (ftnlen)2, (ftnlen)2) == 0) { if (s_cmp(c3, "TRF", (ftnlen)3, (ftnlen)3) == 0) { if (sname) { nb = 64; } else { nb = 64; } } else if (sname && s_cmp(c3, "TRD", (ftnlen)3, (ftnlen)3) == 0) { nb = 32; } else if (sname && s_cmp(c3, "GST", (ftnlen)3, (ftnlen)3) == 0) { nb = 64; } } else if (cname && s_cmp(c2, "HE", (ftnlen)2, (ftnlen)2) == 0) { if (s_cmp(c3, "TRF", (ftnlen)3, (ftnlen)3) == 0) { nb = 64; } else if (s_cmp(c3, "TRD", (ftnlen)3, (ftnlen)3) == 0) { nb = 32; } else if (s_cmp(c3, "GST", (ftnlen)3, (ftnlen)3) == 0) { nb = 64; } } else if (sname && s_cmp(c2, "OR", (ftnlen)2, (ftnlen)2) == 0) { if (*(unsigned char *)c3 == 'G') { if (s_cmp(c4, "QR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "RQ", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "LQ", (ftnlen)2, ( ftnlen)2) == 0 || s_cmp(c4, "QL", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "HR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp( c4, "TR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "BR", ( ftnlen)2, (ftnlen)2) == 0) { nb = 32; } } else if (*(unsigned char *)c3 == 'M') { if (s_cmp(c4, "QR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "RQ", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "LQ", (ftnlen)2, ( ftnlen)2) == 0 || s_cmp(c4, "QL", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "HR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp( c4, "TR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "BR", ( ftnlen)2, (ftnlen)2) == 0) { nb = 32; } } } else if (cname && s_cmp(c2, "UN", (ftnlen)2, (ftnlen)2) == 0) { if (*(unsigned char *)c3 == 'G') { if (s_cmp(c4, "QR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "RQ", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "LQ", (ftnlen)2, ( ftnlen)2) == 0 || s_cmp(c4, "QL", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "HR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp( c4, "TR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "BR", ( ftnlen)2, (ftnlen)2) == 0) { nb = 32; } } else if (*(unsigned char *)c3 == 'M') { if (s_cmp(c4, "QR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "RQ", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "LQ", (ftnlen)2, ( ftnlen)2) == 0 || s_cmp(c4, "QL", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "HR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp( c4, "TR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "BR", ( ftnlen)2, (ftnlen)2) == 0) { nb = 32; } } } else if (s_cmp(c2, "GB", (ftnlen)2, (ftnlen)2) == 0) { if (s_cmp(c3, "TRF", (ftnlen)3, (ftnlen)3) == 0) { if (sname) { if (*n4 <= 64) { nb = 1; } else { nb = 32; } } else { if (*n4 <= 64) { nb = 1; } else { nb = 32; } } } } else if (s_cmp(c2, "PB", (ftnlen)2, (ftnlen)2) == 0) { if (s_cmp(c3, "TRF", (ftnlen)3, (ftnlen)3) == 0) { if (sname) { if (*n2 <= 64) { nb = 1; } else { nb = 32; } } else { if (*n2 <= 64) { nb = 1; } else { nb = 32; } } } } else if (s_cmp(c2, "TR", (ftnlen)2, (ftnlen)2) == 0) { if (s_cmp(c3, "TRI", (ftnlen)3, (ftnlen)3) == 0) { if (sname) { nb = 64; } else { nb = 64; } } } else if (s_cmp(c2, "LA", (ftnlen)2, (ftnlen)2) == 0) { if (s_cmp(c3, "UUM", (ftnlen)3, (ftnlen)3) == 0) { if (sname) { nb = 64; } else { nb = 64; } } } else if (sname && s_cmp(c2, "ST", (ftnlen)2, (ftnlen)2) == 0) { if (s_cmp(c3, "EBZ", (ftnlen)3, (ftnlen)3) == 0) { nb = 1; } } ret_val = nb; return ret_val; L60: /* ISPEC = 2: minimum block size */ nbmin = 2; if (s_cmp(c2, "GE", (ftnlen)2, (ftnlen)2) == 0) { if (s_cmp(c3, "QRF", (ftnlen)3, (ftnlen)3) == 0 || s_cmp(c3, "RQF", ( ftnlen)3, (ftnlen)3) == 0 || s_cmp(c3, "LQF", (ftnlen)3, ( ftnlen)3) == 0 || s_cmp(c3, "QLF", (ftnlen)3, (ftnlen)3) == 0) { if (sname) { nbmin = 2; } else { nbmin = 2; } } else if (s_cmp(c3, "HRD", (ftnlen)3, (ftnlen)3) == 0) { if (sname) { nbmin = 2; } else { nbmin = 2; } } else if (s_cmp(c3, "BRD", (ftnlen)3, (ftnlen)3) == 0) { if (sname) { nbmin = 2; } else { nbmin = 2; } } else if (s_cmp(c3, "TRI", (ftnlen)3, (ftnlen)3) == 0) { if (sname) { nbmin = 2; } else { nbmin = 2; } } } else if (s_cmp(c2, "SY", (ftnlen)2, (ftnlen)2) == 0) { if (s_cmp(c3, "TRF", (ftnlen)3, (ftnlen)3) == 0) { if (sname) { nbmin = 8; } else { nbmin = 8; } } else if (sname && s_cmp(c3, "TRD", (ftnlen)3, (ftnlen)3) == 0) { nbmin = 2; } } else if (cname && s_cmp(c2, "HE", (ftnlen)2, (ftnlen)2) == 0) { if (s_cmp(c3, "TRD", (ftnlen)3, (ftnlen)3) == 0) { nbmin = 2; } } else if (sname && s_cmp(c2, "OR", (ftnlen)2, (ftnlen)2) == 0) { if (*(unsigned char *)c3 == 'G') { if (s_cmp(c4, "QR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "RQ", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "LQ", (ftnlen)2, ( ftnlen)2) == 0 || s_cmp(c4, "QL", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "HR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp( c4, "TR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "BR", ( ftnlen)2, (ftnlen)2) == 0) { nbmin = 2; } } else if (*(unsigned char *)c3 == 'M') { if (s_cmp(c4, "QR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "RQ", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "LQ", (ftnlen)2, ( ftnlen)2) == 0 || s_cmp(c4, "QL", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "HR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp( c4, "TR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "BR", ( ftnlen)2, (ftnlen)2) == 0) { nbmin = 2; } } } else if (cname && s_cmp(c2, "UN", (ftnlen)2, (ftnlen)2) == 0) { if (*(unsigned char *)c3 == 'G') { if (s_cmp(c4, "QR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "RQ", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "LQ", (ftnlen)2, ( ftnlen)2) == 0 || s_cmp(c4, "QL", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "HR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp( c4, "TR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "BR", ( ftnlen)2, (ftnlen)2) == 0) { nbmin = 2; } } else if (*(unsigned char *)c3 == 'M') { if (s_cmp(c4, "QR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "RQ", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "LQ", (ftnlen)2, ( ftnlen)2) == 0 || s_cmp(c4, "QL", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "HR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp( c4, "TR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "BR", ( ftnlen)2, (ftnlen)2) == 0) { nbmin = 2; } } } ret_val = nbmin; return ret_val; L70: /* ISPEC = 3: crossover point */ nx = 0; if (s_cmp(c2, "GE", (ftnlen)2, (ftnlen)2) == 0) { if (s_cmp(c3, "QRF", (ftnlen)3, (ftnlen)3) == 0 || s_cmp(c3, "RQF", ( ftnlen)3, (ftnlen)3) == 0 || s_cmp(c3, "LQF", (ftnlen)3, ( ftnlen)3) == 0 || s_cmp(c3, "QLF", (ftnlen)3, (ftnlen)3) == 0) { if (sname) { nx = 128; } else { nx = 128; } } else if (s_cmp(c3, "HRD", (ftnlen)3, (ftnlen)3) == 0) { if (sname) { nx = 128; } else { nx = 128; } } else if (s_cmp(c3, "BRD", (ftnlen)3, (ftnlen)3) == 0) { if (sname) { nx = 128; } else { nx = 128; } } } else if (s_cmp(c2, "SY", (ftnlen)2, (ftnlen)2) == 0) { if (sname && s_cmp(c3, "TRD", (ftnlen)3, (ftnlen)3) == 0) { nx = 32; } } else if (cname && s_cmp(c2, "HE", (ftnlen)2, (ftnlen)2) == 0) { if (s_cmp(c3, "TRD", (ftnlen)3, (ftnlen)3) == 0) { nx = 32; } } else if (sname && s_cmp(c2, "OR", (ftnlen)2, (ftnlen)2) == 0) { if (*(unsigned char *)c3 == 'G') { if (s_cmp(c4, "QR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "RQ", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "LQ", (ftnlen)2, ( ftnlen)2) == 0 || s_cmp(c4, "QL", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "HR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp( c4, "TR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "BR", ( ftnlen)2, (ftnlen)2) == 0) { nx = 128; } } } else if (cname && s_cmp(c2, "UN", (ftnlen)2, (ftnlen)2) == 0) { if (*(unsigned char *)c3 == 'G') { if (s_cmp(c4, "QR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "RQ", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "LQ", (ftnlen)2, ( ftnlen)2) == 0 || s_cmp(c4, "QL", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "HR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp( c4, "TR", (ftnlen)2, (ftnlen)2) == 0 || s_cmp(c4, "BR", ( ftnlen)2, (ftnlen)2) == 0) { nx = 128; } } } ret_val = nx; return ret_val; L80: /* ISPEC = 4: number of shifts (used by xHSEQR) */ ret_val = 6; return ret_val; L90: /* ISPEC = 5: minimum column dimension (not used) */ ret_val = 2; return ret_val; L100: /* ISPEC = 6: crossover point for SVD (used by xGELSS and xGESVD) */ ret_val = (integer) ((real) min(*n1,*n2) * 1.6f); return ret_val; L110: /* ISPEC = 7: number of processors (not used) */ ret_val = 1; return ret_val; L120: /* ISPEC = 8: crossover point for multishift (used by xHSEQR) */ ret_val = 50; return ret_val; L130: /* ISPEC = 9: maximum size of the subproblems at the bottom of the computation tree in the divide-and-conquer algorithm (used by xGELSD and xGESDD) */ ret_val = 25; return ret_val; L140: /* ISPEC = 10: ieee NaN arithmetic can be trusted not to trap ILAENV = 0 */ ret_val = 1; if (ret_val == 1) { ret_val = igraphieeeck_(&c__1, &c_b163, &c_b164); } return ret_val; L150: /* ISPEC = 11: infinity arithmetic can be trusted not to trap ILAENV = 0 */ ret_val = 1; if (ret_val == 1) { ret_val = igraphieeeck_(&c__0, &c_b163, &c_b164); } return ret_val; L160: /* 12 <= ISPEC <= 16: xHSEQR or one of its subroutines. */ ret_val = igraphiparmq_(ispec, name__, opts, n1, n2, n3, n4) ; return ret_val; /* End of ILAENV */ } /* igraphilaenv_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dgeqr2.c0000644000076500000240000001427013524616145024174 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; /* > \brief \b DGEQR2 computes the QR factorization of a general rectangular matrix using an unblocked algorit hm. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DGEQR2 + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DGEQR2( M, N, A, LDA, TAU, WORK, INFO ) INTEGER INFO, LDA, M, N DOUBLE PRECISION A( LDA, * ), TAU( * ), WORK( * ) > \par Purpose: ============= > > \verbatim > > DGEQR2 computes a QR factorization of a real m by n matrix A: > A = Q * R. > \endverbatim Arguments: ========== > \param[in] M > \verbatim > M is INTEGER > The number of rows of the matrix A. M >= 0. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The number of columns of the matrix A. N >= 0. > \endverbatim > > \param[in,out] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,N) > On entry, the m by n matrix A. > On exit, the elements on and above the diagonal of the array > contain the min(m,n) by n upper trapezoidal matrix R (R is > upper triangular if m >= n); the elements below the diagonal, > with the array TAU, represent the orthogonal matrix Q as a > product of elementary reflectors (see Further Details). > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. LDA >= max(1,M). > \endverbatim > > \param[out] TAU > \verbatim > TAU is DOUBLE PRECISION array, dimension (min(M,N)) > The scalar factors of the elementary reflectors (see Further > Details). > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (N) > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleGEcomputational > \par Further Details: ===================== > > \verbatim > > The matrix Q is represented as a product of elementary reflectors > > Q = H(1) H(2) . . . H(k), where k = min(m,n). > > Each H(i) has the form > > H(i) = I - tau * v * v**T > > where tau is a real scalar, and v is a real vector with > v(1:i-1) = 0 and v(i) = 1; v(i+1:m) is stored on exit in A(i+1:m,i), > and tau in TAU(i). > \endverbatim > ===================================================================== Subroutine */ int igraphdgeqr2_(integer *m, integer *n, doublereal *a, integer * lda, doublereal *tau, doublereal *work, integer *info) { /* System generated locals */ integer a_dim1, a_offset, i__1, i__2, i__3; /* Local variables */ integer i__, k; doublereal aii; extern /* Subroutine */ int igraphdlarf_(char *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *), igraphdlarfg_(integer *, doublereal *, doublereal *, integer *, doublereal *), igraphxerbla_(char *, integer *, ftnlen); /* -- LAPACK computational routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Test the input arguments Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --tau; --work; /* Function Body */ *info = 0; if (*m < 0) { *info = -1; } else if (*n < 0) { *info = -2; } else if (*lda < max(1,*m)) { *info = -4; } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DGEQR2", &i__1, (ftnlen)6); return 0; } k = min(*m,*n); i__1 = k; for (i__ = 1; i__ <= i__1; ++i__) { /* Generate elementary reflector H(i) to annihilate A(i+1:m,i) */ i__2 = *m - i__ + 1; /* Computing MIN */ i__3 = i__ + 1; igraphdlarfg_(&i__2, &a[i__ + i__ * a_dim1], &a[min(i__3,*m) + i__ * a_dim1] , &c__1, &tau[i__]); if (i__ < *n) { /* Apply H(i) to A(i:m,i+1:n) from the left */ aii = a[i__ + i__ * a_dim1]; a[i__ + i__ * a_dim1] = 1.; i__2 = *m - i__ + 1; i__3 = *n - i__; igraphdlarf_("Left", &i__2, &i__3, &a[i__ + i__ * a_dim1], &c__1, &tau[ i__], &a[i__ + (i__ + 1) * a_dim1], lda, &work[1]); a[i__ + i__ * a_dim1] = aii; } /* L10: */ } return 0; /* End of DGEQR2 */ } /* igraphdgeqr2_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlar1v.c0000644000076500000240000003716513524616145024211 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLAR1V computes the (scaled) r-th column of the inverse of the submatrix in rows b1 through bn of the tridiagonal matrix LDLT - λI. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLAR1V + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLAR1V( N, B1, BN, LAMBDA, D, L, LD, LLD, PIVMIN, GAPTOL, Z, WANTNC, NEGCNT, ZTZ, MINGMA, R, ISUPPZ, NRMINV, RESID, RQCORR, WORK ) LOGICAL WANTNC INTEGER B1, BN, N, NEGCNT, R DOUBLE PRECISION GAPTOL, LAMBDA, MINGMA, NRMINV, PIVMIN, RESID, $ RQCORR, ZTZ INTEGER ISUPPZ( * ) DOUBLE PRECISION D( * ), L( * ), LD( * ), LLD( * ), $ WORK( * ) DOUBLE PRECISION Z( * ) > \par Purpose: ============= > > \verbatim > > DLAR1V computes the (scaled) r-th column of the inverse of > the sumbmatrix in rows B1 through BN of the tridiagonal matrix > L D L**T - sigma I. When sigma is close to an eigenvalue, the > computed vector is an accurate eigenvector. Usually, r corresponds > to the index where the eigenvector is largest in magnitude. > The following steps accomplish this computation : > (a) Stationary qd transform, L D L**T - sigma I = L(+) D(+) L(+)**T, > (b) Progressive qd transform, L D L**T - sigma I = U(-) D(-) U(-)**T, > (c) Computation of the diagonal elements of the inverse of > L D L**T - sigma I by combining the above transforms, and choosing > r as the index where the diagonal of the inverse is (one of the) > largest in magnitude. > (d) Computation of the (scaled) r-th column of the inverse using the > twisted factorization obtained by combining the top part of the > the stationary and the bottom part of the progressive transform. > \endverbatim Arguments: ========== > \param[in] N > \verbatim > N is INTEGER > The order of the matrix L D L**T. > \endverbatim > > \param[in] B1 > \verbatim > B1 is INTEGER > First index of the submatrix of L D L**T. > \endverbatim > > \param[in] BN > \verbatim > BN is INTEGER > Last index of the submatrix of L D L**T. > \endverbatim > > \param[in] LAMBDA > \verbatim > LAMBDA is DOUBLE PRECISION > The shift. In order to compute an accurate eigenvector, > LAMBDA should be a good approximation to an eigenvalue > of L D L**T. > \endverbatim > > \param[in] L > \verbatim > L is DOUBLE PRECISION array, dimension (N-1) > The (n-1) subdiagonal elements of the unit bidiagonal matrix > L, in elements 1 to N-1. > \endverbatim > > \param[in] D > \verbatim > D is DOUBLE PRECISION array, dimension (N) > The n diagonal elements of the diagonal matrix D. > \endverbatim > > \param[in] LD > \verbatim > LD is DOUBLE PRECISION array, dimension (N-1) > The n-1 elements L(i)*D(i). > \endverbatim > > \param[in] LLD > \verbatim > LLD is DOUBLE PRECISION array, dimension (N-1) > The n-1 elements L(i)*L(i)*D(i). > \endverbatim > > \param[in] PIVMIN > \verbatim > PIVMIN is DOUBLE PRECISION > The minimum pivot in the Sturm sequence. > \endverbatim > > \param[in] GAPTOL > \verbatim > GAPTOL is DOUBLE PRECISION > Tolerance that indicates when eigenvector entries are negligible > w.r.t. their contribution to the residual. > \endverbatim > > \param[in,out] Z > \verbatim > Z is DOUBLE PRECISION array, dimension (N) > On input, all entries of Z must be set to 0. > On output, Z contains the (scaled) r-th column of the > inverse. The scaling is such that Z(R) equals 1. > \endverbatim > > \param[in] WANTNC > \verbatim > WANTNC is LOGICAL > Specifies whether NEGCNT has to be computed. > \endverbatim > > \param[out] NEGCNT > \verbatim > NEGCNT is INTEGER > If WANTNC is .TRUE. then NEGCNT = the number of pivots < pivmin > in the matrix factorization L D L**T, and NEGCNT = -1 otherwise. > \endverbatim > > \param[out] ZTZ > \verbatim > ZTZ is DOUBLE PRECISION > The square of the 2-norm of Z. > \endverbatim > > \param[out] MINGMA > \verbatim > MINGMA is DOUBLE PRECISION > The reciprocal of the largest (in magnitude) diagonal > element of the inverse of L D L**T - sigma I. > \endverbatim > > \param[in,out] R > \verbatim > R is INTEGER > The twist index for the twisted factorization used to > compute Z. > On input, 0 <= R <= N. If R is input as 0, R is set to > the index where (L D L**T - sigma I)^{-1} is largest > in magnitude. If 1 <= R <= N, R is unchanged. > On output, R contains the twist index used to compute Z. > Ideally, R designates the position of the maximum entry in the > eigenvector. > \endverbatim > > \param[out] ISUPPZ > \verbatim > ISUPPZ is INTEGER array, dimension (2) > The support of the vector in Z, i.e., the vector Z is > nonzero only in elements ISUPPZ(1) through ISUPPZ( 2 ). > \endverbatim > > \param[out] NRMINV > \verbatim > NRMINV is DOUBLE PRECISION > NRMINV = 1/SQRT( ZTZ ) > \endverbatim > > \param[out] RESID > \verbatim > RESID is DOUBLE PRECISION > The residual of the FP vector. > RESID = ABS( MINGMA )/SQRT( ZTZ ) > \endverbatim > > \param[out] RQCORR > \verbatim > RQCORR is DOUBLE PRECISION > The Rayleigh Quotient correction to LAMBDA. > RQCORR = MINGMA*TMP > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (4*N) > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleOTHERauxiliary > \par Contributors: ================== > > Beresford Parlett, University of California, Berkeley, USA \n > Jim Demmel, University of California, Berkeley, USA \n > Inderjit Dhillon, University of Texas, Austin, USA \n > Osni Marques, LBNL/NERSC, USA \n > Christof Voemel, University of California, Berkeley, USA ===================================================================== Subroutine */ int igraphdlar1v_(integer *n, integer *b1, integer *bn, doublereal *lambda, doublereal *d__, doublereal *l, doublereal *ld, doublereal * lld, doublereal *pivmin, doublereal *gaptol, doublereal *z__, logical *wantnc, integer *negcnt, doublereal *ztz, doublereal *mingma, integer *r__, integer *isuppz, doublereal *nrminv, doublereal *resid, doublereal *rqcorr, doublereal *work) { /* System generated locals */ integer i__1; doublereal d__1, d__2, d__3; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ integer i__; doublereal s; integer r1, r2; doublereal eps, tmp; integer neg1, neg2, indp, inds; doublereal dplus; extern doublereal igraphdlamch_(char *); extern logical igraphdisnan_(doublereal *); integer indlpl, indumn; doublereal dminus; logical sawnan1, sawnan2; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ --work; --isuppz; --z__; --lld; --ld; --l; --d__; /* Function Body */ eps = igraphdlamch_("Precision"); if (*r__ == 0) { r1 = *b1; r2 = *bn; } else { r1 = *r__; r2 = *r__; } /* Storage for LPLUS */ indlpl = 0; /* Storage for UMINUS */ indumn = *n; inds = (*n << 1) + 1; indp = *n * 3 + 1; if (*b1 == 1) { work[inds] = 0.; } else { work[inds + *b1 - 1] = lld[*b1 - 1]; } /* Compute the stationary transform (using the differential form) until the index R2. */ sawnan1 = FALSE_; neg1 = 0; s = work[inds + *b1 - 1] - *lambda; i__1 = r1 - 1; for (i__ = *b1; i__ <= i__1; ++i__) { dplus = d__[i__] + s; work[indlpl + i__] = ld[i__] / dplus; if (dplus < 0.) { ++neg1; } work[inds + i__] = s * work[indlpl + i__] * l[i__]; s = work[inds + i__] - *lambda; /* L50: */ } sawnan1 = igraphdisnan_(&s); if (sawnan1) { goto L60; } i__1 = r2 - 1; for (i__ = r1; i__ <= i__1; ++i__) { dplus = d__[i__] + s; work[indlpl + i__] = ld[i__] / dplus; work[inds + i__] = s * work[indlpl + i__] * l[i__]; s = work[inds + i__] - *lambda; /* L51: */ } sawnan1 = igraphdisnan_(&s); L60: if (sawnan1) { /* Runs a slower version of the above loop if a NaN is detected */ neg1 = 0; s = work[inds + *b1 - 1] - *lambda; i__1 = r1 - 1; for (i__ = *b1; i__ <= i__1; ++i__) { dplus = d__[i__] + s; if (abs(dplus) < *pivmin) { dplus = -(*pivmin); } work[indlpl + i__] = ld[i__] / dplus; if (dplus < 0.) { ++neg1; } work[inds + i__] = s * work[indlpl + i__] * l[i__]; if (work[indlpl + i__] == 0.) { work[inds + i__] = lld[i__]; } s = work[inds + i__] - *lambda; /* L70: */ } i__1 = r2 - 1; for (i__ = r1; i__ <= i__1; ++i__) { dplus = d__[i__] + s; if (abs(dplus) < *pivmin) { dplus = -(*pivmin); } work[indlpl + i__] = ld[i__] / dplus; work[inds + i__] = s * work[indlpl + i__] * l[i__]; if (work[indlpl + i__] == 0.) { work[inds + i__] = lld[i__]; } s = work[inds + i__] - *lambda; /* L71: */ } } /* Compute the progressive transform (using the differential form) until the index R1 */ sawnan2 = FALSE_; neg2 = 0; work[indp + *bn - 1] = d__[*bn] - *lambda; i__1 = r1; for (i__ = *bn - 1; i__ >= i__1; --i__) { dminus = lld[i__] + work[indp + i__]; tmp = d__[i__] / dminus; if (dminus < 0.) { ++neg2; } work[indumn + i__] = l[i__] * tmp; work[indp + i__ - 1] = work[indp + i__] * tmp - *lambda; /* L80: */ } tmp = work[indp + r1 - 1]; sawnan2 = igraphdisnan_(&tmp); if (sawnan2) { /* Runs a slower version of the above loop if a NaN is detected */ neg2 = 0; i__1 = r1; for (i__ = *bn - 1; i__ >= i__1; --i__) { dminus = lld[i__] + work[indp + i__]; if (abs(dminus) < *pivmin) { dminus = -(*pivmin); } tmp = d__[i__] / dminus; if (dminus < 0.) { ++neg2; } work[indumn + i__] = l[i__] * tmp; work[indp + i__ - 1] = work[indp + i__] * tmp - *lambda; if (tmp == 0.) { work[indp + i__ - 1] = d__[i__] - *lambda; } /* L100: */ } } /* Find the index (from R1 to R2) of the largest (in magnitude) diagonal element of the inverse */ *mingma = work[inds + r1 - 1] + work[indp + r1 - 1]; if (*mingma < 0.) { ++neg1; } if (*wantnc) { *negcnt = neg1 + neg2; } else { *negcnt = -1; } if (abs(*mingma) == 0.) { *mingma = eps * work[inds + r1 - 1]; } *r__ = r1; i__1 = r2 - 1; for (i__ = r1; i__ <= i__1; ++i__) { tmp = work[inds + i__] + work[indp + i__]; if (tmp == 0.) { tmp = eps * work[inds + i__]; } if (abs(tmp) <= abs(*mingma)) { *mingma = tmp; *r__ = i__ + 1; } /* L110: */ } /* Compute the FP vector: solve N^T v = e_r */ isuppz[1] = *b1; isuppz[2] = *bn; z__[*r__] = 1.; *ztz = 1.; /* Compute the FP vector upwards from R */ if (! sawnan1 && ! sawnan2) { i__1 = *b1; for (i__ = *r__ - 1; i__ >= i__1; --i__) { z__[i__] = -(work[indlpl + i__] * z__[i__ + 1]); if (((d__1 = z__[i__], abs(d__1)) + (d__2 = z__[i__ + 1], abs( d__2))) * (d__3 = ld[i__], abs(d__3)) < *gaptol) { z__[i__] = 0.; isuppz[1] = i__ + 1; goto L220; } *ztz += z__[i__] * z__[i__]; /* L210: */ } L220: ; } else { /* Run slower loop if NaN occurred. */ i__1 = *b1; for (i__ = *r__ - 1; i__ >= i__1; --i__) { if (z__[i__ + 1] == 0.) { z__[i__] = -(ld[i__ + 1] / ld[i__]) * z__[i__ + 2]; } else { z__[i__] = -(work[indlpl + i__] * z__[i__ + 1]); } if (((d__1 = z__[i__], abs(d__1)) + (d__2 = z__[i__ + 1], abs( d__2))) * (d__3 = ld[i__], abs(d__3)) < *gaptol) { z__[i__] = 0.; isuppz[1] = i__ + 1; goto L240; } *ztz += z__[i__] * z__[i__]; /* L230: */ } L240: ; } /* Compute the FP vector downwards from R in blocks of size BLKSIZ */ if (! sawnan1 && ! sawnan2) { i__1 = *bn - 1; for (i__ = *r__; i__ <= i__1; ++i__) { z__[i__ + 1] = -(work[indumn + i__] * z__[i__]); if (((d__1 = z__[i__], abs(d__1)) + (d__2 = z__[i__ + 1], abs( d__2))) * (d__3 = ld[i__], abs(d__3)) < *gaptol) { z__[i__ + 1] = 0.; isuppz[2] = i__; goto L260; } *ztz += z__[i__ + 1] * z__[i__ + 1]; /* L250: */ } L260: ; } else { /* Run slower loop if NaN occurred. */ i__1 = *bn - 1; for (i__ = *r__; i__ <= i__1; ++i__) { if (z__[i__] == 0.) { z__[i__ + 1] = -(ld[i__ - 1] / ld[i__]) * z__[i__ - 1]; } else { z__[i__ + 1] = -(work[indumn + i__] * z__[i__]); } if (((d__1 = z__[i__], abs(d__1)) + (d__2 = z__[i__ + 1], abs( d__2))) * (d__3 = ld[i__], abs(d__3)) < *gaptol) { z__[i__ + 1] = 0.; isuppz[2] = i__; goto L280; } *ztz += z__[i__ + 1] * z__[i__ + 1]; /* L270: */ } L280: ; } /* Compute quantities for convergence test */ tmp = 1. / *ztz; *nrminv = sqrt(tmp); *resid = abs(*mingma) * *nrminv; *rqcorr = *mingma * tmp; return 0; /* End of DLAR1V */ } /* igraphdlar1v_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlasrt.c0000644000076500000240000001622713524616145024305 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLASRT sorts numbers in increasing or decreasing order. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLASRT + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLASRT( ID, N, D, INFO ) CHARACTER ID INTEGER INFO, N DOUBLE PRECISION D( * ) > \par Purpose: ============= > > \verbatim > > Sort the numbers in D in increasing order (if ID = 'I') or > in decreasing order (if ID = 'D' ). > > Use Quick Sort, reverting to Insertion sort on arrays of > size <= 20. Dimension of STACK limits N to about 2**32. > \endverbatim Arguments: ========== > \param[in] ID > \verbatim > ID is CHARACTER*1 > = 'I': sort D in increasing order; > = 'D': sort D in decreasing order. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The length of the array D. > \endverbatim > > \param[in,out] D > \verbatim > D is DOUBLE PRECISION array, dimension (N) > On entry, the array to be sorted. > On exit, D has been sorted into increasing order > (D(1) <= ... <= D(N) ) or into decreasing order > (D(1) >= ... >= D(N) ), depending on ID. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERcomputational ===================================================================== Subroutine */ int igraphdlasrt_(char *id, integer *n, doublereal *d__, integer * info) { /* System generated locals */ integer i__1, i__2; /* Local variables */ integer i__, j; doublereal d1, d2, d3; integer dir; doublereal tmp; integer endd; extern logical igraphlsame_(char *, char *); integer stack[64] /* was [2][32] */; doublereal dmnmx; integer start; extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); integer stkpnt; /* -- LAPACK computational routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Test the input paramters. Parameter adjustments */ --d__; /* Function Body */ *info = 0; dir = -1; if (igraphlsame_(id, "D")) { dir = 0; } else if (igraphlsame_(id, "I")) { dir = 1; } if (dir == -1) { *info = -1; } else if (*n < 0) { *info = -2; } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DLASRT", &i__1, (ftnlen)6); return 0; } /* Quick return if possible */ if (*n <= 1) { return 0; } stkpnt = 1; stack[0] = 1; stack[1] = *n; L10: start = stack[(stkpnt << 1) - 2]; endd = stack[(stkpnt << 1) - 1]; --stkpnt; if (endd - start <= 20 && endd - start > 0) { /* Do Insertion sort on D( START:ENDD ) */ if (dir == 0) { /* Sort into decreasing order */ i__1 = endd; for (i__ = start + 1; i__ <= i__1; ++i__) { i__2 = start + 1; for (j = i__; j >= i__2; --j) { if (d__[j] > d__[j - 1]) { dmnmx = d__[j]; d__[j] = d__[j - 1]; d__[j - 1] = dmnmx; } else { goto L30; } /* L20: */ } L30: ; } } else { /* Sort into increasing order */ i__1 = endd; for (i__ = start + 1; i__ <= i__1; ++i__) { i__2 = start + 1; for (j = i__; j >= i__2; --j) { if (d__[j] < d__[j - 1]) { dmnmx = d__[j]; d__[j] = d__[j - 1]; d__[j - 1] = dmnmx; } else { goto L50; } /* L40: */ } L50: ; } } } else if (endd - start > 20) { /* Partition D( START:ENDD ) and stack parts, largest one first Choose partition entry as median of 3 */ d1 = d__[start]; d2 = d__[endd]; i__ = (start + endd) / 2; d3 = d__[i__]; if (d1 < d2) { if (d3 < d1) { dmnmx = d1; } else if (d3 < d2) { dmnmx = d3; } else { dmnmx = d2; } } else { if (d3 < d2) { dmnmx = d2; } else if (d3 < d1) { dmnmx = d3; } else { dmnmx = d1; } } if (dir == 0) { /* Sort into decreasing order */ i__ = start - 1; j = endd + 1; L60: L70: --j; if (d__[j] < dmnmx) { goto L70; } L80: ++i__; if (d__[i__] > dmnmx) { goto L80; } if (i__ < j) { tmp = d__[i__]; d__[i__] = d__[j]; d__[j] = tmp; goto L60; } if (j - start > endd - j - 1) { ++stkpnt; stack[(stkpnt << 1) - 2] = start; stack[(stkpnt << 1) - 1] = j; ++stkpnt; stack[(stkpnt << 1) - 2] = j + 1; stack[(stkpnt << 1) - 1] = endd; } else { ++stkpnt; stack[(stkpnt << 1) - 2] = j + 1; stack[(stkpnt << 1) - 1] = endd; ++stkpnt; stack[(stkpnt << 1) - 2] = start; stack[(stkpnt << 1) - 1] = j; } } else { /* Sort into increasing order */ i__ = start - 1; j = endd + 1; L90: L100: --j; if (d__[j] > dmnmx) { goto L100; } L110: ++i__; if (d__[i__] < dmnmx) { goto L110; } if (i__ < j) { tmp = d__[i__]; d__[i__] = d__[j]; d__[j] = tmp; goto L90; } if (j - start > endd - j - 1) { ++stkpnt; stack[(stkpnt << 1) - 2] = start; stack[(stkpnt << 1) - 1] = j; ++stkpnt; stack[(stkpnt << 1) - 2] = j + 1; stack[(stkpnt << 1) - 1] = endd; } else { ++stkpnt; stack[(stkpnt << 1) - 2] = j + 1; stack[(stkpnt << 1) - 1] = endd; ++stkpnt; stack[(stkpnt << 1) - 2] = start; stack[(stkpnt << 1) - 1] = j; } } } if (stkpnt > 0) { goto L10; } return 0; /* End of DLASRT */ } /* igraphdlasrt_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dpotf2.c0000644000076500000240000001722413524616145024210 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static doublereal c_b10 = -1.; static doublereal c_b12 = 1.; /* > \brief \b DPOTF2 computes the Cholesky factorization of a symmetric/Hermitian positive definite matrix (u nblocked algorithm). =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DPOTF2 + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DPOTF2( UPLO, N, A, LDA, INFO ) CHARACTER UPLO INTEGER INFO, LDA, N DOUBLE PRECISION A( LDA, * ) > \par Purpose: ============= > > \verbatim > > DPOTF2 computes the Cholesky factorization of a real symmetric > positive definite matrix A. > > The factorization has the form > A = U**T * U , if UPLO = 'U', or > A = L * L**T, if UPLO = 'L', > where U is an upper triangular matrix and L is lower triangular. > > This is the unblocked version of the algorithm, calling Level 2 BLAS. > \endverbatim Arguments: ========== > \param[in] UPLO > \verbatim > UPLO is CHARACTER*1 > Specifies whether the upper or lower triangular part of the > symmetric matrix A is stored. > = 'U': Upper triangular > = 'L': Lower triangular > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix A. N >= 0. > \endverbatim > > \param[in,out] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,N) > On entry, the symmetric matrix A. If UPLO = 'U', the leading > n by n upper triangular part of A contains the upper > triangular part of the matrix A, and the strictly lower > triangular part of A is not referenced. If UPLO = 'L', the > leading n by n lower triangular part of A contains the lower > triangular part of the matrix A, and the strictly upper > triangular part of A is not referenced. > > On exit, if INFO = 0, the factor U or L from the Cholesky > factorization A = U**T *U or A = L*L**T. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. LDA >= max(1,N). > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -k, the k-th argument had an illegal value > > 0: if INFO = k, the leading minor of order k is not > positive definite, and the factorization could not be > completed. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doublePOcomputational ===================================================================== Subroutine */ int igraphdpotf2_(char *uplo, integer *n, doublereal *a, integer * lda, integer *info) { /* System generated locals */ integer a_dim1, a_offset, i__1, i__2, i__3; doublereal d__1; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ integer j; doublereal ajj; extern doublereal igraphddot_(integer *, doublereal *, integer *, doublereal *, integer *); extern /* Subroutine */ int igraphdscal_(integer *, doublereal *, doublereal *, integer *); extern logical igraphlsame_(char *, char *); extern /* Subroutine */ int igraphdgemv_(char *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *); logical upper; extern logical igraphdisnan_(doublereal *); extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); /* -- LAPACK computational routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Test the input parameters. Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; /* Function Body */ *info = 0; upper = igraphlsame_(uplo, "U"); if (! upper && ! igraphlsame_(uplo, "L")) { *info = -1; } else if (*n < 0) { *info = -2; } else if (*lda < max(1,*n)) { *info = -4; } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DPOTF2", &i__1, (ftnlen)6); return 0; } /* Quick return if possible */ if (*n == 0) { return 0; } if (upper) { /* Compute the Cholesky factorization A = U**T *U. */ i__1 = *n; for (j = 1; j <= i__1; ++j) { /* Compute U(J,J) and test for non-positive-definiteness. */ i__2 = j - 1; ajj = a[j + j * a_dim1] - igraphddot_(&i__2, &a[j * a_dim1 + 1], &c__1, &a[j * a_dim1 + 1], &c__1); if (ajj <= 0. || igraphdisnan_(&ajj)) { a[j + j * a_dim1] = ajj; goto L30; } ajj = sqrt(ajj); a[j + j * a_dim1] = ajj; /* Compute elements J+1:N of row J. */ if (j < *n) { i__2 = j - 1; i__3 = *n - j; igraphdgemv_("Transpose", &i__2, &i__3, &c_b10, &a[(j + 1) * a_dim1 + 1], lda, &a[j * a_dim1 + 1], &c__1, &c_b12, &a[j + ( j + 1) * a_dim1], lda); i__2 = *n - j; d__1 = 1. / ajj; igraphdscal_(&i__2, &d__1, &a[j + (j + 1) * a_dim1], lda); } /* L10: */ } } else { /* Compute the Cholesky factorization A = L*L**T. */ i__1 = *n; for (j = 1; j <= i__1; ++j) { /* Compute L(J,J) and test for non-positive-definiteness. */ i__2 = j - 1; ajj = a[j + j * a_dim1] - igraphddot_(&i__2, &a[j + a_dim1], lda, &a[j + a_dim1], lda); if (ajj <= 0. || igraphdisnan_(&ajj)) { a[j + j * a_dim1] = ajj; goto L30; } ajj = sqrt(ajj); a[j + j * a_dim1] = ajj; /* Compute elements J+1:N of column J. */ if (j < *n) { i__2 = *n - j; i__3 = j - 1; igraphdgemv_("No transpose", &i__2, &i__3, &c_b10, &a[j + 1 + a_dim1], lda, &a[j + a_dim1], lda, &c_b12, &a[j + 1 + j * a_dim1], &c__1); i__2 = *n - j; d__1 = 1. / ajj; igraphdscal_(&i__2, &d__1, &a[j + 1 + j * a_dim1], &c__1); } /* L20: */ } } goto L40; L30: *info = j; L40: return 0; /* End of DPOTF2 */ } /* igraphdpotf2_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/disnan.c0000644000076500000240000000510213524616145024256 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DISNAN tests input for NaN. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DISNAN + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== LOGICAL FUNCTION DISNAN( DIN ) DOUBLE PRECISION DIN > \par Purpose: ============= > > \verbatim > > DISNAN returns .TRUE. if its argument is NaN, and .FALSE. > otherwise. To be replaced by the Fortran 2003 intrinsic in the > future. > \endverbatim Arguments: ========== > \param[in] DIN > \verbatim > DIN is DOUBLE PRECISION > Input to test for NaN. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERauxiliary ===================================================================== */ logical igraphdisnan_(doublereal *din) { /* System generated locals */ logical ret_val; /* Local variables */ extern logical igraphdlaisnan_(doublereal *, doublereal *); /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== */ ret_val = igraphdlaisnan_(din, din); return ret_val; } /* igraphdisnan_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlarrb.c0000644000076500000240000003217513524616145024262 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLARRB provides limited bisection to locate eigenvalues for more accuracy. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLARRB + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLARRB( N, D, LLD, IFIRST, ILAST, RTOL1, RTOL2, OFFSET, W, WGAP, WERR, WORK, IWORK, PIVMIN, SPDIAM, TWIST, INFO ) INTEGER IFIRST, ILAST, INFO, N, OFFSET, TWIST DOUBLE PRECISION PIVMIN, RTOL1, RTOL2, SPDIAM INTEGER IWORK( * ) DOUBLE PRECISION D( * ), LLD( * ), W( * ), $ WERR( * ), WGAP( * ), WORK( * ) > \par Purpose: ============= > > \verbatim > > Given the relatively robust representation(RRR) L D L^T, DLARRB > does "limited" bisection to refine the eigenvalues of L D L^T, > W( IFIRST-OFFSET ) through W( ILAST-OFFSET ), to more accuracy. Initial > guesses for these eigenvalues are input in W, the corresponding estimate > of the error in these guesses and their gaps are input in WERR > and WGAP, respectively. During bisection, intervals > [left, right] are maintained by storing their mid-points and > semi-widths in the arrays W and WERR respectively. > \endverbatim Arguments: ========== > \param[in] N > \verbatim > N is INTEGER > The order of the matrix. > \endverbatim > > \param[in] D > \verbatim > D is DOUBLE PRECISION array, dimension (N) > The N diagonal elements of the diagonal matrix D. > \endverbatim > > \param[in] LLD > \verbatim > LLD is DOUBLE PRECISION array, dimension (N-1) > The (N-1) elements L(i)*L(i)*D(i). > \endverbatim > > \param[in] IFIRST > \verbatim > IFIRST is INTEGER > The index of the first eigenvalue to be computed. > \endverbatim > > \param[in] ILAST > \verbatim > ILAST is INTEGER > The index of the last eigenvalue to be computed. > \endverbatim > > \param[in] RTOL1 > \verbatim > RTOL1 is DOUBLE PRECISION > \endverbatim > > \param[in] RTOL2 > \verbatim > RTOL2 is DOUBLE PRECISION > Tolerance for the convergence of the bisection intervals. > An interval [LEFT,RIGHT] has converged if > RIGHT-LEFT.LT.MAX( RTOL1*GAP, RTOL2*MAX(|LEFT|,|RIGHT|) ) > where GAP is the (estimated) distance to the nearest > eigenvalue. > \endverbatim > > \param[in] OFFSET > \verbatim > OFFSET is INTEGER > Offset for the arrays W, WGAP and WERR, i.e., the IFIRST-OFFSET > through ILAST-OFFSET elements of these arrays are to be used. > \endverbatim > > \param[in,out] W > \verbatim > W is DOUBLE PRECISION array, dimension (N) > On input, W( IFIRST-OFFSET ) through W( ILAST-OFFSET ) are > estimates of the eigenvalues of L D L^T indexed IFIRST throug > ILAST. > On output, these estimates are refined. > \endverbatim > > \param[in,out] WGAP > \verbatim > WGAP is DOUBLE PRECISION array, dimension (N-1) > On input, the (estimated) gaps between consecutive > eigenvalues of L D L^T, i.e., WGAP(I-OFFSET) is the gap between > eigenvalues I and I+1. Note that if IFIRST.EQ.ILAST > then WGAP(IFIRST-OFFSET) must be set to ZERO. > On output, these gaps are refined. > \endverbatim > > \param[in,out] WERR > \verbatim > WERR is DOUBLE PRECISION array, dimension (N) > On input, WERR( IFIRST-OFFSET ) through WERR( ILAST-OFFSET ) are > the errors in the estimates of the corresponding elements in W. > On output, these errors are refined. > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (2*N) > Workspace. > \endverbatim > > \param[out] IWORK > \verbatim > IWORK is INTEGER array, dimension (2*N) > Workspace. > \endverbatim > > \param[in] PIVMIN > \verbatim > PIVMIN is DOUBLE PRECISION > The minimum pivot in the Sturm sequence. > \endverbatim > > \param[in] SPDIAM > \verbatim > SPDIAM is DOUBLE PRECISION > The spectral diameter of the matrix. > \endverbatim > > \param[in] TWIST > \verbatim > TWIST is INTEGER > The twist index for the twisted factorization that is used > for the negcount. > TWIST = N: Compute negcount from L D L^T - LAMBDA I = L+ D+ L+^T > TWIST = 1: Compute negcount from L D L^T - LAMBDA I = U- D- U-^T > TWIST = R: Compute negcount from L D L^T - LAMBDA I = N(r) D(r) N(r) > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > Error flag. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERauxiliary > \par Contributors: ================== > > Beresford Parlett, University of California, Berkeley, USA \n > Jim Demmel, University of California, Berkeley, USA \n > Inderjit Dhillon, University of Texas, Austin, USA \n > Osni Marques, LBNL/NERSC, USA \n > Christof Voemel, University of California, Berkeley, USA ===================================================================== Subroutine */ int igraphdlarrb_(integer *n, doublereal *d__, doublereal *lld, integer *ifirst, integer *ilast, doublereal *rtol1, doublereal *rtol2, integer *offset, doublereal *w, doublereal *wgap, doublereal *werr, doublereal *work, integer *iwork, doublereal *pivmin, doublereal * spdiam, integer *twist, integer *info) { /* System generated locals */ integer i__1; doublereal d__1, d__2; /* Builtin functions */ double log(doublereal); /* Local variables */ integer i__, k, r__, i1, ii, ip; doublereal gap, mid, tmp, back, lgap, rgap, left; integer iter, nint, prev, next; doublereal cvrgd, right, width; extern integer igraphdlaneg_(integer *, doublereal *, doublereal *, doublereal * , doublereal *, integer *); integer negcnt; doublereal mnwdth; integer olnint, maxitr; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ --iwork; --work; --werr; --wgap; --w; --lld; --d__; /* Function Body */ *info = 0; maxitr = (integer) ((log(*spdiam + *pivmin) - log(*pivmin)) / log(2.)) + 2; mnwdth = *pivmin * 2.; r__ = *twist; if (r__ < 1 || r__ > *n) { r__ = *n; } /* Initialize unconverged intervals in [ WORK(2*I-1), WORK(2*I) ]. The Sturm Count, Count( WORK(2*I-1) ) is arranged to be I-1, while Count( WORK(2*I) ) is stored in IWORK( 2*I ). The integer IWORK( 2*I-1 ) for an unconverged interval is set to the index of the next unconverged interval, and is -1 or 0 for a converged interval. Thus a linked list of unconverged intervals is set up. */ i1 = *ifirst; /* The number of unconverged intervals */ nint = 0; /* The last unconverged interval found */ prev = 0; rgap = wgap[i1 - *offset]; i__1 = *ilast; for (i__ = i1; i__ <= i__1; ++i__) { k = i__ << 1; ii = i__ - *offset; left = w[ii] - werr[ii]; right = w[ii] + werr[ii]; lgap = rgap; rgap = wgap[ii]; gap = min(lgap,rgap); /* Make sure that [LEFT,RIGHT] contains the desired eigenvalue Compute negcount from dstqds facto L+D+L+^T = L D L^T - LEFT Do while( NEGCNT(LEFT).GT.I-1 ) */ back = werr[ii]; L20: negcnt = igraphdlaneg_(n, &d__[1], &lld[1], &left, pivmin, &r__); if (negcnt > i__ - 1) { left -= back; back *= 2.; goto L20; } /* Do while( NEGCNT(RIGHT).LT.I ) Compute negcount from dstqds facto L+D+L+^T = L D L^T - RIGHT */ back = werr[ii]; L50: negcnt = igraphdlaneg_(n, &d__[1], &lld[1], &right, pivmin, &r__); if (negcnt < i__) { right += back; back *= 2.; goto L50; } width = (d__1 = left - right, abs(d__1)) * .5; /* Computing MAX */ d__1 = abs(left), d__2 = abs(right); tmp = max(d__1,d__2); /* Computing MAX */ d__1 = *rtol1 * gap, d__2 = *rtol2 * tmp; cvrgd = max(d__1,d__2); if (width <= cvrgd || width <= mnwdth) { /* This interval has already converged and does not need refinement. (Note that the gaps might change through refining the eigenvalues, however, they can only get bigger.) Remove it from the list. */ iwork[k - 1] = -1; /* Make sure that I1 always points to the first unconverged interval */ if (i__ == i1 && i__ < *ilast) { i1 = i__ + 1; } if (prev >= i1 && i__ <= *ilast) { iwork[(prev << 1) - 1] = i__ + 1; } } else { /* unconverged interval found */ prev = i__; ++nint; iwork[k - 1] = i__ + 1; iwork[k] = negcnt; } work[k - 1] = left; work[k] = right; /* L75: */ } /* Do while( NINT.GT.0 ), i.e. there are still unconverged intervals and while (ITER.LT.MAXITR) */ iter = 0; L80: prev = i1 - 1; i__ = i1; olnint = nint; i__1 = olnint; for (ip = 1; ip <= i__1; ++ip) { k = i__ << 1; ii = i__ - *offset; rgap = wgap[ii]; lgap = rgap; if (ii > 1) { lgap = wgap[ii - 1]; } gap = min(lgap,rgap); next = iwork[k - 1]; left = work[k - 1]; right = work[k]; mid = (left + right) * .5; /* semiwidth of interval */ width = right - mid; /* Computing MAX */ d__1 = abs(left), d__2 = abs(right); tmp = max(d__1,d__2); /* Computing MAX */ d__1 = *rtol1 * gap, d__2 = *rtol2 * tmp; cvrgd = max(d__1,d__2); if (width <= cvrgd || width <= mnwdth || iter == maxitr) { /* reduce number of unconverged intervals */ --nint; /* Mark interval as converged. */ iwork[k - 1] = 0; if (i1 == i__) { i1 = next; } else { /* Prev holds the last unconverged interval previously examined */ if (prev >= i1) { iwork[(prev << 1) - 1] = next; } } i__ = next; goto L100; } prev = i__; /* Perform one bisection step */ negcnt = igraphdlaneg_(n, &d__[1], &lld[1], &mid, pivmin, &r__); if (negcnt <= i__ - 1) { work[k - 1] = mid; } else { work[k] = mid; } i__ = next; L100: ; } ++iter; /* do another loop if there are still unconverged intervals However, in the last iteration, all intervals are accepted since this is the best we can do. */ if (nint > 0 && iter <= maxitr) { goto L80; } /* At this point, all the intervals have converged */ i__1 = *ilast; for (i__ = *ifirst; i__ <= i__1; ++i__) { k = i__ << 1; ii = i__ - *offset; /* All intervals marked by '0' have been refined. */ if (iwork[k - 1] == 0) { w[ii] = (work[k - 1] + work[k]) * .5; werr[ii] = work[k] - w[ii]; } /* L110: */ } i__1 = *ilast; for (i__ = *ifirst + 1; i__ <= i__1; ++i__) { k = i__ << 1; ii = i__ - *offset; /* Computing MAX */ d__1 = 0., d__2 = w[ii] - werr[ii] - w[ii - 1] - werr[ii - 1]; wgap[ii - 1] = max(d__1,d__2); /* L111: */ } return 0; /* End of DLARRB */ } /* igraphdlarrb_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/xerbla.c0000644000076500000240000000714713524616145024272 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; /* > \brief \b XERBLA =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download XERBLA + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE XERBLA( SRNAME, INFO ) CHARACTER*(*) SRNAME INTEGER INFO > \par Purpose: ============= > > \verbatim > > XERBLA is an error handler for the LAPACK routines. > It is called by an LAPACK routine if an input parameter has an > invalid value. A message is printed and execution stops. > > Installers may consider modifying the STOP statement in order to > call system-specific exception-handling facilities. > \endverbatim Arguments: ========== > \param[in] SRNAME > \verbatim > SRNAME is CHARACTER*(*) > The name of the routine which called XERBLA. > \endverbatim > > \param[in] INFO > \verbatim > INFO is INTEGER > The position of the invalid parameter in the parameter list > of the calling routine. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2011 > \ingroup auxOTHERauxiliary ===================================================================== Subroutine */ int igraphxerbla_(char *srname, integer *info, ftnlen srname_len) { /* Format strings */ static char fmt_9999[] = "(\002 ** On entry to \002,a,\002 parameter num" "ber \002,i2,\002 had \002,\002an illegal value\002)"; /* Builtin functions */ integer s_wsfe(cilist *), do_fio(integer *, char *, ftnlen), e_wsfe(void); /* Subroutine */ int s_stop(char *, ftnlen); /* Local variables */ extern integer igraphlen_trim__(char *, ftnlen); /* Fortran I/O blocks */ static cilist io___1 = { 0, 6, 0, fmt_9999, 0 }; /* -- LAPACK auxiliary routine (version 3.4.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2011 ===================================================================== */ s_wsfe(&io___1); do_fio(&c__1, srname, igraphlen_trim__(srname, srname_len)); do_fio(&c__1, (char *)&(*info), (ftnlen)sizeof(integer)); e_wsfe(); s_stop("", (ftnlen)0); /* End of XERBLA */ return 0; } /* igraphxerbla_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlaswp.c0000644000076500000240000001340013524616145024274 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLASWP performs a series of row interchanges on a general rectangular matrix. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLASWP + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLASWP( N, A, LDA, K1, K2, IPIV, INCX ) INTEGER INCX, K1, K2, LDA, N INTEGER IPIV( * ) DOUBLE PRECISION A( LDA, * ) > \par Purpose: ============= > > \verbatim > > DLASWP performs a series of row interchanges on the matrix A. > One row interchange is initiated for each of rows K1 through K2 of A. > \endverbatim Arguments: ========== > \param[in] N > \verbatim > N is INTEGER > The number of columns of the matrix A. > \endverbatim > > \param[in,out] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,N) > On entry, the matrix of column dimension N to which the row > interchanges will be applied. > On exit, the permuted matrix. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. > \endverbatim > > \param[in] K1 > \verbatim > K1 is INTEGER > The first element of IPIV for which a row interchange will > be done. > \endverbatim > > \param[in] K2 > \verbatim > K2 is INTEGER > The last element of IPIV for which a row interchange will > be done. > \endverbatim > > \param[in] IPIV > \verbatim > IPIV is INTEGER array, dimension (K2*abs(INCX)) > The vector of pivot indices. Only the elements in positions > K1 through K2 of IPIV are accessed. > IPIV(K) = L implies rows K and L are to be interchanged. > \endverbatim > > \param[in] INCX > \verbatim > INCX is INTEGER > The increment between successive values of IPIV. If IPIV > is negative, the pivots are applied in reverse order. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleOTHERauxiliary > \par Further Details: ===================== > > \verbatim > > Modified by > R. C. Whaley, Computer Science Dept., Univ. of Tenn., Knoxville, USA > \endverbatim > ===================================================================== Subroutine */ int igraphdlaswp_(integer *n, doublereal *a, integer *lda, integer *k1, integer *k2, integer *ipiv, integer *incx) { /* System generated locals */ integer a_dim1, a_offset, i__1, i__2, i__3, i__4; /* Local variables */ integer i__, j, k, i1, i2, n32, ip, ix, ix0, inc; doublereal temp; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Interchange row I with row IPIV(I) for each of rows K1 through K2. Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --ipiv; /* Function Body */ if (*incx > 0) { ix0 = *k1; i1 = *k1; i2 = *k2; inc = 1; } else if (*incx < 0) { ix0 = (1 - *k2) * *incx + 1; i1 = *k2; i2 = *k1; inc = -1; } else { return 0; } n32 = *n / 32 << 5; if (n32 != 0) { i__1 = n32; for (j = 1; j <= i__1; j += 32) { ix = ix0; i__2 = i2; i__3 = inc; for (i__ = i1; i__3 < 0 ? i__ >= i__2 : i__ <= i__2; i__ += i__3) { ip = ipiv[ix]; if (ip != i__) { i__4 = j + 31; for (k = j; k <= i__4; ++k) { temp = a[i__ + k * a_dim1]; a[i__ + k * a_dim1] = a[ip + k * a_dim1]; a[ip + k * a_dim1] = temp; /* L10: */ } } ix += *incx; /* L20: */ } /* L30: */ } } if (n32 != *n) { ++n32; ix = ix0; i__1 = i2; i__3 = inc; for (i__ = i1; i__3 < 0 ? i__ >= i__1 : i__ <= i__1; i__ += i__3) { ip = ipiv[ix]; if (ip != i__) { i__2 = *n; for (k = n32; k <= i__2; ++k) { temp = a[i__ + k * a_dim1]; a[i__ + k * a_dim1] = a[ip + k * a_dim1]; a[ip + k * a_dim1] = temp; /* L40: */ } } ix += *incx; /* L50: */ } } return 0; /* End of DLASWP */ } /* igraphdlaswp_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlacn2.c0000644000076500000240000002107313524616145024152 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; static doublereal c_b11 = 1.; /* > \brief \b DLACN2 estimates the 1-norm of a square matrix, using reverse communication for evaluating matr ix-vector products. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLACN2 + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLACN2( N, V, X, ISGN, EST, KASE, ISAVE ) INTEGER KASE, N DOUBLE PRECISION EST INTEGER ISGN( * ), ISAVE( 3 ) DOUBLE PRECISION V( * ), X( * ) > \par Purpose: ============= > > \verbatim > > DLACN2 estimates the 1-norm of a square, real matrix A. > Reverse communication is used for evaluating matrix-vector products. > \endverbatim Arguments: ========== > \param[in] N > \verbatim > N is INTEGER > The order of the matrix. N >= 1. > \endverbatim > > \param[out] V > \verbatim > V is DOUBLE PRECISION array, dimension (N) > On the final return, V = A*W, where EST = norm(V)/norm(W) > (W is not returned). > \endverbatim > > \param[in,out] X > \verbatim > X is DOUBLE PRECISION array, dimension (N) > On an intermediate return, X should be overwritten by > A * X, if KASE=1, > A**T * X, if KASE=2, > and DLACN2 must be re-called with all the other parameters > unchanged. > \endverbatim > > \param[out] ISGN > \verbatim > ISGN is INTEGER array, dimension (N) > \endverbatim > > \param[in,out] EST > \verbatim > EST is DOUBLE PRECISION > On entry with KASE = 1 or 2 and ISAVE(1) = 3, EST should be > unchanged from the previous call to DLACN2. > On exit, EST is an estimate (a lower bound) for norm(A). > \endverbatim > > \param[in,out] KASE > \verbatim > KASE is INTEGER > On the initial call to DLACN2, KASE should be 0. > On an intermediate return, KASE will be 1 or 2, indicating > whether X should be overwritten by A * X or A**T * X. > On the final return from DLACN2, KASE will again be 0. > \endverbatim > > \param[in,out] ISAVE > \verbatim > ISAVE is INTEGER array, dimension (3) > ISAVE is used to save variables between calls to DLACN2 > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleOTHERauxiliary > \par Further Details: ===================== > > \verbatim > > Originally named SONEST, dated March 16, 1988. > > This is a thread safe version of DLACON, which uses the array ISAVE > in place of a SAVE statement, as follows: > > DLACON DLACN2 > JUMP ISAVE(1) > J ISAVE(2) > ITER ISAVE(3) > \endverbatim > \par Contributors: ================== > > Nick Higham, University of Manchester > \par References: ================ > > N.J. Higham, "FORTRAN codes for estimating the one-norm of > a real or complex matrix, with applications to condition estimation", > ACM Trans. Math. Soft., vol. 14, no. 4, pp. 381-396, December 1988. > ===================================================================== Subroutine */ int igraphdlacn2_(integer *n, doublereal *v, doublereal *x, integer *isgn, doublereal *est, integer *kase, integer *isave) { /* System generated locals */ integer i__1; doublereal d__1; /* Builtin functions */ double d_sign(doublereal *, doublereal *); integer i_dnnt(doublereal *); /* Local variables */ integer i__; doublereal temp; extern doublereal igraphdasum_(integer *, doublereal *, integer *); integer jlast; extern /* Subroutine */ int igraphdcopy_(integer *, doublereal *, integer *, doublereal *, integer *); extern integer igraphidamax_(integer *, doublereal *, integer *); doublereal altsgn, estold; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ --isave; --isgn; --x; --v; /* Function Body */ if (*kase == 0) { i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { x[i__] = 1. / (doublereal) (*n); /* L10: */ } *kase = 1; isave[1] = 1; return 0; } switch (isave[1]) { case 1: goto L20; case 2: goto L40; case 3: goto L70; case 4: goto L110; case 5: goto L140; } /* ................ ENTRY (ISAVE( 1 ) = 1) FIRST ITERATION. X HAS BEEN OVERWRITTEN BY A*X. */ L20: if (*n == 1) { v[1] = x[1]; *est = abs(v[1]); /* ... QUIT */ goto L150; } *est = igraphdasum_(n, &x[1], &c__1); i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { x[i__] = d_sign(&c_b11, &x[i__]); isgn[i__] = i_dnnt(&x[i__]); /* L30: */ } *kase = 2; isave[1] = 2; return 0; /* ................ ENTRY (ISAVE( 1 ) = 2) FIRST ITERATION. X HAS BEEN OVERWRITTEN BY TRANSPOSE(A)*X. */ L40: isave[2] = igraphidamax_(n, &x[1], &c__1); isave[3] = 2; /* MAIN LOOP - ITERATIONS 2,3,...,ITMAX. */ L50: i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { x[i__] = 0.; /* L60: */ } x[isave[2]] = 1.; *kase = 1; isave[1] = 3; return 0; /* ................ ENTRY (ISAVE( 1 ) = 3) X HAS BEEN OVERWRITTEN BY A*X. */ L70: igraphdcopy_(n, &x[1], &c__1, &v[1], &c__1); estold = *est; *est = igraphdasum_(n, &v[1], &c__1); i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { d__1 = d_sign(&c_b11, &x[i__]); if (i_dnnt(&d__1) != isgn[i__]) { goto L90; } /* L80: */ } /* REPEATED SIGN VECTOR DETECTED, HENCE ALGORITHM HAS CONVERGED. */ goto L120; L90: /* TEST FOR CYCLING. */ if (*est <= estold) { goto L120; } i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { x[i__] = d_sign(&c_b11, &x[i__]); isgn[i__] = i_dnnt(&x[i__]); /* L100: */ } *kase = 2; isave[1] = 4; return 0; /* ................ ENTRY (ISAVE( 1 ) = 4) X HAS BEEN OVERWRITTEN BY TRANSPOSE(A)*X. */ L110: jlast = isave[2]; isave[2] = igraphidamax_(n, &x[1], &c__1); if (x[jlast] != (d__1 = x[isave[2]], abs(d__1)) && isave[3] < 5) { ++isave[3]; goto L50; } /* ITERATION COMPLETE. FINAL STAGE. */ L120: altsgn = 1.; i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { x[i__] = altsgn * ((doublereal) (i__ - 1) / (doublereal) (*n - 1) + 1.); altsgn = -altsgn; /* L130: */ } *kase = 1; isave[1] = 5; return 0; /* ................ ENTRY (ISAVE( 1 ) = 5) X HAS BEEN OVERWRITTEN BY A*X. */ L140: temp = igraphdasum_(n, &x[1], &c__1) / (doublereal) (*n * 3) * 2.; if (temp > *est) { igraphdcopy_(n, &x[1], &c__1, &v[1], &c__1); *est = temp; } L150: *kase = 0; return 0; /* End of DLACN2 */ } /* igraphdlacn2_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dsymv.c0000644000076500000240000001752413524616145024157 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Subroutine */ int igraphdsymv_(char *uplo, integer *n, doublereal *alpha, doublereal *a, integer *lda, doublereal *x, integer *incx, doublereal *beta, doublereal *y, integer *incy) { /* System generated locals */ integer a_dim1, a_offset, i__1, i__2; /* Local variables */ integer i__, j, ix, iy, jx, jy, kx, ky, info; doublereal temp1, temp2; extern logical igraphlsame_(char *, char *); extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); /* Purpose ======= DSYMV performs the matrix-vector operation y := alpha*A*x + beta*y, where alpha and beta are scalars, x and y are n element vectors and A is an n by n symmetric matrix. Arguments ========== UPLO - CHARACTER*1. On entry, UPLO specifies whether the upper or lower triangular part of the array A is to be referenced as follows: UPLO = 'U' or 'u' Only the upper triangular part of A is to be referenced. UPLO = 'L' or 'l' Only the lower triangular part of A is to be referenced. Unchanged on exit. N - INTEGER. On entry, N specifies the order of the matrix A. N must be at least zero. Unchanged on exit. ALPHA - DOUBLE PRECISION. On entry, ALPHA specifies the scalar alpha. Unchanged on exit. A - DOUBLE PRECISION array of DIMENSION ( LDA, n ). Before entry with UPLO = 'U' or 'u', the leading n by n upper triangular part of the array A must contain the upper triangular part of the symmetric matrix and the strictly lower triangular part of A is not referenced. Before entry with UPLO = 'L' or 'l', the leading n by n lower triangular part of the array A must contain the lower triangular part of the symmetric matrix and the strictly upper triangular part of A is not referenced. Unchanged on exit. LDA - INTEGER. On entry, LDA specifies the first dimension of A as declared in the calling (sub) program. LDA must be at least max( 1, n ). Unchanged on exit. X - DOUBLE PRECISION array of dimension at least ( 1 + ( n - 1 )*abs( INCX ) ). Before entry, the incremented array X must contain the n element vector x. Unchanged on exit. INCX - INTEGER. On entry, INCX specifies the increment for the elements of X. INCX must not be zero. Unchanged on exit. BETA - DOUBLE PRECISION. On entry, BETA specifies the scalar beta. When BETA is supplied as zero then Y need not be set on input. Unchanged on exit. Y - DOUBLE PRECISION array of dimension at least ( 1 + ( n - 1 )*abs( INCY ) ). Before entry, the incremented array Y must contain the n element vector y. On exit, Y is overwritten by the updated vector y. INCY - INTEGER. On entry, INCY specifies the increment for the elements of Y. INCY must not be zero. Unchanged on exit. Further Details =============== Level 2 Blas routine. The vector and matrix arguments are not referenced when N = 0, or M = 0 -- Written on 22-October-1986. Jack Dongarra, Argonne National Lab. Jeremy Du Croz, Nag Central Office. Sven Hammarling, Nag Central Office. Richard Hanson, Sandia National Labs. ===================================================================== Test the input parameters. Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --x; --y; /* Function Body */ info = 0; if (! igraphlsame_(uplo, "U") && ! igraphlsame_(uplo, "L")) { info = 1; } else if (*n < 0) { info = 2; } else if (*lda < max(1,*n)) { info = 5; } else if (*incx == 0) { info = 7; } else if (*incy == 0) { info = 10; } if (info != 0) { igraphxerbla_("DSYMV ", &info, (ftnlen)6); return 0; } /* Quick return if possible. */ if (*n == 0 || *alpha == 0. && *beta == 1.) { return 0; } /* Set up the start points in X and Y. */ if (*incx > 0) { kx = 1; } else { kx = 1 - (*n - 1) * *incx; } if (*incy > 0) { ky = 1; } else { ky = 1 - (*n - 1) * *incy; } /* Start the operations. In this version the elements of A are accessed sequentially with one pass through the triangular part of A. First form y := beta*y. */ if (*beta != 1.) { if (*incy == 1) { if (*beta == 0.) { i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { y[i__] = 0.; /* L10: */ } } else { i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { y[i__] = *beta * y[i__]; /* L20: */ } } } else { iy = ky; if (*beta == 0.) { i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { y[iy] = 0.; iy += *incy; /* L30: */ } } else { i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { y[iy] = *beta * y[iy]; iy += *incy; /* L40: */ } } } } if (*alpha == 0.) { return 0; } if (igraphlsame_(uplo, "U")) { /* Form y when A is stored in upper triangle. */ if (*incx == 1 && *incy == 1) { i__1 = *n; for (j = 1; j <= i__1; ++j) { temp1 = *alpha * x[j]; temp2 = 0.; i__2 = j - 1; for (i__ = 1; i__ <= i__2; ++i__) { y[i__] += temp1 * a[i__ + j * a_dim1]; temp2 += a[i__ + j * a_dim1] * x[i__]; /* L50: */ } y[j] = y[j] + temp1 * a[j + j * a_dim1] + *alpha * temp2; /* L60: */ } } else { jx = kx; jy = ky; i__1 = *n; for (j = 1; j <= i__1; ++j) { temp1 = *alpha * x[jx]; temp2 = 0.; ix = kx; iy = ky; i__2 = j - 1; for (i__ = 1; i__ <= i__2; ++i__) { y[iy] += temp1 * a[i__ + j * a_dim1]; temp2 += a[i__ + j * a_dim1] * x[ix]; ix += *incx; iy += *incy; /* L70: */ } y[jy] = y[jy] + temp1 * a[j + j * a_dim1] + *alpha * temp2; jx += *incx; jy += *incy; /* L80: */ } } } else { /* Form y when A is stored in lower triangle. */ if (*incx == 1 && *incy == 1) { i__1 = *n; for (j = 1; j <= i__1; ++j) { temp1 = *alpha * x[j]; temp2 = 0.; y[j] += temp1 * a[j + j * a_dim1]; i__2 = *n; for (i__ = j + 1; i__ <= i__2; ++i__) { y[i__] += temp1 * a[i__ + j * a_dim1]; temp2 += a[i__ + j * a_dim1] * x[i__]; /* L90: */ } y[j] += *alpha * temp2; /* L100: */ } } else { jx = kx; jy = ky; i__1 = *n; for (j = 1; j <= i__1; ++j) { temp1 = *alpha * x[jx]; temp2 = 0.; y[jy] += temp1 * a[j + j * a_dim1]; ix = jx; iy = jy; i__2 = *n; for (i__ = j + 1; i__ <= i__2; ++i__) { ix += *incx; iy += *incy; y[iy] += temp1 * a[i__ + j * a_dim1]; temp2 += a[i__ + j * a_dim1] * x[ix]; /* L110: */ } y[jy] += *alpha * temp2; jx += *incx; jy += *incy; /* L120: */ } } } return 0; /* End of DSYMV . */ } /* igraphdsymv_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dgebak.c0000644000076500000240000001736113524616145024231 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DGEBAK =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DGEBAK + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DGEBAK( JOB, SIDE, N, ILO, IHI, SCALE, M, V, LDV, INFO ) CHARACTER JOB, SIDE INTEGER IHI, ILO, INFO, LDV, M, N DOUBLE PRECISION SCALE( * ), V( LDV, * ) > \par Purpose: ============= > > \verbatim > > DGEBAK forms the right or left eigenvectors of a real general matrix > by backward transformation on the computed eigenvectors of the > balanced matrix output by DGEBAL. > \endverbatim Arguments: ========== > \param[in] JOB > \verbatim > JOB is CHARACTER*1 > Specifies the type of backward transformation required: > = 'N', do nothing, return immediately; > = 'P', do backward transformation for permutation only; > = 'S', do backward transformation for scaling only; > = 'B', do backward transformations for both permutation and > scaling. > JOB must be the same as the argument JOB supplied to DGEBAL. > \endverbatim > > \param[in] SIDE > \verbatim > SIDE is CHARACTER*1 > = 'R': V contains right eigenvectors; > = 'L': V contains left eigenvectors. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The number of rows of the matrix V. N >= 0. > \endverbatim > > \param[in] ILO > \verbatim > ILO is INTEGER > \endverbatim > > \param[in] IHI > \verbatim > IHI is INTEGER > The integers ILO and IHI determined by DGEBAL. > 1 <= ILO <= IHI <= N, if N > 0; ILO=1 and IHI=0, if N=0. > \endverbatim > > \param[in] SCALE > \verbatim > SCALE is DOUBLE PRECISION array, dimension (N) > Details of the permutation and scaling factors, as returned > by DGEBAL. > \endverbatim > > \param[in] M > \verbatim > M is INTEGER > The number of columns of the matrix V. M >= 0. > \endverbatim > > \param[in,out] V > \verbatim > V is DOUBLE PRECISION array, dimension (LDV,M) > On entry, the matrix of right or left eigenvectors to be > transformed, as returned by DHSEIN or DTREVC. > On exit, V is overwritten by the transformed eigenvectors. > \endverbatim > > \param[in] LDV > \verbatim > LDV is INTEGER > The leading dimension of the array V. LDV >= max(1,N). > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2011 > \ingroup doubleGEcomputational ===================================================================== Subroutine */ int igraphdgebak_(char *job, char *side, integer *n, integer *ilo, integer *ihi, doublereal *scale, integer *m, doublereal *v, integer * ldv, integer *info) { /* System generated locals */ integer v_dim1, v_offset, i__1; /* Local variables */ integer i__, k; doublereal s; integer ii; extern /* Subroutine */ int igraphdscal_(integer *, doublereal *, doublereal *, integer *); extern logical igraphlsame_(char *, char *); extern /* Subroutine */ int igraphdswap_(integer *, doublereal *, integer *, doublereal *, integer *); logical leftv; extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); logical rightv; /* -- LAPACK computational routine (version 3.4.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2011 ===================================================================== Decode and Test the input parameters Parameter adjustments */ --scale; v_dim1 = *ldv; v_offset = 1 + v_dim1; v -= v_offset; /* Function Body */ rightv = igraphlsame_(side, "R"); leftv = igraphlsame_(side, "L"); *info = 0; if (! igraphlsame_(job, "N") && ! igraphlsame_(job, "P") && ! igraphlsame_(job, "S") && ! igraphlsame_(job, "B")) { *info = -1; } else if (! rightv && ! leftv) { *info = -2; } else if (*n < 0) { *info = -3; } else if (*ilo < 1 || *ilo > max(1,*n)) { *info = -4; } else if (*ihi < min(*ilo,*n) || *ihi > *n) { *info = -5; } else if (*m < 0) { *info = -7; } else if (*ldv < max(1,*n)) { *info = -9; } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DGEBAK", &i__1, (ftnlen)6); return 0; } /* Quick return if possible */ if (*n == 0) { return 0; } if (*m == 0) { return 0; } if (igraphlsame_(job, "N")) { return 0; } if (*ilo == *ihi) { goto L30; } /* Backward balance */ if (igraphlsame_(job, "S") || igraphlsame_(job, "B")) { if (rightv) { i__1 = *ihi; for (i__ = *ilo; i__ <= i__1; ++i__) { s = scale[i__]; igraphdscal_(m, &s, &v[i__ + v_dim1], ldv); /* L10: */ } } if (leftv) { i__1 = *ihi; for (i__ = *ilo; i__ <= i__1; ++i__) { s = 1. / scale[i__]; igraphdscal_(m, &s, &v[i__ + v_dim1], ldv); /* L20: */ } } } /* Backward permutation For I = ILO-1 step -1 until 1, IHI+1 step 1 until N do -- */ L30: if (igraphlsame_(job, "P") || igraphlsame_(job, "B")) { if (rightv) { i__1 = *n; for (ii = 1; ii <= i__1; ++ii) { i__ = ii; if (i__ >= *ilo && i__ <= *ihi) { goto L40; } if (i__ < *ilo) { i__ = *ilo - ii; } k = (integer) scale[i__]; if (k == i__) { goto L40; } igraphdswap_(m, &v[i__ + v_dim1], ldv, &v[k + v_dim1], ldv); L40: ; } } if (leftv) { i__1 = *n; for (ii = 1; ii <= i__1; ++ii) { i__ = ii; if (i__ >= *ilo && i__ <= *ihi) { goto L50; } if (i__ < *ilo) { i__ = *ilo - ii; } k = (integer) scale[i__]; if (k == i__) { goto L50; } igraphdswap_(m, &v[i__ + v_dim1], ldv, &v[k + v_dim1], ldv); L50: ; } } } return 0; /* End of DGEBAK */ } /* igraphdgebak_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dsyrk.c0000644000076500000240000002307313524616145024145 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Subroutine */ int igraphdsyrk_(char *uplo, char *trans, integer *n, integer *k, doublereal *alpha, doublereal *a, integer *lda, doublereal *beta, doublereal *c__, integer *ldc) { /* System generated locals */ integer a_dim1, a_offset, c_dim1, c_offset, i__1, i__2, i__3; /* Local variables */ integer i__, j, l, info; doublereal temp; extern logical igraphlsame_(char *, char *); integer nrowa; logical upper; extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); /* Purpose ======= DSYRK performs one of the symmetric rank k operations C := alpha*A*A**T + beta*C, or C := alpha*A**T*A + beta*C, where alpha and beta are scalars, C is an n by n symmetric matrix and A is an n by k matrix in the first case and a k by n matrix in the second case. Arguments ========== UPLO - CHARACTER*1. On entry, UPLO specifies whether the upper or lower triangular part of the array C is to be referenced as follows: UPLO = 'U' or 'u' Only the upper triangular part of C is to be referenced. UPLO = 'L' or 'l' Only the lower triangular part of C is to be referenced. Unchanged on exit. TRANS - CHARACTER*1. On entry, TRANS specifies the operation to be performed as follows: TRANS = 'N' or 'n' C := alpha*A*A**T + beta*C. TRANS = 'T' or 't' C := alpha*A**T*A + beta*C. TRANS = 'C' or 'c' C := alpha*A**T*A + beta*C. Unchanged on exit. N - INTEGER. On entry, N specifies the order of the matrix C. N must be at least zero. Unchanged on exit. K - INTEGER. On entry with TRANS = 'N' or 'n', K specifies the number of columns of the matrix A, and on entry with TRANS = 'T' or 't' or 'C' or 'c', K specifies the number of rows of the matrix A. K must be at least zero. Unchanged on exit. ALPHA - DOUBLE PRECISION. On entry, ALPHA specifies the scalar alpha. Unchanged on exit. A - DOUBLE PRECISION array of DIMENSION ( LDA, ka ), where ka is k when TRANS = 'N' or 'n', and is n otherwise. Before entry with TRANS = 'N' or 'n', the leading n by k part of the array A must contain the matrix A, otherwise the leading k by n part of the array A must contain the matrix A. Unchanged on exit. LDA - INTEGER. On entry, LDA specifies the first dimension of A as declared in the calling (sub) program. When TRANS = 'N' or 'n' then LDA must be at least max( 1, n ), otherwise LDA must be at least max( 1, k ). Unchanged on exit. BETA - DOUBLE PRECISION. On entry, BETA specifies the scalar beta. Unchanged on exit. C - DOUBLE PRECISION array of DIMENSION ( LDC, n ). Before entry with UPLO = 'U' or 'u', the leading n by n upper triangular part of the array C must contain the upper triangular part of the symmetric matrix and the strictly lower triangular part of C is not referenced. On exit, the upper triangular part of the array C is overwritten by the upper triangular part of the updated matrix. Before entry with UPLO = 'L' or 'l', the leading n by n lower triangular part of the array C must contain the lower triangular part of the symmetric matrix and the strictly upper triangular part of C is not referenced. On exit, the lower triangular part of the array C is overwritten by the lower triangular part of the updated matrix. LDC - INTEGER. On entry, LDC specifies the first dimension of C as declared in the calling (sub) program. LDC must be at least max( 1, n ). Unchanged on exit. Further Details =============== Level 3 Blas routine. -- Written on 8-February-1989. Jack Dongarra, Argonne National Laboratory. Iain Duff, AERE Harwell. Jeremy Du Croz, Numerical Algorithms Group Ltd. Sven Hammarling, Numerical Algorithms Group Ltd. ===================================================================== Test the input parameters. Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; c_dim1 = *ldc; c_offset = 1 + c_dim1; c__ -= c_offset; /* Function Body */ if (igraphlsame_(trans, "N")) { nrowa = *n; } else { nrowa = *k; } upper = igraphlsame_(uplo, "U"); info = 0; if (! upper && ! igraphlsame_(uplo, "L")) { info = 1; } else if (! igraphlsame_(trans, "N") && ! igraphlsame_(trans, "T") && ! igraphlsame_(trans, "C")) { info = 2; } else if (*n < 0) { info = 3; } else if (*k < 0) { info = 4; } else if (*lda < max(1,nrowa)) { info = 7; } else if (*ldc < max(1,*n)) { info = 10; } if (info != 0) { igraphxerbla_("DSYRK ", &info, (ftnlen)6); return 0; } /* Quick return if possible. */ if (*n == 0 || (*alpha == 0. || *k == 0) && *beta == 1.) { return 0; } /* And when alpha.eq.zero. */ if (*alpha == 0.) { if (upper) { if (*beta == 0.) { i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = j; for (i__ = 1; i__ <= i__2; ++i__) { c__[i__ + j * c_dim1] = 0.; /* L10: */ } /* L20: */ } } else { i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = j; for (i__ = 1; i__ <= i__2; ++i__) { c__[i__ + j * c_dim1] = *beta * c__[i__ + j * c_dim1]; /* L30: */ } /* L40: */ } } } else { if (*beta == 0.) { i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = *n; for (i__ = j; i__ <= i__2; ++i__) { c__[i__ + j * c_dim1] = 0.; /* L50: */ } /* L60: */ } } else { i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = *n; for (i__ = j; i__ <= i__2; ++i__) { c__[i__ + j * c_dim1] = *beta * c__[i__ + j * c_dim1]; /* L70: */ } /* L80: */ } } } return 0; } /* Start the operations. */ if (igraphlsame_(trans, "N")) { /* Form C := alpha*A*A**T + beta*C. */ if (upper) { i__1 = *n; for (j = 1; j <= i__1; ++j) { if (*beta == 0.) { i__2 = j; for (i__ = 1; i__ <= i__2; ++i__) { c__[i__ + j * c_dim1] = 0.; /* L90: */ } } else if (*beta != 1.) { i__2 = j; for (i__ = 1; i__ <= i__2; ++i__) { c__[i__ + j * c_dim1] = *beta * c__[i__ + j * c_dim1]; /* L100: */ } } i__2 = *k; for (l = 1; l <= i__2; ++l) { if (a[j + l * a_dim1] != 0.) { temp = *alpha * a[j + l * a_dim1]; i__3 = j; for (i__ = 1; i__ <= i__3; ++i__) { c__[i__ + j * c_dim1] += temp * a[i__ + l * a_dim1]; /* L110: */ } } /* L120: */ } /* L130: */ } } else { i__1 = *n; for (j = 1; j <= i__1; ++j) { if (*beta == 0.) { i__2 = *n; for (i__ = j; i__ <= i__2; ++i__) { c__[i__ + j * c_dim1] = 0.; /* L140: */ } } else if (*beta != 1.) { i__2 = *n; for (i__ = j; i__ <= i__2; ++i__) { c__[i__ + j * c_dim1] = *beta * c__[i__ + j * c_dim1]; /* L150: */ } } i__2 = *k; for (l = 1; l <= i__2; ++l) { if (a[j + l * a_dim1] != 0.) { temp = *alpha * a[j + l * a_dim1]; i__3 = *n; for (i__ = j; i__ <= i__3; ++i__) { c__[i__ + j * c_dim1] += temp * a[i__ + l * a_dim1]; /* L160: */ } } /* L170: */ } /* L180: */ } } } else { /* Form C := alpha*A**T*A + beta*C. */ if (upper) { i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = j; for (i__ = 1; i__ <= i__2; ++i__) { temp = 0.; i__3 = *k; for (l = 1; l <= i__3; ++l) { temp += a[l + i__ * a_dim1] * a[l + j * a_dim1]; /* L190: */ } if (*beta == 0.) { c__[i__ + j * c_dim1] = *alpha * temp; } else { c__[i__ + j * c_dim1] = *alpha * temp + *beta * c__[ i__ + j * c_dim1]; } /* L200: */ } /* L210: */ } } else { i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = *n; for (i__ = j; i__ <= i__2; ++i__) { temp = 0.; i__3 = *k; for (l = 1; l <= i__3; ++l) { temp += a[l + i__ * a_dim1] * a[l + j * a_dim1]; /* L220: */ } if (*beta == 0.) { c__[i__ + j * c_dim1] = *alpha * temp; } else { c__[i__ + j * c_dim1] = *alpha * temp + *beta * c__[ i__ + j * c_dim1]; } /* L230: */ } /* L240: */ } } } return 0; /* End of DSYRK . */ } /* igraphdsyrk_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlaqrb.c0000644000076500000240000005031213524616145024252 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; /* ----------------------------------------------------------------------- \BeginDoc \Name: dlaqrb \Description: Compute the eigenvalues and the Schur decomposition of an upper Hessenberg submatrix in rows and columns ILO to IHI. Only the last component of the Schur vectors are computed. This is mostly a modification of the LAPACK routine dlahqr. \Usage: call dlaqrb ( WANTT, N, ILO, IHI, H, LDH, WR, WI, Z, INFO ) \Arguments WANTT Logical variable. (INPUT) = .TRUE. : the full Schur form T is required; = .FALSE.: only eigenvalues are required. N Integer. (INPUT) The order of the matrix H. N >= 0. ILO Integer. (INPUT) IHI Integer. (INPUT) It is assumed that H is already upper quasi-triangular in rows and columns IHI+1:N, and that H(ILO,ILO-1) = 0 (unless ILO = 1). SLAQRB works primarily with the Hessenberg submatrix in rows and columns ILO to IHI, but applies transformations to all of H if WANTT is .TRUE.. 1 <= ILO <= max(1,IHI); IHI <= N. H Double precision array, dimension (LDH,N). (INPUT/OUTPUT) On entry, the upper Hessenberg matrix H. On exit, if WANTT is .TRUE., H is upper quasi-triangular in rows and columns ILO:IHI, with any 2-by-2 diagonal blocks in standard form. If WANTT is .FALSE., the contents of H are unspecified on exit. LDH Integer. (INPUT) The leading dimension of the array H. LDH >= max(1,N). WR Double precision array, dimension (N). (OUTPUT) WI Double precision array, dimension (N). (OUTPUT) The real and imaginary parts, respectively, of the computed eigenvalues ILO to IHI are stored in the corresponding elements of WR and WI. If two eigenvalues are computed as a complex conjugate pair, they are stored in consecutive elements of WR and WI, say the i-th and (i+1)th, with WI(i) > 0 and WI(i+1) < 0. If WANTT is .TRUE., the eigenvalues are stored in the same order as on the diagonal of the Schur form returned in H, with WR(i) = H(i,i), and, if H(i:i+1,i:i+1) is a 2-by-2 diagonal block, WI(i) = sqrt(H(i+1,i)*H(i,i+1)) and WI(i+1) = -WI(i). Z Double precision array, dimension (N). (OUTPUT) On exit Z contains the last components of the Schur vectors. INFO Integer. (OUPUT) = 0: successful exit > 0: SLAQRB failed to compute all the eigenvalues ILO to IHI in a total of 30*(IHI-ILO+1) iterations; if INFO = i, elements i+1:ihi of WR and WI contain those eigenvalues which have been successfully computed. \Remarks 1. None. ----------------------------------------------------------------------- \BeginLib \Local variables: xxxxxx real \Routines called: dlabad LAPACK routine that computes machine constants. dlamch LAPACK routine that determines machine constants. dlanhs LAPACK routine that computes various norms of a matrix. dlanv2 LAPACK routine that computes the Schur factorization of 2 by 2 nonsymmetric matrix in standard form. dlarfg LAPACK Householder reflection construction routine. dcopy Level 1 BLAS that copies one vector to another. drot Level 1 BLAS that applies a rotation to a 2 by 2 matrix. \Author Danny Sorensen Phuong Vu Richard Lehoucq CRPC / Rice University Dept. of Computational & Houston, Texas Applied Mathematics Rice University Houston, Texas \Revision history: xx/xx/92: Version ' 2.4' Modified from the LAPACK routine dlahqr so that only the last component of the Schur vectors are computed. \SCCS Information: @(#) FILE: laqrb.F SID: 2.2 DATE OF SID: 8/27/96 RELEASE: 2 \Remarks 1. None \EndLib ----------------------------------------------------------------------- Subroutine */ int igraphdlaqrb_(logical *wantt, integer *n, integer *ilo, integer *ihi, doublereal *h__, integer *ldh, doublereal *wr, doublereal *wi, doublereal *z__, integer *info) { /* System generated locals */ integer h_dim1, h_offset, i__1, i__2, i__3, i__4; doublereal d__1, d__2; /* Local variables */ integer i__, j, k, l, m; doublereal s, v[3]; integer i1, i2; doublereal t1, t2, t3, v1, v2, v3, h00, h10, h11, h12, h21, h22, h33, h44; integer nh; doublereal cs; integer nr; doublereal sn, h33s, h44s; integer itn, its; doublereal ulp, sum, tst1, h43h34, unfl, ovfl; extern /* Subroutine */ int igraphdrot_(integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *); doublereal work[1]; extern /* Subroutine */ int igraphdcopy_(integer *, doublereal *, integer *, doublereal *, integer *), igraphdlanv2_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *), igraphdlabad_( doublereal *, doublereal *); extern doublereal igraphdlamch_(char *); extern /* Subroutine */ int igraphdlarfg_(integer *, doublereal *, doublereal *, integer *, doublereal *); extern doublereal igraphdlanhs_(char *, integer *, doublereal *, integer *, doublereal *); doublereal smlnum; /* %------------------% | Scalar Arguments | %------------------% %-----------------% | Array Arguments | %-----------------% %------------% | Parameters | %------------% %------------------------% | Local Scalars & Arrays | %------------------------% %--------------------% | External Functions | %--------------------% %----------------------% | External Subroutines | %----------------------% %-----------------------% | Executable Statements | %-----------------------% Parameter adjustments */ h_dim1 = *ldh; h_offset = 1 + h_dim1; h__ -= h_offset; --wr; --wi; --z__; /* Function Body */ *info = 0; /* %--------------------------% | Quick return if possible | %--------------------------% */ if (*n == 0) { return 0; } if (*ilo == *ihi) { wr[*ilo] = h__[*ilo + *ilo * h_dim1]; wi[*ilo] = 0.; return 0; } /* %---------------------------------------------% | Initialize the vector of last components of | | the Schur vectors for accumulation. | %---------------------------------------------% */ i__1 = *n - 1; for (j = 1; j <= i__1; ++j) { z__[j] = 0.; /* L5: */ } z__[*n] = 1.; nh = *ihi - *ilo + 1; /* %-------------------------------------------------------------% | Set machine-dependent constants for the stopping criterion. | | If norm(H) <= sqrt(OVFL), overflow should not occur. | %-------------------------------------------------------------% */ unfl = igraphdlamch_("safe minimum"); ovfl = 1. / unfl; igraphdlabad_(&unfl, &ovfl); ulp = igraphdlamch_("precision"); smlnum = unfl * (nh / ulp); /* %---------------------------------------------------------------% | I1 and I2 are the indices of the first row and last column | | of H to which transformations must be applied. If eigenvalues | | only are computed, I1 and I2 are set inside the main loop. | | Zero out H(J+2,J) = ZERO for J=1:N if WANTT = .TRUE. | | else H(J+2,J) for J=ILO:IHI-ILO-1 if WANTT = .FALSE. | %---------------------------------------------------------------% */ if (*wantt) { i1 = 1; i2 = *n; i__1 = i2 - 2; for (i__ = 1; i__ <= i__1; ++i__) { h__[i1 + i__ + 1 + i__ * h_dim1] = 0.; /* L8: */ } } else { i__1 = *ihi - *ilo - 1; for (i__ = 1; i__ <= i__1; ++i__) { h__[*ilo + i__ + 1 + (*ilo + i__ - 1) * h_dim1] = 0.; /* L9: */ } } /* %---------------------------------------------------% | ITN is the total number of QR iterations allowed. | %---------------------------------------------------% */ itn = nh * 30; /* ------------------------------------------------------------------ The main loop begins here. I is the loop index and decreases from IHI to ILO in steps of 1 or 2. Each iteration of the loop works with the active submatrix in rows and columns L to I. Eigenvalues I+1 to IHI have already converged. Either L = ILO or H(L,L-1) is negligible so that the matrix splits. ------------------------------------------------------------------ */ i__ = *ihi; L10: l = *ilo; if (i__ < *ilo) { goto L150; } /* %--------------------------------------------------------------% | Perform QR iterations on rows and columns ILO to I until a | | submatrix of order 1 or 2 splits off at the bottom because a | | subdiagonal element has become negligible. | %--------------------------------------------------------------% */ i__1 = itn; for (its = 0; its <= i__1; ++its) { /* %----------------------------------------------% | Look for a single small subdiagonal element. | %----------------------------------------------% */ i__2 = l + 1; for (k = i__; k >= i__2; --k) { tst1 = (d__1 = h__[k - 1 + (k - 1) * h_dim1], abs(d__1)) + (d__2 = h__[k + k * h_dim1], abs(d__2)); if (tst1 == 0.) { i__3 = i__ - l + 1; tst1 = igraphdlanhs_("1", &i__3, &h__[l + l * h_dim1], ldh, work); } /* Computing MAX */ d__2 = ulp * tst1; if ((d__1 = h__[k + (k - 1) * h_dim1], abs(d__1)) <= max(d__2, smlnum)) { goto L30; } /* L20: */ } L30: l = k; if (l > *ilo) { /* %------------------------% | H(L,L-1) is negligible | %------------------------% */ h__[l + (l - 1) * h_dim1] = 0.; } /* %-------------------------------------------------------------% | Exit from loop if a submatrix of order 1 or 2 has split off | %-------------------------------------------------------------% */ if (l >= i__ - 1) { goto L140; } /* %---------------------------------------------------------% | Now the active submatrix is in rows and columns L to I. | | If eigenvalues only are being computed, only the active | | submatrix need be transformed. | %---------------------------------------------------------% */ if (! (*wantt)) { i1 = l; i2 = i__; } if (its == 10 || its == 20) { /* %-------------------% | Exceptional shift | %-------------------% */ s = (d__1 = h__[i__ + (i__ - 1) * h_dim1], abs(d__1)) + (d__2 = h__[i__ - 1 + (i__ - 2) * h_dim1], abs(d__2)); h44 = s * .75; h33 = h44; h43h34 = s * -.4375 * s; } else { /* %-----------------------------------------% | Prepare to use Wilkinson's double shift | %-----------------------------------------% */ h44 = h__[i__ + i__ * h_dim1]; h33 = h__[i__ - 1 + (i__ - 1) * h_dim1]; h43h34 = h__[i__ + (i__ - 1) * h_dim1] * h__[i__ - 1 + i__ * h_dim1]; } /* %-----------------------------------------------------% | Look for two consecutive small subdiagonal elements | %-----------------------------------------------------% */ i__2 = l; for (m = i__ - 2; m >= i__2; --m) { /* %---------------------------------------------------------% | Determine the effect of starting the double-shift QR | | iteration at row M, and see if this would make H(M,M-1) | | negligible. | %---------------------------------------------------------% */ h11 = h__[m + m * h_dim1]; h22 = h__[m + 1 + (m + 1) * h_dim1]; h21 = h__[m + 1 + m * h_dim1]; h12 = h__[m + (m + 1) * h_dim1]; h44s = h44 - h11; h33s = h33 - h11; v1 = (h33s * h44s - h43h34) / h21 + h12; v2 = h22 - h11 - h33s - h44s; v3 = h__[m + 2 + (m + 1) * h_dim1]; s = abs(v1) + abs(v2) + abs(v3); v1 /= s; v2 /= s; v3 /= s; v[0] = v1; v[1] = v2; v[2] = v3; if (m == l) { goto L50; } h00 = h__[m - 1 + (m - 1) * h_dim1]; h10 = h__[m + (m - 1) * h_dim1]; tst1 = abs(v1) * (abs(h00) + abs(h11) + abs(h22)); if (abs(h10) * (abs(v2) + abs(v3)) <= ulp * tst1) { goto L50; } /* L40: */ } L50: /* %----------------------% | Double-shift QR step | %----------------------% */ i__2 = i__ - 1; for (k = m; k <= i__2; ++k) { /* ------------------------------------------------------------ The first iteration of this loop determines a reflection G from the vector V and applies it from left and right to H, thus creating a nonzero bulge below the subdiagonal. Each subsequent iteration determines a reflection G to restore the Hessenberg form in the (K-1)th column, and thus chases the bulge one step toward the bottom of the active submatrix. NR is the order of G. ------------------------------------------------------------ Computing MIN */ i__3 = 3, i__4 = i__ - k + 1; nr = min(i__3,i__4); if (k > m) { igraphdcopy_(&nr, &h__[k + (k - 1) * h_dim1], &c__1, v, &c__1); } igraphdlarfg_(&nr, v, &v[1], &c__1, &t1); if (k > m) { h__[k + (k - 1) * h_dim1] = v[0]; h__[k + 1 + (k - 1) * h_dim1] = 0.; if (k < i__ - 1) { h__[k + 2 + (k - 1) * h_dim1] = 0.; } } else if (m > l) { h__[k + (k - 1) * h_dim1] = -h__[k + (k - 1) * h_dim1]; } v2 = v[1]; t2 = t1 * v2; if (nr == 3) { v3 = v[2]; t3 = t1 * v3; /* %------------------------------------------------% | Apply G from the left to transform the rows of | | the matrix in columns K to I2. | %------------------------------------------------% */ i__3 = i2; for (j = k; j <= i__3; ++j) { sum = h__[k + j * h_dim1] + v2 * h__[k + 1 + j * h_dim1] + v3 * h__[k + 2 + j * h_dim1]; h__[k + j * h_dim1] -= sum * t1; h__[k + 1 + j * h_dim1] -= sum * t2; h__[k + 2 + j * h_dim1] -= sum * t3; /* L60: */ } /* %----------------------------------------------------% | Apply G from the right to transform the columns of | | the matrix in rows I1 to min(K+3,I). | %----------------------------------------------------% Computing MIN */ i__4 = k + 3; i__3 = min(i__4,i__); for (j = i1; j <= i__3; ++j) { sum = h__[j + k * h_dim1] + v2 * h__[j + (k + 1) * h_dim1] + v3 * h__[j + (k + 2) * h_dim1]; h__[j + k * h_dim1] -= sum * t1; h__[j + (k + 1) * h_dim1] -= sum * t2; h__[j + (k + 2) * h_dim1] -= sum * t3; /* L70: */ } /* %----------------------------------% | Accumulate transformations for Z | %----------------------------------% */ sum = z__[k] + v2 * z__[k + 1] + v3 * z__[k + 2]; z__[k] -= sum * t1; z__[k + 1] -= sum * t2; z__[k + 2] -= sum * t3; } else if (nr == 2) { /* %------------------------------------------------% | Apply G from the left to transform the rows of | | the matrix in columns K to I2. | %------------------------------------------------% */ i__3 = i2; for (j = k; j <= i__3; ++j) { sum = h__[k + j * h_dim1] + v2 * h__[k + 1 + j * h_dim1]; h__[k + j * h_dim1] -= sum * t1; h__[k + 1 + j * h_dim1] -= sum * t2; /* L90: */ } /* %----------------------------------------------------% | Apply G from the right to transform the columns of | | the matrix in rows I1 to min(K+3,I). | %----------------------------------------------------% */ i__3 = i__; for (j = i1; j <= i__3; ++j) { sum = h__[j + k * h_dim1] + v2 * h__[j + (k + 1) * h_dim1] ; h__[j + k * h_dim1] -= sum * t1; h__[j + (k + 1) * h_dim1] -= sum * t2; /* L100: */ } /* %----------------------------------% | Accumulate transformations for Z | %----------------------------------% */ sum = z__[k] + v2 * z__[k + 1]; z__[k] -= sum * t1; z__[k + 1] -= sum * t2; } /* L120: */ } /* L130: */ } /* %-------------------------------------------------------% | Failure to converge in remaining number of iterations | %-------------------------------------------------------% */ *info = i__; return 0; L140: if (l == i__) { /* %------------------------------------------------------% | H(I,I-1) is negligible: one eigenvalue has converged | %------------------------------------------------------% */ wr[i__] = h__[i__ + i__ * h_dim1]; wi[i__] = 0.; } else if (l == i__ - 1) { /* %--------------------------------------------------------% | H(I-1,I-2) is negligible; | | a pair of eigenvalues have converged. | | | | Transform the 2-by-2 submatrix to standard Schur form, | | and compute and store the eigenvalues. | %--------------------------------------------------------% */ igraphdlanv2_(&h__[i__ - 1 + (i__ - 1) * h_dim1], &h__[i__ - 1 + i__ * h_dim1], &h__[i__ + (i__ - 1) * h_dim1], &h__[i__ + i__ * h_dim1], &wr[i__ - 1], &wi[i__ - 1], &wr[i__], &wi[i__], &cs, &sn); if (*wantt) { /* %-----------------------------------------------------% | Apply the transformation to the rest of H and to Z, | | as required. | %-----------------------------------------------------% */ if (i2 > i__) { i__1 = i2 - i__; igraphdrot_(&i__1, &h__[i__ - 1 + (i__ + 1) * h_dim1], ldh, &h__[ i__ + (i__ + 1) * h_dim1], ldh, &cs, &sn); } i__1 = i__ - i1 - 1; igraphdrot_(&i__1, &h__[i1 + (i__ - 1) * h_dim1], &c__1, &h__[i1 + i__ * h_dim1], &c__1, &cs, &sn); sum = cs * z__[i__ - 1] + sn * z__[i__]; z__[i__] = cs * z__[i__] - sn * z__[i__ - 1]; z__[i__ - 1] = sum; } } /* %---------------------------------------------------------% | Decrement number of remaining iterations, and return to | | start of the main loop with new value of I. | %---------------------------------------------------------% */ itn -= its; i__ = l - 1; goto L10; L150: return 0; /* %---------------% | End of dlaqrb | %---------------% */ } /* igraphdlaqrb_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlasq3.c0000644000076500000240000002714713524616145024206 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLASQ3 checks for deflation, computes a shift and calls dqds. Used by sbdsqr. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLASQ3 + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLASQ3( I0, N0, Z, PP, DMIN, SIGMA, DESIG, QMAX, NFAIL, ITER, NDIV, IEEE, TTYPE, DMIN1, DMIN2, DN, DN1, DN2, G, TAU ) LOGICAL IEEE INTEGER I0, ITER, N0, NDIV, NFAIL, PP DOUBLE PRECISION DESIG, DMIN, DMIN1, DMIN2, DN, DN1, DN2, G, $ QMAX, SIGMA, TAU DOUBLE PRECISION Z( * ) > \par Purpose: ============= > > \verbatim > > DLASQ3 checks for deflation, computes a shift (TAU) and calls dqds. > In case of failure it changes shifts, and tries again until output > is positive. > \endverbatim Arguments: ========== > \param[in] I0 > \verbatim > I0 is INTEGER > First index. > \endverbatim > > \param[in,out] N0 > \verbatim > N0 is INTEGER > Last index. > \endverbatim > > \param[in] Z > \verbatim > Z is DOUBLE PRECISION array, dimension ( 4*N ) > Z holds the qd array. > \endverbatim > > \param[in,out] PP > \verbatim > PP is INTEGER > PP=0 for ping, PP=1 for pong. > PP=2 indicates that flipping was applied to the Z array > and that the initial tests for deflation should not be > performed. > \endverbatim > > \param[out] DMIN > \verbatim > DMIN is DOUBLE PRECISION > Minimum value of d. > \endverbatim > > \param[out] SIGMA > \verbatim > SIGMA is DOUBLE PRECISION > Sum of shifts used in current segment. > \endverbatim > > \param[in,out] DESIG > \verbatim > DESIG is DOUBLE PRECISION > Lower order part of SIGMA > \endverbatim > > \param[in] QMAX > \verbatim > QMAX is DOUBLE PRECISION > Maximum value of q. > \endverbatim > > \param[out] NFAIL > \verbatim > NFAIL is INTEGER > Number of times shift was too big. > \endverbatim > > \param[out] ITER > \verbatim > ITER is INTEGER > Number of iterations. > \endverbatim > > \param[out] NDIV > \verbatim > NDIV is INTEGER > Number of divisions. > \endverbatim > > \param[in] IEEE > \verbatim > IEEE is LOGICAL > Flag for IEEE or non IEEE arithmetic (passed to DLASQ5). > \endverbatim > > \param[in,out] TTYPE > \verbatim > TTYPE is INTEGER > Shift type. > \endverbatim > > \param[in,out] DMIN1 > \verbatim > DMIN1 is DOUBLE PRECISION > \endverbatim > > \param[in,out] DMIN2 > \verbatim > DMIN2 is DOUBLE PRECISION > \endverbatim > > \param[in,out] DN > \verbatim > DN is DOUBLE PRECISION > \endverbatim > > \param[in,out] DN1 > \verbatim > DN1 is DOUBLE PRECISION > \endverbatim > > \param[in,out] DN2 > \verbatim > DN2 is DOUBLE PRECISION > \endverbatim > > \param[in,out] G > \verbatim > G is DOUBLE PRECISION > \endverbatim > > \param[in,out] TAU > \verbatim > TAU is DOUBLE PRECISION > > These are passed as arguments in order to save their values > between calls to DLASQ3. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERcomputational ===================================================================== Subroutine */ int igraphdlasq3_(integer *i0, integer *n0, doublereal *z__, integer *pp, doublereal *dmin__, doublereal *sigma, doublereal *desig, doublereal *qmax, integer *nfail, integer *iter, integer *ndiv, logical *ieee, integer *ttype, doublereal *dmin1, doublereal *dmin2, doublereal *dn, doublereal *dn1, doublereal *dn2, doublereal *g, doublereal *tau) { /* System generated locals */ integer i__1; doublereal d__1, d__2; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ doublereal s, t; integer j4, nn; doublereal eps, tol; integer n0in, ipn4; doublereal tol2, temp; extern /* Subroutine */ int igraphdlasq4_(integer *, integer *, doublereal *, integer *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, integer *, doublereal *), igraphdlasq5_(integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, logical * , doublereal *), igraphdlasq6_(integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *); extern doublereal igraphdlamch_(char *); extern logical igraphdisnan_(doublereal *); /* -- LAPACK computational routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ --z__; /* Function Body */ n0in = *n0; eps = igraphdlamch_("Precision"); tol = eps * 100.; /* Computing 2nd power */ d__1 = tol; tol2 = d__1 * d__1; /* Check for deflation. */ L10: if (*n0 < *i0) { return 0; } if (*n0 == *i0) { goto L20; } nn = (*n0 << 2) + *pp; if (*n0 == *i0 + 1) { goto L40; } /* Check whether E(N0-1) is negligible, 1 eigenvalue. */ if (z__[nn - 5] > tol2 * (*sigma + z__[nn - 3]) && z__[nn - (*pp << 1) - 4] > tol2 * z__[nn - 7]) { goto L30; } L20: z__[(*n0 << 2) - 3] = z__[(*n0 << 2) + *pp - 3] + *sigma; --(*n0); goto L10; /* Check whether E(N0-2) is negligible, 2 eigenvalues. */ L30: if (z__[nn - 9] > tol2 * *sigma && z__[nn - (*pp << 1) - 8] > tol2 * z__[ nn - 11]) { goto L50; } L40: if (z__[nn - 3] > z__[nn - 7]) { s = z__[nn - 3]; z__[nn - 3] = z__[nn - 7]; z__[nn - 7] = s; } t = (z__[nn - 7] - z__[nn - 3] + z__[nn - 5]) * .5; if (z__[nn - 5] > z__[nn - 3] * tol2 && t != 0.) { s = z__[nn - 3] * (z__[nn - 5] / t); if (s <= t) { s = z__[nn - 3] * (z__[nn - 5] / (t * (sqrt(s / t + 1.) + 1.))); } else { s = z__[nn - 3] * (z__[nn - 5] / (t + sqrt(t) * sqrt(t + s))); } t = z__[nn - 7] + (s + z__[nn - 5]); z__[nn - 3] *= z__[nn - 7] / t; z__[nn - 7] = t; } z__[(*n0 << 2) - 7] = z__[nn - 7] + *sigma; z__[(*n0 << 2) - 3] = z__[nn - 3] + *sigma; *n0 += -2; goto L10; L50: if (*pp == 2) { *pp = 0; } /* Reverse the qd-array, if warranted. */ if (*dmin__ <= 0. || *n0 < n0in) { if (z__[(*i0 << 2) + *pp - 3] * 1.5 < z__[(*n0 << 2) + *pp - 3]) { ipn4 = *i0 + *n0 << 2; i__1 = *i0 + *n0 - 1 << 1; for (j4 = *i0 << 2; j4 <= i__1; j4 += 4) { temp = z__[j4 - 3]; z__[j4 - 3] = z__[ipn4 - j4 - 3]; z__[ipn4 - j4 - 3] = temp; temp = z__[j4 - 2]; z__[j4 - 2] = z__[ipn4 - j4 - 2]; z__[ipn4 - j4 - 2] = temp; temp = z__[j4 - 1]; z__[j4 - 1] = z__[ipn4 - j4 - 5]; z__[ipn4 - j4 - 5] = temp; temp = z__[j4]; z__[j4] = z__[ipn4 - j4 - 4]; z__[ipn4 - j4 - 4] = temp; /* L60: */ } if (*n0 - *i0 <= 4) { z__[(*n0 << 2) + *pp - 1] = z__[(*i0 << 2) + *pp - 1]; z__[(*n0 << 2) - *pp] = z__[(*i0 << 2) - *pp]; } /* Computing MIN */ d__1 = *dmin2, d__2 = z__[(*n0 << 2) + *pp - 1]; *dmin2 = min(d__1,d__2); /* Computing MIN */ d__1 = z__[(*n0 << 2) + *pp - 1], d__2 = z__[(*i0 << 2) + *pp - 1] , d__1 = min(d__1,d__2), d__2 = z__[(*i0 << 2) + *pp + 3]; z__[(*n0 << 2) + *pp - 1] = min(d__1,d__2); /* Computing MIN */ d__1 = z__[(*n0 << 2) - *pp], d__2 = z__[(*i0 << 2) - *pp], d__1 = min(d__1,d__2), d__2 = z__[(*i0 << 2) - *pp + 4]; z__[(*n0 << 2) - *pp] = min(d__1,d__2); /* Computing MAX */ d__1 = *qmax, d__2 = z__[(*i0 << 2) + *pp - 3], d__1 = max(d__1, d__2), d__2 = z__[(*i0 << 2) + *pp + 1]; *qmax = max(d__1,d__2); *dmin__ = -0.; } } /* Choose a shift. */ igraphdlasq4_(i0, n0, &z__[1], pp, &n0in, dmin__, dmin1, dmin2, dn, dn1, dn2, tau, ttype, g); /* Call dqds until DMIN > 0. */ L70: igraphdlasq5_(i0, n0, &z__[1], pp, tau, sigma, dmin__, dmin1, dmin2, dn, dn1, dn2, ieee, &eps); *ndiv += *n0 - *i0 + 2; ++(*iter); /* Check status. */ if (*dmin__ >= 0. && *dmin1 >= 0.) { /* Success. */ goto L90; } else if (*dmin__ < 0. && *dmin1 > 0. && z__[(*n0 - 1 << 2) - *pp] < tol * (*sigma + *dn1) && abs(*dn) < tol * *sigma) { /* Convergence hidden by negative DN. */ z__[(*n0 - 1 << 2) - *pp + 2] = 0.; *dmin__ = 0.; goto L90; } else if (*dmin__ < 0.) { /* TAU too big. Select new TAU and try again. */ ++(*nfail); if (*ttype < -22) { /* Failed twice. Play it safe. */ *tau = 0.; } else if (*dmin1 > 0.) { /* Late failure. Gives excellent shift. */ *tau = (*tau + *dmin__) * (1. - eps * 2.); *ttype += -11; } else { /* Early failure. Divide by 4. */ *tau *= .25; *ttype += -12; } goto L70; } else if (igraphdisnan_(dmin__)) { /* NaN. */ if (*tau == 0.) { goto L80; } else { *tau = 0.; goto L70; } } else { /* Possible underflow. Play it safe. */ goto L80; } /* Risk of underflow. */ L80: igraphdlasq6_(i0, n0, &z__[1], pp, dmin__, dmin1, dmin2, dn, dn1, dn2); *ndiv += *n0 - *i0 + 2; ++(*iter); *tau = 0.; L90: if (*tau < *sigma) { *desig += *tau; t = *sigma + *desig; *desig -= t - *sigma; } else { t = *sigma + *tau; *desig = *sigma - (t - *tau) + *desig; } *sigma = t; return 0; /* End of DLASQ3 */ } /* igraphdlasq3_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlartg.c0000644000076500000240000001414713524616145024270 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* > \brief \b DLARTG generates a plane rotation with real cosine and real sine. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLARTG + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLARTG( F, G, CS, SN, R ) DOUBLE PRECISION CS, F, G, R, SN > \par Purpose: ============= > > \verbatim > > DLARTG generate a plane rotation so that > > [ CS SN ] . [ F ] = [ R ] where CS**2 + SN**2 = 1. > [ -SN CS ] [ G ] [ 0 ] > > This is a slower, more accurate version of the BLAS1 routine DROTG, > with the following other differences: > F and G are unchanged on return. > If G=0, then CS=1 and SN=0. > If F=0 and (G .ne. 0), then CS=0 and SN=1 without doing any > floating point operations (saves work in DBDSQR when > there are zeros on the diagonal). > > If F exceeds G in magnitude, CS will be positive. > \endverbatim Arguments: ========== > \param[in] F > \verbatim > F is DOUBLE PRECISION > The first component of vector to be rotated. > \endverbatim > > \param[in] G > \verbatim > G is DOUBLE PRECISION > The second component of vector to be rotated. > \endverbatim > > \param[out] CS > \verbatim > CS is DOUBLE PRECISION > The cosine of the rotation. > \endverbatim > > \param[out] SN > \verbatim > SN is DOUBLE PRECISION > The sine of the rotation. > \endverbatim > > \param[out] R > \verbatim > R is DOUBLE PRECISION > The nonzero component of the rotated vector. > > This version has a few statements commented out for thread safety > (machine parameters are computed on each entry). 10 feb 03, SJH. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERauxiliary ===================================================================== Subroutine */ int igraphdlartg_(doublereal *f, doublereal *g, doublereal *cs, doublereal *sn, doublereal *r__) { /* System generated locals */ integer i__1; doublereal d__1, d__2; /* Builtin functions */ double log(doublereal), pow_di(doublereal *, integer *), sqrt(doublereal); /* Local variables */ integer i__; doublereal f1, g1, eps, scale; integer count; doublereal safmn2, safmx2; extern doublereal igraphdlamch_(char *); doublereal safmin; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== LOGICAL FIRST SAVE FIRST, SAFMX2, SAFMIN, SAFMN2 DATA FIRST / .TRUE. / IF( FIRST ) THEN */ safmin = igraphdlamch_("S"); eps = igraphdlamch_("E"); d__1 = igraphdlamch_("B"); i__1 = (integer) (log(safmin / eps) / log(igraphdlamch_("B")) / 2.); safmn2 = pow_di(&d__1, &i__1); safmx2 = 1. / safmn2; /* FIRST = .FALSE. END IF */ if (*g == 0.) { *cs = 1.; *sn = 0.; *r__ = *f; } else if (*f == 0.) { *cs = 0.; *sn = 1.; *r__ = *g; } else { f1 = *f; g1 = *g; /* Computing MAX */ d__1 = abs(f1), d__2 = abs(g1); scale = max(d__1,d__2); if (scale >= safmx2) { count = 0; L10: ++count; f1 *= safmn2; g1 *= safmn2; /* Computing MAX */ d__1 = abs(f1), d__2 = abs(g1); scale = max(d__1,d__2); if (scale >= safmx2) { goto L10; } /* Computing 2nd power */ d__1 = f1; /* Computing 2nd power */ d__2 = g1; *r__ = sqrt(d__1 * d__1 + d__2 * d__2); *cs = f1 / *r__; *sn = g1 / *r__; i__1 = count; for (i__ = 1; i__ <= i__1; ++i__) { *r__ *= safmx2; /* L20: */ } } else if (scale <= safmn2) { count = 0; L30: ++count; f1 *= safmx2; g1 *= safmx2; /* Computing MAX */ d__1 = abs(f1), d__2 = abs(g1); scale = max(d__1,d__2); if (scale <= safmn2) { goto L30; } /* Computing 2nd power */ d__1 = f1; /* Computing 2nd power */ d__2 = g1; *r__ = sqrt(d__1 * d__1 + d__2 * d__2); *cs = f1 / *r__; *sn = g1 / *r__; i__1 = count; for (i__ = 1; i__ <= i__1; ++i__) { *r__ *= safmn2; /* L40: */ } } else { /* Computing 2nd power */ d__1 = f1; /* Computing 2nd power */ d__2 = g1; *r__ = sqrt(d__1 * d__1 + d__2 * d__2); *cs = f1 / *r__; *sn = g1 / *r__; } if (abs(*f) > abs(*g) && *cs < 0.) { *cs = -(*cs); *sn = -(*sn); *r__ = -(*r__); } } return 0; /* End of DLARTG */ } /* igraphdlartg_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dtrsm.c0000644000076500000240000002761413524616145024147 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Subroutine */ int igraphdtrsm_(char *side, char *uplo, char *transa, char *diag, integer *m, integer *n, doublereal *alpha, doublereal *a, integer * lda, doublereal *b, integer *ldb) { /* System generated locals */ integer a_dim1, a_offset, b_dim1, b_offset, i__1, i__2, i__3; /* Local variables */ integer i__, j, k, info; doublereal temp; logical lside; extern logical igraphlsame_(char *, char *); integer nrowa; logical upper; extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); logical nounit; /* Purpose ======= DTRSM solves one of the matrix equations op( A )*X = alpha*B, or X*op( A ) = alpha*B, where alpha is a scalar, X and B are m by n matrices, A is a unit, or non-unit, upper or lower triangular matrix and op( A ) is one of op( A ) = A or op( A ) = A**T. The matrix X is overwritten on B. Arguments ========== SIDE - CHARACTER*1. On entry, SIDE specifies whether op( A ) appears on the left or right of X as follows: SIDE = 'L' or 'l' op( A )*X = alpha*B. SIDE = 'R' or 'r' X*op( A ) = alpha*B. Unchanged on exit. UPLO - CHARACTER*1. On entry, UPLO specifies whether the matrix A is an upper or lower triangular matrix as follows: UPLO = 'U' or 'u' A is an upper triangular matrix. UPLO = 'L' or 'l' A is a lower triangular matrix. Unchanged on exit. TRANSA - CHARACTER*1. On entry, TRANSA specifies the form of op( A ) to be used in the matrix multiplication as follows: TRANSA = 'N' or 'n' op( A ) = A. TRANSA = 'T' or 't' op( A ) = A**T. TRANSA = 'C' or 'c' op( A ) = A**T. Unchanged on exit. DIAG - CHARACTER*1. On entry, DIAG specifies whether or not A is unit triangular as follows: DIAG = 'U' or 'u' A is assumed to be unit triangular. DIAG = 'N' or 'n' A is not assumed to be unit triangular. Unchanged on exit. M - INTEGER. On entry, M specifies the number of rows of B. M must be at least zero. Unchanged on exit. N - INTEGER. On entry, N specifies the number of columns of B. N must be at least zero. Unchanged on exit. ALPHA - DOUBLE PRECISION. On entry, ALPHA specifies the scalar alpha. When alpha is zero then A is not referenced and B need not be set before entry. Unchanged on exit. A - DOUBLE PRECISION array of DIMENSION ( LDA, k ), where k is m when SIDE = 'L' or 'l' and is n when SIDE = 'R' or 'r'. Before entry with UPLO = 'U' or 'u', the leading k by k upper triangular part of the array A must contain the upper triangular matrix and the strictly lower triangular part of A is not referenced. Before entry with UPLO = 'L' or 'l', the leading k by k lower triangular part of the array A must contain the lower triangular matrix and the strictly upper triangular part of A is not referenced. Note that when DIAG = 'U' or 'u', the diagonal elements of A are not referenced either, but are assumed to be unity. Unchanged on exit. LDA - INTEGER. On entry, LDA specifies the first dimension of A as declared in the calling (sub) program. When SIDE = 'L' or 'l' then LDA must be at least max( 1, m ), when SIDE = 'R' or 'r' then LDA must be at least max( 1, n ). Unchanged on exit. B - DOUBLE PRECISION array of DIMENSION ( LDB, n ). Before entry, the leading m by n part of the array B must contain the right-hand side matrix B, and on exit is overwritten by the solution matrix X. LDB - INTEGER. On entry, LDB specifies the first dimension of B as declared in the calling (sub) program. LDB must be at least max( 1, m ). Unchanged on exit. Further Details =============== Level 3 Blas routine. -- Written on 8-February-1989. Jack Dongarra, Argonne National Laboratory. Iain Duff, AERE Harwell. Jeremy Du Croz, Numerical Algorithms Group Ltd. Sven Hammarling, Numerical Algorithms Group Ltd. ===================================================================== Test the input parameters. Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; b_dim1 = *ldb; b_offset = 1 + b_dim1; b -= b_offset; /* Function Body */ lside = igraphlsame_(side, "L"); if (lside) { nrowa = *m; } else { nrowa = *n; } nounit = igraphlsame_(diag, "N"); upper = igraphlsame_(uplo, "U"); info = 0; if (! lside && ! igraphlsame_(side, "R")) { info = 1; } else if (! upper && ! igraphlsame_(uplo, "L")) { info = 2; } else if (! igraphlsame_(transa, "N") && ! igraphlsame_(transa, "T") && ! igraphlsame_(transa, "C")) { info = 3; } else if (! igraphlsame_(diag, "U") && ! igraphlsame_(diag, "N")) { info = 4; } else if (*m < 0) { info = 5; } else if (*n < 0) { info = 6; } else if (*lda < max(1,nrowa)) { info = 9; } else if (*ldb < max(1,*m)) { info = 11; } if (info != 0) { igraphxerbla_("DTRSM ", &info, (ftnlen)6); return 0; } /* Quick return if possible. */ if (*m == 0 || *n == 0) { return 0; } /* And when alpha.eq.zero. */ if (*alpha == 0.) { i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { b[i__ + j * b_dim1] = 0.; /* L10: */ } /* L20: */ } return 0; } /* Start the operations. */ if (lside) { if (igraphlsame_(transa, "N")) { /* Form B := alpha*inv( A )*B. */ if (upper) { i__1 = *n; for (j = 1; j <= i__1; ++j) { if (*alpha != 1.) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { b[i__ + j * b_dim1] = *alpha * b[i__ + j * b_dim1] ; /* L30: */ } } for (k = *m; k >= 1; --k) { if (b[k + j * b_dim1] != 0.) { if (nounit) { b[k + j * b_dim1] /= a[k + k * a_dim1]; } i__2 = k - 1; for (i__ = 1; i__ <= i__2; ++i__) { b[i__ + j * b_dim1] -= b[k + j * b_dim1] * a[ i__ + k * a_dim1]; /* L40: */ } } /* L50: */ } /* L60: */ } } else { i__1 = *n; for (j = 1; j <= i__1; ++j) { if (*alpha != 1.) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { b[i__ + j * b_dim1] = *alpha * b[i__ + j * b_dim1] ; /* L70: */ } } i__2 = *m; for (k = 1; k <= i__2; ++k) { if (b[k + j * b_dim1] != 0.) { if (nounit) { b[k + j * b_dim1] /= a[k + k * a_dim1]; } i__3 = *m; for (i__ = k + 1; i__ <= i__3; ++i__) { b[i__ + j * b_dim1] -= b[k + j * b_dim1] * a[ i__ + k * a_dim1]; /* L80: */ } } /* L90: */ } /* L100: */ } } } else { /* Form B := alpha*inv( A**T )*B. */ if (upper) { i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { temp = *alpha * b[i__ + j * b_dim1]; i__3 = i__ - 1; for (k = 1; k <= i__3; ++k) { temp -= a[k + i__ * a_dim1] * b[k + j * b_dim1]; /* L110: */ } if (nounit) { temp /= a[i__ + i__ * a_dim1]; } b[i__ + j * b_dim1] = temp; /* L120: */ } /* L130: */ } } else { i__1 = *n; for (j = 1; j <= i__1; ++j) { for (i__ = *m; i__ >= 1; --i__) { temp = *alpha * b[i__ + j * b_dim1]; i__2 = *m; for (k = i__ + 1; k <= i__2; ++k) { temp -= a[k + i__ * a_dim1] * b[k + j * b_dim1]; /* L140: */ } if (nounit) { temp /= a[i__ + i__ * a_dim1]; } b[i__ + j * b_dim1] = temp; /* L150: */ } /* L160: */ } } } } else { if (igraphlsame_(transa, "N")) { /* Form B := alpha*B*inv( A ). */ if (upper) { i__1 = *n; for (j = 1; j <= i__1; ++j) { if (*alpha != 1.) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { b[i__ + j * b_dim1] = *alpha * b[i__ + j * b_dim1] ; /* L170: */ } } i__2 = j - 1; for (k = 1; k <= i__2; ++k) { if (a[k + j * a_dim1] != 0.) { i__3 = *m; for (i__ = 1; i__ <= i__3; ++i__) { b[i__ + j * b_dim1] -= a[k + j * a_dim1] * b[ i__ + k * b_dim1]; /* L180: */ } } /* L190: */ } if (nounit) { temp = 1. / a[j + j * a_dim1]; i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { b[i__ + j * b_dim1] = temp * b[i__ + j * b_dim1]; /* L200: */ } } /* L210: */ } } else { for (j = *n; j >= 1; --j) { if (*alpha != 1.) { i__1 = *m; for (i__ = 1; i__ <= i__1; ++i__) { b[i__ + j * b_dim1] = *alpha * b[i__ + j * b_dim1] ; /* L220: */ } } i__1 = *n; for (k = j + 1; k <= i__1; ++k) { if (a[k + j * a_dim1] != 0.) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { b[i__ + j * b_dim1] -= a[k + j * a_dim1] * b[ i__ + k * b_dim1]; /* L230: */ } } /* L240: */ } if (nounit) { temp = 1. / a[j + j * a_dim1]; i__1 = *m; for (i__ = 1; i__ <= i__1; ++i__) { b[i__ + j * b_dim1] = temp * b[i__ + j * b_dim1]; /* L250: */ } } /* L260: */ } } } else { /* Form B := alpha*B*inv( A**T ). */ if (upper) { for (k = *n; k >= 1; --k) { if (nounit) { temp = 1. / a[k + k * a_dim1]; i__1 = *m; for (i__ = 1; i__ <= i__1; ++i__) { b[i__ + k * b_dim1] = temp * b[i__ + k * b_dim1]; /* L270: */ } } i__1 = k - 1; for (j = 1; j <= i__1; ++j) { if (a[j + k * a_dim1] != 0.) { temp = a[j + k * a_dim1]; i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { b[i__ + j * b_dim1] -= temp * b[i__ + k * b_dim1]; /* L280: */ } } /* L290: */ } if (*alpha != 1.) { i__1 = *m; for (i__ = 1; i__ <= i__1; ++i__) { b[i__ + k * b_dim1] = *alpha * b[i__ + k * b_dim1] ; /* L300: */ } } /* L310: */ } } else { i__1 = *n; for (k = 1; k <= i__1; ++k) { if (nounit) { temp = 1. / a[k + k * a_dim1]; i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { b[i__ + k * b_dim1] = temp * b[i__ + k * b_dim1]; /* L320: */ } } i__2 = *n; for (j = k + 1; j <= i__2; ++j) { if (a[j + k * a_dim1] != 0.) { temp = a[j + k * a_dim1]; i__3 = *m; for (i__ = 1; i__ <= i__3; ++i__) { b[i__ + j * b_dim1] -= temp * b[i__ + k * b_dim1]; /* L330: */ } } /* L340: */ } if (*alpha != 1.) { i__2 = *m; for (i__ = 1; i__ <= i__2; ++i__) { b[i__ + k * b_dim1] = *alpha * b[i__ + k * b_dim1] ; /* L350: */ } } /* L360: */ } } } } return 0; /* End of DTRSM . */ } /* igraphdtrsm_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dlarrf.c0000644000076500000240000004001113524616145024252 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; /* > \brief \b DLARRF finds a new relatively robust representation such that at least one of the eigenvalues i s relatively isolated. =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DLARRF + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DLARRF( N, D, L, LD, CLSTRT, CLEND, W, WGAP, WERR, SPDIAM, CLGAPL, CLGAPR, PIVMIN, SIGMA, DPLUS, LPLUS, WORK, INFO ) INTEGER CLSTRT, CLEND, INFO, N DOUBLE PRECISION CLGAPL, CLGAPR, PIVMIN, SIGMA, SPDIAM DOUBLE PRECISION D( * ), DPLUS( * ), L( * ), LD( * ), $ LPLUS( * ), W( * ), WGAP( * ), WERR( * ), WORK( * ) > \par Purpose: ============= > > \verbatim > > Given the initial representation L D L^T and its cluster of close > eigenvalues (in a relative measure), W( CLSTRT ), W( CLSTRT+1 ), ... > W( CLEND ), DLARRF finds a new relatively robust representation > L D L^T - SIGMA I = L(+) D(+) L(+)^T such that at least one of the > eigenvalues of L(+) D(+) L(+)^T is relatively isolated. > \endverbatim Arguments: ========== > \param[in] N > \verbatim > N is INTEGER > The order of the matrix (subblock, if the matrix splitted). > \endverbatim > > \param[in] D > \verbatim > D is DOUBLE PRECISION array, dimension (N) > The N diagonal elements of the diagonal matrix D. > \endverbatim > > \param[in] L > \verbatim > L is DOUBLE PRECISION array, dimension (N-1) > The (N-1) subdiagonal elements of the unit bidiagonal > matrix L. > \endverbatim > > \param[in] LD > \verbatim > LD is DOUBLE PRECISION array, dimension (N-1) > The (N-1) elements L(i)*D(i). > \endverbatim > > \param[in] CLSTRT > \verbatim > CLSTRT is INTEGER > The index of the first eigenvalue in the cluster. > \endverbatim > > \param[in] CLEND > \verbatim > CLEND is INTEGER > The index of the last eigenvalue in the cluster. > \endverbatim > > \param[in] W > \verbatim > W is DOUBLE PRECISION array, dimension > dimension is >= (CLEND-CLSTRT+1) > The eigenvalue APPROXIMATIONS of L D L^T in ascending order. > W( CLSTRT ) through W( CLEND ) form the cluster of relatively > close eigenalues. > \endverbatim > > \param[in,out] WGAP > \verbatim > WGAP is DOUBLE PRECISION array, dimension > dimension is >= (CLEND-CLSTRT+1) > The separation from the right neighbor eigenvalue in W. > \endverbatim > > \param[in] WERR > \verbatim > WERR is DOUBLE PRECISION array, dimension > dimension is >= (CLEND-CLSTRT+1) > WERR contain the semiwidth of the uncertainty > interval of the corresponding eigenvalue APPROXIMATION in W > \endverbatim > > \param[in] SPDIAM > \verbatim > SPDIAM is DOUBLE PRECISION > estimate of the spectral diameter obtained from the > Gerschgorin intervals > \endverbatim > > \param[in] CLGAPL > \verbatim > CLGAPL is DOUBLE PRECISION > \endverbatim > > \param[in] CLGAPR > \verbatim > CLGAPR is DOUBLE PRECISION > absolute gap on each end of the cluster. > Set by the calling routine to protect against shifts too close > to eigenvalues outside the cluster. > \endverbatim > > \param[in] PIVMIN > \verbatim > PIVMIN is DOUBLE PRECISION > The minimum pivot allowed in the Sturm sequence. > \endverbatim > > \param[out] SIGMA > \verbatim > SIGMA is DOUBLE PRECISION > The shift used to form L(+) D(+) L(+)^T. > \endverbatim > > \param[out] DPLUS > \verbatim > DPLUS is DOUBLE PRECISION array, dimension (N) > The N diagonal elements of the diagonal matrix D(+). > \endverbatim > > \param[out] LPLUS > \verbatim > LPLUS is DOUBLE PRECISION array, dimension (N-1) > The first (N-1) elements of LPLUS contain the subdiagonal > elements of the unit bidiagonal matrix L(+). > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (2*N) > Workspace. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > Signals processing OK (=0) or failure (=1) > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup auxOTHERauxiliary > \par Contributors: ================== > > Beresford Parlett, University of California, Berkeley, USA \n > Jim Demmel, University of California, Berkeley, USA \n > Inderjit Dhillon, University of Texas, Austin, USA \n > Osni Marques, LBNL/NERSC, USA \n > Christof Voemel, University of California, Berkeley, USA ===================================================================== Subroutine */ int igraphdlarrf_(integer *n, doublereal *d__, doublereal *l, doublereal *ld, integer *clstrt, integer *clend, doublereal *w, doublereal *wgap, doublereal *werr, doublereal *spdiam, doublereal * clgapl, doublereal *clgapr, doublereal *pivmin, doublereal *sigma, doublereal *dplus, doublereal *lplus, doublereal *work, integer *info) { /* System generated locals */ integer i__1; doublereal d__1, d__2, d__3; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ integer i__; doublereal s, bestshift, smlgrowth, eps, tmp, max1, max2, rrr1, rrr2, znm2, growthbound, fail, fact, oldp; integer indx; doublereal prod; integer ktry; doublereal fail2, avgap, ldmax, rdmax; integer shift; extern /* Subroutine */ int igraphdcopy_(integer *, doublereal *, integer *, doublereal *, integer *); logical dorrr1; extern doublereal igraphdlamch_(char *); doublereal ldelta; logical nofail; doublereal mingap, lsigma, rdelta; extern logical igraphdisnan_(doublereal *); logical forcer; doublereal rsigma, clwdth; logical sawnan1, sawnan2, tryrrr1; /* -- LAPACK auxiliary routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Parameter adjustments */ --work; --lplus; --dplus; --werr; --wgap; --w; --ld; --l; --d__; /* Function Body */ *info = 0; fact = 2.; eps = igraphdlamch_("Precision"); shift = 0; forcer = FALSE_; /* Note that we cannot guarantee that for any of the shifts tried, the factorization has a small or even moderate element growth. There could be Ritz values at both ends of the cluster and despite backing off, there are examples where all factorizations tried (in IEEE mode, allowing zero pivots & infinities) have INFINITE element growth. For this reason, we should use PIVMIN in this subroutine so that at least the L D L^T factorization exists. It can be checked afterwards whether the element growth caused bad residuals/orthogonality. Decide whether the code should accept the best among all representations despite large element growth or signal INFO=1 */ nofail = TRUE_; /* Compute the average gap length of the cluster */ clwdth = (d__1 = w[*clend] - w[*clstrt], abs(d__1)) + werr[*clend] + werr[ *clstrt]; avgap = clwdth / (doublereal) (*clend - *clstrt); mingap = min(*clgapl,*clgapr); /* Initial values for shifts to both ends of cluster Computing MIN */ d__1 = w[*clstrt], d__2 = w[*clend]; lsigma = min(d__1,d__2) - werr[*clstrt]; /* Computing MAX */ d__1 = w[*clstrt], d__2 = w[*clend]; rsigma = max(d__1,d__2) + werr[*clend]; /* Use a small fudge to make sure that we really shift to the outside */ lsigma -= abs(lsigma) * 4. * eps; rsigma += abs(rsigma) * 4. * eps; /* Compute upper bounds for how much to back off the initial shifts */ ldmax = mingap * .25 + *pivmin * 2.; rdmax = mingap * .25 + *pivmin * 2.; /* Computing MAX */ d__1 = avgap, d__2 = wgap[*clstrt]; ldelta = max(d__1,d__2) / fact; /* Computing MAX */ d__1 = avgap, d__2 = wgap[*clend - 1]; rdelta = max(d__1,d__2) / fact; /* Initialize the record of the best representation found */ s = igraphdlamch_("S"); smlgrowth = 1. / s; fail = (doublereal) (*n - 1) * mingap / (*spdiam * eps); fail2 = (doublereal) (*n - 1) * mingap / (*spdiam * sqrt(eps)); bestshift = lsigma; /* while (KTRY <= KTRYMAX) */ ktry = 0; growthbound = *spdiam * 8.; L5: sawnan1 = FALSE_; sawnan2 = FALSE_; /* Ensure that we do not back off too much of the initial shifts */ ldelta = min(ldmax,ldelta); rdelta = min(rdmax,rdelta); /* Compute the element growth when shifting to both ends of the cluster accept the shift if there is no element growth at one of the two ends Left end */ s = -lsigma; dplus[1] = d__[1] + s; if (abs(dplus[1]) < *pivmin) { dplus[1] = -(*pivmin); /* Need to set SAWNAN1 because refined RRR test should not be used in this case */ sawnan1 = TRUE_; } max1 = abs(dplus[1]); i__1 = *n - 1; for (i__ = 1; i__ <= i__1; ++i__) { lplus[i__] = ld[i__] / dplus[i__]; s = s * lplus[i__] * l[i__] - lsigma; dplus[i__ + 1] = d__[i__ + 1] + s; if ((d__1 = dplus[i__ + 1], abs(d__1)) < *pivmin) { dplus[i__ + 1] = -(*pivmin); /* Need to set SAWNAN1 because refined RRR test should not be used in this case */ sawnan1 = TRUE_; } /* Computing MAX */ d__2 = max1, d__3 = (d__1 = dplus[i__ + 1], abs(d__1)); max1 = max(d__2,d__3); /* L6: */ } sawnan1 = sawnan1 || igraphdisnan_(&max1); if (forcer || max1 <= growthbound && ! sawnan1) { *sigma = lsigma; shift = 1; goto L100; } /* Right end */ s = -rsigma; work[1] = d__[1] + s; if (abs(work[1]) < *pivmin) { work[1] = -(*pivmin); /* Need to set SAWNAN2 because refined RRR test should not be used in this case */ sawnan2 = TRUE_; } max2 = abs(work[1]); i__1 = *n - 1; for (i__ = 1; i__ <= i__1; ++i__) { work[*n + i__] = ld[i__] / work[i__]; s = s * work[*n + i__] * l[i__] - rsigma; work[i__ + 1] = d__[i__ + 1] + s; if ((d__1 = work[i__ + 1], abs(d__1)) < *pivmin) { work[i__ + 1] = -(*pivmin); /* Need to set SAWNAN2 because refined RRR test should not be used in this case */ sawnan2 = TRUE_; } /* Computing MAX */ d__2 = max2, d__3 = (d__1 = work[i__ + 1], abs(d__1)); max2 = max(d__2,d__3); /* L7: */ } sawnan2 = sawnan2 || igraphdisnan_(&max2); if (forcer || max2 <= growthbound && ! sawnan2) { *sigma = rsigma; shift = 2; goto L100; } /* If we are at this point, both shifts led to too much element growth Record the better of the two shifts (provided it didn't lead to NaN) */ if (sawnan1 && sawnan2) { /* both MAX1 and MAX2 are NaN */ goto L50; } else { if (! sawnan1) { indx = 1; if (max1 <= smlgrowth) { smlgrowth = max1; bestshift = lsigma; } } if (! sawnan2) { if (sawnan1 || max2 <= max1) { indx = 2; } if (max2 <= smlgrowth) { smlgrowth = max2; bestshift = rsigma; } } } /* If we are here, both the left and the right shift led to element growth. If the element growth is moderate, then we may still accept the representation, if it passes a refined test for RRR. This test supposes that no NaN occurred. Moreover, we use the refined RRR test only for isolated clusters. */ if (clwdth < mingap / 128. && min(max1,max2) < fail2 && ! sawnan1 && ! sawnan2) { dorrr1 = TRUE_; } else { dorrr1 = FALSE_; } tryrrr1 = TRUE_; if (tryrrr1 && dorrr1) { if (indx == 1) { tmp = (d__1 = dplus[*n], abs(d__1)); znm2 = 1.; prod = 1.; oldp = 1.; for (i__ = *n - 1; i__ >= 1; --i__) { if (prod <= eps) { prod = dplus[i__ + 1] * work[*n + i__ + 1] / (dplus[i__] * work[*n + i__]) * oldp; } else { prod *= (d__1 = work[*n + i__], abs(d__1)); } oldp = prod; /* Computing 2nd power */ d__1 = prod; znm2 += d__1 * d__1; /* Computing MAX */ d__2 = tmp, d__3 = (d__1 = dplus[i__] * prod, abs(d__1)); tmp = max(d__2,d__3); /* L15: */ } rrr1 = tmp / (*spdiam * sqrt(znm2)); if (rrr1 <= 8.) { *sigma = lsigma; shift = 1; goto L100; } } else if (indx == 2) { tmp = (d__1 = work[*n], abs(d__1)); znm2 = 1.; prod = 1.; oldp = 1.; for (i__ = *n - 1; i__ >= 1; --i__) { if (prod <= eps) { prod = work[i__ + 1] * lplus[i__ + 1] / (work[i__] * lplus[i__]) * oldp; } else { prod *= (d__1 = lplus[i__], abs(d__1)); } oldp = prod; /* Computing 2nd power */ d__1 = prod; znm2 += d__1 * d__1; /* Computing MAX */ d__2 = tmp, d__3 = (d__1 = work[i__] * prod, abs(d__1)); tmp = max(d__2,d__3); /* L16: */ } rrr2 = tmp / (*spdiam * sqrt(znm2)); if (rrr2 <= 8.) { *sigma = rsigma; shift = 2; goto L100; } } } L50: if (ktry < 1) { /* If we are here, both shifts failed also the RRR test. Back off to the outside Computing MAX */ d__1 = lsigma - ldelta, d__2 = lsigma - ldmax; lsigma = max(d__1,d__2); /* Computing MIN */ d__1 = rsigma + rdelta, d__2 = rsigma + rdmax; rsigma = min(d__1,d__2); ldelta *= 2.; rdelta *= 2.; ++ktry; goto L5; } else { /* None of the representations investigated satisfied our criteria. Take the best one we found. */ if (smlgrowth < fail || nofail) { lsigma = bestshift; rsigma = bestshift; forcer = TRUE_; goto L5; } else { *info = 1; return 0; } } L100: if (shift == 1) { } else if (shift == 2) { /* store new L and D back into DPLUS, LPLUS */ igraphdcopy_(n, &work[1], &c__1, &dplus[1], &c__1); i__1 = *n - 1; igraphdcopy_(&i__1, &work[*n + 1], &c__1, &lplus[1], &c__1); } return 0; /* End of DLARRF */ } /* igraphdlarrf_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dorm2r.c0000644000076500000240000002034613524616145024216 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static integer c__1 = 1; /* > \brief \b DORM2R multiplies a general matrix by the orthogonal matrix from a QR factorization determined by sgeqrf (unblocked algorithm). =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DORM2R + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DORM2R( SIDE, TRANS, M, N, K, A, LDA, TAU, C, LDC, WORK, INFO ) CHARACTER SIDE, TRANS INTEGER INFO, K, LDA, LDC, M, N DOUBLE PRECISION A( LDA, * ), C( LDC, * ), TAU( * ), WORK( * ) > \par Purpose: ============= > > \verbatim > > DORM2R overwrites the general real m by n matrix C with > > Q * C if SIDE = 'L' and TRANS = 'N', or > > Q**T* C if SIDE = 'L' and TRANS = 'T', or > > C * Q if SIDE = 'R' and TRANS = 'N', or > > C * Q**T if SIDE = 'R' and TRANS = 'T', > > where Q is a real orthogonal matrix defined as the product of k > elementary reflectors > > Q = H(1) H(2) . . . H(k) > > as returned by DGEQRF. Q is of order m if SIDE = 'L' and of order n > if SIDE = 'R'. > \endverbatim Arguments: ========== > \param[in] SIDE > \verbatim > SIDE is CHARACTER*1 > = 'L': apply Q or Q**T from the Left > = 'R': apply Q or Q**T from the Right > \endverbatim > > \param[in] TRANS > \verbatim > TRANS is CHARACTER*1 > = 'N': apply Q (No transpose) > = 'T': apply Q**T (Transpose) > \endverbatim > > \param[in] M > \verbatim > M is INTEGER > The number of rows of the matrix C. M >= 0. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The number of columns of the matrix C. N >= 0. > \endverbatim > > \param[in] K > \verbatim > K is INTEGER > The number of elementary reflectors whose product defines > the matrix Q. > If SIDE = 'L', M >= K >= 0; > if SIDE = 'R', N >= K >= 0. > \endverbatim > > \param[in] A > \verbatim > A is DOUBLE PRECISION array, dimension (LDA,K) > The i-th column must contain the vector which defines the > elementary reflector H(i), for i = 1,2,...,k, as returned by > DGEQRF in the first k columns of its array argument A. > A is modified by the routine but restored on exit. > \endverbatim > > \param[in] LDA > \verbatim > LDA is INTEGER > The leading dimension of the array A. > If SIDE = 'L', LDA >= max(1,M); > if SIDE = 'R', LDA >= max(1,N). > \endverbatim > > \param[in] TAU > \verbatim > TAU is DOUBLE PRECISION array, dimension (K) > TAU(i) must contain the scalar factor of the elementary > reflector H(i), as returned by DGEQRF. > \endverbatim > > \param[in,out] C > \verbatim > C is DOUBLE PRECISION array, dimension (LDC,N) > On entry, the m by n matrix C. > On exit, C is overwritten by Q*C or Q**T*C or C*Q**T or C*Q. > \endverbatim > > \param[in] LDC > \verbatim > LDC is INTEGER > The leading dimension of the array C. LDC >= max(1,M). > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension > (N) if SIDE = 'L', > (M) if SIDE = 'R' > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > < 0: if INFO = -i, the i-th argument had an illegal value > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date September 2012 > \ingroup doubleOTHERcomputational ===================================================================== Subroutine */ int igraphdorm2r_(char *side, char *trans, integer *m, integer *n, integer *k, doublereal *a, integer *lda, doublereal *tau, doublereal * c__, integer *ldc, doublereal *work, integer *info) { /* System generated locals */ integer a_dim1, a_offset, c_dim1, c_offset, i__1, i__2; /* Local variables */ integer i__, i1, i2, i3, ic, jc, mi, ni, nq; doublereal aii; logical left; extern /* Subroutine */ int igraphdlarf_(char *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, doublereal *); extern logical igraphlsame_(char *, char *); extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); logical notran; /* -- LAPACK computational routine (version 3.4.2) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- September 2012 ===================================================================== Test the input arguments Parameter adjustments */ a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; --tau; c_dim1 = *ldc; c_offset = 1 + c_dim1; c__ -= c_offset; --work; /* Function Body */ *info = 0; left = igraphlsame_(side, "L"); notran = igraphlsame_(trans, "N"); /* NQ is the order of Q */ if (left) { nq = *m; } else { nq = *n; } if (! left && ! igraphlsame_(side, "R")) { *info = -1; } else if (! notran && ! igraphlsame_(trans, "T")) { *info = -2; } else if (*m < 0) { *info = -3; } else if (*n < 0) { *info = -4; } else if (*k < 0 || *k > nq) { *info = -5; } else if (*lda < max(1,nq)) { *info = -7; } else if (*ldc < max(1,*m)) { *info = -10; } if (*info != 0) { i__1 = -(*info); igraphxerbla_("DORM2R", &i__1, (ftnlen)6); return 0; } /* Quick return if possible */ if (*m == 0 || *n == 0 || *k == 0) { return 0; } if (left && ! notran || ! left && notran) { i1 = 1; i2 = *k; i3 = 1; } else { i1 = *k; i2 = 1; i3 = -1; } if (left) { ni = *n; jc = 1; } else { mi = *m; ic = 1; } i__1 = i2; i__2 = i3; for (i__ = i1; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ += i__2) { if (left) { /* H(i) is applied to C(i:m,1:n) */ mi = *m - i__ + 1; ic = i__; } else { /* H(i) is applied to C(1:m,i:n) */ ni = *n - i__ + 1; jc = i__; } /* Apply H(i) */ aii = a[i__ + i__ * a_dim1]; a[i__ + i__ * a_dim1] = 1.; igraphdlarf_(side, &mi, &ni, &a[i__ + i__ * a_dim1], &c__1, &tau[i__], &c__[ ic + jc * c_dim1], ldc, &work[1]); a[i__ + i__ * a_dim1] = aii; /* L10: */ } return 0; /* End of DORM2R */ } /* igraphdorm2r_ */ python-igraph-0.8.0/vendor/source/igraph/src/lapack/dhseqr.c0000644000076500000240000005204013524616145024273 0ustar tamasstaff00000000000000/* -- translated by f2c (version 20100827). You must link the resulting object file with libf2c: on Microsoft Windows system, link with libf2c.lib; on Linux or Unix systems, link with .../path/to/libf2c.a -lm or, if you install libf2c.a in a standard place, with -lf2c -lm -- in that order, at the end of the command line, as in cc *.o -lf2c -lm Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., http://www.netlib.org/f2c/libf2c.zip */ #include "f2c.h" /* Table of constant values */ static doublereal c_b11 = 0.; static doublereal c_b12 = 1.; static integer c__12 = 12; static integer c__2 = 2; static integer c__49 = 49; /* > \brief \b DHSEQR =========== DOCUMENTATION =========== Online html documentation available at http://www.netlib.org/lapack/explore-html/ > \htmlonly > Download DHSEQR + dependencies > > [TGZ] > > [ZIP] > > [TXT] > \endhtmlonly Definition: =========== SUBROUTINE DHSEQR( JOB, COMPZ, N, ILO, IHI, H, LDH, WR, WI, Z, LDZ, WORK, LWORK, INFO ) INTEGER IHI, ILO, INFO, LDH, LDZ, LWORK, N CHARACTER COMPZ, JOB DOUBLE PRECISION H( LDH, * ), WI( * ), WORK( * ), WR( * ), $ Z( LDZ, * ) > \par Purpose: ============= > > \verbatim > > DHSEQR computes the eigenvalues of a Hessenberg matrix H > and, optionally, the matrices T and Z from the Schur decomposition > H = Z T Z**T, where T is an upper quasi-triangular matrix (the > Schur form), and Z is the orthogonal matrix of Schur vectors. > > Optionally Z may be postmultiplied into an input orthogonal > matrix Q so that this routine can give the Schur factorization > of a matrix A which has been reduced to the Hessenberg form H > by the orthogonal matrix Q: A = Q*H*Q**T = (QZ)*T*(QZ)**T. > \endverbatim Arguments: ========== > \param[in] JOB > \verbatim > JOB is CHARACTER*1 > = 'E': compute eigenvalues only; > = 'S': compute eigenvalues and the Schur form T. > \endverbatim > > \param[in] COMPZ > \verbatim > COMPZ is CHARACTER*1 > = 'N': no Schur vectors are computed; > = 'I': Z is initialized to the unit matrix and the matrix Z > of Schur vectors of H is returned; > = 'V': Z must contain an orthogonal matrix Q on entry, and > the product Q*Z is returned. > \endverbatim > > \param[in] N > \verbatim > N is INTEGER > The order of the matrix H. N .GE. 0. > \endverbatim > > \param[in] ILO > \verbatim > ILO is INTEGER > \endverbatim > > \param[in] IHI > \verbatim > IHI is INTEGER > > It is assumed that H is already upper triangular in rows > and columns 1:ILO-1 and IHI+1:N. ILO and IHI are normally > set by a previous call to DGEBAL, and then passed to ZGEHRD > when the matrix output by DGEBAL is reduced to Hessenberg > form. Otherwise ILO and IHI should be set to 1 and N > respectively. If N.GT.0, then 1.LE.ILO.LE.IHI.LE.N. > If N = 0, then ILO = 1 and IHI = 0. > \endverbatim > > \param[in,out] H > \verbatim > H is DOUBLE PRECISION array, dimension (LDH,N) > On entry, the upper Hessenberg matrix H. > On exit, if INFO = 0 and JOB = 'S', then H contains the > upper quasi-triangular matrix T from the Schur decomposition > (the Schur form); 2-by-2 diagonal blocks (corresponding to > complex conjugate pairs of eigenvalues) are returned in > standard form, with H(i,i) = H(i+1,i+1) and > H(i+1,i)*H(i,i+1).LT.0. If INFO = 0 and JOB = 'E', the > contents of H are unspecified on exit. (The output value of > H when INFO.GT.0 is given under the description of INFO > below.) > > Unlike earlier versions of DHSEQR, this subroutine may > explicitly H(i,j) = 0 for i.GT.j and j = 1, 2, ... ILO-1 > or j = IHI+1, IHI+2, ... N. > \endverbatim > > \param[in] LDH > \verbatim > LDH is INTEGER > The leading dimension of the array H. LDH .GE. max(1,N). > \endverbatim > > \param[out] WR > \verbatim > WR is DOUBLE PRECISION array, dimension (N) > \endverbatim > > \param[out] WI > \verbatim > WI is DOUBLE PRECISION array, dimension (N) > > The real and imaginary parts, respectively, of the computed > eigenvalues. If two eigenvalues are computed as a complex > conjugate pair, they are stored in consecutive elements of > WR and WI, say the i-th and (i+1)th, with WI(i) .GT. 0 and > WI(i+1) .LT. 0. If JOB = 'S', the eigenvalues are stored in > the same order as on the diagonal of the Schur form returned > in H, with WR(i) = H(i,i) and, if H(i:i+1,i:i+1) is a 2-by-2 > diagonal block, WI(i) = sqrt(-H(i+1,i)*H(i,i+1)) and > WI(i+1) = -WI(i). > \endverbatim > > \param[in,out] Z > \verbatim > Z is DOUBLE PRECISION array, dimension (LDZ,N) > If COMPZ = 'N', Z is not referenced. > If COMPZ = 'I', on entry Z need not be set and on exit, > if INFO = 0, Z contains the orthogonal matrix Z of the Schur > vectors of H. If COMPZ = 'V', on entry Z must contain an > N-by-N matrix Q, which is assumed to be equal to the unit > matrix except for the submatrix Z(ILO:IHI,ILO:IHI). On exit, > if INFO = 0, Z contains Q*Z. > Normally Q is the orthogonal matrix generated by DORGHR > after the call to DGEHRD which formed the Hessenberg matrix > H. (The output value of Z when INFO.GT.0 is given under > the description of INFO below.) > \endverbatim > > \param[in] LDZ > \verbatim > LDZ is INTEGER > The leading dimension of the array Z. if COMPZ = 'I' or > COMPZ = 'V', then LDZ.GE.MAX(1,N). Otherwize, LDZ.GE.1. > \endverbatim > > \param[out] WORK > \verbatim > WORK is DOUBLE PRECISION array, dimension (LWORK) > On exit, if INFO = 0, WORK(1) returns an estimate of > the optimal value for LWORK. > \endverbatim > > \param[in] LWORK > \verbatim > LWORK is INTEGER > The dimension of the array WORK. LWORK .GE. max(1,N) > is sufficient and delivers very good and sometimes > optimal performance. However, LWORK as large as 11*N > may be required for optimal performance. A workspace > query is recommended to determine the optimal workspace > size. > > If LWORK = -1, then DHSEQR does a workspace query. > In this case, DHSEQR checks the input parameters and > estimates the optimal workspace size for the given > values of N, ILO and IHI. The estimate is returned > in WORK(1). No error message related to LWORK is > issued by XERBLA. Neither H nor Z are accessed. > \endverbatim > > \param[out] INFO > \verbatim > INFO is INTEGER > = 0: successful exit > .LT. 0: if INFO = -i, the i-th argument had an illegal > value > .GT. 0: if INFO = i, DHSEQR failed to compute all of > the eigenvalues. Elements 1:ilo-1 and i+1:n of WR > and WI contain those eigenvalues which have been > successfully computed. (Failures are rare.) > > If INFO .GT. 0 and JOB = 'E', then on exit, the > remaining unconverged eigenvalues are the eigen- > values of the upper Hessenberg matrix rows and > columns ILO through INFO of the final, output > value of H. > > If INFO .GT. 0 and JOB = 'S', then on exit > > (*) (initial value of H)*U = U*(final value of H) > > where U is an orthogonal matrix. The final > value of H is upper Hessenberg and quasi-triangular > in rows and columns INFO+1 through IHI. > > If INFO .GT. 0 and COMPZ = 'V', then on exit > > (final value of Z) = (initial value of Z)*U > > where U is the orthogonal matrix in (*) (regard- > less of the value of JOB.) > > If INFO .GT. 0 and COMPZ = 'I', then on exit > (final value of Z) = U > where U is the orthogonal matrix in (*) (regard- > less of the value of JOB.) > > If INFO .GT. 0 and COMPZ = 'N', then Z is not > accessed. > \endverbatim Authors: ======== > \author Univ. of Tennessee > \author Univ. of California Berkeley > \author Univ. of Colorado Denver > \author NAG Ltd. > \date November 2011 > \ingroup doubleOTHERcomputational > \par Contributors: ================== > > Karen Braman and Ralph Byers, Department of Mathematics, > University of Kansas, USA > \par Further Details: ===================== > > \verbatim > > Default values supplied by > ILAENV(ISPEC,'DHSEQR',JOB(:1)//COMPZ(:1),N,ILO,IHI,LWORK). > It is suggested that these defaults be adjusted in order > to attain best performance in each particular > computational environment. > > ISPEC=12: The DLAHQR vs DLAQR0 crossover point. > Default: 75. (Must be at least 11.) > > ISPEC=13: Recommended deflation window size. > This depends on ILO, IHI and NS. NS is the > number of simultaneous shifts returned > by ILAENV(ISPEC=15). (See ISPEC=15 below.) > The default for (IHI-ILO+1).LE.500 is NS. > The default for (IHI-ILO+1).GT.500 is 3*NS/2. > > ISPEC=14: Nibble crossover point. (See IPARMQ for > details.) Default: 14% of deflation window > size. > > ISPEC=15: Number of simultaneous shifts in a multishift > QR iteration. > > If IHI-ILO+1 is ... > > greater than ...but less ... the > or equal to ... than default is > > 1 30 NS = 2(+) > 30 60 NS = 4(+) > 60 150 NS = 10(+) > 150 590 NS = ** > 590 3000 NS = 64 > 3000 6000 NS = 128 > 6000 infinity NS = 256 > > (+) By default some or all matrices of this order > are passed to the implicit double shift routine > DLAHQR and this parameter is ignored. See > ISPEC=12 above and comments in IPARMQ for > details. > > (**) The asterisks (**) indicate an ad-hoc > function of N increasing from 10 to 64. > > ISPEC=16: Select structured matrix multiply. > If the number of simultaneous shifts (specified > by ISPEC=15) is less than 14, then the default > for ISPEC=16 is 0. Otherwise the default for > ISPEC=16 is 2. > \endverbatim > \par References: ================ > > K. Braman, R. Byers and R. Mathias, The Multi-Shift QR > Algorithm Part I: Maintaining Well Focused Shifts, and Level 3 > Performance, SIAM Journal of Matrix Analysis, volume 23, pages > 929--947, 2002. > \n > K. Braman, R. Byers and R. Mathias, The Multi-Shift QR > Algorithm Part II: Aggressive Early Deflation, SIAM Journal > of Matrix Analysis, volume 23, pages 948--973, 2002. ===================================================================== Subroutine */ int igraphdhseqr_(char *job, char *compz, integer *n, integer *ilo, integer *ihi, doublereal *h__, integer *ldh, doublereal *wr, doublereal *wi, doublereal *z__, integer *ldz, doublereal *work, integer *lwork, integer *info) { /* System generated locals */ address a__1[2]; integer h_dim1, h_offset, z_dim1, z_offset, i__1, i__2[2], i__3; doublereal d__1; char ch__1[2]; /* Builtin functions Subroutine */ int s_cat(char *, char **, integer *, integer *, ftnlen); /* Local variables */ integer i__; doublereal hl[2401] /* was [49][49] */; integer kbot, nmin; extern logical igraphlsame_(char *, char *); logical initz; doublereal workl[49]; logical wantt, wantz; extern /* Subroutine */ int igraphdlaqr0_(logical *, logical *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, integer *, doublereal *, integer *, integer *), igraphdlahqr_(logical *, logical *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, integer *, integer *), igraphdlacpy_(char *, integer *, integer *, doublereal *, integer *, doublereal *, integer *), igraphdlaset_(char *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *); extern integer igraphilaenv_(integer *, char *, char *, integer *, integer *, integer *, integer *, ftnlen, ftnlen); extern /* Subroutine */ int igraphxerbla_(char *, integer *, ftnlen); logical lquery; /* -- LAPACK computational routine (version 3.4.0) -- -- LAPACK is a software package provided by Univ. of Tennessee, -- -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- November 2011 ===================================================================== ==== Matrices of order NTINY or smaller must be processed by . DLAHQR because of insufficient subdiagonal scratch space. . (This is a hard limit.) ==== ==== NL allocates some local workspace to help small matrices . through a rare DLAHQR failure. NL .GT. NTINY = 11 is . required and NL .LE. NMIN = ILAENV(ISPEC=12,...) is recom- . mended. (The default value of NMIN is 75.) Using NL = 49 . allows up to six simultaneous shifts and a 16-by-16 . deflation window. ==== ==== Decode and check the input parameters. ==== Parameter adjustments */ h_dim1 = *ldh; h_offset = 1 + h_dim1; h__ -= h_offset; --wr; --wi; z_dim1 = *ldz; z_offset = 1 + z_dim1; z__ -= z_offset; --work; /* Function Body */ wantt = igraphlsame_(job, "S"); initz = igraphlsame_(compz, "I"); wantz = initz || igraphlsame_(compz, "V"); work[1] = (doublereal) max(1,*n); lquery = *lwork == -1; *info = 0; if (! igraphlsame_(job, "E") && ! wantt) { *info = -1; } else if (! igraphlsame_(compz, "N") && ! wantz) { *info = -2; } else if (*n < 0) { *info = -3; } else if (*ilo < 1 || *ilo > max(1,*n)) { *info = -4; } else if (*ihi < min(*ilo,*n) || *ihi > *n) { *info = -5; } else if (*ldh < max(1,*n)) { *info = -7; } else if (*ldz < 1 || wantz && *ldz < max(1,*n)) { *info = -11; } else if (*lwork < max(1,*n) && ! lquery) { *info = -13; } if (*info != 0) { /* ==== Quick return in case of invalid argument. ==== */ i__1 = -(*info); igraphxerbla_("DHSEQR", &i__1, (ftnlen)6); return 0; } else if (*n == 0) { /* ==== Quick return in case N = 0; nothing to do. ==== */ return 0; } else if (lquery) { /* ==== Quick return in case of a workspace query ==== */ igraphdlaqr0_(&wantt, &wantz, n, ilo, ihi, &h__[h_offset], ldh, &wr[1], &wi[ 1], ilo, ihi, &z__[z_offset], ldz, &work[1], lwork, info); /* ==== Ensure reported workspace size is backward-compatible with . previous LAPACK versions. ==== Computing MAX */ d__1 = (doublereal) max(1,*n); work[1] = max(d__1,work[1]); return 0; } else { /* ==== copy eigenvalues isolated by DGEBAL ==== */ i__1 = *ilo - 1; for (i__ = 1; i__ <= i__1; ++i__) { wr[i__] = h__[i__ + i__ * h_dim1]; wi[i__] = 0.; /* L10: */ } i__1 = *n; for (i__ = *ihi + 1; i__ <= i__1; ++i__) { wr[i__] = h__[i__ + i__ * h_dim1]; wi[i__] = 0.; /* L20: */ } /* ==== Initialize Z, if requested ==== */ if (initz) { igraphdlaset_("A", n, n, &c_b11, &c_b12, &z__[z_offset], ldz) ; } /* ==== Quick return if possible ==== */ if (*ilo == *ihi) { wr[*ilo] = h__[*ilo + *ilo * h_dim1]; wi[*ilo] = 0.; return 0; } /* ==== DLAHQR/DLAQR0 crossover point ==== Writing concatenation */ i__2[0] = 1, a__1[0] = job; i__2[1] = 1, a__1[1] = compz; s_cat(ch__1, a__1, i__2, &c__2, (ftnlen)2); nmin = igraphilaenv_(&c__12, "DHSEQR", ch__1, n, ilo, ihi, lwork, (ftnlen)6, (ftnlen)2); nmin = max(11,nmin); /* ==== DLAQR0 for big matrices; DLAHQR for small ones ==== */ if (*n > nmin) { igraphdlaqr0_(&wantt, &wantz, n, ilo, ihi, &h__[h_offset], ldh, &wr[1], &wi[1], ilo, ihi, &z__[z_offset], ldz, &work[1], lwork, info); } else { /* ==== Small matrix ==== */ igraphdlahqr_(&wantt, &wantz, n, ilo, ihi, &h__[h_offset], ldh, &wr[1], &wi[1], ilo, ihi, &z__[z_offset], ldz, info); if (*info > 0) { /* ==== A rare DLAHQR failure! DLAQR0 sometimes succeeds . when DLAHQR fails. ==== */ kbot = *info; if (*n >= 49) { /* ==== Larger matrices have enough subdiagonal scratch . space to call DLAQR0 directly. ==== */ igraphdlaqr0_(&wantt, &wantz, n, ilo, &kbot, &h__[h_offset], ldh, &wr[1], &wi[1], ilo, ihi, &z__[z_offset], ldz, &work[1], lwork, info); } else { /* ==== Tiny matrices don't have enough subdiagonal . scratch space to benefit from DLAQR0. Hence, . tiny matrices must be copied into a larger . array before calling DLAQR0. ==== */ igraphdlacpy_("A", n, n, &h__[h_offset], ldh, hl, &c__49); hl[*n + 1 + *n * 49 - 50] = 0.; i__1 = 49 - *n; igraphdlaset_("A", &c__49, &i__1, &c_b11, &c_b11, &hl[(*n + 1) * 49 - 49], &c__49); igraphdlaqr0_(&wantt, &wantz, &c__49, ilo, &kbot, hl, &c__49, & wr[1], &wi[1], ilo, ihi, &z__[z_offset], ldz, workl, &c__49, info); if (wantt || *info != 0) { igraphdlacpy_("A", n, n, hl, &c__49, &h__[h_offset], ldh); } } } } /* ==== Clear out the trash, if necessary. ==== */ if ((wantt || *info != 0) && *n > 2) { i__1 = *n - 2; i__3 = *n - 2; igraphdlaset_("L", &i__1, &i__3, &c_b11, &c_b11, &h__[h_dim1 + 3], ldh); } /* ==== Ensure reported workspace size is backward-compatible with . previous LAPACK versions. ==== Computing MAX */ d__1 = (doublereal) max(1,*n); work[1] = max(d__1,work[1]); } /* ==== End of DHSEQR ==== */ return 0; } /* igraphdhseqr_ */ python-igraph-0.8.0/vendor/source/igraph/src/foreign-ncol-parser.y0000644000076500000240000001002013524616145025444 0ustar tamasstaff00000000000000/* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ %{ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include "igraph_hacks_internal.h" #include "igraph_types.h" #include "igraph_types_internal.h" #include "igraph_math.h" #include "igraph_memory.h" #include "igraph_error.h" #include "config.h" #include "foreign-ncol-header.h" #include "foreign-ncol-parser.h" #define yyscan_t void* int igraph_ncol_yylex(YYSTYPE* lvalp, YYLTYPE* llocp, void* scanner); int igraph_ncol_yyerror(YYLTYPE* locp, igraph_i_ncol_parsedata_t *context, const char *s); char *igraph_ncol_yyget_text (yyscan_t yyscanner ); int igraph_ncol_yyget_leng (yyscan_t yyscanner ); igraph_real_t igraph_ncol_get_number(const char *str, long int len); #define scanner context->scanner %} %pure-parser %output="y.tab.c" %name-prefix="igraph_ncol_yy" %defines %locations %error-verbose %parse-param { igraph_i_ncol_parsedata_t* context } %lex-param { void *scanner } %union { long int edgenum; double weightnum; } %type edgeid %type weight %token ALNUM %token NEWLINE %token ERROR %% input : /* empty */ | input NEWLINE | input edge ; edge : edgeid edgeid NEWLINE { igraph_vector_push_back(context->vector, $1); igraph_vector_push_back(context->vector, $2); igraph_vector_push_back(context->weights, 0); } | edgeid edgeid weight NEWLINE { igraph_vector_push_back(context->vector, $1); igraph_vector_push_back(context->vector, $2); igraph_vector_push_back(context->weights, $3); context->has_weights = 1; } ; edgeid : ALNUM { igraph_trie_get2(context->trie, igraph_ncol_yyget_text(scanner), igraph_ncol_yyget_leng(scanner), &$$); }; weight : ALNUM { $$=igraph_ncol_get_number(igraph_ncol_yyget_text(scanner), igraph_ncol_yyget_leng(scanner)); } ; %% int igraph_ncol_yyerror(YYLTYPE* locp, igraph_i_ncol_parsedata_t *context, const char *s) { snprintf(context->errmsg, sizeof(context->errmsg)/sizeof(char)-1, "Parse error in NCOL file, line %i (%s)", locp->first_line, s); return 0; } igraph_real_t igraph_ncol_get_number(const char *str, long int length) { igraph_real_t num; char *tmp=igraph_Calloc(length+1, char); strncpy(tmp, str, length); tmp[length]='\0'; sscanf(tmp, "%lf", &num); igraph_Free(tmp); return num; } python-igraph-0.8.0/vendor/source/igraph/src/embedding.c0000644000076500000240000011630213614300625023463 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2013 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_embedding.h" #include "igraph_interface.h" #include "igraph_adjlist.h" #include "igraph_random.h" #include "igraph_centrality.h" #include "igraph_blas.h" typedef struct { const igraph_t *graph; const igraph_vector_t *cvec; const igraph_vector_t *cvec2; igraph_adjlist_t *outlist, *inlist; igraph_inclist_t *eoutlist, *einlist; igraph_vector_t *tmp; const igraph_vector_t *weights; } igraph_i_asembedding_data_t; /* Adjacency matrix, unweighted, undirected. Eigendecomposition is used */ int igraph_i_asembeddingu(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_i_asembedding_data_t *data = extra; igraph_adjlist_t *outlist = data->outlist; const igraph_vector_t *cvec = data->cvec; igraph_vector_int_t *neis; int i, j, nlen; /* to = (A+cD) from */ for (i = 0; i < n; i++) { neis = igraph_adjlist_get(outlist, i); nlen = igraph_vector_int_size(neis); to[i] = 0.0; for (j = 0; j < nlen; j++) { long int nei = (long int) VECTOR(*neis)[j]; to[i] += from[nei]; } to[i] += VECTOR(*cvec)[i] * from[i]; } return 0; } /* Adjacency matrix, weighted, undirected. Eigendecomposition is used. */ int igraph_i_asembeddinguw(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_i_asembedding_data_t *data = extra; igraph_inclist_t *outlist = data->eoutlist; const igraph_vector_t *cvec = data->cvec; const igraph_vector_t *weights = data->weights; const igraph_t *graph = data->graph; igraph_vector_int_t *incs; int i, j, nlen; /* to = (A+cD) from */ for (i = 0; i < n; i++) { incs = igraph_inclist_get(outlist, i); nlen = igraph_vector_int_size(incs); to[i] = 0.0; for (j = 0; j < nlen; j++) { long int edge = VECTOR(*incs)[j]; long int nei = IGRAPH_OTHER(graph, edge, i); igraph_real_t w = VECTOR(*weights)[edge]; to[i] += w * from[nei]; } to[i] += VECTOR(*cvec)[i] * from[i]; } return 0; } /* Adjacency matrix, unweighted, directed. SVD. */ int igraph_i_asembedding(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_i_asembedding_data_t *data = extra; igraph_adjlist_t *outlist = data->outlist; igraph_adjlist_t *inlist = data->inlist; const igraph_vector_t *cvec = data->cvec; igraph_vector_t *tmp = data->tmp; igraph_vector_int_t *neis; int i, j, nlen; /* tmp = (A+cD)' from */ for (i = 0; i < n; i++) { neis = igraph_adjlist_get(inlist, i); nlen = igraph_vector_int_size(neis); VECTOR(*tmp)[i] = 0.0; for (j = 0; j < nlen; j++) { long int nei = (long int) VECTOR(*neis)[j]; VECTOR(*tmp)[i] += from[nei]; } VECTOR(*tmp)[i] += VECTOR(*cvec)[i] * from[i]; } /* to = (A+cD) tmp */ for (i = 0; i < n; i++) { neis = igraph_adjlist_get(outlist, i); nlen = igraph_vector_int_size(neis); to[i] = 0.0; for (j = 0; j < nlen; j++) { long int nei = (long int) VECTOR(*neis)[j]; to[i] += VECTOR(*tmp)[nei]; } to[i] += VECTOR(*cvec)[i] * VECTOR(*tmp)[i]; } return 0; } /* Adjacency matrix, unweighted, directed. SVD, right eigenvectors */ int igraph_i_asembedding_right(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_i_asembedding_data_t *data = extra; igraph_adjlist_t *inlist = data->inlist; const igraph_vector_t *cvec = data->cvec; igraph_vector_int_t *neis; int i, j, nlen; /* to = (A+cD)' from */ for (i = 0; i < n; i++) { neis = igraph_adjlist_get(inlist, i); nlen = igraph_vector_int_size(neis); to[i] = 0.0; for (j = 0; j < nlen; j++) { long int nei = (long int) VECTOR(*neis)[j]; to[i] += from[nei]; } to[i] += VECTOR(*cvec)[i] * from[i]; } return 0; } /* Adjacency matrix, weighted, directed. SVD. */ int igraph_i_asembeddingw(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_i_asembedding_data_t *data = extra; igraph_inclist_t *outlist = data->eoutlist; igraph_inclist_t *inlist = data->einlist; const igraph_vector_t *cvec = data->cvec; const igraph_vector_t *weights = data->weights; const igraph_t *graph = data->graph; igraph_vector_t *tmp = data->tmp; igraph_vector_int_t *incs; int i, j, nlen; /* tmp = (A+cD)' from */ for (i = 0; i < n; i++) { incs = igraph_inclist_get(inlist, i); nlen = igraph_vector_int_size(incs); VECTOR(*tmp)[i] = 0.0; for (j = 0; j < nlen; j++) { long int edge = VECTOR(*incs)[j]; long int nei = IGRAPH_OTHER(graph, edge, i); igraph_real_t w = VECTOR(*weights)[edge]; VECTOR(*tmp)[i] += w * from[nei]; } VECTOR(*tmp)[i] += VECTOR(*cvec)[i] * from[i]; } /* to = (A+cD) tmp */ for (i = 0; i < n; i++) { incs = igraph_inclist_get(outlist, i); nlen = igraph_vector_int_size(incs); to[i] = 0.0; for (j = 0; j < nlen; j++) { long int edge = VECTOR(*incs)[j]; long int nei = IGRAPH_OTHER(graph, edge, i); igraph_real_t w = VECTOR(*weights)[edge]; to[i] += w * VECTOR(*tmp)[nei]; } to[i] += VECTOR(*cvec)[i] * VECTOR(*tmp)[i]; } return 0; } /* Adjacency matrix, weighted, directed. SVD, right eigenvectors. */ int igraph_i_asembeddingw_right(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_i_asembedding_data_t *data = extra; igraph_inclist_t *inlist = data->einlist; const igraph_vector_t *cvec = data->cvec; const igraph_vector_t *weights = data->weights; const igraph_t *graph = data->graph; igraph_vector_int_t *incs; int i, j, nlen; /* to = (A+cD)' from */ for (i = 0; i < n; i++) { incs = igraph_inclist_get(inlist, i); nlen = igraph_vector_int_size(incs); to[i] = 0.0; for (j = 0; j < nlen; j++) { long int edge = VECTOR(*incs)[j]; long int nei = IGRAPH_OTHER(graph, edge, i); igraph_real_t w = VECTOR(*weights)[edge]; to[i] += w * from[nei]; } to[i] += VECTOR(*cvec)[i] * from[i]; } return 0; } /* Laplacian D-A, unweighted, undirected. Eigendecomposition. */ int igraph_i_lsembedding_da(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_i_asembedding_data_t *data = extra; igraph_adjlist_t *outlist = data->outlist; const igraph_vector_t *cvec = data->cvec; igraph_vector_int_t *neis; int i, j, nlen; /* to = (D-A) from */ for (i = 0; i < n; i++) { neis = igraph_adjlist_get(outlist, i); nlen = igraph_vector_int_size(neis); to[i] = 0.0; for (j = 0; j < nlen; j++) { long int nei = (long int) VECTOR(*neis)[j]; to[i] -= from[nei]; } to[i] += VECTOR(*cvec)[i] * from[i]; } return 0; } /* Laplacian D-A, weighted, undirected. Eigendecomposition. */ int igraph_i_lsembedding_daw(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_i_asembedding_data_t *data = extra; igraph_inclist_t *outlist = data->eoutlist; const igraph_vector_t *cvec = data->cvec; const igraph_vector_t *weights = data->weights; const igraph_t *graph = data->graph; igraph_vector_int_t *incs; int i, j, nlen; /* to = (D-A) from */ for (i = 0; i < n; i++) { incs = igraph_inclist_get(outlist, i); nlen = igraph_vector_int_size(incs); to[i] = 0.0; for (j = 0; j < nlen; j++) { long int edge = VECTOR(*incs)[j]; long int nei = IGRAPH_OTHER(graph, edge, i); igraph_real_t w = VECTOR(*weights)[edge]; to[i] -= w * from[nei]; } to[i] += VECTOR(*cvec)[i] * from[i]; } return 0; } /* Laplacian DAD, unweighted, undirected. Eigendecomposition. */ int igraph_i_lsembedding_dad(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_i_asembedding_data_t *data = extra; igraph_adjlist_t *outlist = data->outlist; const igraph_vector_t *cvec = data->cvec; igraph_vector_t *tmp = data->tmp; igraph_vector_int_t *neis; int i, j, nlen; /* to = D^1/2 from */ for (i = 0; i < n; i++) { to[i] = VECTOR(*cvec)[i] * from[i]; } /* tmp = A to */ for (i = 0; i < n; i++) { neis = igraph_adjlist_get(outlist, i); nlen = igraph_vector_int_size(neis); VECTOR(*tmp)[i] = 0.0; for (j = 0; j < nlen; j++) { long int nei = (long int) VECTOR(*neis)[j]; VECTOR(*tmp)[i] += to[nei]; } } /* to = D tmp */ for (i = 0; i < n; i++) { to[i] = VECTOR(*cvec)[i] * VECTOR(*tmp)[i]; } return 0; } int igraph_i_lsembedding_dadw(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_i_asembedding_data_t *data = extra; igraph_inclist_t *outlist = data->eoutlist; const igraph_vector_t *cvec = data->cvec; const igraph_vector_t *weights = data->weights; const igraph_t *graph = data->graph; igraph_vector_t *tmp = data->tmp; igraph_vector_int_t *incs; int i, j, nlen; /* to = D^-1/2 from */ for (i = 0; i < n; i++) { to[i] = VECTOR(*cvec)[i] * from[i]; } /* tmp = A' to */ for (i = 0; i < n; i++) { incs = igraph_inclist_get(outlist, i); nlen = igraph_vector_int_size(incs); VECTOR(*tmp)[i] = 0.0; for (j = 0; j < nlen; j++) { long int edge = VECTOR(*incs)[j]; long int nei = IGRAPH_OTHER(graph, edge, i); igraph_real_t w = VECTOR(*weights)[edge]; VECTOR(*tmp)[i] += w * to[nei]; } } /* to = D tmp */ for (i = 0; i < n; i++) { to[i] = VECTOR(*cvec)[i] * VECTOR(*cvec)[i] * VECTOR(*tmp)[i]; } /* tmp = A to */ for (i = 0; i < n; i++) { incs = igraph_inclist_get(outlist, i); nlen = igraph_vector_int_size(incs); VECTOR(*tmp)[i] = 0.0; for (j = 0; j < nlen; j++) { long int edge = VECTOR(*incs)[j]; long int nei = IGRAPH_OTHER(graph, edge, i); igraph_real_t w = VECTOR(*weights)[edge]; VECTOR(*tmp)[i] += w * to[nei]; } } /* to = D^-1/2 tmp */ for (i = 0; i < n; i++) { to[i] = VECTOR(*cvec)[i] * VECTOR(*tmp)[i]; } return 0; } /* Laplacian I-DAD, unweighted, undirected. Eigendecomposition. */ int igraph_i_lsembedding_idad(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { int i; igraph_i_lsembedding_dad(to, from, n, extra); for (i = 0; i < n; i++) { to[i] = from[i] - to[i]; } return 0; } int igraph_i_lsembedding_idadw(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { int i; igraph_i_lsembedding_dadw(to, from, n, extra); for (i = 0; i < n; i++) { to[i] = from[i] - to[i]; } return 0; } /* Laplacian OAP, unweighted, directed. SVD. */ int igraph_i_lseembedding_oap(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_i_asembedding_data_t *data = extra; igraph_adjlist_t *outlist = data->outlist; igraph_adjlist_t *inlist = data->inlist; const igraph_vector_t *deg_in = data->cvec; const igraph_vector_t *deg_out = data->cvec2; igraph_vector_t *tmp = data->tmp; igraph_vector_int_t *neis; int i, j, nlen; /* tmp = O' from */ for (i = 0; i < n; i++) { VECTOR(*tmp)[i] = VECTOR(*deg_out)[i] * from[i]; } /* to = A' tmp */ for (i = 0; i < n; i++) { neis = igraph_adjlist_get(inlist, i); nlen = igraph_vector_int_size(neis); to[i] = 0.0; for (j = 0; j < nlen; j++) { int nei = VECTOR(*neis)[j]; to[i] += VECTOR(*tmp)[nei]; } } /* tmp = P' to */ for (i = 0; i < n; i++) { VECTOR(*tmp)[i] = VECTOR(*deg_in)[i] * to[i]; } /* to = P tmp */ for (i = 0; i < n; i++) { to[i] = VECTOR(*deg_in)[i] * VECTOR(*tmp)[i]; } /* tmp = A to */ for (i = 0; i < n; i++) { neis = igraph_adjlist_get(outlist, i); nlen = igraph_vector_int_size(neis); VECTOR(*tmp)[i] = 0.0; for (j = 0; j < nlen; j++) { int nei = VECTOR(*neis)[j]; VECTOR(*tmp)[i] += to[nei]; } } /* to = O tmp */ for (i = 0; i < n; i++) { to[i] = VECTOR(*deg_out)[i] * VECTOR(*tmp)[i]; } return 0; } /* Laplacian OAP, unweighted, directed. SVD, right eigenvectors. */ int igraph_i_lseembedding_oap_right(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_i_asembedding_data_t *data = extra; igraph_adjlist_t *inlist = data->inlist; const igraph_vector_t *deg_in = data->cvec; const igraph_vector_t *deg_out = data->cvec2; igraph_vector_t *tmp = data->tmp; igraph_vector_int_t *neis; int i, j, nlen; /* to = O' from */ for (i = 0; i < n; i++) { to[i] = VECTOR(*deg_out)[i] * from[i]; } /* tmp = A' to */ for (i = 0; i < n; i++) { neis = igraph_adjlist_get(inlist, i); nlen = igraph_vector_int_size(neis); VECTOR(*tmp)[i] = 0.0; for (j = 0; j < nlen; j++) { int nei = VECTOR(*neis)[j]; VECTOR(*tmp)[i] += to[nei]; } } /* to = P' tmp */ for (i = 0; i < n; i++) { to[i] = VECTOR(*deg_in)[i] * VECTOR(*tmp)[i]; } return 0; } /* Laplacian OAP, weighted, directed. SVD. */ int igraph_i_lseembedding_oapw(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_i_asembedding_data_t *data = extra; igraph_inclist_t *outlist = data->eoutlist; igraph_inclist_t *inlist = data->einlist; const igraph_vector_t *deg_in = data->cvec; const igraph_vector_t *deg_out = data->cvec2; const igraph_vector_t *weights = data->weights; const igraph_t *graph = data->graph; igraph_vector_t *tmp = data->tmp; igraph_vector_int_t *neis; int i, j, nlen; /* tmp = O' from */ for (i = 0; i < n; i++) { VECTOR(*tmp)[i] = VECTOR(*deg_out)[i] * from[i]; } /* to = A' tmp */ for (i = 0; i < n; i++) { neis = igraph_inclist_get(inlist, i); nlen = igraph_vector_int_size(neis); to[i] = 0.0; for (j = 0; j < nlen; j++) { int edge = VECTOR(*neis)[j]; int nei = IGRAPH_OTHER(graph, edge, i); igraph_real_t w = VECTOR(*weights)[edge]; to[i] += w * VECTOR(*tmp)[nei]; } } /* tmp = P' to */ for (i = 0; i < n; i++) { VECTOR(*tmp)[i] = VECTOR(*deg_in)[i] * to[i]; } /* to = P tmp */ for (i = 0; i < n; i++) { to[i] = VECTOR(*deg_in)[i] * VECTOR(*tmp)[i]; } /* tmp = A to */ for (i = 0; i < n; i++) { neis = igraph_inclist_get(outlist, i); nlen = igraph_vector_int_size(neis); VECTOR(*tmp)[i] = 0.0; for (j = 0; j < nlen; j++) { int edge = VECTOR(*neis)[j]; int nei = IGRAPH_OTHER(graph, edge, i); igraph_real_t w = VECTOR(*weights)[edge]; VECTOR(*tmp)[i] += w * to[nei]; } } /* to = O tmp */ for (i = 0; i < n; i++) { to[i] = VECTOR(*deg_out)[i] * VECTOR(*tmp)[i]; } return 0; } /* Laplacian OAP, weighted, directed. SVD, right eigenvectors. */ int igraph_i_lseembedding_oapw_right(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_i_asembedding_data_t *data = extra; igraph_inclist_t *inlist = data->einlist; const igraph_vector_t *deg_in = data->cvec; const igraph_vector_t *deg_out = data->cvec2; const igraph_vector_t *weights = data->weights; const igraph_t *graph = data->graph; igraph_vector_t *tmp = data->tmp; igraph_vector_int_t *neis; int i, j, nlen; /* to = O' from */ for (i = 0; i < n; i++) { to[i] = VECTOR(*deg_out)[i] * from[i]; } /* tmp = A' to */ for (i = 0; i < n; i++) { neis = igraph_inclist_get(inlist, i); nlen = igraph_vector_int_size(neis); VECTOR(*tmp)[i] = 0.0; for (j = 0; j < nlen; j++) { int edge = VECTOR(*neis)[j]; int nei = IGRAPH_OTHER(graph, edge, i); igraph_real_t w = VECTOR(*weights)[edge]; VECTOR(*tmp)[i] += w * to[nei]; } } /* to = P' tmp */ for (i = 0; i < n; i++) { to[i] = VECTOR(*deg_in)[i] * VECTOR(*tmp)[i]; } return 0; } int igraph_i_spectral_embedding(const igraph_t *graph, igraph_integer_t no, const igraph_vector_t *weights, igraph_eigen_which_position_t which, igraph_bool_t scaled, igraph_matrix_t *X, igraph_matrix_t *Y, igraph_vector_t *D, const igraph_vector_t *cvec, const igraph_vector_t *cvec2, igraph_arpack_options_t *options, igraph_arpack_function_t *callback, igraph_arpack_function_t *callback_right, igraph_bool_t symmetric, igraph_bool_t eigen, igraph_bool_t zapsmall) { igraph_integer_t vc = igraph_vcount(graph); igraph_vector_t tmp; igraph_adjlist_t outlist, inlist; igraph_inclist_t eoutlist, einlist; int i, j, cveclen = igraph_vector_size(cvec); igraph_i_asembedding_data_t data = { graph, cvec, cvec2, &outlist, &inlist, &eoutlist, &einlist, &tmp, weights }; igraph_vector_t tmpD; if (weights && igraph_vector_size(weights) != igraph_ecount(graph)) { IGRAPH_ERROR("Invalid weight vector length", IGRAPH_EINVAL); } if (which != IGRAPH_EIGEN_LM && which != IGRAPH_EIGEN_LA && which != IGRAPH_EIGEN_SA) { IGRAPH_ERROR("Invalid eigenvalue chosen, must be one of " "`largest magnitude', `largest algebraic' or " "`smallest algebraic'", IGRAPH_EINVAL); } if (no > vc) { IGRAPH_ERROR("Too many singular values requested", IGRAPH_EINVAL); } if (no <= 0) { IGRAPH_ERROR("No singular values requested", IGRAPH_EINVAL); } if (cveclen != 1 && cveclen != vc) { IGRAPH_ERROR("Augmentation vector size is invalid, it should be " "the number of vertices or scalar", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_matrix_resize(X, vc, no)); if (Y) { IGRAPH_CHECK(igraph_matrix_resize(Y, vc, no)); } /* empty graph */ if (igraph_ecount(graph) == 0) { igraph_matrix_null(X); if (Y) { igraph_matrix_null(Y); } return 0; } igraph_vector_init(&tmp, vc); IGRAPH_FINALLY(igraph_vector_destroy, &tmp); if (!weights) { IGRAPH_CHECK(igraph_adjlist_init(graph, &outlist, IGRAPH_OUT)); IGRAPH_FINALLY(igraph_adjlist_destroy, &outlist); if (!symmetric) { IGRAPH_CHECK(igraph_adjlist_init(graph, &inlist, IGRAPH_IN)); IGRAPH_FINALLY(igraph_adjlist_destroy, &inlist); } } else { IGRAPH_CHECK(igraph_inclist_init(graph, &eoutlist, IGRAPH_OUT)); IGRAPH_FINALLY(igraph_inclist_destroy, &eoutlist); if (!symmetric) { IGRAPH_CHECK(igraph_inclist_init(graph, &einlist, IGRAPH_IN)); IGRAPH_FINALLY(igraph_inclist_destroy, &einlist); } } IGRAPH_VECTOR_INIT_FINALLY(&tmpD, no); options->n = vc; options->start = 0; /* random start vector */ options->nev = no; switch (which) { case IGRAPH_EIGEN_LM: options->which[0] = 'L'; options->which[1] = 'M'; break; case IGRAPH_EIGEN_LA: options->which[0] = 'L'; options->which[1] = 'A'; break; case IGRAPH_EIGEN_SA: options->which[0] = 'S'; options->which[1] = 'A'; break; default: break; } options->ncv = no + 3; if (options->ncv > vc) { options->ncv = vc; } IGRAPH_CHECK(igraph_arpack_rssolve(callback, &data, options, 0, &tmpD, X)); if (!symmetric) { /* calculate left eigenvalues */ IGRAPH_CHECK(igraph_matrix_resize(Y, vc, no)); for (i = 0; i < no; i++) { igraph_real_t norm; igraph_vector_t v; callback_right(&MATRIX(*Y, 0, i), &MATRIX(*X, 0, i), vc, &data); igraph_vector_view(&v, &MATRIX(*Y, 0, i), vc); norm = 1.0 / igraph_blas_dnrm2(&v); igraph_vector_scale(&v, norm); } } else if (Y) { IGRAPH_CHECK(igraph_matrix_update(Y, X)); } if (zapsmall) { igraph_vector_zapsmall(&tmpD, 0); igraph_matrix_zapsmall(X, 0); if (Y) { igraph_matrix_zapsmall(Y, 0); } } if (D) { igraph_vector_update(D, &tmpD); if (!eigen) { for (i = 0; i < no; i++) { VECTOR(*D)[i] = sqrt(VECTOR(*D)[i]); } } } if (scaled) { if (eigen) { /* eigenvalues were calculated */ for (i = 0; i < no; i++) { VECTOR(tmpD)[i] = sqrt(fabs(VECTOR(tmpD)[i])); } } else { /* singular values were calculated */ for (i = 0; i < no; i++) { VECTOR(tmpD)[i] = sqrt(sqrt(VECTOR(tmpD)[i])); } } for (j = 0; j < vc; j++) { for (i = 0; i < no; i++) { MATRIX(*X, j, i) *= VECTOR(tmpD)[i]; } } if (Y) { for (j = 0; j < vc; j++) { for (i = 0; i < no; i++) { MATRIX(*Y, j, i) *= VECTOR(tmpD)[i]; } } } } igraph_vector_destroy(&tmpD); if (!weights) { if (!symmetric) { igraph_adjlist_destroy(&inlist); IGRAPH_FINALLY_CLEAN(1); } igraph_adjlist_destroy(&outlist); } else { if (!symmetric) { igraph_inclist_destroy(&einlist); IGRAPH_FINALLY_CLEAN(1); } igraph_inclist_destroy(&eoutlist); } igraph_vector_destroy(&tmp); IGRAPH_FINALLY_CLEAN(3); return 0; } /** * \function igraph_adjacency_spectral_embedding * Adjacency spectral embedding * * Spectral decomposition of the adjacency matrices of graphs. * This function computes a \code{no}-dimensional Euclidean * representation of the graph based on its adjacency * matrix, A. This representation is computed via the singular value * decomposition of the adjacency matrix, A=UDV^T. In the case, * where the graph is a random dot product graph generated using latent * position vectors in R^no for each vertex, the embedding will * provide an estimate of these latent vectors. * * * For undirected graphs the latent positions are calculated as * X=U^no D^(1/2) where U^no equals to the first no columns of U, and * D^(1/2) is a diagonal matrix containing the square root of the selected * singular values on the diagonal. * * * For directed graphs the embedding is defined as the pair * X=U^no D^(1/2), Y=V^no D^(1/2). (For undirected graphs U=V, * so it is enough to keep one of them.) * * \param graph The input graph, can be directed or undirected. * \param no An integer scalar. This value is the embedding dimension of * the spectral embedding. Should be smaller than the number of * vertices. The largest no-dimensional non-zero * singular values are used for the spectral embedding. * \param weights Optional edge weights. Supply a null pointer for * unweighted graphs. * \param which Which eigenvalues (or singular values, for directed * graphs) to use, possible values: * \clist * \cli IGRAPH_EIGEN_LM * the ones with the largest magnitude * \cli IGRAPH_EIGEN_LA * the (algebraic) largest ones * \cli IGRAPH_EIGEN_SA * the (algebraic) smallest ones. * \endclist * For directed graphs, IGRAPH_EIGEN_LM and * IGRAPH_EIGEN_LA are the same because singular * values are used for the ordering instead of eigenvalues. * \param scaled Whether to return X and Y (if scaled is non-zero), or * U and V. * \param X Initialized matrix, the estimated latent positions are * stored here. * \param Y Initialized matrix or a null pointer. If not a null * pointer, then the second half of the latent positions are * stored here. (For undirected graphs, this always equals X.) * \param D Initialized vector or a null pointer. If not a null * pointer, then the eigenvalues (for undirected graphs) or the * singular values (for directed graphs) are stored here. * \param cvec A numeric vector, its length is the number vertices in the * graph. This vector is added to the diagonal of the adjacency * matrix, before performing the SVD. * \param options Options to ARPACK. See \ref igraph_arpack_options_t * for details. Note that the function overwrites the * n (number of vertices), nev and * which parameters and it always starts the * calculation from a random start vector. * \return Error code. * */ int igraph_adjacency_spectral_embedding(const igraph_t *graph, igraph_integer_t no, const igraph_vector_t *weights, igraph_eigen_which_position_t which, igraph_bool_t scaled, igraph_matrix_t *X, igraph_matrix_t *Y, igraph_vector_t *D, const igraph_vector_t *cvec, igraph_arpack_options_t *options) { igraph_arpack_function_t *callback, *callback_right; igraph_bool_t directed = igraph_is_directed(graph); if (directed) { callback = weights ? igraph_i_asembeddingw : igraph_i_asembedding; callback_right = (weights ? igraph_i_asembeddingw_right : igraph_i_asembedding_right); } else { callback = weights ? igraph_i_asembeddinguw : igraph_i_asembeddingu; callback_right = 0; } return igraph_i_spectral_embedding(graph, no, weights, which, scaled, X, Y, D, cvec, /* deg2=*/ 0, options, callback, callback_right, /*symmetric=*/ !directed, /*eigen=*/ !directed, /*zapsmall=*/ 1); } int igraph_i_lse_und(const igraph_t *graph, igraph_integer_t no, const igraph_vector_t *weights, igraph_eigen_which_position_t which, igraph_neimode_t degmode, igraph_laplacian_spectral_embedding_type_t type, igraph_bool_t scaled, igraph_matrix_t *X, igraph_matrix_t *Y, igraph_vector_t *D, igraph_arpack_options_t *options) { igraph_arpack_function_t *callback; igraph_vector_t deg; switch (type) { case IGRAPH_EMBEDDING_D_A: callback = weights ? igraph_i_lsembedding_daw : igraph_i_lsembedding_da; break; case IGRAPH_EMBEDDING_DAD: callback = weights ? igraph_i_lsembedding_dadw : igraph_i_lsembedding_dad; break; case IGRAPH_EMBEDDING_I_DAD: callback = weights ? igraph_i_lsembedding_idadw : igraph_i_lsembedding_idad; break; default: IGRAPH_ERROR("Invalid Laplacian spectral embedding type", IGRAPH_EINVAL); break; } IGRAPH_VECTOR_INIT_FINALLY(°, 0); igraph_strength(graph, °, igraph_vss_all(), IGRAPH_ALL, /*loops=*/ 1, weights); switch (type) { case IGRAPH_EMBEDDING_D_A: break; case IGRAPH_EMBEDDING_DAD: case IGRAPH_EMBEDDING_I_DAD: { int i, n = igraph_vector_size(°); for (i = 0; i < n; i++) { VECTOR(deg)[i] = 1.0 / sqrt(VECTOR(deg)[i]); } } break; default: break; } IGRAPH_CHECK(igraph_i_spectral_embedding(graph, no, weights, which, scaled, X, Y, D, /*cvec=*/ °, /*deg2=*/ 0, options, callback, 0, /*symmetric=*/ 1, /*eigen=*/ 1, /*zapsmall=*/ 1)); igraph_vector_destroy(°); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_i_lse_dir(const igraph_t *graph, igraph_integer_t no, const igraph_vector_t *weights, igraph_eigen_which_position_t which, igraph_neimode_t degmode, igraph_laplacian_spectral_embedding_type_t type, igraph_bool_t scaled, igraph_matrix_t *X, igraph_matrix_t *Y, igraph_vector_t *D, igraph_arpack_options_t *options) { igraph_arpack_function_t *callback = weights ? igraph_i_lseembedding_oapw : igraph_i_lseembedding_oap; igraph_arpack_function_t *callback_right = weights ? igraph_i_lseembedding_oapw_right : igraph_i_lseembedding_oap_right; igraph_vector_t deg_in, deg_out; int i, n = igraph_vcount(graph); if (type != IGRAPH_EMBEDDING_OAP) { IGRAPH_ERROR("Invalid Laplacian spectral embedding type", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(°_in, n); IGRAPH_VECTOR_INIT_FINALLY(°_out, n); igraph_strength(graph, °_in, igraph_vss_all(), IGRAPH_IN, /*loops=*/ 1, weights); igraph_strength(graph, °_out, igraph_vss_all(), IGRAPH_OUT, /*loops=*/ 1, weights); for (i = 0; i < n; i++) { VECTOR(deg_in)[i] = 1.0 / sqrt(VECTOR(deg_in)[i]); VECTOR(deg_out)[i] = 1.0 / sqrt(VECTOR(deg_out)[i]); } IGRAPH_CHECK(igraph_i_spectral_embedding(graph, no, weights, which, scaled, X, Y, D, /*cvec=*/ °_in, /*deg2=*/ °_out, options, callback, callback_right, /*symmetric=*/ 0, /*eigen=*/ 0, /*zapsmall=*/ 1)); igraph_vector_destroy(°_in); igraph_vector_destroy(°_out); IGRAPH_FINALLY_CLEAN(2); return 0; } /** * \function igraph_laplacian_spectral_embedding * Spectral embedding of the Laplacian of a graph * * This function essentially does the same as * \ref igraph_adjacency_spectral_embedding, but works on the Laplacian * of the graph, instead of the adjacency matrix. * \param graph The input graph. * \param no The number of eigenvectors (or singular vectors if the graph * is directed) to use for the embedding. * \param weights Optional edge weights. Supply a null pointer for * unweighted graphs. * \param which Which eigenvalues (or singular values, for directed * graphs) to use, possible values: * \clist * \cli IGRAPH_EIGEN_LM * the ones with the largest magnitude * \cli IGRAPH_EIGEN_LA * the (algebraic) largest ones * \cli IGRAPH_EIGEN_SA * the (algebraic) smallest ones. * \endclist * For directed graphs, IGRAPH_EIGEN_LM and * IGRAPH_EIGEN_LA are the same because singular * values are used for the ordering instead of eigenvalues. * \param type The type of the Laplacian to use. Various definitions * exist for the Laplacian of a graph, and one can choose * between them with this argument. Possible values: * \clist * \cli IGRAPH_EMBEDDING_D_A * means D - A where D is the * degree matrix and A is the adjacency matrix * \cli IGRAPH_EMBEDDING_DAD * means Di times A times Di, * where Di is the inverse of the square root of the degree matrix; * \cli IGRAPH_EMBEDDING_I_DAD * means I - Di A Di, where I * is the identity matrix. * \endclist * \param scaled Whether to return X and Y (if scaled is non-zero), or * U and V. * \param X Initialized matrix, the estimated latent positions are * stored here. * \param Y Initialized matrix or a null pointer. If not a null * pointer, then the second half of the latent positions are * stored here. (For undirected graphs, this always equals X.) * \param D Initialized vector or a null pointer. If not a null * pointer, then the eigenvalues (for undirected graphs) or the * singular values (for directed graphs) are stored here. * \param options Options to ARPACK. See \ref igraph_arpack_options_t * for details. Note that the function overwrites the * n (number of vertices), nev and * which parameters and it always starts the * calculation from a random start vector. * \return Error code. * * \sa \ref igraph_adjacency_spectral_embedding to embed the adjacency * matrix. */ int igraph_laplacian_spectral_embedding(const igraph_t *graph, igraph_integer_t no, const igraph_vector_t *weights, igraph_eigen_which_position_t which, igraph_neimode_t degmode, igraph_laplacian_spectral_embedding_type_t type, igraph_bool_t scaled, igraph_matrix_t *X, igraph_matrix_t *Y, igraph_vector_t *D, igraph_arpack_options_t *options) { if (igraph_is_directed(graph)) { return igraph_i_lse_dir(graph, no, weights, which, degmode, type, scaled, X, Y, D, options); } else { return igraph_i_lse_und(graph, no, weights, which, degmode, type, scaled, X, Y, D, options); } } /** * \function igraph_dim_select * Dimensionality selection * * Dimensionality selection for singular values using * profile likelihood. * * * The input of the function is a numeric vector which contains * the measure of "importance" for each dimension. * * * For spectral embedding, these are the singular values of the adjacency * matrix. The singular values are assumed to be generated from a * Gaussian mixture distribution with two components that have different * means and same variance. The dimensionality d is chosen to * maximize the likelihood when the d largest singular values are * assigned to one component of the mixture and the rest of the singular * values assigned to the other component. * * * This function can also be used for the general separation problem, * where we assume that the left and the right of the vector are coming * from two Normal distributions, with different means, and we want * to know their border. * * \param sv A numeric vector, the ordered singular values. * \param dim The result is stored here. * \return Error code. * * Time complexity: O(n), n is the number of values in sv. * * \sa \ref igraph_adjacency_spectral_embedding(). */ int igraph_dim_select(const igraph_vector_t *sv, igraph_integer_t *dim) { int i, n = igraph_vector_size(sv); igraph_real_t x, x2, sum1 = 0.0, sum2 = igraph_vector_sum(sv); igraph_real_t sumsq1 = 0.0, sumsq2 = 0.0; /* to be set */ igraph_real_t oldmean1, oldmean2, mean1 = 0.0, mean2 = sum2 / n; igraph_real_t varsq1 = 0.0, varsq2 = 0.0; /* to be set */ igraph_real_t var1, var2, sd, profile, max = IGRAPH_NEGINFINITY; if (n == 0) { IGRAPH_ERROR("Need at least one singular value for dimensionality " "selection", IGRAPH_EINVAL); } if (n == 1) { *dim = 1; return 0; } for (i = 0; i < n; i++) { x = VECTOR(*sv)[i]; sumsq2 += x * x; varsq2 += (mean2 - x) * (mean2 - x); } for (i = 0; i < n - 1; i++) { int n1 = i + 1, n2 = n - i - 1, n1m1 = n1 - 1, n2m1 = n2 - 1; x = VECTOR(*sv)[i]; x2 = x * x; sum1 += x; sum2 -= x; sumsq1 += x2; sumsq2 -= x2; oldmean1 = mean1; oldmean2 = mean2; mean1 = sum1 / n1; mean2 = sum2 / n2; varsq1 += (x - oldmean1) * (x - mean1); varsq2 -= (x - oldmean2) * (x - mean2); var1 = i == 0 ? 0 : varsq1 / n1m1; var2 = i == n - 2 ? 0 : varsq2 / n2m1; sd = sqrt(( n1m1 * var1 + n2m1 * var2) / (n - 2)); profile = /* - n * log(2.0*M_PI)/2.0 */ /* This is redundant */ - n * log(sd) - ((sumsq1 - 2 * mean1 * sum1 + n1 * mean1 * mean1) + (sumsq2 - 2 * mean2 * sum2 + n2 * mean2 * mean2)) / 2.0 / sd / sd; if (profile > max) { max = profile; *dim = n1; } } /* Plus the last case, all elements in one group */ x = VECTOR(*sv)[n - 1]; sum1 += x; oldmean1 = mean1; mean1 = sum1 / n; sumsq1 += x * x; varsq1 += (x - oldmean1) * (x - mean1); var1 = varsq1 / (n - 1); sd = sqrt(var1); profile = /* - n * log(2.0*M_PI)/2.0 */ /* This is redundant */ - n * log(sd) - (sumsq1 - 2 * mean1 * sum1 + n * mean1 * mean1) / 2.0 / sd / sd; if (profile > max) { max = profile; *dim = n; } return 0; } python-igraph-0.8.0/vendor/source/igraph/src/foreign-lgl-lexer.l0000644000076500000240000000606113524616145025107 0ustar tamasstaff00000000000000/* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ %{ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "config.h" #include #include "foreign-lgl-header.h" #include "foreign-lgl-parser.h" #define YY_EXTRA_TYPE igraph_i_lgl_parsedata_t* #define YY_USER_ACTION yylloc->first_line = yylineno; /* We assume that 'file' is 'stderr' here. */ #ifdef USING_R #define fprintf(file, msg, ...) (1) #endif #ifdef stdout # undef stdout #endif #define stdout 0 #define exit(code) igraph_error("Fatal error in DL parser", __FILE__, \ __LINE__, IGRAPH_PARSEERROR); %} %option noyywrap %option prefix="igraph_lgl_yy" %option outfile="lex.yy.c" %option nounput %option noinput %option nodefault %option reentrant %option bison-bridge %option bison-locations alnum [^ \t\r\n#] %% /* --------------------------------------------------hashmark------*/ # { return HASH; } /* ------------------------------------------------whitespace------*/ [ \t]* { } /* ---------------------------------------------------newline------*/ \n\r|\r\n|\n|\r { return NEWLINE; } /* ----------------------------------------------alphanumeric------*/ {alnum}+ { return ALNUM; } <> { if (yyextra->eof) { yyterminate(); } else { yyextra->eof=1; return NEWLINE; } } . { return ERROR; } %% python-igraph-0.8.0/vendor/source/igraph/src/spectral_properties.c0000644000076500000240000003767713614300625025657 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_structural.h" #include "igraph_interface.h" #include "config.h" #include int igraph_i_weighted_laplacian(const igraph_t *graph, igraph_matrix_t *res, igraph_sparsemat_t *sparseres, igraph_bool_t normalized, const igraph_vector_t *weights) { igraph_eit_t edgeit; int no_of_nodes = (int) igraph_vcount(graph); int no_of_edges = (int) igraph_ecount(graph); igraph_bool_t directed = igraph_is_directed(graph); igraph_vector_t degree; long int i; if (igraph_vector_size(weights) != no_of_edges) { IGRAPH_ERROR("Invalid edge weight vector length", IGRAPH_EINVAL); } if (res) { IGRAPH_CHECK(igraph_matrix_resize(res, no_of_nodes, no_of_nodes)); igraph_matrix_null(res); } if (sparseres) { int nz = directed ? no_of_edges + no_of_nodes : no_of_edges * 2 + no_of_nodes; igraph_sparsemat_resize(sparseres, no_of_nodes, no_of_nodes, nz); } IGRAPH_CHECK(igraph_eit_create(graph, igraph_ess_all(0), &edgeit)); IGRAPH_FINALLY(igraph_eit_destroy, &edgeit); IGRAPH_VECTOR_INIT_FINALLY(°ree, no_of_nodes); if (directed) { if (!normalized) { while (!IGRAPH_EIT_END(edgeit)) { long int edge = IGRAPH_EIT_GET(edgeit); long int from = IGRAPH_FROM(graph, edge); long int to = IGRAPH_TO (graph, edge); igraph_real_t weight = VECTOR(*weights)[edge]; if (from != to) { if (res) { MATRIX(*res, from, to) -= weight; } if (sparseres) { IGRAPH_CHECK(igraph_sparsemat_entry(sparseres, (int) from, (int)to, -weight)); } VECTOR(degree)[from] += weight; } IGRAPH_EIT_NEXT(edgeit); } /* And the diagonal */ for (i = 0; i < no_of_nodes; i++) { if (res) { MATRIX(*res, i, i) = VECTOR(degree)[i]; } if (sparseres) { IGRAPH_CHECK(igraph_sparsemat_entry(sparseres, (int) i, (int) i, VECTOR(degree)[i])); } } } else { /* normalized */ while (!IGRAPH_EIT_END(edgeit)) { long int edge = IGRAPH_EIT_GET(edgeit); long int from = IGRAPH_FROM(graph, edge); long int to = IGRAPH_TO (graph, edge); igraph_real_t weight = VECTOR(*weights)[edge]; if (from != to) { VECTOR(degree)[from] += weight; } IGRAPH_EIT_NEXT(edgeit); } for (i = 0; i < no_of_nodes; i++) { int t = VECTOR(degree)[i] > 0 ? 1 : 0; if (res) { MATRIX(*res, i, i) = t; } if (sparseres) { IGRAPH_CHECK(igraph_sparsemat_entry(sparseres, (int) i, (int) i, t)); } } IGRAPH_EIT_RESET(edgeit); while (!IGRAPH_EIT_END(edgeit)) { long int edge = IGRAPH_EIT_GET(edgeit); long int from = IGRAPH_FROM(graph, edge); long int to = IGRAPH_TO (graph, edge); igraph_real_t weight = VECTOR(*weights)[edge]; if (from != to) { igraph_real_t t = weight / VECTOR(degree)[from]; if (res) { MATRIX(*res, from, to) -= t; } if (sparseres) { IGRAPH_CHECK(igraph_sparsemat_entry(sparseres, (int) from, (int) to, -t)); } } IGRAPH_EIT_NEXT(edgeit); } } } else { /* undirected */ if (!normalized) { while (!IGRAPH_EIT_END(edgeit)) { long int edge = IGRAPH_EIT_GET(edgeit); long int from = IGRAPH_FROM(graph, edge); long int to = IGRAPH_TO (graph, edge); igraph_real_t weight = VECTOR(*weights)[edge]; if (from != to) { if (res) { MATRIX(*res, from, to) -= weight; MATRIX(*res, to, from) -= weight; } if (sparseres) { IGRAPH_CHECK(igraph_sparsemat_entry(sparseres, (int) from, (int) to, -weight)); IGRAPH_CHECK(igraph_sparsemat_entry(sparseres, (int) to, (int) from, -weight)); } VECTOR(degree)[from] += weight; VECTOR(degree)[to] += weight; } IGRAPH_EIT_NEXT(edgeit); } /* And the diagonal */ for (i = 0; i < no_of_nodes; i++) { if (res) { MATRIX(*res, i, i) = VECTOR(degree)[i]; } if (sparseres) { IGRAPH_CHECK(igraph_sparsemat_entry(sparseres, (int) i, (int) i, VECTOR(degree)[i])); } } } else { /* normalized */ while (!IGRAPH_EIT_END(edgeit)) { long int edge = IGRAPH_EIT_GET(edgeit); long int from = IGRAPH_FROM(graph, edge); long int to = IGRAPH_TO (graph, edge); igraph_real_t weight = VECTOR(*weights)[edge]; if (from != to) { VECTOR(degree)[from] += weight; VECTOR(degree)[to] += weight; } IGRAPH_EIT_NEXT(edgeit); } for (i = 0; i < no_of_nodes; i++) { int t = VECTOR(degree)[i] > 0 ? 1 : 0; if (res) { MATRIX(*res, i, i) = t; } if (sparseres) { IGRAPH_CHECK(igraph_sparsemat_entry(sparseres, (int) i, (int) i, t)); } VECTOR(degree)[i] = sqrt(VECTOR(degree)[i]); } IGRAPH_EIT_RESET(edgeit); while (!IGRAPH_EIT_END(edgeit)) { long int edge = IGRAPH_EIT_GET(edgeit); long int from = IGRAPH_FROM(graph, edge); long int to = IGRAPH_TO (graph, edge); igraph_real_t weight = VECTOR(*weights)[edge]; if (from != to) { double diff = weight / (VECTOR(degree)[from] * VECTOR(degree)[to]); if (res) { MATRIX(*res, from, to) -= diff; MATRIX(*res, to, from) -= diff; } if (sparseres) { IGRAPH_CHECK(igraph_sparsemat_entry(sparseres, (int) from, (int) to, -diff)); IGRAPH_CHECK(igraph_sparsemat_entry(sparseres, (int) to, (int) from, -diff)); } } IGRAPH_EIT_NEXT(edgeit); } } } igraph_vector_destroy(°ree); igraph_eit_destroy(&edgeit); IGRAPH_FINALLY_CLEAN(2); return 0; } /** * \function igraph_laplacian * \brief Returns the Laplacian matrix of a graph * * * The graph Laplacian matrix is similar to an adjacency matrix but * contains -1's instead of 1's and the vertex degrees are included in * the diagonal. So the result for edge i--j is -1 if i!=j and is equal * to the degree of vertex i if i==j. igraph_laplacian will work on a * directed graph; in this case, the diagonal will contain the out-degrees. * Loop edges will be ignored. * * * The normalized version of the Laplacian matrix has 1 in the diagonal and * -1/sqrt(d[i]d[j]) if there is an edge from i to j. * * * The first version of this function was written by Vincent Matossian. * \param graph Pointer to the graph to convert. * \param res Pointer to an initialized matrix object, the result is * stored here. It will be resized if needed. * If it is a null pointer, then it is ignored. * At least one of \p res and \p sparseres must be a non-null pointer. * \param sparseres Pointer to an initialized sparse matrix object, the * result is stored here, if it is not a null pointer. * At least one of \p res and \p sparseres must be a non-null pointer. * \param normalized Whether to create a normalized Laplacian matrix. * \param weights An optional vector containing edge weights, to calculate * the weighted Laplacian matrix. Set it to a null pointer to * calculate the unweighted Laplacian. * \return Error code. * * Time complexity: O(|V||V|), * |V| is the * number of vertices in the graph. * * \example examples/simple/igraph_laplacian.c */ int igraph_laplacian(const igraph_t *graph, igraph_matrix_t *res, igraph_sparsemat_t *sparseres, igraph_bool_t normalized, const igraph_vector_t *weights) { igraph_eit_t edgeit; int no_of_nodes = (int) igraph_vcount(graph); int no_of_edges = (int) igraph_ecount(graph); igraph_bool_t directed = igraph_is_directed(graph); int from, to; igraph_integer_t ffrom, fto; igraph_vector_t degree; int i; if (!res && !sparseres) { IGRAPH_ERROR("Laplacian: give at least one of `res' or `sparseres'", IGRAPH_EINVAL); } if (weights) { return igraph_i_weighted_laplacian(graph, res, sparseres, normalized, weights); } if (res) { IGRAPH_CHECK(igraph_matrix_resize(res, no_of_nodes, no_of_nodes)); igraph_matrix_null(res); } if (sparseres) { int nz = directed ? no_of_edges + no_of_nodes : no_of_edges * 2 + no_of_nodes; IGRAPH_CHECK(igraph_sparsemat_resize(sparseres, no_of_nodes, no_of_nodes, nz)); } IGRAPH_CHECK(igraph_eit_create(graph, igraph_ess_all(0), &edgeit)); IGRAPH_FINALLY(igraph_eit_destroy, &edgeit); IGRAPH_VECTOR_INIT_FINALLY(°ree, no_of_nodes); IGRAPH_CHECK(igraph_degree(graph, °ree, igraph_vss_all(), IGRAPH_OUT, IGRAPH_NO_LOOPS)); if (directed) { if (!normalized) { for (i = 0; i < no_of_nodes; i++) { if (res) { MATRIX(*res, i, i) = VECTOR(degree)[i]; } if (sparseres) { IGRAPH_CHECK(igraph_sparsemat_entry(sparseres, i, i, VECTOR(degree)[i])); } } while (!IGRAPH_EIT_END(edgeit)) { igraph_edge(graph, IGRAPH_EIT_GET(edgeit), &ffrom, &fto); from = ffrom; to = fto; if (from != to) { if (res) { MATRIX(*res, from, to) -= 1; } if (sparseres) { IGRAPH_CHECK(igraph_sparsemat_entry(sparseres, from, to, -1.0)); } } IGRAPH_EIT_NEXT(edgeit); } } else { for (i = 0; i < no_of_nodes; i++) { int t = VECTOR(degree)[i] > 0 ? 1 : 0; if (res) { MATRIX(*res, i, i) = t; } if (sparseres) { IGRAPH_CHECK(igraph_sparsemat_entry(sparseres, i, i, t)); } if (VECTOR(degree)[i] > 0) { VECTOR(degree)[i] = 1.0 / VECTOR(degree)[i]; } } while (!IGRAPH_EIT_END(edgeit)) { igraph_edge(graph, IGRAPH_EIT_GET(edgeit), &ffrom, &fto); from = ffrom; to = fto; if (from != to) { if (res) { MATRIX(*res, from, to) -= VECTOR(degree)[from]; } if (sparseres) { IGRAPH_CHECK(igraph_sparsemat_entry(sparseres, from, to, -VECTOR(degree)[from])); } } IGRAPH_EIT_NEXT(edgeit); } } } else { if (!normalized) { for (i = 0; i < no_of_nodes; i++) { if (res) { MATRIX(*res, i, i) = VECTOR(degree)[i]; } if (sparseres) { IGRAPH_CHECK(igraph_sparsemat_entry(sparseres, i, i, VECTOR(degree)[i])); } } while (!IGRAPH_EIT_END(edgeit)) { igraph_edge(graph, IGRAPH_EIT_GET(edgeit), &ffrom, &fto); from = ffrom; to = fto; if (from != to) { if (res) { MATRIX(*res, to, from) -= 1; MATRIX(*res, from, to) -= 1; } if (sparseres) { IGRAPH_CHECK(igraph_sparsemat_entry(sparseres, to, from, -1.0)); IGRAPH_CHECK(igraph_sparsemat_entry(sparseres, from, to, -1.0)); } } IGRAPH_EIT_NEXT(edgeit); } } else { for (i = 0; i < no_of_nodes; i++) { int t = VECTOR(degree)[i] > 0 ? 1 : 0; if (res) { MATRIX(*res, i, i) = t; } if (sparseres) { IGRAPH_CHECK(igraph_sparsemat_entry(sparseres, i, i, t)); } VECTOR(degree)[i] = sqrt(VECTOR(degree)[i]); } while (!IGRAPH_EIT_END(edgeit)) { igraph_edge(graph, IGRAPH_EIT_GET(edgeit), &ffrom, &fto); from = ffrom; to = fto; if (from != to) { double diff = 1.0 / (VECTOR(degree)[from] * VECTOR(degree)[to]); if (res) { MATRIX(*res, from, to) -= diff; MATRIX(*res, to, from) -= diff; } if (sparseres) { IGRAPH_CHECK(igraph_sparsemat_entry(sparseres, from, to, -diff)); IGRAPH_CHECK(igraph_sparsemat_entry(sparseres, to, from, -diff)); } } IGRAPH_EIT_NEXT(edgeit); } } } igraph_vector_destroy(°ree); igraph_eit_destroy(&edgeit); IGRAPH_FINALLY_CLEAN(2); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/visitors.c0000644000076500000240000005176213614300625023437 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph R package. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_visitor.h" #include "igraph_memory.h" #include "igraph_adjlist.h" #include "igraph_interface.h" #include "igraph_dqueue.h" #include "igraph_stack.h" #include "config.h" /** * \function igraph_bfs * Breadth-first search * * A simple breadth-first search, with a lot of different results and * the possibility to call a callback whenever a vertex is visited. * It is allowed to supply null pointers as the output arguments the * user is not interested in, in this case they will be ignored. * * * If not all vertices can be reached from the supplied root vertex, * then additional root vertices will be used, in the order of their * vertex ids. * \param graph The input graph. * \param root The id of the root vertex. It is ignored if the \c * roots argument is not a null pointer. * \param roots Pointer to an initialized vector, or a null * pointer. If not a null pointer, then it is a vector * containing root vertices to start the BFS from. The vertices * are considered in the order they appear. If a root vertex * was already found while searching from another one, then no * search is conducted from it. * \param mode For directed graphs, it defines which edges to follow. * \c IGRAPH_OUT means following the direction of the edges, * \c IGRAPH_IN means the opposite, and * \c IGRAPH_ALL ignores the direction of the edges. * This parameter is ignored for undirected graphs. * \param unreachable Logical scalar, whether the search should visit * the vertices that are unreachable from the given root * node(s). If true, then additional searches are performed * until all vertices are visited. * \param restricted If not a null pointer, then it must be a pointer * to a vector containing vertex ids. The BFS is carried out * only on these vertices. * \param order If not null pointer, then the vertex ids of the graph are * stored here, in the same order as they were visited. * \param rank If not a null pointer, then the rank of each vertex is * stored here. * \param father If not a null pointer, then the id of the father of * each vertex is stored here. * \param pred If not a null pointer, then the id of vertex that was * visited before the current one is stored here. If there is * no such vertex (the current vertex is the root of a search * tree), then -1 is stored. * \param succ If not a null pointer, then the id of the vertex that * was visited after the current one is stored here. If there * is no such vertex (the current one is the last in a search * tree), then -1 is stored. * \param dist If not a null pointer, then the distance from the root of * the current search tree is stored here. * \param callback If not null, then it should be a pointer to a * function of type \ref igraph_bfshandler_t. This function * will be called, whenever a new vertex is visited. * \param extra Extra argument to pass to the callback function. * \return Error code. * * Time complexity: O(|V|+|E|), linear in the number of vertices and * edges. * * \example examples/simple/igraph_bfs.c * \example examples/simple/igraph_bfs2.c */ int igraph_bfs(const igraph_t *graph, igraph_integer_t root, const igraph_vector_t *roots, igraph_neimode_t mode, igraph_bool_t unreachable, const igraph_vector_t *restricted, igraph_vector_t *order, igraph_vector_t *rank, igraph_vector_t *father, igraph_vector_t *pred, igraph_vector_t *succ, igraph_vector_t *dist, igraph_bfshandler_t *callback, void *extra) { igraph_dqueue_t Q; long int no_of_nodes = igraph_vcount(graph); long int actroot = 0; igraph_vector_char_t added; igraph_lazy_adjlist_t adjlist; long int act_rank = 0; long int pred_vec = -1; long int rootpos = 0; long int noroots = roots ? igraph_vector_size(roots) : 1; if (!roots && (root < 0 || root >= no_of_nodes)) { IGRAPH_ERROR("Invalid root vertex in BFS", IGRAPH_EINVAL); } if (roots) { igraph_real_t min, max; igraph_vector_minmax(roots, &min, &max); if (min < 0 || max >= no_of_nodes) { IGRAPH_ERROR("Invalid root vertex in BFS", IGRAPH_EINVAL); } } if (restricted) { igraph_real_t min, max; igraph_vector_minmax(restricted, &min, &max); if (min < 0 || max >= no_of_nodes) { IGRAPH_ERROR("Invalid vertex id in restricted set", IGRAPH_EINVAL); } } if (mode != IGRAPH_OUT && mode != IGRAPH_IN && mode != IGRAPH_ALL) { IGRAPH_ERROR("Invalid mode argument", IGRAPH_EINVMODE); } if (!igraph_is_directed(graph)) { mode = IGRAPH_ALL; } IGRAPH_CHECK(igraph_vector_char_init(&added, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_char_destroy, &added); IGRAPH_CHECK(igraph_dqueue_init(&Q, 100)); IGRAPH_FINALLY(igraph_dqueue_destroy, &Q); IGRAPH_CHECK(igraph_lazy_adjlist_init(graph, &adjlist, mode, /*simplify=*/ 0)); IGRAPH_FINALLY(igraph_lazy_adjlist_destroy, &adjlist); /* Mark the vertices that are not in the restricted set, as already found. Special care must be taken for vertices that are not in the restricted set, but are to be used as 'root' vertices. */ if (restricted) { long int i, n = igraph_vector_size(restricted); igraph_vector_char_fill(&added, 1); for (i = 0; i < n; i++) { long int v = (long int) VECTOR(*restricted)[i]; VECTOR(added)[v] = 0; } } /* Resize result vectors, and fill them with IGRAPH_NAN */ # define VINIT(v) if (v) { \ igraph_vector_resize((v), no_of_nodes); \ igraph_vector_fill((v), IGRAPH_NAN); } VINIT(order); VINIT(rank); VINIT(father); VINIT(pred); VINIT(succ); VINIT(dist); # undef VINIT while (1) { /* Get the next root vertex, if any */ if (roots && rootpos < noroots) { /* We are still going through the 'roots' vector */ actroot = (long int) VECTOR(*roots)[rootpos++]; } else if (!roots && rootpos == 0) { /* We have a single root vertex given, and start now */ actroot = root; rootpos++; } else if (rootpos == noroots && unreachable) { /* We finished the given root(s), but other vertices are also tried as root */ actroot = 0; rootpos++; } else if (unreachable && actroot + 1 < no_of_nodes) { /* We are already doing the other vertices, take the next one */ actroot++; } else { /* No more root nodes to do */ break; } /* OK, we have a new root, start BFS */ if (VECTOR(added)[actroot]) { continue; } IGRAPH_CHECK(igraph_dqueue_push(&Q, actroot)); IGRAPH_CHECK(igraph_dqueue_push(&Q, 0)); VECTOR(added)[actroot] = 1; if (father) { VECTOR(*father)[actroot] = -1; } pred_vec = -1; while (!igraph_dqueue_empty(&Q)) { long int actvect = (long int) igraph_dqueue_pop(&Q); long int actdist = (long int) igraph_dqueue_pop(&Q); long int succ_vec; igraph_vector_t *neis = igraph_lazy_adjlist_get(&adjlist, (igraph_integer_t) actvect); long int i, n = igraph_vector_size(neis); if (pred) { VECTOR(*pred)[actvect] = pred_vec; } if (rank) { VECTOR(*rank) [actvect] = act_rank; } if (order) { VECTOR(*order)[act_rank++] = actvect; } if (dist) { VECTOR(*dist)[actvect] = actdist; } for (i = 0; i < n; i++) { long int nei = (long int) VECTOR(*neis)[i]; if (! VECTOR(added)[nei]) { VECTOR(added)[nei] = 1; IGRAPH_CHECK(igraph_dqueue_push(&Q, nei)); IGRAPH_CHECK(igraph_dqueue_push(&Q, actdist + 1)); if (father) { VECTOR(*father)[nei] = actvect; } } } succ_vec = igraph_dqueue_empty(&Q) ? -1L : (long int) igraph_dqueue_head(&Q); if (callback) { igraph_bool_t terminate = callback(graph, (igraph_integer_t) actvect, (igraph_integer_t) pred_vec, (igraph_integer_t) succ_vec, (igraph_integer_t) act_rank - 1, (igraph_integer_t) actdist, extra); if (terminate) { igraph_lazy_adjlist_destroy(&adjlist); igraph_dqueue_destroy(&Q); igraph_vector_char_destroy(&added); IGRAPH_FINALLY_CLEAN(3); return 0; } } if (succ) { VECTOR(*succ)[actvect] = succ_vec; } pred_vec = actvect; } /* while Q !empty */ } /* for actroot < no_of_nodes */ igraph_lazy_adjlist_destroy(&adjlist); igraph_dqueue_destroy(&Q); igraph_vector_char_destroy(&added); IGRAPH_FINALLY_CLEAN(3); return 0; } /** * \function igraph_i_bfs * \ingroup internal * * Added in version 0.2. * * TODO */ int igraph_i_bfs(igraph_t *graph, igraph_integer_t vid, igraph_neimode_t mode, igraph_vector_t *vids, igraph_vector_t *layers, igraph_vector_t *parents) { igraph_dqueue_t q; long int vidspos = 0; igraph_vector_t neis; long int no_of_nodes = igraph_vcount(graph); long int i; char *added; long int lastlayer = -1; if (!igraph_is_directed(graph)) { mode = IGRAPH_ALL; } if (mode != IGRAPH_OUT && mode != IGRAPH_IN && mode != IGRAPH_ALL) { IGRAPH_ERROR("Invalid mode argument", IGRAPH_EINVMODE); } /* temporary storage */ added = igraph_Calloc(no_of_nodes, char); if (added == 0) { IGRAPH_ERROR("Cannot calculate BFS", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, added); IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); IGRAPH_CHECK(igraph_dqueue_init(&q, 100)); IGRAPH_FINALLY(igraph_dqueue_destroy, &q); /* results */ IGRAPH_CHECK(igraph_vector_resize(vids, no_of_nodes)); igraph_vector_clear(layers); IGRAPH_CHECK(igraph_vector_resize(parents, no_of_nodes)); /* ok start with vid */ IGRAPH_CHECK(igraph_dqueue_push(&q, vid)); IGRAPH_CHECK(igraph_dqueue_push(&q, 0)); IGRAPH_CHECK(igraph_vector_push_back(layers, vidspos)); VECTOR(*vids)[vidspos++] = vid; VECTOR(*parents)[(long int)vid] = vid; added[(long int)vid] = 1; while (!igraph_dqueue_empty(&q)) { long int actvect = (long int) igraph_dqueue_pop(&q); long int actdist = (long int) igraph_dqueue_pop(&q); IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) actvect, mode)); for (i = 0; i < igraph_vector_size(&neis); i++) { long int neighbor = (long int) VECTOR(neis)[i]; if (added[neighbor] == 0) { added[neighbor] = 1; VECTOR(*parents)[neighbor] = actvect; IGRAPH_CHECK(igraph_dqueue_push(&q, neighbor)); IGRAPH_CHECK(igraph_dqueue_push(&q, actdist + 1)); if (lastlayer != actdist + 1) { IGRAPH_CHECK(igraph_vector_push_back(layers, vidspos)); } VECTOR(*vids)[vidspos++] = neighbor; lastlayer = actdist + 1; } } /* for i in neis */ } /* while ! dqueue_empty */ IGRAPH_CHECK(igraph_vector_push_back(layers, vidspos)); igraph_vector_destroy(&neis); igraph_dqueue_destroy(&q); igraph_Free(added); IGRAPH_FINALLY_CLEAN(3); return 0; } /** * \function igraph_dfs * Depth-first search * * A simple depth-first search, with * the possibility to call a callback whenever a vertex is discovered * and/or whenever a subtree is finished. * It is allowed to supply null pointers as the output arguments the * user is not interested in, in this case they will be ignored. * * * If not all vertices can be reached from the supplied root vertex, * then additional root vertices will be used, in the order of their * vertex ids. * \param graph The input graph. * \param root The id of the root vertex. * \param mode For directed graphs, it defines which edges to follow. * \c IGRAPH_OUT means following the direction of the edges, * \c IGRAPH_IN means the opposite, and * \c IGRAPH_ALL ignores the direction of the edges. * This parameter is ignored for undirected graphs. * \param unreachable Logical scalar, whether the search should visit * the vertices that are unreachable from the given root * node(s). If true, then additional searches are performed * until all vertices are visited. * \param order If not null pointer, then the vertex ids of the graph are * stored here, in the same order as they were discovered. * \param order_out If not a null pointer, then the vertex ids of the * graphs are stored here, in the order of the completion of * their subtree. * \param father If not a null pointer, then the id of the father of * each vertex is stored here. * \param dist If not a null pointer, then the distance from the root of * the current search tree is stored here. * \param in_callback If not null, then it should be a pointer to a * function of type \ref igraph_dfshandler_t. This function * will be called, whenever a new vertex is discovered. * \param out_callback If not null, then it should be a pointer to a * function of type \ref igraph_dfshandler_t. This function * will be called, whenever the subtree of a vertex is completed. * \param extra Extra argument to pass to the callback function(s). * \return Error code. * * Time complexity: O(|V|+|E|), linear in the number of vertices and * edges. */ int igraph_dfs(const igraph_t *graph, igraph_integer_t root, igraph_neimode_t mode, igraph_bool_t unreachable, igraph_vector_t *order, igraph_vector_t *order_out, igraph_vector_t *father, igraph_vector_t *dist, igraph_dfshandler_t *in_callback, igraph_dfshandler_t *out_callback, void *extra) { long int no_of_nodes = igraph_vcount(graph); igraph_lazy_adjlist_t adjlist; igraph_stack_t stack; igraph_vector_char_t added; igraph_vector_long_t nptr; long int actroot; long int act_rank = 0; long int rank_out = 0; long int act_dist = 0; if (root < 0 || root >= no_of_nodes) { IGRAPH_ERROR("Invalid root vertex for DFS", IGRAPH_EINVAL); } if (mode != IGRAPH_OUT && mode != IGRAPH_IN && mode != IGRAPH_ALL) { IGRAPH_ERROR("Invalid mode argument", IGRAPH_EINVMODE); } if (!igraph_is_directed(graph)) { mode = IGRAPH_ALL; } IGRAPH_CHECK(igraph_vector_char_init(&added, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_char_destroy, &added); IGRAPH_CHECK(igraph_stack_init(&stack, 100)); IGRAPH_FINALLY(igraph_stack_destroy, &stack); IGRAPH_CHECK(igraph_lazy_adjlist_init(graph, &adjlist, mode, /*simplify=*/ 0)); IGRAPH_FINALLY(igraph_lazy_adjlist_destroy, &adjlist); IGRAPH_CHECK(igraph_vector_long_init(&nptr, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_long_destroy, &nptr); # define FREE_ALL() do { \ igraph_vector_long_destroy(&nptr); \ igraph_lazy_adjlist_destroy(&adjlist); \ igraph_stack_destroy(&stack); \ igraph_vector_char_destroy(&added); \ IGRAPH_FINALLY_CLEAN(4); } while (0) /* Resize result vectors and fill them with IGRAPH_NAN */ # define VINIT(v) if (v) { \ igraph_vector_resize(v, no_of_nodes); \ igraph_vector_fill(v, IGRAPH_NAN); } VINIT(order); VINIT(order_out); VINIT(father); VINIT(dist); # undef VINIT IGRAPH_CHECK(igraph_stack_push(&stack, root)); VECTOR(added)[(long int)root] = 1; if (father) { VECTOR(*father)[(long int)root] = -1; } if (order) { VECTOR(*order)[act_rank++] = root; } if (dist) { VECTOR(*dist)[(long int)root] = 0; } if (in_callback) { igraph_bool_t terminate = in_callback(graph, root, 0, extra); if (terminate) { FREE_ALL(); return 0; } } for (actroot = 0; actroot < no_of_nodes; ) { /* 'root' first, then all other vertices */ if (igraph_stack_empty(&stack)) { if (!unreachable) { break; } if (VECTOR(added)[actroot]) { actroot++; continue; } IGRAPH_CHECK(igraph_stack_push(&stack, actroot)); VECTOR(added)[actroot] = 1; if (father) { VECTOR(*father)[actroot] = -1; } if (order) { VECTOR(*order)[act_rank++] = actroot; } if (dist) { VECTOR(*dist)[actroot] = 0; } if (in_callback) { igraph_bool_t terminate = in_callback(graph, (igraph_integer_t) actroot, 0, extra); if (terminate) { FREE_ALL(); return 0; } } actroot++; } while (!igraph_stack_empty(&stack)) { long int actvect = (long int) igraph_stack_top(&stack); igraph_vector_t *neis = igraph_lazy_adjlist_get(&adjlist, (igraph_integer_t) actvect); long int n = igraph_vector_size(neis); long int *ptr = igraph_vector_long_e_ptr(&nptr, actvect); /* Search for a neighbor that was not yet visited */ igraph_bool_t any = 0; long int nei; while (!any && (*ptr) < n) { nei = (long int) VECTOR(*neis)[(*ptr)]; any = !VECTOR(added)[nei]; (*ptr) ++; } if (any) { /* There is such a neighbor, add it */ IGRAPH_CHECK(igraph_stack_push(&stack, nei)); VECTOR(added)[nei] = 1; if (father) { VECTOR(*father)[ nei ] = actvect; } if (order) { VECTOR(*order)[act_rank++] = nei; } act_dist++; if (dist) { VECTOR(*dist)[nei] = act_dist; } if (in_callback) { igraph_bool_t terminate = in_callback(graph, (igraph_integer_t) nei, (igraph_integer_t) act_dist, extra); if (terminate) { FREE_ALL(); return 0; } } } else { /* There is no such neighbor, finished with the subtree */ igraph_stack_pop(&stack); if (order_out) { VECTOR(*order_out)[rank_out++] = actvect; } act_dist--; if (out_callback) { igraph_bool_t terminate = out_callback(graph, (igraph_integer_t) actvect, (igraph_integer_t) act_dist, extra); if (terminate) { FREE_ALL(); return 0; } } } } } FREE_ALL(); # undef FREE_ALL return 0; } python-igraph-0.8.0/vendor/source/igraph/src/walktrap_graph.cpp0000644000076500000240000001532313614300625025114 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ /* The original version of this file was written by Pascal Pons The original copyright notice follows here. The FSF address was fixed by Tamas Nepusz */ // File: graph.cpp //----------------------------------------------------------------------------- // Walktrap v0.2 -- Finds community structure of networks using random walks // Copyright (C) 2004-2005 Pascal Pons // // This program is free software; you can redistribute it and/or modify // it under the terms of the GNU General Public License as published by // the Free Software Foundation; either version 2 of the License, or // (at your option) any later version. // // This program is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU General Public License for more details. // // You should have received a copy of the GNU General Public License // along with this program; if not, write to the Free Software // Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA // 02110-1301 USA //----------------------------------------------------------------------------- // Author : Pascal Pons // Email : pascal.pons@gmail.com // Web page : http://www-rp.lip6.fr/~latapy/PP/walktrap.html // Location : Paris, France // Time : June 2005 //----------------------------------------------------------------------------- // see readme.txt for more details #include #include #include #include #include // strlen #include "walktrap_graph.h" #include "igraph_interface.h" using namespace std; namespace igraph { namespace walktrap { bool operator<(const Edge& E1, const Edge& E2) { return (E1.neighbor < E2.neighbor); } Vertex::Vertex() { degree = 0; edges = 0; total_weight = 0.; } Vertex::~Vertex() { if (edges) { delete[] edges; } } Graph::Graph() { nb_vertices = 0; nb_edges = 0; vertices = 0; index = 0; total_weight = 0.; } Graph::~Graph () { if (vertices) { delete[] vertices; } } class Edge_list { public: int* V1; int* V2; float* W; int size; int size_max; void add(int v1, int v2, float w); Edge_list() { size = 0; size_max = 1024; V1 = new int[1024]; V2 = new int[1024]; W = new float[1024]; } ~Edge_list() { if (V1) { delete[] V1; } if (V2) { delete[] V2; } if (W) { delete[] W; } } }; void Edge_list::add(int v1, int v2, float w) { if (size == size_max) { int* tmp1 = new int[2 * size_max]; int* tmp2 = new int[2 * size_max]; float* tmp3 = new float[2 * size_max]; for (int i = 0; i < size_max; i++) { tmp1[i] = V1[i]; tmp2[i] = V2[i]; tmp3[i] = W[i]; } delete[] V1; delete[] V2; delete[] W; V1 = tmp1; V2 = tmp2; W = tmp3; size_max *= 2; } V1[size] = v1; V2[size] = v2; W[size] = w; size++; } int Graph::convert_from_igraph(const igraph_t *graph, const igraph_vector_t *weights) { Graph &G = *this; int max_vertex = (int)igraph_vcount(graph) - 1; long int no_of_edges = (long int)igraph_ecount(graph); long int i; long int deg; double w; Edge_list EL; for (i = 0; i < no_of_edges; i++) { igraph_integer_t from, to; int v1, v2; w = weights ? VECTOR(*weights)[i] : 1.0; igraph_edge(graph, i, &from, &to); v1 = (int)from; v2 = (int)to; EL.add(v1, v2, w); } G.nb_vertices = max_vertex + 1; G.vertices = new Vertex[G.nb_vertices]; G.nb_edges = 0; G.total_weight = 0.0; for (int i = 0; i < EL.size; i++) { G.vertices[EL.V1[i]].degree++; G.vertices[EL.V2[i]].degree++; G.vertices[EL.V1[i]].total_weight += EL.W[i]; G.vertices[EL.V2[i]].total_weight += EL.W[i]; G.nb_edges++; G.total_weight += EL.W[i]; } for (int i = 0; i < G.nb_vertices; i++) { deg = G.vertices[i].degree; w = (deg == 0) ? 1.0 : (G.vertices[i].total_weight / double(deg)); G.vertices[i].edges = new Edge[deg + 1]; G.vertices[i].edges[0].neighbor = i; G.vertices[i].edges[0].weight = w; G.vertices[i].total_weight += w; G.vertices[i].degree = 1; } for (int i = 0; i < EL.size; i++) { G.vertices[EL.V1[i]].edges[G.vertices[EL.V1[i]].degree].neighbor = EL.V2[i]; G.vertices[EL.V1[i]].edges[G.vertices[EL.V1[i]].degree].weight = EL.W[i]; G.vertices[EL.V1[i]].degree++; G.vertices[EL.V2[i]].edges[G.vertices[EL.V2[i]].degree].neighbor = EL.V1[i]; G.vertices[EL.V2[i]].edges[G.vertices[EL.V2[i]].degree].weight = EL.W[i]; G.vertices[EL.V2[i]].degree++; } for (int i = 0; i < G.nb_vertices; i++) { sort(G.vertices[i].edges, G.vertices[i].edges + G.vertices[i].degree); } for (int i = 0; i < G.nb_vertices; i++) { // merge multi edges int a = 0; for (int b = 1; b < G.vertices[i].degree; b++) { if (G.vertices[i].edges[b].neighbor == G.vertices[i].edges[a].neighbor) { G.vertices[i].edges[a].weight += G.vertices[i].edges[b].weight; } else { G.vertices[i].edges[++a] = G.vertices[i].edges[b]; } } G.vertices[i].degree = a + 1; } return 0; } long Graph::memory() { size_t m = 0; m += size_t(nb_vertices) * sizeof(Vertex); m += 2 * size_t(nb_edges) * sizeof(Edge); m += sizeof(Graph); if (index != 0) { m += size_t(nb_vertices) * sizeof(char*); for (int i = 0; i < nb_vertices; i++) { m += strlen(index[i]) + 1; } } return m; } } } python-igraph-0.8.0/vendor/source/igraph/src/gengraph_qsort.h0000644000076500000240000003347413614300625024605 0ustar tamasstaff00000000000000/* * * gengraph - generation of random simple connected graphs with prescribed * degree sequence * * Copyright (C) 2006 Fabien Viger * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #ifndef QSORT_H #define QSORT_H #include #include #ifndef register #define register #endif namespace gengraph { //___________________________________________________________________________ // check if every element is zero inline bool check_zero(int *mem, int n) { for (int *v = mem + n; v != mem; ) if (*(--v) != 0) { return false; } return true; } //___________________________________________________________________________ // Sort simple integer arrays in ASCENDING order //___________________________________________________________________________ inline int med3(int a, int b, int c) { if (a < b) { if (c < b) { return (a < c) ? c : a; } else { return b; } } else { if (c < a) { return (b < c) ? c : b; } else { return a; } } } inline void isort(int *v, int t) { if (t < 2) { return; } for (int i = 1; i < t; i++) { register int *w = v + i; int tmp = *w; while (w != v && *(w - 1) > tmp) { *w = *(w - 1); w--; } *w = tmp; } } inline int partitionne(int *v, int t, int p) { int i = 0; int j = t - 1; while (i < j) { while (i <= j && v[i] < p) { i++; } while (i <= j && v[j] > p) { j--; } if (i < j) { int tmp = v[i]; v[i++] = v[j]; v[j--] = tmp; } } if (i == j && v[i] < p) { i++; } assert(i != 0 && i != t); return i; } inline void qsort(int *v, int t) { if (t < 15) { isort(v, t); } else { int x = partitionne(v, t, med3(v[t >> 1], v[(t >> 2) + 2], v[t - (t >> 1) - 2])); qsort(v, x); qsort(v + x, t - x); } } inline int qsort_median(int *v, int t, int pos) { if (t < 10) { isort(v, t); return v[pos]; } int x = partitionne(v, t, med3(v[t >> 1], v[(t >> 2) + 2], v[t - (t >> 1) - 2])); if (pos < x) { return qsort_median(v, x, pos); } else { return qsort_median(v + x, t - x, pos - x); } } inline int qsort_median(int *v, int t) { return qsort_median(v, t, t / 2); } //___________________________________________________________________________ // Sort simple double arrays in ASCENDING order //___________________________________________________________________________ inline double med3(double a, double b, double c) { if (a < b) { if (c < b) { return (a < c) ? c : a; } else { return b; } } else { if (c < a) { return (b < c) ? c : b; } else { return a; } } } inline void isort(double *v, int t) { if (t < 2) { return; } for (int i = 1; i < t; i++) { register double *w = v + i; double tmp = *w; while (w != v && *(w - 1) > tmp) { *w = *(w - 1); w--; } *w = tmp; } } inline int partitionne(double *v, int t, double p) { int i = 0; int j = t - 1; while (i < j) { while (i <= j && v[i] < p) { i++; } while (i <= j && v[j] > p) { j--; } if (i < j) { double tmp = v[i]; v[i++] = v[j]; v[j--] = tmp; } } if (i == j && v[i] < p) { i++; } assert(i != 0 && i != t); return i; } inline void qsort(double *v, int t) { if (t < 15) { isort(v, t); } else { int x = partitionne(v, t, med3(v[t >> 1], v[(t >> 2) + 2], v[t - (t >> 1) - 2])); qsort(v, x); qsort(v + x, t - x); } } inline double qsort_median(double *v, int t, int pos) { if (t < 10) { isort(v, t); return v[pos]; } int x = partitionne(v, t, med3(v[t >> 1], v[(t >> 2) + 2], v[t - (t >> 1) - 2])); if (pos < x) { return qsort_median(v, x, pos); } else { return qsort_median(v + x, t - x, pos - x); } } inline double qsort_median(double *v, int t) { return qsort_median(v, t, t / 2); } //___________________________________________________________________________ // Sort integer arrays according to value stored in mem[], in ASCENDING order inline void isort(int *mem, int *v, int t) { if (t < 2) { return; } for (int i = 1; i < t; i++) { int vtmp = v[i]; int tmp = mem[vtmp]; int j; for (j = i; j > 0 && tmp < mem[v[j - 1]]; j--) { v[j] = v[j - 1]; } v[j] = vtmp; } } inline void qsort(int *mem, int *v, int t) { if (t < 15) { isort(mem, v, t); } else { int p = med3(mem[v[t >> 1]], mem[v[(t >> 2) + 3]], mem[v[t - (t >> 1) - 3]]); int i = 0; int j = t - 1; while (i < j) { while (i <= j && mem[v[i]] < p) { i++; } while (i <= j && mem[v[j]] > p) { j--; } if (i < j) { int tmp = v[i]; v[i++] = v[j]; v[j--] = tmp; } } if (i == j && mem[v[i]] < p) { i++; } assert(i != 0 && i != t); qsort(mem, v, i); qsort(mem, v + i, t - i); } } //Box-Sort 1..n according to value stored in mem[], in DESCENDING order. inline int *pre_boxsort(int *mem, int n, int &offset) { int *yo; // maximum and minimum int mx = mem[0]; int mn = mem[0]; for (yo = mem + n - 1; yo != mem; yo--) { register int x = *yo; if (x > mx) { mx = x; } if (x < mn) { mn = x; } } // box int c = mx - mn + 1; int *box = new int[c]; for (yo = box + c; yo != box; * (--yo) = 0) { } for (yo = mem + n; yo != mem; box[*(--yo) - mn]++) { } // cumul sum int sum = 0; for (yo = box + c; yo != box; ) { sum += *(--yo); *yo = sum; } offset = mn; return box; } inline int *boxsort(int *mem, int n, int *buff = NULL) { int i; if (n <= 0) { return buff; } int offset = 0; int *box = pre_boxsort(mem, n, offset); // sort if (buff == NULL) { buff = new int[n]; } for (i = 0; i < n; i++) { buff[--box[mem[i] - offset]] = i; } // clean delete[] box; return buff; } // merge two sorted arays in their intersection. Store the result in first array, and return length inline int intersect(int *a, int a_len, int *b, int b_len) { if (a_len == 0 || b_len == 0) { return 0; } int *asup = a + a_len; int *bsup = b + b_len; int len = 0; int *p = a; do { if (*a == *b) { p[len++] = *a; } do if (++a == asup) { return len; } while (*a < *b); if (*a == *b) { p[len++] = *a; } do if (++b == bsup) { return len; } while (*b < *a); } while (true); } // merge two sorted arays in their union, store result in m inline int unify(int *m, int *a, int a_len, int *b, int b_len) { int *asup = a + a_len; int *bsup = b + b_len; int len = 0; while (a != asup && b != bsup) { if (*a < *b) { m[len++] = *(a++); } else { if (*a == *b) { a++; } m[len++] = *(b++); } } while (a != asup) { m[len++] = *(a++); } while (b != asup) { m[len++] = *(b++); } return len; } // lexicographic compare inline int lex_comp(int *v1, int *v2, int n) { int *stop = v1 + n; while (v1 != stop && *v1 == *v2) { v1++; v2++; }; if (v1 == stop) { return 0; } else if (*v1 < *v2) { return -1; } else { return 1; } } // lexicographic median of three inline int *lex_med3(int *a, int *b, int *c, int s) { int ab = lex_comp(a, b, s); if (ab == 0) { return a; } else { int cb = lex_comp(c, b, s); if (cb == 0) { return b; } int ca = lex_comp(c, a, s); if (ab < 0) { if (cb > 0) { return b; } else { return (ca > 0) ? c : a; } } else { if (cb < 0) { return b; } else { return (ca < 0) ? c : a; } } } } // Lexicographic sort inline void lex_isort(int **l, int *v, int t, int s) { if (t < 2) { return; } for (int i = 1; i < t; i++) { register int *w = v + i; int tmp = *w; while (w != v && lex_comp(l[tmp], l[*(w - 1)], s) < 0) { *w = *(w - 1); w--; } *w = tmp; } } #ifdef _STABLE_SORT_ONLY #define _CRITICAL_SIZE_QSORT 0x7FFFFFFF #warning "lex_qsort will be replaced by lex_isort" #else #define _CRITICAL_SIZE_QSORT 15 #endif inline void lex_qsort(int **l, int *v, int t, int s) { if (t < _CRITICAL_SIZE_QSORT) { lex_isort(l, v, t, s); } else { int *p = lex_med3(l[v[t >> 1]], l[v[(t >> 2) + 2]], l[v[t - (t >> 1) - 2]], s); int i = 0; int j = t - 1; // printf("pivot = %d\n",p); while (i < j) { // for(int k=0; k 0) { j--; } if (i < j) { // printf(" swap %d[%d] with %d[%d]\n",i,v[i],j,v[j]); int tmp = v[i]; v[i++] = v[j]; v[j--] = tmp; } } if (i == j && lex_comp(l[v[i]], p, s) < 0) { i++; } assert(i != 0 && i != t); lex_qsort(l, v, i, s); lex_qsort(l, v + i, t - i, s); } } // lexicographic indirect compare inline int lex_comp_indirect(int *key, int *v1, int *v2, int n) { int *stop = v1 + n; while (v1 != stop && key[*v1] == key[*v2]) { v1++; v2++; }; if (v1 == stop) { return 0; } else if (key[*v1] < key[*v2]) { return -1; } else { return 1; } } inline int qsort_min(const int a, const int b) { return a <= b ? a : b; } // mix indirect compare inline int mix_comp_indirect(int *key, int a, int b, int **neigh, int *degs) { if (key[a] < key[b]) { return -1; } else if (key[a] > key[b]) { return 1; } else { int cmp = lex_comp_indirect(key, neigh[a], neigh[b], qsort_min(degs[a], degs[b])); if (cmp == 0) { if (degs[a] > degs[b]) { return -1; } if (degs[a] < degs[b]) { return 1; } } return cmp; } } // lexicographic indirect median of three inline int mix_med3_indirect(int *key, int a, int b, int c, int **neigh, int *degs) { int ab = mix_comp_indirect(key, a, b, neigh, degs); if (ab == 0) { return a; } else { int cb = mix_comp_indirect(key, c, b, neigh, degs); if (cb == 0) { return b; } int ca = mix_comp_indirect(key, c, a, neigh, degs); if (ab < 0) { if (cb > 0) { return b; } else { return (ca > 0) ? c : a; } } else { if (cb < 0) { return b; } else { return (ca < 0) ? c : a; } } } } // Sort integer arrays in ASCENDING order inline void mix_isort_indirect(int *key, int *v, int t, int **neigh, int *degs) { if (t < 2) { return; } for (int i = 1; i < t; i++) { register int *w = v + i; int tmp = *w; while (w != v && mix_comp_indirect(key, tmp, *(w - 1), neigh, degs) < 0) { *w = *(w - 1); w--; } *w = tmp; } } inline void mix_qsort_indirect(int *key, int *v, int t, int **neigh, int *degs) { if (t < 15) { mix_isort_indirect(key, v, t, neigh, degs); } else { int p = mix_med3_indirect(key, v[t >> 1], v[(t >> 2) + 2], v[t - (t >> 1) - 2], neigh, degs); int i = 0; int j = t - 1; // printf("pivot = %d\n",p); while (i < j) { // for(int k=0; k 0) { j--; } if (i < j) { // printf(" swap %d[%d] with %d[%d]\n",i,v[i],j,v[j]); int tmp = v[i]; v[i++] = v[j]; v[j--] = tmp; } } if (i == j && mix_comp_indirect(key, v[i], p, neigh, degs) < 0) { i++; } assert(i != 0 && i != t); mix_qsort_indirect(key, v, i, neigh, degs); mix_qsort_indirect(key, v + i, t - i, neigh, degs); } } } // namespace gengraph #endif //QSORT_H python-igraph-0.8.0/vendor/source/igraph/src/drl_graph.cpp0000644000076500000240000012100413614300625024042 0ustar tamasstaff00000000000000/* * Copyright 2007 Sandia Corporation. Under the terms of Contract * DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains * certain rights in this software. * * All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are * met: * * * Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * Neither the name of Sandia National Laboratories nor the names of * its contributors may be used to endorse or promote products derived from * this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT * OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED * TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF * LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING * NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. */ // This file contains the member definitions of the master class #include #include #include #include #include #include #include using namespace std; #include "drl_graph.h" #include "igraph_random.h" #include "igraph_interface.h" #include "igraph_progress.h" #include "igraph_interrupt_internal.h" #ifdef MUSE_MPI #include #endif namespace drl { // constructor -- initializes the schedule variables (as in // graph constructor) // graph::graph ( int proc_id, int tot_procs, char *int_file ) // { // // MPI parameters // myid = proc_id; // num_procs = tot_procs; // // initial annealing parameters // STAGE = 0; // iterations = 0; // temperature = 2000; // attraction = 10; // damping_mult = 1.0; // min_edges = 20; // first_add = fine_first_add = true; // fineDensity = false; // // Brian's original Vx schedule // liquid.iterations = 200; // liquid.temperature = 2000; // liquid.attraction = 2; // liquid.damping_mult = 1.0; // liquid.time_elapsed = 0; // expansion.iterations = 200; // expansion.temperature = 2000; // expansion.attraction = 10; // expansion.damping_mult = 1.0; // expansion.time_elapsed = 0; // cooldown.iterations = 200; // cooldown.temperature = 2000; // cooldown.attraction = 1; // cooldown.damping_mult = .1; // cooldown.time_elapsed = 0; // crunch.iterations = 50; // crunch.temperature = 250; // crunch.attraction = 1; // crunch. damping_mult = .25; // crunch.time_elapsed = 0; // simmer.iterations = 100; // simmer.temperature = 250; // simmer.attraction = .5; // simmer.damping_mult = 0.0; // simmer.time_elapsed = 0; // // scan .int file for node info // scan_int ( int_file ); // // populate node positions and ids // positions.reserve ( num_nodes ); // map < int, int >::iterator cat_iter; // for ( cat_iter = id_catalog.begin(); // cat_iter != id_catalog.end(); // cat_iter++ ) // positions.push_back ( Node( cat_iter->first ) ); // /* // // output positions .ids for debugging // for ( int id = 0; id < num_nodes; id++ ) // cout << positions[id].id << endl; // */ // // read .int file for graph info // read_int ( int_file ); // // initialize density server // density_server.Init(); // } graph::graph(const igraph_t *igraph, const igraph_layout_drl_options_t *options, const igraph_vector_t *weights) { myid = 0; num_procs = 1; STAGE = 0; iterations = options->init_iterations; temperature = options->init_temperature; attraction = options->init_attraction; damping_mult = options->init_damping_mult; min_edges = 20; first_add = fine_first_add = true; fineDensity = false; // Brian's original Vx schedule liquid.iterations = options->liquid_iterations; liquid.temperature = options->liquid_temperature; liquid.attraction = options->liquid_attraction; liquid.damping_mult = options->liquid_damping_mult; liquid.time_elapsed = 0; expansion.iterations = options->expansion_iterations; expansion.temperature = options->expansion_temperature; expansion.attraction = options->expansion_attraction; expansion.damping_mult = options->expansion_damping_mult; expansion.time_elapsed = 0; cooldown.iterations = options->cooldown_iterations; cooldown.temperature = options->cooldown_temperature; cooldown.attraction = options->cooldown_attraction; cooldown.damping_mult = options->cooldown_damping_mult; cooldown.time_elapsed = 0; crunch.iterations = options->crunch_iterations; crunch.temperature = options->crunch_temperature; crunch.attraction = options->crunch_attraction; crunch.damping_mult = options->crunch_damping_mult; crunch.time_elapsed = 0; simmer.iterations = options->simmer_iterations; simmer.temperature = options->simmer_temperature; simmer.attraction = options->simmer_attraction; simmer.damping_mult = options->simmer_damping_mult; simmer.time_elapsed = 0; // scan .int file for node info highest_sim = 1.0; num_nodes = igraph_vcount(igraph); long int no_of_edges = igraph_ecount(igraph); for (long int i = 0; i < num_nodes; i++) { id_catalog[i] = 1; } map< int, int>::iterator cat_iter; for ( cat_iter = id_catalog.begin(); cat_iter != id_catalog.end(); cat_iter++) { cat_iter->second = cat_iter->first; } // populate node positions and ids positions.reserve ( num_nodes ); for ( cat_iter = id_catalog.begin(); cat_iter != id_catalog.end(); cat_iter++ ) { positions.push_back ( Node( cat_iter->first ) ); } // read .int file for graph info long int node_1, node_2; double weight; for (long int i = 0; i < no_of_edges; i++) { node_1 = IGRAPH_FROM(igraph, i); node_2 = IGRAPH_TO(igraph, i); weight = weights ? VECTOR(*weights)[i] : 1.0 ; (neighbors[id_catalog[node_1]])[id_catalog[node_2]] = weight; (neighbors[id_catalog[node_2]])[id_catalog[node_1]] = weight; } // initialize density server density_server.Init(); } // The following subroutine scans the .int file for the following // information: number nodes, node ids, and highest similarity. The // corresponding graph globals are populated: num_nodes, id_catalog, // and highest_sim. // void graph::scan_int ( char *filename ) // { // cout << "Proc. " << myid << " scanning .int file ..." << endl; // // Open (sim) File // ifstream fp ( filename ); // if ( !fp ) // { // cout << "Error: could not open " << filename << ". Program terminated." << endl; // #ifdef MUSE_MPI // MPI_Abort ( MPI_COMM_WORLD, 1 ); // #else // exit (1); // #endif // } // // Read file, parse, and add into data structure // int id1, id2; // float edge_weight; // highest_sim = -1.0; // while ( !fp.eof () ) // { // fp >> id1 >> id2 >> edge_weight; // // ignore negative weights! // if ( edge_weight <= 0 ) // { // cout << "Error: found negative edge weight in " << filename << ". Program stopped." << endl; // #ifdef MUSE_MPI // MPI_Abort ( MPI_COMM_WORLD, 1 ); // #else // exit (1); // #endif // } // if ( highest_sim < edge_weight ) // highest_sim = edge_weight; // id_catalog[id1] = 1; // id_catalog[id2] = 1; // } // fp.close(); // if ( id_catalog.size() == 0 ) // { // cout << "Error: Proc. " << myid << ": " << filename << " is empty. Program terminated." << endl; // #ifdef MUSE_MPI // MPI_Abort ( MPI_COMM_WORLD, 1 ); // #else // exit (1); // #endif // } // // label nodes with sequential integers starting at 0 // map< int, int>::iterator cat_iter; // int id_label; // for ( cat_iter = id_catalog.begin(), id_label = 0; // cat_iter != id_catalog.end(); cat_iter++, id_label++ ) // cat_iter->second = id_label; // /* // // output id_catalog for debugging: // for ( cat_iter = id_catalog.begin(); // cat_iter != id_catalog.end(); // cat_iter++ ) // cout << cat_iter->first << "\t" << cat_iter->second << endl; // */ // num_nodes = id_catalog.size(); // } // read in .parms file, if present /* void graph::read_parms ( char *parms_file ) { // read from .parms file ifstream parms_in ( parms_file ); if ( !parms_in ) { cout << "Error: could not open .parms file! Program stopped." << endl; #ifdef MUSE_MPI MPI_Abort ( MPI_COMM_WORLD, 1 ); #else exit (1); #endif } cout << "Processor " << myid << " reading .parms file." << endl; // read in stage parameters string parm_label; // this is ignored in the .parms file // initial parameters parms_in >> parm_label >> iterations; parms_in >> parm_label >> temperature; parms_in >> parm_label >> attraction; parms_in >> parm_label >> damping_mult; // liquid stage parms_in >> parm_label >> liquid.iterations; parms_in >> parm_label >> liquid.temperature; parms_in >> parm_label >> liquid.attraction; parms_in >> parm_label >> liquid.damping_mult; // expansion stage parms_in >> parm_label >> expansion.iterations; parms_in >> parm_label >> expansion.temperature; parms_in >> parm_label >> expansion.attraction; parms_in >> parm_label >> expansion.damping_mult; // cooldown stage parms_in >> parm_label >> cooldown.iterations; parms_in >> parm_label >> cooldown.temperature; parms_in >> parm_label >> cooldown.attraction; parms_in >> parm_label >> cooldown.damping_mult; // crunch stage parms_in >> parm_label >> crunch.iterations; parms_in >> parm_label >> crunch.temperature; parms_in >> parm_label >> crunch.attraction; parms_in >> parm_label >> crunch.damping_mult; // simmer stage parms_in >> parm_label >> simmer.iterations; parms_in >> parm_label >> simmer.temperature; parms_in >> parm_label >> simmer.attraction; parms_in >> parm_label >> simmer.damping_mult; parms_in.close(); // print out parameters for double checking if ( myid == 0 ) { cout << "Processor 0 reports the following inputs:" << endl; cout << "inital.iterations = " << iterations << endl; cout << "initial.temperature = " << temperature << endl; cout << "initial.attraction = " << attraction << endl; cout << "initial.damping_mult = " << damping_mult << endl; cout << " ..." << endl; cout << "liquid.iterations = " << liquid.iterations << endl; cout << "liquid.temperature = " << liquid.temperature << endl; cout << "liquid.attraction = " << liquid.attraction << endl; cout << "liquid.damping_mult = " << liquid.damping_mult << endl; cout << " ..." << endl; cout << "simmer.iterations = " << simmer.iterations << endl; cout << "simmer.temperature = " << simmer.temperature << endl; cout << "simmer.attraction = " << simmer.attraction << endl; cout << "simmer.damping_mult = " << simmer.damping_mult << endl; } } */ // init_parms -- this subroutine initializes the edge_cut variables // used in the original VxOrd starting with the edge_cut parameter. // In our version, edge_cut = 0 means no cutting, 1 = maximum cut. // We also set the random seed here. void graph::init_parms ( int rand_seed, float edge_cut, float real_parm ) { IGRAPH_UNUSED(rand_seed); // first we translate edge_cut the former tcl sliding scale //CUT_END = cut_length_end = 39000.0 * (1.0 - edge_cut) + 1000.0; CUT_END = cut_length_end = 40000.0 * (1.0 - edge_cut); // cut_length_end cannot actually be 0 if ( cut_length_end <= 1.0 ) { cut_length_end = 1.0; } float cut_length_start = 4.0 * cut_length_end; // now we set the parameters used by ReCompute cut_off_length = cut_length_start; cut_rate = ( cut_length_start - cut_length_end ) / 400.0; // finally set the number of iterations to leave .real coords fixed int full_comp_iters; full_comp_iters = liquid.iterations + expansion.iterations + cooldown.iterations + crunch.iterations + 3; // adjust real parm to iterations (do not enter simmer halfway) if ( real_parm < 0 ) { real_iterations = (int)real_parm; } else if ( real_parm == 1) { real_iterations = full_comp_iters + simmer.iterations + 100; } else { real_iterations = (int)(real_parm * full_comp_iters); } tot_iterations = 0; if ( real_iterations > 0 ) { real_fixed = true; } else { real_fixed = false; } // calculate total expected iterations (for progress bar display) tot_expected_iterations = liquid.iterations + expansion.iterations + cooldown.iterations + crunch.iterations + simmer.iterations; /* // output edge_cutting parms (for debugging) cout << "Processor " << myid << ": " << "cut_length_end = CUT_END = " << cut_length_end << ", cut_length_start = " << cut_length_start << ", cut_rate = " << cut_rate << endl; */ // set random seed // srand ( rand_seed ); // Don't need this in igraph } void graph::init_parms(const igraph_layout_drl_options_t *options) { double rand_seed = 0.0; double real_in = -1.0; init_parms(rand_seed, options->edge_cut, real_in); } // The following subroutine reads a .real file to obtain initial // coordinates. If a node is missing coordinates the coordinates // are computed // void graph::read_real ( char *real_file ) // { // cout << "Processor " << myid << " reading .real file ..." << endl; // // read in .real file and mark as fixed // ifstream real_in ( real_file ); // if ( !real_in ) // { // cout << "Error: proc. " << myid << " could not open .real file." << endl; // #ifdef MUSE_MPI // MPI_Abort ( MPI_COMM_WORLD, 1 ); // #else // exit (1); // #endif // } // int real_id; // float real_x, real_y; // while ( !real_in.eof () ) // { // real_id = -1; // real_in >> real_id >> real_x >> real_y; // if ( real_id >= 0 ) // { // positions[id_catalog[real_id]].x = real_x; // positions[id_catalog[real_id]].y = real_y; // positions[id_catalog[real_id]].fixed = true; // /* // // output positions read (for debugging) // cout << id_catalog[real_id] << " (" << positions[id_catalog[real_id]].x // << ", " << positions[id_catalog[real_id]].y << ") " // << positions[id_catalog[real_id]].fixed << endl; // */ // // add node to density grid // if ( real_iterations > 0 ) // density_server.Add ( positions[id_catalog[real_id]], fineDensity ); // } // } // real_in.close(); // } int graph::read_real ( const igraph_matrix_t *real_mat, const igraph_vector_bool_t *fixed) { long int n = igraph_matrix_nrow(real_mat); for (long int i = 0; i < n; i++) { positions[id_catalog[i]].x = MATRIX(*real_mat, i, 0); positions[id_catalog[i]].y = MATRIX(*real_mat, i, 1); positions[id_catalog[i]].fixed = fixed ? VECTOR(*fixed)[i] : false; if ( real_iterations > 0 ) { density_server.Add ( positions[id_catalog[i]], fineDensity ); } } return 0; } // The read_part_int subroutine reads the .int // file produced by convert_sim and gathers the nodes and their // neighbors in the range start_ind to end_ind. // void graph::read_int ( char *file_name ) // { // ifstream int_file; // int_file.open ( file_name ); // if ( !int_file ) // { // cout << "Error (worker process " << myid << "): could not open .int file." << endl; // #ifdef MUSE_MPI // MPI_Abort ( MPI_COMM_WORLD, 1 ); // #else // exit (1); // #endif // } // cout << "Processor " << myid << " reading .int file ..." << endl; // int node_1, node_2; // float weight; // while ( !int_file.eof() ) // { // weight = 0; // all weights should be >= 0 // int_file >> node_1 >> node_2 >> weight; // if ( weight ) // otherwise we are at end of file // // or it is a self-connected node // { // // normalization from original vxord // weight /= highest_sim; // weight = weight*fabs(weight); // // initialize graph // if ( ( node_1 % num_procs ) == myid ) // (neighbors[id_catalog[node_1]])[id_catalog[node_2]] = weight; // if ( ( node_2 % num_procs ) == myid ) // (neighbors[id_catalog[node_2]])[id_catalog[node_1]] = weight; // } // } // int_file.close(); // /* // // the following code outputs the contents of the neighbors structure // // (to be used for debugging) // map >::iterator i; // map::iterator j; // for ( i = neighbors.begin(); i != neighbors.end(); i++ ) { // cout << myid << ": " << i->first << " "; // for (j = (i->second).begin(); j != (i->second).end(); j++ ) // cout << j->first << " (" << j->second << ") "; // cout << endl; // } // */ // } /********************************************* * Function: ReCompute * * Description: Compute the graph locations * * Modified from original code by B. Wylie * ********************************************/ int graph::ReCompute( ) { // carryover from original VxOrd int MIN = 1; /* // output parameters (for debugging) cout << "ReCompute is using the following parameters: "<< endl; cout << "STAGE: " << STAGE << ", iter: " << iterations << ", temp = " << temperature << ", attract = " << attraction << ", damping_mult = " << damping_mult << ", min_edges = " << min_edges << ", cut_off_length = " << cut_off_length << ", fineDensity = " << fineDensity << endl; */ /* igraph progress report */ float progress = (tot_iterations * 100.0 / tot_expected_iterations); switch (STAGE) { case 0: if (iterations == 0) { IGRAPH_PROGRESS("DrL layout (initialization stage)", progress, 0); } else { IGRAPH_PROGRESS("DrL layout (liquid stage)", progress, 0); } break; case 1: IGRAPH_PROGRESS("DrL layout (expansion stage)", progress, 0); break; case 2: IGRAPH_PROGRESS("DrL layout (cooldown and cluster phase)", progress, 0); break; case 3: IGRAPH_PROGRESS("DrL layout (crunch phase)", progress, 0); break; case 5: IGRAPH_PROGRESS("DrL layout (simmer phase)", progress, 0); break; case 6: IGRAPH_PROGRESS("DrL layout (final phase)", 100.0, 0); break; default: IGRAPH_PROGRESS("DrL layout (unknown phase)", 0.0, 0); break; } /* Compute Energies for individual nodes */ update_nodes (); // check to see if we need to free fixed nodes tot_iterations++; if ( tot_iterations >= real_iterations ) { real_fixed = false; } // **************************************** // AUTOMATIC CONTROL SECTION // **************************************** // STAGE 0: LIQUID if (STAGE == 0) { if ( iterations == 0 ) { start_time = time( NULL ); // if ( myid == 0 ) // cout << "Entering liquid stage ..."; } if (iterations < liquid.iterations) { temperature = liquid.temperature; attraction = liquid.attraction; damping_mult = liquid.damping_mult; iterations++; // if ( myid == 0 ) // cout << "." << flush; } else { stop_time = time( NULL ); liquid.time_elapsed = liquid.time_elapsed + (stop_time - start_time); temperature = expansion.temperature; attraction = expansion.attraction; damping_mult = expansion.damping_mult; iterations = 0; // go to next stage STAGE = 1; start_time = time( NULL ); // if ( myid == 0 ) // cout << "Entering expansion stage ..."; } } // STAGE 1: EXPANSION if (STAGE == 1) { if (iterations < expansion.iterations) { // Play with vars if (attraction > 1) { attraction -= .05; } if (min_edges > 12) { min_edges -= .05; } cut_off_length -= cut_rate; if (damping_mult > .1) { damping_mult -= .005; } iterations++; // if ( myid == 0 ) cout << "." << flush; } else { stop_time = time( NULL ); expansion.time_elapsed = expansion.time_elapsed + (stop_time - start_time); min_edges = 12; damping_mult = cooldown.damping_mult; STAGE = 2; attraction = cooldown.attraction; temperature = cooldown.temperature; iterations = 0; start_time = time( NULL ); // if ( myid == 0 ) // cout << "Entering cool-down stage ..."; } } // STAGE 2: Cool down and cluster else if (STAGE == 2) { if (iterations < cooldown.iterations) { // Reduce temperature if (temperature > 50) { temperature -= 10; } // Reduce cut length if (cut_off_length > cut_length_end) { cut_off_length -= cut_rate * 2; } if (min_edges > MIN) { min_edges -= .2; } //min_edges = 99; iterations++; // if ( myid == 0 ) // cout << "." << flush; } else { stop_time = time( NULL ); cooldown.time_elapsed = cooldown.time_elapsed + (stop_time - start_time); cut_off_length = cut_length_end; temperature = crunch.temperature; damping_mult = crunch.damping_mult; min_edges = MIN; //min_edges = 99; // In other words: no more cutting STAGE = 3; iterations = 0; attraction = crunch.attraction; start_time = time( NULL ); // if ( myid == 0 ) // cout << "Entering crunch stage ..."; } } // STAGE 3: Crunch else if (STAGE == 3) { if (iterations < crunch.iterations) { iterations++; // if ( myid == 0 ) cout << "." << flush; } else { stop_time = time( NULL ); crunch.time_elapsed = crunch.time_elapsed + (stop_time - start_time); iterations = 0; temperature = simmer.temperature; attraction = simmer.attraction; damping_mult = simmer.damping_mult; min_edges = 99; fineDensity = true; STAGE = 5; start_time = time( NULL ); // if ( myid == 0 ) // cout << "Entering simmer stage ..."; } } // STAGE 5: Simmer else if ( STAGE == 5 ) { if (iterations < simmer.iterations) { if (temperature > 50) { temperature -= 2; } iterations++; // if ( myid == 0 ) cout << "." << flush; } else { stop_time = time( NULL ); simmer.time_elapsed = simmer.time_elapsed + (stop_time - start_time); STAGE = 6; // if ( myid == 0 ) // cout << "Layout calculation completed in " << // ( liquid.time_elapsed + expansion.time_elapsed + // cooldown.time_elapsed + crunch.time_elapsed + // simmer.time_elapsed ) // << " seconds (not including I/O)." // << endl; } } // STAGE 6: All Done! else if ( STAGE == 6) { /* // output parameters (for debugging) cout << "ReCompute is using the following parameters: "<< endl; cout << "STAGE: " << STAGE << ", iter: " << iterations << ", temp = " << temperature << ", attract = " << attraction << ", damping_mult = " << damping_mult << ", min_edges = " << min_edges << ", cut_off_length = " << cut_off_length << ", fineDensity = " << fineDensity << endl; */ return 0; } // **************************************** // END AUTOMATIC CONTROL SECTION // **************************************** // Still need more recomputation return 1; } // update_nodes -- this function will complete the primary node update // loop in layout's recompute routine. It follows exactly the same // sequence to ensure similarity of parallel layout to the standard layout void graph::update_nodes ( ) { vector node_indices; // node list of nodes currently being updated float old_positions[2 * MAX_PROCS]; // positions before update float new_positions[2 * MAX_PROCS]; // positions after update bool all_fixed; // check if all nodes are fixed // initial node list consists of 0,1,...,num_procs for ( int i = 0; i < num_procs; i++ ) { node_indices.push_back( i ); } // next we calculate the number of nodes there would be if the // num_nodes by num_procs schedule grid were perfectly square int square_num_nodes = (int)(num_procs + num_procs * floor ((float)(num_nodes - 1) / (float)num_procs )); for ( int i = myid; i < square_num_nodes; i += num_procs ) { // get old positions get_positions ( node_indices, old_positions ); // default new position is old position get_positions ( node_indices, new_positions ); if ( i < num_nodes ) { // advance random sequence according to myid for ( int j = 0; j < 2 * myid; j++ ) { RNG_UNIF01(); } // rand(); // calculate node energy possibilities if ( !(positions[i].fixed && real_fixed) ) { update_node_pos ( i, old_positions, new_positions ); } // advance random sequence for next iteration for ( unsigned int j = 2 * myid; j < 2 * (node_indices.size() - 1); j++ ) { RNG_UNIF01(); } // rand(); } else { // advance random sequence according to use by // the other processors for ( unsigned int j = 0; j < 2 * (node_indices.size()); j++ ) { RNG_UNIF01(); } //rand(); } // check if anything was actually updated (e.g. everything was fixed) all_fixed = true; for ( unsigned int j = 0; j < node_indices.size (); j++ ) if ( !(positions [ node_indices[j] ].fixed && real_fixed) ) { all_fixed = false; } // update positions across processors (if not all fixed) if ( !all_fixed ) { #ifdef MUSE_MPI MPI_Allgather ( &new_positions[2 * myid], 2, MPI_FLOAT, new_positions, 2, MPI_FLOAT, MPI_COMM_WORLD ); #endif // update positions (old to new) update_density ( node_indices, old_positions, new_positions ); } /* if ( myid == 0 ) { // output node list (for debugging) for ( unsigned int j = 0; j < node_indices.size(); j++ ) cout << node_indices[j] << " "; cout << endl; } */ // compute node list for next update for ( unsigned int j = 0; j < node_indices.size(); j++ ) { node_indices [j] += num_procs; } while ( !node_indices.empty() && node_indices.back() >= num_nodes ) { node_indices.pop_back ( ); } } // update first_add and fine_first_add first_add = false; if ( fineDensity ) { fine_first_add = false; } } // The get_positions function takes the node_indices list // and returns the corresponding positions in an array. void graph::get_positions ( vector &node_indices, float return_positions[2 * MAX_PROCS] ) { // fill positions for (unsigned int i = 0; i < node_indices.size(); i++) { return_positions[2 * i] = positions[ node_indices[i] ].x; return_positions[2 * i + 1] = positions[ node_indices[i] ].y; } } // update_node_pos -- this subroutine does the actual work of computing // the new position of a given node. num_act_proc gives the number // of active processes at this level for use by the random number // generators. void graph::update_node_pos ( int node_ind, float old_positions[2 * MAX_PROCS], float new_positions[2 * MAX_PROCS] ) { float energies[2]; // node energies for possible positions float updated_pos[2][2]; // possible positions float pos_x, pos_y; // old VxOrd parameter float jump_length = .010 * temperature; // subtract old node density_server.Subtract ( positions[node_ind], first_add, fine_first_add, fineDensity ); // compute node energy for old solution energies[0] = Compute_Node_Energy ( node_ind ); // move node to centroid position Solve_Analytic ( node_ind, pos_x, pos_y ); positions[node_ind].x = updated_pos[0][0] = pos_x; positions[node_ind].y = updated_pos[0][1] = pos_y; /* // ouput random numbers (for debugging) int rand_0, rand_1; rand_0 = rand(); rand_1 = rand(); cout << myid << ": " << rand_0 << ", " << rand_1 << endl; */ // Do random method (RAND_MAX is C++ maximum random number) updated_pos[1][0] = updated_pos[0][0] + (.5 - RNG_UNIF01()) * jump_length; updated_pos[1][1] = updated_pos[0][1] + (.5 - RNG_UNIF01()) * jump_length; // compute node energy for random position positions[node_ind].x = updated_pos[1][0]; positions[node_ind].y = updated_pos[1][1]; energies[1] = Compute_Node_Energy ( node_ind ); /* // output update possiblities (debugging): cout << node_ind << ": (" << updated_pos[0][0] << "," << updated_pos[0][1] << "), " << energies[0] << "; (" << updated_pos[1][0] << "," << updated_pos[1][1] << "), " << energies[1] << endl; */ // add back old position positions[node_ind].x = old_positions[2 * myid]; positions[node_ind].y = old_positions[2 * myid + 1]; if ( !fineDensity && !first_add ) { density_server.Add ( positions[node_ind], fineDensity ); } else if ( !fine_first_add ) { density_server.Add ( positions[node_ind], fineDensity ); } // choose updated node position with lowest energy if ( energies[0] < energies[1] ) { new_positions[2 * myid] = updated_pos[0][0]; new_positions[2 * myid + 1] = updated_pos[0][1]; positions[node_ind].energy = energies[0]; } else { new_positions[2 * myid] = updated_pos[1][0]; new_positions[2 * myid + 1] = updated_pos[1][1]; positions[node_ind].energy = energies[1]; } } // update_density takes a sequence of node_indices and their positions and // updates the positions by subtracting the old positions and adding the // new positions to the density grid. void graph::update_density ( vector &node_indices, float old_positions[2 * MAX_PROCS], float new_positions[2 * MAX_PROCS] ) { // go through each node and subtract old position from // density grid before adding new position for ( unsigned int i = 0; i < node_indices.size(); i++ ) { positions[node_indices[i]].x = old_positions[2 * i]; positions[node_indices[i]].y = old_positions[2 * i + 1]; density_server.Subtract ( positions[node_indices[i]], first_add, fine_first_add, fineDensity ); positions[node_indices[i]].x = new_positions[2 * i]; positions[node_indices[i]].y = new_positions[2 * i + 1]; density_server.Add ( positions[node_indices[i]], fineDensity ); } } /******************************************** * Function: Compute_Node_Energy * * Description: Compute the node energy * * This code has been modified from the * * original code by B. Wylie. * *********************************************/ float graph::Compute_Node_Energy( int node_ind ) { /* Want to expand 4th power range of attraction */ float attraction_factor = attraction * attraction * attraction * attraction * 2e-2; map ::iterator EI; float x_dis, y_dis; float energy_distance, weight; float node_energy = 0; // Add up all connection energies for (EI = neighbors[node_ind].begin(); EI != neighbors[node_ind].end(); ++EI) { // Get edge weight weight = EI->second; // Compute x,y distance x_dis = positions[ node_ind ].x - positions[ EI->first ].x; y_dis = positions[ node_ind ].y - positions[ EI->first ].y; // Energy Distance energy_distance = x_dis * x_dis + y_dis * y_dis; if (STAGE < 2) { energy_distance *= energy_distance; } // In the liquid phase we want to discourage long link distances if (STAGE == 0) { energy_distance *= energy_distance; } node_energy += weight * attraction_factor * energy_distance; } // output effect of density (debugging) //cout << "[before: " << node_energy; // add density node_energy += density_server.GetDensity ( positions[ node_ind ].x, positions[ node_ind ].y, fineDensity ); // after calling density server (debugging) //cout << ", after: " << node_energy << "]" << endl; // return computated energy return node_energy; } /********************************************* * Function: Solve_Analytic * * Description: Compute the node position * * This is a modified version of the function * * originally written by B. Wylie * *********************************************/ void graph::Solve_Analytic( int node_ind, float &pos_x, float &pos_y ) { map ::iterator EI; float total_weight = 0; float x_dis, y_dis, x_cen = 0, y_cen = 0; float x = 0, y = 0, dis; float damping, weight; // Sum up all connections for (EI = neighbors[node_ind].begin(); EI != neighbors[node_ind].end(); ++EI) { weight = EI->second; total_weight += weight; x += weight * positions[ EI->first ].x; y += weight * positions[ EI->first ].y; } // Now set node position if (total_weight > 0) { // Compute centriod x_cen = x / total_weight; y_cen = y / total_weight; damping = 1.0 - damping_mult; pos_x = damping * positions[ node_ind ].x + (1.0 - damping) * x_cen; pos_y = damping * positions[ node_ind ].y + (1.0 - damping) * y_cen; } else { pos_x = positions[ node_ind ].x; pos_y = positions[ node_ind ].y; } // No cut edge flag (?) if (min_edges == 99) { return; } // Don't cut at end of scale if ( CUT_END >= 39500 ) { return; } float num_connections = sqrt((double)neighbors[node_ind].size()); float maxLength = 0; map::iterator maxIndex; // Go through nodes edges... cutting if necessary for (EI = maxIndex = neighbors[node_ind].begin(); EI != neighbors[node_ind].end(); ++EI) { // Check for at least min edges if (neighbors[node_ind].size() < min_edges) { continue; } x_dis = x_cen - positions[ EI->first ].x; y_dis = y_cen - positions[ EI->first ].y; dis = x_dis * x_dis + y_dis * y_dis; dis *= num_connections; // Store maximum edge if (dis > maxLength) { maxLength = dis; maxIndex = EI; } } // If max length greater than cut_length then cut if (maxLength > cut_off_length) { neighbors[ node_ind ].erase( maxIndex ); } } // write_coord writes out the coordinate file of the final solutions // void graph::write_coord( const char *file_name ) // { // ofstream coordOUT( file_name ); // if ( !coordOUT ) // { // cout << "Could not open " << file_name << ". Program terminated." << endl; // #ifdef MUSE_MPI // MPI_Abort ( MPI_COMM_WORLD, 1 ); // #else // exit (1); // #endif // } // cout << "Writing out solution to " << file_name << " ..." << endl; // for (unsigned int i = 0; i < positions.size(); i++) { // coordOUT << positions[i].id << "\t" << positions[i].x << "\t" << positions[i].y < >::iterator i; map::iterator j; for ( i = neighbors.begin(); i != neighbors.end(); i++ ) for (j = (i->second).begin(); j != (i->second).end(); j++ ) simOUT << positions[i->first].id << "\t" << positions[j->first].id << "\t" << j->second << endl; simOUT.close(); } */ // get_tot_energy adds up the energy for each node to give an estimate of the // quality of the minimization. float graph::get_tot_energy ( ) { float my_tot_energy, tot_energy; my_tot_energy = 0; for ( int i = myid; i < num_nodes; i += num_procs ) { my_tot_energy += positions[i].energy; } //vector::iterator i; //for ( i = positions.begin(); i != positions.end(); i++ ) // tot_energy += i->energy; #ifdef MUSE_MPI MPI_Reduce ( &my_tot_energy, &tot_energy, 1, MPI_FLOAT, MPI_SUM, 0, MPI_COMM_WORLD ); #else tot_energy = my_tot_energy; #endif return tot_energy; } // The following subroutine draws the graph with possible intermediate // output (int_out is set to 0 if not proc. 0). int_out is the parameter // passed by the user, and coord_file is the .coord file. // void graph::draw_graph ( int int_out, char *coord_file ) // { // // layout graph (with possible intermediate output) // int count_iter = 0, count_file = 1; // char int_coord_file [MAX_FILE_NAME + MAX_INT_LENGTH]; // while ( ReCompute( ) ) // if ( (int_out > 0) && (count_iter == int_out) ) // { // // output intermediate solution // sprintf ( int_coord_file, "%s.%d", coord_file, count_file ); // write_coord ( int_coord_file ); // count_iter = 0; // count_file++; // } // else // count_iter++; // } int graph::draw_graph(igraph_matrix_t *res) { int count_iter = 0; while (ReCompute()) { IGRAPH_ALLOW_INTERRUPTION(); count_iter++; } long int n = positions.size(); IGRAPH_CHECK(igraph_matrix_resize(res, n, 2)); for (long int i = 0; i < n; i++) { MATRIX(*res, i, 0) = positions[i].x; MATRIX(*res, i, 1) = positions[i].y; } return 0; } } // namespace drl python-igraph-0.8.0/vendor/source/igraph/src/hrg_splittree_eq.h0000644000076500000240000001543113614300625025113 0ustar tamasstaff00000000000000/* -*- mode: C++ -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ // **************************************************************************************************** // *** COPYRIGHT NOTICE ******************************************************************************* // splittree_eq.h - a binary search tree data structure for storing dendrogram split frequencies // Copyright (C) 2006-2008 Aaron Clauset // // This program is free software; you can redistribute it and/or modify // it under the terms of the GNU General Public License as published by // the Free Software Foundation; either version 2 of the License, or // (at your option) any later version. // // This program is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU General Public License for more details. // // You should have received a copy of the GNU General Public License // along with this program; if not, write to the Free Software // Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA // // See http://www.gnu.org/licenses/gpl.txt for more details. // // **************************************************************************************************** // Author : Aaron Clauset ( aaronc@santafe.edu | http://www.santafe.edu/~aaronc/ ) // Collaborators: Cristopher Moore and Mark E.J. Newman // Project : Hierarchical Random Graphs // Location : University of New Mexico, Dept. of Computer Science AND Santa Fe Institute // Created : 19 April 2006 // Modified : 19 May 2007 // : 20 May 2008 (cleaned up for public consumption) // // *********************************************************************** // // Data structure for storing the split frequences in the sampled // dendrograms. Data is stored efficiently as a red-black binary // search tree (this is a modified version of the rbtree.h file). // // *********************************************************************** #ifndef IGRAPH_HRG_SPLITTREE #define IGRAPH_HRG_SPLITTREE #include using namespace std; namespace fitHRG { // ******** Basic Structures ********************************************* #ifndef IGRAPH_HRG_SLIST #define IGRAPH_HRG_SLIST class slist { public: string x; // stored elementd in linked-list slist* next; // pointer to next elementd slist(): x(""), next(0) { } ~slist() { } }; #endif class keyValuePairSplit { public: string x; // elementsp split (string) double y; // stored weight (double) int c; // stored count (int) keyValuePairSplit* next; // linked-list pointer keyValuePairSplit(): x(""), y(0.0), c(0), next(0) { } ~keyValuePairSplit() { } }; // ******** Tree elementsp Class ***************************************** class elementsp { public: string split; // split represented as a string double weight; // total weight of this split int count; // number of observations of this split bool color; // F: BLACK, T: RED short int mark; // marker elementsp *parent; // pointer to parent node elementsp *left; // pointer for left subtree elementsp *right; // pointer for right subtree elementsp(): split(""), weight(0.0), count(0), color(false), mark(0), parent(0), left(0), right(0) { } ~elementsp() { } }; // ******** Red-Black Tree Class ***************************************** // This vector implementation is a red-black balanced binary tree data // structure. It provides find a stored elementsp in time O(log n), // find the maximum elementsp in time O(1), delete an elementsp in // time O(log n), and insert an elementsp in time O(log n). // // Note that the split="" is assumed to be a special value, and thus // you cannot insert such an item. Beware of this limitation. // class splittree { private: elementsp* root; // binary tree root elementsp* leaf; // all leaf nodes int support; // number of nodes in the tree double total_weight; // total weight stored int total_count; // total number of observations stored // left-rotation operator void rotateLeft(elementsp*); // right-rotation operator void rotateRight(elementsp*); // house-keeping after insertion void insertCleanup(elementsp*); // house-keeping after deletion void deleteCleanup(elementsp*); keyValuePairSplit* returnSubtreeAsList(elementsp*, keyValuePairSplit*); // delete subtree rooted at z void deleteSubTree(elementsp*); // returns minimum of subtree rooted at z elementsp* returnMinKey(elementsp*); // returns successor of z's key elementsp* returnSuccessor(elementsp*); public: // default constructor/destructor splittree(); ~splittree(); // returns value associated with searchKey double returnValue(const string); // returns T if searchKey found, and points foundNode at the // corresponding node elementsp* findItem(const string); // update total_count and total_weight void finishedThisRound(); // insert a new key with stored value bool insertItem(string, double); void clearTree(); // delete a node with given key void deleteItem(string); // delete the entire tree void deleteTree(); // return array of keys in tree string* returnArrayOfKeys(); // return list of keys in tree slist* returnListOfKeys(); // return the tree as a list of keyValuePairSplits keyValuePairSplit* returnTreeAsList(); // returns the maximum key in the tree keyValuePairSplit returnMaxKey(); // returns the minimum key in the tree keyValuePairSplit returnMinKey(); // returns number of items in tree int returnNodecount(); // returns list of splits with given number of Ms keyValuePairSplit* returnTheseSplits(const int); // returns sum of stored values double returnTotal(); }; } // namespace fitHRG #endif python-igraph-0.8.0/vendor/source/igraph/src/drl_layout.cpp0000644000076500000240000003715313614300625024271 0ustar tamasstaff00000000000000/* * Copyright 2007 Sandia Corporation. Under the terms of Contract * DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains * certain rights in this software. * * All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are * met: * * * Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * Neither the name of Sandia National Laboratories nor the names of * its contributors may be used to endorse or promote products derived from * this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT * OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED * TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF * LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING * NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. */ // Layout // // This program implements a parallel force directed graph drawing // algorithm. The algorithm used is based upon a random decomposition // of the graph and simulated shared memory of node position and density. // In this version, the simulated shared memory is spread among all processors // // The structure of the inputs and outputs of this code will be displayed // if the program is called without parameters, or if an erroneous // parameter is passed to the program. // // S. Martin // 5/6/2005 // C++ library routines #include #include #include #include #include #include #include using namespace std; // layout routines and constants #include "drl_layout.h" #include "drl_parse.h" #include "drl_graph.h" // MPI #ifdef MUSE_MPI #include #endif using namespace drl; #include "igraph_layout.h" #include "igraph_random.h" #include "igraph_interface.h" namespace drl { // int main(int argc, char **argv) { // // initialize MPI // int myid, num_procs; // #ifdef MUSE_MPI // MPI_Init ( &argc, &argv ); // MPI_Comm_size ( MPI_COMM_WORLD, &num_procs ); // MPI_Comm_rank ( MPI_COMM_WORLD, &myid ); // #else // myid = 0; // num_procs = 1; // #endif // // parameters that must be broadcast to all processors // int rand_seed; // float edge_cut; // char int_file[MAX_FILE_NAME]; // char coord_file[MAX_FILE_NAME]; // char real_file[MAX_FILE_NAME]; // char parms_file[MAX_FILE_NAME]; // int int_out = 0; // int edges_out = 0; // int parms_in = 0; // float real_in = -1.0; // // user interaction is handled by processor 0 // if ( myid == 0 ) // { // if ( num_procs > MAX_PROCS ) // { // cout << "Error: Maximum number of processors is " << MAX_PROCS << "." << endl; // cout << "Adjust compile time parameter." << endl; // #ifdef MUSE_MPI // MPI_Abort ( MPI_COMM_WORLD, 1 ); // #else // exit (1); // #endif // } // // get user input // parse command_line ( argc, argv ); // rand_seed = command_line.rand_seed; // edge_cut = command_line.edge_cut; // int_out = command_line.int_out; // edges_out = command_line.edges_out; // parms_in = command_line.parms_in; // real_in = command_line.real_in; // strcpy ( coord_file, command_line.coord_file.c_str() ); // strcpy ( int_file, command_line.sim_file.c_str() ); // strcpy ( real_file, command_line.real_file.c_str() ); // strcpy ( parms_file, command_line.parms_file.c_str() ); // } // // now we initialize all processors by reading .int file // #ifdef MUSE_MPI // MPI_Bcast ( &int_file, MAX_FILE_NAME, MPI_CHAR, 0, MPI_COMM_WORLD ); // #endif // graph neighbors ( myid, num_procs, int_file ); // // check for user supplied parameters // #ifdef MUSE_MPI // MPI_Bcast ( &parms_in, 1, MPI_INT, 0, MPI_COMM_WORLD ); // #endif // if ( parms_in ) // { // #ifdef MUSE_MPI // MPI_Bcast ( &parms_file, MAX_FILE_NAME, MPI_CHAR, 0, MPI_COMM_WORLD ); // #endif // neighbors.read_parms ( parms_file ); // } // // set random seed, edge cutting, and real iterations parameters // #ifdef MUSE_MPI // MPI_Bcast ( &rand_seed, 1, MPI_INT, 0, MPI_COMM_WORLD ); // MPI_Bcast ( &edge_cut, 1, MPI_FLOAT, 0, MPI_COMM_WORLD ); // MPI_Bcast ( &real_in, 1, MPI_INT, 0, MPI_COMM_WORLD ); // #endif // neighbors.init_parms ( rand_seed, edge_cut, real_in ); // // check for .real file with existing coordinates // if ( real_in >= 0 ) // { // #ifdef MUSE_MPI // MPI_Bcast ( &real_file, MAX_FILE_NAME, MPI_CHAR, 0, MPI_COMM_WORLD ); // #endif // neighbors.read_real ( real_file ); // } // neighbors.draw_graph ( int_out, coord_file ); // // do we have to write out the edges? // #ifdef MUSE_MPI // MPI_Bcast ( &edges_out, 1, MPI_INT, 0, MPI_COMM_WORLD ); // #endif // if ( edges_out ) // { // #ifdef MUSE_MPI // MPI_Bcast ( &coord_file, MAX_FILE_NAME, MPI_CHAR, 0, MPI_COMM_WORLD ); // #endif // for ( int i = 0; i < num_procs; i++ ) // { // if ( myid == i ) // neighbors.write_sim ( coord_file ); // #ifdef MUSE_MPI // MPI_Barrier ( MPI_COMM_WORLD ); // #endif // } // } // // finally we output file and quit // float tot_energy; // tot_energy = neighbors.get_tot_energy (); // if ( myid == 0 ) // { // neighbors.write_coord ( coord_file ); // cout << "Total Energy: " << tot_energy << "." << endl // << "Program terminated successfully." << endl; // } // // MPI finalize // #ifdef MUSE_MPI // MPI_Finalize (); // #endif // return 0; // } } // namespace drl /** * \section about_drl * * * DrL is a sophisticated layout generator developed and implemented by * Shawn Martin et al. As of October 2012 the original DrL homepage is * unfortunately not available. You can read more about this algorithm * in the following technical report: Martin, S., Brown, W.M., * Klavans, R., Boyack, K.W., DrL: Distributed Recursive (Graph) * Layout. SAND Reports, 2008. 2936: p. 1-10. * * * * Only a subset of the complete DrL functionality is * included in igraph, parallel runs and recursive, multi-level * layouting is not supported. * * * * The parameters of the layout are stored in an \ref * igraph_layout_drl_options_t structure, this can be initialized by * calling the function \ref igraph_layout_drl_options_init(). * The fields of this structure can then be adjusted by hand if needed. * The layout is calculated by an \ref igraph_layout_drl() call. * */ /** * \function igraph_layout_drl_options_init * Initialize parameters for the DrL layout generator * * This function can be used to initialize the struct holding the * parameters for the DrL layout generator. There are a number of * predefined templates available, it is a good idea to start from one * of these by modifying some parameters. * \param options The struct to initialize. * \param templ The template to use. Currently the following templates * are supplied: \c IGRAPH_LAYOUT_DRL_DEFAULT, \c * IGRAPH_LAYOUT_DRL_COARSEN, \c IGRAPH_LAYOUT_DRL_COARSEST, * \c IGRAPH_LAYOUT_DRL_REFINE and \c IGRAPH_LAYOUT_DRL_FINAL. * \return Error code. * * Time complexity: O(1). */ int igraph_layout_drl_options_init(igraph_layout_drl_options_t *options, igraph_layout_drl_default_t templ) { options->edge_cut = 32.0 / 40.0; switch (templ) { case IGRAPH_LAYOUT_DRL_DEFAULT: options->init_iterations = 0; options->init_temperature = 2000; options->init_attraction = 10; options->init_damping_mult = 1.0; options->liquid_iterations = 200; options->liquid_temperature = 2000; options->liquid_attraction = 10; options->liquid_damping_mult = 1.0; options->expansion_iterations = 200; options->expansion_temperature = 2000; options->expansion_attraction = 2; options->expansion_damping_mult = 1.0; options->cooldown_iterations = 200; options->cooldown_temperature = 2000; options->cooldown_attraction = 1; options->cooldown_damping_mult = .1; options->crunch_iterations = 50; options->crunch_temperature = 250; options->crunch_attraction = 1; options->crunch_damping_mult = 0.25; options->simmer_iterations = 100; options->simmer_temperature = 250; options->simmer_attraction = .5; options->simmer_damping_mult = 0; break; case IGRAPH_LAYOUT_DRL_COARSEN: options->init_iterations = 0; options->init_temperature = 2000; options->init_attraction = 10; options->init_damping_mult = 1.0; options->liquid_iterations = 200; options->liquid_temperature = 2000; options->liquid_attraction = 2; options->liquid_damping_mult = 1.0; options->expansion_iterations = 200; options->expansion_temperature = 2000; options->expansion_attraction = 10; options->expansion_damping_mult = 1.0; options->cooldown_iterations = 200; options->cooldown_temperature = 2000; options->cooldown_attraction = 1; options->cooldown_damping_mult = .1; options->crunch_iterations = 50; options->crunch_temperature = 250; options->crunch_attraction = 1; options->crunch_damping_mult = 0.25; options->simmer_iterations = 100; options->simmer_temperature = 250; options->simmer_attraction = .5; options->simmer_damping_mult = 0; break; case IGRAPH_LAYOUT_DRL_COARSEST: options->init_iterations = 0; options->init_temperature = 2000; options->init_attraction = 10; options->init_damping_mult = 1.0; options->liquid_iterations = 200; options->liquid_temperature = 2000; options->liquid_attraction = 2; options->liquid_damping_mult = 1.0; options->expansion_iterations = 200; options->expansion_temperature = 2000; options->expansion_attraction = 10; options->expansion_damping_mult = 1.0; options->cooldown_iterations = 200; options->cooldown_temperature = 2000; options->cooldown_attraction = 1; options->cooldown_damping_mult = .1; options->crunch_iterations = 200; options->crunch_temperature = 250; options->crunch_attraction = 1; options->crunch_damping_mult = 0.25; options->simmer_iterations = 100; options->simmer_temperature = 250; options->simmer_attraction = .5; options->simmer_damping_mult = 0; break; case IGRAPH_LAYOUT_DRL_REFINE: options->init_iterations = 0; options->init_temperature = 50; options->init_attraction = .5; options->init_damping_mult = 0; options->liquid_iterations = 0; options->liquid_temperature = 2000; options->liquid_attraction = 2; options->liquid_damping_mult = 1.0; options->expansion_iterations = 50; options->expansion_temperature = 500; options->expansion_attraction = .1; options->expansion_damping_mult = .25; options->cooldown_iterations = 50; options->cooldown_temperature = 200; options->cooldown_attraction = 1; options->cooldown_damping_mult = .1; options->crunch_iterations = 50; options->crunch_temperature = 250; options->crunch_attraction = 1; options->crunch_damping_mult = 0.25; options->simmer_iterations = 0; options->simmer_temperature = 250; options->simmer_attraction = .5; options->simmer_damping_mult = 0; break; case IGRAPH_LAYOUT_DRL_FINAL: options->init_iterations = 0; options->init_temperature = 50; options->init_attraction = .5; options->init_damping_mult = 0; options->liquid_iterations = 0; options->liquid_temperature = 2000; options->liquid_attraction = 2; options->liquid_damping_mult = 1.0; options->expansion_iterations = 50; options->expansion_temperature = 50; options->expansion_attraction = .1; options->expansion_damping_mult = .25; options->cooldown_iterations = 50; options->cooldown_temperature = 200; options->cooldown_attraction = 1; options->cooldown_damping_mult = .1; options->crunch_iterations = 50; options->crunch_temperature = 250; options->crunch_attraction = 1; options->crunch_damping_mult = 0.25; options->simmer_iterations = 25; options->simmer_temperature = 250; options->simmer_attraction = .5; options->simmer_damping_mult = 0; break; default: IGRAPH_ERROR("Unknown DrL template", IGRAPH_EINVAL); break; } return 0; } /** * \function igraph_layout_drl * The DrL layout generator * * This function implements the force-directed DrL layout generator. * Please see more in the following technical report: Martin, S., * Brown, W.M., Klavans, R., Boyack, K.W., DrL: Distributed Recursive * (Graph) Layout. SAND Reports, 2008. 2936: p. 1-10. * \param graph The input graph. * \param use_seed Logical scalar, if true, then the coordinates * supplied in the \p res argument are used as starting points. * \param res Pointer to a matrix, the result layout is stored * here. It will be resized as needed. * \param options The parameters to pass to the layout generator. * \param weights Edge weights, pointer to a vector. If this is a null * pointer then every edge will have the same weight. * \param fixed Pointer to a logical vector, or a null pointer. Originally, * this argument was used in the DrL algorithm to keep the nodes marked * with this argument as fixed; fixed nodes would then keep their * positions in the initial stages of the algorithm. However, due to how * the DrL code imported into igraph is organized, it seems that the * argument does not do anything and we are not sure whether this is a * bug or a feature in DrL. We are leaving the argument here in order not * to break the API, but note that at the present stage it has no effect. * \return Error code. * * Time complexity: ???. */ int igraph_layout_drl(const igraph_t *graph, igraph_matrix_t *res, igraph_bool_t use_seed, igraph_layout_drl_options_t *options, const igraph_vector_t *weights, const igraph_vector_bool_t *fixed) { RNG_BEGIN(); drl::graph neighbors(graph, options, weights); neighbors.init_parms(options); if (use_seed) { IGRAPH_CHECK(igraph_matrix_resize(res, igraph_vcount(graph), 2)); neighbors.read_real(res, fixed); } neighbors.draw_graph(res); RNG_END(); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/COLAMD/0000755000076500000240000000000013617375001022340 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/src/COLAMD/Makefile0000644000076500000240000000241613524616144024006 0ustar tamasstaff00000000000000#------------------------------------------------------------------------------ # COLAMD Makefile #------------------------------------------------------------------------------ VERSION = 2.8.0 default: all include ../SuiteSparse_config/SuiteSparse_config.mk demos: all # Compile all C code all: ( cd Lib ; $(MAKE) ) ( cd Demo ; $(MAKE) ) # compile just the C-callable libraries (not Demos) library: ( cd Lib ; $(MAKE) ) # remove object files, but keep the compiled programs and library archives clean: ( cd Lib ; $(MAKE) clean ) ( cd Demo ; $(MAKE) clean ) ( cd MATLAB ; $(RM) $(CLEAN) ) # clean, and then remove compiled programs and library archives purge: ( cd Lib ; $(MAKE) purge ) ( cd Demo ; $(MAKE) purge ) ( cd MATLAB ; $(RM) $(CLEAN) ; $(RM) *.mex* ) distclean: purge # get ready for distribution dist: purge ( cd Demo ; $(MAKE) dist ) ccode: library lib: library # install COLAMD install: $(CP) Lib/libcolamd.a $(INSTALL_LIB)/libcolamd.$(VERSION).a ( cd $(INSTALL_LIB) ; ln -sf libcolamd.$(VERSION).a libcolamd.a ) $(CP) Include/colamd.h $(INSTALL_INCLUDE) chmod 644 $(INSTALL_LIB)/libcolamd*.a chmod 644 $(INSTALL_INCLUDE)/colamd.h # uninstall COLAMD uninstall: $(RM) $(INSTALL_LIB)/libcolamd*.a $(RM) $(INSTALL_INCLUDE)/colamd.h python-igraph-0.8.0/vendor/source/igraph/src/COLAMD/Include/0000755000076500000240000000000013617375001023723 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/src/COLAMD/Include/colamd.h0000644000076500000240000002121013524616144025332 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === colamd/symamd prototypes and definitions ============================= */ /* ========================================================================== */ /* COLAMD / SYMAMD include file You must include this file (colamd.h) in any routine that uses colamd, symamd, or the related macros and definitions. Authors: The authors of the code itself are Stefan I. Larimore and Timothy A. Davis (DrTimothyAldenDavis@gmail.com). The algorithm was developed in collaboration with John Gilbert, Xerox PARC, and Esmond Ng, Oak Ridge National Laboratory. Acknowledgements: This work was supported by the National Science Foundation, under grants DMS-9504974 and DMS-9803599. Notice: Copyright (c) 1998-2007, Timothy A. Davis, All Rights Reserved. THIS MATERIAL IS PROVIDED AS IS, WITH ABSOLUTELY NO WARRANTY EXPRESSED OR IMPLIED. ANY USE IS AT YOUR OWN RISK. Permission is hereby granted to use, copy, modify, and/or distribute this program, provided that the Copyright, this License, and the Availability of the original version is retained on all copies and made accessible to the end-user of any code or package that includes COLAMD or any modified version of COLAMD. Availability: The colamd/symamd library is available at http://www.suitesparse.com This file is required by the colamd.c, colamdmex.c, and symamdmex.c files, and by any C code that calls the routines whose prototypes are listed below, or that uses the colamd/symamd definitions listed below. */ #ifndef COLAMD_H #define COLAMD_H /* make it easy for C++ programs to include COLAMD */ #ifdef __cplusplus extern "C" { #endif /* ========================================================================== */ /* === Include files ======================================================== */ /* ========================================================================== */ #include /* ========================================================================== */ /* === COLAMD version ======================================================= */ /* ========================================================================== */ /* COLAMD Version 2.4 and later will include the following definitions. * As an example, to test if the version you are using is 2.4 or later: * * #ifdef COLAMD_VERSION * if (COLAMD_VERSION >= COLAMD_VERSION_CODE (2,4)) ... * #endif * * This also works during compile-time: * * #if defined(COLAMD_VERSION) && (COLAMD_VERSION >= COLAMD_VERSION_CODE (2,4)) * printf ("This is version 2.4 or later\n") ; * #else * printf ("This is an early version\n") ; * #endif * * Versions 2.3 and earlier of COLAMD do not include a #define'd version number. */ #define COLAMD_DATE "Jun 1, 2012" #define COLAMD_VERSION_CODE(main,sub) ((main) * 1000 + (sub)) #define COLAMD_MAIN_VERSION 2 #define COLAMD_SUB_VERSION 8 #define COLAMD_SUBSUB_VERSION 0 #define COLAMD_VERSION \ COLAMD_VERSION_CODE(COLAMD_MAIN_VERSION,COLAMD_SUB_VERSION) /* ========================================================================== */ /* === Knob and statistics definitions ====================================== */ /* ========================================================================== */ /* size of the knobs [ ] array. Only knobs [0..1] are currently used. */ #define COLAMD_KNOBS 20 /* number of output statistics. Only stats [0..6] are currently used. */ #define COLAMD_STATS 20 /* knobs [0] and stats [0]: dense row knob and output statistic. */ #define COLAMD_DENSE_ROW 0 /* knobs [1] and stats [1]: dense column knob and output statistic. */ #define COLAMD_DENSE_COL 1 /* knobs [2]: aggressive absorption */ #define COLAMD_AGGRESSIVE 2 /* stats [2]: memory defragmentation count output statistic */ #define COLAMD_DEFRAG_COUNT 2 /* stats [3]: colamd status: zero OK, > 0 warning or notice, < 0 error */ #define COLAMD_STATUS 3 /* stats [4..6]: error info, or info on jumbled columns */ #define COLAMD_INFO1 4 #define COLAMD_INFO2 5 #define COLAMD_INFO3 6 /* error codes returned in stats [3]: */ #define COLAMD_OK (0) #define COLAMD_OK_BUT_JUMBLED (1) #define COLAMD_ERROR_A_not_present (-1) #define COLAMD_ERROR_p_not_present (-2) #define COLAMD_ERROR_nrow_negative (-3) #define COLAMD_ERROR_ncol_negative (-4) #define COLAMD_ERROR_nnz_negative (-5) #define COLAMD_ERROR_p0_nonzero (-6) #define COLAMD_ERROR_A_too_small (-7) #define COLAMD_ERROR_col_length_negative (-8) #define COLAMD_ERROR_row_index_out_of_bounds (-9) #define COLAMD_ERROR_out_of_memory (-10) #define COLAMD_ERROR_internal_error (-999) /* ========================================================================== */ /* === Prototypes of user-callable routines ================================= */ /* ========================================================================== */ #include "SuiteSparse_config.h" size_t colamd_recommended /* returns recommended value of Alen, */ /* or 0 if input arguments are erroneous */ ( int nnz, /* nonzeros in A */ int n_row, /* number of rows in A */ int n_col /* number of columns in A */ ) ; size_t colamd_l_recommended /* returns recommended value of Alen, */ /* or 0 if input arguments are erroneous */ ( SuiteSparse_long nnz, /* nonzeros in A */ SuiteSparse_long n_row, /* number of rows in A */ SuiteSparse_long n_col /* number of columns in A */ ) ; void colamd_set_defaults /* sets default parameters */ ( /* knobs argument is modified on output */ double knobs [COLAMD_KNOBS] /* parameter settings for colamd */ ) ; void colamd_l_set_defaults /* sets default parameters */ ( /* knobs argument is modified on output */ double knobs [COLAMD_KNOBS] /* parameter settings for colamd */ ) ; int colamd /* returns (1) if successful, (0) otherwise*/ ( /* A and p arguments are modified on output */ int n_row, /* number of rows in A */ int n_col, /* number of columns in A */ int Alen, /* size of the array A */ int A [], /* row indices of A, of size Alen */ int p [], /* column pointers of A, of size n_col+1 */ double knobs [COLAMD_KNOBS],/* parameter settings for colamd */ int stats [COLAMD_STATS] /* colamd output statistics and error codes */ ) ; SuiteSparse_long colamd_l /* returns (1) if successful, (0) otherwise*/ ( /* A and p arguments are modified on output */ SuiteSparse_long n_row, /* number of rows in A */ SuiteSparse_long n_col, /* number of columns in A */ SuiteSparse_long Alen, /* size of the array A */ SuiteSparse_long A [], /* row indices of A, of size Alen */ SuiteSparse_long p [], /* column pointers of A, of size n_col+1 */ double knobs [COLAMD_KNOBS],/* parameter settings for colamd */ SuiteSparse_long stats [COLAMD_STATS] /* colamd output statistics * and error codes */ ) ; int symamd /* return (1) if OK, (0) otherwise */ ( int n, /* number of rows and columns of A */ int A [], /* row indices of A */ int p [], /* column pointers of A */ int perm [], /* output permutation, size n_col+1 */ double knobs [COLAMD_KNOBS], /* parameters (uses defaults if NULL) */ int stats [COLAMD_STATS], /* output statistics and error codes */ void * (*allocate) (size_t, size_t), /* pointer to calloc (ANSI C) or */ /* mxCalloc (for MATLAB mexFunction) */ void (*release) (void *) /* pointer to free (ANSI C) or */ /* mxFree (for MATLAB mexFunction) */ ) ; SuiteSparse_long symamd_l /* return (1) if OK, (0) otherwise */ ( SuiteSparse_long n, /* number of rows and columns of A */ SuiteSparse_long A [], /* row indices of A */ SuiteSparse_long p [], /* column pointers of A */ SuiteSparse_long perm [], /* output permutation, size n_col+1 */ double knobs [COLAMD_KNOBS], /* parameters (uses defaults if NULL) */ SuiteSparse_long stats [COLAMD_STATS], /* output stats and error codes */ void * (*allocate) (size_t, size_t), /* pointer to calloc (ANSI C) or */ /* mxCalloc (for MATLAB mexFunction) */ void (*release) (void *) /* pointer to free (ANSI C) or */ /* mxFree (for MATLAB mexFunction) */ ) ; void colamd_report ( int stats [COLAMD_STATS] ) ; void colamd_l_report ( SuiteSparse_long stats [COLAMD_STATS] ) ; void symamd_report ( int stats [COLAMD_STATS] ) ; void symamd_l_report ( SuiteSparse_long stats [COLAMD_STATS] ) ; #ifndef EXTERN #define EXTERN extern #endif EXTERN int (*colamd_printf) (const char *, ...) ; #ifdef __cplusplus } #endif #endif /* COLAMD_H */ python-igraph-0.8.0/vendor/source/igraph/src/COLAMD/Source/0000755000076500000240000000000013617375001023600 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/src/COLAMD/Source/colamd_global.c0000644000076500000240000000154213524616144026530 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === colamd_global.c ====================================================== */ /* ========================================================================== */ /* ---------------------------------------------------------------------------- * COLAMD, Copyright (C) 2007, Timothy A. Davis. * See License.txt for the Version 2.1 of the GNU Lesser General Public License * http://www.suitesparse.com * -------------------------------------------------------------------------- */ /* Global variables for COLAMD */ #ifndef NPRINT #ifdef MATLAB_MEX_FILE #include "mex.h" int (*colamd_printf) (const char *, ...) = mexPrintf ; #else #include int (*colamd_printf) (const char *, ...) = printf ; #endif #else int (*colamd_printf) (const char *, ...) = ((void *) 0) ; #endif python-igraph-0.8.0/vendor/source/igraph/src/COLAMD/Source/colamd.c0000644000076500000240000032302413524616144025212 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === colamd/symamd - a sparse matrix column ordering algorithm ============ */ /* ========================================================================== */ /* COLAMD / SYMAMD colamd: an approximate minimum degree column ordering algorithm, for LU factorization of symmetric or unsymmetric matrices, QR factorization, least squares, interior point methods for linear programming problems, and other related problems. symamd: an approximate minimum degree ordering algorithm for Cholesky factorization of symmetric matrices. Purpose: Colamd computes a permutation Q such that the Cholesky factorization of (AQ)'(AQ) has less fill-in and requires fewer floating point operations than A'A. This also provides a good ordering for sparse partial pivoting methods, P(AQ) = LU, where Q is computed prior to numerical factorization, and P is computed during numerical factorization via conventional partial pivoting with row interchanges. Colamd is the column ordering method used in SuperLU, part of the ScaLAPACK library. It is also available as built-in function in MATLAB Version 6, available from MathWorks, Inc. (http://www.mathworks.com). This routine can be used in place of colmmd in MATLAB. Symamd computes a permutation P of a symmetric matrix A such that the Cholesky factorization of PAP' has less fill-in and requires fewer floating point operations than A. Symamd constructs a matrix M such that M'M has the same nonzero pattern of A, and then orders the columns of M using colmmd. The column ordering of M is then returned as the row and column ordering P of A. Authors: The authors of the code itself are Stefan I. Larimore and Timothy A. Davis (DrTimothyAldenDavis@gmail.com). The algorithm was developed in collaboration with John Gilbert, Xerox PARC, and Esmond Ng, Oak Ridge National Laboratory. Acknowledgements: This work was supported by the National Science Foundation, under grants DMS-9504974 and DMS-9803599. Copyright and License: Copyright (c) 1998-2007, Timothy A. Davis, All Rights Reserved. COLAMD is also available under alternate licenses, contact T. Davis for details. This library is free software; you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation; either version 2.1 of the License, or (at your option) any later version. This library is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with this library; if not, write to the Free Software Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA Permission is hereby granted to use or copy this program under the terms of the GNU LGPL, provided that the Copyright, this License, and the Availability of the original version is retained on all copies. User documentation of any code that uses this code or any modified version of this code must cite the Copyright, this License, the Availability note, and "Used by permission." Permission to modify the code and to distribute modified code is granted, provided the Copyright, this License, and the Availability note are retained, and a notice that the code was modified is included. Availability: The colamd/symamd library is available at http://www.suitesparse.com Appears as ACM Algorithm 836. See the ChangeLog file for changes since Version 1.0. References: T. A. Davis, J. R. Gilbert, S. Larimore, E. Ng, An approximate column minimum degree ordering algorithm, ACM Transactions on Mathematical Software, vol. 30, no. 3., pp. 353-376, 2004. T. A. Davis, J. R. Gilbert, S. Larimore, E. Ng, Algorithm 836: COLAMD, an approximate column minimum degree ordering algorithm, ACM Transactions on Mathematical Software, vol. 30, no. 3., pp. 377-380, 2004. */ /* ========================================================================== */ /* === Description of user-callable routines ================================ */ /* ========================================================================== */ /* COLAMD includes both int and SuiteSparse_long versions of all its routines. The description below is for the int version. For SuiteSparse_long, all int arguments become SuiteSparse_long. SuiteSparse_long is normally defined as long, except for WIN64. ---------------------------------------------------------------------------- colamd_recommended: ---------------------------------------------------------------------------- C syntax: #include "colamd.h" size_t colamd_recommended (int nnz, int n_row, int n_col) ; size_t colamd_l_recommended (SuiteSparse_long nnz, SuiteSparse_long n_row, SuiteSparse_long n_col) ; Purpose: Returns recommended value of Alen for use by colamd. Returns 0 if any input argument is negative. The use of this routine is optional. Not needed for symamd, which dynamically allocates its own memory. Note that in v2.4 and earlier, these routines returned int or long. They now return a value of type size_t. Arguments (all input arguments): int nnz ; Number of nonzeros in the matrix A. This must be the same value as p [n_col] in the call to colamd - otherwise you will get a wrong value of the recommended memory to use. int n_row ; Number of rows in the matrix A. int n_col ; Number of columns in the matrix A. ---------------------------------------------------------------------------- colamd_set_defaults: ---------------------------------------------------------------------------- C syntax: #include "colamd.h" colamd_set_defaults (double knobs [COLAMD_KNOBS]) ; colamd_l_set_defaults (double knobs [COLAMD_KNOBS]) ; Purpose: Sets the default parameters. The use of this routine is optional. Arguments: double knobs [COLAMD_KNOBS] ; Output only. NOTE: the meaning of the dense row/col knobs has changed in v2.4 knobs [0] and knobs [1] control dense row and col detection: Colamd: rows with more than max (16, knobs [COLAMD_DENSE_ROW] * sqrt (n_col)) entries are removed prior to ordering. Columns with more than max (16, knobs [COLAMD_DENSE_COL] * sqrt (MIN (n_row,n_col))) entries are removed prior to ordering, and placed last in the output column ordering. Symamd: uses only knobs [COLAMD_DENSE_ROW], which is knobs [0]. Rows and columns with more than max (16, knobs [COLAMD_DENSE_ROW] * sqrt (n)) entries are removed prior to ordering, and placed last in the output ordering. COLAMD_DENSE_ROW and COLAMD_DENSE_COL are defined as 0 and 1, respectively, in colamd.h. Default values of these two knobs are both 10. Currently, only knobs [0] and knobs [1] are used, but future versions may use more knobs. If so, they will be properly set to their defaults by the future version of colamd_set_defaults, so that the code that calls colamd will not need to change, assuming that you either use colamd_set_defaults, or pass a (double *) NULL pointer as the knobs array to colamd or symamd. knobs [2]: aggressive absorption knobs [COLAMD_AGGRESSIVE] controls whether or not to do aggressive absorption during the ordering. Default is TRUE. ---------------------------------------------------------------------------- colamd: ---------------------------------------------------------------------------- C syntax: #include "colamd.h" int colamd (int n_row, int n_col, int Alen, int *A, int *p, double knobs [COLAMD_KNOBS], int stats [COLAMD_STATS]) ; SuiteSparse_long colamd_l (SuiteSparse_long n_row, SuiteSparse_long n_col, SuiteSparse_long Alen, SuiteSparse_long *A, SuiteSparse_long *p, double knobs [COLAMD_KNOBS], SuiteSparse_long stats [COLAMD_STATS]) ; Purpose: Computes a column ordering (Q) of A such that P(AQ)=LU or (AQ)'AQ=LL' have less fill-in and require fewer floating point operations than factorizing the unpermuted matrix A or A'A, respectively. Returns: TRUE (1) if successful, FALSE (0) otherwise. Arguments: int n_row ; Input argument. Number of rows in the matrix A. Restriction: n_row >= 0. Colamd returns FALSE if n_row is negative. int n_col ; Input argument. Number of columns in the matrix A. Restriction: n_col >= 0. Colamd returns FALSE if n_col is negative. int Alen ; Input argument. Restriction (see note): Alen >= 2*nnz + 6*(n_col+1) + 4*(n_row+1) + n_col Colamd returns FALSE if these conditions are not met. Note: this restriction makes an modest assumption regarding the size of the two typedef's structures in colamd.h. We do, however, guarantee that Alen >= colamd_recommended (nnz, n_row, n_col) will be sufficient. Note: the macro version does not check for integer overflow, and thus is not recommended. Use the colamd_recommended routine instead. int A [Alen] ; Input argument, undefined on output. A is an integer array of size Alen. Alen must be at least as large as the bare minimum value given above, but this is very low, and can result in excessive run time. For best performance, we recommend that Alen be greater than or equal to colamd_recommended (nnz, n_row, n_col), which adds nnz/5 to the bare minimum value given above. On input, the row indices of the entries in column c of the matrix are held in A [(p [c]) ... (p [c+1]-1)]. The row indices in a given column c need not be in ascending order, and duplicate row indices may be be present. However, colamd will work a little faster if both of these conditions are met (Colamd puts the matrix into this format, if it finds that the the conditions are not met). The matrix is 0-based. That is, rows are in the range 0 to n_row-1, and columns are in the range 0 to n_col-1. Colamd returns FALSE if any row index is out of range. The contents of A are modified during ordering, and are undefined on output. int p [n_col+1] ; Both input and output argument. p is an integer array of size n_col+1. On input, it holds the "pointers" for the column form of the matrix A. Column c of the matrix A is held in A [(p [c]) ... (p [c+1]-1)]. The first entry, p [0], must be zero, and p [c] <= p [c+1] must hold for all c in the range 0 to n_col-1. The value p [n_col] is thus the total number of entries in the pattern of the matrix A. Colamd returns FALSE if these conditions are not met. On output, if colamd returns TRUE, the array p holds the column permutation (Q, for P(AQ)=LU or (AQ)'(AQ)=LL'), where p [0] is the first column index in the new ordering, and p [n_col-1] is the last. That is, p [k] = j means that column j of A is the kth pivot column, in AQ, where k is in the range 0 to n_col-1 (p [0] = j means that column j of A is the first column in AQ). If colamd returns FALSE, then no permutation is returned, and p is undefined on output. double knobs [COLAMD_KNOBS] ; Input argument. See colamd_set_defaults for a description. int stats [COLAMD_STATS] ; Output argument. Statistics on the ordering, and error status. See colamd.h for related definitions. Colamd returns FALSE if stats is not present. stats [0]: number of dense or empty rows ignored. stats [1]: number of dense or empty columns ignored (and ordered last in the output permutation p) Note that a row can become "empty" if it contains only "dense" and/or "empty" columns, and similarly a column can become "empty" if it only contains "dense" and/or "empty" rows. stats [2]: number of garbage collections performed. This can be excessively high if Alen is close to the minimum required value. stats [3]: status code. < 0 is an error code. > 1 is a warning or notice. 0 OK. Each column of the input matrix contained row indices in increasing order, with no duplicates. 1 OK, but columns of input matrix were jumbled (unsorted columns or duplicate entries). Colamd had to do some extra work to sort the matrix first and remove duplicate entries, but it still was able to return a valid permutation (return value of colamd was TRUE). stats [4]: highest numbered column that is unsorted or has duplicate entries. stats [5]: last seen duplicate or unsorted row index. stats [6]: number of duplicate or unsorted row indices. -1 A is a null pointer -2 p is a null pointer -3 n_row is negative stats [4]: n_row -4 n_col is negative stats [4]: n_col -5 number of nonzeros in matrix is negative stats [4]: number of nonzeros, p [n_col] -6 p [0] is nonzero stats [4]: p [0] -7 A is too small stats [4]: required size stats [5]: actual size (Alen) -8 a column has a negative number of entries stats [4]: column with < 0 entries stats [5]: number of entries in col -9 a row index is out of bounds stats [4]: column with bad row index stats [5]: bad row index stats [6]: n_row, # of rows of matrx -10 (unused; see symamd.c) -999 (unused; see symamd.c) Future versions may return more statistics in the stats array. Example: See colamd_example.c for a complete example. To order the columns of a 5-by-4 matrix with 11 nonzero entries in the following nonzero pattern x 0 x 0 x 0 x x 0 x x 0 0 0 x x x x 0 0 with default knobs and no output statistics, do the following: #include "colamd.h" #define ALEN 100 int A [ALEN] = {0, 1, 4, 2, 4, 0, 1, 2, 3, 1, 3} ; int p [ ] = {0, 3, 5, 9, 11} ; int stats [COLAMD_STATS] ; colamd (5, 4, ALEN, A, p, (double *) NULL, stats) ; The permutation is returned in the array p, and A is destroyed. ---------------------------------------------------------------------------- symamd: ---------------------------------------------------------------------------- C syntax: #include "colamd.h" int symamd (int n, int *A, int *p, int *perm, double knobs [COLAMD_KNOBS], int stats [COLAMD_STATS], void (*allocate) (size_t, size_t), void (*release) (void *)) ; SuiteSparse_long symamd_l (SuiteSparse_long n, SuiteSparse_long *A, SuiteSparse_long *p, SuiteSparse_long *perm, double knobs [COLAMD_KNOBS], SuiteSparse_long stats [COLAMD_STATS], void (*allocate) (size_t, size_t), void (*release) (void *)) ; Purpose: The symamd routine computes an ordering P of a symmetric sparse matrix A such that the Cholesky factorization PAP' = LL' remains sparse. It is based on a column ordering of a matrix M constructed so that the nonzero pattern of M'M is the same as A. The matrix A is assumed to be symmetric; only the strictly lower triangular part is accessed. You must pass your selected memory allocator (usually calloc/free or mxCalloc/mxFree) to symamd, for it to allocate memory for the temporary matrix M. Returns: TRUE (1) if successful, FALSE (0) otherwise. Arguments: int n ; Input argument. Number of rows and columns in the symmetrix matrix A. Restriction: n >= 0. Symamd returns FALSE if n is negative. int A [nnz] ; Input argument. A is an integer array of size nnz, where nnz = p [n]. The row indices of the entries in column c of the matrix are held in A [(p [c]) ... (p [c+1]-1)]. The row indices in a given column c need not be in ascending order, and duplicate row indices may be present. However, symamd will run faster if the columns are in sorted order with no duplicate entries. The matrix is 0-based. That is, rows are in the range 0 to n-1, and columns are in the range 0 to n-1. Symamd returns FALSE if any row index is out of range. The contents of A are not modified. int p [n+1] ; Input argument. p is an integer array of size n+1. On input, it holds the "pointers" for the column form of the matrix A. Column c of the matrix A is held in A [(p [c]) ... (p [c+1]-1)]. The first entry, p [0], must be zero, and p [c] <= p [c+1] must hold for all c in the range 0 to n-1. The value p [n] is thus the total number of entries in the pattern of the matrix A. Symamd returns FALSE if these conditions are not met. The contents of p are not modified. int perm [n+1] ; Output argument. On output, if symamd returns TRUE, the array perm holds the permutation P, where perm [0] is the first index in the new ordering, and perm [n-1] is the last. That is, perm [k] = j means that row and column j of A is the kth column in PAP', where k is in the range 0 to n-1 (perm [0] = j means that row and column j of A are the first row and column in PAP'). The array is used as a workspace during the ordering, which is why it must be of length n+1, not just n. double knobs [COLAMD_KNOBS] ; Input argument. See colamd_set_defaults for a description. int stats [COLAMD_STATS] ; Output argument. Statistics on the ordering, and error status. See colamd.h for related definitions. Symamd returns FALSE if stats is not present. stats [0]: number of dense or empty row and columns ignored (and ordered last in the output permutation perm). Note that a row/column can become "empty" if it contains only "dense" and/or "empty" columns/rows. stats [1]: (same as stats [0]) stats [2]: number of garbage collections performed. stats [3]: status code. < 0 is an error code. > 1 is a warning or notice. 0 OK. Each column of the input matrix contained row indices in increasing order, with no duplicates. 1 OK, but columns of input matrix were jumbled (unsorted columns or duplicate entries). Symamd had to do some extra work to sort the matrix first and remove duplicate entries, but it still was able to return a valid permutation (return value of symamd was TRUE). stats [4]: highest numbered column that is unsorted or has duplicate entries. stats [5]: last seen duplicate or unsorted row index. stats [6]: number of duplicate or unsorted row indices. -1 A is a null pointer -2 p is a null pointer -3 (unused, see colamd.c) -4 n is negative stats [4]: n -5 number of nonzeros in matrix is negative stats [4]: # of nonzeros (p [n]). -6 p [0] is nonzero stats [4]: p [0] -7 (unused) -8 a column has a negative number of entries stats [4]: column with < 0 entries stats [5]: number of entries in col -9 a row index is out of bounds stats [4]: column with bad row index stats [5]: bad row index stats [6]: n_row, # of rows of matrx -10 out of memory (unable to allocate temporary workspace for M or count arrays using the "allocate" routine passed into symamd). Future versions may return more statistics in the stats array. void * (*allocate) (size_t, size_t) A pointer to a function providing memory allocation. The allocated memory must be returned initialized to zero. For a C application, this argument should normally be a pointer to calloc. For a MATLAB mexFunction, the routine mxCalloc is passed instead. void (*release) (size_t, size_t) A pointer to a function that frees memory allocated by the memory allocation routine above. For a C application, this argument should normally be a pointer to free. For a MATLAB mexFunction, the routine mxFree is passed instead. ---------------------------------------------------------------------------- colamd_report: ---------------------------------------------------------------------------- C syntax: #include "colamd.h" colamd_report (int stats [COLAMD_STATS]) ; colamd_l_report (SuiteSparse_long stats [COLAMD_STATS]) ; Purpose: Prints the error status and statistics recorded in the stats array on the standard error output (for a standard C routine) or on the MATLAB output (for a mexFunction). Arguments: int stats [COLAMD_STATS] ; Input only. Statistics from colamd. ---------------------------------------------------------------------------- symamd_report: ---------------------------------------------------------------------------- C syntax: #include "colamd.h" symamd_report (int stats [COLAMD_STATS]) ; symamd_l_report (SuiteSparse_long stats [COLAMD_STATS]) ; Purpose: Prints the error status and statistics recorded in the stats array on the standard error output (for a standard C routine) or on the MATLAB output (for a mexFunction). Arguments: int stats [COLAMD_STATS] ; Input only. Statistics from symamd. */ /* ========================================================================== */ /* === Scaffolding code definitions ======================================== */ /* ========================================================================== */ /* Ensure that debugging is turned off: */ #ifndef NDEBUG #define NDEBUG #endif /* turn on debugging by uncommenting the following line #undef NDEBUG */ /* Our "scaffolding code" philosophy: In our opinion, well-written library code should keep its "debugging" code, and just normally have it turned off by the compiler so as not to interfere with performance. This serves several purposes: (1) assertions act as comments to the reader, telling you what the code expects at that point. All assertions will always be true (unless there really is a bug, of course). (2) leaving in the scaffolding code assists anyone who would like to modify the code, or understand the algorithm (by reading the debugging output, one can get a glimpse into what the code is doing). (3) (gasp!) for actually finding bugs. This code has been heavily tested and "should" be fully functional and bug-free ... but you never know... The code will become outrageously slow when debugging is enabled. To control the level of debugging output, set an environment variable D to 0 (little), 1 (some), 2, 3, or 4 (lots). When debugging, you should see the following message on the standard output: colamd: debug version, D = 1 (THIS WILL BE SLOW!) or a similar message for symamd. If you don't, then debugging has not been enabled. */ /* ========================================================================== */ /* === Include files ======================================================== */ /* ========================================================================== */ #include "colamd.h" #include #include #ifdef MATLAB_MEX_FILE #include "mex.h" #include "matrix.h" #endif /* MATLAB_MEX_FILE */ #if !defined (NPRINT) || !defined (NDEBUG) #include #endif #ifndef NULL #define NULL ((void *) 0) #endif /* ========================================================================== */ /* === int or SuiteSparse_long ============================================== */ /* ========================================================================== */ #ifdef DLONG #define Int SuiteSparse_long #define ID SuiteSparse_long_id #define Int_MAX SuiteSparse_long_max #define COLAMD_recommended colamd_l_recommended #define COLAMD_set_defaults colamd_l_set_defaults #define COLAMD_MAIN colamd_l #define SYMAMD_MAIN symamd_l #define COLAMD_report colamd_l_report #define SYMAMD_report symamd_l_report #else #define Int int #define ID "%d" #define Int_MAX INT_MAX #define COLAMD_recommended colamd_recommended #define COLAMD_set_defaults colamd_set_defaults #define COLAMD_MAIN colamd #define SYMAMD_MAIN symamd #define COLAMD_report colamd_report #define SYMAMD_report symamd_report #endif /* ========================================================================== */ /* === Row and Column structures ============================================ */ /* ========================================================================== */ /* User code that makes use of the colamd/symamd routines need not directly */ /* reference these structures. They are used only for colamd_recommended. */ typedef struct Colamd_Col_struct { Int start ; /* index for A of first row in this column, or DEAD */ /* if column is dead */ Int length ; /* number of rows in this column */ union { Int thickness ; /* number of original columns represented by this */ /* col, if the column is alive */ Int parent ; /* parent in parent tree super-column structure, if */ /* the column is dead */ } shared1 ; union { Int score ; /* the score used to maintain heap, if col is alive */ Int order ; /* pivot ordering of this column, if col is dead */ } shared2 ; union { Int headhash ; /* head of a hash bucket, if col is at the head of */ /* a degree list */ Int hash ; /* hash value, if col is not in a degree list */ Int prev ; /* previous column in degree list, if col is in a */ /* degree list (but not at the head of a degree list) */ } shared3 ; union { Int degree_next ; /* next column, if col is in a degree list */ Int hash_next ; /* next column, if col is in a hash list */ } shared4 ; } Colamd_Col ; typedef struct Colamd_Row_struct { Int start ; /* index for A of first col in this row */ Int length ; /* number of principal columns in this row */ union { Int degree ; /* number of principal & non-principal columns in row */ Int p ; /* used as a row pointer in init_rows_cols () */ } shared1 ; union { Int mark ; /* for computing set differences and marking dead rows*/ Int first_column ;/* first column in row (used in garbage collection) */ } shared2 ; } Colamd_Row ; /* ========================================================================== */ /* === Definitions ========================================================== */ /* ========================================================================== */ /* Routines are either PUBLIC (user-callable) or PRIVATE (not user-callable) */ #define PUBLIC #define PRIVATE static #define DENSE_DEGREE(alpha,n) \ ((Int) MAX (16.0, (alpha) * sqrt ((double) (n)))) #define MAX(a,b) (((a) > (b)) ? (a) : (b)) #define MIN(a,b) (((a) < (b)) ? (a) : (b)) #define ONES_COMPLEMENT(r) (-(r)-1) /* -------------------------------------------------------------------------- */ /* Change for version 2.1: define TRUE and FALSE only if not yet defined */ /* -------------------------------------------------------------------------- */ #ifndef TRUE #define TRUE (1) #endif #ifndef FALSE #define FALSE (0) #endif /* -------------------------------------------------------------------------- */ #define EMPTY (-1) /* Row and column status */ #define ALIVE (0) #define DEAD (-1) /* Column status */ #define DEAD_PRINCIPAL (-1) #define DEAD_NON_PRINCIPAL (-2) /* Macros for row and column status update and checking. */ #define ROW_IS_DEAD(r) ROW_IS_MARKED_DEAD (Row[r].shared2.mark) #define ROW_IS_MARKED_DEAD(row_mark) (row_mark < ALIVE) #define ROW_IS_ALIVE(r) (Row [r].shared2.mark >= ALIVE) #define COL_IS_DEAD(c) (Col [c].start < ALIVE) #define COL_IS_ALIVE(c) (Col [c].start >= ALIVE) #define COL_IS_DEAD_PRINCIPAL(c) (Col [c].start == DEAD_PRINCIPAL) #define KILL_ROW(r) { Row [r].shared2.mark = DEAD ; } #define KILL_PRINCIPAL_COL(c) { Col [c].start = DEAD_PRINCIPAL ; } #define KILL_NON_PRINCIPAL_COL(c) { Col [c].start = DEAD_NON_PRINCIPAL ; } /* ========================================================================== */ /* === Colamd reporting mechanism =========================================== */ /* ========================================================================== */ #if defined (MATLAB_MEX_FILE) || defined (MATHWORKS) /* In MATLAB, matrices are 1-based to the user, but 0-based internally */ #define INDEX(i) ((i)+1) #else /* In C, matrices are 0-based and indices are reported as such in *_report */ #define INDEX(i) (i) #endif /* All output goes through the PRINTF macro. */ #define PRINTF(params) { if (colamd_printf != NULL) (void) colamd_printf params ; } /* ========================================================================== */ /* === Prototypes of PRIVATE routines ======================================= */ /* ========================================================================== */ PRIVATE Int init_rows_cols ( Int n_row, Int n_col, Colamd_Row Row [], Colamd_Col Col [], Int A [], Int p [], Int stats [COLAMD_STATS] ) ; PRIVATE void init_scoring ( Int n_row, Int n_col, Colamd_Row Row [], Colamd_Col Col [], Int A [], Int head [], double knobs [COLAMD_KNOBS], Int *p_n_row2, Int *p_n_col2, Int *p_max_deg ) ; PRIVATE Int find_ordering ( Int n_row, Int n_col, Int Alen, Colamd_Row Row [], Colamd_Col Col [], Int A [], Int head [], Int n_col2, Int max_deg, Int pfree, Int aggressive ) ; PRIVATE void order_children ( Int n_col, Colamd_Col Col [], Int p [] ) ; PRIVATE void detect_super_cols ( #ifndef NDEBUG Int n_col, Colamd_Row Row [], #endif /* NDEBUG */ Colamd_Col Col [], Int A [], Int head [], Int row_start, Int row_length ) ; PRIVATE Int garbage_collection ( Int n_row, Int n_col, Colamd_Row Row [], Colamd_Col Col [], Int A [], Int *pfree ) ; PRIVATE Int clear_mark ( Int tag_mark, Int max_mark, Int n_row, Colamd_Row Row [] ) ; PRIVATE void print_report ( char *method, Int stats [COLAMD_STATS] ) ; /* ========================================================================== */ /* === Debugging prototypes and definitions ================================= */ /* ========================================================================== */ #ifndef NDEBUG #include /* colamd_debug is the *ONLY* global variable, and is only */ /* present when debugging */ PRIVATE Int colamd_debug = 0 ; /* debug print level */ #define DEBUG0(params) { PRINTF (params) ; } #define DEBUG1(params) { if (colamd_debug >= 1) PRINTF (params) ; } #define DEBUG2(params) { if (colamd_debug >= 2) PRINTF (params) ; } #define DEBUG3(params) { if (colamd_debug >= 3) PRINTF (params) ; } #define DEBUG4(params) { if (colamd_debug >= 4) PRINTF (params) ; } #ifdef MATLAB_MEX_FILE #define ASSERT(expression) (mxAssert ((expression), "")) #else #define ASSERT(expression) (assert (expression)) #endif /* MATLAB_MEX_FILE */ PRIVATE void colamd_get_debug /* gets the debug print level from getenv */ ( char *method ) ; PRIVATE void debug_deg_lists ( Int n_row, Int n_col, Colamd_Row Row [], Colamd_Col Col [], Int head [], Int min_score, Int should, Int max_deg ) ; PRIVATE void debug_mark ( Int n_row, Colamd_Row Row [], Int tag_mark, Int max_mark ) ; PRIVATE void debug_matrix ( Int n_row, Int n_col, Colamd_Row Row [], Colamd_Col Col [], Int A [] ) ; PRIVATE void debug_structures ( Int n_row, Int n_col, Colamd_Row Row [], Colamd_Col Col [], Int A [], Int n_col2 ) ; #else /* NDEBUG */ /* === No debugging ========================================================= */ #define DEBUG0(params) ; #define DEBUG1(params) ; #define DEBUG2(params) ; #define DEBUG3(params) ; #define DEBUG4(params) ; #define ASSERT(expression) #endif /* NDEBUG */ /* ========================================================================== */ /* === USER-CALLABLE ROUTINES: ============================================== */ /* ========================================================================== */ /* ========================================================================== */ /* === colamd_recommended =================================================== */ /* ========================================================================== */ /* The colamd_recommended routine returns the suggested size for Alen. This value has been determined to provide good balance between the number of garbage collections and the memory requirements for colamd. If any argument is negative, or if integer overflow occurs, a 0 is returned as an error condition. 2*nnz space is required for the row and column indices of the matrix. COLAMD_C (n_col) + COLAMD_R (n_row) space is required for the Col and Row arrays, respectively, which are internal to colamd (roughly 6*n_col + 4*n_row). An additional n_col space is the minimal amount of "elbow room", and nnz/5 more space is recommended for run time efficiency. Alen is approximately 2.2*nnz + 7*n_col + 4*n_row + 10. This function is not needed when using symamd. */ /* add two values of type size_t, and check for integer overflow */ static size_t t_add (size_t a, size_t b, int *ok) { (*ok) = (*ok) && ((a + b) >= MAX (a,b)) ; return ((*ok) ? (a + b) : 0) ; } /* compute a*k where k is a small integer, and check for integer overflow */ static size_t t_mult (size_t a, size_t k, int *ok) { size_t i, s = 0 ; for (i = 0 ; i < k ; i++) { s = t_add (s, a, ok) ; } return (s) ; } /* size of the Col and Row structures */ #define COLAMD_C(n_col,ok) \ ((t_mult (t_add (n_col, 1, ok), sizeof (Colamd_Col), ok) / sizeof (Int))) #define COLAMD_R(n_row,ok) \ ((t_mult (t_add (n_row, 1, ok), sizeof (Colamd_Row), ok) / sizeof (Int))) PUBLIC size_t COLAMD_recommended /* returns recommended value of Alen. */ ( /* === Parameters ======================================================= */ Int nnz, /* number of nonzeros in A */ Int n_row, /* number of rows in A */ Int n_col /* number of columns in A */ ) { size_t s, c, r ; int ok = TRUE ; if (nnz < 0 || n_row < 0 || n_col < 0) { return (0) ; } s = t_mult (nnz, 2, &ok) ; /* 2*nnz */ c = COLAMD_C (n_col, &ok) ; /* size of column structures */ r = COLAMD_R (n_row, &ok) ; /* size of row structures */ s = t_add (s, c, &ok) ; s = t_add (s, r, &ok) ; s = t_add (s, n_col, &ok) ; /* elbow room */ s = t_add (s, nnz/5, &ok) ; /* elbow room */ ok = ok && (s < Int_MAX) ; return (ok ? s : 0) ; } /* ========================================================================== */ /* === colamd_set_defaults ================================================== */ /* ========================================================================== */ /* The colamd_set_defaults routine sets the default values of the user- controllable parameters for colamd and symamd: Colamd: rows with more than max (16, knobs [0] * sqrt (n_col)) entries are removed prior to ordering. Columns with more than max (16, knobs [1] * sqrt (MIN (n_row,n_col))) entries are removed prior to ordering, and placed last in the output column ordering. Symamd: Rows and columns with more than max (16, knobs [0] * sqrt (n)) entries are removed prior to ordering, and placed last in the output ordering. knobs [0] dense row control knobs [1] dense column control knobs [2] if nonzero, do aggresive absorption knobs [3..19] unused, but future versions might use this */ PUBLIC void COLAMD_set_defaults ( /* === Parameters ======================================================= */ double knobs [COLAMD_KNOBS] /* knob array */ ) { /* === Local variables ================================================== */ Int i ; if (!knobs) { return ; /* no knobs to initialize */ } for (i = 0 ; i < COLAMD_KNOBS ; i++) { knobs [i] = 0 ; } knobs [COLAMD_DENSE_ROW] = 10 ; knobs [COLAMD_DENSE_COL] = 10 ; knobs [COLAMD_AGGRESSIVE] = TRUE ; /* default: do aggressive absorption*/ } /* ========================================================================== */ /* === symamd =============================================================== */ /* ========================================================================== */ PUBLIC Int SYMAMD_MAIN /* return TRUE if OK, FALSE otherwise */ ( /* === Parameters ======================================================= */ Int n, /* number of rows and columns of A */ Int A [], /* row indices of A */ Int p [], /* column pointers of A */ Int perm [], /* output permutation, size n+1 */ double knobs [COLAMD_KNOBS], /* parameters (uses defaults if NULL) */ Int stats [COLAMD_STATS], /* output statistics and error codes */ void * (*allocate) (size_t, size_t), /* pointer to calloc (ANSI C) or */ /* mxCalloc (for MATLAB mexFunction) */ void (*release) (void *) /* pointer to free (ANSI C) or */ /* mxFree (for MATLAB mexFunction) */ ) { /* === Local variables ================================================== */ Int *count ; /* length of each column of M, and col pointer*/ Int *mark ; /* mark array for finding duplicate entries */ Int *M ; /* row indices of matrix M */ size_t Mlen ; /* length of M */ Int n_row ; /* number of rows in M */ Int nnz ; /* number of entries in A */ Int i ; /* row index of A */ Int j ; /* column index of A */ Int k ; /* row index of M */ Int mnz ; /* number of nonzeros in M */ Int pp ; /* index into a column of A */ Int last_row ; /* last row seen in the current column */ Int length ; /* number of nonzeros in a column */ double cknobs [COLAMD_KNOBS] ; /* knobs for colamd */ double default_knobs [COLAMD_KNOBS] ; /* default knobs for colamd */ #ifndef NDEBUG colamd_get_debug ("symamd") ; #endif /* NDEBUG */ /* === Check the input arguments ======================================== */ if (!stats) { DEBUG0 (("symamd: stats not present\n")) ; return (FALSE) ; } for (i = 0 ; i < COLAMD_STATS ; i++) { stats [i] = 0 ; } stats [COLAMD_STATUS] = COLAMD_OK ; stats [COLAMD_INFO1] = -1 ; stats [COLAMD_INFO2] = -1 ; if (!A) { stats [COLAMD_STATUS] = COLAMD_ERROR_A_not_present ; DEBUG0 (("symamd: A not present\n")) ; return (FALSE) ; } if (!p) /* p is not present */ { stats [COLAMD_STATUS] = COLAMD_ERROR_p_not_present ; DEBUG0 (("symamd: p not present\n")) ; return (FALSE) ; } if (n < 0) /* n must be >= 0 */ { stats [COLAMD_STATUS] = COLAMD_ERROR_ncol_negative ; stats [COLAMD_INFO1] = n ; DEBUG0 (("symamd: n negative %d\n", n)) ; return (FALSE) ; } nnz = p [n] ; if (nnz < 0) /* nnz must be >= 0 */ { stats [COLAMD_STATUS] = COLAMD_ERROR_nnz_negative ; stats [COLAMD_INFO1] = nnz ; DEBUG0 (("symamd: number of entries negative %d\n", nnz)) ; return (FALSE) ; } if (p [0] != 0) { stats [COLAMD_STATUS] = COLAMD_ERROR_p0_nonzero ; stats [COLAMD_INFO1] = p [0] ; DEBUG0 (("symamd: p[0] not zero %d\n", p [0])) ; return (FALSE) ; } /* === If no knobs, set default knobs =================================== */ if (!knobs) { COLAMD_set_defaults (default_knobs) ; knobs = default_knobs ; } /* === Allocate count and mark ========================================== */ count = (Int *) ((*allocate) (n+1, sizeof (Int))) ; if (!count) { stats [COLAMD_STATUS] = COLAMD_ERROR_out_of_memory ; DEBUG0 (("symamd: allocate count (size %d) failed\n", n+1)) ; return (FALSE) ; } mark = (Int *) ((*allocate) (n+1, sizeof (Int))) ; if (!mark) { stats [COLAMD_STATUS] = COLAMD_ERROR_out_of_memory ; (*release) ((void *) count) ; DEBUG0 (("symamd: allocate mark (size %d) failed\n", n+1)) ; return (FALSE) ; } /* === Compute column counts of M, check if A is valid ================== */ stats [COLAMD_INFO3] = 0 ; /* number of duplicate or unsorted row indices*/ for (i = 0 ; i < n ; i++) { mark [i] = -1 ; } for (j = 0 ; j < n ; j++) { last_row = -1 ; length = p [j+1] - p [j] ; if (length < 0) { /* column pointers must be non-decreasing */ stats [COLAMD_STATUS] = COLAMD_ERROR_col_length_negative ; stats [COLAMD_INFO1] = j ; stats [COLAMD_INFO2] = length ; (*release) ((void *) count) ; (*release) ((void *) mark) ; DEBUG0 (("symamd: col %d negative length %d\n", j, length)) ; return (FALSE) ; } for (pp = p [j] ; pp < p [j+1] ; pp++) { i = A [pp] ; if (i < 0 || i >= n) { /* row index i, in column j, is out of bounds */ stats [COLAMD_STATUS] = COLAMD_ERROR_row_index_out_of_bounds ; stats [COLAMD_INFO1] = j ; stats [COLAMD_INFO2] = i ; stats [COLAMD_INFO3] = n ; (*release) ((void *) count) ; (*release) ((void *) mark) ; DEBUG0 (("symamd: row %d col %d out of bounds\n", i, j)) ; return (FALSE) ; } if (i <= last_row || mark [i] == j) { /* row index is unsorted or repeated (or both), thus col */ /* is jumbled. This is a notice, not an error condition. */ stats [COLAMD_STATUS] = COLAMD_OK_BUT_JUMBLED ; stats [COLAMD_INFO1] = j ; stats [COLAMD_INFO2] = i ; (stats [COLAMD_INFO3]) ++ ; DEBUG1 (("symamd: row %d col %d unsorted/duplicate\n", i, j)) ; } if (i > j && mark [i] != j) { /* row k of M will contain column indices i and j */ count [i]++ ; count [j]++ ; } /* mark the row as having been seen in this column */ mark [i] = j ; last_row = i ; } } /* v2.4: removed free(mark) */ /* === Compute column pointers of M ===================================== */ /* use output permutation, perm, for column pointers of M */ perm [0] = 0 ; for (j = 1 ; j <= n ; j++) { perm [j] = perm [j-1] + count [j-1] ; } for (j = 0 ; j < n ; j++) { count [j] = perm [j] ; } /* === Construct M ====================================================== */ mnz = perm [n] ; n_row = mnz / 2 ; Mlen = COLAMD_recommended (mnz, n_row, n) ; M = (Int *) ((*allocate) (Mlen, sizeof (Int))) ; DEBUG0 (("symamd: M is %d-by-%d with %d entries, Mlen = %g\n", n_row, n, mnz, (double) Mlen)) ; if (!M) { stats [COLAMD_STATUS] = COLAMD_ERROR_out_of_memory ; (*release) ((void *) count) ; (*release) ((void *) mark) ; DEBUG0 (("symamd: allocate M (size %g) failed\n", (double) Mlen)) ; return (FALSE) ; } k = 0 ; if (stats [COLAMD_STATUS] == COLAMD_OK) { /* Matrix is OK */ for (j = 0 ; j < n ; j++) { ASSERT (p [j+1] - p [j] >= 0) ; for (pp = p [j] ; pp < p [j+1] ; pp++) { i = A [pp] ; ASSERT (i >= 0 && i < n) ; if (i > j) { /* row k of M contains column indices i and j */ M [count [i]++] = k ; M [count [j]++] = k ; k++ ; } } } } else { /* Matrix is jumbled. Do not add duplicates to M. Unsorted cols OK. */ DEBUG0 (("symamd: Duplicates in A.\n")) ; for (i = 0 ; i < n ; i++) { mark [i] = -1 ; } for (j = 0 ; j < n ; j++) { ASSERT (p [j+1] - p [j] >= 0) ; for (pp = p [j] ; pp < p [j+1] ; pp++) { i = A [pp] ; ASSERT (i >= 0 && i < n) ; if (i > j && mark [i] != j) { /* row k of M contains column indices i and j */ M [count [i]++] = k ; M [count [j]++] = k ; k++ ; mark [i] = j ; } } } /* v2.4: free(mark) moved below */ } /* count and mark no longer needed */ (*release) ((void *) count) ; (*release) ((void *) mark) ; /* v2.4: free (mark) moved here */ ASSERT (k == n_row) ; /* === Adjust the knobs for M =========================================== */ for (i = 0 ; i < COLAMD_KNOBS ; i++) { cknobs [i] = knobs [i] ; } /* there are no dense rows in M */ cknobs [COLAMD_DENSE_ROW] = -1 ; cknobs [COLAMD_DENSE_COL] = knobs [COLAMD_DENSE_ROW] ; /* === Order the columns of M =========================================== */ /* v2.4: colamd cannot fail here, so the error check is removed */ (void) COLAMD_MAIN (n_row, n, (Int) Mlen, M, perm, cknobs, stats) ; /* Note that the output permutation is now in perm */ /* === get the statistics for symamd from colamd ======================== */ /* a dense column in colamd means a dense row and col in symamd */ stats [COLAMD_DENSE_ROW] = stats [COLAMD_DENSE_COL] ; /* === Free M =========================================================== */ (*release) ((void *) M) ; DEBUG0 (("symamd: done.\n")) ; return (TRUE) ; } /* ========================================================================== */ /* === colamd =============================================================== */ /* ========================================================================== */ /* The colamd routine computes a column ordering Q of a sparse matrix A such that the LU factorization P(AQ) = LU remains sparse, where P is selected via partial pivoting. The routine can also be viewed as providing a permutation Q such that the Cholesky factorization (AQ)'(AQ) = LL' remains sparse. */ PUBLIC Int COLAMD_MAIN /* returns TRUE if successful, FALSE otherwise*/ ( /* === Parameters ======================================================= */ Int n_row, /* number of rows in A */ Int n_col, /* number of columns in A */ Int Alen, /* length of A */ Int A [], /* row indices of A */ Int p [], /* pointers to columns in A */ double knobs [COLAMD_KNOBS],/* parameters (uses defaults if NULL) */ Int stats [COLAMD_STATS] /* output statistics and error codes */ ) { /* === Local variables ================================================== */ Int i ; /* loop index */ Int nnz ; /* nonzeros in A */ size_t Row_size ; /* size of Row [], in integers */ size_t Col_size ; /* size of Col [], in integers */ size_t need ; /* minimum required length of A */ Colamd_Row *Row ; /* pointer into A of Row [0..n_row] array */ Colamd_Col *Col ; /* pointer into A of Col [0..n_col] array */ Int n_col2 ; /* number of non-dense, non-empty columns */ Int n_row2 ; /* number of non-dense, non-empty rows */ Int ngarbage ; /* number of garbage collections performed */ Int max_deg ; /* maximum row degree */ double default_knobs [COLAMD_KNOBS] ; /* default knobs array */ Int aggressive ; /* do aggressive absorption */ int ok ; #ifndef NDEBUG colamd_get_debug ("colamd") ; #endif /* NDEBUG */ /* === Check the input arguments ======================================== */ if (!stats) { DEBUG0 (("colamd: stats not present\n")) ; return (FALSE) ; } for (i = 0 ; i < COLAMD_STATS ; i++) { stats [i] = 0 ; } stats [COLAMD_STATUS] = COLAMD_OK ; stats [COLAMD_INFO1] = -1 ; stats [COLAMD_INFO2] = -1 ; if (!A) /* A is not present */ { stats [COLAMD_STATUS] = COLAMD_ERROR_A_not_present ; DEBUG0 (("colamd: A not present\n")) ; return (FALSE) ; } if (!p) /* p is not present */ { stats [COLAMD_STATUS] = COLAMD_ERROR_p_not_present ; DEBUG0 (("colamd: p not present\n")) ; return (FALSE) ; } if (n_row < 0) /* n_row must be >= 0 */ { stats [COLAMD_STATUS] = COLAMD_ERROR_nrow_negative ; stats [COLAMD_INFO1] = n_row ; DEBUG0 (("colamd: nrow negative %d\n", n_row)) ; return (FALSE) ; } if (n_col < 0) /* n_col must be >= 0 */ { stats [COLAMD_STATUS] = COLAMD_ERROR_ncol_negative ; stats [COLAMD_INFO1] = n_col ; DEBUG0 (("colamd: ncol negative %d\n", n_col)) ; return (FALSE) ; } nnz = p [n_col] ; if (nnz < 0) /* nnz must be >= 0 */ { stats [COLAMD_STATUS] = COLAMD_ERROR_nnz_negative ; stats [COLAMD_INFO1] = nnz ; DEBUG0 (("colamd: number of entries negative %d\n", nnz)) ; return (FALSE) ; } if (p [0] != 0) { stats [COLAMD_STATUS] = COLAMD_ERROR_p0_nonzero ; stats [COLAMD_INFO1] = p [0] ; DEBUG0 (("colamd: p[0] not zero %d\n", p [0])) ; return (FALSE) ; } /* === If no knobs, set default knobs =================================== */ if (!knobs) { COLAMD_set_defaults (default_knobs) ; knobs = default_knobs ; } aggressive = (knobs [COLAMD_AGGRESSIVE] != FALSE) ; /* === Allocate the Row and Col arrays from array A ===================== */ ok = TRUE ; Col_size = COLAMD_C (n_col, &ok) ; /* size of Col array of structs */ Row_size = COLAMD_R (n_row, &ok) ; /* size of Row array of structs */ /* need = 2*nnz + n_col + Col_size + Row_size ; */ need = t_mult (nnz, 2, &ok) ; need = t_add (need, n_col, &ok) ; need = t_add (need, Col_size, &ok) ; need = t_add (need, Row_size, &ok) ; if (!ok || need > (size_t) Alen || need > Int_MAX) { /* not enough space in array A to perform the ordering */ stats [COLAMD_STATUS] = COLAMD_ERROR_A_too_small ; stats [COLAMD_INFO1] = need ; stats [COLAMD_INFO2] = Alen ; DEBUG0 (("colamd: Need Alen >= %d, given only Alen = %d\n", need,Alen)); return (FALSE) ; } Alen -= Col_size + Row_size ; Col = (Colamd_Col *) &A [Alen] ; Row = (Colamd_Row *) &A [Alen + Col_size] ; /* === Construct the row and column data structures ===================== */ if (!init_rows_cols (n_row, n_col, Row, Col, A, p, stats)) { /* input matrix is invalid */ DEBUG0 (("colamd: Matrix invalid\n")) ; return (FALSE) ; } /* === Initialize scores, kill dense rows/columns ======================= */ init_scoring (n_row, n_col, Row, Col, A, p, knobs, &n_row2, &n_col2, &max_deg) ; /* === Order the supercolumns =========================================== */ ngarbage = find_ordering (n_row, n_col, Alen, Row, Col, A, p, n_col2, max_deg, 2*nnz, aggressive) ; /* === Order the non-principal columns ================================== */ order_children (n_col, Col, p) ; /* === Return statistics in stats ======================================= */ stats [COLAMD_DENSE_ROW] = n_row - n_row2 ; stats [COLAMD_DENSE_COL] = n_col - n_col2 ; stats [COLAMD_DEFRAG_COUNT] = ngarbage ; DEBUG0 (("colamd: done.\n")) ; return (TRUE) ; } /* ========================================================================== */ /* === colamd_report ======================================================== */ /* ========================================================================== */ PUBLIC void COLAMD_report ( Int stats [COLAMD_STATS] ) { print_report ("colamd", stats) ; } /* ========================================================================== */ /* === symamd_report ======================================================== */ /* ========================================================================== */ PUBLIC void SYMAMD_report ( Int stats [COLAMD_STATS] ) { print_report ("symamd", stats) ; } /* ========================================================================== */ /* === NON-USER-CALLABLE ROUTINES: ========================================== */ /* ========================================================================== */ /* There are no user-callable routines beyond this point in the file */ /* ========================================================================== */ /* === init_rows_cols ======================================================= */ /* ========================================================================== */ /* Takes the column form of the matrix in A and creates the row form of the matrix. Also, row and column attributes are stored in the Col and Row structs. If the columns are un-sorted or contain duplicate row indices, this routine will also sort and remove duplicate row indices from the column form of the matrix. Returns FALSE if the matrix is invalid, TRUE otherwise. Not user-callable. */ PRIVATE Int init_rows_cols /* returns TRUE if OK, or FALSE otherwise */ ( /* === Parameters ======================================================= */ Int n_row, /* number of rows of A */ Int n_col, /* number of columns of A */ Colamd_Row Row [], /* of size n_row+1 */ Colamd_Col Col [], /* of size n_col+1 */ Int A [], /* row indices of A, of size Alen */ Int p [], /* pointers to columns in A, of size n_col+1 */ Int stats [COLAMD_STATS] /* colamd statistics */ ) { /* === Local variables ================================================== */ Int col ; /* a column index */ Int row ; /* a row index */ Int *cp ; /* a column pointer */ Int *cp_end ; /* a pointer to the end of a column */ Int *rp ; /* a row pointer */ Int *rp_end ; /* a pointer to the end of a row */ Int last_row ; /* previous row */ /* === Initialize columns, and check column pointers ==================== */ for (col = 0 ; col < n_col ; col++) { Col [col].start = p [col] ; Col [col].length = p [col+1] - p [col] ; if (Col [col].length < 0) { /* column pointers must be non-decreasing */ stats [COLAMD_STATUS] = COLAMD_ERROR_col_length_negative ; stats [COLAMD_INFO1] = col ; stats [COLAMD_INFO2] = Col [col].length ; DEBUG0 (("colamd: col %d length %d < 0\n", col, Col [col].length)) ; return (FALSE) ; } Col [col].shared1.thickness = 1 ; Col [col].shared2.score = 0 ; Col [col].shared3.prev = EMPTY ; Col [col].shared4.degree_next = EMPTY ; } /* p [0..n_col] no longer needed, used as "head" in subsequent routines */ /* === Scan columns, compute row degrees, and check row indices ========= */ stats [COLAMD_INFO3] = 0 ; /* number of duplicate or unsorted row indices*/ for (row = 0 ; row < n_row ; row++) { Row [row].length = 0 ; Row [row].shared2.mark = -1 ; } for (col = 0 ; col < n_col ; col++) { last_row = -1 ; cp = &A [p [col]] ; cp_end = &A [p [col+1]] ; while (cp < cp_end) { row = *cp++ ; /* make sure row indices within range */ if (row < 0 || row >= n_row) { stats [COLAMD_STATUS] = COLAMD_ERROR_row_index_out_of_bounds ; stats [COLAMD_INFO1] = col ; stats [COLAMD_INFO2] = row ; stats [COLAMD_INFO3] = n_row ; DEBUG0 (("colamd: row %d col %d out of bounds\n", row, col)) ; return (FALSE) ; } if (row <= last_row || Row [row].shared2.mark == col) { /* row index are unsorted or repeated (or both), thus col */ /* is jumbled. This is a notice, not an error condition. */ stats [COLAMD_STATUS] = COLAMD_OK_BUT_JUMBLED ; stats [COLAMD_INFO1] = col ; stats [COLAMD_INFO2] = row ; (stats [COLAMD_INFO3]) ++ ; DEBUG1 (("colamd: row %d col %d unsorted/duplicate\n",row,col)); } if (Row [row].shared2.mark != col) { Row [row].length++ ; } else { /* this is a repeated entry in the column, */ /* it will be removed */ Col [col].length-- ; } /* mark the row as having been seen in this column */ Row [row].shared2.mark = col ; last_row = row ; } } /* === Compute row pointers ============================================= */ /* row form of the matrix starts directly after the column */ /* form of matrix in A */ Row [0].start = p [n_col] ; Row [0].shared1.p = Row [0].start ; Row [0].shared2.mark = -1 ; for (row = 1 ; row < n_row ; row++) { Row [row].start = Row [row-1].start + Row [row-1].length ; Row [row].shared1.p = Row [row].start ; Row [row].shared2.mark = -1 ; } /* === Create row form ================================================== */ if (stats [COLAMD_STATUS] == COLAMD_OK_BUT_JUMBLED) { /* if cols jumbled, watch for repeated row indices */ for (col = 0 ; col < n_col ; col++) { cp = &A [p [col]] ; cp_end = &A [p [col+1]] ; while (cp < cp_end) { row = *cp++ ; if (Row [row].shared2.mark != col) { A [(Row [row].shared1.p)++] = col ; Row [row].shared2.mark = col ; } } } } else { /* if cols not jumbled, we don't need the mark (this is faster) */ for (col = 0 ; col < n_col ; col++) { cp = &A [p [col]] ; cp_end = &A [p [col+1]] ; while (cp < cp_end) { A [(Row [*cp++].shared1.p)++] = col ; } } } /* === Clear the row marks and set row degrees ========================== */ for (row = 0 ; row < n_row ; row++) { Row [row].shared2.mark = 0 ; Row [row].shared1.degree = Row [row].length ; } /* === See if we need to re-create columns ============================== */ if (stats [COLAMD_STATUS] == COLAMD_OK_BUT_JUMBLED) { DEBUG0 (("colamd: reconstructing column form, matrix jumbled\n")) ; #ifndef NDEBUG /* make sure column lengths are correct */ for (col = 0 ; col < n_col ; col++) { p [col] = Col [col].length ; } for (row = 0 ; row < n_row ; row++) { rp = &A [Row [row].start] ; rp_end = rp + Row [row].length ; while (rp < rp_end) { p [*rp++]-- ; } } for (col = 0 ; col < n_col ; col++) { ASSERT (p [col] == 0) ; } /* now p is all zero (different than when debugging is turned off) */ #endif /* NDEBUG */ /* === Compute col pointers ========================================= */ /* col form of the matrix starts at A [0]. */ /* Note, we may have a gap between the col form and the row */ /* form if there were duplicate entries, if so, it will be */ /* removed upon the first garbage collection */ Col [0].start = 0 ; p [0] = Col [0].start ; for (col = 1 ; col < n_col ; col++) { /* note that the lengths here are for pruned columns, i.e. */ /* no duplicate row indices will exist for these columns */ Col [col].start = Col [col-1].start + Col [col-1].length ; p [col] = Col [col].start ; } /* === Re-create col form =========================================== */ for (row = 0 ; row < n_row ; row++) { rp = &A [Row [row].start] ; rp_end = rp + Row [row].length ; while (rp < rp_end) { A [(p [*rp++])++] = row ; } } } /* === Done. Matrix is not (or no longer) jumbled ====================== */ return (TRUE) ; } /* ========================================================================== */ /* === init_scoring ========================================================= */ /* ========================================================================== */ /* Kills dense or empty columns and rows, calculates an initial score for each column, and places all columns in the degree lists. Not user-callable. */ PRIVATE void init_scoring ( /* === Parameters ======================================================= */ Int n_row, /* number of rows of A */ Int n_col, /* number of columns of A */ Colamd_Row Row [], /* of size n_row+1 */ Colamd_Col Col [], /* of size n_col+1 */ Int A [], /* column form and row form of A */ Int head [], /* of size n_col+1 */ double knobs [COLAMD_KNOBS],/* parameters */ Int *p_n_row2, /* number of non-dense, non-empty rows */ Int *p_n_col2, /* number of non-dense, non-empty columns */ Int *p_max_deg /* maximum row degree */ ) { /* === Local variables ================================================== */ Int c ; /* a column index */ Int r, row ; /* a row index */ Int *cp ; /* a column pointer */ Int deg ; /* degree of a row or column */ Int *cp_end ; /* a pointer to the end of a column */ Int *new_cp ; /* new column pointer */ Int col_length ; /* length of pruned column */ Int score ; /* current column score */ Int n_col2 ; /* number of non-dense, non-empty columns */ Int n_row2 ; /* number of non-dense, non-empty rows */ Int dense_row_count ; /* remove rows with more entries than this */ Int dense_col_count ; /* remove cols with more entries than this */ Int min_score ; /* smallest column score */ Int max_deg ; /* maximum row degree */ Int next_col ; /* Used to add to degree list.*/ #ifndef NDEBUG Int debug_count ; /* debug only. */ #endif /* NDEBUG */ /* === Extract knobs ==================================================== */ /* Note: if knobs contains a NaN, this is undefined: */ if (knobs [COLAMD_DENSE_ROW] < 0) { /* only remove completely dense rows */ dense_row_count = n_col-1 ; } else { dense_row_count = DENSE_DEGREE (knobs [COLAMD_DENSE_ROW], n_col) ; } if (knobs [COLAMD_DENSE_COL] < 0) { /* only remove completely dense columns */ dense_col_count = n_row-1 ; } else { dense_col_count = DENSE_DEGREE (knobs [COLAMD_DENSE_COL], MIN (n_row, n_col)) ; } DEBUG1 (("colamd: densecount: %d %d\n", dense_row_count, dense_col_count)) ; max_deg = 0 ; n_col2 = n_col ; n_row2 = n_row ; /* === Kill empty columns =============================================== */ /* Put the empty columns at the end in their natural order, so that LU */ /* factorization can proceed as far as possible. */ for (c = n_col-1 ; c >= 0 ; c--) { deg = Col [c].length ; if (deg == 0) { /* this is a empty column, kill and order it last */ Col [c].shared2.order = --n_col2 ; KILL_PRINCIPAL_COL (c) ; } } DEBUG1 (("colamd: null columns killed: %d\n", n_col - n_col2)) ; /* === Kill dense columns =============================================== */ /* Put the dense columns at the end, in their natural order */ for (c = n_col-1 ; c >= 0 ; c--) { /* skip any dead columns */ if (COL_IS_DEAD (c)) { continue ; } deg = Col [c].length ; if (deg > dense_col_count) { /* this is a dense column, kill and order it last */ Col [c].shared2.order = --n_col2 ; /* decrement the row degrees */ cp = &A [Col [c].start] ; cp_end = cp + Col [c].length ; while (cp < cp_end) { Row [*cp++].shared1.degree-- ; } KILL_PRINCIPAL_COL (c) ; } } DEBUG1 (("colamd: Dense and null columns killed: %d\n", n_col - n_col2)) ; /* === Kill dense and empty rows ======================================== */ for (r = 0 ; r < n_row ; r++) { deg = Row [r].shared1.degree ; ASSERT (deg >= 0 && deg <= n_col) ; if (deg > dense_row_count || deg == 0) { /* kill a dense or empty row */ KILL_ROW (r) ; --n_row2 ; } else { /* keep track of max degree of remaining rows */ max_deg = MAX (max_deg, deg) ; } } DEBUG1 (("colamd: Dense and null rows killed: %d\n", n_row - n_row2)) ; /* === Compute initial column scores ==================================== */ /* At this point the row degrees are accurate. They reflect the number */ /* of "live" (non-dense) columns in each row. No empty rows exist. */ /* Some "live" columns may contain only dead rows, however. These are */ /* pruned in the code below. */ /* now find the initial matlab score for each column */ for (c = n_col-1 ; c >= 0 ; c--) { /* skip dead column */ if (COL_IS_DEAD (c)) { continue ; } score = 0 ; cp = &A [Col [c].start] ; new_cp = cp ; cp_end = cp + Col [c].length ; while (cp < cp_end) { /* get a row */ row = *cp++ ; /* skip if dead */ if (ROW_IS_DEAD (row)) { continue ; } /* compact the column */ *new_cp++ = row ; /* add row's external degree */ score += Row [row].shared1.degree - 1 ; /* guard against integer overflow */ score = MIN (score, n_col) ; } /* determine pruned column length */ col_length = (Int) (new_cp - &A [Col [c].start]) ; if (col_length == 0) { /* a newly-made null column (all rows in this col are "dense" */ /* and have already been killed) */ DEBUG2 (("Newly null killed: %d\n", c)) ; Col [c].shared2.order = --n_col2 ; KILL_PRINCIPAL_COL (c) ; } else { /* set column length and set score */ ASSERT (score >= 0) ; ASSERT (score <= n_col) ; Col [c].length = col_length ; Col [c].shared2.score = score ; } } DEBUG1 (("colamd: Dense, null, and newly-null columns killed: %d\n", n_col-n_col2)) ; /* At this point, all empty rows and columns are dead. All live columns */ /* are "clean" (containing no dead rows) and simplicial (no supercolumns */ /* yet). Rows may contain dead columns, but all live rows contain at */ /* least one live column. */ #ifndef NDEBUG debug_structures (n_row, n_col, Row, Col, A, n_col2) ; #endif /* NDEBUG */ /* === Initialize degree lists ========================================== */ #ifndef NDEBUG debug_count = 0 ; #endif /* NDEBUG */ /* clear the hash buckets */ for (c = 0 ; c <= n_col ; c++) { head [c] = EMPTY ; } min_score = n_col ; /* place in reverse order, so low column indices are at the front */ /* of the lists. This is to encourage natural tie-breaking */ for (c = n_col-1 ; c >= 0 ; c--) { /* only add principal columns to degree lists */ if (COL_IS_ALIVE (c)) { DEBUG4 (("place %d score %d minscore %d ncol %d\n", c, Col [c].shared2.score, min_score, n_col)) ; /* === Add columns score to DList =============================== */ score = Col [c].shared2.score ; ASSERT (min_score >= 0) ; ASSERT (min_score <= n_col) ; ASSERT (score >= 0) ; ASSERT (score <= n_col) ; ASSERT (head [score] >= EMPTY) ; /* now add this column to dList at proper score location */ next_col = head [score] ; Col [c].shared3.prev = EMPTY ; Col [c].shared4.degree_next = next_col ; /* if there already was a column with the same score, set its */ /* previous pointer to this new column */ if (next_col != EMPTY) { Col [next_col].shared3.prev = c ; } head [score] = c ; /* see if this score is less than current min */ min_score = MIN (min_score, score) ; #ifndef NDEBUG debug_count++ ; #endif /* NDEBUG */ } } #ifndef NDEBUG DEBUG1 (("colamd: Live cols %d out of %d, non-princ: %d\n", debug_count, n_col, n_col-debug_count)) ; ASSERT (debug_count == n_col2) ; debug_deg_lists (n_row, n_col, Row, Col, head, min_score, n_col2, max_deg) ; #endif /* NDEBUG */ /* === Return number of remaining columns, and max row degree =========== */ *p_n_col2 = n_col2 ; *p_n_row2 = n_row2 ; *p_max_deg = max_deg ; } /* ========================================================================== */ /* === find_ordering ======================================================== */ /* ========================================================================== */ /* Order the principal columns of the supercolumn form of the matrix (no supercolumns on input). Uses a minimum approximate column minimum degree ordering method. Not user-callable. */ PRIVATE Int find_ordering /* return the number of garbage collections */ ( /* === Parameters ======================================================= */ Int n_row, /* number of rows of A */ Int n_col, /* number of columns of A */ Int Alen, /* size of A, 2*nnz + n_col or larger */ Colamd_Row Row [], /* of size n_row+1 */ Colamd_Col Col [], /* of size n_col+1 */ Int A [], /* column form and row form of A */ Int head [], /* of size n_col+1 */ Int n_col2, /* Remaining columns to order */ Int max_deg, /* Maximum row degree */ Int pfree, /* index of first free slot (2*nnz on entry) */ Int aggressive ) { /* === Local variables ================================================== */ Int k ; /* current pivot ordering step */ Int pivot_col ; /* current pivot column */ Int *cp ; /* a column pointer */ Int *rp ; /* a row pointer */ Int pivot_row ; /* current pivot row */ Int *new_cp ; /* modified column pointer */ Int *new_rp ; /* modified row pointer */ Int pivot_row_start ; /* pointer to start of pivot row */ Int pivot_row_degree ; /* number of columns in pivot row */ Int pivot_row_length ; /* number of supercolumns in pivot row */ Int pivot_col_score ; /* score of pivot column */ Int needed_memory ; /* free space needed for pivot row */ Int *cp_end ; /* pointer to the end of a column */ Int *rp_end ; /* pointer to the end of a row */ Int row ; /* a row index */ Int col ; /* a column index */ Int max_score ; /* maximum possible score */ Int cur_score ; /* score of current column */ unsigned Int hash ; /* hash value for supernode detection */ Int head_column ; /* head of hash bucket */ Int first_col ; /* first column in hash bucket */ Int tag_mark ; /* marker value for mark array */ Int row_mark ; /* Row [row].shared2.mark */ Int set_difference ; /* set difference size of row with pivot row */ Int min_score ; /* smallest column score */ Int col_thickness ; /* "thickness" (no. of columns in a supercol) */ Int max_mark ; /* maximum value of tag_mark */ Int pivot_col_thickness ; /* number of columns represented by pivot col */ Int prev_col ; /* Used by Dlist operations. */ Int next_col ; /* Used by Dlist operations. */ Int ngarbage ; /* number of garbage collections performed */ #ifndef NDEBUG Int debug_d ; /* debug loop counter */ Int debug_step = 0 ; /* debug loop counter */ #endif /* NDEBUG */ /* === Initialization and clear mark ==================================== */ max_mark = INT_MAX - n_col ; /* INT_MAX defined in */ tag_mark = clear_mark (0, max_mark, n_row, Row) ; min_score = 0 ; ngarbage = 0 ; DEBUG1 (("colamd: Ordering, n_col2=%d\n", n_col2)) ; /* === Order the columns ================================================ */ for (k = 0 ; k < n_col2 ; /* 'k' is incremented below */) { #ifndef NDEBUG if (debug_step % 100 == 0) { DEBUG2 (("\n... Step k: %d out of n_col2: %d\n", k, n_col2)) ; } else { DEBUG3 (("\n----------Step k: %d out of n_col2: %d\n", k, n_col2)) ; } debug_step++ ; debug_deg_lists (n_row, n_col, Row, Col, head, min_score, n_col2-k, max_deg) ; debug_matrix (n_row, n_col, Row, Col, A) ; #endif /* NDEBUG */ /* === Select pivot column, and order it ============================ */ /* make sure degree list isn't empty */ ASSERT (min_score >= 0) ; ASSERT (min_score <= n_col) ; ASSERT (head [min_score] >= EMPTY) ; #ifndef NDEBUG for (debug_d = 0 ; debug_d < min_score ; debug_d++) { ASSERT (head [debug_d] == EMPTY) ; } #endif /* NDEBUG */ /* get pivot column from head of minimum degree list */ while (head [min_score] == EMPTY && min_score < n_col) { min_score++ ; } pivot_col = head [min_score] ; ASSERT (pivot_col >= 0 && pivot_col <= n_col) ; next_col = Col [pivot_col].shared4.degree_next ; head [min_score] = next_col ; if (next_col != EMPTY) { Col [next_col].shared3.prev = EMPTY ; } ASSERT (COL_IS_ALIVE (pivot_col)) ; /* remember score for defrag check */ pivot_col_score = Col [pivot_col].shared2.score ; /* the pivot column is the kth column in the pivot order */ Col [pivot_col].shared2.order = k ; /* increment order count by column thickness */ pivot_col_thickness = Col [pivot_col].shared1.thickness ; k += pivot_col_thickness ; ASSERT (pivot_col_thickness > 0) ; DEBUG3 (("Pivot col: %d thick %d\n", pivot_col, pivot_col_thickness)) ; /* === Garbage_collection, if necessary ============================= */ needed_memory = MIN (pivot_col_score, n_col - k) ; if (pfree + needed_memory >= Alen) { pfree = garbage_collection (n_row, n_col, Row, Col, A, &A [pfree]) ; ngarbage++ ; /* after garbage collection we will have enough */ ASSERT (pfree + needed_memory < Alen) ; /* garbage collection has wiped out the Row[].shared2.mark array */ tag_mark = clear_mark (0, max_mark, n_row, Row) ; #ifndef NDEBUG debug_matrix (n_row, n_col, Row, Col, A) ; #endif /* NDEBUG */ } /* === Compute pivot row pattern ==================================== */ /* get starting location for this new merged row */ pivot_row_start = pfree ; /* initialize new row counts to zero */ pivot_row_degree = 0 ; /* tag pivot column as having been visited so it isn't included */ /* in merged pivot row */ Col [pivot_col].shared1.thickness = -pivot_col_thickness ; /* pivot row is the union of all rows in the pivot column pattern */ cp = &A [Col [pivot_col].start] ; cp_end = cp + Col [pivot_col].length ; while (cp < cp_end) { /* get a row */ row = *cp++ ; DEBUG4 (("Pivot col pattern %d %d\n", ROW_IS_ALIVE (row), row)) ; /* skip if row is dead */ if (ROW_IS_ALIVE (row)) { rp = &A [Row [row].start] ; rp_end = rp + Row [row].length ; while (rp < rp_end) { /* get a column */ col = *rp++ ; /* add the column, if alive and untagged */ col_thickness = Col [col].shared1.thickness ; if (col_thickness > 0 && COL_IS_ALIVE (col)) { /* tag column in pivot row */ Col [col].shared1.thickness = -col_thickness ; ASSERT (pfree < Alen) ; /* place column in pivot row */ A [pfree++] = col ; pivot_row_degree += col_thickness ; } } } } /* clear tag on pivot column */ Col [pivot_col].shared1.thickness = pivot_col_thickness ; max_deg = MAX (max_deg, pivot_row_degree) ; #ifndef NDEBUG DEBUG3 (("check2\n")) ; debug_mark (n_row, Row, tag_mark, max_mark) ; #endif /* NDEBUG */ /* === Kill all rows used to construct pivot row ==================== */ /* also kill pivot row, temporarily */ cp = &A [Col [pivot_col].start] ; cp_end = cp + Col [pivot_col].length ; while (cp < cp_end) { /* may be killing an already dead row */ row = *cp++ ; DEBUG3 (("Kill row in pivot col: %d\n", row)) ; KILL_ROW (row) ; } /* === Select a row index to use as the new pivot row =============== */ pivot_row_length = pfree - pivot_row_start ; if (pivot_row_length > 0) { /* pick the "pivot" row arbitrarily (first row in col) */ pivot_row = A [Col [pivot_col].start] ; DEBUG3 (("Pivotal row is %d\n", pivot_row)) ; } else { /* there is no pivot row, since it is of zero length */ pivot_row = EMPTY ; ASSERT (pivot_row_length == 0) ; } ASSERT (Col [pivot_col].length > 0 || pivot_row_length == 0) ; /* === Approximate degree computation =============================== */ /* Here begins the computation of the approximate degree. The column */ /* score is the sum of the pivot row "length", plus the size of the */ /* set differences of each row in the column minus the pattern of the */ /* pivot row itself. The column ("thickness") itself is also */ /* excluded from the column score (we thus use an approximate */ /* external degree). */ /* The time taken by the following code (compute set differences, and */ /* add them up) is proportional to the size of the data structure */ /* being scanned - that is, the sum of the sizes of each column in */ /* the pivot row. Thus, the amortized time to compute a column score */ /* is proportional to the size of that column (where size, in this */ /* context, is the column "length", or the number of row indices */ /* in that column). The number of row indices in a column is */ /* monotonically non-decreasing, from the length of the original */ /* column on input to colamd. */ /* === Compute set differences ====================================== */ DEBUG3 (("** Computing set differences phase. **\n")) ; /* pivot row is currently dead - it will be revived later. */ DEBUG3 (("Pivot row: ")) ; /* for each column in pivot row */ rp = &A [pivot_row_start] ; rp_end = rp + pivot_row_length ; while (rp < rp_end) { col = *rp++ ; ASSERT (COL_IS_ALIVE (col) && col != pivot_col) ; DEBUG3 (("Col: %d\n", col)) ; /* clear tags used to construct pivot row pattern */ col_thickness = -Col [col].shared1.thickness ; ASSERT (col_thickness > 0) ; Col [col].shared1.thickness = col_thickness ; /* === Remove column from degree list =========================== */ cur_score = Col [col].shared2.score ; prev_col = Col [col].shared3.prev ; next_col = Col [col].shared4.degree_next ; ASSERT (cur_score >= 0) ; ASSERT (cur_score <= n_col) ; ASSERT (cur_score >= EMPTY) ; if (prev_col == EMPTY) { head [cur_score] = next_col ; } else { Col [prev_col].shared4.degree_next = next_col ; } if (next_col != EMPTY) { Col [next_col].shared3.prev = prev_col ; } /* === Scan the column ========================================== */ cp = &A [Col [col].start] ; cp_end = cp + Col [col].length ; while (cp < cp_end) { /* get a row */ row = *cp++ ; row_mark = Row [row].shared2.mark ; /* skip if dead */ if (ROW_IS_MARKED_DEAD (row_mark)) { continue ; } ASSERT (row != pivot_row) ; set_difference = row_mark - tag_mark ; /* check if the row has been seen yet */ if (set_difference < 0) { ASSERT (Row [row].shared1.degree <= max_deg) ; set_difference = Row [row].shared1.degree ; } /* subtract column thickness from this row's set difference */ set_difference -= col_thickness ; ASSERT (set_difference >= 0) ; /* absorb this row if the set difference becomes zero */ if (set_difference == 0 && aggressive) { DEBUG3 (("aggressive absorption. Row: %d\n", row)) ; KILL_ROW (row) ; } else { /* save the new mark */ Row [row].shared2.mark = set_difference + tag_mark ; } } } #ifndef NDEBUG debug_deg_lists (n_row, n_col, Row, Col, head, min_score, n_col2-k-pivot_row_degree, max_deg) ; #endif /* NDEBUG */ /* === Add up set differences for each column ======================= */ DEBUG3 (("** Adding set differences phase. **\n")) ; /* for each column in pivot row */ rp = &A [pivot_row_start] ; rp_end = rp + pivot_row_length ; while (rp < rp_end) { /* get a column */ col = *rp++ ; ASSERT (COL_IS_ALIVE (col) && col != pivot_col) ; hash = 0 ; cur_score = 0 ; cp = &A [Col [col].start] ; /* compact the column */ new_cp = cp ; cp_end = cp + Col [col].length ; DEBUG4 (("Adding set diffs for Col: %d.\n", col)) ; while (cp < cp_end) { /* get a row */ row = *cp++ ; ASSERT(row >= 0 && row < n_row) ; row_mark = Row [row].shared2.mark ; /* skip if dead */ if (ROW_IS_MARKED_DEAD (row_mark)) { DEBUG4 ((" Row %d, dead\n", row)) ; continue ; } DEBUG4 ((" Row %d, set diff %d\n", row, row_mark-tag_mark)); ASSERT (row_mark >= tag_mark) ; /* compact the column */ *new_cp++ = row ; /* compute hash function */ hash += row ; /* add set difference */ cur_score += row_mark - tag_mark ; /* integer overflow... */ cur_score = MIN (cur_score, n_col) ; } /* recompute the column's length */ Col [col].length = (Int) (new_cp - &A [Col [col].start]) ; /* === Further mass elimination ================================= */ if (Col [col].length == 0) { DEBUG4 (("further mass elimination. Col: %d\n", col)) ; /* nothing left but the pivot row in this column */ KILL_PRINCIPAL_COL (col) ; pivot_row_degree -= Col [col].shared1.thickness ; ASSERT (pivot_row_degree >= 0) ; /* order it */ Col [col].shared2.order = k ; /* increment order count by column thickness */ k += Col [col].shared1.thickness ; } else { /* === Prepare for supercolumn detection ==================== */ DEBUG4 (("Preparing supercol detection for Col: %d.\n", col)) ; /* save score so far */ Col [col].shared2.score = cur_score ; /* add column to hash table, for supercolumn detection */ hash %= n_col + 1 ; DEBUG4 ((" Hash = %d, n_col = %d.\n", hash, n_col)) ; ASSERT (((Int) hash) <= n_col) ; head_column = head [hash] ; if (head_column > EMPTY) { /* degree list "hash" is non-empty, use prev (shared3) of */ /* first column in degree list as head of hash bucket */ first_col = Col [head_column].shared3.headhash ; Col [head_column].shared3.headhash = col ; } else { /* degree list "hash" is empty, use head as hash bucket */ first_col = - (head_column + 2) ; head [hash] = - (col + 2) ; } Col [col].shared4.hash_next = first_col ; /* save hash function in Col [col].shared3.hash */ Col [col].shared3.hash = (Int) hash ; ASSERT (COL_IS_ALIVE (col)) ; } } /* The approximate external column degree is now computed. */ /* === Supercolumn detection ======================================== */ DEBUG3 (("** Supercolumn detection phase. **\n")) ; detect_super_cols ( #ifndef NDEBUG n_col, Row, #endif /* NDEBUG */ Col, A, head, pivot_row_start, pivot_row_length) ; /* === Kill the pivotal column ====================================== */ KILL_PRINCIPAL_COL (pivot_col) ; /* === Clear mark =================================================== */ tag_mark = clear_mark (tag_mark+max_deg+1, max_mark, n_row, Row) ; #ifndef NDEBUG DEBUG3 (("check3\n")) ; debug_mark (n_row, Row, tag_mark, max_mark) ; #endif /* NDEBUG */ /* === Finalize the new pivot row, and column scores ================ */ DEBUG3 (("** Finalize scores phase. **\n")) ; /* for each column in pivot row */ rp = &A [pivot_row_start] ; /* compact the pivot row */ new_rp = rp ; rp_end = rp + pivot_row_length ; while (rp < rp_end) { col = *rp++ ; /* skip dead columns */ if (COL_IS_DEAD (col)) { continue ; } *new_rp++ = col ; /* add new pivot row to column */ A [Col [col].start + (Col [col].length++)] = pivot_row ; /* retrieve score so far and add on pivot row's degree. */ /* (we wait until here for this in case the pivot */ /* row's degree was reduced due to mass elimination). */ cur_score = Col [col].shared2.score + pivot_row_degree ; /* calculate the max possible score as the number of */ /* external columns minus the 'k' value minus the */ /* columns thickness */ max_score = n_col - k - Col [col].shared1.thickness ; /* make the score the external degree of the union-of-rows */ cur_score -= Col [col].shared1.thickness ; /* make sure score is less or equal than the max score */ cur_score = MIN (cur_score, max_score) ; ASSERT (cur_score >= 0) ; /* store updated score */ Col [col].shared2.score = cur_score ; /* === Place column back in degree list ========================= */ ASSERT (min_score >= 0) ; ASSERT (min_score <= n_col) ; ASSERT (cur_score >= 0) ; ASSERT (cur_score <= n_col) ; ASSERT (head [cur_score] >= EMPTY) ; next_col = head [cur_score] ; Col [col].shared4.degree_next = next_col ; Col [col].shared3.prev = EMPTY ; if (next_col != EMPTY) { Col [next_col].shared3.prev = col ; } head [cur_score] = col ; /* see if this score is less than current min */ min_score = MIN (min_score, cur_score) ; } #ifndef NDEBUG debug_deg_lists (n_row, n_col, Row, Col, head, min_score, n_col2-k, max_deg) ; #endif /* NDEBUG */ /* === Resurrect the new pivot row ================================== */ if (pivot_row_degree > 0) { /* update pivot row length to reflect any cols that were killed */ /* during super-col detection and mass elimination */ Row [pivot_row].start = pivot_row_start ; Row [pivot_row].length = (Int) (new_rp - &A[pivot_row_start]) ; ASSERT (Row [pivot_row].length > 0) ; Row [pivot_row].shared1.degree = pivot_row_degree ; Row [pivot_row].shared2.mark = 0 ; /* pivot row is no longer dead */ DEBUG1 (("Resurrect Pivot_row %d deg: %d\n", pivot_row, pivot_row_degree)) ; } } /* === All principal columns have now been ordered ====================== */ return (ngarbage) ; } /* ========================================================================== */ /* === order_children ======================================================= */ /* ========================================================================== */ /* The find_ordering routine has ordered all of the principal columns (the representatives of the supercolumns). The non-principal columns have not yet been ordered. This routine orders those columns by walking up the parent tree (a column is a child of the column which absorbed it). The final permutation vector is then placed in p [0 ... n_col-1], with p [0] being the first column, and p [n_col-1] being the last. It doesn't look like it at first glance, but be assured that this routine takes time linear in the number of columns. Although not immediately obvious, the time taken by this routine is O (n_col), that is, linear in the number of columns. Not user-callable. */ PRIVATE void order_children ( /* === Parameters ======================================================= */ Int n_col, /* number of columns of A */ Colamd_Col Col [], /* of size n_col+1 */ Int p [] /* p [0 ... n_col-1] is the column permutation*/ ) { /* === Local variables ================================================== */ Int i ; /* loop counter for all columns */ Int c ; /* column index */ Int parent ; /* index of column's parent */ Int order ; /* column's order */ /* === Order each non-principal column ================================== */ for (i = 0 ; i < n_col ; i++) { /* find an un-ordered non-principal column */ ASSERT (COL_IS_DEAD (i)) ; if (!COL_IS_DEAD_PRINCIPAL (i) && Col [i].shared2.order == EMPTY) { parent = i ; /* once found, find its principal parent */ do { parent = Col [parent].shared1.parent ; } while (!COL_IS_DEAD_PRINCIPAL (parent)) ; /* now, order all un-ordered non-principal columns along path */ /* to this parent. collapse tree at the same time */ c = i ; /* get order of parent */ order = Col [parent].shared2.order ; do { ASSERT (Col [c].shared2.order == EMPTY) ; /* order this column */ Col [c].shared2.order = order++ ; /* collaps tree */ Col [c].shared1.parent = parent ; /* get immediate parent of this column */ c = Col [c].shared1.parent ; /* continue until we hit an ordered column. There are */ /* guarranteed not to be anymore unordered columns */ /* above an ordered column */ } while (Col [c].shared2.order == EMPTY) ; /* re-order the super_col parent to largest order for this group */ Col [parent].shared2.order = order ; } } /* === Generate the permutation ========================================= */ for (c = 0 ; c < n_col ; c++) { p [Col [c].shared2.order] = c ; } } /* ========================================================================== */ /* === detect_super_cols ==================================================== */ /* ========================================================================== */ /* Detects supercolumns by finding matches between columns in the hash buckets. Check amongst columns in the set A [row_start ... row_start + row_length-1]. The columns under consideration are currently *not* in the degree lists, and have already been placed in the hash buckets. The hash bucket for columns whose hash function is equal to h is stored as follows: if head [h] is >= 0, then head [h] contains a degree list, so: head [h] is the first column in degree bucket h. Col [head [h]].headhash gives the first column in hash bucket h. otherwise, the degree list is empty, and: -(head [h] + 2) is the first column in hash bucket h. For a column c in a hash bucket, Col [c].shared3.prev is NOT a "previous column" pointer. Col [c].shared3.hash is used instead as the hash number for that column. The value of Col [c].shared4.hash_next is the next column in the same hash bucket. Assuming no, or "few" hash collisions, the time taken by this routine is linear in the sum of the sizes (lengths) of each column whose score has just been computed in the approximate degree computation. Not user-callable. */ PRIVATE void detect_super_cols ( /* === Parameters ======================================================= */ #ifndef NDEBUG /* these two parameters are only needed when debugging is enabled: */ Int n_col, /* number of columns of A */ Colamd_Row Row [], /* of size n_row+1 */ #endif /* NDEBUG */ Colamd_Col Col [], /* of size n_col+1 */ Int A [], /* row indices of A */ Int head [], /* head of degree lists and hash buckets */ Int row_start, /* pointer to set of columns to check */ Int row_length /* number of columns to check */ ) { /* === Local variables ================================================== */ Int hash ; /* hash value for a column */ Int *rp ; /* pointer to a row */ Int c ; /* a column index */ Int super_c ; /* column index of the column to absorb into */ Int *cp1 ; /* column pointer for column super_c */ Int *cp2 ; /* column pointer for column c */ Int length ; /* length of column super_c */ Int prev_c ; /* column preceding c in hash bucket */ Int i ; /* loop counter */ Int *rp_end ; /* pointer to the end of the row */ Int col ; /* a column index in the row to check */ Int head_column ; /* first column in hash bucket or degree list */ Int first_col ; /* first column in hash bucket */ /* === Consider each column in the row ================================== */ rp = &A [row_start] ; rp_end = rp + row_length ; while (rp < rp_end) { col = *rp++ ; if (COL_IS_DEAD (col)) { continue ; } /* get hash number for this column */ hash = Col [col].shared3.hash ; ASSERT (hash <= n_col) ; /* === Get the first column in this hash bucket ===================== */ head_column = head [hash] ; if (head_column > EMPTY) { first_col = Col [head_column].shared3.headhash ; } else { first_col = - (head_column + 2) ; } /* === Consider each column in the hash bucket ====================== */ for (super_c = first_col ; super_c != EMPTY ; super_c = Col [super_c].shared4.hash_next) { ASSERT (COL_IS_ALIVE (super_c)) ; ASSERT (Col [super_c].shared3.hash == hash) ; length = Col [super_c].length ; /* prev_c is the column preceding column c in the hash bucket */ prev_c = super_c ; /* === Compare super_c with all columns after it ================ */ for (c = Col [super_c].shared4.hash_next ; c != EMPTY ; c = Col [c].shared4.hash_next) { ASSERT (c != super_c) ; ASSERT (COL_IS_ALIVE (c)) ; ASSERT (Col [c].shared3.hash == hash) ; /* not identical if lengths or scores are different */ if (Col [c].length != length || Col [c].shared2.score != Col [super_c].shared2.score) { prev_c = c ; continue ; } /* compare the two columns */ cp1 = &A [Col [super_c].start] ; cp2 = &A [Col [c].start] ; for (i = 0 ; i < length ; i++) { /* the columns are "clean" (no dead rows) */ ASSERT (ROW_IS_ALIVE (*cp1)) ; ASSERT (ROW_IS_ALIVE (*cp2)) ; /* row indices will same order for both supercols, */ /* no gather scatter nessasary */ if (*cp1++ != *cp2++) { break ; } } /* the two columns are different if the for-loop "broke" */ if (i != length) { prev_c = c ; continue ; } /* === Got it! two columns are identical =================== */ ASSERT (Col [c].shared2.score == Col [super_c].shared2.score) ; Col [super_c].shared1.thickness += Col [c].shared1.thickness ; Col [c].shared1.parent = super_c ; KILL_NON_PRINCIPAL_COL (c) ; /* order c later, in order_children() */ Col [c].shared2.order = EMPTY ; /* remove c from hash bucket */ Col [prev_c].shared4.hash_next = Col [c].shared4.hash_next ; } } /* === Empty this hash bucket ======================================= */ if (head_column > EMPTY) { /* corresponding degree list "hash" is not empty */ Col [head_column].shared3.headhash = EMPTY ; } else { /* corresponding degree list "hash" is empty */ head [hash] = EMPTY ; } } } /* ========================================================================== */ /* === garbage_collection =================================================== */ /* ========================================================================== */ /* Defragments and compacts columns and rows in the workspace A. Used when all avaliable memory has been used while performing row merging. Returns the index of the first free position in A, after garbage collection. The time taken by this routine is linear is the size of the array A, which is itself linear in the number of nonzeros in the input matrix. Not user-callable. */ PRIVATE Int garbage_collection /* returns the new value of pfree */ ( /* === Parameters ======================================================= */ Int n_row, /* number of rows */ Int n_col, /* number of columns */ Colamd_Row Row [], /* row info */ Colamd_Col Col [], /* column info */ Int A [], /* A [0 ... Alen-1] holds the matrix */ Int *pfree /* &A [0] ... pfree is in use */ ) { /* === Local variables ================================================== */ Int *psrc ; /* source pointer */ Int *pdest ; /* destination pointer */ Int j ; /* counter */ Int r ; /* a row index */ Int c ; /* a column index */ Int length ; /* length of a row or column */ #ifndef NDEBUG Int debug_rows ; DEBUG2 (("Defrag..\n")) ; for (psrc = &A[0] ; psrc < pfree ; psrc++) ASSERT (*psrc >= 0) ; debug_rows = 0 ; #endif /* NDEBUG */ /* === Defragment the columns =========================================== */ pdest = &A[0] ; for (c = 0 ; c < n_col ; c++) { if (COL_IS_ALIVE (c)) { psrc = &A [Col [c].start] ; /* move and compact the column */ ASSERT (pdest <= psrc) ; Col [c].start = (Int) (pdest - &A [0]) ; length = Col [c].length ; for (j = 0 ; j < length ; j++) { r = *psrc++ ; if (ROW_IS_ALIVE (r)) { *pdest++ = r ; } } Col [c].length = (Int) (pdest - &A [Col [c].start]) ; } } /* === Prepare to defragment the rows =================================== */ for (r = 0 ; r < n_row ; r++) { if (ROW_IS_DEAD (r) || (Row [r].length == 0)) { /* This row is already dead, or is of zero length. Cannot compact * a row of zero length, so kill it. NOTE: in the current version, * there are no zero-length live rows. Kill the row (for the first * time, or again) just to be safe. */ KILL_ROW (r) ; } else { /* save first column index in Row [r].shared2.first_column */ psrc = &A [Row [r].start] ; Row [r].shared2.first_column = *psrc ; ASSERT (ROW_IS_ALIVE (r)) ; /* flag the start of the row with the one's complement of row */ *psrc = ONES_COMPLEMENT (r) ; #ifndef NDEBUG debug_rows++ ; #endif /* NDEBUG */ } } /* === Defragment the rows ============================================== */ psrc = pdest ; while (psrc < pfree) { /* find a negative number ... the start of a row */ if (*psrc++ < 0) { psrc-- ; /* get the row index */ r = ONES_COMPLEMENT (*psrc) ; ASSERT (r >= 0 && r < n_row) ; /* restore first column index */ *psrc = Row [r].shared2.first_column ; ASSERT (ROW_IS_ALIVE (r)) ; ASSERT (Row [r].length > 0) ; /* move and compact the row */ ASSERT (pdest <= psrc) ; Row [r].start = (Int) (pdest - &A [0]) ; length = Row [r].length ; for (j = 0 ; j < length ; j++) { c = *psrc++ ; if (COL_IS_ALIVE (c)) { *pdest++ = c ; } } Row [r].length = (Int) (pdest - &A [Row [r].start]) ; ASSERT (Row [r].length > 0) ; #ifndef NDEBUG debug_rows-- ; #endif /* NDEBUG */ } } /* ensure we found all the rows */ ASSERT (debug_rows == 0) ; /* === Return the new value of pfree ==================================== */ return ((Int) (pdest - &A [0])) ; } /* ========================================================================== */ /* === clear_mark =========================================================== */ /* ========================================================================== */ /* Clears the Row [].shared2.mark array, and returns the new tag_mark. Return value is the new tag_mark. Not user-callable. */ PRIVATE Int clear_mark /* return the new value for tag_mark */ ( /* === Parameters ======================================================= */ Int tag_mark, /* new value of tag_mark */ Int max_mark, /* max allowed value of tag_mark */ Int n_row, /* number of rows in A */ Colamd_Row Row [] /* Row [0 ... n_row-1].shared2.mark is set to zero */ ) { /* === Local variables ================================================== */ Int r ; if (tag_mark <= 0 || tag_mark >= max_mark) { for (r = 0 ; r < n_row ; r++) { if (ROW_IS_ALIVE (r)) { Row [r].shared2.mark = 0 ; } } tag_mark = 1 ; } return (tag_mark) ; } /* ========================================================================== */ /* === print_report ========================================================= */ /* ========================================================================== */ PRIVATE void print_report ( char *method, Int stats [COLAMD_STATS] ) { Int i1, i2, i3 ; PRINTF (("\n%s version %d.%d, %s: ", method, COLAMD_MAIN_VERSION, COLAMD_SUB_VERSION, COLAMD_DATE)) ; if (!stats) { PRINTF (("No statistics available.\n")) ; return ; } i1 = stats [COLAMD_INFO1] ; i2 = stats [COLAMD_INFO2] ; i3 = stats [COLAMD_INFO3] ; if (stats [COLAMD_STATUS] >= 0) { PRINTF (("OK. ")) ; } else { PRINTF (("ERROR. ")) ; } switch (stats [COLAMD_STATUS]) { case COLAMD_OK_BUT_JUMBLED: PRINTF(("Matrix has unsorted or duplicate row indices.\n")) ; PRINTF(("%s: number of duplicate or out-of-order row indices: %d\n", method, i3)) ; PRINTF(("%s: last seen duplicate or out-of-order row index: %d\n", method, INDEX (i2))) ; PRINTF(("%s: last seen in column: %d", method, INDEX (i1))) ; /* no break - fall through to next case instead */ case COLAMD_OK: PRINTF(("\n")) ; PRINTF(("%s: number of dense or empty rows ignored: %d\n", method, stats [COLAMD_DENSE_ROW])) ; PRINTF(("%s: number of dense or empty columns ignored: %d\n", method, stats [COLAMD_DENSE_COL])) ; PRINTF(("%s: number of garbage collections performed: %d\n", method, stats [COLAMD_DEFRAG_COUNT])) ; break ; case COLAMD_ERROR_A_not_present: PRINTF(("Array A (row indices of matrix) not present.\n")) ; break ; case COLAMD_ERROR_p_not_present: PRINTF(("Array p (column pointers for matrix) not present.\n")) ; break ; case COLAMD_ERROR_nrow_negative: PRINTF(("Invalid number of rows (%d).\n", i1)) ; break ; case COLAMD_ERROR_ncol_negative: PRINTF(("Invalid number of columns (%d).\n", i1)) ; break ; case COLAMD_ERROR_nnz_negative: PRINTF(("Invalid number of nonzero entries (%d).\n", i1)) ; break ; case COLAMD_ERROR_p0_nonzero: PRINTF(("Invalid column pointer, p [0] = %d, must be zero.\n", i1)); break ; case COLAMD_ERROR_A_too_small: PRINTF(("Array A too small.\n")) ; PRINTF((" Need Alen >= %d, but given only Alen = %d.\n", i1, i2)) ; break ; case COLAMD_ERROR_col_length_negative: PRINTF (("Column %d has a negative number of nonzero entries (%d).\n", INDEX (i1), i2)) ; break ; case COLAMD_ERROR_row_index_out_of_bounds: PRINTF (("Row index (row %d) out of bounds (%d to %d) in column %d.\n", INDEX (i2), INDEX (0), INDEX (i3-1), INDEX (i1))) ; break ; case COLAMD_ERROR_out_of_memory: PRINTF(("Out of memory.\n")) ; break ; /* v2.4: internal-error case deleted */ } } /* ========================================================================== */ /* === colamd debugging routines ============================================ */ /* ========================================================================== */ /* When debugging is disabled, the remainder of this file is ignored. */ #ifndef NDEBUG /* ========================================================================== */ /* === debug_structures ===================================================== */ /* ========================================================================== */ /* At this point, all empty rows and columns are dead. All live columns are "clean" (containing no dead rows) and simplicial (no supercolumns yet). Rows may contain dead columns, but all live rows contain at least one live column. */ PRIVATE void debug_structures ( /* === Parameters ======================================================= */ Int n_row, Int n_col, Colamd_Row Row [], Colamd_Col Col [], Int A [], Int n_col2 ) { /* === Local variables ================================================== */ Int i ; Int c ; Int *cp ; Int *cp_end ; Int len ; Int score ; Int r ; Int *rp ; Int *rp_end ; Int deg ; /* === Check A, Row, and Col ============================================ */ for (c = 0 ; c < n_col ; c++) { if (COL_IS_ALIVE (c)) { len = Col [c].length ; score = Col [c].shared2.score ; DEBUG4 (("initial live col %5d %5d %5d\n", c, len, score)) ; ASSERT (len > 0) ; ASSERT (score >= 0) ; ASSERT (Col [c].shared1.thickness == 1) ; cp = &A [Col [c].start] ; cp_end = cp + len ; while (cp < cp_end) { r = *cp++ ; ASSERT (ROW_IS_ALIVE (r)) ; } } else { i = Col [c].shared2.order ; ASSERT (i >= n_col2 && i < n_col) ; } } for (r = 0 ; r < n_row ; r++) { if (ROW_IS_ALIVE (r)) { i = 0 ; len = Row [r].length ; deg = Row [r].shared1.degree ; ASSERT (len > 0) ; ASSERT (deg > 0) ; rp = &A [Row [r].start] ; rp_end = rp + len ; while (rp < rp_end) { c = *rp++ ; if (COL_IS_ALIVE (c)) { i++ ; } } ASSERT (i > 0) ; } } } /* ========================================================================== */ /* === debug_deg_lists ====================================================== */ /* ========================================================================== */ /* Prints the contents of the degree lists. Counts the number of columns in the degree list and compares it to the total it should have. Also checks the row degrees. */ PRIVATE void debug_deg_lists ( /* === Parameters ======================================================= */ Int n_row, Int n_col, Colamd_Row Row [], Colamd_Col Col [], Int head [], Int min_score, Int should, Int max_deg ) { /* === Local variables ================================================== */ Int deg ; Int col ; Int have ; Int row ; /* === Check the degree lists =========================================== */ if (n_col > 10000 && colamd_debug <= 0) { return ; } have = 0 ; DEBUG4 (("Degree lists: %d\n", min_score)) ; for (deg = 0 ; deg <= n_col ; deg++) { col = head [deg] ; if (col == EMPTY) { continue ; } DEBUG4 (("%d:", deg)) ; while (col != EMPTY) { DEBUG4 ((" %d", col)) ; have += Col [col].shared1.thickness ; ASSERT (COL_IS_ALIVE (col)) ; col = Col [col].shared4.degree_next ; } DEBUG4 (("\n")) ; } DEBUG4 (("should %d have %d\n", should, have)) ; ASSERT (should == have) ; /* === Check the row degrees ============================================ */ if (n_row > 10000 && colamd_debug <= 0) { return ; } for (row = 0 ; row < n_row ; row++) { if (ROW_IS_ALIVE (row)) { ASSERT (Row [row].shared1.degree <= max_deg) ; } } } /* ========================================================================== */ /* === debug_mark =========================================================== */ /* ========================================================================== */ /* Ensures that the tag_mark is less that the maximum and also ensures that each entry in the mark array is less than the tag mark. */ PRIVATE void debug_mark ( /* === Parameters ======================================================= */ Int n_row, Colamd_Row Row [], Int tag_mark, Int max_mark ) { /* === Local variables ================================================== */ Int r ; /* === Check the Row marks ============================================== */ ASSERT (tag_mark > 0 && tag_mark <= max_mark) ; if (n_row > 10000 && colamd_debug <= 0) { return ; } for (r = 0 ; r < n_row ; r++) { ASSERT (Row [r].shared2.mark < tag_mark) ; } } /* ========================================================================== */ /* === debug_matrix ========================================================= */ /* ========================================================================== */ /* Prints out the contents of the columns and the rows. */ PRIVATE void debug_matrix ( /* === Parameters ======================================================= */ Int n_row, Int n_col, Colamd_Row Row [], Colamd_Col Col [], Int A [] ) { /* === Local variables ================================================== */ Int r ; Int c ; Int *rp ; Int *rp_end ; Int *cp ; Int *cp_end ; /* === Dump the rows and columns of the matrix ========================== */ if (colamd_debug < 3) { return ; } DEBUG3 (("DUMP MATRIX:\n")) ; for (r = 0 ; r < n_row ; r++) { DEBUG3 (("Row %d alive? %d\n", r, ROW_IS_ALIVE (r))) ; if (ROW_IS_DEAD (r)) { continue ; } DEBUG3 (("start %d length %d degree %d\n", Row [r].start, Row [r].length, Row [r].shared1.degree)) ; rp = &A [Row [r].start] ; rp_end = rp + Row [r].length ; while (rp < rp_end) { c = *rp++ ; DEBUG4 ((" %d col %d\n", COL_IS_ALIVE (c), c)) ; } } for (c = 0 ; c < n_col ; c++) { DEBUG3 (("Col %d alive? %d\n", c, COL_IS_ALIVE (c))) ; if (COL_IS_DEAD (c)) { continue ; } DEBUG3 (("start %d length %d shared1 %d shared2 %d\n", Col [c].start, Col [c].length, Col [c].shared1.thickness, Col [c].shared2.score)) ; cp = &A [Col [c].start] ; cp_end = cp + Col [c].length ; while (cp < cp_end) { r = *cp++ ; DEBUG4 ((" %d row %d\n", ROW_IS_ALIVE (r), r)) ; } } } PRIVATE void colamd_get_debug ( char *method ) { FILE *f ; colamd_debug = 0 ; /* no debug printing */ f = fopen ("debug", "r") ; if (f == (FILE *) NULL) { colamd_debug = 0 ; } else { fscanf (f, "%d", &colamd_debug) ; fclose (f) ; } DEBUG0 (("%s: debug version, D = %d (THIS WILL BE SLOW!)\n", method, colamd_debug)) ; } #endif /* NDEBUG */ python-igraph-0.8.0/vendor/source/igraph/src/COLAMD/README.txt0000644000076500000240000001157313524616144024050 0ustar tamasstaff00000000000000COLAMD, Copyright 1998-2012, Timothy A. Davis. http://www.suitesparse.com ------------------------------------------------------------------------------- The COLAMD column approximate minimum degree ordering algorithm computes a permutation vector P such that the LU factorization of A (:,P) tends to be sparser than that of A. The Cholesky factorization of (A (:,P))'*(A (:,P)) will also tend to be sparser than that of A'*A. SYMAMD is a symmetric minimum degree ordering method based on COLAMD, available as a MATLAB-callable function. It constructs a matrix M such that M'*M has the same pattern as A, and then uses COLAMD to compute a column ordering of M. Colamd and symamd tend to be faster and generate better orderings than their MATLAB counterparts, colmmd and symmmd. To compile and test the colamd m-files and mexFunctions, just unpack the COLAMD/ directory from the COLAMD.tar.gz file, and run MATLAB from within that directory. Next, type colamd_test to compile and test colamd and symamd. This will work on any computer with MATLAB (Unix, PC, or Mac). Alternatively, type "make" (in Unix) to compile and run a simple example C code, without using MATLAB. To compile and install the colamd m-files and mexFunctions, just cd to COLAMD/MATLAB and type colamd_install in the MATLAB command window. A short demo will run. Optionally, type colamd_test to run an extensive tests. Type "make" in Unix in the COLAMD directory to compile the C-callable library and to run a short demo. Colamd is a built-in routine in MATLAB, available from The Mathworks, Inc. Under most cases, the compiled COLAMD from Versions 2.0 to the current version do not differ. Colamd Versions 2.2 and 2.3 differ only in their mexFunction interaces to MATLAB. v2.4 fixes a bug in the symamd routine in v2.3. The bug (in v2.3 and earlier) has no effect on the MATLAB symamd mexFunction. v2.5 adds additional checks for integer overflow, so that the "int" version can be safely used with 64-bit pointers. Refer to the ChangeLog for more details. To use colamd and symamd within an application written in C, all you need are colamd.c, colamd_global.c, and colamd.h, which are the C-callable colamd/symamd codes. See colamd.c for more information on how to call colamd from a C program. Requires SuiteSparse_config, in the ../SuiteSparse_config directory relative to this directory. See the colamd.c file or http://www.suitesparse.com for the license to COLAMD. Related papers: T. A. Davis, J. R. Gilbert, S. Larimore, E. Ng, An approximate column minimum degree ordering algorithm, ACM Transactions on Mathematical Software, vol. 30, no. 3., pp. 353-376, 2004. T. A. Davis, J. R. Gilbert, S. Larimore, E. Ng, Algorithm 836: COLAMD, an approximate column minimum degree ordering algorithm, ACM Transactions on Mathematical Software, vol. 30, no. 3., pp. 377-380, 2004. "An approximate minimum degree column ordering algorithm", S. I. Larimore, MS Thesis, Dept. of Computer and Information Science and Engineering, University of Florida, Gainesville, FL, 1998. CISE Tech Report TR-98-016. Approximate Deficiency for Ordering the Columns of a Matrix, J. L. Kern, Senior Thesis, Dept. of Computer and Information Science and Engineering, University of Florida, Gainesville, FL, 1999. Authors: Stefan I. Larimore and Timothy A. Davis, in collaboration with John Gilbert, Xerox PARC (now at UC Santa Barbara), and Esmong Ng, Lawrence Berkeley National Laboratory (much of this work he did while at Oak Ridge National Laboratory). COLAMD files: Demo simple demo Doc additional documentation (see colamd.c for more) Include include file Lib compiled C-callable library Makefile primary Unix Makefile MATLAB MATLAB functions README.txt this file Source C source code ./Demo: colamd_example.c simple example colamd_example.out output of colamd_example.c colamd_l_example.c simple example, long integers colamd_l_example.out output of colamd_l_example.c Makefile Makefile for C demos ./Doc: ChangeLog change log lesser.txt license ./Include: colamd.h include file ./Lib: Makefile Makefile for C-callable library ./MATLAB: colamd2.m MATLAB interface for colamd2 colamd_demo.m simple demo colamd_install.m compile and install colamd2 and symamd2 colamd_make.m compile colamd2 and symamd2 colamdmex.ca MATLAB mexFunction for colamd2 colamd_test.m extensive test colamdtestmex.c test function for colamd Contents.m contents of the MATLAB directory luflops.m test code Makefile Makefile for MATLAB functions symamd2.m MATLAB interface for symamd2 symamdmex.c MATLAB mexFunction for symamd2 symamdtestmex.c test function for symamd ./Source: colamd.c primary source code colamd_global.c globally defined function pointers (malloc, free, ...) python-igraph-0.8.0/vendor/source/igraph/src/vector.c0000644000076500000240000003176113614300625023054 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_types.h" #include "igraph_types_internal.h" #include "igraph_complex.h" #include "bigint.h" #include "config.h" #include #define BASE_IGRAPH_REAL #include "igraph_pmt.h" #include "vector.pmt" #include "igraph_pmt_off.h" #undef BASE_IGRAPH_REAL #define BASE_FLOAT #include "igraph_pmt.h" #include "vector.pmt" #include "igraph_pmt_off.h" #undef BASE_FLOAT #define BASE_LONG #include "igraph_pmt.h" #include "vector.pmt" #include "igraph_pmt_off.h" #undef BASE_LONG #define BASE_CHAR #include "igraph_pmt.h" #include "vector.pmt" #include "igraph_pmt_off.h" #undef BASE_CHAR #define BASE_BOOL #include "igraph_pmt.h" #include "vector.pmt" #include "igraph_pmt_off.h" #undef BASE_BOOL #define BASE_INT #include "igraph_pmt.h" #include "vector.pmt" #include "igraph_pmt_off.h" #undef BASE_INT #define BASE_COMPLEX #include "igraph_pmt.h" #include "vector.pmt" #include "igraph_pmt_off.h" #undef BASE_COMPLEX #define BASE_LIMB #include "igraph_pmt.h" #include "vector.pmt" #include "igraph_pmt_off.h" #undef BASE_LIMB #include "igraph_math.h" int igraph_vector_floor(const igraph_vector_t *from, igraph_vector_long_t *to) { long int i, n = igraph_vector_size(from); IGRAPH_CHECK(igraph_vector_long_resize(to, n)); for (i = 0; i < n; i++) { VECTOR(*to)[i] = (long int) floor(VECTOR(*from)[i]); } return 0; } int igraph_vector_round(const igraph_vector_t *from, igraph_vector_long_t *to) { long int i, n = igraph_vector_size(from); IGRAPH_CHECK(igraph_vector_long_resize(to, n)); for (i = 0; i < n; i++) { VECTOR(*to)[i] = (long int) round(VECTOR(*from)[i]); } return 0; } int igraph_vector_order2(igraph_vector_t *v) { igraph_indheap_t heap; igraph_indheap_init_array(&heap, VECTOR(*v), igraph_vector_size(v)); IGRAPH_FINALLY(igraph_indheap_destroy, &heap); igraph_vector_clear(v); while (!igraph_indheap_empty(&heap)) { IGRAPH_CHECK(igraph_vector_push_back(v, igraph_indheap_max_index(&heap) - 1)); igraph_indheap_delete_max(&heap); } igraph_indheap_destroy(&heap); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \ingroup vector * \function igraph_vector_order * \brief Calculate the order of the elements in a vector. * * * The smallest element will have order zero, the second smallest * order one, etc. * \param v The original \type igraph_vector_t object. * \param v2 A secondary key, another \type igraph_vector_t object. * \param res An initialized \type igraph_vector_t object, it will be * resized to match the size of \p v. The * result of the computation will be stored here. * \param nodes Hint, the largest element in \p v. * \return Error code: * \c IGRAPH_ENOMEM: out of memory * * Time complexity: O() */ int igraph_vector_order(const igraph_vector_t* v, const igraph_vector_t *v2, igraph_vector_t* res, igraph_real_t nodes) { long int edges = igraph_vector_size(v); igraph_vector_t ptr; igraph_vector_t rad; long int i, j; assert(v != NULL); assert(v->stor_begin != NULL); IGRAPH_VECTOR_INIT_FINALLY(&ptr, (long int) nodes + 1); IGRAPH_VECTOR_INIT_FINALLY(&rad, edges); IGRAPH_CHECK(igraph_vector_resize(res, edges)); for (i = 0; i < edges; i++) { long int radix = (long int) v2->stor_begin[i]; if (VECTOR(ptr)[radix] != 0) { VECTOR(rad)[i] = VECTOR(ptr)[radix]; } VECTOR(ptr)[radix] = i + 1; } j = 0; for (i = 0; i < nodes + 1; i++) { if (VECTOR(ptr)[i] != 0) { long int next = (long int) VECTOR(ptr)[i] - 1; res->stor_begin[j++] = next; while (VECTOR(rad)[next] != 0) { next = (long int) VECTOR(rad)[next] - 1; res->stor_begin[j++] = next; } } } igraph_vector_null(&ptr); igraph_vector_null(&rad); for (i = 0; i < edges; i++) { long int edge = (long int) VECTOR(*res)[edges - i - 1]; long int radix = (long int) VECTOR(*v)[edge]; if (VECTOR(ptr)[radix] != 0) { VECTOR(rad)[edge] = VECTOR(ptr)[radix]; } VECTOR(ptr)[radix] = edge + 1; } j = 0; for (i = 0; i < nodes + 1; i++) { if (VECTOR(ptr)[i] != 0) { long int next = (long int) VECTOR(ptr)[i] - 1; res->stor_begin[j++] = next; while (VECTOR(rad)[next] != 0) { next = (long int) VECTOR(rad)[next] - 1; res->stor_begin[j++] = next; } } } igraph_vector_destroy(&ptr); igraph_vector_destroy(&rad); IGRAPH_FINALLY_CLEAN(2); return 0; } int igraph_vector_order1(const igraph_vector_t* v, igraph_vector_t* res, igraph_real_t nodes) { long int edges = igraph_vector_size(v); igraph_vector_t ptr; igraph_vector_t rad; long int i, j; assert(v != NULL); assert(v->stor_begin != NULL); IGRAPH_VECTOR_INIT_FINALLY(&ptr, (long int) nodes + 1); IGRAPH_VECTOR_INIT_FINALLY(&rad, edges); IGRAPH_CHECK(igraph_vector_resize(res, edges)); for (i = 0; i < edges; i++) { long int radix = (long int) v->stor_begin[i]; if (VECTOR(ptr)[radix] != 0) { VECTOR(rad)[i] = VECTOR(ptr)[radix]; } VECTOR(ptr)[radix] = i + 1; } j = 0; for (i = 0; i < nodes + 1; i++) { if (VECTOR(ptr)[i] != 0) { long int next = (long int) VECTOR(ptr)[i] - 1; res->stor_begin[j++] = next; while (VECTOR(rad)[next] != 0) { next = (long int) VECTOR(rad)[next] - 1; res->stor_begin[j++] = next; } } } igraph_vector_destroy(&ptr); igraph_vector_destroy(&rad); IGRAPH_FINALLY_CLEAN(2); return 0; } int igraph_vector_order1_int(const igraph_vector_t* v, igraph_vector_int_t* res, igraph_real_t nodes) { long int edges = igraph_vector_size(v); igraph_vector_t ptr; igraph_vector_t rad; long int i, j; assert(v != NULL); assert(v->stor_begin != NULL); IGRAPH_VECTOR_INIT_FINALLY(&ptr, (long int) nodes + 1); IGRAPH_VECTOR_INIT_FINALLY(&rad, edges); IGRAPH_CHECK(igraph_vector_int_resize(res, edges)); for (i = 0; i < edges; i++) { long int radix = (long int) v->stor_begin[i]; if (VECTOR(ptr)[radix] != 0) { VECTOR(rad)[i] = VECTOR(ptr)[radix]; } VECTOR(ptr)[radix] = i + 1; } j = 0; for (i = 0; i < nodes + 1; i++) { if (VECTOR(ptr)[i] != 0) { long int next = (long int) VECTOR(ptr)[i] - 1; res->stor_begin[j++] = next; while (VECTOR(rad)[next] != 0) { next = (long int) VECTOR(rad)[next] - 1; res->stor_begin[j++] = next; } } } igraph_vector_destroy(&ptr); igraph_vector_destroy(&rad); IGRAPH_FINALLY_CLEAN(2); return 0; } int igraph_vector_rank(const igraph_vector_t *v, igraph_vector_t *res, long int nodes) { igraph_vector_t rad; igraph_vector_t ptr; long int edges = igraph_vector_size(v); long int i, c = 0; IGRAPH_VECTOR_INIT_FINALLY(&rad, nodes); IGRAPH_VECTOR_INIT_FINALLY(&ptr, edges); IGRAPH_CHECK(igraph_vector_resize(res, edges)); for (i = 0; i < edges; i++) { long int elem = (long int) VECTOR(*v)[i]; VECTOR(ptr)[i] = VECTOR(rad)[elem]; VECTOR(rad)[elem] = i + 1; } for (i = 0; i < nodes; i++) { long int p = (long int) VECTOR(rad)[i]; while (p != 0) { VECTOR(*res)[p - 1] = c++; p = (long int) VECTOR(ptr)[p - 1]; } } igraph_vector_destroy(&ptr); igraph_vector_destroy(&rad); IGRAPH_FINALLY_CLEAN(2); return 0; } #ifndef USING_R int igraph_vector_complex_print(const igraph_vector_complex_t *v) { long int i, n = igraph_vector_complex_size(v); if (n != 0) { igraph_complex_t z = VECTOR(*v)[0]; printf("%g%+gi", IGRAPH_REAL(z), IGRAPH_IMAG(z)); } for (i = 1; i < n; i++) { igraph_complex_t z = VECTOR(*v)[i]; printf(" %g%+gi", IGRAPH_REAL(z), IGRAPH_IMAG(z)); } printf("\n"); return 0; } #endif int igraph_vector_complex_fprint(const igraph_vector_complex_t *v, FILE *file) { long int i, n = igraph_vector_complex_size(v); if (n != 0) { igraph_complex_t z = VECTOR(*v)[0]; fprintf(file, "%g%+g", IGRAPH_REAL(z), IGRAPH_IMAG(z)); } for (i = 1; i < n; i++) { igraph_complex_t z = VECTOR(*v)[i]; fprintf(file, " %g%+g", IGRAPH_REAL(z), IGRAPH_IMAG(z)); } fprintf(file, "\n"); return 0; } int igraph_vector_complex_real(const igraph_vector_complex_t *v, igraph_vector_t *real) { int i, n = (int) igraph_vector_complex_size(v); IGRAPH_CHECK(igraph_vector_resize(real, n)); for (i = 0; i < n; i++) { VECTOR(*real)[i] = IGRAPH_REAL(VECTOR(*v)[i]); } return 0; } int igraph_vector_complex_imag(const igraph_vector_complex_t *v, igraph_vector_t *imag) { int i, n = (int) igraph_vector_complex_size(v); IGRAPH_CHECK(igraph_vector_resize(imag, n)); for (i = 0; i < n; i++) { VECTOR(*imag)[i] = IGRAPH_IMAG(VECTOR(*v)[i]); } return 0; } int igraph_vector_complex_realimag(const igraph_vector_complex_t *v, igraph_vector_t *real, igraph_vector_t *imag) { int i, n = (int) igraph_vector_complex_size(v); IGRAPH_CHECK(igraph_vector_resize(real, n)); IGRAPH_CHECK(igraph_vector_resize(imag, n)); for (i = 0; i < n; i++) { igraph_complex_t z = VECTOR(*v)[i]; VECTOR(*real)[i] = IGRAPH_REAL(z); VECTOR(*imag)[i] = IGRAPH_IMAG(z); } return 0; } int igraph_vector_complex_create(igraph_vector_complex_t *v, const igraph_vector_t *real, const igraph_vector_t *imag) { int i, n = (int) igraph_vector_size(real); if (n != igraph_vector_size(imag)) { IGRAPH_ERROR("Real and imag vector sizes don't match", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_vector_complex_init(v, n)); /* FINALLY not needed */ for (i = 0; i < n; i++) { VECTOR(*v)[i] = igraph_complex(VECTOR(*real)[i], VECTOR(*imag)[i]); } return 0; } int igraph_vector_complex_create_polar(igraph_vector_complex_t *v, const igraph_vector_t *r, const igraph_vector_t *theta) { int i, n = (int) igraph_vector_size(r); if (n != igraph_vector_size(theta)) { IGRAPH_ERROR("'r' and 'theta' vector sizes don't match", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_vector_complex_init(v, n)); /* FINALLY not needed */ for (i = 0; i < n; i++) { VECTOR(*v)[i] = igraph_complex_polar(VECTOR(*r)[i], VECTOR(*theta)[i]); } return 0; } igraph_bool_t igraph_vector_e_tol(const igraph_vector_t *lhs, const igraph_vector_t *rhs, igraph_real_t tol) { long int i, s; assert(lhs != 0); assert(rhs != 0); assert(lhs->stor_begin != 0); assert(rhs->stor_begin != 0); s = igraph_vector_size(lhs); if (s != igraph_vector_size(rhs)) { return 0; } else { if (tol == 0) { tol = DBL_EPSILON; } for (i = 0; i < s; i++) { igraph_real_t l = VECTOR(*lhs)[i]; igraph_real_t r = VECTOR(*rhs)[i]; if (l < r - tol || l > r + tol) { return 0; } } return 1; } } int igraph_vector_zapsmall(igraph_vector_t *v, igraph_real_t tol) { int i, n = igraph_vector_size(v); if (tol < 0.0) { IGRAPH_ERROR("`tol' tolerance must be non-negative", IGRAPH_EINVAL); } if (tol == 0.0) { tol = sqrt(DBL_EPSILON); } for (i = 0; i < n; i++) { igraph_real_t val = VECTOR(*v)[i]; if (val < tol && val > -tol) { VECTOR(*v)[i] = 0.0; } } return 0; } python-igraph-0.8.0/vendor/source/igraph/src/clustertool.cpp0000644000076500000240000006444613614300625024477 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ /* The original version of this file was written by Joerg Reichardt The original copyright notice follows here */ /*************************************************************************** main.cpp - description ------------------- begin : Tue Jul 13 11:26:47 CEST 2004 copyright : (C) 2004 by email : ***************************************************************************/ /*************************************************************************** * * * This program is free software; you can redistribute it and/or modify * * it under the terms of the GNU General Public License as published by * * the Free Software Foundation; either version 2 of the License, or * * (at your option) any later version. * * * ***************************************************************************/ #ifdef HAVE_CONFIG_H #include #endif #include #include #include #include #include "NetDataTypes.h" #include "NetRoutines.h" #include "pottsmodel_2.h" #include "igraph_community.h" #include "igraph_error.h" #include "igraph_random.h" #include "igraph_math.h" #include "igraph_interface.h" #include "igraph_components.h" #include "igraph_interrupt_internal.h" int igraph_i_community_spinglass_orig(const igraph_t *graph, const igraph_vector_t *weights, igraph_real_t *modularity, igraph_real_t *temperature, igraph_vector_t *membership, igraph_vector_t *csize, igraph_integer_t spins, igraph_bool_t parupdate, igraph_real_t starttemp, igraph_real_t stoptemp, igraph_real_t coolfact, igraph_spincomm_update_t update_rule, igraph_real_t gamma); int igraph_i_community_spinglass_negative(const igraph_t *graph, const igraph_vector_t *weights, igraph_real_t *modularity, igraph_real_t *temperature, igraph_vector_t *membership, igraph_vector_t *csize, igraph_integer_t spins, igraph_bool_t parupdate, igraph_real_t starttemp, igraph_real_t stoptemp, igraph_real_t coolfact, igraph_spincomm_update_t update_rule, igraph_real_t gamma, /* igraph_matrix_t *adhesion, */ /* igraph_matrix_t *normalised_adhesion, */ /* igraph_real_t *polarization, */ igraph_real_t gamma_minus); /** * \function igraph_community_spinglass * \brief Community detection based on statistical mechanics * * This function implements the community structure detection * algorithm proposed by Joerg Reichardt and Stefan Bornholdt. * The algorithm is described in their paper: Statistical Mechanics of * Community Detection, http://arxiv.org/abs/cond-mat/0603718 . * * From version 0.6 igraph also supports an extension to * the algorithm that allows negative edge weights. This is described * in V.A. Traag and Jeroen Bruggeman: Community detection in networks * with positive and negative links, http://arxiv.org/abs/0811.2329 . * \param graph The input graph, it may be directed but the direction * of the edge is not used in the algorithm. * \param weights The vector giving the edge weights, it may be \c NULL, * in which case all edges are weighted equally. Edge weights * should be positive, altough this is not tested. * \param modularity Pointer to a real number, if not \c NULL then the * modularity score of the solution will be stored here. This is the * gereralized modularity that simplifies to the one defined in * M. E. J. Newman and M. Girvan, Phys. Rev. E 69, 026113 (2004), * if the gamma parameter is one. * \param temperature Pointer to a real number, if not \c NULL then * the temperature at the end of the algorithm will be stored * here. * \param membership Pointer to an initialized vector or \c NULL. If * not \c NULL then the result of the clustering will be stored * here, for each vertex the number of its cluster is given, the * first cluster is numbered zero. The vector will be resized as * needed. * \param csize Pointer to an initialized vector or \c NULL. If not \c * NULL then the sizes of the clusters will stored here in cluster * number order. The vector will be resized as needed. * \param spins Integer giving the number of spins, ie. the maximum * number of clusters. Usually it is not a program to give a high * number here, the default was 25 in the original code. Even if * the number of spins is high the number of clusters in the * result might small. * \param parupdate A logical constant, whether to update all spins in * parallel. The default for this argument was \c FALSE (ie. 0) in * the original code. It is not implemented in the \c * IGRAPH_SPINCOMM_INP_NEG implementation. * \param starttemp Real number, the temperature at the start. The * value of this argument was 1.0 in the original code. * \param stoptemp Real number, the algorithm stops at this * temperature. The default was 0.01 in the original code. * \param coolfact Real number, the coolinf factor for the simulated * annealing. The default was 0.99 in the original code. * \param update_rule The type of the update rule. Possible values: \c * IGRAPH_SPINCOMM_UPDATE_SIMPLE and \c * IGRAPH_SPINCOMM_UPDATE_CONFIG. Basically this parameter defined * the null model based on which the actual clustering is done. If * this is \c IGRAPH_SPINCOMM_UPDATE_SIMPLE then the random graph * (ie. G(n,p)), if it is \c IGRAPH_SPINCOMM_UPDATE then the * configuration model is used. The configuration means that the * baseline for the clustering is a random graph with the same * degree distribution as the input graph. * \param gamma Real number. The gamma parameter of the * algorithm. This defined the weight of the missing and existing * links in the quality function for the clustering. The default * value in the original code was 1.0, which is equal weight to * missing and existing edges. Smaller values make the existing * links contibute more to the energy function which is minimized * in the algorithm. Bigger values make the missing links more * important. (If my understanding is correct.) * \param implementation Constant, chooses between the two * implementations of the spin-glass algorithm that are included * in igraph. \c IGRAPH_SPINCOMM_IMP_ORIG selects the original * implementation, this is faster, \c IGRAPH_SPINCOMM_INP_NEG selects * a new implementation by Vincent Traag that allows negative edge * weights. * \param gamma_minus Real number. Parameter for the \c * IGRAPH_SPINCOMM_IMP_NEG implementation. This * specifies the balance between the importance of present and * non-present negative weighted edges in a community. Smaller values of * \p gamma_minus lead to communities with lesser * negative intra-connectivity. * If this argument is set to zero, the algorithm reduces to a graph * coloring algorithm, using the number of spins as the number of * colors. * \return Error code. * * \sa igraph_community_spinglass_single() for calculating the community * of a single vertex. * * Time complexity: TODO. * * \example examples/simple/spinglass.c */ int igraph_community_spinglass(const igraph_t *graph, const igraph_vector_t *weights, igraph_real_t *modularity, igraph_real_t *temperature, igraph_vector_t *membership, igraph_vector_t *csize, igraph_integer_t spins, igraph_bool_t parupdate, igraph_real_t starttemp, igraph_real_t stoptemp, igraph_real_t coolfact, igraph_spincomm_update_t update_rule, igraph_real_t gamma, /* the rest is for the NegSpin implementation */ igraph_spinglass_implementation_t implementation, /* igraph_matrix_t *adhesion, */ /* igraph_matrix_t *normalised_adhesion, */ /* igraph_real_t *polarization, */ igraph_real_t gamma_minus) { switch (implementation) { case IGRAPH_SPINCOMM_IMP_ORIG: return igraph_i_community_spinglass_orig(graph, weights, modularity, temperature, membership, csize, spins, parupdate, starttemp, stoptemp, coolfact, update_rule, gamma); break; case IGRAPH_SPINCOMM_IMP_NEG: return igraph_i_community_spinglass_negative(graph, weights, modularity, temperature, membership, csize, spins, parupdate, starttemp, stoptemp, coolfact, update_rule, gamma, /* adhesion, normalised_adhesion, */ /* polarization, */ gamma_minus); break; default: IGRAPH_ERROR("Unknown `implementation' in spinglass community finding", IGRAPH_EINVAL); } return 0; } int igraph_i_community_spinglass_orig(const igraph_t *graph, const igraph_vector_t *weights, igraph_real_t *modularity, igraph_real_t *temperature, igraph_vector_t *membership, igraph_vector_t *csize, igraph_integer_t spins, igraph_bool_t parupdate, igraph_real_t starttemp, igraph_real_t stoptemp, igraph_real_t coolfact, igraph_spincomm_update_t update_rule, igraph_real_t gamma) { unsigned long changes, runs; igraph_bool_t use_weights = 0; bool zeroT; double kT, acc, prob; ClusterList *cl_cur; network *net; PottsModel *pm; /* Check arguments */ if (spins < 2 || spins > 500) { IGRAPH_ERROR("Invalid number of spins", IGRAPH_EINVAL); } if (update_rule != IGRAPH_SPINCOMM_UPDATE_SIMPLE && update_rule != IGRAPH_SPINCOMM_UPDATE_CONFIG) { IGRAPH_ERROR("Invalid update rule", IGRAPH_EINVAL); } if (weights) { if (igraph_vector_size(weights) != igraph_ecount(graph)) { IGRAPH_ERROR("Invalid weight vector length", IGRAPH_EINVAL); } use_weights = 1; } if (coolfact < 0 || coolfact >= 1.0) { IGRAPH_ERROR("Invalid cooling factor", IGRAPH_EINVAL); } if (gamma < 0.0) { IGRAPH_ERROR("Invalid gamma value", IGRAPH_EINVAL); } if (starttemp / stoptemp < 1.0) { IGRAPH_ERROR("starttemp should be larger in absolute value than stoptemp", IGRAPH_EINVAL); } /* Check whether we have a single component */ igraph_bool_t conn; IGRAPH_CHECK(igraph_is_connected(graph, &conn, IGRAPH_WEAK)); if (!conn) { IGRAPH_ERROR("Cannot work with unconnected graph", IGRAPH_EINVAL); } net = new network; net->node_list = new DL_Indexed_List(); net->link_list = new DL_Indexed_List(); net->cluster_list = new DL_Indexed_List*>(); /* Transform the igraph_t */ IGRAPH_CHECK(igraph_i_read_network(graph, weights, net, use_weights, 0)); prob = 2.0 * net->sum_weights / double(net->node_list->Size()) / double(net->node_list->Size() - 1); pm = new PottsModel(net, (unsigned int)spins, update_rule); /* initialize the random number generator */ RNG_BEGIN(); if ((stoptemp == 0.0) && (starttemp == 0.0)) { zeroT = true; } else { zeroT = false; } if (!zeroT) { kT = pm->FindStartTemp(gamma, prob, starttemp); } else { kT = stoptemp; } /* assign random initial configuration */ pm->assign_initial_conf(-1); runs = 0; changes = 1; while (changes > 0 && (kT / stoptemp > 1.0 || (zeroT && runs < 150))) { IGRAPH_ALLOW_INTERRUPTION(); /* This is not clean.... */ runs++; if (!zeroT) { kT *= coolfact; if (parupdate) { changes = pm->HeatBathParallelLookup(gamma, prob, kT, 50); } else { acc = pm->HeatBathLookup(gamma, prob, kT, 50); if (acc < (1.0 - 1.0 / double(spins)) * 0.01) { changes = 0; } else { changes = 1; } } } else { if (parupdate) { changes = pm->HeatBathParallelLookupZeroTemp(gamma, prob, 50); } else { acc = pm->HeatBathLookupZeroTemp(gamma, prob, 50); /* less than 1 percent acceptance ratio */ if (acc < (1.0 - 1.0 / double(spins)) * 0.01) { changes = 0; } else { changes = 1; } } } } /* while loop */ pm->WriteClusters(modularity, temperature, csize, membership, kT, gamma); while (net->link_list->Size()) { delete net->link_list->Pop(); } while (net->node_list->Size()) { delete net->node_list->Pop(); } while (net->cluster_list->Size()) { cl_cur = net->cluster_list->Pop(); while (cl_cur->Size()) { cl_cur->Pop(); } delete cl_cur; } delete net->link_list; delete net->node_list; delete net->cluster_list; RNG_END(); delete net; delete pm; return 0; } /** * \function igraph_community_spinglass_single * \brief Community of a single node based on statistical mechanics * * This function implements the community structure detection * algorithm proposed by Joerg Reichardt and Stefan Bornholdt. It is * described in their paper: Statistical Mechanics of * Community Detection, http://arxiv.org/abs/cond-mat/0603718 . * * * This function calculates the community of a single vertex without * calculating all the communities in the graph. * * \param graph The input graph, it may be directed but the direction * of the edges is not used in the algorithm. * \param weights Pointer to a vector with the weights of the edges. * Alternatively \c NULL can be supplied to have the same weight * for every edge. * \param vertex The vertex id of the vertex of which ths community is * calculated. * \param community Pointer to an initialized vector, the result, the * ids of the vertices in the community of the input vertex will be * stored here. The vector will be resized as needed. * \param cohesion Pointer to a real variable, if not \c NULL the * cohesion index of the community will be stored here. * \param adhesion Pointer to a real variable, if not \c NULL the * adhesion index of the community will be stored here. * \param inner_links Pointer to an integer, if not \c NULL the * number of edges within the community is stored here. * \param outer_links Pointer to an integer, if not \c NULL the * number of edges between the community and the rest of the graph * will be stored here. * \param spins The number of spins to use, this can be higher than * the actual number of clusters in the network, in which case some * clusters will contain zero vertices. * \param update_rule The type of the update rule. Possible values: \c * IGRAPH_SPINCOMM_UPDATE_SIMPLE and \c * IGRAPH_SPINCOMM_UPDATE_CONFIG. Basically this parameter defined * the null model based on which the actual clustering is done. If * this is \c IGRAPH_SPINCOMM_UPDATE_SIMPLE then the random graph * (ie. G(n,p)), if it is \c IGRAPH_SPINCOMM_UPDATE then the * configuration model is used. The configuration means that the * baseline for the clustering is a random graph with the same * degree distribution as the input graph. * \param gamma Real number. The gamma parameter of the * algorithm. This defined the weight of the missing and existing * links in the quality function for the clustering. The default * value in the original code was 1.0, which is equal weight to * missing and existing edges. Smaller values make the existing * links contibute more to the energy function which is minimized * in the algorithm. Bigger values make the missing links more * important. (If my understanding is correct.) * \return Error code. * * \sa igraph_community_spinglass() for the traditional version of the * algorithm. * * Time complexity: TODO. */ int igraph_community_spinglass_single(const igraph_t *graph, const igraph_vector_t *weights, igraph_integer_t vertex, igraph_vector_t *community, igraph_real_t *cohesion, igraph_real_t *adhesion, igraph_integer_t *inner_links, igraph_integer_t *outer_links, igraph_integer_t spins, igraph_spincomm_update_t update_rule, igraph_real_t gamma) { igraph_bool_t use_weights = 0; double prob; ClusterList *cl_cur; network *net; PottsModel *pm; char startnode[255]; /* Check arguments */ if (spins < 2 || spins > 500) { IGRAPH_ERROR("Invalid number of spins", IGRAPH_EINVAL); } if (update_rule != IGRAPH_SPINCOMM_UPDATE_SIMPLE && update_rule != IGRAPH_SPINCOMM_UPDATE_CONFIG) { IGRAPH_ERROR("Invalid update rule", IGRAPH_EINVAL); } if (weights) { if (igraph_vector_size(weights) != igraph_ecount(graph)) { IGRAPH_ERROR("Invalid weight vector length", IGRAPH_EINVAL); } use_weights = 1; } if (gamma < 0.0) { IGRAPH_ERROR("Invalid gamme value", IGRAPH_EINVAL); } if (vertex < 0 || vertex > igraph_vcount(graph)) { IGRAPH_ERROR("Invalid vertex id", IGRAPH_EINVAL); } /* Check whether we have a single component */ igraph_bool_t conn; IGRAPH_CHECK(igraph_is_connected(graph, &conn, IGRAPH_WEAK)); if (!conn) { IGRAPH_ERROR("Cannot work with unconnected graph", IGRAPH_EINVAL); } net = new network; net->node_list = new DL_Indexed_List(); net->link_list = new DL_Indexed_List(); net->cluster_list = new DL_Indexed_List*>(); /* Transform the igraph_t */ IGRAPH_CHECK(igraph_i_read_network(graph, weights, net, use_weights, 0)); prob = 2.0 * net->sum_weights / double(net->node_list->Size()) / double(net->node_list->Size() - 1); pm = new PottsModel(net, (unsigned int)spins, update_rule); /* initialize the random number generator */ RNG_BEGIN(); /* to be exected, if we want to find the community around a particular node*/ /* the initial conf is needed, because otherwise, the degree of the nodes is not in the weight property, stupid!!! */ pm->assign_initial_conf(-1); snprintf(startnode, 255, "%li", (long int)vertex + 1); pm->FindCommunityFromStart(gamma, prob, startnode, community, cohesion, adhesion, inner_links, outer_links); while (net->link_list->Size()) { delete net->link_list->Pop(); } while (net->node_list->Size()) { delete net->node_list->Pop(); } while (net->cluster_list->Size()) { cl_cur = net->cluster_list->Pop(); while (cl_cur->Size()) { cl_cur->Pop(); } delete cl_cur; } delete net->link_list; delete net->node_list; delete net->cluster_list; RNG_END(); delete net; delete pm; return 0; } int igraph_i_community_spinglass_negative(const igraph_t *graph, const igraph_vector_t *weights, igraph_real_t *modularity, igraph_real_t *temperature, igraph_vector_t *membership, igraph_vector_t *csize, igraph_integer_t spins, igraph_bool_t parupdate, igraph_real_t starttemp, igraph_real_t stoptemp, igraph_real_t coolfact, igraph_spincomm_update_t update_rule, igraph_real_t gamma, /* igraph_matrix_t *adhesion, */ /* igraph_matrix_t *normalised_adhesion, */ /* igraph_real_t *polarization, */ igraph_real_t gamma_minus) { unsigned long changes, runs; igraph_bool_t use_weights = 0; bool zeroT; double kT, acc; ClusterList *cl_cur; network *net; PottsModelN *pm; igraph_real_t d_n; igraph_real_t d_p; /* Check arguments */ if (parupdate) { IGRAPH_ERROR("Parallel spin update not implemented with " "negative gamma", IGRAPH_UNIMPLEMENTED); } if (spins < 2 || spins > 500) { IGRAPH_ERROR("Invalid number of spins", IGRAPH_EINVAL); } if (update_rule != IGRAPH_SPINCOMM_UPDATE_SIMPLE && update_rule != IGRAPH_SPINCOMM_UPDATE_CONFIG) { IGRAPH_ERROR("Invalid update rule", IGRAPH_EINVAL); } if (weights) { if (igraph_vector_size(weights) != igraph_ecount(graph)) { IGRAPH_ERROR("Invalid weight vector length", IGRAPH_EINVAL); } use_weights = 1; } if (coolfact < 0 || coolfact >= 1.0) { IGRAPH_ERROR("Invalid cooling factor", IGRAPH_EINVAL); } if (gamma < 0.0) { IGRAPH_ERROR("Invalid gamma value", IGRAPH_EINVAL); } if (starttemp / stoptemp < 1.0) { IGRAPH_ERROR("starttemp should be larger in absolute value than stoptemp", IGRAPH_EINVAL); } /* Check whether we have a single component */ igraph_bool_t conn; IGRAPH_CHECK(igraph_is_connected(graph, &conn, IGRAPH_WEAK)); if (!conn) { IGRAPH_ERROR("Cannot work with unconnected graph", IGRAPH_EINVAL); } if (weights) { igraph_vector_minmax(weights, &d_n, &d_p); } else { d_n = d_p = 1; } if (d_n > 0) { d_n = 0; } if (d_p < 0) { d_p = 0; } d_n = -d_n; net = new network; net->node_list = new DL_Indexed_List(); net->link_list = new DL_Indexed_List(); net->cluster_list = new DL_Indexed_List*>(); /* Transform the igraph_t */ IGRAPH_CHECK(igraph_i_read_network(graph, weights, net, use_weights, 0)); bool directed = igraph_is_directed(graph); pm = new PottsModelN(net, (unsigned int)spins, directed); /* initialize the random number generator */ RNG_BEGIN(); if ((stoptemp == 0.0) && (starttemp == 0.0)) { zeroT = true; } else { zeroT = false; } //Begin at a high enough temperature kT = pm->FindStartTemp(gamma, gamma_minus, starttemp); /* assign random initial configuration */ pm->assign_initial_conf(true); runs = 0; changes = 1; acc = 0; while (changes > 0 && (kT / stoptemp > 1.0 || (zeroT && runs < 150))) { IGRAPH_ALLOW_INTERRUPTION(); /* This is not clean.... */ runs++; kT = kT * coolfact; acc = pm->HeatBathLookup(gamma, gamma_minus, kT, 50); if (acc < (1.0 - 1.0 / double(spins)) * 0.001) { changes = 0; } else { changes = 1; } } /* while loop */ /* These are needed, otherwise 'modularity' is not calculated */ igraph_matrix_t adhesion, normalized_adhesion; igraph_real_t polarization; IGRAPH_MATRIX_INIT_FINALLY(&adhesion, 0, 0); IGRAPH_MATRIX_INIT_FINALLY(&normalized_adhesion, 0, 0); pm->WriteClusters(modularity, temperature, csize, membership, &adhesion, &normalized_adhesion, &polarization, kT, d_p, d_n, gamma, gamma_minus); igraph_matrix_destroy(&normalized_adhesion); igraph_matrix_destroy(&adhesion); IGRAPH_FINALLY_CLEAN(2); while (net->link_list->Size()) { delete net->link_list->Pop(); } while (net->node_list->Size()) { delete net->node_list->Pop(); } while (net->cluster_list->Size()) { cl_cur = net->cluster_list->Pop(); while (cl_cur->Size()) { cl_cur->Pop(); } delete cl_cur; } RNG_END(); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/igraph_hashtable.c0000644000076500000240000001040513614300625025027 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_types.h" #include "igraph_types_internal.h" #include "igraph_memory.h" #include "igraph_error.h" #include "config.h" #include int igraph_hashtable_init(igraph_hashtable_t *ht) { IGRAPH_CHECK(igraph_trie_init(&ht->keys, 1)); IGRAPH_FINALLY(igraph_trie_destroy, &ht->keys); IGRAPH_CHECK(igraph_strvector_init(&ht->elements, 0)); IGRAPH_FINALLY(igraph_trie_destroy, &ht->elements); IGRAPH_CHECK(igraph_strvector_init(&ht->defaults, 0)); IGRAPH_FINALLY_CLEAN(2); return 0; } void igraph_hashtable_destroy(igraph_hashtable_t *ht) { igraph_trie_destroy(&ht->keys); igraph_strvector_destroy(&ht->elements); igraph_strvector_destroy(&ht->defaults); } /* Note: may leave the hash table in an inconsistent state if a new element is added, but this is not a big problem, since while the defaults, or the defaults plus the elements may contain more elements than the keys trie, but the data is always retrieved based on the trie */ int igraph_hashtable_addset(igraph_hashtable_t *ht, const char *key, const char *def, const char *elem) { long int size = igraph_trie_size(&ht->keys); long int newid; IGRAPH_CHECK(igraph_trie_get(&ht->keys, key, &newid)); if (newid == size) { /* this is a new element */ IGRAPH_CHECK(igraph_strvector_resize(&ht->defaults, newid + 1)); IGRAPH_CHECK(igraph_strvector_resize(&ht->elements, newid + 1)); IGRAPH_CHECK(igraph_strvector_set(&ht->defaults, newid, def)); IGRAPH_CHECK(igraph_strvector_set(&ht->elements, newid, elem)); } else { /* set an already existing element */ IGRAPH_CHECK(igraph_strvector_set(&ht->elements, newid, elem)); } return 0; } /* Previous comment also applies here */ int igraph_hashtable_addset2(igraph_hashtable_t *ht, const char *key, const char *def, const char *elem, int elemlen) { long int size = igraph_trie_size(&ht->keys); long int newid; char *tmp; IGRAPH_CHECK(igraph_trie_get(&ht->keys, key, &newid)); tmp = igraph_Calloc(elemlen + 1, char); if (tmp == 0) { IGRAPH_ERROR("cannot add element to hash table", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, tmp); strncpy(tmp, elem, elemlen); tmp[elemlen] = '\0'; if (newid == size) { IGRAPH_CHECK(igraph_strvector_resize(&ht->defaults, newid + 1)); IGRAPH_CHECK(igraph_strvector_resize(&ht->elements, newid + 1)); IGRAPH_CHECK(igraph_strvector_set(&ht->defaults, newid, def)); IGRAPH_CHECK(igraph_strvector_set(&ht->elements, newid, tmp)); } else { IGRAPH_CHECK(igraph_strvector_set(&ht->elements, newid, tmp)); } igraph_Free(tmp); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_hashtable_get(igraph_hashtable_t *ht, const char *key, char **elem) { long int newid; IGRAPH_CHECK(igraph_trie_get(&ht->keys, key, &newid)); igraph_strvector_get(&ht->elements, newid, elem); return 0; } int igraph_hashtable_reset(igraph_hashtable_t *ht) { igraph_strvector_destroy(&ht->elements); IGRAPH_CHECK(igraph_strvector_copy(&ht->elements, &ht->defaults)); return 0; } int igraph_hashtable_getkeys(igraph_hashtable_t *ht, const igraph_strvector_t **sv) { return igraph_trie_getkeys(&ht->keys, sv); } python-igraph-0.8.0/vendor/source/igraph/src/qsort_r.c0000644000076500000240000000033113524616145023237 0ustar tamasstaff00000000000000/* * This file is in the public domain. Originally written by Garrett * A. Wollman. * * $FreeBSD: src/lib/libc/stdlib/qsort_r.c,v 1.1 2002/09/10 02:04:49 wollman Exp $ */ #define I_AM_QSORT_R #include "qsort.c" python-igraph-0.8.0/vendor/source/igraph/src/topology.c0000644000076500000240000044342213614300625023427 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_topology.h" #include "igraph_memory.h" #include "igraph_adjlist.h" #include "igraph_interface.h" #include "igraph_interrupt_internal.h" #include "igraph_constructors.h" #include "igraph_conversion.h" #include "igraph_stack.h" #include "igraph_attributes.h" #include "igraph_structural.h" #include "config.h" const unsigned int igraph_i_isoclass_3[] = { 0, 1, 1, 3, 1, 5, 6, 7, 1, 6, 10, 11, 3, 7, 11, 15, 1, 6, 5, 7, 10, 21, 21, 23, 6, 25, 21, 27, 11, 27, 30, 31, 1, 10, 6, 11, 6, 21, 25, 27, 5, 21, 21, 30, 7, 23, 27, 31, 3, 11, 7, 15, 11, 30, 27, 31, 7, 27, 23, 31, 15, 31, 31, 63 }; const unsigned int igraph_i_isoclass_3_idx[] = { 0, 4, 16, 1, 0, 32, 2, 8, 0 }; const unsigned int igraph_i_isoclass_4[] = { 0, 1, 1, 3, 1, 3, 3, 7, 1, 9, 10, 11, 10, 11, 14, 15, 1, 10, 18, 19, 20, 21, 22, 23, 3, 11, 19, 27, 21, 29, 30, 31, 1, 10, 20, 21, 18, 19, 22, 23, 3, 11, 21, 29, 19, 27, 30, 31, 3, 14, 22, 30, 22, 30, 54, 55, 7, 15, 23, 31, 23, 31, 55, 63, 1, 10, 9, 11, 10, 14, 11, 15, 18, 73, 73, 75, 76, 77, 77, 79, 10, 81, 73, 83, 84, 85, 86, 87, 19, 83, 90, 91, 92, 93, 94, 95, 20, 84, 98, 99, 100, 101, 102, 103, 22, 86, 106, 107, 108, 109, 110, 111, 21, 85, 106, 115, 116, 117, 118, 119, 23, 87, 122, 123, 124, 125, 126, 127, 1, 18, 10, 19, 20, 22, 21, 23, 10, 73, 81, 83, 84, 86, 85, 87, 9, 73, 73, 90, 98, 106, 106, 122, 11, 75, 83, 91, 99, 107, 115, 123, 10, 76, 84, 92, 100, 108, 116, 124, 14, 77, 85, 93, 101, 109, 117, 125, 11, 77, 86, 94, 102, 110, 118, 126, 15, 79, 87, 95, 103, 111, 119, 127, 3, 19, 11, 27, 21, 30, 29, 31, 19, 90, 83, 91, 92, 94, 93, 95, 11, 83, 75, 91, 99, 115, 107, 123, 27, 91, 91, 219, 220, 221, 221, 223, 21, 92, 99, 220, 228, 229, 230, 231, 30, 94, 115, 221, 229, 237, 238, 239, 29, 93, 107, 221, 230, 238, 246, 247, 31, 95, 123, 223, 231, 239, 247, 255, 1, 20, 10, 21, 18, 22, 19, 23, 20, 98, 84, 99, 100, 102, 101, 103, 10, 84, 76, 92, 100, 116, 108, 124, 21, 99, 92, 220, 228, 230, 229, 231, 18, 100, 100, 228, 292, 293, 293, 295, 22, 102, 116, 230, 293, 301, 302, 303, 19, 101, 108, 229, 293, 302, 310, 311, 23, 103, 124, 231, 295, 303, 311, 319, 3, 21, 11, 29, 19, 30, 27, 31, 22, 106, 86, 107, 108, 110, 109, 111, 14, 85, 77, 93, 101, 117, 109, 125, 30, 115, 94, 221, 229, 238, 237, 239, 22, 116, 102, 230, 293, 302, 301, 303, 54, 118, 118, 246, 310, 365, 365, 367, 30, 117, 110, 238, 302, 373, 365, 375, 55, 119, 126, 247, 311, 375, 382, 383, 3, 22, 14, 30, 22, 54, 30, 55, 21, 106, 85, 115, 116, 118, 117, 119, 11, 86, 77, 94, 102, 118, 110, 126, 29, 107, 93, 221, 230, 246, 238, 247, 19, 108, 101, 229, 293, 310, 302, 311, 30, 110, 117, 238, 302, 365, 373, 375, 27, 109, 109, 237, 301, 365, 365, 382, 31, 111, 125, 239, 303, 367, 375, 383, 7, 23, 15, 31, 23, 55, 31, 63, 23, 122, 87, 123, 124, 126, 125, 127, 15, 87, 79, 95, 103, 119, 111, 127, 31, 123, 95, 223, 231, 247, 239, 255, 23, 124, 103, 231, 295, 311, 303, 319, 55, 126, 119, 247, 311, 382, 375, 383, 31, 125, 111, 239, 303, 375, 367, 383, 63, 127, 127, 255, 319, 383, 383, 511, 1, 10, 10, 14, 9, 11, 11, 15, 18, 73, 76, 77, 73, 75, 77, 79, 20, 84, 100, 101, 98, 99, 102, 103, 22, 86, 108, 109, 106, 107, 110, 111, 10, 81, 84, 85, 73, 83, 86, 87, 19, 83, 92, 93, 90, 91, 94, 95, 21, 85, 116, 117, 106, 115, 118, 119, 23, 87, 124, 125, 122, 123, 126, 127, 18, 76, 73, 77, 73, 77, 75, 79, 292, 585, 585, 587, 585, 587, 587, 591, 100, 593, 594, 595, 596, 597, 598, 599, 293, 601, 602, 603, 604, 605, 606, 607, 100, 593, 596, 597, 594, 595, 598, 599, 293, 601, 604, 605, 602, 603, 606, 607, 228, 625, 626, 627, 626, 627, 630, 631, 295, 633, 634, 635, 634, 635, 638, 639, 20, 100, 84, 101, 98, 102, 99, 103, 100, 594, 593, 595, 596, 598, 597, 599, 98, 596, 596, 659, 660, 661, 661, 663, 102, 598, 666, 667, 661, 669, 670, 671, 84, 593, 674, 675, 596, 666, 678, 679, 101, 595, 675, 683, 659, 667, 686, 687, 99, 597, 678, 686, 661, 670, 694, 695, 103, 599, 679, 687, 663, 671, 695, 703, 22, 108, 86, 109, 106, 110, 107, 111, 293, 602, 601, 603, 604, 606, 605, 607, 102, 666, 598, 667, 661, 670, 669, 671, 301, 729, 729, 731, 732, 733, 733, 735, 116, 737, 678, 739, 626, 741, 742, 743, 302, 745, 746, 747, 748, 749, 750, 751, 230, 753, 742, 755, 756, 757, 758, 759, 303, 761, 762, 763, 764, 765, 766, 767, 10, 84, 81, 85, 73, 86, 83, 87, 100, 596, 593, 597, 594, 598, 595, 599, 84, 674, 593, 675, 596, 678, 666, 679, 116, 678, 737, 739, 626, 742, 741, 743, 76, 593, 593, 625, 585, 601, 601, 633, 108, 666, 737, 753, 602, 729, 745, 761, 92, 675, 737, 819, 604, 746, 822, 823, 124, 679, 826, 827, 634, 762, 830, 831, 19, 92, 83, 93, 90, 94, 91, 95, 293, 604, 601, 605, 602, 606, 603, 607, 101, 675, 595, 683, 659, 686, 667, 687, 302, 746, 745, 747, 748, 750, 749, 751, 108, 737, 666, 753, 602, 745, 729, 761, 310, 822, 822, 875, 876, 877, 877, 879, 229, 819, 741, 883, 748, 885, 886, 887, 311, 823, 830, 891, 892, 893, 894, 895, 21, 116, 85, 117, 106, 118, 115, 119, 228, 626, 625, 627, 626, 630, 627, 631, 99, 678, 597, 686, 661, 694, 670, 695, 230, 742, 753, 755, 756, 758, 757, 759, 92, 737, 675, 819, 604, 822, 746, 823, 229, 741, 819, 883, 748, 886, 885, 887, 220, 739, 739, 947, 732, 949, 949, 951, 231, 743, 827, 955, 764, 957, 958, 959, 23, 124, 87, 125, 122, 126, 123, 127, 295, 634, 633, 635, 634, 638, 635, 639, 103, 679, 599, 687, 663, 695, 671, 703, 303, 762, 761, 763, 764, 766, 765, 767, 124, 826, 679, 827, 634, 830, 762, 831, 311, 830, 823, 891, 892, 894, 893, 895, 231, 827, 743, 955, 764, 958, 957, 959, 319, 831, 831, 1019, 1020, 1021, 1021, 1023, 1, 18, 20, 22, 10, 19, 21, 23, 10, 73, 84, 86, 81, 83, 85, 87, 10, 76, 100, 108, 84, 92, 116, 124, 14, 77, 101, 109, 85, 93, 117, 125, 9, 73, 98, 106, 73, 90, 106, 122, 11, 75, 99, 107, 83, 91, 115, 123, 11, 77, 102, 110, 86, 94, 118, 126, 15, 79, 103, 111, 87, 95, 119, 127, 20, 100, 98, 102, 84, 101, 99, 103, 100, 594, 596, 598, 593, 595, 597, 599, 84, 593, 596, 666, 674, 675, 678, 679, 101, 595, 659, 667, 675, 683, 686, 687, 98, 596, 660, 661, 596, 659, 661, 663, 102, 598, 661, 669, 666, 667, 670, 671, 99, 597, 661, 670, 678, 686, 694, 695, 103, 599, 663, 671, 679, 687, 695, 703, 18, 292, 100, 293, 100, 293, 228, 295, 76, 585, 593, 601, 593, 601, 625, 633, 73, 585, 594, 602, 596, 604, 626, 634, 77, 587, 595, 603, 597, 605, 627, 635, 73, 585, 596, 604, 594, 602, 626, 634, 77, 587, 597, 605, 595, 603, 627, 635, 75, 587, 598, 606, 598, 606, 630, 638, 79, 591, 599, 607, 599, 607, 631, 639, 22, 293, 102, 301, 116, 302, 230, 303, 108, 602, 666, 729, 737, 745, 753, 761, 86, 601, 598, 729, 678, 746, 742, 762, 109, 603, 667, 731, 739, 747, 755, 763, 106, 604, 661, 732, 626, 748, 756, 764, 110, 606, 670, 733, 741, 749, 757, 765, 107, 605, 669, 733, 742, 750, 758, 766, 111, 607, 671, 735, 743, 751, 759, 767, 10, 100, 84, 116, 76, 108, 92, 124, 84, 596, 674, 678, 593, 666, 675, 679, 81, 593, 593, 737, 593, 737, 737, 826, 85, 597, 675, 739, 625, 753, 819, 827, 73, 594, 596, 626, 585, 602, 604, 634, 86, 598, 678, 742, 601, 729, 746, 762, 83, 595, 666, 741, 601, 745, 822, 830, 87, 599, 679, 743, 633, 761, 823, 831, 21, 228, 99, 230, 92, 229, 220, 231, 116, 626, 678, 742, 737, 741, 739, 743, 85, 625, 597, 753, 675, 819, 739, 827, 117, 627, 686, 755, 819, 883, 947, 955, 106, 626, 661, 756, 604, 748, 732, 764, 118, 630, 694, 758, 822, 886, 949, 957, 115, 627, 670, 757, 746, 885, 949, 958, 119, 631, 695, 759, 823, 887, 951, 959, 19, 293, 101, 302, 108, 310, 229, 311, 92, 604, 675, 746, 737, 822, 819, 823, 83, 601, 595, 745, 666, 822, 741, 830, 93, 605, 683, 747, 753, 875, 883, 891, 90, 602, 659, 748, 602, 876, 748, 892, 94, 606, 686, 750, 745, 877, 885, 893, 91, 603, 667, 749, 729, 877, 886, 894, 95, 607, 687, 751, 761, 879, 887, 895, 23, 295, 103, 303, 124, 311, 231, 319, 124, 634, 679, 762, 826, 830, 827, 831, 87, 633, 599, 761, 679, 823, 743, 831, 125, 635, 687, 763, 827, 891, 955, 1019, 122, 634, 663, 764, 634, 892, 764, 1020, 126, 638, 695, 766, 830, 894, 958, 1021, 123, 635, 671, 765, 762, 893, 957, 1021, 127, 639, 703, 767, 831, 895, 959, 1023, 3, 19, 21, 30, 11, 27, 29, 31, 19, 90, 92, 94, 83, 91, 93, 95, 21, 92, 228, 229, 99, 220, 230, 231, 30, 94, 229, 237, 115, 221, 238, 239, 11, 83, 99, 115, 75, 91, 107, 123, 27, 91, 220, 221, 91, 219, 221, 223, 29, 93, 230, 238, 107, 221, 246, 247, 31, 95, 231, 239, 123, 223, 247, 255, 22, 108, 106, 110, 86, 109, 107, 111, 293, 602, 604, 606, 601, 603, 605, 607, 116, 737, 626, 741, 678, 739, 742, 743, 302, 745, 748, 749, 746, 747, 750, 751, 102, 666, 661, 670, 598, 667, 669, 671, 301, 729, 732, 733, 729, 731, 733, 735, 230, 753, 756, 757, 742, 755, 758, 759, 303, 761, 764, 765, 762, 763, 766, 767, 22, 293, 116, 302, 102, 301, 230, 303, 108, 602, 737, 745, 666, 729, 753, 761, 106, 604, 626, 748, 661, 732, 756, 764, 110, 606, 741, 749, 670, 733, 757, 765, 86, 601, 678, 746, 598, 729, 742, 762, 109, 603, 739, 747, 667, 731, 755, 763, 107, 605, 742, 750, 669, 733, 758, 766, 111, 607, 743, 751, 671, 735, 759, 767, 54, 310, 118, 365, 118, 365, 246, 367, 310, 876, 822, 877, 822, 877, 875, 879, 118, 822, 630, 886, 694, 949, 758, 957, 365, 877, 886, 1755, 949, 1757, 1758, 1759, 118, 822, 694, 949, 630, 886, 758, 957, 365, 877, 949, 1757, 886, 1755, 1758, 1759, 246, 875, 758, 1758, 758, 1758, 1782, 1783, 367, 879, 957, 1759, 957, 1759, 1783, 1791, 14, 101, 85, 117, 77, 109, 93, 125, 101, 659, 675, 686, 595, 667, 683, 687, 85, 675, 625, 819, 597, 739, 753, 827, 117, 686, 819, 947, 627, 755, 883, 955, 77, 595, 597, 627, 587, 603, 605, 635, 109, 667, 739, 755, 603, 731, 747, 763, 93, 683, 753, 883, 605, 747, 875, 891, 125, 687, 827, 955, 635, 763, 891, 1019, 30, 229, 115, 238, 94, 237, 221, 239, 302, 748, 746, 750, 745, 749, 747, 751, 117, 819, 627, 883, 686, 947, 755, 955, 373, 885, 885, 1883, 885, 1883, 1883, 1887, 110, 741, 670, 757, 606, 749, 733, 765, 365, 886, 949, 1758, 877, 1755, 1757, 1759, 238, 883, 757, 1907, 750, 1883, 1758, 1911, 375, 887, 958, 1911, 893, 1917, 1918, 1919, 30, 302, 117, 373, 110, 365, 238, 375, 229, 748, 819, 885, 741, 886, 883, 887, 115, 746, 627, 885, 670, 949, 757, 958, 238, 750, 883, 1883, 757, 1758, 1907, 1911, 94, 745, 686, 885, 606, 877, 750, 893, 237, 749, 947, 1883, 749, 1755, 1883, 1917, 221, 747, 755, 1883, 733, 1757, 1758, 1918, 239, 751, 955, 1887, 765, 1759, 1911, 1919, 55, 311, 119, 375, 126, 382, 247, 383, 311, 892, 823, 893, 830, 894, 891, 895, 119, 823, 631, 887, 695, 951, 759, 959, 375, 893, 887, 1917, 958, 1918, 1911, 1919, 126, 830, 695, 958, 638, 894, 766, 1021, 382, 894, 951, 1918, 894, 2029, 1918, 2031, 247, 891, 759, 1911, 766, 1918, 1783, 2039, 383, 895, 959, 1919, 1021, 2031, 2039, 2047, 1, 20, 18, 22, 10, 21, 19, 23, 20, 98, 100, 102, 84, 99, 101, 103, 18, 100, 292, 293, 100, 228, 293, 295, 22, 102, 293, 301, 116, 230, 302, 303, 10, 84, 100, 116, 76, 92, 108, 124, 21, 99, 228, 230, 92, 220, 229, 231, 19, 101, 293, 302, 108, 229, 310, 311, 23, 103, 295, 303, 124, 231, 311, 319, 10, 84, 73, 86, 81, 85, 83, 87, 100, 596, 594, 598, 593, 597, 595, 599, 76, 593, 585, 601, 593, 625, 601, 633, 108, 666, 602, 729, 737, 753, 745, 761, 84, 674, 596, 678, 593, 675, 666, 679, 116, 678, 626, 742, 737, 739, 741, 743, 92, 675, 604, 746, 737, 819, 822, 823, 124, 679, 634, 762, 826, 827, 830, 831, 10, 100, 76, 108, 84, 116, 92, 124, 84, 596, 593, 666, 674, 678, 675, 679, 73, 594, 585, 602, 596, 626, 604, 634, 86, 598, 601, 729, 678, 742, 746, 762, 81, 593, 593, 737, 593, 737, 737, 826, 85, 597, 625, 753, 675, 739, 819, 827, 83, 595, 601, 745, 666, 741, 822, 830, 87, 599, 633, 761, 679, 743, 823, 831, 14, 101, 77, 109, 85, 117, 93, 125, 101, 659, 595, 667, 675, 686, 683, 687, 77, 595, 587, 603, 597, 627, 605, 635, 109, 667, 603, 731, 739, 755, 747, 763, 85, 675, 597, 739, 625, 819, 753, 827, 117, 686, 627, 755, 819, 947, 883, 955, 93, 683, 605, 747, 753, 883, 875, 891, 125, 687, 635, 763, 827, 955, 891, 1019, 9, 98, 73, 106, 73, 106, 90, 122, 98, 660, 596, 661, 596, 661, 659, 663, 73, 596, 585, 604, 594, 626, 602, 634, 106, 661, 604, 732, 626, 756, 748, 764, 73, 596, 594, 626, 585, 604, 602, 634, 106, 661, 626, 756, 604, 732, 748, 764, 90, 659, 602, 748, 602, 748, 876, 892, 122, 663, 634, 764, 634, 764, 892, 1020, 11, 99, 75, 107, 83, 115, 91, 123, 102, 661, 598, 669, 666, 670, 667, 671, 77, 597, 587, 605, 595, 627, 603, 635, 110, 670, 606, 733, 741, 757, 749, 765, 86, 678, 598, 742, 601, 746, 729, 762, 118, 694, 630, 758, 822, 949, 886, 957, 94, 686, 606, 750, 745, 885, 877, 893, 126, 695, 638, 766, 830, 958, 894, 1021, 11, 102, 77, 110, 86, 118, 94, 126, 99, 661, 597, 670, 678, 694, 686, 695, 75, 598, 587, 606, 598, 630, 606, 638, 107, 669, 605, 733, 742, 758, 750, 766, 83, 666, 595, 741, 601, 822, 745, 830, 115, 670, 627, 757, 746, 949, 885, 958, 91, 667, 603, 749, 729, 886, 877, 894, 123, 671, 635, 765, 762, 957, 893, 1021, 15, 103, 79, 111, 87, 119, 95, 127, 103, 663, 599, 671, 679, 695, 687, 703, 79, 599, 591, 607, 599, 631, 607, 639, 111, 671, 607, 735, 743, 759, 751, 767, 87, 679, 599, 743, 633, 823, 761, 831, 119, 695, 631, 759, 823, 951, 887, 959, 95, 687, 607, 751, 761, 887, 879, 895, 127, 703, 639, 767, 831, 959, 895, 1023, 3, 21, 19, 30, 11, 29, 27, 31, 22, 106, 108, 110, 86, 107, 109, 111, 22, 116, 293, 302, 102, 230, 301, 303, 54, 118, 310, 365, 118, 246, 365, 367, 14, 85, 101, 117, 77, 93, 109, 125, 30, 115, 229, 238, 94, 221, 237, 239, 30, 117, 302, 373, 110, 238, 365, 375, 55, 119, 311, 375, 126, 247, 382, 383, 19, 92, 90, 94, 83, 93, 91, 95, 293, 604, 602, 606, 601, 605, 603, 607, 108, 737, 602, 745, 666, 753, 729, 761, 310, 822, 876, 877, 822, 875, 877, 879, 101, 675, 659, 686, 595, 683, 667, 687, 302, 746, 748, 750, 745, 747, 749, 751, 229, 819, 748, 885, 741, 883, 886, 887, 311, 823, 892, 893, 830, 891, 894, 895, 21, 228, 92, 229, 99, 230, 220, 231, 116, 626, 737, 741, 678, 742, 739, 743, 106, 626, 604, 748, 661, 756, 732, 764, 118, 630, 822, 886, 694, 758, 949, 957, 85, 625, 675, 819, 597, 753, 739, 827, 117, 627, 819, 883, 686, 755, 947, 955, 115, 627, 746, 885, 670, 757, 949, 958, 119, 631, 823, 887, 695, 759, 951, 959, 30, 229, 94, 237, 115, 238, 221, 239, 302, 748, 745, 749, 746, 750, 747, 751, 110, 741, 606, 749, 670, 757, 733, 765, 365, 886, 877, 1755, 949, 1758, 1757, 1759, 117, 819, 686, 947, 627, 883, 755, 955, 373, 885, 885, 1883, 885, 1883, 1883, 1887, 238, 883, 750, 1883, 757, 1907, 1758, 1911, 375, 887, 893, 1917, 958, 1911, 1918, 1919, 11, 99, 83, 115, 75, 107, 91, 123, 102, 661, 666, 670, 598, 669, 667, 671, 86, 678, 601, 746, 598, 742, 729, 762, 118, 694, 822, 949, 630, 758, 886, 957, 77, 597, 595, 627, 587, 605, 603, 635, 110, 670, 741, 757, 606, 733, 749, 765, 94, 686, 745, 885, 606, 750, 877, 893, 126, 695, 830, 958, 638, 766, 894, 1021, 27, 220, 91, 221, 91, 221, 219, 223, 301, 732, 729, 733, 729, 733, 731, 735, 109, 739, 603, 747, 667, 755, 731, 763, 365, 949, 877, 1757, 886, 1758, 1755, 1759, 109, 739, 667, 755, 603, 747, 731, 763, 365, 949, 886, 1758, 877, 1757, 1755, 1759, 237, 947, 749, 1883, 749, 1883, 1755, 1917, 382, 951, 894, 1918, 894, 1918, 2029, 2031, 29, 230, 93, 238, 107, 246, 221, 247, 230, 756, 753, 757, 742, 758, 755, 759, 107, 742, 605, 750, 669, 758, 733, 766, 246, 758, 875, 1758, 758, 1782, 1758, 1783, 93, 753, 683, 883, 605, 875, 747, 891, 238, 757, 883, 1907, 750, 1758, 1883, 1911, 221, 755, 747, 1883, 733, 1758, 1757, 1918, 247, 759, 891, 1911, 766, 1783, 1918, 2039, 31, 231, 95, 239, 123, 247, 223, 255, 303, 764, 761, 765, 762, 766, 763, 767, 111, 743, 607, 751, 671, 759, 735, 767, 367, 957, 879, 1759, 957, 1783, 1759, 1791, 125, 827, 687, 955, 635, 891, 763, 1019, 375, 958, 887, 1911, 893, 1918, 1917, 1919, 239, 955, 751, 1887, 765, 1911, 1759, 1919, 383, 959, 895, 1919, 1021, 2039, 2031, 2047, 3, 22, 22, 54, 14, 30, 30, 55, 21, 106, 116, 118, 85, 115, 117, 119, 19, 108, 293, 310, 101, 229, 302, 311, 30, 110, 302, 365, 117, 238, 373, 375, 11, 86, 102, 118, 77, 94, 110, 126, 29, 107, 230, 246, 93, 221, 238, 247, 27, 109, 301, 365, 109, 237, 365, 382, 31, 111, 303, 367, 125, 239, 375, 383, 21, 116, 106, 118, 85, 117, 115, 119, 228, 626, 626, 630, 625, 627, 627, 631, 92, 737, 604, 822, 675, 819, 746, 823, 229, 741, 748, 886, 819, 883, 885, 887, 99, 678, 661, 694, 597, 686, 670, 695, 230, 742, 756, 758, 753, 755, 757, 759, 220, 739, 732, 949, 739, 947, 949, 951, 231, 743, 764, 957, 827, 955, 958, 959, 19, 293, 108, 310, 101, 302, 229, 311, 92, 604, 737, 822, 675, 746, 819, 823, 90, 602, 602, 876, 659, 748, 748, 892, 94, 606, 745, 877, 686, 750, 885, 893, 83, 601, 666, 822, 595, 745, 741, 830, 93, 605, 753, 875, 683, 747, 883, 891, 91, 603, 729, 877, 667, 749, 886, 894, 95, 607, 761, 879, 687, 751, 887, 895, 30, 302, 110, 365, 117, 373, 238, 375, 229, 748, 741, 886, 819, 885, 883, 887, 94, 745, 606, 877, 686, 885, 750, 893, 237, 749, 749, 1755, 947, 1883, 1883, 1917, 115, 746, 670, 949, 627, 885, 757, 958, 238, 750, 757, 1758, 883, 1883, 1907, 1911, 221, 747, 733, 1757, 755, 1883, 1758, 1918, 239, 751, 765, 1759, 955, 1887, 1911, 1919, 11, 102, 86, 118, 77, 110, 94, 126, 99, 661, 678, 694, 597, 670, 686, 695, 83, 666, 601, 822, 595, 741, 745, 830, 115, 670, 746, 949, 627, 757, 885, 958, 75, 598, 598, 630, 587, 606, 606, 638, 107, 669, 742, 758, 605, 733, 750, 766, 91, 667, 729, 886, 603, 749, 877, 894, 123, 671, 762, 957, 635, 765, 893, 1021, 29, 230, 107, 246, 93, 238, 221, 247, 230, 756, 742, 758, 753, 757, 755, 759, 93, 753, 605, 875, 683, 883, 747, 891, 238, 757, 750, 1758, 883, 1907, 1883, 1911, 107, 742, 669, 758, 605, 750, 733, 766, 246, 758, 758, 1782, 875, 1758, 1758, 1783, 221, 755, 733, 1758, 747, 1883, 1757, 1918, 247, 759, 766, 1783, 891, 1911, 1918, 2039, 27, 301, 109, 365, 109, 365, 237, 382, 220, 732, 739, 949, 739, 949, 947, 951, 91, 729, 603, 877, 667, 886, 749, 894, 221, 733, 747, 1757, 755, 1758, 1883, 1918, 91, 729, 667, 886, 603, 877, 749, 894, 221, 733, 755, 1758, 747, 1757, 1883, 1918, 219, 731, 731, 1755, 731, 1755, 1755, 2029, 223, 735, 763, 1759, 763, 1759, 1917, 2031, 31, 303, 111, 367, 125, 375, 239, 383, 231, 764, 743, 957, 827, 958, 955, 959, 95, 761, 607, 879, 687, 887, 751, 895, 239, 765, 751, 1759, 955, 1911, 1887, 1919, 123, 762, 671, 957, 635, 893, 765, 1021, 247, 766, 759, 1783, 891, 1918, 1911, 2039, 223, 763, 735, 1759, 763, 1917, 1759, 2031, 255, 767, 767, 1791, 1019, 1919, 1919, 2047, 7, 23, 23, 55, 15, 31, 31, 63, 23, 122, 124, 126, 87, 123, 125, 127, 23, 124, 295, 311, 103, 231, 303, 319, 55, 126, 311, 382, 119, 247, 375, 383, 15, 87, 103, 119, 79, 95, 111, 127, 31, 123, 231, 247, 95, 223, 239, 255, 31, 125, 303, 375, 111, 239, 367, 383, 63, 127, 319, 383, 127, 255, 383, 511, 23, 124, 122, 126, 87, 125, 123, 127, 295, 634, 634, 638, 633, 635, 635, 639, 124, 826, 634, 830, 679, 827, 762, 831, 311, 830, 892, 894, 823, 891, 893, 895, 103, 679, 663, 695, 599, 687, 671, 703, 303, 762, 764, 766, 761, 763, 765, 767, 231, 827, 764, 958, 743, 955, 957, 959, 319, 831, 1020, 1021, 831, 1019, 1021, 1023, 23, 295, 124, 311, 103, 303, 231, 319, 124, 634, 826, 830, 679, 762, 827, 831, 122, 634, 634, 892, 663, 764, 764, 1020, 126, 638, 830, 894, 695, 766, 958, 1021, 87, 633, 679, 823, 599, 761, 743, 831, 125, 635, 827, 891, 687, 763, 955, 1019, 123, 635, 762, 893, 671, 765, 957, 1021, 127, 639, 831, 895, 703, 767, 959, 1023, 55, 311, 126, 382, 119, 375, 247, 383, 311, 892, 830, 894, 823, 893, 891, 895, 126, 830, 638, 894, 695, 958, 766, 1021, 382, 894, 894, 2029, 951, 1918, 1918, 2031, 119, 823, 695, 951, 631, 887, 759, 959, 375, 893, 958, 1918, 887, 1917, 1911, 1919, 247, 891, 766, 1918, 759, 1911, 1783, 2039, 383, 895, 1021, 2031, 959, 1919, 2039, 2047, 15, 103, 87, 119, 79, 111, 95, 127, 103, 663, 679, 695, 599, 671, 687, 703, 87, 679, 633, 823, 599, 743, 761, 831, 119, 695, 823, 951, 631, 759, 887, 959, 79, 599, 599, 631, 591, 607, 607, 639, 111, 671, 743, 759, 607, 735, 751, 767, 95, 687, 761, 887, 607, 751, 879, 895, 127, 703, 831, 959, 639, 767, 895, 1023, 31, 231, 123, 247, 95, 239, 223, 255, 303, 764, 762, 766, 761, 765, 763, 767, 125, 827, 635, 891, 687, 955, 763, 1019, 375, 958, 893, 1918, 887, 1911, 1917, 1919, 111, 743, 671, 759, 607, 751, 735, 767, 367, 957, 957, 1783, 879, 1759, 1759, 1791, 239, 955, 765, 1911, 751, 1887, 1759, 1919, 383, 959, 1021, 2039, 895, 1919, 2031, 2047, 31, 303, 125, 375, 111, 367, 239, 383, 231, 764, 827, 958, 743, 957, 955, 959, 123, 762, 635, 893, 671, 957, 765, 1021, 247, 766, 891, 1918, 759, 1783, 1911, 2039, 95, 761, 687, 887, 607, 879, 751, 895, 239, 765, 955, 1911, 751, 1759, 1887, 1919, 223, 763, 763, 1917, 735, 1759, 1759, 2031, 255, 767, 1019, 1919, 767, 1791, 1919, 2047, 63, 319, 127, 383, 127, 383, 255, 511, 319, 1020, 831, 1021, 831, 1021, 1019, 1023, 127, 831, 639, 895, 703, 959, 767, 1023, 383, 1021, 895, 2031, 959, 2039, 1919, 2047, 127, 831, 703, 959, 639, 895, 767, 1023, 383, 1021, 959, 2039, 895, 2031, 1919, 2047, 255, 1019, 767, 1919, 767, 1919, 1791, 2047, 511, 1023, 1023, 2047, 1023, 2047, 2047, 4095 }; const unsigned int igraph_i_isoclass_4_idx[] = { 0, 8, 64, 512, 1, 0, 128, 1024, 2, 16, 0, 2048, 4, 32, 256, 0 }; const unsigned int igraph_i_isoclass_3u[] = { 0, 1, 1, 3, 1, 3, 3, 7 }; const unsigned int igraph_i_isoclass_3u_idx[] = { 0, 1, 2, 1, 0, 4, 2, 4, 0 }; const unsigned int igraph_i_isoclass_4u[] = { 0, 1, 1, 3, 1, 3, 3, 7, 1, 3, 3, 11, 12, 13, 13, 15, 1, 3, 12, 13, 3, 11, 13, 15, 3, 7, 13, 15, 13, 15, 30, 31, 1, 12, 3, 13, 3, 13, 11, 15, 3, 13, 7, 15, 13, 30, 15, 31, 3, 13, 13, 30, 7, 15, 15, 31, 11, 15, 15, 31, 15, 31, 31, 63 }; const unsigned int igraph_i_isoclass_4u_idx[] = { 0, 1, 2, 8, 1, 0, 4, 16, 2, 4, 0, 32, 8, 16, 32, 0 }; const unsigned int igraph_i_isoclass2_3[] = { 0, 1, 1, 2, 1, 3, 4, 5, 1, 4, 6, 7, 2, 5, 7, 8, 1, 4, 3, 5, 6, 9, 9, 10, 4, 11, 9, 12, 7, 12, 13, 14, 1, 6, 4, 7, 4, 9, 11, 12, 3, 9, 9, 13, 5, 10, 12, 14, 2, 7, 5, 8, 7, 13, 12, 14, 5, 12, 10, 14, 8, 14, 14, 15 }; const unsigned int igraph_i_isoclass2_3u[] = { 0, 1, 1, 2, 1, 2, 2, 3 }; const unsigned int igraph_i_isoclass2_4u[] = { 0, 1, 1, 2, 1, 2, 2, 3, 1, 2, 2, 4, 5, 6, 6, 7, 1, 2, 5, 6, 2, 4, 6, 7, 2, 3, 6, 7, 6, 7, 8, 9, 1, 5, 2, 6, 2, 6, 4, 7, 2, 6, 3, 7, 6, 8, 7, 9, 2, 6, 6, 8, 3, 7, 7, 9, 4, 7, 7, 9, 7, 9, 9, 10 }; const unsigned int igraph_i_isoclass2_4[] = { 0, 1, 1, 2, 1, 2, 2, 3, 1, 4, 5, 6, 5, 6, 7, 8, 1, 5, 9, 10, 11, 12, 13, 14, 2, 6, 10, 15, 12, 16, 17, 18, 1, 5, 11, 12, 9, 10, 13, 14, 2, 6, 12, 16, 10, 15, 17, 18, 2, 7, 13, 17, 13, 17, 19, 20, 3, 8, 14, 18, 14, 18, 20, 21, 1, 5, 4, 6, 5, 7, 6, 8, 9, 22, 22, 23, 24, 25, 25, 26, 5, 27, 22, 28, 29, 30, 31, 32, 10, 28, 33, 34, 35, 36, 37, 38, 11, 29, 39, 40, 41, 42, 43, 44, 13, 31, 45, 46, 47, 48, 49, 50, 12, 30, 45, 51, 52, 53, 54, 55, 14, 32, 56, 57, 58, 59, 60, 61, 1, 9, 5, 10, 11, 13, 12, 14, 5, 22, 27, 28, 29, 31, 30, 32, 4, 22, 22, 33, 39, 45, 45, 56, 6, 23, 28, 34, 40, 46, 51, 57, 5, 24, 29, 35, 41, 47, 52, 58, 7, 25, 30, 36, 42, 48, 53, 59, 6, 25, 31, 37, 43, 49, 54, 60, 8, 26, 32, 38, 44, 50, 55, 61, 2, 10, 6, 15, 12, 17, 16, 18, 10, 33, 28, 34, 35, 37, 36, 38, 6, 28, 23, 34, 40, 51, 46, 57, 15, 34, 34, 62, 63, 64, 64, 65, 12, 35, 40, 63, 66, 67, 68, 69, 17, 37, 51, 64, 67, 70, 71, 72, 16, 36, 46, 64, 68, 71, 73, 74, 18, 38, 57, 65, 69, 72, 74, 75, 1, 11, 5, 12, 9, 13, 10, 14, 11, 39, 29, 40, 41, 43, 42, 44, 5, 29, 24, 35, 41, 52, 47, 58, 12, 40, 35, 63, 66, 68, 67, 69, 9, 41, 41, 66, 76, 77, 77, 78, 13, 43, 52, 68, 77, 79, 80, 81, 10, 42, 47, 67, 77, 80, 82, 83, 14, 44, 58, 69, 78, 81, 83, 84, 2, 12, 6, 16, 10, 17, 15, 18, 13, 45, 31, 46, 47, 49, 48, 50, 7, 30, 25, 36, 42, 53, 48, 59, 17, 51, 37, 64, 67, 71, 70, 72, 13, 52, 43, 68, 77, 80, 79, 81, 19, 54, 54, 73, 82, 85, 85, 86, 17, 53, 49, 71, 80, 87, 85, 88, 20, 55, 60, 74, 83, 88, 89, 90, 2, 13, 7, 17, 13, 19, 17, 20, 12, 45, 30, 51, 52, 54, 53, 55, 6, 31, 25, 37, 43, 54, 49, 60, 16, 46, 36, 64, 68, 73, 71, 74, 10, 47, 42, 67, 77, 82, 80, 83, 17, 49, 53, 71, 80, 85, 87, 88, 15, 48, 48, 70, 79, 85, 85, 89, 18, 50, 59, 72, 81, 86, 88, 90, 3, 14, 8, 18, 14, 20, 18, 21, 14, 56, 32, 57, 58, 60, 59, 61, 8, 32, 26, 38, 44, 55, 50, 61, 18, 57, 38, 65, 69, 74, 72, 75, 14, 58, 44, 69, 78, 83, 81, 84, 20, 60, 55, 74, 83, 89, 88, 90, 18, 59, 50, 72, 81, 88, 86, 90, 21, 61, 61, 75, 84, 90, 90, 91, 1, 5, 5, 7, 4, 6, 6, 8, 9, 22, 24, 25, 22, 23, 25, 26, 11, 29, 41, 42, 39, 40, 43, 44, 13, 31, 47, 48, 45, 46, 49, 50, 5, 27, 29, 30, 22, 28, 31, 32, 10, 28, 35, 36, 33, 34, 37, 38, 12, 30, 52, 53, 45, 51, 54, 55, 14, 32, 58, 59, 56, 57, 60, 61, 9, 24, 22, 25, 22, 25, 23, 26, 76, 92, 92, 93, 92, 93, 93, 94, 41, 95, 96, 97, 98, 99, 100, 101, 77, 102, 103, 104, 105, 106, 107, 108, 41, 95, 98, 99, 96, 97, 100, 101, 77, 102, 105, 106, 103, 104, 107, 108, 66, 109, 110, 111, 110, 111, 112, 113, 78, 114, 115, 116, 115, 116, 117, 118, 11, 41, 29, 42, 39, 43, 40, 44, 41, 96, 95, 97, 98, 100, 99, 101, 39, 98, 98, 119, 120, 121, 121, 122, 43, 100, 123, 124, 121, 125, 126, 127, 29, 95, 128, 129, 98, 123, 130, 131, 42, 97, 129, 132, 119, 124, 133, 134, 40, 99, 130, 133, 121, 126, 135, 136, 44, 101, 131, 134, 122, 127, 136, 137, 13, 47, 31, 48, 45, 49, 46, 50, 77, 103, 102, 104, 105, 107, 106, 108, 43, 123, 100, 124, 121, 126, 125, 127, 79, 138, 138, 139, 140, 141, 141, 142, 52, 143, 130, 144, 110, 145, 146, 147, 80, 148, 149, 150, 151, 152, 153, 154, 68, 155, 146, 156, 157, 158, 159, 160, 81, 161, 162, 163, 164, 165, 166, 167, 5, 29, 27, 30, 22, 31, 28, 32, 41, 98, 95, 99, 96, 100, 97, 101, 29, 128, 95, 129, 98, 130, 123, 131, 52, 130, 143, 144, 110, 146, 145, 147, 24, 95, 95, 109, 92, 102, 102, 114, 47, 123, 143, 155, 103, 138, 148, 161, 35, 129, 143, 168, 105, 149, 169, 170, 58, 131, 171, 172, 115, 162, 173, 174, 10, 35, 28, 36, 33, 37, 34, 38, 77, 105, 102, 106, 103, 107, 104, 108, 42, 129, 97, 132, 119, 133, 124, 134, 80, 149, 148, 150, 151, 153, 152, 154, 47, 143, 123, 155, 103, 148, 138, 161, 82, 169, 169, 175, 176, 177, 177, 178, 67, 168, 145, 179, 151, 180, 181, 182, 83, 170, 173, 183, 184, 185, 186, 187, 12, 52, 30, 53, 45, 54, 51, 55, 66, 110, 109, 111, 110, 112, 111, 113, 40, 130, 99, 133, 121, 135, 126, 136, 68, 146, 155, 156, 157, 159, 158, 160, 35, 143, 129, 168, 105, 169, 149, 170, 67, 145, 168, 179, 151, 181, 180, 182, 63, 144, 144, 188, 140, 189, 189, 190, 69, 147, 172, 191, 164, 192, 193, 194, 14, 58, 32, 59, 56, 60, 57, 61, 78, 115, 114, 116, 115, 117, 116, 118, 44, 131, 101, 134, 122, 136, 127, 137, 81, 162, 161, 163, 164, 166, 165, 167, 58, 171, 131, 172, 115, 173, 162, 174, 83, 173, 170, 183, 184, 186, 185, 187, 69, 172, 147, 191, 164, 193, 192, 194, 84, 174, 174, 195, 196, 197, 197, 198, 1, 9, 11, 13, 5, 10, 12, 14, 5, 22, 29, 31, 27, 28, 30, 32, 5, 24, 41, 47, 29, 35, 52, 58, 7, 25, 42, 48, 30, 36, 53, 59, 4, 22, 39, 45, 22, 33, 45, 56, 6, 23, 40, 46, 28, 34, 51, 57, 6, 25, 43, 49, 31, 37, 54, 60, 8, 26, 44, 50, 32, 38, 55, 61, 11, 41, 39, 43, 29, 42, 40, 44, 41, 96, 98, 100, 95, 97, 99, 101, 29, 95, 98, 123, 128, 129, 130, 131, 42, 97, 119, 124, 129, 132, 133, 134, 39, 98, 120, 121, 98, 119, 121, 122, 43, 100, 121, 125, 123, 124, 126, 127, 40, 99, 121, 126, 130, 133, 135, 136, 44, 101, 122, 127, 131, 134, 136, 137, 9, 76, 41, 77, 41, 77, 66, 78, 24, 92, 95, 102, 95, 102, 109, 114, 22, 92, 96, 103, 98, 105, 110, 115, 25, 93, 97, 104, 99, 106, 111, 116, 22, 92, 98, 105, 96, 103, 110, 115, 25, 93, 99, 106, 97, 104, 111, 116, 23, 93, 100, 107, 100, 107, 112, 117, 26, 94, 101, 108, 101, 108, 113, 118, 13, 77, 43, 79, 52, 80, 68, 81, 47, 103, 123, 138, 143, 148, 155, 161, 31, 102, 100, 138, 130, 149, 146, 162, 48, 104, 124, 139, 144, 150, 156, 163, 45, 105, 121, 140, 110, 151, 157, 164, 49, 107, 126, 141, 145, 152, 158, 165, 46, 106, 125, 141, 146, 153, 159, 166, 50, 108, 127, 142, 147, 154, 160, 167, 5, 41, 29, 52, 24, 47, 35, 58, 29, 98, 128, 130, 95, 123, 129, 131, 27, 95, 95, 143, 95, 143, 143, 171, 30, 99, 129, 144, 109, 155, 168, 172, 22, 96, 98, 110, 92, 103, 105, 115, 31, 100, 130, 146, 102, 138, 149, 162, 28, 97, 123, 145, 102, 148, 169, 173, 32, 101, 131, 147, 114, 161, 170, 174, 12, 66, 40, 68, 35, 67, 63, 69, 52, 110, 130, 146, 143, 145, 144, 147, 30, 109, 99, 155, 129, 168, 144, 172, 53, 111, 133, 156, 168, 179, 188, 191, 45, 110, 121, 157, 105, 151, 140, 164, 54, 112, 135, 159, 169, 181, 189, 192, 51, 111, 126, 158, 149, 180, 189, 193, 55, 113, 136, 160, 170, 182, 190, 194, 10, 77, 42, 80, 47, 82, 67, 83, 35, 105, 129, 149, 143, 169, 168, 170, 28, 102, 97, 148, 123, 169, 145, 173, 36, 106, 132, 150, 155, 175, 179, 183, 33, 103, 119, 151, 103, 176, 151, 184, 37, 107, 133, 153, 148, 177, 180, 185, 34, 104, 124, 152, 138, 177, 181, 186, 38, 108, 134, 154, 161, 178, 182, 187, 14, 78, 44, 81, 58, 83, 69, 84, 58, 115, 131, 162, 171, 173, 172, 174, 32, 114, 101, 161, 131, 170, 147, 174, 59, 116, 134, 163, 172, 183, 191, 195, 56, 115, 122, 164, 115, 184, 164, 196, 60, 117, 136, 166, 173, 186, 193, 197, 57, 116, 127, 165, 162, 185, 192, 197, 61, 118, 137, 167, 174, 187, 194, 198, 2, 10, 12, 17, 6, 15, 16, 18, 10, 33, 35, 37, 28, 34, 36, 38, 12, 35, 66, 67, 40, 63, 68, 69, 17, 37, 67, 70, 51, 64, 71, 72, 6, 28, 40, 51, 23, 34, 46, 57, 15, 34, 63, 64, 34, 62, 64, 65, 16, 36, 68, 71, 46, 64, 73, 74, 18, 38, 69, 72, 57, 65, 74, 75, 13, 47, 45, 49, 31, 48, 46, 50, 77, 103, 105, 107, 102, 104, 106, 108, 52, 143, 110, 145, 130, 144, 146, 147, 80, 148, 151, 152, 149, 150, 153, 154, 43, 123, 121, 126, 100, 124, 125, 127, 79, 138, 140, 141, 138, 139, 141, 142, 68, 155, 157, 158, 146, 156, 159, 160, 81, 161, 164, 165, 162, 163, 166, 167, 13, 77, 52, 80, 43, 79, 68, 81, 47, 103, 143, 148, 123, 138, 155, 161, 45, 105, 110, 151, 121, 140, 157, 164, 49, 107, 145, 152, 126, 141, 158, 165, 31, 102, 130, 149, 100, 138, 146, 162, 48, 104, 144, 150, 124, 139, 156, 163, 46, 106, 146, 153, 125, 141, 159, 166, 50, 108, 147, 154, 127, 142, 160, 167, 19, 82, 54, 85, 54, 85, 73, 86, 82, 176, 169, 177, 169, 177, 175, 178, 54, 169, 112, 181, 135, 189, 159, 192, 85, 177, 181, 199, 189, 200, 201, 202, 54, 169, 135, 189, 112, 181, 159, 192, 85, 177, 189, 200, 181, 199, 201, 202, 73, 175, 159, 201, 159, 201, 203, 204, 86, 178, 192, 202, 192, 202, 204, 205, 7, 42, 30, 53, 25, 48, 36, 59, 42, 119, 129, 133, 97, 124, 132, 134, 30, 129, 109, 168, 99, 144, 155, 172, 53, 133, 168, 188, 111, 156, 179, 191, 25, 97, 99, 111, 93, 104, 106, 116, 48, 124, 144, 156, 104, 139, 150, 163, 36, 132, 155, 179, 106, 150, 175, 183, 59, 134, 172, 191, 116, 163, 183, 195, 17, 67, 51, 71, 37, 70, 64, 72, 80, 151, 149, 153, 148, 152, 150, 154, 53, 168, 111, 179, 133, 188, 156, 191, 87, 180, 180, 206, 180, 206, 206, 207, 49, 145, 126, 158, 107, 152, 141, 165, 85, 181, 189, 201, 177, 199, 200, 202, 71, 179, 158, 208, 153, 206, 201, 209, 88, 182, 193, 209, 185, 210, 211, 212, 17, 80, 53, 87, 49, 85, 71, 88, 67, 151, 168, 180, 145, 181, 179, 182, 51, 149, 111, 180, 126, 189, 158, 193, 71, 153, 179, 206, 158, 201, 208, 209, 37, 148, 133, 180, 107, 177, 153, 185, 70, 152, 188, 206, 152, 199, 206, 210, 64, 150, 156, 206, 141, 200, 201, 211, 72, 154, 191, 207, 165, 202, 209, 212, 20, 83, 55, 88, 60, 89, 74, 90, 83, 184, 170, 185, 173, 186, 183, 187, 55, 170, 113, 182, 136, 190, 160, 194, 88, 185, 182, 210, 193, 211, 209, 212, 60, 173, 136, 193, 117, 186, 166, 197, 89, 186, 190, 211, 186, 213, 211, 214, 74, 183, 160, 209, 166, 211, 204, 215, 90, 187, 194, 212, 197, 214, 215, 216, 1, 11, 9, 13, 5, 12, 10, 14, 11, 39, 41, 43, 29, 40, 42, 44, 9, 41, 76, 77, 41, 66, 77, 78, 13, 43, 77, 79, 52, 68, 80, 81, 5, 29, 41, 52, 24, 35, 47, 58, 12, 40, 66, 68, 35, 63, 67, 69, 10, 42, 77, 80, 47, 67, 82, 83, 14, 44, 78, 81, 58, 69, 83, 84, 5, 29, 22, 31, 27, 30, 28, 32, 41, 98, 96, 100, 95, 99, 97, 101, 24, 95, 92, 102, 95, 109, 102, 114, 47, 123, 103, 138, 143, 155, 148, 161, 29, 128, 98, 130, 95, 129, 123, 131, 52, 130, 110, 146, 143, 144, 145, 147, 35, 129, 105, 149, 143, 168, 169, 170, 58, 131, 115, 162, 171, 172, 173, 174, 5, 41, 24, 47, 29, 52, 35, 58, 29, 98, 95, 123, 128, 130, 129, 131, 22, 96, 92, 103, 98, 110, 105, 115, 31, 100, 102, 138, 130, 146, 149, 162, 27, 95, 95, 143, 95, 143, 143, 171, 30, 99, 109, 155, 129, 144, 168, 172, 28, 97, 102, 148, 123, 145, 169, 173, 32, 101, 114, 161, 131, 147, 170, 174, 7, 42, 25, 48, 30, 53, 36, 59, 42, 119, 97, 124, 129, 133, 132, 134, 25, 97, 93, 104, 99, 111, 106, 116, 48, 124, 104, 139, 144, 156, 150, 163, 30, 129, 99, 144, 109, 168, 155, 172, 53, 133, 111, 156, 168, 188, 179, 191, 36, 132, 106, 150, 155, 179, 175, 183, 59, 134, 116, 163, 172, 191, 183, 195, 4, 39, 22, 45, 22, 45, 33, 56, 39, 120, 98, 121, 98, 121, 119, 122, 22, 98, 92, 105, 96, 110, 103, 115, 45, 121, 105, 140, 110, 157, 151, 164, 22, 98, 96, 110, 92, 105, 103, 115, 45, 121, 110, 157, 105, 140, 151, 164, 33, 119, 103, 151, 103, 151, 176, 184, 56, 122, 115, 164, 115, 164, 184, 196, 6, 40, 23, 46, 28, 51, 34, 57, 43, 121, 100, 125, 123, 126, 124, 127, 25, 99, 93, 106, 97, 111, 104, 116, 49, 126, 107, 141, 145, 158, 152, 165, 31, 130, 100, 146, 102, 149, 138, 162, 54, 135, 112, 159, 169, 189, 181, 192, 37, 133, 107, 153, 148, 180, 177, 185, 60, 136, 117, 166, 173, 193, 186, 197, 6, 43, 25, 49, 31, 54, 37, 60, 40, 121, 99, 126, 130, 135, 133, 136, 23, 100, 93, 107, 100, 112, 107, 117, 46, 125, 106, 141, 146, 159, 153, 166, 28, 123, 97, 145, 102, 169, 148, 173, 51, 126, 111, 158, 149, 189, 180, 193, 34, 124, 104, 152, 138, 181, 177, 186, 57, 127, 116, 165, 162, 192, 185, 197, 8, 44, 26, 50, 32, 55, 38, 61, 44, 122, 101, 127, 131, 136, 134, 137, 26, 101, 94, 108, 101, 113, 108, 118, 50, 127, 108, 142, 147, 160, 154, 167, 32, 131, 101, 147, 114, 170, 161, 174, 55, 136, 113, 160, 170, 190, 182, 194, 38, 134, 108, 154, 161, 182, 178, 187, 61, 137, 118, 167, 174, 194, 187, 198, 2, 12, 10, 17, 6, 16, 15, 18, 13, 45, 47, 49, 31, 46, 48, 50, 13, 52, 77, 80, 43, 68, 79, 81, 19, 54, 82, 85, 54, 73, 85, 86, 7, 30, 42, 53, 25, 36, 48, 59, 17, 51, 67, 71, 37, 64, 70, 72, 17, 53, 80, 87, 49, 71, 85, 88, 20, 55, 83, 88, 60, 74, 89, 90, 10, 35, 33, 37, 28, 36, 34, 38, 77, 105, 103, 107, 102, 106, 104, 108, 47, 143, 103, 148, 123, 155, 138, 161, 82, 169, 176, 177, 169, 175, 177, 178, 42, 129, 119, 133, 97, 132, 124, 134, 80, 149, 151, 153, 148, 150, 152, 154, 67, 168, 151, 180, 145, 179, 181, 182, 83, 170, 184, 185, 173, 183, 186, 187, 12, 66, 35, 67, 40, 68, 63, 69, 52, 110, 143, 145, 130, 146, 144, 147, 45, 110, 105, 151, 121, 157, 140, 164, 54, 112, 169, 181, 135, 159, 189, 192, 30, 109, 129, 168, 99, 155, 144, 172, 53, 111, 168, 179, 133, 156, 188, 191, 51, 111, 149, 180, 126, 158, 189, 193, 55, 113, 170, 182, 136, 160, 190, 194, 17, 67, 37, 70, 51, 71, 64, 72, 80, 151, 148, 152, 149, 153, 150, 154, 49, 145, 107, 152, 126, 158, 141, 165, 85, 181, 177, 199, 189, 201, 200, 202, 53, 168, 133, 188, 111, 179, 156, 191, 87, 180, 180, 206, 180, 206, 206, 207, 71, 179, 153, 206, 158, 208, 201, 209, 88, 182, 185, 210, 193, 209, 211, 212, 6, 40, 28, 51, 23, 46, 34, 57, 43, 121, 123, 126, 100, 125, 124, 127, 31, 130, 102, 149, 100, 146, 138, 162, 54, 135, 169, 189, 112, 159, 181, 192, 25, 99, 97, 111, 93, 106, 104, 116, 49, 126, 145, 158, 107, 141, 152, 165, 37, 133, 148, 180, 107, 153, 177, 185, 60, 136, 173, 193, 117, 166, 186, 197, 15, 63, 34, 64, 34, 64, 62, 65, 79, 140, 138, 141, 138, 141, 139, 142, 48, 144, 104, 150, 124, 156, 139, 163, 85, 189, 177, 200, 181, 201, 199, 202, 48, 144, 124, 156, 104, 150, 139, 163, 85, 189, 181, 201, 177, 200, 199, 202, 70, 188, 152, 206, 152, 206, 199, 210, 89, 190, 186, 211, 186, 211, 213, 214, 16, 68, 36, 71, 46, 73, 64, 74, 68, 157, 155, 158, 146, 159, 156, 160, 46, 146, 106, 153, 125, 159, 141, 166, 73, 159, 175, 201, 159, 203, 201, 204, 36, 155, 132, 179, 106, 175, 150, 183, 71, 158, 179, 208, 153, 201, 206, 209, 64, 156, 150, 206, 141, 201, 200, 211, 74, 160, 183, 209, 166, 204, 211, 215, 18, 69, 38, 72, 57, 74, 65, 75, 81, 164, 161, 165, 162, 166, 163, 167, 50, 147, 108, 154, 127, 160, 142, 167, 86, 192, 178, 202, 192, 204, 202, 205, 59, 172, 134, 191, 116, 183, 163, 195, 88, 193, 182, 209, 185, 211, 210, 212, 72, 191, 154, 207, 165, 209, 202, 212, 90, 194, 187, 212, 197, 215, 214, 216, 2, 13, 13, 19, 7, 17, 17, 20, 12, 45, 52, 54, 30, 51, 53, 55, 10, 47, 77, 82, 42, 67, 80, 83, 17, 49, 80, 85, 53, 71, 87, 88, 6, 31, 43, 54, 25, 37, 49, 60, 16, 46, 68, 73, 36, 64, 71, 74, 15, 48, 79, 85, 48, 70, 85, 89, 18, 50, 81, 86, 59, 72, 88, 90, 12, 52, 45, 54, 30, 53, 51, 55, 66, 110, 110, 112, 109, 111, 111, 113, 35, 143, 105, 169, 129, 168, 149, 170, 67, 145, 151, 181, 168, 179, 180, 182, 40, 130, 121, 135, 99, 133, 126, 136, 68, 146, 157, 159, 155, 156, 158, 160, 63, 144, 140, 189, 144, 188, 189, 190, 69, 147, 164, 192, 172, 191, 193, 194, 10, 77, 47, 82, 42, 80, 67, 83, 35, 105, 143, 169, 129, 149, 168, 170, 33, 103, 103, 176, 119, 151, 151, 184, 37, 107, 148, 177, 133, 153, 180, 185, 28, 102, 123, 169, 97, 148, 145, 173, 36, 106, 155, 175, 132, 150, 179, 183, 34, 104, 138, 177, 124, 152, 181, 186, 38, 108, 161, 178, 134, 154, 182, 187, 17, 80, 49, 85, 53, 87, 71, 88, 67, 151, 145, 181, 168, 180, 179, 182, 37, 148, 107, 177, 133, 180, 153, 185, 70, 152, 152, 199, 188, 206, 206, 210, 51, 149, 126, 189, 111, 180, 158, 193, 71, 153, 158, 201, 179, 206, 208, 209, 64, 150, 141, 200, 156, 206, 201, 211, 72, 154, 165, 202, 191, 207, 209, 212, 6, 43, 31, 54, 25, 49, 37, 60, 40, 121, 130, 135, 99, 126, 133, 136, 28, 123, 102, 169, 97, 145, 148, 173, 51, 126, 149, 189, 111, 158, 180, 193, 23, 100, 100, 112, 93, 107, 107, 117, 46, 125, 146, 159, 106, 141, 153, 166, 34, 124, 138, 181, 104, 152, 177, 186, 57, 127, 162, 192, 116, 165, 185, 197, 16, 68, 46, 73, 36, 71, 64, 74, 68, 157, 146, 159, 155, 158, 156, 160, 36, 155, 106, 175, 132, 179, 150, 183, 71, 158, 153, 201, 179, 208, 206, 209, 46, 146, 125, 159, 106, 153, 141, 166, 73, 159, 159, 203, 175, 201, 201, 204, 64, 156, 141, 201, 150, 206, 200, 211, 74, 160, 166, 204, 183, 209, 211, 215, 15, 79, 48, 85, 48, 85, 70, 89, 63, 140, 144, 189, 144, 189, 188, 190, 34, 138, 104, 177, 124, 181, 152, 186, 64, 141, 150, 200, 156, 201, 206, 211, 34, 138, 124, 181, 104, 177, 152, 186, 64, 141, 156, 201, 150, 200, 206, 211, 62, 139, 139, 199, 139, 199, 199, 213, 65, 142, 163, 202, 163, 202, 210, 214, 18, 81, 50, 86, 59, 88, 72, 90, 69, 164, 147, 192, 172, 193, 191, 194, 38, 161, 108, 178, 134, 182, 154, 187, 72, 165, 154, 202, 191, 209, 207, 212, 57, 162, 127, 192, 116, 185, 165, 197, 74, 166, 160, 204, 183, 211, 209, 215, 65, 163, 142, 202, 163, 210, 202, 214, 75, 167, 167, 205, 195, 212, 212, 216, 3, 14, 14, 20, 8, 18, 18, 21, 14, 56, 58, 60, 32, 57, 59, 61, 14, 58, 78, 83, 44, 69, 81, 84, 20, 60, 83, 89, 55, 74, 88, 90, 8, 32, 44, 55, 26, 38, 50, 61, 18, 57, 69, 74, 38, 65, 72, 75, 18, 59, 81, 88, 50, 72, 86, 90, 21, 61, 84, 90, 61, 75, 90, 91, 14, 58, 56, 60, 32, 59, 57, 61, 78, 115, 115, 117, 114, 116, 116, 118, 58, 171, 115, 173, 131, 172, 162, 174, 83, 173, 184, 186, 170, 183, 185, 187, 44, 131, 122, 136, 101, 134, 127, 137, 81, 162, 164, 166, 161, 163, 165, 167, 69, 172, 164, 193, 147, 191, 192, 194, 84, 174, 196, 197, 174, 195, 197, 198, 14, 78, 58, 83, 44, 81, 69, 84, 58, 115, 171, 173, 131, 162, 172, 174, 56, 115, 115, 184, 122, 164, 164, 196, 60, 117, 173, 186, 136, 166, 193, 197, 32, 114, 131, 170, 101, 161, 147, 174, 59, 116, 172, 183, 134, 163, 191, 195, 57, 116, 162, 185, 127, 165, 192, 197, 61, 118, 174, 187, 137, 167, 194, 198, 20, 83, 60, 89, 55, 88, 74, 90, 83, 184, 173, 186, 170, 185, 183, 187, 60, 173, 117, 186, 136, 193, 166, 197, 89, 186, 186, 213, 190, 211, 211, 214, 55, 170, 136, 190, 113, 182, 160, 194, 88, 185, 193, 211, 182, 210, 209, 212, 74, 183, 166, 211, 160, 209, 204, 215, 90, 187, 197, 214, 194, 212, 215, 216, 8, 44, 32, 55, 26, 50, 38, 61, 44, 122, 131, 136, 101, 127, 134, 137, 32, 131, 114, 170, 101, 147, 161, 174, 55, 136, 170, 190, 113, 160, 182, 194, 26, 101, 101, 113, 94, 108, 108, 118, 50, 127, 147, 160, 108, 142, 154, 167, 38, 134, 161, 182, 108, 154, 178, 187, 61, 137, 174, 194, 118, 167, 187, 198, 18, 69, 57, 74, 38, 72, 65, 75, 81, 164, 162, 166, 161, 165, 163, 167, 59, 172, 116, 183, 134, 191, 163, 195, 88, 193, 185, 211, 182, 209, 210, 212, 50, 147, 127, 160, 108, 154, 142, 167, 86, 192, 192, 204, 178, 202, 202, 205, 72, 191, 165, 209, 154, 207, 202, 212, 90, 194, 197, 215, 187, 212, 214, 216, 18, 81, 59, 88, 50, 86, 72, 90, 69, 164, 172, 193, 147, 192, 191, 194, 57, 162, 116, 185, 127, 192, 165, 197, 74, 166, 183, 211, 160, 204, 209, 215, 38, 161, 134, 182, 108, 178, 154, 187, 72, 165, 191, 209, 154, 202, 207, 212, 65, 163, 163, 210, 142, 202, 202, 214, 75, 167, 195, 212, 167, 205, 212, 216, 21, 84, 61, 90, 61, 90, 75, 91, 84, 196, 174, 197, 174, 197, 195, 198, 61, 174, 118, 187, 137, 194, 167, 198, 90, 197, 187, 214, 194, 215, 212, 216, 61, 174, 137, 194, 118, 187, 167, 198, 90, 197, 194, 215, 187, 214, 212, 216, 75, 195, 167, 212, 167, 212, 205, 216, 91, 198, 198, 216, 198, 216, 216, 217 }; const unsigned int igraph_i_isographs_3[] = { 0, 1, 3, 5, 6, 7, 10, 11, 15, 21, 23, 25, 27, 30, 31, 63 }; const unsigned int igraph_i_isographs_3u[] = { 0, 1, 3, 7 }; const unsigned int igraph_i_isographs_4[] = { 0, 1, 3, 7, 9, 10, 11, 14, 15, 18, 19, 20, 21, 22, 23, 27, 29, 30, 31, 54, 55, 63, 73, 75, 76, 77, 79, 81, 83, 84, 85, 86, 87, 90, 91, 92, 93, 94, 95, 98, 99, 100, 101, 102, 103, 106, 107, 108, 109, 110, 111, 115, 116, 117, 118, 119, 122, 123, 124, 125, 126, 127, 219, 220, 221, 223, 228, 229, 230, 231, 237, 238, 239, 246, 247, 255, 292, 293, 295, 301, 302, 303, 310, 311, 319, 365, 367, 373, 375, 382, 383, 511, 585, 587, 591, 593, 594, 595, 596, 597, 598, 599, 601, 602, 603, 604, 605, 606, 607, 625, 626, 627, 630, 631, 633, 634, 635, 638, 639, 659, 660, 661, 663, 666, 667, 669, 670, 671, 674, 675, 678, 679, 683, 686, 687, 694, 695, 703, 729, 731, 732, 733, 735, 737, 739, 741, 742, 743, 745, 746, 747, 748, 749, 750, 751, 753, 755, 756, 757, 758, 759, 761, 762, 763, 764, 765, 766, 767, 819, 822, 823, 826, 827, 830, 831, 875, 876, 877, 879, 883, 885, 886, 887, 891, 892, 893, 894, 895, 947, 949, 951, 955, 957, 958, 959, 1019, 1020, 1021, 1023, 1755, 1757, 1758, 1759, 1782, 1783, 1791, 1883, 1887, 1907, 1911, 1917, 1918, 1919, 2029, 2031, 2039, 2047, 4095 }; const unsigned int igraph_i_isographs_4u[] = { 0, 1, 3, 7, 11, 12, 13, 15, 30, 31, 63 }; const unsigned int igraph_i_classedges_3[] = { 1, 2, 0, 2, 2, 1, 0, 1, 2, 0, 1, 0 }; const unsigned int igraph_i_classedges_3u[] = { 1, 2, 0, 2, 0, 1 }; const unsigned int igraph_i_classedges_4[] = { 2, 3, 1, 3, 0, 3, 3, 2, 1, 2, 0, 2, 3, 1, 2, 1, 0, 1, 3, 0, 2, 0, 1, 0 }; const unsigned int igraph_i_classedges_4u[] = { 2, 3, 1, 3, 0, 3, 1, 2, 0, 2, 0, 1 }; /** * \section about_graph_isomorphism * * igraph provides four set of functions to deal with graph * isomorphism problems. * * The \ref igraph_isomorphic() and \ref igraph_subisomorphic() * functions make up the first set (in addition with the \ref * igraph_permute_vertices() function). These functions choose the * algorithm which is best for the supplied input graph. (The choice is * not very sophisticated though, see their documentation for * details.) * * The VF2 graph (and subgraph) isomorphism algorithm is implemented in * igraph, these functions are the second set. See \ref * igraph_isomorphic_vf2() and \ref igraph_subisomorphic_vf2() for * starters. * * Functions for the BLISS algorithm constitute the third set, * see \ref igraph_isomorphic_bliss(). * * Finally, the isomorphism classes of all graphs with three and * four vertices are precomputed and stored in igraph, so for these * small graphs there is a very simple fast way to decide isomorphism. * See \ref igraph_isomorphic_34(). * */ /** * \function igraph_isoclass * \brief Determine the isomorphism class of a graph with 3 or 4 vertices * * * All graphs with a given number of vertices belong to a number of * isomorphism classes, with every graph in a given class being * isomorphic to each other. * * * This function gives the isomorphism class (a number) of a * graph. Two graphs have the same isomorphism class if and only if * they are isomorphic. * * * The first isomorphism class is numbered zero and it is the empty * graph, the last isomorphism class is the full graph. The number of * isomorphism class for directed graphs with three vertices is 16 * (between 0 and 15), for undirected graph it is only 4. For graphs * with four vertices it is 218 (directed) and 11 (undirected). * * \param graph The graph object. * \param isoclass Pointer to an integer, the isomorphism class will * be stored here. * \return Error code. * \sa \ref igraph_isomorphic(), \ref igraph_isoclass_subgraph(), * \ref igraph_isoclass_create(), \ref igraph_motifs_randesu(). * * Because of some limitations this function works only for graphs * with three of four vertices. * * * Time complexity: O(|E|), the number of edges in the graph. */ int igraph_isoclass(const igraph_t *graph, igraph_integer_t *isoclass) { long int e; long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_integer_t from, to; unsigned char idx, mul; const unsigned int *arr_idx, *arr_code; int code = 0; if (no_of_nodes < 3 || no_of_nodes > 4) { IGRAPH_ERROR("Only implemented for graphs with 3 or 4 vertices", IGRAPH_UNIMPLEMENTED); } if (igraph_is_directed(graph)) { if (no_of_nodes == 3) { arr_idx = igraph_i_isoclass_3_idx; arr_code = igraph_i_isoclass2_3; mul = 3; } else { arr_idx = igraph_i_isoclass_4_idx; arr_code = igraph_i_isoclass2_4; mul = 4; } } else { if (no_of_nodes == 3) { arr_idx = igraph_i_isoclass_3u_idx; arr_code = igraph_i_isoclass2_3u; mul = 3; } else { arr_idx = igraph_i_isoclass_4u_idx; arr_code = igraph_i_isoclass2_4u; mul = 4; } } for (e = 0; e < no_of_edges; e++) { igraph_edge(graph, (igraph_integer_t) e, &from, &to); idx = (unsigned char) (mul * from + to); code |= arr_idx[idx]; } *isoclass = (igraph_integer_t) arr_code[code]; return 0; } /** * \function igraph_isomorphic * \brief Decides whether two graphs are isomorphic * * * From Wikipedia: The graph isomorphism problem or GI problem is the * graph theory problem of determining whether, given two graphs G1 * and G2, it is possible to permute (or relabel) the vertices of one * graph so that it is equal to the other. Such a permutation is * called a graph isomorphism. * * This function decides which graph isomorphism algorithm to be * used based on the input graphs. Right now it does the following: * \olist * \oli If one graph is directed and the other undirected then an * error is triggered. * \oli If the two graphs does not have the same number of vertices * and edges it returns with \c FALSE. * \oli Otherwise, if the graphs have three or four vertices then an O(1) * algorithm is used with precomputed data. * \oli Otherwise BLISS is used, see \ref igraph_isomorphic_bliss(). * \endolist * * * Please call the VF2 and BLISS functions directly if you need * something more sophisticated, e.g. you need the isomorphic mapping. * * \param graph1 The first graph. * \param graph2 The second graph. * \param iso Pointer to a logical variable, will be set to TRUE (1) * if the two graphs are isomorphic, and FALSE (0) otherwise. * \return Error code. * \sa \ref igraph_isoclass(), \ref igraph_isoclass_subgraph(), * \ref igraph_isoclass_create(). * * Time complexity: exponential. */ int igraph_isomorphic(const igraph_t *graph1, const igraph_t *graph2, igraph_bool_t *iso) { long int nodes1 = igraph_vcount(graph1), nodes2 = igraph_vcount(graph2); long int edges1 = igraph_ecount(graph1), edges2 = igraph_ecount(graph2); igraph_bool_t dir1 = igraph_is_directed(graph1), dir2 = igraph_is_directed(graph2); igraph_bool_t loop1, loop2; if (dir1 != dir2) { IGRAPH_ERROR("Cannot compare directed and undirected graphs", IGRAPH_EINVAL); } else if (nodes1 != nodes2 || edges1 != edges2) { *iso = 0; } else if (nodes1 == 3 || nodes1 == 4) { IGRAPH_CHECK(igraph_has_loop(graph1, &loop1)); IGRAPH_CHECK(igraph_has_loop(graph2, &loop2)); if (!loop1 && !loop2) { IGRAPH_CHECK(igraph_isomorphic_34(graph1, graph2, iso)); } else { IGRAPH_CHECK(igraph_isomorphic_bliss(graph1, graph2, NULL, NULL, iso, 0, 0, /*sh=*/ IGRAPH_BLISS_F, 0, 0)); } } else { IGRAPH_CHECK(igraph_isomorphic_bliss(graph1, graph2, NULL, NULL, iso, 0, 0, /*sh=*/ IGRAPH_BLISS_F, 0, 0)); } return 0; } /** * \function igraph_isomorphic_34 * Graph isomorphism for 3-4 vertices * * This function uses precomputed indices to decide isomorphism * problems for graphs with only 3 or 4 vertices. * \param graph1 The first input graph. * \param graph2 The second input graph. Must have the same * directedness as \p graph1. * \param iso Pointer to a boolean, the result is stored here. * \return Error code. * * Time complexity: O(1). */ int igraph_isomorphic_34(const igraph_t *graph1, const igraph_t *graph2, igraph_bool_t *iso) { igraph_integer_t class1, class2; IGRAPH_CHECK(igraph_isoclass(graph1, &class1)); IGRAPH_CHECK(igraph_isoclass(graph2, &class2)); *iso = (class1 == class2); return 0; } /** * \function igraph_isoclass_subgraph * \brief The isomorphism class of a subgraph of a graph. * * * This function is only implemented for subgraphs with three or four * vertices. * \param graph The graph object. * \param vids A vector containing the vertex ids to be considered as * a subgraph. Each vertex id should be included at most once. * \param isoclass Pointer to an integer, this will be set to the * isomorphism class. * \return Error code. * \sa \ref igraph_isoclass(), \ref igraph_isomorphic(), * \ref igraph_isoclass_create(). * * Time complexity: O((d+n)*n), d is the average degree in the network, * and n is the number of vertices in \c vids. */ int igraph_isoclass_subgraph(const igraph_t *graph, igraph_vector_t *vids, igraph_integer_t *isoclass) { int nodes = (int) igraph_vector_size(vids); igraph_bool_t directed = igraph_is_directed(graph); igraph_vector_t neis; unsigned char mul, idx; const unsigned int *arr_idx, *arr_code; int code = 0; long int i, j, s; if (nodes < 3 || nodes > 4) { IGRAPH_ERROR("Only for three- or four-vertex subgraphs", IGRAPH_UNIMPLEMENTED); } IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); if (directed) { if (nodes == 3) { arr_idx = igraph_i_isoclass_3_idx; arr_code = igraph_i_isoclass2_3; mul = 3; } else { arr_idx = igraph_i_isoclass_4_idx; arr_code = igraph_i_isoclass2_4; mul = 4; } } else { if (nodes == 3) { arr_idx = igraph_i_isoclass_3u_idx; arr_code = igraph_i_isoclass2_3u; mul = 3; } else { arr_idx = igraph_i_isoclass_4u_idx; arr_code = igraph_i_isoclass2_4u; mul = 4; } } for (i = 0; i < nodes; i++) { long int from = (long int) VECTOR(*vids)[i]; igraph_neighbors(graph, &neis, (igraph_integer_t) from, IGRAPH_OUT); s = igraph_vector_size(&neis); for (j = 0; j < s; j++) { long int nei = (long int) VECTOR(neis)[j], to; if (igraph_vector_search(vids, 0, nei, &to)) { idx = (unsigned char) (mul * i + to); code |= arr_idx[idx]; } } } *isoclass = (igraph_integer_t) arr_code[code]; igraph_vector_destroy(&neis); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_isoclass_create * \brief Creates a graph from the given isomorphism class. * * * This function is implemented only for graphs with three or four * vertices. * \param graph Pointer to an uninitialized graph object. * \param size The number of vertices to add to the graph. * \param number The isomorphism class. * \param directed Logical constant, whether to create a directed * graph. * \return Error code. * \sa \ref igraph_isoclass(), * \ref igraph_isoclass_subgraph(), * \ref igraph_isomorphic(). * * Time complexity: O(|V|+|E|), the number of vertices plus the number * of edges in the graph to create. */ int igraph_isoclass_create(igraph_t *graph, igraph_integer_t size, igraph_integer_t number, igraph_bool_t directed) { igraph_vector_t edges; const unsigned int *classedges; long int power; long int code; long int pos; if (size < 3 || size > 4) { IGRAPH_ERROR("Only for graphs with three of four vertices", IGRAPH_UNIMPLEMENTED); } IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); if (directed) { if (size == 3) { classedges = igraph_i_classedges_3; if (number < 0 || number >= (int)(sizeof(igraph_i_isographs_3) / sizeof(unsigned int))) { IGRAPH_ERROR("`number' invalid, cannot create graph", IGRAPH_EINVAL); } code = igraph_i_isographs_3[ (long int) number]; power = 32; } else { classedges = igraph_i_classedges_4; if (number < 0 || number >= (int)(sizeof(igraph_i_isographs_4) / sizeof(unsigned int))) { IGRAPH_ERROR("`number' invalid, cannot create graph", IGRAPH_EINVAL); } code = igraph_i_isographs_4[ (long int) number]; power = 2048; } } else { if (size == 3) { classedges = igraph_i_classedges_3u; if (number < 0 || number >= (int)(sizeof(igraph_i_isographs_3u) / sizeof(unsigned int))) { IGRAPH_ERROR("`number' invalid, cannot create graph", IGRAPH_EINVAL); } code = igraph_i_isographs_3u[ (long int) number]; power = 4; } else { classedges = igraph_i_classedges_4u; if (number < 0 || number >= (int)(sizeof(igraph_i_isographs_4u) / sizeof(unsigned int))) { IGRAPH_ERROR("`number' invalid, cannot create graph", IGRAPH_EINVAL); } code = igraph_i_isographs_4u[ (long int) number]; power = 32; } } pos = 0; while (code > 0) { if (code >= power) { IGRAPH_CHECK(igraph_vector_push_back(&edges, classedges[2 * pos])); IGRAPH_CHECK(igraph_vector_push_back(&edges, classedges[2 * pos + 1])); code -= power; } power /= 2; pos++; } IGRAPH_CHECK(igraph_create(graph, &edges, size, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \section about_vf2 * * * The VF2 algorithm can search for a subgraph in a larger graph, or check if two * graphs are isomorphic. See P. Foggia, C. Sansone, M. Vento, An Improved algorithm for * matching large graphs, Proc. of the 3rd IAPR-TC-15 International * Workshop on Graph-based Representations, Italy, 2001. * * * * VF2 supports both vertex and edge-colored graphs, as well as custom vertex or edge * compatibility functions. * * * * VF2 works with both directed and undirected graphs. Only simple graphs are supported. * Self-loops or multi-edges must not be present in the graphs. Currently, the VF2 * functions do not check that the input graph is simple: it is the responsibility * of the user to pass in valid input. * */ /** * \function igraph_isomorphic_function_vf2 * The generic VF2 interface * * * This function is an implementation of the VF2 isomorphism algorithm, * see P. Foggia, C. Sansone, M. Vento, An Improved algorithm for * matching large graphs, Proc. of the 3rd IAPR-TC-15 International * Workshop on Graph-based Representations, Italy, 2001. * * For using it you need to define a callback function of type * \ref igraph_isohandler_t. This function will be called whenever VF2 * finds an isomorphism between the two graphs. The mapping between * the two graphs will be also provided to this function. If the * callback returns a nonzero value then the search is continued, * otherwise it stops. The callback function must not destroy the * mapping vectors that are passed to it. * \param graph1 The first input graph. * \param graph2 The second input graph. * \param vertex_color1 An optional color vector for the first graph. If * color vectors are given for both graphs, then the isomorphism is * calculated on the colored graphs; i.e. two vertices can match * only if their color also matches. Supply a null pointer here if * your graphs are not colored. * \param vertex_color2 An optional color vector for the second graph. See * the previous argument for explanation. * \param edge_color1 An optional edge color vector for the first * graph. The matching edges in the two graphs must have matching * colors as well. Supply a null pointer here if your graphs are not * edge-colored. * \param edge_color2 The edge color vector for the second graph. * \param map12 Pointer to an initialized vector or \c NULL. If not \c * NULL and the supplied graphs are isomorphic then the permutation * taking \p graph1 to \p graph is stored here. If not \c NULL and the * graphs are not isomorphic then a zero-length vector is returned. * \param map21 This is the same as \p map12, but for the permutation * taking \p graph2 to \p graph1. * \param isohandler_fn The callback function to be called if an * isomorphism is found. See also \ref igraph_isohandler_t. * \param node_compat_fn A pointer to a function of type \ref * igraph_isocompat_t. This function will be called by the algorithm to * determine whether two nodes are compatible. * \param edge_compat_fn A pointer to a function of type \ref * igraph_isocompat_t. This function will be called by the algorithm to * determine whether two edges are compatible. * \param arg Extra argument to supply to functions \p isohandler_fn, \p * node_compat_fn and \p edge_compat_fn. * \return Error code. * * Time complexity: exponential. */ int igraph_isomorphic_function_vf2(const igraph_t *graph1, const igraph_t *graph2, const igraph_vector_int_t *vertex_color1, const igraph_vector_int_t *vertex_color2, const igraph_vector_int_t *edge_color1, const igraph_vector_int_t *edge_color2, igraph_vector_t *map12, igraph_vector_t *map21, igraph_isohandler_t *isohandler_fn, igraph_isocompat_t *node_compat_fn, igraph_isocompat_t *edge_compat_fn, void *arg) { long int no_of_nodes = igraph_vcount(graph1); long int no_of_edges = igraph_ecount(graph1); igraph_vector_t mycore_1, mycore_2, *core_1 = &mycore_1, *core_2 = &mycore_2; igraph_vector_t in_1, in_2, out_1, out_2; long int in_1_size = 0, in_2_size = 0, out_1_size = 0, out_2_size = 0; igraph_vector_t *inneis_1, *inneis_2, *outneis_1, *outneis_2; long int matched_nodes = 0; long int depth; long int cand1, cand2; long int last1, last2; igraph_stack_t path; igraph_lazy_adjlist_t inadj1, inadj2, outadj1, outadj2; igraph_vector_t indeg1, indeg2, outdeg1, outdeg2; if (igraph_is_directed(graph1) != igraph_is_directed(graph2)) { IGRAPH_ERROR("Cannot compare directed and undirected graphs", IGRAPH_EINVAL); } if ( (vertex_color1 && !vertex_color2) || (!vertex_color1 && vertex_color2) ) { IGRAPH_WARNING("Only one graph is vertex-colored, vertex colors will be ignored"); vertex_color1 = vertex_color2 = 0; } if ( (edge_color1 && !edge_color2) || (!edge_color1 && edge_color2)) { IGRAPH_WARNING("Only one graph is edge-colored, edge colors will be ignored"); edge_color1 = edge_color2 = 0; } if (no_of_nodes != igraph_vcount(graph2) || no_of_edges != igraph_ecount(graph2)) { return 0; } if (vertex_color1) { if (igraph_vector_int_size(vertex_color1) != no_of_nodes || igraph_vector_int_size(vertex_color2) != no_of_nodes) { IGRAPH_ERROR("Invalid vertex color vector length", IGRAPH_EINVAL); } } if (edge_color1) { if (igraph_vector_int_size(edge_color1) != no_of_edges || igraph_vector_int_size(edge_color2) != no_of_edges) { IGRAPH_ERROR("Invalid edge color vector length", IGRAPH_EINVAL); } } /* Check color distribution */ if (vertex_color1) { int ret = 0; igraph_vector_int_t tmp1, tmp2; IGRAPH_CHECK(igraph_vector_int_copy(&tmp1, vertex_color1)); IGRAPH_FINALLY(igraph_vector_int_destroy, &tmp1); IGRAPH_CHECK(igraph_vector_int_copy(&tmp2, vertex_color2)); IGRAPH_FINALLY(igraph_vector_int_destroy, &tmp2); igraph_vector_int_sort(&tmp1); igraph_vector_int_sort(&tmp2); ret = !igraph_vector_int_all_e(&tmp1, &tmp2); igraph_vector_int_destroy(&tmp1); igraph_vector_int_destroy(&tmp2); IGRAPH_FINALLY_CLEAN(2); if (ret) { return 0; } } /* Check edge color distribution */ if (edge_color1) { int ret = 0; igraph_vector_int_t tmp1, tmp2; IGRAPH_CHECK(igraph_vector_int_copy(&tmp1, edge_color1)); IGRAPH_FINALLY(igraph_vector_int_destroy, &tmp1); IGRAPH_CHECK(igraph_vector_int_copy(&tmp2, edge_color2)); IGRAPH_FINALLY(igraph_vector_int_destroy, &tmp2); igraph_vector_int_sort(&tmp1); igraph_vector_int_sort(&tmp2); ret = !igraph_vector_int_all_e(&tmp1, &tmp2); igraph_vector_int_destroy(&tmp1); igraph_vector_int_destroy(&tmp2); IGRAPH_FINALLY_CLEAN(2); if (ret) { return 0; } } if (map12) { core_1 = map12; IGRAPH_CHECK(igraph_vector_resize(core_1, no_of_nodes)); } else { IGRAPH_VECTOR_INIT_FINALLY(core_1, no_of_nodes); } igraph_vector_fill(core_1, -1); if (map21) { core_2 = map21; IGRAPH_CHECK(igraph_vector_resize(core_2, no_of_nodes)); igraph_vector_null(core_2); } else { IGRAPH_VECTOR_INIT_FINALLY(core_2, no_of_nodes); } igraph_vector_fill(core_2, -1); IGRAPH_VECTOR_INIT_FINALLY(&in_1, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&in_2, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&out_1, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&out_2, no_of_nodes); IGRAPH_CHECK(igraph_stack_init(&path, 0)); IGRAPH_FINALLY(igraph_stack_destroy, &path); IGRAPH_CHECK(igraph_lazy_adjlist_init(graph1, &inadj1, IGRAPH_IN, IGRAPH_SIMPLIFY)); IGRAPH_FINALLY(igraph_lazy_adjlist_destroy, &inadj1); IGRAPH_CHECK(igraph_lazy_adjlist_init(graph1, &outadj1, IGRAPH_OUT, IGRAPH_SIMPLIFY)); IGRAPH_FINALLY(igraph_lazy_adjlist_destroy, &outadj1); IGRAPH_CHECK(igraph_lazy_adjlist_init(graph2, &inadj2, IGRAPH_IN, IGRAPH_SIMPLIFY)); IGRAPH_FINALLY(igraph_lazy_adjlist_destroy, &inadj2); IGRAPH_CHECK(igraph_lazy_adjlist_init(graph2, &outadj2, IGRAPH_OUT, IGRAPH_SIMPLIFY)); IGRAPH_FINALLY(igraph_lazy_adjlist_destroy, &outadj2); IGRAPH_VECTOR_INIT_FINALLY(&indeg1, 0); IGRAPH_VECTOR_INIT_FINALLY(&indeg2, 0); IGRAPH_VECTOR_INIT_FINALLY(&outdeg1, 0); IGRAPH_VECTOR_INIT_FINALLY(&outdeg2, 0); IGRAPH_CHECK(igraph_stack_reserve(&path, no_of_nodes * 2)); IGRAPH_CHECK(igraph_degree(graph1, &indeg1, igraph_vss_all(), IGRAPH_IN, IGRAPH_LOOPS)); IGRAPH_CHECK(igraph_degree(graph2, &indeg2, igraph_vss_all(), IGRAPH_IN, IGRAPH_LOOPS)); IGRAPH_CHECK(igraph_degree(graph1, &outdeg1, igraph_vss_all(), IGRAPH_OUT, IGRAPH_LOOPS)); IGRAPH_CHECK(igraph_degree(graph2, &outdeg2, igraph_vss_all(), IGRAPH_OUT, IGRAPH_LOOPS)); depth = 0; last1 = -1; last2 = -1; while (depth >= 0) { long int i; IGRAPH_ALLOW_INTERRUPTION(); cand1 = -1; cand2 = -1; /* Search for the next pair to try */ if ((in_1_size != in_2_size) || (out_1_size != out_2_size)) { /* step back, nothing to do */ } else if (out_1_size > 0 && out_2_size > 0) { /**************************************************************/ /* cand2, search not always needed */ if (last2 >= 0) { cand2 = last2; } else { i = 0; while (cand2 < 0 && i < no_of_nodes) { if (VECTOR(out_2)[i] > 0 && VECTOR(*core_2)[i] < 0) { cand2 = i; } i++; } } /* search for cand1 now, it should be bigger than last1 */ i = last1 + 1; while (cand1 < 0 && i < no_of_nodes) { if (VECTOR(out_1)[i] > 0 && VECTOR(*core_1)[i] < 0) { cand1 = i; } i++; } } else if (in_1_size > 0 && in_2_size > 0) { /**************************************************************/ /* cand2, search not always needed */ if (last2 >= 0) { cand2 = last2; } else { i = 0; while (cand2 < 0 && i < no_of_nodes) { if (VECTOR(in_2)[i] > 0 && VECTOR(*core_2)[i] < 0) { cand2 = i; } i++; } } /* search for cand1 now, should be bigger than last1 */ i = last1 + 1; while (cand1 < 0 && i < no_of_nodes) { if (VECTOR(in_1)[i] > 0 && VECTOR(*core_1)[i] < 0) { cand1 = i; } i++; } } else { /**************************************************************/ /* cand2, search not always needed */ if (last2 >= 0) { cand2 = last2; } else { i = 0; while (cand2 < 0 && i < no_of_nodes) { if (VECTOR(*core_2)[i] < 0) { cand2 = i; } i++; } } /* search for cand1, should be bigger than last1 */ i = last1 + 1; while (cand1 < 0 && i < no_of_nodes) { if (VECTOR(*core_1)[i] < 0) { cand1 = i; } i++; } } /* Ok, we have cand1, cand2 as candidates. Or not? */ if (cand1 < 0 || cand2 < 0) { /**************************************************************/ /* dead end, step back, if possible. Otherwise we'll terminate */ if (depth >= 1) { last2 = (long int) igraph_stack_pop(&path); last1 = (long int) igraph_stack_pop(&path); matched_nodes -= 1; VECTOR(*core_1)[last1] = -1; VECTOR(*core_2)[last2] = -1; if (VECTOR(in_1)[last1] != 0) { in_1_size += 1; } if (VECTOR(out_1)[last1] != 0) { out_1_size += 1; } if (VECTOR(in_2)[last2] != 0) { in_2_size += 1; } if (VECTOR(out_2)[last2] != 0) { out_2_size += 1; } inneis_1 = igraph_lazy_adjlist_get(&inadj1, (igraph_integer_t) last1); for (i = 0; i < igraph_vector_size(inneis_1); i++) { long int node = (long int) VECTOR(*inneis_1)[i]; if (VECTOR(in_1)[node] == depth) { VECTOR(in_1)[node] = 0; in_1_size -= 1; } } outneis_1 = igraph_lazy_adjlist_get(&outadj1, (igraph_integer_t) last1); for (i = 0; i < igraph_vector_size(outneis_1); i++) { long int node = (long int) VECTOR(*outneis_1)[i]; if (VECTOR(out_1)[node] == depth) { VECTOR(out_1)[node] = 0; out_1_size -= 1; } } inneis_2 = igraph_lazy_adjlist_get(&inadj2, (igraph_integer_t) last2); for (i = 0; i < igraph_vector_size(inneis_2); i++) { long int node = (long int) VECTOR(*inneis_2)[i]; if (VECTOR(in_2)[node] == depth) { VECTOR(in_2)[node] = 0; in_2_size -= 1; } } outneis_2 = igraph_lazy_adjlist_get(&outadj2, (igraph_integer_t) last2); for (i = 0; i < igraph_vector_size(outneis_2); i++) { long int node = (long int) VECTOR(*outneis_2)[i]; if (VECTOR(out_2)[node] == depth) { VECTOR(out_2)[node] = 0; out_2_size -= 1; } } } /* end of stepping back */ depth -= 1; } else { /**************************************************************/ /* step forward if worth, check if worth first */ long int xin1 = 0, xin2 = 0, xout1 = 0, xout2 = 0; igraph_bool_t end = 0; inneis_1 = igraph_lazy_adjlist_get(&inadj1, (igraph_integer_t) cand1); outneis_1 = igraph_lazy_adjlist_get(&outadj1, (igraph_integer_t) cand1); inneis_2 = igraph_lazy_adjlist_get(&inadj2, (igraph_integer_t) cand2); outneis_2 = igraph_lazy_adjlist_get(&outadj2, (igraph_integer_t) cand2); if (VECTOR(indeg1)[cand1] != VECTOR(indeg2)[cand2] || VECTOR(outdeg1)[cand1] != VECTOR(outdeg2)[cand2]) { end = 1; } if (vertex_color1 && VECTOR(*vertex_color1)[cand1] != VECTOR(*vertex_color2)[cand2]) { end = 1; } if (node_compat_fn && !node_compat_fn(graph1, graph2, (igraph_integer_t) cand1, (igraph_integer_t) cand2, arg)) { end = 1; } for (i = 0; !end && i < igraph_vector_size(inneis_1); i++) { long int node = (long int) VECTOR(*inneis_1)[i]; if (VECTOR(*core_1)[node] >= 0) { long int node2 = (long int) VECTOR(*core_1)[node]; /* check if there is a node2->cand2 edge */ if (!igraph_vector_binsearch2(inneis_2, node2)) { end = 1; } else if (edge_color1 || edge_compat_fn) { igraph_integer_t eid1, eid2; igraph_get_eid(graph1, &eid1, (igraph_integer_t) node, (igraph_integer_t) cand1, /*directed=*/ 1, /*error=*/ 1); igraph_get_eid(graph2, &eid2, (igraph_integer_t) node2, (igraph_integer_t) cand2, /*directed=*/ 1, /*error=*/ 1); if (edge_color1 && VECTOR(*edge_color1)[(long int)eid1] != VECTOR(*edge_color2)[(long int)eid2]) { end = 1; } if (edge_compat_fn && !edge_compat_fn(graph1, graph2, eid1, eid2, arg)) { end = 1; } } } else { if (VECTOR(in_1)[node] != 0) { xin1++; } if (VECTOR(out_1)[node] != 0) { xout1++; } } } for (i = 0; !end && i < igraph_vector_size(outneis_1); i++) { long int node = (long int) VECTOR(*outneis_1)[i]; if (VECTOR(*core_1)[node] >= 0) { long int node2 = (long int) VECTOR(*core_1)[node]; /* check if there is a cand2->node2 edge */ if (!igraph_vector_binsearch2(outneis_2, node2)) { end = 1; } else if (edge_color1 || edge_compat_fn) { igraph_integer_t eid1, eid2; igraph_get_eid(graph1, &eid1, (igraph_integer_t) cand1, (igraph_integer_t) node, /*directed=*/ 1, /*error=*/ 1); igraph_get_eid(graph2, &eid2, (igraph_integer_t) cand2, (igraph_integer_t) node2, /*directed=*/ 1, /*error=*/ 1); if (edge_color1 && VECTOR(*edge_color1)[(long int)eid1] != VECTOR(*edge_color2)[(long int)eid2]) { end = 1; } if (edge_compat_fn && !edge_compat_fn(graph1, graph2, eid1, eid2, arg)) { end = 1; } } } else { if (VECTOR(in_1)[node] != 0) { xin1++; } if (VECTOR(out_1)[node] != 0) { xout1++; } } } for (i = 0; !end && i < igraph_vector_size(inneis_2); i++) { long int node = (long int) VECTOR(*inneis_2)[i]; if (VECTOR(*core_2)[node] >= 0) { long int node2 = (long int) VECTOR(*core_2)[node]; /* check if there is a node2->cand1 edge */ if (!igraph_vector_binsearch2(inneis_1, node2)) { end = 1; } else if (edge_color1 || edge_compat_fn) { igraph_integer_t eid1, eid2; igraph_get_eid(graph1, &eid1, (igraph_integer_t) node2, (igraph_integer_t) cand1, /*directed=*/ 1, /*error=*/ 1); igraph_get_eid(graph2, &eid2, (igraph_integer_t) node, (igraph_integer_t) cand2, /*directed=*/ 1, /*error=*/ 1); if (edge_color1 && VECTOR(*edge_color1)[(long int)eid1] != VECTOR(*edge_color2)[(long int)eid2]) { end = 1; } if (edge_compat_fn && !edge_compat_fn(graph1, graph2, eid1, eid2, arg)) { end = 1; } } } else { if (VECTOR(in_2)[node] != 0) { xin2++; } if (VECTOR(out_2)[node] != 0) { xout2++; } } } for (i = 0; !end && i < igraph_vector_size(outneis_2); i++) { long int node = (long int) VECTOR(*outneis_2)[i]; if (VECTOR(*core_2)[node] >= 0) { long int node2 = (long int) VECTOR(*core_2)[node]; /* check if there is a cand1->node2 edge */ if (!igraph_vector_binsearch2(outneis_1, node2)) { end = 1; } else if (edge_color1 || edge_compat_fn) { igraph_integer_t eid1, eid2; igraph_get_eid(graph1, &eid1, (igraph_integer_t) cand1, (igraph_integer_t) node2, /*directed=*/ 1, /*error=*/ 1); igraph_get_eid(graph2, &eid2, (igraph_integer_t) cand2, (igraph_integer_t) node, /*directed=*/ 1, /*error=*/ 1); if (edge_color1 && VECTOR(*edge_color1)[(long int)eid1] != VECTOR(*edge_color2)[(long int)eid2]) { end = 1; } if (edge_compat_fn && !edge_compat_fn(graph1, graph2, eid1, eid2, arg)) { end = 1; } } } else { if (VECTOR(in_2)[node] != 0) { xin2++; } if (VECTOR(out_2)[node] != 0) { xout2++; } } } if (!end && (xin1 == xin2 && xout1 == xout2)) { /* Ok, we add the (cand1, cand2) pair to the mapping */ depth += 1; IGRAPH_CHECK(igraph_stack_push(&path, cand1)); IGRAPH_CHECK(igraph_stack_push(&path, cand2)); matched_nodes += 1; VECTOR(*core_1)[cand1] = cand2; VECTOR(*core_2)[cand2] = cand1; /* update in_*, out_* */ if (VECTOR(in_1)[cand1] != 0) { in_1_size -= 1; } if (VECTOR(out_1)[cand1] != 0) { out_1_size -= 1; } if (VECTOR(in_2)[cand2] != 0) { in_2_size -= 1; } if (VECTOR(out_2)[cand2] != 0) { out_2_size -= 1; } inneis_1 = igraph_lazy_adjlist_get(&inadj1, (igraph_integer_t) cand1); for (i = 0; i < igraph_vector_size(inneis_1); i++) { long int node = (long int) VECTOR(*inneis_1)[i]; if (VECTOR(in_1)[node] == 0 && VECTOR(*core_1)[node] < 0) { VECTOR(in_1)[node] = depth; in_1_size += 1; } } outneis_1 = igraph_lazy_adjlist_get(&outadj1, (igraph_integer_t) cand1); for (i = 0; i < igraph_vector_size(outneis_1); i++) { long int node = (long int) VECTOR(*outneis_1)[i]; if (VECTOR(out_1)[node] == 0 && VECTOR(*core_1)[node] < 0) { VECTOR(out_1)[node] = depth; out_1_size += 1; } } inneis_2 = igraph_lazy_adjlist_get(&inadj2, (igraph_integer_t) cand2); for (i = 0; i < igraph_vector_size(inneis_2); i++) { long int node = (long int) VECTOR(*inneis_2)[i]; if (VECTOR(in_2)[node] == 0 && VECTOR(*core_2)[node] < 0) { VECTOR(in_2)[node] = depth; in_2_size += 1; } } outneis_2 = igraph_lazy_adjlist_get(&outadj2, (igraph_integer_t) cand2); for (i = 0; i < igraph_vector_size(outneis_2); i++) { long int node = (long int) VECTOR(*outneis_2)[i]; if (VECTOR(out_2)[node] == 0 && VECTOR(*core_2)[node] < 0) { VECTOR(out_2)[node] = depth; out_2_size += 1; } } last1 = -1; last2 = -1; /* this the first time here */ } else { last1 = cand1; last2 = cand2; } } if (matched_nodes == no_of_nodes && isohandler_fn) { if (!isohandler_fn(core_1, core_2, arg)) { break; } } } igraph_vector_destroy(&outdeg2); igraph_vector_destroy(&outdeg1); igraph_vector_destroy(&indeg2); igraph_vector_destroy(&indeg1); igraph_lazy_adjlist_destroy(&outadj2); igraph_lazy_adjlist_destroy(&inadj2); igraph_lazy_adjlist_destroy(&outadj1); igraph_lazy_adjlist_destroy(&inadj1); igraph_stack_destroy(&path); igraph_vector_destroy(&out_2); igraph_vector_destroy(&out_1); igraph_vector_destroy(&in_2); igraph_vector_destroy(&in_1); IGRAPH_FINALLY_CLEAN(13); if (!map21) { igraph_vector_destroy(core_2); IGRAPH_FINALLY_CLEAN(1); } if (!map12) { igraph_vector_destroy(core_1); IGRAPH_FINALLY_CLEAN(1); } return 0; } typedef struct { igraph_isocompat_t *node_compat_fn, *edge_compat_fn; void *arg, *carg; } igraph_i_iso_cb_data_t; igraph_bool_t igraph_i_isocompat_node_cb(const igraph_t *graph1, const igraph_t *graph2, const igraph_integer_t g1_num, const igraph_integer_t g2_num, void *arg) { igraph_i_iso_cb_data_t *data = arg; return data->node_compat_fn(graph1, graph2, g1_num, g2_num, data->carg); } igraph_bool_t igraph_i_isocompat_edge_cb(const igraph_t *graph1, const igraph_t *graph2, const igraph_integer_t g1_num, const igraph_integer_t g2_num, void *arg) { igraph_i_iso_cb_data_t *data = arg; return data->edge_compat_fn(graph1, graph2, g1_num, g2_num, data->carg); } igraph_bool_t igraph_i_isomorphic_vf2(igraph_vector_t *map12, igraph_vector_t *map21, void *arg) { igraph_i_iso_cb_data_t *data = arg; igraph_bool_t *iso = data->arg; IGRAPH_UNUSED(map12); IGRAPH_UNUSED(map21); *iso = 1; return 0; /* don't need to continue */ } /** * \function igraph_isomorphic_vf2 * \brief Isomorphism via VF2 * * * This function performs the VF2 algorithm via calling \ref * igraph_isomorphic_function_vf2(). * * Note that this function cannot be used for * deciding subgraph isomorphism, use \ref igraph_subisomorphic_vf2() * for that. * \param graph1 The first graph, may be directed or undirected. * \param graph2 The second graph. It must have the same directedness * as \p graph1, otherwise an error is reported. * \param vertex_color1 An optional color vector for the first graph. If * color vectors are given for both graphs, then the isomorphism is * calculated on the colored graphs; i.e. two vertices can match * only if their color also matches. Supply a null pointer here if * your graphs are not colored. * \param vertex_color2 An optional color vector for the second graph. See * the previous argument for explanation. * \param edge_color1 An optional edge color vector for the first * graph. The matching edges in the two graphs must have matching * colors as well. Supply a null pointer here if your graphs are not * edge-colored. * \param edge_color2 The edge color vector for the second graph. * \param iso Pointer to a logical constant, the result of the * algorithm will be placed here. * \param map12 Pointer to an initialized vector or a NULL pointer. If not * a NULL pointer then the mapping from \p graph1 to \p graph2 is * stored here. If the graphs are not isomorphic then the vector is * cleared (ie. has zero elements). * \param map21 Pointer to an initialized vector or a NULL pointer. If not * a NULL pointer then the mapping from \p graph2 to \p graph1 is * stored here. If the graphs are not isomorphic then the vector is * cleared (ie. has zero elements). * \param node_compat_fn A pointer to a function of type \ref * igraph_isocompat_t. This function will be called by the algorithm to * determine whether two nodes are compatible. * \param edge_compat_fn A pointer to a function of type \ref * igraph_isocompat_t. This function will be called by the algorithm to * determine whether two edges are compatible. * \param arg Extra argument to supply to functions \p node_compat_fn * and \p edge_compat_fn. * \return Error code. * * \sa \ref igraph_subisomorphic_vf2(), * \ref igraph_count_isomorphisms_vf2(), * \ref igraph_get_isomorphisms_vf2(), * * Time complexity: exponential, what did you expect? * * \example examples/simple/igraph_isomorphic_vf2.c */ int igraph_isomorphic_vf2(const igraph_t *graph1, const igraph_t *graph2, const igraph_vector_int_t *vertex_color1, const igraph_vector_int_t *vertex_color2, const igraph_vector_int_t *edge_color1, const igraph_vector_int_t *edge_color2, igraph_bool_t *iso, igraph_vector_t *map12, igraph_vector_t *map21, igraph_isocompat_t *node_compat_fn, igraph_isocompat_t *edge_compat_fn, void *arg) { igraph_i_iso_cb_data_t data = { node_compat_fn, edge_compat_fn, iso, arg }; igraph_isocompat_t *ncb = node_compat_fn ? igraph_i_isocompat_node_cb : 0; igraph_isocompat_t *ecb = edge_compat_fn ? igraph_i_isocompat_edge_cb : 0; *iso = 0; IGRAPH_CHECK(igraph_isomorphic_function_vf2(graph1, graph2, vertex_color1, vertex_color2, edge_color1, edge_color2, map12, map21, (igraph_isohandler_t*) igraph_i_isomorphic_vf2, ncb, ecb, &data)); if (! *iso) { if (map12) { igraph_vector_clear(map12); } if (map21) { igraph_vector_clear(map21); } } return 0; } igraph_bool_t igraph_i_count_isomorphisms_vf2(const igraph_vector_t *map12, const igraph_vector_t *map21, void *arg) { igraph_i_iso_cb_data_t *data = arg; igraph_integer_t *count = data->arg; IGRAPH_UNUSED(map12); IGRAPH_UNUSED(map21); *count += 1; return 1; /* always continue */ } /** * \function igraph_count_isomorphisms_vf2 * Number of isomorphisms via VF2 * * This function counts the number of isomorphic mappings between two * graphs. It uses the generic \ref igraph_isomorphic_function_vf2() * function. * \param graph1 The first input graph, may be directed or undirected. * \param graph2 The second input graph, it must have the same * directedness as \p graph1, or an error will be reported. * \param vertex_color1 An optional color vector for the first graph. If * color vectors are given for both graphs, then the isomorphism is * calculated on the colored graphs; i.e. two vertices can match * only if their color also matches. Supply a null pointer here if * your graphs are not colored. * \param vertex_color2 An optional color vector for the second graph. See * the previous argument for explanation. * \param edge_color1 An optional edge color vector for the first * graph. The matching edges in the two graphs must have matching * colors as well. Supply a null pointer here if your graphs are not * edge-colored. * \param edge_color2 The edge color vector for the second graph. * \param count Point to an integer, the result will be stored here. * \param node_compat_fn A pointer to a function of type \ref * igraph_isocompat_t. This function will be called by the algorithm to * determine whether two nodes are compatible. * \param edge_compat_fn A pointer to a function of type \ref * igraph_isocompat_t. This function will be called by the algorithm to * determine whether two edges are compatible. * \param arg Extra argument to supply to functions \p node_compat_fn and * \p edge_compat_fn. * \return Error code. * * Time complexity: exponential. */ int igraph_count_isomorphisms_vf2(const igraph_t *graph1, const igraph_t *graph2, const igraph_vector_int_t *vertex_color1, const igraph_vector_int_t *vertex_color2, const igraph_vector_int_t *edge_color1, const igraph_vector_int_t *edge_color2, igraph_integer_t *count, igraph_isocompat_t *node_compat_fn, igraph_isocompat_t *edge_compat_fn, void *arg) { igraph_i_iso_cb_data_t data = { node_compat_fn, edge_compat_fn, count, arg }; igraph_isocompat_t *ncb = node_compat_fn ? igraph_i_isocompat_node_cb : 0; igraph_isocompat_t *ecb = edge_compat_fn ? igraph_i_isocompat_edge_cb : 0; *count = 0; IGRAPH_CHECK(igraph_isomorphic_function_vf2(graph1, graph2, vertex_color1, vertex_color2, edge_color1, edge_color2, 0, 0, (igraph_isohandler_t*) igraph_i_count_isomorphisms_vf2, ncb, ecb, &data)); return 0; } void igraph_i_get_isomorphisms_free(igraph_vector_ptr_t *data) { long int i, n = igraph_vector_ptr_size(data); for (i = 0; i < n; i++) { igraph_vector_t *vec = VECTOR(*data)[i]; igraph_vector_destroy(vec); igraph_free(vec); } } igraph_bool_t igraph_i_get_isomorphisms_vf2(const igraph_vector_t *map12, const igraph_vector_t *map21, void *arg) { igraph_i_iso_cb_data_t *data = arg; igraph_vector_ptr_t *ptrvector = data->arg; igraph_vector_t *newvector = igraph_Calloc(1, igraph_vector_t); IGRAPH_UNUSED(map12); if (!newvector) { igraph_error("Out of memory", __FILE__, __LINE__, IGRAPH_ENOMEM); return 0; /* stop right here */ } IGRAPH_FINALLY(igraph_free, newvector); IGRAPH_CHECK(igraph_vector_copy(newvector, map21)); IGRAPH_FINALLY(igraph_vector_destroy, newvector); IGRAPH_CHECK(igraph_vector_ptr_push_back(ptrvector, newvector)); IGRAPH_FINALLY_CLEAN(2); return 1; /* continue finding subisomorphisms */ } /** * \function igraph_get_isomorphisms_vf2 * Collect the isomorphic mappings * * This function finds all the isomorphic mappings between two * graphs. It uses the \ref igraph_isomorphic_function_vf2() * function. Call the function with the same graph as \p graph1 and \p * graph2 to get automorphisms. * \param graph1 The first input graph, may be directed or undirected. * \param graph2 The second input graph, it must have the same * directedness as \p graph1, or an error will be reported. * \param vertex_color1 An optional color vector for the first graph. If * color vectors are given for both graphs, then the isomorphism is * calculated on the colored graphs; i.e. two vertices can match * only if their color also matches. Supply a null pointer here if * your graphs are not colored. * \param vertex_color2 An optional color vector for the second graph. See * the previous argument for explanation. * \param edge_color1 An optional edge color vector for the first * graph. The matching edges in the two graphs must have matching * colors as well. Supply a null pointer here if your graphs are not * edge-colored. * \param edge_color2 The edge color vector for the second graph. * \param maps Pointer vector. On return it is empty if the input graphs * are no isomorphic. Otherwise it contains pointers to * igraph_vector_t objects, each vector is an * isomorphic mapping of \p graph2 to \p graph1. Please note that * you need to 1) Destroy the vectors via \ref * igraph_vector_destroy(), 2) free them via * free() and then 3) call \ref * igraph_vector_ptr_destroy() on the pointer vector to deallocate all * memory when \p maps is no longer needed. * \param node_compat_fn A pointer to a function of type \ref * igraph_isocompat_t. This function will be called by the algorithm to * determine whether two nodes are compatible. * \param edge_compat_fn A pointer to a function of type \ref * igraph_isocompat_t. This function will be called by the algorithm to * determine whether two edges are compatible. * \param arg Extra argument to supply to functions \p node_compat_fn * and \p edge_compat_fn. * \return Error code. * * Time complexity: exponential. */ int igraph_get_isomorphisms_vf2(const igraph_t *graph1, const igraph_t *graph2, const igraph_vector_int_t *vertex_color1, const igraph_vector_int_t *vertex_color2, const igraph_vector_int_t *edge_color1, const igraph_vector_int_t *edge_color2, igraph_vector_ptr_t *maps, igraph_isocompat_t *node_compat_fn, igraph_isocompat_t *edge_compat_fn, void *arg) { igraph_i_iso_cb_data_t data = { node_compat_fn, edge_compat_fn, maps, arg }; igraph_isocompat_t *ncb = node_compat_fn ? igraph_i_isocompat_node_cb : 0; igraph_isocompat_t *ecb = edge_compat_fn ? igraph_i_isocompat_edge_cb : 0; igraph_vector_ptr_clear(maps); IGRAPH_FINALLY(igraph_i_get_isomorphisms_free, maps); IGRAPH_CHECK(igraph_isomorphic_function_vf2(graph1, graph2, vertex_color1, vertex_color2, edge_color1, edge_color2, 0, 0, (igraph_isohandler_t*) igraph_i_get_isomorphisms_vf2, ncb, ecb, &data)); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_subisomorphic * Decide subgraph isomorphism * * Check whether \p graph2 is isomorphic to a subgraph of \p graph1. * Currently this function just calls \ref igraph_subisomorphic_vf2() * for all graphs. * \param graph1 The first input graph, may be directed or * undirected. This is supposed to be the bigger graph. * \param graph2 The second input graph, it must have the same * directedness as \p graph2, or an error is triggered. This is * supposed to be the smaller graph. * \param iso Pointer to a boolean, the result is stored here. * \return Error code. * * Time complexity: exponential. */ int igraph_subisomorphic(const igraph_t *graph1, const igraph_t *graph2, igraph_bool_t *iso) { return igraph_subisomorphic_vf2(graph1, graph2, 0, 0, 0, 0, iso, 0, 0, 0, 0, 0); } /** * \function igraph_subisomorphic_function_vf2 * Generic VF2 function for subgraph isomorphism problems * * This function is the pair of \ref igraph_isomorphic_function_vf2(), * for subgraph isomorphism problems. It searches for subgraphs of \p * graph1 which are isomorphic to \p graph2. When it founds an * isomorphic mapping it calls the supplied callback \p isohandler_fn. * The mapping (and its inverse) and the additional \p arg argument * are supplied to the callback. * \param graph1 The first input graph, may be directed or * undirected. This is supposed to be the larger graph. * \param graph2 The second input graph, it must have the same * directedness as \p graph1. This is supposed to be the smaller * graph. * \param vertex_color1 An optional color vector for the first graph. If * color vectors are given for both graphs, then the subgraph isomorphism is * calculated on the colored graphs; i.e. two vertices can match * only if their color also matches. Supply a null pointer here if * your graphs are not colored. * \param vertex_color2 An optional color vector for the second graph. See * the previous argument for explanation. * \param edge_color1 An optional edge color vector for the first * graph. The matching edges in the two graphs must have matching * colors as well. Supply a null pointer here if your graphs are not * edge-colored. * \param edge_color2 The edge color vector for the second graph. * \param map12 Pointer to a vector or \c NULL. If not \c NULL, then an * isomorphic mapping from \p graph1 to \p graph2 is stored here. * \param map21 Pointer to a vector ot \c NULL. If not \c NULL, then * an isomorphic mapping from \p graph2 to \p graph1 is stored * here. * \param isohandler_fn A pointer to a function of type \ref * igraph_isohandler_t. This will be called whenever a subgraph * isomorphism is found. If the function returns with a non-zero value * then the search is continued, otherwise it stops and the function * returns. * \param node_compat_fn A pointer to a function of type \ref * igraph_isocompat_t. This function will be called by the algorithm to * determine whether two nodes are compatible. * \param edge_compat_fn A pointer to a function of type \ref * igraph_isocompat_t. This function will be called by the algorithm to * determine whether two edges are compatible. * \param arg Extra argument to supply to functions \p isohandler_fn, \p * node_compat_fn and \p edge_compat_fn. * \return Error code. * * Time complexity: exponential. */ int igraph_subisomorphic_function_vf2(const igraph_t *graph1, const igraph_t *graph2, const igraph_vector_int_t *vertex_color1, const igraph_vector_int_t *vertex_color2, const igraph_vector_int_t *edge_color1, const igraph_vector_int_t *edge_color2, igraph_vector_t *map12, igraph_vector_t *map21, igraph_isohandler_t *isohandler_fn, igraph_isocompat_t *node_compat_fn, igraph_isocompat_t *edge_compat_fn, void *arg) { long int no_of_nodes1 = igraph_vcount(graph1), no_of_nodes2 = igraph_vcount(graph2); long int no_of_edges1 = igraph_ecount(graph1), no_of_edges2 = igraph_ecount(graph2); igraph_vector_t mycore_1, mycore_2, *core_1 = &mycore_1, *core_2 = &mycore_2; igraph_vector_t in_1, in_2, out_1, out_2; long int in_1_size = 0, in_2_size = 0, out_1_size = 0, out_2_size = 0; igraph_vector_t *inneis_1, *inneis_2, *outneis_1, *outneis_2; long int matched_nodes = 0; long int depth; long int cand1, cand2; long int last1, last2; igraph_stack_t path; igraph_lazy_adjlist_t inadj1, inadj2, outadj1, outadj2; igraph_vector_t indeg1, indeg2, outdeg1, outdeg2; if (igraph_is_directed(graph1) != igraph_is_directed(graph2)) { IGRAPH_ERROR("Cannot compare directed and undirected graphs", IGRAPH_EINVAL); } if (no_of_nodes1 < no_of_nodes2 || no_of_edges1 < no_of_edges2) { return 0; } if ( (vertex_color1 && !vertex_color2) || (!vertex_color1 && vertex_color2) ) { IGRAPH_WARNING("Only one graph is vertex colored, colors will be ignored"); vertex_color1 = vertex_color2 = 0; } if ( (edge_color1 && !edge_color2) || (!edge_color1 && edge_color2) ) { IGRAPH_WARNING("Only one graph is edge colored, colors will be ignored"); edge_color1 = edge_color2 = 0; } if (vertex_color1) { if (igraph_vector_int_size(vertex_color1) != no_of_nodes1 || igraph_vector_int_size(vertex_color2) != no_of_nodes2) { IGRAPH_ERROR("Invalid vertex color vector length", IGRAPH_EINVAL); } } if (edge_color1) { if (igraph_vector_int_size(edge_color1) != no_of_edges1 || igraph_vector_int_size(edge_color2) != no_of_edges2) { IGRAPH_ERROR("Invalid edge color vector length", IGRAPH_EINVAL); } } /* Check color distribution */ if (vertex_color1) { /* TODO */ } /* Check edge color distribution */ if (edge_color1) { /* TODO */ } if (map12) { core_1 = map12; IGRAPH_CHECK(igraph_vector_resize(core_1, no_of_nodes1)); } else { IGRAPH_VECTOR_INIT_FINALLY(core_1, no_of_nodes1); } igraph_vector_fill(core_1, -1); if (map21) { core_2 = map21; IGRAPH_CHECK(igraph_vector_resize(core_2, no_of_nodes2)); } else { IGRAPH_VECTOR_INIT_FINALLY(core_2, no_of_nodes2); } igraph_vector_fill(core_2, -1); IGRAPH_VECTOR_INIT_FINALLY(&in_1, no_of_nodes1); IGRAPH_VECTOR_INIT_FINALLY(&in_2, no_of_nodes2); IGRAPH_VECTOR_INIT_FINALLY(&out_1, no_of_nodes1); IGRAPH_VECTOR_INIT_FINALLY(&out_2, no_of_nodes2); IGRAPH_CHECK(igraph_stack_init(&path, 0)); IGRAPH_FINALLY(igraph_stack_destroy, &path); IGRAPH_CHECK(igraph_lazy_adjlist_init(graph1, &inadj1, IGRAPH_IN, IGRAPH_SIMPLIFY)); IGRAPH_FINALLY(igraph_lazy_adjlist_destroy, &inadj1); IGRAPH_CHECK(igraph_lazy_adjlist_init(graph1, &outadj1, IGRAPH_OUT, IGRAPH_SIMPLIFY)); IGRAPH_FINALLY(igraph_lazy_adjlist_destroy, &outadj1); IGRAPH_CHECK(igraph_lazy_adjlist_init(graph2, &inadj2, IGRAPH_IN, IGRAPH_SIMPLIFY)); IGRAPH_FINALLY(igraph_lazy_adjlist_destroy, &inadj2); IGRAPH_CHECK(igraph_lazy_adjlist_init(graph2, &outadj2, IGRAPH_OUT, IGRAPH_SIMPLIFY)); IGRAPH_FINALLY(igraph_lazy_adjlist_destroy, &outadj2); IGRAPH_VECTOR_INIT_FINALLY(&indeg1, 0); IGRAPH_VECTOR_INIT_FINALLY(&indeg2, 0); IGRAPH_VECTOR_INIT_FINALLY(&outdeg1, 0); IGRAPH_VECTOR_INIT_FINALLY(&outdeg2, 0); IGRAPH_CHECK(igraph_stack_reserve(&path, no_of_nodes2 * 2)); IGRAPH_CHECK(igraph_degree(graph1, &indeg1, igraph_vss_all(), IGRAPH_IN, IGRAPH_LOOPS)); IGRAPH_CHECK(igraph_degree(graph2, &indeg2, igraph_vss_all(), IGRAPH_IN, IGRAPH_LOOPS)); IGRAPH_CHECK(igraph_degree(graph1, &outdeg1, igraph_vss_all(), IGRAPH_OUT, IGRAPH_LOOPS)); IGRAPH_CHECK(igraph_degree(graph2, &outdeg2, igraph_vss_all(), IGRAPH_OUT, IGRAPH_LOOPS)); depth = 0; last1 = -1; last2 = -1; while (depth >= 0) { long int i; IGRAPH_ALLOW_INTERRUPTION(); cand1 = -1; cand2 = -1; /* Search for the next pair to try */ if ((in_1_size < in_2_size) || (out_1_size < out_2_size)) { /* step back, nothing to do */ } else if (out_1_size > 0 && out_2_size > 0) { /**************************************************************/ /* cand2, search not always needed */ if (last2 >= 0) { cand2 = last2; } else { i = 0; while (cand2 < 0 && i < no_of_nodes2) { if (VECTOR(out_2)[i] > 0 && VECTOR(*core_2)[i] < 0) { cand2 = i; } i++; } } /* search for cand1 now, it should be bigger than last1 */ i = last1 + 1; while (cand1 < 0 && i < no_of_nodes1) { if (VECTOR(out_1)[i] > 0 && VECTOR(*core_1)[i] < 0) { cand1 = i; } i++; } } else if (in_1_size > 0 && in_2_size > 0) { /**************************************************************/ /* cand2, search not always needed */ if (last2 >= 0) { cand2 = last2; } else { i = 0; while (cand2 < 0 && i < no_of_nodes2) { if (VECTOR(in_2)[i] > 0 && VECTOR(*core_2)[i] < 0) { cand2 = i; } i++; } } /* search for cand1 now, should be bigger than last1 */ i = last1 + 1; while (cand1 < 0 && i < no_of_nodes1) { if (VECTOR(in_1)[i] > 0 && VECTOR(*core_1)[i] < 0) { cand1 = i; } i++; } } else { /**************************************************************/ /* cand2, search not always needed */ if (last2 >= 0) { cand2 = last2; } else { i = 0; while (cand2 < 0 && i < no_of_nodes2) { if (VECTOR(*core_2)[i] < 0) { cand2 = i; } i++; } } /* search for cand1, should be bigger than last1 */ i = last1 + 1; while (cand1 < 0 && i < no_of_nodes1) { if (VECTOR(*core_1)[i] < 0) { cand1 = i; } i++; } } /* Ok, we have cand1, cand2 as candidates. Or not? */ if (cand1 < 0 || cand2 < 0) { /**************************************************************/ /* dead end, step back, if possible. Otherwise we'll terminate */ if (depth >= 1) { last2 = (long int) igraph_stack_pop(&path); last1 = (long int) igraph_stack_pop(&path); matched_nodes -= 1; VECTOR(*core_1)[last1] = -1; VECTOR(*core_2)[last2] = -1; if (VECTOR(in_1)[last1] != 0) { in_1_size += 1; } if (VECTOR(out_1)[last1] != 0) { out_1_size += 1; } if (VECTOR(in_2)[last2] != 0) { in_2_size += 1; } if (VECTOR(out_2)[last2] != 0) { out_2_size += 1; } inneis_1 = igraph_lazy_adjlist_get(&inadj1, (igraph_integer_t) last1); for (i = 0; i < igraph_vector_size(inneis_1); i++) { long int node = (long int) VECTOR(*inneis_1)[i]; if (VECTOR(in_1)[node] == depth) { VECTOR(in_1)[node] = 0; in_1_size -= 1; } } outneis_1 = igraph_lazy_adjlist_get(&outadj1, (igraph_integer_t) last1); for (i = 0; i < igraph_vector_size(outneis_1); i++) { long int node = (long int) VECTOR(*outneis_1)[i]; if (VECTOR(out_1)[node] == depth) { VECTOR(out_1)[node] = 0; out_1_size -= 1; } } inneis_2 = igraph_lazy_adjlist_get(&inadj2, (igraph_integer_t) last2); for (i = 0; i < igraph_vector_size(inneis_2); i++) { long int node = (long int) VECTOR(*inneis_2)[i]; if (VECTOR(in_2)[node] == depth) { VECTOR(in_2)[node] = 0; in_2_size -= 1; } } outneis_2 = igraph_lazy_adjlist_get(&outadj2, (igraph_integer_t) last2); for (i = 0; i < igraph_vector_size(outneis_2); i++) { long int node = (long int) VECTOR(*outneis_2)[i]; if (VECTOR(out_2)[node] == depth) { VECTOR(out_2)[node] = 0; out_2_size -= 1; } } } /* end of stepping back */ depth -= 1; } else { /**************************************************************/ /* step forward if worth, check if worth first */ long int xin1 = 0, xin2 = 0, xout1 = 0, xout2 = 0; igraph_bool_t end = 0; inneis_1 = igraph_lazy_adjlist_get(&inadj1, (igraph_integer_t) cand1); outneis_1 = igraph_lazy_adjlist_get(&outadj1, (igraph_integer_t) cand1); inneis_2 = igraph_lazy_adjlist_get(&inadj2, (igraph_integer_t) cand2); outneis_2 = igraph_lazy_adjlist_get(&outadj2, (igraph_integer_t) cand2); if (VECTOR(indeg1)[cand1] < VECTOR(indeg2)[cand2] || VECTOR(outdeg1)[cand1] < VECTOR(outdeg2)[cand2]) { end = 1; } if (vertex_color1 && VECTOR(*vertex_color1)[cand1] != VECTOR(*vertex_color2)[cand2]) { end = 1; } if (node_compat_fn && !node_compat_fn(graph1, graph2, (igraph_integer_t) cand1, (igraph_integer_t) cand2, arg)) { end = 1; } for (i = 0; !end && i < igraph_vector_size(inneis_1); i++) { long int node = (long int) VECTOR(*inneis_1)[i]; if (VECTOR(*core_1)[node] < 0) { if (VECTOR(in_1)[node] != 0) { xin1++; } if (VECTOR(out_1)[node] != 0) { xout1++; } } } for (i = 0; !end && i < igraph_vector_size(outneis_1); i++) { long int node = (long int) VECTOR(*outneis_1)[i]; if (VECTOR(*core_1)[node] < 0) { if (VECTOR(in_1)[node] != 0) { xin1++; } if (VECTOR(out_1)[node] != 0) { xout1++; } } } for (i = 0; !end && i < igraph_vector_size(inneis_2); i++) { long int node = (long int) VECTOR(*inneis_2)[i]; if (VECTOR(*core_2)[node] >= 0) { long int node2 = (long int) VECTOR(*core_2)[node]; /* check if there is a node2->cand1 edge */ if (!igraph_vector_binsearch2(inneis_1, node2)) { end = 1; } else if (edge_color1 || edge_compat_fn) { igraph_integer_t eid1, eid2; igraph_get_eid(graph1, &eid1, (igraph_integer_t) node2, (igraph_integer_t) cand1, /*directed=*/ 1, /*error=*/ 1); igraph_get_eid(graph2, &eid2, (igraph_integer_t) node, (igraph_integer_t) cand2, /*directed=*/ 1, /*error=*/ 1); if (edge_color1 && VECTOR(*edge_color1)[(long int)eid1] != VECTOR(*edge_color2)[(long int)eid2]) { end = 1; } if (edge_compat_fn && !edge_compat_fn(graph1, graph2, eid1, eid2, arg)) { end = 1; } } } else { if (VECTOR(in_2)[node] != 0) { xin2++; } if (VECTOR(out_2)[node] != 0) { xout2++; } } } for (i = 0; !end && i < igraph_vector_size(outneis_2); i++) { long int node = (long int) VECTOR(*outneis_2)[i]; if (VECTOR(*core_2)[node] >= 0) { long int node2 = (long int) VECTOR(*core_2)[node]; /* check if there is a cand1->node2 edge */ if (!igraph_vector_binsearch2(outneis_1, node2)) { end = 1; } else if (edge_color1 || edge_compat_fn) { igraph_integer_t eid1, eid2; igraph_get_eid(graph1, &eid1, (igraph_integer_t) cand1, (igraph_integer_t) node2, /*directed=*/ 1, /*error=*/ 1); igraph_get_eid(graph2, &eid2, (igraph_integer_t) cand2, (igraph_integer_t) node, /*directed=*/ 1, /*error=*/ 1); if (edge_color1 && VECTOR(*edge_color1)[(long int)eid1] != VECTOR(*edge_color2)[(long int)eid2]) { end = 1; } if (edge_compat_fn && !edge_compat_fn(graph1, graph2, eid1, eid2, arg)) { end = 1; } } } else { if (VECTOR(in_2)[node] != 0) { xin2++; } if (VECTOR(out_2)[node] != 0) { xout2++; } } } if (!end && (xin1 >= xin2 && xout1 >= xout2)) { /* Ok, we add the (cand1, cand2) pair to the mapping */ depth += 1; IGRAPH_CHECK(igraph_stack_push(&path, cand1)); IGRAPH_CHECK(igraph_stack_push(&path, cand2)); matched_nodes += 1; VECTOR(*core_1)[cand1] = cand2; VECTOR(*core_2)[cand2] = cand1; /* update in_*, out_* */ if (VECTOR(in_1)[cand1] != 0) { in_1_size -= 1; } if (VECTOR(out_1)[cand1] != 0) { out_1_size -= 1; } if (VECTOR(in_2)[cand2] != 0) { in_2_size -= 1; } if (VECTOR(out_2)[cand2] != 0) { out_2_size -= 1; } inneis_1 = igraph_lazy_adjlist_get(&inadj1, (igraph_integer_t) cand1); for (i = 0; i < igraph_vector_size(inneis_1); i++) { long int node = (long int) VECTOR(*inneis_1)[i]; if (VECTOR(in_1)[node] == 0 && VECTOR(*core_1)[node] < 0) { VECTOR(in_1)[node] = depth; in_1_size += 1; } } outneis_1 = igraph_lazy_adjlist_get(&outadj1, (igraph_integer_t) cand1); for (i = 0; i < igraph_vector_size(outneis_1); i++) { long int node = (long int) VECTOR(*outneis_1)[i]; if (VECTOR(out_1)[node] == 0 && VECTOR(*core_1)[node] < 0) { VECTOR(out_1)[node] = depth; out_1_size += 1; } } inneis_2 = igraph_lazy_adjlist_get(&inadj2, (igraph_integer_t) cand2); for (i = 0; i < igraph_vector_size(inneis_2); i++) { long int node = (long int) VECTOR(*inneis_2)[i]; if (VECTOR(in_2)[node] == 0 && VECTOR(*core_2)[node] < 0) { VECTOR(in_2)[node] = depth; in_2_size += 1; } } outneis_2 = igraph_lazy_adjlist_get(&outadj2, (igraph_integer_t) cand2); for (i = 0; i < igraph_vector_size(outneis_2); i++) { long int node = (long int) VECTOR(*outneis_2)[i]; if (VECTOR(out_2)[node] == 0 && VECTOR(*core_2)[node] < 0) { VECTOR(out_2)[node] = depth; out_2_size += 1; } } last1 = -1; last2 = -1; /* this the first time here */ } else { last1 = cand1; last2 = cand2; } } if (matched_nodes == no_of_nodes2 && isohandler_fn) { if (!isohandler_fn(core_1, core_2, arg)) { break; } } } igraph_vector_destroy(&outdeg2); igraph_vector_destroy(&outdeg1); igraph_vector_destroy(&indeg2); igraph_vector_destroy(&indeg1); igraph_lazy_adjlist_destroy(&outadj2); igraph_lazy_adjlist_destroy(&inadj2); igraph_lazy_adjlist_destroy(&outadj1); igraph_lazy_adjlist_destroy(&inadj1); igraph_stack_destroy(&path); igraph_vector_destroy(&out_2); igraph_vector_destroy(&out_1); igraph_vector_destroy(&in_2); igraph_vector_destroy(&in_1); IGRAPH_FINALLY_CLEAN(13); if (!map21) { igraph_vector_destroy(core_2); IGRAPH_FINALLY_CLEAN(1); } if (!map12) { igraph_vector_destroy(core_1); IGRAPH_FINALLY_CLEAN(1); } return 0; } igraph_bool_t igraph_i_subisomorphic_vf2(const igraph_vector_t *map12, const igraph_vector_t *map21, void *arg) { igraph_i_iso_cb_data_t *data = arg; igraph_bool_t *iso = data->arg; IGRAPH_UNUSED(map12); IGRAPH_UNUSED(map21); *iso = 1; return 0; /* stop */ } /** * \function igraph_subisomorphic_vf2 * Decide subgraph isomorphism using VF2 * * Decides whether a subgraph of \p graph1 is isomorphic to \p * graph2. It uses \ref igraph_subisomorphic_function_vf2(). * \param graph1 The first input graph, may be directed or * undirected. This is supposed to be the larger graph. * \param graph2 The second input graph, it must have the same * directedness as \p graph1. This is supposed to be the smaller * graph. * \param vertex_color1 An optional color vector for the first graph. If * color vectors are given for both graphs, then the subgraph isomorphism is * calculated on the colored graphs; i.e. two vertices can match * only if their color also matches. Supply a null pointer here if * your graphs are not colored. * \param vertex_color2 An optional color vector for the second graph. See * the previous argument for explanation. * \param edge_color1 An optional edge color vector for the first * graph. The matching edges in the two graphs must have matching * colors as well. Supply a null pointer here if your graphs are not * edge-colored. * \param edge_color2 The edge color vector for the second graph. * \param iso Pointer to a boolean. The result of the decision problem * is stored here. * \param map12 Pointer to a vector or \c NULL. If not \c NULL, then an * isomorphic mapping from \p graph1 to \p graph2 is stored here. * \param map21 Pointer to a vector ot \c NULL. If not \c NULL, then * an isomorphic mapping from \p graph2 to \p graph1 is stored * here. * \param node_compat_fn A pointer to a function of type \ref * igraph_isocompat_t. This function will be called by the algorithm to * determine whether two nodes are compatible. * \param edge_compat_fn A pointer to a function of type \ref * igraph_isocompat_t. This function will be called by the algorithm to * determine whether two edges are compatible. * \param arg Extra argument to supply to functions \p node_compat_fn * and \p edge_compat_fn. * \return Error code. * * Time complexity: exponential. */ int igraph_subisomorphic_vf2(const igraph_t *graph1, const igraph_t *graph2, const igraph_vector_int_t *vertex_color1, const igraph_vector_int_t *vertex_color2, const igraph_vector_int_t *edge_color1, const igraph_vector_int_t *edge_color2, igraph_bool_t *iso, igraph_vector_t *map12, igraph_vector_t *map21, igraph_isocompat_t *node_compat_fn, igraph_isocompat_t *edge_compat_fn, void *arg) { igraph_i_iso_cb_data_t data = { node_compat_fn, edge_compat_fn, iso, arg }; igraph_isocompat_t *ncb = node_compat_fn ? igraph_i_isocompat_node_cb : 0; igraph_isocompat_t *ecb = edge_compat_fn ? igraph_i_isocompat_edge_cb : 0; *iso = 0; IGRAPH_CHECK(igraph_subisomorphic_function_vf2(graph1, graph2, vertex_color1, vertex_color2, edge_color1, edge_color2, map12, map21, (igraph_isohandler_t *) igraph_i_subisomorphic_vf2, ncb, ecb, &data)); if (! *iso) { if (map12) { igraph_vector_clear(map12); } if (map21) { igraph_vector_clear(map21); } } return 0; } igraph_bool_t igraph_i_count_subisomorphisms_vf2(const igraph_vector_t *map12, const igraph_vector_t *map21, void *arg) { igraph_i_iso_cb_data_t *data = arg; igraph_integer_t *count = data->arg; IGRAPH_UNUSED(map12); IGRAPH_UNUSED(map21); *count += 1; return 1; /* always continue */ } /** * \function igraph_count_subisomorphisms_vf2 * Number of subgraph isomorphisms using VF2 * * Count the number of isomorphisms between subgraphs of \p graph1 and * \p graph2. This function uses \ref * igraph_subisomorphic_function_vf2(). * \param graph1 The first input graph, may be directed or * undirected. This is supposed to be the larger graph. * \param graph2 The second input graph, it must have the same * directedness as \p graph1. This is supposed to be the smaller * graph. * \param vertex_color1 An optional color vector for the first graph. If * color vectors are given for both graphs, then the subgraph isomorphism is * calculated on the colored graphs; i.e. two vertices can match * only if their color also matches. Supply a null pointer here if * your graphs are not colored. * \param vertex_color2 An optional color vector for the second graph. See * the previous argument for explanation. * \param edge_color1 An optional edge color vector for the first * graph. The matching edges in the two graphs must have matching * colors as well. Supply a null pointer here if your graphs are not * edge-colored. * \param edge_color2 The edge color vector for the second graph. * \param count Pointer to an integer. The number of subgraph * isomorphisms is stored here. * \param node_compat_fn A pointer to a function of type \ref * igraph_isocompat_t. This function will be called by the algorithm to * determine whether two nodes are compatible. * \param edge_compat_fn A pointer to a function of type \ref * igraph_isocompat_t. This function will be called by the algorithm to * determine whether two edges are compatible. * \param arg Extra argument to supply to functions \p node_compat_fn and * \p edge_compat_fn. * \return Error code. * * Time complexity: exponential. */ int igraph_count_subisomorphisms_vf2(const igraph_t *graph1, const igraph_t *graph2, const igraph_vector_int_t *vertex_color1, const igraph_vector_int_t *vertex_color2, const igraph_vector_int_t *edge_color1, const igraph_vector_int_t *edge_color2, igraph_integer_t *count, igraph_isocompat_t *node_compat_fn, igraph_isocompat_t *edge_compat_fn, void *arg) { igraph_i_iso_cb_data_t data = { node_compat_fn, edge_compat_fn, count, arg }; igraph_isocompat_t *ncb = node_compat_fn ? igraph_i_isocompat_node_cb : 0; igraph_isocompat_t *ecb = edge_compat_fn ? igraph_i_isocompat_edge_cb : 0; *count = 0; IGRAPH_CHECK(igraph_subisomorphic_function_vf2(graph1, graph2, vertex_color1, vertex_color2, edge_color1, edge_color2, 0, 0, (igraph_isohandler_t*) igraph_i_count_subisomorphisms_vf2, ncb, ecb, &data)); return 0; } void igraph_i_get_subisomorphisms_free(igraph_vector_ptr_t *data) { long int i, n = igraph_vector_ptr_size(data); for (i = 0; i < n; i++) { igraph_vector_t *vec = VECTOR(*data)[i]; igraph_vector_destroy(vec); igraph_free(vec); } } igraph_bool_t igraph_i_get_subisomorphisms_vf2(const igraph_vector_t *map12, const igraph_vector_t *map21, void *arg) { igraph_i_iso_cb_data_t *data = arg; igraph_vector_ptr_t *vector = data->arg; igraph_vector_t *newvector = igraph_Calloc(1, igraph_vector_t); IGRAPH_UNUSED(map12); if (!newvector) { igraph_error("Out of memory", __FILE__, __LINE__, IGRAPH_ENOMEM); return 0; /* stop right here */ } IGRAPH_FINALLY(igraph_free, newvector); IGRAPH_CHECK(igraph_vector_copy(newvector, map21)); IGRAPH_FINALLY(igraph_vector_destroy, newvector); IGRAPH_CHECK(igraph_vector_ptr_push_back(vector, newvector)); IGRAPH_FINALLY_CLEAN(2); return 1; /* continue finding subisomorphisms */ } /** * \function igraph_get_subisomorphisms_vf2 * Return all subgraph isomorphic mappings * * This function collects all isomorphic mappings of \p graph2 to a * subgraph of \p graph1. It uses the \ref * igraph_subisomorphic_function_vf2() function. * \param graph1 The first input graph, may be directed or * undirected. This is supposed to be the larger graph. * \param graph2 The second input graph, it must have the same * directedness as \p graph1. This is supposed to be the smaller * graph. * \param vertex_color1 An optional color vector for the first graph. If * color vectors are given for both graphs, then the subgraph isomorphism is * calculated on the colored graphs; i.e. two vertices can match * only if their color also matches. Supply a null pointer here if * your graphs are not colored. * \param vertex_color2 An optional color vector for the second graph. See * the previous argument for explanation. * \param edge_color1 An optional edge color vector for the first * graph. The matching edges in the two graphs must have matching * colors as well. Supply a null pointer here if your graphs are not * edge-colored. * \param edge_color2 The edge color vector for the second graph. * \param maps Pointer vector. On return it contains pointers to * igraph_vector_t objects, each vector is an * isomorphic mapping of \p graph2 to a subgraph of \p graph1. Please note that * you need to 1) Destroy the vectors via \ref * igraph_vector_destroy(), 2) free them via * free() and then 3) call \ref * igraph_vector_ptr_destroy() on the pointer vector to deallocate all * memory when \p maps is no longer needed. * \param node_compat_fn A pointer to a function of type \ref * igraph_isocompat_t. This function will be called by the algorithm to * determine whether two nodes are compatible. * \param edge_compat_fn A pointer to a function of type \ref * igraph_isocompat_t. This function will be called by the algorithm to * determine whether two edges are compatible. * \param arg Extra argument to supply to functions \p node_compat_fn * and \p edge_compat_fn. * \return Error code. * * Time complexity: exponential. */ int igraph_get_subisomorphisms_vf2(const igraph_t *graph1, const igraph_t *graph2, const igraph_vector_int_t *vertex_color1, const igraph_vector_int_t *vertex_color2, const igraph_vector_int_t *edge_color1, const igraph_vector_int_t *edge_color2, igraph_vector_ptr_t *maps, igraph_isocompat_t *node_compat_fn, igraph_isocompat_t *edge_compat_fn, void *arg) { igraph_i_iso_cb_data_t data = { node_compat_fn, edge_compat_fn, maps, arg }; igraph_isocompat_t *ncb = node_compat_fn ? igraph_i_isocompat_node_cb : 0; igraph_isocompat_t *ecb = edge_compat_fn ? igraph_i_isocompat_edge_cb : 0; igraph_vector_ptr_clear(maps); IGRAPH_FINALLY(igraph_i_get_subisomorphisms_free, maps); IGRAPH_CHECK(igraph_subisomorphic_function_vf2(graph1, graph2, vertex_color1, vertex_color2, edge_color1, edge_color2, 0, 0, (igraph_isohandler_t*) igraph_i_get_subisomorphisms_vf2, ncb, ecb, &data)); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_permute_vertices * Permute the vertices * * This function creates a new graph from the input graph by permuting * its vertices according to the specified mapping. Call this function * with the output of \ref igraph_canonical_permutation() to create * the canonical form of a graph. * \param graph The input graph. * \param res Pointer to an uninitialized graph object. The new graph * is created here. * \param permutation The permutation to apply. Vertex 0 is mapped to * the first element of the vector, vertex 1 to the second, * etc. Note that it is not checked that the vector contains every * element only once, and no range checking is performed either. * \return Error code. * * Time complexity: O(|V|+|E|), linear in terms of the number of * vertices and edges. */ int igraph_permute_vertices(const igraph_t *graph, igraph_t *res, const igraph_vector_t *permutation) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_vector_t edges; long int i, p = 0; if (igraph_vector_size(permutation) != no_of_nodes) { IGRAPH_ERROR("Permute vertices: invalid permutation vector size", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(&edges, no_of_edges * 2); for (i = 0; i < no_of_edges; i++) { VECTOR(edges)[p++] = VECTOR(*permutation)[ (long int) IGRAPH_FROM(graph, i) ]; VECTOR(edges)[p++] = VECTOR(*permutation)[ (long int) IGRAPH_TO(graph, i) ]; } IGRAPH_CHECK(igraph_create(res, &edges, (igraph_integer_t) no_of_nodes, igraph_is_directed(graph))); /* Attributes */ if (graph->attr) { igraph_vector_t index; igraph_vector_t vtypes; IGRAPH_I_ATTRIBUTE_DESTROY(res); IGRAPH_I_ATTRIBUTE_COPY(res, graph, /*graph=*/1, /*vertex=*/0, /*edge=*/1); IGRAPH_VECTOR_INIT_FINALLY(&vtypes, 0); IGRAPH_CHECK(igraph_i_attribute_get_info(graph, 0, 0, 0, &vtypes, 0, 0)); if (igraph_vector_size(&vtypes) != 0) { IGRAPH_VECTOR_INIT_FINALLY(&index, no_of_nodes); for (i = 0; i < no_of_nodes; i++) { VECTOR(index)[ (long int) VECTOR(*permutation)[i] ] = i; } IGRAPH_CHECK(igraph_i_attribute_permute_vertices(graph, res, &index)); igraph_vector_destroy(&index); IGRAPH_FINALLY_CLEAN(1); } igraph_vector_destroy(&vtypes); IGRAPH_FINALLY_CLEAN(1); } igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \section about_bliss * * * BLISS is a successor of the famous NAUTY algorithm and * implementation. While using the same ideas in general, with better * heuristics and data structures BLISS outperforms NAUTY on most * graphs. * * * * BLISS was developed and implemented by Tommi Junttila and Petteri Kaski at * Helsinki University of Technology, Finland. For more information, * see the BLISS homepage at http://www.tcs.hut.fi/Software/bliss/ and the publication * Tommi Junttila, Petteri Kaski: "Engineering an Efficient Canonical Labeling * Tool for Large and Sparse Graphs" at https://doi.org/10.1137/1.9781611972870.13 * * * * BLISS works with both directed graphs and undirected graphs. It supports graphs with * self-loops, but not graphs with multi-edges. * * * * BLISS version 0.73 is included in igraph. * */ /** * \function igraph_isomorphic_bliss * Graph isomorphism via BLISS * * This function uses the BLISS graph isomorphism algorithm, a * successor of the famous NAUTY algorithm and implementation. BLISS * is open source and licensed according to the GNU GPL. See * http://www.tcs.hut.fi/Software/bliss/index.html for * details. Currently the 0.73 version of BLISS is included in igraph. * * * * \param graph1 The first input graph. Multiple edges between the same nodes * are not supported and will cause an incorrect result to be returned. * \param graph2 The second input graph. Multiple edges between the same nodes * are not supported and will cause an incorrect result to be returned. * \param colors1 An optional vertex color vector for the first graph. Supply a * null pointer if your graph is not colored. * \param colors2 An optional vertex color vector for the second graph. Supply a * null pointer if your graph is not colored. * \param iso Pointer to a boolean, the result is stored here. * \param map12 A vector or \c NULL pointer. If not \c NULL then an * isomorphic mapping from \p graph1 to \p graph2 is stored here. * If the input graphs are not isomorphic then this vector is * cleared, i.e. it will have length zero. * \param map21 Similar to \p map12, but for the mapping from \p * graph2 to \p graph1. * \param sh Splitting heuristics to be used for the graphs. See * \ref igraph_bliss_sh_t. * \param info1 If not \c NULL, information about the canonization of * the first input graph is stored here. See \ref igraph_bliss_info_t * for details. Note that if the two graphs have different number * of vertices or edges, then this is not filled. * \param info2 Same as \p info1, but for the second graph. * \return Error code. * * Time complexity: exponential, but in practice it is quite fast. */ int igraph_isomorphic_bliss(const igraph_t *graph1, const igraph_t *graph2, const igraph_vector_int_t *colors1, const igraph_vector_int_t *colors2, igraph_bool_t *iso, igraph_vector_t *map12, igraph_vector_t *map21, igraph_bliss_sh_t sh, igraph_bliss_info_t *info1, igraph_bliss_info_t *info2) { long int no_of_nodes = igraph_vcount(graph1); long int no_of_edges = igraph_ecount(graph1); igraph_vector_t perm1, perm2; igraph_vector_t vmap12, *mymap12 = &vmap12; igraph_vector_t from, to, index; igraph_vector_t from2, to2, index2; igraph_bool_t directed; long int i, j; *iso = 0; if (info1) { info1->nof_nodes = info1->nof_leaf_nodes = info1->nof_bad_nodes = info1->nof_canupdates = info1->max_level = info1->nof_generators = -1; info1->group_size = 0; } if (info2) { info2->nof_nodes = info2->nof_leaf_nodes = info2->nof_bad_nodes = info2->nof_canupdates = info2->max_level = info2->nof_generators = -1; info2->group_size = 0; } directed = igraph_is_directed(graph1); if (igraph_is_directed(graph2) != directed) { IGRAPH_ERROR("Cannot compare directed and undirected graphs", IGRAPH_EINVAL); } if ((colors1 == NULL || colors2 == NULL) && colors1 != colors2) { IGRAPH_WARNING("Only one of the graphs is vertex colored, colors will be ignored"); colors1 = NULL; colors2 = NULL; } if (no_of_nodes != igraph_vcount(graph2) || no_of_edges != igraph_ecount(graph2)) { if (map12) { igraph_vector_clear(map12); } if (map21) { igraph_vector_clear(map21); } return 0; } if (map12) { mymap12 = map12; } else { IGRAPH_VECTOR_INIT_FINALLY(mymap12, 0); } IGRAPH_VECTOR_INIT_FINALLY(&perm1, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&perm2, no_of_nodes); IGRAPH_CHECK(igraph_canonical_permutation(graph1, colors1, &perm1, sh, info1)); IGRAPH_CHECK(igraph_canonical_permutation(graph2, colors2, &perm2, sh, info2)); IGRAPH_CHECK(igraph_vector_resize(mymap12, no_of_nodes)); /* The inverse of perm2 is produced in mymap12 */ for (i = 0; i < no_of_nodes; i++) { VECTOR(*mymap12)[ (long int)VECTOR(perm2)[i] ] = i; } /* Now we produce perm2^{-1} o perm1 in perm2 */ for (i = 0; i < no_of_nodes; i++) { VECTOR(perm2)[i] = VECTOR(*mymap12)[ (long int) VECTOR(perm1)[i] ]; } /* Copy it to mymap12 */ igraph_vector_update(mymap12, &perm2); igraph_vector_destroy(&perm1); igraph_vector_destroy(&perm2); IGRAPH_FINALLY_CLEAN(2); /* Check isomorphism, we apply the permutation in mymap12 to graph1 and should get graph2 */ IGRAPH_VECTOR_INIT_FINALLY(&from, no_of_edges); IGRAPH_VECTOR_INIT_FINALLY(&to, no_of_edges); IGRAPH_VECTOR_INIT_FINALLY(&index, no_of_edges); IGRAPH_VECTOR_INIT_FINALLY(&from2, no_of_edges * 2); IGRAPH_VECTOR_INIT_FINALLY(&to2, no_of_edges); IGRAPH_VECTOR_INIT_FINALLY(&index2, no_of_edges); for (i = 0; i < no_of_edges; i++) { VECTOR(from)[i] = VECTOR(*mymap12)[ (long int) IGRAPH_FROM(graph1, i) ]; VECTOR(to)[i] = VECTOR(*mymap12)[ (long int) IGRAPH_TO (graph1, i) ]; if (! directed && VECTOR(from)[i] < VECTOR(to)[i]) { igraph_real_t tmp = VECTOR(from)[i]; VECTOR(from)[i] = VECTOR(to)[i]; VECTOR(to)[i] = tmp; } } igraph_vector_order(&from, &to, &index, no_of_nodes); igraph_get_edgelist(graph2, &from2, /*bycol=*/ 1); for (i = 0, j = no_of_edges; i < no_of_edges; i++, j++) { VECTOR(to2)[i] = VECTOR(from2)[j]; if (! directed && VECTOR(from2)[i] < VECTOR(to2)[i]) { igraph_real_t tmp = VECTOR(from2)[i]; VECTOR(from2)[i] = VECTOR(to2)[i]; VECTOR(to2)[i] = tmp; } } igraph_vector_resize(&from2, no_of_edges); igraph_vector_order(&from2, &to2, &index2, no_of_nodes); *iso = 1; for (i = 0; i < no_of_edges; i++) { long int i1 = (long int) VECTOR(index)[i]; long int i2 = (long int) VECTOR(index2)[i]; if (VECTOR(from)[i1] != VECTOR(from2)[i2] || VECTOR(to)[i1] != VECTOR(to2)[i2]) { *iso = 0; break; } } /* If the graphs are coloured, we also need to check that applying the permutation mymap12 to colors1 gives colors2. */ if (*iso && colors1 != NULL) { for (i = 0; i < no_of_nodes; i++) { if (VECTOR(*colors1)[i] != VECTOR(*colors2)[(long int) VECTOR(*mymap12)[i] ]) { *iso = 0; break; } } } igraph_vector_destroy(&index2); igraph_vector_destroy(&to2); igraph_vector_destroy(&from2); igraph_vector_destroy(&index); igraph_vector_destroy(&to); igraph_vector_destroy(&from); IGRAPH_FINALLY_CLEAN(6); if (*iso) { /* The inverse of mymap12 */ if (map21) { IGRAPH_CHECK(igraph_vector_resize(map21, no_of_nodes)); for (i = 0; i < no_of_nodes; i++) { VECTOR(*map21)[ (long int) VECTOR(*mymap12)[i] ] = i; } } } else { if (map12) { igraph_vector_clear(map12); } if (map21) { igraph_vector_clear(map21); } } if (!map12) { igraph_vector_destroy(mymap12); IGRAPH_FINALLY_CLEAN(1); } return 0; } /** * \function igraph_simplify_and_colorize * \brief Simplify the graph and compute self-loop and edge multiplicities. * * * This function creates a vertex and edge colored simple graph from the input * graph. The vertex colors are computed as the number of incident self-loops * to each vertex in the input graph. The edge colors are computed as the number of * parallel edges in the input graph that were merged to create each edge * in the simple graph. * * * The resulting colored simple graph is suitable for use by isomorphism checking * algorithms such as VF2, which only support simple graphs, but can consider * vertex and edge colors. * * \param graph The graph object, typically having self-loops or multi-edges. * \param res An uninitialized graph object. The result will be stored here * \param vertex_color Computed vertex colors corresponding to self-loop multiplicities. * \param edge_color Computed edge colors corresponding to edge multiplicities * \return Error code. * * \sa \ref igraph_simplify(), \ref igraph_isomorphic_vf2(), \ref igraph_subisomorphic_vf2() * */ int igraph_simplify_and_colorize( const igraph_t *graph, igraph_t *res, igraph_vector_int_t *vertex_color, igraph_vector_int_t *edge_color) { igraph_es_t es; igraph_eit_t eit; igraph_vector_t edges; long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); long int pto = -1, pfrom = -1; long int i; IGRAPH_CHECK(igraph_es_all(&es, IGRAPH_EDGEORDER_FROM)); IGRAPH_FINALLY(igraph_es_destroy, &es); IGRAPH_CHECK(igraph_eit_create(graph, es, &eit)); IGRAPH_FINALLY(igraph_eit_destroy, &eit); IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_CHECK(igraph_vector_reserve(&edges, no_of_edges * 2)); IGRAPH_CHECK(igraph_vector_int_resize(vertex_color, no_of_nodes)); igraph_vector_int_null(vertex_color); IGRAPH_CHECK(igraph_vector_int_resize(edge_color, no_of_edges)); igraph_vector_int_null(edge_color); i = -1; for (; !IGRAPH_EIT_END(eit); IGRAPH_EIT_NEXT(eit)) { long int edge = IGRAPH_EIT_GET(eit); long int from = IGRAPH_FROM(graph, edge); long int to = IGRAPH_TO(graph, edge); if (to == from) { VECTOR(*vertex_color)[to]++; continue; } if (to == pto && from == pfrom) { VECTOR(*edge_color)[i]++; } else { igraph_vector_push_back(&edges, from); igraph_vector_push_back(&edges, to); i++; VECTOR(*edge_color)[i] = 1; } pfrom = from; pto = to; } igraph_vector_int_resize(edge_color, i + 1); igraph_eit_destroy(&eit); igraph_es_destroy(&es); IGRAPH_FINALLY_CLEAN(2); IGRAPH_CHECK(igraph_create(res, &edges, no_of_nodes, igraph_is_directed(graph))); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } python-igraph-0.8.0/vendor/source/igraph/src/gengraph_hash.h0000644000076500000240000002126013614300625024346 0ustar tamasstaff00000000000000/* * * gengraph - generation of random simple connected graphs with prescribed * degree sequence * * Copyright (C) 2006 Fabien Viger * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #ifndef HASH_H #define HASH_H #include #include "gengraph_definitions.h" //_________________________________________________________________________ // Hash table profiling... Active only if definition below is uncommented //_________________________________________________________________________ //#define _HASH_PROFILE namespace gengraph { #ifdef _HASH_PROFILE void _hash_add_iter(); void _hash_add_call(); void _hash_put_iter(); void _hash_put_call(); void _hash_rm_iter(); void _hash_rm_call(); void _hash_find_iter(); void _hash_find_call(); void _hash_rand_iter(); void _hash_rand_call(); void _hash_expand_call(); void _hash_prof(); #define _HASH_ADD_ITER() _hash_add_iter() #define _HASH_ADD_CALL() _hash_add_call() #define _HASH_PUT_ITER() _hash_put_iter() #define _HASH_PUT_CALL() _hash_put_call() #define _HASH_RM_ITER() _hash_rm_iter() #define _HASH_RM_CALL() _hash_rm_call() #define _HASH_FIND_ITER() _hash_find_iter() #define _HASH_FIND_CALL() _hash_find_call() #define _HASH_RAND_ITER() _hash_rand_iter() #define _HASH_RAND_CALL() _hash_rand_call() #define _HASH_EXP_CALL() _hash_expand_call() #else #define _HASH_ADD_ITER() {} #define _HASH_ADD_CALL() {} #define _HASH_PUT_ITER() {} #define _HASH_PUT_CALL() {} #define _HASH_RM_ITER() {} #define _HASH_RM_CALL() {} #define _HASH_FIND_ITER() {} #define _HASH_FIND_CALL() {} #define _HASH_RAND_ITER() {} #define _HASH_RAND_CALL() {} #define _HASH_EXP_CALL() {} #endif //_________________________________________________________________________ // Hash Table properties. Works best when HASH_SIZE_IS_POWER2 is uncommented // but takes 2.25 times the needed space, in average (from 1.5 to 3) // If you have memory issues, Try to comment it: tables will take 1.5 times // the minimal space //_________________________________________________________________________ #define HASH_SIZE_IS_POWER2 #define MACRO_RATHER_THAN_INLINE // under HASH_MIN_SIZE, vectors are not hash table (just a simle array) #define HASH_MIN_SIZE 100 #define IS_HASH(x) ((x)>HASH_MIN_SIZE) #define HASH_NONE (-1) #ifdef HASH_SIZE_IS_POWER2 inline int HASH_EXPAND(int x) { _HASH_EXP_CALL(); x += x; x |= x >> 1; x |= x >> 2; x |= x >> 4; x |= x >> 8; x |= x >> 16; return x + 1; } #define HASH_KEY(x,size) ((x*2198737)&((size)-1)) #endif //HASH_SIZE_IS_POWER2 #ifdef MACRO_RATHER_THAN_INLINE #ifndef HASH_SIZE_IS_POWER2 #define HASH_EXPAND(x) ((x)+((x)>>1)) #define HASH_UNEXPAND(x) ((((x)<<1)+1)/3) #define HASH_KEY(x,size) ((x)%(size)) #endif //HASH_SIZE_IS_POWER2 #define HASH_SIZE(x) (IS_HASH(x) ? HASH_EXPAND(x) : (x) ) #define HASH_REKEY(k,size) ((k)==0 ? (size)-1 : (k)-1) #else //MACRO_RATHER_THAN_INLINE #ifndef HASH_SIZE_IS_POWER2 inline int HASH_KEY(const int x, const int size) { assert(x >= 0); return x % size; }; inline int HASH_EXPAND(const int x) { _HASH_EXP_CALL(); return x + (x >> 1); }; inline int HASH_UNEXPAND(const int x) { return ((x << 1) + 1) / 3; }; #endif //HASH_SIZE_IS_POWER2 inline int HASH_REKEY(const int k, const int s) { assert(k >= 0); if (k == 0) { return s - 1; } else { return k - 1; } }; inline int HASH_SIZE(const int x) { if (IS_HASH(x)) { return HASH_EXPAND(x); } else { return x; } }; #endif //MACRO_RATHER_THAN_INLINE inline int HASH_PAIR_KEY(const int x, const int y, const int size) { return HASH_KEY(x * 1434879443 + y, size); } //_________________________________________________________________________ // Hash-only functions : table must NOT be Raw. // the argument 'size' is the total size of the hash table //_________________________________________________________________________ // copy hash table into raw vector inline void H_copy(int *mem, int *h, int size) { for (int i = HASH_EXPAND(size); i--; h++) if (*h != HASH_NONE) { *(mem++) = *h; } } // Look for the place to add an element. Return NULL if element is already here. inline int* H_add(int* h, const int size, int a) { _HASH_ADD_CALL(); _HASH_ADD_ITER(); int k = HASH_KEY(a, size); if (h[k] == HASH_NONE) { return h + k; } while (h[k] != a) { _HASH_ADD_ITER(); k = HASH_REKEY(k, size); if (h[k] == HASH_NONE) { return h + k; } } return NULL; } // would element be well placed in newk ? inline bool H_better(const int a, const int size, const int currentk, const int newk) { int k = HASH_KEY(a, size); if (newk < currentk) { return (k < currentk && k >= newk); } else { return (k < currentk || k >= newk); } } // removes h[k] inline void H_rm(int* h, const int size, int k) { _HASH_RM_CALL(); int lasthole = k; do { _HASH_RM_ITER(); k = HASH_REKEY(k, size); int next = h[k]; if (next == HASH_NONE) { break; } if (H_better(next, size, k, lasthole)) { h[lasthole] = next; lasthole = k; } } while (true); h[lasthole] = HASH_NONE; } //put a inline int* H_put(int* h, const int size, const int a) { assert(H_add(h, size, a) != NULL); _HASH_PUT_CALL(); _HASH_PUT_ITER(); int k = HASH_KEY(a, size); while (h[k] != HASH_NONE) { k = HASH_REKEY(k, size); _HASH_PUT_ITER(); } h[k] = a; assert(H_add(h, size, a) == NULL); return h + k; } // find A inline int H_find(int *h, int size, const int a) { assert(H_add(h, size, a) == NULL); _HASH_FIND_CALL(); _HASH_FIND_ITER(); int k = HASH_KEY(a, size); while (h[k] != a) { k = HASH_REKEY(k, size); _HASH_FIND_ITER(); } return k; } // Look for the place to add an element. Return NULL if element is already here. inline bool H_pair_insert(int* h, const int size, int a, int b) { _HASH_ADD_CALL(); _HASH_ADD_ITER(); int k = HASH_PAIR_KEY(a, b, size); if (h[2 * k] == HASH_NONE) { h[2 * k] = a; h[2 * k + 1] = b; return true; } while (h[2 * k] != a || h[2 * k + 1] != b) { _HASH_ADD_ITER(); k = HASH_REKEY(k, size); if (h[2 * k] == HASH_NONE) { h[2 * k] = a; h[2 * k + 1] = b; return true; } } return false; } //_________________________________________________________________________ // Generic functions : table can be either Hash or Raw. // the argument 'size' is the number of elements //_________________________________________________________________________ // Look for an element inline bool H_is(int *mem, const int size, const int elem) { if (IS_HASH(size)) { return (H_add(mem, HASH_EXPAND(size), elem) == NULL); } else { return fast_search(mem, size, elem) != NULL; } } //pick random location (containing an element) inline int* H_random(int* mem, int size) { if (!IS_HASH(size)) { return mem + (my_random() % size); } _HASH_RAND_CALL(); size = HASH_EXPAND(size); int* yo; do { yo = mem + HASH_KEY(my_random(), size); _HASH_RAND_ITER(); } while (*yo == HASH_NONE); return yo; } // replace *k by b inline int* H_rpl(int *mem, int size, int* k, const int b) { assert(!H_is(mem, size, b)); if (!IS_HASH(size)) { *k = b; return k; } else { size = HASH_EXPAND(size); assert(mem + int(k - mem) == k); H_rm(mem, size, int(k - mem)); return H_put(mem, size, b); } } // replace a by b inline int* H_rpl(int *mem, int size, const int a, const int b) { assert(H_is(mem, size, a)); assert(!H_is(mem, size, b)); if (!IS_HASH(size)) { return fast_rpl(mem, a, b); } else { size = HASH_EXPAND(size); H_rm(mem, size, H_find(mem, size, a)); return H_put(mem, size, b); } } } // namespace gengraph #endif //HASH_H python-igraph-0.8.0/vendor/source/igraph/src/triangles_template.h0000644000076500000240000000734313614300625025441 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2005-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ long int no_of_nodes = igraph_vcount(graph); long int node, i, j, nn; igraph_adjlist_t allneis; igraph_vector_int_t *neis1, *neis2; long int neilen1, neilen2, deg1; long int *neis; long int maxdegree; igraph_vector_int_t order; igraph_vector_int_t rank; igraph_vector_t degree; igraph_vector_int_init(&order, no_of_nodes); IGRAPH_FINALLY(igraph_vector_int_destroy, &order); IGRAPH_VECTOR_INIT_FINALLY(°ree, no_of_nodes); IGRAPH_CHECK(igraph_degree(graph, °ree, igraph_vss_all(), IGRAPH_ALL, IGRAPH_LOOPS)); maxdegree = (long int) igraph_vector_max(°ree) + 1; igraph_vector_order1_int(°ree, &order, maxdegree); igraph_vector_int_init(&rank, no_of_nodes); IGRAPH_FINALLY(igraph_vector_int_destroy, &rank); for (i = 0; i < no_of_nodes; i++) { VECTOR(rank)[ VECTOR(order)[i] ] = no_of_nodes - i - 1; } IGRAPH_CHECK(igraph_adjlist_init(graph, &allneis, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_adjlist_destroy, &allneis); IGRAPH_CHECK(igraph_i_trans4_al_simplify(&allneis, &rank)); neis = igraph_Calloc(no_of_nodes, long int); if (neis == 0) { IGRAPH_ERROR("undirected local transitivity failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, neis); #ifndef TRIANGLES IGRAPH_CHECK(igraph_vector_resize(res, no_of_nodes)); igraph_vector_null(res); #else igraph_vector_int_clear(res); #endif for (nn = no_of_nodes - 1; nn >= 0; nn--) { node = VECTOR(order)[nn]; IGRAPH_ALLOW_INTERRUPTION(); neis1 = igraph_adjlist_get(&allneis, node); neilen1 = igraph_vector_int_size(neis1); deg1 = (long int) VECTOR(degree)[node]; /* Mark the neighbors of the node */ for (i = 0; i < neilen1; i++) { neis[ (long int) VECTOR(*neis1)[i] ] = node + 1; } for (i = 0; i < neilen1; i++) { long int nei = (long int) VECTOR(*neis1)[i]; neis2 = igraph_adjlist_get(&allneis, nei); neilen2 = igraph_vector_int_size(neis2); for (j = 0; j < neilen2; j++) { long int nei2 = (long int) VECTOR(*neis2)[j]; if (neis[nei2] == node + 1) { #ifndef TRIANGLES VECTOR(*res)[nei2] += 1; VECTOR(*res)[nei] += 1; VECTOR(*res)[node] += 1; #else IGRAPH_CHECK(igraph_vector_int_push_back(res, node)); IGRAPH_CHECK(igraph_vector_int_push_back(res, nei)); IGRAPH_CHECK(igraph_vector_int_push_back(res, nei2)); #endif } } } #ifdef TRANSIT if (mode == IGRAPH_TRANSITIVITY_ZERO && deg1 < 2) { VECTOR(*res)[node] = 0.0; } else { VECTOR(*res)[node] = VECTOR(*res)[node] / deg1 / (deg1 - 1) * 2.0; } #endif #ifdef TRIEDGES VECTOR(*res)[node] += deg1; #endif } igraph_free(neis); igraph_adjlist_destroy(&allneis); igraph_vector_int_destroy(&rank); igraph_vector_destroy(°ree); igraph_vector_int_destroy(&order); IGRAPH_FINALLY_CLEAN(5); python-igraph-0.8.0/vendor/source/igraph/src/drl_layout_3d.h0000644000076500000240000000563613614300625024325 0ustar tamasstaff00000000000000/* * Copyright 2007 Sandia Corporation. Under the terms of Contract * DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains * certain rights in this software. * * All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are * met: * * * Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * Neither the name of Sandia National Laboratories nor the names of * its contributors may be used to endorse or promote products derived from * this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT * OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED * TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF * LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING * NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. */ // This file contains compile time parameters which affect the entire // DrL program. #define DRL_VERSION "3.2 5/5/2006" // compile time parameters for MPI message passing #define MAX_PROCS 256 // maximum number of processors #define MAX_FILE_NAME 250 // max length of filename #define MAX_INT_LENGTH 4 // max length of integer suffix of intermediate .coord file // Compile time adjustable parameters for the Density grid #define GRID_SIZE 100 // size of Density grid #define VIEW_SIZE 250.0 // actual physical size of layout plane // these values use more memory but have // little effect on performance or layout #define RADIUS 10 // radius for density fall-off: // larger values tends to slow down // the program and clump the data #define HALF_VIEW 125.0 // 1/2 of VIEW_SIZE #define VIEW_TO_GRID .4 // ratio of GRID_SIZE to VIEW_SIZE /* // original values for VxOrd #define GRID_SIZE 400 // size of VxOrd Density grid #define VIEW_SIZE 1600.0 // actual physical size of VxOrd plane #define RADIUS 10 // radius for density fall-off #define HALF_VIEW 800 // 1/2 of VIEW_SIZE #define VIEW_TO_GRID .25 // ratio of GRID_SIZE to VIEW_SIZE */ python-igraph-0.8.0/vendor/source/igraph/src/DensityGrid.cpp0000644000076500000240000002165713614300625024342 0ustar tamasstaff00000000000000/* * Copyright 2007 Sandia Corporation. Under the terms of Contract * DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains * certain rights in this software. * * All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are * met: * * * Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * Neither the name of Sandia National Laboratories nor the names of * its contributors may be used to endorse or promote products derived from * this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT * OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED * TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF * LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING * NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. */ // This file contains the member definitions of the DensityGrid.h class // This code is modified from the original code by B.N. Wylie #include #include #include #include #include using namespace std; #include "drl_Node.h" #include "DensityGrid.h" #include "igraph_error.h" #define GET_BIN(y, x) (Bins[y*GRID_SIZE+x]) namespace drl { //******************************************************* // Density Grid Destructor -- deallocates memory used // for Density matrix, fall_off matrix, and node deque. DensityGrid::~DensityGrid () { delete[] Density; delete[] fall_off; delete[] Bins; } /********************************************* * Function: Density_Grid::Reset * * Description: Reset the density grid * *********************************************/ // changed from reset to init since we will only // call this once in the parallel version of layout void DensityGrid::Init() { try { Density = new float[GRID_SIZE][GRID_SIZE]; fall_off = new float[RADIUS * 2 + 1][RADIUS * 2 + 1]; Bins = new deque[GRID_SIZE * GRID_SIZE]; } catch (bad_alloc errora) { // cout << "Error: Out of memory! Program stopped." << endl; #ifdef MUSE_MPI MPI_Abort ( MPI_COMM_WORLD, 1 ); #else igraph_error("DrL is out of memory", __FILE__, __LINE__, IGRAPH_ENOMEM); return; #endif } // Clear Grid int i; for (i = 0; i < GRID_SIZE; i++) for (int j = 0; j < GRID_SIZE; j++) { Density[i][j] = 0; GET_BIN(i, j).erase(GET_BIN(i, j).begin(), GET_BIN(i, j).end()); } // Compute fall off for (i = -RADIUS; i <= RADIUS; i++) for (int j = -RADIUS; j <= RADIUS; j++) { fall_off[i + RADIUS][j + RADIUS] = (float)((RADIUS - fabs((float)i)) / RADIUS) * (float)((RADIUS - fabs((float)j)) / RADIUS); } } /*************************************************** * Function: DensityGrid::GetDensity * * Description: Get_Density from density grid * **************************************************/ float DensityGrid::GetDensity(float Nx, float Ny, bool fineDensity) { deque::iterator BI; int x_grid, y_grid; float x_dist, y_dist, distance, density = 0; int boundary = 10; // boundary around plane /* Where to look */ x_grid = (int)((Nx + HALF_VIEW + .5) * VIEW_TO_GRID); y_grid = (int)((Ny + HALF_VIEW + .5) * VIEW_TO_GRID); // Check for edges of density grid (10000 is arbitrary high density) if (x_grid > GRID_SIZE - boundary || x_grid < boundary) { return 10000; } if (y_grid > GRID_SIZE - boundary || y_grid < boundary) { return 10000; } // Fine density? if (fineDensity) { // Go through nearest bins for (int i = y_grid - 1; i <= y_grid + 1; i++) for (int j = x_grid - 1; j <= x_grid + 1; j++) { // Look through bin and add fine repulsions for (BI = GET_BIN(i, j).begin(); BI != GET_BIN(i, j).end(); ++BI) { x_dist = Nx - (BI->x); y_dist = Ny - (BI->y); distance = x_dist * x_dist + y_dist * y_dist; density += 1e-4 / (distance + 1e-50); } } // Course density } else { // Add rough estimate density = Density[y_grid][x_grid]; density *= density; } return density; } /// Wrapper functions for the Add and subtract methods /// Nodes should all be passed by constant ref void DensityGrid::Add(Node &n, bool fineDensity) { if (fineDensity) { fineAdd(n); } else { Add(n); } } void DensityGrid::Subtract( Node &n, bool first_add, bool fine_first_add, bool fineDensity) { if ( fineDensity && !fine_first_add ) { fineSubtract (n); } else if ( !first_add ) { Subtract(n); } } /*************************************************** * Function: DensityGrid::Subtract * * Description: Subtract a node from density grid * **************************************************/ void DensityGrid::Subtract(Node &N) { int x_grid, y_grid, diam; float *den_ptr, *fall_ptr; /* Where to subtract */ x_grid = (int)((N.sub_x + HALF_VIEW + .5) * VIEW_TO_GRID); y_grid = (int)((N.sub_y + HALF_VIEW + .5) * VIEW_TO_GRID); x_grid -= RADIUS; y_grid -= RADIUS; diam = 2 * RADIUS; // check to see that we are inside grid if ( (x_grid >= GRID_SIZE) || (x_grid < 0) || (y_grid >= GRID_SIZE) || (y_grid < 0) ) { #ifdef MUSE_MPI MPI_Abort ( MPI_COMM_WORLD, 1 ); #else igraph_error("Exceeded density grid in DrL", __FILE__, __LINE__, IGRAPH_EDRL); return; #endif } /* Subtract density values */ den_ptr = &Density[y_grid][x_grid]; fall_ptr = &fall_off[0][0]; for (int i = 0; i <= diam; i++) { for (int j = 0; j <= diam; j++) { *den_ptr++ -= *fall_ptr++; } den_ptr += GRID_SIZE - (diam + 1); } } /*************************************************** * Function: DensityGrid::Add * * Description: Add a node to the density grid * **************************************************/ void DensityGrid::Add(Node &N) { int x_grid, y_grid, diam; float *den_ptr, *fall_ptr; /* Where to add */ x_grid = (int)((N.x + HALF_VIEW + .5) * VIEW_TO_GRID); y_grid = (int)((N.y + HALF_VIEW + .5) * VIEW_TO_GRID); N.sub_x = N.x; N.sub_y = N.y; x_grid -= RADIUS; y_grid -= RADIUS; diam = 2 * RADIUS; // check to see that we are inside grid if ( (x_grid >= GRID_SIZE) || (x_grid < 0) || (y_grid >= GRID_SIZE) || (y_grid < 0) ) { #ifdef MUSE_MPI MPI_Abort ( MPI_COMM_WORLD, 1 ); #else igraph_error("Exceeded density grid in DrL", __FILE__, __LINE__, IGRAPH_EDRL); return; #endif } /* Add density values */ den_ptr = &Density[y_grid][x_grid]; fall_ptr = &fall_off[0][0]; for (int i = 0; i <= diam; i++) { for (int j = 0; j <= diam; j++) { *den_ptr++ += *fall_ptr++; } den_ptr += GRID_SIZE - (diam + 1); } } /*************************************************** * Function: DensityGrid::fineSubtract * * Description: Subtract a node from bins * **************************************************/ void DensityGrid::fineSubtract(Node &N) { int x_grid, y_grid; /* Where to subtract */ x_grid = (int)((N.sub_x + HALF_VIEW + .5) * VIEW_TO_GRID); y_grid = (int)((N.sub_y + HALF_VIEW + .5) * VIEW_TO_GRID); GET_BIN(y_grid, x_grid).pop_front(); } /*************************************************** * Function: DensityGrid::fineAdd * * Description: Add a node to the bins * **************************************************/ void DensityGrid::fineAdd(Node &N) { int x_grid, y_grid; /* Where to add */ x_grid = (int)((N.x + HALF_VIEW + .5) * VIEW_TO_GRID); y_grid = (int)((N.y + HALF_VIEW + .5) * VIEW_TO_GRID); N.sub_x = N.x; N.sub_y = N.y; GET_BIN(y_grid, x_grid).push_back(N); } } // namespace drl python-igraph-0.8.0/vendor/source/igraph/src/iterators.c0000644000076500000240000016521413614300625023567 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2005-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_iterators.h" #include "igraph_memory.h" #include "igraph_random.h" #include "igraph_interface.h" #include "config.h" #include #include /** * \section about_iterators About selectors, iterators * * Everything about vertices and vertex selectors also applies * to edges and edge selectors unless explicitly noted otherwise. * * The vertex (and edge) selector notion was introduced in igraph 0.2. * It is a way to reference a sequence of vertices or edges * independently of the graph. * * While this might sound quite mysterious, it is actually very * simple. For example, all vertices of a graph can be selected by * \ref igraph_vs_all() and the graph independence means that * \ref igraph_vs_all() is not parametrized by a graph object. That is, * \ref igraph_vs_all() is the general \em concept of selecting all vertices * of a graph. A vertex selector is then a way to specify the class of vertices * to be visited. The selector might specify that all vertices of a graph or * all the neighbours of a vertex are to be visited. A vertex selector is a * way of saying that you want to visit a bunch of vertices, as opposed to a * vertex iterator which is a concrete plan for visiting each of the * chosen vertices of a specific graph. * * To determine the actual vertex IDs implied by a vertex selector, you * need to apply the concept of selecting vertices to a specific graph object. * This can be accomplished by instantiating a vertex iterator using a * specific vertex selection concept and a specific graph object. The notion * of vertex iterators can be thought of in the following way. Given a * specific graph object and the class of vertices to be visited, a vertex * iterator is a road map, plan or route for how to visit the chosen * vertices. * * Some vertex selectors have \em immediate versions. These have the * prefix \c igraph_vss instead of \c igraph_vs, e.g. \ref igraph_vss_all() * instead of \ref igraph_vs_all(). The immediate versions are to be used in * the parameter list of the igraph functions, such as \ref igraph_degree(). * These functions are not associated with any \type igraph_vs_t object, so * they have no separate constructors and destructors * (destroy functions). */ /** * \section about_vertex_selectors * * Vertex selectors are created by vertex selector constructors, * can be instantiated with \ref igraph_vit_create(), and are * destroyed with \ref igraph_vs_destroy(). */ /** * \function igraph_vs_all * \brief Vertex set, all vertices of a graph. * * \param vs Pointer to an uninitialized \type igraph_vs_t object. * \return Error code. * \sa \ref igraph_vss_all(), \ref igraph_vs_destroy() * * This selector includes all vertices of a given graph in * increasing vertex id order. * * * Time complexity: O(1). */ int igraph_vs_all(igraph_vs_t *vs) { vs->type = IGRAPH_VS_ALL; return 0; } /** * \function igraph_vss_all * \brief All vertices of a graph (immediate version). * * Immediate vertex selector for all vertices in a graph. It can * be used conveniently when some vertex property (eg. betweenness, * degree, etc.) should be calculated for all vertices. * * \return A vertex selector for all vertices in a graph. * \sa \ref igraph_vs_all() * * Time complexity: O(1). */ igraph_vs_t igraph_vss_all(void) { igraph_vs_t allvs; allvs.type = IGRAPH_VS_ALL; return allvs; } /** * \function igraph_vs_adj * \brief Adjacent vertices of a vertex. * * All neighboring vertices of a given vertex are selected by this * selector. The \c mode argument controls the type of the neighboring * vertices to be selected. The vertices are visited in increasing vertex * ID order, as of igraph version 0.4. * * \param vs Pointer to an uninitialized vertex selector object. * \param vid Vertex ID, the center of the neighborhood. * \param mode Decides the type of the neighborhood for directed * graphs. This parameter is ignored for undirected graphs. * Possible values: * \clist * \cli IGRAPH_OUT * All vertices to which there is a directed edge from \c vid. That * is, all the out-neighbors of \c vid. * \cli IGRAPH_IN * All vertices from which there is a directed edge to \c vid. In * other words, all the in-neighbors of \c vid. * \cli IGRAPH_ALL * All vertices to which or from which there is a directed edge * from/to \c vid. That is, all the neighbors of \c vid considered * as if the graph is undirected. * \endclist * \return Error code. * \sa \ref igraph_vs_destroy() * * Time complexity: O(1). */ int igraph_vs_adj(igraph_vs_t *vs, igraph_integer_t vid, igraph_neimode_t mode) { vs->type = IGRAPH_VS_ADJ; vs->data.adj.vid = vid; vs->data.adj.mode = mode; return 0; } /** * \function igraph_vs_nonadj * \brief Non-adjacent vertices of a vertex. * * All non-neighboring vertices of a given vertex. The \p mode * argument controls the type of neighboring vertices \em not to * select. Instead of selecting immediate neighbors of \c vid as is done by * \ref igraph_vs_adj(), the current function selects vertices that are \em not * immediate neighbors of \c vid. * * \param vs Pointer to an uninitialized vertex selector object. * \param vid Vertex ID, the \quote center \endquote of the * non-neighborhood. * \param mode The type of neighborhood not to select in directed * graphs. Possible values: * \clist * \cli IGRAPH_OUT * All vertices will be selected except those to which there is a * directed edge from \c vid. That is, we select all vertices * excluding the out-neighbors of \c vid. * \cli IGRAPH_IN * All vertices will be selected except those from which there is a * directed edge to \c vid. In other words, we select all vertices * but the in-neighbors of \c vid. * \cli IGRAPH_ALL * All vertices will be selected except those from or to which there * is a directed edge to or from \c vid. That is, we select all * vertices of \c vid except for its immediate neighbors. * \endclist * \return Error code. * \sa \ref igraph_vs_destroy() * * Time complexity: O(1). * * \example examples/simple/igraph_vs_nonadj.c */ int igraph_vs_nonadj(igraph_vs_t *vs, igraph_integer_t vid, igraph_neimode_t mode) { vs->type = IGRAPH_VS_NONADJ; vs->data.adj.vid = vid; vs->data.adj.mode = mode; return 0; } /** * \function igraph_vs_none * \brief Empty vertex set. * * Creates an empty vertex selector. * * \param vs Pointer to an uninitialized vertex selector object. * \return Error code. * \sa \ref igraph_vss_none(), \ref igraph_vs_destroy() * * Time complexity: O(1). */ int igraph_vs_none(igraph_vs_t *vs) { vs->type = IGRAPH_VS_NONE; return 0; } /** * \function igraph_vss_none * \brief Empty vertex set (immediate version). * * The immediate version of the empty vertex selector. * * \return An empty vertex selector. * \sa \ref igraph_vs_none() * * Time complexity: O(1). */ igraph_vs_t igraph_vss_none(void) { igraph_vs_t nonevs; nonevs.type = IGRAPH_VS_NONE; return nonevs; } /** * \function igraph_vs_1 * \brief Vertex set with a single vertex. * * This vertex selector selects a single vertex. * * \param vs Pointer to an uninitialized vertex selector object. * \param vid The vertex id to be selected. * \return Error Code. * \sa \ref igraph_vss_1(), \ref igraph_vs_destroy() * * Time complexity: O(1). */ int igraph_vs_1(igraph_vs_t *vs, igraph_integer_t vid) { vs->type = IGRAPH_VS_1; vs->data.vid = vid; return 0; } /** * \function igraph_vss_1 * \brief Vertex set with a single vertex (immediate version). * * The immediate version of the single-vertex selector. * * \param vid The vertex to be selected. * \return A vertex selector containing a single vertex. * \sa \ref igraph_vs_1() * * Time complexity: O(1). */ igraph_vs_t igraph_vss_1(igraph_integer_t vid) { igraph_vs_t onevs; onevs.type = IGRAPH_VS_1; onevs.data.vid = vid; return onevs; } /** * \function igraph_vs_vector * \brief Vertex set based on a vector. * * This function makes it possible to handle a \type vector_t * temporarily as a vertex selector. The vertex selector should be * thought of like a \em view to the vector. If you make changes to * the vector that also affects the vertex selector. Destroying the * vertex selector does not destroy the vector. (Of course.) Do not * destroy the vector before destroying the vertex selector, or you * might get strange behavior. * * \param vs Pointer to an uninitialized vertex selector. * \param v Pointer to a \type igraph_vector_t object. * \return Error code. * \sa \ref igraph_vss_vector(), \ref igraph_vs_destroy() * * Time complexity: O(1). * * \example examples/simple/igraph_vs_vector.c */ int igraph_vs_vector(igraph_vs_t *vs, const igraph_vector_t *v) { vs->type = IGRAPH_VS_VECTORPTR; vs->data.vecptr = v; return 0; } /** * \function igraph_vss_vector * \brief Vertex set based on a vector (immediate version). * * This is the immediate version of \ref igraph_vs_vector. * * \param v Pointer to a \type igraph_vector_t object. * \return A vertex selector object containing the vertices in the * vector. * \sa \ref igraph_vs_vector() * * Time complexity: O(1). */ igraph_vs_t igraph_vss_vector(const igraph_vector_t *v) { igraph_vs_t vecvs; vecvs.type = IGRAPH_VS_VECTORPTR; vecvs.data.vecptr = v; return vecvs; } /** * \function igraph_vs_vector_small * \brief Create a vertex set by giving its elements. * * This function can be used to create a vertex selector with a couple * of vertices. Do not forget to include a -1 after the * last vertex id. The behavior of the function is undefined if you * don't use a -1 properly. * * * Note that the vertex ids supplied will be parsed as * int's so you cannot supply arbitrarily large (too * large for int) vertex ids here. * * \param vs Pointer to an uninitialized vertex selector object. * \param ... Additional parameters, these will be the vertex ids to * be included in the vertex selector. Supply a -1 * after the last vertex id. * \return Error code. * \sa \ref igraph_vs_destroy() * * Time complexity: O(n), the number of vertex ids supplied. */ int igraph_vs_vector_small(igraph_vs_t *vs, ...) { va_list ap; long int i, n = 0; vs->type = IGRAPH_VS_VECTOR; vs->data.vecptr = igraph_Calloc(1, igraph_vector_t); if (vs->data.vecptr == 0) { IGRAPH_ERROR("Cannot create vertex selector", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (igraph_vector_t*)vs->data.vecptr); va_start(ap, vs); while (1) { int num = va_arg(ap, int); if (num == -1) { break; } n++; } va_end(ap); IGRAPH_VECTOR_INIT_FINALLY((igraph_vector_t*)vs->data.vecptr, n); va_start(ap, vs); for (i = 0; i < n; i++) { VECTOR(*vs->data.vecptr)[i] = (igraph_real_t) va_arg(ap, int); } va_end(ap); IGRAPH_FINALLY_CLEAN(2); return 0; } /** * \function igraph_vs_vector_copy * \brief Vertex set based on a vector, with copying. * * This function makes it possible to handle a \type vector_t * permanently as a vertex selector. The vertex selector creates a * copy of the original vector, so the vector can safely be destroyed * after creating the vertex selector. Changing the original vector * will not affect the vertex selector. The vertex selector is * responsible for deleting the copy made by itself. * * \param vs Pointer to an uninitialized vertex selector. * \param v Pointer to a \type igraph_vector_t object. * \return Error code. * \sa \ref igraph_vs_destroy() * * Time complexity: O(1). */ int igraph_vs_vector_copy(igraph_vs_t *vs, const igraph_vector_t *v) { vs->type = IGRAPH_VS_VECTOR; vs->data.vecptr = igraph_Calloc(1, igraph_vector_t); if (vs->data.vecptr == 0) { IGRAPH_ERROR("Cannot create vertex selector", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (igraph_vector_t*)vs->data.vecptr); IGRAPH_CHECK(igraph_vector_copy((igraph_vector_t*)vs->data.vecptr, v)); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_vs_seq * \brief Vertex set, an interval of vertices. * * Creates a vertex selector containing all vertices with vertex id * equal to or bigger than \c from and equal to or smaller than \c * to. * * \param vs Pointer to an uninitialized vertex selector object. * \param from The first vertex id to be included in the vertex * selector. * \param to The last vertex id to be included in the vertex * selector. * \return Error code. * \sa \ref igraph_vss_seq(), \ref igraph_vs_destroy() * * Time complexity: O(1). * * \example examples/simple/igraph_vs_seq.c */ int igraph_vs_seq(igraph_vs_t *vs, igraph_integer_t from, igraph_integer_t to) { vs->type = IGRAPH_VS_SEQ; vs->data.seq.from = from; vs->data.seq.to = to + 1; return 0; } /** * \function igraph_vss_seq * \brief An interval of vertices (immediate version). * * The immediate version of \ref igraph_vs_seq(). * * \param from The first vertex id to be included in the vertex * selector. * \param to The last vertex id to be included in the vertex * selector. * \return Error code. * \sa \ref igraph_vs_seq() * * Time complexity: O(1). */ igraph_vs_t igraph_vss_seq(igraph_integer_t from, igraph_integer_t to) { igraph_vs_t vs; vs.type = IGRAPH_VS_SEQ; vs.data.seq.from = from; vs.data.seq.to = to + 1; return vs; } /** * \function igraph_vs_destroy * \brief Destroy a vertex set. * * This function should be called for all vertex selectors when they * are not needed. The memory allocated for the vertex selector will * be deallocated. Do not call this function on vertex selectors * created with the immediate versions of the vertex selector * constructors (starting with igraph_vss). * * \param vs Pointer to a vertex selector object. * * Time complexity: operating system dependent, usually O(1). */ void igraph_vs_destroy(igraph_vs_t *vs) { switch (vs->type) { case IGRAPH_VS_ALL: case IGRAPH_VS_ADJ: case IGRAPH_VS_NONE: case IGRAPH_VS_1: case IGRAPH_VS_VECTORPTR: case IGRAPH_VS_SEQ: case IGRAPH_VS_NONADJ: break; case IGRAPH_VS_VECTOR: igraph_vector_destroy((igraph_vector_t*)vs->data.vecptr); igraph_Free(vs->data.vecptr); break; default: break; } } /** * \function igraph_vs_is_all * \brief Check whether all vertices are included. * * This function checks whether the vertex selector object was created * by \ref igraph_vs_all() or \ref igraph_vss_all(). Note that the * vertex selector might contain all vertices in a given graph but if * it wasn't created by the two constructors mentioned here the return * value will be FALSE. * * \param vs Pointer to a vertex selector object. * \return TRUE (1) if the vertex selector contains all vertices and * FALSE (0) otherwise. * * Time complexity: O(1). */ igraph_bool_t igraph_vs_is_all(const igraph_vs_t *vs) { return vs->type == IGRAPH_VS_ALL; } int igraph_vs_as_vector(const igraph_t *graph, igraph_vs_t vs, igraph_vector_t *v) { igraph_vit_t vit; IGRAPH_CHECK(igraph_vit_create(graph, vs, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); IGRAPH_CHECK(igraph_vit_as_vector(&vit, v)); igraph_vit_destroy(&vit); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_vs_copy * \brief Creates a copy of a vertex selector. * \param src The selector being copied. * \param dest An uninitialized selector that will contain the copy. */ int igraph_vs_copy(igraph_vs_t* dest, const igraph_vs_t* src) { memcpy(dest, src, sizeof(igraph_vs_t)); switch (dest->type) { case IGRAPH_VS_VECTOR: dest->data.vecptr = igraph_Calloc(1, igraph_vector_t); if (!dest->data.vecptr) { IGRAPH_ERROR("Cannot copy vertex selector", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_copy((igraph_vector_t*)dest->data.vecptr, (igraph_vector_t*)src->data.vecptr)); break; } return 0; } /** * \function igraph_vs_type * \brief Returns the type of the vertex selector. */ int igraph_vs_type(const igraph_vs_t *vs) { return vs->type; } /** * \function igraph_vs_size * \brief Returns the size of the vertex selector. * * The size of the vertex selector is the number of vertices it will * yield when it is iterated over. * * \param graph The graph over which we will iterate. * \param result The result will be returned here. */ int igraph_vs_size(const igraph_t *graph, const igraph_vs_t *vs, igraph_integer_t *result) { igraph_vector_t vec; igraph_bool_t *seen; long i; switch (vs->type) { case IGRAPH_VS_NONE: *result = 0; return 0; case IGRAPH_VS_1: *result = 0; if (vs->data.vid < igraph_vcount(graph) && vs->data.vid >= 0) { *result = 1; } return 0; case IGRAPH_VS_SEQ: *result = vs->data.seq.to - vs->data.seq.from; return 0; case IGRAPH_VS_ALL: *result = igraph_vcount(graph); return 0; case IGRAPH_VS_ADJ: IGRAPH_VECTOR_INIT_FINALLY(&vec, 0); IGRAPH_CHECK(igraph_neighbors(graph, &vec, vs->data.adj.vid, vs->data.adj.mode)); *result = (igraph_integer_t) igraph_vector_size(&vec); igraph_vector_destroy(&vec); IGRAPH_FINALLY_CLEAN(1); return 0; case IGRAPH_VS_NONADJ: IGRAPH_VECTOR_INIT_FINALLY(&vec, 0); IGRAPH_CHECK(igraph_neighbors(graph, &vec, vs->data.adj.vid, vs->data.adj.mode)); *result = igraph_vcount(graph); seen = igraph_Calloc(*result, igraph_bool_t); if (seen == 0) { IGRAPH_ERROR("Cannot calculate selector length", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, seen); for (i = 0; i < igraph_vector_size(&vec); i++) { if (!seen[(long int)VECTOR(vec)[i]]) { (*result)--; seen[(long int)VECTOR(vec)[i]] = 1; } } igraph_free(seen); igraph_vector_destroy(&vec); IGRAPH_FINALLY_CLEAN(2); return 0; case IGRAPH_VS_VECTOR: case IGRAPH_VS_VECTORPTR: *result = (igraph_integer_t) igraph_vector_size((igraph_vector_t*)vs->data.vecptr); return 0; } IGRAPH_ERROR("Cannot calculate selector length, invalid selector type", IGRAPH_EINVAL); } /***************************************************/ /** * \function igraph_vit_create * \brief Creates a vertex iterator from a vertex selector. * * This function instantiates a vertex selector object with a given * graph. This is the step when the actual vertex ids are created from * the \em logical notion of the vertex selector based on the graph. * Eg. a vertex selector created with \ref igraph_vs_all() contains * knowledge that \em all vertices are included in a (yet indefinite) * graph. When instantiating it a vertex iterator object is created, * this contains the actual vertex ids in the graph supplied as a * parameter. * * * The same vertex selector object can be used to instantiate any * number vertex iterators. * * \param graph An \type igraph_t object, a graph. * \param vs A vertex selector object. * \param vit Pointer to an uninitialized vertex iterator object. * \return Error code. * \sa \ref igraph_vit_destroy(). * * Time complexity: it depends on the vertex selector type. O(1) for * vertex selectors created with \ref igraph_vs_all(), \ref * igraph_vs_none(), \ref igraph_vs_1, \ref igraph_vs_vector, \ref * igraph_vs_seq(), \ref igraph_vs_vector(), \ref * igraph_vs_vector_small(). O(d) for \ref igraph_vs_adj(), d is the * number of vertex ids to be included in the iterator. O(|V|) for * \ref igraph_vs_nonadj(), |V| is the number of vertices in the graph. */ int igraph_vit_create(const igraph_t *graph, igraph_vs_t vs, igraph_vit_t *vit) { igraph_vector_t vec; igraph_bool_t *seen; long int i, j, n; switch (vs.type) { case IGRAPH_VS_ALL: vit->type = IGRAPH_VIT_SEQ; vit->pos = 0; vit->start = 0; vit->end = igraph_vcount(graph); break; case IGRAPH_VS_ADJ: vit->type = IGRAPH_VIT_VECTOR; vit->pos = 0; vit->start = 0; vit->vec = igraph_Calloc(1, igraph_vector_t); if (vit->vec == 0) { IGRAPH_ERROR("Cannot create iterator", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (igraph_vector_t*) vit->vec); IGRAPH_VECTOR_INIT_FINALLY((igraph_vector_t*)vit->vec, 0); IGRAPH_CHECK(igraph_neighbors(graph, (igraph_vector_t*)vit->vec, vs.data.adj.vid, vs.data.adj.mode)); vit->end = igraph_vector_size(vit->vec); IGRAPH_FINALLY_CLEAN(2); break; case IGRAPH_VS_NONADJ: vit->type = IGRAPH_VIT_VECTOR; vit->pos = 0; vit->start = 0; vit->vec = igraph_Calloc(1, igraph_vector_t); if (vit->vec == 0) { IGRAPH_ERROR("Cannot create iterator", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (igraph_vector_t*) vit->vec); IGRAPH_VECTOR_INIT_FINALLY((igraph_vector_t *) vit->vec, 0); IGRAPH_VECTOR_INIT_FINALLY(&vec, 0); IGRAPH_CHECK(igraph_neighbors(graph, &vec, vs.data.adj.vid, vs.data.adj.mode)); n = igraph_vcount(graph); seen = igraph_Calloc(n, igraph_bool_t); if (seen == 0) { IGRAPH_ERROR("Cannot create iterator", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, seen); for (i = 0; i < igraph_vector_size(&vec); i++) { if (! seen [ (long int) VECTOR(vec)[i] ] ) { n--; seen[ (long int) VECTOR(vec)[i] ] = 1; } } IGRAPH_CHECK(igraph_vector_resize((igraph_vector_t*)vit->vec, n)); for (i = 0, j = 0; j < n; i++) { if (!seen[i]) { VECTOR(*vit->vec)[j++] = i; } } igraph_Free(seen); igraph_vector_destroy(&vec); vit->end = n; IGRAPH_FINALLY_CLEAN(4); break; case IGRAPH_VS_NONE: vit->type = IGRAPH_VIT_SEQ; vit->pos = 0; vit->start = 0; vit->end = 0; break; case IGRAPH_VS_1: vit->type = IGRAPH_VIT_SEQ; vit->pos = vs.data.vid; vit->start = vs.data.vid; vit->end = vs.data.vid + 1; if (vit->pos >= igraph_vcount(graph)) { IGRAPH_ERROR("Cannot create iterator, invalid vertex id", IGRAPH_EINVVID); } break; case IGRAPH_VS_VECTORPTR: case IGRAPH_VS_VECTOR: vit->type = IGRAPH_VIT_VECTORPTR; vit->pos = 0; vit->start = 0; vit->vec = vs.data.vecptr; vit->end = igraph_vector_size(vit->vec); if (!igraph_vector_isininterval(vit->vec, 0, igraph_vcount(graph) - 1)) { IGRAPH_ERROR("Cannot create iterator, invalid vertex id", IGRAPH_EINVVID); } break; case IGRAPH_VS_SEQ: vit->type = IGRAPH_VIT_SEQ; vit->pos = vs.data.seq.from; vit->start = vs.data.seq.from; vit->end = vs.data.seq.to; break; default: IGRAPH_ERROR("Cannot create iterator, invalid selector", IGRAPH_EINVAL); break; } return 0; } /** * \function igraph_vit_destroy * \brief Destroys a vertex iterator. * * * Deallocates memory allocated for a vertex iterator. * * \param vit Pointer to an initialized vertex iterator object. * \sa \ref igraph_vit_create() * * Time complexity: operating system dependent, usually O(1). */ void igraph_vit_destroy(const igraph_vit_t *vit) { switch (vit->type) { case IGRAPH_VIT_SEQ: case IGRAPH_VIT_VECTORPTR: break; case IGRAPH_VIT_VECTOR: igraph_vector_destroy((igraph_vector_t*)vit->vec); igraph_free((igraph_vector_t*)vit->vec); break; default: /* IGRAPH_ERROR("Cannot destroy iterator, unknown type", IGRAPH_EINVAL); */ break; } } int igraph_vit_as_vector(const igraph_vit_t *vit, igraph_vector_t *v) { long int i; IGRAPH_CHECK(igraph_vector_resize(v, IGRAPH_VIT_SIZE(*vit))); switch (vit->type) { case IGRAPH_VIT_SEQ: for (i = 0; i < IGRAPH_VIT_SIZE(*vit); i++) { VECTOR(*v)[i] = vit->start + i; } break; case IGRAPH_VIT_VECTOR: case IGRAPH_VIT_VECTORPTR: for (i = 0; i < IGRAPH_VIT_SIZE(*vit); i++) { VECTOR(*v)[i] = VECTOR(*vit->vec)[i]; } break; default: IGRAPH_ERROR("Cannot convert to vector, unknown iterator type", IGRAPH_EINVAL); break; } return 0; } /*******************************************************/ /** * \function igraph_es_all * \brief Edge set, all edges. * * \param es Pointer to an uninitialized edge selector object. * \param order Constant giving the order in which the edges will be * included in the selector. Possible values: * \c IGRAPH_EDGEORDER_ID, edge id order. * \c IGRAPH_EDGEORDER_FROM, vertex id order, the id of the * \em source vertex counts for directed graphs. The order * of the incident edges of a given vertex is arbitrary. * \c IGRAPH_EDGEORDER_TO, vertex id order, the id of the \em * target vertex counts for directed graphs. The order * of the incident edges of a given vertex is arbitrary. * For undirected graph the latter two is the same. * \return Error code. * \sa \ref igraph_ess_all(), \ref igraph_es_destroy() * * Time complexity: O(1). */ int igraph_es_all(igraph_es_t *es, igraph_edgeorder_type_t order) { switch (order) { case IGRAPH_EDGEORDER_ID: es->type = IGRAPH_ES_ALL; break; case IGRAPH_EDGEORDER_FROM: es->type = IGRAPH_ES_ALLFROM; break; case IGRAPH_EDGEORDER_TO: es->type = IGRAPH_ES_ALLTO; break; default: IGRAPH_ERROR("Invalid edge order, cannot create selector", IGRAPH_EINVAL); break; } return 0; } /** * \function igraph_ess_all * \brief Edge set, all edges (immediate version) * * The immediate version of the all-vertices selector. * * \param order Constant giving the order of the edges in the edge * selector. See \ref igraph_es_all() for the possible values. * \return The edge selector. * \sa \ref igraph_es_all() * * Time complexity: O(1). */ igraph_es_t igraph_ess_all(igraph_edgeorder_type_t order) { igraph_es_t es; igraph_es_all(&es, order); /* cannot fail */ return es; } /** * \function igraph_es_adj * \brief Adjacent edges of a vertex. * * This function was superseded by \ref igraph_es_incident() in igraph 0.6. * Please use \ref igraph_es_incident() instead of this function. * * * Deprecated in version 0.6. */ int igraph_es_adj(igraph_es_t *es, igraph_integer_t vid, igraph_neimode_t mode) { IGRAPH_WARNING("igraph_es_adj is deprecated, use igraph_es_incident"); return igraph_es_incident(es, vid, mode); } /** * \function igraph_es_incident * \brief Edges incident on a given vertex. * * \param es Pointer to an uninitialized edge selector object. * \param vid Vertex id, of which the incident edges will be * selected. * \param mode Constant giving the type of the incident edges to * select. This is ignored for undirected graphs. Possible values: * \c IGRAPH_OUT, outgoing edges; * \c IGRAPH_IN, incoming edges; * \c IGRAPH_ALL, all edges. * \return Error code. * \sa \ref igraph_es_destroy() * * Time complexity: O(1). * * \example examples/simple/igraph_es_adj.c */ int igraph_es_incident(igraph_es_t *es, igraph_integer_t vid, igraph_neimode_t mode) { es->type = IGRAPH_ES_INCIDENT; es->data.incident.vid = vid; es->data.incident.mode = mode; return 0; } /** * \function igraph_es_none * \brief Empty edge selector. * * \param es Pointer to an uninitialized edge selector object to * initialize. * \return Error code. * \sa \ref igraph_ess_none(), \ref igraph_es_destroy() * * Time complexity: O(1). */ int igraph_es_none(igraph_es_t *es) { es->type = IGRAPH_ES_NONE; return 0; } /** * \function igraph_ess_none * \brief Immediate empty edge selector. * * * Immediate version of the empty edge selector. * * \return Initialized empty edge selector. * \sa \ref igraph_es_none() * * Time complexity: O(1). */ igraph_es_t igraph_ess_none(void) { igraph_es_t es; es.type = IGRAPH_ES_NONE; return es; } /** * \function igraph_es_1 * \brief Edge selector containing a single edge. * * \param es Pointer to an uninitialized edge selector object. * \param eid Edge id of the edge to select. * \return Error code. * \sa \ref igraph_ess_1(), \ref igraph_es_destroy() * * Time complexity: O(1). */ int igraph_es_1(igraph_es_t *es, igraph_integer_t eid) { es->type = IGRAPH_ES_1; es->data.eid = eid; return 0; } /** * \function igraph_ess_1 * \brief Immediate version of the single edge edge selector. * * \param eid The id of the edge. * \return The edge selector. * \sa \ref igraph_es_1() * * Time complexity: O(1). */ igraph_es_t igraph_ess_1(igraph_integer_t eid) { igraph_es_t es; es.type = IGRAPH_ES_1; es.data.eid = eid; return es; } /** * \function igraph_es_vector * \brief Handle a vector as an edge selector. * * * Creates an edge selector which serves as a view to a vector * containing edge ids. Do not destroy the vector before destroying * the view. * * Many views can be created to the same vector. * * \param es Pointer to an uninitialized edge selector. * \param v Vector containing edge ids. * \return Error code. * \sa \ref igraph_ess_vector(), \ref igraph_es_destroy() * * Time complexity: O(1). */ int igraph_es_vector(igraph_es_t *es, const igraph_vector_t *v) { es->type = IGRAPH_ES_VECTORPTR; es->data.vecptr = v; return 0; } /** * \function igraph_es_vector_copy * \brief Edge set, based on a vector, with copying. * * * This function makes it possible to handle a \type vector_t * permanently as an edge selector. The edge selector creates a * copy of the original vector, so the vector can safely be destroyed * after creating the edge selector. Changing the original vector * will not affect the edge selector. The edge selector is * responsible for deleting the copy made by itself. * * \param es Pointer to an uninitialized edge selector. * \param v Pointer to a \type igraph_vector_t object. * \return Error code. * \sa \ref igraph_es_destroy() * * Time complexity: O(1). */ int igraph_es_vector_copy(igraph_es_t *es, const igraph_vector_t *v) { es->type = IGRAPH_ES_VECTOR; es->data.vecptr = igraph_Calloc(1, igraph_vector_t); if (es->data.vecptr == 0) { IGRAPH_ERROR("Cannot create edge selector", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (igraph_vector_t*)es->data.vecptr); IGRAPH_CHECK(igraph_vector_copy((igraph_vector_t*)es->data.vecptr, v)); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_ess_vector * \brief Immediate vector view edge selector. * * * This is the immediate version of the vector of edge ids edge * selector. * * \param v The vector of edge ids. * \return Edge selector, initialized. * \sa \ref igraph_es_vector() * * Time complexity: O(1). */ igraph_es_t igraph_ess_vector(const igraph_vector_t *v) { igraph_es_t es; es.type = IGRAPH_ES_VECTORPTR; es.data.vecptr = v; return es; } /** * \function igraph_es_fromto * \brief Edge selector, all edges between two vertex sets. * * * This function is not implemented yet. * * \param es Pointer to an uninitialized edge selector. * \param from Vertex selector, their outgoing edges will be * selected. * \param to Vertex selector, their incoming edges will be selected * from the previous selection. * \return Error code. * \sa \ref igraph_es_destroy() * * Time complexity: O(1). * * \example examples/simple/igraph_es_fromto.c */ int igraph_es_fromto(igraph_es_t *es, igraph_vs_t from, igraph_vs_t to) { IGRAPH_UNUSED(es); IGRAPH_UNUSED(from); IGRAPH_UNUSED(to); IGRAPH_ERROR("igraph_es_fromto not implemented yet", IGRAPH_UNIMPLEMENTED); /* TODO */ return 0; } /** * \function igraph_es_seq * \brief Edge selector, a sequence of edge ids. * * All edge ids between from and to will be * included in the edge selection. * * \param es Pointer to an uninitialized edge selector object. * \param from The first edge id to be included. * \param to The last edge id to be included. * \return Error code. * \sa \ref igraph_ess_seq(), \ref igraph_es_destroy() * * Time complexity: O(1). */ int igraph_es_seq(igraph_es_t *es, igraph_integer_t from, igraph_integer_t to) { es->type = IGRAPH_ES_SEQ; es->data.seq.from = from; es->data.seq.to = to; return 0; } /** * \function igraph_ess_seq * \brief Immediate version of the sequence edge selector. * * \param from The first edge id to include. * \param to The last edge id to include. * \return The initialized edge selector. * \sa \ref igraph_es_seq() * * Time complexity: O(1). */ igraph_es_t igraph_ess_seq(igraph_integer_t from, igraph_integer_t to) { igraph_es_t es; es.type = IGRAPH_ES_SEQ; es.data.seq.from = from; es.data.seq.to = to; return es; } /** * \function igraph_es_pairs * \brief Edge selector, multiple edges defined by their endpoints in a vector. * * The edges between the given pairs of vertices will be included in the * edge selection. The vertex pairs must be defined in the vector v, * the first element of the vector is the first vertex of the first edge * to be selected, the second element is the second vertex of the first * edge, the third element is the first vertex of the second edge and * so on. * * \param es Pointer to an uninitialized edge selector object. * \param v The vector containing the endpoints of the edges. * \param directed Whether the graph is directed or not. * \return Error code. * \sa \ref igraph_es_pairs_small(), \ref igraph_es_destroy() * * Time complexity: O(n), the number of edges being selected. * * \example examples/simple/igraph_es_pairs.c */ int igraph_es_pairs(igraph_es_t *es, const igraph_vector_t *v, igraph_bool_t directed) { es->type = IGRAPH_ES_PAIRS; es->data.path.mode = directed; es->data.path.ptr = igraph_Calloc(1, igraph_vector_t); if (es->data.path.ptr == 0) { IGRAPH_ERROR("Cannot create edge selector", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (igraph_vector_t*) es->data.path.ptr); IGRAPH_CHECK(igraph_vector_copy((igraph_vector_t*) es->data.path.ptr, v)); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_es_pairs_small * \brief Edge selector, multiple edges defined by their endpoints as arguments. * * The edges between the given pairs of vertices will be included in the * edge selection. The vertex pairs must be given as the arguments of the * function call, the third argument is the first vertex of the first edge, * the fourth argument is the second vertex of the first edge, the fifth * is the first vertex of the second edge and so on. The last element of the * argument list must be -1 to denote the end of the argument list. * * \param es Pointer to an uninitialized edge selector object. * \param directed Whether the graph is directed or not. * \return Error code. * \sa \ref igraph_es_pairs(), \ref igraph_es_destroy() * * Time complexity: O(n), the number of edges being selected. */ int igraph_es_pairs_small(igraph_es_t *es, igraph_bool_t directed, ...) { va_list ap; long int i, n = 0; es->type = IGRAPH_ES_PAIRS; es->data.path.mode = directed; es->data.path.ptr = igraph_Calloc(1, igraph_vector_t); if (es->data.path.ptr == 0) { IGRAPH_ERROR("Cannot create edge selector", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (igraph_vector_t*)es->data.path.ptr); va_start(ap, directed); while (1) { int num = va_arg(ap, int); if (num == -1) { break; } n++; } va_end(ap); IGRAPH_VECTOR_INIT_FINALLY( (igraph_vector_t*) es->data.path.ptr, n); va_start(ap, directed); for (i = 0; i < n; i++) { VECTOR(*es->data.path.ptr)[i] = (igraph_real_t) va_arg(ap, int); } va_end(ap); IGRAPH_FINALLY_CLEAN(2); return 0; } int igraph_es_multipairs(igraph_es_t *es, const igraph_vector_t *v, igraph_bool_t directed) { es->type = IGRAPH_ES_MULTIPAIRS; es->data.path.mode = directed; es->data.path.ptr = igraph_Calloc(1, igraph_vector_t); if (es->data.path.ptr == 0) { IGRAPH_ERROR("Cannot create edge selector", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (igraph_vector_t*) es->data.path.ptr); IGRAPH_CHECK(igraph_vector_copy((igraph_vector_t*) es->data.path.ptr, v)); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \example examples/simple/igraph_es_path.c */ int igraph_es_path(igraph_es_t *es, const igraph_vector_t *v, igraph_bool_t directed) { es->type = IGRAPH_ES_PATH; es->data.path.mode = directed; es->data.path.ptr = igraph_Calloc(1, igraph_vector_t); if (es->data.path.ptr == 0) { IGRAPH_ERROR("Cannot create edge selector", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (igraph_vector_t*) es->data.path.ptr); IGRAPH_CHECK(igraph_vector_copy((igraph_vector_t*) es->data.path.ptr, v)); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_es_path_small(igraph_es_t *es, igraph_bool_t directed, ...) { va_list ap; long int i, n = 0; es->type = IGRAPH_ES_PATH; es->data.path.mode = directed; es->data.path.ptr = igraph_Calloc(1, igraph_vector_t); if (es->data.path.ptr == 0) { IGRAPH_ERROR("Cannot create edge selector", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (igraph_vector_t*)es->data.path.ptr); va_start(ap, directed); while (1) { int num = va_arg(ap, int); if (num == -1) { break; } n++; } va_end(ap); IGRAPH_VECTOR_INIT_FINALLY( (igraph_vector_t*) es->data.path.ptr, n); va_start(ap, directed); for (i = 0; i < n; i++) { VECTOR(*es->data.path.ptr)[i] = (igraph_real_t) va_arg(ap, int); } va_end(ap); IGRAPH_FINALLY_CLEAN(2); return 0; } /** * \function igraph_es_destroy * \brief Destroys an edge selector object. * * * Call this function on an edge selector when it is not needed any * more. Do \em not call this function on edge selectors created by * immediate constructors, those don't need to be destroyed. * * \param es Pointer to an edge selector object. * * Time complexity: operating system dependent, usually O(1). */ void igraph_es_destroy(igraph_es_t *es) { switch (es->type) { case IGRAPH_ES_ALL: case IGRAPH_ES_ALLFROM: case IGRAPH_ES_ALLTO: case IGRAPH_ES_INCIDENT: case IGRAPH_ES_NONE: case IGRAPH_ES_1: case IGRAPH_ES_VECTORPTR: case IGRAPH_ES_SEQ: break; case IGRAPH_ES_VECTOR: igraph_vector_destroy((igraph_vector_t*)es->data.vecptr); igraph_Free(es->data.vecptr); break; case IGRAPH_ES_PAIRS: case IGRAPH_ES_PATH: case IGRAPH_ES_MULTIPAIRS: igraph_vector_destroy((igraph_vector_t*)es->data.path.ptr); igraph_Free(es->data.path.ptr); break; default: break; } } /** * \function igraph_es_is_all * \brief Check whether an edge selector includes all edges. * * \param es Pointer to an edge selector object. * \return TRUE (1) if es was created with \ref * igraph_es_all() or \ref igraph_ess_all(), and FALSE (0) otherwise. * * Time complexity: O(1). */ igraph_bool_t igraph_es_is_all(const igraph_es_t *es) { return es->type == IGRAPH_ES_ALL; } /** * \function igraph_es_copy * \brief Creates a copy of an edge selector. * \param src The selector being copied. * \param dest An uninitialized selector that will contain the copy. * \sa \ref igraph_es_destroy() */ int igraph_es_copy(igraph_es_t* dest, const igraph_es_t* src) { memcpy(dest, src, sizeof(igraph_es_t)); switch (dest->type) { case IGRAPH_ES_VECTOR: dest->data.vecptr = igraph_Calloc(1, igraph_vector_t); if (!dest->data.vecptr) { IGRAPH_ERROR("Cannot copy edge selector", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_copy((igraph_vector_t*)dest->data.vecptr, (igraph_vector_t*)src->data.vecptr)); break; case IGRAPH_ES_PATH: case IGRAPH_ES_PAIRS: case IGRAPH_ES_MULTIPAIRS: dest->data.path.ptr = igraph_Calloc(1, igraph_vector_t); if (!dest->data.path.ptr) { IGRAPH_ERROR("Cannot copy edge selector", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_copy((igraph_vector_t*)dest->data.path.ptr, (igraph_vector_t*)src->data.path.ptr)); break; } return 0; } int igraph_es_as_vector(const igraph_t *graph, igraph_es_t es, igraph_vector_t *v) { igraph_eit_t eit; IGRAPH_CHECK(igraph_eit_create(graph, es, &eit)); IGRAPH_FINALLY(igraph_eit_destroy, &eit); IGRAPH_CHECK(igraph_eit_as_vector(&eit, v)); igraph_eit_destroy(&eit); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_es_type * \brief Returns the type of the edge selector. */ int igraph_es_type(const igraph_es_t *es) { return es->type; } int igraph_i_es_pairs_size(const igraph_t *graph, const igraph_es_t *es, igraph_integer_t *result); int igraph_i_es_path_size(const igraph_t *graph, const igraph_es_t *es, igraph_integer_t *result); int igraph_i_es_multipairs_size(const igraph_t *graph, const igraph_es_t *es, igraph_integer_t *result); /** * \function igraph_es_size * \brief Returns the size of the edge selector. * * The size of the edge selector is the number of edges it will * yield when it is iterated over. * * \param graph The graph over which we will iterate. * \param result The result will be returned here. */ int igraph_es_size(const igraph_t *graph, const igraph_es_t *es, igraph_integer_t *result) { igraph_vector_t v; switch (es->type) { case IGRAPH_ES_ALL: *result = igraph_ecount(graph); return 0; case IGRAPH_ES_ALLFROM: *result = igraph_ecount(graph); return 0; case IGRAPH_ES_ALLTO: *result = igraph_ecount(graph); return 0; case IGRAPH_ES_INCIDENT: IGRAPH_VECTOR_INIT_FINALLY(&v, 0); IGRAPH_CHECK(igraph_incident(graph, &v, es->data.incident.vid, es->data.incident.mode)); *result = (igraph_integer_t) igraph_vector_size(&v); igraph_vector_destroy(&v); IGRAPH_FINALLY_CLEAN(1); return 0; case IGRAPH_ES_NONE: *result = 0; return 0; case IGRAPH_ES_1: if (es->data.eid < igraph_ecount(graph) && es->data.eid >= 0) { *result = 1; } else { *result = 0; } return 0; case IGRAPH_ES_VECTOR: case IGRAPH_ES_VECTORPTR: *result = (igraph_integer_t) igraph_vector_size((igraph_vector_t*)es->data.vecptr); return 0; case IGRAPH_ES_SEQ: *result = es->data.seq.to - es->data.seq.from; return 0; case IGRAPH_ES_PAIRS: IGRAPH_CHECK(igraph_i_es_pairs_size(graph, es, result)); return 0; case IGRAPH_ES_PATH: IGRAPH_CHECK(igraph_i_es_path_size(graph, es, result)); return 0; case IGRAPH_ES_MULTIPAIRS: IGRAPH_CHECK(igraph_i_es_multipairs_size(graph, es, result)); return 0; default: IGRAPH_ERROR("Cannot calculate selector length, invalid selector type", IGRAPH_EINVAL); } return 0; } int igraph_i_es_pairs_size(const igraph_t *graph, const igraph_es_t *es, igraph_integer_t *result) { long int n = igraph_vector_size(es->data.path.ptr); long int no_of_nodes = igraph_vcount(graph); long int i; if (n % 2 != 0) { IGRAPH_ERROR("Cannot calculate edge selector length from odd number of vertices", IGRAPH_EINVAL); } if (!igraph_vector_isininterval(es->data.path.ptr, 0, no_of_nodes - 1)) { IGRAPH_ERROR("Cannot calculate edge selector length", IGRAPH_EINVVID); } *result = (igraph_integer_t) (n / 2); /* Check for the existence of all edges */ for (i = 0; i < *result; i++) { long int from = (long int) VECTOR(*es->data.path.ptr)[2 * i]; long int to = (long int) VECTOR(*es->data.path.ptr)[2 * i + 1]; igraph_integer_t eid; IGRAPH_CHECK(igraph_get_eid(graph, &eid, (igraph_integer_t) from, (igraph_integer_t) to, es->data.path.mode, /*error=*/ 1)); } return 0; } int igraph_i_es_path_size(const igraph_t *graph, const igraph_es_t *es, igraph_integer_t *result) { long int n = igraph_vector_size(es->data.path.ptr); long int no_of_nodes = igraph_vcount(graph); long int i; if (!igraph_vector_isininterval(es->data.path.ptr, 0, no_of_nodes - 1)) { IGRAPH_ERROR("Cannot calculate selector length", IGRAPH_EINVVID); } if (n <= 1) { *result = 0; } else { *result = (igraph_integer_t) (n - 1); } for (i = 0; i < *result; i++) { long int from = (long int) VECTOR(*es->data.path.ptr)[i]; long int to = (long int) VECTOR(*es->data.path.ptr)[i + 1]; igraph_integer_t eid; IGRAPH_CHECK(igraph_get_eid(graph, &eid, (igraph_integer_t) from, (igraph_integer_t) to, es->data.path.mode, /*error=*/ 1)); } return 0; } int igraph_i_es_multipairs_size(const igraph_t *graph, const igraph_es_t *es, igraph_integer_t *result) { IGRAPH_UNUSED(graph); IGRAPH_UNUSED(es); IGRAPH_UNUSED(result); IGRAPH_ERROR("Cannot calculate edge selector length", IGRAPH_UNIMPLEMENTED); } /**************************************************/ int igraph_i_eit_create_allfromto(const igraph_t *graph, igraph_eit_t *eit, igraph_neimode_t mode); int igraph_i_eit_pairs(const igraph_t *graph, igraph_es_t es, igraph_eit_t *eit); int igraph_i_eit_multipairs(const igraph_t *graph, igraph_es_t es, igraph_eit_t *eit); int igraph_i_eit_path(const igraph_t *graph, igraph_es_t es, igraph_eit_t *eit); int igraph_i_eit_create_allfromto(const igraph_t *graph, igraph_eit_t *eit, igraph_neimode_t mode) { igraph_vector_t *vec; long int no_of_nodes = igraph_vcount(graph); long int i; vec = igraph_Calloc(1, igraph_vector_t); if (vec == 0) { IGRAPH_ERROR("Cannot create edge iterator", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, vec); IGRAPH_VECTOR_INIT_FINALLY(vec, 0); IGRAPH_CHECK(igraph_vector_reserve(vec, igraph_ecount(graph))); if (igraph_is_directed(graph)) { igraph_vector_t adj; IGRAPH_VECTOR_INIT_FINALLY(&adj, 0); for (i = 0; i < no_of_nodes; i++) { igraph_incident(graph, &adj, (igraph_integer_t) i, mode); igraph_vector_append(vec, &adj); } igraph_vector_destroy(&adj); IGRAPH_FINALLY_CLEAN(1); } else { igraph_vector_t adj; igraph_bool_t *added; long int j; IGRAPH_VECTOR_INIT_FINALLY(&adj, 0); added = igraph_Calloc(igraph_ecount(graph), igraph_bool_t); if (added == 0) { IGRAPH_ERROR("Cannot create edge iterator", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, added); for (i = 0; i < no_of_nodes; i++) { igraph_incident(graph, &adj, (igraph_integer_t) i, IGRAPH_ALL); for (j = 0; j < igraph_vector_size(&adj); j++) { if (!added[ (long int)VECTOR(adj)[j] ]) { igraph_vector_push_back(vec, VECTOR(adj)[j]); added[ (long int)VECTOR(adj)[j] ] += 1; } } } igraph_vector_destroy(&adj); igraph_Free(added); IGRAPH_FINALLY_CLEAN(2); } eit->type = IGRAPH_EIT_VECTOR; eit->pos = 0; eit->start = 0; eit->vec = vec; eit->end = igraph_vector_size(eit->vec); IGRAPH_FINALLY_CLEAN(2); return 0; } int igraph_i_eit_pairs(const igraph_t *graph, igraph_es_t es, igraph_eit_t *eit) { long int n = igraph_vector_size(es.data.path.ptr); long int no_of_nodes = igraph_vcount(graph); long int i; if (n % 2 != 0) { IGRAPH_ERROR("Cannot create edge iterator from odd number of vertices", IGRAPH_EINVAL); } if (!igraph_vector_isininterval(es.data.path.ptr, 0, no_of_nodes - 1)) { IGRAPH_ERROR("Cannot create edge iterator", IGRAPH_EINVVID); } eit->type = IGRAPH_EIT_VECTOR; eit->pos = 0; eit->start = 0; eit->end = n / 2; eit->vec = igraph_Calloc(1, igraph_vector_t); if (eit->vec == 0) { IGRAPH_ERROR("Cannot create edge iterator", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (igraph_vector_t*)eit->vec); IGRAPH_VECTOR_INIT_FINALLY((igraph_vector_t*)eit->vec, n / 2); for (i = 0; i < igraph_vector_size(eit->vec); i++) { long int from = (long int) VECTOR(*es.data.path.ptr)[2 * i]; long int to = (long int) VECTOR(*es.data.path.ptr)[2 * i + 1]; igraph_integer_t eid; IGRAPH_CHECK(igraph_get_eid(graph, &eid, (igraph_integer_t) from, (igraph_integer_t) to, es.data.path.mode, /*error=*/ 1)); VECTOR(*eit->vec)[i] = eid; } IGRAPH_FINALLY_CLEAN(2); return 0; } int igraph_i_eit_multipairs(const igraph_t *graph, igraph_es_t es, igraph_eit_t *eit) { long int n = igraph_vector_size(es.data.path.ptr); long int no_of_nodes = igraph_vcount(graph); if (n % 2 != 0) { IGRAPH_ERROR("Cannot create edge iterator from odd number of vertices", IGRAPH_EINVAL); } if (!igraph_vector_isininterval(es.data.path.ptr, 0, no_of_nodes - 1)) { IGRAPH_ERROR("Cannot create edge iterator", IGRAPH_EINVVID); } eit->type = IGRAPH_EIT_VECTOR; eit->pos = 0; eit->start = 0; eit->end = n / 2; eit->vec = igraph_Calloc(1, igraph_vector_t); if (eit->vec == 0) { IGRAPH_ERROR("Cannot create edge iterator", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (igraph_vector_t*)eit->vec); IGRAPH_VECTOR_INIT_FINALLY((igraph_vector_t*)eit->vec, n / 2); IGRAPH_CHECK(igraph_get_eids_multi(graph, (igraph_vector_t *) eit->vec, /*pairs=*/ es.data.path.ptr, /*path=*/ 0, es.data.path.mode, /*error=*/ 1)); IGRAPH_FINALLY_CLEAN(2); return 0; } int igraph_i_eit_path(const igraph_t *graph, igraph_es_t es, igraph_eit_t *eit) { long int n = igraph_vector_size(es.data.path.ptr); long int no_of_nodes = igraph_vcount(graph); long int i, len; if (!igraph_vector_isininterval(es.data.path.ptr, 0, no_of_nodes - 1)) { IGRAPH_ERROR("Cannot create edge iterator", IGRAPH_EINVVID); } if (n <= 1) { len = 0; } else { len = n - 1; } eit->type = IGRAPH_EIT_VECTOR; eit->pos = 0; eit->start = 0; eit->end = len; eit->vec = igraph_Calloc(1, igraph_vector_t); if (eit->vec == 0) { IGRAPH_ERROR("Cannot create edge iterator", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (igraph_vector_t*)eit->vec); IGRAPH_VECTOR_INIT_FINALLY((igraph_vector_t *)eit->vec, len); for (i = 0; i < len; i++) { long int from = (long int) VECTOR(*es.data.path.ptr)[i]; long int to = (long int) VECTOR(*es.data.path.ptr)[i + 1]; igraph_integer_t eid; IGRAPH_CHECK(igraph_get_eid(graph, &eid, (igraph_integer_t) from, (igraph_integer_t) to, es.data.path.mode, /*error=*/ 1)); VECTOR(*eit->vec)[i] = eid; } IGRAPH_FINALLY_CLEAN(2); return 0; } /** * \function igraph_eit_create * \brief Creates an edge iterator from an edge selector. * * * This function creates an edge iterator based on an edge selector * and a graph. * * * The same edge selector can be used to create many edge iterators, * also for different graphs. * * \param graph An \type igraph_t object for which the edge selector * will be instantiated. * \param es The edge selector to instantiate. * \param eit Pointer to an uninitialized edge iterator. * \return Error code. * \sa \ref igraph_eit_destroy() * * Time complexity: depends on the type of the edge selector. For edge * selectors created by \ref igraph_es_all(), \ref igraph_es_none(), * \ref igraph_es_1(), igraph_es_vector(), igraph_es_seq() it is * O(1). For \ref igraph_es_incident() it is O(d) where d is the number of * incident edges of the vertex. */ int igraph_eit_create(const igraph_t *graph, igraph_es_t es, igraph_eit_t *eit) { switch (es.type) { case IGRAPH_ES_ALL: eit->type = IGRAPH_EIT_SEQ; eit->pos = 0; eit->start = 0; eit->end = igraph_ecount(graph); break; case IGRAPH_ES_ALLFROM: IGRAPH_CHECK(igraph_i_eit_create_allfromto(graph, eit, IGRAPH_OUT)); break; case IGRAPH_ES_ALLTO: IGRAPH_CHECK(igraph_i_eit_create_allfromto(graph, eit, IGRAPH_IN)); break; case IGRAPH_ES_INCIDENT: eit->type = IGRAPH_EIT_VECTOR; eit->pos = 0; eit->start = 0; eit->vec = igraph_Calloc(1, igraph_vector_t); if (eit->vec == 0) { IGRAPH_ERROR("Cannot create iterator", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (igraph_vector_t*) eit->vec); IGRAPH_VECTOR_INIT_FINALLY((igraph_vector_t*)eit->vec, 0); IGRAPH_CHECK(igraph_incident(graph, (igraph_vector_t*)eit->vec, es.data.incident.vid, es.data.incident.mode)); eit->end = igraph_vector_size(eit->vec); IGRAPH_FINALLY_CLEAN(2); break; case IGRAPH_ES_NONE: eit->type = IGRAPH_EIT_SEQ; eit->pos = 0; eit->start = 0; eit->end = 0; break; case IGRAPH_ES_1: eit->type = IGRAPH_EIT_SEQ; eit->pos = es.data.eid; eit->start = es.data.eid; eit->end = es.data.eid + 1; if (eit->pos >= igraph_ecount(graph)) { IGRAPH_ERROR("Cannot create iterator, invalid edge id", IGRAPH_EINVVID); } break; case IGRAPH_ES_VECTOR: case IGRAPH_ES_VECTORPTR: eit->type = IGRAPH_EIT_VECTORPTR; eit->pos = 0; eit->start = 0; eit->vec = es.data.vecptr; eit->end = igraph_vector_size(eit->vec); if (!igraph_vector_isininterval(eit->vec, 0, igraph_ecount(graph) - 1)) { IGRAPH_ERROR("Cannot create iterator, invalid edge id", IGRAPH_EINVVID); } break; case IGRAPH_ES_SEQ: eit->type = IGRAPH_EIT_SEQ; eit->pos = es.data.seq.from; eit->start = es.data.seq.from; eit->end = es.data.seq.to; break; case IGRAPH_ES_PAIRS: IGRAPH_CHECK(igraph_i_eit_pairs(graph, es, eit)); break; case IGRAPH_ES_MULTIPAIRS: IGRAPH_CHECK(igraph_i_eit_multipairs(graph, es, eit)); break; case IGRAPH_ES_PATH: IGRAPH_CHECK(igraph_i_eit_path(graph, es, eit)); break; default: IGRAPH_ERROR("Cannot create iterator, invalid selector", IGRAPH_EINVAL); break; } return 0; } /** * \function igraph_eit_destroy * \brief Destroys an edge iterator. * * \param eit Pointer to an edge iterator to destroy. * \sa \ref igraph_eit_create() * * Time complexity: operating system dependent, usually O(1). */ void igraph_eit_destroy(const igraph_eit_t *eit) { switch (eit->type) { case IGRAPH_EIT_SEQ: case IGRAPH_EIT_VECTORPTR: break; case IGRAPH_EIT_VECTOR: igraph_vector_destroy((igraph_vector_t*)eit->vec); igraph_free((igraph_vector_t*)eit->vec); break; default: /* IGRAPH_ERROR("Cannot destroy iterator, unknown type", IGRAPH_EINVAL); */ break; } } int igraph_eit_as_vector(const igraph_eit_t *eit, igraph_vector_t *v) { long int i; IGRAPH_CHECK(igraph_vector_resize(v, IGRAPH_EIT_SIZE(*eit))); switch (eit->type) { case IGRAPH_EIT_SEQ: for (i = 0; i < IGRAPH_EIT_SIZE(*eit); i++) { VECTOR(*v)[i] = eit->start + i; } break; case IGRAPH_EIT_VECTOR: case IGRAPH_EIT_VECTORPTR: for (i = 0; i < IGRAPH_EIT_SIZE(*eit); i++) { VECTOR(*v)[i] = VECTOR(*eit->vec)[i]; } break; default: IGRAPH_ERROR("Cannot convert to vector, unknown iterator type", IGRAPH_EINVAL); break; } return 0; } python-igraph-0.8.0/vendor/source/igraph/src/motifs.c0000644000076500000240000011630013614300625023044 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_motifs.h" #include "igraph_memory.h" #include "igraph_random.h" #include "igraph_adjlist.h" #include "igraph_interrupt_internal.h" #include "igraph_interface.h" #include "igraph_nongraph.h" #include "igraph_structural.h" #include "igraph_stack.h" #include "config.h" #include extern unsigned int igraph_i_isoclass_3[]; extern unsigned int igraph_i_isoclass_4[]; extern unsigned int igraph_i_isoclass_3u[]; extern unsigned int igraph_i_isoclass_4u[]; extern unsigned int igraph_i_isoclass2_3[]; extern unsigned int igraph_i_isoclass2_4[]; extern unsigned int igraph_i_isoclass2_3u[]; extern unsigned int igraph_i_isoclass2_4u[]; extern unsigned int igraph_i_isoclass_3_idx[]; extern unsigned int igraph_i_isoclass_4_idx[]; extern unsigned int igraph_i_isoclass_3u_idx[]; extern unsigned int igraph_i_isoclass_4u_idx[]; /** * Callback function for igraph_motifs_randesu that counts the motifs by * isomorphism class in a histogram. */ igraph_bool_t igraph_i_motifs_randesu_update_hist(const igraph_t *graph, igraph_vector_t *vids, int isoclass, void* extra) { igraph_vector_t *hist = (igraph_vector_t*)extra; IGRAPH_UNUSED(graph); IGRAPH_UNUSED(vids); VECTOR(*hist)[isoclass]++; return 0; } /** * \function igraph_motifs_randesu * \brief Count the number of motifs in a graph * * * Motifs are small connected subgraphs of a given structure in a * graph. It is argued that the motif profile (ie. the number of * different motifs in the graph) is characteristic for different * types of networks and network function is related to the motifs in * the graph. * * * This function is able to find the different motifs of size three * and four (ie. the number of different subgraphs with three and four * vertices) in the network. * * * In a big network the total number of motifs can be very large, so * it takes a lot of time to find all of them, a sampling method can * be used. This function is capable of doing sampling via the * \c cut_prob argument. This argument gives the probability that * a branch of the motif search tree will not be explored. See * S. Wernicke and F. Rasche: FANMOD: a tool for fast network motif * detection, Bioinformatics 22(9), 1152--1153, 2006 for details. * * * Set the \c cut_prob argument to a zero vector for finding all * motifs. * * * Directed motifs will be counted in directed graphs and undirected * motifs in undirected graphs. * * \param graph The graph to find the motifs in. * \param hist The result of the computation, it gives the number of * motifs found for each isomorphism class. See * \ref igraph_isoclass() for help about isomorphism classes. * Note that this function does \em not count isomorphism * classes that are not connected and will report NaN (more * precisely \c IGRAPH_NAN) for them. * \param size The size of the motifs to search for. Only three and * four are implemented currently. The limitation is not in the * motif finding code, but the graph isomorphism code. * \param cut_prob Vector of probabilities for cutting the search tree * at a given level. The first element is the first level, etc. * Supply all zeros here (of length \c size) to find all motifs * in a graph. * \return Error code. * \sa \ref igraph_motifs_randesu_estimate() for estimating the number * of motifs in a graph, this can help to set the \c cut_prob * parameter; \ref igraph_motifs_randesu_no() to calculate the total * number of motifs of a given size in a graph; * \ref igraph_motifs_randesu_callback() for calling a callback function * for every motif found; \ref igraph_subisomorphic_lad() for finding * subgraphs on more than 4 vertices. * * Time complexity: TODO. * * \example examples/simple/igraph_motifs_randesu.c */ int igraph_motifs_randesu(const igraph_t *graph, igraph_vector_t *hist, int size, const igraph_vector_t *cut_prob) { int histlen; if (size != 3 && size != 4) { IGRAPH_ERROR("Only 3 and 4 vertex motifs are implemented", IGRAPH_EINVAL); } if (size == 3) { histlen = igraph_is_directed(graph) ? 16 : 4; } else { histlen = igraph_is_directed(graph) ? 218 : 11; } IGRAPH_CHECK(igraph_vector_resize(hist, histlen)); igraph_vector_null(hist); IGRAPH_CHECK(igraph_motifs_randesu_callback(graph, size, cut_prob, &igraph_i_motifs_randesu_update_hist, hist)); if (size == 3) { if (igraph_is_directed(graph)) { VECTOR(*hist)[0] = VECTOR(*hist)[1] = VECTOR(*hist)[3] = IGRAPH_NAN; } else { VECTOR(*hist)[0] = VECTOR(*hist)[1] = IGRAPH_NAN; } } else if (size == 4) { if (igraph_is_directed(graph)) { int not_connected[] = { 0, 1, 2, 4, 5, 6, 9, 10, 11, 15, 22, 23, 27, 28, 33, 34, 39, 62, 120 }; int i, n = sizeof(not_connected) / sizeof(int); for (i = 0; i < n; i++) { VECTOR(*hist)[not_connected[i]] = IGRAPH_NAN; } } else { VECTOR(*hist)[0] = VECTOR(*hist)[1] = VECTOR(*hist)[2] = VECTOR(*hist)[3] = VECTOR(*hist)[5] = IGRAPH_NAN; } } return IGRAPH_SUCCESS; } /** * \function igraph_motifs_randesu_callback * \brief Finds motifs in a graph and calls a function for each of them * * * Similarly to \ref igraph_motifs_randesu(), this function is able to find the * different motifs of size three and four (ie. the number of different * subgraphs with three and four vertices) in the network. However, instead of * counting them, the function will call a callback function for each motif * found to allow further tests or post-processing. * * * The \c cut_prob argument also allows sampling the motifs, just like for * \ref igraph_motifs_randesu(). Set the \c cut_prob argument to a zero vector * for finding all motifs. * * \param graph The graph to find the motifs in. * \param size The size of the motifs to search for. Only three and * four are implemented currently. The limitation is not in the * motif finding code, but the graph isomorphism code. * \param cut_prob Vector of probabilities for cutting the search tree * at a given level. The first element is the first level, etc. * Supply all zeros here (of length \c size) to find all motifs * in a graph. * \param callback A pointer to a function of type \ref igraph_motifs_handler_t. * This function will be called whenever a new motif is found. * \param extra Extra argument to pass to the callback function. * \return Error code. * * Time complexity: TODO. * * \example examples/simple/igraph_motifs_randesu.c */ int igraph_motifs_randesu_callback(const igraph_t *graph, int size, const igraph_vector_t *cut_prob, igraph_motifs_handler_t *callback, void* extra) { long int no_of_nodes = igraph_vcount(graph); igraph_adjlist_t allneis, alloutneis; igraph_vector_int_t *neis; long int father; long int i, j, s; long int motifs = 0; igraph_vector_t vids; /* this is G */ igraph_vector_t adjverts; /* this is V_E */ igraph_stack_t stack; /* this is S */ long int *added; char *subg; unsigned int *arr_idx, *arr_code; int code = 0; unsigned char mul, idx; igraph_bool_t terminate = 0; if (size != 3 && size != 4) { IGRAPH_ERROR("Only 3 and 4 vertex motifs are implemented", IGRAPH_EINVAL); } if (igraph_vector_size(cut_prob) < size) { IGRAPH_ERROR("The size of the cut probability vector must not be smaller than the motif size.", IGRAPH_EINVAL); } if (size == 3) { mul = 3; if (igraph_is_directed(graph)) { arr_idx = igraph_i_isoclass_3_idx; arr_code = igraph_i_isoclass2_3; } else { arr_idx = igraph_i_isoclass_3u_idx; arr_code = igraph_i_isoclass2_3u; } } else { mul = 4; if (igraph_is_directed(graph)) { arr_idx = igraph_i_isoclass_4_idx; arr_code = igraph_i_isoclass2_4; } else { arr_idx = igraph_i_isoclass_4u_idx; arr_code = igraph_i_isoclass2_4u; } } added = igraph_Calloc(no_of_nodes, long int); if (added == 0) { IGRAPH_ERROR("Cannot find motifs", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, added); subg = igraph_Calloc(no_of_nodes, char); if (subg == 0) { IGRAPH_ERROR("Cannot find motifs", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, subg); IGRAPH_CHECK(igraph_adjlist_init(graph, &allneis, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_adjlist_destroy, &allneis); IGRAPH_CHECK(igraph_adjlist_init(graph, &alloutneis, IGRAPH_OUT)); IGRAPH_FINALLY(igraph_adjlist_destroy, &alloutneis); IGRAPH_VECTOR_INIT_FINALLY(&vids, 0); IGRAPH_VECTOR_INIT_FINALLY(&adjverts, 0); IGRAPH_CHECK(igraph_stack_init(&stack, 0)); IGRAPH_FINALLY(igraph_stack_destroy, &stack); RNG_BEGIN(); for (father = 0; father < no_of_nodes; father++) { long int level; IGRAPH_ALLOW_INTERRUPTION(); if (VECTOR(*cut_prob)[0] == 1 || RNG_UNIF01() < VECTOR(*cut_prob)[0]) { continue; } /* init G */ igraph_vector_clear(&vids); level = 0; IGRAPH_CHECK(igraph_vector_push_back(&vids, father)); subg[father] = 1; added[father] += 1; level += 1; /* init V_E */ igraph_vector_clear(&adjverts); neis = igraph_adjlist_get(&allneis, father); s = igraph_vector_int_size(neis); for (i = 0; i < s; i++) { long int nei = (long int) VECTOR(*neis)[i]; if (!added[nei] && nei > father) { IGRAPH_CHECK(igraph_vector_push_back(&adjverts, nei)); IGRAPH_CHECK(igraph_vector_push_back(&adjverts, father)); } added[nei] += 1; } /* init S */ igraph_stack_clear(&stack); while (level > 1 || !igraph_vector_empty(&adjverts)) { igraph_real_t cp = VECTOR(*cut_prob)[level]; if (level == size - 1) { s = igraph_vector_size(&adjverts) / 2; for (i = 0; i < s; i++) { long int k, s2; long int last; if (cp != 0 && RNG_UNIF01() < cp) { continue; } motifs += 1; last = (long int) VECTOR(adjverts)[2 * i]; IGRAPH_CHECK(igraph_vector_push_back(&vids, last)); subg[last] = (char) size; code = 0; idx = 0; for (k = 0; k < size; k++) { long int from = (long int) VECTOR(vids)[k]; neis = igraph_adjlist_get(&alloutneis, from); s2 = igraph_vector_int_size(neis); for (j = 0; j < s2; j++) { long int nei = (long int) VECTOR(*neis)[j]; if (subg[nei] && k != subg[nei] - 1) { idx = (unsigned char) (mul * k + (subg[nei] - 1)); code |= arr_idx[idx]; } } } if (callback(graph, &vids, (int) arr_code[code], extra)) { terminate = 1; break; } igraph_vector_pop_back(&vids); subg[last] = 0; } } /* did the callback function asked us to terminate the search? */ if (terminate) { break; } /* can we step down? */ if (level < size - 1 && !igraph_vector_empty(&adjverts)) { /* we might step down */ long int neifather = (long int) igraph_vector_pop_back(&adjverts); long int nei = (long int) igraph_vector_pop_back(&adjverts); if (cp == 0 || RNG_UNIF01() > cp) { /* yes, step down */ IGRAPH_CHECK(igraph_vector_push_back(&vids, nei)); subg[nei] = (char) level + 1; added[nei] += 1; level += 1; IGRAPH_CHECK(igraph_stack_push(&stack, neifather)); IGRAPH_CHECK(igraph_stack_push(&stack, nei)); IGRAPH_CHECK(igraph_stack_push(&stack, level)); neis = igraph_adjlist_get(&allneis, nei); s = igraph_vector_int_size(neis); for (i = 0; i < s; i++) { long int nei2 = (long int) VECTOR(*neis)[i]; if (!added[nei2] && nei2 > father) { IGRAPH_CHECK(igraph_vector_push_back(&adjverts, nei2)); IGRAPH_CHECK(igraph_vector_push_back(&adjverts, nei)); } added[nei2] += 1; } } } else { /* no, step back */ long int nei, neifather; while (!igraph_stack_empty(&stack) && level == igraph_stack_top(&stack) - 1) { igraph_stack_pop(&stack); nei = (long int) igraph_stack_pop(&stack); neifather = (long int) igraph_stack_pop(&stack); igraph_vector_push_back(&adjverts, nei); igraph_vector_push_back(&adjverts, neifather); } nei = (long int) igraph_vector_pop_back(&vids); subg[nei] = 0; added[nei] -= 1; level -= 1; neis = igraph_adjlist_get(&allneis, nei); s = igraph_vector_int_size(neis); for (i = 0; i < s; i++) { added[ (long int) VECTOR(*neis)[i] ] -= 1; } while (!igraph_vector_empty(&adjverts) && igraph_vector_tail(&adjverts) == nei) { igraph_vector_pop_back(&adjverts); igraph_vector_pop_back(&adjverts); } } } /* while */ /* did the callback function asked us to terminate the search? */ if (terminate) { break; } /* clear the added vector */ added[father] -= 1; subg[father] = 0; neis = igraph_adjlist_get(&allneis, father); s = igraph_vector_int_size(neis); for (i = 0; i < s; i++) { added[ (long int) VECTOR(*neis)[i] ] -= 1; } } /* for father */ RNG_END(); igraph_Free(added); igraph_Free(subg); igraph_vector_destroy(&vids); igraph_vector_destroy(&adjverts); igraph_adjlist_destroy(&alloutneis); igraph_adjlist_destroy(&allneis); igraph_stack_destroy(&stack); IGRAPH_FINALLY_CLEAN(7); return 0; } /** * \function igraph_motifs_randesu_estimate * \brief Estimate the total number of motifs in a graph * * * This function is useful for large graphs for which it is not * feasible to count all the different motifs, because there is very * many of them. * * * The total number of motifs is estimated by taking a sample of * vertices and counts all motifs in which these vertices are * included. (There is also a \c cut_prob parameter which gives the * probabilities to cut a branch of the search tree.) * * * Directed motifs will be counted in directed graphs and undirected * motifs in undirected graphs. * * \param graph The graph object to study. * \param est Pointer to an integer type, the result will be stored * here. * \param size The size of the motif to look for. * \param cut_prob Vector giving the probabilities to cut a branch of * the search tree and omit counting the motifs in that branch. * It contains a probability for each level. Supply \c size * zeros here to count all the motifs in the sample. * \param sample_size The number of vertices to use as the * sample. This parameter is only used if the \c parsample * argument is a null pointer. * \param parsample Either pointer to an initialized vector or a null * pointer. If a vector then the vertex ids in the vector are * used as a sample. If a null pointer then the \c sample_size * argument is used to create a sample of vertices drawn with * uniform probability. * \return Error code. * \sa \ref igraph_motifs_randesu(), \ref igraph_motifs_randesu_no(). * * Time complexity: TODO. */ int igraph_motifs_randesu_estimate(const igraph_t *graph, igraph_integer_t *est, int size, const igraph_vector_t *cut_prob, igraph_integer_t sample_size, const igraph_vector_t *parsample) { long int no_of_nodes = igraph_vcount(graph); igraph_vector_t neis; igraph_vector_t vids; /* this is G */ igraph_vector_t adjverts; /* this is V_E */ igraph_stack_t stack; /* this is S */ long int *added; igraph_vector_t *sample; long int sam; long int i; added = igraph_Calloc(no_of_nodes, long int); if (added == 0) { IGRAPH_ERROR("Cannot find motifs", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, added); IGRAPH_VECTOR_INIT_FINALLY(&vids, 0); IGRAPH_VECTOR_INIT_FINALLY(&adjverts, 0); IGRAPH_CHECK(igraph_stack_init(&stack, 0)); IGRAPH_FINALLY(igraph_stack_destroy, &stack); IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); if (parsample == 0) { sample = igraph_Calloc(1, igraph_vector_t); if (sample == 0) { IGRAPH_ERROR("Cannot estimate motifs", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, sample); IGRAPH_VECTOR_INIT_FINALLY(sample, 0); IGRAPH_CHECK(igraph_random_sample(sample, 0, no_of_nodes - 1, sample_size)); } else { sample = (igraph_vector_t*)parsample; sample_size = (igraph_integer_t) igraph_vector_size(sample); } *est = 0; RNG_BEGIN(); for (sam = 0; sam < sample_size; sam++) { long int father = (long int) VECTOR(*sample)[sam]; long int level, s; IGRAPH_ALLOW_INTERRUPTION(); if (VECTOR(*cut_prob)[0] == 1 || RNG_UNIF01() < VECTOR(*cut_prob)[0]) { continue; } /* init G */ igraph_vector_clear(&vids); level = 0; IGRAPH_CHECK(igraph_vector_push_back(&vids, father)); added[father] += 1; level += 1; /* init V_E */ igraph_vector_clear(&adjverts); IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) father, IGRAPH_ALL)); s = igraph_vector_size(&neis); for (i = 0; i < s; i++) { long int nei = (long int) VECTOR(neis)[i]; if (!added[nei] && nei > father) { IGRAPH_CHECK(igraph_vector_push_back(&adjverts, nei)); IGRAPH_CHECK(igraph_vector_push_back(&adjverts, father)); } added[nei] += 1; } /* init S */ igraph_stack_clear(&stack); while (level > 1 || !igraph_vector_empty(&adjverts)) { igraph_real_t cp = VECTOR(*cut_prob)[level]; if (level == size - 1) { s = igraph_vector_size(&adjverts) / 2; for (i = 0; i < s; i++) { if (cp != 0 && RNG_UNIF01() < cp) { continue; } (*est) += 1; } } if (level < size - 1 && !igraph_vector_empty(&adjverts)) { /* We might step down */ long int neifather = (long int) igraph_vector_pop_back(&adjverts); long int nei = (long int) igraph_vector_pop_back(&adjverts); if (cp == 0 || RNG_UNIF01() > cp) { /* Yes, step down */ IGRAPH_CHECK(igraph_vector_push_back(&vids, nei)); added[nei] += 1; level += 1; IGRAPH_CHECK(igraph_stack_push(&stack, neifather)); IGRAPH_CHECK(igraph_stack_push(&stack, nei)); IGRAPH_CHECK(igraph_stack_push(&stack, level)); IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) nei, IGRAPH_ALL)); s = igraph_vector_size(&neis); for (i = 0; i < s; i++) { long int nei2 = (long int) VECTOR(neis)[i]; if (!added[nei2] && nei2 > father) { IGRAPH_CHECK(igraph_vector_push_back(&adjverts, nei2)); IGRAPH_CHECK(igraph_vector_push_back(&adjverts, nei)); } added[nei2] += 1; } } } else { /* no, step back */ long int nei, neifather; while (!igraph_stack_empty(&stack) && level == igraph_stack_top(&stack) - 1) { igraph_stack_pop(&stack); nei = (long int) igraph_stack_pop(&stack); neifather = (long int) igraph_stack_pop(&stack); igraph_vector_push_back(&adjverts, nei); igraph_vector_push_back(&adjverts, neifather); } nei = (long int) igraph_vector_pop_back(&vids); added[nei] -= 1; level -= 1; IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) nei, IGRAPH_ALL)); s = igraph_vector_size(&neis); for (i = 0; i < s; i++) { added[ (long int) VECTOR(neis)[i] ] -= 1; } while (!igraph_vector_empty(&adjverts) && igraph_vector_tail(&adjverts) == nei) { igraph_vector_pop_back(&adjverts); igraph_vector_pop_back(&adjverts); } } } /* while */ /* clear the added vector */ added[father] -= 1; IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) father, IGRAPH_ALL)); s = igraph_vector_size(&neis); for (i = 0; i < s; i++) { added[ (long int) VECTOR(neis)[i] ] -= 1; } } /* for father */ RNG_END(); (*est) *= ((double)no_of_nodes / sample_size); if (parsample == 0) { igraph_vector_destroy(sample); igraph_Free(sample); IGRAPH_FINALLY_CLEAN(2); } igraph_Free(added); igraph_vector_destroy(&vids); igraph_vector_destroy(&adjverts); igraph_stack_destroy(&stack); igraph_vector_destroy(&neis); IGRAPH_FINALLY_CLEAN(5); return 0; } /** * \function igraph_motifs_randesu_no * \brief Count the total number of motifs in a graph * * * This function counts the total number of motifs in a graph without * assigning isomorphism classes to them. * * * Directed motifs will be counted in directed graphs and undirected * motifs in undirected graphs. * * \param graph The graph object to study. * \param no Pointer to an integer type, the result will be stored * here. * \param size The size of the motifs to count. * \param cut_prob Vector giving the probabilities that a branch of * the search tree will be cut at a given level. * \return Error code. * \sa \ref igraph_motifs_randesu(), \ref * igraph_motifs_randesu_estimate(). * * Time complexity: TODO. */ int igraph_motifs_randesu_no(const igraph_t *graph, igraph_integer_t *no, int size, const igraph_vector_t *cut_prob) { long int no_of_nodes = igraph_vcount(graph); igraph_vector_t neis; igraph_vector_t vids; /* this is G */ igraph_vector_t adjverts; /* this is V_E */ igraph_stack_t stack; /* this is S */ long int *added; long int father; long int i; added = igraph_Calloc(no_of_nodes, long int); if (added == 0) { IGRAPH_ERROR("Cannot find motifs", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, added); IGRAPH_VECTOR_INIT_FINALLY(&vids, 0); IGRAPH_VECTOR_INIT_FINALLY(&adjverts, 0); IGRAPH_CHECK(igraph_stack_init(&stack, 0)); IGRAPH_FINALLY(igraph_stack_destroy, &stack); IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); *no = 0; RNG_BEGIN(); for (father = 0; father < no_of_nodes; father++) { long int level, s; IGRAPH_ALLOW_INTERRUPTION(); if (VECTOR(*cut_prob)[0] == 1 || RNG_UNIF01() < VECTOR(*cut_prob)[0]) { continue; } /* init G */ igraph_vector_clear(&vids); level = 0; IGRAPH_CHECK(igraph_vector_push_back(&vids, father)); added[father] += 1; level += 1; /* init V_E */ igraph_vector_clear(&adjverts); IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) father, IGRAPH_ALL)); s = igraph_vector_size(&neis); for (i = 0; i < s; i++) { long int nei = (long int) VECTOR(neis)[i]; if (!added[nei] && nei > father) { IGRAPH_CHECK(igraph_vector_push_back(&adjverts, nei)); IGRAPH_CHECK(igraph_vector_push_back(&adjverts, father)); } added[nei] += 1; } /* init S */ igraph_stack_clear(&stack); while (level > 1 || !igraph_vector_empty(&adjverts)) { igraph_real_t cp = VECTOR(*cut_prob)[level]; if (level == size - 1) { s = igraph_vector_size(&adjverts) / 2; for (i = 0; i < s; i++) { if (cp != 0 && RNG_UNIF01() < cp) { continue; } (*no) += 1; } } if (level < size - 1 && !igraph_vector_empty(&adjverts)) { /* We might step down */ long int neifather = (long int) igraph_vector_pop_back(&adjverts); long int nei = (long int) igraph_vector_pop_back(&adjverts); if (cp == 0 || RNG_UNIF01() > cp) { /* Yes, step down */ IGRAPH_CHECK(igraph_vector_push_back(&vids, nei)); added[nei] += 1; level += 1; IGRAPH_CHECK(igraph_stack_push(&stack, neifather)); IGRAPH_CHECK(igraph_stack_push(&stack, nei)); IGRAPH_CHECK(igraph_stack_push(&stack, level)); IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) nei, IGRAPH_ALL)); s = igraph_vector_size(&neis); for (i = 0; i < s; i++) { long int nei2 = (long int) VECTOR(neis)[i]; if (!added[nei2] && nei2 > father) { IGRAPH_CHECK(igraph_vector_push_back(&adjverts, nei2)); IGRAPH_CHECK(igraph_vector_push_back(&adjverts, nei)); } added[nei2] += 1; } } } else { /* no, step back */ long int nei, neifather; while (!igraph_stack_empty(&stack) && level == igraph_stack_top(&stack) - 1) { igraph_stack_pop(&stack); nei = (long int) igraph_stack_pop(&stack); neifather = (long int) igraph_stack_pop(&stack); igraph_vector_push_back(&adjverts, nei); igraph_vector_push_back(&adjverts, neifather); } nei = (long int) igraph_vector_pop_back(&vids); added[nei] -= 1; level -= 1; IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) nei, IGRAPH_ALL)); s = igraph_vector_size(&neis); for (i = 0; i < s; i++) { added[ (long int) VECTOR(neis)[i] ] -= 1; } while (!igraph_vector_empty(&adjverts) && igraph_vector_tail(&adjverts) == nei) { igraph_vector_pop_back(&adjverts); igraph_vector_pop_back(&adjverts); } } } /* while */ /* clear the added vector */ added[father] -= 1; IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) father, IGRAPH_ALL)); s = igraph_vector_size(&neis); for (i = 0; i < s; i++) { added[ (long int) VECTOR(neis)[i] ] -= 1; } } /* for father */ RNG_END(); igraph_Free(added); igraph_vector_destroy(&vids); igraph_vector_destroy(&adjverts); igraph_stack_destroy(&stack); igraph_vector_destroy(&neis); IGRAPH_FINALLY_CLEAN(5); return 0; } /** * \function igraph_dyad_census * \brief Calculating the dyad census as defined by Holland and Leinhardt * * * Dyad census means classifying each pair of vertices of a directed * graph into three categories: mutual, there is an edge from \c a to * \c b and also from \c b to \c a; asymmetric, there is an edge * either from \c a to \c b or from \c b to \c a but not the other way * and null, no edges between \c a and \c b. * * * Holland, P.W. and Leinhardt, S. (1970). A Method for Detecting * Structure in Sociometric Data. American Journal of Sociology, * 70, 492-513. * \param graph The input graph, a warning is given if undirected as * the results are undefined for undirected graphs. * \param mut Pointer to an integer, the number of mutual dyads is * stored here. * \param asym Pointer to an integer, the number of asymmetric dyads * is stored here. * \param null Pointer to an integer, the number of null dyads is * stored here. In case of an integer overflow (i.e. too many * null dyads), -1 will be returned. * \return Error code. * * \sa \ref igraph_reciprocity(), \ref igraph_triad_census(). * * Time complexity: O(|V|+|E|), the number of vertices plus the number * of edges. */ int igraph_dyad_census(const igraph_t *graph, igraph_integer_t *mut, igraph_integer_t *asym, igraph_integer_t *null) { igraph_integer_t nonrec = 0, rec = 0; igraph_vector_t inneis, outneis; igraph_integer_t vc = igraph_vcount(graph); long int i; if (!igraph_is_directed(graph)) { IGRAPH_WARNING("Dyad census called on undirected graph"); } IGRAPH_VECTOR_INIT_FINALLY(&inneis, 0); IGRAPH_VECTOR_INIT_FINALLY(&outneis, 0); for (i = 0; i < vc; i++) { long int ip, op; igraph_neighbors(graph, &inneis, i, IGRAPH_IN); igraph_neighbors(graph, &outneis, i, IGRAPH_OUT); ip = op = 0; while (ip < igraph_vector_size(&inneis) && op < igraph_vector_size(&outneis)) { if (VECTOR(inneis)[ip] < VECTOR(outneis)[op]) { nonrec += 1; ip++; } else if (VECTOR(inneis)[ip] > VECTOR(outneis)[op]) { nonrec += 1; op++; } else { rec += 1; ip++; op++; } } nonrec += (igraph_vector_size(&inneis) - ip) + (igraph_vector_size(&outneis) - op); } igraph_vector_destroy(&inneis); igraph_vector_destroy(&outneis); IGRAPH_FINALLY_CLEAN(2); *mut = rec / 2; *asym = nonrec / 2; if (vc % 2) { *null = vc * ((vc - 1) / 2); } else { *null = (vc / 2) * (vc - 1); } if (*null < vc) { IGRAPH_WARNING("Integer overflow, returning -1"); *null = -1; } else { *null = *null - (*mut) - (*asym); } return 0; } /** * \function igraph_triad_census_24 * TODO */ int igraph_triad_census_24(const igraph_t *graph, igraph_real_t *res2, igraph_real_t *res4) { long int vc = igraph_vcount(graph); igraph_vector_long_t seen; igraph_vector_int_t *neis, *neis2; long int i, j, k, s, neilen, neilen2, ign; igraph_adjlist_t adjlist; IGRAPH_CHECK(igraph_vector_long_init(&seen, vc)); IGRAPH_FINALLY(igraph_vector_long_destroy, &seen); IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist); *res2 = *res4 = 0; for (i = 0; i < vc; i++) { IGRAPH_ALLOW_INTERRUPTION(); neis = igraph_adjlist_get(&adjlist, i); neilen = igraph_vector_int_size(neis); /* mark neighbors of i & i itself */ VECTOR(seen)[i] = i + 1; ign = 0; for (j = 0; j < neilen; j++) { long int nei = (long int) VECTOR(*neis)[j]; if (VECTOR(seen)[nei] == i + 1 || VECTOR(seen)[nei] == -(i + 1)) { /* multiple edges or loop edge */ VECTOR(seen)[nei] = -(i + 1); ign++; } else { VECTOR(seen)[nei] = i + 1; } } for (j = 0; j < neilen; j++) { long int nei = (long int) VECTOR(*neis)[j]; if (nei <= i || (j > 0 && nei == VECTOR(*neis)[j - 1])) { continue; } neis2 = igraph_adjlist_get(&adjlist, nei); neilen2 = igraph_vector_int_size(neis2); s = 0; for (k = 0; k < neilen2; k++) { long int nei2 = (long int) VECTOR(*neis2)[k]; if (k > 0 && nei2 == VECTOR(*neis2)[k - 1]) { continue; } if (VECTOR(seen)[nei2] != i + 1 && VECTOR(seen)[nei2] != -(i + 1)) { s++; } } if (VECTOR(seen)[nei] > 0) { *res2 += vc - s - neilen + ign - 1; } else { *res4 += vc - s - neilen + ign - 1; } } } igraph_adjlist_destroy(&adjlist); igraph_vector_long_destroy(&seen); IGRAPH_FINALLY_CLEAN(2); return 0; } /** * \function igraph_triad_census * \brief Triad census, as defined by Davis and Leinhardt * * * Calculating the triad census means classifying every triple of * vertices in a directed graph. A triple can be in one of 16 states: * \clist * \cli 003 * A, B, C, the empty graph. * \cli 012 * A->B, C, a graph with a single directed edge. * \cli 102 * A<->B, C, a graph with a mutual connection between two vertices. * \cli 021D * A<-B->C, the binary out-tree. * \cli 021U * A->B<-C, the binary in-tree. * \cli 021C * A->B->C, the directed line. * \cli 111D * A<->B<-C. * \cli 111U * A<->B->C. * \cli 030T * A->B<-C, A->C. * \cli 030C * A<-B<-C, A->C. * \cli 201 * A<->B<->C. * \cli 120D * A<-B->C, A<->C. * \cli 120U * A->B<-C, A<->C. * \cli 120C * A->B->C, A<->C. * \cli 210 * A->B<->C, A<->C. * \cli 300 * A<->B<->C, A<->C, the complete graph. * \endclist * * * See also Davis, J.A. and Leinhardt, S. (1972). The Structure of * Positive Interpersonal Relations in Small Groups. In J. Berger * (Ed.), Sociological Theories in Progress, Volume 2, 218-251. * Boston: Houghton Mifflin. * * * This function calls \ref igraph_motifs_randesu() which is an * implementation of the FANMOD motif finder tool, see \ref * igraph_motifs_randesu() for details. Note that the order of the * triads is not the same for \ref igraph_triad_census() and \ref * igraph_motifs_randesu(). * * \param graph The input graph. A warning is given for undirected * graphs, as the result is undefined for those. * \param res Pointer to an initialized vector, the result is stored * here in the same order as given in the list above. Note that this * order is different than the one used by \ref igraph_motifs_randesu(). * \return Error code. * * \sa \ref igraph_motifs_randesu(), \ref igraph_dyad_census(). * * Time complexity: TODO. */ int igraph_triad_census(const igraph_t *graph, igraph_vector_t *res) { igraph_vector_t cut_prob; igraph_real_t m2, m4; igraph_vector_t tmp; igraph_integer_t vc = igraph_vcount(graph); igraph_real_t total; if (!igraph_is_directed(graph)) { IGRAPH_WARNING("Triad census called on an undirected graph"); } IGRAPH_VECTOR_INIT_FINALLY(&tmp, 0); IGRAPH_VECTOR_INIT_FINALLY(&cut_prob, 3); /* all zeros */ IGRAPH_CHECK(igraph_vector_resize(res, 16)); igraph_vector_null(res); IGRAPH_CHECK(igraph_motifs_randesu(graph, &tmp, 3, &cut_prob)); IGRAPH_CHECK(igraph_triad_census_24(graph, &m2, &m4)); total = ((igraph_real_t)vc) * (vc - 1); total *= (vc - 2); total /= 6; /* Reorder */ if (igraph_is_directed(graph)) { VECTOR(tmp)[0] = 0; VECTOR(tmp)[1] = m2; VECTOR(tmp)[3] = m4; VECTOR(tmp)[0] = total - igraph_vector_sum(&tmp); VECTOR(*res)[0] = VECTOR(tmp)[0]; VECTOR(*res)[1] = VECTOR(tmp)[1]; VECTOR(*res)[2] = VECTOR(tmp)[3]; VECTOR(*res)[3] = VECTOR(tmp)[6]; VECTOR(*res)[4] = VECTOR(tmp)[2]; VECTOR(*res)[5] = VECTOR(tmp)[4]; VECTOR(*res)[6] = VECTOR(tmp)[5]; VECTOR(*res)[7] = VECTOR(tmp)[9]; VECTOR(*res)[8] = VECTOR(tmp)[7]; VECTOR(*res)[9] = VECTOR(tmp)[11]; VECTOR(*res)[10] = VECTOR(tmp)[10]; VECTOR(*res)[11] = VECTOR(tmp)[8]; VECTOR(*res)[12] = VECTOR(tmp)[13]; VECTOR(*res)[13] = VECTOR(tmp)[12]; VECTOR(*res)[14] = VECTOR(tmp)[14]; VECTOR(*res)[15] = VECTOR(tmp)[15]; } else { VECTOR(tmp)[0] = 0; VECTOR(tmp)[1] = m2; VECTOR(tmp)[0] = total - igraph_vector_sum(&tmp); VECTOR(*res)[0] = VECTOR(tmp)[0]; VECTOR(*res)[2] = VECTOR(tmp)[1]; VECTOR(*res)[10] = VECTOR(tmp)[2]; VECTOR(*res)[15] = VECTOR(tmp)[3]; } igraph_vector_destroy(&cut_prob); igraph_vector_destroy(&tmp); IGRAPH_FINALLY_CLEAN(2); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/scg.c0000644000076500000240000026722513614300625022334 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-12 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ /* * SCGlib : A C library for the spectral coarse graining of matrices * as described in the paper: Shrinking Matrices while preserving their * eigenpairs with Application to the Spectral Coarse Graining of Graphs. * Preprint available at * * Copyright (C) 2008 David Morton de Lachapelle * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 2 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA * 02110-1301 USA * * DESCRIPTION * ----------- * The grouping function takes as argument 'nev' eigenvectors and * and tries to minimize the eigenpair shifts induced by the coarse * graining (Section 5 of the above reference). The eigenvectors are * stored in a 'nev'x'n' matrix 'v'. * The 'algo' parameter can take the following values * 1 -> Optimal method (sec. 5.3.1) * 2 -> Intervals+k-means (sec. 5.3.3) * 3 -> Intervals (sec. 5.3.2) * 4 -> Exact SCG (sec. 5.4.1--last paragraph) * 'nt' is a vector of length 'nev' giving either the size of the * partitions (if algo = 1) or the number of intervals to cut the * eigenvectors if algo = 2 or algo = 3. When algo = 4 this parameter * is ignored. 'maxiter' fixes the maximum number of iterations of * the k-means algorithm, and is only considered when algo = 2. * All the algorithms try to find a minimizing partition of * ||v_i-Pv_i|| where P is a problem-specific projector and v_i denotes * the eigenvectors stored in v. The final partition is worked out * as decribed in Method 1 of Section 5.4.2. * 'matrix' provides the type of SCG (i.e. the form of P). So far, * the options are those described in section 6, that is: * 1 -> Symmetric (sec. 6.1) * 2 -> Laplacian (sec. 6.2) * 3 -> Stochastic (sec. 6.3) * In the stochastic case, a valid distribution probability 'p' must be * provided. In all other cases, 'p' is ignored and can be set to NULL. * The group labels in the final partition are given in 'gr' as positive * consecutive integers starting from 0. */ #include "igraph_scg.h" #include "igraph_eigen.h" #include "igraph_interface.h" #include "igraph_structural.h" #include "igraph_constructors.h" #include "igraph_conversion.h" #include "igraph_memory.h" #include "scg_headers.h" #include "math.h" /** * \section about_scg * * * The SCG functions provide a framework, called Spectral Coarse Graining * (SCG), for reducing large graphs while preserving their * spectral-related features, that is features * closely related with the eigenvalues and eigenvectors of a graph * matrix (which for now can be the adjacency, the stochastic, or the * Laplacian matrix). * * * * Common examples of such features comprise the first-passage-time of * random walkers on Markovian graphs, thermodynamic properties of * lattice models in statistical physics (e.g. Ising model), and the * epidemic threshold of epidemic network models (SIR and SIS models). * * * * SCG differs from traditional clustering schemes by producing a * coarse-grained graph (not just a partition of * the vertices), representative of the original one. As shown in [1], * Principal Component Analysis can be viewed as a particular SCG, * called exact SCG, where the matrix to be * coarse-grained is the covariance matrix of some data set. * * * * SCG should be of interest to practitioners of various * fields dealing with problems where matrix eigenpairs play an important * role, as for instance is the case of dynamical processes on networks. * * *
SCG in brief * * The main idea of SCG is to operate on a matrix a shrinkage operation * specifically designed to preserve some of the matrix eigenpairs while * not altering other important matrix features (such as its structure). * Mathematically, this idea was expressed as follows. Consider a * (complex) n x n matrix M and form the product *
* M'=LMR*, *
* where n' < n and L, R are from C[n'xn]} and are such * that LR*=I[n'] (R* denotes the conjugate transpose of R). Under * these assumptions, it can be shown that P=R*L is an n'-rank * projector and that, if (lambda, v) is a (right) * eigenpair of M (i.e. Mv=lambda v} and P is orthogonal, there exists * an eigenvalue lambda' of M' such that *
* |lambda-lambda'| <= const ||e[P](v)|| * [1+O(||e[P](v)||2)], *
* where ||e[P](v)||=||v-Pv||. Hence, if P (or equivalently * L, R) is chosen so as to make ||e[P](v)|| as small as possible, one * can preserve to any desired level the original eigenvalue * lambda in the coarse-grained matrix M'; * under extra assumptions on M, this result can be generalized to * eigenvectors [1]. This leads to the following generic definition of a * SCG problem. * * * * Given M (C[nxn]) and (lambda, v), a (right) eigenpair of M to be * preserved by the coarse graining, the problem is to find a projector * P' solving *
* min(||e[P](v)||, p in Omega), *
* where Omega is a set of projectors in C[nxn] described by some * ad hoc constraints c[1], ..., c[r] * (e.g. c[1]: P in R[nxn], c[2]: P=t(P), c[3]: P[i,j] >= 0}, etc). * * * * Choosing pertinent constraints to solve the SCG problem is of great * importance in applications. For instance, in the absence of * constraints the SCG problem is solved trivially by * P'=vv* (v is assumed normalized). We have designed a particular * constraint, called homogeneous mixing, which * ensures that vertices belonging to the same group are merged * consistently from a physical point of view (see [1] for * details). Under this constraint the SCG problem reduces to finding * the partition of 1, ..., n (labeling the original vertices) * minimizing *
* ||e[P](v)||2 = * sum([v(i)-(Pv)(i)]2; * alpha=1,...,n', i in alpha), *
* where alpha denotes a group (i.e. a block) in a partition of * {1, ..., n}, and |alpha| is the number of elements in alpha. * * * * If M is symmetric or stochastic, for instance, then it may be * desirable (or mandatory) to choose L, R so that M' is symmetric or * stochastic as well. This structural constraint * has led to the construction of particular semi-projectors for * symmetric [1], stochastic [3] and Laplacian [2] matrices, that are * made available. * * * * In short, the coarse graining of matrices and graphs involves: * \olist * \oli Retrieving a matrix or a graph matrix M from the * problem. * \oli Computing the eigenpairs of M to be preserved in the * coarse-grained graph or matrix. * \oli Setting some problem-specific constraints (e.g. dimension of * the coarse-grained object). * \oli Solving the constrained SCG problem, that is finding P'. * \oli Computing from P' two semi-projectors L' and R' * (e.g. following the method proposed in [1]). * \oli Working out the product M'=L'MR'* and, if needed, defining * from M' a coarse-grained graph. * \endolist * *
* *
Functions for performing SCG * * The main functions are \ref igraph_scg_adjacency(), \ref * igraph_scg_laplacian() and \ref igraph_scg_stochastic(). * These functions handle all the steps involved in the * Spectral Coarse Graining (SCG) of some particular matrices and graphs * as described above and in reference [1]. In more details, * they compute some prescribed eigenpairs of a matrix or a * graph matrix, (for now adjacency, Laplacian and stochastic matrices are * available), work out an optimal partition to preserve the eigenpairs, * and finally output a coarse-grained matrix or graph along with other * useful information. * * * * These steps can also be carried out independently: (1) Use * \ref igraph_get_adjacency(), \ref igraph_get_sparsemat(), * \ref igraph_laplacian(), \ref igraph_get_stochastic() or \ref * igraph_get_stochastic_sparsemat() to compute a matrix M. * (2) Work out some prescribed eigenpairs of M e.g. by * means of \ref igraph_arpack_rssolve() or \ref * igraph_arpack_rnsolve(). (3) Invoke one the four * algorithms of the function \ref igraph_scg_grouping() to get a * partition that will preserve the eigenpairs in the coarse-grained * matrix. (4) Compute the semi-projectors L and R using * \ref igraph_scg_semiprojectors() and from there the coarse-grained * matrix M'=LMR*. If necessary, construct a coarse-grained graph from * M' (e.g. as in [1]). * *
* *
References * * [1] D. Morton de Lachapelle, D. Gfeller, and P. De Los Rios, * Shrinking Matrices while Preserving their Eigenpairs with Application * to the Spectral Coarse Graining of Graphs. Submitted to * SIAM Journal on Matrix Analysis and * Applications, 2008. * http://people.epfl.ch/david.morton * * * [2] D. Gfeller, and P. De Los Rios, Spectral Coarse Graining and * Synchronization in Oscillator Networks. * Physical Review Letters, * 100(17), 2008. * http://arxiv.org/abs/0708.2055 * * * [3] D. Gfeller, and P. De Los Rios, Spectral Coarse Graining of Complex * Networks, Physical Review Letters, * 99(3), 2007. * http://arxiv.org/abs/0706.0812 * *
*/ /** * \function igraph_scg_grouping * \brief SCG problem solver * * This function solves the Spectral Coarse Graining (SCG) problem; * either exactly, or approximately but faster. * * * The algorithm \c IGRAPH_SCG_OPTIMUM solves exactly the SCG problem * for each eigenvector in \p V. The running time of this algorithm is * O(max(nt) m^2) for the symmetric and laplacian matrix problems * It is O(m^3) for the stochastic problem. Here m is the number * of rows in \p V. In all three cases, the memory usage is O(m^2). * * * The algorithms \c IGRAPH_SCG_INTERV and \c IGRAPH_SCG_INTERV_KM solve * approximately the SCG problem by performing a (for now) constant * binning of the components of the eigenvectors, that is \p nt * VECTOR(nt_vec)[i]) constant-size bins are used to * partition V[,i]. When \p algo is \c * IGRAPH_SCG_INTERV_KM, the (Lloyd) k-means algorithm is * run on each partition obtained by \c IGRAPH_SCG_INTERV to improve * accuracy. * * * Once a minimizing partition (either exact or approximate) has been * found for each eigenvector, the final grouping is worked out as * follows: two vertices are grouped together in the final partition if * they are grouped together in each minimizing partition. In general the * size of the final partition is not known in advance when the number * of columns in \p V is larger than one. * * * Finally, the algorithm \c IGRAPH_SCG_EXACT groups the vertices with * equal components in each eigenvector. The last three algorithms * essentially have linear running time and memory load. * * \param V The matrix of eigenvectors to be preserved by coarse * graining, each column is an eigenvector. * \param groups Pointer to an initialized vector, the result of the * SCG is stored here. * \param nt Positive integer. When \p algo is \c IGRAPH_SCG_OPTIMUM, * it gives the number of groups to partition each eigenvector * separately. When \p algo is \c IGRAPH_SCG_INTERV or \c * IGRAPH_SCG_INTERV_KM, it gives the number of intervals to * partition each eigenvector. This is ignored when \p algo is \c * IGRAPH_SCG_EXACT. * \param nt_vec A numeric vector of length one or the length must * match the number of eigenvectors given in \p V, or a \c NULL * pointer. If not \c NULL, then this argument gives the number of * groups or intervals, and \p nt is ignored. Different number of * groups or intervals can be specified for each eigenvector. * \param mtype The type of semi-projectors used in the SCG. Possible * values are \c IGRAPH_SCG_SYMMETRIC, \c IGRAPH_SCG_STOCHASTIC and * \c IGRAPH_SCG_LAPLACIAN. * \param algo The algorithm to solve the SCG problem. Possible * values: \c IGRAPH_SCG_OPTIMUM, \c IGRAPH_SCG_INTERV_KM, \c * IGRAPH_SCG_INTERV and \c IGRAPH_SCG_EXACT. Please see the * details about them above. * \param p A probability vector, or \c NULL. This argument must be * given if \p mtype is \c IGRAPH_SCG_STOCHASTIC, but it is ignored * otherwise. For the stochastic case it gives the stationary * probability distribution of a Markov chain, the one specified by * the graph/matrix under study. * \param maxiter A positive integer giving the number of iterations * of the k-means algorithm when \p algo is \c * IGRAPH_SCG_INTERV_KM. It is ignored in other cases. A reasonable * (initial) value for this argument is 100. * \return Error code. * * Time complexity: see description above. * * \sa \ref igraph_scg_adjacency(), \ref igraph_scg_laplacian(), \ref * igraph_scg_stochastic(). * * \example examples/simple/igraph_scg_grouping.c * \example examples/simple/igraph_scg_grouping2.c * \example examples/simple/igraph_scg_grouping3.c * \example examples/simple/igraph_scg_grouping4.c */ int igraph_scg_grouping(const igraph_matrix_t *V, igraph_vector_t *groups, igraph_integer_t nt, const igraph_vector_t *nt_vec, igraph_scg_matrix_t mtype, igraph_scg_algorithm_t algo, const igraph_vector_t *p, igraph_integer_t maxiter) { int no_of_nodes = (int) igraph_matrix_nrow(V); int nev = (int) igraph_matrix_ncol(V); igraph_matrix_int_t gr_mat; int i; if (nt_vec && igraph_vector_size(nt_vec) != 1 && igraph_vector_size(nt_vec) != nev) { IGRAPH_ERROR("Invalid length for interval specification", IGRAPH_EINVAL); } if (nt_vec && igraph_vector_size(nt_vec) == 1) { nt = (igraph_integer_t) VECTOR(*nt_vec)[0]; nt_vec = 0; } if (!nt_vec && algo != IGRAPH_SCG_EXACT) { if (nt <= 1 || nt >= no_of_nodes) { IGRAPH_ERROR("Invalid interval specification", IGRAPH_EINVAL); } } else if (algo != IGRAPH_SCG_EXACT) { igraph_real_t min, max; igraph_vector_minmax(nt_vec, &min, &max); if (min <= 1 || max >= no_of_nodes) { IGRAPH_ERROR("Invalid interval specification", IGRAPH_EINVAL); } } if (mtype == IGRAPH_SCG_STOCHASTIC && !p) { IGRAPH_ERROR("`p' must be given for the stochastic matrix case", IGRAPH_EINVAL); } if (p && igraph_vector_size(p) != no_of_nodes) { IGRAPH_ERROR("Invalid `p' vector size", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_vector_resize(groups, no_of_nodes)); #define INVEC(i) (nt_vec ? VECTOR(*nt_vec)[i] : nt) IGRAPH_CHECK(igraph_matrix_int_init(&gr_mat, no_of_nodes, nev)); IGRAPH_FINALLY(igraph_matrix_int_destroy, &gr_mat); switch (algo) { case IGRAPH_SCG_OPTIMUM: for (i = 0; i < nev; i++) { IGRAPH_CHECK(igraph_i_optimal_partition(&MATRIX(*V, 0, i), &MATRIX(gr_mat, 0, i), no_of_nodes, (int) INVEC(i), mtype, p ? VECTOR(*p) : 0, 0)); } break; case IGRAPH_SCG_INTERV_KM: for (i = 0; i < nev; i++) { igraph_vector_t tmpv; igraph_vector_view(&tmpv, &MATRIX(*V, 0, i), no_of_nodes); IGRAPH_CHECK(igraph_i_intervals_plus_kmeans(&tmpv, &MATRIX(gr_mat, 0, i), no_of_nodes, (int) INVEC(i), maxiter)); } break; case IGRAPH_SCG_INTERV: for (i = 0; i < nev; i++) { igraph_vector_t tmpv; igraph_vector_view(&tmpv, &MATRIX(*V, 0, i), no_of_nodes); IGRAPH_CHECK(igraph_i_intervals_method(&tmpv, &MATRIX(gr_mat, 0, i), no_of_nodes, (int) INVEC(i))); } break; case IGRAPH_SCG_EXACT: for (i = 0; i < nev; i++) { IGRAPH_CHECK(igraph_i_exact_coarse_graining(&MATRIX(*V, 0, i), &MATRIX(gr_mat, 0, i), no_of_nodes)); } break; } #undef INVEC if (nev == 1) { for (i = 0; i < no_of_nodes; i++) { VECTOR(*groups)[i] = MATRIX(gr_mat, i, 0); } } else { igraph_i_scg_groups_t *g = igraph_Calloc(no_of_nodes, igraph_i_scg_groups_t); int gr_nb = 0; IGRAPH_CHECK(igraph_matrix_int_transpose(&gr_mat)); for (i = 0; i < no_of_nodes; i++) { g[i].ind = i; g[i].n = nev; g[i].gr = &MATRIX(gr_mat, 0, i); } qsort(g, (size_t) no_of_nodes, sizeof(igraph_i_scg_groups_t), igraph_i_compare_groups); VECTOR(*groups)[g[0].ind] = gr_nb; for (i = 1; i < no_of_nodes; i++) { if (igraph_i_compare_groups(&g[i], &g[i - 1]) != 0) { gr_nb++; } VECTOR(*groups)[g[i].ind] = gr_nb; } igraph_Free(g); } igraph_matrix_int_destroy(&gr_mat); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_i_scg_semiprojectors_sym(const igraph_vector_t *groups, igraph_matrix_t *L, igraph_matrix_t *R, igraph_sparsemat_t *Lsparse, igraph_sparsemat_t *Rsparse, int no_of_groups, int no_of_nodes) { igraph_vector_t tab; int i; IGRAPH_VECTOR_INIT_FINALLY(&tab, no_of_groups); for (i = 0; i < no_of_nodes; i++) { VECTOR(tab)[ (int) VECTOR(*groups)[i] ] += 1; } for (i = 0; i < no_of_groups; i++) { VECTOR(tab)[i] = sqrt(VECTOR(tab)[i]); } if (L) { IGRAPH_CHECK(igraph_matrix_resize(L, no_of_groups, no_of_nodes)); igraph_matrix_null(L); for (i = 0; i < no_of_nodes; i++) { int g = (int) VECTOR(*groups)[i]; MATRIX(*L, g, i) = 1 / VECTOR(tab)[g]; } } if (R) { if (L) { IGRAPH_CHECK(igraph_matrix_update(R, L)); } else { IGRAPH_CHECK(igraph_matrix_resize(R, no_of_groups, no_of_nodes)); igraph_matrix_null(R); for (i = 0; i < no_of_nodes; i++) { int g = (int) VECTOR(*groups)[i]; MATRIX(*R, g, i) = 1 / VECTOR(tab)[g]; } } } if (Lsparse) { IGRAPH_CHECK(igraph_sparsemat_init(Lsparse, no_of_groups, no_of_nodes, /* nzmax= */ no_of_nodes)); for (i = 0; i < no_of_nodes; i++) { int g = (int) VECTOR(*groups)[i]; IGRAPH_CHECK(igraph_sparsemat_entry(Lsparse, g, i, 1 / VECTOR(tab)[g])); } } if (Rsparse) { IGRAPH_CHECK(igraph_sparsemat_init(Rsparse, no_of_groups, no_of_nodes, /* nzmax= */ no_of_nodes)); for (i = 0; i < no_of_nodes; i++) { int g = (int) VECTOR(*groups)[i]; IGRAPH_CHECK(igraph_sparsemat_entry(Rsparse, g, i, 1 / VECTOR(tab)[g])); } } igraph_vector_destroy(&tab); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_i_scg_semiprojectors_lap(const igraph_vector_t *groups, igraph_matrix_t *L, igraph_matrix_t *R, igraph_sparsemat_t *Lsparse, igraph_sparsemat_t *Rsparse, int no_of_groups, int no_of_nodes, igraph_scg_norm_t norm) { igraph_vector_t tab; int i; IGRAPH_VECTOR_INIT_FINALLY(&tab, no_of_groups); for (i = 0; i < no_of_nodes; i++) { VECTOR(tab)[ (int) VECTOR(*groups)[i] ] += 1; } for (i = 0; i < no_of_groups; i++) { VECTOR(tab)[i] = VECTOR(tab)[i]; } if (norm == IGRAPH_SCG_NORM_ROW) { if (L) { IGRAPH_CHECK(igraph_matrix_resize(L, no_of_groups, no_of_nodes)); igraph_matrix_null(L); for (i = 0; i < no_of_nodes; i++) { int g = (int) VECTOR(*groups)[i]; MATRIX(*L, g, i) = 1.0 / VECTOR(tab)[g]; } } if (R) { IGRAPH_CHECK(igraph_matrix_resize(R, no_of_groups, no_of_nodes)); igraph_matrix_null(R); for (i = 0; i < no_of_nodes; i++) { int g = (int) VECTOR(*groups)[i]; MATRIX(*R, g, i) = 1.0; } } if (Lsparse) { IGRAPH_CHECK(igraph_sparsemat_init(Lsparse, no_of_groups, no_of_nodes, /* nzmax= */ no_of_nodes)); for (i = 0; i < no_of_nodes; i++) { int g = (int) VECTOR(*groups)[i]; IGRAPH_CHECK(igraph_sparsemat_entry(Lsparse, g, i, 1.0 / VECTOR(tab)[g])); } } if (Rsparse) { IGRAPH_CHECK(igraph_sparsemat_init(Rsparse, no_of_groups, no_of_nodes, /* nzmax= */ no_of_nodes)); for (i = 0; i < no_of_nodes; i++) { int g = (int) VECTOR(*groups)[i]; IGRAPH_CHECK(igraph_sparsemat_entry(Rsparse, g, i, 1.0)); } } } else { if (L) { IGRAPH_CHECK(igraph_matrix_resize(L, no_of_groups, no_of_nodes)); igraph_matrix_null(L); for (i = 0; i < no_of_nodes; i++) { int g = (int) VECTOR(*groups)[i]; MATRIX(*L, g, i) = 1.0; } } if (R) { IGRAPH_CHECK(igraph_matrix_resize(R, no_of_groups, no_of_nodes)); igraph_matrix_null(R); for (i = 0; i < no_of_nodes; i++) { int g = (int) VECTOR(*groups)[i]; MATRIX(*R, g, i) = 1.0 / VECTOR(tab)[g]; } } if (Lsparse) { IGRAPH_CHECK(igraph_sparsemat_init(Lsparse, no_of_groups, no_of_nodes, /* nzmax= */ no_of_nodes)); for (i = 0; i < no_of_nodes; i++) { int g = (int) VECTOR(*groups)[i]; IGRAPH_CHECK(igraph_sparsemat_entry(Lsparse, g, i, 1.0)); } } if (Rsparse) { IGRAPH_CHECK(igraph_sparsemat_init(Rsparse, no_of_groups, no_of_nodes, /* nzmax= */ no_of_nodes)); for (i = 0; i < no_of_nodes; i++) { int g = (int) VECTOR(*groups)[i]; IGRAPH_CHECK(igraph_sparsemat_entry(Rsparse, g, i, 1.0 / VECTOR(tab)[g])); } } } igraph_vector_destroy(&tab); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_i_scg_semiprojectors_sto(const igraph_vector_t *groups, igraph_matrix_t *L, igraph_matrix_t *R, igraph_sparsemat_t *Lsparse, igraph_sparsemat_t *Rsparse, int no_of_groups, int no_of_nodes, const igraph_vector_t *p, igraph_scg_norm_t norm) { igraph_vector_t pgr, pnormed; int i; IGRAPH_VECTOR_INIT_FINALLY(&pgr, no_of_groups); IGRAPH_VECTOR_INIT_FINALLY(&pnormed, no_of_nodes); for (i = 0; i < no_of_nodes; i++) { int g = (int) VECTOR(*groups)[i]; VECTOR(pgr)[g] += VECTOR(*p)[i]; } for (i = 0; i < no_of_nodes; i++) { int g = (int) VECTOR(*groups)[i]; VECTOR(pnormed)[i] = VECTOR(*p)[i] / VECTOR(pgr)[g]; } if (norm == IGRAPH_SCG_NORM_ROW) { if (L) { IGRAPH_CHECK(igraph_matrix_resize(L, no_of_groups, no_of_nodes)); igraph_matrix_null(L); for (i = 0; i < no_of_nodes; i++) { int g = (int) VECTOR(*groups)[i]; MATRIX(*L, g, i) = VECTOR(pnormed)[i]; } } if (R) { IGRAPH_CHECK(igraph_matrix_resize(R, no_of_groups, no_of_nodes)); igraph_matrix_null(R); for (i = 0; i < no_of_nodes; i++) { int g = (int) VECTOR(*groups)[i]; MATRIX(*R, g, i) = 1.0; } } if (Lsparse) { IGRAPH_CHECK(igraph_sparsemat_init(Lsparse, no_of_groups, no_of_nodes, /* nzmax= */ no_of_nodes)); for (i = 0; i < no_of_nodes; i++) { int g = (int) VECTOR(*groups)[i]; IGRAPH_CHECK(igraph_sparsemat_entry(Lsparse, g, i, VECTOR(pnormed)[i])); } } if (Rsparse) { IGRAPH_CHECK(igraph_sparsemat_init(Rsparse, no_of_groups, no_of_nodes, /* nzmax= */ no_of_nodes)); for (i = 0; i < no_of_nodes; i++) { int g = (int) VECTOR(*groups)[i]; IGRAPH_CHECK(igraph_sparsemat_entry(Rsparse, g, i, 1.0)); } } } else { if (L) { IGRAPH_CHECK(igraph_matrix_resize(L, no_of_groups, no_of_nodes)); igraph_matrix_null(L); for (i = 0; i < no_of_nodes; i++) { int g = (int ) VECTOR(*groups)[i]; MATRIX(*L, g, i) = 1.0; } } if (R) { IGRAPH_CHECK(igraph_matrix_resize(R, no_of_groups, no_of_nodes)); igraph_matrix_null(R); for (i = 0; i < no_of_nodes; i++) { int g = (int) VECTOR(*groups)[i]; MATRIX(*R, g, i) = VECTOR(pnormed)[i]; } } if (Lsparse) { IGRAPH_CHECK(igraph_sparsemat_init(Lsparse, no_of_groups, no_of_nodes, /* nzmax= */ no_of_nodes)); for (i = 0; i < no_of_nodes; i++) { int g = (int) VECTOR(*groups)[i]; IGRAPH_CHECK(igraph_sparsemat_entry(Lsparse, g, i, 1.0)); } } if (Rsparse) { IGRAPH_CHECK(igraph_sparsemat_init(Rsparse, no_of_groups, no_of_nodes, /* nzmax= */ no_of_nodes)); for (i = 0; i < no_of_nodes; i++) { int g = (int) VECTOR(*groups)[i]; IGRAPH_CHECK(igraph_sparsemat_entry(Rsparse, g, i, VECTOR(pnormed)[i])); } } } igraph_vector_destroy(&pnormed); igraph_vector_destroy(&pgr); IGRAPH_FINALLY_CLEAN(2); return 0; } /** * \function igraph_scg_semiprojectors * \brief Compute SCG semi-projectors for a given partition * * The three types of semi-projectors are defined as follows. * Let gamma(j) label the group of vertex j in a partition of all the * vertices. * * * The symmetric semi-projectors are defined as *
* L[alpha,j] = R[alpha,j] = 1/sqrt(|alpha|) delta[alpha,gamma(j)], *
* the (row) Laplacian semi-projectors as *
* L[alpha,j] = 1/|alpha| delta[alpha,gamma(j)] *
* and *
* R[alpha,j] = delta[alpha,gamma(j)], *
* and the (row) stochastic semi-projectors as *
* L[alpha,j] = p[1][j] / sum(p[1][k]; k in gamma(j)) * delta[alpha,gamma(j)] *
* and *
* R[alpha,j] = delta[alpha,gamma(j)], *
* where p[1] is the (left) eigenvector associated with the * one-eigenvalue of the stochastic matrix. L and R are * defined in a symmetric way when \p norm is \c * IGRAPH_SCG_NORM_COL. All these semi-projectors verify various * properties described in the reference. * \param groups A vector of integers, giving the group label of every * vertex in the partition. Group labels should start at zero and * should be sequential. * \param mtype The type of semi-projectors. For now \c * IGRAPH_SCG_SYMMETRIC, \c IGRAPH_SCG_STOCHASTIC and \c * IGRAP_SCG_LAPLACIAN are supported. * \param L If not a \c NULL pointer, then it must be a pointer to * an initialized matrix. The left semi-projector is stored here. * \param R If not a \c NULL pointer, then it must be a pointer to * an initialized matrix. The right semi-projector is stored here. * \param Lsparse If not a \c NULL pointer, then it must be a pointer * to an uninitialized sparse matrix. The left semi-projector is * stored here. * \param Rsparse If not a \c NULL pointer, then it must be a pointer * to an uninitialized sparse matrix. The right semi-projector is * stored here. * \param p \c NULL, or a probability vector of the same length as \p * groups. \p p is the stationary probability distribution of a * Markov chain when \p mtype is \c IGRAPH_SCG_STOCHASTIC. This * argument is ignored in all other cases. * \param norm Either \c IGRAPH_SCG_NORM_ROW or \c IGRAPH_SCG_NORM_COL. * Specifies whether the rows or the columns of the Laplacian * matrix sum up to zero, or whether the rows or the columns of the * stochastic matrix sum up to one. * \return Error code. * * Time complexity: TODO. * * \sa \ref igraph_scg_adjacency(), \ref igraph_scg_stochastic() and * \ref igraph_scg_laplacian(), \ref igraph_scg_grouping(). * * \example examples/simple/igraph_scg_semiprojectors.c * \example examples/simple/igraph_scg_semiprojectors2.c * \example examples/simple/igraph_scg_semiprojectors3.c */ int igraph_scg_semiprojectors(const igraph_vector_t *groups, igraph_scg_matrix_t mtype, igraph_matrix_t *L, igraph_matrix_t *R, igraph_sparsemat_t *Lsparse, igraph_sparsemat_t *Rsparse, const igraph_vector_t *p, igraph_scg_norm_t norm) { int no_of_nodes = (int) igraph_vector_size(groups); int no_of_groups; igraph_real_t min, max; igraph_vector_minmax(groups, &min, &max); no_of_groups = (int) max + 1; if (min < 0 || max >= no_of_nodes) { IGRAPH_ERROR("Invalid membership vector", IGRAPH_EINVAL); } if (mtype == IGRAPH_SCG_STOCHASTIC && !p) { IGRAPH_ERROR("`p' must be given for the stochastic matrix case", IGRAPH_EINVAL); } if (p && igraph_vector_size(p) != no_of_nodes) { IGRAPH_ERROR("Invalid `p' vector length, should match number of vertices", IGRAPH_EINVAL); } switch (mtype) { case IGRAPH_SCG_SYMMETRIC: IGRAPH_CHECK(igraph_i_scg_semiprojectors_sym(groups, L, R, Lsparse, Rsparse, no_of_groups, no_of_nodes)); break; case IGRAPH_SCG_LAPLACIAN: IGRAPH_CHECK(igraph_i_scg_semiprojectors_lap(groups, L, R, Lsparse, Rsparse, no_of_groups, no_of_nodes, norm)); break; case IGRAPH_SCG_STOCHASTIC: IGRAPH_CHECK(igraph_i_scg_semiprojectors_sto(groups, L, R, Lsparse, Rsparse, no_of_groups, no_of_nodes, p, norm)); break; } return 0; } /** * \function igraph_scg_norm_eps * Calculate SCG residuals * * Computes |v[i]-Pv[i]|, where v[i] is the i-th eigenvector in \p V * and P is the projector corresponding to the \p mtype argument. * * \param V The matrix of eigenvectors to be preserved by coarse * graining, each column is an eigenvector. * \param groups A vector of integers, giving the group label of every * vertex in the partition. Group labels should start at zero and * should be sequential. * \param eps Pointer to a real value, the result is stored here. * \param mtype The type of semi-projectors. For now \c * IGRAPH_SCG_SYMMETRIC, \c IGRAPH_SCG_STOCHASTIC and \c * IGRAP_SCG_LAPLACIAN are supported. * \param p \c NULL, or a probability vector of the same length as \p * groups. \p p is the stationary probability distribution of a * Markov chain when \p mtype is \c IGRAPH_SCG_STOCHASTIC. This * argument is ignored in all other cases. * \param norm Either \c IGRAPH_SCG_NORM_ROW or \c IGRAPH_SCG_NORM_COL. * Specifies whether the rows or the columns of the Laplacian * matrix sum up to zero, or whether the rows or the columns of the * stochastic matrix sum up to one. * \return Error code. * * Time complexity: TODO. * * \sa \ref igraph_scg_adjacency(), \ref igraph_scg_stochastic() and * \ref igraph_scg_laplacian(), \ref igraph_scg_grouping(), \ref * igraph_scg_semiprojectors(). */ int igraph_scg_norm_eps(const igraph_matrix_t *V, const igraph_vector_t *groups, igraph_vector_t *eps, igraph_scg_matrix_t mtype, const igraph_vector_t *p, igraph_scg_norm_t norm) { int no_of_nodes = (int) igraph_vector_size(groups); int no_of_groups; int no_of_vectors = (int) igraph_matrix_ncol(V); igraph_real_t min, max; igraph_sparsemat_t Lsparse, Rsparse, Lsparse2, Rsparse2, Rsparse3, proj; igraph_vector_t x, res; int k, i; if (igraph_matrix_nrow(V) != no_of_nodes) { IGRAPH_ERROR("Eigenvector length and group vector length do not match", IGRAPH_EINVAL); } igraph_vector_minmax(groups, &min, &max); no_of_groups = (int) max + 1; if (min < 0 || max >= no_of_nodes) { IGRAPH_ERROR("Invalid membership vector", IGRAPH_EINVAL); } if (mtype == IGRAPH_SCG_STOCHASTIC && !p) { IGRAPH_ERROR("`p' must be given for the stochastic matrix case", IGRAPH_EINVAL); } if (p && igraph_vector_size(p) != no_of_nodes) { IGRAPH_ERROR("Invalid `p' vector length, should match number of vertices", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_scg_semiprojectors(groups, mtype, /* L= */ 0, /* R= */ 0, &Lsparse, &Rsparse, p, norm)); IGRAPH_FINALLY(igraph_sparsemat_destroy, &Lsparse); IGRAPH_FINALLY(igraph_sparsemat_destroy, &Rsparse); IGRAPH_CHECK(igraph_sparsemat_compress(&Lsparse, &Lsparse2)); IGRAPH_FINALLY(igraph_sparsemat_destroy, &Lsparse2); IGRAPH_CHECK(igraph_sparsemat_compress(&Rsparse, &Rsparse2)); IGRAPH_FINALLY(igraph_sparsemat_destroy, &Rsparse2); IGRAPH_CHECK(igraph_sparsemat_transpose(&Rsparse2, &Rsparse3, /*values=*/ 1)); IGRAPH_FINALLY(igraph_sparsemat_destroy, &Rsparse3); IGRAPH_CHECK(igraph_sparsemat_multiply(&Rsparse3, &Lsparse2, &proj)); IGRAPH_FINALLY(igraph_sparsemat_destroy, &proj); IGRAPH_VECTOR_INIT_FINALLY(&res, no_of_nodes); IGRAPH_CHECK(igraph_vector_resize(eps, no_of_vectors)); for (k = 0; k < no_of_vectors; k++) { igraph_vector_view(&x, &MATRIX(*V, 0, k), no_of_nodes); igraph_vector_null(&res); IGRAPH_CHECK(igraph_sparsemat_gaxpy(&proj, &x, &res)); VECTOR(*eps)[k] = 0.0; for (i = 0; i < no_of_nodes; i++) { igraph_real_t di = MATRIX(*V, i, k) - VECTOR(res)[i]; VECTOR(*eps)[k] += di * di; } VECTOR(*eps)[k] = sqrt(VECTOR(*eps)[k]); } igraph_vector_destroy(&res); igraph_sparsemat_destroy(&proj); igraph_sparsemat_destroy(&Rsparse3); igraph_sparsemat_destroy(&Rsparse2); igraph_sparsemat_destroy(&Lsparse2); igraph_sparsemat_destroy(&Rsparse); igraph_sparsemat_destroy(&Lsparse); IGRAPH_FINALLY_CLEAN(7); return 0; } int igraph_i_matrix_laplacian(const igraph_matrix_t *matrix, igraph_matrix_t *mymatrix, igraph_scg_norm_t norm) { igraph_vector_t degree; int i, j, n = (int) igraph_matrix_nrow(matrix); IGRAPH_CHECK(igraph_matrix_resize(mymatrix, n, n)); IGRAPH_VECTOR_INIT_FINALLY(°ree, n); if (norm == IGRAPH_SCG_NORM_ROW) { IGRAPH_CHECK(igraph_matrix_rowsum(matrix, °ree)); } else { IGRAPH_CHECK(igraph_matrix_colsum(matrix, °ree)); } for (i = 0; i < n; i++) { VECTOR(degree)[i] -= MATRIX(*matrix, i, i); } for (i = 0; i < n; i++) { for (j = 0; j < n; j++) { MATRIX(*mymatrix, i, j) = - MATRIX(*matrix, i, j); } MATRIX(*mymatrix, i, i) = VECTOR(degree)[i]; } igraph_vector_destroy(°ree); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_i_sparsemat_laplacian(const igraph_sparsemat_t *sparse, igraph_sparsemat_t *mysparse, igraph_scg_norm_t norm) { igraph_vector_t degree; int i, n = (int) igraph_sparsemat_nrow(sparse); int nzmax = igraph_sparsemat_nzmax(sparse); igraph_sparsemat_iterator_t it; IGRAPH_CHECK(igraph_sparsemat_init(mysparse, n, n, nzmax + n)); IGRAPH_FINALLY(igraph_sparsemat_destroy, mysparse); igraph_sparsemat_iterator_init(&it, (igraph_sparsemat_t *) sparse); IGRAPH_VECTOR_INIT_FINALLY(°ree, n); for (igraph_sparsemat_iterator_reset(&it); !igraph_sparsemat_iterator_end(&it); igraph_sparsemat_iterator_next(&it)) { int row = igraph_sparsemat_iterator_row(&it); int col = igraph_sparsemat_iterator_col(&it); if (row != col) { igraph_real_t val = igraph_sparsemat_iterator_get(&it); if (norm == IGRAPH_SCG_NORM_ROW) { VECTOR(degree)[row] += val; } else { VECTOR(degree)[col] += val; } } } /* Diagonal */ for (i = 0; i < n; i++) { igraph_sparsemat_entry(mysparse, i, i, VECTOR(degree)[i]); } /* And the rest, filter out diagonal elements */ for (igraph_sparsemat_iterator_reset(&it); !igraph_sparsemat_iterator_end(&it); igraph_sparsemat_iterator_next(&it)) { int row = igraph_sparsemat_iterator_row(&it); int col = igraph_sparsemat_iterator_col(&it); if (row != col) { igraph_real_t val = igraph_sparsemat_iterator_get(&it); igraph_sparsemat_entry(mysparse, row, col, -val); } } igraph_vector_destroy(°ree); IGRAPH_FINALLY_CLEAN(2); /* + mysparse */ return 0; } int igraph_i_matrix_stochastic(const igraph_matrix_t *matrix, igraph_matrix_t *mymatrix, igraph_scg_norm_t norm) { int i, j, n = (int) igraph_matrix_nrow(matrix); IGRAPH_CHECK(igraph_matrix_copy(mymatrix, matrix)); if (norm == IGRAPH_SCG_NORM_ROW) { for (i = 0; i < n; i++) { igraph_real_t sum = 0.0; for (j = 0; j < n; j++) { sum += MATRIX(*matrix, i, j); } if (sum == 0) { IGRAPH_WARNING("Zero degree vertices"); } for (j = 0; j < n; j++) { MATRIX(*mymatrix, i, j) = MATRIX(*matrix, i, j) / sum; } } } else { for (i = 0; i < n; i++) { igraph_real_t sum = 0.0; for (j = 0; j < n; j++) { sum += MATRIX(*matrix, j, i); } if (sum == 0) { IGRAPH_WARNING("Zero degree vertices"); } for (j = 0; j < n; j++) { MATRIX(*mymatrix, j, i) = MATRIX(*matrix, j, i) / sum; } } } return 0; } int igraph_i_normalize_sparsemat(igraph_sparsemat_t *sparsemat, igraph_bool_t column_wise); int igraph_i_sparsemat_stochastic(const igraph_sparsemat_t *sparse, igraph_sparsemat_t *mysparse, igraph_scg_norm_t norm) { IGRAPH_CHECK(igraph_sparsemat_copy(mysparse, sparse)); IGRAPH_FINALLY(igraph_sparsemat_destroy, mysparse); IGRAPH_CHECK(igraph_i_normalize_sparsemat(mysparse, norm == IGRAPH_SCG_NORM_COL)); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_i_scg_get_result(igraph_scg_matrix_t type, const igraph_matrix_t *matrix, const igraph_sparsemat_t *sparsemat, const igraph_sparsemat_t *Lsparse, const igraph_sparsemat_t *Rsparse_t, igraph_t *scg_graph, igraph_matrix_t *scg_matrix, igraph_sparsemat_t *scg_sparsemat, igraph_bool_t directed) { /* We need to calculate either scg_matrix (if input is dense), or scg_sparsemat (if input is sparse). For the latter we might need to temporarily use another matrix. */ if (matrix) { igraph_matrix_t *my_scg_matrix = scg_matrix, v_scg_matrix; igraph_matrix_t tmp; igraph_sparsemat_t *myLsparse = (igraph_sparsemat_t *) Lsparse, v_Lsparse; if (!scg_matrix) { my_scg_matrix = &v_scg_matrix; IGRAPH_CHECK(igraph_matrix_init(my_scg_matrix, 0, 0)); IGRAPH_FINALLY(igraph_matrix_destroy, my_scg_matrix); } if (!igraph_sparsemat_is_cc(Lsparse)) { myLsparse = &v_Lsparse; IGRAPH_CHECK(igraph_sparsemat_compress(Lsparse, myLsparse)); IGRAPH_FINALLY(igraph_sparsemat_destroy, myLsparse); } IGRAPH_CHECK(igraph_matrix_init(&tmp, 0, 0)); IGRAPH_FINALLY(igraph_matrix_destroy, &tmp); IGRAPH_CHECK(igraph_sparsemat_dense_multiply(matrix, Rsparse_t, &tmp)); IGRAPH_CHECK(igraph_sparsemat_multiply_by_dense(myLsparse, &tmp, my_scg_matrix)); igraph_matrix_destroy(&tmp); IGRAPH_FINALLY_CLEAN(1); if (scg_sparsemat) { IGRAPH_CHECK(igraph_matrix_as_sparsemat(scg_sparsemat, my_scg_matrix, /* tol= */ 0)); IGRAPH_FINALLY(igraph_sparsemat_destroy, scg_sparsemat); } if (scg_graph) { if (type != IGRAPH_SCG_LAPLACIAN) { IGRAPH_CHECK(igraph_weighted_adjacency(scg_graph, my_scg_matrix, directed ? IGRAPH_ADJ_DIRECTED : IGRAPH_ADJ_UNDIRECTED, "weight", /*loops=*/ 1)); } else { int i, j, n = (int) igraph_matrix_nrow(my_scg_matrix); igraph_matrix_t tmp; IGRAPH_MATRIX_INIT_FINALLY(&tmp, n, n); for (i = 0; i < n; i++) { for (j = 0; j < n; j++) { MATRIX(tmp, i, j) = -MATRIX(*my_scg_matrix, i, j); } MATRIX(tmp, i, i) = 0; } IGRAPH_CHECK(igraph_weighted_adjacency(scg_graph, &tmp, directed ? IGRAPH_ADJ_DIRECTED : IGRAPH_ADJ_UNDIRECTED, "weight", /*loops=*/ 0)); igraph_matrix_destroy(&tmp); IGRAPH_FINALLY_CLEAN(1); } IGRAPH_FINALLY(igraph_destroy, scg_graph); } if (scg_graph) { IGRAPH_FINALLY_CLEAN(1); } if (scg_sparsemat) { IGRAPH_FINALLY_CLEAN(1); } if (!igraph_sparsemat_is_cc(Lsparse)) { igraph_sparsemat_destroy(myLsparse); IGRAPH_FINALLY_CLEAN(1); } if (!scg_matrix) { igraph_matrix_destroy(my_scg_matrix); IGRAPH_FINALLY_CLEAN(1); } } else { /* sparsemat */ igraph_sparsemat_t *my_scg_sparsemat = scg_sparsemat, v_scg_sparsemat; igraph_sparsemat_t tmp, *mysparsemat = (igraph_sparsemat_t *) sparsemat, v_sparsemat, *myLsparse = (igraph_sparsemat_t *) Lsparse, v_Lsparse; if (!scg_sparsemat) { my_scg_sparsemat = &v_scg_sparsemat; } if (!igraph_sparsemat_is_cc(sparsemat)) { mysparsemat = &v_sparsemat; IGRAPH_CHECK(igraph_sparsemat_compress(sparsemat, mysparsemat)); IGRAPH_FINALLY(igraph_sparsemat_destroy, mysparsemat); } if (!igraph_sparsemat_is_cc(Lsparse)) { myLsparse = &v_Lsparse; IGRAPH_CHECK(igraph_sparsemat_compress(Lsparse, myLsparse)); IGRAPH_FINALLY(igraph_sparsemat_destroy, myLsparse); } IGRAPH_CHECK(igraph_sparsemat_multiply(mysparsemat, Rsparse_t, &tmp)); IGRAPH_FINALLY(igraph_sparsemat_destroy, &tmp); IGRAPH_CHECK(igraph_sparsemat_multiply(myLsparse, &tmp, my_scg_sparsemat)); igraph_sparsemat_destroy(&tmp); IGRAPH_FINALLY_CLEAN(1); IGRAPH_FINALLY(igraph_sparsemat_destroy, my_scg_sparsemat); if (scg_matrix) { IGRAPH_CHECK(igraph_sparsemat_as_matrix(scg_matrix, my_scg_sparsemat)); } if (scg_graph) { if (type != IGRAPH_SCG_LAPLACIAN) { IGRAPH_CHECK(igraph_weighted_sparsemat(scg_graph, my_scg_sparsemat, directed, "weight", /*loops=*/ 1)); } else { igraph_sparsemat_t tmp; IGRAPH_CHECK(igraph_sparsemat_copy(&tmp, my_scg_sparsemat)); IGRAPH_FINALLY(igraph_sparsemat_destroy, &tmp); IGRAPH_CHECK(igraph_sparsemat_neg(&tmp)); IGRAPH_CHECK(igraph_weighted_sparsemat(scg_graph, &tmp, directed, "weight", /*loops=*/ 0)); igraph_sparsemat_destroy(&tmp); IGRAPH_FINALLY_CLEAN(1); } IGRAPH_FINALLY(igraph_destroy, scg_graph); } if (scg_graph) { IGRAPH_FINALLY_CLEAN(1); } if (!scg_sparsemat) { igraph_sparsemat_destroy(my_scg_sparsemat); } IGRAPH_FINALLY_CLEAN(1); /* my_scg_sparsemat */ if (!igraph_sparsemat_is_cc(Lsparse)) { igraph_sparsemat_destroy(myLsparse); IGRAPH_FINALLY_CLEAN(1); } if (!igraph_sparsemat_is_cc(sparsemat)) { igraph_sparsemat_destroy(mysparsemat); IGRAPH_FINALLY_CLEAN(1); } } return 0; } int igraph_i_scg_common_checks(const igraph_t *graph, const igraph_matrix_t *matrix, const igraph_sparsemat_t *sparsemat, const igraph_vector_t *ev, igraph_integer_t nt, const igraph_vector_t *nt_vec, const igraph_matrix_t *vectors, const igraph_matrix_complex_t *vectors_cmplx, const igraph_vector_t *groups, const igraph_t *scg_graph, const igraph_matrix_t *scg_matrix, const igraph_sparsemat_t *scg_sparsemat, const igraph_vector_t *p, igraph_real_t *evmin, igraph_real_t *evmax) { int no_of_nodes = -1; igraph_real_t min, max; int no_of_ev = (int) igraph_vector_size(ev); if ( (graph ? 1 : 0) + (matrix ? 1 : 0) + (sparsemat ? 1 : 0) != 1 ) { IGRAPH_ERROR("Give exactly one of `graph', `matrix' and `sparsemat'", IGRAPH_EINVAL); } if (graph) { no_of_nodes = igraph_vcount(graph); } else if (matrix) { no_of_nodes = (int) igraph_matrix_nrow(matrix); } else if (sparsemat) { no_of_nodes = (int) igraph_sparsemat_nrow(sparsemat); } if ((matrix && igraph_matrix_ncol(matrix) != no_of_nodes) || (sparsemat && igraph_sparsemat_ncol(sparsemat) != no_of_nodes)) { IGRAPH_ERROR("Matrix must be square", IGRAPH_NONSQUARE); } igraph_vector_minmax(ev, evmin, evmax); if (*evmin < 0 || *evmax >= no_of_nodes) { IGRAPH_ERROR("Invalid eigenvectors given", IGRAPH_EINVAL); } if (!nt_vec && (nt <= 1 || nt >= no_of_nodes)) { IGRAPH_ERROR("Invalid interval specification", IGRAPH_EINVAL); } if (nt_vec) { if (igraph_vector_size(nt_vec) != 1 && igraph_vector_size(nt_vec) != no_of_ev) { IGRAPH_ERROR("Invalid length for interval specification", IGRAPH_EINVAL); } igraph_vector_minmax(nt_vec, &min, &max); if (min <= 1 || max >= no_of_nodes) { IGRAPH_ERROR("Invalid interval specification", IGRAPH_EINVAL); } } if (vectors && igraph_matrix_size(vectors) != 0 && (igraph_matrix_ncol(vectors) != no_of_ev || igraph_matrix_nrow(vectors) != no_of_nodes)) { IGRAPH_ERROR("Invalid eigenvector matrix size", IGRAPH_EINVAL); } if (vectors_cmplx && igraph_matrix_complex_size(vectors_cmplx) != 0 && (igraph_matrix_complex_ncol(vectors_cmplx) != no_of_ev || igraph_matrix_complex_nrow(vectors_cmplx) != no_of_nodes)) { IGRAPH_ERROR("Invalid eigenvector matrix size", IGRAPH_EINVAL); } if (groups && igraph_vector_size(groups) != 0 && igraph_vector_size(groups) != no_of_nodes) { IGRAPH_ERROR("Invalid `groups' vector size", IGRAPH_EINVAL); } if ( (scg_graph != 0) + (scg_matrix != 0) + (scg_sparsemat != 0) == 0 ) { IGRAPH_ERROR("No output is requested, please give at least one of " "`scg_graph', `scg_matrix' and `scg_sparsemat'", IGRAPH_EINVAL); } if (p && igraph_vector_size(p) != 0 && igraph_vector_size(p) != no_of_nodes) { IGRAPH_ERROR("Invalid `p' vector size", IGRAPH_EINVAL); } return 0; } /** * \function igraph_scg_adjacency * Spectral coarse graining, symmetric case. * * This function handles all the steps involved in the Spectral Coarse * Graining (SCG) of some matrices and graphs as described in the * reference below. * * \param graph The input graph. Exactly one of \p graph, \p matrix * and \p sparsemat must be given, the other two must be \c NULL * pointers. * \param matrix The input matrix. Exactly one of \p graph, \p matrix * and \p sparsemat must be given, the other two must be \c NULL * pointers. * \param sparsemat The input sparse matrix. Exactly one of \p graph, * \p matrix and \p sparsemat must be given, the other two must be * \c NULL pointers. * \param ev A vector of positive integers giving the indexes of the * eigenpairs to be preserved. 1 designates the eigenvalue with * largest algebraic value, 2 the one with second largest algebraic * value, etc. * \param nt Positive integer. When \p algo is \c IGRAPH_SCG_OPTIMUM, * it gives the number of groups to partition each eigenvector * separately. When \p algo is \c IGRAPH_SCG_INTERV or \c * IGRAPH_SCG_INTERV_KM, it gives the number of intervals to * partition each eigenvector. This is ignored when \p algo is \c * IGRAPH_SCG_EXACT. * \param nt_vec A numeric vector of length one or the length must * match the number of eigenvectors given in \p V, or a \c NULL * pointer. If not \c NULL, then this argument gives the number of * groups or intervals, and \p nt is ignored. Different number of * groups or intervals can be specified for each eigenvector. * \param algo The algorithm to solve the SCG problem. Possible * values: \c IGRAPH_SCG_OPTIMUM, \c IGRAPH_SCG_INTERV_KM, \c * IGRAPH_SCG_INTERV and \c IGRAPH_SCG_EXACT. Please see the * details about them above. * \param values If this is not \c NULL and the eigenvectors are * re-calculated, then the eigenvalues are stored here. * \param vectors If this is not \c NULL, and not a zero-length * matrix, then it is interpreted as the eigenvectors to use for * the coarse-graining. Otherwise the eigenvectors are * re-calculated, and they are stored here. (If this is not \c NULL.) * \param groups If this is not \c NULL, and not a zero-length vector, * then it is interpreted as the vector of group labels. (Group * labels are integers from zero and are sequential.) Otherwise * group labels are re-calculated and stored here, if this argument * is not a null pointer. * \param use_arpack Whether to use ARPACK for solving the * eigenproblem. Currently ARPACK is not implemented. * \param maxiter A positive integer giving the number of iterations * of the k-means algorithm when \p algo is \c * IGRAPH_SCG_INTERV_KM. It is ignored in other cases. A reasonable * (initial) value for this argument is 100. * \param scg_graph If not a \c NULL pointer, then the coarse-grained * graph is returned here. * \param scg_matrix If not a \c NULL pointer, then it must be an * initialied matrix, and the coarse-grained matrix is returned * here. * \param scg_sparsemat If not a \c NULL pointer, then the coarse * grained matrix is returned here, in sparse matrix form. * \param L If not a \c NULL pointer, then it must be an initialized * matrix and the left semi-projector is returned here. * \param R If not a \c NULL pointer, then it must be an initialized * matrix and the right semi-projector is returned here. * \param Lsparse If not a \c NULL pointer, then the left * semi-projector is returned here. * \param Rsparse If not a \c NULL pointer, then the right * semi-projector is returned here. * \return Error code. * * Time complexity: TODO. * * \sa \ref igraph_scg_grouping(), \ref igraph_scg_semiprojectors(), * \ref igraph_scg_stochastic() and \ref igraph_scg_laplacian(). * * \example examples/simple/scg.c */ int igraph_scg_adjacency(const igraph_t *graph, const igraph_matrix_t *matrix, const igraph_sparsemat_t *sparsemat, const igraph_vector_t *ev, igraph_integer_t nt, const igraph_vector_t *nt_vec, igraph_scg_algorithm_t algo, igraph_vector_t *values, igraph_matrix_t *vectors, igraph_vector_t *groups, igraph_bool_t use_arpack, igraph_integer_t maxiter, igraph_t *scg_graph, igraph_matrix_t *scg_matrix, igraph_sparsemat_t *scg_sparsemat, igraph_matrix_t *L, igraph_matrix_t *R, igraph_sparsemat_t *Lsparse, igraph_sparsemat_t *Rsparse) { igraph_sparsemat_t *mysparsemat = (igraph_sparsemat_t*) sparsemat, real_sparsemat; int no_of_ev = (int) igraph_vector_size(ev); /* eigenvectors are calculated and returned */ igraph_bool_t do_vectors = vectors && igraph_matrix_size(vectors) == 0; /* groups are calculated */ igraph_bool_t do_groups = !groups || igraph_vector_size(groups) == 0; /* eigenvectors are not returned but must be calculated for groups */ igraph_bool_t tmp_vectors = !do_vectors && do_groups; /* need temporary vector for groups */ igraph_bool_t tmp_groups = !groups; igraph_matrix_t myvectors; igraph_vector_t mygroups; igraph_bool_t tmp_lsparse = !Lsparse, tmp_rsparse = !Rsparse; igraph_sparsemat_t myLsparse, myRsparse, tmpsparse, Rsparse_t; int no_of_nodes; igraph_real_t evmin, evmax; igraph_bool_t directed; /* --------------------------------------------------------------------*/ /* Argument checks */ IGRAPH_CHECK(igraph_i_scg_common_checks(graph, matrix, sparsemat, ev, nt, nt_vec, vectors, 0, groups, scg_graph, scg_matrix, scg_sparsemat, /*p=*/ 0, &evmin, &evmax)); if (graph) { no_of_nodes = igraph_vcount(graph); directed = igraph_is_directed(graph); } else if (matrix) { no_of_nodes = (int) igraph_matrix_nrow(matrix); directed = !igraph_matrix_is_symmetric(matrix); } else { no_of_nodes = (int) igraph_sparsemat_nrow(sparsemat); directed = !igraph_sparsemat_is_symmetric(sparsemat); } /* -------------------------------------------------------------------- */ /* Convert graph, if needed */ if (graph) { mysparsemat = &real_sparsemat; IGRAPH_CHECK(igraph_get_sparsemat(graph, mysparsemat)); IGRAPH_FINALLY(igraph_sparsemat_destroy, mysparsemat); } /* -------------------------------------------------------------------- */ /* Compute eigenpairs, if needed */ if (tmp_vectors) { vectors = &myvectors; IGRAPH_MATRIX_INIT_FINALLY(vectors, no_of_nodes, no_of_ev); } if (do_vectors || tmp_vectors) { igraph_arpack_options_t options; igraph_eigen_which_t which; igraph_matrix_t tmp; igraph_vector_t tmpev; igraph_vector_t tmpeval; int i; which.pos = IGRAPH_EIGEN_SELECT; which.il = (int) (no_of_nodes - evmax + 1); which.iu = (int) (no_of_nodes - evmin + 1); if (values) { IGRAPH_VECTOR_INIT_FINALLY(&tmpeval, 0); } IGRAPH_CHECK(igraph_matrix_init(&tmp, no_of_nodes, which.iu - which.il + 1)); IGRAPH_FINALLY(igraph_matrix_destroy, &tmp); IGRAPH_CHECK(igraph_eigen_matrix_symmetric(matrix, mysparsemat, /* fun= */ 0, no_of_nodes, /* extra= */ 0, /* algorithm= */ use_arpack ? IGRAPH_EIGEN_ARPACK : IGRAPH_EIGEN_LAPACK, &which, &options, /*storage=*/ 0, values ? &tmpeval : 0, &tmp)); IGRAPH_VECTOR_INIT_FINALLY(&tmpev, no_of_ev); for (i = 0; i < no_of_ev; i++) { VECTOR(tmpev)[i] = evmax - VECTOR(*ev)[i]; } if (values) { IGRAPH_CHECK(igraph_vector_index(&tmpeval, values, &tmpev)); } IGRAPH_CHECK(igraph_matrix_select_cols(&tmp, vectors, &tmpev)); igraph_vector_destroy(&tmpev); igraph_matrix_destroy(&tmp); IGRAPH_FINALLY_CLEAN(2); if (values) { igraph_vector_destroy(&tmpeval); IGRAPH_FINALLY_CLEAN(1); } } /* -------------------------------------------------------------------- */ /* Work out groups, if needed */ if (tmp_groups) { groups = &mygroups; IGRAPH_VECTOR_INIT_FINALLY((igraph_vector_t*)groups, no_of_nodes); } if (do_groups) { IGRAPH_CHECK(igraph_scg_grouping(vectors, (igraph_vector_t*)groups, nt, nt_vec, IGRAPH_SCG_SYMMETRIC, algo, /*p=*/ 0, maxiter)); } /* -------------------------------------------------------------------- */ /* Perform coarse graining */ if (tmp_lsparse) { Lsparse = &myLsparse; } if (tmp_rsparse) { Rsparse = &myRsparse; } IGRAPH_CHECK(igraph_scg_semiprojectors(groups, IGRAPH_SCG_SYMMETRIC, L, R, Lsparse, Rsparse, /*p=*/ 0, IGRAPH_SCG_NORM_ROW)); if (tmp_groups) { igraph_vector_destroy((igraph_vector_t*) groups); IGRAPH_FINALLY_CLEAN(1); } if (tmp_vectors) { igraph_matrix_destroy(vectors); IGRAPH_FINALLY_CLEAN(1); } if (Rsparse) { IGRAPH_FINALLY(igraph_sparsemat_destroy, Rsparse); } if (Lsparse) { IGRAPH_FINALLY(igraph_sparsemat_destroy, Lsparse); } /* -------------------------------------------------------------------- */ /* Compute coarse grained matrix/graph/sparse matrix */ IGRAPH_CHECK(igraph_sparsemat_compress(Rsparse, &tmpsparse)); IGRAPH_FINALLY(igraph_sparsemat_destroy, &tmpsparse); IGRAPH_CHECK(igraph_sparsemat_transpose(&tmpsparse, &Rsparse_t, /*values=*/ 1)); igraph_sparsemat_destroy(&tmpsparse); IGRAPH_FINALLY_CLEAN(1); IGRAPH_FINALLY(igraph_sparsemat_destroy, &Rsparse_t); IGRAPH_CHECK(igraph_i_scg_get_result(IGRAPH_SCG_SYMMETRIC, matrix, mysparsemat, Lsparse, &Rsparse_t, scg_graph, scg_matrix, scg_sparsemat, directed)); /* -------------------------------------------------------------------- */ /* Clean up */ igraph_sparsemat_destroy(&Rsparse_t); IGRAPH_FINALLY_CLEAN(1); if (Lsparse) { IGRAPH_FINALLY_CLEAN(1); } if (Rsparse) { IGRAPH_FINALLY_CLEAN(1); } if (graph) { igraph_sparsemat_destroy(mysparsemat); IGRAPH_FINALLY_CLEAN(1); } return 0; } /** * \function igraph_scg_stochastic * Spectral coarse graining, stochastic case. * * This function handles all the steps involved in the Spectral Coarse * Graining (SCG) of some matrices and graphs as described in the * reference below. * * \param graph The input graph. Exactly one of \p graph, \p matrix * and \p sparsemat must be given, the other two must be \c NULL * pointers. * \param matrix The input matrix. Exactly one of \p graph, \p matrix * and \p sparsemat must be given, the other two must be \c NULL * pointers. * \param sparsemat The input sparse matrix. Exactly one of \p graph, * \p matrix and \p sparsemat must be given, the other two must be * \c NULL pointers. * \param ev A vector of positive integers giving the indexes of the * eigenpairs to be preserved. 1 designates the eigenvalue with * largest magnitude, 2 the one with second largest magnitude, etc. * \param nt Positive integer. When \p algo is \c IGRAPH_SCG_OPTIMUM, * it gives the number of groups to partition each eigenvector * separately. When \p algo is \c IGRAPH_SCG_INTERV or \c * IGRAPH_SCG_INTERV_KM, it gives the number of intervals to * partition each eigenvector. This is ignored when \p algo is \c * IGRAPH_SCG_EXACT. * \param nt_vec A numeric vector of length one or the length must * match the number of eigenvectors given in \p V, or a \c NULL * pointer. If not \c NULL, then this argument gives the number of * groups or intervals, and \p nt is ignored. Different number of * groups or intervals can be specified for each eigenvector. * \param algo The algorithm to solve the SCG problem. Possible * values: \c IGRAPH_SCG_OPTIMUM, \c IGRAPH_SCG_INTERV_KM, \c * IGRAPH_SCG_INTERV and \c IGRAPH_SCG_EXACT. Please see the * details about them above. * \param norm Either \c IGRAPH_SCG_NORM_ROW or \c IGRAPH_SCG_NORM_COL. * Specifies whether the rows or the columns of the * stochastic matrix sum up to one. * \param values If this is not \c NULL and the eigenvectors are * re-calculated, then the eigenvalues are stored here. * \param vectors If this is not \c NULL, and not a zero-length * matrix, then it is interpreted as the eigenvectors to use for * the coarse-graining. Otherwise the eigenvectors are * re-calculated, and they are stored here. (If this is not \c NULL.) * \param groups If this is not \c NULL, and not a zero-length vector, * then it is interpreted as the vector of group labels. (Group * labels are integers from zero and are sequential.) Otherwise * group labels are re-calculated and stored here, if this argument * is not a null pointer. * \param p If this is not \c NULL, and not zero length, then it is * interpreted as the stationary probability distribution of the * Markov chain corresponding to the input matrix/graph. Its length * must match the number of vertices in the input graph (or number * of rows in the input matrix). If not given, then the stationary * distribution is calculated and stored here. (Unless this * argument is a \c NULL pointer, in which case it is not stored.) * \param use_arpack Whether to use ARPACK for solving the * eigenproblem. Currently ARPACK is not implemented. * \param maxiter A positive integer giving the number of iterations * of the k-means algorithm when \p algo is \c * IGRAPH_SCG_INTERV_KM. It is ignored in other cases. A reasonable * (initial) value for this argument is 100. * \param scg_graph If not a \c NULL pointer, then the coarse-grained * graph is returned here. * \param scg_matrix If not a \c NULL pointer, then it must be an * initialied matrix, and the coarse-grained matrix is returned * here. * \param scg_sparsemat If not a \c NULL pointer, then the coarse * grained matrix is returned here, in sparse matrix form. * \param L If not a \c NULL pointer, then it must be an initialized * matrix and the left semi-projector is returned here. * \param R If not a \c NULL pointer, then it must be an initialized * matrix and the right semi-projector is returned here. * \param Lsparse If not a \c NULL pointer, then the left * semi-projector is returned here. * \param Rsparse If not a \c NULL pointer, then the right * semi-projector is returned here. * \return Error code. * * Time complexity: TODO. * * \sa \ref igraph_scg_grouping(), \ref igraph_scg_semiprojectors(), * \ref igraph_scg_adjacency() and \ref igraph_scg_laplacian(). * * \example examples/simple/scg2.c */ int igraph_scg_stochastic(const igraph_t *graph, const igraph_matrix_t *matrix, const igraph_sparsemat_t *sparsemat, const igraph_vector_t *ev, igraph_integer_t nt, const igraph_vector_t *nt_vec, igraph_scg_algorithm_t algo, igraph_scg_norm_t norm, igraph_vector_complex_t *values, igraph_matrix_complex_t *vectors, igraph_vector_t *groups, igraph_vector_t *p, igraph_bool_t use_arpack, igraph_integer_t maxiter, igraph_t *scg_graph, igraph_matrix_t *scg_matrix, igraph_sparsemat_t *scg_sparsemat, igraph_matrix_t *L, igraph_matrix_t *R, igraph_sparsemat_t *Lsparse, igraph_sparsemat_t *Rsparse) { igraph_matrix_t *mymatrix = (igraph_matrix_t*) matrix, real_matrix; igraph_sparsemat_t *mysparsemat = (igraph_sparsemat_t*) sparsemat, real_sparsemat; int no_of_nodes; igraph_real_t evmin, evmax; igraph_arpack_options_t options; igraph_eigen_which_t which; /* eigenvectors are calculated and returned */ igraph_bool_t do_vectors = vectors && igraph_matrix_complex_size(vectors) == 0; /* groups are calculated */ igraph_bool_t do_groups = !groups || igraph_vector_size(groups) == 0; igraph_bool_t tmp_groups = !groups; /* eigenvectors are not returned but must be calculated for groups */ igraph_bool_t tmp_vectors = !do_vectors && do_groups; igraph_matrix_complex_t myvectors; igraph_vector_t mygroups; igraph_bool_t do_p = !p || igraph_vector_size(p) == 0; igraph_vector_t *myp = (igraph_vector_t *) p, real_p; int no_of_ev = (int) igraph_vector_size(ev); igraph_bool_t tmp_lsparse = !Lsparse, tmp_rsparse = !Rsparse; igraph_sparsemat_t myLsparse, myRsparse, tmpsparse, Rsparse_t; /* --------------------------------------------------------------------*/ /* Argument checks */ IGRAPH_CHECK(igraph_i_scg_common_checks(graph, matrix, sparsemat, ev, nt, nt_vec, 0, vectors, groups, scg_graph, scg_matrix, scg_sparsemat, p, &evmin, &evmax)); if (graph) { no_of_nodes = igraph_vcount(graph); } else if (matrix) { no_of_nodes = (int) igraph_matrix_nrow(matrix); } else { no_of_nodes = (int) igraph_sparsemat_nrow(sparsemat); } /* -------------------------------------------------------------------- */ /* Convert graph, if needed */ if (graph) { mysparsemat = &real_sparsemat; IGRAPH_CHECK(igraph_get_stochastic_sparsemat(graph, mysparsemat, norm == IGRAPH_SCG_NORM_COL)); IGRAPH_FINALLY(igraph_sparsemat_destroy, mysparsemat); } else if (matrix) { mymatrix = &real_matrix; IGRAPH_CHECK(igraph_i_matrix_stochastic(matrix, mymatrix, norm)); IGRAPH_FINALLY(igraph_matrix_destroy, mymatrix); } else { /* sparsemat */ mysparsemat = &real_sparsemat; IGRAPH_CHECK(igraph_i_sparsemat_stochastic(sparsemat, mysparsemat, norm)); IGRAPH_FINALLY(igraph_sparsemat_destroy, mysparsemat); } /* -------------------------------------------------------------------- */ /* Compute eigenpairs, if needed */ if (tmp_vectors) { vectors = &myvectors; IGRAPH_CHECK(igraph_matrix_complex_init(vectors, no_of_nodes, no_of_ev)); IGRAPH_FINALLY(igraph_matrix_complex_destroy, vectors); } if (do_vectors || tmp_vectors) { igraph_matrix_complex_t tmp; igraph_vector_t tmpev; igraph_vector_complex_t tmpeval; int i; which.pos = IGRAPH_EIGEN_SELECT; which.il = (int) (no_of_nodes - evmax + 1); which.iu = (int) (no_of_nodes - evmin + 1); if (values) { IGRAPH_CHECK(igraph_vector_complex_init(&tmpeval, 0)); IGRAPH_FINALLY(igraph_vector_complex_destroy, &tmpeval); } IGRAPH_CHECK(igraph_matrix_complex_init(&tmp, no_of_nodes, which.iu - which.il + 1)); IGRAPH_FINALLY(igraph_matrix_complex_destroy, &tmp); IGRAPH_CHECK(igraph_eigen_matrix(mymatrix, mysparsemat, /*fun=*/ 0, no_of_nodes, /*extra=*/ 0, use_arpack ? IGRAPH_EIGEN_ARPACK : IGRAPH_EIGEN_LAPACK, &which, &options, /*storage=*/ 0, values ? &tmpeval : 0, &tmp)); IGRAPH_VECTOR_INIT_FINALLY(&tmpev, no_of_ev); for (i = 0; i < no_of_ev; i++) { VECTOR(tmpev)[i] = evmax - VECTOR(*ev)[i]; } if (values) { IGRAPH_CHECK(igraph_vector_complex_index(&tmpeval, values, &tmpev)); } IGRAPH_CHECK(igraph_matrix_complex_select_cols(&tmp, vectors, &tmpev)); igraph_vector_destroy(&tmpev); igraph_matrix_complex_destroy(&tmp); IGRAPH_FINALLY_CLEAN(2); if (values) { igraph_vector_complex_destroy(&tmpeval); IGRAPH_FINALLY_CLEAN(1); } } /* Compute p if not supplied */ if (do_p) { igraph_eigen_which_t w; igraph_matrix_complex_t tmp; igraph_arpack_options_t o; igraph_matrix_t trans, *mytrans = &trans; igraph_sparsemat_t sparse_trans, *mysparse_trans = &sparse_trans; int i; igraph_arpack_options_init(&o); if (!p) { IGRAPH_VECTOR_INIT_FINALLY(&real_p, no_of_nodes); myp = &real_p; } else { IGRAPH_CHECK(igraph_vector_resize(p, no_of_nodes)); } IGRAPH_CHECK(igraph_matrix_complex_init(&tmp, 0, 0)); IGRAPH_FINALLY(igraph_matrix_complex_destroy, &tmp); w.pos = IGRAPH_EIGEN_LR; w.howmany = 1; if (mymatrix) { IGRAPH_CHECK(igraph_matrix_copy(&trans, mymatrix)); IGRAPH_FINALLY(igraph_matrix_destroy, &trans); IGRAPH_CHECK(igraph_matrix_transpose(&trans)); mysparse_trans = 0; } else { IGRAPH_CHECK(igraph_sparsemat_transpose(mysparsemat, &sparse_trans, /*values=*/ 1)); IGRAPH_FINALLY(igraph_sparsemat_destroy, mysparse_trans); mytrans = 0; } IGRAPH_CHECK(igraph_eigen_matrix(mytrans, mysparse_trans, /*fun=*/ 0, no_of_nodes, /*extra=*/ 0, /*algorith=*/ use_arpack ? IGRAPH_EIGEN_ARPACK : IGRAPH_EIGEN_LAPACK, &w, &o, /*storage=*/ 0, /*values=*/ 0, &tmp)); if (mymatrix) { igraph_matrix_destroy(&trans); IGRAPH_FINALLY_CLEAN(1); } else { igraph_sparsemat_destroy(mysparse_trans); IGRAPH_FINALLY_CLEAN(1); } for (i = 0; i < no_of_nodes; i++) { VECTOR(*myp)[i] = fabs(IGRAPH_REAL(MATRIX(tmp, i, 0))); } igraph_matrix_complex_destroy(&tmp); IGRAPH_FINALLY_CLEAN(1); } /* -------------------------------------------------------------------- */ /* Work out groups, if needed */ /* TODO: use complex part as well */ if (tmp_groups) { groups = &mygroups; IGRAPH_VECTOR_INIT_FINALLY((igraph_vector_t*)groups, no_of_nodes); } if (do_groups) { igraph_matrix_t tmp; IGRAPH_MATRIX_INIT_FINALLY(&tmp, 0, 0); IGRAPH_CHECK(igraph_matrix_complex_real(vectors, &tmp)); IGRAPH_CHECK(igraph_scg_grouping(&tmp, (igraph_vector_t*)groups, nt, nt_vec, IGRAPH_SCG_STOCHASTIC, algo, myp, maxiter)); igraph_matrix_destroy(&tmp); IGRAPH_FINALLY_CLEAN(1); } /* -------------------------------------------------------------------- */ /* Perform coarse graining */ if (tmp_lsparse) { Lsparse = &myLsparse; } if (tmp_rsparse) { Rsparse = &myRsparse; } IGRAPH_CHECK(igraph_scg_semiprojectors(groups, IGRAPH_SCG_STOCHASTIC, L, R, Lsparse, Rsparse, myp, norm)); if (tmp_groups) { igraph_vector_destroy((igraph_vector_t*) groups); IGRAPH_FINALLY_CLEAN(1); } if (!p && do_p) { igraph_vector_destroy(myp); IGRAPH_FINALLY_CLEAN(1); } if (tmp_vectors) { igraph_matrix_complex_destroy(vectors); IGRAPH_FINALLY_CLEAN(1); } if (Rsparse) { IGRAPH_FINALLY(igraph_sparsemat_destroy, Rsparse); } if (Lsparse) { IGRAPH_FINALLY(igraph_sparsemat_destroy, Lsparse); } /* -------------------------------------------------------------------- */ /* Compute coarse grained matrix/graph/sparse matrix */ IGRAPH_CHECK(igraph_sparsemat_compress(Rsparse, &tmpsparse)); IGRAPH_FINALLY(igraph_sparsemat_destroy, &tmpsparse); IGRAPH_CHECK(igraph_sparsemat_transpose(&tmpsparse, &Rsparse_t, /*values=*/ 1)); igraph_sparsemat_destroy(&tmpsparse); IGRAPH_FINALLY_CLEAN(1); IGRAPH_FINALLY(igraph_sparsemat_destroy, &Rsparse_t); IGRAPH_CHECK(igraph_i_scg_get_result(IGRAPH_SCG_STOCHASTIC, mymatrix, mysparsemat, Lsparse, &Rsparse_t, scg_graph, scg_matrix, scg_sparsemat, /*directed=*/ 1)); /* -------------------------------------------------------------------- */ /* Clean up */ igraph_sparsemat_destroy(&Rsparse_t); IGRAPH_FINALLY_CLEAN(1); if (Lsparse) { IGRAPH_FINALLY_CLEAN(1); } if (Rsparse) { IGRAPH_FINALLY_CLEAN(1); } if (graph) { igraph_sparsemat_destroy(mysparsemat); IGRAPH_FINALLY_CLEAN(1); } else if (matrix) { igraph_matrix_destroy(mymatrix); IGRAPH_FINALLY_CLEAN(1); } else { igraph_sparsemat_destroy(mysparsemat); IGRAPH_FINALLY_CLEAN(1); } return 0; } /** * \function igraph_scg_laplacian * Spectral coarse graining, laplacian matrix. * This function handles all the steps involved in the Spectral Coarse * Graining (SCG) of some matrices and graphs as described in the * reference below. * * \param graph The input graph. Exactly one of \p graph, \p matrix * and \p sparsemat must be given, the other two must be \c NULL * pointers. * \param matrix The input matrix. Exactly one of \p graph, \p matrix * and \p sparsemat must be given, the other two must be \c NULL * pointers. * \param sparsemat The input sparse matrix. Exactly one of \p graph, * \p matrix and \p sparsemat must be given, the other two must be * \c NULL pointers. * \param ev A vector of positive integers giving the indexes of the * eigenpairs to be preserved. 1 designates the eigenvalue with * largest magnitude, 2 the one with second largest magnitude, etc. * \param nt Positive integer. When \p algo is \c IGRAPH_SCG_OPTIMUM, * it gives the number of groups to partition each eigenvector * separately. When \p algo is \c IGRAPH_SCG_INTERV or \c * IGRAPH_SCG_INTERV_KM, it gives the number of intervals to * partition each eigenvector. This is ignored when \p algo is \c * IGRAPH_SCG_EXACT. * \param nt_vec A numeric vector of length one or the length must * match the number of eigenvectors given in \p V, or a \c NULL * pointer. If not \c NULL, then this argument gives the number of * groups or intervals, and \p nt is ignored. Different number of * groups or intervals can be specified for each eigenvector. * \param algo The algorithm to solve the SCG problem. Possible * values: \c IGRAPH_SCG_OPTIMUM, \c IGRAPH_SCG_INTERV_KM, \c * IGRAPH_SCG_INTERV and \c IGRAPH_SCG_EXACT. Please see the * details about them above. * \param norm Either \c IGRAPH_SCG_NORM_ROW or \c IGRAPH_SCG_NORM_COL. * Specifies whether the rows or the columns of the Laplacian * matrix sum up to zero. * \param direction Whether to work with left or right eigenvectors. * Possible values: \c IGRAPH_SCG_DIRECTION_DEFAULT, \c * IGRAPH_SCG_DIRECTION_LEFT, \c IGRAPH_SCG_DIRECTION_RIGHT. This * argument is currently ignored and right eigenvectors are always * used. * \param values If this is not \c NULL and the eigenvectors are * re-calculated, then the eigenvalues are stored here. * \param vectors If this is not \c NULL, and not a zero-length * matrix, then it is interpreted as the eigenvectors to use for * the coarse-graining. Otherwise the eigenvectors are * re-calculated, and they are stored here. (If this is not \c NULL.) * \param groups If this is not \c NULL, and not a zero-length vector, * then it is interpreted as the vector of group labels. (Group * labels are integers from zero and are sequential.) Otherwise * group labels are re-calculated and stored here, if this argument * is not a null pointer. * \param use_arpack Whether to use ARPACK for solving the * eigenproblem. Currently ARPACK is not implemented. * \param maxiter A positive integer giving the number of iterations * of the k-means algorithm when \p algo is \c * IGRAPH_SCG_INTERV_KM. It is ignored in other cases. A reasonable * (initial) value for this argument is 100. * \param scg_graph If not a \c NULL pointer, then the coarse-grained * graph is returned here. * \param scg_matrix If not a \c NULL pointer, then it must be an * initialied matrix, and the coarse-grained matrix is returned * here. * \param scg_sparsemat If not a \c NULL pointer, then the coarse * grained matrix is returned here, in sparse matrix form. * \param L If not a \c NULL pointer, then it must be an initialized * matrix and the left semi-projector is returned here. * \param R If not a \c NULL pointer, then it must be an initialized * matrix and the right semi-projector is returned here. * \param Lsparse If not a \c NULL pointer, then the left * semi-projector is returned here. * \param Rsparse If not a \c NULL pointer, then the right * semi-projector is returned here. * \return Error code. * * Time complexity: TODO. * * \sa \ref igraph_scg_grouping(), \ref igraph_scg_semiprojectors(), * \ref igraph_scg_stochastic() and \ref igraph_scg_adjacency(). * * \example examples/simple/scg3.c */ int igraph_scg_laplacian(const igraph_t *graph, const igraph_matrix_t *matrix, const igraph_sparsemat_t *sparsemat, const igraph_vector_t *ev, igraph_integer_t nt, const igraph_vector_t *nt_vec, igraph_scg_algorithm_t algo, igraph_scg_norm_t norm, igraph_scg_direction_t direction, igraph_vector_complex_t *values, igraph_matrix_complex_t *vectors, igraph_vector_t *groups, igraph_bool_t use_arpack, igraph_integer_t maxiter, igraph_t *scg_graph, igraph_matrix_t *scg_matrix, igraph_sparsemat_t *scg_sparsemat, igraph_matrix_t *L, igraph_matrix_t *R, igraph_sparsemat_t *Lsparse, igraph_sparsemat_t *Rsparse) { igraph_matrix_t *mymatrix = (igraph_matrix_t*) matrix, real_matrix; igraph_sparsemat_t *mysparsemat = (igraph_sparsemat_t*) sparsemat, real_sparsemat; int no_of_nodes; igraph_real_t evmin, evmax; igraph_arpack_options_t options; igraph_eigen_which_t which; /* eigenvectors are calculated and returned */ igraph_bool_t do_vectors = vectors && igraph_matrix_complex_size(vectors) == 0; /* groups are calculated */ igraph_bool_t do_groups = !groups || igraph_vector_size(groups) == 0; igraph_bool_t tmp_groups = !groups; /* eigenvectors are not returned but must be calculated for groups */ igraph_bool_t tmp_vectors = !do_vectors && do_groups; igraph_matrix_complex_t myvectors; igraph_vector_t mygroups; int no_of_ev = (int) igraph_vector_size(ev); igraph_bool_t tmp_lsparse = !Lsparse, tmp_rsparse = !Rsparse; igraph_sparsemat_t myLsparse, myRsparse, tmpsparse, Rsparse_t; /* --------------------------------------------------------------------*/ /* Argument checks */ IGRAPH_CHECK(igraph_i_scg_common_checks(graph, matrix, sparsemat, ev, nt, nt_vec, 0, vectors, groups, scg_graph, scg_matrix, scg_sparsemat, /*p=*/ 0, &evmin, &evmax)); if (graph) { no_of_nodes = igraph_vcount(graph); } else if (matrix) { no_of_nodes = (int) igraph_matrix_nrow(matrix); } else { no_of_nodes = (int) igraph_sparsemat_nrow(sparsemat); } /* -------------------------------------------------------------------- */ /* Convert graph, if needed, get Laplacian matrix */ if (graph) { mysparsemat = &real_sparsemat; IGRAPH_CHECK(igraph_sparsemat_init(mysparsemat, 0, 0, 0)); IGRAPH_FINALLY(igraph_sparsemat_destroy, mysparsemat); IGRAPH_CHECK(igraph_laplacian(graph, 0, mysparsemat, /*normalized=*/ 0, /*weights=*/ 0)); } else if (matrix) { mymatrix = &real_matrix; IGRAPH_MATRIX_INIT_FINALLY(mymatrix, no_of_nodes, no_of_nodes); IGRAPH_CHECK(igraph_i_matrix_laplacian(matrix, mymatrix, norm)); } else { /* sparsemat */ mysparsemat = &real_sparsemat; IGRAPH_CHECK(igraph_i_sparsemat_laplacian(sparsemat, mysparsemat, norm == IGRAPH_SCG_NORM_COL)); IGRAPH_FINALLY(igraph_sparsemat_destroy, mysparsemat); } /* -------------------------------------------------------------------- */ /* Compute eigenpairs, if needed */ if (tmp_vectors) { vectors = &myvectors; IGRAPH_CHECK(igraph_matrix_complex_init(vectors, no_of_nodes, no_of_ev)); IGRAPH_FINALLY(igraph_matrix_complex_destroy, vectors); } if (do_vectors || tmp_vectors) { igraph_matrix_complex_t tmp; igraph_vector_t tmpev; igraph_vector_complex_t tmpeval; int i; which.pos = IGRAPH_EIGEN_SELECT; which.il = (int) (no_of_nodes - evmax + 1); which.iu = (int) (no_of_nodes - evmin + 1); if (values) { IGRAPH_CHECK(igraph_vector_complex_init(&tmpeval, 0)); IGRAPH_FINALLY(igraph_vector_complex_destroy, &tmpeval); } IGRAPH_CHECK(igraph_matrix_complex_init(&tmp, no_of_nodes, which.iu - which.il + 1)); IGRAPH_FINALLY(igraph_matrix_complex_destroy, &tmp); IGRAPH_CHECK(igraph_eigen_matrix(mymatrix, mysparsemat, /*fun=*/ 0, no_of_nodes, /*extra=*/ 0, use_arpack ? IGRAPH_EIGEN_ARPACK : IGRAPH_EIGEN_LAPACK, &which, &options, /*storage=*/ 0, values ? &tmpeval : 0, &tmp)); IGRAPH_VECTOR_INIT_FINALLY(&tmpev, no_of_ev); for (i = 0; i < no_of_ev; i++) { VECTOR(tmpev)[i] = evmax - VECTOR(*ev)[i]; } if (values) { IGRAPH_CHECK(igraph_vector_complex_index(&tmpeval, values, &tmpev)); } IGRAPH_CHECK(igraph_matrix_complex_select_cols(&tmp, vectors, &tmpev)); igraph_vector_destroy(&tmpev); igraph_matrix_complex_destroy(&tmp); IGRAPH_FINALLY_CLEAN(2); if (values) { igraph_vector_complex_destroy(&tmpeval); IGRAPH_FINALLY_CLEAN(1); } } /* -------------------------------------------------------------------- */ /* Work out groups, if needed */ /* TODO: use complex part as well */ if (tmp_groups) { groups = &mygroups; IGRAPH_VECTOR_INIT_FINALLY((igraph_vector_t*)groups, no_of_nodes); } if (do_groups) { igraph_matrix_t tmp; IGRAPH_MATRIX_INIT_FINALLY(&tmp, 0, 0); IGRAPH_CHECK(igraph_matrix_complex_real(vectors, &tmp)); IGRAPH_CHECK(igraph_scg_grouping(&tmp, (igraph_vector_t*)groups, nt, nt_vec, IGRAPH_SCG_LAPLACIAN, algo, /*p=*/ 0, maxiter)); igraph_matrix_destroy(&tmp); IGRAPH_FINALLY_CLEAN(1); } /* -------------------------------------------------------------------- */ /* Perform coarse graining */ if (tmp_lsparse) { Lsparse = &myLsparse; } if (tmp_rsparse) { Rsparse = &myRsparse; } IGRAPH_CHECK(igraph_scg_semiprojectors(groups, IGRAPH_SCG_LAPLACIAN, L, R, Lsparse, Rsparse, /*p=*/ 0, norm)); if (tmp_groups) { igraph_vector_destroy((igraph_vector_t*) groups); IGRAPH_FINALLY_CLEAN(1); } if (tmp_vectors) { igraph_matrix_complex_destroy(vectors); IGRAPH_FINALLY_CLEAN(1); } if (Rsparse) { IGRAPH_FINALLY(igraph_sparsemat_destroy, Rsparse); } if (Lsparse) { IGRAPH_FINALLY(igraph_sparsemat_destroy, Lsparse); } /* -------------------------------------------------------------------- */ /* Compute coarse grained matrix/graph/sparse matrix */ IGRAPH_CHECK(igraph_sparsemat_compress(Rsparse, &tmpsparse)); IGRAPH_FINALLY(igraph_sparsemat_destroy, &tmpsparse); IGRAPH_CHECK(igraph_sparsemat_transpose(&tmpsparse, &Rsparse_t, /*values=*/ 1)); igraph_sparsemat_destroy(&tmpsparse); IGRAPH_FINALLY_CLEAN(1); IGRAPH_FINALLY(igraph_sparsemat_destroy, &Rsparse_t); IGRAPH_CHECK(igraph_i_scg_get_result(IGRAPH_SCG_LAPLACIAN, mymatrix, mysparsemat, Lsparse, &Rsparse_t, scg_graph, scg_matrix, scg_sparsemat, /*directed=*/ 1)); /* -------------------------------------------------------------------- */ /* Clean up */ igraph_sparsemat_destroy(&Rsparse_t); IGRAPH_FINALLY_CLEAN(1); if (Lsparse) { IGRAPH_FINALLY_CLEAN(1); } if (Rsparse) { IGRAPH_FINALLY_CLEAN(1); } if (graph) { igraph_sparsemat_destroy(mysparsemat); IGRAPH_FINALLY_CLEAN(1); } else if (matrix) { igraph_matrix_destroy(mymatrix); IGRAPH_FINALLY_CLEAN(1); } else { igraph_sparsemat_destroy(mysparsemat); IGRAPH_FINALLY_CLEAN(1); } return 0; } python-igraph-0.8.0/vendor/source/igraph/src/gengraph_graph_molloy_hash.cpp0000644000076500000240000010232713614300625027461 0ustar tamasstaff00000000000000/* * * gengraph - generation of random simple connected graphs with prescribed * degree sequence * * Copyright (C) 2006 Fabien Viger * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #include "gengraph_definitions.h" #include #include #include #include #include "gengraph_qsort.h" #include "gengraph_hash.h" #include "gengraph_degree_sequence.h" #include "gengraph_graph_molloy_hash.h" #include "config.h" #include "igraph_math.h" #include "igraph_constructors.h" #include "igraph_error.h" #include "igraph_statusbar.h" #include "igraph_progress.h" namespace gengraph { //_________________________________________________________________________ void graph_molloy_hash::compute_neigh() { int *p = links; for (int i = 0; i < n; i++) { neigh[i] = p; p += HASH_SIZE(deg[i]); } } //_________________________________________________________________________ void graph_molloy_hash::compute_size() { size = 0; for (int i = 0; i < n; i++) { size += HASH_SIZE(deg[i]); } } //_________________________________________________________________________ void graph_molloy_hash::init() { for (int i = 0; i < size; i++) { links[i] = HASH_NONE; } } //_________________________________________________________________________ graph_molloy_hash::graph_molloy_hash(degree_sequence °s) { igraph_status("Allocating memory for graph...", 0); int s = alloc(degs); igraph_statusf("%d bytes allocated successfully\n", 0, s); } //_________________________________________________________________________ int graph_molloy_hash::alloc(degree_sequence °s) { n = degs.size(); a = degs.sum(); assert(a % 2 == 0); deg = degs.seq(); compute_size(); deg = new int[n + size]; if (deg == NULL) { return 0; } int i; for (i = 0; i < n; i++) { deg[i] = degs[i]; } links = deg + n; init(); neigh = new int*[n]; if (neigh == NULL) { return 0; } compute_neigh(); return sizeof(int *)*n + sizeof(int) * (n + size); } //_________________________________________________________________________ graph_molloy_hash::~graph_molloy_hash() { if (deg != NULL) { delete[] deg; } if (neigh != NULL) { delete[] neigh; } deg = NULL; neigh = NULL; } //_________________________________________________________________________ graph_molloy_hash::graph_molloy_hash(int *svg) { // Read n n = *(svg++); // Read a a = *(svg++); assert(a % 2 == 0); // Read degree sequence degree_sequence dd(n, svg); // Build neigh[] and alloc links[] alloc(dd); dd.detach(); // Read links[] restore(svg + n); } //_________________________________________________________________________ int *graph_molloy_hash::hard_copy() { int *hc = new int[2 + n + a / 2]; // to store n,a,deg[] and links[] hc[0] = n; hc[1] = a; memcpy(hc + 2, deg, sizeof(int)*n); int *p = hc + 2 + n; int *l = links; for (int i = 0; i < n; i++) for (int j = HASH_SIZE(deg[i]); j--; l++) { register int d; if ((d = *l) != HASH_NONE && d >= i) { *(p++) = d; } } assert(p == hc + 2 + n + a / 2); return hc; } //_________________________________________________________________________ bool graph_molloy_hash::is_connected() { bool *visited = new bool[n]; int *buff = new int[n]; int comp_size = depth_search(visited, buff); delete[] visited; delete[] buff; return (comp_size == n); } //_________________________________________________________________________ int* graph_molloy_hash::backup() { int *b = new int[a / 2]; int *c = b; int *p = links; for (int i = 0; i < n; i++) for (int d = HASH_SIZE(deg[i]); d--; p++) if (*p != HASH_NONE && *p > i) { *(c++) = *p; } assert(c == b + (a / 2)); return b; } //_________________________________________________________________________ void graph_molloy_hash::restore(int* b) { init(); int i; int *dd = new int[n]; memcpy(dd, deg, sizeof(int)*n); for (i = 0; i < n; i++) { deg[i] = 0; } for (i = 0; i < n - 1; i++) { while (deg[i] < dd[i]) { add_edge(i, *b, dd); b++; } } delete[] dd; } //_________________________________________________________________________ bool graph_molloy_hash::isolated(int v, int K, int *Kbuff, bool *visited) { if (K < 2) { return false; } #ifdef OPT_ISOLATED if (K <= deg[v] + 1) { return false; } #endif //OPT_ISOLATED int *seen = Kbuff; int *known = Kbuff; int *max = Kbuff + K; *(known++) = v; visited[v] = true; bool is_isolated = true; while (known != seen) { v = *(seen++); int *ww = neigh[v]; int w; for (int d = HASH_SIZE(deg[v]); d--; ww++) if ((w = *ww) != HASH_NONE && !visited[w]) { #ifdef OPT_ISOLATED if (K <= deg[w] + 1 || known == max) { #else //OPT_ISOLATED if (known == max) { #endif //OPT_ISOLATED is_isolated = false; goto end_isolated; } visited[w] = true; *(known++) = w; } } end_isolated: // Undo the changes to visited[]... while (known != Kbuff) { visited[*(--known)] = false; } return is_isolated; } //_________________________________________________________________________ int graph_molloy_hash::random_edge_swap(int K, int *Kbuff, bool *visited) { // Pick two random vertices a and c int f1 = pick_random_vertex(); int f2 = pick_random_vertex(); // Check that f1 != f2 if (f1 == f2) { return 0; } // Get two random edges (f1,*f1t1) and (f2,*f2t2) int *f1t1 = random_neighbour(f1); int t1 = *f1t1; int *f2t2 = random_neighbour(f2); int t2 = *f2t2; // Check simplicity if (t1 == t2 || f1 == t2 || f2 == t1) { return 0; } if (is_edge(f1, t2) || is_edge(f2, t1)) { return 0; } // Swap int *f1t2 = H_rpl(neigh[f1], deg[f1], f1t1, t2); int *f2t1 = H_rpl(neigh[f2], deg[f2], f2t2, t1); int *t1f2 = H_rpl(neigh[t1], deg[t1], f1, f2); int *t2f1 = H_rpl(neigh[t2], deg[t2], f2, f1); // isolation test if (K <= 2) { return 1; } if ( !isolated(f1, K, Kbuff, visited) && !isolated(f2, K, Kbuff, visited) ) { return 1; } // undo swap H_rpl(neigh[f1], deg[f1], f1t2, t1); H_rpl(neigh[f2], deg[f2], f2t1, t2); H_rpl(neigh[t1], deg[t1], t1f2, f1); H_rpl(neigh[t2], deg[t2], t2f1, f2); return 0; } //_________________________________________________________________________ unsigned long graph_molloy_hash::shuffle(unsigned long times, unsigned long maxtimes, int type) { igraph_progress("Shuffle", 0, 0); // assert(verify()); // counters unsigned long nb_swaps = 0; unsigned long all_swaps = 0; unsigned long cost = 0; // window double T = double(min((unsigned long)(a), times) / 10); if (type == OPTIMAL_HEURISTICS) { T = double(optimal_window()); } if (type == BRUTE_FORCE_HEURISTICS) { T = double(times * 2); } // isolation test parameter, and buffers double K = 2.4; int *Kbuff = new int[int(K) + 1]; bool *visited = new bool[n]; for (int i = 0; i < n; i++) { visited[i] = false; } // Used for monitoring , active only if VERBOSE() int failures = 0; int successes = 0; double avg_K = 0; double avg_T = 0; unsigned long next = times; next = 0; // Shuffle: while #edge swap attempts validated by connectivity < times ... while (times > nb_swaps && maxtimes > all_swaps) { // Backup graph int *save = backup(); // Prepare counters, K, T unsigned long swaps = 0; int K_int = 0; if (type == FINAL_HEURISTICS || type == BRUTE_FORCE_HEURISTICS) { K_int = int(K); } unsigned long T_int = (unsigned long)(floor(T)); if (T_int < 1) { T_int = 1; } // compute cost cost += T_int; if (K_int > 2) { cost += (unsigned long)(K_int) * (unsigned long)(T_int); } // Perform T edge swap attempts for (int i = T_int; i > 0; i--) { // try one swap swaps += (unsigned long)(random_edge_swap(K_int, Kbuff, visited)); all_swaps++; // Verbose if (nb_swaps + swaps > next) { next = (nb_swaps + swaps) + max((unsigned long)(100), (unsigned long)(times / 1000)); int progress = int(double(nb_swaps + swaps) / double(times)); igraph_progress("Shuffle", progress, 0); } } // test connectivity cost += (unsigned long)(a / 2); bool ok = is_connected(); // performance monitor { avg_T += double(T_int); avg_K += double(K_int); if (ok) { successes++; } else { failures++; } } // restore graph if needed, and count validated swaps if (ok) { nb_swaps += swaps; } else { restore(save); next = nb_swaps; } delete[] save; // Adjust K and T following the heuristics. switch (type) { int steps; case GKAN_HEURISTICS: if (ok) { T += 1.0; } else { T *= 0.5; } break; case FAB_HEURISTICS: steps = 50 / (8 + failures + successes); if (steps < 1) { steps = 1; } while (steps--) if (ok) { T *= 1.17182818; } else { T *= 0.9; } if (T > double(5 * a)) { T = double(5 * a); } break; case FINAL_HEURISTICS: if (ok) { if ((K + 10.0)*T > 5.0 * double(a)) { K /= 1.03; } else { T *= 2; } } else { K *= 1.35; delete[] Kbuff; Kbuff = new int[int(K) + 1]; } break; case OPTIMAL_HEURISTICS: if (ok) { T = double(optimal_window()); } break; case BRUTE_FORCE_HEURISTICS: K *= 2; delete[] Kbuff; Kbuff = new int[int(K) + 1]; break; default: IGRAPH_ERROR("Error in graph_molloy_hash::shuffle(): " "Unknown heuristics type", IGRAPH_EINVAL); return 0; } } delete[] Kbuff; delete[] visited; if (maxtimes <= all_swaps) { IGRAPH_WARNING("Cannot shuffle graph, maybe there is only a single one?"); } // Status report { igraph_status("*** Shuffle Monitor ***\n", 0); igraph_statusf(" - Average cost : %f / validated edge swap\n", 0, double(cost) / double(nb_swaps)); igraph_statusf(" - Connectivity tests : %d (%d successes, %d failures)\n", 0, successes + failures, successes, failures); igraph_statusf(" - Average window : %d\n", 0, int(avg_T / double(successes + failures))); if (type == FINAL_HEURISTICS || type == BRUTE_FORCE_HEURISTICS) igraph_statusf(" - Average isolation test width : %f\n", 0, avg_K / double(successes + failures)); } return nb_swaps; } //_________________________________________________________________________ void graph_molloy_hash::print(FILE *f) { int i, j; for (i = 0; i < n; i++) { fprintf(f, "%d", i); for (j = 0; j < HASH_SIZE(deg[i]); j++) if (neigh[i][j] != HASH_NONE) { fprintf(f, " %d", neigh[i][j]); } fprintf(f, "\n"); } } int graph_molloy_hash::print(igraph_t *graph) { int i, j; long int ptr = 0; igraph_vector_t edges; IGRAPH_VECTOR_INIT_FINALLY(&edges, a); // every edge is counted twice.... for (i = 0; i < n; i++) { for (j = 0; j < HASH_SIZE(deg[i]); j++) { if (neigh[i][j] != HASH_NONE) { if (neigh[i][j] > i) { VECTOR(edges)[ptr++] = i; VECTOR(edges)[ptr++] = neigh[i][j]; } } } } IGRAPH_CHECK(igraph_create(graph, &edges, n, /*undirected=*/ 0)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } //_________________________________________________________________________ bool graph_molloy_hash::try_shuffle(int T, int K, int *backup_graph) { // init all int *Kbuff = NULL; bool *visited = NULL; if (K > 2) { Kbuff = new int[K]; visited = new bool[n]; for (int i = 0; i < n; i++) { visited[i] = false; } } int *back = backup_graph; if (back == NULL) { back = backup(); } // perform T edge swap attempts while (T--) { random_edge_swap(K, Kbuff, visited); } // clean if (visited != NULL) { delete[] visited; } if (Kbuff != NULL) { delete[] Kbuff; } // check & restore bool yo = is_connected(); restore(back); if (backup_graph == NULL) { delete[] back; } return yo; } //_________________________________________________________________________ #define _TRUST_BERNOULLI_LOWER 0.01 bool bernoulli_param_is_lower(int success, int trials, double param) { if (double(success) >= double(trials)*param) { return false; } double comb = 1.0; double fact = 1.0; for (int i = 0; i < success; i++) { comb *= double(trials - i); fact *= double(i + 1); } comb /= fact; comb *= pow(param, double(success)) * exp(double(trials - success) * log1p(-param)); double sum = comb; while (success && sum < _TRUST_BERNOULLI_LOWER) { comb *= double(success) * (1.0 - param) / (double(trials - success) * param); sum += comb; success--; } // fprintf(stderr,"bernoulli test : %d/%d success against p=%f -> %s\n",success, trials, param, (sum < _TRUST_BERNOULLI_LOWER) ? "lower" : "can't say"); return (sum < _TRUST_BERNOULLI_LOWER); } //_________________________________________________________________________ #define _MIN_SUCCESS_FOR_BERNOULLI_TRUST 100 double graph_molloy_hash::average_cost(int T, int *backup, double min_cost) { if (T < 1) { return 1e+99; } int successes = 0; int trials = 0; while (successes < _MIN_SUCCESS_FOR_BERNOULLI_TRUST && !bernoulli_param_is_lower(successes, trials, 1.0 / min_cost)) { if (try_shuffle(T, 0, backup)) { successes++; } trials++; } if (successes >= _MIN_SUCCESS_FOR_BERNOULLI_TRUST) { return double(trials) / double(successes) * (1.0 + double(a / 2) / double(T)); } else { return 2.0 * min_cost; } } //_________________________________________________________________________ int graph_molloy_hash::optimal_window() { int Tmax; int optimal_T = 1; double min_cost = 1e+99; int *back = backup(); // on cherche une borne sup pour Tmax int been_greater = 0; for (Tmax = 1; Tmax <= 5 * a ; Tmax *= 2) { double c = average_cost(Tmax, back, min_cost); if (c > 1.5 * min_cost) { break; } if (c > 1.2 * min_cost && ++been_greater >= 3) { break; } if (c < min_cost) { min_cost = c; optimal_T = Tmax; } igraph_statusf("Tmax = %d [%f]", 0, Tmax, min_cost); } // on cree Tmin int Tmin = int(0.5 * double(a) / (min_cost - 1.0)); igraph_statusf("Optimal T is in [%d, %d]\n", 0, Tmin, Tmax); // on cherche autour double span = 2.0; int try_again = 4; while (span > 1.05 && optimal_T <= 5 * a) { igraph_statusf("Best T [cost]: %d [%f]", 0, optimal_T, min_cost); int T_low = int(double(optimal_T) / span); int T_high = int(double(optimal_T) * span); double c_low = average_cost(T_low, back, min_cost); double c_high = average_cost(T_high, back, min_cost); if (c_low < min_cost && c_high < min_cost) { if (try_again--) { continue; } { igraph_status("Warning: when looking for optimal T,\n", 0); igraph_statusf("Low: %d [%f] Middle: %d [%f] High: %d [%f]\n", 0, T_low, c_low, optimal_T, min_cost, T_high, c_high); } delete[] back; return optimal_T; } if (c_low < min_cost) { optimal_T = T_low; min_cost = c_low; } else if (c_high < min_cost) { optimal_T = T_high; min_cost = c_high; }; span = pow(span, 0.618); } delete[] back; return optimal_T; } //_________________________________________________________________________ double graph_molloy_hash::eval_K(int quality) { double K = 5.0; double avg_K = 1.0; for (int i = quality; i--; ) { int int_K = int(floor(K + 0.5)); if (try_shuffle(a / (int_K + 1), int_K)) { K *= 0.8; /*fprintf(stderr,"+");*/ } else { K *= 1.25; /*fprintf(stderr,"-");*/ } if (i < quality / 2) { avg_K *= K; } } return pow(avg_K, 1.0 / double(quality / 2)); } //_________________________________________________________________________ double graph_molloy_hash::effective_K(int K, int quality) { if (K < 3) { return 0.0; } long sum_K = 0; int *Kbuff = new int[K]; bool *visited = new bool[n]; int i; for (i = 0; i < n; i++) { visited[i] = false; } for (int i = 0; i < quality; i++) { // assert(verify()); int f1, f2, t1, t2; int *f1t1, *f2t2; do { // Pick two random vertices do { f1 = pick_random_vertex(); f2 = pick_random_vertex(); } while (f1 == f2); // Pick two random neighbours f1t1 = random_neighbour(f1); t1 = *f1t1; f2t2 = random_neighbour(f2); t2 = *f2t2; // test simplicity } while (t1 == t2 || f1 == t2 || f2 == t1 || is_edge(f1, t2) || is_edge(f2, t1)); // swap swap_edges(f1, t2, f2, t1); // assert(verify()); sum_K += effective_isolated(deg[f1] > deg[t2] ? f1 : t2, K, Kbuff, visited); // assert(verify()); sum_K += effective_isolated(deg[f2] > deg[t1] ? f2 : t1, K, Kbuff, visited); // assert(verify()); // undo swap swap_edges(f1, t2, f2, t1); // assert(verify()); } delete[] Kbuff; delete[] visited; return double(sum_K) / double(2 * quality); } //_________________________________________________________________________ long graph_molloy_hash::effective_isolated(int v, int K, int *Kbuff, bool *visited) { int i; for (i = 0; i < K; i++) { Kbuff[i] = -1; } long count = 0; int left = K; int *KB = Kbuff; //yapido = (my_random()%1000 == 0); depth_isolated(v, count, left, K, KB, visited); while (KB-- != Kbuff) { visited[*KB] = false; } //if(yapido) fprintf(stderr,"\n"); return count; } //_________________________________________________________________________ void graph_molloy_hash::depth_isolated(int v, long &calls, int &left_to_explore, int dmax, int * &Kbuff, bool *visited) { if (left_to_explore == 0) { return; } // if(yapido) fprintf(stderr,"%d ",deg[v]); if (--left_to_explore == 0) { return; } if (deg[v] + 1 >= dmax) { left_to_explore = 0; return; } *(Kbuff++) = v; visited[v] = true; // print(); // fflush(stdout); calls++; int *copy = NULL; int *w = neigh[v]; if (IS_HASH(deg[v])) { copy = new int[deg[v]]; H_copy(copy, w, deg[v]); w = copy; } qsort(deg, w, deg[v]); w += deg[v]; for (int i = deg[v]; i--; ) { if (visited[*--w]) { calls++; } else { depth_isolated(*w, calls, left_to_explore, dmax, Kbuff, visited); } if (left_to_explore == 0) { break; } } if (copy != NULL) { delete[] copy; } } //_________________________________________________________________________ int graph_molloy_hash::depth_search(bool *visited, int *buff, int v0) { for (int i = 0; i < n; i++) { visited[i] = false; } int *to_visit = buff; int nb_visited = 1; visited[v0] = true; *(to_visit++) = v0; while (to_visit != buff && nb_visited < n) { int v = *(--to_visit); int *ww = neigh[v]; int w; for (int k = HASH_SIZE(deg[v]); k--; ww++) { if (HASH_NONE != (w = *ww) && !visited[w]) { visited[w] = true; nb_visited++; *(to_visit++) = w; } } } return nb_visited; } //_________________________________________________________________________ // bool graph_molloy_hash::verify() { // fprintf(stderr,"Warning: graph_molloy_hash::verify() called..\n"); // fprintf(stderr," try to convert graph into graph_molloy_opt() instead\n"); // return true; // } /*____________________________________________________________________________ Not to use anymore : use graph_molloy_opt class instead bool graph_molloy_hash::verify() { int i; assert(neigh[0]==links); // verify edges count int sum = 0; for(i=0; in) n=i; n++; // degrees ? if(VERBOSE()) fprintf(stderr,"%d, #edges=",n); int *degs = new int[n]; rewind(f); while(fgets(buff,FBUFF_SIZE,f)) { int d = 0; if(sscanf(buff,"%d",&i)==1) { char *b = buff; while(skip_int(b)) d++; degs[i]=d; } } // allocate memory degree_sequence dd(n,degs); if(VERBOSE()) fprintf(stderr,"%d\nAllocating memory...",dd.sum()); alloc(dd); // add edges if(VERBOSE()) fprintf(stderr,"done\nCreating edges..."); rewind(f); for(i=0; im) m=deg[k]; return m; } bool graph_molloy_hash::havelhakimi() { int i; int dmax = max_degree()+1; // Sort vertices using basket-sort, in descending degrees int *nb = new int[dmax]; int *sorted = new int[n]; // init basket for(i=0; i=0; i--) { int t=nb[i]; nb[i]=c; c+=t; } // sort for(i=0; i0; ) { // pick a vertex. we could pick any, but here we pick the one with biggest degree int v = sorted[first]; // look for current degree of v while(nb[d]<=first) d--; // store it in dv int dv = d; // bind it ! c -= dv; int dc = d; // residual degree of vertices we bind to int fc = ++first; // position of the first vertex with degree dc while(dv>0 && dc>0) { int lc = nb[dc]; if(lc!=fc) { while(dv>0 && lc>fc) { // binds v with sorted[--lc] dv--; int w = sorted[--lc]; add_edge(v,w); } fc = nb[dc]; nb[dc] = lc; } dc--; } if(dv != 0) { // We couldn't bind entirely v if(VERBOSE()) { fprintf(stderr,"Error in graph_molloy_hash::havelhakimi() :\n"); fprintf(stderr,"Couldn't bind vertex %d entirely (%d edges remaining)\n",v,dv); } delete[] nb; delete[] sorted; return false; } } assert(c==0); delete[] nb; delete[] sorted; return true; } bool graph_molloy_hash::make_connected() { assert(verify()); if(a/2 < n-1) { // fprintf(stderr,"\ngraph::make_connected() failed : #edges < #vertices-1\n"); return false; } int i; // Data struct for the visit : // - buff[] contains vertices to visit // - dist[V] is V's distance modulo 4 to the root of its comp, or -1 if it hasn't been visited yet #define MC_BUFF_SIZE (n+2) int *buff = new int[MC_BUFF_SIZE]; unsigned char * dist = new unsigned char[n]; #define NOT_VISITED 255 #define FORBIDDEN 254 for(i=n; i>0; dist[--i]=NOT_VISITED); // Data struct to store components : either surplus trees or surplus edges are stored at buff[]'s end // - A Tree is coded by one of its vertices // - An edge (a,b) is coded by the TWO ints a and b int *ffub = buff+MC_BUFF_SIZE; edge *edges = (edge *) ffub; int *trees = ffub; int *min_ffub = buff+1+(MC_BUFF_SIZE%2 ? 0 : 1); // There will be only one "fatty" component, and trees. edge fatty_edge; fatty_edge.from = -1; bool enough_edges = false; // start main loop for(int v0=0; v0min_ffub) min_ffub+=2; // update limit of ffub's storage //assert(verify()); } else if(dist[w]==next_dist || (w!=HASH_NONE && w>v && dist[w]==current_dist)) { // we found a removable edge if(is_a_tree) { // we must first merge with the fatty component is_a_tree = false; if(fatty_edge.from < 0) { // we ARE the first component! fatty is us fatty_edge.from = v; fatty_edge.to = w; } else { // we connect to fatty swap_edges(fatty_edge.from, fatty_edge.to, v, w); //assert(verify()); } } else { // we have removable edges to give! if(trees!=ffub) { // some trees still.. Let's merge with them! assert(trees>=min_ffub); assert(edges==(edge *)ffub); swap_edges(v,w,*trees,neigh[*trees][0]); trees++; //assert(verify()); } else if(!enough_edges) { // Store the removable edge for future use if(edges<=(edge *)min_ffub+1) enough_edges = true; else { edges--; edges->from = v; edges->to = w; } } } } } } // Mark component while(to_visit!=buff) dist[*(--to_visit)] = FORBIDDEN; // Check if it is a tree if(is_a_tree ) { assert(deg[v0]!=0); if(edges!=(edge *)ffub) { // let's bind the tree we found with a removable edge in stock assert(trees == ffub); if(edges<(edge *)min_ffub) edges=(edge *)min_ffub; swap_edges(v0,neigh[v0][0],edges->from,edges->to); edges++; assert(verify()); } else { // add the tree to the list of trees assert(trees>min_ffub); *(--trees) = v0; assert(verify()); } } } delete[] buff; delete[] dist; return(trees == ffub); } int64_t graph_molloy_hash::slow_connected_shuffle(int64_t times) { assert(verify()); int64_t nb_swaps = 0; int T = 1; while(times>nb_swaps) { // Backup graph int *save = backup(); // Swaps int swaps = 0; for(int i=T; i>0; i--) { // Pick two random vertices a and c int f1 = pick_random_vertex(); int f2 = pick_random_vertex(); // Check that f1 != f2 if(f1==f2) continue; // Get two random edges (f1,*f1t1) and (f2,*f2t2) int *f1t1 = random_neighbour(f1); int t1 = *f1t1; int *f2t2 = random_neighbour(f2); int t2 = *f2t2; // Check simplicity if(t1==t2 || f1==t2 || f2==t1) continue; if(is_edge(f1,t2) || is_edge(f2,t1)) continue; // Swap H_rpl(neigh[f1],deg[f1],f1t1,t2); H_rpl(neigh[f2],deg[f2],f2t2,t1); H_rpl(neigh[t1],deg[t1],f1,f2); H_rpl(neigh[t2],deg[t2],f2,f1); swaps++; } // test connectivity bool ok = is_connected(); if(ok) { nb_swaps += swaps; } else { restore(save); } delete[] save; } return nb_swaps; } int graph_molloy_hash::width_search(unsigned char *dist, int *buff, int v0) { for(int i=0; i 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_types.h" #include "igraph_dqueue.h" #define BASE_IGRAPH_REAL #include "igraph_pmt.h" #include "dqueue.pmt" #include "igraph_pmt_off.h" #undef BASE_IGRAPH_REAL #define BASE_LONG #include "igraph_pmt.h" #include "dqueue.pmt" #include "igraph_pmt_off.h" #undef BASE_LONG #define BASE_CHAR #include "igraph_pmt.h" #include "dqueue.pmt" #include "igraph_pmt_off.h" #undef BASE_CHAR #define BASE_BOOL #include "igraph_pmt.h" #include "dqueue.pmt" #include "igraph_pmt_off.h" #undef BASE_BOOL #define BASE_INT #include "igraph_pmt.h" #include "dqueue.pmt" #include "igraph_pmt_off.h" #undef BASE_INT python-igraph-0.8.0/vendor/source/igraph/src/drl_parse.h0000644000076500000240000000512213614300625023522 0ustar tamasstaff00000000000000/* * Copyright 2007 Sandia Corporation. Under the terms of Contract * DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains * certain rights in this software. * * All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are * met: * * * Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * Neither the name of Sandia National Laboratories nor the names of * its contributors may be used to endorse or promote products derived from * this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT * OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED * TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF * LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING * NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. */ // The parse class contains the methods necessary to parse // the command line, print help, and do error checking #ifdef MUSE_MPI #include #endif namespace drl { class parse { public: // Methods parse ( int argc, char **argv ); ~parse () {} // user parameters string sim_file; // .sim file string coord_file; // .coord file string parms_file; // .parms file string real_file; // .real file int rand_seed; // random seed int >= 0 float edge_cut; // edge cutting real [0,1] int int_out; // intermediate output, int >= 1 int edges_out; // true if .edges file is requested int parms_in; // true if .parms file is to be read float real_in; // true if .real file is to be read private: void print_syntax ( const char *error_string ); }; } // namespace drl python-igraph-0.8.0/vendor/source/igraph/src/igraph_buckets.c0000644000076500000240000001376313614300625024546 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_types.h" #include "igraph_types_internal.h" #include "config.h" #include /* The igraph_buckets_t data structure can store at most 'size' * unique integers in 'bsize' buckets. It has the following simple * operations (in addition to _init() and _destroy(): * - _add() adding an element to the given bucket. * - _popmax() removing an element from the bucket with the highest * id. * Currently buckets work as stacks, last-in-first-out mode. * - _empty() queries whether the buckets is empty. * * Internal representation: we use a vector to create single linked * lists, and another vector that points to the starting element of * each bucket. Zero means the end of the chain. So bucket i contains * elements bptr[i], buckets[bptr[i]], buckets[buckets[bptr[i]]], * etc., until a zero is found. * * We also keep the total number of elements in the buckets and the * id of the non-empty bucket with the highest id, to facilitate the * _empty() and _popmax() operations. */ int igraph_buckets_init(igraph_buckets_t *b, long int bsize, long int size) { IGRAPH_VECTOR_LONG_INIT_FINALLY(&b->bptr, bsize); IGRAPH_VECTOR_LONG_INIT_FINALLY(&b->buckets, size); b->max = -1; b->no = 0; IGRAPH_FINALLY_CLEAN(2); return 0; } void igraph_buckets_destroy(igraph_buckets_t *b) { igraph_vector_long_destroy(&b->bptr); igraph_vector_long_destroy(&b->buckets); } long int igraph_buckets_popmax(igraph_buckets_t *b) { /* Precondition: there is at least a non-empty bucket */ /* Search for the highest bucket first */ long int max; while ( (max = (long int) VECTOR(b->bptr)[(long int) b->max]) == 0) { b->max --; } VECTOR(b->bptr)[(long int) b->max] = VECTOR(b->buckets)[max - 1]; b->no--; return max - 1; } long int igraph_buckets_pop(igraph_buckets_t *b, long int bucket) { long int ret = VECTOR(b->bptr)[bucket] - 1; VECTOR(b->bptr)[bucket] = VECTOR(b->buckets)[ret]; b->no--; return ret; } igraph_bool_t igraph_buckets_empty(const igraph_buckets_t *b) { return (b->no == 0); } igraph_bool_t igraph_buckets_empty_bucket(const igraph_buckets_t *b, long int bucket) { return VECTOR(b->bptr)[bucket] == 0; } void igraph_buckets_add(igraph_buckets_t *b, long int bucket, long int elem) { VECTOR(b->buckets)[(long int) elem] = VECTOR(b->bptr)[(long int) bucket]; VECTOR(b->bptr)[(long int) bucket] = elem + 1; if (bucket > b->max) { b->max = (int) bucket; } b->no++; } void igraph_buckets_clear(igraph_buckets_t *b) { igraph_vector_long_null(&b->bptr); igraph_vector_long_null(&b->buckets); b->max = -1; b->no = 0; } int igraph_dbuckets_init(igraph_dbuckets_t *b, long int bsize, long int size) { IGRAPH_VECTOR_LONG_INIT_FINALLY(&b->bptr, bsize); IGRAPH_VECTOR_LONG_INIT_FINALLY(&b->next, size); IGRAPH_VECTOR_LONG_INIT_FINALLY(&b->prev, size); b->max = -1; b->no = 0; IGRAPH_FINALLY_CLEAN(3); return 0; } void igraph_dbuckets_destroy(igraph_dbuckets_t *b) { igraph_vector_long_destroy(&b->bptr); igraph_vector_long_destroy(&b->next); igraph_vector_long_destroy(&b->prev); } void igraph_dbuckets_clear(igraph_dbuckets_t *b) { igraph_vector_long_null(&b->bptr); igraph_vector_long_null(&b->next); igraph_vector_long_null(&b->prev); b->max = -1; b->no = 0; } long int igraph_dbuckets_popmax(igraph_dbuckets_t *b) { long int max; while ( (max = (long int) VECTOR(b->bptr)[(long int) b->max]) == 0) { b->max --; } return igraph_dbuckets_pop(b, b->max); } long int igraph_dbuckets_pop(igraph_dbuckets_t *b, long int bucket) { long int ret = VECTOR(b->bptr)[bucket] - 1; long int next = VECTOR(b->next)[ret]; VECTOR(b->bptr)[bucket] = next; if (next != 0) { VECTOR(b->prev)[next - 1] = 0; } b->no--; return ret; } igraph_bool_t igraph_dbuckets_empty(const igraph_dbuckets_t *b) { return (b->no == 0); } igraph_bool_t igraph_dbuckets_empty_bucket(const igraph_dbuckets_t *b, long int bucket) { return VECTOR(b->bptr)[bucket] == 0; } void igraph_dbuckets_add(igraph_dbuckets_t *b, long int bucket, long int elem) { long int oldfirst = VECTOR(b->bptr)[bucket]; VECTOR(b->bptr)[bucket] = elem + 1; VECTOR(b->next)[elem] = oldfirst; if (oldfirst != 0) { VECTOR(b->prev)[oldfirst - 1] = elem + 1; } if (bucket > b->max) { b->max = (int) bucket; } b->no++; } /* Remove an arbitrary element */ void igraph_dbuckets_delete(igraph_dbuckets_t *b, long int bucket, long int elem) { if (VECTOR(b->bptr)[bucket] == elem + 1) { /* First element in bucket */ long int next = VECTOR(b->next)[elem]; if (next != 0) { VECTOR(b->prev)[next - 1] = 0; } VECTOR(b->bptr)[bucket] = next; } else { long int next = VECTOR(b->next)[elem]; long int prev = VECTOR(b->prev)[elem]; if (next != 0) { VECTOR(b->prev)[next - 1] = prev; } if (prev != 0) { VECTOR(b->next)[prev - 1] = next; } } b->no--; } python-igraph-0.8.0/vendor/source/igraph/src/mixing.c0000644000076500000240000002510113614300625023034 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_mixing.h" #include "igraph_interface.h" /** * \function igraph_assortativity_nominal * Assortativity of a graph based on vertex categories * * Assuming the vertices of the input graph belong to different * categories, this function calculates the assortativity coefficient of * the graph. The assortativity coefficient is between minus one and one * and it is one if all connections stay within categories, it is * minus one, if the network is perfectly disassortative. For a * randomly connected network it is (asymptotically) zero. * * See equation (2) in M. E. J. Newman: Mixing patterns * in networks, Phys. Rev. E 67, 026126 (2003) * (http://arxiv.org/abs/cond-mat/0209450) for the proper * definition. * * \param graph The input graph, it can be directed or undirected. * \param types Vector giving the vertex types. They are assumed to be * integer numbers, starting with zero. * \param res Pointer to a real variable, the result is stored here. * \param directed Boolean, it gives whether to consider edge * directions in a directed graph. It is ignored for undirected * graphs. * \return Error code. * * Time complexity: O(|E|+t), |E| is the number of edges, t is the * number of vertex types. * * \sa \ref igraph_assortativity if the vertex types are defines by * numeric values (e.g. vertex degree), instead of categories. * * \example examples/simple/assortativity.c */ int igraph_assortativity_nominal(const igraph_t *graph, const igraph_vector_t *types, igraph_real_t *res, igraph_bool_t directed) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); long int no_of_types; igraph_vector_t ai, bi, eii; long int e, i; igraph_real_t sumaibi = 0.0, sumeii = 0.0; if (igraph_vector_size(types) != no_of_nodes) { IGRAPH_ERROR("Invalid `types' vector length", IGRAPH_EINVAL); } if (igraph_vector_min(types) < 0) { IGRAPH_ERROR("Invalid `types' vector", IGRAPH_EINVAL); } directed = directed && igraph_is_directed(graph); no_of_types = (long int) igraph_vector_max(types) + 1; IGRAPH_VECTOR_INIT_FINALLY(&ai, no_of_types); IGRAPH_VECTOR_INIT_FINALLY(&bi, no_of_types); IGRAPH_VECTOR_INIT_FINALLY(&eii, no_of_types); for (e = 0; e < no_of_edges; e++) { long int from = IGRAPH_FROM(graph, e); long int to = IGRAPH_TO(graph, e); long int from_type = (long int) VECTOR(*types)[from]; long int to_type = (long int) VECTOR(*types)[to]; VECTOR(ai)[from_type] += 1; VECTOR(bi)[to_type] += 1; if (from_type == to_type) { VECTOR(eii)[from_type] += 1; } if (!directed) { if (from_type == to_type) { VECTOR(eii)[from_type] += 1; } VECTOR(ai)[to_type] += 1; VECTOR(bi)[from_type] += 1; } } for (i = 0; i < no_of_types; i++) { sumaibi += (VECTOR(ai)[i] / no_of_edges) * (VECTOR(bi)[i] / no_of_edges); sumeii += (VECTOR(eii)[i] / no_of_edges); } if (!directed) { sumaibi /= 4.0; sumeii /= 2.0; } *res = (sumeii - sumaibi) / (1.0 - sumaibi); igraph_vector_destroy(&eii); igraph_vector_destroy(&bi); igraph_vector_destroy(&ai); IGRAPH_FINALLY_CLEAN(3); return 0; } /** * \function igraph_assortativity * Assortativity based on numeric properties of vertices * * This function calculates the assortativity coefficient of the input * graph. This coefficient is basically the correlation between the * actual connectivity patterns of the vertices and the pattern * expected from the distribution of the vertex types. * * See equation (21) in M. E. J. Newman: Mixing patterns * in networks, Phys. Rev. E 67, 026126 (2003) * (http://arxiv.org/abs/cond-mat/0209450) for the proper * definition. The actual calculation is performed using equation (26) * in the same paper for directed graphs, and equation (4) in * M. E. J. Newman: Assortative mixing in networks, * Phys. Rev. Lett. 89, 208701 (2002) * (http://arxiv.org/abs/cond-mat/0205405/) for undirected graphs. * * \param graph The input graph, it can be directed or undirected. * \param types1 The vertex values, these can be arbitrary numeric * values. * \param types2 A second value vector to be using for the incoming * edges when calculating assortativity for a directed graph. * Supply a null pointer here if you want to use the same values * for outgoing and incoming edges. This argument is ignored * (with a warning) if it is not a null pointer and undirected * assortativity coefficient is being calculated. * \param res Pointer to a real variable, the result is stored here. * \param directed Boolean, whether to consider edge directions for * directed graphs. It is ignored for undirected graphs. * \return Error code. * * Time complexity: O(|E|), linear in the number of edges of the * graph. * * \sa \ref igraph_assortativity_nominal() if you have discrete vertex * categories instead of numeric labels, and \ref * igraph_assortativity_degree() for the special case of assortativity * based on vertex degree. * * \example examples/simple/assortativity.c */ int igraph_assortativity(const igraph_t *graph, const igraph_vector_t *types1, const igraph_vector_t *types2, igraph_real_t *res, igraph_bool_t directed) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); long int e; directed = directed && igraph_is_directed(graph); if (!directed && types2) { IGRAPH_WARNING("Only `types1' is used for undirected case"); } if (igraph_vector_size(types1) != no_of_nodes) { IGRAPH_ERROR("Invalid `types1' vector length", IGRAPH_EINVAL); } if (types2 && igraph_vector_size(types2) != no_of_nodes) { IGRAPH_ERROR("Invalid `types2' vector length", IGRAPH_EINVAL); } if (!directed) { igraph_real_t num1 = 0.0, num2 = 0.0, den1 = 0.0; for (e = 0; e < no_of_edges; e++) { long int from = IGRAPH_FROM(graph, e); long int to = IGRAPH_TO(graph, e); igraph_real_t from_type = VECTOR(*types1)[from]; igraph_real_t to_type = VECTOR(*types1)[to]; num1 += from_type * to_type; num2 += from_type + to_type; den1 += from_type * from_type + to_type * to_type; } num1 /= no_of_edges; den1 /= no_of_edges * 2; num2 /= no_of_edges * 2; num2 = num2 * num2; *res = (num1 - num2) / (den1 - num2); } else { igraph_real_t num1 = 0.0, num2 = 0.0, num3 = 0.0, den1 = 0.0, den2 = 0.0; igraph_real_t num, den; if (!types2) { types2 = types1; } for (e = 0; e < no_of_edges; e++) { long int from = IGRAPH_FROM(graph, e); long int to = IGRAPH_TO(graph, e); igraph_real_t from_type = VECTOR(*types1)[from]; igraph_real_t to_type = VECTOR(*types2)[to]; num1 += from_type * to_type; num2 += from_type; num3 += to_type; den1 += from_type * from_type; den2 += to_type * to_type; } num = num1 - num2 * num3 / no_of_edges; den = sqrt(den1 - num2 * num2 / no_of_edges) * sqrt(den2 - num3 * num3 / no_of_edges); *res = num / den; } return 0; } /** * \function igraph_assortativity_degree * Assortativity of a graph based on vertex degree * * Assortativity based on vertex degree, please see the discussion at * the documentation of \ref igraph_assortativity() for details. * * \param graph The input graph, it can be directed or undirected. * \param res Pointer to a real variable, the result is stored here. * \param directed Boolean, whether to consider edge directions for * directed graphs. This argument is ignored for undirected * graphs. Supply 1 (=TRUE) here to do the natural thing, i.e. use * directed version of the measure for directed graphs and the * undirected version for undirected graphs. * \return Error code. * * Time complexity: O(|E|+|V|), |E| is the number of edges, |V| is * the number of vertices. * * \sa \ref igraph_assortativity() for the general function * calculating assortativity for any kind of numeric vertex values. * * \example examples/simple/assortativity.c */ int igraph_assortativity_degree(const igraph_t *graph, igraph_real_t *res, igraph_bool_t directed) { directed = directed && igraph_is_directed(graph); if (directed) { igraph_vector_t indegree, outdegree; igraph_vector_init(&indegree, 0); igraph_vector_init(&outdegree, 0); igraph_degree(graph, &indegree, igraph_vss_all(), IGRAPH_IN, /*loops=*/ 1); igraph_degree(graph, &outdegree, igraph_vss_all(), IGRAPH_OUT, /*loops=*/ 1); igraph_vector_add_constant(&indegree, -1); igraph_vector_add_constant(&outdegree, -1); igraph_assortativity(graph, &outdegree, &indegree, res, /*directed=*/ 1); igraph_vector_destroy(&indegree); igraph_vector_destroy(&outdegree); } else { igraph_vector_t degree; igraph_vector_init(°ree, 0); igraph_degree(graph, °ree, igraph_vss_all(), IGRAPH_ALL, /*loops=*/ 1); igraph_vector_add_constant(°ree, -1); igraph_assortativity(graph, °ree, 0, res, /*directed=*/ 0); igraph_vector_destroy(°ree); } return 0; } python-igraph-0.8.0/vendor/source/igraph/src/hrg_graph_simp.h0000644000076500000240000001255413614300625024547 0ustar tamasstaff00000000000000/* -*- mode: C++ -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ // **************************************************************************************************** // *** COPYRIGHT NOTICE ******************************************************************************* // graph_simp.h - graph data structure // Copyright (C) 2006-2008 Aaron Clauset // // This program is free software; you can redistribute it and/or modify // it under the terms of the GNU General Public License as published by // the Free Software Foundation; either version 2 of the License, or // (at your option) any later version. // // This program is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU General Public License for more details. // // You should have received a copy of the GNU General Public License // along with this program; if not, write to the Free Software // Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA // // See http://www.gnu.org/licenses/gpl.txt for more details. // // **************************************************************************************************** // Author : Aaron Clauset ( aaronc@santafe.edu | http://www.santafe.edu/~aaronc/ ) // Collaborators: Cristopher Moore and Mark E.J. Newman // Project : Hierarchical Random Graphs // Location : University of New Mexico, Dept. of Computer Science AND Santa Fe Institute // Created : 21 June 2006 // Modified : 23 December 2007 (cleaned up for public consumption) // // ************************************************************************ // // Simple graph data structure. The basic structure is an adjacency // list of edges, along with degree information for the vertices. // // ************************************************************************ #ifndef IGRAPH_HRG_SIMPLEGRAPH #define IGRAPH_HRG_SIMPLEGRAPH #include #include #include #include "hrg_rbtree.h" #include "hrg_dendro.h" using namespace std; namespace fitHRG { // ******** Basic Structures ********************************************* #ifndef IGRAPH_HRG_SIMPLEEDGE #define IGRAPH_HRG_SIMPLEEDGE class simpleEdge { public: int x; // index of edge terminator simpleEdge* next; // pointer to next elementd simpleEdge(): x(-1), next(0) { } ~simpleEdge() { } }; #endif #ifndef IGRAPH_HRG_SIMPLEVERT #define IGRAPH_HRG_SIMPLEVERT class simpleVert { public: string name; // (external) name of vertex int degree; // degree of this vertex int group_true; // index of vertex's true group simpleVert(): name(""), degree(0), group_true(-1) { } ~simpleVert() { } }; #endif #ifndef IGRAPH_HRG_TWOEDGE #define IGRAPH_HRG_TWOEDGE class twoEdge { public: int o; // index of edge originator int x; // index of edge terminator twoEdge(): o(-1), x(-1) { } ~twoEdge() { } }; #endif // ******** Graph Class with Edge Statistics ***************************** class simpleGraph { public: simpleGraph(const int); ~simpleGraph(); // add group label to vertex i bool addGroup(const int, const int); // add (i,j) to graph bool addLink(const int, const int); // true if (i,j) is already in graph bool doesLinkExist(const int, const int); // returns A(i,j) double getAdjacency(const int, const int); // returns degree of vertex i int getDegree(const int); // returns group label of vertex i int getGroupLabel(const int); // returns name of vertex i string getName(const int); // returns edge list of vertex i simpleEdge* getNeighborList(const int); // return pointer to a node simpleVert* getNode(const int); // returns num_groups int getNumGroups(); // returns m int getNumLinks(); // returns n int getNumNodes(); // set name of vertex i bool setName(const int, const string); private: simpleVert* nodes; // list of nodes simpleEdge** nodeLink; // linked list of neighbors to vertex simpleEdge** nodeLinkTail; // pointers to tail of neighbor list double** A; // adjacency matrix for this graph twoEdge* E; // list of all edges (array) int n; // number of vertices int m; // number of directed edges int num_groups; // number of bins in node histograms // quicksort functions void QsortMain(block*, int, int); int QsortPartition(block*, int, int, int); }; } // namespace fitHRG #endif python-igraph-0.8.0/vendor/source/igraph/src/prpack.h0000644000076500000240000000323013614300625023025 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_PRPACK #define IGRAPH_PRPACK #undef __BEGIN_DECLS #undef __END_DECLS #ifdef __cplusplus #define __BEGIN_DECLS extern "C" { #define __END_DECLS } #else #define __BEGIN_DECLS /* empty */ #define __END_DECLS /* empty */ #endif #include "igraph_types.h" #include "igraph_datatype.h" #include "igraph_iterators.h" #include "igraph_interface.h" __BEGIN_DECLS int igraph_personalized_pagerank_prpack(const igraph_t *graph, igraph_vector_t *vector, igraph_real_t *value, const igraph_vs_t vids, igraph_bool_t directed, igraph_real_t damping, igraph_vector_t *reset, const igraph_vector_t *weights); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/src/gengraph_vertex_cover.h0000644000076500000240000000453513614300625026144 0ustar tamasstaff00000000000000/* * * gengraph - generation of random simple connected graphs with prescribed * degree sequence * * Copyright (C) 2006 Fabien Viger * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #ifndef _VERTEX_COVER_H #define _VERTEX_COVER_H // vertex_cover() builds a list of vertices which covers every edge of the graph // Input is a classical adjacency-list graph // As an output, vertex_cover() modify the degrees in degs[], so that // any vertex with a degree > 0 belongs to the vertex coverage. // Moreover, vertex_cover() keeps links[] intact, permuting only the adjacency lists #include "gengraph_box_list.h" #ifndef register #define register #endif namespace gengraph { void vertex_cover(int n, int *links, int *deg, int **neigh = NULL) { int i; // create and initialize neigh[] if (neigh == NULL) { neigh = new int*[n]; neigh[0] = links; for (i = 1; i < n; i++) { neigh[i] = neigh[i - 1] + deg[i]; } } // create box_list box_list bl(n, deg); do { int v; // remove vertices adjacent to vertices of degree 1 while ((v = bl.get_one()) >= 0) { bl.pop_vertex(v, neigh); } // remove vertex of max degree and its highest-degree neighbour if (!bl.is_empty()) { v = bl.get_max(); int *w = neigh[v]; register int v2 = *(w++); register int dm = deg[v2]; register int k = deg[v] - 1; while (k--) if (deg[*(w++)] > dm) { v2 = *(w - 1); dm = deg[v2]; }; bl.pop_vertex(v, neigh); bl.pop_vertex(v2, neigh); } } while (!bl.is_empty()); } } // namespace gengraph #endif //_VERTEX_COVER_H python-igraph-0.8.0/vendor/source/igraph/src/layout_gem.c0000644000076500000240000002253513614300625023716 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph R package. Copyright (C) 2014 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_layout.h" #include "igraph_interface.h" #include "igraph_random.h" #include "igraph_math.h" /** * \ingroup layout * \function igraph_layout_gem * * The GEM layout algorithm, as described in Arne Frick, Andreas Ludwig, * Heiko Mehldau: A Fast Adaptive Layout Algorithm for Undirected Graphs, * Proc. Graph Drawing 1994, LNCS 894, pp. 388-403, 1995. * \param graph The input graph. Edge directions are ignored in * directed graphs. * \param res The result is stored here. If the \p use_seed argument * is true (non-zero), then this matrix is also used as the * starting point of the algorithm. * \param use_seed Boolean, whether to use the supplied coordinates in * \p res as the starting point. If false (zero), then a * uniform random starting point is used. * \param maxiter The maximum number of iterations to * perform. Updating a single vertex counts as an iteration. * A reasonable default is 40 * n * n, where n is the number of * vertices. The original paper suggests 4 * n * n, but this * usually only works if the other parameters are set up carefully. * \param temp_max The maximum allowed local temperature. A reasonable * default is the number of vertices. * \param temp_min The global temperature at which the algorithm * terminates (even before reaching \p maxiter iterations). A * reasonable default is 1/10. * \param temp_init Initial local temperature of all vertices. A * reasonable default is the square root of the number of * vertices. * \return Error code. * * Time complexity: O(t * n * (n+e)), where n is the number of vertices, * e is the number of edges and t is the number of time steps * performed. */ int igraph_layout_gem(const igraph_t *graph, igraph_matrix_t *res, igraph_bool_t use_seed, igraph_integer_t maxiter, igraph_real_t temp_max, igraph_real_t temp_min, igraph_real_t temp_init) { igraph_integer_t no_nodes = igraph_vcount(graph); igraph_vector_int_t perm; igraph_vector_float_t impulse_x, impulse_y, temp, skew_gauge; igraph_integer_t i; float temp_global; igraph_integer_t perm_pointer = 0; float barycenter_x = 0.0, barycenter_y = 0.0; igraph_vector_t phi; igraph_vector_t neis; const float elen_des2 = 128 * 128; const float gamma = 1 / 16.0; const float alpha_o = M_PI; const float alpha_r = M_PI / 3.0; const float sigma_o = 1.0 / 3.0; const float sigma_r = 1.0 / 2.0 / no_nodes; if (maxiter < 0) { IGRAPH_ERROR("Number of iterations must be non-negative in GEM layout", IGRAPH_EINVAL); } if (use_seed && (igraph_matrix_nrow(res) != no_nodes || igraph_matrix_ncol(res) != 2)) { IGRAPH_ERROR("Invalid start position matrix size in GEM layout", IGRAPH_EINVAL); } if (temp_max <= 0) { IGRAPH_ERROR("Maximum temperature should be positive in GEM layout", IGRAPH_EINVAL); } if (temp_min <= 0) { IGRAPH_ERROR("Minimum temperature should be positive in GEM layout", IGRAPH_EINVAL); } if (temp_init <= 0) { IGRAPH_ERROR("Initial temperature should be positive in GEM layout", IGRAPH_EINVAL); } if (temp_max < temp_init || temp_init < temp_min) { IGRAPH_ERROR("Minimum <= Initial <= Maximum temperature is required " "in GEM layout", IGRAPH_EINVAL); } if (no_nodes == 0) { return 0; } IGRAPH_CHECK(igraph_vector_float_init(&impulse_x, no_nodes)); IGRAPH_FINALLY(igraph_vector_float_destroy, &impulse_x); IGRAPH_CHECK(igraph_vector_float_init(&impulse_y, no_nodes)); IGRAPH_FINALLY(igraph_vector_float_destroy, &impulse_y); IGRAPH_CHECK(igraph_vector_float_init(&temp, no_nodes)); IGRAPH_FINALLY(igraph_vector_float_destroy, &temp); IGRAPH_CHECK(igraph_vector_float_init(&skew_gauge, no_nodes)); IGRAPH_FINALLY(igraph_vector_float_destroy, &skew_gauge); IGRAPH_CHECK(igraph_vector_int_init_seq(&perm, 0, no_nodes - 1)); IGRAPH_FINALLY(igraph_vector_int_destroy, &perm); IGRAPH_VECTOR_INIT_FINALLY(&phi, no_nodes); IGRAPH_VECTOR_INIT_FINALLY(&neis, 10); RNG_BEGIN(); /* Initialization */ igraph_degree(graph, &phi, igraph_vss_all(), IGRAPH_ALL, IGRAPH_LOOPS); if (!use_seed) { const igraph_real_t width_half = no_nodes * 100, height_half = width_half; IGRAPH_CHECK(igraph_matrix_resize(res, no_nodes, 2)); for (i = 0; i < no_nodes; i++) { MATRIX(*res, i, 0) = RNG_UNIF(-width_half, width_half); MATRIX(*res, i, 1) = RNG_UNIF(-height_half, height_half); barycenter_x += MATRIX(*res, i, 0); barycenter_y += MATRIX(*res, i, 1); VECTOR(phi)[i] *= (VECTOR(phi)[i] / 2.0 + 1.0); } } else { for (i = 0; i < no_nodes; i++) { barycenter_x += MATRIX(*res, i, 0); barycenter_y += MATRIX(*res, i, 1); VECTOR(phi)[i] *= (VECTOR(phi)[i] / 2.0 + 1.0); } } igraph_vector_float_fill(&temp, temp_init); temp_global = temp_init * no_nodes; while (temp_global > temp_min * no_nodes && maxiter > 0) { /* choose a vertex v to update */ igraph_integer_t u, v, nlen, j; float px, py, pvx, pvy; if (!perm_pointer) { igraph_vector_int_shuffle(&perm); perm_pointer = no_nodes - 1; } v = VECTOR(perm)[perm_pointer--]; /* compute v's impulse */ px = (barycenter_x / no_nodes - MATRIX(*res, v, 0)) * gamma * VECTOR(phi)[v]; py = (barycenter_y / no_nodes - MATRIX(*res, v, 1)) * gamma * VECTOR(phi)[v]; px += RNG_UNIF(-32.0, 32.0); py += RNG_UNIF(-32.0, 32.0); for (u = 0; u < no_nodes; u++) { float dx, dy, dist2; if (u == v) { continue; } dx = MATRIX(*res, v, 0) - MATRIX(*res, u, 0); dy = MATRIX(*res, v, 1) - MATRIX(*res, u, 1); dist2 = dx * dx + dy * dy; if (dist2 != 0) { px += dx * elen_des2 / dist2; py += dy * elen_des2 / dist2; } } IGRAPH_CHECK(igraph_neighbors(graph, &neis, v, IGRAPH_ALL)); nlen = igraph_vector_size(&neis); for (j = 0; j < nlen; j++) { igraph_integer_t u = VECTOR(neis)[j]; float dx = MATRIX(*res, v, 0) - MATRIX(*res, u, 0); float dy = MATRIX(*res, v, 1) - MATRIX(*res, u, 1); float dist2 = dx * dx + dy * dy; px -= dx * dist2 / (elen_des2 * VECTOR(phi)[v]); py -= dy * dist2 / (elen_des2 * VECTOR(phi)[v]); } /* update v's position and temperature */ if (px != 0 || py != 0) { float plen = sqrtf(px * px + py * py); px *= VECTOR(temp)[v] / plen; py *= VECTOR(temp)[v] / plen; MATRIX(*res, v, 0) += px; MATRIX(*res, v, 1) += py; barycenter_x += px; barycenter_y += py; } pvx = VECTOR(impulse_x)[v]; pvy = VECTOR(impulse_y)[v]; if (pvx != 0 || pvy != 0) { float beta = atan2f(pvy - py, pvx - px); float sin_beta = sinf(beta); float sign_sin_beta = (sin_beta > 0) ? 1 : ((sin_beta < 0) ? -1 : 0); float cos_beta = cosf(beta); float abs_cos_beta = fabsf(cos_beta); float old_temp = VECTOR(temp)[v]; if (sin(beta) >= sin(M_PI_2 + alpha_r / 2.0)) { VECTOR(skew_gauge)[v] += sigma_r * sign_sin_beta; } if (abs_cos_beta >= cosf(alpha_o / 2.0)) { VECTOR(temp)[v] *= sigma_o * cos_beta; } VECTOR(temp)[v] *= (1 - fabsf(VECTOR(skew_gauge)[v])); if (VECTOR(temp)[v] > temp_max) { VECTOR(temp)[v] = temp_max; } VECTOR(impulse_x)[v] = px; VECTOR(impulse_y)[v] = py; temp_global += VECTOR(temp)[v] - old_temp; } maxiter--; } /* while temp && iter */ RNG_END(); igraph_vector_destroy(&neis); igraph_vector_destroy(&phi); igraph_vector_int_destroy(&perm); igraph_vector_float_destroy(&skew_gauge); igraph_vector_float_destroy(&temp); igraph_vector_float_destroy(&impulse_y); igraph_vector_float_destroy(&impulse_x); IGRAPH_FINALLY_CLEAN(7); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/vector.pmt0000644000076500000240000022652413614300625023435 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2003-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_memory.h" #include "igraph_error.h" #include "igraph_random.h" #include "igraph_qsort.h" #include #include /* memcpy & co. */ #include #include /* va_start & co */ #include /** * \ingroup vector * \section about_igraph_vector_t_objects About \type igraph_vector_t objects * * The \type igraph_vector_t data type is a simple and efficient * interface to arrays containing numbers. It is something * similar as (but much simpler than) the \type vector template * in the C++ standard library. * * Vectors are used extensively in \a igraph, all * functions which expect or return a list of numbers use * igraph_vector_t to achieve this. * * The \type igraph_vector_t type usually uses * O(n) space * to store n elements. Sometimes it * uses more, this is because vectors can shrink, but even if they * shrink, the current implementation does not free a single bit of * memory. * * The elements in an \type igraph_vector_t * object are indexed from zero, we follow the usual C convention * here. * * The elements of a vector always occupy a single block of * memory, the starting address of this memory block can be queried * with the \ref VECTOR macro. This way, vector objects can be used * with standard mathematical libraries, like the GNU Scientific * Library. */ /** * \ingroup vector * \section igraph_vector_constructors_and_destructors Constructors and * Destructors * * \type igraph_vector_t objects have to be initialized before using * them, this is analogous to calling a constructor on them. There are a * number of \type igraph_vector_t constructors, for your * convenience. \ref igraph_vector_init() is the basic constructor, it * creates a vector of the given length, filled with zeros. * \ref igraph_vector_copy() creates a new identical copy * of an already existing and initialized vector. \ref * igraph_vector_init_copy() creates a vector by copying a regular C array. * \ref igraph_vector_init_seq() creates a vector containing a regular * sequence with increment one. * * \ref igraph_vector_view() is a special constructor, it allows you to * handle a regular C array as a \type vector without copying * its elements. * * * If a \type igraph_vector_t object is not needed any more, it * should be destroyed to free its allocated memory by calling the * \type igraph_vector_t destructor, \ref igraph_vector_destroy(). * * Note that vectors created by \ref igraph_vector_view() are special, * you mustn't call \ref igraph_vector_destroy() on these. */ /** * \ingroup vector * \function igraph_vector_init * \brief Initializes a vector object (constructor). * * * Every vector needs to be initialized before it can be used, and * there are a number of initialization functions or otherwise called * constructors. This function constructs a vector of the given size and * initializes each entry to 0. Note that \ref igraph_vector_null() can be * used to set each element of a vector to zero. However, if you want a * vector of zeros, it is much faster to use this function than to create a * vector and then invoke \ref igraph_vector_null(). * * * Every vector object initialized by this function should be * destroyed (ie. the memory allocated for it should be freed) when it * is not needed anymore, the \ref igraph_vector_destroy() function is * responsible for this. * \param v Pointer to a not yet initialized vector object. * \param size The size of the vector. * \return error code: * \c IGRAPH_ENOMEM if there is not enough memory. * * Time complexity: operating system dependent, the amount of * \quote time \endquote required to allocate * O(n) elements, * n is the number of elements. */ int FUNCTION(igraph_vector, init) (TYPE(igraph_vector)* v, int long size) { long int alloc_size = size > 0 ? size : 1; if (size < 0) { size = 0; } v->stor_begin = igraph_Calloc(alloc_size, BASE); if (v->stor_begin == 0) { IGRAPH_ERROR("cannot init vector", IGRAPH_ENOMEM); } v->stor_end = v->stor_begin + alloc_size; v->end = v->stor_begin + size; return 0; } /** * \ingroup vector * \function igraph_vector_view * \brief Handle a regular C array as a \type igraph_vector_t. * * * This is a special \type igraph_vector_t constructor. It allows to * handle a regular C array as a \type igraph_vector_t temporarily. * Be sure that you \em don't ever call the destructor (\ref * igraph_vector_destroy()) on objects created by this constructor. * \param v Pointer to an uninitialized \type igraph_vector_t object. * \param data Pointer, the C array. It may not be \c NULL. * \param length The length of the C array. * \return Pointer to the vector object, the same as the * \p v parameter, for convenience. * * Time complexity: O(1) */ const TYPE(igraph_vector)*FUNCTION(igraph_vector, view) (const TYPE(igraph_vector) *v, const BASE *data, long int length) { TYPE(igraph_vector) *v2 = (TYPE(igraph_vector)*)v; assert(data != 0); v2->stor_begin = (BASE*)data; v2->stor_end = (BASE*)data + length; v2->end = v2->stor_end; return v; } #ifndef BASE_COMPLEX /** * \ingroup vector * \function igraph_vector_init_real * \brief Create an \type igraph_vector_t from the parameters. * * * Because of how C and the C library handles variable length argument * lists, it is required that you supply real constants to this * function. This means that * \verbatim igraph_vector_t v; * igraph_vector_init_real(&v, 5, 1,2,3,4,5); \endverbatim * is an error at runtime and the results are undefined. This is * the proper way: * \verbatim igraph_vector_t v; * igraph_vector_init_real(&v, 5, 1.0,2.0,3.0,4.0,5.0); \endverbatim * \param v Pointer to an uninitialized \type igraph_vector_t object. * \param no Positive integer, the number of \type igraph_real_t * parameters to follow. * \param ... The elements of the vector. * \return Error code, this can be \c IGRAPH_ENOMEM * if there isn't enough memory to allocate the vector. * * \sa \ref igraph_vector_init_real_end(), \ref igraph_vector_init_int() for similar * functions. * * Time complexity: depends on the time required to allocate memory, * but at least O(n), the number of * elements in the vector. */ int FUNCTION(igraph_vector, init_real)(TYPE(igraph_vector) *v, int no, ...) { int i = 0; va_list ap; IGRAPH_CHECK(FUNCTION(igraph_vector, init)(v, no)); va_start(ap, no); for (i = 0; i < no; i++) { VECTOR(*v)[i] = (BASE) va_arg(ap, double); } va_end(ap); return 0; } /** * \ingroup vector * \function igraph_vector_init_real_end * \brief Create an \type igraph_vector_t from the parameters. * * * This constructor is similar to \ref igraph_vector_init_real(), the only * difference is that instead of giving the number of elements in the * vector, a special marker element follows the last real vector * element. * \param v Pointer to an uninitialized \type igraph_vector_t object. * \param endmark This element will signal the end of the vector. It * will \em not be part of the vector. * \param ... The elements of the vector. * \return Error code, \c IGRAPH_ENOMEM if there * isn't enough memory. * * \sa \ref igraph_vector_init_real() and \ref igraph_vector_init_int_end() for * similar functions. * * Time complexity: at least O(n) for * n elements plus the time * complexity of the memory allocation. */ int FUNCTION(igraph_vector, init_real_end)(TYPE(igraph_vector) *v, BASE endmark, ...) { int i = 0, n = 0; va_list ap; va_start(ap, endmark); while (1) { BASE num = (BASE) va_arg(ap, double); if (num == endmark) { break; } n++; } va_end(ap); IGRAPH_CHECK(FUNCTION(igraph_vector, init)(v, n)); IGRAPH_FINALLY(FUNCTION(igraph_vector, destroy), v); va_start(ap, endmark); for (i = 0; i < n; i++) { VECTOR(*v)[i] = (BASE) va_arg(ap, double); } va_end(ap); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \ingroup vector * \function igraph_vector_init_int * \brief Create an \type igraph_vector_t containing the parameters. * * * This function is similar to \ref igraph_vector_init_real(), but it expects * \type int parameters. It is important that all parameters * should be of this type, otherwise the result of the function call * is undefined. * \param v Pointer to an uninitialized \type igraph_vector_t object. * \param no The number of \type int parameters to follow. * \param ... The elements of the vector. * \return Error code, \c IGRAPH_ENOMEM if there is * not enough memory. * \sa \ref igraph_vector_init_real() and igraph_vector_init_int_end(), these are * similar functions. * * Time complexity: at least O(n) for * n elements plus the time * complexity of the memory allocation. */ int FUNCTION(igraph_vector, init_int)(TYPE(igraph_vector) *v, int no, ...) { int i = 0; va_list ap; IGRAPH_CHECK(FUNCTION(igraph_vector, init)(v, no)); va_start(ap, no); for (i = 0; i < no; i++) { VECTOR(*v)[i] = (BASE) va_arg(ap, int); } va_end(ap); return 0; } /** * \ingroup vector * \function igraph_vector_init_int_end * \brief Create an \type igraph_vector_t from the parameters. * * * This constructor is similar to \ref igraph_vector_init_int(), the only * difference is that instead of giving the number of elements in the * vector, a special marker element follows the last real vector * element. * \param v Pointer to an uninitialized \type igraph_vector_t object. * \param endmark This element will signal the end of the vector. It * will \em not be part of the vector. * \param ... The elements of the vector. * \return Error code, \c IGRAPH_ENOMEM if there * isn't enough memory. * * \sa \ref igraph_vector_init_int() and \ref igraph_vector_init_real_end() for * similar functions. * * Time complexity: at least O(n) for * n elements plus the time * complexity of the memory allocation. */ int FUNCTION(igraph_vector_init, int_end)(TYPE(igraph_vector) *v, int endmark, ...) { int i = 0, n = 0; va_list ap; va_start(ap, endmark); while (1) { int num = va_arg(ap, int); if (num == endmark) { break; } n++; } va_end(ap); IGRAPH_CHECK(FUNCTION(igraph_vector, init)(v, n)); IGRAPH_FINALLY(FUNCTION(igraph_vector, destroy), v); va_start(ap, endmark); for (i = 0; i < n; i++) { VECTOR(*v)[i] = (BASE) va_arg(ap, int); } va_end(ap); IGRAPH_FINALLY_CLEAN(1); return 0; } #endif /* ifndef BASE_COMPLEX */ /** * \ingroup vector * \function igraph_vector_destroy * \brief Destroys a vector object. * * * All vectors initialized by \ref igraph_vector_init() should be properly * destroyed by this function. A destroyed vector needs to be * reinitialized by \ref igraph_vector_init(), \ref igraph_vector_init_copy() or * another constructor. * \param v Pointer to the (previously initialized) vector object to * destroy. * * Time complexity: operating system dependent. */ void FUNCTION(igraph_vector, destroy) (TYPE(igraph_vector)* v) { assert(v != 0); if (v->stor_begin != 0) { igraph_Free(v->stor_begin); v->stor_begin = NULL; } } /** * \ingroup vector * \function igraph_vector_capacity * \brief Returns the allocated capacity of the vector * * Note that this might be different from the size of the vector (as * queried by \ref igraph_vector_size(), and specifies how many elements * the vector can hold, without reallocation. * \param v Pointer to the (previously initialized) vector object * to query. * \return The allocated capacity. * * \sa \ref igraph_vector_size(). * * Time complexity: O(1). */ long int FUNCTION(igraph_vector, capacity)(const TYPE(igraph_vector)*v) { return v->stor_end - v->stor_begin; } /** * \ingroup vector * \function igraph_vector_reserve * \brief Reserves memory for a vector. * * * \a igraph vectors are flexible, they can grow and * shrink. Growing * however occasionally needs the data in the vector to be copied. * In order to avoid this, you can call this function to reserve space for * future growth of the vector. * * * Note that this function does \em not change the size of the * vector. Let us see a small example to clarify things: if you * reserve space for 100 elements and the size of your * vector was (and still is) 60, then you can surely add additional 40 * elements to your vector before it will be copied. * \param v The vector object. * \param size The new \em allocated size of the vector. * \return Error code: * \c IGRAPH_ENOMEM if there is not enough memory. * * Time complexity: operating system dependent, should be around * O(n), n * is the new allocated size of the vector. */ int FUNCTION(igraph_vector, reserve) (TYPE(igraph_vector)* v, long int size) { long int actual_size = FUNCTION(igraph_vector, size)(v); BASE *tmp; assert(v != NULL); assert(v->stor_begin != NULL); if (size <= FUNCTION(igraph_vector, size)(v)) { return 0; } tmp = igraph_Realloc(v->stor_begin, (size_t) size, BASE); if (tmp == 0) { IGRAPH_ERROR("cannot reserve space for vector", IGRAPH_ENOMEM); } v->stor_begin = tmp; v->stor_end = v->stor_begin + size; v->end = v->stor_begin + actual_size; return 0; } /** * \ingroup vector * \function igraph_vector_empty * \brief Decides whether the size of the vector is zero. * * \param v The vector object. * \return Non-zero number (true) if the size of the vector is zero and * zero (false) otherwise. * * Time complexity: O(1). */ igraph_bool_t FUNCTION(igraph_vector, empty) (const TYPE(igraph_vector)* v) { assert(v != NULL); assert(v->stor_begin != NULL); return v->stor_begin == v->end; } /** * \ingroup vector * \function igraph_vector_size * \brief Gives the size (=length) of the vector. * * \param v The vector object * \return The size of the vector. * * Time complexity: O(1). */ long int FUNCTION(igraph_vector, size) (const TYPE(igraph_vector)* v) { assert(v != NULL); assert(v->stor_begin != NULL); return v->end - v->stor_begin; } /** * \ingroup vector * \function igraph_vector_clear * \brief Removes all elements from a vector. * * * This function simply sets the size of the vector to zero, it does * not free any allocated memory. For that you have to call * \ref igraph_vector_destroy(). * \param v The vector object. * * Time complexity: O(1). */ void FUNCTION(igraph_vector, clear) (TYPE(igraph_vector)* v) { assert(v != NULL); assert(v->stor_begin != NULL); v->end = v->stor_begin; } /** * \ingroup vector * \function igraph_vector_push_back * \brief Appends one element to a vector. * * * This function resizes the vector to be one element longer and * sets the very last element in the vector to \p e. * \param v The vector object. * \param e The element to append to the vector. * \return Error code: * \c IGRAPH_ENOMEM: not enough memory. * * Time complexity: operating system dependent. What is important is that * a sequence of n * subsequent calls to this function has time complexity * O(n), even if there * hadn't been any space reserved for the new elements by * \ref igraph_vector_reserve(). This is implemented by a trick similar to the C++ * \type vector class: each time more memory is allocated for a * vector, the size of the additionally allocated memory is the same * as the vector's current length. (We assume here that the time * complexity of memory allocation is at most linear.) */ int FUNCTION(igraph_vector, push_back) (TYPE(igraph_vector)* v, BASE e) { assert(v != NULL); assert(v->stor_begin != NULL); /* full, allocate more storage */ if (v->stor_end == v->end) { long int new_size = FUNCTION(igraph_vector, size)(v) * 2; if (new_size == 0) { new_size = 1; } IGRAPH_CHECK(FUNCTION(igraph_vector, reserve)(v, new_size)); } *(v->end) = e; v->end += 1; return 0; } /** * \ingroup vector * \function igraph_vector_insert * \brief Inserts a single element into a vector. * * Note that this function does not do range checking. Insertion will shift the * elements from the position given to the end of the vector one position to the * right, and the new element will be inserted in the empty space created at * the given position. The size of the vector will increase by one. * * \param v The vector object. * \param pos The position where the new element is to be inserted. * \param value The new element to be inserted. */ int FUNCTION(igraph_vector, insert)(TYPE(igraph_vector) *v, long int pos, BASE value) { size_t size = (size_t) FUNCTION(igraph_vector, size)(v); IGRAPH_CHECK(FUNCTION(igraph_vector, resize)(v, (long) size + 1)); if (pos < size) { memmove(v->stor_begin + pos + 1, v->stor_begin + pos, sizeof(BASE) * (size - (size_t) pos)); } v->stor_begin[pos] = value; return 0; } /** * \ingroup vector * \section igraph_vector_accessing_elements Accessing elements * * The simplest way to access an element of a vector is to use the * \ref VECTOR macro. This macro can be used both for querying and setting * \type igraph_vector_t elements. If you need a function, \ref * igraph_vector_e() queries and \ref igraph_vector_set() sets an element of a * vector. \ref igraph_vector_e_ptr() returns the address of an element. * * \ref igraph_vector_tail() returns the last element of a non-empty * vector. There is no igraph_vector_head() function * however, as it is easy to write VECTOR(v)[0] * instead. */ /** * \ingroup vector * \function igraph_vector_e * \brief Access an element of a vector. * \param v The \type igraph_vector_t object. * \param pos The position of the element, the index of the first * element is zero. * \return The desired element. * \sa \ref igraph_vector_e_ptr() and the \ref VECTOR macro. * * Time complexity: O(1). */ BASE FUNCTION(igraph_vector, e) (const TYPE(igraph_vector)* v, long int pos) { assert(v != NULL); assert(v->stor_begin != NULL); return * (v->stor_begin + pos); } /** * \ingroup vector * \function igraph_vector_e_ptr * \brief Get the address of an element of a vector * \param v The \type igraph_vector_t object. * \param pos The position of the element, the position of the first * element is zero. * \return Pointer to the desired element. * \sa \ref igraph_vector_e() and the \ref VECTOR macro. * * Time complexity: O(1). */ BASE* FUNCTION(igraph_vector, e_ptr) (const TYPE(igraph_vector)* v, long int pos) { assert(v != NULL); assert(v->stor_begin != NULL); return v->stor_begin + pos; } /** * \ingroup vector * \function igraph_vector_set * \brief Assignment to an element of a vector. * \param v The \type igraph_vector_t element. * \param pos Position of the element to set. * \param value New value of the element. * \sa \ref igraph_vector_e(). */ void FUNCTION(igraph_vector, set) (TYPE(igraph_vector)* v, long int pos, BASE value) { assert(v != NULL); assert(v->stor_begin != NULL); *(v->stor_begin + pos) = value; } /** * \ingroup vector * \function igraph_vector_null * \brief Sets each element in the vector to zero. * * * Note that \ref igraph_vector_init() sets the elements to zero as well, so * it makes no sense to call this function on a just initialized * vector. Thus if you want to construct a vector of zeros, then you should * use \ref igraph_vector_init(). * \param v The vector object. * * Time complexity: O(n), the size of * the vector. */ void FUNCTION(igraph_vector, null) (TYPE(igraph_vector)* v) { assert(v != NULL); assert(v->stor_begin != NULL); if (FUNCTION(igraph_vector, size)(v) > 0) { memset(v->stor_begin, 0, sizeof(BASE) * (size_t) FUNCTION(igraph_vector, size)(v)); } } /** * \function igraph_vector_fill * \brief Fill a vector with a constant element * * Sets each element of the vector to the supplied constant. * \param vector The vector to work on. * \param e The element to fill with. * * Time complexity: O(n), the size of the vector. */ void FUNCTION(igraph_vector, fill) (TYPE(igraph_vector)* v, BASE e) { BASE *ptr; assert(v != NULL); assert(v->stor_begin != NULL); for (ptr = v->stor_begin; ptr < v->end; ptr++) { *ptr = e; } } /** * \ingroup vector * \function igraph_vector_tail * \brief Returns the last element in a vector. * * * It is an error to call this function on an empty vector, the result * is undefined. * \param v The vector object. * \return The last element. * * Time complexity: O(1). */ BASE FUNCTION(igraph_vector, tail)(const TYPE(igraph_vector) *v) { assert(v != NULL); assert(v->stor_begin != NULL); return *((v->end) - 1); } /** * \ingroup vector * \function igraph_vector_pop_back * \brief Removes and returns the last element of a vector. * * * It is an error to call this function with an empty vector. * \param v The vector object. * \return The removed last element. * * Time complexity: O(1). */ BASE FUNCTION(igraph_vector, pop_back)(TYPE(igraph_vector)* v) { BASE tmp; assert(v != NULL); assert(v->stor_begin != NULL); assert(v->end != v->stor_begin); tmp = FUNCTION(igraph_vector, e)(v, FUNCTION(igraph_vector, size)(v) - 1); v->end -= 1; return tmp; } #ifndef NOTORDERED /** * \ingroup vector * \function igraph_vector_sort_cmp * \brief Internal comparison function of vector elements, used by * \ref igraph_vector_sort(). */ int FUNCTION(igraph_vector, sort_cmp)(const void *a, const void *b) { const BASE *da = (const BASE *) a; const BASE *db = (const BASE *) b; return (*da > *db) - (*da < *db); } /** * \ingroup vector * \function igraph_vector_sort * \brief Sorts the elements of the vector into ascending order. * * * This function uses the built-in sort function of the C library. * \param v Pointer to an initialized vector object. * * Time complexity: should be * O(nlogn) for * n * elements. */ void FUNCTION(igraph_vector, sort)(TYPE(igraph_vector) *v) { assert(v != NULL); assert(v->stor_begin != NULL); igraph_qsort(v->stor_begin, (size_t) FUNCTION(igraph_vector, size)(v), sizeof(BASE), FUNCTION(igraph_vector, sort_cmp)); } /** * Ascending comparison function passed to qsort from igraph_vector_qsort_ind */ int FUNCTION(igraph_vector, i_qsort_ind_cmp_asc)(const void *p1, const void *p2) { BASE **pa = (BASE **) p1; BASE **pb = (BASE **) p2; if ( **pa < **pb ) { return -1; } if ( **pa > **pb) { return 1; } return 0; } /** * Descending comparison function passed to qsort from igraph_vector_qsort_ind */ int FUNCTION(igraph_vector, i_qsort_ind_cmp_desc)(const void *p1, const void *p2) { BASE **pa = (BASE **) p1; BASE **pb = (BASE **) p2; if ( **pa < **pb ) { return 1; } if ( **pa > **pb) { return -1; } return 0; } /** * \function igraph_vector_qsort_ind * \brief Return a permutation of indices that sorts a vector * * Takes an unsorted array \c v as input and computes an array of * indices inds such that v[ inds[i] ], with i increasing from 0, is * an ordered array (either ascending or descending, depending on * \v order). The order of indices for identical elements is not * defined. * * \param v the array to be sorted * \param inds the output array of indices. this must be initialized, * but will be resized * \param descending whether the output array should be sorted in descending * order. * \return Error code. * * This routine uses the C library qsort routine. * Algorithm: 1) create an array of pointers to the elements of v. 2) * Pass this array to qsort. 3) after sorting the difference between * the pointer value and the first pointer value gives its original * position in the array. Use this to set the values of inds. * * Some tests show that this routine is faster than * igraph_vector_heapsort_ind by about 10 percent * for small vectors to a factor of two for large vectors. */ long int FUNCTION(igraph_vector, qsort_ind)(TYPE(igraph_vector) *v, igraph_vector_t *inds, igraph_bool_t descending) { long int i; BASE **vind, *first; size_t n = (size_t) FUNCTION(igraph_vector, size)(v); IGRAPH_CHECK(igraph_vector_resize(inds, (long) n)); if (n == 0) { return 0; } vind = igraph_Calloc(n, BASE*); if (vind == 0) { IGRAPH_ERROR("igraph_vector_qsort_ind failed", IGRAPH_ENOMEM); } for (i = 0; i < n; i++) { vind[i] = &VECTOR(*v)[i]; } first = vind[0]; if (descending) { igraph_qsort(vind, n, sizeof(BASE**), FUNCTION(igraph_vector, i_qsort_ind_cmp_desc)); } else { igraph_qsort(vind, n, sizeof(BASE**), FUNCTION(igraph_vector, i_qsort_ind_cmp_asc)); } for (i = 0; i < n; i++) { VECTOR(*inds)[i] = vind[i] - first; } igraph_Free(vind); return 0; } #endif /** * \ingroup vector * \function igraph_vector_resize * \brief Resize the vector. * * * Note that this function does not free any memory, just sets the * size of the vector to the given one. It can on the other hand * allocate more memory if the new size is larger than the previous * one. In this case the newly appeared elements in the vector are * \em not set to zero, they are uninitialized. * \param v The vector object * \param newsize The new size of the vector. * \return Error code, * \c IGRAPH_ENOMEM if there is not enough * memory. Note that this function \em never returns an error * if the vector is made smaller. * \sa \ref igraph_vector_reserve() for allocating memory for future * extensions of a vector. \ref igraph_vector_resize_min() for * deallocating the unnneded memory for a vector. * * Time complexity: O(1) if the new * size is smaller, operating system dependent if it is larger. In the * latter case it is usually around * O(n), * n is the new size of the vector. */ int FUNCTION(igraph_vector, resize)(TYPE(igraph_vector)* v, long int newsize) { assert(v != NULL); assert(v->stor_begin != NULL); IGRAPH_CHECK(FUNCTION(igraph_vector, reserve)(v, newsize)); v->end = v->stor_begin + newsize; return 0; } /** * \ingroup vector * \function igraph_vector_resize_min * \brief Deallocate the unused memory of a vector. * * * Note that this function involves additional memory allocation and * may result an out-of-memory error. * \param v Pointer to an initialized vector. * \return Error code. * * \sa \ref igraph_vector_resize(), \ref igraph_vector_reserve(). * * Time complexity: operating system dependent. */ int FUNCTION(igraph_vector, resize_min)(TYPE(igraph_vector)*v) { size_t size; BASE *tmp; if (v->stor_end == v->end) { return 0; } size = (size_t) (v->end - v->stor_begin); tmp = igraph_Realloc(v->stor_begin, size, BASE); if (tmp == 0) { IGRAPH_ERROR("cannot resize vector", IGRAPH_ENOMEM); } else { v->stor_begin = tmp; v->stor_end = v->end = v->stor_begin + size; } return 0; } #ifndef NOTORDERED /** * \ingroup vector * \function igraph_vector_max * \brief Gives the maximum element of the vector. * * * If the size of the vector is zero, an arbitrary number is * returned. * \param v The vector object. * \return The maximum element. * * Time complexity: O(n), * n is the size of the vector. */ BASE FUNCTION(igraph_vector, max)(const TYPE(igraph_vector)* v) { BASE max; BASE *ptr; assert(v != NULL); assert(v->stor_begin != NULL); max = *(v->stor_begin); ptr = v->stor_begin + 1; while (ptr < v->end) { if ((*ptr) > max) { max = *ptr; } ptr++; } return max; } /** * \ingroup vector * \function igraph_vector_which_max * \brief Gives the position of the maximum element of the vector. * * * If the size of the vector is zero, -1 is * returned. * \param v The vector object. * \return The position of the first maximum element. * * Time complexity: O(n), * n is the size of the vector. */ long int FUNCTION(igraph_vector, which_max)(const TYPE(igraph_vector)* v) { long int which = -1; if (!FUNCTION(igraph_vector, empty)(v)) { BASE max; BASE *ptr; long int pos; assert(v != NULL); assert(v->stor_begin != NULL); max = *(v->stor_begin); which = 0; ptr = v->stor_begin + 1; pos = 1; while (ptr < v->end) { if ((*ptr) > max) { max = *ptr; which = pos; } ptr++; pos++; } } return which; } /** * \function igraph_vector_min * \brief Smallest element of a vector. * * The vector must be non-empty. * \param v The input vector. * \return The smallest element of \p v. * * Time complexity: O(n), the number of elements. */ BASE FUNCTION(igraph_vector, min)(const TYPE(igraph_vector)* v) { BASE min; BASE *ptr; assert(v != NULL); assert(v->stor_begin != NULL); min = *(v->stor_begin); ptr = v->stor_begin + 1; while (ptr < v->end) { if ((*ptr) < min) { min = *ptr; } ptr++; } return min; } /** * \function igraph_vector_which_min * \brief Index of the smallest element. * * The vector must be non-empty. * If the smallest element is not unique, then the index of the first * is returned. * \param v The input vector. * \return Index of the smallest element. * * Time complexity: O(n), the number of elements. */ long int FUNCTION(igraph_vector, which_min)(const TYPE(igraph_vector)* v) { long int which = -1; if (!FUNCTION(igraph_vector, empty)(v)) { BASE min; BASE *ptr; long int pos; assert(v != NULL); assert(v->stor_begin != NULL); min = *(v->stor_begin); which = 0; ptr = v->stor_begin + 1; pos = 1; while (ptr < v->end) { if ((*ptr) < min) { min = *ptr; which = pos; } ptr++; pos++; } } return which; } #endif /** * \ingroup vector * \function igraph_vector_init_copy * \brief Initializes a vector from an ordinary C array (constructor). * * \param v Pointer to an uninitialized vector object. * \param data A regular C array. * \param length The length of the C array. * \return Error code: * \c IGRAPH_ENOMEM if there is not enough memory. * * Time complexity: operating system specific, usually * O(\p length). */ int FUNCTION(igraph_vector, init_copy)(TYPE(igraph_vector) *v, const BASE *data, long int length) { v->stor_begin = igraph_Calloc(length, BASE); if (v->stor_begin == 0) { IGRAPH_ERROR("cannot init vector from array", IGRAPH_ENOMEM); } v->stor_end = v->stor_begin + length; v->end = v->stor_end; memcpy(v->stor_begin, data, (size_t) length * sizeof(BASE)); return 0; } /** * \ingroup vector * \function igraph_vector_copy_to * \brief Copies the contents of a vector to a C array. * * * The C array should have sufficient length. * \param v The vector object. * \param to The C array. * * Time complexity: O(n), * n is the size of the vector. */ void FUNCTION(igraph_vector, copy_to)(const TYPE(igraph_vector) *v, BASE *to) { assert(v != NULL); assert(v->stor_begin != NULL); if (v->end != v->stor_begin) { memcpy(to, v->stor_begin, sizeof(BASE) * (size_t) (v->end - v->stor_begin)); } } /** * \ingroup vector * \function igraph_vector_copy * \brief Initializes a vector from another vector object (constructor). * * * The contents of the existing vector object will be copied to * the new one. * \param to Pointer to a not yet initialized vector object. * \param from The original vector object to copy. * \return Error code: * \c IGRAPH_ENOMEM if there is not enough memory. * * Time complexity: operating system dependent, usually * O(n), * n is the size of the vector. */ int FUNCTION(igraph_vector, copy)(TYPE(igraph_vector) *to, const TYPE(igraph_vector) *from) { assert(from != NULL); assert(from->stor_begin != NULL); to->stor_begin = igraph_Calloc(FUNCTION(igraph_vector, size)(from), BASE); if (to->stor_begin == 0) { IGRAPH_ERROR("cannot copy vector", IGRAPH_ENOMEM); } to->stor_end = to->stor_begin + FUNCTION(igraph_vector, size)(from); to->end = to->stor_end; memcpy(to->stor_begin, from->stor_begin, (size_t) FUNCTION(igraph_vector, size)(from) * sizeof(BASE)); return 0; } /** * \ingroup vector * \function igraph_vector_sum * \brief Calculates the sum of the elements in the vector. * * * For the empty vector 0.0 is returned. * \param v The vector object. * \return The sum of the elements. * * Time complexity: O(n), the size of * the vector. */ BASE FUNCTION(igraph_vector, sum)(const TYPE(igraph_vector) *v) { BASE res = ZERO; BASE *p; assert(v != NULL); assert(v->stor_begin != NULL); for (p = v->stor_begin; p < v->end; p++) { #ifdef SUM SUM(res, res, *p); #else res += *p; #endif } return res; } igraph_real_t FUNCTION(igraph_vector, sumsq)(const TYPE(igraph_vector) *v) { igraph_real_t res = 0.0; BASE *p; assert(v != NULL); assert(v->stor_begin != NULL); for (p = v->stor_begin; p < v->end; p++) { #ifdef SQ res += SQ(*p); #else res += (*p) * (*p); #endif } return res; } /** * \ingroup vector * \function igraph_vector_prod * \brief Calculates the product of the elements in the vector. * * * For the empty vector one (1) is returned. * \param v The vector object. * \return The product of the elements. * * Time complexity: O(n), the size of * the vector. */ BASE FUNCTION(igraph_vector, prod)(const TYPE(igraph_vector) *v) { BASE res = ONE; BASE *p; assert(v != NULL); assert(v->stor_begin != NULL); for (p = v->stor_begin; p < v->end; p++) { #ifdef PROD PROD(res, res, *p); #else res *= *p; #endif } return res; } /** * \ingroup vector * \function igraph_vector_cumsum * \brief Calculates the cumulative sum of the elements in the vector. * * * \param to An initialized vector object that will store the cumulative * sums. Element i of this vector will store the sum of the elements * of the 'from' vector, up to and including element i. * \param from The input vector. * \return Error code. * * Time complexity: O(n), the size of the vector. */ int FUNCTION(igraph_vector, cumsum)(TYPE(igraph_vector) *to, const TYPE(igraph_vector) *from) { BASE res = ZERO; BASE *p, *p2; assert(from != NULL); assert(from->stor_begin != NULL); assert(to != NULL); assert(to->stor_begin != NULL); IGRAPH_CHECK(FUNCTION(igraph_vector, resize)(to, FUNCTION(igraph_vector, size)(from))); for (p = from->stor_begin, p2 = to->stor_begin; p < from->end; p++, p2++) { #ifdef SUM SUM(res, res, *p); #else res += *p; #endif *p2 = res; } return 0; } #ifndef NOTORDERED /** * \ingroup vector * \function igraph_vector_init_seq * \brief Initializes a vector with a sequence. * * * The vector will contain the numbers \p from, * \p from+1, ..., \p to. * \param v Pointer to an uninitialized vector object. * \param from The lower limit in the sequence (inclusive). * \param to The upper limit in the sequence (inclusive). * \return Error code: * \c IGRAPH_ENOMEM: out of memory. * * Time complexity: O(n), the number * of elements in the vector. */ int FUNCTION(igraph_vector, init_seq)(TYPE(igraph_vector) *v, BASE from, BASE to) { BASE *p; IGRAPH_CHECK(FUNCTION(igraph_vector, init)(v, (long int) (to - from + 1))); for (p = v->stor_begin; p < v->end; p++) { *p = from++; } return 0; } #endif /** * \ingroup vector * \function igraph_vector_remove_section * \brief Deletes a section from a vector. * * * Note that this function does not do range checking. The result is * undefined if you supply invalid limits. * \param v The vector object. * \param from The position of the first element to remove. * \param to The position of the first element \em not to remove. * * Time complexity: O(n-from), * n is the number of elements in the * vector. */ void FUNCTION(igraph_vector, remove_section)(TYPE(igraph_vector) *v, long int from, long int to) { assert(v != NULL); assert(v->stor_begin != NULL); /* Not removing from the end? */ if (to < FUNCTION(igraph_vector, size)(v)) { memmove(v->stor_begin + from, v->stor_begin + to, sizeof(BASE) * (size_t) (v->end - v->stor_begin - to)); } v->end -= (to - from); } /** * \ingroup vector * \function igraph_vector_remove * \brief Removes a single element from a vector. * * Note that this function does not do range checking. * \param v The vector object. * \param elem The position of the element to remove. * * Time complexity: O(n-elem), * n is the number of elements in the * vector. */ void FUNCTION(igraph_vector, remove)(TYPE(igraph_vector) *v, long int elem) { assert(v != NULL); assert(v->stor_begin != NULL); FUNCTION(igraph_vector, remove_section)(v, elem, elem + 1); } /** * \ingroup vector * \function igraph_vector_move_interval * \brief Copies a section of a vector. * * * The result of this function is undefined if the source and target * intervals overlap. * \param v The vector object. * \param begin The position of the first element to move. * \param end The position of the first element \em not to move. * \param to The target position. * \return Error code, the current implementation always returns with * success. * * Time complexity: O(end-begin). */ int FUNCTION(igraph_vector, move_interval)(TYPE(igraph_vector) *v, long int begin, long int end, long int to) { assert(v != NULL); assert(v->stor_begin != NULL); memcpy(v->stor_begin + to, v->stor_begin + begin, sizeof(BASE) * (size_t) (end - begin)); return 0; } int FUNCTION(igraph_vector, move_interval2)(TYPE(igraph_vector) *v, long int begin, long int end, long int to) { assert(v != NULL); assert(v->stor_begin != NULL); memmove(v->stor_begin + to, v->stor_begin + begin, sizeof(BASE) * (size_t) (end - begin)); return 0; } /** * \ingroup vector * \function igraph_vector_permdelete * \brief Remove elements of a vector (for internal use). */ void FUNCTION(igraph_vector, permdelete)(TYPE(igraph_vector) *v, const igraph_vector_t *index, long int nremove) { long int i, n; assert(v != NULL); assert(v->stor_begin != NULL); n = FUNCTION(igraph_vector, size)(v); for (i = 0; i < n; i++) { if (VECTOR(*index)[i] != 0) { VECTOR(*v)[ (long int)VECTOR(*index)[i] - 1 ] = VECTOR(*v)[i]; } } v->end -= nremove; } #ifndef NOTORDERED /** * \ingroup vector * \function igraph_vector_isininterval * \brief Checks if all elements of a vector are in the given * interval. * * \param v The vector object. * \param low The lower limit of the interval (inclusive). * \param high The higher limit of the interval (inclusive). * \return True (positive integer) if all vector elements are in the * interval, false (zero) otherwise. * * Time complexity: O(n), the number * of elements in the vector. */ igraph_bool_t FUNCTION(igraph_vector, isininterval)(const TYPE(igraph_vector) *v, BASE low, BASE high) { BASE *ptr; assert(v != NULL); assert(v->stor_begin != NULL); for (ptr = v->stor_begin; ptr < v->end; ptr++) { if (*ptr < low || *ptr > high) { return 0; } } return 1; } /** * \ingroup vector * \function igraph_vector_any_smaller * \brief Checks if any element of a vector is smaller than a limit. * * \param v The \type igraph_vector_t object. * \param limit The limit. * \return True (positive integer) if the vector contains at least one * smaller element than \p limit, false (zero) * otherwise. * * Time complexity: O(n), the number * of elements in the vector. */ igraph_bool_t FUNCTION(igraph_vector, any_smaller)(const TYPE(igraph_vector) *v, BASE limit) { BASE *ptr; assert(v != NULL); assert(v->stor_begin != NULL); for (ptr = v->stor_begin; ptr < v->end; ptr++) { if (*ptr < limit) { return 1; } } return 0; } #endif /** * \ingroup vector * \function igraph_vector_all_e * \brief Are all elements equal? * * \param lhs The first vector. * \param rhs The second vector. * \return Positive integer (=true) if the elements in the \p lhs are all * equal to the corresponding elements in \p rhs. Returns \c 0 * (=false) if the lengths of the vectors don't match. * * Time complexity: O(n), the length of the vectors. */ igraph_bool_t FUNCTION(igraph_vector, all_e)(const TYPE(igraph_vector) *lhs, const TYPE(igraph_vector) *rhs) { long int i, s; assert(lhs != 0); assert(rhs != 0); assert(lhs->stor_begin != 0); assert(rhs->stor_begin != 0); s = FUNCTION(igraph_vector, size)(lhs); if (s != FUNCTION(igraph_vector, size)(rhs)) { return 0; } else { for (i = 0; i < s; i++) { BASE l = VECTOR(*lhs)[i]; BASE r = VECTOR(*rhs)[i]; #ifdef EQ if (!EQ(l, r)) { #else if (l != r) { #endif return 0; } } return 1; } } igraph_bool_t FUNCTION(igraph_vector, is_equal)(const TYPE(igraph_vector) *lhs, const TYPE(igraph_vector) *rhs) { return FUNCTION(igraph_vector, all_e)(lhs, rhs); } #ifndef NOTORDERED /** * \ingroup vector * \function igraph_vector_all_l * \brief Are all elements less? * * \param lhs The first vector. * \param rhs The second vector. * \return Positive integer (=true) if the elements in the \p lhs are all * less than the corresponding elements in \p rhs. Returns \c 0 * (=false) if the lengths of the vectors don't match. * * Time complexity: O(n), the length of the vectors. */ igraph_bool_t FUNCTION(igraph_vector, all_l)(const TYPE(igraph_vector) *lhs, const TYPE(igraph_vector) *rhs) { long int i, s; assert(lhs != 0); assert(rhs != 0); assert(lhs->stor_begin != 0); assert(rhs->stor_begin != 0); s = FUNCTION(igraph_vector, size)(lhs); if (s != FUNCTION(igraph_vector, size)(rhs)) { return 0; } else { for (i = 0; i < s; i++) { BASE l = VECTOR(*lhs)[i]; BASE r = VECTOR(*rhs)[i]; if (l >= r) { return 0; } } return 1; } } /** * \ingroup vector * \function igraph_vector_all_g * \brief Are all elements greater? * * \param lhs The first vector. * \param rhs The second vector. * \return Positive integer (=true) if the elements in the \p lhs are all * greater than the corresponding elements in \p rhs. Returns \c 0 * (=false) if the lengths of the vectors don't match. * * Time complexity: O(n), the length of the vectors. */ igraph_bool_t FUNCTION(igraph_vector, all_g)(const TYPE(igraph_vector) *lhs, const TYPE(igraph_vector) *rhs) { long int i, s; assert(lhs != 0); assert(rhs != 0); assert(lhs->stor_begin != 0); assert(rhs->stor_begin != 0); s = FUNCTION(igraph_vector, size)(lhs); if (s != FUNCTION(igraph_vector, size)(rhs)) { return 0; } else { for (i = 0; i < s; i++) { BASE l = VECTOR(*lhs)[i]; BASE r = VECTOR(*rhs)[i]; if (l <= r) { return 0; } } return 1; } } /** * \ingroup vector * \function igraph_vector_all_le * \brief Are all elements less or equal? * * \param lhs The first vector. * \param rhs The second vector. * \return Positive integer (=true) if the elements in the \p lhs are all * less than or equal to the corresponding elements in \p * rhs. Returns \c 0 (=false) if the lengths of the vectors don't * match. * * Time complexity: O(n), the length of the vectors. */ igraph_bool_t FUNCTION(igraph_vector, all_le)(const TYPE(igraph_vector) *lhs, const TYPE(igraph_vector) *rhs) { long int i, s; assert(lhs != 0); assert(rhs != 0); assert(lhs->stor_begin != 0); assert(rhs->stor_begin != 0); s = FUNCTION(igraph_vector, size)(lhs); if (s != FUNCTION(igraph_vector, size)(rhs)) { return 0; } else { for (i = 0; i < s; i++) { BASE l = VECTOR(*lhs)[i]; BASE r = VECTOR(*rhs)[i]; if (l > r) { return 0; } } return 1; } } /** * \ingroup vector * \function igraph_vector_all_ge * \brief Are all elements greater or equal? * * \param lhs The first vector. * \param rhs The second vector. * \return Positive integer (=true) if the elements in the \p lhs are all * greater than or equal to the corresponding elements in \p * rhs. Returns \c 0 (=false) if the lengths of the vectors don't * match. * * Time complexity: O(n), the length of the vectors. */ igraph_bool_t FUNCTION(igraph_vector, all_ge)(const TYPE(igraph_vector) *lhs, const TYPE(igraph_vector) *rhs) { long int i, s; assert(lhs != 0); assert(rhs != 0); assert(lhs->stor_begin != 0); assert(rhs->stor_begin != 0); s = FUNCTION(igraph_vector, size)(lhs); if (s != FUNCTION(igraph_vector, size)(rhs)) { return 0; } else { for (i = 0; i < s; i++) { BASE l = VECTOR(*lhs)[i]; BASE r = VECTOR(*rhs)[i]; if (l < r) { return 0; } } return 1; } } #endif igraph_bool_t FUNCTION(igraph_i_vector, binsearch_slice)(const TYPE(igraph_vector) *v, BASE what, long int *pos, long int start, long int end); #ifndef NOTORDERED /** * \ingroup vector * \function igraph_vector_binsearch * \brief Finds an element by binary searching a sorted vector. * * * It is assumed that the vector is sorted. If the specified element * (\p what) is not in the vector, then the * position of where it should be inserted (to keep the vector sorted) * is returned. * \param v The \type igraph_vector_t object. * \param what The element to search for. * \param pos Pointer to a \type long int. This is set to the * position of an instance of \p what in the * vector if it is present. If \p v does not * contain \p what then * \p pos is set to the position to which it * should be inserted (to keep the the vector sorted of course). * \return Positive integer (true) if \p what is * found in the vector, zero (false) otherwise. * * Time complexity: O(log(n)), * n is the number of elements in * \p v. */ igraph_bool_t FUNCTION(igraph_vector, binsearch)(const TYPE(igraph_vector) *v, BASE what, long int *pos) { return FUNCTION(igraph_i_vector, binsearch_slice)(v, what, pos, 0, FUNCTION(igraph_vector, size)(v)); } igraph_bool_t FUNCTION(igraph_i_vector, binsearch_slice)(const TYPE(igraph_vector) *v, BASE what, long int *pos, long int start, long int end) { long int left = start; long int right = end - 1; while (left <= right) { /* (right + left) / 2 could theoretically overflow for long vectors */ long int middle = left + ((right - left) >> 1); if (VECTOR(*v)[middle] > what) { right = middle - 1; } else if (VECTOR(*v)[middle] < what) { left = middle + 1; } else { if (pos != 0) { *pos = middle; } return 1; } } /* if we are here, the element was not found */ if (pos != 0) { *pos = left; } return 0; } /** * \ingroup vector * \function igraph_vector_binsearch2 * \brief Binary search, without returning the index. * * * It is assumed that the vector is sorted. * \param v The \type igraph_vector_t object. * \param what The element to search for. * \return Positive integer (true) if \p what is * found in the vector, zero (false) otherwise. * * Time complexity: O(log(n)), * n is the number of elements in * \p v. */ igraph_bool_t FUNCTION(igraph_vector, binsearch2)(const TYPE(igraph_vector) *v, BASE what) { long int left = 0; long int right = FUNCTION(igraph_vector, size)(v) - 1; while (left <= right) { /* (right + left) / 2 could theoretically overflow for long vectors */ long int middle = left + ((right - left) >> 1); if (what < VECTOR(*v)[middle]) { right = middle - 1; } else if (what > VECTOR(*v)[middle]) { left = middle + 1; } else { return 1; } } return 0; } #endif /** * \function igraph_vector_scale * \brief Multiply all elements of a vector by a constant * * \param v The vector. * \param by The constant. * \return Error code. The current implementation always returns with success. * * Added in version 0.2. * * Time complexity: O(n), the number of elements in a vector. */ void FUNCTION(igraph_vector, scale)(TYPE(igraph_vector) *v, BASE by) { long int i; for (i = 0; i < FUNCTION(igraph_vector, size)(v); i++) { #ifdef PROD PROD(VECTOR(*v)[i], VECTOR(*v)[i], by); #else VECTOR(*v)[i] *= by; #endif } } /** * \function igraph_vector_add_constant * \brief Add a constant to the vector. * * \p plus is added to every element of \p v. Note that overflow * might happen. * \param v The input vector. * \param plus The constant to add. * * Time complexity: O(n), the number of elements. */ void FUNCTION(igraph_vector, add_constant)(TYPE(igraph_vector) *v, BASE plus) { long int i, n = FUNCTION(igraph_vector, size)(v); for (i = 0; i < n; i++) { #ifdef SUM SUM(VECTOR(*v)[i], VECTOR(*v)[i], plus); #else VECTOR(*v)[i] += plus; #endif } } /** * \function igraph_vector_contains * \brief Linear search in a vector. * * Check whether the supplied element is included in the vector, by * linear search. * \param v The input vector. * \param e The element to look for. * \return \c TRUE if the element is found and \c FALSE otherwise. * * Time complexity: O(n), the length of the vector. */ igraph_bool_t FUNCTION(igraph_vector, contains)(const TYPE(igraph_vector) *v, BASE e) { BASE *p = v->stor_begin; while (p < v->end) { #ifdef EQ if (EQ(*p, e)) { #else if (*p == e) { #endif return 1; } p++; } return 0; } /** * \function igraph_vector_search * \brief Search from a given position * * The supplied element \p what is searched in vector \p v, starting * from element index \p from. If found then the index of the first * instance (after \p from) is stored in \p pos. * \param v The input vector. * \param from The index to start searching from. No range checking is * performed. * \param what The element to find. * \param pos If not \c NULL then the index of the found element is * stored here. * \return Boolean, \c TRUE if the element was found, \c FALSE * otherwise. * * Time complexity: O(m), the number of elements to search, the length * of the vector minus the \p from argument. */ igraph_bool_t FUNCTION(igraph_vector, search)(const TYPE(igraph_vector) *v, long int from, BASE what, long int *pos) { long int i, n = FUNCTION(igraph_vector, size)(v); for (i = from; i < n; i++) { #ifdef EQ if (EQ(VECTOR(*v)[i], what)) { break; } #else if (VECTOR(*v)[i] == what) { break; } #endif } if (i < n) { if (pos != 0) { *pos = i; } return 1; } else { return 0; } } #ifndef NOTORDERED /** * \function igraph_vector_filter_smaller * \ingroup internal */ int FUNCTION(igraph_vector, filter_smaller)(TYPE(igraph_vector) *v, BASE elem) { long int i = 0, n = FUNCTION(igraph_vector, size)(v); long int s; while (i < n && VECTOR(*v)[i] < elem) { i++; } s = i; while (s < n && VECTOR(*v)[s] == elem) { s++; } FUNCTION(igraph_vector, remove_section)(v, 0, i + (s - i) / 2); return 0; } #endif /** * \function igraph_vector_append * \brief Append a vector to another one. * * The target vector will be resized (except \p from is empty). * \param to The vector to append to. * \param from The vector to append, it is kept unchanged. * \return Error code. * * Time complexity: O(n), the number of elements in the new vector. */ int FUNCTION(igraph_vector, append)(TYPE(igraph_vector) *to, const TYPE(igraph_vector) *from) { long tosize, fromsize; tosize = FUNCTION(igraph_vector, size)(to); fromsize = FUNCTION(igraph_vector, size)(from); IGRAPH_CHECK(FUNCTION(igraph_vector, resize)(to, tosize + fromsize)); memcpy(to->stor_begin + tosize, from->stor_begin, sizeof(BASE) * (size_t) fromsize); to->end = to->stor_begin + tosize + fromsize; return 0; } /** * \function igraph_vector_get_interval */ int FUNCTION(igraph_vector, get_interval)(const TYPE(igraph_vector) *v, TYPE(igraph_vector) *res, long int from, long int to) { IGRAPH_CHECK(FUNCTION(igraph_vector, resize)(res, to - from)); memcpy(res->stor_begin, v->stor_begin + from, (size_t) (to - from) * sizeof(BASE)); return 0; } #ifndef NOTORDERED /** * \function igraph_vector_maxdifference * \brief The maximum absolute difference of \p m1 and \p m2 * * The element with the largest absolute value in \p m1 - \p m2 is * returned. Both vectors must be non-empty, but they not need to have * the same length, the extra elements in the longer vector are ignored. * \param m1 The first vector. * \param m2 The second vector. * \return The maximum absolute difference of \p m1 and \p m2. * * Time complexity: O(n), the number of elements in the shorter * vector. */ igraph_real_t FUNCTION(igraph_vector, maxdifference)(const TYPE(igraph_vector) *m1, const TYPE(igraph_vector) *m2) { long int n1 = FUNCTION(igraph_vector, size)(m1); long int n2 = FUNCTION(igraph_vector, size)(m2); long int n = n1 < n2 ? n1 : n2; long int i; igraph_real_t diff = 0.0; for (i = 0; i < n; i++) { igraph_real_t d = fabs((igraph_real_t)(VECTOR(*m1)[i]) - (igraph_real_t)(VECTOR(*m2)[i])); if (d > diff) { diff = d; } } return diff; } #endif /** * \function igraph_vector_update * \brief Update a vector from another one. * * After this operation the contents of \p to will be exactly the same * \p from. \p to will be resized if it was originally shorter or * longer than \p from. * \param to The vector to update. * \param from The vector to update from. * \return Error code. * * Time complexity: O(n), the number of elements in \p from. */ int FUNCTION(igraph_vector, update)(TYPE(igraph_vector) *to, const TYPE(igraph_vector) *from) { size_t n = (size_t) FUNCTION(igraph_vector, size)(from); FUNCTION(igraph_vector, resize)(to, (long) n); memcpy(to->stor_begin, from->stor_begin, sizeof(BASE)*n); return 0; } /** * \function igraph_vector_swap * \brief Swap elements of two vectors. * * The two vectors must have the same length, otherwise an error * happens. * \param v1 The first vector. * \param v2 The second vector. * \return Error code. * * Time complexity: O(n), the length of the vectors. */ int FUNCTION(igraph_vector, swap)(TYPE(igraph_vector) *v1, TYPE(igraph_vector) *v2) { long int i, n1 = FUNCTION(igraph_vector, size)(v1); long int n2 = FUNCTION(igraph_vector, size)(v2); if (n1 != n2) { IGRAPH_ERROR("Vectors must have the same number of elements for swapping", IGRAPH_EINVAL); } for (i = 0; i < n1; i++) { BASE tmp; tmp = VECTOR(*v1)[i]; VECTOR(*v1)[i] = VECTOR(*v2)[i]; VECTOR(*v2)[i] = tmp; } return 0; } /** * \function igraph_vector_swap_elements * \brief Swap two elements in a vector. * * Note that currently no range checking is performed. * \param v The input vector. * \param i Index of the first element. * \param j index of the second element. (Might be the same as the * first.) * \return Error code, currently always \c IGRAPH_SUCCESS. * * Time complexity: O(1). */ int FUNCTION(igraph_vector, swap_elements)(TYPE(igraph_vector) *v, long int i, long int j) { BASE tmp = VECTOR(*v)[i]; VECTOR(*v)[i] = VECTOR(*v)[j]; VECTOR(*v)[j] = tmp; return 0; } /** * \function igraph_vector_reverse * \brief Reverse the elements of a vector. * * The first element will be last, the last element will be * first, etc. * \param v The input vector. * \return Error code, currently always \c IGRAPH_SUCCESS. * * Time complexity: O(n), the number of elements. */ int FUNCTION(igraph_vector, reverse)(TYPE(igraph_vector) *v) { long int n = FUNCTION(igraph_vector, size)(v), n2 = n / 2; long int i, j; for (i = 0, j = n - 1; i < n2; i++, j--) { BASE tmp; tmp = VECTOR(*v)[i]; VECTOR(*v)[i] = VECTOR(*v)[j]; VECTOR(*v)[j] = tmp; } return 0; } /** * \ingroup vector * \function igraph_vector_shuffle * \brief Shuffles a vector in-place using the Fisher-Yates method * * * The Fisher-Yates shuffle ensures that every implementation is * equally probable when using a proper randomness source. Of course * this does not apply to pseudo-random generators as the cycle of * these generators is less than the number of possible permutations * of the vector if the vector is long enough. * \param v The vector object. * \return Error code, currently always \c IGRAPH_SUCCESS. * * Time complexity: O(n), * n is the number of elements in the * vector. * * * References: * \clist * \cli (Fisher & Yates 1963) * R. A. Fisher and F. Yates. \emb Statistical Tables for Biological, * Agricultural and Medical Research. \eme Oliver and Boyd, 6th edition, * 1963, page 37. * \cli (Knuth 1998) * D. E. Knuth. \emb Seminumerical Algorithms, \eme volume 2 of \emb The Art * of Computer Programming. \eme Addison-Wesley, 3rd edition, 1998, page 145. * \endclist * * \example examples/simple/igraph_fisher_yates_shuffle.c */ int FUNCTION(igraph_vector, shuffle)(TYPE(igraph_vector) *v) { long int n = FUNCTION(igraph_vector, size)(v); long int k; BASE dummy; RNG_BEGIN(); while (n > 1) { k = RNG_INTEGER(0, n - 1); n--; dummy = VECTOR(*v)[n]; VECTOR(*v)[n] = VECTOR(*v)[k]; VECTOR(*v)[k] = dummy; } RNG_END(); return IGRAPH_SUCCESS; } /** * \function igraph_vector_add * \brief Add two vectors. * * Add the elements of \p v2 to \p v1, the result is stored in \p * v1. The two vectors must have the same length. * \param v1 The first vector, the result will be stored here. * \param v2 The second vector, its contents will be unchanged. * \return Error code. * * Time complexity: O(n), the number of elements. */ int FUNCTION(igraph_vector, add)(TYPE(igraph_vector) *v1, const TYPE(igraph_vector) *v2) { long int n1 = FUNCTION(igraph_vector, size)(v1); long int n2 = FUNCTION(igraph_vector, size)(v2); long int i; if (n1 != n2) { IGRAPH_ERROR("Vectors must have the same number of elements for swapping", IGRAPH_EINVAL); } for (i = 0; i < n1; i++) { #ifdef SUM SUM(VECTOR(*v1)[i], VECTOR(*v1)[i], VECTOR(*v2)[i]); #else VECTOR(*v1)[i] += VECTOR(*v2)[i]; #endif } return 0; } /** * \function igraph_vector_sub * \brief Subtract a vector from another one. * * Subtract the elements of \p v2 from \p v1, the result is stored in * \p v1. The two vectors must have the same length. * \param v1 The first vector, to subtract from. The result is stored * here. * \param v2 The vector to subtract, it will be unchanged. * \return Error code. * * Time complexity: O(n), the length of the vectors. */ int FUNCTION(igraph_vector, sub)(TYPE(igraph_vector) *v1, const TYPE(igraph_vector) *v2) { long int n1 = FUNCTION(igraph_vector, size)(v1); long int n2 = FUNCTION(igraph_vector, size)(v2); long int i; if (n1 != n2) { IGRAPH_ERROR("Vectors must have the same number of elements for swapping", IGRAPH_EINVAL); } for (i = 0; i < n1; i++) { #ifdef DIFF DIFF(VECTOR(*v1)[i], VECTOR(*v1)[i], VECTOR(*v2)[i]); #else VECTOR(*v1)[i] -= VECTOR(*v2)[i]; #endif } return 0; } /** * \function igraph_vector_mul * \brief Multiply two vectors. * * \p v1 will be multiplied by \p v2, elementwise. The two vectors * must have the same length. * \param v1 The first vector, the result will be stored here. * \param v2 The second vector, it is left unchanged. * \return Error code. * * Time complexity: O(n), the number of elements. */ int FUNCTION(igraph_vector, mul)(TYPE(igraph_vector) *v1, const TYPE(igraph_vector) *v2) { long int n1 = FUNCTION(igraph_vector, size)(v1); long int n2 = FUNCTION(igraph_vector, size)(v2); long int i; if (n1 != n2) { IGRAPH_ERROR("Vectors must have the same number of elements for swapping", IGRAPH_EINVAL); } for (i = 0; i < n1; i++) { #ifdef PROD PROD(VECTOR(*v1)[i], VECTOR(*v1)[i], VECTOR(*v2)[i]); #else VECTOR(*v1)[i] *= VECTOR(*v2)[i]; #endif } return 0; } /** * \function igraph_vector_div * \brief Divide a vector by another one. * * \p v1 is divided by \p v2, elementwise. They must have the same length. If the * base type of the vector can generate divide by zero errors then * please make sure that \p v2 contains no zero if you want to avoid * trouble. * \param v1 The dividend. The result is also stored here. * \param v2 The divisor, it is left unchanged. * \return Error code. * * Time complexity: O(n), the length of the vectors. */ int FUNCTION(igraph_vector, div)(TYPE(igraph_vector) *v1, const TYPE(igraph_vector) *v2) { long int n1 = FUNCTION(igraph_vector, size)(v1); long int n2 = FUNCTION(igraph_vector, size)(v2); long int i; if (n1 != n2) { IGRAPH_ERROR("Vectors must have the same number of elements for swapping", IGRAPH_EINVAL); } for (i = 0; i < n1; i++) { #ifdef DIV DIV(VECTOR(*v1)[i], VECTOR(*v1)[i], VECTOR(*v2)[i]); #else VECTOR(*v1)[i] /= VECTOR(*v2)[i]; #endif } return 0; } #ifndef NOABS int FUNCTION(igraph_vector, abs)(TYPE(igraph_vector) *v) { #ifdef UNSIGNED /* Nothing do to, unsigned type */ #else long int i, n = FUNCTION(igraph_vector, size)(v); for (i = 0; i < n; i++) { VECTOR(*v)[i] = VECTOR(*v)[i] >= 0 ? VECTOR(*v)[i] : -VECTOR(*v)[i]; } #endif return 0; } #endif #ifndef NOTORDERED /** * \function igraph_vector_minmax * \brief Minimum and maximum elements of a vector. * * Handy if you want to have both the smallest and largest element of * a vector. The vector is only traversed once. The vector must by non-empty. * \param v The input vector. It must contain at least one element. * \param min Pointer to a base type variable, the minimum is stored * here. * \param max Pointer to a base type variable, the maximum is stored * here. * \return Error code. * * Time complexity: O(n), the number of elements. */ int FUNCTION(igraph_vector, minmax)(const TYPE(igraph_vector) *v, BASE *min, BASE *max) { long int n = FUNCTION(igraph_vector, size)(v); long int i; *min = *max = VECTOR(*v)[0]; for (i = 1; i < n; i++) { BASE tmp = VECTOR(*v)[i]; if (tmp > *max) { *max = tmp; } else if (tmp < *min) { *min = tmp; } } return 0; } /** * \function igraph_vector_which_minmax * \brief Index of the minimum and maximum elements * * Handy if you need the indices of the smallest and largest * elements. The vector is traversed only once. The vector must to * non-empty. * \param v The input vector. It must contain at least one element. * \param which_min The index of the minimum element will be stored * here. * \param which_max The index of the maximum element will be stored * here. * \return Error code. * * Time complexity: O(n), the number of elements. */ int FUNCTION(igraph_vector, which_minmax)(const TYPE(igraph_vector) *v, long int *which_min, long int *which_max) { long int n = FUNCTION(igraph_vector, size)(v); long int i; BASE min, max; *which_min = *which_max = 0; min = max = VECTOR(*v)[0]; for (i = 1; i < n; i++) { BASE tmp = VECTOR(*v)[i]; if (tmp > max) { max = tmp; *which_max = i; } else if (tmp < min) { min = tmp; *which_min = i; } } return 0; } #endif /** * \function igraph_vector_isnull * \brief Are all elements zero? * * Checks whether all elements of a vector are zero. * \param v The input vector * \return Boolean, \c TRUE if the vector contains only zeros, \c * FALSE otherwise. * * Time complexity: O(n), the number of elements. */ igraph_bool_t FUNCTION(igraph_vector, isnull)(const TYPE(igraph_vector) *v) { long int n = FUNCTION(igraph_vector, size)(v); long int i = 0; #ifdef EQ while (i < n && EQ(VECTOR(*v)[i], ZERO)) { #else while (i < n && VECTOR(*v)[i] == ZERO) { #endif i++; } return i == n; } #ifndef NOTORDERED int FUNCTION(igraph_i_vector, intersect_sorted)( const TYPE(igraph_vector) *v1, long int begin1, long int end1, const TYPE(igraph_vector) *v2, long int begin2, long int end2, TYPE(igraph_vector) *result); /** * \function igraph_vector_intersect_sorted * \brief Calculates the intersection of two sorted vectors * * The elements that are contained in both vectors are stored in the result * vector. All three vectors must be initialized. * * * Instead of the naive intersection which takes O(n), this function uses * the set intersection method of Ricardo Baeza-Yates, which is more efficient * when one of the vectors is significantly smaller than the other, and * gives similar performance on average when the two vectors are equal. * * * The algorithm keeps the multiplicities of the elements: if an element appears * k1 times in the first vector and k2 times in the second, the result * will include that element min(k1, k2) times. * * * Reference: Baeza-Yates R: A fast set intersection algorithm for sorted * sequences. In: Lecture Notes in Computer Science, vol. 3109/2004, pp. * 400--408, 2004. Springer Berlin/Heidelberg. ISBN: 978-3-540-22341-2. * * \param v1 the first vector * \param v2 the second vector * \param result the result vector, which will also be sorted. * * Time complexity: O(m log(n)) where m is the size of the smaller vector * and n is the size of the larger one. */ int FUNCTION(igraph_vector, intersect_sorted)(const TYPE(igraph_vector) *v1, const TYPE(igraph_vector) *v2, TYPE(igraph_vector) *result) { long int size1, size2; size1 = FUNCTION(igraph_vector, size)(v1); size2 = FUNCTION(igraph_vector, size)(v2); FUNCTION(igraph_vector, clear)(result); if (size1 == 0 || size2 == 0) { return 0; } IGRAPH_CHECK(FUNCTION(igraph_i_vector, intersect_sorted)( v1, 0, size1, v2, 0, size2, result)); return 0; } int FUNCTION(igraph_i_vector, intersect_sorted)( const TYPE(igraph_vector) *v1, long int begin1, long int end1, const TYPE(igraph_vector) *v2, long int begin2, long int end2, TYPE(igraph_vector) *result) { long int size1, size2, probe1, probe2; if (begin1 == end1 || begin2 == end2) { return 0; } size1 = end1 - begin1; size2 = end2 - begin2; if (size1 < size2) { probe1 = begin1 + (size1 >> 1); /* pick the median element */ FUNCTION(igraph_i_vector, binsearch_slice)(v2, VECTOR(*v1)[probe1], &probe2, begin2, end2); IGRAPH_CHECK(FUNCTION(igraph_i_vector, intersect_sorted)( v1, begin1, probe1, v2, begin2, probe2, result )); if (!(probe2 == end2 || VECTOR(*v1)[probe1] < VECTOR(*v2)[probe2])) { IGRAPH_CHECK(FUNCTION(igraph_vector, push_back)(result, VECTOR(*v2)[probe2])); probe2++; } IGRAPH_CHECK(FUNCTION(igraph_i_vector, intersect_sorted)( v1, probe1 + 1, end1, v2, probe2, end2, result )); } else { probe2 = begin2 + (size2 >> 1); /* pick the median element */ FUNCTION(igraph_i_vector, binsearch_slice)(v1, VECTOR(*v2)[probe2], &probe1, begin1, end1); IGRAPH_CHECK(FUNCTION(igraph_i_vector, intersect_sorted)( v1, begin1, probe1, v2, begin2, probe2, result )); if (!(probe1 == end1 || VECTOR(*v2)[probe2] < VECTOR(*v1)[probe1])) { IGRAPH_CHECK(FUNCTION(igraph_vector, push_back)(result, VECTOR(*v2)[probe2])); probe1++; } IGRAPH_CHECK(FUNCTION(igraph_i_vector, intersect_sorted)( v1, probe1, end1, v2, probe2 + 1, end2, result )); } return 0; } /** * \function igraph_vector_difference_sorted * \brief Calculates the difference between two sorted vectors (considered as sets) * * The elements that are contained in only the first vector but not the second are * stored in the result vector. All three vectors must be initialized. * * \param v1 the first vector * \param v2 the second vector * \param result the result vector */ int FUNCTION(igraph_vector, difference_sorted)(const TYPE(igraph_vector) *v1, const TYPE(igraph_vector) *v2, TYPE(igraph_vector) *result) { long int i, j, i0, j0; i0 = FUNCTION(igraph_vector, size)(v1); j0 = FUNCTION(igraph_vector, size)(v2); i = j = 0; if (i0 == 0) { /* v1 is empty, this is easy */ FUNCTION(igraph_vector, clear)(result); return IGRAPH_SUCCESS; } if (j0 == 0) { /* v2 is empty, this is easy */ IGRAPH_CHECK(FUNCTION(igraph_vector, resize)(result, i0)); memcpy(result->stor_begin, v1->stor_begin, sizeof(BASE) * (size_t) i0); return IGRAPH_SUCCESS; } FUNCTION(igraph_vector, clear)(result); /* Copy the part of v1 that is less than the first element of v2 */ while (i < i0 && VECTOR(*v1)[i] < VECTOR(*v2)[j]) { i++; } if (i > 0) { IGRAPH_CHECK(FUNCTION(igraph_vector, resize)(result, i)); memcpy(result->stor_begin, v1->stor_begin, sizeof(BASE) * (size_t) i); } while (i < i0 && j < j0) { BASE element = VECTOR(*v1)[i]; if (element == VECTOR(*v2)[j]) { i++; j++; while (i < i0 && VECTOR(*v1)[i] == element) { i++; } while (j < j0 && VECTOR(*v2)[j] == element) { j++; } } else if (element < VECTOR(*v2)[j]) { IGRAPH_CHECK(FUNCTION(igraph_vector, push_back)(result, element)); i++; } else { j++; } } if (i < i0) { long int oldsize = FUNCTION(igraph_vector, size)(result); IGRAPH_CHECK(FUNCTION(igraph_vector, resize)(result, oldsize + i0 - i)); memcpy(result->stor_begin + oldsize, v1->stor_begin + i, sizeof(BASE) * (size_t) (i0 - i)); } return 0; } #endif #if defined(OUT_FORMAT) #ifndef USING_R int FUNCTION(igraph_vector, print)(const TYPE(igraph_vector) *v) { long int i, n = FUNCTION(igraph_vector, size)(v); if (n != 0) { #ifdef PRINTFUNC PRINTFUNC(VECTOR(*v)[0]); #else printf(OUT_FORMAT, VECTOR(*v)[0]); #endif } for (i = 1; i < n; i++) { #ifdef PRINTFUNC putchar(' '); PRINTFUNC(VECTOR(*v)[i]); #else printf(" " OUT_FORMAT, VECTOR(*v)[i]); #endif } printf("\n"); return 0; } int FUNCTION(igraph_vector, printf)(const TYPE(igraph_vector) *v, const char *format) { long int i, n = FUNCTION(igraph_vector, size)(v); if (n != 0) { printf(format, VECTOR(*v)[0]); } for (i = 1; i < n; i++) { putchar(' '); printf(format, VECTOR(*v)[i]); } printf("\n"); return 0; } #endif int FUNCTION(igraph_vector, fprint)(const TYPE(igraph_vector) *v, FILE *file) { long int i, n = FUNCTION(igraph_vector, size)(v); if (n != 0) { #ifdef FPRINTFUNC FPRINTFUNC(file, VECTOR(*v)[0]); #else fprintf(file, OUT_FORMAT, VECTOR(*v)[0]); #endif } for (i = 1; i < n; i++) { #ifdef FPRINTFUNC fputc(' ', file); FPRINTFUNC(file, VECTOR(*v)[i]); #else fprintf(file, " " OUT_FORMAT, VECTOR(*v)[i]); #endif } fprintf(file, "\n"); return 0; } #endif int FUNCTION(igraph_vector, index)(const TYPE(igraph_vector) *v, TYPE(igraph_vector) *newv, const igraph_vector_t *idx) { long int i, newlen = igraph_vector_size(idx); IGRAPH_CHECK(FUNCTION(igraph_vector, resize)(newv, newlen)); for (i = 0; i < newlen; i++) { long int j = (long int) VECTOR(*idx)[i]; VECTOR(*newv)[i] = VECTOR(*v)[j]; } return 0; } int FUNCTION(igraph_vector, index_int)(TYPE(igraph_vector) *v, const igraph_vector_int_t *idx) { BASE *tmp; int i, n = igraph_vector_int_size(idx); tmp = igraph_Calloc(n, BASE); if (!tmp) { IGRAPH_ERROR("Cannot index vector", IGRAPH_ENOMEM); } for (i = 0; i < n; i++) { tmp[i] = VECTOR(*v)[ VECTOR(*idx)[i] ]; } igraph_Free(v->stor_begin); v->stor_begin = tmp; v->stor_end = v->end = tmp + n; return 0; } python-igraph-0.8.0/vendor/source/igraph/src/cs/0000755000076500000240000000000013617375001022006 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_load.c0000644000076500000240000000304613524616145023565 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* load a triplet matrix from a file */ cs *cs_load (FILE *f) { CS_INT i, j ; double x ; #ifdef CS_COMPLEX double xi ; #endif cs *T ; if (!f) return (NULL) ; /* check inputs */ T = cs_spalloc (0, 0, 1, 1, 1) ; /* allocate result */ #ifdef CS_COMPLEX while (fscanf (f, ""CS_ID" "CS_ID" %lg %lg\n", &i, &j, &x, &xi) == 4) #else while (fscanf (f, ""CS_ID" "CS_ID" %lg\n", &i, &j, &x) == 3) #endif { #ifdef CS_COMPLEX if (!cs_entry (T, i, j, x + xi*I)) return (cs_spfree (T)) ; #else if (!cs_entry (T, i, j, x)) return (cs_spfree (T)) ; #endif } return (T) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_ipvec.c0000644000076500000240000000231213524616145023747 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* x(p) = b, for dense vectors x and b; p=NULL denotes identity */ CS_INT cs_ipvec (const CS_INT *p, const CS_ENTRY *b, CS_ENTRY *x, CS_INT n) { CS_INT k ; if (!x || !b) return (0) ; /* check inputs */ for (k = 0 ; k < n ; k++) x [p ? p [k] : k] = b [k] ; return (1) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_reach.c0000644000076500000240000000306713524616145023733 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* xi [top...n-1] = nodes reachable from graph of G*P' via nodes in B(:,k). * xi [n...2n-1] used as workspace */ CS_INT cs_reach (cs *G, const cs *B, CS_INT k, CS_INT *xi, const CS_INT *pinv) { CS_INT p, n, top, *Bp, *Bi, *Gp ; if (!CS_CSC (G) || !CS_CSC (B) || !xi) return (-1) ; /* check inputs */ n = G->n ; Bp = B->p ; Bi = B->i ; Gp = G->p ; top = n ; for (p = Bp [k] ; p < Bp [k+1] ; p++) { if (!CS_MARKED (Gp, Bi [p])) /* start a dfs at unmarked node i */ { top = cs_dfs (Bi [p], G, top, xi, xi+n, pinv) ; } } for (p = top ; p < n ; p++) CS_MARK (Gp, xi [p]) ; /* restore G */ return (top) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_chol.c0000644000076500000240000000727313524616144023600 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* L = chol (A, [pinv parent cp]), pinv is optional */ csn *cs_chol (const cs *A, const css *S) { CS_ENTRY d, lki, *Lx, *x, *Cx ; CS_INT top, i, p, k, n, *Li, *Lp, *cp, *pinv, *s, *c, *parent, *Cp, *Ci ; cs *L, *C, *E ; csn *N ; if (!CS_CSC (A) || !S || !S->cp || !S->parent) return (NULL) ; n = A->n ; N = cs_calloc (1, sizeof (csn)) ; /* allocate result */ c = cs_malloc (2*n, sizeof (CS_INT)) ; /* get CS_INT workspace */ x = cs_malloc (n, sizeof (CS_ENTRY)) ; /* get CS_ENTRY workspace */ cp = S->cp ; pinv = S->pinv ; parent = S->parent ; C = pinv ? cs_symperm (A, pinv, 1) : ((cs *) A) ; E = pinv ? C : NULL ; /* E is alias for A, or a copy E=A(p,p) */ if (!N || !c || !x || !C) return (cs_ndone (N, E, c, x, 0)) ; s = c + n ; Cp = C->p ; Ci = C->i ; Cx = C->x ; N->L = L = cs_spalloc (n, n, cp [n], 1, 0) ; /* allocate result */ if (!L) return (cs_ndone (N, E, c, x, 0)) ; Lp = L->p ; Li = L->i ; Lx = L->x ; for (k = 0 ; k < n ; k++) Lp [k] = c [k] = cp [k] ; for (k = 0 ; k < n ; k++) /* compute L(k,:) for L*L' = C */ { /* --- Nonzero pattern of L(k,:) ------------------------------------ */ top = cs_ereach (C, k, parent, s, c) ; /* find pattern of L(k,:) */ x [k] = 0 ; /* x (0:k) is now zero */ for (p = Cp [k] ; p < Cp [k+1] ; p++) /* x = full(triu(C(:,k))) */ { if (Ci [p] <= k) x [Ci [p]] = Cx [p] ; } d = x [k] ; /* d = C(k,k) */ x [k] = 0 ; /* clear x for k+1st iteration */ /* --- Triangular solve --------------------------------------------- */ for ( ; top < n ; top++) /* solve L(0:k-1,0:k-1) * x = C(:,k) */ { i = s [top] ; /* s [top..n-1] is pattern of L(k,:) */ lki = x [i] / Lx [Lp [i]] ; /* L(k,i) = x (i) / L(i,i) */ x [i] = 0 ; /* clear x for k+1st iteration */ for (p = Lp [i] + 1 ; p < c [i] ; p++) { x [Li [p]] -= Lx [p] * lki ; } d -= lki * CS_CONJ (lki) ; /* d = d - L(k,i)*L(k,i) */ p = c [i]++ ; Li [p] = k ; /* store L(k,i) in column i */ Lx [p] = CS_CONJ (lki) ; } /* --- Compute L(k,k) ----------------------------------------------- */ if (CS_REAL (d) <= 0 || CS_IMAG (d) != 0) return (cs_ndone (N, E, c, x, 0)) ; /* not pos def */ p = c [k]++ ; Li [p] = k ; /* store L(k,k) = sqrt (d) in column k */ Lx [p] = sqrt (d) ; } Lp [n] = cp [n] ; /* finalize L */ return (cs_ndone (N, E, c, x, 1)) ; /* success: free E,s,x; return N */ } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_pvec.c0000644000076500000240000000231113524616145023575 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* x = b(p), for dense vectors x and b; p=NULL denotes identity */ CS_INT cs_pvec (const CS_INT *p, const CS_ENTRY *b, CS_ENTRY *x, CS_INT n) { CS_INT k ; if (!x || !b) return (0) ; /* check inputs */ for (k = 0 ; k < n ; k++) x [k] = b [p ? p [k] : k] ; return (1) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_dmperm.c0000644000076500000240000001622413524616145024134 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* breadth-first search for coarse decomposition (C0,C1,R1 or R0,R3,C3) */ static CS_INT cs_bfs (const cs *A, CS_INT n, CS_INT *wi, CS_INT *wj, CS_INT *queue, const CS_INT *imatch, const CS_INT *jmatch, CS_INT mark) { CS_INT *Ap, *Ai, head = 0, tail = 0, j, i, p, j2 ; cs *C ; for (j = 0 ; j < n ; j++) /* place all unmatched nodes in queue */ { if (imatch [j] >= 0) continue ; /* skip j if matched */ wj [j] = 0 ; /* j in set C0 (R0 if transpose) */ queue [tail++] = j ; /* place unmatched col j in queue */ } if (tail == 0) return (1) ; /* quick return if no unmatched nodes */ C = (mark == 1) ? ((cs *) A) : cs_transpose (A, 0) ; if (!C) return (0) ; /* bfs of C=A' to find R3,C3 from R0 */ Ap = C->p ; Ai = C->i ; while (head < tail) /* while queue is not empty */ { j = queue [head++] ; /* get the head of the queue */ for (p = Ap [j] ; p < Ap [j+1] ; p++) { i = Ai [p] ; if (wi [i] >= 0) continue ; /* skip if i is marked */ wi [i] = mark ; /* i in set R1 (C3 if transpose) */ j2 = jmatch [i] ; /* traverse alternating path to j2 */ if (wj [j2] >= 0) continue ;/* skip j2 if it is marked */ wj [j2] = mark ; /* j2 in set C1 (R3 if transpose) */ queue [tail++] = j2 ; /* add j2 to queue */ } } if (mark != 1) cs_spfree (C) ; /* free A' if it was created */ return (1) ; } /* collect matched rows and columns into p and q */ static void cs_matched (CS_INT n, const CS_INT *wj, const CS_INT *imatch, CS_INT *p, CS_INT *q, CS_INT *cc, CS_INT *rr, CS_INT set, CS_INT mark) { CS_INT kc = cc [set], j ; CS_INT kr = rr [set-1] ; for (j = 0 ; j < n ; j++) { if (wj [j] != mark) continue ; /* skip if j is not in C set */ p [kr++] = imatch [j] ; q [kc++] = j ; } cc [set+1] = kc ; rr [set] = kr ; } /* collect unmatched rows into the permutation vector p */ static void cs_unmatched (CS_INT m, const CS_INT *wi, CS_INT *p, CS_INT *rr, CS_INT set) { CS_INT i, kr = rr [set] ; for (i = 0 ; i < m ; i++) if (wi [i] == 0) p [kr++] = i ; rr [set+1] = kr ; } /* return 1 if row i is in R2 */ static CS_INT cs_rprune (CS_INT i, CS_INT j, CS_ENTRY aij, void *other) { CS_INT *rr = (CS_INT *) other ; return (i >= rr [1] && i < rr [2]) ; } /* Given A, compute coarse and then fine dmperm */ csd *cs_dmperm (const cs *A, CS_INT seed) { CS_INT m, n, i, j, k, cnz, nc, *jmatch, *imatch, *wi, *wj, *pinv, *Cp, *Ci, *ps, *rs, nb1, nb2, *p, *q, *cc, *rr, *r, *s, ok ; cs *C ; csd *D, *scc ; /* --- Maximum matching ------------------------------------------------- */ if (!CS_CSC (A)) return (NULL) ; /* check inputs */ m = A->m ; n = A->n ; D = cs_dalloc (m, n) ; /* allocate result */ if (!D) return (NULL) ; p = D->p ; q = D->q ; r = D->r ; s = D->s ; cc = D->cc ; rr = D->rr ; jmatch = cs_maxtrans (A, seed) ; /* max transversal */ imatch = jmatch + m ; /* imatch = inverse of jmatch */ if (!jmatch) return (cs_ddone (D, NULL, jmatch, 0)) ; /* --- Coarse decomposition --------------------------------------------- */ wi = r ; wj = s ; /* use r and s as workspace */ for (j = 0 ; j < n ; j++) wj [j] = -1 ; /* unmark all cols for bfs */ for (i = 0 ; i < m ; i++) wi [i] = -1 ; /* unmark all rows for bfs */ cs_bfs (A, n, wi, wj, q, imatch, jmatch, 1) ; /* find C1, R1 from C0*/ ok = cs_bfs (A, m, wj, wi, p, jmatch, imatch, 3) ; /* find R3, C3 from R0*/ if (!ok) return (cs_ddone (D, NULL, jmatch, 0)) ; cs_unmatched (n, wj, q, cc, 0) ; /* unmatched set C0 */ cs_matched (n, wj, imatch, p, q, cc, rr, 1, 1) ; /* set R1 and C1 */ cs_matched (n, wj, imatch, p, q, cc, rr, 2, -1) ; /* set R2 and C2 */ cs_matched (n, wj, imatch, p, q, cc, rr, 3, 3) ; /* set R3 and C3 */ cs_unmatched (m, wi, p, rr, 3) ; /* unmatched set R0 */ cs_free (jmatch) ; /* --- Fine decomposition ----------------------------------------------- */ pinv = cs_pinv (p, m) ; /* pinv=p' */ if (!pinv) return (cs_ddone (D, NULL, NULL, 0)) ; C = cs_permute (A, pinv, q, 0) ;/* C=A(p,q) (it will hold A(R2,C2)) */ cs_free (pinv) ; if (!C) return (cs_ddone (D, NULL, NULL, 0)) ; Cp = C->p ; nc = cc [3] - cc [2] ; /* delete cols C0, C1, and C3 from C */ if (cc [2] > 0) for (j = cc [2] ; j <= cc [3] ; j++) Cp [j-cc[2]] = Cp [j] ; C->n = nc ; if (rr [2] - rr [1] < m) /* delete rows R0, R1, and R3 from C */ { cs_fkeep (C, cs_rprune, rr) ; cnz = Cp [nc] ; Ci = C->i ; if (rr [1] > 0) for (k = 0 ; k < cnz ; k++) Ci [k] -= rr [1] ; } C->m = nc ; scc = cs_scc (C) ; /* find strongly connected components of C*/ if (!scc) return (cs_ddone (D, C, NULL, 0)) ; /* --- Combine coarse and fine decompositions --------------------------- */ ps = scc->p ; /* C(ps,ps) is the permuted matrix */ rs = scc->r ; /* kth block is rs[k]..rs[k+1]-1 */ nb1 = scc->nb ; /* # of blocks of A(R2,C2) */ for (k = 0 ; k < nc ; k++) wj [k] = q [ps [k] + cc [2]] ; for (k = 0 ; k < nc ; k++) q [k + cc [2]] = wj [k] ; for (k = 0 ; k < nc ; k++) wi [k] = p [ps [k] + rr [1]] ; for (k = 0 ; k < nc ; k++) p [k + rr [1]] = wi [k] ; nb2 = 0 ; /* create the fine block partitions */ r [0] = s [0] = 0 ; if (cc [2] > 0) nb2++ ; /* leading coarse block A (R1, [C0 C1]) */ for (k = 0 ; k < nb1 ; k++) /* coarse block A (R2,C2) */ { r [nb2] = rs [k] + rr [1] ; /* A (R2,C2) splits into nb1 fine blocks */ s [nb2] = rs [k] + cc [2] ; nb2++ ; } if (rr [2] < m) { r [nb2] = rr [2] ; /* trailing coarse block A ([R3 R0], C3) */ s [nb2] = cc [3] ; nb2++ ; } r [nb2] = m ; s [nb2] = n ; D->nb = nb2 ; cs_dfree (scc) ; return (cs_ddone (D, C, NULL, 1)) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_lsolve.c0000644000076500000240000000261013524616145024146 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* solve Lx=b where x and b are dense. x=b on input, solution on output. */ CS_INT cs_lsolve (const cs *L, CS_ENTRY *x) { CS_INT p, j, n, *Lp, *Li ; CS_ENTRY *Lx ; if (!CS_CSC (L) || !x) return (0) ; /* check inputs */ n = L->n ; Lp = L->p ; Li = L->i ; Lx = L->x ; for (j = 0 ; j < n ; j++) { x [j] /= Lx [Lp [j]] ; for (p = Lp [j]+1 ; p < Lp [j+1] ; p++) { x [Li [p]] -= Lx [p] * x [j] ; } } return (1) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_qrsol.c0000644000076500000240000000533113524616145024005 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* x=A\b where A can be rectangular; b overwritten with solution */ CS_INT cs_qrsol (CS_INT order, const cs *A, CS_ENTRY *b) { CS_ENTRY *x ; css *S ; csn *N ; cs *AT = NULL ; CS_INT k, m, n, ok ; if (!CS_CSC (A) || !b) return (0) ; /* check inputs */ n = A->n ; m = A->m ; if (m >= n) { S = cs_sqr (order, A, 1) ; /* ordering and symbolic analysis */ N = cs_qr (A, S) ; /* numeric QR factorization */ x = cs_calloc (S ? S->m2 : 1, sizeof (CS_ENTRY)) ; /* get workspace */ ok = (S && N && x) ; if (ok) { cs_ipvec (S->pinv, b, x, m) ; /* x(0:m-1) = b(p(0:m-1) */ for (k = 0 ; k < n ; k++) /* apply Householder refl. to x */ { cs_happly (N->L, k, N->B [k], x) ; } cs_usolve (N->U, x) ; /* x = R\x */ cs_ipvec (S->q, x, b, n) ; /* b(q(0:n-1)) = x(0:n-1) */ } } else { AT = cs_transpose (A, 1) ; /* Ax=b is underdetermined */ S = cs_sqr (order, AT, 1) ; /* ordering and symbolic analysis */ N = cs_qr (AT, S) ; /* numeric QR factorization of A' */ x = cs_calloc (S ? S->m2 : 1, sizeof (CS_ENTRY)) ; /* get workspace */ ok = (AT && S && N && x) ; if (ok) { cs_pvec (S->q, b, x, m) ; /* x(q(0:m-1)) = b(0:m-1) */ cs_utsolve (N->U, x) ; /* x = R'\x */ for (k = m-1 ; k >= 0 ; k--) /* apply Householder refl. to x */ { cs_happly (N->L, k, N->B [k], x) ; } cs_pvec (S->pinv, x, b, n) ; /* b(0:n-1) = x(p(0:n-1)) */ } } cs_free (x) ; cs_sfree (S) ; cs_nfree (N) ; cs_spfree (AT) ; return (ok) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_symperm.c0000644000076500000240000000516513524616145024346 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* C = A(p,p) where A and C are symmetric the upper part stored; pinv not p */ cs *cs_symperm (const cs *A, const CS_INT *pinv, CS_INT values) { CS_INT i, j, p, q, i2, j2, n, *Ap, *Ai, *Cp, *Ci, *w ; CS_ENTRY *Cx, *Ax ; cs *C ; if (!CS_CSC (A)) return (NULL) ; /* check inputs */ n = A->n ; Ap = A->p ; Ai = A->i ; Ax = A->x ; C = cs_spalloc (n, n, Ap [n], values && (Ax != NULL), 0) ; /* alloc result*/ w = cs_calloc (n, sizeof (CS_INT)) ; /* get workspace */ if (!C || !w) return (cs_done (C, w, NULL, 0)) ; /* out of memory */ Cp = C->p ; Ci = C->i ; Cx = C->x ; for (j = 0 ; j < n ; j++) /* count entries in each column of C */ { j2 = pinv ? pinv [j] : j ; /* column j of A is column j2 of C */ for (p = Ap [j] ; p < Ap [j+1] ; p++) { i = Ai [p] ; if (i > j) continue ; /* skip lower triangular part of A */ i2 = pinv ? pinv [i] : i ; /* row i of A is row i2 of C */ w [CS_MAX (i2, j2)]++ ; /* column count of C */ } } cs_cumsum (Cp, w, n) ; /* compute column pointers of C */ for (j = 0 ; j < n ; j++) { j2 = pinv ? pinv [j] : j ; /* column j of A is column j2 of C */ for (p = Ap [j] ; p < Ap [j+1] ; p++) { i = Ai [p] ; if (i > j) continue ; /* skip lower triangular part of A*/ i2 = pinv ? pinv [i] : i ; /* row i of A is row i2 of C */ Ci [q = w [CS_MAX (i2, j2)]++] = CS_MIN (i2, j2) ; if (Cx) Cx [q] = (i2 <= j2) ? Ax [p] : CS_CONJ (Ax [p]) ; } } return (cs_done (C, w, NULL, 1)) ; /* success; free workspace, return C */ } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_schol.c0000644000076500000240000000401513524616145023753 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* ordering and symbolic analysis for a Cholesky factorization */ css *cs_schol (CS_INT order, const cs *A) { CS_INT n, *c, *post, *P ; cs *C ; css *S ; if (!CS_CSC (A)) return (NULL) ; /* check inputs */ n = A->n ; S = cs_calloc (1, sizeof (css)) ; /* allocate result S */ if (!S) return (NULL) ; /* out of memory */ P = cs_amd (order, A) ; /* P = amd(A+A'), or natural */ S->pinv = cs_pinv (P, n) ; /* find inverse permutation */ cs_free (P) ; if (order && !S->pinv) return (cs_sfree (S)) ; C = cs_symperm (A, S->pinv, 0) ; /* C = spones(triu(A(P,P))) */ S->parent = cs_etree (C, 0) ; /* find etree of C */ post = cs_post (S->parent, n) ; /* postorder the etree */ c = cs_counts (C, S->parent, post, 0) ; /* find column counts of chol(C) */ cs_free (post) ; cs_spfree (C) ; S->cp = cs_malloc (n+1, sizeof (CS_INT)) ; /* allocate result S->cp */ S->unz = S->lnz = cs_cumsum (S->cp, c, n) ; /* find column pointers for L */ cs_free (c) ; return ((S->lnz >= 0) ? S : cs_sfree (S)) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_droptol.c0000644000076500000240000000217213524616145024330 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" static CS_INT cs_tol (CS_INT i, CS_INT j, CS_ENTRY aij, void *tol) { return (CS_ABS (aij) > *((double *) tol)) ; } CS_INT cs_droptol (cs *A, double tol) { return (cs_fkeep (A, &cs_tol, &tol)) ; /* keep all large entries */ } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_entry.c0000644000076500000240000000251113524616145024003 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* add an entry to a triplet matrix; return 1 if ok, 0 otherwise */ CS_INT cs_entry (cs *T, CS_INT i, CS_INT j, CS_ENTRY x) { if (!CS_TRIPLET (T) || i < 0 || j < 0) return (0) ; /* check inputs */ if (T->nz >= T->nzmax && !cs_sprealloc (T,2*(T->nzmax))) return (0) ; if (T->x) T->x [T->nz] = x ; T->i [T->nz] = i ; T->p [T->nz++] = j ; T->m = CS_MAX (T->m, i+1) ; T->n = CS_MAX (T->n, j+1) ; return (1) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_randperm.c0000644000076500000240000000357113524616145024461 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_random.h" #include "cs.h" /* return a random permutation vector, the identity perm, or p = n-1:-1:0. * seed = -1 means p = n-1:-1:0. seed = 0 means p = identity. otherwise * p = random permutation. */ CS_INT *cs_randperm (CS_INT n, CS_INT seed) { CS_INT *p, k, j, t ; if (seed == 0) return (NULL) ; /* return p = NULL (identity) */ p = cs_malloc (n, sizeof (CS_INT)) ; /* allocate result */ if (!p) return (NULL) ; /* out of memory */ for (k = 0 ; k < n ; k++) p [k] = n-k-1 ; if (seed == -1) return (p) ; /* return reverse permutation */ /* srand (seed) ; /\* get new random number seed *\/ */ RNG_BEGIN(); for (k = 0 ; k < n ; k++) { /* j = k + (rand ( ) % (n-k)) ; /\* j = rand CS_INT in range k to n-1 *\/ */ j = k + RNG_INTEGER(k, n-1) ; t = p [j] ; /* swap p[k] and p[j] */ p [j] = p [k] ; p [k] = t ; } RNG_END(); return (p) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_scatter.c0000644000076500000240000000340313524616145024310 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* x = x + beta * A(:,j), where x is a dense vector and A(:,j) is sparse */ CS_INT cs_scatter (const cs *A, CS_INT j, CS_ENTRY beta, CS_INT *w, CS_ENTRY *x, CS_INT mark, cs *C, CS_INT nz) { CS_INT i, p, *Ap, *Ai, *Ci ; CS_ENTRY *Ax ; if (!CS_CSC (A) || !w || !CS_CSC (C)) return (-1) ; /* check inputs */ Ap = A->p ; Ai = A->i ; Ax = A->x ; Ci = C->i ; for (p = Ap [j] ; p < Ap [j+1] ; p++) { i = Ai [p] ; /* A(i,j) is nonzero */ if (w [i] < mark) { w [i] = mark ; /* i is new entry in column j */ Ci [nz++] = i ; /* add i to pattern of C(:,j) */ if (x) x [i] = beta * Ax [p] ; /* x(i) = beta*A(i,j) */ } else if (x) x [i] += beta * Ax [p] ; /* i exists in C(:,j) already */ } return (nz) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_leaf.c0000644000076500000240000000361513524616145023557 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* consider A(i,j), node j in ith row subtree and return lca(jprev,j) */ CS_INT cs_leaf (CS_INT i, CS_INT j, const CS_INT *first, CS_INT *maxfirst, CS_INT *prevleaf, CS_INT *ancestor, CS_INT *jleaf) { CS_INT q, s, sparent, jprev ; if (!first || !maxfirst || !prevleaf || !ancestor || !jleaf) return (-1) ; *jleaf = 0 ; if (i <= j || first [j] <= maxfirst [i]) return (-1) ; /* j not a leaf */ maxfirst [i] = first [j] ; /* update max first[j] seen so far */ jprev = prevleaf [i] ; /* jprev = previous leaf of ith subtree */ prevleaf [i] = j ; *jleaf = (jprev == -1) ? 1: 2 ; /* j is first or subsequent leaf */ if (*jleaf == 1) return (i) ; /* if 1st leaf, q = root of ith subtree */ for (q = jprev ; q != ancestor [q] ; q = ancestor [q]) ; for (s = jprev ; s != q ; s = sparent) { sparent = ancestor [s] ; /* path compression */ ancestor [s] = q ; } return (q) ; /* q = least common ancester (jprev,j) */ } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_post.c0000644000076500000240000000370113524616145023631 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* post order a forest */ CS_INT *cs_post (const CS_INT *parent, CS_INT n) { CS_INT j, k = 0, *post, *w, *head, *next, *stack ; if (!parent) return (NULL) ; /* check inputs */ post = cs_malloc (n, sizeof (CS_INT)) ; /* allocate result */ w = cs_malloc (3*n, sizeof (CS_INT)) ; /* get workspace */ if (!w || !post) return (cs_idone (post, NULL, w, 0)) ; head = w ; next = w + n ; stack = w + 2*n ; for (j = 0 ; j < n ; j++) head [j] = -1 ; /* empty linked lists */ for (j = n-1 ; j >= 0 ; j--) /* traverse nodes in reverse order*/ { if (parent [j] == -1) continue ; /* j is a root */ next [j] = head [parent [j]] ; /* add j to list of its parent */ head [parent [j]] = j ; } for (j = 0 ; j < n ; j++) { if (parent [j] != -1) continue ; /* skip j if it is not a root */ k = cs_tdfs (j, k, head, next, post, stack) ; } return (cs_idone (post, NULL, w, 1)) ; /* success; free w, return post */ } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_dupl.c0000644000076500000240000000437313524616145023616 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* remove duplicate entries from A */ CS_INT cs_dupl (cs *A) { CS_INT i, j, p, q, nz = 0, n, m, *Ap, *Ai, *w ; CS_ENTRY *Ax ; if (!CS_CSC (A)) return (0) ; /* check inputs */ m = A->m ; n = A->n ; Ap = A->p ; Ai = A->i ; Ax = A->x ; w = cs_malloc (m, sizeof (CS_INT)) ; /* get workspace */ if (!w) return (0) ; /* out of memory */ for (i = 0 ; i < m ; i++) w [i] = -1 ; /* row i not yet seen */ for (j = 0 ; j < n ; j++) { q = nz ; /* column j will start at q */ for (p = Ap [j] ; p < Ap [j+1] ; p++) { i = Ai [p] ; /* A(i,j) is nonzero */ if (w [i] >= q) { Ax [w [i]] += Ax [p] ; /* A(i,j) is a duplicate */ } else { w [i] = nz ; /* record where row i occurs */ Ai [nz] = i ; /* keep A(i,j) */ Ax [nz++] = Ax [p] ; } } Ap [j] = q ; /* record start of column j */ } Ap [n] = nz ; /* finalize A */ cs_free (w) ; /* free workspace */ return (cs_sprealloc (A, 0)) ; /* remove extra space from A */ } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_malloc.c0000644000076500000240000000340413524616145024113 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" #ifdef MATLAB_MEX_FILE #define malloc mxMalloc #define free mxFree #define realloc mxRealloc #define calloc mxCalloc #endif /* wrapper for malloc */ void *cs_malloc (CS_INT n, size_t size) { return (malloc (CS_MAX (n,1) * size)) ; } /* wrapper for calloc */ void *cs_calloc (CS_INT n, size_t size) { return (calloc (CS_MAX (n,1), size)) ; } /* wrapper for free */ void *cs_free (void *p) { if (p) free (p) ; /* free p if it is not already NULL */ return (NULL) ; /* return NULL to simplify the use of cs_free */ } /* wrapper for realloc */ void *cs_realloc (void *p, CS_INT n, size_t size, CS_INT *ok) { void *pnew ; pnew = realloc (p, CS_MAX (n,1) * size) ; /* realloc the block */ *ok = (pnew != NULL) ; /* realloc fails if pnew is NULL */ return ((*ok) ? pnew : p) ; /* return original p if failure */ } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_dfs.c0000644000076500000240000000475313524616145023430 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* depth-first-search of the graph of a matrix, starting at node j */ CS_INT cs_dfs (CS_INT j, cs *G, CS_INT top, CS_INT *xi, CS_INT *pstack, const CS_INT *pinv) { CS_INT i, p, p2, done, jnew, head = 0, *Gp, *Gi ; if (!CS_CSC (G) || !xi || !pstack) return (-1) ; /* check inputs */ Gp = G->p ; Gi = G->i ; xi [0] = j ; /* initialize the recursion stack */ while (head >= 0) { j = xi [head] ; /* get j from the top of the recursion stack */ jnew = pinv ? (pinv [j]) : j ; if (!CS_MARKED (Gp, j)) { CS_MARK (Gp, j) ; /* mark node j as visited */ pstack [head] = (jnew < 0) ? 0 : CS_UNFLIP (Gp [jnew]) ; } done = 1 ; /* node j done if no unvisited neighbors */ p2 = (jnew < 0) ? 0 : CS_UNFLIP (Gp [jnew+1]) ; for (p = pstack [head] ; p < p2 ; p++) /* examine all neighbors of j */ { i = Gi [p] ; /* consider neighbor node i */ if (CS_MARKED (Gp, i)) continue ; /* skip visited node i */ pstack [head] = p ; /* pause depth-first search of node j */ xi [++head] = i ; /* start dfs at node i */ done = 0 ; /* node j is not done */ break ; /* break, to start dfs (i) */ } if (done) /* depth-first search at node j is done */ { head-- ; /* remove j from the recursion stack */ xi [--top] = j ; /* and place in the output stack */ } } return (top) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_lusol.c0000644000076500000240000000334713524616145024010 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* x=A\b where A is unsymmetric; b overwritten with solution */ CS_INT cs_lusol (CS_INT order, const cs *A, CS_ENTRY *b, double tol) { CS_ENTRY *x ; css *S ; csn *N ; CS_INT n, ok ; if (!CS_CSC (A) || !b) return (0) ; /* check inputs */ n = A->n ; S = cs_sqr (order, A, 0) ; /* ordering and symbolic analysis */ N = cs_lu (A, S, tol) ; /* numeric LU factorization */ x = cs_malloc (n, sizeof (CS_ENTRY)) ; /* get workspace */ ok = (S && N && x) ; if (ok) { cs_ipvec (N->pinv, b, x, n) ; /* x = b(p) */ cs_lsolve (N->L, x) ; /* x = L\x */ cs_usolve (N->U, x) ; /* x = U\x */ cs_ipvec (S->q, x, b, n) ; /* b(q) = x */ } cs_free (x) ; cs_sfree (S) ; cs_nfree (N) ; return (ok) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_add.c0000644000076500000240000000441113524616144023372 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* C = alpha*A + beta*B */ cs *cs_add (const cs *A, const cs *B, CS_ENTRY alpha, CS_ENTRY beta) { CS_INT p, j, nz = 0, anz, *Cp, *Ci, *Bp, m, n, bnz, *w, values ; CS_ENTRY *x, *Bx, *Cx ; cs *C ; if (!CS_CSC (A) || !CS_CSC (B)) return (NULL) ; /* check inputs */ if (A->m != B->m || A->n != B->n) return (NULL) ; m = A->m ; anz = A->p [A->n] ; n = B->n ; Bp = B->p ; Bx = B->x ; bnz = Bp [n] ; w = cs_calloc (m, sizeof (CS_INT)) ; /* get workspace */ values = (A->x != NULL) && (Bx != NULL) ; x = values ? cs_malloc (m, sizeof (CS_ENTRY)) : NULL ; /* get workspace */ C = cs_spalloc (m, n, anz + bnz, values, 0) ; /* allocate result*/ if (!C || !w || (values && !x)) return (cs_done (C, w, x, 0)) ; Cp = C->p ; Ci = C->i ; Cx = C->x ; for (j = 0 ; j < n ; j++) { Cp [j] = nz ; /* column j of C starts here */ nz = cs_scatter (A, j, alpha, w, x, j+1, C, nz) ; /* alpha*A(:,j)*/ nz = cs_scatter (B, j, beta, w, x, j+1, C, nz) ; /* beta*B(:,j) */ if (values) for (p = Cp [j] ; p < nz ; p++) Cx [p] = x [Ci [p]] ; } Cp [n] = nz ; /* finalize the last column of C */ cs_sprealloc (C, 0) ; /* remove extra space from C */ return (cs_done (C, w, x, 1)) ; /* success; free workspace, return C */ } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_updown.c0000644000076500000240000000567013524616145024167 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* sparse Cholesky update/downdate, L*L' + sigma*w*w' (sigma = +1 or -1) */ CS_INT cs_updown (cs *L, CS_INT sigma, const cs *C, const CS_INT *parent) { CS_INT n, p, f, j, *Lp, *Li, *Cp, *Ci ; CS_ENTRY *Lx, *Cx, alpha, gamma, w1, w2, *w ; double beta = 1, beta2 = 1, delta ; #ifdef CS_COMPLEX cs_complex_t phase ; #endif if (!CS_CSC (L) || !CS_CSC (C) || !parent) return (0) ; /* check inputs */ Lp = L->p ; Li = L->i ; Lx = L->x ; n = L->n ; Cp = C->p ; Ci = C->i ; Cx = C->x ; if ((p = Cp [0]) >= Cp [1]) return (1) ; /* return if C empty */ w = cs_malloc (n, sizeof (CS_ENTRY)) ; /* get workspace */ if (!w) return (0) ; /* out of memory */ f = Ci [p] ; for ( ; p < Cp [1] ; p++) f = CS_MIN (f, Ci [p]) ; /* f = min (find (C)) */ for (j = f ; j != -1 ; j = parent [j]) w [j] = 0 ; /* clear workspace w */ for (p = Cp [0] ; p < Cp [1] ; p++) w [Ci [p]] = Cx [p] ; /* w = C */ for (j = f ; j != -1 ; j = parent [j]) /* walk path f up to root */ { p = Lp [j] ; alpha = w [j] / Lx [p] ; /* alpha = w(j) / L(j,j) */ beta2 = beta*beta + sigma*alpha*CS_CONJ(alpha) ; if (beta2 <= 0) break ; /* not positive definite */ beta2 = sqrt (beta2) ; delta = (sigma > 0) ? (beta / beta2) : (beta2 / beta) ; gamma = sigma * CS_CONJ(alpha) / (beta2 * beta) ; Lx [p] = delta * Lx [p] + ((sigma > 0) ? (gamma * w [j]) : 0) ; beta = beta2 ; #ifdef CS_COMPLEX phase = CS_ABS (Lx [p]) / Lx [p] ; /* phase = abs(L(j,j))/L(j,j)*/ Lx [p] *= phase ; /* L(j,j) = L(j,j) * phase */ #endif for (p++ ; p < Lp [j+1] ; p++) { w1 = w [Li [p]] ; w [Li [p]] = w2 = w1 - alpha * Lx [p] ; Lx [p] = delta * Lx [p] + gamma * ((sigma > 0) ? w1 : w2) ; #ifdef CS_COMPLEX Lx [p] *= phase ; /* L(i,j) = L(i,j) * phase */ #endif } } cs_free (w) ; return (beta2 > 0) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_utsolve.c0000644000076500000240000000264213524616145024350 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* solve U'x=b where x and b are dense. x=b on input, solution on output. */ CS_INT cs_utsolve (const cs *U, CS_ENTRY *x) { CS_INT p, j, n, *Up, *Ui ; CS_ENTRY *Ux ; if (!CS_CSC (U) || !x) return (0) ; /* check inputs */ n = U->n ; Up = U->p ; Ui = U->i ; Ux = U->x ; for (j = 0 ; j < n ; j++) { for (p = Up [j] ; p < Up [j+1]-1 ; p++) { x [j] -= CS_CONJ (Ux [p]) * x [Ui [p]] ; } x [j] /= CS_CONJ (Ux [Up [j+1]-1]) ; } return (1) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_cholsol.c0000644000076500000240000000334313524616144024310 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* x=A\b where A is symmetric positive definite; b overwritten with solution */ CS_INT cs_cholsol (CS_INT order, const cs *A, CS_ENTRY *b) { CS_ENTRY *x ; css *S ; csn *N ; CS_INT n, ok ; if (!CS_CSC (A) || !b) return (0) ; /* check inputs */ n = A->n ; S = cs_schol (order, A) ; /* ordering and symbolic analysis */ N = cs_chol (A, S) ; /* numeric Cholesky factorization */ x = cs_malloc (n, sizeof (CS_ENTRY)) ; /* get workspace */ ok = (S && N && x) ; if (ok) { cs_ipvec (S->pinv, b, x, n) ; /* x = P*b */ cs_lsolve (N->L, x) ; /* x = L\x */ cs_ltsolve (N->L, x) ; /* x = L'\x */ cs_pvec (S->pinv, x, b, n) ; /* b = P'*x */ } cs_free (x) ; cs_sfree (S) ; cs_nfree (N) ; return (ok) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_compress.c0000644000076500000240000000355313524616144024503 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* C = compressed-column form of a triplet matrix T */ cs *cs_compress (const cs *T) { CS_INT m, n, nz, p, k, *Cp, *Ci, *w, *Ti, *Tj ; CS_ENTRY *Cx, *Tx ; cs *C ; if (!CS_TRIPLET (T)) return (NULL) ; /* check inputs */ m = T->m ; n = T->n ; Ti = T->i ; Tj = T->p ; Tx = T->x ; nz = T->nz ; C = cs_spalloc (m, n, nz, Tx != NULL, 0) ; /* allocate result */ w = cs_calloc (n, sizeof (CS_INT)) ; /* get workspace */ if (!C || !w) return (cs_done (C, w, NULL, 0)) ; /* out of memory */ Cp = C->p ; Ci = C->i ; Cx = C->x ; for (k = 0 ; k < nz ; k++) w [Tj [k]]++ ; /* column counts */ cs_cumsum (Cp, w, n) ; /* column pointers */ for (k = 0 ; k < nz ; k++) { Ci [p = w [Tj [k]]++] = Ti [k] ; /* A(i,j) is the pth entry in C */ if (Cx) Cx [p] = Tx [k] ; } return (cs_done (C, w, NULL, 1)) ; /* success; free w and return C */ } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_transpose.c0000644000076500000240000000363313524616145024666 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* C = A' */ cs *cs_transpose (const cs *A, CS_INT values) { CS_INT p, q, j, *Cp, *Ci, n, m, *Ap, *Ai, *w ; CS_ENTRY *Cx, *Ax ; cs *C ; if (!CS_CSC (A)) return (NULL) ; /* check inputs */ m = A->m ; n = A->n ; Ap = A->p ; Ai = A->i ; Ax = A->x ; C = cs_spalloc (n, m, Ap [n], values && Ax, 0) ; /* allocate result */ w = cs_calloc (m, sizeof (CS_INT)) ; /* get workspace */ if (!C || !w) return (cs_done (C, w, NULL, 0)) ; /* out of memory */ Cp = C->p ; Ci = C->i ; Cx = C->x ; for (p = 0 ; p < Ap [n] ; p++) w [Ai [p]]++ ; /* row counts */ cs_cumsum (Cp, w, m) ; /* row pointers */ for (j = 0 ; j < n ; j++) { for (p = Ap [j] ; p < Ap [j+1] ; p++) { Ci [q = w [Ai [p]]++] = j ; /* place A(i,j) as entry C(j,i) */ if (Cx) Cx [q] = (values > 0) ? CS_CONJ (Ax [p]) : Ax [p] ; } } return (cs_done (C, w, NULL, 1)) ; /* success; free w and return C */ } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_maxtrans.c0000644000076500000240000001243113524616145024501 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* find an augmenting path starting at column k and extend the match if found */ static void cs_augment (CS_INT k, const cs *A, CS_INT *jmatch, CS_INT *cheap, CS_INT *w, CS_INT *js, CS_INT *is, CS_INT *ps) { CS_INT found = 0, p, i = -1, *Ap = A->p, *Ai = A->i, head = 0, j ; js [0] = k ; /* start with just node k in jstack */ while (head >= 0) { /* --- Start (or continue) depth-first-search at node j ------------- */ j = js [head] ; /* get j from top of jstack */ if (w [j] != k) /* 1st time j visited for kth path */ { w [j] = k ; /* mark j as visited for kth path */ for (p = cheap [j] ; p < Ap [j+1] && !found ; p++) { i = Ai [p] ; /* try a cheap assignment (i,j) */ found = (jmatch [i] == -1) ; } cheap [j] = p ; /* start here next time j is traversed*/ if (found) { is [head] = i ; /* column j matched with row i */ break ; /* end of augmenting path */ } ps [head] = Ap [j] ; /* no cheap match: start dfs for j */ } /* --- Depth-first-search of neighbors of j ------------------------- */ for (p = ps [head] ; p < Ap [j+1] ; p++) { i = Ai [p] ; /* consider row i */ if (w [jmatch [i]] == k) continue ; /* skip jmatch [i] if marked */ ps [head] = p + 1 ; /* pause dfs of node j */ is [head] = i ; /* i will be matched with j if found */ js [++head] = jmatch [i] ; /* start dfs at column jmatch [i] */ break ; } if (p == Ap [j+1]) head-- ; /* node j is done; pop from stack */ } /* augment the match if path found: */ if (found) for (p = head ; p >= 0 ; p--) jmatch [is [p]] = js [p] ; } /* find a maximum transveral */ CS_INT *cs_maxtrans (const cs *A, CS_INT seed) /*[jmatch [0..m-1]; imatch [0..n-1]]*/ { CS_INT i, j, k, n, m, p, n2 = 0, m2 = 0, *Ap, *jimatch, *w, *cheap, *js, *is, *ps, *Ai, *Cp, *jmatch, *imatch, *q ; cs *C ; if (!CS_CSC (A)) return (NULL) ; /* check inputs */ n = A->n ; m = A->m ; Ap = A->p ; Ai = A->i ; w = jimatch = cs_calloc (m+n, sizeof (CS_INT)) ; /* allocate result */ if (!jimatch) return (NULL) ; for (k = 0, j = 0 ; j < n ; j++) /* count nonempty rows and columns */ { n2 += (Ap [j] < Ap [j+1]) ; for (p = Ap [j] ; p < Ap [j+1] ; p++) { w [Ai [p]] = 1 ; k += (j == Ai [p]) ; /* count entries already on diagonal */ } } if (k == CS_MIN (m,n)) /* quick return if diagonal zero-free */ { jmatch = jimatch ; imatch = jimatch + m ; for (i = 0 ; i < k ; i++) jmatch [i] = i ; for ( ; i < m ; i++) jmatch [i] = -1 ; for (j = 0 ; j < k ; j++) imatch [j] = j ; for ( ; j < n ; j++) imatch [j] = -1 ; return (cs_idone (jimatch, NULL, NULL, 1)) ; } for (i = 0 ; i < m ; i++) m2 += w [i] ; C = (m2 < n2) ? cs_transpose (A,0) : ((cs *) A) ; /* transpose if needed */ if (!C) return (cs_idone (jimatch, (m2 < n2) ? C : NULL, NULL, 0)) ; n = C->n ; m = C->m ; Cp = C->p ; jmatch = (m2 < n2) ? jimatch + n : jimatch ; imatch = (m2 < n2) ? jimatch : jimatch + m ; w = cs_malloc (5*n, sizeof (CS_INT)) ; /* get workspace */ if (!w) return (cs_idone (jimatch, (m2 < n2) ? C : NULL, w, 0)) ; cheap = w + n ; js = w + 2*n ; is = w + 3*n ; ps = w + 4*n ; for (j = 0 ; j < n ; j++) cheap [j] = Cp [j] ; /* for cheap assignment */ for (j = 0 ; j < n ; j++) w [j] = -1 ; /* all columns unflagged */ for (i = 0 ; i < m ; i++) jmatch [i] = -1 ; /* nothing matched yet */ q = cs_randperm (n, seed) ; /* q = random permutation */ for (k = 0 ; k < n ; k++) /* augment, starting at column q[k] */ { cs_augment (q ? q [k]: k, C, jmatch, cheap, w, js, is, ps) ; } cs_free (q) ; for (j = 0 ; j < n ; j++) imatch [j] = -1 ; /* find row match */ for (i = 0 ; i < m ; i++) if (jmatch [i] >= 0) imatch [jmatch [i]] = i ; return (cs_idone (jimatch, (m2 < n2) ? C : NULL, w, 1)) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_print.c0000644000076500000240000000534113524616145024002 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* print a sparse matrix */ /* CS_INT cs_print (const cs *A, CS_INT brief) */ /* { */ /* CS_INT p, j, m, n, nzmax, nz, *Ap, *Ai ; */ /* CS_ENTRY *Ax ; */ /* if (!A) { printf ("(null)\n") ; return (0) ; } */ /* m = A->m ; n = A->n ; Ap = A->p ; Ai = A->i ; Ax = A->x ; */ /* nzmax = A->nzmax ; nz = A->nz ; */ /* printf ("CXSparse Version %d.%d.%d, %s. %s\n", CS_VER, CS_SUBVER, */ /* CS_SUBSUB, CS_DATE, CS_COPYRIGHT) ; */ /* if (nz < 0) */ /* { */ /* printf (""CS_ID"-by-"CS_ID", nzmax: "CS_ID" nnz: "CS_ID", 1-norm: %g\n", m, n, nzmax, */ /* Ap [n], cs_norm (A)) ; */ /* for (j = 0 ; j < n ; j++) */ /* { */ /* printf (" col "CS_ID" : locations "CS_ID" to "CS_ID"\n", j, Ap [j], Ap [j+1]-1); */ /* for (p = Ap [j] ; p < Ap [j+1] ; p++) */ /* { */ /* #ifdef CS_COMPLEX */ /* printf (" "CS_ID" : (%g, %g)\n", Ai [p], */ /* Ax ? CS_REAL (Ax [p]) : 1, Ax ? CS_IMAG (Ax [p]) : 0) ; */ /* #else */ /* printf (" "CS_ID" : %g\n", Ai [p], Ax ? Ax [p] : 1) ; */ /* #endif */ /* if (brief && p > 20) { printf (" ...\n") ; return (1) ; } */ /* } */ /* } */ /* } */ /* else */ /* { */ /* printf ("triplet: "CS_ID"-by-"CS_ID", nzmax: "CS_ID" nnz: "CS_ID"\n", m, n, nzmax, nz) ; */ /* for (p = 0 ; p < nz ; p++) */ /* { */ /* #ifdef CS_COMPLEX */ /* printf (" "CS_ID" "CS_ID" : (%g, %g)\n", Ai [p], Ap [p], */ /* Ax ? CS_REAL (Ax [p]) : 1, Ax ? CS_IMAG (Ax [p]) : 0) ; */ /* #else */ /* printf (" "CS_ID" "CS_ID" : %g\n", Ai [p], Ap [p], Ax ? Ax [p] : 1) ; */ /* #endif */ /* if (brief && p > 20) { printf (" ...\n") ; return (1) ; } */ /* } */ /* } */ /* return (1) ; */ /* } */ python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_lu.c0000644000076500000240000001152113524616145023263 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* [L,U,pinv]=lu(A, [q lnz unz]). lnz and unz can be guess */ csn *cs_lu (const cs *A, const css *S, double tol) { cs *L, *U ; csn *N ; CS_ENTRY pivot, *Lx, *Ux, *x ; double a, t ; CS_INT *Lp, *Li, *Up, *Ui, *pinv, *xi, *q, n, ipiv, k, top, p, i, col, lnz,unz; if (!CS_CSC (A) || !S) return (NULL) ; /* check inputs */ n = A->n ; q = S->q ; lnz = S->lnz ; unz = S->unz ; x = cs_malloc (n, sizeof (CS_ENTRY)) ; /* get CS_ENTRY workspace */ xi = cs_malloc (2*n, sizeof (CS_INT)) ; /* get CS_INT workspace */ N = cs_calloc (1, sizeof (csn)) ; /* allocate result */ if (!x || !xi || !N) return (cs_ndone (N, NULL, xi, x, 0)) ; N->L = L = cs_spalloc (n, n, lnz, 1, 0) ; /* allocate result L */ N->U = U = cs_spalloc (n, n, unz, 1, 0) ; /* allocate result U */ N->pinv = pinv = cs_malloc (n, sizeof (CS_INT)) ; /* allocate result pinv */ if (!L || !U || !pinv) return (cs_ndone (N, NULL, xi, x, 0)) ; Lp = L->p ; Up = U->p ; for (i = 0 ; i < n ; i++) x [i] = 0 ; /* clear workspace */ for (i = 0 ; i < n ; i++) pinv [i] = -1 ; /* no rows pivotal yet */ for (k = 0 ; k <= n ; k++) Lp [k] = 0 ; /* no cols of L yet */ lnz = unz = 0 ; for (k = 0 ; k < n ; k++) /* compute L(:,k) and U(:,k) */ { /* --- Triangular solve --------------------------------------------- */ Lp [k] = lnz ; /* L(:,k) starts here */ Up [k] = unz ; /* U(:,k) starts here */ if ((lnz + n > L->nzmax && !cs_sprealloc (L, 2*L->nzmax + n)) || (unz + n > U->nzmax && !cs_sprealloc (U, 2*U->nzmax + n))) { return (cs_ndone (N, NULL, xi, x, 0)) ; } Li = L->i ; Lx = L->x ; Ui = U->i ; Ux = U->x ; col = q ? (q [k]) : k ; top = cs_spsolve (L, A, col, xi, x, pinv, 1) ; /* x = L\A(:,col) */ /* --- Find pivot --------------------------------------------------- */ ipiv = -1 ; a = -1 ; for (p = top ; p < n ; p++) { i = xi [p] ; /* x(i) is nonzero */ if (pinv [i] < 0) /* row i is not yet pivotal */ { if ((t = CS_ABS (x [i])) > a) { a = t ; /* largest pivot candidate so far */ ipiv = i ; } } else /* x(i) is the entry U(pinv[i],k) */ { Ui [unz] = pinv [i] ; Ux [unz++] = x [i] ; } } if (ipiv == -1 || a <= 0) return (cs_ndone (N, NULL, xi, x, 0)) ; if (pinv [col] < 0 && CS_ABS (x [col]) >= a*tol) ipiv = col ; /* --- Divide by pivot ---------------------------------------------- */ pivot = x [ipiv] ; /* the chosen pivot */ Ui [unz] = k ; /* last entry in U(:,k) is U(k,k) */ Ux [unz++] = pivot ; pinv [ipiv] = k ; /* ipiv is the kth pivot row */ Li [lnz] = ipiv ; /* first entry in L(:,k) is L(k,k) = 1 */ Lx [lnz++] = 1 ; for (p = top ; p < n ; p++) /* L(k+1:n,k) = x / pivot */ { i = xi [p] ; if (pinv [i] < 0) /* x(i) is an entry in L(:,k) */ { Li [lnz] = i ; /* save unpermuted row in L */ Lx [lnz++] = x [i] / pivot ; /* scale pivot column */ } x [i] = 0 ; /* x [0..n-1] = 0 for next k */ } } /* --- Finalize L and U ------------------------------------------------- */ Lp [n] = lnz ; Up [n] = unz ; Li = L->i ; /* fix row indices of L for final pinv */ for (p = 0 ; p < lnz ; p++) Li [p] = pinv [Li [p]] ; cs_sprealloc (L, 0) ; /* remove extra space from L and U */ cs_sprealloc (U, 0) ; return (cs_ndone (N, NULL, xi, x, 1)) ; /* success */ } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_multiply.c0000644000076500000240000000464713524616145024535 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* C = A*B */ cs *cs_multiply (const cs *A, const cs *B) { CS_INT p, j, nz = 0, anz, *Cp, *Ci, *Bp, m, n, bnz, *w, values, *Bi ; CS_ENTRY *x, *Bx, *Cx ; cs *C ; if (!CS_CSC (A) || !CS_CSC (B)) return (NULL) ; /* check inputs */ if (A->n != B->m) return (NULL) ; m = A->m ; anz = A->p [A->n] ; n = B->n ; Bp = B->p ; Bi = B->i ; Bx = B->x ; bnz = Bp [n] ; w = cs_calloc (m, sizeof (CS_INT)) ; /* get workspace */ values = (A->x != NULL) && (Bx != NULL) ; x = values ? cs_malloc (m, sizeof (CS_ENTRY)) : NULL ; /* get workspace */ C = cs_spalloc (m, n, anz + bnz, values, 0) ; /* allocate result */ if (!C || !w || (values && !x)) return (cs_done (C, w, x, 0)) ; Cp = C->p ; for (j = 0 ; j < n ; j++) { if (nz + m > C->nzmax && !cs_sprealloc (C, 2*(C->nzmax)+m)) { return (cs_done (C, w, x, 0)) ; /* out of memory */ } Ci = C->i ; Cx = C->x ; /* C->i and C->x may be reallocated */ Cp [j] = nz ; /* column j of C starts here */ for (p = Bp [j] ; p < Bp [j+1] ; p++) { nz = cs_scatter (A, Bi [p], Bx ? Bx [p] : 1, w, x, j+1, C, nz) ; } if (values) for (p = Cp [j] ; p < nz ; p++) Cx [p] = x [Ci [p]] ; } Cp [n] = nz ; /* finalize the last column of C */ cs_sprealloc (C, 0) ; /* remove extra space from C */ return (cs_done (C, w, x, 1)) ; /* success; free workspace, return C */ } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_gaxpy.c0000644000076500000240000000246413524616145024001 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* y = A*x+y */ CS_INT cs_gaxpy (const cs *A, const CS_ENTRY *x, CS_ENTRY *y) { CS_INT p, j, n, *Ap, *Ai ; CS_ENTRY *Ax ; if (!CS_CSC (A) || !x || !y) return (0) ; /* check inputs */ n = A->n ; Ap = A->p ; Ai = A->i ; Ax = A->x ; for (j = 0 ; j < n ; j++) { for (p = Ap [j] ; p < Ap [j+1] ; p++) { y [Ai [p]] += Ax [p] * x [j] ; } } return (1) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_ltsolve.c0000644000076500000240000000264113524616145024336 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* solve L'x=b where x and b are dense. x=b on input, solution on output. */ CS_INT cs_ltsolve (const cs *L, CS_ENTRY *x) { CS_INT p, j, n, *Lp, *Li ; CS_ENTRY *Lx ; if (!CS_CSC (L) || !x) return (0) ; /* check inputs */ n = L->n ; Lp = L->p ; Li = L->i ; Lx = L->x ; for (j = n-1 ; j >= 0 ; j--) { for (p = Lp [j]+1 ; p < Lp [j+1] ; p++) { x [j] -= CS_CONJ (Lx [p]) * x [Li [p]] ; } x [j] /= CS_CONJ (Lx [Lp [j]]) ; } return (1) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_usolve.c0000644000076500000240000000261713524616145024166 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* solve Ux=b where x and b are dense. x=b on input, solution on output. */ CS_INT cs_usolve (const cs *U, CS_ENTRY *x) { CS_INT p, j, n, *Up, *Ui ; CS_ENTRY *Ux ; if (!CS_CSC (U) || !x) return (0) ; /* check inputs */ n = U->n ; Up = U->p ; Ui = U->i ; Ux = U->x ; for (j = n-1 ; j >= 0 ; j--) { x [j] /= Ux [Up [j+1]-1] ; for (p = Up [j] ; p < Up [j+1]-1 ; p++) { x [Ui [p]] -= Ux [p] * x [j] ; } } return (1) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_fkeep.c0000644000076500000240000000347713524616145023750 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* drop entries for which fkeep(A(i,j)) is false; return nz if OK, else -1 */ CS_INT cs_fkeep (cs *A, CS_INT (*fkeep) (CS_INT, CS_INT, CS_ENTRY, void *), void *other) { CS_INT j, p, nz = 0, n, *Ap, *Ai ; CS_ENTRY *Ax ; if (!CS_CSC (A) || !fkeep) return (-1) ; /* check inputs */ n = A->n ; Ap = A->p ; Ai = A->i ; Ax = A->x ; for (j = 0 ; j < n ; j++) { p = Ap [j] ; /* get current location of col j */ Ap [j] = nz ; /* record new location of col j */ for ( ; p < Ap [j+1] ; p++) { if (fkeep (Ai [p], j, Ax ? Ax [p] : 1, other)) { if (Ax) Ax [nz] = Ax [p] ; /* keep A(i,j) */ Ai [nz++] = Ai [p] ; } } } Ap [n] = nz ; /* finalize A */ cs_sprealloc (A, 0) ; /* remove extra space from A */ return (nz) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_spsolve.c0000644000076500000240000000435013524616145024340 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* solve Gx=b(:,k), where G is either upper (lo=0) or lower (lo=1) triangular */ CS_INT cs_spsolve (cs *G, const cs *B, CS_INT k, CS_INT *xi, CS_ENTRY *x, const CS_INT *pinv, CS_INT lo) { CS_INT j, J, p, q, px, top, n, *Gp, *Gi, *Bp, *Bi ; CS_ENTRY *Gx, *Bx ; if (!CS_CSC (G) || !CS_CSC (B) || !xi || !x) return (-1) ; Gp = G->p ; Gi = G->i ; Gx = G->x ; n = G->n ; Bp = B->p ; Bi = B->i ; Bx = B->x ; top = cs_reach (G, B, k, xi, pinv) ; /* xi[top..n-1]=Reach(B(:,k)) */ for (p = top ; p < n ; p++) x [xi [p]] = 0 ; /* clear x */ for (p = Bp [k] ; p < Bp [k+1] ; p++) x [Bi [p]] = Bx [p] ; /* scatter B */ for (px = top ; px < n ; px++) { j = xi [px] ; /* x(j) is nonzero */ J = pinv ? (pinv [j]) : j ; /* j maps to col J of G */ if (J < 0) continue ; /* column J is empty */ x [j] /= Gx [lo ? (Gp [J]) : (Gp [J+1]-1)] ;/* x(j) /= G(j,j) */ p = lo ? (Gp [J]+1) : (Gp [J]) ; /* lo: L(j,j) 1st entry */ q = lo ? (Gp [J+1]) : (Gp [J+1]-1) ; /* up: U(j,j) last entry */ for ( ; p < q ; p++) { x [Gi [p]] -= Gx [p] * x [j] ; /* x(i) -= G(i,j) * x(j) */ } } return (top) ; /* return top of stack */ } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_happly.c0000644000076500000240000000273313524616145024145 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* apply the ith Householder vector to x */ CS_INT cs_happly (const cs *V, CS_INT i, double beta, CS_ENTRY *x) { CS_INT p, *Vp, *Vi ; CS_ENTRY *Vx, tau = 0 ; if (!CS_CSC (V) || !x) return (0) ; /* check inputs */ Vp = V->p ; Vi = V->i ; Vx = V->x ; for (p = Vp [i] ; p < Vp [i+1] ; p++) /* tau = v'*x */ { tau += CS_CONJ (Vx [p]) * x [Vi [p]] ; } tau *= beta ; /* tau = beta*(v'*x) */ for (p = Vp [i] ; p < Vp [i+1] ; p++) /* x = x - v*tau */ { x [Vi [p]] -= Vx [p] * tau ; } return (1) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_ereach.c0000644000076500000240000000373413524616145024101 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* find nonzero pattern of Cholesky L(k,1:k-1) using etree and triu(A(:,k)) */ CS_INT cs_ereach (const cs *A, CS_INT k, const CS_INT *parent, CS_INT *s, CS_INT *w) { CS_INT i, p, n, len, top, *Ap, *Ai ; if (!CS_CSC (A) || !parent || !s || !w) return (-1) ; /* check inputs */ top = n = A->n ; Ap = A->p ; Ai = A->i ; CS_MARK (w, k) ; /* mark node k as visited */ for (p = Ap [k] ; p < Ap [k+1] ; p++) { i = Ai [p] ; /* A(i,k) is nonzero */ if (i > k) continue ; /* only use upper triangular part of A */ for (len = 0 ; !CS_MARKED (w,i) ; i = parent [i]) /* traverse up etree*/ { s [len++] = i ; /* L(k,i) is nonzero */ CS_MARK (w, i) ; /* mark i as visited */ } while (len > 0) s [--top] = s [--len] ; /* push path onto stack */ } for (p = top ; p < n ; p++) CS_MARK (w, s [p]) ; /* unmark all nodes */ CS_MARK (w, k) ; /* unmark node k */ return (top) ; /* s [top..n-1] contains pattern of L(k,:)*/ } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_sqr.c0000644000076500000240000001131013524616145023444 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* compute nnz(V) = S->lnz, S->pinv, S->leftmost, S->m2 from A and S->parent */ static CS_INT cs_vcount (const cs *A, css *S) { CS_INT i, k, p, pa, n = A->n, m = A->m, *Ap = A->p, *Ai = A->i, *next, *head, *tail, *nque, *pinv, *leftmost, *w, *parent = S->parent ; S->pinv = pinv = cs_malloc (m+n, sizeof (CS_INT)) ; /* allocate pinv, */ S->leftmost = leftmost = cs_malloc (m, sizeof (CS_INT)) ; /* and leftmost */ w = cs_malloc (m+3*n, sizeof (CS_INT)) ; /* get workspace */ if (!pinv || !w || !leftmost) { cs_free (w) ; /* pinv and leftmost freed later */ return (0) ; /* out of memory */ } next = w ; head = w + m ; tail = w + m + n ; nque = w + m + 2*n ; for (k = 0 ; k < n ; k++) head [k] = -1 ; /* queue k is empty */ for (k = 0 ; k < n ; k++) tail [k] = -1 ; for (k = 0 ; k < n ; k++) nque [k] = 0 ; for (i = 0 ; i < m ; i++) leftmost [i] = -1 ; for (k = n-1 ; k >= 0 ; k--) { for (p = Ap [k] ; p < Ap [k+1] ; p++) { leftmost [Ai [p]] = k ; /* leftmost[i] = min(find(A(i,:)))*/ } } for (i = m-1 ; i >= 0 ; i--) /* scan rows in reverse order */ { pinv [i] = -1 ; /* row i is not yet ordered */ k = leftmost [i] ; if (k == -1) continue ; /* row i is empty */ if (nque [k]++ == 0) tail [k] = i ; /* first row in queue k */ next [i] = head [k] ; /* put i at head of queue k */ head [k] = i ; } S->lnz = 0 ; S->m2 = m ; for (k = 0 ; k < n ; k++) /* find row permutation and nnz(V)*/ { i = head [k] ; /* remove row i from queue k */ S->lnz++ ; /* count V(k,k) as nonzero */ if (i < 0) i = S->m2++ ; /* add a fictitious row */ pinv [i] = k ; /* associate row i with V(:,k) */ if (--nque [k] <= 0) continue ; /* skip if V(k+1:m,k) is empty */ S->lnz += nque [k] ; /* nque [k] is nnz (V(k+1:m,k)) */ if ((pa = parent [k]) != -1) /* move all rows to parent of k */ { if (nque [pa] == 0) tail [pa] = tail [k] ; next [tail [k]] = head [pa] ; head [pa] = next [i] ; nque [pa] += nque [k] ; } } for (i = 0 ; i < m ; i++) if (pinv [i] < 0) pinv [i] = k++ ; cs_free (w) ; return (1) ; } /* symbolic ordering and analysis for QR or LU */ css *cs_sqr (CS_INT order, const cs *A, CS_INT qr) { CS_INT n, k, ok = 1, *post ; css *S ; if (!CS_CSC (A)) return (NULL) ; /* check inputs */ n = A->n ; S = cs_calloc (1, sizeof (css)) ; /* allocate result S */ if (!S) return (NULL) ; /* out of memory */ S->q = cs_amd (order, A) ; /* fill-reducing ordering */ if (order && !S->q) return (cs_sfree (S)) ; if (qr) /* QR symbolic analysis */ { cs *C = order ? cs_permute (A, NULL, S->q, 0) : ((cs *) A) ; S->parent = cs_etree (C, 1) ; /* etree of C'*C, where C=A(:,q) */ post = cs_post (S->parent, n) ; S->cp = cs_counts (C, S->parent, post, 1) ; /* col counts chol(C'*C) */ cs_free (post) ; ok = C && S->parent && S->cp && cs_vcount (C, S) ; if (ok) for (S->unz = 0, k = 0 ; k < n ; k++) S->unz += S->cp [k] ; ok = ok && S->lnz >= 0 && S->unz >= 0 ; /* CS_INT overflow guard */ if (order) cs_spfree (C) ; } else { S->unz = 4*(A->p [n]) + n ; /* for LU factorization only, */ S->lnz = S->unz ; /* guess nnz(L) and nnz(U) */ } return (ok ? S : cs_sfree (S)) ; /* return result S */ } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_amd.c0000644000076500000240000004201113524616144023401 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* clear w */ static CS_INT cs_wclear (CS_INT mark, CS_INT lemax, CS_INT *w, CS_INT n) { CS_INT k ; if (mark < 2 || (mark + lemax < 0)) { for (k = 0 ; k < n ; k++) if (w [k] != 0) w [k] = 1 ; mark = 2 ; } return (mark) ; /* at this point, w [0..n-1] < mark holds */ } /* keep off-diagonal entries; drop diagonal entries */ static CS_INT cs_diag (CS_INT i, CS_INT j, CS_ENTRY aij, void *other) { return (i != j) ; } /* p = amd(A+A') if symmetric is true, or amd(A'A) otherwise */ CS_INT *cs_amd (CS_INT order, const cs *A) /* order 0:natural, 1:Chol, 2:LU, 3:QR */ { cs *C, *A2, *AT ; CS_INT *Cp, *Ci, *last, *W, *len, *nv, *next, *P, *head, *elen, *degree, *w, *hhead, *ATp, *ATi, d, dk, dext, lemax = 0, e, elenk, eln, i, j, k, k1, k2, k3, jlast, ln, dense, nzmax, mindeg = 0, nvi, nvj, nvk, mark, wnvi, ok, cnz, nel = 0, p, p1, p2, p3, p4, pj, pk, pk1, pk2, pn, q, n, m, t ; unsigned CS_INT h ; /* --- Construct matrix C ----------------------------------------------- */ if (!CS_CSC (A) || order <= 0 || order > 3) return (NULL) ; /* check */ AT = cs_transpose (A, 0) ; /* compute A' */ if (!AT) return (NULL) ; m = A->m ; n = A->n ; dense = CS_MAX (16, 10 * sqrt ((double) n)) ; /* find dense threshold */ dense = CS_MIN (n-2, dense) ; if (order == 1 && n == m) { C = cs_add (A, AT, 0, 0) ; /* C = A+A' */ } else if (order == 2) { ATp = AT->p ; /* drop dense columns from AT */ ATi = AT->i ; for (p2 = 0, j = 0 ; j < m ; j++) { p = ATp [j] ; /* column j of AT starts here */ ATp [j] = p2 ; /* new column j starts here */ if (ATp [j+1] - p > dense) continue ; /* skip dense col j */ for ( ; p < ATp [j+1] ; p++) ATi [p2++] = ATi [p] ; } ATp [m] = p2 ; /* finalize AT */ A2 = cs_transpose (AT, 0) ; /* A2 = AT' */ C = A2 ? cs_multiply (AT, A2) : NULL ; /* C=A'*A with no dense rows */ cs_spfree (A2) ; } else { C = cs_multiply (AT, A) ; /* C=A'*A */ } cs_spfree (AT) ; if (!C) return (NULL) ; cs_fkeep (C, &cs_diag, NULL) ; /* drop diagonal entries */ Cp = C->p ; cnz = Cp [n] ; P = cs_malloc (n+1, sizeof (CS_INT)) ; /* allocate result */ W = cs_malloc (8*(n+1), sizeof (CS_INT)) ; /* get workspace */ t = cnz + cnz/5 + 2*n ; /* add elbow room to C */ if (!P || !W || !cs_sprealloc (C, t)) return (cs_idone (P, C, W, 0)) ; len = W ; nv = W + (n+1) ; next = W + 2*(n+1) ; head = W + 3*(n+1) ; elen = W + 4*(n+1) ; degree = W + 5*(n+1) ; w = W + 6*(n+1) ; hhead = W + 7*(n+1) ; last = P ; /* use P as workspace for last */ /* --- Initialize quotient graph ---------------------------------------- */ for (k = 0 ; k < n ; k++) len [k] = Cp [k+1] - Cp [k] ; len [n] = 0 ; nzmax = C->nzmax ; Ci = C->i ; for (i = 0 ; i <= n ; i++) { head [i] = -1 ; /* degree list i is empty */ last [i] = -1 ; next [i] = -1 ; hhead [i] = -1 ; /* hash list i is empty */ nv [i] = 1 ; /* node i is just one node */ w [i] = 1 ; /* node i is alive */ elen [i] = 0 ; /* Ek of node i is empty */ degree [i] = len [i] ; /* degree of node i */ } mark = cs_wclear (0, 0, w, n) ; /* clear w */ elen [n] = -2 ; /* n is a dead element */ Cp [n] = -1 ; /* n is a root of assembly tree */ w [n] = 0 ; /* n is a dead element */ /* --- Initialize degree lists ------------------------------------------ */ for (i = 0 ; i < n ; i++) { d = degree [i] ; if (d == 0) /* node i is empty */ { elen [i] = -2 ; /* element i is dead */ nel++ ; Cp [i] = -1 ; /* i is a root of assembly tree */ w [i] = 0 ; } else if (d > dense) /* node i is dense */ { nv [i] = 0 ; /* absorb i into element n */ elen [i] = -1 ; /* node i is dead */ nel++ ; Cp [i] = CS_FLIP (n) ; nv [n]++ ; } else { if (head [d] != -1) last [head [d]] = i ; next [i] = head [d] ; /* put node i in degree list d */ head [d] = i ; } } while (nel < n) /* while (selecting pivots) do */ { /* --- Select node of minimum approximate degree -------------------- */ for (k = -1 ; mindeg < n && (k = head [mindeg]) == -1 ; mindeg++) ; if (next [k] != -1) last [next [k]] = -1 ; head [mindeg] = next [k] ; /* remove k from degree list */ elenk = elen [k] ; /* elenk = |Ek| */ nvk = nv [k] ; /* # of nodes k represents */ nel += nvk ; /* nv[k] nodes of A eliminated */ /* --- Garbage collection ------------------------------------------- */ if (elenk > 0 && cnz + mindeg >= nzmax) { for (j = 0 ; j < n ; j++) { if ((p = Cp [j]) >= 0) /* j is a live node or element */ { Cp [j] = Ci [p] ; /* save first entry of object */ Ci [p] = CS_FLIP (j) ; /* first entry is now CS_FLIP(j) */ } } for (q = 0, p = 0 ; p < cnz ; ) /* scan all of memory */ { if ((j = CS_FLIP (Ci [p++])) >= 0) /* found object j */ { Ci [q] = Cp [j] ; /* restore first entry of object */ Cp [j] = q++ ; /* new pointer to object j */ for (k3 = 0 ; k3 < len [j]-1 ; k3++) Ci [q++] = Ci [p++] ; } } cnz = q ; /* Ci [cnz...nzmax-1] now free */ } /* --- Construct new element ---------------------------------------- */ dk = 0 ; nv [k] = -nvk ; /* flag k as in Lk */ p = Cp [k] ; pk1 = (elenk == 0) ? p : cnz ; /* do in place if elen[k] == 0 */ pk2 = pk1 ; for (k1 = 1 ; k1 <= elenk + 1 ; k1++) { if (k1 > elenk) { e = k ; /* search the nodes in k */ pj = p ; /* list of nodes starts at Ci[pj]*/ ln = len [k] - elenk ; /* length of list of nodes in k */ } else { e = Ci [p++] ; /* search the nodes in e */ pj = Cp [e] ; ln = len [e] ; /* length of list of nodes in e */ } for (k2 = 1 ; k2 <= ln ; k2++) { i = Ci [pj++] ; if ((nvi = nv [i]) <= 0) continue ; /* node i dead, or seen */ dk += nvi ; /* degree[Lk] += size of node i */ nv [i] = -nvi ; /* negate nv[i] to denote i in Lk*/ Ci [pk2++] = i ; /* place i in Lk */ if (next [i] != -1) last [next [i]] = last [i] ; if (last [i] != -1) /* remove i from degree list */ { next [last [i]] = next [i] ; } else { head [degree [i]] = next [i] ; } } if (e != k) { Cp [e] = CS_FLIP (k) ; /* absorb e into k */ w [e] = 0 ; /* e is now a dead element */ } } if (elenk != 0) cnz = pk2 ; /* Ci [cnz...nzmax] is free */ degree [k] = dk ; /* external degree of k - |Lk\i| */ Cp [k] = pk1 ; /* element k is in Ci[pk1..pk2-1] */ len [k] = pk2 - pk1 ; elen [k] = -2 ; /* k is now an element */ /* --- Find set differences ----------------------------------------- */ mark = cs_wclear (mark, lemax, w, n) ; /* clear w if necessary */ for (pk = pk1 ; pk < pk2 ; pk++) /* scan 1: find |Le\Lk| */ { i = Ci [pk] ; if ((eln = elen [i]) <= 0) continue ;/* skip if elen[i] empty */ nvi = -nv [i] ; /* nv [i] was negated */ wnvi = mark - nvi ; for (p = Cp [i] ; p <= Cp [i] + eln - 1 ; p++) /* scan Ei */ { e = Ci [p] ; if (w [e] >= mark) { w [e] -= nvi ; /* decrement |Le\Lk| */ } else if (w [e] != 0) /* ensure e is a live element */ { w [e] = degree [e] + wnvi ; /* 1st time e seen in scan 1 */ } } } /* --- Degree update ------------------------------------------------ */ for (pk = pk1 ; pk < pk2 ; pk++) /* scan2: degree update */ { i = Ci [pk] ; /* consider node i in Lk */ p1 = Cp [i] ; p2 = p1 + elen [i] - 1 ; pn = p1 ; for (h = 0, d = 0, p = p1 ; p <= p2 ; p++) /* scan Ei */ { e = Ci [p] ; if (w [e] != 0) /* e is an unabsorbed element */ { dext = w [e] - mark ; /* dext = |Le\Lk| */ if (dext > 0) { d += dext ; /* sum up the set differences */ Ci [pn++] = e ; /* keep e in Ei */ h += e ; /* compute the hash of node i */ } else { Cp [e] = CS_FLIP (k) ; /* aggressive absorb. e->k */ w [e] = 0 ; /* e is a dead element */ } } } elen [i] = pn - p1 + 1 ; /* elen[i] = |Ei| */ p3 = pn ; p4 = p1 + len [i] ; for (p = p2 + 1 ; p < p4 ; p++) /* prune edges in Ai */ { j = Ci [p] ; if ((nvj = nv [j]) <= 0) continue ; /* node j dead or in Lk */ d += nvj ; /* degree(i) += |j| */ Ci [pn++] = j ; /* place j in node list of i */ h += j ; /* compute hash for node i */ } if (d == 0) /* check for mass elimination */ { Cp [i] = CS_FLIP (k) ; /* absorb i into k */ nvi = -nv [i] ; dk -= nvi ; /* |Lk| -= |i| */ nvk += nvi ; /* |k| += nv[i] */ nel += nvi ; nv [i] = 0 ; elen [i] = -1 ; /* node i is dead */ } else { degree [i] = CS_MIN (degree [i], d) ; /* update degree(i) */ Ci [pn] = Ci [p3] ; /* move first node to end */ Ci [p3] = Ci [p1] ; /* move 1st el. to end of Ei */ Ci [p1] = k ; /* add k as 1st element in of Ei */ len [i] = pn - p1 + 1 ; /* new len of adj. list of node i */ h %= n ; /* finalize hash of i */ next [i] = hhead [h] ; /* place i in hash bucket */ hhead [h] = i ; last [i] = h ; /* save hash of i in last[i] */ } } /* scan2 is done */ degree [k] = dk ; /* finalize |Lk| */ lemax = CS_MAX (lemax, dk) ; mark = cs_wclear (mark+lemax, lemax, w, n) ; /* clear w */ /* --- Supernode detection ------------------------------------------ */ for (pk = pk1 ; pk < pk2 ; pk++) { i = Ci [pk] ; if (nv [i] >= 0) continue ; /* skip if i is dead */ h = last [i] ; /* scan hash bucket of node i */ i = hhead [h] ; hhead [h] = -1 ; /* hash bucket will be empty */ for ( ; i != -1 && next [i] != -1 ; i = next [i], mark++) { ln = len [i] ; eln = elen [i] ; for (p = Cp [i]+1 ; p <= Cp [i] + ln-1 ; p++) w [Ci [p]] = mark; jlast = i ; for (j = next [i] ; j != -1 ; ) /* compare i with all j */ { ok = (len [j] == ln) && (elen [j] == eln) ; for (p = Cp [j] + 1 ; ok && p <= Cp [j] + ln - 1 ; p++) { if (w [Ci [p]] != mark) ok = 0 ; /* compare i and j*/ } if (ok) /* i and j are identical */ { Cp [j] = CS_FLIP (i) ; /* absorb j into i */ nv [i] += nv [j] ; nv [j] = 0 ; elen [j] = -1 ; /* node j is dead */ j = next [j] ; /* delete j from hash bucket */ next [jlast] = j ; } else { jlast = j ; /* j and i are different */ j = next [j] ; } } } } /* --- Finalize new element------------------------------------------ */ for (p = pk1, pk = pk1 ; pk < pk2 ; pk++) /* finalize Lk */ { i = Ci [pk] ; if ((nvi = -nv [i]) <= 0) continue ;/* skip if i is dead */ nv [i] = nvi ; /* restore nv[i] */ d = degree [i] + dk - nvi ; /* compute external degree(i) */ d = CS_MIN (d, n - nel - nvi) ; if (head [d] != -1) last [head [d]] = i ; next [i] = head [d] ; /* put i back in degree list */ last [i] = -1 ; head [d] = i ; mindeg = CS_MIN (mindeg, d) ; /* find new minimum degree */ degree [i] = d ; Ci [p++] = i ; /* place i in Lk */ } nv [k] = nvk ; /* # nodes absorbed into k */ if ((len [k] = p-pk1) == 0) /* length of adj list of element k*/ { Cp [k] = -1 ; /* k is a root of the tree */ w [k] = 0 ; /* k is now a dead element */ } if (elenk != 0) cnz = p ; /* free unused space in Lk */ } /* --- Postordering ----------------------------------------------------- */ for (i = 0 ; i < n ; i++) Cp [i] = CS_FLIP (Cp [i]) ;/* fix assembly tree */ for (j = 0 ; j <= n ; j++) head [j] = -1 ; for (j = n ; j >= 0 ; j--) /* place unordered nodes in lists */ { if (nv [j] > 0) continue ; /* skip if j is an element */ next [j] = head [Cp [j]] ; /* place j in list of its parent */ head [Cp [j]] = j ; } for (e = n ; e >= 0 ; e--) /* place elements in lists */ { if (nv [e] <= 0) continue ; /* skip unless e is an element */ if (Cp [e] != -1) { next [e] = head [Cp [e]] ; /* place e in list of its parent */ head [Cp [e]] = e ; } } for (k = 0, i = 0 ; i <= n ; i++) /* postorder the assembly tree */ { if (Cp [i] == -1) k = cs_tdfs (i, k, head, next, P, w) ; } return (cs_idone (P, C, W, 1)) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_cumsum.c0000644000076500000240000000270113524616145024154 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* p [0..n] = cumulative sum of c [0..n-1], and then copy p [0..n-1] into c */ double cs_cumsum (CS_INT *p, CS_INT *c, CS_INT n) { CS_INT i, nz = 0 ; double nz2 = 0 ; if (!p || !c) return (-1) ; /* check inputs */ for (i = 0 ; i < n ; i++) { p [i] = nz ; nz += c [i] ; nz2 += c [i] ; /* also in double to avoid CS_INT overflow */ c [i] = p [i] ; /* also copy p[0..n-1] back into c[0..n-1]*/ } p [n] = nz ; return (nz2) ; /* return sum (c [0..n-1]) */ } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_dropzeros.c0000644000076500000240000000214313524616145024672 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" static CS_INT cs_nonzero (CS_INT i, CS_INT j, CS_ENTRY aij, void *other) { return (aij != 0) ; } CS_INT cs_dropzeros (cs *A) { return (cs_fkeep (A, &cs_nonzero, NULL)) ; /* keep all nonzero entries */ } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_permute.c0000644000076500000240000000362513524616145024332 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* C = A(p,q) where p and q are permutations of 0..m-1 and 0..n-1. */ cs *cs_permute (const cs *A, const CS_INT *pinv, const CS_INT *q, CS_INT values) { CS_INT t, j, k, nz = 0, m, n, *Ap, *Ai, *Cp, *Ci ; CS_ENTRY *Cx, *Ax ; cs *C ; if (!CS_CSC (A)) return (NULL) ; /* check inputs */ m = A->m ; n = A->n ; Ap = A->p ; Ai = A->i ; Ax = A->x ; C = cs_spalloc (m, n, Ap [n], values && Ax != NULL, 0) ; /* alloc result */ if (!C) return (cs_done (C, NULL, NULL, 0)) ; /* out of memory */ Cp = C->p ; Ci = C->i ; Cx = C->x ; for (k = 0 ; k < n ; k++) { Cp [k] = nz ; /* column k of C is column q[k] of A */ j = q ? (q [k]) : k ; for (t = Ap [j] ; t < Ap [j+1] ; t++) { if (Cx) Cx [nz] = Ax [t] ; /* row i of A is row pinv[i] of C */ Ci [nz++] = pinv ? (pinv [Ai [t]]) : Ai [t] ; } } Cp [n] = nz ; /* finalize the last column of C */ return (cs_done (C, NULL, NULL, 1)) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_house.c0000644000076500000240000000334013524616145023766 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* create a Householder reflection [v,beta,s]=house(x), overwrite x with v, * where (I-beta*v*v')*x = s*e1 and e1 = [1 0 ... 0]'. * Note that this CXSparse version is different than CSparse. See Higham, * Accuracy & Stability of Num Algorithms, 2nd ed, 2002, page 357. */ CS_ENTRY cs_house (CS_ENTRY *x, double *beta, CS_INT n) { CS_ENTRY s = 0 ; CS_INT i ; if (!x || !beta) return (-1) ; /* check inputs */ /* s = norm(x) */ for (i = 0 ; i < n ; i++) s += x [i] * CS_CONJ (x [i]) ; s = sqrt (s) ; if (s == 0) { (*beta) = 0 ; x [0] = 1 ; } else { /* s = sign(x[0]) * norm (x) ; */ if (x [0] != 0) { s *= x [0] / CS_ABS (x [0]) ; } x [0] += s ; (*beta) = 1. / CS_REAL (CS_CONJ (s) * x [0]) ; } return (-s) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs.h0000644000076500000240000007620513524616144022601 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef _CXS_H #define _CXS_H #include #include #include #include #ifdef MATLAB_MEX_FILE #include "mex.h" #endif #ifdef __cplusplus #ifndef NCOMPLEX #include typedef std::complex cs_complex_t ; #endif extern "C" { #else #ifndef NCOMPLEX #include #define cs_complex_t double _Complex #endif #endif #define CS_VER 2 /* CXSparse Version 2.2.3 */ #define CS_SUBVER 2 #define CS_SUBSUB 3 #define CS_DATE "Mar 24, 2009" /* CXSparse release date */ #define CS_COPYRIGHT "Copyright (c) Timothy A. Davis, 2006-2009" #define CXSPARSE /* define UF_long */ #include "UFconfig.h" /* -------------------------------------------------------------------------- */ /* double/int version of CXSparse */ /* -------------------------------------------------------------------------- */ /* --- primary CSparse routines and data structures ------------------------- */ typedef struct cs_di_sparse /* matrix in compressed-column or triplet form */ { int nzmax ; /* maximum number of entries */ int m ; /* number of rows */ int n ; /* number of columns */ int *p ; /* column pointers (size n+1) or col indices (size nzmax) */ int *i ; /* row indices, size nzmax */ double *x ; /* numerical values, size nzmax */ int nz ; /* # of entries in triplet matrix, -1 for compressed-col */ } cs_di ; cs_di *cs_di_add (const cs_di *A, const cs_di *B, double alpha, double beta) ; int cs_di_cholsol (int order, const cs_di *A, double *b) ; int cs_di_dupl (cs_di *A) ; int cs_di_entry (cs_di *T, int i, int j, double x) ; int cs_di_lusol (int order, const cs_di *A, double *b, double tol) ; int cs_di_gaxpy (const cs_di *A, const double *x, double *y) ; cs_di *cs_di_multiply (const cs_di *A, const cs_di *B) ; int cs_di_qrsol (int order, const cs_di *A, double *b) ; cs_di *cs_di_transpose (const cs_di *A, int values) ; cs_di *cs_di_compress (const cs_di *T) ; double cs_di_norm (const cs_di *A) ; int cs_di_print (const cs_di *A, int brief) ; cs_di *cs_di_load (FILE *f) ; /* utilities */ void *cs_di_calloc (int n, size_t size) ; void *cs_di_free (void *p) ; void *cs_di_realloc (void *p, int n, size_t size, int *ok) ; cs_di *cs_di_spalloc (int m, int n, int nzmax, int values, int t) ; cs_di *cs_di_spfree (cs_di *A) ; int cs_di_sprealloc (cs_di *A, int nzmax) ; void *cs_di_malloc (int n, size_t size) ; /* --- secondary CSparse routines and data structures ----------------------- */ typedef struct cs_di_symbolic /* symbolic Cholesky, LU, or QR analysis */ { int *pinv ; /* inverse row perm. for QR, fill red. perm for Chol */ int *q ; /* fill-reducing column permutation for LU and QR */ int *parent ; /* elimination tree for Cholesky and QR */ int *cp ; /* column pointers for Cholesky, row counts for QR */ int *leftmost ; /* leftmost[i] = min(find(A(i,:))), for QR */ int m2 ; /* # of rows for QR, after adding fictitious rows */ double lnz ; /* # entries in L for LU or Cholesky; in V for QR */ double unz ; /* # entries in U for LU; in R for QR */ } cs_dis ; typedef struct cs_di_numeric /* numeric Cholesky, LU, or QR factorization */ { cs_di *L ; /* L for LU and Cholesky, V for QR */ cs_di *U ; /* U for LU, r for QR, not used for Cholesky */ int *pinv ; /* partial pivoting for LU */ double *B ; /* beta [0..n-1] for QR */ } cs_din ; typedef struct cs_di_dmperm_results /* cs_di_dmperm or cs_di_scc output */ { int *p ; /* size m, row permutation */ int *q ; /* size n, column permutation */ int *r ; /* size nb+1, block k is rows r[k] to r[k+1]-1 in A(p,q) */ int *s ; /* size nb+1, block k is cols s[k] to s[k+1]-1 in A(p,q) */ int nb ; /* # of blocks in fine dmperm decomposition */ int rr [5] ; /* coarse row decomposition */ int cc [5] ; /* coarse column decomposition */ } cs_did ; int *cs_di_amd (int order, const cs_di *A) ; cs_din *cs_di_chol (const cs_di *A, const cs_dis *S) ; cs_did *cs_di_dmperm (const cs_di *A, int seed) ; int cs_di_droptol (cs_di *A, double tol) ; int cs_di_dropzeros (cs_di *A) ; int cs_di_happly (const cs_di *V, int i, double beta, double *x) ; int cs_di_ipvec (const int *p, const double *b, double *x, int n) ; int cs_di_lsolve (const cs_di *L, double *x) ; int cs_di_ltsolve (const cs_di *L, double *x) ; cs_din *cs_di_lu (const cs_di *A, const cs_dis *S, double tol) ; cs_di *cs_di_permute (const cs_di *A, const int *pinv, const int *q, int values) ; int *cs_di_pinv (const int *p, int n) ; int cs_di_pvec (const int *p, const double *b, double *x, int n) ; cs_din *cs_di_qr (const cs_di *A, const cs_dis *S) ; cs_dis *cs_di_schol (int order, const cs_di *A) ; cs_dis *cs_di_sqr (int order, const cs_di *A, int qr) ; cs_di *cs_di_symperm (const cs_di *A, const int *pinv, int values) ; int cs_di_usolve (const cs_di *U, double *x) ; int cs_di_utsolve (const cs_di *U, double *x) ; int cs_di_updown (cs_di *L, int sigma, const cs_di *C, const int *parent) ; /* utilities */ cs_dis *cs_di_sfree (cs_dis *S) ; cs_din *cs_di_nfree (cs_din *N) ; cs_did *cs_di_dfree (cs_did *D) ; /* --- tertiary CSparse routines -------------------------------------------- */ int *cs_di_counts (const cs_di *A, const int *parent, const int *post, int ata) ; double cs_di_cumsum (int *p, int *c, int n) ; int cs_di_dfs (int j, cs_di *G, int top, int *xi, int *pstack, const int *pinv) ; int *cs_di_etree (const cs_di *A, int ata) ; int cs_di_fkeep (cs_di *A, int (*fkeep) (int, int, double, void *), void *other) ; double cs_di_house (double *x, double *beta, int n) ; int *cs_di_maxtrans (const cs_di *A, int seed) ; int *cs_di_post (const int *parent, int n) ; cs_did *cs_di_scc (cs_di *A) ; int cs_di_scatter (const cs_di *A, int j, double beta, int *w, double *x, int mark, cs_di *C, int nz) ; int cs_di_tdfs (int j, int k, int *head, const int *next, int *post, int *stack) ; int cs_di_leaf (int i, int j, const int *first, int *maxfirst, int *prevleaf, int *ancestor, int *jleaf) ; int cs_di_reach (cs_di *G, const cs_di *B, int k, int *xi, const int *pinv) ; int cs_di_spsolve (cs_di *L, const cs_di *B, int k, int *xi, double *x, const int *pinv, int lo) ; int cs_di_ereach (const cs_di *A, int k, const int *parent, int *s, int *w) ; int *cs_di_randperm (int n, int seed) ; /* utilities */ cs_did *cs_di_dalloc (int m, int n) ; cs_di *cs_di_done (cs_di *C, void *w, void *x, int ok) ; int *cs_di_idone (int *p, cs_di *C, void *w, int ok) ; cs_din *cs_di_ndone (cs_din *N, cs_di *C, void *w, void *x, int ok) ; cs_did *cs_di_ddone (cs_did *D, cs_di *C, void *w, int ok) ; /* -------------------------------------------------------------------------- */ /* double/UF_long version of CXSparse */ /* -------------------------------------------------------------------------- */ /* --- primary CSparse routines and data structures ------------------------- */ typedef struct cs_dl_sparse /* matrix in compressed-column or triplet form */ { UF_long nzmax ; /* maximum number of entries */ UF_long m ; /* number of rows */ UF_long n ; /* number of columns */ UF_long *p ; /* column pointers (size n+1) or col indlces (size nzmax) */ UF_long *i ; /* row indices, size nzmax */ double *x ; /* numerical values, size nzmax */ UF_long nz ; /* # of entries in triplet matrix, -1 for compressed-col */ } cs_dl ; cs_dl *cs_dl_add (const cs_dl *A, const cs_dl *B, double alpha, double beta) ; UF_long cs_dl_cholsol (UF_long order, const cs_dl *A, double *b) ; UF_long cs_dl_dupl (cs_dl *A) ; UF_long cs_dl_entry (cs_dl *T, UF_long i, UF_long j, double x) ; UF_long cs_dl_lusol (UF_long order, const cs_dl *A, double *b, double tol) ; UF_long cs_dl_gaxpy (const cs_dl *A, const double *x, double *y) ; cs_dl *cs_dl_multiply (const cs_dl *A, const cs_dl *B) ; UF_long cs_dl_qrsol (UF_long order, const cs_dl *A, double *b) ; cs_dl *cs_dl_transpose (const cs_dl *A, UF_long values) ; cs_dl *cs_dl_compress (const cs_dl *T) ; double cs_dl_norm (const cs_dl *A) ; UF_long cs_dl_print (const cs_dl *A, UF_long brief) ; cs_dl *cs_dl_load (FILE *f) ; /* utilities */ void *cs_dl_calloc (UF_long n, size_t size) ; void *cs_dl_free (void *p) ; void *cs_dl_realloc (void *p, UF_long n, size_t size, UF_long *ok) ; cs_dl *cs_dl_spalloc (UF_long m, UF_long n, UF_long nzmax, UF_long values, UF_long t) ; cs_dl *cs_dl_spfree (cs_dl *A) ; UF_long cs_dl_sprealloc (cs_dl *A, UF_long nzmax) ; void *cs_dl_malloc (UF_long n, size_t size) ; /* --- secondary CSparse routines and data structures ----------------------- */ typedef struct cs_dl_symbolic /* symbolic Cholesky, LU, or QR analysis */ { UF_long *pinv ; /* inverse row perm. for QR, fill red. perm for Chol */ UF_long *q ; /* fill-reducing column permutation for LU and QR */ UF_long *parent ; /* elimination tree for Cholesky and QR */ UF_long *cp ; /* column pointers for Cholesky, row counts for QR */ UF_long *leftmost ; /* leftmost[i] = min(find(A(i,:))), for QR */ UF_long m2 ; /* # of rows for QR, after adding fictitious rows */ double lnz ; /* # entries in L for LU or Cholesky; in V for QR */ double unz ; /* # entries in U for LU; in R for QR */ } cs_dls ; typedef struct cs_dl_numeric /* numeric Cholesky, LU, or QR factorization */ { cs_dl *L ; /* L for LU and Cholesky, V for QR */ cs_dl *U ; /* U for LU, r for QR, not used for Cholesky */ UF_long *pinv ; /* partial pivoting for LU */ double *B ; /* beta [0..n-1] for QR */ } cs_dln ; typedef struct cs_dl_dmperm_results /* cs_dl_dmperm or cs_dl_scc output */ { UF_long *p ; /* size m, row permutation */ UF_long *q ; /* size n, column permutation */ UF_long *r ; /* size nb+1, block k is rows r[k] to r[k+1]-1 in A(p,q) */ UF_long *s ; /* size nb+1, block k is cols s[k] to s[k+1]-1 in A(p,q) */ UF_long nb ; /* # of blocks in fine dmperm decomposition */ UF_long rr [5] ; /* coarse row decomposition */ UF_long cc [5] ; /* coarse column decomposition */ } cs_dld ; UF_long *cs_dl_amd (UF_long order, const cs_dl *A) ; cs_dln *cs_dl_chol (const cs_dl *A, const cs_dls *S) ; cs_dld *cs_dl_dmperm (const cs_dl *A, UF_long seed) ; UF_long cs_dl_droptol (cs_dl *A, double tol) ; UF_long cs_dl_dropzeros (cs_dl *A) ; UF_long cs_dl_happly (const cs_dl *V, UF_long i, double beta, double *x) ; UF_long cs_dl_ipvec (const UF_long *p, const double *b, double *x, UF_long n) ; UF_long cs_dl_lsolve (const cs_dl *L, double *x) ; UF_long cs_dl_ltsolve (const cs_dl *L, double *x) ; cs_dln *cs_dl_lu (const cs_dl *A, const cs_dls *S, double tol) ; cs_dl *cs_dl_permute (const cs_dl *A, const UF_long *pinv, const UF_long *q, UF_long values) ; UF_long *cs_dl_pinv (const UF_long *p, UF_long n) ; UF_long cs_dl_pvec (const UF_long *p, const double *b, double *x, UF_long n) ; cs_dln *cs_dl_qr (const cs_dl *A, const cs_dls *S) ; cs_dls *cs_dl_schol (UF_long order, const cs_dl *A) ; cs_dls *cs_dl_sqr (UF_long order, const cs_dl *A, UF_long qr) ; cs_dl *cs_dl_symperm (const cs_dl *A, const UF_long *pinv, UF_long values) ; UF_long cs_dl_usolve (const cs_dl *U, double *x) ; UF_long cs_dl_utsolve (const cs_dl *U, double *x) ; UF_long cs_dl_updown (cs_dl *L, UF_long sigma, const cs_dl *C, const UF_long *parent) ; /* utilities */ cs_dls *cs_dl_sfree (cs_dls *S) ; cs_dln *cs_dl_nfree (cs_dln *N) ; cs_dld *cs_dl_dfree (cs_dld *D) ; /* --- tertiary CSparse routines -------------------------------------------- */ UF_long *cs_dl_counts (const cs_dl *A, const UF_long *parent, const UF_long *post, UF_long ata) ; double cs_dl_cumsum (UF_long *p, UF_long *c, UF_long n) ; UF_long cs_dl_dfs (UF_long j, cs_dl *G, UF_long top, UF_long *xi, UF_long *pstack, const UF_long *pinv) ; UF_long *cs_dl_etree (const cs_dl *A, UF_long ata) ; UF_long cs_dl_fkeep (cs_dl *A, UF_long (*fkeep) (UF_long, UF_long, double, void *), void *other) ; double cs_dl_house (double *x, double *beta, UF_long n) ; UF_long *cs_dl_maxtrans (const cs_dl *A, UF_long seed) ; UF_long *cs_dl_post (const UF_long *parent, UF_long n) ; cs_dld *cs_dl_scc (cs_dl *A) ; UF_long cs_dl_scatter (const cs_dl *A, UF_long j, double beta, UF_long *w, double *x, UF_long mark,cs_dl *C, UF_long nz) ; UF_long cs_dl_tdfs (UF_long j, UF_long k, UF_long *head, const UF_long *next, UF_long *post, UF_long *stack) ; UF_long cs_dl_leaf (UF_long i, UF_long j, const UF_long *first, UF_long *maxfirst, UF_long *prevleaf, UF_long *ancestor, UF_long *jleaf) ; UF_long cs_dl_reach (cs_dl *G, const cs_dl *B, UF_long k, UF_long *xi, const UF_long *pinv) ; UF_long cs_dl_spsolve (cs_dl *L, const cs_dl *B, UF_long k, UF_long *xi, double *x, const UF_long *pinv, UF_long lo) ; UF_long cs_dl_ereach (const cs_dl *A, UF_long k, const UF_long *parent, UF_long *s, UF_long *w) ; UF_long *cs_dl_randperm (UF_long n, UF_long seed) ; /* utilities */ cs_dld *cs_dl_dalloc (UF_long m, UF_long n) ; cs_dl *cs_dl_done (cs_dl *C, void *w, void *x, UF_long ok) ; UF_long *cs_dl_idone (UF_long *p, cs_dl *C, void *w, UF_long ok) ; cs_dln *cs_dl_ndone (cs_dln *N, cs_dl *C, void *w, void *x, UF_long ok) ; cs_dld *cs_dl_ddone (cs_dld *D, cs_dl *C, void *w, UF_long ok) ; /* -------------------------------------------------------------------------- */ /* complex/int version of CXSparse */ /* -------------------------------------------------------------------------- */ #ifndef NCOMPLEX /* --- primary CSparse routines and data structures ------------------------- */ typedef struct cs_ci_sparse /* matrix in compressed-column or triplet form */ { int nzmax ; /* maximum number of entries */ int m ; /* number of rows */ int n ; /* number of columns */ int *p ; /* column pointers (size n+1) or col indices (size nzmax) */ int *i ; /* row indices, size nzmax */ cs_complex_t *x ; /* numerical values, size nzmax */ int nz ; /* # of entries in triplet matrix, -1 for compressed-col */ } cs_ci ; cs_ci *cs_ci_add (const cs_ci *A, const cs_ci *B, cs_complex_t alpha, cs_complex_t beta) ; int cs_ci_cholsol (int order, const cs_ci *A, cs_complex_t *b) ; int cs_ci_dupl (cs_ci *A) ; int cs_ci_entry (cs_ci *T, int i, int j, cs_complex_t x) ; int cs_ci_lusol (int order, const cs_ci *A, cs_complex_t *b, double tol) ; int cs_ci_gaxpy (const cs_ci *A, const cs_complex_t *x, cs_complex_t *y) ; cs_ci *cs_ci_multiply (const cs_ci *A, const cs_ci *B) ; int cs_ci_qrsol (int order, const cs_ci *A, cs_complex_t *b) ; cs_ci *cs_ci_transpose (const cs_ci *A, int values) ; cs_ci *cs_ci_compress (const cs_ci *T) ; double cs_ci_norm (const cs_ci *A) ; int cs_ci_print (const cs_ci *A, int brief) ; cs_ci *cs_ci_load (FILE *f) ; /* utilities */ void *cs_ci_calloc (int n, size_t size) ; void *cs_ci_free (void *p) ; void *cs_ci_realloc (void *p, int n, size_t size, int *ok) ; cs_ci *cs_ci_spalloc (int m, int n, int nzmax, int values, int t) ; cs_ci *cs_ci_spfree (cs_ci *A) ; int cs_ci_sprealloc (cs_ci *A, int nzmax) ; void *cs_ci_malloc (int n, size_t size) ; /* --- secondary CSparse routines and data structures ----------------------- */ typedef struct cs_ci_symbolic /* symbolic Cholesky, LU, or QR analysis */ { int *pinv ; /* inverse row perm. for QR, fill red. perm for Chol */ int *q ; /* fill-reducing column permutation for LU and QR */ int *parent ; /* elimination tree for Cholesky and QR */ int *cp ; /* column pointers for Cholesky, row counts for QR */ int *leftmost ; /* leftmost[i] = min(find(A(i,:))), for QR */ int m2 ; /* # of rows for QR, after adding fictitious rows */ double lnz ; /* # entries in L for LU or Cholesky; in V for QR */ double unz ; /* # entries in U for LU; in R for QR */ } cs_cis ; typedef struct cs_ci_numeric /* numeric Cholesky, LU, or QR factorization */ { cs_ci *L ; /* L for LU and Cholesky, V for QR */ cs_ci *U ; /* U for LU, r for QR, not used for Cholesky */ int *pinv ; /* partial pivoting for LU */ double *B ; /* beta [0..n-1] for QR */ } cs_cin ; typedef struct cs_ci_dmperm_results /* cs_ci_dmperm or cs_ci_scc output */ { int *p ; /* size m, row permutation */ int *q ; /* size n, column permutation */ int *r ; /* size nb+1, block k is rows r[k] to r[k+1]-1 in A(p,q) */ int *s ; /* size nb+1, block k is cols s[k] to s[k+1]-1 in A(p,q) */ int nb ; /* # of blocks in fine dmperm decomposition */ int rr [5] ; /* coarse row decomposition */ int cc [5] ; /* coarse column decomposition */ } cs_cid ; int *cs_ci_amd (int order, const cs_ci *A) ; cs_cin *cs_ci_chol (const cs_ci *A, const cs_cis *S) ; cs_cid *cs_ci_dmperm (const cs_ci *A, int seed) ; int cs_ci_droptol (cs_ci *A, double tol) ; int cs_ci_dropzeros (cs_ci *A) ; int cs_ci_happly (const cs_ci *V, int i, double beta, cs_complex_t *x) ; int cs_ci_ipvec (const int *p, const cs_complex_t *b, cs_complex_t *x, int n) ; int cs_ci_lsolve (const cs_ci *L, cs_complex_t *x) ; int cs_ci_ltsolve (const cs_ci *L, cs_complex_t *x) ; cs_cin *cs_ci_lu (const cs_ci *A, const cs_cis *S, double tol) ; cs_ci *cs_ci_permute (const cs_ci *A, const int *pinv, const int *q, int values) ; int *cs_ci_pinv (const int *p, int n) ; int cs_ci_pvec (const int *p, const cs_complex_t *b, cs_complex_t *x, int n) ; cs_cin *cs_ci_qr (const cs_ci *A, const cs_cis *S) ; cs_cis *cs_ci_schol (int order, const cs_ci *A) ; cs_cis *cs_ci_sqr (int order, const cs_ci *A, int qr) ; cs_ci *cs_ci_symperm (const cs_ci *A, const int *pinv, int values) ; int cs_ci_usolve (const cs_ci *U, cs_complex_t *x) ; int cs_ci_utsolve (const cs_ci *U, cs_complex_t *x) ; int cs_ci_updown (cs_ci *L, int sigma, const cs_ci *C, const int *parent) ; /* utilities */ cs_cis *cs_ci_sfree (cs_cis *S) ; cs_cin *cs_ci_nfree (cs_cin *N) ; cs_cid *cs_ci_dfree (cs_cid *D) ; /* --- tertiary CSparse routines -------------------------------------------- */ int *cs_ci_counts (const cs_ci *A, const int *parent, const int *post, int ata) ; double cs_ci_cumsum (int *p, int *c, int n) ; int cs_ci_dfs (int j, cs_ci *G, int top, int *xi, int *pstack, const int *pinv) ; int *cs_ci_etree (const cs_ci *A, int ata) ; int cs_ci_fkeep (cs_ci *A, int (*fkeep) (int, int, cs_complex_t, void *), void *other) ; cs_complex_t cs_ci_house (cs_complex_t *x, double *beta, int n) ; int *cs_ci_maxtrans (const cs_ci *A, int seed) ; int *cs_ci_post (const int *parent, int n) ; cs_cid *cs_ci_scc (cs_ci *A) ; int cs_ci_scatter (const cs_ci *A, int j, cs_complex_t beta, int *w, cs_complex_t *x, int mark,cs_ci *C, int nz) ; int cs_ci_tdfs (int j, int k, int *head, const int *next, int *post, int *stack) ; int cs_ci_leaf (int i, int j, const int *first, int *maxfirst, int *prevleaf, int *ancestor, int *jleaf) ; int cs_ci_reach (cs_ci *G, const cs_ci *B, int k, int *xi, const int *pinv) ; int cs_ci_spsolve (cs_ci *L, const cs_ci *B, int k, int *xi, cs_complex_t *x, const int *pinv, int lo) ; int cs_ci_ereach (const cs_ci *A, int k, const int *parent, int *s, int *w) ; int *cs_ci_randperm (int n, int seed) ; /* utilities */ cs_cid *cs_ci_dalloc (int m, int n) ; cs_ci *cs_ci_done (cs_ci *C, void *w, void *x, int ok) ; int *cs_ci_idone (int *p, cs_ci *C, void *w, int ok) ; cs_cin *cs_ci_ndone (cs_cin *N, cs_ci *C, void *w, void *x, int ok) ; cs_cid *cs_ci_ddone (cs_cid *D, cs_ci *C, void *w, int ok) ; /* -------------------------------------------------------------------------- */ /* complex/UF_long version of CXSparse */ /* -------------------------------------------------------------------------- */ /* --- primary CSparse routines and data structures ------------------------- */ typedef struct cs_cl_sparse /* matrix in compressed-column or triplet form */ { UF_long nzmax ; /* maximum number of entries */ UF_long m ; /* number of rows */ UF_long n ; /* number of columns */ UF_long *p ; /* column pointers (size n+1) or col indlces (size nzmax) */ UF_long *i ; /* row indices, size nzmax */ cs_complex_t *x ; /* numerical values, size nzmax */ UF_long nz ; /* # of entries in triplet matrix, -1 for compressed-col */ } cs_cl ; cs_cl *cs_cl_add (const cs_cl *A, const cs_cl *B, cs_complex_t alpha, cs_complex_t beta) ; UF_long cs_cl_cholsol (UF_long order, const cs_cl *A, cs_complex_t *b) ; UF_long cs_cl_dupl (cs_cl *A) ; UF_long cs_cl_entry (cs_cl *T, UF_long i, UF_long j, cs_complex_t x) ; UF_long cs_cl_lusol (UF_long order, const cs_cl *A, cs_complex_t *b, double tol) ; UF_long cs_cl_gaxpy (const cs_cl *A, const cs_complex_t *x, cs_complex_t *y) ; cs_cl *cs_cl_multiply (const cs_cl *A, const cs_cl *B) ; UF_long cs_cl_qrsol (UF_long order, const cs_cl *A, cs_complex_t *b) ; cs_cl *cs_cl_transpose (const cs_cl *A, UF_long values) ; cs_cl *cs_cl_compress (const cs_cl *T) ; double cs_cl_norm (const cs_cl *A) ; UF_long cs_cl_print (const cs_cl *A, UF_long brief) ; cs_cl *cs_cl_load (FILE *f) ; /* utilities */ void *cs_cl_calloc (UF_long n, size_t size) ; void *cs_cl_free (void *p) ; void *cs_cl_realloc (void *p, UF_long n, size_t size, UF_long *ok) ; cs_cl *cs_cl_spalloc (UF_long m, UF_long n, UF_long nzmax, UF_long values, UF_long t) ; cs_cl *cs_cl_spfree (cs_cl *A) ; UF_long cs_cl_sprealloc (cs_cl *A, UF_long nzmax) ; void *cs_cl_malloc (UF_long n, size_t size) ; /* --- secondary CSparse routines and data structures ----------------------- */ typedef struct cs_cl_symbolic /* symbolic Cholesky, LU, or QR analysis */ { UF_long *pinv ; /* inverse row perm. for QR, fill red. perm for Chol */ UF_long *q ; /* fill-reducing column permutation for LU and QR */ UF_long *parent ; /* elimination tree for Cholesky and QR */ UF_long *cp ; /* column pointers for Cholesky, row counts for QR */ UF_long *leftmost ; /* leftmost[i] = min(find(A(i,:))), for QR */ UF_long m2 ; /* # of rows for QR, after adding fictitious rows */ double lnz ; /* # entries in L for LU or Cholesky; in V for QR */ double unz ; /* # entries in U for LU; in R for QR */ } cs_cls ; typedef struct cs_cl_numeric /* numeric Cholesky, LU, or QR factorization */ { cs_cl *L ; /* L for LU and Cholesky, V for QR */ cs_cl *U ; /* U for LU, r for QR, not used for Cholesky */ UF_long *pinv ; /* partial pivoting for LU */ double *B ; /* beta [0..n-1] for QR */ } cs_cln ; typedef struct cs_cl_dmperm_results /* cs_cl_dmperm or cs_cl_scc output */ { UF_long *p ; /* size m, row permutation */ UF_long *q ; /* size n, column permutation */ UF_long *r ; /* size nb+1, block k is rows r[k] to r[k+1]-1 in A(p,q) */ UF_long *s ; /* size nb+1, block k is cols s[k] to s[k+1]-1 in A(p,q) */ UF_long nb ; /* # of blocks in fine dmperm decomposition */ UF_long rr [5] ; /* coarse row decomposition */ UF_long cc [5] ; /* coarse column decomposition */ } cs_cld ; UF_long *cs_cl_amd (UF_long order, const cs_cl *A) ; cs_cln *cs_cl_chol (const cs_cl *A, const cs_cls *S) ; cs_cld *cs_cl_dmperm (const cs_cl *A, UF_long seed) ; UF_long cs_cl_droptol (cs_cl *A, double tol) ; UF_long cs_cl_dropzeros (cs_cl *A) ; UF_long cs_cl_happly (const cs_cl *V, UF_long i, double beta, cs_complex_t *x) ; UF_long cs_cl_ipvec (const UF_long *p, const cs_complex_t *b, cs_complex_t *x, UF_long n) ; UF_long cs_cl_lsolve (const cs_cl *L, cs_complex_t *x) ; UF_long cs_cl_ltsolve (const cs_cl *L, cs_complex_t *x) ; cs_cln *cs_cl_lu (const cs_cl *A, const cs_cls *S, double tol) ; cs_cl *cs_cl_permute (const cs_cl *A, const UF_long *pinv, const UF_long *q, UF_long values) ; UF_long *cs_cl_pinv (const UF_long *p, UF_long n) ; UF_long cs_cl_pvec (const UF_long *p, const cs_complex_t *b, cs_complex_t *x, UF_long n) ; cs_cln *cs_cl_qr (const cs_cl *A, const cs_cls *S) ; cs_cls *cs_cl_schol (UF_long order, const cs_cl *A) ; cs_cls *cs_cl_sqr (UF_long order, const cs_cl *A, UF_long qr) ; cs_cl *cs_cl_symperm (const cs_cl *A, const UF_long *pinv, UF_long values) ; UF_long cs_cl_usolve (const cs_cl *U, cs_complex_t *x) ; UF_long cs_cl_utsolve (const cs_cl *U, cs_complex_t *x) ; UF_long cs_cl_updown (cs_cl *L, UF_long sigma, const cs_cl *C, const UF_long *parent) ; /* utilities */ cs_cls *cs_cl_sfree (cs_cls *S) ; cs_cln *cs_cl_nfree (cs_cln *N) ; cs_cld *cs_cl_dfree (cs_cld *D) ; /* --- tertiary CSparse routines -------------------------------------------- */ UF_long *cs_cl_counts (const cs_cl *A, const UF_long *parent, const UF_long *post, UF_long ata) ; double cs_cl_cumsum (UF_long *p, UF_long *c, UF_long n) ; UF_long cs_cl_dfs (UF_long j, cs_cl *G, UF_long top, UF_long *xi, UF_long *pstack, const UF_long *pinv) ; UF_long *cs_cl_etree (const cs_cl *A, UF_long ata) ; UF_long cs_cl_fkeep (cs_cl *A, UF_long (*fkeep) (UF_long, UF_long, cs_complex_t, void *), void *other) ; cs_complex_t cs_cl_house (cs_complex_t *x, double *beta, UF_long n) ; UF_long *cs_cl_maxtrans (const cs_cl *A, UF_long seed) ; UF_long *cs_cl_post (const UF_long *parent, UF_long n) ; cs_cld *cs_cl_scc (cs_cl *A) ; UF_long cs_cl_scatter (const cs_cl *A, UF_long j, cs_complex_t beta, UF_long *w, cs_complex_t *x, UF_long mark,cs_cl *C, UF_long nz) ; UF_long cs_cl_tdfs (UF_long j, UF_long k, UF_long *head, const UF_long *next, UF_long *post, UF_long *stack) ; UF_long cs_cl_leaf (UF_long i, UF_long j, const UF_long *first, UF_long *maxfirst, UF_long *prevleaf, UF_long *ancestor, UF_long *jleaf) ; UF_long cs_cl_reach (cs_cl *G, const cs_cl *B, UF_long k, UF_long *xi, const UF_long *pinv) ; UF_long cs_cl_spsolve (cs_cl *L, const cs_cl *B, UF_long k, UF_long *xi, cs_complex_t *x, const UF_long *pinv, UF_long lo) ; UF_long cs_cl_ereach (const cs_cl *A, UF_long k, const UF_long *parent, UF_long *s, UF_long *w) ; UF_long *cs_cl_randperm (UF_long n, UF_long seed) ; /* utilities */ cs_cld *cs_cl_dalloc (UF_long m, UF_long n) ; cs_cl *cs_cl_done (cs_cl *C, void *w, void *x, UF_long ok) ; UF_long *cs_cl_idone (UF_long *p, cs_cl *C, void *w, UF_long ok) ; cs_cln *cs_cl_ndone (cs_cln *N, cs_cl *C, void *w, void *x, UF_long ok) ; cs_cld *cs_cl_ddone (cs_cld *D, cs_cl *C, void *w, UF_long ok) ; #endif /* -------------------------------------------------------------------------- */ /* Macros for constructing each version of CSparse */ /* -------------------------------------------------------------------------- */ #ifdef CS_LONG #define CS_INT UF_long #define CS_INT_MAX UF_long_max #define CS_ID UF_long_id #ifdef CS_COMPLEX #define CS_ENTRY cs_complex_t #define CS_NAME(nm) cs_cl ## nm #define cs cs_cl #else #define CS_ENTRY double #define CS_NAME(nm) cs_dl ## nm #define cs cs_dl #endif #else #define CS_INT int #define CS_INT_MAX INT_MAX #define CS_ID "%d" #ifdef CS_COMPLEX #define CS_ENTRY cs_complex_t #define CS_NAME(nm) cs_ci ## nm #define cs cs_ci #else #define CS_ENTRY double #define CS_NAME(nm) cs_di ## nm #define cs cs_di #endif #endif #ifdef CS_COMPLEX #define CS_REAL(x) creal(x) #define CS_IMAG(x) cimag(x) #define CS_CONJ(x) conj(x) #define CS_ABS(x) cabs(x) #else #define CS_REAL(x) (x) #define CS_IMAG(x) (0.) #define CS_CONJ(x) (x) #define CS_ABS(x) fabs(x) #endif #define CS_MAX(a,b) (((a) > (b)) ? (a) : (b)) #define CS_MIN(a,b) (((a) < (b)) ? (a) : (b)) #define CS_FLIP(i) (-(i)-2) #define CS_UNFLIP(i) (((i) < 0) ? CS_FLIP(i) : (i)) #define CS_MARKED(w,j) (w [j] < 0) #define CS_MARK(w,j) { w [j] = CS_FLIP (w [j]) ; } #define CS_CSC(A) (A && (A->nz == -1)) #define CS_TRIPLET(A) (A && (A->nz >= 0)) /* --- primary CSparse routines and data structures ------------------------- */ #define cs_add CS_NAME (_add) #define cs_cholsol CS_NAME (_cholsol) #define cs_dupl CS_NAME (_dupl) #define cs_entry CS_NAME (_entry) #define cs_lusol CS_NAME (_lusol) #define cs_gaxpy CS_NAME (_gaxpy) #define cs_multiply CS_NAME (_multiply) #define cs_qrsol CS_NAME (_qrsol) #define cs_transpose CS_NAME (_transpose) #define cs_compress CS_NAME (_compress) #define cs_norm CS_NAME (_norm) #define cs_print CS_NAME (_print) #define cs_load CS_NAME (_load) /* utilities */ #define cs_calloc CS_NAME (_calloc) #define cs_free CS_NAME (_free) #define cs_realloc CS_NAME (_realloc) #define cs_spalloc CS_NAME (_spalloc) #define cs_spfree CS_NAME (_spfree) #define cs_sprealloc CS_NAME (_sprealloc) #define cs_malloc CS_NAME (_malloc) /* --- secondary CSparse routines and data structures ----------------------- */ #define css CS_NAME (s) #define csn CS_NAME (n) #define csd CS_NAME (d) #define cs_amd CS_NAME (_amd) #define cs_chol CS_NAME (_chol) #define cs_dmperm CS_NAME (_dmperm) #define cs_droptol CS_NAME (_droptol) #define cs_dropzeros CS_NAME (_dropzeros) #define cs_happly CS_NAME (_happly) #define cs_ipvec CS_NAME (_ipvec) #define cs_lsolve CS_NAME (_lsolve) #define cs_ltsolve CS_NAME (_ltsolve) #define cs_lu CS_NAME (_lu) #define cs_permute CS_NAME (_permute) #define cs_pinv CS_NAME (_pinv) #define cs_pvec CS_NAME (_pvec) #define cs_qr CS_NAME (_qr) #define cs_schol CS_NAME (_schol) #define cs_sqr CS_NAME (_sqr) #define cs_symperm CS_NAME (_symperm) #define cs_usolve CS_NAME (_usolve) #define cs_utsolve CS_NAME (_utsolve) #define cs_updown CS_NAME (_updown) /* utilities */ #define cs_sfree CS_NAME (_sfree) #define cs_nfree CS_NAME (_nfree) #define cs_dfree CS_NAME (_dfree) /* --- tertiary CSparse routines -------------------------------------------- */ #define cs_counts CS_NAME (_counts) #define cs_cumsum CS_NAME (_cumsum) #define cs_dfs CS_NAME (_dfs) #define cs_etree CS_NAME (_etree) #define cs_fkeep CS_NAME (_fkeep) #define cs_house CS_NAME (_house) #define cs_invmatch CS_NAME (_invmatch) #define cs_maxtrans CS_NAME (_maxtrans) #define cs_post CS_NAME (_post) #define cs_scc CS_NAME (_scc) #define cs_scatter CS_NAME (_scatter) #define cs_tdfs CS_NAME (_tdfs) #define cs_reach CS_NAME (_reach) #define cs_spsolve CS_NAME (_spsolve) #define cs_ereach CS_NAME (_ereach) #define cs_randperm CS_NAME (_randperm) #define cs_leaf CS_NAME (_leaf) /* utilities */ #define cs_dalloc CS_NAME (_dalloc) #define cs_done CS_NAME (_done) #define cs_idone CS_NAME (_idone) #define cs_ndone CS_NAME (_ndone) #define cs_ddone CS_NAME (_ddone) /* -------------------------------------------------------------------------- */ /* Conversion routines */ /* -------------------------------------------------------------------------- */ #ifndef NCOMPLEX cs_di *cs_i_real (cs_ci *A, int real) ; cs_ci *cs_i_complex (cs_di *A, int real) ; cs_dl *cs_l_real (cs_cl *A, UF_long real) ; cs_cl *cs_l_complex (cs_dl *A, UF_long real) ; #endif #ifdef __cplusplus } #endif #endif python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_etree.c0000644000076500000240000000433513524616145023754 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* compute the etree of A (using triu(A), or A'A without forming A'A */ CS_INT *cs_etree (const cs *A, CS_INT ata) { CS_INT i, k, p, m, n, inext, *Ap, *Ai, *w, *parent, *ancestor, *prev ; if (!CS_CSC (A)) return (NULL) ; /* check inputs */ m = A->m ; n = A->n ; Ap = A->p ; Ai = A->i ; parent = cs_malloc (n, sizeof (CS_INT)) ; /* allocate result */ w = cs_malloc (n + (ata ? m : 0), sizeof (CS_INT)) ; /* get workspace */ if (!w || !parent) return (cs_idone (parent, NULL, w, 0)) ; ancestor = w ; prev = w + n ; if (ata) for (i = 0 ; i < m ; i++) prev [i] = -1 ; for (k = 0 ; k < n ; k++) { parent [k] = -1 ; /* node k has no parent yet */ ancestor [k] = -1 ; /* nor does k have an ancestor */ for (p = Ap [k] ; p < Ap [k+1] ; p++) { i = ata ? (prev [Ai [p]]) : (Ai [p]) ; for ( ; i != -1 && i < k ; i = inext) /* traverse from i to k */ { inext = ancestor [i] ; /* inext = ancestor of i */ ancestor [i] = k ; /* path compression */ if (inext == -1) parent [i] = k ; /* no anc., parent is k */ } if (ata) prev [Ai [p]] = k ; } } return (cs_idone (parent, NULL, w, 1)) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_pinv.c0000644000076500000240000000254013524616145023620 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* pinv = p', or p = pinv' */ CS_INT *cs_pinv (CS_INT const *p, CS_INT n) { CS_INT k, *pinv ; if (!p) return (NULL) ; /* p = NULL denotes identity */ pinv = cs_malloc (n, sizeof (CS_INT)) ; /* allocate result */ if (!pinv) return (NULL) ; /* out of memory */ for (k = 0 ; k < n ; k++) pinv [p [k]] = k ;/* invert the permutation */ return (pinv) ; /* return result */ } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_scc.c0000644000076500000240000000534213524616145023417 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* find the strongly connected components of a square matrix */ csd *cs_scc (cs *A) /* matrix A temporarily modified, then restored */ { CS_INT n, i, k, b, nb = 0, top, *xi, *pstack, *p, *r, *Ap, *ATp, *rcopy, *Blk ; cs *AT ; csd *D ; if (!CS_CSC (A)) return (NULL) ; /* check inputs */ n = A->n ; Ap = A->p ; D = cs_dalloc (n, 0) ; /* allocate result */ AT = cs_transpose (A, 0) ; /* AT = A' */ xi = cs_malloc (2*n+1, sizeof (CS_INT)) ; /* get workspace */ if (!D || !AT || !xi) return (cs_ddone (D, AT, xi, 0)) ; Blk = xi ; rcopy = pstack = xi + n ; p = D->p ; r = D->r ; ATp = AT->p ; top = n ; for (i = 0 ; i < n ; i++) /* first dfs(A) to find finish times (xi) */ { if (!CS_MARKED (Ap, i)) top = cs_dfs (i, A, top, xi, pstack, NULL) ; } for (i = 0 ; i < n ; i++) CS_MARK (Ap, i) ; /* restore A; unmark all nodes*/ top = n ; nb = n ; for (k = 0 ; k < n ; k++) /* dfs(A') to find strongly connnected comp */ { i = xi [k] ; /* get i in reverse order of finish times */ if (CS_MARKED (ATp, i)) continue ; /* skip node i if already ordered */ r [nb--] = top ; /* node i is the start of a component in p */ top = cs_dfs (i, AT, top, p, pstack, NULL) ; } r [nb] = 0 ; /* first block starts at zero; shift r up */ for (k = nb ; k <= n ; k++) r [k-nb] = r [k] ; D->nb = nb = n-nb ; /* nb = # of strongly connected components */ for (b = 0 ; b < nb ; b++) /* sort each block in natural order */ { for (k = r [b] ; k < r [b+1] ; k++) Blk [p [k]] = b ; } for (b = 0 ; b <= nb ; b++) rcopy [b] = r [b] ; for (i = 0 ; i < n ; i++) p [rcopy [Blk [i]]++] = i ; return (cs_ddone (D, AT, xi, 1)) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_qr.c0000644000076500000240000001052313524616145023266 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* sparse QR factorization [V,beta,pinv,R] = qr (A) */ csn *cs_qr (const cs *A, const css *S) { CS_ENTRY *Rx, *Vx, *Ax, *x ; double *Beta ; CS_INT i, k, p, m, n, vnz, p1, top, m2, len, col, rnz, *s, *leftmost, *Ap, *Ai, *parent, *Rp, *Ri, *Vp, *Vi, *w, *pinv, *q ; cs *R, *V ; csn *N ; if (!CS_CSC (A) || !S) return (NULL) ; m = A->m ; n = A->n ; Ap = A->p ; Ai = A->i ; Ax = A->x ; q = S->q ; parent = S->parent ; pinv = S->pinv ; m2 = S->m2 ; vnz = S->lnz ; rnz = S->unz ; leftmost = S->leftmost ; w = cs_malloc (m2+n, sizeof (CS_INT)) ; /* get CS_INT workspace */ x = cs_malloc (m2, sizeof (CS_ENTRY)) ; /* get CS_ENTRY workspace */ N = cs_calloc (1, sizeof (csn)) ; /* allocate result */ if (!w || !x || !N) return (cs_ndone (N, NULL, w, x, 0)) ; s = w + m2 ; /* s is size n */ for (k = 0 ; k < m2 ; k++) x [k] = 0 ; /* clear workspace x */ N->L = V = cs_spalloc (m2, n, vnz, 1, 0) ; /* allocate result V */ N->U = R = cs_spalloc (m2, n, rnz, 1, 0) ; /* allocate result R */ N->B = Beta = cs_malloc (n, sizeof (double)) ; /* allocate result Beta */ if (!R || !V || !Beta) return (cs_ndone (N, NULL, w, x, 0)) ; Rp = R->p ; Ri = R->i ; Rx = R->x ; Vp = V->p ; Vi = V->i ; Vx = V->x ; for (i = 0 ; i < m2 ; i++) w [i] = -1 ; /* clear w, to mark nodes */ rnz = 0 ; vnz = 0 ; for (k = 0 ; k < n ; k++) /* compute V and R */ { Rp [k] = rnz ; /* R(:,k) starts here */ Vp [k] = p1 = vnz ; /* V(:,k) starts here */ w [k] = k ; /* add V(k,k) to pattern of V */ Vi [vnz++] = k ; top = n ; col = q ? q [k] : k ; for (p = Ap [col] ; p < Ap [col+1] ; p++) /* find R(:,k) pattern */ { i = leftmost [Ai [p]] ; /* i = min(find(A(i,q))) */ for (len = 0 ; w [i] != k ; i = parent [i]) /* traverse up to k */ { s [len++] = i ; w [i] = k ; } while (len > 0) s [--top] = s [--len] ; /* push path on stack */ i = pinv [Ai [p]] ; /* i = permuted row of A(:,col) */ x [i] = Ax [p] ; /* x (i) = A(:,col) */ if (i > k && w [i] < k) /* pattern of V(:,k) = x (k+1:m) */ { Vi [vnz++] = i ; /* add i to pattern of V(:,k) */ w [i] = k ; } } for (p = top ; p < n ; p++) /* for each i in pattern of R(:,k) */ { i = s [p] ; /* R(i,k) is nonzero */ cs_happly (V, i, Beta [i], x) ; /* apply (V(i),Beta(i)) to x */ Ri [rnz] = i ; /* R(i,k) = x(i) */ Rx [rnz++] = x [i] ; x [i] = 0 ; if (parent [i] == k) vnz = cs_scatter (V, i, 0, w, NULL, k, V, vnz); } for (p = p1 ; p < vnz ; p++) /* gather V(:,k) = x */ { Vx [p] = x [Vi [p]] ; x [Vi [p]] = 0 ; } Ri [rnz] = k ; /* R(k,k) = norm (x) */ Rx [rnz++] = cs_house (Vx+p1, Beta+k, vnz-p1) ; /* [v,beta]=house(x) */ } Rp [n] = rnz ; /* finalize R */ Vp [n] = vnz ; /* finalize V */ return (cs_ndone (N, NULL, w, x, 1)) ; /* success */ } python-igraph-0.8.0/vendor/source/igraph/src/cs/UFconfig.h0000644000076500000240000001021113524616144023655 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === UFconfig.h =========================================================== */ /* ========================================================================== */ /* Configuration file for SuiteSparse: a Suite of Sparse matrix packages * (AMD, COLAMD, CCOLAMD, CAMD, CHOLMOD, UMFPACK, CXSparse, and others). * * UFconfig.h provides the definition of the long integer. On most systems, * a C program can be compiled in LP64 mode, in which long's and pointers are * both 64-bits, and int's are 32-bits. Windows 64, however, uses the LLP64 * model, in which int's and long's are 32-bits, and long long's and pointers * are 64-bits. * * SuiteSparse packages that include long integer versions are * intended for the LP64 mode. However, as a workaround for Windows 64 * (and perhaps other systems), the long integer can be redefined. * * If _WIN64 is defined, then the __int64 type is used instead of long. * * The long integer can also be defined at compile time. For example, this * could be added to UFconfig.mk: * * CFLAGS = -O -D'UF_long=long long' -D'UF_long_max=9223372036854775801' \ * -D'UF_long_id="%lld"' * * This file defines UF_long as either long (on all but _WIN64) or * __int64 on Windows 64. The intent is that a UF_long is always a 64-bit * integer in a 64-bit code. ptrdiff_t might be a better choice than long; * it is always the same size as a pointer. * * This file also defines the SUITESPARSE_VERSION and related definitions. * * Copyright (c) 2007, University of Florida. No licensing restrictions * apply to this file or to the UFconfig directory. Author: Timothy A. Davis. */ #ifndef _UFCONFIG_H #define _UFCONFIG_H #ifdef __cplusplus extern "C" { #endif #include /* ========================================================================== */ /* === UF_long ============================================================== */ /* ========================================================================== */ #ifndef UF_long #ifdef _WIN64 #define UF_long __int64 #define UF_long_max _I64_MAX #define UF_long_id "%I64d" #else #define UF_long long #define UF_long_max LONG_MAX #define UF_long_id "%ld" #endif #endif /* ========================================================================== */ /* === SuiteSparse version ================================================== */ /* ========================================================================== */ /* SuiteSparse is not a package itself, but a collection of packages, some of * which must be used together (UMFPACK requires AMD, CHOLMOD requires AMD, * COLAMD, CAMD, and CCOLAMD, etc). A version number is provided here for the * collection itself. The versions of packages within each version of * SuiteSparse are meant to work together. Combining one packge from one * version of SuiteSparse, with another package from another version of * SuiteSparse, may or may not work. * * SuiteSparse Version 3.3.0 contains the following packages: * * AMD version 2.2.0 * CAMD version 2.2.0 * COLAMD version 2.7.1 * CCOLAMD version 2.7.1 * CHOLMOD version 1.7.1 * CSparse version 2.2.3 * CXSparse version 2.2.3 * KLU version 1.1.0 * BTF version 1.0.1 * LDL version 2.0.1 * UFconfig version number is the same as SuiteSparse * UMFPACK version 5.3.0 * RBio version 1.1.1 * UFcollection version 1.2.0 * LINFACTOR version 1.1.0 * MESHND version 1.1.1 * SSMULT version 2.0.0 * MATLAB_Tools no specific version number * SuiteSparseQR version 1.1.1 * * Other package dependencies: * BLAS required by CHOLMOD and UMFPACK * LAPACK required by CHOLMOD * METIS 4.0.1 required by CHOLMOD (optional) and KLU (optional) */ #define SUITESPARSE_DATE "Mar 24, 2009" #define SUITESPARSE_VER_CODE(main,sub) ((main) * 1000 + (sub)) #define SUITESPARSE_MAIN_VERSION 3 #define SUITESPARSE_SUB_VERSION 3 #define SUITESPARSE_SUBSUB_VERSION 0 #define SUITESPARSE_VERSION \ SUITESPARSE_VER_CODE(SUITESPARSE_MAIN_VERSION,SUITESPARSE_SUB_VERSION) #ifdef __cplusplus } #endif #endif python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_norm.c0000644000076500000240000000253513524616145023623 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* 1-norm of a sparse matrix = max (sum (abs (A))), largest column sum */ double cs_norm (const cs *A) { CS_INT p, j, n, *Ap ; CS_ENTRY *Ax ; double norm = 0, s ; if (!CS_CSC (A) || !A->x) return (-1) ; /* check inputs */ n = A->n ; Ap = A->p ; Ax = A->x ; for (j = 0 ; j < n ; j++) { for (s = 0, p = Ap [j] ; p < Ap [j+1] ; p++) s += CS_ABS (Ax [p]) ; norm = CS_MAX (norm, s) ; } return (norm) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_tdfs.c0000644000076500000240000000345313524616145023610 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* depth-first search and postorder of a tree rooted at node j */ CS_INT cs_tdfs (CS_INT j, CS_INT k, CS_INT *head, const CS_INT *next, CS_INT *post, CS_INT *stack) { CS_INT i, p, top = 0 ; if (!head || !next || !post || !stack) return (-1) ; /* check inputs */ stack [0] = j ; /* place j on the stack */ while (top >= 0) /* while (stack is not empty) */ { p = stack [top] ; /* p = top of stack */ i = head [p] ; /* i = youngest child of p */ if (i == -1) { top-- ; /* p has no unordered children left */ post [k++] = p ; /* node p is the kth postordered node */ } else { head [p] = next [i] ; /* remove i from children of p */ stack [++top] = i ; /* start dfs on child node i */ } } return (k) ; } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_counts.c0000644000076500000240000000730113524616144024156 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* column counts of LL'=A or LL'=A'A, given parent & post ordering */ #define HEAD(k,j) (ata ? head [k] : j) #define NEXT(J) (ata ? next [J] : -1) static void init_ata (cs *AT, const CS_INT *post, CS_INT *w, CS_INT **head, CS_INT **next) { CS_INT i, k, p, m = AT->n, n = AT->m, *ATp = AT->p, *ATi = AT->i ; *head = w+4*n, *next = w+5*n+1 ; for (k = 0 ; k < n ; k++) w [post [k]] = k ; /* invert post */ for (i = 0 ; i < m ; i++) { for (k = n, p = ATp[i] ; p < ATp[i+1] ; p++) k = CS_MIN (k, w [ATi[p]]); (*next) [i] = (*head) [k] ; /* place row i in linked list k */ (*head) [k] = i ; } } CS_INT *cs_counts (const cs *A, const CS_INT *parent, const CS_INT *post, CS_INT ata) { CS_INT i, j, k, n, m, J, s, p, q, jleaf, *ATp, *ATi, *maxfirst, *prevleaf, *ancestor, *head = NULL, *next = NULL, *colcount, *w, *first, *delta ; cs *AT ; if (!CS_CSC (A) || !parent || !post) return (NULL) ; /* check inputs */ m = A->m ; n = A->n ; s = 4*n + (ata ? (n+m+1) : 0) ; delta = colcount = cs_malloc (n, sizeof (CS_INT)) ; /* allocate result */ w = cs_malloc (s, sizeof (CS_INT)) ; /* get workspace */ AT = cs_transpose (A, 0) ; /* AT = A' */ if (!AT || !colcount || !w) return (cs_idone (colcount, AT, w, 0)) ; ancestor = w ; maxfirst = w+n ; prevleaf = w+2*n ; first = w+3*n ; for (k = 0 ; k < s ; k++) w [k] = -1 ; /* clear workspace w [0..s-1] */ for (k = 0 ; k < n ; k++) /* find first [j] */ { j = post [k] ; delta [j] = (first [j] == -1) ? 1 : 0 ; /* delta[j]=1 if j is a leaf */ for ( ; j != -1 && first [j] == -1 ; j = parent [j]) first [j] = k ; } ATp = AT->p ; ATi = AT->i ; if (ata) init_ata (AT, post, w, &head, &next) ; for (i = 0 ; i < n ; i++) ancestor [i] = i ; /* each node in its own set */ for (k = 0 ; k < n ; k++) { j = post [k] ; /* j is the kth node in postordered etree */ if (parent [j] != -1) delta [parent [j]]-- ; /* j is not a root */ for (J = HEAD (k,j) ; J != -1 ; J = NEXT (J)) /* J=j for LL'=A case */ { for (p = ATp [J] ; p < ATp [J+1] ; p++) { i = ATi [p] ; q = cs_leaf (i, j, first, maxfirst, prevleaf, ancestor, &jleaf); if (jleaf >= 1) delta [j]++ ; /* A(i,j) is in skeleton */ if (jleaf == 2) delta [q]-- ; /* account for overlap in q */ } } if (parent [j] != -1) ancestor [j] = parent [j] ; } for (j = 0 ; j < n ; j++) /* sum up delta's of each child */ { if (parent [j] != -1) colcount [parent [j]] += colcount [j] ; } return (cs_idone (colcount, AT, w, 1)) ; /* success: free workspace */ } python-igraph-0.8.0/vendor/source/igraph/src/cs/cs_util.c0000644000076500000240000001160413524616145023622 0ustar tamasstaff00000000000000/* * CXSPARSE: a Concise Sparse Matrix package - Extended. * Copyright (c) 2006-2009, Timothy A. Davis. * http://www.cise.ufl.edu/research/sparse/CXSparse * * CXSparse is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * CXSparse is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this Module; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #include "cs.h" /* allocate a sparse matrix (triplet form or compressed-column form) */ cs *cs_spalloc (CS_INT m, CS_INT n, CS_INT nzmax, CS_INT values, CS_INT triplet) { cs *A = cs_calloc (1, sizeof (cs)) ; /* allocate the cs struct */ if (!A) return (NULL) ; /* out of memory */ A->m = m ; /* define dimensions and nzmax */ A->n = n ; A->nzmax = nzmax = CS_MAX (nzmax, 1) ; A->nz = triplet ? 0 : -1 ; /* allocate triplet or comp.col */ A->p = cs_malloc (triplet ? nzmax : n+1, sizeof (CS_INT)) ; A->i = cs_malloc (nzmax, sizeof (CS_INT)) ; A->x = values ? cs_malloc (nzmax, sizeof (CS_ENTRY)) : NULL ; return ((!A->p || !A->i || (values && !A->x)) ? cs_spfree (A) : A) ; } /* change the max # of entries sparse matrix */ CS_INT cs_sprealloc (cs *A, CS_INT nzmax) { CS_INT ok, oki, okj = 1, okx = 1 ; if (!A) return (0) ; if (nzmax <= 0) nzmax = (CS_CSC (A)) ? (A->p [A->n]) : A->nz ; A->i = cs_realloc (A->i, nzmax, sizeof (CS_INT), &oki) ; if (CS_TRIPLET (A)) A->p = cs_realloc (A->p, nzmax, sizeof (CS_INT), &okj) ; if (A->x) A->x = cs_realloc (A->x, nzmax, sizeof (CS_ENTRY), &okx) ; ok = (oki && okj && okx) ; if (ok) A->nzmax = nzmax ; return (ok) ; } /* free a sparse matrix */ cs *cs_spfree (cs *A) { if (!A) return (NULL) ; /* do nothing if A already NULL */ cs_free (A->p) ; cs_free (A->i) ; cs_free (A->x) ; return (cs_free (A)) ; /* free the cs struct and return NULL */ } /* free a numeric factorization */ csn *cs_nfree (csn *N) { if (!N) return (NULL) ; /* do nothing if N already NULL */ cs_spfree (N->L) ; cs_spfree (N->U) ; cs_free (N->pinv) ; cs_free (N->B) ; return (cs_free (N)) ; /* free the csn struct and return NULL */ } /* free a symbolic factorization */ css *cs_sfree (css *S) { if (!S) return (NULL) ; /* do nothing if S already NULL */ cs_free (S->pinv) ; cs_free (S->q) ; cs_free (S->parent) ; cs_free (S->cp) ; cs_free (S->leftmost) ; return (cs_free (S)) ; /* free the css struct and return NULL */ } /* allocate a cs_dmperm or cs_scc result */ csd *cs_dalloc (CS_INT m, CS_INT n) { csd *D ; D = cs_calloc (1, sizeof (csd)) ; if (!D) return (NULL) ; D->p = cs_malloc (m, sizeof (CS_INT)) ; D->r = cs_malloc (m+6, sizeof (CS_INT)) ; D->q = cs_malloc (n, sizeof (CS_INT)) ; D->s = cs_malloc (n+6, sizeof (CS_INT)) ; return ((!D->p || !D->r || !D->q || !D->s) ? cs_dfree (D) : D) ; } /* free a cs_dmperm or cs_scc result */ csd *cs_dfree (csd *D) { if (!D) return (NULL) ; /* do nothing if D already NULL */ cs_free (D->p) ; cs_free (D->q) ; cs_free (D->r) ; cs_free (D->s) ; return (cs_free (D)) ; } /* free workspace and return a sparse matrix result */ cs *cs_done (cs *C, void *w, void *x, CS_INT ok) { cs_free (w) ; /* free workspace */ cs_free (x) ; return (ok ? C : cs_spfree (C)) ; /* return result if OK, else free it */ } /* free workspace and return CS_INT array result */ CS_INT *cs_idone (CS_INT *p, cs *C, void *w, CS_INT ok) { cs_spfree (C) ; /* free temporary matrix */ cs_free (w) ; /* free workspace */ return (ok ? p : cs_free (p)) ; /* return result if OK, else free it */ } /* free workspace and return a numeric factorization (Cholesky, LU, or QR) */ csn *cs_ndone (csn *N, cs *C, void *w, void *x, CS_INT ok) { cs_spfree (C) ; /* free temporary matrix */ cs_free (w) ; /* free workspace */ cs_free (x) ; return (ok ? N : cs_nfree (N)) ; /* return result if OK, else free it */ } /* free workspace and return a csd result */ csd *cs_ddone (csd *D, cs *C, void *w, CS_INT ok) { cs_spfree (C) ; /* free temporary matrix */ cs_free (w) ; /* free workspace */ return (ok ? D : cs_dfree (D)) ; /* return result if OK, else free it */ } python-igraph-0.8.0/vendor/source/igraph/src/prpack.cpp0000644000076500000240000000674313614300625023374 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "prpack.h" #include "prpack/prpack_igraph_graph.h" #include "prpack/prpack_solver.h" #include "igraph_error.h" using namespace prpack; using namespace std; /* * PRPACK-based implementation of \c igraph_personalized_pagerank. * * See \c igraph_personalized_pagerank for the documentation of the parameters. */ int igraph_personalized_pagerank_prpack(const igraph_t *graph, igraph_vector_t *vector, igraph_real_t *value, const igraph_vs_t vids, igraph_bool_t directed, igraph_real_t damping, igraph_vector_t *reset, const igraph_vector_t *weights) { long int i, no_of_nodes = igraph_vcount(graph), nodes_to_calc; igraph_vit_t vit; double* u = 0; double* v = 0; const prpack_result* res; if (reset) { /* Normalize reset vector so the sum is 1 */ double reset_sum = igraph_vector_sum(reset); if (igraph_vector_min(reset) < 0) { IGRAPH_ERROR("the reset vector must not contain negative elements", IGRAPH_EINVAL); } if (reset_sum == 0) { IGRAPH_ERROR("the sum of the elements in the reset vector must not be zero", IGRAPH_EINVAL); } // Construct the personalization vector v = new double[no_of_nodes]; for (i = 0; i < no_of_nodes; i++) { v[i] = VECTOR(*reset)[i] / reset_sum; } } // Construct and run the solver prpack_igraph_graph prpack_graph(graph, weights, directed); prpack_solver solver(&prpack_graph, false); res = solver.solve(damping, 1e-10, u, v, ""); // Delete the personalization vector if (v) { delete[] v; } // Check whether the solver converged // TODO: this is commented out because some of the solvers do not implement it yet /* if (!res->converged) { IGRAPH_WARNING("PRPACK solver failed to converge. Results may be inaccurate."); } */ // Fill the result vector IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); nodes_to_calc = IGRAPH_VIT_SIZE(vit); IGRAPH_CHECK(igraph_vector_resize(vector, nodes_to_calc)); for (IGRAPH_VIT_RESET(vit), i = 0; !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit), i++) { VECTOR(*vector)[i] = res->x[(long int)IGRAPH_VIT_GET(vit)]; } igraph_vit_destroy(&vit); IGRAPH_FINALLY_CLEAN(1); // TODO: can we get the eigenvalue? We'll just fake it until we can. if (value) { *value = 1.0; } delete res; return IGRAPH_SUCCESS; } python-igraph-0.8.0/vendor/source/igraph/src/cohesive_blocks.c0000644000076500000240000005305713614300625024716 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_cohesive_blocks.h" #include "igraph_interface.h" #include "igraph_memory.h" #include "igraph_flow.h" #include "igraph_separators.h" #include "igraph_structural.h" #include "igraph_components.h" #include "igraph_dqueue.h" #include "igraph_constructors.h" #include "igraph_interrupt_internal.h" #include "igraph_statusbar.h" void igraph_i_cohesive_blocks_free(igraph_vector_ptr_t *ptr) { long int i, n = igraph_vector_ptr_size(ptr); for (i = 0; i < n; i++) { igraph_t *g = VECTOR(*ptr)[i]; if (g) { igraph_destroy(g); igraph_free(g); } } } void igraph_i_cohesive_blocks_free2(igraph_vector_ptr_t *ptr) { long int i, n = igraph_vector_ptr_size(ptr); for (i = 0; i < n; i++) { igraph_vector_long_t *v = VECTOR(*ptr)[i]; if (v) { igraph_vector_long_destroy(v); igraph_free(v); } } } void igraph_i_cohesive_blocks_free3(igraph_vector_ptr_t *ptr) { long int i, n = igraph_vector_ptr_size(ptr); for (i = 0; i < n; i++) { igraph_vector_t *v = VECTOR(*ptr)[i]; if (v) { igraph_vector_destroy(v); igraph_free(v); } } } /* This is kind of a BFS to find the components of the graph, after * deleting the vertices marked in 'excluded'. * These vertices are not put in the BFS queue, but they are added to * all neighboring components. */ int igraph_i_cb_components(igraph_t *graph, const igraph_vector_bool_t *excluded, igraph_vector_long_t *components, long int *no, /* working area follows */ igraph_vector_long_t *compid, igraph_dqueue_t *Q, igraph_vector_t *neis) { long int no_of_nodes = igraph_vcount(graph); long int i; long int cno = 0; igraph_vector_long_clear(components); igraph_dqueue_clear(Q); IGRAPH_CHECK(igraph_vector_long_resize(compid, no_of_nodes)); igraph_vector_long_null(compid); for (i = 0; i < no_of_nodes; i++) { if (VECTOR(*compid)[i]) { continue; } if (VECTOR(*excluded)[i]) { continue; } IGRAPH_CHECK(igraph_dqueue_push(Q, i)); IGRAPH_CHECK(igraph_vector_long_push_back(components, i)); VECTOR(*compid)[i] = ++cno; while (!igraph_dqueue_empty(Q)) { igraph_integer_t node = (igraph_integer_t) igraph_dqueue_pop(Q); long int j, n; IGRAPH_CHECK(igraph_neighbors(graph, neis, node, IGRAPH_ALL)); n = igraph_vector_size(neis); for (j = 0; j < n; j++) { long int v = (long int) VECTOR(*neis)[j]; if (VECTOR(*excluded)[v]) { if (VECTOR(*compid)[v] != cno) { VECTOR(*compid)[v] = cno; IGRAPH_CHECK(igraph_vector_long_push_back(components, v)); } } else { if (!VECTOR(*compid)[v]) { VECTOR(*compid)[v] = cno; /* could be anything positive */ IGRAPH_CHECK(igraph_vector_long_push_back(components, v)); IGRAPH_CHECK(igraph_dqueue_push(Q, v)); } } } } /* while !igraph_dqueue_empty */ IGRAPH_CHECK(igraph_vector_long_push_back(components, -1)); } /* for ik. Thus a hiearchy of vertex subsets * is found, whith the entire graph G at its root. See the following * reference for details: J. Moody and D. R. White. Structural * cohesion and embeddedness: A hierarchical concept of social * groups. American Sociological Review, 68(1):103--127, Feb 2003. * * This function implements cohesive blocking and * calculates the complete cohesive block hierarchy of a graph. * * \param graph The input graph. It must be undirected and simple. See * \ref igraph_is_simple(). * \param blocks If not a null pointer, then it must be an initialized * vector of pointers and the cohesive blocks are stored here. * Each block is encoded with a numeric vector, that contains the * vertex ids of the block. * \param cohesion If not a null pointer, then it must be an initialized * vector and the cohesion of the blocks is stored here, in the same * order as the blocks in the \p blocks pointer vector. * \param parent If not a null pointer, then it must be an initialized * vector and the block hierarchy is stored here. For each block, the * id (i.e. the position in the \p blocks pointer vector) of its * parent block is stored. For the top block in the hierarchy, * -1 is stored. * \param block_tree If not a null pointer, then it must be a pointer * to an uninitialized graph, and the block hierarchy is stored * here as an igraph graph. The vertex ids correspond to the order * of the blocks in the \p blocks vector. * \return Error code. * * Time complexity: TODO. * * \example examples/simple/cohesive_blocks.c */ int igraph_cohesive_blocks(const igraph_t *graph, igraph_vector_ptr_t *blocks, igraph_vector_t *cohesion, igraph_vector_t *parent, igraph_t *block_tree) { /* Some implementation comments. Everything is relatively straightforward, except, that we need to follow the vertex ids of the various subgraphs, without having to store two-way mappings at each level. The subgraphs can overlap, this complicates things a bit. The 'Q' vector is used as a double ended queue and it contains the subgraphs to work on in the future. Some other vectors are associated with it. 'Qparent' gives the parent graph of a graph in Q. Qmapping gives the mapping of the vertices from the graph to the parent graph. Qcohesion is the vertex connectivity of the graph. Qptr is an integer and points to the next graph to work on. */ igraph_vector_ptr_t Q; igraph_vector_ptr_t Qmapping; igraph_vector_long_t Qparent; igraph_vector_long_t Qcohesion; igraph_vector_bool_t Qcheck; long int Qptr = 0; igraph_integer_t conn; igraph_bool_t is_simple; igraph_t *graph_copy; igraph_vector_ptr_t separators; igraph_vector_t compvertices; igraph_vector_long_t components; igraph_vector_bool_t marked; igraph_vector_long_t compid; igraph_dqueue_t bfsQ; igraph_vector_t neis; if (igraph_is_directed(graph)) { IGRAPH_ERROR("Cohesive blocking only works on undirected graphs", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_is_simple(graph, &is_simple)); if (!is_simple) { IGRAPH_ERROR("Cohesive blocking only works on simple graphs", IGRAPH_EINVAL); } IGRAPH_STATUS("Starting cohesive block calculation.\n", 0); if (blocks) { igraph_vector_ptr_clear(blocks); } if (cohesion) { igraph_vector_clear(cohesion); } if (parent) { igraph_vector_clear(parent); } IGRAPH_CHECK(igraph_vector_ptr_init(&Q, 1)); IGRAPH_FINALLY(igraph_vector_ptr_destroy, &Q); IGRAPH_FINALLY(igraph_i_cohesive_blocks_free, &Q); IGRAPH_CHECK(igraph_vector_ptr_init(&Qmapping, 1)); IGRAPH_FINALLY(igraph_vector_ptr_destroy, &Qmapping); IGRAPH_FINALLY(igraph_i_cohesive_blocks_free2, &Qmapping); IGRAPH_CHECK(igraph_vector_long_init(&Qparent, 1)); IGRAPH_FINALLY(igraph_vector_long_destroy, &Qparent); IGRAPH_CHECK(igraph_vector_long_init(&Qcohesion, 1)); IGRAPH_FINALLY(igraph_vector_long_destroy, &Qcohesion); IGRAPH_CHECK(igraph_vector_bool_init(&Qcheck, 1)); IGRAPH_FINALLY(igraph_vector_bool_destroy, &Qcheck); IGRAPH_CHECK(igraph_vector_ptr_init(&separators, 0)); IGRAPH_FINALLY(igraph_vector_ptr_destroy, &separators); IGRAPH_VECTOR_INIT_FINALLY(&compvertices, 0); IGRAPH_CHECK(igraph_vector_bool_init(&marked, 0)); IGRAPH_FINALLY(igraph_vector_bool_destroy, &marked); IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); IGRAPH_CHECK(igraph_dqueue_init(&bfsQ, 100)); IGRAPH_FINALLY(igraph_dqueue_destroy, &bfsQ); IGRAPH_CHECK(igraph_vector_long_init(&compid, 0)); IGRAPH_FINALLY(igraph_vector_long_destroy, &compid); IGRAPH_CHECK(igraph_vector_long_init(&components, 0)); IGRAPH_FINALLY(igraph_vector_long_destroy, &components); /* Put the input graph in the queue */ graph_copy = igraph_Calloc(1, igraph_t); if (!graph_copy) { IGRAPH_ERROR("Cannot do cohesive blocking", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_copy(graph_copy, graph)); VECTOR(Q)[0] = graph_copy; VECTOR(Qmapping)[0] = 0; /* Identity mapping */ VECTOR(Qparent)[0] = -1; /* Has no parent */ IGRAPH_CHECK(igraph_vertex_connectivity(graph, &conn, /*checks=*/ 1)); VECTOR(Qcohesion)[0] = conn; VECTOR(Qcheck)[0] = 0; /* Then work until the queue is empty */ while (Qptr < igraph_vector_ptr_size(&Q)) { igraph_t *mygraph = VECTOR(Q)[Qptr]; igraph_bool_t mycheck = VECTOR(Qcheck)[Qptr]; long int mynodes = igraph_vcount(mygraph); long int i, nsep; long int no, kept = 0; long int cptr = 0; long int nsepv = 0; igraph_bool_t addedsep = 0; IGRAPH_STATUSF(("Candidate %li: %li vertices,", 0, Qptr, mynodes)); IGRAPH_ALLOW_INTERRUPTION(); /* Get the separators */ IGRAPH_CHECK(igraph_minimum_size_separators(mygraph, &separators)); IGRAPH_FINALLY(igraph_i_cohesive_blocks_free3, &separators); nsep = igraph_vector_ptr_size(&separators); IGRAPH_STATUSF((" %li separators,", 0, nsep)); /* Remove them from the graph, also mark them */ IGRAPH_CHECK(igraph_vector_bool_resize(&marked, mynodes)); igraph_vector_bool_null(&marked); for (i = 0; i < nsep; i++) { igraph_vector_t *v = VECTOR(separators)[i]; long int j, n = igraph_vector_size(v); for (j = 0; j < n; j++) { long int vv = (long int) VECTOR(*v)[j]; if (!VECTOR(marked)[vv]) { nsepv++; VECTOR(marked)[vv] = 1; } } } /* Find the connected components, omitting the separator vertices, but including the neighboring separator vertices */ IGRAPH_CHECK(igraph_i_cb_components(mygraph, &marked, &components, &no, &compid, &bfsQ, &neis)); /* Add the separator vertices themselves, as another component, but only if there is at least one vertex not included in any separator. */ if (nsepv != mynodes) { addedsep = 1; for (i = 0; i < mynodes; i++) { if (VECTOR(marked)[i]) { IGRAPH_CHECK(igraph_vector_long_push_back(&components, i)); } } IGRAPH_CHECK(igraph_vector_long_push_back(&components, -1)); no++; } IGRAPH_STATUSF((" %li new candidates,", 0, no)); for (i = 0; i < no; i++) { igraph_vector_t *newmapping; igraph_t *newgraph; igraph_integer_t maxdeg; igraph_vector_clear(&compvertices); while (1) { long int v = VECTOR(components)[cptr++]; if (v < 0) { break; } IGRAPH_CHECK(igraph_vector_push_back(&compvertices, v)); } newmapping = igraph_Calloc(1, igraph_vector_t); if (!newmapping) { IGRAPH_ERROR("Cannot do cohesive blocking", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newmapping); IGRAPH_VECTOR_INIT_FINALLY(newmapping, 0); newgraph = igraph_Calloc(1, igraph_t); if (!newgraph) { IGRAPH_ERROR("Cannot do cohesive blocking", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newgraph); IGRAPH_CHECK(igraph_induced_subgraph_map(mygraph, newgraph, igraph_vss_vector(&compvertices), IGRAPH_SUBGRAPH_AUTO, /*map=*/ 0, /*invmap=*/ newmapping)); IGRAPH_FINALLY(igraph_destroy, newgraph); IGRAPH_CHECK(igraph_maxdegree(newgraph, &maxdeg, igraph_vss_all(), IGRAPH_ALL, IGRAPH_LOOPS)); if (maxdeg > VECTOR(Qcohesion)[Qptr]) { igraph_integer_t newconn; kept++; IGRAPH_CHECK(igraph_vector_ptr_push_back(&Q, newgraph)); IGRAPH_FINALLY_CLEAN(2); IGRAPH_CHECK(igraph_vector_ptr_push_back(&Qmapping, newmapping)); IGRAPH_FINALLY_CLEAN(2); IGRAPH_CHECK(igraph_vertex_connectivity(newgraph, &newconn, /*checks=*/ 1)); IGRAPH_CHECK(igraph_vector_long_push_back(&Qcohesion, newconn)); IGRAPH_CHECK(igraph_vector_long_push_back(&Qparent, Qptr)); IGRAPH_CHECK(igraph_vector_bool_push_back(&Qcheck, mycheck || addedsep)); } else { igraph_destroy(newgraph); igraph_free(newgraph); igraph_vector_destroy(newmapping); igraph_free(newmapping); IGRAPH_FINALLY_CLEAN(4); } } IGRAPH_STATUSF((" keeping %li.\n", 0, kept)); igraph_destroy(mygraph); igraph_free(mygraph); VECTOR(Q)[Qptr] = 0; igraph_i_cohesive_blocks_free3(&separators); IGRAPH_FINALLY_CLEAN(1); Qptr++; } igraph_vector_long_destroy(&components); igraph_vector_long_destroy(&compid); igraph_dqueue_destroy(&bfsQ); igraph_vector_destroy(&neis); igraph_vector_bool_destroy(&marked); igraph_vector_destroy(&compvertices); igraph_vector_ptr_destroy(&separators); IGRAPH_FINALLY_CLEAN(7); if (blocks || cohesion || parent || block_tree) { igraph_integer_t noblocks = (igraph_integer_t) Qptr, badblocks = 0; igraph_vector_bool_t removed; long int i, resptr = 0; igraph_vector_long_t rewritemap; IGRAPH_CHECK(igraph_vector_bool_init(&removed, noblocks)); IGRAPH_FINALLY(igraph_vector_bool_destroy, &removed); IGRAPH_CHECK(igraph_vector_long_init(&rewritemap, noblocks)); IGRAPH_FINALLY(igraph_vector_long_destroy, &rewritemap); for (i = 1; i < noblocks; i++) { long int p = VECTOR(Qparent)[i]; while (VECTOR(removed)[p]) { p = VECTOR(Qparent)[p]; } if (VECTOR(Qcohesion)[p] >= VECTOR(Qcohesion)[i]) { VECTOR(removed)[i] = 1; badblocks++; } } /* Rewrite the mappings */ for (i = 1; i < Qptr; i++) { long int p = VECTOR(Qparent)[i]; igraph_vector_t *mapping = VECTOR(Qmapping)[i]; igraph_vector_t *pmapping = VECTOR(Qmapping)[p]; long int j, n = igraph_vector_size(mapping); if (!pmapping) { continue; } for (j = 0; j < n; j++) { long int v = (long int) VECTOR(*mapping)[j]; VECTOR(*mapping)[j] = VECTOR(*pmapping)[v]; } } /* Because we also put the separator vertices in the queue, it is not ensured that the found blocks are not subsets of each other. We check this now. */ for (i = 1; i < noblocks; i++) { long int j, ic; igraph_vector_t *ivec; if (!VECTOR(Qcheck)[i] || VECTOR(removed)[i]) { continue; } ivec = VECTOR(Qmapping)[i]; ic = VECTOR(Qcohesion)[i]; for (j = 1; j < noblocks; j++) { igraph_vector_t *jvec; long int jc; if (j == i || !VECTOR(Qcheck)[j] || VECTOR(removed)[j]) { continue; } jvec = VECTOR(Qmapping)[j]; jc = VECTOR(Qcohesion)[j]; if (igraph_i_cb_isin(ivec, jvec) && jc >= ic) { badblocks++; VECTOR(removed)[i] = 1; break; } } } noblocks -= badblocks; if (blocks) { IGRAPH_CHECK(igraph_vector_ptr_resize(blocks, noblocks)); } if (cohesion) { IGRAPH_CHECK(igraph_vector_resize(cohesion, noblocks)); } if (parent) { IGRAPH_CHECK(igraph_vector_resize(parent, noblocks)); } for (i = 0; i < Qptr; i++) { if (VECTOR(removed)[i]) { IGRAPH_STATUSF(("Candidate %li ignored.\n", 0, i)); continue; } else { IGRAPH_STATUSF(("Candidate %li is a cohesive (sub)block\n", 0, i)); } VECTOR(rewritemap)[i] = resptr; if (cohesion) { VECTOR(*cohesion)[resptr] = VECTOR(Qcohesion)[i]; } if (parent || block_tree) { long int p = VECTOR(Qparent)[i]; while (p >= 0 && VECTOR(removed)[p]) { p = VECTOR(Qparent)[p]; } if (p >= 0) { p = VECTOR(rewritemap)[p]; } VECTOR(Qparent)[i] = p; if (parent) { VECTOR(*parent)[resptr] = p; } } if (blocks) { VECTOR(*blocks)[resptr] = VECTOR(Qmapping)[i]; VECTOR(Qmapping)[i] = 0; } resptr++; } /* Plus the original graph */ if (blocks) { igraph_vector_t *orig = igraph_Calloc(1, igraph_vector_t); if (!orig) { IGRAPH_ERROR("Cannot do cohesive blocking", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, orig); IGRAPH_CHECK(igraph_vector_init_seq(orig, 0, igraph_vcount(graph) - 1)); VECTOR(*blocks)[0] = orig; IGRAPH_FINALLY_CLEAN(1); } if (block_tree) { igraph_vector_t edges; long int eptr = 0; IGRAPH_VECTOR_INIT_FINALLY(&edges, noblocks * 2 - 2); for (i = 1; i < Qptr; i++) { if (VECTOR(removed)[i]) { continue; } VECTOR(edges)[eptr++] = VECTOR(Qparent)[i]; VECTOR(edges)[eptr++] = VECTOR(rewritemap)[i]; } IGRAPH_CHECK(igraph_create(block_tree, &edges, noblocks, IGRAPH_DIRECTED)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); } igraph_vector_long_destroy(&rewritemap); igraph_vector_bool_destroy(&removed); IGRAPH_FINALLY_CLEAN(2); } igraph_vector_bool_destroy(&Qcheck); igraph_vector_long_destroy(&Qcohesion); igraph_vector_long_destroy(&Qparent); igraph_i_cohesive_blocks_free2(&Qmapping); IGRAPH_FINALLY_CLEAN(4); igraph_vector_ptr_destroy(&Qmapping); igraph_vector_ptr_destroy(&Q); IGRAPH_FINALLY_CLEAN(3); /* + the elements of Q, they were already destroyed */ IGRAPH_STATUS("Cohesive blocking done.\n", 0); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/type_indexededgelist.c0000644000076500000240000016634113614300625025757 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2005-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_datatype.h" #include "igraph_interface.h" #include "igraph_attributes.h" #include "igraph_memory.h" #include /* memset & co. */ #include "config.h" /* Internal functions */ int igraph_i_create_start(igraph_vector_t *res, igraph_vector_t *el, igraph_vector_t *index, igraph_integer_t nodes); /** * \section about_basic_interface * * This is the very minimal API in \a igraph. All the other * functions use this minimal set for creating and manipulating * graphs. * * This is a very important principle since it makes possible to * implement other data representations by implementing only this * minimal set. */ /** * \ingroup interface * \function igraph_empty * \brief Creates an empty graph with some vertices and no edges. * * * The most basic constructor, all the other constructors should call * this to create a minimal graph object. Our use of the term "empty graph" * in the above description should be distinguished from the mathematical * definition of the empty or null graph. Strictly speaking, the empty or null * graph in graph theory is the graph with no vertices and no edges. However * by "empty graph" as used in \c igraph we mean a graph having zero or more * vertices, but no edges. * \param graph Pointer to a not-yet initialized graph object. * \param n The number of vertices in the graph, a non-negative * integer number is expected. * \param directed Boolean; whether the graph is directed or not. Supported * values are: * \clist * \cli IGRAPH_DIRECTED * The graph will be \em directed. * \cli IGRAPH_UNDIRECTED * The graph will be \em undirected. * \endclist * \return Error code: * \c IGRAPH_EINVAL: invalid number of vertices. * * Time complexity: O(|V|) for a graph with * |V| vertices (and no edges). * * \example examples/simple/igraph_empty.c */ int igraph_empty(igraph_t *graph, igraph_integer_t n, igraph_bool_t directed) { return igraph_empty_attrs(graph, n, directed, 0); } /** * \ingroup interface * \function igraph_empty_attrs * \brief Creates an empty graph with some vertices, no edges and some graph attributes. * * * Use this instead of \ref igraph_empty() if you wish to add some graph * attributes right after initialization. This function is currently * not very interesting for the ordinary user. Just supply 0 here or * use \ref igraph_empty(). * \param graph Pointer to a not-yet initialized graph object. * \param n The number of vertices in the graph; a non-negative * integer number is expected. * \param directed Boolean; whether the graph is directed or not. Supported * values are: * \clist * \cli IGRAPH_DIRECTED * Create a \em directed graph. * \cli IGRAPH_UNDIRECTED * Create an \em undirected graph. * \endclist * \param attr The attributes. * \return Error code: * \c IGRAPH_EINVAL: invalid number of vertices. * * Time complexity: O(|V|) for a graph with * |V| vertices (and no edges). */ int igraph_empty_attrs(igraph_t *graph, igraph_integer_t n, igraph_bool_t directed, void* attr) { if (n < 0) { IGRAPH_ERROR("cannot create empty graph with negative number of vertices", IGRAPH_EINVAL); } if (!IGRAPH_FINITE(n)) { IGRAPH_ERROR("number of vertices is not finite (NA, NaN or Inf)", IGRAPH_EINVAL); } graph->n = 0; graph->directed = directed; IGRAPH_VECTOR_INIT_FINALLY(&graph->from, 0); IGRAPH_VECTOR_INIT_FINALLY(&graph->to, 0); IGRAPH_VECTOR_INIT_FINALLY(&graph->oi, 0); IGRAPH_VECTOR_INIT_FINALLY(&graph->ii, 0); IGRAPH_VECTOR_INIT_FINALLY(&graph->os, 1); IGRAPH_VECTOR_INIT_FINALLY(&graph->is, 1); VECTOR(graph->os)[0] = 0; VECTOR(graph->is)[0] = 0; /* init attributes */ graph->attr = 0; IGRAPH_CHECK(igraph_i_attribute_init(graph, attr)); /* add the vertices */ IGRAPH_CHECK(igraph_add_vertices(graph, n, 0)); IGRAPH_FINALLY_CLEAN(6); return 0; } /** * \ingroup interface * \function igraph_destroy * \brief Frees the memory allocated for a graph object. * * * This function should be called for every graph object exactly once. * * * This function invalidates all iterators (of course), but the * iterators of a graph should be destroyed before the graph itself * anyway. * \param graph Pointer to the graph to free. * * Time complexity: operating system specific. */ void igraph_destroy(igraph_t *graph) { IGRAPH_I_ATTRIBUTE_DESTROY(graph); igraph_vector_destroy(&graph->from); igraph_vector_destroy(&graph->to); igraph_vector_destroy(&graph->oi); igraph_vector_destroy(&graph->ii); igraph_vector_destroy(&graph->os); igraph_vector_destroy(&graph->is); } /** * \ingroup interface * \function igraph_copy * \brief Creates an exact (deep) copy of a graph. * * * This function deeply copies a graph object to create an exact * replica of it. The new replica should be destroyed by calling * \ref igraph_destroy() on it when not needed any more. * * * You can also create a shallow copy of a graph by simply using the * standard assignment operator, but be careful and do \em not * destroy a shallow replica. To avoid this mistake, creating shallow * copies is not recommended. * \param to Pointer to an uninitialized graph object. * \param from Pointer to the graph object to copy. * \return Error code. * * Time complexity: O(|V|+|E|) for a * graph with |V| vertices and * |E| edges. * * \example examples/simple/igraph_copy.c */ int igraph_copy(igraph_t *to, const igraph_t *from) { to->n = from->n; to->directed = from->directed; IGRAPH_CHECK(igraph_vector_copy(&to->from, &from->from)); IGRAPH_FINALLY(igraph_vector_destroy, &to->from); IGRAPH_CHECK(igraph_vector_copy(&to->to, &from->to)); IGRAPH_FINALLY(igraph_vector_destroy, &to->to); IGRAPH_CHECK(igraph_vector_copy(&to->oi, &from->oi)); IGRAPH_FINALLY(igraph_vector_destroy, &to->oi); IGRAPH_CHECK(igraph_vector_copy(&to->ii, &from->ii)); IGRAPH_FINALLY(igraph_vector_destroy, &to->ii); IGRAPH_CHECK(igraph_vector_copy(&to->os, &from->os)); IGRAPH_FINALLY(igraph_vector_destroy, &to->os); IGRAPH_CHECK(igraph_vector_copy(&to->is, &from->is)); IGRAPH_FINALLY(igraph_vector_destroy, &to->is); IGRAPH_I_ATTRIBUTE_COPY(to, from, 1, 1, 1); /* does IGRAPH_CHECK */ IGRAPH_FINALLY_CLEAN(6); return 0; } /** * \ingroup interface * \function igraph_add_edges * \brief Adds edges to a graph object. * * * The edges are given in a vector, the * first two elements define the first edge (the order is * from, to for directed * graphs). The vector * should contain even number of integer numbers between zero and the * number of vertices in the graph minus one (inclusive). If you also * want to add new vertices, call igraph_add_vertices() first. * \param graph The graph to which the edges will be added. * \param edges The edges themselves. * \param attr The attributes of the new edges, only used by high level * interfaces currently, you can supply 0 here. * \return Error code: * \c IGRAPH_EINVEVECTOR: invalid (odd) * edges vector length, \c IGRAPH_EINVVID: * invalid vertex id in edges vector. * * This function invalidates all iterators. * * * Time complexity: O(|V|+|E|) where * |V| is the number of vertices and * |E| is the number of * edges in the \em new, extended graph. * * \example examples/simple/igraph_add_edges.c */ int igraph_add_edges(igraph_t *graph, const igraph_vector_t *edges, void *attr) { long int no_of_edges = igraph_vector_size(&graph->from); long int edges_to_add = igraph_vector_size(edges) / 2; long int i = 0; igraph_error_handler_t *oldhandler; int ret1, ret2; igraph_vector_t newoi, newii; igraph_bool_t directed = igraph_is_directed(graph); if (igraph_vector_size(edges) % 2 != 0) { IGRAPH_ERROR("invalid (odd) length of edges vector", IGRAPH_EINVEVECTOR); } if (!igraph_vector_isininterval(edges, 0, igraph_vcount(graph) - 1)) { IGRAPH_ERROR("cannot add edges", IGRAPH_EINVVID); } /* from & to */ IGRAPH_CHECK(igraph_vector_reserve(&graph->from, no_of_edges + edges_to_add)); IGRAPH_CHECK(igraph_vector_reserve(&graph->to, no_of_edges + edges_to_add)); while (i < edges_to_add * 2) { if (directed || VECTOR(*edges)[i] > VECTOR(*edges)[i + 1]) { igraph_vector_push_back(&graph->from, VECTOR(*edges)[i++]); /* reserved */ igraph_vector_push_back(&graph->to, VECTOR(*edges)[i++]); /* reserved */ } else { igraph_vector_push_back(&graph->to, VECTOR(*edges)[i++]); /* reserved */ igraph_vector_push_back(&graph->from, VECTOR(*edges)[i++]); /* reserved */ } } /* disable the error handler temporarily */ oldhandler = igraph_set_error_handler(igraph_error_handler_ignore); /* oi & ii */ ret1 = igraph_vector_init(&newoi, no_of_edges); ret2 = igraph_vector_init(&newii, no_of_edges); if (ret1 != 0 || ret2 != 0) { igraph_vector_resize(&graph->from, no_of_edges); /* gets smaller */ igraph_vector_resize(&graph->to, no_of_edges); /* gets smaller */ igraph_set_error_handler(oldhandler); IGRAPH_ERROR("cannot add edges", IGRAPH_ERROR_SELECT_2(ret1, ret2)); } ret1 = igraph_vector_order(&graph->from, &graph->to, &newoi, graph->n); ret2 = igraph_vector_order(&graph->to, &graph->from, &newii, graph->n); if (ret1 != 0 || ret2 != 0) { igraph_vector_resize(&graph->from, no_of_edges); igraph_vector_resize(&graph->to, no_of_edges); igraph_vector_destroy(&newoi); igraph_vector_destroy(&newii); igraph_set_error_handler(oldhandler); IGRAPH_ERROR("cannot add edges", IGRAPH_ERROR_SELECT_2(ret1, ret2)); } /* Attributes */ if (graph->attr) { igraph_set_error_handler(oldhandler); ret1 = igraph_i_attribute_add_edges(graph, edges, attr); igraph_set_error_handler(igraph_error_handler_ignore); if (ret1 != 0) { igraph_vector_resize(&graph->from, no_of_edges); igraph_vector_resize(&graph->to, no_of_edges); igraph_vector_destroy(&newoi); igraph_vector_destroy(&newii); igraph_set_error_handler(oldhandler); IGRAPH_ERROR("cannot add edges", ret1); } } /* os & is, its length does not change, error safe */ igraph_i_create_start(&graph->os, &graph->from, &newoi, graph->n); igraph_i_create_start(&graph->is, &graph->to, &newii, graph->n); /* everything went fine */ igraph_vector_destroy(&graph->oi); igraph_vector_destroy(&graph->ii); graph->oi = newoi; graph->ii = newii; igraph_set_error_handler(oldhandler); return 0; } /** * \ingroup interface * \function igraph_add_vertices * \brief Adds vertices to a graph. * * * This function invalidates all iterators. * * \param graph The graph object to extend. * \param nv Non-negative integer giving the number of * vertices to add. * \param attr The attributes of the new vertices, only used by * high level interfaces, you can supply 0 here. * \return Error code: * \c IGRAPH_EINVAL: invalid number of new * vertices. * * Time complexity: O(|V|) where * |V| is * the number of vertices in the \em new, extended graph. * * \example examples/simple/igraph_add_vertices.c */ int igraph_add_vertices(igraph_t *graph, igraph_integer_t nv, void *attr) { long int ec = igraph_ecount(graph); long int i; if (nv < 0) { IGRAPH_ERROR("cannot add negative number of vertices", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_vector_reserve(&graph->os, graph->n + nv + 1)); IGRAPH_CHECK(igraph_vector_reserve(&graph->is, graph->n + nv + 1)); igraph_vector_resize(&graph->os, graph->n + nv + 1); /* reserved */ igraph_vector_resize(&graph->is, graph->n + nv + 1); /* reserved */ for (i = graph->n + 1; i < graph->n + nv + 1; i++) { VECTOR(graph->os)[i] = ec; VECTOR(graph->is)[i] = ec; } graph->n += nv; if (graph->attr) { IGRAPH_CHECK(igraph_i_attribute_add_vertices(graph, nv, attr)); } return 0; } /** * \ingroup interface * \function igraph_delete_edges * \brief Removes edges from a graph. * * * The edges to remove are given as an edge selector. * * * This function cannot remove vertices, they will be kept, even if * they lose all their edges. * * * This function invalidates all iterators. * \param graph The graph to work on. * \param edges The edges to remove. * \return Error code. * * Time complexity: O(|V|+|E|) where * |V| * and |E| are the number of vertices * and edges in the \em original graph, respectively. * * \example examples/simple/igraph_delete_edges.c */ int igraph_delete_edges(igraph_t *graph, igraph_es_t edges) { long int no_of_edges = igraph_ecount(graph); long int no_of_nodes = igraph_vcount(graph); long int edges_to_remove = 0; long int remaining_edges; igraph_eit_t eit; igraph_vector_t newfrom, newto, newoi; int *mark; long int i, j; mark = igraph_Calloc(no_of_edges, int); if (mark == 0) { IGRAPH_ERROR("Cannot delete edges", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, mark); IGRAPH_CHECK(igraph_eit_create(graph, edges, &eit)); IGRAPH_FINALLY(igraph_eit_destroy, &eit); for (IGRAPH_EIT_RESET(eit); !IGRAPH_EIT_END(eit); IGRAPH_EIT_NEXT(eit)) { long int e = IGRAPH_EIT_GET(eit); if (mark[e] == 0) { edges_to_remove++; mark[e]++; } } remaining_edges = no_of_edges - edges_to_remove; /* We don't need the iterator any more */ igraph_eit_destroy(&eit); IGRAPH_FINALLY_CLEAN(1); IGRAPH_VECTOR_INIT_FINALLY(&newfrom, remaining_edges); IGRAPH_VECTOR_INIT_FINALLY(&newto, remaining_edges); /* Actually remove the edges, move from pos i to pos j in newfrom/newto */ for (i = 0, j = 0; j < remaining_edges; i++) { if (mark[i] == 0) { VECTOR(newfrom)[j] = VECTOR(graph->from)[i]; VECTOR(newto)[j] = VECTOR(graph->to)[i]; j++; } } /* Create index, this might require additional memory */ IGRAPH_VECTOR_INIT_FINALLY(&newoi, remaining_edges); IGRAPH_CHECK(igraph_vector_order(&newfrom, &newto, &newoi, no_of_nodes)); IGRAPH_CHECK(igraph_vector_order(&newto, &newfrom, &graph->ii, no_of_nodes)); /* Edge attributes, we need an index that gives the ids of the original edges for every new edge. */ if (graph->attr) { igraph_vector_t idx; IGRAPH_VECTOR_INIT_FINALLY(&idx, remaining_edges); for (i = 0, j = 0; i < no_of_edges; i++) { if (mark[i] == 0) { VECTOR(idx)[j++] = i; } } IGRAPH_CHECK(igraph_i_attribute_permute_edges(graph, graph, &idx)); igraph_vector_destroy(&idx); IGRAPH_FINALLY_CLEAN(1); } /* Ok, we've all memory needed, free the old structure */ igraph_vector_destroy(&graph->from); igraph_vector_destroy(&graph->to); igraph_vector_destroy(&graph->oi); graph->from = newfrom; graph->to = newto; graph->oi = newoi; IGRAPH_FINALLY_CLEAN(3); igraph_Free(mark); IGRAPH_FINALLY_CLEAN(1); /* Create start vectors, no memory is needed for this */ igraph_i_create_start(&graph->os, &graph->from, &graph->oi, (igraph_integer_t) no_of_nodes); igraph_i_create_start(&graph->is, &graph->to, &graph->ii, (igraph_integer_t) no_of_nodes); /* Nothing to deallocate... */ return 0; } /** * \ingroup interface * \function igraph_delete_vertices * \brief Removes vertices (with all their edges) from the graph. * * * This function changes the ids of the vertices (except in some very * special cases, but these should not be relied on anyway). * * * This function invalidates all iterators. * * \param graph The graph to work on. * \param vertices The ids of the vertices to remove in a * vector. The vector may contain the same id more * than once. * \return Error code: * \c IGRAPH_EINVVID: invalid vertex id. * * Time complexity: O(|V|+|E|), * |V| and * |E| are the number of vertices and * edges in the original graph. * * \example examples/simple/igraph_delete_vertices.c */ int igraph_delete_vertices(igraph_t *graph, const igraph_vs_t vertices) { return igraph_delete_vertices_idx(graph, vertices, /* idx= */ 0, /* invidx= */ 0); } int igraph_delete_vertices_idx(igraph_t *graph, const igraph_vs_t vertices, igraph_vector_t *idx, igraph_vector_t *invidx) { long int no_of_edges = igraph_ecount(graph); long int no_of_nodes = igraph_vcount(graph); igraph_vector_t edge_recoding, vertex_recoding; igraph_vector_t *my_vertex_recoding = &vertex_recoding; igraph_vit_t vit; igraph_t newgraph; long int i, j; long int remaining_vertices, remaining_edges; if (idx) { my_vertex_recoding = idx; IGRAPH_CHECK(igraph_vector_resize(idx, no_of_nodes)); igraph_vector_null(idx); } else { IGRAPH_VECTOR_INIT_FINALLY(&vertex_recoding, no_of_nodes); } IGRAPH_VECTOR_INIT_FINALLY(&edge_recoding, no_of_edges); IGRAPH_CHECK(igraph_vit_create(graph, vertices, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); /* mark the vertices to delete */ for (; !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit) ) { long int vertex = IGRAPH_VIT_GET(vit); if (vertex < 0 || vertex >= no_of_nodes) { IGRAPH_ERROR("Cannot delete vertices", IGRAPH_EINVVID); } VECTOR(*my_vertex_recoding)[vertex] = 1; } /* create vertex recoding vector */ for (remaining_vertices = 0, i = 0; i < no_of_nodes; i++) { if (VECTOR(*my_vertex_recoding)[i] == 0) { VECTOR(*my_vertex_recoding)[i] = remaining_vertices + 1; remaining_vertices++; } else { VECTOR(*my_vertex_recoding)[i] = 0; } } /* create edge recoding vector */ for (remaining_edges = 0, i = 0; i < no_of_edges; i++) { long int from = (long int) VECTOR(graph->from)[i]; long int to = (long int) VECTOR(graph->to)[i]; if (VECTOR(*my_vertex_recoding)[from] != 0 && VECTOR(*my_vertex_recoding)[to ] != 0) { VECTOR(edge_recoding)[i] = remaining_edges + 1; remaining_edges++; } } /* start creating the graph */ newgraph.n = (igraph_integer_t) remaining_vertices; newgraph.directed = graph->directed; /* allocate vectors */ IGRAPH_VECTOR_INIT_FINALLY(&newgraph.from, remaining_edges); IGRAPH_VECTOR_INIT_FINALLY(&newgraph.to, remaining_edges); IGRAPH_VECTOR_INIT_FINALLY(&newgraph.oi, remaining_edges); IGRAPH_VECTOR_INIT_FINALLY(&newgraph.ii, remaining_edges); IGRAPH_VECTOR_INIT_FINALLY(&newgraph.os, remaining_vertices + 1); IGRAPH_VECTOR_INIT_FINALLY(&newgraph.is, remaining_vertices + 1); /* Add the edges */ for (i = 0, j = 0; j < remaining_edges; i++) { if (VECTOR(edge_recoding)[i] > 0) { long int from = (long int) VECTOR(graph->from)[i]; long int to = (long int) VECTOR(graph->to )[i]; VECTOR(newgraph.from)[j] = VECTOR(*my_vertex_recoding)[from] - 1; VECTOR(newgraph.to )[j] = VECTOR(*my_vertex_recoding)[to] - 1; j++; } } /* update oi & ii */ IGRAPH_CHECK(igraph_vector_order(&newgraph.from, &newgraph.to, &newgraph.oi, remaining_vertices)); IGRAPH_CHECK(igraph_vector_order(&newgraph.to, &newgraph.from, &newgraph.ii, remaining_vertices)); IGRAPH_CHECK(igraph_i_create_start(&newgraph.os, &newgraph.from, &newgraph.oi, (igraph_integer_t) remaining_vertices)); IGRAPH_CHECK(igraph_i_create_start(&newgraph.is, &newgraph.to, &newgraph.ii, (igraph_integer_t) remaining_vertices)); /* attributes */ IGRAPH_I_ATTRIBUTE_COPY(&newgraph, graph, /*graph=*/ 1, /*vertex=*/0, /*edge=*/0); IGRAPH_FINALLY_CLEAN(6); IGRAPH_FINALLY(igraph_destroy, &newgraph); if (newgraph.attr) { igraph_vector_t iidx; IGRAPH_VECTOR_INIT_FINALLY(&iidx, remaining_vertices); for (i = 0; i < no_of_nodes; i++) { long int jj = (long int) VECTOR(*my_vertex_recoding)[i]; if (jj != 0) { VECTOR(iidx)[ jj - 1 ] = i; } } IGRAPH_CHECK(igraph_i_attribute_permute_vertices(graph, &newgraph, &iidx)); IGRAPH_CHECK(igraph_vector_resize(&iidx, remaining_edges)); for (i = 0; i < no_of_edges; i++) { long int jj = (long int) VECTOR(edge_recoding)[i]; if (jj != 0) { VECTOR(iidx)[ jj - 1 ] = i; } } IGRAPH_CHECK(igraph_i_attribute_permute_edges(graph, &newgraph, &iidx)); igraph_vector_destroy(&iidx); IGRAPH_FINALLY_CLEAN(1); } igraph_vit_destroy(&vit); igraph_vector_destroy(&edge_recoding); igraph_destroy(graph); *graph = newgraph; IGRAPH_FINALLY_CLEAN(3); /* TODO: this is duplicate */ if (invidx) { IGRAPH_CHECK(igraph_vector_resize(invidx, remaining_vertices)); for (i = 0; i < no_of_nodes; i++) { long int newid = (long int) VECTOR(*my_vertex_recoding)[i]; if (newid != 0) { VECTOR(*invidx)[newid - 1] = i; } } } if (!idx) { igraph_vector_destroy(my_vertex_recoding); IGRAPH_FINALLY_CLEAN(1); } return 0; } /** * \ingroup interface * \function igraph_vcount * \brief The number of vertices in a graph. * * \param graph The graph. * \return Number of vertices. * * Time complexity: O(1) */ igraph_integer_t igraph_vcount(const igraph_t *graph) { return graph->n; } /** * \ingroup interface * \function igraph_ecount * \brief The number of edges in a graph. * * \param graph The graph. * \return Number of edges. * * Time complexity: O(1) */ igraph_integer_t igraph_ecount(const igraph_t *graph) { return (igraph_integer_t) igraph_vector_size(&graph->from); } /** * \ingroup interface * \function igraph_neighbors * \brief Adjacent vertices to a vertex. * * \param graph The graph to work on. * \param neis This vector will contain the result. The vector should * be initialized beforehand and will be resized. Starting from igraph * version 0.4 this vector is always sorted, the vertex ids are * in increasing order. * \param pnode The id of the node for which the adjacent vertices are * to be searched. * \param mode Defines the way adjacent vertices are searched in * directed graphs. It can have the following values: * \c IGRAPH_OUT, vertices reachable by an * edge from the specified vertex are searched; * \c IGRAPH_IN, vertices from which the * specified vertex is reachable are searched; * \c IGRAPH_ALL, both kinds of vertices are * searched. * This parameter is ignored for undirected graphs. * \return Error code: * \c IGRAPH_EINVVID: invalid vertex id. * \c IGRAPH_EINVMODE: invalid mode argument. * \c IGRAPH_ENOMEM: not enough memory. * * Time complexity: O(d), * d is the number * of adjacent vertices to the queried vertex. * * \example examples/simple/igraph_neighbors.c */ int igraph_neighbors(const igraph_t *graph, igraph_vector_t *neis, igraph_integer_t pnode, igraph_neimode_t mode) { long int length = 0, idx = 0; long int i, j; long int node = pnode; if (node < 0 || node > igraph_vcount(graph) - 1) { IGRAPH_ERROR("cannot get neighbors", IGRAPH_EINVVID); } if (mode != IGRAPH_OUT && mode != IGRAPH_IN && mode != IGRAPH_ALL) { IGRAPH_ERROR("cannot get neighbors", IGRAPH_EINVMODE); } if (! graph->directed) { mode = IGRAPH_ALL; } /* Calculate needed space first & allocate it*/ if (mode & IGRAPH_OUT) { length += (VECTOR(graph->os)[node + 1] - VECTOR(graph->os)[node]); } if (mode & IGRAPH_IN) { length += (VECTOR(graph->is)[node + 1] - VECTOR(graph->is)[node]); } IGRAPH_CHECK(igraph_vector_resize(neis, length)); if (!igraph_is_directed(graph) || mode != IGRAPH_ALL) { if (mode & IGRAPH_OUT) { j = (long int) VECTOR(graph->os)[node + 1]; for (i = (long int) VECTOR(graph->os)[node]; i < j; i++) { VECTOR(*neis)[idx++] = VECTOR(graph->to)[ (long int)VECTOR(graph->oi)[i] ]; } } if (mode & IGRAPH_IN) { j = (long int) VECTOR(graph->is)[node + 1]; for (i = (long int) VECTOR(graph->is)[node]; i < j; i++) { VECTOR(*neis)[idx++] = VECTOR(graph->from)[ (long int)VECTOR(graph->ii)[i] ]; } } } else { /* both in- and out- neighbors in a directed graph, we need to merge the two 'vectors' */ long int jj1 = (long int) VECTOR(graph->os)[node + 1]; long int j2 = (long int) VECTOR(graph->is)[node + 1]; long int i1 = (long int) VECTOR(graph->os)[node]; long int i2 = (long int) VECTOR(graph->is)[node]; while (i1 < jj1 && i2 < j2) { long int n1 = (long int) VECTOR(graph->to)[ (long int)VECTOR(graph->oi)[i1] ]; long int n2 = (long int) VECTOR(graph->from)[ (long int)VECTOR(graph->ii)[i2] ]; if (n1 < n2) { VECTOR(*neis)[idx++] = n1; i1++; } else if (n1 > n2) { VECTOR(*neis)[idx++] = n2; i2++; } else { VECTOR(*neis)[idx++] = n1; VECTOR(*neis)[idx++] = n2; i1++; i2++; } } while (i1 < jj1) { long int n1 = (long int) VECTOR(graph->to)[ (long int)VECTOR(graph->oi)[i1] ]; VECTOR(*neis)[idx++] = n1; i1++; } while (i2 < j2) { long int n2 = (long int) VECTOR(graph->from)[ (long int)VECTOR(graph->ii)[i2] ]; VECTOR(*neis)[idx++] = n2; i2++; } } return 0; } /** * \ingroup internal * */ int igraph_i_create_start(igraph_vector_t *res, igraph_vector_t *el, igraph_vector_t *iindex, igraph_integer_t nodes) { # define EDGE(i) (VECTOR(*el)[ (long int) VECTOR(*iindex)[(i)] ]) long int no_of_nodes; long int no_of_edges; long int i, j, idx; no_of_nodes = nodes; no_of_edges = igraph_vector_size(el); /* result */ IGRAPH_CHECK(igraph_vector_resize(res, nodes + 1)); /* create the index */ if (igraph_vector_size(el) == 0) { /* empty graph */ igraph_vector_null(res); } else { idx = -1; for (i = 0; i <= EDGE(0); i++) { idx++; VECTOR(*res)[idx] = 0; } for (i = 1; i < no_of_edges; i++) { long int n = (long int) (EDGE(i) - EDGE((long int)VECTOR(*res)[idx])); for (j = 0; j < n; j++) { idx++; VECTOR(*res)[idx] = i; } } j = (long int) EDGE((long int)VECTOR(*res)[idx]); for (i = 0; i < no_of_nodes - j; i++) { idx++; VECTOR(*res)[idx] = no_of_edges; } } /* clean */ # undef EDGE return 0; } /** * \ingroup interface * \function igraph_is_directed * \brief Is this a directed graph? * * \param graph The graph. * \return Logical value, TRUE if the graph is directed, * FALSE otherwise. * * Time complexity: O(1) * * \example examples/simple/igraph_is_directed.c */ igraph_bool_t igraph_is_directed(const igraph_t *graph) { return graph->directed; } /** * \ingroup interface * \function igraph_degree * \brief The degree of some vertices in a graph. * * * This function calculates the in-, out- or total degree of the * specified vertices. * \param graph The graph. * \param res Vector, this will contain the result. It should be * initialized and will be resized to be the appropriate size. * \param vids Vector, giving the vertex ids of which the degree will * be calculated. * \param mode Defines the type of the degree. Valid modes are: * \c IGRAPH_OUT, out-degree; * \c IGRAPH_IN, in-degree; * \c IGRAPH_ALL, total degree (sum of the * in- and out-degree). * This parameter is ignored for undirected graphs. * \param loops Boolean, gives whether the self-loops should be * counted. * \return Error code: * \c IGRAPH_EINVVID: invalid vertex id. * \c IGRAPH_EINVMODE: invalid mode argument. * * Time complexity: O(v) if * loops is * TRUE, and * O(v*d) * otherwise. v is the number of * vertices for which the degree will be calculated, and * d is their (average) degree. * * \sa \ref igraph_strength() for the version that takes into account * edge weights. * * \example examples/simple/igraph_degree.c */ int igraph_degree(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, igraph_neimode_t mode, igraph_bool_t loops) { long int nodes_to_calc; long int i, j; igraph_vit_t vit; IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); if (mode != IGRAPH_OUT && mode != IGRAPH_IN && mode != IGRAPH_ALL) { IGRAPH_ERROR("degree calculation failed", IGRAPH_EINVMODE); } nodes_to_calc = IGRAPH_VIT_SIZE(vit); if (!igraph_is_directed(graph)) { mode = IGRAPH_ALL; } IGRAPH_CHECK(igraph_vector_resize(res, nodes_to_calc)); igraph_vector_null(res); if (loops) { if (mode & IGRAPH_OUT) { for (IGRAPH_VIT_RESET(vit), i = 0; !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit), i++) { long int vid = IGRAPH_VIT_GET(vit); VECTOR(*res)[i] += (VECTOR(graph->os)[vid + 1] - VECTOR(graph->os)[vid]); } } if (mode & IGRAPH_IN) { for (IGRAPH_VIT_RESET(vit), i = 0; !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit), i++) { long int vid = IGRAPH_VIT_GET(vit); VECTOR(*res)[i] += (VECTOR(graph->is)[vid + 1] - VECTOR(graph->is)[vid]); } } } else { /* no loops */ if (mode & IGRAPH_OUT) { for (IGRAPH_VIT_RESET(vit), i = 0; !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit), i++) { long int vid = IGRAPH_VIT_GET(vit); VECTOR(*res)[i] += (VECTOR(graph->os)[vid + 1] - VECTOR(graph->os)[vid]); for (j = (long int) VECTOR(graph->os)[vid]; j < VECTOR(graph->os)[vid + 1]; j++) { if (VECTOR(graph->to)[ (long int)VECTOR(graph->oi)[j] ] == vid) { VECTOR(*res)[i] -= 1; } } } } if (mode & IGRAPH_IN) { for (IGRAPH_VIT_RESET(vit), i = 0; !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit), i++) { long int vid = IGRAPH_VIT_GET(vit); VECTOR(*res)[i] += (VECTOR(graph->is)[vid + 1] - VECTOR(graph->is)[vid]); for (j = (long int) VECTOR(graph->is)[vid]; j < VECTOR(graph->is)[vid + 1]; j++) { if (VECTOR(graph->from)[ (long int)VECTOR(graph->ii)[j] ] == vid) { VECTOR(*res)[i] -= 1; } } } } } /* loops */ igraph_vit_destroy(&vit); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_edge * \brief Gives the head and tail vertices of an edge. * * \param graph The graph object. * \param eid The edge id. * \param from Pointer to an \type igraph_integer_t. The tail of the edge * will be placed here. * \param to Pointer to an \type igraph_integer_t. The head of the edge * will be placed here. * \return Error code. The current implementation always returns with * success. * \sa \ref igraph_get_eid() for the opposite operation. * * Added in version 0.2. * * Time complexity: O(1). */ int igraph_edge(const igraph_t *graph, igraph_integer_t eid, igraph_integer_t *from, igraph_integer_t *to) { if (igraph_is_directed(graph)) { *from = (igraph_integer_t) VECTOR(graph->from)[(long int)eid]; *to = (igraph_integer_t) VECTOR(graph->to )[(long int)eid]; } else { *from = (igraph_integer_t) VECTOR(graph->to )[(long int)eid]; *to = (igraph_integer_t) VECTOR(graph->from)[(long int)eid]; } return 0; } int igraph_edges(const igraph_t *graph, igraph_es_t eids, igraph_vector_t *edges) { igraph_eit_t eit; long int n, ptr = 0; IGRAPH_CHECK(igraph_eit_create(graph, eids, &eit)); IGRAPH_FINALLY(igraph_eit_destroy, &eit); n = IGRAPH_EIT_SIZE(eit); IGRAPH_CHECK(igraph_vector_resize(edges, n * 2)); if (igraph_is_directed(graph)) { for (; !IGRAPH_EIT_END(eit); IGRAPH_EIT_NEXT(eit)) { long int e = IGRAPH_EIT_GET(eit); VECTOR(*edges)[ptr++] = IGRAPH_FROM(graph, e); VECTOR(*edges)[ptr++] = IGRAPH_TO(graph, e); } } else { for (; !IGRAPH_EIT_END(eit); IGRAPH_EIT_NEXT(eit)) { long int e = IGRAPH_EIT_GET(eit); VECTOR(*edges)[ptr++] = IGRAPH_TO(graph, e); VECTOR(*edges)[ptr++] = IGRAPH_FROM(graph, e); } } igraph_eit_destroy(&eit); IGRAPH_FINALLY_CLEAN(1); return 0; } /* This is an unsafe macro. Only supply variable names, i.e. no expressions as parameters, otherwise nasty things can happen */ #define BINSEARCH(start,end,value,iindex,edgelist,N,pos) \ do { \ while ((start) < (end)) { \ long int mid=(start)+((end)-(start))/2; \ long int e=(long int) VECTOR((iindex))[mid]; \ if (VECTOR((edgelist))[e] < (value)) { \ (start)=mid+1; \ } else { \ (end)=mid; \ } \ } \ if ((start)<(N)) { \ long int e=(long int) VECTOR((iindex))[(start)]; \ if (VECTOR((edgelist))[e] == (value)) { \ *(pos)=(igraph_integer_t) e; \ } \ } } while(0) #define FIND_DIRECTED_EDGE(graph,xfrom,xto,eid) \ do { \ long int start=(long int) VECTOR(graph->os)[xfrom]; \ long int end=(long int) VECTOR(graph->os)[xfrom+1]; \ long int N=end; \ long int start2=(long int) VECTOR(graph->is)[xto]; \ long int end2=(long int) VECTOR(graph->is)[xto+1]; \ long int N2=end2; \ if (end-startoi,graph->to,N,eid); \ } else { \ BINSEARCH(start2,end2,xfrom,graph->ii,graph->from,N2,eid); \ } \ } while (0) #define FIND_UNDIRECTED_EDGE(graph,from,to,eid) \ do { \ long int xfrom1= from > to ? from : to; \ long int xto1= from > to ? to : from; \ FIND_DIRECTED_EDGE(graph,xfrom1,xto1,eid); \ } while (0) /** * \function igraph_get_eid * \brief Get the edge id from the end points of an edge. * * For undirected graphs \c pfrom and \c pto are exchangeable. * * \param graph The graph object. * \param eid Pointer to an integer, the edge id will be stored here. * \param pfrom The starting point of the edge. * \param pto The end point of the edge. * \param directed Logical constant, whether to search for directed * edges in a directed graph. Ignored for undirected graphs. * \param error Logical scalar, whether to report an error if the edge * was not found. If it is false, then -1 will be assigned to \p eid. * \return Error code. * \sa \ref igraph_edge() for the opposite operation. * * Time complexity: O(log (d)), where d is smaller of the out-degree * of \c pfrom and in-degree of \c pto if \p directed is true. If \p directed * is false, then it is O(log(d)+log(d2)), where d is the same as before and * d2 is the minimum of the out-degree of \c pto and the in-degree of \c pfrom. * * \example examples/simple/igraph_get_eid.c * * Added in version 0.2. */ int igraph_get_eid(const igraph_t *graph, igraph_integer_t *eid, igraph_integer_t pfrom, igraph_integer_t pto, igraph_bool_t directed, igraph_bool_t error) { long int from = pfrom, to = pto; long int nov = igraph_vcount(graph); if (from < 0 || to < 0 || from > nov - 1 || to > nov - 1) { IGRAPH_ERROR("cannot get edge id", IGRAPH_EINVVID); } *eid = -1; if (igraph_is_directed(graph)) { /* Directed graph */ FIND_DIRECTED_EDGE(graph, from, to, eid); if (!directed && *eid < 0) { FIND_DIRECTED_EDGE(graph, to, from, eid); } } else { /* Undirected graph, they only have one mode */ FIND_UNDIRECTED_EDGE(graph, from, to, eid); } if (*eid < 0) { if (error) { IGRAPH_ERROR("Cannot get edge id, no such edge", IGRAPH_EINVAL); } } return IGRAPH_SUCCESS; } int igraph_get_eids_pairs(const igraph_t *graph, igraph_vector_t *eids, const igraph_vector_t *pairs, igraph_bool_t directed, igraph_bool_t error); int igraph_get_eids_path(const igraph_t *graph, igraph_vector_t *eids, const igraph_vector_t *path, igraph_bool_t directed, igraph_bool_t error); int igraph_get_eids_pairs(const igraph_t *graph, igraph_vector_t *eids, const igraph_vector_t *pairs, igraph_bool_t directed, igraph_bool_t error) { long int n = igraph_vector_size(pairs); long int no_of_nodes = igraph_vcount(graph); long int i; igraph_integer_t eid = -1; if (n % 2 != 0) { IGRAPH_ERROR("Cannot get edge ids, invalid length of edge ids", IGRAPH_EINVAL); } if (!igraph_vector_isininterval(pairs, 0, no_of_nodes - 1)) { IGRAPH_ERROR("Cannot get edge ids, invalid vertex id", IGRAPH_EINVVID); } IGRAPH_CHECK(igraph_vector_resize(eids, n / 2)); if (igraph_is_directed(graph)) { for (i = 0; i < n / 2; i++) { long int from = (long int) VECTOR(*pairs)[2 * i]; long int to = (long int) VECTOR(*pairs)[2 * i + 1]; eid = -1; FIND_DIRECTED_EDGE(graph, from, to, &eid); if (!directed && eid < 0) { FIND_DIRECTED_EDGE(graph, to, from, &eid); } VECTOR(*eids)[i] = eid; if (eid < 0 && error) { IGRAPH_ERROR("Cannot get edge id, no such edge", IGRAPH_EINVAL); } } } else { for (i = 0; i < n / 2; i++) { long int from = (long int) VECTOR(*pairs)[2 * i]; long int to = (long int) VECTOR(*pairs)[2 * i + 1]; eid = -1; FIND_UNDIRECTED_EDGE(graph, from, to, &eid); VECTOR(*eids)[i] = eid; if (eid < 0 && error) { IGRAPH_ERROR("Cannot get edge id, no such edge", IGRAPH_EINVAL); } } } return 0; } int igraph_get_eids_path(const igraph_t *graph, igraph_vector_t *eids, const igraph_vector_t *path, igraph_bool_t directed, igraph_bool_t error) { long int n = igraph_vector_size(path); long int no_of_nodes = igraph_vcount(graph); long int i; igraph_integer_t eid = -1; if (!igraph_vector_isininterval(path, 0, no_of_nodes - 1)) { IGRAPH_ERROR("Cannot get edge ids, invalid vertex id", IGRAPH_EINVVID); } IGRAPH_CHECK(igraph_vector_resize(eids, n == 0 ? 0 : n - 1)); if (igraph_is_directed(graph)) { for (i = 0; i < n - 1; i++) { long int from = (long int) VECTOR(*path)[i]; long int to = (long int) VECTOR(*path)[i + 1]; eid = -1; FIND_DIRECTED_EDGE(graph, from, to, &eid); if (!directed && eid < 0) { FIND_DIRECTED_EDGE(graph, to, from, &eid); } VECTOR(*eids)[i] = eid; if (eid < 0 && error) { IGRAPH_ERROR("Cannot get edge id, no such edge", IGRAPH_EINVAL); } } } else { for (i = 0; i < n - 1; i++) { long int from = (long int) VECTOR(*path)[i]; long int to = (long int) VECTOR(*path)[i + 1]; eid = -1; FIND_UNDIRECTED_EDGE(graph, from, to, &eid); VECTOR(*eids)[i] = eid; if (eid < 0 && error) { IGRAPH_ERROR("Cannot get edge id, no such edge", IGRAPH_EINVAL); } } } return 0; } /** * \function igraph_get_eids * Return edge ids based on the adjacent vertices. * * This function operates in two modes. If the \c pairs argument is * not a null pointer, but the \c path argument is, then it searches * for the edge ids of all pairs of vertices given in \c pairs. The * pairs of vertex ids are taken consecutively from the vector, * i.e. VECTOR(pairs)[0] and * VECTOR(pairs)[1] give the first * pair, VECTOR(pairs)[2] and * VECTOR(pairs)[3] the second pair, etc. * * * If the \c pairs argument is a null pointer, and \c path is not a * null pointer, then the \c path is interpreted as a path given by * vertex ids and the edges along the path are returned. * * * If neither \c pairs nor \c path are null pointers, then both are * considered (first \c pairs and then \c path), and the results are * concatenated. * * * If the \c error argument is true, then it is an error to give pairs * of vertices that are not connected. Otherwise -1 is * reported for not connected vertices. * * * If there are multiple edges in the graph, then these are ignored; * i.e. for a given pair of vertex ids, always the same edge id is * returned, even if the pair is given multiple time in \c pairs or in * \c path. See \ref igraph_get_eids_multi() for a similar function * that works differently in case of multiple edges. * * \param graph The input graph. * \param eids Pointer to an initialized vector, the result is stored * here. It will be resized as needed. * \param pairs Vector giving pairs of vertices, or a null pointer. * \param path Vector giving vertex ids along a path, or a null * pointer. * \param directed Logical scalar, whether to consider edge directions * in directed graphs. This is ignored for undirected graphs. * \param error Logical scalar, whether it is an error to supply * non-connected vertices. If false, then -1 is * returned for non-connected pairs. * \return Error code. * * Time complexity: O(n log(d)), where n is the number of queried * edges and d is the average degree of the vertices. * * \sa \ref igraph_get_eid() for a single edge, \ref * igraph_get_eids_multi() for a version that handles multiple edges * better (at a cost). * * \example examples/simple/igraph_get_eids.c */ int igraph_get_eids(const igraph_t *graph, igraph_vector_t *eids, const igraph_vector_t *pairs, const igraph_vector_t *path, igraph_bool_t directed, igraph_bool_t error) { if (!pairs && !path) { igraph_vector_clear(eids); return 0; } else if (pairs && !path) { return igraph_get_eids_pairs(graph, eids, pairs, directed, error); } else if (!pairs && path) { return igraph_get_eids_path(graph, eids, path, directed, error); } else { /* both */ igraph_vector_t tmp; IGRAPH_VECTOR_INIT_FINALLY(&tmp, 0); IGRAPH_CHECK(igraph_get_eids_pairs(graph, eids, pairs, directed, error)); IGRAPH_CHECK(igraph_get_eids_path(graph, &tmp, path, directed, error)); IGRAPH_CHECK(igraph_vector_append(eids, &tmp)); igraph_vector_destroy(&tmp); IGRAPH_FINALLY_CLEAN(1); return 0; } } #undef BINSEARCH #undef FIND_DIRECTED_EDGE #undef FIND_UNDIRECTED_EDGE #define BINSEARCH(start,end,value,iindex,edgelist,N,pos,seen) \ do { \ while ((start) < (end)) { \ long int mid=(start)+((end)-(start))/2; \ long int e=(long int) VECTOR((iindex))[mid]; \ if (VECTOR((edgelist))[e] < (value)) { \ (start)=mid+1; \ } else { \ (end)=mid; \ } \ } \ if ((start)<(N)) { \ long int e=(long int) VECTOR((iindex))[(start)]; \ while ((start)<(N) && seen[e] && VECTOR(edgelist)[e] == (value)) { \ (start)++; \ e=(long int) VECTOR(iindex)[(start)]; \ } \ if ((start)<(N) && !(seen[e]) && VECTOR(edgelist)[e] == (value)) { \ *(pos)=(igraph_integer_t) e; \ } \ } } while(0) #define FIND_DIRECTED_EDGE(graph,xfrom,xto,eid,seen) \ do { \ long int start=(long int) VECTOR(graph->os)[xfrom]; \ long int end=(long int) VECTOR(graph->os)[xfrom+1]; \ long int N=end; \ long int start2=(long int) VECTOR(graph->is)[xto]; \ long int end2=(long int) VECTOR(graph->is)[xto+1]; \ long int N2=end2; \ if (end-startoi,graph->to,N,eid,seen); \ } else { \ BINSEARCH(start2,end2,xfrom,graph->ii,graph->from,N2,eid,seen); \ } \ } while (0) #define FIND_UNDIRECTED_EDGE(graph,from,to,eid,seen) \ do { \ long int xfrom1= from > to ? from : to; \ long int xto1= from > to ? to : from; \ FIND_DIRECTED_EDGE(graph,xfrom1,xto1,eid,seen); \ } while (0) int igraph_get_eids_multipairs(const igraph_t *graph, igraph_vector_t *eids, const igraph_vector_t *pairs, igraph_bool_t directed, igraph_bool_t error); int igraph_get_eids_multipath(const igraph_t *graph, igraph_vector_t *eids, const igraph_vector_t *path, igraph_bool_t directed, igraph_bool_t error); int igraph_get_eids_multipairs(const igraph_t *graph, igraph_vector_t *eids, const igraph_vector_t *pairs, igraph_bool_t directed, igraph_bool_t error) { long int n = igraph_vector_size(pairs); long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_bool_t *seen; long int i; igraph_integer_t eid = -1; if (n % 2 != 0) { IGRAPH_ERROR("Cannot get edge ids, invalid length of edge ids", IGRAPH_EINVAL); } if (!igraph_vector_isininterval(pairs, 0, no_of_nodes - 1)) { IGRAPH_ERROR("Cannot get edge ids, invalid vertex id", IGRAPH_EINVVID); } seen = igraph_Calloc(no_of_edges, igraph_bool_t); if (seen == 0) { IGRAPH_ERROR("Cannot get edge ids", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, seen); IGRAPH_CHECK(igraph_vector_resize(eids, n / 2)); if (igraph_is_directed(graph)) { for (i = 0; i < n / 2; i++) { long int from = (long int) VECTOR(*pairs)[2 * i]; long int to = (long int) VECTOR(*pairs)[2 * i + 1]; eid = -1; FIND_DIRECTED_EDGE(graph, from, to, &eid, seen); if (!directed && eid < 0) { FIND_DIRECTED_EDGE(graph, to, from, &eid, seen); } VECTOR(*eids)[i] = eid; if (eid >= 0) { seen[(long int)(eid)] = 1; } else if (error) { IGRAPH_ERROR("Cannot get edge id, no such edge", IGRAPH_EINVAL); } } } else { for (i = 0; i < n / 2; i++) { long int from = (long int) VECTOR(*pairs)[2 * i]; long int to = (long int) VECTOR(*pairs)[2 * i + 1]; eid = -1; FIND_UNDIRECTED_EDGE(graph, from, to, &eid, seen); VECTOR(*eids)[i] = eid; if (eid >= 0) { seen[(long int)(eid)] = 1; } else if (error) { IGRAPH_ERROR("Cannot get edge id, no such edge", IGRAPH_EINVAL); } } } igraph_Free(seen); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_get_eids_multipath(const igraph_t *graph, igraph_vector_t *eids, const igraph_vector_t *path, igraph_bool_t directed, igraph_bool_t error) { long int n = igraph_vector_size(path); long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_bool_t *seen; long int i; igraph_integer_t eid = -1; if (!igraph_vector_isininterval(path, 0, no_of_nodes - 1)) { IGRAPH_ERROR("Cannot get edge ids, invalid vertex id", IGRAPH_EINVVID); } seen = igraph_Calloc(no_of_edges, igraph_bool_t); if (!seen) { IGRAPH_ERROR("Cannot get edge ids", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, seen); IGRAPH_CHECK(igraph_vector_resize(eids, n == 0 ? 0 : n - 1)); if (igraph_is_directed(graph)) { for (i = 0; i < n - 1; i++) { long int from = (long int) VECTOR(*path)[i]; long int to = (long int) VECTOR(*path)[i + 1]; eid = -1; FIND_DIRECTED_EDGE(graph, from, to, &eid, seen); if (!directed && eid < 0) { FIND_DIRECTED_EDGE(graph, to, from, &eid, seen); } VECTOR(*eids)[i] = eid; if (eid >= 0) { seen[(long int)(eid)] = 1; } else if (error) { IGRAPH_ERROR("Cannot get edge id, no such edge", IGRAPH_EINVAL); } } } else { for (i = 0; i < n - 1; i++) { long int from = (long int) VECTOR(*path)[i]; long int to = (long int) VECTOR(*path)[i + 1]; eid = -1; FIND_UNDIRECTED_EDGE(graph, from, to, &eid, seen); VECTOR(*eids)[i] = eid; if (eid >= 0) { seen[(long int)(eid)] = 1; } else if (error) { IGRAPH_ERROR("Cannot get edge id, no such edge", IGRAPH_EINVAL); } } } igraph_Free(seen); IGRAPH_FINALLY_CLEAN(1); return 0; } #undef BINSEARCH #undef FIND_DIRECTED_EDGE #undef FIND_UNDIRECTED_EDGE /** * \function igraph_get_eids_multi * \brief Query edge ids based on their adjacent vertices, handle multiple edges. * * This function operates in two modes. If the \c pairs argument is * not a null pointer, but the \c path argument is, then it searches * for the edge ids of all pairs of vertices given in \c pairs. The * pairs of vertex ids are taken consecutively from the vector, * i.e. VECTOR(pairs)[0] and * VECTOR(pairs)[1] give the first pair, * VECTOR(pairs)[2] and VECTOR(pairs)[3] the * second pair, etc. * * * If the \c pairs argument is a null pointer, and \c path is not a * null pointer, then the \c path is interpreted as a path given by * vertex ids and the edges along the path are returned. * * * If the \c error argument is true, then it is an error to give pairs of * vertices that are not connected. Otherwise -1 is * returned for not connected vertex pairs. * * * An error is triggered if both \c pairs and \c path are non-null * pointers. * * * This function handles multiple edges properly, i.e. if the same * pair is given multiple times and they are indeed connected by * multiple edges, then each time a different edge id is reported. * * \param graph The input graph. * \param eids Pointer to an initialized vector, the result is stored * here. It will be resized as needed. * \param pairs Vector giving pairs of vertices, or a null pointer. * \param path Vector giving vertex ids along a path, or a null * pointer. * \param directed Logical scalar, whether to consider edge directions * in directed graphs. This is ignored for undirected graphs. * \param error Logical scalar, whether to report an error if * non-connected vertices are specified. If false, then -1 * is returned for non-connected vertex pairs. * \return Error code. * * Time complexity: O(|E|+n log(d)), where |E| is the number of edges * in the graph, n is the number of queried edges and d is the average * degree of the vertices. * * \sa \ref igraph_get_eid() for a single edge, \ref * igraph_get_eids() for a faster version that does not handle * multiple edges. */ int igraph_get_eids_multi(const igraph_t *graph, igraph_vector_t *eids, const igraph_vector_t *pairs, const igraph_vector_t *path, igraph_bool_t directed, igraph_bool_t error) { if (!pairs && !path) { igraph_vector_clear(eids); return 0; } else if (pairs && !path) { return igraph_get_eids_multipairs(graph, eids, pairs, directed, error); } else if (!pairs && path) { return igraph_get_eids_multipath(graph, eids, path, directed, error); } else { /* both */ IGRAPH_ERROR("Give `pairs' or `path' but not both", IGRAPH_EINVAL); } } /** * \function igraph_adjacent * \brief Gives the incident edges of a vertex. * * This function was superseded by \ref igraph_incident() in igraph 0.6. * Please use \ref igraph_incident() instead of this function. * * * Added in version 0.2, deprecated in version 0.6. */ int igraph_adjacent(const igraph_t *graph, igraph_vector_t *eids, igraph_integer_t pnode, igraph_neimode_t mode) { IGRAPH_WARNING("igraph_adjacent is deprecated, use igraph_incident"); return igraph_incident(graph, eids, pnode, mode); } /** * \function igraph_incident * \brief Gives the incident edges of a vertex. * * \param graph The graph object. * \param eids An initialized \type vector_t object. It will be resized * to hold the result. * \param pnode A vertex id. * \param mode Specifies what kind of edges to include for directed * graphs. \c IGRAPH_OUT means only outgoing edges, \c IGRAPH_IN only * incoming edges, \c IGRAPH_ALL both. This parameter is ignored for * undirected graphs. * \return Error code. \c IGRAPH_EINVVID: invalid \p pnode argument, * \c IGRAPH_EINVMODE: invalid \p mode argument. * * Added in version 0.2. * * Time complexity: O(d), the number of incident edges to \p pnode. */ int igraph_incident(const igraph_t *graph, igraph_vector_t *eids, igraph_integer_t pnode, igraph_neimode_t mode) { long int length = 0, idx = 0; long int i, j; long int node = pnode; if (node < 0 || node > igraph_vcount(graph) - 1) { IGRAPH_ERROR("cannot get neighbors", IGRAPH_EINVVID); } if (mode != IGRAPH_OUT && mode != IGRAPH_IN && mode != IGRAPH_ALL) { IGRAPH_ERROR("cannot get neighbors", IGRAPH_EINVMODE); } if (! graph->directed) { mode = IGRAPH_ALL; } /* Calculate needed space first & allocate it*/ if (mode & IGRAPH_OUT) { length += (VECTOR(graph->os)[node + 1] - VECTOR(graph->os)[node]); } if (mode & IGRAPH_IN) { length += (VECTOR(graph->is)[node + 1] - VECTOR(graph->is)[node]); } IGRAPH_CHECK(igraph_vector_resize(eids, length)); if (mode & IGRAPH_OUT) { j = (long int) VECTOR(graph->os)[node + 1]; for (i = (long int) VECTOR(graph->os)[node]; i < j; i++) { VECTOR(*eids)[idx++] = VECTOR(graph->oi)[i]; } } if (mode & IGRAPH_IN) { j = (long int) VECTOR(graph->is)[node + 1]; for (i = (long int) VECTOR(graph->is)[node]; i < j; i++) { VECTOR(*eids)[idx++] = VECTOR(graph->ii)[i]; } } return 0; } python-igraph-0.8.0/vendor/source/igraph/src/hrg_graph.h0000644000076500000240000001377113614300625023521 0ustar tamasstaff00000000000000/* -*- mode: C++ -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ // **************************************************************************************************** // *** COPYRIGHT NOTICE ******************************************************************************* // graph.h - graph data structure for hierarchical random graphs // Copyright (C) 2005-2008 Aaron Clauset // // This program is free software; you can redistribute it and/or modify // it under the terms of the GNU General Public License as published by // the Free Software Foundation; either version 2 of the License, or // (at your option) any later version. // // This program is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU General Public License for more details. // // You should have received a copy of the GNU General Public License // along with this program; if not, write to the Free Software // Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA // // See http://www.gnu.org/licenses/gpl.txt for more details. // // **************************************************************************************************** // Author : Aaron Clauset ( aaronc@santafe.edu | http://www.santafe.edu/~aaronc/ ) // Collaborators: Cristopher Moore and Mark E.J. Newman // Project : Hierarchical Random Graphs // Location : University of New Mexico, Dept. of Computer Science AND Santa Fe Institute // Created : 8 November 2005 // Modified : 23 December 2007 (cleaned up for public consumption) // // **************************************************************************************************** // // Graph data structure for hierarchical random graphs. The basic structure is an adjacency list of // edges; however, many additional pieces of metadata are stored as well. Each node stores its // external name, its degree and (if assigned) its group index. // // **************************************************************************************************** #ifndef IGRAPH_HRG_GRAPH #define IGRAPH_HRG_GRAPH #include #include #include #include "hrg_rbtree.h" using namespace std; namespace fitHRG { // ******** Basic Structures ********************************************* #ifndef IGRAPH_HRG_EDGE #define IGRAPH_HRG_EDGE class edge { public: int x; // stored integer value (edge terminator) double* h; // (histogram) weights of edge existence double total_weight; // (histogram) total weight observed int obs_count; // number of observations in histogram edge* next; // pointer to next elementd edge(): x(-1), h(0), total_weight(0.0), obs_count(0), next(0) { } ~edge() { if (h != NULL) { delete [] h; } h = NULL; } }; #endif #ifndef IGRAPH_HRG_VERT #define IGRAPH_HRG_VERT class vert { public: string name; // (external) name of vertex int degree; // degree of this vertex vert(): name(""), degree(0) { } ~vert() { } }; #endif // ******** Graph Class with Edge Statistics ***************************** class graph { public: graph(const int, bool predict = false); ~graph(); // add (i,j) to graph bool addLink(const int, const int); // add weight to (i,j)'s histogram bool addAdjacencyObs(const int, const int, const double, const double); // add to obs_count and total_weight void addAdjacencyEnd(); // true if (i,j) is already in graph bool doesLinkExist(const int, const int); // returns degree of vertex i int getDegree(const int); // returns name of vertex i string getName(const int); // returns edge list of vertex i edge* getNeighborList(const int); // return ptr to histogram of edge (i,j) double* getAdjacencyHist(const int, const int); // return average value of adjacency A(i,j) double getAdjacencyAverage(const int, const int); // returns bin_resolution double getBinResolution(); // returns num_bins int getNumBins(); // returns m int numLinks(); // returns n int numNodes(); // returns total_weight double getTotalWeight(); // reset edge (i,j)'s histogram void resetAdjacencyHistogram(const int, const int); // reset all edge histograms void resetAllAdjacencies(); // clear all links from graph void resetLinks(); // allocate edge histograms void setAdjacencyHistograms(const int); // set name of vertex i bool setName(const int, const string); private: bool predict; // do we need prediction? vert* nodes; // list of nodes edge** nodeLink; // linked list of neighbors to vertex edge** nodeLinkTail; // pointers to tail of neighbor list double*** A; // stochastic adjacency matrix for this graph int obs_count; // number of observations in A double total_weight; // total weight added to A int n; // number of vertices int m; // number of directed edges int num_bins; // number of bins in edge histograms double bin_resolution; // width of histogram bin }; } // namespace fitHRG #endif python-igraph-0.8.0/vendor/source/igraph/src/igraph_glpk_support.h0000644000076500000240000000271313614300625025635 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_GLPK_SUPPORT_H #define IGRAPH_GLPK_SUPPORT_H #include "config.h" /* Note: only files calling the GLPK routines directly need to include this header. */ #ifdef HAVE_GLPK #include int igraph_i_glpk_check(int retval, const char* message); void igraph_i_glpk_interruption_hook(glp_tree *tree, void *info); #define IGRAPH_GLPK_CHECK(func, message) do {\ int igraph_i_ret = igraph_i_glpk_check(func, message); \ if (IGRAPH_UNLIKELY(igraph_i_ret != 0)) {\ return igraph_i_ret; \ } } while (0) #endif #endif python-igraph-0.8.0/vendor/source/igraph/src/bigint.c0000644000076500000240000002265313614300625023026 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "bigint.h" #include "igraph_error.h" #include "igraph_memory.h" int igraph_biguint_init(igraph_biguint_t *b) { IGRAPH_CHECK(igraph_vector_limb_init(&b->v, IGRAPH_BIGUINT_DEFAULT_SIZE)); igraph_vector_limb_clear(&b->v); return 0; } void igraph_biguint_destroy(igraph_biguint_t *b) { igraph_vector_limb_destroy(&b->v); } int igraph_biguint_copy(igraph_biguint_t *to, igraph_biguint_t *from) { return igraph_vector_limb_copy(&to->v, &from->v); } int igraph_biguint_extend(igraph_biguint_t *b, limb_t l) { return igraph_vector_limb_push_back(&b->v, l); } int igraph_biguint_size(igraph_biguint_t *b) { return (int) igraph_vector_limb_size(&b->v); } int igraph_biguint_resize(igraph_biguint_t *b, int newlength) { int origlen = igraph_biguint_size(b); IGRAPH_CHECK(igraph_vector_limb_resize(&b->v, newlength)); if (newlength > origlen) { memset(VECTOR(b->v) + origlen, 0, (size_t) (newlength - origlen) * sizeof(limb_t)); } return 0; } int igraph_biguint_reserve(igraph_biguint_t *b, int length) { return igraph_vector_limb_reserve(&b->v, length); } int igraph_biguint_zero(igraph_biguint_t *b) { igraph_vector_limb_clear(&b->v); return 0; } int igraph_biguint_set_limb(igraph_biguint_t *b, int value) { IGRAPH_CHECK(igraph_vector_limb_resize(&b->v, 1)); VECTOR(b->v)[0] = (limb_t) value; return 0; } igraph_real_t igraph_biguint_get(igraph_biguint_t *b) { int size = igraph_biguint_size(b); int i; double val = VECTOR(b->v)[size - 1]; if (size == 0) { return 0.0; } for (i = size - 2; i >= 0; i--) { val = val * LIMBMASK + VECTOR(b->v)[i]; if (!IGRAPH_FINITE(val)) { break; } } return val; } int igraph_biguint_compare_limb(igraph_biguint_t *b, limb_t l) { int n = igraph_biguint_size(b); return bn_cmp_limb(VECTOR(b->v), l, (count_t) n); } int igraph_biguint_compare(igraph_biguint_t *left, igraph_biguint_t *right) { /* bn_cmp requires the two numbers to have the same number of limbs, so we do this partially by hand here */ int size_left = igraph_biguint_size(left); int size_right = igraph_biguint_size(right); while (size_left > size_right) { if (VECTOR(left->v)[--size_left] > 0) { return +1; } } while (size_right > size_left) { if (VECTOR(right->v)[--size_right] > 0) { return -1; } } return bn_cmp( VECTOR(left->v), VECTOR(right->v), (count_t) size_right ); } igraph_bool_t igraph_biguint_equal(igraph_biguint_t *left, igraph_biguint_t *right) { return 0 == igraph_biguint_compare(left, right); } igraph_bool_t igraph_biguint_bigger(igraph_biguint_t *left, igraph_biguint_t *right) { return 0 < igraph_biguint_compare(left, right); } igraph_bool_t igraph_biguint_biggerorequal(igraph_biguint_t *left, igraph_biguint_t *right) { return 0 <= igraph_biguint_compare(left, right); } int igraph_biguint_inc(igraph_biguint_t *res, igraph_biguint_t *b) { return igraph_biguint_add_limb(res, b, 1); } int igraph_biguint_dec(igraph_biguint_t *res, igraph_biguint_t *b) { return igraph_biguint_sub_limb(res, b, 1); } int igraph_biguint_add_limb(igraph_biguint_t *res, igraph_biguint_t *b, limb_t l) { int nlimb = igraph_biguint_size(b); limb_t carry; if (res != b) { IGRAPH_CHECK(igraph_biguint_resize(res, nlimb)); } carry = bn_add_limb( VECTOR(res->v), VECTOR(b->v), l, (count_t) nlimb); if (carry) { IGRAPH_CHECK(igraph_biguint_extend(res, carry)); } return 0; } int igraph_biguint_sub_limb(igraph_biguint_t *res, igraph_biguint_t *b, limb_t l) { int nlimb = igraph_biguint_size(b); if (res != b) { IGRAPH_CHECK(igraph_biguint_resize(res, nlimb)); } /* We don't check the return value here */ bn_sub_limb( VECTOR(res->v), VECTOR(b->v), l, (count_t) nlimb); return 0; } int igraph_biguint_mul_limb(igraph_biguint_t *res, igraph_biguint_t *b, limb_t l) { int nlimb = igraph_biguint_size(b); limb_t carry; if (res != b) { IGRAPH_CHECK(igraph_biguint_resize(res, nlimb)); } carry = bn_mul_limb( VECTOR(res->v), VECTOR(b->v), l, (count_t) nlimb); if (carry) { IGRAPH_CHECK(igraph_biguint_extend(res, carry)); } return 0; } int igraph_biguint_add(igraph_biguint_t *res, igraph_biguint_t *left, igraph_biguint_t *right) { int size_left = igraph_biguint_size(left); int size_right = igraph_biguint_size(right); limb_t carry; if (size_left > size_right) { IGRAPH_CHECK(igraph_biguint_resize(right, size_left)); size_right = size_left; } else if (size_left < size_right) { IGRAPH_CHECK(igraph_biguint_resize(left, size_right)); size_left = size_right; } IGRAPH_CHECK(igraph_biguint_resize(res, size_left)); carry = bn_add( VECTOR(res->v), VECTOR(left->v), VECTOR(right->v), (count_t) size_left); if (carry) { IGRAPH_CHECK(igraph_biguint_extend(res, carry)); } return 0; } int igraph_biguint_sub(igraph_biguint_t *res, igraph_biguint_t *left, igraph_biguint_t *right) { int size_left = igraph_biguint_size(left); int size_right = igraph_biguint_size(right); if (size_left > size_right) { IGRAPH_CHECK(igraph_biguint_resize(right, size_left)); size_right = size_left; } else if (size_left < size_right) { IGRAPH_CHECK(igraph_biguint_resize(left, size_right)); size_left = size_right; } IGRAPH_CHECK(igraph_biguint_resize(res, size_left)); /* We don't check return value, left should not be smaller than right! */ bn_sub( VECTOR(res->v), VECTOR(left->v), VECTOR(right->v), (count_t) size_left); return 0; } int igraph_biguint_mul(igraph_biguint_t *res, igraph_biguint_t *left, igraph_biguint_t *right) { int size_left = igraph_biguint_size(left); int size_right = igraph_biguint_size(right); if (size_left > size_right) { IGRAPH_CHECK(igraph_biguint_resize(right, size_left)); size_right = size_left; } else if (size_left < size_right) { IGRAPH_CHECK(igraph_biguint_resize(left, size_right)); size_left = size_right; } IGRAPH_CHECK(igraph_biguint_resize(res, 2 * size_left)); bn_mul( VECTOR(res->v), VECTOR(left->v), VECTOR(right->v), (count_t) size_left ); return 0; } int igraph_biguint_div(igraph_biguint_t *q, igraph_biguint_t *r, igraph_biguint_t *u, igraph_biguint_t *v) { int ret; int size_q = igraph_biguint_size(q); int size_r = igraph_biguint_size(r); int size_u = igraph_biguint_size(u); int size_v = igraph_biguint_size(v); int size_qru = size_q > size_r ? size_q : size_r; size_qru = size_u > size_qru ? size_u : size_qru; if (size_q < size_qru) { IGRAPH_CHECK(igraph_biguint_resize(q, size_qru)); } if (size_r < size_qru) { IGRAPH_CHECK(igraph_biguint_resize(r, size_qru)); } if (size_u < size_qru) { IGRAPH_CHECK(igraph_biguint_resize(u, size_qru)); } ret = bn_div( VECTOR(q->v), VECTOR(r->v), VECTOR(u->v), VECTOR(v->v), (count_t) size_qru, (count_t) size_v ); if (ret) { IGRAPH_ERROR("Bigint division by zero", IGRAPH_EDIVZERO); } return 0; } #ifndef USING_R int igraph_biguint_print(igraph_biguint_t *b) { return igraph_biguint_fprint(b, stdout); } #endif int igraph_biguint_fprint(igraph_biguint_t *b, FILE *file) { /* It is hard to control memory allocation for the bn2d function, so we do our own version */ int n = igraph_biguint_size(b); long int size = 12 * n + 1; igraph_biguint_t tmp; char *dst; limb_t r; /* Zero? */ if (!bn_cmp_limb(VECTOR(b->v), 0, (count_t) n)) { fputs("0", file); return 0; } IGRAPH_CHECK(igraph_biguint_copy(&tmp, b)); IGRAPH_FINALLY(igraph_biguint_destroy, &tmp); dst = igraph_Calloc(size, char); if (!dst) { IGRAPH_ERROR("Cannot print big number", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, dst); size--; dst[size] = '\0'; while (0 != bn_cmp_limb(VECTOR(tmp.v), 0, (count_t) n)) { r = bn_div_limb(VECTOR(tmp.v), VECTOR(tmp.v), 10, (count_t) n); dst[--size] = '0' + (char) r; } fputs(&dst[size], file); igraph_Free(dst); igraph_biguint_destroy(&tmp); IGRAPH_FINALLY_CLEAN(2); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/array.pmt0000644000076500000240000000526713614300625023250 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_types.h" int FUNCTION(igraph_array3, init)(TYPE(igraph_array3) *a, long int n1, long int n2, long int n3) { int ret; ret = FUNCTION(igraph_vector, init)(&a->data, n1 * n2 * n3); a->n1 = n1; a->n2 = n2; a->n3 = n3; a->n1n2 = n1 * n2; return ret; } void FUNCTION(igraph_array3, destroy)(TYPE(igraph_array3) *a) { FUNCTION(igraph_vector, destroy)(&a->data); } long int FUNCTION(igraph_array3, size)(const TYPE(igraph_array3) *a) { return (a->n1n2) * (a->n3); } long int FUNCTION(igraph_array3, n)(const TYPE(igraph_array3) *a, long int idx) { switch (idx) { case 1: return a->n1; break; case 2: return a->n2; break; case 3: return a->n3; break; } return 0; } int FUNCTION(igraph_array3, resize)(TYPE(igraph_array3) *a, long int n1, long int n2, long int n3) { int ret = FUNCTION(igraph_vector, resize)(&a->data, n1 * n2 * n3); a->n1 = n1; a->n2 = n2; a->n3 = n3; a->n1n2 = n1 * n2; return ret; } void FUNCTION(igraph_array3, null)(TYPE(igraph_array3) *a) { FUNCTION(igraph_vector, null)(&a->data); } BASE FUNCTION(igraph_array3, sum)(const TYPE(igraph_array3) *a) { return FUNCTION(igraph_vector, sum)(&a->data); } void FUNCTION(igraph_array3, scale)(TYPE(igraph_array3) *a, BASE by) { FUNCTION(igraph_vector, scale)(&a->data, by); } void FUNCTION(igraph_array3, fill)(TYPE(igraph_array3) *a, BASE e) { FUNCTION(igraph_vector, fill)(&a->data, e); } int FUNCTION(igraph_array3, update)(TYPE(igraph_array3) *to, const TYPE(igraph_array3) *from) { IGRAPH_CHECK(FUNCTION(igraph_array3, resize)(to, from->n1, from->n2, from->n3)); FUNCTION(igraph_vector, update)(&to->data, &from->data); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/gengraph_graph_molloy_optimized.h0000644000076500000240000002723213614300625030210 0ustar tamasstaff00000000000000/* * * gengraph - generation of random simple connected graphs with prescribed * degree sequence * * Copyright (C) 2006 Fabien Viger * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #ifndef GRAPH_MOLLOY_OPT_H #define GRAPH_MOLLOY_OPT_H #include "gengraph_definitions.h" #include "gengraph_degree_sequence.h" #include "gengraph_qsort.h" #include #include "gengraph_random.h" namespace gengraph { // This class handles graphs with a constant degree sequence. class graph_molloy_opt { private: // Random generator KW_RNG::RNG rng; // Number of vertices int n; //Number of arcs ( = #edges * 2 ) int a; // The degree sequence of the graph int *deg; // The array containing all links int *links; // The array containing pointers to adjacency list of every vertices int **neigh; // Allocate memory according to degree_sequence (for constructor use only!!) void alloc(degree_sequence &); // Compute #edges inline void refresh_nbarcs() { a = 0; for (int* d = deg + n; d != deg; ) { a += *(--d); } } // Build neigh with deg and links void compute_neigh(); // Swap edges. The swap MUST be valid !!! inline void swap_edges(int from1, int to1, int from2, int to2) { fast_rpl(neigh[from1], to1, to2); fast_rpl(neigh[from2], to2, to1); fast_rpl(neigh[to1], from1, from2); fast_rpl(neigh[to2], from2, from1); } // Swap edges only if they are simple. return false if unsuccessful. bool swap_edges_simple(int, int, int, int); // Test if vertex is in an isolated component of size dmax. void depth_isolated(int v, long &calls, int &left_to_explore, int dmax, int * &Kbuff, bool *visited); // breadth-first search. Store the distance (modulo 3) in dist[]. Returns eplorated component size. int width_search(unsigned char *dist, int *buff, int v0 = 0, int toclear = -1); // depth-first search. int depth_search(bool *visited, int *buff, int v0 = 0); // breadth-first search that count the number of shortest paths going from src to each vertex int breadth_path_search(int src, int *buff, double *paths, unsigned char *dist); // Used by traceroute_sample() ONLY void add_traceroute_edge(int, int, int*, double** red = NULL, double t = 1.0); // Used by traceroute() and betweenness(). if newdeg[]=NULL, do not discover edges. // breadth_path_search() must have been called to give the corresponding buff[],dist[],paths[] and nb_vertices void explore_usp(double *target, int nb_vertices, int *buff, double *paths, unsigned char *dist, int *newdeg = NULL, double **edge_redudancy = NULL); void explore_asp(double *target, int nb_vertices, int *buff, double *paths, unsigned char *dist, int *newdeg = NULL, double **edge_redudancy = NULL); void explore_rsp(double *target, int nb_vertices, int *buff, double *paths, unsigned char *dist, int *newdeg = NULL, double **edge_redudancy = NULL); // Return component indexes where vertices belong to, starting from 0, // sorted by size (biggest component has index 0) int *components(int *comp = NULL); // pick k random vertices of degree > 0. int *pick_random_vertices(int &k, int *output = NULL, int nb_v = -1, int *among = NULL); public: // neigh[] inline int** neighbors() { return neigh; }; // deg[] inline int* degrees() { return deg; }; //adjacency list of v inline int* operator[](const int v) { return neigh[v]; }; //degree of v inline int degree(const int v) { return deg[v]; }; //compare adjacency lists inline int compare(const int v, const int w) { return deg[v] == deg[w] ? lex_comp(neigh[v], neigh[w], deg[v]) : (deg[v] > deg[w] ? -1 : 1); }; // Detach deg[] and neigh[] void detach(); // Destroy deg and links ~graph_molloy_opt(); // Create graph from file (stdin not supported unless rewind() possible) graph_molloy_opt(FILE *f); // Allocate memory for the graph. Create deg and links. No edge is created. graph_molloy_opt(degree_sequence &); // Create graph from hard copy graph_molloy_opt(int *); // Create hard copy of graph int *hard_copy(); // Remove unused edges, updates neigh[], recreate links[] void clean(); // nb arcs inline int nbarcs() { return a; }; // last degree inline int last_degree() { return deg[n - 1]; }; // nb vertices inline int nbvertices() { return n; }; // nb vertices having degree > 0 inline int nbvertices_real() { int s = 0; for (int *d = deg + n; d-- != deg; ) if (*d) { s++; } return s; }; // return list of vertices with degree > 0. Compute #vertices, if not given. int *vertices_real(int &nb_v); // Keep only giant component void giant_comp(); // nb vertices in giant component int nbvertices_comp(); // nb arcs in giant component int nbarcs_comp(); // print graph in SUCC_LIST mode, in stdout void print(FILE *f = stdout, bool NOZERO = true); // Bind the graph avoiding multiple edges or self-edges (return false if fail) bool havelhakimi(); // Get the graph connected (return false if fail) bool make_connected(); // Test if graph is connected bool is_connected(); // Maximum degree int max_degree(); // breadth-first search. Store the distance (modulo 3) in dist[]. void breadth_search(int *dist, int v0 = 0, int* buff = NULL); // is edge ? inline bool is_edge(const int a, const int b) { if (deg[b] < deg[a]) { return (fast_search(neigh[b], deg[b], a) != NULL); } else { return (fast_search(neigh[a], deg[a], b) != NULL); } } // Backup graph [sizeof(int) bytes per edge] int* backup(int *here = NULL); // Restore from backup. Assume that degrees haven't changed void restore(int* back); // Resplace with hard backup. void replace(int* _hardbackup); // Backup degs of graph int* backup_degs(int *here = NULL); // Restore degs from neigh[]. Need last degree, though void restore_degs(int last_degree); // Restore degs[] from backup. Assume that links[] has only been permuted void restore_degs_only(int* backup_degs); // Restore degs[] and neigh[]. Assume that links[] has only been permuted void restore_degs_and_neigh(int* backup_degs); // WARNING : the following shuffle() algorithms are slow. // Use graph_molloy_hash::connected_shuffle() instead. // "Fab" Shuffle (Optimized heuristic of Gkantsidis algo.) long fab_connected_shuffle(long); // "Optimized-Fab" Shuffle (Optimized heuristic of Gkantsidis algo, with isolated pairs) long opt_fab_connected_shuffle(long); // Gkantsidis Shuffle long gkantsidis_connected_shuffle(long); // Connected Shuffle long slow_connected_shuffle(long); // shortest paths where vertex is an extremity double *vertex_betweenness(int mode, bool trivial_path = false); // Sample the graph with traceroute-like exploration from src[] to dst[]. // if dst[]=NULL, pick nb_dst new random destinations for each src double traceroute_sample(int mode, int nb_src, int *src, int nb_dst, int* dst, double *redudancy = NULL, double **edge_redudancy = NULL); // does one breadth-first search and returns the average_distance. double avg_dist(unsigned char *dist, int *buff, int v0, int &nb_vertices, int toclear = -1); // Number of edges needed to disconnect graph (one random instance) int disconnecting_edges(); // Compute vertex covering of the graph. Warning : this modifies degs[] void vertex_covering(); // Path sampling. Input is nb_dst[] and dst[]. nb_dst[v],dst[v] describe all paths (v,x) double path_sampling(int *nb_dst, int *dst = NULL, double *redudancies = NULL, double **edge_redudancy = NULL); // keep only core (tree parts are deleted). Returns number of removed vertices. int core(); // try to disconnect the graph by swapping edges (with isolation tests) int try_disconnect(int K, int max_tries = 10000000); // Eric & Cun-Hui estimator double rho(int mode, int nb_src, int *src, int nb_dst, int *dst = NULL); // sort adjacency lists void sort(); // sort the vertices according to their degrees (highest first) and to their adjacency lists (lexicographic) int* sort_vertices(int *buff = NULL); // count cycles passing through vertex v int cycles(int v); // remove vertex (i.e. remove all edges adjacent to vertex) void remove_vertex(int v); // pick k random vertices of degree > 0. If k \in [0,1[, k is understood as a density. int *pick_random_src(double k, int *nb = NULL, int* buff = NULL, int nb_v = -1, int* among = NULL); // pick k random vertices of degree > 0. If k \in [0,1], k is understood as a density. int *pick_random_dst(double k, int *nb = NULL, int* buff = NULL, int nb_v = -1, int* among = NULL); // For debug purposes : verify validity of the graph (symetry, simplicity) #define VERIFY_NORMAL 0 #define VERIFY_NONEIGH 1 #define VERIFY_NOARCS 2 bool verify(int mode = VERIFY_NORMAL); /*___________________________________________________________________________________ Not to use anymore : use graph_molloy_hash class instead public: // Shuffle. returns number of swaps done. void shuffle(long); // Connected Shuffle long connected_shuffle(long); // Get caracteristic K double eval_K(int quality = 100); // Get effective K double effective_K(int K, int quality = 10000); // Test window double window(int K, double ratio); // Try to shuffle n times. Return true if at the end, the graph was still connected. bool try_shuffle(int T, int K); //___________________________________________________________________________________ //*/ /*___________________________________________________________________________________ Not to use anymore : replaced by vertex_betweenness() 22/04/2005 // shortest paths where vertex is an extremity long long *vertex_betweenness_usp(bool trivial_path); // shortest paths where vertex is an extremity long long *vertex_betweenness_rsp(bool trivial_path); // same, but when multiple shortest path are possible, average the weights. double *vertex_betweenness_asp(bool trivial_path); //___________________________________________________________________________________ //*/ }; } // namespace gengraph #endif //GRAPH_MOLLOY_OPT_H python-igraph-0.8.0/vendor/source/igraph/src/scan.c0000644000076500000240000007504513614300625022501 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2013 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_scan.h" #include "igraph_interface.h" #include "igraph_adjlist.h" #include "igraph_memory.h" #include "igraph_interrupt_internal.h" #include "igraph_arpack.h" #include "igraph_eigen.h" #include "igraph_centrality.h" #include "igraph_operators.h" #include "igraph_dqueue.h" #include "igraph_stack.h" /** * \section about_local_scan * * * The scan statistic is a summary of the locality statistics that is computed * from the local neighborhood of each vertex. For details, see * Priebe, C. E., Conroy, J. M., Marchette, D. J., Park, Y. (2005). * Scan Statistics on Enron Graphs. Computational and Mathematical Organization Theory. * */ /** * \function igraph_local_scan_0 * Local scan-statistics, k=0 * * K=0 scan-statistics is arbitrarily defined as the vertex degree for * unweighted, and the vertex strength for weighted graphs. See \ref * igraph_degree() and \ref igraph_strength(). * * \param graph The input graph * \param res An initialized vector, the results are stored here. * \param weights Weight vector for weighted graphs, null pointer for * unweighted graphs. * \param mode Type of the neighborhood, \c IGRAPH_OUT means outgoing, * \c IGRAPH_IN means incoming and \c IGRAPH_ALL means all edges. * \return Error code. * */ int igraph_local_scan_0(const igraph_t *graph, igraph_vector_t *res, const igraph_vector_t *weights, igraph_neimode_t mode) { if (weights) { igraph_strength(graph, res, igraph_vss_all(), mode, /*loops=*/ 1, weights); } else { igraph_degree(graph, res, igraph_vss_all(), mode, /*loops=*/ 1); } return 0; } /* From triangles.c */ int igraph_i_trans4_al_simplify(igraph_adjlist_t *al, const igraph_vector_int_t *rank); /* This removes loop, multiple edges and edges that point "backwards" according to the rank vector. It works on edge lists */ int igraph_i_trans4_il_simplify(const igraph_t *graph, igraph_inclist_t *il, const igraph_vector_int_t *rank) { long int i; long int n = il->length; igraph_vector_int_t mark; igraph_vector_int_init(&mark, n); IGRAPH_FINALLY(igraph_vector_int_destroy, &mark); for (i = 0; i < n; i++) { igraph_vector_int_t *v = &il->incs[i]; int j, l = igraph_vector_int_size(v); int irank = VECTOR(*rank)[i]; VECTOR(mark)[i] = i + 1; for (j = 0; j < l; /* nothing */) { long int edge = (long int) VECTOR(*v)[j]; long int e = IGRAPH_OTHER(graph, edge, i); if (VECTOR(*rank)[e] > irank && VECTOR(mark)[e] != i + 1) { VECTOR(mark)[e] = i + 1; j++; } else { VECTOR(*v)[j] = igraph_vector_int_tail(v); igraph_vector_int_pop_back(v); l--; } } } igraph_vector_int_destroy(&mark); IGRAPH_FINALLY_CLEAN(1); return 0; } /* This one handles both weighted and unweighted cases */ int igraph_i_local_scan_1_directed(const igraph_t *graph, igraph_vector_t *res, const igraph_vector_t *weights, igraph_neimode_t mode) { int no_of_nodes = igraph_vcount(graph); igraph_inclist_t incs; int i, node; igraph_vector_int_t neis; IGRAPH_CHECK(igraph_inclist_init(graph, &incs, mode)); IGRAPH_FINALLY(igraph_inclist_destroy, &incs); igraph_vector_int_init(&neis, no_of_nodes); IGRAPH_FINALLY(igraph_vector_int_destroy, &neis); igraph_vector_resize(res, no_of_nodes); igraph_vector_null(res); for (node = 0; node < no_of_nodes; node++) { igraph_vector_int_t *edges1 = igraph_inclist_get(&incs, node); int edgeslen1 = igraph_vector_int_size(edges1); IGRAPH_ALLOW_INTERRUPTION(); /* Mark neighbors and self*/ VECTOR(neis)[node] = node + 1; for (i = 0; i < edgeslen1; i++) { int e = VECTOR(*edges1)[i]; int nei = IGRAPH_OTHER(graph, e, node); igraph_real_t w = weights ? VECTOR(*weights)[e] : 1; VECTOR(neis)[nei] = node + 1; VECTOR(*res)[node] += w; } /* Crawl neighbors */ for (i = 0; i < edgeslen1; i++) { int e2 = VECTOR(*edges1)[i]; int nei = IGRAPH_OTHER(graph, e2, node); igraph_vector_int_t *edges2 = igraph_inclist_get(&incs, nei); int j, edgeslen2 = igraph_vector_int_size(edges2); for (j = 0; j < edgeslen2; j++) { int e2 = VECTOR(*edges2)[j]; int nei2 = IGRAPH_OTHER(graph, e2, nei); igraph_real_t w2 = weights ? VECTOR(*weights)[e2] : 1; if (VECTOR(neis)[nei2] == node + 1) { VECTOR(*res)[node] += w2; } } } } /* node < no_of_nodes */ igraph_vector_int_destroy(&neis); igraph_inclist_destroy(&incs); IGRAPH_FINALLY_CLEAN(2); return 0; } int igraph_i_local_scan_1_directed_all(const igraph_t *graph, igraph_vector_t *res, const igraph_vector_t *weights) { int no_of_nodes = igraph_vcount(graph); igraph_inclist_t incs; int i, node; igraph_vector_int_t neis; IGRAPH_CHECK(igraph_inclist_init(graph, &incs, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_inclist_destroy, &incs); igraph_vector_int_init(&neis, no_of_nodes); IGRAPH_FINALLY(igraph_vector_int_destroy, &neis); igraph_vector_resize(res, no_of_nodes); igraph_vector_null(res); for (node = 0; node < no_of_nodes; node++) { igraph_vector_int_t *edges1 = igraph_inclist_get(&incs, node); int edgeslen1 = igraph_vector_int_size(edges1); IGRAPH_ALLOW_INTERRUPTION(); /* Mark neighbors. We also count the edges that are incident to ego. Note that this time we do not mark ego, because we don't want to double count its incident edges later, when we are going over the incident edges of ego's neighbors. */ for (i = 0; i < edgeslen1; i++) { int e = VECTOR(*edges1)[i]; int nei = IGRAPH_OTHER(graph, e, node); igraph_real_t w = weights ? VECTOR(*weights)[e] : 1; VECTOR(neis)[nei] = node + 1; VECTOR(*res)[node] += w; } /* Crawl neighbors. We make sure that each neighbor of 'node' is only crawed once. We count all qualifying edges of ego, and then unmark ego to avoid double counting. */ for (i = 0; i < edgeslen1; i++) { int e2 = VECTOR(*edges1)[i]; int nei = IGRAPH_OTHER(graph, e2, node); igraph_vector_int_t *edges2; int j, edgeslen2; if (VECTOR(neis)[nei] != node + 1) { continue; } edges2 = igraph_inclist_get(&incs, nei); edgeslen2 = igraph_vector_int_size(edges2); for (j = 0; j < edgeslen2; j++) { int e2 = VECTOR(*edges2)[j]; int nei2 = IGRAPH_OTHER(graph, e2, nei); igraph_real_t w2 = weights ? VECTOR(*weights)[e2] : 1; if (VECTOR(neis)[nei2] == node + 1) { VECTOR(*res)[node] += w2; } } VECTOR(neis)[nei] = 0; } } /* node < no_of_nodes */ igraph_vector_int_destroy(&neis); igraph_inclist_destroy(&incs); IGRAPH_FINALLY_CLEAN(2); return 0; } int igraph_i_local_scan_1_sumweights(const igraph_t *graph, igraph_vector_t *res, const igraph_vector_t *weights) { long int no_of_nodes = igraph_vcount(graph); long int node, i, j, nn; igraph_inclist_t allinc; igraph_vector_int_t *neis1, *neis2; long int neilen1, neilen2; long int *neis; long int maxdegree; igraph_vector_int_t order; igraph_vector_int_t rank; igraph_vector_t degree, *edge1 = °ree; /* reuse degree as edge1 */ if (igraph_vector_size(weights) != igraph_ecount(graph)) { IGRAPH_ERROR("Invalid weight vector length", IGRAPH_EINVAL); } igraph_vector_int_init(&order, no_of_nodes); IGRAPH_FINALLY(igraph_vector_int_destroy, &order); IGRAPH_VECTOR_INIT_FINALLY(°ree, no_of_nodes); IGRAPH_CHECK(igraph_degree(graph, °ree, igraph_vss_all(), IGRAPH_ALL, IGRAPH_LOOPS)); maxdegree = (long int) igraph_vector_max(°ree) + 1; igraph_vector_order1_int(°ree, &order, maxdegree); igraph_vector_int_init(&rank, no_of_nodes); IGRAPH_FINALLY(igraph_vector_int_destroy, &rank); for (i = 0; i < no_of_nodes; i++) { VECTOR(rank)[ VECTOR(order)[i] ] = no_of_nodes - i - 1; } IGRAPH_CHECK(igraph_inclist_init(graph, &allinc, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_inclist_destroy, &allinc); IGRAPH_CHECK(igraph_i_trans4_il_simplify(graph, &allinc, &rank)); neis = igraph_Calloc(no_of_nodes, long int); if (neis == 0) { IGRAPH_ERROR("undirected local transitivity failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, neis); IGRAPH_CHECK(igraph_strength(graph, res, igraph_vss_all(), IGRAPH_ALL, IGRAPH_LOOPS, weights)); for (nn = no_of_nodes - 1; nn >= 0; nn--) { node = VECTOR(order)[nn]; IGRAPH_ALLOW_INTERRUPTION(); neis1 = igraph_inclist_get(&allinc, node); neilen1 = igraph_vector_int_size(neis1); /* Mark the neighbors of the node */ for (i = 0; i < neilen1; i++) { int edge = VECTOR(*neis1)[i]; int nei = IGRAPH_OTHER(graph, edge, node); VECTOR(*edge1)[nei] = VECTOR(*weights)[edge]; neis[nei] = node + 1; } for (i = 0; i < neilen1; i++) { long int edge = VECTOR(*neis1)[i]; long int nei = IGRAPH_OTHER(graph, edge, node); igraph_real_t w = VECTOR(*weights)[edge]; neis2 = igraph_inclist_get(&allinc, nei); neilen2 = igraph_vector_int_size(neis2); for (j = 0; j < neilen2; j++) { long int edge2 = VECTOR(*neis2)[j]; long int nei2 = IGRAPH_OTHER(graph, edge2, nei); igraph_real_t w2 = VECTOR(*weights)[edge2]; if (neis[nei2] == node + 1) { VECTOR(*res)[node] += w2; VECTOR(*res)[nei2] += w; VECTOR(*res)[nei] += VECTOR(*edge1)[nei2]; } } } } igraph_free(neis); igraph_inclist_destroy(&allinc); igraph_vector_int_destroy(&rank); igraph_vector_destroy(°ree); igraph_vector_int_destroy(&order); IGRAPH_FINALLY_CLEAN(5); return 0; } /** * \function igraph_local_scan_1_ecount * Local scan-statistics, k=1, edge count and sum of weights * * Count the number of edges or the sum the edge weights in the * 1-neighborhood of vertices. * * \param graph The input graph * \param res An initialized vector, the results are stored here. * \param weights Weight vector for weighted graphs, null pointer for * unweighted graphs. * \param mode Type of the neighborhood, \c IGRAPH_OUT means outgoing, * \c IGRAPH_IN means incoming and \c IGRAPH_ALL means all edges. * \return Error code. * */ int igraph_local_scan_1_ecount(const igraph_t *graph, igraph_vector_t *res, const igraph_vector_t *weights, igraph_neimode_t mode) { if (igraph_is_directed(graph)) { if (mode != IGRAPH_ALL) { return igraph_i_local_scan_1_directed(graph, res, weights, mode); } else { return igraph_i_local_scan_1_directed_all(graph, res, weights); } } else { if (weights) { return igraph_i_local_scan_1_sumweights(graph, res, weights); } else { #define TRIEDGES #include "triangles_template.h" #undef TRIEDGES } } return 0; } int igraph_i_local_scan_0_them_w(const igraph_t *us, const igraph_t *them, igraph_vector_t *res, const igraph_vector_t *weights_them, igraph_neimode_t mode) { igraph_t is; igraph_vector_t map2; int i, m; if (!weights_them) { IGRAPH_ERROR("Edge weights not given for weighted scan-0", IGRAPH_EINVAL); } if (igraph_vector_size(weights_them) != igraph_ecount(them)) { IGRAPH_ERROR("Invalid weights length for scan-0", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(&map2, 0); igraph_intersection(&is, us, them, /*map1=*/ 0, &map2); IGRAPH_FINALLY(igraph_destroy, &is); /* Rewrite the map as edge weights */ m = igraph_vector_size(&map2); for (i = 0; i < m; i++) { VECTOR(map2)[i] = VECTOR(*weights_them)[ (int) VECTOR(map2)[i] ]; } igraph_strength(&is, res, igraph_vss_all(), mode, IGRAPH_LOOPS, /*weights=*/ &map2); igraph_destroy(&is); igraph_vector_destroy(&map2); IGRAPH_FINALLY_CLEAN(2); return 0; } /** * \function igraph_local_scan_0_them * Local THEM scan-statistics, k=0 * * K=0 scan-statistics is arbitrarily defined as the vertex degree for * unweighted, and the vertex strength for weighted graphs. See \ref * igraph_degree() and \ref igraph_strength(). * * \param us The input graph, to use to extract the neighborhoods. * \param them The input graph to use for the actually counting. * \param res An initialized vector, the results are stored here. * \param weights_them Weight vector for weighted graphs, null pointer for * unweighted graphs. * \param mode Type of the neighborhood, \c IGRAPH_OUT means outgoing, * \c IGRAPH_IN means incoming and \c IGRAPH_ALL means all edges. * \return Error code. * */ int igraph_local_scan_0_them(const igraph_t *us, const igraph_t *them, igraph_vector_t *res, const igraph_vector_t *weights_them, igraph_neimode_t mode) { igraph_t is; if (igraph_vcount(us) != igraph_vcount(them)) { IGRAPH_ERROR("Number of vertices don't match in scan-0", IGRAPH_EINVAL); } if (igraph_is_directed(us) != igraph_is_directed(them)) { IGRAPH_ERROR("Directedness don't match in scan-0", IGRAPH_EINVAL); } if (weights_them) { return igraph_i_local_scan_0_them_w(us, them, res, weights_them, mode); } igraph_intersection(&is, us, them, /*edgemap1=*/ 0, /*edgemap2=*/ 0); IGRAPH_FINALLY(igraph_destroy, &is); igraph_degree(&is, res, igraph_vss_all(), mode, IGRAPH_LOOPS); igraph_destroy(&is); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_local_scan_1_ecount_them * Local THEM scan-statistics, k=1, edge count and sum of weights * * Count the number of edges or the sum the edge weights in the * 1-neighborhood of vertices. * * \param us The input graph to extract the neighborhoods. * \param them The input graph to perform the counting. * \param weights_them Weight vector for weighted graphs, null pointer for * unweighted graphs. * \param mode Type of the neighborhood, \c IGRAPH_OUT means outgoing, * \c IGRAPH_IN means incoming and \c IGRAPH_ALL means all edges. * \return Error code. * * \sa \ref igraph_local_scan_1_ecount() for the US statistics. */ int igraph_local_scan_1_ecount_them(const igraph_t *us, const igraph_t *them, igraph_vector_t *res, const igraph_vector_t *weights_them, igraph_neimode_t mode) { int no_of_nodes = igraph_vcount(us); igraph_adjlist_t adj_us; igraph_inclist_t incs_them; igraph_vector_int_t neis; int node; if (igraph_vcount(them) != no_of_nodes) { IGRAPH_ERROR("Number of vertices must match in scan-1", IGRAPH_EINVAL); } if (igraph_is_directed(us) != igraph_is_directed(them)) { IGRAPH_ERROR("Directedness must match in scan-1", IGRAPH_EINVAL); } if (weights_them && igraph_vector_size(weights_them) != igraph_ecount(them)) { IGRAPH_ERROR("Invalid weight vector length in scan-1 (them)", IGRAPH_EINVAL); } igraph_adjlist_init(us, &adj_us, mode); IGRAPH_FINALLY(igraph_adjlist_destroy, &adj_us); igraph_adjlist_simplify(&adj_us); igraph_inclist_init(them, &incs_them, mode); IGRAPH_FINALLY(igraph_inclist_destroy, &incs_them); igraph_vector_int_init(&neis, no_of_nodes); IGRAPH_FINALLY(igraph_vector_int_destroy, &neis); igraph_vector_resize(res, no_of_nodes); igraph_vector_null(res); for (node = 0; node < no_of_nodes; node++) { igraph_vector_int_t *neis_us = igraph_adjlist_get(&adj_us, node); igraph_vector_int_t *edges1_them = igraph_inclist_get(&incs_them, node); int len1_us = igraph_vector_int_size(neis_us); int len1_them = igraph_vector_int_size(edges1_them); int i; IGRAPH_ALLOW_INTERRUPTION(); /* Mark neighbors and self in us */ VECTOR(neis)[node] = node + 1; for (i = 0; i < len1_us; i++) { int nei = VECTOR(*neis_us)[i]; VECTOR(neis)[nei] = node + 1; } /* Crawl neighbors in them, first ego */ for (i = 0; i < len1_them; i++) { int e = VECTOR(*edges1_them)[i]; int nei = IGRAPH_OTHER(them, e, node); if (VECTOR(neis)[nei] == node + 1) { igraph_real_t w = weights_them ? VECTOR(*weights_them)[e] : 1; VECTOR(*res)[node] += w; } } /* Then the rest */ for (i = 0; i < len1_us; i++) { int nei = VECTOR(*neis_us)[i]; igraph_vector_int_t *edges2_them = igraph_inclist_get(&incs_them, nei); int j, len2_them = igraph_vector_int_size(edges2_them); for (j = 0; j < len2_them; j++) { int e2 = VECTOR(*edges2_them)[j]; int nei2 = IGRAPH_OTHER(them, e2, nei); if (VECTOR(neis)[nei2] == node + 1) { igraph_real_t w = weights_them ? VECTOR(*weights_them)[e2] : 1; VECTOR(*res)[node] += w; } } } /* For undirected, it was double counted */ if (mode == IGRAPH_ALL || ! igraph_is_directed(us)) { VECTOR(*res)[node] /= 2.0; } } /* node < no_of_nodes */ igraph_vector_int_destroy(&neis); igraph_inclist_destroy(&incs_them); igraph_adjlist_destroy(&adj_us); IGRAPH_FINALLY_CLEAN(3); return 0; } /** * \function igraph_local_scan_k_ecount * Local scan-statistics, general function, edge count and sum of weights * * Count the number of edges or the sum the edge weights in the * k-neighborhood of vertices. * * \param graph The input graph * \param k The size of the neighborhood, non-negative integer. * The k=0 case is special, see \ref igraph_local_scan_0(). * \param res An initialized vector, the results are stored here. * \param weights Weight vector for weighted graphs, null pointer for * unweighted graphs. * \param mode Type of the neighborhood, \c IGRAPH_OUT means outgoing, * \c IGRAPH_IN means incoming and \c IGRAPH_ALL means all edges. * \return Error code. * */ int igraph_local_scan_k_ecount(const igraph_t *graph, int k, igraph_vector_t *res, const igraph_vector_t *weights, igraph_neimode_t mode) { int no_of_nodes = igraph_vcount(graph); int node; igraph_dqueue_int_t Q; igraph_vector_int_t marked; igraph_inclist_t incs; if (k < 0) { IGRAPH_ERROR("k must be non-negative in k-scan", IGRAPH_EINVAL); } if (weights && igraph_vector_size(weights) != igraph_ecount(graph)) { IGRAPH_ERROR("Invalid weight vector length in k-scan", IGRAPH_EINVAL); } if (k == 0) { return igraph_local_scan_0(graph, res, weights, mode); } if (k == 1) { return igraph_local_scan_1_ecount(graph, res, weights, mode); } /* We do a BFS form each node, and simply count the number of edges on the way */ IGRAPH_CHECK(igraph_dqueue_int_init(&Q, 100)); IGRAPH_FINALLY(igraph_dqueue_int_destroy, &Q); IGRAPH_CHECK(igraph_vector_int_init(&marked, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_int_destroy, &marked); IGRAPH_CHECK(igraph_inclist_init(graph, &incs, mode)); IGRAPH_FINALLY(igraph_inclist_destroy, &incs); IGRAPH_CHECK(igraph_vector_resize(res, no_of_nodes)); igraph_vector_null(res); for (node = 0 ; node < no_of_nodes ; node++) { igraph_dqueue_int_push(&Q, node); igraph_dqueue_int_push(&Q, 0); VECTOR(marked)[node] = node + 1; while (!igraph_dqueue_int_empty(&Q)) { int act = igraph_dqueue_int_pop(&Q); int dist = igraph_dqueue_int_pop(&Q) + 1; igraph_vector_int_t *edges = igraph_inclist_get(&incs, act); int i, edgeslen = igraph_vector_int_size(edges); for (i = 0; i < edgeslen; i++) { int edge = VECTOR(*edges)[i]; int nei = IGRAPH_OTHER(graph, edge, act); if (dist <= k || VECTOR(marked)[nei] == node + 1) { igraph_real_t w = weights ? VECTOR(*weights)[edge] : 1; VECTOR(*res)[node] += w; } if (dist <= k && VECTOR(marked)[nei] != node + 1) { igraph_dqueue_int_push(&Q, nei); igraph_dqueue_int_push(&Q, dist); VECTOR(marked)[nei] = node + 1; } } } if (mode == IGRAPH_ALL || ! igraph_is_directed(graph)) { VECTOR(*res)[node] /= 2.0; } } /* node < no_of_nodes */ igraph_inclist_destroy(&incs); igraph_vector_int_destroy(&marked); igraph_dqueue_int_destroy(&Q); IGRAPH_FINALLY_CLEAN(3); return 0; } /** * \function igraph_local_scan_k_ecount_them * Local THEM scan-statistics, general function, edge count and sum of weights * * Count the number of edges or the sum the edge weights in the * k-neighborhood of vertices. * * \param us The input graph to extract the neighborhoods. * \param them The input graph to perform the counting. * \param k The size of the neighborhood, non-negative integer. * The k=0 case is special, see \ref igraph_local_scan_0_them(). * \param weights_them Weight vector for weighted graphs, null pointer for * unweighted graphs. * \param mode Type of the neighborhood, \c IGRAPH_OUT means outgoing, * \c IGRAPH_IN means incoming and \c IGRAPH_ALL means all edges. * \return Error code. * * \sa \ref igraph_local_scan_1_ecount() for the US statistics. */ int igraph_local_scan_k_ecount_them(const igraph_t *us, const igraph_t *them, int k, igraph_vector_t *res, const igraph_vector_t *weights_them, igraph_neimode_t mode) { int no_of_nodes = igraph_vcount(us); int node; igraph_dqueue_int_t Q; igraph_vector_int_t marked; igraph_stack_int_t ST; igraph_inclist_t incs_us, incs_them; if (igraph_vcount(them) != no_of_nodes) { IGRAPH_ERROR("Number of vertices must match in scan-k", IGRAPH_EINVAL); } if (igraph_is_directed(us) != igraph_is_directed(them)) { IGRAPH_ERROR("Directedness must match in scan-k", IGRAPH_EINVAL); } if (k < 0) { IGRAPH_ERROR("k must be non-negative in k-scan", IGRAPH_EINVAL); } if (weights_them && igraph_vector_size(weights_them) != igraph_ecount(them)) { IGRAPH_ERROR("Invalid weight vector length in k-scan (them)", IGRAPH_EINVAL); } if (k == 0) { return igraph_local_scan_0_them(us, them, res, weights_them, mode); } if (k == 1) { return igraph_local_scan_1_ecount_them(us, them, res, weights_them, mode); } /* We mark the nodes in US in a BFS. Then we check the outgoing edges of all marked nodes in THEM. */ IGRAPH_CHECK(igraph_dqueue_int_init(&Q, 100)); IGRAPH_FINALLY(igraph_dqueue_int_destroy, &Q); IGRAPH_CHECK(igraph_vector_int_init(&marked, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_int_destroy, &marked); IGRAPH_CHECK(igraph_inclist_init(us, &incs_us, mode)); IGRAPH_FINALLY(igraph_inclist_destroy, &incs_us); IGRAPH_CHECK(igraph_inclist_init(them, &incs_them, mode)); IGRAPH_FINALLY(igraph_inclist_destroy, &incs_them); IGRAPH_CHECK(igraph_stack_int_init(&ST, 100)); IGRAPH_FINALLY(igraph_stack_int_destroy, &ST); IGRAPH_CHECK(igraph_vector_resize(res, no_of_nodes)); igraph_vector_null(res); for (node = 0; node < no_of_nodes; node++) { /* BFS to mark the nodes in US */ IGRAPH_CHECK(igraph_dqueue_int_push(&Q, node)); IGRAPH_CHECK(igraph_dqueue_int_push(&Q, 0)); IGRAPH_CHECK(igraph_stack_int_push(&ST, node)); VECTOR(marked)[node] = node + 1; while (!igraph_dqueue_int_empty(&Q)) { int act = igraph_dqueue_int_pop(&Q); int dist = igraph_dqueue_int_pop(&Q) + 1; igraph_vector_int_t *edges = igraph_inclist_get(&incs_us, act); int i, edgeslen = igraph_vector_int_size(edges); for (i = 0; i < edgeslen; i++) { int edge = VECTOR(*edges)[i]; int nei = IGRAPH_OTHER(us, edge, act); if (dist <= k && VECTOR(marked)[nei] != node + 1) { igraph_dqueue_int_push(&Q, nei); igraph_dqueue_int_push(&Q, dist); VECTOR(marked)[nei] = node + 1; igraph_stack_int_push(&ST, nei); } } } /* Now check the edges of all nodes in THEM */ while (!igraph_stack_int_empty(&ST)) { int act = igraph_stack_int_pop(&ST); igraph_vector_int_t *edges = igraph_inclist_get(&incs_them, act); int i, edgeslen = igraph_vector_int_size(edges); for (i = 0; i < edgeslen; i++) { int edge = VECTOR(*edges)[i]; int nei = IGRAPH_OTHER(them, edge, act); if (VECTOR(marked)[nei] == node + 1) { igraph_real_t w = weights_them ? VECTOR(*weights_them)[edge] : 1; VECTOR(*res)[node] += w; } } } if (mode == IGRAPH_ALL || ! igraph_is_directed(us)) { VECTOR(*res)[node] /= 2; } } /* node < no_of_nodes */ igraph_stack_int_destroy(&ST); igraph_inclist_destroy(&incs_them); igraph_inclist_destroy(&incs_us); igraph_vector_int_destroy(&marked); igraph_dqueue_int_destroy(&Q); IGRAPH_FINALLY_CLEAN(5); return 0; } /** * \function igraph_local_scan_neighborhood_ecount * Local scan-statistics with pre-calculated neighborhoods * * Count the number of edges, or sum the edge weigths in * neighborhoods given as a parameter. * * \param graph The graph to perform the counting/summing in. * \param res Initialized vector, the result is stored here. * \param weights Weight vector for weighted graphs, null pointer for * unweighted graphs. * \param neighborhoods List of igraph_vector_int_t * objects, the neighborhoods, one for each vertex in the * graph. * \return Error code. */ int igraph_local_scan_neighborhood_ecount(const igraph_t *graph, igraph_vector_t *res, const igraph_vector_t *weights, const igraph_vector_ptr_t *neighborhoods) { int node, no_of_nodes = igraph_vcount(graph); igraph_inclist_t incs; igraph_vector_int_t marked; igraph_bool_t directed = igraph_is_directed(graph); if (weights && igraph_vector_size(weights) != igraph_ecount(graph)) { IGRAPH_ERROR("Invalid weight vector length in local scan", IGRAPH_EINVAL); } if (igraph_vector_ptr_size(neighborhoods) != no_of_nodes) { IGRAPH_ERROR("Invalid neighborhood list length in local scan", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_vector_int_init(&marked, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_int_destroy, &marked); IGRAPH_CHECK(igraph_inclist_init(graph, &incs, IGRAPH_OUT)); IGRAPH_FINALLY(igraph_inclist_destroy, &incs); IGRAPH_CHECK(igraph_vector_resize(res, no_of_nodes)); igraph_vector_null(res); for (node = 0; node < no_of_nodes; node++) { igraph_vector_int_t *nei = VECTOR(*neighborhoods)[node]; int i, neilen = igraph_vector_int_size(nei); VECTOR(marked)[node] = node + 1; for (i = 0; i < neilen; i++) { int vertex = VECTOR(*nei)[i]; if (vertex < 0 || vertex >= no_of_nodes) { IGRAPH_ERROR("Invalid vertex id in neighborhood list in local scan", IGRAPH_EINVAL); } VECTOR(marked)[vertex] = node + 1; } for (i = 0; i < neilen; i++) { int vertex = VECTOR(*nei)[i]; igraph_vector_int_t *edges = igraph_inclist_get(&incs, vertex); int j, edgeslen = igraph_vector_int_size(edges); for (j = 0; j < edgeslen; j++) { int edge = VECTOR(*edges)[j]; int nei2 = IGRAPH_OTHER(graph, edge, vertex); if (VECTOR(marked)[nei2] == node + 1) { igraph_real_t w = weights ? VECTOR(*weights)[edge] : 1; VECTOR(*res)[node] += w; } } } if (!directed) { VECTOR(*res)[node] /= 2.0; } } igraph_inclist_destroy(&incs); igraph_vector_int_destroy(&marked); IGRAPH_FINALLY_CLEAN(2); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/walktrap_graph.h0000644000076500000240000000703513614300625024562 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ /* The original version of this file was written by Pascal Pons The original copyright notice follows here */ // File: graph.h //----------------------------------------------------------------------------- // Walktrap v0.2 -- Finds community structure of networks using random walks // Copyright (C) 2004-2005 Pascal Pons // // This program is free software; you can redistribute it and/or modify // it under the terms of the GNU General Public License as published by // the Free Software Foundation; either version 2 of the License, or // (at your option) any later version. // // This program is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU General Public License for more details. // // You should have received a copy of the GNU General Public License // along with this program; if not, write to the Free Software // Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA // 02110-1301 USA //----------------------------------------------------------------------------- // Author : Pascal Pons // Email : pascal.pons@gmail.com // Web page : http://www-rp.lip6.fr/~latapy/PP/walktrap.html // Location : Paris, France // Time : June 2005 //----------------------------------------------------------------------------- // see readme.txt for more details /* FSF address above was fixed by Tamas Nepusz */ #ifndef GRAPH_H #define GRAPH_H #include #include "igraph_community.h" namespace igraph { namespace walktrap { using namespace std; class Edge { // code an edge of a given vertex public: int neighbor; // the number of the neighbor vertex float weight; // the weight of the edge }; bool operator<(const Edge& E1, const Edge& E2); class Vertex { public: Edge* edges; // the edges of the vertex int degree; // number of neighbors float total_weight; // the total weight of the vertex Vertex(); // creates empty vertex ~Vertex(); // destructor }; class Graph { public: int nb_vertices; // number of vertices int nb_edges; // number of edges float total_weight; // total weight of the edges Vertex* vertices; // array of the vertices long memory(); // the total memory used in Bytes Graph(); // create an empty graph ~Graph(); // destructor char** index; // to keep the real name of the vertices int convert_from_igraph(const igraph_t * igraph, const igraph_vector_t *weights); }; } } /* end of namespaces */ #endif python-igraph-0.8.0/vendor/source/igraph/src/triangles.c0000644000076500000240000010532113614300625023534 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2005-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_transitivity.h" #include "igraph_interface.h" #include "igraph_adjlist.h" #include "igraph_memory.h" #include "igraph_interrupt_internal.h" #include "igraph_centrality.h" #include "igraph_motifs.h" #include "igraph_structural.h" /** * \function igraph_transitivity_avglocal_undirected * \brief Average local transitivity (clustering coefficient). * * The transitivity measures the probability that two neighbors of a * vertex are connected. In case of the average local transitivity, * this probability is calculated for each vertex and then the average * is taken. Vertices with less than two neighbors require special treatment, * they will either be left out from the calculation or they will be considered * as having zero transitivity, depending on the \c mode argument. * * * Note that this measure is different from the global transitivity measure * (see \ref igraph_transitivity_undirected() ) as it simply takes the * average local transitivity across the whole network. See the following * reference for more details: * * * D. J. Watts and S. Strogatz: Collective dynamics of small-world networks. * Nature 393(6684):440-442 (1998). * * * Clustering coefficient is an alternative name for transitivity. * * \param graph The input graph, directed graphs are considered as * undirected ones. * \param res Pointer to a real variable, the result will be stored here. * \param mode Defines how to treat vertices with degree less than two. * \c IGRAPH_TRANSITIVITY_NAN leaves them out from averaging, * \c IGRAPH_TRANSITIVITY_ZERO includes them with zero transitivity. * The result will be \c NaN if the mode is \c IGRAPH_TRANSITIVITY_NAN * and there are no vertices with more than one neighbor. * * \return Error code. * * \sa \ref igraph_transitivity_undirected(), \ref * igraph_transitivity_local_undirected(). * * Time complexity: O(|V|*d^2), |V| is the number of vertices in the * graph and d is the average degree. */ int igraph_transitivity_avglocal_undirected(const igraph_t *graph, igraph_real_t *res, igraph_transitivity_mode_t mode) { long int no_of_nodes = igraph_vcount(graph); igraph_real_t sum = 0.0; igraph_integer_t count = 0; long int node, i, j, nn; igraph_adjlist_t allneis; igraph_vector_int_t *neis1, *neis2; long int neilen1, neilen2; long int *neis; long int maxdegree; igraph_vector_t order; igraph_vector_t rank; igraph_vector_t degree; igraph_vector_t triangles; IGRAPH_VECTOR_INIT_FINALLY(&order, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(°ree, no_of_nodes); IGRAPH_CHECK(igraph_degree(graph, °ree, igraph_vss_all(), IGRAPH_ALL, IGRAPH_LOOPS)); maxdegree = (long int) igraph_vector_max(°ree) + 1; igraph_vector_order1(°ree, &order, maxdegree); igraph_vector_destroy(°ree); IGRAPH_FINALLY_CLEAN(1); IGRAPH_VECTOR_INIT_FINALLY(&rank, no_of_nodes); for (i = 0; i < no_of_nodes; i++) { VECTOR(rank)[ (long int) VECTOR(order)[i] ] = no_of_nodes - i - 1; } IGRAPH_CHECK(igraph_adjlist_init(graph, &allneis, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_adjlist_destroy, &allneis); IGRAPH_CHECK(igraph_adjlist_simplify(&allneis)); neis = igraph_Calloc(no_of_nodes, long int); if (neis == 0) { IGRAPH_ERROR("undirected average local transitivity failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, neis); IGRAPH_VECTOR_INIT_FINALLY(&triangles, no_of_nodes); for (nn = no_of_nodes - 1; nn >= 0; nn--) { node = (long int) VECTOR(order)[nn]; IGRAPH_ALLOW_INTERRUPTION(); neis1 = igraph_adjlist_get(&allneis, node); neilen1 = igraph_vector_int_size(neis1); /* Mark the neighbors of 'node' */ for (i = 0; i < neilen1; i++) { neis[ (long int)VECTOR(*neis1)[i] ] = node + 1; } for (i = 0; i < neilen1; i++) { long int nei = (long int) VECTOR(*neis1)[i]; if (VECTOR(rank)[nei] > VECTOR(rank)[node]) { neis2 = igraph_adjlist_get(&allneis, nei); neilen2 = igraph_vector_int_size(neis2); for (j = 0; j < neilen2; j++) { long int nei2 = (long int) VECTOR(*neis2)[j]; if (VECTOR(rank)[nei2] < VECTOR(rank)[nei]) { continue; } if (neis[nei2] == node + 1) { VECTOR(triangles)[nei2] += 1; VECTOR(triangles)[nei] += 1; VECTOR(triangles)[node] += 1; } } } } if (neilen1 >= 2) { sum += VECTOR(triangles)[node] / neilen1 / (neilen1 - 1) * 2.0; count++; } else if (mode == IGRAPH_TRANSITIVITY_ZERO) { count++; } } *res = sum / count; igraph_vector_destroy(&triangles); igraph_Free(neis); igraph_adjlist_destroy(&allneis); igraph_vector_destroy(&rank); igraph_vector_destroy(&order); IGRAPH_FINALLY_CLEAN(5); return 0; } int igraph_transitivity_local_undirected1(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, igraph_transitivity_mode_t mode) { #define TRANSIT #include "triangles_template1.h" #undef TRANSIT return 0; } int igraph_transitivity_local_undirected2(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, igraph_transitivity_mode_t mode) { long int no_of_nodes = igraph_vcount(graph); igraph_vit_t vit; long int nodes_to_calc, affected_nodes; long int maxdegree = 0; long int i, j, k, nn; igraph_lazy_adjlist_t adjlist; igraph_vector_t indexv, avids, rank, order, triangles, degree; long int *neis; IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); nodes_to_calc = IGRAPH_VIT_SIZE(vit); IGRAPH_CHECK(igraph_lazy_adjlist_init(graph, &adjlist, IGRAPH_ALL, IGRAPH_SIMPLIFY)); IGRAPH_FINALLY(igraph_lazy_adjlist_destroy, &adjlist); IGRAPH_VECTOR_INIT_FINALLY(&indexv, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&avids, 0); IGRAPH_CHECK(igraph_vector_reserve(&avids, nodes_to_calc)); k = 0; for (i = 0; i < nodes_to_calc; IGRAPH_VIT_NEXT(vit), i++) { long int v = IGRAPH_VIT_GET(vit); igraph_vector_t *neis2; long int neilen; if (VECTOR(indexv)[v] == 0) { VECTOR(indexv)[v] = k + 1; k++; IGRAPH_CHECK(igraph_vector_push_back(&avids, v)); } neis2 = igraph_lazy_adjlist_get(&adjlist, (igraph_integer_t) v); neilen = igraph_vector_size(neis2); for (j = 0; j < neilen; j++) { long int nei = (long int) VECTOR(*neis2)[j]; if (VECTOR(indexv)[nei] == 0) { VECTOR(indexv)[nei] = k + 1; k++; IGRAPH_CHECK(igraph_vector_push_back(&avids, nei)); } } } /* Degree, ordering, ranking */ affected_nodes = igraph_vector_size(&avids); IGRAPH_VECTOR_INIT_FINALLY(&order, 0); IGRAPH_VECTOR_INIT_FINALLY(°ree, affected_nodes); for (i = 0; i < affected_nodes; i++) { long int v = (long int) VECTOR(avids)[i]; igraph_vector_t *neis2; long int deg; neis2 = igraph_lazy_adjlist_get(&adjlist, (igraph_integer_t) v); VECTOR(degree)[i] = deg = igraph_vector_size(neis2); if (deg > maxdegree) { maxdegree = deg; } } igraph_vector_order1(°ree, &order, maxdegree + 1); igraph_vector_destroy(°ree); IGRAPH_FINALLY_CLEAN(1); IGRAPH_VECTOR_INIT_FINALLY(&rank, affected_nodes); for (i = 0; i < affected_nodes; i++) { VECTOR(rank)[ (long int) VECTOR(order)[i] ] = affected_nodes - i - 1; } neis = igraph_Calloc(no_of_nodes, long int); if (neis == 0) { IGRAPH_ERROR("local transitivity calculation failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, neis); IGRAPH_VECTOR_INIT_FINALLY(&triangles, affected_nodes); for (nn = affected_nodes - 1; nn >= 0; nn--) { long int node = (long int) VECTOR(avids) [ (long int) VECTOR(order)[nn] ]; igraph_vector_t *neis1, *neis2; long int neilen1, neilen2; long int nodeindex = (long int) VECTOR(indexv)[node]; long int noderank = (long int) VECTOR(rank) [nodeindex - 1]; /* fprintf(stderr, "node %li (indexv %li, rank %li)\n", node, */ /* (long int)VECTOR(indexv)[node]-1, noderank); */ IGRAPH_ALLOW_INTERRUPTION(); neis1 = igraph_lazy_adjlist_get(&adjlist, (igraph_integer_t) node); neilen1 = igraph_vector_size(neis1); for (i = 0; i < neilen1; i++) { long int nei = (long int) VECTOR(*neis1)[i]; neis[nei] = node + 1; } for (i = 0; i < neilen1; i++) { long int nei = (long int) VECTOR(*neis1)[i]; long int neiindex = (long int) VECTOR(indexv)[nei]; long int neirank = (long int) VECTOR(rank)[neiindex - 1]; /* fprintf(stderr, " nei %li (indexv %li, rank %li)\n", nei, */ /* neiindex, neirank); */ if (neirank > noderank) { neis2 = igraph_lazy_adjlist_get(&adjlist, (igraph_integer_t) nei); neilen2 = igraph_vector_size(neis2); for (j = 0; j < neilen2; j++) { long int nei2 = (long int) VECTOR(*neis2)[j]; long int nei2index = (long int) VECTOR(indexv)[nei2]; long int nei2rank = (long int) VECTOR(rank)[nei2index - 1]; /* fprintf(stderr, " triple %li %li %li\n", node, nei, nei2); */ if (nei2rank < neirank) { continue; } if (neis[nei2] == node + 1) { /* fprintf(stderr, " triangle\n"); */ VECTOR(triangles) [ nei2index - 1 ] += 1; VECTOR(triangles) [ neiindex - 1 ] += 1; VECTOR(triangles) [ nodeindex - 1 ] += 1; } } } } } /* Ok, for all affected vertices the number of triangles were counted */ IGRAPH_CHECK(igraph_vector_resize(res, nodes_to_calc)); IGRAPH_VIT_RESET(vit); for (i = 0; i < nodes_to_calc; i++, IGRAPH_VIT_NEXT(vit)) { long int node = IGRAPH_VIT_GET(vit); long int idx = (long int) VECTOR(indexv)[node] - 1; igraph_vector_t *neis2 = igraph_lazy_adjlist_get(&adjlist, (igraph_integer_t) node); long int deg = igraph_vector_size(neis2); if (mode == IGRAPH_TRANSITIVITY_ZERO && deg < 2) { VECTOR(*res)[i] = 0.0; } else { VECTOR(*res)[i] = VECTOR(triangles)[idx] / deg / (deg - 1) * 2.0; } /* fprintf(stderr, "%f %f\n", VECTOR(triangles)[idx], triples); */ } igraph_vector_destroy(&triangles); igraph_free(neis); igraph_vector_destroy(&rank); igraph_vector_destroy(&order); igraph_vector_destroy(&avids); igraph_vector_destroy(&indexv); igraph_lazy_adjlist_destroy(&adjlist); igraph_vit_destroy(&vit); IGRAPH_FINALLY_CLEAN(8); return 0; } /* We don't use this, it is theoretically good, but practically not. */ /* int igraph_transitivity_local_undirected3(const igraph_t *graph, */ /* igraph_vector_t *res, */ /* const igraph_vs_t vids) { */ /* igraph_vit_t vit; */ /* long int nodes_to_calc; */ /* igraph_lazy_adjlist_t adjlist; */ /* long int i, j; */ /* IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit)); */ /* IGRAPH_FINALLY(igraph_vit_destroy, &vit); */ /* nodes_to_calc=IGRAPH_VIT_SIZE(vit); */ /* IGRAPH_CHECK(igraph_lazy_adjlist_init(graph, &adjlist, IGRAPH_ALL, */ /* IGRAPH_SIMPLIFY)); */ /* IGRAPH_FINALLY(igraph_lazy_adjlist_destroy, &adjlist); */ /* IGRAPH_CHECK(igraph_vector_resize(res, nodes_to_calc)); */ /* for (i=0, IGRAPH_VIT_RESET(vit); !IGRAPH_VIT_END(vit); */ /* i++, IGRAPH_VIT_NEXT(vit)) { */ /* long int node=IGRAPH_VIT_GET(vit); */ /* igraph_vector_t *neis=igraph_lazy_adjlist_get(&adjlist, node); */ /* long int n1=igraph_vector_size(neis); */ /* igraph_real_t triangles=0; */ /* igraph_real_t triples=(double)n1*(n1-1); */ /* IGRAPH_ALLOW_INTERRUPTION(); */ /* for (j=0; j nei2) { */ /* l2++; */ /* } else { */ /* triangles+=1; */ /* l1++; l2++; */ /* } */ /* } */ /* } */ /* /\* We're done with 'node' *\/ */ /* VECTOR(*res)[i] = triangles / triples; */ /* } */ /* igraph_lazy_adjlist_destroy(&adjlist); */ /* igraph_vit_destroy(&vit); */ /* IGRAPH_FINALLY_CLEAN(2); */ /* return 0; */ /* } */ /* This removes loop, multiple edges and edges that point "backwards" according to the rank vector. */ int igraph_i_trans4_al_simplify(igraph_adjlist_t *al, const igraph_vector_int_t *rank) { long int i; long int n = al->length; igraph_vector_int_t mark; igraph_vector_int_init(&mark, n); IGRAPH_FINALLY(igraph_vector_int_destroy, &mark); for (i = 0; i < n; i++) { igraph_vector_int_t *v = &al->adjs[i]; int j, l = igraph_vector_int_size(v); int irank = VECTOR(*rank)[i]; VECTOR(mark)[i] = i + 1; for (j = 0; j < l; /* nothing */) { long int e = (long int) VECTOR(*v)[j]; if (VECTOR(*rank)[e] > irank && VECTOR(mark)[e] != i + 1) { VECTOR(mark)[e] = i + 1; j++; } else { VECTOR(*v)[j] = igraph_vector_int_tail(v); igraph_vector_int_pop_back(v); l--; } } } igraph_vector_int_destroy(&mark); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_transitivity_local_undirected4(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, igraph_transitivity_mode_t mode) { #define TRANSIT 1 #include "triangles_template.h" #undef TRANSIT return 0; } /** * \function igraph_transitivity_local_undirected * \brief Calculates the local transitivity (clustering coefficient) of a graph. * * The transitivity measures the probability that two neighbors of a * vertex are connected. In case of the local transitivity, this * probability is calculated separately for each vertex. * * * Note that this measure is different from the global transitivity measure * (see \ref igraph_transitivity_undirected() ) as it calculates a transitivity * value for each vertex individually. See the following reference for more * details: * * * D. J. Watts and S. Strogatz: Collective dynamics of small-world networks. * Nature 393(6684):440-442 (1998). * * * Clustering coefficient is an alternative name for transitivity. * * \param graph The input graph, which should be undirected and simple. * \param res Pointer to an initialized vector, the result will be * stored here. It will be resized as needed. * \param vids Vertex set, the vertices for which the local * transitivity will be calculated. * \param mode Defines how to treat vertices with degree less than two. * \c IGRAPH_TRANSITIVITY_NAN returns \c NaN for these vertices, * \c IGRAPH_TRANSITIVITY_ZERO returns zero. * \return Error code. * * \sa \ref igraph_transitivity_undirected(), \ref * igraph_transitivity_avglocal_undirected(). * * Time complexity: O(n*d^2), n is the number of vertices for which * the transitivity is calculated, d is the average vertex degree. */ int igraph_transitivity_local_undirected(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, igraph_transitivity_mode_t mode) { igraph_bool_t simple; if (igraph_is_directed(graph)) { IGRAPH_ERROR("Transitivity works on undirected graphs only", IGRAPH_EINVAL); } igraph_is_simple(graph, &simple); if (!simple) { IGRAPH_ERROR("Transitivity works on simple graphs only", IGRAPH_EINVAL); } if (igraph_vs_is_all(&vids)) { return igraph_transitivity_local_undirected4(graph, res, vids, mode); } else { igraph_vit_t vit; long int size; IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); size = IGRAPH_VIT_SIZE(vit); igraph_vit_destroy(&vit); IGRAPH_FINALLY_CLEAN(1); if (size < 100) { return igraph_transitivity_local_undirected1(graph, res, vids, mode); } else { return igraph_transitivity_local_undirected2(graph, res, vids, mode); } } return 0; } int igraph_adjacent_triangles1(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids) { # include "triangles_template1.h" return 0; } int igraph_adjacent_triangles4(const igraph_t *graph, igraph_vector_t *res) { # include "triangles_template.h" return 0; } /** * \function igraph_adjacent_triangles * Count the number of triangles a vertex is part of * * \param graph The input graph. Edge directions are ignored. * \param res Initiliazed vector, the results are stored here. * \param vids The vertices to perform the calculation for. * \return Error mode. * * \sa \ref igraph_list_triangles() to list them. * * Time complexity: O(d^2 n), d is the average vertex degree of the * queried vertices, n is their number. */ int igraph_adjacent_triangles(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids) { if (igraph_vs_is_all(&vids)) { return igraph_adjacent_triangles4(graph, res); } else { return igraph_adjacent_triangles1(graph, res, vids); } return 0; } /** * \function igraph_list_triangles * Find all triangles in a graph * * \param graph The input graph, edge directions are ignored. * \param res Pointer to an initialized integer vector, the result * is stored here, in a long list of triples of vertex ids. * Each triple is a triangle in the graph. Each triangle is * listed exactly once. * \return Error code. * * \sa \ref igraph_transitivity_undirected() to count the triangles, * \ref igraph_adjacent_triangles() to count the triangles a vertex * participates in. * * Time complexity: O(d^2 n), d is the average degree, n is the number * of vertices. */ int igraph_list_triangles(const igraph_t *graph, igraph_vector_int_t *res) { # define TRIANGLES # include "triangles_template.h" # undef TRIANGLES return 0; } /** * \ingroup structural * \function igraph_transitivity_undirected * \brief Calculates the transitivity (clustering coefficient) of a graph. * * * The transitivity measures the probability that two neighbors of a * vertex are connected. More precisely, this is the ratio of the * triangles and connected triples in the graph, the result is a * single real number. Directed graphs are considered as undirected ones. * * * Note that this measure is different from the local transitivity measure * (see \ref igraph_transitivity_local_undirected() ) as it calculates a single * value for the whole graph. See the following reference for more details: * * * S. Wasserman and K. Faust: Social Network Analysis: Methods and * Applications. Cambridge: Cambridge University Press, 1994. * * * Clustering coefficient is an alternative name for transitivity. * * \param graph The graph object. * \param res Pointer to a real variable, the result will be stored here. * \param mode Defines how to treat graphs with no connected triples. * \c IGRAPH_TRANSITIVITY_NAN returns \c NaN in this case, * \c IGRAPH_TRANSITIVITY_ZERO returns zero. * \return Error code: * \c IGRAPH_ENOMEM: not enough memory for * temporary data. * * \sa \ref igraph_transitivity_local_undirected(), * \ref igraph_transitivity_avglocal_undirected(). * * Time complexity: O(|V|*d^2), |V| is the number of vertices in * the graph, d is the average node degree. * * \example examples/simple/igraph_transitivity.c */ int igraph_transitivity_undirected(const igraph_t *graph, igraph_real_t *res, igraph_transitivity_mode_t mode) { long int no_of_nodes = igraph_vcount(graph); igraph_real_t triples = 0, triangles = 0; long int node, nn; long int maxdegree; long int *neis; igraph_vector_t order; igraph_vector_t rank; igraph_vector_t degree; igraph_adjlist_t allneis; igraph_vector_int_t *neis1, *neis2; long int i, j, neilen1, neilen2; IGRAPH_VECTOR_INIT_FINALLY(&order, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(°ree, no_of_nodes); IGRAPH_CHECK(igraph_degree(graph, °ree, igraph_vss_all(), IGRAPH_ALL, IGRAPH_LOOPS)); maxdegree = (long int) igraph_vector_max(°ree) + 1; igraph_vector_order1(°ree, &order, maxdegree); igraph_vector_destroy(°ree); IGRAPH_FINALLY_CLEAN(1); IGRAPH_VECTOR_INIT_FINALLY(&rank, no_of_nodes); for (i = 0; i < no_of_nodes; i++) { VECTOR(rank)[ (long int) VECTOR(order)[i] ] = no_of_nodes - i - 1; } IGRAPH_CHECK(igraph_adjlist_init(graph, &allneis, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_adjlist_destroy, &allneis); IGRAPH_CHECK(igraph_adjlist_simplify(&allneis)); neis = igraph_Calloc(no_of_nodes, long int); if (neis == 0) { IGRAPH_ERROR("undirected transitivity failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, neis); for (nn = no_of_nodes - 1; nn >= 0; nn--) { node = (long int) VECTOR(order)[nn]; IGRAPH_ALLOW_INTERRUPTION(); neis1 = igraph_adjlist_get(&allneis, node); neilen1 = igraph_vector_int_size(neis1); triples += (double)neilen1 * (neilen1 - 1); /* Mark the neighbors of 'node' */ for (i = 0; i < neilen1; i++) { long int nei = (long int) VECTOR(*neis1)[i]; neis[nei] = node + 1; } for (i = 0; i < neilen1; i++) { long int nei = (long int) VECTOR(*neis1)[i]; /* If 'nei' is not ready yet */ if (VECTOR(rank)[nei] > VECTOR(rank)[node]) { neis2 = igraph_adjlist_get(&allneis, nei); neilen2 = igraph_vector_int_size(neis2); for (j = 0; j < neilen2; j++) { long int nei2 = (long int) VECTOR(*neis2)[j]; if (neis[nei2] == node + 1) { triangles += 1.0; } } } } } igraph_Free(neis); igraph_adjlist_destroy(&allneis); igraph_vector_destroy(&rank); igraph_vector_destroy(&order); IGRAPH_FINALLY_CLEAN(4); if (triples == 0 && mode == IGRAPH_TRANSITIVITY_ZERO) { *res = 0; } else { *res = triangles / triples * 2.0; } return 0; } int igraph_transitivity_barrat1(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, const igraph_vector_t *weights, igraph_transitivity_mode_t mode); int igraph_transitivity_barrat4(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, const igraph_vector_t *weights, igraph_transitivity_mode_t mode); int igraph_transitivity_barrat1(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, const igraph_vector_t *weights, igraph_transitivity_mode_t mode) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_vit_t vit; long int nodes_to_calc; igraph_vector_t *adj1, *adj2; igraph_vector_long_t neis; igraph_vector_t actw; igraph_lazy_inclist_t incident; long int i; igraph_vector_t strength; if (!weights) { IGRAPH_WARNING("No weights given for Barrat's transitivity, unweighted version is used"); return igraph_transitivity_local_undirected(graph, res, vids, mode); } if (igraph_vector_size(weights) != no_of_edges) { IGRAPH_ERROR("Invalid edge weight vector length", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); nodes_to_calc = IGRAPH_VIT_SIZE(vit); IGRAPH_CHECK(igraph_vector_long_init(&neis, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_long_destroy, &neis); IGRAPH_VECTOR_INIT_FINALLY(&actw, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&strength, 0); IGRAPH_CHECK(igraph_strength(graph, &strength, igraph_vss_all(), IGRAPH_ALL, IGRAPH_LOOPS, weights)); igraph_lazy_inclist_init(graph, &incident, IGRAPH_ALL); IGRAPH_FINALLY(igraph_lazy_inclist_destroy, &incident); IGRAPH_CHECK(igraph_vector_resize(res, nodes_to_calc)); for (i = 0; !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit), i++) { long int node = IGRAPH_VIT_GET(vit); long int adjlen1, adjlen2, j, k; igraph_real_t triples, triangles; IGRAPH_ALLOW_INTERRUPTION(); adj1 = igraph_lazy_inclist_get(&incident, (igraph_integer_t) node); adjlen1 = igraph_vector_size(adj1); /* Mark the neighbors of the node */ for (j = 0; j < adjlen1; j++) { long int edge = (long int) VECTOR(*adj1)[j]; long int nei = IGRAPH_OTHER(graph, edge, node); VECTOR(neis)[nei] = i + 1; VECTOR(actw)[nei] = VECTOR(*weights)[edge]; } triples = VECTOR(strength)[node] * (adjlen1 - 1); triangles = 0.0; for (j = 0; j < adjlen1; j++) { long int edge1 = (long int) VECTOR(*adj1)[j]; igraph_real_t weight1 = VECTOR(*weights)[edge1]; long int v = IGRAPH_OTHER(graph, edge1, node); adj2 = igraph_lazy_inclist_get(&incident, (igraph_integer_t) v); adjlen2 = igraph_vector_size(adj2); for (k = 0; k < adjlen2; k++) { long int edge2 = (long int) VECTOR(*adj2)[k]; long int v2 = IGRAPH_OTHER(graph, edge2, v); if (VECTOR(neis)[v2] == i + 1) { triangles += (VECTOR(actw)[v2] + weight1) / 2.0; } } } if (mode == IGRAPH_TRANSITIVITY_ZERO && triples == 0) { VECTOR(*res)[i] = 0.0; } else { VECTOR(*res)[i] = triangles / triples; } } igraph_lazy_inclist_destroy(&incident); igraph_vector_destroy(&strength); igraph_vector_destroy(&actw); igraph_vector_long_destroy(&neis); igraph_vit_destroy(&vit); IGRAPH_FINALLY_CLEAN(5); return 0; } int igraph_transitivity_barrat4(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, const igraph_vector_t *weights, igraph_transitivity_mode_t mode) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_vector_t order, degree, rank; long int maxdegree; igraph_inclist_t incident; igraph_vector_long_t neis; igraph_vector_int_t *adj1, *adj2; igraph_vector_t actw; long int i, nn; if (!weights) { IGRAPH_WARNING("No weights given for Barrat's transitivity, unweighted version is used"); return igraph_transitivity_local_undirected(graph, res, vids, mode); } if (igraph_vector_size(weights) != no_of_edges) { IGRAPH_ERROR("Invalid edge weight vector length", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(&order, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(°ree, no_of_nodes); IGRAPH_CHECK(igraph_degree(graph, °ree, igraph_vss_all(), IGRAPH_ALL, IGRAPH_LOOPS)); maxdegree = (long int) igraph_vector_max(°ree) + 1; IGRAPH_CHECK(igraph_vector_order1(°ree, &order, maxdegree)); IGRAPH_CHECK(igraph_strength(graph, °ree, igraph_vss_all(), IGRAPH_ALL, IGRAPH_LOOPS, weights)); IGRAPH_VECTOR_INIT_FINALLY(&rank, no_of_nodes); for (i = 0; i < no_of_nodes; i++) { VECTOR(rank)[ (long int)VECTOR(order)[i] ] = no_of_nodes - i - 1; } IGRAPH_CHECK(igraph_inclist_init(graph, &incident, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_inclist_destroy, &incident); IGRAPH_CHECK(igraph_vector_long_init(&neis, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_long_destroy, &neis); IGRAPH_VECTOR_INIT_FINALLY(&actw, no_of_nodes); IGRAPH_CHECK(igraph_vector_resize(res, no_of_nodes)); igraph_vector_null(res); for (nn = no_of_nodes - 1; nn >= 0; nn--) { long int adjlen1, adjlen2; igraph_real_t triples; long int node = (long int) VECTOR(order)[nn]; IGRAPH_ALLOW_INTERRUPTION(); adj1 = igraph_inclist_get(&incident, node); adjlen1 = igraph_vector_int_size(adj1); triples = VECTOR(degree)[node] * (adjlen1 - 1) / 2.0; /* Mark the neighbors of the node */ for (i = 0; i < adjlen1; i++) { long int edge = (long int) VECTOR(*adj1)[i]; long int nei = IGRAPH_OTHER(graph, edge, node); VECTOR(neis)[nei] = node + 1; VECTOR(actw)[nei] = VECTOR(*weights)[edge]; } for (i = 0; i < adjlen1; i++) { long int edge1 = (long int) VECTOR(*adj1)[i]; igraph_real_t weight1 = VECTOR(*weights)[edge1]; long int nei = IGRAPH_OTHER(graph, edge1, node); long int j; if (VECTOR(rank)[nei] > VECTOR(rank)[node]) { adj2 = igraph_inclist_get(&incident, nei); adjlen2 = igraph_vector_int_size(adj2); for (j = 0; j < adjlen2; j++) { long int edge2 = (long int) VECTOR(*adj2)[j]; igraph_real_t weight2 = VECTOR(*weights)[edge2]; long int nei2 = IGRAPH_OTHER(graph, edge2, nei); if (VECTOR(rank)[nei2] < VECTOR(rank)[nei]) { continue; } if (VECTOR(neis)[nei2] == node + 1) { VECTOR(*res)[nei2] += (VECTOR(actw)[nei2] + weight2) / 2.0; VECTOR(*res)[nei] += (weight1 + weight2) / 2.0; VECTOR(*res)[node] += (VECTOR(actw)[nei2] + weight1) / 2.0; } } } } if (mode == IGRAPH_TRANSITIVITY_ZERO && triples == 0) { VECTOR(*res)[node] = 0.0; } else { VECTOR(*res)[node] /= triples; } } igraph_vector_destroy(&actw); igraph_vector_long_destroy(&neis); igraph_inclist_destroy(&incident); igraph_vector_destroy(&rank); igraph_vector_destroy(°ree); igraph_vector_destroy(&order); IGRAPH_FINALLY_CLEAN(6); return 0; } /** * \function igraph_transitivity_barrat * Weighted transitivity, as defined by A. Barrat. * * This is a local transitivity, i.e. a vertex-level index. For a * given vertex \c i, from all triangles in which it participates we * consider the weight of the edges incident on \c i. The transitivity * is the sum of these weights divided by twice the strength of the * vertex (see \ref igraph_strength()) and the degree of the vertex * minus one. See Alain Barrat, Marc Barthelemy, Romualdo * Pastor-Satorras, Alessandro Vespignani: The architecture of complex * weighted networks, Proc. Natl. Acad. Sci. USA 101, 3747 (2004) at * http://arxiv.org/abs/cond-mat/0311416 for the exact formula. * * \param graph The input graph, edge directions are ignored for * directed graphs. Note that the function does NOT work for * non-simple graphs. * \param res Pointer to an initialized vector, the result will be * stored here. It will be resized as needed. * \param vids The vertices for which the calculation is performed. * \param weights Edge weights. If this is a null pointer, then a * warning is given and \ref igraph_transitivity_local_undirected() * is called. * \param mode Defines how to treat vertices with zero strength. * \c IGRAPH_TRANSITIVITY_NAN says that the transitivity of these * vertices is \c NaN, \c IGRAPH_TRANSITIVITY_ZERO says it is zero. * * \return Error code. * * Time complexity: O(|V|*d^2), |V| is the number of vertices in * the graph, d is the average node degree. * * \sa \ref igraph_transitivity_undirected(), \ref * igraph_transitivity_local_undirected() and \ref * igraph_transitivity_avglocal_undirected() for other kinds of * (non-weighted) transitivity. */ int igraph_transitivity_barrat(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, const igraph_vector_t *weights, igraph_transitivity_mode_t mode) { if (igraph_vs_is_all(&vids)) { return igraph_transitivity_barrat4(graph, res, vids, weights, mode); } else { return igraph_transitivity_barrat1(graph, res, vids, weights, mode); } return 0; } python-igraph-0.8.0/vendor/source/igraph/src/maximal_cliques_template.h0000644000076500000240000003343413614300625026626 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2013 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifdef IGRAPH_MC_ORIG #define RESTYPE igraph_vector_ptr_t *res #define RESNAME res #define SUFFIX #define RECORD do { \ igraph_vector_t *cl=igraph_Calloc(1, igraph_vector_t); \ int j; \ if (!cl) { \ IGRAPH_ERROR("Cannot list maximal cliques", IGRAPH_ENOMEM); \ } \ IGRAPH_CHECK(igraph_vector_ptr_push_back(res, cl)); \ IGRAPH_CHECK(igraph_vector_init(cl, clsize)); \ for (j=0; j hsize) { \ long hcapacity = igraph_vector_capacity(hist); \ long j; \ int err; \ if (hcapacity < clsize && clsize < 2*hcapacity) \ err = igraph_vector_reserve(hist, 2*hcapacity); \ err = igraph_vector_resize(hist, clsize); \ if (err != IGRAPH_SUCCESS) \ IGRAPH_ERROR("Cannot count maximal cliques", IGRAPH_ENOMEM); \ for (j=hsize; j < clsize; j++) \ VECTOR(*hist)[j] = 0; \ } \ VECTOR(*hist)[clsize-1] += 1; \ } while (0) #define FINALLY \ igraph_vector_clear(hist); \ igraph_vector_reserve(hist, 50); /* initially reserve space for 50 elements */ #define FOR_LOOP_OVER_VERTICES for (i=0; i PE && XS > XE) { /* Found a maximum clique, report it */ int clsize = igraph_vector_int_size(R); if (min_size <= clsize && (clsize <= max_size || max_size <= 0)) { RECORD; } } else if (PS <= PE) { /* Select a pivot element */ int pivot, mynextv; igraph_i_maximal_cliques_select_pivot(PX, PS, PE, XS, XE, pos, adjlist, &pivot, nextv, oldPS, oldXE); while ((mynextv = igraph_vector_int_pop_back(nextv)) != -1) { int newPS, newXE; /* Going down, prepare */ igraph_i_maximal_cliques_down(PX, PS, PE, XS, XE, pos, adjlist, mynextv, R, &newPS, &newXE); /* Recursive call */ err = FUNCTION(igraph_i_maximal_cliques_bk, SUFFIX)( PX, newPS, PE, XS, newXE, PS, XE, R, pos, adjlist, RESNAME, nextv, H, min_size, max_size); if (err == IGRAPH_STOP) { return err; } else { IGRAPH_CHECK(err); } /* Putting v from P to X */ if (igraph_vector_int_tail(nextv) != -1) { igraph_i_maximal_cliques_PX(PX, PS, &PE, &XS, XE, pos, adjlist, mynextv, H); } } } /* Putting back vertices from X to P, see notes in H */ igraph_i_maximal_cliques_up(PX, PS, PE, XS, XE, pos, adjlist, R, H); return 0; } int FUNCTION(igraph_maximal_cliques, SUFFIX)( const igraph_t *graph, RESTYPE, igraph_integer_t min_size, igraph_integer_t max_size) { /* Implementation details. TODO */ igraph_vector_int_t PX, R, H, pos, nextv; igraph_vector_t coreness, order; igraph_vector_int_t rank; /* TODO: this is not needed */ int i, ii, nn, no_of_nodes = igraph_vcount(graph); igraph_adjlist_t adjlist, fulladjlist; igraph_real_t pgreset = round(no_of_nodes / 100.0), pg = pgreset, pgc = 0; int err; IGRAPH_UNUSED(nn); if (igraph_is_directed(graph)) { IGRAPH_WARNING("Edge directions are ignored for maximal clique " "calculation"); } igraph_vector_init(&order, no_of_nodes); IGRAPH_FINALLY(igraph_vector_destroy, &order); igraph_vector_int_init(&rank, no_of_nodes); IGRAPH_FINALLY(igraph_vector_int_destroy, &rank); igraph_vector_init(&coreness, no_of_nodes); igraph_coreness(graph, &coreness, /*mode=*/ IGRAPH_ALL); IGRAPH_FINALLY(igraph_vector_destroy, &coreness); igraph_vector_qsort_ind(&coreness, &order, /*descending=*/ 0); for (ii = 0; ii < no_of_nodes; ii++) { int v = VECTOR(order)[ii]; VECTOR(rank)[v] = ii; } igraph_vector_destroy(&coreness); IGRAPH_FINALLY_CLEAN(1); igraph_adjlist_init(graph, &adjlist, IGRAPH_ALL); igraph_adjlist_simplify(&adjlist); igraph_adjlist_init(graph, &fulladjlist, IGRAPH_ALL); IGRAPH_FINALLY(igraph_adjlist_destroy, &fulladjlist); igraph_adjlist_simplify(&fulladjlist); igraph_vector_int_init(&PX, 20); IGRAPH_FINALLY(igraph_vector_int_destroy, &PX); igraph_vector_int_init(&R, 20); IGRAPH_FINALLY(igraph_vector_int_destroy, &R); igraph_vector_int_init(&H, 100); IGRAPH_FINALLY(igraph_vector_int_destroy, &H); igraph_vector_int_init(&pos, no_of_nodes); IGRAPH_FINALLY(igraph_vector_int_destroy, &pos); igraph_vector_int_init(&nextv, 100); IGRAPH_FINALLY(igraph_vector_int_destroy, &nextv); FINALLY; FOR_LOOP_OVER_VERTICES int v; int vrank; igraph_vector_int_t *vneis; int vdeg; int Pptr, Xptr, PS, PE, XS, XE; int j; FOR_LOOP_OVER_VERTICES_PREPARE; v = VECTOR(order)[i]; vrank = VECTOR(rank)[v]; vneis = igraph_adjlist_get(&fulladjlist, v); vdeg = igraph_vector_int_size(vneis); Pptr = 0; Xptr = vdeg - 1; PS = 0; XE = vdeg - 1; pg--; if (pg <= 0) { IGRAPH_PROGRESS("Maximal cliques: ", pgc++, NULL); pg = pgreset; } IGRAPH_ALLOW_INTERRUPTION(); igraph_vector_int_resize(&PX, vdeg); igraph_vector_int_resize(&R, 1); igraph_vector_int_resize(&H, 1); igraph_vector_int_null(&pos); /* TODO: makes it quadratic? */ igraph_vector_int_resize(&nextv, 1); VECTOR(H)[0] = -1; /* marks the end of the recursion */ VECTOR(nextv)[0] = -1; /* ================================================================*/ /* P <- G(v[i]) intersect { v[i+1], ..., v[n-1] } X <- G(v[i]) intersect { v[0], ..., v[i-1] } */ VECTOR(R)[0] = v; for (j = 0; j < vdeg; j++) { int vx = VECTOR(*vneis)[j]; if (VECTOR(rank)[vx] > vrank) { VECTOR(PX)[Pptr] = vx; VECTOR(pos)[vx] = Pptr + 1; Pptr++; } else if (VECTOR(rank)[vx] < vrank) { VECTOR(PX)[Xptr] = vx; VECTOR(pos)[vx] = Xptr + 1; Xptr--; } } PE = Pptr - 1; XS = Xptr + 1; /* end of P, start of X in PX */ /* Create an adjacency list that is specific to the v vertex. It only contains 'v' and its neighbors. Moreover, we only deal with the vertices in P and X (and R). */ igraph_vector_int_update(igraph_adjlist_get(&adjlist, v), igraph_adjlist_get(&fulladjlist, v)); for (j = 0; j <= vdeg - 1; j++) { int vv = VECTOR(PX)[j]; igraph_vector_int_t *fadj = igraph_adjlist_get(&fulladjlist, vv); igraph_vector_int_t *radj = igraph_adjlist_get(&adjlist, vv); int k, fn = igraph_vector_int_size(fadj); igraph_vector_int_clear(radj); for (k = 0; k < fn; k++) { int nei = VECTOR(*fadj)[k]; int neipos = VECTOR(pos)[nei] - 1; if (neipos >= PS && neipos <= XE) { igraph_vector_int_push_back(radj, nei); } } } /* Reorder the adjacency lists, according to P and X. */ igraph_i_maximal_cliques_reorder_adjlists(&PX, PS, PE, XS, XE, &pos, &adjlist); err = FUNCTION(igraph_i_maximal_cliques_bk, SUFFIX)( &PX, PS, PE, XS, XE, PS, XE, &R, &pos, &adjlist, RESNAME, &nextv, &H, min_size, max_size); if (err == IGRAPH_STOP) { break; } else { IGRAPH_CHECK(err); } } IGRAPH_PROGRESS("Maximal cliques: ", 100.0, NULL); igraph_vector_int_destroy(&nextv); igraph_vector_int_destroy(&pos); igraph_vector_int_destroy(&H); igraph_vector_int_destroy(&R); igraph_vector_int_destroy(&PX); igraph_adjlist_destroy(&fulladjlist); igraph_adjlist_destroy(&adjlist); igraph_vector_int_destroy(&rank); igraph_vector_destroy(&order); IGRAPH_FINALLY_CLEAN(10); /* + res */ return 0; } #undef RESTYPE #undef RESNAME #undef SUFFIX #undef RECORD #undef FINALLY #undef FOR_LOOP_OVER_VERTICES #undef FOR_LOOP_OVER_VERTICES_PREPARE python-igraph-0.8.0/vendor/source/igraph/src/random.c0000644000076500000240000022241713614300625023032 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2005-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_random.h" #include "igraph_error.h" #include "config.h" #include #include #include #include "igraph_math.h" #include "igraph_types.h" #include "igraph_vector.h" #include "igraph_memory.h" #include "igraph_matrix.h" /** * \section about_rngs * *
* About random numbers in igraph, use cases * * * Some algorithms in igraph, e.g. the generation of random graphs, * require random number generators (RNGs). Prior to version 0.6 * igraph did not have a sophisticated way to deal with random number * generators at the C level, but this has changed. From version 0.6 * different and multiple random number generators are supported. * *
* */ /** * \section rng_use_cases * *
Use cases * *
Normal (default) use * * If the user does not use any of the RNG functions explicitly, but calls * some of the randomized igraph functions, then a default RNG is set * up the first time an igraph function needs random numbers. The * seed of this RNG is the output of the time(0) function * call, using the time function from the standard C * library. This ensures that igraph creates a different random graph, * each time the C program is called. * * * * The created default generator is stored internally and can be * queried with the \ref igraph_rng_default() function. * *
* *
Reproducible simulations * * If reproducible results are needed, then the user should set the * seed of the default random number generator explicitly, using the * \ref igraph_rng_seed() function on the default generator, \ref * igraph_rng_default(). When setting the seed to the same number, * igraph generates exactly the same random graph (or series of random * graphs). * *
* *
Changing the default generator * * By default igraph uses the \ref igraph_rng_default() random number * generator. This can be changed any time by calling \ref * igraph_rng_set_default(), with an already initialized random number * generator. Note that the old (replaced) generator is not * destroyed, so no memory is deallocated. * *
* *
Using multiple generators * * igraph also provides functions to set up multiple random number * generators, using the \ref igraph_rng_init() function, and then * generating random numbers from them, e.g. with \ref igraph_rng_get_integer() * and/or \ref igraph_rng_get_unif() calls. * * * * Note that initializing a new random number generator is * independent of the generator that the igraph functions themselves * use. If you want to replace that, then please use \ref * igraph_rng_set_default(). * *
* *
Example * * \example examples/simple/random_seed.c * *
* *
*/ /* ------------------------------------ */ typedef struct { int i, j; long int x[31]; } igraph_i_rng_glibc2_state_t; unsigned long int igraph_i_rng_glibc2_get(int *i, int *j, int n, long int *x) { unsigned long int k; x[*i] += x[*j]; k = (x[*i] >> 1) & 0x7FFFFFFF; (*i)++; if (*i == n) { *i = 0; } (*j)++ ; if (*j == n) { *j = 0; } return k; } unsigned long int igraph_rng_glibc2_get(void *vstate) { igraph_i_rng_glibc2_state_t *state = (igraph_i_rng_glibc2_state_t*) vstate; return igraph_i_rng_glibc2_get(&state->i, &state->j, 31, state->x); } igraph_real_t igraph_rng_glibc2_get_real(void *state) { return igraph_rng_glibc2_get(state) / 2147483648.0; } /* this function is independent of the bit size */ void igraph_i_rng_glibc2_init(long int *x, int n, unsigned long int s) { int i; if (s == 0) { s = 1; } x[0] = (long) s; for (i = 1 ; i < n ; i++) { const long int h = s / 127773; const long int t = 16807 * ((long) s - h * 127773) - h * 2836; if (t < 0) { s = (unsigned long) t + 2147483647 ; } else { s = (unsigned long) t ; } x[i] = (long int) s ; } } int igraph_rng_glibc2_seed(void *vstate, unsigned long int seed) { igraph_i_rng_glibc2_state_t *state = (igraph_i_rng_glibc2_state_t*) vstate; int i; igraph_i_rng_glibc2_init(state->x, 31, seed); state->i = 3; state->j = 0; for (i = 0; i < 10 * 31; i++) { igraph_rng_glibc2_get(state); } return 0; } int igraph_rng_glibc2_init(void **state) { igraph_i_rng_glibc2_state_t *st; st = igraph_Calloc(1, igraph_i_rng_glibc2_state_t); if (!st) { IGRAPH_ERROR("Cannot initialize RNG", IGRAPH_ENOMEM); } (*state) = st; igraph_rng_glibc2_seed(st, 0); return 0; } void igraph_rng_glibc2_destroy(void *vstate) { igraph_i_rng_glibc2_state_t *state = (igraph_i_rng_glibc2_state_t*) vstate; igraph_Free(state); } /** * \var igraph_rngtype_glibc2 * \brief The random number generator type introduced in GNU libc 2 * * It is a linear feedback shift register generator with a 128-byte * buffer. This generator was the default prior to igraph version 0.6, * at least on systems relying on GNU libc. * * This generator was ported from the GNU Scientific Library. */ const igraph_rng_type_t igraph_rngtype_glibc2 = { /* name= */ "LIBC", /* min= */ 0, /* max= */ RAND_MAX, /* init= */ igraph_rng_glibc2_init, /* destroy= */ igraph_rng_glibc2_destroy, /* seed= */ igraph_rng_glibc2_seed, /* get= */ igraph_rng_glibc2_get, /* get_real= */ igraph_rng_glibc2_get_real, /* get_norm= */ 0, /* get_geom= */ 0, /* get_binom= */ 0, /* get_exp= */ 0, /* get_gamma= */ 0 }; /* ------------------------------------ */ typedef struct { unsigned long int x; } igraph_i_rng_rand_state_t; unsigned long int igraph_rng_rand_get(void *vstate) { igraph_i_rng_rand_state_t *state = vstate; state->x = (1103515245 * state->x + 12345) & 0x7fffffffUL; return state->x; } igraph_real_t igraph_rng_rand_get_real(void *vstate) { return igraph_rng_rand_get (vstate) / 2147483648.0 ; } int igraph_rng_rand_seed(void *vstate, unsigned long int seed) { igraph_i_rng_rand_state_t *state = vstate; state->x = seed; return 0; } int igraph_rng_rand_init(void **state) { igraph_i_rng_rand_state_t *st; st = igraph_Calloc(1, igraph_i_rng_rand_state_t); if (!st) { IGRAPH_ERROR("Cannot initialize RNG", IGRAPH_ENOMEM); } (*state) = st; igraph_rng_rand_seed(st, 0); return 0; } void igraph_rng_rand_destroy(void *vstate) { igraph_i_rng_rand_state_t *state = (igraph_i_rng_rand_state_t*) vstate; igraph_Free(state); } /** * \var igraph_rngtype_rand * \brief The old BSD rand/stand random number generator * * The sequence is * x_{n+1} = (a x_n + c) mod m * with a = 1103515245, c = 12345 and m = 2^31 = 2147483648. The seed * specifies the initial value, x_1. * * The theoretical value of x_{10001} is 1910041713. * * The period of this generator is 2^31. * * This generator is not very good -- the low bits of successive * numbers are correlated. * * This generator was ported from the GNU Scientific Library. */ const igraph_rng_type_t igraph_rngtype_rand = { /* name= */ "RAND", /* min= */ 0, /* max= */ 0x7fffffffUL, /* init= */ igraph_rng_rand_init, /* destroy= */ igraph_rng_rand_destroy, /* seed= */ igraph_rng_rand_seed, /* get= */ igraph_rng_rand_get, /* get_real= */ igraph_rng_rand_get_real, /* get_norm= */ 0, /* get_geom= */ 0, /* get_binom= */ 0, /* get_exp= */ 0, /* get_gamma= */ 0 }; /* ------------------------------------ */ #define N 624 /* Period parameters */ #define M 397 /* most significant w-r bits */ static const unsigned long UPPER_MASK = 0x80000000UL; /* least significant r bits */ static const unsigned long LOWER_MASK = 0x7fffffffUL; typedef struct { unsigned long mt[N]; int mti; } igraph_i_rng_mt19937_state_t; unsigned long int igraph_rng_mt19937_get(void *vstate) { igraph_i_rng_mt19937_state_t *state = vstate; unsigned long k ; unsigned long int *const mt = state->mt; #define MAGIC(y) (((y)&0x1) ? 0x9908b0dfUL : 0) if (state->mti >= N) { /* generate N words at one time */ int kk; for (kk = 0; kk < N - M; kk++) { unsigned long y = (mt[kk] & UPPER_MASK) | (mt[kk + 1] & LOWER_MASK); mt[kk] = mt[kk + M] ^ (y >> 1) ^ MAGIC(y); } for (; kk < N - 1; kk++) { unsigned long y = (mt[kk] & UPPER_MASK) | (mt[kk + 1] & LOWER_MASK); mt[kk] = mt[kk + (M - N)] ^ (y >> 1) ^ MAGIC(y); } { unsigned long y = (mt[N - 1] & UPPER_MASK) | (mt[0] & LOWER_MASK); mt[N - 1] = mt[M - 1] ^ (y >> 1) ^ MAGIC(y); } state->mti = 0; } #undef MAGIC /* Tempering */ k = mt[state->mti]; k ^= (k >> 11); k ^= (k << 7) & 0x9d2c5680UL; k ^= (k << 15) & 0xefc60000UL; k ^= (k >> 18); state->mti++; return k; } igraph_real_t igraph_rng_mt19937_get_real(void *vstate) { return igraph_rng_mt19937_get (vstate) / 4294967296.0 ; } int igraph_rng_mt19937_seed(void *vstate, unsigned long int seed) { igraph_i_rng_mt19937_state_t *state = vstate; int i; memset(state, 0, sizeof(igraph_i_rng_mt19937_state_t)); if (seed == 0) { seed = 4357; /* the default seed is 4357 */ } state->mt[0] = seed & 0xffffffffUL; for (i = 1; i < N; i++) { /* See Knuth's "Art of Computer Programming" Vol. 2, 3rd Ed. p.106 for multiplier. */ state->mt[i] = (1812433253UL * (state->mt[i - 1] ^ (state->mt[i - 1] >> 30)) + (unsigned long) i); state->mt[i] &= 0xffffffffUL; } state->mti = i; return 0; } int igraph_rng_mt19937_init(void **state) { igraph_i_rng_mt19937_state_t *st; st = igraph_Calloc(1, igraph_i_rng_mt19937_state_t); if (!st) { IGRAPH_ERROR("Cannot initialize RNG", IGRAPH_ENOMEM); } (*state) = st; igraph_rng_mt19937_seed(st, 0); return 0; } void igraph_rng_mt19937_destroy(void *vstate) { igraph_i_rng_mt19937_state_t *state = (igraph_i_rng_mt19937_state_t*) vstate; igraph_Free(state); } /** * \var igraph_rngtype_mt19937 * \brief The MT19937 random number generator * * The MT19937 generator of Makoto Matsumoto and Takuji Nishimura is a * variant of the twisted generalized feedback shift-register * algorithm, and is known as the “Mersenne Twister†generator. It has * a Mersenne prime period of 2^19937 - 1 (about 10^6000) and is * equi-distributed in 623 dimensions. It has passed the diehard * statistical tests. It uses 624 words of state per generator and is * comparable in speed to the other generators. The original generator * used a default seed of 4357 and choosing s equal to zero in * gsl_rng_set reproduces this. Later versions switched to 5489 as the * default seed, you can choose this explicitly via igraph_rng_seed * instead if you require it. * * For more information see, * Makoto Matsumoto and Takuji Nishimura, “Mersenne Twister: A * 623-dimensionally equidistributed uniform pseudorandom number * generatorâ€. ACM Transactions on Modeling and Computer Simulation, * Vol. 8, No. 1 (Jan. 1998), Pages 3–30 * * The generator igraph_rngtype_mt19937 uses the second revision of the * seeding procedure published by the two authors above in 2002. The * original seeding procedures could cause spurious artifacts for some * seed values. * * This generator was ported from the GNU Scientific Library. */ const igraph_rng_type_t igraph_rngtype_mt19937 = { /* name= */ "MT19937", /* min= */ 0, /* max= */ 0xffffffffUL, /* init= */ igraph_rng_mt19937_init, /* destroy= */ igraph_rng_mt19937_destroy, /* seed= */ igraph_rng_mt19937_seed, /* get= */ igraph_rng_mt19937_get, /* get_real= */ igraph_rng_mt19937_get_real, /* get_norm= */ 0, /* get_geom= */ 0, /* get_binom= */ 0, /* get_exp= */ 0, /* get_gamma= */ 0 }; #undef N #undef M /* ------------------------------------ */ #ifndef USING_R igraph_i_rng_mt19937_state_t igraph_i_rng_default_state; #define addr(a) (&a) /** * \var igraph_i_rng_default * The default igraph random number generator * * This generator is used by all builtin igraph functions that need to * generate random numbers; e.g. all random graph generators. * * You can use \ref igraph_i_rng_default with \ref igraph_rng_seed() * to set its seed. * * You can change the default generator using the \ref * igraph_rng_set_default() function. */ IGRAPH_THREAD_LOCAL igraph_rng_t igraph_i_rng_default = { addr(igraph_rngtype_mt19937), addr(igraph_i_rng_default_state), /* def= */ 1 }; #undef addr /** * \function igraph_rng_set_default * Set the default igraph random number generator * * \param rng The random number generator to use as default from now * on. Calling \ref igraph_rng_destroy() on it, while it is still * being used as the default will result craches and/or * unpredictable results. * * Time complexity: O(1). */ void igraph_rng_set_default(igraph_rng_t *rng) { igraph_i_rng_default = (*rng); } #endif /* ------------------------------------ */ #ifdef USING_R double unif_rand(void); double norm_rand(void); double exp_rand(void); double Rf_rgeom(double); double Rf_rbinom(double, double); double Rf_rgamma(double, double); int igraph_rng_R_init(void **state) { IGRAPH_ERROR("R RNG error, unsupported function called", IGRAPH_EINTERNAL); return 0; } void igraph_rng_R_destroy(void *state) { igraph_error("R RNG error, unsupported function called", __FILE__, __LINE__, IGRAPH_EINTERNAL); } int igraph_rng_R_seed(void *state, unsigned long int seed) { IGRAPH_ERROR("R RNG error, unsupported function called", IGRAPH_EINTERNAL); return 0; } unsigned long int igraph_rng_R_get(void *state) { return (unsigned long) (unif_rand() * 0x7FFFFFFFUL); } igraph_real_t igraph_rng_R_get_real(void *state) { return unif_rand(); } igraph_real_t igraph_rng_R_get_norm(void *state) { return norm_rand(); } igraph_real_t igraph_rng_R_get_geom(void *state, igraph_real_t p) { return Rf_rgeom(p); } igraph_real_t igraph_rng_R_get_binom(void *state, long int n, igraph_real_t p) { return Rf_rbinom(n, p); } igraph_real_t igraph_rng_R_get_gamma(void *state, igraph_real_t shape, igraph_real_t scale) { return Rf_rgamma(shape, scale); } igraph_real_t igraph_rng_R_get_exp(void *state, igraph_real_t rate) { igraph_real_t scale = 1.0 / rate; if (!IGRAPH_FINITE(scale) || scale <= 0.0) { if (scale == 0.0) { return 0.0; } return IGRAPH_NAN; } return scale * exp_rand(); } igraph_rng_type_t igraph_rngtype_R = { /* name= */ "GNU R", /* min= */ 0, /* max= */ 0x7FFFFFFFUL, /* init= */ igraph_rng_R_init, /* destroy= */ igraph_rng_R_destroy, /* seed= */ igraph_rng_R_seed, /* get= */ igraph_rng_R_get, /* get_real= */ igraph_rng_R_get_real, /* get_norm= */ igraph_rng_R_get_norm, /* get_geom= */ igraph_rng_R_get_geom, /* get_binom= */ igraph_rng_R_get_binom, /* get_exp= */ igraph_rng_R_get_exp }; IGRAPH_THREAD_LOCAL igraph_rng_t igraph_i_rng_default = { &igraph_rngtype_R, 0, /* def= */ 1 }; #endif /* ------------------------------------ */ /** * \function igraph_rng_default * Query the default random number generator. * * \return A pointer to the default random number generator. * * \sa igraph_rng_set_default() */ igraph_rng_t *igraph_rng_default() { return &igraph_i_rng_default; } /* ------------------------------------ */ double igraph_norm_rand(igraph_rng_t *rng); double igraph_rgeom(igraph_rng_t *rng, double p); double igraph_rbinom(igraph_rng_t *rng, double nin, double pp); double igraph_rexp(igraph_rng_t *rng, double rate); double igraph_rgamma(igraph_rng_t *rng, double shape, double scale); /** * \function igraph_rng_init * Initialize a random number generator * * This function allocates memory for a random number generator, with * the given type, and sets its seed to the default. * * \param rng Pointer to an uninitialized RNG. * \param type The type of the RNG, please see the documentation for * the supported types. * \return Error code. * * Time complexity: depends on the type of the generator, but usually * it should be O(1). */ int igraph_rng_init(igraph_rng_t *rng, const igraph_rng_type_t *type) { rng->type = type; IGRAPH_CHECK(rng->type->init(&rng->state)); return 0; } /** * \function igraph_rng_destroy * Deallocate memory associated with a random number generator * * \param rng The RNG to destroy. Do not destroy an RNG that is used * as the default igraph RNG. * * Time complexity: O(1). */ void igraph_rng_destroy(igraph_rng_t *rng) { rng->type->destroy(rng->state); } /** * \function igraph_rng_seed * Set the seed of a random number generator * * \param rng The RNG. * \param seed The new seed. * \return Error code. * * Time complexity: usually O(1), but may depend on the type of the * RNG. */ int igraph_rng_seed(igraph_rng_t *rng, unsigned long int seed) { const igraph_rng_type_t *type = rng->type; rng->def = 0; IGRAPH_CHECK(type->seed(rng->state, seed)); return 0; } /** * \function igraph_rng_max * Query the maximum possible integer for a random number generator * * \param rng The RNG. * \return The largest possible integer that can be generated by * calling \ref igraph_rng_get_integer() on the RNG. * * Time complexity: O(1). */ unsigned long int igraph_rng_max(igraph_rng_t *rng) { const igraph_rng_type_t *type = rng->type; return type->max; } /** * \function igraph_rng_min * Query the minimum possible integer for a random number generator * * \param rng The RNG. * \return The smallest possible integer that can be generated by * calling \ref igraph_rng_get_integer() on the RNG. * * Time complexity: O(1). */ unsigned long int igraph_rng_min(igraph_rng_t *rng) { const igraph_rng_type_t *type = rng->type; return type->min; } /** * \function igraph_rng_name * Query the type of a random number generator * * \param rng The RNG. * \return The name of the type of the generator. Do not deallocate or * change the returned string pointer. * * Time complexity: O(1). */ const char *igraph_rng_name(igraph_rng_t *rng) { const igraph_rng_type_t *type = rng->type; return type->name; } /** * \function igraph_rng_get_integer * Generate an integer random number from an interval * * \param rng Pointer to the RNG to use for the generation. Use \ref * igraph_rng_default() here to use the default igraph RNG. * \param l Lower limit, inclusive, it can be negative as well. * \param h Upper limit, inclusive, it can be negative as well, but it * should be at least l. * \return The generated random integer. * * Time complexity: depends on the generator, but should be usually * O(1). */ long int igraph_rng_get_integer(igraph_rng_t *rng, long int l, long int h) { const igraph_rng_type_t *type = rng->type; if (type->get_real) { return (long int)(type->get_real(rng->state) * (h - l + 1) + l); } else if (type->get) { unsigned long int max = type->max; return (long int)(type->get(rng->state) / ((double)max + 1) * (h - l + 1) + l); } IGRAPH_ERROR("Internal random generator error", IGRAPH_EINTERNAL); return 0; } /** * \function igraph_rng_get_normal * Normally distributed random numbers * * \param rng Pointer to the RNG to use. Use \ref igraph_rng_default() * here to use the default igraph RNG. * \param m The mean. * \param s Standard deviation. * \return The generated normally distributed random number. * * Time complexity: depends on the type of the RNG. */ igraph_real_t igraph_rng_get_normal(igraph_rng_t *rng, igraph_real_t m, igraph_real_t s) { const igraph_rng_type_t *type = rng->type; if (type->get_norm) { return type->get_norm(rng->state) * s + m; } else { return igraph_norm_rand(rng) * s + m; } } /** * \function igraph_rng_get_unif * Generate real, uniform random numbers from an interval * * \param rng Pointer to the RNG to use. Use \ref igraph_rng_default() * here to use the default igraph RNG. * \param l The lower bound, it can be negative. * \param h The upper bound, it can be negative, but it has to be * larger than the lower bound. * \return The generated uniformly distributed random number. * * Time complexity: depends on the type of the RNG. */ igraph_real_t igraph_rng_get_unif(igraph_rng_t *rng, igraph_real_t l, igraph_real_t h) { const igraph_rng_type_t *type = rng->type; if (type->get_real) { return type->get_real(rng->state) * (h - l) + l; } else if (type->get) { unsigned long int max = type->max; return type->get(rng->state) / ((double)max + 1) * (double)(h - l) + l; } IGRAPH_ERROR("Internal random generator error", IGRAPH_EINTERNAL); return 0; } /** * \function igraph_rng_get_unif01 * Generate real, uniform random number from the unit interval * * \param rng Pointer to the RNG to use. Use \ref igraph_rng_default() * here to use the default igraph RNG. * \return The generated uniformly distributed random number. * * Time complexity: depends on the type of the RNG. */ igraph_real_t igraph_rng_get_unif01(igraph_rng_t *rng) { const igraph_rng_type_t *type = rng->type; if (type->get_real) { return type->get_real(rng->state); } else if (type->get) { unsigned long int max = type->max; return type->get(rng->state) / ((double)max + 1); } IGRAPH_ERROR("Internal random generator error", IGRAPH_EINTERNAL); return 0; } /** * \function igraph_rng_get_geom * Generate geometrically distributed random numbers * * \param rng Pointer to the RNG to use. Use \ref igraph_rng_default() * here to use the default igraph RNG. * \param p The probability of success in each trial. Must be larger * than zero and smaller or equal to 1. * \return The generated geometrically distributed random number. * * Time complexity: depends on the type of the RNG. */ igraph_real_t igraph_rng_get_geom(igraph_rng_t *rng, igraph_real_t p) { const igraph_rng_type_t *type = rng->type; if (type->get_geom) { return type->get_geom(rng->state, p); } else { return igraph_rgeom(rng, p); } } /** * \function igraph_rng_get_binom * Generate binomially distributed random numbers * * \param rng Pointer to the RNG to use. Use \ref igraph_rng_default() * here to use the default igraph RNG. * \param n Number of observations. * \param p Probability of an event. * \return The generated binomially distributed random number. * * Time complexity: depends on the type of the RNG. */ igraph_real_t igraph_rng_get_binom(igraph_rng_t *rng, long int n, igraph_real_t p) { const igraph_rng_type_t *type = rng->type; if (type->get_binom) { return type->get_binom(rng->state, n, p); } else { return igraph_rbinom(rng, n, p); } } /** * \function igraph_rng_get_gamma * Generate sample from a Gamma distribution * * \param rng Pointer to the RNG to use. Use \ref igraph_rng_default() * here to use the default igraph RNG. * \param shape Shape parameter. * \param scale Scale parameter. * \return The generated sample * * Time complexity: depends on RNG. */ igraph_real_t igraph_rng_get_gamma(igraph_rng_t *rng, igraph_real_t shape, igraph_real_t scale) { const igraph_rng_type_t *type = rng->type; if (type->get_gamma) { return type->get_gamma(rng->state, shape, scale); } else { return igraph_rgamma(rng, shape, scale); } } unsigned long int igraph_rng_get_int31(igraph_rng_t *rng) { const igraph_rng_type_t *type = rng->type; unsigned long int max = type->max; if (type->get && max == 0x7FFFFFFFUL) { return type->get(rng->state); } else if (type->get_real) { return (unsigned long int) (type->get_real(rng->state) * 0x7FFFFFFFUL); } else { return (unsigned long int) (igraph_rng_get_unif01(rng) * 0x7FFFFFFFUL); } } igraph_real_t igraph_rng_get_exp(igraph_rng_t *rng, igraph_real_t rate) { const igraph_rng_type_t *type = rng->type; if (type->get_exp) { return type->get_exp(rng->state, rate); } else { return igraph_rexp(rng, rate); } } #ifndef HAVE_EXPM1 #ifndef USING_R /* R provides a replacement */ /* expm1 replacement */ double expm1 (double x) { if (fabs(x) < M_LN2) { /* Compute the Taylor series S = x + (1/2!) x^2 + (1/3!) x^3 + ... */ double i = 1.0; double sum = x; double term = x / 1.0; do { term *= x / ++i; sum += term; } while (fabs(term) > fabs(sum) * 2.22e-16); return sum; } return expl(x) - 1.0L; } #endif #endif #ifndef HAVE_RINT #ifndef USING_R /* R provides a replacement */ /* rint replacement */ double rint (double x) { return ( (x < 0.) ? -floor(-x + .5) : floor(x + .5) ); } #endif #endif #ifndef HAVE_RINTF float rintf (float x) { return ( (x < (float)0.) ? -(float)floor(-x + .5) : (float)floor(x + .5) ); } #endif /* * \ingroup internal * * This function appends the rest of the needed random number to the * result vector. */ int igraph_i_random_sample_alga(igraph_vector_t *res, igraph_integer_t l, igraph_integer_t h, igraph_integer_t length) { igraph_real_t N = h - l + 1; igraph_real_t n = length; igraph_real_t top = N - n; igraph_real_t Nreal = N; igraph_real_t S = 0; igraph_real_t V, quot; l = l - 1; while (n >= 2) { V = RNG_UNIF01(); S = 1; quot = top / Nreal; while (quot > V) { S += 1; top = -1.0 + top; Nreal = -1.0 + Nreal; quot = (quot * top) / Nreal; } l += S; igraph_vector_push_back(res, l); /* allocated */ Nreal = -1.0 + Nreal; n = -1 + n; } S = floor(round(Nreal) * RNG_UNIF01()); l += S + 1; igraph_vector_push_back(res, l); /* allocated */ return 0; } /** * \ingroup nongraph * \function igraph_random_sample * \brief Generates an increasing random sequence of integers. * * * This function generates an increasing sequence of random integer * numbers from a given interval. The algorithm is taken literally * from (Vitter 1987). This method can be used for generating numbers from a * \em very large interval. It is primarily created for randomly * selecting some edges from the sometimes huge set of possible edges * in a large graph. * * Note that the type of the lower and the upper limit is \c igraph_real_t, * not \c igraph_integer_t. This does not mean that you can pass fractional * numbers there; these values must still be integral, but we need the * longer range of \c igraph_real_t in several places in the library * (for instance, when generating Erdos-Renyi graphs). * \param res Pointer to an initialized vector. This will hold the * result. It will be resized to the proper size. * \param l The lower limit of the generation interval (inclusive). This must * be less than or equal to the upper limit, and it must be integral. * Passing a fractional number here results in undefined behaviour. * \param h The upper limit of the generation interval (inclusive). This must * be greater than or equal to the lower limit, and it must be integral. * Passing a fractional number here results in undefined behaviour. * \param length The number of random integers to generate. * \return The error code \c IGRAPH_EINVAL is returned in each of the * following cases: (1) The given lower limit is greater than the * given upper limit, i.e. \c l > \c h. (2) Assuming that * \c l < \c h and N is the sample size, the above error code is * returned if N > |\c h - \c l|, i.e. the sample size exceeds the * size of the candidate pool. * * Time complexity: according to (Vitter 1987), the expected * running time is O(length). * * * Reference: * \clist * \cli (Vitter 1987) * J. S. Vitter. An efficient algorithm for sequential random sampling. * \emb ACM Transactions on Mathematical Software, \eme 13(1):58--67, 1987. * \endclist * * \example examples/simple/igraph_random_sample.c */ int igraph_random_sample(igraph_vector_t *res, igraph_real_t l, igraph_real_t h, igraph_integer_t length) { igraph_real_t N = h - l + 1; igraph_real_t n = length; int retval; igraph_real_t nreal = length; igraph_real_t ninv = (nreal != 0) ? 1.0 / nreal : 0.0; igraph_real_t Nreal = N; igraph_real_t Vprime; igraph_real_t qu1 = -n + 1 + N; igraph_real_t qu1real = -nreal + 1.0 + Nreal; igraph_real_t negalphainv = -13; igraph_real_t threshold = -negalphainv * n; igraph_real_t S; /* getting back some sense of sanity */ if (l > h) { IGRAPH_ERROR("Lower limit is greater than upper limit", IGRAPH_EINVAL); } /* now we know that l <= h */ if (length > N) { IGRAPH_ERROR("Sample size exceeds size of candidate pool", IGRAPH_EINVAL); } /* treat rare cases quickly */ if (l == h) { IGRAPH_CHECK(igraph_vector_resize(res, 1)); VECTOR(*res)[0] = l; return 0; } if (length == 0) { igraph_vector_clear(res); return 0; } if (length == N) { long int i = 0; IGRAPH_CHECK(igraph_vector_resize(res, length)); for (i = 0; i < length; i++) { VECTOR(*res)[i] = l++; } return 0; } igraph_vector_clear(res); IGRAPH_CHECK(igraph_vector_reserve(res, length)); RNG_BEGIN(); Vprime = exp(log(RNG_UNIF01()) * ninv); l = l - 1; while (n > 1 && threshold < N) { igraph_real_t X, U; igraph_real_t limit, t; igraph_real_t negSreal, y1, y2, top, bottom; igraph_real_t nmin1inv = 1.0 / (-1.0 + nreal); while (1) { while (1) { X = Nreal * (-Vprime + 1.0); S = floor(X); // if (S==0) { S=1; } if (S < qu1) { break; } Vprime = exp(log(RNG_UNIF01()) * ninv); } U = RNG_UNIF01(); negSreal = -S; y1 = exp(log(U * Nreal / qu1real) * nmin1inv); Vprime = y1 * (-X / Nreal + 1.0) * (qu1real / (negSreal + qu1real)); if (Vprime <= 1.0) { break; } y2 = 1.0; top = -1.0 + Nreal; if (-1 + n > S) { bottom = -nreal + Nreal; limit = -S + N; } else { bottom = -1.0 + negSreal + Nreal; limit = qu1; } for (t = -1 + N; t >= limit; t--) { y2 = (y2 * top) / bottom; top = -1.0 + top; bottom = -1.0 + bottom; } if (Nreal / (-X + Nreal) >= y1 * exp(log(y2)*nmin1inv)) { Vprime = exp(log(RNG_UNIF01()) * nmin1inv); break; } Vprime = exp(log(RNG_UNIF01()) * ninv); } l += S + 1; igraph_vector_push_back(res, l); /* allocated */ N = -S + (-1 + N); Nreal = negSreal + (-1.0 + Nreal); n = -1 + n; nreal = -1.0 + nreal; ninv = nmin1inv; qu1 = -S + qu1; qu1real = negSreal + qu1real; threshold = threshold + negalphainv; } if (n > 1) { retval = igraph_i_random_sample_alga(res, (igraph_integer_t) l + 1, (igraph_integer_t) h, (igraph_integer_t) n); } else { retval = 0; S = floor(N * Vprime); l += S + 1; igraph_vector_push_back(res, l); /* allocated */ } RNG_END(); return retval; } #ifdef USING_R /* These are never called. But they are correct, nevertheless */ double igraph_norm_rand(igraph_rng_t *rng) { return norm_rand(); } double igraph_rgeom(igraph_rng_t *rng, double p) { return Rf_rgeom(p); } double igraph_rbinom(igraph_rng_t *rng, double nin, double pp) { return Rf_rbinom(nin, pp); } double igraph_rexp(igraph_rng_t *rng, double rate) { igraph_real_t scale = 1.0 / rate; if (!IGRAPH_FINITE(scale) || scale <= 0.0) { if (scale == 0.0) { return 0.0; } return IGRAPH_NAN; } return scale * exp_rand(); } double igraph_rgamma(igraph_rng_t *rng, double shape, double scale) { return Rf_rgamma(shape, scale); } #else /* * Mathlib : A C Library of Special Functions * Copyright (C) 1998 Ross Ihaka * Copyright (C) 2000 The R Development Core Team * based on AS 111 (C) 1977 Royal Statistical Society * and on AS 241 (C) 1988 Royal Statistical Society * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 2 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA. * * SYNOPSIS * * double qnorm5(double p, double mu, double sigma, * int lower_tail, int log_p) * {qnorm (..) is synonymous and preferred inside R} * * DESCRIPTION * * Compute the quantile function for the normal distribution. * * For small to moderate probabilities, algorithm referenced * below is used to obtain an initial approximation which is * polished with a final Newton step. * * For very large arguments, an algorithm of Wichura is used. * * REFERENCE * * Beasley, J. D. and S. G. Springer (1977). * Algorithm AS 111: The percentage points of the normal distribution, * Applied Statistics, 26, 118-121. * * Wichura, M.J. (1988). * Algorithm AS 241: The Percentage Points of the Normal Distribution. * Applied Statistics, 37, 477-484. */ /* * Mathlib : A C Library of Special Functions * Copyright (C) 1998-2004 The R Development Core Team * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 2 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ /* Private header file for use during compilation of Mathlib */ #ifndef MATHLIB_PRIVATE_H #define MATHLIB_PRIVATE_H #define ML_POSINF IGRAPH_INFINITY #define ML_NEGINF -IGRAPH_INFINITY #define ML_NAN IGRAPH_NAN #define ML_ERROR(x) /* nothing */ #define ML_UNDERFLOW (DBL_MIN * DBL_MIN) #define ML_VALID(x) (!ISNAN(x)) #define ME_NONE 0 /* no error */ #define ME_DOMAIN 1 /* argument out of domain */ #define ME_RANGE 2 /* value out of range */ #define ME_NOCONV 4 /* process did not converge */ #define ME_PRECISION 8 /* does not have "full" precision */ #define ME_UNDERFLOW 16 /* and underflow occurred (important for IEEE)*/ #define ML_ERR_return_NAN { ML_ERROR(ME_DOMAIN); return ML_NAN; } /* Wilcoxon Rank Sum Distribution */ #define WILCOX_MAX 50 /* Wilcoxon Signed Rank Distribution */ #define SIGNRANK_MAX 50 /* Formerly private part of Mathlib.h */ /* always remap internal functions */ #define bd0 Rf_bd0 #define chebyshev_eval Rf_chebyshev_eval #define chebyshev_init Rf_chebyshev_init #define i1mach Rf_i1mach #define gammalims Rf_gammalims #define lfastchoose Rf_lfastchoose #define lgammacor Rf_lgammacor #define stirlerr Rf_stirlerr /* Chebyshev Series */ int chebyshev_init(double*, int, double); double chebyshev_eval(double, const double *, const int); /* Gamma and Related Functions */ void gammalims(double*, double*); double lgammacor(double); /* log(gamma) correction */ double stirlerr(double); /* Stirling expansion "error" */ double lfastchoose(double, double); double bd0(double, double); /* Consider adding these two to the API (Rmath.h): */ double dbinom_raw(double, double, double, double, int); double dpois_raw (double, double, int); double pnchisq_raw(double, double, double, double, double, int); int i1mach(int); /* From toms708.c */ void bratio(double a, double b, double x, double y, double *w, double *w1, int *ierr); #endif /* MATHLIB_PRIVATE_H */ /* Utilities for `dpq' handling (density/probability/quantile) */ /* give_log in "d"; log_p in "p" & "q" : */ #define give_log log_p /* "DEFAULT" */ /* --------- */ #define R_D__0 (log_p ? ML_NEGINF : 0.) /* 0 */ #define R_D__1 (log_p ? 0. : 1.) /* 1 */ #define R_DT_0 (lower_tail ? R_D__0 : R_D__1) /* 0 */ #define R_DT_1 (lower_tail ? R_D__1 : R_D__0) /* 1 */ #define R_D_Lval(p) (lower_tail ? (p) : (1 - (p))) /* p */ #define R_D_Cval(p) (lower_tail ? (1 - (p)) : (p)) /* 1 - p */ #define R_D_val(x) (log_p ? log(x) : (x)) /* x in pF(x,..) */ #define R_D_qIv(p) (log_p ? exp(p) : (p)) /* p in qF(p,..) */ #define R_D_exp(x) (log_p ? (x) : exp(x)) /* exp(x) */ #define R_D_log(p) (log_p ? (p) : log(p)) /* log(p) */ #define R_D_Clog(p) (log_p ? log1p(-(p)) : (1 - (p)))/* [log](1-p) */ /* log(1-exp(x)): R_D_LExp(x) == (log1p(- R_D_qIv(x))) but even more stable:*/ #define R_D_LExp(x) (log_p ? R_Log1_Exp(x) : log1p(-x)) /*till 1.8.x: * #define R_DT_val(x) R_D_val(R_D_Lval(x)) * #define R_DT_Cval(x) R_D_val(R_D_Cval(x)) */ #define R_DT_val(x) (lower_tail ? R_D_val(x) : R_D_Clog(x)) #define R_DT_Cval(x) (lower_tail ? R_D_Clog(x) : R_D_val(x)) /*#define R_DT_qIv(p) R_D_Lval(R_D_qIv(p)) * p in qF ! */ #define R_DT_qIv(p) (log_p ? (lower_tail ? exp(p) : - expm1(p)) \ : R_D_Lval(p)) /*#define R_DT_CIv(p) R_D_Cval(R_D_qIv(p)) * 1 - p in qF */ #define R_DT_CIv(p) (log_p ? (lower_tail ? -expm1(p) : exp(p)) \ : R_D_Cval(p)) #define R_DT_exp(x) R_D_exp(R_D_Lval(x)) /* exp(x) */ #define R_DT_Cexp(x) R_D_exp(R_D_Cval(x)) /* exp(1 - x) */ #define R_DT_log(p) (lower_tail? R_D_log(p) : R_D_LExp(p))/* log(p) in qF */ #define R_DT_Clog(p) (lower_tail? R_D_LExp(p): R_D_log(p))/* log(1-p) in qF*/ #define R_DT_Log(p) (lower_tail? (p) : R_Log1_Exp(p)) /* == R_DT_log when we already "know" log_p == TRUE :*/ #define R_Q_P01_check(p) \ if ((log_p && p > 0) || \ (!log_p && (p < 0 || p > 1)) ) \ ML_ERR_return_NAN /* additions for density functions (C.Loader) */ #define R_D_fexp(f,x) (give_log ? -0.5*log(f)+(x) : exp(x)/sqrt(f)) #define R_D_forceint(x) floor((x) + 0.5) #define R_D_nonint(x) (fabs((x) - floor((x)+0.5)) > 1e-7) /* [neg]ative or [non int]eger : */ #define R_D_negInonint(x) (x < 0. || R_D_nonint(x)) #define R_D_nonint_check(x) \ if(R_D_nonint(x)) { \ MATHLIB_WARNING("non-integer x = %f", x); \ return R_D__0; \ } double igraph_qnorm5(double p, double mu, double sigma, int lower_tail, int log_p) { double p_, q, r, val; #ifdef IEEE_754 if (ISNAN(p) || ISNAN(mu) || ISNAN(sigma)) { return p + mu + sigma; } #endif if (p == R_DT_0) { return ML_NEGINF; } if (p == R_DT_1) { return ML_POSINF; } R_Q_P01_check(p); if (sigma < 0) { ML_ERR_return_NAN; } if (sigma == 0) { return mu; } p_ = R_DT_qIv(p);/* real lower_tail prob. p */ q = p_ - 0.5; /*-- use AS 241 --- */ /* double ppnd16_(double *p, long *ifault)*/ /* ALGORITHM AS241 APPL. STATIST. (1988) VOL. 37, NO. 3 Produces the normal deviate Z corresponding to a given lower tail area of P; Z is accurate to about 1 part in 10**16. (original fortran code used PARAMETER(..) for the coefficients and provided hash codes for checking them...) */ if (fabs(q) <= .425) {/* 0.075 <= p <= 0.925 */ r = .180625 - q * q; val = q * (((((((r * 2509.0809287301226727 + 33430.575583588128105) * r + 67265.770927008700853) * r + 45921.953931549871457) * r + 13731.693765509461125) * r + 1971.5909503065514427) * r + 133.14166789178437745) * r + 3.387132872796366608) / (((((((r * 5226.495278852854561 + 28729.085735721942674) * r + 39307.89580009271061) * r + 21213.794301586595867) * r + 5394.1960214247511077) * r + 687.1870074920579083) * r + 42.313330701600911252) * r + 1.); } else { /* closer than 0.075 from {0,1} boundary */ /* r = min(p, 1-p) < 0.075 */ if (q > 0) { r = R_DT_CIv(p); /* 1-p */ } else { r = p_; /* = R_DT_Iv(p) ^= p */ } r = sqrt(- ((log_p && ((lower_tail && q <= 0) || (!lower_tail && q > 0))) ? p : /* else */ log(r))); /* r = sqrt(-log(r)) <==> min(p, 1-p) = exp( - r^2 ) */ if (r <= 5.) { /* <==> min(p,1-p) >= exp(-25) ~= 1.3888e-11 */ r += -1.6; val = (((((((r * 7.7454501427834140764e-4 + .0227238449892691845833) * r + .24178072517745061177) * r + 1.27045825245236838258) * r + 3.64784832476320460504) * r + 5.7694972214606914055) * r + 4.6303378461565452959) * r + 1.42343711074968357734) / (((((((r * 1.05075007164441684324e-9 + 5.475938084995344946e-4) * r + .0151986665636164571966) * r + .14810397642748007459) * r + .68976733498510000455) * r + 1.6763848301838038494) * r + 2.05319162663775882187) * r + 1.); } else { /* very close to 0 or 1 */ r += -5.; val = (((((((r * 2.01033439929228813265e-7 + 2.71155556874348757815e-5) * r + .0012426609473880784386) * r + .026532189526576123093) * r + .29656057182850489123) * r + 1.7848265399172913358) * r + 5.4637849111641143699) * r + 6.6579046435011037772) / (((((((r * 2.04426310338993978564e-15 + 1.4215117583164458887e-7) * r + 1.8463183175100546818e-5) * r + 7.868691311456132591e-4) * r + .0148753612908506148525) * r + .13692988092273580531) * r + .59983220655588793769) * r + 1.); } if (q < 0.0) { val = -val; } /* return (q >= 0.)? r : -r ;*/ } return mu + sigma * val; } double fsign(double x, double y) { #ifdef IEEE_754 if (ISNAN(x) || ISNAN(y)) { return x + y; } #endif return ((y >= 0) ? fabs(x) : -fabs(x)); } int imax2(int x, int y) { return (x < y) ? y : x; } int imin2(int x, int y) { return (x < y) ? x : y; } #if HAVE_WORKING_ISFINITE || HAVE_ISFINITE /* isfinite is defined in according to C99 */ #define R_FINITE(x) isfinite(x) #elif HAVE_WORKING_FINITE || HAVE_FINITE /* include header needed to define finite() */ #ifdef HAVE_IEEE754_H #include /* newer Linuxen */ #else #ifdef HAVE_IEEEFP_H #include /* others [Solaris], .. */ #endif #endif #define R_FINITE(x) finite(x) #else #define R_FINITE(x) R_finite(x) #endif int R_finite(double x) { #if HAVE_WORKING_ISFINITE || HAVE_ISFINITE return isfinite(x); #elif HAVE_WORKING_FINITE || HAVE_FINITE return finite(x); #else /* neither finite nor isfinite work. Do we really need the AIX exception? */ # ifdef _AIX # include return FINITE(x); # elif defined(_MSC_VER) return _finite(x); #else return (!isnan(x) & (x != 1 / 0.0) & (x != -1.0 / 0.0)); # endif #endif } int R_isnancpp(double x) { return (isnan(x) != 0); } #ifdef __cplusplus int R_isnancpp(double); /* in arithmetic.c */ #define ISNAN(x) R_isnancpp(x) #else #define ISNAN(x) (isnan(x)!=0) #endif double igraph_norm_rand(igraph_rng_t *rng) { double u1; #define BIG 134217728 /* 2^27 */ /* unif_rand() alone is not of high enough precision */ u1 = igraph_rng_get_unif01(rng); u1 = (int)(BIG * u1) + igraph_rng_get_unif01(rng); return igraph_qnorm5(u1 / BIG, 0.0, 1.0, 1, 0); } /* * Mathlib : A C Library of Special Functions * Copyright (C) 1998 Ross Ihaka * Copyright (C) 2000-2002 the R Development Core Team * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 2 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA. * * SYNOPSIS * * #include * double exp_rand(void); * * DESCRIPTION * * Random variates from the standard exponential distribution. * * REFERENCE * * Ahrens, J.H. and Dieter, U. (1972). * Computer methods for sampling from the exponential and * normal distributions. * Comm. ACM, 15, 873-882. */ double igraph_exp_rand(igraph_rng_t *rng) { /* q[k-1] = sum(log(2)^k / k!) k=1,..,n, */ /* The highest n (here 8) is determined by q[n-1] = 1.0 */ /* within standard precision */ const double q[] = { 0.6931471805599453, 0.9333736875190459, 0.9888777961838675, 0.9984959252914960, 0.9998292811061389, 0.9999833164100727, 0.9999985691438767, 0.9999998906925558, 0.9999999924734159, 0.9999999995283275, 0.9999999999728814, 0.9999999999985598, 0.9999999999999289, 0.9999999999999968, 0.9999999999999999, 1.0000000000000000 }; double a, u, ustar, umin; int i; a = 0.; /* precaution if u = 0 is ever returned */ u = igraph_rng_get_unif01(rng); while (u <= 0.0 || u >= 1.0) { u = igraph_rng_get_unif01(rng); } for (;;) { u += u; if (u > 1.0) { break; } a += q[0]; } u -= 1.; if (u <= q[0]) { return a + u; } i = 0; ustar = igraph_rng_get_unif01(rng); umin = ustar; do { ustar = igraph_rng_get_unif01(rng); if (ustar < umin) { umin = ustar; } i++; } while (u > q[i]); return a + umin * q[0]; } /* * Mathlib : A C Library of Special Functions * Copyright (C) 1998 Ross Ihaka * Copyright (C) 2000-2001 The R Development Core Team * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 2 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA. * * SYNOPSIS * * #include * double rpois(double lambda) * * DESCRIPTION * * Random variates from the Poisson distribution. * * REFERENCE * * Ahrens, J.H. and Dieter, U. (1982). * Computer generation of Poisson deviates * from modified normal distributions. * ACM Trans. Math. Software 8, 163-179. */ #define a0 -0.5 #define a1 0.3333333 #define a2 -0.2500068 #define a3 0.2000118 #define a4 -0.1661269 #define a5 0.1421878 #define a6 -0.1384794 #define a7 0.1250060 #define one_7 0.1428571428571428571 #define one_12 0.0833333333333333333 #define one_24 0.0416666666666666667 #define repeat for(;;) #define FALSE 0 #define TRUE 1 #define M_1_SQRT_2PI 0.398942280401432677939946059934 /* 1/sqrt(2pi) */ double igraph_rpois(igraph_rng_t *rng, double mu) { /* Factorial Table (0:9)! */ const double fact[10] = { 1., 1., 2., 6., 24., 120., 720., 5040., 40320., 362880. }; /* These are static --- persistent between calls for same mu : */ static IGRAPH_THREAD_LOCAL int l, m; static IGRAPH_THREAD_LOCAL double b1, b2, c, c0, c1, c2, c3; static IGRAPH_THREAD_LOCAL double pp[36], p0, p, q, s, d, omega; static IGRAPH_THREAD_LOCAL double big_l;/* integer "w/o overflow" */ static IGRAPH_THREAD_LOCAL double muprev = 0., muprev2 = 0.;/*, muold = 0.*/ /* Local Vars [initialize some for -Wall]: */ double del, difmuk = 0., E = 0., fk = 0., fx, fy, g, px, py, t, u = 0., v, x; double pois = -1.; int k, kflag, big_mu, new_big_mu = FALSE; if (!R_FINITE(mu)) { ML_ERR_return_NAN; } if (mu <= 0.) { return 0.; } big_mu = mu >= 10.; if (big_mu) { new_big_mu = FALSE; } if (!(big_mu && mu == muprev)) {/* maybe compute new persistent par.s */ if (big_mu) { new_big_mu = TRUE; /* Case A. (recalculation of s,d,l because mu has changed): * The Poisson probabilities pk exceed the discrete normal * probabilities fk whenever k >= m(mu). */ muprev = mu; s = sqrt(mu); d = 6. * mu * mu; big_l = floor(mu - 1.1484); /* = an upper bound to m(mu) for all mu >= 10.*/ } else { /* Small mu ( < 10) -- not using normal approx. */ /* Case B. (start new table and calculate p0 if necessary) */ /*muprev = 0.;-* such that next time, mu != muprev ..*/ if (mu != muprev) { muprev = mu; m = imax2(1, (int) mu); l = 0; /* pp[] is already ok up to pp[l] */ q = p0 = p = exp(-mu); } repeat { /* Step U. uniform sample for inversion method */ u = igraph_rng_get_unif01(rng); if (u <= p0) { return 0.; } /* Step T. table comparison until the end pp[l] of the pp-table of cumulative Poisson probabilities (0.458 > ~= pp[9](= 0.45792971447) for mu=10 ) */ if (l != 0) { for (k = (u <= 0.458) ? 1 : imin2(l, m); k <= l; k++) if (u <= pp[k]) { return (double)k; } if (l == 35) { /* u > pp[35] */ continue; } } /* Step C. creation of new Poisson probabilities p[l..] and their cumulatives q =: pp[k] */ l++; for (k = l; k <= 35; k++) { p *= mu / k; q += p; pp[k] = q; if (u <= q) { l = k; return (double)k; } } l = 35; } /* end(repeat) */ }/* mu < 10 */ } /* end {initialize persistent vars} */ /* Only if mu >= 10 : ----------------------- */ /* Step N. normal sample */ g = mu + s * igraph_norm_rand(rng);/* norm_rand() ~ N(0,1), standard normal */ if (g >= 0.) { pois = floor(g); /* Step I. immediate acceptance if pois is large enough */ if (pois >= big_l) { return pois; } /* Step S. squeeze acceptance */ fk = pois; difmuk = mu - fk; u = igraph_rng_get_unif01(rng); /* ~ U(0,1) - sample */ if (d * u >= difmuk * difmuk * difmuk) { return pois; } } /* Step P. preparations for steps Q and H. (recalculations of parameters if necessary) */ if (new_big_mu || mu != muprev2) { /* Careful! muprev2 is not always == muprev because one might have exited in step I or S */ muprev2 = mu; omega = M_1_SQRT_2PI / s; /* The quantities b1, b2, c3, c2, c1, c0 are for the Hermite * approximations to the discrete normal probabilities fk. */ b1 = one_24 / mu; b2 = 0.3 * b1 * b1; c3 = one_7 * b1 * b2; c2 = b2 - 15. * c3; c1 = b1 - 6. * b2 + 45. * c3; c0 = 1. - b1 + 3. * b2 - 15. * c3; c = 0.1069 / mu; /* guarantees majorization by the 'hat'-function. */ } if (g >= 0.) { /* 'Subroutine' F is called (kflag=0 for correct return) */ kflag = 0; goto Step_F; } repeat { /* Step E. Exponential Sample */ E = igraph_exp_rand(rng);/* ~ Exp(1) (standard exponential) */ /* sample t from the laplace 'hat' (if t <= -0.6744 then pk < fk for all mu >= 10.) */ u = 2 * igraph_rng_get_unif01(rng) - 1.; t = 1.8 + fsign(E, u); if (t > -0.6744) { pois = floor(mu + s * t); fk = pois; difmuk = mu - fk; /* 'subroutine' F is called (kflag=1 for correct return) */ kflag = 1; Step_F: /* 'subroutine' F : calculation of px,py,fx,fy. */ if (pois < 10) { /* use factorials from table fact[] */ px = -mu; py = pow(mu, pois) / fact[(int)pois]; } else { /* Case pois >= 10 uses polynomial approximation a0-a7 for accuracy when advisable */ del = one_12 / fk; del = del * (1. - 4.8 * del * del); v = difmuk / fk; if (fabs(v) <= 0.25) px = fk * v * v * (((((((a7 * v + a6) * v + a5) * v + a4) * v + a3) * v + a2) * v + a1) * v + a0) - del; else { /* |v| > 1/4 */ px = fk * log(1. + v) - difmuk - del; } py = M_1_SQRT_2PI / sqrt(fk); } x = (0.5 - difmuk) / s; x *= x;/* x^2 */ fx = -0.5 * x; fy = omega * (((c3 * x + c2) * x + c1) * x + c0); if (kflag > 0) { /* Step H. Hat acceptance (E is repeated on rejection) */ if (c * fabs(u) <= py * exp(px + E) - fy * exp(fx + E)) { break; } } else /* Step Q. Quotient acceptance (rare case) */ if (fy - u * fy <= py * exp(px - fx)) { break; } }/* t > -.67.. */ } return pois; } #undef a1 #undef a2 #undef a3 #undef a4 #undef a5 #undef a6 #undef a7 double igraph_rgeom(igraph_rng_t *rng, double p) { if (ISNAN(p) || p <= 0 || p > 1) { ML_ERR_return_NAN; } return igraph_rpois(rng, igraph_exp_rand(rng) * ((1 - p) / p)); } /* This is from nmath/rbinom.c */ #define repeat for(;;) double igraph_rbinom(igraph_rng_t *rng, double nin, double pp) { /* FIXME: These should become THREAD_specific globals : */ static IGRAPH_THREAD_LOCAL double c, fm, npq, p1, p2, p3, p4, qn; static IGRAPH_THREAD_LOCAL double xl, xll, xlr, xm, xr; static IGRAPH_THREAD_LOCAL double psave = -1.0; static IGRAPH_THREAD_LOCAL int nsave = -1; static IGRAPH_THREAD_LOCAL int m; double f, f1, f2, u, v, w, w2, x, x1, x2, z, z2; double p, q, np, g, r, al, alv, amaxp, ffm, ynorm; int i, ix, k, n; if (!R_FINITE(nin)) { ML_ERR_return_NAN; } n = floor(nin + 0.5); if (n != nin) { ML_ERR_return_NAN; } if (!R_FINITE(pp) || /* n=0, p=0, p=1 are not errors */ n < 0 || pp < 0. || pp > 1.) { ML_ERR_return_NAN; } if (n == 0 || pp == 0.) { return 0; } if (pp == 1.) { return n; } p = fmin(pp, 1. - pp); q = 1. - p; np = n * p; r = p / q; g = r * (n + 1); /* Setup, perform only when parameters change [using static (globals): */ /* FIXING: Want this thread safe -- use as little (thread globals) as possible */ if (pp != psave || n != nsave) { psave = pp; nsave = n; if (np < 30.0) { /* inverse cdf logic for mean less than 30 */ qn = pow(q, (double) n); goto L_np_small; } else { ffm = np + p; m = ffm; fm = m; npq = np * q; p1 = (int)(2.195 * sqrt(npq) - 4.6 * q) + 0.5; xm = fm + 0.5; xl = xm - p1; xr = xm + p1; c = 0.134 + 20.5 / (15.3 + fm); al = (ffm - xl) / (ffm - xl * p); xll = al * (1.0 + 0.5 * al); al = (xr - ffm) / (xr * q); xlr = al * (1.0 + 0.5 * al); p2 = p1 * (1.0 + c + c); p3 = p2 + c / xll; p4 = p3 + c / xlr; } } else if (n == nsave) { if (np < 30.0) { goto L_np_small; } } /*-------------------------- np = n*p >= 30 : ------------------- */ repeat { u = igraph_rng_get_unif01(rng) * p4; v = igraph_rng_get_unif01(rng); /* triangular region */ if (u <= p1) { ix = xm - p1 * v + u; goto finis; } /* parallelogram region */ if (u <= p2) { x = xl + (u - p1) / c; v = v * c + 1.0 - fabs(xm - x) / p1; if (v > 1.0 || v <= 0.) { continue; } ix = x; } else { if (u > p3) { /* right tail */ ix = xr - log(v) / xlr; if (ix > n) { continue; } v = v * (u - p3) * xlr; } else {/* left tail */ ix = xl + log(v) / xll; if (ix < 0) { continue; } v = v * (u - p2) * xll; } } /* determine appropriate way to perform accept/reject test */ k = abs(ix - m); if (k <= 20 || k >= npq / 2 - 1) { /* explicit evaluation */ f = 1.0; if (m < ix) { for (i = m + 1; i <= ix; i++) { f *= (g / i - r); } } else if (m != ix) { for (i = ix + 1; i <= m; i++) { f /= (g / i - r); } } if (v <= f) { goto finis; } } else { /* squeezing using upper and lower bounds on log(f(x)) */ amaxp = (k / npq) * ((k * (k / 3. + 0.625) + 0.1666666666666) / npq + 0.5); ynorm = -k * k / (2.0 * npq); alv = log(v); if (alv < ynorm - amaxp) { goto finis; } if (alv <= ynorm + amaxp) { /* Stirling's formula to machine accuracy */ /* for the final acceptance/rejection test */ x1 = ix + 1; f1 = fm + 1.0; z = n + 1 - fm; w = n - ix + 1.0; z2 = z * z; x2 = x1 * x1; f2 = f1 * f1; w2 = w * w; if (alv <= xm * log(f1 / x1) + (n - m + 0.5) * log(z / w) + (ix - m) * log(w * p / (x1 * q)) + (13860.0 - (462.0 - (132.0 - (99.0 - 140.0 / f2) / f2) / f2) / f2) / f1 / 166320.0 + (13860.0 - (462.0 - (132.0 - (99.0 - 140.0 / z2) / z2) / z2) / z2) / z / 166320.0 + (13860.0 - (462.0 - (132.0 - (99.0 - 140.0 / x2) / x2) / x2) / x2) / x1 / 166320.0 + (13860.0 - (462.0 - (132.0 - (99.0 - 140.0 / w2) / w2) / w2) / w2) / w / 166320.) { goto finis; } } } } L_np_small: /*---------------------- np = n*p < 30 : ------------------------- */ repeat { ix = 0; f = qn; u = igraph_rng_get_unif01(rng); repeat { if (u < f) { goto finis; } if (ix > 110) { break; } u -= f; ix++; f *= (g / ix - r); } } finis: if (psave > 0.5) { ix = n - ix; } return (double)ix; } igraph_real_t igraph_rexp(igraph_rng_t *rng, double rate) { igraph_real_t scale = 1.0 / rate; if (!IGRAPH_FINITE(scale) || scale <= 0.0) { if (scale == 0.0) { return 0.0; } return IGRAPH_NAN; } return scale * igraph_exp_rand(rng); } /* * Mathlib : A C Library of Special Functions * Copyright (C) 1998 Ross Ihaka * Copyright (C) 2000 The R Core Team * Copyright (C) 2003 The R Foundation * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 2 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, a copy is available at * http://www.r-project.org/Licenses/ * * SYNOPSIS * * double dnorm4(double x, double mu, double sigma, int give_log) * {dnorm (..) is synonymous and preferred inside R} * * DESCRIPTION * * Compute the density of the normal distribution. */ double igraph_dnorm(double x, double mu, double sigma, int give_log) { #ifdef IEEE_754 if (ISNAN(x) || ISNAN(mu) || ISNAN(sigma)) { return x + mu + sigma; } #endif if (!R_FINITE(sigma)) { return R_D__0; } if (!R_FINITE(x) && mu == x) { return ML_NAN; /* x-mu is NaN */ } if (sigma <= 0) { if (sigma < 0) { ML_ERR_return_NAN; } /* sigma == 0 */ return (x == mu) ? ML_POSINF : R_D__0; } x = (x - mu) / sigma; if (!R_FINITE(x)) { return R_D__0; } return (give_log ? -(M_LN_SQRT_2PI + 0.5 * x * x + log(sigma)) : M_1_SQRT_2PI * exp(-0.5 * x * x) / sigma); /* M_1_SQRT_2PI = 1 / sqrt(2 * pi) */ } /* This is from nmath/rgamma.c */ /* * Mathlib : A C Library of Special Functions * Copyright (C) 1998 Ross Ihaka * Copyright (C) 2000--2008 The R Core Team * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 2 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, a copy is available at * http://www.r-project.org/Licenses/ * * SYNOPSIS * * #include * double rgamma(double a, double scale); * * DESCRIPTION * * Random variates from the gamma distribution. * * REFERENCES * * [1] Shape parameter a >= 1. Algorithm GD in: * * Ahrens, J.H. and Dieter, U. (1982). * Generating gamma variates by a modified * rejection technique. * Comm. ACM, 25, 47-54. * * * [2] Shape parameter 0 < a < 1. Algorithm GS in: * * Ahrens, J.H. and Dieter, U. (1974). * Computer methods for sampling from gamma, beta, * poisson and binomial distributions. * Computing, 12, 223-246. * * Input: a = parameter (mean) of the standard gamma distribution. * Output: a variate from the gamma(a)-distribution */ double igraph_rgamma(igraph_rng_t *rng, double a, double scale) { /* Constants : */ const static double sqrt32 = 5.656854; const static double exp_m1 = 0.36787944117144232159;/* exp(-1) = 1/e */ /* Coefficients q[k] - for q0 = sum(q[k]*a^(-k)) * Coefficients a[k] - for q = q0+(t*t/2)*sum(a[k]*v^k) * Coefficients e[k] - for exp(q)-1 = sum(e[k]*q^k) */ const static double q1 = 0.04166669; const static double q2 = 0.02083148; const static double q3 = 0.00801191; const static double q4 = 0.00144121; const static double q5 = -7.388e-5; const static double q6 = 2.4511e-4; const static double q7 = 2.424e-4; const static double a1 = 0.3333333; const static double a2 = -0.250003; const static double a3 = 0.2000062; const static double a4 = -0.1662921; const static double a5 = 0.1423657; const static double a6 = -0.1367177; const static double a7 = 0.1233795; /* State variables [FIXME for threading!] :*/ static double aa = 0.; static double aaa = 0.; static double s, s2, d; /* no. 1 (step 1) */ static double q0, b, si, c;/* no. 2 (step 4) */ double e, p, q, r, t, u, v, w, x, ret_val; if (!R_FINITE(a) || !R_FINITE(scale) || a < 0.0 || scale <= 0.0) { if (scale == 0.) { return 0.; } ML_ERR_return_NAN; } if (a < 1.) { /* GS algorithm for parameters a < 1 */ if (a == 0) { return 0.; } e = 1.0 + exp_m1 * a; repeat { p = e * igraph_rng_get_unif01(rng); if (p >= 1.0) { x = -log((e - p) / a); if (igraph_exp_rand(rng) >= (1.0 - a) * log(x)) { break; } } else { x = exp(log(p) / a); if (igraph_exp_rand(rng) >= x) { break; } } } return scale * x; } /* --- a >= 1 : GD algorithm --- */ /* Step 1: Recalculations of s2, s, d if a has changed */ if (a != aa) { aa = a; s2 = a - 0.5; s = sqrt(s2); d = sqrt32 - s * 12.0; } /* Step 2: t = standard normal deviate, x = (s,1/2) -normal deviate. */ /* immediate acceptance (i) */ t = igraph_norm_rand(rng); x = s + 0.5 * t; ret_val = x * x; if (t >= 0.0) { return scale * ret_val; } /* Step 3: u = 0,1 - uniform sample. squeeze acceptance (s) */ u = igraph_rng_get_unif01(rng); if (d * u <= t * t * t) { return scale * ret_val; } /* Step 4: recalculations of q0, b, si, c if necessary */ if (a != aaa) { aaa = a; r = 1.0 / a; q0 = ((((((q7 * r + q6) * r + q5) * r + q4) * r + q3) * r + q2) * r + q1) * r; /* Approximation depending on size of parameter a */ /* The constants in the expressions for b, si and c */ /* were established by numerical experiments */ if (a <= 3.686) { b = 0.463 + s + 0.178 * s2; si = 1.235; c = 0.195 / s - 0.079 + 0.16 * s; } else if (a <= 13.022) { b = 1.654 + 0.0076 * s2; si = 1.68 / s + 0.275; c = 0.062 / s + 0.024; } else { b = 1.77; si = 0.75; c = 0.1515 / s; } } /* Step 5: no quotient test if x not positive */ if (x > 0.0) { /* Step 6: calculation of v and quotient q */ v = t / (s + s); if (fabs(v) <= 0.25) q = q0 + 0.5 * t * t * ((((((a7 * v + a6) * v + a5) * v + a4) * v + a3) * v + a2) * v + a1) * v; else { q = q0 - s * t + 0.25 * t * t + (s2 + s2) * log(1.0 + v); } /* Step 7: quotient acceptance (q) */ if (log(1.0 - u) <= q) { return scale * ret_val; } } repeat { /* Step 8: e = standard exponential deviate * u = 0,1 -uniform deviate * t = (b,si)-double exponential (laplace) sample */ e = igraph_exp_rand(rng); u = igraph_rng_get_unif01(rng); u = u + u - 1.0; if (u < 0.0) { t = b - si * e; } else { t = b + si * e; } /* Step 9: rejection if t < tau(1) = -0.71874483771719 */ if (t >= -0.71874483771719) { /* Step 10: calculation of v and quotient q */ v = t / (s + s); if (fabs(v) <= 0.25) q = q0 + 0.5 * t * t * ((((((a7 * v + a6) * v + a5) * v + a4) * v + a3) * v + a2) * v + a1) * v; else { q = q0 - s * t + 0.25 * t * t + (s2 + s2) * log(1.0 + v); } /* Step 11: hat acceptance (h) */ /* (if q not positive go to step 8) */ if (q > 0.0) { w = expm1(q); /* ^^^^^ original code had approximation with rel.err < 2e-7 */ /* if t is rejected sample again at step 8 */ if (c * fabs(u) <= w * exp(e - 0.5 * t * t)) { break; } } } } /* repeat .. until `t' is accepted */ x = s + 0.5 * t; return scale * x * x; } #endif int igraph_rng_get_dirichlet(igraph_rng_t *rng, const igraph_vector_t *alpha, igraph_vector_t *result) { igraph_integer_t len = igraph_vector_size(alpha); igraph_integer_t j; igraph_real_t sum = 0.0; if (len < 2) { IGRAPH_ERROR("Dirichlet parameter vector too short, must " "have at least two entries", IGRAPH_EINVAL); } if (igraph_vector_min(alpha) <= 0) { IGRAPH_ERROR("Dirichlet concentration parameters must be positive", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_vector_resize(result, len)); RNG_BEGIN(); for (j = 0; j < len; j++) { VECTOR(*result)[j] = igraph_rng_get_gamma(rng, VECTOR(*alpha)[j], 1.0); sum += VECTOR(*result)[j]; } for (j = 0; j < len; j++) { VECTOR(*result)[j] /= sum; } RNG_END(); return 0; } /********************************************************** * Testing purposes * *********************************************************/ /* int main() { */ /* int i; */ /* RNG_BEGIN(); */ /* for (i=0; i<1000; i++) { */ /* printf("%li ", RNG_INTEGER(1,10)); */ /* } */ /* printf("\n"); */ /* for (i=0; i<1000; i++) { */ /* printf("%f ", RNG_UNIF(0,1)); */ /* } */ /* printf("\n"); */ /* for (i=0; i<1000; i++) { */ /* printf("%f ", RNG_NORMAL(0,5)); */ /* } */ /* printf("\n"); */ /* RNG_END(); */ /* return 0; */ /* } */ python-igraph-0.8.0/vendor/source/igraph/src/microscopic_update.c0000644000076500000240000016424413614300625025431 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* Microscopic update rules for dealing with agent-level strategy revision. Copyright (C) 2011 Minh Van Nguyen This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_iterators.h" #include "igraph_interface.h" #include "igraph_microscopic_update.h" #include "igraph_nongraph.h" #include "igraph_random.h" #include /* * Internal use only. * Compute the cumulative proportionate values of a vector. The vector is * assumed to hold values associated with edges. * * \param graph The graph object representing the game network. No error * checks will be performed on this graph. You are responsible for * ensuring that this is a valid graph for the particular * microscopic update rule at hand. * \param U A vector of edge values for which we want to compute cumulative * proportionate values. So U[i] is the value of the edge with ID i. * With a local perspective, we would only compute cumulative * proportionate values for some combination of U. This vector could * be, for example, a vector of weights for edges in \p graph. It is * assumed that each value of U is nonnegative; it is your * responsibility to ensure this. Furthermore, this vector must have a * length the same as the number of edges in \p graph; you are * responsible for ensuring this condition holds. * \param V Pointer to an uninitialized vector. The cumulative proportionate * values will be computed and stored here. No error checks will be * performed on this parameter. * \param islocal Boolean; this flag controls which perspective to use. If * true then we use the local perspective; otherwise we use the global * perspective. In the context of this function, the local perspective * for a vertex v consists of all edges incident on v. In contrast, the * global perspective for v consists of all edges in \p graph. * \param vid The vertex to use if we are considering a local perspective, * i.e. if \p islocal is true. This vertex will be ignored if * \p islocal is false. That is, if \p islocal is false then it is safe * pass the value -1 here. On the other hand, if \p islocal is true then * it is assumed that this is indeed a vertex of \p graph. * \param mode Defines the sort of neighbourhood to consider for \p vid. This * is only relevant if we are considering the local perspective, i.e. if * \p islocal is true. If we are considering the global perspective, * then this parameter would be ignored. In other words, if \p islocal * is false then it is safe to pass the value \p IGRAPH_ALL here. If * \p graph is undirected, then we use all the immediate neighbours of * \p vid. Thus if you know that \p graph is undirected, then it is * safe to pass the value \p IGRAPH_ALL here. Supported values are: * \clist * \cli IGRAPH_OUT * Use the out-neighbours of \p vid. This option is only relevant * when \p graph is a digraph and we are considering the local * perspective. * \cli IGRAPH_IN * Use the in-neighbours of \p vid. Again this option is only relevant * when \p graph is a directed graph and we are considering the local * perspective. * \cli IGRAPH_ALL * Use both the in- and out-neighbours of \p vid. This option is only * relevant if \p graph is a digraph and we are considering a local * perspective. Also use this value if \p graph is undirected or we * are considering the global perspective. * \endclist * \return Codes: * \clist * \cli IGRAPH_EINVAL * This error code is returned in the following case: The vector * \p U, or some combination of its values, sums to zero. * \cli IGRAPH_SUCCESS * This signal is returned if the cumulative proportionate values * were successfully computed. * \endclist * * Time complexity: O(2n) where n is the number of edges in the perspective * of \p vid. */ int igraph_ecumulative_proportionate_values(const igraph_t *graph, const igraph_vector_t *U, igraph_vector_t *V, igraph_bool_t islocal, igraph_integer_t vid, igraph_neimode_t mode) { igraph_eit_t A; /* all edges in v's perspective */ igraph_es_t es; igraph_integer_t e; igraph_real_t C; /* cumulative probability */ igraph_real_t P; /* probability */ igraph_real_t S; /* sum of values */ long int i; /* Set the perspective. Let v be the vertex under consideration. The local */ /* perspective for v consists of edges incident on it. In contrast, the */ /* global perspective for v are all edges in the given graph. Hence in the */ /* global perspective, we will ignore the given vertex and the given */ /* neighbourhood type, but instead consider all edges in the given graph. */ if (islocal) { IGRAPH_CHECK(igraph_es_incident(&es, vid, mode)); } else { IGRAPH_CHECK(igraph_es_all(&es, IGRAPH_EDGEORDER_ID)); } IGRAPH_FINALLY(igraph_es_destroy, &es); /* Sum up all the values of vector U in the perspective for v. This sum */ /* will be used in normalizing each value. */ /* NOTE: Here we assume that each value to be summed is nonnegative, */ /* and at least one of the values is nonzero. The behaviour resulting */ /* from all values being zero would be division by zero later on when */ /* we normalize each value. We check to see that the values sum to zero. */ /* NOTE: In this function, the order in which we iterate through the */ /* edges of interest should be the same as the order in which we do so */ /* in the caller function. If the caller function doesn't care about the */ /* order of values in the resulting vector V, then there's no need to take */ /* special notice of that order. But in some cases the order of values in */ /* V is taken into account, for example, in the Moran process. */ S = 0.0; IGRAPH_CHECK(igraph_eit_create(graph, es, &A)); IGRAPH_FINALLY(igraph_eit_destroy, &A); while (!IGRAPH_EIT_END(A)) { e = (igraph_integer_t)IGRAPH_EIT_GET(A); S += (igraph_real_t)VECTOR(*U)[e]; IGRAPH_EIT_NEXT(A); } /* avoid division by zero later on */ if (S == (igraph_real_t)0.0) { igraph_eit_destroy(&A); igraph_es_destroy(&es); IGRAPH_FINALLY_CLEAN(2); IGRAPH_ERROR("Vector of values sums to zero", IGRAPH_EINVAL); } /* Get cumulative probability and relative value for each edge in the */ /* perspective of v. The vector V holds the cumulative proportionate */ /* values of all edges in v's perspective. The value V[0] is the */ /* cumulative proportionate value of the first edge in the edge iterator */ /* A. The value V[1] is the cumulative proportionate value of the second */ /* edge in the iterator A. And so on. */ C = 0.0; i = 0; IGRAPH_EIT_RESET(A); IGRAPH_VECTOR_INIT_FINALLY(V, IGRAPH_EIT_SIZE(A)); while (!IGRAPH_EIT_END(A)) { e = (igraph_integer_t)IGRAPH_EIT_GET(A); /* NOTE: Beware of division by zero here. This can happen if the vector */ /* of values, or the combination of interest, sums to zero. */ P = (igraph_real_t)VECTOR(*U)[e] / S; C += P; VECTOR(*V)[i] = C; i++; IGRAPH_EIT_NEXT(A); } igraph_eit_destroy(&A); igraph_es_destroy(&es); /* Pop V, A and es from the finally stack -- that's three items */ IGRAPH_FINALLY_CLEAN(3); return IGRAPH_SUCCESS; } /* * Internal use only. * Compute the cumulative proportionate values of a vector. The vector is * assumed to hold values associated with vertices. * * \param graph The graph object representing the game network. No error * checks will be performed on this graph. You are responsible for * ensuring that this is a valid graph for the particular * microscopic update rule at hand. * \param U A vector of vertex values for which we want to compute cumulative * proportionate values. The vector could be, for example, a vector of * fitness for vertices of \p graph. It is assumed that each value of U * is nonnegative; it is your responsibility to ensure this. Also U, or * a combination of interest, is assumed to sum to a positive value; * this condition will be checked. * \param V Pointer to an uninitialized vector. The cumulative proportionate * values will be computed and stored here. No error checks will be * performed on this parameter. * \param islocal Boolean; this flag controls which perspective to use. If * true then we use the local perspective; otherwise we use the global * perspective. The local perspective for a vertex v is the set of all * immediate neighbours of v. In contrast, the global perspective * for v is the vertex set of \p graph. * \param vid The vertex to use if we are considering a local perspective, * i.e. if \p islocal is true. This vertex will be ignored if * \p islocal is false. That is, if \p islocal is false then it is safe * pass the value -1 here. On the other hand, if \p islocal is true then * it is assumed that this is indeed a vertex of \p graph. * \param mode Defines the sort of neighbourhood to consider for \p vid. This * is only relevant if we are considering the local perspective, i.e. if * \p islocal is true. If we are considering the global perspective, * then this parameter would be ignored. In other words, if \p islocal * is false then it is safe to pass the value \p IGRAPH_ALL here. If * \p graph is undirected, then we use all the immediate neighbours of * \p vid. Thus if you know that \p graph is undirected, then it is * safe to pass the value \p IGRAPH_ALL here. Supported values are: * \clist * \cli IGRAPH_OUT * Use the out-neighbours of \p vid. This option is only relevant * when \p graph is a digraph and we are considering the local * perspective. * \cli IGRAPH_IN * Use the in-neighbours of \p vid. Again this option is only relevant * when \p graph is a directed graph and we are considering the local * perspective. * \cli IGRAPH_ALL * Use both the in- and out-neighbours of \p vid. This option is only * relevant if \p graph is a digraph and we are considering a local * perspective. Also use this value if \p graph is undirected or we * are considering the global perspective. * \endclist * \return Codes: * \clist * \cli IGRAPH_EINVAL * This error code is returned in the following case: The vector * \p U, or some combination of its values, sums to zero. * \cli IGRAPH_SUCCESS * This signal is returned if the cumulative proportionate values * were successfully computed. * \endclist * * Time complexity: O(2n) where n is the number of vertices in the * perspective of vid. */ int igraph_vcumulative_proportionate_values(const igraph_t *graph, const igraph_vector_t *U, igraph_vector_t *V, igraph_bool_t islocal, igraph_integer_t vid, igraph_neimode_t mode) { igraph_integer_t v; igraph_real_t C; /* cumulative probability */ igraph_real_t P; /* probability */ igraph_real_t S; /* sum of values */ igraph_vit_t A; /* all vertices in v's perspective */ igraph_vs_t vs; long int i; /* Set the perspective. Let v be the vertex under consideration; it might */ /* be that we want to update v's strategy. The local perspective for v */ /* consists of its immediate neighbours. In contrast, the global */ /* perspective for v are all the vertices in the given graph. Hence in the */ /* global perspective, we will ignore the given vertex and the given */ /* neighbourhood type, but instead consider all vertices in the given */ /* graph. */ if (islocal) { IGRAPH_CHECK(igraph_vs_adj(&vs, vid, mode)); } else { IGRAPH_CHECK(igraph_vs_all(&vs)); } IGRAPH_FINALLY(igraph_vs_destroy, &vs); /* Sum up all the values of vector U in the perspective for v. This */ /* sum will be used in normalizing each value. If we are using a local */ /* perspective, then we also need to consider the quantity of v in */ /* computing the sum. */ /* NOTE: Here we assume that each value to be summed is nonnegative, */ /* and at least one of the values is nonzero. The behaviour resulting */ /* from all values being zero would be division by zero later on when */ /* we normalize each value. We check to see that the values sum to zero. */ /* NOTE: In this function, the order in which we iterate through the */ /* vertices of interest should be the same as the order in which we do so */ /* in the caller function. If the caller function doesn't care about the */ /* order of values in the resulting vector V, then there's no need to take */ /* special notice of that order. But in some cases the order of values in */ /* V is taken into account, for example, in roulette wheel selection. */ S = 0.0; IGRAPH_CHECK(igraph_vit_create(graph, vs, &A)); IGRAPH_FINALLY(igraph_vit_destroy, &A); while (!IGRAPH_VIT_END(A)) { v = (igraph_integer_t)IGRAPH_VIT_GET(A); S += (igraph_real_t)VECTOR(*U)[v]; IGRAPH_VIT_NEXT(A); } if (islocal) { S += (igraph_real_t)VECTOR(*U)[vid]; } /* avoid division by zero later on */ if (S == (igraph_real_t)0.0) { igraph_vit_destroy(&A); igraph_vs_destroy(&vs); IGRAPH_FINALLY_CLEAN(2); IGRAPH_ERROR("Vector of values sums to zero", IGRAPH_EINVAL); } /* Get cumulative probability and relative value for each vertex in the */ /* perspective of v. The vector V holds the cumulative proportionate */ /* values of all vertices in v's perspective. The value V[0] is the */ /* cumulative proportionate value of the first vertex in the vertex */ /* iterator A. The value V[1] is the cumulative proportionate value of */ /* the second vertex in the iterator A. And so on. If we are using the */ /* local perspective, then we also need to consider the cumulative */ /* proportionate value of v. In the case of the local perspective, we */ /* don't need to compute and store v's cumulative proportionate value, */ /* but we pretend that such value is appended to the vector V. */ C = 0.0; i = 0; IGRAPH_VIT_RESET(A); IGRAPH_VECTOR_INIT_FINALLY(V, IGRAPH_VIT_SIZE(A)); while (!IGRAPH_VIT_END(A)) { v = (igraph_integer_t)IGRAPH_VIT_GET(A); /* NOTE: Beware of division by zero here. This can happen if the vector */ /* of values, or a combination of interest, sums to zero. */ P = (igraph_real_t)VECTOR(*U)[v] / S; C += P; VECTOR(*V)[i] = C; i++; IGRAPH_VIT_NEXT(A); } igraph_vit_destroy(&A); igraph_vs_destroy(&vs); /* Pop V, A and vs from the finally stack -- that's three items */ IGRAPH_FINALLY_CLEAN(3); return IGRAPH_SUCCESS; } /* * Internal use only. * A set of standard tests to be performed prior to strategy updates. The * tests contained in this function are common to many strategy revision * functions in this file. This function is meant to be invoked from within * a specific strategy update function in order to perform certain common * tests, including sanity checks and conditions under which no strategy * updates are necessary. * * \param graph The graph object representing the game network. This cannot * be the empty or trivial graph, but must have at least two vertices * and one edge. If \p graph has one vertex, then no strategy update * would take place. Furthermore, if \p graph has at least two vertices * but zero edges, then strategy update would also not take place. * \param vid The vertex whose strategy is to be updated. It is assumed that * \p vid represents a vertex in \p graph. No checking is performed and * it is your responsibility to ensure that \p vid is indeed a vertex * of \p graph. If an isolated vertex is provided, i.e. the input * vertex has degree 0, then no strategy update would take place and * \p vid would retain its current strategy. Strategy update would also * not take place if the local neighbourhood of \p vid are its * in-neighbours (respectively out-neighbours), but \p vid has zero * in-neighbours (respectively out-neighbours). Loops are ignored in * computing the degree (in, out, all) of \p vid. * \param quantities A vector of quantities providing the quantity of each * vertex in \p graph. Think of each entry of the vector as being * generated by a function such as the fitness function for the game. * So if the vector represents fitness quantities, then each vector * entry is the fitness of some vertex. The length of this vector must * be the same as the number of vertices in the vertex set of \p graph. * \param strategies A vector of the current strategies for the vertex * population. Each strategy is identified with a nonnegative integer, * whose interpretation depends on the payoff matrix of the game. * Generally we use the strategy ID as a row or column index of the * payoff matrix. The length of this vector must be the same as the * number of vertices in the vertex set of \p graph. * \param mode Defines the sort of neighbourhood to consider for \p vid. If * \p graph is undirected, then we use all the immediate neighbours of * \p vid. Thus if you know that \p graph is undirected, then it is safe * to pass the value \p IGRAPH_ALL here. Supported values are: * \clist * \cli IGRAPH_OUT * Use the out-neighbours of \p vid. This option is only relevant * when \p graph is a directed graph. * \cli IGRAPH_IN * Use the in-neighbours of \p vid. Again this option is only relevant * when \p graph is a directed graph. * \cli IGRAPH_ALL * Use both the in- and out-neighbours of \p vid. This option is only * relevant if \p graph is a digraph. Also use this value if * \p graph is undirected. * \endclist * \param updates Boolean; at the end of this test suite, this flag * indicates whether to proceed with strategy revision. If true then * strategy revision should proceed; otherwise there is no need to * continue with revising a vertex's strategy. A caller function that * invokes this function would use the value of \p updates to * determine whether to proceed with strategy revision. * \param islocal Boolean; this flag controls which perspective to use. If * true then we use the local perspective; otherwise we use the global * perspective. The local perspective for \p vid is the set of all * immediate neighbours of \p vid. In contrast, the global perspective * for \p vid is the vertex set of \p graph. * \return Codes: * \clist * \cli IGRAPH_EINVAL * This error code is returned in each of the following cases: * (1) Any of the parameters \p graph, \p quantities, or * \p strategies is a null pointer. (2) The vector \p quantities * or \p strategies has a length different from the number of * vertices in \p graph. (3) The parameter \p graph is the empty * or null graph, i.e. the graph with zero vertices and edges. * \cli IGRAPH_SUCCESS * This signal is returned if no errors were raised. You should use * the value of the boolean \p updates to decide whether to go * ahead with updating a vertex's strategy. * \endclist */ int igraph_microscopic_standard_tests(const igraph_t *graph, igraph_integer_t vid, const igraph_vector_t *quantities, const igraph_vector_t *strategies, igraph_neimode_t mode, igraph_bool_t *updates, igraph_bool_t islocal) { igraph_integer_t nvert; igraph_vector_t degv; *updates = 1; /* sanity checks */ if (graph == NULL) { IGRAPH_ERROR("Graph is a null pointer", IGRAPH_EINVAL); } if (quantities == NULL) { IGRAPH_ERROR("Quantities vector is a null pointer", IGRAPH_EINVAL); } if (strategies == NULL) { IGRAPH_ERROR("Strategies vector is a null pointer", IGRAPH_EINVAL); } /* the empty graph */ nvert = igraph_vcount(graph); if (nvert < 1) { IGRAPH_ERROR("Graph cannot be the empty graph", IGRAPH_EINVAL); } /* invalid vector length */ if (nvert != (igraph_integer_t)igraph_vector_size(quantities)) { IGRAPH_ERROR("Size of quantities vector different from number of vertices", IGRAPH_EINVAL); } if (nvert != (igraph_integer_t)igraph_vector_size(strategies)) { IGRAPH_ERROR("Size of strategies vector different from number of vertices", IGRAPH_EINVAL); } /* Various conditions under which no strategy updates will take place. That * is, the vertex retains its current strategy. */ /* given graph has < 2 vertices */ if (nvert < 2) { *updates = 0; } /* graph has >= 2 vertices, but no edges */ if (igraph_ecount(graph) < 1) { *updates = 0; } /* Test for vertex isolation, depending on the perspective given. For * undirected graphs, a given vertex v is isolated if its degree is zero. * If we are considering in-neighbours (respectively out-neighbours), then * we say that v is isolated if its in-degree (respectively out-degree) is * zero. In general, this vertex isolation test is only relevant if we are * using a local perspective, i.e. if we only consider the immediate * neighbours (local perspective) of v as opposed to all vertices in the * vertex set of the graph (global perspective). */ if (islocal) { /* Moving on ahead with vertex isolation test, since local perspective */ /* is requested. */ IGRAPH_VECTOR_INIT_FINALLY(°v, 1); IGRAPH_CHECK(igraph_degree(graph, °v, igraph_vss_1(vid), mode, IGRAPH_NO_LOOPS)); if (VECTOR(degv)[0] < 1) { *updates = 0; } igraph_vector_destroy(°v); IGRAPH_FINALLY_CLEAN(1); } return IGRAPH_SUCCESS; } /** * \ingroup spatialgames * \function igraph_deterministic_optimal_imitation * \brief Adopt a strategy via deterministic optimal imitation. * * A simple deterministic imitation strategy where a vertex revises its * strategy to that which yields a local optimal. Here "local" is with * respect to the immediate neighbours of the vertex. The vertex retains its * current strategy where this strategy yields a locally optimal quantity. * The quantity in this case could be a measure such as fitness. * * \param graph The graph object representing the game network. This cannot * be the empty or trivial graph, but must have at least two vertices * and one edge. If \p graph has one vertex, then no strategy update * would take place. Furthermore, if \p graph has at least two vertices * but zero edges, then strategy update would also not take place. * \param vid The vertex whose strategy is to be updated. It is assumed that * \p vid represents a vertex in \p graph. No checking is performed and * it is your responsibility to ensure that \p vid is indeed a vertex * of \p graph. If an isolated vertex is provided, i.e. the input * vertex has degree 0, then no strategy update would take place and * \p vid would retain its current strategy. Strategy update would also * not take place if the local neighbourhood of \p vid are its * in-neighbours (respectively out-neighbours), but \p vid has zero * in-neighbours (respectively out-neighbours). Loops are ignored in * computing the degree (in, out, all) of \p vid. * \param optimality Logical; controls the type of optimality to be used. * Supported values are: * \clist * \cli IGRAPH_MAXIMUM * Use maximum deterministic imitation, where the strategy of the * vertex with maximum quantity (e.g. fitness) would be adopted. We * update the strategy of \p vid to that which yields a local * maximum. * \cli IGRAPH_MINIMUM * Use minimum deterministic imitation. That is, the strategy of the * vertex with minimum quantity would be imitated. In other words, * update to the strategy that yields a local minimum. * \endclist * \param quantities A vector of quantities providing the quantity of each * vertex in \p graph. Think of each entry of the vector as being * generated by a function such as the fitness function for the game. * So if the vector represents fitness quantities, then each vector * entry is the fitness of some vertex. The length of this vector must * be the same as the number of vertices in the vertex set of \p graph. * \param strategies A vector of the current strategies for the vertex * population. The updated strategy for \p vid would be stored here. * Each strategy is identified with a nonnegative integer, whose * interpretation depends on the payoff matrix of the game. Generally * we use the strategy ID as a row or column index of the payoff * matrix. The length of this vector must be the same as the number of * vertices in the vertex set of \p graph. * \param mode Defines the sort of neighbourhood to consider for \p vid. If * \p graph is undirected, then we use all the immediate neighbours of * \p vid. Thus if you know that \p graph is undirected, then it is safe * to pass the value \p IGRAPH_ALL here. Supported values are: * \clist * \cli IGRAPH_OUT * Use the out-neighbours of \p vid. This option is only relevant * when \p graph is a directed graph. * \cli IGRAPH_IN * Use the in-neighbours of \p vid. Again this option is only relevant * when \p graph is a directed graph. * \cli IGRAPH_ALL * Use both the in- and out-neighbours of \p vid. This option is only * relevant if \p graph is a digraph. Also use this value if * \p graph is undirected. * \endclist * \return The error code \p IGRAPH_EINVAL is returned in each of the * following cases: (1) Any of the parameters \p graph, \p quantities, * or \p strategies is a null pointer. (2) The vector \p quantities * or \p strategies has a length different from the number of vertices * in \p graph. (3) The parameter \p graph is the empty or null graph, * i.e. the graph with zero vertices and edges. * * Time complexity: O(2d), where d is the degree of the vertex \p vid. * * \example examples/simple/igraph_deterministic_optimal_imitation.c */ int igraph_deterministic_optimal_imitation(const igraph_t *graph, igraph_integer_t vid, igraph_optimal_t optimality, const igraph_vector_t *quantities, igraph_vector_t *strategies, igraph_neimode_t mode) { igraph_integer_t i, k, v; igraph_real_t q; igraph_vector_t adj; igraph_bool_t updates; IGRAPH_CHECK(igraph_microscopic_standard_tests(graph, vid, quantities, strategies, mode, &updates, /*is local?*/ 1)); if (!updates) { return IGRAPH_SUCCESS; /* Nothing to do */ } /* Choose a locally optimal strategy to imitate. This can be either maximum * or minimum deterministic imitation. By now we know that the given vertex v * has degree >= 1 and at least 1 edge. Then within its immediate * neighbourhood adj(v) and including v itself, there exists a vertex whose * strategy yields a local optimal quantity. */ /* Random permutation of adj(v). This ensures that if there are multiple */ /* candidates with an optimal strategy, then we choose one such candidate */ /* at random. */ IGRAPH_VECTOR_INIT_FINALLY(&adj, 0); IGRAPH_CHECK(igraph_neighbors(graph, &adj, vid, mode)); IGRAPH_CHECK(igraph_vector_shuffle(&adj)); /* maximum deterministic imitation */ i = vid; q = (igraph_real_t)VECTOR(*quantities)[vid]; if (optimality == IGRAPH_MAXIMUM) { for (k = 0; k < igraph_vector_size(&adj); k++) { v = (igraph_integer_t) VECTOR(adj)[k]; if ((igraph_real_t)VECTOR(*quantities)[v] > q) { i = v; q = (igraph_real_t)VECTOR(*quantities)[v]; } } } else { /* minimum deterministic imitation */ for (k = 0; k < igraph_vector_size(&adj); k++) { v = (igraph_integer_t) VECTOR(adj)[k]; if ((igraph_real_t)VECTOR(*quantities)[v] < q) { i = v; q = (igraph_real_t)VECTOR(*quantities)[v]; } } } /* Now i is a vertex with a locally optimal quantity, the value of which */ /* is q. Update the strategy of vid to that of i. */ VECTOR(*strategies)[vid] = VECTOR(*strategies)[i]; igraph_vector_destroy(&adj); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } /** * \ingroup spatialgames * \function igraph_moran_process * \brief The Moran process in a network setting. * * This is an extension of the classic Moran process to a network setting. * The Moran process is a model of haploid (asexual) reproduction within a * population having a fixed size. In the network setting, the Moran process * operates on a weighted graph. At each time step a vertex a is chosen for * reproduction and another vertex b is chosen for death. Vertex a gives birth * to an identical clone c, which replaces b. Vertex c is a clone of a in that * c inherits both the current quantity (e.g. fitness) and current strategy * of a. * * * The graph G representing the game network is assumed to be simple, * i.e. free of loops and without multiple edges. If, on the other hand, G has * a loop incident on some vertex v, then it is possible that when v is chosen * for reproduction it would forgo this opportunity. In particular, when v is * chosen for reproduction and v is also chosen for death, the clone of v * would be v itself with its current vertex ID. In effect v forgoes its * chance for reproduction. * * \param graph The graph object representing the game network. This cannot * be the empty or trivial graph, but must have at least two vertices * and one edge. The Moran process will not take place in each of the * following cases: (1) If \p graph has one vertex. (2) If \p graph has * at least two vertices but zero edges. * \param weights A vector of all edge weights for \p graph. Thus weights[i] * means the weight of the edge with edge ID i. For the purpose of the * Moran process, each weight is assumed to be positive; it is your * responsibility to ensure this condition holds. The length of this * vector must be the same as the number of edges in \p graph. * \param quantities A vector of quantities providing the quantity of each * vertex in \p graph. The quantity of the new clone will be stored * here. Think of each entry of the vector as being generated by a * function such as the fitness function for the game. So if the vector * represents fitness quantities, then each vector entry is the fitness * of some vertex. The length of this vector must be the same as the * number of vertices in the vertex set of \p graph. For the purpose of * the Moran process, each vector entry is assumed to be nonnegative; * no checks will be performed for this. It is your responsibility to * ensure that at least one entry is positive. Furthermore, this vector * cannot be a vector of zeros; this condition will be checked. * \param strategies A vector of the current strategies for the vertex * population. The strategy of the new clone will be stored here. Each * strategy is identified with a nonnegative integer, whose * interpretation depends on the payoff matrix of the game. Generally * we use the strategy ID as a row or column index of the payoff * matrix. The length of this vector must be the same as the number of * vertices in the vertex set of \p graph. * \param mode Defines the sort of neighbourhood to consider for the vertex a * chosen for reproduction. This is only relevant if \p graph is * directed. If \p graph is undirected, then it is safe to pass the * value \p IGRAPH_ALL here. Supported values are: * \clist * \cli IGRAPH_OUT * Use the out-neighbours of a. This option is only relevant when * \p graph is directed. * \cli IGRAPH_IN * Use the in-neighbours of a. Again this option is only relevant * when \p graph is directed. * \cli IGRAPH_ALL * Use both the in- and out-neighbours of a. This option is only * relevant if \p graph is directed. Also use this value if * \p graph is undirected. * \endclist * \return The error code \p IGRAPH_EINVAL is returned in each of the following * cases: (1) Any of the parameters \p graph, \p weights, * \p quantities or \p strategies is a null pointer. (2) The vector * \p quantities or \p strategies has a length different from the * number of vertices in \p graph. (3) The vector \p weights has a * length different from the number of edges in \p graph. (4) The * parameter \p graph is the empty or null graph, i.e. the graph with * zero vertices and edges. (5) The vector \p weights, or the * combination of interest, sums to zero. (6) The vector \p quantities, * or the combination of interest, sums to zero. * * Time complexity: depends on the random number generator, but is usually * O(n) where n is the number of vertices in \p graph. * * * References: * \clist * \cli (Lieberman et al. 2005) * E. Lieberman, C. Hauert, and M. A. Nowak. Evolutionary dynamics on * graphs. \emb Nature, \eme 433(7023):312--316, 2005. * \cli (Moran 1958) * P. A. P. Moran. Random processes in genetics. \emb Mathematical * Proceedings of the Cambridge Philosophical Society, \eme 54(1):60--71, * 1958. * \endclist * * \example examples/simple/igraph_moran_process.c */ int igraph_moran_process(const igraph_t *graph, const igraph_vector_t *weights, igraph_vector_t *quantities, igraph_vector_t *strategies, igraph_neimode_t mode) { igraph_bool_t updates; igraph_integer_t a = -1; /* vertex chosen for reproduction */ igraph_integer_t b = -1; /* vertex chosen for death */ igraph_integer_t e, nedge, u, v; igraph_real_t r; /* random number */ igraph_vector_t deg; igraph_vector_t V; /* vector of cumulative proportionate values */ igraph_vit_t vA; /* vertex list */ igraph_eit_t eA; /* edge list */ igraph_vs_t vs; igraph_es_t es; long int i; /* don't test for vertex isolation, hence vid = -1 and islocal = 0 */ IGRAPH_CHECK(igraph_microscopic_standard_tests(graph, /*vid*/ -1, quantities, strategies, mode, &updates, /*is local?*/ 0)); if (!updates) { return IGRAPH_SUCCESS; /* nothing more to do */ } if (weights == NULL) { IGRAPH_ERROR("Weights vector is a null pointer", IGRAPH_EINVAL); } nedge = igraph_ecount(graph); if (nedge != (igraph_integer_t)igraph_vector_size(weights)) { IGRAPH_ERROR("Size of weights vector different from number of edges", IGRAPH_EINVAL); } /* Cumulative proportionate quantities. We are using the global */ /* perspective, hence islocal = 0, vid = -1 and mode = IGRAPH_ALL. */ IGRAPH_CHECK(igraph_vcumulative_proportionate_values(graph, quantities, &V, /*is local?*/ 0, /*vid*/ -1, /*mode*/ IGRAPH_ALL)); /* Choose a vertex for reproduction from among all vertices in the graph. */ /* The vertex is chosen proportionate to its quantity and such that its */ /* degree is >= 1. In case we are considering in-neighbours (respectively */ /* out-neighbours), the chosen vertex must have in-degree (respectively */ /* out-degree) >= 1. All loops will be ignored. At this point, we know */ /* that the graph has at least one edge, which may be directed or not. */ /* Furthermore the quantities of all vertices sum to a positive value. */ /* Hence at least one vertex will be chosen for reproduction. */ IGRAPH_CHECK(igraph_vs_all(&vs)); IGRAPH_FINALLY(igraph_vs_destroy, &vs); IGRAPH_CHECK(igraph_vit_create(graph, vs, &vA)); IGRAPH_FINALLY(igraph_vit_destroy, &vA); RNG_BEGIN(); r = RNG_UNIF01(); RNG_END(); i = 0; IGRAPH_VECTOR_INIT_FINALLY(°, 1); while (!IGRAPH_VIT_END(vA)) { u = (igraph_integer_t)IGRAPH_VIT_GET(vA); IGRAPH_CHECK(igraph_degree(graph, °, igraph_vss_1(u), mode, IGRAPH_NO_LOOPS)); if (VECTOR(deg)[0] < 1) { i++; IGRAPH_VIT_NEXT(vA); continue; } if (r <= VECTOR(V)[i]) { /* we have found our candidate vertex for reproduction */ a = u; break; } i++; IGRAPH_VIT_NEXT(vA); } /* By now we should have chosen a vertex for reproduction. Check this. */ assert(a >= 0); /* Cumulative proportionate weights. We are using the local perspective */ /* with respect to vertex a, which has been chosen for reproduction. */ /* The degree of a is deg(a) >= 1 with respect to the mode "mode", which */ /* can flag either the in-degree, out-degree or all degree of a. But it */ /* still might happen that the edge weights of interest would sum to zero. */ /* An error would be raised in that case. */ igraph_vector_destroy(&V); IGRAPH_CHECK(igraph_ecumulative_proportionate_values(graph, weights, &V, /*is local?*/ 1, /*vertex*/ a, mode)); /* Choose a vertex for death from among all vertices in a's perspective. */ /* Let E be all the edges in the perspective of a. If (u,v) \in E is any */ /* such edge, then we have a = u or a = v. That is, any edge in E has a */ /* for one of its endpoints. As G is assumed to be a simple graph, then */ /* exactly one of u or v is the vertex a. Without loss of generality, we */ /* assume that each edge in E has the form (a, v_i). Then the vertex v_j */ /* chosen for death is chosen proportionate to the weight of the edge */ /* (a, v_j). */ IGRAPH_CHECK(igraph_es_incident(&es, a, mode)); IGRAPH_FINALLY(igraph_es_destroy, &es); IGRAPH_CHECK(igraph_eit_create(graph, es, &eA)); IGRAPH_FINALLY(igraph_eit_destroy, &eA); RNG_BEGIN(); r = RNG_UNIF01(); RNG_END(); i = 0; while (!IGRAPH_EIT_END(eA)) { e = (igraph_integer_t)IGRAPH_EIT_GET(eA); if (r <= VECTOR(V)[i]) { /* We have found our candidate vertex for death; call this vertex b. */ /* As G is simple, then a =/= b. Check the latter condition. */ IGRAPH_CHECK(igraph_edge(graph, /*edge ID*/ e, /*tail vertex*/ &u, /*head vertex*/ &v)); if (a == u) { b = v; } else { b = u; } assert(a != b); /* always true if G is simple */ break; } i++; IGRAPH_EIT_NEXT(eA); } /* By now a vertex a is chosen for reproduction and a vertex b is chosen */ /* for death. Check that b has indeed been chosen. Clone vertex a and kill */ /* vertex b. Let the clone c have the vertex ID of b, and the strategy and */ /* quantity of a. */ assert(b >= 0); VECTOR(*quantities)[b] = VECTOR(*quantities)[a]; VECTOR(*strategies)[b] = VECTOR(*strategies)[a]; igraph_vector_destroy(°); igraph_vector_destroy(&V); igraph_vit_destroy(&vA); igraph_eit_destroy(&eA); igraph_vs_destroy(&vs); igraph_es_destroy(&es); IGRAPH_FINALLY_CLEAN(6); return IGRAPH_SUCCESS; } /** * \ingroup spatialgames * \function igraph_roulette_wheel_imitation * \brief Adopt a strategy via roulette wheel selection. * * A simple stochastic imitation strategy where a vertex revises its * strategy to that of a vertex u chosen proportionate to u's quantity * (e.g. fitness). This is a special case of stochastic imitation, where a * candidate is not chosen uniformly at random but proportionate to its * quantity. * * \param graph The graph object representing the game network. This cannot * be the empty or trivial graph, but must have at least two vertices * and one edge. If \p graph has one vertex, then no strategy update * would take place. Furthermore, if \p graph has at least two vertices * but zero edges, then strategy update would also not take place. * \param vid The vertex whose strategy is to be updated. It is assumed that * \p vid represents a vertex in \p graph. No checking is performed and * it is your responsibility to ensure that \p vid is indeed a vertex * of \p graph. If an isolated vertex is provided, i.e. the input * vertex has degree 0, then no strategy update would take place and * \p vid would retain its current strategy. Strategy update would also * not take place if the local neighbourhood of \p vid are its * in-neighbours (respectively out-neighbours), but \p vid has zero * in-neighbours (respectively out-neighbours). Loops are ignored in * computing the degree (in, out, all) of \p vid. * \param islocal Boolean; this flag controls which perspective to use in * computing the relative quantity. If true then we use the local * perspective; otherwise we use the global perspective. The local * perspective for \p vid is the set of all immediate neighbours of * \p vid. In contrast, the global perspective for \p vid is the * vertex set of \p graph. * \param quantities A vector of quantities providing the quantity of each * vertex in \p graph. Think of each entry of the vector as being * generated by a function such as the fitness function for the game. * So if the vector represents fitness quantities, then each vector * entry is the fitness of some vertex. The length of this vector must * be the same as the number of vertices in the vertex set of \p graph. * For the purpose of roulette wheel selection, each vector entry is * assumed to be nonnegative; no checks will be performed for this. It * is your responsibility to ensure that at least one entry is nonzero. * Furthermore, this vector cannot be a vector of zeros; this condition * will be checked. * \param strategies A vector of the current strategies for the vertex * population. The updated strategy for \p vid would be stored here. * Each strategy is identified with a nonnegative integer, whose * interpretation depends on the payoff matrix of the game. Generally * we use the strategy ID as a row or column index of the payoff * matrix. The length of this vector must be the same as the number of * vertices in the vertex set of \p graph. * \param mode Defines the sort of neighbourhood to consider for \p vid. This * is only relevant if we are considering the local perspective, i.e. if * \p islocal is true. If we are considering the global perspective, * then it is safe to pass the value \p IGRAPH_ALL here. If \p graph is * undirected, then we use all the immediate neighbours of \p vid. Thus * if you know that \p graph is undirected, then it is safe to pass the * value \p IGRAPH_ALL here. Supported values are: * \clist * \cli IGRAPH_OUT * Use the out-neighbours of \p vid. This option is only relevant * when \p graph is a digraph and we are considering the local * perspective. * \cli IGRAPH_IN * Use the in-neighbours of \p vid. Again this option is only relevant * when \p graph is a directed graph and we are considering the local * perspective. * \cli IGRAPH_ALL * Use both the in- and out-neighbours of \p vid. This option is only * relevant if \p graph is a digraph. Also use this value if * \p graph is undirected or we are considering the global * perspective. * \endclist * \return The error code \p IGRAPH_EINVAL is returned in each of the following * cases: (1) Any of the parameters \p graph, \p quantities, or * \p strategies is a null pointer. (2) The vector \p quantities or * \p strategies has a length different from the number of vertices * in \p graph. (3) The parameter \p graph is the empty or null graph, * i.e. the graph with zero vertices and edges. (4) The vector * \p quantities sums to zero. * * Time complexity: O(n) where n is the number of vertices in the perspective * to consider. If we consider the global perspective, then n is the number * of vertices in the vertex set of \p graph. On the other hand, for the local * perspective n is the degree of \p vid, excluding loops. * * * Reference: * \clist * \cli (Yu & Gen 2010) * X. Yu and M. Gen. \emb Introduction to Evolutionary Algorithms. \eme * Springer, 2010, pages 18--20. * \endclist * * \example examples/simple/igraph_roulette_wheel_imitation.c */ int igraph_roulette_wheel_imitation(const igraph_t *graph, igraph_integer_t vid, igraph_bool_t islocal, const igraph_vector_t *quantities, igraph_vector_t *strategies, igraph_neimode_t mode) { igraph_bool_t updates; igraph_integer_t u; igraph_real_t r; /* random number */ igraph_vector_t V; /* vector of cumulative proportionate quantities */ igraph_vit_t A; /* all vertices in v's perspective */ igraph_vs_t vs; long int i; IGRAPH_CHECK(igraph_microscopic_standard_tests(graph, vid, quantities, strategies, mode, &updates, islocal)); if (!updates) { return IGRAPH_SUCCESS; /* nothing further to do */ } /* set the perspective */ if (islocal) { IGRAPH_CHECK(igraph_vs_adj(&vs, vid, mode)); } else { IGRAPH_CHECK(igraph_vs_all(&vs)); } IGRAPH_FINALLY(igraph_vs_destroy, &vs); IGRAPH_CHECK(igraph_vit_create(graph, vs, &A)); IGRAPH_FINALLY(igraph_vit_destroy, &A); IGRAPH_CHECK(igraph_vcumulative_proportionate_values(graph, quantities, &V, islocal, vid, mode)); /* Finally, choose a vertex u to imitate. The vertex u is chosen */ /* proportionate to its quantity. In the case of a local perspective, we */ /* pretend that v's cumulative proportionate quantity has been appended to */ /* the vector V. Let V be of length n so that V[n-1] is the last element */ /* of V, and let r be a real number chosen uniformly at random from the */ /* unit interval [0,1]. If r > V[i] for all i < n, then v defaults to */ /* retaining its current strategy. Similarly in the case of the global */ /* perspective, if r > V[i] for all i < n - 1 then v would adopt the */ /* strategy of the vertex whose cumulative proportionate quantity is */ /* V[n-1]. */ /* NOTE: Here we assume that the order in which we iterate through the */ /* vertices in A is the same as the order in which we do so in the */ /* invoked function igraph_vcumulative_proportionate_values(). */ /* Otherwise we would incorrectly associate each V[i] with a vertex in A. */ RNG_BEGIN(); r = RNG_UNIF01(); RNG_END(); i = 0; while (!IGRAPH_VIT_END(A)) { if (r <= VECTOR(V)[i]) { /* We have found our candidate vertex for imitation. Update strategy */ /* of v to that of u, and exit the selection loop. */ u = (igraph_integer_t)IGRAPH_VIT_GET(A); VECTOR(*strategies)[vid] = VECTOR(*strategies)[u]; break; } i++; IGRAPH_VIT_NEXT(A); } /* By now, vertex v should either retain its current strategy or it has */ /* adopted the strategy of a vertex in its perspective. Nothing else to */ /* do, but clean up. */ igraph_vector_destroy(&V); igraph_vit_destroy(&A); igraph_vs_destroy(&vs); IGRAPH_FINALLY_CLEAN(3); return IGRAPH_SUCCESS; } /** * \ingroup spatialgames * \function igraph_stochastic_imitation * \brief Adopt a strategy via stochastic imitation with uniform selection. * * A simple stochastic imitation strategy where a vertex revises its * strategy to that of a vertex chosen uniformly at random from its local * neighbourhood. This is called stochastic imitation via uniform selection, * where the strategy to imitate is chosen via some random process. For the * purposes of this function, we use uniform selection from a pool of * candidates. * * \param graph The graph object representing the game network. This cannot * be the empty or trivial graph, but must have at least two vertices * and one edge. If \p graph has one vertex, then no strategy update * would take place. Furthermore, if \p graph has at least two vertices * but zero edges, then strategy update would also not take place. * \param vid The vertex whose strategy is to be updated. It is assumed that * \p vid represents a vertex in \p graph. No checking is performed and * it is your responsibility to ensure that \p vid is indeed a vertex * of \p graph. If an isolated vertex is provided, i.e. the input * vertex has degree 0, then no strategy update would take place and * \p vid would retain its current strategy. Strategy update would also * not take place if the local neighbourhood of \p vid are its * in-neighbours (respectively out-neighbours), but \p vid has zero * in-neighbours (respectively out-neighbours). Loops are ignored in * computing the degree (in, out, all) of \p vid. * \param algo This flag controls which algorithm to use in stochastic * imitation. Supported values are: * \clist * \cli IGRAPH_IMITATE_AUGMENTED * Augmented imitation. Vertex \p vid imitates the strategy of the * chosen vertex u provided that doing so would increase the * quantity (e.g. fitness) of \p vid. Augmented imitation can be * thought of as "imitate if better". * \cli IGRAPH_IMITATE_BLIND * Blind imitation. Vertex \p vid blindly imitates the strategy of * the chosen vertex u, regardless of whether doing so would * increase or decrease the quantity of \p vid. * \cli IGRAPH_IMITATE_CONTRACTED * Contracted imitation. Here vertex \p vid imitates the strategy of * the chosen vertex u if doing so would decrease the quantity of * \p vid. Think of contracted imitation as "imitate if worse". * \endclist * \param quantities A vector of quantities providing the quantity of each * vertex in \p graph. Think of each entry of the vector as being * generated by a function such as the fitness function for the game. * So if the vector represents fitness quantities, then each vector * entry is the fitness of some vertex. The length of this vector must * be the same as the number of vertices in the vertex set of \p graph. * \param strategies A vector of the current strategies for the vertex * population. The updated strategy for \p vid would be stored here. * Each strategy is identified with a nonnegative integer, whose * interpretation depends on the payoff matrix of the game. Generally * we use the strategy ID as a row or column index of the payoff * matrix. The length of this vector must be the same as the number of * vertices in the vertex set of \p graph. * \param mode Defines the sort of neighbourhood to consider for \p vid. If * \p graph is undirected, then we use all the immediate neighbours of * \p vid. Thus if you know that \p graph is undirected, then it is safe * to pass the value \p IGRAPH_ALL here. Supported values are: * \clist * \cli IGRAPH_OUT * Use the out-neighbours of \p vid. This option is only relevant * when \p graph is a directed graph. * \cli IGRAPH_IN * Use the in-neighbours of \p vid. Again this option is only relevant * when \p graph is a directed graph. * \cli IGRAPH_ALL * Use both the in- and out-neighbours of \p vid. This option is only * relevant if \p graph is a digraph. Also use this value if * \p graph is undirected. * \endclist * \return The error code \p IGRAPH_EINVAL is returned in each of the following * cases: (1) Any of the parameters \p graph, \p quantities, or * \p strategies is a null pointer. (2) The vector \p quantities or * \p strategies has a length different from the number of vertices * in \p graph. (3) The parameter \p graph is the empty or null graph, * i.e. the graph with zero vertices and edges. (4) The parameter * \p algo refers to an unsupported stochastic imitation algorithm. * * Time complexity: depends on the uniform random number generator, but should * usually be O(1). * * \example examples/simple/igraph_stochastic_imitation.c */ int igraph_stochastic_imitation(const igraph_t *graph, igraph_integer_t vid, igraph_imitate_algorithm_t algo, const igraph_vector_t *quantities, igraph_vector_t *strategies, igraph_neimode_t mode) { igraph_bool_t updates; igraph_integer_t u; igraph_vector_t adj; int i; /* sanity checks */ if (algo != IGRAPH_IMITATE_AUGMENTED && algo != IGRAPH_IMITATE_BLIND && algo != IGRAPH_IMITATE_CONTRACTED) { IGRAPH_ERROR("Unsupported stochastic imitation algorithm", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_microscopic_standard_tests(graph, vid, quantities, strategies, mode, &updates, /*is local?*/ 1)); if (!updates) { return IGRAPH_SUCCESS; /* nothing more to do */ } /* immediate neighbours of v */ IGRAPH_VECTOR_INIT_FINALLY(&adj, 0); IGRAPH_CHECK(igraph_neighbors(graph, &adj, vid, mode)); /* Blind imitation. Let v be the vertex whose strategy we want to revise. */ /* Choose a vertex u uniformly at random from the immediate neighbours of */ /* v, including v itself. Then blindly update the strategy of v to that of */ /* u, irrespective of whether doing so would increase or decrease the */ /* quantity (e.g. fitness) of v. Here v retains its current strategy if */ /* the chosen vertex u is indeed v itself. */ if (algo == IGRAPH_IMITATE_BLIND) { IGRAPH_CHECK(igraph_vector_push_back(&adj, vid)); RNG_BEGIN(); i = (int) RNG_INTEGER(0, igraph_vector_size(&adj) - 1); RNG_END(); u = (igraph_integer_t) VECTOR(adj)[i]; VECTOR(*strategies)[vid] = VECTOR(*strategies)[u]; } /* Augmented imitation. Let v be the vertex whose strategy we want to */ /* revise. Let f be the quantity function for the game. Choose a vertex u */ /* uniformly at random from the immediate neighbours of v; do not include */ /* v. Then v imitates the strategy of u if f(u) > f(v). Otherwise v */ /* retains its current strategy. */ else if (algo == IGRAPH_IMITATE_AUGMENTED) { RNG_BEGIN(); i = (int) RNG_INTEGER(0, igraph_vector_size(&adj) - 1); RNG_END(); u = (igraph_integer_t) VECTOR(adj)[i]; if (VECTOR(*quantities)[u] > VECTOR(*quantities)[vid]) { VECTOR(*strategies)[vid] = VECTOR(*strategies)[u]; } } /* Contracted imitation. Let v be the vertex whose strategy we want to */ /* update and let f be the quantity function for the game. Choose a vertex */ /* u uniformly at random from the immediate neighbours of v, excluding v */ /* itself. Then v imitates the strategy of u provided that f(u) < f(v). */ /* Otherwise v retains its current strategy. */ else if (algo == IGRAPH_IMITATE_CONTRACTED) { RNG_BEGIN(); i = (int) RNG_INTEGER(0, igraph_vector_size(&adj) - 1); RNG_END(); u = (igraph_integer_t) VECTOR(adj)[i]; if (VECTOR(*quantities)[u] < VECTOR(*quantities)[vid]) { VECTOR(*strategies)[vid] = VECTOR(*strategies)[u]; } } /* clean up */ igraph_vector_destroy(&adj); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } python-igraph-0.8.0/vendor/source/igraph/src/igraph_math.h0000644000076500000240000000505613614300625024040 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2008-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_MATH_H #define IGRAPH_MATH_H #include "config.h" #include #include #undef __BEGIN_DECLS #undef __END_DECLS #ifdef __cplusplus #define __BEGIN_DECLS extern "C" { #define __END_DECLS } #else #define __BEGIN_DECLS /* empty */ #define __END_DECLS /* empty */ #endif __BEGIN_DECLS /** * \def IGRAPH_SHORTEST_PATH_EPSILON * * Relative error threshold used in weighted shortest path calculations * to decide whether two shortest paths are of equal length. */ #define IGRAPH_SHORTEST_PATH_EPSILON 1e-10 /* * Compiler-related hacks, mostly because of Microsoft Visual C++ */ double igraph_i_round(double X); int igraph_i_snprintf(char *buffer, size_t count, const char *format, ...); double igraph_log2(const double a); double igraph_log1p(double a); long double igraph_fabsl(long double a); double igraph_fmin(double a, double b); #ifndef HAVE_LOG2 #define log2(a) igraph_log2(a) #endif #ifndef HAVE_LOG1P #define log1p(a) igraph_log1p(a) #endif #ifndef HAVE_FABSL #define fabsl(a) igraph_fabsl(a) #endif #ifndef HAVE_FMIN #define fmin(a,b) igraph_fmin((a),(b)) #endif #ifndef HAVE_ROUND #define round igraph_i_round #endif #ifndef M_PI #define M_PI 3.14159265358979323846 #endif #ifndef M_PI_2 #define M_PI_2 1.57079632679489661923 #endif #ifndef M_LN2 #define M_LN2 0.69314718055994530942 #endif #ifndef M_SQRT2 #define M_SQRT2 1.4142135623730950488016887 #endif #ifndef M_LN_SQRT_2PI #define M_LN_SQRT_2PI 0.918938533204672741780329736406 /* log(sqrt(2*pi)) == log(2*pi)/2 */ #endif int igraph_almost_equals(double a, double b, double eps); int igraph_cmp_epsilon(double a, double b, double eps); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/src/bliss.cc0000644000076500000240000002247013614300625023026 0ustar tamasstaff00000000000000/* Copyright (C) 2003-2006 Tommi Junttila This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License version 2 as published by the Free Software Foundation. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301, USA. */ /* FSF address fixed in the above notice on 1 Oct 2009 by Tamas Nepusz */ #include "bliss/graph.hh" #include "igraph_types.h" #include "igraph_topology.h" #include "igraph_datatype.h" #include "igraph_interface.h" using namespace bliss; using namespace std; namespace { // unnamed namespace inline AbstractGraph *bliss_from_igraph(const igraph_t *graph) { unsigned int nof_vertices = (unsigned int)igraph_vcount(graph); unsigned int nof_edges = (unsigned int)igraph_ecount(graph); AbstractGraph *g; if (igraph_is_directed(graph)) { g = new Digraph(nof_vertices); } else { g = new Graph(nof_vertices); } g->set_verbose_level(0); for (unsigned int i = 0; i < nof_edges; i++) { g->add_edge((unsigned int)IGRAPH_FROM(graph, i), (unsigned int)IGRAPH_TO(graph, i)); } return g; } void bliss_free_graph(AbstractGraph *g) { delete g; } inline int bliss_set_sh(AbstractGraph *g, igraph_bliss_sh_t sh, bool directed) { if (directed) { Digraph::SplittingHeuristic gsh = Digraph::shs_fsm; switch (sh) { case IGRAPH_BLISS_F: gsh = Digraph::shs_f; break; case IGRAPH_BLISS_FL: gsh = Digraph::shs_fl; break; case IGRAPH_BLISS_FS: gsh = Digraph::shs_fs; break; case IGRAPH_BLISS_FM: gsh = Digraph::shs_fm; break; case IGRAPH_BLISS_FLM: gsh = Digraph::shs_flm; break; case IGRAPH_BLISS_FSM: gsh = Digraph::shs_fsm; break; default: IGRAPH_ERROR("Invalid splitting heuristic", IGRAPH_EINVAL); } static_cast(g)->set_splitting_heuristic(gsh); } else { Graph::SplittingHeuristic gsh = Graph::shs_fsm; switch (sh) { case IGRAPH_BLISS_F: gsh = Graph::shs_f; break; case IGRAPH_BLISS_FL: gsh = Graph::shs_fl; break; case IGRAPH_BLISS_FS: gsh = Graph::shs_fs; break; case IGRAPH_BLISS_FM: gsh = Graph::shs_fm; break; case IGRAPH_BLISS_FLM: gsh = Graph::shs_flm; break; case IGRAPH_BLISS_FSM: gsh = Graph::shs_fsm; break; default: IGRAPH_ERROR("Invalid splitting heuristic", IGRAPH_EINVAL); } static_cast(g)->set_splitting_heuristic(gsh); } return IGRAPH_SUCCESS; } inline int bliss_set_colors(AbstractGraph *g, const igraph_vector_int_t *colors) { if (colors == NULL) { return IGRAPH_SUCCESS; } const int n = g->get_nof_vertices(); if (n != igraph_vector_int_size(colors)) { IGRAPH_ERROR("Invalid vertex color vector length", IGRAPH_EINVAL); } for (int i = 0; i < n; ++i) { g->change_color(i, VECTOR(*colors)[i]); } return IGRAPH_SUCCESS; } inline void bliss_info_to_igraph(igraph_bliss_info_t *info, const Stats &stats) { if (info) { info->max_level = stats.get_max_level(); info->nof_nodes = stats.get_nof_nodes(); info->nof_leaf_nodes = stats.get_nof_leaf_nodes(); info->nof_bad_nodes = stats.get_nof_bad_nodes(); info->nof_canupdates = stats.get_nof_canupdates(); info->nof_generators = stats.get_nof_generators(); stats.group_size.tostring(&info->group_size); } } // this is the callback function used with AbstractGraph::find_automorphisms() // it collects the group generators into a pointer vector void collect_generators(void *generators, unsigned int n, const unsigned int *aut) { igraph_vector_ptr_t *gen = static_cast(generators); igraph_vector_t *newvector = igraph_Calloc(1, igraph_vector_t); igraph_vector_init(newvector, n); copy(aut, aut + n, newvector->stor_begin); // takes care of unsigned int -> double conversion igraph_vector_ptr_push_back(gen, newvector); } } // end unnamed namespace /** * \function igraph_canonical_permutation * Canonical permutation using BLISS * * This function computes the canonical permutation which transforms * the graph into a canonical form by using the BLISS algorithm. * * \param graph The input graph. Multiple edges between the same nodes * are not supported and will cause an incorrect result to be returned. * \param colors An optional vertex color vector for the graph. Supply a * null pointer is the graph is not colored. * \param labeling Pointer to a vector, the result is stored here. The * permutation takes vertex 0 to the first element of the vector, * vertex 1 to the second, etc. The vector will be resized as * needed. * \param sh The splitting heuristics to be used in BLISS. See \ref * igraph_bliss_sh_t. * \param info If not \c NULL then information on BLISS internals is * stored here. See \ref igraph_bliss_info_t. * \return Error code. * * Time complexity: exponential, in practice it is fast for many graphs. */ int igraph_canonical_permutation(const igraph_t *graph, const igraph_vector_int_t *colors, igraph_vector_t *labeling, igraph_bliss_sh_t sh, igraph_bliss_info_t *info) { AbstractGraph *g = bliss_from_igraph(graph); IGRAPH_FINALLY(bliss_free_graph, g); const unsigned int N = g->get_nof_vertices(); IGRAPH_CHECK(bliss_set_sh(g, sh, igraph_is_directed(graph))); IGRAPH_CHECK(bliss_set_colors(g, colors)); Stats stats; const unsigned int *cl = g->canonical_form(stats, NULL, NULL); IGRAPH_CHECK(igraph_vector_resize(labeling, N)); for (unsigned int i = 0; i < N; i++) { VECTOR(*labeling)[i] = cl[i]; } bliss_info_to_igraph(info, stats); delete g; IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } /** * \function igraph_automorphisms * Number of automorphisms using BLISS * * The number of automorphisms of a graph is computed using BLISS. The * result is returned as part of the \p info structure, in tag \c * group_size. It is returned as a string, as it can be very high even * for relatively small graphs. If the GNU MP library is used then * this number is exact, otherwise a long double is used * and it is only approximate. See also \ref igraph_bliss_info_t. * * \param graph The input graph. Multiple edges between the same nodes * are not supported and will cause an incorrect result to be returned. * \param colors An optional vertex color vector for the graph. Supply a * null pointer is the graph is not colored. * \param sh The splitting heuristics to be used in BLISS. See \ref * igraph_bliss_sh_t. * \param info The result is stored here, in particular in the \c * group_size tag of \p info. * \return Error code. * * Time complexity: exponential, in practice it is fast for many graphs. */ int igraph_automorphisms(const igraph_t *graph, const igraph_vector_int_t *colors, igraph_bliss_sh_t sh, igraph_bliss_info_t *info) { AbstractGraph *g = bliss_from_igraph(graph); IGRAPH_FINALLY(bliss_free_graph, g); IGRAPH_CHECK(bliss_set_sh(g, sh, igraph_is_directed(graph))); IGRAPH_CHECK(bliss_set_colors(g, colors)); Stats stats; g->find_automorphisms(stats, NULL, NULL); bliss_info_to_igraph(info, stats); delete g; IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } /** * \function igraph_automorphism_group * Automorphism group generators using BLISS * * The generators of the automorphism group of a graph are computed * using BLISS. The generator set may not be minimal and may depend on * the splitting heuristics. * * \param graph The input graph. Multiple edges between the same nodes * are not supported and will cause an incorrect result to be returned. * \param colors An optional vertex color vector for the graph. Supply a * null pointer is the graph is not colored. * \param generators Must be an initialized pointer vector. It will * contain pointers to \ref igraph_vector_t objects * representing generators of the automorphism group. * \param sh The splitting heuristics to be used in BLISS. See \ref * igraph_bliss_sh_t. * \param info If not \c NULL then information on BLISS internals is * stored here. See \ref igraph_bliss_info_t. * \return Error code. * * Time complexity: exponential, in practice it is fast for many graphs. */ int igraph_automorphism_group( const igraph_t *graph, const igraph_vector_int_t *colors, igraph_vector_ptr_t *generators, igraph_bliss_sh_t sh, igraph_bliss_info_t *info) { AbstractGraph *g = bliss_from_igraph(graph); IGRAPH_FINALLY(bliss_free_graph, g); IGRAPH_CHECK(bliss_set_sh(g, sh, igraph_is_directed(graph))); IGRAPH_CHECK(bliss_set_colors(g, colors)); Stats stats; igraph_vector_ptr_resize(generators, 0); g->find_automorphisms(stats, collect_generators, generators); bliss_info_to_igraph(info, stats); delete g; IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } python-igraph-0.8.0/vendor/source/igraph/src/f2c_dummy.c0000644000076500000240000000162313614300625023431 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ int MAIN__(void) { return 0; } python-igraph-0.8.0/vendor/source/igraph/src/lapack.c0000644000076500000240000010456413614300625023007 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_lapack.h" #include "igraph_lapack_internal.h" /** * \function igraph_lapack_dgetrf * LU factorization of a general M-by-N matrix * * The factorization has the form * A = P * L * U * where P is a permutation matrix, L is lower triangular with unit * diagonal elements (lower trapezoidal if m > n), and U is upper * triangular (upper trapezoidal if m < n). * \param a The input/output matrix. On entry, the M-by-N matrix to be * factored. On exit, the factors L and U from the factorization * A = P * L * U; the unit diagonal elements of L are not * stored. * \param ipiv An integer vector, the pivot indices are stored here, * unless it is a null pointer. Row i of the matrix was * interchanged with row ipiv[i]. * \param info LAPACK error code. Zero on successful exit. If positive * and i, then U(i,i) is exactly zero. The factorization has been * completed, but the factor U is exactly singular, and division * by zero will occur if it is used to solve a system of * equations. If LAPACK returns an error, i.e. a negative info * value, then an igraph error is generated as well. * \return Error code. * * Time complexity: TODO. */ int igraph_lapack_dgetrf(igraph_matrix_t *a, igraph_vector_int_t *ipiv, int *info) { int m = (int) igraph_matrix_nrow(a); int n = (int) igraph_matrix_ncol(a); int lda = m > 0 ? m : 1; igraph_vector_int_t *myipiv = ipiv, vipiv; if (!ipiv) { IGRAPH_CHECK(igraph_vector_int_init(&vipiv, m < n ? m : n)); IGRAPH_FINALLY(igraph_vector_int_destroy, &vipiv); myipiv = &vipiv; } igraphdgetrf_(&m, &n, VECTOR(a->data), &lda, VECTOR(*myipiv), info); if (*info > 0) { IGRAPH_WARNING("LU: factor is exactly singular"); } else if (*info < 0) { switch (*info) { case -1: IGRAPH_ERROR("Invalid number of rows", IGRAPH_ELAPACK); break; case -2: IGRAPH_ERROR("Invalid number of columns", IGRAPH_ELAPACK); break; case -3: IGRAPH_ERROR("Invalid input matrix", IGRAPH_ELAPACK); break; case -4: IGRAPH_ERROR("Invalid LDA parameter", IGRAPH_ELAPACK); break; case -5: IGRAPH_ERROR("Invalid pivot vector", IGRAPH_ELAPACK); break; case -6: IGRAPH_ERROR("Invalid info argument", IGRAPH_ELAPACK); break; default: IGRAPH_ERROR("Unknown LAPACK error", IGRAPH_ELAPACK); break; } } if (!ipiv) { igraph_vector_int_destroy(&vipiv); IGRAPH_FINALLY_CLEAN(1); } return 0; } /** * \function igraph_lapack_dgetrs * Solve general system of linear equations using LU factorization * * This function calls LAPACK to solve a system of linear equations * A * X = B or A' * X = B * with a general N-by-N matrix A using the LU factorization * computed by \ref igraph_lapack_dgetrf. * \param transpose Logical scalar, whether to transpose the input * matrix. * \param a A matrix containing the L and U factors from the * factorization A = P*L*U. * \param ipiv An integer vector, the pivot indices from \ref * igraph_lapack_dgetrf must be given here. * \param b The right hand side matrix must be given here. * \return Error code. * * Time complexity: TODO. */ int igraph_lapack_dgetrs(igraph_bool_t transpose, const igraph_matrix_t *a, igraph_vector_int_t *ipiv, igraph_matrix_t *b) { char trans = transpose ? 'T' : 'N'; int n = (int) igraph_matrix_nrow(a); int nrhs = (int) igraph_matrix_ncol(b); int lda = n > 0 ? n : 1; int ldb = n > 0 ? n : 1; int info; if (n != igraph_matrix_ncol(a)) { IGRAPH_ERROR("Cannot LU solve matrix", IGRAPH_NONSQUARE); } if (n != igraph_matrix_nrow(b)) { IGRAPH_ERROR("Cannot LU solve matrix, RHS of wrong size", IGRAPH_EINVAL); } igraphdgetrs_(&trans, &n, &nrhs, VECTOR(a->data), &lda, VECTOR(*ipiv), VECTOR(b->data), &ldb, &info); if (info < 0) { switch (info) { case -1: IGRAPH_ERROR("Invalid transpose argument", IGRAPH_ELAPACK); break; case -2: IGRAPH_ERROR("Invalid number of rows/columns", IGRAPH_ELAPACK); break; case -3: IGRAPH_ERROR("Invalid number of RHS vectors", IGRAPH_ELAPACK); break; case -4: IGRAPH_ERROR("Invalid LU matrix", IGRAPH_ELAPACK); break; case -5: IGRAPH_ERROR("Invalid LDA parameter", IGRAPH_ELAPACK); break; case -6: IGRAPH_ERROR("Invalid pivot vector", IGRAPH_ELAPACK); break; case -7: IGRAPH_ERROR("Invalid RHS matrix", IGRAPH_ELAPACK); break; case -8: IGRAPH_ERROR("Invalid LDB parameter", IGRAPH_ELAPACK); break; case -9: IGRAPH_ERROR("Invalid info argument", IGRAPH_ELAPACK); break; default: IGRAPH_ERROR("Unknown LAPACK error", IGRAPH_ELAPACK); break; } } return 0; } /** * \function igraph_lapack_dgesv * Solve system of linear equations with LU factorization * * This function computes the solution to a real system of linear * equations A * X = B, where A is an N-by-N matrix and X and B are * N-by-NRHS matrices. * * The LU decomposition with partial pivoting and row * interchanges is used to factor A as * A = P * L * U, * where P is a permutation matrix, L is unit lower triangular, and U is * upper triangular. The factored form of A is then used to solve the * system of equations A * X = B. * \param a Matrix. On entry the N-by-N coefficient matrix, on exit, * the factors L and U from the factorization A=P*L*U; the unit * diagonal elements of L are not stored. * \param ipiv An integer vector or a null pointer. If not a null * pointer, then the pivot indices that define the permutation * matrix P, are stored here. Row i of the matrix was * interchanged with row IPIV(i). * \param b Matrix, on entry the right hand side matrix should be * stored here. On exit, if there was no error, and the info * argument is zero, then it contains the solution matrix X. * \param info The LAPACK info code. If it is positive, then * U(info,info) is exactly zero. In this case the factorization * has been completed, but the factor U is exactly * singular, so the solution could not be computed. * \return Error code. * * Time complexity: TODO. * * \example examples/simple/igraph_lapack_dgesv.c */ int igraph_lapack_dgesv(igraph_matrix_t *a, igraph_vector_int_t *ipiv, igraph_matrix_t *b, int *info) { int n = (int) igraph_matrix_nrow(a); int nrhs = (int) igraph_matrix_ncol(b); int lda = n > 0 ? n : 1; int ldb = n > 0 ? n : 1; igraph_vector_int_t *myipiv = ipiv, vipiv; if (n != igraph_matrix_ncol(a)) { IGRAPH_ERROR("Cannot LU solve matrix", IGRAPH_NONSQUARE); } if (n != igraph_matrix_nrow(b)) { IGRAPH_ERROR("Cannot LU solve matrix, RHS of wrong size", IGRAPH_EINVAL); } if (!ipiv) { IGRAPH_CHECK(igraph_vector_int_init(&vipiv, n)); IGRAPH_FINALLY(igraph_vector_int_destroy, &vipiv); myipiv = &vipiv; } igraphdgesv_(&n, &nrhs, VECTOR(a->data), &lda, VECTOR(*myipiv), VECTOR(b->data), &ldb, info); if (*info > 0) { IGRAPH_WARNING("LU: factor is exactly singular"); } else if (*info < 0) { switch (*info) { case -1: IGRAPH_ERROR("Invalid number of rows/column", IGRAPH_ELAPACK); break; case -2: IGRAPH_ERROR("Invalid number of RHS vectors", IGRAPH_ELAPACK); break; case -3: IGRAPH_ERROR("Invalid input matrix", IGRAPH_ELAPACK); break; case -4: IGRAPH_ERROR("Invalid LDA parameter", IGRAPH_ELAPACK); break; case -5: IGRAPH_ERROR("Invalid pivot vector", IGRAPH_ELAPACK); break; case -6: IGRAPH_ERROR("Invalid RHS matrix", IGRAPH_ELAPACK); break; case -7: IGRAPH_ERROR("Invalid LDB parameter", IGRAPH_ELAPACK); break; case -8: IGRAPH_ERROR("Invalid info argument", IGRAPH_ELAPACK); break; default: IGRAPH_ERROR("Unknown LAPACK error", IGRAPH_ELAPACK); break; } } if (!ipiv) { igraph_vector_int_destroy(&vipiv); IGRAPH_FINALLY_CLEAN(1); } return 0; } /** * \function igraph_lapack_dsyevr * Selected eigenvalues and optionally eigenvectors of a symmetric matrix * * Calls the DSYEVR LAPACK function to compute selected eigenvalues * and, optionally, eigenvectors of a real symmetric matrix A. * Eigenvalues and eigenvectors can be selected by specifying either * a range of values or a range of indices for the desired eigenvalues. * * See more in the LAPACK documentation. * \param A Matrix, on entry it contains the symmetric input * matrix. Only the leading N-by-N upper triangular part is * used for the computation. * \param which Constant that gives which eigenvalues (and possibly * the corresponding eigenvectors) to calculate. Possible * values are \c IGRAPH_LAPACK_DSYEV_ALL, all eigenvalues; * \c IGRAPH_LAPACK_DSYEV_INTERVAL, all eigenvalues in the * half-open interval (vl,vu]; * \c IGRAPH_LAPACK_DSYEV_SELECT, the il-th through iu-th * eigenvalues. * \param vl If \p which is \c IGRAPH_LAPACK_DSYEV_INTERVAL, then * this is the lower bound of the interval to be searched for * eigenvalues. See also the \p vestimate argument. * \param vu If \p which is \c IGRAPH_LAPACK_DSYEV_INTERVAL, then * this is the upper bound of the interval to be searched for * eigenvalues. See also the \p vestimate argument. * \param vestimate An upper bound for the number of eigenvalues in * the (vl,vu] interval, if \p which is \c * IGRAPH_LAPACK_DSYEV_INTERVAL. Memory is allocated only for * the given number of eigenvalues (and eigenvectors), so this * upper bound must be correct. * \param il The index of the smallest eigenvalue to return, if \p * which is \c IGRAPH_LAPACK_DSYEV_SELECT. * \param iu The index of the largets eigenvalue to return, if \p * which is \c IGRAPH_LAPACK_DSYEV_SELECT. * \param abstol The absolute error tolerance for the eigevalues. An * approximate eigenvalue is accepted as converged when it is * determined to lie in an interval [a,b] of width less than or * equal to abstol + EPS * max(|a|,|b|), where EPS is the * machine precision. * \param values An initialized vector, the eigenvalues are stored * here, unless it is a null pointer. It will be resized as * needed. * \param vectors An initialized matrix, the eigenvectors are stored * in its columns, unless it is a null pointer. It will be * resized as needed. * \param support An integer vector. If not a null pointer, then it * will be resized to (2*max(1,M)) (M is a the total number of * eigenvalues found). Then the support of the eigenvectors in * \p vectors is stored here, i.e., the indices * indicating the nonzero elements in \p vectors. * The i-th eigenvector is nonzero only in elements * support(2*i-1) through support(2*i). * \return Error code. * * Time complexity: TODO. * * \example examples/simple/igraph_lapack_dsyevr.c */ int igraph_lapack_dsyevr(const igraph_matrix_t *A, igraph_lapack_dsyev_which_t which, igraph_real_t vl, igraph_real_t vu, int vestimate, int il, int iu, igraph_real_t abstol, igraph_vector_t *values, igraph_matrix_t *vectors, igraph_vector_int_t *support) { igraph_matrix_t Acopy; char jobz = vectors ? 'V' : 'N', range, uplo = 'U'; int n = (int) igraph_matrix_nrow(A), lda = n, ldz = n; int m, info; igraph_vector_t *myvalues = values, vvalues; igraph_vector_int_t *mysupport = support, vsupport; igraph_vector_t work; igraph_vector_int_t iwork; int lwork = -1, liwork = -1; if (n != igraph_matrix_ncol(A)) { IGRAPH_ERROR("Cannot find eigenvalues/vectors", IGRAPH_NONSQUARE); } if (which == IGRAPH_LAPACK_DSYEV_INTERVAL && (vestimate < 1 || vestimate > n)) { IGRAPH_ERROR("Estimated (upper bound) number of eigenvalues must be " "between 1 and n", IGRAPH_EINVAL); } if (which == IGRAPH_LAPACK_DSYEV_SELECT && iu - il < 0) { IGRAPH_ERROR("Invalid 'il' and/or 'iu' values", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_matrix_copy(&Acopy, A)); IGRAPH_FINALLY(igraph_matrix_destroy, &Acopy); IGRAPH_VECTOR_INIT_FINALLY(&work, 1); IGRAPH_CHECK(igraph_vector_int_init(&iwork, 1)); IGRAPH_FINALLY(igraph_vector_int_destroy, &iwork); if (!values) { IGRAPH_VECTOR_INIT_FINALLY(&vvalues, 0); myvalues = &vvalues; } if (!support) { IGRAPH_CHECK(igraph_vector_int_init(&vsupport, 0)); IGRAPH_FINALLY(igraph_vector_int_destroy, &vsupport); mysupport = &vsupport; } IGRAPH_CHECK(igraph_vector_resize(myvalues, n)); switch (which) { case IGRAPH_LAPACK_DSYEV_ALL: range = 'A'; IGRAPH_CHECK(igraph_vector_int_resize(mysupport, 2 * n)); if (vectors) { IGRAPH_CHECK(igraph_matrix_resize(vectors, n, n)); } break; case IGRAPH_LAPACK_DSYEV_INTERVAL: range = 'V'; IGRAPH_CHECK(igraph_vector_int_resize(mysupport, 2 * vestimate)); if (vectors) { IGRAPH_CHECK(igraph_matrix_resize(vectors, n, vestimate)); } break; case IGRAPH_LAPACK_DSYEV_SELECT: range = 'I'; IGRAPH_CHECK(igraph_vector_int_resize(mysupport, 2 * (iu - il + 1))); if (vectors) { IGRAPH_CHECK(igraph_matrix_resize(vectors, n, iu - il + 1)); } break; } igraphdsyevr_(&jobz, &range, &uplo, &n, &MATRIX(Acopy, 0, 0), &lda, &vl, &vu, &il, &iu, &abstol, &m, VECTOR(*myvalues), vectors ? &MATRIX(*vectors, 0, 0) : 0, &ldz, VECTOR(*mysupport), VECTOR(work), &lwork, VECTOR(iwork), &liwork, &info); if (info != 0) { IGRAPH_ERROR("Invalid argument to dsyevr in workspace query", IGRAPH_EINVAL); } lwork = (int) VECTOR(work)[0]; liwork = VECTOR(iwork)[0]; IGRAPH_CHECK(igraph_vector_resize(&work, lwork)); IGRAPH_CHECK(igraph_vector_int_resize(&iwork, liwork)); igraphdsyevr_(&jobz, &range, &uplo, &n, &MATRIX(Acopy, 0, 0), &lda, &vl, &vu, &il, &iu, &abstol, &m, VECTOR(*myvalues), vectors ? &MATRIX(*vectors, 0, 0) : 0, &ldz, VECTOR(*mysupport), VECTOR(work), &lwork, VECTOR(iwork), &liwork, &info); if (info != 0) { IGRAPH_ERROR("Invalid argument to dsyevr in calculation", IGRAPH_EINVAL); } if (values) { IGRAPH_CHECK(igraph_vector_resize(values, m)); } if (vectors) { IGRAPH_CHECK(igraph_matrix_resize(vectors, n, m)); } if (support) { IGRAPH_CHECK(igraph_vector_int_resize(support, m)); } if (!support) { igraph_vector_int_destroy(&vsupport); IGRAPH_FINALLY_CLEAN(1); } if (!values) { igraph_vector_destroy(&vvalues); IGRAPH_FINALLY_CLEAN(1); } igraph_vector_int_destroy(&iwork); igraph_vector_destroy(&work); igraph_matrix_destroy(&Acopy); IGRAPH_FINALLY_CLEAN(3); return 0; } /** * \function igraph_lapack_dgeev * Eigenvalues and optionally eigenvectors of a non-symmetric matrix * * This function calls LAPACK to compute, for an N-by-N real * nonsymmetric matrix A, the eigenvalues and, optionally, the left * and/or right eigenvectors. * * * The right eigenvector v(j) of A satisfies * A * v(j) = lambda(j) * v(j) * where lambda(j) is its eigenvalue. * The left eigenvector u(j) of A satisfies * u(j)**H * A = lambda(j) * u(j)**H * where u(j)**H denotes the conjugate transpose of u(j). * * * The computed eigenvectors are normalized to have Euclidean norm * equal to 1 and largest component real. * * \param A matrix. On entry it contains the N-by-N input matrix. * \param valuesreal Pointer to an initialized vector, or a null * pointer. If not a null pointer, then the real parts of the * eigenvalues are stored here. The vector will be resized as * needed. * \param valuesimag Pointer to an initialized vector, or a null * pointer. If not a null pointer, then the imaginary parts of * the eigenvalues are stored here. The vector will be resized * as needed. * \param vectorsleft Pointer to an initialized matrix, or a null * pointer. If not a null pointer, then the left eigenvectors * are stored in the columns of the matrix. The matrix will be * resized as needed. * \param vectorsright Pointer to an initialized matrix, or a null * pointer. If not a null pointer, then the right eigenvectors * are stored in the columns of the matrix. The matrix will be * resized as needed. * \param info This argument is used for two purposes. As an input * argument it gives whether an igraph error should be * generated if the QR algorithm fails to compute all * eigenvalues. If \p info is non-zero, then an error is * generated, otherwise only a warning is given. * On exit it contains the LAPACK error code. * Zero means successful exit. * A negative values means that some of the arguments had an * illegal value, this always triggers an igraph error. An i * positive value means that the QR algorithm failed to * compute all the eigenvalues, and no eigenvectors have been * computed; element i+1:N of \p valuesreal and \p valuesimag * contain eigenvalues which have converged. This case only * generates an igraph error, if \p info was non-zero on entry. * \return Error code. * * Time complexity: TODO. * * \example examples/simple/igraph_lapack_dgeev.c */ int igraph_lapack_dgeev(const igraph_matrix_t *A, igraph_vector_t *valuesreal, igraph_vector_t *valuesimag, igraph_matrix_t *vectorsleft, igraph_matrix_t *vectorsright, int *info) { char jobvl = vectorsleft ? 'V' : 'N'; char jobvr = vectorsright ? 'V' : 'N'; int n = (int) igraph_matrix_nrow(A); int lda = n, ldvl = n, ldvr = n, lwork = -1; igraph_vector_t work; igraph_vector_t *myreal = valuesreal, *myimag = valuesimag, vreal, vimag; igraph_matrix_t Acopy; int error = *info; if (igraph_matrix_ncol(A) != n) { IGRAPH_ERROR("Cannot calculate eigenvalues (dgeev)", IGRAPH_NONSQUARE); } IGRAPH_CHECK(igraph_matrix_copy(&Acopy, A)); IGRAPH_FINALLY(igraph_matrix_destroy, &Acopy); IGRAPH_VECTOR_INIT_FINALLY(&work, 1); if (!valuesreal) { IGRAPH_VECTOR_INIT_FINALLY(&vreal, n); myreal = &vreal; } else { IGRAPH_CHECK(igraph_vector_resize(myreal, n)); } if (!valuesimag) { IGRAPH_VECTOR_INIT_FINALLY(&vimag, n); myimag = &vimag; } else { IGRAPH_CHECK(igraph_vector_resize(myimag, n)); } if (vectorsleft) { IGRAPH_CHECK(igraph_matrix_resize(vectorsleft, n, n)); } if (vectorsright) { IGRAPH_CHECK(igraph_matrix_resize(vectorsright, n, n)); } igraphdgeev_(&jobvl, &jobvr, &n, &MATRIX(Acopy, 0, 0), &lda, VECTOR(*myreal), VECTOR(*myimag), vectorsleft ? &MATRIX(*vectorsleft, 0, 0) : 0, &ldvl, vectorsright ? &MATRIX(*vectorsright, 0, 0) : 0, &ldvr, VECTOR(work), &lwork, info); lwork = (int) VECTOR(work)[0]; IGRAPH_CHECK(igraph_vector_resize(&work, lwork)); igraphdgeev_(&jobvl, &jobvr, &n, &MATRIX(Acopy, 0, 0), &lda, VECTOR(*myreal), VECTOR(*myimag), vectorsleft ? &MATRIX(*vectorsleft, 0, 0) : 0, &ldvl, vectorsright ? &MATRIX(*vectorsright, 0, 0) : 0, &ldvr, VECTOR(work), &lwork, info); if (*info < 0) { IGRAPH_ERROR("Cannot calculate eigenvalues (dgeev)", IGRAPH_ELAPACK); } else if (*info > 0) { if (error) { IGRAPH_ERROR("Cannot calculate eigenvalues (dgeev)", IGRAPH_ELAPACK); } else { IGRAPH_WARNING("Cannot calculate eigenvalues (dgeev)"); } } if (!valuesimag) { igraph_vector_destroy(&vimag); IGRAPH_FINALLY_CLEAN(1); } if (!valuesreal) { igraph_vector_destroy(&vreal); IGRAPH_FINALLY_CLEAN(1); } igraph_vector_destroy(&work); igraph_matrix_destroy(&Acopy); IGRAPH_FINALLY_CLEAN(2); return 0; } /** * \function igraph_lapack_dgeevx * Eigenvalues/vectors of nonsymmetric matrices, expert mode * * This function calculates the eigenvalues and optionally the left * and/or right eigenvectors of a nonsymmetric N-by-N real matrix. * * * Optionally also, it computes a balancing transformation to improve * the conditioning of the eigenvalues and eigenvectors (\p ilo, \pihi, * \p scale, and \p abnrm), reciprocal condition numbers for the * eigenvalues (\p rconde), and reciprocal condition numbers for the * right eigenvectors (\p rcondv). * * * The right eigenvector v(j) of A satisfies * A * v(j) = lambda(j) * v(j) * where lambda(j) is its eigenvalue. * The left eigenvector u(j) of A satisfies * u(j)**H * A = lambda(j) * u(j)**H * where u(j)**H denotes the conjugate transpose of u(j). * * * The computed eigenvectors are normalized to have Euclidean norm * equal to 1 and largest component real. * * * Balancing a matrix means permuting the rows and columns to make it * more nearly upper triangular, and applying a diagonal similarity * transformation D * A * D**(-1), where D is a diagonal matrix, to * make its rows and columns closer in norm and the condition numbers * of its eigenvalues and eigenvectors smaller. The computed * reciprocal condition numbers correspond to the balanced matrix. * Permuting rows and columns will not change the condition numbers * (in exact arithmetic) but diagonal scaling will. For further * explanation of balancing, see section 4.10.2 of the LAPACK * Users' Guide. * * \param balance Scalar that indicated, whether the input matrix * should be balanced. Possible values: * \clist * \cli IGRAPH_LAPACK_DGEEVX_BALANCE_NONE * no not diagonally scale or permute. * \cli IGRAPH_LAPACK_DGEEVX_BALANCE_PERM * perform permutations to make the matrix more nearly upper * triangular. Do not diagonally scale. * \cli IGRAPH_LAPACK_DGEEVX_BALANCE_SCALE * diagonally scale the matrix, i.e. replace A by * D*A*D**(-1), where D is a diagonal matrix, chosen to make * the rows and columns of A more equal in norm. Do not * permute. * \cli IGRAPH_LAPACK_DGEEVX_BALANCE_BOTH * both diagonally scale and permute A. * \endclist * \param A The input matrix, must be square. * \param valuesreal An initialized vector, or a NULL pointer. If not * a NULL pointer, then the real parts of the eigenvalues are stored * here. The vector will be resized, as needed. * \param valuesimag An initialized vector, or a NULL pointer. If not * a NULL pointer, then the imaginary parts of the eigenvalues are stored * here. The vector will be resized, as needed. * \param vectorsleft An initialized matrix or a NULL pointer. If not * a null pointer, then the left eigenvectors are stored here. The * order corresponds to the eigenvalues and the eigenvectors are * stored in a compressed form. If the j-th eigenvalue is real then * column j contains the corresponding eigenvector. If the j-th and * (j+1)-th eigenvalues form a complex conjugate pair, then the j-th * and (j+1)-th columns contain their corresponding eigenvectors. * \param vectorsright An initialized matrix or a NULL pointer. If not * a null pointer, then the right eigenvectors are stored here. The * format is the same, as for the \p vectorsleft argument. * \param ilo * \param ihi \p ilo and \p ihi are integer values determined when A was * balanced. The balanced A(i,j) = 0 if I>J and * J=1,...,ilo-1 or I=ihi+1,...,N. * \param scale Pointer to an initialized vector or a NULL pointer. If * not a NULL pointer, then details of the permutations and scaling * factors applied when balancing \param A, are stored here. * If P(j) is the index of the row and column * interchanged with row and column j, and D(j) is the scaling * factor applied to row and column j, then * \clist * \cli scale(J) = P(J), for J = 1,...,ilo-1 * \cli scale(J) = D(J), for J = ilo,...,ihi * \cli scale(J) = P(J) for J = ihi+1,...,N. * \endclist * The order in which the interchanges are made is N to \p ihi+1, * then 1 to \p ilo-1. * \param abnrm Pointer to a real variable, the one-norm of the * balanced matrix is stored here. (The one-norm is the maximum of * the sum of absolute values of elements in any column.) * \param rconde An initialized vector or a NULL pointer. If not a * null pointer, then the reciprocal condition numbers of the * eigenvalues are stored here. * \param rcondv An initialized vector or a NULL pointer. If not a * null pointer, then the reciprocal condition numbers of the right * eigenvectors are stored here. * \param info This argument is used for two purposes. As an input * argument it gives whether an igraph error should be * generated if the QR algorithm fails to compute all * eigenvalues. If \p info is non-zero, then an error is * generated, otherwise only a warning is given. * On exit it contains the LAPACK error code. * Zero means successful exit. * A negative values means that some of the arguments had an * illegal value, this always triggers an igraph error. An i * positive value means that the QR algorithm failed to * compute all the eigenvalues, and no eigenvectors have been * computed; element i+1:N of \p valuesreal and \p valuesimag * contain eigenvalues which have converged. This case only * generated an igraph error, if \p info was non-zero on entry. * \return Error code. * * Time complexity: TODO * * \example examples/simple/igraph_lapack_dgeevx.c */ int igraph_lapack_dgeevx(igraph_lapack_dgeevx_balance_t balance, const igraph_matrix_t *A, igraph_vector_t *valuesreal, igraph_vector_t *valuesimag, igraph_matrix_t *vectorsleft, igraph_matrix_t *vectorsright, int *ilo, int *ihi, igraph_vector_t *scale, igraph_real_t *abnrm, igraph_vector_t *rconde, igraph_vector_t *rcondv, int *info) { char balanc; char jobvl = vectorsleft ? 'V' : 'N'; char jobvr = vectorsright ? 'V' : 'N'; char sense; int n = (int) igraph_matrix_nrow(A); int lda = n, ldvl = n, ldvr = n, lwork = -1; igraph_vector_t work; igraph_vector_int_t iwork; igraph_matrix_t Acopy; int error = *info; igraph_vector_t *myreal = valuesreal, *myimag = valuesimag, vreal, vimag; igraph_vector_t *myscale = scale, vscale; if (igraph_matrix_ncol(A) != n) { IGRAPH_ERROR("Cannot calculate eigenvalues (dgeevx)", IGRAPH_NONSQUARE); } switch (balance) { case IGRAPH_LAPACK_DGEEVX_BALANCE_NONE: balanc = 'N'; break; case IGRAPH_LAPACK_DGEEVX_BALANCE_PERM: balanc = 'P'; break; case IGRAPH_LAPACK_DGEEVX_BALANCE_SCALE: balanc = 'S'; break; case IGRAPH_LAPACK_DGEEVX_BALANCE_BOTH: balanc = 'B'; break; default: IGRAPH_ERROR("Invalid 'balance' argument", IGRAPH_EINVAL); break; } if (!rconde && !rcondv) { sense = 'N'; } else if (rconde && !rcondv) { sense = 'E'; } else if (!rconde && rcondv) { sense = 'V'; } else { sense = 'B'; } IGRAPH_CHECK(igraph_matrix_copy(&Acopy, A)); IGRAPH_FINALLY(igraph_matrix_destroy, &Acopy); IGRAPH_VECTOR_INIT_FINALLY(&work, 1); IGRAPH_CHECK(igraph_vector_int_init(&iwork, n)); IGRAPH_FINALLY(igraph_vector_int_destroy, &iwork); if (!valuesreal) { IGRAPH_VECTOR_INIT_FINALLY(&vreal, n); myreal = &vreal; } else { IGRAPH_CHECK(igraph_vector_resize(myreal, n)); } if (!valuesimag) { IGRAPH_VECTOR_INIT_FINALLY(&vimag, n); myimag = &vimag; } else { IGRAPH_CHECK(igraph_vector_resize(myimag, n)); } if (!scale) { IGRAPH_VECTOR_INIT_FINALLY(&vscale, n); myscale = &vscale; } else { IGRAPH_CHECK(igraph_vector_resize(scale, n)); } if (vectorsleft) { IGRAPH_CHECK(igraph_matrix_resize(vectorsleft, n, n)); } if (vectorsright) { IGRAPH_CHECK(igraph_matrix_resize(vectorsright, n, n)); } igraphdgeevx_(&balanc, &jobvl, &jobvr, &sense, &n, &MATRIX(Acopy, 0, 0), &lda, VECTOR(*myreal), VECTOR(*myimag), vectorsleft ? &MATRIX(*vectorsleft, 0, 0) : 0, &ldvl, vectorsright ? &MATRIX(*vectorsright, 0, 0) : 0, &ldvr, ilo, ihi, VECTOR(*myscale), abnrm, rconde ? VECTOR(*rconde) : 0, rcondv ? VECTOR(*rcondv) : 0, VECTOR(work), &lwork, VECTOR(iwork), info); lwork = (int) VECTOR(work)[0]; IGRAPH_CHECK(igraph_vector_resize(&work, lwork)); igraphdgeevx_(&balanc, &jobvl, &jobvr, &sense, &n, &MATRIX(Acopy, 0, 0), &lda, VECTOR(*myreal), VECTOR(*myimag), vectorsleft ? &MATRIX(*vectorsleft, 0, 0) : 0, &ldvl, vectorsright ? &MATRIX(*vectorsright, 0, 0) : 0, &ldvr, ilo, ihi, VECTOR(*myscale), abnrm, rconde ? VECTOR(*rconde) : 0, rcondv ? VECTOR(*rcondv) : 0, VECTOR(work), &lwork, VECTOR(iwork), info); if (*info < 0) { IGRAPH_ERROR("Cannot calculate eigenvalues (dgeev)", IGRAPH_ELAPACK); } else if (*info > 0) { if (error) { IGRAPH_ERROR("Cannot calculate eigenvalues (dgeev)", IGRAPH_ELAPACK); } else { IGRAPH_WARNING("Cannot calculate eigenvalues (dgeev)"); } } if (!scale) { igraph_vector_destroy(&vscale); IGRAPH_FINALLY_CLEAN(1); } if (!valuesimag) { igraph_vector_destroy(&vimag); IGRAPH_FINALLY_CLEAN(1); } if (!valuesreal) { igraph_vector_destroy(&vreal); IGRAPH_FINALLY_CLEAN(1); } igraph_vector_int_destroy(&iwork); igraph_vector_destroy(&work); igraph_matrix_destroy(&Acopy); IGRAPH_FINALLY_CLEAN(3); return 0; } int igraph_lapack_dgehrd(const igraph_matrix_t *A, int ilo, int ihi, igraph_matrix_t *result) { int n = (int) igraph_matrix_nrow(A); int lda = n; int lwork = -1; igraph_vector_t work; igraph_real_t optwork; igraph_vector_t tau; igraph_matrix_t Acopy; int info = 0; int i; if (igraph_matrix_ncol(A) != n) { IGRAPH_ERROR("Hessenberg reduction failed", IGRAPH_NONSQUARE); } if (ilo < 1 || ihi > n || ilo > ihi) { IGRAPH_ERROR("Invalid `ilo' and/or `ihi'", IGRAPH_EINVAL); } if (n <= 1) { IGRAPH_CHECK(igraph_matrix_update(result, A)); return 0; } IGRAPH_CHECK(igraph_matrix_copy(&Acopy, A)); IGRAPH_FINALLY(igraph_matrix_destroy, &Acopy); IGRAPH_VECTOR_INIT_FINALLY(&tau, n - 1); igraphdgehrd_(&n, &ilo, &ihi, &MATRIX(Acopy, 0, 0), &lda, VECTOR(tau), &optwork, &lwork, &info); if (info != 0) { IGRAPH_ERROR("Internal Hessenberg transformation error", IGRAPH_EINTERNAL); } lwork = (int) optwork; IGRAPH_VECTOR_INIT_FINALLY(&work, lwork); igraphdgehrd_(&n, &ilo, &ihi, &MATRIX(Acopy, 0, 0), &lda, VECTOR(tau), VECTOR(work), &lwork, &info); if (info != 0) { IGRAPH_ERROR("Internal Hessenberg transformation error", IGRAPH_EINTERNAL); } igraph_vector_destroy(&work); igraph_vector_destroy(&tau); IGRAPH_FINALLY_CLEAN(2); IGRAPH_CHECK(igraph_matrix_update(result, &Acopy)); igraph_matrix_destroy(&Acopy); IGRAPH_FINALLY_CLEAN(1); for (i = 0; i < n - 2; i++) { int j; for (j = i + 2; j < n; j++) { MATRIX(*result, j, i) = 0.0; } } return 0; } int igraph_lapack_ddot(const igraph_vector_t *v1, const igraph_vector_t *v2, igraph_real_t *res) { int n = igraph_vector_size(v1); int one = 1; if (igraph_vector_size(v2) != n) { IGRAPH_ERROR("Dot product of vectors with different dimensions", IGRAPH_EINVAL); } *res = igraphddot_(&n, VECTOR(*v1), &one, VECTOR(*v2), &one); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/complex.c0000644000076500000240000002741013614300625023215 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_complex.h" #include "igraph_math.h" #include /** * \example igraph_complex.c */ igraph_complex_t igraph_complex(igraph_real_t x, igraph_real_t y) { igraph_complex_t res; IGRAPH_REAL(res) = x; IGRAPH_IMAG(res) = y; return res; } igraph_complex_t igraph_complex_polar(igraph_real_t r, igraph_real_t theta) { igraph_complex_t res; IGRAPH_REAL(res) = r * cos(theta); IGRAPH_IMAG(res) = r * sin(theta); return res; } igraph_bool_t igraph_complex_eq_tol(igraph_complex_t z1, igraph_complex_t z2, igraph_real_t tol) { if (fabs(IGRAPH_REAL(z1) - IGRAPH_REAL(z2)) > tol || fabs(IGRAPH_IMAG(z1) - IGRAPH_IMAG(z2)) > tol) { return 0; } return 1; } igraph_real_t igraph_complex_mod(igraph_complex_t z) { igraph_real_t x = IGRAPH_REAL(z); igraph_real_t y = IGRAPH_IMAG(z); return hypot(x, y); } igraph_real_t igraph_complex_arg(igraph_complex_t z) { igraph_real_t x = IGRAPH_REAL(z); igraph_real_t y = IGRAPH_IMAG(z); if (x == 0.0 && y == 0.0) { return 0.0; } return atan2(y, x); } igraph_complex_t igraph_complex_add(igraph_complex_t z1, igraph_complex_t z2) { igraph_complex_t res; IGRAPH_REAL(res) = IGRAPH_REAL(z1) + IGRAPH_REAL(z2); IGRAPH_IMAG(res) = IGRAPH_IMAG(z1) + IGRAPH_IMAG(z2); return res; } igraph_complex_t igraph_complex_sub(igraph_complex_t z1, igraph_complex_t z2) { igraph_complex_t res; IGRAPH_REAL(res) = IGRAPH_REAL(z1) - IGRAPH_REAL(z2); IGRAPH_IMAG(res) = IGRAPH_IMAG(z1) - IGRAPH_IMAG(z2); return res; } igraph_complex_t igraph_complex_mul(igraph_complex_t z1, igraph_complex_t z2) { igraph_complex_t res; IGRAPH_REAL(res) = IGRAPH_REAL(z1) * IGRAPH_REAL(z2) - IGRAPH_IMAG(z1) * IGRAPH_IMAG(z2); IGRAPH_IMAG(res) = IGRAPH_REAL(z1) * IGRAPH_IMAG(z2) + IGRAPH_IMAG(z1) * IGRAPH_REAL(z2); return res; } igraph_complex_t igraph_complex_div(igraph_complex_t z1, igraph_complex_t z2) { igraph_complex_t res; igraph_real_t z1r = IGRAPH_REAL(z1), z1i = IGRAPH_IMAG(z1); igraph_real_t z2r = IGRAPH_REAL(z2), z2i = IGRAPH_IMAG(z2); igraph_real_t s = 1.0 / igraph_complex_abs(z2); igraph_real_t sz2r = s * z2r; igraph_real_t sz2i = s * z2i; IGRAPH_REAL(res) = (z1r * sz2r + z1i * sz2i) * s; IGRAPH_IMAG(res) = (z1i * sz2r - z1r * sz2i) * s; return res; } igraph_complex_t igraph_complex_add_real(igraph_complex_t z, igraph_real_t x) { igraph_complex_t res; IGRAPH_REAL(res) = IGRAPH_REAL(z) + x; IGRAPH_IMAG(res) = IGRAPH_IMAG(z); return res; } igraph_complex_t igraph_complex_add_imag(igraph_complex_t z, igraph_real_t y) { igraph_complex_t res; IGRAPH_REAL(res) = IGRAPH_REAL(z); IGRAPH_IMAG(res) = IGRAPH_IMAG(z) + y; return res; } igraph_complex_t igraph_complex_sub_real(igraph_complex_t z, igraph_real_t x) { igraph_complex_t res; IGRAPH_REAL(res) = IGRAPH_REAL(z) - x; IGRAPH_IMAG(res) = IGRAPH_IMAG(z); return res; } igraph_complex_t igraph_complex_sub_imag(igraph_complex_t z, igraph_real_t y) { igraph_complex_t res; IGRAPH_REAL(res) = IGRAPH_REAL(z); IGRAPH_IMAG(res) = IGRAPH_IMAG(z) - y; return res; } igraph_complex_t igraph_complex_mul_real(igraph_complex_t z, igraph_real_t x) { igraph_complex_t res; IGRAPH_REAL(res) = IGRAPH_REAL(z) * x; IGRAPH_IMAG(res) = IGRAPH_IMAG(z) * x; return res; } igraph_complex_t igraph_complex_mul_imag(igraph_complex_t z, igraph_real_t y) { igraph_complex_t res; IGRAPH_REAL(res) = - IGRAPH_IMAG(z) * y; IGRAPH_IMAG(res) = IGRAPH_REAL(z) * y; return res; } igraph_complex_t igraph_complex_div_real(igraph_complex_t z, igraph_real_t x) { igraph_complex_t res; IGRAPH_REAL(res) = IGRAPH_REAL(z) / x; IGRAPH_IMAG(res) = IGRAPH_IMAG(z) / x; return res; } igraph_complex_t igraph_complex_div_imag(igraph_complex_t z, igraph_real_t y) { igraph_complex_t res; IGRAPH_REAL(res) = IGRAPH_IMAG(z) / y; IGRAPH_IMAG(res) = - IGRAPH_REAL(z) / y; return res; } igraph_complex_t igraph_complex_conj(igraph_complex_t z) { igraph_complex_t res; IGRAPH_REAL(res) = IGRAPH_REAL(z); IGRAPH_IMAG(res) = - IGRAPH_IMAG(z); return res; } igraph_complex_t igraph_complex_neg(igraph_complex_t z) { igraph_complex_t res; IGRAPH_REAL(res) = - IGRAPH_REAL(z); IGRAPH_IMAG(res) = - IGRAPH_IMAG(z); return res; } igraph_complex_t igraph_complex_inv(igraph_complex_t z) { igraph_complex_t res; igraph_real_t s = 1.0 / igraph_complex_abs(z); IGRAPH_REAL(res) = (IGRAPH_REAL(z) * s) * s; IGRAPH_IMAG(res) = - (IGRAPH_IMAG(z) * s) * s; return res; } igraph_real_t igraph_complex_abs(igraph_complex_t z) { return hypot(IGRAPH_REAL(z), IGRAPH_IMAG(z)); } igraph_real_t igraph_complex_logabs(igraph_complex_t z) { igraph_real_t xabs = fabs(IGRAPH_REAL(z)); igraph_real_t yabs = fabs(IGRAPH_IMAG(z)); igraph_real_t max, u; if (xabs >= yabs) { max = xabs; u = yabs / xabs; } else { max = yabs; u = xabs / yabs; } return log (max) + 0.5 * log1p (u * u); } igraph_complex_t igraph_complex_sqrt(igraph_complex_t z) { igraph_complex_t res; if (IGRAPH_REAL(z) == 0.0 && IGRAPH_IMAG(z) == 0.0) { IGRAPH_REAL(res) = IGRAPH_IMAG(res) = 0.0; } else { igraph_real_t x = fabs (IGRAPH_REAL(z)); igraph_real_t y = fabs (IGRAPH_IMAG(z)); igraph_real_t w; if (x >= y) { igraph_real_t t = y / x; w = sqrt (x) * sqrt (0.5 * (1.0 + sqrt (1.0 + t * t))); } else { igraph_real_t t = x / y; w = sqrt (y) * sqrt (0.5 * (t + sqrt (1.0 + t * t))); } if (IGRAPH_REAL(z) >= 0.0) { igraph_real_t ai = IGRAPH_IMAG(z); IGRAPH_REAL(res) = w; IGRAPH_IMAG(res) = ai / (2.0 * w); } else { igraph_real_t ai = IGRAPH_IMAG(z); igraph_real_t vi = (ai >= 0) ? w : -w; IGRAPH_REAL(res) = ai / (2.0 * vi); IGRAPH_IMAG(res) = vi; } } return res; } igraph_complex_t igraph_complex_sqrt_real(igraph_real_t x) { igraph_complex_t res; if (x >= 0) { IGRAPH_REAL(res) = sqrt(x); IGRAPH_IMAG(res) = 0.0; } else { IGRAPH_REAL(res) = 0.0; IGRAPH_IMAG(res) = sqrt(-x); } return res; } igraph_complex_t igraph_complex_exp(igraph_complex_t z) { igraph_real_t rho = exp(IGRAPH_REAL(z)); igraph_real_t theta = IGRAPH_IMAG(z); igraph_complex_t res; IGRAPH_REAL(res) = rho * cos(theta); IGRAPH_IMAG(res) = rho * sin(theta); return res; } igraph_complex_t igraph_complex_pow(igraph_complex_t z1, igraph_complex_t z2) { igraph_complex_t res; if (IGRAPH_REAL(z1) == 0 && IGRAPH_IMAG(z1) == 0.0) { if (IGRAPH_REAL(z2) == 0 && IGRAPH_IMAG(z2) == 0.0) { IGRAPH_REAL(res) = 1.0; IGRAPH_IMAG(res) = 0.0; } else { IGRAPH_REAL(res) = IGRAPH_IMAG(res) = 0.0; } } else if (IGRAPH_REAL(z2) == 1.0 && IGRAPH_IMAG(z2) == 0.0) { IGRAPH_REAL(res) = IGRAPH_REAL(z1); IGRAPH_IMAG(res) = IGRAPH_IMAG(z1); } else if (IGRAPH_REAL(z2) == -1.0 && IGRAPH_IMAG(z2) == 0.0) { res = igraph_complex_inv(z1); } else { igraph_real_t logr = igraph_complex_logabs (z1); igraph_real_t theta = igraph_complex_arg (z1); igraph_real_t z2r = IGRAPH_REAL(z2), z2i = IGRAPH_IMAG(z2); igraph_real_t rho = exp (logr * z2r - z2i * theta); igraph_real_t beta = theta * z2r + z2i * logr; IGRAPH_REAL(res) = rho * cos(beta); IGRAPH_IMAG(res) = rho * sin(beta); } return res; } igraph_complex_t igraph_complex_pow_real(igraph_complex_t z, igraph_real_t x) { igraph_complex_t res; if (IGRAPH_REAL(z) == 0.0 && IGRAPH_IMAG(z) == 0.0) { if (x == 0) { IGRAPH_REAL(res) = 1.0; IGRAPH_IMAG(res) = 0.0; } else { IGRAPH_REAL(res) = IGRAPH_IMAG(res) = 0.0; } } else { igraph_real_t logr = igraph_complex_logabs(z); igraph_real_t theta = igraph_complex_arg(z); igraph_real_t rho = exp (logr * x); igraph_real_t beta = theta * x; IGRAPH_REAL(res) = rho * cos(beta); IGRAPH_IMAG(res) = rho * sin(beta); } return res; } igraph_complex_t igraph_complex_log(igraph_complex_t z) { igraph_complex_t res; IGRAPH_REAL(res) = igraph_complex_logabs(z); IGRAPH_IMAG(res) = igraph_complex_arg(z); return res; } igraph_complex_t igraph_complex_log10(igraph_complex_t z) { return igraph_complex_mul_real(igraph_complex_log(z), 1 / log(10.0)); } igraph_complex_t igraph_complex_log_b(igraph_complex_t z, igraph_complex_t b) { return igraph_complex_div (igraph_complex_log(z), igraph_complex_log(b)); } igraph_complex_t igraph_complex_sin(igraph_complex_t z) { igraph_real_t zr = IGRAPH_REAL(z); igraph_real_t zi = IGRAPH_IMAG(z); igraph_complex_t res; if (zi == 0.0) { IGRAPH_REAL(res) = sin(zr); IGRAPH_IMAG(res) = 0.0; } else { IGRAPH_REAL(res) = sin(zr) * cosh(zi); IGRAPH_IMAG(res) = cos(zr) * sinh(zi); } return res; } igraph_complex_t igraph_complex_cos(igraph_complex_t z) { igraph_real_t zr = IGRAPH_REAL(z); igraph_real_t zi = IGRAPH_IMAG(z); igraph_complex_t res; if (zi == 0.0) { IGRAPH_REAL(res) = cos(zr); IGRAPH_IMAG(res) = 0.0; } else { IGRAPH_REAL(res) = cos(zr) * cosh(zi); IGRAPH_IMAG(res) = sin(zr) * sinh(-zi); } return res; } igraph_complex_t igraph_complex_tan(igraph_complex_t z) { igraph_real_t zr = IGRAPH_REAL(z); igraph_real_t zi = IGRAPH_IMAG(z); igraph_complex_t res; if (fabs (zi) < 1) { igraph_real_t D = pow (cos (zr), 2.0) + pow (sinh (zi), 2.0); IGRAPH_REAL(res) = 0.5 * sin (2 * zr) / D; IGRAPH_IMAG(res) = 0.5 * sinh (2 * zi) / D; } else { igraph_real_t u = exp (-zi); igraph_real_t C = 2 * u / (1 - pow (u, 2.0)); igraph_real_t D = 1 + pow (cos (zr), 2.0) * pow (C, 2.0); igraph_real_t S = pow (C, 2.0); igraph_real_t T = 1.0 / tanh (zi); IGRAPH_REAL(res) = 0.5 * sin (2 * zr) * S / D; IGRAPH_IMAG(res) = T / D; } return res; } igraph_complex_t igraph_complex_sec(igraph_complex_t z) { return igraph_complex_inv(igraph_complex_cos(z)); } igraph_complex_t igraph_complex_csc(igraph_complex_t z) { return igraph_complex_inv(igraph_complex_sin(z)); } igraph_complex_t igraph_complex_cot(igraph_complex_t z) { return igraph_complex_inv(igraph_complex_tan(z)); } python-igraph-0.8.0/vendor/source/igraph/src/infomap_Greedy.cc0000644000076500000240000005440313614300625024643 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "infomap_Greedy.h" #include #define plogp( x ) ( (x) > 0.0 ? (x)*log(x) : 0.0 ) Greedy::Greedy(FlowGraph * fgraph) { graph = fgraph; Nnode = graph->Nnode; alpha = graph->alpha;// teleportation probability beta = 1.0 - alpha; // probability to take normal step Nempty = 0; vector(Nnode).swap(mod_empty); vector(Nnode).swap(node_index); vector(Nnode).swap(mod_exit); vector(Nnode).swap(mod_size); vector(Nnode).swap(mod_danglingSize); vector(Nnode).swap(mod_teleportWeight); vector(Nnode).swap(mod_members); nodeSize_log_nodeSize = graph->nodeSize_log_nodeSize; exit_log_exit = graph->exit_log_exit; size_log_size = graph->size_log_size; exitFlow = graph->exitFlow; Node ** node = graph->node; for (int i = 0; i < Nnode; i++) { // For each module node_index[i] = i; mod_exit[i] = node[i]->exit; mod_size[i] = node[i]->size; mod_danglingSize[i] = node[i]->danglingSize; mod_teleportWeight[i] = node[i]->teleportWeight; mod_members[i] = node[i]->members.size(); } exit = plogp(exitFlow); codeLength = exit - 2.0 * exit_log_exit + size_log_size - nodeSize_log_nodeSize; } Greedy::~Greedy() { } void delete_Greedy(Greedy *greedy) { delete greedy; } /** Greedy optimizing (as in Blodel and Al.) : * for each vertex (selected in a random order) compute the best possible move within neighborhood */ bool Greedy::optimize() { bool moved = false; Node ** node = graph->node; RNG_BEGIN(); // Generate random enumeration of nodes vector randomOrder(Nnode); for (int i = 0; i < Nnode; i++) { randomOrder[i] = i; } for (int i = 0; i < Nnode - 1; i++) { //int randPos = i ; //XXX int randPos = RNG_INTEGER(i, Nnode - 1); // swap i & randPos int tmp = randomOrder[i]; randomOrder[i] = randomOrder[randPos]; randomOrder[randPos] = tmp; } unsigned int offset = 1; vector redirect(Nnode, 0); vector > > flowNtoM(Nnode); for (int k = 0; k < Nnode; k++) { // Pick nodes in random order int flip = randomOrder[k]; int oldM = node_index[flip]; // Reset offset when int overflows if (offset > INT_MAX) { for (int j = 0; j < Nnode; j++) { redirect[j] = 0; } offset = 1; } // Size of vector with module links int NmodLinks = 0; // For all outLinks int NoutLinks = node[flip]->outLinks.size(); if (NoutLinks == 0) { //dangling node, add node to calculate flow below redirect[oldM] = offset + NmodLinks; flowNtoM[NmodLinks].first = oldM; flowNtoM[NmodLinks].second.first = 0.0; flowNtoM[NmodLinks].second.second = 0.0; NmodLinks++; } else { for (int j = 0; j < NoutLinks; j++) { int nb_M = node_index[node[flip]->outLinks[j].first]; // index destination du lien double nb_flow = node[flip]->outLinks[j].second; // wgt du lien if (redirect[nb_M] >= offset) { flowNtoM[redirect[nb_M] - offset].second.first += nb_flow; } else { redirect[nb_M] = offset + NmodLinks; flowNtoM[NmodLinks].first = nb_M; flowNtoM[NmodLinks].second.first = nb_flow; flowNtoM[NmodLinks].second.second = 0.0; NmodLinks++; } } } // For all inLinks int NinLinks = node[flip]->inLinks.size(); for (int j = 0; j < NinLinks; j++) { int nb_M = node_index[node[flip]->inLinks[j].first]; double nb_flow = node[flip]->inLinks[j].second; if (redirect[nb_M] >= offset) { flowNtoM[redirect[nb_M] - offset].second.second += nb_flow; } else { redirect[nb_M] = offset + NmodLinks; flowNtoM[NmodLinks].first = nb_M; flowNtoM[NmodLinks].second.first = 0.0; flowNtoM[NmodLinks].second.second = nb_flow; NmodLinks++; } } // For teleportation and dangling nodes for (int j = 0; j < NmodLinks; j++) { int newM = flowNtoM[j].first; if (newM == oldM) { flowNtoM[j].second.first += (alpha * node[flip]->size + beta * node[flip]->danglingSize) * (mod_teleportWeight[oldM] - node[flip]->teleportWeight); flowNtoM[j].second.second += (alpha * (mod_size[oldM] - node[flip]->size) + beta * (mod_danglingSize[oldM] - node[flip]->danglingSize)) * node[flip]->teleportWeight; } else { flowNtoM[j].second.first += (alpha * node[flip]->size + beta * node[flip]->danglingSize) * mod_teleportWeight[newM]; flowNtoM[j].second.second += (alpha * mod_size[newM] + beta * mod_danglingSize[newM] ) * node[flip]->teleportWeight; } } // Calculate flow to/from own module (default value if no link to // own module) double outFlowOldM = (alpha * node[flip]->size + beta * node[flip]->danglingSize) * (mod_teleportWeight[oldM] - node[flip]->teleportWeight) ; double inFlowOldM = (alpha * (mod_size[oldM] - node[flip]->size) + beta * (mod_danglingSize[oldM] - node[flip]->danglingSize)) * node[flip]->teleportWeight; if (redirect[oldM] >= offset) { outFlowOldM = flowNtoM[redirect[oldM] - offset].second.first; inFlowOldM = flowNtoM[redirect[oldM] - offset].second.second; } // Option to move to empty module (if node not already alone) if (mod_members[oldM] > static_cast(node[flip]->members.size())) { if (Nempty > 0) { flowNtoM[NmodLinks].first = mod_empty[Nempty - 1]; flowNtoM[NmodLinks].second.first = 0.0; flowNtoM[NmodLinks].second.second = 0.0; NmodLinks++; } } // Randomize link order for optimized search for (int j = 0; j < NmodLinks - 1; j++) { //int randPos = j ; // XXX int randPos = RNG_INTEGER(j, NmodLinks - 1); int tmp_M = flowNtoM[j].first; double tmp_outFlow = flowNtoM[j].second.first; double tmp_inFlow = flowNtoM[j].second.second; flowNtoM[j].first = flowNtoM[randPos].first; flowNtoM[j].second.first = flowNtoM[randPos].second.first; flowNtoM[j].second.second = flowNtoM[randPos].second.second; flowNtoM[randPos].first = tmp_M; flowNtoM[randPos].second.first = tmp_outFlow; flowNtoM[randPos].second.second = tmp_inFlow; } int bestM = oldM; double best_outFlow = 0.0; double best_inFlow = 0.0; double best_delta = 0.0; // Find the move that minimizes the description length for (int j = 0; j < NmodLinks; j++) { int newM = flowNtoM[j].first; double outFlowNewM = flowNtoM[j].second.first; double inFlowNewM = flowNtoM[j].second.second; if (newM != oldM) { double delta_exit = plogp(exitFlow + outFlowOldM + inFlowOldM - outFlowNewM - inFlowNewM) - exit; double delta_exit_log_exit = - plogp(mod_exit[oldM]) - plogp(mod_exit[newM]) + plogp(mod_exit[oldM] - node[flip]->exit + outFlowOldM + inFlowOldM) + plogp(mod_exit[newM] + node[flip]->exit - outFlowNewM - inFlowNewM); double delta_size_log_size = - plogp(mod_exit[oldM] + mod_size[oldM]) - plogp(mod_exit[newM] + mod_size[newM]) + plogp(mod_exit[oldM] + mod_size[oldM] - node[flip]->exit - node[flip]->size + outFlowOldM + inFlowOldM) + plogp(mod_exit[newM] + mod_size[newM] + node[flip]->exit + node[flip]->size - outFlowNewM - inFlowNewM); double deltaL = delta_exit - 2.0 * delta_exit_log_exit + delta_size_log_size; if (deltaL - best_delta < -1e-10) { bestM = newM; best_outFlow = outFlowNewM; best_inFlow = inFlowNewM; best_delta = deltaL; } } } // Make best possible move if (bestM != oldM) { //Update empty module vector if (mod_members[bestM] == 0) { Nempty--; } if (mod_members[oldM] == static_cast(node[flip]->members.size())) { mod_empty[Nempty] = oldM; Nempty++; } exitFlow -= mod_exit[oldM] + mod_exit[bestM]; exit_log_exit -= plogp(mod_exit[oldM]) + plogp(mod_exit[bestM]); size_log_size -= plogp(mod_exit[oldM] + mod_size[oldM]) + plogp(mod_exit[bestM] + mod_size[bestM]); mod_exit[oldM] -= node[flip]->exit - outFlowOldM - inFlowOldM; mod_size[oldM] -= node[flip]->size; mod_danglingSize[oldM] -= node[flip]->danglingSize; mod_teleportWeight[oldM] -= node[flip]->teleportWeight; mod_members[oldM] -= node[flip]->members.size(); mod_exit[bestM] += node[flip]->exit - best_outFlow - best_inFlow; mod_size[bestM] += node[flip]->size; mod_danglingSize[bestM] += node[flip]->danglingSize; mod_teleportWeight[bestM] += node[flip]->teleportWeight; mod_members[bestM] += node[flip]->members.size(); exitFlow += mod_exit[oldM] + mod_exit[bestM]; // Update terms in map equation exit_log_exit += plogp(mod_exit[oldM]) + plogp(mod_exit[bestM]); size_log_size += plogp(mod_exit[oldM] + mod_size[oldM]) + plogp(mod_exit[bestM] + mod_size[bestM]); exit = plogp(exitFlow); // Update code length codeLength = exit - 2.0 * exit_log_exit + size_log_size - nodeSize_log_nodeSize; node_index[flip] = bestM; moved = true; } offset += Nnode; } RNG_END(); return moved; } /** Apply the move to the given network */ void Greedy::apply(bool sort) { //void Greedy::level(Node ***node_tmp, bool sort) { //old fct prepare(sort) vector modSnode; // will give ids of no-empty modules (nodes) int Nmod = 0; if (sort) { multimap Msize; for (int i = 0; i < Nnode; i++) { if (mod_members[i] > 0) { Nmod++; Msize.insert(pair(mod_size[i], i)); } } for (multimap::reverse_iterator it = Msize.rbegin(); it != Msize.rend(); it++) { modSnode.push_back(it->second); } } else { for (int i = 0; i < Nnode; i++) { if (mod_members[i] > 0) { Nmod++; modSnode.push_back(i); } } } //modSnode[id_when_no_empty_node] = id_in_mod_tbl // Create the new graph FlowGraph * tmp_fgraph = new FlowGraph(Nmod); IGRAPH_FINALLY(delete_FlowGraph, tmp_fgraph); Node ** node_tmp = tmp_fgraph->node ; Node ** node = graph->node; vector nodeInMod = vector(Nnode); // creation of new nodes for (int i = 0; i < Nmod; i++) { //node_tmp[i] = new Node(); vector().swap(node_tmp[i]->members); // clear membership node_tmp[i]->exit = mod_exit[modSnode[i]]; node_tmp[i]->size = mod_size[modSnode[i]]; node_tmp[i]->danglingSize = mod_danglingSize[modSnode[i]]; node_tmp[i]->teleportWeight = mod_teleportWeight[modSnode[i]]; nodeInMod[modSnode[i]] = i; } //nodeInMode[id_in_mod_tbl] = id_when_no_empty_node // Calculate outflow of links to different modules vector > outFlowNtoM(Nmod); map::iterator it_M; for (int i = 0; i < Nnode; i++) { int i_M = nodeInMod[node_index[i]]; //final id of the module of the node i // add node members to the module copy( node[i]->members.begin(), node[i]->members.end(), back_inserter( node_tmp[i_M]->members ) ); int NoutLinks = node[i]->outLinks.size(); for (int j = 0; j < NoutLinks; j++) { int nb = node[i]->outLinks[j].first; int nb_M = nodeInMod[node_index[nb]]; double nb_flow = node[i]->outLinks[j].second; if (nb != i) { it_M = outFlowNtoM[i_M].find(nb_M); if (it_M != outFlowNtoM[i_M].end()) { it_M->second += nb_flow; } else { outFlowNtoM[i_M].insert(make_pair(nb_M, nb_flow)); } } } } // Create outLinks at new level for (int i = 0; i < Nmod; i++) { for (it_M = outFlowNtoM[i].begin(); it_M != outFlowNtoM[i].end(); it_M++) { if (it_M->first != i) { node_tmp[i]->outLinks.push_back(make_pair(it_M->first, it_M->second)); } } } // Calculate inflow of links from different modules vector > inFlowNtoM(Nmod); for (int i = 0; i < Nnode; i++) { int i_M = nodeInMod[node_index[i]]; int NinLinks = node[i]->inLinks.size(); for (int j = 0; j < NinLinks; j++) { int nb = node[i]->inLinks[j].first; int nb_M = nodeInMod[node_index[nb]]; double nb_flow = node[i]->inLinks[j].second; if (nb != i) { it_M = inFlowNtoM[i_M].find(nb_M); if (it_M != inFlowNtoM[i_M].end()) { it_M->second += nb_flow; } else { inFlowNtoM[i_M].insert(make_pair(nb_M, nb_flow)); } } } } // Create inLinks at new level for (int i = 0; i < Nmod; i++) { for (it_M = inFlowNtoM[i].begin(); it_M != inFlowNtoM[i].end(); it_M++) { if (it_M->first != i) { node_tmp[i]->inLinks.push_back(make_pair(it_M->first, it_M->second)); } } } // Option to move to empty module vector().swap(mod_empty); Nempty = 0; //swap node between tmp_graph and graph, then destroy tmp_fgraph graph->swap(tmp_fgraph); Nnode = Nmod; delete tmp_fgraph; IGRAPH_FINALLY_CLEAN(1); } /** * RAZ et recalcul : * - mod_exit * - mod_size * - mod_danglingSize * - mod_teleportWeight * - mod_members * and * - exit_log_exit * - size_log_size * - exitFlow * - exit * - codeLength * according to **node / node[i]->index */ void Greedy::tune(void) { exit_log_exit = 0.0; size_log_size = 0.0; exitFlow = 0.0; for (int i = 0; i < Nnode; i++) { mod_exit[i] = 0.0; mod_size[i] = 0.0; mod_danglingSize[i] = 0.0; mod_teleportWeight[i] = 0.0; mod_members[i] = 0; } Node ** node = graph->node; // Update all values except contribution from teleportation for (int i = 0; i < Nnode; i++) { int i_M = node_index[i]; // module id of node i int Nlinks = node[i]->outLinks.size(); mod_size[i_M] += node[i]->size; mod_danglingSize[i_M] += node[i]->danglingSize; mod_teleportWeight[i_M] += node[i]->teleportWeight; mod_members[i_M]++; for (int j = 0; j < Nlinks; j++) { int neighbor = node[i]->outLinks[j].first; double neighbor_w = node[i]->outLinks[j].second; int neighbor_M = node_index[neighbor]; if (i_M != neighbor_M) { // neighbor in an other module mod_exit[i_M] += neighbor_w; } } } // Update contribution from teleportation for (int i = 0; i < Nnode; i++) { mod_exit[i] += (alpha * mod_size[i] + beta * mod_danglingSize[i]) * (1.0 - mod_teleportWeight[i]); } for (int i = 0; i < Nnode; i++) { exit_log_exit += plogp(mod_exit[i]); size_log_size += plogp(mod_exit[i] + mod_size[i]); exitFlow += mod_exit[i]; } exit = plogp(exitFlow); codeLength = exit - 2.0 * exit_log_exit + size_log_size - nodeSize_log_nodeSize; } /* Compute the new CodeSize if modules are merged as indicated by moveTo */ void Greedy::setMove(int *moveTo) { //void Greedy::determMove(int *moveTo) { Node ** node = graph->node; //printf("setMove nNode:%d \n", Nnode); for (int i = 0 ; i < Nnode ; i++) { // pour chaque module int oldM = i; int newM = moveTo[i]; //printf("old -> new : %d -> %d \n", oldM, newM); if (newM != oldM) { // Si je comprend bien : // outFlow... : c'est le "flow" de i-> autre sommet du meme module // inFlow... : c'est le "flow" depuis un autre sommet du meme module --> i double outFlowOldM = (alpha * node[i]->size + beta * node[i]->danglingSize) * (mod_teleportWeight[oldM] - node[i]->teleportWeight); double inFlowOldM = (alpha * (mod_size[oldM] - node[i]->size) + beta * (mod_danglingSize[oldM] - node[i]->danglingSize)) * node[i]->teleportWeight; double outFlowNewM = (alpha * node[i]->size + beta * node[i]->danglingSize) * mod_teleportWeight[newM]; double inFlowNewM = (alpha * mod_size[newM] + beta * mod_danglingSize[newM]) * node[i]->teleportWeight; // For all outLinks int NoutLinks = node[i]->outLinks.size(); for (int j = 0; j < NoutLinks; j++) { int nb_M = node_index[node[i]->outLinks[j].first]; double nb_flow = node[i]->outLinks[j].second; if (nb_M == oldM) { outFlowOldM += nb_flow; } else if (nb_M == newM) { outFlowNewM += nb_flow; } } // For all inLinks int NinLinks = node[i]->inLinks.size(); for (int j = 0; j < NinLinks; j++) { int nb_M = node_index[node[i]->inLinks[j].first]; double nb_flow = node[i]->inLinks[j].second; if (nb_M == oldM) { inFlowOldM += nb_flow; } else if (nb_M == newM) { inFlowNewM += nb_flow; } } // Update empty module vector // RAZ de mod_empty et Nempty ds calibrate() if (mod_members[newM] == 0) { // si le nouveau etait vide, on a un vide de moins... Nempty--; } if (mod_members[oldM] == static_cast(node[i]->members.size())) { // si l'ancien avait la taille de celui qui bouge, un vide de plus mod_empty[Nempty] = oldM; Nempty++; } exitFlow -= mod_exit[oldM] + mod_exit[newM]; exit_log_exit -= plogp(mod_exit[oldM]) + plogp(mod_exit[newM]); size_log_size -= plogp(mod_exit[oldM] + mod_size[oldM]) + plogp(mod_exit[newM] + mod_size[newM]); mod_exit[oldM] -= node[i]->exit - outFlowOldM - inFlowOldM; mod_size[oldM] -= node[i]->size; mod_danglingSize[oldM] -= node[i]->danglingSize; mod_teleportWeight[oldM] -= node[i]->teleportWeight; mod_members[oldM] -= node[i]->members.size(); mod_exit[newM] += node[i]->exit - outFlowNewM - inFlowNewM; mod_size[newM] += node[i]->size; mod_danglingSize[newM] += node[i]->danglingSize; mod_teleportWeight[newM] += node[i]->teleportWeight; mod_members[newM] += node[i]->members.size(); exitFlow += mod_exit[oldM] + mod_exit[newM]; exit_log_exit += plogp(mod_exit[oldM]) + plogp(mod_exit[newM]); size_log_size += plogp(mod_exit[oldM] + mod_size[oldM]) + plogp(mod_exit[newM] + mod_size[newM]); exit = plogp(exitFlow); codeLength = exit - 2.0 * exit_log_exit + size_log_size - nodeSize_log_nodeSize; node_index[i] = newM; } } } python-igraph-0.8.0/vendor/source/igraph/src/infomap_Node.cc0000644000076500000240000000425613614300625024312 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "infomap_Node.h" Node::Node() { exit = 0.0; size = 0.0; selfLink = 0.0; } Node::Node(int nodenr, double tpweight) { teleportWeight = tpweight; exit = 0.0; size = 0.0; selfLink = 0.0; members.push_back(nodenr); // members = [nodenr] } void cpyNode(Node *newNode, Node *oldNode) { newNode->exit = oldNode->exit; newNode->size = oldNode->size; newNode->teleportWeight = oldNode->teleportWeight; newNode->danglingSize = oldNode->danglingSize; int Nmembers = oldNode->members.size(); newNode->members = vector(Nmembers); for (int i = 0; i < Nmembers; i++) { newNode->members[i] = oldNode->members[i]; } newNode->selfLink = oldNode->selfLink; int NoutLinks = oldNode->outLinks.size(); newNode->outLinks = vector >(NoutLinks); for (int i = 0; i < NoutLinks; i++) { newNode->outLinks[i].first = oldNode->outLinks[i].first; newNode->outLinks[i].second = oldNode->outLinks[i].second; } int NinLinks = oldNode->inLinks.size(); newNode->inLinks = vector >(NinLinks); for (int i = 0; i < NinLinks; i++) { newNode->inLinks[i].first = oldNode->inLinks[i].first; newNode->inLinks[i].second = oldNode->inLinks[i].second; } } python-igraph-0.8.0/vendor/source/igraph/src/igraph_hrg_types.cc0000644000076500000240000036363413614300625025262 0ustar tamasstaff00000000000000// *********************************************************************** // *** COPYRIGHT NOTICE ************************************************** // rbtree - red-black tree (self-balancing binary tree data structure) // Copyright (C) 2004 Aaron Clauset // // This program is free software; you can redistribute it and/or modify // it under the terms of the GNU General Public License as published by // the Free Software Foundation; either version 2 of the License, or // (at your option) any later version. // // This program is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU General Public License for more details. // // You should have received a copy of the GNU General Public License // along with this program; if not, write to the Free Software // Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA // // See http://www.gnu.org/licenses/gpl.txt for more details. // // *********************************************************************** // Author : Aaron Clauset ( aaronc@santafe.edu | // http://www.santafe.edu/~aaronc/ ) // Collaborators: Cristopher Moore and Mark Newman // Project : Hierarchical Random Graphs // Location : University of New Mexico, Dept. of Computer Science // AND Santa Fe Institute // Created : Spring 2004 // Modified : many, many times // // *********************************************************************** #include "hrg_rbtree.h" #include "hrg_dendro.h" #include "hrg_graph.h" #include "hrg_splittree_eq.h" #include "hrg_graph_simp.h" #include "igraph_hrg.h" #include "igraph_constructors.h" #include "igraph_random.h" using namespace fitHRG; // ******** Red-Black Tree Methods *************************************** rbtree::rbtree() { root = new elementrb; leaf = new elementrb; leaf->parent = root; root->left = leaf; root->right = leaf; support = 0; } rbtree::~rbtree() { if (root != NULL && (root->left != leaf || root->right != leaf)) { deleteSubTree(root); } if (root) { delete root; } delete leaf; support = 0; root = 0; leaf = 0; } void rbtree::deleteTree() { if (root != NULL) { deleteSubTree(root); } } // does not leak memory void rbtree::deleteSubTree(elementrb *z) { if (z->left != leaf) { deleteSubTree(z->left); } if (z->right != leaf) { deleteSubTree(z->right); } delete z; } // ******** Search Functions ********************************************* // public search function - if there exists a elementrb in the tree // with key=searchKey, it returns TRUE and foundNode is set to point // to the found node; otherwise, it sets foundNode=NULL and returns // FALSE elementrb* rbtree::findItem(const int searchKey) { elementrb *current = root; // empty tree; bail out if (current->key == -1) { return NULL; } while (current != leaf) { // left-or-right? if (searchKey < current->key) { // try moving down-left if (current->left != leaf) { current = current->left; } else { // failure; bail out return NULL; } } else { // left-or-right? if (searchKey > current->key) { // try moving down-left if (current->right != leaf) { current = current->right; } else { // failure; bail out return NULL; } } else { // found (searchKey==current->key) return current; } } } return NULL; } int rbtree::returnValue(const int searchKey) { elementrb* test = findItem(searchKey); if (!test) { return 0; } else { return test->value; } } // ******** Return Item Functions **************************************** int* rbtree::returnArrayOfKeys() { int* array; array = new int [support]; bool flag_go = true; int index = 0; elementrb *curr; if (support == 1) { array[0] = root->key; } else if (support == 2) { array[0] = root->key; if (root->left == leaf) { array[1] = root->right->key; } else { array[1] = root->left->key; } } else { for (int i = 0; i < support; i++) { array[i] = -1; } // non-recursive traversal of tree structure curr = root; curr->mark = 1; while (flag_go) { // - is it time, and is left child the leaf node? if (curr->mark == 1 && curr->left == leaf) { curr->mark = 2; } // - is it time, and is right child the leaf node? if (curr->mark == 2 && curr->right == leaf) { curr->mark = 3; } if (curr->mark == 1) { // - go left curr->mark = 2; curr = curr->left; curr->mark = 1; } else if (curr->mark == 2) { // - else go right curr->mark = 3; curr = curr->right; curr->mark = 1; } else { // - else go up a level curr->mark = 0; array[index++] = curr->key; curr = curr->parent; if (curr == NULL) { flag_go = false; } } } } return array; } list* rbtree::returnListOfKeys() { keyValuePair *curr, *prev; list *head = 0, *tail = 0, *newlist; curr = returnTreeAsList(); while (curr != NULL) { newlist = new list; newlist->x = curr->x; if (head == NULL) { head = newlist; tail = head; } else { tail->next = newlist; tail = newlist; } prev = curr; curr = curr->next; delete prev; prev = NULL; } return head; } keyValuePair* rbtree::returnTreeAsList() { // pre-order traversal keyValuePair *head, *tail; head = new keyValuePair; head->x = root->key; head->y = root->value; tail = head; if (root->left != leaf) { tail = returnSubtreeAsList(root->left, tail); } if (root->right != leaf) { tail = returnSubtreeAsList(root->right, tail); } if (head->x == -1) { return NULL; /* empty tree */ } else { return head; } } keyValuePair* rbtree::returnSubtreeAsList(elementrb *z, keyValuePair *head) { keyValuePair *newnode, *tail; newnode = new keyValuePair; newnode->x = z->key; newnode->y = z->value; head->next = newnode; tail = newnode; if (z->left != leaf) { tail = returnSubtreeAsList(z->left, tail); } if (z->right != leaf) { tail = returnSubtreeAsList(z->right, tail); } return tail; } keyValuePair rbtree::returnMaxKey() { keyValuePair themax; elementrb *current; current = root; // search to bottom-right corner of tree while (current->right != leaf) { current = current->right; } themax.x = current->key; themax.y = current->value; return themax; } keyValuePair rbtree::returnMinKey() { keyValuePair themin; elementrb *current; current = root; // search to bottom-left corner of tree while (current->left != leaf) { current = current->left; } themin.x = current->key; themin.y = current->value; return themin; } // private functions for deleteItem() (although these could easily be // made public, I suppose) elementrb* rbtree::returnMinKey(elementrb *z) { elementrb *current; current = z; // search to bottom-right corner of tree while (current->left != leaf) { current = current->left; } return current; } elementrb* rbtree::returnSuccessor(elementrb *z) { elementrb *current, *w; w = z; // if right-subtree exists, return min of it if (w->right != leaf) { return returnMinKey(w->right); } // else search up in tree current = w->parent; while ((current != NULL) && (w == current->right)) { w = current; // move up in tree until find a non-right-child current = current->parent; } return current; } int rbtree::returnNodecount() { return support; } // ******** Insert Functions ********************************************* // public insert function void rbtree::insertItem(int newKey, int newValue) { // first we check to see if newKey is already present in the tree; // if so, we do nothing; if not, we must find where to insert the // key elementrb *newNode, *current; // find newKey in tree; return pointer to it O(log k) current = findItem(newKey); if (current == NULL) { newNode = new elementrb; // elementrb for the rbtree newNode->key = newKey; newNode->value = newValue; newNode->color = true; // new nodes are always RED newNode->parent = NULL; // new node initially has no parent newNode->left = leaf; // left leaf newNode->right = leaf; // right leaf support++; // increment node count in rbtree // must now search for where to insert newNode, i.e., find the // correct parent and set the parent and child to point to each // other properly current = root; if (current->key == -1) { // insert as root delete root; // delete old root root = newNode; // set root to newNode leaf->parent = newNode; // set leaf's parent current = leaf; // skip next loop } // search for insertion point while (current != leaf) { // left-or-right? if (newKey < current->key) { // try moving down-left if (current->left != leaf) { current = current->left; } else { // else found new parent newNode->parent = current; // set parent current->left = newNode; // set child current = leaf; // exit search } } else { // try moving down-right if (current->right != leaf) { current = current->right; } else { // else found new parent newNode->parent = current; // set parent current->right = newNode; // set child current = leaf; // exit search } } } // now do the house-keeping necessary to preserve the red-black // properties insertCleanup(newNode); } return; } // private house-keeping function for insertion void rbtree::insertCleanup(elementrb *z) { // fix now if z is root if (z->parent == NULL) { z->color = false; return; } elementrb *temp; // while z is not root and z's parent is RED while (z->parent != NULL && z->parent->color) { if (z->parent == z->parent->parent->left) { // z's parent is LEFT-CHILD temp = z->parent->parent->right; // grab z's uncle if (temp->color) { z->parent->color = false; // color z's parent BLACK (Case 1) temp->color = false; // color z's uncle BLACK (Case 1) z->parent->parent->color = true; // color z's grandpar. RED (Case 1) z = z->parent->parent; // set z = z's grandparent (Case 1) } else { if (z == z->parent->right) { // z is RIGHT-CHILD z = z->parent; // set z = z's parent (Case 2) rotateLeft(z); // perform left-rotation (Case 2) } z->parent->color = false; // color z's parent BLACK (Case 3) z->parent->parent->color = true; // color z's grandpar. RED (Case 3) rotateRight(z->parent->parent); // perform right-rotation (Case 3) } } else { // z's parent is RIGHT-CHILD temp = z->parent->parent->left; // grab z's uncle if (temp->color) { z->parent->color = false; // color z's parent BLACK (Case 1) temp->color = false; // color z's uncle BLACK (Case 1) z->parent->parent->color = true; // color z's grandpar. RED (Case 1) z = z->parent->parent; // set z = z's grandparent (Case 1) } else { if (z == z->parent->left) { // z is LEFT-CHILD z = z->parent; // set z = z's parent (Case 2) rotateRight(z); // perform right-rotation (Case 2) } z->parent->color = false; // color z's parent BLACK (Case 3) z->parent->parent->color = true; // color z's grandpar. RED (Case 3) rotateLeft(z->parent->parent); // perform left-rotation (Case 3) } } } root->color = false; // color the root BLACK return; } // ******** Delete // ******** Functions ********************************************* void rbtree::replaceItem(int key, int newValue) { elementrb* ptr; ptr = findItem(key); ptr->value = newValue; return; } void rbtree::incrementValue(int key) { elementrb* ptr; ptr = findItem(key); ptr->value = 1 + ptr->value; return; } // public delete function void rbtree::deleteItem(int killKey) { elementrb *x, *y, *z; z = findItem(killKey); if (z == NULL) { return; // item not present; bail out } if (support == 1) { // attempt to delete the root root->key = -1; // restore root node to default state root->value = -1; root->color = false; root->parent = NULL; root->left = leaf; root->right = leaf; support--; // set support to zero return; // exit - no more work to do } if (z != NULL) { support--; // decrement node count if ((z->left == leaf) || (z->right == leaf)) { y = z; // case of less than two children, // set y to be z } else { y = returnSuccessor(z); // set y to be z's key-successor } if (y->left != leaf) { x = y->left; // pick y's one child (left-child) } else { x = y->right; // (right-child) } x->parent = y->parent; // make y's child's parent be y's parent if (y->parent == NULL) { root = x; // if y is the root, x is now root } else { if (y == y->parent->left) { // decide y's relationship with y's parent y->parent->left = x; // replace x as y's parent's left child } else { y->parent->right = x; // replace x as y's parent's left child } } if (y != z) { // insert y into z's spot z->key = y->key; // copy y data into z z->value = y->value; } // do house-keeping to maintain balance if (y->color == false) { deleteCleanup(x); } delete y; y = NULL; } return; } void rbtree::deleteCleanup(elementrb *x) { elementrb *w, *t; // until x is the root, or x is RED while ((x != root) && (x->color == false)) { if (x == x->parent->left) { // branch on x being a LEFT-CHILD w = x->parent->right; // grab x's sibling if (w->color == true) { // if x's sibling is RED w->color = false; // color w BLACK (case 1) x->parent->color = true; // color x's parent RED (case 1) rotateLeft(x->parent); // left rotation on x's parent (case 1) w = x->parent->right; // make w be x's right sibling (case 1) } if ((w->left->color == false) && (w->right->color == false)) { w->color = true; // color w RED (case 2) x = x->parent; // examine x's parent (case 2) } else { if (w->right->color == false) { w->left->color = false; // color w's left child BLACK (case 3) w->color = true; // color w RED (case 3) t = x->parent; // store x's parent (case 3) rotateRight(w); // right rotation on w (case 3) x->parent = t; // restore x's parent (case 3) w = x->parent->right; // make w be x's right sibling (case 3) } w->color = x->parent->color; // w's color := x's parent's (case 4) x->parent->color = false; // color x's parent BLACK (case 4) w->right->color = false; // color w's right child BLACK (case 4) rotateLeft(x->parent); // left rotation on x's parent (case 4) x = root; // finished work. bail out (case 4) } } else { // x is RIGHT-CHILD w = x->parent->left; // grab x's sibling if (w->color == true) { // if x's sibling is RED w->color = false; // color w BLACK (case 1) x->parent->color = true; // color x's parent RED (case 1) rotateRight(x->parent); // right rotation on x's parent (case 1) w = x->parent->left; // make w be x's left sibling (case 1) } if ((w->right->color == false) && (w->left->color == false)) { w->color = true; // color w RED (case 2) x = x->parent; // examine x's parent (case 2) } else { if (w->left->color == false) { w->right->color = false; // color w's right child BLACK (case 3) w->color = true; // color w RED (case 3) t = x->parent; // store x's parent (case 3) rotateLeft(w); // left rotation on w (case 3) x->parent = t; // restore x's parent (case 3) w = x->parent->left; // make w be x's left sibling (case 3) } w->color = x->parent->color; // w's color := x's parent's (case 4) x->parent->color = false; // color x's parent BLACK (case 4) w->left->color = false; // color w's left child BLACK (case 4) rotateRight(x->parent); // right rotation on x's parent (case 4) x = root; // x is now the root (case 4) } } } x->color = false; // color x (the root) BLACK (exit) return; } // ******** Rotation Functions ****************************************** void rbtree::rotateLeft(elementrb *x) { elementrb *y; // do pointer-swapping operations for left-rotation y = x->right; // grab right child x->right = y->left; // make x's RIGHT-CHILD be y's LEFT-CHILD y->left->parent = x; // make x be y's LEFT-CHILD's parent y->parent = x->parent; // make y's new parent be x's old parent if (x->parent == NULL) { root = y; // if x was root, make y root } else { // if x is LEFT-CHILD, make y be x's parent's if (x == x->parent->left) { x->parent->left = y; // left-child } else { x->parent->right = y; // right-child } } y->left = x; // make x be y's LEFT-CHILD x->parent = y; // make y be x's parent return; } void rbtree::rotateRight(elementrb *y) { elementrb *x; // do pointer-swapping operations for right-rotation x = y->left; // grab left child y->left = x->right; // replace left child yith x's right subtree x->right->parent = y; // replace y as x's right subtree's parent x->parent = y->parent; // make x's new parent be y's old parent // if y was root, make x root if (y->parent == NULL) { root = x; } else { // if y is RIGHT-CHILD, make x be y's parent's if (y == y->parent->right) { // right-child y->parent->right = x; } else { // left-child y->parent->left = x; } } x->right = y; // make y be x's RIGHT-CHILD y->parent = x; // make x be y's parent return; } // *********************************************************************** // *** COPYRIGHT NOTICE ************************************************** // dendro.h - hierarchical random graph (hrg) data structure // Copyright (C) 2005-2009 Aaron Clauset // // This program is free software; you can redistribute it and/or modify // it under the terms of the GNU General Public License as published by // the Free Software Foundation; either version 2 of the License, or // (at your option) any later version. // // This program is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU General Public License for more details. // // You should have received a copy of the GNU General Public License // along with this program; if not, write to the Free Software // Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA // // See http://www.gnu.org/licenses/gpl.txt for more details. // // *********************************************************************** // Author : Aaron Clauset ( aaronc@santafe.edu | // http://www.santafe.edu/~aaronc/ ) // Collaborators: Cristopher Moore and Mark E.J. Newman // Project : Hierarchical Random Graphs // Location : University of New Mexico, Dept. of Computer Science // AND Santa Fe Institute // Created : 26 October 2005 - 7 December 2005 // Modified : 23 December 2007 (cleaned up for public consumption) // // *********************************************************************** // // Maximum likelihood dendrogram data structure. This is the heart of // the HRG algorithm: all manipulations are done here and all data is // stored here. The data structure uses the separate graph data // structure to store the basic adjacency information (in a // dangerously mutable way). // // *********************************************************************** // ******** Dendrogram Methods ******************************************* dendro::dendro(): root(0), internal(0), leaf(0), d(0), splithist(0), paths(0), ctree(0), cancestor(0), g(0) { } dendro::~dendro() { list *curr, *prev; if (g) { delete g; // O(m) g = 0; } if (internal) { delete [] internal; // O(n) internal = 0; } if (leaf) { delete [] leaf; // O(n) leaf = 0; } if (d) { delete d; // O(n) d = 0; } if (splithist) { delete splithist; // potentially long splithist = 0; } if (paths) { for (int i = 0; i < n; i++) { curr = paths[i]; while (curr) { prev = curr; curr = curr->next; delete prev; prev = 0; } paths[i] = 0; } delete [] paths; } paths = 0; if (ctree) { delete [] ctree; // O(n) ctree = 0; } if (cancestor) { delete [] cancestor; // O(n) cancestor = 0; } } // ********************************************************************* void dendro::binarySearchInsert(elementd* x, elementd* y) { if (y->p < x->p) { // go to left subtree if (x->L == NULL) { // check if left subtree is empty x->L = y; // make x left child y->M = x; // make y parent of child return; } else { binarySearchInsert(x->L, y); } } else { // go to right subtree if (x->R == NULL) { // check if right subtree is empty x->R = y; // make x right child y->M = x; // make y parent of child return; } else { binarySearchInsert(x->R, y); } } return; } // ********************************************************************** list* dendro::binarySearchFind(const double v) { list *head = NULL, *tail = NULL, *newlist; elementd *current = root; bool flag_stopSearch = false; while (!flag_stopSearch) { // continue until we're finished newlist = new list; // add this node to the path newlist->x = current->label; if (current == root) { head = newlist; tail = head; } else { tail->next = newlist; tail = newlist; } if (v < current->p) { // now try left subtree if (current->L->type == GRAPH) { flag_stopSearch = true; } else { current = current->L; } } else { // else try right subtree if (current->R->type == GRAPH) { flag_stopSearch = true; } else { current = current->R; } } } return head; } // *********************************************************************** string dendro::buildSplit(elementd* thisNode) { // A "split" is defined as the bipartition of vertices into the sets // of leaves below the internal vertex in the tree (denoted by "C"), // and those above it (denoted as "M"). For simplicity, we represent // this bipartition as a character string of length n, where the ith // character denotes the partition membership (C,M) of the ith leaf // node. bool flag_go = true; const short int k = 1 + DENDRO + GRAPH; elementd* curr; split sp; sp.initializeSplit(n); // default split string O(n) curr = thisNode; // - set start node as top this sub-tree curr->type = k + 1; // - initialize in-order tree traversal while (flag_go) { // - is it time, and is left child a graph node? if (curr->type == k + 1 && curr->L->type == GRAPH) { sp.s[curr->L->index] = 'C'; // - mark this leaf curr->type = k + 2; } // - is it time, and is right child a graph node? if (curr->type == k + 2 && curr->R->type == GRAPH) { sp.s[curr->R->index] = 'C'; // - mark this leaf curr->type = k + 3; } if (curr->type == k + 1) { // - go left curr->type = k + 2; curr = curr->L; curr->type = k + 1; } else if (curr->type == k + 2) { // - else go right curr->type = k + 3; curr = curr->R; curr->type = k + 1; } else { // - else go up a level curr->type = DENDRO; if (curr->index == thisNode->index || curr->M == NULL) { flag_go = false; curr = NULL; } else { curr = curr->M; } } } // any leaf that was not already marked must be in the remainder of // the tree for (int i = 0; i < n; i++) { if (sp.s[i] != 'C') { sp.s[i] = 'M'; } } return sp.s; } // ********************************************************************** void dendro::buildDendrogram() { /* the initialization of the dendrogram structure goes like this: * 1) we allocate space for the n-1 internal nodes of the * dendrogram, and then the n leaf nodes * 2) we build a random binary tree structure out of the internal * nodes by assigning each a uniformly random value over [0,1] and * then inserting it into the tree according to the * binary-search rule. * 3) next, we make a random permutation of the n leaf nodes and add * them to the dendrogram D by replacing the emptpy spots in-order * 4) then, we compute the path from the root to each leaf and store * that in each leaf (this is prep work for the next step) * 5) finally, we compute the values for nL, nR, e (and thus p) and * the label for each internal node by allocating each of the m * edges in g to the appropriate internal node */ // --- Initialization and memory allocation for data structures // After allocating the memory for D and G, we need to mark the // nodes for G as being non-internal vertices, and then insert them // into a random binary tree structure. For simplicity, we make the // first internal node in the array the root. n = g->numNodes(); // size of graph leaf = new elementd [n]; // allocate memory for G, O(n) internal = new elementd [n - 1]; // allocate memory for D, O(n) d = new interns(n - 2); // allocate memory for internal // edges of D, O(n) for (int i = 0; i < n; i++) { // initialize leaf nodes leaf[i].type = GRAPH; leaf[i].label = i; leaf[i].index = i; leaf[i].n = 1; } // initialize internal nodes root = &internal[0]; root->label = 0; root->index = 0; root->p = RNG_UNIF01(); // insert remaining internal vertices, O(n log n) for (int i = 1; i < (n - 1); i++) { internal[i].label = i; internal[i].index = i; internal[i].p = RNG_UNIF01(); binarySearchInsert(root, &internal[i]); } // --- Hang leaf nodes off end of dendrogram O(n log n) // To impose this random hierarchical relationship on G, we first // take a random permutation of the leaf vertices and then replace // the NULLs at the bottom of the tree in-order with the leafs. As a // hack to ensure that we can find the leafs later using a binary // search, we assign each of them the p value of their parent, // perturbed slightly so as to preserve the binary search property. block* array; array = new block [n]; for (int i = 0; i < n; i++) { array[i].x = RNG_UNIF01(); array[i].y = i; } QsortMain(array, 0, n - 1); int k = 0; // replace NULLs with leaf nodes, and for (int i = 0; i < (n - 1); i++) { // maintain binary search property, O(n) if (internal[i].L == NULL) { internal[i].L = &leaf[array[k].y]; leaf[array[k].y].M = &internal[i]; leaf[array[k++].y].p = internal[i].p - 0.0000000000001; } if (internal[i].R == NULL) { internal[i].R = &leaf[array[k].y]; leaf[array[k].y].M = &internal[i]; leaf[array[k++].y].p = internal[i].p + 0.0000000000001; } } delete [] array; // --- Compute the path from root -> leaf for each leaf O(n log n) // Using the binary search property, we can find each leaf node in // O(log n) time. The binarySearchFind() function returns the list // of internal node indices that the search crossed, in the order of // root -> ... -> leaf, for use in the subsequent few operations. if (paths != NULL) { list *curr, *prev; for (int i = 0; i < n; i++) { curr = paths[i]; while (curr != NULL) { prev = curr; curr = curr->next; delete prev; prev = NULL; } paths[i] = NULL; } delete [] paths; } paths = NULL; paths = new list* [n]; for (int i = 0; i < n; i++) { paths[i] = binarySearchFind(leaf[i].p); } // --- Count e for each internal node O(m) // To count the number of edges that span the L and R subtrees for // each internal node, we use the path information we just // computed. Then, we loop over all edges in G and find the common // ancestor in D of the two endpoints and increment that internal // node's e count. This process takes O(m) time because in a roughly // balanced binary tree (given by our random dendrogram), the vast // majority of vertices take basically constant time to find their // common ancestor. Note that because our adjacency list is // symmetric, we overcount each e by a factor of 2, so we need to // correct this after. elementd* ancestor; edge* curr; for (int i = 0; i < (n - 1); i++) { internal[i].e = 0; internal[i].label = -1; } for (int i = 0; i < n; i++) { curr = g->getNeighborList(i); while (curr != NULL) { ancestor = findCommonAncestor(paths, i, curr->x); ancestor->e += 1; curr = curr->next; } } for (int i = 0; i < (n - 1); i++) { internal[i].e /= 2; } // --- Count n for each internal node O(n log n) // To tabulate the number of leafs in each subtree rooted at an // internal node, we use the path information computed above. for (int i = 0; i < n; i++) { ancestor = &leaf[i]; ancestor = ancestor->M; while (ancestor != NULL) { ancestor->n++; ancestor = ancestor->M; } } // --- Label all internal vertices O(n log n) // We want to label each internal vertex with the smallest leaf // index of its children. This will allow us to collapse many // leaf-orderings into a single dendrogram structure that is // independent of child-exhanges (since these have no impact on the // likelihood of the hierarchical structure). To do this, we loop // over the leaf vertices from smallest to largest and walk along // that leaf's path from the root. If we find an unlabeled internal // node, then we mark it with this leaf's index. for (int i = 0; i < n; i++) { ancestor = &leaf[i]; while (ancestor != NULL) { if (ancestor->label == -1 || ancestor->label > leaf[i].label) { ancestor->label = leaf[i].label; } ancestor = ancestor->M; } } // --- Exchange children to enforce order-property O(n) // We state that the order-property requires that an internal node's // label is the smallest index of its left subtree. The dendrogram // so far doesn't reflect this, so we need to step through each // internal vertex and make that adjustment (swapping nL and nR if // we make a change). elementd *tempe; for (int i = 0; i < (n - 1); i++) { if (internal[i].L->label > internal[i].label) { tempe = internal[i].L; internal[i].L = internal[i].R; internal[i].R = tempe; } } // --- Tabulate internal dendrogram edges O(n^2) // For the MCMC moves later on, we'll need to be able to choose, // uniformly at random, an internal edge of the dendrogram to // manipulate. There are always n-2 of them, and we can find them // simply by scanning across the internal vertices and observing // which have children that are also internal vertices. Note: very // important that the order property be enforced before this step is // taken; otherwise, the internal edges wont reflect the actual // dendrogram structure. for (int i = 0; i < (n - 1); i++) { if (internal[i].L->type == DENDRO) { d->addEdge(i, internal[i].L->index, LEFT); } if (internal[i].R->type == DENDRO) { d->addEdge(i, internal[i].R->index, RIGHT); } } // --- Clear memory for paths O(n log n) // Now that we're finished using the paths, we need to deallocate // them manually. list *current, *previous; for (int i = 0; i < n; i++) { current = paths[i]; while (current) { previous = current; current = current->next; delete previous; previous = NULL; } paths[i] = NULL; } delete [] paths; paths = NULL; // --- Compute p_i for each internal node O(n) // Each internal node's p_i = e_i / (nL_i*nR_i), and now that we // have each of those pieces, we may calculate this value for each // internal node. Given these, we can then calculate the // log-likelihood of the entire dendrogram structure \log(L) = // \sum_{i=1}^{n} ( ( e_i \log[p_i] ) + ( (nL_i*nR_i - e_i) // \log[1-p_i] ) ) L = 0.0; double dL; int nL_nR, ei; for (int i = 0; i < (n - 1); i++) { nL_nR = internal[i].L->n * internal[i].R->n; ei = internal[i].e; internal[i].p = (double)(ei) / (double)(nL_nR); if (ei == 0 || ei == nL_nR) { dL = 0.0; } else { dL = ei * log(internal[i].p) + (nL_nR - ei) * log(1.0 - internal[i].p); } internal[i].logL = dL; L += dL; } for (int i = 0; i < (n - 1); i++) { if (internal[i].label > internal[i].L->label) { tempe = internal[i].L; internal[i].L = internal[i].R; internal[i].R = tempe; } } // Dendrogram is now built return; } // *********************************************************************** void dendro::clearDendrograph() { // Clear out the memory and references used by the dendrograph // structure - this is intended to be called just before an // importDendrogramStructure call so as to avoid memory leaks and // overwriting the references therein. if (g != NULL) { delete g; // O(m) g = NULL; } if (leaf != NULL) { delete [] leaf; // O(n) leaf = NULL; } if (internal != NULL) { delete [] internal; // O(n) internal = NULL; } if (d != NULL) { delete d; // O(n) d = NULL; } root = NULL; return; } // ********************************************************************** int dendro::computeEdgeCount(const int a, const short int atype, const int b, const short int btype) { // This function computes the number of edges that cross between the // subtree internal[a] and the subtree internal[b]. To do this, we // use an array A[1..n] integers which take values -1 if A[i] is in // the subtree defined by internal[a], +1 if A[i] is in the subtree // internal[b], and 0 otherwise. Taking the smaller of the two sets, // we then scan over the edges attached to that set of vertices and // count the number of endpoints we see in the other set. bool flag_go = true; int nA, nB; int count = 0; const short int k = 1 + DENDRO + GRAPH; elementd* curr; // First, we push the leaf nodes in the L and R subtrees into // balanced binary tree structures so that we can search them // quickly later on. if (atype == GRAPH) { // default case, subtree A is size 1 // insert single node as member of left subtree subtreeL.insertItem(a, -1); nA = 1; // } else { // explore subtree A, O(|A|) curr = &internal[a]; curr->type = k + 1; nA = 0; while (flag_go) { if (curr->index == internal[a].M->index) { internal[a].type = DENDRO; flag_go = false; } else { // - is it time, and is left child a graph node? if (curr->type == k + 1 && curr->L->type == GRAPH) { subtreeL.insertItem(curr->L->index, -1); curr->type = k + 2; nA++; } // - is it time, and is right child a graph node? if (curr->type == k + 2 && curr->R->type == GRAPH) { subtreeL.insertItem(curr->R->index, -1); curr->type = k + 3; nA++; } if (curr->type == k + 1) { // - go left curr->type = k + 2; curr = curr->L; curr->type = k + 1; } else if (curr->type == k + 2) { // - else go right curr->type = k + 3; curr = curr->R; curr->type = k + 1; } else { // - else go up a level curr->type = DENDRO; curr = curr->M; if (curr == NULL) { flag_go = false; } } } } } if (btype == GRAPH) { // default case, subtree A is size 1 // insert node as single member of right subtree subtreeR.insertItem(b, 1); nB = 1; } else { flag_go = true; // explore subtree B, O(|B|) curr = &internal[b]; curr->type = k + 1; nB = 0; while (flag_go) { if (curr->index == internal[b].M->index) { internal[b].type = DENDRO; flag_go = false; } else { // - is it time, and is left child a graph node? if (curr->type == k + 1 && curr->L->type == GRAPH) { subtreeR.insertItem(curr->L->index, 1); curr->type = k + 2; nB++; } // - is it time, and is right child a graph node? if (curr->type == k + 2 && curr->R->type == GRAPH) { subtreeR.insertItem(curr->R->index, 1); curr->type = k + 3; nB++; } if (curr->type == k + 1) { // - look left curr->type = k + 2; curr = curr->L; curr->type = k + 1; } else if (curr->type == k + 2) { // - look right curr->type = k + 3; curr = curr->R; curr->type = k + 1; } else { // - else go up a level curr->type = DENDRO; curr = curr->M; if (curr == NULL) { flag_go = false; } } } } } // Now, we take the smaller subtree and ask how many of its // emerging edges have their partner in the other subtree. O(|A| log // |A|) time edge* current; int* treeList; if (nA < nB) { // subtreeL is smaller treeList = subtreeL.returnArrayOfKeys(); for (int i = 0; i < nA; i++) { current = g->getNeighborList(treeList[i]); // loop over each of its neighbors v_j while (current != NULL) { // to see if v_j is in A if (subtreeR.findItem(current->x) != NULL) { count++; } current = current->next; } subtreeL.deleteItem(treeList[i]); } delete [] treeList; treeList = subtreeR.returnArrayOfKeys(); for (int i = 0; i < nB; i++) { subtreeR.deleteItem(treeList[i]); } delete [] treeList; } else { // subtreeR is smaller treeList = subtreeR.returnArrayOfKeys(); for (int i = 0; i < nB; i++) { current = g->getNeighborList(treeList[i]); // loop over each of its neighbors v_j while (current != NULL) { // to see if v_j is in B if (subtreeL.findItem(current->x) != NULL) { count++; } current = current->next; } subtreeR.deleteItem(treeList[i]); } delete [] treeList; treeList = subtreeL.returnArrayOfKeys(); for (int i = 0; i < nA; i++) { subtreeL.deleteItem(treeList[i]); } delete [] treeList; } return count; } // *********************************************************************** int dendro::countChildren(const string s) { int len = s.size(); int numC = 0; for (int i = 0; i < len; i++) { if (s[i] == 'C') { numC++; } } return numC; } // *********************************************************************** void dendro::cullSplitHist() { string* array; int tot, leng; array = splithist->returnArrayOfKeys(); tot = splithist->returnTotal(); leng = splithist->returnNodecount(); for (int i = 0; i < leng; i++) { if ((splithist->returnValue(array[i]) / tot) < 0.5) { splithist->deleteItem(array[i]); } } delete [] array; array = NULL; return; } // ********************************************************************** elementd* dendro::findCommonAncestor(list** paths, const int i, const int j) { list* headOne = paths[i]; list* headTwo = paths[j]; elementd* lastStep = NULL; while (headOne->x == headTwo->x) { lastStep = &internal[headOne->x]; headOne = headOne->next; headTwo = headTwo->next; if (headOne == NULL || headTwo == NULL) { break; } } return lastStep; // Returns address of an internal node; do not deallocate } // ********************************************************************** int dendro::getConsensusSize() { string *array; double value, tot; int numSplits, numCons; numSplits = splithist->returnNodecount(); array = splithist->returnArrayOfKeys(); tot = splithist->returnTotal(); numCons = 0; for (int i = 0; i < numSplits; i++) { value = splithist->returnValue(array[i]); if (value / tot > 0.5) { numCons++; } } delete [] array; array = NULL; return numCons; } // ********************************************************************** splittree* dendro::getConsensusSplits() { string *array; splittree *consensusTree; double value, tot; consensusTree = new splittree; int numSplits; // We look at all of the splits in our split histogram and add any // one that's in the majority to our consensusTree, which we then // return (note that consensusTree needs to be deallocated by the // user). numSplits = splithist->returnNodecount(); array = splithist->returnArrayOfKeys(); tot = splithist->returnTotal(); for (int i = 0; i < numSplits; i++) { value = splithist->returnValue(array[i]); if (value / tot > 0.5) { consensusTree->insertItem(array[i], value / tot); } } delete [] array; array = NULL; return consensusTree; } // *********************************************************************** double dendro::getLikelihood() { return L; } // *********************************************************************** void dendro::getSplitList(splittree* split_tree) { string sp; for (int i = 0; i < (n - 1); i++) { sp = d->getSplit(i); if (!sp.empty() && sp[1] != '-') { split_tree->insertItem(sp, 0.0); } } return; } // *********************************************************************** double dendro::getSplitTotalWeight() { if (splithist) { return splithist->returnTotal(); } else { return 0; } } // *********************************************************************** bool dendro::importDendrogramStructure(const igraph_hrg_t *hrg) { n = igraph_hrg_size(hrg); // allocate memory for G, O(n) leaf = new elementd[n]; // allocate memory for D, O(n) internal = new elementd[n - 1]; // allocate memory for internal edges of D, O(n) d = new interns(n - 2); // initialize leaf nodes for (int i = 0; i < n; i++) { leaf[i].type = GRAPH; leaf[i].label = i; leaf[i].index = i; leaf[i].n = 1; } // initialize internal nodes root = &internal[0]; root->label = 0; for (int i = 1; i < n - 1; i++) { internal[i].index = i; internal[i].label = -1; } // import basic structure from hrg object, O(n) for (int i = 0; i < n - 1; i++) { int L = VECTOR(hrg->left)[i]; int R = VECTOR(hrg->right)[i]; if (L < 0) { internal[i].L = &internal[-L - 1]; internal[-L - 1].M = &internal[i]; } else { internal[i].L = &leaf[L]; leaf[L].M = &internal[i]; } if (R < 0) { internal[i].R = &internal[-R - 1]; internal[-R - 1].M = &internal[i]; } else { internal[i].R = &leaf[R]; leaf[R].M = &internal[i]; } internal[i].p = VECTOR(hrg->prob)[i]; internal[i].e = VECTOR(hrg->edges)[i]; internal[i].n = VECTOR(hrg->vertices)[i]; internal[i].index = i; } // --- Label all internal vertices O(n log n) elementd *curr; for (int i = 0; i < n; i++) { curr = &leaf[i]; while (curr) { if (curr->label == -1 || curr->label > leaf[i].label) { curr->label = leaf[i].label; } curr = curr -> M; } } // --- Exchange children to enforce order-property O(n) elementd *tempe; for (int i = 0; i < n - 1; i++) { if (internal[i].L->label > internal[i].label) { tempe = internal[i].L; internal[i].L = internal[i].R; internal[i].R = tempe; } } // --- Tabulate internal dendrogram edges O(n) for (int i = 0; i < (n - 1); i++) { if (internal[i].L->type == DENDRO) { d->addEdge(i, internal[i].L->index, LEFT); } if (internal[i].R->type == DENDRO) { d->addEdge(i, internal[i].R->index, RIGHT); } } // --- Compute p_i for each internal node O(n) // Each internal node's p_i = e_i / (nL_i*nR_i), and now that we // have each of those pieces, we may calculate this value for each // internal node. Given these, we can then calculate the // log-likelihood of the entire dendrogram structure // \log(L) = \sum_{i=1}^{n} ( ( e_i \log[p_i] ) + // ( (nL_i*nR_i - e_i) \log[1-p_i] ) ) L = 0.0; double dL; int nL_nR, ei; for (int i = 0; i < (n - 1); i++) { nL_nR = internal[i].L->n * internal[i].R->n; ei = internal[i].e; if (ei == 0 || ei == nL_nR) { dL = 0.0; } else { dL = (double)(ei) * log(internal[i].p) + (double)(nL_nR - ei) * log(1.0 - internal[i].p); } internal[i].logL = dL; L += dL; } return true; } // *********************************************************************** void dendro::makeRandomGraph() { if (g != NULL) { delete g; } g = NULL; g = new graph(n); list *curr, *prev; if (paths) { for (int i = 0; i < n; i++) { curr = paths[i]; while (curr != NULL) { prev = curr; curr = curr->next; delete prev; prev = NULL; } paths[i] = NULL; } delete [] paths; } // build paths from root O(n d) paths = new list* [n]; for (int i = 0; i < n; i++) { paths[i] = reversePathToRoot(i); } elementd* commonAncestor; // O((h+d)*n^2) - h: height of D; d: average degree in G for (int i = 0; i < n; i++) { // decide neighbors of v_i for (int j = (i + 1); j < n; j++) { commonAncestor = findCommonAncestor(paths, i, j); if (RNG_UNIF01() < commonAncestor->p) { if (!(g->doesLinkExist(i, j))) { g->addLink(i, j); } if (!(g->doesLinkExist(j, i))) { g->addLink(j, i); } } } } for (int i = 0; i < n; i++) { curr = paths[i]; while (curr != NULL) { prev = curr; curr = curr->next; delete prev; prev = NULL; } paths[i] = NULL; } delete [] paths; // delete paths data structure O(n log n) paths = NULL; return; } // ********************************************************************** bool dendro::monteCarloMove(double& delta, bool& ftaken, const double T) { // A single MC move begins with the selection of a random internal // edge (a,b) of the dendrogram. This also determines the three // subtrees i, j, k that we will rearrange, and we choose uniformly // from among the options. // // If (a,b) is a left-edge, then we have ((i,j),k), and moves // ((i,j),k) -> ((i,k),j) (alpha move) // -> (i,(j,k)) + enforce order-property for (j,k) (beta move) // // If (a,b) is a right-edge, then we have (i,(j,k)), and moves // (i,(j,k)) -> ((i,k),j) (alpha move) // -> ((i,j),k) (beta move) // // For each of these moves, we need to know what the change in // likelihood will be, so that we can determine with what // probability we execute the move. elementd *temp; ipair *tempPair; int x, y, e_x, e_y, n_i, n_j, n_k, n_x, n_y; short int t; double p_x, p_y, L_x, L_y, dLogL; string new_split; // The remainder of the code executes a single MCMC move, where we // sample the dendrograms proportionally to their likelihoods (i.e., // temperature=1, if you're comparing it to the usual MCMC // framework). delta = 0.0; ftaken = false; tempPair = d->getRandomEdge(); // returns address; no need to deallocate x = tempPair->x; // copy contents of referenced random edge y = tempPair->y; // into local variables t = tempPair->t; if (t == LEFT) { if (RNG_UNIF01() < 0.5) { // ## LEFT ALPHA move: ((i,j),k) -> ((i,k),j) // We need to calculate the change in the likelihood (dLogL) // that would result from this move. Most of the information // needed to do this is already available, the exception being // e_ik, the number of edges that span the i and k subtrees. I // use a slow algorithm O(n) to do this, since I don't know of a // better way at this point. (After several attempts to find a // faster method, no luck.) n_i = internal[y].L->n; n_j = internal[y].R->n; n_k = internal[x].R->n; n_y = n_i * n_k; e_y = computeEdgeCount(internal[y].L->index, internal[y].L->type, internal[x].R->index, internal[x].R->type); p_y = (double)(e_y) / (double)(n_y); if (e_y == 0 || e_y == n_y) { L_y = 0.0; } else { L_y = (double)(e_y) * log(p_y) + (double)(n_y - e_y) * log(1.0 - p_y); } n_x = (n_i + n_k) * n_j; e_x = internal[x].e + internal[y].e - e_y; // e_yj p_x = (double)(e_x) / (double)(n_x); if (e_x == 0 || e_x == n_x) { L_x = 0.0; } else { L_x = (double)(e_x) * log(p_x) + (double)(n_x - e_x) * log(1.0 - p_x); } dLogL = (L_x - internal[x].logL) + (L_y - internal[y].logL); if ((dLogL > 0.0) || (RNG_UNIF01() < exp(T * dLogL))) { // make LEFT ALPHA move ftaken = true; d->swapEdges(x, internal[x].R->index, RIGHT, y, internal[y].R->index, RIGHT); temp = internal[x].R; // - swap j and k internal[x].R = internal[y].R; internal[y].R = temp; internal[x].R->M = &internal[x]; // - adjust parent pointers internal[y].R->M = &internal[y]; internal[y].n = n_i + n_k; // - update n for [y] internal[x].e = e_x; // - update e_i for [x] and [y] internal[y].e = e_y; internal[x].p = p_x; // - update p_i for [x] and [y] internal[y].p = p_y; internal[x].logL = L_x; // - update L_i for [x] and [y] internal[y].logL = L_y; // - order-property maintained L += dLogL; // - update LogL delta = dLogL; } } else { // ## LEFT BETA move: ((i,j),k) -> (i,(j,k)) n_i = internal[y].L->n; n_j = internal[y].R->n; n_k = internal[x].R->n; n_y = n_j * n_k; e_y = computeEdgeCount(internal[y].R->index, internal[y].R->type, internal[x].R->index, internal[x].R->type); p_y = (double)(e_y) / (double)(n_y); if (e_y == 0 || e_y == n_y) { L_y = 0.0; } else { L_y = (double)(e_y) * log(p_y) + (double)(n_y - e_y) * log(1.0 - p_y); } n_x = (n_j + n_k) * n_i; e_x = internal[x].e + internal[y].e - e_y; // e_yj p_x = (double)(e_x) / (double)(n_x); if (e_x == 0 || e_x == n_x) { L_x = 0.0; } else { L_x = (double)(e_x) * log(p_x) + (double)(n_x - e_x) * log(1.0 - p_x); } dLogL = (L_x - internal[x].logL) + (L_y - internal[y].logL); if ((dLogL > 0.0) || (RNG_UNIF01() < exp(T * dLogL))) { // make LEFT BETA move ftaken = true; d->swapEdges(y, internal[y].L->index, LEFT, y, internal[y].R->index, RIGHT); temp = internal[y].L; // - swap L and R of [y] internal[y].L = internal[y].R; internal[y].R = temp; d->swapEdges(x, internal[x].R->index, RIGHT, y, internal[y].R->index, RIGHT); temp = internal[x].R; // - swap i and k internal[x].R = internal[y].R; internal[y].R = temp; internal[x].R->M = &internal[x]; // - adjust parent pointers internal[y].R->M = &internal[y]; d->swapEdges(x, internal[x].L->index, LEFT, x, internal[x].R->index, RIGHT); temp = internal[x].L; // - swap L and R of [x] internal[x].L = internal[x].R; internal[x].R = temp; internal[y].n = n_j + n_k; // - update n internal[x].e = e_x; // - update e_i internal[y].e = e_y; internal[x].p = p_x; // - update p_i internal[y].p = p_y; internal[x].logL = L_x; // - update logL_i internal[y].logL = L_y; if (internal[y].R->label < internal[y].L->label) { // - enforce order-property if necessary d->swapEdges(y, internal[y].L->index, LEFT, y, internal[y].R->index, RIGHT); temp = internal[y].L; internal[y].L = internal[y].R; internal[y].R = temp; } // internal[y].label = internal[y].L->label; L += dLogL; // - update LogL delta = dLogL; } } } else { // right-edge: t == RIGHT if (RNG_UNIF01() < 0.5) { // alpha move: (i,(j,k)) -> ((i,k),j) n_i = internal[x].L->n; n_j = internal[y].L->n; n_k = internal[y].R->n; n_y = n_i * n_k; e_y = computeEdgeCount(internal[x].L->index, internal[x].L->type, internal[y].R->index, internal[y].R->type); p_y = (double)(e_y) / (double)(n_y); if (e_y == 0 || e_y == n_y) { L_y = 0.0; } else { L_y = (double)(e_y) * log(p_y) + (double)(n_y - e_y) * log(1.0 - p_y); } n_x = (n_i + n_k) * n_j; e_x = internal[x].e + internal[y].e - e_y; // e_yj p_x = (double)(e_x) / (double)(n_x); if (e_x == 0 || e_x == n_x) { L_x = 0.0; } else { L_x = (double)(e_x) * log(p_x) + (double)(n_x - e_x) * log(1.0 - p_x); } dLogL = (L_x - internal[x].logL) + (L_y - internal[y].logL); if ((dLogL > 0.0) || (RNG_UNIF01() < exp(T * dLogL))) { // make RIGHT ALPHA move ftaken = true; d->swapEdges(x, internal[x].L->index, LEFT, x, internal[x].R->index, RIGHT); temp = internal[x].L; // - swap L and R of [x] internal[x].L = internal[x].R; internal[x].R = temp; d->swapEdges(y, internal[y].L->index, LEFT, x, internal[x].R->index, RIGHT); temp = internal[y].L; // - swap i and j internal[y].L = internal[x].R; internal[x].R = temp; internal[x].R->M = &internal[x]; // - adjust parent pointers internal[y].L->M = &internal[y]; internal[y].n = n_i + n_k; // - update n internal[x].e = e_x; // - update e_i internal[y].e = e_y; internal[x].p = p_x; // - update p_i internal[y].p = p_y; internal[x].logL = L_x; // - update logL_i internal[y].logL = L_y; internal[y].label = internal[x].label; // - update order property L += dLogL; // - update LogL delta = dLogL; } } else { // beta move: (i,(j,k)) -> ((i,j),k) n_i = internal[x].L->n; n_j = internal[y].L->n; n_k = internal[y].R->n; n_y = n_i * n_j; e_y = computeEdgeCount(internal[x].L->index, internal[x].L->type, internal[y].L->index, internal[y].L->type); p_y = (double)(e_y) / (double)(n_y); if (e_y == 0 || e_y == n_y) { L_y = 0.0; } else { L_y = (double)(e_y) * log(p_y) + (double)(n_y - e_y) * log(1.0 - p_y); } n_x = (n_i + n_j) * n_k; e_x = internal[x].e + internal[y].e - e_y; // e_yk p_x = (double)(e_x) / (double)(n_x); if (e_x == 0 || e_x == n_x) { L_x = 0.0; } else { L_x = (double)(e_x) * log(p_x) + (double)(n_x - e_x) * log(1.0 - p_x); } dLogL = (L_x - internal[x].logL) + (L_y - internal[y].logL); if ((dLogL > 0.0) || (RNG_UNIF01() < exp(T * dLogL))) { // make RIGHT BETA move ftaken = true; d->swapEdges(x, internal[x].L->index, LEFT, x, internal[x].R->index, RIGHT); temp = internal[x].L; // - swap L and R of [x] internal[x].L = internal[x].R; internal[x].R = temp; d->swapEdges(x, internal[x].R->index, RIGHT, y, internal[y].R->index, RIGHT); temp = internal[x].R; // - swap i and k internal[x].R = internal[y].R; internal[y].R = temp; internal[x].R->M = &internal[x]; // - adjust parent pointers internal[y].R->M = &internal[y]; d->swapEdges(y, internal[y].L->index, LEFT, y, internal[y].R->index, RIGHT); temp = internal[y].L; // - swap L and R of [y] internal[y].L = internal[y].R; internal[y].R = temp; internal[y].n = n_i + n_j; // - update n internal[x].e = e_x; // - update e_i internal[y].e = e_y; internal[x].p = p_x; // - update p_i internal[y].p = p_y; internal[x].logL = L_x; // - update logL_i internal[y].logL = L_y; internal[y].label = internal[x].label; // - order-property L += dLogL; // - update LogL delta = dLogL; } } } return true; } // ********************************************************************** void dendro::refreshLikelihood() { // recalculates the log-likelihood of the dendrogram structure L = 0.0; double dL; int nL_nR, ei; for (int i = 0; i < (n - 1); i++) { nL_nR = internal[i].L->n * internal[i].R->n; ei = internal[i].e; internal[i].p = (double)(ei) / (double)(nL_nR); if (ei == 0 || ei == nL_nR) { dL = 0.0; } else { dL = ei * log(internal[i].p) + (nL_nR - ei) * log(1.0 - internal[i].p); } internal[i].logL = dL; L += dL; } return; } // ********************************************************************** void dendro::QsortMain (block* array, int left, int right) { if (right > left) { int pivot = left; int part = QsortPartition(array, left, right, pivot); QsortMain(array, left, part - 1); QsortMain(array, part + 1, right ); } return; } int dendro::QsortPartition (block* array, int left, int right, int index) { block p_value, temp; p_value.x = array[index].x; p_value.y = array[index].y; // swap(array[p_value], array[right]) temp.x = array[right].x; temp.y = array[right].y; array[right].x = array[index].x; array[right].y = array[index].y; array[index].x = temp.x; array[index].y = temp.y; int stored = left; for (int i = left; i < right; i++) { if (array[i].x <= p_value.x) { // swap(array[stored], array[i]) temp.x = array[i].x; temp.y = array[i].y; array[i].x = array[stored].x; array[i].y = array[stored].y; array[stored].x = temp.x; array[stored].y = temp.y; stored++; } } // swap(array[right], array[stored]) temp.x = array[stored].x; temp.y = array[stored].y; array[stored].x = array[right].x; array[stored].y = array[right].y; array[right].x = temp.x; array[right].y = temp.y; return stored; } void dendro::recordConsensusTree(igraph_vector_t *parents, igraph_vector_t *weights) { keyValuePairSplit *curr, *prev; child *newChild; int orig_nodes = g->numNodes(); // First, cull the split hist so that only splits with weight >= 0.5 // remain cullSplitHist(); int treesize = splithist->returnNodecount(); // Now, initialize the various arrays we use to keep track of the // internal structure of the consensus tree. ctree = new cnode[treesize]; cancestor = new int[n]; for (int i = 0; i < treesize; i++) { ctree[i].index = i; } for (int i = 0; i < n; i++) { cancestor[i] = -1; } int ii = 0; // To build the majority consensus tree, we do the following: For // each possible number of Ms in the split string (a number that // ranges from n-2 down to 0), and for each split with that number // of Ms, we create a new internal node of the tree, and connect the // oldest ancestor of each C to that node (at most once). Then, we // update our list of oldest ancestors to reflect this new join, and // proceed. for (int i = n - 2; i >= 0; i--) { // First, we get a list of all the splits with this exactly i Ms curr = splithist->returnTheseSplits(i); // Now we loop over that list while (curr != NULL) { splithist->deleteItem(curr->x); // add weight to this internal node ctree[ii].weight = curr->y; // examine each letter of this split for (int j = 0; j < n; j++) { if (curr->x[j] == 'C') { // - node is child of this internal node if (cancestor[j] == -1) { // - first time this leaf has ever been seen newChild = new child; newChild->type = GRAPH; newChild->index = j; newChild->next = NULL; // - attach child to list if (ctree[ii].lastChild == NULL) { ctree[ii].children = newChild; ctree[ii].lastChild = newChild; ctree[ii].degree = 1; } else { ctree[ii].lastChild->next = newChild; ctree[ii].lastChild = newChild; ctree[ii].degree += 1; } } else { // - this leaf has been seen before // If the parent of the ancestor of this leaf is the // current internal node then this leaf is already a // descendant of this internal node, and we can move on; // otherwise, we need to add that ancestor to this // internal node's child list, and update various // relations if (ctree[cancestor[j]].parent != ii) { ctree[cancestor[j]].parent = ii; newChild = new child; newChild->type = DENDRO; newChild->index = cancestor[j]; newChild->next = NULL; // - attach child to list if (ctree[ii].lastChild == NULL) { ctree[ii].children = newChild; ctree[ii].lastChild = newChild; ctree[ii].degree = 1; } else { ctree[ii].lastChild->next = newChild; ctree[ii].lastChild = newChild; ctree[ii].degree += 1; } } } // note new ancestry for this leaf cancestor[j] = ii; } } // update internal node index ii++; prev = curr; curr = curr->next; delete prev; } } // Return the consensus tree igraph_vector_resize(parents, ii + orig_nodes); if (weights) { igraph_vector_resize(weights, ii); } for (int i = 0; i < ii; i++) { child *sat, *sit = ctree[i].children; while (sit) { VECTOR(*parents)[orig_nodes + i] = ctree[i].parent < 0 ? -1 : orig_nodes + ctree[i].parent; if (sit->type == GRAPH) { VECTOR(*parents)[sit->index] = orig_nodes + i; } sat = sit; sit = sit->next; delete sat; } if (weights) { VECTOR(*weights)[i] = ctree[i].weight; } ctree[i].children = 0; } // Plus the isolate nodes for (int i = 0; i < n; i++) { if (cancestor[i] == -1) { VECTOR(*parents)[i] = -1; } } } // ********************************************************************** void dendro::recordDendrogramStructure(igraph_hrg_t *hrg) { for (int i = 0; i < n - 1; i++) { int li = internal[i].L->index; int ri = internal[i].R->index; VECTOR(hrg->left )[i] = internal[i].L->type == DENDRO ? -li - 1 : li; VECTOR(hrg->right)[i] = internal[i].R->type == DENDRO ? -ri - 1 : ri; VECTOR(hrg->prob )[i] = internal[i].p; VECTOR(hrg->edges)[i] = internal[i].e; VECTOR(hrg->vertices)[i] = internal[i].n; } } void dendro::recordGraphStructure(igraph_t *graph) { igraph_vector_t edges; int no_of_nodes = g->numNodes(); int no_of_edges = g->numLinks() / 2; int idx = 0; igraph_vector_init(&edges, no_of_edges * 2); IGRAPH_FINALLY(igraph_vector_destroy, &edges); for (int i = 0; i < n; i++) { edge *curr = g->getNeighborList(i); while (curr) { if (i < curr->x) { VECTOR(edges)[idx++] = i; VECTOR(edges)[idx++] = curr->x; } curr = curr->next; } } igraph_create(graph, &edges, no_of_nodes, /* directed= */ 0); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); } // ********************************************************************** list* dendro::reversePathToRoot(const int leafIndex) { list *head, *subhead, *newlist; head = subhead = newlist = NULL; elementd *current = &leaf[leafIndex]; // continue until we're finished while (current != NULL) { // add this node to the path newlist = new list; newlist->x = current->index; newlist->next = NULL; if (head == NULL) { head = newlist; } else { subhead = head; head = newlist; head->next = subhead; } current = current->M; } return head; } // *********************************************************************** bool dendro::sampleSplitLikelihoods(int &sample_num) { // In order to compute the majority agreement dendrogram at // equilibrium, we need to calculate the leaf partition defined by // each split (internal edge) of the tree. Because splits are only // defined on a Cayley tree, the buildSplit() function returns the // default "--...--" string for the root and the root's left // child. When tabulating the frequency of splits, one of these // needs to be excluded. IGRAPH_UNUSED(sample_num); string* array; int k; double tot; string new_split; // To decompose the tree into its splits, we simply loop over all // the internal nodes and replace the old split for the ith internal // node with its new split. This is a bit time consuming to do // O(n^2), so try not to do this very often. Once the decomposition // is had, we insert them into the split histogram, which tracks the // cumulative weight for each respective split observed. if (splithist == NULL) { splithist = new splittree; } for (int i = 0; i < (n - 1); i++) { new_split = buildSplit(&internal[i]); d->replaceSplit(i, new_split); if (!new_split.empty() && new_split[1] != '-') { if (!splithist->insertItem(new_split, 1.0)) { return false; } } } splithist->finishedThisRound(); // For large graphs, the split histogram can get extremely large, so // we need to employ some measures to prevent it from swamping the // available memory. When the number of splits exceeds a threshold // (say, a million), we progressively delete splits that have a // weight less than a rising (k*0.001 of the total weight) fraction // of the splits, on the assumption that losing such weight is // unlikely to effect the ultimate split statistics. This deletion // procedure is slow O(m lg m), but should only happen very rarely. int split_max = n * 500; int leng; if (splithist->returnNodecount() > split_max) { k = 1; while (splithist->returnNodecount() > split_max) { array = splithist->returnArrayOfKeys(); tot = splithist->returnTotal(); leng = splithist->returnNodecount(); for (int i = 0; i < leng; i++) { if ((splithist->returnValue(array[i]) / tot) < k * 0.001) { splithist->deleteItem(array[i]); } } delete [] array; array = NULL; k++; } } return true; } void dendro::sampleAdjacencyLikelihoods() { // Here, we sample the probability values associated with every // adjacency in A, weighted by their likelihood. The weighted // histogram is stored in the graph data structure, so we simply // need to add an observation to each node-pair that corresponds to // the associated branch point's probability and the dendrogram's // overall likelihood. double nn; double norm = ((double)(n) * (double)(n)) / 4.0; if (L > 0.0) { L = 0.0; } elementd* ancestor; list *currL, *prevL; if (paths != NULL) { for (int i = 0; i < n; i++) { currL = paths[i]; while (currL != NULL) { prevL = currL; currL = currL->next; delete prevL; prevL = NULL; } paths[i] = NULL; } delete [] paths; } paths = NULL; paths = new list* [n]; for (int i = 0; i < n; i++) { // construct paths from root, O(n^2) at worst paths[i] = reversePathToRoot(i); } // add obs for every node-pair, always O(n^2) for (int i = 0; i < n; i++) { for (int j = i + 1; j < n; j++) { // find internal node, O(n) at worst ancestor = findCommonAncestor(paths, i, j); nn = ((double)(ancestor->L->n) * (double)(ancestor->R->n)) / norm; // add obs of ->p to (i,j) histogram, and g->addAdjacencyObs(i, j, ancestor->p, nn); // add obs of ->p to (j,i) histogram g->addAdjacencyObs(j, i, ancestor->p, nn); } } // finish-up: upate total weight in histograms g->addAdjacencyEnd(); return; } void dendro::resetDendrograph() { // Reset the dendrograph structure for the next trial if (leaf != NULL) { delete [] leaf; // O(n) leaf = NULL; } if (internal != NULL) { delete [] internal; // O(n) internal = NULL; } if (d != NULL) { delete d; // O(n) d = NULL; } root = NULL; if (paths != NULL) { list *curr, *prev; for (int i = 0; i < n; i++) { curr = paths[i]; while (curr != NULL) { prev = curr; curr = curr->next; delete prev; prev = NULL; } paths[i] = NULL; } delete [] paths; } paths = NULL; L = 1.0; return; } // ********************************************************************** // *** COPYRIGHT NOTICE ************************************************* // graph.h - graph data structure for hierarchical random graphs // Copyright (C) 2005-2008 Aaron Clauset // // This program is free software; you can redistribute it and/or modify // it under the terms of the GNU General Public License as published by // the Free Software Foundation; either version 2 of the License, or // (at your option) any later version. // // This program is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU General Public License for more details. // // You should have received a copy of the GNU General Public License // along with this program; if not, write to the Free Software // Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA // // See http://www.gnu.org/licenses/gpl.txt for more details. // // ********************************************************************** // Author : Aaron Clauset ( aaronc@santafe.edu | // http://www.santafe.edu/~aaronc/ ) // Collaborators: Cristopher Moore and Mark E.J. Newman // Project : Hierarchical Random Graphs // Location : University of New Mexico, Dept. of Computer Science // AND Santa Fe Institute // Created : 8 November 2005 // Modified : 23 December 2007 (cleaned up for public consumption) // // *********************************************************************** // // Graph data structure for hierarchical random graphs. The basic // structure is an adjacency list of edges; however, many additional // pieces of metadata are stored as well. Each node stores its // external name, its degree and (if assigned) its group index. // // *********************************************************************** // ******** Constructor / Destructor ************************************* graph::graph(const int size, bool predict) : predict(predict) { n = size; m = 0; nodes = new vert [n]; nodeLink = new edge* [n]; nodeLinkTail = new edge* [n]; for (int i = 0; i < n; i++) { nodeLink[i] = NULL; nodeLinkTail[i] = NULL; } if (predict) { A = new double** [n]; for (int i = 0; i < n; i++) { A[i] = new double* [n]; } obs_count = 0; total_weight = 0.0; bin_resolution = 0.0; num_bins = 0; } } graph::~graph() { edge *curr, *prev; for (int i = 0; i < n; i++) { curr = nodeLink[i]; while (curr != NULL) { prev = curr; curr = curr->next; delete prev; } } delete [] nodeLink; nodeLink = NULL; delete [] nodeLinkTail; nodeLinkTail = NULL; delete [] nodes; nodes = NULL; if (predict) { for (int i = 0; i < n; i++) { for (int j = 0; j < n; j++) { delete [] A[i][j]; } delete [] A[i]; } delete [] A; A = NULL; } } // ********************************************************************** bool graph::addLink(const int i, const int j) { // Adds the directed edge (i,j) to the adjacency list for v_i edge* newedge; if (i >= 0 && i < n && j >= 0 && j < n) { newedge = new edge; newedge->x = j; if (nodeLink[i] == NULL) { // first neighbor nodeLink[i] = newedge; nodeLinkTail[i] = newedge; nodes[i].degree = 1; } else { // subsequent neighbor nodeLinkTail[i]->next = newedge; nodeLinkTail[i] = newedge; nodes[i].degree++; } // increment edge count m++; return true; } else { return false; } } // *********************************************************************** bool graph::addAdjacencyObs(const int i, const int j, const double probability, const double size) { // Adds the observation obs to the histogram of the edge (i,j) // Note: user must manually add observation to edge (j,i) by calling // this function with that argument if (bin_resolution > 0.0 && probability >= 0.0 && probability <= 1.0 && size >= 0.0 && size <= 1.0 && i >= 0 && i < n && j >= 0 && j < n) { int index = (int)(probability / bin_resolution + 0.5); if (index < 0) { index = 0; } else if (index > num_bins) { index = num_bins; } // Add the weight to the proper probability bin if (A[i][j][index] < 0.5) { A[i][j][index] = 1.0; } else { A[i][j][index] += 1.0; } return true; } return false; } // ********************************************************************** void graph::addAdjacencyEnd() { // We need to also keep a running total of how much weight has been added // to the histogram, and the number of observations in the histogram. if (obs_count == 0) { total_weight = 1.0; obs_count = 1; } else { total_weight += 1.0; obs_count++; } return; } bool graph::doesLinkExist(const int i, const int j) { // This function determines if the edge (i,j) already exists in the // adjacency list of v_i edge* curr; if (i >= 0 && i < n && j >= 0 && j < n) { curr = nodeLink[i]; while (curr != NULL) { if (curr->x == j) { return true; } curr = curr->next; } } return false; } // ********************************************************************** int graph::getDegree(const int i) { if (i >= 0 && i < n) { return nodes[i].degree; } else { return -1; } } string graph::getName(const int i) { if (i >= 0 && i < n) { return nodes[i].name; } else { return ""; } } // NOTE: Returns address; deallocation of returned object is dangerous edge* graph::getNeighborList(const int i) { if (i >= 0 && i < n) { return nodeLink[i]; } else { return NULL; } } double* graph::getAdjacencyHist(const int i, const int j) { if (i >= 0 && i < n && j >= 0 && j < n) { return A[i][j]; } else { return NULL; } } // ********************************************************************** double graph::getAdjacencyAverage(const int i, const int j) { double average = 0.0; if (i != j) { for (int k = 0; k < num_bins; k++) { if (A[i][j][k] > 0.0) { average += (A[i][j][k] / total_weight) * ((double)(k) * bin_resolution); } } } return average; } int graph::numLinks() { return m; } int graph::numNodes() { return n; } double graph::getBinResolution() { return bin_resolution; } int graph::getNumBins() { return num_bins; } double graph::getTotalWeight() { return total_weight; } // *********************************************************************** void graph::resetAllAdjacencies() { for (int i = 0; i < n; i++) { for (int j = 0; j < n; j++) { for (int k = 0; k < num_bins; k++) { A[i][j][k] = 0.0; } } } obs_count = 0; total_weight = 0.0; return; } // ********************************************************************** void graph::resetAdjacencyHistogram(const int i, const int j) { if (i >= 0 && i < n && j >= 0 && j < n) { for (int k = 0; k < num_bins; k++) { A[i][j][k] = 0.0; } } return; } // ********************************************************************** void graph::resetLinks() { edge *curr, *prev; for (int i = 0; i < n; i++) { curr = nodeLink[i]; while (curr != NULL) { prev = curr; curr = curr->next; delete prev; } nodeLink[i] = NULL; nodeLinkTail[i] = NULL; nodes[i].degree = 0; } m = 0; return; } // ********************************************************************** void graph::setAdjacencyHistograms(const int bin_count) { // For all possible adjacencies, setup an edge histograms num_bins = bin_count + 1; bin_resolution = 1.0 / (double)(bin_count); for (int i = 0; i < n; i++) { for (int j = 0; j < n; j++) { A[i][j] = new double [num_bins]; for (int k = 0; k < num_bins; k++) { A[i][j][k] = 0.0; } } } return; } bool graph::setName(const int i, const string text) { if (i >= 0 && i < n) { nodes[i].name = text; return true; } else { return false; } } // ********************************************************************** interns::interns(const int n) { q = n; count = 0; edgelist = new ipair [q]; splitlist = new string [q + 1]; indexLUT = new int* [q + 1]; for (int i = 0; i < (q + 1); i++) { indexLUT[i] = new int [2]; indexLUT[i][0] = indexLUT[i][1] = -1; } } interns::~interns() { delete [] edgelist; delete [] splitlist; for (int i = 0; i < (q + 1); i++) { delete [] indexLUT[i]; } delete [] indexLUT; } // *********************************************************************** // NOTE: Returns an address to another object -- do not deallocate ipair* interns::getEdge(const int i) { return &edgelist[i]; } // *********************************************************************** // NOTE: Returns an address to another object -- do not deallocate ipair* interns::getRandomEdge() { return &edgelist[(int)(floor((double)(q) * RNG_UNIF01()))]; } // *********************************************************************** string interns::getSplit(const int i) { if (i >= 0 && i <= q) { return splitlist[i]; } else { return ""; } } // ********************************************************************** bool interns::addEdge(const int new_x, const int new_y, const short int new_type) { // This function adds a new edge (i,j,t,sp) to the list of internal // edges. After checking that the inputs fall in the appropriate // range of values, it records the new edgelist index in the // indexLUT and then puts the input values into that edgelist // location. if (count < q && new_x >= 0 && new_x < (q + 1) && new_y >= 0 && new_y < (q + 2) && (new_type == LEFT || new_type == RIGHT)) { if (new_type == LEFT) { indexLUT[new_x][0] = count; } else { indexLUT[new_x][1] = count; } edgelist[count].x = new_x; edgelist[count].y = new_y; edgelist[count].t = new_type; count++; return true; } else { return false; } } // ********************************************************************** bool interns::replaceSplit(const int i, const string sp) { // When an internal edge is changed, its split must be replaced as // well. This function provides that access; it stores the split // defined by an internal edge (x,y) at the location [y], which // is unique. if (i >= 0 && i <= q) { splitlist[i] = sp; return true; } return false; } // *********************************************************************** bool interns::swapEdges(const int one_x, const int one_y, const short int one_type, const int two_x, const int two_y, const short int two_type) { // The moves on the dendrogram always swap edges, either of which // (or both, or neither) can by internal edges. So, this function // mirrors that operation for the internal edgelist and indexLUT. int index, jndex, temp; bool one_isInternal = false; bool two_isInternal = false; if (one_x >= 0 && one_x < (q + 1) && two_x >= 0 && two_x < (q + 1) && (two_type == LEFT || two_type == RIGHT) && one_y >= 0 && one_y < (q + 2) && two_y >= 0 && two_y < (q + 2) && (one_type == LEFT || one_type == RIGHT)) { if (one_type == LEFT) { temp = 0; } else { temp = 1; } if (indexLUT[one_x][temp] > -1) { one_isInternal = true; } if (two_type == LEFT) { temp = 0; } else { temp = 1; } if (indexLUT[two_x][temp] > -1) { two_isInternal = true; } if (one_isInternal && two_isInternal) { if (one_type == LEFT) { index = indexLUT[one_x][0]; } else { index = indexLUT[one_x][1]; } if (two_type == LEFT) { jndex = indexLUT[two_x][0]; } else { jndex = indexLUT[two_x][1]; } temp = edgelist[index].y; edgelist[index].y = edgelist[jndex].y; edgelist[jndex].y = temp; } else if (one_isInternal) { if (one_type == LEFT) { index = indexLUT[one_x][0]; indexLUT[one_x][0] = -1; } else { index = indexLUT[one_x][1]; indexLUT[one_x][1] = -1; } edgelist[index].x = two_x; edgelist[index].t = two_type; if (two_type == LEFT) { indexLUT[two_x][0] = index; } else { indexLUT[two_x][1] = index; } // add new } else if (two_isInternal) { if (two_type == LEFT) { index = indexLUT[two_x][0]; indexLUT[two_x][0] = -1; } else { index = indexLUT[two_x][1]; indexLUT[two_x][1] = -1; } edgelist[index].x = one_x; edgelist[index].t = one_type; if (one_type == LEFT) { indexLUT[one_x][0] = index; } else { indexLUT[one_x][1] = index; } // add new } else { ; } // else neither is internal return true; } else { return false; } } // ******** Red-Black Tree Methods *************************************** splittree::splittree() { root = new elementsp; leaf = new elementsp; leaf->parent = root; root->left = leaf; root->right = leaf; support = 0; total_weight = 0.0; total_count = 0; } splittree::~splittree() { if (root != NULL && (root->left != leaf || root->right != leaf)) { deleteSubTree(root); root = NULL; } support = 0; total_weight = 0.0; total_count = 0; if (root) { delete root; } delete leaf; root = NULL; leaf = NULL; } void splittree::deleteTree() { if (root != NULL) { deleteSubTree(root); root = NULL; } return; } void splittree::deleteSubTree(elementsp *z) { if (z->left != leaf) { deleteSubTree(z->left); z->left = NULL; } if (z->right != leaf) { deleteSubTree(z->right); z->right = NULL; } delete z; /* No point in setting z to NULL here because z is passed by value */ /* z = NULL; */ return; } // ******** Reset Functions ********************************************* // O(n lg n) void splittree::clearTree() { string *array = returnArrayOfKeys(); for (int i = 0; i < support; i++) { deleteItem(array[i]); } delete [] array; return; } // ******** Search Functions ********************************************* // public search function - if there exists a elementsp in the tree // with key=searchKey, it returns TRUE and foundNode is set to point // to the found node; otherwise, it sets foundNode=NULL and returns // FALSE elementsp* splittree::findItem(const string searchKey) { elementsp *current = root; if (current->split.empty()) { return NULL; // empty tree; bail out } while (current != leaf) { if (searchKey.compare(current->split) < 0) { // left-or-right? // try moving down-left if (current->left != leaf) { current = current->left; } else { // failure; bail out return NULL; } } else { if (searchKey.compare(current->split) > 0) { // left-or-right? if (current->right != leaf) { // try moving down-left current = current->right; } else { // failure; bail out return NULL; } } else { // found (searchKey==current->split) return current; } } } return NULL; } double splittree::returnValue(const string searchKey) { elementsp* test = findItem(searchKey); if (test == NULL) { return 0.0; } else { return test->weight; } } // ******** Return Item Functions *************************************** // public function which returns the tree, via pre-order traversal, as // a linked list string* splittree::returnArrayOfKeys() { string* array; array = new string [support]; bool flag_go = true; int index = 0; elementsp *curr; if (support == 1) { array[0] = root->split; } else if (support == 2) { array[0] = root->split; if (root->left == leaf) { array[1] = root->right->split; } else { array[1] = root->left->split; } } else { for (int i = 0; i < support; i++) { array[i] = -1; } // non-recursive traversal of tree structure curr = root; curr->mark = 1; while (flag_go) { // - is it time, and is left child the leaf node? if (curr->mark == 1 && curr->left == leaf) { curr->mark = 2; } // - is it time, and is right child the leaf node? if (curr->mark == 2 && curr->right == leaf) { curr->mark = 3; } if (curr->mark == 1) { // - go left curr->mark = 2; curr = curr->left; curr->mark = 1; } else if (curr->mark == 2) { // - else go right curr->mark = 3; curr = curr->right; curr->mark = 1; } else { // - else go up a level curr->mark = 0; array[index++] = curr->split; curr = curr->parent; if (curr == NULL) { flag_go = false; } } } } return array; } slist* splittree::returnListOfKeys() { keyValuePairSplit *curr, *prev; slist *head = NULL, *tail = NULL, *newlist; curr = returnTreeAsList(); while (curr != NULL) { newlist = new slist; newlist->x = curr->x; if (head == NULL) { head = newlist; tail = head; } else { tail->next = newlist; tail = newlist; } prev = curr; curr = curr->next; delete prev; prev = NULL; } return head; } // pre-order traversal keyValuePairSplit* splittree::returnTreeAsList() { keyValuePairSplit *head, *tail; head = new keyValuePairSplit; head->x = root->split; head->y = root->weight; head->c = root->count; tail = head; if (root->left != leaf) { tail = returnSubtreeAsList(root->left, tail); } if (root->right != leaf) { tail = returnSubtreeAsList(root->right, tail); } if (head->x.empty()) { return NULL; /* empty tree */ } else { return head; } } keyValuePairSplit* splittree::returnSubtreeAsList(elementsp *z, keyValuePairSplit *head) { keyValuePairSplit *newnode, *tail; newnode = new keyValuePairSplit; newnode->x = z->split; newnode->y = z->weight; newnode->c = z->count; head->next = newnode; tail = newnode; if (z->left != leaf) { tail = returnSubtreeAsList(z->left, tail); } if (z->right != leaf) { tail = returnSubtreeAsList(z->right, tail); } return tail; } keyValuePairSplit splittree::returnMaxKey() { keyValuePairSplit themax; elementsp *current; current = root; // search to bottom-right corner of tree while (current->right != leaf) { current = current->right; } themax.x = current->split; themax.y = current->weight; return themax; } keyValuePairSplit splittree::returnMinKey() { keyValuePairSplit themin; elementsp *current; current = root; // search to bottom-left corner of tree while (current->left != leaf) { current = current->left; } themin.x = current->split; themin.y = current->weight; return themin; } // private functions for deleteItem() (although these could easily be // made public, I suppose) elementsp* splittree::returnMinKey(elementsp *z) { elementsp *current; current = z; // search to bottom-right corner of tree while (current->left != leaf) { current = current->left; } // return pointer to the minimum return current; } elementsp* splittree::returnSuccessor(elementsp *z) { elementsp *current, *w; w = z; // if right-subtree exists, return min of it if (w->right != leaf) { return returnMinKey(w->right); } // else search up in tree // move up in tree until find a non-right-child current = w->parent; while ((current != NULL) && (w == current->right)) { w = current; current = current->parent; } return current; } int splittree::returnNodecount() { return support; } keyValuePairSplit* splittree::returnTheseSplits(const int target) { keyValuePairSplit *head, *curr, *prev, *newhead, *newtail, *newpair; int count, len; head = returnTreeAsList(); prev = newhead = newtail = newpair = NULL; curr = head; while (curr != NULL) { count = 0; len = curr->x.size(); for (int i = 0; i < len; i++) { if (curr->x[i] == 'M') { count++; } } if (count == target && curr->x[1] != '*') { newpair = new keyValuePairSplit; newpair->x = curr->x; newpair->y = curr->y; newpair->next = NULL; if (newhead == NULL) { newhead = newpair; newtail = newpair; } else { newtail->next = newpair; newtail = newpair; } } prev = curr; curr = curr->next; delete prev; prev = NULL; } return newhead; } double splittree::returnTotal() { return total_weight; } // ******** Insert Functions ********************************************* void splittree::finishedThisRound() { // We need to also keep a running total of how much weight has been // added to the histogram. if (total_count == 0) { total_weight = 1.0; total_count = 1; } else { total_weight += 1.0; total_count++; } return; } // public insert function bool splittree::insertItem(string newKey, double newValue) { // first we check to see if newKey is already present in the tree; // if so, we do nothing; if not, we must find where to insert the // key elementsp *newNode, *current; // find newKey in tree; return pointer to it O(log k) current = findItem(newKey); if (current != NULL) { current->weight += 1.0; // And finally, we keep track of how many observations went into // the histogram current->count++; return true; } else { newNode = new elementsp; // elementsp for the splittree newNode->split = newKey; // store newKey newNode->weight = newValue; // store newValue newNode->color = true; // new nodes are always RED newNode->parent = NULL; // new node initially has no parent newNode->left = leaf; // left leaf newNode->right = leaf; // right leaf newNode->count = 1; support++; // increment node count in splittree // must now search for where to insert newNode, i.e., find the // correct parent and set the parent and child to point to each // other properly current = root; if (current->split.empty()) { // insert as root delete root; // delete old root root = newNode; // set root to newNode leaf->parent = newNode; // set leaf's parent current = leaf; // skip next loop } // search for insertion point while (current != leaf) { // left-or-right? if (newKey.compare(current->split) < 0) { // try moving down-left if (current->left != leaf) { current = current->left; } else { // else found new parent newNode->parent = current; // set parent current->left = newNode; // set child current = leaf; // exit search } } else { // if (current->right != leaf) { // try moving down-right current = current->right; } else { // else found new parent newNode->parent = current; // set parent current->right = newNode; // set child current = leaf; // exit search } } } // now do the house-keeping necessary to preserve the red-black // properties insertCleanup(newNode); } return true; } // private house-keeping function for insertion void splittree::insertCleanup(elementsp *z) { // fix now if z is root if (z->parent == NULL) { z->color = false; return; } elementsp *temp; // while z is not root and z's parent is RED while (z->parent != NULL && z->parent->color) { if (z->parent == z->parent->parent->left) { // z's parent is LEFT-CHILD temp = z->parent->parent->right; // grab z's uncle if (temp->color) { z->parent->color = false; // color z's parent BLACK (Case 1) temp->color = false; // color z's uncle BLACK (Case 1) z->parent->parent->color = true; // color z's grandpa RED (Case 1) z = z->parent->parent; // set z = z's grandpa (Case 1) } else { if (z == z->parent->right) { // z is RIGHT-CHILD z = z->parent; // set z = z's parent (Case 2) rotateLeft(z); // perform left-rotation (Case 2) } z->parent->color = false; // color z's parent BLACK (Case 3) z->parent->parent->color = true; // color z's grandpa RED (Case 3) rotateRight(z->parent->parent); // perform right-rotation (Case 3) } } else { // z's parent is RIGHT-CHILD temp = z->parent->parent->left; // grab z's uncle if (temp->color) { z->parent->color = false; // color z's parent BLACK (Case 1) temp->color = false; // color z's uncle BLACK (Case 1) z->parent->parent->color = true; // color z's grandpa RED (Case 1) z = z->parent->parent; // set z = z's grandpa (Case 1) } else { if (z == z->parent->left) { // z is LEFT-CHILD z = z->parent; // set z = z's parent (Case 2) rotateRight(z); // perform right-rotation (Case 2) } z->parent->color = false; // color z's parent BLACK (Case 3) z->parent->parent->color = true; // color z's grandpa RED (Case 3) rotateLeft(z->parent->parent); // perform left-rotation (Case 3) } } } root->color = false; // color the root BLACK return; } // ******** Delete Functions ******************************************** // public delete function void splittree::deleteItem(string killKey) { elementsp *x, *y, *z; z = findItem(killKey); if (z == NULL) { return; // item not present; bail out } if (support == 1) { // -- attempt to delete the root root->split = ""; // restore root node to default state root->weight = 0.0; // root->color = false; // root->parent = NULL; // root->left = leaf; // root->right = leaf; // support--; // set support to zero total_weight = 0.0; // set total weight to zero total_count--; // return; // exit - no more work to do } if (z != NULL) { support--; // decrement node count if ((z->left == leaf) || (z->right == leaf)) { // case of less than two children y = z; // set y to be z } else { y = returnSuccessor(z); // set y to be z's key-successor } if (y->left != leaf) { x = y->left; // pick y's one child (left-child) } else { x = y->right; // (right-child) } x->parent = y->parent; // make y's child's parent be y's parent if (y->parent == NULL) { root = x; // if y is the root, x is now root } else { if (y == y->parent->left) {// decide y's relationship with y's parent y->parent->left = x; // replace x as y's parent's left child } else { y->parent->right = x; } // replace x as y's parent's left child } if (y != z) { // insert y into z's spot z->split = y->split; // copy y data into z z->weight = y->weight; // z->count = y->count; // } // // do house-keeping to maintain balance if (y->color == false) { deleteCleanup(x); } delete y; // deallocate y y = NULL; // point y to NULL for safety } // return; } void splittree::deleteCleanup(elementsp *x) { elementsp *w, *t; // until x is the root, or x is RED while ((x != root) && (x->color == false)) { if (x == x->parent->left) { // branch on x being a LEFT-CHILD w = x->parent->right; // grab x's sibling if (w->color == true) { // if x's sibling is RED w->color = false; // color w BLACK (case 1) x->parent->color = true; // color x's parent RED (case 1) rotateLeft(x->parent); // left rotation on x's parent (case 1) w = x->parent->right; // make w be x's right sibling (case 1) } if ((w->left->color == false) && (w->right->color == false)) { w->color = true; // color w RED (case 2) x = x->parent; // examine x's parent (case 2) } else { // if (w->right->color == false) { w->left->color = false; // color w's left child BLACK (case 3) w->color = true; // color w RED (case 3) t = x->parent; // store x's parent rotateRight(w); // right rotation on w (case 3) x->parent = t; // restore x's parent w = x->parent->right; // make w be x's right sibling (case 3) } // w->color = x->parent->color; // w's color := x's parent's (case 4) x->parent->color = false; // color x's parent BLACK (case 4) w->right->color = false; // color w's right child BLACK (case 4) rotateLeft(x->parent); // left rotation on x's parent (case 4) x = root; // finished work. bail out (case 4) } // } else { // x is RIGHT-CHILD w = x->parent->left; // grab x's sibling if (w->color == true) { // if x's sibling is RED w->color = false; // color w BLACK (case 1) x->parent->color = true; // color x's parent RED (case 1) rotateRight(x->parent); // right rotation on x's parent (case 1) w = x->parent->left; // make w be x's left sibling (case 1) } if ((w->right->color == false) && (w->left->color == false)) { w->color = true; // color w RED (case 2) x = x->parent; // examine x's parent (case 2) } else { // if (w->left->color == false) { // w->right->color = false; // color w's right child BLACK (case 3) w->color = true; // color w RED (case 3) t = x->parent; // store x's parent rotateLeft(w); // left rotation on w (case 3) x->parent = t; // restore x's parent w = x->parent->left; // make w be x's left sibling (case 3) } // w->color = x->parent->color; // w's color := x's parent's (case 4) x->parent->color = false; // color x's parent BLACK (case 4) w->left->color = false; // color w's left child BLACK (case 4) rotateRight(x->parent); // right rotation on x's parent (case 4) x = root; // x is now the root (case 4) } } } x->color = false; // color x (the root) BLACK (exit) return; } // ******** Rotation Functions ******************************************* void splittree::rotateLeft(elementsp *x) { elementsp *y; // do pointer-swapping operations for left-rotation y = x->right; // grab right child x->right = y->left; // make x's RIGHT-CHILD be y's LEFT-CHILD y->left->parent = x; // make x be y's LEFT-CHILD's parent y->parent = x->parent; // make y's new parent be x's old parent if (x->parent == NULL) { root = y; // if x was root, make y root } else { // if (x == x->parent->left) { // if x is LEFT-CHILD, make y be x's parent's x->parent->left = y; // left-child } else { x->parent->right = y; // right-child } } y->left = x; // make x be y's LEFT-CHILD x->parent = y; // make y be x's parent return; } void splittree::rotateRight(elementsp *y) { elementsp *x; // do pointer-swapping operations for right-rotation x = y->left; // grab left child y->left = x->right; // replace left child yith x's right subtree x->right->parent = y; // replace y as x's right subtree's parent x->parent = y->parent; // make x's new parent be y's old parent if (y->parent == NULL) { root = x; // if y was root, make x root } else { if (y == y->parent->right) { // if y is R-CHILD, make x be y's parent's y->parent->right = x; // right-child } else { y->parent->left = x; // left-child } } x->right = y; // make y be x's RIGHT-CHILD y->parent = x; // make x be y's parent return; } // *********************************************************************** // *** COPYRIGHT NOTICE ************************************************** // graph_simp.h - graph data structure // Copyright (C) 2006-2008 Aaron Clauset // // This program is free software; you can redistribute it and/or modify // it under the terms of the GNU General Public License as published by // the Free Software Foundation; either version 2 of the License, or // (at your option) any later version. // // This program is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU General Public License for more details. // // You should have received a copy of the GNU General Public License // along with this program; if not, write to the Free Software // Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA // // See http://www.gnu.org/licenses/gpl.txt for more details. // // *********************************************************************** // Author : Aaron Clauset ( aaronc@santafe.edu | // http://www.santafe.edu/~aaronc/ ) // Collaborators: Cristopher Moore and Mark E.J. Newman // Project : Hierarchical Random Graphs // Location : University of New Mexico, Dept. of Computer Science // AND Santa Fe Institute // Created : 21 June 2006 // Modified : 23 December 2007 (cleaned up for public consumption) // // ************************************************************************ // ******** Constructor / Destructor ************************************* simpleGraph::simpleGraph(const int size): n(size), m(0), num_groups(0) { nodes = new simpleVert [n]; nodeLink = new simpleEdge* [n]; nodeLinkTail = new simpleEdge* [n]; A = new double* [n]; for (int i = 0; i < n; i++) { nodeLink[i] = NULL; nodeLinkTail[i] = NULL; A[i] = new double [n]; for (int j = 0; j < n; j++) { A[i][j] = 0.0; } } E = NULL; } simpleGraph::~simpleGraph() { simpleEdge *curr, *prev; for (int i = 0; i < n; i++) { curr = nodeLink[i]; delete [] A[i]; while (curr != NULL) { prev = curr; curr = curr->next; delete prev; } } curr = NULL; prev = NULL; if (E != NULL) { delete [] E; E = NULL; } delete [] A; A = NULL; delete [] nodeLink; nodeLink = NULL; delete [] nodeLinkTail; nodeLinkTail = NULL; delete [] nodes; nodes = NULL; } // *********************************************************************** bool simpleGraph::addGroup(const int i, const int group_index) { if (i >= 0 && i < n) { nodes[i].group_true = group_index; return true; } else { return false; } } // *********************************************************************** bool simpleGraph::addLink(const int i, const int j) { // Adds the directed edge (i,j) to the adjacency list for v_i simpleEdge* newedge; if (i >= 0 && i < n && j >= 0 && j < n) { A[i][j] = 1.0; newedge = new simpleEdge; newedge->x = j; if (nodeLink[i] == NULL) { // first neighbor nodeLink[i] = newedge; nodeLinkTail[i] = newedge; nodes[i].degree = 1; } else { // subsequent neighbor nodeLinkTail[i]->next = newedge; nodeLinkTail[i] = newedge; nodes[i].degree++; } m++; // increment edge count newedge = NULL; return true; } else { return false; } } // *********************************************************************** bool simpleGraph::doesLinkExist(const int i, const int j) { // This function determines if the edge (i,j) already exists in the // adjacency list of v_i if (i >= 0 && i < n && j >= 0 && j < n) { if (A[i][j] > 0.1) { return true; } else { return false; } } else { return false; } return false; } // ********************************************************************** double simpleGraph::getAdjacency(const int i, const int j) { if (i >= 0 && i < n && j >= 0 && j < n) { return A[i][j]; } else { return -1.0; } } int simpleGraph::getDegree(const int i) { if (i >= 0 && i < n) { return nodes[i].degree; } else { return -1; } } int simpleGraph::getGroupLabel(const int i) { if (i >= 0 && i < n) { return nodes[i].group_true; } else { return -1; } } string simpleGraph::getName(const int i) { if (i >= 0 && i < n) { return nodes[i].name; } else { return ""; } } // NOTE: The following three functions return addresses; deallocation // of returned object is dangerous simpleEdge* simpleGraph::getNeighborList(const int i) { if (i >= 0 && i < n) { return nodeLink[i]; } else { return NULL; } } // END-NOTE // ********************************************************************* int simpleGraph::getNumGroups() { return num_groups; } int simpleGraph::getNumLinks() { return m; } int simpleGraph::getNumNodes() { return n; } simpleVert* simpleGraph::getNode(const int i) { if (i >= 0 && i < n) { return &nodes[i]; } else { return NULL; } } // ********************************************************************** bool simpleGraph::setName(const int i, const string text) { if (i >= 0 && i < n) { nodes[i].name = text; return true; } else { return false; } } // ********************************************************************** void simpleGraph::QsortMain (block* array, int left, int right) { if (right > left) { int pivot = left; int part = QsortPartition(array, left, right, pivot); QsortMain(array, left, part - 1); QsortMain(array, part + 1, right ); } return; } int simpleGraph::QsortPartition (block* array, int left, int right, int index) { block p_value, temp; p_value.x = array[index].x; p_value.y = array[index].y; // swap(array[p_value], array[right]) temp.x = array[right].x; temp.y = array[right].y; array[right].x = array[index].x; array[right].y = array[index].y; array[index].x = temp.x; array[index].y = temp.y; int stored = left; for (int i = left; i < right; i++) { if (array[i].x <= p_value.x) { // swap(array[stored], array[i]) temp.x = array[i].x; temp.y = array[i].y; array[i].x = array[stored].x; array[i].y = array[stored].y; array[stored].x = temp.x; array[stored].y = temp.y; stored++; } } // swap(array[right], array[stored]) temp.x = array[stored].x; temp.y = array[stored].y; array[stored].x = array[right].x; array[stored].y = array[right].y; array[right].x = temp.x; array[right].y = temp.y; return stored; } // *********************************************************************** python-igraph-0.8.0/vendor/source/igraph/src/foreign.c0000644000076500000240000040104013614300625023172 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph R package. Copyright (C) 2005-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_foreign.h" #include "config.h" #include "igraph_math.h" #include "igraph_gml_tree.h" #include "igraph_memory.h" #include "igraph_attributes.h" #include "igraph_interface.h" #include "igraph_interrupt_internal.h" #include "igraph_constructors.h" #include "igraph_types_internal.h" #include /* isspace */ #include #include /** * \section about_loadsave * * These functions can write a graph to a file, or read a graph * from a file. * * Note that as \a igraph uses the traditional C streams, it is * possible to read/write files from/to memory, at least on GNU * operating systems supporting \quote non-standard\endquote streams. */ /** * \ingroup loadsave * \function igraph_read_graph_edgelist * \brief Reads an edge list from a file and creates a graph. * * * This format is simply a series of even number integers separated by * whitespace. The one edge (ie. two integers) per line format is thus * not required (but recommended for readability). Edges of directed * graphs are assumed to be in from, to order. * \param graph Pointer to an uninitialized graph object. * \param instream Pointer to a stream, it should be readable. * \param n The number of vertices in the graph. If smaller than the * largest integer in the file it will be ignored. It is thus * safe to supply zero here. * \param directed Logical, if true the graph is directed, if false it * will be undirected. * \return Error code: * \c IGRAPH_PARSEERROR: if there is a * problem reading the file, or the file is syntactically * incorrect. * * Time complexity: O(|V|+|E|), the * number of vertices plus the number of edges. It is assumed that * reading an integer requires O(1) * time. */ int igraph_read_graph_edgelist(igraph_t *graph, FILE *instream, igraph_integer_t n, igraph_bool_t directed) { igraph_vector_t edges = IGRAPH_VECTOR_NULL; long int from, to; int c; IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_CHECK(igraph_vector_reserve(&edges, 100)); /* skip all whitespace */ do { c = getc (instream); } while (isspace (c)); ungetc (c, instream); while (!feof(instream)) { int read; IGRAPH_ALLOW_INTERRUPTION(); read = fscanf(instream, "%li", &from); if (read != 1) { IGRAPH_ERROR("parsing edgelist file failed", IGRAPH_PARSEERROR); } read = fscanf(instream, "%li", &to); if (read != 1) { IGRAPH_ERROR("parsing edgelist file failed", IGRAPH_PARSEERROR); } IGRAPH_CHECK(igraph_vector_push_back(&edges, from)); IGRAPH_CHECK(igraph_vector_push_back(&edges, to)); /* skip all whitespace */ do { c = getc (instream); } while (isspace (c)); ungetc (c, instream); } IGRAPH_CHECK(igraph_create(graph, &edges, n, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } #include "foreign-ncol-header.h" int igraph_ncol_yylex_init_extra (igraph_i_ncol_parsedata_t* user_defined, void* scanner); int igraph_ncol_yylex_destroy (void *scanner ); int igraph_ncol_yyparse (igraph_i_ncol_parsedata_t* context); void igraph_ncol_yyset_in (FILE * in_str, void* yyscanner ); /** * \ingroup loadsave * \function igraph_read_graph_ncol * \brief Reads a .ncol file used by LGL. * * Also useful for creating graphs from \quote named\endquote (and * optionally weighted) edge lists. * * * This format is used by the Large Graph Layout program * (http://lgl.sourceforge.net), and it is simply a * symbolic weighted edge list. It is a simple text file with one edge * per line. An edge is defined by two symbolic vertex names separated * by whitespace. (The symbolic vertex names themselves cannot contain * whitespace. They might follow by an optional number, this will be * the weight of the edge; the number can be negative and can be in * scientific notation. If there is no weight specified to an edge it * is assumed to be zero. * * * The resulting graph is always undirected. * LGL cannot deal with files which contain multiple or loop edges, * this is however not checked here, as \a igraph is happy with * these. * \param graph Pointer to an uninitialized graph object. * \param instream Pointer to a stream, it should be readable. * \param predefnames Pointer to the symbolic names of the vertices in * the file. If \c NULL is given here then vertex ids will be * assigned to vertex names in the order of their appearance in * the \c .ncol file. If it is not \c NULL and some unknown * vertex names are found in the \c .ncol file then new vertex * ids will be assigned to them. * \param names Logical value, if TRUE the symbolic names of the * vertices will be added to the graph as a vertex attribute * called \quote name\endquote. * \param weights Whether to add the weights of the edges to the * graph as an edge attribute called \quote weight\endquote. * \c IGRAPH_ADD_WEIGHTS_YES adds the weights (even if they * are not present in the file, in this case they are assumed * to be zero). \c IGRAPH_ADD_WEIGHTS_NO does not add any * edge attribute. \c IGRAPH_ADD_WEIGHTS_IF_PRESENT adds the * attribute if and only if there is at least one explicit * edge weight in the input file. * \param directed Whether to create a directed graph. As this format * was originally used only for undirected graphs there is no * information in the file about the directedness of the graph. * Set this parameter to \c IGRAPH_DIRECTED or \c * IGRAPH_UNDIRECTED to create a directed or undirected graph. * \return Error code: * \c IGRAPH_PARSEERROR: if there is a * problem reading * the file, or the file is syntactically incorrect. * * Time complexity: * O(|V|+|E|log(|V|)) if we neglect * the time required by the parsing. As usual * |V| is the number of vertices, * while |E| is the number of edges. * * \sa \ref igraph_read_graph_lgl(), \ref igraph_write_graph_ncol() */ int igraph_read_graph_ncol(igraph_t *graph, FILE *instream, igraph_strvector_t *predefnames, igraph_bool_t names, igraph_add_weights_t weights, igraph_bool_t directed) { igraph_vector_t edges, ws; igraph_trie_t trie = IGRAPH_TRIE_NULL; igraph_integer_t no_of_nodes; long int no_predefined = 0; igraph_vector_ptr_t name, weight; igraph_vector_ptr_t *pname = 0, *pweight = 0; igraph_attribute_record_t namerec, weightrec; const char *namestr = "name", *weightstr = "weight"; igraph_i_ncol_parsedata_t context; IGRAPH_CHECK(igraph_empty(graph, 0, directed)); IGRAPH_FINALLY(igraph_destroy, graph); IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_TRIE_INIT_FINALLY(&trie, names); IGRAPH_VECTOR_INIT_FINALLY(&ws, 0); /* Add the predefined names, if any */ if (predefnames != 0) { long int i, id, n; char *key; n = no_predefined = igraph_strvector_size(predefnames); for (i = 0; i < n; i++) { igraph_strvector_get(predefnames, i, &key); igraph_trie_get(&trie, key, &id); if (id != i) { IGRAPH_WARNING("reading NCOL file, duplicate entry in predefnames"); no_predefined--; } } } context.has_weights = 0; context.vector = &edges; context.weights = &ws; context.trie = ≜ context.eof = 0; igraph_ncol_yylex_init_extra(&context, &context.scanner); IGRAPH_FINALLY(igraph_ncol_yylex_destroy, context.scanner); igraph_ncol_yyset_in(instream, context.scanner); if (igraph_ncol_yyparse(&context)) { if (context.errmsg[0] != 0) { IGRAPH_ERROR(context.errmsg, IGRAPH_PARSEERROR); } else { IGRAPH_ERROR("Cannot read NCOL file", IGRAPH_PARSEERROR); } } if (predefnames != 0 && igraph_trie_size(&trie) != no_predefined) { IGRAPH_WARNING("unknown vertex/vertices found, predefnames extended"); } if (names) { const igraph_strvector_t *namevec; IGRAPH_CHECK(igraph_vector_ptr_init(&name, 1)); pname = &name; igraph_trie_getkeys(&trie, &namevec); /* dirty */ namerec.name = namestr; namerec.type = IGRAPH_ATTRIBUTE_STRING; namerec.value = namevec; VECTOR(name)[0] = &namerec; } if (weights == IGRAPH_ADD_WEIGHTS_YES || (weights == IGRAPH_ADD_WEIGHTS_IF_PRESENT && context.has_weights)) { IGRAPH_CHECK(igraph_vector_ptr_init(&weight, 1)); pweight = &weight; weightrec.name = weightstr; weightrec.type = IGRAPH_ATTRIBUTE_NUMERIC; weightrec.value = &ws; VECTOR(weight)[0] = &weightrec; } if (igraph_vector_empty(&edges)) { no_of_nodes = 0; } else { no_of_nodes = igraph_vector_max(&edges) + 1; } IGRAPH_CHECK(igraph_add_vertices(graph, no_of_nodes, pname)); IGRAPH_CHECK(igraph_add_edges(graph, &edges, pweight)); if (pname) { igraph_vector_ptr_destroy(pname); } if (pweight) { igraph_vector_ptr_destroy(pweight); } igraph_vector_destroy(&ws); igraph_trie_destroy(&trie); igraph_vector_destroy(&edges); igraph_ncol_yylex_destroy(context.scanner); IGRAPH_FINALLY_CLEAN(5); return 0; } #include "foreign-lgl-header.h" int igraph_lgl_yylex_init_extra (igraph_i_lgl_parsedata_t* user_defined, void* scanner); int igraph_lgl_yylex_destroy (void *scanner ); int igraph_lgl_yyparse (igraph_i_lgl_parsedata_t* context); void igraph_lgl_yyset_in (FILE * in_str, void* yyscanner ); /** * \ingroup loadsave * \function igraph_read_graph_lgl * \brief Reads a graph from an .lgl file * * * The .lgl format is used by the Large Graph * Layout visualization software * (http://lgl.sourceforge.net), it can * describe undirected optionally weighted graphs. From the LGL * manual: * * \blockquote The second format is the LGL file format * (.lgl file * suffix). This is yet another graph file format that tries to be as * stingy as possible with space, yet keeping the edge file in a human * readable (not binary) format. The format itself is like the * following: * \verbatim # vertex1name vertex2name [optionalWeight] vertex3name [optionalWeight] \endverbatim * Here, the first vertex of an edge is preceded with a pound sign * '#'. Then each vertex that shares an edge with that vertex is * listed one per line on subsequent lines. \endblockquote * * * LGL cannot handle loop and multiple edges or directed graphs, but * in \a igraph it is not an error to have multiple and loop edges. * \param graph Pointer to an uninitialized graph object. * \param instream A stream, it should be readable. * \param names Logical value, if TRUE the symbolic names of the * vertices will be added to the graph as a vertex attribute * called \quote name\endquote. * \param weights Whether to add the weights of the edges to the * graph as an edge attribute called \quote weight\endquote. * \c IGRAPH_ADD_WEIGHTS_YES adds the weights (even if they * are not present in the file, in this case they are assumed * to be zero). \c IGRAPH_ADD_WEIGHTS_NO does not add any * edge attribute. \c IGRAPH_ADD_WEIGHTS_IF_PRESENT adds the * attribute if and only if there is at least one explicit * edge weight in the input file. * \param directed Whether to create a directed graph. As this format * was originally used only for undirected graphs there is no * information in the file about the directedness of the graph. * Set this parameter to \c IGRAPH_DIRECTED or \c * IGRAPH_UNDIRECTED to create a directed or undirected graph. * \return Error code: * \c IGRAPH_PARSEERROR: if there is a * problem reading the file, or the file is syntactically * incorrect. * * Time complexity: * O(|V|+|E|log(|V|)) if we neglect * the time required by the parsing. As usual * |V| is the number of vertices, * while |E| is the number of edges. * * \sa \ref igraph_read_graph_ncol(), \ref igraph_write_graph_lgl() * * \example examples/simple/igraph_read_graph_lgl.c */ int igraph_read_graph_lgl(igraph_t *graph, FILE *instream, igraph_bool_t names, igraph_add_weights_t weights, igraph_bool_t directed) { igraph_vector_t edges = IGRAPH_VECTOR_NULL, ws = IGRAPH_VECTOR_NULL; igraph_trie_t trie = IGRAPH_TRIE_NULL; igraph_vector_ptr_t name, weight; igraph_vector_ptr_t *pname = 0, *pweight = 0; igraph_attribute_record_t namerec, weightrec; const char *namestr = "name", *weightstr = "weight"; igraph_i_lgl_parsedata_t context; IGRAPH_VECTOR_INIT_FINALLY(&ws, 0); IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_TRIE_INIT_FINALLY(&trie, names); context.has_weights = 0; context.vector = &edges; context.weights = &ws; context.trie = ≜ context.eof = 0; igraph_lgl_yylex_init_extra(&context, &context.scanner); IGRAPH_FINALLY(igraph_lgl_yylex_destroy, context.scanner); igraph_lgl_yyset_in(instream, context.scanner); if (igraph_lgl_yyparse(&context)) { if (context.errmsg[0] != 0) { IGRAPH_ERROR(context.errmsg, IGRAPH_PARSEERROR); } else { IGRAPH_ERROR("Cannot read LGL file", IGRAPH_PARSEERROR); } } IGRAPH_CHECK(igraph_empty(graph, 0, directed)); IGRAPH_FINALLY(igraph_destroy, graph); if (names) { const igraph_strvector_t *namevec; IGRAPH_CHECK(igraph_vector_ptr_init(&name, 1)); IGRAPH_FINALLY(igraph_vector_ptr_destroy, &name); pname = &name; igraph_trie_getkeys(&trie, &namevec); /* dirty */ namerec.name = namestr; namerec.type = IGRAPH_ATTRIBUTE_STRING; namerec.value = namevec; VECTOR(name)[0] = &namerec; } if (weights == IGRAPH_ADD_WEIGHTS_YES || (weights == IGRAPH_ADD_WEIGHTS_IF_PRESENT && context.has_weights)) { IGRAPH_CHECK(igraph_vector_ptr_init(&weight, 1)); IGRAPH_FINALLY(igraph_vector_ptr_destroy, &weight); pweight = &weight; weightrec.name = weightstr; weightrec.type = IGRAPH_ATTRIBUTE_NUMERIC; weightrec.value = &ws; VECTOR(weight)[0] = &weightrec; } IGRAPH_CHECK(igraph_add_vertices(graph, (igraph_integer_t) igraph_trie_size(&trie), pname)); IGRAPH_CHECK(igraph_add_edges(graph, &edges, pweight)); if (pweight) { igraph_vector_ptr_destroy(pweight); IGRAPH_FINALLY_CLEAN(1); } if (pname) { igraph_vector_ptr_destroy(pname); IGRAPH_FINALLY_CLEAN(1); } igraph_trie_destroy(&trie); igraph_vector_destroy(&edges); igraph_vector_destroy(&ws); igraph_lgl_yylex_destroy(context.scanner); IGRAPH_FINALLY_CLEAN(5); return 0; } #include "foreign-pajek-header.h" int igraph_pajek_yylex_init_extra(igraph_i_pajek_parsedata_t* user_defined, void* scanner); int igraph_pajek_yylex_destroy (void *scanner ); int igraph_pajek_yyparse (igraph_i_pajek_parsedata_t* context); void igraph_pajek_yyset_in (FILE * in_str, void* yyscanner ); /** * \function igraph_read_graph_pajek * \brief Reads a file in Pajek format * * \param graph Pointer to an uninitialized graph object. * \param file An already opened file handler. * \return Error code. * * * Only a subset of the Pajek format is implemented. This is partially * because this format is not very well documented, but also because * igraph does not support some Pajek features, like * multigraphs. * * * Starting from version 0.6.1 igraph reads bipartite (two-mode) * graphs from Pajek files and add the \c type vertex attribute for them. * Warnings are given for invalid edges, i.e. edges connecting * vertices of the same type. * * * The list of the current limitations: * \olist * \oli Only .net files are supported, Pajek * project files (.paj) are not. These might be * supported in the future if there is need for it. * \oli Time events networks are not supported. * \oli Hypergraphs (ie. graphs with non-binary edges) are not * supported. * \oli Graphs with both directed and non-directed edges are not * supported, are they cannot be represented in * igraph. * \oli Only Pajek networks are supported, permutations, hierarchies, * clusters and vectors are not. * \oli Graphs with multiple edge sets are not supported. * \endolist * * * If there are attribute handlers installed, * igraph also reads the vertex and edge attributes * from the file. Most attributes are renamed to be more informative: * `\c color' instead of `\c c', `\c xfact' instead of `\c x_fact', * `\c yfact' instead of `y_fact', `\c labeldist' instead of `\c lr', * `\c labeldegree2' instead of `\c lphi', `\c framewidth' instead of `\c bw', * `\c fontsize' * instead of `\c fos', `\c rotation' instead of `\c phi', `\c radius' instead * of `\c r', * `\c diamondratio' instead of `\c q', `\c labeldegree' instead of `\c la', * `\c vertexsize' * instead of `\c size', `\c color' instead of `\c ic', `\c framecolor' instead of * `\c bc', `\c labelcolor' instead of `\c lc', these belong to vertices. * * * Edge attributes are also renamed, `\c s' to `\c arrowsize', `\c w' * to `\c edgewidth', `\c h1' to `\c hook1', `\c h2' to `\c hook2', * `\c a1' to `\c angle1', `\c a2' to `\c angle2', `\c k1' to * `\c velocity1', `\c k2' to `\c velocity2', `\c ap' to `\c * arrowpos', `\c lp' to `\c labelpos', `\c lr' to * `\c labelangle', `\c lphi' to `\c labelangle2', `\c la' to `\c * labeldegree', `\c fos' to * `\c fontsize', `\c a' to `\c arrowtype', `\c p' to `\c * linepattern', `\c l' to `\c label', `\c lc' to * `\c labelcolor', `\c c' to `\c color'. * * * In addition the following vertex attributes might be added: `\c id' * if there are vertex ids in the file, `\c x' and `\c y' or `\c x' * and `\c y' and `\c z' if there are vertex coordinates in the file. * * The `\c weight' edge attribute might be * added if there are edge weights present. * * * See the pajek homepage: * http://vlado.fmf.uni-lj.si/pub/networks/pajek/ for more info on * Pajek and the Pajek manual: * http://vlado.fmf.uni-lj.si/pub/networks/pajek/doc/pajekman.pdf for * information on the Pajek file format. * * * Time complexity: O(|V|+|E|+|A|), |V| is the number of vertices, |E| * the number of edges, |A| the number of attributes (vertex + edge) * in the graph if there are attribute handlers installed. * * \sa \ref igraph_write_graph_pajek() for writing Pajek files, \ref * igraph_read_graph_graphml() for reading GraphML files. * * \example examples/simple/foreign.c */ int igraph_read_graph_pajek(igraph_t *graph, FILE *instream) { igraph_vector_t edges; igraph_trie_t vattrnames; igraph_vector_ptr_t vattrs; igraph_trie_t eattrnames; igraph_vector_ptr_t eattrs; long int i, j; igraph_i_pajek_parsedata_t context; IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_TRIE_INIT_FINALLY(&vattrnames, 1); IGRAPH_VECTOR_PTR_INIT_FINALLY(&vattrs, 0); IGRAPH_TRIE_INIT_FINALLY(&eattrnames, 1); IGRAPH_VECTOR_PTR_INIT_FINALLY(&eattrs, 0); context.vector = &edges; context.mode = 0; context.vcount = -1; context.vertexid = 0; context.vertex_attribute_names = &vattrnames; context.vertex_attributes = &vattrs; context.edge_attribute_names = &eattrnames; context.edge_attributes = &eattrs; context.actedge = 0; context.eof = 0; igraph_pajek_yylex_init_extra(&context, &context.scanner); IGRAPH_FINALLY(igraph_pajek_yylex_destroy, context.scanner); igraph_pajek_yyset_in(instream, context.scanner); if (igraph_pajek_yyparse(&context)) { if (context.errmsg[0] != 0) { IGRAPH_ERROR(context.errmsg, IGRAPH_PARSEERROR); } else { IGRAPH_ERROR("Cannot read Pajek file", IGRAPH_PARSEERROR); } } if (context.vcount < 0) { IGRAPH_ERROR("invalid vertex count in Pajek file", IGRAPH_EINVAL); } if (context.vcount2 < 0) { IGRAPH_ERROR("invalid 2-mode vertex count in Pajek file", IGRAPH_EINVAL); } for (i = 0; i < igraph_vector_ptr_size(&eattrs); i++) { igraph_attribute_record_t *rec = VECTOR(eattrs)[i]; if (rec->type == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_vector_t *vec = (igraph_vector_t*)rec->value; long int origsize = igraph_vector_size(vec); igraph_vector_resize(vec, context.actedge); for (j = origsize; j < context.actedge; j++) { VECTOR(*vec)[j] = IGRAPH_NAN; } } else if (rec->type == IGRAPH_ATTRIBUTE_STRING) { igraph_strvector_t *strvec = (igraph_strvector_t*)rec->value; long int origsize = igraph_strvector_size(strvec); igraph_strvector_resize(strvec, context.actedge); for (j = origsize; j < context.actedge; j++) { igraph_strvector_set(strvec, j, ""); } } } IGRAPH_CHECK(igraph_empty(graph, 0, context.directed)); IGRAPH_FINALLY(igraph_destroy, graph); IGRAPH_CHECK(igraph_add_vertices(graph, context.vcount, &vattrs)); IGRAPH_CHECK(igraph_add_edges(graph, &edges, &eattrs)); for (i = 0; i < igraph_vector_ptr_size(&vattrs); i++) { igraph_attribute_record_t *rec = VECTOR(vattrs)[i]; if (rec->type == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_vector_t *vec = (igraph_vector_t*) rec->value; igraph_vector_destroy(vec); igraph_Free(vec); } else if (rec->type == IGRAPH_ATTRIBUTE_STRING) { igraph_strvector_t *strvec = (igraph_strvector_t *)rec->value; igraph_strvector_destroy(strvec); igraph_Free(strvec); } igraph_free( (char*)(rec->name)); igraph_Free(rec); } for (i = 0; i < igraph_vector_ptr_size(&eattrs); i++) { igraph_attribute_record_t *rec = VECTOR(eattrs)[i]; if (rec->type == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_vector_t *vec = (igraph_vector_t*) rec->value; igraph_vector_destroy(vec); igraph_Free(vec); } else if (rec->type == IGRAPH_ATTRIBUTE_STRING) { igraph_strvector_t *strvec = (igraph_strvector_t *)rec->value; igraph_strvector_destroy(strvec); igraph_Free(strvec); } igraph_free( (char*)(rec->name)); igraph_Free(rec); } igraph_vector_destroy(&edges); igraph_vector_ptr_destroy(&eattrs); igraph_trie_destroy(&eattrnames); igraph_vector_ptr_destroy(&vattrs); igraph_trie_destroy(&vattrnames); igraph_pajek_yylex_destroy(context.scanner); IGRAPH_FINALLY_CLEAN(7); return 0; } /** * \function igraph_read_graph_dimacs * \brief Read a graph in DIMACS format. * * This function reads the DIMACS file format, more specifically the * version for network flow problems, see the files at * ftp://dimacs.rutgers.edu/pub/netflow/general-info/ * * * This is a line-oriented text file (ASCII) format. The first * character of each line defines the type of the line. If the first * character is c the line is a comment line and it is * ignored. There is one problem line (p in the file, it * must appear before any node and arc descriptor lines. The problem * line has three fields separated by spaces: the problem type * (min, max or asn), the * number of vertices and number of edges in the graph. * Exactly two node identification lines are expected * (n), one for the source, one for the target vertex. * These have two fields: the id of the vertex and the type of the * vertex, either s (=source) or t * (=target). Arc lines start with a and have three * fields: the source vertex, the target vertex and the edge capacity. * * * Vertex ids are numbered from 1. * \param graph Pointer to an uninitialized graph object. * \param instream The file to read from. * \param source Pointer to an integer, the id of the source node will * be stored here. (The igraph vertex id, which is one less than * the actual number in the file.) It is ignored if * NULL. * \param target Pointer to an integer, the (igraph) id of the target * node will be stored here. It is ignored if NULL. * \param capacity Pointer to an initialized vector, the capacity of * the edges will be stored here if not NULL. * \param directed Boolean, whether to create a directed graph. * \return Error code. * * Time complexity: O(|V|+|E|+c), the number of vertices plus the * number of edges, plus the size of the file in characters. * * \sa \ref igraph_write_graph_dimacs() */ int igraph_read_graph_dimacs(igraph_t *graph, FILE *instream, igraph_strvector_t *problem, igraph_vector_t *label, igraph_integer_t *source, igraph_integer_t *target, igraph_vector_t *capacity, igraph_bool_t directed) { igraph_vector_t edges; long int no_of_nodes = -1; long int no_of_edges = -1; long int tsource = -1; long int ttarget = -1; char prob[21]; char c; int problem_type = 0; #define PROBLEM_EDGE 1 #define PROBLEM_MAX 2 IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); if (capacity) { igraph_vector_clear(capacity); } while (!feof(instream)) { int read; char str[3]; IGRAPH_ALLOW_INTERRUPTION(); read = fscanf(instream, "%2c", str); if (feof(instream)) { break; } if (read != 1) { IGRAPH_ERROR("parsing dimacs file failed", IGRAPH_PARSEERROR); } switch (str[0]) { long int tmp, tmp2; long int from, to; igraph_real_t cap; case 'c': /* comment */ break; case 'p': if (no_of_nodes != -1) { IGRAPH_ERROR("reading dimacs file failed, double 'p' line", IGRAPH_PARSEERROR); } read = fscanf(instream, "%20s %li %li", prob, &no_of_nodes, &no_of_edges); if (read != 3) { IGRAPH_ERROR("reading dimacs file failed", IGRAPH_PARSEERROR); } if (!strcmp(prob, "edge")) { /* edge list */ problem_type = PROBLEM_EDGE; if (label) { long int i; IGRAPH_CHECK(igraph_vector_resize(label, no_of_nodes)); for (i = 0; i < no_of_nodes; i++) { VECTOR(*label)[i] = i + 1; } } } else if (!strcmp(prob, "max")) { /* maximum flow problem */ problem_type = PROBLEM_MAX; if (capacity) { IGRAPH_CHECK(igraph_vector_reserve(capacity, no_of_edges)); } } else { IGRAPH_ERROR("Unknown problem type, should be 'edge' or 'max'", IGRAPH_PARSEERROR); } if (problem) { igraph_strvector_clear(problem); IGRAPH_CHECK(igraph_strvector_add(problem, prob)); } IGRAPH_CHECK(igraph_vector_reserve(&edges, no_of_edges * 2)); break; case 'n': /* for MAX this is either the source or target vertex, for EDGE this is a vertex label */ if (problem_type == PROBLEM_MAX) { str[0] = 'x'; read = fscanf(instream, "%li %1s", &tmp, str); if (str[0] == 's') { if (tsource != -1) { IGRAPH_ERROR("reading dimacsfile: multiple source vertex line", IGRAPH_PARSEERROR); } else { tsource = tmp; } } else if (str[0] == 't') { if (ttarget != -1) { IGRAPH_ERROR("reading dimacsfile: multiple target vertex line", IGRAPH_PARSEERROR); } else { ttarget = tmp; } } else { IGRAPH_ERROR("invalid node descriptor line in dimacs file", IGRAPH_PARSEERROR); } } else { read = fscanf(instream, "%li %li", &tmp, &tmp2); if (label) { VECTOR(*label)[tmp] = tmp2; } } break; case 'a': /* This is valid only for MAX, a weighted edge */ if (problem_type != PROBLEM_MAX) { IGRAPH_ERROR("'a' lines are allowed only in MAX problem files", IGRAPH_PARSEERROR); } read = fscanf(instream, "%li %li %lf", &from, &to, &cap); if (read != 3) { IGRAPH_ERROR("reading dimacs file", IGRAPH_PARSEERROR); } IGRAPH_CHECK(igraph_vector_push_back(&edges, from - 1)); IGRAPH_CHECK(igraph_vector_push_back(&edges, to - 1)); if (capacity) { IGRAPH_CHECK(igraph_vector_push_back(capacity, cap)); } break; case 'e': /* Edge line, only in EDGE */ if (problem_type != PROBLEM_EDGE) { IGRAPH_ERROR("'e' lines are allowed only in EDGE problem files", IGRAPH_PARSEERROR); } read = fscanf(instream, "%li %li", &from, &to); if (read != 2) { IGRAPH_ERROR("reading dimacs file", IGRAPH_PARSEERROR); } IGRAPH_CHECK(igraph_vector_push_back(&edges, from - 1)); IGRAPH_CHECK(igraph_vector_push_back(&edges, to - 1)); break; default: IGRAPH_ERROR("unknown line type in dimacs file", IGRAPH_PARSEERROR); } /* Go to next line */ while (!feof(instream) && (c = (char) getc(instream)) != '\n') ; } if (source) { *source = (igraph_integer_t) tsource - 1; } if (target) { *target = (igraph_integer_t) ttarget - 1; } IGRAPH_CHECK(igraph_create(graph, &edges, (igraph_integer_t) no_of_nodes, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_i_read_graph_graphdb_getword(FILE *instream) { int b1, b2; unsigned char c1, c2; b1 = fgetc(instream); b2 = fgetc(instream); if (b1 != EOF) { c1 = (unsigned char) b1; c2 = (unsigned char) b2; return c1 | (c2 << 8); } else { return -1; } } /** * \function igraph_read_graph_graphdb * \brief Read a graph in the binary graph database format. * * This is a binary format, used in the graph database * for isomorphism testing. From the (now defunct) graph database * homepage: * * * \blockquote * The graphs are stored in a compact binary format, one graph per * file. The file is composed of 16 bit words, which are represented * using the so-called little-endian convention, i.e. the least * significant byte of the word is stored first. * * * Then, for each node, the file contains the list of edges coming * out of the node itself. The list is represented by a word encoding * its length, followed by a word for each edge, representing the * destination node of the edge. Node numeration is 0-based, so the * first node of the graph has index 0. \endblockquote * * * Only unlabelled graphs are implemented. * \param graph Pointer to an uninitialized graph object. * \param instream The stream to read from. * \param directed Logical scalar, whether to create a directed graph. * \return Error code. * * Time complexity: O(|V|+|E|), the number of vertices plus the * number of edges. * * \example examples/simple/igraph_read_graph_graphdb.c */ int igraph_read_graph_graphdb(igraph_t *graph, FILE *instream, igraph_bool_t directed) { igraph_vector_t edges; long int nodes; long int i, j; igraph_bool_t end = 0; IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); nodes = igraph_i_read_graph_graphdb_getword(instream); if (nodes < 0) { IGRAPH_ERROR("Can't read from file", IGRAPH_EFILE); } for (i = 0; !end && i < nodes; i++) { long int len = igraph_i_read_graph_graphdb_getword(instream); if (len < 0) { end = 1; break; } for (j = 0; ! end && j < len; j++) { long int to = igraph_i_read_graph_graphdb_getword(instream); if (to < 0) { end = 1; break; } IGRAPH_CHECK(igraph_vector_push_back(&edges, i)); IGRAPH_CHECK(igraph_vector_push_back(&edges, to)); } } if (end) { IGRAPH_ERROR("Truncated graphdb file", IGRAPH_EFILE); } IGRAPH_CHECK(igraph_create(graph, &edges, (igraph_integer_t) nodes, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } #include "foreign-gml-header.h" int igraph_gml_yylex_init_extra (igraph_i_gml_parsedata_t* user_defined, void* scanner); int igraph_gml_yylex_destroy (void *scanner ); int igraph_gml_yyparse (igraph_i_gml_parsedata_t* context); void igraph_gml_yyset_in (FILE * in_str, void* yyscanner ); void igraph_i_gml_destroy_attrs(igraph_vector_ptr_t **ptr) { long int i; igraph_vector_ptr_t *vec; for (i = 0; i < 3; i++) { long int j; vec = ptr[i]; for (j = 0; j < igraph_vector_ptr_size(vec); j++) { igraph_attribute_record_t *atrec = VECTOR(*vec)[j]; if (atrec->type == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_vector_t *value = (igraph_vector_t*)atrec->value; if (value != 0) { igraph_vector_destroy(value); igraph_Free(value); } } else { igraph_strvector_t *value = (igraph_strvector_t*)atrec->value; if (value != 0) { igraph_strvector_destroy(value); igraph_Free(value); } } igraph_Free(atrec->name); igraph_Free(atrec); } igraph_vector_ptr_destroy(vec); } } igraph_real_t igraph_i_gml_toreal(igraph_gml_tree_t *node, long int pos) { igraph_real_t value = 0.0; int type = igraph_gml_tree_type(node, pos); switch (type) { case IGRAPH_I_GML_TREE_INTEGER: value = igraph_gml_tree_get_integer(node, pos); break; case IGRAPH_I_GML_TREE_REAL: value = igraph_gml_tree_get_real(node, pos); break; default: IGRAPH_ERROR("Internal error while parsing GML file", IGRAPH_FAILURE); break; } return value; } const char *igraph_i_gml_tostring(igraph_gml_tree_t *node, long int pos) { int type = igraph_gml_tree_type(node, pos); char tmp[256]; const char *p = tmp; long int i; igraph_real_t d; switch (type) { case IGRAPH_I_GML_TREE_INTEGER: i = igraph_gml_tree_get_integer(node, pos); snprintf(tmp, sizeof(tmp) / sizeof(char), "%li", i); break; case IGRAPH_I_GML_TREE_REAL: d = igraph_gml_tree_get_real(node, pos); igraph_real_snprintf_precise(tmp, sizeof(tmp) / sizeof(char), d); break; case IGRAPH_I_GML_TREE_STRING: p = igraph_gml_tree_get_string(node, pos); break; default: break; } return p; } /** * \function igraph_read_graph_gml * \brief Read a graph in GML format. * * GML is a simple textual format, see * http://www.fim.uni-passau.de/en/fim/faculty/chairs/theoretische-informatik/projects.html for details. * * * Although all syntactically correct GML can be parsed, * we implement only a subset of this format, some attributes might be * ignored. Here is a list of all the differences: * \olist * \oli Only node and edge attributes are * used, and only if they have a simple type: integer, real or * string. So if an attribute is an array or a record, then it is * ignored. This is also true if only some values of the * attribute are complex. * \oli Top level attributes except for Version and the * first graph attribute are completely ignored. * \oli Graph attributes except for node and * edge are completely ignored. * \oli There is no maximum line length. * \oli There is no maximum keyword length. * \oli Character entities in strings are not interpreted. * \oli We allow inf (infinity) and nan * (not a number) as a real number. This is case insensitive, so * nan, NaN and NAN are equal. * \endolist * * Please contact us if you cannot live with these * limitations of the GML parser. * \param graph Pointer to an uninitialized graph object. * \param instream The stream to read the GML file from. * \return Error code. * * Time complexity: should be proportional to the length of the file. * * \sa \ref igraph_read_graph_graphml() for a more modern format, * \ref igraph_write_graph_gml() for writing GML files. * * \example examples/simple/gml.c */ int igraph_read_graph_gml(igraph_t *graph, FILE *instream) { long int i, p; long int no_of_nodes = 0, no_of_edges = 0; igraph_trie_t trie; igraph_vector_t edges; igraph_bool_t directed = IGRAPH_UNDIRECTED; igraph_gml_tree_t *gtree; long int gidx; igraph_trie_t vattrnames; igraph_trie_t eattrnames; igraph_trie_t gattrnames; igraph_vector_ptr_t gattrs = IGRAPH_VECTOR_PTR_NULL, vattrs = IGRAPH_VECTOR_PTR_NULL, eattrs = IGRAPH_VECTOR_PTR_NULL; igraph_vector_ptr_t *attrs[3]; long int edgeptr = 0; igraph_i_gml_parsedata_t context; attrs[0] = &gattrs; attrs[1] = &vattrs; attrs[2] = &eattrs; context.eof = 0; context.tree = 0; igraph_gml_yylex_init_extra(&context, &context.scanner); IGRAPH_FINALLY(igraph_gml_yylex_destroy, context.scanner); igraph_gml_yyset_in(instream, context.scanner); i = igraph_gml_yyparse(&context); if (i != 0) { if (context.errmsg[0] != 0) { IGRAPH_ERROR(context.errmsg, IGRAPH_PARSEERROR); } else { IGRAPH_ERROR("Cannot read GML file", IGRAPH_PARSEERROR); } } IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); /* Check version, if present, integer and not '1' then ignored */ i = igraph_gml_tree_find(context.tree, "Version", 0); if (i >= 0 && igraph_gml_tree_type(context.tree, i) == IGRAPH_I_GML_TREE_INTEGER && igraph_gml_tree_get_integer(context.tree, i) != 1) { igraph_gml_tree_destroy(context.tree); IGRAPH_ERROR("Unknown GML version", IGRAPH_UNIMPLEMENTED); /* RETURN HERE!!!! */ } /* get the graph */ gidx = igraph_gml_tree_find(context.tree, "graph", 0); if (gidx == -1) { IGRAPH_ERROR("No 'graph' object in GML file", IGRAPH_PARSEERROR); } if (igraph_gml_tree_type(context.tree, gidx) != IGRAPH_I_GML_TREE_TREE) { IGRAPH_ERROR("Invalid type for 'graph' object in GML file", IGRAPH_PARSEERROR); } gtree = igraph_gml_tree_get_tree(context.tree, gidx); IGRAPH_FINALLY(igraph_i_gml_destroy_attrs, &attrs); igraph_vector_ptr_init(&gattrs, 0); igraph_vector_ptr_init(&vattrs, 0); igraph_vector_ptr_init(&eattrs, 0); IGRAPH_TRIE_INIT_FINALLY(&trie, 0); IGRAPH_TRIE_INIT_FINALLY(&vattrnames, 0); IGRAPH_TRIE_INIT_FINALLY(&eattrnames, 0); IGRAPH_TRIE_INIT_FINALLY(&gattrnames, 0); /* Is is directed? */ i = igraph_gml_tree_find(gtree, "directed", 0); if (i >= 0 && igraph_gml_tree_type(gtree, i) == IGRAPH_I_GML_TREE_INTEGER) { if (igraph_gml_tree_get_integer(gtree, i) == 1) { directed = IGRAPH_DIRECTED; } } /* Now we go over all objects in the graph and collect the attribute names and types. Plus we collect node ids. We also do some checks. */ for (i = 0; i < igraph_gml_tree_length(gtree); i++) { long int j; char cname[100]; const char *name = igraph_gml_tree_name(gtree, i); if (!strcmp(name, "node")) { igraph_gml_tree_t *node; igraph_bool_t hasid; no_of_nodes++; if (igraph_gml_tree_type(gtree, i) != IGRAPH_I_GML_TREE_TREE) { IGRAPH_ERROR("'node' is not a list", IGRAPH_PARSEERROR); } node = igraph_gml_tree_get_tree(gtree, i); hasid = 0; for (j = 0; j < igraph_gml_tree_length(node); j++) { const char *name = igraph_gml_tree_name(node, j); long int trieid, triesize = igraph_trie_size(&vattrnames); IGRAPH_CHECK(igraph_trie_get(&vattrnames, name, &trieid)); if (trieid == triesize) { /* new attribute */ igraph_attribute_record_t *atrec = igraph_Calloc(1, igraph_attribute_record_t); int type = igraph_gml_tree_type(node, j); if (!atrec) { IGRAPH_ERROR("Cannot read GML file", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_ptr_push_back(&vattrs, atrec)); atrec->name = strdup(name); if (type == IGRAPH_I_GML_TREE_INTEGER || type == IGRAPH_I_GML_TREE_REAL) { atrec->type = IGRAPH_ATTRIBUTE_NUMERIC; } else { atrec->type = IGRAPH_ATTRIBUTE_STRING; } } else { /* already seen, should we update type? */ igraph_attribute_record_t *atrec = VECTOR(vattrs)[trieid]; int type1 = atrec->type; int type2 = igraph_gml_tree_type(node, j); if (type1 == IGRAPH_ATTRIBUTE_NUMERIC && type2 == IGRAPH_I_GML_TREE_STRING) { atrec->type = IGRAPH_ATTRIBUTE_STRING; } } /* check id */ if (!hasid && !strcmp(name, "id")) { long int id; if (igraph_gml_tree_type(node, j) != IGRAPH_I_GML_TREE_INTEGER) { IGRAPH_ERROR("Non-integer node id in GML file", IGRAPH_PARSEERROR); } id = igraph_gml_tree_get_integer(node, j); snprintf(cname, sizeof(cname) / sizeof(char) -1, "%li", id); IGRAPH_CHECK(igraph_trie_get(&trie, cname, &id)); hasid = 1; } } if (!hasid) { IGRAPH_ERROR("Node without 'id' while parsing GML file", IGRAPH_PARSEERROR); } } else if (!strcmp(name, "edge")) { igraph_gml_tree_t *edge; igraph_bool_t has_source = 0, has_target = 0; no_of_edges++; if (igraph_gml_tree_type(gtree, i) != IGRAPH_I_GML_TREE_TREE) { IGRAPH_ERROR("'edge' is not a list", IGRAPH_PARSEERROR); } edge = igraph_gml_tree_get_tree(gtree, i); has_source = has_target = 0; for (j = 0; j < igraph_gml_tree_length(edge); j++) { const char *name = igraph_gml_tree_name(edge, j); if (!strcmp(name, "source")) { has_source = 1; if (igraph_gml_tree_type(edge, j) != IGRAPH_I_GML_TREE_INTEGER) { IGRAPH_ERROR("Non-integer 'source' for an edge in GML file", IGRAPH_PARSEERROR); } } else if (!strcmp(name, "target")) { has_target = 1; if (igraph_gml_tree_type(edge, j) != IGRAPH_I_GML_TREE_INTEGER) { IGRAPH_ERROR("Non-integer 'source' for an edge in GML file", IGRAPH_PARSEERROR); } } else { long int trieid, triesize = igraph_trie_size(&eattrnames); IGRAPH_CHECK(igraph_trie_get(&eattrnames, name, &trieid)); if (trieid == triesize) { /* new attribute */ igraph_attribute_record_t *atrec = igraph_Calloc(1, igraph_attribute_record_t); int type = igraph_gml_tree_type(edge, j); if (!atrec) { IGRAPH_ERROR("Cannot read GML file", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_ptr_push_back(&eattrs, atrec)); atrec->name = strdup(name); if (type == IGRAPH_I_GML_TREE_INTEGER || type == IGRAPH_I_GML_TREE_REAL) { atrec->type = IGRAPH_ATTRIBUTE_NUMERIC; } else { atrec->type = IGRAPH_ATTRIBUTE_STRING; } } else { /* already seen, should we update type? */ igraph_attribute_record_t *atrec = VECTOR(eattrs)[trieid]; int type1 = atrec->type; int type2 = igraph_gml_tree_type(edge, j); if (type1 == IGRAPH_ATTRIBUTE_NUMERIC && type2 == IGRAPH_I_GML_TREE_STRING) { atrec->type = IGRAPH_ATTRIBUTE_STRING; } } } } /* for */ if (!has_source) { IGRAPH_ERROR("No 'source' for edge in GML file", IGRAPH_PARSEERROR); } if (!has_target) { IGRAPH_ERROR("No 'target' for edge in GML file", IGRAPH_PARSEERROR); } } else { /* anything to do? Maybe add as graph attribute.... */ } } /* check vertex id uniqueness */ if (igraph_trie_size(&trie) != no_of_nodes) { IGRAPH_ERROR("Node 'id' not unique", IGRAPH_PARSEERROR); } /* now we allocate the vectors and strvectors for the attributes */ for (i = 0; i < igraph_vector_ptr_size(&vattrs); i++) { igraph_attribute_record_t *atrec = VECTOR(vattrs)[i]; int type = atrec->type; if (type == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_vector_t *p = igraph_Calloc(1, igraph_vector_t); atrec->value = p; IGRAPH_CHECK(igraph_vector_init(p, no_of_nodes)); } else if (type == IGRAPH_ATTRIBUTE_STRING) { igraph_strvector_t *p = igraph_Calloc(1, igraph_strvector_t); atrec->value = p; IGRAPH_CHECK(igraph_strvector_init(p, no_of_nodes)); } else { IGRAPH_WARNING("A composite attribute ignored"); } } for (i = 0; i < igraph_vector_ptr_size(&eattrs); i++) { igraph_attribute_record_t *atrec = VECTOR(eattrs)[i]; int type = atrec->type; if (type == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_vector_t *p = igraph_Calloc(1, igraph_vector_t); atrec->value = p; IGRAPH_CHECK(igraph_vector_init(p, no_of_edges)); } else if (type == IGRAPH_ATTRIBUTE_STRING) { igraph_strvector_t *p = igraph_Calloc(1, igraph_strvector_t); atrec->value = p; IGRAPH_CHECK(igraph_strvector_init(p, no_of_edges)); } else { IGRAPH_WARNING("A composite attribute ignored"); } } /* Ok, now the edges, attributes too */ IGRAPH_CHECK(igraph_vector_resize(&edges, no_of_edges * 2)); p = -1; while ( (p = igraph_gml_tree_find(gtree, "edge", p + 1)) != -1) { igraph_gml_tree_t *edge; long int from, to, fromidx = 0, toidx = 0; char name[100]; long int j; edge = igraph_gml_tree_get_tree(gtree, p); for (j = 0; j < igraph_gml_tree_length(edge); j++) { const char *n = igraph_gml_tree_name(edge, j); if (!strcmp(n, "source")) { fromidx = igraph_gml_tree_find(edge, "source", 0); } else if (!strcmp(n, "target")) { toidx = igraph_gml_tree_find(edge, "target", 0); } else { long int edgeid = edgeptr / 2; long int trieidx; igraph_attribute_record_t *atrec; int type; igraph_trie_get(&eattrnames, n, &trieidx); atrec = VECTOR(eattrs)[trieidx]; type = atrec->type; if (type == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_vector_t *v = (igraph_vector_t *)atrec->value; VECTOR(*v)[edgeid] = igraph_i_gml_toreal(edge, j); } else if (type == IGRAPH_ATTRIBUTE_STRING) { igraph_strvector_t *v = (igraph_strvector_t *)atrec->value; const char *value = igraph_i_gml_tostring(edge, j); IGRAPH_CHECK(igraph_strvector_set(v, edgeid, value)); } } } from = igraph_gml_tree_get_integer(edge, fromidx); to = igraph_gml_tree_get_integer(edge, toidx); snprintf(name, sizeof(name) / sizeof(char) -1, "%li", from); IGRAPH_CHECK(igraph_trie_get(&trie, name, &from)); snprintf(name, sizeof(name) / sizeof(char) -1, "%li", to); IGRAPH_CHECK(igraph_trie_get(&trie, name, &to)); if (igraph_trie_size(&trie) != no_of_nodes) { IGRAPH_ERROR("Unknown node id found at an edge", IGRAPH_PARSEERROR); } VECTOR(edges)[edgeptr++] = from; VECTOR(edges)[edgeptr++] = to; } /* and add vertex attributes */ for (i = 0; i < igraph_gml_tree_length(gtree); i++) { const char *n; char name[100]; long int j, k; n = igraph_gml_tree_name(gtree, i); if (!strcmp(n, "node")) { igraph_gml_tree_t *node = igraph_gml_tree_get_tree(gtree, i); long int iidx = igraph_gml_tree_find(node, "id", 0); long int id = igraph_gml_tree_get_integer(node, iidx); snprintf(name, sizeof(name) / sizeof(char) -1, "%li", id); igraph_trie_get(&trie, name, &id); for (j = 0; j < igraph_gml_tree_length(node); j++) { const char *aname = igraph_gml_tree_name(node, j); igraph_attribute_record_t *atrec; int type; igraph_trie_get(&vattrnames, aname, &k); atrec = VECTOR(vattrs)[k]; type = atrec->type; if (type == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_vector_t *v = (igraph_vector_t *)atrec->value; VECTOR(*v)[id] = igraph_i_gml_toreal(node, j); } else if (type == IGRAPH_ATTRIBUTE_STRING) { igraph_strvector_t *v = (igraph_strvector_t *)atrec->value; const char *value = igraph_i_gml_tostring(node, j); IGRAPH_CHECK(igraph_strvector_set(v, id, value)); } } } } igraph_gml_tree_destroy(context.tree); igraph_trie_destroy(&trie); igraph_trie_destroy(&gattrnames); igraph_trie_destroy(&vattrnames); igraph_trie_destroy(&eattrnames); IGRAPH_FINALLY_CLEAN(4); IGRAPH_CHECK(igraph_empty_attrs(graph, 0, directed, 0)); /* TODO */ IGRAPH_CHECK(igraph_add_vertices(graph, (igraph_integer_t) no_of_nodes, &vattrs)); IGRAPH_CHECK(igraph_add_edges(graph, &edges, &eattrs)); igraph_i_gml_destroy_attrs(attrs); igraph_vector_destroy(&edges); igraph_gml_yylex_destroy(context.scanner); IGRAPH_FINALLY_CLEAN(3); return 0; } /** * \ingroup loadsave * \function igraph_write_graph_edgelist * \brief Writes the edge list of a graph to a file. * * * One edge is written per line, separated by a single space. * For directed graphs edges are written in from, to order. * \param graph The graph object to write. * \param outstream Pointer to a stream, it should be writable. * \return Error code: * \c IGRAPH_EFILE if there is an error writing the * file. * * Time complexity: O(|E|), the * number of edges in the graph. It is assumed that writing an * integer to the file requires O(1) * time. */ int igraph_write_graph_edgelist(const igraph_t *graph, FILE *outstream) { igraph_eit_t it; IGRAPH_CHECK(igraph_eit_create(graph, igraph_ess_all(IGRAPH_EDGEORDER_FROM), &it)); IGRAPH_FINALLY(igraph_eit_destroy, &it); while (!IGRAPH_EIT_END(it)) { igraph_integer_t from, to; int ret; igraph_edge(graph, IGRAPH_EIT_GET(it), &from, &to); ret = fprintf(outstream, "%li %li\n", (long int) from, (long int) to); if (ret < 0) { IGRAPH_ERROR("Write error", IGRAPH_EFILE); } IGRAPH_EIT_NEXT(it); } igraph_eit_destroy(&it); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \ingroup loadsave * \function igraph_write_graph_ncol * \brief Writes the graph to a file in .ncol format * * * .ncol is a format used by LGL, see \ref * igraph_read_graph_ncol() for details. * * * Note that having multiple or loop edges in an * .ncol file breaks the LGL software but * \a igraph does not check for this condition. * \param graph The graph to write. * \param outstream The stream object to write to, it should be * writable. * \param names The name of the vertex attribute, if symbolic names * are written to the file. If not, supply 0 here. * \param weights The name of the edge attribute, if they are also * written to the file. If you don't want weights, supply 0 * here. * \return Error code: * \c IGRAPH_EFILE if there is an error writing the * file. * * Time complexity: O(|E|), the * number of edges. All file operations are expected to have time * complexity O(1). * * \sa \ref igraph_read_graph_ncol(), \ref igraph_write_graph_lgl() */ int igraph_write_graph_ncol(const igraph_t *graph, FILE *outstream, const char *names, const char *weights) { igraph_eit_t it; igraph_attribute_type_t nametype, weighttype; IGRAPH_CHECK(igraph_eit_create(graph, igraph_ess_all(IGRAPH_EDGEORDER_FROM), &it)); IGRAPH_FINALLY(igraph_eit_destroy, &it); /* Check if we have the names attribute */ if (names && !igraph_i_attribute_has_attr(graph, IGRAPH_ATTRIBUTE_VERTEX, names)) { names = 0; IGRAPH_WARNING("names attribute does not exists"); } if (names) { IGRAPH_CHECK(igraph_i_attribute_gettype(graph, &nametype, IGRAPH_ATTRIBUTE_VERTEX, names)); } if (names && nametype != IGRAPH_ATTRIBUTE_NUMERIC && nametype != IGRAPH_ATTRIBUTE_STRING) { IGRAPH_WARNING("ignoring names attribute, unknown attribute type"); names = 0; } /* Check the weights as well */ if (weights && !igraph_i_attribute_has_attr(graph, IGRAPH_ATTRIBUTE_EDGE, weights)) { weights = 0; IGRAPH_WARNING("weights attribute does not exists"); } if (weights) { IGRAPH_CHECK(igraph_i_attribute_gettype(graph, &weighttype, IGRAPH_ATTRIBUTE_EDGE, weights)); } if (weights && weighttype != IGRAPH_ATTRIBUTE_NUMERIC) { IGRAPH_WARNING("ignoring weights attribute, unknown attribute type"); weights = 0; } if (names == 0 && weights == 0) { /* No names, no weights */ while (!IGRAPH_EIT_END(it)) { igraph_integer_t from, to; int ret; igraph_edge(graph, IGRAPH_EIT_GET(it), &from, &to); ret = fprintf(outstream, "%li %li\n", (long int) from, (long int) to); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } IGRAPH_EIT_NEXT(it); } } else if (weights == 0) { /* No weights, but use names */ igraph_strvector_t nvec; IGRAPH_CHECK(igraph_strvector_init(&nvec, igraph_vcount(graph))); IGRAPH_FINALLY(igraph_strvector_destroy, &nvec); IGRAPH_CHECK(igraph_i_attribute_get_string_vertex_attr(graph, names, igraph_vss_all(), &nvec)); while (!IGRAPH_EIT_END(it)) { igraph_integer_t edge = IGRAPH_EIT_GET(it); igraph_integer_t from, to; int ret = 0; char *str1, *str2; igraph_edge(graph, edge, &from, &to); igraph_strvector_get(&nvec, from, &str1); igraph_strvector_get(&nvec, to, &str2); ret = fprintf(outstream, "%s %s\n", str1, str2); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } IGRAPH_EIT_NEXT(it); } igraph_strvector_destroy(&nvec); IGRAPH_FINALLY_CLEAN(1); } else if (names == 0) { /* No names but weights */ igraph_vector_t wvec; IGRAPH_VECTOR_INIT_FINALLY(&wvec, igraph_ecount(graph)); IGRAPH_CHECK(igraph_i_attribute_get_numeric_edge_attr(graph, weights, igraph_ess_all(IGRAPH_EDGEORDER_ID), &wvec)); while (!IGRAPH_EIT_END(it)) { igraph_integer_t edge = IGRAPH_EIT_GET(it); igraph_integer_t from, to; int ret1, ret2, ret3; igraph_edge(graph, edge, &from, &to); ret1 = fprintf(outstream, "%li %li ", (long int)from, (long int)to); ret2 = igraph_real_fprintf_precise(outstream, VECTOR(wvec)[(long int)edge]); ret3 = fputc('\n', outstream); if (ret1 < 0 || ret2 < 0 || ret3 == EOF) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } IGRAPH_EIT_NEXT(it); } igraph_vector_destroy(&wvec); IGRAPH_FINALLY_CLEAN(1); } else { /* Both names and weights */ igraph_strvector_t nvec; igraph_vector_t wvec; IGRAPH_VECTOR_INIT_FINALLY(&wvec, igraph_ecount(graph)); IGRAPH_CHECK(igraph_strvector_init(&nvec, igraph_vcount(graph))); IGRAPH_FINALLY(igraph_strvector_destroy, &nvec); IGRAPH_CHECK(igraph_i_attribute_get_numeric_edge_attr(graph, weights, igraph_ess_all(IGRAPH_EDGEORDER_ID), &wvec)); IGRAPH_CHECK(igraph_i_attribute_get_string_vertex_attr(graph, names, igraph_vss_all(), &nvec)); while (!IGRAPH_EIT_END(it)) { igraph_integer_t edge = IGRAPH_EIT_GET(it); igraph_integer_t from, to; int ret = 0, ret2 = 0; char *str1, *str2; igraph_edge(graph, edge, &from, &to); igraph_strvector_get(&nvec, from, &str1); igraph_strvector_get(&nvec, to, &str2); ret = fprintf(outstream, "%s %s ", str1, str2); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } ret = igraph_real_fprintf_precise(outstream, VECTOR(wvec)[(long int)edge]); ret2 = fputc('\n', outstream); if (ret < 0 || ret2 == EOF) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } IGRAPH_EIT_NEXT(it); } igraph_strvector_destroy(&nvec); igraph_vector_destroy(&wvec); IGRAPH_FINALLY_CLEAN(2); } igraph_eit_destroy(&it); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \ingroup loadsave * \function igraph_write_graph_lgl * \brief Writes the graph to a file in .lgl format * * * .lgl is a format used by LGL, see \ref * igraph_read_graph_lgl() for details. * * * Note that having multiple or loop edges in an * .lgl file breaks the LGL software but \a igraph * does not check for this condition. * \param graph The graph to write. * \param outstream The stream object to write to, it should be * writable. * \param names The name of the vertex attribute, if symbolic names * are written to the file. If not supply 0 here. * \param weights The name of the edge attribute, if they are also * written to the file. If you don't want weights supply 0 * here. * \param isolates Logical, if TRUE isolated vertices are also written * to the file. If FALSE they will be omitted. * \return Error code: * \c IGRAPH_EFILE if there is an error * writing the file. * * Time complexity: O(|E|), the * number of edges if \p isolates is * FALSE, O(|V|+|E|) otherwise. All * file operations are expected to have time complexity * O(1). * * \sa \ref igraph_read_graph_lgl(), \ref igraph_write_graph_ncol() * * \example examples/simple/igraph_write_graph_lgl.c */ int igraph_write_graph_lgl(const igraph_t *graph, FILE *outstream, const char *names, const char *weights, igraph_bool_t isolates) { igraph_eit_t it; long int actvertex = -1; igraph_attribute_type_t nametype, weighttype; IGRAPH_CHECK(igraph_eit_create(graph, igraph_ess_all(IGRAPH_EDGEORDER_FROM), &it)); IGRAPH_FINALLY(igraph_eit_destroy, &it); /* Check if we have the names attribute */ if (names && !igraph_i_attribute_has_attr(graph, IGRAPH_ATTRIBUTE_VERTEX, names)) { names = 0; IGRAPH_WARNING("names attribute does not exists"); } if (names) { IGRAPH_CHECK(igraph_i_attribute_gettype(graph, &nametype, IGRAPH_ATTRIBUTE_VERTEX, names)); } if (names && nametype != IGRAPH_ATTRIBUTE_NUMERIC && nametype != IGRAPH_ATTRIBUTE_STRING) { IGRAPH_WARNING("ignoring names attribute, unknown attribute type"); names = 0; } /* Check the weights as well */ if (weights && !igraph_i_attribute_has_attr(graph, IGRAPH_ATTRIBUTE_EDGE, weights)) { weights = 0; IGRAPH_WARNING("weights attribute does not exists"); } if (weights) { IGRAPH_CHECK(igraph_i_attribute_gettype(graph, &weighttype, IGRAPH_ATTRIBUTE_EDGE, weights)); } if (weights && weighttype != IGRAPH_ATTRIBUTE_NUMERIC && weighttype != IGRAPH_ATTRIBUTE_STRING) { IGRAPH_WARNING("ignoring weights attribute, unknown attribute type"); weights = 0; } if (names == 0 && weights == 0) { /* No names, no weights */ while (!IGRAPH_EIT_END(it)) { igraph_integer_t from, to; int ret; igraph_edge(graph, IGRAPH_EIT_GET(it), &from, &to); if (from == actvertex) { ret = fprintf(outstream, "%li\n", (long int)to); } else { actvertex = from; ret = fprintf(outstream, "# %li\n%li\n", (long int)from, (long int)to); } if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } IGRAPH_EIT_NEXT(it); } } else if (weights == 0) { /* No weights but use names */ igraph_strvector_t nvec; IGRAPH_CHECK(igraph_strvector_init(&nvec, igraph_vcount(graph))); IGRAPH_FINALLY(igraph_strvector_destroy, &nvec); IGRAPH_CHECK(igraph_i_attribute_get_string_vertex_attr(graph, names, igraph_vss_all(), &nvec)); while (!IGRAPH_EIT_END(it)) { igraph_integer_t edge = IGRAPH_EIT_GET(it); igraph_integer_t from, to; int ret = 0; char *str1, *str2; igraph_edge(graph, edge, &from, &to); igraph_strvector_get(&nvec, to, &str2); if (from == actvertex) { ret = fprintf(outstream, "%s\n", str2); } else { actvertex = from; igraph_strvector_get(&nvec, from, &str1); ret = fprintf(outstream, "# %s\n%s\n", str1, str2); } if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } IGRAPH_EIT_NEXT(it); } IGRAPH_FINALLY_CLEAN(1); } else if (names == 0) { igraph_strvector_t wvec; IGRAPH_CHECK(igraph_strvector_init(&wvec, igraph_ecount(graph))); IGRAPH_FINALLY(igraph_strvector_destroy, &wvec); IGRAPH_CHECK(igraph_i_attribute_get_string_edge_attr(graph, weights, igraph_ess_all(IGRAPH_EDGEORDER_ID), &wvec)); /* No names but weights */ while (!IGRAPH_EIT_END(it)) { igraph_integer_t edge = IGRAPH_EIT_GET(it); igraph_integer_t from, to; int ret = 0; char *str1; igraph_edge(graph, edge, &from, &to); igraph_strvector_get(&wvec, edge, &str1); if (from == actvertex) { ret = fprintf(outstream, "%li %s\n", (long)to, str1); } else { actvertex = from; ret = fprintf(outstream, "# %li\n%li %s\n", (long)from, (long)to, str1); } if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } IGRAPH_EIT_NEXT(it); } igraph_strvector_destroy(&wvec); IGRAPH_FINALLY_CLEAN(1); } else { /* Both names and weights */ igraph_strvector_t nvec, wvec; IGRAPH_CHECK(igraph_strvector_init(&wvec, igraph_ecount(graph))); IGRAPH_FINALLY(igraph_strvector_destroy, &wvec); IGRAPH_CHECK(igraph_strvector_init(&nvec, igraph_vcount(graph))); IGRAPH_FINALLY(igraph_strvector_destroy, &nvec); IGRAPH_CHECK(igraph_i_attribute_get_string_edge_attr(graph, weights, igraph_ess_all(IGRAPH_EDGEORDER_ID), &wvec)); IGRAPH_CHECK(igraph_i_attribute_get_string_vertex_attr(graph, names, igraph_vss_all(), &nvec)); while (!IGRAPH_EIT_END(it)) { igraph_integer_t edge = IGRAPH_EIT_GET(it); igraph_integer_t from, to; int ret = 0; char *str1, *str2, *str3; igraph_edge(graph, edge, &from, &to); igraph_strvector_get(&nvec, to, &str2); igraph_strvector_get(&wvec, edge, &str3); if (from == actvertex) { ret = fprintf(outstream, "%s ", str2); } else { actvertex = from; igraph_strvector_get(&nvec, from, &str1); ret = fprintf(outstream, "# %s\n%s ", str1, str2); } if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } ret = fprintf(outstream, "%s\n", str3); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } IGRAPH_EIT_NEXT(it); } igraph_strvector_destroy(&nvec); igraph_strvector_destroy(&wvec); IGRAPH_FINALLY_CLEAN(2); } if (isolates) { long int nov = igraph_vcount(graph); long int i; int ret = 0; igraph_vector_t deg; igraph_strvector_t nvec; char *str; IGRAPH_VECTOR_INIT_FINALLY(°, 1); IGRAPH_CHECK(igraph_strvector_init(&nvec, 1)); IGRAPH_FINALLY(igraph_strvector_destroy, &nvec); for (i = 0; i < nov; i++) { igraph_degree(graph, °, igraph_vss_1((igraph_integer_t) i), IGRAPH_ALL, IGRAPH_LOOPS); if (VECTOR(deg)[0] == 0) { if (names == 0) { ret = fprintf(outstream, "# %li\n", i); } else { IGRAPH_CHECK(igraph_i_attribute_get_string_vertex_attr(graph, names, igraph_vss_1((igraph_integer_t) i), &nvec)); igraph_strvector_get(&nvec, 0, &str); ret = fprintf(outstream, "# %s\n", str); } } if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } } igraph_strvector_destroy(&nvec); igraph_vector_destroy(°); IGRAPH_FINALLY_CLEAN(2); } igraph_eit_destroy(&it); IGRAPH_FINALLY_CLEAN(1); return 0; } /* Order matters here! */ #define V_ID 0 #define V_X 1 #define V_Y 2 #define V_Z 3 #define V_SHAPE 4 #define V_XFACT 5 #define V_YFACT 6 #define V_COLOR_RED 7 #define V_COLOR_GREEN 8 #define V_COLOR_BLUE 9 #define V_FRAMECOLOR_RED 10 #define V_FRAMECOLOR_GREEN 11 #define V_FRAMECOLOR_BLUE 12 #define V_LABELCOLOR_RED 13 #define V_LABELCOLOR_GREEN 14 #define V_LABELCOLOR_BLUE 15 #define V_LABELDIST 16 #define V_LABELDEGREE2 17 #define V_FRAMEWIDTH 18 #define V_FONTSIZE 19 #define V_ROTATION 20 #define V_RADIUS 21 #define V_DIAMONDRATIO 22 #define V_LABELDEGREE 23 #define V_VERTEXSIZE 24 #define V_FONT 25 #define V_URL 26 #define V_COLOR 27 #define V_FRAMECOLOR 28 #define V_LABELCOLOR 29 #define V_LAST 30 #define E_WEIGHT 0 #define E_COLOR_RED 1 #define E_COLOR_GREEN 2 #define E_COLOR_BLUE 3 #define E_ARROWSIZE 4 #define E_EDGEWIDTH 5 #define E_HOOK1 6 #define E_HOOK2 7 #define E_ANGLE1 8 #define E_ANGLE2 9 #define E_VELOCITY1 10 #define E_VELOCITY2 11 #define E_ARROWPOS 12 #define E_LABELPOS 13 #define E_LABELANGLE 14 #define E_LABELANGLE2 15 #define E_LABELDEGREE 16 #define E_FONTSIZE 17 #define E_ARROWTYPE 18 #define E_LINEPATTERN 19 #define E_LABEL 20 #define E_LABELCOLOR 21 #define E_COLOR 22 #define E_LAST 23 int igraph_i_pajek_escape(char* src, char** dest) { long int destlen = 0; igraph_bool_t need_escape = 0; /* Determine whether the string contains characters to be escaped */ char *s, *d; for (s = src; *s; s++, destlen++) { if (*s == '\\') { need_escape = 1; destlen++; } else if (*s == '"') { need_escape = 1; destlen++; } else if (!isalnum(*s)) { need_escape = 1; } } if (!need_escape) { /* At this point, we know that the string does not contain any chars * that would warrant escaping. Therefore, we simply quote it and * return the quoted string. This is necessary because Pajek uses some * reserved words in its format (like 'c' standing for color) and they * have to be quoted as well. */ *dest = igraph_Calloc(destlen + 3, char); if (!*dest) { IGRAPH_ERROR("Not enough memory", IGRAPH_ENOMEM); } d = *dest; strcpy(d + 1, src); d[0] = d[destlen + 1] = '"'; d[destlen + 2] = 0; return IGRAPH_SUCCESS; } *dest = igraph_Calloc(destlen + 3, char); if (!*dest) { IGRAPH_ERROR("Not enough memory", IGRAPH_ENOMEM); } d = *dest; *d = '"'; d++; for (s = src; *s; s++, d++) { switch (*s) { case '\\': case '"': *d = '\\'; d++; default: *d = *s; } } *d = '"'; d++; *d = 0; return IGRAPH_SUCCESS; } /** * \function igraph_write_graph_pajek * \brief Writes a graph to a file in Pajek format. * * * The Pajek vertex and edge parameters (like color) are determined by * the attributes of the vertices and edges, of course this requires * an attribute handler to be installed. The names of the * corresponding vertex and edge attributes are listed at \ref * igraph_read_graph_pajek(), eg. the `\c color' vertex attributes * determines the color (`\c c' in Pajek) parameter. * * * As of version 0.6.1 igraph writes bipartite graphs into Pajek files * correctly, i.e. they will be also bipartite when read into Pajek. * As Pajek is less flexible for bipartite graphs (the numeric ids of * the vertices must be sorted according to vertex type), igraph might * need to reorder the vertices when writing a bipartite Pajek file. * This effectively means that numeric vertex ids usually change when * a bipartite graph is written to a Pajek file, and then read back * into igraph. * \param graph The graph object to write. * \param outstream The file to write to. It should be opened and * writable. Make sure that you open the file in binary format if you use MS Windows, * otherwise end of line characters will be messed up. (igraph will be able * to read back these messed up files, but Pajek won't.) * \return Error code. * * Time complexity: O(|V|+|E|+|A|), |V| is the number of vertices, |E| * is the number of edges, |A| the number of attributes (vertex + * edge) in the graph if there are attribute handlers installed. * * \sa \ref igraph_read_graph_pajek() for reading Pajek graphs, \ref * igraph_write_graph_graphml() for writing a graph in GraphML format, * this suites igraph graphs better. * * \example examples/simple/igraph_write_graph_pajek.c */ int igraph_write_graph_pajek(const igraph_t *graph, FILE *outstream) { long int no_of_nodes = igraph_vcount(graph); long int i, j; igraph_attribute_type_t vtypes[V_LAST], etypes[E_LAST]; igraph_bool_t write_vertex_attrs = 0; /* Same order as the #define's */ const char *vnames[] = { "id", "x", "y", "z", "shape", "xfact", "yfact", "", "", "", "", "", "", "", "", "", "labeldist", "labeldegree2", "framewidth", "fontsize", "rotation", "radius", "diamondratio", "labeldegree", "vertexsize", "font", "url", "color", "framecolor", "labelcolor" }; const char *vnumnames[] = { "xfact", "yfact", "labeldist", "labeldegree2", "framewidth", "fontsize", "rotation", "radius", "diamondratio", "labeldegree", "vertexsize" }; const char *vnumnames2[] = { "x_fact", "y_fact", "lr", "lphi", "bw", "fos", "phi", "r", "q", "la", "size" }; const char *vstrnames[] = { "font", "url", "color", "framecolor", "labelcolor" }; const char *vstrnames2[] = { "font", "url", "ic", "bc", "lc" }; const char *enames[] = { "weight", "", "", "", "arrowsize", "edgewidth", "hook1", "hook2", "angle1", "angle2", "velocity1", "velocity2", "arrowpos", "labelpos", "labelangle", "labelangle2", "labeldegree", "fontsize", "arrowtype", "linepattern", "label", "labelcolor", "color" }; const char *enumnames[] = { "arrowsize", "edgewidth", "hook1", "hook2", "angle1", "angle2", "velocity1", "velocity2", "arrowpos", "labelpos", "labelangle", "labelangle2", "labeldegree", "fontsize" }; const char *enumnames2[] = { "s", "w", "h1", "h2", "a1", "a2", "k1", "k2", "ap", "lp", "lr", "lphi", "la", "fos" }; const char *estrnames[] = { "arrowtype", "linepattern", "label", "labelcolor", "color" }; const char *estrnames2[] = { "a", "p", "l", "lc", "c" }; const char *newline = "\x0d\x0a"; igraph_es_t es; igraph_eit_t eit; igraph_vector_t numv; igraph_strvector_t strv; igraph_vector_t ex_numa; igraph_vector_t ex_stra; igraph_vector_t vx_numa; igraph_vector_t vx_stra; char *s, *escaped; igraph_bool_t bipartite = 0; igraph_vector_int_t bip_index, bip_index2; igraph_vector_bool_t bvec; long int notop = 0, nobottom = 0; IGRAPH_VECTOR_INIT_FINALLY(&numv, 1); IGRAPH_STRVECTOR_INIT_FINALLY(&strv, 1); IGRAPH_VECTOR_INIT_FINALLY(&ex_numa, 0); IGRAPH_VECTOR_INIT_FINALLY(&ex_stra, 0); IGRAPH_VECTOR_INIT_FINALLY(&vx_numa, 0); IGRAPH_VECTOR_INIT_FINALLY(&vx_stra, 0); /* Check if graph is bipartite */ if (igraph_i_attribute_has_attr(graph, IGRAPH_ATTRIBUTE_VERTEX, "type")) { igraph_attribute_type_t type_type; igraph_i_attribute_gettype(graph, &type_type, IGRAPH_ATTRIBUTE_VERTEX, "type"); if (type_type == IGRAPH_ATTRIBUTE_BOOLEAN) { int bptr = 0, tptr = 0; bipartite = 1; write_vertex_attrs = 1; /* Count top and bottom vertices, we go over them twice, because we want to keep their original order */ IGRAPH_CHECK(igraph_vector_int_init(&bip_index, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_int_destroy, &bip_index); IGRAPH_CHECK(igraph_vector_int_init(&bip_index2, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_int_destroy, &bip_index2); IGRAPH_CHECK(igraph_vector_bool_init(&bvec, 1)); IGRAPH_FINALLY(igraph_vector_bool_destroy, &bvec); for (i = 0; i < no_of_nodes; i++) { IGRAPH_CHECK(igraph_i_attribute_get_bool_vertex_attr(graph, "type", igraph_vss_1((igraph_integer_t) i), &bvec)); if (VECTOR(bvec)[0]) { notop++; } else { nobottom++; } } for (i = 0, bptr = 0, tptr = (int) nobottom; i < no_of_nodes; i++) { IGRAPH_CHECK(igraph_i_attribute_get_bool_vertex_attr(graph, "type", igraph_vss_1((igraph_integer_t) i), &bvec)); if (VECTOR(bvec)[0]) { VECTOR(bip_index)[tptr] = (int) i; VECTOR(bip_index2)[i] = tptr; tptr++; } else { VECTOR(bip_index)[bptr] = (int) i; VECTOR(bip_index2)[i] = bptr; bptr++; } } igraph_vector_bool_destroy(&bvec); IGRAPH_FINALLY_CLEAN(1); } } /* Write header */ if (bipartite) { if (fprintf(outstream, "*Vertices %li %li%s", no_of_nodes, nobottom, newline) < 0) { IGRAPH_ERROR("Cannot write pajek file", IGRAPH_EFILE); } } else { if (fprintf(outstream, "*Vertices %li%s", no_of_nodes, newline) < 0) { IGRAPH_ERROR("Cannot write pajek file", IGRAPH_EFILE); } } /* Check the vertex attributes */ memset(vtypes, 0, sizeof(vtypes[0])*V_LAST); for (i = 0; i < V_LAST; i++) { if (igraph_i_attribute_has_attr(graph, IGRAPH_ATTRIBUTE_VERTEX, vnames[i])) { igraph_i_attribute_gettype(graph, &vtypes[i], IGRAPH_ATTRIBUTE_VERTEX, vnames[i]); write_vertex_attrs = 1; } else { vtypes[i] = (igraph_attribute_type_t) -1; } } for (i = 0; i < (long int) (sizeof(vnumnames) / sizeof(const char*)); i++) { igraph_attribute_type_t type; if (igraph_i_attribute_has_attr(graph, IGRAPH_ATTRIBUTE_VERTEX, vnumnames[i])) { igraph_i_attribute_gettype(graph, &type, IGRAPH_ATTRIBUTE_VERTEX, vnumnames[i]); if (type == IGRAPH_ATTRIBUTE_NUMERIC) { IGRAPH_CHECK(igraph_vector_push_back(&vx_numa, i)); } } } for (i = 0; i < (long int) (sizeof(vstrnames) / sizeof(const char*)); i++) { igraph_attribute_type_t type; if (igraph_i_attribute_has_attr(graph, IGRAPH_ATTRIBUTE_VERTEX, vstrnames[i])) { igraph_i_attribute_gettype(graph, &type, IGRAPH_ATTRIBUTE_VERTEX, vstrnames[i]); if (type == IGRAPH_ATTRIBUTE_STRING) { IGRAPH_CHECK(igraph_vector_push_back(&vx_stra, i)); } } } /* Write vertices */ if (write_vertex_attrs) { for (i = 0; i < no_of_nodes; i++) { long int id = bipartite ? VECTOR(bip_index)[i] : i; /* vertex id */ fprintf(outstream, "%li", i + 1); if (vtypes[V_ID] == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_i_attribute_get_numeric_vertex_attr(graph, vnames[V_ID], igraph_vss_1((igraph_integer_t) id), &numv); fputs(" \"", outstream); igraph_real_fprintf_precise(outstream, VECTOR(numv)[0]); fputc('"', outstream); } else if (vtypes[V_ID] == IGRAPH_ATTRIBUTE_STRING) { igraph_i_attribute_get_string_vertex_attr(graph, vnames[V_ID], igraph_vss_1((igraph_integer_t) id), &strv); igraph_strvector_get(&strv, 0, &s); IGRAPH_CHECK(igraph_i_pajek_escape(s, &escaped)); fprintf(outstream, " %s", escaped); igraph_Free(escaped); } else { fprintf(outstream, " \"%li\"", id + 1); } /* coordinates */ if (vtypes[V_X] == IGRAPH_ATTRIBUTE_NUMERIC && vtypes[V_Y] == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_i_attribute_get_numeric_vertex_attr(graph, vnames[V_X], igraph_vss_1((igraph_integer_t) id), &numv); fputc(' ', outstream); igraph_real_fprintf_precise(outstream, VECTOR(numv)[0]); igraph_i_attribute_get_numeric_vertex_attr(graph, vnames[V_Y], igraph_vss_1((igraph_integer_t) id), &numv); fputc(' ', outstream); igraph_real_fprintf_precise(outstream, VECTOR(numv)[0]); if (vtypes[V_Z] == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_i_attribute_get_numeric_vertex_attr(graph, vnames[V_Z], igraph_vss_1((igraph_integer_t) id), &numv); fputc(' ', outstream); igraph_real_fprintf_precise(outstream, VECTOR(numv)[0]); } } /* shape */ if (vtypes[V_SHAPE] == IGRAPH_ATTRIBUTE_STRING) { igraph_i_attribute_get_string_vertex_attr(graph, vnames[V_SHAPE], igraph_vss_1((igraph_integer_t) id), &strv); igraph_strvector_get(&strv, 0, &s); IGRAPH_CHECK(igraph_i_pajek_escape(s, &escaped)); fprintf(outstream, " %s", escaped); igraph_Free(escaped); } /* numeric parameters */ for (j = 0; j < igraph_vector_size(&vx_numa); j++) { int idx = (int) VECTOR(vx_numa)[j]; igraph_i_attribute_get_numeric_vertex_attr(graph, vnumnames[idx], igraph_vss_1((igraph_integer_t) id), &numv); fprintf(outstream, " %s ", vnumnames2[idx]); igraph_real_fprintf_precise(outstream, VECTOR(numv)[0]); } /* string parameters */ for (j = 0; j < igraph_vector_size(&vx_stra); j++) { int idx = (int) VECTOR(vx_stra)[j]; igraph_i_attribute_get_string_vertex_attr(graph, vstrnames[idx], igraph_vss_1((igraph_integer_t) id), &strv); igraph_strvector_get(&strv, 0, &s); IGRAPH_CHECK(igraph_i_pajek_escape(s, &escaped)); fprintf(outstream, " %s %s", vstrnames2[idx], escaped); igraph_Free(escaped); } /* trailing newline */ fprintf(outstream, "%s", newline); } } /* edges header */ if (igraph_is_directed(graph)) { fprintf(outstream, "*Arcs%s", newline); } else { fprintf(outstream, "*Edges%s", newline); } IGRAPH_CHECK(igraph_es_all(&es, IGRAPH_EDGEORDER_ID)); IGRAPH_FINALLY(igraph_es_destroy, &es); IGRAPH_CHECK(igraph_eit_create(graph, es, &eit)); IGRAPH_FINALLY(igraph_eit_destroy, &eit); /* Check edge attributes */ for (i = 0; i < E_LAST; i++) { if (igraph_i_attribute_has_attr(graph, IGRAPH_ATTRIBUTE_EDGE, enames[i])) { igraph_i_attribute_gettype(graph, &etypes[i], IGRAPH_ATTRIBUTE_EDGE, enames[i]); } else { etypes[i] = (igraph_attribute_type_t) -1; } } for (i = 0; i < (long int) (sizeof(enumnames) / sizeof(const char*)); i++) { igraph_attribute_type_t type; if (igraph_i_attribute_has_attr(graph, IGRAPH_ATTRIBUTE_EDGE, enumnames[i])) { igraph_i_attribute_gettype(graph, &type, IGRAPH_ATTRIBUTE_EDGE, enumnames[i]); if (type == IGRAPH_ATTRIBUTE_NUMERIC) { IGRAPH_CHECK(igraph_vector_push_back(&ex_numa, i)); } } } for (i = 0; i < (long int) (sizeof(estrnames) / sizeof(const char*)); i++) { igraph_attribute_type_t type; if (igraph_i_attribute_has_attr(graph, IGRAPH_ATTRIBUTE_EDGE, estrnames[i])) { igraph_i_attribute_gettype(graph, &type, IGRAPH_ATTRIBUTE_EDGE, estrnames[i]); if (type == IGRAPH_ATTRIBUTE_STRING) { IGRAPH_CHECK(igraph_vector_push_back(&ex_stra, i)); } } } for (i = 0; !IGRAPH_EIT_END(eit); IGRAPH_EIT_NEXT(eit), i++) { long int edge = IGRAPH_EIT_GET(eit); igraph_integer_t from, to; igraph_edge(graph, (igraph_integer_t) edge, &from, &to); if (bipartite) { from = VECTOR(bip_index2)[from]; to = VECTOR(bip_index2)[to]; } fprintf(outstream, "%li %li", (long int) from + 1, (long int) to + 1); /* Weights */ if (etypes[E_WEIGHT] == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_i_attribute_get_numeric_edge_attr(graph, enames[E_WEIGHT], igraph_ess_1((igraph_integer_t) edge), &numv); fputc(' ', outstream); igraph_real_fprintf_precise(outstream, VECTOR(numv)[0]); } /* numeric parameters */ for (j = 0; j < igraph_vector_size(&ex_numa); j++) { int idx = (int) VECTOR(ex_numa)[j]; igraph_i_attribute_get_numeric_edge_attr(graph, enumnames[idx], igraph_ess_1((igraph_integer_t) edge), &numv); fprintf(outstream, " %s ", enumnames2[idx]); igraph_real_fprintf_precise(outstream, VECTOR(numv)[0]); } /* string parameters */ for (j = 0; j < igraph_vector_size(&ex_stra); j++) { int idx = (int) VECTOR(ex_stra)[j]; igraph_i_attribute_get_string_edge_attr(graph, estrnames[idx], igraph_ess_1((igraph_integer_t) edge), &strv); igraph_strvector_get(&strv, 0, &s); IGRAPH_CHECK(igraph_i_pajek_escape(s, &escaped)); fprintf(outstream, " %s %s", estrnames2[idx], escaped); igraph_Free(escaped); } /* trailing newline */ fprintf(outstream, "%s", newline); } igraph_eit_destroy(&eit); igraph_es_destroy(&es); IGRAPH_FINALLY_CLEAN(2); if (bipartite) { igraph_vector_int_destroy(&bip_index2); igraph_vector_int_destroy(&bip_index); IGRAPH_FINALLY_CLEAN(2); } igraph_vector_destroy(&ex_numa); igraph_vector_destroy(&ex_stra); igraph_vector_destroy(&vx_numa); igraph_vector_destroy(&vx_stra); igraph_strvector_destroy(&strv); igraph_vector_destroy(&numv); IGRAPH_FINALLY_CLEAN(6); return 0; } /** * \function igraph_write_graph_dimacs * \brief Write a graph in DIMACS format. * * This function writes a graph to an output stream in DIMACS format, * describing a maximum flow problem. * See ftp://dimacs.rutgers.edu/pub/netflow/general-info/ * * * This file format is discussed in the documentation of \ref * igraph_read_graph_dimacs(), see that for more information. * * \param graph The graph to write to the stream. * \param outstream The stream. * \param source Integer, the id of the source vertex for the maximum * flow. * \param target Integer, the id of the target vertex. * \param capacity Pointer to an initialized vector containing the * edge capacity values. * \return Error code. * * Time complexity: O(|E|), the number of edges in the graph. * * \sa igraph_read_graph_dimacs() */ int igraph_write_graph_dimacs(const igraph_t *graph, FILE *outstream, long int source, long int target, const igraph_vector_t *capacity) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_eit_t it; long int i = 0; int ret, ret1, ret2, ret3; if (igraph_vector_size(capacity) != no_of_edges) { IGRAPH_ERROR("invalid capacity vector length", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_eit_create(graph, igraph_ess_all(IGRAPH_EDGEORDER_ID), &it)); IGRAPH_FINALLY(igraph_eit_destroy, &it); ret = fprintf(outstream, "c created by igraph\np max %li %li\nn %li s\nn %li t\n", no_of_nodes, no_of_edges, source + 1, target + 1); if (ret < 0) { IGRAPH_ERROR("Write error", IGRAPH_EFILE); } while (!IGRAPH_EIT_END(it)) { igraph_integer_t from, to; igraph_real_t cap; igraph_edge(graph, IGRAPH_EIT_GET(it), &from, &to); cap = VECTOR(*capacity)[i++]; ret1 = fprintf(outstream, "a %li %li ", (long int) from + 1, (long int) to + 1); ret2 = igraph_real_fprintf_precise(outstream, cap); ret3 = fputc('\n', outstream); if (ret1 < 0 || ret2 < 0 || ret3 == EOF) { IGRAPH_ERROR("Write error", IGRAPH_EFILE); } IGRAPH_EIT_NEXT(it); } igraph_eit_destroy(&it); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_i_gml_convert_to_key(const char *orig, char **key) { int no = 1; char strno[50]; size_t i, len = strlen(orig), newlen = 0, plen = 0; /* do we need a prefix? */ if (len == 0 || !isalpha(orig[0])) { no++; snprintf(strno, sizeof(strno) - 1, "igraph"); plen = newlen = strlen(strno); } for (i = 0; i < len; i++) { if (isalnum(orig[i])) { newlen++; } } *key = igraph_Calloc(newlen + 1, char); if (! *key) { IGRAPH_ERROR("Writing GML file failed", IGRAPH_ENOMEM); } memcpy(*key, strno, plen * sizeof(char)); for (i = 0; i < len; i++) { if (isalnum(orig[i])) { (*key)[plen++] = orig[i]; } } (*key)[newlen] = '\0'; return 0; } #define CHECK(cmd) do { ret=cmd; if (ret<0) IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } while (0) /** * \function igraph_write_graph_gml * \brief Write the graph to a stream in GML format * * GML is a quite general textual format, see * http://www.fim.uni-passau.de/en/fim/faculty/chairs/theoretische-informatik/projects.html for details. * * The graph, vertex and edges attributes are written to the * file as well, if they are numeric or string. * * As igraph is more forgiving about attribute names, it might * be necessary to simplify the them before writing to the GML file. * This way we'll have a syntactically correct GML file. The following * simple procedure is performed on each attribute name: first the alphanumeric * characters are extracted, the others are ignored. Then if the first character * is not a letter then the attribute name is prefixed with igraph. * Note that this might result identical names for two attributes, igraph * does not check this. * * The id vertex attribute is treated specially. * If the id argument is not 0 then it should be a numeric * vector with the vertex ids and the id vertex attribute is * ignored (if there is one). If id is 0 and there is a * numeric id vertex attribute that is used instead. If ids * are not specified in either way then the regular igraph vertex ids are used. * * Note that whichever way vertex ids are specified, their * uniqueness is not checked. * * If the graph has edge attributes named source * or target they're silently ignored. GML uses these attributes * to specify the edges, so we cannot write them to the file. Rename them * before calling this function if you want to preserve them. * \param graph The graph to write to the stream. * \param outstream The stream to write the file to. * \param id Either NULL or a numeric vector with the vertex ids. * See details above. * \param creator An optional string to write to the stream in the creator line. * If this is 0 then the current date and time is added. * \return Error code. * * Time complexity: should be proportional to the number of characters written * to the file. * * \sa \ref igraph_read_graph_gml() for reading GML files, * \ref igraph_read_graph_graphml() for a more modern format. * * \example examples/simple/gml.c */ int igraph_write_graph_gml(const igraph_t *graph, FILE *outstream, const igraph_vector_t *id, const char *creator) { int ret; igraph_strvector_t gnames, vnames, enames; igraph_vector_t gtypes, vtypes, etypes; igraph_vector_t numv; igraph_strvector_t strv; igraph_vector_bool_t boolv; long int i; long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_vector_t v_myid; const igraph_vector_t *myid = id; time_t curtime = time(0); char *timestr = ctime(&curtime); timestr[strlen(timestr) - 1] = '\0'; /* nicely remove \n */ CHECK(fprintf(outstream, "Creator \"igraph version %s %s\"\nVersion 1\ngraph\n[\n", PACKAGE_VERSION, creator ? creator : timestr)); IGRAPH_STRVECTOR_INIT_FINALLY(&gnames, 0); IGRAPH_STRVECTOR_INIT_FINALLY(&vnames, 0); IGRAPH_STRVECTOR_INIT_FINALLY(&enames, 0); IGRAPH_VECTOR_INIT_FINALLY(>ypes, 0); IGRAPH_VECTOR_INIT_FINALLY(&vtypes, 0); IGRAPH_VECTOR_INIT_FINALLY(&etypes, 0); IGRAPH_CHECK(igraph_i_attribute_get_info(graph, &gnames, >ypes, &vnames, &vtypes, &enames, &etypes)); IGRAPH_VECTOR_INIT_FINALLY(&numv, 1); IGRAPH_STRVECTOR_INIT_FINALLY(&strv, 1); IGRAPH_VECTOR_BOOL_INIT_FINALLY(&boolv, 1); /* Check whether there is an 'id' node attribute if the supplied is 0 */ if (!id) { igraph_bool_t found = 0; for (i = 0; i < igraph_vector_size(&vtypes); i++) { char *n; igraph_strvector_get(&vnames, i, &n); if (!strcmp(n, "id") && VECTOR(vtypes)[i] == IGRAPH_ATTRIBUTE_NUMERIC) { found = 1; break; } } if (found) { IGRAPH_VECTOR_INIT_FINALLY(&v_myid, no_of_nodes); IGRAPH_CHECK(igraph_i_attribute_get_numeric_vertex_attr(graph, "id", igraph_vss_all(), &v_myid)); myid = &v_myid; } } /* directedness */ CHECK(fprintf(outstream, " directed %i\n", igraph_is_directed(graph) ? 1 : 0)); /* Graph attributes first */ for (i = 0; i < igraph_vector_size(>ypes); i++) { char *name, *newname; igraph_strvector_get(&gnames, i, &name); IGRAPH_CHECK(igraph_i_gml_convert_to_key(name, &newname)); if (VECTOR(gtypes)[i] == IGRAPH_ATTRIBUTE_NUMERIC) { IGRAPH_CHECK(igraph_i_attribute_get_numeric_graph_attr(graph, name, &numv)); CHECK(fprintf(outstream, " %s ", newname)); CHECK(igraph_real_fprintf_precise(outstream, VECTOR(numv)[0])); CHECK(fputc('\n', outstream)); } else if (VECTOR(gtypes)[i] == IGRAPH_ATTRIBUTE_STRING) { char *s; IGRAPH_CHECK(igraph_i_attribute_get_string_graph_attr(graph, name, &strv)); igraph_strvector_get(&strv, 0, &s); CHECK(fprintf(outstream, " %s \"%s\"\n", newname, s)); } else if (VECTOR(gtypes)[i] == IGRAPH_ATTRIBUTE_BOOLEAN) { IGRAPH_CHECK(igraph_i_attribute_get_bool_graph_attr(graph, name, &boolv)); CHECK(fprintf(outstream, " %s %d\n", newname, VECTOR(boolv)[0] ? 1 : 0)); IGRAPH_WARNING("A boolean graph attribute was converted to numeric"); } else { IGRAPH_WARNING("A non-numeric, non-string, non-boolean graph attribute ignored"); } igraph_Free(newname); } /* Now come the vertices */ for (i = 0; i < no_of_nodes; i++) { long int j; CHECK(fprintf(outstream, " node\n [\n")); /* id */ CHECK(fprintf(outstream, " id %li\n", myid ? (long int)VECTOR(*myid)[i] : i)); /* other attributes */ for (j = 0; j < igraph_vector_size(&vtypes); j++) { int type = (int) VECTOR(vtypes)[j]; char *name, *newname; igraph_strvector_get(&vnames, j, &name); if (!strcmp(name, "id")) { continue; } IGRAPH_CHECK(igraph_i_gml_convert_to_key(name, &newname)); if (type == IGRAPH_ATTRIBUTE_NUMERIC) { IGRAPH_CHECK(igraph_i_attribute_get_numeric_vertex_attr(graph, name, igraph_vss_1((igraph_integer_t) i), &numv)); CHECK(fprintf(outstream, " %s ", newname)); CHECK(igraph_real_fprintf_precise(outstream, VECTOR(numv)[0])); CHECK(fputc('\n', outstream)); } else if (type == IGRAPH_ATTRIBUTE_STRING) { char *s; IGRAPH_CHECK(igraph_i_attribute_get_string_vertex_attr(graph, name, igraph_vss_1((igraph_integer_t) i), &strv)); igraph_strvector_get(&strv, 0, &s); CHECK(fprintf(outstream, " %s \"%s\"\n", newname, s)); } else if (type == IGRAPH_ATTRIBUTE_BOOLEAN) { IGRAPH_CHECK(igraph_i_attribute_get_bool_vertex_attr(graph, name, igraph_vss_1((igraph_integer_t) i), &boolv)); CHECK(fprintf(outstream, " %s %d\n", newname, VECTOR(boolv)[0] ? 1 : 0)); IGRAPH_WARNING("A boolean vertex attribute was converted to numeric"); } else { IGRAPH_WARNING("A non-numeric, non-string, non-boolean edge attribute was ignored"); } igraph_Free(newname); } CHECK(fprintf(outstream, " ]\n")); } /* The edges too */ for (i = 0; i < no_of_edges; i++) { long int from = IGRAPH_FROM(graph, i); long int to = IGRAPH_TO(graph, i); long int j; CHECK(fprintf(outstream, " edge\n [\n")); /* source and target */ CHECK(fprintf(outstream, " source %li\n", myid ? (long int)VECTOR(*myid)[from] : from)); CHECK(fprintf(outstream, " target %li\n", myid ? (long int)VECTOR(*myid)[to] : to)); /* other attributes */ for (j = 0; j < igraph_vector_size(&etypes); j++) { int type = (int) VECTOR(etypes)[j]; char *name, *newname; igraph_strvector_get(&enames, j, &name); if (!strcmp(name, "source") || !strcmp(name, "target")) { continue; } IGRAPH_CHECK(igraph_i_gml_convert_to_key(name, &newname)); if (type == IGRAPH_ATTRIBUTE_NUMERIC) { IGRAPH_CHECK(igraph_i_attribute_get_numeric_edge_attr(graph, name, igraph_ess_1((igraph_integer_t) i), &numv)); CHECK(fprintf(outstream, " %s ", newname)); CHECK(igraph_real_fprintf_precise(outstream, VECTOR(numv)[0])); CHECK(fputc('\n', outstream)); } else if (type == IGRAPH_ATTRIBUTE_STRING) { char *s; IGRAPH_CHECK(igraph_i_attribute_get_string_edge_attr(graph, name, igraph_ess_1((igraph_integer_t) i), &strv)); igraph_strvector_get(&strv, 0, &s); CHECK(fprintf(outstream, " %s \"%s\"\n", newname, s)); } else if (type == IGRAPH_ATTRIBUTE_BOOLEAN) { IGRAPH_CHECK(igraph_i_attribute_get_bool_edge_attr(graph, name, igraph_ess_1((igraph_integer_t) i), &boolv)); CHECK(fprintf(outstream, " %s %d\n", newname, VECTOR(boolv)[0] ? 1 : 0)); IGRAPH_WARNING("A boolean edge attribute was converted to numeric"); } else { IGRAPH_WARNING("A non-numeric, non-string, non-boolean edge attribute was ignored"); } igraph_Free(newname); } CHECK(fprintf(outstream, " ]\n")); } CHECK(fprintf(outstream, "]\n")); if (&v_myid == myid) { igraph_vector_destroy(&v_myid); IGRAPH_FINALLY_CLEAN(1); } igraph_vector_bool_destroy(&boolv); igraph_strvector_destroy(&strv); igraph_vector_destroy(&numv); igraph_vector_destroy(&etypes); igraph_vector_destroy(&vtypes); igraph_vector_destroy(>ypes); igraph_strvector_destroy(&enames); igraph_strvector_destroy(&vnames); igraph_strvector_destroy(&gnames); IGRAPH_FINALLY_CLEAN(9); return 0; } int igraph_i_dot_escape(const char *orig, char **result) { /* do we have to escape the string at all? */ long int i, j, len = (long int) strlen(orig), newlen = 0; igraph_bool_t need_quote = 0, is_number = 1; /* first, check whether the string is equal to some reserved word */ if (!strcasecmp(orig, "graph") || !strcasecmp(orig, "digraph") || !strcasecmp(orig, "node") || !strcasecmp(orig, "edge") || !strcasecmp(orig, "strict") || !strcasecmp(orig, "subgraph")) { need_quote = 1; is_number = 0; } /* next, check whether we need to escape the string for any other reason. * Also update is_number and newlen */ for (i = 0; i < len; i++) { if (isdigit(orig[i])) { newlen++; } else if (orig[i] == '-' && i == 0) { newlen++; } else if (orig[i] == '.') { if (is_number) { newlen++; } else { need_quote = 1; newlen++; } } else if (orig[i] == '_') { is_number = 0; newlen++; } else if (orig[i] == '\\' || orig[i] == '"' || orig[i] == '\n') { need_quote = 1; is_number = 0; newlen += 2; /* will be escaped */ } else if (isalpha(orig[i])) { is_number = 0; newlen++; } else { is_number = 0; need_quote = 1; newlen++; } } if (is_number && orig[len - 1] == '.') { is_number = 0; } if (!is_number && isdigit(orig[0])) { need_quote = 1; } if (is_number || !need_quote) { *result = strdup(orig); if (!*result) { IGRAPH_ERROR("Writing DOT file failed", IGRAPH_ENOMEM); } } else { *result = igraph_Calloc(newlen + 3, char); (*result)[0] = '"'; (*result)[newlen + 1] = '"'; (*result)[newlen + 2] = '\0'; for (i = 0, j = 1; i < len; i++) { if (orig[i] == '\n') { (*result)[j++] = '\\'; (*result)[j++] = 'n'; continue; } if (orig[i] == '\\' || orig[i] == '"') { (*result)[j++] = '\\'; } (*result)[j++] = orig[i]; } } return 0; } /** * \function igraph_write_graph_dot * \brief Write the graph to a stream in DOT format * * DOT is the format used by the widely known GraphViz software, see * http://www.graphviz.org for details. The grammar of the DOT format * can be found here: http://www.graphviz.org/doc/info/lang.html * * This is only a preliminary implementation, only the vertices * and the edges are written but not the attributes or any visualization * information. * * \param graph The graph to write to the stream. * \param outstream The stream to write the file to. * * Time complexity: should be proportional to the number of characters written * to the file. * * \sa \ref igraph_write_graph_graphml() for a more modern format. * * \example examples/simple/dot.c */ int igraph_write_graph_dot(const igraph_t *graph, FILE* outstream) { int ret; long int i, j; long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); char edgeop[3]; igraph_strvector_t gnames, vnames, enames; igraph_vector_t gtypes, vtypes, etypes; igraph_vector_t numv; igraph_strvector_t strv; igraph_vector_bool_t boolv; IGRAPH_STRVECTOR_INIT_FINALLY(&gnames, 0); IGRAPH_STRVECTOR_INIT_FINALLY(&vnames, 0); IGRAPH_STRVECTOR_INIT_FINALLY(&enames, 0); IGRAPH_VECTOR_INIT_FINALLY(>ypes, 0); IGRAPH_VECTOR_INIT_FINALLY(&vtypes, 0); IGRAPH_VECTOR_INIT_FINALLY(&etypes, 0); IGRAPH_CHECK(igraph_i_attribute_get_info(graph, &gnames, >ypes, &vnames, &vtypes, &enames, &etypes)); IGRAPH_VECTOR_INIT_FINALLY(&numv, 1); IGRAPH_STRVECTOR_INIT_FINALLY(&strv, 1); IGRAPH_VECTOR_BOOL_INIT_FINALLY(&boolv, 1); CHECK(fprintf(outstream, "/* Created by igraph %s */\n", PACKAGE_VERSION)); if (igraph_is_directed(graph)) { CHECK(fprintf(outstream, "digraph {\n")); strcpy(edgeop, "->"); } else { CHECK(fprintf(outstream, "graph {\n")); strcpy(edgeop, "--"); } /* Write the graph attributes */ if (igraph_vector_size(>ypes) > 0) { CHECK(fprintf(outstream, " graph [\n")); for (i = 0; i < igraph_vector_size(>ypes); i++) { char *name, *newname; igraph_strvector_get(&gnames, i, &name); IGRAPH_CHECK(igraph_i_dot_escape(name, &newname)); if (VECTOR(gtypes)[i] == IGRAPH_ATTRIBUTE_NUMERIC) { IGRAPH_CHECK(igraph_i_attribute_get_numeric_graph_attr(graph, name, &numv)); if (VECTOR(numv)[0] == (long)VECTOR(numv)[0]) { CHECK(fprintf(outstream, " %s=%ld\n", newname, (long)VECTOR(numv)[0])); } else { CHECK(fprintf(outstream, " %s=", newname)); CHECK(igraph_real_fprintf_precise(outstream, VECTOR(numv)[0])); CHECK(fputc('\n', outstream)); } } else if (VECTOR(gtypes)[i] == IGRAPH_ATTRIBUTE_STRING) { char *s, *news; IGRAPH_CHECK(igraph_i_attribute_get_string_graph_attr(graph, name, &strv)); igraph_strvector_get(&strv, 0, &s); IGRAPH_CHECK(igraph_i_dot_escape(s, &news)); CHECK(fprintf(outstream, " %s=%s\n", newname, news)); igraph_Free(news); } else if (VECTOR(gtypes)[i] == IGRAPH_ATTRIBUTE_BOOLEAN) { IGRAPH_CHECK(igraph_i_attribute_get_bool_graph_attr(graph, name, &boolv)); CHECK(fprintf(outstream, " %s=%d\n", newname, VECTOR(boolv)[0] ? 1 : 0)); IGRAPH_WARNING("A boolean graph attribute was converted to numeric"); } else { IGRAPH_WARNING("A non-numeric, non-string, non-boolean graph attribute ignored"); } igraph_Free(newname); } CHECK(fprintf(outstream, " ];\n")); } /* Write the vertices */ if (igraph_vector_size(&vtypes) > 0) { for (i = 0; i < no_of_nodes; i++) { CHECK(fprintf(outstream, " %ld [\n", i)); for (j = 0; j < igraph_vector_size(&vtypes); j++) { char *name, *newname; igraph_strvector_get(&vnames, j, &name); IGRAPH_CHECK(igraph_i_dot_escape(name, &newname)); if (VECTOR(vtypes)[j] == IGRAPH_ATTRIBUTE_NUMERIC) { IGRAPH_CHECK(igraph_i_attribute_get_numeric_vertex_attr(graph, name, igraph_vss_1((igraph_integer_t) i), &numv)); if (VECTOR(numv)[0] == (long)VECTOR(numv)[0]) { CHECK(fprintf(outstream, " %s=%ld\n", newname, (long)VECTOR(numv)[0])); } else { CHECK(fprintf(outstream, " %s=", newname)); CHECK(igraph_real_fprintf_precise(outstream, VECTOR(numv)[0])); CHECK(fputc('\n', outstream)); } } else if (VECTOR(vtypes)[j] == IGRAPH_ATTRIBUTE_STRING) { char *s, *news; IGRAPH_CHECK(igraph_i_attribute_get_string_vertex_attr(graph, name, igraph_vss_1((igraph_integer_t) i), &strv)); igraph_strvector_get(&strv, 0, &s); IGRAPH_CHECK(igraph_i_dot_escape(s, &news)); CHECK(fprintf(outstream, " %s=%s\n", newname, news)); igraph_Free(news); } else if (VECTOR(vtypes)[j] == IGRAPH_ATTRIBUTE_BOOLEAN) { IGRAPH_CHECK(igraph_i_attribute_get_bool_vertex_attr(graph, name, igraph_vss_1((igraph_integer_t) i), &boolv)); CHECK(fprintf(outstream, " %s=%d\n", newname, VECTOR(boolv)[0] ? 1 : 0)); IGRAPH_WARNING("A boolean vertex attribute was converted to numeric"); } else { IGRAPH_WARNING("A non-numeric, non-string, non-boolean vertex attribute was ignored"); } igraph_Free(newname); } CHECK(fprintf(outstream, " ];\n")); } } else { for (i = 0; i < no_of_nodes; i++) { CHECK(fprintf(outstream, " %ld;\n", i)); } } CHECK(fprintf(outstream, "\n")); /* Write the edges */ if (igraph_vector_size(&etypes) > 0) { for (i = 0; i < no_of_edges; i++) { long int from = IGRAPH_FROM(graph, i); long int to = IGRAPH_TO(graph, i); CHECK(fprintf(outstream, " %ld %s %ld [\n", from, edgeop, to)); for (j = 0; j < igraph_vector_size(&etypes); j++) { char *name, *newname; igraph_strvector_get(&enames, j, &name); IGRAPH_CHECK(igraph_i_dot_escape(name, &newname)); if (VECTOR(etypes)[j] == IGRAPH_ATTRIBUTE_NUMERIC) { IGRAPH_CHECK(igraph_i_attribute_get_numeric_edge_attr(graph, name, igraph_ess_1((igraph_integer_t) i), &numv)); if (VECTOR(numv)[0] == (long)VECTOR(numv)[0]) { CHECK(fprintf(outstream, " %s=%ld\n", newname, (long)VECTOR(numv)[0])); } else { CHECK(fprintf(outstream, " %s=", newname)); CHECK(igraph_real_fprintf_precise(outstream, VECTOR(numv)[0])); CHECK(fputc('\n', outstream)); } igraph_Free(newname); } else if (VECTOR(etypes)[j] == IGRAPH_ATTRIBUTE_STRING) { char *s, *news; IGRAPH_CHECK(igraph_i_attribute_get_string_edge_attr(graph, name, igraph_ess_1((igraph_integer_t) i), &strv)); igraph_strvector_get(&strv, 0, &s); IGRAPH_CHECK(igraph_i_dot_escape(s, &news)); CHECK(fprintf(outstream, " %s=%s\n", newname, news)); igraph_Free(newname); igraph_Free(news); } else if (VECTOR(etypes)[j] == IGRAPH_ATTRIBUTE_BOOLEAN) { IGRAPH_CHECK(igraph_i_attribute_get_bool_edge_attr(graph, name, igraph_ess_1((igraph_integer_t) i), &boolv)); CHECK(fprintf(outstream, " %s=%d\n", newname, VECTOR(boolv)[0] ? 1 : 0)); IGRAPH_WARNING("A boolean edge attribute was converted to numeric"); } else { IGRAPH_WARNING("A non-numeric, non-string graph attribute ignored"); } } CHECK(fprintf(outstream, " ];\n")); } } else { for (i = 0; i < no_of_edges; i++) { long int from = IGRAPH_FROM(graph, i); long int to = IGRAPH_TO(graph, i); CHECK(fprintf(outstream, " %ld %s %ld;\n", from, edgeop, to)); } } CHECK(fprintf(outstream, "}\n")); igraph_vector_bool_destroy(&boolv); igraph_strvector_destroy(&strv); igraph_vector_destroy(&numv); igraph_vector_destroy(&etypes); igraph_vector_destroy(&vtypes); igraph_vector_destroy(>ypes); igraph_strvector_destroy(&enames); igraph_strvector_destroy(&vnames); igraph_strvector_destroy(&gnames); IGRAPH_FINALLY_CLEAN(9); return 0; } #include "foreign-dl-header.h" int igraph_dl_yylex_init_extra (igraph_i_dl_parsedata_t* user_defined, void* scanner); int igraph_dl_yylex_destroy (void *scanner ); int igraph_dl_yyparse (igraph_i_dl_parsedata_t* context); void igraph_dl_yyset_in (FILE * in_str, void* yyscanner ); /** * \function igraph_read_graph_dl * \brief Read a file in the DL format of UCINET * * This is a simple textual file format used by UCINET. See * http://www.analytictech.com/networks/dataentry.htm for * examples. All the forms described here are supported by * igraph. Vertex names and edge weights are also supported and they * are added as attributes. (If an attribute handler is attached.) * * Note the specification does not mention whether the * format is case sensitive or not. For igraph DL files are case * sensitive, i.e. \c Larry and \c larry are not the same. * \param graph Pointer to an uninitialized graph object. * \param instream The stream to read the DL file from. * \param directed Logical scalar, whether to create a directed file. * \return Error code. * * Time complexity: linear in terms of the number of edges and * vertices, except for the matrix format, which is quadratic in the * number of vertices. * * \example examples/simple/igraph_read_graph_dl.c */ int igraph_read_graph_dl(igraph_t *graph, FILE *instream, igraph_bool_t directed) { int i; long int n, n2; const igraph_strvector_t *namevec = 0; igraph_vector_ptr_t name, weight; igraph_vector_ptr_t *pname = 0, *pweight = 0; igraph_attribute_record_t namerec, weightrec; const char *namestr = "name", *weightstr = "weight"; igraph_i_dl_parsedata_t context; context.eof = 0; context.mode = 0; context.n = -1; context.from = 0; context.to = 0; IGRAPH_VECTOR_INIT_FINALLY(&context.edges, 0); IGRAPH_VECTOR_INIT_FINALLY(&context.weights, 0); IGRAPH_CHECK(igraph_strvector_init(&context.labels, 0)); IGRAPH_FINALLY(igraph_strvector_destroy, &context.labels); IGRAPH_TRIE_INIT_FINALLY(&context.trie, /*names=*/ 1); igraph_dl_yylex_init_extra(&context, &context.scanner); IGRAPH_FINALLY(igraph_dl_yylex_destroy, context.scanner); igraph_dl_yyset_in(instream, context.scanner); i = igraph_dl_yyparse(&context); if (i != 0) { if (context.errmsg[0] != 0) { IGRAPH_ERROR(context.errmsg, IGRAPH_PARSEERROR); } else { IGRAPH_ERROR("Cannot read DL file", IGRAPH_PARSEERROR); } } /* Extend the weight vector, if needed */ n = igraph_vector_size(&context.weights); n2 = igraph_vector_size(&context.edges) / 2; if (n != 0) { igraph_vector_resize(&context.weights, n2); for (; n < n2; n++) { VECTOR(context.weights)[n] = IGRAPH_NAN; } } /* Check number of vertices */ if (n2 > 0) { n = (long int) igraph_vector_max(&context.edges); } else { n = 0; } if (n >= context.n) { IGRAPH_WARNING("More vertices than specified in `DL' file"); context.n = n; } /* OK, everything is ready, create the graph */ IGRAPH_CHECK(igraph_empty(graph, 0, directed)); IGRAPH_FINALLY(igraph_destroy, graph); /* Labels */ if (igraph_strvector_size(&context.labels) != 0) { namevec = (const igraph_strvector_t*) &context.labels; } else if (igraph_trie_size(&context.trie) != 0) { igraph_trie_getkeys(&context.trie, &namevec); } if (namevec) { IGRAPH_CHECK(igraph_vector_ptr_init(&name, 1)); IGRAPH_FINALLY(igraph_vector_ptr_destroy, &name); pname = &name; namerec.name = namestr; namerec.type = IGRAPH_ATTRIBUTE_STRING; namerec.value = namevec; VECTOR(name)[0] = &namerec; } /* Weights */ if (igraph_vector_size(&context.weights) != 0) { IGRAPH_CHECK(igraph_vector_ptr_init(&weight, 1)); IGRAPH_FINALLY(igraph_vector_ptr_destroy, &weight); pweight = &weight; weightrec.name = weightstr; weightrec.type = IGRAPH_ATTRIBUTE_NUMERIC; weightrec.value = &context.weights; VECTOR(weight)[0] = &weightrec; } IGRAPH_CHECK(igraph_add_vertices(graph, (igraph_integer_t) context.n, pname)); IGRAPH_CHECK(igraph_add_edges(graph, &context.edges, pweight)); if (pweight) { igraph_vector_ptr_destroy(pweight); IGRAPH_FINALLY_CLEAN(1); } if (pname) { igraph_vector_ptr_destroy(pname); IGRAPH_FINALLY_CLEAN(1); } /* don't destroy the graph itself but pop it from the finally stack */ IGRAPH_FINALLY_CLEAN(1); igraph_trie_destroy(&context.trie); igraph_strvector_destroy(&context.labels); igraph_vector_destroy(&context.edges); igraph_vector_destroy(&context.weights); igraph_dl_yylex_destroy(context.scanner); IGRAPH_FINALLY_CLEAN(5); return 0; } /** * \function igraph_write_graph_leda * \brief Write a graph in LEDA native graph format. * * This function writes a graph to an output stream in LEDA format. * See http://www.algorithmic-solutions.info/leda_guide/graphs/leda_native_graph_fileformat.html * * * The support for the LEDA format is very basic at the moment; igraph * writes only the LEDA graph section which supports one selected vertex * and edge attribute and no layout information or visual attributes. * * \param graph The graph to write to the stream. * \param outstream The stream. * \param vertex_attr_name The name of the vertex attribute whose values * are to be stored in the output or \c NULL if no * vertex attribute has to be stored. * \param edge_attr_name The name of the edge attribute whose values * are to be stored in the output or \c NULL if no * edge attribute has to be stored. * \return Error code. * * Time complexity: O(|V|+|E|), the number of vertices and edges in the * graph. * * \example examples/simple/igraph_write_graph_leda.c */ int igraph_write_graph_leda(const igraph_t *graph, FILE *outstream, const char* vertex_attr_name, const char* edge_attr_name) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_eit_t it; long int i = 0; int ret; igraph_attribute_type_t vertex_attr_type = IGRAPH_ATTRIBUTE_DEFAULT; igraph_attribute_type_t edge_attr_type = IGRAPH_ATTRIBUTE_DEFAULT; igraph_integer_t from, to, rev; IGRAPH_CHECK(igraph_eit_create(graph, igraph_ess_all(IGRAPH_EDGEORDER_FROM), &it)); IGRAPH_FINALLY(igraph_eit_destroy, &it); /* Check if we have the vertex attribute */ if (vertex_attr_name && !igraph_i_attribute_has_attr(graph, IGRAPH_ATTRIBUTE_VERTEX, vertex_attr_name)) { vertex_attr_name = 0; IGRAPH_WARNING("specified vertex attribute does not exist"); } if (vertex_attr_name) { IGRAPH_CHECK(igraph_i_attribute_gettype(graph, &vertex_attr_type, IGRAPH_ATTRIBUTE_VERTEX, vertex_attr_name)); if (vertex_attr_type != IGRAPH_ATTRIBUTE_NUMERIC && vertex_attr_type != IGRAPH_ATTRIBUTE_STRING) { vertex_attr_name = 0; vertex_attr_type = IGRAPH_ATTRIBUTE_DEFAULT; IGRAPH_WARNING("specified vertex attribute must be numeric or string"); } } /* Check if we have the edge attribute */ if (edge_attr_name && !igraph_i_attribute_has_attr(graph, IGRAPH_ATTRIBUTE_EDGE, edge_attr_name)) { edge_attr_name = 0; IGRAPH_WARNING("specified edge attribute does not exist"); } if (edge_attr_name) { IGRAPH_CHECK(igraph_i_attribute_gettype(graph, &edge_attr_type, IGRAPH_ATTRIBUTE_EDGE, edge_attr_name)); if (edge_attr_type != IGRAPH_ATTRIBUTE_NUMERIC && edge_attr_type != IGRAPH_ATTRIBUTE_STRING) { edge_attr_name = 0; edge_attr_type = IGRAPH_ATTRIBUTE_DEFAULT; IGRAPH_WARNING("specified edge attribute must be numeric or string"); } } /* Start writing header */ CHECK(fprintf(outstream, "LEDA.GRAPH\n")); switch (vertex_attr_type) { case IGRAPH_ATTRIBUTE_NUMERIC: CHECK(fprintf(outstream, "float\n")); break; case IGRAPH_ATTRIBUTE_STRING: CHECK(fprintf(outstream, "string\n")); break; default: CHECK(fprintf(outstream, "void\n")); } switch (edge_attr_type) { case IGRAPH_ATTRIBUTE_NUMERIC: CHECK(fprintf(outstream, "float\n")); break; case IGRAPH_ATTRIBUTE_STRING: CHECK(fprintf(outstream, "string\n")); break; default: CHECK(fprintf(outstream, "void\n")); } CHECK(fprintf(outstream, "%d\n", (igraph_is_directed(graph) ? -1 : -2))); /* Start writing vertices */ CHECK(fprintf(outstream, "# Vertices\n")); CHECK(fprintf(outstream, "%ld\n", no_of_nodes)); if (vertex_attr_type == IGRAPH_ATTRIBUTE_NUMERIC) { /* Vertices with numeric attributes */ igraph_vector_t values; IGRAPH_VECTOR_INIT_FINALLY(&values, no_of_nodes); IGRAPH_CHECK(igraph_i_attribute_get_numeric_vertex_attr( graph, vertex_attr_name, igraph_vss_all(), &values)); for (i = 0; i < no_of_nodes; i++) { CHECK(fprintf(outstream, "|{")); CHECK(igraph_real_fprintf_precise(outstream, VECTOR(values)[i])); CHECK(fprintf(outstream, "}|\n")); } igraph_vector_destroy(&values); IGRAPH_FINALLY_CLEAN(1); } else if (vertex_attr_type == IGRAPH_ATTRIBUTE_STRING) { /* Vertices with string attributes */ igraph_strvector_t values; IGRAPH_CHECK(igraph_strvector_init(&values, no_of_nodes)); IGRAPH_FINALLY(igraph_strvector_destroy, &values); IGRAPH_CHECK(igraph_i_attribute_get_string_vertex_attr( graph, vertex_attr_name, igraph_vss_all(), &values)); for (i = 0; i < no_of_nodes; i++) { const char* str = STR(values, i); if (strchr(str, '\n') != 0) { IGRAPH_ERROR("edge attribute values cannot contain newline characters", IGRAPH_EINVAL); } CHECK(fprintf(outstream, "|{%s}|\n", str)); } igraph_strvector_destroy(&values); IGRAPH_FINALLY_CLEAN(1); } else { /* Vertices with no attributes */ for (i = 0; i < no_of_nodes; i++) { CHECK(fprintf(outstream, "|{}|\n")); } } CHECK(fprintf(outstream, "# Edges\n")); CHECK(fprintf(outstream, "%ld\n", no_of_edges)); if (edge_attr_type == IGRAPH_ATTRIBUTE_NUMERIC) { /* Edges with numeric attributes */ igraph_vector_t values; IGRAPH_VECTOR_INIT_FINALLY(&values, no_of_nodes); IGRAPH_CHECK(igraph_i_attribute_get_numeric_edge_attr( graph, edge_attr_name, igraph_ess_all(IGRAPH_EDGEORDER_ID), &values)); while (!IGRAPH_EIT_END(it)) { long int eid = IGRAPH_EIT_GET(it); igraph_edge(graph, (igraph_integer_t) eid, &from, &to); igraph_get_eid(graph, &rev, to, from, 1, 0); if (rev == IGRAPH_EIT_GET(it)) { rev = -1; } CHECK(fprintf(outstream, "%ld %ld %ld |{", (long int) from + 1, (long int) to + 1, (long int) rev + 1)); CHECK(igraph_real_fprintf_precise(outstream, VECTOR(values)[eid])); CHECK(fprintf(outstream, "}|\n")); IGRAPH_EIT_NEXT(it); } igraph_vector_destroy(&values); IGRAPH_FINALLY_CLEAN(1); } else if (edge_attr_type == IGRAPH_ATTRIBUTE_STRING) { /* Edges with string attributes */ igraph_strvector_t values; IGRAPH_CHECK(igraph_strvector_init(&values, no_of_nodes)); IGRAPH_FINALLY(igraph_strvector_destroy, &values); IGRAPH_CHECK(igraph_i_attribute_get_string_edge_attr( graph, edge_attr_name, igraph_ess_all(IGRAPH_EDGEORDER_ID), &values)); while (!IGRAPH_EIT_END(it)) { long int eid = IGRAPH_EIT_GET(it); const char* str = STR(values, eid); igraph_edge(graph, (igraph_integer_t) eid, &from, &to); igraph_get_eid(graph, &rev, to, from, 1, 0); if (rev == IGRAPH_EIT_GET(it)) { rev = -1; } if (strchr(str, '\n') != 0) { IGRAPH_ERROR("edge attribute values cannot contain newline characters", IGRAPH_EINVAL); } CHECK(fprintf(outstream, "%ld %ld %ld |{%s}|\n", (long int) from + 1, (long int) to + 1, (long int) rev + 1, str)); IGRAPH_EIT_NEXT(it); } igraph_strvector_destroy(&values); IGRAPH_FINALLY_CLEAN(1); } else { /* Edges with no attributes */ while (!IGRAPH_EIT_END(it)) { igraph_edge(graph, IGRAPH_EIT_GET(it), &from, &to); igraph_get_eid(graph, &rev, to, from, 1, 0); if (rev == IGRAPH_EIT_GET(it)) { rev = -1; } CHECK(fprintf(outstream, "%ld %ld %ld |{}|\n", (long int) from + 1, (long int) to + 1, (long int) rev + 1)); IGRAPH_EIT_NEXT(it); } } igraph_eit_destroy(&it); IGRAPH_FINALLY_CLEAN(1); return 0; } #undef CHECK python-igraph-0.8.0/vendor/source/igraph/src/gengraph_header.h0000644000076500000240000000610213614300625024651 0ustar tamasstaff00000000000000/* * * gengraph - generation of random simple connected graphs with prescribed * degree sequence * * Copyright (C) 2006 Fabien Viger * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #include "gengraph_definitions.h" #include #include #include "gengraph_random.h" namespace gengraph { static KW_RNG::RNG _my_random; int my_random() { return _my_random.rand_int31(); } void my_srandom(int x) { _my_random.init(x, !x * 13, x * x + 1, (x >> 16) + (x << 16)); } int my_binomial(double pp, int n) { return _my_random.binomial(pp, n); } double my_random01() { return _my_random.rand_halfopen01(); } } #ifdef _WIN32 #include #include void set_priority_low() { HANDLE hProcess = OpenProcess(PROCESS_ALL_ACCESS, TRUE, _getpid()); SetPriorityClass(hProcess, IDLE_PRIORITY_CLASS); } #else #include #endif namespace gengraph { static int VERB; int VERBOSE() { return VERB; } void SET_VERBOSE(int v) { VERB = v; } //Hash profiling static unsigned long _hash_rm_i = 0; static unsigned long _hash_rm_c = 0; static unsigned long _hash_add_i = 0; static unsigned long _hash_add_c = 0; static unsigned long _hash_put_i = 0; static unsigned long _hash_put_c = 0; static unsigned long _hash_find_i = 0; static unsigned long _hash_find_c = 0; static unsigned long _hash_rand_i = 0; static unsigned long _hash_rand_c = 0; static unsigned long _hash_expand = 0; inline void _hash_add_iter() { _hash_add_i++; } inline void _hash_add_call() { _hash_add_c++; } inline void _hash_put_iter() { _hash_put_i++; } inline void _hash_put_call() { _hash_put_c++; } inline void _hash_rm_iter() { _hash_rm_i++; } inline void _hash_rm_call() { _hash_rm_c++; } inline void _hash_find_iter() { _hash_find_i++; } inline void _hash_find_call() { _hash_find_c++; } inline void _hash_rand_iter() { _hash_rand_i++; } inline void _hash_rand_call() { _hash_rand_c++; } inline void _hash_expand_call() { _hash_expand++; } // void _hash_prof() { // fprintf(stderr,"HASH_ADD : %lu / %lu\n", _hash_add_c , _hash_add_i); // fprintf(stderr,"HASH_PUT : %lu / %lu\n", _hash_put_c , _hash_put_i); // fprintf(stderr,"HASH_FIND: %lu / %lu\n", _hash_find_c, _hash_find_i); // fprintf(stderr,"HASH_RM : %lu / %lu\n", _hash_rm_c , _hash_rm_i); // fprintf(stderr,"HASH_RAND: %lu / %lu\n", _hash_rand_c, _hash_rand_i); // fprintf(stderr,"HASH_EXPAND : %lu calls\n", _hash_expand); // } } // namespace gengraph python-igraph-0.8.0/vendor/source/igraph/src/infomap.cc0000644000076500000240000002734313614300625023347 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA ---- The original version of this file was written by Martin Rosvall email: martin.rosvall@physics.umu.se homePage: http://www.tp.umu.se/~rosvall/ It was integrated in igraph by Emmanuel Navarro email: navarro@irit.fr homePage: http://www.irit.fr/~Emmanuel.Navarro/ */ #include #include "igraph_interface.h" #include "igraph_community.h" #include "igraph_interrupt_internal.h" #include "infomap_Node.h" #include "infomap_Greedy.h" /****************************************************************************/ int infomap_partition(FlowGraph * fgraph, bool rcall) { Greedy * greedy; // save the original graph FlowGraph * cpy_fgraph = new FlowGraph(fgraph); IGRAPH_FINALLY(delete_FlowGraph, cpy_fgraph); int Nnode = cpy_fgraph->Nnode; // "real" number of vertex, ie. number of vertex of the graph int iteration = 0; double outer_oldCodeLength, newCodeLength; int *initial_move = NULL; bool initial_move_done = true; do { // Main loop outer_oldCodeLength = fgraph->codeLength; if (iteration > 0) { /**********************************************************************/ // FIRST PART: re-split the network (if need) // =========================================== // intial_move indicate current clustering initial_move = new int[Nnode]; // new_cluster_id --> old_cluster_id (save curent clustering state) IGRAPH_FINALLY(operator delete [], initial_move); initial_move_done = false; int *subMoveTo = NULL; // enventual new partitionment of original graph if ((iteration % 2 == 0) && (fgraph->Nnode > 1)) { // 0/ Submodule movements : partition each module of the // current partition (rec. call) subMoveTo = new int[Nnode]; // vid_cpy_fgraph --> new_cluster_id (new partition) IGRAPH_FINALLY(operator delete [], subMoveTo); int subModIndex = 0; for (int i = 0 ; i < fgraph->Nnode ; i++) { // partition each non trivial module int sub_Nnode = fgraph->node[i]->members.size(); if (sub_Nnode > 1) { // If the module is not trivial int *sub_members = new int[sub_Nnode]; // id_sub --> id IGRAPH_FINALLY(operator delete [], sub_members); for (int j = 0 ; j < sub_Nnode ; j++) { sub_members[j] = fgraph->node[i]->members[j]; } // extraction of the subgraph FlowGraph *sub_fgraph = new FlowGraph(cpy_fgraph, sub_Nnode, sub_members); IGRAPH_FINALLY(delete_FlowGraph, sub_fgraph); sub_fgraph->initiate(); // recursif call of partitionment on the subgraph infomap_partition(sub_fgraph, true); // Record membership changes for (int j = 0; j < sub_fgraph->Nnode; j++) { int Nmembers = sub_fgraph->node[j]->members.size(); for (int k = 0; k < Nmembers; k++) { subMoveTo[sub_members[sub_fgraph->node[j]->members[k]]] = subModIndex; } initial_move[subModIndex] = i; subModIndex++; } delete sub_fgraph; IGRAPH_FINALLY_CLEAN(1); delete [] sub_members; IGRAPH_FINALLY_CLEAN(1); } else { subMoveTo[fgraph->node[i]->members[0]] = subModIndex; initial_move[subModIndex] = i; subModIndex++; } } } else { // 1/ Single-node movements : allows each node to move (again) // save current modules for (int i = 0; i < fgraph->Nnode; i++) { // for each module int Nmembers = fgraph->node[i]->members.size(); // Module size for (int j = 0; j < Nmembers; j++) { // for each vertex (of the module) initial_move[fgraph->node[i]->members[j]] = i; } } } fgraph->back_to(cpy_fgraph); if (subMoveTo) { Greedy *cpy_greedy = new Greedy(fgraph); IGRAPH_FINALLY(delete_Greedy, cpy_greedy); cpy_greedy->setMove(subMoveTo); cpy_greedy->apply(false); delete_Greedy(cpy_greedy); IGRAPH_FINALLY_CLEAN(1); delete [] subMoveTo; IGRAPH_FINALLY_CLEAN(1); } } /**********************************************************************/ // SECOND PART: greedy optimizing it self // =========================================== double oldCodeLength; do { // greedy optimizing object creation greedy = new Greedy(fgraph); IGRAPH_FINALLY(delete_Greedy, greedy); // Initial move to apply ? if (!initial_move_done && initial_move) { initial_move_done = true; greedy->setMove(initial_move); } oldCodeLength = greedy->codeLength; bool moved = true; int Nloops = 0; //int count = 0; double inner_oldCodeLength = 1000; while (moved) { // main greedy optimizing loop inner_oldCodeLength = greedy->codeLength; moved = greedy->optimize(); Nloops++; //count++; if (fabs(greedy->codeLength - inner_oldCodeLength) < 1.0e-10) // if the move does'n reduce the codelenght -> exit ! { moved = false; } //if (count == 10) { // greedy->tune(); // count = 0; //} } // transform the network to network of modules: greedy->apply(true); newCodeLength = greedy->codeLength; // destroy greedy object delete greedy; IGRAPH_FINALLY_CLEAN(1); } while (oldCodeLength - newCodeLength > 1.0e-10); // while there is some improvement if (iteration > 0) { delete [] initial_move; IGRAPH_FINALLY_CLEAN(1); } iteration++; if (!rcall) { IGRAPH_ALLOW_INTERRUPTION(); } } while (outer_oldCodeLength - newCodeLength > 1.0e-10); delete cpy_fgraph; IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } /** * \function igraph_community_infomap * \brief Find community structure that minimizes the expected * description length of a random walker trajectory. * * Implementation of the InfoMap community detection algorithm.of * Martin Rosvall and Carl T. Bergstrom. * * See : * Visualization of the math and the map generator: www.mapequation.org * [2] The original paper: M. Rosvall and C. T. Bergstrom, Maps of * information flow reveal community structure in complex networks, PNAS * 105, 1118 (2008) [http://dx.doi.org/10.1073/pnas.0706851105 , * http://arxiv.org/abs/0707.0609 ] * [3] A more detailed paper: M. Rosvall, D. Axelsson, and C. T. Bergstrom, * The map equation, Eur. Phys. J. Special Topics 178, 13 (2009). * [http://dx.doi.org/10.1140/epjst/e2010-01179-1 , * http://arxiv.org/abs/0906.1405 ] * * The original C++ implementation of Martin Rosvall is used, * see http://www.tp.umu.se/~rosvall/downloads/infomap_undir.tgz . * Intergation in igraph has be done by Emmanuel Navarro (who is grateful to * Martin Rosvall and Carl T. Bergstrom for providing this source code.) * * * Note that the graph must not contain isolated vertices. * * * If you want to specify a random seed (as in original * implementation) you can use \ref igraph_rng_seed(). * * \param graph The input graph. * \param e_weights Numeric vector giving the weights of the edges. * If it is a NULL pointer then all edges will have equal * weights. The weights are expected to be positive. * \param v_weights Numeric vector giving the weights of the vertices. * If it is a NULL pointer then all vertices will have equal * weights. The weights are expected to be positive. * \param nb_trials The number of attempts to partition the network * (can be any integer value equal or larger than 1). * \param membership Pointer to a vector. The membership vector is * stored here. * \param codelength Pointer to a real. If not NULL the code length of the * partition is stored here. * \return Error code. * * \sa \ref igraph_community_spinglass(), \ref * igraph_community_edge_betweenness(), \ref igraph_community_walktrap(). * * Time complexity: TODO. */ int igraph_community_infomap(const igraph_t * graph, const igraph_vector_t *e_weights, const igraph_vector_t *v_weights, int nb_trials, igraph_vector_t *membership, igraph_real_t *codelength) { FlowGraph * fgraph = new FlowGraph(graph, e_weights, v_weights); IGRAPH_FINALLY(delete_FlowGraph, fgraph); // compute stationary distribution fgraph->initiate(); FlowGraph * cpy_fgraph ; double shortestCodeLength = 1000.0; // create membership vector int Nnode = fgraph->Nnode; IGRAPH_CHECK(igraph_vector_resize(membership, Nnode)); for (int trial = 0; trial < nb_trials; trial++) { cpy_fgraph = new FlowGraph(fgraph); IGRAPH_FINALLY(delete_FlowGraph, cpy_fgraph); //partition the network IGRAPH_CHECK(infomap_partition(cpy_fgraph, false)); // if better than the better... if (cpy_fgraph->codeLength < shortestCodeLength) { shortestCodeLength = cpy_fgraph->codeLength; // ... store the partition for (int i = 0 ; i < cpy_fgraph->Nnode ; i++) { int Nmembers = cpy_fgraph->node[i]->members.size(); for (int k = 0; k < Nmembers; k++) { //cluster[ cpy_fgraph->node[i]->members[k] ] = i; VECTOR(*membership)[cpy_fgraph->node[i]->members[k]] = i; } } } delete_FlowGraph(cpy_fgraph); IGRAPH_FINALLY_CLEAN(1); } *codelength = (igraph_real_t) shortestCodeLength / log(2.0); delete fgraph; IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } python-igraph-0.8.0/vendor/source/igraph/src/igraph_gml_tree.h0000644000076500000240000000653713614300625024712 0ustar tamasstaff00000000000000/* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef REST_GML_TREE_H #define REST_GML_TREE_H #undef __BEGIN_DECLS #undef __END_DECLS #ifdef __cplusplus #define __BEGIN_DECLS extern "C" { #define __END_DECLS } #else #define __BEGIN_DECLS /* empty */ #define __END_DECLS /* empty */ #endif #include "igraph_types.h" #include "igraph_vector.h" #include "igraph_vector_ptr.h" __BEGIN_DECLS typedef enum { IGRAPH_I_GML_TREE_TREE = 0, IGRAPH_I_GML_TREE_INTEGER, IGRAPH_I_GML_TREE_REAL, IGRAPH_I_GML_TREE_STRING, IGRAPH_I_GML_TREE_DELETED } igraph_i_gml_tree_type_t; typedef struct igraph_gml_tree_t { igraph_vector_ptr_t names; igraph_vector_char_t types; igraph_vector_ptr_t children; } igraph_gml_tree_t; int igraph_gml_tree_init_integer(igraph_gml_tree_t *t, const char *name, int namelen, igraph_integer_t value); int igraph_gml_tree_init_real(igraph_gml_tree_t *t, const char *name, int namelen, igraph_real_t value); int igraph_gml_tree_init_string(igraph_gml_tree_t *t, const char *name, int namelen, const char *value, int valuelen); int igraph_gml_tree_init_tree(igraph_gml_tree_t *t, const char *name, int namelen, igraph_gml_tree_t *value); void igraph_gml_tree_destroy(igraph_gml_tree_t *t); void igraph_gml_tree_delete(igraph_gml_tree_t *t, long int pos); int igraph_gml_tree_mergedest(igraph_gml_tree_t *t1, igraph_gml_tree_t *t2); long int igraph_gml_tree_length(const igraph_gml_tree_t *t); long int igraph_gml_tree_find(const igraph_gml_tree_t *t, const char *name, long int from); long int igraph_gml_tree_findback(const igraph_gml_tree_t *t, const char *name, long int from); int igraph_gml_tree_type(const igraph_gml_tree_t *t, long int pos); const char *igraph_gml_tree_name(const igraph_gml_tree_t *t, long int pos); igraph_integer_t igraph_gml_tree_get_integer(const igraph_gml_tree_t *t, long int pos); igraph_real_t igraph_gml_tree_get_real(const igraph_gml_tree_t *t, long int pos); const char *igraph_gml_tree_get_string(const igraph_gml_tree_t *t, long int pos); igraph_gml_tree_t *igraph_gml_tree_get_tree(const igraph_gml_tree_t *t, long int pos); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/src/igraph_hrg.cc0000644000076500000240000010323313614300625024021 0ustar tamasstaff00000000000000/* -*- mode: C++ -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_interface.h" #include "igraph_community.h" #include "igraph_memory.h" #include "igraph_constructors.h" #include "igraph_attributes.h" #include "igraph_foreign.h" #include "igraph_hrg.h" #include "igraph_random.h" #include "hrg_dendro.h" #include "hrg_graph.h" #include "hrg_graph_simp.h" using namespace fitHRG; /** * \section hrg_intro Introduction * * A hierarchical random graph is an ensemble of undirected * graphs with \c n vertices. It is defined via a binary tree with \c * n leaf and \c n-1 internal vertices, where the * internal vertices are labeled with probabilities. * The probability that two vertices are connected in the random graph * is given by the probability label at their closest common * ancestor. * * * Please read the following two articles for more about * hierarchical random graphs: A. Clauset, C. Moore, and M.E.J. Newman. * Hierarchical structure and the prediction of missing links in networks. * Nature 453, 98 - 101 (2008); and A. Clauset, C. Moore, and M.E.J. Newman. * Structural Inference of Hierarchies in Networks. In E. M. Airoldi * et al. (Eds.): ICML 2006 Ws, Lecture Notes in Computer Science * 4503, 1-13. Springer-Verlag, Berlin Heidelberg (2007). * * * * igraph contains functions for fitting HRG models to a given network * (\ref igraph_hrg_fit), for generating networks from a given HRG * ensemble (\ref igraph_hrg_game, \ref igraph_hrg_sample), converting * an igraph graph to a HRG and back (\ref igraph_hrg_create, \ref * igraph_hrg_dendrogram), for calculating a consensus tree from a * set of sampled HRGs (\ref igraph_hrg_consensus) and for predicting * missing edges in a network based on its HRG models (\ref * igraph_hrg_predict). * * * The igraph HRG implementation is heavily based on the code * published by Aaron Clauset, at his website, * http://tuvalu.santafe.edu/~aaronc/hierarchy/ * */ namespace fitHRG { struct pblock { double L; int i; int j; }; } int markovChainMonteCarlo(dendro *d, unsigned int period, igraph_hrg_t *hrg) { igraph_real_t bestL = d->getLikelihood(); double dL; bool flag_taken; // Because moves in the dendrogram space are chosen (Monte // Carlo) so that we sample dendrograms with probability // proportional to their likelihood, a likelihood-proportional // sampling of the dendrogram models would be equivalent to a // uniform sampling of the walk itself. We would still have to // decide how often to sample the walk (at most once every n // steps is recommended) but for simplicity, the code here // simply runs the MCMC itself. To actually compute something // over the set of sampled dendrogram models (in a Bayesian // model averaging sense), you'll need to code that yourself. // do 'period' MCMC moves before doing anything else for (unsigned int i = 0; i < period; i++) { // make a MCMC move IGRAPH_CHECK(! d->monteCarloMove(dL, flag_taken, 1.0)); // get likelihood of this D given G igraph_real_t cl = d->getLikelihood(); if (cl > bestL) { // store the current best likelihood bestL = cl; // record the HRG structure d->recordDendrogramStructure(hrg); } } // corrects floating-point errors O(n) d->refreshLikelihood(); return 0; } int markovChainMonteCarlo2(dendro *d, int num_samples) { bool flag_taken; double dL, ptest = 1.0 / (50.0 * (double)(d->g->numNodes())); int sample_num = 0, t = 1, thresh = 200 * d->g->numNodes(); // Since we're sampling uniformly at random over the equilibrium // walk, we just need to do a bunch of MCMC moves and let the // sampling happen on its own. while (sample_num < num_samples) { // Make a single MCMC move d->monteCarloMove(dL, flag_taken, 1.0); // We sample the dendrogram space once every n MCMC moves (on // average). Depending on the flags on the command line, we sample // different aspects of the dendrograph structure. if (t > thresh && RNG_UNIF01() < ptest) { sample_num++; d->sampleSplitLikelihoods(sample_num); } t++; // correct floating-point errors O(n) d->refreshLikelihood(); // TODO: less frequently } return 0; } int MCMCEquilibrium_Find(dendro *d, igraph_hrg_t *hrg) { // We want to run the MCMC until we've found equilibrium; we // use the heuristic of the average log-likelihood (which is // exactly the entropy) over X steps being very close to the // average log-likelihood (entropy) over the X steps that // preceded those. In other words, we look for an apparent // local convergence of the entropy measure of the MCMC. bool flag_taken; igraph_real_t dL, Likeli; igraph_real_t oldMeanL; igraph_real_t newMeanL = -1e-49; while (1) { oldMeanL = newMeanL; newMeanL = 0.0; for (int i = 0; i < 65536; i++) { IGRAPH_CHECK(! d->monteCarloMove(dL, flag_taken, 1.0)); Likeli = d->getLikelihood(); newMeanL += Likeli; } // corrects floating-point errors O(n) d->refreshLikelihood(); if (fabs(newMeanL - oldMeanL) / 65536.0 < 1.0) { break; } } // Record the result if (hrg) { d->recordDendrogramStructure(hrg); } return 0; } int igraph_i_hrg_getgraph(const igraph_t *igraph, dendro *d) { int no_of_nodes = igraph_vcount(igraph); int no_of_edges = igraph_ecount(igraph); int i; // Create graph d->g = new graph(no_of_nodes); // Add edges for (i = 0; i < no_of_edges; i++) { int from = IGRAPH_FROM(igraph, i); int to = IGRAPH_TO(igraph, i); if (from == to) { continue; } if (!d->g->doesLinkExist(from, to)) { d->g->addLink(from, to); } if (!d->g->doesLinkExist(to, from)) { d->g->addLink(to, from); } } d->buildDendrogram(); return 0; } int igraph_i_hrg_getsimplegraph(const igraph_t *igraph, dendro *d, simpleGraph **sg, int num_bins) { int no_of_nodes = igraph_vcount(igraph); int no_of_edges = igraph_ecount(igraph); int i; // Create graphs d->g = new graph(no_of_nodes, true); d->g->setAdjacencyHistograms(num_bins); (*sg) = new simpleGraph(no_of_nodes); for (i = 0; i < no_of_edges; i++) { int from = IGRAPH_FROM(igraph, i); int to = IGRAPH_TO(igraph, i); if (from == to) { continue; } if (!d->g->doesLinkExist(from, to)) { d->g->addLink(from, to); } if (!d->g->doesLinkExist(to, from)) { d->g->addLink(to, from); } if (!(*sg)->doesLinkExist(from, to)) { (*sg)->addLink(from, to); } if (!(*sg)->doesLinkExist(to, from)) { (*sg)->addLink(to, from); } } d->buildDendrogram(); return 0; } /** * \function igraph_hrg_init * Allocate memory for a HRG. * * This function must be called before passing an \ref igraph_hrg_t to * an igraph function. * \param hrg Pointer to the HRG data structure to initialize. * \param n The number of vertices in the graph that is modeled by * this HRG. It can be zero, if this is not yet known. * \return Error code. * * Time complexity: O(n), the number of vertices in the graph. */ int igraph_hrg_init(igraph_hrg_t *hrg, int n) { IGRAPH_VECTOR_INIT_FINALLY(&hrg->left, n - 1); IGRAPH_VECTOR_INIT_FINALLY(&hrg->right, n - 1); IGRAPH_VECTOR_INIT_FINALLY(&hrg->prob, n - 1); IGRAPH_VECTOR_INIT_FINALLY(&hrg->edges, n - 1); IGRAPH_VECTOR_INIT_FINALLY(&hrg->vertices, n - 1); IGRAPH_FINALLY_CLEAN(5); return 0; } /** * \function igraph_hrg_destroy * Deallocate memory for an HRG. * * The HRG data structure can be reinitialized again with an \ref * igraph_hrg_destroy call. * \param hrg Pointer to the HRG data structure to deallocate. * * Time complexity: operating system dependent. */ void igraph_hrg_destroy(igraph_hrg_t *hrg) { igraph_vector_destroy(&hrg->left); igraph_vector_destroy(&hrg->right); igraph_vector_destroy(&hrg->prob); igraph_vector_destroy(&hrg->edges); igraph_vector_destroy(&hrg->vertices); } /** * \function igraph_hrg_size * Returns the size of the HRG, the number of leaf nodes. * * \param hrg Pointer to the HRG. * \return The number of leaf nodes in the HRG. * * Time complexity: O(1). */ int igraph_hrg_size(const igraph_hrg_t *hrg) { return igraph_vector_size(&hrg->left) + 1; } /** * \function igraph_hrg_resize * Resize a HRG. * * \param hrg Pointer to an initialized (see \ref igraph_hrg_init) * HRG. * \param newsize The new size, i.e. the number of leaf nodes. * \return Error code. * * Time complexity: O(n), n is the new size. */ int igraph_hrg_resize(igraph_hrg_t *hrg, int newsize) { int origsize = igraph_hrg_size(hrg); int ret = 0; igraph_error_handler_t *oldhandler = igraph_set_error_handler(igraph_error_handler_ignore); ret = igraph_vector_resize(&hrg->left, newsize - 1); ret |= igraph_vector_resize(&hrg->right, newsize - 1); ret |= igraph_vector_resize(&hrg->prob, newsize - 1); ret |= igraph_vector_resize(&hrg->edges, newsize - 1); ret |= igraph_vector_resize(&hrg->vertices, newsize - 1); igraph_set_error_handler(oldhandler); if (ret) { igraph_vector_resize(&hrg->left, origsize); igraph_vector_resize(&hrg->right, origsize); igraph_vector_resize(&hrg->prob, origsize); igraph_vector_resize(&hrg->edges, origsize); igraph_vector_resize(&hrg->vertices, origsize); IGRAPH_ERROR("Cannot resize HRG", ret); } return 0; } /** * \function igraph_hrg_fit * Fit a hierarchical random graph model to a network * * \param graph The igraph graph to fit the model to. Edge directions * are ignored in directed graphs. * \param hrg Pointer to an initialized HRG, the result of the fitting * is stored here. It can also be used to pass a HRG to the * function, that can be used as the starting point of the Markov * Chain Monte Carlo fitting, if the \c start argument is true. * \param start Logical, whether to start the fitting from the given * HRG. * \param steps Integer, the number of MCMC steps to take in the * fitting procedure. If this is zero, then the fitting stop is a * convergence criteria is fulfilled. * \return Error code. * * Time complexity: TODO. */ int igraph_hrg_fit(const igraph_t *graph, igraph_hrg_t *hrg, igraph_bool_t start, int steps) { int no_of_nodes = igraph_vcount(graph); dendro *d; RNG_BEGIN(); d = new dendro; // If we want to start from HRG if (start) { d->clearDendrograph(); if (igraph_hrg_size(hrg) != no_of_nodes) { delete d; IGRAPH_ERROR("Invalid HRG to start from", IGRAPH_EINVAL); } // Convert the igraph graph IGRAPH_CHECK(igraph_i_hrg_getgraph(graph, d)); d->importDendrogramStructure(hrg); } else { // Convert the igraph graph IGRAPH_CHECK(igraph_i_hrg_getgraph(graph, d)); IGRAPH_CHECK(igraph_hrg_resize(hrg, no_of_nodes)); } // Run fixed number of steps, or until convergence if (steps > 0) { IGRAPH_CHECK(markovChainMonteCarlo(d, steps, hrg)); } else { IGRAPH_CHECK(MCMCEquilibrium_Find(d, hrg)); } delete d; RNG_END(); return 0; } /** * \function igraph_hrg_sample * Sample from a hierarchical random graph model * * Sample from a hierarchical random graph ensemble. The ensemble can * be given as a graph (\c input_graph), or as a HRG object (\c hrg). * If a graph is given, then first an MCMC optimization is performed * to find the optimal fitting model; then the MCMC is used to sample * the graph(s). * \param input_graph An igraph graph, or a null pointer. If not a * null pointer, then a HRG is first fitted to the graph, possibly * starting from the given HRG, if the \c start argument is true. If * is is a null pointer, then the given HRG is used as a starting * point, to find the optimum of the Markov chain, before the * sampling. * \param sample Pointer to an uninitialized graph, or a null * pointer. If only one sample is requested, and it is not a null * pointer, then the sample is stored here. * \param samples An initialized vector of pointers. If more than one * samples are requested, then they are stored here. Note that to * free this data structure, you need to call \ref igraph_destroy on * each graph first, then \c free() on all pointers, and finally * \ref igraph_vector_ptr_destroy. * \param no_samples The number of samples to generate. * \param hrg A HRG. It is modified during the sampling. * \param start Logical, whether to start the MCMC from the given * HRG. * \return Error code. * * Time complexity: TODO. */ int igraph_hrg_sample(const igraph_t *input_graph, igraph_t *sample, igraph_vector_ptr_t *samples, int no_samples, igraph_hrg_t *hrg, igraph_bool_t start) { int i; dendro *d; if (no_samples < 0) { IGRAPH_ERROR("Number of samples must be non-negative", IGRAPH_EINVAL); } if (!sample && !samples) { IGRAPH_ERROR("Give at least one of `sample' and `samples'", IGRAPH_EINVAL); } if (no_samples != 1 && sample) { IGRAPH_ERROR("Number of samples should be one if `sample' is given", IGRAPH_EINVAL); } if (no_samples > 1 && !samples) { IGRAPH_ERROR("`samples' must be non-null if number of samples " "is larger than 1", IGRAPH_EINVAL); } if (!start && !input_graph) { IGRAPH_ERROR("Input graph must be given if initial HRG is not used", IGRAPH_EINVAL); } if (!start) { IGRAPH_CHECK(igraph_hrg_resize(hrg, igraph_vcount(input_graph))); } if (input_graph && igraph_hrg_size(hrg) != igraph_vcount(input_graph)) { IGRAPH_ERROR("Invalid HRG size, should match number of nodes", IGRAPH_EINVAL); } RNG_BEGIN(); d = new dendro; // Need to find equilibrium first? if (start) { d->clearDendrograph(); d->importDendrogramStructure(hrg); } else { IGRAPH_CHECK(MCMCEquilibrium_Find(d, hrg)); } // TODO: free on error if (sample) { // A single graph d->makeRandomGraph(); d->recordGraphStructure(sample); if (samples) { igraph_t *G = igraph_Calloc(1, igraph_t); if (!G) { IGRAPH_ERROR("Cannot sample HRG graphs", IGRAPH_ENOMEM); } d->recordGraphStructure(G); IGRAPH_CHECK(igraph_vector_ptr_resize(samples, 1)); VECTOR(*samples)[0] = G; } } else { // Sample many IGRAPH_CHECK(igraph_vector_ptr_resize(samples, no_samples)); for (i = 0; i < no_samples; i++) { igraph_t *G = igraph_Calloc(1, igraph_t); if (!G) { IGRAPH_ERROR("Cannot sample HRG graphs", IGRAPH_ENOMEM); } d->makeRandomGraph(); d->recordGraphStructure(G); VECTOR(*samples)[i] = G; } } delete d; RNG_END(); return 0; } /** * \function igraph_hrg_game * Generate a hierarchical random graph * * This function is a simple shortcut to \ref igraph_hrg_sample. * It creates a single graph, from the given HRG. * \param graph Pointer to an uninitialized graph, the new graph is * created here. * \param hrg The hierarchical random graph model to sample from. It * is modified during the MCMC process. * \return Error code. * * Time complexity: TODO. */ int igraph_hrg_game(igraph_t *graph, const igraph_hrg_t *hrg) { return igraph_hrg_sample(/* input_graph= */ 0, /* sample= */ graph, /* samples= */ 0, /* no_samples=*/ 1, /* hrg= */ (igraph_hrg_t*) hrg, /* start= */ 1); } /** * \function igraph_hrg_dendrogram * Create a dendrogram from a hierarchical random graph. * * Creates the igraph graph equivalent of an \ref igraph_hrg_t data * structure. * \param graph Pointer to an uninitialized graph, the result is * stored here. * \param hrg The hierarchical random graph to convert. * \return Error code. * * Time complexity: O(n), the number of vertices in the graph. */ int igraph_hrg_dendrogram(igraph_t *graph, const igraph_hrg_t *hrg) { int orig_nodes = igraph_hrg_size(hrg); int no_of_nodes = orig_nodes * 2 - 1; int no_of_edges = no_of_nodes - 1; igraph_vector_t edges; int i, idx = 0; igraph_vector_ptr_t vattrs; igraph_vector_t prob; igraph_attribute_record_t rec = { "probability", IGRAPH_ATTRIBUTE_NUMERIC, &prob }; // Probability labels, for leaf nodes they are IGRAPH_NAN IGRAPH_VECTOR_INIT_FINALLY(&prob, no_of_nodes); for (i = 0; i < orig_nodes; i++) { VECTOR(prob)[i] = IGRAPH_NAN; } for (i = 0; i < orig_nodes - 1; i++) { VECTOR(prob)[orig_nodes + i] = VECTOR(hrg->prob)[i]; } IGRAPH_VECTOR_INIT_FINALLY(&edges, no_of_edges * 2); IGRAPH_CHECK(igraph_vector_ptr_init(&vattrs, 1)); IGRAPH_FINALLY(igraph_vector_ptr_destroy, &vattrs); VECTOR(vattrs)[0] = &rec; for (i = 0; i < orig_nodes - 1; i++) { int left = VECTOR(hrg->left)[i]; int right = VECTOR(hrg->right)[i]; VECTOR(edges)[idx++] = orig_nodes + i; VECTOR(edges)[idx++] = left < 0 ? orig_nodes - left - 1 : left; VECTOR(edges)[idx++] = orig_nodes + i; VECTOR(edges)[idx++] = right < 0 ? orig_nodes - right - 1 : right; } IGRAPH_CHECK(igraph_empty(graph, 0, IGRAPH_DIRECTED)); IGRAPH_FINALLY(igraph_destroy, graph); IGRAPH_CHECK(igraph_add_vertices(graph, no_of_nodes, &vattrs)); IGRAPH_CHECK(igraph_add_edges(graph, &edges, 0)); igraph_vector_ptr_destroy(&vattrs); igraph_vector_destroy(&edges); igraph_vector_destroy(&prob); IGRAPH_FINALLY_CLEAN(4); // + 1 for graph return 0; } /** * \function igraph_hrg_consensus * Calculate a consensus tree for a HRG. * * The calculation can be started from the given HRG (\c hrg), or (if * \c start is false), a HRG is first fitted to the given graph. * * \param graph The input graph. * \param parents An initialized vector, the results are stored * here. For each vertex, the id of its parent vertex is stored, or * -1, if the vertex is the root vertex in the tree. The first n * vertex ids (from 0) refer to the original vertices of the graph, * the other ids refer to vertex groups. * \param weights Numeric vector, counts the number of times a given * tree split occured in the generated network samples, for each * internal vertices. The order is the same as in \c parents. * \param hrg A hierarchical random graph. It is used as a starting * point for the sampling, if the \c start argument is true. It is * modified along the MCMC. * \param start Logical, whether to use the supplied HRG (in \c hrg) * as a starting point for the MCMC. * \param num_samples The number of samples to generate for creating * the consensus tree. * \return Error code. * * Time complexity: TODO. */ int igraph_hrg_consensus(const igraph_t *graph, igraph_vector_t *parents, igraph_vector_t *weights, igraph_hrg_t *hrg, igraph_bool_t start, int num_samples) { dendro *d; if (start && !hrg) { IGRAPH_ERROR("`hrg' must be given is `start' is true", IGRAPH_EINVAL); } RNG_BEGIN(); d = new dendro; if (start) { d->clearDendrograph(); IGRAPH_CHECK(igraph_i_hrg_getgraph(graph, d)); d->importDendrogramStructure(hrg); } else { IGRAPH_CHECK(igraph_i_hrg_getgraph(graph, d)); if (hrg) { igraph_hrg_resize(hrg, igraph_vcount(graph)); } IGRAPH_CHECK(MCMCEquilibrium_Find(d, hrg)); } IGRAPH_CHECK(markovChainMonteCarlo2(d, num_samples)); d->recordConsensusTree(parents, weights); delete d; RNG_END(); return 0; } int MCMCEquilibrium_Sample(dendro *d, int num_samples) { // Because moves in the dendrogram space are chosen (Monte // Carlo) so that we sample dendrograms with probability // proportional to their likelihood, a likelihood-proportional // sampling of the dendrogram models would be equivalent to a // uniform sampling of the walk itself. We would still have to // decide how often to sample the walk (at most once every n steps // is recommended) but for simplicity, the code here simply runs the // MCMC itself. To actually compute something over the set of // sampled dendrogram models (in a Bayesian model averaging sense), // you'll need to code that yourself. double dL; bool flag_taken; int sample_num = 0; int t = 1, thresh = 100 * d->g->numNodes(); double ptest = 1.0 / 10.0 / d->g->numNodes(); while (sample_num < num_samples) { d->monteCarloMove(dL, flag_taken, 1.0); if (t > thresh && RNG_UNIF01() < ptest) { sample_num++; d->sampleAdjacencyLikelihoods(); } d->refreshLikelihood(); // TODO: less frequently t++; } return 0; } int QsortPartition (pblock* array, int left, int right, int index) { pblock p_value, temp; p_value.L = array[index].L; p_value.i = array[index].i; p_value.j = array[index].j; // swap(array[p_value], array[right]) temp.L = array[right].L; temp.i = array[right].i; temp.j = array[right].j; array[right].L = array[index].L; array[right].i = array[index].i; array[right].j = array[index].j; array[index].L = temp.L; array[index].i = temp.i; array[index].j = temp.j; int stored = left; for (int i = left; i < right; i++) { if (array[i].L <= p_value.L) { // swap(array[stored], array[i]) temp.L = array[i].L; temp.i = array[i].i; temp.j = array[i].j; array[i].L = array[stored].L; array[i].i = array[stored].i; array[i].j = array[stored].j; array[stored].L = temp.L; array[stored].i = temp.i; array[stored].j = temp.j; stored++; } } // swap(array[right], array[stored]) temp.L = array[stored].L; temp.i = array[stored].i; temp.j = array[stored].j; array[stored].L = array[right].L; array[stored].i = array[right].i; array[stored].j = array[right].j; array[right].L = temp.L; array[right].i = temp.i; array[right].j = temp.j; return stored; } void QsortMain (pblock* array, int left, int right) { if (right > left) { int pivot = left; int part = QsortPartition(array, left, right, pivot); QsortMain(array, left, part - 1); QsortMain(array, part + 1, right ); } return; } int rankCandidatesByProbability(simpleGraph *sg, dendro *d, pblock *br_list, int mk) { int mkk = 0; int n = sg->getNumNodes(); for (int i = 0; i < n; i++) { for (int j = i + 1; j < n; j++) { if (sg->getAdjacency(i, j) < 0.5) { double temp = d->g->getAdjacencyAverage(i, j); br_list[mkk].L = temp * (1.0 + RNG_UNIF01() / 1000.0); br_list[mkk].i = i; br_list[mkk].j = j; mkk++; } } } // Sort the candidates by their average probability QsortMain(br_list, 0, mk - 1); return 0; } int recordPredictions(pblock *br_list, igraph_vector_t *edges, igraph_vector_t *prob, int mk) { IGRAPH_CHECK(igraph_vector_resize(edges, mk * 2)); IGRAPH_CHECK(igraph_vector_resize(prob, mk)); for (int i = mk - 1, idx = 0, idx2 = 0; i >= 0; i--) { VECTOR(*edges)[idx++] = br_list[i].i; VECTOR(*edges)[idx++] = br_list[i].j; VECTOR(*prob)[idx2++] = br_list[i].L; } return 0; } /** * \function igraph_hrg_predict * Predict missing edges in a graph, based on HRG models * * Samples HRG models for a network, and estimated the probability * that an edge was falsely observed as non-existent in the network. * \param graph The input graph. * \param edges The list of missing edges is stored here, the first * two elements are the first edge, the next two the second edge, * etc. * \param prob Vector of probabilies for the existence of missing * edges, in the order corresponding to \c edges. * \param hrg A HRG, it is used as a starting point if \c start is * true. It is also modified during the MCMC sampling. * \param start Logical, whether to start the MCMC from the given HRG. * \param num_samples The number of samples to generate. * \param num_bins Controls the resolution of the edge * probabilities. Higher numbers result higher resolution. * \return Error code. * * Time complexity: TODO. */ int igraph_hrg_predict(const igraph_t *graph, igraph_vector_t *edges, igraph_vector_t *prob, igraph_hrg_t *hrg, igraph_bool_t start, int num_samples, int num_bins) { dendro *d; pblock *br_list; int mk; simpleGraph *sg; if (start && !hrg) { IGRAPH_ERROR("`hrg' must be given is `start' is true", IGRAPH_EINVAL); } RNG_BEGIN(); d = new dendro; IGRAPH_CHECK(igraph_i_hrg_getsimplegraph(graph, d, &sg, num_bins)); mk = sg->getNumNodes() * (sg->getNumNodes() - 1) / 2 - sg->getNumLinks() / 2; br_list = new pblock[mk]; for (int i = 0; i < mk; i++) { br_list[i].L = 0.0; br_list[i].i = -1; br_list[i].j = -1; } if (start) { d->clearDendrograph(); // this has cleared the graph as well.... bug? IGRAPH_CHECK(igraph_i_hrg_getsimplegraph(graph, d, &sg, num_bins)); d->importDendrogramStructure(hrg); } else { if (hrg) { igraph_hrg_resize(hrg, igraph_vcount(graph)); } IGRAPH_CHECK(MCMCEquilibrium_Find(d, hrg)); } IGRAPH_CHECK(MCMCEquilibrium_Sample(d, num_samples)); IGRAPH_CHECK(rankCandidatesByProbability(sg, d, br_list, mk)); IGRAPH_CHECK(recordPredictions(br_list, edges, prob, mk)); delete d; delete sg; delete [] br_list; RNG_END(); return 0; } /** * \function igraph_hrg_create * Create a HRG from an igraph graph. * * \param hrg Pointer to an initialized \ref igraph_hrg_t. The result * is stored here. * \param graph The igraph graph to convert. It must be a directed * binary tree, with n-1 internal and n leaf vertices. The root * vertex must have in-degree zero. * \param prob The vector of probabilities, this is used to label the * internal nodes of the hierarchical random graph. The values * corresponding to the leaves are ignored. * \return Error code. * * Time complexity: O(n), the number of vertices in the tree. */ int igraph_hrg_create(igraph_hrg_t *hrg, const igraph_t *graph, const igraph_vector_t *prob) { int no_of_nodes = igraph_vcount(graph); int no_of_internal = (no_of_nodes - 1) / 2; igraph_vector_t deg, idx; int root = 0; int d0 = 0, d1 = 0, d2 = 0; int ii = 0, il = 0; igraph_vector_t neis; igraph_vector_t path; // -------------------------------------------------------- // CHECKS // -------------------------------------------------------- // At least three vertices are required if (no_of_nodes < 3) { IGRAPH_ERROR("HRG tree must have at least three vertices", IGRAPH_EINVAL); } // Prob vector was given if (!prob) { IGRAPH_ERROR("Probability vector must be given for HRG", IGRAPH_EINVAL); } // Length of prob vector if (igraph_vector_size(prob) != no_of_nodes) { IGRAPH_ERROR("HRG probability vector of wrong size", IGRAPH_EINVAL); } // Must be a directed graph if (!igraph_is_directed(graph)) { IGRAPH_ERROR("HRG graph must be directed", IGRAPH_EINVAL); } // Number of nodes must be odd if (no_of_nodes % 2 == 0) { IGRAPH_ERROR("Complete HRG graph must have odd number of vertices", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(°, 0); // Every vertex, except for the root must have in-degree one. IGRAPH_CHECK(igraph_degree(graph, °, igraph_vss_all(), IGRAPH_IN, IGRAPH_LOOPS)); for (int i = 0; i < no_of_nodes; i++) { int d = VECTOR(deg)[i]; switch (d) { case 0: d0++; root = i; break; case 1: d1++; break; default: IGRAPH_ERROR("HRG nodes must have in-degree one, except for the " "root vertex", IGRAPH_EINVAL); } } if (d1 != no_of_nodes - 1 || d0 != 1) { IGRAPH_ERROR("HRG nodes must have in-degree one, except for the " "root vertex", IGRAPH_EINVAL); } // Every internal vertex must have out-degree two, // leaves out-degree zero d0 = d1 = d2 = 0; IGRAPH_CHECK(igraph_degree(graph, °, igraph_vss_all(), IGRAPH_OUT, IGRAPH_LOOPS)); for (int i = 0; i < no_of_nodes; i++) { int d = VECTOR(deg)[i]; switch (d) { case 0: d0++; break; case 2: d2++; break; default: IGRAPH_ERROR("HRG nodes must have out-degree 2 (internal nodes) or " "degree 0 (leaves)", IGRAPH_EINVAL); } } // Number of internal and external nodes is correct // This basically checks that the graph has one component if (d0 != d2 + 1) { IGRAPH_ERROR("HRG degrees are incorrect, maybe multiple components?", IGRAPH_EINVAL); } // -------------------------------------------------------- // Graph is good, do the conversion // -------------------------------------------------------- // Create an index, that maps the root node as first, then // the internal nodes, then the leaf nodes IGRAPH_VECTOR_INIT_FINALLY(&idx, no_of_nodes); VECTOR(idx)[root] = - (ii++) - 1; for (int i = 0; i < no_of_nodes; i++) { int d = VECTOR(deg)[i]; if (i == root) { continue; } if (d == 2) { VECTOR(idx)[i] = - (ii++) - 1; } if (d == 0) { VECTOR(idx)[i] = (il++); } } igraph_hrg_resize(hrg, no_of_internal + 1); IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); for (int i = 0; i < no_of_nodes; i++) { int ri = VECTOR(idx)[i]; if (ri >= 0) { continue; } IGRAPH_CHECK(igraph_neighbors(graph, &neis, i, IGRAPH_OUT)); VECTOR(hrg->left )[-ri - 1] = VECTOR(idx)[ (int) VECTOR(neis)[0] ]; VECTOR(hrg->right)[-ri - 1] = VECTOR(idx)[ (int) VECTOR(neis)[1] ]; VECTOR(hrg->prob )[-ri - 1] = VECTOR(*prob)[i]; } // Calculate the number of vertices and edges in each subtree igraph_vector_null(&hrg->edges); igraph_vector_null(&hrg->vertices); IGRAPH_VECTOR_INIT_FINALLY(&path, 0); IGRAPH_CHECK(igraph_vector_push_back(&path, VECTOR(idx)[root])); while (!igraph_vector_empty(&path)) { int ri = igraph_vector_tail(&path); int lc = VECTOR(hrg->left)[-ri - 1]; int rc = VECTOR(hrg->right)[-ri - 1]; if (lc < 0 && VECTOR(hrg->vertices)[-lc - 1] == 0) { // Go left IGRAPH_CHECK(igraph_vector_push_back(&path, lc)); } else if (rc < 0 && VECTOR(hrg->vertices)[-rc - 1] == 0) { // Go right IGRAPH_CHECK(igraph_vector_push_back(&path, rc)); } else { // Subtrees are done, update node and go up VECTOR(hrg->vertices)[-ri - 1] += lc < 0 ? VECTOR(hrg->vertices)[-lc - 1] : 1; VECTOR(hrg->vertices)[-ri - 1] += rc < 0 ? VECTOR(hrg->vertices)[-rc - 1] : 1; VECTOR(hrg->edges)[-ri - 1] += lc < 0 ? VECTOR(hrg->edges)[-lc - 1] + 1 : 1; VECTOR(hrg->edges)[-ri - 1] += rc < 0 ? VECTOR(hrg->edges)[-rc - 1] + 1 : 1; igraph_vector_pop_back(&path); } } igraph_vector_destroy(&path); igraph_vector_destroy(&neis); igraph_vector_destroy(&idx); igraph_vector_destroy(°); IGRAPH_FINALLY_CLEAN(4); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/cattributes.c0000644000076500000240000044435613614300625024113 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2005-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_attributes.h" #include "igraph_memory.h" #include "config.h" #include "igraph_math.h" #include "igraph_interface.h" #include "igraph_random.h" #include /* An attribute is either a numeric vector (vector_t) or a string vector (strvector_t). The attribute itself is stored in a struct igraph_attribute_record_t, there is one such object for each attribute. The igraph_t has a pointer to an array of three vector_ptr_t's which contains pointers to igraph_i_cattribute_t's. Graph attributes are first, then vertex and edge attributes. */ igraph_bool_t igraph_i_cattribute_find(const igraph_vector_ptr_t *ptrvec, const char *name, long int *idx) { long int i, n = igraph_vector_ptr_size(ptrvec); igraph_bool_t l = 0; for (i = 0; !l && i < n; i++) { igraph_attribute_record_t *rec = VECTOR(*ptrvec)[i]; l = !strcmp(rec->name, name); } if (idx) { *idx = i - 1; } return l; } typedef struct igraph_i_cattributes_t { igraph_vector_ptr_t gal; igraph_vector_ptr_t val; igraph_vector_ptr_t eal; } igraph_i_cattributes_t; int igraph_i_cattributes_copy_attribute_record(igraph_attribute_record_t **newrec, const igraph_attribute_record_t *rec) { igraph_vector_t *num, *newnum; igraph_strvector_t *str, *newstr; *newrec = igraph_Calloc(1, igraph_attribute_record_t); if (!(*newrec)) { IGRAPH_ERROR("Cannot copy attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, *newrec); (*newrec)->type = rec->type; (*newrec)->name = strdup(rec->name); if (!(*newrec)->name) { IGRAPH_ERROR("Cannot copy attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (void*)(*newrec)->name); if (rec->type == IGRAPH_ATTRIBUTE_NUMERIC) { num = (igraph_vector_t *)rec->value; newnum = igraph_Calloc(1, igraph_vector_t); if (!newnum) { IGRAPH_ERROR("Cannot copy attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newnum); IGRAPH_CHECK(igraph_vector_copy(newnum, num)); IGRAPH_FINALLY(igraph_vector_destroy, newnum); (*newrec)->value = newnum; } else if (rec->type == IGRAPH_ATTRIBUTE_STRING) { str = (igraph_strvector_t*)rec->value; newstr = igraph_Calloc(1, igraph_strvector_t); if (!newstr) { IGRAPH_ERROR("Cannot copy attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newstr); IGRAPH_CHECK(igraph_strvector_copy(newstr, str)); IGRAPH_FINALLY(igraph_strvector_destroy, newstr); (*newrec)->value = newstr; } else if (rec->type == IGRAPH_ATTRIBUTE_BOOLEAN) { igraph_vector_bool_t *log = (igraph_vector_bool_t*) rec->value; igraph_vector_bool_t *newlog = igraph_Calloc(1, igraph_vector_bool_t); if (!newlog) { IGRAPH_ERROR("Cannot copy attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newlog); IGRAPH_CHECK(igraph_vector_bool_copy(newlog, log)); IGRAPH_FINALLY(igraph_vector_bool_destroy, newlog); (*newrec)->value = newlog; } IGRAPH_FINALLY_CLEAN(4); return 0; } int igraph_i_cattribute_init(igraph_t *graph, igraph_vector_ptr_t *attr) { igraph_attribute_record_t *attr_rec; long int i, n; igraph_i_cattributes_t *nattr; n = attr ? igraph_vector_ptr_size(attr) : 0; nattr = igraph_Calloc(1, igraph_i_cattributes_t); if (!nattr) { IGRAPH_ERROR("Can't init attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, nattr); IGRAPH_CHECK(igraph_vector_ptr_init(&nattr->gal, n)); IGRAPH_FINALLY(igraph_vector_ptr_destroy, &nattr->gal); IGRAPH_CHECK(igraph_vector_ptr_init(&nattr->val, 0)); IGRAPH_FINALLY(igraph_vector_ptr_destroy, &nattr->val); IGRAPH_CHECK(igraph_vector_ptr_init(&nattr->eal, 0)); IGRAPH_FINALLY_CLEAN(3); for (i = 0; i < n; i++) { IGRAPH_CHECK(igraph_i_cattributes_copy_attribute_record( &attr_rec, VECTOR(*attr)[i])); VECTOR(nattr->gal)[i] = attr_rec; } graph->attr = nattr; return 0; } void igraph_i_cattribute_destroy(igraph_t *graph) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *als[3] = { &attr->gal, &attr->val, &attr->eal }; long int i, n, a; igraph_vector_t *num; igraph_strvector_t *str; igraph_vector_bool_t *boolvec; igraph_attribute_record_t *rec; for (a = 0; a < 3; a++) { n = igraph_vector_ptr_size(als[a]); for (i = 0; i < n; i++) { rec = VECTOR(*als[a])[i]; if (rec) { if (rec->type == IGRAPH_ATTRIBUTE_NUMERIC) { num = (igraph_vector_t*)rec->value; igraph_vector_destroy(num); igraph_free(num); } else if (rec->type == IGRAPH_ATTRIBUTE_STRING) { str = (igraph_strvector_t*)rec->value; igraph_strvector_destroy(str); igraph_free(str); } else if (rec->type == IGRAPH_ATTRIBUTE_BOOLEAN) { boolvec = (igraph_vector_bool_t*)rec->value; igraph_vector_bool_destroy(boolvec); igraph_free(boolvec); } igraph_free((char*)rec->name); igraph_free(rec); } } } igraph_vector_ptr_destroy(&attr->gal); igraph_vector_ptr_destroy(&attr->val); igraph_vector_ptr_destroy(&attr->eal); igraph_free(graph->attr); graph->attr = 0; } /* Almost the same as destroy, but we might have null pointers */ void igraph_i_cattribute_copy_free(igraph_i_cattributes_t *attr) { igraph_vector_ptr_t *als[3] = { &attr->gal, &attr->val, &attr->eal }; long int i, n, a; igraph_vector_t *num; igraph_strvector_t *str; igraph_vector_bool_t *boolvec; igraph_attribute_record_t *rec; for (a = 0; a < 3; a++) { n = igraph_vector_ptr_size(als[a]); for (i = 0; i < n; i++) { rec = VECTOR(*als[a])[i]; if (!rec) { continue; } if (rec->type == IGRAPH_ATTRIBUTE_NUMERIC) { num = (igraph_vector_t*)rec->value; igraph_vector_destroy(num); igraph_free(num); } else if (rec->type == IGRAPH_ATTRIBUTE_BOOLEAN) { boolvec = (igraph_vector_bool_t*)rec->value; igraph_vector_bool_destroy(boolvec); igraph_free(boolvec); } else if (rec->type == IGRAPH_ATTRIBUTE_STRING) { str = (igraph_strvector_t*)rec->value; igraph_strvector_destroy(str); igraph_free(str); } igraph_free((char*)rec->name); igraph_free(rec); } } } /* No reference counting here. If you use attributes in C you should know what you're doing. */ int igraph_i_cattribute_copy(igraph_t *to, const igraph_t *from, igraph_bool_t ga, igraph_bool_t va, igraph_bool_t ea) { igraph_i_cattributes_t *attrfrom = from->attr, *attrto; igraph_vector_ptr_t *alto[3], *alfrom[3] = { &attrfrom->gal, &attrfrom->val, &attrfrom->eal }; long int i, n, a; igraph_bool_t copy[3] = { ga, va, ea }; to->attr = attrto = igraph_Calloc(1, igraph_i_cattributes_t); if (!attrto) { IGRAPH_ERROR("Cannot copy attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, attrto); IGRAPH_VECTOR_PTR_INIT_FINALLY(&attrto->gal, 0); IGRAPH_VECTOR_PTR_INIT_FINALLY(&attrto->val, 0); IGRAPH_VECTOR_PTR_INIT_FINALLY(&attrto->eal, 0); IGRAPH_FINALLY_CLEAN(3); IGRAPH_FINALLY(igraph_i_cattribute_copy_free, attrto); alto[0] = &attrto->gal; alto[1] = &attrto->val; alto[2] = &attrto->eal; for (a = 0; a < 3; a++) { if (copy[a]) { n = igraph_vector_ptr_size(alfrom[a]); IGRAPH_CHECK(igraph_vector_ptr_resize(alto[a], n)); igraph_vector_ptr_null(alto[a]); for (i = 0; i < n; i++) { igraph_attribute_record_t *newrec; IGRAPH_CHECK(igraph_i_cattributes_copy_attribute_record(&newrec, VECTOR(*alfrom[a])[i])); VECTOR(*alto[a])[i] = newrec; } } } IGRAPH_FINALLY_CLEAN(2); return 0; } int igraph_i_cattribute_add_vertices(igraph_t *graph, long int nv, igraph_vector_ptr_t *nattr) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *val = &attr->val; long int length = igraph_vector_ptr_size(val); long int nattrno = nattr == NULL ? 0 : igraph_vector_ptr_size(nattr); long int origlen = igraph_vcount(graph) - nv; long int newattrs = 0, i; igraph_vector_t news; /* First add the new attributes if any */ newattrs = 0; IGRAPH_VECTOR_INIT_FINALLY(&news, 0); for (i = 0; i < nattrno; i++) { igraph_attribute_record_t *nattr_entry = VECTOR(*nattr)[i]; const char *nname = nattr_entry->name; long int j; igraph_bool_t l = igraph_i_cattribute_find(val, nname, &j); if (!l) { newattrs++; IGRAPH_CHECK(igraph_vector_push_back(&news, i)); } else { /* check types */ if (nattr_entry->type != ((igraph_attribute_record_t*)VECTOR(*val)[j])->type) { IGRAPH_ERROR("You cannot mix attribute types", IGRAPH_EINVAL); } } } /* Add NA/empty string vectors for the existing vertices */ if (newattrs != 0) { for (i = 0; i < newattrs; i++) { igraph_attribute_record_t *tmp = VECTOR(*nattr)[(long int)VECTOR(news)[i]]; igraph_attribute_record_t *newrec = igraph_Calloc(1, igraph_attribute_record_t); igraph_attribute_type_t type = tmp->type; if (!newrec) { IGRAPH_ERROR("Cannot add attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newrec); newrec->type = type; newrec->name = strdup(tmp->name); if (!newrec->name) { IGRAPH_ERROR("Cannot add attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (char*)newrec->name); if (type == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_vector_t *newnum = igraph_Calloc(1, igraph_vector_t); if (!newnum) { IGRAPH_ERROR("Cannot add attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newnum); IGRAPH_VECTOR_INIT_FINALLY(newnum, origlen); newrec->value = newnum; igraph_vector_fill(newnum, IGRAPH_NAN); } else if (type == IGRAPH_ATTRIBUTE_STRING) { igraph_strvector_t *newstr = igraph_Calloc(1, igraph_strvector_t); if (!newstr) { IGRAPH_ERROR("Cannot add attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newstr); IGRAPH_STRVECTOR_INIT_FINALLY(newstr, origlen); newrec->value = newstr; } else if (type == IGRAPH_ATTRIBUTE_BOOLEAN) { igraph_vector_bool_t *newbool = igraph_Calloc(1, igraph_vector_bool_t); if (!newbool) { IGRAPH_ERROR("Cannot add attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newbool); IGRAPH_CHECK(igraph_vector_bool_init(newbool, origlen)); IGRAPH_FINALLY(igraph_vector_bool_destroy, newbool); newrec->value = newbool; igraph_vector_bool_fill(newbool, 0); } IGRAPH_CHECK(igraph_vector_ptr_push_back(val, newrec)); IGRAPH_FINALLY_CLEAN(4); } length = igraph_vector_ptr_size(val); } /* Now append the new values */ for (i = 0; i < length; i++) { igraph_attribute_record_t *oldrec = VECTOR(*val)[i]; igraph_attribute_record_t *newrec = 0; const char *name = oldrec->name; long int j; igraph_bool_t l = 0; if (nattr) { l = igraph_i_cattribute_find(nattr, name, &j); } if (l) { /* This attribute is present in nattr */ igraph_vector_t *oldnum, *newnum; igraph_strvector_t *oldstr, *newstr; igraph_vector_bool_t *oldbool, *newbool; newrec = VECTOR(*nattr)[j]; oldnum = (igraph_vector_t*)oldrec->value; newnum = (igraph_vector_t*)newrec->value; oldstr = (igraph_strvector_t*)oldrec->value; newstr = (igraph_strvector_t*)newrec->value; oldbool = (igraph_vector_bool_t*)oldrec->value; newbool = (igraph_vector_bool_t*)newrec->value; if (oldrec->type != newrec->type) { IGRAPH_ERROR("Attribute types do not match", IGRAPH_EINVAL); } switch (oldrec->type) { case IGRAPH_ATTRIBUTE_NUMERIC: if (nv != igraph_vector_size(newnum)) { IGRAPH_ERROR("Invalid numeric attribute length", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_vector_append(oldnum, newnum)); break; case IGRAPH_ATTRIBUTE_STRING: if (nv != igraph_strvector_size(newstr)) { IGRAPH_ERROR("Invalid string attribute length", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_strvector_append(oldstr, newstr)); break; case IGRAPH_ATTRIBUTE_BOOLEAN: if (nv != igraph_vector_bool_size(newbool)) { IGRAPH_ERROR("Invalid Boolean attribute length", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_vector_bool_append(oldbool, newbool)); break; default: IGRAPH_WARNING("Invalid attribute type"); break; } } else { /* No such attribute, append NA's */ igraph_vector_t *oldnum = (igraph_vector_t *)oldrec->value; igraph_strvector_t *oldstr = (igraph_strvector_t*)oldrec->value; igraph_vector_bool_t *oldbool = (igraph_vector_bool_t*)oldrec->value; switch (oldrec->type) { case IGRAPH_ATTRIBUTE_NUMERIC: IGRAPH_CHECK(igraph_vector_resize(oldnum, origlen + nv)); for (j = origlen; j < origlen + nv; j++) { VECTOR(*oldnum)[j] = IGRAPH_NAN; } break; case IGRAPH_ATTRIBUTE_STRING: IGRAPH_CHECK(igraph_strvector_resize(oldstr, origlen + nv)); break; case IGRAPH_ATTRIBUTE_BOOLEAN: IGRAPH_CHECK(igraph_vector_bool_resize(oldbool, origlen + nv)); for (j = origlen; j < origlen + nv; j++) { VECTOR(*oldbool)[j] = 0; } break; default: IGRAPH_WARNING("Invalid attribute type"); break; } } } igraph_vector_destroy(&news); IGRAPH_FINALLY_CLEAN(1); return 0; } void igraph_i_cattribute_permute_free(igraph_vector_ptr_t *v) { long int i, n = igraph_vector_ptr_size(v); for (i = 0; i < n; i++) { igraph_attribute_record_t *rec = VECTOR(*v)[i]; igraph_Free(rec->name); if (rec->type == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_vector_t *numv = (igraph_vector_t*) rec->value; igraph_vector_destroy(numv); igraph_Free(numv); } else if (rec->type == IGRAPH_ATTRIBUTE_STRING) { igraph_strvector_t *strv = (igraph_strvector_t*) rec->value; igraph_strvector_destroy(strv); igraph_Free(strv); } else if (rec->type == IGRAPH_ATTRIBUTE_BOOLEAN) { igraph_vector_bool_t *boolv = (igraph_vector_bool_t*) rec->value; igraph_vector_bool_destroy(boolv); igraph_Free(boolv); } igraph_Free(rec); } igraph_vector_ptr_clear(v); } int igraph_i_cattribute_permute_vertices(const igraph_t *graph, igraph_t *newgraph, const igraph_vector_t *idx) { if (graph == newgraph) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *val = &attr->val; long int valno = igraph_vector_ptr_size(val); long int i; for (i = 0; i < valno; i++) { igraph_attribute_record_t *oldrec = VECTOR(*val)[i]; igraph_attribute_type_t type = oldrec->type; igraph_vector_t *num, *newnum; igraph_strvector_t *str, *newstr; igraph_vector_bool_t *oldbool, *newbool; switch (type) { case IGRAPH_ATTRIBUTE_NUMERIC: num = (igraph_vector_t*) oldrec->value; newnum = igraph_Calloc(1, igraph_vector_t); if (!newnum) { IGRAPH_ERROR("Cannot permute vertex attributes", IGRAPH_ENOMEM); } IGRAPH_VECTOR_INIT_FINALLY(newnum, 0); igraph_vector_index(num, newnum, idx); oldrec->value = newnum; igraph_vector_destroy(num); igraph_Free(num); IGRAPH_FINALLY_CLEAN(1); break; case IGRAPH_ATTRIBUTE_BOOLEAN: oldbool = (igraph_vector_bool_t*) oldrec->value; newbool = igraph_Calloc(1, igraph_vector_bool_t); if (!newbool) { IGRAPH_ERROR("Cannot permute vertex attributes", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_bool_init(newbool, 0)); IGRAPH_FINALLY(igraph_vector_bool_destroy, newbool); igraph_vector_bool_index(oldbool, newbool, idx); oldrec->value = newbool; igraph_vector_bool_destroy(oldbool); igraph_Free(oldbool); IGRAPH_FINALLY_CLEAN(1); break; case IGRAPH_ATTRIBUTE_STRING: str = (igraph_strvector_t*)oldrec->value; newstr = igraph_Calloc(1, igraph_strvector_t); if (!newstr) { IGRAPH_ERROR("Cannot permute vertex attributes", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_strvector_init(newstr, 0)); IGRAPH_FINALLY(igraph_strvector_destroy, newstr); igraph_strvector_index(str, newstr, idx); oldrec->value = newstr; igraph_strvector_destroy(str); igraph_Free(str); IGRAPH_FINALLY_CLEAN(1); break; default: IGRAPH_WARNING("Unknown edge attribute ignored"); } } } else { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *val = &attr->val; long int valno = igraph_vector_ptr_size(val); long int i; /* New vertex attributes */ igraph_i_cattributes_t *new_attr = newgraph->attr; igraph_vector_ptr_t *new_val = &new_attr->val; if (igraph_vector_ptr_size(new_val) != 0) { IGRAPH_ERROR("Vertex attributes were already copied", IGRAPH_EATTRIBUTES); } IGRAPH_CHECK(igraph_vector_ptr_resize(new_val, valno)); IGRAPH_FINALLY(igraph_i_cattribute_permute_free, new_val); for (i = 0; i < valno; i++) { igraph_attribute_record_t *oldrec = VECTOR(*val)[i]; igraph_attribute_type_t type = oldrec->type; igraph_vector_t *num, *newnum; igraph_strvector_t *str, *newstr; igraph_vector_bool_t *oldbool, *newbool; /* The record itself */ igraph_attribute_record_t *new_rec = igraph_Calloc(1, igraph_attribute_record_t); if (!new_rec) { IGRAPH_ERROR("Cannot create vertex attributes", IGRAPH_ENOMEM); } new_rec->name = strdup(oldrec->name); new_rec->type = oldrec->type; VECTOR(*new_val)[i] = new_rec; /* The data */ switch (type) { case IGRAPH_ATTRIBUTE_NUMERIC: num = (igraph_vector_t*)oldrec->value; newnum = igraph_Calloc(1, igraph_vector_t); if (!newnum) { IGRAPH_ERROR("Cannot permute vertex attributes", IGRAPH_ENOMEM); } IGRAPH_VECTOR_INIT_FINALLY(newnum, 0); igraph_vector_index(num, newnum, idx); new_rec->value = newnum; IGRAPH_FINALLY_CLEAN(1); break; case IGRAPH_ATTRIBUTE_BOOLEAN: oldbool = (igraph_vector_bool_t*)oldrec->value; newbool = igraph_Calloc(1, igraph_vector_bool_t); if (!newbool) { IGRAPH_ERROR("Cannot permute vertex attributes", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_bool_init(newbool, 0)); IGRAPH_FINALLY(igraph_vector_bool_destroy, newbool); igraph_vector_bool_index(oldbool, newbool, idx); new_rec->value = newbool; IGRAPH_FINALLY_CLEAN(1); break; case IGRAPH_ATTRIBUTE_STRING: str = (igraph_strvector_t*)oldrec->value; newstr = igraph_Calloc(1, igraph_strvector_t); if (!newstr) { IGRAPH_ERROR("Cannot permute vertex attributes", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_strvector_init(newstr, 0)); IGRAPH_FINALLY(igraph_strvector_destroy, newstr); igraph_strvector_index(str, newstr, idx); new_rec->value = newstr; IGRAPH_FINALLY_CLEAN(1); break; default: IGRAPH_WARNING("Unknown vertex attribute ignored"); } } } IGRAPH_FINALLY_CLEAN(1); return 0; } typedef int igraph_cattributes_combine_num_t(const igraph_vector_t *input, igraph_real_t *output); typedef int igraph_cattributes_combine_str_t(const igraph_strvector_t *input, char **output); typedef int igraph_cattributes_combine_bool_t(const igraph_vector_bool_t *input, igraph_bool_t *output); int igraph_i_cattributes_cn_sum(const igraph_attribute_record_t *oldrec, igraph_attribute_record_t * newrec, const igraph_vector_ptr_t *merges) { const igraph_vector_t *oldv = oldrec->value; igraph_vector_t *newv = igraph_Calloc(1, igraph_vector_t); long int newlen = igraph_vector_ptr_size(merges); long int i; if (!newv) { IGRAPH_ERROR("Cannot combine attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newv); IGRAPH_VECTOR_INIT_FINALLY(newv, newlen); for (i = 0; i < newlen; i++) { igraph_real_t s = 0.0; igraph_vector_t *idx = VECTOR(*merges)[i]; long int j, n = igraph_vector_size(idx); for (j = 0; j < n; j++) { long int x = (long int) VECTOR(*idx)[j]; s += VECTOR(*oldv)[x]; } VECTOR(*newv)[i] = s; } IGRAPH_FINALLY_CLEAN(2); newrec->value = newv; return 0; } int igraph_i_cattributes_cn_prod(const igraph_attribute_record_t *oldrec, igraph_attribute_record_t * newrec, const igraph_vector_ptr_t *merges) { const igraph_vector_t *oldv = oldrec->value; igraph_vector_t *newv = igraph_Calloc(1, igraph_vector_t); long int newlen = igraph_vector_ptr_size(merges); long int i; if (!newv) { IGRAPH_ERROR("Cannot combine attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newv); IGRAPH_VECTOR_INIT_FINALLY(newv, newlen); for (i = 0; i < newlen; i++) { igraph_real_t s = 1.0; igraph_vector_t *idx = VECTOR(*merges)[i]; long int j, n = igraph_vector_size(idx); for (j = 0; j < n; j++) { long int x = (long int) VECTOR(*idx)[j]; s *= VECTOR(*oldv)[x]; } VECTOR(*newv)[i] = s; } IGRAPH_FINALLY_CLEAN(2); newrec->value = newv; return 0; } int igraph_i_cattributes_cn_min(const igraph_attribute_record_t *oldrec, igraph_attribute_record_t * newrec, const igraph_vector_ptr_t *merges) { const igraph_vector_t *oldv = oldrec->value; igraph_vector_t *newv = igraph_Calloc(1, igraph_vector_t); long int newlen = igraph_vector_ptr_size(merges); long int i; igraph_real_t nan = IGRAPH_NAN; if (!newv) { IGRAPH_ERROR("Cannot combine attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newv); IGRAPH_VECTOR_INIT_FINALLY(newv, newlen); for (i = 0; i < newlen; i++) { igraph_vector_t *idx = VECTOR(*merges)[i]; long int j, n = igraph_vector_size(idx); igraph_real_t m = n > 0 ? VECTOR(*oldv)[ (long int) VECTOR(*idx)[0] ] : nan; for (j = 1; j < n; j++) { long int x = (long int) VECTOR(*idx)[j]; igraph_real_t val = VECTOR(*oldv)[x]; if (val < m) { m = val; } } VECTOR(*newv)[i] = m; } IGRAPH_FINALLY_CLEAN(2); newrec->value = newv; return 0; } int igraph_i_cattributes_cn_max(const igraph_attribute_record_t *oldrec, igraph_attribute_record_t * newrec, const igraph_vector_ptr_t *merges) { const igraph_vector_t *oldv = oldrec->value; igraph_vector_t *newv = igraph_Calloc(1, igraph_vector_t); long int newlen = igraph_vector_ptr_size(merges); long int i; igraph_real_t nan = IGRAPH_NAN; if (!newv) { IGRAPH_ERROR("Cannot combine attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newv); IGRAPH_VECTOR_INIT_FINALLY(newv, newlen); for (i = 0; i < newlen; i++) { igraph_vector_t *idx = VECTOR(*merges)[i]; long int j, n = igraph_vector_size(idx); igraph_real_t m = n > 0 ? VECTOR(*oldv)[ (long int) VECTOR(*idx)[0] ] : nan; for (j = 1; j < n; j++) { long int x = (long int) VECTOR(*idx)[j]; igraph_real_t val = VECTOR(*oldv)[x]; if (val > m) { m = val; } } VECTOR(*newv)[i] = m; } IGRAPH_FINALLY_CLEAN(2); newrec->value = newv; return 0; } int igraph_i_cattributes_cn_random(const igraph_attribute_record_t *oldrec, igraph_attribute_record_t * newrec, const igraph_vector_ptr_t *merges) { const igraph_vector_t *oldv = oldrec->value; igraph_vector_t *newv = igraph_Calloc(1, igraph_vector_t); long int newlen = igraph_vector_ptr_size(merges); long int i; igraph_real_t nan = IGRAPH_NAN; if (!newv) { IGRAPH_ERROR("Cannot combine attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newv); IGRAPH_VECTOR_INIT_FINALLY(newv, newlen); RNG_BEGIN(); for (i = 0; i < newlen; i++) { igraph_vector_t *idx = VECTOR(*merges)[i]; long int n = igraph_vector_size(idx); if (n == 0) { VECTOR(*newv)[i] = nan; } else if (n == 1) { VECTOR(*newv)[i] = VECTOR(*oldv)[ (long int) VECTOR(*idx)[0] ]; } else { long int r = RNG_INTEGER(0, n - 1); VECTOR(*newv)[i] = VECTOR(*oldv)[ (long int) VECTOR(*idx)[r] ]; } } RNG_END(); IGRAPH_FINALLY_CLEAN(2); newrec->value = newv; return 0; } int igraph_i_cattributes_cn_first(const igraph_attribute_record_t *oldrec, igraph_attribute_record_t * newrec, const igraph_vector_ptr_t *merges) { const igraph_vector_t *oldv = oldrec->value; igraph_vector_t *newv = igraph_Calloc(1, igraph_vector_t); long int newlen = igraph_vector_ptr_size(merges); long int i; igraph_real_t nan = IGRAPH_NAN; if (!newv) { IGRAPH_ERROR("Cannot combine attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newv); IGRAPH_VECTOR_INIT_FINALLY(newv, newlen); for (i = 0; i < newlen; i++) { igraph_vector_t *idx = VECTOR(*merges)[i]; long int n = igraph_vector_size(idx); if (n == 0) { VECTOR(*newv)[i] = nan; } else { VECTOR(*newv)[i] = VECTOR(*oldv)[ (long int) VECTOR(*idx)[0] ]; } } IGRAPH_FINALLY_CLEAN(2); newrec->value = newv; return 0; } int igraph_i_cattributes_cn_last(const igraph_attribute_record_t *oldrec, igraph_attribute_record_t * newrec, const igraph_vector_ptr_t *merges) { const igraph_vector_t *oldv = oldrec->value; igraph_vector_t *newv = igraph_Calloc(1, igraph_vector_t); long int newlen = igraph_vector_ptr_size(merges); long int i; igraph_real_t nan = IGRAPH_NAN; if (!newv) { IGRAPH_ERROR("Cannot combine attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newv); IGRAPH_VECTOR_INIT_FINALLY(newv, newlen); for (i = 0; i < newlen; i++) { igraph_vector_t *idx = VECTOR(*merges)[i]; long int n = igraph_vector_size(idx); if (n == 0) { VECTOR(*newv)[i] = nan; } else { VECTOR(*newv)[i] = VECTOR(*oldv)[ (long int) VECTOR(*idx)[n - 1] ]; } } IGRAPH_FINALLY_CLEAN(2); newrec->value = newv; return 0; } int igraph_i_cattributes_cn_mean(const igraph_attribute_record_t *oldrec, igraph_attribute_record_t * newrec, const igraph_vector_ptr_t *merges) { const igraph_vector_t *oldv = oldrec->value; igraph_vector_t *newv = igraph_Calloc(1, igraph_vector_t); long int newlen = igraph_vector_ptr_size(merges); long int i; igraph_real_t nan = IGRAPH_NAN; if (!newv) { IGRAPH_ERROR("Cannot combine attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newv); IGRAPH_VECTOR_INIT_FINALLY(newv, newlen); for (i = 0; i < newlen; i++) { igraph_vector_t *idx = VECTOR(*merges)[i]; long int j, n = igraph_vector_size(idx); igraph_real_t s = n > 0 ? 0.0 : nan; for (j = 0; j < n; j++) { long int x = (long int) VECTOR(*idx)[j]; s += VECTOR(*oldv)[x]; } if (n > 0) { s = s / n; } VECTOR(*newv)[i] = s; } IGRAPH_FINALLY_CLEAN(2); newrec->value = newv; return 0; } int igraph_i_cattributes_cn_func(const igraph_attribute_record_t *oldrec, igraph_attribute_record_t *newrec, const igraph_vector_ptr_t *merges, igraph_cattributes_combine_num_t *func) { const igraph_vector_t *oldv = oldrec->value; long int newlen = igraph_vector_ptr_size(merges); long int i; igraph_vector_t *newv = igraph_Calloc(1, igraph_vector_t); igraph_vector_t values; if (!newv) { IGRAPH_ERROR("Cannot combine attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newv); IGRAPH_VECTOR_INIT_FINALLY(newv, newlen); IGRAPH_VECTOR_INIT_FINALLY(&values, 0); for (i = 0; i < newlen; i++) { igraph_vector_t *idx = VECTOR(*merges)[i]; long int j, n = igraph_vector_size(idx); igraph_real_t res; IGRAPH_CHECK(igraph_vector_resize(&values, n)); for (j = 0; j < n; j++) { long int x = (long int) VECTOR(*idx)[j]; VECTOR(values)[j] = VECTOR(*oldv)[x]; } IGRAPH_CHECK(func(&values, &res)); VECTOR(*newv)[i] = res; } igraph_vector_destroy(&values); IGRAPH_FINALLY_CLEAN(3); newrec->value = newv; return 0; } int igraph_i_cattributes_cb_random(const igraph_attribute_record_t *oldrec, igraph_attribute_record_t * newrec, const igraph_vector_ptr_t *merges) { const igraph_vector_bool_t *oldv = oldrec->value; igraph_vector_bool_t *newv = igraph_Calloc(1, igraph_vector_bool_t); long int newlen = igraph_vector_ptr_size(merges); long int i; if (!newv) { IGRAPH_ERROR("Cannot combine attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newv); IGRAPH_CHECK(igraph_vector_bool_init(newv, newlen)); IGRAPH_FINALLY(igraph_vector_bool_destroy, newv); RNG_BEGIN(); for (i = 0; i < newlen; i++) { igraph_vector_t *idx = VECTOR(*merges)[i]; long int n = igraph_vector_size(idx); if (n == 0) { VECTOR(*newv)[i] = 0; } else if (n == 1) { VECTOR(*newv)[i] = VECTOR(*oldv)[ (long int) VECTOR(*idx)[0] ]; } else { long int r = RNG_INTEGER(0, n - 1); VECTOR(*newv)[i] = VECTOR(*oldv)[ (long int) VECTOR(*idx)[r] ]; } } RNG_END(); IGRAPH_FINALLY_CLEAN(2); newrec->value = newv; return 0; } int igraph_i_cattributes_cb_first(const igraph_attribute_record_t *oldrec, igraph_attribute_record_t * newrec, const igraph_vector_ptr_t *merges) { const igraph_vector_bool_t *oldv = oldrec->value; igraph_vector_bool_t *newv = igraph_Calloc(1, igraph_vector_bool_t); long int newlen = igraph_vector_ptr_size(merges); long int i; if (!newv) { IGRAPH_ERROR("Cannot combine attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newv); IGRAPH_CHECK(igraph_vector_bool_init(newv, newlen)); IGRAPH_FINALLY(igraph_vector_bool_destroy, newv); for (i = 0; i < newlen; i++) { igraph_vector_t *idx = VECTOR(*merges)[i]; long int n = igraph_vector_size(idx); if (n == 0) { VECTOR(*newv)[i] = 0; } else { VECTOR(*newv)[i] = VECTOR(*oldv)[ (long int) VECTOR(*idx)[0] ]; } } IGRAPH_FINALLY_CLEAN(2); newrec->value = newv; return 0; } int igraph_i_cattributes_cb_last(const igraph_attribute_record_t *oldrec, igraph_attribute_record_t * newrec, const igraph_vector_ptr_t *merges) { const igraph_vector_bool_t *oldv = oldrec->value; igraph_vector_bool_t *newv = igraph_Calloc(1, igraph_vector_bool_t); long int newlen = igraph_vector_ptr_size(merges); long int i; if (!newv) { IGRAPH_ERROR("Cannot combine attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newv); IGRAPH_CHECK(igraph_vector_bool_init(newv, newlen)); IGRAPH_FINALLY(igraph_vector_bool_destroy, newv); for (i = 0; i < newlen; i++) { igraph_vector_t *idx = VECTOR(*merges)[i]; long int n = igraph_vector_size(idx); if (n == 0) { VECTOR(*newv)[i] = 0; } else { VECTOR(*newv)[i] = VECTOR(*oldv)[ (long int) VECTOR(*idx)[n - 1] ]; } } IGRAPH_FINALLY_CLEAN(2); newrec->value = newv; return 0; } int igraph_i_cattributes_cb_all_is_true(const igraph_attribute_record_t *oldrec, igraph_attribute_record_t * newrec, const igraph_vector_ptr_t *merges) { const igraph_vector_bool_t *oldv = oldrec->value; igraph_vector_bool_t *newv = igraph_Calloc(1, igraph_vector_bool_t); long int newlen = igraph_vector_ptr_size(merges); long int i, j, n, x; if (!newv) { IGRAPH_ERROR("Cannot combine attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newv); IGRAPH_CHECK(igraph_vector_bool_init(newv, newlen)); IGRAPH_FINALLY(igraph_vector_bool_destroy, newv); for (i = 0; i < newlen; i++) { igraph_vector_t *idx = VECTOR(*merges)[i]; n = igraph_vector_size(idx); VECTOR(*newv)[i] = 1; for (j = 0; j < n; j++) { x = (long int) VECTOR(*idx)[j]; if (!VECTOR(*oldv)[x]) { VECTOR(*newv)[i] = 0; break; } } } IGRAPH_FINALLY_CLEAN(2); newrec->value = newv; return 0; } int igraph_i_cattributes_cb_any_is_true(const igraph_attribute_record_t *oldrec, igraph_attribute_record_t * newrec, const igraph_vector_ptr_t *merges) { const igraph_vector_bool_t *oldv = oldrec->value; igraph_vector_bool_t *newv = igraph_Calloc(1, igraph_vector_bool_t); long int newlen = igraph_vector_ptr_size(merges); long int i, j, n, x; if (!newv) { IGRAPH_ERROR("Cannot combine attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newv); IGRAPH_CHECK(igraph_vector_bool_init(newv, newlen)); IGRAPH_FINALLY(igraph_vector_bool_destroy, newv); for (i = 0; i < newlen; i++) { igraph_vector_t *idx = VECTOR(*merges)[i]; n = igraph_vector_size(idx); VECTOR(*newv)[i] = 0; for (j = 0; j < n; j++) { x = (long int) VECTOR(*idx)[j]; if (VECTOR(*oldv)[x]) { VECTOR(*newv)[i] = 1; break; } } } IGRAPH_FINALLY_CLEAN(2); newrec->value = newv; return 0; } int igraph_i_cattributes_cb_majority(const igraph_attribute_record_t *oldrec, igraph_attribute_record_t * newrec, const igraph_vector_ptr_t *merges) { const igraph_vector_bool_t *oldv = oldrec->value; igraph_vector_bool_t *newv = igraph_Calloc(1, igraph_vector_bool_t); long int newlen = igraph_vector_ptr_size(merges); long int i, j, n, x, num_trues; if (!newv) { IGRAPH_ERROR("Cannot combine attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newv); IGRAPH_CHECK(igraph_vector_bool_init(newv, newlen)); IGRAPH_FINALLY(igraph_vector_bool_destroy, newv); RNG_BEGIN(); for (i = 0; i < newlen; i++) { igraph_vector_t *idx = VECTOR(*merges)[i]; n = igraph_vector_size(idx); num_trues = 0; for (j = 0; j < n; j++) { x = (long int) VECTOR(*idx)[j]; if (VECTOR(*oldv)[x]) { num_trues++; } } if (n % 2 != 0) { VECTOR(*newv)[i] = (num_trues > n / 2); } else { if (num_trues == n / 2) { VECTOR(*newv)[i] = (RNG_UNIF01() < 0.5); } else { VECTOR(*newv)[i] = (num_trues > n / 2); } } } RNG_END(); IGRAPH_FINALLY_CLEAN(2); newrec->value = newv; return 0; } int igraph_i_cattributes_cb_func(const igraph_attribute_record_t *oldrec, igraph_attribute_record_t *newrec, const igraph_vector_ptr_t *merges, igraph_cattributes_combine_bool_t *func) { const igraph_vector_bool_t *oldv = oldrec->value; long int newlen = igraph_vector_ptr_size(merges); long int i; igraph_vector_bool_t *newv = igraph_Calloc(1, igraph_vector_bool_t); igraph_vector_bool_t values; if (!newv) { IGRAPH_ERROR("Cannot combine attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newv); IGRAPH_CHECK(igraph_vector_bool_init(newv, newlen)); IGRAPH_FINALLY(igraph_vector_bool_destroy, newv); IGRAPH_CHECK(igraph_vector_bool_init(&values, 0)); IGRAPH_FINALLY(igraph_vector_bool_destroy, newv); for (i = 0; i < newlen; i++) { igraph_vector_t *idx = VECTOR(*merges)[i]; long int j, n = igraph_vector_size(idx); igraph_bool_t res; IGRAPH_CHECK(igraph_vector_bool_resize(&values, n)); for (j = 0; j < n; j++) { long int x = (long int) VECTOR(*idx)[j]; VECTOR(values)[j] = VECTOR(*oldv)[x]; } IGRAPH_CHECK(func(&values, &res)); VECTOR(*newv)[i] = res; } igraph_vector_bool_destroy(&values); IGRAPH_FINALLY_CLEAN(3); newrec->value = newv; return 0; } int igraph_i_cattributes_sn_random(const igraph_attribute_record_t *oldrec, igraph_attribute_record_t *newrec, const igraph_vector_ptr_t *merges) { const igraph_strvector_t *oldv = oldrec->value; long int newlen = igraph_vector_ptr_size(merges); long int i; igraph_strvector_t *newv = igraph_Calloc(1, igraph_strvector_t); if (!newv) { IGRAPH_ERROR("Cannot combine attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newv); IGRAPH_CHECK(igraph_strvector_init(newv, newlen)); IGRAPH_FINALLY(igraph_strvector_destroy, newv); RNG_BEGIN(); for (i = 0; i < newlen; i++) { igraph_vector_t *idx = VECTOR(*merges)[i]; long int n = igraph_vector_size(idx); char *tmp; if (n == 0) { IGRAPH_CHECK(igraph_strvector_set(newv, i, "")); } else if (n == 1) { igraph_strvector_get(oldv, 0, &tmp); IGRAPH_CHECK(igraph_strvector_set(newv, i, tmp)); } else { long int r = RNG_INTEGER(0, n - 1); igraph_strvector_get(oldv, r, &tmp); IGRAPH_CHECK(igraph_strvector_set(newv, i, tmp)); } } RNG_END(); IGRAPH_FINALLY_CLEAN(2); newrec->value = newv; return 0; } int igraph_i_cattributes_sn_first(const igraph_attribute_record_t *oldrec, igraph_attribute_record_t *newrec, const igraph_vector_ptr_t *merges) { const igraph_strvector_t *oldv = oldrec->value; long int i, newlen = igraph_vector_ptr_size(merges); igraph_strvector_t *newv = igraph_Calloc(1, igraph_strvector_t); if (!newv) { IGRAPH_ERROR("Cannot combine attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newv); IGRAPH_CHECK(igraph_strvector_init(newv, newlen)); IGRAPH_FINALLY(igraph_strvector_destroy, newv); for (i = 0; i < newlen; i++) { igraph_vector_t *idx = VECTOR(*merges)[i]; long int n = igraph_vector_size(idx); if (n == 0) { IGRAPH_CHECK(igraph_strvector_set(newv, i, "")); } else { char *tmp; igraph_strvector_get(oldv, (long int) VECTOR(*idx)[0], &tmp); IGRAPH_CHECK(igraph_strvector_set(newv, i, tmp)); } } IGRAPH_FINALLY_CLEAN(2); newrec->value = newv; return 0; } int igraph_i_cattributes_sn_last(const igraph_attribute_record_t *oldrec, igraph_attribute_record_t *newrec, const igraph_vector_ptr_t *merges) { const igraph_strvector_t *oldv = oldrec->value; long int i, newlen = igraph_vector_ptr_size(merges); igraph_strvector_t *newv = igraph_Calloc(1, igraph_strvector_t); if (!newv) { IGRAPH_ERROR("Cannot combine attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newv); IGRAPH_CHECK(igraph_strvector_init(newv, newlen)); IGRAPH_FINALLY(igraph_strvector_destroy, newv); for (i = 0; i < newlen; i++) { igraph_vector_t *idx = VECTOR(*merges)[i]; long int n = igraph_vector_size(idx); if (n == 0) { IGRAPH_CHECK(igraph_strvector_set(newv, i, "")); } else { char *tmp; igraph_strvector_get(oldv, (long int) VECTOR(*idx)[n - 1], &tmp); IGRAPH_CHECK(igraph_strvector_set(newv, i, tmp)); } } IGRAPH_FINALLY_CLEAN(2); newrec->value = newv; return 0; } int igraph_i_cattributes_sn_concat(const igraph_attribute_record_t *oldrec, igraph_attribute_record_t *newrec, const igraph_vector_ptr_t *merges) { const igraph_strvector_t *oldv = oldrec->value; long int i, newlen = igraph_vector_ptr_size(merges); igraph_strvector_t *newv = igraph_Calloc(1, igraph_strvector_t); if (!newv) { IGRAPH_ERROR("Cannot combine attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newv); IGRAPH_CHECK(igraph_strvector_init(newv, newlen)); IGRAPH_FINALLY(igraph_strvector_destroy, newv); for (i = 0; i < newlen; i++) { igraph_vector_t *idx = VECTOR(*merges)[i]; long int j, n = igraph_vector_size(idx); size_t len = 0; char *tmp, *tmp2; for (j = 0; j < n; j++) { igraph_strvector_get(oldv, j, &tmp); len += strlen(tmp); } tmp2 = igraph_Calloc(len + 1, char); if (!tmp2) { IGRAPH_ERROR("Cannot combine attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, tmp2); len = 0; for (j = 0; j < n; j++) { igraph_strvector_get(oldv, j, &tmp); strcpy(tmp2 + len, tmp); len += strlen(tmp); } IGRAPH_CHECK(igraph_strvector_set(newv, i, tmp2)); igraph_Free(tmp2); IGRAPH_FINALLY_CLEAN(1); } IGRAPH_FINALLY_CLEAN(2); newrec->value = newv; return 0; } int igraph_i_cattributes_sn_func(const igraph_attribute_record_t *oldrec, igraph_attribute_record_t *newrec, const igraph_vector_ptr_t *merges, igraph_cattributes_combine_str_t *func) { const igraph_strvector_t *oldv = oldrec->value; long int newlen = igraph_vector_ptr_size(merges); long int i; igraph_strvector_t *newv = igraph_Calloc(1, igraph_strvector_t); igraph_strvector_t values; if (!newv) { IGRAPH_ERROR("Cannot combine attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newv); IGRAPH_CHECK(igraph_strvector_init(newv, newlen)); IGRAPH_FINALLY(igraph_strvector_destroy, newv); IGRAPH_CHECK(igraph_strvector_init(newv, 0)); IGRAPH_FINALLY(igraph_strvector_destroy, &values); for (i = 0; i < newlen; i++) { igraph_vector_t *idx = VECTOR(*merges)[i]; long int j, n = igraph_vector_size(idx); char *res; IGRAPH_CHECK(igraph_strvector_resize(&values, n)); for (j = 0; j < n; j++) { long int x = (long int) VECTOR(*idx)[j]; char *elem; igraph_strvector_get(oldv, x, &elem); IGRAPH_CHECK(igraph_strvector_set(newv, j, elem)); } IGRAPH_CHECK(func(&values, &res)); IGRAPH_FINALLY(igraph_free, res); IGRAPH_CHECK(igraph_strvector_set(newv, i, res)); IGRAPH_FINALLY_CLEAN(1); igraph_Free(res); } igraph_strvector_destroy(&values); IGRAPH_FINALLY_CLEAN(3); newrec->value = newv; return 0; } int igraph_i_cattribute_combine_vertices(const igraph_t *graph, igraph_t *newgraph, const igraph_vector_ptr_t *merges, const igraph_attribute_combination_t *comb) { igraph_i_cattributes_t *attr = graph->attr; igraph_i_cattributes_t *toattr = newgraph->attr; igraph_vector_ptr_t *val = &attr->val; igraph_vector_ptr_t *new_val = &toattr->val; long int valno = igraph_vector_ptr_size(val); long int i, j, keepno = 0; int *TODO; igraph_function_pointer_t *funcs; TODO = igraph_Calloc(valno, int); if (!TODO) { IGRAPH_ERROR("Cannot combine vertex attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, TODO); funcs = igraph_Calloc(valno, igraph_function_pointer_t); if (!funcs) { IGRAPH_ERROR("Cannot combine vertex attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, funcs); for (i = 0; i < valno; i++) { igraph_attribute_record_t *oldrec = VECTOR(*val)[i]; const char *name = oldrec->name; igraph_attribute_combination_type_t todo; igraph_function_pointer_t voidfunc; igraph_attribute_combination_query(comb, name, &todo, &voidfunc); TODO[i] = todo; funcs[i] = voidfunc; if (todo != IGRAPH_ATTRIBUTE_COMBINE_IGNORE) { keepno++; } } IGRAPH_CHECK(igraph_vector_ptr_resize(new_val, keepno)); IGRAPH_FINALLY(igraph_i_cattribute_permute_free, new_val); for (i = 0, j = 0; i < valno; i++) { igraph_attribute_record_t *newrec, *oldrec = VECTOR(*val)[i]; const char *name = oldrec->name; igraph_attribute_combination_type_t todo = (igraph_attribute_combination_type_t) (TODO[i]); igraph_attribute_type_t type = oldrec->type; igraph_cattributes_combine_num_t *numfunc = (igraph_cattributes_combine_num_t*) funcs[i]; igraph_cattributes_combine_str_t *strfunc = (igraph_cattributes_combine_str_t*) funcs[i]; igraph_cattributes_combine_bool_t *boolfunc = (igraph_cattributes_combine_bool_t*) funcs[i]; if (todo == IGRAPH_ATTRIBUTE_COMBINE_DEFAULT || todo == IGRAPH_ATTRIBUTE_COMBINE_IGNORE) { continue; } newrec = igraph_Calloc(1, igraph_attribute_record_t); if (!newrec) { IGRAPH_ERROR("Cannot combine vertex attributes", IGRAPH_ENOMEM); } newrec->name = strdup(name); newrec->type = type; VECTOR(*new_val)[j] = newrec; if (type == IGRAPH_ATTRIBUTE_NUMERIC) { switch (todo) { case IGRAPH_ATTRIBUTE_COMBINE_FUNCTION: IGRAPH_CHECK(igraph_i_cattributes_cn_func(oldrec, newrec, merges, numfunc)); break; case IGRAPH_ATTRIBUTE_COMBINE_SUM: IGRAPH_CHECK(igraph_i_cattributes_cn_sum(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_PROD: IGRAPH_CHECK(igraph_i_cattributes_cn_prod(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_MIN: IGRAPH_CHECK(igraph_i_cattributes_cn_min(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_MAX: IGRAPH_CHECK(igraph_i_cattributes_cn_max(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_RANDOM: IGRAPH_CHECK(igraph_i_cattributes_cn_random(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_FIRST: IGRAPH_CHECK(igraph_i_cattributes_cn_first(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_LAST: IGRAPH_CHECK(igraph_i_cattributes_cn_last(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_MEAN: IGRAPH_CHECK(igraph_i_cattributes_cn_mean(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_MEDIAN: IGRAPH_ERROR("Median calculation not implemented", IGRAPH_UNIMPLEMENTED); break; case IGRAPH_ATTRIBUTE_COMBINE_CONCAT: IGRAPH_ERROR("Cannot concatenate numeric attributes", IGRAPH_EATTRCOMBINE); break; default: IGRAPH_ERROR("Unknown attribute_combination", IGRAPH_UNIMPLEMENTED); break; } } else if (type == IGRAPH_ATTRIBUTE_BOOLEAN) { switch (todo) { case IGRAPH_ATTRIBUTE_COMBINE_FUNCTION: IGRAPH_CHECK(igraph_i_cattributes_cb_func(oldrec, newrec, merges, boolfunc)); break; case IGRAPH_ATTRIBUTE_COMBINE_SUM: case IGRAPH_ATTRIBUTE_COMBINE_MAX: IGRAPH_CHECK(igraph_i_cattributes_cb_any_is_true(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_PROD: case IGRAPH_ATTRIBUTE_COMBINE_MIN: IGRAPH_CHECK(igraph_i_cattributes_cb_all_is_true(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_MEAN: case IGRAPH_ATTRIBUTE_COMBINE_MEDIAN: IGRAPH_CHECK(igraph_i_cattributes_cb_majority(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_RANDOM: IGRAPH_CHECK(igraph_i_cattributes_cb_random(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_FIRST: IGRAPH_CHECK(igraph_i_cattributes_cb_first(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_LAST: IGRAPH_CHECK(igraph_i_cattributes_cb_last(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_CONCAT: IGRAPH_ERROR("Cannot calculate concatenation of Booleans", IGRAPH_EATTRCOMBINE); break; default: IGRAPH_ERROR("Unknown attribute_combination", IGRAPH_UNIMPLEMENTED); break; } } else if (type == IGRAPH_ATTRIBUTE_STRING) { switch (todo) { case IGRAPH_ATTRIBUTE_COMBINE_FUNCTION: IGRAPH_CHECK(igraph_i_cattributes_sn_func(oldrec, newrec, merges, strfunc)); break; case IGRAPH_ATTRIBUTE_COMBINE_SUM: IGRAPH_ERROR("Cannot sum strings", IGRAPH_EATTRCOMBINE); break; case IGRAPH_ATTRIBUTE_COMBINE_PROD: IGRAPH_ERROR("Cannot multiply strings", IGRAPH_EATTRCOMBINE); break; case IGRAPH_ATTRIBUTE_COMBINE_MIN: IGRAPH_ERROR("Cannot find minimum of strings", IGRAPH_EATTRCOMBINE); break; case IGRAPH_ATTRIBUTE_COMBINE_MAX: IGRAPH_ERROR("Cannot find maximum of strings", IGRAPH_EATTRCOMBINE); break; case IGRAPH_ATTRIBUTE_COMBINE_MEAN: IGRAPH_ERROR("Cannot calculate mean of strings", IGRAPH_EATTRCOMBINE); break; case IGRAPH_ATTRIBUTE_COMBINE_MEDIAN: IGRAPH_ERROR("Cannot calculate median of strings", IGRAPH_EATTRCOMBINE); break; case IGRAPH_ATTRIBUTE_COMBINE_RANDOM: IGRAPH_CHECK(igraph_i_cattributes_sn_random(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_FIRST: IGRAPH_CHECK(igraph_i_cattributes_sn_first(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_LAST: IGRAPH_CHECK(igraph_i_cattributes_sn_last(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_CONCAT: IGRAPH_CHECK(igraph_i_cattributes_sn_concat(oldrec, newrec, merges)); break; default: IGRAPH_ERROR("Unknown attribute_combination", IGRAPH_UNIMPLEMENTED); break; } } else { IGRAPH_ERROR("Unknown attribute type, this should not happen", IGRAPH_UNIMPLEMENTED); } j++; } igraph_free(funcs); igraph_free(TODO); IGRAPH_FINALLY_CLEAN(2); return 0; } /* void igraph_i_cattribute_delete_vertices(igraph_t *graph, */ /* const igraph_vector_t *eidx, */ /* const igraph_vector_t *vidx) { */ /* igraph_i_cattributes_t *attr=graph->attr; */ /* igraph_vector_ptr_t *val=&attr->val; */ /* igraph_vector_ptr_t *eal=&attr->eal; */ /* long int valno=igraph_vector_ptr_size(val); */ /* long int ealno=igraph_vector_ptr_size(eal); */ /* long int i; */ /* long int origlen, newlen; */ /* /\* Vertices *\/ */ /* origlen=igraph_vector_size(vidx); */ /* newlen=0; */ /* for (i=0; i0) { */ /* newlen++; */ /* } */ /* } */ /* for (i=0; itype; */ /* igraph_vector_t *num=(igraph_vector_t*)oldrec->value; */ /* igraph_strvector_t *str=(igraph_strvector_t*)oldrec->value; */ /* switch (type) { */ /* case IGRAPH_ATTRIBUTE_NUMERIC: */ /* igraph_vector_permdelete(num, vidx, origlen-newlen); */ /* break; */ /* case IGRAPH_ATTRIBUTE_STRING: */ /* igraph_strvector_permdelete(str, vidx, origlen-newlen); */ /* break; */ /* default: */ /* IGRAPH_WARNING("Unknown vertex attribute ignored"); */ /* } */ /* } */ /* /\* Edges *\/ */ /* origlen=igraph_vector_size(eidx); */ /* newlen=0; */ /* for (i=0; i0) { */ /* newlen++; */ /* } */ /* } */ /* for (i=0; itype; */ /* igraph_vector_t *num=(igraph_vector_t*)oldrec->value; */ /* igraph_strvector_t *str=(igraph_strvector_t*)oldrec->value; */ /* switch (type) { */ /* case IGRAPH_ATTRIBUTE_NUMERIC: */ /* igraph_vector_permdelete(num, eidx, origlen-newlen); */ /* break; */ /* case IGRAPH_ATTRIBUTE_STRING: */ /* igraph_strvector_permdelete(str, eidx, origlen-newlen); */ /* break; */ /* default: */ /* IGRAPH_WARNING("Unknown edge attribute ignored"); */ /* } */ /* } */ /* } */ int igraph_i_cattribute_add_edges(igraph_t *graph, const igraph_vector_t *edges, igraph_vector_ptr_t *nattr) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *eal = &attr->eal; long int ealno = igraph_vector_ptr_size(eal); long int ne = igraph_vector_size(edges) / 2; long int origlen = igraph_ecount(graph) - ne; long int nattrno = nattr == 0 ? 0 : igraph_vector_ptr_size(nattr); igraph_vector_t news; long int newattrs, i; /* First add the new attributes if any */ newattrs = 0; IGRAPH_VECTOR_INIT_FINALLY(&news, 0); for (i = 0; i < nattrno; i++) { igraph_attribute_record_t *nattr_entry = VECTOR(*nattr)[i]; const char *nname = nattr_entry->name; long int j; igraph_bool_t l = igraph_i_cattribute_find(eal, nname, &j); if (!l) { newattrs++; IGRAPH_CHECK(igraph_vector_push_back(&news, i)); } else { /* check types */ if (nattr_entry->type != ((igraph_attribute_record_t*)VECTOR(*eal)[j])->type) { IGRAPH_ERROR("You cannot mix attribute types", IGRAPH_EINVAL); } } } /* Add NA/empty string vectors for the existing vertices */ if (newattrs != 0) { for (i = 0; i < newattrs; i++) { igraph_attribute_record_t *tmp = VECTOR(*nattr)[(long int)VECTOR(news)[i]]; igraph_attribute_record_t *newrec = igraph_Calloc(1, igraph_attribute_record_t); igraph_attribute_type_t type = tmp->type; if (!newrec) { IGRAPH_ERROR("Cannot add attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newrec); newrec->type = type; newrec->name = strdup(tmp->name); if (!newrec->name) { IGRAPH_ERROR("Cannot add attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (char*)newrec->name); if (type == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_vector_t *newnum = igraph_Calloc(1, igraph_vector_t); if (!newnum) { IGRAPH_ERROR("Cannot add attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newnum); IGRAPH_VECTOR_INIT_FINALLY(newnum, origlen); newrec->value = newnum; igraph_vector_fill(newnum, IGRAPH_NAN); } else if (type == IGRAPH_ATTRIBUTE_BOOLEAN) { igraph_vector_bool_t *newbool = igraph_Calloc(1, igraph_vector_bool_t); if (!newbool) { IGRAPH_ERROR("Cannot add attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newbool); IGRAPH_CHECK(igraph_vector_bool_init(newbool, origlen)); IGRAPH_FINALLY(igraph_vector_bool_destroy, newbool); newrec->value = newbool; igraph_vector_bool_fill(newbool, 0); } else if (type == IGRAPH_ATTRIBUTE_STRING) { igraph_strvector_t *newstr = igraph_Calloc(1, igraph_strvector_t); if (!newstr) { IGRAPH_ERROR("Cannot add attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newstr); IGRAPH_STRVECTOR_INIT_FINALLY(newstr, origlen); newrec->value = newstr; } IGRAPH_CHECK(igraph_vector_ptr_push_back(eal, newrec)); IGRAPH_FINALLY_CLEAN(4); } ealno = igraph_vector_ptr_size(eal); } /* Now append the new values */ for (i = 0; i < ealno; i++) { igraph_attribute_record_t *oldrec = VECTOR(*eal)[i]; igraph_attribute_record_t *newrec = 0; const char *name = oldrec->name; long int j; igraph_bool_t l = 0; if (nattr) { l = igraph_i_cattribute_find(nattr, name, &j); } if (l) { /* This attribute is present in nattr */ igraph_vector_t *oldnum, *newnum; igraph_strvector_t *oldstr, *newstr; igraph_vector_bool_t *oldbool, *newbool; newrec = VECTOR(*nattr)[j]; oldnum = (igraph_vector_t*)oldrec->value; newnum = (igraph_vector_t*)newrec->value; oldstr = (igraph_strvector_t*)oldrec->value; newstr = (igraph_strvector_t*)newrec->value; oldbool = (igraph_vector_bool_t*)oldrec->value; newbool = (igraph_vector_bool_t*)newrec->value; if (oldrec->type != newrec->type) { IGRAPH_ERROR("Attribute types do not match", IGRAPH_EINVAL); } switch (oldrec->type) { case IGRAPH_ATTRIBUTE_NUMERIC: if (ne != igraph_vector_size(newnum)) { IGRAPH_ERROR("Invalid numeric attribute length", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_vector_append(oldnum, newnum)); break; case IGRAPH_ATTRIBUTE_STRING: if (ne != igraph_strvector_size(newstr)) { IGRAPH_ERROR("Invalid string attribute length", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_strvector_append(oldstr, newstr)); break; case IGRAPH_ATTRIBUTE_BOOLEAN: if (ne != igraph_vector_bool_size(newbool)) { IGRAPH_ERROR("Invalid Boolean attribute length", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_vector_bool_append(oldbool, newbool)); break; default: IGRAPH_WARNING("Invalid attribute type"); break; } } else { /* No such attribute, append NA's */ igraph_vector_t *oldnum = (igraph_vector_t *)oldrec->value; igraph_strvector_t *oldstr = (igraph_strvector_t*)oldrec->value; igraph_vector_bool_t *oldbool = (igraph_vector_bool_t *)oldrec->value; switch (oldrec->type) { case IGRAPH_ATTRIBUTE_NUMERIC: IGRAPH_CHECK(igraph_vector_resize(oldnum, origlen + ne)); for (j = origlen; j < origlen + ne; j++) { VECTOR(*oldnum)[j] = IGRAPH_NAN; } break; case IGRAPH_ATTRIBUTE_STRING: IGRAPH_CHECK(igraph_strvector_resize(oldstr, origlen + ne)); break; case IGRAPH_ATTRIBUTE_BOOLEAN: IGRAPH_CHECK(igraph_vector_bool_resize(oldbool, origlen + ne)); for (j = origlen; j < origlen + ne; j++) { VECTOR(*oldbool)[j] = 0; } break; default: IGRAPH_WARNING("Invalid attribute type"); break; } } } igraph_vector_destroy(&news); IGRAPH_FINALLY_CLEAN(1); return 0; } /* void igraph_i_cattribute_delete_edges(igraph_t *graph, const igraph_vector_t *idx) { */ /* igraph_i_cattributes_t *attr=graph->attr; */ /* igraph_vector_ptr_t *eal=&attr->eal; */ /* long int ealno=igraph_vector_ptr_size(eal); */ /* long int i; */ /* long int origlen=igraph_vector_size(idx), newlen; */ /* newlen=0; */ /* for (i=0; i0) { */ /* newlen++; */ /* } */ /* } */ /* for (i=0; itype; */ /* igraph_vector_t *num=(igraph_vector_t*)oldrec->value; */ /* igraph_strvector_t *str=(igraph_strvector_t*)oldrec->value; */ /* switch (type) { */ /* case IGRAPH_ATTRIBUTE_NUMERIC: */ /* igraph_vector_permdelete(num, idx, origlen-newlen); */ /* break; */ /* case IGRAPH_ATTRIBUTE_STRING: */ /* igraph_strvector_permdelete(str, idx, origlen-newlen); */ /* break; */ /* default: */ /* IGRAPH_WARNING("Unknown edge attribute ignored"); */ /* } */ /* } */ /* } */ int igraph_i_cattribute_permute_edges(const igraph_t *graph, igraph_t *newgraph, const igraph_vector_t *idx) { if (graph == newgraph) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *eal = &attr->eal; long int ealno = igraph_vector_ptr_size(eal); long int i; for (i = 0; i < ealno; i++) { igraph_attribute_record_t *oldrec = VECTOR(*eal)[i]; igraph_attribute_type_t type = oldrec->type; igraph_vector_t *num, *newnum; igraph_strvector_t *str, *newstr; igraph_vector_bool_t *oldbool, *newbool; switch (type) { case IGRAPH_ATTRIBUTE_NUMERIC: num = (igraph_vector_t*) oldrec->value; newnum = igraph_Calloc(1, igraph_vector_t); if (!newnum) { IGRAPH_ERROR("Cannot permute edge attributes", IGRAPH_ENOMEM); } IGRAPH_VECTOR_INIT_FINALLY(newnum, 0); igraph_vector_index(num, newnum, idx); oldrec->value = newnum; igraph_vector_destroy(num); igraph_Free(num); IGRAPH_FINALLY_CLEAN(1); break; case IGRAPH_ATTRIBUTE_BOOLEAN: oldbool = (igraph_vector_bool_t*) oldrec->value; newbool = igraph_Calloc(1, igraph_vector_bool_t); if (!newbool) { IGRAPH_ERROR("Cannot permute edge attributes", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_bool_init(newbool, 0)); IGRAPH_FINALLY(igraph_vector_bool_destroy, newbool); igraph_vector_bool_index(oldbool, newbool, idx); oldrec->value = newbool; igraph_vector_bool_destroy(oldbool); igraph_Free(oldbool); IGRAPH_FINALLY_CLEAN(1); break; case IGRAPH_ATTRIBUTE_STRING: str = (igraph_strvector_t*)oldrec->value; newstr = igraph_Calloc(1, igraph_strvector_t); if (!newstr) { IGRAPH_ERROR("Cannot permute edge attributes", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_strvector_init(newstr, 0)); IGRAPH_FINALLY(igraph_strvector_destroy, newstr); igraph_strvector_index(str, newstr, idx); oldrec->value = newstr; igraph_strvector_destroy(str); igraph_Free(str); IGRAPH_FINALLY_CLEAN(1); break; default: IGRAPH_WARNING("Unknown edge attribute ignored"); } } } else { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *eal = &attr->eal; long int ealno = igraph_vector_ptr_size(eal); long int i; /* New edge attributes */ igraph_i_cattributes_t *new_attr = newgraph->attr; igraph_vector_ptr_t *new_eal = &new_attr->eal; IGRAPH_CHECK(igraph_vector_ptr_resize(new_eal, ealno)); IGRAPH_FINALLY(igraph_i_cattribute_permute_free, new_eal); for (i = 0; i < ealno; i++) { igraph_attribute_record_t *oldrec = VECTOR(*eal)[i]; igraph_attribute_type_t type = oldrec->type; igraph_vector_t *num, *newnum; igraph_strvector_t *str, *newstr; igraph_vector_bool_t *oldbool, *newbool; /* The record itself */ igraph_attribute_record_t *new_rec = igraph_Calloc(1, igraph_attribute_record_t); if (!new_rec) { IGRAPH_ERROR("Cannot create edge attributes", IGRAPH_ENOMEM); } new_rec->name = strdup(oldrec->name); new_rec->type = oldrec->type; VECTOR(*new_eal)[i] = new_rec; switch (type) { case IGRAPH_ATTRIBUTE_NUMERIC: num = (igraph_vector_t*) oldrec->value; newnum = igraph_Calloc(1, igraph_vector_t); if (!newnum) { IGRAPH_ERROR("Cannot permute edge attributes", IGRAPH_ENOMEM); } IGRAPH_VECTOR_INIT_FINALLY(newnum, 0); igraph_vector_index(num, newnum, idx); new_rec->value = newnum; IGRAPH_FINALLY_CLEAN(1); break; case IGRAPH_ATTRIBUTE_STRING: str = (igraph_strvector_t*)oldrec->value; newstr = igraph_Calloc(1, igraph_strvector_t); if (!newstr) { IGRAPH_ERROR("Cannot permute edge attributes", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_strvector_init(newstr, 0)); IGRAPH_FINALLY(igraph_strvector_destroy, newstr); igraph_strvector_index(str, newstr, idx); new_rec->value = newstr; IGRAPH_FINALLY_CLEAN(1); break; case IGRAPH_ATTRIBUTE_BOOLEAN: oldbool = (igraph_vector_bool_t*) oldrec->value; newbool = igraph_Calloc(1, igraph_vector_bool_t); if (!newbool) { IGRAPH_ERROR("Cannot permute edge attributes", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_bool_init(newbool, 0)); IGRAPH_FINALLY(igraph_vector_bool_destroy, newbool); igraph_vector_bool_index(oldbool, newbool, idx); new_rec->value = newbool; IGRAPH_FINALLY_CLEAN(1); break; default: IGRAPH_WARNING("Unknown edge attribute ignored"); } } IGRAPH_FINALLY_CLEAN(1); } return 0; } int igraph_i_cattribute_combine_edges(const igraph_t *graph, igraph_t *newgraph, const igraph_vector_ptr_t *merges, const igraph_attribute_combination_t *comb) { igraph_i_cattributes_t *attr = graph->attr; igraph_i_cattributes_t *toattr = newgraph->attr; igraph_vector_ptr_t *eal = &attr->eal; igraph_vector_ptr_t *new_eal = &toattr->eal; long int ealno = igraph_vector_ptr_size(eal); long int i, j, keepno = 0; int *TODO; igraph_function_pointer_t *funcs; TODO = igraph_Calloc(ealno, int); if (!TODO) { IGRAPH_ERROR("Cannot combine edge attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, TODO); funcs = igraph_Calloc(ealno, igraph_function_pointer_t); if (!funcs) { IGRAPH_ERROR("Cannot combine edge attributes", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, funcs); for (i = 0; i < ealno; i++) { igraph_attribute_record_t *oldrec = VECTOR(*eal)[i]; const char *name = oldrec->name; igraph_attribute_combination_type_t todo; igraph_function_pointer_t voidfunc; igraph_attribute_combination_query(comb, name, &todo, &voidfunc); TODO[i] = todo; funcs[i] = voidfunc; if (todo != IGRAPH_ATTRIBUTE_COMBINE_IGNORE) { keepno++; } } IGRAPH_CHECK(igraph_vector_ptr_resize(new_eal, keepno)); IGRAPH_FINALLY(igraph_i_cattribute_permute_free, new_eal); for (i = 0, j = 0; i < ealno; i++) { igraph_attribute_record_t *newrec, *oldrec = VECTOR(*eal)[i]; const char *name = oldrec->name; igraph_attribute_combination_type_t todo = (igraph_attribute_combination_type_t) (TODO[i]); igraph_attribute_type_t type = oldrec->type; igraph_cattributes_combine_num_t *numfunc = (igraph_cattributes_combine_num_t*) funcs[i]; igraph_cattributes_combine_str_t *strfunc = (igraph_cattributes_combine_str_t*) funcs[i]; igraph_cattributes_combine_bool_t *boolfunc = (igraph_cattributes_combine_bool_t*) funcs[i]; if (todo == IGRAPH_ATTRIBUTE_COMBINE_DEFAULT || todo == IGRAPH_ATTRIBUTE_COMBINE_IGNORE) { continue; } newrec = igraph_Calloc(1, igraph_attribute_record_t); if (!newrec) { IGRAPH_ERROR("Cannot combine edge attributes", IGRAPH_ENOMEM); } newrec->name = strdup(name); newrec->type = type; VECTOR(*new_eal)[j] = newrec; if (type == IGRAPH_ATTRIBUTE_NUMERIC) { switch (todo) { case IGRAPH_ATTRIBUTE_COMBINE_FUNCTION: IGRAPH_CHECK(igraph_i_cattributes_cn_func(oldrec, newrec, merges, numfunc)); break; case IGRAPH_ATTRIBUTE_COMBINE_SUM: IGRAPH_CHECK(igraph_i_cattributes_cn_sum(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_PROD: IGRAPH_CHECK(igraph_i_cattributes_cn_prod(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_MIN: IGRAPH_CHECK(igraph_i_cattributes_cn_min(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_MAX: IGRAPH_CHECK(igraph_i_cattributes_cn_max(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_RANDOM: IGRAPH_CHECK(igraph_i_cattributes_cn_random(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_FIRST: IGRAPH_CHECK(igraph_i_cattributes_cn_first(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_LAST: IGRAPH_CHECK(igraph_i_cattributes_cn_last(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_MEAN: IGRAPH_CHECK(igraph_i_cattributes_cn_mean(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_MEDIAN: IGRAPH_ERROR("Median calculation not implemented", IGRAPH_UNIMPLEMENTED); break; case IGRAPH_ATTRIBUTE_COMBINE_CONCAT: IGRAPH_ERROR("Cannot concatenate numeric attributes", IGRAPH_EATTRCOMBINE); break; default: IGRAPH_ERROR("Unknown attribute_combination", IGRAPH_UNIMPLEMENTED); break; } } else if (type == IGRAPH_ATTRIBUTE_BOOLEAN) { switch (todo) { case IGRAPH_ATTRIBUTE_COMBINE_FUNCTION: IGRAPH_CHECK(igraph_i_cattributes_cb_func(oldrec, newrec, merges, boolfunc)); break; case IGRAPH_ATTRIBUTE_COMBINE_SUM: case IGRAPH_ATTRIBUTE_COMBINE_MAX: IGRAPH_CHECK(igraph_i_cattributes_cb_any_is_true(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_PROD: case IGRAPH_ATTRIBUTE_COMBINE_MIN: IGRAPH_CHECK(igraph_i_cattributes_cb_all_is_true(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_MEAN: case IGRAPH_ATTRIBUTE_COMBINE_MEDIAN: IGRAPH_CHECK(igraph_i_cattributes_cb_majority(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_RANDOM: IGRAPH_CHECK(igraph_i_cattributes_cb_random(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_FIRST: IGRAPH_CHECK(igraph_i_cattributes_cb_first(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_LAST: IGRAPH_CHECK(igraph_i_cattributes_cb_last(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_CONCAT: IGRAPH_ERROR("Cannot calculate concatenation of Booleans", IGRAPH_EATTRCOMBINE); break; default: IGRAPH_ERROR("Unknown attribute_combination", IGRAPH_UNIMPLEMENTED); break; } } else if (type == IGRAPH_ATTRIBUTE_STRING) { switch (todo) { case IGRAPH_ATTRIBUTE_COMBINE_FUNCTION: IGRAPH_CHECK(igraph_i_cattributes_sn_func(oldrec, newrec, merges, strfunc)); break; case IGRAPH_ATTRIBUTE_COMBINE_SUM: IGRAPH_ERROR("Cannot sum strings", IGRAPH_EATTRCOMBINE); break; case IGRAPH_ATTRIBUTE_COMBINE_PROD: IGRAPH_ERROR("Cannot multiply strings", IGRAPH_EATTRCOMBINE); break; case IGRAPH_ATTRIBUTE_COMBINE_MIN: IGRAPH_ERROR("Cannot find minimum of strings", IGRAPH_EATTRCOMBINE); break; case IGRAPH_ATTRIBUTE_COMBINE_MAX: IGRAPH_ERROR("Cannot find maximum of strings", IGRAPH_EATTRCOMBINE); break; case IGRAPH_ATTRIBUTE_COMBINE_MEAN: IGRAPH_ERROR("Cannot calculate mean of strings", IGRAPH_EATTRCOMBINE); break; case IGRAPH_ATTRIBUTE_COMBINE_MEDIAN: IGRAPH_ERROR("Cannot calculate median of strings", IGRAPH_EATTRCOMBINE); break; case IGRAPH_ATTRIBUTE_COMBINE_RANDOM: IGRAPH_CHECK(igraph_i_cattributes_sn_random(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_FIRST: IGRAPH_CHECK(igraph_i_cattributes_sn_first(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_LAST: IGRAPH_CHECK(igraph_i_cattributes_sn_last(oldrec, newrec, merges)); break; case IGRAPH_ATTRIBUTE_COMBINE_CONCAT: IGRAPH_CHECK(igraph_i_cattributes_sn_concat(oldrec, newrec, merges)); break; default: IGRAPH_ERROR("Unknown attribute_combination", IGRAPH_UNIMPLEMENTED); break; } } else { IGRAPH_ERROR("Unknown attribute type, this should not happen", IGRAPH_UNIMPLEMENTED); } j++; } igraph_free(funcs); igraph_free(TODO); IGRAPH_FINALLY_CLEAN(2); return 0; } int igraph_i_cattribute_get_info(const igraph_t *graph, igraph_strvector_t *gnames, igraph_vector_t *gtypes, igraph_strvector_t *vnames, igraph_vector_t *vtypes, igraph_strvector_t *enames, igraph_vector_t *etypes) { igraph_strvector_t *names[3] = { gnames, vnames, enames }; igraph_vector_t *types[3] = { gtypes, vtypes, etypes }; igraph_i_cattributes_t *at = graph->attr; igraph_vector_ptr_t *attr[3] = { &at->gal, &at->val, &at->eal }; long int i, j; for (i = 0; i < 3; i++) { igraph_strvector_t *n = names[i]; igraph_vector_t *t = types[i]; igraph_vector_ptr_t *al = attr[i]; long int len = igraph_vector_ptr_size(al); if (n) { IGRAPH_CHECK(igraph_strvector_resize(n, len)); } if (t) { IGRAPH_CHECK(igraph_vector_resize(t, len)); } for (j = 0; j < len; j++) { igraph_attribute_record_t *rec = VECTOR(*al)[j]; const char *name = rec->name; igraph_attribute_type_t type = rec->type; if (n) { IGRAPH_CHECK(igraph_strvector_set(n, j, name)); } if (t) { VECTOR(*t)[j] = type; } } } return 0; } igraph_bool_t igraph_i_cattribute_has_attr(const igraph_t *graph, igraph_attribute_elemtype_t type, const char *name) { igraph_i_cattributes_t *at = graph->attr; igraph_vector_ptr_t *attr[3] = { &at->gal, &at->val, &at->eal }; long int attrnum; switch (type) { case IGRAPH_ATTRIBUTE_GRAPH: attrnum = 0; break; case IGRAPH_ATTRIBUTE_VERTEX: attrnum = 1; break; case IGRAPH_ATTRIBUTE_EDGE: attrnum = 2; break; default: IGRAPH_ERROR("Unknown attribute element type", IGRAPH_EINVAL); break; } return igraph_i_cattribute_find(attr[attrnum], name, 0); } int igraph_i_cattribute_gettype(const igraph_t *graph, igraph_attribute_type_t *type, igraph_attribute_elemtype_t elemtype, const char *name) { long int attrnum; igraph_attribute_record_t *rec; igraph_i_cattributes_t *at = graph->attr; igraph_vector_ptr_t *attr[3] = { &at->gal, &at->val, &at->eal }; igraph_vector_ptr_t *al; long int j; igraph_bool_t l = 0; switch (elemtype) { case IGRAPH_ATTRIBUTE_GRAPH: attrnum = 0; break; case IGRAPH_ATTRIBUTE_VERTEX: attrnum = 1; break; case IGRAPH_ATTRIBUTE_EDGE: attrnum = 2; break; default: IGRAPH_ERROR("Unknown attribute element type", IGRAPH_EINVAL); break; } al = attr[attrnum]; l = igraph_i_cattribute_find(al, name, &j); if (!l) { IGRAPH_ERROR("Unknown attribute", IGRAPH_EINVAL); } rec = VECTOR(*al)[j]; *type = rec->type; return 0; } int igraph_i_cattribute_get_numeric_graph_attr(const igraph_t *graph, const char *name, igraph_vector_t *value) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *gal = &attr->gal; long int j; igraph_attribute_record_t *rec; igraph_vector_t *num; igraph_bool_t l = igraph_i_cattribute_find(gal, name, &j); if (!l) { IGRAPH_ERROR("Unknown attribute", IGRAPH_EINVAL); } rec = VECTOR(*gal)[j]; num = (igraph_vector_t*)rec->value; IGRAPH_CHECK(igraph_vector_resize(value, 1)); VECTOR(*value)[0] = VECTOR(*num)[0]; return 0; } int igraph_i_cattribute_get_bool_graph_attr(const igraph_t *graph, const char *name, igraph_vector_bool_t *value) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *gal = &attr->gal; long int j; igraph_attribute_record_t *rec; igraph_vector_bool_t *log; igraph_bool_t l = igraph_i_cattribute_find(gal, name, &j); if (!l) { IGRAPH_ERROR("Unknown attribute", IGRAPH_EINVAL); } rec = VECTOR(*gal)[j]; log = (igraph_vector_bool_t*)rec->value; IGRAPH_CHECK(igraph_vector_bool_resize(value, 1)); VECTOR(*value)[0] = VECTOR(*log)[0]; return 0; } int igraph_i_cattribute_get_string_graph_attr(const igraph_t *graph, const char *name, igraph_strvector_t *value) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *gal = &attr->gal; long int j; igraph_attribute_record_t *rec; igraph_strvector_t *str; igraph_bool_t l = igraph_i_cattribute_find(gal, name, &j); if (!l) { IGRAPH_ERROR("Unknown attribute", IGRAPH_EINVAL); } rec = VECTOR(*gal)[j]; str = (igraph_strvector_t*)rec->value; IGRAPH_CHECK(igraph_strvector_resize(value, 1)); IGRAPH_CHECK(igraph_strvector_set(value, 0, STR(*str, 0))); return 0; } int igraph_i_cattribute_get_numeric_vertex_attr(const igraph_t *graph, const char *name, igraph_vs_t vs, igraph_vector_t *value) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *val = &attr->val; long int j; igraph_attribute_record_t *rec; igraph_vector_t *num; igraph_bool_t l = igraph_i_cattribute_find(val, name, &j); if (!l) { IGRAPH_ERROR("Unknown attribute", IGRAPH_EINVAL); } rec = VECTOR(*val)[j]; num = (igraph_vector_t*)rec->value; if (igraph_vs_is_all(&vs)) { igraph_vector_clear(value); IGRAPH_CHECK(igraph_vector_append(value, num)); } else { igraph_vit_t it; long int i = 0; IGRAPH_CHECK(igraph_vit_create(graph, vs, &it)); IGRAPH_FINALLY(igraph_vit_destroy, &it); IGRAPH_CHECK(igraph_vector_resize(value, IGRAPH_VIT_SIZE(it))); for (; !IGRAPH_VIT_END(it); IGRAPH_VIT_NEXT(it), i++) { long int v = IGRAPH_VIT_GET(it); VECTOR(*value)[i] = VECTOR(*num)[v]; } igraph_vit_destroy(&it); IGRAPH_FINALLY_CLEAN(1); } return 0; } int igraph_i_cattribute_get_bool_vertex_attr(const igraph_t *graph, const char *name, igraph_vs_t vs, igraph_vector_bool_t *value) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *val = &attr->val; igraph_vit_t it; long int i, j, v; igraph_attribute_record_t *rec; igraph_vector_bool_t *log; igraph_bool_t l = igraph_i_cattribute_find(val, name, &j); if (!l) { IGRAPH_ERROR("Unknown attribute", IGRAPH_EINVAL); } rec = VECTOR(*val)[j]; log = (igraph_vector_bool_t*)rec->value; if (igraph_vs_is_all(&vs)) { igraph_vector_bool_clear(value); IGRAPH_CHECK(igraph_vector_bool_append(value, log)); } else { IGRAPH_CHECK(igraph_vit_create(graph, vs, &it)); IGRAPH_FINALLY(igraph_vit_destroy, &it); IGRAPH_CHECK(igraph_vector_bool_resize(value, IGRAPH_VIT_SIZE(it))); for (i = 0; !IGRAPH_VIT_END(it); IGRAPH_VIT_NEXT(it), i++) { v = IGRAPH_VIT_GET(it); VECTOR(*value)[i] = VECTOR(*log)[v]; } igraph_vit_destroy(&it); IGRAPH_FINALLY_CLEAN(1); } return 0; } int igraph_i_cattribute_get_string_vertex_attr(const igraph_t *graph, const char *name, igraph_vs_t vs, igraph_strvector_t *value) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *val = &attr->val; long int j; igraph_attribute_record_t *rec; igraph_strvector_t *str; igraph_bool_t l = igraph_i_cattribute_find(val, name, &j); if (!l) { IGRAPH_ERROR("Unknown attribute", IGRAPH_EINVAL); } rec = VECTOR(*val)[j]; str = (igraph_strvector_t*)rec->value; if (igraph_vs_is_all(&vs)) { igraph_strvector_resize(value, 0); IGRAPH_CHECK(igraph_strvector_append(value, str)); } else { igraph_vit_t it; long int i = 0; IGRAPH_CHECK(igraph_vit_create(graph, vs, &it)); IGRAPH_FINALLY(igraph_vit_destroy, &it); IGRAPH_CHECK(igraph_strvector_resize(value, IGRAPH_VIT_SIZE(it))); for (; !IGRAPH_VIT_END(it); IGRAPH_VIT_NEXT(it), i++) { long int v = IGRAPH_VIT_GET(it); char *s; igraph_strvector_get(str, v, &s); IGRAPH_CHECK(igraph_strvector_set(value, i, s)); } igraph_vit_destroy(&it); IGRAPH_FINALLY_CLEAN(1); } return 0; } int igraph_i_cattribute_get_numeric_edge_attr(const igraph_t *graph, const char *name, igraph_es_t es, igraph_vector_t *value) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *eal = &attr->eal; long int j; igraph_attribute_record_t *rec; igraph_vector_t *num; igraph_bool_t l = igraph_i_cattribute_find(eal, name, &j); if (!l) { IGRAPH_ERROR("Unknown attribute", IGRAPH_EINVAL); } rec = VECTOR(*eal)[j]; num = (igraph_vector_t*)rec->value; if (igraph_es_is_all(&es)) { igraph_vector_clear(value); IGRAPH_CHECK(igraph_vector_append(value, num)); } else { igraph_eit_t it; long int i = 0; IGRAPH_CHECK(igraph_eit_create(graph, es, &it)); IGRAPH_FINALLY(igraph_eit_destroy, &it); IGRAPH_CHECK(igraph_vector_resize(value, IGRAPH_EIT_SIZE(it))); for (; !IGRAPH_EIT_END(it); IGRAPH_EIT_NEXT(it), i++) { long int e = IGRAPH_EIT_GET(it); VECTOR(*value)[i] = VECTOR(*num)[e]; } igraph_eit_destroy(&it); IGRAPH_FINALLY_CLEAN(1); } return 0; } int igraph_i_cattribute_get_string_edge_attr(const igraph_t *graph, const char *name, igraph_es_t es, igraph_strvector_t *value) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *eal = &attr->eal; long int j; igraph_attribute_record_t *rec; igraph_strvector_t *str; igraph_bool_t l = igraph_i_cattribute_find(eal, name, &j); if (!l) { IGRAPH_ERROR("Unknown attribute", IGRAPH_EINVAL); } rec = VECTOR(*eal)[j]; str = (igraph_strvector_t*)rec->value; if (igraph_es_is_all(&es)) { igraph_strvector_resize(value, 0); IGRAPH_CHECK(igraph_strvector_append(value, str)); } else { igraph_eit_t it; long int i = 0; IGRAPH_CHECK(igraph_eit_create(graph, es, &it)); IGRAPH_FINALLY(igraph_eit_destroy, &it); IGRAPH_CHECK(igraph_strvector_resize(value, IGRAPH_EIT_SIZE(it))); for (; !IGRAPH_EIT_END(it); IGRAPH_EIT_NEXT(it), i++) { long int e = IGRAPH_EIT_GET(it); char *s; igraph_strvector_get(str, e, &s); IGRAPH_CHECK(igraph_strvector_set(value, i, s)); } igraph_eit_destroy(&it); IGRAPH_FINALLY_CLEAN(1); } return 0; } int igraph_i_cattribute_get_bool_edge_attr(const igraph_t *graph, const char *name, igraph_es_t es, igraph_vector_bool_t *value) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *eal = &attr->eal; long int j; igraph_attribute_record_t *rec; igraph_vector_bool_t *log; igraph_bool_t l = igraph_i_cattribute_find(eal, name, &j); if (!l) { IGRAPH_ERROR("Unknown attribute", IGRAPH_EINVAL); } rec = VECTOR(*eal)[j]; log = (igraph_vector_bool_t*)rec->value; if (igraph_es_is_all(&es)) { igraph_vector_bool_clear(value); IGRAPH_CHECK(igraph_vector_bool_append(value, log)); } else { igraph_eit_t it; long int i = 0; IGRAPH_CHECK(igraph_eit_create(graph, es, &it)); IGRAPH_FINALLY(igraph_eit_destroy, &it); IGRAPH_CHECK(igraph_vector_bool_resize(value, IGRAPH_EIT_SIZE(it))); for (; !IGRAPH_EIT_END(it); IGRAPH_EIT_NEXT(it), i++) { long int e = IGRAPH_EIT_GET(it); VECTOR(*value)[i] = VECTOR(*log)[e]; } igraph_eit_destroy(&it); IGRAPH_FINALLY_CLEAN(1); } return 0; } /* -------------------------------------- */ const igraph_attribute_table_t igraph_cattribute_table = { &igraph_i_cattribute_init, &igraph_i_cattribute_destroy, &igraph_i_cattribute_copy, &igraph_i_cattribute_add_vertices, &igraph_i_cattribute_permute_vertices, &igraph_i_cattribute_combine_vertices, &igraph_i_cattribute_add_edges, &igraph_i_cattribute_permute_edges, &igraph_i_cattribute_combine_edges, &igraph_i_cattribute_get_info, &igraph_i_cattribute_has_attr, &igraph_i_cattribute_gettype, &igraph_i_cattribute_get_numeric_graph_attr, &igraph_i_cattribute_get_string_graph_attr, &igraph_i_cattribute_get_bool_graph_attr, &igraph_i_cattribute_get_numeric_vertex_attr, &igraph_i_cattribute_get_string_vertex_attr, &igraph_i_cattribute_get_bool_vertex_attr, &igraph_i_cattribute_get_numeric_edge_attr, &igraph_i_cattribute_get_string_edge_attr, &igraph_i_cattribute_get_bool_edge_attr }; /* -------------------------------------- */ /** * \section cattributes * There is an experimental attribute handler that can be used * from C code. In this section we show how this works. This attribute * handler is by default not attached (the default is no attribute * handler), so we first need to attach it: * * igraph_i_set_attribute_table(&igraph_cattribute_table); * * * Now the attribute functions are available. Please note that * the attribute handler must be attached before you call any other * igraph functions, otherwise you might end up with graphs without * attributes and an active attribute handler, which might cause * unexpected program behaviour. The rule is that you attach the * attribute handler in the beginning of your * main() and never touch it again. (Detaching * the attribute handler might lead to memory leaks.) * * It is not currently possible to have attribute handlers on a * per-graph basis. All graphs in an application must be managed with * the same attribute handler. (Including the default case when there * is no attribute handler at all. * * The C attribute handler supports attaching real numbers and * character strings as attributes. No vectors are allowed, ie. every * vertex might have an attribute called name, but it is * not possible to have a coords graph (or other) * attribute which is a vector of numbers. * * \example examples/simple/cattributes.c * \example examples/simple/cattributes2.c * \example examples/simple/cattributes3.c * \example examples/simple/cattributes4.c */ /** * \function igraph_cattribute_GAN * Query a numeric graph attribute. * * Returns the value of the given numeric graph attribute. * The attribute must exist, otherwise an error is triggered. * \param graph The input graph. * \param name The name of the attribute to query. * \return The value of the attribute. * * \sa \ref GAN for a simpler interface. * * Time complexity: O(Ag), the number of graph attributes. */ igraph_real_t igraph_cattribute_GAN(const igraph_t *graph, const char *name) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *gal = &attr->gal; long int j; igraph_attribute_record_t *rec; igraph_vector_t *num; igraph_bool_t l = igraph_i_cattribute_find(gal, name, &j); if (!l) { igraph_error("Unknown attribute", __FILE__, __LINE__, IGRAPH_EINVAL); return 0; } rec = VECTOR(*gal)[j]; num = (igraph_vector_t*)rec->value; return VECTOR(*num)[0]; } /** * \function igraph_cattribute_GAB * Query a boolean graph attribute. * * Returns the value of the given numeric graph attribute. * The attribute must exist, otherwise an error is triggered. * \param graph The input graph. * \param name The name of the attribute to query. * \return The value of the attribute. * * \sa \ref GAB for a simpler interface. * * Time complexity: O(Ag), the number of graph attributes. */ igraph_bool_t igraph_cattribute_GAB(const igraph_t *graph, const char *name) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *gal = &attr->gal; long int j; igraph_attribute_record_t *rec; igraph_vector_bool_t *log; igraph_bool_t l = igraph_i_cattribute_find(gal, name, &j); if (!l) { igraph_error("Unknown attribute", __FILE__, __LINE__, IGRAPH_EINVAL); return 0; } rec = VECTOR(*gal)[j]; log = (igraph_vector_bool_t*)rec->value; return VECTOR(*log)[0]; } /** * \function igraph_cattribute_GAS * Query a string graph attribute. * * Returns a const pointer to the string graph attribute * specified in \p name. * The attribute must exist, otherwise an error is triggered. * \param graph The input graph. * \param name The name of the attribute to query. * \return The value of the attribute. * * \sa \ref GAS for a simpler interface. * * Time complexity: O(Ag), the number of graph attributes. */ const char* igraph_cattribute_GAS(const igraph_t *graph, const char *name) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *gal = &attr->gal; long int j; igraph_attribute_record_t *rec; igraph_strvector_t *str; igraph_bool_t l = igraph_i_cattribute_find(gal, name, &j); if (!l) { igraph_error("Unknown attribute", __FILE__, __LINE__, IGRAPH_EINVAL); return 0; } rec = VECTOR(*gal)[j]; str = (igraph_strvector_t*)rec->value; return STR(*str, 0); } /** * \function igraph_cattribute_VAN * Query a numeric vertex attribute. * * The attribute must exist, otherwise an error is triggered. * \param graph The input graph. * \param name The name of the attribute. * \param vid The id of the queried vertex. * \return The value of the attribute. * * \sa \ref VAN macro for a simpler interface. * * Time complexity: O(Av), the number of vertex attributes. */ igraph_real_t igraph_cattribute_VAN(const igraph_t *graph, const char *name, igraph_integer_t vid) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *val = &attr->val; long int j; igraph_attribute_record_t *rec; igraph_vector_t *num; igraph_bool_t l = igraph_i_cattribute_find(val, name, &j); if (!l) { igraph_error("Unknown attribute", __FILE__, __LINE__, IGRAPH_EINVAL); return 0; } rec = VECTOR(*val)[j]; num = (igraph_vector_t*)rec->value; return VECTOR(*num)[(long int)vid]; } /** * \function igraph_cattribute_VAB * Query a boolean vertex attribute. * * The attribute must exist, otherwise an error is triggered. * \param graph The input graph. * \param name The name of the attribute. * \param vid The id of the queried vertex. * \return The value of the attribute. * * \sa \ref VAB macro for a simpler interface. * * Time complexity: O(Av), the number of vertex attributes. */ igraph_bool_t igraph_cattribute_VAB(const igraph_t *graph, const char *name, igraph_integer_t vid) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *val = &attr->val; long int j; igraph_attribute_record_t *rec; igraph_vector_bool_t *log; igraph_bool_t l = igraph_i_cattribute_find(val, name, &j); if (!l) { igraph_error("Unknown attribute", __FILE__, __LINE__, IGRAPH_EINVAL); return 0; } rec = VECTOR(*val)[j]; log = (igraph_vector_bool_t*)rec->value; return VECTOR(*log)[(long int)vid]; } /** * \function igraph_cattribute_VAS * Query a string vertex attribute. * * The attribute must exist, otherwise an error is triggered. * \param graph The input graph. * \param name The name of the attribute. * \param vid The id of the queried vertex. * \return The value of the attribute. * * \sa The macro \ref VAS for a simpler interface. * * Time complexity: O(Av), the number of vertex attributes. */ const char* igraph_cattribute_VAS(const igraph_t *graph, const char *name, igraph_integer_t vid) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *val = &attr->val; long int j; igraph_attribute_record_t *rec; igraph_strvector_t *str; igraph_bool_t l = igraph_i_cattribute_find(val, name, &j); if (!l) { igraph_error("Unknown attribute", __FILE__, __LINE__, IGRAPH_EINVAL); return 0; } rec = VECTOR(*val)[j]; str = (igraph_strvector_t*)rec->value; return STR(*str, (long int)vid); } /** * \function igraph_cattribute_EAN * Query a numeric edge attribute. * * The attribute must exist, otherwise an error is triggered. * \param graph The input graph. * \param name The name of the attribute. * \param eid The id of the queried edge. * \return The value of the attribute. * * \sa \ref EAN for an easier interface. * * Time complexity: O(Ae), the number of edge attributes. */ igraph_real_t igraph_cattribute_EAN(const igraph_t *graph, const char *name, igraph_integer_t eid) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *eal = &attr->eal; long int j; igraph_attribute_record_t *rec; igraph_vector_t *num; igraph_bool_t l = igraph_i_cattribute_find(eal, name, &j); if (!l) { igraph_error("Unknown attribute", __FILE__, __LINE__, IGRAPH_EINVAL); return 0; } rec = VECTOR(*eal)[j]; num = (igraph_vector_t*)rec->value; return VECTOR(*num)[(long int)eid]; } /** * \function igraph_cattribute_EAB * Query a boolean edge attribute. * * The attribute must exist, otherwise an error is triggered. * \param graph The input graph. * \param name The name of the attribute. * \param eid The id of the queried edge. * \return The value of the attribute. * * \sa \ref EAB for an easier interface. * * Time complexity: O(Ae), the number of edge attributes. */ igraph_bool_t igraph_cattribute_EAB(const igraph_t *graph, const char *name, igraph_integer_t eid) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *eal = &attr->eal; long int j; igraph_attribute_record_t *rec; igraph_vector_bool_t *log; igraph_bool_t l = igraph_i_cattribute_find(eal, name, &j); if (!l) { igraph_error("Unknown attribute", __FILE__, __LINE__, IGRAPH_EINVAL); return 0; } rec = VECTOR(*eal)[j]; log = (igraph_vector_bool_t*)rec->value; return VECTOR(*log)[(long int)eid]; } /** * \function igraph_cattribute_EAS * Query a string edge attribute. * * The attribute must exist, otherwise an error is triggered. * \param graph The input graph. * \param name The name of the attribute. * \param eid The id of the queried edge. * \return The value of the attribute. * * \se \ref EAS if you want to type less. * * Time complexity: O(Ae), the number of edge attributes. */ const char* igraph_cattribute_EAS(const igraph_t *graph, const char *name, igraph_integer_t eid) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *eal = &attr->eal; long int j; igraph_attribute_record_t *rec; igraph_strvector_t *str; igraph_bool_t l = igraph_i_cattribute_find(eal, name, &j); if (!l) { igraph_error("Unknown attribute", __FILE__, __LINE__, IGRAPH_EINVAL); return 0; } rec = VECTOR(*eal)[j]; str = (igraph_strvector_t*)rec->value; return STR(*str, (long int)eid); } /** * \function igraph_cattribute_VANV * Query a numeric vertex attribute for many vertices * * \param graph The input graph. * \param name The name of the attribute. * \param vids The vertices to query. * \param result Pointer to an initialized vector, the result is * stored here. It will be resized, if needed. * \return Error code. * * Time complexity: O(v), where v is the number of vertices in 'vids'. */ int igraph_cattribute_VANV(const igraph_t *graph, const char *name, igraph_vs_t vids, igraph_vector_t *result) { return igraph_i_cattribute_get_numeric_vertex_attr(graph, name, vids, result); } /** * \function igraph_cattribute_VABV * Query a boolean vertex attribute for many vertices * * \param graph The input graph. * \param name The name of the attribute. * \param vids The vertices to query. * \param result Pointer to an initialized boolean vector, the result is * stored here. It will be resized, if needed. * \return Error code. * * Time complexity: O(v), where v is the number of vertices in 'vids'. */ int igraph_cattribute_VABV(const igraph_t *graph, const char *name, igraph_vs_t vids, igraph_vector_bool_t *result) { return igraph_i_cattribute_get_bool_vertex_attr(graph, name, vids, result); } /** * \function igraph_cattribute_EANV * Query a numeric edge attribute for many edges * * \param graph The input graph. * \param name The name of the attribute. * \param eids The edges to query. * \param result Pointer to an initialized vector, the result is * stored here. It will be resized, if needed. * \return Error code. * * Time complexity: O(e), where e is the number of edges in 'eids'. */ int igraph_cattribute_EANV(const igraph_t *graph, const char *name, igraph_es_t eids, igraph_vector_t *result) { return igraph_i_cattribute_get_numeric_edge_attr(graph, name, eids, result); } /** * \function igraph_cattribute_EABV * Query a boolean edge attribute for many edges * * \param graph The input graph. * \param name The name of the attribute. * \param eids The edges to query. * \param result Pointer to an initialized boolean vector, the result is * stored here. It will be resized, if needed. * \return Error code. * * Time complexity: O(e), where e is the number of edges in 'eids'. */ int igraph_cattribute_EABV(const igraph_t *graph, const char *name, igraph_es_t eids, igraph_vector_bool_t *result) { return igraph_i_cattribute_get_bool_edge_attr(graph, name, eids, result); } /** * \function igraph_cattribute_VASV * Query a string vertex attribute for many vertices * * \param graph The input graph. * \param name The name of the attribute. * \param vids The vertices to query. * \param result Pointer to an initialized string vector, the result * is stored here. It will be resized, if needed. * \return Error code. * * Time complexity: O(v), where v is the number of vertices in 'vids'. * (We assume that the string attributes have a bounded length.) */ int igraph_cattribute_VASV(const igraph_t *graph, const char *name, igraph_vs_t vids, igraph_strvector_t *result) { return igraph_i_cattribute_get_string_vertex_attr(graph, name, vids, result); } /** * \function igraph_cattribute_EASV * Query a string edge attribute for many edges * * \param graph The input graph. * \param name The name of the attribute. * \param vids The edges to query. * \param result Pointer to an initialized string vector, the result * is stored here. It will be resized, if needed. * \return Error code. * * Time complexity: O(e), where e is the number of edges in * 'eids'. (We assume that the string attributes have a bounded length.) */ int igraph_cattribute_EASV(const igraph_t *graph, const char *name, igraph_es_t eids, igraph_strvector_t *result) { return igraph_i_cattribute_get_string_edge_attr(graph, name, eids, result); } /** * \function igraph_cattribute_list * List all attributes * * See \ref igraph_attribute_type_t for the various attribute types. * \param graph The input graph. * \param gnames String vector, the names of the graph attributes. * \param gtypes Numeric vector, the types of the graph attributes. * \param vnames String vector, the names of the vertex attributes. * \param vtypes Numeric vector, the types of the vertex attributes. * \param enames String vector, the names of the edge attributes. * \param etypes Numeric vector, the types of the edge attributes. * \return Error code. * * Naturally, the string vector with the attribute names and the * numeric vector with the attribute types are in the right order, * i.e. the first name corresponds to the first type, etc. * * Time complexity: O(Ag+Av+Ae), the number of all attributes. */ int igraph_cattribute_list(const igraph_t *graph, igraph_strvector_t *gnames, igraph_vector_t *gtypes, igraph_strvector_t *vnames, igraph_vector_t *vtypes, igraph_strvector_t *enames, igraph_vector_t *etypes) { return igraph_i_cattribute_get_info(graph, gnames, gtypes, vnames, vtypes, enames, etypes); } /** * \function igraph_cattribute_has_attr * Checks whether a (graph, vertex or edge) attribute exists * * \param graph The graph. * \param type The type of the attribute, \c IGRAPH_ATTRIBUTE_GRAPH, * \c IGRAPH_ATTRIBUTE_VERTEX or \c IGRAPH_ATTRIBUTE_EDGE. * \param name Character constant, the name of the attribute. * \return Logical value, TRUE if the attribute exists, FALSE otherwise. * * Time complexity: O(A), the number of (graph, vertex or edge) * attributes, assuming attribute names are not too long. */ igraph_bool_t igraph_cattribute_has_attr(const igraph_t *graph, igraph_attribute_elemtype_t type, const char *name) { return igraph_i_cattribute_has_attr(graph, type, name); } /** * \function igraph_cattribute_GAN_set * Set a numeric graph attribute * * \param graph The graph. * \param name Name of the graph attribute. If there is no such * attribute yet, then it will be added. * \param value The (new) value of the graph attribute. * \return Error code. * * \se \ref SETGAN if you want to type less. * * Time complexity: O(1). */ int igraph_cattribute_GAN_set(igraph_t *graph, const char *name, igraph_real_t value) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *gal = &attr->gal; long int j; igraph_bool_t l = igraph_i_cattribute_find(gal, name, &j); if (l) { igraph_attribute_record_t *rec = VECTOR(*gal)[j]; if (rec->type != IGRAPH_ATTRIBUTE_NUMERIC) { IGRAPH_ERROR("Invalid attribute type", IGRAPH_EINVAL); } else { igraph_vector_t *num = (igraph_vector_t *)rec->value; VECTOR(*num)[0] = value; } } else { igraph_attribute_record_t *rec = igraph_Calloc(1, igraph_attribute_record_t); igraph_vector_t *num; if (!rec) { IGRAPH_ERROR("Cannot add graph attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, rec); rec->name = strdup(name); if (!rec->name) { IGRAPH_ERROR("Cannot add graph attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (char*)rec->name); rec->type = IGRAPH_ATTRIBUTE_NUMERIC; num = igraph_Calloc(1, igraph_vector_t); if (!num) { IGRAPH_ERROR("Cannot add graph attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, num); IGRAPH_VECTOR_INIT_FINALLY(num, 1); VECTOR(*num)[0] = value; rec->value = num; IGRAPH_CHECK(igraph_vector_ptr_push_back(gal, rec)); IGRAPH_FINALLY_CLEAN(4); } return 0; } /** * \function igraph_cattribute_GAB_set * Set a boolean graph attribute * * \param graph The graph. * \param name Name of the graph attribute. If there is no such * attribute yet, then it will be added. * \param value The (new) value of the graph attribute. * \return Error code. * * \se \ref SETGAN if you want to type less. * * Time complexity: O(1). */ int igraph_cattribute_GAB_set(igraph_t *graph, const char *name, igraph_bool_t value) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *gal = &attr->gal; long int j; igraph_bool_t l = igraph_i_cattribute_find(gal, name, &j); if (l) { igraph_attribute_record_t *rec = VECTOR(*gal)[j]; if (rec->type != IGRAPH_ATTRIBUTE_BOOLEAN) { IGRAPH_ERROR("Invalid attribute type", IGRAPH_EINVAL); } else { igraph_vector_bool_t *log = (igraph_vector_bool_t *)rec->value; VECTOR(*log)[0] = value; } } else { igraph_attribute_record_t *rec = igraph_Calloc(1, igraph_attribute_record_t); igraph_vector_bool_t *log; if (!rec) { IGRAPH_ERROR("Cannot add graph attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, rec); rec->name = strdup(name); if (!rec->name) { IGRAPH_ERROR("Cannot add graph attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (char*)rec->name); rec->type = IGRAPH_ATTRIBUTE_BOOLEAN; log = igraph_Calloc(1, igraph_vector_bool_t); if (!log) { IGRAPH_ERROR("Cannot add graph attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, log); IGRAPH_CHECK(igraph_vector_bool_init(log, 1)); IGRAPH_FINALLY(igraph_vector_bool_destroy, log); VECTOR(*log)[0] = value; rec->value = log; IGRAPH_CHECK(igraph_vector_ptr_push_back(gal, rec)); IGRAPH_FINALLY_CLEAN(4); } return 0; } /** * \function igraph_cattribute_GAS_set * Set a string graph attribute. * * \param graph The graph. * \param name Name of the graph attribute. If there is no such * attribute yet, then it will be added. * \param value The (new) value of the graph attribute. It will be * copied. * \return Error code. * * \se \ref SETGAS if you want to type less. * * Time complexity: O(1). */ int igraph_cattribute_GAS_set(igraph_t *graph, const char *name, const char *value) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *gal = &attr->gal; long int j; igraph_bool_t l = igraph_i_cattribute_find(gal, name, &j); if (l) { igraph_attribute_record_t *rec = VECTOR(*gal)[j]; if (rec->type != IGRAPH_ATTRIBUTE_STRING) { IGRAPH_ERROR("Invalid attribute type", IGRAPH_EINVAL); } else { igraph_strvector_t *str = (igraph_strvector_t*)rec->value; IGRAPH_CHECK(igraph_strvector_set(str, 0, value)); } } else { igraph_attribute_record_t *rec = igraph_Calloc(1, igraph_attribute_record_t); igraph_strvector_t *str; if (!rec) { IGRAPH_ERROR("Cannot add graph attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, rec); rec->name = strdup(name); if (!rec->name) { IGRAPH_ERROR("Cannot add graph attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (char*)rec->name); rec->type = IGRAPH_ATTRIBUTE_STRING; str = igraph_Calloc(1, igraph_strvector_t); if (!str) { IGRAPH_ERROR("Cannot add graph attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, str); IGRAPH_STRVECTOR_INIT_FINALLY(str, 1); IGRAPH_CHECK(igraph_strvector_set(str, 0, value)); rec->value = str; IGRAPH_CHECK(igraph_vector_ptr_push_back(gal, rec)); IGRAPH_FINALLY_CLEAN(4); } return 0; } /** * \function igraph_cattribute_VAN_set * Set a numeric vertex attribute * * The attribute will be added if not present already. If present it * will be overwritten. The same \p value is set for all vertices * included in \p vid. * \param graph The graph. * \param name Name of the attribute. * \param vid Vertices for which to set the attribute. * \param value The (new) value of the attribute. * \return Error code. * * \sa \ref SETVAN for a simpler way. * * Time complexity: O(n), the number of vertices if the attribute is * new, O(|vid|) otherwise. */ int igraph_cattribute_VAN_set(igraph_t *graph, const char *name, igraph_integer_t vid, igraph_real_t value) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *val = &attr->val; long int j; igraph_bool_t l = igraph_i_cattribute_find(val, name, &j); if (l) { igraph_attribute_record_t *rec = VECTOR(*val)[j]; if (rec->type != IGRAPH_ATTRIBUTE_NUMERIC) { IGRAPH_ERROR("Invalid attribute type", IGRAPH_EINVAL); } else { igraph_vector_t *num = (igraph_vector_t*)rec->value; VECTOR(*num)[(long int)vid] = value; } } else { igraph_attribute_record_t *rec = igraph_Calloc(1, igraph_attribute_record_t); igraph_vector_t *num; if (!rec) { IGRAPH_ERROR("Cannot add vertex attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, rec); rec->name = strdup(name); if (!rec->name) { IGRAPH_ERROR("Cannot add vertex attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (char*)rec->name); rec->type = IGRAPH_ATTRIBUTE_NUMERIC; num = igraph_Calloc(1, igraph_vector_t); if (!num) { IGRAPH_ERROR("Cannot add vertex attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, num); IGRAPH_VECTOR_INIT_FINALLY(num, igraph_vcount(graph)); igraph_vector_fill(num, IGRAPH_NAN); VECTOR(*num)[(long int)vid] = value; rec->value = num; IGRAPH_CHECK(igraph_vector_ptr_push_back(val, rec)); IGRAPH_FINALLY_CLEAN(4); } return 0; } /** * \function igraph_cattribute_VAB_set * Set a boolean vertex attribute * * The attribute will be added if not present already. If present it * will be overwritten. The same \p value is set for all vertices * included in \p vid. * \param graph The graph. * \param name Name of the attribute. * \param vid Vertices for which to set the attribute. * \param value The (new) value of the attribute. * \return Error code. * * \sa \ref SETVAB for a simpler way. * * Time complexity: O(n), the number of vertices if the attribute is * new, O(|vid|) otherwise. */ int igraph_cattribute_VAB_set(igraph_t *graph, const char *name, igraph_integer_t vid, igraph_bool_t value) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *val = &attr->val; long int j; igraph_bool_t l = igraph_i_cattribute_find(val, name, &j); if (l) { igraph_attribute_record_t *rec = VECTOR(*val)[j]; if (rec->type != IGRAPH_ATTRIBUTE_BOOLEAN) { IGRAPH_ERROR("Invalid attribute type", IGRAPH_EINVAL); } else { igraph_vector_bool_t *log = (igraph_vector_bool_t*)rec->value; VECTOR(*log)[(long int)vid] = value; } } else { igraph_attribute_record_t *rec = igraph_Calloc(1, igraph_attribute_record_t); igraph_vector_bool_t *log; if (!rec) { IGRAPH_ERROR("Cannot add vertex attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, rec); rec->name = strdup(name); if (!rec->name) { IGRAPH_ERROR("Cannot add vertex attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (char*)rec->name); rec->type = IGRAPH_ATTRIBUTE_BOOLEAN; log = igraph_Calloc(1, igraph_vector_bool_t); if (!log) { IGRAPH_ERROR("Cannot add vertex attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, log); IGRAPH_CHECK(igraph_vector_bool_init(log, igraph_vcount(graph))); IGRAPH_FINALLY(igraph_vector_bool_destroy, log); igraph_vector_bool_fill(log, 0); VECTOR(*log)[(long int)vid] = value; rec->value = log; IGRAPH_CHECK(igraph_vector_ptr_push_back(val, rec)); IGRAPH_FINALLY_CLEAN(4); } return 0; } /** * \function igraph_cattribute_VAS_set * Set a string vertex attribute * * The attribute will be added if not present already. If present it * will be overwritten. The same \p value is set for all vertices * included in \p vid. * \param graph The graph. * \param name Name of the attribute. * \param vid Vertices for which to set the attribute. * \param value The (new) value of the attribute. * \return Error code. * * \sa \ref SETVAS for a simpler way. * * Time complexity: O(n*l), n is the number of vertices, l is the * length of the string to set. If the attribute if not new then only * O(|vid|*l). */ int igraph_cattribute_VAS_set(igraph_t *graph, const char *name, igraph_integer_t vid, const char *value) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *val = &attr->val; long int j; igraph_bool_t l = igraph_i_cattribute_find(val, name, &j); if (l) { igraph_attribute_record_t *rec = VECTOR(*val)[j]; if (rec->type != IGRAPH_ATTRIBUTE_STRING) { IGRAPH_ERROR("Invalid attribute type", IGRAPH_EINVAL); } else { igraph_strvector_t *str = (igraph_strvector_t*)rec->value; IGRAPH_CHECK(igraph_strvector_set(str, vid, value)); } } else { igraph_attribute_record_t *rec = igraph_Calloc(1, igraph_attribute_record_t); igraph_strvector_t *str; if (!rec) { IGRAPH_ERROR("Cannot add vertex attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, rec); rec->name = strdup(name); if (!rec->name) { IGRAPH_ERROR("Cannot add vertex attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (char*)rec->name); rec->type = IGRAPH_ATTRIBUTE_STRING; str = igraph_Calloc(1, igraph_strvector_t); if (!str) { IGRAPH_ERROR("Cannot add vertex attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, str); IGRAPH_STRVECTOR_INIT_FINALLY(str, igraph_vcount(graph)); IGRAPH_CHECK(igraph_strvector_set(str, vid, value)); rec->value = str; IGRAPH_CHECK(igraph_vector_ptr_push_back(val, rec)); IGRAPH_FINALLY_CLEAN(4); } return 0; } /** * \function igraph_cattribute_EAN_set * Set a numeric edge attribute * * The attribute will be added if not present already. If present it * will be overwritten. The same \p value is set for all edges * included in \p vid. * \param graph The graph. * \param name Name of the attribute. * \param eid Edges for which to set the attribute. * \param value The (new) value of the attribute. * \return Error code. * * \sa \ref SETEAN for a simpler way. * * Time complexity: O(e), the number of edges if the attribute is * new, O(|eid|) otherwise. */ int igraph_cattribute_EAN_set(igraph_t *graph, const char *name, igraph_integer_t eid, igraph_real_t value) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *eal = &attr->eal; long int j; igraph_bool_t l = igraph_i_cattribute_find(eal, name, &j); if (l) { igraph_attribute_record_t *rec = VECTOR(*eal)[j]; if (rec->type != IGRAPH_ATTRIBUTE_NUMERIC) { IGRAPH_ERROR("Invalid attribute type", IGRAPH_EINVAL); } else { igraph_vector_t *num = (igraph_vector_t*)rec->value; VECTOR(*num)[(long int)eid] = value; } } else { igraph_attribute_record_t *rec = igraph_Calloc(1, igraph_attribute_record_t); igraph_vector_t *num; if (!rec) { IGRAPH_ERROR("Cannot add edge attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, rec); rec->name = strdup(name); if (!rec->name) { IGRAPH_ERROR("Cannot add edge attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (char*)rec->name); rec->type = IGRAPH_ATTRIBUTE_NUMERIC; num = igraph_Calloc(1, igraph_vector_t); if (!num) { IGRAPH_ERROR("Cannot add edge attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, num); IGRAPH_VECTOR_INIT_FINALLY(num, igraph_ecount(graph)); igraph_vector_fill(num, IGRAPH_NAN); VECTOR(*num)[(long int)eid] = value; rec->value = num; IGRAPH_CHECK(igraph_vector_ptr_push_back(eal, rec)); IGRAPH_FINALLY_CLEAN(4); } return 0; } /** * \function igraph_cattribute_EAB_set * Set a boolean edge attribute * * The attribute will be added if not present already. If present it * will be overwritten. The same \p value is set for all edges * included in \p vid. * \param graph The graph. * \param name Name of the attribute. * \param eid Edges for which to set the attribute. * \param value The (new) value of the attribute. * \return Error code. * * \sa \ref SETEAB for a simpler way. * * Time complexity: O(e), the number of edges if the attribute is * new, O(|eid|) otherwise. */ int igraph_cattribute_EAB_set(igraph_t *graph, const char *name, igraph_integer_t eid, igraph_bool_t value) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *eal = &attr->eal; long int j; igraph_bool_t l = igraph_i_cattribute_find(eal, name, &j); if (l) { igraph_attribute_record_t *rec = VECTOR(*eal)[j]; if (rec->type != IGRAPH_ATTRIBUTE_BOOLEAN) { IGRAPH_ERROR("Invalid attribute type", IGRAPH_EINVAL); } else { igraph_vector_bool_t *log = (igraph_vector_bool_t*)rec->value; VECTOR(*log)[(long int)eid] = value; } } else { igraph_attribute_record_t *rec = igraph_Calloc(1, igraph_attribute_record_t); igraph_vector_bool_t *log; if (!rec) { IGRAPH_ERROR("Cannot add edge attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, rec); rec->name = strdup(name); if (!rec->name) { IGRAPH_ERROR("Cannot add edge attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (char*)rec->name); rec->type = IGRAPH_ATTRIBUTE_BOOLEAN; log = igraph_Calloc(1, igraph_vector_bool_t); if (!log) { IGRAPH_ERROR("Cannot add edge attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, log); IGRAPH_CHECK(igraph_vector_bool_init(log, igraph_ecount(graph))); IGRAPH_FINALLY(igraph_vector_bool_destroy, log); igraph_vector_bool_fill(log, 0); VECTOR(*log)[(long int)eid] = value; rec->value = log; IGRAPH_CHECK(igraph_vector_ptr_push_back(eal, rec)); IGRAPH_FINALLY_CLEAN(4); } return 0; } /** * \function igraph_cattribute_EAS_set * Set a string edge attribute * * The attribute will be added if not present already. If present it * will be overwritten. The same \p value is set for all edges * included in \p vid. * \param graph The graph. * \param name Name of the attribute. * \param eid Edges for which to set the attribute. * \param value The (new) value of the attribute. * \return Error code. * * \sa \ref SETEAS for a simpler way. * * Time complexity: O(e*l), n is the number of edges, l is the * length of the string to set. If the attribute if not new then only * O(|eid|*l). */ int igraph_cattribute_EAS_set(igraph_t *graph, const char *name, igraph_integer_t eid, const char *value) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *eal = &attr->eal; long int j; igraph_bool_t l = igraph_i_cattribute_find(eal, name, &j); if (l) { igraph_attribute_record_t *rec = VECTOR(*eal)[j]; if (rec->type != IGRAPH_ATTRIBUTE_STRING) { IGRAPH_ERROR("Invalid attribute type", IGRAPH_EINVAL); } else { igraph_strvector_t *str = (igraph_strvector_t*)rec->value; IGRAPH_CHECK(igraph_strvector_set(str, eid, value)); } } else { igraph_attribute_record_t *rec = igraph_Calloc(1, igraph_attribute_record_t); igraph_strvector_t *str; if (!rec) { IGRAPH_ERROR("Cannot add edge attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, rec); rec->name = strdup(name); if (!rec->name) { IGRAPH_ERROR("Cannot add edge attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (char*)rec->name); rec->type = IGRAPH_ATTRIBUTE_STRING; str = igraph_Calloc(1, igraph_strvector_t); if (!str) { IGRAPH_ERROR("Cannot add edge attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, str); IGRAPH_STRVECTOR_INIT_FINALLY(str, igraph_ecount(graph)); IGRAPH_CHECK(igraph_strvector_set(str, eid, value)); rec->value = str; IGRAPH_CHECK(igraph_vector_ptr_push_back(eal, rec)); IGRAPH_FINALLY_CLEAN(4); } return 0; } /** * \function igraph_cattribute_VAN_setv * Set a numeric vertex attribute for all vertices. * * The attribute will be added if not present yet. * \param graph The graph. * \param name Name of the attribute. * \param v The new attribute values. The length of this vector must * match the number of vertices. * \return Error code. * * \sa \ref SETVANV for a simpler way. * * Time complexity: O(n), the number of vertices. */ int igraph_cattribute_VAN_setv(igraph_t *graph, const char *name, const igraph_vector_t *v) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *val = &attr->val; long int j; igraph_bool_t l = igraph_i_cattribute_find(val, name, &j); /* Check length first */ if (igraph_vector_size(v) != igraph_vcount(graph)) { IGRAPH_ERROR("Invalid vertex attribute vector length", IGRAPH_EINVAL); } if (l) { /* Already present, check type */ igraph_attribute_record_t *rec = VECTOR(*val)[j]; igraph_vector_t *num = (igraph_vector_t *)rec->value; if (rec->type != IGRAPH_ATTRIBUTE_NUMERIC) { IGRAPH_ERROR("Attribute type mismatch", IGRAPH_EINVAL); } igraph_vector_clear(num); IGRAPH_CHECK(igraph_vector_append(num, v)); } else { /* Add it */ igraph_attribute_record_t *rec = igraph_Calloc(1, igraph_attribute_record_t); igraph_vector_t *num; if (!rec) { IGRAPH_ERROR("Cannot add vertex attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, rec); rec->type = IGRAPH_ATTRIBUTE_NUMERIC; rec->name = strdup(name); if (!rec->name) { IGRAPH_ERROR("Cannot add vertex attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (char*)rec->name); num = igraph_Calloc(1, igraph_vector_t); if (!num) { IGRAPH_ERROR("Cannot add vertex attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, num); rec->value = num; IGRAPH_CHECK(igraph_vector_copy(num, v)); IGRAPH_FINALLY(igraph_vector_destroy, num); IGRAPH_CHECK(igraph_vector_ptr_push_back(val, rec)); IGRAPH_FINALLY_CLEAN(4); } return 0; } /** * \function igraph_cattribute_VAB_setv * Set a boolean vertex attribute for all vertices. * * The attribute will be added if not present yet. * \param graph The graph. * \param name Name of the attribute. * \param v The new attribute values. The length of this boolean vector must * match the number of vertices. * \return Error code. * * \sa \ref SETVANV for a simpler way. * * Time complexity: O(n), the number of vertices. */ int igraph_cattribute_VAB_setv(igraph_t *graph, const char *name, const igraph_vector_bool_t *v) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *val = &attr->val; long int j; igraph_bool_t l = igraph_i_cattribute_find(val, name, &j); /* Check length first */ if (igraph_vector_bool_size(v) != igraph_vcount(graph)) { IGRAPH_ERROR("Invalid vertex attribute vector length", IGRAPH_EINVAL); } if (l) { /* Already present, check type */ igraph_attribute_record_t *rec = VECTOR(*val)[j]; igraph_vector_bool_t *log = (igraph_vector_bool_t *)rec->value; if (rec->type != IGRAPH_ATTRIBUTE_BOOLEAN) { IGRAPH_ERROR("Attribute type mismatch", IGRAPH_EINVAL); } igraph_vector_bool_clear(log); IGRAPH_CHECK(igraph_vector_bool_append(log, v)); } else { /* Add it */ igraph_attribute_record_t *rec = igraph_Calloc(1, igraph_attribute_record_t); igraph_vector_bool_t *log; if (!rec) { IGRAPH_ERROR("Cannot add vertex attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, rec); rec->type = IGRAPH_ATTRIBUTE_BOOLEAN; rec->name = strdup(name); if (!rec->name) { IGRAPH_ERROR("Cannot add vertex attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (char*)rec->name); log = igraph_Calloc(1, igraph_vector_bool_t); if (!log) { IGRAPH_ERROR("Cannot add vertex attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, log); rec->value = log; IGRAPH_CHECK(igraph_vector_bool_copy(log, v)); IGRAPH_FINALLY(igraph_vector_destroy, log); IGRAPH_CHECK(igraph_vector_ptr_push_back(val, rec)); IGRAPH_FINALLY_CLEAN(4); } return 0; } /** * \function igraph_cattribute_VAS_setv * Set a string vertex attribute for all vertices. * * The attribute will be added if not present yet. * \param graph The graph. * \param name Name of the attribute. * \param sv String vector, the new attribute values. The length of this vector must * match the number of vertices. * \return Error code. * * \sa \ref SETVASV for a simpler way. * * Time complexity: O(n+l), n is the number of vertices, l is the * total length of the strings. */ int igraph_cattribute_VAS_setv(igraph_t *graph, const char *name, const igraph_strvector_t *sv) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *val = &attr->val; long int j; igraph_bool_t l = igraph_i_cattribute_find(val, name, &j); /* Check length first */ if (igraph_strvector_size(sv) != igraph_vcount(graph)) { IGRAPH_ERROR("Invalid vertex attribute vector length", IGRAPH_EINVAL); } if (l) { /* Already present, check type */ igraph_attribute_record_t *rec = VECTOR(*val)[j]; igraph_strvector_t *str = (igraph_strvector_t *)rec->value; if (rec->type != IGRAPH_ATTRIBUTE_STRING) { IGRAPH_ERROR("Attribute type mismatch", IGRAPH_EINVAL); } igraph_strvector_clear(str); IGRAPH_CHECK(igraph_strvector_append(str, sv)); } else { /* Add it */ igraph_attribute_record_t *rec = igraph_Calloc(1, igraph_attribute_record_t); igraph_strvector_t *str; if (!rec) { IGRAPH_ERROR("Cannot add vertex attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, rec); rec->type = IGRAPH_ATTRIBUTE_STRING; rec->name = strdup(name); if (!rec->name) { IGRAPH_ERROR("Cannot add vertex attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (char*)rec->name); str = igraph_Calloc(1, igraph_strvector_t); if (!str) { IGRAPH_ERROR("Cannot add vertex attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, str); rec->value = str; IGRAPH_CHECK(igraph_strvector_copy(str, sv)); IGRAPH_FINALLY(igraph_strvector_destroy, str); IGRAPH_CHECK(igraph_vector_ptr_push_back(val, rec)); IGRAPH_FINALLY_CLEAN(4); } return 0; } /** * \function igraph_cattribute_EAN_setv * Set a numeric edge attribute for all vertices. * * The attribute will be added if not present yet. * \param graph The graph. * \param name Name of the attribute. * \param v The new attribute values. The length of this vector must * match the number of edges. * \return Error code. * * \sa \ref SETEANV for a simpler way. * * Time complexity: O(e), the number of edges. */ int igraph_cattribute_EAN_setv(igraph_t *graph, const char *name, const igraph_vector_t *v) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *eal = &attr->eal; long int j; igraph_bool_t l = igraph_i_cattribute_find(eal, name, &j); /* Check length first */ if (igraph_vector_size(v) != igraph_ecount(graph)) { IGRAPH_ERROR("Invalid edge attribute vector length", IGRAPH_EINVAL); } if (l) { /* Already present, check type */ igraph_attribute_record_t *rec = VECTOR(*eal)[j]; igraph_vector_t *num = (igraph_vector_t *)rec->value; if (rec->type != IGRAPH_ATTRIBUTE_NUMERIC) { IGRAPH_ERROR("Attribute type mismatch", IGRAPH_EINVAL); } igraph_vector_clear(num); IGRAPH_CHECK(igraph_vector_append(num, v)); } else { /* Add it */ igraph_attribute_record_t *rec = igraph_Calloc(1, igraph_attribute_record_t); igraph_vector_t *num; if (!rec) { IGRAPH_ERROR("Cannot add edge attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, rec); rec->type = IGRAPH_ATTRIBUTE_NUMERIC; rec->name = strdup(name); if (!rec->name) { IGRAPH_ERROR("Cannot add edge attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (char*)rec->name); num = igraph_Calloc(1, igraph_vector_t); if (!num) { IGRAPH_ERROR("Cannot add edge attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, num); rec->value = num; IGRAPH_CHECK(igraph_vector_copy(num, v)); IGRAPH_FINALLY(igraph_vector_destroy, num); IGRAPH_CHECK(igraph_vector_ptr_push_back(eal, rec)); IGRAPH_FINALLY_CLEAN(4); } return 0; } /** * \function igraph_cattribute_EAB_setv * Set a boolean edge attribute for all vertices. * * The attribute will be added if not present yet. * \param graph The graph. * \param name Name of the attribute. * \param v The new attribute values. The length of this vector must * match the number of edges. * \return Error code. * * \sa \ref SETEABV for a simpler way. * * Time complexity: O(e), the number of edges. */ int igraph_cattribute_EAB_setv(igraph_t *graph, const char *name, const igraph_vector_bool_t *v) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *eal = &attr->eal; long int j; igraph_bool_t l = igraph_i_cattribute_find(eal, name, &j); /* Check length first */ if (igraph_vector_bool_size(v) != igraph_ecount(graph)) { IGRAPH_ERROR("Invalid edge attribute vector length", IGRAPH_EINVAL); } if (l) { /* Already present, check type */ igraph_attribute_record_t *rec = VECTOR(*eal)[j]; igraph_vector_bool_t *log = (igraph_vector_bool_t *)rec->value; if (rec->type != IGRAPH_ATTRIBUTE_BOOLEAN) { IGRAPH_ERROR("Attribute type mismatch", IGRAPH_EINVAL); } igraph_vector_bool_clear(log); IGRAPH_CHECK(igraph_vector_bool_append(log, v)); } else { /* Add it */ igraph_attribute_record_t *rec = igraph_Calloc(1, igraph_attribute_record_t); igraph_vector_bool_t *log; if (!rec) { IGRAPH_ERROR("Cannot add edge attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, rec); rec->type = IGRAPH_ATTRIBUTE_BOOLEAN; rec->name = strdup(name); if (!rec->name) { IGRAPH_ERROR("Cannot add edge attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (char*)rec->name); log = igraph_Calloc(1, igraph_vector_bool_t); if (!log) { IGRAPH_ERROR("Cannot add edge attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, log); rec->value = log; IGRAPH_CHECK(igraph_vector_bool_copy(log, v)); IGRAPH_FINALLY(igraph_vector_bool_destroy, log); IGRAPH_CHECK(igraph_vector_ptr_push_back(eal, rec)); IGRAPH_FINALLY_CLEAN(4); } return 0; } /** * \function igraph_cattribute_EAS_setv * Set a string edge attribute for all vertices. * * The attribute will be added if not present yet. * \param graph The graph. * \param name Name of the attribute. * \param sv String vector, the new attribute values. The length of this vector must * match the number of edges. * \return Error code. * * \sa \ref SETEASV for a simpler way. * * Time complexity: O(e+l), e is the number of edges, l is the * total length of the strings. */ int igraph_cattribute_EAS_setv(igraph_t *graph, const char *name, const igraph_strvector_t *sv) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *eal = &attr->eal; long int j; igraph_bool_t l = igraph_i_cattribute_find(eal, name, &j); /* Check length first */ if (igraph_strvector_size(sv) != igraph_ecount(graph)) { IGRAPH_ERROR("Invalid edge attribute vector length", IGRAPH_EINVAL); } if (l) { /* Already present, check type */ igraph_attribute_record_t *rec = VECTOR(*eal)[j]; igraph_strvector_t *str = (igraph_strvector_t *)rec->value; if (rec->type != IGRAPH_ATTRIBUTE_STRING) { IGRAPH_ERROR("Attribute type mismatch", IGRAPH_EINVAL); } igraph_strvector_clear(str); IGRAPH_CHECK(igraph_strvector_append(str, sv)); } else { /* Add it */ igraph_attribute_record_t *rec = igraph_Calloc(1, igraph_attribute_record_t); igraph_strvector_t *str; if (!rec) { IGRAPH_ERROR("Cannot add vertex attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, rec); rec->type = IGRAPH_ATTRIBUTE_STRING; rec->name = strdup(name); if (!rec->name) { IGRAPH_ERROR("Cannot add vertex attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, (char*)rec->name); str = igraph_Calloc(1, igraph_strvector_t); if (!str) { IGRAPH_ERROR("Cannot add vertex attribute", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, str); rec->value = str; IGRAPH_CHECK(igraph_strvector_copy(str, sv)); IGRAPH_FINALLY(igraph_strvector_destroy, str); IGRAPH_CHECK(igraph_vector_ptr_push_back(eal, rec)); IGRAPH_FINALLY_CLEAN(4); } return 0; } void igraph_i_cattribute_free_rec(igraph_attribute_record_t *rec) { if (rec->type == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_vector_t *num = (igraph_vector_t*)rec->value; igraph_vector_destroy(num); } else if (rec->type == IGRAPH_ATTRIBUTE_STRING) { igraph_strvector_t *str = (igraph_strvector_t*)rec->value; igraph_strvector_destroy(str); } else if (rec->type == IGRAPH_ATTRIBUTE_BOOLEAN) { igraph_vector_bool_t *boolvec = (igraph_vector_bool_t*)rec->value; igraph_vector_bool_destroy(boolvec); } igraph_Free(rec->name); igraph_Free(rec->value); igraph_Free(rec); } /** * \function igraph_cattribute_remove_g * Remove a graph attribute * * \param graph The graph object. * \param name Name of the graph attribute to remove. * * \sa \ref DELGA for a simpler way. * */ void igraph_cattribute_remove_g(igraph_t *graph, const char *name) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *gal = &attr->gal; long int j; igraph_bool_t l = igraph_i_cattribute_find(gal, name, &j); if (l) { igraph_i_cattribute_free_rec(VECTOR(*gal)[j]); igraph_vector_ptr_remove(gal, j); } else { IGRAPH_WARNING("Cannot remove non-existent graph attribute"); } } /** * \function igraph_cattribute_remove_v * Remove a vertex attribute * * \param graph The graph object. * \param name Name of the vertex attribute to remove. * * \sa \ref DELVA for a simpler way. * */ void igraph_cattribute_remove_v(igraph_t *graph, const char *name) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *val = &attr->val; long int j; igraph_bool_t l = igraph_i_cattribute_find(val, name, &j); if (l) { igraph_i_cattribute_free_rec(VECTOR(*val)[j]); igraph_vector_ptr_remove(val, j); } else { IGRAPH_WARNING("Cannot remove non-existent graph attribute"); } } /** * \function igraph_cattribute_remove_e * Remove an edge attribute * * \param graph The graph object. * \param name Name of the edge attribute to remove. * * \sa \ref DELEA for a simpler way. * */ void igraph_cattribute_remove_e(igraph_t *graph, const char *name) { igraph_i_cattributes_t *attr = graph->attr; igraph_vector_ptr_t *eal = &attr->eal; long int j; igraph_bool_t l = igraph_i_cattribute_find(eal, name, &j); if (l) { igraph_i_cattribute_free_rec(VECTOR(*eal)[j]); igraph_vector_ptr_remove(eal, j); } else { IGRAPH_WARNING("Cannot remove non-existent graph attribute"); } } /** * \function igraph_cattribute_remove_all * Remove all graph/vertex/edge attributes * * \param graph The graph object. * \param g Boolean, whether to remove graph attributes. * \param v Boolean, whether to remove vertex attributes. * \param e Boolean, whether to remove edge attributes. * * \sa \ref DELGAS, \ref DELVAS, \ref DELEAS, \ref DELALL for simpler * ways. */ void igraph_cattribute_remove_all(igraph_t *graph, igraph_bool_t g, igraph_bool_t v, igraph_bool_t e) { igraph_i_cattributes_t *attr = graph->attr; if (g) { igraph_vector_ptr_t *gal = &attr->gal; long int i, n = igraph_vector_ptr_size(gal); for (i = 0; i < n; i++) { igraph_i_cattribute_free_rec(VECTOR(*gal)[i]); } igraph_vector_ptr_clear(gal); } if (v) { igraph_vector_ptr_t *val = &attr->val; long int i, n = igraph_vector_ptr_size(val); for (i = 0; i < n; i++) { igraph_i_cattribute_free_rec(VECTOR(*val)[i]); } igraph_vector_ptr_clear(val); } if (e) { igraph_vector_ptr_t *eal = &attr->eal; long int i, n = igraph_vector_ptr_size(eal); for (i = 0; i < n; i++) { igraph_i_cattribute_free_rec(VECTOR(*eal)[i]); } igraph_vector_ptr_clear(eal); } } python-igraph-0.8.0/vendor/source/igraph/src/dotproduct.c0000644000076500000240000002166713614300625023745 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2014 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_games.h" #include "igraph_random.h" #include "igraph_constructors.h" #include "igraph_lapack.h" /** * \function igraph_dot_product_game * Generate a random dot product graph * * In this model, each vertex is represented by a latent * position vector. Probability of an edge between two vertices are given * by the dot product of their latent position vectors. * * * See also Christine Leigh Myers Nickel: Random dot product graphs, a * model for social networks. Dissertation, Johns Hopkins University, * Maryland, USA, 2006. * * \param graph The output graph is stored here. * \param vecs A matrix in which each latent position vector is a * column. The dot product of the latent position vectors should be * in the [0,1] interval, otherwise a warning is given. For * negative dot products, no edges are added; dot products that are * larger than one always add an edge. * \param directed Should the generated graph be directed? * \return Error code. * * Time complexity: O(n*n*m), where n is the number of vertices, * and m is the length of the latent vectors. * * \sa \ref igraph_sample_dirichlet(), \ref * igraph_sample_sphere_volume(), \ref igraph_sample_sphere_surface() * for functions to generate the latent vectors. */ int igraph_dot_product_game(igraph_t *graph, const igraph_matrix_t *vecs, igraph_bool_t directed) { igraph_integer_t nrow = igraph_matrix_nrow(vecs); igraph_integer_t ncol = igraph_matrix_ncol(vecs); int i, j; igraph_vector_t edges; igraph_bool_t warned_neg = 0, warned_big = 0; IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); RNG_BEGIN(); for (i = 0; i < ncol; i++) { int from = directed ? 0 : i + 1; igraph_vector_t v1; igraph_vector_view(&v1, &MATRIX(*vecs, 0, i), nrow); for (j = from; j < ncol; j++) { igraph_real_t prob; igraph_vector_t v2; if (i == j) { continue; } igraph_vector_view(&v2, &MATRIX(*vecs, 0, j), nrow); igraph_lapack_ddot(&v1, &v2, &prob); if (prob < 0 && ! warned_neg) { warned_neg = 1; IGRAPH_WARNING("Negative connection probability in " "dot-product graph"); } else if (prob > 1 && ! warned_big) { warned_big = 1; IGRAPH_WARNING("Greater than 1 connection probability in " "dot-product graph"); IGRAPH_CHECK(igraph_vector_push_back(&edges, i)); IGRAPH_CHECK(igraph_vector_push_back(&edges, j)); } else if (RNG_UNIF01() < prob) { IGRAPH_CHECK(igraph_vector_push_back(&edges, i)); IGRAPH_CHECK(igraph_vector_push_back(&edges, j)); } } } RNG_END(); igraph_create(graph, &edges, ncol, directed); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_sample_sphere_surface * Sample points uniformly from the surface of a sphere * * The center of the sphere is at the origin. * * \param dim The dimension of the random vectors. * \param n The number of vectors to sample. * \param radius Radius of the sphere, it must be positive. * \param positive Whether to restrict sampling to the positive * orthant. * \param res Pointer to an initialized matrix, the result is * stored here, each column will be a sampled vector. The matrix is * resized, as needed. * \return Error code. * * Time complexity: O(n*dim*g), where g is the time complexity of * generating a standard normal random number. * * \sa \ref igraph_sample_sphere_volume(), \ref * igraph_sample_dirichlet() for other similar samplers. */ int igraph_sample_sphere_surface(igraph_integer_t dim, igraph_integer_t n, igraph_real_t radius, igraph_bool_t positive, igraph_matrix_t *res) { igraph_integer_t i, j; if (dim < 2) { IGRAPH_ERROR("Sphere must be at least two dimensional to sample from " "surface", IGRAPH_EINVAL); } if (n < 0) { IGRAPH_ERROR("Number of samples must be non-negative", IGRAPH_EINVAL); } if (radius <= 0) { IGRAPH_ERROR("Sphere radius must be positive", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_matrix_resize(res, dim, n)); RNG_BEGIN(); for (i = 0; i < n; i++) { igraph_real_t *col = &MATRIX(*res, 0, i); igraph_real_t sum = 0.0; for (j = 0; j < dim; j++) { col[j] = RNG_NORMAL(0, 1); sum += col[j] * col[j]; } sum = sqrt(sum); for (j = 0; j < dim; j++) { col[j] = radius * col[j] / sum; } if (positive) { for (j = 0; j < dim; j++) { col[j] = fabs(col[j]); } } } RNG_END(); return 0; } /** * \function igraph_sample_sphere_volume * Sample points uniformly from the volume of a sphere * * The center of the sphere is at the origin. * * \param dim The dimension of the random vectors. * \param n The number of vectors to sample. * \param radius Radius of the sphere, it must be positive. * \param positive Whether to restrict sampling to the positive * orthant. * \param res Pointer to an initialized matrix, the result is * stored here, each column will be a sampled vector. The matrix is * resized, as needed. * \return Error code. * * Time complexity: O(n*dim*g), where g is the time complexity of * generating a standard normal random number. * * \sa \ref igraph_sample_sphere_surface(), \ref * igraph_sample_dirichlet() for other similar samplers. */ int igraph_sample_sphere_volume(igraph_integer_t dim, igraph_integer_t n, igraph_real_t radius, igraph_bool_t positive, igraph_matrix_t *res) { igraph_integer_t i, j; /* Arguments are checked by the following call */ IGRAPH_CHECK(igraph_sample_sphere_surface(dim, n, radius, positive, res)); RNG_BEGIN(); for (i = 0; i < n; i++) { igraph_real_t *col = &MATRIX(*res, 0, i); igraph_real_t U = pow(RNG_UNIF01(), 1.0 / dim); for (j = 0; j < dim; j++) { col[j] *= U; } } RNG_END(); return 0; } /** * \function igraph_sample_dirichlet * Sample points from a Dirichlet distribution * * \param n The number of vectors to sample. * \param alpha The parameters of the Dirichlet distribution. They * must be positive. The length of this vector gives the dimension * of the generated samples. * \param res Pointer to an initialized matrix, the result is stored * here, one sample in each column. It will be resized, as needed. * \return Error code. * * Time complexity: O(n * dim * g), where dim is the dimension of the * sample vectors, set by the length of alpha, and g is the time * complexity of sampling from a Gamma distribution. * * \sa \ref igraph_sample_sphere_surface() and * \ref igraph_sample_sphere_volume() for other methods to sample * latent vectors. */ int igraph_sample_dirichlet(igraph_integer_t n, const igraph_vector_t *alpha, igraph_matrix_t *res) { igraph_integer_t len = igraph_vector_size(alpha); igraph_integer_t i; igraph_vector_t vec; if (n < 0) { IGRAPH_ERROR("Number of samples should be non-negative", IGRAPH_EINVAL); } if (len < 2) { IGRAPH_ERROR("Dirichlet parameter vector too short, must " "have at least two entries", IGRAPH_EINVAL); } if (igraph_vector_min(alpha) <= 0) { IGRAPH_ERROR("Dirichlet concentration parameters must be positive", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_matrix_resize(res, len, n)); RNG_BEGIN(); for (i = 0; i < n; i++) { igraph_vector_view(&vec, &MATRIX(*res, 0, i), len); igraph_rng_get_dirichlet(igraph_rng_default(), alpha, &vec); } RNG_END(); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/bignum.c0000644000076500000240000013630413614300625023032 0ustar tamasstaff00000000000000/****************************************************************************** * bn.c - big number math implementation * * Copyright (c) 2004 by Juergen Buchmueller * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 2 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software Foundation, * Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA * * $Id: bignum.c,v 1.17 2005/07/23 02:55:53 pullmoll Exp $ ******************************************************************************/ #include #include "bignum.h" #include "config.h" #include "math.h" #include "igraph_error.h" #ifndef ASM_X86 #ifdef X86 #define ASM_X86 1 #endif #endif /** * @brief Return hex representation of a big number * * Returns the hex representation of a[], * where a is a big number integer with nlimb limbs. * * @param a pointer to an array of limbs * @param nlimb number of limbs in the array * * @result string containing the hex representation of a */ const char *bn2x(limb_t *a, count_t nlimb) { static IGRAPH_THREAD_LOCAL count_t which = 0; static IGRAPH_THREAD_LOCAL char *xbuff[8] = { NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL }; char *dst; count_t size; count_t n = nlimb; if (0 == n) { return "0"; } which = (which + 1) % 8; size = 8 * n + 1; if (NULL != xbuff[which]) { free(xbuff[which]); } dst = xbuff[which] = calloc(size, sizeof(char)); if (NULL == dst) { return "memory error"; } while (n-- > 0) { dst += snprintf(dst, size, "%08x", a[n]); size -= 8; } return xbuff[which]; } /** * @brief Return decimal representation of a big number * * Returns the decimal representation of a[], * where a is a big number integer with nlimb limbs. * * @param a pointer to an array of limbs * @param nlimb number of limbs in the array * * @result string containing the decimal representation of a */ const char *bn2d(limb_t *a, count_t nlimb) { static IGRAPH_THREAD_LOCAL count_t which = 0; static IGRAPH_THREAD_LOCAL char *dbuff[8] = { NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL }; static IGRAPH_THREAD_LOCAL limb_t v[BN_MAXSIZE]; limb_t r; char *dst; count_t size; count_t n = bn_sizeof(a, nlimb); if (0 == n) { return "0"; } bn_copy(v, a, n); which = (which + 1) % 8; size = 12 * n + 1; if (NULL != dbuff[which]) { free(dbuff[which]); } dst = dbuff[which] = calloc(size, sizeof(char)); if (NULL == dst) { return "memory error"; } size--; while (0 != bn_cmp_limb(v, 0, n)) { r = bn_div_limb(v, v, 10, n); dst[--size] = '0' + (char) r; } return &dst[size]; } /** * @brief Return decimal representation of a big number pair * * Returns the decimal representation of a[].b[], * where a is a big number integer with alimb limbs, * and b is a multiprecision fixed fraction with blimb limbs. * * @param a pointer to an array of limbs * @param alimb number of limbs in the a array * @param b pointer to an array of limbs * @param blimb number of limbs in the b array * * @result string containing the decimal representation of a.b */ const char *bn2f(limb_t *a, count_t alimb, limb_t *b, count_t blimb) { static IGRAPH_THREAD_LOCAL count_t which = 0; static IGRAPH_THREAD_LOCAL char *dbuff[8] = { NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL }; static IGRAPH_THREAD_LOCAL limb_t v[BN_MAXSIZE]; static IGRAPH_THREAD_LOCAL limb_t w[BN_MAXSIZE]; limb_t r; char *dst; count_t size; bn_copy(v, a, alimb); bn_copy(w, b, blimb); which = (which + 1) % 8; size = 12 * (alimb + blimb) + 1 + 1; if (NULL != dbuff[which]) { free(dbuff[which]); } dst = dbuff[which] = calloc(size, sizeof(char)); if (NULL == dst) { return "memory error"; } size = 12 * alimb; while (0 != bn_cmp_limb(w, 0, blimb) && size < 12 * (alimb + blimb)) { r = bn_mul_limb(w, w, 10, blimb); dst[size++] = '0' + (char) r; } size = 12 * alimb; dst[size] = '.'; while (0 != bn_cmp_limb(v, 0, alimb) && size > 0) { r = bn_div_limb(v, v, 10, alimb); dst[--size] = '0' + (char) r; } return &dst[size]; } /** * @brief Return binary representation of a big number * * Returns the binary representation of a[], * where a is a big number integer with nlimb limbs. * * @param a pointer to an array of limbs * @param nlimb number of limbs in the array * * @result string containing the binary representation of a */ const char *bn2b(limb_t *a, count_t nlimb) { static IGRAPH_THREAD_LOCAL count_t which = 0; static IGRAPH_THREAD_LOCAL char *bbuff[8] = { NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL }; limb_t r; char *dst; count_t size; count_t n = bn_sizeof(a, nlimb); if (0 == n) { return "0"; } which = (which + 1) % 8; size = LIMBBITS * n + 1; if (NULL != bbuff[which]) { free(bbuff[which]); } dst = bbuff[which] = calloc(size, sizeof(char)); if (NULL == dst) { return "memory error"; } n = 0; size--; while (size-- > 0) { r = (a[n / LIMBBITS] >> (n % LIMBBITS)) & 1; n++; dst[size] = '0' + (char) r; } return &dst[size]; } /** * @brief Zero an array of limbs * * Sets a[] = 0 * where a is a big number integer of nlimb limbs. * * @param a pointer to an array of limbs * @param nlimb number of limbs in the array * */ void bn_zero(limb_t a[], count_t nlimb) { memset(a, 0, nlimb * sizeof(limb_t)); } /** * @brief Set an array of limbs to a single limb value * * Sets a[] = d * where a is a big number integer of nlimb limbs, * and d is a single limb * * @param a pointer to an array of limbs to set * @param d limb value to set a to * @param nlimb number of limbs in the array * */ void bn_limb(limb_t a[], limb_t d, count_t nlimb) { memset(a, 0, nlimb * sizeof(limb_t)); a[0] = d; } /** * @brief Copy an array of limbs * * Sets a[] = b[] * where a and b are a big number integers of nlimb limbs * * @param a pointer to an array of limbs (destination) * @param b pointer to an array of limbs (source) * @param nlimb number of limbs in the arrays */ void bn_copy(limb_t a[], limb_t b[], count_t nlimb) { memcpy(a, b, nlimb * sizeof(limb_t)); } /** * @brief Return significant size of a big number * * Returns size of significant limbs in a[] * i.e. searches for the first non-zero limb from * nlimb-1 downto 0. * * @param a pointer to an array of limbs (candidate) * @param nlimb number of limbs in the arrays * * @result number of significant limbs in a */ count_t bn_sizeof(limb_t a[], count_t nlimb) { while (nlimb-- > 0) if (0 != a[nlimb]) { return ++nlimb; } return 0; } /** * @brief Return sign of a bignum minus a limb * * Returns the sign of (a[] - b) * where a is a big number integer of nlimb limbs, * and b is a single limb + * @param a pointer to an array of limbs (minuend) * @param b a single limb (subtrahend) * @param nlimb number of limbs in the array a * * @result sign of the comparison: -1 ab */ int bn_cmp_limb(limb_t a[], limb_t b, count_t nlimb) { if (0 == nlimb) { return 0; } while (nlimb-- > 1) if (0 != a[nlimb]) { return +1; } if (a[0] < b) { return -1; } if (a[0] > b) { return +1; } return 0; } /** * @brief Return sign of bignum a minus bignum b * * Returns the sign of (a[] - b[]) * where a and b are a big number integers of nlimb limbs * * @param a pointer to an array of limbs (minuend) * @param b pointer to an array of limbs (subtrahend) * @param nlimb number of limbs in the arrays * * @result sign of the comparison: -1 ab */ int bn_cmp(limb_t a[], limb_t b[], count_t nlimb) { if (0 == nlimb) { return 0; } while (nlimb-- > 0) { if (a[nlimb] > b[nlimb]) { return +1; /* GT */ } if (a[nlimb] < b[nlimb]) { return -1; /* LT */ } } return 0; /* EQ */ } /** * @brief Single limb is even test * * Returns 1 if a is even, else 0 * where a is a single limb * * @param a a single limb * * @result zero if a is odd, 1 if a is even */ int sl_iseven(limb_t a) { return (a & 1) ? 0 : 1; } /** * @brief bignum is even test * * Returns 1 if a[] is even, else 0 * where a is a big number integer of nlimb limbs * Note: a zero limb big number integer is even! * * @param a pointer to an array of limbs * @param nlimb number of limbs in the arrays * * @result zero if a is odd, 1 if a is even */ int bn_iseven(limb_t *a, count_t nlimb) { if (0 == nlimb) { return 1; } return (a[0] & 1) ? 0 : 1; } /** * @brief Add a single limb to a bignum * * Computes w[] = u[] + v * where w, u are big number integers of nlimb lims each, * and v is a single limb. * Returns carry if the addition overflows. * * Ref: Derived from Knuth Algorithm A. * * @param w pointer to an array of limbs receiving result * @param u pointer to an array of limbs (addend 1) * @param v a single limb * @param nlimb number of limbs in the arrays w and u * * @result The carry status of the addition */ limb_t bn_add_limb(limb_t w[], limb_t u[], limb_t v, count_t nlimb) { limb_t carry; count_t j; /* Copy u to w, so we can bail out if no borrow is left */ if (w != u) { bn_copy(w, u, nlimb); } /* Add v to first limb of u */ w[0] += v; carry = (w[0] < v ? 1 : 0); /* Add carry to subsequent limbs */ for (j = 1; 0 != carry && j < nlimb; j++) { w[j] += carry; carry = (w[j] < carry ? 1 : 0); } return carry; } /** * @brief Subtract a single limb from a bignum * * Computes w[] = u[] - v * where w, u are big number integers of nlimb limbs each, * and v is a single limb. * Returns borrow (0 if u >= v, or 1 if v > u). * * Ref: Derived from Knuth Algorithm S. * * @param w pointer to an array of limbs receiving the result * @param u pointer to an array of limbs (minuend) * @param v single limb (subtrahend) * @param nlimb number of limbs in the arrays * * @result borrow of the subtraction (0 if u >= v, 1 if u < v) */ limb_t bn_sub_limb(limb_t w[], limb_t u[], limb_t v, count_t nlimb) { limb_t borrow; count_t j; /* Copy u to w, so we can bail out if no borrow is left */ if (w != u) { bn_copy(w, u, nlimb); } /* Subtract v from first limb of u */ w[0] -= v; borrow = (w[0] > ~v ? 1 : 0); /* Subtract borrow from subsequent limbs */ for (j = 1; 0 != borrow && j < nlimb; j++) { w[j] -= borrow; borrow = (w[j] > ~borrow ? 1 : 0); } return borrow; } /** * @brief Divide a bignum by a single limb * * Computes quotient q[] = u[] / v * and returns remainder r = u[] % v * where q, u are big number integers of nlimb limbs each, * and v is a single limb. * * Makes no assumptions about normalisation. * * Ref: Knuth Vol 2 Ch 4.3.1 Exercise 16 p625 * * @param q pointer to an array of limbs receiving the quotient * @param u pointer to an array of limbs (dividend) * @param v single limb (divisor) * @param nlimb number of limbs in the arrays * * @result single limb remainder of the division (modulo) */ limb_t bn_div_limb(limb_t q[], limb_t u[], limb_t v, count_t nlimb) { count_t j; limb_t t[2], r; count_t shift; if (0 == nlimb) { return 0; } if (0 == v) { return LIMBMASK; /* Divide by zero error */ } /* * Normalize first: * qequires high bit of V to be set, * so find most significant by shifting * until DIGMSB is set. */ for (shift = 0; 0 == (v & DIGMSB); shift++) { v <<= 1; } r = bn_shl(q, u, shift, nlimb); j = nlimb; while (j-- > 0) { t[0] = q[j]; t[1] = r; sl_div(&q[j], &r, t, v); } /* Unnormalize */ r >>= shift; return r; } /** * @brief Modulo a bignum by a single limb * * Computes remainder (modulo) r = u[] mod v * Computes r = u[] mod v * where u is a big number integer of nlimb * and r, v are single precision limbs * * Use remainder from divide function. * * @param u pointer to an array of limbs (dividend) * @param v single limb (divisor) * @param nlimb number of limbs in the arrays * * @result single limb remainder of the division (modulo) */ limb_t bn_mod_limb(limb_t u[], limb_t v, count_t nlimb) { static IGRAPH_THREAD_LOCAL limb_t q[2 * BN_MAXSIZE]; limb_t r; r = bn_div_limb(q, u, v, nlimb); bn_zero(q, nlimb); return r; } /** * @brief Multiply a bignum by a single limb * * Computes product w[] = u[] * v * Returns overflow k * where w, u are big number integers of nlimb each * and v is a single limb * * @param w pointer to an array of limbs to receive the result * @param u pointer to an array of limbs (factor) * @param v single limb (other factor) * @param nlimb number of limbs in the arrays * * @result zero if no overflow, else overflow (value of w[nlimb]) */ limb_t bn_mul_limb(limb_t w[], limb_t u[], limb_t v, count_t nlimb) { limb_t t[2]; limb_t carry; count_t j; if (0 == v) { bn_zero(w, nlimb); return 0; } for (j = 0, carry = 0; j < nlimb; j++) { sl_mul(t, u[j], v); w[j] = t[0] + carry; carry = t[1] + (w[j] < carry ? 1 : 0); } return carry; } #if HAVE_U64 /** * @brief Computes quotient and remainder of 64 bit / 32 bit * * Computes quotient q = u[] / v, remainder r = u[] mod v * where u[] is a double limb. * * With native support for double limb division * * @param q pointer to the limb to receive the quotient * @param r pointer to the limb to receive the remainder * @param u pointer to an array of two limbs * @param v single limb divisor * * @result zero on success */ limb_t sl_div(limb_t *q, limb_t *r, limb_t u[2], limb_t v) { #if ASM_X86 limb_t qq; limb_t rr; if (0 == v) /* division by zero */ { return LIMBMASK; } asm volatile( "divl %4" : "=a"(qq), "=d"(rr) : "a"(u[0]), "d"(u[1]), "g"(v)); *q = qq; *r = rr; #else dlimb_t dd; if (0 == v) /* division by zero */ { return LIMBMASK; } dd = ((dlimb_t)u[1] << LIMBBITS) | u[0]; *q = (limb_t) (dd / v); *r = dd % v; #endif return 0; } #else #define B (HALFMASK + 1) /** * @brief Computes quotient and remainder of 64 bit / 32 bit * * Computes quotient q = u / v, remainder r = u mod v * where u is a double limb * and q, v, r are single precision limbs. * Returns high limb of quotient (max value is 1) * Assumes normalized such that v1 >= b/2 * where b is size of HALF_DIGIT * i.e. the most significant bit of v should be one * * In terms of half-limbs in Knuth notation: * (q2q1q0) = (u4u3u2u1u0) / (v1v0) * (r1r0) = (u4u3u2u1u0) % (v1v0) * for m = 2, n = 2 where u4 = 0 * * We set q = (q1q0) and return q2 as "overflow' * Returned q2 is either 0 or 1. * * @param q pointer to the limb to receive the quotient * @param r pointer to the limb to receive the remainder * @param u pointer to an array of two limbs * @param v single limb divisor * * @result zero on success */ limb_t sl_div(limb_t *q, limb_t *r, limb_t u[2], limb_t v) { limb_t quot; limb_t rem; limb_t ul; limb_t uh; limb_t p0; limb_t p1; limb_t v0; limb_t v1; limb_t u0; limb_t u1; limb_t u2; limb_t u3; limb_t borrow; limb_t q1; limb_t q2; limb_t s; limb_t t; /* Check for normalisation */ if (0 == (v & DIGMSB)) { *q = *r = 0; return LIMBMASK; } /* Split up into half-limbs */ v0 = LSH(v); v1 = MSH(v); u0 = LSH(u[0]); u1 = MSH(u[0]); u2 = LSH(u[1]); u3 = MSH(u[1]); /* Do three rounds of Knuth Algorithm D Vol 2 p272 */ /* * ROUND 1 calculate q2: * estimate quot = (u4u3)/v1 = 0 or 1, * then set (u4u3u2) -= quot*(v1v0) where u4 = 0. */ quot = u3 / v1; if (quot > 0) { rem = u3 - quot * v1; t = SHL(rem) | u2; if (quot * v0 > t) { quot--; } } uh = 0; /* (u4) */ ul = u[1]; /* (u3u2) */ if (quot > 0) { /* (u4u3u2) -= quot*(v1v0) where u4 = 0 */ p0 = quot * v0; p1 = quot * v1; s = p0 + SHL(p1); ul -= s; borrow = (ul > ~s ? 1 : 0); uh -= MSH(p1) - borrow; if (0 != MSH(uh)) { /* add back */ quot--; ul += v; uh = 0; } } q2 = quot; /* * ROUND 2 calculate q1: * estimate quot = (u3u2) / v1, * then set (u3u2u1) -= quot*(v1v0) */ t = ul; quot = t / v1; rem = t - quot * v1; /* Test on v0 */ t = SHL(rem) | u1; if (B == quot || (quot * v0) > t) { quot--; rem += v1; t = SHL(rem) | u1; if (rem < B && (quot * v0) > t) { quot--; } } /* * multiply and subtract: * (u3u2u1)' = (u3u2u1) - quot*(v1v0) */ uh = MSH(ul); /* (0u3) */ ul = SHL(ul) | u1; /* (u2u1) */ p0 = quot * v0; p1 = quot * v1; s = p0 + SHL(p1); ul -= s; borrow = (ul > ~s ? 1 : 0); uh -= MSH(p1) - borrow; if (0 != MSH(uh)) { /* add back v */ quot--; ul += v; uh = 0; } /* quotient q1 */ q1 = quot; /* * ROUND 3: * calculate q0; estimate quot = (u2u1) / v1, * then set (u2u1u0) -= quot(v1v0) */ t = ul; quot = t / v1; rem = t - quot * v1; /* Test on v0 */ t = SHL(rem) | u0; if (B == quot || (quot * v0) > t) { quot--; rem += v1; t = SHL(rem) | u0; if (rem < B && (quot * v0) > t) { quot--; } } /* * multiply and subtract: * (u2u1u0)" = (u2u1u0)' - quot(v1v0) */ uh = MSH(ul); /* (0u2) */ ul = SHL(ul) | u0; /* (u1u0) */ p0 = quot * v0; p1 = quot * v1; s = p0 + SHL(p1); ul -= s; borrow = (ul > ~s ? 1 : 0); uh -= MSH(p1) - borrow; if (0 != MSH(uh)) { /* add back v */ quot--; ul += v; uh = 0; } /* quotient q1q0 */ *q = SHL(q1) | LSH(quot); /* Remainder is in (u1u0) i.e. ul */ *r = ul; /* quotient q2 (overflow) is returned */ return q2; } #endif /* HAVE_U64 */ /** * @brief Return greatest common divisor of two single limbs * * Returns gcd(x, y) * * Ref: Schneier 2nd ed, p245 * * @param x single limb candidate #1 * @param y single limb candidate #2 * * @result return zero if x and y are zero, else gcd(x,y) */ limb_t sl_gcd(limb_t x, limb_t y) { limb_t g; if (x + y == 0) { return 0; /* Error */ } g = y; while (x > 0) { g = x; x = y % x; y = g; } return g; } /** * @brief Compute single limb exp = x^e mod m * * Computes exp = x^e mod m * Binary left-to-right method * * @param exp pointer to limb to receive result * @param x single limb x (base) * @param e single limb e (exponent) * @param m single limb m (modulus) * * @result zero on success (always!?) */ int sl_modexp(limb_t *exp, limb_t x, limb_t e, limb_t m) { limb_t mask; limb_t y; /* Temp variable */ /* Find most significant bit in e */ for (mask = DIGMSB; mask > 0; mask >>= 1) { if (e & mask) { break; } } y = x; for (mask >>= 1; mask > 0; mask >>= 1) { sl_modmul(&y, y, y, m); /* y = (y^2) % m */ if (e & mask) { sl_modmul(&y, y, x, m); /* y = (y*x) % m*/ } } *exp = y; return 0; } /** * @brief Compute single limb inverse inv = u^(-1) % v * * Computes inv = u^(-1) % v * Ref: Knuth Algorithm X Vol 2 p 342 * ignoring u2, v2, t2 and avoiding negative numbers * * @param inv pointer to limb to receive result * @param u single limb to inverse * @param v single limb modulus * * @result zero on success (always!?) */ int sl_modinv(limb_t *inv, limb_t u, limb_t v) { limb_t u1, u3, v1, v3, t1, t3, q, w; int iter = 1; /* Step X1. Initialize */ u1 = 1; u3 = u; v1 = 0; v3 = v; /* Step X2. */ while (v3 != 0) { /* Step X3. */ q = u3 / v3; /* Divide and */ t3 = u3 % v3; w = q * v1; /* "Subtract" */ t1 = u1 + w; /* Swap */ u1 = v1; v1 = t1; u3 = v3; v3 = t3; iter = -iter; } if (iter < 0) { *inv = v - u1; } else { *inv = u1; } return 0; } /** * @brief Compute single limb a = (x * y) % mod * * Computes a = (x * y) % m * * @param a pointer to single limb to receive result * @param x single limb factor 1 * @param y single limb factor 2 * @param m single limb modulus * * @result zero on success (always!?) */ int sl_modmul(limb_t *a, limb_t x, limb_t y, limb_t m) { static IGRAPH_THREAD_LOCAL limb_t pp[2]; /* pp[] = x * y */ sl_mul(pp, x, y); /* *a = pp[] % m */ *a = bn_mod_limb(pp, m, 2); /* Clean temp */ pp[0] = pp[1] = 0; return 0; } #if HAVE_U64 /** * @brief Compute double limb product of two single limbs * * Computes p[] = x * y * where p is two limbs (double precision) and x, y are single * limbs. Use double precision natively supported on this machine. * * @param p pointer to an array of two limbs receiving the result * @param x single limb factor #1 * @param y single limb factor #2 * * @result zero on success (always) */ int sl_mul(limb_t p[2], limb_t x, limb_t y) { dlimb_t dd; dd = (dlimb_t)x * y; p[0] = (limb_t)dd; p[1] = (limb_t)(dd >> 32); return 0; } #else /** * @brief Compute double limb product of two single limbs * * Computes p[] = x * y * Source: Arbitrary Precision Computation * http://numbers.computation.free.fr/Constants/constants.html * * The limbs x and y are split in halves and the four products * x1*y1, x0*y1, x1*y0 and x0*y0 are added shifting them to * their respective least significant bit position: * p[1] = x1*y1 + high(x0*y1 + x1*y0) + ch << 16 + cl * p[0] = x0*y0 + low(x0*y1 + x1*y0) << 16 * ch = carry from adding x0*y1 + x1*y0 * cl = carry from adding low(x0*y1 + x1*y0) << 16 to p[0] * * @param p pointer to an array of two limbs receiving the result * @param x single limb factor #1 * @param y single limb factor #2 * * @result zero on success (always) */ int sl_mul(limb_t p[2], limb_t x, limb_t y) { limb_t x0, y0, x1, y1; limb_t t, u, carry; /* * Split each x,y into two halves * x = x0 + B*x1 * y = y0 + B*y1 * where B = 2^16, half the limb size * Product is * xy = x0y0 + B(x0y1 + x1y0) + B^2(x1y1) */ x0 = LSH(x); x1 = MSH(x); y0 = LSH(y); y1 = MSH(y); /* Compute low part (w/o carry) */ p[0] = x0 * y0; /* middle part */ t = x0 * y1; u = x1 * y0; t += u; carry = (t < u ? 1 : 0); /* * The carry will go to high half of p[1], * and the high half of t will go into the * into low half of p[1] */ carry = SHL(carry) + MSH(t); /* add low half of t to high half of p[0] */ t = SHL(t); p[0] += t; if (p[0] < t) { carry++; } p[1] = x1 * y1 + carry; return 0; } #endif /* HAVE_U64 */ /** * @brief Compute division of big number by a "half digit" * * Computes q[] = u[] / v, also returns r = u[] % v * where q, a are big number integers of nlimb limbs each, * and d, r are single limbs * * Using bit-by-bit method from MSB to LSB, * so v must be <= HALFMASK * * According to "Principles in PGP by Phil Zimmermann" * * @param q pointer to an array of limbs to receive the result * @param u pointer to an array of limbs (dividend) * @param v single limb (actually half limb) divisor * @param nlimb number of limbs in the arrays * * @result returns remainder of the division */ limb_t bn_div_hdig(limb_t q[], limb_t u[], limb_t v, count_t nlimb) { limb_t mask = DIGMSB; limb_t r = 0; if (v > HALFMASK) { igraph_errorf("bn_div_hdig called with v:%x", __FILE__, __LINE__, (int) v); } if (0 == nlimb) { return 0; } if (0 == v) { return 0; /* Divide by zero error */ } /* Initialize quotient */ bn_zero(q, nlimb); /* Work from MSB to LSB */ while (nlimb > 0) { /* Multiply remainder by 2 */ r <<= 1; /* Look at current bit */ if (u[nlimb - 1] & mask) { r++; } if (r >= v) { /* Remainder became greater than divisor */ r -= v; q[nlimb - 1] |= mask; } /* next bit */ mask >>= 1; if (0 != mask) { continue; } /* next limb */ --nlimb; mask = DIGMSB; } return r; } /** * @brief Compute single limb remainder of bignum % single limb * * Computes r = u[] % v * where a is a big number integer of nlimb * and r, v are single limbs, using bit-by-bit * method from MSB to LSB. * * Ref: * Derived from principles in PGP by Phil Zimmermann * Note: * This method will only work until r <<= 1 overflows. * i.e. for d < DIGMSB, but we keep HALF_DIGIT * limit for safety, and also because we don't * have a 32nd bit. * * @param u pointer to big number to divide * @param v single limb (actually half limb) modulus * @param nlimb number of limbs in the array * * @result returns remainder of the division */ limb_t bn_mod_hdig(limb_t u[], limb_t v, count_t nlimb) { limb_t mask; limb_t r; if (0 == nlimb) { return 0; } if (0 == v) { return 0; /* Divide by zero error */ } if (v > HALFMASK) { igraph_errorf("bn_mod_hdig called with v:%x", __FILE__, __LINE__, (int) v); } /* Work from left to right */ mask = DIGMSB; r = 0; while (nlimb > 0) { /* Multiply remainder by 2 */ r <<= 1; /* Look at current bit */ if (u[nlimb - 1] & mask) { r++; } if (r >= v) /* Remainder became greater than divisor */ { r -= v; } /* next bit */ mask >>= 1; if (0 != mask) { continue; } /* next limb */ --nlimb; mask = DIGMSB; } return r; } /** * @brief Addition of two bignum arrays * * Computes w[] = u[] + v[] * where w, u, v are big number integers of nlimb limbs each. * Returns carry, i.e. w[nlimb], as 0 or 1. * * Ref: Knuth Vol 2 Ch 4.3.1 p 266 Algorithm A. * * @param w pointer to array of limbs to receive the result * @param u pointer to array of limbs (addend #1) * @param v pointer to array of limbs (addend #2) * @param nlimb number of limbs in the arrays * * @result returns the carry, i.e. w[nlimb], as 0 or 1 */ limb_t bn_add(limb_t w[], limb_t u[], limb_t v[], count_t nlimb) { limb_t carry; count_t j; for (j = 0, carry = 0; j < nlimb; j++) { /* * add limbs w[j] = u[j] + v[j] + carry; * set carry = 1 if carry (overflow) occurs */ w[j] = u[j] + carry; carry = (w[j] < carry ? 1 : 0); w[j] = w[j] + v[j]; if (w[j] < v[j]) { carry++; } } /* w[n] = carry */ return carry; } /** * @brief Subtraction of two bignum arrays * * Calculates w[] = u[] - v[] where u[] >= v[] * w, u, v are big number integers of nlimb limbs each * Returns 0 if ok, or 1 if v was greater than u. * * Ref: Knuth Vol 2 Ch 4.3.1 p 267 Algorithm S. * * @param w pointer to array of limbs to receive the result * @param u pointer to array of limbs (minuend) * @param v pointer to array of limbs (subtrahend) * @param nlimb number of limbs in the arrays * * @result zero on success, 1 if v was greater than u */ limb_t bn_sub(limb_t w[], limb_t u[], limb_t v[], count_t nlimb) { limb_t borrow; count_t j; for (j = 0, borrow = 0; j < nlimb; j++) { /* * Subtract limbs w[j] = u[j] - v[j] - borrow; * set borrow = 1 if borrow occurs */ w[j] = u[j] - borrow; borrow = (w[j] > ~borrow ? 1 : 0); w[j] = w[j] - v[j]; if (w[j] > ~v[j]) { borrow++; } } /* borrow should be 0, if u >= v */ return borrow; } /** * @brief Product of two bignum arrays * * Computes product w[] = u[] * v[] * where u, v are big number integers of nlimb each * and w is a big number integer of 2*nlimb limbs. * * Ref: Knuth Vol 2 Ch 4.3.1 p 268 Algorithm M. * * @param w pointer to array of limbs to receive the result * @param u pointer to array of limbs (factor #1) * @param v pointer to array of limbs (factor #2) * @param nlimb number of limbs in the arrays * * @result zero on success (always!?) */ int bn_mul(limb_t w[], limb_t u[], limb_t v[], count_t nlimb) { limb_t t[2]; limb_t carry; count_t i, j, m, n; m = n = nlimb; /* zero result */ bn_zero(w, 2 * nlimb); for (j = 0; j < n; j++) { /* zero multiplier? */ if (0 == v[j]) { w[j + m] = 0; continue; } /* Initialize i */ carry = 0; for (i = 0; i < m; i++) { /* * Multiply and add: * t = u[i] * v[j] + w[i+j] + carry */ sl_mul(t, u[i], v[j]); t[0] += carry; if (t[0] < carry) { t[1]++; } t[0] += w[i + j]; if (t[0] < w[i + j]) { t[1]++; } w[i + j] = t[0]; carry = t[1]; } w[j + m] = carry; } return 0; } /** * @brief Shift left a bignum by a number of bits (less than LIMBBITS) * * Computes a[] = b[] << x * Where a and b are big number integers of nlimb each. * The shift count must be less than LIMBBITS * * @param a pointer to array of limbs to receive the result * @param b pointer to array of limbs to shift left * @param x number of bits to shift (must be less than LIMBBITS) * @param nlimb number of limbs in the arrays * * @result returns a single limb "carry", i.e. bits that came out left */ limb_t bn_shl(limb_t a[], limb_t b[], count_t x, count_t nlimb) { count_t i, y; limb_t carry, temp; if (0 == nlimb) { return 0; } if (0 == x) { /* no shift at all */ if (a != b) { bn_copy(a, b, nlimb); } return 0; } /* check shift amount */ if (x >= LIMBBITS) { igraph_errorf("bn_shl() called with x >= %d", __FILE__, __LINE__, LIMBBITS); return 0; } y = LIMBBITS - x; carry = 0; for (i = 0; i < nlimb; i++) { temp = b[i] >> y; a[i] = (b[i] << x) | carry; carry = temp; } return carry; } /** * @brief Shift right a bignum by a number of bits (less than LIMBBITS) * * Computes a[] = b[] >> x * Where a and b are big number integers of nlimb each. * The shift count must be less than LIMBBITS * * @param a pointer to array of limbs to receive the result * @param b pointer to array of limbs to shift right * @param x number of bits to shift (must be less than LIMBBITS) * @param nlimb number of limbs in the arrays * * @result returns a single limb "carry", i.e. bits that came out right */ limb_t bn_shr(limb_t a[], limb_t b[], count_t x, count_t nlimb) { count_t i, y; limb_t carry, temp; if (0 == nlimb) { return 0; } if (0 == x) { /* no shift at all */ if (a != b) { bn_copy(a, b, nlimb); } return 0; } /* check shift amount */ if (x >= LIMBBITS) { igraph_errorf("bn_shr() called with x >= %d", __FILE__, __LINE__, LIMBBITS); } y = LIMBBITS - x; carry = 0; i = nlimb; while (i-- > 0) { temp = b[i] << y; a[i] = (b[i] >> x) | carry; carry = temp; } return carry; } /** * @brief Check a quotient for overflow * * Returns 1 if quot is too big, * i.e. if (quot * Vn-2) > (b.rem + Uj+n-2) * Returns 0 if ok * * @param quot quotient under test * @param rem remainder * @param * * @result zero on success */ static int quot_overflow(limb_t quot, limb_t rem, limb_t v, limb_t u) { limb_t t[2]; sl_mul(t, quot, v); if (t[1] < rem) { return 0; } if (t[1] > rem) { return 1; } if (t[0] > u) { return 1; } return 0; } /** * @brief Compute quotient and remainder of bignum division * * Computes quotient q[] = u[] / v[] * and remainder r[] = u[] % v[] * where q, r, u are big number integers of ulimb limbs, * and the divisor v of vlimb limbs. * * Ref: Knuth Vol 2 Ch 4.3.1 p 272 Algorithm D. * * @param q pointer to array of limbs to receive quotient * @param r pointer to array of limbs to receive remainder * @param u pointer to array of limbs (dividend) * @param ulimb number of limbs in the q, r, u arrays * @param v pointer to array of limbs (divisor) * @param vlimb number of limbs in the v array * * @result zero on success, LIMBASK on division by zero */ int bn_div(limb_t q[], limb_t r[], limb_t u[], limb_t v[], count_t ulimb, count_t vlimb) { static IGRAPH_THREAD_LOCAL limb_t qq[BN_MAXSIZE]; static IGRAPH_THREAD_LOCAL limb_t uu[BN_MAXSIZE]; static IGRAPH_THREAD_LOCAL limb_t vv[BN_MAXSIZE]; limb_t mask; limb_t overflow; limb_t quot; limb_t rem; limb_t t[2]; limb_t *ww; count_t n, m, i, j, shift; int ok, cmp; /* find size of v */ n = bn_sizeof(v, vlimb); /* Catch special cases */ if (0 == n) { return (int) LIMBMASK; /* Error: divide by zero */ } if (1 == n) { /* Use short division instead */ r[0] = bn_div_limb(q, u, v[0], ulimb); return 0; } /* find size of u */ m = bn_sizeof(u, ulimb); if (m < n) { /* v > u: just set q = 0 and r = u */ bn_zero(q, ulimb); bn_copy(r, u, ulimb); return 0; } if (m == n) { /* u and v are the same length: compare them */ cmp = bn_cmp(u, v, (unsigned int)n); if (0 == cmp) { /* v == u: set q = 1 and r = 0 */ bn_limb(q, 1, ulimb); bn_zero(r, ulimb); return 0; } if (cmp < 0) { /* v > u: set q = 0 and r = u */ bn_zero(q, ulimb); bn_copy(r, u, ulimb); return 0; } } /* m greater than or equal to n */ m -= n; /* clear quotient qq */ bn_zero(qq, ulimb); /* * Normalize v: requires high bit of v[n-1] to be set, * so find most significant bit, then shift left */ mask = DIGMSB; for (shift = 0; shift < LIMBBITS; shift++) { if (v[n - 1] & mask) { break; } mask >>= 1; } /* normalize vv from v */ overflow = bn_shl(vv, v, shift, n); /* copy normalized dividend u into remainder uu */ overflow = bn_shl(uu, u, shift, n + m); /* new limb u[m+n] */ t[0] = overflow; j = m + 1; while (j-- > 0) { /* quot = (b * u[j+n] + u[j+n-1]) / v[n-1] */ ok = 0; /* This is Uj+n */ t[1] = t[0]; t[0] = uu[j + n - 1]; overflow = sl_div(", &rem, t, vv[n - 1]); if (overflow) { /* quot = b */ quot = LIMBMASK; rem = uu[j + n - 1] + vv[n - 1]; if (rem < vv[n - 1]) { ok = 1; } } if (0 == ok && quot_overflow(quot, rem, vv[n - 2], uu[j + n - 2])) { /* quot * v[n-2] > b * rem + u[j+n-2] */ quot--; rem += vv[n - 1]; if (rem >= vv[n - 1]) if (quot_overflow(quot, rem, vv[n - 2], uu[j + n - 2])) { quot--; } } /* multiply and subtract vv[] * quot */ ww = &uu[j]; if (0 == quot) { overflow = 0; } else { /* quot is non zero */ limb_t tt[2]; limb_t borrow; for (i = 0, borrow = 0; i < n; i++) { sl_mul(tt, quot, vv[i]); ww[i] -= borrow; borrow = (ww[i] > ~borrow ? 1 : 0); ww[i] -= tt[0]; if (ww[i] > ~tt[0]) { borrow++; } borrow += tt[1]; } /* * w[n] is not in array w[0..n-1]: * subtract final borrow */ overflow = t[1] - borrow; } /* test for remainder */ if (overflow) { quot--; /* add back if mul/sub was negative */ overflow = bn_add(ww, ww, vv, n); } qq[j] = quot; /* u[j+n] for next round */ t[0] = uu[j + n - 1]; } /* clear uu[] limbs from n to n+m */ for (j = n; j < m + n; j++) { uu[j] = 0; } /* denormalize remainder */ bn_shr(r, uu, shift, n); /* copy quotient */ bn_copy(q, qq, n + m); /* clear temps */ bn_zero(qq, n); bn_zero(uu, n); bn_zero(vv, n); return 0; } /** * @brief Compute remainder of bignum division (modulo) * * Calculates r[] = u[] % v[] * where r, v are big number integers of length vlimb * and u is a big number integer of length ulimb. * r may overlap v. * * Note that r here is only vlimb long, * whereas in bn_div it is ulimb long. * * Use remainder from bn_div function. * * @param r pointer to array of limbs to receive remainder * @param u pointer to array of limbs (dividend) * @param ulimb number of limbs in the u array * @param v pointer to array of limbs (divisor) * @param vlimb number of limbs in the r and v array * * @result zero on success, LIMBASK on division by zero */ limb_t bn_mod(limb_t r[], limb_t u[], count_t ulimb, limb_t v[], count_t vlimb) { static IGRAPH_THREAD_LOCAL limb_t qq[2 * BN_MAXSIZE]; static IGRAPH_THREAD_LOCAL limb_t rr[2 * BN_MAXSIZE]; limb_t d0; /* rr[] = u[] % v[n] */ d0 = (limb_t) bn_div(qq, rr, u, v, ulimb, vlimb); /* copy vlimb limbs of remainder */ bn_copy(r, rr, vlimb); /* zero temps */ bn_zero(rr, ulimb); bn_zero(qq, ulimb); return d0; } /** * @brief Compute greatest common divisor * * Computes g = gcd(x, y) * Reference: Schneier * * @param g pointer to array of limbs to receive the gcd * @param x pointer to array of limbs (candidate #1) * @param y pointer to array of limbs (candidate #2) * @param nlimb number of limbs in the arrays * * @result zero on succes (always) */ int bn_gcd(limb_t g[], limb_t x[], limb_t y[], count_t nlimb) { static IGRAPH_THREAD_LOCAL limb_t yy[BN_MAXSIZE]; static IGRAPH_THREAD_LOCAL limb_t xx[BN_MAXSIZE]; bn_copy(xx, x, nlimb); bn_copy(yy, y, nlimb); /* g = y */ bn_copy(g, yy, nlimb); /* while (x > 0) { */ while (0 != bn_cmp_limb(xx, 0, nlimb)) { /* g = x */ bn_copy(g, xx, nlimb); /* x = y % x */ bn_mod(xx, yy, nlimb, xx, nlimb); /* y = g */ bn_copy(yy, g, nlimb); } bn_zero(xx, nlimb); bn_zero(yy, nlimb); /* gcd is left in g */ return 0; } /** * @brief Compute modular exponentiation of bignums * * Computes y[] = (x[]^e[]) % m[] * Binary MSB to LSB method * * @param y pointer to array of limbs to receive the result * @param x pointer to array of limbs (base) * @param e pointer to array of limbs (exponent) * @param m pointer to array of limbs (modulus) * @param nlimb number of limbs in the arrays * * @result zero on success, -1 on error (nlimb is zero) */ int bn_modexp(limb_t y[], limb_t x[], limb_t e[], limb_t m[], count_t nlimb) { limb_t mask; count_t n; if (nlimb == 0) { return -1; } /* Find second-most significant bit in e */ n = bn_sizeof(e, nlimb); for (mask = DIGMSB; 0 != mask; mask >>= 1) { if (e[n - 1] & mask) { break; } } /* next bit, because we start off with y[] == x[] */ mask >>= 1; if (0 == mask) { mask = DIGMSB; n--; } /* y[] = x[] */ bn_copy(y, x, nlimb); while (n > 0) { /* y[] = (y[] ^ 2) % m[] */ bn_modmul(y, y, y, m, nlimb); if (e[n - 1] & mask) /* y[] = (y[] * x[]) % m[] */ { bn_modmul(y, y, x, m, nlimb); } /* next bit */ mask >>= 1; if (0 == mask) { mask = DIGMSB; n--; } } return 0; } /** * @brief Compute modular product of two bignums * * Computes a[] = (x[] * y[]) % m[] * where a, x, y and m are big numbers of nlimb length * * @param a pointer to array of limbs to receive the result * @param x pointer to array of limbs (factor #1) * @param y pointer to array of limbs (factor #2) * @param m pointer to array of limbs (modulus) * @param nlimb number of limbs in the arrays * * @result zero on success, LIMBMASK if m was zero (division by zero) */ limb_t bn_modmul(limb_t a[], limb_t x[], limb_t y[], limb_t m[], count_t nlimb) { static IGRAPH_THREAD_LOCAL limb_t pp[2 * BN_MAXSIZE]; limb_t d0; /* pp[] = x[] * y[] (NB: double size pp[]) */ bn_mul(pp, x, y, nlimb); /* a[] = pp[] % m[] */ d0 = bn_mod(a, pp, 2 * nlimb, m, nlimb); /* zero temp */ bn_zero(pp, 2 * nlimb); return d0; } /** * @brief Compute modular inverse * * Computes inv[] = u[]^(-1) % v[] * Ref: Knuth Algorithm X Vol 2 p 342 * ignoring u2, v2, t2 and avoiding negative numbers. * * @param inv pointer to array of limbs receiving the result * @param u pointer to array of limbs (candidate) * @param v pointer to array of limbs (modulus) * @param nlimb number of limbs in the arrays * * @result zero on success */ int bn_modinv(limb_t inv[], limb_t u[], limb_t v[], count_t nlimb) { /* Allocate temp variables */ static IGRAPH_THREAD_LOCAL limb_t u1[BN_MAXSIZE]; static IGRAPH_THREAD_LOCAL limb_t u3[BN_MAXSIZE]; static IGRAPH_THREAD_LOCAL limb_t v1[BN_MAXSIZE]; static IGRAPH_THREAD_LOCAL limb_t v3[BN_MAXSIZE]; static IGRAPH_THREAD_LOCAL limb_t t1[BN_MAXSIZE]; static IGRAPH_THREAD_LOCAL limb_t t3[BN_MAXSIZE]; static IGRAPH_THREAD_LOCAL limb_t q[BN_MAXSIZE]; static IGRAPH_THREAD_LOCAL limb_t w[2 * BN_MAXSIZE]; int iter; /* Step X1. Initialize */ bn_limb(u1, 1, nlimb); /* u1 = 1 */ bn_limb(v1, 0, nlimb); /* v1 = 0 */ bn_copy(u3, u, nlimb); /* u3 = u */ bn_copy(v3, v, nlimb); /* v3 = v */ /* remember odd/even iterations */ iter = 1; /* Step X2. Loop while v3 != 0 */ while (0 != bn_cmp_limb(v3, 0, nlimb)) { /* Step X3. Divide and "Subtract" */ /* q = u3 / v3, t3 = u3 % v3 */ bn_div(q, t3, u3, v3, nlimb, nlimb); /* w = q * v1 */ bn_mul(w, q, v1, nlimb); /* t1 = u1 + w */ bn_add(t1, u1, w, nlimb); /* Swap u1 <= v1 <= t1 */ bn_copy(u1, v1, nlimb); bn_copy(v1, t1, nlimb); /* Swap u3 <= v3 <= t3 */ bn_copy(u3, v3, nlimb); bn_copy(v3, t3, nlimb); iter ^= 1; } if (iter) { bn_copy(inv, u1, nlimb); /* inv = u1 */ } else { bn_sub(inv, v, u1, nlimb); /* inv = v - u1 */ } /* clear temp vars */ bn_zero(u1, nlimb); bn_zero(v1, nlimb); bn_zero(t1, nlimb); bn_zero(u3, nlimb); bn_zero(v3, nlimb); bn_zero(t3, nlimb); bn_zero(q, nlimb); bn_zero(w, 2 * nlimb); return 0; } /** * @brief Compute square root (and fraction) of a bignum * * Compute q[] = sqrt(u[]), * where q and u are big number integers of nlimb limbs * * Method according to sqrt.html of 2001-08-15: * Act on bytes from MSB to LSB, counting the number of times * that we can subtract consecutive odd numbers starting with * 1, 3, 5. Just uses add, subtract, shift and comparisons. * * The pointer r can be NULL if caller is not interested in * the (partial) fraction. * * @param q pointer to array of limbs to receive the result (integer) * @param r pointer to array of limbs to receive the result (fraction) * @param u pointer to array of limbs (square) * @param rlimb number of limbs in the q and r arrays * @param ulimb number of limbs in the u array * * @result zero on success */ int bn_sqrt(limb_t q[], limb_t r[], limb_t u[], count_t rlimb, count_t ulimb) { static IGRAPH_THREAD_LOCAL limb_t step[BN_MAXSIZE]; static IGRAPH_THREAD_LOCAL limb_t accu[BN_MAXSIZE]; static IGRAPH_THREAD_LOCAL limb_t w[2 * BN_MAXSIZE]; limb_t d; count_t m, n; count_t shift; bn_zero(q, ulimb); bn_limb(step, 1, BN_MAXSIZE); bn_limb(accu, 0, BN_MAXSIZE); n = bn_sizeof(u, ulimb); /* determine first non-zero byte from MSB to LSB */ if (0 != (u[n - 1] >> 24)) { shift = 32; } else if (0 != (u[n - 1] >> 16)) { shift = 24; } else if (0 != (u[n - 1] >> 8)) { shift = 16; } else { shift = 8; } m = 1; while (n-- > 0) { while (shift > 0) { /* shift accu one byte left */ bn_shl(accu, accu, 8, m + 1); /* shift for next byte from u[] */ shift -= 8; accu[0] |= (u[n] >> shift) & 0xff; /* digit = 0 */ d = 0; /* subtract consecutive odd numbers step[] until overflow */ for (d = 0; bn_cmp(step, accu, m + 1) <= 0; d++) { bn_sub(accu, accu, step, m + 1); bn_add_limb(step, step, 2, m + 1); } /* put digit into result */ bn_shl(q, q, 4, m); q[0] |= d; /* step[] = 2 * q[] * 16 + 1 */ bn_shl(step, q, 5, m + 1); bn_add_limb(step, step, 1, m + 1); } shift = 32; if (0 == (n & 1)) { m++; } } /* Caller does not want to know the fraction? */ if (NULL == r) { return 0; } /* nothing left to do if remainder is zero */ if (0 == bn_cmp_limb(accu, 0, ulimb)) { bn_zero(r, rlimb); return 0; } /* Start off with the integer part */ bn_zero(w, 2 * BN_MAXSIZE); bn_copy(w, q, ulimb); n = rlimb * (LIMBBITS / 4); while (n-- > 0) { /* shift accu one byte left */ bn_shl(accu, accu, 8, rlimb); /* subtract consecutive odd numbers step[] until overflow */ for (d = 0; bn_cmp(step, accu, rlimb) <= 0; d++) { bn_sub(accu, accu, step, rlimb); bn_add_limb(step, step, 2, rlimb); } /* put digit into result */ bn_shl(w, w, 4, rlimb); w[0] |= d; /* step[] = 2 * w[] * 16 + 1 */ bn_shl(step, w, 5, rlimb); bn_add_limb(step, step, 1, rlimb); } /* copy remainder */ bn_copy(r, w, rlimb); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/foreign-pajek-header.h0000644000076500000240000000257713614300625025531 0ustar tamasstaff00000000000000/* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard street, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_vector.h" #include "igraph_types_internal.h" typedef struct { void *scanner; int eof; char errmsg[300]; igraph_vector_t *vector; igraph_bool_t directed; int vcount, vcount2; int actfrom; int actto; int mode; /* 0: general, 1: vertex, 2: edge */ igraph_trie_t *vertex_attribute_names; igraph_vector_ptr_t *vertex_attributes; igraph_trie_t *edge_attribute_names; igraph_vector_ptr_t *edge_attributes; int vertexid; int actvertex; int actedge; } igraph_i_pajek_parsedata_t; python-igraph-0.8.0/vendor/source/igraph/src/sir.c0000644000076500000240000002144713614300625022347 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2014 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_epidemics.h" #include "igraph_random.h" #include "igraph_adjlist.h" #include "igraph_interface.h" #include "igraph_psumtree.h" #include "igraph_memory.h" #include "igraph_structural.h" int igraph_sir_init(igraph_sir_t *sir) { igraph_vector_init(&sir->times, 1); IGRAPH_FINALLY(igraph_vector_destroy, &sir->times); igraph_vector_int_init(&sir->no_s, 1); IGRAPH_FINALLY(igraph_vector_int_destroy, &sir->no_s); igraph_vector_int_init(&sir->no_i, 1); IGRAPH_FINALLY(igraph_vector_int_destroy, &sir->no_i); igraph_vector_int_init(&sir->no_r, 1); IGRAPH_FINALLY_CLEAN(3); return 0; } /** * \function igraph_sir_destroy * Deallocate memory associated with a SIR simulation run * * \param sir The \ref igraph_sir_t object storing the simulation. */ void igraph_sir_destroy(igraph_sir_t *sir) { igraph_vector_destroy(&sir->times); igraph_vector_int_destroy(&sir->no_s); igraph_vector_int_destroy(&sir->no_i); igraph_vector_int_destroy(&sir->no_r); } void igraph_i_sir_destroy(igraph_vector_ptr_t *v) { int i, n = igraph_vector_ptr_size(v); for (i = 0; i < n; i++) { igraph_sir_t *s = VECTOR(*v)[i]; if (s) { igraph_sir_destroy(s); } } } #define S_S 0 #define S_I 1 #define S_R 2 /** * \function igraph_sir * Perform a number of SIR epidemics model runs on a graph * * The SIR model is a simple model from epidemiology. The individuals * of the population might be in three states: susceptible, infected * and recovered. Recovered people are assumed to be immune to the * disease. Susceptibles become infected with a rate that depends on * their number of infected neigbors. Infected people become recovered * with a constant rate. See these parameters below. * * * This function runs multiple simulations, all starting with a * single uniformly randomly chosen infected individual. A simulation * is stopped when no infected individuals are left. * * \param graph The graph to perform the model on. For directed graphs * edge directions are ignored and a warning is given. * \param beta The rate of infection of an individual that is * susceptible and has a single infected neighbor. * The infection rate of a susceptible individual with n * infected neighbors is n times beta. Formally * this is the rate parameter of an exponential distribution. * \param gamma The rate of recovery of an infected individual. * Formally, this is the rate parameter of an exponential * distribution. * \param no_sim The number of simulation runs to perform. * \param result The result of the simulation is stored here, * in a list of \ref igraph_sir_t objects. To deallocate * memory, the user needs to call \ref igraph_sir_destroy on * each element, before destroying the pointer vector itself. * \return Error code. * * Time complexity: O(no_sim * (|V| + |E| log(|V|))). */ int igraph_sir(const igraph_t *graph, igraph_real_t beta, igraph_real_t gamma, igraph_integer_t no_sim, igraph_vector_ptr_t *result) { int infected; igraph_vector_int_t status; igraph_adjlist_t adjlist; int no_of_nodes = igraph_vcount(graph); int i, j, ns, ni, nr; igraph_vector_int_t *neis; igraph_psumtree_t tree; igraph_real_t psum; int neilen; igraph_bool_t simple; if (no_of_nodes == 0) { IGRAPH_ERROR("Cannot run SIR model on empty graph", IGRAPH_EINVAL); } if (igraph_is_directed(graph)) { IGRAPH_WARNING("Edge directions are ignored in SIR model"); } if (beta < 0) { IGRAPH_ERROR("Beta must be non-negative in SIR model", IGRAPH_EINVAL); } if (gamma < 0) { IGRAPH_ERROR("Gamma must be non-negative in SIR model", IGRAPH_EINVAL); } if (no_sim <= 0) { IGRAPH_ERROR("Number of SIR simulations must be positive", IGRAPH_EINVAL); } igraph_is_simple(graph, &simple); if (!simple) { IGRAPH_ERROR("SIR model only works with simple graphs", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_vector_int_init(&status, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_int_destroy, &status); IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist); IGRAPH_CHECK(igraph_psumtree_init(&tree, no_of_nodes)); IGRAPH_FINALLY(igraph_psumtree_destroy, &tree); IGRAPH_CHECK(igraph_vector_ptr_resize(result, no_sim)); igraph_vector_ptr_null(result); IGRAPH_FINALLY(igraph_i_sir_destroy, result); for (i = 0; i < no_sim; i++) { igraph_sir_t *sir = igraph_Calloc(1, igraph_sir_t); if (!sir) { IGRAPH_ERROR("Cannot run SIR model", IGRAPH_ENOMEM); } igraph_sir_init(sir); VECTOR(*result)[i] = sir; } RNG_BEGIN(); for (j = 0; j < no_sim; j++) { igraph_sir_t *sir = VECTOR(*result)[j]; igraph_vector_t *times_v = &sir->times; igraph_vector_int_t *no_s_v = &sir->no_s; igraph_vector_int_t *no_i_v = &sir->no_i; igraph_vector_int_t *no_r_v = &sir->no_r; infected = RNG_INTEGER(0, no_of_nodes - 1); /* Initially infected */ igraph_vector_int_null(&status); VECTOR(status)[infected] = S_I; ns = no_of_nodes - 1; ni = 1; nr = 0; VECTOR(*times_v)[0] = 0.0; VECTOR(*no_s_v)[0] = ns; VECTOR(*no_i_v)[0] = ni; VECTOR(*no_r_v)[0] = nr; if (igraph_psumtree_sum(&tree) != 0) { igraph_psumtree_reset(&tree); } /* Rates */ igraph_psumtree_update(&tree, infected, gamma); neis = igraph_adjlist_get(&adjlist, infected); neilen = igraph_vector_int_size(neis); for (i = 0; i < neilen; i++) { int nei = VECTOR(*neis)[i]; igraph_psumtree_update(&tree, nei, beta); } while (ni > 0) { igraph_real_t tt; igraph_real_t r; long int vchange; psum = igraph_psumtree_sum(&tree); tt = igraph_rng_get_exp(igraph_rng_default(), psum); r = RNG_UNIF(0, psum); igraph_psumtree_search(&tree, &vchange, r); neis = igraph_adjlist_get(&adjlist, vchange); neilen = igraph_vector_int_size(neis); if (VECTOR(status)[vchange] == S_I) { VECTOR(status)[vchange] = S_R; ni--; nr++; igraph_psumtree_update(&tree, vchange, 0.0); for (i = 0; i < neilen; i++) { int nei = VECTOR(*neis)[i]; if (VECTOR(status)[nei] == S_S) { igraph_real_t rate = igraph_psumtree_get(&tree, nei); igraph_psumtree_update(&tree, nei, rate - beta); } } } else { /* S_S */ VECTOR(status)[vchange] = S_I; ns--; ni++; igraph_psumtree_update(&tree, vchange, gamma); for (i = 0; i < neilen; i++) { int nei = VECTOR(*neis)[i]; if (VECTOR(status)[nei] == S_S) { igraph_real_t rate = igraph_psumtree_get(&tree, nei); igraph_psumtree_update(&tree, nei, rate + beta); } } } if (times_v) { igraph_vector_push_back(times_v, tt + igraph_vector_tail(times_v)); } if (no_s_v) { igraph_vector_int_push_back(no_s_v, ns); } if (no_i_v) { igraph_vector_int_push_back(no_i_v, ni); } if (no_r_v) { igraph_vector_int_push_back(no_r_v, nr); } } /* psum > 0 */ } /* j < no_sim */ RNG_END(); igraph_psumtree_destroy(&tree); igraph_adjlist_destroy(&adjlist); igraph_vector_int_destroy(&status); IGRAPH_FINALLY_CLEAN(4); /* + result */ return 0; } python-igraph-0.8.0/vendor/source/igraph/src/igraph_flow_internal.h0000644000076500000240000000301613614300625025744 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_FLOW_INTERNAL_H #define IGRAPH_FLOW_INTERNAL_H #include "igraph_types.h" #include "igraph_marked_queue.h" #include "igraph_estack.h" #include "igraph_datatype.h" typedef int igraph_provan_shier_pivot_t(const igraph_t *graph, const igraph_marked_queue_t *S, const igraph_estack_t *T, long int source, long int target, long int *v, igraph_vector_t *Isv, void *arg); #endif python-igraph-0.8.0/vendor/source/igraph/src/matrix.pmt0000644000076500000240000013721213614300625023432 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2003-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_memory.h" #include "igraph_random.h" #include "igraph_error.h" #include #include /* memcpy & co. */ #include /** * \section about_igraph_matrix_t_objects About \type igraph_matrix_t objects * * This type is just an interface to \type igraph_vector_t. * * The \type igraph_matrix_t type usually stores n * elements in O(n) space, but not always. See the documentation of * the vector type. */ /** * \section igraph_matrix_constructor_and_destructor Matrix constructors and * destructors */ /** * \ingroup matrix * \function igraph_matrix_init * \brief Initializes a matrix. * * * Every matrix needs to be initialized before using it. This is done * by calling this function. A matrix has to be destroyed if it is not * needed any more; see \ref igraph_matrix_destroy(). * \param m Pointer to a not yet initialized matrix object to be * initialized. * \param nrow The number of rows in the matrix. * \param ncol The number of columns in the matrix. * \return Error code. * * Time complexity: usually O(n), * n is the * number of elements in the matrix. */ int FUNCTION(igraph_matrix, init)(TYPE(igraph_matrix) *m, long int nrow, long int ncol) { int ret1; ret1 = FUNCTION(igraph_vector, init)(&m->data, nrow * ncol); m->nrow = nrow; m->ncol = ncol; return ret1; } const TYPE(igraph_matrix) *FUNCTION(igraph_matrix, view)(const TYPE(igraph_matrix) *m, const BASE *data, long int nrow, long int ncol) { TYPE(igraph_matrix) *m2 = (TYPE(igraph_matrix)*)m; FUNCTION(igraph_vector, view)(&m2->data, data, nrow * ncol); m2->nrow = nrow; m2->ncol = ncol; return m; } /** * \ingroup matrix * \function igraph_matrix_destroy * \brief Destroys a matrix object. * * * This function frees all the memory allocated for a matrix * object. The destroyed object needs to be reinitialized before using * it again. * \param m The matrix to destroy. * * Time complexity: operating system dependent. */ void FUNCTION(igraph_matrix, destroy)(TYPE(igraph_matrix) *m) { FUNCTION(igraph_vector, destroy)(&m->data); } /** * \ingroup matrix * \function igraph_matrix_capacity * \brief Returns the number of elements allocated for a matrix. * * Note that this might be different from the size of the matrix (as * queried by \ref igraph_matrix_size(), and specifies how many elements * the matrix can hold, without reallocation. * \param v Pointer to the (previously initialized) matrix object * to query. * \return The allocated capacity. * * \sa \ref igraph_matrix_size(), \ref igraph_matrix_nrow(), * \ref igraph_matrix_ncol(). * * Time complexity: O(1). */ long int FUNCTION(igraph_matrix, capacity)(const TYPE(igraph_matrix) *m) { return FUNCTION(igraph_vector, capacity)(&m->data); } /** * \section igraph_matrix_accessing_elements Accessing elements of a matrix */ /** * \ingroup matrix * \function igraph_matrix_resize * \brief Resizes a matrix. * * * This function resizes a matrix by adding more elements to it. * The matrix contains arbitrary data after resizing it. * That is, after calling this function you cannot expect that element * (i,j) in the matrix remains the * same as before. * \param m Pointer to an already initialized matrix object. * \param nrow The number of rows in the resized matrix. * \param ncol The number of columns in the resized matrix. * \return Error code. * * Time complexity: O(1) if the * matrix gets smaller, usually O(n) * if it gets larger, n is the * number of elements in the resized matrix. */ int FUNCTION(igraph_matrix, resize)(TYPE(igraph_matrix) *m, long int nrow, long int ncol) { FUNCTION(igraph_vector, resize)(&m->data, nrow * ncol); m->nrow = nrow; m->ncol = ncol; return 0; } /** * \ingroup matrix * \function igraph_matrix_resize_min * \brief Deallocates unused memory for a matrix. * * * Note that this function might fail if there is not enough memory * available. * * * Also note, that this function leaves the matrix intact, i.e. * it does not destroy any of the elements. However, usually it involves * copying the matrix in memory. * \param m Pointer to an initialized matrix. * \return Error code. * * \sa \ref igraph_matrix_resize(). * * Time complexity: operating system dependent. */ int FUNCTION(igraph_matrix, resize_min)(TYPE(igraph_matrix) *m) { TYPE(igraph_vector) tmp; long int size = FUNCTION(igraph_matrix, size)(m); long int capacity = FUNCTION(igraph_matrix, capacity)(m); if (size == capacity) { return 0; } IGRAPH_CHECK(FUNCTION(igraph_vector, init)(&tmp, size)); FUNCTION(igraph_vector, update)(&tmp, &m->data); FUNCTION(igraph_vector, destroy)(&m->data); m->data = tmp; return 0; } /** * \ingroup matrix * \function igraph_matrix_size * \brief The number of elements in a matrix. * * \param m Pointer to an initialized matrix object. * \return The size of the matrix. * * Time complexity: O(1). */ long int FUNCTION(igraph_matrix, size)(const TYPE(igraph_matrix) *m) { return (m->nrow) * (m->ncol); } /** * \ingroup matrix * \function igraph_matrix_nrow * \brief The number of rows in a matrix. * * \param m Pointer to an initialized matrix object. * \return The number of rows in the matrix. * * Time complexity: O(1). */ long int FUNCTION(igraph_matrix, nrow)(const TYPE(igraph_matrix) *m) { return m->nrow; } /** * \ingroup matrix * \function igraph_matrix_ncol * \brief The number of columns in a matrix. * * \param m Pointer to an initialized matrix object. * \return The number of columns in the matrix. * * Time complexity: O(1). */ long int FUNCTION(igraph_matrix, ncol)(const TYPE(igraph_matrix) *m) { return m->ncol; } /** * \ingroup matrix * \function igraph_matrix_copy_to * \brief Copies a matrix to a regular C array. * * * The matrix is copied columnwise, as this is the format most * programs and languages use. * The C array should be of sufficient size; there are (of course) no * range checks. * \param m Pointer to an initialized matrix object. * \param to Pointer to a C array; the place to copy the data to. * \return Error code. * * Time complexity: O(n), * n is the number of * elements in the matrix. */ void FUNCTION(igraph_matrix, copy_to)(const TYPE(igraph_matrix) *m, BASE *to) { FUNCTION(igraph_vector, copy_to)(&m->data, to); } /** * \ingroup matrix * \function igraph_matrix_null * \brief Sets all elements in a matrix to zero. * * \param m Pointer to an initialized matrix object. * * Time complexity: O(n), * n is the number of elements in * the matrix. */ void FUNCTION(igraph_matrix, null)(TYPE(igraph_matrix) *m) { FUNCTION(igraph_vector, null)(&m->data); } /** * \ingroup matrix * \function igraph_matrix_add_cols * \brief Adds columns to a matrix. * \param m The matrix object. * \param n The number of columns to add. * \return Error code, \c IGRAPH_ENOMEM if there is * not enough memory to perform the operation. * * Time complexity: linear with the number of elements of the new, * resized matrix. */ int FUNCTION(igraph_matrix, add_cols)(TYPE(igraph_matrix) *m, long int n) { FUNCTION(igraph_matrix, resize)(m, m->nrow, m->ncol + n); return 0; } /** * \ingroup matrix * \function igraph_matrix_add_rows * \brief Adds rows to a matrix. * \param m The matrix object. * \param n The number of rows to add. * \return Error code, \c IGRAPH_ENOMEM if there * isn't enough memory for the operation. * * Time complexity: linear with the number of elements of the new, * resized matrix. */ int FUNCTION(igraph_matrix, add_rows)(TYPE(igraph_matrix) *m, long int n) { long int i; FUNCTION(igraph_vector, resize)(&m->data, (m->ncol) * (m->nrow + n)); for (i = m->ncol - 1; i >= 0; i--) { FUNCTION(igraph_vector, move_interval2)(&m->data, (m->nrow)*i, (m->nrow) * (i + 1), (m->nrow + n)*i); } m->nrow += n; return 0; } /** * \ingroup matrix * \function igraph_matrix_remove_col * \brief Removes a column from a matrix. * * \param m The matrix object. * \param col The column to remove. * \return Error code, always returns with success. * * Time complexity: linear with the number of elements of the new, * resized matrix. */ int FUNCTION(igraph_matrix, remove_col)(TYPE(igraph_matrix) *m, long int col) { FUNCTION(igraph_vector, remove_section)(&m->data, (m->nrow)*col, (m->nrow) * (col + 1)); m->ncol--; return 0; } /** * \ingroup matrix * \function igraph_matrix_permdelete_rows * \brief Removes rows from a matrix (for internal use). * * Time complexity: linear with the number of elements of the original * matrix. */ int FUNCTION(igraph_matrix, permdelete_rows)(TYPE(igraph_matrix) *m, long int *index, long int nremove) { long int i, j; for (j = 0; j < m->nrow; j++) { if (index[j] != 0) { for (i = 0; i < m->ncol; i++) { MATRIX(*m, index[j] - 1, i) = MATRIX(*m, j, i); } } } /* Remove unnecessary elements from the end of each column */ for (i = 0; i < m->ncol; i++) FUNCTION(igraph_vector, remove_section)(&m->data, (i + 1) * (m->nrow - nremove), (i + 1) * (m->nrow - nremove) + nremove); FUNCTION(igraph_matrix, resize)(m, m->nrow - nremove, m->ncol); return 0; } /** * \ingroup matrix * \function igraph_matrix_delete_rows_neg * \brief Removes columns from a matrix (for internal use). * * Time complexity: linear with the number of elements of the original * matrix. */ int FUNCTION(igraph_matrix, delete_rows_neg)(TYPE(igraph_matrix) *m, const igraph_vector_t *neg, long int nremove) { long int i, j, idx = 0; for (i = 0; i < m->ncol; i++) { for (j = 0; j < m->nrow; j++) { if (VECTOR(*neg)[j] >= 0) { MATRIX(*m, idx++, i) = MATRIX(*m, j, i); } } idx = 0; } FUNCTION(igraph_matrix, resize)(m, m->nrow - nremove, m->ncol); return 0; } /** * \ingroup matrix * \function igraph_matrix_copy * \brief Copies a matrix. * * * Creates a matrix object by copying from an existing matrix. * \param to Pointer to an uninitialized matrix object. * \param from The initialized matrix object to copy. * \return Error code, \c IGRAPH_ENOMEM if there * isn't enough memory to allocate the new matrix. * * Time complexity: O(n), the number * of elements in the matrix. */ int FUNCTION(igraph_matrix, copy)(TYPE(igraph_matrix) *to, const TYPE(igraph_matrix) *from) { to->nrow = from->nrow; to->ncol = from->ncol; return FUNCTION(igraph_vector, copy)(&to->data, &from->data); } #ifndef NOTORDERED /** * \function igraph_matrix_max * * Returns the maximal element of a matrix. * \param m The matrix object. * \return The maximum element. For empty matrix the returned value is * undefined. * * Added in version 0.2. * * Time complexity: O(n), the number of elements in the matrix. */ igraph_real_t FUNCTION(igraph_matrix, max)(const TYPE(igraph_matrix) *m) { return FUNCTION(igraph_vector, max)(&m->data); } #endif /** * \function igraph_matrix_scale * * Multiplies each element of the matrix by a constant. * \param m The matrix. * \param by The constant. * * Added in version 0.2. * * Time complexity: O(n), the number of elements in the matrix. */ void FUNCTION(igraph_matrix, scale)(TYPE(igraph_matrix) *m, BASE by) { FUNCTION(igraph_vector, scale)(&m->data, by); } /** * \function igraph_matrix_select_rows * \brief Select some rows of a matrix. * * This function selects some rows of a matrix and returns them in a * new matrix. The result matrix should be initialized before calling * the function. * \param m The input matrix. * \param res The result matrix. It should be initialized and will be * resized as needed. * \param rows Vector; it contains the row indices (starting with * zero) to extract. Note that no range checking is performed. * \return Error code. * * Time complexity: O(nm), n is the number of rows, m the number of * columns of the result matrix. */ int FUNCTION(igraph_matrix, select_rows)(const TYPE(igraph_matrix) *m, TYPE(igraph_matrix) *res, const igraph_vector_t *rows) { long int norows = igraph_vector_size(rows); long int i, j, ncols = FUNCTION(igraph_matrix, ncol)(m); IGRAPH_CHECK(FUNCTION(igraph_matrix, resize)(res, norows, ncols)); for (i = 0; i < norows; i++) { for (j = 0; j < ncols; j++) { MATRIX(*res, i, j) = MATRIX(*m, (long int)VECTOR(*rows)[i], j); } } return 0; } /** * \function igraph_matrix_select_rows_cols * \brief Select some rows and columns of a matrix. * * This function selects some rows and columns of a matrix and returns * them in a new matrix. The result matrix should be initialized before * calling the function. * \param m The input matrix. * \param res The result matrix. It should be initialized and will be * resized as needed. * \param rows Vector; it contains the row indices (starting with * zero) to extract. Note that no range checking is performed. * \param cols Vector; it contains the column indices (starting with * zero) to extract. Note that no range checking is performed. * \return Error code. * * Time complexity: O(nm), n is the number of rows, m the number of * columns of the result matrix. */ int FUNCTION(igraph_matrix, select_rows_cols)(const TYPE(igraph_matrix) *m, TYPE(igraph_matrix) *res, const igraph_vector_t *rows, const igraph_vector_t *cols) { long int nrows = igraph_vector_size(rows); long int ncols = igraph_vector_size(cols); long int i, j; IGRAPH_CHECK(FUNCTION(igraph_matrix, resize)(res, nrows, ncols)); for (i = 0; i < nrows; i++) { for (j = 0; j < ncols; j++) { MATRIX(*res, i, j) = MATRIX(*m, (long int)VECTOR(*rows)[i], (long int)VECTOR(*cols)[j]); } } return 0; } /** * \function igraph_matrix_get_col * \brief Select a column. * * Extract a column of a matrix and return it as a vector. * \param m The input matrix. * \param res The result will we stored in this vector. It should be * initialized and will be resized as needed. * \param index The index of the column to select. * \return Error code. * * Time complexity: O(n), the number of rows in the matrix. */ int FUNCTION(igraph_matrix, get_col)(const TYPE(igraph_matrix) *m, TYPE(igraph_vector) *res, long int index) { long int nrow = FUNCTION(igraph_matrix, nrow)(m); if (index >= m->ncol) { IGRAPH_ERROR("Index out of range for selecting matrix column", IGRAPH_EINVAL); } IGRAPH_CHECK(FUNCTION(igraph_vector, get_interval)(&m->data, res, nrow * index, nrow * (index + 1))); return 0; } /** * \function igraph_matrix_sum * \brief Sum of elements. * * Returns the sum of the elements of a matrix. * \param m The input matrix. * \return The sum of the elements. * * Time complexity: O(mn), the number of elements in the matrix. */ BASE FUNCTION(igraph_matrix, sum)(const TYPE(igraph_matrix) *m) { return FUNCTION(igraph_vector, sum)(&m->data); } /** * \function igraph_matrix_all_e * \brief Are all elements equal? * * \param lhs The first matrix. * \param rhs The second matrix. * \return Positive integer (=true) if the elements in the \p lhs are all * equal to the corresponding elements in \p rhs. Returns \c 0 * (=false) if the dimensions of the matrices don't match. * * Time complexity: O(nm), the size of the matrices. */ igraph_bool_t FUNCTION(igraph_matrix, all_e)(const TYPE(igraph_matrix) *lhs, const TYPE(igraph_matrix) *rhs) { return lhs->ncol == rhs->ncol && lhs->nrow == rhs->nrow && FUNCTION(igraph_vector, all_e)(&lhs->data, &rhs->data); } igraph_bool_t FUNCTION(igraph_matrix, is_equal)(const TYPE(igraph_matrix) *lhs, const TYPE(igraph_matrix) *rhs) { return FUNCTION(igraph_matrix, all_e)(lhs, rhs); } #ifndef NOTORDERED /** * \function igraph_matrix_all_l * \brief Are all elements less? * * \param lhs The first matrix. * \param rhs The second matrix. * \return Positive integer (=true) if the elements in the \p lhs are all * less than the corresponding elements in \p rhs. Returns \c 0 * (=false) if the dimensions of the matrices don't match. * * Time complexity: O(nm), the size of the matrices. */ igraph_bool_t FUNCTION(igraph_matrix, all_l)(const TYPE(igraph_matrix) *lhs, const TYPE(igraph_matrix) *rhs) { return lhs->ncol == rhs->ncol && lhs->nrow == rhs->nrow && FUNCTION(igraph_vector, all_l)(&lhs->data, &rhs->data); } /** * \function igraph_matrix_all_g * \brief Are all elements greater? * * \param lhs The first matrix. * \param rhs The second matrix. * \return Positive integer (=true) if the elements in the \p lhs are all * greater than the corresponding elements in \p rhs. Returns \c 0 * (=false) if the dimensions of the matrices don't match. * * Time complexity: O(nm), the size of the matrices. */ igraph_bool_t FUNCTION(igraph_matrix, all_g)(const TYPE(igraph_matrix) *lhs, const TYPE(igraph_matrix) *rhs) { return lhs->ncol == rhs->ncol && lhs->nrow == rhs->nrow && FUNCTION(igraph_vector, all_g)(&lhs->data, &rhs->data); } /** * \function igraph_matrix_all_le * \brief Are all elements less or equal? * * \param lhs The first matrix. * \param rhs The second matrix. * \return Positive integer (=true) if the elements in the \p lhs are all * less than or equal to the corresponding elements in \p * rhs. Returns \c 0 (=false) if the dimensions of the matrices * don't match. * * Time complexity: O(nm), the size of the matrices. */ igraph_bool_t FUNCTION(igraph_matrix, all_le)(const TYPE(igraph_matrix) *lhs, const TYPE(igraph_matrix) *rhs) { return lhs->ncol == rhs->ncol && lhs->nrow == rhs->nrow && FUNCTION(igraph_vector, all_le)(&lhs->data, &rhs->data); } /** * \function igraph_matrix_all_ge * \brief Are all elements greater or equal? * * \param lhs The first matrix. * \param rhs The second matrix. * \return Positive integer (=true) if the elements in the \p lhs are all * greater than or equal to the corresponding elements in \p * rhs. Returns \c 0 (=false) if the dimensions of the matrices * don't match. * * Time complexity: O(nm), the size of the matrices. */ igraph_bool_t FUNCTION(igraph_matrix, all_ge)(const TYPE(igraph_matrix) *lhs, const TYPE(igraph_matrix) *rhs) { return lhs->ncol == rhs->ncol && lhs->nrow == rhs->nrow && FUNCTION(igraph_vector, all_ge)(&lhs->data, &rhs->data); } #endif #ifndef NOTORDERED /** * \function igraph_matrix_maxdifference * \brief Maximum absolute difference between two matrices. * * Calculate the maximum absolute difference of two matrices. Both matrices * must be non-empty. If their dimensions differ then a warning is given and * the comparison is performed by vectors columnwise from both matrices. * The remaining elements in the larger vector are ignored. * \param m1 The first matrix. * \param m2 The second matrix. * \return The element with the largest absolute value in \c m1 - \c m2. * * Time complexity: O(mn), the elements in the smaller matrix. */ igraph_real_t FUNCTION(igraph_matrix, maxdifference)(const TYPE(igraph_matrix) *m1, const TYPE(igraph_matrix) *m2) { long int col1 = FUNCTION(igraph_matrix, ncol)(m1); long int col2 = FUNCTION(igraph_matrix, ncol)(m2); long int row1 = FUNCTION(igraph_matrix, nrow)(m1); long int row2 = FUNCTION(igraph_matrix, nrow)(m2); if (col1 != col2 || row1 != row2) { IGRAPH_WARNING("Comparing non-conformant matrices"); } return FUNCTION(igraph_vector, maxdifference)(&m1->data, &m2->data); } #endif /** * \function igraph_matrix_transpose * \brief Transpose a matrix. * * Calculate the transpose of a matrix. Note that the function * reallocates the memory used for the matrix. * \param m The input (and output) matrix. * \return Error code. * * Time complexity: O(mn), the number of elements in the matrix. */ int FUNCTION(igraph_matrix, transpose)(TYPE(igraph_matrix) *m) { long int nrow = m->nrow; long int ncol = m->ncol; if (nrow > 1 && ncol > 1) { TYPE(igraph_vector) newdata; long int i, size = nrow * ncol, mod = size - 1; FUNCTION(igraph_vector, init)(&newdata, size); IGRAPH_FINALLY(FUNCTION(igraph_vector, destroy), &newdata); for (i = 0; i < size; i++) { VECTOR(newdata)[i] = VECTOR(m->data)[ (i * nrow) % mod ]; } VECTOR(newdata)[size - 1] = VECTOR(m->data)[size - 1]; FUNCTION(igraph_vector, destroy)(&m->data); IGRAPH_FINALLY_CLEAN(1); m->data = newdata; } m->nrow = ncol; m->ncol = nrow; return 0; } /** * \function igraph_matrix_e * Extract an element from a matrix. * * Use this if you need a function for some reason and cannot use the * \ref MATRIX macro. Note that no range checking is performed. * \param m The input matrix. * \param row The row index. * \param col The column index. * \return The element in the given row and column. * * Time complexity: O(1). */ BASE FUNCTION(igraph_matrix, e)(const TYPE(igraph_matrix) *m, long int row, long int col) { return MATRIX(*m, row, col); } /** * \function igraph_matrix_e_ptr * Pointer to an element of a matrix. * * The function returns a pointer to an element. No range checking is * performed. * \param m The input matrix. * \param row The row index. * \param col The column index. * \return Pointer to the element in the given row and column. * * Time complexity: O(1). */ BASE* FUNCTION(igraph_matrix, e_ptr)(const TYPE(igraph_matrix) *m, long int row, long int col) { return &MATRIX(*m, row, col); } /** * \function igraph_matrix_set * Set an element. * * Set an element of a matrix. No range checking is performed. * \param m The input matrix. * \param row The row index. * \param col The column index. * \param value The new value of the element. * * Time complexity: O(1). */ void FUNCTION(igraph_matrix, set)(TYPE(igraph_matrix)* m, long int row, long int col, BASE value) { MATRIX(*m, row, col) = value; } /** * \function igraph_matrix_fill * Fill with an element. * * Set the matrix to a constant matrix. * \param m The input matrix. * \param e The element to set. * * Time complexity: O(mn), the number of elements. */ void FUNCTION(igraph_matrix, fill)(TYPE(igraph_matrix) *m, BASE e) { FUNCTION(igraph_vector, fill)(&m->data, e); } /** * \function igraph_matrix_update * Update from another matrix. * * This function replicates \p from in the matrix \p to. * Note that \p to must be already initialized. * \param to The result matrix. * \param from The matrix to replicate; it is left unchanged. * \return Error code. * * Time complexity: O(mn), the number of elements. */ int FUNCTION(igraph_matrix, update)(TYPE(igraph_matrix) *to, const TYPE(igraph_matrix) *from) { IGRAPH_CHECK(FUNCTION(igraph_matrix, resize)(to, from->nrow, from->ncol)); FUNCTION(igraph_vector, update)(&to->data, &from->data); return 0; } /** * \function igraph_matrix_rbind * Combine two matrices rowwise. * * This function places the rows of \p from below the rows of \c to * and stores the result in \p to. The number of columns in the two * matrices must match. * \param to The upper matrix; the result is also stored here. * \param from The lower matrix. It is left unchanged. * \return Error code. * * Time complexity: O(mn), the number of elements in the newly created * matrix. */ int FUNCTION(igraph_matrix, rbind)(TYPE(igraph_matrix) *to, const TYPE(igraph_matrix) *from) { long int tocols = to->ncol, fromcols = from->ncol; long int torows = to->nrow, fromrows = from->nrow; long int offset, c, r, index, offset2; if (tocols != fromcols) { IGRAPH_ERROR("Cannot do rbind, number of columns do not match", IGRAPH_EINVAL); } IGRAPH_CHECK(FUNCTION(igraph_vector, resize)(&to->data, tocols * (fromrows + torows))); to->nrow += fromrows; offset = (tocols - 1) * fromrows; index = tocols * torows - 1; for (c = tocols - 1; c > 0; c--) { for (r = 0; r < torows; r++, index--) { VECTOR(to->data)[index + offset] = VECTOR(to->data)[index]; } offset -= fromrows; } offset = torows; offset2 = 0; for (c = 0; c < tocols; c++) { memcpy(VECTOR(to->data) + offset, VECTOR(from->data) + offset2, sizeof(BASE) * (size_t) fromrows); offset += fromrows + torows; offset2 += fromrows; } return 0; } /** * \function igraph_matrix_cbind * Combine matrices columnwise. * * This function places the columns of \p from on the right of \p to, * and stores the result in \p to. * \param to The left matrix; the result is stored here too. * \param from The right matrix. It is left unchanged. * \return Error code. * * Time complexity: O(mn), the number of elements on the new matrix. */ int FUNCTION(igraph_matrix, cbind)(TYPE(igraph_matrix) *to, const TYPE(igraph_matrix) *from) { long int tocols = to->ncol, fromcols = from->ncol; long int torows = to->nrow, fromrows = from->nrow; if (torows != fromrows) { IGRAPH_ERROR("Cannot do rbind, number of rows do not match", IGRAPH_EINVAL); } IGRAPH_CHECK(FUNCTION(igraph_matrix, resize)(to, torows, tocols + fromcols)); FUNCTION(igraph_vector, copy_to)(&from->data, VECTOR(to->data) + tocols * torows); return 0; } /** * \function igraph_matrix_swap * Swap two matrices. * * The contents of the two matrices will be swapped. They must have the * same dimensions. * \param m1 The first matrix. * \param m2 The second matrix. * \return Error code. * * Time complexity: O(mn), the number of elements in the matrices. */ int FUNCTION(igraph_matrix, swap)(TYPE(igraph_matrix) *m1, TYPE(igraph_matrix) *m2) { if (m1->nrow != m2->nrow || m1->ncol != m2->ncol) { IGRAPH_ERROR("Cannot swap non-conformant matrices", IGRAPH_EINVAL); } return FUNCTION(igraph_vector, swap)(&m1->data, &m2->data); } /** * \function igraph_matrix_get_row * Extract a row. * * Extract a row from a matrix and return it as a vector. * \param m The input matrix. * \param res Pointer to an initialized vector; it will be resized if * needed. * \param index The index of the row to select. * \return Error code. * * Time complexity: O(n), the number of columns in the matrix. */ int FUNCTION(igraph_matrix, get_row)(const TYPE(igraph_matrix) *m, TYPE(igraph_vector) *res, long int index) { long int rows = m->nrow, cols = m->ncol; long int i, j; if (index >= rows) { IGRAPH_ERROR("Index out of range for selecting matrix row", IGRAPH_EINVAL); } IGRAPH_CHECK(FUNCTION(igraph_vector, resize)(res, cols)); for (i = index, j = 0; j < cols; i += rows, j++) { VECTOR(*res)[j] = VECTOR(m->data)[i]; } return 0; } /** * \function igraph_matrix_set_row * Set a row from a vector. * * Sets the elements of a row with the given vector. This has the effect of * setting row \c index to have the elements in the vector \c v. The length of * the vector and the number of columns in the matrix must match, * otherwise an error is triggered. * \param m The input matrix. * \param v The vector containing the new elements of the row. * \param index Index of the row to set. * \return Error code. * * Time complexity: O(n), the number of columns in the matrix. */ int FUNCTION(igraph_matrix, set_row)(TYPE(igraph_matrix) *m, const TYPE(igraph_vector) *v, long int index) { long int rows = m->nrow, cols = m->ncol; long int i, j; if (index >= rows) { IGRAPH_ERROR("Index out of range for selecting matrix row", IGRAPH_EINVAL); } if (FUNCTION(igraph_vector, size)(v) != cols) { IGRAPH_ERROR("Cannot set matrix row, invalid vector length", IGRAPH_EINVAL); } for (i = index, j = 0; j < cols; i += rows, j++) { VECTOR(m->data)[i] = VECTOR(*v)[j]; } return 0; } /** * \function igraph_matrix_set_col * Set a column from a vector. * * Sets the elements of a column with the given vector. In effect, column * \c index will be set with elements from the vector \c v. The length of * the vector and the number of rows in the matrix must match, * otherwise an error is triggered. * \param m The input matrix. * \param v The vector containing the new elements of the column. * \param index Index of the column to set. * \return Error code. * * Time complexity: O(m), the number of rows in the matrix. */ int FUNCTION(igraph_matrix, set_col)(TYPE(igraph_matrix) *m, const TYPE(igraph_vector) *v, long int index) { long int rows = m->nrow, cols = m->ncol; long int i, j; if (index >= cols) { IGRAPH_ERROR("Index out of range for setting matrix column", IGRAPH_EINVAL); } if (FUNCTION(igraph_vector, size)(v) != rows) { IGRAPH_ERROR("Cannot set matrix column, invalid vector length", IGRAPH_EINVAL); } for (i = index * rows, j = 0; j < rows; i++, j++) { VECTOR(m->data)[i] = VECTOR(*v)[j]; } return 0; } /** * \function igraph_matrix_swap_rows * Swap two rows. * * Swap two rows in the matrix. * \param m The input matrix. * \param i The index of the first row. * \param j The index of the second row. * \return Error code. * * Time complexity: O(n), the number of columns. */ int FUNCTION(igraph_matrix, swap_rows)(TYPE(igraph_matrix) *m, long int i, long int j) { long int ncol = m->ncol, nrow = m->nrow; long int n = nrow * ncol; long int index1, index2; if (i >= nrow || j >= nrow) { IGRAPH_ERROR("Cannot swap rows, index out of range", IGRAPH_EINVAL); } if (i == j) { return 0; } for (index1 = i, index2 = j; index1 < n; index1 += nrow, index2 += nrow) { BASE tmp; tmp = VECTOR(m->data)[index1]; VECTOR(m->data)[index1] = VECTOR(m->data)[index2]; VECTOR(m->data)[index2] = tmp; } return 0; } /** * \function igraph_matrix_swap_cols * Swap two columns. * * Swap two columns in the matrix. * \param m The input matrix. * \param i The index of the first column. * \param j The index of the second column. * \return Error code. * * Time complexity: O(m), the number of rows. */ int FUNCTION(igraph_matrix, swap_cols)(TYPE(igraph_matrix) *m, long int i, long int j) { long int ncol = m->ncol, nrow = m->nrow; long int k, index1, index2; if (i >= ncol || j >= ncol) { IGRAPH_ERROR("Cannot swap columns, index out of range", IGRAPH_EINVAL); } if (i == j) { return 0; } for (index1 = i * nrow, index2 = j * nrow, k = 0; k < nrow; k++, index1++, index2++) { BASE tmp = VECTOR(m->data)[index1]; VECTOR(m->data)[index1] = VECTOR(m->data)[index2]; VECTOR(m->data)[index2] = tmp; } return 0; } /** * \function igraph_matrix_add_constant * Add a constant to every element. * * \param m The input matrix. * \param plud The constant to add. * * Time complexity: O(mn), the number of elements. */ void FUNCTION(igraph_matrix, add_constant)(TYPE(igraph_matrix) *m, BASE plus) { FUNCTION(igraph_vector, add_constant)(&m->data, plus); } /** * \function igraph_matrix_add * Add two matrices. * * Add \p m2 to \p m1, and store the result in \p m1. The dimensions of the * matrices must match. * \param m1 The first matrix; the result will be stored here. * \param m2 The second matrix; it is left unchanged. * \return Error code. * * Time complexity: O(mn), the number of elements. */ int FUNCTION(igraph_matrix, add)(TYPE(igraph_matrix) *m1, const TYPE(igraph_matrix) *m2) { if (m1->nrow != m2->nrow || m1->ncol != m2->ncol) { IGRAPH_ERROR("Cannot add non-conformant matrices", IGRAPH_EINVAL); } return FUNCTION(igraph_vector, add)(&m1->data, &m2->data); } /** * \function igraph_matrix_sub * Difference of two matrices. * * Subtract \p m2 from \p m1 and store the result in \p m1. * The dimensions of the two matrices must match. * \param m1 The first matrix; the result is stored here. * \param m2 The second matrix; it is left unchanged. * \return Error code. * * Time complexity: O(mn), the number of elements. */ int FUNCTION(igraph_matrix, sub)(TYPE(igraph_matrix) *m1, const TYPE(igraph_matrix) *m2) { if (m1->nrow != m2->nrow || m1->ncol != m2->ncol) { IGRAPH_ERROR("Cannot subtract non-conformant matrices", IGRAPH_EINVAL); } return FUNCTION(igraph_vector, sub)(&m1->data, &m2->data); } /** * \function igraph_matrix_mul_elements * Elementwise multiplication. * * Multiply \p m1 by \p m2 elementwise and store the result in \p m1. * The dimensions of the two matrices must match. * \param m1 The first matrix; the result is stored here. * \param m2 The second matrix; it is left unchanged. * \return Error code. * * Time complexity: O(mn), the number of elements. */ int FUNCTION(igraph_matrix, mul_elements)(TYPE(igraph_matrix) *m1, const TYPE(igraph_matrix) *m2) { if (m1->nrow != m2->nrow || m1->ncol != m2->ncol) { IGRAPH_ERROR("Cannot multiply non-conformant matrices", IGRAPH_EINVAL); } return FUNCTION(igraph_vector, mul)(&m1->data, &m2->data); } /** * \function igraph_matrix_div_elements * Elementwise division. * * Divide \p m1 by \p m2 elementwise and store the result in \p m1. * The dimensions of the two matrices must match. * \param m1 The dividend. The result is store here. * \param m2 The divisor. It is left unchanged. * \return Error code. * * Time complexity: O(mn), the number of elements. */ int FUNCTION(igraph_matrix, div_elements)(TYPE(igraph_matrix) *m1, const TYPE(igraph_matrix) *m2) { if (m1->nrow != m2->nrow || m1->ncol != m2->ncol) { IGRAPH_ERROR("Cannot divide non-conformant matrices", IGRAPH_EINVAL); } return FUNCTION(igraph_vector, div)(&m1->data, &m2->data); } #ifndef NOTORDERED /** * \function igraph_matrix_min * Minimum element. * * Returns the smallest element of a non-empty matrix. * \param m The input matrix. * \return The smallest element. * * Time complexity: O(mn), the number of elements. */ igraph_real_t FUNCTION(igraph_matrix, min)(const TYPE(igraph_matrix) *m) { return FUNCTION(igraph_vector, min)(&m->data); } /** * \function igraph_matrix_which_min * Indices of the minimum. * * Gives the indices of the (first) smallest element in a non-empty * matrix. * \param m The matrix. * \param i Pointer to a long int. The row index of the * minimum is stored here. * \param j Pointer to a long int. The column index of * the minimum is stored here. * \return Error code. * * Time complexity: O(mn), the number of elements. */ int FUNCTION(igraph_matrix, which_min)(const TYPE(igraph_matrix) *m, long int *i, long int *j) { long int vmin = FUNCTION(igraph_vector, which_min)(&m->data); *i = vmin % m->nrow; *j = vmin / m->nrow; return 0; } /** * \function igraph_matrix_which_max * Indices of the maximum. * * Gives the indices of the (first) largest element in a non-empty * matrix. * \param m The matrix. * \param i Pointer to a long int. The row index of the * maximum is stored here. * \param j Pointer to a long int. The column index of * the maximum is stored here. * \return Error code. * * Time complexity: O(mn), the number of elements. */ int FUNCTION(igraph_matrix, which_max)(const TYPE(igraph_matrix) *m, long int *i, long int *j) { long int vmax = FUNCTION(igraph_vector, which_max)(&m->data); *i = vmax % m->nrow; *j = vmax / m->nrow; return 0; } /** * \function igraph_matrix_minmax * Minimum and maximum * * The maximum and minimum elements of a non-empty matrix. * \param m The input matrix. * \param min Pointer to a base type. The minimum is stored here. * \param max Pointer to a base type. The maximum is stored here. * \return Error code. * * Time complexity: O(mn), the number of elements. */ int FUNCTION(igraph_matrix, minmax)(const TYPE(igraph_matrix) *m, BASE *min, BASE *max) { return FUNCTION(igraph_vector, minmax)(&m->data, min, max); } /** * \function igraph_matrix_which_minmax * Indices of the minimum and maximum * * Find the positions of the smallest and largest elements of a * non-empty matrix. * \param m The input matrix. * \param imin Pointer to a long int, the row index of * the minimum is stored here. * \param jmin Pointer to a long int, the column index of * the minimum is stored here. * \param imax Pointer to a long int, the row index of * the maximum is stored here. * \param jmax Pointer to a long int, the column index of * the maximum is stored here. * \return Error code. * * Time complexity: O(mn), the number of elements. */ int FUNCTION(igraph_matrix, which_minmax)(const TYPE(igraph_matrix) *m, long int *imin, long int *jmin, long int *imax, long int *jmax) { long int vmin, vmax; FUNCTION(igraph_vector, which_minmax)(&m->data, &vmin, &vmax); *imin = vmin % m->nrow; *jmin = vmin / m->nrow; *imax = vmax % m->nrow; *jmax = vmax / m->nrow; return 0; } #endif /** * \function igraph_matrix_isnull * Check for a null matrix. * * Checks whether all elements are zero. * \param m The input matrix. * \return Boolean, \c TRUE is \p m contains only zeros and \c FALSE * otherwise. * * Time complexity: O(mn), the number of elements. */ igraph_bool_t FUNCTION(igraph_matrix, isnull)(const TYPE(igraph_matrix) *m) { return FUNCTION(igraph_vector, isnull)(&m->data); } /** * \function igraph_matrix_empty * Check for an empty matrix. * * It is possible to have a matrix with zero rows or zero columns, or * even both. This functions checks for these. * \param m The input matrix. * \return Boolean, \c TRUE if the matrix contains zero elements, and * \c FALSE otherwise. * * Time complexity: O(1). */ igraph_bool_t FUNCTION(igraph_matrix, empty)(const TYPE(igraph_matrix) *m) { return FUNCTION(igraph_vector, empty)(&m->data); } /** * \function igraph_matrix_is_symmetric * Check for symmetric matrix. * * A non-square matrix is not symmetric by definition. * \param m The input matrix. * \return Boolean, \c TRUE if the matrix is square and symmetric, \c * FALSE otherwise. * * Time complexity: O(mn), the number of elements. O(1) for non-square * matrices. */ igraph_bool_t FUNCTION(igraph_matrix, is_symmetric)(const TYPE(igraph_matrix) *m) { long int n = m->nrow; long int r, c; if (m->ncol != n) { return 0; } for (r = 1; r < n; r++) { for (c = 0; c < r; c++) { BASE a1 = MATRIX(*m, r, c); BASE a2 = MATRIX(*m, c, r); #ifdef EQ if (!EQ(a1, a2)) { return 0; } #else if (a1 != a2) { return 0; } #endif } } return 1; } /** * \function igraph_matrix_prod * Product of the elements. * * Note this function can result in overflow easily, even for not too * big matrices. * \param m The input matrix. * \return The product of the elements. * * Time complexity: O(mn), the number of elements. */ BASE FUNCTION(igraph_matrix, prod)(const TYPE(igraph_matrix) *m) { return FUNCTION(igraph_vector, prod)(&m->data); } /** * \function igraph_matrix_rowsum * Rowwise sum. * * Calculate the sum of the elements in each row. * \param m The input matrix. * \param res Pointer to an initialized vector; the result is stored * here. It will be resized if necessary. * \return Error code. * * Time complexity: O(mn), the number of elements in the matrix. */ int FUNCTION(igraph_matrix, rowsum)(const TYPE(igraph_matrix) *m, TYPE(igraph_vector) *res) { long int nrow = m->nrow, ncol = m->ncol; long int r, c; BASE sum; IGRAPH_CHECK(FUNCTION(igraph_vector, resize)(res, nrow)); for (r = 0; r < nrow; r++) { sum = ZERO; for (c = 0; c < ncol; c++) { #ifdef SUM SUM(sum, sum, MATRIX(*m, r, c)); #else sum += MATRIX(*m, r, c); #endif } VECTOR(*res)[r] = sum; } return 0; } /** * \function igraph_matrix_colsum * Columnwise sum. * * Calculate the sum of the elements in each column. * \param m The input matrix. * \param res Pointer to an initialized vector; the result is stored * here. It will be resized if necessary. * \return Error code. * * Time complexity: O(mn), the number of elements in the matrix. */ int FUNCTION(igraph_matrix, colsum)(const TYPE(igraph_matrix) *m, TYPE(igraph_vector) *res) { long int nrow = m->nrow, ncol = m->ncol; long int r, c; BASE sum; IGRAPH_CHECK(FUNCTION(igraph_vector, resize)(res, ncol)); for (c = 0; c < ncol; c++) { sum = ZERO; for (r = 0; r < nrow; r++) { #ifdef SUM SUM(sum, sum, MATRIX(*m, r, c)); #else sum += MATRIX(*m, r, c); #endif } VECTOR(*res)[c] = sum; } return 0; } /** * \function igraph_matrix_contains * Search for an element. * * Search for the given element in the matrix. * \param m The input matrix. * \param e The element to search for. * \return Boolean, \c TRUE if the matrix contains \p e, \c FALSE * otherwise. * * Time complexity: O(mn), the number of elements. */ igraph_bool_t FUNCTION(igraph_matrix, contains)(const TYPE(igraph_matrix) *m, BASE e) { return FUNCTION(igraph_vector, contains)(&m->data, e); } /** * \function igraph_matrix_search * Search from a given position. * * Search for an element in a matrix and start the search from the * given position. The search is performed columnwise. * \param m The input matrix. * \param from The position to search from, the positions are * enumerated columnwise. * \param what The element to search for. * \param pos Pointer to a long int. If the element is * found, then this is set to the position of its first appearance. * \param row Pointer to a long int. If the element is * found, then this is set to its row index. * \param col Pointer to a long int. If the element is * found, then this is set to its column index. * \return Boolean, \c TRUE if the element is found, \c FALSE * otherwise. * * Time complexity: O(mn), the number of elements. */ igraph_bool_t FUNCTION(igraph_matrix, search)(const TYPE(igraph_matrix) *m, long int from, BASE what, long int *pos, long int *row, long int *col) { igraph_bool_t find = FUNCTION(igraph_vector, search)(&m->data, from, what, pos); if (find) { *row = *pos % m->nrow; *col = *pos / m->nrow; } return find; } /** * \function igraph_matrix_remove_row * Remove a row. * * A row is removed from the matrix. * \param m The input matrix. * \param row The index of the row to remove. * \return Error code. * * Time complexity: O(mn), the number of elements in the matrix. */ int FUNCTION(igraph_matrix, remove_row)(TYPE(igraph_matrix) *m, long int row) { long int c, r, index = row + 1, leap = 1, n = m->nrow * m->ncol; if (row >= m->nrow) { IGRAPH_ERROR("Cannot remove row, index out of range", IGRAPH_EINVAL); } for (c = 0; c < m->ncol; c++) { for (r = 0; r < m->nrow - 1 && index < n; r++) { VECTOR(m->data)[index - leap] = VECTOR(m->data)[index]; index++; } leap++; index++; } m->nrow--; FUNCTION(igraph_vector, resize)(&m->data, m->nrow * m->ncol); return 0; } /** * \function igraph_matrix_select_cols * \brief Select some columns of a matrix. * * This function selects some columns of a matrix and returns them in a * new matrix. The result matrix should be initialized before calling * the function. * \param m The input matrix. * \param res The result matrix. It should be initialized and will be * resized as needed. * \param cols Vector; it contains the column indices (starting with * zero) to extract. Note that no range checking is performed. * \return Error code. * * Time complexity: O(nm), n is the number of rows, m the number of * columns of the result matrix. */ int FUNCTION(igraph_matrix, select_cols)(const TYPE(igraph_matrix) *m, TYPE(igraph_matrix) *res, const igraph_vector_t *cols) { long int ncols = igraph_vector_size(cols); long int nrows = m->nrow; long int i, j; IGRAPH_CHECK(FUNCTION(igraph_matrix, resize)(res, nrows, ncols)); for (i = 0; i < nrows; i++) { for (j = 0; j < ncols; j++) { MATRIX(*res, i, j) = MATRIX(*m, i, (long int)VECTOR(*cols)[j]); } } return 0; } #ifdef OUT_FORMAT #ifndef USING_R int FUNCTION(igraph_matrix, print)(const TYPE(igraph_matrix) *m) { long int nr = FUNCTION(igraph_matrix, nrow)(m); long int nc = FUNCTION(igraph_matrix, ncol)(m); long int i, j; for (i = 0; i < nr; i++) { for (j = 0; j < nc; j++) { if (j != 0) { putchar(' '); } printf(OUT_FORMAT, MATRIX(*m, i, j)); } printf("\n"); } return 0; } int FUNCTION(igraph_matrix, printf)(const TYPE(igraph_matrix) *m, const char *format) { long int nr = FUNCTION(igraph_matrix, nrow)(m); long int nc = FUNCTION(igraph_matrix, ncol)(m); long int i, j; for (i = 0; i < nr; i++) { for (j = 0; j < nc; j++) { if (j != 0) { putchar(' '); } printf(format, MATRIX(*m, i, j)); } printf("\n"); } return 0; } #endif int FUNCTION(igraph_matrix, fprint)(const TYPE(igraph_matrix) *m, FILE *file) { long int nr = FUNCTION(igraph_matrix, nrow)(m); long int nc = FUNCTION(igraph_matrix, ncol)(m); long int i, j; for (i = 0; i < nr; i++) { for (j = 0; j < nc; j++) { if (j != 0) { fputc(' ', file); } fprintf(file, OUT_FORMAT, MATRIX(*m, i, j)); } fprintf(file, "\n"); } return 0; } #endif python-igraph-0.8.0/vendor/source/igraph/src/decomposition.c0000644000076500000240000003537213614300625024430 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2008-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_structural.h" #include "igraph_error.h" #include "igraph_adjlist.h" #include "igraph_interface.h" /** * \function igraph_maximum_cardinality_search * Maximum cardinality search * * This function implements the maximum cardinality search algorithm * discussed in * Robert E Tarjan and Mihalis Yannakakis: Simple linear-time * algorithms to test chordality of graphs, test acyclicity of * hypergraphs, and selectively reduce acyclic hypergraphs. * SIAM Journal of Computation 13, 566--579, 1984. * * \param graph The input graph, which should be undirected and simple. * of the edges is ignored. * \param alpha Pointer to an initialized vector, the result is stored here. * It will be resized, as needed. Upon return it contains * the rank of the each vertex. * \param alpham1 Pointer to an initialized vector or a \c NULL * pointer. If not \c NULL, then the inverse of \p alpha is stored * here. * \return Error code. * * Time complexity: O(|V|+|E|), linear in terms of the number of * vertices and edges. * * \sa \ref igraph_is_chordal(). */ int igraph_maximum_cardinality_search(const igraph_t *graph, igraph_vector_t *alpha, igraph_vector_t *alpham1) { long int no_of_nodes = igraph_vcount(graph); igraph_vector_long_t size; igraph_vector_long_t head, next, prev; /* doubly linked list with head */ long int i; igraph_adjlist_t adjlist; igraph_bool_t simple; /***************/ /* local j, v; */ /***************/ long int j, v; if (igraph_is_directed(graph)) { IGRAPH_ERROR("Maximum cardinality search works on undirected graphs only", IGRAPH_EINVAL); } igraph_is_simple(graph, &simple); if (!simple) { IGRAPH_ERROR("Maximum cardinality search works on simple graphs only", IGRAPH_EINVAL); } if (no_of_nodes == 0) { igraph_vector_clear(alpha); if (alpham1) { igraph_vector_clear(alpham1); } return IGRAPH_SUCCESS; } IGRAPH_CHECK(igraph_vector_long_init(&size, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_long_destroy, &size); IGRAPH_CHECK(igraph_vector_long_init(&head, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_long_destroy, &head); IGRAPH_CHECK(igraph_vector_long_init(&next, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_long_destroy, &next); IGRAPH_CHECK(igraph_vector_long_init(&prev, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_long_destroy, &prev); IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist); IGRAPH_CHECK(igraph_vector_resize(alpha, no_of_nodes)); if (alpham1) { IGRAPH_CHECK(igraph_vector_resize(alpham1, no_of_nodes)); } /***********************************************/ /* for i in [0,n-1] -> set(i) := emptyset rof; */ /***********************************************/ /* nothing to do, 'head' contains all zeros */ /*********************************************************/ /* for v in vertices -> size(v):=0; add v to set(0) rof; */ /*********************************************************/ VECTOR(head)[0] = 1; for (v = 0; v < no_of_nodes; v++) { VECTOR(next)[v] = v + 2; VECTOR(prev)[v] = v; } VECTOR(next)[no_of_nodes - 1] = 0; /* size is already all zero */ /***************/ /* i:=n; j:=0; */ /***************/ i = no_of_nodes; j = 0; /**************/ /* do i>=1 -> */ /**************/ while (i >= 1) { long int x, k, len; igraph_vector_int_t *neis; /********************************/ /* v := delete any from set(j) */ /********************************/ v = VECTOR(head)[j] - 1; x = VECTOR(next)[v]; VECTOR(head)[j] = x; if (x != 0) { VECTOR(prev)[x - 1] = 0; } /*************************************************/ /* alpha(v) := i; alpham1(i) := v; size(v) := -1 */ /*************************************************/ VECTOR(*alpha)[v] = i - 1; if (alpham1) { VECTOR(*alpham1)[i - 1] = v; } VECTOR(size)[v] = -1; /********************************************/ /* for {v,w} in E such that size(w) >= 0 -> */ /********************************************/ neis = igraph_adjlist_get(&adjlist, v); len = igraph_vector_int_size(neis); for (k = 0; k < len; k++) { long int w = (long int) VECTOR(*neis)[k]; long int ws = VECTOR(size)[w]; if (ws >= 0) { /******************************/ /* delete w from set(size(w)) */ /******************************/ long int nw = VECTOR(next)[w]; long int pw = VECTOR(prev)[w]; if (nw != 0) { VECTOR(prev)[nw - 1] = pw; } if (pw != 0) { VECTOR(next)[pw - 1] = nw; } else { VECTOR(head)[ws] = nw; } /******************************/ /* size(w) := size(w)+1 */ /******************************/ VECTOR(size)[w] += 1; /******************************/ /* add w to set(size(w)) */ /******************************/ ws = VECTOR(size)[w]; nw = VECTOR(head)[ws]; VECTOR(next)[w] = nw; VECTOR(prev)[w] = 0; if (nw != 0) { VECTOR(prev)[nw - 1] = w + 1; } VECTOR(head)[ws] = w + 1; } } /***********************/ /* i := i-1; j := j+1; */ /***********************/ i -= 1; j += 1; /*********************************************/ /* do j>=0 and set(j)=emptyset -> j:=j-1; od */ /*********************************************/ if (j < no_of_nodes) { while (j >= 0 && VECTOR(head)[j] == 0) { j--; } } } igraph_adjlist_destroy(&adjlist); igraph_vector_long_destroy(&prev); igraph_vector_long_destroy(&next); igraph_vector_long_destroy(&head); igraph_vector_long_destroy(&size); IGRAPH_FINALLY_CLEAN(5); return 0; } /** * \function igraph_is_chordal * Decides whether a graph is chordal * * A graph is chordal if each of its cycles of four or more nodes * has a chord, which is an edge joining two nodes that are not * adjacent in the cycle. An equivalent definition is that any * chordless cycles have at most three nodes. * * If either \p alpha or \p alpha1 is given, then the other is * calculated by taking simply the inverse. If neither are given, * then \ref igraph_maximum_cardinality_search() is called to calculate * them. * \param graph The input graph, it might be directed, but edge * direction is ignored. * \param alpha Either an alpha vector coming from * \ref igraph_maximum_cardinality_search() (on the same graph), or a * null pointer. * \param alpham1 Either an inverse alpha vector coming from \ref * igraph_maximum_cardinality_search() (on the same graph) or a null * pointer. * \param chordal Pointer to a boolean, the result is stored here. * \param fill_in Pointer to an initialized vector, or a null * pointer. If not a null pointer, then the fill-in of the graph is * stored here. The fill-in is the set of edges that are needed to * make the graph chordal. The vector is resized as needed. * \param newgraph Pointer to an uninitialized graph, or a null * pointer. If not a null pointer, then a new triangulated graph is * created here. This essentially means adding the fill-in edges to * the original graph. * \return Error code. * * Time complexity: O(n). * * \sa \ref igraph_maximum_cardinality_search(). */ int igraph_is_chordal(const igraph_t *graph, const igraph_vector_t *alpha, const igraph_vector_t *alpham1, igraph_bool_t *chordal, igraph_vector_t *fill_in, igraph_t *newgraph) { long int no_of_nodes = igraph_vcount(graph); const igraph_vector_t *my_alpha = alpha, *my_alpham1 = alpham1; igraph_vector_t v_alpha, v_alpham1; igraph_vector_long_t f, index; long int i; igraph_adjlist_t adjlist; igraph_vector_long_t mark; igraph_bool_t calc_edges = fill_in || newgraph; igraph_vector_t *my_fill_in = fill_in, v_fill_in; /*****************/ /* local v, w, x */ /*****************/ long int v, w, x; if (!chordal && !calc_edges) { /* Nothing to calculate */ return 0; } if (!alpha && !alpham1) { IGRAPH_VECTOR_INIT_FINALLY(&v_alpha, no_of_nodes); my_alpha = &v_alpha; IGRAPH_VECTOR_INIT_FINALLY(&v_alpham1, no_of_nodes); my_alpham1 = &v_alpham1; IGRAPH_CHECK(igraph_maximum_cardinality_search(graph, (igraph_vector_t*) my_alpha, (igraph_vector_t*) my_alpham1)); } else if (alpha && !alpham1) { long int v; IGRAPH_VECTOR_INIT_FINALLY(&v_alpham1, no_of_nodes); my_alpham1 = &v_alpham1; for (v = 0; v < no_of_nodes; v++) { long int i = (long int) VECTOR(*my_alpha)[v]; VECTOR(*my_alpham1)[i] = v; } } else if (!alpha && alpham1) { long int i; IGRAPH_VECTOR_INIT_FINALLY(&v_alpha, no_of_nodes); my_alpha = &v_alpha; for (i = 0; i < no_of_nodes; i++) { long int v = (long int) VECTOR(*my_alpham1)[i]; VECTOR(*my_alpha)[v] = i; } } if (!fill_in && newgraph) { IGRAPH_VECTOR_INIT_FINALLY(&v_fill_in, 0); my_fill_in = &v_fill_in; } IGRAPH_CHECK(igraph_vector_long_init(&f, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_long_destroy, &f); IGRAPH_CHECK(igraph_vector_long_init(&index, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_long_destroy, &index); IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist); IGRAPH_CHECK(igraph_vector_long_init(&mark, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_long_destroy, &mark); if (my_fill_in) { igraph_vector_clear(my_fill_in); } if (chordal) { *chordal = 1; } /*********************/ /* for i in [1,n] -> */ /*********************/ for (i = 0; i < no_of_nodes; i++) { igraph_vector_int_t *neis; long int j, len; /**********************************************/ /* w := alpham1(i); f(w) := w; index(w) := i; */ /**********************************************/ w = (long int) VECTOR(*my_alpham1)[i]; VECTOR(f)[w] = w; VECTOR(index)[w] = i; /******************************************/ /* for {v,w} in E such that alpha(v) */ /******************************************/ neis = igraph_adjlist_get(&adjlist, w); len = igraph_vector_int_size(neis); for (j = 0; j < len; j++) { v = (long int) VECTOR(*neis)[j]; VECTOR(mark)[v] = w + 1; } for (j = 0; j < len; j++) { v = (long int) VECTOR(*neis)[j]; if (VECTOR(*my_alpha)[v] >= i) { continue; } /**********/ /* x := v */ /**********/ x = v; /********************/ /* do index(x) */ /********************/ while (VECTOR(index)[x] < i) { /******************/ /* index(x) := i; */ /******************/ VECTOR(index)[x] = i; /**********************************/ /* add {x,w} to E union F(alpha); */ /**********************************/ if (VECTOR(mark)[x] != w + 1) { if (chordal) { *chordal = 0; } if (my_fill_in) { IGRAPH_CHECK(igraph_vector_push_back(my_fill_in, x)); IGRAPH_CHECK(igraph_vector_push_back(my_fill_in, w)); } if (!calc_edges) { /* make sure that we exit from all loops */ i = no_of_nodes; j = len; break; } } /*************/ /* x := f(x) */ /*************/ x = VECTOR(f)[x]; } /* while (VECTOR(index)[x] < i) */ /*****************************/ /* if (f(x)=x -> f(x):=w; fi */ /*****************************/ if (VECTOR(f)[x] == x) { VECTOR(f)[x] = w; } } } igraph_vector_long_destroy(&mark); igraph_adjlist_destroy(&adjlist); igraph_vector_long_destroy(&index); igraph_vector_long_destroy(&f); IGRAPH_FINALLY_CLEAN(4); if (newgraph) { IGRAPH_CHECK(igraph_copy(newgraph, graph)); IGRAPH_FINALLY(igraph_destroy, newgraph); IGRAPH_CHECK(igraph_add_edges(newgraph, my_fill_in, 0)); IGRAPH_FINALLY_CLEAN(1); } if (!fill_in && newgraph) { igraph_vector_destroy(&v_fill_in); IGRAPH_FINALLY_CLEAN(1); } if (!alpha && !alpham1) { igraph_vector_destroy(&v_alpham1); igraph_vector_destroy(&v_alpha); IGRAPH_FINALLY_CLEAN(2); } else if (alpha && !alpham1) { igraph_vector_destroy(&v_alpham1); IGRAPH_FINALLY_CLEAN(1); } else if (!alpha && alpham1) { igraph_vector_destroy(&v_alpha); IGRAPH_FINALLY_CLEAN(1); } return 0; } python-igraph-0.8.0/vendor/source/igraph/src/qsort.c0000644000076500000240000001512413614300625022715 0ustar tamasstaff00000000000000/*- * Copyright (c) 1992, 1993 * The Regents of the University of California. All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions * are met: * 1. Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * 2. Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * 3. All advertising materials mentioning features or use of this software * must display the following acknowledgement: * This product includes software developed by the University of * California, Berkeley and its contributors. * 4. Neither the name of the University nor the names of its contributors * may be used to endorse or promote products derived from this software * without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE * ARE DISCLAIMED. IN NO EVENT SHALL THE REGENTS OR CONTRIBUTORS BE LIABLE * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL * DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS * OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) * HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY * OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF * SUCH DAMAGE. */ #ifdef _MSC_VER /* MSVC does not have inline when compiling C source files */ #define inline __inline #define __unused #endif #ifndef __unused #define __unused __attribute__ ((unused)) #endif #if defined(LIBC_SCCS) && !defined(lint) static char sccsid[] = "@(#)qsort.c 8.1 (Berkeley) 6/4/93"; #endif /* LIBC_SCCS and not lint */ /*#include */ #include #ifdef I_AM_QSORT_R typedef int cmp_t(void *, const void *, const void *); #else typedef int cmp_t(const void *, const void *); #endif static inline char *med3(char *, char *, char *, cmp_t *, void *); static inline void swapfunc(char *, char *, int, int); #define igraph_min(a, b) (a) < (b) ? a : b /* * Qsort routine from Bentley & McIlroy's "Engineering a Sort Function". */ #define swapcode(TYPE, parmi, parmj, n) { \ long i = (n) / sizeof (TYPE); \ TYPE *pi = (TYPE *) (parmi); \ TYPE *pj = (TYPE *) (parmj); \ do { \ TYPE t = *pi; \ *pi++ = *pj; \ *pj++ = t; \ } while (--i > 0); \ } #define SWAPINIT(a, es) swaptype = ((char *)a - (char *)0) % sizeof(long) || \ es % sizeof(long) ? 2 : es == sizeof(long)? 0 : 1; static inline void swapfunc(a, b, n, swaptype) char *a, *b; int n, swaptype; { if (swaptype <= 1) swapcode(long, a, b, n) else swapcode(char, a, b, n) } #define swap(a, b) \ if (swaptype == 0) { \ long t = *(long *)(a); \ *(long *)(a) = *(long *)(b); \ *(long *)(b) = t; \ } else \ swapfunc(a, b, es, swaptype) #define vecswap(a, b, n) if ((n) > 0) swapfunc(a, b, n, swaptype) #ifdef I_AM_QSORT_R #define CMP(t, x, y) (cmp((t), (x), (y))) #else #define CMP(t, x, y) (cmp((x), (y))) #endif static inline char * med3(char *a, char *b, char *c, cmp_t *cmp, void *thunk #ifndef I_AM_QSORT_R __unused #endif ) { return CMP(thunk, a, b) < 0 ? (CMP(thunk, b, c) < 0 ? b : (CMP(thunk, a, c) < 0 ? c : a )) : (CMP(thunk, b, c) > 0 ? b : (CMP(thunk, a, c) < 0 ? a : c )); } #ifdef I_AM_QSORT_R void igraph_qsort_r(void *a, size_t n, size_t es, void *thunk, cmp_t *cmp) #else #define thunk NULL void igraph_qsort(void *a, size_t n, size_t es, cmp_t *cmp) #endif { char *pa, *pb, *pc, *pd, *pl, *pm, *pn; int d, r, swaptype, swap_cnt; loop: SWAPINIT(a, es); swap_cnt = 0; if (n < 7) { for (pm = (char *)a + es; pm < (char *)a + n * es; pm += es) for (pl = pm; pl > (char *)a && CMP(thunk, pl - es, pl) > 0; pl -= es) { swap(pl, pl - es); } return; } pm = (char *)a + (n / 2) * es; if (n > 7) { pl = a; pn = (char *)a + (n - 1) * es; if (n > 40) { d = (n / 8) * es; pl = med3(pl, pl + d, pl + 2 * d, cmp, thunk); pm = med3(pm - d, pm, pm + d, cmp, thunk); pn = med3(pn - 2 * d, pn - d, pn, cmp, thunk); } pm = med3(pl, pm, pn, cmp, thunk); } swap(a, pm); pa = pb = (char *)a + es; pc = pd = (char *)a + (n - 1) * es; for (;;) { while (pb <= pc && (r = CMP(thunk, pb, a)) <= 0) { if (r == 0) { swap_cnt = 1; swap(pa, pb); pa += es; } pb += es; } while (pb <= pc && (r = CMP(thunk, pc, a)) >= 0) { if (r == 0) { swap_cnt = 1; swap(pc, pd); pd -= es; } pc -= es; } if (pb > pc) { break; } swap(pb, pc); swap_cnt = 1; pb += es; pc -= es; } if (swap_cnt == 0) { /* Switch to insertion sort */ for (pm = (char *)a + es; pm < (char *)a + n * es; pm += es) for (pl = pm; pl > (char *)a && CMP(thunk, pl - es, pl) > 0; pl -= es) { swap(pl, pl - es); } return; } pn = (char *)a + n * es; r = igraph_min(pa - (char *)a, pb - pa); vecswap(a, pb - r, r); r = igraph_min((size_t)(pd - pc), (size_t)(pn - pd - es)); vecswap(pb, pn - r, r); if ((size_t)(r = pb - pa) > es) #ifdef I_AM_QSORT_R igraph_qsort_r(a, r / es, es, thunk, cmp); #else igraph_qsort(a, r / es, es, cmp); #endif if ((size_t)(r = pd - pc) > es) { /* Iterate rather than recurse to save stack space */ a = pn - r; n = r / es; goto loop; } /* qsort(pn - r, r / es, es, cmp);*/ } python-igraph-0.8.0/vendor/source/igraph/src/sbm.c0000644000076500000240000005445713614300625022342 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph R library. Copyright (C) 2003-2013 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_interface.h" #include "igraph_vector.h" #include "igraph_matrix.h" #include "igraph_random.h" #include "igraph_constructors.h" #include "igraph_games.h" #include /* for DBL_EPSILON */ #include /* for sqrt */ /** * \function igraph_sbm_game * Sample from a stochastic block model * * This function samples graphs from a stochastic block * model by (doing the equivalent of) Bernoulli * trials for each potential edge with the probabilities * given by the Bernoulli rate matrix, \p pref_matrix. * See Faust, K., & Wasserman, S. (1992a). Blockmodels: * Interpretation and evaluation. Social Networks, 14, 5-–61. * * * The order of the vertex ids in the generated graph corresponds to * the \p block_sizes argument. * * \param graph The output graph. * \param n Number of vertices. * \param pref_matrix The matrix giving the Bernoulli rates. * This is a KxK matrix, where K is the number of groups. * The probability of creating an edge between vertices from * groups i and j is given by element (i,j). * \param block_sizes An integer vector giving the number of * vertices in each group. * \param directed Boolean, whether to create a directed graph. If * this argument is false, then \p pref_matrix must be symmetric. * \param loops Boolean, whether to create self-loops. * \return Error code. * * Time complexity: O(|V|+|E|+K^2), where |V| is the number of * vertices, |E| is the number of edges, and K is the number of * groups. * * \sa \ref igraph_erdos_renyi_game() for a simple Bernoulli graph. * */ int igraph_sbm_game(igraph_t *graph, igraph_integer_t n, const igraph_matrix_t *pref_matrix, const igraph_vector_int_t *block_sizes, igraph_bool_t directed, igraph_bool_t loops) { int no_blocks = igraph_matrix_nrow(pref_matrix); int from, to, fromoff = 0; igraph_real_t minp, maxp; igraph_vector_t edges; /* ------------------------------------------------------------ */ /* Check arguments */ /* ------------------------------------------------------------ */ if (igraph_matrix_ncol(pref_matrix) != no_blocks) { IGRAPH_ERROR("Preference matrix is not square", IGRAPH_NONSQUARE); } igraph_matrix_minmax(pref_matrix, &minp, &maxp); if (minp < 0 || maxp > 1) { IGRAPH_ERROR("Connection probabilities must in [0,1]", IGRAPH_EINVAL); } if (n < 0) { IGRAPH_ERROR("Number of vertices must be non-negative", IGRAPH_EINVAL); } if (!directed && !igraph_matrix_is_symmetric(pref_matrix)) { IGRAPH_ERROR("Preference matrix must be symmetric for undirected graphs", IGRAPH_EINVAL); } if (igraph_vector_int_size(block_sizes) != no_blocks) { IGRAPH_ERROR("Invalid block size vector length", IGRAPH_EINVAL); } if (igraph_vector_int_min(block_sizes) < 0) { IGRAPH_ERROR("Block size must be non-negative", IGRAPH_EINVAL); } if (igraph_vector_int_sum(block_sizes) != n) { IGRAPH_ERROR("Block sizes must sum up to number of vertices", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); RNG_BEGIN(); for (from = 0; from < no_blocks; from++) { double fromsize = VECTOR(*block_sizes)[from]; int start = directed ? 0 : from; int i, tooff = 0; for (i = 0; i < start; i++) { tooff += VECTOR(*block_sizes)[i]; } for (to = start; to < no_blocks; to++) { double tosize = VECTOR(*block_sizes)[to]; igraph_real_t prob = MATRIX(*pref_matrix, from, to); double maxedges, last = RNG_GEOM(prob); if (directed && loops) { maxedges = fromsize * tosize; while (last < maxedges) { int vto = floor(last / fromsize); int vfrom = last - (igraph_real_t)vto * fromsize; igraph_vector_push_back(&edges, fromoff + vfrom); igraph_vector_push_back(&edges, tooff + vto); last += RNG_GEOM(prob); last += 1; } } else if (directed && !loops && from != to) { maxedges = fromsize * tosize; while (last < maxedges) { int vto = floor(last / fromsize); int vfrom = last - (igraph_real_t)vto * fromsize; igraph_vector_push_back(&edges, fromoff + vfrom); igraph_vector_push_back(&edges, tooff + vto); last += RNG_GEOM(prob); last += 1; } } else if (directed && !loops && from == to) { maxedges = fromsize * (fromsize - 1); while (last < maxedges) { int vto = floor(last / fromsize); int vfrom = last - (igraph_real_t)vto * fromsize; if (vfrom == vto) { vto = fromsize - 1; } igraph_vector_push_back(&edges, fromoff + vfrom); igraph_vector_push_back(&edges, tooff + vto); last += RNG_GEOM(prob); last += 1; } } else if (!directed && loops && from != to) { maxedges = fromsize * tosize; while (last < maxedges) { int vto = floor(last / fromsize); int vfrom = last - (igraph_real_t)vto * fromsize; igraph_vector_push_back(&edges, fromoff + vfrom); igraph_vector_push_back(&edges, tooff + vto); last += RNG_GEOM(prob); last += 1; } } else if (!directed && loops && from == to) { maxedges = fromsize * (fromsize + 1) / 2.0; while (last < maxedges) { long int vto = floor((sqrt(8 * last + 1) - 1) / 2); long int vfrom = last - (((igraph_real_t)vto) * (vto + 1)) / 2; igraph_vector_push_back(&edges, fromoff + vfrom); igraph_vector_push_back(&edges, tooff + vto); last += RNG_GEOM(prob); last += 1; } } else if (!directed && !loops && from != to) { maxedges = fromsize * tosize; while (last < maxedges) { int vto = floor(last / fromsize); int vfrom = last - (igraph_real_t)vto * fromsize; igraph_vector_push_back(&edges, fromoff + vfrom); igraph_vector_push_back(&edges, tooff + vto); last += RNG_GEOM(prob); last += 1; } } else { /*!directed && !loops && from==to */ maxedges = fromsize * (fromsize - 1) / 2.0; while (last < maxedges) { int vto = floor((sqrt(8 * last + 1) + 1) / 2); int vfrom = last - (((igraph_real_t)vto) * (vto - 1)) / 2; igraph_vector_push_back(&edges, fromoff + vfrom); igraph_vector_push_back(&edges, tooff + vto); last += RNG_GEOM(prob); last += 1; } } tooff += tosize; } fromoff += fromsize; } RNG_END(); igraph_create(graph, &edges, n, directed); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_hsbm_game * Hierarchical stochastic block model * * The function generates a random graph according to the hierarchical * stochastic block model. * * \param graph The generated graph is stored here. * \param n The number of vertices in the graph. * \param m The number of vertices per block. n/m must be integer. * \param rho The fraction of vertices per cluster, * within a block. Must sum up to 1, and rho * m must be integer * for all elements of rho. * \param C A square, symmetric numeric matrix, the Bernoulli rates for * the clusters within a block. Its size must mach the size of the * \code{rho} vector. * \param p The Bernoulli rate of connections between * vertices in different blocks. * \return Error code. * * \sa \ref igraph_sbm_game() for the classic stochastic block model, * \ref igraph_hsbm_list_game() for a more general version. */ int igraph_hsbm_game(igraph_t *graph, igraph_integer_t n, igraph_integer_t m, const igraph_vector_t *rho, const igraph_matrix_t *C, igraph_real_t p) { int b, i, k = igraph_vector_size(rho); igraph_vector_t csizes; igraph_real_t sq_dbl_epsilon = sqrt(DBL_EPSILON); int no_blocks = n / m; igraph_vector_t edges; int offset = 0; if (n < 1) { IGRAPH_ERROR("`n' must be positive for HSBM", IGRAPH_EINVAL); } if (m < 1) { IGRAPH_ERROR("`m' must be positive for HSBM", IGRAPH_EINVAL); } if ((long) n % (long) m) { IGRAPH_ERROR("`n' must be a multiple of `m' for HSBM", IGRAPH_EINVAL); } if (!igraph_vector_isininterval(rho, 0, 1)) { IGRAPH_ERROR("`rho' must be between zero and one for HSBM", IGRAPH_EINVAL); } if (igraph_matrix_min(C) < 0 || igraph_matrix_max(C) > 1) { IGRAPH_ERROR("`C' must be between zero and one for HSBM", IGRAPH_EINVAL); } if (fabs(igraph_vector_sum(rho) - 1.0) > sq_dbl_epsilon) { IGRAPH_ERROR("`rho' must sum up to 1 for HSBM", IGRAPH_EINVAL); } if (igraph_matrix_nrow(C) != k || igraph_matrix_ncol(C) != k) { IGRAPH_ERROR("`C' dimensions must match `rho' dimensions in HSBM", IGRAPH_EINVAL); } if (!igraph_matrix_is_symmetric(C)) { IGRAPH_ERROR("`C' must be a symmetric matrix", IGRAPH_EINVAL); } if (p < 0 || p > 1) { IGRAPH_ERROR("`p' must be a probability for HSBM", IGRAPH_EINVAL); } for (i = 0; i < k; i++) { igraph_real_t s = VECTOR(*rho)[i] * m; if (fabs(round(s) - s) > sq_dbl_epsilon) { IGRAPH_ERROR("`rho' * `m' is not integer in HSBM", IGRAPH_EINVAL); } } IGRAPH_VECTOR_INIT_FINALLY(&csizes, k); for (i = 0; i < k; i++) { VECTOR(csizes)[i] = round(VECTOR(*rho)[i] * m); } IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); RNG_BEGIN(); /* Block models first */ for (b = 0; b < no_blocks; b++) { int from, to, fromoff = 0; for (from = 0; from < k; from++) { int fromsize = VECTOR(csizes)[from]; int i, tooff = 0; for (i = 0; i < from; i++) { tooff += VECTOR(csizes)[i]; } for (to = from; to < k; to++) { int tosize = VECTOR(csizes)[to]; igraph_real_t prob = MATRIX(*C, from, to); igraph_real_t maxedges; igraph_real_t last = RNG_GEOM(prob); if (from != to) { maxedges = fromsize * tosize; while (last < maxedges) { int vto = floor(last / fromsize); int vfrom = last - (igraph_real_t)vto * fromsize; igraph_vector_push_back(&edges, offset + fromoff + vfrom); igraph_vector_push_back(&edges, offset + tooff + vto); last += RNG_GEOM(prob); last += 1; } } else { /* from==to */ maxedges = fromsize * (fromsize - 1) / 2.0; while (last < maxedges) { int vto = floor((sqrt(8 * last + 1) + 1) / 2); int vfrom = last - (((igraph_real_t)vto) * (vto - 1)) / 2; igraph_vector_push_back(&edges, offset + fromoff + vfrom); igraph_vector_push_back(&edges, offset + tooff + vto); last += RNG_GEOM(prob); last += 1; } } tooff += tosize; } fromoff += fromsize; } offset += m; } /* And now the rest, if not a special case */ if (p == 1) { int fromoff = 0, tooff = m; for (b = 0; b < no_blocks; b++) { igraph_real_t fromsize = m; igraph_real_t tosize = n - tooff; int from, to; for (from = 0; from < fromsize; from++) { for (to = 0; to < tosize; to++) { igraph_vector_push_back(&edges, fromoff + from); igraph_vector_push_back(&edges, tooff + to); } } fromoff += m; tooff += m; } } else if (p > 0) { int fromoff = 0, tooff = m; for (b = 0; b < no_blocks; b++) { igraph_real_t fromsize = m; igraph_real_t tosize = n - tooff; igraph_real_t maxedges = fromsize * tosize; igraph_real_t last = RNG_GEOM(p); while (last < maxedges) { int vto = floor(last / fromsize); int vfrom = last - (igraph_real_t) vto * fromsize; igraph_vector_push_back(&edges, fromoff + vfrom); igraph_vector_push_back(&edges, tooff + vto); last += RNG_GEOM(p); last += 1; } fromoff += m; tooff += m; } } RNG_END(); igraph_create(graph, &edges, n, /*directed=*/ 0); igraph_vector_destroy(&edges); igraph_vector_destroy(&csizes); IGRAPH_FINALLY_CLEAN(2); return 0; } /** * \function igraph_hsbm_list_game * Hierarchical stochastic block model, more general version * * The function generates a random graph according to the hierarchical * stochastic block model. * * \param graph The generated graph is stored here. * \param n The number of vertices in the graph. * \param mlist An integer vector of block sizes. * \param rholist A list of rho vectors (\c igraph_vector_t objects), one * for each block. * \param Clist A list of square matrices (\c igraph_matrix_t objects), * one for each block, giving the Bernoulli rates of connections * within the block. * \param p The Bernoulli rate of connections between * vertices in different blocks. * \return Error code. * * \sa \ref igraph_sbm_game() for the classic stochastic block model, * \ref igraph_hsbm_game() for a simpler general version. */ int igraph_hsbm_list_game(igraph_t *graph, igraph_integer_t n, const igraph_vector_int_t *mlist, const igraph_vector_ptr_t *rholist, const igraph_vector_ptr_t *Clist, igraph_real_t p) { int i, no_blocks = igraph_vector_ptr_size(rholist); igraph_real_t sq_dbl_epsilon = sqrt(DBL_EPSILON); igraph_vector_t csizes, edges; int b, offset = 0; if (n < 1) { IGRAPH_ERROR("`n' must be positive for HSBM", IGRAPH_EINVAL); } if (no_blocks == 0) { IGRAPH_ERROR("`rholist' empty for HSBM", IGRAPH_EINVAL); } if (igraph_vector_ptr_size(Clist) != no_blocks && igraph_vector_int_size(mlist) != no_blocks) { IGRAPH_ERROR("`rholist' must have same length as `Clist' and `m' " "for HSBM", IGRAPH_EINVAL); } if (p < 0 || p > 1) { IGRAPH_ERROR("`p' must be a probability for HSBM", IGRAPH_EINVAL); } /* Checks for m's */ if (igraph_vector_int_sum(mlist) != n) { IGRAPH_ERROR("`m' must sum up to `n' for HSBM", IGRAPH_EINVAL); } if (igraph_vector_int_min(mlist) < 1) { IGRAPH_ERROR("`m' must be positive for HSBM", IGRAPH_EINVAL); } /* Checks for the rhos */ for (i = 0; i < no_blocks; i++) { const igraph_vector_t *rho = VECTOR(*rholist)[i]; if (!igraph_vector_isininterval(rho, 0, 1)) { IGRAPH_ERROR("`rho' must be between zero and one for HSBM", IGRAPH_EINVAL); } if (fabs(igraph_vector_sum(rho) - 1.0) > sq_dbl_epsilon) { IGRAPH_ERROR("`rho' must sum up to 1 for HSBM", IGRAPH_EINVAL); } } /* Checks for the Cs */ for (i = 0; i < no_blocks; i++) { const igraph_matrix_t *C = VECTOR(*Clist)[i]; if (igraph_matrix_min(C) < 0 || igraph_matrix_max(C) > 1) { IGRAPH_ERROR("`C' must be between zero and one for HSBM", IGRAPH_EINVAL); } if (!igraph_matrix_is_symmetric(C)) { IGRAPH_ERROR("`C' must be a symmetric matrix", IGRAPH_EINVAL); } } /* Check that C and rho sizes match */ for (i = 0; i < no_blocks; i++) { const igraph_vector_t *rho = VECTOR(*rholist)[i]; const igraph_matrix_t *C = VECTOR(*Clist)[i]; int k = igraph_vector_size(rho); if (igraph_matrix_nrow(C) != k || igraph_matrix_ncol(C) != k) { IGRAPH_ERROR("`C' dimensions must match `rho' dimensions in HSBM", IGRAPH_EINVAL); } } /* Check that rho * m is integer */ for (i = 0; i < no_blocks; i++) { const igraph_vector_t *rho = VECTOR(*rholist)[i]; igraph_real_t m = VECTOR(*mlist)[i]; int j, k = igraph_vector_size(rho); for (j = 0; j < k; j++) { igraph_real_t s = VECTOR(*rho)[j] * m; if (fabs(round(s) - s) > sq_dbl_epsilon) { IGRAPH_ERROR("`rho' * `m' is not integer in HSBM", IGRAPH_EINVAL); } } } IGRAPH_VECTOR_INIT_FINALLY(&csizes, 0); IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); RNG_BEGIN(); /* Block models first */ for (b = 0; b < no_blocks; b++) { int from, to, fromoff = 0; const igraph_vector_t *rho = VECTOR(*rholist)[b]; const igraph_matrix_t *C = VECTOR(*Clist)[b]; igraph_real_t m = VECTOR(*mlist)[b]; int k = igraph_vector_size(rho); igraph_vector_resize(&csizes, k); for (i = 0; i < k; i++) { VECTOR(csizes)[i] = round(VECTOR(*rho)[i] * m); } for (from = 0; from < k; from++) { int fromsize = VECTOR(csizes)[from]; int i, tooff = 0; for (i = 0; i < from; i++) { tooff += VECTOR(csizes)[i]; } for (to = from; to < k; to++) { int tosize = VECTOR(csizes)[to]; igraph_real_t prob = MATRIX(*C, from, to); igraph_real_t maxedges; igraph_real_t last = RNG_GEOM(prob); if (from != to) { maxedges = fromsize * tosize; while (last < maxedges) { int vto = floor(last / fromsize); int vfrom = last - (igraph_real_t)vto * fromsize; igraph_vector_push_back(&edges, offset + fromoff + vfrom); igraph_vector_push_back(&edges, offset + tooff + vto); last += RNG_GEOM(prob); last += 1; } } else { /* from==to */ maxedges = fromsize * (fromsize - 1) / 2.0; while (last < maxedges) { int vto = floor((sqrt(8 * last + 1) + 1) / 2); int vfrom = last - (((igraph_real_t)vto) * (vto - 1)) / 2; igraph_vector_push_back(&edges, offset + fromoff + vfrom); igraph_vector_push_back(&edges, offset + tooff + vto); last += RNG_GEOM(prob); last += 1; } } tooff += tosize; } fromoff += fromsize; } offset += m; } /* And now the rest, if not a special case */ if (p == 1) { int fromoff = 0, tooff = VECTOR(*mlist)[0]; for (b = 0; b < no_blocks; b++) { igraph_real_t fromsize = VECTOR(*mlist)[b]; igraph_real_t tosize = n - tooff; int from, to; for (from = 0; from < fromsize; from++) { for (to = 0; to < tosize; to++) { igraph_vector_push_back(&edges, fromoff + from); igraph_vector_push_back(&edges, tooff + to); } } fromoff += fromsize; if (b + 1 < no_blocks) { tooff += VECTOR(*mlist)[b + 1]; } } } else if (p > 0) { int fromoff = 0, tooff = VECTOR(*mlist)[0]; for (b = 0; b < no_blocks; b++) { igraph_real_t fromsize = VECTOR(*mlist)[b]; igraph_real_t tosize = n - tooff; igraph_real_t maxedges = fromsize * tosize; igraph_real_t last = RNG_GEOM(p); while (last < maxedges) { int vto = floor(last / fromsize); int vfrom = last - (igraph_real_t) vto * fromsize; igraph_vector_push_back(&edges, fromoff + vfrom); igraph_vector_push_back(&edges, tooff + vto); last += RNG_GEOM(p); last += 1; } fromoff += fromsize; if (b + 1 < no_blocks) { tooff += VECTOR(*mlist)[b + 1]; } } } RNG_END(); igraph_create(graph, &edges, n, /*directed=*/ 0); igraph_vector_destroy(&edges); igraph_vector_destroy(&csizes); IGRAPH_FINALLY_CLEAN(2); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/foreign-gml-header.h0000644000076500000240000000176413614300625025213 0ustar tamasstaff00000000000000/* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard street, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_gml_tree.h" typedef struct { void *scanner; int eof; char errmsg[300]; igraph_gml_tree_t *tree; } igraph_i_gml_parsedata_t; python-igraph-0.8.0/vendor/source/igraph/src/drl_graph.h0000644000076500000240000001134013614300625023510 0ustar tamasstaff00000000000000/* * Copyright 2007 Sandia Corporation. Under the terms of Contract * DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains * certain rights in this software. * * All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are * met: * * * Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * Neither the name of Sandia National Laboratories nor the names of * its contributors may be used to endorse or promote products derived from * this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT * OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED * TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF * LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING * NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. */ // The graph class contains the methods necessary to draw the // graph. It calls on the density server class to obtain // position and density information #include "DensityGrid.h" #include "igraph_layout.h" namespace drl { // layout schedule information struct layout_schedule { int iterations; float temperature; float attraction; float damping_mult; time_t time_elapsed; }; class graph { public: // Methods void init_parms ( int rand_seed, float edge_cut, float real_parm ); void init_parms ( const igraph_layout_drl_options_t *options ); void read_parms ( char *parms_file ); void read_real ( char *real_file ); int read_real ( const igraph_matrix_t *real_mat, const igraph_vector_bool_t *fixed); void scan_int ( char *filename ); void read_int ( char *file_name ); void draw_graph ( int int_out, char *coord_file ); int draw_graph (igraph_matrix_t *res); void write_coord ( const char *file_name ); void write_sim ( const char *file_name ); float get_tot_energy ( ); // Con/Decon graph( int proc_id, int tot_procs, char *int_file ); ~graph( ) { } graph( const igraph_t *igraph, const igraph_layout_drl_options_t *options, const igraph_vector_t *weights); private: // Methods int ReCompute ( ); void update_nodes ( ); float Compute_Node_Energy ( int node_ind ); void Solve_Analytic ( int node_ind, float &pos_x, float &pos_y ); void get_positions ( vector &node_indices, float return_positions[2 * MAX_PROCS] ); void update_density ( vector &node_indices, float old_positions[2 * MAX_PROCS], float new_positions[2 * MAX_PROCS] ); void update_node_pos ( int node_ind, float old_positions[2 * MAX_PROCS], float new_positions[2 * MAX_PROCS] ); // MPI information int myid, num_procs; // graph decomposition information int num_nodes; // number of nodes in graph float highest_sim; // highest sim for normalization map id_catalog; // id_catalog[file id] = internal id map > neighbors; // neighbors of nodes on this proc. // graph layout information vector positions; DensityGrid density_server; // original VxOrd information int STAGE, iterations; float temperature, attraction, damping_mult; float min_edges, CUT_END, cut_length_end, cut_off_length, cut_rate; bool first_add, fine_first_add, fineDensity; // scheduling variables layout_schedule liquid; layout_schedule expansion; layout_schedule cooldown; layout_schedule crunch; layout_schedule simmer; // timing statistics time_t start_time, stop_time; // online clustering information int real_iterations; // number of iterations to hold .real input fixed int tot_iterations; int tot_expected_iterations; // for progress bar bool real_fixed; }; } // namespace drl python-igraph-0.8.0/vendor/source/igraph/src/scg_optimal_method.c0000644000076500000240000001746013614300625025413 0ustar tamasstaff00000000000000/* * SCGlib : A C library for the spectral coarse graining of matrices * as described in the paper: Shrinking Matrices while preserving their * eigenpairs with Application to the Spectral Coarse Graining of Graphs. * Preprint available at * * Copyright (C) 2008 David Morton de Lachapelle * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 2 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA * 02110-1301 USA * * DESCRIPTION * ----------- * This file implements algorithm 5.8 of the above reference. * The optimal_partition function returns the minimizing partition * with size 'nt' of the objective function ||v-Pv||, where P is * a problem-specific projector. So far, Symmetric (matrix=1), * Laplacian (matrix=2) and Stochastic (matrix=3) projectors * have been implemented (the cost_matrix function below). * In the stochastic case, 'p' is expected to be a valid propability * vector. In all other cases, 'p' is ignored and can be set to NULL. * The group labels are given in 'gr' as positive consecutive integers * starting from 0. */ #include "igraph_error.h" #include "igraph_memory.h" #include "igraph_matrix.h" #include "igraph_vector.h" #include "scg_headers.h" int igraph_i_optimal_partition(const igraph_real_t *v, int *gr, int n, int nt, int matrix, const igraph_real_t *p, igraph_real_t *value) { int i, non_ties, q, j, l, part_ind, col; igraph_i_scg_indval_t *vs = igraph_Calloc(n, igraph_i_scg_indval_t); igraph_real_t *Cv, temp, sumOfSquares; igraph_vector_t ps; igraph_matrix_t F; igraph_matrix_int_t Q; /*----------------------------------------------- -----Sorts v and counts non-ties----------------- -----------------------------------------------*/ if (!vs) { IGRAPH_ERROR("SCG error", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, vs); for (i = 0; i < n; i++) { vs[i].val = v[i]; vs[i].ind = i; } qsort(vs, (size_t) n, sizeof(igraph_i_scg_indval_t), igraph_i_compare_ind_val); non_ties = 1; for (i = 1; i < n; i++) { if (vs[i].val < vs[i - 1].val - 1e-14 || vs[i].val > vs[i - 1].val + 1e-14) { non_ties++; } } if (nt >= non_ties) { IGRAPH_ERROR("`Invalid number of intervals, should be smaller than " "number of unique values in V", IGRAPH_EINVAL); } /*------------------------------------------------ ------Computes Cv, the matrix of costs------------ ------------------------------------------------*/ Cv = igraph_i_real_sym_matrix(n); if (!Cv) { IGRAPH_ERROR("SCG error", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, Cv); /* if stochastic SCG orders p */ if (matrix == 3) { IGRAPH_VECTOR_INIT_FINALLY(&ps, n); for (i = 0; i < n; i++) { VECTOR(ps)[i] = p[vs[i].ind]; } } IGRAPH_CHECK(igraph_i_cost_matrix(Cv, vs, n, matrix, &ps)); if (matrix == 3) { igraph_vector_destroy(&ps); IGRAPH_FINALLY_CLEAN(1); } /*------------------------------------------------- -------Fills up matrices F and Q------------------- -------------------------------------------------*/ /*here j also is a counter but the use of unsigned variables is to be proscribed in "for (unsigned int j=...;j>=0;j--)", for such loops never ends!*/ IGRAPH_MATRIX_INIT_FINALLY(&F, nt, n); IGRAPH_CHECK(igraph_matrix_int_init(&Q, nt, n)); IGRAPH_FINALLY(igraph_matrix_destroy, &Q); for (i = 0; i < n; i++) { MATRIX(Q, 0, i)++; } for (i = 0; i < nt; i++) { MATRIX(Q, i, i) = i + 1; } for (i = 0; i < n; i++) { MATRIX(F, 0, i) = igraph_i_real_sym_mat_get(Cv, 0, i); } for (i = 1; i < nt; i++) for (j = i + 1; j < n; j++) { MATRIX(F, i, j) = MATRIX(F, i - 1, i - 1) + igraph_i_real_sym_mat_get(Cv, i, j); MATRIX(Q, i, j) = 2; for (q = i - 1; q <= j - 1; q++) { temp = MATRIX(F, i - 1, q) + igraph_i_real_sym_mat_get(Cv, q + 1, j); if (temp < MATRIX(F, i, j)) { MATRIX(F, i, j) = temp; MATRIX(Q, i, j) = q + 2; } } } igraph_i_free_real_sym_matrix(Cv); IGRAPH_FINALLY_CLEAN(1); /*-------------------------------------------------- -------Back-tracks through Q to work out the groups- --------------------------------------------------*/ part_ind = nt; col = n - 1; for (j = nt - 1; j >= 0; j--) { for (i = MATRIX(Q, j, col) - 1; i <= col; i++) { gr[vs[i].ind] = part_ind - 1; } if (MATRIX(Q, j, col) != 2) { col = MATRIX(Q, j, col) - 2; part_ind -= 1; } else { if (j > 1) { for (l = 0; l <= (j - 1); l++) { gr[vs[l].ind] = l; } break; } else { col = MATRIX(Q, j, col) - 2; part_ind -= 1; } } } sumOfSquares = MATRIX(F, nt - 1, n - 1); igraph_matrix_destroy(&F); igraph_matrix_int_destroy(&Q); igraph_Free(vs); IGRAPH_FINALLY_CLEAN(3); if (value) { *value = sumOfSquares; } return 0; } int igraph_i_cost_matrix(igraph_real_t*Cv, const igraph_i_scg_indval_t *vs, int n, int matrix, const igraph_vector_t *ps) { /* if symmetric of Laplacian SCG -> same Cv */ if (matrix == 1 || matrix == 2) { int i, j; igraph_vector_t w, w2; IGRAPH_VECTOR_INIT_FINALLY(&w, n + 1); IGRAPH_VECTOR_INIT_FINALLY(&w2, n + 1); VECTOR(w)[1] = vs[0].val; VECTOR(w2)[1] = vs[0].val * vs[0].val; for (i = 2; i <= n; i++) { VECTOR(w)[i] = VECTOR(w)[i - 1] + vs[i - 1].val; VECTOR(w2)[i] = VECTOR(w2)[i - 1] + vs[i - 1].val * vs[i - 1].val; } for (i = 0; i < n; i++) { for (j = i + 1; j < n; j++) { igraph_real_t v = (VECTOR(w2)[j + 1] - VECTOR(w2)[i]) - (VECTOR(w)[j + 1] - VECTOR(w)[i]) * (VECTOR(w)[j + 1] - VECTOR(w)[i]) / (j - i + 1); igraph_i_real_sym_mat_set(Cv, i, j, v); } } igraph_vector_destroy(&w); igraph_vector_destroy(&w2); IGRAPH_FINALLY_CLEAN(2); } /* if stochastic */ /* TODO: optimize it to O(n^2) instead of O(n^3) (as above) */ if (matrix == 3) { int i, j, k; igraph_real_t t1, t2; for (i = 0; i < n; i++) { for (j = i + 1; j < n; j++) { t1 = t2 = 0; for (k = i; k < j; k++) { t1 += VECTOR(*ps)[k]; t2 += VECTOR(*ps)[k] * vs[k].val; } t1 = t2 / t1; t2 = 0; for (k = i; k < j; k++) { t2 += (vs[k].val - t1) * (vs[k].val - t1); } igraph_i_real_sym_mat_set(Cv, i, j, t2); } } } return 0; } python-igraph-0.8.0/vendor/source/igraph/src/community_leiden.c0000644000076500000240000013564713614300625025126 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_adjlist.h" #include "igraph_community.h" #include "igraph_dqueue.h" #include "igraph_interface.h" #include "igraph_interrupt_internal.h" #include "igraph_memory.h" #include "igraph_random.h" #include "igraph_stack.h" #include "igraph_constructors.h" /* Move nodes in order to improve the quality of a partition. * * This function considers each node and greedily moves it to a neighboring * community that maximizes the improvement in the quality of a partition. * * The nodes are examined in a queue, and initially all nodes are put in the * queue in a random order. Nodes are popped from the queue when they are * examined, and only neighbors of nodes that are moved (which are not part of * the cluster the node was moved to) are pushed to the queue again. * * The \c membership vector is used as the starting point to move around nodes, * and is updated in-place. * */ int igraph_i_community_leiden_fastmovenodes(const igraph_t *graph, const igraph_inclist_t *edges_per_node, const igraph_vector_t *edge_weights, const igraph_vector_t *node_weights, const igraph_real_t resolution_parameter, igraph_integer_t *nb_clusters, igraph_vector_t *membership) { igraph_dqueue_t unstable_nodes; igraph_real_t max_diff = 0.0, diff = 0.0; igraph_integer_t n = igraph_vcount(graph); igraph_vector_bool_t neighbor_cluster_added, node_is_stable; igraph_vector_t node_order, cluster_weights, edge_weights_per_cluster, neighbor_clusters; igraph_vector_int_t nb_nodes_per_cluster; igraph_stack_t empty_clusters; long int i, j, c, nb_neigh_clusters; /* Initialize queue of unstable nodes and whether node is stable. Only * unstable nodes are in the queue. */ IGRAPH_CHECK(igraph_vector_bool_init(&node_is_stable, n)); IGRAPH_FINALLY(igraph_vector_bool_destroy, &node_is_stable); IGRAPH_CHECK(igraph_dqueue_init(&unstable_nodes, n)); IGRAPH_FINALLY(igraph_dqueue_destroy, &unstable_nodes); /* Shuffle nodes */ IGRAPH_CHECK(igraph_vector_init_seq(&node_order, 0, n - 1)); IGRAPH_FINALLY(igraph_vector_destroy, &node_order); IGRAPH_CHECK(igraph_vector_shuffle(&node_order)); /* Add to the queue */ for (i = 0; i < n; i++) { igraph_dqueue_push(&unstable_nodes, (long int)VECTOR(node_order)[i]); } /* Initialize cluster weights and nb nodes */ IGRAPH_CHECK(igraph_vector_init(&cluster_weights, n)); IGRAPH_FINALLY(igraph_vector_destroy, &cluster_weights); IGRAPH_CHECK(igraph_vector_int_init(&nb_nodes_per_cluster, n)); IGRAPH_FINALLY(igraph_vector_int_destroy, &nb_nodes_per_cluster); for (i = 0; i < n; i++) { c = (long int)VECTOR(*membership)[i]; VECTOR(cluster_weights)[c] += VECTOR(*node_weights)[i]; VECTOR(nb_nodes_per_cluster)[c] += 1; } /* Initialize empty clusters */ IGRAPH_CHECK(igraph_stack_init(&empty_clusters, n)); IGRAPH_FINALLY(igraph_stack_destroy, &empty_clusters); for (c = 0; c < n; c++) if (VECTOR(nb_nodes_per_cluster)[c] == 0) { igraph_stack_push(&empty_clusters, c); } /* Initialize vectors to be used in calculating differences */ IGRAPH_CHECK(igraph_vector_init(&edge_weights_per_cluster, n)); IGRAPH_FINALLY(igraph_vector_destroy, &edge_weights_per_cluster); /* Initialize neighboring cluster */ IGRAPH_CHECK(igraph_vector_bool_init(&neighbor_cluster_added, n)); IGRAPH_FINALLY(igraph_vector_bool_destroy, &neighbor_cluster_added); IGRAPH_CHECK(igraph_vector_init(&neighbor_clusters, n)); IGRAPH_FINALLY(igraph_vector_destroy, &neighbor_clusters); /* Iterate while the queue is not empty */ j = 0; while (!igraph_dqueue_empty(&unstable_nodes)) { long int v = (long int)igraph_dqueue_pop(&unstable_nodes); long int best_cluster, current_cluster = VECTOR(*membership)[v]; long int degree, i; igraph_vector_int_t *edges; /* Remove node from current cluster */ VECTOR(cluster_weights)[current_cluster] -= VECTOR(*node_weights)[v]; VECTOR(nb_nodes_per_cluster)[current_cluster]--; if (VECTOR(nb_nodes_per_cluster)[current_cluster] == 0) { igraph_stack_push(&empty_clusters, current_cluster); } /* Find out neighboring clusters */ c = (long int)igraph_stack_top(&empty_clusters); VECTOR(neighbor_clusters)[0] = c; VECTOR(neighbor_cluster_added)[c] = 1; nb_neigh_clusters = 1; /* Determine the edge weight to each neighboring cluster */ edges = igraph_inclist_get(edges_per_node, v); degree = igraph_vector_int_size(edges); for (i = 0; i < degree; i++) { long int e = VECTOR(*edges)[i]; long int u = (long int)IGRAPH_OTHER(graph, e, v); c = VECTOR(*membership)[u]; if (!VECTOR(neighbor_cluster_added)[c]) { VECTOR(neighbor_cluster_added)[c] = 1; VECTOR(neighbor_clusters)[nb_neigh_clusters++] = c; } VECTOR(edge_weights_per_cluster)[c] += VECTOR(*edge_weights)[e]; } /* Calculate maximum diff */ best_cluster = current_cluster; max_diff = VECTOR(edge_weights_per_cluster)[current_cluster] - VECTOR(*node_weights)[v] * VECTOR(cluster_weights)[current_cluster] * resolution_parameter; for (i = 0; i < nb_neigh_clusters; i++) { c = VECTOR(neighbor_clusters)[i]; diff = VECTOR(edge_weights_per_cluster)[c] - VECTOR(*node_weights)[v] * VECTOR(cluster_weights)[c] * resolution_parameter; if (diff > max_diff) { best_cluster = c; max_diff = diff; } VECTOR(edge_weights_per_cluster)[c] = 0.0; VECTOR(neighbor_cluster_added)[c] = 0; } /* Move node to best cluster */ VECTOR(cluster_weights)[best_cluster] += VECTOR(*node_weights)[v]; VECTOR(nb_nodes_per_cluster)[best_cluster]++; if (best_cluster == igraph_stack_top(&empty_clusters)) { igraph_stack_pop(&empty_clusters); } /* Mark node as stable */ VECTOR(node_is_stable)[v] = 1; /* Add stable neighbours that are not part of the new cluster to the queue */ if (best_cluster != current_cluster) { VECTOR(*membership)[v] = best_cluster; for (i = 0; i < degree; i++) { long int e = VECTOR(*edges)[i]; long int u = (long int)IGRAPH_OTHER(graph, e, v); if (VECTOR(node_is_stable)[u] && VECTOR(*membership)[u] != best_cluster) { igraph_dqueue_push(&unstable_nodes, u); VECTOR(node_is_stable)[u] = 0; } } } j++; if (j > 10000) { IGRAPH_ALLOW_INTERRUPTION(); j = 0; } } IGRAPH_CHECK(igraph_reindex_membership(membership, NULL, nb_clusters)); igraph_vector_destroy(&neighbor_clusters); igraph_vector_bool_destroy(&neighbor_cluster_added); igraph_vector_destroy(&edge_weights_per_cluster); igraph_stack_destroy(&empty_clusters); igraph_vector_int_destroy(&nb_nodes_per_cluster); igraph_vector_destroy(&cluster_weights); igraph_vector_destroy(&node_order); igraph_dqueue_destroy(&unstable_nodes); igraph_vector_bool_destroy(&node_is_stable); IGRAPH_FINALLY_CLEAN(9); return IGRAPH_SUCCESS; } /* Clean a refined membership vector. * * This function examines all nodes in \c node_subset and updates \c * refined_membership to ensure that the clusters are numbered consecutively, * starting from \c nb_refined_clusters. The \c nb_refined_clusters is also * updated itself. If C is the initial \c nb_refined_clusters and C' the * resulting \c nb_refined_clusters, then nodes in \c node_subset are numbered * C, C + 1, ..., C' - 1. */ int igraph_i_community_leiden_clean_refined_membership(const igraph_vector_t* node_subset, igraph_vector_t *refined_membership, igraph_integer_t* nb_refined_clusters) { long int i, n = igraph_vector_size(node_subset); igraph_vector_t new_cluster; IGRAPH_CHECK(igraph_vector_init(&new_cluster, n)); IGRAPH_FINALLY(igraph_vector_destroy, &new_cluster); /* Clean clusters. We will store the new cluster + 1 so that cluster == 0 * indicates that no membership was assigned yet. */ *nb_refined_clusters += 1; for (i = 0; i < n; i++) { long int v = (long int)VECTOR(*node_subset)[i]; long int c = (long int)VECTOR(*refined_membership)[v]; if (VECTOR(new_cluster)[c] == 0) { VECTOR(new_cluster)[c] = (igraph_real_t)(*nb_refined_clusters); *nb_refined_clusters += 1; } } /* Assign new cluster */ for (i = 0; i < n; i++) { long int v = (long int)VECTOR(*node_subset)[i]; long int c = (long int)VECTOR(*refined_membership)[v]; VECTOR(*refined_membership)[v] = VECTOR(new_cluster)[c] - 1; } /* We used the cluster + 1, so correct */ *nb_refined_clusters -= 1; igraph_vector_destroy(&new_cluster); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } /* Merge nodes for a subset of the nodes. This is used to refine a partition. * * The nodes included in \c node_subset are assumed to be the nodes i for which * membership[i] = cluster_subset. * * All nodes in \c node_subset are initialized to a singleton partition in \c * refined_membership. Only singleton clusters can be merged if they are * sufficiently well connected to the current subgraph induced by \c * node_subset. * * We only examine each node once. Instead of greedily choosing the maximum * possible cluster to merge with, the cluster is chosen randomly among all * possibilities that do not decrease the quality of the partition. The * probability of choosing a certain cluster is proportional to exp(diff/beta). * For beta to 0 this converges to selecting a cluster with the maximum * improvement. For beta to infinity this converges to a uniform distribution * among all eligible clusters. * * The \c refined_membership is updated for node in \c node_subset. The number * of refined clusters, \c nb_refined_clusters is used to set the actual refined * cluster membership and is updated after this routine. Within each cluster * (i.e. for a given \c node_subset), the refined membership is initially simply * set to 0, ..., n - 1 (for n nodes in \c node_subset). However, for each \c * node_subset the refined membership should of course be unique. Hence, after * merging, the refined membership starts with \c nb_refined_clusters, which is * also updated to ensure that the resulting \c nb_refined_clusters counts all * refined clusters that have already been processed. See * igraph_i_community_leiden_clean_refined_membership for more information about * this aspect. */ int igraph_i_community_leiden_mergenodes(const igraph_t *graph, const igraph_inclist_t *edges_per_node, const igraph_vector_t *edge_weights, const igraph_vector_t *node_weights, const igraph_vector_t *node_subset, const igraph_vector_t *membership, const igraph_integer_t cluster_subset, const igraph_real_t resolution_parameter, const igraph_real_t beta, igraph_integer_t *nb_refined_clusters, igraph_vector_t *refined_membership) { igraph_vector_t node_order; igraph_vector_bool_t non_singleton_cluster, neighbor_cluster_added; igraph_real_t max_diff, total_cum_trans_diff, diff = 0.0, total_node_weight = 0.0; igraph_integer_t n = igraph_vector_size(node_subset); igraph_vector_t cluster_weights, cum_trans_diff, edge_weights_per_cluster, external_edge_weight_per_cluster_in_subset, neighbor_clusters; igraph_vector_int_t *edges, nb_nodes_per_cluster; long int i, j, degree, nb_neigh_clusters; /* Initialize cluster weights */ IGRAPH_CHECK(igraph_vector_init(&cluster_weights, n)); IGRAPH_FINALLY(igraph_vector_destroy, &cluster_weights); /* Initialize number of nodes per cluster */ IGRAPH_CHECK(igraph_vector_int_init(&nb_nodes_per_cluster, n)); IGRAPH_FINALLY(igraph_vector_int_destroy, &nb_nodes_per_cluster); /* Initialize external edge weight per cluster in subset */ IGRAPH_CHECK(igraph_vector_init(&external_edge_weight_per_cluster_in_subset, n)); IGRAPH_FINALLY(igraph_vector_destroy, &external_edge_weight_per_cluster_in_subset); /* Initialize administration for a singleton partition */ for (i = 0; i < n; i++) { long int v = (long int)VECTOR(*node_subset)[i]; VECTOR(*refined_membership)[v] = i; VECTOR(cluster_weights)[i] += VECTOR(*node_weights)[v]; VECTOR(nb_nodes_per_cluster)[i] += 1; total_node_weight += VECTOR(*node_weights)[v]; /* Find out neighboring clusters */ edges = igraph_inclist_get(edges_per_node, v); degree = igraph_vector_int_size(edges); for (j = 0; j < degree; j++) { long int e = VECTOR(*edges)[j]; long int u = (long int)IGRAPH_OTHER(graph, e, v); if (VECTOR(*membership)[u] == cluster_subset) { VECTOR(external_edge_weight_per_cluster_in_subset)[i] += VECTOR(*edge_weights)[e]; } } } /* Shuffle nodes */ IGRAPH_CHECK(igraph_vector_copy(&node_order, node_subset)); IGRAPH_FINALLY(igraph_vector_destroy, &node_order); IGRAPH_CHECK(igraph_vector_shuffle(&node_order)); /* Initialize non singleton clusters */ IGRAPH_CHECK(igraph_vector_bool_init(&non_singleton_cluster, n)); IGRAPH_FINALLY(igraph_vector_bool_destroy, &non_singleton_cluster); /* Initialize vectors to be used in calculating differences */ IGRAPH_CHECK(igraph_vector_init(&edge_weights_per_cluster, n)); IGRAPH_FINALLY(igraph_vector_destroy, &edge_weights_per_cluster); /* Initialize neighboring cluster */ IGRAPH_CHECK(igraph_vector_bool_init(&neighbor_cluster_added, n)); IGRAPH_FINALLY(igraph_vector_bool_destroy, &neighbor_cluster_added); IGRAPH_CHECK(igraph_vector_init(&neighbor_clusters, n)); IGRAPH_FINALLY(igraph_vector_destroy, &neighbor_clusters); /* Initialize cumulative transformed difference */ IGRAPH_CHECK(igraph_vector_init(&cum_trans_diff, n)); IGRAPH_FINALLY(igraph_vector_destroy, &cum_trans_diff); RNG_BEGIN(); for (i = 0; i < n; i++) { long int v = (long int)VECTOR(node_order)[i]; long int chosen_cluster, best_cluster, current_cluster = (long int)VECTOR(*refined_membership)[v]; if (!VECTOR(non_singleton_cluster)[current_cluster] && (VECTOR(external_edge_weight_per_cluster_in_subset)[current_cluster] >= VECTOR(cluster_weights)[current_cluster] * (total_node_weight - VECTOR(cluster_weights)[current_cluster]) * resolution_parameter)) { /* Remove node from current cluster, which is then a singleton by * definition. */ VECTOR(cluster_weights)[current_cluster] = 0.0; VECTOR(nb_nodes_per_cluster)[current_cluster] = 0; /* Find out neighboring clusters */ edges = igraph_inclist_get(edges_per_node, v); degree = igraph_vector_int_size(edges); /* Also add current cluster to ensure it can be chosen. */ VECTOR(neighbor_clusters)[0] = current_cluster; VECTOR(neighbor_cluster_added)[current_cluster] = 1; nb_neigh_clusters = 1; for (j = 0; j < degree; j++) { long int e = (long int)VECTOR(*edges)[j]; long int u = (long int)IGRAPH_OTHER(graph, e, v); if (VECTOR(*membership)[u] == cluster_subset) { long int c = VECTOR(*refined_membership)[u]; if (!VECTOR(neighbor_cluster_added)[c]) { VECTOR(neighbor_cluster_added)[c] = 1; VECTOR(neighbor_clusters)[nb_neigh_clusters++] = c; } VECTOR(edge_weights_per_cluster)[c] += VECTOR(*edge_weights)[e]; } } /* Calculate diffs */ best_cluster = current_cluster; max_diff = 0.0; total_cum_trans_diff = 0.0; for (j = 0; j < nb_neigh_clusters; j++) { long int c = (long int)VECTOR(neighbor_clusters)[j]; if (VECTOR(external_edge_weight_per_cluster_in_subset)[c] >= VECTOR(cluster_weights)[c] * (total_node_weight - VECTOR(cluster_weights)[c]) * resolution_parameter) { diff = VECTOR(edge_weights_per_cluster)[c] - VECTOR(*node_weights)[v] * VECTOR(cluster_weights)[c] * resolution_parameter; if (diff > max_diff) { best_cluster = c; max_diff = diff; } /* Calculate the transformed difference for sampling */ if (diff >= 0) { total_cum_trans_diff += exp(diff / beta); } } VECTOR(cum_trans_diff)[j] = total_cum_trans_diff; VECTOR(edge_weights_per_cluster)[c] = 0.0; VECTOR(neighbor_cluster_added)[c] = 0; } /* Determine the neighboring cluster to which the currently selected node * will be moved. */ if (total_cum_trans_diff < IGRAPH_INFINITY) { igraph_real_t r = igraph_rng_get_unif(igraph_rng_default(), 0, total_cum_trans_diff); long int chosen_idx; igraph_i_vector_binsearch_slice(&cum_trans_diff, r, &chosen_idx, 0, nb_neigh_clusters); chosen_cluster = VECTOR(neighbor_clusters)[chosen_idx]; } else { chosen_cluster = best_cluster; } /* Move node to randomly chosen cluster */ VECTOR(cluster_weights)[chosen_cluster] += VECTOR(*node_weights)[v]; VECTOR(nb_nodes_per_cluster)[chosen_cluster]++; for (j = 0; j < degree; j++) { long int e = (long int)VECTOR(*edges)[j]; long int u = (long int)IGRAPH_OTHER(graph, e, v); if (VECTOR(*membership)[u] == cluster_subset) { if (VECTOR(*refined_membership)[u] == chosen_cluster) { VECTOR(external_edge_weight_per_cluster_in_subset)[chosen_cluster] -= VECTOR(*edge_weights)[e]; } else { VECTOR(external_edge_weight_per_cluster_in_subset)[chosen_cluster] += VECTOR(*edge_weights)[e]; } } } /* Set cluster */ if (chosen_cluster != current_cluster) { VECTOR(*refined_membership)[v] = chosen_cluster; VECTOR(non_singleton_cluster)[chosen_cluster] = 1; } } /* end if singleton and may be merged */ } RNG_END(); IGRAPH_CHECK(igraph_i_community_leiden_clean_refined_membership(node_subset, refined_membership, nb_refined_clusters)); igraph_vector_destroy(&cum_trans_diff); igraph_vector_destroy(&neighbor_clusters); igraph_vector_bool_destroy(&neighbor_cluster_added); igraph_vector_destroy(&edge_weights_per_cluster); igraph_vector_bool_destroy(&non_singleton_cluster); igraph_vector_destroy(&node_order); igraph_vector_destroy(&external_edge_weight_per_cluster_in_subset); igraph_vector_int_destroy(&nb_nodes_per_cluster); igraph_vector_destroy(&cluster_weights); IGRAPH_FINALLY_CLEAN(9); return IGRAPH_SUCCESS; } /* Create clusters out of a membership vector. * * The cluster pointer vector should be initialized for all entries of the * membership vector, no range checking is performed. If a vector for a cluster * does not yet exist it will be created and initialized. If a vector for a * cluster already does exist it will not be emptied on first use. Hence, it * should be ensured that all clusters are always properly empty (or * non-existing) before calling this function. */ int igraph_i_community_get_clusters(const igraph_vector_t *membership, igraph_vector_ptr_t *clusters) { long int i, c, n = igraph_vector_size(membership); igraph_vector_t *cluster; for (i = 0; i < n; i++) { /* Get cluster for node i */ c = VECTOR(*membership)[i]; cluster = (igraph_vector_t*)VECTOR(*clusters)[c]; /* No cluster vector exists yet, so we create a new one */ if (!cluster) { cluster = igraph_Calloc(1, igraph_vector_t); if (cluster == 0) { IGRAPH_ERROR("Cannot allocate memory for assigning cluster", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_init(cluster, 0)); VECTOR(*clusters)[c] = cluster; } /* Add node i to cluster vector */ igraph_vector_push_back(cluster, i); } return IGRAPH_SUCCESS; } /* Aggregate the graph based on the \c refined membership while setting the * membership of each aggregated node according to the \c membership. * * Technically speaking we have that * aggregated_membership[refined_membership[v]] = membership[v] for each node v. * * The new aggregated graph is returned in \c aggregated_graph. This graph * object should not yet be initialized, `igraph_create` is called on it, and * responsibility for destroying the object lies with the calling method * * The remaining results, aggregated_edge_weights, aggregate_node_weights and * aggregated_membership are all expected to be initialized. * */ int igraph_i_community_leiden_aggregate( const igraph_t *graph, const igraph_inclist_t *edges_per_node, const igraph_vector_t *edge_weights, const igraph_vector_t *node_weights, const igraph_vector_t *membership, const igraph_vector_t *refined_membership, const igraph_integer_t nb_refined_clusters, igraph_t *aggregated_graph, igraph_vector_t *aggregated_edge_weights, igraph_vector_t *aggregated_node_weights, igraph_vector_t *aggregated_membership) { igraph_vector_t aggregated_edges, edge_weight_to_cluster; igraph_vector_ptr_t refined_clusters; igraph_vector_int_t *incident_edges; igraph_vector_t neighbor_clusters; igraph_vector_bool_t neighbor_cluster_added; long int i, j, c, degree, nb_neigh_clusters; /* Get refined clusters */ IGRAPH_CHECK(igraph_vector_ptr_init(&refined_clusters, nb_refined_clusters)); igraph_vector_ptr_set_item_destructor(&refined_clusters, igraph_vector_destroy); IGRAPH_FINALLY(igraph_vector_ptr_destroy_all, &refined_clusters); IGRAPH_CHECK(igraph_i_community_get_clusters(refined_membership, &refined_clusters)); /* Initialize new edges */ IGRAPH_CHECK(igraph_vector_init(&aggregated_edges, 0)); IGRAPH_FINALLY(igraph_vector_destroy, &aggregated_edges); /* We clear the aggregated edge weights, we will push each new edge weight */ igraph_vector_clear(aggregated_edge_weights); /* Simply resize the aggregated node weights and membership, they can be set * directly */ IGRAPH_CHECK(igraph_vector_resize(aggregated_node_weights, nb_refined_clusters)); IGRAPH_CHECK(igraph_vector_resize(aggregated_membership, nb_refined_clusters)); IGRAPH_CHECK(igraph_vector_init(&edge_weight_to_cluster, nb_refined_clusters)); IGRAPH_FINALLY(igraph_vector_destroy, &edge_weight_to_cluster); /* Initialize neighboring cluster */ IGRAPH_CHECK(igraph_vector_bool_init(&neighbor_cluster_added, nb_refined_clusters)); IGRAPH_FINALLY(igraph_vector_bool_destroy, &neighbor_cluster_added); IGRAPH_CHECK(igraph_vector_init(&neighbor_clusters, nb_refined_clusters)); IGRAPH_FINALLY(igraph_vector_destroy, &neighbor_clusters); /* Check per cluster */ for (c = 0; c < nb_refined_clusters; c++) { igraph_vector_t* refined_cluster = (igraph_vector_t*)VECTOR(refined_clusters)[c]; long int n_c = igraph_vector_size(refined_cluster); long int v = -1; /* Calculate the total edge weight to other clusters */ VECTOR(*aggregated_node_weights)[c] = 0.0; nb_neigh_clusters = 0; for (i = 0; i < n_c; i++) { v = (long int)VECTOR(*refined_cluster)[i]; incident_edges = igraph_inclist_get(edges_per_node, v); degree = igraph_vector_int_size(incident_edges); for (j = 0; j < degree; j++) { long int e = VECTOR(*incident_edges)[j]; long int u = (long int)IGRAPH_OTHER(graph, e, v); long int c2 = VECTOR(*refined_membership)[u]; if (c2 > c) { if (!VECTOR(neighbor_cluster_added)[c2]) { VECTOR(neighbor_cluster_added)[c2] = 1; VECTOR(neighbor_clusters)[nb_neigh_clusters++] = c2; } VECTOR(edge_weight_to_cluster)[c2] += VECTOR(*edge_weights)[e]; } } VECTOR(*aggregated_node_weights)[c] += VECTOR(*node_weights)[v]; } /* Add actual edges from this cluster to the other clusters */ for (i = 0; i < nb_neigh_clusters; i++) { long int c2 = VECTOR(neighbor_clusters)[i]; /* Add edge */ igraph_vector_push_back(&aggregated_edges, c); igraph_vector_push_back(&aggregated_edges, c2); /* Add edge weight */ igraph_vector_push_back(aggregated_edge_weights, VECTOR(edge_weight_to_cluster)[c2]); VECTOR(edge_weight_to_cluster)[c2] = 0.0; VECTOR(neighbor_cluster_added)[c2] = 0; } VECTOR(*aggregated_membership)[c] = VECTOR(*membership)[v]; } IGRAPH_CHECK(igraph_create(aggregated_graph, &aggregated_edges, nb_refined_clusters, IGRAPH_UNDIRECTED)); igraph_vector_destroy(&neighbor_clusters); igraph_vector_bool_destroy(&neighbor_cluster_added); igraph_vector_destroy(&edge_weight_to_cluster); igraph_vector_destroy(&aggregated_edges); igraph_vector_ptr_destroy_all(&refined_clusters); IGRAPH_FINALLY_CLEAN(5); return IGRAPH_SUCCESS; } /* Calculate the quality of the partition. * * The quality is defined as * * 1 / 2m sum_ij (A_ij - gamma n_i n_j)d(s_i, s_j) * * where m is the total edge weight, A_ij is the weight of edge (i, j), gamma is * the so-called resolution parameter, n_i is the node weight of node i, s_i is * the cluster of node i and d(x, y) = 1 if and only if x = y and 0 otherwise. * * Note that by setting n_i = k_i the degree of node i and dividing gamma by 2m, * we effectively optimize modularity. By setting n_i = 1 we optimize the * Constant Potts Model. * * This can be represented as a sum over clusters as * * 1 / 2m sum_c (e_c - gamma N_c^2) * * where e_c = sum_ij A_ij d(s_i, c)d(s_j, c) is (twice) the internal edge * weight in cluster c and N_c = sum_i n_i d(s_i, c) is the sum of the node * weights inside cluster c. This is how the quality is calculated in practice. * */ int igraph_i_community_leiden_quality(const igraph_t *graph, const igraph_vector_t *edge_weights, const igraph_vector_t *node_weights, const igraph_vector_t *membership, const igraph_integer_t nb_comms, const igraph_real_t resolution_parameter, igraph_real_t *quality) { igraph_vector_t cluster_weights; igraph_real_t total_edge_weight = 0.0; igraph_eit_t eit; long int i, c, n = igraph_vcount(graph);; *quality = 0.0; /* Create the edgelist */ IGRAPH_CHECK(igraph_eit_create(graph, igraph_ess_all(IGRAPH_EDGEORDER_ID), &eit)); IGRAPH_FINALLY(igraph_eit_destroy, &eit); i = 0; while (!IGRAPH_EIT_END(eit)) { igraph_integer_t e = IGRAPH_EIT_GET(eit), from, to; IGRAPH_CHECK(igraph_edge(graph, e, &from, &to)); total_edge_weight += VECTOR(*edge_weights)[e]; /* We add the internal edge weights */ if (VECTOR(*membership)[(long int) from] == VECTOR(*membership)[(long int) to]) { *quality += 2 * VECTOR(*edge_weights)[e]; } IGRAPH_EIT_NEXT(eit); } igraph_eit_destroy(&eit); IGRAPH_FINALLY_CLEAN(1); /* Initialize cluster weights and nb nodes */ IGRAPH_CHECK(igraph_vector_init(&cluster_weights, n)); IGRAPH_FINALLY(igraph_vector_destroy, &cluster_weights); for (i = 0; i < n; i++) { c = VECTOR(*membership)[i]; VECTOR(cluster_weights)[c] += VECTOR(*node_weights)[i]; } /* We subtract gamma * N_c^2 */ for (c = 0; c < nb_comms; c++) { *quality -= resolution_parameter * VECTOR(cluster_weights)[c] * VECTOR(cluster_weights)[c]; } igraph_vector_destroy(&cluster_weights); IGRAPH_FINALLY_CLEAN(1); /* We normalise by 2m */ *quality /= (2.0 * total_edge_weight); return IGRAPH_SUCCESS; } /* This is the core of the Leiden algorithm and relies on subroutines to * perform the three different phases: (1) local moving of nodes, (2) * refinement of the partition and (3) aggregation of the network based on the * refined partition, using the non-refined partition to create an initial * partition for the aggregate network. */ int igraph_i_community_leiden(const igraph_t *graph, const igraph_vector_t *edge_weights, const igraph_vector_t *node_weights, const igraph_real_t resolution_parameter, const igraph_real_t beta, igraph_vector_t *membership, igraph_integer_t *nb_clusters, igraph_real_t *quality) { igraph_integer_t nb_refined_clusters; long int i, c, n = igraph_vcount(graph); igraph_t *aggregated_graph, *tmp_graph; igraph_vector_t *aggregated_edge_weights, *aggregated_node_weights, *aggregated_membership; igraph_vector_t tmp_edge_weights, tmp_node_weights, tmp_membership; igraph_vector_t refined_membership; igraph_vector_int_t aggregate_node; igraph_vector_ptr_t clusters; igraph_inclist_t edges_per_node; igraph_bool_t continue_clustering; igraph_integer_t level = 0; /* Initialize temporary weights and membership to be used in aggregation */ IGRAPH_CHECK(igraph_vector_init(&tmp_edge_weights, 0)); IGRAPH_FINALLY(igraph_vector_destroy, &tmp_edge_weights); IGRAPH_CHECK(igraph_vector_init(&tmp_node_weights, 0)); IGRAPH_FINALLY(igraph_vector_destroy, &tmp_node_weights); IGRAPH_CHECK(igraph_vector_init(&tmp_membership, 0)); IGRAPH_FINALLY(igraph_vector_destroy, &tmp_membership); /* Initialize clusters */ IGRAPH_CHECK(igraph_vector_ptr_init(&clusters, n)); igraph_vector_ptr_set_item_destructor(&clusters, igraph_vector_destroy); IGRAPH_FINALLY(igraph_vector_ptr_destroy_all, &clusters); /* Initialize aggregate nodes, which initially is identical to simply the * nodes in the graph. */ IGRAPH_CHECK(igraph_vector_int_init(&aggregate_node, n)); IGRAPH_FINALLY(igraph_vector_int_destroy, &aggregate_node); for (i = 0; i < n; i++) { VECTOR(aggregate_node)[i] = i; } IGRAPH_CHECK(igraph_vector_init(&refined_membership, 0)); IGRAPH_FINALLY(igraph_vector_destroy, &refined_membership); /* Initialize aggregated graph, weights and membership. */ aggregated_graph = graph; aggregated_edge_weights = edge_weights; aggregated_node_weights = node_weights; aggregated_membership = membership; /* Clean membership and count number of *clusters */ IGRAPH_CHECK(igraph_reindex_membership(aggregated_membership, NULL, nb_clusters)); if (*nb_clusters > n) { IGRAPH_ERROR("Too many communities in membership vector", IGRAPH_EINVAL); } do { /* Get incidence list for fast iteration */ IGRAPH_CHECK(igraph_inclist_init(aggregated_graph, &edges_per_node, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_inclist_destroy, &edges_per_node); /* Move around the nodes in order to increase the quality */ IGRAPH_CHECK(igraph_i_community_leiden_fastmovenodes(aggregated_graph, &edges_per_node, aggregated_edge_weights, aggregated_node_weights, resolution_parameter, nb_clusters, aggregated_membership)); /* We only continue clustering if not all clusters are represented by a * single node yet */ continue_clustering = (*nb_clusters < igraph_vcount(aggregated_graph)); if (continue_clustering) { /* Set original membership */ if (level > 0) { for (i = 0; i < n; i++) { long int v_aggregate = VECTOR(aggregate_node)[i]; VECTOR(*membership)[i] = VECTOR(*aggregated_membership)[v_aggregate]; } } /* Get node sets for each cluster. */ IGRAPH_CHECK(igraph_i_community_get_clusters(aggregated_membership, &clusters)); /* Ensure refined membership is correct size */ IGRAPH_CHECK(igraph_vector_resize(&refined_membership, igraph_vcount(aggregated_graph))); /* Refine each cluster */ nb_refined_clusters = 0; for (c = 0; c < *nb_clusters; c++) { igraph_vector_t* cluster = (igraph_vector_t*)VECTOR(clusters)[c]; IGRAPH_CHECK(igraph_i_community_leiden_mergenodes(aggregated_graph, &edges_per_node, aggregated_edge_weights, aggregated_node_weights, cluster, aggregated_membership, c, resolution_parameter, beta, &nb_refined_clusters, &refined_membership)); /* Empty cluster */ igraph_vector_clear(cluster); } /* If refinement didn't aggregate anything, we aggregate on the basis of * the actual clustering */ if (nb_refined_clusters >= igraph_vcount(aggregated_graph)) { igraph_vector_update(&refined_membership, aggregated_membership); } /* Keep track of aggregate node. */ for (i = 0; i < n; i++) { /* Current aggregate node */ igraph_integer_t v_aggregate = VECTOR(aggregate_node)[i]; /* New aggregate node */ VECTOR(aggregate_node)[i] = (igraph_integer_t)VECTOR(refined_membership)[v_aggregate]; } /* Allocate temporary graph */ tmp_graph = igraph_Calloc(1, igraph_t); if (tmp_graph == 0) { IGRAPH_ERROR("Leiden algorithm failed, could not allocate memory for aggregate graph", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, tmp_graph); IGRAPH_CHECK(igraph_i_community_leiden_aggregate( aggregated_graph, &edges_per_node, aggregated_edge_weights, aggregated_node_weights, aggregated_membership, &refined_membership, nb_refined_clusters, tmp_graph, &tmp_edge_weights, &tmp_node_weights, &tmp_membership)); /* Graph has been created by aggregation, ensure it is properly destroyed if * an error occurs. */ IGRAPH_FINALLY(igraph_destroy, tmp_graph); if (level >= 1) { /* Destroy previously allocated graph (note that aggregated_graph points to * the previously allocated tmp_graph). */ igraph_destroy(aggregated_graph); igraph_Free(aggregated_graph); IGRAPH_FINALLY_CLEAN(2); } /* On the lowest level, the actual graph and node and edge weights and * membership are used. On higher levels, we will have to use a new graph * and node and edge weights to represent them. We perform the allocation * of memory here. We only allocate the memory once, and simply update * them in any subsequent rounds. */ if (level == 0) { aggregated_edge_weights = igraph_Calloc(1, igraph_vector_t); if (aggregated_edge_weights == 0) { IGRAPH_ERROR("Leiden algorithm failed, could not allocate memory for aggregate edge weights", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, aggregated_edge_weights); IGRAPH_CHECK(igraph_vector_init(aggregated_edge_weights, 0)); IGRAPH_FINALLY(igraph_vector_destroy, aggregated_edge_weights); aggregated_node_weights = igraph_Calloc(1, igraph_vector_t); if (aggregated_node_weights == 0) { IGRAPH_ERROR("Leiden algorithm failed, could not allocate memory for aggregate node weights", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, aggregated_node_weights); IGRAPH_CHECK(igraph_vector_init(aggregated_node_weights, 0)); IGRAPH_FINALLY(igraph_vector_destroy, aggregated_node_weights); aggregated_membership = igraph_Calloc(1, igraph_vector_t); if (aggregated_membership == 0) { IGRAPH_ERROR("Leiden algorithm failed, could not allocate memory for aggregate membership", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, aggregated_membership); IGRAPH_CHECK(igraph_vector_init(aggregated_membership, 0)); IGRAPH_FINALLY(igraph_vector_destroy, aggregated_membership); } /* Set the aggregated graph correctly */ aggregated_graph = tmp_graph; /* Update the aggregated administration. This does not allocate memory, * it will always fit in existing memory allocated previously. */ igraph_vector_update(aggregated_edge_weights, &tmp_edge_weights); igraph_vector_update(aggregated_node_weights, &tmp_node_weights); igraph_vector_update(aggregated_membership, &tmp_membership); level += 1; } /* We are done iterating, so we destroy the incidence list */ igraph_inclist_destroy(&edges_per_node); IGRAPH_FINALLY_CLEAN(1); } while (continue_clustering); /* If memory was allocated to represent the aggregated administration we need * to make sure it is properly freed. This is only done if we have at least * passed on to the next level of aggregation. */ if (level > 0) { igraph_destroy(aggregated_graph); igraph_Free(aggregated_graph); igraph_vector_destroy(aggregated_membership); igraph_Free(aggregated_membership); igraph_vector_destroy(aggregated_node_weights); igraph_Free(aggregated_node_weights); igraph_vector_destroy(aggregated_edge_weights); igraph_Free(aggregated_edge_weights); IGRAPH_FINALLY_CLEAN(8); } /* Free remaining memory */ igraph_vector_destroy(&refined_membership); igraph_vector_int_destroy(&aggregate_node); igraph_vector_ptr_destroy_all(&clusters); igraph_vector_destroy(&tmp_membership); igraph_vector_destroy(&tmp_node_weights); igraph_vector_destroy(&tmp_edge_weights); IGRAPH_FINALLY_CLEAN(6); /* Calculate quality */ if (quality) { igraph_i_community_leiden_quality(graph, edge_weights, node_weights, membership, *nb_clusters, resolution_parameter, quality); } return IGRAPH_SUCCESS; } /** * \ingroup communities * \function igraph_community_leiden * \brief Finding community structure using the Leiden algorithm. * * This function implements the Leiden algorithm for finding community * structure, see Traag, V. A., Waltman, L., & van Eck, N. J. (2019). From * Louvain to Leiden: guaranteeing well-connected communities. Scientific * reports, 9(1), 5233. http://dx.doi.org/10.1038/s41598-019-41695-z. * * * It is similar to the multilevel algorithm, often called the Louvain * algorithm, but it is faster and yields higher quality solutions. It can * optimize both modularity and the Constant Potts Model, which does not suffer * from the resolution-limit (see preprint http://arxiv.org/abs/1104.3083). * * * The Leiden algorithm consists of three phases: (1) local moving of nodes, * (2) refinement of the partition and (3) aggregation of the network based on * the refined partition, using the non-refined partition to create an initial * partition for the aggregate network. In the local move procedure in the * Leiden algorithm, only nodes whose neighborhood has changed are visited. The * refinement is done by restarting from a singleton partition within each * cluster and gradually merging the subclusters. When aggregating, a single * cluster may then be represented by several nodes (which are the subclusters * identified in the refinement). * * * The Leiden algorithm provides several guarantees. The Leiden algorithm is * typically iterated: the output of one iteration is used as the input for the * next iteration. At each iteration all clusters are guaranteed to be * connected and well-separated. After an iteration in which nothing has * changed, all nodes and some parts are guaranteed to be locally optimally * assigned. Finally, asymptotically, all subsets of all clusters are * guaranteed to be locally optimally assigned. For more details, please see * Traag, Waltman & van Eck (2019). * * * The objective function being optimized is * * * 1 / 2m sum_ij (A_ij - gamma n_i n_j)d(s_i, s_j) * * * where m is the total edge weight, A_ij is the weight of edge (i, j), gamma is * the so-called resolution parameter, n_i is the node weight of node i, s_i is * the cluster of node i and d(x, y) = 1 if and only if x = y and 0 otherwise. * By setting n_i = k_i, the degree of node i, and dividing gamma by 2m, you * effectively obtain an expression for modularity. Hence, the standard * modularity will be optimized when you supply the degrees as \c node_weights * and by supplying as a resolution parameter 1.0/(2*m), with m the number of * edges. * * \param graph The input graph. It must be an undirected graph. * \param edge_weights Numeric vector containing edge weights. If \c NULL, every edge * has equal weight of 1. The weights need not be non-negative. * \param node_weights Numeric vector containing node weights. * \param resolution_parameter The resolution parameter used, which is * represented by gamma in the objective function mentioned in the * documentation. * \param beta The randomness used in the refinement step when merging. A small * amount of randomness (\c beta = 0.01) typically works well. * \param start Start from membership vector. If this is true, the optimization * will start from the provided membership vector. If this is false, the * optimization will start from a singleton partition. * \param membership The membership vector. This is both used as the initial * membership from which optimisation starts and is updated in place. It * must hence be properly initialized. When finding clusters from scratch it * is typically started using a singleton clustering. This can be achieved * using \c igraph_vector_init_seq. * \param nb_clusters The number of clusters contained in \c membership. Must * not be a \c NULL pointer. * \param quality The quality of the partition, in terms of the objective * function as included in the documentation. If \c NULL the quality will * not be calculated. * \return Error code. * * Time complexity: near linear on sparse graphs. * * \example examples/simple/igraph_community_leiden.c */ int igraph_community_leiden(const igraph_t *graph, const igraph_vector_t *edge_weights, const igraph_vector_t *node_weights, const igraph_real_t resolution_parameter, const igraph_real_t beta, const igraph_bool_t start, igraph_vector_t *membership, igraph_integer_t *nb_clusters, igraph_real_t *quality) { igraph_vector_t *i_edge_weights, *i_node_weights; int ret; igraph_integer_t n = igraph_vcount(graph); if (start) { if (!membership) { IGRAPH_ERROR("Cannot start optimization if membership is missing", IGRAPH_EINVAL); } if (igraph_vector_size(membership) != n) { IGRAPH_ERROR("Initial membership length does not equal the number of vertices", IGRAPH_EINVAL); } } else { int i; if (!membership) IGRAPH_ERROR("Membership vector should be supplied and initialized, " "even when not starting optimization from it", IGRAPH_EINVAL); igraph_vector_resize(membership, n); for (i = 0; i < n; i++) { VECTOR(*membership)[i] = i; } } if (igraph_is_directed(graph)) { IGRAPH_ERROR("Leiden algorithm is only implemented for undirected graphs", IGRAPH_EINVAL); } /* Check edge weights to possibly use default */ if (!edge_weights) { i_edge_weights = igraph_Calloc(1, igraph_vector_t); if (i_edge_weights == 0) { IGRAPH_ERROR("Leiden algorithm failed, could not allocate memory for edge weights", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_init(i_edge_weights, igraph_ecount(graph))); IGRAPH_FINALLY(free, i_edge_weights); IGRAPH_FINALLY(igraph_vector_destroy, i_edge_weights); igraph_vector_fill(i_edge_weights, 1); } else { i_edge_weights = edge_weights; } /* Check edge weights to possibly use default */ if (!node_weights) { i_node_weights = igraph_Calloc(1, igraph_vector_t); if (i_node_weights == 0) { IGRAPH_ERROR("Leiden algorithm failed, could not allocate memory for node weights", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_init(i_node_weights, n)); IGRAPH_FINALLY(free, i_node_weights); IGRAPH_FINALLY(igraph_vector_destroy, i_node_weights); igraph_vector_fill(i_node_weights, 1); } else { i_node_weights = node_weights; } /* Perform actual Leiden algorithm */ ret = igraph_i_community_leiden(graph, i_edge_weights, i_node_weights, resolution_parameter, beta, membership, nb_clusters, quality); if (!edge_weights) { igraph_vector_destroy(i_edge_weights); igraph_Free(i_edge_weights); IGRAPH_FINALLY_CLEAN(2); } if (!node_weights) { igraph_vector_destroy(i_node_weights); igraph_Free(i_node_weights); IGRAPH_FINALLY_CLEAN(2); } return ret; } python-igraph-0.8.0/vendor/source/igraph/src/f2c/0000755000076500000240000000000013617375001022053 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/src/f2c/r_lg10.c0000644000076500000240000000042713524616145023312 0ustar tamasstaff00000000000000#include "f2c.h" #define log10e 0.43429448190325182765 #ifdef KR_headers double log(); double r_lg10(x) real *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double r_lg10(real *x) #endif { return( log10e * log(*x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/d_nint.c0000644000076500000240000000043113524616145023474 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double floor(); double d_nint(x) doublereal *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double d_nint(doublereal *x) #endif { return( (*x)>=0 ? floor(*x + .5) : -floor(.5 - *x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/r_atn2.c0000644000076500000240000000037513524616145023415 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double atan2(); double r_atn2(x,y) real *x, *y; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double r_atn2(real *x, real *y) #endif { return( atan2(*x,*y) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/fio.h0000644000076500000240000000557313524616145023017 0ustar tamasstaff00000000000000#ifndef SYSDEP_H_INCLUDED #include "sysdep1.h" #endif #include "stdio.h" #include "errno.h" #ifndef NULL /* ANSI C */ #include "stddef.h" #endif #ifndef SEEK_SET #define SEEK_SET 0 #define SEEK_CUR 1 #define SEEK_END 2 #endif #ifndef FOPEN #define FOPEN fopen #endif #ifndef FREOPEN #define FREOPEN freopen #endif #ifndef FSEEK #define FSEEK fseek #endif #ifndef FSTAT #define FSTAT fstat #endif #ifndef FTELL #define FTELL ftell #endif #ifndef OFF_T #define OFF_T long #endif #ifndef STAT_ST #define STAT_ST stat #endif #ifndef STAT #define STAT stat #endif #ifdef MSDOS #ifndef NON_UNIX_STDIO #define NON_UNIX_STDIO #endif #endif #ifdef UIOLEN_int typedef int uiolen; #else typedef long uiolen; #endif /*units*/ typedef struct { FILE *ufd; /*0=unconnected*/ char *ufnm; #ifndef MSDOS long uinode; int udev; #endif int url; /*0=sequential*/ flag useek; /*true=can backspace, use dir, ...*/ flag ufmt; flag urw; /* (1 for can read) | (2 for can write) */ flag ublnk; flag uend; flag uwrt; /*last io was write*/ flag uscrtch; } unit; #undef Void #ifdef KR_headers #define Void /*void*/ extern int (*f__getn)(); /* for formatted input */ extern void (*f__putn)(); /* for formatted output */ extern void x_putc(); extern long f__inode(); extern VOID sig_die(); extern int (*f__donewrec)(), t_putc(), x_wSL(); extern int c_sfe(), err__fl(), xrd_SL(), f__putbuf(); #else #define Void void #ifdef __cplusplus extern "C" { #endif extern int (*f__getn)(void); /* for formatted input */ extern void (*f__putn)(int); /* for formatted output */ extern void x_putc(int); extern long f__inode(char*,int*); extern void sig_die(const char*,int); extern void f__fatal(int, const char*); extern int t_runc(alist*); extern int f__nowreading(unit*), f__nowwriting(unit*); extern int fk_open(int,int,ftnint); extern int en_fio(void); extern void f_init(void); extern int (*f__donewrec)(void), t_putc(int), x_wSL(void); extern void b_char(const char*,char*,ftnlen), g_char(const char*,ftnlen,char*); extern int c_sfe(cilist*), z_rnew(void); extern int err__fl(int,int,const char*); extern int xrd_SL(void); extern int f__putbuf(int); #endif extern flag f__init; extern cilist *f__elist; /*active external io list*/ extern flag f__reading,f__external,f__sequential,f__formatted; extern int (*f__doend)(Void); extern FILE *f__cf; /*current file*/ extern unit *f__curunit; /*current unit*/ extern unit f__units[]; #define err(f,m,s) {if(f) errno= m; else f__fatal(m,s); return(m);} #define errfl(f,m,s) return err__fl((int)f,m,s) /*Table sizes*/ #define MXUNIT 100 extern int f__recpos; /*position in current record*/ extern OFF_T f__cursor; /* offset to move to */ extern OFF_T f__hiwater; /* so TL doesn't confuse us */ #ifdef __cplusplus } #endif #define WRITE 1 #define READ 2 #define SEQ 3 #define DIR 4 #define FMT 5 #define UNF 6 #define EXT 7 #define INT 8 #define buf_end(x) (x->_flag & _IONBF ? x->_ptr : x->_base + BUFSIZ) python-igraph-0.8.0/vendor/source/igraph/src/f2c/h_nint.c0000644000076500000240000000043113524616145023500 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double floor(); shortint h_nint(x) real *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif shortint h_nint(real *x) #endif { return (shortint)(*x >= 0 ? floor(*x + .5) : -floor(.5 - *x)); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/math.hvc0000644000076500000240000000006213524616145023510 0ustar tamasstaff00000000000000/* for VC 4.2 */ #include #undef complex python-igraph-0.8.0/vendor/source/igraph/src/f2c/h_mod.c0000644000076500000240000000031713524616145023312 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers shortint h_mod(a,b) short *a, *b; #else shortint h_mod(short *a, short *b) #endif { return( *a % *b); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/signal1.h00000644000076500000240000000151213524616145023645 0ustar tamasstaff00000000000000/* You may need to adjust the definition of signal1 to supply a */ /* cast to the correct argument type. This detail is system- and */ /* compiler-dependent. The #define below assumes signal.h declares */ /* type SIG_PF for the signal function's second argument. */ /* For some C++ compilers, "#define Sigarg_t ..." may be appropriate. */ #include #ifndef Sigret_t #define Sigret_t void #endif #ifndef Sigarg_t #ifdef KR_headers #define Sigarg_t #else #define Sigarg_t int #endif #endif /*Sigarg_t*/ #ifdef USE_SIG_PF /* compile with -DUSE_SIG_PF under IRIX */ #define sig_pf SIG_PF #else typedef Sigret_t (*sig_pf)(Sigarg_t); #endif #define signal1(a,b) signal(a,(sig_pf)b) #ifdef __cplusplus #define Sigarg ... #define Use_Sigarg #else #define Sigarg Int n #define Use_Sigarg n = n /* shut up compiler warning */ #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/i_indx.c0000644000076500000240000000065613524616145023504 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers integer i_indx(a, b, la, lb) char *a, *b; ftnlen la, lb; #else integer i_indx(char *a, char *b, ftnlen la, ftnlen lb) #endif { ftnlen i, n; char *s, *t, *bend; n = la - lb + 1; bend = b + lb; for(i = 0 ; i < n ; ++i) { s = a + i; t = b; while(t < bend) if(*s++ != *t++) goto no; return(i+1); no: ; } return(0); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/libf2c.lbc0000644000076500000240000000307213524616145023704 0ustar tamasstaff00000000000000abort_.obj backspac.obj c_abs.obj c_cos.obj c_div.obj c_exp.obj c_log.obj c_sin.obj c_sqrt.obj cabs.obj close.obj d_abs.obj d_acos.obj d_asin.obj d_atan.obj d_atn2.obj d_cnjg.obj d_cos.obj d_cosh.obj d_dim.obj d_exp.obj d_imag.obj d_int.obj d_lg10.obj d_log.obj d_mod.obj d_nint.obj d_prod.obj d_sign.obj d_sin.obj d_sinh.obj d_sqrt.obj d_tan.obj d_tanh.obj derf_.obj derfc_.obj dfe.obj dolio.obj dtime_.obj due.obj ef1asc_.obj ef1cmc_.obj endfile.obj erf_.obj erfc_.obj err.obj etime_.obj exit_.obj f77_aloc.obj f77vers.obj fmt.obj fmtlib.obj ftell_.obj getarg_.obj getenv_.obj h_abs.obj h_dim.obj h_dnnt.obj h_indx.obj h_len.obj h_mod.obj h_nint.obj h_sign.obj hl_ge.obj hl_gt.obj hl_le.obj hl_lt.obj i77vers.obj i_abs.obj i_dim.obj i_dnnt.obj i_indx.obj i_len.obj i_mod.obj i_nint.obj i_sign.obj iargc_.obj iio.obj ilnw.obj inquire.obj l_ge.obj l_gt.obj l_le.obj l_lt.obj lbitbits.obj lbitshft.obj lread.obj lwrite.obj main.obj open.obj pow_ci.obj pow_dd.obj pow_di.obj pow_hh.obj pow_ii.obj pow_ri.obj pow_zi.obj pow_zz.obj r_abs.obj r_acos.obj r_asin.obj r_atan.obj r_atn2.obj r_cnjg.obj r_cos.obj r_cosh.obj r_dim.obj r_exp.obj r_imag.obj r_int.obj r_lg10.obj r_log.obj r_mod.obj r_nint.obj r_sign.obj r_sin.obj r_sinh.obj r_sqrt.obj r_tan.obj r_tanh.obj rdfmt.obj rewind.obj rsfe.obj rsli.obj rsne.obj s_cat.obj s_cmp.obj s_copy.obj s_paus.obj s_rnge.obj s_stop.obj sfe.obj sig_die.obj signal_.obj sue.obj system_.obj typesize.obj uio.obj uninit.obj util.obj wref.obj wrtfmt.obj wsfe.obj wsle.obj wsne.obj xwsne.obj z_abs.obj z_cos.obj z_div.obj z_exp.obj z_log.obj z_sin.obj z_sqrt.obj python-igraph-0.8.0/vendor/source/igraph/src/f2c/r_dim.c0000644000076500000240000000032613524616145023316 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers double r_dim(a,b) real *a, *b; #else double r_dim(real *a, real *b) #endif { return( *a > *b ? *a - *b : 0); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/d_cosh.c0000644000076500000240000000036513524616145023466 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double cosh(); double d_cosh(x) doublereal *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double d_cosh(doublereal *x) #endif { return( cosh(*x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/i_dim.c0000644000076500000240000000034113524616145023302 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers integer i_dim(a,b) integer *a, *b; #else integer i_dim(integer *a, integer *b) #endif { return( *a > *b ? *a - *b : 0); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/d_tanh.c0000644000076500000240000000036513524616145023464 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double tanh(); double d_tanh(x) doublereal *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double d_tanh(doublereal *x) #endif { return( tanh(*x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/i_len.c0000644000076500000240000000031313524616145023306 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers integer i_len(s, n) char *s; ftnlen n; #else integer i_len(char *s, ftnlen n) #endif { return(n); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/system_.c0000644000076500000240000000121413524616145023704 0ustar tamasstaff00000000000000/* f77 interface to system routine */ #include "f2c.h" #ifdef KR_headers extern char *F77_aloc(); integer system_(s, n) register char *s; ftnlen n; #else #undef abs #undef min #undef max #include "stdlib.h" #ifdef __cplusplus extern "C" { #endif extern char *F77_aloc(ftnlen, const char*); integer system_(register char *s, ftnlen n) #endif { char buff0[256], *buff; register char *bp, *blast; integer rv; buff = bp = n < sizeof(buff0) ? buff0 : F77_aloc(n+1, "system_"); blast = bp + n; while(bp < blast && *s) *bp++ = *s++; *bp = 0; rv = system(buff); if (buff != buff0) free(buff); return rv; } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/d_prod.c0000644000076500000240000000031713524616145023473 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers double d_prod(x,y) real *x, *y; #else double d_prod(real *x, real *y) #endif { return( (*x) * (*y) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/erfc_.c0000644000076500000240000000042313524616145023300 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifndef REAL #define REAL double #endif #ifdef KR_headers double erfc(); REAL erfc_(x) real *x; #else extern double erfc(double); REAL erfc_(real *x) #endif { return( erfc((double)*x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/s_cat.c0000644000076500000240000000266213524616145023322 0ustar tamasstaff00000000000000/* Unless compiled with -DNO_OVERWRITE, this variant of s_cat allows the * target of a concatenation to appear on its right-hand side (contrary * to the Fortran 77 Standard, but in accordance with Fortran 90). */ #include "f2c.h" #ifndef NO_OVERWRITE #include "stdio.h" #undef abs #ifdef KR_headers extern char *F77_aloc(); extern void free(); extern void exit_(); #else #undef min #undef max #include "stdlib.h" extern #ifdef __cplusplus "C" #endif char *F77_aloc(ftnlen, const char*); #endif #include "string.h" #endif /* NO_OVERWRITE */ #ifdef __cplusplus extern "C" { #endif VOID #ifdef KR_headers s_cat(lp, rpp, rnp, np, ll) char *lp, *rpp[]; ftnint rnp[], *np; ftnlen ll; #else s_cat(char *lp, char *rpp[], ftnint rnp[], ftnint *np, ftnlen ll) #endif { ftnlen i, nc; char *rp; ftnlen n = *np; #ifndef NO_OVERWRITE ftnlen L, m; char *lp0, *lp1; lp0 = 0; lp1 = lp; L = ll; i = 0; while(i < n) { rp = rpp[i]; m = rnp[i++]; if (rp >= lp1 || rp + m <= lp) { if ((L -= m) <= 0) { n = i; break; } lp1 += m; continue; } lp0 = lp; lp = lp1 = F77_aloc(L = ll, "s_cat"); break; } lp1 = lp; #endif /* NO_OVERWRITE */ for(i = 0 ; i < n ; ++i) { nc = ll; if(rnp[i] < nc) nc = rnp[i]; ll -= nc; rp = rpp[i]; while(--nc >= 0) *lp++ = *rp++; } while(--ll >= 0) *lp++ = ' '; #ifndef NO_OVERWRITE if (lp0) { memcpy(lp0, lp1, L); free(lp1); } #endif } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/i_sign.c0000644000076500000240000000040413524616145023471 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers integer i_sign(a,b) integer *a, *b; #else integer i_sign(integer *a, integer *b) #endif { integer x; x = (*a >= 0 ? *a : - *a); return( *b >= 0 ? x : -x); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/r_log.c0000644000076500000240000000034513524616145023327 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double log(); double r_log(x) real *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double r_log(real *x) #endif { return( log(*x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/f2c.h00000644000076500000240000001237513524616145022772 0ustar tamasstaff00000000000000/* f2c.h -- Standard Fortran to C header file */ /** barf [ba:rf] 2. "He suggested using FORTRAN, and everybody barfed." - From The Shogakukan DICTIONARY OF NEW ENGLISH (Second edition) */ #ifndef F2C_INCLUDE #define F2C_INCLUDE #if defined(__alpha__) || defined(__sparc64__) || defined(__x86_64__) || defined(__ia64__) typedef int integer; typedef unsigned int uinteger; #else typedef long int integer; typedef unsigned long int uinteger; #endif typedef char *address; typedef short int shortint; typedef float real; typedef double doublereal; typedef struct { real r, i; } f2c_complex; typedef struct { doublereal r, i; } doublecomplex; #if defined(__alpha__) || defined(__sparc64__) || defined(__x86_64__) || defined(__ia64__) typedef int logical; #else typedef long int logical; #endif typedef short int shortlogical; typedef char logical1; typedef char integer1; #ifdef INTEGER_STAR_8 /* Adjust for integer*8. */ #if defined(__alpha__) || defined(__sparc64__) || defined(__x86_64__) || defined(__ia64__) typedef long longint; /* system-dependent */ typedef unsigned long ulongint; /* system-dependent */ #else typedef long long longint; /* system-dependent - oh yeah*/ typedef unsigned long long ulongint; /* system-dependent - oh yeah*/ #endif #define qbit_clear(a,b) ((a) & ~((ulongint)1 << (b))) #define qbit_set(a,b) ((a) | ((ulongint)1 << (b))) #endif #define TRUE_ (1) #define FALSE_ (0) /* Extern is for use with -E */ #ifndef Extern #define Extern extern #endif /* I/O stuff */ #ifdef f2c_i2 /* for -i2 */ typedef short flag; typedef short ftnlen; typedef short ftnint; #else #if defined(__alpha__) || defined(__sparc64__) || defined(__x86_64__) || defined(__ia64__) typedef int flag; typedef int ftnlen; typedef int ftnint; #else typedef long int flag; typedef long int ftnlen; typedef long int ftnint; #endif #endif /*external read, write*/ typedef struct { flag cierr; ftnint ciunit; flag ciend; char *cifmt; ftnint cirec; } cilist; /*internal read, write*/ typedef struct { flag icierr; char *iciunit; flag iciend; char *icifmt; ftnint icirlen; ftnint icirnum; } icilist; /*open*/ typedef struct { flag oerr; ftnint ounit; char *ofnm; ftnlen ofnmlen; char *osta; char *oacc; char *ofm; ftnint orl; char *oblnk; } olist; /*close*/ typedef struct { flag cerr; ftnint cunit; char *csta; } cllist; /*rewind, backspace, endfile*/ typedef struct { flag aerr; ftnint aunit; } alist; /* inquire */ typedef struct { flag inerr; ftnint inunit; char *infile; ftnlen infilen; ftnint *inex; /*parameters in standard's order*/ ftnint *inopen; ftnint *innum; ftnint *innamed; char *inname; ftnlen innamlen; char *inacc; ftnlen inacclen; char *inseq; ftnlen inseqlen; char *indir; ftnlen indirlen; char *infmt; ftnlen infmtlen; char *inform; ftnint informlen; char *inunf; ftnlen inunflen; ftnint *inrecl; ftnint *innrec; char *inblank; ftnlen inblanklen; } inlist; #define VOID void union Multitype { /* for multiple entry points */ integer1 g; shortint h; integer i; /* longint j; */ real r; doublereal d; complex c; doublecomplex z; }; typedef union Multitype Multitype; /*typedef long int Long;*/ /* No longer used; formerly in Namelist */ struct Vardesc { /* for Namelist */ char *name; char *addr; ftnlen *dims; int type; }; typedef struct Vardesc Vardesc; struct Namelist { char *name; Vardesc **vars; int nvars; }; typedef struct Namelist Namelist; #define abs(x) ((x) >= 0 ? (x) : -(x)) #define dabs(x) (doublereal)abs(x) #define min(a,b) ((a) <= (b) ? (a) : (b)) #define max(a,b) ((a) >= (b) ? (a) : (b)) #define dmin(a,b) (doublereal)min(a,b) #define dmax(a,b) (doublereal)max(a,b) #define bit_test(a,b) ((a) >> (b) & 1) #define bit_clear(a,b) ((a) & ~((uinteger)1 << (b))) #define bit_set(a,b) ((a) | ((uinteger)1 << (b))) /* procedure parameter types for -A and -C++ */ #define F2C_proc_par_types 1 #ifdef __cplusplus typedef int /* Unknown procedure type */ (*U_fp)(...); typedef shortint (*J_fp)(...); typedef integer (*I_fp)(...); typedef real (*R_fp)(...); typedef doublereal (*D_fp)(...), (*E_fp)(...); typedef /* Complex */ VOID (*C_fp)(...); typedef /* Double Complex */ VOID (*Z_fp)(...); typedef logical (*L_fp)(...); typedef shortlogical (*K_fp)(...); typedef /* Character */ VOID (*H_fp)(...); typedef /* Subroutine */ int (*S_fp)(...); #else typedef int /* Unknown procedure type */ (*U_fp)(); typedef shortint (*J_fp)(); typedef integer (*I_fp)(); typedef real (*R_fp)(); typedef doublereal (*D_fp)(), (*E_fp)(); typedef /* Complex */ VOID (*C_fp)(); typedef /* Double Complex */ VOID (*Z_fp)(); typedef logical (*L_fp)(); typedef shortlogical (*K_fp)(); typedef /* Character */ VOID (*H_fp)(); typedef /* Subroutine */ int (*S_fp)(); #endif /* E_fp is for real functions when -R is not specified */ typedef VOID C_f; /* complex function */ typedef VOID H_f; /* character function */ typedef VOID Z_f; /* double complex function */ typedef doublereal E_f; /* real function with -R not specified */ /* undef any lower-case symbols that your C compiler predefines, e.g.: */ #ifndef Skip_f2c_Undefs #undef cray #undef gcos #undef mc68010 #undef mc68020 #undef mips #undef pdp11 #undef sgi #undef sparc #undef sun #undef sun2 #undef sun3 #undef sun4 #undef u370 #undef u3b #undef u3b2 #undef u3b5 #undef unix #undef vax #endif #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/makefile.wat0000644000076500000240000000557013524616145024360 0ustar tamasstaff00000000000000# For making f2c.lib (here called watf2c.lib) with WATCOM C/C++ . # Invoke with "wmake -u -f makefile.wat" . # In the CFLAGS line below, "-bt=nt" is for NT and W9x. # With WATCOM, it is necessary to explicitly load main.obj . # To get signed zeros in write statements on IEEE-arithmetic systems, # add -DSIGNED_ZEROS to the CFLAGS assignment below and add signbit.obj # to the objects in the "w =" list below. CC = wcc386 CFLAGS = -fpd -DMSDOS -DUSE_CLOCK -DNO_ONEXIT -bt=nt -DNO_My_ctype .c.obj: $(CC) $(CFLAGS) $*.c w = \ abort_.obj \ backspac.obj \ c_abs.obj \ c_cos.obj \ c_div.obj \ c_exp.obj \ c_log.obj \ c_sin.obj \ c_sqrt.obj \ cabs.obj \ close.obj \ d_abs.obj \ d_acos.obj \ d_asin.obj \ d_atan.obj \ d_atn2.obj \ d_cnjg.obj \ d_cos.obj \ d_cosh.obj \ d_dim.obj \ d_exp.obj \ d_imag.obj \ d_int.obj \ d_lg10.obj \ d_log.obj \ d_mod.obj \ d_nint.obj \ d_prod.obj \ d_sign.obj \ d_sin.obj \ d_sinh.obj \ d_sqrt.obj \ d_tan.obj \ d_tanh.obj \ derf_.obj \ derfc_.obj \ dfe.obj \ dolio.obj \ dtime_.obj \ due.obj \ ef1asc_.obj \ ef1cmc_.obj \ endfile.obj \ erf_.obj \ erfc_.obj \ err.obj \ etime_.obj \ exit_.obj \ f77_aloc.obj \ f77vers.obj \ fmt.obj \ fmtlib.obj \ ftell_.obj \ getarg_.obj \ getenv_.obj \ h_abs.obj \ h_dim.obj \ h_dnnt.obj \ h_indx.obj \ h_len.obj \ h_mod.obj \ h_nint.obj \ h_sign.obj \ hl_ge.obj \ hl_gt.obj \ hl_le.obj \ hl_lt.obj \ i77vers.obj \ i_abs.obj \ i_dim.obj \ i_dnnt.obj \ i_indx.obj \ i_len.obj \ i_mod.obj \ i_nint.obj \ i_sign.obj \ iargc_.obj \ iio.obj \ ilnw.obj \ inquire.obj \ l_ge.obj \ l_gt.obj \ l_le.obj \ l_lt.obj \ lbitbits.obj \ lbitshft.obj \ lread.obj \ lwrite.obj \ main.obj \ open.obj \ pow_ci.obj \ pow_dd.obj \ pow_di.obj \ pow_hh.obj \ pow_ii.obj \ pow_ri.obj \ pow_zi.obj \ pow_zz.obj \ r_abs.obj \ r_acos.obj \ r_asin.obj \ r_atan.obj \ r_atn2.obj \ r_cnjg.obj \ r_cos.obj \ r_cosh.obj \ r_dim.obj \ r_exp.obj \ r_imag.obj \ r_int.obj \ r_lg10.obj \ r_log.obj \ r_mod.obj \ r_nint.obj \ r_sign.obj \ r_sin.obj \ r_sinh.obj \ r_sqrt.obj \ r_tan.obj \ r_tanh.obj \ rdfmt.obj \ rewind.obj \ rsfe.obj \ rsli.obj \ rsne.obj \ s_cat.obj \ s_cmp.obj \ s_copy.obj \ s_paus.obj \ s_rnge.obj \ s_stop.obj \ sfe.obj \ sig_die.obj \ signal_.obj \ sue.obj \ system_.obj \ typesize.obj \ uio.obj \ uninit.obj \ util.obj \ wref.obj \ wrtfmt.obj \ wsfe.obj \ wsle.obj \ wsne.obj \ xwsne.obj \ z_abs.obj \ z_cos.obj \ z_div.obj \ z_exp.obj \ z_log.obj \ z_sin.obj \ z_sqrt.obj watf2c.lib: f2c.h signal1.h sysdep1.h $w wlib -c watf2c.lib @libf2c f2c.h: f2c.h0 copy f2c.h0 f2c.h signal1.h: signal1.h0 copy signal1.h0 signal1.h sysdep1.h: sysdep1.h0 copy sysdep1.h0 sysdep1.h signbit.obj uninit.obj: arith.h arith.h: arithchk.c comptry.bat wcl386 -DNO_FPINIT arithchk.c arithchk >arith.h del arithchk.exe del arithchk.obj python-igraph-0.8.0/vendor/source/igraph/src/f2c/signal_.c0000644000076500000240000000045313524616145023641 0ustar tamasstaff00000000000000#include "f2c.h" #include "signal1.h" #ifdef __cplusplus extern "C" { #endif ftnint #ifdef KR_headers signal_(sigp, proc) integer *sigp; sig_pf proc; #else signal_(integer *sigp, sig_pf proc) #endif { int sig; sig = (int)*sigp; return (ftnint)signal(sig, proc); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/pow_hh.c0000644000076500000240000000075113524616145023512 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers shortint pow_hh(ap, bp) shortint *ap, *bp; #else shortint pow_hh(shortint *ap, shortint *bp) #endif { shortint pow, x, n; unsigned u; x = *ap; n = *bp; if (n <= 0) { if (n == 0 || x == 1) return 1; if (x != -1) return x == 0 ? 1/x : 0; n = -n; } u = n; for(pow = 1; ; ) { if(u & 01) pow *= x; if(u >>= 1) x *= x; else break; } return(pow); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/z_sqrt.c0000644000076500000240000000110513524616145023542 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double sqrt(), f__cabs(); VOID z_sqrt(r, z) doublecomplex *r, *z; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif extern double f__cabs(double, double); void z_sqrt(doublecomplex *r, doublecomplex *z) #endif { double mag, zi = z->i, zr = z->r; if( (mag = f__cabs(zr, zi)) == 0.) r->r = r->i = 0.; else if(zr > 0) { r->r = sqrt(0.5 * (mag + zr) ); r->i = zi / r->r / 2; } else { r->i = sqrt(0.5 * (mag - zr) ); if(zi < 0) r->i = - r->i; r->r = zi / r->i / 2; } } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/util.c0000644000076500000240000000171413524616145023203 0ustar tamasstaff00000000000000#include "sysdep1.h" /* here to get stat64 on some badly designed Linux systems */ #include "f2c.h" #include "fio.h" #ifdef __cplusplus extern "C" { #endif VOID #ifdef KR_headers #define Const /*nothing*/ g_char(a,alen,b) char *a,*b; ftnlen alen; #else #define Const const g_char(const char *a, ftnlen alen, char *b) #endif { Const char *x = a + alen; char *y = b + alen; for(;; y--) { if (x <= a) { *b = 0; return; } if (*--x != ' ') break; } *y-- = 0; do *y-- = *x; while(x-- > a); } VOID #ifdef KR_headers b_char(a,b,blen) char *a,*b; ftnlen blen; #else b_char(const char *a, char *b, ftnlen blen) #endif { int i; for(i=0;ir, z->i ) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/r_tanh.c0000644000076500000240000000035113524616145023475 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double tanh(); double r_tanh(x) real *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double r_tanh(real *x) #endif { return( tanh(*x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/c_abs.c0000644000076500000240000000043013524616145023267 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers extern double f__cabs(); double c_abs(z) f2c_complex *z; #else extern double f__cabs(double, double); double c_abs(f2c_complex *z) #endif { return( f__cabs( z->r, z->i ) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/pow_dd.c0000644000076500000240000000042413524616145023477 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double pow(); double pow_dd(ap, bp) doublereal *ap, *bp; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double pow_dd(doublereal *ap, doublereal *bp) #endif { return(pow(*ap, *bp) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/s_copy.c0000644000076500000240000000200013524616145023507 0ustar tamasstaff00000000000000/* Unless compiled with -DNO_OVERWRITE, this variant of s_copy allows the * target of an assignment to appear on its right-hand side (contrary * to the Fortran 77 Standard, but in accordance with Fortran 90), * as in a(2:5) = a(4:7) . */ #include "f2c.h" #ifdef __cplusplus extern "C" { #endif /* assign strings: a = b */ #ifdef KR_headers VOID s_copy(a, b, la, lb) register char *a, *b; ftnlen la, lb; #else void s_copy(register char *a, register char *b, ftnlen la, ftnlen lb) #endif { register char *aend, *bend; aend = a + la; if(la <= lb) #ifndef NO_OVERWRITE if (a <= b || a >= b + la) #endif while(a < aend) *a++ = *b++; #ifndef NO_OVERWRITE else for(b += la; a < aend; ) *--aend = *--b; #endif else { bend = b + lb; #ifndef NO_OVERWRITE if (a <= b || a >= bend) #endif while(b < bend) *a++ = *b++; #ifndef NO_OVERWRITE else { a += lb; while(b < bend) *--a = *--bend; a += lb; } #endif while(a < aend) *a++ = ' '; } } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/ctype.c0000644000076500000240000000005013524616145023342 0ustar tamasstaff00000000000000#define My_ctype_DEF #include "ctype.h" python-igraph-0.8.0/vendor/source/igraph/src/f2c/dtime_.c0000644000076500000240000000171413524616145023467 0ustar tamasstaff00000000000000#include "time.h" #ifdef MSDOS #undef USE_CLOCK #define USE_CLOCK #endif #ifndef REAL #define REAL double #endif #ifndef USE_CLOCK #define _INCLUDE_POSIX_SOURCE /* for HP-UX */ #define _INCLUDE_XOPEN_SOURCE /* for HP-UX */ #include "sys/types.h" #include "sys/times.h" #ifdef __cplusplus extern "C" { #endif #endif #undef Hz #ifdef CLK_TCK #define Hz CLK_TCK #else #ifdef HZ #define Hz HZ #else #define Hz 60 #endif #endif REAL #ifdef KR_headers dtime_(tarray) float *tarray; #else dtime_(float *tarray) #endif { #ifdef USE_CLOCK #ifndef CLOCKS_PER_SECOND #define CLOCKS_PER_SECOND Hz #endif static double t0; double t = clock(); tarray[1] = 0; tarray[0] = (t - t0) / CLOCKS_PER_SECOND; t0 = t; return tarray[0]; #else struct tms t; static struct tms t0; times(&t); tarray[0] = (double)(t.tms_utime - t0.tms_utime) / Hz; tarray[1] = (double)(t.tms_stime - t0.tms_stime) / Hz; t0 = t; return tarray[0] + tarray[1]; #endif } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/makefile.vc0000644000076500000240000000561213524616145024172 0ustar tamasstaff00000000000000# For making f2c.lib (here called vcf2c.lib) with Microsoft Visual C++ . # Invoke with "nmake -f makefile.vc" . # To get signed zeros in write statements on IEEE-arithmetic systems, # add -DSIGNED_ZEROS to the CFLAGS assignment below and add signbit.obj # to the objects in the "w =" list below. CC = cl CFLAGS = -DUSE_CLOCK -DMSDOS -DNO_ONEXIT -Ot1 -DNO_My_ctype -DNO_ISATTY .c.obj: $(CC) -c $(CFLAGS) $*.c w = \ abort_.obj \ backspac.obj \ c_abs.obj \ c_cos.obj \ c_div.obj \ c_exp.obj \ c_log.obj \ c_sin.obj \ c_sqrt.obj \ cabs.obj \ close.obj \ d_abs.obj \ d_acos.obj \ d_asin.obj \ d_atan.obj \ d_atn2.obj \ d_cnjg.obj \ d_cos.obj \ d_cosh.obj \ d_dim.obj \ d_exp.obj \ d_imag.obj \ d_int.obj \ d_lg10.obj \ d_log.obj \ d_mod.obj \ d_nint.obj \ d_prod.obj \ d_sign.obj \ d_sin.obj \ d_sinh.obj \ d_sqrt.obj \ d_tan.obj \ d_tanh.obj \ derf_.obj \ derfc_.obj \ dfe.obj \ dolio.obj \ dtime_.obj \ due.obj \ ef1asc_.obj \ ef1cmc_.obj \ endfile.obj \ erf_.obj \ erfc_.obj \ err.obj \ etime_.obj \ exit_.obj \ f77_aloc.obj \ f77vers.obj \ fmt.obj \ fmtlib.obj \ ftell_.obj \ getarg_.obj \ getenv_.obj \ h_abs.obj \ h_dim.obj \ h_dnnt.obj \ h_indx.obj \ h_len.obj \ h_mod.obj \ h_nint.obj \ h_sign.obj \ hl_ge.obj \ hl_gt.obj \ hl_le.obj \ hl_lt.obj \ i77vers.obj \ i_abs.obj \ i_dim.obj \ i_dnnt.obj \ i_indx.obj \ i_len.obj \ i_mod.obj \ i_nint.obj \ i_sign.obj \ iargc_.obj \ iio.obj \ ilnw.obj \ inquire.obj \ l_ge.obj \ l_gt.obj \ l_le.obj \ l_lt.obj \ lbitbits.obj \ lbitshft.obj \ lread.obj \ lwrite.obj \ main.obj \ open.obj \ pow_ci.obj \ pow_dd.obj \ pow_di.obj \ pow_hh.obj \ pow_ii.obj \ pow_ri.obj \ pow_zi.obj \ pow_zz.obj \ r_abs.obj \ r_acos.obj \ r_asin.obj \ r_atan.obj \ r_atn2.obj \ r_cnjg.obj \ r_cos.obj \ r_cosh.obj \ r_dim.obj \ r_exp.obj \ r_imag.obj \ r_int.obj \ r_lg10.obj \ r_log.obj \ r_mod.obj \ r_nint.obj \ r_sign.obj \ r_sin.obj \ r_sinh.obj \ r_sqrt.obj \ r_tan.obj \ r_tanh.obj \ rdfmt.obj \ rewind.obj \ rsfe.obj \ rsli.obj \ rsne.obj \ s_cat.obj \ s_cmp.obj \ s_copy.obj \ s_paus.obj \ s_rnge.obj \ s_stop.obj \ sfe.obj \ sig_die.obj \ signal_.obj \ sue.obj \ system_.obj \ typesize.obj \ uio.obj \ uninit.obj \ util.obj \ wref.obj \ wrtfmt.obj \ wsfe.obj \ wsle.obj \ wsne.obj \ xwsne.obj \ z_abs.obj \ z_cos.obj \ z_div.obj \ z_exp.obj \ z_log.obj \ z_sin.obj \ z_sqrt.obj all: f2c.h math.h signal1.h sysdep1.h vcf2c.lib f2c.h: f2c.h0 copy f2c.h0 f2c.h math.h: math.hvc copy math.hvc math.h signal1.h: signal1.h0 copy signal1.h0 signal1.h sysdep1.h: sysdep1.h0 copy sysdep1.h0 sysdep1.h vcf2c.lib: $w lib -out:vcf2c.lib @libf2c.lbc open.obj: open.c $(CC) -c $(CFLAGS) -DMSDOS open.c signbit.obj uninit.obj: arith.h arith.h: arithchk.c comptry.bat $(CC) $(CFLAGS) -DNO_FPINIT arithchk.c arithchk >arith.h del arithchk.exe del arithchk.obj python-igraph-0.8.0/vendor/source/igraph/src/f2c/r_nint.c0000644000076500000240000000041513524616145023514 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double floor(); double r_nint(x) real *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double r_nint(real *x) #endif { return( (*x)>=0 ? floor(*x + .5) : -floor(.5 - *x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/d_lg10.c0000644000076500000240000000044313524616145023272 0ustar tamasstaff00000000000000#include "f2c.h" #define log10e 0.43429448190325182765 #ifdef KR_headers double log(); double d_lg10(x) doublereal *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double d_lg10(doublereal *x) #endif { return( log10e * log(*x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/i77vers.c0000644000076500000240000004332013524616145023533 0ustar tamasstaff00000000000000 char _libi77_version_f2c[] = "\n@(#) LIBI77 VERSION (f2c) pjw,dmg-mods 20030321\n"; /* 2.01 $ format added 2.02 Coding bug in open.c repaired 2.03 fixed bugs in lread.c (read * with negative f-format) and lio.c and lio.h (e-format conforming to spec) 2.04 changed open.c and err.c (fopen and freopen respectively) to update to new c-library (append mode) 2.05 added namelist capability 2.06 allow internal list and namelist I/O */ /* close.c: allow upper-case STATUS= values endfile.c create fort.nnn if unit nnn not open; else if (file length == 0) use creat() rather than copy; use local copy() rather than forking /bin/cp; rewind, fseek to clear buffer (for no reading past EOF) err.c use neither setbuf nor setvbuf; make stderr buffered fio.h #define _bufend inquire.c upper case responses; omit byfile test from SEQUENTIAL= answer "YES" to DIRECT= for unopened file (open to debate) lio.c flush stderr, stdout at end of each stmt space before character strings in list output only at line start lio.h adjust LEW, LED consistent with old libI77 lread.c use atof() allow "nnn*," when reading complex constants open.c try opening for writing when open for read fails, with special uwrt value (2) delaying creat() to first write; set curunit so error messages don't drop core; no file name ==> fort.nnn except for STATUS='SCRATCH' rdfmt.c use atof(); trust EOF == end-of-file (so don't read past end-of-file after endfile stmt) sfe.c flush stderr, stdout at end of each stmt wrtfmt.c: use upper case put wrt_E and wrt_F into wref.c, use sprintf() rather than ecvt() and fcvt() [more accurate on VAX] */ /* 16 Oct. 1988: uwrt = 3 after write, rewind, so close won't zap the file. */ /* 10 July 1989: change _bufend to buf_end in fio.h, wsfe.c, wrtfmt.c */ /* 28 Nov. 1989: corrections for IEEE and Cray arithmetic */ /* 29 Nov. 1989: change various int return types to long for f2c */ /* 30 Nov. 1989: various types from f2c.h */ /* 6 Dec. 1989: types corrected various places */ /* 19 Dec. 1989: make iostat= work right for internal I/O */ /* 8 Jan. 1990: add rsne, wsne -- routines for handling NAMELIST */ /* 28 Jan. 1990: have NAMELIST read treat $ as &, general white space as blank */ /* 27 Mar. 1990: change an = to == in rd_L(rdfmt.c) so formatted reads of logical values reject letters other than fFtT; have nowwriting reset cf */ /* 14 Aug. 1990: adjust lread.c to treat tabs as spaces in list input */ /* 17 Aug. 1990: adjust open.c to recognize blank='Z...' as well as blank='z...' when reopening an open file */ /* 30 Aug. 1990: prevent embedded blanks in list output of complex values; omit exponent field in list output of values of magnitude between 10 and 1e8; prevent writing stdin and reading stdout or stderr; don't close stdin, stdout, or stderr when reopening units 5, 6, 0. */ /* 18 Sep. 1990: add component udev to unit and consider old == new file iff uinode and udev values agree; use stat rather than access to check existence of file (when STATUS='OLD')*/ /* 2 Oct. 1990: adjust rewind.c so two successive rewinds after a write don't clobber the file. */ /* 9 Oct. 1990: add #include "fcntl.h" to endfile.c, err.c, open.c; adjust g_char in util.c for segmented memories. */ /* 17 Oct. 1990: replace abort() and _cleanup() with calls on sig_die(...,1) (defined in main.c). */ /* 5 Nov. 1990: changes to open.c: complain if new= is specified and the file already exists; allow file= to be omitted in open stmts and allow status='replace' (Fortran 90 extensions). */ /* 11 Dec. 1990: adjustments for POSIX. */ /* 15 Jan. 1991: tweak i_ungetc in rsli.c to allow reading from strings in read-only memory. */ /* 25 Apr. 1991: adjust namelist stuff to work with f2c -i2 */ /* 26 Apr. 1991: fix some bugs with NAMELIST read of multi-dim. arrays */ /* 16 May 1991: increase LEFBL in lio.h to bypass NeXT bug */ /* 17 Oct. 1991: change type of length field in sequential unformatted records from int to long (for systems where sizeof(int) can vary, depending on the compiler or compiler options). */ /* 14 Nov. 1991: change uint to Uint in fmt.h, rdfmt.c, wrtfmt.c. */ /* 25 Nov. 1991: change uint to Uint in lwrite.c; change sizeof(int) to sizeof(uioint) in fseeks in sue.c (missed on 17 Oct.). */ /* 1 Dec. 1991: uio.c: add test for read failure (seq. unformatted reads); adjust an error return from EOF to off end of record */ /* 12 Dec. 1991: rsli.c: fix bug with internal list input that caused the last character of each record to be ignored. iio.c: adjust error message in internal formatted input from "end-of-file" to "off end of record" if the format specifies more characters than the record contains. */ /* 17 Jan. 1992: lread.c, rsne.c: in list and namelist input, treat "r* ," and "r*," alike (where r is a positive integer constant), and fix a bug in handling null values following items with repeat counts (e.g., 2*1,,3); for namelist reading of a numeric array, allow a new name-value subsequence to terminate the current one (as though the current one ended with the right number of null values). lio.h, lwrite.c: omit insignificant zeros in list and namelist output. To get the old behavior, compile with -DOld_list_output . */ /* 18 Jan. 1992: make list output consistent with F format by printing .1 rather than 0.1 (introduced yesterday). */ /* 3 Feb. 1992: rsne.c: fix namelist read bug that caused the character following a comma to be ignored. */ /* 19 May 1992: adjust iio.c, ilnw.c, rdfmt.c and rsli.c to make err= work with internal list and formatted I/O. */ /* 18 July 1992: adjust rsne.c to allow namelist input to stop at an & (e.g. &end). */ /* 23 July 1992: switch to ANSI prototypes unless KR_headers is #defined ; recognize Z format (assuming 8-bit bytes). */ /* 14 Aug. 1992: tweak wrt_E in wref.c to avoid -NaN */ /* 23 Oct. 1992: Supply missing l_eof = 0 assignment to s_rsne() in rsne.c (so end-of-file on other files won't confuse namelist reads of external files). Prepend f__ to external names that are only of internal interest to lib[FI]77. */ /* 1 Feb. 1993: backspace.c: fix bug that bit when last char of 2nd buffer == '\n'. endfile.c: guard against tiny L_tmpnam; close and reopen files in t_runc(). lio.h: lengthen LINTW (buffer size in lwrite.c). err.c, open.c: more prepending of f__ (to [rw]_mode). */ /* 5 Feb. 1993: tweaks to NAMELIST: rsne.c: ? prints the namelist being sought; namelists of the wrong name are skipped (after an error message; xwsne.c: namelist writes have a newline before each new variable. open.c: ACCESS='APPEND' positions sequential files at EOF (nonstandard extension -- that doesn't require changing data structures). */ /* 9 Feb. 1993: Change some #ifdef MSDOS lines to #ifdef NON_UNIX_STDIO. err.c: under NON_UNIX_STDIO, avoid close(creat(name,0666)) when the unit has another file descriptor for name. */ /* 4 March 1993: err.c, open.c: take declaration of fdopen from rawio.h; open.c: always give f__w_mode[] 4 elements for use in t_runc (in endfile.c -- for change of 1 Feb. 1993). */ /* 6 March 1993: uio.c: adjust off-end-of-record test for sequential unformatted reads to respond to err= rather than end=. */ /* 12 March 1993: various tweaks for C++ */ /* 6 April 1993: adjust error returns for formatted inputs to flush the current input line when err=label is specified. To restore the old behavior (input left mid-line), either adjust the #definition of errfl in fio.h or omit the invocation of f__doend in err__fl (in err.c). */ /* 23 June 1993: iio.c: fix bug in format reversions for internal writes. */ /* 5 Aug. 1993: lread.c: fix bug in handling repetition counts for logical data (during list or namelist input). Change struct f__syl to struct syl (for buggy compilers). */ /* 7 Aug. 1993: lread.c: fix bug in namelist reading of incomplete logical arrays. */ /* 9 Aug. 1993: lread.c: fix bug in namelist reading of an incomplete array of numeric data followed by another namelist item whose name starts with 'd', 'D', 'e', or 'E'. */ /* 8 Sept. 1993: open.c: protect #include "sys/..." with #ifndef NON_UNIX_STDIO; Version date not changed. */ /* 10 Nov. 1993: backspace.c: add nonsense for #ifdef MSDOS */ /* 8 Dec. 1993: iio.c: adjust internal formatted reads to treat short records as though padded with blanks (rather than causing an "off end of record" error). */ /* 22 Feb. 1994: lread.c: check that realloc did not return NULL. */ /* 6 June 1994: Under NON_UNIX_STDIO, use binary mode for direct formatted files (avoiding any confusion regarding \n). */ /* 5 July 1994: Fix bug (introduced 6 June 1994?) in reopening files under NON_UNIX_STDIO. */ /* 6 July 1994: wref.c: protect with #ifdef GOOD_SPRINTF_EXPONENT an optimization that requires exponents to have 2 digits when 2 digits suffice. lwrite.c wsfe.c (list and formatted external output): omit ' ' carriage-control when compiled with -DOMIT_BLANK_CC . Off-by-one bug fixed in character count for list output of character strings. Omit '.' in list-directed printing of Nan, Infinity. */ /* 12 July 1994: wrtfmt.c: under G11.4, write 0. as " .0000 " rather than " .0000E+00". */ /* 3 Aug. 1994: lwrite.c: do not insert a newline when appending an oversize item to an empty line. */ /* 12 Aug. 1994: rsli.c rsne.c: fix glitch (reset nml_read) that kept ERR= (in list- or format-directed input) from working after a NAMELIST READ. */ /* 7 Sept. 1994: typesize.c: adjust to allow types LOGICAL*1, LOGICAL*2, INTEGER*1, and (under -DAllow_TYQUAD) INTEGER*8 in NAMELISTs. */ /* 6 Oct. 1994: util.c: omit f__mvgbt, as it is never used. */ /* 2 Nov. 1994: add #ifdef ALWAYS_FLUSH logic. */ /* 26 Jan. 1995: wref.c: fix glitch in printing the exponent of 0 when GOOD_SPRINTF_EXPONENT is not #defined. */ /* 24 Feb. 1995: iio.c: z_getc: insert (unsigned char *) to allow internal reading of characters with high-bit set (on machines that sign-extend characters). */ /* 14 March 1995:lread.c and rsfe.c: adjust s_rsle and s_rsfe to check for end-of-file (to prevent infinite loops with empty read statements). */ /* 26 May 1995: iio.c: z_wnew: fix bug in handling T format items in internal writes whose last item is written to an earlier position than some previous item. */ /* 29 Aug. 1995: backspace.c: adjust MSDOS logic. */ /* 6 Sept. 1995: Adjust namelist input to treat a subscripted name whose subscripts do not involve colons similarly to the name without a subscript: accept several values, stored in successive elements starting at the indicated subscript. Adjust namelist output to quote character strings (avoiding confusion with arrays of character strings). Adjust f_init calls for people who don't use libF77's main(); now open and namelist read statements invoke f_init if needed. */ /* 7 Sept. 1995: Fix some bugs with -DAllow_TYQUAD (for integer*8). Add -DNo_Namelist_Comments lines to rsne.c. */ /* 5 Oct. 1995: wrtfmt.c: fix bug with t editing (f__cursor was not always zeroed in mv_cur). */ /* 11 Oct. 1995: move defs of f__hiwater, f__svic, f__icptr from wrtfmt.c to err.c */ /* 15 Mar. 1996: lread.c, rsfe.c: honor END= in READ stmt with empty iolist */ /* 13 May 1996: add ftell_.c and fseek_.c */ /* 9 June 1996: Adjust rsli.c and lread.c so internal list input with too few items in the input string will honor end= . */ /* 12 Sept. 1995:fmtlib.c: fix glitch in printing the most negative integer. */ /* 25 Sept. 1995:fmt.h: for formatted writes of negative integer*1 values, make ic signed on ANSI systems. If formatted writes of integer*1 values trouble you when using a K&R C compiler, switch to an ANSI compiler or use a compiler flag that makes characters signed. */ /* 9 Dec. 1996: d[fu]e.c, err.c: complain about non-positive rec= in direct read and write statements. ftell_.c: change param "unit" to "Unit" for -DKR_headers. */ /* 26 Feb. 1997: ftell_.c: on systems that define SEEK_SET, etc., use SEEK_SET, SEEK_CUR, SEEK_END for *whence = 0, 1, 2. */ /* 7 Apr. 1997: fmt.c: adjust to complain at missing numbers in formats (but still treat missing ".nnn" as ".0"). */ /* 11 Apr. 1997: err.c: attempt to make stderr line buffered rather than fully buffered. (Buffering is needed for format items T and TR.) */ /* 27 May 1997: ftell_.c: fix typo (that caused the third argument to be treated as 2 on some systems). */ /* 5 Aug. 1997: lread.c: adjust to accord with a change to the Fortran 8X draft (in 1990 or 1991) that rescinded permission to elide quote marks in namelist input of character data; compile with -DF8X_NML_ELIDE_QUOTES to get the old behavior. wrtfmt.o: wrt_G: tweak to print the right number of 0's for zero under G format. */ /* 16 Aug. 1997: iio.c: fix bug in internal writes to an array of character strings that sometimes caused one more array element than required by the format to be blank-filled. Example: format(1x). */ /* 16 Sept. 1997:fmt.[ch] rdfmt.c wrtfmt.c: tweak struct syl for machines with 64-bit pointers and 32-bit ints that did not 64-bit align struct syl (e.g., Linux on the DEC Alpha). */ /* 19 Jan. 1998: backspace.c: for b->ufmt==0, change sizeof(int) to sizeof(uiolen). On machines where this would make a difference, it is best for portability to compile libI77 with -DUIOLEN_int (which will render the change invisible). */ /* 4 March 1998: open.c: fix glitch in comparing file names under -DNON_UNIX_STDIO */ /* 17 March 1998: endfile.c, open.c: acquire temporary files from tmpfile(), unless compiled with -DNON_ANSI_STDIO, which uses mktemp(). New buffering scheme independent of NON_UNIX_STDIO for handling T format items. Now -DNON_UNIX_STDIO is no longer be necessary for Linux, and libf2c no longer causes stderr to be buffered -- the former setbuf or setvbuf call for stderr was to make T format items work. open.c: use the Posix access() function to check existence or nonexistence of files, except under -DNON_POSIX_STDIO, where trial fopen calls are used. */ /* 5 April 1998: wsfe.c: make $ format item work: this was lost in the changes of 17 March 1998. */ /* 28 May 1998: backspace.c dfe.c due.c iio.c lread.c rsfe.c sue.c wsfe.c: set f__curunit sooner so various error messages will correctly identify the I/O unit involved. */ /* 17 June 1998: lread.c: unless compiled with ALLOW_FLOAT_IN_INTEGER_LIST_INPUT #defined, treat floating-point numbers (containing either a decimal point or an exponent field) as errors when they appear as list input for integer data. */ /* 7 Sept. 1998: move e_wdfe from sfe.c to dfe.c, where it was originally. Why did it ever move to sfe.c? */ /* 2 May 1999: open.c: set f__external (to get "external" versus "internal" right in the error message if we cannot open the file). err.c: cast a pointer difference to (int) for %d. rdfmt.c: omit fixed-length buffer that could be overwritten by formats Inn or Lnn with nn > 83. */ /* 3 May 1999: open.c: insert two casts for machines with 64-bit longs. */ /* 18 June 1999: backspace.c: allow for b->ufd changing in t_runc */ /* 27 June 1999: rsne.c: fix bug in namelist input: a misplaced increment */ /* could cause wrong array elements to be assigned; e.g., */ /* "&input k(5)=10*1 &end" assigned k(5) and k(15..23) */ /* 15 Nov. 1999: endfile.c: set state to writing (b->uwrt = 1) when an */ /* endfile statement requires copying the file. */ /* (Otherwise an immediately following rewind statement */ /* could make the file appear empty.) Also, supply a */ /* missing (long) cast in the sprintf call. */ /* sfe.c: add #ifdef ALWAYS_FLUSH logic, for formatted I/O: */ /* Compiling libf2c with -DALWAYS_FLUSH should prevent losing */ /* any data in buffers should the program fault. It also */ /* makes the program run more slowly. */ /* 20 April 2000: rsne.c, xwsne.c: tweaks that only matter if ftnint and */ /* ftnlen are of different fundamental types (different numbers */ /* of bits). Since these files will not compile when this */ /* change matters, the above VERSION string remains unchanged. */ /* 4 July 2000: adjustments to permit compilation by C++ compilers; */ /* VERSION string remains unchanged. */ /* 5 Dec. 2000: lread.c: under namelist input, when reading a logical array, */ /* treat Tstuff= and Fstuff= as new assignments rather than as */ /* logical constants. */ /* 22 Feb. 2001: endfile.c: adjust to use truncate() unless compiled with */ /* -DNO_TRUNCATE (or with -DMSDOS). */ /* 1 March 2001: endfile.c: switch to ftruncate (absent -DNO_TRUNCATE), */ /* thus permitting truncation of scratch files on true Unix */ /* systems, where scratch files have no name. Add an fflush() */ /* (surprisingly) needed on some Linux systems. */ /* 11 Oct. 2001: backspac.c dfe.c due.c endfile.c err.c fio.h fmt.c fmt.h */ /* inquire.c open.c rdfmt.c sue.c util.c: change fseek and */ /* ftell to FSEEK and FTELL (#defined to be fseek and ftell, */ /* respectively, in fio.h unless otherwise #defined), and use */ /* type OFF_T (#defined to be long unless otherwise #defined) */ /* to permit handling files over 2GB long where possible, */ /* with suitable -D options, provided for some systems in new */ /* header file sysdep1.h (copied from sysdep1.h0 by default). */ /* 15 Nov. 2001: endfile.c: add FSEEK after FTRUNCATE. */ /* 28 Nov. 2001: fmt.h lwrite.c wref.c and (new) signbit.c: on IEEE systems, */ /* print -0 as -0 when compiled with -DSIGNED_ZEROS. See */ /* comments in makefile or (better) libf2c/makefile.* . */ /* 6 Sept. 2002: rsne.c: fix bug with multiple repeat counts in reading */ /* namelists, e.g., &nl a(2) = 3*1.0, 2*2.0, 3*3.0 / */ /* 21 March 2003: err.c: before writing to a file after reading from it, */ /* f_seek(file, 0, SEEK_CUR) to make writing legal in ANSI C. */ python-igraph-0.8.0/vendor/source/igraph/src/f2c/pow_ri.c0000644000076500000240000000066413524616145023530 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers double pow_ri(ap, bp) real *ap; integer *bp; #else double pow_ri(real *ap, integer *bp) #endif { double pow, x; integer n; unsigned long u; pow = 1; x = *ap; n = *bp; if(n != 0) { if(n < 0) { n = -n; x = 1/x; } for(u = n; ; ) { if(u & 01) pow *= x; if(u >>= 1) x *= x; else break; } } return(pow); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/f77_aloc.c0000644000076500000240000000125413524616145023626 0ustar tamasstaff00000000000000#include "f2c.h" #undef abs #undef min #undef max #include "stdio.h" static integer memfailure = 3; #ifdef KR_headers extern char *malloc(); extern void exit_(); char * F77_aloc(Len, whence) integer Len; char *whence; #else #include "stdlib.h" #ifdef __cplusplus extern "C" { #endif #ifdef __cplusplus extern "C" { #endif extern void exit_(integer*); #ifdef __cplusplus } #endif char * F77_aloc(integer Len, const char *whence) #endif { char *rv; unsigned int uLen = (unsigned int) Len; /* for K&R C */ if (!(rv = (char*)malloc(uLen))) { fprintf(stderr, "malloc(%u) failure in %s\n", uLen, whence); exit_(&memfailure); } return rv; } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/d_atn2.c0000644000076500000240000000041713524616145023374 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double atan2(); double d_atn2(x,y) doublereal *x, *y; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double d_atn2(doublereal *x, doublereal *y) #endif { return( atan2(*x,*y) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/rsfe.c0000644000076500000240000000272413524616145023167 0ustar tamasstaff00000000000000/* read sequential formatted external */ #include "f2c.h" #include "fio.h" #include "fmt.h" #ifdef __cplusplus extern "C" { #endif int xrd_SL(Void) { int ch; if(!f__curunit->uend) while((ch=getc(f__cf))!='\n') if (ch == EOF) { f__curunit->uend = 1; break; } f__cursor=f__recpos=0; return(1); } int x_getc(Void) { int ch; if(f__curunit->uend) return(EOF); ch = getc(f__cf); if(ch!=EOF && ch!='\n') { f__recpos++; return(ch); } if(ch=='\n') { (void) ungetc(ch,f__cf); return(ch); } if(f__curunit->uend || feof(f__cf)) { errno=0; f__curunit->uend=1; return(-1); } return(-1); } int x_endp(Void) { xrd_SL(); return f__curunit->uend == 1 ? EOF : 0; } int x_rev(Void) { (void) xrd_SL(); return(0); } #ifdef KR_headers integer s_rsfe(a) cilist *a; /* start */ #else integer s_rsfe(cilist *a) /* start */ #endif { int n; if(!f__init) f_init(); f__reading=1; f__sequential=1; f__formatted=1; f__external=1; if(n=c_sfe(a)) return(n); f__elist=a; f__cursor=f__recpos=0; f__scale=0; f__fmtbuf=a->cifmt; f__cf=f__curunit->ufd; if(pars_f(f__fmtbuf)<0) err(a->cierr,100,"startio"); f__getn= x_getc; f__doed= rd_ed; f__doned= rd_ned; fmt_bg(); f__doend=x_endp; f__donewrec=xrd_SL; f__dorevert=x_rev; f__cblank=f__curunit->ublnk; f__cplus=0; if(f__curunit->uwrt && f__nowreading(f__curunit)) err(a->cierr,errno,"read start"); if(f__curunit->uend) err(f__elist->ciend,(EOF),"read start"); return(0); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/r_sqrt.c0000644000076500000240000000035113524616145023534 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double sqrt(); double r_sqrt(x) real *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double r_sqrt(real *x) #endif { return( sqrt(*x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/r_exp.c0000644000076500000240000000034513524616145023342 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double exp(); double r_exp(x) real *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double r_exp(real *x) #endif { return( exp(*x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/r_cos.c0000644000076500000240000000034513524616145023332 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double cos(); double r_cos(x) real *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double r_cos(real *x) #endif { return( cos(*x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/makefile.u0000644000076500000240000001631313524616145024026 0ustar tamasstaff00000000000000# Unix makefile: see README. # For C++, first "make hadd". # If your compiler does not recognize ANSI C, add # -DKR_headers # to the CFLAGS = line below. # On Sun and other BSD systems that do not provide an ANSI sprintf, add # -DUSE_STRLEN # to the CFLAGS = line below. # On Linux systems, add # -DNON_UNIX_STDIO # to the CFLAGS = line below. For libf2c.so under Linux, also add # -fPIC # to the CFLAGS = line below. .SUFFIXES: .c .o CC = cc SHELL = /bin/sh CFLAGS = -O # compile, then strip unnecessary symbols .c.o: $(CC) -c -DSkip_f2c_Undefs $(CFLAGS) $*.c ld -r -x -o $*.xxx $*.o mv $*.xxx $*.o ## Under Solaris (and other systems that do not understand ld -x), ## omit -x in the ld line above. ## If your system does not have the ld command, comment out ## or remove both the ld and mv lines above. MISC = f77vers.o i77vers.o main.o s_rnge.o abort_.o exit_.o getarg_.o iargc_.o\ getenv_.o signal_.o s_stop.o s_paus.o system_.o cabs.o ctype.o\ derf_.o derfc_.o erf_.o erfc_.o sig_die.o uninit.o POW = pow_ci.o pow_dd.o pow_di.o pow_hh.o pow_ii.o pow_ri.o pow_zi.o pow_zz.o CX = c_abs.o c_cos.o c_div.o c_exp.o c_log.o c_sin.o c_sqrt.o DCX = z_abs.o z_cos.o z_div.o z_exp.o z_log.o z_sin.o z_sqrt.o REAL = r_abs.o r_acos.o r_asin.o r_atan.o r_atn2.o r_cnjg.o r_cos.o\ r_cosh.o r_dim.o r_exp.o r_imag.o r_int.o\ r_lg10.o r_log.o r_mod.o r_nint.o r_sign.o\ r_sin.o r_sinh.o r_sqrt.o r_tan.o r_tanh.o DBL = d_abs.o d_acos.o d_asin.o d_atan.o d_atn2.o\ d_cnjg.o d_cos.o d_cosh.o d_dim.o d_exp.o\ d_imag.o d_int.o d_lg10.o d_log.o d_mod.o\ d_nint.o d_prod.o d_sign.o d_sin.o d_sinh.o\ d_sqrt.o d_tan.o d_tanh.o INT = i_abs.o i_dim.o i_dnnt.o i_indx.o i_len.o i_mod.o i_nint.o i_sign.o\ lbitbits.o lbitshft.o HALF = h_abs.o h_dim.o h_dnnt.o h_indx.o h_len.o h_mod.o h_nint.o h_sign.o CMP = l_ge.o l_gt.o l_le.o l_lt.o hl_ge.o hl_gt.o hl_le.o hl_lt.o EFL = ef1asc_.o ef1cmc_.o CHAR = f77_aloc.o s_cat.o s_cmp.o s_copy.o I77 = backspac.o close.o dfe.o dolio.o due.o endfile.o err.o\ fmt.o fmtlib.o ftell_.o iio.o ilnw.o inquire.o lread.o lwrite.o\ open.o rdfmt.o rewind.o rsfe.o rsli.o rsne.o sfe.o sue.o\ typesize.o uio.o util.o wref.o wrtfmt.o wsfe.o wsle.o wsne.o xwsne.o QINT = pow_qq.o qbitbits.o qbitshft.o ftell64_.o TIME = dtime_.o etime_.o # If you get an error compiling dtime_.c or etime_.c, try adding # -DUSE_CLOCK to the CFLAGS assignment above; if that does not work, # omit $(TIME) from OFILES = assignment below. # To get signed zeros in write statements on IEEE-arithmetic systems, # add -DSIGNED_ZEROS to the CFLAGS assignment below and add signbit.o # to the end of the OFILES = assignment below. # For INTEGER*8 support (which requires system-dependent adjustments to # f2c.h), add $(QINT) to the OFILES = assignment below... OFILES = $(MISC) $(POW) $(CX) $(DCX) $(REAL) $(DBL) $(INT) \ $(HALF) $(CMP) $(EFL) $(CHAR) $(I77) $(TIME) all: f2c.h signal1.h sysdep1.h $(OFILES) libf2c.a: $(OFILES) ar r libf2c.a $? -ranlib libf2c.a ## Shared-library variant: the following rule works on Linux ## systems. Details are system-dependent. Under Linux, -fPIC ## must appear in the CFLAGS assignment when making libf2c.so. ## Under Solaris, use -Kpic in CFLAGS and use "ld -G" instead ## of "$(CC) -shared". ## For MacOSX 10.4 and 10.5 (and perhaps other versions >= 10.3), use ## "MACOSX_DEPLOYMENT_TARGET=10.3 libtool -dynamic -undefined dynamic_lookup -single_module" ## instead of "$(CC) -shared", and when running programs linked against libf2c.so, ## arrange for $DYLD_LIBRARY_PATH to include the directory containing libf2c.so. libf2c.so: $(OFILES) $(CC) -shared -o libf2c.so $(OFILES) ### If your system lacks ranlib, you don't need it; see README. f77vers.o: f77vers.c $(CC) -c f77vers.c i77vers.o: i77vers.c $(CC) -c i77vers.c # To get an "f2c.h" for use with "f2c -C++", first "make hadd" hadd: f2c.h0 f2ch.add cat f2c.h0 f2ch.add >f2c.h # For use with "f2c" and "f2c -A": f2c.h: f2c.h0 cp f2c.h0 f2c.h # You may need to adjust signal1.h and sysdep1.h suitably for your system... signal1.h: signal1.h0 cp signal1.h0 signal1.h sysdep1.h: sysdep1.h0 cp sysdep1.h0 sysdep1.h # If your system lacks onexit() and you are not using an # ANSI C compiler, then you should uncomment the following # two lines (for compiling main.o): #main.o: main.c # $(CC) -c -DNO_ONEXIT -DSkip_f2c_Undefs main.c # On at least some Sun systems, it is more appropriate to # uncomment the following two lines: #main.o: main.c # $(CC) -c -Donexit=on_exit -DSkip_f2c_Undefs main.c install: libf2c.a cp libf2c.a $(LIBDIR) -ranlib $(LIBDIR)/libf2c.a clean: rm -f *.o arith.h signal1.h sysdep1.h backspac.o: fio.h close.o: fio.h dfe.o: fio.h dfe.o: fmt.h due.o: fio.h endfile.o: fio.h rawio.h err.o: fio.h rawio.h fmt.o: fio.h fmt.o: fmt.h iio.o: fio.h iio.o: fmt.h ilnw.o: fio.h ilnw.o: lio.h inquire.o: fio.h lread.o: fio.h lread.o: fmt.h lread.o: lio.h lread.o: fp.h lwrite.o: fio.h lwrite.o: fmt.h lwrite.o: lio.h open.o: fio.h rawio.h rdfmt.o: fio.h rdfmt.o: fmt.h rdfmt.o: fp.h rewind.o: fio.h rsfe.o: fio.h rsfe.o: fmt.h rsli.o: fio.h rsli.o: lio.h rsne.o: fio.h rsne.o: lio.h sfe.o: fio.h signbit.o: arith.h sue.o: fio.h uio.o: fio.h uninit.o: arith.h util.o: fio.h wref.o: fio.h wref.o: fmt.h wref.o: fp.h wrtfmt.o: fio.h wrtfmt.o: fmt.h wsfe.o: fio.h wsfe.o: fmt.h wsle.o: fio.h wsle.o: fmt.h wsle.o: lio.h wsne.o: fio.h wsne.o: lio.h xwsne.o: fio.h xwsne.o: lio.h xwsne.o: fmt.h arith.h: arithchk.c $(CC) $(CFLAGS) -DNO_FPINIT arithchk.c -lm ||\ $(CC) -DNO_LONG_LONG $(CFLAGS) -DNO_FPINIT arithchk.c -lm ./a.out >arith.h rm -f a.out arithchk.o check: xsum Notice README abort_.c arithchk.c backspac.c c_abs.c c_cos.c \ c_div.c c_exp.c c_log.c c_sin.c c_sqrt.c cabs.c close.c comptry.bat \ ctype.c ctype.h \ d_abs.c d_acos.c d_asin.c d_atan.c d_atn2.c d_cnjg.c d_cos.c d_cosh.c \ d_dim.c d_exp.c d_imag.c d_int.c d_lg10.c d_log.c d_mod.c \ d_nint.c d_prod.c d_sign.c d_sin.c d_sinh.c d_sqrt.c d_tan.c \ d_tanh.c derf_.c derfc_.c dfe.c dolio.c dtime_.c due.c ef1asc_.c \ ef1cmc_.c endfile.c erf_.c erfc_.c err.c etime_.c exit_.c f2c.h0 \ f2ch.add f77_aloc.c f77vers.c fio.h fmt.c fmt.h fmtlib.c \ fp.h ftell_.c ftell64_.c \ getarg_.c getenv_.c h_abs.c h_dim.c h_dnnt.c h_indx.c h_len.c \ h_mod.c h_nint.c h_sign.c hl_ge.c hl_gt.c hl_le.c hl_lt.c \ i77vers.c i_abs.c i_dim.c i_dnnt.c i_indx.c i_len.c i_mod.c \ i_nint.c i_sign.c iargc_.c iio.c ilnw.c inquire.c l_ge.c l_gt.c \ l_le.c l_lt.c lbitbits.c lbitshft.c libf2c.lbc libf2c.sy lio.h \ lread.c lwrite.c main.c makefile.sy makefile.u makefile.vc \ makefile.wat math.hvc mkfile.plan9 open.c pow_ci.c pow_dd.c \ pow_di.c pow_hh.c pow_ii.c pow_qq.c pow_ri.c pow_zi.c pow_zz.c \ qbitbits.c qbitshft.c r_abs.c r_acos.c r_asin.c r_atan.c r_atn2.c \ r_cnjg.c r_cos.c r_cosh.c r_dim.c r_exp.c r_imag.c r_int.c r_lg10.c \ r_log.c r_mod.c r_nint.c r_sign.c r_sin.c r_sinh.c r_sqrt.c \ r_tan.c r_tanh.c rawio.h rdfmt.c rewind.c rsfe.c rsli.c rsne.c \ s_cat.c s_cmp.c s_copy.c s_paus.c s_rnge.c s_stop.c scomptry.bat sfe.c \ sig_die.c signal1.h0 signal_.c signbit.c sue.c sysdep1.h0 system_.c \ typesize.c \ uio.c uninit.c util.c wref.c wrtfmt.c wsfe.c wsle.c wsne.c xwsne.c \ z_abs.c z_cos.c z_div.c z_exp.c z_log.c z_sin.c z_sqrt.c >xsum1.out cmp xsum0.out xsum1.out && mv xsum1.out xsum.out || diff xsum[01].out python-igraph-0.8.0/vendor/source/igraph/src/f2c/d_abs.c0000644000076500000240000000033213524616145023271 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers double d_abs(x) doublereal *x; #else double d_abs(doublereal *x) #endif { if(*x >= 0) return(*x); return(- *x); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/pow_zz.c0000644000076500000240000000104513524616145023553 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double log(), exp(), cos(), sin(), atan2(), f__cabs(); VOID pow_zz(r,a,b) doublecomplex *r, *a, *b; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif extern double f__cabs(double,double); void pow_zz(doublecomplex *r, doublecomplex *a, doublecomplex *b) #endif { double logr, logi, x, y; logr = log( f__cabs(a->r, a->i) ); logi = atan2(a->i, a->r); x = exp( logr * b->r - logi * b->i ); y = logr * b->i + logi * b->r; r->r = x * cos(y); r->i = x * sin(y); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/h_dim.c0000644000076500000240000000034613524616145023306 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers shortint h_dim(a,b) shortint *a, *b; #else shortint h_dim(shortint *a, shortint *b) #endif { return( *a > *b ? *a - *b : 0); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/mkfile.plan90000644000076500000240000001206613524616145024300 0ustar tamasstaff00000000000000# Plan 9 mkfile for libf2c.a$O f2c.h # For use with "f2c" and "f2c -A": f2c.h: f2c.h0 cp f2c.h0 f2c.h # You may need to adjust signal1.h suitably for your system... signal1.h: signal1.h0 cp signal1.h0 signal1.h clean: rm -f libf2c.a$O *.$O arith.h backspac.$O: fio.h close.$O: fio.h dfe.$O: fio.h dfe.$O: fmt.h due.$O: fio.h endfile.$O: fio.h rawio.h err.$O: fio.h rawio.h fmt.$O: fio.h fmt.$O: fmt.h iio.$O: fio.h iio.$O: fmt.h ilnw.$O: fio.h ilnw.$O: lio.h inquire.$O: fio.h lread.$O: fio.h lread.$O: fmt.h lread.$O: lio.h lread.$O: fp.h lwrite.$O: fio.h lwrite.$O: fmt.h lwrite.$O: lio.h open.$O: fio.h rawio.h rdfmt.$O: fio.h rdfmt.$O: fmt.h rdfmt.$O: fp.h rewind.$O: fio.h rsfe.$O: fio.h rsfe.$O: fmt.h rsli.$O: fio.h rsli.$O: lio.h rsne.$O: fio.h rsne.$O: lio.h sfe.$O: fio.h sue.$O: fio.h uio.$O: fio.h uninit.$O: arith.h util.$O: fio.h wref.$O: fio.h wref.$O: fmt.h wref.$O: fp.h wrtfmt.$O: fio.h wrtfmt.$O: fmt.h wsfe.$O: fio.h wsfe.$O: fmt.h wsle.$O: fio.h wsle.$O: fmt.h wsle.$O: lio.h wsne.$O: fio.h wsne.$O: lio.h xwsne.$O: fio.h xwsne.$O: lio.h xwsne.$O: fmt.h arith.h: arithchk.c pcc -DNO_FPINIT -o arithchk arithchk.c arithchk >$target rm arithchk xsum.out:V: check check: xsum Notice README abort_.c arithchk.c backspac.c c_abs.c c_cos.c \ c_div.c c_exp.c c_log.c c_sin.c c_sqrt.c cabs.c close.c comptry.bat \ d_abs.c d_acos.c d_asin.c d_atan.c d_atn2.c d_cnjg.c d_cos.c d_cosh.c \ d_dim.c d_exp.c d_imag.c d_int.c d_lg10.c d_log.c d_mod.c \ d_nint.c d_prod.c d_sign.c d_sin.c d_sinh.c d_sqrt.c d_tan.c \ d_tanh.c derf_.c derfc_.c dfe.c dolio.c dtime_.c due.c ef1asc_.c \ ef1cmc_.c endfile.c erf_.c erfc_.c err.c etime_.c exit_.c f2c.h0 \ f2ch.add f77_aloc.c f77vers.c fio.h fmt.c fmt.h fmtlib.c \ fp.h ftell_.c \ getarg_.c getenv_.c h_abs.c h_dim.c h_dnnt.c h_indx.c h_len.c \ h_mod.c h_nint.c h_sign.c hl_ge.c hl_gt.c hl_le.c hl_lt.c \ i77vers.c i_abs.c i_dim.c i_dnnt.c i_indx.c i_len.c i_mod.c \ i_nint.c i_sign.c iargc_.c iio.c ilnw.c inquire.c l_ge.c l_gt.c \ l_le.c l_lt.c lbitbits.c lbitshft.c libf2c.lbc libf2c.sy lio.h \ lread.c lwrite.c main.c makefile.sy makefile.u makefile.vc \ makefile.wat math.hvc mkfile.plan9 open.c pow_ci.c pow_dd.c \ pow_di.c pow_hh.c pow_ii.c pow_qq.c pow_ri.c pow_zi.c pow_zz.c \ qbitbits.c qbitshft.c r_abs.c r_acos.c r_asin.c r_atan.c r_atn2.c \ r_cnjg.c r_cos.c r_cosh.c r_dim.c r_exp.c r_imag.c r_int.c r_lg10.c \ r_log.c r_mod.c r_nint.c r_sign.c r_sin.c r_sinh.c r_sqrt.c \ r_tan.c r_tanh.c rawio.h rdfmt.c rewind.c rsfe.c rsli.c rsne.c \ s_cat.c s_cmp.c s_copy.c s_paus.c s_rnge.c s_stop.c sfe.c \ sig_die.c signal1.h0 signal_.c sue.c system_.c typesize.c uio.c \ uninit.c util.c wref.c wrtfmt.c wsfe.c wsle.c wsne.c xwsne.c \ z_abs.c z_cos.c z_div.c z_exp.c z_log.c z_sin.c z_sqrt.c >xsum1.out cmp xsum0.out xsum1.out && mv xsum1.out xsum.out || diff xsum[01].out python-igraph-0.8.0/vendor/source/igraph/src/f2c/h_len.c0000644000076500000240000000031513524616145023307 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers shortint h_len(s, n) char *s; ftnlen n; #else shortint h_len(char *s, ftnlen n) #endif { return(n); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/wref.c0000644000076500000240000001121313524616145023164 0ustar tamasstaff00000000000000#include "f2c.h" #include "fio.h" #ifndef KR_headers #undef abs #undef min #undef max #include "stdlib.h" #include "string.h" #endif #include "fmt.h" #include "fp.h" #ifndef VAX #include "ctype.h" #ifdef __cplusplus extern "C" { #endif #endif int #ifdef KR_headers wrt_E(p,w,d,e,len) ufloat *p; ftnlen len; #else wrt_E(ufloat *p, int w, int d, int e, ftnlen len) #endif { char buf[FMAX+EXPMAXDIGS+4], *s, *se; int d1, delta, e1, i, sign, signspace; double dd; #ifdef WANT_LEAD_0 int insert0 = 0; #endif #ifndef VAX int e0 = e; #endif if(e <= 0) e = 2; if(f__scale) { if(f__scale >= d + 2 || f__scale <= -d) goto nogood; } if(f__scale <= 0) --d; if (len == sizeof(real)) dd = p->pf; else dd = p->pd; if (dd < 0.) { signspace = sign = 1; dd = -dd; } else { sign = 0; signspace = (int)f__cplus; #ifndef VAX if (!dd) { #ifdef SIGNED_ZEROS if (signbit_f2c(&dd)) signspace = sign = 1; #endif dd = 0.; /* avoid -0 */ } #endif } delta = w - (2 /* for the . and the d adjustment above */ + 2 /* for the E+ */ + signspace + d + e); #ifdef WANT_LEAD_0 if (f__scale <= 0 && delta > 0) { delta--; insert0 = 1; } else #endif if (delta < 0) { nogood: while(--w >= 0) PUT('*'); return(0); } if (f__scale < 0) d += f__scale; if (d > FMAX) { d1 = d - FMAX; d = FMAX; } else d1 = 0; sprintf(buf,"%#.*E", d, dd); #ifndef VAX /* check for NaN, Infinity */ if (!isdigit(buf[0])) { switch(buf[0]) { case 'n': case 'N': signspace = 0; /* no sign for NaNs */ } delta = w - strlen(buf) - signspace; if (delta < 0) goto nogood; while(--delta >= 0) PUT(' '); if (signspace) PUT(sign ? '-' : '+'); for(s = buf; *s; s++) PUT(*s); return 0; } #endif se = buf + d + 3; #ifdef GOOD_SPRINTF_EXPONENT /* When possible, exponent has 2 digits. */ if (f__scale != 1 && dd) sprintf(se, "%+.2d", atoi(se) + 1 - f__scale); #else if (dd) sprintf(se, "%+.2d", atoi(se) + 1 - f__scale); else strcpy(se, "+00"); #endif s = ++se; if (e < 2) { if (*s != '0') goto nogood; } #ifndef VAX /* accommodate 3 significant digits in exponent */ if (s[2]) { #ifdef Pedantic if (!e0 && !s[3]) for(s -= 2, e1 = 2; s[0] = s[1]; s++); /* Pedantic gives the behavior that Fortran 77 specifies, */ /* i.e., requires that E be specified for exponent fields */ /* of more than 3 digits. With Pedantic undefined, we get */ /* the behavior that Cray displays -- you get a bigger */ /* exponent field if it fits. */ #else if (!e0) { for(s -= 2, e1 = 2; s[0] = s[1]; s++) #ifdef CRAY delta--; if ((delta += 4) < 0) goto nogood #endif ; } #endif else if (e0 >= 0) goto shift; else e1 = e; } else shift: #endif for(s += 2, e1 = 2; *s; ++e1, ++s) if (e1 >= e) goto nogood; while(--delta >= 0) PUT(' '); if (signspace) PUT(sign ? '-' : '+'); s = buf; i = f__scale; if (f__scale <= 0) { #ifdef WANT_LEAD_0 if (insert0) PUT('0'); #endif PUT('.'); for(; i < 0; ++i) PUT('0'); PUT(*s); s += 2; } else if (f__scale > 1) { PUT(*s); s += 2; while(--i > 0) PUT(*s++); PUT('.'); } if (d1) { se -= 2; while(s < se) PUT(*s++); se += 2; do PUT('0'); while(--d1 > 0); } while(s < se) PUT(*s++); if (e < 2) PUT(s[1]); else { while(++e1 <= e) PUT('0'); while(*s) PUT(*s++); } return 0; } int #ifdef KR_headers wrt_F(p,w,d,len) ufloat *p; ftnlen len; #else wrt_F(ufloat *p, int w, int d, ftnlen len) #endif { int d1, sign, n; double x; char *b, buf[MAXINTDIGS+MAXFRACDIGS+4], *s; x= (len==sizeof(real)?p->pf:p->pd); if (d < MAXFRACDIGS) d1 = 0; else { d1 = d - MAXFRACDIGS; d = MAXFRACDIGS; } if (x < 0.) { x = -x; sign = 1; } else { sign = 0; #ifndef VAX if (!x) { #ifdef SIGNED_ZEROS if (signbit_f2c(&x)) sign = 2; #endif x = 0.; } #endif } if (n = f__scale) if (n > 0) do x *= 10.; while(--n > 0); else do x *= 0.1; while(++n < 0); #ifdef USE_STRLEN sprintf(b = buf, "%#.*f", d, x); n = strlen(b) + d1; #else n = sprintf(b = buf, "%#.*f", d, x) + d1; #endif #ifndef WANT_LEAD_0 if (buf[0] == '0' && d) { ++b; --n; } #endif if (sign == 1) { /* check for all zeros */ for(s = b;;) { while(*s == '0') s++; switch(*s) { case '.': s++; continue; case 0: sign = 0; } break; } } if (sign || f__cplus) ++n; if (n > w) { #ifdef WANT_LEAD_0 if (buf[0] == '0' && --n == w) ++b; else #endif { while(--w >= 0) PUT('*'); return 0; } } for(w -= n; --w >= 0; ) PUT(' '); if (sign) PUT('-'); else if (f__cplus) PUT('+'); while(n = *b++) PUT(n); while(--d1 >= 0) PUT('0'); return 0; } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/changes0000644000076500000240000040750413524616145023424 0ustar tamasstaff0000000000000031 Aug. 1989: 1. A(min(i,j)) now is translated correctly (where A is an array). 2. 7 and 8 character variable names are allowed (but elicit a complaint under -ext). 3. LOGICAL*1 is treated as LOGICAL, with just one error message per LOGICAL*1 statement (rather than one per variable declared in that statement). [Note that LOGICAL*1 is not in Fortran 77.] Like f77, f2c now allows the format in a read or write statement to be an integer array. 5 Sept. 1989: Fixed botch in argument passing of substrings of equivalenced variables. 15 Sept. 1989: Warn about incorrect code generated when a character-valued function is not declared external and is passed as a parameter (in violation of the Fortran 77 standard) before it is invoked. Example: subroutine foo(a,b) character*10 a,b call goo(a,b) b = a(3) end 18 Sept. 1989: Complain about overlapping initializations. 20 Sept. 1989: Warn about names declared EXTERNAL but never referenced; include such names as externs in the generated C (even though most C compilers will discard them). 24 Sept. 1989: New option -w8 to suppress complaint when COMMON or EQUIVALENCE forces word alignment of a double. Under -A (for ANSI C), ensure that floating constants (terminated by 'f') contain either a decimal point or an exponent field. Repair bugs sometimes encountered with CHAR and ICHAR intrinsic functions. Restore f77's optimizations for copying and comparing character strings of length 1. Always assume floating-point valued routines in libF77 return doubles, even under -R. Repair occasional omission of arguments in routines having multiple entry points. Repair bugs in computing offsets of character strings involved in EQUIVALENCE. Don't omit structure qualification when COMMON variables are used as FORMATs or internal files. 2 Oct. 1989: Warn about variables that appear only in data stmts; don't emit them. Fix bugs in character DATA for noncharacter variables involved in EQUIVALENCE. Treat noncharacter variables initialized (at least partly) with character data as though they were equivalenced -- put out a struct and #define the variables. This eliminates the hideous and nonportable numeric values that were used to initialize such variables. Treat IMPLICIT NONE as IMPLICIT UNDEFINED(A-Z) . Quit when given invalid options. 8 Oct. 1989: Modified naming scheme for generated intermediate variables; more are recycled, fewer distinct ones used. New option -W nn specifies nn characters/word for Hollerith data initializing non-character variables. Bug fix: x(i:min(i+10,j)) used to elicit "Can't handle opcode 31 yet". Integer expressions of the form (i+const1) - (i+const2), where i is a scalar integer variable, are now simplified to (const1-const2); this leads to simpler translation of some substring expressions. Initialize uninitialized portions of character string arrays to 0 rather than to blanks. 9 Oct. 1989: New option -c to insert comments showing original Fortran source. New option -g to insert line numbers of original Fortran source. 10 Oct. 1989: ! recognized as in-line comment delimiter (a la Fortran 88). 24 Oct. 1989: New options to ease coping with systems that want the structs that result from COMMON blocks to be defined just once: -E causes uninitialized COMMON blocks to be declared Extern; if Extern is undefined, f2c.h #defines it to be extern. -ec causes a separate .c file to be emitted for each uninitialized COMMON block: COMMON /ABC/ yields abc_com.c; thus one can compile *_com.c into a library to ensure precisely one definition. -e1c is similar to -ec, except that everything goes into one file, along with comments that give a sed script for splitting the file into the pieces that -ec would give. This is for use with netlib's "execute f2c" service (for which -ec is coerced into -e1c, and the sed script will put everything but the COMMON definitions into f2c_out.c ). 28 Oct. 1989: Convert "i = i op ..." into "i op= ...;" even when i is a dummy argument. 13 Nov. 1989: Name integer constants (passed as arguments) c__... rather than c_... so common /c/stuff call foo(1) ... is translated correctly. 19 Nov. 1989: Floating-point constants are now kept as strings unless they are involved in constant expressions that get simplified. The floating-point constants kept as strings can have arbitrarily many significant figures and a very large exponent field (as large as long int allows on the machine on which f2c runs). Thus, for example, the body of subroutine zot(x) double precision x(6), pi parameter (pi=3.1415926535897932384626433832795028841972) x(1) = pi x(2) = pi+1 x(3) = 9287349823749272.7429874923740978492734D-298374 x(4) = .89 x(5) = 4.0005 x(6) = 10D7 end now gets translated into x[1] = 3.1415926535897932384626433832795028841972; x[2] = 4.1415926535897931; x[3] = 9.2873498237492727429874923740978492734e-298359; x[4] = (float).89; x[5] = (float)4.0005; x[6] = 1e8; rather than the former x[1] = 3.1415926535897931; x[2] = 4.1415926535897931; x[3] = 0.; x[4] = (float)0.89000000000000003; x[5] = (float)4.0004999999999997; x[6] = 100000000.; Recognition of f77 machine-constant intrinsics deleted, i.e., epbase, epprec, epemin, epemax, eptiny, ephuge, epmrsp. 22 Nov. 1989: Workarounds for glitches on some Sun systems... libf77: libF77/makefile modified to point out possible need to compile libF77/main.c with -Donexit=on_exit . libi77: libI77/wref.c (and libI77/README) modified so non-ANSI systems can compile with USE_STRLEN defined, which will cause sprintf(b = buf, "%#.*f", d, x); n = strlen(b) + d1; rather than n = sprintf(b = buf, "%#.*f", d, x) + d1; to be compiled. 26 Nov. 1989: Longer names are now accepted (up to 50 characters); names may contain underscores (in which case they will have two underscores appended, to avoid clashes with library names). 28 Nov. 1989: libi77 updated: 1. Allow 3 (or, on Crays, 4) digit exponents under format Ew.d . 2. Try to get things right on machines where ints have 16 bits. 29 Nov. 1989: Supplied missing semicolon in parameterless subroutines that have multiple entry points (all of them parameterless). 30 Nov. 1989: libf77 and libi77 revised to use types from f2c.h. f2c now types floating-point valued C library routines as "double" rather than "doublereal" (for use with nonstandard C compilers for which "double" is IEEE double extended). 1 Dec. 1989: f2c.h updated to eliminate #defines rendered unnecessary (and, indeed, dangerous) by change of 26 Nov. to long names possibly containing underscores. libi77 further revised: yesterday's change omitted two tweaks to fmt.h (tweaks which only matter if float and real or double and doublereal are different types). 2 Dec. 1989: Better error message (than "bad tag") for NAMELIST, which no longer inhibits C output. 4 Dec. 1989: Allow capital letters in hex constants (f77 extension; e.g., x'a012BCd', X'A012BCD' and x'a012bcd' are all treated as the integer 167848909). libi77 further revised: lio.c lio.h lread.c wref.c wrtfmt.c tweaked again to allow float and real or double and doublereal to be different. 6 Dec. 1989: Revised f2c.h -- required for the following... Simpler looking translations for abs, min, max, using #defines in revised f2c.h . libi77: more corrections to types; additions for NAMELIST. Corrected casts in some I/O calls. Translation of NAMELIST; libi77 must still be revised. Currently libi77 gives you a run-time error message if you attempt NAMELIST I/O. 7 Dec. 1989: Fixed bug that prevented local integer variables that appear in DATA stmts from being ASSIGNed statement labels. Fillers (for DATA statements initializing EQUIVALENCEd variables and variables in COMMON) typed integer rather than doublereal (for slightly more portability, e.g. to Crays). libi77: missing return values supplied in a few places; some tests reordered for better working on the Cray. libf77: better accuracy for complex divide, complex square root, real mod function (casts to double; double temporaries). 9 Dec. 1989: Fixed bug that caused needless (albeit harmless) empty lines to be inserted in the C output when a comment line contained trailing blanks. Further tweak to type of fillers: allow doublereal fillers if the struct has doublereal data. 11 Dec. 1989: Alteration of rule for producing external (C) names from names that contain underscores. Now the external name is always obtained by appending a pair of underscores. 12 Dec. 1989: C production inhibited after most errors. 15 Dec. 1989: Fixed bug in headers for subroutines having two or more character strings arguments: the length arguments were reversed. 19 Dec. 1989: f2c.h libf77 libi77: adjusted so #undefs in f2c.h should not foil compilation of libF77 and libI77. libf77: getenv_ adjusted to work with unsorted environments. libi77: the iostat= specifier should now work right with internal I/O. 20 Dec. 1989: f2c bugs fixed: In the absence of an err= specifier, the iostat= specifier was generally set wrong. Character strings containing explicit nulls (\0) were truncated at the first null. Unlabeled DO loops recognized; must be terminated by ENDDO. (Don't ask for CYCLE, EXIT, named DO loops, or DO WHILE.) 29 Dec. 1989: Nested unlabeled DO loops now handled properly; new warning for extraneous text at end of FORMAT. 30 Dec. 1989: Fixed bug in translating dble(real(...)), dble(sngl(...)), and dble(float(...)), where ... is either of type double complex or is an expression requiring assignment to intermediate variables (e.g., dble(real(foo(x+1))), where foo is a function and x is a variable). Regard nonblank label fields on continuation lines as an error. 3 Jan. 1990: New option -C++ yields output that should be understood by C++ compilers. 6 Jan. 1989: -a now excludes variables that appear in a namelist from those that it makes automatic. (As before, it also excludes variables that appear in a common, data, equivalence, or save statement.) The syntactically correct Fortran read(*,i) x end now yields syntactically correct C (even though both the Fortran and C are buggy -- no FORMAT has not been ASSIGNed to i). 7 Jan. 1990: libi77: routines supporting NAMELIST added. Surrounding quotes made optional when no ambiguity arises in a list or namelist READ of a character-string value. 9 Jan. 1990: f2c.src made available. 16 Jan. 1990: New options -P to produce ANSI C or C++ prototypes for procedures defined. Change to -A and -C++: f2c tries to infer prototypes for invoked procedures unless the new -!P option is given. New warning messages for inconsistent calling sequences among procedures within a single file. Most of f2c/src is affected. f2c.h: typedefs for procedure arguments added; netlib's f2c service will insert appropriate typedefs for use with older versions of f2c.h. 17 Jan. 1990: f2c/src: defs.h exec.c format.c proc.c putpcc.c version.c xsum0.out updated. Castargs and protofile made extern in defs.h; exec.c modified so superfluous else clauses are diagnosed; unused variables omitted from declarations in format.c proc.c putpcc.c . 21 Jan. 1990: No C emitted for procedures declared external but not referenced. f2c.h: more new types added for use with -P. New feature: f2c accepts as arguments files ending in .p or .P; such files are assumed to be prototype files, such as produced by the -P option. All prototype files are read before any Fortran files and apply globally to all Fortran files. Suitable prototypes help f2c warn about calling-sequence errors and can tell f2c how to type procedures declared external but not explicitly typed; the latter is mainly of interest for users of the -A and -C++ options. (Prototype arguments are not available to netlib's "execute f2c" service.) New option -it tells f2c to try to infer types of untyped external arguments from their use as parameters to prototyped or previously defined procedures. f2c/src: many minor cleanups; most modules changed. Individual files in f2c/src are now in "bundle" format. The former f2c.1 is now f2c.1t; "f2c.1t from f2c" and "f2c.1t from f2c/src" are now the same, as are "f2c.1 from f2c" and "f2c.1 from f2c/src". People who do not obtain a new copy of "all from f2c/src" should at least add fclose(sortfp); after the call on do_init_data(outfile, sortfp) in format_data.c . 22 Jan. 1990: Cleaner man page wording (thanks to Doug McIlroy). -it now also applies to all untyped EXTERNAL procedures, not just arguments. 23 Jan. 01:34:00 EST 1990: Bug fixes: under -A and -C++, incorrect C was generated for subroutines having multiple entries but no arguments. Under -A -P, subroutines of no arguments were given prototype calling sequence () rather than (void). Character-valued functions elicited erroneous warning messages about inconsistent calling sequences when referenced by another procedure in the same file. f2c.1t: omit first appearance of libF77.a in FILES section; load order of libraries is -lF77 -lI77, not vice versa (bug introduced in yesterday's edits); define .F macro for those whose -man lacks it. (For a while after yesterday's fixes were posted, f2c.1t was out of date. Sorry!) 23 Jan. 9:53:24 EST 1990: Character substring expressions involving function calls having character arguments (including the intrinsic len function) yielded incorrect C. Procedures defined after invocation (in the same file) with conflicting argument types also got an erroneous message about the wrong number of arguments. 24 Jan. 11:44:00 EST 1990: Bug fixes: -p omitted #undefs; COMMON block names containing underscores had their C names incorrectly computed; a COMMON block having the name of a previously defined procedure wreaked havoc; if all arguments were .P files, f2c tried reading the second as a Fortran file. New feature: -P emits comments showing COMMON block lengths, so one can get warnings of incompatible COMMON block lengths by having f2c read .P (or .p) files. Now by running f2c twice, first with -P -!c (or -P!c), then with *.P among the arguments, you can be warned of inconsistent COMMON usage, and COMMON blocks having inconsistent lengths will be given the maximum length. (The latter always did happen within each input file; now -P lets you extend this behavior across files.) 26 Jan. 16:44:00 EST 1990: Option -it made less aggressive: untyped external procedures that are invoked are now typed by the rules of Fortran, rather than by previous use of procedures to which they are passed as arguments before being invoked. Option -P now includes information about references, i.e., called procedures, in the prototype files (in the form of special comments). This allows iterative invocations of f2c to infer more about untyped external names, particularly when multiple Fortran files are involved. As usual, there are some obscure bug fixes: 1. Repair of erroneous warning messages about inconsistent number of arguments that arose when a character dummy parameter was discovered to be a function or when multiple entry points involved character variables appearing in a previous entry point. 2. Repair of memory fault after error msg about "adjustable character function". 3. Under -U, allow MAIN_ as a subroutine name (in the same file as a main program). 4. Change for consistency: a known function invoked as a subroutine, then as a function elicits a warning rather than an error. 26 Jan. 22:32:00 EST 1990: Fixed two bugs that resulted in incorrect C for substrings, within the body of a character-valued function, of the function's name, when those substrings were arguments to another function (even implicitly, as in character-string assignment). 28 Jan. 18:32:00 EST 1990: libf77, libi77: checksum files added; "make check" looks for transmission errors. NAMELIST read modified to allow $ rather than & to precede a namelist name, to allow $ rather than / to terminate input where the name of another variable would otherwise be expected, and to regard all nonprinting ASCII characters <= ' ' as spaces. 29 Jan. 02:11:00 EST 1990: "fc from f2c" added. -it option made the default; -!it turns it off. Type information is now updated in a previously missed case. -P option tweaked again; message about when rerunning f2c may change prototypes or declarations made more accurate. New option -Ps implies -P and returns exit status 4 if rerunning f2c -P with prototype inputs might change prototypes or declarations. Now you can execute a crude script like cat *.f >zap.F rm -f zap.P while :; do f2c -Ps -!c zap.[FP] case $? in 4) ;; *) break;; esac done to get a file zap.P of the best prototypes f2c can determine for *.f . Jan. 29 07:30:21 EST 1990: Forgot to check for error status when setting return code 4 under -Ps; error status (1, 2, 3, or, for caught signal, 126) now takes precedence. Jan 29 14:17:00 EST 1990: Incorrect handling of open(n,'filename') repaired -- now treated as open(n,file='filename') (and, under -ext, given an error message). New optional source file memset.c for people whose systems don't provide memset, memcmp, and memcpy; #include in mem.c changed to #include "string.h" so BSD people can create a local string.h that simply says #include . Jan 30 10:34:00 EST 1990: Fix erroneous warning at end of definition of a procedure with character arguments when the procedure had previously been called with a numeric argument instead of a character argument. (There were two warnings, the second one incorrectly complaining of a wrong number of arguments.) Jan 30 16:29:41 EST 1990: Fix case where -P and -Ps erroneously reported another iteration necessary. (Only harm is the extra iteration.) Feb 3 01:40:00 EST 1990: Supply semicolon occasionally omitted under -c . Try to force correct alignment when numeric variables are initialized with character data (a non-standard and non-portable practice). You must use the -W option if your code has such data statements and is meant to run on a machine with other than 4 characters/word; e.g., for code meant to run on a Cray, you would specify -W8 . Allow parentheses around expressions in output lists (in write and print statements). Rename source files so their names are <= 12 characters long (so there's room to append .Z and still have <= 14 characters); renamed files: formatdata.c niceprintf.c niceprintf.h safstrncpy.c . f2c material made available by anonymous ftp from research.att.com (look in dist/f2c ). Feb 3 03:49:00 EST 1990: Repair memory fault that arose from use (in an assignment or call) of a non-argument variable declared CHARACTER*(*). Feb 9 01:35:43 EST 1990: Fix erroneous error msg about bad types in subroutine foo(a,adim) dimension a(adim) integer adim Fix improper passing of character args (and possible memory fault) in the expression part of a computed goto. Fix botched calling sequences in array references involving functions having character args. Fix memory fault caused by invocation of character-valued functions of no arguments. Fix botched calling sequence of a character*1-valued function assigned to a character*1 variable. Fix bug in error msg for inconsistent number of args in prototypes. Allow generation of C output despite inconsistencies in prototypes, but give exit code 8. Simplify include logic (by removing some bogus logic); never prepend "/usr/include/" to file names. Minor cleanups (that should produce no visible change in f2c's behavior) in intr.c parse.h main.c defs.h formatdata.c p1output.c . Feb 10 00:19:38 EST 1990: Insert (integer) casts when floating-point expressions are used as subscripts. Make SAVE stmt (with no variable list) override -a . Minor cleanups: change field to Field in struct Addrblock (for the benefit of buggy C compilers); omit system("/bin/cp ...") in misc.c . Feb 13 00:39:00 EST 1990: Error msg fix in gram.dcl: change "cannot make %s parameter" to "cannot make into parameter". Feb 14 14:02:00 EST 1990: Various cleanups (invisible on systems with 4-byte ints), thanks to Dave Regan: vaxx.c eliminated; %d changed to %ld various places; external names adjusted for the benefit of stupid systems (that ignore case and recognize only 6 significant characters in external names); buffer shortened in xsum.c (e.g. for MS-DOS); fopen modes distinguish text and binary files; several unused functions eliminated; missing arg supplied to an unlikely fatalstr invocation. Thu Feb 15 19:15:53 EST 1990: More cleanups (invisible on systems with 4 byte ints); casts inserted so most complaints from cyntax(1) and lint(1) go away; a few (int) versus (long) casts corrected. Fri Feb 16 19:55:00 EST 1990: Recognize and translate unnamed Fortran 8x do while statements. Fix bug that occasionally caused improper breaking of character strings. New error message for attempts to provide DATA in a type-declaration statement. Sat Feb 17 11:43:00 EST 1990: Fix infinite loop clf -> Fatal -> done -> clf after I/O error. Change "if (addrp->vclass = CLPROC)" to "if (addrp->vclass == CLPROC)" in p1_addr (in p1output.c); this was probably harmless. Move a misplaced } in lex.c (which slowed initkey()). Thanks to Gary Word for pointing these things out. Sun Feb 18 18:07:00 EST 1990: Detect overlapping initializations of arrays and scalar variables in previously missed cases. Treat logical*2 as logical (after issuing a warning). Don't pass string literals to p1_comment(). Correct a cast (introduced 16 Feb.) in gram.expr; this matters e.g. on a Cray. Attempt to isolate UNIX-specific things in sysdep.c (a new source file). Unless sysdep.c is compiled with SYSTEM_SORT defined, the intermediate files created for DATA statements are now sorted in-core without invoking system(). Tue Feb 20 16:10:35 EST 1990: Move definition of binread and binwrite from init.c to sysdep.c . Recognize Fortran 8x tokens < <= == >= > <> as synonyms for .LT. .LE. .EQ. .GE. .GT. .NE. Minor cleanup in putpcc.c: fully remove simoffset(). More discussion of system dependencies added to libI77/README. Tue Feb 20 21:44:07 EST 1990: Minor cleanups for the benefit of EBCDIC machines -- try to remove the assumption that 'a' through 'z' are contiguous. (Thanks again to Gary Word.) Also, change log2 to log_2 (shouldn't be necessary). Wed Feb 21 06:24:56 EST 1990: Fix botch in init.c introduced in previous change; only matters to non-ASCII machines. Thu Feb 22 17:29:12 EST 1990: Allow several entry points to mention the same array. Protect parameter adjustments with if's (for the case that an array is not an argument to all entrypoints). Under -u, allow subroutine foo(x,n) real x(n) integer n Compute intermediate variables used to evaluate dimension expressions at the right time. Example previously mistranslated: subroutine foo(x,k,m,n) real x(min(k,m,n)) ... write(*,*) x Detect duplicate arguments. (The error msg points to the first executable stmt -- not wonderful, but not worth fixing.) Minor cleanup of min/max computation (sometimes slightly simpler). Sun Feb 25 09:39:01 EST 1990: Minor tweak to multiple entry points: protect parameter adjustments with if's only for (array) args that do not appear in all entry points. Minor tweaks to format.c and io.c (invisible unless your compiler complained at the duplicate #defines of IOSUNIT and IOSFMT or at comparisons of p1gets(...) with NULL). Sun Feb 25 18:40:10 EST 1990: Fix bug introduced Feb. 22: if a subprogram contained DATA and the first executable statement was labeled, then the label got lost. (Just change INEXEC to INDATA in p1output.c; it occurs just once.) Mon Feb 26 17:45:10 EST 1990: Fix bug in handling of " and ' in comments. Wed Mar 28 01:43:06 EST 1990: libI77: 1. Repair nasty I/O bug: opening two files and closing the first (after possibly reading or writing it), then writing the second caused the last buffer of the second to be lost. 2. Formatted reads of logical values treated all letters other than t or T as f (false). libI77 files changed: err.c rdfmt.c Version.c (Request "libi77 from f2c" -- you can't get these files individually.) f2c itself: Repair nasty bug in translation of ELSE IF (condition involving complicated abs, min, or max) -- auxiliary statements were emitted at the wrong place. Supply semicolon previously omitted from the translation of a label (of a CONTINUE) immediately preceding an ELSE IF or an ELSE. This bug made f2c produce invalid C. Correct a memory fault that occurred (on some machines) when the error message "adjustable dimension on non-argument" should be given. Minor tweaks to remove some harmless warnings by overly chatty C compilers. Argument arays having constant dimensions but a variable lower bound (e.g., x(n+1:n+3)) had a * omitted from scalar arguments involved in the array offset computation. Wed Mar 28 18:47:59 EST 1990: libf77: add exit(0) to end of main [return(0) encounters a Cray bug] Sun Apr 1 16:20:58 EDT 1990: Avoid dereferencing null when processing equivalences after an error. Fri Apr 6 08:29:49 EDT 1990: Calls involving alternate return specifiers omitted processing needed for things like min, max, abs, and // (concatenation). INTEGER*2 PARAMETERs were treated as INTEGER*4. Convert some O(n^2) parsing to O(n). Tue Apr 10 20:07:02 EDT 1990: When inconsistent calling sequences involve differing numbers of arguments, report the first differing argument rather than the numbers of arguments. Fix bug under -a: formatted I/O in which either the unit or the format was a local character variable sometimes resulted in invalid C (a static struct initialized with an automatic component). Improve error message for invalid flag after elided -. Complain when literal table overflows, rather than infinitely looping. (The complaint mentions the new and otherwise undocumented -NL option for specifying a larger literal table.) New option -h for forcing strings to word (or, with -hd, double-word) boundaries where possible. Repair a bug that could cause improper splitting of strings. Fix bug (cast of c to doublereal) in subroutine foo(c,r) double complex c double precision r c = cmplx(r,real(c)) end New include file "sysdep.h" has some things from defs.h (and elsewhere) that one may need to modify on some systems. Some large arrays that were previously statically allocated are now dynamically allocated when f2c starts running. f2c/src files changed: README cds.c defs.h f2c.1 f2c.1t format.c formatdata.c init.c io.c lex.c main.c makefile mem.c misc.c names.c niceprintf.c output.c parse_args.c pread.c put.c putpcc.c sysdep.h version.c xsum0.out Wed Apr 11 18:27:12 EDT 1990: Fix bug in argument consistency checking of character, complex, and double complex valued functions. If the same source file contained a definition of such a function with arguments not explicitly typed, then subsequent references to the function might get erroneous warnings of inconsistent calling sequences. Tweaks to sysdep.h for partially ANSI systems. New options -kr and -krd cause f2c to use temporary variables to enforce Fortran evaluation-order rules with pernicious, old-style C compilers that apply the associative law to floating-point operations. Sat Apr 14 15:50:15 EDT 1990: libi77: libI77 adjusted to allow list-directed and namelist I/O of internal files; bug in namelist I/O of logical and character arrays fixed; list input of complex numbers adjusted to permit d or D to denote the start of the exponent field of a component. f2c itself: fix bug in handling complicated lower-bound expressions for character substrings; e.g., min and max did not work right, nor did function invocations involving character arguments. Switch to octal notation, rather than hexadecimal, for nonprinting characters in character and string constants. Fix bug (when neither -A nor -C++ was specified) in typing of external arguments of type complex, double complex, or character: subroutine foo(c) external c complex c now results in /* Complex */ int (*c) (); (as, indeed, it once did) rather than complex (*c) (); Sat Apr 14 22:50:39 EDT 1990: libI77/makefile: updated "make check" to omit lio.c lib[FI]77/makefile: trivial change: define CC = cc, reference $(CC). (Request, e.g., "libi77 from f2c" -- you can't ask for individual files from lib[FI]77.) Wed Apr 18 00:56:37 EDT 1990: Move declaration of atof() from defs.h to sysdep.h, where it is now not declared if stdlib.h is included. (NeXT's stdlib.h has a #define atof that otherwise wreaks havoc.) Under -u, provide a more intelligible error message (than "bad tag") for an attempt to define a function without specifying its type. Wed Apr 18 17:26:27 EDT 1990: Recognize \v (vertical tab) in Hollerith as well as quoted strings; add recognition of \r (carriage return). New option -!bs turns off recognition of escapes in character strings (\0, \\, \b, \f, \n, \r, \t, \v). Move to sysdep.c initialization of some arrays whose initialization assumed ASCII; #define Table_size in sysdep.h rather than using hard-coded 256 in allocating arrays of size 1 << (bits/byte). Thu Apr 19 08:13:21 EDT 1990: Warn when escapes would make Hollerith extend beyond statement end. Omit max() definition from misc.c (should be invisible except on systems that erroneously #define max in stdlib.h). Mon Apr 23 22:24:51 EDT 1990: When producing default-style C (no -A or -C++), cast switch expressions to (int). Move "-lF77 -lI77 -lm -lc" to link_msg, defined in sysdep.c . Add #define scrub(x) to sysdep.h, with invocations in format.c and formatdata.c, so that people who have systems like VMS that would otherwise create multiple versions of intermediate files can #define scrub(x) unlink(x) Tue Apr 24 18:28:36 EDT 1990: Pass string lengths once rather than twice to a function of character arguments involved in comparison of character strings of length 1. Fri Apr 27 13:11:52 EDT 1990: Fix bug that made f2c gag on concatenations involving char(...) on some systems. Sat Apr 28 23:20:16 EDT 1990: Fix control-stack bug in if(...) then else if (complicated condition) else endif (where the complicated condition causes assignment to an auxiliary variable, e.g., max(a*b,c)). Mon Apr 30 13:30:10 EDT 1990: Change fillers for DATA with holes from substructures to arrays (in an attempt to make things work right with C compilers that have funny padding rules for substructures, e.g., Sun C compilers). Minor cleanup of exec.c (should not affect generated C). Mon Apr 30 23:13:51 EDT 1990: Fix bug in handling return values of functions having multiple entry points of differing return types. Sat May 5 01:45:18 EDT 1990: Fix type inference bug in subroutine foo(x) call goo(x) end subroutine goo(i) i = 3 end Instead of warning of inconsistent calling sequences for goo, f2c was simply making i a real variable; now i is correctly typed as an integer variable, and f2c issues an error message. Adjust error messages issued at end of declarations so they don't blame the first executable statement. Sun May 6 01:29:07 EDT 1990: Fix bug in -P and -Ps: warn when the definition of a subprogram adds information that would change prototypes or previous declarations. Thu May 10 18:09:15 EDT 1990: Fix further obscure bug with (default) -it: inconsistent calling sequences and I/O statements could interact to cause a memory fault. Example: SUBROUTINE FOO CALL GOO(' Something') ! Forgot integer first arg END SUBROUTINE GOO(IUNIT,MSG) CHARACTER*(*)MSG WRITE(IUNIT,'(1X,A)') MSG END Fri May 11 16:49:11 EDT 1990: Under -!c, do not delete any .c files (when there are errors). Avoid dereferencing 0 when a fatal error occurs while reading Fortran on stdin. Wed May 16 18:24:42 EDT 1990: f2c.ps made available. Mon Jun 4 12:53:08 EDT 1990: Diagnose I/O units of invalid type. Add specific error msg about dummy arguments in common. Wed Jun 13 12:43:17 EDT 1990: Under -A, supply a missing "[1]" for CHARACTER*1 variables that appear both in a DATA statement and in either COMMON or EQUIVALENCE. Mon Jun 18 16:58:31 EDT 1990: Trivial updates to f2c.ps . ("Fortran 8x" --> "Fortran 90"; omit "(draft)" from "(draft) ANSI C".) Tue Jun 19 07:36:32 EDT 1990: Fix incorrect code generated for ELSE IF(expression involving function call passing non-constant substring). Under -h, preserve the property that strings are null-terminated where possible. Remove spaces between # and define in lex.c output.c parse.h . Mon Jun 25 07:22:59 EDT 1990: Minor tweak to makefile to reduce unnecessary recompilations. Tue Jun 26 11:49:53 EDT 1990: Fix unintended truncation of some integer constants on machines where casting a long to (int) may change the value. E.g., when f2c ran on machines with 16-bit ints, "i = 99999" was being translated to "i = -31073;". Wed Jun 27 11:05:32 EDT 1990: Arrange for CHARACTER-valued PARAMETERs to honor their length specifications. Allow CHAR(nn) in expressions defining such PARAMETERs. Fri Jul 20 09:17:30 EDT 1990: Avoid dereferencing 0 when a FORMAT statement has no label. Thu Jul 26 11:09:39 EDT 1990: Remarks about VOID and binread,binwrite added to README. Tweaks to parse_args: should be invisible unless your compiler complained at (short)*store. Thu Aug 2 02:07:58 EDT 1990: f2c.ps: change the first line of page 5 from include stuff to include 'stuff' Tue Aug 14 13:21:24 EDT 1990: libi77: libI77 adjusted to treat tabs as spaces in list input. Fri Aug 17 07:24:53 EDT 1990: libi77: libI77 adjusted so a blank='ZERO' clause (upper case Z) in an open of a currently open file works right. Tue Aug 28 01:56:44 EDT 1990: Fix bug in warnings of inconsistent calling sequences: if an argument to a subprogram was never referenced, then a previous invocation of the subprogram (in the same source file) that passed something of the wrong type for that argument did not elicit a warning message. Thu Aug 30 09:46:12 EDT 1990: libi77: prevent embedded blanks in list output of complex values; omit exponent field in list output of values of magnitude between 10 and 1e8; prevent writing stdin and reading stdout or stderr; don't close stdin, stdout, or stderr when reopening units 5, 6, 0. Tue Sep 4 12:30:57 EDT 1990: Fix bug in C emitted under -I2 or -i2 for INTEGER*4 FUNCTION. Warn of missing final END even if there are previous errors. Fri Sep 7 13:55:34 EDT 1990: Remark about "make xsum.out" and "make f2c" added to README. Tue Sep 18 23:50:01 EDT 1990: Fix null dereference (and, on some systems, writing of bogus *_com.c files) under -ec or -e1c when a prototype file (*.p or *.P) describes COMMON blocks that do not appear in the Fortran source. libi77: Add some #ifdef lines (#ifdef MSDOS, #ifndef MSDOS) to avoid references to stat and fstat on non-UNIX systems. On UNIX systems, add component udev to unit; decide that old and new files are the same iff both the uinode and udev components of unit agree. When an open stmt specifies STATUS='OLD', use stat rather than access (on UNIX systems) to check the existence of the file (in case directories leading to the file have funny permissions and this is a setuid or setgid program). Thu Sep 27 16:04:09 EDT 1990: Supply missing entry for Impldoblock in blksize array of cpexpr (in expr.c). No examples are known where this omission caused trouble. Tue Oct 2 22:58:09 EDT 1990: libf77: test signal(...) == SIG_IGN rather than & 01 in main(). libi77: adjust rewind.c so two successive rewinds after a write don't clobber the file. Thu Oct 11 18:00:14 EDT 1990: libi77: minor cleanups: add #include "fcntl.h" to endfile.c, err.c, open.c; adjust g_char in util.c for segmented memories; in f_inqu (inquire.c), define x appropriately when MSDOS is defined. Mon Oct 15 20:02:11 EDT 1990: Add #ifdef MSDOS pointer adjustments to mem.c; treat NAME= as a synonym for FILE= in OPEN statements. Wed Oct 17 16:40:37 EDT 1990: libf77, libi77: minor cleanups: _cleanup() and abort() invocations replaced by invocations of sig_die in main.c; some error messages previously lost in buffers will now appear. Mon Oct 22 16:11:27 EDT 1990: libf77: separate sig_die from main (for folks who don't want to use the main in libF77). libi77: minor tweak to comments in README. Fri Nov 2 13:49:35 EST 1990: Use two underscores rather than one in generated temporary variable names to avoid conflict with COMMON names. f2c.ps updated to reflect this change and the NAME= extension introduced 15 Oct. Repair a rare memory fault in io.c . Mon Nov 5 16:43:55 EST 1990: libi77: changes to open.c (and err.c): complain if an open stmt specifies new= and the file already exists (as specified by Fortrans 77 and 90); allow file= to be omitted in open stmts and allow status='replace' (Fortran 90 extensions). Fri Nov 30 10:10:14 EST 1990: Adjust malloc.c for unusual systems whose sbrk() can return values not properly aligned for doubles. Arrange for slightly more helpful and less repetitive warnings for non-character variables initialized with character data; these warnings are (still) suppressed by -w66. Fri Nov 30 15:57:59 EST 1990: Minor tweak to README (about changing VOID in f2c.h). Mon Dec 3 07:36:20 EST 1990: Fix spelling of "character" in f2c.1t. Tue Dec 4 09:48:56 EST 1990: Remark about link_msg and libf2c added to f2c/README. Thu Dec 6 08:33:24 EST 1990: Under -U, render label nnn as L_nnn rather than Lnnn. Fri Dec 7 18:05:00 EST 1990: Add more names from f2c.h (e.g. integer, real) to the c_keywords list of names to which an underscore is appended to avoid confusion. Mon Dec 10 19:11:15 EST 1990: Minor tweaks to makefile (./xsum) and README (binread/binwrite). libi77: a few modifications for POSIX systems; meant to be invisible elsewhere. Sun Dec 16 23:03:16 EST 1990: Fix null dereference caused by unusual erroneous input, e.g. call foo('abc') end subroutine foo(msg) data n/3/ character*(*) msg end (Subroutine foo is illegal because the character statement comes after a data statement.) Use decimal rather than hex constants in xsum.c (to prevent erroneous warning messages about constant overflow). Mon Dec 17 12:26:40 EST 1990: Fix rare extra underscore in character length parameters passed for multiple entry points. Wed Dec 19 17:19:26 EST 1990: Allow generation of C despite error messages about bad alignment forced by equivalence. Allow variable-length concatenations in I/O statements, such as open(3, file=bletch(1:n) // '.xyz') Fri Dec 28 17:08:30 EST 1990: Fix bug under -p with formats and internal I/O "units" in COMMON, as in COMMON /FIGLEA/F CHARACTER*20 F F = '(A)' WRITE (*,FMT=F) 'Hello, world!' END Tue Jan 15 12:00:24 EST 1991: Fix bug when two equivalence groups are merged, the second with nonzero offset, and the result is then merged into a common block. Example: INTEGER W(3), X(3), Y(3), Z(3) COMMON /ZOT/ Z EQUIVALENCE (W(1),X(1)), (X(2),Y(1)), (Z(3),X(1)) ***** W WAS GIVEN THE WRONG OFFSET Recognize Fortran 90's optional NML= in NAMELIST READs and WRITEs. (Currently NML= and FMT= are treated as synonyms -- there's no error message if, e.g., NML= specifies a format.) libi77: minor adjustment to allow internal READs from character string constants in read-only memory. Fri Jan 18 22:56:15 EST 1991: Add comment to README about needing to comment out the typedef of size_t in sysdep.h on some systems, e.g. Sun 4.1. Fix misspelling of "statement" in an error message in lex.c Wed Jan 23 00:38:48 EST 1991: Allow hex, octal, and binary constants to have the qualifying letter (z, x, o, or b) either before or after the quoted string containing the digits. For now this change will not be reflected in f2c.ps . Tue Jan 29 16:23:45 EST 1991: Arrange for character-valued statement functions to give results of the right length (that of the statement function's name). Wed Jan 30 07:05:32 EST 1991: More tweaks for character-valued statement functions: an error check and an adjustment so a right-hand side of nonconstant length (e.g., a substring) is handled right. Wed Jan 30 09:49:36 EST 1991: Fix p1_head to avoid printing (char *)0 with %s. Thu Jan 31 13:53:44 EST 1991: Add a test after the cleanup call generated for I/O statements with ERR= or END= clauses to catch the unlikely event that the cleanup routine encounters an error. Mon Feb 4 08:00:58 EST 1991: Minor cleanup: omit unneeded jumps and labels from code generated for some NAMELIST READs and WRITEs with IOSTAT=, ERR=, and/or END=. Tue Feb 5 01:39:36 EST 1991: Change Mktemp to mktmp (for the benefit of systems so brain-damaged that they do not distinguish case in external names -- and that for some reason want to load mktemp). Try to get xsum0.out right this time (it somehow didn't get updated on 4 Feb. 1991). Add note to libi77/README about adjusting the interpretation of RECL= specifiers in OPENs for direct unformatted I/O. Thu Feb 7 17:24:42 EST 1991: New option -r casts values of REAL functions, including intrinsics, to REAL. This only matters for unportable code like real r r = asin(1.) if (r .eq. asin(1.)) ... [The behavior of such code varies with the Fortran compiler used -- and sometimes is affected by compiler options.] For now, the man page at the end of f2c.ps is the only part of f2c.ps that reflects this new option. Fri Feb 8 18:12:51 EST 1991: Cast pointer differences passed as arguments to the appropriate type. This matters, e.g., with MSDOS compilers that yield a long pointer difference but have int == short. Disallow nonpositive dimensions. Fri Feb 15 12:24:15 EST 1991: Change %d to %ld in sprintf call in putpower in putpcc.c. Free more memory (e.g. allowing translation of larger Fortran files under MS-DOS). Recognize READ (character expression) and WRITE (character expression) as formatted I/O with the format given by the character expression. Update year in Notice. Sat Feb 16 00:42:32 EST 1991: Recant recognizing WRITE(character expression) as formatted output -- Fortran 77 is not symmetric in its syntax for READ and WRITE. Mon Mar 4 15:19:42 EST 1991: Fix bug in passing the real part of a complex argument to an intrinsic function. Omit unneeded parentheses in nested calls to intrinsics. Example: subroutine foo(x, y) complex y x = exp(sin(real(y))) + exp(imag(y)) end Fri Mar 8 15:05:42 EST 1991: Fix a comment in expr.c; omit safstrncpy.c (which had bugs in cases not used by f2c). Wed Mar 13 02:27:23 EST 1991: Initialize firstmemblock->next in mem_init in mem.c . [On most systems it was fortuituously 0, but with System V, -lmalloc could trip on this missed initialization.] Wed Mar 13 11:47:42 EST 1991: Fix a reference to freed memory. Wed Mar 27 00:42:19 EST 1991: Fix a memory fault caused by such illegal Fortran as function foo x = 3 logical foo ! declaration among executables foo=.false. ! used to suffer memory fault end Fri Apr 5 08:30:31 EST 1991: Fix loss of % in some format expressions, e.g. write(*,'(1h%)') Fix botch introduced 27 March 1991 that caused subroutines with multiple entry points to have extraneous declarations of ret_val. Fri Apr 5 12:44:02 EST 1991 Try again to omit extraneous ret_val declarations -- this morning's fix was sometimes wrong. Mon Apr 8 13:47:06 EDT 1991: Arrange for s_rnge to have the right prototype under -A -C . Wed Apr 17 13:36:03 EDT 1991: New fatal error message for apparent invocation of a recursive statement function. Thu Apr 25 15:13:37 EDT 1991: F2c and libi77 adjusted so NAMELIST works with -i2. (I forgot about -i2 when adding NAMELIST.) This required a change to f2c.h (that only affects NAMELIST I/O under -i2.) Man-page description of -i2 adjusted to reflect that -i2 stores array lengths in short ints. Fri Apr 26 02:54:41 EDT 1991: Libi77: fix some bugs in NAMELIST reading of multi-dimensional arrays (file rsne.c). Thu May 9 02:13:51 EDT 1991: Omit a trailing space in expr.c (could cause a false xsum value if a mailer drops the trailing blank). Thu May 16 13:14:59 EDT 1991: Libi77: increase LEFBL in lio.h to overcome a NeXT bug. Tweak for compilers that recognize "nested" comments: inside comments, turn /* into /+ (as well as */ into +/). Sat May 25 11:44:25 EDT 1991: libf77: s_rnge: declare line long int rather than int. Fri May 31 07:51:50 EDT 1991: libf77: system_: officially return status. Mon Jun 17 16:52:53 EDT 1991: Minor tweaks: omit unnecessary declaration of strcmp (that caused trouble on a system where strcmp was a macro) from misc.c; add SHELL = /bin/sh to makefiles. Fix a dereference of null when a CHARACTER*(*) declaration appears (illegally) after DATA. Complain only once per subroutine about declarations appearing after DATA. Mon Jul 1 00:28:13 EDT 1991: Add test and error message for illegal use of subroutine names, e.g. SUBROUTINE ZAP(A) ZAP = A END Mon Jul 8 21:49:20 EDT 1991: Issue a warning about things like integer i i = 'abc' (which is treated as i = ichar('a')). [It might be nice to treat 'abc' as an integer initialized (in a DATA statement) with 'abc', but other matters have higher priority.] Render i = ichar('A') as i = 'A'; rather than i = 65; (which assumes ASCII). Fri Jul 12 07:41:30 EDT 1991: Note added to README about erroneous definitions of __STDC__ . Sat Jul 13 13:38:54 EDT 1991: Fix bugs in double type convesions of complex values, e.g. sngl(real(...)) or dble(real(...)) (where ... is complex). Mon Jul 15 13:21:42 EDT 1991: Fix bug introduced 8 July 1991 that caused erroneous warnings "ichar([first char. of] char. string) assumed for conversion to numeric" when a subroutine had an array of character strings as an argument. Wed Aug 28 01:12:17 EDT 1991: Omit an unused function in format.c, an unused variable in proc.c . Under -r8, promote complex to double complex (as the man page claims). Fri Aug 30 17:19:17 EDT 1991: f2c.ps updated: slightly expand description of intrinsics and,or,xor, not; add mention of intrinsics lshift, rshift; add note about f2c accepting Fortran 90 inline comments (starting with !); update Cobalt Blue address. Tue Sep 17 07:17:33 EDT 1991: libI77: err.c and open.c modified to use modes "rb" and "wb" when (f)opening unformatted files; README updated to point out that it may be necessary to change these modes to "r" and "w" on some non-ANSI systems. Tue Oct 15 10:25:49 EDT 1991: Minor tweaks that make some PC compilers happier: insert some casts, add args to signal functions. Change -g to emit uncommented #line lines -- and to emit more of them; update fc, f2c.1, f2c.1t, f2c.ps to reflect this. Change uchar to Uchar in xsum.c . Bring gram.c up to date. Thu Oct 17 09:22:05 EDT 1991: libi77: README, fio.h, sue.c, uio.c changed so the length field in unformatted sequential records has type long rather than int (unless UIOLEN_int is #defined). This is for systems where sizeof(int) can vary, depending on the compiler or compiler options. Thu Oct 17 13:42:59 EDT 1991: libi77: inquire.c: when MSDOS is defined, don't strcmp units[i].ufnm when it is NULL. Fri Oct 18 15:16:00 EDT 1991: Correct xsum0.out in "all from f2c/src" (somehow botched on 15 Oct.). Tue Oct 22 18:12:56 EDT 1991: Fix memory fault when a character*(*) argument is used (illegally) as a dummy variable in the definition of a statement function. (The memory fault occurred when the statement function was invoked.) Complain about implicit character*(*). Thu Nov 14 08:50:42 EST 1991: libi77: change uint to Uint in fmt.h, rdfmt.c, wrtfmt.c; this change should be invisible unless you're running a brain-damaged system. Mon Nov 25 19:04:40 EST 1991: libi77: correct botches introduced 17 Oct. 1991 and 14 Nov. 1991 (change uint to Uint in lwrite.c; other changes that only matter if sizeof(int) != sizeof(long)). Add a more meaningful error message when bailing out due to an attempt to invoke a COMMON variable as a function. Sun Dec 1 19:29:24 EST 1991: libi77: uio.c: add test for read failure (seq. unformatted reads); adjust an error return from EOF to off end of record. Tue Dec 10 17:42:28 EST 1991: Add tests to prevent memory faults with bad uses of character*(*). Thu Dec 12 11:24:41 EST 1991: libi77: fix bug with internal list input that caused the last character of each record to be ignored; adjust error message in internal formatted input from "end-of-file" to "off end of record" if the format specifies more characters than the record contains. Wed Dec 18 17:48:11 EST 1991: Fix bug in translating nonsensical ichar invocations involving concatenations. Fix bug in passing intrinsics lle, llt, lge, lgt as arguments; hl_le was being passed rather than l_le, etc. libf77: adjust length parameters from long to ftnlen, for compiling with f2c_i2 defined. Sat Dec 21 15:30:57 EST 1991: Allow DO nnn ... to end with an END DO statement labelled nnn. Tue Dec 31 13:53:47 EST 1991: Fix bug in handling dimension a(n**3,2) -- pow_ii was called incorrectly. Fix bug in translating subroutine x(abc,n) character abc(n) write(abc,'(i10)') 123 end (omitted declaration and initialiation of abc_dim1). Complain about dimension expressions of such invalid types as complex and logical. Fri Jan 17 11:54:20 EST 1992: Diagnose some illegal uses of main program name (rather than memory faulting). libi77: (1) In list and namelist input, treat "r* ," and "r*," alike (where r is a positive integer constant), and fix a bug in handling null values following items with repeat counts (e.g., 2*1,,3). (2) For namelist reading of a numeric array, allow a new name-value subsequence to terminate the current one (as though the current one ended with the right number of null values). (3) [lio.h, lwrite.c]: omit insignificant zeros in list and namelist output. (Compile with -DOld_list_output to get the old behavior.) Sat Jan 18 15:58:01 EST 1992: libi77: make list output consistent with F format by printing .1 rather than 0.1 (introduced yesterday). Wed Jan 22 08:32:43 EST 1992: libi77: add comment to README pointing out preconnection of Fortran units 5, 6, 0 to stdin, stdout, stderr (respectively). Mon Feb 3 11:57:53 EST 1992: libi77: fix namelist read bug that caused the character following a comma to be ignored. Fri Feb 28 01:04:26 EST 1992: libf77: fix buggy z_sqrt.c (double precision square root), which misbehaved for arguments in the southwest quadrant. Thu Mar 19 15:05:18 EST 1992: Fix bug (introduced 17 Jan 1992) in handling multiple entry points of differing types (with implicitly typed entries appearing after the first executable statement). Fix memory fault in the following illegal Fortran: double precision foo(i) * illegal: above should be "double precision function foo(i)" foo = i * 3.2 entry moo(i) end Note about ANSI_Libraries (relevant, e.g., to IRIX 4.0.1 and AIX) added to README. Abort zero divides during constant simplification. Sat Mar 21 01:27:09 EST 1992: Tweak ckalloc (misc.c) for systems where malloc(0) = 0; this matters for subroutines with multiple entry points but no arguments. Add "struct memblock;" to init.c (irrelevant to most compilers). Wed Mar 25 13:31:05 EST 1992: Fix bug with IMPLICIT INTEGER*4(...): under -i2 or -I2, the *4 was ignored. Tue May 5 09:53:55 EDT 1992: Tweaks to README; e.g., ANSI_LIbraries changed to ANSI_Libraries . Wed May 6 23:49:07 EDT 1992 Under -A and -C++, have subroutines return 0 (even if they have no * arguments). Adjust libi77 (rsne.c and lread.c) for systems where ungetc is a macro. Tweak lib[FI]77/makefile to use unique intermediate file names (for parallel makes). Tue May 19 09:03:05 EDT 1992: Adjust libI77 to make err= work with internal list and formatted I/O. Sat May 23 18:17:42 EDT 1992: Under -A and -C++, supply "return 0;" after the code generated for a STOP statement -- the C compiler doesn't know that s_stop won't return. New (mutually exclusive) options: -f treats all input lines as free-format lines, honoring text that appears after column 72 and not padding lines shorter than 72 characters with blanks (which matters if a character string is continued across 2 or more lines). -72 treats text appearing after column 72 as an error. Sun May 24 09:45:37 EDT 1992: Tweak description of -f in f2c.1 and f2c.1t; update f2c.ps . Fri May 29 01:17:15 EDT 1992: Complain about externals used as variables. Example subroutine foo(a,b) external b a = a*b ! illegal use of b; perhaps should be b() end Mon Jun 15 11:15:27 EDT 1992: Fix bug in handling namelists with names that have underscores. Sat Jun 27 17:30:59 EDT 1992: Under -A and -C++, end Main program aliases with "return 0;". Under -A and -C++, use .P files and usage in previous subprograms in the current file to give prototypes for functions declared EXTERNAL but not invoked. Fix memory fault under -d1 -P . Under -A and -C++, cast arguments to the right types in calling a function that has been defined in the current file or in a .P file. Fix bug in handling multi-dimensional arrays with array references in their leading dimensions. Fix bug in the intrinsic cmplx function when the first argument involves an expression for which f2c generates temporary variables, e.g. cmplx(abs(real(a)),1.) . Sat Jul 18 07:36:58 EDT 1992: Fix buglet with -e1c (invisible on most systems) temporary file f2c_functions was unlinked before being closed. libf77: fix bugs in evaluating m**n for integer n < 0 and m an integer different from 1 or a real or double precision 0. Catch SIGTRAP (to print "Trace trap" before aborting). Programs that previously erroneously computed 1 for 0**-1 may now fault. Relevant routines: main.c pow_di.c pow_hh.c pow_ii.c pow_ri.c . Sat Jul 18 08:40:10 EDT 1992: libi77: allow namelist input to end with & (e.g. &end). Thu Jul 23 00:14:43 EDT 1992 Append two underscores rather than one to C keywords used as local variables to avoid conflicts with similarly named COMMON blocks. Thu Jul 23 11:20:55 EDT 1992: libf77, libi77 updated to assume ANSI prototypes unless KR_headers is #defined. libi77 now recognizes a Z format item as in Fortran 90; the implementation assumes 8-bit bytes and botches character strings on little-endian machines (by printing their bytes from right to left): expect this bug to persist; fixing it would require a change to the I/O calling sequences. Tue Jul 28 15:18:33 EDT 1992: libi77: insert missed "#ifdef KR_headers" lines around getnum header in rsne.c. Version not updated. NOTE: "index from f2c" now ends with current timestamps of files in "all from f2c/src", sorted by time. To bring your source up to date, obtain source files with a timestamp later than the time shown in your version.c. Fri Aug 14 08:07:09 EDT 1992: libi77: tweak wrt_E in wref.c to avoid signing NaNs. Sun Aug 23 19:05:22 EDT 1992: fc: supply : after O in getopt invocation (for -O1 -O2 -O3). Mon Aug 24 18:37:59 EDT 1992: Recant above tweak to fc: getopt is dumber than I thought; it's necessary to say -O 1 (etc.). libF77/README: add comments about ABORT, ERF, DERF, ERFC, DERFC, GETARG, GETENV, IARGC, SIGNAL, and SYSTEM. Tue Oct 27 01:57:42 EST 1992: libf77, libi77: 1. Fix botched indirection in signal_.c. 2. Supply missing l_eof = 0 assignment to s_rsne() in rsne.c (so end-of-file on other files won't confuse namelist reads of external files). 3. Prepend f__ to external names that are only of internal interest to lib[FI]77. Thu Oct 29 12:37:18 EST 1992: libf77: Fix botch in signal_.c when KR_headers is #defined; add CFLAGS to makefile. libi77: trivial change to makefile for consistency with libF77/makefile. Wed Feb 3 02:05:16 EST 1993: Recognize types INTEGER*1, LOGICAL*1, LOGICAL*2, INTEGER*8. INTEGER*8 is not well tested and will only work reasonably on systems where int = 4 bytes, long = 8 bytes; on such systems, you'll have to modify f2c.h appropriately, changing integer from long to int and adding typedef long longint. You'll also have to compile libI77 with Allow_TYQUAD #defined and adjust libF77/makefile to compile pow_qq.c. In the f2c source, changes for INTEGER*8 are delimited by #ifdef TYQUAD ... #endif. You can omit the INTEGER*8 changes by compiling with NO_TYQUAD #defined. Otherwise, the new command-line option -!i8 disables recognition of INTEGER*8. libf77: add pow_qq.c libi77: add #ifdef Allow_TYQUAD stuff. Changes for INTEGER*1, LOGICAL*1, and LOGICAL*2 came last 23 July 1992. Fix bug in backspace (that only bit when the last character of the second or subsequent buffer read was the previous newline). Guard against L_tmpnam being too small in endfile.c. For MSDOS, close and reopen files when copying to truncate. Lengthen LINTW (buffer size in lwrite.c). Add \ to the end of #define lines that get broken. Fix bug in handling NAMELIST of items in EQUIVALENCE. Under -h (or -hd), convert Hollerith to integer in general expressions (e.g., assignments), not just when they're passed as arguments, and blank-pad rather than 0-pad the Hollerith to a multiple of sizeof(integer) or sizeof(doublereal). Add command-line option -s, which instructs f2c preserve multi- dimensional subscripts (by emitting and using appropriate #defines). Fix glitch (with default type inferences) in examples like call foo('abc') end subroutine foo(goo) end This gave two warning messages: Warning on line 4 of y.f: inconsistent calling sequences for foo: here 1, previously 2 args and string lengths. Warning on line 4 of y.f: inconsistent calling sequences for foo: here 2, previously 1 args and string lengths. Now the second Warning is suppressed. Complain about all inconsistent arguments, not just the first. Switch to automatic creation of "all from f2c/src". For folks getting f2c source via ftp, this means f2c/src/all.Z is now an empty file rather than a bundle. Separate -P and -A: -P no longer implies -A. Thu Feb 4 00:32:20 EST 1993: Fix some glitches (introduced yesterday) with -h . Fri Feb 5 01:40:38 EST 1993: Fix bug in types conveyed for namelists (introduced 3 Feb. 1993). Fri Feb 5 21:26:43 EST 1993: libi77: tweaks to NAMELIST and open (after comments by Harold Youngren): 1. Reading a ? instead of &name (the start of a namelist) causes the namelist being sought to be written to stdout (unit 6); to omit this feature, compile rsne.c with -DNo_Namelist_Questions. 2. Reading the wrong namelist name now leads to an error message and an attempt to skip input until the right namelist name is found; to omit this feature, compile rsne.c with -DNo_Bad_Namelist_Skip. 3. Namelist writes now insert newlines before each variable; to omit this feature, compile xwsne.c with -DNo_Extra_Namelist_Newlines. 4. For OPEN of sequential files, ACCESS='APPEND' (or access='anything else starting with "A" or "a"') causes the file to be positioned at end-of-file, so a write will append to the file. (This is nonstandard, but does not require modifying data structures.) Mon Feb 8 14:40:37 EST 1993: Increase number of continuation lines allowed from 19 to 99, and allow changing this limit with -NC (e.g. -NC200 for 200 lines). Treat control-Z (at the beginning of a line) as end-of-file: see the new penultimate paragraph of README. Fix a rarely seen glitch that could make an error messages to say "line 0". Tue Feb 9 02:05:40 EST 1993 libi77: change some #ifdef MSDOS lines to #ifdef NON_UNIX_STDIO, and, in err.c under NON_UNIX_STDIO, avoid close(creat(name,0666)) when the unit has another file descriptor for name. Tue Feb 9 17:12:49 EST 1993 libi77: more tweaks for NON_UNIX_STDIO: use stdio routines rather than open, close, creat, seek, fdopen (except for f__isdev). Fri Feb 12 15:49:33 EST 1993 Update src/gram.c (which was forgotten in the recent updates). Most folks regenerate it anyway (wity yacc or bison). Thu Mar 4 17:07:38 EST 1993 Increase default max labels in computed gotos and alternate returns to 257, and allow -Nl1234 to specify this number. Tweak put.c to check p->tag == TADDR in realpart() and imagpart(). Adjust fc script to allow .r (RATFOR) files and -C (check subscripts). Avoid declaring strchr in niceprintf.c under -DANSI_Libraries . gram.c updated again. libi77: err.c, open.c: take declaration of fdopen from rawio.h. Sat Mar 6 07:09:11 EST 1993 libi77: uio.c: adjust off-end-of-record test for sequential unformatted reads to respond to err= rather than end= . Sat Mar 6 16:12:47 EST 1993 Treat scalar arguments of the form (v) and v+0, where v is a variable, as expressions: assign to a temporary variable, and pass the latter. gram.c updated. Mon Mar 8 09:35:38 EST 1993 "f2c.h from f2c" updated to add types logical1 and integer1 for LOGICAL*1 and INTEGER*1. ("f2c.h from f2c" is supposed to be the same as "f2c.h from f2c/src", which was updated 3 Feb. 1993.) Mon Mar 8 17:57:55 EST 1993 Fix rarely seen bug that could cause strange casts in function invocations (revealed by an example with msdos/f2c.exe). msdos/f2cx.exe.Z and msdos/f2c.exe.Z updated (ftp access only). Fri Mar 12 12:37:01 EST 1993 Fix bug with -s in handling subscripts involving min, max, and complicated expressions requiring temporaries. Fix bug in handling COMMONs that need padding by a char array. msdos/f2cx.exe.Z and msdos/f2c.exe.Z updated (ftp access only). Fri Mar 12 17:16:16 EST 1993 libf77, libi77: updated for compiling under C++. Mon Mar 15 16:21:37 EST 1993 libi77: more minor tweaks (for -DKR_headers); Version.c not changed. Thu Mar 18 12:37:30 EST 1993 Flag -r (for discarding carriage-returns on systems that end lines with carriage-return/newline pairs, e.g. PCs) added to xsum, and xsum.c converted to ANSI/ISO syntax (with K&R syntax available with -DKR_headers). [When time permits, the f2c source will undergo a similar conversion.] libi77: tweaks to #includes in endfile.c, err.c, open.c, rawio.h; Version.c not changed. f2c.ps updated (to pick up revision of 2 Feb. 1993 to f2c.1). Fri Mar 19 09:19:26 EST 1993 libi77: add (char *) casts to malloc and realloc invocations in err.c, open.c; Version.c not changed. Tue Mar 30 07:17:15 EST 1993 Fix bug introduced 6 March 1993: possible memory corruption when loops in data statements involve constant subscripts, as in DATA (GUNIT(1,I),I=0,14)/15*-1/ Tue Mar 30 16:17:42 EST 1993 Fix bug with -s: (floating-point array item)*(complex item) generates an _subscr() reference for the floating-point array, but a #define for the _subscr() was omitted. Tue Apr 6 12:11:22 EDT 1993 libi77: adjust error returns for formatted inputs to flush the current input line when err= is specified. To restore the old behavior (input left mid-line), either adjust the #definition of errfl in fio.h or omit the invocation of f__doend in err__fl (in err.c). Tue Apr 6 13:30:04 EDT 1993 Fix bug revealed in subroutine foo(i) call goo(int(i)) end which now passes a copy of i, rather than i itself. Sat Apr 17 11:41:02 EDT 1993 Adjust appending of underscores to conform with f2c.ps ("A Fortran to C Converter"): names that conflict with C keywords or f2c type names now have just one underscore appended (rather than two); add "integer1", "logical1", "longint" to the keyword list. Append underscores to names that appear in EQUIVALENCE and are component names in a structure declared in f2c.h, thus avoiding a problem caused by the #defines emitted for equivalences. Example: complex a equivalence (i,j) a = 1 ! a.i went awry because of #define i j = 2 write(*,*) a, i end Adjust line-breaking logic to avoid splitting very long constants (and names). Example: ! The next line starts with tab and thus is a free-format line. a=.012345689012345689012345689012345689012345689012345689012345689012345689 end Omit extraneous "return 0;" from entry stubs emitted for multiple entry points of type character, complex, or double complex. Sat Apr 17 14:35:05 EDT 1993 Fix bug (introduced 4 Feb.) in separating -P from -A that kept f2c from re-reading a .P file written without -A or -C++ describing a routine with an external argument. [See the just-added note about separating -P from -A in the changes above for 3 Feb. 1993.] Fix bug (type UNKNOWN for V in the example below) revealed by subroutine a() external c call b(c) end subroutine b(v) end Sun Apr 18 19:55:26 EDT 1993 Fix wrong calling sequence for mem() in yesterday's addition to equiv.c . Wed Apr 21 17:39:46 EDT 1993 Fix bug revealed in ASSIGN 10 TO L1 GO TO 20 10 ASSIGN 30 TO L2 STOP 10 20 ASSIGN 10 TO L2 ! Bug here because 10 had been assigned ! to another label, then defined. GO TO L2 30 END Fri Apr 23 18:38:50 EDT 1993 Fix bug with -h revealed in CHARACTER*9 FOO WRITE(FOO,'(I6)') 1 WRITE(FOO,'(I6)') 2 ! struct icilist io___3 botched END Tue Apr 27 16:08:28 EDT 1993 Tweak to makefile: remove "size f2c". Tue May 4 23:48:20 EDT 1993 libf77: tweak signal_ line of f2ch.add . Tue Jun 1 13:47:13 EDT 1993 Fix bug introduced 3 Feb. 1993 in handling multiple entry points with differing return types -- the postfix array in proc.c needed a new entry for integer*8 (which resulted in wrong Multitype suffixes for non-integral types). For (default) K&R C, generate VOID rather than int functions for functions of Fortran type character, complex, and double complex. msdos/f2cx.exe.Z and msdos/f2c.exe.Z updated (ftp access only). Tue Jun 1 23:11:15 EDT 1993 f2c.h: add Multitype component g and commented type longint. proc.c: omit "return 0;" from stubs for complex and double complex entries (when entries have multiple types); add test to avoid memory fault with illegal combinations of entry types. Mon Jun 7 12:00:47 EDT 1993 Fix memory fault in common /c/ m integer m(1) data m(1)/1/, m(2)/2/ ! one too many initializers end msdos/f2cx.exe.Z and msdos/f2c.exe.Z updated (ftp access only). Fri Jun 18 13:55:51 EDT 1993 libi77: change type of signal_ in f2ch.add; change type of il in union Uint from long to integer (for machines like the DEC Alpha, where integer should be the same as int). Version.c not changed. Tweak gram.dcl and gram.head: add semicolons after some rules that lacked them, and remove an extraneous semicolon. These changes are completely transparent to our local yacc programs, but apparently matter on some VMS systems. Wed Jun 23 01:02:56 EDT 1993 Update "fc" shell script, and bring f2c.1 and f2c.1t up to date: they're meant to be linked with (i.e., the same as) src/f2c.1 and src/f2c.1t . [In the last update of f2c.1* (2 Feb. 1993), only src/f2c.1 and src/f2c.1t got changed -- a mistake.] Wed Jun 23 09:04:31 EDT 1993 libi77: fix bug in format reversions for internal writes. Example: character*60 lines(2) write(lines,"('n =',i3,2(' more text',i3))") 3, 4, 5, 6 write(*,*) 'lines(1) = ', lines(1) write(*,*) 'lines(2) = ', lines(2) end gave an error message that began "iio: off end of record", rather than giving the correct output: lines(1) = n = 3 more text 4 more text 5 lines(2) = more text 6 more text Thu Aug 5 11:31:14 EDT 1993 libi77: lread.c: fix bug in handling repetition counts for logical data (during list or namelist input). Change struct f__syl to struct syl (for buggy compilers). Sat Aug 7 16:05:30 EDT 1993 libi77: lread.c (again): fix bug in namelist reading of incomplete logical arrays. Fix minor calling-sequence errors in format.c, output.c, putpcc.c: should be invisible. Mon Aug 9 09:12:38 EDT 1993 Fix erroneous cast under -A in translating character*(*) function getc() getc(2:3)=' ' !wrong cast in first arg to s_copy end libi77: lread.c: fix bug in namelist reading of an incomplete array of numeric data followed by another namelist item whose name starts with 'd', 'D', 'e', or 'E'. Fri Aug 20 13:22:10 EDT 1993 Fix bug in do while revealed by subroutine skdig (line, i) character line*(*), ch*1 integer i logical isdigit isdigit(ch) = ch.ge.'0' .and. ch.le.'9' do while (isdigit(line(i:i))) ! ch__1[0] was set before ! "while(...) {...}" i = i + 1 enddo end Fri Aug 27 08:22:54 EDT 1993 Add #ifdefs to avoid declaring atol when it is a macro; version.c not updated. Wed Sep 8 12:24:26 EDT 1993 libi77: open.c: protect #include "sys/..." with #ifndef NON_UNIX_STDIO; Version date not changed. Thu Sep 9 08:51:21 EDT 1993 Adjust "include" to interpret file names relative to the directory of the file that contains the "include". Fri Sep 24 00:56:12 EDT 1993 Fix offset error resulting from repeating the same equivalence statement twice. Example: real a(2), b(2) equivalence (a(2), b(2)) equivalence (a(2), b(2)) end Increase MAXTOKENLEN (to roughly the largest allowed by ANSI C). Mon Sep 27 08:55:09 EDT 1993 libi77: endfile.c: protect #include "sys/types.h" with #ifndef NON_UNIX_STDIO; Version.c not changed. Fri Oct 15 15:37:26 EDT 1993 Fix rarely seen parsing bug illustrated by subroutine foo(xabcdefghij) character*(*) xabcdefghij IF (xabcdefghij.NE.'##') GOTO 40 40 end in which the spacing in the IF line is crucial. Thu Oct 21 13:55:11 EDT 1993 Give more meaningful error message (then "unexpected character in cds") when constant simplification leads to Infinity or NaN. Wed Nov 10 15:01:05 EST 1993 libi77: backspace.c: adjust, under -DMSDOS, to cope with MSDOS text files, as handled by some popular PC C compilers. Beware: the (defective) libraries associated with these compilers assume lines end with \r\n (conventional MS-DOS text files) -- and ftell (and hence the current implementation of backspace) screws up if lines with just \n. Thu Nov 18 09:37:47 EST 1993 Give a better error (than "control stack empty") for an extraneous ENDDO. Example: enddo end Update comments about ftp in "readme from f2c". Sun Nov 28 17:26:50 EST 1993 Change format of time stamp in version.c to yyyymmdd. Sort parameter adjustments (or complain of impossible dependencies) so that dummy arguments are referenced only after being adjusted. Example: subroutine foo(a,b) integer a(2) ! a must be adjusted before b double precision b(a(1),a(2)) call goo(b(3,4)) end Adjust structs for initialized common blocks and equivalence classes to omit the trailing struct component added to force alignment when padding already forces the desired alignment. Example: PROGRAM TEST COMMON /Z/ A, CC CHARACTER*4 CC DATA cc /'a'/ END now gives struct { integer fill_1[1]; char e_2[4]; } z_ = { {0}, {'a', ' ', ' ', ' '} }; rather than struct { integer fill_1[1]; char e_2[4]; real e_3; } z_ = { {0}, {'a', ' ', ' ', ' '}, (float)0. }; Wed Dec 8 16:24:43 EST 1993 Adjust lex.c to recognize # nnn "filename" lines emitted by cpp; this affects the file names and line numbers in error messages and the #line lines emitted under -g. Under -g, arrange for a file that starts with an executable statement to have the first #line line indicate line 1, rather than the line number of the END statement ending the main program. Adjust fc script to run files ending in .F through /lib/cpp. Fix bug ("Impossible tag 2") in if (t .eq. (0,2)) write(*,*) 'Bug!' end libi77: iio.c: adjust internal formatted reads to treat short records as though padded with blanks (rather than causing an "off end of record" error). Wed Dec 15 15:19:15 EST 1993 fc: adjusted for .F files to pass -D and -I options to cpp. Fri Dec 17 20:03:38 EST 1993 Fix botch introduced 28 Nov. 1993 in vax.c; change "version of" to "version". Tue Jan 4 15:39:52 EST 1994 msdos/f2cx.exe.Z and msdos/f2c.exe.Z updated (ftp access only). Wed Jan 19 08:55:19 EST 1994 Arrange to accept integer Nx, Ny, Nz parameter (Nx = 10, Ny = 20) parameter (Nz = max(Nx, Ny)) integer c(Nz) call foo(c) end rather than complaining "Declaration error for c: adjustable dimension on non-argument". The necessary changes cause some hitherto unfolded constant expressions to be folded. Accept BYTE as a synonym for INTEGER*1. Thu Jan 27 08:57:40 EST 1994 Fix botch in changes of 19 Jan. 1994 that broke entry points with multi-dimensional array arguments that did not appear in the subprogram argument list and whose leading dimensions depend on arguments. Mon Feb 7 09:24:30 EST 1994 Remove artifact in "fc" script that caused -O to be ignored: 87c87 < # lcc ignores -O... --- > CFLAGS="$CFLAGS $O" Sun Feb 20 17:04:58 EST 1994 Fix bugs reading .P files for routines with arguments of type INTEGER*1, INTEGER*8, LOGICAL*2. Fix glitch in reporting inconsistent arguments for routines involving character arguments: "arg n" had n too large by the number of character arguments. Tue Feb 22 20:50:08 EST 1994 Trivial changes to data.c format.c main.c niceprintf.c output.h and sysdep.h (consistency improvements). libI77: lread.c: check for NULL return from realloc. Fri Feb 25 23:56:08 EST 1994 output.c, sysdep.h: arrange for -DUSE_DTOA to use dtoa.c and g_fmt.c for correctly rounded decimal values on IEEE-arithmetic machines (plus machines with VAX and IBM-mainframe arithmetic). These routines are available from netlib's fp directory. msdos/f2cx.exe.Z and msdos/f2c.exe.Z updated (ftp access only); the former uses -DUSE_DTOA to keep 12 from printing as 12.000000000000001. vax.c: fix wrong arguments to badtag and frchain introduced 28 Nov. 1993. Source for f2c converted to ANSI/ISO format, with the K&R format available by compilation with -DKR_headers . Arrange for (double precision expression) relop (single precision constant) to retain the single-precision nature of the constant. Example: double precision t if (t .eq. 0.3) ... Mon Feb 28 11:40:24 EST 1994 README updated to reflect a modification just made to netlib's "dtoa.c from fp": 96a97,105 > Also add the rule > > dtoa.o: dtoa.c > $(CC) -c $(CFLAGS) -DMALLOC=ckalloc -DIEEE... dtoa.c > > (without the initial tab) to the makefile, where IEEE... is one of > IEEE_MC68k, IEEE_8087, VAX, or IBM, depending on your machine's > arithmetic. See the comments near the start of dtoa.c. > Sat Mar 5 09:41:52 EST 1994 Complain about functions with the name of a previously declared common block (which is illegal). New option -d specifies the directory for output .c and .P files; f2c.1 and f2c.1t updated. The former undocumented debug option -dnnn is now -Dnnn. Thu Mar 10 10:21:44 EST 1994 libf77: add #undef min and #undef max lines to s_paus.c s_stop.c and system_.c; Version.c not changed. libi77: add -DPad_UDread lines to uio.c and explanation to README: Some buggy Fortran programs use unformatted direct I/O to write an incomplete record and later read more from that record than they have written. For records other than the last, the unwritten portion of the record reads as binary zeros. The last record is a special case: attempting to read more from it than was written gives end-of-file -- which may help one find a bug. Some other Fortran I/O libraries treat the last record no differently than others and thus give no help in finding the bug of reading more than was written. If you wish to have this behavior, compile uio.c with -DPad_UDread . Version.c not changed. Tue Mar 29 17:27:54 EST 1994 Adjust make_param so dimensions involving min, max, and other complicated constant expressions do not provoke error messages about adjustable dimensions on non-arguments. Fix botch introduced 19 Jan 1994: "adjustable dimension on non- argument" messages could cause some things to be freed twice. Tue May 10 07:55:12 EDT 1994 Trivial changes to exec.c, p1output.c, parse_args.c, proc.c, and putpcc.c: change arguments from type foo[] to type *foo for consistency with defs.h. For most compilers, this makes no difference. Thu Jun 2 12:18:18 EDT 1994 Fix bug in handling FORMAT statements that have adjacent character (or Hollerith) strings: an extraneous \002 appeared between the strings. libf77: under -DNO_ONEXIT, arrange for f_exit to be called just once; previously, upon abnormal termination (including stop statements), it was called twice. Mon Jun 6 15:52:57 EDT 1994 libf77: Avoid references to SIGABRT and SIGIOT if neither is defined; Version.c not changed. libi77: Add cast to definition of errfl() in fio.h; this only matters on systems with sizeof(int) < sizeof(long). Under -DNON_UNIX_STDIO, use binary mode for direct formatted files (to avoid any confusion connected with \n characters). Fri Jun 10 16:47:31 EDT 1994 Fix bug under -A in handling unreferenced (and undeclared) external arguments in subroutines with multiple entry points. Example: subroutine m(fcn,futil) external fcn,futil call fcn entry mintio(i1) ! (D_fp)0 rather than (U_fp)0 for futil end Wed Jun 15 10:38:14 EDT 1994 Allow char(constant expression) function in parameter declarations. (This was probably broken in the changes of 29 March 1994.) Fri Jul 1 23:54:00 EDT 1994 Minor adjustments to makefile (rule for f2c.1 commented out) and sysdep.h (#undef KR_headers if __STDC__ is #defined, and base test for ANSI_Libraries and ANSI_Prototypes on KR_headers rather than __STDC__); version.c touched but not changed. libi77: adjust fp.h so local.h is only needed under -DV10; Version.c not changed. Tue Jul 5 03:05:46 EDT 1994 Fix segmentation fault in subroutine foo(a,b,k) data i/1/ double precision a(k,1) ! sequence error: must precede data b = a(i,1) end libi77: Fix bug (introduced 6 June 1994?) in reopening files under NON_UNIX_STDIO. Fix some error messages caused by illegal Fortran. Examples: * 1. x(i) = 0 !Missing declaration for array x call f(x) !Said Impossible storage class 8 in routine mkaddr end !Now says invalid use of statement function x * 2. f = g !No declaration for g; by default it's a real variable call g !Said invalid class code 2 for function g end !Now says g cannot be called * 3. intrinsic foo !Invalid intrinsic name a = foo(b) !Said intrcall: bad intrgroup 0 end !Now just complains about line 1 Tue Jul 5 11:14:26 EDT 1994 Fix glitch in handling erroneous statement function declarations. Example: a(j(i) - i) = a(j(i) - i) + 1 ! bad statement function call foo(a(3)) ! Said Impossible type 0 in routine mktmpn end ! Now warns that i and j are not used Wed Jul 6 17:31:25 EDT 1994 Tweak test for statement functions that (illegally) call themselves; f2c will now proceed to check for other errors, rather than bailing out at the first recursive statement function reference. Warn about but retain divisions by 0 (instead of calling them "compiler errors" and quiting). On IEEE machines, this permits double precision nan, ninf, pinf nan = 0.d0/0.d0 pinf = 1.d0/0.d0 ninf = -1.d0/0.d0 write(*,*) 'nan, pinf, ninf = ', nan, pinf, ninf end to print nan, pinf, ninf = NaN Infinity -Infinity libi77: wref.c: protect with #ifdef GOOD_SPRINTF_EXPONENT an optimization that requires exponents to have 2 digits when 2 digits suffice. lwrite.c wsfe.c (list and formatted external output): omit ' ' carriage-control when compiled with -DOMIT_BLANK_CC . Off-by-one bug fixed in character count for list output of character strings. Omit '.' in list-directed printing of Nan, Infinity. Mon Jul 11 13:05:33 EDT 1994 src/gram.c updated. Tue Jul 12 10:24:42 EDT 1994 libi77: wrtfmt.c: under G11.4, write 0. as " .0000 " rather than " .0000E+00". Thu Jul 14 17:55:46 EDT 1994 Fix glitch in changes of 6 July 1994 that could cause erroneous "division by zero" warnings (or worse). Example: subroutine foo(a,b) y = b a = a / y ! erroneous warning of division by zero end Mon Aug 1 16:45:17 EDT 1994 libi77: lread.c rsne.c: for benefit of systems with a buggy stdio.h, declare ungetc when neither KR_headers nor ungetc is #defined. Version.c not changed. Wed Aug 3 01:53:00 EDT 1994 libi77: lwrite.c (list output): do not insert a newline when appending an oversize item to an empty line. Mon Aug 8 00:51:01 EDT 1994 Fix bug (introduced 3 Feb. 1993) that, under -i2, kept LOGICAL*2 variables from appearing in INQUIRE statements. Under -I2, allow LOGICAL*4 variables to appear in INQUIRE. Fix intrinsic function LEN so it returns a short value under -i2, a long value otherwise. exec.c: fix obscure memory fault possible with bizarre (and highly erroneous) DO-loop syntax. Fri Aug 12 10:45:57 EDT 1994 libi77: fix glitch that kept ERR= (in list- or format-directed input) from working after a NAMELIST READ. Thu Aug 25 13:58:26 EDT 1994 Suppress -s when -C is specified. Give full pathname (netlib@research.att.com) for netlib in readme and src/README. Wed Sep 7 22:13:20 EDT 1994 libi77: typesize.c: adjust to allow types LOGICAL*1, LOGICAL*2, INTEGER*1, and (under -DAllow_TYQUAD) INTEGER*8 in NAMELISTs. Fri Sep 16 17:50:18 EDT 1994 Change name adjustment for reserved words: instead of just appending "_" (a single underscore), append "_a_" to local variable names to avoid trouble when a common block is named a reserved word and the same reserved word is also a local variable name. Example: common /const/ a,b,c real const(3) equivalence (const(1),a) a = 1.234 end Arrange for ichar() to treat characters as unsigned. libf77: s_cmp.c: treat characters as unsigned in comparisons. These changes for unsignedness only matter for strings that contain non-ASCII characters. Now ichar() should always be >= 0. Sat Sep 17 11:19:32 EDT 1994 fc: set rc=$? before exit (to get exit code right in trap code). Mon Sep 19 17:49:43 EDT 1994 libf77: s_paus.c: flush stderr after PAUSE; add #ifdef MSDOS stuff. libi77: README: point out general need for -DMSDOS under MS-DOS. Tue Sep 20 11:42:30 EDT 1994 Fix bug in comparing identically named common blocks, in which all components have the same names and types, but at least one is dimensioned (1) and the other is not dimensioned. Example: subroutine foo common /ab/ a a=1. !!! translated correctly to ab_1.a = (float)1.; end subroutine goo common /ab/ a(1) a(1)=2. !!! translated erroneously to ab_1.a[0] = (float)2. end Tue Sep 27 23:47:34 EDT 1994 Fix bug introduced 16 Sept. 1994: don't add _a_ to C keywords used as external names. In fact, return to earlier behavior of appending __ to C keywords unless they are used as external names, in which case they get just one underscore appended. Adjust constant handling so integer and logical PARAMETERs retain type information, particularly under -I2. Example: SUBROUTINE FOO INTEGER I INTEGER*1 I1 INTEGER*2 I2 INTEGER*4 I4 LOGICAL L LOGICAL*1 L1 LOGICAL*2 L2 LOGICAL*4 L4 PARAMETER (L=.FALSE., L1=.FALSE., L2=.FALSE., L4=.FALSE.) PARAMETER (I=0,I1=0,I2=0,I4=0) CALL DUMMY(I, I1, I2, I4, L, L1, L2, L4) END f2c.1t: Change f\^2c to f2c (omit half-narrow space) in line following ".SH NAME" for benefit of systems that cannot cope with troff commands in this context. Wed Sep 28 12:45:19 EDT 1994 libf77: s_cmp.c fix glitch in -DKR_headers version introduced 12 days ago. Thu Oct 6 09:46:53 EDT 1994 libi77: util.c: omit f__mvgbt (which is never used). f2c.h: change "long" to "long int" to facilitate the adjustments by means of sed described above. Comment out unused typedef of Long. Fri Oct 21 18:02:24 EDT 1994 libf77: add s_catow.c and adjust README to point out that changing "s_cat.o" to "s_catow.o" in the makefile will permit the target of a concatenation to appear on its right-hand side (contrary to the Fortran 77 Standard and at the cost of some run-time efficiency). Wed Nov 2 00:03:58 EST 1994 Adjust -g output to contain only one #line line per statement, inserting \ before the \n ending lines broken because of their length [this insertion was recanted 10 Dec. 1994]. This change accommodates an idiocy in the ANSI/ISO C standard, which leaves undefined the behavior of #line lines that occur within the arguments to a macro call. Wed Nov 2 14:44:27 EST 1994 libi77: under compilation with -DALWAYS_FLUSH, flush buffers at the end of each write statement, and test (via the return from fflush) for write failures, which can be caught with an ERR= specifier in the write statement. This extra flushing slows execution, but can abort execution or alter the flow of control when a disk fills up. f2c/src/io.c: Add ERR= test to e_wsle invocation (end of list-directed external output) to catch write failures when libI77 is compiled with -DALWAYS_FLUSH. Thu Nov 3 10:59:13 EST 1994 Fix bug in handling dimensions involving certain intrinsic functions of constant expressions: the expressions, rather than pointers to them, were passed. Example: subroutine subtest(n,x) real x(2**n,n) ! pow_ii(2,n) was called; now it's pow_ii(&c__2,n) x(2,2)=3. end Tue Nov 8 23:56:30 EST 1994 malloc.c: remove assumption that only malloc calls sbrk. This appears to make malloc.c useful on RS6000 systems. Sun Nov 13 13:09:38 EST 1994 Turn off constant folding of integers used in floating-point expressions, so the assignment in subroutine foo(x) double precision x x = x*1000000*500000 end is rendered as *x = *x * 1000000 * 500000; rather than as *x *= 1783793664; Sat Dec 10 16:31:40 EST 1994 Supply a better error message (than "Impossible type 14") for subroutine foo foo = 3 end Under -g, convey name of included files to #line lines. Recant insertion of \ introduced (under -g) 2 Nov. 1994. Thu Dec 15 14:33:55 EST 1994 New command-line option -Idir specifies directories in which to look for non-absolute include files (after looking in the directory of the current input file). There can be several -Idir options, each specifying one directory. All -Idir options are considered, from left to right, until a suitably named file is found. The -I2 and -I4 command-line options have precedence, so directories named 2 or 4 must be spelled by some circumlocation, such as -I./2 . f2c.ps updated to mention the new -Idir option, correct a typo, and bring the man page at the end up to date. lex.c: fix bug in reading line numbers in #line lines. fc updated to pass -Idir options to f2c. Thu Dec 29 09:48:03 EST 1994 Fix bug (e.g., addressing fault) in diagnosing inconsistency in the type of function eta in the following example: function foo(c1,c2) double complex foo,c1,c2 double precision eta foo = eta(c1,c2) end function eta(c1,c2) double complex eta,c1,c2 eta = c1*c2 end Mon Jan 2 13:27:26 EST 1995 Retain casts for SNGL (or FLOAT) that were erroneously optimized away. Example: subroutine foo(a,b) double precision a,b a = float(b) ! now rendered as *a = (real) (*b); end Use float (rather than double) temporaries in certain expressions of type complex. Example: the temporary for sngl(b) in complex a double precision b a = sngl(b) - (3.,4.) is now of type float. Fri Jan 6 00:00:27 EST 1995 Adjust intrinsic function cmplx to act as dcmplx (returning double complex rather than complex) if either of its args is of type double precision. The double temporaries used prior to 2 Jan. 1995 previously gave it this same behavior. Thu Jan 12 12:31:35 EST 1995 Adjust -krd to use double temporaries in some calculations of type complex. libf77: pow_[dhiqrz][hiq].c: adjust x**i to work on machines that sign-extend right shifts when i is the most negative integer. Wed Jan 25 00:14:42 EST 1995 Fix memory fault in handling overlapping initializations in block data common /zot/ d double precision d(3) character*6 v(4) real r(2) equivalence (d(3),r(1)), (d(1),v(1)) data v/'abcdef', 'ghijkl', 'mnopqr', 'stuvwx'/ data r/4.,5./ end names.c: add "far", "huge", "near" to c_keywords (causing them to have __ appended when used as local variables). libf77: add s_copyow.c, an alternative to s_copy.c for handling (illegal) character assignments where the right- and left-hand sides overlap, as in a(2:4) = a(1:3). Thu Jan 26 14:21:19 EST 1995 libf77: roll s_catow.c and s_copyow.c into s_cat.c and s_copy.c, respectively, allowing the left-hand side of a character assignment to appear on its right-hand side unless s_cat.c and s_copy.c are compiled with -DNO_OVERWRITE (which is a bit more efficient). Fortran 77 forbids the left-hand side from participating in the right-hand side (of a character assignment), but Fortran 90 allows it. libi77: wref.c: fix glitch in printing the exponent of 0 when GOOD_SPRINTF_EXPONENT is not #defined. Fri Jan 27 12:25:41 EST 1995 Under -C++ -ec (or -C++ -e1c), surround struct declarations with #ifdef __cplusplus extern "C" { #endif and #ifdef __cplusplus } #endif (This isn't needed with cfront, but apparently is necessary with some other C++ compilers.) libf77: minor tweak to s_copy.c: copy forward whenever possible (for better cache behavior). Wed Feb 1 10:26:12 EST 1995 Complain about parameter statements that assign values to dummy arguments, as in subroutine foo(x) parameter(x = 3.4) end Sat Feb 4 20:22:02 EST 1995 fc: omit "lib=/lib/num/lib.lo". Wed Feb 8 08:41:14 EST 1995 Minor changes to exec.c, putpcc.c to avoid "bad tag" or "error in frexpr" with certain invalid Fortran. Sat Feb 11 08:57:39 EST 1995 Complain about integer overflows, both in simplifying integer expressions, and in converting integers from decimal to binary. Fix a memory fault in putcx1() associated with invalid input. Thu Feb 23 11:20:59 EST 1995 Omit MAXTOKENLEN; realloc token if necessary (to handle very long strings). Fri Feb 24 11:02:00 EST 1995 libi77: iio.c: z_getc: insert (unsigned char *) to allow internal reading of characters with high-bit set (on machines that sign-extend characters). Tue Mar 14 18:22:42 EST 1995 Fix glitch (in io.c) in handling 0-length strings in format statements, as in write(*,10) 10 format(' ab','','cd') libi77: lread.c and rsfe.c: adjust s_rsle and s_rsfe to check for end-of-file (to prevent infinite loops with empty read statements). Wed Mar 22 10:01:46 EST 1995 f2c.ps: adjust discussion of -P on p. 7 to reflect a change made 3 Feb. 1993: -P no longer implies -A. Fri Apr 21 18:35:00 EDT 1995 fc script: remove absolute paths (since PATH specifies only standard places). On most systems, it's still necessary to adjust the PATH assignment at the start of fc to fit the local conventions. Fri May 26 10:03:17 EDT 1995 fc script: add recognition of -P and .P files. libi77: iio.c: z_wnew: fix bug in handling T format items in internal writes whose last item is written to an earlier position than some previous item. Wed May 31 11:39:48 EDT 1995 libf77: added subroutine exit(rc) (with integer return code rc), which works like a stop statement but supplies rc as the program's return code. Fri Jun 2 11:56:50 EDT 1995 Fix memory fault in parameter (x=2.) data x /2./ end This now elicits two error messages; the second ("too many initializers"), though not desirable, seems hard to eliminate without considerable hassle. Mon Jul 17 23:24:20 EDT 1995 Fix botch in simplifying constants in certain complex expressions. Example: subroutine foo(s,z) double complex z double precision s, M, P parameter ( M = 100.d0, P = 2.d0 ) z = M * M / s * dcmplx (1.d0, P/M) *** The imaginary part of z was miscomputed *** end Under -ext, complain about nonintegral dimensions. Fri Jul 21 11:18:36 EDT 1995 Fix glitch on line 159 of init.c: change "(shortlogical *)0)", to "(shortlogical *)0", This affects multiple entry points when some but not all have arguments of type logical*2. libi77: adjust lwrite.c, wref.c, wrtfmt.c so compiling with -DWANT_LEAD_0 causes formatted writes of floating-point numbers of magnitude < 1 to have an explicit 0 before the decimal point (if the field-width permits it). Note that the Fortran 77 Standard leaves it up to the implementation whether to supply these superfluous zeros. Tue Aug 1 09:25:56 EDT 1995 Permit real (or double precision) parameters in dimension expressions. Mon Aug 7 08:04:00 EDT 1995 Append "_eqv" rather than just "_" to names that that appear in EQUIVALENCE statements as well as structs in f2c.h (to avoid a conflict when these names also name common blocks). Tue Aug 8 12:49:02 EDT 1995 Modify yesterday's change: merge st_fields with c_keywords, to cope with equivalences introduced to permit initializing numeric variables with character data. DATA statements causing these equivalences can appear after executable statements, so the only safe course is to rename all local variable with names in the former st_fields list. This has the unfortunate side effect that the common local variable "i" will henceforth be renamed "i__". Wed Aug 30 00:19:32 EDT 1995 libf77: add F77_aloc, now used in s_cat and system_ (to allocate memory and check for failure in so doing). libi77: improve MSDOS logic in backspace.c. Wed Sep 6 09:06:19 EDT 1995 libf77: Fix return type of system_ (integer) under -DKR_headers. libi77: Move some f_init calls around for people who do not use libF77's main(); now open and namelist read statements that are the first I/O statements executed should work right in that context. Adjust namelist input to treat a subscripted name whose subscripts do not involve colons similarly to the name without a subscript: accept several values, stored in successive elements starting at the indicated subscript. Adjust namelist output to quote character strings (avoiding confusion with arrays of character strings). Thu Sep 7 00:36:04 EDT 1995 Fix glitch in integer*8 exponentiation function: it's pow_qq, not pow_qi. libi77: fix some bugs with -DAllow_TYQUAD (for integer*8); when looking for the &name that starts NAMELIST input, treat lines whose first nonblank character is something other than &, $, or ? as comment lines (i.e., ignore them), unless rsne.c is compiled with -DNo_Namelist_Comments. Thu Sep 7 09:05:40 EDT 1995 libi77: rdfmt.c: one more tweak for -DAllow_TYQUAD. Tue Sep 19 00:03:02 EDT 1995 Adjust handling of floating-point subscript bounds (a questionable f2c extension) so subscripts in the generated C are of integral type. Move #define of roundup to proc.c (where its use is commented out); version.c left at 19950918. Wed Sep 20 17:24:19 EDT 1995 Fix bug in handling ichar() under -h. Thu Oct 5 07:52:56 EDT 1995 libi77: wrtfmt.c: fix bug with t editing (f__cursor was not always zeroed in mv_cur). Tue Oct 10 10:47:54 EDT 1995 Under -ext, warn about X**-Y and X**+Y. Following the original f77, f2c treats these as X**(-Y) and X**(+Y), respectively. (They are not allowed by the official Fortran 77 Standard.) Some Fortran compilers give a bizarre interpretation to larger contexts, making multiplication noncommutative: they treat X**-Y*Z as X**(-Y*Z) rather than X**(-Y)*Z, which, following the rules of Fortran 77, is the same as (X**(-Y))*Z. Wed Oct 11 13:27:05 EDT 1995 libi77: move defs of f__hiwater, f__svic, f__icptr from wrtfmt.c to err.c. This should work around a problem with buggy loaders and sometimes leads to smaller executable programs. Sat Oct 21 23:54:22 EDT 1995 Under -h, fix bug in the treatment of ichar('0') in arithmetic expressions. Demote to -dneg (a new command-line option not mentioned in the man page) imitation of the original f77's treatment of unary minus applied to a REAL operand (yielding a DOUBLE PRECISION result). Previously this imitation (which was present for debugging) occurred under (the default) -!R. It is still suppressed by -R. Tue Nov 7 23:52:57 EST 1995 Adjust assigned GOTOs to honor SAVE declarations. Add comments about ranlib to lib[FI]77/README and makefile. Tue Dec 19 22:54:06 EST 1995 libf77: s_cat.c: fix bug when 2nd or later arg overlaps lhs. Tue Jan 2 17:54:00 EST 1996 libi77: rdfmt.c: move #include "ctype.h" up before "stdlib.h"; no change to Version.c. Sun Feb 25 22:20:20 EST 1996 Adjust expr.c to permit raising the integer constants 1 and -1 to negative constant integral powers. Avoid faulting when -T and -d are not followed by a directory name (immediately, without intervening spaces). Wed Feb 28 12:49:01 EST 1996 Fix a glitch in handling complex parameters assigned a "wrong" type. Example: complex d, z parameter(z = (0d0,0d0)) data d/z/ ! elicited "non-constant initializer" call foo(d) end Thu Feb 29 00:53:12 EST 1996 Fix bug in handling character parameters assigned a char() value. Example: character*2 b,c character*1 esc parameter(esc = char(27)) integer i data (b(i:i),i=1,2)/esc,'a'/ data (c(i:i),i=1,2)/esc,'b'/ ! memory fault call foo(b,c) end Fri Mar 1 23:44:51 EST 1996 Fix glitch in evaluating .EQ. and .NE. when both operands are logical constants (.TRUE. or .FALSE.). Fri Mar 15 17:29:54 EST 1996 libi77: lread.c, rsfe.c: honor END= in READ stmts with empty iolist. Tue Mar 19 23:08:32 EST 1996 lex.c: arrange for a "statement" consisting of a single short bogus keyword to elicit an error message showing the whole keyword. The error message formerly omitted the last letter of the bad keyword. libf77: s_cat.c: supply missing break after overlap detection. Mon May 13 23:35:26 EDT 1996 Recognize Fortran 90's /= as a synonym for .NE.. (<> remains a synonym for .NE..) Emit an empty int function of no arguments to supply an external name to named block data subprograms (so they can be called somewhere to force them to be loaded from a library). Fix bug (memory fault) in handling the following illegal Fortran: parameter(i=1) equivalence(i,j) end Treat cdabs, cdcos, cdexp, cdlog, cdsin, and cdsqrt as synonyms for the double complex intrinsics zabs, zcos, zexp, zlog, zsin, and zsqrt, respectively, unless -cd is specified. Recognize the Fortran 90 bit-manipulation intrinsics btest, iand, ibclr, ibits, ibset, ieor, ior, ishft, and ishftc, unless -i90 is specified. Note that iand, ieor, and ior are thus now synonyms for "and", "xor", and "or", respectively. Add three macros (bit_test, bit_clear, bit_set) to f2c.h for use with btest, ibclr, and ibset, respectively. Add new functions [lq]bit_bits, [lq]bit_shift, and [lq]_bit_cshift to libF77 for use with ibits, ishft, and ishftc, respectively. Add integer function ftell(unit) (returning -1 on error) and subroutine fseek(unit, offset, whence, *) to libI77 (with branch to label * on error). Tue May 14 23:21:12 EDT 1996 Fix glitch (possible memory fault, or worse) in handling multiple entry points with names over 28 characters long. Mon Jun 10 01:20:16 EDT 1996 Update netlib E-mail and ftp addresses in f2c/readme and f2c/src/readme (which are different files) -- to reflect the upcoming breakup of AT&T. libf77: trivial tweaks to F77_aloc.c and system_.c; Version.c not changed. libi77: Adjust rsli.c and lread.c so internal list input with too few items in the input string will honor end= . Mon Jun 10 22:59:57 EDT 1996 Add Bits_per_Byte to sysdep.h and adjust definition of Table_size to depend on Bits_per_Byte (forcing Table_size to be a power of 2); in lex.c, change "comstart[c & 0xfff]" to "comstart[c & (Table_size-1)]" to avoid an out-of-range subscript on end-of-file. Wed Jun 12 00:24:28 EDT 1996 Fix bug in output.c (dereferencing a freed pointer) revealed in print * !np in out_call in output.c clobbered by free end !during out_expr. Wed Jun 19 08:12:47 EDT 1996 f2c.h: add types uinteger, ulongint (for libF77); add qbit_clear and qbit_set macros (in a commented-out section) for integer*8. For integer*8, use qbit_clear and qbit_set for ibclr and ibset. libf77: add casts to unsigned in [lq]bitshft.c. Thu Jun 20 13:30:43 EDT 1996 Complain at character*(*) in common (rather than faulting). Fix bug in recognizing hex constants that start with "16#" (e.g., 16#1234abcd, which is a synonym for z'1234abcd'). Fix bugs in constant folding of expressions involving btest, ibclr, and ibset. Fix bug in constant folding of rshift(16#80000000, -31) (on a 32-bit machine; more generally, the bug was in constant folding of rshift(ibset(0,NBITS-1), 1-NBITS) when f2c runs on a machine with long ints having NBITS bits. Mon Jun 24 07:58:53 EDT 1996 Adjust struct Literal and newlabel() function to accommodate huge source files (with more than 32767 newlabel() invocations). Omit .c file when the .f file has a missing final end statement. Wed Jun 26 14:00:02 EDT 1996 libi77: Add discussion of MXUNIT (highest allowed Fortran unit number) to libI77/README. Fri Jun 28 14:16:11 EDT 1996 Fix glitch with -onetrip: the temporary variable used for nonconstant initial loop variable values was recycled too soon. Example: do i = j+1, k call foo(i+1) ! temp for j+1 was reused here enddo end Tue Jul 2 16:11:27 EDT 1996 formatdata.c: add a 0 to the end of the basetype array (for TYBLANK) (an omission that was harmless on most machines). expr.c: fix a dereference of NULL that was only possible with buggy input, such as subroutine $sub(s) ! the '$' is erroneous character s*(*) s(1:) = ' ' end Sat Jul 6 00:44:56 EDT 1996 Fix glitch in the intrinsic "real" function when applied to a complex (or double complex) variable and passed as an argument to some intrinsic functions. Example: complex a b = sqrt(a) end Fix glitch (only visible if you do not use f2c's malloc and the malloc you do use is defective in the sense that malloc(0) returns 0) in handling include files that end with another include (perhaps followed by comments). Fix glitch with character*(*) arguments named "h" and "i" when the body of the subroutine invokes the intrinsic LEN function. Arrange that after a previous "f2c -P foo.f" has produced foo.P, running "f2c foo.P foo.f" will produce valid C when foo.f contains call sub('1234') end subroutine sub(msg) end Specifically, the length argument in "call sub" is now suppressed. With or without foo.P, it is also now suppressed when the order of subprograms in file foo.f is reversed: subroutine sub(msg) end call sub('1234') end Adjust copyright notices to reflect AT&T breakup. Wed Jul 10 09:25:49 EDT 1996 Fix bug (possible memory fault) in handling erroneously placed and inconsistent declarations. Example that faulted: character*1 w(8) call foo(w) end subroutine foo(m) data h /0.5/ integer m(2) ! should be before data end Fix bug (possible fault) in handling illegal "if" constructions. Example (that faulted): subroutine foo(i,j) if (i) then ! bug: i is integer, not logical else if (j) then ! bug: j is integer, not logical endif end Fix glitch with character*(*) argument named "ret_len" to a character*(*) function. Wed Jul 10 23:04:16 EDT 1996 Fix more glitches in the intrinsic "real" function when applied to a complex (or double complex) variable and passed as an argument to some intrinsic functions. Example: complex a, b r = sqrt(real(conjg(a))) + sqrt(real(a*b)) end Thu Jul 11 17:27:16 EDT 1996 Fix a memory fault associated with complicated, illegal input. Example: subroutine goo character a call foo(a) ! inconsistent with subsequent def and call end subroutine foo(a) end call foo(a) end Wed Jul 17 19:18:28 EDT 1996 Fix yet another case of intrinsic "real" applied to a complex argument. Example: complex a(3) x = sqrt(real(a(2))) ! gave error message about bad tag end Mon Aug 26 11:28:57 EDT 1996 Tweak sysdep.c for non-Unix systems in which process ID's can be over 5 digits long. Tue Aug 27 08:31:32 EDT 1996 Adjust the ishft intrinsic to use unsigned right shifts. (Previously, a negative constant second operand resulted in a possibly signed shift.) Thu Sep 12 14:04:07 EDT 1996 equiv.c: fix glitch with -DKR_headers. libi77: fmtlib.c: fix bug in printing the most negative integer. Fri Sep 13 08:54:40 EDT 1996 Diagnose some illegal appearances of substring notation. Tue Sep 17 17:48:09 EDT 1996 Fix fault in handling some complex parameters. Example: subroutine foo(a) double complex a, b parameter(b = (0,1)) a = b ! f2c faulted here end Thu Sep 26 07:47:10 EDT 1996 libi77: fmt.h: for formatted writes of negative integer*1 values, make ic signed on ANSI systems. If formatted writes of integer*1 values trouble you when using a K&R C compiler, switch to an ANSI compiler or use a compiler flag that makes characters signed. Tue Oct 1 14:41:36 EDT 1996 Give a better error message when dummy arguments appear in data statements. Thu Oct 17 13:37:22 EDT 1996 Fix bug in typechecking arguments to character and complex (or double complex) functions; the bug could cause length arguments for character arguments to be omitted on invocations appearing textually after the first invocation. For example, in subroutine foo character c complex zot call goo(zot(c), zot(c)) end the length was omitted from the second invocation of zot, and there was an erroneous error message about inconsistent calling sequences. Wed Dec 4 13:59:14 EST 1996 Fix bug revealed by subroutine test(cdum,rdum) complex cdum rdum=cos(real(cdum)) ! "Unexpected tag 3 in opconv_fudge" end Fix glitch in parsing "DO 10 D0 = 1, 10". Fix glitch in parsing real*8 x real*8 x ! erroneous "incompatible type" message call foo(x) end Mon Dec 9 23:15:02 EST 1996 Fix glitch in parameter adjustments for arrays whose lower bound depends on a scalar argument. Example: subroutine bug(p,z,m,n) integer z(*),m,n double precision p(z(m):z(m) + n) ! p_offset botched call foo(p(0), p(n)) end libi77: complain about non-positive rec= in direct read and write statements. libf77: trivial adjustments; Version.c not changed. Wed Feb 12 00:18:03 EST 1997 output.c: fix (seldom problematic) glitch in out_call: put parens around the ... in a test of the form "if (q->tag == TADDR && ...)". vax.c: fix bug revealed in the "psi_offset =" assignment in the following example: subroutine foo(psi,m) integer z(100),m common /a/ z double precision psi(z(m):z(m) + 10) call foo(m+1, psi(0),psi(10)) end Mon Feb 24 23:44:54 EST 1997 For consistency with f2c's current treatment of adjacent character strings in FORMAT statements, recognize a Hollerith string following a string (and merge adjacent strings in FORMAT statements). Wed Feb 26 13:41:11 EST 1997 New libf2c.zip, a combination of the libf77 and libi77 bundles (and available only by ftp). libf77: adjust functions with a complex output argument to permit aliasing it with input arguments. (For now, at least, this is just for possible benefit of g77.) libi77: tweak to ftell_.c for systems with strange definitions of SEEK_SET, etc. Tue Apr 8 20:57:08 EDT 1997 libf77: [cz]_div.c: tweaks invisible on most systems (that may improve things slightly with optimized compilation on systems that use gratuitous extra precision). libi77: fmt.c: adjust to complain at missing numbers in formats (but still treat missing ".nnn" as ".0"). Fri Apr 11 14:05:57 EDT 1997 libi77: err.c: attempt to make stderr line buffered rather than fully buffered. (Buffering is needed for format items T and TR.) Thu Apr 17 22:42:43 EDT 1997 libf77: add F77_aloc.o to makefile (and makefile.u in libf2c.zip). Fri Apr 25 19:32:09 EDT 1997 libf77: add [de]time_.c (which may give trouble on some systems). Tue May 27 09:18:52 EDT 1997 libi77: ftell_.c: fix typo that caused the third argument to be treated as 2 on some systems. Mon Jun 9 00:04:37 EDT 1997 libi77 (and libf2c.zip): adjust include order in err.c lread.c wref.c rdfmt.c to include fmt.h (etc.) after system includes. Version.c not changed. Mon Jul 21 16:04:54 EDT 1997 proc.c: fix glitch in logic for "nonpositive dimension" message. libi77: inquire.c: always include string.h (for possible use with -DNON_UNIX_STDIO); Version.c not changed. Thu Jul 24 17:11:23 EDT 1997 Tweak "Notice" to reflect the AT&T breakup -- we missed it when updating the copyright notices in the source files last summer. Adjust src/makefile so malloc.o is not used by default, but can be specified with "make MALLOC=malloc.o". Add comments to src/README about the "CRAY" T3E. Tue Aug 5 14:53:25 EDT 1997 Add definition of calloc to malloc.c; this makes f2c's malloc work on some systems where trouble hitherto arose because references to calloc brought in the system's malloc. (On sensible systems, calloc is defined separately from malloc. To avoid confusion on other systems, f2c/malloc.c now defines calloc.) libi77: lread.c: adjust to accord with a change to the Fortran 8X draft (in 1990 or 1991) that rescinded permission to elide quote marks in namelist input of character data; to get the old behavior, compile with F8X_NML_ELIDE_QUOTES #defined. wrtfmt.o: wrt_G: tweak to print the right number of 0's for zero under G format. Sat Aug 16 05:45:32 EDT 1997 libi77: iio.c: fix bug in internal writes to an array of character strings that sometimes caused one more array element than required by the format to be blank-filled. Example: format(1x). Wed Sep 17 00:39:29 EDT 1997 libi77: fmt.[ch] rdfmt.c wrtfmt.c: tweak struct syl for machines with 64-bit pointers and 32-bit ints that did not 64-bit align struct syl (e.g., Linux on the DEC Alpha). This change should be invisible on other machines. Sun Sep 21 22:05:19 EDT 1997 libf77: [de]time_.c (Unix systems only): change return type to double. Thu Dec 4 22:10:09 EST 1997 Fix bug with handling large blocks of comments (over 4k); parts of the second and subsequent blocks were likely to be lost (not copied into comments in the resulting C). Allow comment lines to be longer before breaking them. Mon Jan 19 17:19:27 EST 1998 makefile: change the rule for making gram.c to one for making gram1.c; henceforth, asking netlib to "send all from f2c/src" will bring you a working gram.c. Nowadays there are simply too many broken versions of yacc floating around. libi77: backspace.c: for b->ufmt==0, change sizeof(int) to sizeof(uiolen). On machines where this would make a difference, it is best for portability to compile libI77 with -DUIOLEN_int, which will render the change invisible. Tue Feb 24 08:35:33 EST 1998 makefile: remove gram.c from the "make clean" rule. Wed Feb 25 08:29:39 EST 1998 makefile: change CFLAGS assignment to -O; add "veryclean" rule. Wed Mar 4 13:13:21 EST 1998 libi77: open.c: fix glitch in comparing file names under -DNON_UNIX_STDIO. Mon Mar 9 23:56:56 EST 1998 putpcc.c: omit an unnecessary temporary variable in computing (expr)**3. libf77, libi77: minor tweaks to make some C++ compilers happy; Version.c not changed. Wed Mar 18 18:08:47 EST 1998 libf77: minor tweaks to [ed]time_.c; Version.c not changed. libi77: endfile.c, open.c: acquire temporary files from tmpfile(), unless compiled with -DNON_ANSI_STDIO, which uses mktemp(). New buffering scheme independent of NON_UNIX_STDIO for handling T format items. Now -DNON_UNIX_STDIO is no longer be necessary for Linux, and libf2c no longer causes stderr to be buffered -- the former setbuf or setvbuf call for stderr was to make T format items work. open.c: use the Posix access() function to check existence or nonexistence of files, except under -DNON_POSIX_STDIO, where trial fopen calls are used. In open.c, fix botch in changes of 19980304. libf2c.zip: the PC makefiles are now set for NT/W95, with comments about changes for DOS. Fri Apr 3 17:22:12 EST 1998 Adjust fix of 19960913 to again permit substring notation on character variables in data statements. Sun Apr 5 19:26:50 EDT 1998 libi77: wsfe.c: make $ format item work: this was lost in the changes of 17 March 1998. Sat May 16 19:08:51 EDT 1998 Adjust output of ftnlen constants: rather than appending L, prepend (ftnlen). This should make the resulting C more portable, e.g., to systems (such as DEC Alpha Unix systems) on which long may be longer than ftnlen. Adjust -r so it also casts REAL expressions passed to intrinsic functions to REAL. Wed May 27 16:02:35 EDT 1998 libf2c.zip: tweak description of compiling libf2c for INTEGER*8 to accord with makefile.u rather than libF77/makefile. Thu May 28 22:45:59 EDT 1998 libi77: backspace.c dfe.c due.c iio.c lread.c rsfe.c sue.c wsfe.c: set f__curunit sooner so various error messages will correctly identify the I/O unit involved. libf2c.zip: above, plus tweaks to PC makefiles: for some purposes, it's still best to compile with -DMSDOS (even for use with NT). Thu Jun 18 01:22:52 EDT 1998 libi77: lread.c: modified so floating-point numbers (containing either a decimal point or an exponent field) are treated as errors when they appear as list input for integer data. Compile lread.c with -DALLOW_FLOAT_IN_INTEGER_LIST_INPUT to restore the old behavior. Mon Aug 31 10:38:54 EDT 1998 formatdata.c: if possible, and assuming doubles must be aligned on double boundaries, use existing holes in DATA for common blocks to force alignment of the block. For example, block data common /abc/ a, b double precision a integer b(2) data b(2)/1/ end used to generate struct { integer fill_1[3]; integer e_2; doublereal e_3; } abc_ = { {0}, 1, 0. }; and now generates struct { doublereal fill_1[1]; integer fill_2[1]; integer e_3; } abc_ = { {0}, {0}, 1 }; In the old generated C, e_3 was added to force alignment; in the new C, fill_1 does this job. Mon Sep 7 19:48:51 EDT 1998 libi77: move e_wdfe from sfe.c to dfe.c, where it was originally. Why did it ever move to sfe.c? Tue Sep 8 10:22:50 EDT 1998 Treat dreal as a synonym for dble unless -cd is specified on the command line. Sun Sep 13 22:23:41 EDT 1998 format.c: fix bug in writing prototypes under f2c -A ... *.P: under some circumstances involving external functions with no known type, a null pointer was passed to printf. Tue Oct 20 23:25:54 EDT 1998 Comments added to libf2c/README and libF77/README, pointing out the need to modify signal1.h on some systems. Wed Feb 10 22:59:52 EST 1999 defs.h lex.c: permit long names (up to at least roughly MAX_SHARPLINE_LEN = 1000 characters long) in #line lines (which only matters under -g). fc: add -U option; recognize .so files. Sat Feb 13 10:18:27 EST 1999 libf2c: endfile.c, lread.c, signal1.h0: minor tweaks to make some (C++) compilers happier; f77_aloc.c: make exit_() visible to C++ compilers. Version strings not changed. Thu Mar 11 23:14:02 EST 1999 Modify f2c (exec.c, expr.c) to diagnose incorrect mixing of types when (f2c extended) intrinsic functions are involved, as in (not(17) .and. 4). Catching this in the first executable statement is a bit tricky, as some checking must be postponed until all statement function declarations have been parsed. Thus there is a chance of today's changes introducing bugs under (let us hope) unusual conditions. Sun Mar 28 13:17:44 EST 1999 lex.c: tweak to get the file name right in error messages caused by statements just after a # nnn "filename" line emitted by the C preprocessor. (The trouble is that the line following the # nnn line must be read to see if it is a continuation of the stuff that preceded the # nnn line.) When # nnn "filename" lines appear among the lines for a Fortran statement, the filename reported in an error message for the statement should now be the file that was current when the first line of the statement was read. Sun May 2 22:38:25 EDT 1999 libf77, libi77, libf2c.zip: make getenv_() more portable (call getenv() rather than knowing about char **environ); adjust some complex intrinsics to work with overlapping arguments (caused by inappropriate use of equivalence); open.c: get "external" versus "internal" right in the error message if a file cannot be opened; err.c: cast a pointer difference to (int) for %d; rdfmt.c: omit fixed-length buffer that could be overwritten by formats Inn or Lnn with nn > 83. Mon May 3 13:14:07 EDT 1999 "Invisible" changes to omit a few compiler warnings in f2c and libf2c; two new casts in libf2c/open.c that matter with 64-bit longs, and one more tweak (libf2c/c_log.c) for pathological equivalences. Minor update to "fc" script: new -L flag and comment correction. Fri Jun 18 02:33:08 EDT 1999 libf2c.zip: rename backspace.c backspac.c, and fix a glitch in it -- b->ufd may change in t_runc(). (For now, it's still backspace.c in the libi77 bundle.) Sun Jun 27 22:05:47 EDT 1999 libf2c.zip, libi77: rsne.c: fix bug in namelist input: a misplaced increment could cause wrong array elements to be assigned; e.g., "&input k(5)=10*1 &end" assigned k(5) and k(15 .. 23). Tue Sep 7 14:10:24 EDT 1999 f2c.h, libf2c/f2c.h0, libf2c/README: minor tweaks so a simple sed command converts f2c.h == libf2c/f2c.h0 to a form suitable for machines with 8-byte longs and doubles, 4-byte int's and floats, while working with a forthcoming (ill-advised) update to the C standard that outlaws plain "unsigned". f2c.h, libf2c/f2c.h0: change "if 0" to "#ifdef INTEGER_STAR_8". libf77, libf2c.zip: [cz]_div.c and README: arrange for compilation under -DIEEE_COMPLEX_DIVIDE to make these routines avoid calling sig_die when the denominator of a complex or double complex division vanishes; instead, they return pairs of NaNs or Infinities, depending whether the numerator also vanishes or not. Tue Oct 5 23:50:14 EDT 1999 formatdata.c, io.c, output.c, sysdep.c: adjust to make format strings legal when they contain 8-bit characters with the high bit on. (For many C compilers, this is not necessary, but it the ANSI/ISO C standard does not require this to work.) libf2c.zip: tweak README and correct xsum0.out. Mon Oct 25 17:30:54 EDT 1999 io.c: fix glitch introduced in the previous change (19991005) that caused format(' %') to print "%%" rather than "%". Mon Nov 15 12:10:35 EST 1999 libf2c.zip: fix bug with the sequence backspace(n); endfile(n); rewind(n); read(n). Supply missing (long) casts in a couple of places where they matter when size(ftnint) == sizeof(int) < sizeof(long). Tue Jan 18 19:22:24 EST 2000 Arrange for parameter statements involving min(...) and max(...) functions of three or more arguments to work. Warn about text after "end" (rather than reporting a syntax error with a surprising line number). Accept preprocessor line numbers of the form "# 1234" (possibly with trailing blanks). Accept a comma after write(...) and before a list of things to write. Fri Jan 21 17:26:27 EST 2000 Minor updates to make compiling Win32 console binaries easier. A side effect is that the MSDOS restriction of only one Fortran file per invocation is lifted (and "f2c *.f") works. Tue Feb 1 18:38:32 EST 2000 f2c/src/tokdefs.h added (to help people on non-Unix systems -- the makefile has always had a rule for generating tokdefs.h). Fri Mar 10 18:48:17 EST 2000 libf77, libf2c.zip: z_log.c: the real part of the double complex log of numbers near, e.g., (+-1,eps) with |eps| small is now more accurate. For example if z = (1,1d-7), then "write(*,*) z" now writes "(5.E-15,1.E-07" rather than the previous "(4.88498131E-15,1.E-07)". Thu Apr 20 13:02:54 EDT 2000 libf77, libi77, libf2c.zip: s_cat.c, rsne.c, xwsne.c: fix type errors that only matter if sizeof(ftnint) != sizeof(ftnlen). Tue May 30 23:36:18 EDT 2000 expr.c: adjust subcheck() to use a temporary variable of type TYLONG rather than TYSHORT under -C -I2. Wed May 31 08:48:03 EDT 2000 Simplify yesterday's adjustment; today's change should be invisible. Tue Jul 4 22:52:21 EDT 2000 misc.c, function "addressable": fix fault with "f2c -I2 foo.f" when foo.f consists of the 4 lines subroutine foo(c) character*(*) c i = min(len(c),23) end Sundry files: tweaks for portability, e.g., for compilation by overly fastidious C++ compilers; "false" and "true" now treated as C keywords (so they get two underscores appended). libf77, libi77, libf2c.zip: "invisible" adjustments to permit compilation by C++ compilers; version numbers not changed. Thu Jul 6 23:46:07 EDT 2000 Various files: tweaks to banish more compiler warnings. lib?77, libf2c.zip/makefile.u: add "|| true" to ranlib invocations. Thanks to Nelson H. F. Beebe for messages leading to these changes (and to many of the ones two days ago). xsum.c: tweak include order. Fri Jul 7 18:01:25 EDT 2000 fc: accept -m xxx or -mxxx, pass them to the compiler as -mxxx (suggestion of Nelson Beebe). Note that fc simply appends to CFLAGS, so system-specific stuff can be supplied in the environment variable CFLAGS. With some shells, invocations of the form CFLAGS='system-specific stuff' fc ... are one way to do this. Thu Aug 17 21:38:36 EDT 2000 Fix obscure glitch: in "Error on line nnn of ...: Bad # line:...", get nnn right. Sat Sep 30 00:28:30 EDT 2000 libf77, libf2c.zip: dtime_.c, etime_.c: use floating-point divide; dtime_.d, erf_.c, erfc_.c, etime.c: for use with "f2c -R", compile with -DREAL=float. Tue Dec 5 22:55:56 EST 2000 lread.c: under namelist input, when reading a logical array, treat Tstuff= and Fstuff= as new assignments rather than as logical constants. Fri Feb 23 00:43:56 EST 2001 libf2c: endfile.c: adjust to use truncate() unless compiled with -DNO_TRUNCATE (or with -DMSDOS). Add libf2c/mkfile.plan9. Sat Feb 24 21:14:24 EST 2001 Prevent malloc(0) when a subroutine of no arguments has an entry with no arguments, as in subroutine foo entry goo end Fix a fault that was possible when MAIN (illegally) had entry points. Fix a buffer overflow connected with the error message for names more than MAXNAMELEN (i.e., 50) bytes long. Fix a bug in command-line argument passing that caused the invocation "f2c -!czork foo.f" to complain about two invalid flags ('-ork' and '-oo.f') instead of just one ('-ork'). fc: add -s option (strip executable); portability tweaks. Adjustments to handing of integer*8 to permit processing 8-byte hex, binary, octal, and decimal constants. The adjustments are only available when type long long (for >= 64 bit integers) is available to f2c; they are assumed available unless f2c is compiled with either -DNO_TYQUAD or -DNO_LONGLONG. As has long been the case, compilation of f2c itself with -DNO_TYQUAD eliminates recognition of integer*8 altogether. Compilation with just -DNO_LONGLONG permits the previous handling of integer*8, which could only handle 32-bit constants associated with integer*8 variables. New command-line argument -i8const (available only when f2c itself is compiled with neither -DNO_TYQUAD nor -DNO_LONGLONG) suppresses the new automatic promotion of integer constants too long to express as 32-bit values to type integer*8. There are corresponding updates to f2c.1 and f2c.1t. Wed Feb 28 00:50:04 EST 2001 Adjust misc.c for (older) systems that recognize long long but do not have LLONG_MAX or LONGLONG_MAX in limits.h. main.c: filter out bad files before dofork loop to avoid trouble in Win32 "f2c.exe" binaries. Thu Mar 1 16:25:19 EST 2001 Cosmetic change for consistency with some other netlib directories: change NO_LONGLONG to NO_LONG_LONG. (This includes adjusting the above entry for Feb 23 2001.) No change (other than timestamp) to version.c. libf2c: endfile.c: switch to ftruncate (absent -DNO_TRUNCATE), thus permitting truncation of scratch files on true Unix systems, where scratch files have no name. Add an fflush() (surprisingly) needed on some Linux systems. Tue Mar 20 22:03:23 EST 2001 expr.c: complain ("impossible conversion") about attempts to assign character expressions ... to integer variables, rather than implicitly assigning ichar(...). Sat Jun 23 23:08:22 EDT 2001 New command-line option -trapuv adds calls on _uninit_f2c() to prologs to dynamically initialize local variables, except those appearing in SAVE or DATA statements, with values that may help find references to uninitialized variables. For example, with IEEE arithmetic, floating- point variables are initialized to signaling NaNs. expr.c: new warning for out-of-bounds constant substring expressions. Under -C, such expressions now inhibit C output. libf2c/mkfile.plan9: fix glitch with rule for "check" (or xsum.out). libf2c.zip: add uninit.c (for _uninit_f2c()) in support of -trapuv. fc, f2c.1, f2c.1t: adjust for -trapuv. Thu Jul 5 22:00:51 EDT 2001 libf2c.zip: modify uninit.c for __mc68k__ under Linux. Wed Aug 22 08:01:37 EDT 2001 cds.c, expr.c: in constants, preserve the sign of 0. expr.c: fix some glitches in folding constants to integer*8 (when NO_LONG_LONG is not #defined). intr.c: fold constant min(...) and max(...) expressions. Fri Nov 16 02:00:03 EST 2001 libf2c.zip: tweak to permit handling files over 2GB long where possible, with suitable -D options, provided for some systems in new header file sysdep1.h (copied from sysdep1.h0 by default). Add an fseek to endfile.c to fix a glitch on some systems. Wed Nov 28 17:58:12 EST 2001 libf2c.zip: on IEEE systems, print -0 as -0 when the relevant libf2c/makefile.* is suitably adjusted: see comments about -DSIGNED_ZEROS in libf2c/makefile.*. Fri Jan 18 16:17:44 EST 2002 libf2c.zip: fix bugs (reported by Holger Helmke) in qbit_bits(): wrong return type, missing ~ on y in return value. This affects the intrinsic ibits function for first argument of type integer*8. Thu Feb 7 17:14:43 EST 2002 Fix bug handling leading array dimensions in common: invalid C resulted. Example (after one provided by Dmitry G. Baksheyev): subroutine foo(a) common/c/m integer m, n equivalence(m,n) integer a(n,2) a(1,2) = 3 end Fix a bug, apparently introduced sometime after 19980913, in handling certain substring expressions that involve temporary assignments and the first invocation of an implicitly typed function. When the expressions appeared in "else if (...)" and "do while(...)", the temporary assignments appeared too soon. Examples are hard to find, but here is one (after an example provided by Nat Bachman): subroutine foo(n) character*8 s do while (moo(s(n+1:n+2)) .ge. 2) n = n + 1 enddo end It is hard for f2c to get this sort of example correct when the "untyped" function is a generic intrinsic. When incorrect code would otherwise result, f2c now issues an error message and declines to produce C. For example, subroutine foo(n) character*8 s double precision goo do while (sin(goo(s(n+1:n+2))) .ge. 2) n = n + 1 enddo end gives the new error message, but both subroutine foo(n) character*8 s double precision goo do while (dsin(goo(s(n+1:n+2))) .ge. 2) n = n + 1 enddo end and subroutine foo(n) character*8 s double precision goo do while (sin(goo(min(n, (n-3)**2))) .ge. 2) n = n + 1 enddo end give correct C. Fri Feb 8 08:43:40 EST 2002 Make a cleaner fix of the bug fixed yesterday in handling certain "do while(...)" and "else if (...)" constructs involving auxiliary assignments. (Yesterday's changes to expr.c are recanted; expr.c is now restored to that of 20010820.) Now subroutine foo(n) character*8 s double precision goo do while (sin(goo(s(n+1:n+2))) .ge. 0.2) n = n + 1 enddo end is correctly translated. Thu Mar 14 12:53:08 EST 2002 lex.c: adjust to avoid an error message under -72 when source files are in CRLF form ("text mode" on Microsoft systems), a source line is exactly 72 characters long, and f2c is run on a system (such as a Unix or Linux system) that does not distinguish text and binary modes. Example (in CRLF form): write(*,*)"Hello world, with a source line that is 72 chars long." end libf2c/z_log.c: add code to cope with buggy compilers (e.g., some versions of gcc under -O2 or -O3) that do floating-point comparisons against values computed into extended-precision registers on some systems (such as Intel IA32 systems). Compile with -DNO_DOUBLE_EXTENDED to omit the kludge that circumvents this bug. Thu May 2 19:09:01 EDT 2002 src/misc.c, src/sysdep.h, src/gram.c: tweaks for KR_headers (a rare concern today); version.c touched but left unchanged. libf2c: fix glitch in makefile.vc; KR_header tweaks in s_stop.c and uninit.c (which also had a misplaced #endif). Wed Jun 5 16:13:34 EDT 2002 libf2c: uninit.c: for Linux on an ARM processor, add some #ifndef _FPU... tests; f77vers.c not changed. Tue Jun 25 15:13:32 EDT 2002 New command-line option -K requests old-style ("K&R") C. The default is changed to -A (ANSI/ISO style). Under -K, cast string-length arguments to (ftnlen). This should matter only in the unusual case that "readme" instructs obtaining f2c.h by sed 's/long int /long long /' f2c.h0 >f2c.h Increase defaults for some table sizes: make -Nn802 -Nq300 -Nx400 the default. Fri Sep 6 18:39:24 EDT 2002 libf2c.zip: rsne.c: fix bug with multiple repeat counts in reading namelists, e.g., &nl a(2) = 3*1.0, 2*2.0, 3*3.0 / (Bug found by Jim McDonald, reported by Toon Moene.) Fri Oct 4 10:23:51 EDT 2002 libf2c.zip: uninit.c: on IRIX systems, omit references to shell variables (a dreg). This only matters with f2c -trapuv . Thu Dec 12 22:16:00 EST 2002 proc.c: tweak to omit "* 1" from "a_offset = 1 + a_dim1 * 1;". libf2c.zip: uninit.c: adjust to work with HP-UX B.11.11 as well as HP-UX B.10.20; f77vers.c not changed. Tue Feb 11 08:19:54 EST 2003 Fix a fault with f2c -s on the following example of invalid Fortran (reported by Nickolay A. Khokhlov); "function" should appear before "cat" on the first line: character*(*) cat(a, b) character*(*) a, b cat = a // b end Issue warnings about inappropriate uses of arrays a, b, c and pass a temporary for d in real a(2), b(2), c(2), d call foo((a), 1*b, +c, +d) end (correcting bugs reported by Arnaud Desitter). Thu Mar 6 22:48:08 EST 2003 output.c: fix a bug leading to "Unexpected tag 4 in opconv_fudge" when f2c -s processes the real part of a complex array reference. Example (simplified from netlib/linpack/zchdc.f): subroutine foo(a,work,n,k) integer k, n complex*16 a(n,n), work(n) work(k) = dcmplx(dsqrt(dreal(a(k,k))),0.0d0) end (Thanks to Nickolay A. Khokhlov for the bug report.) Thu Mar 20 13:50:12 EST 2003 format.c: code around a bug (reported by Nelson H. F. Beebe) in some versions of FreeBSD. Compiling with __FreeBSD__ but not NO_FSCANF_LL_BUG #defined or with FSCANF_LL_BUG #defined causes special logic to replace fscanf(infile, "%llx", result) with custom logic. Here's an example (from Beebe) where the bug bit: integer*8 m, n m = 9223372036854775807 end Fri Mar 21 13:14:05 EST 2003 libf2c.zip: err.c: before writing to a file after reading from it, do an f_seek(file, 0, SEEK_CUR) to make writing legal in ANSI C. Fri Jun 6 14:56:44 EDT 2003 libf2c.zip: add comments about libf2c.so (and a rule that works under Linux, after an adjustment to the CFLAGS = line) to libf2c/makefile.u. Sat Oct 25 07:57:53 MDT 2003 README, main.c, sysdep.c: adjust comments about libf2c and expand the comments thereon in the C that f2c writes (since too few people read the README files). Change makefile to makefile.u (with the expectation that people will "cp makefile.u makefile" and edit makefile if necessary) and add makefile.vc (for Microsoft Visual C++). Thu Oct 7 23:25:28 MDT 2004 names.c: for convenience of MSVC++ users, map "cdecl" to "cdecl__". Fri Mar 4 18:40:48 MST 2005 sysdep.c, makefile.u, new file sysdeptest.c: changes in response to a message forwarded by Eric Grosse from Thierry Carrez (who is apparently unaware of f2c's -T option) about an unlikely security issue: that a local attacker could plant symbolic links in /tmp corresponding to temporary file names that f2c generates and thus cause overwriting of arbitrary files. Today's change is that if neither -T nor the unusual debugging flag -Dn is specified and the system is not an MS-Windows system (which cannot have symbolic links, as far as I know), then f2c's temporary files will be written in a temporary directory that is readable and writable only by the user and that is removed at the end of f2c's execution. To disable today's change, compile sysdep.c with -DNO_TEMPDIR (i.e., with NO_TEMPDIR #defined). Sun Mar 27 20:06:49 MST 2005 sysdep.c: in set_tmp_names(), fix botched placement of "if (debugflag == 1) return;": move it below declarations. Sun May 1 21:45:46 MDT 2005 sysdep.c: fix a possible fault under -DMSDOS and improper handling of a tmpnam failure under the unusual combination of both -DNO_MKDTEMP and -DNO_MKSTEMP (without -DNO_TEMPDIR). Tue Oct 4 23:38:54 MDT 2005 libf2c.zip: uninit.c: on IA32 Linux systems, leave the rounding precision alone rather than forcing it to 53 bits; compile with -DUNINIT_F2C_PRECISION_53 to get the former behavior. This only affects Fortran files translated by f2c -trapuv . Sun May 7 00:38:59 MDT 2006 main.c, version.c: add options -? (or --help) that print out pointers to usage documentation and -v (or --version) that print the current version. fc script: fix botch with -O[123]; recognize --version (or -v) and --help (or -?). Add f2c.pdf == PDF version of f2c.ps. Sun Oct 8 02:45:04 MDT 2006 putpcc.c: fix glitch in subscripting complex variables: subscripts of type integer*8 were converted to integer*4, which causes trouble when 32-bit addressing does not suffice. Tue Sep 11 23:54:05 MDT 2007 xsum.c: insert explicit "int" before main. Mon Dec 3 20:53:24 MST 2007 libf2c/main.c: insert explicit "int" before main. Sat Apr 5 21:39:57 MDT 2008 libf2c.zip: tweaks for political C++ and const correctness, and to fix ctype trouble in some recent Linux versions. No behavior should change. Sun Apr 6 22:38:56 MDT 2008 libf2c.zip: adjust alternate makefiles to reflect yesterday's change. Wed Nov 26 23:23:27 MST 2008 libf2c.zip: add brief discussion of MacOSX to comments in makefile.u. Fri Jan 2 23:13:25 MST 2009 libf2c.zip: add -DNO_ISATTY to CFLAGS assignment in makefile.vc. Sat Apr 11 18:06:00 MDT 2009 src/sysdep.c src/sysdeptest.c: tweak for MacOSX (include ). NOTE: the old libf77 and libi77 bundles are no longer being updated. Use libf2c.zip instead. python-igraph-0.8.0/vendor/source/igraph/src/f2c/d_tan.c0000644000076500000240000000036113524616145023310 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double tan(); double d_tan(x) doublereal *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double d_tan(doublereal *x) #endif { return( tan(*x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/backspac.c0000644000076500000240000000246013524616145023774 0ustar tamasstaff00000000000000#include "f2c.h" #include "fio.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers integer f_back(a) alist *a; #else integer f_back(alist *a) #endif { unit *b; OFF_T v, w, x, y, z; uiolen n; FILE *f; f__curunit = b = &f__units[a->aunit]; /* curunit for error messages */ if(a->aunit >= MXUNIT || a->aunit < 0) err(a->aerr,101,"backspace") if(b->useek==0) err(a->aerr,106,"backspace") if(b->ufd == NULL) { fk_open(1, 1, a->aunit); return(0); } if(b->uend==1) { b->uend=0; return(0); } if(b->uwrt) { t_runc(a); if (f__nowreading(b)) err(a->aerr,errno,"backspace") } f = b->ufd; /* may have changed in t_runc() */ if(b->url>0) { x=FTELL(f); y = x % b->url; if(y == 0) x--; x /= b->url; x *= b->url; (void) FSEEK(f,x,SEEK_SET); return(0); } if(b->ufmt==0) { FSEEK(f,-(OFF_T)sizeof(uiolen),SEEK_CUR); fread((char *)&n,sizeof(uiolen),1,f); FSEEK(f,-(OFF_T)n-2*sizeof(uiolen),SEEK_CUR); return(0); } w = x = FTELL(f); z = 0; loop: while(x) { x -= x < 64 ? x : 64; FSEEK(f,x,SEEK_SET); for(y = x; y < w; y++) { if (getc(f) != '\n') continue; v = FTELL(f); if (v == w) { if (z) goto break2; goto loop; } z = v; } err(a->aerr,(EOF),"backspace") } break2: FSEEK(f, z, SEEK_SET); return 0; } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/d_asin.c0000644000076500000240000000036513524616145023464 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double asin(); double d_asin(x) doublereal *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double d_asin(doublereal *x) #endif { return( asin(*x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/endfile.c0000644000076500000240000000542613524616145023640 0ustar tamasstaff00000000000000#include "f2c.h" #include "fio.h" /* Compile this with -DNO_TRUNCATE if unistd.h does not exist or */ /* if it does not define int truncate(const char *name, off_t). */ #ifdef MSDOS #undef NO_TRUNCATE #define NO_TRUNCATE #endif #ifndef NO_TRUNCATE #include "unistd.h" #endif #ifdef KR_headers extern char *strcpy(); extern FILE *tmpfile(); #else #undef abs #undef min #undef max #include "stdlib.h" #include "string.h" #ifdef __cplusplus extern "C" { #endif #endif extern char *f__r_mode[], *f__w_mode[]; #ifdef KR_headers integer f_end(a) alist *a; #else integer f_end(alist *a) #endif { unit *b; FILE *tf; if(a->aunit>=MXUNIT || a->aunit<0) err(a->aerr,101,"endfile"); b = &f__units[a->aunit]; if(b->ufd==NULL) { char nbuf[10]; sprintf(nbuf,"fort.%ld",(long)a->aunit); if (tf = FOPEN(nbuf, f__w_mode[0])) fclose(tf); return(0); } b->uend=1; return(b->useek ? t_runc(a) : 0); } #ifdef NO_TRUNCATE static int #ifdef KR_headers copy(from, len, to) FILE *from, *to; register long len; #else copy(FILE *from, register long len, FILE *to) #endif { int len1; char buf[BUFSIZ]; while(fread(buf, len1 = len > BUFSIZ ? BUFSIZ : (int)len, 1, from)) { if (!fwrite(buf, len1, 1, to)) return 1; if ((len -= len1) <= 0) break; } return 0; } #endif /* NO_TRUNCATE */ int #ifdef KR_headers t_runc(a) alist *a; #else t_runc(alist *a) #endif { OFF_T loc, len; unit *b; int rc; FILE *bf; #ifdef NO_TRUNCATE FILE *tf; #endif b = &f__units[a->aunit]; if(b->url) return(0); /*don't truncate direct files*/ loc=FTELL(bf = b->ufd); FSEEK(bf,(OFF_T)0,SEEK_END); len=FTELL(bf); if (loc >= len || b->useek == 0) return(0); #ifdef NO_TRUNCATE if (b->ufnm == NULL) return 0; rc = 0; fclose(b->ufd); if (!loc) { if (!(bf = FOPEN(b->ufnm, f__w_mode[b->ufmt]))) rc = 1; if (b->uwrt) b->uwrt = 1; goto done; } if (!(bf = FOPEN(b->ufnm, f__r_mode[0])) || !(tf = tmpfile())) { #ifdef NON_UNIX_STDIO bad: #endif rc = 1; goto done; } if (copy(bf, (long)loc, tf)) { bad1: rc = 1; goto done1; } if (!(bf = FREOPEN(b->ufnm, f__w_mode[0], bf))) goto bad1; rewind(tf); if (copy(tf, (long)loc, bf)) goto bad1; b->uwrt = 1; b->urw = 2; #ifdef NON_UNIX_STDIO if (b->ufmt) { fclose(bf); if (!(bf = FOPEN(b->ufnm, f__w_mode[3]))) goto bad; FSEEK(bf,(OFF_T)0,SEEK_END); b->urw = 3; } #endif done1: fclose(tf); done: f__cf = b->ufd = bf; #else /* NO_TRUNCATE */ if (b->urw & 2) fflush(b->ufd); /* necessary on some Linux systems */ #ifndef FTRUNCATE #define FTRUNCATE ftruncate #endif rc = FTRUNCATE(fileno(b->ufd), loc); /* The following FSEEK is unnecessary on some systems, */ /* but should be harmless. */ FSEEK(b->ufd, (OFF_T)0, SEEK_END); #endif /* NO_TRUNCATE */ if (rc) err(a->aerr,111,"endfile"); return 0; } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/abort_.c0000644000076500000240000000046013524616145023471 0ustar tamasstaff00000000000000#include "stdio.h" #include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers extern VOID sig_die(); int abort_() #else extern void sig_die(const char*,int); int abort_(void) #endif { sig_die("Fortran abort routine called", 1); return 0; /* not reached */ } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/d_acos.c0000644000076500000240000000036513524616145023457 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double acos(); double d_acos(x) doublereal *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double d_acos(doublereal *x) #endif { return( acos(*x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/r_sin.c0000644000076500000240000000034513524616145023337 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double sin(); double r_sin(x) real *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double r_sin(real *x) #endif { return( sin(*x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/lbitshft.c0000644000076500000240000000040213524616145024036 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif integer #ifdef KR_headers lbit_shift(a, b) integer a; integer b; #else lbit_shift(integer a, integer b) #endif { return b >= 0 ? a << b : (integer)((uinteger)a >> -b); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/i_mod.c0000644000076500000240000000032313524616145023310 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers integer i_mod(a,b) integer *a, *b; #else integer i_mod(integer *a, integer *b) #endif { return( *a % *b); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/d_int.c0000644000076500000240000000041513524616145023320 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double floor(); double d_int(x) doublereal *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double d_int(doublereal *x) #endif { return( (*x>0) ? floor(*x) : -floor(- *x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/r_mod.c0000644000076500000240000000124613524616145023326 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers #ifdef IEEE_drem double drem(); #else double floor(); #endif double r_mod(x,y) real *x, *y; #else #ifdef IEEE_drem double drem(double, double); #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif #endif double r_mod(real *x, real *y) #endif { #ifdef IEEE_drem double xa, ya, z; if ((ya = *y) < 0.) ya = -ya; z = drem(xa = *x, ya); if (xa > 0) { if (z < 0) z += ya; } else if (z > 0) z -= ya; return z; #else double quotient; if( (quotient = (double)*x / *y) >= 0) quotient = floor(quotient); else quotient = -floor(-quotient); return(*x - (*y) * quotient ); #endif } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/erf_.c0000644000076500000240000000041613524616145023137 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifndef REAL #define REAL double #endif #ifdef KR_headers double erf(); REAL erf_(x) real *x; #else extern double erf(double); REAL erf_(real *x) #endif { return( erf((double)*x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/pow_di.c0000644000076500000240000000070013524616145023501 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers double pow_di(ap, bp) doublereal *ap; integer *bp; #else double pow_di(doublereal *ap, integer *bp) #endif { double pow, x; integer n; unsigned long u; pow = 1; x = *ap; n = *bp; if(n != 0) { if(n < 0) { n = -n; x = 1/x; } for(u = n; ; ) { if(u & 01) pow *= x; if(u >>= 1) x *= x; else break; } } return(pow); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/sysdep1.h00000644000076500000240000000234413524616145023703 0ustar tamasstaff00000000000000#ifndef SYSDEP_H_INCLUDED #define SYSDEP_H_INCLUDED #ifdef _MSC_VER #define FTRUNCATE chsize #endif #undef USE_LARGEFILE #ifndef NO_LONG_LONG #ifdef __sun__ #define USE_LARGEFILE #define OFF_T off64_t #endif #ifdef __linux__ #define USE_LARGEFILE #define OFF_T __off64_t #endif #ifdef _AIX43 #define _LARGE_FILES #define _LARGE_FILE_API #define USE_LARGEFILE #endif /*_AIX43*/ #ifdef __hpux #define _FILE64 #define _LARGEFILE64_SOURCE #define USE_LARGEFILE #endif /*__hpux*/ #ifdef __sgi #define USE_LARGEFILE #endif /*__sgi*/ #ifdef __FreeBSD__ #define OFF_T off_t #define FSEEK fseeko #define FTELL ftello #endif #ifdef USE_LARGEFILE #ifndef OFF_T #define OFF_T off64_t #endif #define _LARGEFILE_SOURCE #define _LARGEFILE64_SOURCE #include #include #define FOPEN fopen64 #define FREOPEN freopen64 #define FSEEK fseeko64 #define FSTAT fstat64 #define FTELL ftello64 #define FTRUNCATE ftruncate64 #define STAT stat64 #define STAT_ST stat64 #endif /*USE_LARGEFILE*/ #endif /*NO_LONG_LONG*/ #ifndef NON_UNIX_STDIO #ifndef USE_LARGEFILE #define _INCLUDE_POSIX_SOURCE /* for HP-UX */ #define _INCLUDE_XOPEN_SOURCE /* for HP-UX */ #include "sys/types.h" #include "sys/stat.h" #endif #endif #endif /*SYSDEP_H_INCLUDED*/ python-igraph-0.8.0/vendor/source/igraph/src/f2c/h_dnnt.c0000644000076500000240000000044613524616145023501 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double floor(); shortint h_dnnt(x) doublereal *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif shortint h_dnnt(doublereal *x) #endif { return (shortint)(*x >= 0. ? floor(*x + .5) : -floor(.5 - *x)); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/r_acos.c0000644000076500000240000000035113524616145023470 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double acos(); double r_acos(x) real *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double r_acos(real *x) #endif { return( acos(*x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/lread.c0000644000076500000240000003462313524616145023322 0ustar tamasstaff00000000000000#include "f2c.h" #include "fio.h" /* Compile with -DF8X_NML_ELIDE_QUOTES to permit eliding quotation */ /* marks in namelist input a la the Fortran 8X Draft published in */ /* the May 1989 issue of Fortran Forum. */ #ifdef Allow_TYQUAD static longint f__llx; #endif #ifdef KR_headers extern double atof(); extern char *malloc(), *realloc(); int (*f__lioproc)(), (*l_getc)(), (*l_ungetc)(); #else #undef abs #undef min #undef max #include "stdlib.h" #endif #include "fmt.h" #include "lio.h" #include "ctype.h" #include "fp.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers extern char *f__fmtbuf; #else extern const char *f__fmtbuf; int (*f__lioproc)(ftnint*, char*, ftnlen, ftnint), (*l_getc)(void), (*l_ungetc)(int,FILE*); #endif int l_eof; #define isblnk(x) (f__ltab[x+1]&B) #define issep(x) (f__ltab[x+1]&SX) #define isapos(x) (f__ltab[x+1]&AX) #define isexp(x) (f__ltab[x+1]&EX) #define issign(x) (f__ltab[x+1]&SG) #define iswhit(x) (f__ltab[x+1]&WH) #define SX 1 #define B 2 #define AX 4 #define EX 8 #define SG 16 #define WH 32 char f__ltab[128+1] = { /* offset one for EOF */ 0, 0,0,AX,0,0,0,0,0,0,WH|B,SX|WH,0,0,0,0,0, 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0, SX|B|WH,0,AX,0,0,0,0,AX,0,0,0,SG,SX,SG,0,SX, 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0, 0,0,0,0,EX,EX,0,0,0,0,0,0,0,0,0,0, 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0, AX,0,0,0,EX,EX,0,0,0,0,0,0,0,0,0,0, 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 }; #ifdef ungetc static int #ifdef KR_headers un_getc(x,f__cf) int x; FILE *f__cf; #else un_getc(int x, FILE *f__cf) #endif { return ungetc(x,f__cf); } #else #define un_getc ungetc #ifdef KR_headers extern int ungetc(); #else extern int ungetc(int, FILE*); /* for systems with a buggy stdio.h */ #endif #endif int t_getc(Void) { int ch; if(f__curunit->uend) return(EOF); if((ch=getc(f__cf))!=EOF) return(ch); if(feof(f__cf)) f__curunit->uend = l_eof = 1; return(EOF); } integer e_rsle(Void) { int ch; if(f__curunit->uend) return(0); while((ch=t_getc())!='\n') if (ch == EOF) { if(feof(f__cf)) f__curunit->uend = l_eof = 1; return EOF; } return(0); } flag f__lquit; int f__lcount,f__ltype,nml_read; char *f__lchar; double f__lx,f__ly; #define ERR(x) if(n=(x)) return(n) #define GETC(x) (x=(*l_getc)()) #define Ungetc(x,y) (*l_ungetc)(x,y) static int #ifdef KR_headers l_R(poststar, reqint) int poststar, reqint; #else l_R(int poststar, int reqint) #endif { char s[FMAX+EXPMAXDIGS+4]; register int ch; register char *sp, *spe, *sp1; long e, exp; int havenum, havestar, se; if (!poststar) { if (f__lcount > 0) return(0); f__lcount = 1; } #ifdef Allow_TYQUAD f__llx = 0; #endif f__ltype = 0; exp = 0; havestar = 0; retry: sp1 = sp = s; spe = sp + FMAX; havenum = 0; switch(GETC(ch)) { case '-': *sp++ = ch; sp1++; spe++; case '+': GETC(ch); } while(ch == '0') { ++havenum; GETC(ch); } while(isdigit(ch)) { if (sp < spe) *sp++ = ch; else ++exp; GETC(ch); } if (ch == '*' && !poststar) { if (sp == sp1 || exp || *s == '-') { errfl(f__elist->cierr,112,"bad repetition count"); } poststar = havestar = 1; *sp = 0; f__lcount = atoi(s); goto retry; } if (ch == '.') { #ifndef ALLOW_FLOAT_IN_INTEGER_LIST_INPUT if (reqint) errfl(f__elist->cierr,115,"invalid integer"); #endif GETC(ch); if (sp == sp1) while(ch == '0') { ++havenum; --exp; GETC(ch); } while(isdigit(ch)) { if (sp < spe) { *sp++ = ch; --exp; } GETC(ch); } } havenum += sp - sp1; se = 0; if (issign(ch)) goto signonly; if (havenum && isexp(ch)) { #ifndef ALLOW_FLOAT_IN_INTEGER_LIST_INPUT if (reqint) errfl(f__elist->cierr,115,"invalid integer"); #endif GETC(ch); if (issign(ch)) { signonly: if (ch == '-') se = 1; GETC(ch); } if (!isdigit(ch)) { bad: errfl(f__elist->cierr,112,"exponent field"); } e = ch - '0'; while(isdigit(GETC(ch))) { e = 10*e + ch - '0'; if (e > EXPMAX) goto bad; } if (se) exp -= e; else exp += e; } (void) Ungetc(ch, f__cf); if (sp > sp1) { ++havenum; while(*--sp == '0') ++exp; if (exp) sprintf(sp+1, "e%ld", exp); else sp[1] = 0; f__lx = atof(s); #ifdef Allow_TYQUAD if (reqint&2 && (se = sp - sp1 + exp) > 14 && se < 20) { /* Assuming 64-bit longint and 32-bit long. */ if (exp < 0) sp += exp; if (sp1 <= sp) { f__llx = *sp1 - '0'; while(++sp1 <= sp) f__llx = 10*f__llx + (*sp1 - '0'); } while(--exp >= 0) f__llx *= 10; if (*s == '-') f__llx = -f__llx; } #endif } else f__lx = 0.; if (havenum) f__ltype = TYLONG; else switch(ch) { case ',': case '/': break; default: if (havestar && ( ch == ' ' ||ch == '\t' ||ch == '\n')) break; if (nml_read > 1) { f__lquit = 2; return 0; } errfl(f__elist->cierr,112,"invalid number"); } return 0; } static int #ifdef KR_headers rd_count(ch) register int ch; #else rd_count(register int ch) #endif { if (ch < '0' || ch > '9') return 1; f__lcount = ch - '0'; while(GETC(ch) >= '0' && ch <= '9') f__lcount = 10*f__lcount + ch - '0'; Ungetc(ch,f__cf); return f__lcount <= 0; } static int l_C(Void) { int ch, nml_save; double lz; if(f__lcount>0) return(0); f__ltype=0; GETC(ch); if(ch!='(') { if (nml_read > 1 && (ch < '0' || ch > '9')) { Ungetc(ch,f__cf); f__lquit = 2; return 0; } if (rd_count(ch)) if(!f__cf || !feof(f__cf)) errfl(f__elist->cierr,112,"complex format"); else err(f__elist->cierr,(EOF),"lread"); if(GETC(ch)!='*') { if(!f__cf || !feof(f__cf)) errfl(f__elist->cierr,112,"no star"); else err(f__elist->cierr,(EOF),"lread"); } if(GETC(ch)!='(') { Ungetc(ch,f__cf); return(0); } } else f__lcount = 1; while(iswhit(GETC(ch))); Ungetc(ch,f__cf); nml_save = nml_read; nml_read = 0; if (ch = l_R(1,0)) return ch; if (!f__ltype) errfl(f__elist->cierr,112,"no real part"); lz = f__lx; while(iswhit(GETC(ch))); if(ch!=',') { (void) Ungetc(ch,f__cf); errfl(f__elist->cierr,112,"no comma"); } while(iswhit(GETC(ch))); (void) Ungetc(ch,f__cf); if (ch = l_R(1,0)) return ch; if (!f__ltype) errfl(f__elist->cierr,112,"no imaginary part"); while(iswhit(GETC(ch))); if(ch!=')') errfl(f__elist->cierr,112,"no )"); f__ly = f__lx; f__lx = lz; #ifdef Allow_TYQUAD f__llx = 0; #endif nml_read = nml_save; return(0); } static char nmLbuf[256], *nmL_next; static int (*nmL_getc_save)(Void); #ifdef KR_headers static int (*nmL_ungetc_save)(/* int, FILE* */); #else static int (*nmL_ungetc_save)(int, FILE*); #endif static int nmL_getc(Void) { int rv; if (rv = *nmL_next++) return rv; l_getc = nmL_getc_save; l_ungetc = nmL_ungetc_save; return (*l_getc)(); } static int #ifdef KR_headers nmL_ungetc(x, f) int x; FILE *f; #else nmL_ungetc(int x, FILE *f) #endif { f = f; /* banish non-use warning */ return *--nmL_next = x; } static int #ifdef KR_headers Lfinish(ch, dot, rvp) int ch, dot, *rvp; #else Lfinish(int ch, int dot, int *rvp) #endif { char *s, *se; static char what[] = "namelist input"; s = nmLbuf + 2; se = nmLbuf + sizeof(nmLbuf) - 1; *s++ = ch; while(!issep(GETC(ch)) && ch!=EOF) { if (s >= se) { nmLbuf_ovfl: return *rvp = err__fl(f__elist->cierr,131,what); } *s++ = ch; if (ch != '=') continue; if (dot) return *rvp = err__fl(f__elist->cierr,112,what); got_eq: *s = 0; nmL_getc_save = l_getc; l_getc = nmL_getc; nmL_ungetc_save = l_ungetc; l_ungetc = nmL_ungetc; nmLbuf[1] = *(nmL_next = nmLbuf) = ','; *rvp = f__lcount = 0; return 1; } if (dot) goto done; for(;;) { if (s >= se) goto nmLbuf_ovfl; *s++ = ch; if (!isblnk(ch)) break; if (GETC(ch) == EOF) goto done; } if (ch == '=') goto got_eq; done: Ungetc(ch, f__cf); return 0; } static int l_L(Void) { int ch, rv, sawdot; if(f__lcount>0) return(0); f__lcount = 1; f__ltype=0; GETC(ch); if(isdigit(ch)) { rd_count(ch); if(GETC(ch)!='*') if(!f__cf || !feof(f__cf)) errfl(f__elist->cierr,112,"no star"); else err(f__elist->cierr,(EOF),"lread"); GETC(ch); } sawdot = 0; if(ch == '.') { sawdot = 1; GETC(ch); } switch(ch) { case 't': case 'T': if (nml_read && Lfinish(ch, sawdot, &rv)) return rv; f__lx=1; break; case 'f': case 'F': if (nml_read && Lfinish(ch, sawdot, &rv)) return rv; f__lx=0; break; default: if(isblnk(ch) || issep(ch) || ch==EOF) { (void) Ungetc(ch,f__cf); return(0); } if (nml_read > 1) { Ungetc(ch,f__cf); f__lquit = 2; return 0; } errfl(f__elist->cierr,112,"logical"); } f__ltype=TYLONG; while(!issep(GETC(ch)) && ch!=EOF); Ungetc(ch, f__cf); return(0); } #define BUFSIZE 128 static int l_CHAR(Void) { int ch,size,i; static char rafail[] = "realloc failure"; char quote,*p; if(f__lcount>0) return(0); f__ltype=0; if(f__lchar!=NULL) free(f__lchar); size=BUFSIZE; p=f__lchar = (char *)malloc((unsigned int)size); if(f__lchar == NULL) errfl(f__elist->cierr,113,"no space"); GETC(ch); if(isdigit(ch)) { /* allow Fortran 8x-style unquoted string... */ /* either find a repetition count or the string */ f__lcount = ch - '0'; *p++ = ch; for(i = 1;;) { switch(GETC(ch)) { case '*': if (f__lcount == 0) { f__lcount = 1; #ifndef F8X_NML_ELIDE_QUOTES if (nml_read) goto no_quote; #endif goto noquote; } p = f__lchar; goto have_lcount; case ',': case ' ': case '\t': case '\n': case '/': Ungetc(ch,f__cf); /* no break */ case EOF: f__lcount = 1; f__ltype = TYCHAR; return *p = 0; } if (!isdigit(ch)) { f__lcount = 1; #ifndef F8X_NML_ELIDE_QUOTES if (nml_read) { no_quote: errfl(f__elist->cierr,112, "undelimited character string"); } #endif goto noquote; } *p++ = ch; f__lcount = 10*f__lcount + ch - '0'; if (++i == size) { f__lchar = (char *)realloc(f__lchar, (unsigned int)(size += BUFSIZE)); if(f__lchar == NULL) errfl(f__elist->cierr,113,rafail); p = f__lchar + i; } } } else (void) Ungetc(ch,f__cf); have_lcount: if(GETC(ch)=='\'' || ch=='"') quote=ch; else if(isblnk(ch) || (issep(ch) && ch != '\n') || ch==EOF) { Ungetc(ch,f__cf); return 0; } #ifndef F8X_NML_ELIDE_QUOTES else if (nml_read > 1) { Ungetc(ch,f__cf); f__lquit = 2; return 0; } #endif else { /* Fortran 8x-style unquoted string */ *p++ = ch; for(i = 1;;) { switch(GETC(ch)) { case ',': case ' ': case '\t': case '\n': case '/': Ungetc(ch,f__cf); /* no break */ case EOF: f__ltype = TYCHAR; return *p = 0; } noquote: *p++ = ch; if (++i == size) { f__lchar = (char *)realloc(f__lchar, (unsigned int)(size += BUFSIZE)); if(f__lchar == NULL) errfl(f__elist->cierr,113,rafail); p = f__lchar + i; } } } f__ltype=TYCHAR; for(i=0;;) { while(GETC(ch)!=quote && ch!='\n' && ch!=EOF && ++icierr,113,rafail); p=f__lchar+i-1; *p++ = ch; } else if(ch==EOF) return(EOF); else if(ch=='\n') { if(*(p-1) != '\\') continue; i--; p--; if(++iciunit]; if(a->ciunit>=MXUNIT || a->ciunit<0) err(a->cierr,101,"stler"); f__scale=f__recpos=0; f__elist=a; if(f__curunit->ufd==NULL && fk_open(SEQ,FMT,a->ciunit)) err(a->cierr,102,"lio"); f__cf=f__curunit->ufd; if(!f__curunit->ufmt) err(a->cierr,103,"lio") return(0); } int #ifdef KR_headers l_read(number,ptr,len,type) ftnint *number,type; char *ptr; ftnlen len; #else l_read(ftnint *number, char *ptr, ftnlen len, ftnint type) #endif { #define Ptr ((flex *)ptr) int i,n,ch; doublereal *yy; real *xx; for(i=0;i<*number;i++) { if(f__lquit) return(0); if(l_eof) err(f__elist->ciend, EOF, "list in") if(f__lcount == 0) { f__ltype = 0; for(;;) { GETC(ch); switch(ch) { case EOF: err(f__elist->ciend,(EOF),"list in") case ' ': case '\t': case '\n': continue; case '/': f__lquit = 1; goto loopend; case ',': f__lcount = 1; goto loopend; default: (void) Ungetc(ch, f__cf); goto rddata; } } } rddata: switch((int)type) { case TYINT1: case TYSHORT: case TYLONG: #ifndef ALLOW_FLOAT_IN_INTEGER_LIST_INPUT ERR(l_R(0,1)); break; #endif case TYREAL: case TYDREAL: ERR(l_R(0,0)); break; #ifdef TYQUAD case TYQUAD: n = l_R(0,2); if (n) return n; break; #endif case TYCOMPLEX: case TYDCOMPLEX: ERR(l_C()); break; case TYLOGICAL1: case TYLOGICAL2: case TYLOGICAL: ERR(l_L()); break; case TYCHAR: ERR(l_CHAR()); break; } while (GETC(ch) == ' ' || ch == '\t'); if (ch != ',' || f__lcount > 1) Ungetc(ch,f__cf); loopend: if(f__lquit) return(0); if(f__cf && ferror(f__cf)) { clearerr(f__cf); errfl(f__elist->cierr,errno,"list in"); } if(f__ltype==0) goto bump; switch((int)type) { case TYINT1: case TYLOGICAL1: Ptr->flchar = (char)f__lx; break; case TYLOGICAL2: case TYSHORT: Ptr->flshort = (short)f__lx; break; case TYLOGICAL: case TYLONG: Ptr->flint = (ftnint)f__lx; break; #ifdef Allow_TYQUAD case TYQUAD: if (!(Ptr->fllongint = f__llx)) Ptr->fllongint = f__lx; break; #endif case TYREAL: Ptr->flreal=f__lx; break; case TYDREAL: Ptr->fldouble=f__lx; break; case TYCOMPLEX: xx=(real *)ptr; *xx++ = f__lx; *xx = f__ly; break; case TYDCOMPLEX: yy=(doublereal *)ptr; *yy++ = f__lx; *yy = f__ly; break; case TYCHAR: b_char(f__lchar,ptr,len); break; } bump: if(f__lcount>0) f__lcount--; ptr += len; if (nml_read) nml_read++; } return(0); #undef Ptr } #ifdef KR_headers integer s_rsle(a) cilist *a; #else integer s_rsle(cilist *a) #endif { int n; f__reading=1; f__external=1; f__formatted=1; if(n=c_le(a)) return(n); f__lioproc = l_read; f__lquit = 0; f__lcount = 0; l_eof = 0; if(f__curunit->uwrt && f__nowreading(f__curunit)) err(a->cierr,errno,"read start"); if(f__curunit->uend) err(f__elist->ciend,(EOF),"read start"); l_getc = t_getc; l_ungetc = un_getc; f__doend = xrd_SL; return(0); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/r_asin.c0000644000076500000240000000035113524616145023475 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double asin(); double r_asin(x) real *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double r_asin(real *x) #endif { return( asin(*x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/fmt.h0000644000076500000240000000372613524616145023026 0ustar tamasstaff00000000000000struct syl { int op; int p1; union { int i[2]; char *s;} p2; }; #define RET1 1 #define REVERT 2 #define GOTO 3 #define X 4 #define SLASH 5 #define STACK 6 #define I 7 #define ED 8 #define NED 9 #define IM 10 #define APOS 11 #define H 12 #define TL 13 #define TR 14 #define T 15 #define COLON 16 #define S 17 #define SP 18 #define SS 19 #define P 20 #define BN 21 #define BZ 22 #define F 23 #define E 24 #define EE 25 #define D 26 #define G 27 #define GE 28 #define L 29 #define A 30 #define AW 31 #define O 32 #define NONL 33 #define OM 34 #define Z 35 #define ZM 36 typedef union { real pf; doublereal pd; } ufloat; typedef union { short is; #ifndef KR_headers signed #endif char ic; integer il; #ifdef Allow_TYQUAD longint ili; #endif } Uint; #ifdef KR_headers extern int (*f__doed)(),(*f__doned)(); extern int (*f__dorevert)(); extern int rd_ed(),rd_ned(); extern int w_ed(),w_ned(); extern int signbit_f2c(); extern char *f__fmtbuf; #else #ifdef __cplusplus extern "C" { #define Cextern extern "C" #else #define Cextern extern #endif extern const char *f__fmtbuf; extern int (*f__doed)(struct syl*, char*, ftnlen),(*f__doned)(struct syl*); extern int (*f__dorevert)(void); extern void fmt_bg(void); extern int pars_f(const char*); extern int rd_ed(struct syl*, char*, ftnlen),rd_ned(struct syl*); extern int signbit_f2c(double*); extern int w_ed(struct syl*, char*, ftnlen),w_ned(struct syl*); extern int wrt_E(ufloat*, int, int, int, ftnlen); extern int wrt_F(ufloat*, int, int, ftnlen); extern int wrt_L(Uint*, int, ftnlen); #endif extern int f__pc,f__parenlvl,f__revloc; extern flag f__cblank,f__cplus,f__workdone, f__nonl; extern int f__scale; #ifdef __cplusplus } #endif #define GET(x) if((x=(*f__getn)())<0) return(x) #define VAL(x) (x!='\n'?x:' ') #define PUT(x) (*f__putn)(x) #undef TYQUAD #ifndef Allow_TYQUAD #undef longint #define longint long #else #define TYQUAD 14 #endif #ifdef KR_headers extern char *f__icvt(); #else Cextern char *f__icvt(longint, int*, int*, int); #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/comptry.bat0000644000076500000240000000017513524616145024247 0ustar tamasstaff00000000000000%1 %2 %3 %4 %5 %6 %7 %8 %9 if errorlevel 1 goto nolonglong exit 0 :nolonglong %1 -DNO_LONG_LONG %2 %3 %4 %5 %6 %7 %8 %9 python-igraph-0.8.0/vendor/source/igraph/src/f2c/signal1.h0000644000076500000240000000151213524616145023565 0ustar tamasstaff00000000000000/* You may need to adjust the definition of signal1 to supply a */ /* cast to the correct argument type. This detail is system- and */ /* compiler-dependent. The #define below assumes signal.h declares */ /* type SIG_PF for the signal function's second argument. */ /* For some C++ compilers, "#define Sigarg_t ..." may be appropriate. */ #include #ifndef Sigret_t #define Sigret_t void #endif #ifndef Sigarg_t #ifdef KR_headers #define Sigarg_t #else #define Sigarg_t int #endif #endif /*Sigarg_t*/ #ifdef USE_SIG_PF /* compile with -DUSE_SIG_PF under IRIX */ #define sig_pf SIG_PF #else typedef Sigret_t (*sig_pf)(Sigarg_t); #endif #define signal1(a,b) signal(a,(sig_pf)b) #ifdef __cplusplus #define Sigarg ... #define Use_Sigarg #else #define Sigarg Int n #define Use_Sigarg n = n /* shut up compiler warning */ #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/wsne.c0000644000076500000240000000073713524616145023206 0ustar tamasstaff00000000000000#include "f2c.h" #include "fio.h" #include "lio.h" #ifdef __cplusplus extern "C" { #endif integer #ifdef KR_headers s_wsne(a) cilist *a; #else s_wsne(cilist *a) #endif { int n; if(n=c_le(a)) return(n); f__reading=0; f__external=1; f__formatted=1; f__putn = x_putc; L_len = LINE; f__donewrec = x_wSL; if(f__curunit->uwrt != 1 && f__nowwriting(f__curunit)) err(a->cierr, errno, "namelist output start"); x_wsne(a); return e_wsle(); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/dummy.c0000644000076500000240000000004013524616145023350 0ustar tamasstaff00000000000000 int MAIN__(void) { return 0; } python-igraph-0.8.0/vendor/source/igraph/src/f2c/getarg_.c0000644000076500000240000000112013524616145023625 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif /* * subroutine getarg(k, c) * returns the kth unix command argument in fortran character * variable argument c */ #ifdef KR_headers VOID getarg_(n, s, ls) ftnint *n; char *s; ftnlen ls; #define Const /*nothing*/ #else #define Const const void getarg_(ftnint *n, char *s, ftnlen ls) #endif { extern int xargc; extern char **xargv; Const char *t; int i; if(*n>=0 && *nf2c.h On such machines, one can enable INTEGER*8 by uncommenting the typedefs of longint and ulongint in f2c.h and adjusting them, so they read typedef long longint; typedef unsigned long ulongint; and by compiling libf2c with -DAllow_TYQUAD, as discussed below. Most of the routines in libf2c are support routines for Fortran intrinsic functions or for operations that f2c chooses not to do "in line". There are a few exceptions, summarized below -- functions and subroutines that appear to your program as ordinary external Fortran routines. If you use the REAL valued functions listed below (ERF, ERFC, DTIME, and ETIME) with "f2c -R", then you need to compile the corresponding source files with -DREAL=float. To do this, it is perhaps simplest to add "-DREAL=float" to CFLAGS in the makefile. 1. CALL ABORT prints a message and causes a core dump. 2. ERF(r) and DERF(d) and the REAL and DOUBLE PRECISION error functions (with x REAL and d DOUBLE PRECISION); DERF must be declared DOUBLE PRECISION in your program. Both ERF and DERF assume your C library provides the underlying erf() function (which not all systems do). 3. ERFC(r) and DERFC(d) are the complementary error functions: ERFC(r) = 1 - ERF(r) and DERFC(d) = 1.d0 - DERFC(d) (except that their results may be more accurate than explicitly evaluating the above formulae would give). Again, ERFC and r are REAL, and DERFC and d are DOUBLE PRECISION (and must be declared as such in your program), and ERFC and DERFC rely on your system's erfc(). 4. CALL GETARG(n,s), where n is an INTEGER and s is a CHARACTER variable, sets s to the n-th command-line argument (or to all blanks if there are fewer than n command-line arguments); CALL GETARG(0,s) sets s to the name of the program (on systems that support this feature). See IARGC below. 5. CALL GETENV(name, value), where name and value are of type CHARACTER, sets value to the environment value, $name, of name (or to blanks if $name has not been set). 6. NARGS = IARGC() sets NARGS to the number of command-line arguments (an INTEGER value). 7. CALL SIGNAL(n,func), where n is an INTEGER and func is an EXTERNAL procedure, arranges for func to be invoked when n occurs (on systems where this makes sense). If your compiler complains about the signal calls in main.c, s_paus.c, and signal_.c, you may need to adjust signal1.h suitably. See the comments in signal1.h. 8. ETIME(ARR) and DTIME(ARR) are REAL functions that return execution times. ARR is declared REAL ARR(2). The elapsed user and system CPU times are stored in ARR(1) and ARR(2), respectively. ETIME returns the total elapsed CPU time, i.e., ARR(1) + ARR(2). DTIME returns total elapsed CPU time since the previous call on DTIME. 9. CALL SYSTEM(cmd), where cmd is of type CHARACTER, passes cmd to the system's command processor (on systems where this can be done). 10. CALL FLUSH flushes all buffers. 11. FTELL(i) is an INTEGER function that returns the current offset of Fortran unit i (or -1 if unit i is not open). 12. CALL FSEEK(i, offset, whence, *errlab) attemps to move Fortran unit i to the specified offset: absolute offset if whence = 0; relative to the current offset if whence = 1; relative to the end of the file if whence = 2. It branches to label errlab if unit i is not open or if the call otherwise fails. The routines whose objects are makefile.u's $(I77) are for I/O. The following comments apply to them. If your system lacks /usr/include/local.h , then you should create an appropriate local.h in this directory. An appropriate local.h may simply be empty, or it may #define VAX or #define CRAY (or whatever else you must do to make fp.h work right). Alternatively, edit fp.h to suite your machine. If your system lacks /usr/include/fcntl.h , then you should simply create an empty fcntl.h in this directory. If your compiler then complains about creat and open not having a prototype, compile with OPEN_DECL defined. On many systems, open and creat are declared in fcntl.h . If your system's sprintf does not work the way ANSI C specifies -- specifically, if it does not return the number of characters transmitted -- then insert the line #define USE_STRLEN at the end of fmt.h . This is necessary with at least some versions of Sun software. In particular, if you get a warning about an improper pointer/integer combination in compiling wref.c, then you need to compile with -DUSE_STRLEN . If your system's fopen does not like the ANSI binary reading and writing modes "rb" and "wb", then you should compile open.c with NON_ANSI_RW_MODES #defined. If you get error messages about references to cf->_ptr and cf->_base when compiling wrtfmt.c and wsfe.c or to stderr->_flag when compiling err.c, then insert the line #define NON_UNIX_STDIO at the beginning of fio.h, and recompile everything (or at least those modules that contain NON_UNIX_STDIO). Unformatted sequential records consist of a length of record contents, the record contents themselves, and the length of record contents again (for backspace). Prior to 17 Oct. 1991, the length was of type int; now it is of type long, but you can change it back to int by inserting #define UIOLEN_int at the beginning of fio.h. This affects only sue.c and uio.c . If you have a really ancient K&R C compiler that does not understand void, add -Dvoid=int to the definition of CFLAGS in the makefile. On VAX, Cray, or Research Tenth-Edition Unix systems, you may need to add -DVAX, -DCRAY, or -DV10 (respectively) to CFLAGS to make fp.h work correctly. Alternatively, you may need to edit fp.h to suit your machine. If your compiler complains about the signal calls in main.c, s_paus.c, and signal_.c, you may need to adjust signal1.h suitably. See the comments in signal1.h. You may need to supply the following non-ANSI routines: fstat(int fileds, struct stat *buf) is similar to stat(char *name, struct stat *buf), except that the first argument, fileds, is the file descriptor returned by open rather than the name of the file. fstat is used in the system-dependent routine canseek (in the libf2c source file err.c), which is supposed to return 1 if it's possible to issue seeks on the file in question, 0 if it's not; you may need to suitably modify err.c . On non-UNIX systems, you can avoid references to fstat and stat by compiling with NON_UNIX_STDIO defined; in that case, you may need to supply access(char *Name,0), which is supposed to return 0 if file Name exists, nonzero otherwise. char * mktemp(char *buf) is supposed to replace the 6 trailing X's in buf with a unique number and then return buf. The idea is to get a unique name for a temporary file. On non-UNIX systems, you may need to change a few other, e.g.: the form of name computed by mktemp() in endfile.c and open.c; the use of the open(), close(), and creat() system calls in endfile.c, err.c, open.c; and the modes in calls on fopen() and fdopen() (and perhaps the use of fdopen() itself -- it's supposed to return a FILE* corresponding to a given an integer file descriptor) in err.c and open.c (component ufmt of struct unit is 1 for formatted I/O -- text mode on some systems -- and 0 for unformatted I/O -- binary mode on some systems). Compiling with -DNON_UNIX_STDIO omits all references to creat() and almost all references to open() and close(), the exception being in the function f__isdev() (in open.c). If you wish to use translated Fortran that has funny notions of record length for direct unformatted I/O (i.e., that assumes RECL= values in OPEN statements are not bytes but rather counts of some other units -- e.g., 4-character words for VMS), then you should insert an appropriate #define for url_Adjust at the beginning of open.c . For VMS Fortran, for example, #define url_Adjust(x) x *= 4 would suffice. By default, Fortran I/O units 5, 6, and 0 are pre-connected to stdin, stdout, and stderr, respectively. You can change this behavior by changing f_init() in err.c to suit your needs. Note that f2c assumes READ(*... means READ(5... and WRITE(*... means WRITE(6... . Moreover, an OPEN(n,... statement that does not specify a file name (and does not specify STATUS='SCRATCH') assumes FILE='fort.n' . You can change this by editing open.c and endfile.c suitably. Unless you adjust the "#define MXUNIT" line in fio.h, Fortran units 0, 1, ..., 99 are available, i.e., the highest allowed unit number is MXUNIT - 1. Lines protected from compilation by #ifdef Allow_TYQUAD are for a possible extension to 64-bit integers in which integer = int = 32 bits and longint = long = 64 bits. The makefile does not attempt to compile pow_qq.c, qbitbits.c, and qbitshft.c, which are meant for use with INTEGER*8. To use INTEGER*8, you must modify f2c.h to declare longint and ulongint appropriately; then add $(QINT) to the end of the makefile's dependency list for libf2c.a (if makefile is a copy of makefile.u; for the PC makefiles, add pow_qq.obj qbitbits.obj qbitshft.obj to the library's dependency list and adjust libf2c.lbc or libf2c.sy accordingly). Also add -DAllow_TYQUAD to the makefile's CFLAGS assignment. To make longint and ulongint available, it may suffice to add -DINTEGER_STAR_8 to the CFLAGS assignment. Following Fortran 90, s_cat.c and s_copy.c allow the target of a (character string) assignment to be appear on its right-hand, at the cost of some extra overhead for all run-time concatenations. If you prefer the extra efficiency that comes with the Fortran 77 requirement that the left-hand side of a character assignment not be involved in the right-hand side, compile s_cat.c and s_copy.c with -DNO_OVERWRITE . Extensions (Feb. 1993) to NAMELIST processing: 1. Reading a ? instead of &name (the start of a namelist) causes the namelist being sought to be written to stdout (unit 6); to omit this feature, compile rsne.c with -DNo_Namelist_Questions. 2. Reading the wrong namelist name now leads to an error message and an attempt to skip input until the right namelist name is found; to omit this feature, compile rsne.c with -DNo_Bad_Namelist_Skip. 3. Namelist writes now insert newlines before each variable; to omit this feature, compile xwsne.c with -DNo_Extra_Namelist_Newlines. 4. (Sept. 1995) When looking for the &name that starts namelist input, lines whose first non-blank character is something other than &, $, or ? are treated as comment lines and ignored, unless rsne.c is compiled with -DNo_Namelist_Comments. Nonstandard extension (Feb. 1993) to open: for sequential files, ACCESS='APPEND' (or access='anything else starting with "A" or "a"') causes the file to be positioned at end-of-file, so a write will append to the file. Some buggy Fortran programs use unformatted direct I/O to write an incomplete record and later read more from that record than they have written. For records other than the last, the unwritten portion of the record reads as binary zeros. The last record is a special case: attempting to read more from it than was written gives end-of-file -- which may help one find a bug. Some other Fortran I/O libraries treat the last record no differently than others and thus give no help in finding the bug of reading more than was written. If you wish to have this behavior, compile uio.c with -DPad_UDread . If you want to be able to catch write failures (e.g., due to a disk being full) with an ERR= specifier, compile dfe.c, due.c, sfe.c, sue.c, and wsle.c with -DALWAYS_FLUSH. This will lead to slower execution and more I/O, but should make ERR= work as expected, provided fflush returns an error return when its physical write fails. Carriage controls are meant to be interpreted by the UNIX col program (or a similar program). Sometimes it's convenient to use only ' ' as the carriage control character (normal single spacing). If you compile lwrite.c and wsfe.c with -DOMIT_BLANK_CC, formatted external output lines will have an initial ' ' quietly omitted, making use of the col program unnecessary with output that only has ' ' for carriage control. The Fortran 77 Standard leaves it up to the implementation whether formatted writes of floating-point numbers of absolute value < 1 have a zero before the decimal point. By default, libI77 omits such superfluous zeros, but you can cause them to appear by compiling lwrite.c, wref.c, and wrtfmt.c with -DWANT_LEAD_0 . If your (Unix) system lacks a ranlib command, you don't need it. Either comment out the makefile's ranlib invocation, or install a harmless "ranlib" command somewhere in your PATH, such as the one-line shell script exit 0 or (on some systems) exec /usr/bin/ar lts $1 >/dev/null By default, the routines that implement complex and double complex division, c_div.c and z_div.c, call sig_die to print an error message and exit if they see a divisor of 0, as this is sometimes helpful for debugging. On systems with IEEE arithmetic, compiling c_div.c and z_div.c with -DIEEE_COMPLEX_DIVIDE causes them instead to set both the real and imaginary parts of the result to +INFINITY if the numerator is nonzero, or to NaN if it vanishes. Nowadays most Unix and Linux systems have function int ftruncate(int fildes, off_t len); defined in system header file unistd.h that adjusts the length of file descriptor fildes to length len. Unless endfile.c is compiled with -DNO_TRUNCATE, endfile.c #includes "unistd.h" and calls ftruncate() if necessary to shorten files. If your system lacks ftruncate(), compile endfile.c with -DNO_TRUNCATE to make endfile.c use the older and more portable scheme of shortening a file by copying to a temporary file and back again. The initializations for "f2c -trapuv" are done by _uninit_f2c(), whose source is uninit.c, introduced June 2001. On IEEE-arithmetic systems, _uninit_f2c should initialize floating-point variables to signaling NaNs and, at its first invocation, should enable the invalid operation exception. Alas, the rules for distinguishing signaling from quiet NaNs were not specified in the IEEE P754 standard, nor were the precise means of enabling and disabling IEEE-arithmetic exceptions, and these details are thus system dependent. There are #ifdef's in uninit.c that specify them for some popular systems. If yours is not one of these systems, it may take some detective work to discover the appropriate details for your system. Sometimes it helps to look in the standard include directories for header files with relevant-sounding names, such as ieeefp.h, nan.h, or trap.h, and it may be simplest to run experiments to see what distinguishes a signaling from a quiet NaN. (If x is initialized to a signaling NaN and the invalid operation exception is masked off, as it should be by default on IEEE-arithmetic systems, then computing, say, y = x + 1 will yield a quiet NaN.) python-igraph-0.8.0/vendor/source/igraph/src/f2c/iio.c0000644000076500000240000000511713524616145023007 0ustar tamasstaff00000000000000#include "f2c.h" #include "fio.h" #include "fmt.h" #ifdef __cplusplus extern "C" { #endif extern char *f__icptr; char *f__icend; extern icilist *f__svic; int f__icnum; int z_getc(Void) { if(f__recpos++ < f__svic->icirlen) { if(f__icptr >= f__icend) err(f__svic->iciend,(EOF),"endfile"); return(*(unsigned char *)f__icptr++); } return '\n'; } void #ifdef KR_headers z_putc(c) #else z_putc(int c) #endif { if (f__icptr < f__icend && f__recpos++ < f__svic->icirlen) *f__icptr++ = c; } int z_rnew(Void) { f__icptr = f__svic->iciunit + (++f__icnum)*f__svic->icirlen; f__recpos = 0; f__cursor = 0; f__hiwater = 0; return 1; } static int z_endp(Void) { (*f__donewrec)(); return 0; } int #ifdef KR_headers c_si(a) icilist *a; #else c_si(icilist *a) #endif { f__elist = (cilist *)a; f__fmtbuf=a->icifmt; f__curunit = 0; f__sequential=f__formatted=1; f__external=0; if(pars_f(f__fmtbuf)<0) err(a->icierr,100,"startint"); fmt_bg(); f__cblank=f__cplus=f__scale=0; f__svic=a; f__icnum=f__recpos=0; f__cursor = 0; f__hiwater = 0; f__icptr = a->iciunit; f__icend = f__icptr + a->icirlen*a->icirnum; f__cf = 0; return(0); } int iw_rev(Void) { if(f__workdone) z_endp(); f__hiwater = f__recpos = f__cursor = 0; return(f__workdone=0); } #ifdef KR_headers integer s_rsfi(a) icilist *a; #else integer s_rsfi(icilist *a) #endif { int n; if(n=c_si(a)) return(n); f__reading=1; f__doed=rd_ed; f__doned=rd_ned; f__getn=z_getc; f__dorevert = z_endp; f__donewrec = z_rnew; f__doend = z_endp; return(0); } int z_wnew(Void) { if (f__recpos < f__hiwater) { f__icptr += f__hiwater - f__recpos; f__recpos = f__hiwater; } while(f__recpos++ < f__svic->icirlen) *f__icptr++ = ' '; f__recpos = 0; f__cursor = 0; f__hiwater = 0; f__icnum++; return 1; } #ifdef KR_headers integer s_wsfi(a) icilist *a; #else integer s_wsfi(icilist *a) #endif { int n; if(n=c_si(a)) return(n); f__reading=0; f__doed=w_ed; f__doned=w_ned; f__putn=z_putc; f__dorevert = iw_rev; f__donewrec = z_wnew; f__doend = z_endp; return(0); } integer e_rsfi(Void) { int n = en_fio(); f__fmtbuf = NULL; return(n); } integer e_wsfi(Void) { int n; n = en_fio(); f__fmtbuf = NULL; if(f__svic->icirnum != 1 && (f__icnum > f__svic->icirnum || (f__icnum == f__svic->icirnum && (f__recpos | f__hiwater)))) err(f__svic->icierr,110,"inwrite"); if (f__recpos < f__hiwater) f__recpos = f__hiwater; if (f__recpos >= f__svic->icirlen) err(f__svic->icierr,110,"recend"); if (!f__recpos && f__icnum) return n; while(f__recpos++ < f__svic->icirlen) *f__icptr++ = ' '; return n; } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/c_sin.c0000644000076500000240000000055213524616145023320 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers extern double sin(), cos(), sinh(), cosh(); VOID c_sin(r, z) f2c_complex *r, *z; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif void c_sin(f2c_complex *r, f2c_complex *z) #endif { double zi = z->i, zr = z->r; r->r = sin(zr) * cosh(zi); r->i = cos(zr) * sinh(zi); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/Notice0000644000076500000240000000227413524616145023230 0ustar tamasstaff00000000000000/**************************************************************** Copyright 1990 - 1997 by AT&T, Lucent Technologies and Bellcore. Permission to use, copy, modify, and distribute this software and its documentation for any purpose and without fee is hereby granted, provided that the above copyright notice appear in all copies and that both that the copyright notice and this permission notice and warranty disclaimer appear in supporting documentation, and that the names of AT&T, Bell Laboratories, Lucent or Bellcore or any of their entities not be used in advertising or publicity pertaining to distribution of the software without specific, written prior permission. AT&T, Lucent and Bellcore disclaim all warranties with regard to this software, including all implied warranties of merchantability and fitness. In no event shall AT&T, Lucent or Bellcore be liable for any special, indirect or consequential damages or any damages whatsoever resulting from loss of use, data or profits, whether in an action of contract, negligence or other tortious action, arising out of or in connection with the use or performance of this software. ****************************************************************/ python-igraph-0.8.0/vendor/source/igraph/src/f2c/h_sign.c0000644000076500000240000000041213524616145023467 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers shortint h_sign(a,b) shortint *a, *b; #else shortint h_sign(shortint *a, shortint *b) #endif { shortint x; x = (*a >= 0 ? *a : - *a); return( *b >= 0 ? x : -x); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/hl_ge.c0000644000076500000240000000053213524616145023301 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers extern integer s_cmp(); shortlogical hl_ge(a,b,la,lb) char *a, *b; ftnlen la, lb; #else extern integer s_cmp(char *, char *, ftnlen, ftnlen); shortlogical hl_ge(char *a, char *b, ftnlen la, ftnlen lb) #endif { return(s_cmp(a,b,la,lb) >= 0); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/iargc_.c0000644000076500000240000000030413524616145023444 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers ftnint iargc_() #else ftnint iargc_(void) #endif { extern int xargc; return ( xargc - 1 ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/d_sign.c0000644000076500000240000000041213524616145023463 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers double d_sign(a,b) doublereal *a, *b; #else double d_sign(doublereal *a, doublereal *b) #endif { double x; x = (*a >= 0 ? *a : - *a); return( *b >= 0 ? x : -x); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/z_cos.c0000644000076500000240000000055313524616145023343 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double sin(), cos(), sinh(), cosh(); VOID z_cos(r, z) doublecomplex *r, *z; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif void z_cos(doublecomplex *r, doublecomplex *z) #endif { double zi = z->i, zr = z->r; r->r = cos(zr) * cosh(zi); r->i = - sin(zr) * sinh(zi); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/z_exp.c0000644000076500000240000000054513524616145023354 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double exp(), cos(), sin(); VOID z_exp(r, z) doublecomplex *r, *z; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif void z_exp(doublecomplex *r, doublecomplex *z) #endif { double expx, zi = z->i; expx = exp(z->r); r->r = expx * cos(zi); r->i = expx * sin(zi); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/f77vers.c0000644000076500000240000001150513524616145023530 0ustar tamasstaff00000000000000 char _libf77_version_f2c[] = "\n@(#) LIBF77 VERSION (f2c) 20051004\n"; /* 2.00 11 June 1980. File version.c added to library. 2.01 31 May 1988. s_paus() flushes stderr; names of hl_* fixed [ d]erf[c ] added 8 Aug. 1989: #ifdefs for f2c -i2 added to s_cat.c 29 Nov. 1989: s_cmp returns long (for f2c) 30 Nov. 1989: arg types from f2c.h 12 Dec. 1989: s_rnge allows long names 19 Dec. 1989: getenv_ allows unsorted environment 28 Mar. 1990: add exit(0) to end of main() 2 Oct. 1990: test signal(...) == SIG_IGN rather than & 01 in main 17 Oct. 1990: abort() calls changed to sig_die(...,1) 22 Oct. 1990: separate sig_die from main 25 Apr. 1991: minor, theoretically invisible tweaks to s_cat, sig_die 31 May 1991: make system_ return status 18 Dec. 1991: change long to ftnlen (for -i2) many places 28 Feb. 1992: repair z_sqrt.c (scribbled on input, gave wrong answer) 18 July 1992: for n < 0, repair handling of 0**n in pow_[dr]i.c and m**n in pow_hh.c and pow_ii.c; catch SIGTRAP in main() for error msg before abort 23 July 1992: switch to ANSI prototypes unless KR_headers is #defined 23 Oct. 1992: fix botch in signal_.c (erroneous deref of 2nd arg); change Cabs to f__cabs. 12 March 1993: various tweaks for C++ 2 June 1994: adjust so abnormal terminations invoke f_exit just once 16 Sept. 1994: s_cmp: treat characters as unsigned in comparisons. 19 Sept. 1994: s_paus: flush after end of PAUSE; add -DMSDOS 12 Jan. 1995: pow_[dhiqrz][hiq]: adjust x**i to work on machines that sign-extend right shifts when i is the most negative integer. 26 Jan. 1995: adjust s_cat.c, s_copy.c to permit the left-hand side of character assignments to appear on the right-hand side (unless compiled with -DNO_OVERWRITE). 27 Jan. 1995: minor tweak to s_copy.c: copy forward whenever possible (for better cache behavior). 30 May 1995: added subroutine exit(rc) integer rc. Version not changed. 29 Aug. 1995: add F77_aloc.c; use it in s_cat.c and system_.c. 6 Sept. 1995: fix return type of system_ under -DKR_headers. 19 Dec. 1995: s_cat.c: fix bug when 2nd or later arg overlaps lhs. 19 Mar. 1996: s_cat.c: supply missing break after overlap detection. 13 May 1996: add [lq]bitbits.c and [lq]bitshft.c (f90 bit intrinsics). 19 June 1996: add casts to unsigned in [lq]bitshft.c. 26 Feb. 1997: adjust functions with a complex output argument to permit aliasing it with input arguments. (For now, at least, this is just for possible benefit of g77.) 4 April 1997: [cz]_div.c: tweaks invisible on most systems (that may affect systems using gratuitous extra precision). 19 Sept. 1997: [de]time_.c (Unix systems only): change return type to double. 2 May 1999: getenv_.c: omit environ in favor of getenv(). c_cos.c, c_exp.c, c_sin.c, d_cnjg.c, r_cnjg.c, z_cos.c, z_exp.c, z_log.c, z_sin.c: cope fully with overlapping arguments caused by equivalence. 3 May 1999: "invisible" tweaks to omit compiler warnings in abort_.c, ef1asc_.c, s_rnge.c, s_stop.c. 7 Sept. 1999: [cz]_div.c: arrange for compilation under -DIEEE_COMPLEX_DIVIDE to make these routines avoid calling sig_die when the denominator vanishes; instead, they return pairs of NaNs or Infinities, depending whether the numerator also vanishes or not. VERSION not changed. 15 Nov. 1999: s_rnge.c: add casts for the case of sizeof(ftnint) == sizeof(int) < sizeof(long). 10 March 2000: z_log.c: improve accuracy of Real(log(z)) for, e.g., z near (+-1,eps) with |eps| small. For the old evaluation, compile with -DPre20000310 . 20 April 2000: s_cat.c: tweak argument types to accord with calls by f2c when ftnint and ftnlen are of different sizes (different numbers of bits). 4 July 2000: adjustments to permit compilation by C++ compilers; VERSION string remains unchanged. 29 Sept. 2000: dtime_.c, etime_.c: use floating-point divide. dtime_.d, erf_.c, erfc_.c, etime.c: for use with "f2c -R", compile with -DREAL=float. 23 June 2001: add uninit.c; [fi]77vers.c: make version strings visible as extern char _lib[fi]77_version_f2c[]. 5 July 2001: modify uninit.c for __mc68k__ under Linux. 16 Nov. 2001: uninit.c: Linux Power PC logic supplied by Alan Bain. 18 Jan. 2002: fix glitches in qbit_bits(): wrong return type, missing ~ on y in return value. 14 March 2002: z_log.c: add code to cope with buggy compilers (e.g., some versions of gcc under -O2 or -O3) that do floating-point comparisons against values computed into extended-precision registers on some systems (such as Intel IA32 systems). Compile with -DNO_DOUBLE_EXTENDED to omit the new logic. 4 Oct. 2002: uninit.c: on IRIX systems, omit use of shell variables. 10 Oct 2005: uninit.c: on IA32 Linux systems, leave the rounding precision alone rather than forcing it to 53 bits; compile with -DUNINIT_F2C_PRECISION_53 to get the former behavior. */ python-igraph-0.8.0/vendor/source/igraph/src/f2c/uninit.c0000644000076500000240000002540613524616145023540 0ustar tamasstaff00000000000000#include #include #include #include "arith.h" #define TYSHORT 2 #define TYLONG 3 #define TYREAL 4 #define TYDREAL 5 #define TYCOMPLEX 6 #define TYDCOMPLEX 7 #define TYINT1 11 #define TYQUAD 14 #ifndef Long #define Long long #endif #ifdef __mips #define RNAN 0xffc00000 /* Quiet NaN */ #define DNAN0 0xfff80000 /* Signalling NaN double Big endian */ #define DNAN1 0 #endif #ifdef _PA_RISC1_1 #define RNAN 0xffc00000 /* Quiet Nan -- big endian */ #define DNAN0 0xfff80000 #define DNAN1 0 #endif #ifndef RNAN #define RNAN 0xff800001 #ifdef IEEE_MC68k /* set on PPC*/ #define DNAN0 0xfff00000 /* Quiet NaN big endian */ #define DNAN1 1 #else #define DNAN0 1 /* LSB, MSB for little endian machines */ #define DNAN1 0xfff00000 #endif #endif /*RNAN*/ #ifdef KR_headers #define Void /*void*/ #define FA7UL (unsigned Long) 0xfa7a7a7aL #else #define Void void #define FA7UL 0xfa7a7a7aUL #endif #ifdef __cplusplus extern "C" { #endif static void ieee0(Void); static unsigned Long rnan = RNAN, dnan0 = DNAN0, dnan1 = DNAN1; double _0 = 0.; void unsupported_error() { fprintf(stderr,"Runtime Error: Your Architecture is not supported by the" " -trapuv option of f2c\n"); exit(-1); } void #ifdef KR_headers _uninit_f2c(x, type, len) void *x; int type; long len; #else _uninit_f2c(void *x, int type, long len) #endif { static int first = 1; unsigned Long *lx, *lxe; if (first) { first = 0; ieee0(); } if (len == 1) switch(type) { case TYINT1: *(char*)x = 'Z'; return; case TYSHORT: *(short*)x = 0xfa7a; break; case TYLONG: *(unsigned Long*)x = FA7UL; return; case TYQUAD: case TYCOMPLEX: case TYDCOMPLEX: break; case TYREAL: *(unsigned Long*)x = rnan; return; case TYDREAL: lx = (unsigned Long*)x; lx[0] = dnan0; lx[1] = dnan1; return; default: printf("Surprise type %d in _uninit_f2c\n", type); } switch(type) { case TYINT1: memset(x, 'Z', len); break; case TYSHORT: *(short*)x = 0xfa7a; break; case TYQUAD: len *= 2; /* no break */ case TYLONG: lx = (unsigned Long*)x; lxe = lx + len; while(lx < lxe) *lx++ = FA7UL; break; case TYCOMPLEX: len *= 2; /* no break */ case TYREAL: lx = (unsigned Long*)x; lxe = lx + len; while(lx < lxe) *lx++ = rnan; break; case TYDCOMPLEX: len *= 2; /* no break */ case TYDREAL: lx = (unsigned Long*)x; for(lxe = lx + 2*len; lx < lxe; lx += 2) { lx[0] = dnan0; lx[1] = dnan1; } } } #ifdef __cplusplus } #endif #ifndef MSpc #ifdef MSDOS #define MSpc #else #ifdef _WIN32 #define MSpc #endif #endif #endif #ifdef MSpc #define IEEE0_done #include "float.h" #include "signal.h" static void ieee0(Void) { #ifndef __alpha #ifndef EM_DENORMAL #define EM_DENORMAL _EM_DENORMAL #endif #ifndef EM_UNDERFLOW #define EM_UNDERFLOW _EM_UNDERFLOW #endif #ifndef EM_INEXACT #define EM_INEXACT _EM_INEXACT #endif #ifndef MCW_EM #define MCW_EM _MCW_EM #endif _control87(EM_DENORMAL | EM_UNDERFLOW | EM_INEXACT, MCW_EM); #endif /* With MS VC++, compiling and linking with -Zi will permit */ /* clicking to invoke the MS C++ debugger, which will show */ /* the point of error -- provided SIGFPE is SIG_DFL. */ signal(SIGFPE, SIG_DFL); } #endif /* MSpc */ /* What follows is for SGI IRIX only */ #if defined(__mips) && defined(__sgi) /* must link with -lfpe */ #define IEEE0_done /* code from Eric Grosse */ #include #include #include "/usr/include/sigfpe.h" /* full pathname for lcc -N */ #include "/usr/include/sys/fpu.h" static void #ifdef KR_headers ieeeuserhand(exception, val) unsigned exception[5]; int val[2]; #else ieeeuserhand(unsigned exception[5], int val[2]) #endif { fflush(stdout); fprintf(stderr,"ieee0() aborting because of "); if(exception[0]==_OVERFL) fprintf(stderr,"overflow\n"); else if(exception[0]==_UNDERFL) fprintf(stderr,"underflow\n"); else if(exception[0]==_DIVZERO) fprintf(stderr,"divide by 0\n"); else if(exception[0]==_INVALID) fprintf(stderr,"invalid operation\n"); else fprintf(stderr,"\tunknown reason\n"); fflush(stderr); abort(); } static void #ifdef KR_headers ieeeuserhand2(j) unsigned int **j; #else ieeeuserhand2(unsigned int **j) #endif { fprintf(stderr,"ieee0() aborting because of confusion\n"); abort(); } static void ieee0(Void) { int i; for(i=1; i<=4; i++){ sigfpe_[i].count = 1000; sigfpe_[i].trace = 1; sigfpe_[i].repls = _USER_DETERMINED; } sigfpe_[1].repls = _ZERO; /* underflow */ handle_sigfpes( _ON, _EN_UNDERFL|_EN_OVERFL|_EN_DIVZERO|_EN_INVALID, ieeeuserhand,_ABORT_ON_ERROR,ieeeuserhand2); } #endif /* IRIX mips */ /* * The following is the preferred method but depends upon a GLIBC extension only * to be found in GLIBC 2.2 or later. It is a GNU extension, not included in the * C99 extensions which allow the FP status register to be examined in a platform * independent way. It should be used if at all possible -- AFRB */ #ifdef __GLIBC__ #define IEEE0_done #if ((__GLIBC__>=2) && (__GLIBC_MINOR__>=2)) #define _GNU_SOURCE 1 #include static void ieee0(Void) { /* Clear all exception flags */ if (fedisableexcept(FE_ALL_EXCEPT)==-1) unsupported_error(); if (feenableexcept(FE_DIVBYZERO|FE_INVALID|FE_OVERFLOW)==-1) unsupported_error(); } /* Many linux cases will be treated through GLIBC. Note that modern * linux runs on many non-i86 plaforms and as a result the following code * must be processor dependent rather than simply OS specific */ #else /* __GLIBC__<2.2 */ #include #ifdef __alpha__ #ifndef USE_setfpucw #define __setfpucw(x) __fpu_control = (x) #endif #endif /* Not all versions of libc define _FPU_SETCW; * * some only provide the __setfpucw() function. * */ #ifndef _FPU_SETCW #define _FPU_SETCW(cw) __setfpucw(cw) #endif /* The exact set of flags we want to set in the FPU control word * depends on the architecture. * Note also that whether an exception is enabled or disabled when * the _FPU_MASK_nn bit is set is architecture dependent! * Enabled-when-set: M68k, ARM, MIPS, PowerPC * Disabled-when-set: x86, Alpha * The state we are after is: * exceptions on division by zero, overflow and invalid operation. */ #ifdef __alpha__ #ifndef USE_setfpucw #define __setfpucw(x) __fpu_control = (x) #endif #endif #ifndef _FPU_SETCW #undef Can_use__setfpucw #define Can_use__setfpucw #endif #undef RQD_FPU_MASK #undef RQD_FPU_CLEAR_MASK #if (defined(__mc68000__) || defined(__mc68020__) || defined(mc68020) || defined (__mc68k__)) /* Reported 20010705 by Alan Bain */ /* Note that IEEE 754 IOP (illegal operation) */ /* = Signaling NAN (SNAN) + operation error (OPERR). */ #define RQD_FPU_STATE (_FPU_IEEE + _FPU_DOUBLE + _FPU_MASK_OPERR + \ _FPU_MASK_DZ + _FPU_MASK_SNAN+_FPU_MASK_OVFL) #define RQD_FPU_MASK (_FPU_MASK_OPERR+_FPU_MASK_DZ+_FPU_MASK_SNAN+_FPU_MASK_OVFL) #elif (defined(__powerpc__)||defined(_ARCH_PPC)||defined(_ARCH_PWR)) /* !__mc68k__ */ /* The following is NOT a mistake -- the author of the fpu_control.h * for the PPC has erroneously defined IEEE mode to turn on exceptions * other than Inexact! Start from default then and turn on only the ones * which we want*/ /* I have changed _FPU_MASK_UM here to _FPU_MASK_ZM, because that is * in line with all the other architectures specified here. -- AFRB */ #define RQD_FPU_STATE (_FPU_DEFAULT +_FPU_MASK_OM+_FPU_MASK_IM+_FPU_MASK_ZM) #define RQD_FPU_MASK (_FPU_MASK_OM+_FPU_MASK_IM+_FPU_MASK_ZM) #elif (defined(__arm__)) /* On ARM too, IEEE implies all exceptions enabled. * -- Peter Maydell * Unfortunately some version of ARMlinux don't include any * flags in the fpu_control.h file */ #define RQD_FPU_STATE (_FPU_DEFAULT +_FPU_MASK_OM+_FPU_MASK_IM+_FPU_MASK_ZM) #define RQD_FPU_MASK (_FPU_MASK_OM+_FPU_MASK_IM+_FPU_MASK_ZM) #elif (defined(__mips__)) /* And same again for MIPS; _FPU_IEEE => exceptions seems a common meme. * * MIPS uses different MASK constant names, no idea why -- PMM * */ #define RQD_FPU_STATE (_FPU_DEFAULT +_FPU_MASK_O+_FPU_MASK_V+_FPU_MASK_Z) #define RQD_FPU_MASK (_FPU_MASK_O+_FPU_MASK_V+_FPU_MASK_Z) #elif (defined(__sparc__)) #define RQD_FPU_STATE (_FPU_DEFAULT +_FPU_DOUBLE+_FPU_MASK_OM+_FPU_MASK_IM+_FPU_MASK_ZM) #define RQD_FPU_MASK (_FPU_MASK_OM+_FPU_MASK_IM+_FPU_MASK_ZM) #elif (defined(__i386__) || defined(__alpha__)) /* This case is for Intel, and also Alpha, because the Alpha header * purposely emulates x86 flags and meanings for compatibility with * stupid programs. * We used to try this case for anything defining _FPU_IEEE, but I think * that that's a bad idea because it isn't really likely to work. * Instead for unknown architectures we just won't allow -trapuv to work. * Trying this case was just getting us * (a) compile errors on archs which didn't know all these constants * (b) silent wrong behaviour on archs (like SPARC) which do know all * constants but have different semantics for them */ #define RQD_FPU_STATE (_FPU_IEEE - _FPU_EXTENDED + _FPU_DOUBLE - _FPU_MASK_IM - _FPU_MASK_ZM - _FPU_MASK_OM) #define RQD_FPU_CLEAR_MASK (_FPU_MASK_IM + _FPU_MASK_ZM + _FPU_MASK_OM) #endif static void ieee0(Void) { #ifdef RQD_FPU_STATE #ifndef UNINIT_F2C_PRECISION_53 /* 20051004 */ __fpu_control = RQD_FPU_STATE; _FPU_SETCW(__fpu_control); #else /* unmask invalid, etc., and keep current rounding precision */ fpu_control_t cw; _FPU_GETCW(cw); #ifdef RQD_FPU_CLEAR_MASK cw &= ~ RQD_FPU_CLEAR_MASK; #else cw |= RQD_FPU_MASK; #endif _FPU_SETCW(cw); #endif #else /* !_FPU_IEEE */ fprintf(stderr, "\n%s\n%s\n%s\n%s\n", "WARNING: _uninit_f2c in libf2c does not know how", "to enable trapping on this system, so f2c's -trapuv", "option will not detect uninitialized variables unless", "you can enable trapping manually."); fflush(stderr); #endif /* _FPU_IEEE */ } #endif /* __GLIBC__>2.2 */ #endif /* __GLIBC__ */ /* Specific to OSF/1 */ #if (defined(__alpha)&&defined(__osf__)) #ifndef IEEE0_done #define IEEE0_done #include static void ieee0(Void) { ieee_set_fp_control(IEEE_TRAP_ENABLE_INV); } #endif /*IEEE0_done*/ #endif /*__alpha OSF/1*/ #ifdef __hpux #define IEEE0_done #define _INCLUDE_HPUX_SOURCE #include #ifndef FP_X_INV #include #define fpsetmask fesettrapenable #define FP_X_INV FE_INVALID #endif static void ieee0(Void) { fpsetmask(FP_X_INV); } #endif /*__hpux*/ #ifdef _AIX #define IEEE0_done #include static void ieee0(Void) { fp_enable(TRP_INVALID); fp_trap(FP_TRAP_SYNC); } #endif /*_AIX*/ #ifdef __sun #define IEEE0_done #include static void ieee0(Void) { fpsetmask(FP_X_INV); } #endif /*__sparc*/ #ifndef IEEE0_done static void ieee0(Void) {} #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/f2ch.add0000644000076500000240000001365413524616145023364 0ustar tamasstaff00000000000000/* If you are using a C++ compiler, append the following to f2c.h for compiling libF77 and libI77. */ #ifdef __cplusplus extern "C" { extern int abort_(void); extern double c_abs(complex *); extern void c_cos(complex *, complex *); extern void c_div(complex *, complex *, complex *); extern void c_exp(complex *, complex *); extern void c_log(complex *, complex *); extern void c_sin(complex *, complex *); extern void c_sqrt(complex *, complex *); extern double d_abs(double *); extern double d_acos(double *); extern double d_asin(double *); extern double d_atan(double *); extern double d_atn2(double *, double *); extern void d_cnjg(doublecomplex *, doublecomplex *); extern double d_cos(double *); extern double d_cosh(double *); extern double d_dim(double *, double *); extern double d_exp(double *); extern double d_imag(doublecomplex *); extern double d_int(double *); extern double d_lg10(double *); extern double d_log(double *); extern double d_mod(double *, double *); extern double d_nint(double *); extern double d_prod(float *, float *); extern double d_sign(double *, double *); extern double d_sin(double *); extern double d_sinh(double *); extern double d_sqrt(double *); extern double d_tan(double *); extern double d_tanh(double *); extern double derf_(double *); extern double derfc_(double *); extern integer do_fio(ftnint *, char *, ftnlen); extern integer do_lio(ftnint *, ftnint *, char *, ftnlen); extern integer do_uio(ftnint *, char *, ftnlen); extern integer e_rdfe(void); extern integer e_rdue(void); extern integer e_rsfe(void); extern integer e_rsfi(void); extern integer e_rsle(void); extern integer e_rsli(void); extern integer e_rsue(void); extern integer e_wdfe(void); extern integer e_wdue(void); extern integer e_wsfe(void); extern integer e_wsfi(void); extern integer e_wsle(void); extern integer e_wsli(void); extern integer e_wsue(void); extern int ef1asc_(ftnint *, ftnlen *, ftnint *, ftnlen *); extern integer ef1cmc_(ftnint *, ftnlen *, ftnint *, ftnlen *); extern double erf(double); extern double erf_(float *); extern double erfc(double); extern double erfc_(float *); extern integer f_back(alist *); extern integer f_clos(cllist *); extern integer f_end(alist *); extern void f_exit(void); extern integer f_inqu(inlist *); extern integer f_open(olist *); extern integer f_rew(alist *); extern int flush_(void); extern void getarg_(integer *, char *, ftnlen); extern void getenv_(char *, char *, ftnlen, ftnlen); extern short h_abs(short *); extern short h_dim(short *, short *); extern short h_dnnt(double *); extern short h_indx(char *, char *, ftnlen, ftnlen); extern short h_len(char *, ftnlen); extern short h_mod(short *, short *); extern short h_nint(float *); extern short h_sign(short *, short *); extern short hl_ge(char *, char *, ftnlen, ftnlen); extern short hl_gt(char *, char *, ftnlen, ftnlen); extern short hl_le(char *, char *, ftnlen, ftnlen); extern short hl_lt(char *, char *, ftnlen, ftnlen); extern integer i_abs(integer *); extern integer i_dim(integer *, integer *); extern integer i_dnnt(double *); extern integer i_indx(char *, char *, ftnlen, ftnlen); extern integer i_len(char *, ftnlen); extern integer i_mod(integer *, integer *); extern integer i_nint(float *); extern integer i_sign(integer *, integer *); extern integer iargc_(void); extern ftnlen l_ge(char *, char *, ftnlen, ftnlen); extern ftnlen l_gt(char *, char *, ftnlen, ftnlen); extern ftnlen l_le(char *, char *, ftnlen, ftnlen); extern ftnlen l_lt(char *, char *, ftnlen, ftnlen); extern void pow_ci(complex *, complex *, integer *); extern double pow_dd(double *, double *); extern double pow_di(double *, integer *); extern short pow_hh(short *, shortint *); extern integer pow_ii(integer *, integer *); extern double pow_ri(float *, integer *); extern void pow_zi(doublecomplex *, doublecomplex *, integer *); extern void pow_zz(doublecomplex *, doublecomplex *, doublecomplex *); extern double r_abs(float *); extern double r_acos(float *); extern double r_asin(float *); extern double r_atan(float *); extern double r_atn2(float *, float *); extern void r_cnjg(complex *, complex *); extern double r_cos(float *); extern double r_cosh(float *); extern double r_dim(float *, float *); extern double r_exp(float *); extern double r_imag(complex *); extern double r_int(float *); extern double r_lg10(float *); extern double r_log(float *); extern double r_mod(float *, float *); extern double r_nint(float *); extern double r_sign(float *, float *); extern double r_sin(float *); extern double r_sinh(float *); extern double r_sqrt(float *); extern double r_tan(float *); extern double r_tanh(float *); extern void s_cat(char *, char **, integer *, integer *, ftnlen); extern integer s_cmp(char *, char *, ftnlen, ftnlen); extern void s_copy(char *, char *, ftnlen, ftnlen); extern int s_paus(char *, ftnlen); extern integer s_rdfe(cilist *); extern integer s_rdue(cilist *); extern integer s_rnge(char *, integer, char *, integer); extern integer s_rsfe(cilist *); extern integer s_rsfi(icilist *); extern integer s_rsle(cilist *); extern integer s_rsli(icilist *); extern integer s_rsne(cilist *); extern integer s_rsni(icilist *); extern integer s_rsue(cilist *); extern int s_stop(char *, ftnlen); extern integer s_wdfe(cilist *); extern integer s_wdue(cilist *); extern integer s_wsfe(cilist *); extern integer s_wsfi(icilist *); extern integer s_wsle(cilist *); extern integer s_wsli(icilist *); extern integer s_wsne(cilist *); extern integer s_wsni(icilist *); extern integer s_wsue(cilist *); extern void sig_die(char *, int); extern integer signal_(integer *, void (*)(int)); extern integer system_(char *, ftnlen); extern double z_abs(doublecomplex *); extern void z_cos(doublecomplex *, doublecomplex *); extern void z_div(doublecomplex *, doublecomplex *, doublecomplex *); extern void z_exp(doublecomplex *, doublecomplex *); extern void z_log(doublecomplex *, doublecomplex *); extern void z_sin(doublecomplex *, doublecomplex *); extern void z_sqrt(doublecomplex *, doublecomplex *); } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/s_cmp.c0000644000076500000240000000132213524616145023322 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif /* compare two strings */ #ifdef KR_headers integer s_cmp(a0, b0, la, lb) char *a0, *b0; ftnlen la, lb; #else integer s_cmp(char *a0, char *b0, ftnlen la, ftnlen lb) #endif { register unsigned char *a, *aend, *b, *bend; a = (unsigned char *)a0; b = (unsigned char *)b0; aend = a + la; bend = b + lb; if(la <= lb) { while(a < aend) if(*a != *b) return( *a - *b ); else { ++a; ++b; } while(b < bend) if(*b != ' ') return( ' ' - *b ); else ++b; } else { while(b < bend) if(*a == *b) { ++a; ++b; } else return( *a - *b ); while(a < aend) if(*a != ' ') return(*a - ' '); else ++a; } return(0); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/r_sinh.c0000644000076500000240000000035113524616145023504 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double sinh(); double r_sinh(x) real *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double r_sinh(real *x) #endif { return( sinh(*x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/getenv_.c0000644000076500000240000000230713524616145023654 0ustar tamasstaff00000000000000#include "f2c.h" #undef abs #ifdef KR_headers extern char *F77_aloc(), *getenv(); #else #include #include #ifdef __cplusplus extern "C" { #endif extern char *F77_aloc(ftnlen, const char*); #endif /* * getenv - f77 subroutine to return environment variables * * called by: * call getenv (ENV_NAME, char_var) * where: * ENV_NAME is the name of an environment variable * char_var is a character variable which will receive * the current value of ENV_NAME, or all blanks * if ENV_NAME is not defined */ #ifdef KR_headers VOID getenv_(fname, value, flen, vlen) char *value, *fname; ftnlen vlen, flen; #else void getenv_(char *fname, char *value, ftnlen flen, ftnlen vlen) #endif { char buf[256], *ep, *fp; integer i; if (flen <= 0) goto add_blanks; for(i = 0; i < sizeof(buf); i++) { if (i == flen || (buf[i] = fname[i]) == ' ') { buf[i] = 0; ep = getenv(buf); goto have_ep; } } while(i < flen && fname[i] != ' ') i++; strncpy(fp = F77_aloc(i+1, "getenv_"), fname, (int)i); fp[i] = 0; ep = getenv(fp); free(fp); have_ep: if (ep) while(*ep && vlen-- > 0) *value++ = *ep++; add_blanks: while(vlen-- > 0) *value++ = ' '; } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/wrtfmt.c0000644000076500000240000001652213524616145023554 0ustar tamasstaff00000000000000#include "f2c.h" #include "fio.h" #include "fmt.h" #ifdef __cplusplus extern "C" { #endif extern icilist *f__svic; extern char *f__icptr; static int mv_cur(Void) /* shouldn't use fseek because it insists on calling fflush */ /* instead we know too much about stdio */ { int cursor = f__cursor; f__cursor = 0; if(f__external == 0) { if(cursor < 0) { if(f__hiwater < f__recpos) f__hiwater = f__recpos; f__recpos += cursor; f__icptr += cursor; if(f__recpos < 0) err(f__elist->cierr, 110, "left off"); } else if(cursor > 0) { if(f__recpos + cursor >= f__svic->icirlen) err(f__elist->cierr, 110, "recend"); if(f__hiwater <= f__recpos) for(; cursor > 0; cursor--) (*f__putn)(' '); else if(f__hiwater <= f__recpos + cursor) { cursor -= f__hiwater - f__recpos; f__icptr += f__hiwater - f__recpos; f__recpos = f__hiwater; for(; cursor > 0; cursor--) (*f__putn)(' '); } else { f__icptr += cursor; f__recpos += cursor; } } return(0); } if (cursor > 0) { if(f__hiwater <= f__recpos) for(;cursor>0;cursor--) (*f__putn)(' '); else if(f__hiwater <= f__recpos + cursor) { cursor -= f__hiwater - f__recpos; f__recpos = f__hiwater; for(; cursor > 0; cursor--) (*f__putn)(' '); } else { f__recpos += cursor; } } else if (cursor < 0) { if(cursor + f__recpos < 0) err(f__elist->cierr,110,"left off"); if(f__hiwater < f__recpos) f__hiwater = f__recpos; f__recpos += cursor; } return(0); } static int #ifdef KR_headers wrt_Z(n,w,minlen,len) Uint *n; int w, minlen; ftnlen len; #else wrt_Z(Uint *n, int w, int minlen, ftnlen len) #endif { register char *s, *se; register int i, w1; static int one = 1; static char hex[] = "0123456789ABCDEF"; s = (char *)n; --len; if (*(char *)&one) { /* little endian */ se = s; s += len; i = -1; } else { se = s + len; i = 1; } for(;; s += i) if (s == se || *s) break; w1 = (i*(se-s) << 1) + 1; if (*s & 0xf0) w1++; if (w1 > w) for(i = 0; i < w; i++) (*f__putn)('*'); else { if ((minlen -= w1) > 0) w1 += minlen; while(--w >= w1) (*f__putn)(' '); while(--minlen >= 0) (*f__putn)('0'); if (!(*s & 0xf0)) { (*f__putn)(hex[*s & 0xf]); if (s == se) return 0; s += i; } for(;; s += i) { (*f__putn)(hex[*s >> 4 & 0xf]); (*f__putn)(hex[*s & 0xf]); if (s == se) break; } } return 0; } static int #ifdef KR_headers wrt_I(n,w,len, base) Uint *n; ftnlen len; register int base; #else wrt_I(Uint *n, int w, ftnlen len, register int base) #endif { int ndigit,sign,spare,i; longint x; char *ans; if(len==sizeof(integer)) x=n->il; else if(len == sizeof(char)) x = n->ic; #ifdef Allow_TYQUAD else if (len == sizeof(longint)) x = n->ili; #endif else x=n->is; ans=f__icvt(x,&ndigit,&sign, base); spare=w-ndigit; if(sign || f__cplus) spare--; if(spare<0) for(i=0;iil; else if(len == sizeof(char)) x = n->ic; #ifdef Allow_TYQUAD else if (len == sizeof(longint)) x = n->ili; #endif else x=n->is; ans=f__icvt(x,&ndigit,&sign, base); if(sign || f__cplus) xsign=1; else xsign=0; if(ndigit+xsign>w || m+xsign>w) { for(i=0;i=m) spare=w-ndigit-xsign; else spare=w-m-xsign; for(i=0;iil; else if(sz == sizeof(char)) x = n->ic; else x=n->is; for(i=0;i 0) (*f__putn)(*p++); return(0); } static int #ifdef KR_headers wrt_AW(p,w,len) char * p; ftnlen len; #else wrt_AW(char * p, int w, ftnlen len) #endif { while(w>len) { w--; (*f__putn)(' '); } while(w-- > 0) (*f__putn)(*p++); return(0); } static int #ifdef KR_headers wrt_G(p,w,d,e,len) ufloat *p; ftnlen len; #else wrt_G(ufloat *p, int w, int d, int e, ftnlen len) #endif { double up = 1,x; int i=0,oldscale,n,j; x = len==sizeof(real)?p->pf:p->pd; if(x < 0 ) x = -x; if(x<.1) { if (x != 0.) return(wrt_E(p,w,d,e,len)); i = 1; goto have_i; } for(;i<=d;i++,up*=10) { if(x>=up) continue; have_i: oldscale = f__scale; f__scale = 0; if(e==0) n=4; else n=e+2; i=wrt_F(p,w-n,d-i,len); for(j=0;jop) { default: fprintf(stderr,"w_ed, unexpected code: %d\n", p->op); sig_die(f__fmtbuf, 1); case I: return(wrt_I((Uint *)ptr,p->p1,len, 10)); case IM: return(wrt_IM((Uint *)ptr,p->p1,p->p2.i[0],len,10)); /* O and OM don't work right for character, double, complex, */ /* or doublecomplex, and they differ from Fortran 90 in */ /* showing a minus sign for negative values. */ case O: return(wrt_I((Uint *)ptr, p->p1, len, 8)); case OM: return(wrt_IM((Uint *)ptr,p->p1,p->p2.i[0],len,8)); case L: return(wrt_L((Uint *)ptr,p->p1, len)); case A: return(wrt_A(ptr,len)); case AW: return(wrt_AW(ptr,p->p1,len)); case D: case E: case EE: return(wrt_E((ufloat *)ptr,p->p1,p->p2.i[0],p->p2.i[1],len)); case G: case GE: return(wrt_G((ufloat *)ptr,p->p1,p->p2.i[0],p->p2.i[1],len)); case F: return(wrt_F((ufloat *)ptr,p->p1,p->p2.i[0],len)); /* Z and ZM assume 8-bit bytes. */ case Z: return(wrt_Z((Uint *)ptr,p->p1,0,len)); case ZM: return(wrt_Z((Uint *)ptr,p->p1,p->p2.i[0],len)); } } int #ifdef KR_headers w_ned(p) struct syl *p; #else w_ned(struct syl *p) #endif { switch(p->op) { default: fprintf(stderr,"w_ned, unexpected code: %d\n", p->op); sig_die(f__fmtbuf, 1); case SLASH: return((*f__donewrec)()); case T: f__cursor = p->p1-f__recpos - 1; return(1); case TL: f__cursor -= p->p1; if(f__cursor < -f__recpos) /* TL1000, 1X */ f__cursor = -f__recpos; return(1); case TR: case X: f__cursor += p->p1; return(1); case APOS: return(wrt_AP(p->p2.s)); case H: return(wrt_H(p->p1,p->p2.s)); } } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/rsli.c0000644000076500000240000000337113524616145023200 0ustar tamasstaff00000000000000#include "f2c.h" #include "fio.h" #include "lio.h" #include "fmt.h" /* for f__doend */ #ifdef __cplusplus extern "C" { #endif extern flag f__lquit; extern int f__lcount; extern char *f__icptr; extern char *f__icend; extern icilist *f__svic; extern int f__icnum, f__recpos; static int i_getc(Void) { if(f__recpos >= f__svic->icirlen) { if (f__recpos++ == f__svic->icirlen) return '\n'; z_rnew(); } f__recpos++; if(f__icptr >= f__icend) return EOF; return(*f__icptr++); } static #ifdef KR_headers int i_ungetc(ch, f) int ch; FILE *f; #else int i_ungetc(int ch, FILE *f) #endif { if (--f__recpos == f__svic->icirlen) return '\n'; if (f__recpos < -1) err(f__svic->icierr,110,"recend"); /* *--icptr == ch, and icptr may point to read-only memory */ return *--f__icptr /* = ch */; } static void #ifdef KR_headers c_lir(a) icilist *a; #else c_lir(icilist *a) #endif { extern int l_eof; f__reading = 1; f__external = 0; f__formatted = 1; f__svic = a; L_len = a->icirlen; f__recpos = -1; f__icnum = f__recpos = 0; f__cursor = 0; l_getc = i_getc; l_ungetc = i_ungetc; l_eof = 0; f__icptr = a->iciunit; f__icend = f__icptr + a->icirlen*a->icirnum; f__cf = 0; f__curunit = 0; f__elist = (cilist *)a; } #ifdef KR_headers integer s_rsli(a) icilist *a; #else integer s_rsli(icilist *a) #endif { f__lioproc = l_read; f__lquit = 0; f__lcount = 0; c_lir(a); f__doend = 0; return(0); } integer e_rsli(Void) { return 0; } #ifdef KR_headers integer s_rsni(a) icilist *a; #else extern int x_rsne(cilist*); integer s_rsni(icilist *a) #endif { extern int nml_read; integer rv; cilist ca; ca.ciend = a->iciend; ca.cierr = a->icierr; ca.cifmt = a->icifmt; c_lir(a); rv = x_rsne(&ca); nml_read = 0; return rv; } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/h_indx.c0000644000076500000240000000067213524616145023501 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers shortint h_indx(a, b, la, lb) char *a, *b; ftnlen la, lb; #else shortint h_indx(char *a, char *b, ftnlen la, ftnlen lb) #endif { ftnlen i, n; char *s, *t, *bend; n = la - lb + 1; bend = b + lb; for(i = 0 ; i < n ; ++i) { s = a + i; t = b; while(t < bend) if(*s++ != *t++) goto no; return((shortint)i+1); no: ; } return(0); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/err.c0000644000076500000240000001445213524616145023021 0ustar tamasstaff00000000000000#include "sysdep1.h" /* here to get stat64 on some badly designed Linux systems */ #include "f2c.h" #ifdef KR_headers #define Const /*nothing*/ extern char *malloc(); #else #define Const const #undef abs #undef min #undef max #include "stdlib.h" #endif #include "fio.h" #include "fmt.h" /* for struct syl */ /* Compile this with -DNO_ISATTY if unistd.h does not exist or */ /* if it does not define int isatty(int). */ #ifdef NO_ISATTY #define isatty(x) 0 #else #include #endif #ifdef __cplusplus extern "C" { #endif /*global definitions*/ unit f__units[MXUNIT]; /*unit table*/ flag f__init; /*0 on entry, 1 after initializations*/ cilist *f__elist; /*active external io list*/ icilist *f__svic; /*active internal io list*/ flag f__reading; /*1 if reading, 0 if writing*/ flag f__cplus,f__cblank; Const char *f__fmtbuf; flag f__external; /*1 if external io, 0 if internal */ #ifdef KR_headers int (*f__doed)(),(*f__doned)(); int (*f__doend)(),(*f__donewrec)(),(*f__dorevert)(); int (*f__getn)(); /* for formatted input */ void (*f__putn)(); /* for formatted output */ #else int (*f__getn)(void); /* for formatted input */ void (*f__putn)(int); /* for formatted output */ int (*f__doed)(struct syl*, char*, ftnlen),(*f__doned)(struct syl*); int (*f__dorevert)(void),(*f__donewrec)(void),(*f__doend)(void); #endif flag f__sequential; /*1 if sequential io, 0 if direct*/ flag f__formatted; /*1 if formatted io, 0 if unformatted*/ FILE *f__cf; /*current file*/ unit *f__curunit; /*current unit*/ int f__recpos; /*place in current record*/ OFF_T f__cursor, f__hiwater; int f__scale; char *f__icptr; /*error messages*/ Const char *F_err[] = { "error in format", /* 100 */ "illegal unit number", /* 101 */ "formatted io not allowed", /* 102 */ "unformatted io not allowed", /* 103 */ "direct io not allowed", /* 104 */ "sequential io not allowed", /* 105 */ "can't backspace file", /* 106 */ "null file name", /* 107 */ "can't stat file", /* 108 */ "unit not connected", /* 109 */ "off end of record", /* 110 */ "truncation failed in endfile", /* 111 */ "incomprehensible list input", /* 112 */ "out of free space", /* 113 */ "unit not connected", /* 114 */ "read unexpected character", /* 115 */ "bad logical input field", /* 116 */ "bad variable type", /* 117 */ "bad namelist name", /* 118 */ "variable not in namelist", /* 119 */ "no end record", /* 120 */ "variable count incorrect", /* 121 */ "subscript for scalar variable", /* 122 */ "invalid array section", /* 123 */ "substring out of bounds", /* 124 */ "subscript out of bounds", /* 125 */ "can't read file", /* 126 */ "can't write file", /* 127 */ "'new' file exists", /* 128 */ "can't append to file", /* 129 */ "non-positive record number", /* 130 */ "nmLbuf overflow" /* 131 */ }; #define MAXERR (sizeof(F_err)/sizeof(char *)+100) int #ifdef KR_headers f__canseek(f) FILE *f; /*SYSDEP*/ #else f__canseek(FILE *f) /*SYSDEP*/ #endif { #ifdef NON_UNIX_STDIO return !isatty(fileno(f)); #else struct STAT_ST x; if (FSTAT(fileno(f),&x) < 0) return(0); #ifdef S_IFMT switch(x.st_mode & S_IFMT) { case S_IFDIR: case S_IFREG: if(x.st_nlink > 0) /* !pipe */ return(1); else return(0); case S_IFCHR: if(isatty(fileno(f))) return(0); return(1); #ifdef S_IFBLK case S_IFBLK: return(1); #endif } #else #ifdef S_ISDIR /* POSIX version */ if (S_ISREG(x.st_mode) || S_ISDIR(x.st_mode)) { if(x.st_nlink > 0) /* !pipe */ return(1); else return(0); } if (S_ISCHR(x.st_mode)) { if(isatty(fileno(f))) return(0); return(1); } if (S_ISBLK(x.st_mode)) return(1); #else Help! How does fstat work on this system? #endif #endif return(0); /* who knows what it is? */ #endif } void #ifdef KR_headers f__fatal(n,s) char *s; #else f__fatal(int n, const char *s) #endif { if(n<100 && n>=0) perror(s); /*SYSDEP*/ else if(n >= (int)MAXERR || n < -1) { fprintf(stderr,"%s: illegal error number %d\n",s,n); } else if(n == -1) fprintf(stderr,"%s: end of file\n",s); else fprintf(stderr,"%s: %s\n",s,F_err[n-100]); if (f__curunit) { fprintf(stderr,"apparent state: unit %d ", (int)(f__curunit-f__units)); fprintf(stderr, f__curunit->ufnm ? "named %s\n" : "(unnamed)\n", f__curunit->ufnm); } else fprintf(stderr,"apparent state: internal I/O\n"); if (f__fmtbuf) fprintf(stderr,"last format: %s\n",f__fmtbuf); fprintf(stderr,"lately %s %s %s %s",f__reading?"reading":"writing", f__sequential?"sequential":"direct",f__formatted?"formatted":"unformatted", f__external?"external":"internal"); sig_die(" IO", 1); } /*initialization routine*/ VOID f_init(Void) { unit *p; f__init=1; p= &f__units[0]; p->ufd=stderr; p->useek=f__canseek(stderr); p->ufmt=1; p->uwrt=1; p = &f__units[5]; p->ufd=stdin; p->useek=f__canseek(stdin); p->ufmt=1; p->uwrt=0; p= &f__units[6]; p->ufd=stdout; p->useek=f__canseek(stdout); p->ufmt=1; p->uwrt=1; } int #ifdef KR_headers f__nowreading(x) unit *x; #else f__nowreading(unit *x) #endif { OFF_T loc; int ufmt, urw; extern char *f__r_mode[], *f__w_mode[]; if (x->urw & 1) goto done; if (!x->ufnm) goto cantread; ufmt = x->url ? 0 : x->ufmt; loc = FTELL(x->ufd); urw = 3; if (!FREOPEN(x->ufnm, f__w_mode[ufmt|2], x->ufd)) { urw = 1; if(!FREOPEN(x->ufnm, f__r_mode[ufmt], x->ufd)) { cantread: errno = 126; return 1; } } FSEEK(x->ufd,loc,SEEK_SET); x->urw = urw; done: x->uwrt = 0; return 0; } int #ifdef KR_headers f__nowwriting(x) unit *x; #else f__nowwriting(unit *x) #endif { OFF_T loc; int ufmt; extern char *f__w_mode[]; if (x->urw & 2) { if (x->urw & 1) FSEEK(x->ufd, (OFF_T)0, SEEK_CUR); goto done; } if (!x->ufnm) goto cantwrite; ufmt = x->url ? 0 : x->ufmt; if (x->uwrt == 3) { /* just did write, rewind */ if (!(f__cf = x->ufd = FREOPEN(x->ufnm,f__w_mode[ufmt],x->ufd))) goto cantwrite; x->urw = 2; } else { loc=FTELL(x->ufd); if (!(f__cf = x->ufd = FREOPEN(x->ufnm, f__w_mode[ufmt | 2], x->ufd))) { x->ufd = NULL; cantwrite: errno = 127; return(1); } x->urw = 3; FSEEK(x->ufd,loc,SEEK_SET); } done: x->uwrt = 1; return 0; } int #ifdef KR_headers err__fl(f, m, s) int f, m; char *s; #else err__fl(int f, int m, const char *s) #endif { if (!f) f__fatal(m, s); if (f__doend) (*f__doend)(); return errno = m; } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/hl_lt.c0000644000076500000240000000053113524616145023324 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers extern integer s_cmp(); shortlogical hl_lt(a,b,la,lb) char *a, *b; ftnlen la, lb; #else extern integer s_cmp(char *, char *, ftnlen, ftnlen); shortlogical hl_lt(char *a, char *b, ftnlen la, ftnlen lb) #endif { return(s_cmp(a,b,la,lb) < 0); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/pow_ci.c0000644000076500000240000000065013524616145023504 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers VOID pow_ci(p, a, b) /* p = a**b */ f2c_complex *p, *a; integer *b; #else extern void pow_zi(doublecomplex*, doublecomplex*, integer*); void pow_ci(f2c_complex *p, f2c_complex *a, integer *b) /* p = a**b */ #endif { doublecomplex p1, a1; a1.r = a->r; a1.i = a->i; pow_zi(&p1, &a1, b); p->r = p1.r; p->i = p1.i; } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/c_exp.c0000644000076500000240000000055113524616145023322 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers extern double exp(), cos(), sin(); VOID c_exp(r, z) f2c_complex *r, *z; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif void c_exp(f2c_complex *r, f2c_complex *z) #endif { double expx, zi = z->i; expx = exp(z->r); r->r = expx * cos(zi); r->i = expx * sin(zi); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/main.c0000644000076500000240000000426613524616145023157 0ustar tamasstaff00000000000000/* STARTUP PROCEDURE FOR UNIX FORTRAN PROGRAMS */ #include "stdio.h" #include "signal1.h" #ifndef SIGIOT #ifdef SIGABRT #define SIGIOT SIGABRT #endif #endif #ifndef KR_headers #undef VOID #include "stdlib.h" #ifdef __cplusplus extern "C" { #endif #endif #ifndef VOID #define VOID void #endif #ifdef __cplusplus extern "C" { #endif #ifdef NO__STDC #define ONEXIT onexit extern VOID f_exit(); #else #ifndef KR_headers extern void f_exit(void); #ifndef NO_ONEXIT #define ONEXIT atexit extern int atexit(void (*)(void)); #endif #else #ifndef NO_ONEXIT #define ONEXIT onexit extern VOID f_exit(); #endif #endif #endif #ifdef KR_headers extern VOID f_init(), sig_die(); extern int MAIN__(); #define Int /* int */ #else extern void f_init(void), sig_die(const char*, int); extern int MAIN__(void); #define Int int #endif static VOID sigfdie(Sigarg) { Use_Sigarg; sig_die("Floating Exception", 1); } static VOID sigidie(Sigarg) { Use_Sigarg; sig_die("IOT Trap", 1); } #ifdef SIGQUIT static VOID sigqdie(Sigarg) { Use_Sigarg; sig_die("Quit signal", 1); } #endif static VOID sigindie(Sigarg) { Use_Sigarg; sig_die("Interrupt", 0); } static VOID sigtdie(Sigarg) { Use_Sigarg; sig_die("Killed", 0); } #ifdef SIGTRAP static VOID sigtrdie(Sigarg) { Use_Sigarg; sig_die("Trace trap", 1); } #endif int xargc; char **xargv; #ifdef __cplusplus } #endif int #ifdef KR_headers main(argc, argv) int argc; char **argv; #else main(int argc, char **argv) #endif { xargc = argc; xargv = argv; signal1(SIGFPE, sigfdie); /* ignore underflow, enable overflow */ #ifdef SIGIOT signal1(SIGIOT, sigidie); #endif #ifdef SIGTRAP signal1(SIGTRAP, sigtrdie); #endif #ifdef SIGQUIT if(signal1(SIGQUIT,sigqdie) == SIG_IGN) signal1(SIGQUIT, SIG_IGN); #endif if(signal1(SIGINT, sigindie) == SIG_IGN) signal1(SIGINT, SIG_IGN); signal1(SIGTERM,sigtdie); #ifdef pdp11 ldfps(01200); /* detect overflow as an exception */ #endif f_init(); #ifndef NO_ONEXIT ONEXIT(f_exit); #endif MAIN__(); #ifdef NO_ONEXIT f_exit(); #endif exit(0); /* exit(0) rather than return(0) to bypass Cray bug */ return 0; /* For compilers that complain of missing return values; */ /* others will complain that this is unreachable code. */ } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/sue.c0000644000076500000240000000351113524616145023017 0ustar tamasstaff00000000000000#include "f2c.h" #include "fio.h" #ifdef __cplusplus extern "C" { #endif extern uiolen f__reclen; OFF_T f__recloc; int #ifdef KR_headers c_sue(a) cilist *a; #else c_sue(cilist *a) #endif { f__external=f__sequential=1; f__formatted=0; f__curunit = &f__units[a->ciunit]; if(a->ciunit >= MXUNIT || a->ciunit < 0) err(a->cierr,101,"startio"); f__elist=a; if(f__curunit->ufd==NULL && fk_open(SEQ,UNF,a->ciunit)) err(a->cierr,114,"sue"); f__cf=f__curunit->ufd; if(f__curunit->ufmt) err(a->cierr,103,"sue") if(!f__curunit->useek) err(a->cierr,103,"sue") return(0); } #ifdef KR_headers integer s_rsue(a) cilist *a; #else integer s_rsue(cilist *a) #endif { int n; if(!f__init) f_init(); f__reading=1; if(n=c_sue(a)) return(n); f__recpos=0; if(f__curunit->uwrt && f__nowreading(f__curunit)) err(a->cierr, errno, "read start"); if(fread((char *)&f__reclen,sizeof(uiolen),1,f__cf) != 1) { if(feof(f__cf)) { f__curunit->uend = 1; err(a->ciend, EOF, "start"); } clearerr(f__cf); err(a->cierr, errno, "start"); } return(0); } #ifdef KR_headers integer s_wsue(a) cilist *a; #else integer s_wsue(cilist *a) #endif { int n; if(!f__init) f_init(); if(n=c_sue(a)) return(n); f__reading=0; f__reclen=0; if(f__curunit->uwrt != 1 && f__nowwriting(f__curunit)) err(a->cierr, errno, "write start"); f__recloc=FTELL(f__cf); FSEEK(f__cf,(OFF_T)sizeof(uiolen),SEEK_CUR); return(0); } integer e_wsue(Void) { OFF_T loc; fwrite((char *)&f__reclen,sizeof(uiolen),1,f__cf); #ifdef ALWAYS_FLUSH if (fflush(f__cf)) err(f__elist->cierr, errno, "write end"); #endif loc=FTELL(f__cf); FSEEK(f__cf,f__recloc,SEEK_SET); fwrite((char *)&f__reclen,sizeof(uiolen),1,f__cf); FSEEK(f__cf,loc,SEEK_SET); return(0); } integer e_rsue(Void) { FSEEK(f__cf,(OFF_T)(f__reclen-f__recpos+sizeof(uiolen)),SEEK_CUR); return(0); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/c_cos.c0000644000076500000240000000055613524616145023317 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers extern double sin(), cos(), sinh(), cosh(); VOID c_cos(r, z) f2c_complex *r, *z; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif void c_cos(f2c_complex *r, f2c_complex *z) #endif { double zi = z->i, zr = z->r; r->r = cos(zr) * cosh(zi); r->i = - sin(zr) * sinh(zi); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/signbit.c0000644000076500000240000000051213524616145023660 0ustar tamasstaff00000000000000#include "arith.h" #ifndef Long #define Long long #endif int #ifdef KR_headers signbit_f2c(x) double *x; #else signbit_f2c(double *x) #endif { #ifdef IEEE_MC68k if (*(Long*)x & 0x80000000) return 1; #else #ifdef IEEE_8087 if (((Long*)x)[1] & 0x80000000) return 1; #endif /*IEEE_8087*/ #endif /*IEEE_MC68k*/ return 0; } python-igraph-0.8.0/vendor/source/igraph/src/f2c/due.c0000644000076500000240000000313013524616145022775 0ustar tamasstaff00000000000000#include "f2c.h" #include "fio.h" #ifdef __cplusplus extern "C" { #endif int #ifdef KR_headers c_due(a) cilist *a; #else c_due(cilist *a) #endif { if(!f__init) f_init(); f__sequential=f__formatted=f__recpos=0; f__external=1; f__curunit = &f__units[a->ciunit]; if(a->ciunit>=MXUNIT || a->ciunit<0) err(a->cierr,101,"startio"); f__elist=a; if(f__curunit->ufd==NULL && fk_open(DIR,UNF,a->ciunit) ) err(a->cierr,104,"due"); f__cf=f__curunit->ufd; if(f__curunit->ufmt) err(a->cierr,102,"cdue") if(!f__curunit->useek) err(a->cierr,104,"cdue") if(f__curunit->ufd==NULL) err(a->cierr,114,"cdue") if(a->cirec <= 0) err(a->cierr,130,"due") FSEEK(f__cf,(OFF_T)(a->cirec-1)*f__curunit->url,SEEK_SET); f__curunit->uend = 0; return(0); } #ifdef KR_headers integer s_rdue(a) cilist *a; #else integer s_rdue(cilist *a) #endif { int n; f__reading=1; if(n=c_due(a)) return(n); if(f__curunit->uwrt && f__nowreading(f__curunit)) err(a->cierr,errno,"read start"); return(0); } #ifdef KR_headers integer s_wdue(a) cilist *a; #else integer s_wdue(cilist *a) #endif { int n; f__reading=0; if(n=c_due(a)) return(n); if(f__curunit->uwrt != 1 && f__nowwriting(f__curunit)) err(a->cierr,errno,"write start"); return(0); } integer e_rdue(Void) { if(f__curunit->url==1 || f__recpos==f__curunit->url) return(0); FSEEK(f__cf,(OFF_T)(f__curunit->url-f__recpos),SEEK_CUR); if(FTELL(f__cf)%f__curunit->url) err(f__elist->cierr,200,"syserr"); return(0); } integer e_wdue(Void) { #ifdef ALWAYS_FLUSH if (fflush(f__cf)) err(f__elist->cierr,errno,"write end"); #endif return(e_rdue()); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/i_nint.c0000644000076500000240000000042613524616145023505 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double floor(); integer i_nint(x) real *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif integer i_nint(real *x) #endif { return (integer)(*x >= 0 ? floor(*x + .5) : -floor(.5 - *x)); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/z_sin.c0000644000076500000240000000054713524616145023353 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double sin(), cos(), sinh(), cosh(); VOID z_sin(r, z) doublecomplex *r, *z; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif void z_sin(doublecomplex *r, doublecomplex *z) #endif { double zi = z->i, zr = z->r; r->r = sin(zr) * cosh(zi); r->i = cos(zr) * sinh(zi); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/sig_die.c0000644000076500000240000000126113524616145023626 0ustar tamasstaff00000000000000#include "stdio.h" #include "signal.h" #ifndef SIGIOT #ifdef SIGABRT #define SIGIOT SIGABRT #endif #endif #ifdef KR_headers void sig_die(s, kill) char *s; int kill; #else #include "stdlib.h" #ifdef __cplusplus extern "C" { #endif #ifdef __cplusplus extern "C" { #endif extern void f_exit(void); void sig_die(const char *s, int kill) #endif { /* print error message, then clear buffers */ fprintf(stderr, "%s\n", s); if(kill) { fflush(stderr); f_exit(); fflush(stderr); /* now get a core */ #ifdef SIGIOT signal(SIGIOT, SIG_DFL); #endif abort(); } else { #ifdef NO_ONEXIT f_exit(); #endif exit(1); } } #ifdef __cplusplus } #endif #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/scomptry.bat0000644000076500000240000000026513524616145024432 0ustar tamasstaff00000000000000%1 -DWRITE_ARITH_H -DNO_FPINIT %2 %3 %4 %5 %6 %7 %8 %9 if errorlevel 1 goto nolonglong exit 0 :nolonglong %1 -DNO_LONG_LONG -DWRITE_ARITH_H -DNO_FPINIT %2 %3 %4 %5 %6 %7 %8 %9 python-igraph-0.8.0/vendor/source/igraph/src/f2c/fmtlib.c0000644000076500000240000000154113524616145023501 0ustar tamasstaff00000000000000/* @(#)fmtlib.c 1.2 */ #define MAXINTLENGTH 23 #include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifndef Allow_TYQUAD #undef longint #define longint long #undef ulongint #define ulongint unsigned long #endif #ifdef KR_headers char *f__icvt(value,ndigit,sign, base) longint value; int *ndigit,*sign; register int base; #else char *f__icvt(longint value, int *ndigit, int *sign, int base) #endif { static char buf[MAXINTLENGTH+1]; register int i; ulongint uvalue; if(value > 0) { uvalue = value; *sign = 0; } else if (value < 0) { uvalue = -value; *sign = 1; } else { *sign = 0; *ndigit = 1; buf[MAXINTLENGTH-1] = '0'; return &buf[MAXINTLENGTH-1]; } i = MAXINTLENGTH; do { buf[--i] = (uvalue%base) + '0'; uvalue /= base; } while(uvalue > 0); *ndigit = MAXINTLENGTH - i; return &buf[i]; } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/rawio.h0000644000076500000240000000131613524616145023352 0ustar tamasstaff00000000000000#ifndef KR_headers #ifdef MSDOS #include "io.h" #ifndef WATCOM #define close _close #define creat _creat #define open _open #define read _read #define write _write #endif /*WATCOM*/ #endif /*MSDOS*/ #ifdef __cplusplus extern "C" { #endif #ifndef MSDOS #ifdef OPEN_DECL extern int creat(const char*,int), open(const char*,int); #endif extern int close(int); extern int read(int,void*,size_t), write(int,void*,size_t); extern int unlink(const char*); #ifndef _POSIX_SOURCE #ifndef NON_UNIX_STDIO extern FILE *fdopen(int, const char*); #endif #endif #endif /*KR_HEADERS*/ extern char *mktemp(char*); #ifdef __cplusplus } #endif #endif #include "fcntl.h" #ifndef O_WRONLY #define O_RDONLY 0 #define O_WRONLY 1 #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/uio.c0000644000076500000240000000312313524616145023016 0ustar tamasstaff00000000000000#include "f2c.h" #include "fio.h" #ifdef __cplusplus extern "C" { #endif uiolen f__reclen; int #ifdef KR_headers do_us(number,ptr,len) ftnint *number; char *ptr; ftnlen len; #else do_us(ftnint *number, char *ptr, ftnlen len) #endif { if(f__reading) { f__recpos += (int)(*number * len); if(f__recpos>f__reclen) err(f__elist->cierr, 110, "do_us"); if (fread(ptr,(int)len,(int)(*number),f__cf) != *number) err(f__elist->ciend, EOF, "do_us"); return(0); } else { f__reclen += *number * len; (void) fwrite(ptr,(int)len,(int)(*number),f__cf); return(0); } } #ifdef KR_headers integer do_ud(number,ptr,len) ftnint *number; char *ptr; ftnlen len; #else integer do_ud(ftnint *number, char *ptr, ftnlen len) #endif { f__recpos += (int)(*number * len); if(f__recpos > f__curunit->url && f__curunit->url!=1) err(f__elist->cierr,110,"do_ud"); if(f__reading) { #ifdef Pad_UDread #ifdef KR_headers int i; #else size_t i; #endif if (!(i = fread(ptr,(int)len,(int)(*number),f__cf)) && !(f__recpos - *number*len)) err(f__elist->cierr,EOF,"do_ud") if (i < *number) memset(ptr + i*len, 0, (*number - i)*len); return 0; #else if(fread(ptr,(int)len,(int)(*number),f__cf) != *number) err(f__elist->cierr,EOF,"do_ud") else return(0); #endif } (void) fwrite(ptr,(int)len,(int)(*number),f__cf); return(0); } #ifdef KR_headers integer do_uio(number,ptr,len) ftnint *number; char *ptr; ftnlen len; #else integer do_uio(ftnint *number, char *ptr, ftnlen len) #endif { if(f__sequential) return(do_us(number,ptr,len)); else return(do_ud(number,ptr,len)); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/etime_.c0000644000076500000240000000150713524616145023470 0ustar tamasstaff00000000000000#include "time.h" #ifdef MSDOS #undef USE_CLOCK #define USE_CLOCK #endif #ifndef REAL #define REAL double #endif #ifndef USE_CLOCK #define _INCLUDE_POSIX_SOURCE /* for HP-UX */ #define _INCLUDE_XOPEN_SOURCE /* for HP-UX */ #include "sys/types.h" #include "sys/times.h" #ifdef __cplusplus extern "C" { #endif #endif #undef Hz #ifdef CLK_TCK #define Hz CLK_TCK #else #ifdef HZ #define Hz HZ #else #define Hz 60 #endif #endif REAL #ifdef KR_headers etime_(tarray) float *tarray; #else etime_(float *tarray) #endif { #ifdef USE_CLOCK #ifndef CLOCKS_PER_SECOND #define CLOCKS_PER_SECOND Hz #endif double t = clock(); tarray[1] = 0; return tarray[0] = t / CLOCKS_PER_SECOND; #else struct tms t; times(&t); return (tarray[0] = (double)t.tms_utime/Hz) + (tarray[1] = (double)t.tms_stime/Hz); #endif } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/ctype.h0000644000076500000240000000216313524616145023356 0ustar tamasstaff00000000000000/* Custom ctype.h to overcome trouble with recent versions of Linux libc.a */ #ifdef NO_My_ctype #include #else /*{*/ #ifndef My_ctype_DEF extern char My_ctype[]; #else /*{*/ char My_ctype[264] = { 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}; #endif /*}*/ #define isdigit(x) (My_ctype[(x)+8] & 1) #define isspace(x) (My_ctype[(x)+8] & 2) #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/s_paus.c0000644000076500000240000000312113524616145023512 0ustar tamasstaff00000000000000#include "stdio.h" #include "f2c.h" #define PAUSESIG 15 #include "signal1.h" #ifdef KR_headers #define Void /* void */ #define Int /* int */ #else #define Void void #define Int int #undef abs #undef min #undef max #include "stdlib.h" #ifdef __cplusplus extern "C" { #endif #ifdef __cplusplus extern "C" { #endif extern int getpid(void), isatty(int), pause(void); #endif extern VOID f_exit(Void); #ifndef MSDOS static VOID waitpause(Sigarg) { Use_Sigarg; return; } #endif static VOID #ifdef KR_headers s_1paus(fin) FILE *fin; #else s_1paus(FILE *fin) #endif { fprintf(stderr, "To resume execution, type go. Other input will terminate the job.\n"); fflush(stderr); if( getc(fin)!='g' || getc(fin)!='o' || getc(fin)!='\n' ) { fprintf(stderr, "STOP\n"); #ifdef NO_ONEXIT f_exit(); #endif exit(0); } } int #ifdef KR_headers s_paus(s, n) char *s; ftnlen n; #else s_paus(char *s, ftnlen n) #endif { fprintf(stderr, "PAUSE "); if(n > 0) fprintf(stderr, " %.*s", (int)n, s); fprintf(stderr, " statement executed\n"); if( isatty(fileno(stdin)) ) s_1paus(stdin); else { #ifdef MSDOS FILE *fin; fin = fopen("con", "r"); if (!fin) { fprintf(stderr, "s_paus: can't open con!\n"); fflush(stderr); exit(1); } s_1paus(fin); fclose(fin); #else fprintf(stderr, "To resume execution, execute a kill -%d %d command\n", PAUSESIG, getpid() ); signal1(PAUSESIG, waitpause); fflush(stderr); pause(); #endif } fprintf(stderr, "Execution resumes after PAUSE.\n"); fflush(stderr); return 0; /* NOT REACHED */ #ifdef __cplusplus } #endif } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/makefile.sy0000644000076500000240000000565613524616145024225 0ustar tamasstaff00000000000000# For making f2c.lib (here called syf2c.lib) with Symantec C++ . # Invoke with "make -f makefile.sy" . # In the CFLAGS line below, "-mn" is for NT and W9x. # For 32-bit addressing with MSDOS, change "-mn" to "-mx". # With Symantec, it is necessary to explicitly load main.obj . # To get signed zeros in write statements on IEEE-arithmetic systems, # add -DSIGNED_ZEROS to the CFLAGS assignment below and add signbit.obj # to the objects in the "w =" list below. CC = sc CFLAGS = -DMSDOS -D_POSIX_SOURCE -DNO_ONEXIT -s -mn -DUSE_CLOCK -DNO_My_ctype .c.obj: $(CC) -c $(CFLAGS) $*.c w = \ abort_.obj \ backspac.obj \ c_abs.obj \ c_cos.obj \ c_div.obj \ c_exp.obj \ c_log.obj \ c_sin.obj \ c_sqrt.obj \ cabs.obj \ close.obj \ d_abs.obj \ d_acos.obj \ d_asin.obj \ d_atan.obj \ d_atn2.obj \ d_cnjg.obj \ d_cos.obj \ d_cosh.obj \ d_dim.obj \ d_exp.obj \ d_imag.obj \ d_int.obj \ d_lg10.obj \ d_log.obj \ d_mod.obj \ d_nint.obj \ d_prod.obj \ d_sign.obj \ d_sin.obj \ d_sinh.obj \ d_sqrt.obj \ d_tan.obj \ d_tanh.obj \ derf_.obj \ derfc_.obj \ dfe.obj \ dolio.obj \ dtime_.obj \ due.obj \ ef1asc_.obj \ ef1cmc_.obj \ endfile.obj \ erf_.obj \ erfc_.obj \ err.obj \ etime_.obj \ exit_.obj \ f77_aloc.obj \ f77vers.obj \ fmt.obj \ fmtlib.obj \ ftell_.obj \ getarg_.obj \ getenv_.obj \ h_abs.obj \ h_dim.obj \ h_dnnt.obj \ h_indx.obj \ h_len.obj \ h_mod.obj \ h_nint.obj \ h_sign.obj \ hl_ge.obj \ hl_gt.obj \ hl_le.obj \ hl_lt.obj \ i77vers.obj \ i_abs.obj \ i_dim.obj \ i_dnnt.obj \ i_indx.obj \ i_len.obj \ i_mod.obj \ i_nint.obj \ i_sign.obj \ iargc_.obj \ iio.obj \ ilnw.obj \ inquire.obj \ l_ge.obj \ l_gt.obj \ l_le.obj \ l_lt.obj \ lbitbits.obj \ lbitshft.obj \ lread.obj \ lwrite.obj \ main.obj \ open.obj \ pow_ci.obj \ pow_dd.obj \ pow_di.obj \ pow_hh.obj \ pow_ii.obj \ pow_ri.obj \ pow_zi.obj \ pow_zz.obj \ r_abs.obj \ r_acos.obj \ r_asin.obj \ r_atan.obj \ r_atn2.obj \ r_cnjg.obj \ r_cos.obj \ r_cosh.obj \ r_dim.obj \ r_exp.obj \ r_imag.obj \ r_int.obj \ r_lg10.obj \ r_log.obj \ r_mod.obj \ r_nint.obj \ r_sign.obj \ r_sin.obj \ r_sinh.obj \ r_sqrt.obj \ r_tan.obj \ r_tanh.obj \ rdfmt.obj \ rewind.obj \ rsfe.obj \ rsli.obj \ rsne.obj \ s_cat.obj \ s_cmp.obj \ s_copy.obj \ s_paus.obj \ s_rnge.obj \ s_stop.obj \ sfe.obj \ sig_die.obj \ signal_.obj \ sue.obj \ system_.obj \ typesize.obj \ uio.obj \ util.obj \ uninit.obj \ wref.obj \ wrtfmt.obj \ wsfe.obj \ wsle.obj \ wsne.obj \ xwsne.obj \ z_abs.obj \ z_cos.obj \ z_div.obj \ z_exp.obj \ z_log.obj \ z_sin.obj \ z_sqrt.obj syf2c.lib: f2c.h signal1.h sysdep1.h $w lib /B /C syf2c.lib @libf2c.sy f2c.h: f2c.h0 copy f2c.h0 f2c.h signal1.h: signal1.h0 copy signal1.h0 signal1.h sysdep1.h: sysdep1.h0 copy sysdep1.h0 sysdep1.h signbit.obj uninit.obj: arith.h arith.h: arithchk.c scomptry.bat $(CC) $(CFLAGS) arithchk.c arithchk del arithchk.exe del arithchk.obj python-igraph-0.8.0/vendor/source/igraph/src/f2c/wsle.c0000644000076500000240000000127113524616145023176 0ustar tamasstaff00000000000000#include "f2c.h" #include "fio.h" #include "fmt.h" #include "lio.h" #include "string.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers integer s_wsle(a) cilist *a; #else integer s_wsle(cilist *a) #endif { int n; if(n=c_le(a)) return(n); f__reading=0; f__external=1; f__formatted=1; f__putn = x_putc; f__lioproc = l_write; L_len = LINE; f__donewrec = x_wSL; if(f__curunit->uwrt != 1 && f__nowwriting(f__curunit)) err(a->cierr, errno, "list output start"); return(0); } integer e_wsle(Void) { int n = f__putbuf('\n'); f__recpos=0; #ifdef ALWAYS_FLUSH if (!n && fflush(f__cf)) err(f__elist->cierr, errno, "write end"); #endif return(n); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/pow_zi.c0000644000076500000240000000152313524616145023533 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers VOID pow_zi(p, a, b) /* p = a**b */ doublecomplex *p, *a; integer *b; #else extern void z_div(doublecomplex*, doublecomplex*, doublecomplex*); void pow_zi(doublecomplex *p, doublecomplex *a, integer *b) /* p = a**b */ #endif { integer n; unsigned long u; double t; doublecomplex q, x; static doublecomplex one = {1.0, 0.0}; n = *b; q.r = 1; q.i = 0; if(n == 0) goto done; if(n < 0) { n = -n; z_div(&x, &one, a); } else { x.r = a->r; x.i = a->i; } for(u = n; ; ) { if(u & 01) { t = q.r * x.r - q.i * x.i; q.i = q.r * x.i + q.i * x.r; q.r = t; } if(u >>= 1) { t = x.r * x.r - x.i * x.i; x.i = 2 * x.r * x.i; x.r = t; } else break; } done: p->i = q.i; p->r = q.r; } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/c_div.c0000644000076500000240000000167013524616145023313 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers extern VOID sig_die(); VOID c_div(c, a, b) f2c_complex *a, *b, *c; #else extern void sig_die(const char*,int); void c_div(f2c_complex *c, f2c_complex *a, f2c_complex *b) #endif { double ratio, den; double abr, abi, cr; if( (abr = b->r) < 0.) abr = - abr; if( (abi = b->i) < 0.) abi = - abi; if( abr <= abi ) { if(abi == 0) { #ifdef IEEE_COMPLEX_DIVIDE float af, bf; af = bf = abr; if (a->i != 0 || a->r != 0) af = 1.; c->i = c->r = af / bf; return; #else sig_die("complex division by zero", 1); #endif } ratio = (double)b->r / b->i ; den = b->i * (1 + ratio*ratio); cr = (a->r*ratio + a->i) / den; c->i = (a->i*ratio - a->r) / den; } else { ratio = (double)b->i / b->r ; den = b->r * (1 + ratio*ratio); cr = (a->r + a->i*ratio) / den; c->i = (a->i - a->r*ratio) / den; } c->r = cr; } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/l_ge.c0000644000076500000240000000051613524616145023133 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers extern integer s_cmp(); logical l_ge(a,b,la,lb) char *a, *b; ftnlen la, lb; #else extern integer s_cmp(char *, char *, ftnlen, ftnlen); logical l_ge(char *a, char *b, ftnlen la, ftnlen lb) #endif { return(s_cmp(a,b,la,lb) >= 0); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/d_log.c0000644000076500000240000000036113524616145023307 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double log(); double d_log(x) doublereal *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double d_log(doublereal *x) #endif { return( log(*x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/z_div.c0000644000076500000240000000162113524616145023336 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers extern VOID sig_die(); VOID z_div(c, a, b) doublecomplex *a, *b, *c; #else extern void sig_die(const char*, int); void z_div(doublecomplex *c, doublecomplex *a, doublecomplex *b) #endif { double ratio, den; double abr, abi, cr; if( (abr = b->r) < 0.) abr = - abr; if( (abi = b->i) < 0.) abi = - abi; if( abr <= abi ) { if(abi == 0) { #ifdef IEEE_COMPLEX_DIVIDE if (a->i != 0 || a->r != 0) abi = 1.; c->i = c->r = abi / abr; return; #else sig_die("complex division by zero", 1); #endif } ratio = b->r / b->i ; den = b->i * (1 + ratio*ratio); cr = (a->r*ratio + a->i) / den; c->i = (a->i*ratio - a->r) / den; } else { ratio = b->i / b->r ; den = b->r * (1 + ratio*ratio); cr = (a->r + a->i*ratio) / den; c->i = (a->i - a->r*ratio) / den; } c->r = cr; } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/derf_.c0000644000076500000240000000035713524616145023307 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers double erf(); double derf_(x) doublereal *x; #else extern double erf(double); double derf_(doublereal *x) #endif { return( erf(*x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/lwrite.c0000644000076500000240000001101013524616145023522 0ustar tamasstaff00000000000000#include "f2c.h" #include "fio.h" #include "fmt.h" #include "lio.h" #ifdef __cplusplus extern "C" { #endif ftnint L_len; int f__Aquote; static VOID donewrec(Void) { if (f__recpos) (*f__donewrec)(); } static VOID #ifdef KR_headers lwrt_I(n) longint n; #else lwrt_I(longint n) #endif { char *p; int ndigit, sign; p = f__icvt(n, &ndigit, &sign, 10); if(f__recpos + ndigit >= L_len) donewrec(); PUT(' '); if (sign) PUT('-'); while(*p) PUT(*p++); } static VOID #ifdef KR_headers lwrt_L(n, len) ftnint n; ftnlen len; #else lwrt_L(ftnint n, ftnlen len) #endif { if(f__recpos+LLOGW>=L_len) donewrec(); wrt_L((Uint *)&n,LLOGW, len); } static VOID #ifdef KR_headers lwrt_A(p,len) char *p; ftnlen len; #else lwrt_A(char *p, ftnlen len) #endif { int a; char *p1, *pe; a = 0; pe = p + len; if (f__Aquote) { a = 3; if (len > 1 && p[len-1] == ' ') { while(--len > 1 && p[len-1] == ' '); pe = p + len; } p1 = p; while(p1 < pe) if (*p1++ == '\'') a++; } if(f__recpos+len+a >= L_len) donewrec(); if (a #ifndef OMIT_BLANK_CC || !f__recpos #endif ) PUT(' '); if (a) { PUT('\''); while(p < pe) { if (*p == '\'') PUT('\''); PUT(*p++); } PUT('\''); } else while(p < pe) PUT(*p++); } static int #ifdef KR_headers l_g(buf, n) char *buf; double n; #else l_g(char *buf, double n) #endif { #ifdef Old_list_output doublereal absn; char *fmt; absn = n; if (absn < 0) absn = -absn; fmt = LLOW <= absn && absn < LHIGH ? LFFMT : LEFMT; #ifdef USE_STRLEN sprintf(buf, fmt, n); return strlen(buf); #else return sprintf(buf, fmt, n); #endif #else register char *b, c, c1; b = buf; *b++ = ' '; if (n < 0) { *b++ = '-'; n = -n; } else *b++ = ' '; if (n == 0) { #ifdef SIGNED_ZEROS if (signbit_f2c(&n)) *b++ = '-'; #endif *b++ = '0'; *b++ = '.'; *b = 0; goto f__ret; } sprintf(b, LGFMT, n); switch(*b) { #ifndef WANT_LEAD_0 case '0': while(b[0] = b[1]) b++; break; #endif case 'i': case 'I': /* Infinity */ case 'n': case 'N': /* NaN */ while(*++b); break; default: /* Fortran 77 insists on having a decimal point... */ for(;; b++) switch(*b) { case 0: *b++ = '.'; *b = 0; goto f__ret; case '.': while(*++b); goto f__ret; case 'E': for(c1 = '.', c = 'E'; *b = c1; c1 = c, c = *++b); goto f__ret; } } f__ret: return b - buf; #endif } static VOID #ifdef KR_headers l_put(s) register char *s; #else l_put(register char *s) #endif { #ifdef KR_headers register void (*pn)() = f__putn; #else register void (*pn)(int) = f__putn; #endif register int c; while(c = *s++) (*pn)(c); } static VOID #ifdef KR_headers lwrt_F(n) double n; #else lwrt_F(double n) #endif { char buf[LEFBL]; if(f__recpos + l_g(buf,n) >= L_len) donewrec(); l_put(buf); } static VOID #ifdef KR_headers lwrt_C(a,b) double a,b; #else lwrt_C(double a, double b) #endif { char *ba, *bb, bufa[LEFBL], bufb[LEFBL]; int al, bl; al = l_g(bufa, a); for(ba = bufa; *ba == ' '; ba++) --al; bl = l_g(bufb, b) + 1; /* intentionally high by 1 */ for(bb = bufb; *bb == ' '; bb++) --bl; if(f__recpos + al + bl + 3 >= L_len) donewrec(); #ifdef OMIT_BLANK_CC else #endif PUT(' '); PUT('('); l_put(ba); PUT(','); if (f__recpos + bl >= L_len) { (*f__donewrec)(); #ifndef OMIT_BLANK_CC PUT(' '); #endif } l_put(bb); PUT(')'); } int #ifdef KR_headers l_write(number,ptr,len,type) ftnint *number,type; char *ptr; ftnlen len; #else l_write(ftnint *number, char *ptr, ftnlen len, ftnint type) #endif { #define Ptr ((flex *)ptr) int i; longint x; double y,z; real *xx; doublereal *yy; for(i=0;i< *number; i++) { switch((int)type) { default: f__fatal(117,"unknown type in lio"); case TYINT1: x = Ptr->flchar; goto xint; case TYSHORT: x=Ptr->flshort; goto xint; #ifdef Allow_TYQUAD case TYQUAD: x = Ptr->fllongint; goto xint; #endif case TYLONG: x=Ptr->flint; xint: lwrt_I(x); break; case TYREAL: y=Ptr->flreal; goto xfloat; case TYDREAL: y=Ptr->fldouble; xfloat: lwrt_F(y); break; case TYCOMPLEX: xx= &Ptr->flreal; y = *xx++; z = *xx; goto xcomplex; case TYDCOMPLEX: yy = &Ptr->fldouble; y= *yy++; z = *yy; xcomplex: lwrt_C(y,z); break; case TYLOGICAL1: x = Ptr->flchar; goto xlog; case TYLOGICAL2: x = Ptr->flshort; goto xlog; case TYLOGICAL: x = Ptr->flint; xlog: lwrt_L(Ptr->flint, len); break; case TYCHAR: lwrt_A(ptr,len); break; } ptr += len; } return(0); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/d_sinh.c0000644000076500000240000000036513524616145023473 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double sinh(); double d_sinh(x) doublereal *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double d_sinh(doublereal *x) #endif { return( sinh(*x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/typesize.c0000644000076500000240000000060613524616145024101 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif ftnlen f__typesize[] = { 0, 0, sizeof(shortint), sizeof(integer), sizeof(real), sizeof(doublereal), sizeof(f2c_complex), sizeof(doublecomplex), sizeof(logical), sizeof(char), 0, sizeof(integer1), sizeof(logical1), sizeof(shortlogical), #ifdef Allow_TYQUAD sizeof(longint), #endif 0}; #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/ftell_.c0000644000076500000240000000160413524616145023471 0ustar tamasstaff00000000000000#include "f2c.h" #include "fio.h" #ifdef __cplusplus extern "C" { #endif static FILE * #ifdef KR_headers unit_chk(Unit, who) integer Unit; char *who; #else unit_chk(integer Unit, const char *who) #endif { if (Unit >= MXUNIT || Unit < 0) f__fatal(101, who); return f__units[Unit].ufd; } integer #ifdef KR_headers ftell_(Unit) integer *Unit; #else ftell_(integer *Unit) #endif { FILE *f; return (f = unit_chk(*Unit, "ftell")) ? ftell(f) : -1L; } int #ifdef KR_headers fseek_(Unit, offset, whence) integer *Unit, *offset, *whence; #else fseek_(integer *Unit, integer *offset, integer *whence) #endif { FILE *f; int w = (int)*whence; #ifdef SEEK_SET static int wohin[3] = { SEEK_SET, SEEK_CUR, SEEK_END }; #endif if (w < 0 || w > 2) w = 0; #ifdef SEEK_SET w = wohin[w]; #endif return !(f = unit_chk(*Unit, "fseek")) || fseek(f, *offset, w) ? 1 : 0; } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/l_lt.c0000644000076500000240000000051513524616145023156 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers extern integer s_cmp(); logical l_lt(a,b,la,lb) char *a, *b; ftnlen la, lb; #else extern integer s_cmp(char *, char *, ftnlen, ftnlen); logical l_lt(char *a, char *b, ftnlen la, ftnlen lb) #endif { return(s_cmp(a,b,la,lb) < 0); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/r_sign.c0000644000076500000240000000037013524616145023504 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers double r_sign(a,b) real *a, *b; #else double r_sign(real *a, real *b) #endif { double x; x = (*a >= 0 ? *a : - *a); return( *b >= 0 ? x : -x); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/d_dim.c0000644000076500000240000000035013524616145023275 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers double d_dim(a,b) doublereal *a, *b; #else double d_dim(doublereal *a, doublereal *b) #endif { return( *a > *b ? *a - *b : 0); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/c_sqrt.c0000644000076500000240000000115113524616145023514 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers extern double sqrt(), f__cabs(); VOID c_sqrt(r, z) f2c_complex *r, *z; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif extern double f__cabs(double, double); void c_sqrt(f2c_complex *r, f2c_complex *z) #endif { double mag, t; double zi = z->i, zr = z->r; if( (mag = f__cabs(zr, zi)) == 0.) r->r = r->i = 0.; else if(zr > 0) { r->r = t = sqrt(0.5 * (mag + zr) ); t = zi / t; r->i = 0.5 * t; } else { t = sqrt(0.5 * (mag - zr) ); if(zi < 0) t = -t; r->i = t; t = zi / t; r->r = 0.5 * t; } } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/dolio.c0000644000076500000240000000072713524616145023337 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers extern int (*f__lioproc)(); integer do_lio(type,number,ptr,len) ftnint *number,*type; char *ptr; ftnlen len; #else extern int (*f__lioproc)(ftnint*, char*, ftnlen, ftnint); integer do_lio(ftnint *type, ftnint *number, char *ptr, ftnlen len) #endif { return((*f__lioproc)(number,ptr,len,*type)); } #ifdef __cplusplus } #endif #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/fp.h0000644000076500000240000000123113524616145022632 0ustar tamasstaff00000000000000#define FMAX 40 #define EXPMAXDIGS 8 #define EXPMAX 99999999 /* FMAX = max number of nonzero digits passed to atof() */ /* EXPMAX = 10^EXPMAXDIGS - 1 = largest allowed exponent absolute value */ #ifdef V10 /* Research Tenth-Edition Unix */ #include "local.h" #endif /* MAXFRACDIGS and MAXINTDIGS are for wrt_F -- bounds (not necessarily tight) on the maximum number of digits to the right and left of * the decimal point. */ #ifdef VAX #define MAXFRACDIGS 56 #define MAXINTDIGS 38 #else #ifdef CRAY #define MAXFRACDIGS 9880 #define MAXINTDIGS 9864 #else /* values that suffice for IEEE double */ #define MAXFRACDIGS 344 #define MAXINTDIGS 308 #endif #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/h_abs.c0000644000076500000240000000033213524616145023275 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers shortint h_abs(x) shortint *x; #else shortint h_abs(shortint *x) #endif { if(*x >= 0) return(*x); return(- *x); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/r_cnjg.c0000644000076500000240000000036713524616145023473 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers VOID r_cnjg(r, z) f2c_complex *r, *z; #else VOID r_cnjg(f2c_complex *r, f2c_complex *z) #endif { real zi = z->i; r->r = z->r; r->i = -zi; } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/c_log.c0000644000076500000240000000061413524616145023307 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers extern double log(), f__cabs(), atan2(); VOID c_log(r, z) f2c_complex *r, *z; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif extern double f__cabs(double, double); void c_log(f2c_complex *r, f2c_complex *z) #endif { double zi, zr; r->i = atan2(zi = z->i, zr = z->r); r->r = log( f__cabs(zr, zi) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/cabs.c0000644000076500000240000000075613524616145023143 0ustar tamasstaff00000000000000#ifdef KR_headers extern double sqrt(); double f__cabs(real, imag) double real, imag; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double f__cabs(double real, double imag) #endif { double temp; if(real < 0) real = -real; if(imag < 0) imag = -imag; if(imag > real){ temp = real; real = imag; imag = temp; } if((real+imag) == real) return(real); temp = imag/real; temp = real*sqrt(1.0 + temp*temp); /*overflow!!*/ return(temp); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/sysdep1.h0000644000076500000240000000247113524616145023624 0ustar tamasstaff00000000000000#ifndef SYSDEP_H_INCLUDED #define SYSDEP_H_INCLUDED #ifdef _MSC_VER #define FTRUNCATE chsize #endif #undef USE_LARGEFILE #ifndef NO_LONG_LONG #ifdef __sun__ #define USE_LARGEFILE #define OFF_T off64_t #endif #ifdef __linux__ #define USE_LARGEFILE #ifdef __GLIBC__ #define OFF_T __off64_t #else #define OFF_T off64_t #endif /* __GLIBC__ */ #endif /* __linux__ */ #ifdef _AIX43 #define _LARGE_FILES #define _LARGE_FILE_API #define USE_LARGEFILE #endif /*_AIX43*/ #ifdef __hpux #define _FILE64 #define _LARGEFILE64_SOURCE #define USE_LARGEFILE #endif /*__hpux*/ #ifdef __sgi #define USE_LARGEFILE #endif /*__sgi*/ #ifdef __FreeBSD__ #define OFF_T off_t #define FSEEK fseeko #define FTELL ftello #endif #ifdef USE_LARGEFILE #ifndef OFF_T #define OFF_T off64_t #endif #define _LARGEFILE_SOURCE #define _LARGEFILE64_SOURCE #include #include #define FOPEN fopen64 #define FREOPEN freopen64 #define FSEEK fseeko64 #define FSTAT fstat64 #define FTELL ftello64 #define FTRUNCATE ftruncate64 #define STAT stat64 #define STAT_ST stat64 #endif /*USE_LARGEFILE*/ #endif /*NO_LONG_LONG*/ #ifndef NON_UNIX_STDIO #ifndef USE_LARGEFILE #define _INCLUDE_POSIX_SOURCE /* for HP-UX */ #define _INCLUDE_XOPEN_SOURCE /* for HP-UX */ #include "sys/types.h" #include "sys/stat.h" #endif #endif #endif /*SYSDEP_H_INCLUDED*/ python-igraph-0.8.0/vendor/source/igraph/src/f2c/r_atan.c0000644000076500000240000000035113524616145023466 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double atan(); double r_atan(x) real *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double r_atan(real *x) #endif { return( atan(*x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/libf2c.sy0000644000076500000240000000400313524616145023572 0ustar tamasstaff00000000000000+abort_.obj & +backspac.obj & +c_abs.obj & +c_cos.obj & +c_div.obj & +c_exp.obj & +c_log.obj & +c_sin.obj & +c_sqrt.obj & +cabs.obj & +close.obj & +d_abs.obj & +d_acos.obj & +d_asin.obj & +d_atan.obj & +d_atn2.obj & +d_cnjg.obj & +d_cos.obj & +d_cosh.obj & +d_dim.obj & +d_exp.obj & +d_imag.obj & +d_int.obj & +d_lg10.obj & +d_log.obj & +d_mod.obj & +d_nint.obj & +d_prod.obj & +d_sign.obj & +d_sin.obj & +d_sinh.obj & +d_sqrt.obj & +d_tan.obj & +d_tanh.obj & +derf_.obj & +derfc_.obj & +dfe.obj & +dolio.obj & +dtime_.obj & +due.obj & +ef1asc_.obj & +ef1cmc_.obj & +endfile.obj & +erf_.obj & +erfc_.obj & +err.obj & +etime_.obj & +exit_.obj & +f77_aloc.obj & +f77vers.obj & +fmt.obj & +fmtlib.obj & +ftell_.obj & +getarg_.obj & +getenv_.obj & +h_abs.obj & +h_dim.obj & +h_dnnt.obj & +h_indx.obj & +h_len.obj & +h_mod.obj & +h_nint.obj & +h_sign.obj & +hl_ge.obj & +hl_gt.obj & +hl_le.obj & +hl_lt.obj & +i77vers.obj & +i_abs.obj & +i_dim.obj & +i_dnnt.obj & +i_indx.obj & +i_len.obj & +i_mod.obj & +i_nint.obj & +i_sign.obj & +iargc_.obj & +iio.obj & +ilnw.obj & +inquire.obj & +l_ge.obj & +l_gt.obj & +l_le.obj & +l_lt.obj & +lbitbits.obj & +lbitshft.obj & +lread.obj & +lwrite.obj & +main.obj & +open.obj & +pow_ci.obj & +pow_dd.obj & +pow_di.obj & +pow_hh.obj & +pow_ii.obj & +pow_ri.obj & +pow_zi.obj & +pow_zz.obj & +r_abs.obj & +r_acos.obj & +r_asin.obj & +r_atan.obj & +r_atn2.obj & +r_cnjg.obj & +r_cos.obj & +r_cosh.obj & +r_dim.obj & +r_exp.obj & +r_imag.obj & +r_int.obj & +r_lg10.obj & +r_log.obj & +r_mod.obj & +r_nint.obj & +r_sign.obj & +r_sin.obj & +r_sinh.obj & +r_sqrt.obj & +r_tan.obj & +r_tanh.obj & +rdfmt.obj & +rewind.obj & +rsfe.obj & +rsli.obj & +rsne.obj & +s_cat.obj & +s_cmp.obj & +s_copy.obj & +s_paus.obj & +s_rnge.obj & +s_stop.obj & +sfe.obj & +sig_die.obj & +signal_.obj & +sue.obj & +system_.obj & +typesize.obj & +uio.obj & +uninit.obj & +util.obj & +wref.obj & +wrtfmt.obj & +wsfe.obj & +wsle.obj & +wsne.obj & +xwsne.obj & +z_abs.obj & +z_cos.obj & +z_div.obj & +z_exp.obj & +z_log.obj & +z_sin.obj & +z_sqrt.obj python-igraph-0.8.0/vendor/source/igraph/src/f2c/inquire.c0000644000076500000240000000525413524616145023705 0ustar tamasstaff00000000000000#include "f2c.h" #include "fio.h" #include "string.h" #ifdef NON_UNIX_STDIO #ifndef MSDOS #include "unistd.h" /* for access() */ #endif #endif #ifdef KR_headers integer f_inqu(a) inlist *a; #else #ifdef __cplusplus extern "C" integer f_inqu(inlist*); #endif #ifdef MSDOS #undef abs #undef min #undef max #include "io.h" #endif integer f_inqu(inlist *a) #endif { flag byfile; int i; #ifndef NON_UNIX_STDIO int n; #endif unit *p; char buf[256]; long x; if(a->infile!=NULL) { byfile=1; g_char(a->infile,a->infilen,buf); #ifdef NON_UNIX_STDIO x = access(buf,0) ? -1 : 0; for(i=0,p=NULL;iinunitinunit>=0) { p= &f__units[a->inunit]; } else { p=NULL; } } if(a->inex!=NULL) if(byfile && x != -1 || !byfile && p!=NULL) *a->inex=1; else *a->inex=0; if(a->inopen!=NULL) if(byfile) *a->inopen=(p!=NULL); else *a->inopen=(p!=NULL && p->ufd!=NULL); if(a->innum!=NULL) *a->innum= p-f__units; if(a->innamed!=NULL) if(byfile || p!=NULL && p->ufnm!=NULL) *a->innamed=1; else *a->innamed=0; if(a->inname!=NULL) if(byfile) b_char(buf,a->inname,a->innamlen); else if(p!=NULL && p->ufnm!=NULL) b_char(p->ufnm,a->inname,a->innamlen); if(a->inacc!=NULL && p!=NULL && p->ufd!=NULL) if(p->url) b_char("DIRECT",a->inacc,a->inacclen); else b_char("SEQUENTIAL",a->inacc,a->inacclen); if(a->inseq!=NULL) if(p!=NULL && p->url) b_char("NO",a->inseq,a->inseqlen); else b_char("YES",a->inseq,a->inseqlen); if(a->indir!=NULL) if(p==NULL || p->url) b_char("YES",a->indir,a->indirlen); else b_char("NO",a->indir,a->indirlen); if(a->infmt!=NULL) if(p!=NULL && p->ufmt==0) b_char("UNFORMATTED",a->infmt,a->infmtlen); else b_char("FORMATTED",a->infmt,a->infmtlen); if(a->inform!=NULL) if(p!=NULL && p->ufmt==0) b_char("NO",a->inform,a->informlen); else b_char("YES",a->inform,a->informlen); if(a->inunf) if(p!=NULL && p->ufmt==0) b_char("YES",a->inunf,a->inunflen); else if (p!=NULL) b_char("NO",a->inunf,a->inunflen); else b_char("UNKNOWN",a->inunf,a->inunflen); if(a->inrecl!=NULL && p!=NULL) *a->inrecl=p->url; if(a->innrec!=NULL && p!=NULL && p->url>0) *a->innrec=(ftnint)(FTELL(p->ufd)/p->url+1); if(a->inblank && p!=NULL && p->ufmt) if(p->ublnk) b_char("ZERO",a->inblank,a->inblanklen); else b_char("NULL",a->inblank,a->inblanklen); return(0); } python-igraph-0.8.0/vendor/source/igraph/src/f2c/xsum0.out0000644000076500000240000000755113524616145023674 0ustar tamasstaff00000000000000Notice 76f23b4 1212 README 16a3882f 16876 abort_.c f51c808 304 arithchk.c fae7c666 5171 backspac.c 10ebf554 1328 c_abs.c fec22c59 272 c_cos.c 18fc0ea3 354 c_div.c 1797c106 936 c_exp.c 1b85b1fc 349 c_log.c 28cdfed 384 c_sin.c 1ccaedc8 350 c_sqrt.c f1ee88d5 605 cabs.c f3d3b5f2 494 close.c 173f01de 1393 comptry.bat f8a8a0d5 125 ctype.c f553a125 40 ctype.h 1e54977d 1139 d_abs.c e58094ef 218 d_acos.c e5ecf93d 245 d_asin.c e12ceeff 245 d_atan.c 53034db 245 d_atn2.c ff8a1a78 271 d_cnjg.c 1c27c728 255 d_cos.c c0eb625 241 d_cosh.c 11dc4adb 245 d_dim.c e1ccb774 232 d_exp.c 1879c41c 241 d_imag.c fe9c703e 201 d_int.c f5de3566 269 d_lg10.c 1a1d7b77 291 d_log.c 1b368adf 241 d_mod.c f540cf24 688 d_nint.c ff913b40 281 d_prod.c ad4856b 207 d_sign.c 9562fc5 266 d_sin.c 6e3f542 241 d_sinh.c 18b22950 245 d_sqrt.c 17e1db09 245 d_tan.c ec93ebdb 241 d_tanh.c 1c55d15b 245 derf_.c f85e74a3 239 derfc_.c e96b7667 253 dfe.c 1d658105 2624 dolio.c 19c9fbd9 471 dtime_.c c982be4 972 due.c ee219f6d 1624 ef1asc_.c e0576e63 521 ef1cmc_.c ea5ad9e8 427 endfile.c 6f7201d 2838 erf_.c e82f7790 270 erfc_.c ba65441 275 err.c e59d1707 6442 etime_.c 19d1fdad 839 exit_.c ff4baa3a 543 f2c.h0 e770b7d8 4688 f2ch.add ef66bf17 6060 f77_aloc.c f8daf96e 684 f77vers.c ed1c96fa 4933 fio.h e41d245e 2939 fmt.c f9a1bb94 8566 fmt.h ec84ce17 2006 fmtlib.c eefc6a27 865 fp.h 100fb355 665 ftell_.c 78218d 900 ftell64_.c e2c4b21e 917 getarg_.c fd514f59 592 getenv_.c f4b06e2 1223 h_abs.c e4443109 218 h_dim.c c6e48bc 230 h_dnnt.c f6bb90e 294 h_indx.c ef8461eb 442 h_len.c e8c3633 205 h_mod.c 7355bd0 207 h_nint.c f0da3396 281 h_sign.c f1370ffd 266 hl_ge.c ed792501 346 hl_gt.c feeacbd9 345 hl_le.c f6fb5d6e 346 hl_lt.c 18501419 345 i77vers.c f57b8ef2 18128 i_abs.c 12ab51ab 214 i_dim.c f2a56785 225 i_dnnt.c 11748482 291 i_indx.c fb59026f 430 i_len.c 17d17252 203 i_mod.c bef73ae 211 i_nint.c e494b804 278 i_sign.c fa015b08 260 iargc_.c 49abda3 196 iio.c f958b627 2639 ilnw.c fe0ab14b 1125 inquire.c 1883d542 2732 l_ge.c f4710e74 334 l_gt.c e8db94a7 333 l_le.c c9c0a99 334 l_lt.c 767e79f 333 lbitbits.c 33fe981 1097 lbitshft.c e81981d2 258 libf2c.lbc 10af591e 1594 libf2c.sy fd5f568f 2051 lio.h 805735d 1564 lread.c f1e54a1f 14739 lwrite.c f80da63f 4616 main.c 371f60f 2230 makefile.sy 174ccb83 2990 makefile.u fce2cb5f 7302 makefile.vc 179d7b1c 2942 makefile.wat 18b044ac 2936 math.hvc 19bb2d07 50 mkfile.plan9 e67e471e 5174 open.c e7bcc295 5701 pow_ci.c fa934cec 412 pow_dd.c f004559b 276 pow_di.c a4db539 448 pow_hh.c d1a45a9 489 pow_ii.c 1fcf2742 488 pow_qq.c e6a32de6 516 pow_ri.c e7d9fc2a 436 pow_zi.c 1b894af7 851 pow_zz.c f81a06b5 549 qbitbits.c fdb9910e 1151 qbitshft.c 873054d 258 r_abs.c f471383c 206 r_acos.c 1a6aca63 233 r_asin.c e8555587 233 r_atan.c eac25444 233 r_atn2.c f611bea 253 r_cnjg.c a8d7805 235 r_cos.c fdef1ece 229 r_cosh.c f05d1ae 233 r_dim.c ee23e1a8 214 r_exp.c 1da16cd7 229 r_imag.c 166ad0f3 189 r_int.c fc80b9a8 257 r_lg10.c e876cfab 279 r_log.c 2062254 229 r_mod.c 187363fc 678 r_nint.c 6edcbb2 269 r_sign.c 1ae32441 248 r_sin.c c3d968 229 r_sinh.c 1090c850 233 r_sqrt.c ffbb0625 233 r_tan.c fe85179d 229 r_tanh.c 10ffcc5b 233 rawio.h 1ab49f7c 718 rdfmt.c 7222fee 8925 rewind.c e4c6236f 475 rsfe.c eb9e882c 1492 rsli.c 11f59b61 1785 rsne.c fea7e5be 11585 s_cat.c 164a6ff1 1458 s_cmp.c e69e8b60 722 s_copy.c 1e258852 1024 s_paus.c e37cfe6 1617 s_rnge.c e8cf83a3 759 s_stop.c ffa80b24 762 scomptry.bat ed740ad8 181 sfe.c 1e10bda3 828 sig_die.c 12eb0eac 689 signal1.h0 1d43ee57 842 signal_.c f3ef9cfc 299 signbit.c e37eac06 330 sue.c 9705ecf 1865 sysdep1.h0 1812022d 1202 system_.c ff72e46c 652 typesize.c eee307ae 386 uio.c e354a770 1619 uninit.c fe760fb0 7584 util.c 172fa76e 972 wref.c 17bbfb7b 4747 wrtfmt.c 113fc4f9 7506 wsfe.c f2d1fe4d 1280 wsle.c fe50b4c9 697 wsne.c 428bfda 479 xwsne.c 185c4bdc 1174 z_abs.c 1fa0640d 268 z_cos.c facccd9b 363 z_div.c e6f03676 913 z_exp.c 1a8506e8 357 z_log.c 6bf3b22 2729 z_sin.c 1aa35b59 359 z_sqrt.c 1864d867 581 python-igraph-0.8.0/vendor/source/igraph/src/f2c/rewind.c0000644000076500000240000000073313524616145023516 0ustar tamasstaff00000000000000#include "f2c.h" #include "fio.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers integer f_rew(a) alist *a; #else integer f_rew(alist *a) #endif { unit *b; if(a->aunit>=MXUNIT || a->aunit<0) err(a->aerr,101,"rewind"); b = &f__units[a->aunit]; if(b->ufd == NULL || b->uwrt == 3) return(0); if(!b->useek) err(a->aerr,106,"rewind") if(b->uwrt) { (void) t_runc(a); b->uwrt = 3; } rewind(b->ufd); b->uend=0; return(0); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/rdfmt.c0000644000076500000240000002133513524616145023343 0ustar tamasstaff00000000000000#include "f2c.h" #include "fio.h" #ifdef KR_headers extern double atof(); #define Const /*nothing*/ #else #define Const const #undef abs #undef min #undef max #include "stdlib.h" #endif #include "fmt.h" #include "fp.h" #include "ctype.h" #ifdef __cplusplus extern "C" { #endif static int #ifdef KR_headers rd_Z(n,w,len) Uint *n; ftnlen len; #else rd_Z(Uint *n, int w, ftnlen len) #endif { long x[9]; char *s, *s0, *s1, *se, *t; Const char *sc; int ch, i, w1, w2; static char hex[256]; static int one = 1; int bad = 0; if (!hex['0']) { sc = "0123456789"; while(ch = *sc++) hex[ch] = ch - '0' + 1; sc = "ABCDEF"; while(ch = *sc++) hex[ch] = hex[ch + 'a' - 'A'] = ch - 'A' + 11; } s = s0 = (char *)x; s1 = (char *)&x[4]; se = (char *)&x[8]; if (len > 4*sizeof(long)) return errno = 117; while (w) { GET(ch); if (ch==',' || ch=='\n') break; w--; if (ch > ' ') { if (!hex[ch & 0xff]) bad++; *s++ = ch; if (s == se) { /* discard excess characters */ for(t = s0, s = s1; t < s1;) *t++ = *s++; s = s1; } } } if (bad) return errno = 115; w = (int)len; w1 = s - s0; w2 = w1+1 >> 1; t = (char *)n; if (*(char *)&one) { /* little endian */ t += w - 1; i = -1; } else i = 1; for(; w > w2; t += i, --w) *t = 0; if (!w) return 0; if (w < w2) s0 = s - (w << 1); else if (w1 & 1) { *t = hex[*s0++ & 0xff] - 1; if (!--w) return 0; t += i; } do { *t = hex[*s0 & 0xff]-1 << 4 | hex[s0[1] & 0xff]-1; t += i; s0 += 2; } while(--w); return 0; } static int #ifdef KR_headers rd_I(n,w,len, base) Uint *n; int w; ftnlen len; register int base; #else rd_I(Uint *n, int w, ftnlen len, register int base) #endif { int ch, sign; longint x = 0; if (w <= 0) goto have_x; for(;;) { GET(ch); if (ch != ' ') break; if (!--w) goto have_x; } sign = 0; switch(ch) { case ',': case '\n': w = 0; goto have_x; case '-': sign = 1; case '+': break; default: if (ch >= '0' && ch <= '9') { x = ch - '0'; break; } goto have_x; } while(--w) { GET(ch); if (ch >= '0' && ch <= '9') { x = x*base + ch - '0'; continue; } if (ch != ' ') { if (ch == '\n' || ch == ',') w = 0; break; } if (f__cblank) x *= base; } if (sign) x = -x; have_x: if(len == sizeof(integer)) n->il=x; else if(len == sizeof(char)) n->ic = (char)x; #ifdef Allow_TYQUAD else if (len == sizeof(longint)) n->ili = x; #endif else n->is = (short)x; if (w) { while(--w) GET(ch); return errno = 115; } return 0; } static int #ifdef KR_headers rd_L(n,w,len) ftnint *n; ftnlen len; #else rd_L(ftnint *n, int w, ftnlen len) #endif { int ch, dot, lv; if (w <= 0) goto bad; for(;;) { GET(ch); --w; if (ch != ' ') break; if (!w) goto bad; } dot = 0; retry: switch(ch) { case '.': if (dot++ || !w) goto bad; GET(ch); --w; goto retry; case 't': case 'T': lv = 1; break; case 'f': case 'F': lv = 0; break; default: bad: for(; w > 0; --w) GET(ch); /* no break */ case ',': case '\n': return errno = 116; } switch(len) { case sizeof(char): *(char *)n = (char)lv; break; case sizeof(short): *(short *)n = (short)lv; break; default: *n = lv; } while(w-- > 0) { GET(ch); if (ch == ',' || ch == '\n') break; } return 0; } static int #ifdef KR_headers rd_F(p, w, d, len) ufloat *p; ftnlen len; #else rd_F(ufloat *p, int w, int d, ftnlen len) #endif { char s[FMAX+EXPMAXDIGS+4]; register int ch; register char *sp, *spe, *sp1; double x; int scale1, se; long e, exp; sp1 = sp = s; spe = sp + FMAX; exp = -d; x = 0.; do { GET(ch); w--; } while (ch == ' ' && w); switch(ch) { case '-': *sp++ = ch; sp1++; spe++; case '+': if (!w) goto zero; --w; GET(ch); } while(ch == ' ') { blankdrop: if (!w--) goto zero; GET(ch); } while(ch == '0') { if (!w--) goto zero; GET(ch); } if (ch == ' ' && f__cblank) goto blankdrop; scale1 = f__scale; while(isdigit(ch)) { digloop1: if (sp < spe) *sp++ = ch; else ++exp; digloop1e: if (!w--) goto done; GET(ch); } if (ch == ' ') { if (f__cblank) { ch = '0'; goto digloop1; } goto digloop1e; } if (ch == '.') { exp += d; if (!w--) goto done; GET(ch); if (sp == sp1) { /* no digits yet */ while(ch == '0') { skip01: --exp; skip0: if (!w--) goto done; GET(ch); } if (ch == ' ') { if (f__cblank) goto skip01; goto skip0; } } while(isdigit(ch)) { digloop2: if (sp < spe) { *sp++ = ch; --exp; } digloop2e: if (!w--) goto done; GET(ch); } if (ch == ' ') { if (f__cblank) { ch = '0'; goto digloop2; } goto digloop2e; } } switch(ch) { default: break; case '-': se = 1; goto signonly; case '+': se = 0; goto signonly; case 'e': case 'E': case 'd': case 'D': if (!w--) goto bad; GET(ch); while(ch == ' ') { if (!w--) goto bad; GET(ch); } se = 0; switch(ch) { case '-': se = 1; case '+': signonly: if (!w--) goto bad; GET(ch); } while(ch == ' ') { if (!w--) goto bad; GET(ch); } if (!isdigit(ch)) goto bad; e = ch - '0'; for(;;) { if (!w--) { ch = '\n'; break; } GET(ch); if (!isdigit(ch)) { if (ch == ' ') { if (f__cblank) ch = '0'; else continue; } else break; } e = 10*e + ch - '0'; if (e > EXPMAX && sp > sp1) goto bad; } if (se) exp -= e; else exp += e; scale1 = 0; } switch(ch) { case '\n': case ',': break; default: bad: return (errno = 115); } done: if (sp > sp1) { while(*--sp == '0') ++exp; if (exp -= scale1) sprintf(sp+1, "e%ld", exp); else sp[1] = 0; x = atof(s); } zero: if (len == sizeof(real)) p->pf = x; else p->pd = x; return(0); } static int #ifdef KR_headers rd_A(p,len) char *p; ftnlen len; #else rd_A(char *p, ftnlen len) #endif { int i,ch; for(i=0;i=len) { for(i=0;i0;f__cursor--) if((ch=(*f__getn)())<0) return(ch); if(f__cursor<0) { if(f__recpos+f__cursor < 0) /*err(elist->cierr,110,"fmt")*/ f__cursor = -f__recpos; /* is this in the standard? */ if(f__external == 0) { extern char *f__icptr; f__icptr += f__cursor; } else if(f__curunit && f__curunit->useek) (void) FSEEK(f__cf, f__cursor,SEEK_CUR); else err(f__elist->cierr,106,"fmt"); f__recpos += f__cursor; f__cursor=0; } switch(p->op) { default: fprintf(stderr,"rd_ed, unexpected code: %d\n", p->op); sig_die(f__fmtbuf, 1); case IM: case I: ch = rd_I((Uint *)ptr,p->p1,len, 10); break; /* O and OM don't work right for character, double, complex, */ /* or doublecomplex, and they differ from Fortran 90 in */ /* showing a minus sign for negative values. */ case OM: case O: ch = rd_I((Uint *)ptr, p->p1, len, 8); break; case L: ch = rd_L((ftnint *)ptr,p->p1,len); break; case A: ch = rd_A(ptr,len); break; case AW: ch = rd_AW(ptr,p->p1,len); break; case E: case EE: case D: case G: case GE: case F: ch = rd_F((ufloat *)ptr,p->p1,p->p2.i[0],len); break; /* Z and ZM assume 8-bit bytes. */ case ZM: case Z: ch = rd_Z((Uint *)ptr, p->p1, len); break; } if(ch == 0) return(ch); else if(ch == EOF) return(EOF); if (f__cf) clearerr(f__cf); return(errno); } int #ifdef KR_headers rd_ned(p) struct syl *p; #else rd_ned(struct syl *p) #endif { switch(p->op) { default: fprintf(stderr,"rd_ned, unexpected code: %d\n", p->op); sig_die(f__fmtbuf, 1); case APOS: return(rd_POS(p->p2.s)); case H: return(rd_H(p->p1,p->p2.s)); case SLASH: return((*f__donewrec)()); case TR: case X: f__cursor += p->p1; return(1); case T: f__cursor=p->p1-f__recpos - 1; return(1); case TL: f__cursor -= p->p1; if(f__cursor < -f__recpos) /* TL1000, 1X */ f__cursor = -f__recpos; return(1); } } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/l_gt.c0000644000076500000240000000051513524616145023151 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers extern integer s_cmp(); logical l_gt(a,b,la,lb) char *a, *b; ftnlen la, lb; #else extern integer s_cmp(char *, char *, ftnlen, ftnlen); logical l_gt(char *a, char *b, ftnlen la, ftnlen lb) #endif { return(s_cmp(a,b,la,lb) > 0); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/pow_ii.c0000644000076500000240000000075013524616145023513 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers integer pow_ii(ap, bp) integer *ap, *bp; #else integer pow_ii(integer *ap, integer *bp) #endif { integer pow, x, n; unsigned long u; x = *ap; n = *bp; if (n <= 0) { if (n == 0 || x == 1) return 1; if (x != -1) return x == 0 ? 1/x : 0; n = -n; } u = n; for(pow = 1; ; ) { if(u & 01) pow *= x; if(u >>= 1) x *= x; else break; } return(pow); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/rsne.c0000644000076500000240000002650113524616145023176 0ustar tamasstaff00000000000000#include "f2c.h" #include "fio.h" #include "lio.h" #define MAX_NL_CACHE 3 /* maximum number of namelist hash tables to cache */ #define MAXDIM 20 /* maximum number of subscripts */ struct dimen { ftnlen extent; ftnlen curval; ftnlen delta; ftnlen stride; }; typedef struct dimen dimen; struct hashentry { struct hashentry *next; char *name; Vardesc *vd; }; typedef struct hashentry hashentry; struct hashtab { struct hashtab *next; Namelist *nl; int htsize; hashentry *tab[1]; }; typedef struct hashtab hashtab; static hashtab *nl_cache; static int n_nlcache; static hashentry **zot; static int colonseen; extern ftnlen f__typesize[]; extern flag f__lquit; extern int f__lcount, nml_read; extern int t_getc(Void); #ifdef KR_headers extern char *malloc(), *memset(); #define Const /*nothing*/ #ifdef ungetc static int un_getc(x,f__cf) int x; FILE *f__cf; { return ungetc(x,f__cf); } #else #define un_getc ungetc extern int ungetc(); #endif #else #define Const const #undef abs #undef min #undef max #include "stdlib.h" #include "string.h" #ifdef __cplusplus extern "C" { #endif #ifdef ungetc static int un_getc(int x, FILE *f__cf) { return ungetc(x,f__cf); } #else #define un_getc ungetc extern int ungetc(int, FILE*); /* for systems with a buggy stdio.h */ #endif #endif static Vardesc * #ifdef KR_headers hash(ht, s) hashtab *ht; register char *s; #else hash(hashtab *ht, register char *s) #endif { register int c, x; register hashentry *h; char *s0 = s; for(x = 0; c = *s++; x = x & 0x4000 ? ((x << 1) & 0x7fff) + 1 : x << 1) x += c; for(h = *(zot = ht->tab + x % ht->htsize); h; h = h->next) if (!strcmp(s0, h->name)) return h->vd; return 0; } hashtab * #ifdef KR_headers mk_hashtab(nl) Namelist *nl; #else mk_hashtab(Namelist *nl) #endif { int nht, nv; hashtab *ht; Vardesc *v, **vd, **vde; hashentry *he; hashtab **x, **x0, *y; for(x = &nl_cache; y = *x; x0 = x, x = &y->next) if (nl == y->nl) return y; if (n_nlcache >= MAX_NL_CACHE) { /* discard least recently used namelist hash table */ y = *x0; free((char *)y->next); y->next = 0; } else n_nlcache++; nv = nl->nvars; if (nv >= 0x4000) nht = 0x7fff; else { for(nht = 1; nht < nv; nht <<= 1); nht += nht - 1; } ht = (hashtab *)malloc(sizeof(hashtab) + (nht-1)*sizeof(hashentry *) + nv*sizeof(hashentry)); if (!ht) return 0; he = (hashentry *)&ht->tab[nht]; ht->nl = nl; ht->htsize = nht; ht->next = nl_cache; nl_cache = ht; memset((char *)ht->tab, 0, nht*sizeof(hashentry *)); vd = nl->vars; vde = vd + nv; while(vd < vde) { v = *vd++; if (!hash(ht, v->name)) { he->next = *zot; *zot = he; he->name = v->name; he->vd = v; he++; } } return ht; } static char Alpha[256], Alphanum[256]; static VOID nl_init(Void) { Const char *s; int c; if(!f__init) f_init(); for(s = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"; c = *s++; ) Alpha[c] = Alphanum[c] = Alpha[c + 'a' - 'A'] = Alphanum[c + 'a' - 'A'] = c; for(s = "0123456789_"; c = *s++; ) Alphanum[c] = c; } #define GETC(x) (x=(*l_getc)()) #define Ungetc(x,y) (*l_ungetc)(x,y) static int #ifdef KR_headers getname(s, slen) register char *s; int slen; #else getname(register char *s, int slen) #endif { register char *se = s + slen - 1; register int ch; GETC(ch); if (!(*s++ = Alpha[ch & 0xff])) { if (ch != EOF) ch = 115; errfl(f__elist->cierr, ch, "namelist read"); } while(*s = Alphanum[GETC(ch) & 0xff]) if (s < se) s++; if (ch == EOF) err(f__elist->cierr, EOF, "namelist read"); if (ch > ' ') Ungetc(ch,f__cf); return *s = 0; } static int #ifdef KR_headers getnum(chp, val) int *chp; ftnlen *val; #else getnum(int *chp, ftnlen *val) #endif { register int ch, sign; register ftnlen x; while(GETC(ch) <= ' ' && ch >= 0); if (ch == '-') { sign = 1; GETC(ch); } else { sign = 0; if (ch == '+') GETC(ch); } x = ch - '0'; if (x < 0 || x > 9) return 115; while(GETC(ch) >= '0' && ch <= '9') x = 10*x + ch - '0'; while(ch <= ' ' && ch >= 0) GETC(ch); if (ch == EOF) return EOF; *val = sign ? -x : x; *chp = ch; return 0; } static int #ifdef KR_headers getdimen(chp, d, delta, extent, x1) int *chp; dimen *d; ftnlen delta, extent, *x1; #else getdimen(int *chp, dimen *d, ftnlen delta, ftnlen extent, ftnlen *x1) #endif { register int k; ftnlen x2, x3; if (k = getnum(chp, x1)) return k; x3 = 1; if (*chp == ':') { if (k = getnum(chp, &x2)) return k; x2 -= *x1; if (*chp == ':') { if (k = getnum(chp, &x3)) return k; if (!x3) return 123; x2 /= x3; colonseen = 1; } if (x2 < 0 || x2 >= extent) return 123; d->extent = x2 + 1; } else d->extent = 1; d->curval = 0; d->delta = delta; d->stride = x3; return 0; } #ifndef No_Namelist_Questions static Void #ifdef KR_headers print_ne(a) cilist *a; #else print_ne(cilist *a) #endif { flag intext = f__external; int rpsave = f__recpos; FILE *cfsave = f__cf; unit *usave = f__curunit; cilist t; t = *a; t.ciunit = 6; s_wsne(&t); fflush(f__cf); f__external = intext; f__reading = 1; f__recpos = rpsave; f__cf = cfsave; f__curunit = usave; f__elist = a; } #endif static char where0[] = "namelist read start "; int #ifdef KR_headers x_rsne(a) cilist *a; #else x_rsne(cilist *a) #endif { int ch, got1, k, n, nd, quote, readall; Namelist *nl; static char where[] = "namelist read"; char buf[64]; hashtab *ht; Vardesc *v; dimen *dn, *dn0, *dn1; ftnlen *dims, *dims1; ftnlen b, b0, b1, ex, no, nomax, size, span; ftnint no1, no2, type; char *vaddr; long iva, ivae; dimen dimens[MAXDIM], substr; if (!Alpha['a']) nl_init(); f__reading=1; f__formatted=1; got1 = 0; top: for(;;) switch(GETC(ch)) { case EOF: eof: err(a->ciend,(EOF),where0); case '&': case '$': goto have_amp; #ifndef No_Namelist_Questions case '?': print_ne(a); continue; #endif default: if (ch <= ' ' && ch >= 0) continue; #ifndef No_Namelist_Comments while(GETC(ch) != '\n') if (ch == EOF) goto eof; #else errfl(a->cierr, 115, where0); #endif } have_amp: if (ch = getname(buf,sizeof(buf))) return ch; nl = (Namelist *)a->cifmt; if (strcmp(buf, nl->name)) #ifdef No_Bad_Namelist_Skip errfl(a->cierr, 118, where0); #else { fprintf(stderr, "Skipping namelist \"%s\": seeking namelist \"%s\".\n", buf, nl->name); fflush(stderr); for(;;) switch(GETC(ch)) { case EOF: err(a->ciend, EOF, where0); case '/': case '&': case '$': if (f__external) e_rsle(); else z_rnew(); goto top; case '"': case '\'': quote = ch; more_quoted: while(GETC(ch) != quote) if (ch == EOF) err(a->ciend, EOF, where0); if (GETC(ch) == quote) goto more_quoted; Ungetc(ch,f__cf); default: continue; } } #endif ht = mk_hashtab(nl); if (!ht) errfl(f__elist->cierr, 113, where0); for(;;) { for(;;) switch(GETC(ch)) { case EOF: if (got1) return 0; err(a->ciend, EOF, where0); case '/': case '$': case '&': return 0; default: if (ch <= ' ' && ch >= 0 || ch == ',') continue; Ungetc(ch,f__cf); if (ch = getname(buf,sizeof(buf))) return ch; goto havename; } havename: v = hash(ht,buf); if (!v) errfl(a->cierr, 119, where); while(GETC(ch) <= ' ' && ch >= 0); vaddr = v->addr; type = v->type; if (type < 0) { size = -type; type = TYCHAR; } else size = f__typesize[type]; ivae = size; iva = readall = 0; if (ch == '(' /*)*/ ) { dn = dimens; if (!(dims = v->dims)) { if (type != TYCHAR) errfl(a->cierr, 122, where); if (k = getdimen(&ch, dn, (ftnlen)size, (ftnlen)size, &b)) errfl(a->cierr, k, where); if (ch != ')') errfl(a->cierr, 115, where); b1 = dn->extent; if (--b < 0 || b + b1 > size) return 124; iva += b; size = b1; while(GETC(ch) <= ' ' && ch >= 0); goto scalar; } nd = (int)dims[0]; nomax = span = dims[1]; ivae = iva + size*nomax; colonseen = 0; if (k = getdimen(&ch, dn, size, nomax, &b)) errfl(a->cierr, k, where); no = dn->extent; b0 = dims[2]; dims1 = dims += 3; ex = 1; for(n = 1; n++ < nd; dims++) { if (ch != ',') errfl(a->cierr, 115, where); dn1 = dn + 1; span /= *dims; if (k = getdimen(&ch, dn1, dn->delta**dims, span, &b1)) errfl(a->cierr, k, where); ex *= *dims; b += b1*ex; no *= dn1->extent; dn = dn1; } if (ch != ')') errfl(a->cierr, 115, where); readall = 1 - colonseen; b -= b0; if (b < 0 || b >= nomax) errfl(a->cierr, 125, where); iva += size * b; dims = dims1; while(GETC(ch) <= ' ' && ch >= 0); no1 = 1; dn0 = dimens; if (type == TYCHAR && ch == '(' /*)*/) { if (k = getdimen(&ch, &substr, size, size, &b)) errfl(a->cierr, k, where); if (ch != ')') errfl(a->cierr, 115, where); b1 = substr.extent; if (--b < 0 || b + b1 > size) return 124; iva += b; b0 = size; size = b1; while(GETC(ch) <= ' ' && ch >= 0); if (b1 < b0) goto delta_adj; } if (readall) goto delta_adj; for(; dn0 < dn; dn0++) { if (dn0->extent != *dims++ || dn0->stride != 1) break; no1 *= dn0->extent; } if (dn0 == dimens && dimens[0].stride == 1) { no1 = dimens[0].extent; dn0++; } delta_adj: ex = 0; for(dn1 = dn0; dn1 <= dn; dn1++) ex += (dn1->extent-1) * (dn1->delta *= dn1->stride); for(dn1 = dn; dn1 > dn0; dn1--) { ex -= (dn1->extent - 1) * dn1->delta; dn1->delta -= ex; } } else if (dims = v->dims) { no = no1 = dims[1]; ivae = iva + no*size; } else scalar: no = no1 = 1; if (ch != '=') errfl(a->cierr, 115, where); got1 = nml_read = 1; f__lcount = 0; readloop: for(;;) { if (iva >= ivae || iva < 0) { f__lquit = 1; goto mustend; } else if (iva + no1*size > ivae) no1 = (ivae - iva)/size; f__lquit = 0; if (k = l_read(&no1, vaddr + iva, size, type)) return k; if (f__lquit == 1) return 0; if (readall) { iva += dn0->delta; if (f__lcount > 0) { no2 = (ivae - iva)/size; if (no2 > f__lcount) no2 = f__lcount; if (k = l_read(&no2, vaddr + iva, size, type)) return k; iva += no2 * dn0->delta; } } mustend: GETC(ch); if (readall) if (iva >= ivae) readall = 0; else for(;;) { switch(ch) { case ' ': case '\t': case '\n': GETC(ch); continue; } break; } if (ch == '/' || ch == '$' || ch == '&') { f__lquit = 1; return 0; } else if (f__lquit) { while(ch <= ' ' && ch >= 0) GETC(ch); Ungetc(ch,f__cf); if (!Alpha[ch & 0xff] && ch >= 0) errfl(a->cierr, 125, where); break; } Ungetc(ch,f__cf); if (readall && !Alpha[ch & 0xff]) goto readloop; if ((no -= no1) <= 0) break; for(dn1 = dn0; dn1 <= dn; dn1++) { if (++dn1->curval < dn1->extent) { iva += dn1->delta; goto readloop; } dn1->curval = 0; } break; } } } integer #ifdef KR_headers s_rsne(a) cilist *a; #else s_rsne(cilist *a) #endif { extern int l_eof; int n; f__external=1; l_eof = 0; if(n = c_le(a)) return n; if(f__curunit->uwrt && f__nowreading(f__curunit)) err(a->cierr,errno,where0); l_getc = t_getc; l_ungetc = un_getc; f__doend = xrd_SL; n = x_rsne(a); nml_read = 0; if (n) return n; return e_rsle(); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/lio.h0000644000076500000240000000303413524616145023013 0ustar tamasstaff00000000000000/* copy of ftypes from the compiler */ /* variable types * numeric assumptions: * int < reals < complexes * TYDREAL-TYREAL = TYDCOMPLEX-TYCOMPLEX */ /* 0-10 retain their old (pre LOGICAL*1, etc.) */ /* values to allow mixing old and new objects. */ #define TYUNKNOWN 0 #define TYADDR 1 #define TYSHORT 2 #define TYLONG 3 #define TYREAL 4 #define TYDREAL 5 #define TYCOMPLEX 6 #define TYDCOMPLEX 7 #define TYLOGICAL 8 #define TYCHAR 9 #define TYSUBR 10 #define TYINT1 11 #define TYLOGICAL1 12 #define TYLOGICAL2 13 #ifdef Allow_TYQUAD #undef TYQUAD #define TYQUAD 14 #endif #define LINTW 24 #define LINE 80 #define LLOGW 2 #ifdef Old_list_output #define LLOW 1.0 #define LHIGH 1.e9 #define LEFMT " %# .8E" #define LFFMT " %# .9g" #else #define LGFMT "%.9G" #endif /* LEFBL 20 should suffice; 24 overcomes a NeXT bug. */ #define LEFBL 24 typedef union { char flchar; short flshort; ftnint flint; #ifdef Allow_TYQUAD longint fllongint; #endif real flreal; doublereal fldouble; } flex; #ifdef KR_headers extern int (*f__lioproc)(), (*l_getc)(), (*l_ungetc)(); extern int l_read(), l_write(); #else #ifdef __cplusplus extern "C" { #endif extern int (*f__lioproc)(ftnint*, char*, ftnlen, ftnint); extern int l_write(ftnint*, char*, ftnlen, ftnint); extern void x_wsne(cilist*); extern int c_le(cilist*), (*l_getc)(void), (*l_ungetc)(int,FILE*); extern int l_read(ftnint*,char*,ftnlen,ftnint); extern integer e_rsle(void), e_wsle(void), s_wsne(cilist*); extern int z_rnew(void); #endif extern ftnint L_len; extern int f__scale; #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/xwsne.c0000644000076500000240000000222613524616145023371 0ustar tamasstaff00000000000000#include "f2c.h" #include "fio.h" #include "lio.h" #include "fmt.h" extern int f__Aquote; static VOID nl_donewrec(Void) { (*f__donewrec)(); PUT(' '); } #ifdef KR_headers x_wsne(a) cilist *a; #else #include "string.h" #ifdef __cplusplus extern "C" { #endif VOID x_wsne(cilist *a) #endif { Namelist *nl; char *s; Vardesc *v, **vd, **vde; ftnint number, type; ftnlen *dims; ftnlen size; extern ftnlen f__typesize[]; nl = (Namelist *)a->cifmt; PUT('&'); for(s = nl->name; *s; s++) PUT(*s); PUT(' '); f__Aquote = 1; vd = nl->vars; vde = vd + nl->nvars; while(vd < vde) { v = *vd++; s = v->name; #ifdef No_Extra_Namelist_Newlines if (f__recpos+strlen(s)+2 >= L_len) #endif nl_donewrec(); while(*s) PUT(*s++); PUT(' '); PUT('='); number = (dims = v->dims) ? dims[1] : 1; type = v->type; if (type < 0) { size = -type; type = TYCHAR; } else size = f__typesize[type]; l_write(&number, v->addr, size, type); if (vd < vde) { if (f__recpos+2 >= L_len) nl_donewrec(); PUT(','); PUT(' '); } else if (f__recpos+1 >= L_len) nl_donewrec(); } f__Aquote = 0; PUT('/'); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/l_le.c0000644000076500000240000000051613524616145023140 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers extern integer s_cmp(); logical l_le(a,b,la,lb) char *a, *b; ftnlen la, lb; #else extern integer s_cmp(char *, char *, ftnlen, ftnlen); logical l_le(char *a, char *b, ftnlen la, ftnlen lb) #endif { return(s_cmp(a,b,la,lb) <= 0); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/s_stop.c0000644000076500000240000000137213524616145023535 0ustar tamasstaff00000000000000#include "stdio.h" #include "f2c.h" #ifdef KR_headers extern void f_exit(); int s_stop(s, n) char *s; ftnlen n; #else #undef abs #undef min #undef max #include "stdlib.h" #ifdef __cplusplus extern "C" { #endif #ifdef __cplusplus extern "C" { #endif void f_exit(void); int s_stop(char *s, ftnlen n) #endif { int i; if(n > 0) { fprintf(stderr, "STOP "); for(i = 0; ii); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/lbitbits.c0000644000076500000240000000211113524616145024032 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifndef LONGBITS #define LONGBITS 32 #endif integer #ifdef KR_headers lbit_bits(a, b, len) integer a, b, len; #else lbit_bits(integer a, integer b, integer len) #endif { /* Assume 2's complement arithmetic */ unsigned long x, y; x = (unsigned long) a; y = (unsigned long)-1L; x >>= b; y <<= len; return (integer)(x & ~y); } integer #ifdef KR_headers lbit_cshift(a, b, len) integer a, b, len; #else lbit_cshift(integer a, integer b, integer len) #endif { unsigned long x, y, z; x = (unsigned long)a; if (len <= 0) { if (len == 0) return 0; goto full_len; } if (len >= LONGBITS) { full_len: if (b >= 0) { b %= LONGBITS; return (integer)(x << b | x >> LONGBITS -b ); } b = -b; b %= LONGBITS; return (integer)(x << LONGBITS - b | x >> b); } y = z = (unsigned long)-1; y <<= len; z &= ~y; y &= x; x &= z; if (b >= 0) { b %= len; return (integer)(y | z & (x << b | x >> len - b)); } b = -b; b %= len; return (integer)(y | z & (x >> b | x << len - b)); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/z_log.c0000644000076500000240000000525113524616145023340 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double log(), f__cabs(), atan2(); #define ANSI(x) () #else #define ANSI(x) x #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif extern double f__cabs(double, double); #endif #ifndef NO_DOUBLE_EXTENDED #ifndef GCC_COMPARE_BUG_FIXED #ifndef Pre20000310 #ifdef Comment Some versions of gcc, such as 2.95.3 and 3.0.4, are buggy under -O2 or -O3: on IA32 (Intel 80x87) systems, they may do comparisons on values computed in extended-precision registers. This can lead to the test "s > s0" that was used below being carried out incorrectly. The fix below cannot be spoiled by overzealous optimization, since the compiler cannot know whether gcc_bug_bypass_diff_F2C will be nonzero. (We expect it always to be zero. The weird name is unlikely to collide with anything.) An example (provided by Ulrich Jakobus) where the bug fix matters is double complex a, b a = (.1099557428756427618354862829619, .9857360542953131909982289471372) b = log(a) An alternative to the fix below would be to use 53-bit rounding precision, but the means of specifying this 80x87 feature are highly unportable. #endif /*Comment*/ #define BYPASS_GCC_COMPARE_BUG double (*gcc_bug_bypass_diff_F2C) ANSI((double*,double*)); static double #ifdef KR_headers diff1(a,b) double *a, *b; #else diff1(double *a, double *b) #endif { return *a - *b; } #endif /*Pre20000310*/ #endif /*GCC_COMPARE_BUG_FIXED*/ #endif /*NO_DOUBLE_EXTENDED*/ #ifdef KR_headers VOID z_log(r, z) doublecomplex *r, *z; #else void z_log(doublecomplex *r, doublecomplex *z) #endif { double s, s0, t, t2, u, v; double zi = z->i, zr = z->r; #ifdef BYPASS_GCC_COMPARE_BUG double (*diff) ANSI((double*,double*)); #endif r->i = atan2(zi, zr); #ifdef Pre20000310 r->r = log( f__cabs( zr, zi ) ); #else if (zi < 0) zi = -zi; if (zr < 0) zr = -zr; if (zr < zi) { t = zi; zi = zr; zr = t; } t = zi/zr; s = zr * sqrt(1 + t*t); /* now s = f__cabs(zi,zr), and zr = |zr| >= |zi| = zi */ if ((t = s - 1) < 0) t = -t; if (t > .01) r->r = log(s); else { #ifdef Comment log(1+x) = x - x^2/2 + x^3/3 - x^4/4 + - ... = x(1 - x/2 + x^2/3 -+...) [sqrt(y^2 + z^2) - 1] * [sqrt(y^2 + z^2) + 1] = y^2 + z^2 - 1, so sqrt(y^2 + z^2) - 1 = (y^2 + z^2 - 1) / [sqrt(y^2 + z^2) + 1] #endif /*Comment*/ #ifdef BYPASS_GCC_COMPARE_BUG if (!(diff = gcc_bug_bypass_diff_F2C)) diff = diff1; #endif t = ((zr*zr - 1.) + zi*zi) / (s + 1); t2 = t*t; s = 1. - 0.5*t; u = v = 1; do { s0 = s; u *= t2; v += 2; s += u/v - t*u/(v+1); } #ifdef BYPASS_GCC_COMPARE_BUG while(s - s0 > 1e-18 || (*diff)(&s,&s0) > 0.); #else while(s > s0); #endif r->r = s*t; } #endif } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/exit_.c0000644000076500000240000000103713524616145023334 0ustar tamasstaff00000000000000/* This gives the effect of subroutine exit(rc) integer*4 rc stop end * with the added side effect of supplying rc as the program's exit code. */ #include "f2c.h" #undef abs #undef min #undef max #ifndef KR_headers #include "stdlib.h" #ifdef __cplusplus extern "C" { #endif #ifdef __cplusplus extern "C" { #endif extern void f_exit(void); #endif void #ifdef KR_headers exit_(rc) integer *rc; #else exit_(integer *rc) #endif { #ifdef NO_ONEXIT f_exit(); #endif exit(*rc); } #ifdef __cplusplus } #endif #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/ilnw.c0000644000076500000240000000214513524616145023176 0ustar tamasstaff00000000000000#include "f2c.h" #include "fio.h" #include "lio.h" #ifdef __cplusplus extern "C" { #endif extern char *f__icptr; extern char *f__icend; extern icilist *f__svic; extern int f__icnum; #ifdef KR_headers extern void z_putc(); #else extern void z_putc(int); #endif static int z_wSL(Void) { while(f__recpos < f__svic->icirlen) z_putc(' '); return z_rnew(); } static void #ifdef KR_headers c_liw(a) icilist *a; #else c_liw(icilist *a) #endif { f__reading = 0; f__external = 0; f__formatted = 1; f__putn = z_putc; L_len = a->icirlen; f__donewrec = z_wSL; f__svic = a; f__icnum = f__recpos = 0; f__cursor = 0; f__cf = 0; f__curunit = 0; f__icptr = a->iciunit; f__icend = f__icptr + a->icirlen*a->icirnum; f__elist = (cilist *)a; } integer #ifdef KR_headers s_wsni(a) icilist *a; #else s_wsni(icilist *a) #endif { cilist ca; c_liw(a); ca.cifmt = a->icifmt; x_wsne(&ca); z_wSL(); return 0; } integer #ifdef KR_headers s_wsli(a) icilist *a; #else s_wsli(icilist *a) #endif { f__lioproc = l_write; c_liw(a); return(0); } integer e_wsli(Void) { z_wSL(); return(0); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/wsfe.c0000644000076500000240000000240013524616145023163 0ustar tamasstaff00000000000000/*write sequential formatted external*/ #include "f2c.h" #include "fio.h" #include "fmt.h" #ifdef __cplusplus extern "C" { #endif int x_wSL(Void) { int n = f__putbuf('\n'); f__hiwater = f__recpos = f__cursor = 0; return(n == 0); } static int xw_end(Void) { int n; if(f__nonl) { f__putbuf(n = 0); fflush(f__cf); } else n = f__putbuf('\n'); f__hiwater = f__recpos = f__cursor = 0; return n; } static int xw_rev(Void) { int n = 0; if(f__workdone) { n = f__putbuf('\n'); f__workdone = 0; } f__hiwater = f__recpos = f__cursor = 0; return n; } #ifdef KR_headers integer s_wsfe(a) cilist *a; /*start*/ #else integer s_wsfe(cilist *a) /*start*/ #endif { int n; if(!f__init) f_init(); f__reading=0; f__sequential=1; f__formatted=1; f__external=1; if(n=c_sfe(a)) return(n); f__elist=a; f__hiwater = f__cursor=f__recpos=0; f__nonl = 0; f__scale=0; f__fmtbuf=a->cifmt; f__cf=f__curunit->ufd; if(pars_f(f__fmtbuf)<0) err(a->cierr,100,"startio"); f__putn= x_putc; f__doed= w_ed; f__doned= w_ned; f__doend=xw_end; f__dorevert=xw_rev; f__donewrec=x_wSL; fmt_bg(); f__cplus=0; f__cblank=f__curunit->ublnk; if(f__curunit->uwrt != 1 && f__nowwriting(f__curunit)) err(a->cierr,errno,"write start"); return(0); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/r_tan.c0000644000076500000240000000034513524616145023330 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double tan(); double r_tan(x) real *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double r_tan(real *x) #endif { return( tan(*x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/hl_gt.c0000644000076500000240000000053113524616145023317 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers extern integer s_cmp(); shortlogical hl_gt(a,b,la,lb) char *a, *b; ftnlen la, lb; #else extern integer s_cmp(char *, char *, ftnlen, ftnlen); shortlogical hl_gt(char *a, char *b, ftnlen la, ftnlen lb) #endif { return(s_cmp(a,b,la,lb) > 0); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/sfe.c0000644000076500000240000000147413524616145023006 0ustar tamasstaff00000000000000/* sequential formatted external common routines*/ #include "f2c.h" #include "fio.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers extern char *f__fmtbuf; #else extern const char *f__fmtbuf; #endif integer e_rsfe(Void) { int n; n=en_fio(); f__fmtbuf=NULL; return(n); } int #ifdef KR_headers c_sfe(a) cilist *a; /* check */ #else c_sfe(cilist *a) /* check */ #endif { unit *p; f__curunit = p = &f__units[a->ciunit]; if(a->ciunit >= MXUNIT || a->ciunit<0) err(a->cierr,101,"startio"); if(p->ufd==NULL && fk_open(SEQ,FMT,a->ciunit)) err(a->cierr,114,"sfe") if(!p->ufmt) err(a->cierr,102,"sfe") return(0); } integer e_wsfe(Void) { int n = en_fio(); f__fmtbuf = NULL; #ifdef ALWAYS_FLUSH if (!n && fflush(f__cf)) err(f__elist->cierr, errno, "write end"); #endif return n; } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/dfe.c0000644000076500000240000000510013524616145022755 0ustar tamasstaff00000000000000#include "f2c.h" #include "fio.h" #include "fmt.h" #ifdef __cplusplus extern "C" { #endif int y_rsk(Void) { if(f__curunit->uend || f__curunit->url <= f__recpos || f__curunit->url == 1) return 0; do { getc(f__cf); } while(++f__recpos < f__curunit->url); return 0; } int y_getc(Void) { int ch; if(f__curunit->uend) return(-1); if((ch=getc(f__cf))!=EOF) { f__recpos++; if(f__curunit->url>=f__recpos || f__curunit->url==1) return(ch); else return(' '); } if(feof(f__cf)) { f__curunit->uend=1; errno=0; return(-1); } err(f__elist->cierr,errno,"readingd"); } static int y_rev(Void) { if (f__recpos < f__hiwater) f__recpos = f__hiwater; if (f__curunit->url > 1) while(f__recpos < f__curunit->url) (*f__putn)(' '); if (f__recpos) f__putbuf(0); f__recpos = 0; return(0); } static int y_err(Void) { err(f__elist->cierr, 110, "dfe"); } static int y_newrec(Void) { y_rev(); f__hiwater = f__cursor = 0; return(1); } int #ifdef KR_headers c_dfe(a) cilist *a; #else c_dfe(cilist *a) #endif { f__sequential=0; f__formatted=f__external=1; f__elist=a; f__cursor=f__scale=f__recpos=0; f__curunit = &f__units[a->ciunit]; if(a->ciunit>MXUNIT || a->ciunit<0) err(a->cierr,101,"startchk"); if(f__curunit->ufd==NULL && fk_open(DIR,FMT,a->ciunit)) err(a->cierr,104,"dfe"); f__cf=f__curunit->ufd; if(!f__curunit->ufmt) err(a->cierr,102,"dfe") if(!f__curunit->useek) err(a->cierr,104,"dfe") f__fmtbuf=a->cifmt; if(a->cirec <= 0) err(a->cierr,130,"dfe") FSEEK(f__cf,(OFF_T)f__curunit->url * (a->cirec-1),SEEK_SET); f__curunit->uend = 0; return(0); } #ifdef KR_headers integer s_rdfe(a) cilist *a; #else integer s_rdfe(cilist *a) #endif { int n; if(!f__init) f_init(); f__reading=1; if(n=c_dfe(a))return(n); if(f__curunit->uwrt && f__nowreading(f__curunit)) err(a->cierr,errno,"read start"); f__getn = y_getc; f__doed = rd_ed; f__doned = rd_ned; f__dorevert = f__donewrec = y_err; f__doend = y_rsk; if(pars_f(f__fmtbuf)<0) err(a->cierr,100,"read start"); fmt_bg(); return(0); } #ifdef KR_headers integer s_wdfe(a) cilist *a; #else integer s_wdfe(cilist *a) #endif { int n; if(!f__init) f_init(); f__reading=0; if(n=c_dfe(a)) return(n); if(f__curunit->uwrt != 1 && f__nowwriting(f__curunit)) err(a->cierr,errno,"startwrt"); f__putn = x_putc; f__doed = w_ed; f__doned= w_ned; f__dorevert = y_err; f__donewrec = y_newrec; f__doend = y_rev; if(pars_f(f__fmtbuf)<0) err(a->cierr,100,"startwrt"); fmt_bg(); return(0); } integer e_rdfe(Void) { en_fio(); return 0; } integer e_wdfe(Void) { return en_fio(); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/r_imag.c0000644000076500000240000000030513524616145023457 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers double r_imag(z) f2c_complex *z; #else double r_imag(f2c_complex *z) #endif { return(z->i); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/d_exp.c0000644000076500000240000000036113524616145023322 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double exp(); double d_exp(x) doublereal *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double d_exp(doublereal *x) #endif { return( exp(*x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/fmt.c0000644000076500000240000002056613524616145023022 0ustar tamasstaff00000000000000#include "f2c.h" #include "fio.h" #include "fmt.h" #ifdef __cplusplus extern "C" { #endif #define skip(s) while(*s==' ') s++ #ifdef interdata #define SYLMX 300 #endif #ifdef pdp11 #define SYLMX 300 #endif #ifdef vax #define SYLMX 300 #endif #ifndef SYLMX #define SYLMX 300 #endif #define GLITCH '\2' /* special quote character for stu */ extern flag f__cblank,f__cplus; /*blanks in I and compulsory plus*/ static struct syl f__syl[SYLMX]; int f__parenlvl,f__pc,f__revloc; #ifdef KR_headers #define Const /*nothing*/ #else #define Const const #endif static #ifdef KR_headers char *ap_end(s) char *s; #else const char *ap_end(const char *s) #endif { char quote; quote= *s++; for(;*s;s++) { if(*s!=quote) continue; if(*++s!=quote) return(s); } if(f__elist->cierr) { errno = 100; return(NULL); } f__fatal(100, "bad string"); /*NOTREACHED*/ return 0; } static int #ifdef KR_headers op_gen(a,b,c,d) #else op_gen(int a, int b, int c, int d) #endif { struct syl *p= &f__syl[f__pc]; if(f__pc>=SYLMX) { fprintf(stderr,"format too complicated:\n"); sig_die(f__fmtbuf, 1); } p->op=a; p->p1=b; p->p2.i[0]=c; p->p2.i[1]=d; return(f__pc++); } #ifdef KR_headers static char *f_list(); static char *gt_num(s,n,n1) char *s; int *n, n1; #else static const char *f_list(const char*); static const char *gt_num(const char *s, int *n, int n1) #endif { int m=0,f__cnt=0; char c; for(c= *s;;c = *s) { if(c==' ') { s++; continue; } if(c>'9' || c<'0') break; m=10*m+c-'0'; f__cnt++; s++; } if(f__cnt==0) { if (!n1) s = 0; *n=n1; } else *n=m; return(s); } static #ifdef KR_headers char *f_s(s,curloc) char *s; #else const char *f_s(const char *s, int curloc) #endif { skip(s); if(*s++!='(') { return(NULL); } if(f__parenlvl++ ==1) f__revloc=curloc; if(op_gen(RET1,curloc,0,0)<0 || (s=f_list(s))==NULL) { return(NULL); } skip(s); return(s); } static int #ifdef KR_headers ne_d(s,p) char *s,**p; #else ne_d(const char *s, const char **p) #endif { int n,x,sign=0; struct syl *sp; switch(*s) { default: return(0); case ':': (void) op_gen(COLON,0,0,0); break; case '$': (void) op_gen(NONL, 0, 0, 0); break; case 'B': case 'b': if(*++s=='z' || *s == 'Z') (void) op_gen(BZ,0,0,0); else (void) op_gen(BN,0,0,0); break; case 'S': case 's': if(*(s+1)=='s' || *(s+1) == 'S') { x=SS; s++; } else if(*(s+1)=='p' || *(s+1) == 'P') { x=SP; s++; } else x=S; (void) op_gen(x,0,0,0); break; case '/': (void) op_gen(SLASH,0,0,0); break; case '-': sign=1; case '+': s++; /*OUTRAGEOUS CODING TRICK*/ case '0': case '1': case '2': case '3': case '4': case '5': case '6': case '7': case '8': case '9': if (!(s=gt_num(s,&n,0))) { bad: *p = 0; return 1; } switch(*s) { default: return(0); case 'P': case 'p': if(sign) n= -n; (void) op_gen(P,n,0,0); break; case 'X': case 'x': (void) op_gen(X,n,0,0); break; case 'H': case 'h': sp = &f__syl[op_gen(H,n,0,0)]; sp->p2.s = (char*)s + 1; s+=n; break; } break; case GLITCH: case '"': case '\'': sp = &f__syl[op_gen(APOS,0,0,0)]; sp->p2.s = (char*)s; if((*p = ap_end(s)) == NULL) return(0); return(1); case 'T': case 't': if(*(s+1)=='l' || *(s+1) == 'L') { x=TL; s++; } else if(*(s+1)=='r'|| *(s+1) == 'R') { x=TR; s++; } else x=T; if (!(s=gt_num(s+1,&n,0))) goto bad; s--; (void) op_gen(x,n,0,0); break; case 'X': case 'x': (void) op_gen(X,1,0,0); break; case 'P': case 'p': (void) op_gen(P,1,0,0); break; } s++; *p=s; return(1); } static int #ifdef KR_headers e_d(s,p) char *s,**p; #else e_d(const char *s, const char **p) #endif { int i,im,n,w,d,e,found=0,x=0; Const char *sv=s; s=gt_num(s,&n,1); (void) op_gen(STACK,n,0,0); switch(*s++) { default: break; case 'E': case 'e': x=1; case 'G': case 'g': found=1; if (!(s=gt_num(s,&w,0))) { bad: *p = 0; return 1; } if(w==0) break; if(*s=='.') { if (!(s=gt_num(s+1,&d,0))) goto bad; } else d=0; if(*s!='E' && *s != 'e') (void) op_gen(x==1?E:G,w,d,0); /* default is Ew.dE2 */ else { if (!(s=gt_num(s+1,&e,0))) goto bad; (void) op_gen(x==1?EE:GE,w,d,e); } break; case 'O': case 'o': i = O; im = OM; goto finish_I; case 'Z': case 'z': i = Z; im = ZM; goto finish_I; case 'L': case 'l': found=1; if (!(s=gt_num(s,&w,0))) goto bad; if(w==0) break; (void) op_gen(L,w,0,0); break; case 'A': case 'a': found=1; skip(s); if(*s>='0' && *s<='9') { s=gt_num(s,&w,1); if(w==0) break; (void) op_gen(AW,w,0,0); break; } (void) op_gen(A,0,0,0); break; case 'F': case 'f': if (!(s=gt_num(s,&w,0))) goto bad; found=1; if(w==0) break; if(*s=='.') { if (!(s=gt_num(s+1,&d,0))) goto bad; } else d=0; (void) op_gen(F,w,d,0); break; case 'D': case 'd': found=1; if (!(s=gt_num(s,&w,0))) goto bad; if(w==0) break; if(*s=='.') { if (!(s=gt_num(s+1,&d,0))) goto bad; } else d=0; (void) op_gen(D,w,d,0); break; case 'I': case 'i': i = I; im = IM; finish_I: if (!(s=gt_num(s,&w,0))) goto bad; found=1; if(w==0) break; if(*s!='.') { (void) op_gen(i,w,0,0); break; } if (!(s=gt_num(s+1,&d,0))) goto bad; (void) op_gen(im,w,d,0); break; } if(found==0) { f__pc--; /*unSTACK*/ *p=sv; return(0); } *p=s; return(1); } static #ifdef KR_headers char *i_tem(s) char *s; #else const char *i_tem(const char *s) #endif { const char *t; int n,curloc; if(*s==')') return(s); if(ne_d(s,&t)) return(t); if(e_d(s,&t)) return(t); s=gt_num(s,&n,1); if((curloc=op_gen(STACK,n,0,0))<0) return(NULL); return(f_s(s,curloc)); } static #ifdef KR_headers char *f_list(s) char *s; #else const char *f_list(const char *s) #endif { for(;*s!=0;) { skip(s); if((s=i_tem(s))==NULL) return(NULL); skip(s); if(*s==',') s++; else if(*s==')') { if(--f__parenlvl==0) { (void) op_gen(REVERT,f__revloc,0,0); return(++s); } (void) op_gen(GOTO,0,0,0); return(++s); } } return(NULL); } int #ifdef KR_headers pars_f(s) char *s; #else pars_f(const char *s) #endif { f__parenlvl=f__revloc=f__pc=0; if(f_s(s,0) == NULL) { return(-1); } return(0); } #define STKSZ 10 int f__cnt[STKSZ],f__ret[STKSZ],f__cp,f__rp; flag f__workdone, f__nonl; static int #ifdef KR_headers type_f(n) #else type_f(int n) #endif { switch(n) { default: return(n); case RET1: return(RET1); case REVERT: return(REVERT); case GOTO: return(GOTO); case STACK: return(STACK); case X: case SLASH: case APOS: case H: case T: case TL: case TR: return(NED); case F: case I: case IM: case A: case AW: case O: case OM: case L: case E: case EE: case D: case G: case GE: case Z: case ZM: return(ED); } } #ifdef KR_headers integer do_fio(number,ptr,len) ftnint *number; ftnlen len; char *ptr; #else integer do_fio(ftnint *number, char *ptr, ftnlen len) #endif { struct syl *p; int n,i; for(i=0;i<*number;i++,ptr+=len) { loop: switch(type_f((p= &f__syl[f__pc])->op)) { default: fprintf(stderr,"unknown code in do_fio: %d\n%s\n", p->op,f__fmtbuf); err(f__elist->cierr,100,"do_fio"); case NED: if((*f__doned)(p)) { f__pc++; goto loop; } f__pc++; continue; case ED: if(f__cnt[f__cp]<=0) { f__cp--; f__pc++; goto loop; } if(ptr==NULL) return((*f__doend)()); f__cnt[f__cp]--; f__workdone=1; if((n=(*f__doed)(p,ptr,len))>0) errfl(f__elist->cierr,errno,"fmt"); if(n<0) err(f__elist->ciend,(EOF),"fmt"); continue; case STACK: f__cnt[++f__cp]=p->p1; f__pc++; goto loop; case RET1: f__ret[++f__rp]=p->p1; f__pc++; goto loop; case GOTO: if(--f__cnt[f__cp]<=0) { f__cp--; f__rp--; f__pc++; goto loop; } f__pc=1+f__ret[f__rp--]; goto loop; case REVERT: f__rp=f__cp=0; f__pc = p->p1; if(ptr==NULL) return((*f__doend)()); if(!f__workdone) return(0); if((n=(*f__dorevert)()) != 0) return(n); goto loop; case COLON: if(ptr==NULL) return((*f__doend)()); f__pc++; goto loop; case NONL: f__nonl = 1; f__pc++; goto loop; case S: case SS: f__cplus=0; f__pc++; goto loop; case SP: f__cplus = 1; f__pc++; goto loop; case P: f__scale=p->p1; f__pc++; goto loop; case BN: f__cblank=0; f__pc++; goto loop; case BZ: f__cblank=1; f__pc++; goto loop; } } return(0); } int en_fio(Void) { ftnint one=1; return(do_fio(&one,(char *)NULL,(ftnint)0)); } VOID fmt_bg(Void) { f__workdone=f__cp=f__rp=f__pc=f__cursor=0; f__cnt[0]=f__ret[0]=0; } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/i_abs.c0000644000076500000240000000032613524616145023301 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers integer i_abs(x) integer *x; #else integer i_abs(integer *x) #endif { if(*x >= 0) return(*x); return(- *x); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/d_cos.c0000644000076500000240000000036113524616145023312 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double cos(); double d_cos(x) doublereal *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double d_cos(doublereal *x) #endif { return( cos(*x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/r_abs.c0000644000076500000240000000031613524616145023311 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers double r_abs(x) real *x; #else double r_abs(real *x) #endif { if(*x >= 0) return(*x); return(- *x); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/arithchk.c0000644000076500000240000001263613524616145024030 0ustar tamasstaff00000000000000/**************************************************************** Copyright (C) 1997, 1998, 2000 Lucent Technologies All Rights Reserved Permission to use, copy, modify, and distribute this software and its documentation for any purpose and without fee is hereby granted, provided that the above copyright notice appear in all copies and that both that the copyright notice and this permission notice and warranty disclaimer appear in supporting documentation, and that the name of Lucent or any of its entities not be used in advertising or publicity pertaining to distribution of the software without specific, written prior permission. LUCENT DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS SOFTWARE, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL LUCENT OR ANY OF ITS ENTITIES BE LIABLE FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE. ****************************************************************/ /* Try to deduce arith.h from arithmetic properties. */ #include #include #include #ifdef NO_FPINIT #define fpinit_ASL() #else #ifndef KR_headers extern #ifdef __cplusplus "C" #endif void fpinit_ASL(void); #endif /*KR_headers*/ #endif /*NO_FPINIT*/ static int dalign; typedef struct Akind { char *name; int kind; } Akind; static Akind IEEE_8087 = { "IEEE_8087", 1 }, IEEE_MC68k = { "IEEE_MC68k", 2 }, IBM = { "IBM", 3 }, VAX = { "VAX", 4 }, CRAY = { "CRAY", 5}; static double t_nan; static Akind * Lcheck(void) { union { double d; long L[2]; } u; struct { double d; long L; } x[2]; if (sizeof(x) > 2*(sizeof(double) + sizeof(long))) dalign = 1; u.L[0] = u.L[1] = 0; u.d = 1e13; if (u.L[0] == 1117925532 && u.L[1] == -448790528) return &IEEE_MC68k; if (u.L[1] == 1117925532 && u.L[0] == -448790528) return &IEEE_8087; if (u.L[0] == -2065213935 && u.L[1] == 10752) return &VAX; if (u.L[0] == 1267827943 && u.L[1] == 704643072) return &IBM; return 0; } static Akind * icheck(void) { union { double d; int L[2]; } u; struct { double d; int L; } x[2]; if (sizeof(x) > 2*(sizeof(double) + sizeof(int))) dalign = 1; u.L[0] = u.L[1] = 0; u.d = 1e13; if (u.L[0] == 1117925532 && u.L[1] == -448790528) return &IEEE_MC68k; if (u.L[1] == 1117925532 && u.L[0] == -448790528) return &IEEE_8087; if (u.L[0] == -2065213935 && u.L[1] == 10752) return &VAX; if (u.L[0] == 1267827943 && u.L[1] == 704643072) return &IBM; return 0; } /* avoid possible warning message with printf("") */ const char *const emptyfmt = ""; #ifdef __GNUC__ # pragma GCC diagnostic push # ifndef __clang__ # pragma GCC diagnostic ignored "-Wformat-security" # pragma GCC diagnostic ignored "-Wunused-but-set-variable" # else # pragma GCC diagnostic ignored "-Wformat-zero-length" # endif #endif static Akind * ccheck(void) { union { double d; long L; } u; long Cray1; /* Cray1 = 4617762693716115456 -- without overflow on non-Crays */ Cray1 = printf(emptyfmt) < 0 ? 0 : 4617762; if (printf(emptyfmt, Cray1) >= 0) Cray1 = 1000000*Cray1 + 693716; if (printf(emptyfmt, Cray1) >= 0) Cray1 = 1000000*Cray1 + 115456; u.d = 1e13; if (u.L == Cray1) return &CRAY; return 0; } static int fzcheck(void) { double a, b; int i; a = 1.; b = .1; for(i = 155;; b *= b, i >>= 1) { if (i & 1) { a *= b; if (i == 1) break; } } b = a * a; return b == 0.; } static int need_nancheck(void) { double t; errno = 0; t = log(t_nan); if (errno == 0) return 1; errno = 0; t = sqrt(t_nan); return errno == 0; } #ifdef __GNUC__ # ifndef __clang__ # pragma GCC diagnostic pop # endif #endif void get_nanbits(unsigned int *b, int k) { union { double d; unsigned int z[2]; } u, u1, u2; k = 2 - k; u1.z[k] = u2.z[k] = 0x7ff00000; u1.z[1-k] = u2.z[1-k] = 0; u.d = u1.d - u2.d; /* Infinity - Infinity */ b[0] = u.z[0]; b[1] = u.z[1]; } int main(void) { FILE *f; Akind *a = 0; int Ldef = 0; unsigned int nanbits[2]; fpinit_ASL(); #ifdef WRITE_ARITH_H /* for Symantec's buggy "make" */ f = fopen("arith.h", "w"); if (!f) { printf("Cannot open arith.h\n"); return 1; } #else f = stdout; #endif if (sizeof(double) == 2*sizeof(long)) a = Lcheck(); else if (sizeof(double) == 2*sizeof(int)) { Ldef = 1; a = icheck(); } else if (sizeof(double) == sizeof(long)) a = ccheck(); if (a) { fprintf(f, "#define %s\n#define Arith_Kind_ASL %d\n", a->name, a->kind); if (Ldef) fprintf(f, "#define Long int\n#define Intcast (int)(long)\n"); if (dalign) fprintf(f, "#define Double_Align\n"); if (sizeof(char*) == 8) fprintf(f, "#define X64_bit_pointers\n"); #ifndef NO_LONG_LONG if (sizeof(long long) < 8) #endif fprintf(f, "#define NO_LONG_LONG\n"); if (a->kind <= 2) { if (fzcheck()) fprintf(f, "#define Sudden_Underflow\n"); t_nan = -a->kind; if (need_nancheck()) fprintf(f, "#define NANCHECK\n"); if (sizeof(double) == 2*sizeof(unsigned int)) { get_nanbits(nanbits, a->kind); fprintf(f, "#define QNaN0 0x%x\n", nanbits[0]); fprintf(f, "#define QNaN1 0x%x\n", nanbits[1]); } } return 0; } fprintf(f, "/* Unknown arithmetic */\n"); return 1; } #ifdef __sun #ifdef __i386 /* kludge for Intel Solaris */ void fpsetprec(int x) { } #endif #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/d_sin.c0000644000076500000240000000036113524616145023317 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double sin(); double d_sin(x) doublereal *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double d_sin(doublereal *x) #endif { return( sin(*x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/s_rnge.c0000644000076500000240000000136713524616145023507 0ustar tamasstaff00000000000000#include "stdio.h" #include "f2c.h" #ifdef __cplusplus extern "C" { #endif /* called when a subscript is out of range */ #ifdef KR_headers extern VOID sig_die(); integer s_rnge(varn, offset, procn, line) char *varn, *procn; ftnint offset, line; #else extern VOID sig_die(const char*,int); integer s_rnge(char *varn, ftnint offset, char *procn, ftnint line) #endif { register int i; fprintf(stderr, "Subscript out of range on file line %ld, procedure ", (long)line); while((i = *procn) && i != '_' && i != ' ') putc(*procn++, stderr); fprintf(stderr, ".\nAttempt to access the %ld-th element of variable ", (long)offset+1); while((i = *varn) && i != ' ') putc(*varn++, stderr); sig_die(".", 1); return 0; /* not reached */ } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/open.c0000644000076500000240000001310513524616145023164 0ustar tamasstaff00000000000000#include "f2c.h" #include "fio.h" #include "string.h" #ifndef NON_POSIX_STDIO #ifdef MSDOS #include "io.h" #else #include "unistd.h" /* for access */ #endif #endif #ifdef KR_headers extern char *malloc(); #ifdef NON_ANSI_STDIO extern char *mktemp(); #endif extern integer f_clos(); #define Const /*nothing*/ #else #define Const const #undef abs #undef min #undef max #include "stdlib.h" #ifdef __cplusplus extern "C" { #endif extern int f__canseek(FILE*); extern integer f_clos(cllist*); #endif #ifdef NON_ANSI_RW_MODES Const char *f__r_mode[2] = {"r", "r"}; Const char *f__w_mode[4] = {"w", "w", "r+w", "r+w"}; #else Const char *f__r_mode[2] = {"rb", "r"}; Const char *f__w_mode[4] = {"wb", "w", "r+b", "r+"}; #endif static char f__buf0[400], *f__buf = f__buf0; int f__buflen = (int)sizeof(f__buf0); static void #ifdef KR_headers f__bufadj(n, c) int n, c; #else f__bufadj(int n, int c) #endif { unsigned int len; char *nbuf, *s, *t, *te; if (f__buf == f__buf0) f__buflen = 1024; while(f__buflen <= n) f__buflen <<= 1; len = (unsigned int)f__buflen; if (len != f__buflen || !(nbuf = (char*)malloc(len))) f__fatal(113, "malloc failure"); s = nbuf; t = f__buf; te = t + c; while(t < te) *s++ = *t++; if (f__buf != f__buf0) free(f__buf); f__buf = nbuf; } int #ifdef KR_headers f__putbuf(c) int c; #else f__putbuf(int c) #endif { char *s, *se; int n; if (f__hiwater > f__recpos) f__recpos = f__hiwater; n = f__recpos + 1; if (n >= f__buflen) f__bufadj(n, f__recpos); s = f__buf; se = s + f__recpos; if (c) *se++ = c; *se = 0; for(;;) { fputs(s, f__cf); s += strlen(s); if (s >= se) break; /* normally happens the first time */ putc(*s++, f__cf); } return 0; } void #ifdef KR_headers x_putc(c) #else x_putc(int c) #endif { if (f__recpos >= f__buflen) f__bufadj(f__recpos, f__buflen); f__buf[f__recpos++] = c; } #define opnerr(f,m,s) {if(f) errno= m; else opn_err(m,s,a); return(m);} static void #ifdef KR_headers opn_err(m, s, a) int m; char *s; olist *a; #else opn_err(int m, const char *s, olist *a) #endif { if (a->ofnm) { /* supply file name to error message */ if (a->ofnmlen >= f__buflen) f__bufadj((int)a->ofnmlen, 0); g_char(a->ofnm, a->ofnmlen, f__curunit->ufnm = f__buf); } f__fatal(m, s); } #ifdef KR_headers integer f_open(a) olist *a; #else integer f_open(olist *a) #endif { unit *b; integer rv; char buf[256], *s; cllist x; int ufmt; FILE *tf; #ifndef NON_UNIX_STDIO int n; #endif f__external = 1; if(a->ounit>=MXUNIT || a->ounit<0) err(a->oerr,101,"open") if (!f__init) f_init(); f__curunit = b = &f__units[a->ounit]; if(b->ufd) { if(a->ofnm==0) { same: if (a->oblnk) b->ublnk = *a->oblnk == 'z' || *a->oblnk == 'Z'; return(0); } #ifdef NON_UNIX_STDIO if (b->ufnm && strlen(b->ufnm) == a->ofnmlen && !strncmp(b->ufnm, a->ofnm, (unsigned)a->ofnmlen)) goto same; #else g_char(a->ofnm,a->ofnmlen,buf); if (f__inode(buf,&n) == b->uinode && n == b->udev) goto same; #endif x.cunit=a->ounit; x.csta=0; x.cerr=a->oerr; if ((rv = f_clos(&x)) != 0) return rv; } b->url = (int)a->orl; b->ublnk = a->oblnk && (*a->oblnk == 'z' || *a->oblnk == 'Z'); if(a->ofm==0) { if(b->url>0) b->ufmt=0; else b->ufmt=1; } else if(*a->ofm=='f' || *a->ofm == 'F') b->ufmt=1; else b->ufmt=0; ufmt = b->ufmt; #ifdef url_Adjust if (b->url && !ufmt) url_Adjust(b->url); #endif if (a->ofnm) { g_char(a->ofnm,a->ofnmlen,buf); if (!buf[0]) opnerr(a->oerr,107,"open") } else sprintf(buf, "fort.%ld", (long)a->ounit); b->uscrtch = 0; b->uend=0; b->uwrt = 0; b->ufd = 0; b->urw = 3; switch(a->osta ? *a->osta : 'u') { case 'o': case 'O': #ifdef NON_POSIX_STDIO if (!(tf = FOPEN(buf,"r"))) opnerr(a->oerr,errno,"open") fclose(tf); #else if (access(buf,0)) opnerr(a->oerr,errno,"open") #endif break; case 's': case 'S': b->uscrtch=1; #ifdef NON_ANSI_STDIO (void) strcpy(buf,"tmp.FXXXXXX"); (void) mktemp(buf); goto replace; #else if (!(b->ufd = tmpfile())) opnerr(a->oerr,errno,"open") b->ufnm = 0; #ifndef NON_UNIX_STDIO b->uinode = b->udev = -1; #endif b->useek = 1; return 0; #endif case 'n': case 'N': #ifdef NON_POSIX_STDIO if ((tf = FOPEN(buf,"r")) || (tf = FOPEN(buf,"a"))) { fclose(tf); opnerr(a->oerr,128,"open") } #else if (!access(buf,0)) opnerr(a->oerr,128,"open") #endif /* no break */ case 'r': /* Fortran 90 replace option */ case 'R': #ifdef NON_ANSI_STDIO replace: #endif if (tf = FOPEN(buf,f__w_mode[0])) fclose(tf); } b->ufnm=(char *) malloc((unsigned int)(strlen(buf)+1)); if(b->ufnm==NULL) opnerr(a->oerr,113,"no space"); (void) strcpy(b->ufnm,buf); if ((s = a->oacc) && b->url) ufmt = 0; if(!(tf = FOPEN(buf, f__w_mode[ufmt|2]))) { if (tf = FOPEN(buf, f__r_mode[ufmt])) b->urw = 1; else if (tf = FOPEN(buf, f__w_mode[ufmt])) { b->uwrt = 1; b->urw = 2; } else err(a->oerr, errno, "open"); } b->useek = f__canseek(b->ufd = tf); #ifndef NON_UNIX_STDIO if((b->uinode = f__inode(buf,&b->udev)) == -1) opnerr(a->oerr,108,"open") #endif if(b->useek) if (a->orl) rewind(b->ufd); else if ((s = a->oacc) && (*s == 'a' || *s == 'A') && FSEEK(b->ufd, 0L, SEEK_END)) opnerr(a->oerr,129,"open"); return(0); } int #ifdef KR_headers fk_open(seq,fmt,n) ftnint n; #else fk_open(int seq, int fmt, ftnint n) #endif { char nbuf[10]; olist a; (void) sprintf(nbuf,"fort.%ld",(long)n); a.oerr=1; a.ounit=n; a.ofnm=nbuf; a.ofnmlen=strlen(nbuf); a.osta=NULL; a.oacc= (char*)(seq==SEQ?"s":"d"); a.ofm = (char*)(fmt==FMT?"f":"u"); a.orl = seq==DIR?1:0; a.oblnk=NULL; return(f_open(&a)); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/i_dnnt.c0000644000076500000240000000044313524616145023477 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double floor(); integer i_dnnt(x) doublereal *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif integer i_dnnt(doublereal *x) #endif { return (integer)(*x >= 0. ? floor(*x + .5) : -floor(.5 - *x)); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/ef1cmc_.c0000644000076500000240000000065313524616145023524 0ustar tamasstaff00000000000000/* EFL support routine to compare two character strings */ #include "f2c.h" #ifdef __cplusplus extern "C" { #endif #ifdef KR_headers extern integer s_cmp(); integer ef1cmc_(a, la, b, lb) ftnint *a, *b; ftnlen *la, *lb; #else extern integer s_cmp(char*,char*,ftnlen,ftnlen); integer ef1cmc_(ftnint *a, ftnlen *la, ftnint *b, ftnlen *lb) #endif { return( s_cmp( (char *)a, (char *)b, *la, *lb) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/d_atan.c0000644000076500000240000000036513524616145023455 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double atan(); double d_atan(x) doublereal *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double d_atan(doublereal *x) #endif { return( atan(*x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/close.c0000644000076500000240000000256113524616145023334 0ustar tamasstaff00000000000000#include "f2c.h" #include "fio.h" #ifdef KR_headers integer f_clos(a) cllist *a; #else #undef abs #undef min #undef max #include "stdlib.h" #ifdef NON_UNIX_STDIO #ifndef unlink #define unlink remove #endif #else #ifdef MSDOS #include "io.h" #else #ifdef __cplusplus extern "C" int unlink(const char*); #else extern int unlink(const char*); #endif #endif #endif #ifdef __cplusplus extern "C" { #endif integer f_clos(cllist *a) #endif { unit *b; if(a->cunit >= MXUNIT) return(0); b= &f__units[a->cunit]; if(b->ufd==NULL) goto done; if (b->uscrtch == 1) goto Delete; if (!a->csta) goto Keep; switch(*a->csta) { default: Keep: case 'k': case 'K': if(b->uwrt == 1) t_runc((alist *)a); if(b->ufnm) { fclose(b->ufd); free(b->ufnm); } break; case 'd': case 'D': Delete: fclose(b->ufd); if(b->ufnm) { unlink(b->ufnm); /*SYSDEP*/ free(b->ufnm); } } b->ufd=NULL; done: b->uend=0; b->ufnm=NULL; return(0); } void #ifdef KR_headers f_exit() #else f_exit(void) #endif { int i; static cllist xx; if (!xx.cerr) { xx.cerr=1; xx.csta=NULL; for(i=0;i 0) { if (z < 0) z += ya; } else if (z > 0) z -= ya; return z; #else double quotient; if( (quotient = *x / *y) >= 0) quotient = floor(quotient); else quotient = -floor(-quotient); return(*x - (*y) * quotient ); #endif } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/r_int.c0000644000076500000240000000040113524616145023331 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef KR_headers double floor(); double r_int(x) real *x; #else #undef abs #include "math.h" #ifdef __cplusplus extern "C" { #endif double r_int(real *x) #endif { return( (*x>0) ? floor(*x) : -floor(- *x) ); } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/ef1asc_.c0000644000076500000240000000101113524616145023515 0ustar tamasstaff00000000000000/* EFL support routine to copy string b to string a */ #include "f2c.h" #ifdef __cplusplus extern "C" { #endif #define M ( (long) (sizeof(long) - 1) ) #define EVEN(x) ( ( (x)+ M) & (~M) ) #ifdef KR_headers extern VOID s_copy(); ef1asc_(a, la, b, lb) ftnint *a, *b; ftnlen *la, *lb; #else extern void s_copy(char*,char*,ftnlen,ftnlen); int ef1asc_(ftnint *a, ftnlen *la, ftnint *b, ftnlen *lb) #endif { s_copy( (char *)a, (char *)b, EVEN(*la), *lb ); return 0; /* ignored return value */ } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/f2c/d_cnjg.c0000644000076500000240000000037713524616145023456 0ustar tamasstaff00000000000000#include "f2c.h" #ifdef __cplusplus extern "C" { #endif VOID #ifdef KR_headers d_cnjg(r, z) doublecomplex *r, *z; #else d_cnjg(doublecomplex *r, doublecomplex *z) #endif { doublereal zi = z->i; r->r = z->r; r->i = -zi; } #ifdef __cplusplus } #endif python-igraph-0.8.0/vendor/source/igraph/src/gengraph_degree_sequence.cpp0000644000076500000240000002674213614300625027113 0ustar tamasstaff00000000000000/* * * gengraph - generation of random simple connected graphs with prescribed * degree sequence * * Copyright (C) 2006 Fabien Viger * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #include "gengraph_definitions.h" #include "gengraph_random.h" #include "gengraph_powerlaw.h" #include "gengraph_degree_sequence.h" #include "gengraph_hash.h" #include "igraph_statusbar.h" #include #include #include #include #include // using namespace __gnu_cxx; using namespace std; namespace gengraph { // shuffle an int[] randomly void random_permute(int *a, int n); // sort an array of positive integers in time & place O(n + max) void cumul_sort(int *q, int n); void degree_sequence::detach() { deg = NULL; } degree_sequence::~degree_sequence() { if (deg != NULL) { delete[] deg; } deg = NULL; } void degree_sequence::make_even(int mini, int maxi) { if (total % 2 == 0) { return; } if (maxi < 0) { maxi = 0x7FFFFFFF; } int i; for (i = 0; i < n; i++) { if (deg[i] > mini) { deg[i]--; total--; break; } else if (deg[i] < maxi) { deg[i]++; total++; break; } } if (i == n) { IGRAPH_WARNING("Warning: degree_sequence::make_even() forced one " "degree to go over degmax"); deg[0]++; total++; } } void degree_sequence::shuffle() { random_permute(deg, n); } void degree_sequence::sort() { cumul_sort(deg, n); } void degree_sequence::compute_total() { total = 0; for (int i = 0; i < n; i++) { total += deg[i]; } } degree_sequence:: degree_sequence(int n0, int *degs) { deg = degs; n = n0; compute_total(); } degree_sequence:: degree_sequence(const igraph_vector_t *out_seq) { n = igraph_vector_size(out_seq); deg = new int[n]; for (long int i = 0; i < n; i++) { deg[i] = VECTOR(*out_seq)[i]; } compute_total(); } #ifndef FBUFF_SIZE #define FBUFF_SIZE 999 #endif //FBUFF_SIZE // degree_sequence::degree_sequence(FILE *f, bool DISTRIB) { // n = 0; // total = 0; // char *buff = new char[FBUFF_SIZE]; // char *c; // vector degree; // if(!DISTRIB) { // // Input is a 'raw' degree sequence d0 d1 d2 d3 ... // while(fgets(buff, FBUFF_SIZE, f)) { // int d = strtol(buff, &c, 10); // if(c == buff) continue; // degree.push_back(d); // total += d; // } // n = int(degree.size()); // deg = new int[n]; // int *yo = deg; // vector::iterator end = degree.end(); // for(vector::iterator it=degree.begin(); it!=end; *(yo++) = *(it++)); // } // else { // // Input is a degree distribution : d0 #(degree=d0), d1 #(degree=d1), ... // vector n_with_degree; // int line = 0; // int syntax = 0; // int ignored = 0; // int first_syntax = 0; // int first_ignored = 0; // while(fgets(buff, FBUFF_SIZE, f)) { // line++; // int d = strtol(buff, &c, 10); // if(c == buff) { ignored++; first_ignored = line; continue; } // char *cc; // int i = strtol(c, &cc, 10); // if(cc == c) { syntax++; first_syntax = line; continue; } // n += i; // total += i*d; // degree.push_back(d); // n_with_degree.push_back(i); // if( cc != c) { syntax++; first_syntax = line; } // } // if(VERBOSE()) { // if(ignored > 0) fprintf(stderr,"Ignored %d lines (first was line #%d)\n", ignored, first_ignored); // if(syntax > 0) fprintf(stderr,"Found %d probable syntax errors (first was line #%d)\n", syntax, first_syntax); // } // deg = new int[n]; // int *yo = deg; // vector::iterator it_n = n_with_degree.begin(); // for(vector::iterator it = degree.begin(); it != degree.end(); it++) // for(int k = *(it_n++); k--; *yo++ = *it); // } // if(VERBOSE()) { // if(total % 2 != 0) fprintf(stderr,"Warning: degree sequence is odd\n"); // fprintf(stderr,"Degree sequence created. N=%d, 2M=%d\n", n, total); // } // } // n vertices, exponent, min degree, max degree, average degree (optional, default is -1) degree_sequence:: degree_sequence(int _n, double exp, int degmin, int degmax, double z) { n = _n; if (exp == 0.0) { // Binomial distribution if (z < 0) { igraph_error("Fatal error in degree_sequence Ctor: " "positive average degree must be specified", __FILE__, __LINE__, IGRAPH_EINVAL); } if (degmax < 0) { degmax = n - 1; } total = int(floor(double(n) * z + 0.5)); deg = new int[n]; KW_RNG::RNG myrand; double p = (z - double(degmin)) / double(n); total = 0; for (int i = 0; i < n; i++) { do { deg[i] = 1 + myrand.binomial(p, n); } while (deg[i] > degmax); total += deg[i]; } } else { // Power-law distribution igraph_status("Creating powerlaw sampler...", 0); powerlaw pw(exp, degmin, degmax); if (z == -1.0) { pw.init(); igraph_statusf("done. Mean=%f\n", 0, pw.mean()); } else { double offset = pw.init_to_mean(z); igraph_statusf("done. Offset=%f, Mean=%f\n", 0, offset, pw.mean()); } deg = new int[n]; total = 0; int i; igraph_statusf("Sampling %d random numbers...", 0, n); for (i = 0; i < n; i++) { deg[i] = pw.sample(); total += deg[i]; } igraph_status("done\nSimple statistics on degrees...", 0); int wanted_total = int(floor(z * n + 0.5)); sort(); igraph_statusf("done : Max=%d, Total=%d.\n", 0, deg[0], total); if (z != -1.0) { igraph_statusf("Adjusting total to %d...", 0, wanted_total); int iterations = 0; while (total != wanted_total) { sort(); for (i = 0; i < n && total > wanted_total; i++) { total -= deg[i]; if (total + degmin <= wanted_total) { deg[i] = wanted_total - total; } else { deg[i] = pw.sample(); } total += deg[i]; } iterations += i; for (i = n - 1; i > 0 && total < wanted_total; i--) { total -= deg[i]; if (total + (deg[0] >> 1) >= wanted_total) { deg[i] = wanted_total - total; } else { deg[i] = pw.sample(); } total += deg[i]; } iterations += n - 1 - i; } igraph_statusf("done(%d iterations).", 0, iterations); igraph_statusf(" Now, degmax = %d\n", 0, dmax()); } shuffle(); } } // void degree_sequence::print() { // for(int i=0; ideg[i]) dmin=deg[i]; // int *dd = new int[dmax-dmin+1]; // for(i=dmin; i<=dmax; i++) dd[i-dmin]=0; // if(VERBOSE()) fprintf(stderr,"Computing cumulative distribution..."); // for(i=0; i0) printf("%d %d\n",i,dd[i-dmin]); // delete[] dd; // } bool degree_sequence::havelhakimi() { int i; int dm = dmax() + 1; // Sort vertices using basket-sort, in descending degrees int *nb = new int[dm]; int *sorted = new int[n]; // init basket for (i = 0; i < dm; i++) { nb[i] = 0; } // count basket for (i = 0; i < n; i++) { nb[deg[i]]++; } // cumul int c = 0; for (i = dm - 1; i >= 0; i--) { int t = nb[i]; nb[i] = c; c += t; } // sort for (i = 0; i < n; i++) { sorted[nb[deg[i]]++] = i; } // Binding process starts int first = 0; // vertex with biggest residual degree int d = dm - 1; // maximum residual degree available for (c = total / 2; c > 0; ) { // We design by 'v' the vertex of highest degree (indexed by first) // look for current degree of v while (nb[d] <= first) { d--; } // store it in dv int dv = d; // bind it ! c -= dv; int dc = d; // residual degree of vertices we bind to int fc = ++first; // position of the first vertex with degree dc while (dv > 0 && dc > 0) { int lc = nb[dc]; if (lc != fc) { while (dv > 0 && lc > fc) { // binds v with sorted[--lc] dv--; lc--; } fc = nb[dc]; nb[dc] = lc; } dc--; } if (dv != 0) { // We couldn't bind entirely v delete[] nb; delete[] sorted; return false; } } delete[] nb; delete[] sorted; return true; } //************************* // Subroutines definitions //************************* inline int int_adjust(double x) { return (int(floor(x + random_float()))); } void random_permute(int *a, int n) { int j, tmp; for (int i = 0; i < n - 1; i++) { j = i + my_random() % (n - i); tmp = a[i]; a[i] = a[j]; a[j] = tmp; } } void cumul_sort(int *q, int n) { // looks for the maximum q[i] and minimum if (n == 0) { return; } int qmax = q[0]; int qmin = q[0]; int i; for (i = 0; i < n; i++) if (q[i] > qmax) { qmax = q[i]; } for (i = 0; i < n; i++) if (q[i] < qmin) { qmin = q[i]; } // counts #q[i] with given q int *nb = new int[qmax - qmin + 1]; for (int *onk = nb + (qmax - qmin + 1); onk != nb; * (--onk) = 0) { } for (i = 0; i < n; i++) { nb[q[i] - qmin]++; } // counts cumulative distribution for (i = qmax - qmin; i > 0; i--) { nb[i - 1] += nb[i]; } // sort by q[i] int last_q; int tmp; int modifier = qmax - qmin + 1; for (int current = 0; current < n; current++) { tmp = q[current]; if (tmp >= qmin && tmp <= qmax) { last_q = qmin; do { q[current] = last_q + modifier; last_q = tmp; current = --nb[last_q - qmin]; } while ((tmp = q[current]) >= qmin && tmp <= qmax); q[current] = last_q + modifier; } } delete[] nb; for (i = 0; i < n; i++) { q[i] = q[i] - modifier; } } } // namespace gengraph python-igraph-0.8.0/vendor/source/igraph/src/igraph_cliquer.c0000644000076500000240000002513113614300625024542 0ustar tamasstaff00000000000000 #include "igraph_cliquer.h" #include "igraph_memory.h" #include "igraph_constants.h" #include "igraph_interrupt_internal.h" #include "cliquer/cliquer.h" #include "config.h" #include /* Call this to allow for interruption in Cliquer callback functions */ #define CLIQUER_ALLOW_INTERRUPTION() \ { \ if (igraph_i_interruption_handler) \ if (igraph_allow_interruption(NULL) != IGRAPH_SUCCESS) { \ cliquer_interrupted = 1; \ return FALSE; \ } \ } /* Interruptable Cliquer functions must be wrapped in CLIQUER_INTERRUPTABLE when called */ #define CLIQUER_INTERRUPTABLE(x) \ { \ cliquer_interrupted = 0; \ x; \ if (cliquer_interrupted) return IGRAPH_INTERRUPTED; \ } /* Nonzero value signals interuption from Cliquer callback function */ static IGRAPH_THREAD_LOCAL int cliquer_interrupted; /* For use with IGRAPH_FINALLY */ static void free_clique_list(igraph_vector_ptr_t *vp) { igraph_integer_t i, len; len = igraph_vector_ptr_size(vp); for (i = 0; i < len; ++i) { igraph_vector_destroy((igraph_vector_t *) VECTOR(*vp)[i]); } igraph_vector_ptr_free_all(vp); } /* We shall use this option struct for all calls to Cliquer */ static IGRAPH_THREAD_LOCAL clique_options igraph_cliquer_opt = { reorder_by_default, NULL, NULL, NULL, NULL, NULL, NULL, 0 }; /* Convert an igraph graph to a Cliquer graph */ static void igraph_to_cliquer(const igraph_t *ig, graph_t **cg) { igraph_integer_t vcount, ecount; int i; if (igraph_is_directed(ig)) { IGRAPH_WARNING("Edge directions are ignored for clique calculations"); } vcount = igraph_vcount(ig); ecount = igraph_ecount(ig); *cg = graph_new(vcount); for (i = 0; i < ecount; ++i) { long s, t; s = IGRAPH_FROM(ig, i); t = IGRAPH_TO(ig, i); if (s != t) { GRAPH_ADD_EDGE(*cg, s, t); } } } /* Copy weights to a Cliquer graph */ static int set_weights(const igraph_vector_t *vertex_weights, graph_t *g) { int i; assert(vertex_weights != NULL); if (igraph_vector_size(vertex_weights) != g->n) { IGRAPH_ERROR("Invalid vertex weight vector length", IGRAPH_EINVAL); } for (i = 0; i < g->n; ++i) { g->weights[i] = VECTOR(*vertex_weights)[i]; if (g->weights[i] != VECTOR(*vertex_weights)[i]) { IGRAPH_WARNING("Only integer vertex weights are supported; weights will be truncated to their integer parts"); } if (g->weights[i] <= 0) { IGRAPH_ERROR("Vertex weights must be positive", IGRAPH_EINVAL); } } return IGRAPH_SUCCESS; } /* Find all cliques. */ static boolean collect_cliques_callback(set_t s, graph_t *g, clique_options *opt) { igraph_vector_ptr_t *list; igraph_vector_t *clique; int i, j; CLIQUER_ALLOW_INTERRUPTION(); list = (igraph_vector_ptr_t *) opt->user_data; clique = (igraph_vector_t *) malloc(sizeof(igraph_vector_t)); igraph_vector_init(clique, set_size(s)); i = -1; j = 0; while ((i = set_return_next(s, i)) >= 0) { VECTOR(*clique)[j++] = i; } igraph_vector_ptr_push_back(list, clique); return TRUE; } int igraph_i_cliquer_cliques(const igraph_t *graph, igraph_vector_ptr_t *res, igraph_integer_t min_size, igraph_integer_t max_size) { graph_t *g; igraph_integer_t vcount = igraph_vcount(graph); if (vcount == 0) { igraph_vector_ptr_clear(res); return IGRAPH_SUCCESS; } if (min_size <= 0) { min_size = 1; } if (max_size <= 0) { max_size = 0; } if (max_size > 0 && max_size < min_size) { IGRAPH_ERROR("max_size must not be smaller than min_size", IGRAPH_EINVAL); } igraph_to_cliquer(graph, &g); IGRAPH_FINALLY(graph_free, g); igraph_vector_ptr_clear(res); igraph_cliquer_opt.user_data = res; igraph_cliquer_opt.user_function = &collect_cliques_callback; IGRAPH_FINALLY(free_clique_list, res); CLIQUER_INTERRUPTABLE(clique_unweighted_find_all(g, min_size, max_size, /* maximal= */ FALSE, &igraph_cliquer_opt)); IGRAPH_FINALLY_CLEAN(1); graph_free(g); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } /* Count cliques of each size. */ static boolean count_cliques_callback(set_t s, graph_t *g, clique_options *opt) { igraph_vector_t *hist; CLIQUER_ALLOW_INTERRUPTION(); hist = (igraph_vector_t *) opt->user_data; VECTOR(*hist)[set_size(s) - 1] += 1; return TRUE; } int igraph_i_cliquer_histogram(const igraph_t *graph, igraph_vector_t *hist, igraph_integer_t min_size, igraph_integer_t max_size) { graph_t *g; int i; igraph_integer_t vcount = igraph_vcount(graph); if (vcount == 0) { igraph_vector_clear(hist); return IGRAPH_SUCCESS; } if (min_size <= 0) { min_size = 1; } if (max_size <= 0) { max_size = vcount; /* also used for initial hist vector size, do not set to zero */ } if (max_size < min_size) { IGRAPH_ERROR("max_size must not be smaller than min_size", IGRAPH_EINVAL); } igraph_to_cliquer(graph, &g); IGRAPH_FINALLY(graph_free, g); igraph_vector_resize(hist, max_size); igraph_vector_null(hist); igraph_cliquer_opt.user_data = hist; igraph_cliquer_opt.user_function = &count_cliques_callback; CLIQUER_INTERRUPTABLE(clique_unweighted_find_all(g, min_size, max_size, /* maximal= */ FALSE, &igraph_cliquer_opt)); for (i = max_size; i > 0; --i) if (VECTOR(*hist)[i - 1] > 0) { break; } igraph_vector_resize(hist, i); igraph_vector_resize_min(hist); graph_free(g); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } /* Call function for each clique. */ struct callback_data { igraph_clique_handler_t *handler; void *arg; }; static boolean callback_callback(set_t s, graph_t *g, clique_options *opt) { igraph_vector_t *clique; struct callback_data *cd; int i, j; CLIQUER_ALLOW_INTERRUPTION(); cd = (struct callback_data *) opt->user_data; clique = (igraph_vector_t *) malloc(sizeof(igraph_vector_t)); igraph_vector_init(clique, set_size(s)); i = -1; j = 0; while ((i = set_return_next(s, i)) >= 0) { VECTOR(*clique)[j++] = i; } return (*(cd->handler))(clique, cd->arg); } int igraph_i_cliquer_callback(const igraph_t *graph, igraph_integer_t min_size, igraph_integer_t max_size, igraph_clique_handler_t *cliquehandler_fn, void *arg) { graph_t *g; struct callback_data cd; igraph_integer_t vcount = igraph_vcount(graph); if (vcount == 0) { return IGRAPH_SUCCESS; } if (min_size <= 0) { min_size = 1; } if (max_size <= 0) { max_size = 0; } if (max_size > 0 && max_size < min_size) { IGRAPH_ERROR("max_size must not be smaller than min_size", IGRAPH_EINVAL); } igraph_to_cliquer(graph, &g); IGRAPH_FINALLY(graph_free, g); cd.handler = cliquehandler_fn; cd.arg = arg; igraph_cliquer_opt.user_data = &cd; igraph_cliquer_opt.user_function = &callback_callback; CLIQUER_INTERRUPTABLE(clique_unweighted_find_all(g, min_size, max_size, /* maximal= */ FALSE, &igraph_cliquer_opt)); graph_free(g); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } /* Find weighted cliques in given weight range. */ int igraph_i_weighted_cliques(const igraph_t *graph, const igraph_vector_t *vertex_weights, igraph_vector_ptr_t *res, igraph_real_t min_weight, igraph_real_t max_weight, igraph_bool_t maximal) { graph_t *g; igraph_integer_t vcount = igraph_vcount(graph); if (vcount == 0) { igraph_vector_ptr_clear(res); return IGRAPH_SUCCESS; } if (min_weight != (int) min_weight) { IGRAPH_WARNING("Only integer vertex weights are supported; the minimum weight will be truncated to its integer part"); min_weight = (int) min_weight; } if (max_weight != (int) max_weight) { IGRAPH_WARNING("Only integer vertex weights are supported; the maximum weight will be truncated to its integer part"); max_weight = (int) max_weight; } if (min_weight <= 0) { min_weight = 1; } if (max_weight <= 0) { max_weight = 0; } if (max_weight > 0 && max_weight < min_weight) { IGRAPH_ERROR("max_weight must not be smaller than min_weight", IGRAPH_EINVAL); } igraph_to_cliquer(graph, &g); IGRAPH_FINALLY(graph_free, g); IGRAPH_CHECK(set_weights(vertex_weights, g)); igraph_vector_ptr_clear(res); igraph_cliquer_opt.user_data = res; igraph_cliquer_opt.user_function = &collect_cliques_callback; IGRAPH_FINALLY(free_clique_list, res); CLIQUER_INTERRUPTABLE(clique_find_all(g, min_weight, max_weight, maximal, &igraph_cliquer_opt)); IGRAPH_FINALLY_CLEAN(1); graph_free(g); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } /* Find largest weighted cliques. */ int igraph_i_largest_weighted_cliques(const igraph_t *graph, const igraph_vector_t *vertex_weights, igraph_vector_ptr_t *res) { graph_t *g; igraph_integer_t vcount = igraph_vcount(graph); if (vcount == 0) { igraph_vector_ptr_clear(res); return IGRAPH_SUCCESS; } igraph_to_cliquer(graph, &g); IGRAPH_FINALLY(graph_free, g); IGRAPH_CHECK(set_weights(vertex_weights, g)); igraph_vector_ptr_clear(res); igraph_cliquer_opt.user_data = res; igraph_cliquer_opt.user_function = &collect_cliques_callback; IGRAPH_FINALLY(free_clique_list, res); CLIQUER_INTERRUPTABLE(clique_find_all(g, 0, 0, FALSE, &igraph_cliquer_opt)); IGRAPH_FINALLY_CLEAN(1); graph_free(g); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } /* Find weight of largest weight clique. */ int igraph_i_weighted_clique_number(const igraph_t *graph, const igraph_vector_t *vertex_weights, igraph_real_t *res) { graph_t *g; igraph_integer_t vcount = igraph_vcount(graph); if (vcount == 0) { *res = 0; return IGRAPH_SUCCESS; } igraph_to_cliquer(graph, &g); IGRAPH_FINALLY(graph_free, g); IGRAPH_CHECK(set_weights(vertex_weights, g)); igraph_cliquer_opt.user_function = NULL; /* we are not using a callback function, thus this is not interruptable */ *res = clique_max_weight(g, &igraph_cliquer_opt); graph_free(g); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } python-igraph-0.8.0/vendor/source/igraph/src/gml_tree.c0000644000076500000240000001724313614300625023347 0ustar tamasstaff00000000000000/* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_gml_tree.h" #include "igraph_memory.h" #include "igraph_error.h" #include "config.h" #include #include int igraph_gml_tree_init_integer(igraph_gml_tree_t *t, const char *name, int namelen, igraph_integer_t value) { igraph_integer_t *p; IGRAPH_UNUSED(namelen); IGRAPH_VECTOR_PTR_INIT_FINALLY(&t->names, 1); IGRAPH_CHECK(igraph_vector_char_init(&t->types, 1)); IGRAPH_FINALLY(igraph_vector_char_destroy, &t->types); IGRAPH_VECTOR_PTR_INIT_FINALLY(&t->children, 1); /* names */ VECTOR(t->names)[0] = (void*)name; /* types */ VECTOR(t->types)[0] = IGRAPH_I_GML_TREE_INTEGER; /* children */ p = igraph_Calloc(1, igraph_integer_t); if (!p) { IGRAPH_ERROR("Cannot create integer GML tree node", IGRAPH_ENOMEM); } *p = value; VECTOR(t->children)[0] = p; IGRAPH_FINALLY_CLEAN(3); return 0; } int igraph_gml_tree_init_real(igraph_gml_tree_t *t, const char *name, int namelen, igraph_real_t value) { igraph_real_t *p; IGRAPH_UNUSED(namelen); IGRAPH_VECTOR_PTR_INIT_FINALLY(&t->names, 1); IGRAPH_CHECK(igraph_vector_char_init(&t->types, 1)); IGRAPH_FINALLY(igraph_vector_char_destroy, &t->types); IGRAPH_VECTOR_PTR_INIT_FINALLY(&t->children, 1); /* names */ VECTOR(t->names)[0] = (void*) name; /* types */ VECTOR(t->types)[0] = IGRAPH_I_GML_TREE_REAL; /* children */ p = igraph_Calloc(1, igraph_real_t); if (!p) { IGRAPH_ERROR("Cannot create real GML tree node", IGRAPH_ENOMEM); } *p = value; VECTOR(t->children)[0] = p; IGRAPH_FINALLY_CLEAN(3); return 0; } int igraph_gml_tree_init_string(igraph_gml_tree_t *t, const char *name, int namelen, const char *value, int valuelen) { IGRAPH_UNUSED(namelen); IGRAPH_UNUSED(valuelen); IGRAPH_VECTOR_PTR_INIT_FINALLY(&t->names, 1); IGRAPH_CHECK(igraph_vector_char_init(&t->types, 1)); IGRAPH_FINALLY(igraph_vector_char_destroy, &t->types); IGRAPH_VECTOR_PTR_INIT_FINALLY(&t->children, 1); /* names */ VECTOR(t->names)[0] = (void*) name; /* types */ VECTOR(t->types)[0] = IGRAPH_I_GML_TREE_STRING; /* children */ VECTOR(t->children)[0] = (void*)value; IGRAPH_FINALLY_CLEAN(3); return 0; } int igraph_gml_tree_init_tree(igraph_gml_tree_t *t, const char *name, int namelen, igraph_gml_tree_t *value) { IGRAPH_UNUSED(namelen); IGRAPH_VECTOR_PTR_INIT_FINALLY(&t->names, 1); IGRAPH_CHECK(igraph_vector_char_init(&t->types, 1)); IGRAPH_FINALLY(igraph_vector_char_destroy, &t->types); IGRAPH_VECTOR_PTR_INIT_FINALLY(&t->children, 1); /* names */ VECTOR(t->names)[0] = (void*)name; /* types */ VECTOR(t->types)[0] = IGRAPH_I_GML_TREE_TREE; /* children */ VECTOR(t->children)[0] = value; IGRAPH_FINALLY_CLEAN(3); return 0; } /* merge is destructive, the _second_ tree is destroyed */ int igraph_gml_tree_mergedest(igraph_gml_tree_t *t1, igraph_gml_tree_t *t2) { long int i, n = igraph_vector_ptr_size(&t2->children); for (i = 0; i < n; i++) { IGRAPH_CHECK(igraph_vector_ptr_push_back(&t1->names, VECTOR(t2->names)[i])); IGRAPH_CHECK(igraph_vector_char_push_back(&t1->types, VECTOR(t2->types)[i])); IGRAPH_CHECK(igraph_vector_ptr_push_back(&t1->children, VECTOR(t2->children)[i])); } igraph_vector_ptr_destroy(&t2->names); igraph_vector_char_destroy(&t2->types); igraph_vector_ptr_destroy(&t2->children); return 0; } void igraph_gml_tree_destroy(igraph_gml_tree_t *t) { long int i, n = igraph_vector_ptr_size(&t->children); for (i = 0; i < n; i++) { int type = VECTOR(t->types)[i]; switch (type) { case IGRAPH_I_GML_TREE_TREE: igraph_gml_tree_destroy(VECTOR(t->children)[i]); igraph_Free(VECTOR(t->names)[i]); break; case IGRAPH_I_GML_TREE_INTEGER: igraph_Free(VECTOR(t->children)[i]); igraph_Free(VECTOR(t->names)[i]); break; case IGRAPH_I_GML_TREE_REAL: igraph_Free(VECTOR(t->children)[i]); igraph_Free(VECTOR(t->names)[i]); break; case IGRAPH_I_GML_TREE_STRING: igraph_Free(VECTOR(t->children)[i]); igraph_Free(VECTOR(t->names)[i]); break; case IGRAPH_I_GML_TREE_DELETED: break; } } igraph_vector_ptr_destroy(&t->names); igraph_vector_char_destroy(&t->types); igraph_vector_ptr_destroy(&t->children); igraph_Free(t); } long int igraph_gml_tree_length(const igraph_gml_tree_t *t) { return igraph_vector_ptr_size(&t->names); } long int igraph_gml_tree_find(const igraph_gml_tree_t *t, const char *name, long int from) { long int size = igraph_vector_ptr_size(&t->names); while ( from < size && (! VECTOR(t->names)[from] || strcmp(VECTOR(t->names)[from], name)) ) { from++; } if (from == size) { from = -1; } return from; } long int igraph_gml_tree_findback(const igraph_gml_tree_t *t, const char *name, long int from) { while ( from >= 0 && (! VECTOR(t->names)[from] || strcmp(VECTOR(t->names)[from], name)) ) { from--; } return from; } int igraph_gml_tree_type(const igraph_gml_tree_t *t, long int pos) { return VECTOR(t->types)[pos]; } const char *igraph_gml_tree_name(const igraph_gml_tree_t *t, long int pos) { return VECTOR(t->names)[pos]; } igraph_integer_t igraph_gml_tree_get_integer(const igraph_gml_tree_t *t, long int pos) { igraph_integer_t *i = VECTOR(t->children)[pos]; return *i; } igraph_real_t igraph_gml_tree_get_real(const igraph_gml_tree_t *t, long int pos) { igraph_real_t *d = VECTOR(t->children)[pos]; return *d; } const char *igraph_gml_tree_get_string(const igraph_gml_tree_t *t, long int pos) { const char *s = VECTOR(t->children)[pos]; return s; } igraph_gml_tree_t *igraph_gml_tree_get_tree(const igraph_gml_tree_t *t, long int pos) { igraph_gml_tree_t *tree = VECTOR(t->children)[pos]; return tree; } void igraph_gml_tree_delete(igraph_gml_tree_t *t, long int pos) { if (VECTOR(t->types)[pos] == IGRAPH_I_GML_TREE_TREE) { igraph_gml_tree_destroy(VECTOR(t->children)[pos]); } igraph_Free(VECTOR(t->names)[pos]); igraph_Free(VECTOR(t->children)[pos]); VECTOR(t->children)[pos] = 0; VECTOR(t->names)[pos] = 0; VECTOR(t->types)[pos] = IGRAPH_I_GML_TREE_DELETED; } python-igraph-0.8.0/vendor/source/igraph/src/Makefile.am0000644000076500000240000004470213614300625023441 0ustar tamasstaff00000000000000# This is to make sure that the headers get built before they are included BUILT_SOURCES = foreign-ncol-parser.h foreign-lgl-parser.h \ foreign-dl-parser.h foreign-gml-parser.h \ foreign-pajek-parser.h # This is needed to ensure that yacc (or bison) builds the header files # Unfortunately this is not the default behaviour in MinGW/MSYS AM_YFLAGS = -d lib_LTLIBRARIES = libigraph.la include lapack/blas.inc include lapack/lapack.inc include lapack/arpack.inc include plfit/plfit.inc F2C = f2c/abort_.c f2c/dolio.c f2c/r_sin.c\ f2c/dummy.c f2c/dtime_.c f2c/iio.c f2c/r_sinh.c\ f2c/backspac.c f2c/due.c f2c/ilnw.c f2c/r_sqrt.c\ f2c/c_abs.c f2c/ef1asc_.c f2c/inquire.c f2c/r_tan.c\ f2c/c_cos.c f2c/ef1cmc_.c f2c/l_ge.c f2c/r_tanh.c\ f2c/c_div.c f2c/endfile.c f2c/l_gt.c f2c/rdfmt.c\ f2c/c_exp.c f2c/erf_.c f2c/l_le.c f2c/rewind.c\ f2c/c_log.c f2c/erfc_.c f2c/l_lt.c f2c/rsfe.c\ f2c/c_sin.c f2c/err.c f2c/lbitbits.c f2c/rsli.c\ f2c/c_sqrt.c f2c/etime_.c f2c/lbitshft.c f2c/rsne.c\ f2c/cabs.c f2c/exit_.c f2c/lread.c f2c/s_cat.c\ f2c/close.c f2c/f77_aloc.c f2c/lwrite.c f2c/s_cmp.c\ f2c/ctype.c f2c/f77vers.c f2c/s_copy.c\ f2c/d_abs.c f2c/fmt.c f2c/open.c f2c/s_paus.c\ f2c/d_acos.c f2c/fmtlib.c f2c/pow_ci.c f2c/s_rnge.c\ f2c/d_asin.c f2c/ftell_.c f2c/pow_dd.c f2c/s_stop.c\ f2c/d_atan.c f2c/pow_di.c f2c/sfe.c\ f2c/d_atn2.c f2c/getenv_.c f2c/pow_hh.c f2c/sig_die.c\ f2c/d_cnjg.c f2c/h_abs.c f2c/pow_ii.c f2c/signal_.c\ f2c/d_cos.c f2c/h_dim.c f2c/pow_ri.c f2c/signbit.c\ f2c/d_cosh.c f2c/h_dnnt.c f2c/pow_zi.c f2c/sue.c\ f2c/d_dim.c f2c/h_indx.c f2c/pow_zz.c f2c/system_.c\ f2c/d_exp.c f2c/h_len.c f2c/r_abs.c f2c/typesize.c\ f2c/d_imag.c f2c/h_mod.c f2c/r_acos.c f2c/uio.c\ f2c/d_int.c f2c/h_nint.c f2c/r_asin.c f2c/uninit.c\ f2c/d_lg10.c f2c/h_sign.c f2c/r_atan.c f2c/util.c\ f2c/d_log.c f2c/hl_ge.c f2c/r_atn2.c f2c/wref.c\ f2c/d_mod.c f2c/hl_gt.c f2c/r_cnjg.c f2c/wrtfmt.c\ f2c/d_nint.c f2c/hl_le.c f2c/r_cos.c f2c/wsfe.c\ f2c/d_prod.c f2c/hl_lt.c f2c/r_cosh.c f2c/wsle.c\ f2c/d_sign.c f2c/i77vers.c f2c/r_dim.c f2c/wsne.c\ f2c/d_sin.c f2c/i_abs.c f2c/r_exp.c f2c/xwsne.c\ f2c/d_sinh.c f2c/i_dim.c f2c/r_imag.c f2c/z_abs.c\ f2c/d_sqrt.c f2c/i_dnnt.c f2c/r_int.c f2c/z_cos.c\ f2c/d_tan.c f2c/i_indx.c f2c/r_lg10.c f2c/z_div.c\ f2c/d_tanh.c f2c/i_len.c f2c/r_log.c f2c/z_exp.c\ f2c/derf_.c f2c/i_mod.c f2c/r_mod.c f2c/z_log.c\ f2c/derfc_.c f2c/i_nint.c f2c/r_nint.c f2c/z_sin.c\ f2c/dfe.c f2c/i_sign.c f2c/r_sign.c f2c/z_sqrt.c # We also have to pack f2c/arithchk.c in the distribution in case the # user wants to compile it using the internal f2c. f2c/arithchk.c is # not linked into libf2c.la (hence we cannot add it to libf2c_la_SOURCES) # but is needed to build f2c/arith.h EXTRA_DIST = f2c/arithchk.c if INTERNAL_F2C libf2c_la_SOURCES = f2c.h f2c/fio.h f2c/fmt.h f2c/sysdep1.h\ f2c/sysdep1.h0 f2c/lio.h f2c/fp.h f2c/signal1.h\ f2c/signal1.h0 $(F2C) libf2c_la_CFLAGS = -DSkip_f2c_Undefs -I. -I$(top_srcdir)/include -I$(top_builddir)/include -I$(top_builddir)/src/f2c $(WARNING_CFLAGS) f2c/arith.h: f2c/arithchk.c $(CC) $(CFLAGS) -DNO_FPINIT $(top_srcdir)/src/f2c/arithchk.c -lm -o f2c/arith || \ $(CC) -DNO_LONG_LONG $(CFLAGS) -DNO_FPINIT $(top_srcdir)/src/f2c/arithchk.c \ $(WARNING_CFLAGS) -lm -o f2c/arith f2c/arith > f2c/arith.h f2c/sysdep1.h: f2c/sysdep1.h0 cp f2c/sysdep1.h0 f2c/sysdep1.h f2c/signal1.h: f2c/signal1.h0 cp f2c/signal1.h0 f2c/signal1.h F2C_LIB = libf2c.la BUILT_SOURCES += f2c/arith.h endif if INTERNAL_BLAS libblas_la_SOURCES = f2c.h $(BLAS) libblas_la_CFLAGS = -I. -I$(top_srcdir)/include -I$(top_builddir)/include $(WARNING_CFLAGS) BLAS_LIB = libblas.la endif if INTERNAL_LAPACK liblapack_la_SOURCES = f2c.h $(LAPACK) liblapack_la_CFLAGS = -I. -I$(top_srcdir)/include -I$(top_builddir)/include $(WARNING_CFLAGS) libdlamch_la_SOURCES = lapack/dlamch.c libdlamch_la_CFLAGS = $(FLOATSTORE) -I. -I$(top_srcdir)/include -I$(top_builddir)/include $(WARNING_CFLAGS) LAPACK_LIB = liblapack.la libdlamch.la endif if INTERNAL_ARPACK libarpack_la_SOURCES = f2c.h $(ARPACK) libarpack_la_CFLAGS = -I. -I$(top_srcdir)/include -I$(top_builddir)/include $(WARNING_CFLAGS) ARPACK_LIB = libarpack.la endif include ../optional/glpk/glpk.inc if INTERNAL_GLPK libglpk_la_SOURCES = $(GLPK) libglpk_la_CFLAGS = -I$(top_srcdir)/optional/glpk libglpk_la_CPPFLAGS = -I$(top_srcdir)/include GLPK_LIB = libglpk.la endif include prpack/prpack.inc libprpack_la_SOURCES = $(PRPACK) libprpack_la_CFLAGS = -I$(top_srcdir)/include -DPRPACK_IGRAPH_SUPPORT libprpack_la_CPPFLAGS = -I$(top_srcdir)/include -DPRPACK_IGRAPH_SUPPORT PRPACK_LIB = libprpack.la libplfit_la_SOURCES = $(PLFIT) PLFIT_LIB = libplfit.la noinst_LTLIBRARIES = $(F2C_LIB) $(BLAS_LIB) $(LAPACK_LIB) $(ARPACK_LIB) \ $(GLPK_LIB) $(PLFIT_LIB) $(PRPACK_LIB) CS = cs/cs_add.c cs/cs_happly.c cs/cs_pvec.c \ cs/cs_amd.c cs/cs_house.c cs/cs_qr.c \ cs/cs_chol.c cs/cs_ipvec.c cs/cs_qrsol.c \ cs/cs_cholsol.c cs/cs_leaf.c cs/cs_randperm.c \ cs/cs_compress.c cs/cs_load.c cs/cs_reach.c \ cs/cs_counts.c cs/cs_lsolve.c cs/cs_scatter.c \ cs/cs_cumsum.c cs/cs_ltsolve.c cs/cs_scc.c \ cs/cs_dfs.c cs/cs_lu.c cs/cs_schol.c \ cs/cs_dmperm.c cs/cs_lusol.c cs/cs_spsolve.c \ cs/cs_droptol.c cs/cs_malloc.c cs/cs_sqr.c \ cs/cs_dropzeros.c cs/cs_maxtrans.c cs/cs_symperm.c \ cs/cs_dupl.c cs/cs_multiply.c cs/cs_tdfs.c \ cs/cs_entry.c cs/cs_norm.c cs/cs_transpose.c \ cs/cs_ereach.c cs/cs_permute.c cs/cs_updown.c \ cs/cs_etree.c cs/cs_pinv.c cs/cs_usolve.c \ cs/cs_fkeep.c cs/cs_post.c cs/cs_util.c \ cs/cs_gaxpy.c cs/cs_print.c cs/cs_utsolve.c \ cs/cs.h cs/UFconfig.h CHOLMOD = CHOLMOD/Check/cholmod_check.c \ CHOLMOD/Check/cholmod_read.c \ CHOLMOD/Check/cholmod_write.c \ CHOLMOD/Cholesky/cholmod_amd.c \ CHOLMOD/Cholesky/cholmod_analyze.c \ CHOLMOD/Cholesky/cholmod_colamd.c \ CHOLMOD/Cholesky/cholmod_etree.c \ CHOLMOD/Cholesky/cholmod_factorize.c \ CHOLMOD/Cholesky/cholmod_postorder.c \ CHOLMOD/Cholesky/cholmod_rcond.c \ CHOLMOD/Cholesky/cholmod_resymbol.c \ CHOLMOD/Cholesky/cholmod_rowcolcounts.c \ CHOLMOD/Cholesky/cholmod_rowfac.c \ CHOLMOD/Cholesky/cholmod_solve.c \ CHOLMOD/Cholesky/cholmod_spsolve.c \ CHOLMOD/Core/cholmod_aat.c \ CHOLMOD/Core/cholmod_add.c \ CHOLMOD/Core/cholmod_band.c \ CHOLMOD/Core/cholmod_change_factor.c \ CHOLMOD/Core/cholmod_common.c \ CHOLMOD/Core/cholmod_complex.c \ CHOLMOD/Core/cholmod_copy.c \ CHOLMOD/Core/cholmod_dense.c \ CHOLMOD/Core/cholmod_error.c \ CHOLMOD/Core/cholmod_factor.c \ CHOLMOD/Core/cholmod_memory.c \ CHOLMOD/Core/cholmod_sparse.c \ CHOLMOD/Core/cholmod_transpose.c \ CHOLMOD/Core/cholmod_triplet.c \ CHOLMOD/Core/cholmod_version.c \ CHOLMOD/MatrixOps/cholmod_drop.c \ CHOLMOD/MatrixOps/cholmod_horzcat.c \ CHOLMOD/MatrixOps/cholmod_norm.c \ CHOLMOD/MatrixOps/cholmod_scale.c \ CHOLMOD/MatrixOps/cholmod_sdmult.c \ CHOLMOD/MatrixOps/cholmod_ssmult.c \ CHOLMOD/MatrixOps/cholmod_submatrix.c \ CHOLMOD/MatrixOps/cholmod_symmetry.c \ CHOLMOD/MatrixOps/cholmod_vertcat.c \ CHOLMOD/Modify/cholmod_rowadd.c \ CHOLMOD/Modify/cholmod_rowdel.c \ CHOLMOD/Modify/cholmod_updown.c \ CHOLMOD/Partition/cholmod_camd.c \ CHOLMOD/Partition/cholmod_ccolamd.c \ CHOLMOD/Partition/cholmod_csymamd.c \ CHOLMOD/Partition/cholmod_metis.c \ CHOLMOD/Partition/cholmod_nesdis.c \ CHOLMOD/Supernodal/cholmod_super_numeric.c \ CHOLMOD/Supernodal/cholmod_super_solve.c \ CHOLMOD/Supernodal/cholmod_super_symbolic.c \ CHOLMOD/Include/cholmod.h \ CHOLMOD/Include/cholmod_blas.h \ CHOLMOD/Include/cholmod_camd.h \ CHOLMOD/Include/cholmod_check.h \ CHOLMOD/Include/cholmod_cholesky.h \ CHOLMOD/Include/cholmod_complexity.h \ CHOLMOD/Include/cholmod_config.h \ CHOLMOD/Include/cholmod_core.h \ CHOLMOD/Include/cholmod_internal.h \ CHOLMOD/Include/cholmod_io64.h \ CHOLMOD/Include/cholmod_matrixops.h \ CHOLMOD/Include/cholmod_modify.h \ CHOLMOD/Include/cholmod_partition.h \ CHOLMOD/Include/cholmod_supernodal.h \ CHOLMOD/Include/cholmod_template.h EXTRA_DIST += CHOLMOD/Cholesky/t_cholmod_lsolve.c \ CHOLMOD/Cholesky/t_cholmod_ltsolve.c \ CHOLMOD/Cholesky/t_cholmod_rowfac.c \ CHOLMOD/Cholesky/t_cholmod_solve.c \ CHOLMOD/Core/t_cholmod_change_factor.c \ CHOLMOD/Core/t_cholmod_dense.c \ CHOLMOD/Core/t_cholmod_transpose.c \ CHOLMOD/Core/t_cholmod_triplet.c \ CHOLMOD/MatrixOps/t_cholmod_sdmult.c \ CHOLMOD/Modify/t_cholmod_updown.c \ CHOLMOD/Modify/t_cholmod_updown_numkr.c \ CHOLMOD/Supernodal/t_cholmod_gpu.c \ CHOLMOD/Supernodal/t_cholmod_super_numeric.c \ CHOLMOD/Supernodal/t_cholmod_super_solve.c AMD = AMD/Source/amd_1.c \ AMD/Source/amd_2.c \ AMD/Source/amd_aat.c \ AMD/Source/amd_control.c \ AMD/Source/amd_defaults.c \ AMD/Source/amd_dump.c \ AMD/Source/amd_global.c \ AMD/Source/amd_info.c \ AMD/Source/amd_order.c \ AMD/Source/amd_post_tree.c \ AMD/Source/amd_postorder.c \ AMD/Source/amd_preprocess.c \ AMD/Source/amd_valid.c \ AMD/Include/amd.h \ AMD/Include/amd_internal.h COLAMD = COLAMD/Source/colamd.c \ COLAMD/Source/colamd_global.c \ COLAMD/Include/colamd.h SPCONFIG = SuiteSparse_config/SuiteSparse_config.c \ SuiteSparse_config/SuiteSparse_config.h HEADERS_PRIVATE = atlas-edges.h \ bliss/bignum.hh bliss/defs.hh \ bliss/graph.hh bliss/uintseqhash.hh \ bliss/heap.hh bliss/kqueue.hh \ bliss/kstack.hh bliss/orbit.hh \ bliss/partition.hh bliss/utils.hh \ NetDataTypes.h NetRoutines.h \ pottsmodel_2.h \ igraph_gml_tree.h \ walktrap_graph.h walktrap_communities.h \ walktrap_heap.h \ infomap_Greedy.h infomap_Node.h infomap_Greedy.h infomap_FlowGraph.h \ igraph_math.h \ drl_layout.h drl_parse.h drl_graph.h \ drl_graph_3d.h drl_layout_3d.h \ drl_Node.h drl_Node_3d.h \ DensityGrid.h DensityGrid_3d.h \ igraph_flow_internal.h \ vector.pmt matrix.pmt stack.pmt dqueue.pmt heap.pmt array.pmt \ igraph_types_internal.h \ foreign-dl-header.h bignum.h bigint.h \ gengraph_box_list.h gengraph_definitions.h \ gengraph_degree_sequence.h gengraph_graph_molloy_hash.h \ gengraph_graph_molloy_optimized.h \ gengraph_hash.h gengraph_header.h gengraph_powerlaw.h \ gengraph_qsort.h gengraph_random.h gengraph_vertex_cover.h \ igraph_blas_internal.h igraph_arpack_internal.h \ igraph_lapack_internal.h igraph_glpk_support.h \ igraph_marked_queue.h igraph_estack.h \ hrg_dendro.h hrg_graph.h hrg_rbtree.h hrg_splittree_eq.h \ hrg_graph_simp.h foreign-gml-header.h \ foreign-ncol-header.h foreign-lgl-header.h \ foreign-pajek-header.h igraph_interrupt_internal.h \ scg_headers.h igraph_hacks_internal.h triangles_template.h \ triangles_template1.h maximal_cliques_template.h prpack.h \ igraph_cliquer.h cliquer/graph.h cliquer/cliquer.h cliquer/misc.h \ cliquer/cliquerconf.h cliquer/reorder.h cliquer/set.h \ structural_properties_internal.h HEADERS_PUBLIC =../include/igraph.h ../include/igraph_memory.h \ ../include/igraph_random.h ../include/igraph_types.h \ ../include/igraph_vector.h ../include/igraph_matrix.h \ ../include/igraph_array.h ../include/igraph_dqueue.h \ ../include/igraph_stack.h ../include/igraph_heap.h \ ../include/igraph_arpack.h \ ../include/igraph_attributes.h ../include/igraph_error.h \ ../include/igraph_pmt.h ../include/igraph_pmt_off.h \ ../include/igraph_adjlist.h ../include/igraph_iterators.h \ ../include/igraph_bipartite.h ../include/igraph_layout.h \ ../include/igraph_centrality.h ../include/igraph_motifs.h \ ../include/igraph_cliques.h ../include/igraph_neighborhood.h \ ../include/igraph_cocitation.h ../include/igraph_nongraph.h \ ../include/igraph_community.h ../include/igraph_operators.h \ ../include/igraph_components.h ../include/igraph_paths.h \ ../include/igraph_constructors.h ../include/igraph_progress.h \ ../include/igraph_conversion.h \ ../include/igraph_datatype.h ../include/igraph_structural.h\ ../include/igraph_flow.h ../include/igraph_topology.h \ ../include/igraph_foreign.h ../include/igraph_transitivity.h \ ../include/igraph_games.h ../include/igraph_visitor.h \ ../include/igraph_interface.h ../include/igraph_constants.h \ ../include/igraph_vector_pmt.h ../include/igraph_matrix_pmt.h\ ../include/igraph_array_pmt.h ../include/igraph_dqueue_pmt.h\ ../include/igraph_stack_pmt.h ../include/igraph_heap_pmt.h \ ../include/igraph_vector_ptr.h ../include/igraph_spmatrix.h \ ../include/igraph_strvector.h ../include/igraph_psumtree.h \ ../include/igraph_sparsemat.h ../include/igraph_mixing.h \ ../include/igraph_version.h ../include/igraph_blas.h \ ../include/igraph_separators.h ../include/igraph_cohesive_blocks.h \ ../include/igraph_lapack.h ../include/igraph_complex.h \ ../include/igraph_eigen.h ../include/igraph_statusbar.h \ ../include/igraph_hrg.h ../include/igraph_microscopic_update.h \ ../include/igraph_interrupt.h ../include/igraph_threading.h \ ../include/igraph_scg.h ../include/igraph_qsort.h \ ../include/igraph_matching.h ../include/igraph_embedding.h \ ../include/igraph_scan.h ../include/igraph_graphlets.h \ ../include/igraph_vector_type.h ../include/igraph_epidemics.h \ ../include/igraph_lsap.h ../include/igraph_decls.h \ ../include/igraph_coloring.h SOURCES = basic_query.c games.c cocitation.c iterators.c \ structural_properties.c components.c layout.c \ structure_generators.c conversion.c \ type_indexededgelist.c spanning_trees.c \ igraph_error.c interrupt.c other.c foreign.c random.c \ attributes.c \ foreign-ncol-parser.y foreign-ncol-lexer.l \ foreign-lgl-parser.y foreign-lgl-lexer.l \ foreign-pajek-parser.y foreign-pajek-lexer.l \ foreign-gml-parser.y foreign-gml-lexer.l \ dqueue.c heap.c igraph_heap.c igraph_stack.c \ igraph_strvector.c igraph_trie.c matrix.c \ vector.c vector_ptr.c memory.c adjlist.c \ visitors.c igraph_grid.c atlas.c topology.c \ motifs.c progress.c operators.c \ igraph_psumtree.c array.c igraph_hashtable.c \ foreign-graphml.c flow.c igraph_buckets.c \ NetDataTypes.cpp NetRoutines.cpp clustertool.cpp \ pottsmodel_2.cpp spectral_properties.c cores.c \ igraph_set.c cliques.c \ walktrap.cpp walktrap_heap.cpp \ walktrap_graph.cpp walktrap_communities.cpp \ infomap.cc infomap_Greedy.cc infomap_Node.cc infomap_FlowGraph.cc \ spmatrix.c community.c fast_community.c community_leiden.c \ gml_tree.c \ bliss/orbit.cc bliss/defs.cc bliss/uintseqhash.cc \ bliss/partition.cc bliss/graph.cc \ bliss/bliss_heap.cc bliss/utils.cc bliss.cc \ cattributes.c zeroin.c bfgs.c math.c \ forestfire.c microscopic_update.c \ blas.c arpack.c centrality.c drl_layout.cpp drl_parse.cpp \ drl_graph.cpp DensityGrid.cpp \ gengraph_box_list.cpp gengraph_degree_sequence.cpp \ gengraph_graph_molloy_hash.cpp \ gengraph_graph_molloy_optimized.cpp \ gengraph_mr-connected.cpp gengraph_powerlaw.cpp \ gengraph_random.cpp decomposition.c bipartite.c \ drl_layout_3d.cpp drl_graph_3d.cpp \ DensityGrid_3d.cpp \ foreign-dl-parser.y foreign-dl-lexer.l \ $(CS) sparsemat.c mixing.c bigint.c bignum.c \ version.c optimal_modularity.c \ igraph_fixed_vectorlist.c separators.c \ igraph_marked_queue.c igraph_estack.c st-cuts.c \ cohesive_blocks.c statusbar.c \ lapack.c complex.c eigen.c feedback_arc_set.c \ sugiyama.c glpk_support.c \ igraph_hrg_types.cc igraph_hrg.cc \ distances.c fortran_intrinsics.c matching.c \ scg.c scg_approximate_methods.c scg_exact_scg.c \ scg_kmeans.c scg_utils.c scg_optimal_method.c \ qsort.c qsort_r.c types.c lad.c hacks.c \ embedding.c scan.c triangles.c glet.c \ maximal_cliques.c sbm.c dotproduct.c sir.c \ prpack.cpp $(CHOLMOD) $(AMD) $(COLAMD) \ $(SPCONFIG) layout_gem.c layout_dh.c lsap.c \ layout_fr.c layout_kk.c paths.c \ random_walk.c \ igraph_cliquer.c cliquer/cliquer.c cliquer/cliquer_graph.c cliquer/reorder.c \ coloring.c \ degree_sequence.cpp if INTERNAL_F2C else SOURCES += f2c/dummy.c endif libigraph_la_SOURCES = $(SOURCES) $(HEADERS_PRIVATE) libigraph_la_CFLAGS = -I$(top_srcdir)/include \ -I$(top_builddir)/include \ -I$(top_srcdir)/src/CHOLMOD/Include \ -I$(top_builddir)/src/CHOLMOD/Include \ -I$(top_srcdir)/src/AMD/Include \ -I$(top_builddir)/src/AMD/Include \ -I$(top_srcdir)/src/COLAMD/Include \ -I$(top_builddir)/src/COLAMD/Include \ -I$(top_srcdir)/src/SuiteSparse_config \ -I$(top_builddir)/src/SuiteSparse_config \ -DNPARTITION -DNTIMER -DNCAMD $(WARNING_CFLAGS) libigraph_la_CXXFLAGS = -I$(top_srcdir)/include -I$(top_builddir)/include $(WARNING_CFLAGS) libigraph_la_LDFLAGS = -no-undefined libigraph_la_LIBADD = -lm $(XML2_LIBS) $(F2C_LIB) $(BLAS_LIB) \ $(LAPACK_LIB) $(ARPACK_LIB) $(GLPK_LIB) $(PRPACK_LIB) \ $(PLFIT_LIB) if INTERNAL_GLPK libigraph_la_CFLAGS += -I$(top_srcdir)/optional/glpk libigraph_la_CXXFLAGS += -I$(top_srcdir)/optional/glpk endif libigraph_la_CFLAGS += -I$(top_srcdir)/src/prpack -DPRPACK_IGRAPH_SUPPORT libigraph_la_CXXFLAGS += -I$(top_srcdir)/src/prpack -DPRPACK_IGRAPH_SUPPORT igraphincludedir = $(includedir)/igraph igraphinclude_HEADERS = $(HEADERS_PUBLIC) MAINTAINERCLEANFILES = Makefile.in foreign-lgl-parser.h foreign-ncol-parser.h echosources: $(info $(SOURCES) $(LAPACK) $(ARPACK) $(BLAS) $(libf2c_la_SOURCES) \ $(libdlamch_la_SOURCES) $(libplfit_la_SOURCES) $(PRPACK)) echoheaders: $(info $(HEADERS_PUBLIC)) echoheadersprivate: $(info $(HEADERS_PRIVATE)) .PHONY: sources parsersources: $(DIST_COMMON) python-igraph-0.8.0/vendor/source/igraph/src/AMD/0000755000076500000240000000000013617375001022002 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/src/AMD/Makefile0000644000076500000240000000337513524616144023455 0ustar tamasstaff00000000000000#------------------------------------------------------------------------------ # AMD Makefile (for GNU Make or original make) #------------------------------------------------------------------------------ VERSION = 2.3.1 default: all include ../SuiteSparse_config/SuiteSparse_config.mk demos: all # Compile all C code. Do not compile the FORTRAN versions. all: ( cd Lib ; $(MAKE) ) ( cd Demo ; $(MAKE) ) # compile just the C-callable libraries (not Demos) library: ( cd Lib ; $(MAKE) ) # compile the FORTRAN libraries and demo programs (not compiled by "make all") fortran: ( cd Lib ; $(MAKE) fortran ) ( cd Demo ; $(MAKE) fortran ) # compile a FORTRAN demo program that calls the C version of AMD # (not compiled by "make all") cross: ( cd Demo ; $(MAKE) cross ) # remove object files, but keep the compiled programs and library archives clean: ( cd Lib ; $(MAKE) clean ) ( cd Demo ; $(MAKE) clean ) ( cd MATLAB ; $(RM) $(CLEAN) ) ( cd Doc ; $(MAKE) clean ) # clean, and then remove compiled programs and library archives purge: ( cd Lib ; $(MAKE) purge ) ( cd Demo ; $(MAKE) purge ) ( cd MATLAB ; $(RM) $(CLEAN) ; $(RM) *.mex* ) ( cd Doc ; $(MAKE) purge ) distclean: purge # create PDF documents for the original distribution docs: ( cd Doc ; $(MAKE) ) # get ready for distribution dist: purge ( cd Demo ; $(MAKE) dist ) ( cd Doc ; $(MAKE) ) ccode: library lib: library # install AMD install: $(CP) Lib/libamd.a $(INSTALL_LIB)/libamd.$(VERSION).a ( cd $(INSTALL_LIB) ; ln -sf libamd.$(VERSION).a libamd.a ) $(CP) Include/amd.h $(INSTALL_INCLUDE) chmod 644 $(INSTALL_LIB)/libamd* chmod 644 $(INSTALL_INCLUDE)/amd.h # uninstall AMD uninstall: $(RM) $(INSTALL_LIB)/libamd*.a $(RM) $(INSTALL_INCLUDE)/amd.h python-igraph-0.8.0/vendor/source/igraph/src/AMD/Include/0000755000076500000240000000000013617375001023365 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/src/AMD/Include/amd_internal.h0000644000076500000240000002161113524616144026177 0ustar tamasstaff00000000000000/* ========================================================================= */ /* === amd_internal.h ====================================================== */ /* ========================================================================= */ /* ------------------------------------------------------------------------- */ /* AMD, Copyright (c) Timothy A. Davis, */ /* Patrick R. Amestoy, and Iain S. Duff. See ../README.txt for License. */ /* email: DrTimothyAldenDavis@gmail.com */ /* ------------------------------------------------------------------------- */ /* This file is for internal use in AMD itself, and does not normally need to * be included in user code (it is included in UMFPACK, however). All others * should use amd.h instead. * * The following compile-time definitions affect how AMD is compiled. * * -DNPRINT * * Disable all printing. stdio.h will not be included. Printing can * be re-enabled at run-time by setting the global pointer amd_printf * to printf (or mexPrintf for a MATLAB mexFunction). * * -DNMALLOC * * No memory manager is defined at compile-time. You MUST define the * function pointers amd_malloc, amd_free, amd_realloc, and * amd_calloc at run-time for AMD to work properly. */ /* ========================================================================= */ /* === NDEBUG ============================================================== */ /* ========================================================================= */ /* * Turning on debugging takes some work (see below). If you do not edit this * file, then debugging is always turned off, regardless of whether or not * -DNDEBUG is specified in your compiler options. * * If AMD is being compiled as a mexFunction, then MATLAB_MEX_FILE is defined, * and mxAssert is used instead of assert. If debugging is not enabled, no * MATLAB include files or functions are used. Thus, the AMD library libamd.a * can be safely used in either a stand-alone C program or in another * mexFunction, without any change. */ /* AMD will be exceedingly slow when running in debug mode. The next three lines ensure that debugging is turned off. */ #ifndef NDEBUG #define NDEBUG #endif /* To enable debugging, uncomment the following line: #undef NDEBUG */ /* ------------------------------------------------------------------------- */ /* ANSI include files */ /* ------------------------------------------------------------------------- */ /* from stdlib.h: size_t, malloc, free, realloc, and calloc */ #include #if !defined(NPRINT) || !defined(NDEBUG) /* from stdio.h: printf. Not included if NPRINT is defined at compile time. * fopen and fscanf are used when debugging. */ #include #endif /* from limits.h: INT_MAX and LONG_MAX */ #include /* from math.h: sqrt */ #include /* ------------------------------------------------------------------------- */ /* MATLAB include files (only if being used in or via MATLAB) */ /* ------------------------------------------------------------------------- */ #ifdef MATLAB_MEX_FILE #include "matrix.h" #include "mex.h" #endif /* ------------------------------------------------------------------------- */ /* basic definitions */ /* ------------------------------------------------------------------------- */ #ifdef FLIP #undef FLIP #endif #ifdef MAX #undef MAX #endif #ifdef MIN #undef MIN #endif #ifdef EMPTY #undef EMPTY #endif #ifdef GLOBAL #undef GLOBAL #endif #ifdef PRIVATE #undef PRIVATE #endif /* FLIP is a "negation about -1", and is used to mark an integer i that is * normally non-negative. FLIP (EMPTY) is EMPTY. FLIP of a number > EMPTY * is negative, and FLIP of a number < EMTPY is positive. FLIP (FLIP (i)) = i * for all integers i. UNFLIP (i) is >= EMPTY. */ #define EMPTY (-1) #define FLIP(i) (-(i)-2) #define UNFLIP(i) ((i < EMPTY) ? FLIP (i) : (i)) /* for integer MAX/MIN, or for doubles when we don't care how NaN's behave: */ #define MAX(a,b) (((a) > (b)) ? (a) : (b)) #define MIN(a,b) (((a) < (b)) ? (a) : (b)) /* logical expression of p implies q: */ #define IMPLIES(p,q) (!(p) || (q)) /* Note that the IBM RS 6000 xlc predefines TRUE and FALSE in . */ /* The Compaq Alpha also predefines TRUE and FALSE. */ #ifdef TRUE #undef TRUE #endif #ifdef FALSE #undef FALSE #endif #define TRUE (1) #define FALSE (0) #define PRIVATE static #define GLOBAL #define EMPTY (-1) /* Note that Linux's gcc 2.96 defines NULL as ((void *) 0), but other */ /* compilers (even gcc 2.95.2 on Solaris) define NULL as 0 or (0). We */ /* need to use the ANSI standard value of 0. */ #ifdef NULL #undef NULL #endif #define NULL 0 /* largest value of size_t */ #ifndef SIZE_T_MAX #ifdef SIZE_MAX /* C99 only */ #define SIZE_T_MAX SIZE_MAX #else #define SIZE_T_MAX ((size_t) (-1)) #endif #endif /* ------------------------------------------------------------------------- */ /* integer type for AMD: int or SuiteSparse_long */ /* ------------------------------------------------------------------------- */ #include "amd.h" #if defined (DLONG) || defined (ZLONG) #define Int SuiteSparse_long #define ID SuiteSparse_long_id #define Int_MAX SuiteSparse_long_max #define AMD_order amd_l_order #define AMD_defaults amd_l_defaults #define AMD_control amd_l_control #define AMD_info amd_l_info #define AMD_1 amd_l1 #define AMD_2 amd_l2 #define AMD_valid amd_l_valid #define AMD_aat amd_l_aat #define AMD_postorder amd_l_postorder #define AMD_post_tree amd_l_post_tree #define AMD_dump amd_l_dump #define AMD_debug amd_l_debug #define AMD_debug_init amd_l_debug_init #define AMD_preprocess amd_l_preprocess #else #define Int int #define ID "%d" #define Int_MAX INT_MAX #define AMD_order amd_order #define AMD_defaults amd_defaults #define AMD_control amd_control #define AMD_info amd_info #define AMD_1 amd_1 #define AMD_2 amd_2 #define AMD_valid amd_valid #define AMD_aat amd_aat #define AMD_postorder amd_postorder #define AMD_post_tree amd_post_tree #define AMD_dump amd_dump #define AMD_debug amd_debug #define AMD_debug_init amd_debug_init #define AMD_preprocess amd_preprocess #endif /* ========================================================================= */ /* === PRINTF macro ======================================================== */ /* ========================================================================= */ /* All output goes through the PRINTF macro. */ #define PRINTF(params) { if (amd_printf != NULL) (void) amd_printf params ; } /* ------------------------------------------------------------------------- */ /* AMD routine definitions (not user-callable) */ /* ------------------------------------------------------------------------- */ GLOBAL size_t AMD_aat ( Int n, const Int Ap [ ], const Int Ai [ ], Int Len [ ], Int Tp [ ], double Info [ ] ) ; GLOBAL void AMD_1 ( Int n, const Int Ap [ ], const Int Ai [ ], Int P [ ], Int Pinv [ ], Int Len [ ], Int slen, Int S [ ], double Control [ ], double Info [ ] ) ; GLOBAL void AMD_postorder ( Int nn, Int Parent [ ], Int Npiv [ ], Int Fsize [ ], Int Order [ ], Int Child [ ], Int Sibling [ ], Int Stack [ ] ) ; GLOBAL Int AMD_post_tree ( Int root, Int k, Int Child [ ], const Int Sibling [ ], Int Order [ ], Int Stack [ ] #ifndef NDEBUG , Int nn #endif ) ; GLOBAL void AMD_preprocess ( Int n, const Int Ap [ ], const Int Ai [ ], Int Rp [ ], Int Ri [ ], Int W [ ], Int Flag [ ] ) ; /* ------------------------------------------------------------------------- */ /* debugging definitions */ /* ------------------------------------------------------------------------- */ #ifndef NDEBUG /* from assert.h: assert macro */ #include #ifndef EXTERN #define EXTERN extern #endif EXTERN Int AMD_debug ; GLOBAL void AMD_debug_init ( char *s ) ; GLOBAL void AMD_dump ( Int n, Int Pe [ ], Int Iw [ ], Int Len [ ], Int iwlen, Int pfree, Int Nv [ ], Int Next [ ], Int Last [ ], Int Head [ ], Int Elen [ ], Int Degree [ ], Int W [ ], Int nel ) ; #ifdef ASSERT #undef ASSERT #endif /* Use mxAssert if AMD is compiled into a mexFunction */ #ifdef MATLAB_MEX_FILE #define ASSERT(expression) (mxAssert ((expression), "")) #else #define ASSERT(expression) (assert (expression)) #endif #define AMD_DEBUG0(params) { PRINTF (params) ; } #define AMD_DEBUG1(params) { if (AMD_debug >= 1) PRINTF (params) ; } #define AMD_DEBUG2(params) { if (AMD_debug >= 2) PRINTF (params) ; } #define AMD_DEBUG3(params) { if (AMD_debug >= 3) PRINTF (params) ; } #define AMD_DEBUG4(params) { if (AMD_debug >= 4) PRINTF (params) ; } #else /* no debugging */ #define ASSERT(expression) #define AMD_DEBUG0(params) #define AMD_DEBUG1(params) #define AMD_DEBUG2(params) #define AMD_DEBUG3(params) #define AMD_DEBUG4(params) #endif python-igraph-0.8.0/vendor/source/igraph/src/AMD/Include/amd.h0000644000076500000240000004363013524616144024310 0ustar tamasstaff00000000000000/* ========================================================================= */ /* === AMD: approximate minimum degree ordering =========================== */ /* ========================================================================= */ /* ------------------------------------------------------------------------- */ /* AMD Version 2.2, Copyright (c) 2007 by Timothy A. Davis, */ /* Patrick R. Amestoy, and Iain S. Duff. See ../README.txt for License. */ /* email: DrTimothyAldenDavis@gmail.com */ /* ------------------------------------------------------------------------- */ /* AMD finds a symmetric ordering P of a matrix A so that the Cholesky * factorization of P*A*P' has fewer nonzeros and takes less work than the * Cholesky factorization of A. If A is not symmetric, then it performs its * ordering on the matrix A+A'. Two sets of user-callable routines are * provided, one for int integers and the other for SuiteSparse_long integers. * * The method is based on the approximate minimum degree algorithm, discussed * in Amestoy, Davis, and Duff, "An approximate degree ordering algorithm", * SIAM Journal of Matrix Analysis and Applications, vol. 17, no. 4, pp. * 886-905, 1996. This package can perform both the AMD ordering (with * aggressive absorption), and the AMDBAR ordering (without aggressive * absorption) discussed in the above paper. This package differs from the * Fortran codes discussed in the paper: * * (1) it can ignore "dense" rows and columns, leading to faster run times * (2) it computes the ordering of A+A' if A is not symmetric * (3) it is followed by a depth-first post-ordering of the assembly tree * (or supernodal elimination tree) * * For historical reasons, the Fortran versions, amd.f and amdbar.f, have * been left (nearly) unchanged. They compute the identical ordering as * described in the above paper. */ #ifndef AMD_H #define AMD_H /* make it easy for C++ programs to include AMD */ #ifdef __cplusplus extern "C" { #endif /* get the definition of size_t: */ #include #include "SuiteSparse_config.h" int amd_order /* returns AMD_OK, AMD_OK_BUT_JUMBLED, * AMD_INVALID, or AMD_OUT_OF_MEMORY */ ( int n, /* A is n-by-n. n must be >= 0. */ const int Ap [ ], /* column pointers for A, of size n+1 */ const int Ai [ ], /* row indices of A, of size nz = Ap [n] */ int P [ ], /* output permutation, of size n */ double Control [ ], /* input Control settings, of size AMD_CONTROL */ double Info [ ] /* output Info statistics, of size AMD_INFO */ ) ; SuiteSparse_long amd_l_order /* see above for description of arguments */ ( SuiteSparse_long n, const SuiteSparse_long Ap [ ], const SuiteSparse_long Ai [ ], SuiteSparse_long P [ ], double Control [ ], double Info [ ] ) ; /* Input arguments (not modified): * * n: the matrix A is n-by-n. * Ap: an int/SuiteSparse_long array of size n+1, containing column * pointers of A. * Ai: an int/SuiteSparse_long array of size nz, containing the row * indices of A, where nz = Ap [n]. * Control: a double array of size AMD_CONTROL, containing control * parameters. Defaults are used if Control is NULL. * * Output arguments (not defined on input): * * P: an int/SuiteSparse_long array of size n, containing the output * permutation. If row i is the kth pivot row, then P [k] = i. In * MATLAB notation, the reordered matrix is A (P,P). * Info: a double array of size AMD_INFO, containing statistical * information. Ignored if Info is NULL. * * On input, the matrix A is stored in column-oriented form. The row indices * of nonzero entries in column j are stored in Ai [Ap [j] ... Ap [j+1]-1]. * * If the row indices appear in ascending order in each column, and there * are no duplicate entries, then amd_order is slightly more efficient in * terms of time and memory usage. If this condition does not hold, a copy * of the matrix is created (where these conditions do hold), and the copy is * ordered. This feature is new to v2.0 (v1.2 and earlier required this * condition to hold for the input matrix). * * Row indices must be in the range 0 to * n-1. Ap [0] must be zero, and thus nz = Ap [n] is the number of nonzeros * in A. The array Ap is of size n+1, and the array Ai is of size nz = Ap [n]. * The matrix does not need to be symmetric, and the diagonal does not need to * be present (if diagonal entries are present, they are ignored except for * the output statistic Info [AMD_NZDIAG]). The arrays Ai and Ap are not * modified. This form of the Ap and Ai arrays to represent the nonzero * pattern of the matrix A is the same as that used internally by MATLAB. * If you wish to use a more flexible input structure, please see the * umfpack_*_triplet_to_col routines in the UMFPACK package, at * http://www.suitesparse.com. * * Restrictions: n >= 0. Ap [0] = 0. Ap [j] <= Ap [j+1] for all j in the * range 0 to n-1. nz = Ap [n] >= 0. Ai [0..nz-1] must be in the range 0 * to n-1. Finally, Ai, Ap, and P must not be NULL. If any of these * restrictions are not met, AMD returns AMD_INVALID. * * AMD returns: * * AMD_OK if the matrix is valid and sufficient memory can be allocated to * perform the ordering. * * AMD_OUT_OF_MEMORY if not enough memory can be allocated. * * AMD_INVALID if the input arguments n, Ap, Ai are invalid, or if P is * NULL. * * AMD_OK_BUT_JUMBLED if the matrix had unsorted columns, and/or duplicate * entries, but was otherwise valid. * * The AMD routine first forms the pattern of the matrix A+A', and then * computes a fill-reducing ordering, P. If P [k] = i, then row/column i of * the original is the kth pivotal row. In MATLAB notation, the permuted * matrix is A (P,P), except that 0-based indexing is used instead of the * 1-based indexing in MATLAB. * * The Control array is used to set various parameters for AMD. If a NULL * pointer is passed, default values are used. The Control array is not * modified. * * Control [AMD_DENSE]: controls the threshold for "dense" rows/columns. * A dense row/column in A+A' can cause AMD to spend a lot of time in * ordering the matrix. If Control [AMD_DENSE] >= 0, rows/columns * with more than Control [AMD_DENSE] * sqrt (n) entries are ignored * during the ordering, and placed last in the output order. The * default value of Control [AMD_DENSE] is 10. If negative, no * rows/columns are treated as "dense". Rows/columns with 16 or * fewer off-diagonal entries are never considered "dense". * * Control [AMD_AGGRESSIVE]: controls whether or not to use aggressive * absorption, in which a prior element is absorbed into the current * element if is a subset of the current element, even if it is not * adjacent to the current pivot element (refer to Amestoy, Davis, * & Duff, 1996, for more details). The default value is nonzero, * which means to perform aggressive absorption. This nearly always * leads to a better ordering (because the approximate degrees are * more accurate) and a lower execution time. There are cases where * it can lead to a slightly worse ordering, however. To turn it off, * set Control [AMD_AGGRESSIVE] to 0. * * Control [2..4] are not used in the current version, but may be used in * future versions. * * The Info array provides statistics about the ordering on output. If it is * not present, the statistics are not returned. This is not an error * condition. * * Info [AMD_STATUS]: the return value of AMD, either AMD_OK, * AMD_OK_BUT_JUMBLED, AMD_OUT_OF_MEMORY, or AMD_INVALID. * * Info [AMD_N]: n, the size of the input matrix * * Info [AMD_NZ]: the number of nonzeros in A, nz = Ap [n] * * Info [AMD_SYMMETRY]: the symmetry of the matrix A. It is the number * of "matched" off-diagonal entries divided by the total number of * off-diagonal entries. An entry A(i,j) is matched if A(j,i) is also * an entry, for any pair (i,j) for which i != j. In MATLAB notation, * S = spones (A) ; * B = tril (S, -1) + triu (S, 1) ; * symmetry = nnz (B & B') / nnz (B) ; * * Info [AMD_NZDIAG]: the number of entries on the diagonal of A. * * Info [AMD_NZ_A_PLUS_AT]: the number of nonzeros in A+A', excluding the * diagonal. If A is perfectly symmetric (Info [AMD_SYMMETRY] = 1) * with a fully nonzero diagonal, then Info [AMD_NZ_A_PLUS_AT] = nz-n * (the smallest possible value). If A is perfectly unsymmetric * (Info [AMD_SYMMETRY] = 0, for an upper triangular matrix, for * example) with no diagonal, then Info [AMD_NZ_A_PLUS_AT] = 2*nz * (the largest possible value). * * Info [AMD_NDENSE]: the number of "dense" rows/columns of A+A' that were * removed from A prior to ordering. These are placed last in the * output order P. * * Info [AMD_MEMORY]: the amount of memory used by AMD, in bytes. In the * current version, this is 1.2 * Info [AMD_NZ_A_PLUS_AT] + 9*n * times the size of an integer. This is at most 2.4nz + 9n. This * excludes the size of the input arguments Ai, Ap, and P, which have * a total size of nz + 2*n + 1 integers. * * Info [AMD_NCMPA]: the number of garbage collections performed. * * Info [AMD_LNZ]: the number of nonzeros in L (excluding the diagonal). * This is a slight upper bound because mass elimination is combined * with the approximate degree update. It is a rough upper bound if * there are many "dense" rows/columns. The rest of the statistics, * below, are also slight or rough upper bounds, for the same reasons. * The post-ordering of the assembly tree might also not exactly * correspond to a true elimination tree postordering. * * Info [AMD_NDIV]: the number of divide operations for a subsequent LDL' * or LU factorization of the permuted matrix A (P,P). * * Info [AMD_NMULTSUBS_LDL]: the number of multiply-subtract pairs for a * subsequent LDL' factorization of A (P,P). * * Info [AMD_NMULTSUBS_LU]: the number of multiply-subtract pairs for a * subsequent LU factorization of A (P,P), assuming that no numerical * pivoting is required. * * Info [AMD_DMAX]: the maximum number of nonzeros in any column of L, * including the diagonal. * * Info [14..19] are not used in the current version, but may be used in * future versions. */ /* ------------------------------------------------------------------------- */ /* direct interface to AMD */ /* ------------------------------------------------------------------------- */ /* amd_2 is the primary AMD ordering routine. It is not meant to be * user-callable because of its restrictive inputs and because it destroys * the user's input matrix. It does not check its inputs for errors, either. * However, if you can work with these restrictions it can be faster than * amd_order and use less memory (assuming that you can create your own copy * of the matrix for AMD to destroy). Refer to AMD/Source/amd_2.c for a * description of each parameter. */ void amd_2 ( int n, int Pe [ ], int Iw [ ], int Len [ ], int iwlen, int pfree, int Nv [ ], int Next [ ], int Last [ ], int Head [ ], int Elen [ ], int Degree [ ], int W [ ], double Control [ ], double Info [ ] ) ; void amd_l2 ( SuiteSparse_long n, SuiteSparse_long Pe [ ], SuiteSparse_long Iw [ ], SuiteSparse_long Len [ ], SuiteSparse_long iwlen, SuiteSparse_long pfree, SuiteSparse_long Nv [ ], SuiteSparse_long Next [ ], SuiteSparse_long Last [ ], SuiteSparse_long Head [ ], SuiteSparse_long Elen [ ], SuiteSparse_long Degree [ ], SuiteSparse_long W [ ], double Control [ ], double Info [ ] ) ; /* ------------------------------------------------------------------------- */ /* amd_valid */ /* ------------------------------------------------------------------------- */ /* Returns AMD_OK or AMD_OK_BUT_JUMBLED if the matrix is valid as input to * amd_order; the latter is returned if the matrix has unsorted and/or * duplicate row indices in one or more columns. Returns AMD_INVALID if the * matrix cannot be passed to amd_order. For amd_order, the matrix must also * be square. The first two arguments are the number of rows and the number * of columns of the matrix. For its use in AMD, these must both equal n. * * NOTE: this routine returned TRUE/FALSE in v1.2 and earlier. */ int amd_valid ( int n_row, /* # of rows */ int n_col, /* # of columns */ const int Ap [ ], /* column pointers, of size n_col+1 */ const int Ai [ ] /* row indices, of size Ap [n_col] */ ) ; SuiteSparse_long amd_l_valid ( SuiteSparse_long n_row, SuiteSparse_long n_col, const SuiteSparse_long Ap [ ], const SuiteSparse_long Ai [ ] ) ; /* ------------------------------------------------------------------------- */ /* AMD memory manager and printf routines */ /* ------------------------------------------------------------------------- */ /* The user can redefine these to change the malloc, free, and printf routines * that AMD uses. */ #ifndef EXTERN #define EXTERN extern #endif EXTERN void *(*amd_malloc) (size_t) ; /* pointer to malloc */ EXTERN void (*amd_free) (void *) ; /* pointer to free */ EXTERN void *(*amd_realloc) (void *, size_t) ; /* pointer to realloc */ EXTERN void *(*amd_calloc) (size_t, size_t) ; /* pointer to calloc */ EXTERN int (*amd_printf) (const char *, ...) ; /* pointer to printf */ /* ------------------------------------------------------------------------- */ /* AMD Control and Info arrays */ /* ------------------------------------------------------------------------- */ /* amd_defaults: sets the default control settings */ void amd_defaults (double Control [ ]) ; void amd_l_defaults (double Control [ ]) ; /* amd_control: prints the control settings */ void amd_control (double Control [ ]) ; void amd_l_control (double Control [ ]) ; /* amd_info: prints the statistics */ void amd_info (double Info [ ]) ; void amd_l_info (double Info [ ]) ; #define AMD_CONTROL 5 /* size of Control array */ #define AMD_INFO 20 /* size of Info array */ /* contents of Control */ #define AMD_DENSE 0 /* "dense" if degree > Control [0] * sqrt (n) */ #define AMD_AGGRESSIVE 1 /* do aggressive absorption if Control [1] != 0 */ /* default Control settings */ #define AMD_DEFAULT_DENSE 10.0 /* default "dense" degree 10*sqrt(n) */ #define AMD_DEFAULT_AGGRESSIVE 1 /* do aggressive absorption by default */ /* contents of Info */ #define AMD_STATUS 0 /* return value of amd_order and amd_l_order */ #define AMD_N 1 /* A is n-by-n */ #define AMD_NZ 2 /* number of nonzeros in A */ #define AMD_SYMMETRY 3 /* symmetry of pattern (1 is sym., 0 is unsym.) */ #define AMD_NZDIAG 4 /* # of entries on diagonal */ #define AMD_NZ_A_PLUS_AT 5 /* nz in A+A' */ #define AMD_NDENSE 6 /* number of "dense" rows/columns in A */ #define AMD_MEMORY 7 /* amount of memory used by AMD */ #define AMD_NCMPA 8 /* number of garbage collections in AMD */ #define AMD_LNZ 9 /* approx. nz in L, excluding the diagonal */ #define AMD_NDIV 10 /* number of fl. point divides for LU and LDL' */ #define AMD_NMULTSUBS_LDL 11 /* number of fl. point (*,-) pairs for LDL' */ #define AMD_NMULTSUBS_LU 12 /* number of fl. point (*,-) pairs for LU */ #define AMD_DMAX 13 /* max nz. in any column of L, incl. diagonal */ /* ------------------------------------------------------------------------- */ /* return values of AMD */ /* ------------------------------------------------------------------------- */ #define AMD_OK 0 /* success */ #define AMD_OUT_OF_MEMORY -1 /* malloc failed, or problem too large */ #define AMD_INVALID -2 /* input arguments are not valid */ #define AMD_OK_BUT_JUMBLED 1 /* input matrix is OK for amd_order, but * columns were not sorted, and/or duplicate entries were present. AMD had * to do extra work before ordering the matrix. This is a warning, not an * error. */ /* ========================================================================== */ /* === AMD version ========================================================== */ /* ========================================================================== */ /* AMD Version 1.2 and later include the following definitions. * As an example, to test if the version you are using is 1.2 or later: * * #ifdef AMD_VERSION * if (AMD_VERSION >= AMD_VERSION_CODE (1,2)) ... * #endif * * This also works during compile-time: * * #if defined(AMD_VERSION) && (AMD_VERSION >= AMD_VERSION_CODE (1,2)) * printf ("This is version 1.2 or later\n") ; * #else * printf ("This is an early version\n") ; * #endif * * Versions 1.1 and earlier of AMD do not include a #define'd version number. */ #define AMD_DATE "Jun 20, 2012" #define AMD_VERSION_CODE(main,sub) ((main) * 1000 + (sub)) #define AMD_MAIN_VERSION 2 #define AMD_SUB_VERSION 3 #define AMD_SUBSUB_VERSION 1 #define AMD_VERSION AMD_VERSION_CODE(AMD_MAIN_VERSION,AMD_SUB_VERSION) #ifdef __cplusplus } #endif #endif python-igraph-0.8.0/vendor/source/igraph/src/AMD/Source/0000755000076500000240000000000013617375001023242 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/src/AMD/Source/amd_global.c0000644000076500000240000000615513524616144025501 0ustar tamasstaff00000000000000/* ========================================================================= */ /* === amd_global ========================================================== */ /* ========================================================================= */ /* ------------------------------------------------------------------------- */ /* AMD, Copyright (c) Timothy A. Davis, */ /* Patrick R. Amestoy, and Iain S. Duff. See ../README.txt for License. */ /* email: DrTimothyAldenDavis@gmail.com */ /* ------------------------------------------------------------------------- */ #include #ifdef MATLAB_MEX_FILE #include "mex.h" #include "matrix.h" #endif #ifndef NULL #define NULL 0 #endif /* ========================================================================= */ /* === Default AMD memory manager ========================================== */ /* ========================================================================= */ /* The user can redefine these global pointers at run-time to change the memory * manager used by AMD. AMD only uses malloc and free; realloc and calloc are * include for completeness, in case another package wants to use the same * memory manager as AMD. * * If compiling as a MATLAB mexFunction, the default memory manager is mxMalloc. * You can also compile AMD as a standard ANSI-C library and link a mexFunction * against it, and then redefine these pointers at run-time, in your * mexFunction. * * If -DNMALLOC is defined at compile-time, no memory manager is specified at * compile-time. You must then define these functions at run-time, before * calling AMD, for AMD to work properly. */ #ifndef NMALLOC #ifdef MATLAB_MEX_FILE /* MATLAB mexFunction: */ void *(*amd_malloc) (size_t) = mxMalloc ; void (*amd_free) (void *) = mxFree ; void *(*amd_realloc) (void *, size_t) = mxRealloc ; void *(*amd_calloc) (size_t, size_t) = mxCalloc ; #else /* standard ANSI-C: */ void *(*amd_malloc) (size_t) = malloc ; void (*amd_free) (void *) = free ; void *(*amd_realloc) (void *, size_t) = realloc ; void *(*amd_calloc) (size_t, size_t) = calloc ; #endif #else /* no memory manager defined at compile-time; you MUST define one at run-time */ void *(*amd_malloc) (size_t) = NULL ; void (*amd_free) (void *) = NULL ; void *(*amd_realloc) (void *, size_t) = NULL ; void *(*amd_calloc) (size_t, size_t) = NULL ; #endif /* ========================================================================= */ /* === Default AMD printf routine ========================================== */ /* ========================================================================= */ /* The user can redefine this global pointer at run-time to change the printf * routine used by AMD. If NULL, no printing occurs. * * If -DNPRINT is defined at compile-time, stdio.h is not included. Printing * can then be enabled at run-time by setting amd_printf to a non-NULL function. */ #ifndef NPRINT #ifdef MATLAB_MEX_FILE int (*amd_printf) (const char *, ...) = mexPrintf ; #else #include int (*amd_printf) (const char *, ...) = printf ; #endif #else int (*amd_printf) (const char *, ...) = NULL ; #endif python-igraph-0.8.0/vendor/source/igraph/src/AMD/Source/amd_info.c0000644000076500000240000001011513524616144025163 0ustar tamasstaff00000000000000/* ========================================================================= */ /* === AMD_info ============================================================ */ /* ========================================================================= */ /* ------------------------------------------------------------------------- */ /* AMD, Copyright (c) Timothy A. Davis, */ /* Patrick R. Amestoy, and Iain S. Duff. See ../README.txt for License. */ /* email: DrTimothyAldenDavis@gmail.com */ /* ------------------------------------------------------------------------- */ /* User-callable. Prints the output statistics for AMD. See amd.h * for details. If the Info array is not present, nothing is printed. */ #include "amd_internal.h" #define PRI(format,x) { if (x >= 0) { PRINTF ((format, x)) ; }} GLOBAL void AMD_info ( double Info [ ] ) { double n, ndiv, nmultsubs_ldl, nmultsubs_lu, lnz, lnzd ; PRINTF (("\nAMD version %d.%d.%d, %s, results:\n", AMD_MAIN_VERSION, AMD_SUB_VERSION, AMD_SUBSUB_VERSION, AMD_DATE)) ; if (!Info) { return ; } n = Info [AMD_N] ; ndiv = Info [AMD_NDIV] ; nmultsubs_ldl = Info [AMD_NMULTSUBS_LDL] ; nmultsubs_lu = Info [AMD_NMULTSUBS_LU] ; lnz = Info [AMD_LNZ] ; lnzd = (n >= 0 && lnz >= 0) ? (n + lnz) : (-1) ; /* AMD return status */ PRINTF ((" status: ")) ; if (Info [AMD_STATUS] == AMD_OK) { PRINTF (("OK\n")) ; } else if (Info [AMD_STATUS] == AMD_OUT_OF_MEMORY) { PRINTF (("out of memory\n")) ; } else if (Info [AMD_STATUS] == AMD_INVALID) { PRINTF (("invalid matrix\n")) ; } else if (Info [AMD_STATUS] == AMD_OK_BUT_JUMBLED) { PRINTF (("OK, but jumbled\n")) ; } else { PRINTF (("unknown\n")) ; } /* statistics about the input matrix */ PRI (" n, dimension of A: %.20g\n", n); PRI (" nz, number of nonzeros in A: %.20g\n", Info [AMD_NZ]) ; PRI (" symmetry of A: %.4f\n", Info [AMD_SYMMETRY]) ; PRI (" number of nonzeros on diagonal: %.20g\n", Info [AMD_NZDIAG]) ; PRI (" nonzeros in pattern of A+A' (excl. diagonal): %.20g\n", Info [AMD_NZ_A_PLUS_AT]) ; PRI (" # dense rows/columns of A+A': %.20g\n", Info [AMD_NDENSE]) ; /* statistics about AMD's behavior */ PRI (" memory used, in bytes: %.20g\n", Info [AMD_MEMORY]) ; PRI (" # of memory compactions: %.20g\n", Info [AMD_NCMPA]) ; /* statistics about the ordering quality */ PRINTF (("\n" " The following approximate statistics are for a subsequent\n" " factorization of A(P,P) + A(P,P)'. They are slight upper\n" " bounds if there are no dense rows/columns in A+A', and become\n" " looser if dense rows/columns exist.\n\n")) ; PRI (" nonzeros in L (excluding diagonal): %.20g\n", lnz) ; PRI (" nonzeros in L (including diagonal): %.20g\n", lnzd) ; PRI (" # divide operations for LDL' or LU: %.20g\n", ndiv) ; PRI (" # multiply-subtract operations for LDL': %.20g\n", nmultsubs_ldl) ; PRI (" # multiply-subtract operations for LU: %.20g\n", nmultsubs_lu) ; PRI (" max nz. in any column of L (incl. diagonal): %.20g\n", Info [AMD_DMAX]) ; /* total flop counts for various factorizations */ if (n >= 0 && ndiv >= 0 && nmultsubs_ldl >= 0 && nmultsubs_lu >= 0) { PRINTF (("\n" " chol flop count for real A, sqrt counted as 1 flop: %.20g\n" " LDL' flop count for real A: %.20g\n" " LDL' flop count for complex A: %.20g\n" " LU flop count for real A (with no pivoting): %.20g\n" " LU flop count for complex A (with no pivoting): %.20g\n\n", n + ndiv + 2*nmultsubs_ldl, ndiv + 2*nmultsubs_ldl, 9*ndiv + 8*nmultsubs_ldl, ndiv + 2*nmultsubs_lu, 9*ndiv + 8*nmultsubs_lu)) ; } } python-igraph-0.8.0/vendor/source/igraph/src/AMD/Source/amd_preprocess.c0000644000076500000240000000734013524616144026423 0ustar tamasstaff00000000000000/* ========================================================================= */ /* === AMD_preprocess ====================================================== */ /* ========================================================================= */ /* ------------------------------------------------------------------------- */ /* AMD, Copyright (c) Timothy A. Davis, */ /* Patrick R. Amestoy, and Iain S. Duff. See ../README.txt for License. */ /* email: DrTimothyAldenDavis@gmail.com */ /* ------------------------------------------------------------------------- */ /* Sorts, removes duplicate entries, and transposes from the nonzero pattern of * a column-form matrix A, to obtain the matrix R. The input matrix can have * duplicate entries and/or unsorted columns (AMD_valid (n,Ap,Ai) must not be * AMD_INVALID). * * This input condition is NOT checked. This routine is not user-callable. */ #include "amd_internal.h" /* ========================================================================= */ /* === AMD_preprocess ====================================================== */ /* ========================================================================= */ /* AMD_preprocess does not check its input for errors or allocate workspace. * On input, the condition (AMD_valid (n,n,Ap,Ai) != AMD_INVALID) must hold. */ GLOBAL void AMD_preprocess ( Int n, /* input matrix: A is n-by-n */ const Int Ap [ ], /* size n+1 */ const Int Ai [ ], /* size nz = Ap [n] */ /* output matrix R: */ Int Rp [ ], /* size n+1 */ Int Ri [ ], /* size nz (or less, if duplicates present) */ Int W [ ], /* workspace of size n */ Int Flag [ ] /* workspace of size n */ ) { /* --------------------------------------------------------------------- */ /* local variables */ /* --------------------------------------------------------------------- */ Int i, j, p, p2 ; ASSERT (AMD_valid (n, n, Ap, Ai) != AMD_INVALID) ; /* --------------------------------------------------------------------- */ /* count the entries in each row of A (excluding duplicates) */ /* --------------------------------------------------------------------- */ for (i = 0 ; i < n ; i++) { W [i] = 0 ; /* # of nonzeros in row i (excl duplicates) */ Flag [i] = EMPTY ; /* Flag [i] = j if i appears in column j */ } for (j = 0 ; j < n ; j++) { p2 = Ap [j+1] ; for (p = Ap [j] ; p < p2 ; p++) { i = Ai [p] ; if (Flag [i] != j) { /* row index i has not yet appeared in column j */ W [i]++ ; /* one more entry in row i */ Flag [i] = j ; /* flag row index i as appearing in col j*/ } } } /* --------------------------------------------------------------------- */ /* compute the row pointers for R */ /* --------------------------------------------------------------------- */ Rp [0] = 0 ; for (i = 0 ; i < n ; i++) { Rp [i+1] = Rp [i] + W [i] ; } for (i = 0 ; i < n ; i++) { W [i] = Rp [i] ; Flag [i] = EMPTY ; } /* --------------------------------------------------------------------- */ /* construct the row form matrix R */ /* --------------------------------------------------------------------- */ /* R = row form of pattern of A */ for (j = 0 ; j < n ; j++) { p2 = Ap [j+1] ; for (p = Ap [j] ; p < p2 ; p++) { i = Ai [p] ; if (Flag [i] != j) { /* row index i has not yet appeared in column j */ Ri [W [i]++] = j ; /* put col j in row i */ Flag [i] = j ; /* flag row index i as appearing in col j*/ } } } #ifndef NDEBUG ASSERT (AMD_valid (n, n, Rp, Ri) == AMD_OK) ; for (j = 0 ; j < n ; j++) { ASSERT (W [j] == Rp [j+1]) ; } #endif } python-igraph-0.8.0/vendor/source/igraph/src/AMD/Source/amd_defaults.c0000644000076500000240000000234513524616144026045 0ustar tamasstaff00000000000000/* ========================================================================= */ /* === AMD_defaults ======================================================== */ /* ========================================================================= */ /* ------------------------------------------------------------------------- */ /* AMD, Copyright (c) Timothy A. Davis, */ /* Patrick R. Amestoy, and Iain S. Duff. See ../README.txt for License. */ /* email: DrTimothyAldenDavis@gmail.com */ /* ------------------------------------------------------------------------- */ /* User-callable. Sets default control parameters for AMD. See amd.h * for details. */ #include "amd_internal.h" /* ========================================================================= */ /* === AMD defaults ======================================================== */ /* ========================================================================= */ GLOBAL void AMD_defaults ( double Control [ ] ) { Int i ; if (Control != (double *) NULL) { for (i = 0 ; i < AMD_CONTROL ; i++) { Control [i] = 0 ; } Control [AMD_DENSE] = AMD_DEFAULT_DENSE ; Control [AMD_AGGRESSIVE] = AMD_DEFAULT_AGGRESSIVE ; } } python-igraph-0.8.0/vendor/source/igraph/src/AMD/Source/amd_post_tree.c0000644000076500000240000000716713524616144026251 0ustar tamasstaff00000000000000/* ========================================================================= */ /* === AMD_post_tree ======================================================= */ /* ========================================================================= */ /* ------------------------------------------------------------------------- */ /* AMD, Copyright (c) Timothy A. Davis, */ /* Patrick R. Amestoy, and Iain S. Duff. See ../README.txt for License. */ /* email: DrTimothyAldenDavis@gmail.com */ /* ------------------------------------------------------------------------- */ /* Post-ordering of a supernodal elimination tree. */ #include "amd_internal.h" GLOBAL Int AMD_post_tree ( Int root, /* root of the tree */ Int k, /* start numbering at k */ Int Child [ ], /* input argument of size nn, undefined on * output. Child [i] is the head of a link * list of all nodes that are children of node * i in the tree. */ const Int Sibling [ ], /* input argument of size nn, not modified. * If f is a node in the link list of the * children of node i, then Sibling [f] is the * next child of node i. */ Int Order [ ], /* output order, of size nn. Order [i] = k * if node i is the kth node of the reordered * tree. */ Int Stack [ ] /* workspace of size nn */ #ifndef NDEBUG , Int nn /* nodes are in the range 0..nn-1. */ #endif ) { Int f, head, h, i ; #if 0 /* --------------------------------------------------------------------- */ /* recursive version (Stack [ ] is not used): */ /* --------------------------------------------------------------------- */ /* this is simple, but can caouse stack overflow if nn is large */ i = root ; for (f = Child [i] ; f != EMPTY ; f = Sibling [f]) { k = AMD_post_tree (f, k, Child, Sibling, Order, Stack, nn) ; } Order [i] = k++ ; return (k) ; #endif /* --------------------------------------------------------------------- */ /* non-recursive version, using an explicit stack */ /* --------------------------------------------------------------------- */ /* push root on the stack */ head = 0 ; Stack [0] = root ; while (head >= 0) { /* get head of stack */ ASSERT (head < nn) ; i = Stack [head] ; AMD_DEBUG1 (("head of stack "ID" \n", i)) ; ASSERT (i >= 0 && i < nn) ; if (Child [i] != EMPTY) { /* the children of i are not yet ordered */ /* push each child onto the stack in reverse order */ /* so that small ones at the head of the list get popped first */ /* and the biggest one at the end of the list gets popped last */ for (f = Child [i] ; f != EMPTY ; f = Sibling [f]) { head++ ; ASSERT (head < nn) ; ASSERT (f >= 0 && f < nn) ; } h = head ; ASSERT (head < nn) ; for (f = Child [i] ; f != EMPTY ; f = Sibling [f]) { ASSERT (h > 0) ; Stack [h--] = f ; AMD_DEBUG1 (("push "ID" on stack\n", f)) ; ASSERT (f >= 0 && f < nn) ; } ASSERT (Stack [h] == i) ; /* delete child list so that i gets ordered next time we see it */ Child [i] = EMPTY ; } else { /* the children of i (if there were any) are already ordered */ /* remove i from the stack and order it. Front i is kth front */ head-- ; AMD_DEBUG1 (("pop "ID" order "ID"\n", i, k)) ; Order [i] = k++ ; ASSERT (k <= nn) ; } #ifndef NDEBUG AMD_DEBUG1 (("\nStack:")) ; for (h = head ; h >= 0 ; h--) { Int j = Stack [h] ; AMD_DEBUG1 ((" "ID, j)) ; ASSERT (j >= 0 && j < nn) ; } AMD_DEBUG1 (("\n\n")) ; ASSERT (head < nn) ; #endif } return (k) ; } python-igraph-0.8.0/vendor/source/igraph/src/AMD/Source/amdbar.f0000644000076500000240000014607213524616144024654 0ustar tamasstaff00000000000000C----------------------------------------------------------------------- C AMDBAR: approximate minimum degree, without aggressive absorption C----------------------------------------------------------------------- SUBROUTINE AMDBAR $ (N, PE, IW, LEN, IWLEN, PFREE, NV, NEXT, $ LAST, HEAD, ELEN, DEGREE, NCMPA, W) INTEGER N, IWLEN, PFREE, NCMPA, IW (IWLEN), PE (N), $ DEGREE (N), NV (N), NEXT (N), LAST (N), HEAD (N), $ ELEN (N), W (N), LEN (N) C Given a representation of the nonzero pattern of a symmetric matrix, C A, (excluding the diagonal) perform an approximate minimum C (UMFPACK/MA38-style) degree ordering to compute a pivot order C such that the introduction of nonzeros (fill-in) in the Cholesky C factors A = LL^T are kept low. At each step, the pivot C selected is the one with the minimum UMFPACK/MA38-style C upper-bound on the external degree. C C This routine does not do aggresive absorption (as done by AMD). C ********************************************************************** C ***** CAUTION: ARGUMENTS ARE NOT CHECKED FOR ERRORS ON INPUT. ****** C ********************************************************************** C References: C C [1] Timothy A. Davis and Iain Duff, "An unsymmetric-pattern C multifrontal method for sparse LU factorization", SIAM J. C Matrix Analysis and Applications, vol. 18, no. 1, pp. C 140-158. Discusses UMFPACK / MA38, which first introduced C the approximate minimum degree used by this routine. C C [2] Patrick Amestoy, Timothy A. Davis, and Iain S. Duff, "An C approximate degree ordering algorithm," SIAM J. Matrix C Analysis and Applications, vol. 17, no. 4, pp. 886-905, C 1996. Discusses AMD, AMDBAR, and MC47B. C C [3] Alan George and Joseph Liu, "The evolution of the minimum C degree ordering algorithm," SIAM Review, vol. 31, no. 1, C pp. 1-19, 1989. We list below the features mentioned in C that paper that this code includes: C C mass elimination: C Yes. MA27 relied on supervariable detection for mass C elimination. C indistinguishable nodes: C Yes (we call these "supervariables"). This was also in C the MA27 code - although we modified the method of C detecting them (the previous hash was the true degree, C which we no longer keep track of). A supervariable is C a set of rows with identical nonzero pattern. All C variables in a supervariable are eliminated together. C Each supervariable has as its numerical name that of C one of its variables (its principal variable). C quotient graph representation: C Yes. We use the term "element" for the cliques formed C during elimination. This was also in the MA27 code. C The algorithm can operate in place, but it will work C more efficiently if given some "elbow room." C element absorption: C Yes. This was also in the MA27 code. C external degree: C Yes. The MA27 code was based on the true degree. C incomplete degree update and multiple elimination: C No. This was not in MA27, either. Our method of C degree update within MC47B/BD is element-based, not C variable-based. It is thus not well-suited for use C with incomplete degree update or multiple elimination. C----------------------------------------------------------------------- C Authors, and Copyright (C) 1995 by: C Timothy A. Davis, Patrick Amestoy, Iain S. Duff, & John K. Reid. C C Acknowledgements: C This work (and the UMFPACK package) was supported by the C National Science Foundation (ASC-9111263 and DMS-9223088). C The UMFPACK/MA38 approximate degree update algorithm, the C unsymmetric analog which forms the basis of MC47B/BD, was C developed while Tim Davis was supported by CERFACS (Toulouse, C France) in a post-doctoral position. C C Date: September, 1995 C----------------------------------------------------------------------- C----------------------------------------------------------------------- C INPUT ARGUMENTS (unaltered): C----------------------------------------------------------------------- C n: The matrix order. C C Restriction: 1 .le. n .lt. (iovflo/2)-2, where iovflo is C the largest positive integer that your computer can represent. C iwlen: The length of iw (1..iwlen). On input, the matrix is C stored in iw (1..pfree-1). However, iw (1..iwlen) should be C slightly larger than what is required to hold the matrix, at C least iwlen .ge. pfree + n is recommended. Otherwise, C excessive compressions will take place. C *** We do not recommend running this algorithm with *** C *** iwlen .lt. pfree + n. *** C *** Better performance will be obtained if *** C *** iwlen .ge. pfree + n *** C *** or better yet *** C *** iwlen .gt. 1.2 * pfree *** C *** (where pfree is its value on input). *** C The algorithm will not run at all if iwlen .lt. pfree-1. C C Restriction: iwlen .ge. pfree-1 C----------------------------------------------------------------------- C INPUT/OUPUT ARGUMENTS: C----------------------------------------------------------------------- C pe: On input, pe (i) is the index in iw of the start of row i, or C zero if row i has no off-diagonal non-zeros. C C During execution, it is used for both supervariables and C elements: C C * Principal supervariable i: index into iw of the C description of supervariable i. A supervariable C represents one or more rows of the matrix C with identical nonzero pattern. C * Non-principal supervariable i: if i has been absorbed C into another supervariable j, then pe (i) = -j. C That is, j has the same pattern as i. C Note that j might later be absorbed into another C supervariable j2, in which case pe (i) is still -j, C and pe (j) = -j2. C * Unabsorbed element e: the index into iw of the description C of element e, if e has not yet been absorbed by a C subsequent element. Element e is created when C the supervariable of the same name is selected as C the pivot. C * Absorbed element e: if element e is absorbed into element C e2, then pe (e) = -e2. This occurs when the pattern of C e (that is, Le) is found to be a subset of the pattern C of e2 (that is, Le2). If element e is "null" (it has C no nonzeros outside its pivot block), then pe (e) = 0. C C On output, pe holds the assembly tree/forest, which implicitly C represents a pivot order with identical fill-in as the actual C order (via a depth-first search of the tree). C C On output: C If nv (i) .gt. 0, then i represents a node in the assembly tree, C and the parent of i is -pe (i), or zero if i is a root. C If nv (i) = 0, then (i,-pe (i)) represents an edge in a C subtree, the root of which is a node in the assembly tree. C pfree: On input the tail end of the array, iw (pfree..iwlen), C is empty, and the matrix is stored in iw (1..pfree-1). C During execution, additional data is placed in iw, and pfree C is modified so that iw (pfree..iwlen) is always the unused part C of iw. On output, pfree is set equal to the size of iw that C would have been needed for no compressions to occur. If C ncmpa is zero, then pfree (on output) is less than or equal to C iwlen, and the space iw (pfree+1 ... iwlen) was not used. C Otherwise, pfree (on output) is greater than iwlen, and all the C memory in iw was used. C----------------------------------------------------------------------- C INPUT/MODIFIED (undefined on output): C----------------------------------------------------------------------- C len: On input, len (i) holds the number of entries in row i of the C matrix, excluding the diagonal. The contents of len (1..n) C are undefined on output. C iw: On input, iw (1..pfree-1) holds the description of each row i C in the matrix. The matrix must be symmetric, and both upper C and lower triangular parts must be present. The diagonal must C not be present. Row i is held as follows: C C len (i): the length of the row i data structure C iw (pe (i) ... pe (i) + len (i) - 1): C the list of column indices for nonzeros C in row i (simple supervariables), excluding C the diagonal. All supervariables start with C one row/column each (supervariable i is just C row i). C if len (i) is zero on input, then pe (i) is ignored C on input. C C Note that the rows need not be in any particular order, C and there may be empty space between the rows. C C During execution, the supervariable i experiences fill-in. C This is represented by placing in i a list of the elements C that cause fill-in in supervariable i: C C len (i): the length of supervariable i C iw (pe (i) ... pe (i) + elen (i) - 1): C the list of elements that contain i. This list C is kept short by removing absorbed elements. C iw (pe (i) + elen (i) ... pe (i) + len (i) - 1): C the list of supervariables in i. This list C is kept short by removing nonprincipal C variables, and any entry j that is also C contained in at least one of the elements C (j in Le) in the list for i (e in row i). C C When supervariable i is selected as pivot, we create an C element e of the same name (e=i): C C len (e): the length of element e C iw (pe (e) ... pe (e) + len (e) - 1): C the list of supervariables in element e. C C An element represents the fill-in that occurs when supervariable C i is selected as pivot (which represents the selection of row i C and all non-principal variables whose principal variable is i). C We use the term Le to denote the set of all supervariables C in element e. Absorbed supervariables and elements are pruned C from these lists when computationally convenient. C C CAUTION: THE INPUT MATRIX IS OVERWRITTEN DURING COMPUTATION. C The contents of iw are undefined on output. C----------------------------------------------------------------------- C OUTPUT (need not be set on input): C----------------------------------------------------------------------- C nv: During execution, abs (nv (i)) is equal to the number of rows C that are represented by the principal supervariable i. If i is C a nonprincipal variable, then nv (i) = 0. Initially, C nv (i) = 1 for all i. nv (i) .lt. 0 signifies that i is a C principal variable in the pattern Lme of the current pivot C element me. On output, nv (e) holds the true degree of element C e at the time it was created (including the diagonal part). C ncmpa: The number of times iw was compressed. If this is C excessive, then the execution took longer than what could have C been. To reduce ncmpa, try increasing iwlen to be 10% or 20% C larger than the value of pfree on input (or at least C iwlen .ge. pfree + n). The fastest performance will be C obtained when ncmpa is returned as zero. If iwlen is set to C the value returned by pfree on *output*, then no compressions C will occur. C elen: See the description of iw above. At the start of execution, C elen (i) is set to zero. During execution, elen (i) is the C number of elements in the list for supervariable i. When e C becomes an element, elen (e) = -nel is set, where nel is the C current step of factorization. elen (i) = 0 is done when i C becomes nonprincipal. C C For variables, elen (i) .ge. 0 holds until just before the C permutation vectors are computed. For elements, C elen (e) .lt. 0 holds. C C On output elen (1..n) holds the inverse permutation (the same C as the 'INVP' argument in Sparspak). That is, if k = elen (i), C then row i is the kth pivot row. Row i of A appears as the C (elen(i))-th row in the permuted matrix, PAP^T. C last: In a degree list, last (i) is the supervariable preceding i, C or zero if i is the head of the list. In a hash bucket, C last (i) is the hash key for i. last (head (hash)) is also C used as the head of a hash bucket if head (hash) contains a C degree list (see head, below). C C On output, last (1..n) holds the permutation (the same as the C 'PERM' argument in Sparspak). That is, if i = last (k), then C row i is the kth pivot row. Row last (k) of A is the k-th row C in the permuted matrix, PAP^T. C----------------------------------------------------------------------- C LOCAL (not input or output - used only during execution): C----------------------------------------------------------------------- C degree: If i is a supervariable, then degree (i) holds the C current approximation of the external degree of row i (an upper C bound). The external degree is the number of nonzeros in row i, C minus abs (nv (i)) (the diagonal part). The bound is equal to C the external degree if elen (i) is less than or equal to two. C C We also use the term "external degree" for elements e to refer C to |Le \ Lme|. If e is an element, then degree (e) holds |Le|, C which is the degree of the off-diagonal part of the element e C (not including the diagonal part). C head: head is used for degree lists. head (deg) is the first C supervariable in a degree list (all supervariables i in a C degree list deg have the same approximate degree, namely, C deg = degree (i)). If the list deg is empty then C head (deg) = 0. C C During supervariable detection head (hash) also serves as a C pointer to a hash bucket. C If head (hash) .gt. 0, there is a degree list of degree hash. C The hash bucket head pointer is last (head (hash)). C If head (hash) = 0, then the degree list and hash bucket are C both empty. C If head (hash) .lt. 0, then the degree list is empty, and C -head (hash) is the head of the hash bucket. C After supervariable detection is complete, all hash buckets C are empty, and the (last (head (hash)) = 0) condition is C restored for the non-empty degree lists. C next: next (i) is the supervariable following i in a link list, or C zero if i is the last in the list. Used for two kinds of C lists: degree lists and hash buckets (a supervariable can be C in only one kind of list at a time). C w: The flag array w determines the status of elements and C variables, and the external degree of elements. C C for elements: C if w (e) = 0, then the element e is absorbed C if w (e) .ge. wflg, then w (e) - wflg is the size of C the set |Le \ Lme|, in terms of nonzeros (the C sum of abs (nv (i)) for each principal variable i that C is both in the pattern of element e and NOT in the C pattern of the current pivot element, me). C if wflg .gt. w (e) .gt. 0, then e is not absorbed and has C not yet been seen in the scan of the element lists in C the computation of |Le\Lme| in loop 150 below. C C for variables: C during supervariable detection, if w (j) .ne. wflg then j is C not in the pattern of variable i C C The w array is initialized by setting w (i) = 1 for all i, C and by setting wflg = 2. It is reinitialized if wflg becomes C too large (to ensure that wflg+n does not cause integer C overflow). C----------------------------------------------------------------------- C LOCAL INTEGERS: C----------------------------------------------------------------------- INTEGER DEG, DEGME, DMAX, E, ELENME, ELN, HASH, HMOD, I, $ ILAST, INEXT, J, JLAST, JNEXT, K, KNT1, KNT2, KNT3, $ LENJ, LN, MAXMEM, ME, MEM, MINDEG, NEL, NEWMEM, $ NLEFT, NVI, NVJ, NVPIV, SLENME, WE, WFLG, WNVI, X C deg: the degree of a variable or element C degme: size, |Lme|, of the current element, me (= degree (me)) C dext: external degree, |Le \ Lme|, of some element e C dmax: largest |Le| seen so far C e: an element C elenme: the length, elen (me), of element list of pivotal var. C eln: the length, elen (...), of an element list C hash: the computed value of the hash function C hmod: the hash function is computed modulo hmod = max (1,n-1) C i: a supervariable C ilast: the entry in a link list preceding i C inext: the entry in a link list following i C j: a supervariable C jlast: the entry in a link list preceding j C jnext: the entry in a link list, or path, following j C k: the pivot order of an element or variable C knt1: loop counter used during element construction C knt2: loop counter used during element construction C knt3: loop counter used during compression C lenj: len (j) C ln: length of a supervariable list C maxmem: amount of memory needed for no compressions C me: current supervariable being eliminated, and the C current element created by eliminating that C supervariable C mem: memory in use assuming no compressions have occurred C mindeg: current minimum degree C nel: number of pivots selected so far C newmem: amount of new memory needed for current pivot element C nleft: n - nel, the number of nonpivotal rows/columns remaining C nvi: the number of variables in a supervariable i (= nv (i)) C nvj: the number of variables in a supervariable j (= nv (j)) C nvpiv: number of pivots in current element C slenme: number of variables in variable list of pivotal variable C we: w (e) C wflg: used for flagging the w array. See description of iw. C wnvi: wflg - nv (i) C x: either a supervariable or an element C----------------------------------------------------------------------- C LOCAL POINTERS: C----------------------------------------------------------------------- INTEGER P, P1, P2, P3, PDST, PEND, PJ, PME, PME1, PME2, PN, PSRC C Any parameter (pe (...) or pfree) or local variable C starting with "p" (for Pointer) is an index into iw, C and all indices into iw use variables starting with C "p." The only exception to this rule is the iwlen C input argument. C p: pointer into lots of things C p1: pe (i) for some variable i (start of element list) C p2: pe (i) + elen (i) - 1 for some var. i (end of el. list) C p3: index of first supervariable in clean list C pdst: destination pointer, for compression C pend: end of memory to compress C pj: pointer into an element or variable C pme: pointer into the current element (pme1...pme2) C pme1: the current element, me, is stored in iw (pme1...pme2) C pme2: the end of the current element C pn: pointer into a "clean" variable, also used to compress C psrc: source pointer, for compression C----------------------------------------------------------------------- C FUNCTIONS CALLED: C----------------------------------------------------------------------- INTRINSIC MAX, MIN, MOD C======================================================================= C INITIALIZATIONS C======================================================================= WFLG = 2 MINDEG = 1 NCMPA = 0 NEL = 0 HMOD = MAX (1, N-1) DMAX = 0 MEM = PFREE - 1 MAXMEM = MEM ME = 0 DO 10 I = 1, N LAST (I) = 0 HEAD (I) = 0 NV (I) = 1 W (I) = 1 ELEN (I) = 0 DEGREE (I) = LEN (I) 10 CONTINUE C ---------------------------------------------------------------- C initialize degree lists and eliminate rows with no off-diag. nz. C ---------------------------------------------------------------- DO 20 I = 1, N DEG = DEGREE (I) IF (DEG .GT. 0) THEN C ---------------------------------------------------------- C place i in the degree list corresponding to its degree C ---------------------------------------------------------- INEXT = HEAD (DEG) IF (INEXT .NE. 0) LAST (INEXT) = I NEXT (I) = INEXT HEAD (DEG) = I ELSE C ---------------------------------------------------------- C we have a variable that can be eliminated at once because C there is no off-diagonal non-zero in its row. C ---------------------------------------------------------- NEL = NEL + 1 ELEN (I) = -NEL PE (I) = 0 W (I) = 0 ENDIF 20 CONTINUE C======================================================================= C WHILE (selecting pivots) DO C======================================================================= 30 CONTINUE IF (NEL .LT. N) THEN C======================================================================= C GET PIVOT OF MINIMUM DEGREE C======================================================================= C ------------------------------------------------------------- C find next supervariable for elimination C ------------------------------------------------------------- DO 40 DEG = MINDEG, N ME = HEAD (DEG) IF (ME .GT. 0) GOTO 50 40 CONTINUE 50 CONTINUE MINDEG = DEG C ------------------------------------------------------------- C remove chosen variable from link list C ------------------------------------------------------------- INEXT = NEXT (ME) IF (INEXT .NE. 0) LAST (INEXT) = 0 HEAD (DEG) = INEXT C ------------------------------------------------------------- C me represents the elimination of pivots nel+1 to nel+nv(me). C place me itself as the first in this set. It will be moved C to the nel+nv(me) position when the permutation vectors are C computed. C ------------------------------------------------------------- ELENME = ELEN (ME) ELEN (ME) = - (NEL + 1) NVPIV = NV (ME) NEL = NEL + NVPIV C======================================================================= C CONSTRUCT NEW ELEMENT C======================================================================= C ------------------------------------------------------------- C At this point, me is the pivotal supervariable. It will be C converted into the current element. Scan list of the C pivotal supervariable, me, setting tree pointers and C constructing new list of supervariables for the new element, C me. p is a pointer to the current position in the old list. C ------------------------------------------------------------- C flag the variable "me" as being in Lme by negating nv (me) NV (ME) = -NVPIV DEGME = 0 IF (ELENME .EQ. 0) THEN C ---------------------------------------------------------- C construct the new element in place C ---------------------------------------------------------- PME1 = PE (ME) PME2 = PME1 - 1 DO 60 P = PME1, PME1 + LEN (ME) - 1 I = IW (P) NVI = NV (I) IF (NVI .GT. 0) THEN C ---------------------------------------------------- C i is a principal variable not yet placed in Lme. C store i in new list C ---------------------------------------------------- DEGME = DEGME + NVI C flag i as being in Lme by negating nv (i) NV (I) = -NVI PME2 = PME2 + 1 IW (PME2) = I C ---------------------------------------------------- C remove variable i from degree list. C ---------------------------------------------------- ILAST = LAST (I) INEXT = NEXT (I) IF (INEXT .NE. 0) LAST (INEXT) = ILAST IF (ILAST .NE. 0) THEN NEXT (ILAST) = INEXT ELSE C i is at the head of the degree list HEAD (DEGREE (I)) = INEXT ENDIF ENDIF 60 CONTINUE C this element takes no new memory in iw: NEWMEM = 0 ELSE C ---------------------------------------------------------- C construct the new element in empty space, iw (pfree ...) C ---------------------------------------------------------- P = PE (ME) PME1 = PFREE SLENME = LEN (ME) - ELENME DO 120 KNT1 = 1, ELENME + 1 IF (KNT1 .GT. ELENME) THEN C search the supervariables in me. E = ME PJ = P LN = SLENME ELSE C search the elements in me. E = IW (P) P = P + 1 PJ = PE (E) LN = LEN (E) ENDIF C ------------------------------------------------------- C search for different supervariables and add them to the C new list, compressing when necessary. this loop is C executed once for each element in the list and once for C all the supervariables in the list. C ------------------------------------------------------- DO 110 KNT2 = 1, LN I = IW (PJ) PJ = PJ + 1 NVI = NV (I) IF (NVI .GT. 0) THEN C ------------------------------------------------- C compress iw, if necessary C ------------------------------------------------- IF (PFREE .GT. IWLEN) THEN C prepare for compressing iw by adjusting C pointers and lengths so that the lists being C searched in the inner and outer loops contain C only the remaining entries. PE (ME) = P LEN (ME) = LEN (ME) - KNT1 IF (LEN (ME) .EQ. 0) THEN C nothing left of supervariable me PE (ME) = 0 ENDIF PE (E) = PJ LEN (E) = LN - KNT2 IF (LEN (E) .EQ. 0) THEN C nothing left of element e PE (E) = 0 ENDIF NCMPA = NCMPA + 1 C store first item in pe C set first entry to -item DO 70 J = 1, N PN = PE (J) IF (PN .GT. 0) THEN PE (J) = IW (PN) IW (PN) = -J ENDIF 70 CONTINUE C psrc/pdst point to source/destination PDST = 1 PSRC = 1 PEND = PME1 - 1 C while loop: 80 CONTINUE IF (PSRC .LE. PEND) THEN C search for next negative entry J = -IW (PSRC) PSRC = PSRC + 1 IF (J .GT. 0) THEN IW (PDST) = PE (J) PE (J) = PDST PDST = PDST + 1 C copy from source to destination LENJ = LEN (J) DO 90 KNT3 = 0, LENJ - 2 IW (PDST + KNT3) = IW (PSRC + KNT3) 90 CONTINUE PDST = PDST + LENJ - 1 PSRC = PSRC + LENJ - 1 ENDIF GOTO 80 ENDIF C move the new partially-constructed element P1 = PDST DO 100 PSRC = PME1, PFREE - 1 IW (PDST) = IW (PSRC) PDST = PDST + 1 100 CONTINUE PME1 = P1 PFREE = PDST PJ = PE (E) P = PE (ME) ENDIF C ------------------------------------------------- C i is a principal variable not yet placed in Lme C store i in new list C ------------------------------------------------- DEGME = DEGME + NVI C flag i as being in Lme by negating nv (i) NV (I) = -NVI IW (PFREE) = I PFREE = PFREE + 1 C ------------------------------------------------- C remove variable i from degree link list C ------------------------------------------------- ILAST = LAST (I) INEXT = NEXT (I) IF (INEXT .NE. 0) LAST (INEXT) = ILAST IF (ILAST .NE. 0) THEN NEXT (ILAST) = INEXT ELSE C i is at the head of the degree list HEAD (DEGREE (I)) = INEXT ENDIF ENDIF 110 CONTINUE IF (E .NE. ME) THEN C set tree pointer and flag to indicate element e is C absorbed into new element me (the parent of e is me) PE (E) = -ME W (E) = 0 ENDIF 120 CONTINUE PME2 = PFREE - 1 C this element takes newmem new memory in iw (possibly zero) NEWMEM = PFREE - PME1 MEM = MEM + NEWMEM MAXMEM = MAX (MAXMEM, MEM) ENDIF C ------------------------------------------------------------- C me has now been converted into an element in iw (pme1..pme2) C ------------------------------------------------------------- C degme holds the external degree of new element DEGREE (ME) = DEGME PE (ME) = PME1 LEN (ME) = PME2 - PME1 + 1 C ------------------------------------------------------------- C make sure that wflg is not too large. With the current C value of wflg, wflg+n must not cause integer overflow C ------------------------------------------------------------- IF (WFLG + N .LE. WFLG) THEN DO 130 X = 1, N IF (W (X) .NE. 0) W (X) = 1 130 CONTINUE WFLG = 2 ENDIF C======================================================================= C COMPUTE (w (e) - wflg) = |Le\Lme| FOR ALL ELEMENTS C======================================================================= C ------------------------------------------------------------- C Scan 1: compute the external degrees of previous elements C with respect to the current element. That is: C (w (e) - wflg) = |Le \ Lme| C for each element e that appears in any supervariable in Lme. C The notation Le refers to the pattern (list of C supervariables) of a previous element e, where e is not yet C absorbed, stored in iw (pe (e) + 1 ... pe (e) + iw (pe (e))). C The notation Lme refers to the pattern of the current element C (stored in iw (pme1..pme2)). If (w (e) - wflg) becomes C zero, then the element e will be absorbed in scan 2. C ------------------------------------------------------------- DO 150 PME = PME1, PME2 I = IW (PME) ELN = ELEN (I) IF (ELN .GT. 0) THEN C note that nv (i) has been negated to denote i in Lme: NVI = -NV (I) WNVI = WFLG - NVI DO 140 P = PE (I), PE (I) + ELN - 1 E = IW (P) WE = W (E) IF (WE .GE. WFLG) THEN C unabsorbed element e has been seen in this loop WE = WE - NVI ELSE IF (WE .NE. 0) THEN C e is an unabsorbed element C this is the first we have seen e in all of Scan 1 WE = DEGREE (E) + WNVI ENDIF W (E) = WE 140 CONTINUE ENDIF 150 CONTINUE C======================================================================= C DEGREE UPDATE AND ELEMENT ABSORPTION C======================================================================= C ------------------------------------------------------------- C Scan 2: for each i in Lme, sum up the degree of Lme (which C is degme), plus the sum of the external degrees of each Le C for the elements e appearing within i, plus the C supervariables in i. Place i in hash list. C ------------------------------------------------------------- DO 180 PME = PME1, PME2 I = IW (PME) P1 = PE (I) P2 = P1 + ELEN (I) - 1 PN = P1 HASH = 0 DEG = 0 C ---------------------------------------------------------- C scan the element list associated with supervariable i C ---------------------------------------------------------- C UMFPACK/MA38-style approximate degree: DO 160 P = P1, P2 E = IW (P) WE = W (E) IF (WE .NE. 0) THEN C e is an unabsorbed element DEG = DEG + WE - WFLG IW (PN) = E PN = PN + 1 HASH = HASH + E ENDIF 160 CONTINUE C count the number of elements in i (including me): ELEN (I) = PN - P1 + 1 C ---------------------------------------------------------- C scan the supervariables in the list associated with i C ---------------------------------------------------------- P3 = PN DO 170 P = P2 + 1, P1 + LEN (I) - 1 J = IW (P) NVJ = NV (J) IF (NVJ .GT. 0) THEN C j is unabsorbed, and not in Lme. C add to degree and add to new list DEG = DEG + NVJ IW (PN) = J PN = PN + 1 HASH = HASH + J ENDIF 170 CONTINUE C ---------------------------------------------------------- C update the degree and check for mass elimination C ---------------------------------------------------------- IF (ELEN (I) .EQ. 1 .AND. P3 .EQ. PN) THEN C ------------------------------------------------------- C mass elimination C ------------------------------------------------------- C There is nothing left of this node except for an C edge to the current pivot element. elen (i) is 1, C and there are no variables adjacent to node i. C Absorb i into the current pivot element, me. PE (I) = -ME NVI = -NV (I) DEGME = DEGME - NVI NVPIV = NVPIV + NVI NEL = NEL + NVI NV (I) = 0 ELEN (I) = 0 ELSE C ------------------------------------------------------- C update the upper-bound degree of i C ------------------------------------------------------- C the following degree does not yet include the size C of the current element, which is added later: DEGREE (I) = MIN (DEGREE (I), DEG) C ------------------------------------------------------- C add me to the list for i C ------------------------------------------------------- C move first supervariable to end of list IW (PN) = IW (P3) C move first element to end of element part of list IW (P3) = IW (P1) C add new element to front of list. IW (P1) = ME C store the new length of the list in len (i) LEN (I) = PN - P1 + 1 C ------------------------------------------------------- C place in hash bucket. Save hash key of i in last (i). C ------------------------------------------------------- HASH = MOD (HASH, HMOD) + 1 J = HEAD (HASH) IF (J .LE. 0) THEN C the degree list is empty, hash head is -j NEXT (I) = -J HEAD (HASH) = -I ELSE C degree list is not empty C use last (head (hash)) as hash head NEXT (I) = LAST (J) LAST (J) = I ENDIF LAST (I) = HASH ENDIF 180 CONTINUE DEGREE (ME) = DEGME C ------------------------------------------------------------- C Clear the counter array, w (...), by incrementing wflg. C ------------------------------------------------------------- DMAX = MAX (DMAX, DEGME) WFLG = WFLG + DMAX C make sure that wflg+n does not cause integer overflow IF (WFLG + N .LE. WFLG) THEN DO 190 X = 1, N IF (W (X) .NE. 0) W (X) = 1 190 CONTINUE WFLG = 2 ENDIF C at this point, w (1..n) .lt. wflg holds C======================================================================= C SUPERVARIABLE DETECTION C======================================================================= DO 250 PME = PME1, PME2 I = IW (PME) IF (NV (I) .LT. 0) THEN C i is a principal variable in Lme C ------------------------------------------------------- C examine all hash buckets with 2 or more variables. We C do this by examing all unique hash keys for super- C variables in the pattern Lme of the current element, me C ------------------------------------------------------- HASH = LAST (I) C let i = head of hash bucket, and empty the hash bucket J = HEAD (HASH) IF (J .EQ. 0) GOTO 250 IF (J .LT. 0) THEN C degree list is empty I = -J HEAD (HASH) = 0 ELSE C degree list is not empty, restore last () of head I = LAST (J) LAST (J) = 0 ENDIF IF (I .EQ. 0) GOTO 250 C while loop: 200 CONTINUE IF (NEXT (I) .NE. 0) THEN C ---------------------------------------------------- C this bucket has one or more variables following i. C scan all of them to see if i can absorb any entries C that follow i in hash bucket. Scatter i into w. C ---------------------------------------------------- LN = LEN (I) ELN = ELEN (I) C do not flag the first element in the list (me) DO 210 P = PE (I) + 1, PE (I) + LN - 1 W (IW (P)) = WFLG 210 CONTINUE C ---------------------------------------------------- C scan every other entry j following i in bucket C ---------------------------------------------------- JLAST = I J = NEXT (I) C while loop: 220 CONTINUE IF (J .NE. 0) THEN C ------------------------------------------------- C check if j and i have identical nonzero pattern C ------------------------------------------------- IF (LEN (J) .NE. LN) THEN C i and j do not have same size data structure GOTO 240 ENDIF IF (ELEN (J) .NE. ELN) THEN C i and j do not have same number of adjacent el GOTO 240 ENDIF C do not flag the first element in the list (me) DO 230 P = PE (J) + 1, PE (J) + LN - 1 IF (W (IW (P)) .NE. WFLG) THEN C an entry (iw(p)) is in j but not in i GOTO 240 ENDIF 230 CONTINUE C ------------------------------------------------- C found it! j can be absorbed into i C ------------------------------------------------- PE (J) = -I C both nv (i) and nv (j) are negated since they C are in Lme, and the absolute values of each C are the number of variables in i and j: NV (I) = NV (I) + NV (J) NV (J) = 0 ELEN (J) = 0 C delete j from hash bucket J = NEXT (J) NEXT (JLAST) = J GOTO 220 C ------------------------------------------------- 240 CONTINUE C j cannot be absorbed into i C ------------------------------------------------- JLAST = J J = NEXT (J) GOTO 220 ENDIF C ---------------------------------------------------- C no more variables can be absorbed into i C go to next i in bucket and clear flag array C ---------------------------------------------------- WFLG = WFLG + 1 I = NEXT (I) IF (I .NE. 0) GOTO 200 ENDIF ENDIF 250 CONTINUE C======================================================================= C RESTORE DEGREE LISTS AND REMOVE NONPRINCIPAL SUPERVAR. FROM ELEMENT C======================================================================= P = PME1 NLEFT = N - NEL DO 260 PME = PME1, PME2 I = IW (PME) NVI = -NV (I) IF (NVI .GT. 0) THEN C i is a principal variable in Lme C restore nv (i) to signify that i is principal NV (I) = NVI C ------------------------------------------------------- C compute the external degree (add size of current elem) C ------------------------------------------------------- DEG = MAX (1, MIN (DEGREE (I) + DEGME-NVI, NLEFT-NVI)) C ------------------------------------------------------- C place the supervariable at the head of the degree list C ------------------------------------------------------- INEXT = HEAD (DEG) IF (INEXT .NE. 0) LAST (INEXT) = I NEXT (I) = INEXT LAST (I) = 0 HEAD (DEG) = I C ------------------------------------------------------- C save the new degree, and find the minimum degree C ------------------------------------------------------- MINDEG = MIN (MINDEG, DEG) DEGREE (I) = DEG C ------------------------------------------------------- C place the supervariable in the element pattern C ------------------------------------------------------- IW (P) = I P = P + 1 ENDIF 260 CONTINUE C======================================================================= C FINALIZE THE NEW ELEMENT C======================================================================= NV (ME) = NVPIV + DEGME C nv (me) is now the degree of pivot (including diagonal part) C save the length of the list for the new element me LEN (ME) = P - PME1 IF (LEN (ME) .EQ. 0) THEN C there is nothing left of the current pivot element PE (ME) = 0 W (ME) = 0 ENDIF IF (NEWMEM .NE. 0) THEN C element was not constructed in place: deallocate part C of it (final size is less than or equal to newmem, C since newly nonprincipal variables have been removed). PFREE = P MEM = MEM - NEWMEM + LEN (ME) ENDIF C======================================================================= C END WHILE (selecting pivots) GOTO 30 ENDIF C======================================================================= C======================================================================= C COMPUTE THE PERMUTATION VECTORS C======================================================================= C ---------------------------------------------------------------- C The time taken by the following code is O(n). At this C point, elen (e) = -k has been done for all elements e, C and elen (i) = 0 has been done for all nonprincipal C variables i. At this point, there are no principal C supervariables left, and all elements are absorbed. C ---------------------------------------------------------------- C ---------------------------------------------------------------- C compute the ordering of unordered nonprincipal variables C ---------------------------------------------------------------- DO 290 I = 1, N IF (ELEN (I) .EQ. 0) THEN C ---------------------------------------------------------- C i is an un-ordered row. Traverse the tree from i until C reaching an element, e. The element, e, was the C principal supervariable of i and all nodes in the path C from i to when e was selected as pivot. C ---------------------------------------------------------- J = -PE (I) C while (j is a variable) do: 270 CONTINUE IF (ELEN (J) .GE. 0) THEN J = -PE (J) GOTO 270 ENDIF E = J C ---------------------------------------------------------- C get the current pivot ordering of e C ---------------------------------------------------------- K = -ELEN (E) C ---------------------------------------------------------- C traverse the path again from i to e, and compress the C path (all nodes point to e). Path compression allows C this code to compute in O(n) time. Order the unordered C nodes in the path, and place the element e at the end. C ---------------------------------------------------------- J = I C while (j is a variable) do: 280 CONTINUE IF (ELEN (J) .GE. 0) THEN JNEXT = -PE (J) PE (J) = -E IF (ELEN (J) .EQ. 0) THEN C j is an unordered row ELEN (J) = K K = K + 1 ENDIF J = JNEXT GOTO 280 ENDIF C leave elen (e) negative, so we know it is an element ELEN (E) = -K ENDIF 290 CONTINUE C ---------------------------------------------------------------- C reset the inverse permutation (elen (1..n)) to be positive, C and compute the permutation (last (1..n)). C ---------------------------------------------------------------- DO 300 I = 1, N K = ABS (ELEN (I)) LAST (K) = I ELEN (I) = K 300 CONTINUE C======================================================================= C RETURN THE MEMORY USAGE IN IW C======================================================================= C If maxmem is less than or equal to iwlen, then no compressions C occurred, and iw (maxmem+1 ... iwlen) was unused. Otherwise C compressions did occur, and iwlen would have had to have been C greater than or equal to maxmem for no compressions to occur. C Return the value of maxmem in the pfree argument. PFREE = MAXMEM RETURN END python-igraph-0.8.0/vendor/source/igraph/src/AMD/Source/amd_1.c0000644000076500000240000001311613524616144024374 0ustar tamasstaff00000000000000/* ========================================================================= */ /* === AMD_1 =============================================================== */ /* ========================================================================= */ /* ------------------------------------------------------------------------- */ /* AMD, Copyright (c) Timothy A. Davis, */ /* Patrick R. Amestoy, and Iain S. Duff. See ../README.txt for License. */ /* email: DrTimothyAldenDavis@gmail.com */ /* ------------------------------------------------------------------------- */ /* AMD_1: Construct A+A' for a sparse matrix A and perform the AMD ordering. * * The n-by-n sparse matrix A can be unsymmetric. It is stored in MATLAB-style * compressed-column form, with sorted row indices in each column, and no * duplicate entries. Diagonal entries may be present, but they are ignored. * Row indices of column j of A are stored in Ai [Ap [j] ... Ap [j+1]-1]. * Ap [0] must be zero, and nz = Ap [n] is the number of entries in A. The * size of the matrix, n, must be greater than or equal to zero. * * This routine must be preceded by a call to AMD_aat, which computes the * number of entries in each row/column in A+A', excluding the diagonal. * Len [j], on input, is the number of entries in row/column j of A+A'. This * routine constructs the matrix A+A' and then calls AMD_2. No error checking * is performed (this was done in AMD_valid). */ #include "amd_internal.h" GLOBAL void AMD_1 ( Int n, /* n > 0 */ const Int Ap [ ], /* input of size n+1, not modified */ const Int Ai [ ], /* input of size nz = Ap [n], not modified */ Int P [ ], /* size n output permutation */ Int Pinv [ ], /* size n output inverse permutation */ Int Len [ ], /* size n input, undefined on output */ Int slen, /* slen >= sum (Len [0..n-1]) + 7n, * ideally slen = 1.2 * sum (Len) + 8n */ Int S [ ], /* size slen workspace */ double Control [ ], /* input array of size AMD_CONTROL */ double Info [ ] /* output array of size AMD_INFO */ ) { Int i, j, k, p, pfree, iwlen, pj, p1, p2, pj2, *Iw, *Pe, *Nv, *Head, *Elen, *Degree, *s, *W, *Sp, *Tp ; /* --------------------------------------------------------------------- */ /* construct the matrix for AMD_2 */ /* --------------------------------------------------------------------- */ ASSERT (n > 0) ; iwlen = slen - 6*n ; s = S ; Pe = s ; s += n ; Nv = s ; s += n ; Head = s ; s += n ; Elen = s ; s += n ; Degree = s ; s += n ; W = s ; s += n ; Iw = s ; s += iwlen ; ASSERT (AMD_valid (n, n, Ap, Ai) == AMD_OK) ; /* construct the pointers for A+A' */ Sp = Nv ; /* use Nv and W as workspace for Sp and Tp [ */ Tp = W ; pfree = 0 ; for (j = 0 ; j < n ; j++) { Pe [j] = pfree ; Sp [j] = pfree ; pfree += Len [j] ; } /* Note that this restriction on iwlen is slightly more restrictive than * what is strictly required in AMD_2. AMD_2 can operate with no elbow * room at all, but it will be very slow. For better performance, at * least size-n elbow room is enforced. */ ASSERT (iwlen >= pfree + n) ; #ifndef NDEBUG for (p = 0 ; p < iwlen ; p++) Iw [p] = EMPTY ; #endif for (k = 0 ; k < n ; k++) { AMD_DEBUG1 (("Construct row/column k= "ID" of A+A'\n", k)) ; p1 = Ap [k] ; p2 = Ap [k+1] ; /* construct A+A' */ for (p = p1 ; p < p2 ; ) { /* scan the upper triangular part of A */ j = Ai [p] ; ASSERT (j >= 0 && j < n) ; if (j < k) { /* entry A (j,k) in the strictly upper triangular part */ ASSERT (Sp [j] < (j == n-1 ? pfree : Pe [j+1])) ; ASSERT (Sp [k] < (k == n-1 ? pfree : Pe [k+1])) ; Iw [Sp [j]++] = k ; Iw [Sp [k]++] = j ; p++ ; } else if (j == k) { /* skip the diagonal */ p++ ; break ; } else /* j > k */ { /* first entry below the diagonal */ break ; } /* scan lower triangular part of A, in column j until reaching * row k. Start where last scan left off. */ ASSERT (Ap [j] <= Tp [j] && Tp [j] <= Ap [j+1]) ; pj2 = Ap [j+1] ; for (pj = Tp [j] ; pj < pj2 ; ) { i = Ai [pj] ; ASSERT (i >= 0 && i < n) ; if (i < k) { /* A (i,j) is only in the lower part, not in upper */ ASSERT (Sp [i] < (i == n-1 ? pfree : Pe [i+1])) ; ASSERT (Sp [j] < (j == n-1 ? pfree : Pe [j+1])) ; Iw [Sp [i]++] = j ; Iw [Sp [j]++] = i ; pj++ ; } else if (i == k) { /* entry A (k,j) in lower part and A (j,k) in upper */ pj++ ; break ; } else /* i > k */ { /* consider this entry later, when k advances to i */ break ; } } Tp [j] = pj ; } Tp [k] = p ; } /* clean up, for remaining mismatched entries */ for (j = 0 ; j < n ; j++) { for (pj = Tp [j] ; pj < Ap [j+1] ; pj++) { i = Ai [pj] ; ASSERT (i >= 0 && i < n) ; /* A (i,j) is only in the lower part, not in upper */ ASSERT (Sp [i] < (i == n-1 ? pfree : Pe [i+1])) ; ASSERT (Sp [j] < (j == n-1 ? pfree : Pe [j+1])) ; Iw [Sp [i]++] = j ; Iw [Sp [j]++] = i ; } } #ifndef NDEBUG for (j = 0 ; j < n-1 ; j++) ASSERT (Sp [j] == Pe [j+1]) ; ASSERT (Sp [n-1] == pfree) ; #endif /* Tp and Sp no longer needed ] */ /* --------------------------------------------------------------------- */ /* order the matrix */ /* --------------------------------------------------------------------- */ AMD_2 (n, Pe, Iw, Len, iwlen, pfree, Nv, Pinv, P, Head, Elen, Degree, W, Control, Info) ; } python-igraph-0.8.0/vendor/source/igraph/src/AMD/Source/amd_postorder.c0000644000076500000240000001260513524616144026257 0ustar tamasstaff00000000000000/* ========================================================================= */ /* === AMD_postorder ======================================================= */ /* ========================================================================= */ /* ------------------------------------------------------------------------- */ /* AMD, Copyright (c) Timothy A. Davis, */ /* Patrick R. Amestoy, and Iain S. Duff. See ../README.txt for License. */ /* email: DrTimothyAldenDavis@gmail.com */ /* ------------------------------------------------------------------------- */ /* Perform a postordering (via depth-first search) of an assembly tree. */ #include "amd_internal.h" GLOBAL void AMD_postorder ( /* inputs, not modified on output: */ Int nn, /* nodes are in the range 0..nn-1 */ Int Parent [ ], /* Parent [j] is the parent of j, or EMPTY if root */ Int Nv [ ], /* Nv [j] > 0 number of pivots represented by node j, * or zero if j is not a node. */ Int Fsize [ ], /* Fsize [j]: size of node j */ /* output, not defined on input: */ Int Order [ ], /* output post-order */ /* workspaces of size nn: */ Int Child [ ], Int Sibling [ ], Int Stack [ ] ) { Int i, j, k, parent, frsize, f, fprev, maxfrsize, bigfprev, bigf, fnext ; for (j = 0 ; j < nn ; j++) { Child [j] = EMPTY ; Sibling [j] = EMPTY ; } /* --------------------------------------------------------------------- */ /* place the children in link lists - bigger elements tend to be last */ /* --------------------------------------------------------------------- */ for (j = nn-1 ; j >= 0 ; j--) { if (Nv [j] > 0) { /* this is an element */ parent = Parent [j] ; if (parent != EMPTY) { /* place the element in link list of the children its parent */ /* bigger elements will tend to be at the end of the list */ Sibling [j] = Child [parent] ; Child [parent] = j ; } } } #ifndef NDEBUG { Int nels, ff, nchild ; AMD_DEBUG1 (("\n\n================================ AMD_postorder:\n")); nels = 0 ; for (j = 0 ; j < nn ; j++) { if (Nv [j] > 0) { AMD_DEBUG1 (( ""ID" : nels "ID" npiv "ID" size "ID " parent "ID" maxfr "ID"\n", j, nels, Nv [j], Fsize [j], Parent [j], Fsize [j])) ; /* this is an element */ /* dump the link list of children */ nchild = 0 ; AMD_DEBUG1 ((" Children: ")) ; for (ff = Child [j] ; ff != EMPTY ; ff = Sibling [ff]) { AMD_DEBUG1 ((ID" ", ff)) ; ASSERT (Parent [ff] == j) ; nchild++ ; ASSERT (nchild < nn) ; } AMD_DEBUG1 (("\n")) ; parent = Parent [j] ; if (parent != EMPTY) { ASSERT (Nv [parent] > 0) ; } nels++ ; } } } AMD_DEBUG1 (("\n\nGo through the children of each node, and put\n" "the biggest child last in each list:\n")) ; #endif /* --------------------------------------------------------------------- */ /* place the largest child last in the list of children for each node */ /* --------------------------------------------------------------------- */ for (i = 0 ; i < nn ; i++) { if (Nv [i] > 0 && Child [i] != EMPTY) { #ifndef NDEBUG Int nchild ; AMD_DEBUG1 (("Before partial sort, element "ID"\n", i)) ; nchild = 0 ; for (f = Child [i] ; f != EMPTY ; f = Sibling [f]) { ASSERT (f >= 0 && f < nn) ; AMD_DEBUG1 ((" f: "ID" size: "ID"\n", f, Fsize [f])) ; nchild++ ; ASSERT (nchild <= nn) ; } #endif /* find the biggest element in the child list */ fprev = EMPTY ; maxfrsize = EMPTY ; bigfprev = EMPTY ; bigf = EMPTY ; for (f = Child [i] ; f != EMPTY ; f = Sibling [f]) { ASSERT (f >= 0 && f < nn) ; frsize = Fsize [f] ; if (frsize >= maxfrsize) { /* this is the biggest seen so far */ maxfrsize = frsize ; bigfprev = fprev ; bigf = f ; } fprev = f ; } ASSERT (bigf != EMPTY) ; fnext = Sibling [bigf] ; AMD_DEBUG1 (("bigf "ID" maxfrsize "ID" bigfprev "ID" fnext "ID " fprev " ID"\n", bigf, maxfrsize, bigfprev, fnext, fprev)) ; if (fnext != EMPTY) { /* if fnext is EMPTY then bigf is already at the end of list */ if (bigfprev == EMPTY) { /* delete bigf from the element of the list */ Child [i] = fnext ; } else { /* delete bigf from the middle of the list */ Sibling [bigfprev] = fnext ; } /* put bigf at the end of the list */ Sibling [bigf] = EMPTY ; ASSERT (Child [i] != EMPTY) ; ASSERT (fprev != bigf) ; ASSERT (fprev != EMPTY) ; Sibling [fprev] = bigf ; } #ifndef NDEBUG AMD_DEBUG1 (("After partial sort, element "ID"\n", i)) ; for (f = Child [i] ; f != EMPTY ; f = Sibling [f]) { ASSERT (f >= 0 && f < nn) ; AMD_DEBUG1 ((" "ID" "ID"\n", f, Fsize [f])) ; ASSERT (Nv [f] > 0) ; nchild-- ; } ASSERT (nchild == 0) ; #endif } } /* --------------------------------------------------------------------- */ /* postorder the assembly tree */ /* --------------------------------------------------------------------- */ for (i = 0 ; i < nn ; i++) { Order [i] = EMPTY ; } k = 0 ; for (i = 0 ; i < nn ; i++) { if (Parent [i] == EMPTY && Nv [i] > 0) { AMD_DEBUG1 (("Root of assembly tree "ID"\n", i)) ; k = AMD_post_tree (i, k, Child, Sibling, Order, Stack #ifndef NDEBUG , nn #endif ) ; } } } python-igraph-0.8.0/vendor/source/igraph/src/AMD/Source/amd_valid.c0000644000076500000240000000564413524616144025342 0ustar tamasstaff00000000000000/* ========================================================================= */ /* === AMD_valid =========================================================== */ /* ========================================================================= */ /* ------------------------------------------------------------------------- */ /* AMD, Copyright (c) Timothy A. Davis, */ /* Patrick R. Amestoy, and Iain S. Duff. See ../README.txt for License. */ /* email: DrTimothyAldenDavis@gmail.com */ /* ------------------------------------------------------------------------- */ /* Check if a column-form matrix is valid or not. The matrix A is * n_row-by-n_col. The row indices of entries in column j are in * Ai [Ap [j] ... Ap [j+1]-1]. Required conditions are: * * n_row >= 0 * n_col >= 0 * nz = Ap [n_col] >= 0 number of entries in the matrix * Ap [0] == 0 * Ap [j] <= Ap [j+1] for all j in the range 0 to n_col. * Ai [0 ... nz-1] must be in the range 0 to n_row-1. * * If any of the above conditions hold, AMD_INVALID is returned. If the * following condition holds, AMD_OK_BUT_JUMBLED is returned (a warning, * not an error): * * row indices in Ai [Ap [j] ... Ap [j+1]-1] are not sorted in ascending * order, and/or duplicate entries exist. * * Otherwise, AMD_OK is returned. * * In v1.2 and earlier, this function returned TRUE if the matrix was valid * (now returns AMD_OK), or FALSE otherwise (now returns AMD_INVALID or * AMD_OK_BUT_JUMBLED). */ #include "amd_internal.h" GLOBAL Int AMD_valid ( /* inputs, not modified on output: */ Int n_row, /* A is n_row-by-n_col */ Int n_col, const Int Ap [ ], /* column pointers of A, of size n_col+1 */ const Int Ai [ ] /* row indices of A, of size nz = Ap [n_col] */ ) { Int nz, j, p1, p2, ilast, i, p, result = AMD_OK ; if (n_row < 0 || n_col < 0 || Ap == NULL || Ai == NULL) { return (AMD_INVALID) ; } nz = Ap [n_col] ; if (Ap [0] != 0 || nz < 0) { /* column pointers must start at Ap [0] = 0, and Ap [n] must be >= 0 */ AMD_DEBUG0 (("column 0 pointer bad or nz < 0\n")) ; return (AMD_INVALID) ; } for (j = 0 ; j < n_col ; j++) { p1 = Ap [j] ; p2 = Ap [j+1] ; AMD_DEBUG2 (("\nColumn: "ID" p1: "ID" p2: "ID"\n", j, p1, p2)) ; if (p1 > p2) { /* column pointers must be ascending */ AMD_DEBUG0 (("column "ID" pointer bad\n", j)) ; return (AMD_INVALID) ; } ilast = EMPTY ; for (p = p1 ; p < p2 ; p++) { i = Ai [p] ; AMD_DEBUG3 (("row: "ID"\n", i)) ; if (i < 0 || i >= n_row) { /* row index out of range */ AMD_DEBUG0 (("index out of range, col "ID" row "ID"\n", j, i)); return (AMD_INVALID) ; } if (i <= ilast) { /* row index unsorted, or duplicate entry present */ AMD_DEBUG1 (("index unsorted/dupl col "ID" row "ID"\n", j, i)); result = AMD_OK_BUT_JUMBLED ; } ilast = i ; } } return (result) ; } python-igraph-0.8.0/vendor/source/igraph/src/AMD/Source/amd_2.c0000644000076500000240000017647113524616144024413 0ustar tamasstaff00000000000000/* ========================================================================= */ /* === AMD_2 =============================================================== */ /* ========================================================================= */ /* ------------------------------------------------------------------------- */ /* AMD, Copyright (c) Timothy A. Davis, */ /* Patrick R. Amestoy, and Iain S. Duff. See ../README.txt for License. */ /* email: DrTimothyAldenDavis@gmail.com */ /* ------------------------------------------------------------------------- */ /* AMD_2: performs the AMD ordering on a symmetric sparse matrix A, followed * by a postordering (via depth-first search) of the assembly tree using the * AMD_postorder routine. */ #include "amd_internal.h" /* ========================================================================= */ /* === clear_flag ========================================================== */ /* ========================================================================= */ static Int clear_flag (Int wflg, Int wbig, Int W [ ], Int n) { Int x ; if (wflg < 2 || wflg >= wbig) { for (x = 0 ; x < n ; x++) { if (W [x] != 0) W [x] = 1 ; } wflg = 2 ; } /* at this point, W [0..n-1] < wflg holds */ return (wflg) ; } /* ========================================================================= */ /* === AMD_2 =============================================================== */ /* ========================================================================= */ GLOBAL void AMD_2 ( Int n, /* A is n-by-n, where n > 0 */ Int Pe [ ], /* Pe [0..n-1]: index in Iw of row i on input */ Int Iw [ ], /* workspace of size iwlen. Iw [0..pfree-1] * holds the matrix on input */ Int Len [ ], /* Len [0..n-1]: length for row/column i on input */ Int iwlen, /* length of Iw. iwlen >= pfree + n */ Int pfree, /* Iw [pfree ... iwlen-1] is empty on input */ /* 7 size-n workspaces, not defined on input: */ Int Nv [ ], /* the size of each supernode on output */ Int Next [ ], /* the output inverse permutation */ Int Last [ ], /* the output permutation */ Int Head [ ], Int Elen [ ], /* the size columns of L for each supernode */ Int Degree [ ], Int W [ ], /* control parameters and output statistics */ double Control [ ], /* array of size AMD_CONTROL */ double Info [ ] /* array of size AMD_INFO */ ) { /* * Given a representation of the nonzero pattern of a symmetric matrix, A, * (excluding the diagonal) perform an approximate minimum (UMFPACK/MA38-style) * degree ordering to compute a pivot order such that the introduction of * nonzeros (fill-in) in the Cholesky factors A = LL' is kept low. At each * step, the pivot selected is the one with the minimum UMFAPACK/MA38-style * upper-bound on the external degree. This routine can optionally perform * aggresive absorption (as done by MC47B in the Harwell Subroutine * Library). * * The approximate degree algorithm implemented here is the symmetric analog of * the degree update algorithm in MA38 and UMFPACK (the Unsymmetric-pattern * MultiFrontal PACKage, both by Davis and Duff). The routine is based on the * MA27 minimum degree ordering algorithm by Iain Duff and John Reid. * * This routine is a translation of the original AMDBAR and MC47B routines, * in Fortran, with the following modifications: * * (1) dense rows/columns are removed prior to ordering the matrix, and placed * last in the output order. The presence of a dense row/column can * increase the ordering time by up to O(n^2), unless they are removed * prior to ordering. * * (2) the minimum degree ordering is followed by a postordering (depth-first * search) of the assembly tree. Note that mass elimination (discussed * below) combined with the approximate degree update can lead to the mass * elimination of nodes with lower exact degree than the current pivot * element. No additional fill-in is caused in the representation of the * Schur complement. The mass-eliminated nodes merge with the current * pivot element. They are ordered prior to the current pivot element. * Because they can have lower exact degree than the current element, the * merger of two or more of these nodes in the current pivot element can * lead to a single element that is not a "fundamental supernode". The * diagonal block can have zeros in it. Thus, the assembly tree used here * is not guaranteed to be the precise supernodal elemination tree (with * "funadmental" supernodes), and the postordering performed by this * routine is not guaranteed to be a precise postordering of the * elimination tree. * * (3) input parameters are added, to control aggressive absorption and the * detection of "dense" rows/columns of A. * * (4) additional statistical information is returned, such as the number of * nonzeros in L, and the flop counts for subsequent LDL' and LU * factorizations. These are slight upper bounds, because of the mass * elimination issue discussed above. * * (5) additional routines are added to interface this routine to MATLAB * to provide a simple C-callable user-interface, to check inputs for * errors, compute the symmetry of the pattern of A and the number of * nonzeros in each row/column of A+A', to compute the pattern of A+A', * to perform the assembly tree postordering, and to provide debugging * ouput. Many of these functions are also provided by the Fortran * Harwell Subroutine Library routine MC47A. * * (6) both int and SuiteSparse_long versions are provided. In the * descriptions below and integer is and int or SuiteSparse_long depending * on which version is being used. ********************************************************************** ***** CAUTION: ARGUMENTS ARE NOT CHECKED FOR ERRORS ON INPUT. ****** ********************************************************************** ** If you want error checking, a more versatile input format, and a ** ** simpler user interface, use amd_order or amd_l_order instead. ** ** This routine is not meant to be user-callable. ** ********************************************************************** * ---------------------------------------------------------------------------- * References: * ---------------------------------------------------------------------------- * * [1] Timothy A. Davis and Iain Duff, "An unsymmetric-pattern multifrontal * method for sparse LU factorization", SIAM J. Matrix Analysis and * Applications, vol. 18, no. 1, pp. 140-158. Discusses UMFPACK / MA38, * which first introduced the approximate minimum degree used by this * routine. * * [2] Patrick Amestoy, Timothy A. Davis, and Iain S. Duff, "An approximate * minimum degree ordering algorithm," SIAM J. Matrix Analysis and * Applications, vol. 17, no. 4, pp. 886-905, 1996. Discusses AMDBAR and * MC47B, which are the Fortran versions of this routine. * * [3] Alan George and Joseph Liu, "The evolution of the minimum degree * ordering algorithm," SIAM Review, vol. 31, no. 1, pp. 1-19, 1989. * We list below the features mentioned in that paper that this code * includes: * * mass elimination: * Yes. MA27 relied on supervariable detection for mass elimination. * * indistinguishable nodes: * Yes (we call these "supervariables"). This was also in the MA27 * code - although we modified the method of detecting them (the * previous hash was the true degree, which we no longer keep track * of). A supervariable is a set of rows with identical nonzero * pattern. All variables in a supervariable are eliminated together. * Each supervariable has as its numerical name that of one of its * variables (its principal variable). * * quotient graph representation: * Yes. We use the term "element" for the cliques formed during * elimination. This was also in the MA27 code. The algorithm can * operate in place, but it will work more efficiently if given some * "elbow room." * * element absorption: * Yes. This was also in the MA27 code. * * external degree: * Yes. The MA27 code was based on the true degree. * * incomplete degree update and multiple elimination: * No. This was not in MA27, either. Our method of degree update * within MC47B is element-based, not variable-based. It is thus * not well-suited for use with incomplete degree update or multiple * elimination. * * Authors, and Copyright (C) 2004 by: * Timothy A. Davis, Patrick Amestoy, Iain S. Duff, John K. Reid. * * Acknowledgements: This work (and the UMFPACK package) was supported by the * National Science Foundation (ASC-9111263, DMS-9223088, and CCR-0203270). * The UMFPACK/MA38 approximate degree update algorithm, the unsymmetric analog * which forms the basis of AMD, was developed while Tim Davis was supported by * CERFACS (Toulouse, France) in a post-doctoral position. This C version, and * the etree postorder, were written while Tim Davis was on sabbatical at * Stanford University and Lawrence Berkeley National Laboratory. * ---------------------------------------------------------------------------- * INPUT ARGUMENTS (unaltered): * ---------------------------------------------------------------------------- * n: The matrix order. Restriction: n >= 1. * * iwlen: The size of the Iw array. On input, the matrix is stored in * Iw [0..pfree-1]. However, Iw [0..iwlen-1] should be slightly larger * than what is required to hold the matrix, at least iwlen >= pfree + n. * Otherwise, excessive compressions will take place. The recommended * value of iwlen is 1.2 * pfree + n, which is the value used in the * user-callable interface to this routine (amd_order.c). The algorithm * will not run at all if iwlen < pfree. Restriction: iwlen >= pfree + n. * Note that this is slightly more restrictive than the actual minimum * (iwlen >= pfree), but AMD_2 will be very slow with no elbow room. * Thus, this routine enforces a bare minimum elbow room of size n. * * pfree: On input the tail end of the array, Iw [pfree..iwlen-1], is empty, * and the matrix is stored in Iw [0..pfree-1]. During execution, * additional data is placed in Iw, and pfree is modified so that * Iw [pfree..iwlen-1] is always the unused part of Iw. * * Control: A double array of size AMD_CONTROL containing input parameters * that affect how the ordering is computed. If NULL, then default * settings are used. * * Control [AMD_DENSE] is used to determine whether or not a given input * row is "dense". A row is "dense" if the number of entries in the row * exceeds Control [AMD_DENSE] times sqrt (n), except that rows with 16 or * fewer entries are never considered "dense". To turn off the detection * of dense rows, set Control [AMD_DENSE] to a negative number, or to a * number larger than sqrt (n). The default value of Control [AMD_DENSE] * is AMD_DEFAULT_DENSE, which is defined in amd.h as 10. * * Control [AMD_AGGRESSIVE] is used to determine whether or not aggressive * absorption is to be performed. If nonzero, then aggressive absorption * is performed (this is the default). * ---------------------------------------------------------------------------- * INPUT/OUPUT ARGUMENTS: * ---------------------------------------------------------------------------- * * Pe: An integer array of size n. On input, Pe [i] is the index in Iw of * the start of row i. Pe [i] is ignored if row i has no off-diagonal * entries. Thus Pe [i] must be in the range 0 to pfree-1 for non-empty * rows. * * During execution, it is used for both supervariables and elements: * * Principal supervariable i: index into Iw of the description of * supervariable i. A supervariable represents one or more rows of * the matrix with identical nonzero pattern. In this case, * Pe [i] >= 0. * * Non-principal supervariable i: if i has been absorbed into another * supervariable j, then Pe [i] = FLIP (j), where FLIP (j) is defined * as (-(j)-2). Row j has the same pattern as row i. Note that j * might later be absorbed into another supervariable j2, in which * case Pe [i] is still FLIP (j), and Pe [j] = FLIP (j2) which is * < EMPTY, where EMPTY is defined as (-1) in amd_internal.h. * * Unabsorbed element e: the index into Iw of the description of element * e, if e has not yet been absorbed by a subsequent element. Element * e is created when the supervariable of the same name is selected as * the pivot. In this case, Pe [i] >= 0. * * Absorbed element e: if element e is absorbed into element e2, then * Pe [e] = FLIP (e2). This occurs when the pattern of e (which we * refer to as Le) is found to be a subset of the pattern of e2 (that * is, Le2). In this case, Pe [i] < EMPTY. If element e is "null" * (it has no nonzeros outside its pivot block), then Pe [e] = EMPTY, * and e is the root of an assembly subtree (or the whole tree if * there is just one such root). * * Dense variable i: if i is "dense", then Pe [i] = EMPTY. * * On output, Pe holds the assembly tree/forest, which implicitly * represents a pivot order with identical fill-in as the actual order * (via a depth-first search of the tree), as follows. If Nv [i] > 0, * then i represents a node in the assembly tree, and the parent of i is * Pe [i], or EMPTY if i is a root. If Nv [i] = 0, then (i, Pe [i]) * represents an edge in a subtree, the root of which is a node in the * assembly tree. Note that i refers to a row/column in the original * matrix, not the permuted matrix. * * Info: A double array of size AMD_INFO. If present, (that is, not NULL), * then statistics about the ordering are returned in the Info array. * See amd.h for a description. * ---------------------------------------------------------------------------- * INPUT/MODIFIED (undefined on output): * ---------------------------------------------------------------------------- * * Len: An integer array of size n. On input, Len [i] holds the number of * entries in row i of the matrix, excluding the diagonal. The contents * of Len are undefined on output. * * Iw: An integer array of size iwlen. On input, Iw [0..pfree-1] holds the * description of each row i in the matrix. The matrix must be symmetric, * and both upper and lower triangular parts must be present. The * diagonal must not be present. Row i is held as follows: * * Len [i]: the length of the row i data structure in the Iw array. * Iw [Pe [i] ... Pe [i] + Len [i] - 1]: * the list of column indices for nonzeros in row i (simple * supervariables), excluding the diagonal. All supervariables * start with one row/column each (supervariable i is just row i). * If Len [i] is zero on input, then Pe [i] is ignored on input. * * Note that the rows need not be in any particular order, and there * may be empty space between the rows. * * During execution, the supervariable i experiences fill-in. This is * represented by placing in i a list of the elements that cause fill-in * in supervariable i: * * Len [i]: the length of supervariable i in the Iw array. * Iw [Pe [i] ... Pe [i] + Elen [i] - 1]: * the list of elements that contain i. This list is kept short * by removing absorbed elements. * Iw [Pe [i] + Elen [i] ... Pe [i] + Len [i] - 1]: * the list of supervariables in i. This list is kept short by * removing nonprincipal variables, and any entry j that is also * contained in at least one of the elements (j in Le) in the list * for i (e in row i). * * When supervariable i is selected as pivot, we create an element e of * the same name (e=i): * * Len [e]: the length of element e in the Iw array. * Iw [Pe [e] ... Pe [e] + Len [e] - 1]: * the list of supervariables in element e. * * An element represents the fill-in that occurs when supervariable i is * selected as pivot (which represents the selection of row i and all * non-principal variables whose principal variable is i). We use the * term Le to denote the set of all supervariables in element e. Absorbed * supervariables and elements are pruned from these lists when * computationally convenient. * * CAUTION: THE INPUT MATRIX IS OVERWRITTEN DURING COMPUTATION. * The contents of Iw are undefined on output. * ---------------------------------------------------------------------------- * OUTPUT (need not be set on input): * ---------------------------------------------------------------------------- * * Nv: An integer array of size n. During execution, ABS (Nv [i]) is equal to * the number of rows that are represented by the principal supervariable * i. If i is a nonprincipal or dense variable, then Nv [i] = 0. * Initially, Nv [i] = 1 for all i. Nv [i] < 0 signifies that i is a * principal variable in the pattern Lme of the current pivot element me. * After element me is constructed, Nv [i] is set back to a positive * value. * * On output, Nv [i] holds the number of pivots represented by super * row/column i of the original matrix, or Nv [i] = 0 for non-principal * rows/columns. Note that i refers to a row/column in the original * matrix, not the permuted matrix. * * Elen: An integer array of size n. See the description of Iw above. At the * start of execution, Elen [i] is set to zero for all rows i. During * execution, Elen [i] is the number of elements in the list for * supervariable i. When e becomes an element, Elen [e] = FLIP (esize) is * set, where esize is the size of the element (the number of pivots, plus * the number of nonpivotal entries). Thus Elen [e] < EMPTY. * Elen (i) = EMPTY set when variable i becomes nonprincipal. * * For variables, Elen (i) >= EMPTY holds until just before the * postordering and permutation vectors are computed. For elements, * Elen [e] < EMPTY holds. * * On output, Elen [i] is the degree of the row/column in the Cholesky * factorization of the permuted matrix, corresponding to the original row * i, if i is a super row/column. It is equal to EMPTY if i is * non-principal. Note that i refers to a row/column in the original * matrix, not the permuted matrix. * * Note that the contents of Elen on output differ from the Fortran * version (Elen holds the inverse permutation in the Fortran version, * which is instead returned in the Next array in this C version, * described below). * * Last: In a degree list, Last [i] is the supervariable preceding i, or EMPTY * if i is the head of the list. In a hash bucket, Last [i] is the hash * key for i. * * Last [Head [hash]] is also used as the head of a hash bucket if * Head [hash] contains a degree list (see the description of Head, * below). * * On output, Last [0..n-1] holds the permutation. That is, if * i = Last [k], then row i is the kth pivot row (where k ranges from 0 to * n-1). Row Last [k] of A is the kth row in the permuted matrix, PAP'. * * Next: Next [i] is the supervariable following i in a link list, or EMPTY if * i is the last in the list. Used for two kinds of lists: degree lists * and hash buckets (a supervariable can be in only one kind of list at a * time). * * On output Next [0..n-1] holds the inverse permutation. That is, if * k = Next [i], then row i is the kth pivot row. Row i of A appears as * the (Next[i])-th row in the permuted matrix, PAP'. * * Note that the contents of Next on output differ from the Fortran * version (Next is undefined on output in the Fortran version). * ---------------------------------------------------------------------------- * LOCAL WORKSPACE (not input or output - used only during execution): * ---------------------------------------------------------------------------- * * Degree: An integer array of size n. If i is a supervariable, then * Degree [i] holds the current approximation of the external degree of * row i (an upper bound). The external degree is the number of nonzeros * in row i, minus ABS (Nv [i]), the diagonal part. The bound is equal to * the exact external degree if Elen [i] is less than or equal to two. * * We also use the term "external degree" for elements e to refer to * |Le \ Lme|. If e is an element, then Degree [e] is |Le|, which is the * degree of the off-diagonal part of the element e (not including the * diagonal part). * * Head: An integer array of size n. Head is used for degree lists. * Head [deg] is the first supervariable in a degree list. All * supervariables i in a degree list Head [deg] have the same approximate * degree, namely, deg = Degree [i]. If the list Head [deg] is empty then * Head [deg] = EMPTY. * * During supervariable detection Head [hash] also serves as a pointer to * a hash bucket. If Head [hash] >= 0, there is a degree list of degree * hash. The hash bucket head pointer is Last [Head [hash]]. If * Head [hash] = EMPTY, then the degree list and hash bucket are both * empty. If Head [hash] < EMPTY, then the degree list is empty, and * FLIP (Head [hash]) is the head of the hash bucket. After supervariable * detection is complete, all hash buckets are empty, and the * (Last [Head [hash]] = EMPTY) condition is restored for the non-empty * degree lists. * * W: An integer array of size n. The flag array W determines the status of * elements and variables, and the external degree of elements. * * for elements: * if W [e] = 0, then the element e is absorbed. * if W [e] >= wflg, then W [e] - wflg is the size of the set * |Le \ Lme|, in terms of nonzeros (the sum of ABS (Nv [i]) for * each principal variable i that is both in the pattern of * element e and NOT in the pattern of the current pivot element, * me). * if wflg > W [e] > 0, then e is not absorbed and has not yet been * seen in the scan of the element lists in the computation of * |Le\Lme| in Scan 1 below. * * for variables: * during supervariable detection, if W [j] != wflg then j is * not in the pattern of variable i. * * The W array is initialized by setting W [i] = 1 for all i, and by * setting wflg = 2. It is reinitialized if wflg becomes too large (to * ensure that wflg+n does not cause integer overflow). * ---------------------------------------------------------------------------- * LOCAL INTEGERS: * ---------------------------------------------------------------------------- */ Int deg, degme, dext, lemax, e, elenme, eln, i, ilast, inext, j, jlast, jnext, k, knt1, knt2, knt3, lenj, ln, me, mindeg, nel, nleft, nvi, nvj, nvpiv, slenme, wbig, we, wflg, wnvi, ok, ndense, ncmpa, dense, aggressive ; unsigned Int hash ; /* unsigned, so that hash % n is well defined.*/ /* * deg: the degree of a variable or element * degme: size, |Lme|, of the current element, me (= Degree [me]) * dext: external degree, |Le \ Lme|, of some element e * lemax: largest |Le| seen so far (called dmax in Fortran version) * e: an element * elenme: the length, Elen [me], of element list of pivotal variable * eln: the length, Elen [...], of an element list * hash: the computed value of the hash function * i: a supervariable * ilast: the entry in a link list preceding i * inext: the entry in a link list following i * j: a supervariable * jlast: the entry in a link list preceding j * jnext: the entry in a link list, or path, following j * k: the pivot order of an element or variable * knt1: loop counter used during element construction * knt2: loop counter used during element construction * knt3: loop counter used during compression * lenj: Len [j] * ln: length of a supervariable list * me: current supervariable being eliminated, and the current * element created by eliminating that supervariable * mindeg: current minimum degree * nel: number of pivots selected so far * nleft: n - nel, the number of nonpivotal rows/columns remaining * nvi: the number of variables in a supervariable i (= Nv [i]) * nvj: the number of variables in a supervariable j (= Nv [j]) * nvpiv: number of pivots in current element * slenme: number of variables in variable list of pivotal variable * wbig: = (INT_MAX - n) for the int version, (SuiteSparse_long_max - n) * for the SuiteSparse_long version. wflg is not allowed to * be >= wbig. * we: W [e] * wflg: used for flagging the W array. See description of Iw. * wnvi: wflg - Nv [i] * x: either a supervariable or an element * * ok: true if supervariable j can be absorbed into i * ndense: number of "dense" rows/columns * dense: rows/columns with initial degree > dense are considered "dense" * aggressive: true if aggressive absorption is being performed * ncmpa: number of garbage collections * ---------------------------------------------------------------------------- * LOCAL DOUBLES, used for statistical output only (except for alpha): * ---------------------------------------------------------------------------- */ double f, r, ndiv, s, nms_lu, nms_ldl, dmax, alpha, lnz, lnzme ; /* * f: nvpiv * r: degme + nvpiv * ndiv: number of divisions for LU or LDL' factorizations * s: number of multiply-subtract pairs for LU factorization, for the * current element me * nms_lu number of multiply-subtract pairs for LU factorization * nms_ldl number of multiply-subtract pairs for LDL' factorization * dmax: the largest number of entries in any column of L, including the * diagonal * alpha: "dense" degree ratio * lnz: the number of nonzeros in L (excluding the diagonal) * lnzme: the number of nonzeros in L (excl. the diagonal) for the * current element me * ---------------------------------------------------------------------------- * LOCAL "POINTERS" (indices into the Iw array) * ---------------------------------------------------------------------------- */ Int p, p1, p2, p3, p4, pdst, pend, pj, pme, pme1, pme2, pn, psrc ; /* * Any parameter (Pe [...] or pfree) or local variable starting with "p" (for * Pointer) is an index into Iw, and all indices into Iw use variables starting * with "p." The only exception to this rule is the iwlen input argument. * * p: pointer into lots of things * p1: Pe [i] for some variable i (start of element list) * p2: Pe [i] + Elen [i] - 1 for some variable i * p3: index of first supervariable in clean list * p4: * pdst: destination pointer, for compression * pend: end of memory to compress * pj: pointer into an element or variable * pme: pointer into the current element (pme1...pme2) * pme1: the current element, me, is stored in Iw [pme1...pme2] * pme2: the end of the current element * pn: pointer into a "clean" variable, also used to compress * psrc: source pointer, for compression */ /* ========================================================================= */ /* INITIALIZATIONS */ /* ========================================================================= */ /* Note that this restriction on iwlen is slightly more restrictive than * what is actually required in AMD_2. AMD_2 can operate with no elbow * room at all, but it will be slow. For better performance, at least * size-n elbow room is enforced. */ ASSERT (iwlen >= pfree + n) ; ASSERT (n > 0) ; /* initialize output statistics */ lnz = 0 ; ndiv = 0 ; nms_lu = 0 ; nms_ldl = 0 ; dmax = 1 ; me = EMPTY ; mindeg = 0 ; ncmpa = 0 ; nel = 0 ; lemax = 0 ; /* get control parameters */ if (Control != (double *) NULL) { alpha = Control [AMD_DENSE] ; aggressive = (Control [AMD_AGGRESSIVE] != 0) ; } else { alpha = AMD_DEFAULT_DENSE ; aggressive = AMD_DEFAULT_AGGRESSIVE ; } /* Note: if alpha is NaN, this is undefined: */ if (alpha < 0) { /* only remove completely dense rows/columns */ dense = n-2 ; } else { dense = alpha * sqrt ((double) n) ; } dense = MAX (16, dense) ; dense = MIN (n, dense) ; AMD_DEBUG1 (("\n\nAMD (debug), alpha %g, aggr. "ID"\n", alpha, aggressive)) ; for (i = 0 ; i < n ; i++) { Last [i] = EMPTY ; Head [i] = EMPTY ; Next [i] = EMPTY ; /* if separate Hhead array is used for hash buckets: * Hhead [i] = EMPTY ; */ Nv [i] = 1 ; W [i] = 1 ; Elen [i] = 0 ; Degree [i] = Len [i] ; } #ifndef NDEBUG AMD_DEBUG1 (("\n======Nel "ID" initial\n", nel)) ; AMD_dump (n, Pe, Iw, Len, iwlen, pfree, Nv, Next, Last, Head, Elen, Degree, W, -1) ; #endif /* initialize wflg */ wbig = Int_MAX - n ; wflg = clear_flag (0, wbig, W, n) ; /* --------------------------------------------------------------------- */ /* initialize degree lists and eliminate dense and empty rows */ /* --------------------------------------------------------------------- */ ndense = 0 ; for (i = 0 ; i < n ; i++) { deg = Degree [i] ; ASSERT (deg >= 0 && deg < n) ; if (deg == 0) { /* ------------------------------------------------------------- * we have a variable that can be eliminated at once because * there is no off-diagonal non-zero in its row. Note that * Nv [i] = 1 for an empty variable i. It is treated just * the same as an eliminated element i. * ------------------------------------------------------------- */ Elen [i] = FLIP (1) ; nel++ ; Pe [i] = EMPTY ; W [i] = 0 ; } else if (deg > dense) { /* ------------------------------------------------------------- * Dense variables are not treated as elements, but as unordered, * non-principal variables that have no parent. They do not take * part in the postorder, since Nv [i] = 0. Note that the Fortran * version does not have this option. * ------------------------------------------------------------- */ AMD_DEBUG1 (("Dense node "ID" degree "ID"\n", i, deg)) ; ndense++ ; Nv [i] = 0 ; /* do not postorder this node */ Elen [i] = EMPTY ; nel++ ; Pe [i] = EMPTY ; } else { /* ------------------------------------------------------------- * place i in the degree list corresponding to its degree * ------------------------------------------------------------- */ inext = Head [deg] ; ASSERT (inext >= EMPTY && inext < n) ; if (inext != EMPTY) Last [inext] = i ; Next [i] = inext ; Head [deg] = i ; } } /* ========================================================================= */ /* WHILE (selecting pivots) DO */ /* ========================================================================= */ while (nel < n) { #ifndef NDEBUG AMD_DEBUG1 (("\n======Nel "ID"\n", nel)) ; if (AMD_debug >= 2) { AMD_dump (n, Pe, Iw, Len, iwlen, pfree, Nv, Next, Last, Head, Elen, Degree, W, nel) ; } #endif /* ========================================================================= */ /* GET PIVOT OF MINIMUM DEGREE */ /* ========================================================================= */ /* ----------------------------------------------------------------- */ /* find next supervariable for elimination */ /* ----------------------------------------------------------------- */ ASSERT (mindeg >= 0 && mindeg < n) ; for (deg = mindeg ; deg < n ; deg++) { me = Head [deg] ; if (me != EMPTY) break ; } mindeg = deg ; ASSERT (me >= 0 && me < n) ; AMD_DEBUG1 (("=================me: "ID"\n", me)) ; /* ----------------------------------------------------------------- */ /* remove chosen variable from link list */ /* ----------------------------------------------------------------- */ inext = Next [me] ; ASSERT (inext >= EMPTY && inext < n) ; if (inext != EMPTY) Last [inext] = EMPTY ; Head [deg] = inext ; /* ----------------------------------------------------------------- */ /* me represents the elimination of pivots nel to nel+Nv[me]-1. */ /* place me itself as the first in this set. */ /* ----------------------------------------------------------------- */ elenme = Elen [me] ; nvpiv = Nv [me] ; ASSERT (nvpiv > 0) ; nel += nvpiv ; /* ========================================================================= */ /* CONSTRUCT NEW ELEMENT */ /* ========================================================================= */ /* ----------------------------------------------------------------- * At this point, me is the pivotal supervariable. It will be * converted into the current element. Scan list of the pivotal * supervariable, me, setting tree pointers and constructing new list * of supervariables for the new element, me. p is a pointer to the * current position in the old list. * ----------------------------------------------------------------- */ /* flag the variable "me" as being in Lme by negating Nv [me] */ Nv [me] = -nvpiv ; degme = 0 ; ASSERT (Pe [me] >= 0 && Pe [me] < iwlen) ; if (elenme == 0) { /* ------------------------------------------------------------- */ /* construct the new element in place */ /* ------------------------------------------------------------- */ pme1 = Pe [me] ; pme2 = pme1 - 1 ; for (p = pme1 ; p <= pme1 + Len [me] - 1 ; p++) { i = Iw [p] ; ASSERT (i >= 0 && i < n && Nv [i] >= 0) ; nvi = Nv [i] ; if (nvi > 0) { /* ----------------------------------------------------- */ /* i is a principal variable not yet placed in Lme. */ /* store i in new list */ /* ----------------------------------------------------- */ /* flag i as being in Lme by negating Nv [i] */ degme += nvi ; Nv [i] = -nvi ; Iw [++pme2] = i ; /* ----------------------------------------------------- */ /* remove variable i from degree list. */ /* ----------------------------------------------------- */ ilast = Last [i] ; inext = Next [i] ; ASSERT (ilast >= EMPTY && ilast < n) ; ASSERT (inext >= EMPTY && inext < n) ; if (inext != EMPTY) Last [inext] = ilast ; if (ilast != EMPTY) { Next [ilast] = inext ; } else { /* i is at the head of the degree list */ ASSERT (Degree [i] >= 0 && Degree [i] < n) ; Head [Degree [i]] = inext ; } } } } else { /* ------------------------------------------------------------- */ /* construct the new element in empty space, Iw [pfree ...] */ /* ------------------------------------------------------------- */ p = Pe [me] ; pme1 = pfree ; slenme = Len [me] - elenme ; for (knt1 = 1 ; knt1 <= elenme + 1 ; knt1++) { if (knt1 > elenme) { /* search the supervariables in me. */ e = me ; pj = p ; ln = slenme ; AMD_DEBUG2 (("Search sv: "ID" "ID" "ID"\n", me,pj,ln)) ; } else { /* search the elements in me. */ e = Iw [p++] ; ASSERT (e >= 0 && e < n) ; pj = Pe [e] ; ln = Len [e] ; AMD_DEBUG2 (("Search element e "ID" in me "ID"\n", e,me)) ; ASSERT (Elen [e] < EMPTY && W [e] > 0 && pj >= 0) ; } ASSERT (ln >= 0 && (ln == 0 || (pj >= 0 && pj < iwlen))) ; /* --------------------------------------------------------- * search for different supervariables and add them to the * new list, compressing when necessary. this loop is * executed once for each element in the list and once for * all the supervariables in the list. * --------------------------------------------------------- */ for (knt2 = 1 ; knt2 <= ln ; knt2++) { i = Iw [pj++] ; ASSERT (i >= 0 && i < n && (i == me || Elen [i] >= EMPTY)); nvi = Nv [i] ; AMD_DEBUG2 ((": "ID" "ID" "ID" "ID"\n", i, Elen [i], Nv [i], wflg)) ; if (nvi > 0) { /* ------------------------------------------------- */ /* compress Iw, if necessary */ /* ------------------------------------------------- */ if (pfree >= iwlen) { AMD_DEBUG1 (("GARBAGE COLLECTION\n")) ; /* prepare for compressing Iw by adjusting pointers * and lengths so that the lists being searched in * the inner and outer loops contain only the * remaining entries. */ Pe [me] = p ; Len [me] -= knt1 ; /* check if nothing left of supervariable me */ if (Len [me] == 0) Pe [me] = EMPTY ; Pe [e] = pj ; Len [e] = ln - knt2 ; /* nothing left of element e */ if (Len [e] == 0) Pe [e] = EMPTY ; ncmpa++ ; /* one more garbage collection */ /* store first entry of each object in Pe */ /* FLIP the first entry in each object */ for (j = 0 ; j < n ; j++) { pn = Pe [j] ; if (pn >= 0) { ASSERT (pn >= 0 && pn < iwlen) ; Pe [j] = Iw [pn] ; Iw [pn] = FLIP (j) ; } } /* psrc/pdst point to source/destination */ psrc = 0 ; pdst = 0 ; pend = pme1 - 1 ; while (psrc <= pend) { /* search for next FLIP'd entry */ j = FLIP (Iw [psrc++]) ; if (j >= 0) { AMD_DEBUG2 (("Got object j: "ID"\n", j)) ; Iw [pdst] = Pe [j] ; Pe [j] = pdst++ ; lenj = Len [j] ; /* copy from source to destination */ for (knt3 = 0 ; knt3 <= lenj - 2 ; knt3++) { Iw [pdst++] = Iw [psrc++] ; } } } /* move the new partially-constructed element */ p1 = pdst ; for (psrc = pme1 ; psrc <= pfree-1 ; psrc++) { Iw [pdst++] = Iw [psrc] ; } pme1 = p1 ; pfree = pdst ; pj = Pe [e] ; p = Pe [me] ; } /* ------------------------------------------------- */ /* i is a principal variable not yet placed in Lme */ /* store i in new list */ /* ------------------------------------------------- */ /* flag i as being in Lme by negating Nv [i] */ degme += nvi ; Nv [i] = -nvi ; Iw [pfree++] = i ; AMD_DEBUG2 ((" s: "ID" nv "ID"\n", i, Nv [i])); /* ------------------------------------------------- */ /* remove variable i from degree link list */ /* ------------------------------------------------- */ ilast = Last [i] ; inext = Next [i] ; ASSERT (ilast >= EMPTY && ilast < n) ; ASSERT (inext >= EMPTY && inext < n) ; if (inext != EMPTY) Last [inext] = ilast ; if (ilast != EMPTY) { Next [ilast] = inext ; } else { /* i is at the head of the degree list */ ASSERT (Degree [i] >= 0 && Degree [i] < n) ; Head [Degree [i]] = inext ; } } } if (e != me) { /* set tree pointer and flag to indicate element e is * absorbed into new element me (the parent of e is me) */ AMD_DEBUG1 ((" Element "ID" => "ID"\n", e, me)) ; Pe [e] = FLIP (me) ; W [e] = 0 ; } } pme2 = pfree - 1 ; } /* ----------------------------------------------------------------- */ /* me has now been converted into an element in Iw [pme1..pme2] */ /* ----------------------------------------------------------------- */ /* degme holds the external degree of new element */ Degree [me] = degme ; Pe [me] = pme1 ; Len [me] = pme2 - pme1 + 1 ; ASSERT (Pe [me] >= 0 && Pe [me] < iwlen) ; Elen [me] = FLIP (nvpiv + degme) ; /* FLIP (Elen (me)) is now the degree of pivot (including * diagonal part). */ #ifndef NDEBUG AMD_DEBUG2 (("New element structure: length= "ID"\n", pme2-pme1+1)) ; for (pme = pme1 ; pme <= pme2 ; pme++) AMD_DEBUG3 ((" "ID"", Iw[pme])); AMD_DEBUG3 (("\n")) ; #endif /* ----------------------------------------------------------------- */ /* make sure that wflg is not too large. */ /* ----------------------------------------------------------------- */ /* With the current value of wflg, wflg+n must not cause integer * overflow */ wflg = clear_flag (wflg, wbig, W, n) ; /* ========================================================================= */ /* COMPUTE (W [e] - wflg) = |Le\Lme| FOR ALL ELEMENTS */ /* ========================================================================= */ /* ----------------------------------------------------------------- * Scan 1: compute the external degrees of previous elements with * respect to the current element. That is: * (W [e] - wflg) = |Le \ Lme| * for each element e that appears in any supervariable in Lme. The * notation Le refers to the pattern (list of supervariables) of a * previous element e, where e is not yet absorbed, stored in * Iw [Pe [e] + 1 ... Pe [e] + Len [e]]. The notation Lme * refers to the pattern of the current element (stored in * Iw [pme1..pme2]). If aggressive absorption is enabled, and * (W [e] - wflg) becomes zero, then the element e will be absorbed * in Scan 2. * ----------------------------------------------------------------- */ AMD_DEBUG2 (("me: ")) ; for (pme = pme1 ; pme <= pme2 ; pme++) { i = Iw [pme] ; ASSERT (i >= 0 && i < n) ; eln = Elen [i] ; AMD_DEBUG3 ((""ID" Elen "ID": \n", i, eln)) ; if (eln > 0) { /* note that Nv [i] has been negated to denote i in Lme: */ nvi = -Nv [i] ; ASSERT (nvi > 0 && Pe [i] >= 0 && Pe [i] < iwlen) ; wnvi = wflg - nvi ; for (p = Pe [i] ; p <= Pe [i] + eln - 1 ; p++) { e = Iw [p] ; ASSERT (e >= 0 && e < n) ; we = W [e] ; AMD_DEBUG4 ((" e "ID" we "ID" ", e, we)) ; if (we >= wflg) { /* unabsorbed element e has been seen in this loop */ AMD_DEBUG4 ((" unabsorbed, first time seen")) ; we -= nvi ; } else if (we != 0) { /* e is an unabsorbed element */ /* this is the first we have seen e in all of Scan 1 */ AMD_DEBUG4 ((" unabsorbed")) ; we = Degree [e] + wnvi ; } AMD_DEBUG4 (("\n")) ; W [e] = we ; } } } AMD_DEBUG2 (("\n")) ; /* ========================================================================= */ /* DEGREE UPDATE AND ELEMENT ABSORPTION */ /* ========================================================================= */ /* ----------------------------------------------------------------- * Scan 2: for each i in Lme, sum up the degree of Lme (which is * degme), plus the sum of the external degrees of each Le for the * elements e appearing within i, plus the supervariables in i. * Place i in hash list. * ----------------------------------------------------------------- */ for (pme = pme1 ; pme <= pme2 ; pme++) { i = Iw [pme] ; ASSERT (i >= 0 && i < n && Nv [i] < 0 && Elen [i] >= 0) ; AMD_DEBUG2 (("Updating: i "ID" "ID" "ID"\n", i, Elen[i], Len [i])); p1 = Pe [i] ; p2 = p1 + Elen [i] - 1 ; pn = p1 ; hash = 0 ; deg = 0 ; ASSERT (p1 >= 0 && p1 < iwlen && p2 >= -1 && p2 < iwlen) ; /* ------------------------------------------------------------- */ /* scan the element list associated with supervariable i */ /* ------------------------------------------------------------- */ /* UMFPACK/MA38-style approximate degree: */ if (aggressive) { for (p = p1 ; p <= p2 ; p++) { e = Iw [p] ; ASSERT (e >= 0 && e < n) ; we = W [e] ; if (we != 0) { /* e is an unabsorbed element */ /* dext = | Le \ Lme | */ dext = we - wflg ; if (dext > 0) { deg += dext ; Iw [pn++] = e ; hash += e ; AMD_DEBUG4 ((" e: "ID" hash = "ID"\n",e,hash)) ; } else { /* external degree of e is zero, absorb e into me*/ AMD_DEBUG1 ((" Element "ID" =>"ID" (aggressive)\n", e, me)) ; ASSERT (dext == 0) ; Pe [e] = FLIP (me) ; W [e] = 0 ; } } } } else { for (p = p1 ; p <= p2 ; p++) { e = Iw [p] ; ASSERT (e >= 0 && e < n) ; we = W [e] ; if (we != 0) { /* e is an unabsorbed element */ dext = we - wflg ; ASSERT (dext >= 0) ; deg += dext ; Iw [pn++] = e ; hash += e ; AMD_DEBUG4 ((" e: "ID" hash = "ID"\n",e,hash)) ; } } } /* count the number of elements in i (including me): */ Elen [i] = pn - p1 + 1 ; /* ------------------------------------------------------------- */ /* scan the supervariables in the list associated with i */ /* ------------------------------------------------------------- */ /* The bulk of the AMD run time is typically spent in this loop, * particularly if the matrix has many dense rows that are not * removed prior to ordering. */ p3 = pn ; p4 = p1 + Len [i] ; for (p = p2 + 1 ; p < p4 ; p++) { j = Iw [p] ; ASSERT (j >= 0 && j < n) ; nvj = Nv [j] ; if (nvj > 0) { /* j is unabsorbed, and not in Lme. */ /* add to degree and add to new list */ deg += nvj ; Iw [pn++] = j ; hash += j ; AMD_DEBUG4 ((" s: "ID" hash "ID" Nv[j]= "ID"\n", j, hash, nvj)) ; } } /* ------------------------------------------------------------- */ /* update the degree and check for mass elimination */ /* ------------------------------------------------------------- */ /* with aggressive absorption, deg==0 is identical to the * Elen [i] == 1 && p3 == pn test, below. */ ASSERT (IMPLIES (aggressive, (deg==0) == (Elen[i]==1 && p3==pn))) ; if (Elen [i] == 1 && p3 == pn) { /* --------------------------------------------------------- */ /* mass elimination */ /* --------------------------------------------------------- */ /* There is nothing left of this node except for an edge to * the current pivot element. Elen [i] is 1, and there are * no variables adjacent to node i. Absorb i into the * current pivot element, me. Note that if there are two or * more mass eliminations, fillin due to mass elimination is * possible within the nvpiv-by-nvpiv pivot block. It is this * step that causes AMD's analysis to be an upper bound. * * The reason is that the selected pivot has a lower * approximate degree than the true degree of the two mass * eliminated nodes. There is no edge between the two mass * eliminated nodes. They are merged with the current pivot * anyway. * * No fillin occurs in the Schur complement, in any case, * and this effect does not decrease the quality of the * ordering itself, just the quality of the nonzero and * flop count analysis. It also means that the post-ordering * is not an exact elimination tree post-ordering. */ AMD_DEBUG1 ((" MASS i "ID" => parent e "ID"\n", i, me)) ; Pe [i] = FLIP (me) ; nvi = -Nv [i] ; degme -= nvi ; nvpiv += nvi ; nel += nvi ; Nv [i] = 0 ; Elen [i] = EMPTY ; } else { /* --------------------------------------------------------- */ /* update the upper-bound degree of i */ /* --------------------------------------------------------- */ /* the following degree does not yet include the size * of the current element, which is added later: */ Degree [i] = MIN (Degree [i], deg) ; /* --------------------------------------------------------- */ /* add me to the list for i */ /* --------------------------------------------------------- */ /* move first supervariable to end of list */ Iw [pn] = Iw [p3] ; /* move first element to end of element part of list */ Iw [p3] = Iw [p1] ; /* add new element, me, to front of list. */ Iw [p1] = me ; /* store the new length of the list in Len [i] */ Len [i] = pn - p1 + 1 ; /* --------------------------------------------------------- */ /* place in hash bucket. Save hash key of i in Last [i]. */ /* --------------------------------------------------------- */ /* NOTE: this can fail if hash is negative, because the ANSI C * standard does not define a % b when a and/or b are negative. * That's why hash is defined as an unsigned Int, to avoid this * problem. */ hash = hash % n ; ASSERT (((Int) hash) >= 0 && ((Int) hash) < n) ; /* if the Hhead array is not used: */ j = Head [hash] ; if (j <= EMPTY) { /* degree list is empty, hash head is FLIP (j) */ Next [i] = FLIP (j) ; Head [hash] = FLIP (i) ; } else { /* degree list is not empty, use Last [Head [hash]] as * hash head. */ Next [i] = Last [j] ; Last [j] = i ; } /* if a separate Hhead array is used: * Next [i] = Hhead [hash] ; Hhead [hash] = i ; */ Last [i] = hash ; } } Degree [me] = degme ; /* ----------------------------------------------------------------- */ /* Clear the counter array, W [...], by incrementing wflg. */ /* ----------------------------------------------------------------- */ /* make sure that wflg+n does not cause integer overflow */ lemax = MAX (lemax, degme) ; wflg += lemax ; wflg = clear_flag (wflg, wbig, W, n) ; /* at this point, W [0..n-1] < wflg holds */ /* ========================================================================= */ /* SUPERVARIABLE DETECTION */ /* ========================================================================= */ AMD_DEBUG1 (("Detecting supervariables:\n")) ; for (pme = pme1 ; pme <= pme2 ; pme++) { i = Iw [pme] ; ASSERT (i >= 0 && i < n) ; AMD_DEBUG2 (("Consider i "ID" nv "ID"\n", i, Nv [i])) ; if (Nv [i] < 0) { /* i is a principal variable in Lme */ /* --------------------------------------------------------- * examine all hash buckets with 2 or more variables. We do * this by examing all unique hash keys for supervariables in * the pattern Lme of the current element, me * --------------------------------------------------------- */ /* let i = head of hash bucket, and empty the hash bucket */ ASSERT (Last [i] >= 0 && Last [i] < n) ; hash = Last [i] ; /* if Hhead array is not used: */ j = Head [hash] ; if (j == EMPTY) { /* hash bucket and degree list are both empty */ i = EMPTY ; } else if (j < EMPTY) { /* degree list is empty */ i = FLIP (j) ; Head [hash] = EMPTY ; } else { /* degree list is not empty, restore Last [j] of head j */ i = Last [j] ; Last [j] = EMPTY ; } /* if separate Hhead array is used: * i = Hhead [hash] ; Hhead [hash] = EMPTY ; */ ASSERT (i >= EMPTY && i < n) ; AMD_DEBUG2 (("----i "ID" hash "ID"\n", i, hash)) ; while (i != EMPTY && Next [i] != EMPTY) { /* ----------------------------------------------------- * this bucket has one or more variables following i. * scan all of them to see if i can absorb any entries * that follow i in hash bucket. Scatter i into w. * ----------------------------------------------------- */ ln = Len [i] ; eln = Elen [i] ; ASSERT (ln >= 0 && eln >= 0) ; ASSERT (Pe [i] >= 0 && Pe [i] < iwlen) ; /* do not flag the first element in the list (me) */ for (p = Pe [i] + 1 ; p <= Pe [i] + ln - 1 ; p++) { ASSERT (Iw [p] >= 0 && Iw [p] < n) ; W [Iw [p]] = wflg ; } /* ----------------------------------------------------- */ /* scan every other entry j following i in bucket */ /* ----------------------------------------------------- */ jlast = i ; j = Next [i] ; ASSERT (j >= EMPTY && j < n) ; while (j != EMPTY) { /* ------------------------------------------------- */ /* check if j and i have identical nonzero pattern */ /* ------------------------------------------------- */ AMD_DEBUG3 (("compare i "ID" and j "ID"\n", i,j)) ; /* check if i and j have the same Len and Elen */ ASSERT (Len [j] >= 0 && Elen [j] >= 0) ; ASSERT (Pe [j] >= 0 && Pe [j] < iwlen) ; ok = (Len [j] == ln) && (Elen [j] == eln) ; /* skip the first element in the list (me) */ for (p = Pe [j] + 1 ; ok && p <= Pe [j] + ln - 1 ; p++) { ASSERT (Iw [p] >= 0 && Iw [p] < n) ; if (W [Iw [p]] != wflg) ok = 0 ; } if (ok) { /* --------------------------------------------- */ /* found it! j can be absorbed into i */ /* --------------------------------------------- */ AMD_DEBUG1 (("found it! j "ID" => i "ID"\n", j,i)); Pe [j] = FLIP (i) ; /* both Nv [i] and Nv [j] are negated since they */ /* are in Lme, and the absolute values of each */ /* are the number of variables in i and j: */ Nv [i] += Nv [j] ; Nv [j] = 0 ; Elen [j] = EMPTY ; /* delete j from hash bucket */ ASSERT (j != Next [j]) ; j = Next [j] ; Next [jlast] = j ; } else { /* j cannot be absorbed into i */ jlast = j ; ASSERT (j != Next [j]) ; j = Next [j] ; } ASSERT (j >= EMPTY && j < n) ; } /* ----------------------------------------------------- * no more variables can be absorbed into i * go to next i in bucket and clear flag array * ----------------------------------------------------- */ wflg++ ; i = Next [i] ; ASSERT (i >= EMPTY && i < n) ; } } } AMD_DEBUG2 (("detect done\n")) ; /* ========================================================================= */ /* RESTORE DEGREE LISTS AND REMOVE NONPRINCIPAL SUPERVARIABLES FROM ELEMENT */ /* ========================================================================= */ p = pme1 ; nleft = n - nel ; for (pme = pme1 ; pme <= pme2 ; pme++) { i = Iw [pme] ; ASSERT (i >= 0 && i < n) ; nvi = -Nv [i] ; AMD_DEBUG3 (("Restore i "ID" "ID"\n", i, nvi)) ; if (nvi > 0) { /* i is a principal variable in Lme */ /* restore Nv [i] to signify that i is principal */ Nv [i] = nvi ; /* --------------------------------------------------------- */ /* compute the external degree (add size of current element) */ /* --------------------------------------------------------- */ deg = Degree [i] + degme - nvi ; deg = MIN (deg, nleft - nvi) ; ASSERT (IMPLIES (aggressive, deg > 0) && deg >= 0 && deg < n) ; /* --------------------------------------------------------- */ /* place the supervariable at the head of the degree list */ /* --------------------------------------------------------- */ inext = Head [deg] ; ASSERT (inext >= EMPTY && inext < n) ; if (inext != EMPTY) Last [inext] = i ; Next [i] = inext ; Last [i] = EMPTY ; Head [deg] = i ; /* --------------------------------------------------------- */ /* save the new degree, and find the minimum degree */ /* --------------------------------------------------------- */ mindeg = MIN (mindeg, deg) ; Degree [i] = deg ; /* --------------------------------------------------------- */ /* place the supervariable in the element pattern */ /* --------------------------------------------------------- */ Iw [p++] = i ; } } AMD_DEBUG2 (("restore done\n")) ; /* ========================================================================= */ /* FINALIZE THE NEW ELEMENT */ /* ========================================================================= */ AMD_DEBUG2 (("ME = "ID" DONE\n", me)) ; Nv [me] = nvpiv ; /* save the length of the list for the new element me */ Len [me] = p - pme1 ; if (Len [me] == 0) { /* there is nothing left of the current pivot element */ /* it is a root of the assembly tree */ Pe [me] = EMPTY ; W [me] = 0 ; } if (elenme != 0) { /* element was not constructed in place: deallocate part of */ /* it since newly nonprincipal variables may have been removed */ pfree = p ; } /* The new element has nvpiv pivots and the size of the contribution * block for a multifrontal method is degme-by-degme, not including * the "dense" rows/columns. If the "dense" rows/columns are included, * the frontal matrix is no larger than * (degme+ndense)-by-(degme+ndense). */ if (Info != (double *) NULL) { f = nvpiv ; r = degme + ndense ; dmax = MAX (dmax, f + r) ; /* number of nonzeros in L (excluding the diagonal) */ lnzme = f*r + (f-1)*f/2 ; lnz += lnzme ; /* number of divide operations for LDL' and for LU */ ndiv += lnzme ; /* number of multiply-subtract pairs for LU */ s = f*r*r + r*(f-1)*f + (f-1)*f*(2*f-1)/6 ; nms_lu += s ; /* number of multiply-subtract pairs for LDL' */ nms_ldl += (s + lnzme)/2 ; } #ifndef NDEBUG AMD_DEBUG2 (("finalize done nel "ID" n "ID"\n ::::\n", nel, n)) ; for (pme = Pe [me] ; pme <= Pe [me] + Len [me] - 1 ; pme++) { AMD_DEBUG3 ((" "ID"", Iw [pme])) ; } AMD_DEBUG3 (("\n")) ; #endif } /* ========================================================================= */ /* DONE SELECTING PIVOTS */ /* ========================================================================= */ if (Info != (double *) NULL) { /* count the work to factorize the ndense-by-ndense submatrix */ f = ndense ; dmax = MAX (dmax, (double) ndense) ; /* number of nonzeros in L (excluding the diagonal) */ lnzme = (f-1)*f/2 ; lnz += lnzme ; /* number of divide operations for LDL' and for LU */ ndiv += lnzme ; /* number of multiply-subtract pairs for LU */ s = (f-1)*f*(2*f-1)/6 ; nms_lu += s ; /* number of multiply-subtract pairs for LDL' */ nms_ldl += (s + lnzme)/2 ; /* number of nz's in L (excl. diagonal) */ Info [AMD_LNZ] = lnz ; /* number of divide ops for LU and LDL' */ Info [AMD_NDIV] = ndiv ; /* number of multiply-subtract pairs for LDL' */ Info [AMD_NMULTSUBS_LDL] = nms_ldl ; /* number of multiply-subtract pairs for LU */ Info [AMD_NMULTSUBS_LU] = nms_lu ; /* number of "dense" rows/columns */ Info [AMD_NDENSE] = ndense ; /* largest front is dmax-by-dmax */ Info [AMD_DMAX] = dmax ; /* number of garbage collections in AMD */ Info [AMD_NCMPA] = ncmpa ; /* successful ordering */ Info [AMD_STATUS] = AMD_OK ; } /* ========================================================================= */ /* POST-ORDERING */ /* ========================================================================= */ /* ------------------------------------------------------------------------- * Variables at this point: * * Pe: holds the elimination tree. The parent of j is FLIP (Pe [j]), * or EMPTY if j is a root. The tree holds both elements and * non-principal (unordered) variables absorbed into them. * Dense variables are non-principal and unordered. * * Elen: holds the size of each element, including the diagonal part. * FLIP (Elen [e]) > 0 if e is an element. For unordered * variables i, Elen [i] is EMPTY. * * Nv: Nv [e] > 0 is the number of pivots represented by the element e. * For unordered variables i, Nv [i] is zero. * * Contents no longer needed: * W, Iw, Len, Degree, Head, Next, Last. * * The matrix itself has been destroyed. * * n: the size of the matrix. * No other scalars needed (pfree, iwlen, etc.) * ------------------------------------------------------------------------- */ /* restore Pe */ for (i = 0 ; i < n ; i++) { Pe [i] = FLIP (Pe [i]) ; } /* restore Elen, for output information, and for postordering */ for (i = 0 ; i < n ; i++) { Elen [i] = FLIP (Elen [i]) ; } /* Now the parent of j is Pe [j], or EMPTY if j is a root. Elen [e] > 0 * is the size of element e. Elen [i] is EMPTY for unordered variable i. */ #ifndef NDEBUG AMD_DEBUG2 (("\nTree:\n")) ; for (i = 0 ; i < n ; i++) { AMD_DEBUG2 ((" "ID" parent: "ID" ", i, Pe [i])) ; ASSERT (Pe [i] >= EMPTY && Pe [i] < n) ; if (Nv [i] > 0) { /* this is an element */ e = i ; AMD_DEBUG2 ((" element, size is "ID"\n", Elen [i])) ; ASSERT (Elen [e] > 0) ; } AMD_DEBUG2 (("\n")) ; } AMD_DEBUG2 (("\nelements:\n")) ; for (e = 0 ; e < n ; e++) { if (Nv [e] > 0) { AMD_DEBUG3 (("Element e= "ID" size "ID" nv "ID" \n", e, Elen [e], Nv [e])) ; } } AMD_DEBUG2 (("\nvariables:\n")) ; for (i = 0 ; i < n ; i++) { Int cnt ; if (Nv [i] == 0) { AMD_DEBUG3 (("i unordered: "ID"\n", i)) ; j = Pe [i] ; cnt = 0 ; AMD_DEBUG3 ((" j: "ID"\n", j)) ; if (j == EMPTY) { AMD_DEBUG3 ((" i is a dense variable\n")) ; } else { ASSERT (j >= 0 && j < n) ; while (Nv [j] == 0) { AMD_DEBUG3 ((" j : "ID"\n", j)) ; j = Pe [j] ; AMD_DEBUG3 ((" j:: "ID"\n", j)) ; cnt++ ; if (cnt > n) break ; } e = j ; AMD_DEBUG3 ((" got to e: "ID"\n", e)) ; } } } #endif /* ========================================================================= */ /* compress the paths of the variables */ /* ========================================================================= */ for (i = 0 ; i < n ; i++) { if (Nv [i] == 0) { /* ------------------------------------------------------------- * i is an un-ordered row. Traverse the tree from i until * reaching an element, e. The element, e, was the principal * supervariable of i and all nodes in the path from i to when e * was selected as pivot. * ------------------------------------------------------------- */ AMD_DEBUG1 (("Path compression, i unordered: "ID"\n", i)) ; j = Pe [i] ; ASSERT (j >= EMPTY && j < n) ; AMD_DEBUG3 ((" j: "ID"\n", j)) ; if (j == EMPTY) { /* Skip a dense variable. It has no parent. */ AMD_DEBUG3 ((" i is a dense variable\n")) ; continue ; } /* while (j is a variable) */ while (Nv [j] == 0) { AMD_DEBUG3 ((" j : "ID"\n", j)) ; j = Pe [j] ; AMD_DEBUG3 ((" j:: "ID"\n", j)) ; ASSERT (j >= 0 && j < n) ; } /* got to an element e */ e = j ; AMD_DEBUG3 (("got to e: "ID"\n", e)) ; /* ------------------------------------------------------------- * traverse the path again from i to e, and compress the path * (all nodes point to e). Path compression allows this code to * compute in O(n) time. * ------------------------------------------------------------- */ j = i ; /* while (j is a variable) */ while (Nv [j] == 0) { jnext = Pe [j] ; AMD_DEBUG3 (("j "ID" jnext "ID"\n", j, jnext)) ; Pe [j] = e ; j = jnext ; ASSERT (j >= 0 && j < n) ; } } } /* ========================================================================= */ /* postorder the assembly tree */ /* ========================================================================= */ AMD_postorder (n, Pe, Nv, Elen, W, /* output order */ Head, Next, Last) ; /* workspace */ /* ========================================================================= */ /* compute output permutation and inverse permutation */ /* ========================================================================= */ /* W [e] = k means that element e is the kth element in the new * order. e is in the range 0 to n-1, and k is in the range 0 to * the number of elements. Use Head for inverse order. */ for (k = 0 ; k < n ; k++) { Head [k] = EMPTY ; Next [k] = EMPTY ; } for (e = 0 ; e < n ; e++) { k = W [e] ; ASSERT ((k == EMPTY) == (Nv [e] == 0)) ; if (k != EMPTY) { ASSERT (k >= 0 && k < n) ; Head [k] = e ; } } /* construct output inverse permutation in Next, * and permutation in Last */ nel = 0 ; for (k = 0 ; k < n ; k++) { e = Head [k] ; if (e == EMPTY) break ; ASSERT (e >= 0 && e < n && Nv [e] > 0) ; Next [e] = nel ; nel += Nv [e] ; } ASSERT (nel == n - ndense) ; /* order non-principal variables (dense, & those merged into supervar's) */ for (i = 0 ; i < n ; i++) { if (Nv [i] == 0) { e = Pe [i] ; ASSERT (e >= EMPTY && e < n) ; if (e != EMPTY) { /* This is an unordered variable that was merged * into element e via supernode detection or mass * elimination of i when e became the pivot element. * Place i in order just before e. */ ASSERT (Next [i] == EMPTY && Nv [e] > 0) ; Next [i] = Next [e] ; Next [e]++ ; } else { /* This is a dense unordered variable, with no parent. * Place it last in the output order. */ Next [i] = nel++ ; } } } ASSERT (nel == n) ; AMD_DEBUG2 (("\n\nPerm:\n")) ; for (i = 0 ; i < n ; i++) { k = Next [i] ; ASSERT (k >= 0 && k < n) ; Last [k] = i ; AMD_DEBUG2 ((" perm ["ID"] = "ID"\n", k, i)) ; } } python-igraph-0.8.0/vendor/source/igraph/src/AMD/Source/amd_aat.c0000644000076500000240000001135713524616144025006 0ustar tamasstaff00000000000000/* ========================================================================= */ /* === AMD_aat ============================================================= */ /* ========================================================================= */ /* ------------------------------------------------------------------------- */ /* AMD, Copyright (c) Timothy A. Davis, */ /* Patrick R. Amestoy, and Iain S. Duff. See ../README.txt for License. */ /* email: DrTimothyAldenDavis@gmail.com */ /* ------------------------------------------------------------------------- */ /* AMD_aat: compute the symmetry of the pattern of A, and count the number of * nonzeros each column of A+A' (excluding the diagonal). Assumes the input * matrix has no errors, with sorted columns and no duplicates * (AMD_valid (n, n, Ap, Ai) must be AMD_OK, but this condition is not * checked). */ #include "amd_internal.h" GLOBAL size_t AMD_aat /* returns nz in A+A' */ ( Int n, const Int Ap [ ], const Int Ai [ ], Int Len [ ], /* Len [j]: length of column j of A+A', excl diagonal*/ Int Tp [ ], /* workspace of size n */ double Info [ ] ) { Int p1, p2, p, i, j, pj, pj2, k, nzdiag, nzboth, nz ; double sym ; size_t nzaat ; #ifndef NDEBUG AMD_debug_init ("AMD AAT") ; for (k = 0 ; k < n ; k++) Tp [k] = EMPTY ; ASSERT (AMD_valid (n, n, Ap, Ai) == AMD_OK) ; #endif if (Info != (double *) NULL) { /* clear the Info array, if it exists */ for (i = 0 ; i < AMD_INFO ; i++) { Info [i] = EMPTY ; } Info [AMD_STATUS] = AMD_OK ; } for (k = 0 ; k < n ; k++) { Len [k] = 0 ; } nzdiag = 0 ; nzboth = 0 ; nz = Ap [n] ; for (k = 0 ; k < n ; k++) { p1 = Ap [k] ; p2 = Ap [k+1] ; AMD_DEBUG2 (("\nAAT Column: "ID" p1: "ID" p2: "ID"\n", k, p1, p2)) ; /* construct A+A' */ for (p = p1 ; p < p2 ; ) { /* scan the upper triangular part of A */ j = Ai [p] ; if (j < k) { /* entry A (j,k) is in the strictly upper triangular part, * add both A (j,k) and A (k,j) to the matrix A+A' */ Len [j]++ ; Len [k]++ ; AMD_DEBUG3 ((" upper ("ID","ID") ("ID","ID")\n", j,k, k,j)); p++ ; } else if (j == k) { /* skip the diagonal */ p++ ; nzdiag++ ; break ; } else /* j > k */ { /* first entry below the diagonal */ break ; } /* scan lower triangular part of A, in column j until reaching * row k. Start where last scan left off. */ ASSERT (Tp [j] != EMPTY) ; ASSERT (Ap [j] <= Tp [j] && Tp [j] <= Ap [j+1]) ; pj2 = Ap [j+1] ; for (pj = Tp [j] ; pj < pj2 ; ) { i = Ai [pj] ; if (i < k) { /* A (i,j) is only in the lower part, not in upper. * add both A (i,j) and A (j,i) to the matrix A+A' */ Len [i]++ ; Len [j]++ ; AMD_DEBUG3 ((" lower ("ID","ID") ("ID","ID")\n", i,j, j,i)) ; pj++ ; } else if (i == k) { /* entry A (k,j) in lower part and A (j,k) in upper */ pj++ ; nzboth++ ; break ; } else /* i > k */ { /* consider this entry later, when k advances to i */ break ; } } Tp [j] = pj ; } /* Tp [k] points to the entry just below the diagonal in column k */ Tp [k] = p ; } /* clean up, for remaining mismatched entries */ for (j = 0 ; j < n ; j++) { for (pj = Tp [j] ; pj < Ap [j+1] ; pj++) { i = Ai [pj] ; /* A (i,j) is only in the lower part, not in upper. * add both A (i,j) and A (j,i) to the matrix A+A' */ Len [i]++ ; Len [j]++ ; AMD_DEBUG3 ((" lower cleanup ("ID","ID") ("ID","ID")\n", i,j, j,i)) ; } } /* --------------------------------------------------------------------- */ /* compute the symmetry of the nonzero pattern of A */ /* --------------------------------------------------------------------- */ /* Given a matrix A, the symmetry of A is: * B = tril (spones (A), -1) + triu (spones (A), 1) ; * sym = nnz (B & B') / nnz (B) ; * or 1 if nnz (B) is zero. */ if (nz == nzdiag) { sym = 1 ; } else { sym = (2 * (double) nzboth) / ((double) (nz - nzdiag)) ; } nzaat = 0 ; for (k = 0 ; k < n ; k++) { nzaat += Len [k] ; } AMD_DEBUG1 (("AMD nz in A+A', excluding diagonal (nzaat) = %g\n", (double) nzaat)) ; AMD_DEBUG1 ((" nzboth: "ID" nz: "ID" nzdiag: "ID" symmetry: %g\n", nzboth, nz, nzdiag, sym)) ; if (Info != (double *) NULL) { Info [AMD_STATUS] = AMD_OK ; Info [AMD_N] = n ; Info [AMD_NZ] = nz ; Info [AMD_SYMMETRY] = sym ; /* symmetry of pattern of A */ Info [AMD_NZDIAG] = nzdiag ; /* nonzeros on diagonal of A */ Info [AMD_NZ_A_PLUS_AT] = nzaat ; /* nonzeros in A+A' */ } return (nzaat) ; } python-igraph-0.8.0/vendor/source/igraph/src/AMD/Source/amd_dump.c0000644000076500000240000001162413524616144025203 0ustar tamasstaff00000000000000/* ========================================================================= */ /* === AMD_dump ============================================================ */ /* ========================================================================= */ /* ------------------------------------------------------------------------- */ /* AMD, Copyright (c) Timothy A. Davis, */ /* Patrick R. Amestoy, and Iain S. Duff. See ../README.txt for License. */ /* email: DrTimothyAldenDavis@gmail.com */ /* ------------------------------------------------------------------------- */ /* Debugging routines for AMD. Not used if NDEBUG is not defined at compile- * time (the default). See comments in amd_internal.h on how to enable * debugging. Not user-callable. */ #include "amd_internal.h" #ifndef NDEBUG /* This global variable is present only when debugging */ GLOBAL Int AMD_debug = -999 ; /* default is no debug printing */ /* ========================================================================= */ /* === AMD_debug_init ====================================================== */ /* ========================================================================= */ /* Sets the debug print level, by reading the file debug.amd (if it exists) */ GLOBAL void AMD_debug_init ( char *s ) { FILE *f ; f = fopen ("debug.amd", "r") ; if (f == (FILE *) NULL) { AMD_debug = -999 ; } else { fscanf (f, ID, &AMD_debug) ; fclose (f) ; } if (AMD_debug >= 0) { printf ("%s: AMD_debug_init, D= "ID"\n", s, AMD_debug) ; } } /* ========================================================================= */ /* === AMD_dump ============================================================ */ /* ========================================================================= */ /* Dump AMD's data structure, except for the hash buckets. This routine * cannot be called when the hash buckets are non-empty. */ GLOBAL void AMD_dump ( Int n, /* A is n-by-n */ Int Pe [ ], /* pe [0..n-1]: index in iw of start of row i */ Int Iw [ ], /* workspace of size iwlen, iwlen [0..pfree-1] * holds the matrix on input */ Int Len [ ], /* len [0..n-1]: length for row i */ Int iwlen, /* length of iw */ Int pfree, /* iw [pfree ... iwlen-1] is empty on input */ Int Nv [ ], /* nv [0..n-1] */ Int Next [ ], /* next [0..n-1] */ Int Last [ ], /* last [0..n-1] */ Int Head [ ], /* head [0..n-1] */ Int Elen [ ], /* size n */ Int Degree [ ], /* size n */ Int W [ ], /* size n */ Int nel ) { Int i, pe, elen, nv, len, e, p, k, j, deg, w, cnt, ilast ; if (AMD_debug < 0) return ; ASSERT (pfree <= iwlen) ; AMD_DEBUG3 (("\nAMD dump, pfree: "ID"\n", pfree)) ; for (i = 0 ; i < n ; i++) { pe = Pe [i] ; elen = Elen [i] ; nv = Nv [i] ; len = Len [i] ; w = W [i] ; if (elen >= EMPTY) { if (nv == 0) { AMD_DEBUG3 (("\nI "ID": nonprincipal: ", i)) ; ASSERT (elen == EMPTY) ; if (pe == EMPTY) { AMD_DEBUG3 ((" dense node\n")) ; ASSERT (w == 1) ; } else { ASSERT (pe < EMPTY) ; AMD_DEBUG3 ((" i "ID" -> parent "ID"\n", i, FLIP (Pe[i]))); } } else { AMD_DEBUG3 (("\nI "ID": active principal supervariable:\n",i)); AMD_DEBUG3 ((" nv(i): "ID" Flag: %d\n", nv, (nv < 0))) ; ASSERT (elen >= 0) ; ASSERT (nv > 0 && pe >= 0) ; p = pe ; AMD_DEBUG3 ((" e/s: ")) ; if (elen == 0) AMD_DEBUG3 ((" : ")) ; ASSERT (pe + len <= pfree) ; for (k = 0 ; k < len ; k++) { j = Iw [p] ; AMD_DEBUG3 ((" "ID"", j)) ; ASSERT (j >= 0 && j < n) ; if (k == elen-1) AMD_DEBUG3 ((" : ")) ; p++ ; } AMD_DEBUG3 (("\n")) ; } } else { e = i ; if (w == 0) { AMD_DEBUG3 (("\nE "ID": absorbed element: w "ID"\n", e, w)) ; ASSERT (nv > 0 && pe < 0) ; AMD_DEBUG3 ((" e "ID" -> parent "ID"\n", e, FLIP (Pe [e]))) ; } else { AMD_DEBUG3 (("\nE "ID": unabsorbed element: w "ID"\n", e, w)) ; ASSERT (nv > 0 && pe >= 0) ; p = pe ; AMD_DEBUG3 ((" : ")) ; ASSERT (pe + len <= pfree) ; for (k = 0 ; k < len ; k++) { j = Iw [p] ; AMD_DEBUG3 ((" "ID"", j)) ; ASSERT (j >= 0 && j < n) ; p++ ; } AMD_DEBUG3 (("\n")) ; } } } /* this routine cannot be called when the hash buckets are non-empty */ AMD_DEBUG3 (("\nDegree lists:\n")) ; if (nel >= 0) { cnt = 0 ; for (deg = 0 ; deg < n ; deg++) { if (Head [deg] == EMPTY) continue ; ilast = EMPTY ; AMD_DEBUG3 ((ID": \n", deg)) ; for (i = Head [deg] ; i != EMPTY ; i = Next [i]) { AMD_DEBUG3 ((" "ID" : next "ID" last "ID" deg "ID"\n", i, Next [i], Last [i], Degree [i])) ; ASSERT (i >= 0 && i < n && ilast == Last [i] && deg == Degree [i]) ; cnt += Nv [i] ; ilast = i ; } AMD_DEBUG3 (("\n")) ; } ASSERT (cnt == n - nel) ; } } #endif python-igraph-0.8.0/vendor/source/igraph/src/AMD/Source/amd_order.c0000644000076500000240000001337413524616144025355 0ustar tamasstaff00000000000000/* ========================================================================= */ /* === AMD_order =========================================================== */ /* ========================================================================= */ /* ------------------------------------------------------------------------- */ /* AMD, Copyright (c) Timothy A. Davis, */ /* Patrick R. Amestoy, and Iain S. Duff. See ../README.txt for License. */ /* email: DrTimothyAldenDavis@gmail.com */ /* ------------------------------------------------------------------------- */ /* User-callable AMD minimum degree ordering routine. See amd.h for * documentation. */ #include "amd_internal.h" /* ========================================================================= */ /* === AMD_order =========================================================== */ /* ========================================================================= */ GLOBAL Int AMD_order ( Int n, const Int Ap [ ], const Int Ai [ ], Int P [ ], double Control [ ], double Info [ ] ) { Int *Len, *S, nz, i, *Pinv, info, status, *Rp, *Ri, *Cp, *Ci, ok ; size_t nzaat, slen ; double mem = 0 ; #ifndef NDEBUG AMD_debug_init ("amd") ; #endif /* clear the Info array, if it exists */ info = Info != (double *) NULL ; if (info) { for (i = 0 ; i < AMD_INFO ; i++) { Info [i] = EMPTY ; } Info [AMD_N] = n ; Info [AMD_STATUS] = AMD_OK ; } /* make sure inputs exist and n is >= 0 */ if (Ai == (Int *) NULL || Ap == (Int *) NULL || P == (Int *) NULL || n < 0) { if (info) Info [AMD_STATUS] = AMD_INVALID ; return (AMD_INVALID) ; /* arguments are invalid */ } if (n == 0) { return (AMD_OK) ; /* n is 0 so there's nothing to do */ } nz = Ap [n] ; if (info) { Info [AMD_NZ] = nz ; } if (nz < 0) { if (info) Info [AMD_STATUS] = AMD_INVALID ; return (AMD_INVALID) ; } /* check if n or nz will cause size_t overflow */ if (((size_t) n) >= SIZE_T_MAX / sizeof (Int) || ((size_t) nz) >= SIZE_T_MAX / sizeof (Int)) { if (info) Info [AMD_STATUS] = AMD_OUT_OF_MEMORY ; return (AMD_OUT_OF_MEMORY) ; /* problem too large */ } /* check the input matrix: AMD_OK, AMD_INVALID, or AMD_OK_BUT_JUMBLED */ status = AMD_valid (n, n, Ap, Ai) ; if (status == AMD_INVALID) { if (info) Info [AMD_STATUS] = AMD_INVALID ; return (AMD_INVALID) ; /* matrix is invalid */ } /* allocate two size-n integer workspaces */ Len = amd_malloc (n * sizeof (Int)) ; Pinv = amd_malloc (n * sizeof (Int)) ; mem += n ; mem += n ; if (!Len || !Pinv) { /* :: out of memory :: */ amd_free (Len) ; amd_free (Pinv) ; if (info) Info [AMD_STATUS] = AMD_OUT_OF_MEMORY ; return (AMD_OUT_OF_MEMORY) ; } if (status == AMD_OK_BUT_JUMBLED) { /* sort the input matrix and remove duplicate entries */ AMD_DEBUG1 (("Matrix is jumbled\n")) ; Rp = amd_malloc ((n+1) * sizeof (Int)) ; Ri = amd_malloc (MAX (nz,1) * sizeof (Int)) ; mem += (n+1) ; mem += MAX (nz,1) ; if (!Rp || !Ri) { /* :: out of memory :: */ amd_free (Rp) ; amd_free (Ri) ; amd_free (Len) ; amd_free (Pinv) ; if (info) Info [AMD_STATUS] = AMD_OUT_OF_MEMORY ; return (AMD_OUT_OF_MEMORY) ; } /* use Len and Pinv as workspace to create R = A' */ AMD_preprocess (n, Ap, Ai, Rp, Ri, Len, Pinv) ; Cp = Rp ; Ci = Ri ; } else { /* order the input matrix as-is. No need to compute R = A' first */ Rp = NULL ; Ri = NULL ; Cp = (Int *) Ap ; Ci = (Int *) Ai ; } /* --------------------------------------------------------------------- */ /* determine the symmetry and count off-diagonal nonzeros in A+A' */ /* --------------------------------------------------------------------- */ nzaat = AMD_aat (n, Cp, Ci, Len, P, Info) ; AMD_DEBUG1 (("nzaat: %g\n", (double) nzaat)) ; ASSERT ((MAX (nz-n, 0) <= nzaat) && (nzaat <= 2 * (size_t) nz)) ; /* --------------------------------------------------------------------- */ /* allocate workspace for matrix, elbow room, and 6 size-n vectors */ /* --------------------------------------------------------------------- */ S = NULL ; slen = nzaat ; /* space for matrix */ ok = ((slen + nzaat/5) >= slen) ; /* check for size_t overflow */ slen += nzaat/5 ; /* add elbow room */ for (i = 0 ; ok && i < 7 ; i++) { ok = ((slen + n) > slen) ; /* check for size_t overflow */ slen += n ; /* size-n elbow room, 6 size-n work */ } mem += slen ; ok = ok && (slen < SIZE_T_MAX / sizeof (Int)) ; /* check for overflow */ ok = ok && (slen < Int_MAX) ; /* S[i] for Int i must be OK */ if (ok) { S = amd_malloc (slen * sizeof (Int)) ; } AMD_DEBUG1 (("slen %g\n", (double) slen)) ; if (!S) { /* :: out of memory :: (or problem too large) */ amd_free (Rp) ; amd_free (Ri) ; amd_free (Len) ; amd_free (Pinv) ; if (info) Info [AMD_STATUS] = AMD_OUT_OF_MEMORY ; return (AMD_OUT_OF_MEMORY) ; } if (info) { /* memory usage, in bytes. */ Info [AMD_MEMORY] = mem * sizeof (Int) ; } /* --------------------------------------------------------------------- */ /* order the matrix */ /* --------------------------------------------------------------------- */ AMD_1 (n, Cp, Ci, P, Pinv, Len, slen, S, Control, Info) ; /* --------------------------------------------------------------------- */ /* free the workspace */ /* --------------------------------------------------------------------- */ amd_free (Rp) ; amd_free (Ri) ; amd_free (Len) ; amd_free (Pinv) ; amd_free (S) ; if (info) Info [AMD_STATUS] = status ; return (status) ; /* successful ordering */ } python-igraph-0.8.0/vendor/source/igraph/src/AMD/Source/amd_control.c0000644000076500000240000000337213524616144025717 0ustar tamasstaff00000000000000/* ========================================================================= */ /* === AMD_control ========================================================= */ /* ========================================================================= */ /* ------------------------------------------------------------------------- */ /* AMD, Copyright (c) Timothy A. Davis, */ /* Patrick R. Amestoy, and Iain S. Duff. See ../README.txt for License. */ /* email: DrTimothyAldenDavis@gmail.com */ /* ------------------------------------------------------------------------- */ /* User-callable. Prints the control parameters for AMD. See amd.h * for details. If the Control array is not present, the defaults are * printed instead. */ #include "amd_internal.h" GLOBAL void AMD_control ( double Control [ ] ) { double alpha ; Int aggressive ; if (Control != (double *) NULL) { alpha = Control [AMD_DENSE] ; aggressive = Control [AMD_AGGRESSIVE] != 0 ; } else { alpha = AMD_DEFAULT_DENSE ; aggressive = AMD_DEFAULT_AGGRESSIVE ; } PRINTF (("\nAMD version %d.%d.%d, %s: approximate minimum degree ordering\n" " dense row parameter: %g\n", AMD_MAIN_VERSION, AMD_SUB_VERSION, AMD_SUBSUB_VERSION, AMD_DATE, alpha)) ; if (alpha < 0) { PRINTF ((" no rows treated as dense\n")) ; } else { PRINTF (( " (rows with more than max (%g * sqrt (n), 16) entries are\n" " considered \"dense\", and placed last in output permutation)\n", alpha)) ; } if (aggressive) { PRINTF ((" aggressive absorption: yes\n")) ; } else { PRINTF ((" aggressive absorption: no\n")) ; } PRINTF ((" size of AMD integer: %d\n\n", sizeof (Int))) ; } python-igraph-0.8.0/vendor/source/igraph/src/AMD/Source/amd.f0000644000076500000240000014662113524616144024167 0ustar tamasstaff00000000000000C----------------------------------------------------------------------- C AMD: approximate minimum degree, with aggressive absorption C----------------------------------------------------------------------- SUBROUTINE AMD $ (N, PE, IW, LEN, IWLEN, PFREE, NV, NEXT, $ LAST, HEAD, ELEN, DEGREE, NCMPA, W) INTEGER N, IWLEN, PFREE, NCMPA, IW (IWLEN), PE (N), $ DEGREE (N), NV (N), NEXT (N), LAST (N), HEAD (N), $ ELEN (N), W (N), LEN (N) C Given a representation of the nonzero pattern of a symmetric matrix, C A, (excluding the diagonal) perform an approximate minimum C (UMFPACK/MA38-style) degree ordering to compute a pivot order C such that the introduction of nonzeros (fill-in) in the Cholesky C factors A = LL^T are kept low. At each step, the pivot C selected is the one with the minimum UMFPACK/MA38-style C upper-bound on the external degree. C C Aggresive absorption is used to tighten the bound on the degree. C ********************************************************************** C ***** CAUTION: ARGUMENTS ARE NOT CHECKED FOR ERRORS ON INPUT. ****** C ********************************************************************** C References: C C [1] Timothy A. Davis and Iain Duff, "An unsymmetric-pattern C multifrontal method for sparse LU factorization", SIAM J. C Matrix Analysis and Applications, vol. 18, no. 1, pp. C 140-158. Discusses UMFPACK / MA38, which first introduced C the approximate minimum degree used by this routine. C C [2] Patrick Amestoy, Timothy A. Davis, and Iain S. Duff, "An C approximate degree ordering algorithm," SIAM J. Matrix C Analysis and Applications, vol. 17, no. 4, pp. 886-905, C 1996. Discusses AMD, AMDBAR, and MC47B. C C [3] Alan George and Joseph Liu, "The evolution of the minimum C degree ordering algorithm," SIAM Review, vol. 31, no. 1, C pp. 1-19, 1989. We list below the features mentioned in C that paper that this code includes: C C mass elimination: C Yes. MA27 relied on supervariable detection for mass C elimination. C indistinguishable nodes: C Yes (we call these "supervariables"). This was also in C the MA27 code - although we modified the method of C detecting them (the previous hash was the true degree, C which we no longer keep track of). A supervariable is C a set of rows with identical nonzero pattern. All C variables in a supervariable are eliminated together. C Each supervariable has as its numerical name that of C one of its variables (its principal variable). C quotient graph representation: C Yes. We use the term "element" for the cliques formed C during elimination. This was also in the MA27 code. C The algorithm can operate in place, but it will work C more efficiently if given some "elbow room." C element absorption: C Yes. This was also in the MA27 code. C external degree: C Yes. The MA27 code was based on the true degree. C incomplete degree update and multiple elimination: C No. This was not in MA27, either. Our method of C degree update within MC47B/BD is element-based, not C variable-based. It is thus not well-suited for use C with incomplete degree update or multiple elimination. C----------------------------------------------------------------------- C Authors, and Copyright (C) 1995 by: C Timothy A. Davis, Patrick Amestoy, Iain S. Duff, & John K. Reid. C C Acknowledgements: C This work (and the UMFPACK package) was supported by the C National Science Foundation (ASC-9111263 and DMS-9223088). C The UMFPACK/MA38 approximate degree update algorithm, the C unsymmetric analog which forms the basis of MC47B/BD, was C developed while Tim Davis was supported by CERFACS (Toulouse, C France) in a post-doctoral position. C C Date: September, 1995 C----------------------------------------------------------------------- C----------------------------------------------------------------------- C INPUT ARGUMENTS (unaltered): C----------------------------------------------------------------------- C n: The matrix order. C C Restriction: 1 .le. n .lt. (iovflo/2)-2, where iovflo is C the largest positive integer that your computer can represent. C iwlen: The length of iw (1..iwlen). On input, the matrix is C stored in iw (1..pfree-1). However, iw (1..iwlen) should be C slightly larger than what is required to hold the matrix, at C least iwlen .ge. pfree + n is recommended. Otherwise, C excessive compressions will take place. C *** We do not recommend running this algorithm with *** C *** iwlen .lt. pfree + n. *** C *** Better performance will be obtained if *** C *** iwlen .ge. pfree + n *** C *** or better yet *** C *** iwlen .gt. 1.2 * pfree *** C *** (where pfree is its value on input). *** C The algorithm will not run at all if iwlen .lt. pfree-1. C C Restriction: iwlen .ge. pfree-1 C----------------------------------------------------------------------- C INPUT/OUPUT ARGUMENTS: C----------------------------------------------------------------------- C pe: On input, pe (i) is the index in iw of the start of row i, or C zero if row i has no off-diagonal non-zeros. C C During execution, it is used for both supervariables and C elements: C C * Principal supervariable i: index into iw of the C description of supervariable i. A supervariable C represents one or more rows of the matrix C with identical nonzero pattern. C * Non-principal supervariable i: if i has been absorbed C into another supervariable j, then pe (i) = -j. C That is, j has the same pattern as i. C Note that j might later be absorbed into another C supervariable j2, in which case pe (i) is still -j, C and pe (j) = -j2. C * Unabsorbed element e: the index into iw of the description C of element e, if e has not yet been absorbed by a C subsequent element. Element e is created when C the supervariable of the same name is selected as C the pivot. C * Absorbed element e: if element e is absorbed into element C e2, then pe (e) = -e2. This occurs when the pattern of C e (that is, Le) is found to be a subset of the pattern C of e2 (that is, Le2). If element e is "null" (it has C no nonzeros outside its pivot block), then pe (e) = 0. C C On output, pe holds the assembly tree/forest, which implicitly C represents a pivot order with identical fill-in as the actual C order (via a depth-first search of the tree). C C On output: C If nv (i) .gt. 0, then i represents a node in the assembly tree, C and the parent of i is -pe (i), or zero if i is a root. C If nv (i) = 0, then (i,-pe (i)) represents an edge in a C subtree, the root of which is a node in the assembly tree. C pfree: On input the tail end of the array, iw (pfree..iwlen), C is empty, and the matrix is stored in iw (1..pfree-1). C During execution, additional data is placed in iw, and pfree C is modified so that iw (pfree..iwlen) is always the unused part C of iw. On output, pfree is set equal to the size of iw that C would have been needed for no compressions to occur. If C ncmpa is zero, then pfree (on output) is less than or equal to C iwlen, and the space iw (pfree+1 ... iwlen) was not used. C Otherwise, pfree (on output) is greater than iwlen, and all the C memory in iw was used. C----------------------------------------------------------------------- C INPUT/MODIFIED (undefined on output): C----------------------------------------------------------------------- C len: On input, len (i) holds the number of entries in row i of the C matrix, excluding the diagonal. The contents of len (1..n) C are undefined on output. C iw: On input, iw (1..pfree-1) holds the description of each row i C in the matrix. The matrix must be symmetric, and both upper C and lower triangular parts must be present. The diagonal must C not be present. Row i is held as follows: C C len (i): the length of the row i data structure C iw (pe (i) ... pe (i) + len (i) - 1): C the list of column indices for nonzeros C in row i (simple supervariables), excluding C the diagonal. All supervariables start with C one row/column each (supervariable i is just C row i). C if len (i) is zero on input, then pe (i) is ignored C on input. C C Note that the rows need not be in any particular order, C and there may be empty space between the rows. C C During execution, the supervariable i experiences fill-in. C This is represented by placing in i a list of the elements C that cause fill-in in supervariable i: C C len (i): the length of supervariable i C iw (pe (i) ... pe (i) + elen (i) - 1): C the list of elements that contain i. This list C is kept short by removing absorbed elements. C iw (pe (i) + elen (i) ... pe (i) + len (i) - 1): C the list of supervariables in i. This list C is kept short by removing nonprincipal C variables, and any entry j that is also C contained in at least one of the elements C (j in Le) in the list for i (e in row i). C C When supervariable i is selected as pivot, we create an C element e of the same name (e=i): C C len (e): the length of element e C iw (pe (e) ... pe (e) + len (e) - 1): C the list of supervariables in element e. C C An element represents the fill-in that occurs when supervariable C i is selected as pivot (which represents the selection of row i C and all non-principal variables whose principal variable is i). C We use the term Le to denote the set of all supervariables C in element e. Absorbed supervariables and elements are pruned C from these lists when computationally convenient. C C CAUTION: THE INPUT MATRIX IS OVERWRITTEN DURING COMPUTATION. C The contents of iw are undefined on output. C----------------------------------------------------------------------- C OUTPUT (need not be set on input): C----------------------------------------------------------------------- C nv: During execution, abs (nv (i)) is equal to the number of rows C that are represented by the principal supervariable i. If i is C a nonprincipal variable, then nv (i) = 0. Initially, C nv (i) = 1 for all i. nv (i) .lt. 0 signifies that i is a C principal variable in the pattern Lme of the current pivot C element me. On output, nv (e) holds the true degree of element C e at the time it was created (including the diagonal part). C ncmpa: The number of times iw was compressed. If this is C excessive, then the execution took longer than what could have C been. To reduce ncmpa, try increasing iwlen to be 10% or 20% C larger than the value of pfree on input (or at least C iwlen .ge. pfree + n). The fastest performance will be C obtained when ncmpa is returned as zero. If iwlen is set to C the value returned by pfree on *output*, then no compressions C will occur. C elen: See the description of iw above. At the start of execution, C elen (i) is set to zero. During execution, elen (i) is the C number of elements in the list for supervariable i. When e C becomes an element, elen (e) = -nel is set, where nel is the C current step of factorization. elen (i) = 0 is done when i C becomes nonprincipal. C C For variables, elen (i) .ge. 0 holds until just before the C permutation vectors are computed. For elements, C elen (e) .lt. 0 holds. C C On output elen (1..n) holds the inverse permutation (the same C as the 'INVP' argument in Sparspak). That is, if k = elen (i), C then row i is the kth pivot row. Row i of A appears as the C (elen(i))-th row in the permuted matrix, PAP^T. C last: In a degree list, last (i) is the supervariable preceding i, C or zero if i is the head of the list. In a hash bucket, C last (i) is the hash key for i. last (head (hash)) is also C used as the head of a hash bucket if head (hash) contains a C degree list (see head, below). C C On output, last (1..n) holds the permutation (the same as the C 'PERM' argument in Sparspak). That is, if i = last (k), then C row i is the kth pivot row. Row last (k) of A is the k-th row C in the permuted matrix, PAP^T. C----------------------------------------------------------------------- C LOCAL (not input or output - used only during execution): C----------------------------------------------------------------------- C degree: If i is a supervariable, then degree (i) holds the C current approximation of the external degree of row i (an upper C bound). The external degree is the number of nonzeros in row i, C minus abs (nv (i)) (the diagonal part). The bound is equal to C the external degree if elen (i) is less than or equal to two. C C We also use the term "external degree" for elements e to refer C to |Le \ Lme|. If e is an element, then degree (e) holds |Le|, C which is the degree of the off-diagonal part of the element e C (not including the diagonal part). C head: head is used for degree lists. head (deg) is the first C supervariable in a degree list (all supervariables i in a C degree list deg have the same approximate degree, namely, C deg = degree (i)). If the list deg is empty then C head (deg) = 0. C C During supervariable detection head (hash) also serves as a C pointer to a hash bucket. C If head (hash) .gt. 0, there is a degree list of degree hash. C The hash bucket head pointer is last (head (hash)). C If head (hash) = 0, then the degree list and hash bucket are C both empty. C If head (hash) .lt. 0, then the degree list is empty, and C -head (hash) is the head of the hash bucket. C After supervariable detection is complete, all hash buckets C are empty, and the (last (head (hash)) = 0) condition is C restored for the non-empty degree lists. C next: next (i) is the supervariable following i in a link list, or C zero if i is the last in the list. Used for two kinds of C lists: degree lists and hash buckets (a supervariable can be C in only one kind of list at a time). C w: The flag array w determines the status of elements and C variables, and the external degree of elements. C C for elements: C if w (e) = 0, then the element e is absorbed C if w (e) .ge. wflg, then w (e) - wflg is the size of C the set |Le \ Lme|, in terms of nonzeros (the C sum of abs (nv (i)) for each principal variable i that C is both in the pattern of element e and NOT in the C pattern of the current pivot element, me). C if wflg .gt. w (e) .gt. 0, then e is not absorbed and has C not yet been seen in the scan of the element lists in C the computation of |Le\Lme| in loop 150 below. C C for variables: C during supervariable detection, if w (j) .ne. wflg then j is C not in the pattern of variable i C C The w array is initialized by setting w (i) = 1 for all i, C and by setting wflg = 2. It is reinitialized if wflg becomes C too large (to ensure that wflg+n does not cause integer C overflow). C----------------------------------------------------------------------- C LOCAL INTEGERS: C----------------------------------------------------------------------- INTEGER DEG, DEGME, DEXT, DMAX, E, ELENME, ELN, HASH, HMOD, I, $ ILAST, INEXT, J, JLAST, JNEXT, K, KNT1, KNT2, KNT3, $ LENJ, LN, MAXMEM, ME, MEM, MINDEG, NEL, NEWMEM, $ NLEFT, NVI, NVJ, NVPIV, SLENME, WE, WFLG, WNVI, X C deg: the degree of a variable or element C degme: size, |Lme|, of the current element, me (= degree (me)) C dext: external degree, |Le \ Lme|, of some element e C dmax: largest |Le| seen so far C e: an element C elenme: the length, elen (me), of element list of pivotal var. C eln: the length, elen (...), of an element list C hash: the computed value of the hash function C hmod: the hash function is computed modulo hmod = max (1,n-1) C i: a supervariable C ilast: the entry in a link list preceding i C inext: the entry in a link list following i C j: a supervariable C jlast: the entry in a link list preceding j C jnext: the entry in a link list, or path, following j C k: the pivot order of an element or variable C knt1: loop counter used during element construction C knt2: loop counter used during element construction C knt3: loop counter used during compression C lenj: len (j) C ln: length of a supervariable list C maxmem: amount of memory needed for no compressions C me: current supervariable being eliminated, and the C current element created by eliminating that C supervariable C mem: memory in use assuming no compressions have occurred C mindeg: current minimum degree C nel: number of pivots selected so far C newmem: amount of new memory needed for current pivot element C nleft: n - nel, the number of nonpivotal rows/columns remaining C nvi: the number of variables in a supervariable i (= nv (i)) C nvj: the number of variables in a supervariable j (= nv (j)) C nvpiv: number of pivots in current element C slenme: number of variables in variable list of pivotal variable C we: w (e) C wflg: used for flagging the w array. See description of iw. C wnvi: wflg - nv (i) C x: either a supervariable or an element C----------------------------------------------------------------------- C LOCAL POINTERS: C----------------------------------------------------------------------- INTEGER P, P1, P2, P3, PDST, PEND, PJ, PME, PME1, PME2, PN, PSRC C Any parameter (pe (...) or pfree) or local variable C starting with "p" (for Pointer) is an index into iw, C and all indices into iw use variables starting with C "p." The only exception to this rule is the iwlen C input argument. C p: pointer into lots of things C p1: pe (i) for some variable i (start of element list) C p2: pe (i) + elen (i) - 1 for some var. i (end of el. list) C p3: index of first supervariable in clean list C pdst: destination pointer, for compression C pend: end of memory to compress C pj: pointer into an element or variable C pme: pointer into the current element (pme1...pme2) C pme1: the current element, me, is stored in iw (pme1...pme2) C pme2: the end of the current element C pn: pointer into a "clean" variable, also used to compress C psrc: source pointer, for compression C----------------------------------------------------------------------- C FUNCTIONS CALLED: C----------------------------------------------------------------------- INTRINSIC MAX, MIN, MOD C======================================================================= C INITIALIZATIONS C======================================================================= WFLG = 2 MINDEG = 1 NCMPA = 0 NEL = 0 HMOD = MAX (1, N-1) DMAX = 0 MEM = PFREE - 1 MAXMEM = MEM ME = 0 DO 10 I = 1, N LAST (I) = 0 HEAD (I) = 0 NV (I) = 1 W (I) = 1 ELEN (I) = 0 DEGREE (I) = LEN (I) 10 CONTINUE C ---------------------------------------------------------------- C initialize degree lists and eliminate rows with no off-diag. nz. C ---------------------------------------------------------------- DO 20 I = 1, N DEG = DEGREE (I) IF (DEG .GT. 0) THEN C ---------------------------------------------------------- C place i in the degree list corresponding to its degree C ---------------------------------------------------------- INEXT = HEAD (DEG) IF (INEXT .NE. 0) LAST (INEXT) = I NEXT (I) = INEXT HEAD (DEG) = I ELSE C ---------------------------------------------------------- C we have a variable that can be eliminated at once because C there is no off-diagonal non-zero in its row. C ---------------------------------------------------------- NEL = NEL + 1 ELEN (I) = -NEL PE (I) = 0 W (I) = 0 ENDIF 20 CONTINUE C======================================================================= C WHILE (selecting pivots) DO C======================================================================= 30 CONTINUE IF (NEL .LT. N) THEN C======================================================================= C GET PIVOT OF MINIMUM DEGREE C======================================================================= C ------------------------------------------------------------- C find next supervariable for elimination C ------------------------------------------------------------- DO 40 DEG = MINDEG, N ME = HEAD (DEG) IF (ME .GT. 0) GOTO 50 40 CONTINUE 50 CONTINUE MINDEG = DEG C ------------------------------------------------------------- C remove chosen variable from link list C ------------------------------------------------------------- INEXT = NEXT (ME) IF (INEXT .NE. 0) LAST (INEXT) = 0 HEAD (DEG) = INEXT C ------------------------------------------------------------- C me represents the elimination of pivots nel+1 to nel+nv(me). C place me itself as the first in this set. It will be moved C to the nel+nv(me) position when the permutation vectors are C computed. C ------------------------------------------------------------- ELENME = ELEN (ME) ELEN (ME) = - (NEL + 1) NVPIV = NV (ME) NEL = NEL + NVPIV C======================================================================= C CONSTRUCT NEW ELEMENT C======================================================================= C ------------------------------------------------------------- C At this point, me is the pivotal supervariable. It will be C converted into the current element. Scan list of the C pivotal supervariable, me, setting tree pointers and C constructing new list of supervariables for the new element, C me. p is a pointer to the current position in the old list. C ------------------------------------------------------------- C flag the variable "me" as being in Lme by negating nv (me) NV (ME) = -NVPIV DEGME = 0 IF (ELENME .EQ. 0) THEN C ---------------------------------------------------------- C construct the new element in place C ---------------------------------------------------------- PME1 = PE (ME) PME2 = PME1 - 1 DO 60 P = PME1, PME1 + LEN (ME) - 1 I = IW (P) NVI = NV (I) IF (NVI .GT. 0) THEN C ---------------------------------------------------- C i is a principal variable not yet placed in Lme. C store i in new list C ---------------------------------------------------- DEGME = DEGME + NVI C flag i as being in Lme by negating nv (i) NV (I) = -NVI PME2 = PME2 + 1 IW (PME2) = I C ---------------------------------------------------- C remove variable i from degree list. C ---------------------------------------------------- ILAST = LAST (I) INEXT = NEXT (I) IF (INEXT .NE. 0) LAST (INEXT) = ILAST IF (ILAST .NE. 0) THEN NEXT (ILAST) = INEXT ELSE C i is at the head of the degree list HEAD (DEGREE (I)) = INEXT ENDIF ENDIF 60 CONTINUE C this element takes no new memory in iw: NEWMEM = 0 ELSE C ---------------------------------------------------------- C construct the new element in empty space, iw (pfree ...) C ---------------------------------------------------------- P = PE (ME) PME1 = PFREE SLENME = LEN (ME) - ELENME DO 120 KNT1 = 1, ELENME + 1 IF (KNT1 .GT. ELENME) THEN C search the supervariables in me. E = ME PJ = P LN = SLENME ELSE C search the elements in me. E = IW (P) P = P + 1 PJ = PE (E) LN = LEN (E) ENDIF C ------------------------------------------------------- C search for different supervariables and add them to the C new list, compressing when necessary. this loop is C executed once for each element in the list and once for C all the supervariables in the list. C ------------------------------------------------------- DO 110 KNT2 = 1, LN I = IW (PJ) PJ = PJ + 1 NVI = NV (I) IF (NVI .GT. 0) THEN C ------------------------------------------------- C compress iw, if necessary C ------------------------------------------------- IF (PFREE .GT. IWLEN) THEN C prepare for compressing iw by adjusting C pointers and lengths so that the lists being C searched in the inner and outer loops contain C only the remaining entries. PE (ME) = P LEN (ME) = LEN (ME) - KNT1 IF (LEN (ME) .EQ. 0) THEN C nothing left of supervariable me PE (ME) = 0 ENDIF PE (E) = PJ LEN (E) = LN - KNT2 IF (LEN (E) .EQ. 0) THEN C nothing left of element e PE (E) = 0 ENDIF NCMPA = NCMPA + 1 C store first item in pe C set first entry to -item DO 70 J = 1, N PN = PE (J) IF (PN .GT. 0) THEN PE (J) = IW (PN) IW (PN) = -J ENDIF 70 CONTINUE C psrc/pdst point to source/destination PDST = 1 PSRC = 1 PEND = PME1 - 1 C while loop: 80 CONTINUE IF (PSRC .LE. PEND) THEN C search for next negative entry J = -IW (PSRC) PSRC = PSRC + 1 IF (J .GT. 0) THEN IW (PDST) = PE (J) PE (J) = PDST PDST = PDST + 1 C copy from source to destination LENJ = LEN (J) DO 90 KNT3 = 0, LENJ - 2 IW (PDST + KNT3) = IW (PSRC + KNT3) 90 CONTINUE PDST = PDST + LENJ - 1 PSRC = PSRC + LENJ - 1 ENDIF GOTO 80 ENDIF C move the new partially-constructed element P1 = PDST DO 100 PSRC = PME1, PFREE - 1 IW (PDST) = IW (PSRC) PDST = PDST + 1 100 CONTINUE PME1 = P1 PFREE = PDST PJ = PE (E) P = PE (ME) ENDIF C ------------------------------------------------- C i is a principal variable not yet placed in Lme C store i in new list C ------------------------------------------------- DEGME = DEGME + NVI C flag i as being in Lme by negating nv (i) NV (I) = -NVI IW (PFREE) = I PFREE = PFREE + 1 C ------------------------------------------------- C remove variable i from degree link list C ------------------------------------------------- ILAST = LAST (I) INEXT = NEXT (I) IF (INEXT .NE. 0) LAST (INEXT) = ILAST IF (ILAST .NE. 0) THEN NEXT (ILAST) = INEXT ELSE C i is at the head of the degree list HEAD (DEGREE (I)) = INEXT ENDIF ENDIF 110 CONTINUE IF (E .NE. ME) THEN C set tree pointer and flag to indicate element e is C absorbed into new element me (the parent of e is me) PE (E) = -ME W (E) = 0 ENDIF 120 CONTINUE PME2 = PFREE - 1 C this element takes newmem new memory in iw (possibly zero) NEWMEM = PFREE - PME1 MEM = MEM + NEWMEM MAXMEM = MAX (MAXMEM, MEM) ENDIF C ------------------------------------------------------------- C me has now been converted into an element in iw (pme1..pme2) C ------------------------------------------------------------- C degme holds the external degree of new element DEGREE (ME) = DEGME PE (ME) = PME1 LEN (ME) = PME2 - PME1 + 1 C ------------------------------------------------------------- C make sure that wflg is not too large. With the current C value of wflg, wflg+n must not cause integer overflow C ------------------------------------------------------------- IF (WFLG + N .LE. WFLG) THEN DO 130 X = 1, N IF (W (X) .NE. 0) W (X) = 1 130 CONTINUE WFLG = 2 ENDIF C======================================================================= C COMPUTE (w (e) - wflg) = |Le\Lme| FOR ALL ELEMENTS C======================================================================= C ------------------------------------------------------------- C Scan 1: compute the external degrees of previous elements C with respect to the current element. That is: C (w (e) - wflg) = |Le \ Lme| C for each element e that appears in any supervariable in Lme. C The notation Le refers to the pattern (list of C supervariables) of a previous element e, where e is not yet C absorbed, stored in iw (pe (e) + 1 ... pe (e) + iw (pe (e))). C The notation Lme refers to the pattern of the current element C (stored in iw (pme1..pme2)). If (w (e) - wflg) becomes C zero, then the element e will be absorbed in scan 2. C ------------------------------------------------------------- DO 150 PME = PME1, PME2 I = IW (PME) ELN = ELEN (I) IF (ELN .GT. 0) THEN C note that nv (i) has been negated to denote i in Lme: NVI = -NV (I) WNVI = WFLG - NVI DO 140 P = PE (I), PE (I) + ELN - 1 E = IW (P) WE = W (E) IF (WE .GE. WFLG) THEN C unabsorbed element e has been seen in this loop WE = WE - NVI ELSE IF (WE .NE. 0) THEN C e is an unabsorbed element C this is the first we have seen e in all of Scan 1 WE = DEGREE (E) + WNVI ENDIF W (E) = WE 140 CONTINUE ENDIF 150 CONTINUE C======================================================================= C DEGREE UPDATE AND ELEMENT ABSORPTION C======================================================================= C ------------------------------------------------------------- C Scan 2: for each i in Lme, sum up the degree of Lme (which C is degme), plus the sum of the external degrees of each Le C for the elements e appearing within i, plus the C supervariables in i. Place i in hash list. C ------------------------------------------------------------- DO 180 PME = PME1, PME2 I = IW (PME) P1 = PE (I) P2 = P1 + ELEN (I) - 1 PN = P1 HASH = 0 DEG = 0 C ---------------------------------------------------------- C scan the element list associated with supervariable i C ---------------------------------------------------------- DO 160 P = P1, P2 E = IW (P) C dext = | Le \ Lme | DEXT = W (E) - WFLG IF (DEXT .GT. 0) THEN DEG = DEG + DEXT IW (PN) = E PN = PN + 1 HASH = HASH + E ELSE IF (DEXT .EQ. 0) THEN C aggressive absorption: e is not adjacent to me, but C the |Le \ Lme| is 0, so absorb it into me PE (E) = -ME W (E) = 0 ELSE C element e has already been absorbed, due to C regular absorption, in do loop 120 above. Ignore it. CONTINUE ENDIF 160 CONTINUE C count the number of elements in i (including me): ELEN (I) = PN - P1 + 1 C ---------------------------------------------------------- C scan the supervariables in the list associated with i C ---------------------------------------------------------- P3 = PN DO 170 P = P2 + 1, P1 + LEN (I) - 1 J = IW (P) NVJ = NV (J) IF (NVJ .GT. 0) THEN C j is unabsorbed, and not in Lme. C add to degree and add to new list DEG = DEG + NVJ IW (PN) = J PN = PN + 1 HASH = HASH + J ENDIF 170 CONTINUE C ---------------------------------------------------------- C update the degree and check for mass elimination C ---------------------------------------------------------- IF (DEG .EQ. 0) THEN C ------------------------------------------------------- C mass elimination C ------------------------------------------------------- C There is nothing left of this node except for an C edge to the current pivot element. elen (i) is 1, C and there are no variables adjacent to node i. C Absorb i into the current pivot element, me. PE (I) = -ME NVI = -NV (I) DEGME = DEGME - NVI NVPIV = NVPIV + NVI NEL = NEL + NVI NV (I) = 0 ELEN (I) = 0 ELSE C ------------------------------------------------------- C update the upper-bound degree of i C ------------------------------------------------------- C the following degree does not yet include the size C of the current element, which is added later: DEGREE (I) = MIN (DEGREE (I), DEG) C ------------------------------------------------------- C add me to the list for i C ------------------------------------------------------- C move first supervariable to end of list IW (PN) = IW (P3) C move first element to end of element part of list IW (P3) = IW (P1) C add new element to front of list. IW (P1) = ME C store the new length of the list in len (i) LEN (I) = PN - P1 + 1 C ------------------------------------------------------- C place in hash bucket. Save hash key of i in last (i). C ------------------------------------------------------- HASH = MOD (HASH, HMOD) + 1 J = HEAD (HASH) IF (J .LE. 0) THEN C the degree list is empty, hash head is -j NEXT (I) = -J HEAD (HASH) = -I ELSE C degree list is not empty C use last (head (hash)) as hash head NEXT (I) = LAST (J) LAST (J) = I ENDIF LAST (I) = HASH ENDIF 180 CONTINUE DEGREE (ME) = DEGME C ------------------------------------------------------------- C Clear the counter array, w (...), by incrementing wflg. C ------------------------------------------------------------- DMAX = MAX (DMAX, DEGME) WFLG = WFLG + DMAX C make sure that wflg+n does not cause integer overflow IF (WFLG + N .LE. WFLG) THEN DO 190 X = 1, N IF (W (X) .NE. 0) W (X) = 1 190 CONTINUE WFLG = 2 ENDIF C at this point, w (1..n) .lt. wflg holds C======================================================================= C SUPERVARIABLE DETECTION C======================================================================= DO 250 PME = PME1, PME2 I = IW (PME) IF (NV (I) .LT. 0) THEN C i is a principal variable in Lme C ------------------------------------------------------- C examine all hash buckets with 2 or more variables. We C do this by examing all unique hash keys for super- C variables in the pattern Lme of the current element, me C ------------------------------------------------------- HASH = LAST (I) C let i = head of hash bucket, and empty the hash bucket J = HEAD (HASH) IF (J .EQ. 0) GOTO 250 IF (J .LT. 0) THEN C degree list is empty I = -J HEAD (HASH) = 0 ELSE C degree list is not empty, restore last () of head I = LAST (J) LAST (J) = 0 ENDIF IF (I .EQ. 0) GOTO 250 C while loop: 200 CONTINUE IF (NEXT (I) .NE. 0) THEN C ---------------------------------------------------- C this bucket has one or more variables following i. C scan all of them to see if i can absorb any entries C that follow i in hash bucket. Scatter i into w. C ---------------------------------------------------- LN = LEN (I) ELN = ELEN (I) C do not flag the first element in the list (me) DO 210 P = PE (I) + 1, PE (I) + LN - 1 W (IW (P)) = WFLG 210 CONTINUE C ---------------------------------------------------- C scan every other entry j following i in bucket C ---------------------------------------------------- JLAST = I J = NEXT (I) C while loop: 220 CONTINUE IF (J .NE. 0) THEN C ------------------------------------------------- C check if j and i have identical nonzero pattern C ------------------------------------------------- IF (LEN (J) .NE. LN) THEN C i and j do not have same size data structure GOTO 240 ENDIF IF (ELEN (J) .NE. ELN) THEN C i and j do not have same number of adjacent el GOTO 240 ENDIF C do not flag the first element in the list (me) DO 230 P = PE (J) + 1, PE (J) + LN - 1 IF (W (IW (P)) .NE. WFLG) THEN C an entry (iw(p)) is in j but not in i GOTO 240 ENDIF 230 CONTINUE C ------------------------------------------------- C found it! j can be absorbed into i C ------------------------------------------------- PE (J) = -I C both nv (i) and nv (j) are negated since they C are in Lme, and the absolute values of each C are the number of variables in i and j: NV (I) = NV (I) + NV (J) NV (J) = 0 ELEN (J) = 0 C delete j from hash bucket J = NEXT (J) NEXT (JLAST) = J GOTO 220 C ------------------------------------------------- 240 CONTINUE C j cannot be absorbed into i C ------------------------------------------------- JLAST = J J = NEXT (J) GOTO 220 ENDIF C ---------------------------------------------------- C no more variables can be absorbed into i C go to next i in bucket and clear flag array C ---------------------------------------------------- WFLG = WFLG + 1 I = NEXT (I) IF (I .NE. 0) GOTO 200 ENDIF ENDIF 250 CONTINUE C======================================================================= C RESTORE DEGREE LISTS AND REMOVE NONPRINCIPAL SUPERVAR. FROM ELEMENT C======================================================================= P = PME1 NLEFT = N - NEL DO 260 PME = PME1, PME2 I = IW (PME) NVI = -NV (I) IF (NVI .GT. 0) THEN C i is a principal variable in Lme C restore nv (i) to signify that i is principal NV (I) = NVI C ------------------------------------------------------- C compute the external degree (add size of current elem) C ------------------------------------------------------- DEG = MIN (DEGREE (I) + DEGME - NVI, NLEFT - NVI) C ------------------------------------------------------- C place the supervariable at the head of the degree list C ------------------------------------------------------- INEXT = HEAD (DEG) IF (INEXT .NE. 0) LAST (INEXT) = I NEXT (I) = INEXT LAST (I) = 0 HEAD (DEG) = I C ------------------------------------------------------- C save the new degree, and find the minimum degree C ------------------------------------------------------- MINDEG = MIN (MINDEG, DEG) DEGREE (I) = DEG C ------------------------------------------------------- C place the supervariable in the element pattern C ------------------------------------------------------- IW (P) = I P = P + 1 ENDIF 260 CONTINUE C======================================================================= C FINALIZE THE NEW ELEMENT C======================================================================= NV (ME) = NVPIV + DEGME C nv (me) is now the degree of pivot (including diagonal part) C save the length of the list for the new element me LEN (ME) = P - PME1 IF (LEN (ME) .EQ. 0) THEN C there is nothing left of the current pivot element PE (ME) = 0 W (ME) = 0 ENDIF IF (NEWMEM .NE. 0) THEN C element was not constructed in place: deallocate part C of it (final size is less than or equal to newmem, C since newly nonprincipal variables have been removed). PFREE = P MEM = MEM - NEWMEM + LEN (ME) ENDIF C======================================================================= C END WHILE (selecting pivots) GOTO 30 ENDIF C======================================================================= C======================================================================= C COMPUTE THE PERMUTATION VECTORS C======================================================================= C ---------------------------------------------------------------- C The time taken by the following code is O(n). At this C point, elen (e) = -k has been done for all elements e, C and elen (i) = 0 has been done for all nonprincipal C variables i. At this point, there are no principal C supervariables left, and all elements are absorbed. C ---------------------------------------------------------------- C ---------------------------------------------------------------- C compute the ordering of unordered nonprincipal variables C ---------------------------------------------------------------- DO 290 I = 1, N IF (ELEN (I) .EQ. 0) THEN C ---------------------------------------------------------- C i is an un-ordered row. Traverse the tree from i until C reaching an element, e. The element, e, was the C principal supervariable of i and all nodes in the path C from i to when e was selected as pivot. C ---------------------------------------------------------- J = -PE (I) C while (j is a variable) do: 270 CONTINUE IF (ELEN (J) .GE. 0) THEN J = -PE (J) GOTO 270 ENDIF E = J C ---------------------------------------------------------- C get the current pivot ordering of e C ---------------------------------------------------------- K = -ELEN (E) C ---------------------------------------------------------- C traverse the path again from i to e, and compress the C path (all nodes point to e). Path compression allows C this code to compute in O(n) time. Order the unordered C nodes in the path, and place the element e at the end. C ---------------------------------------------------------- J = I C while (j is a variable) do: 280 CONTINUE IF (ELEN (J) .GE. 0) THEN JNEXT = -PE (J) PE (J) = -E IF (ELEN (J) .EQ. 0) THEN C j is an unordered row ELEN (J) = K K = K + 1 ENDIF J = JNEXT GOTO 280 ENDIF C leave elen (e) negative, so we know it is an element ELEN (E) = -K ENDIF 290 CONTINUE C ---------------------------------------------------------------- C reset the inverse permutation (elen (1..n)) to be positive, C and compute the permutation (last (1..n)). C ---------------------------------------------------------------- DO 300 I = 1, N K = ABS (ELEN (I)) LAST (K) = I ELEN (I) = K 300 CONTINUE C======================================================================= C RETURN THE MEMORY USAGE IN IW C======================================================================= C If maxmem is less than or equal to iwlen, then no compressions C occurred, and iw (maxmem+1 ... iwlen) was unused. Otherwise C compressions did occur, and iwlen would have had to have been C greater than or equal to maxmem for no compressions to occur. C Return the value of maxmem in the pfree argument. PFREE = MAXMEM RETURN END python-igraph-0.8.0/vendor/source/igraph/src/AMD/README.txt0000644000076500000240000002130113524616144023500 0ustar tamasstaff00000000000000AMD, Copyright (c) 2009-2012 by Timothy A. Davis (http://www.suitesparse.com), Patrick R. Amestoy, and Iain S. Duff. All Rights Reserved. AMD is available under alternate licences; contact T. Davis for details. AMD: a set of routines for permuting sparse matrices prior to factorization. Includes a version in C, a version in Fortran, and a MATLAB mexFunction. Requires SuiteSparse_config, in the ../SuiteSparse_config directory relative to this directory. Quick start (Unix, or Windows with Cygwin): To compile, test, and install AMD, you may wish to first configure the installation by editting the ../SuiteSparse_config/SuiteSparse_config.mk file. Next, cd to this directory (AMD) and type "make" (or "make lib" if you do not have MATLAB). To compile and run a demo program for the Fortran version, type "make fortran". When done, type "make clean" to remove unused *.o files (keeps the compiled libraries and demo programs). See the User Guide (Doc/AMD_UserGuide.pdf), or ../SuiteSparse_config/SuiteSparse_config.mk for more details. Quick start (for MATLAB users); To compile, test, and install the AMD mexFunction, cd to the AMD/MATLAB directory and type amd_make at the MATLAB prompt. ------------------------------------------------------------------------------- AMD License: Your use or distribution of AMD or any modified version of AMD implies that you agree to this License. This library is free software; you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation; either version 2.1 of the License, or (at your option) any later version. This library is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with this library; if not, write to the Free Software Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA Permission is hereby granted to use or copy this program under the terms of the GNU LGPL, provided that the Copyright, this License, and the Availability of the original version is retained on all copies. User documentation of any code that uses this code or any modified version of this code must cite the Copyright, this License, the Availability note, and "Used by permission." Permission to modify the code and to distribute modified code is granted, provided the Copyright, this License, and the Availability note are retained, and a notice that the code was modified is included. Availability: http://www.suitesparse.com ------------------------------------------------------------------------------- This is the AMD README file. It is a terse overview of AMD. Refer to the User Guide (Doc/AMD_UserGuide.pdf) for how to install and use AMD. Description: AMD is a set of routines for pre-ordering sparse matrices prior to Cholesky or LU factorization, using the approximate minimum degree ordering algorithm. Written in ANSI/ISO C with a MATLAB interface, and in Fortran 77. Authors: Timothy A. Davis (DrTimothyAldenDavis@gmail.com) Patrick R. Amestory, ENSEEIHT, Toulouse, France. Iain S. Duff, Rutherford Appleton Laboratory, UK. Acknowledgements: This work was supported by the National Science Foundation, under grants DMS-9504974, DMS-9803599, and CCR-0203270. Portions of this work were done while on sabbatical at Stanford University and Lawrence Berkeley National Laboratory (with funding from the SciDAC program). I would like to thank Gene Golub, Esmond Ng, and Horst Simon for making this sabbatical possible. ------------------------------------------------------------------------------- Files and directories in the AMD distribution: ------------------------------------------------------------------------------- --------------------------------------------------------------------------- Subdirectories of the AMD directory: --------------------------------------------------------------------------- Doc documentation Source primary source code Include include file for use in your code that calls AMD Demo demo programs. also serves as test of the AMD installation. MATLAB AMD mexFunction for MATLAB, and supporting m-files Lib where the compiled C-callable and Fortran-callable AMD libraries placed. --------------------------------------------------------------------------- Files in the AMD directory: --------------------------------------------------------------------------- Makefile top-level Makefile for GNU make or original make. Windows users would require Cygwin to use "make" README.txt this file --------------------------------------------------------------------------- Doc directory: documentation --------------------------------------------------------------------------- ChangeLog change log License the AMD License Makefile for creating the documentation AMD_UserGuide.bib AMD User Guide (references) AMD_UserGuide.tex AMD User Guide (LaTeX) AMD_UserGuide.pdf AMD User Guide (PDF) lesser.txt the GNU LGPL license --------------------------------------------------------------------------- Source directory: --------------------------------------------------------------------------- amd_order.c user-callable, primary AMD ordering routine amd_control.c user-callable, prints the control parameters amd_defaults.c user-callable, sets default control parameters amd_info.c user-callable, prints the statistics from AMD amd_1.c non-user-callable, construct A+A' amd_2.c user-callable, primary ordering kernel (a C version of amd.f and amdbar.f, with post-ordering added) amd_aat.c non-user-callable, computes nnz (A+A') amd_dump.c non-user-callable, debugging routines amd_postorder.c non-user-callable, postorder amd_post_tree.c non-user-callable, postorder just one tree amd_valid.c non-user-callable, verifies a matrix amd_preprocess.c non-user-callable, computes A', removes duplic amd.f user-callable Fortran 77 version amdbar.f user-callable Fortran 77 version --------------------------------------------------------------------------- Include directory: --------------------------------------------------------------------------- amd.h include file for C programs that use AMD amd_internal.h non-user-callable, include file for AMD --------------------------------------------------------------------------- Demo directory: --------------------------------------------------------------------------- Makefile for GNU make or original make amd_demo.c C demo program for AMD amd_demo.out output of amd_demo.c amd_demo2.c C demo program for AMD, jumbled matrix amd_demo2.out output of amd_demo2.c amd_l_demo.c C demo program for AMD (long integer version) amd_l_demo.out output of amd_l_demo.c amd_simple.c simple C demo program for AMD amd_simple.out output of amd_simple.c amd_f77demo.f Fortran 77 demo program for AMD amd_f77demo.out output of amd_f77demo.f amd_f77simple.c simple Fortran 77 demo program for AMD amd_f77simple.out output of amd_f77simple.f amd_f77cross.f Fortran 77 demo, calls the C version of AMD amd_f77cross.out output of amd_f77cross.f amd_f77wrapper.c Fortran-callable wrapper for C version of AMD --------------------------------------------------------------------------- MATLAB directory: --------------------------------------------------------------------------- GNUmakefile a nice Makefile, for GNU make Makefile an ugly Unix Makefile (for older make's) Contents.m for "help amd2" listing of toolbox contents amd2.m MATLAB help file for AMD amd_make.m MATLAB m-file for compiling AMD mexFunction amd_install.m compile and install the AMD mexFunction amd_mex.c AMD mexFunction for MATLAB amd_demo.m MATLAB demo for AMD amd_demo.m.out diary output of amd_demo.m can_24.mat input file for AMD demo --------------------------------------------------------------------------- Lib directory: libamd.a and libamdf77.a libraries placed here --------------------------------------------------------------------------- GNUmakefile a nice Makefile, for GNU make Makefile an ugly Unix Makefile (for older make's) libamd.def AMD definitions for Windows python-igraph-0.8.0/vendor/source/igraph/src/NetDataTypes.h0000644000076500000240000005767313614300625024136 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ /* The original version of this file was written by Jörg Reichardt The original copyright notice follows here */ /*************************************************************************** NetDataTypes.h - description ------------------- begin : Mon Oct 6 2003 copyright : (C) 2003 by Joerg Reichardt email : reichardt@mitte ***************************************************************************/ /*************************************************************************** * * * This program is free software; you can redistribute it and/or modify * * it under the terms of the GNU General Public License as published by * * the Free Software Foundation; either version 2 of the License, or * * (at your option) any later version. * * * ***************************************************************************/ #ifndef NETDATATYPES_H #define NETDATATYPES_H #include //########################################################################################### struct HUGE_INDEX { unsigned int field_index; unsigned long in_field_index; }; template class HugeArray { private: unsigned long int size; unsigned int highest_field_index; unsigned long max_bit_left; unsigned long max_index; DATA *data; DATA *fields[32]; public: HUGE_INDEX get_huge_index(unsigned long); DATA &Set(unsigned long); DATA Get(unsigned long); HugeArray(void); ~HugeArray(void); DATA &operator[](unsigned long); unsigned long Size(void) { return max_index; } } ; //############################################################################################### template class DLList; template class DL_Indexed_List; template class ClusterList; template class DLList_Iter; template class DLItem { friend class DLList ; friend class DL_Indexed_List; friend class DLList_Iter; private: L_DATA item; unsigned long index; DLItem *previous; DLItem *next; DLItem(L_DATA i, unsigned long ind); DLItem(L_DATA i, unsigned long ind, DLItem *p, DLItem *n); ~DLItem(); public: void del() { delete item; } }; template class DLList { friend class DLList_Iter; protected: DLItem *head; DLItem *tail; unsigned long number_of_items; DLItem *pInsert(L_DATA, DLItem*); L_DATA pDelete(DLItem*); public: DLList(void); ~DLList(); unsigned long Size(void) { return number_of_items; } int Insert(L_DATA, unsigned long); int Delete(unsigned long); int fDelete(L_DATA); L_DATA Push(L_DATA); L_DATA Pop(void); L_DATA Get(unsigned long); int Enqueue(L_DATA); L_DATA Dequeue(void); unsigned long Is_In_List(L_DATA); void delete_items(); }; template class DL_Indexed_List : virtual public DLList { friend class DLList_Iter; private: DLItem *pInsert(L_DATA, DLItem*); L_DATA pDelete(DLItem*); HugeArray*> array; unsigned long last_index; public: DL_Indexed_List(void); ~DL_Indexed_List(); L_DATA Push(L_DATA); L_DATA Pop(void); L_DATA Get(unsigned long); }; //##################################################################################################### template class DLList_Iter { private: DLList *list; DLItem *current; bool end_reached; public: DLList_Iter(void); ~DLList_Iter() { end_reached = true; }; L_DATA Next(void); L_DATA Previous(void); L_DATA First(DLList *l); L_DATA Last(DLList *l); bool End(void) { return end_reached; } DLItem *Get_Current(void) { return current; } L_DATA Get_Current_Item(void) { return current->item; } void Set_Current(DLItem *c) { current = c; } void Set_Status(bool s) { end_reached = s; } bool Swap(DLList_Iter); //swapt die beiden Elemente, wenn sie in der gleichen Liste stehen!! }; //##################################################################################################### struct RGBcolor { unsigned int red; unsigned int green; unsigned int blue; char pajek_c[20]; }; //------------------------------------------------------------------------------- class NLink; class NNode { friend class NLink; private : unsigned long index; unsigned long cluster_index; unsigned long marker, affiliations; unsigned long *state_history; unsigned int max_states; long distance; double clustering; double weight; double affinity; // double old_weight; DLList *neighbours; //list with pointers to neighbours DLList *n_links; DLList *global_link_list; char name[255]; RGBcolor color; public : NNode(unsigned long, unsigned long, DLList*, char*, int); ~NNode(); unsigned long Get_Index(void) { return (index); } unsigned long Get_ClusterIndex(void) { return (cluster_index); } unsigned long Get_Marker(void) { return marker; } void Set_Marker(unsigned long m) { marker = m; } unsigned long Get_Affiliations(void) { return affiliations; } void Set_Affiliations(unsigned long m) { affiliations = m; } void Set_ClusterIndex(unsigned long ci) { cluster_index = ci; return; } void Set_Index(unsigned long i) { index = i; return; } unsigned long Get_Degree(void) { return (neighbours->Size()); } char *Get_Name(void) { return name; } void Set_Name(char* n) { strcpy(name, n); } double Get_Links_Among_Neigbours(void); double Get_Clustering(void); double Get_Weight(void) { return weight; } double Get_Affinity(void) { return affinity; } unsigned long *Get_StateHistory(void) { return state_history; } void Add_StateHistory(unsigned int q); // double Get_OldWeight(void) {return old_weight;} void Set_Weight(double w) { weight = w; } void Set_Affinity(double w) { affinity = w; } // void Set_OldWeight(double w) {old_weight=w;} long Get_Distance(void) { return distance; } void Set_Distance(long d) { distance = d; } int Connect_To(NNode*, double); DLList *Get_Neighbours(void) { return neighbours; } DLList *Get_Links(void) { return n_links; } int Disconnect_From(NNode*); int Disconnect_From_All(void); bool Is_Linked_To(NNode*); RGBcolor Get_Color(void) { return color; } void Set_Color(RGBcolor c); NLink *Get_LinkToNeighbour(NNode *neighbour); }; //##################################################################################################### class NLink { friend class NNode; private : NNode *start; NNode *end; double weight; double old_weight; unsigned long index; unsigned long marker; public : NLink( NNode*, NNode*, double); ~NLink(); unsigned long Get_Start_Index(void) { return (start->Get_Index()); } unsigned long Get_End_Index(void) { return (end->Get_Index()); } NNode *Get_Start(void) { return (start); } NNode *Get_End(void) { return (end); } double Get_Weight(void) { return weight; } void Set_Weight(double w) { weight = w; } double Get_OldWeight(void) { return old_weight; } void Set_OldWeight(double w) { old_weight = w; } unsigned long Get_Marker(void) { return marker; } void Set_Marker(unsigned long m) { marker = m; } unsigned long Get_Index() { return index; } void Set_Index(unsigned long i) { index = i; } }; //##################################################################################################### template class ClusterList : public DLList { friend class DLList_Iter; private: long links_out_of_cluster; unsigned long links_inside_cluster; unsigned long frequency; double cluster_energy; DLList *candidates; long marker; public: ClusterList(void); ~ClusterList(); long Get_Links_OOC(void) { return (links_out_of_cluster); } void Set_Links_OOC(long looc) { links_out_of_cluster = looc; } unsigned long Get_Links_IC(void) { return (links_inside_cluster); } unsigned long Get_Frequency(void) { return (frequency); } void IncreaseFrequency(void) { frequency++; } void Set_Links_IC(unsigned long lic) { links_inside_cluster = lic; } double Get_Energy(void) { return (cluster_energy); } void Set_Energy(double e) { cluster_energy = e; } DLList *Get_Candidates(void) { return candidates; } bool operator<(ClusterList &b); bool operator==(ClusterList &b); long Get_Marker(void) { return marker; } void Set_Marker(long m) { marker = m; } }; //##################################################################################################### template class DL_Node_List : virtual public DL_Indexed_List { friend class DLList_Iter; private: DLItem *pInsert(NNode*, DLItem*); NNode* pDelete(DLItem*); HugeArray*> array; unsigned long last_index; public: DL_Node_List(void); ~DL_Node_List(); NNode* Push(NNode*); NNode* Pop(void); NNode* Get(unsigned long); int Delete(unsigned long); }; //##################################################################################################### struct cluster_join_move { ClusterList *c1; ClusterList *c2; double joint_energy; long joint_looc; unsigned long joint_lic; } ; struct network { DL_Indexed_List *node_list; DL_Indexed_List *link_list; DL_Indexed_List*> *cluster_list; DL_Indexed_List *moveset; unsigned long max_k; unsigned long min_k; unsigned long diameter; double av_weight; double max_weight; double min_weight; double sum_weights; double av_k; double av_bids; unsigned long max_bids; unsigned long min_bids; unsigned long sum_bids; } ; /* struct network { DLList *node_list; DLList *link_list; DLList*> *cluster_list; DLList *moveset; } ; */ template HugeArray::HugeArray(void) { max_bit_left = 1 << 31; //wir setzen das 31. Bit auf 1 size = 2; max_index = 0; highest_field_index = 0; data = new DATA[2]; //ein extra Platz fuer das Nullelement data[0] = 0; data[1] = 0; for (int i = 0; i < 32; i++) { fields[i] = NULL; } fields[highest_field_index] = data; } template HugeArray::~HugeArray(void) { for (unsigned int i = 0; i <= highest_field_index; i++) { data = fields[i]; delete [] data; } } template HUGE_INDEX HugeArray::get_huge_index(unsigned long index) { HUGE_INDEX h_index; unsigned int shift_index = 0; unsigned long help_index; help_index = index; if (index < 2) { h_index.field_index = 0; h_index.in_field_index = index; return h_index; } // wie oft muessen wir help_index nach links shiften, damit das 31. Bit gesetzt ist?? while (!(max_bit_left & help_index)) { help_index <<= 1; shift_index++; } h_index.field_index = 31 - shift_index; // das hoechste besetzte Bit im Index help_index = 1 << h_index.field_index; // in help_index wird das hoechste besetzte Bit von Index gesetzt h_index.in_field_index = (index ^ help_index); // index XOR help_index, womit alle bits unter dem hoechsten erhalten bleiben return h_index; } template DATA &HugeArray::Set(unsigned long int index) { HUGE_INDEX h_index; unsigned long data_size; while (size < index + 1) { highest_field_index++; data_size = 1 << highest_field_index; data = new DATA[data_size]; for (unsigned long i = 0; i < data_size; i++) { data[i] = 0; } size = size + data_size; //overflow noch abfangen //printf("Vergroesserung auf: %u bei index %u\n",size,index); fields[highest_field_index] = data; } h_index = get_huge_index(index); //printf("index %lu = %lu . %lu\n",index,h_index.field_index,h_index.in_field_index); data = fields[h_index.field_index]; if (max_index < index) { max_index = index; } return (data[h_index.in_field_index]); } template DATA HugeArray::Get(unsigned long index) { return (Set(index)); } template DATA &HugeArray::operator[](unsigned long index) { return (Set(index)); } //############################################################################### template DLItem::DLItem(L_DATA i, unsigned long ind) : item(i), index(ind), previous(0), next(0) { } template DLItem::DLItem(L_DATA i, unsigned long ind, DLItem *p, DLItem *n) : item(i), index(ind), previous(p), next(n) { } template DLItem::~DLItem() { //delete item; //eigentlich muessten wir pruefen, ob item ueberhaupt ein Pointer ist... //previous=NULL; //next=NULL; } //###################################################################################################################### template DLList::DLList(void) { head = tail = NULL; number_of_items = 0; head = new DLItem(NULL, 0); //fuer head und Tail gibt es das gleiche Array-Element!! Vorsicht!! tail = new DLItem(NULL, 0); if ( !head || !tail ) { if (head) { delete (head); } if (tail) { delete (tail); } return; } else { head->next = tail; tail->previous = head; } } template DLList::~DLList() { DLItem *cur = head, *next; while (cur) { next = cur->next; delete (cur); cur = next; } number_of_items = 0; // printf("Liste Zerstoert!\n"); } template void DLList::delete_items() { DLItem *cur, *next; cur = this->head; while (cur) { next = cur->next; cur->del(); cur = next; } this->number_of_items = 0; } //privates Insert template DLItem *DLList::pInsert(L_DATA data, DLItem *pos) { DLItem *i = new DLItem(data, number_of_items + 1, pos->previous, pos); if (i) { pos->previous->next = i; pos->previous = i; number_of_items++; return (i); } else { return (0); } } //privates delete template L_DATA DLList::pDelete(DLItem *i) { L_DATA data = i->item; i->previous->next = i->next; i->next->previous = i->previous; // array[i->index]=0; delete (i); number_of_items--; return (data); } //oeffentliches Insert template int DLList::Insert(L_DATA data, unsigned long pos) { if ((pos < 0) || (pos > (number_of_items))) { return (0); } DLItem *cur = head; while (pos--) { cur = cur->next; } return (pInsert(data, cur) != 0); } //oeffentliche Delete template int DLList::Delete(unsigned long pos) { if ((pos < 0) || (pos > (number_of_items))) { return (0); } DLItem *cur = head; while (pos--) { cur = cur->next; } return (pDelete(cur) != 0); } //oeffentliche Delete template int DLList::fDelete(L_DATA data) { if ((number_of_items == 0) || (!data)) { return (0); } DLItem *cur; cur = head->next; while ((cur != tail) && (cur->item != data)) { cur = cur->next; } if (cur != tail) { return (pDelete(cur) != 0); } return (0); } template L_DATA DLList::Push(L_DATA data) { DLItem *tmp; tmp = pInsert(data, tail); if (tmp) { return (tmp->item); } return (0); } template L_DATA DLList::Pop(void) { return (pDelete(tail->previous)); } template L_DATA DLList::Get(unsigned long pos) { if ((pos < 1) || (pos > (number_of_items + 1))) { return (0); } // return(array[pos]->item); DLItem *cur = head; while (pos--) { cur = cur->next; } return (cur->item); } template int DLList::Enqueue(L_DATA data) { return (pInsert(data, tail) != 0); } template L_DATA DLList::Dequeue(void) { return (pDelete(head->next)); } //gibt Index des gesuchte Listenelement zurueck, besser waere eigentlich zeiger template unsigned long DLList::Is_In_List(L_DATA data) { DLItem *cur = head, *next; unsigned long pos = 0; while (cur) { next = cur->next; if (cur->item == data) { return (pos) ; } cur = next; pos++; } return (0); } //###################################################################################################################### template DL_Indexed_List::DL_Indexed_List(void) : DLList() { last_index = 0; } template DL_Indexed_List::~DL_Indexed_List() { /* This is already done by the DLList destructor */ /* DLItem *cur, *next; */ /* cur=this->head; */ /* while (cur) */ /* { */ /* next=cur->next; */ /* delete(cur); */ /* cur=next; */ /* } */ /* this->number_of_items=0; */ // printf("Liste Zerstoert!\n"); } //privates Insert template DLItem *DL_Indexed_List::pInsert(L_DATA data, DLItem *pos) { DLItem *i = new DLItem(data, last_index, pos->previous, pos); if (i) { pos->previous->next = i; pos->previous = i; this->number_of_items++; array[last_index] = i; last_index++; return (i); } else { return (0); } } //privates delete template L_DATA DL_Indexed_List::pDelete(DLItem *i) { L_DATA data = i->item; i->previous->next = i->next; i->next->previous = i->previous; array[i->index] = 0; last_index = i->index; delete (i); this->number_of_items--; return (data); } template L_DATA DL_Indexed_List::Push(L_DATA data) { DLItem *tmp; tmp = pInsert(data, this->tail); if (tmp) { return (tmp->item); } return (0); } template L_DATA DL_Indexed_List::Pop(void) { return (pDelete(this->tail->previous)); } template L_DATA DL_Indexed_List::Get(unsigned long pos) { if (pos > this->number_of_items - 1) { return (0); } return (array[pos]->item); } //####################################################################################### //************************************************************************************************************ template ClusterList::ClusterList(void) : DLList() { links_out_of_cluster = 0; links_inside_cluster = 0; frequency = 1; cluster_energy = 1e30; candidates = new DLList(); marker = 0; } template ClusterList::~ClusterList() { while (candidates->Size()) { candidates->Pop(); } delete candidates; } template bool ClusterList::operator==(ClusterList &b) { bool found = false; L_DATA n_cur, n_cur_b; DLList_Iter a_iter, b_iter; if (this->Size() != b.Size()) { return false; } n_cur = a_iter.First(this); while (!(a_iter.End())) { found = false; n_cur_b = b_iter.First(&b); while (!(b_iter.End()) && !found) { if (n_cur == n_cur_b) { found = true; } n_cur_b = b_iter.Next(); } if (!found) { return false; } n_cur = a_iter.Next(); } return (found); } //A bool ClusterList::operator<(ClusterList &b) { bool found = false; L_DATA n_cur, n_cur_b; DLList_Iter a_iter, b_iter; if (this->Size() >= b.Size()) { return false; } n_cur = a_iter.First(this); while (!(a_iter.End())) { found = false; n_cur_b = b_iter.First(&b); while (!(b_iter.End()) && !found) { if (n_cur == n_cur_b) { found = true; } n_cur_b = b_iter.Next(); } if (!found) { return false; } n_cur = a_iter.Next(); } return (found); } //##################################################################################### template DLList_Iter::DLList_Iter() { list = NULL; current = NULL; end_reached = true; } template L_DATA DLList_Iter::Next(void) { current = current->next; if (current == (list->tail)) { end_reached = true; } return (current->item); } template L_DATA DLList_Iter::Previous(void) { current = current->previous; if (current == (list->head)) { end_reached = true; } return (current->item); } template L_DATA DLList_Iter::First(DLList *l) { list = l; current = list->head->next; if (current == (list->tail)) { end_reached = true; } else { end_reached = false; } return (current->item); } template L_DATA DLList_Iter::Last(DLList *l) { list = l; current = list->tail->previous; if (current == (list->head)) { end_reached = true; // falls die List leer ist } else { end_reached = false; } return (current->item); } template bool DLList_Iter::Swap(DLList_Iter b) { L_DATA h; if (list != b.list) { return false; //elemeten muessen aus der gleichen List stammen } if (end_reached || b.end_reached) { return false; } h = current->item; current->item = b.current->item; b.current->item = h; return true; } #endif python-igraph-0.8.0/vendor/source/igraph/src/scg_exact_scg.c0000644000076500000240000000425713614300625024346 0ustar tamasstaff00000000000000/* * SCGlib : A C library for the spectral coarse graining of matrices * as described in the paper: Shrinking Matrices while preserving their * eigenpairs with Application to the Spectral Coarse Graining of Graphs. * Preprint available at * * Copyright (C) 2008 David Morton de Lachapelle * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 2 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA * 02110-1301 USA * * DESCRIPTION * ----------- * The exact_coarse_graining function labels all the objects whose * components in 'v' are equal. The result is stored in 'gr'. Labels * are positive consecutive integers starting from 0. * See also Section 5.4.1 (last paragraph) of the above reference. */ #include "igraph_memory.h" #include "scg_headers.h" #include int igraph_i_exact_coarse_graining(const igraph_real_t *v, int *gr, const int n) { int i, gr_nb; igraph_i_scg_indval_t *w = igraph_Calloc(n, igraph_i_scg_indval_t); if (!w) { IGRAPH_ERROR("SCG error", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, w); for (i = 0; i < n; i++) { w[i].val = v[i]; w[i].ind = i; } qsort(w, (size_t) n, sizeof(igraph_i_scg_indval_t), igraph_i_compare_ind_val); gr_nb = 0; gr[w[0].ind] = gr_nb; for (i = 1; i < n; i++) { if ( fabs(w[i].val - w[i - 1].val) > 1e-14 ) { gr_nb++; } gr[w[i].ind] = gr_nb; } igraph_Free(w); IGRAPH_FINALLY_CLEAN(1); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/gengraph_box_list.cpp0000644000076500000240000000472313614300625025606 0ustar tamasstaff00000000000000/* * * gengraph - generation of random simple connected graphs with prescribed * degree sequence * * Copyright (C) 2006 Fabien Viger * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #include "gengraph_box_list.h" #include namespace gengraph { void box_list::insert(int v) { register int d = deg[v]; if (d < 1) { return; } if (d > dmax) { dmax = d; } int yo = list[d - 1]; list[d - 1] = v; prev[v] = -1; next[v] = yo; if (yo >= 0) { prev[yo] = v; } } void box_list::pop(int v) { register int p = prev[v]; register int n = next[v]; if (p < 0) { register int d = deg[v]; assert(list[d - 1] == v); list[d - 1] = n; if (d == dmax && n < 0) do { dmax--; } while (dmax > 0 && list[dmax - 1] < 0); } else { next[p] = n; } if (n >= 0) { prev[n] = p; } } box_list::box_list(int n0, int *deg0) : n(n0), deg(deg0) { next = new int[n]; prev = new int[n]; dmax = -1; int i; for (i = 0; i < n; i++) if (deg[i] > dmax) { dmax = deg[i]; } list = new int[dmax]; for (i = 0; i < dmax; i++) { list[i] = -1; } for (i = 0; i < n; i++) { insert(i); } } box_list::~box_list() { delete[] prev; delete[] next; delete[] list; } void box_list::pop_vertex(int v, int **neigh) { int k = deg[v]; if (k < 1) { return; } pop(v); int *w = neigh[v]; while (k--) { int v2 = *(w++); register int *w2 = neigh[v2]; while (*w2 != v) { w2++; } register int *w3 = neigh[v2] + (deg[v2] - 1); assert(w2 <= w3); register int tmp = *w3; *w3 = *w2; *w2 = tmp; pop(v2); deg[v2]--; insert(v2); } } } // namespace gengraph python-igraph-0.8.0/vendor/source/igraph/src/community.c0000644000076500000240000044033013614300625023572 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_community.h" #include "igraph_constructors.h" #include "igraph_memory.h" #include "igraph_random.h" #include "igraph_arpack.h" #include "igraph_arpack_internal.h" #include "igraph_adjlist.h" #include "igraph_interface.h" #include "igraph_interrupt_internal.h" #include "igraph_components.h" #include "igraph_dqueue.h" #include "igraph_progress.h" #include "igraph_stack.h" #include "igraph_spmatrix.h" #include "igraph_statusbar.h" #include "igraph_types_internal.h" #include "igraph_conversion.h" #include "igraph_centrality.h" #include "igraph_structural.h" #include "config.h" #include #include #ifdef USING_R #include #endif int igraph_i_rewrite_membership_vector(igraph_vector_t *membership) { long int no = (long int) igraph_vector_max(membership) + 1; igraph_vector_t idx; long int realno = 0; long int i; long int len = igraph_vector_size(membership); IGRAPH_VECTOR_INIT_FINALLY(&idx, no); for (i = 0; i < len; i++) { long int t = (long int) VECTOR(*membership)[i]; if (VECTOR(idx)[t]) { VECTOR(*membership)[i] = VECTOR(idx)[t] - 1; } else { VECTOR(idx)[t] = ++realno; VECTOR(*membership)[i] = VECTOR(idx)[t] - 1; } } igraph_vector_destroy(&idx); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_i_community_eb_get_merges2(const igraph_t *graph, const igraph_vector_t *edges, const igraph_vector_t *weights, igraph_matrix_t *res, igraph_vector_t *bridges, igraph_vector_t *modularity, igraph_vector_t *membership) { igraph_vector_t mymembership; long int no_of_nodes = igraph_vcount(graph); long int i; igraph_real_t maxmod = -1; long int midx = 0; igraph_integer_t no_comps; IGRAPH_VECTOR_INIT_FINALLY(&mymembership, no_of_nodes); if (membership) { IGRAPH_CHECK(igraph_vector_resize(membership, no_of_nodes)); } if (modularity || res || bridges) { IGRAPH_CHECK(igraph_clusters(graph, 0, 0, &no_comps, IGRAPH_WEAK)); if (modularity) { IGRAPH_CHECK(igraph_vector_resize(modularity, no_of_nodes - no_comps + 1)); } if (res) { IGRAPH_CHECK(igraph_matrix_resize(res, no_of_nodes - no_comps, 2)); } if (bridges) { IGRAPH_CHECK(igraph_vector_resize(bridges, no_of_nodes - no_comps)); } } for (i = 0; i < no_of_nodes; i++) { VECTOR(mymembership)[i] = i; } if (membership) { igraph_vector_update(membership, &mymembership); } IGRAPH_CHECK(igraph_modularity(graph, &mymembership, &maxmod, weights)); if (modularity) { VECTOR(*modularity)[0] = maxmod; } for (i = igraph_vector_size(edges) - 1; i >= 0; i--) { long int edge = (long int) VECTOR(*edges)[i]; long int from = IGRAPH_FROM(graph, edge); long int to = IGRAPH_TO(graph, edge); long int c1 = (long int) VECTOR(mymembership)[from]; long int c2 = (long int) VECTOR(mymembership)[to]; igraph_real_t actmod; long int j; if (c1 != c2) { /* this is a merge */ if (res) { MATRIX(*res, midx, 0) = c1; MATRIX(*res, midx, 1) = c2; } if (bridges) { VECTOR(*bridges)[midx] = i + 1; } /* The new cluster has id no_of_nodes+midx+1 */ for (j = 0; j < no_of_nodes; j++) { if (VECTOR(mymembership)[j] == c1 || VECTOR(mymembership)[j] == c2) { VECTOR(mymembership)[j] = no_of_nodes + midx; } } IGRAPH_CHECK(igraph_modularity(graph, &mymembership, &actmod, weights)); if (modularity) { VECTOR(*modularity)[midx + 1] = actmod; if (actmod > maxmod) { maxmod = actmod; if (membership) { igraph_vector_update(membership, &mymembership); } } } midx++; } } if (membership) { IGRAPH_CHECK(igraph_i_rewrite_membership_vector(membership)); } igraph_vector_destroy(&mymembership); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_community_eb_get_merges * \brief Calculating the merges, ie. the dendrogram for an edge betweenness community structure * * * This function is handy if you have a sequence of edge which are * gradually removed from the network and you would like to know how * the network falls apart into separate components. The edge sequence * may come from the \ref igraph_community_edge_betweenness() * function, but this is not necessary. Note that \ref * igraph_community_edge_betweenness can also calculate the * dendrogram, via its \p merges argument. * * \param graph The input graph. * \param edges Vector containing the edges to be removed from the * network, all edges are expected to appear exactly once in the * vector. * \param weights An optional vector containing edge weights. If null, * the unweighted modularity scores will be calculated. If not null, * the weighted modularity scores will be calculated. Ignored if both * \p modularity and \p membership are nulls. * \param res Pointer to an initialized matrix, if not NULL then the * dendrogram will be stored here, in the same form as for the \ref * igraph_community_walktrap() function: the matrix has two columns * and each line is a merge given by the ids of the merged * components. The component ids are number from zero and * component ids smaller than the number of vertices in the graph * belong to individual vertices. The non-trivial components * containing at least two vertices are numbered from \c n, \c n is * the number of vertices in the graph. So if the first line * contains \c a and \c b that means that components \c a and \c b * are merged into component \c n, the second line creates * component \c n+1, etc. The matrix will be resized as needed. * \param bridges Pointer to an initialized vector or NULL. If not * null then the index of the edge removals which split the network * will be stored here. The vector will be resized as needed. * \param modularity If not a null pointer, then the modularity values * for the different divisions, corresponding to the merges matrix, * will be stored here. * \param membership If not a null pointer, then the membership vector * for the best division (in terms of modularity) will be stored * here. * \return Error code. * * \sa \ref igraph_community_edge_betweenness(). * * Time complexity: O(|E|+|V|log|V|), |V| is the number of vertices, * |E| is the number of edges. */ int igraph_community_eb_get_merges(const igraph_t *graph, const igraph_vector_t *edges, const igraph_vector_t *weights, igraph_matrix_t *res, igraph_vector_t *bridges, igraph_vector_t *modularity, igraph_vector_t *membership) { long int no_of_nodes = igraph_vcount(graph); igraph_vector_t ptr; long int i, midx = 0; igraph_integer_t no_comps; if (membership || modularity) { return igraph_i_community_eb_get_merges2(graph, edges, weights, res, bridges, modularity, membership); } IGRAPH_CHECK(igraph_clusters(graph, 0, 0, &no_comps, IGRAPH_WEAK)); IGRAPH_VECTOR_INIT_FINALLY(&ptr, no_of_nodes * 2 - 1); if (res) { IGRAPH_CHECK(igraph_matrix_resize(res, no_of_nodes - no_comps, 2)); } if (bridges) { IGRAPH_CHECK(igraph_vector_resize(bridges, no_of_nodes - no_comps)); } for (i = igraph_vector_size(edges) - 1; i >= 0; i--) { igraph_integer_t edge = (igraph_integer_t) VECTOR(*edges)[i]; igraph_integer_t from, to, c1, c2, idx; igraph_edge(graph, edge, &from, &to); idx = from + 1; while (VECTOR(ptr)[idx - 1] != 0) { idx = (igraph_integer_t) VECTOR(ptr)[idx - 1]; } c1 = idx - 1; idx = to + 1; while (VECTOR(ptr)[idx - 1] != 0) { idx = (igraph_integer_t) VECTOR(ptr)[idx - 1]; } c2 = idx - 1; if (c1 != c2) { /* this is a merge */ if (res) { MATRIX(*res, midx, 0) = c1; MATRIX(*res, midx, 1) = c2; } if (bridges) { VECTOR(*bridges)[midx] = i + 1; } VECTOR(ptr)[c1] = no_of_nodes + midx + 1; VECTOR(ptr)[c2] = no_of_nodes + midx + 1; VECTOR(ptr)[from] = no_of_nodes + midx + 1; VECTOR(ptr)[to] = no_of_nodes + midx + 1; midx++; } } igraph_vector_destroy(&ptr); IGRAPH_FINALLY_CLEAN(1); return 0; } /* Find the smallest active element in the vector */ long int igraph_i_vector_which_max_not_null(const igraph_vector_t *v, const char *passive) { long int which, i = 0, size = igraph_vector_size(v); igraph_real_t max; while (passive[i]) { i++; } which = i; max = VECTOR(*v)[which]; for (i++; i < size; i++) { igraph_real_t elem = VECTOR(*v)[i]; if (!passive[i] && elem > max) { max = elem; which = i; } } return which; } /** * \function igraph_community_edge_betweenness * \brief Community finding based on edge betweenness * * Community structure detection based on the betweenness of the edges * in the network. The algorithm was invented by M. Girvan and * M. Newman, see: M. Girvan and M. E. J. Newman: Community structure in * social and biological networks, Proc. Nat. Acad. Sci. USA 99, 7821-7826 * (2002). * * * The idea is that the betweenness of the edges connecting two * communities is typically high, as many of the shortest paths * between nodes in separate communities go through them. So we * gradually remove the edge with highest betweenness from the * network, and recalculate edge betweenness after every removal. * This way sooner or later the network falls off to two components, * then after a while one of these components falls off to two smaller * components, etc. until all edges are removed. This is a divisive * hierarchical approach, the result is a dendrogram. * \param graph The input graph. * \param result Pointer to an initialized vector, the result will be * stored here, the ids of the removed edges in the order of their * removal. It will be resized as needed. It may be NULL if * the edge IDs are not needed by the caller. * \param edge_betweenness Pointer to an initialized vector or * NULL. In the former case the edge betweenness of the removed * edge is stored here. The vector will be resized as needed. * \param merges Pointer to an initialized matrix or NULL. If not NULL * then merges performed by the algorithm are stored here. Even if * this is a divisive algorithm, we can replay it backwards and * note which two clusters were merged. Clusters are numbered from * zero, see the \p merges argument of \ref * igraph_community_walktrap() for details. The matrix will be * resized as needed. * \param bridges Pointer to an initialized vector of NULL. If not * NULL then all edge removals which separated the network into * more components are marked here. * \param modularity If not a null pointer, then the modularity values * of the different divisions are stored here, in the order * corresponding to the merge matrix. The modularity values will * take weights into account if \p weights is not null. * \param membership If not a null pointer, then the membership vector, * corresponding to the highest modularity value, is stored here. * \param directed Logical constant, whether to calculate directed * betweenness (ie. directed paths) for directed graphs. It is * ignored for undirected graphs. * \param weights An optional vector containing edge weights. If null, * the unweighted edge betweenness scores will be calculated and * used. If not null, the weighted edge betweenness scores will be * calculated and used. * \return Error code. * * \sa \ref igraph_community_eb_get_merges(), \ref * igraph_community_spinglass(), \ref igraph_community_walktrap(). * * Time complexity: O(|V||E|^2), as the betweenness calculation requires * O(|V||E|) and we do it |E|-1 times. * * \example examples/simple/igraph_community_edge_betweenness.c */ int igraph_community_edge_betweenness(const igraph_t *graph, igraph_vector_t *result, igraph_vector_t *edge_betweenness, igraph_matrix_t *merges, igraph_vector_t *bridges, igraph_vector_t *modularity, igraph_vector_t *membership, igraph_bool_t directed, const igraph_vector_t *weights) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); double *distance, *tmpscore; unsigned long long int *nrgeo; long int source, i, e; igraph_inclist_t elist_out, elist_in, fathers; igraph_inclist_t *elist_out_p, *elist_in_p; igraph_vector_int_t *neip; long int neino; igraph_vector_t eb; long int maxedge, pos; igraph_integer_t from, to; igraph_bool_t result_owned = 0; igraph_stack_t stack = IGRAPH_STACK_NULL; igraph_real_t steps, steps_done; char *passive; /* Needed only for the unweighted case */ igraph_dqueue_t q = IGRAPH_DQUEUE_NULL; /* Needed only for the weighted case */ igraph_2wheap_t heap; if (result == 0) { result = igraph_Calloc(1, igraph_vector_t); if (result == 0) { IGRAPH_ERROR("edge betweenness community structure failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, result); IGRAPH_VECTOR_INIT_FINALLY(result, 0); result_owned = 1; } directed = directed && igraph_is_directed(graph); if (directed) { IGRAPH_CHECK(igraph_inclist_init(graph, &elist_out, IGRAPH_OUT)); IGRAPH_FINALLY(igraph_inclist_destroy, &elist_out); IGRAPH_CHECK(igraph_inclist_init(graph, &elist_in, IGRAPH_IN)); IGRAPH_FINALLY(igraph_inclist_destroy, &elist_in); elist_out_p = &elist_out; elist_in_p = &elist_in; } else { IGRAPH_CHECK(igraph_inclist_init(graph, &elist_out, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_inclist_destroy, &elist_out); elist_out_p = elist_in_p = &elist_out; } distance = igraph_Calloc(no_of_nodes, double); if (distance == 0) { IGRAPH_ERROR("edge betweenness community structure failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, distance); nrgeo = igraph_Calloc(no_of_nodes, unsigned long long int); if (nrgeo == 0) { IGRAPH_ERROR("edge betweenness community structure failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, nrgeo); tmpscore = igraph_Calloc(no_of_nodes, double); if (tmpscore == 0) { IGRAPH_ERROR("edge betweenness community structure failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, tmpscore); if (weights == 0) { IGRAPH_DQUEUE_INIT_FINALLY(&q, 100); } else { if (igraph_vector_min(weights) <= 0) { IGRAPH_ERROR("weights must be strictly positive", IGRAPH_EINVAL); } if (membership != 0) { IGRAPH_WARNING("Membership vector will be selected based on the lowest "\ "modularity score."); } if (modularity != 0 || membership != 0) { IGRAPH_WARNING("Modularity calculation with weighted edge betweenness "\ "community detection might not make sense -- modularity treats edge "\ "weights as similarities while edge betwenness treats them as "\ "distances"); } IGRAPH_CHECK(igraph_2wheap_init(&heap, no_of_nodes)); IGRAPH_FINALLY(igraph_2wheap_destroy, &heap); IGRAPH_CHECK(igraph_inclist_init_empty(&fathers, (igraph_integer_t) no_of_nodes)); IGRAPH_FINALLY(igraph_inclist_destroy, &fathers); } IGRAPH_CHECK(igraph_stack_init(&stack, no_of_nodes)); IGRAPH_FINALLY(igraph_stack_destroy, &stack); IGRAPH_CHECK(igraph_vector_resize(result, no_of_edges)); if (edge_betweenness) { IGRAPH_CHECK(igraph_vector_resize(edge_betweenness, no_of_edges)); VECTOR(*edge_betweenness)[no_of_edges - 1] = 0; } IGRAPH_VECTOR_INIT_FINALLY(&eb, no_of_edges); passive = igraph_Calloc(no_of_edges, char); if (!passive) { IGRAPH_ERROR("edge betweenness community structure failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, passive); /* Estimate the number of steps to be taken. * It is assumed that one iteration is O(|E||V|), but |V| is constant * anyway, so we will have approximately |E|^2 / 2 steps, and one * iteration of the outer loop advances the step counter by the number * of remaining edges at that iteration. */ steps = no_of_edges / 2.0 * (no_of_edges + 1); steps_done = 0; for (e = 0; e < no_of_edges; steps_done += no_of_edges - e, e++) { IGRAPH_PROGRESS("Edge betweenness community detection: ", 100.0 * steps_done / steps, NULL); igraph_vector_null(&eb); if (weights == 0) { /* Unweighted variant follows */ /* The following for loop is copied almost intact from * igraph_edge_betweenness_estimate */ for (source = 0; source < no_of_nodes; source++) { IGRAPH_ALLOW_INTERRUPTION(); memset(distance, 0, (size_t) no_of_nodes * sizeof(double)); memset(nrgeo, 0, (size_t) no_of_nodes * sizeof(unsigned long long int)); memset(tmpscore, 0, (size_t) no_of_nodes * sizeof(double)); igraph_stack_clear(&stack); /* it should be empty anyway... */ IGRAPH_CHECK(igraph_dqueue_push(&q, source)); nrgeo[source] = 1; distance[source] = 0; while (!igraph_dqueue_empty(&q)) { long int actnode = (long int) igraph_dqueue_pop(&q); neip = igraph_inclist_get(elist_out_p, actnode); neino = igraph_vector_int_size(neip); for (i = 0; i < neino; i++) { igraph_integer_t edge = (igraph_integer_t) VECTOR(*neip)[i], from, to; long int neighbor; igraph_edge(graph, edge, &from, &to); neighbor = actnode != from ? from : to; if (nrgeo[neighbor] != 0) { /* we've already seen this node, another shortest path? */ if (distance[neighbor] == distance[actnode] + 1) { nrgeo[neighbor] += nrgeo[actnode]; } } else { /* we haven't seen this node yet */ nrgeo[neighbor] += nrgeo[actnode]; distance[neighbor] = distance[actnode] + 1; IGRAPH_CHECK(igraph_dqueue_push(&q, neighbor)); IGRAPH_CHECK(igraph_stack_push(&stack, neighbor)); } } } /* while !igraph_dqueue_empty */ /* Ok, we've the distance of each node and also the number of shortest paths to them. Now we do an inverse search, starting with the farthest nodes. */ while (!igraph_stack_empty(&stack)) { long int actnode = (long int) igraph_stack_pop(&stack); if (distance[actnode] < 1) { continue; /* skip source node */ } /* set the temporary score of the friends */ neip = igraph_inclist_get(elist_in_p, actnode); neino = igraph_vector_int_size(neip); for (i = 0; i < neino; i++) { long int edge = (long int) VECTOR(*neip)[i]; long int neighbor = IGRAPH_OTHER(graph, edge, actnode); if (distance[neighbor] == distance[actnode] - 1 && nrgeo[neighbor] != 0) { tmpscore[neighbor] += (tmpscore[actnode] + 1) * nrgeo[neighbor] / nrgeo[actnode]; VECTOR(eb)[edge] += (tmpscore[actnode] + 1) * nrgeo[neighbor] / nrgeo[actnode]; } } } /* Ok, we've the scores for this source */ } /* for source <= no_of_nodes */ } else { /* Weighted variant follows */ /* The following for loop is copied almost intact from * igraph_i_edge_betweenness_estimate_weighted */ for (source = 0; source < no_of_nodes; source++) { /* This will contain the edge betweenness in the current step */ IGRAPH_ALLOW_INTERRUPTION(); memset(distance, 0, (size_t) no_of_nodes * sizeof(double)); memset(nrgeo, 0, (size_t) no_of_nodes * sizeof(unsigned long long int)); memset(tmpscore, 0, (size_t) no_of_nodes * sizeof(double)); igraph_2wheap_push_with_index(&heap, source, 0); distance[source] = 1.0; nrgeo[source] = 1; while (!igraph_2wheap_empty(&heap)) { long int minnei = igraph_2wheap_max_index(&heap); igraph_real_t mindist = -igraph_2wheap_delete_max(&heap); igraph_stack_push(&stack, minnei); neip = igraph_inclist_get(elist_out_p, minnei); neino = igraph_vector_int_size(neip); for (i = 0; i < neino; i++) { long int edge = VECTOR(*neip)[i]; long int to = IGRAPH_OTHER(graph, edge, minnei); igraph_real_t altdist = mindist + VECTOR(*weights)[edge]; igraph_real_t curdist = distance[to]; igraph_vector_int_t *v; if (curdist == 0) { /* This is the first finite distance to 'to' */ v = igraph_inclist_get(&fathers, to); igraph_vector_int_resize(v, 1); VECTOR(*v)[0] = edge; nrgeo[to] = nrgeo[minnei]; distance[to] = altdist + 1.0; IGRAPH_CHECK(igraph_2wheap_push_with_index(&heap, to, -altdist)); } else if (altdist < curdist - 1) { /* This is a shorter path */ v = igraph_inclist_get(&fathers, to); igraph_vector_int_resize(v, 1); VECTOR(*v)[0] = edge; nrgeo[to] = nrgeo[minnei]; distance[to] = altdist + 1.0; IGRAPH_CHECK(igraph_2wheap_modify(&heap, to, -altdist)); } else if (altdist == curdist - 1) { /* Another path with the same length */ v = igraph_inclist_get(&fathers, to); igraph_vector_int_push_back(v, edge); nrgeo[to] += nrgeo[minnei]; } } } /* igraph_2wheap_empty(&Q) */ while (!igraph_stack_empty(&stack)) { long int w = (long int) igraph_stack_pop(&stack); igraph_vector_int_t *fatv = igraph_inclist_get(&fathers, w); long int fatv_len = igraph_vector_int_size(fatv); for (i = 0; i < fatv_len; i++) { long int fedge = (long int) VECTOR(*fatv)[i]; long int neighbor = IGRAPH_OTHER(graph, fedge, w); tmpscore[neighbor] += (tmpscore[w] + 1) * nrgeo[neighbor] / nrgeo[w]; VECTOR(eb)[fedge] += (tmpscore[w] + 1) * nrgeo[neighbor] / nrgeo[w]; } tmpscore[w] = 0; distance[w] = 0; nrgeo[w] = 0; igraph_vector_int_clear(fatv); } } /* source < no_of_nodes */ } /* Now look for the smallest edge betweenness */ /* and eliminate that edge from the network */ maxedge = igraph_i_vector_which_max_not_null(&eb, passive); VECTOR(*result)[e] = maxedge; if (edge_betweenness) { VECTOR(*edge_betweenness)[e] = VECTOR(eb)[maxedge]; if (!directed) { VECTOR(*edge_betweenness)[e] /= 2.0; } } passive[maxedge] = 1; igraph_edge(graph, (igraph_integer_t) maxedge, &from, &to); neip = igraph_inclist_get(elist_in_p, to); neino = igraph_vector_int_size(neip); igraph_vector_int_search(neip, 0, maxedge, &pos); VECTOR(*neip)[pos] = VECTOR(*neip)[neino - 1]; igraph_vector_int_pop_back(neip); neip = igraph_inclist_get(elist_out_p, from); neino = igraph_vector_int_size(neip); igraph_vector_int_search(neip, 0, maxedge, &pos); VECTOR(*neip)[pos] = VECTOR(*neip)[neino - 1]; igraph_vector_int_pop_back(neip); } IGRAPH_PROGRESS("Edge betweenness community detection: ", 100.0, NULL); igraph_free(passive); igraph_vector_destroy(&eb); igraph_stack_destroy(&stack); IGRAPH_FINALLY_CLEAN(3); if (weights == 0) { igraph_dqueue_destroy(&q); IGRAPH_FINALLY_CLEAN(1); } else { igraph_2wheap_destroy(&heap); igraph_inclist_destroy(&fathers); IGRAPH_FINALLY_CLEAN(2); } igraph_free(tmpscore); igraph_free(nrgeo); igraph_free(distance); IGRAPH_FINALLY_CLEAN(3); if (directed) { igraph_inclist_destroy(&elist_out); igraph_inclist_destroy(&elist_in); IGRAPH_FINALLY_CLEAN(2); } else { igraph_inclist_destroy(&elist_out); IGRAPH_FINALLY_CLEAN(1); } if (merges || bridges || modularity || membership) { IGRAPH_CHECK(igraph_community_eb_get_merges(graph, result, weights, merges, bridges, modularity, membership)); } if (result_owned) { igraph_vector_destroy(result); free(result); IGRAPH_FINALLY_CLEAN(2); } return 0; } /** * \function igraph_community_to_membership * \brief Create membership vector from community structure dendrogram * * This function creates a membership vector from a community * structure dendrogram. A membership vector contains for each vertex * the id of its graph component, the graph components are numbered * from zero, see the same argument of \ref igraph_clusters() for an * example of a membership vector. * * * Many community detection algorithms return with a \em merges * matrix, \ref igraph_community_walktrap() and \ref * igraph_community_edge_betweenness() are two examples. The matrix * contains the merge operations performed while mapping the * hierarchical structure of a network. If the matrix has \c n-1 rows, * where \c n is the number of vertices in the graph, then it contains * the hierarchical structure of the whole network and it is called a * dendrogram. * * * This function performs \p steps merge operations as prescribed by * the \p merges matrix and returns the current state of the network. * * * If \p merges is not a complete dendrogram, it is possible to * take \p steps steps if \p steps is not bigger than the number * lines in \p merges. * \param merges The two-column matrix containing the merge * operations. See \ref igraph_community_walktrap() for the * detailed syntax. * \param nodes The number of leaf nodes in the dendrogram * \param steps Integer constant, the number of steps to take. * \param membership Pointer to an initialized vector, the membership * results will be stored here, if not NULL. The vector will be * resized as needed. * \param csize Pointer to an initialized vector, or NULL. If not NULL * then the sizes of the components will be stored here, the vector * will be resized as needed. * * \sa \ref igraph_community_walktrap(), \ref * igraph_community_edge_betweenness(), \ref * igraph_community_fastgreedy() for community structure detection * algorithms. * * Time complexity: O(|V|), the number of vertices in the graph. */ int igraph_community_to_membership(const igraph_matrix_t *merges, igraph_integer_t nodes, igraph_integer_t steps, igraph_vector_t *membership, igraph_vector_t *csize) { long int no_of_nodes = nodes; long int components = no_of_nodes - steps; long int i, found = 0; igraph_vector_t tmp; if (steps > igraph_matrix_nrow(merges)) { IGRAPH_ERROR("`steps' to big or `merges' matrix too short", IGRAPH_EINVAL); } if (membership) { IGRAPH_CHECK(igraph_vector_resize(membership, no_of_nodes)); igraph_vector_null(membership); } if (csize) { IGRAPH_CHECK(igraph_vector_resize(csize, components)); igraph_vector_null(csize); } IGRAPH_VECTOR_INIT_FINALLY(&tmp, steps); for (i = steps - 1; i >= 0; i--) { long int c1 = (long int) MATRIX(*merges, i, 0); long int c2 = (long int) MATRIX(*merges, i, 1); /* new component? */ if (VECTOR(tmp)[i] == 0) { found++; VECTOR(tmp)[i] = found; } if (c1 < no_of_nodes) { long int cid = (long int) VECTOR(tmp)[i] - 1; if (membership) { VECTOR(*membership)[c1] = cid + 1; } if (csize) { VECTOR(*csize)[cid] += 1; } } else { VECTOR(tmp)[c1 - no_of_nodes] = VECTOR(tmp)[i]; } if (c2 < no_of_nodes) { long int cid = (long int) VECTOR(tmp)[i] - 1; if (membership) { VECTOR(*membership)[c2] = cid + 1; } if (csize) { VECTOR(*csize)[cid] += 1; } } else { VECTOR(tmp)[c2 - no_of_nodes] = VECTOR(tmp)[i]; } } if (membership || csize) { for (i = 0; i < no_of_nodes; i++) { long int tmp = (long int) VECTOR(*membership)[i]; if (tmp != 0) { if (membership) { VECTOR(*membership)[i] = tmp - 1; } } else { if (csize) { VECTOR(*csize)[found] += 1; } if (membership) { VECTOR(*membership)[i] = found; } found++; } } } igraph_vector_destroy(&tmp); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_modularity * \brief Calculate the modularity of a graph with respect to some vertex types * * The modularity of a graph with respect to some division (or vertex * types) measures how good the division is, or how separated are the * different vertex types from each other. It is defined as * Q=1/(2m) * sum((Aij - ki*kj / (2m)) delta(ci,cj), i, j), here `m' is the * number of edges, `Aij' is the element of the `A' adjacency matrix * in row `i' and column `j', `ki' is the degree of `i', `kj' is the * degree of `j', `ci' is the type (or component) of `i', `cj' that of * `j', the sum goes over all `i' and `j' pairs of vertices, and * `delta(x,y)' is one if x=y and zero otherwise. * * * Modularity on weighted graphs is also meaningful. When taking edge * weights into account, `Aij' becomes the weight of the corresponding * edge (or 0 if there is no edge), `ki' is the total weight of edges * incident on vertex `i', `kj' is the total weight of edges incident * on vertex `j' and `m' is the total weight of all edges. * * * See also Clauset, A.; Newman, M. E. J.; Moore, C. Finding * community structure in very large networks, Physical Review E, * 2004, 70, 066111. * \param graph The input graph. It must be undirected; directed graphs are * not supported yet. * \param membership Numeric vector which gives the type of each * vertex, ie. the component to which it belongs. * It does not have to be consecutive, i.e. empty communities are * allowed. * \param modularity Pointer to a real number, the result will be * stored here. * \param weights Weight vector or NULL if no weights are specified. * \return Error code. * * Time complexity: O(|V|+|E|), the number of vertices plus the number * of edges. */ int igraph_modularity(const igraph_t *graph, const igraph_vector_t *membership, igraph_real_t *modularity, const igraph_vector_t *weights) { igraph_vector_t e, a; long int types = (long int) igraph_vector_max(membership) + 1; long int no_of_edges = igraph_ecount(graph); long int i; igraph_integer_t from, to; igraph_real_t m; long int c1, c2; if (igraph_is_directed(graph)) { #ifndef USING_R IGRAPH_ERROR("modularity is implemented for undirected graphs", IGRAPH_EINVAL); #else REprintf("Modularity is implemented for undirected graphs only.\n"); #endif } if (igraph_vector_size(membership) < igraph_vcount(graph)) { IGRAPH_ERROR("cannot calculate modularity, membership vector too short", IGRAPH_EINVAL); } if (igraph_vector_min(membership) < 0) { IGRAPH_ERROR("Invalid membership vector", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(&e, types); IGRAPH_VECTOR_INIT_FINALLY(&a, types); if (weights) { if (igraph_vector_size(weights) < no_of_edges) IGRAPH_ERROR("cannot calculate modularity, weight vector too short", IGRAPH_EINVAL); m = igraph_vector_sum(weights); for (i = 0; i < no_of_edges; i++) { igraph_real_t w = VECTOR(*weights)[i]; if (w < 0) { IGRAPH_ERROR("negative weight in weight vector", IGRAPH_EINVAL); } igraph_edge(graph, (igraph_integer_t) i, &from, &to); c1 = (long int) VECTOR(*membership)[from]; c2 = (long int) VECTOR(*membership)[to]; if (c1 == c2) { VECTOR(e)[c1] += 2 * w; } VECTOR(a)[c1] += w; VECTOR(a)[c2] += w; } } else { m = no_of_edges; for (i = 0; i < no_of_edges; i++) { igraph_edge(graph, (igraph_integer_t) i, &from, &to); c1 = (long int) VECTOR(*membership)[from]; c2 = (long int) VECTOR(*membership)[to]; if (c1 == c2) { VECTOR(e)[c1] += 2; } VECTOR(a)[c1] += 1; VECTOR(a)[c2] += 1; } } *modularity = 0.0; if (m > 0) { for (i = 0; i < types; i++) { igraph_real_t tmp = VECTOR(a)[i] / 2 / m; *modularity += VECTOR(e)[i] / 2 / m; *modularity -= tmp * tmp; } } igraph_vector_destroy(&e); igraph_vector_destroy(&a); IGRAPH_FINALLY_CLEAN(2); return 0; } /** * \function igraph_modularity_matrix * \brief Calculate the modularity matrix * * This function returns the modularity matrix defined as * `B_ij = A_ij - k_i k_j * / 2 m` * where `A_ij` denotes the adjacency matrix, `k_i` is the degree of node `i` * and `m` is the total weight in the graph. Note that self-loops are multiplied * by 2 in this implementation. If weights are specified, the weighted * counterparts are used. * * \param graph The input graph * \param modmat Pointer to an initialized matrix in which the modularity * matrix is stored. * \param weights Edge weights, pointer to a vector. If this is a null pointer * then every edge is assumed to have a weight of 1. */ int igraph_modularity_matrix(const igraph_t *graph, igraph_matrix_t *modmat, const igraph_vector_t *weights) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_real_t sw = weights ? igraph_vector_sum(weights) : no_of_edges; igraph_vector_t deg; long int i, j; if (weights && igraph_vector_size(weights) != no_of_edges) { IGRAPH_ERROR("Invalid weight vector length", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(°, no_of_nodes); if (!weights) { IGRAPH_CHECK(igraph_degree(graph, °, igraph_vss_all(), IGRAPH_ALL, IGRAPH_LOOPS)); } else { IGRAPH_CHECK(igraph_strength(graph, °, igraph_vss_all(), IGRAPH_ALL, IGRAPH_LOOPS, weights)); } IGRAPH_CHECK(igraph_get_adjacency(graph, modmat, IGRAPH_GET_ADJACENCY_BOTH, /*eids=*/ 0)); for (i = 0; i < no_of_nodes; i++) { MATRIX(*modmat, i, i) *= 2; } for (i = 0; i < no_of_nodes; i++) { for (j = 0; j < no_of_nodes; j++) { MATRIX(*modmat, i, j) -= VECTOR(deg)[i] * VECTOR(deg)[j] / 2.0 / sw; } } igraph_vector_destroy(°); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_reindex_membership * \brief Makes the IDs in a membership vector continuous * * This function reindexes component IDs in a membership vector * in a way that the new IDs start from zero and go up to C-1, * where C is the number of unique component IDs in the original * vector. The supplied membership is expected to fall in the * range 0, ..., n - 1. * * \param membership Numeric vector which gives the type of each * vertex, ie. the component to which it belongs. * The vector will be altered in-place. * \param new_to_old Pointer to a vector which will contain the * old component ID for each new one, or NULL, * in which case it is not returned. The vector * will be resized as needed. * \param nb_clusters Pointer to an integer for the number of * distinct clusters. If not NULL, this will be * updated to reflect the number of distinct * clusters found in membership. * * Time complexity: should be O(n) for n elements. */ int igraph_reindex_membership(igraph_vector_t *membership, igraph_vector_t *new_to_old, igraph_integer_t *nb_clusters) { long int i, n = igraph_vector_size(membership); igraph_vector_t new_cluster; igraph_integer_t i_nb_clusters; /* We allow original cluster indices in the range 0, ..., n - 1 */ IGRAPH_CHECK(igraph_vector_init(&new_cluster, n)); IGRAPH_FINALLY(igraph_vector_destroy, &new_cluster); if (new_to_old) { igraph_vector_clear(new_to_old); } /* Clean clusters. We will store the new cluster + 1 so that membership == 0 * indicates that no cluster was assigned yet. */ i_nb_clusters = 1; for (i = 0; i < n; i++) { long int c = (long int)VECTOR(*membership)[i]; if (c >= n) { IGRAPH_ERROR("Cluster out of range", IGRAPH_EINVAL); } if (VECTOR(new_cluster)[c] == 0) { VECTOR(new_cluster)[c] = (igraph_real_t)i_nb_clusters; i_nb_clusters += 1; if (new_to_old) { IGRAPH_CHECK(igraph_vector_push_back(new_to_old, c)); } } } /* Assign new membership */ for (i = 0; i < n; i++) { long int c = (long int)VECTOR(*membership)[i]; VECTOR(*membership)[i] = VECTOR(new_cluster)[c] - 1; } if (nb_clusters) { /* We used the cluster + 1, so correct */ *nb_clusters = i_nb_clusters - 1; } igraph_vector_destroy(&new_cluster); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } /********************************************************************/ /** * \section about_leading_eigenvector_methods * * * The function documented in these section implements the * leading eigenvector method developed by Mark Newman and * published in MEJ Newman: Finding community structure using the * eigenvectors of matrices, Phys Rev E 74:036104 (2006). * * * The heart of the method is the definition of the modularity matrix, * B, which is B=A-P, A being the adjacency matrix of the (undirected) * network, and P contains the probability that certain edges are * present according to the configuration model In * other words, a Pij element of P is the probability that there is an * edge between vertices i and j in a random network in which the * degrees of all vertices are the same as in the input graph. * * * The leading eigenvector method works by calculating the eigenvector * of the modularity matrix for the largest positive eigenvalue and * then separating vertices into two community based on the sign of * the corresponding element in the eigenvector. If all elements in * the eigenvector are of the same sign that means that the network * has no underlying community structure. * Check Newman's paper to understand why this is a good method for * detecting community structure. * * * The leading eigenvector community structure detection method is * implemented in \ref igraph_community_leading_eigenvector(). After * the initial split, the following splits are done in a way to * optimize modularity regarding to the original network. Note that * any further refinement, for example using Kernighan-Lin, as * proposed in Section V.A of Newman (2006), is not implemented here. * * * * \example examples/simple/igraph_community_leading_eigenvector.c * */ typedef struct igraph_i_community_leading_eigenvector_data_t { igraph_vector_t *idx; igraph_vector_t *idx2; igraph_adjlist_t *adjlist; igraph_inclist_t *inclist; igraph_vector_t *tmp; long int no_of_edges; igraph_vector_t *mymembership; long int comm; const igraph_vector_t *weights; const igraph_t *graph; igraph_vector_t *strength; igraph_real_t sumweights; } igraph_i_community_leading_eigenvector_data_t; int igraph_i_community_leading_eigenvector(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_i_community_leading_eigenvector_data_t *data = extra; long int j, k, nlen, size = n; igraph_vector_t *idx = data->idx; igraph_vector_t *idx2 = data->idx2; igraph_vector_t *tmp = data->tmp; igraph_adjlist_t *adjlist = data->adjlist; igraph_real_t ktx, ktx2; long int no_of_edges = data->no_of_edges; igraph_vector_t *mymembership = data->mymembership; long int comm = data->comm; /* Ax */ for (j = 0; j < size; j++) { long int oldid = (long int) VECTOR(*idx)[j]; igraph_vector_int_t *neis = igraph_adjlist_get(adjlist, oldid); nlen = igraph_vector_int_size(neis); to[j] = 0.0; VECTOR(*tmp)[j] = 0.0; for (k = 0; k < nlen; k++) { long int nei = (long int) VECTOR(*neis)[k]; long int neimemb = (long int) VECTOR(*mymembership)[nei]; if (neimemb == comm) { to[j] += from[ (long int) VECTOR(*idx2)[nei] ]; VECTOR(*tmp)[j] += 1; } } } /* Now calculate k^Tx/2m */ ktx = 0.0; ktx2 = 0.0; for (j = 0; j < size; j++) { long int oldid = (long int) VECTOR(*idx)[j]; igraph_vector_int_t *neis = igraph_adjlist_get(adjlist, oldid); long int degree = igraph_vector_int_size(neis); ktx += from[j] * degree; ktx2 += degree; } ktx = ktx / no_of_edges / 2.0; ktx2 = ktx2 / no_of_edges / 2.0; /* Now calculate Bx */ for (j = 0; j < size; j++) { long int oldid = (long int) VECTOR(*idx)[j]; igraph_vector_int_t *neis = igraph_adjlist_get(adjlist, oldid); igraph_real_t degree = igraph_vector_int_size(neis); to[j] = to[j] - ktx * degree; VECTOR(*tmp)[j] = VECTOR(*tmp)[j] - ktx2 * degree; } /* -d_ij summa l in G B_il */ for (j = 0; j < size; j++) { to[j] -= VECTOR(*tmp)[j] * from[j]; } return 0; } int igraph_i_community_leading_eigenvector2(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_i_community_leading_eigenvector_data_t *data = extra; long int j, k, nlen, size = n; igraph_vector_t *idx = data->idx; igraph_vector_t *idx2 = data->idx2; igraph_vector_t *tmp = data->tmp; igraph_adjlist_t *adjlist = data->adjlist; igraph_real_t ktx, ktx2; long int no_of_edges = data->no_of_edges; igraph_vector_t *mymembership = data->mymembership; long int comm = data->comm; /* Ax */ for (j = 0; j < size; j++) { long int oldid = (long int) VECTOR(*idx)[j]; igraph_vector_int_t *neis = igraph_adjlist_get(adjlist, oldid); nlen = igraph_vector_int_size(neis); to[j] = 0.0; VECTOR(*tmp)[j] = 0.0; for (k = 0; k < nlen; k++) { long int nei = (long int) VECTOR(*neis)[k]; long int neimemb = (long int) VECTOR(*mymembership)[nei]; if (neimemb == comm) { long int fi = (long int) VECTOR(*idx2)[nei]; if (fi < size) { to[j] += from[fi]; } VECTOR(*tmp)[j] += 1; } } } /* Now calculate k^Tx/2m */ ktx = 0.0; ktx2 = 0.0; for (j = 0; j < size + 1; j++) { long int oldid = (long int) VECTOR(*idx)[j]; igraph_vector_int_t *neis = igraph_adjlist_get(adjlist, oldid); long int degree = igraph_vector_int_size(neis); if (j < size) { ktx += from[j] * degree; } ktx2 += degree; } ktx = ktx / no_of_edges / 2.0; ktx2 = ktx2 / no_of_edges / 2.0; /* Now calculate Bx */ for (j = 0; j < size; j++) { long int oldid = (long int) VECTOR(*idx)[j]; igraph_vector_int_t *neis = igraph_adjlist_get(adjlist, oldid); igraph_real_t degree = igraph_vector_int_size(neis); to[j] = to[j] - ktx * degree; VECTOR(*tmp)[j] = VECTOR(*tmp)[j] - ktx2 * degree; } /* -d_ij summa l in G B_il */ for (j = 0; j < size; j++) { to[j] -= VECTOR(*tmp)[j] * from[j]; } return 0; } int igraph_i_community_leading_eigenvector_weighted(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_i_community_leading_eigenvector_data_t *data = extra; long int j, k, nlen, size = n; igraph_vector_t *idx = data->idx; igraph_vector_t *idx2 = data->idx2; igraph_vector_t *tmp = data->tmp; igraph_inclist_t *inclist = data->inclist; igraph_real_t ktx, ktx2; igraph_vector_t *mymembership = data->mymembership; long int comm = data->comm; const igraph_vector_t *weights = data->weights; const igraph_t *graph = data->graph; igraph_vector_t *strength = data->strength; igraph_real_t sw = data->sumweights; /* Ax */ for (j = 0; j < size; j++) { long int oldid = (long int) VECTOR(*idx)[j]; igraph_vector_int_t *inc = igraph_inclist_get(inclist, oldid); nlen = igraph_vector_int_size(inc); to[j] = 0.0; VECTOR(*tmp)[j] = 0.0; for (k = 0; k < nlen; k++) { long int edge = (long int) VECTOR(*inc)[k]; igraph_real_t w = VECTOR(*weights)[edge]; long int nei = IGRAPH_OTHER(graph, edge, oldid); long int neimemb = (long int) VECTOR(*mymembership)[nei]; if (neimemb == comm) { to[j] += from[ (long int) VECTOR(*idx2)[nei] ] * w; VECTOR(*tmp)[j] += w; } } } /* k^Tx/2m */ ktx = 0.0; ktx2 = 0.0; for (j = 0; j < size; j++) { long int oldid = (long int) VECTOR(*idx)[j]; igraph_real_t str = VECTOR(*strength)[oldid]; ktx += from[j] * str; ktx2 += str; } ktx = ktx / sw / 2.0; ktx2 = ktx2 / sw / 2.0; /* Bx */ for (j = 0; j < size; j++) { long int oldid = (long int) VECTOR(*idx)[j]; igraph_real_t str = VECTOR(*strength)[oldid]; to[j] = to[j] - ktx * str; VECTOR(*tmp)[j] = VECTOR(*tmp)[j] - ktx2 * str; } /* -d_ij summa l in G B_il */ for (j = 0; j < size; j++) { to[j] -= VECTOR(*tmp)[j] * from[j]; } return 0; } int igraph_i_community_leading_eigenvector2_weighted(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_i_community_leading_eigenvector_data_t *data = extra; long int j, k, nlen, size = n; igraph_vector_t *idx = data->idx; igraph_vector_t *idx2 = data->idx2; igraph_vector_t *tmp = data->tmp; igraph_inclist_t *inclist = data->inclist; igraph_real_t ktx, ktx2; igraph_vector_t *mymembership = data->mymembership; long int comm = data->comm; const igraph_vector_t *weights = data->weights; const igraph_t *graph = data->graph; igraph_vector_t *strength = data->strength; igraph_real_t sw = data->sumweights; /* Ax */ for (j = 0; j < size; j++) { long int oldid = (long int) VECTOR(*idx)[j]; igraph_vector_int_t *inc = igraph_inclist_get(inclist, oldid); nlen = igraph_vector_int_size(inc); to[j] = 0.0; VECTOR(*tmp)[j] = 0.0; for (k = 0; k < nlen; k++) { long int edge = (long int) VECTOR(*inc)[k]; igraph_real_t w = VECTOR(*weights)[edge]; long int nei = IGRAPH_OTHER(graph, edge, oldid); long int neimemb = (long int) VECTOR(*mymembership)[nei]; if (neimemb == comm) { long int fi = (long int) VECTOR(*idx2)[nei]; if (fi < size) { to[j] += from[fi] * w; } VECTOR(*tmp)[j] += w; } } } /* k^Tx/2m */ ktx = 0.0; ktx2 = 0.0; for (j = 0; j < size + 1; j++) { long int oldid = (long int) VECTOR(*idx)[j]; igraph_real_t str = VECTOR(*strength)[oldid]; if (j < size) { ktx += from[j] * str; } ktx2 += str; } ktx = ktx / sw / 2.0; ktx2 = ktx2 / sw / 2.0; /* Bx */ for (j = 0; j < size; j++) { long int oldid = (long int) VECTOR(*idx)[j]; igraph_real_t str = VECTOR(*strength)[oldid]; to[j] = to[j] - ktx * str; VECTOR(*tmp)[j] = VECTOR(*tmp)[j] - ktx2 * str; } /* -d_ij summa l in G B_il */ for (j = 0; j < size; j++) { to[j] -= VECTOR(*tmp)[j] * from[j]; } return 0; } void igraph_i_levc_free(igraph_vector_ptr_t *ptr) { long int i, n = igraph_vector_ptr_size(ptr); for (i = 0; i < n; i++) { igraph_vector_t *v = VECTOR(*ptr)[i]; if (v) { igraph_vector_destroy(v); igraph_free(v); } } } void igraph_i_error_handler_none(const char *reason, const char *file, int line, int igraph_errno) { IGRAPH_UNUSED(reason); IGRAPH_UNUSED(file); IGRAPH_UNUSED(line); IGRAPH_UNUSED(igraph_errno); /* do nothing */ } /** * \ingroup communities * \function igraph_community_leading_eigenvector * \brief Leading eigenvector community finding (proper version). * * Newman's leading eigenvector method for detecting community * structure. This is the proper implementation of the recursive, * divisive algorithm: each split is done by maximizing the modularity * regarding the original network, see MEJ Newman: Finding community * structure in networks using the eigenvectors of matrices, * Phys Rev E 74:036104 (2006). * * \param graph The undirected input graph. * \param weights The weights of the edges, or a null pointer for * unweighted graphs. * \param merges The result of the algorithm, a matrix containing the * information about the splits performed. The matrix is built in * the opposite way however, it is like the result of an * agglomerative algorithm. If at the end of the algorithm (after * \p steps steps was done) there are p communities, * then these are numbered from zero to p-1. The * first line of the matrix contains the first merge * (which is in reality the last split) of two communities into * community p, the merge in the second line forms * community p+1, etc. The matrix should be * initialized before calling and will be resized as needed. * This argument is ignored of it is \c NULL. * \param membership The membership of the vertices after all the * splits were performed will be stored here. The vector must be * initialized before calling and will be resized as needed. * This argument is ignored if it is \c NULL. This argument can * also be used to supply a starting configuration for the community * finding, in the format of a membership vector. In this case the * \p start argument must be set to 1. * \param steps The maximum number of steps to perform. It might * happen that some component (or the whole network) has no * underlying community structure and no further steps can be * done. If you want as many steps as possible then supply the * number of vertices in the network here. * \param options The options for ARPACK. \c n is always * overwritten. \c ncv is set to at least 4. * \param modularity If not a null pointer, then it must be a pointer * to a real number and the modularity score of the final division * is stored here. * \param start Boolean, whether to use the community structure given * in the \p membership argument as a starting point. * \param eigenvalues Pointer to an initialized vector or a null * pointer. If not a null pointer, then the eigenvalues calculated * along the community structure detection are stored here. The * non-positive eigenvalues, that do not result a split, are stored * as well. * \param eigenvectors If not a null pointer, then the eigenvectors * that are calculated in each step of the algorithm, are stored here, * in a pointer vector. Each eigenvector is stored in an * \ref igraph_vector_t object. The user is responsible of * deallocating the memory that belongs to the individual vectors, * by calling first \ref igraph_vector_destroy(), and then * free() on them. * \param history Pointer to an initialized vector or a null pointer. * If not a null pointer, then a trace of the algorithm is stored * here, encoded numerically. The various operations: * \clist * \cli IGRAPH_LEVC_HIST_START_FULL * Start the algorithm from an initial state where each connected * component is a separate community. * \cli IGRAPH_LEVC_HIST_START_GIVEN * Start the algorithm from a given community structure. The next * value in the vector contains the initial number of * communities. * \cli IGRAPH_LEVC_HIST_SPLIT * Split a community into two communities. The id of the splitted * community is given in the next element of the history vector. * The id of the first new community is the same as the id of the * splitted community. The id of the second community equals to * the number of communities before the split. * \cli IGRAPH_LEVC_HIST_FAILED * Tried to split a community, but it was not worth it, as it * does not result in a bigger modularity value. The id of the * community is given in the next element of the vector. * \endclist * \param callback A null pointer or a function of type \ref * igraph_community_leading_eigenvector_callback_t. If given, this * callback function is called after each eigenvector/eigenvalue * calculation. If the callback returns a non-zero value, then the * community finding algorithm stops. See the arguments passed to * the callback at the documentation of \ref * igraph_community_leading_eigenvector_callback_t. * \param callback_extra Extra argument to pass to the callback * function. * \return Error code. * * \sa \ref igraph_community_walktrap() and \ref * igraph_community_spinglass() for other community structure * detection methods. * * Time complexity: O(|E|+|V|^2*steps), |V| is the number of vertices, * |E| the number of edges, steps the number of splits * performed. */ int igraph_community_leading_eigenvector(const igraph_t *graph, const igraph_vector_t *weights, igraph_matrix_t *merges, igraph_vector_t *membership, igraph_integer_t steps, igraph_arpack_options_t *options, igraph_real_t *modularity, igraph_bool_t start, igraph_vector_t *eigenvalues, igraph_vector_ptr_t *eigenvectors, igraph_vector_t *history, igraph_community_leading_eigenvector_callback_t *callback, void *callback_extra) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_dqueue_t tosplit; igraph_vector_t idx, idx2, mymerges; igraph_vector_t strength, tmp; long int staken = 0; igraph_adjlist_t adjlist; igraph_inclist_t inclist; long int i, j, k, l; long int communities; igraph_vector_t vmembership, *mymembership = membership; igraph_i_community_leading_eigenvector_data_t extra; igraph_arpack_storage_t storage; igraph_real_t mod = 0; igraph_arpack_function_t *arpcb1 = weights ? igraph_i_community_leading_eigenvector_weighted : igraph_i_community_leading_eigenvector; igraph_arpack_function_t *arpcb2 = weights ? igraph_i_community_leading_eigenvector2_weighted : igraph_i_community_leading_eigenvector2; igraph_real_t sumweights = 0.0; if (weights && no_of_edges != igraph_vector_size(weights)) { IGRAPH_ERROR("Invalid weight vector length", IGRAPH_EINVAL); } if (start && !membership) { IGRAPH_ERROR("Cannot start from given configuration if memberships " "missing", IGRAPH_EINVAL); } if (start && membership && igraph_vector_size(membership) != no_of_nodes) { IGRAPH_ERROR("Wrong length for vector of predefined memberships", IGRAPH_EINVAL); } if (start && membership && igraph_vector_max(membership) >= no_of_nodes) { IGRAPH_WARNING("Too many communities in membership start vector"); } if (igraph_is_directed(graph)) { IGRAPH_WARNING("This method was developed for undirected graphs"); } if (steps < 0 || steps > no_of_nodes - 1) { steps = (igraph_integer_t) no_of_nodes - 1; } if (!membership) { mymembership = &vmembership; IGRAPH_VECTOR_INIT_FINALLY(mymembership, 0); } IGRAPH_VECTOR_INIT_FINALLY(&mymerges, 0); IGRAPH_CHECK(igraph_vector_reserve(&mymerges, steps * 2)); IGRAPH_VECTOR_INIT_FINALLY(&idx, 0); if (eigenvalues) { igraph_vector_clear(eigenvalues); } if (eigenvectors) { igraph_vector_ptr_clear(eigenvectors); IGRAPH_FINALLY(igraph_i_levc_free, eigenvectors); } IGRAPH_STATUS("Starting leading eigenvector method.\n", 0); if (!start) { /* Calculate the weakly connected components in the graph and use them as * an initial split */ IGRAPH_CHECK(igraph_clusters(graph, mymembership, &idx, 0, IGRAPH_WEAK)); communities = igraph_vector_size(&idx); IGRAPH_STATUSF(("Starting from %li component(s).\n", 0, communities)); if (history) { IGRAPH_CHECK(igraph_vector_push_back(history, IGRAPH_LEVC_HIST_START_FULL)); } } else { /* Just create the idx vector for the given membership vector */ communities = (long int) igraph_vector_max(mymembership) + 1; IGRAPH_STATUSF(("Starting from given membership vector with %li " "communities.\n", 0, communities)); if (history) { IGRAPH_CHECK(igraph_vector_push_back(history, IGRAPH_LEVC_HIST_START_GIVEN)); IGRAPH_CHECK(igraph_vector_push_back(history, communities)); } IGRAPH_CHECK(igraph_vector_resize(&idx, communities)); igraph_vector_null(&idx); for (i = 0; i < no_of_nodes; i++) { int t = (int) VECTOR(*mymembership)[i]; VECTOR(idx)[t] += 1; } } IGRAPH_DQUEUE_INIT_FINALLY(&tosplit, 100); for (i = 0; i < communities; i++) { if (VECTOR(idx)[i] > 2) { igraph_dqueue_push(&tosplit, i); } } for (i = 1; i < communities; i++) { /* Record merge */ IGRAPH_CHECK(igraph_vector_push_back(&mymerges, i - 1)); IGRAPH_CHECK(igraph_vector_push_back(&mymerges, i)); if (eigenvalues) { IGRAPH_CHECK(igraph_vector_push_back(eigenvalues, IGRAPH_NAN)); } if (eigenvectors) { igraph_vector_t *v = igraph_Calloc(1, igraph_vector_t); if (!v) { IGRAPH_ERROR("Cannot do leading eigenvector community detection", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, v); IGRAPH_VECTOR_INIT_FINALLY(v, 0); IGRAPH_CHECK(igraph_vector_ptr_push_back(eigenvectors, v)); IGRAPH_FINALLY_CLEAN(2); } if (history) { IGRAPH_CHECK(igraph_vector_push_back(history, IGRAPH_LEVC_HIST_SPLIT)); IGRAPH_CHECK(igraph_vector_push_back(history, i - 1)); } } staken = communities - 1; IGRAPH_VECTOR_INIT_FINALLY(&tmp, no_of_nodes); IGRAPH_CHECK(igraph_vector_resize(&idx, no_of_nodes)); igraph_vector_null(&idx); IGRAPH_VECTOR_INIT_FINALLY(&idx2, no_of_nodes); if (!weights) { IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist); } else { IGRAPH_CHECK(igraph_inclist_init(graph, &inclist, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_inclist_destroy, &inclist); IGRAPH_VECTOR_INIT_FINALLY(&strength, no_of_nodes); IGRAPH_CHECK(igraph_strength(graph, &strength, igraph_vss_all(), IGRAPH_ALL, IGRAPH_LOOPS, weights)); sumweights = igraph_vector_sum(weights); } options->ncv = 0; /* 0 means "automatic" in igraph_arpack_rssolve */ options->start = 0; options->which[0] = 'L'; options->which[1] = 'A'; /* Memory for ARPACK */ /* We are allocating memory for 20 eigenvectors since options->ncv won't be * larger than 20 when using automatic mode in igraph_arpack_rssolve */ IGRAPH_CHECK(igraph_arpack_storage_init(&storage, (int) no_of_nodes, 20, (int) no_of_nodes, 1)); IGRAPH_FINALLY(igraph_arpack_storage_destroy, &storage); extra.idx = &idx; extra.idx2 = &idx2; extra.tmp = &tmp; extra.adjlist = &adjlist; extra.inclist = &inclist; extra.weights = weights; extra.sumweights = sumweights; extra.graph = graph; extra.strength = &strength; extra.no_of_edges = no_of_edges; extra.mymembership = mymembership; while (!igraph_dqueue_empty(&tosplit) && staken < steps) { long int comm = (long int) igraph_dqueue_pop_back(&tosplit); /* depth first search */ long int size = 0; igraph_real_t tmpev; IGRAPH_STATUSF(("Trying to split community %li... ", 0, comm)); IGRAPH_ALLOW_INTERRUPTION(); for (i = 0; i < no_of_nodes; i++) { if (VECTOR(*mymembership)[i] == comm) { VECTOR(idx)[size] = i; VECTOR(idx2)[i] = size++; } } staken++; if (size <= 2) { continue; } /* We solve two eigenproblems, one for the original modularity matrix, and one for the modularity matrix after deleting the last row and last column from it. This is a trick to find multiple leading eigenvalues, because ARPACK is sometimes unstable when the first two eigenvalues are requested, but it does much better for the single principal eigenvalue. */ /* We start with the smaller eigenproblem. */ options->n = (int) size - 1; options->info = 0; options->nev = 1; options->ldv = 0; options->ncv = 0; /* 0 means "automatic" in igraph_arpack_rssolve */ options->nconv = 0; options->lworkl = 0; /* we surely have enough space */ extra.comm = comm; /* We try calling the solver twice, once from a random starting point, once from a fixed one. This is because for some hard cases it tends to fail. We need to suppress error handling for the first call. */ { int i; igraph_error_handler_t *errh = igraph_set_error_handler(igraph_i_error_handler_none); igraph_warning_handler_t *warnh = igraph_set_warning_handler(igraph_warning_handler_ignore); igraph_arpack_rssolve(arpcb2, &extra, options, &storage, /*values=*/ 0, /*vectors=*/ 0); igraph_set_error_handler(errh); igraph_set_warning_handler(warnh); if (options->nconv < 1) { /* Call again from a fixed starting point. Note that we cannot use a * fixed all-1 starting vector as sometimes ARPACK would return a * 'starting vector is zero' error -- this is of course not true but * it's a result of ARPACK >= 3.6.3 trying to force the starting vector * into the range of OP (i.e. the matrix being solved). The initial * vector we use here seems to work, but I have no theoretical argument * for its usage; it just happens to work. */ options->start = 1; options->info = 0; options->ncv = 0; options->lworkl = 0; /* we surely have enough space */ for (i = 0; i < options->n ; i++) { storage.resid[i] = i % 2 ? 1 : -1; } IGRAPH_CHECK(igraph_arpack_rssolve(arpcb2, &extra, options, &storage, /*values=*/ 0, /*vectors=*/ 0)); options->start = 0; } } if (options->nconv < 1) { IGRAPH_ERROR("ARPACK did not converge", IGRAPH_ARPACK_FAILED); } tmpev = storage.d[0]; /* Now we do the original eigenproblem, again, twice if needed */ options->n = (int) size; options->info = 0; options->nev = 1; options->ldv = 0; options->nconv = 0; options->lworkl = 0; /* we surely have enough space */ options->ncv = 0; /* 0 means "automatic" in igraph_arpack_rssolve */ { int i; igraph_error_handler_t *errh = igraph_set_error_handler(igraph_i_error_handler_none); igraph_arpack_rssolve(arpcb1, &extra, options, &storage, /*values=*/ 0, /*vectors=*/ 0); igraph_set_error_handler(errh); if (options->nconv < 1) { /* Call again from a fixed starting point. See the comment a few lines * above about the exact choice of this starting vector */ options->start = 1; options->info = 0; options->ncv = 0; options->lworkl = 0; /* we surely have enough space */ for (i = 0; i < options->n; i++) { storage.resid[i] = i % 2 ? 1 : -1; } IGRAPH_CHECK(igraph_arpack_rssolve(arpcb1, &extra, options, &storage, /*values=*/ 0, /*vectors=*/ 0)); options->start = 0; } } if (options->nconv < 1) { IGRAPH_ERROR("ARPACK did not converge", IGRAPH_ARPACK_FAILED); } /* Ok, we have the leading eigenvector of the modularity matrix*/ /* ---------------------------------------------------------------*/ /* To avoid numeric errors */ if (fabs(storage.d[0]) < 1e-8) { storage.d[0] = 0; } /* We replace very small (in absolute value) elements of the leading eigenvector with zero, to get the same result, consistently.*/ for (i = 0; i < size; i++) { if (fabs(storage.v[i]) < 1e-8) { storage.v[i] = 0; } } /* Just to have the always the same result, we multiply by -1 if the first (nonzero) element is not positive. */ for (i = 0; i < size; i++) { if (storage.v[i] != 0) { break; } } if (i < size && storage.v[i] < 0) { for (i = 0; i < size; i++) { storage.v[i] = - storage.v[i]; } } /* ---------------------------------------------------------------*/ if (callback) { igraph_vector_t vv; int ret; igraph_vector_view(&vv, storage.v, size); ret = callback(mymembership, comm, storage.d[0], &vv, arpcb1, &extra, callback_extra); if (ret) { break; } } if (eigenvalues) { IGRAPH_CHECK(igraph_vector_push_back(eigenvalues, storage.d[0])); } if (eigenvectors) { igraph_vector_t *v = igraph_Calloc(1, igraph_vector_t); if (!v) { IGRAPH_ERROR("Cannot do leading eigenvector community detection", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, v); IGRAPH_VECTOR_INIT_FINALLY(v, size); for (i = 0; i < size; i++) { VECTOR(*v)[i] = storage.v[i]; } IGRAPH_CHECK(igraph_vector_ptr_push_back(eigenvectors, v)); IGRAPH_FINALLY_CLEAN(2); } if (storage.d[0] <= 0) { IGRAPH_STATUS("no split.\n", 0); if (history) { IGRAPH_CHECK(igraph_vector_push_back(history, IGRAPH_LEVC_HIST_FAILED)); IGRAPH_CHECK(igraph_vector_push_back(history, comm)); } continue; } /* Check for multiple leading eigenvalues */ if (fabs(storage.d[0] - tmpev) < 1e-8) { IGRAPH_STATUS("multiple principal eigenvalue, no split.\n", 0); if (history) { IGRAPH_CHECK(igraph_vector_push_back(history, IGRAPH_LEVC_HIST_FAILED)); IGRAPH_CHECK(igraph_vector_push_back(history, comm)); } continue; } /* Count the number of vertices in each community after the split */ l = 0; for (j = 0; j < size; j++) { if (storage.v[j] < 0) { storage.v[j] = -1; l++; } else { storage.v[j] = 1; } } if (l == 0 || l == size) { IGRAPH_STATUS("no split.\n", 0); if (history) { IGRAPH_CHECK(igraph_vector_push_back(history, IGRAPH_LEVC_HIST_FAILED)); IGRAPH_CHECK(igraph_vector_push_back(history, comm)); } continue; } /* Check that Q increases with our choice of split */ arpcb1(storage.v + size, storage.v, (int) size, &extra); mod = 0; for (i = 0; i < size; i++) { mod += storage.v[size + i] * storage.v[i]; } if (mod <= 1e-8) { IGRAPH_STATUS("no modularity increase, no split.\n", 0); if (history) { IGRAPH_CHECK(igraph_vector_push_back(history, IGRAPH_LEVC_HIST_FAILED)); IGRAPH_CHECK(igraph_vector_push_back(history, comm)); } continue; } communities++; IGRAPH_STATUS("split.\n", 0); /* Rewrite the mymembership vector */ for (j = 0; j < size; j++) { if (storage.v[j] < 0) { long int oldid = (long int) VECTOR(idx)[j]; VECTOR(*mymembership)[oldid] = communities - 1; } } /* Record merge */ IGRAPH_CHECK(igraph_vector_push_back(&mymerges, comm)); IGRAPH_CHECK(igraph_vector_push_back(&mymerges, communities - 1)); if (history) { IGRAPH_CHECK(igraph_vector_push_back(history, IGRAPH_LEVC_HIST_SPLIT)); IGRAPH_CHECK(igraph_vector_push_back(history, comm)); } /* Store the resulting communities in the queue if needed */ if (l > 1) { IGRAPH_CHECK(igraph_dqueue_push(&tosplit, communities - 1)); } if (size - l > 1) { IGRAPH_CHECK(igraph_dqueue_push(&tosplit, comm)); } } igraph_arpack_storage_destroy(&storage); IGRAPH_FINALLY_CLEAN(1); if (!weights) { igraph_adjlist_destroy(&adjlist); IGRAPH_FINALLY_CLEAN(1); } else { igraph_inclist_destroy(&inclist); igraph_vector_destroy(&strength); IGRAPH_FINALLY_CLEAN(2); } igraph_dqueue_destroy(&tosplit); igraph_vector_destroy(&tmp); igraph_vector_destroy(&idx2); IGRAPH_FINALLY_CLEAN(3); IGRAPH_STATUS("Done.\n", 0); /* reform the mymerges vector */ if (merges) { igraph_vector_null(&idx); l = igraph_vector_size(&mymerges); k = communities; j = 0; IGRAPH_CHECK(igraph_matrix_resize(merges, l / 2, 2)); for (i = l; i > 0; i -= 2) { long int from = (long int) VECTOR(mymerges)[i - 1]; long int to = (long int) VECTOR(mymerges)[i - 2]; MATRIX(*merges, j, 0) = VECTOR(mymerges)[i - 2]; MATRIX(*merges, j, 1) = VECTOR(mymerges)[i - 1]; if (VECTOR(idx)[from] != 0) { MATRIX(*merges, j, 1) = VECTOR(idx)[from] - 1; } if (VECTOR(idx)[to] != 0) { MATRIX(*merges, j, 0) = VECTOR(idx)[to] - 1; } VECTOR(idx)[to] = ++k; j++; } } if (eigenvectors) { IGRAPH_FINALLY_CLEAN(1); } igraph_vector_destroy(&idx); igraph_vector_destroy(&mymerges); IGRAPH_FINALLY_CLEAN(2); if (modularity) { IGRAPH_CHECK(igraph_modularity(graph, mymembership, modularity, weights)); } if (!membership) { igraph_vector_destroy(mymembership); IGRAPH_FINALLY_CLEAN(1); } return 0; } /** * \function igraph_le_community_to_membership * Vertex membership from the leading eigenvector community structure * * This function creates a membership vector from the * result of \ref igraph_community_leading_eigenvector(), * It takes \c membership * and performs \c steps merges, according to the supplied * \c merges matrix. * \param merges The matrix defining the merges to make. * This is usually from the output of the leading eigenvector community * structure detection routines. * \param steps The number of steps to make according to \c merges. * \param membership Initially the starting membership vector, * on output the resulting membership vector, after performing \c steps merges. * \param csize Optionally the sizes of the communities is stored here, * if this is not a null pointer, but an initialized vector. * \return Error code. * * Time complexity: O(|V|), the number of vertices. */ int igraph_le_community_to_membership(const igraph_matrix_t *merges, igraph_integer_t steps, igraph_vector_t *membership, igraph_vector_t *csize) { long int no_of_nodes = igraph_vector_size(membership); igraph_vector_t fake_memb; long int components, i; if (igraph_matrix_nrow(merges) < steps) { IGRAPH_ERROR("`steps' to big or `merges' matrix too short", IGRAPH_EINVAL); } components = (long int) igraph_vector_max(membership) + 1; if (components > no_of_nodes) { IGRAPH_ERROR("Invalid membership vector, too many components", IGRAPH_EINVAL); } if (steps >= components) { IGRAPH_ERROR("Cannot make `steps' steps from supplied membership vector", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(&fake_memb, components); /* Check membership vector */ for (i = 0; i < no_of_nodes; i++) { if (VECTOR(*membership)[i] < 0) { IGRAPH_ERROR("Invalid membership vector, negative id", IGRAPH_EINVAL); } VECTOR(fake_memb)[ (long int) VECTOR(*membership)[i] ] += 1; } for (i = 0; i < components; i++) { if (VECTOR(fake_memb)[i] == 0) { IGRAPH_ERROR("Invalid membership vector, empty cluster", IGRAPH_EINVAL); } } IGRAPH_CHECK(igraph_community_to_membership(merges, (igraph_integer_t) components, steps, &fake_memb, 0)); /* Ok, now we have the membership of the initial components, rewrite the original membership vector. */ if (csize) { IGRAPH_CHECK(igraph_vector_resize(csize, components - steps)); igraph_vector_null(csize); } for (i = 0; i < no_of_nodes; i++) { VECTOR(*membership)[i] = VECTOR(fake_memb)[ (long int) VECTOR(*membership)[i] ]; if (csize) { VECTOR(*csize)[ (long int) VECTOR(*membership)[i] ] += 1; } } igraph_vector_destroy(&fake_memb); IGRAPH_FINALLY_CLEAN(1); return 0; } /********************************************************************/ /** * \ingroup communities * \function igraph_community_fluid_communities * \brief Community detection algorithm based on the simple idea of * several fluids interacting in a non-homogeneous environment * (the graph topology), expanding and contracting based on their * interaction and density. * * This function implements the community detection method described in: * Parés F, Gasulla DG, et. al. (2018) Fluid Communities: A Competitive, * Scalable and Diverse Community Detection Algorithm. In: Complex Networks * & Their Applications VI: Proceedings of Complex Networks 2017 (The Sixth * International Conference on Complex Networks and Their Applications), * Springer, vol 689, p 229. * * \param graph The input graph. The graph must be simple and connected. * Empty graphs are not supported as well as single vertex graphs. * Edge directions are ignored. Weights are not considered. * \param no_of_communities The number of communities to be found. Must be * greater than 0 and fewer than number of vertices in the graph. * \param membership The result vector mapping vertices to the communities * they are assigned to. * \param modularity If not a null pointer, then it must be a pointer * to a real number. The modularity score of the detected community * structure is stored here. * \return Error code. * * Time complexity: O(|E|) * * \example examples/tests/igraph_community_fluid_communities.c */ int igraph_community_fluid_communities(const igraph_t *graph, igraph_integer_t no_of_communities, igraph_vector_t *membership, igraph_real_t *modularity) { /* Declaration of variables */ long int no_of_nodes, i, j, k, kv1; igraph_adjlist_t al; double max_density; igraph_bool_t res, running; igraph_vector_t node_order, density, label_counters, dominant_labels, nonzero_labels; igraph_vector_int_t com_to_numvertices; /* Initialization of variables needed for initial checking */ no_of_nodes = igraph_vcount(graph); /* Checking input values */ if (no_of_nodes < 2) { IGRAPH_ERROR("Empty and single vertex graphs are not supported.", IGRAPH_EINVAL); } if ((long int) no_of_communities < 1) { IGRAPH_ERROR("'no_of_communities' must be greater than 0.", IGRAPH_EINVAL); } if ((long int) no_of_communities > no_of_nodes) { IGRAPH_ERROR("'no_of_communities' can not be greater than number of nodes in " "the graph.", IGRAPH_EINVAL); } igraph_is_simple(graph, &res); if (!res) { IGRAPH_ERROR("Only simple graphs are supported.", IGRAPH_EINVAL); } igraph_is_connected(graph, &res, IGRAPH_WEAK); if (!res) { IGRAPH_ERROR("Disconnected graphs are not supported.", IGRAPH_EINVAL); } if (igraph_is_directed(graph)) { IGRAPH_WARNING("Edge directions are ignored."); } /* Internal variables initialization */ max_density = 1.0; running = 1; /* Resize membership vector (number of nodes) */ IGRAPH_CHECK(igraph_vector_resize(membership, no_of_nodes)); /* Initialize density and com_to_numvertices vectors */ IGRAPH_CHECK(igraph_vector_init(&density, (long int) no_of_communities)); IGRAPH_FINALLY(igraph_vector_destroy, &density); IGRAPH_CHECK(igraph_vector_int_init(&com_to_numvertices, (long int) no_of_communities)); IGRAPH_FINALLY(igraph_vector_int_destroy, &com_to_numvertices); /* Initialize node ordering vector */ IGRAPH_CHECK(igraph_vector_init_seq(&node_order, 0, no_of_nodes - 1)); IGRAPH_FINALLY(igraph_vector_destroy, &node_order); /* Initialize the membership vector with 0 values */ igraph_vector_null(membership); /* Initialize densities to max_density */ igraph_vector_fill(&density, max_density); RNG_BEGIN(); /* Initialize com_to_numvertices and initialize communities into membership vector */ IGRAPH_CHECK(igraph_vector_shuffle(&node_order)); for (i = 0; i < no_of_communities; i++) { /* Initialize membership at initial nodes for each community * where 0 refers to have no label*/ VECTOR(*membership)[(long int)VECTOR(node_order)[i]] = i + 1.0; /* Initialize com_to_numvertices list: Number of vertices for each community */ VECTOR(com_to_numvertices)[i] = 1; } /* Create an adjacency list representation for efficiency. */ IGRAPH_CHECK(igraph_adjlist_init(graph, &al, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_adjlist_destroy, &al); /* Create storage space for counting distinct labels and dominant ones */ IGRAPH_VECTOR_INIT_FINALLY(&dominant_labels, (long int) no_of_communities); IGRAPH_VECTOR_INIT_FINALLY(&nonzero_labels, (long int) no_of_communities); IGRAPH_CHECK(igraph_vector_init(&label_counters, (long int) no_of_communities)); IGRAPH_FINALLY(igraph_vector_destroy, &label_counters); /* running is the convergence boolean variable */ running = 1; while (running) { /* Declarations of varibales used inside main loop */ long int v1, size, rand_idx; igraph_real_t max_count, label_counter_diff; igraph_vector_int_t *neis; igraph_bool_t same_label_in_dominant; running = 0; /* Shuffle the node ordering vector */ IGRAPH_CHECK(igraph_vector_shuffle(&node_order)); /* In the prescribed order, loop over the vertices and reassign labels */ for (i = 0; i < no_of_nodes; i++) { /* Clear dominant_labels and nonzero_labels vectors */ igraph_vector_clear(&dominant_labels); igraph_vector_null(&label_counters); /* Obtain actual node index */ v1 = (long int) VECTOR(node_order)[i]; /* Take into account same label in updating rule */ kv1 = (long int) VECTOR(*membership)[v1]; max_count = 0.0; if (kv1 != 0) { VECTOR(label_counters)[kv1 - 1] += VECTOR(density)[kv1 - 1]; /* Set up max_count */ max_count = VECTOR(density)[kv1 - 1]; /* Initialize dominant_labels */ IGRAPH_CHECK(igraph_vector_resize(&dominant_labels, 1)); VECTOR(dominant_labels)[0] = kv1; } /* Count the weights corresponding to different labels */ neis = igraph_adjlist_get(&al, v1); size = igraph_vector_int_size(neis); for (j = 0; j < size; j++) { k = (long int) VECTOR(*membership)[(long)VECTOR(*neis)[j]]; /* skip if it has no label yet */ if (k == 0) { continue; } /* Update label counter and evaluate diff against max_count*/ VECTOR(label_counters)[k - 1] += VECTOR(density)[k - 1]; label_counter_diff = VECTOR(label_counters)[k - 1] - max_count; /* Check if this label must be included in dominant_labels vector */ if (label_counter_diff > 0.0001) { max_count = VECTOR(label_counters)[k - 1]; IGRAPH_CHECK(igraph_vector_resize(&dominant_labels, 1)); VECTOR(dominant_labels)[0] = k; } else if (-0.0001 < label_counter_diff && label_counter_diff < 0.0001) { IGRAPH_CHECK(igraph_vector_push_back(&dominant_labels, k)); } } if (!igraph_vector_empty(&dominant_labels)) { /* Maintain same label if it exists in dominant_labels */ same_label_in_dominant = igraph_vector_contains(&dominant_labels, kv1); if (!same_label_in_dominant) { /* We need at least one more iteration */ running = 1; /* Select randomly from the dominant labels */ rand_idx = RNG_INTEGER(0, igraph_vector_size(&dominant_labels) - 1); k = (long int) VECTOR(dominant_labels)[rand_idx]; if (kv1 != 0) { /* Subtract 1 vertex from corresponding community in com_to_numvertices */ VECTOR(com_to_numvertices)[kv1 - 1] -= 1; /* Re-calculate density for community kv1 */ VECTOR(density)[kv1 - 1] = max_density / VECTOR(com_to_numvertices)[kv1 - 1]; } /* Update vertex new label */ VECTOR(*membership)[v1] = k; /* Add 1 vertex to corresponding new community in com_to_numvertices */ VECTOR(com_to_numvertices)[k - 1] += 1; /* Re-calculate density for new community k */ VECTOR(density)[k - 1] = max_density / VECTOR(com_to_numvertices)[k - 1]; } } } } RNG_END(); /* Shift back the membership vector */ /* There must be no 0 labels in membership vector at this point */ for (i = 0; i < no_of_nodes; i++) { VECTOR(*membership)[i] -= 1; /* Something went wrong: At least one vertex has no community assigned */ if (VECTOR(*membership)[i] < 0) { IGRAPH_ERROR("Something went wrong during execution. One or more vertices got " "no community assigned at algorithm convergence.", IGRAPH_EINTERNAL); } } igraph_adjlist_destroy(&al); IGRAPH_FINALLY_CLEAN(1); if (modularity) { IGRAPH_CHECK(igraph_modularity(graph, membership, modularity, NULL)); } igraph_vector_destroy(&node_order); igraph_vector_destroy(&density); igraph_vector_int_destroy(&com_to_numvertices); igraph_vector_destroy(&label_counters); igraph_vector_destroy(&dominant_labels); igraph_vector_destroy(&nonzero_labels); IGRAPH_FINALLY_CLEAN(6); return 0; } /********************************************************************/ /** * \ingroup communities * \function igraph_community_label_propagation * \brief Community detection based on label propagation * * This function implements the community detection method described in: * Raghavan, U.N. and Albert, R. and Kumara, S.: Near linear time algorithm * to detect community structures in large-scale networks. Phys Rev E * 76, 036106. (2007). This version extends the original method by * the ability to take edge weights into consideration and also * by allowing some labels to be fixed. * * * Weights are taken into account as follows: when the new label of node * i is determined, the algorithm iterates over all edges incident on * node i and calculate the total weight of edges leading to other * nodes with label 0, 1, 2, ..., k-1 (where k is the number of possible * labels). The new label of node i will then be the label whose edges * (among the ones incident on node i) have the highest total weight. * * \param graph The input graph, should be undirected to make sense. * \param membership The membership vector, the result is returned here. * For each vertex it gives the ID of its community (label). * \param weights The weight vector, it should contain a positive * weight for all the edges. * \param initial The initial state. If NULL, every vertex will have * a different label at the beginning. Otherwise it must be a vector * with an entry for each vertex. Non-negative values denote different * labels, negative entries denote vertices without labels. * \param fixed Boolean vector denoting which labels are fixed. Of course * this makes sense only if you provided an initial state, otherwise * this element will be ignored. Also note that vertices without labels * cannot be fixed. * \param modularity If not a null pointer, then it must be a pointer * to a real number. The modularity score of the detected community * structure is stored here. * \return Error code. * * Time complexity: O(m+n) * * \example examples/simple/igraph_community_label_propagation.c */ int igraph_community_label_propagation(const igraph_t *graph, igraph_vector_t *membership, const igraph_vector_t *weights, const igraph_vector_t *initial, igraph_vector_bool_t *fixed, igraph_real_t *modularity) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); long int no_of_not_fixed_nodes = no_of_nodes; long int i, j, k; igraph_adjlist_t al; igraph_inclist_t il; igraph_bool_t running = 1; igraph_vector_t label_counters, dominant_labels, nonzero_labels, node_order; /* The implementation uses a trick to avoid negative array indexing: * elements of the membership vector are increased by 1 at the start * of the algorithm; this to allow us to denote unlabeled vertices * (if any) by zeroes. The membership vector is shifted back in the end */ /* Do some initial checks */ if (fixed && igraph_vector_bool_size(fixed) != no_of_nodes) { IGRAPH_ERROR("Invalid fixed labeling vector length", IGRAPH_EINVAL); } if (weights) { if (igraph_vector_size(weights) != no_of_edges) { IGRAPH_ERROR("Invalid weight vector length", IGRAPH_EINVAL); } else if (igraph_vector_min(weights) < 0) { IGRAPH_ERROR("Weights must be non-negative", IGRAPH_EINVAL); } } if (fixed && !initial) { IGRAPH_WARNING("Ignoring fixed vertices as no initial labeling given"); } IGRAPH_CHECK(igraph_vector_resize(membership, no_of_nodes)); if (initial) { if (igraph_vector_size(initial) != no_of_nodes) { IGRAPH_ERROR("Invalid initial labeling vector length", IGRAPH_EINVAL); } /* Check if the labels used are valid, initialize membership vector */ for (i = 0; i < no_of_nodes; i++) { if (VECTOR(*initial)[i] < 0) { VECTOR(*membership)[i] = 0; } else { VECTOR(*membership)[i] = floor(VECTOR(*initial)[i]) + 1; } } if (fixed) { for (i = 0; i < no_of_nodes; i++) { if (VECTOR(*fixed)[i]) { if (VECTOR(*membership)[i] == 0) { IGRAPH_WARNING("Fixed nodes cannot be unlabeled, ignoring them"); VECTOR(*fixed)[i] = 0; } else { no_of_not_fixed_nodes--; } } } } i = (long int) igraph_vector_max(membership); if (i > no_of_nodes) { IGRAPH_ERROR("elements of the initial labeling vector must be between 0 and |V|-1", IGRAPH_EINVAL); } if (i <= 0) { IGRAPH_ERROR("at least one vertex must be labeled in the initial labeling", IGRAPH_EINVAL); } } else { for (i = 0; i < no_of_nodes; i++) { VECTOR(*membership)[i] = i + 1; } } /* Create an adjacency/incidence list representation for efficiency. * For the unweighted case, the adjacency list is enough. For the * weighted case, we need the incidence list */ if (weights) { IGRAPH_CHECK(igraph_inclist_init(graph, &il, IGRAPH_IN)); IGRAPH_FINALLY(igraph_inclist_destroy, &il); } else { IGRAPH_CHECK(igraph_adjlist_init(graph, &al, IGRAPH_IN)); IGRAPH_FINALLY(igraph_adjlist_destroy, &al); } /* Create storage space for counting distinct labels and dominant ones */ IGRAPH_VECTOR_INIT_FINALLY(&label_counters, no_of_nodes + 1); IGRAPH_VECTOR_INIT_FINALLY(&dominant_labels, 0); IGRAPH_VECTOR_INIT_FINALLY(&nonzero_labels, 0); IGRAPH_CHECK(igraph_vector_reserve(&dominant_labels, 2)); RNG_BEGIN(); /* Initialize node ordering vector with only the not fixed nodes */ if (fixed) { IGRAPH_VECTOR_INIT_FINALLY(&node_order, no_of_not_fixed_nodes); for (i = 0, j = 0; i < no_of_nodes; i++) { if (!VECTOR(*fixed)[i]) { VECTOR(node_order)[j] = i; j++; } } } else { IGRAPH_CHECK(igraph_vector_init_seq(&node_order, 0, no_of_nodes - 1)); IGRAPH_FINALLY(igraph_vector_destroy, &node_order); } running = 1; while (running) { long int v1, num_neis; igraph_real_t max_count; igraph_vector_int_t *neis; igraph_vector_int_t *ineis; igraph_bool_t was_zero; running = 0; /* Shuffle the node ordering vector */ IGRAPH_CHECK(igraph_vector_shuffle(&node_order)); /* In the prescribed order, loop over the vertices and reassign labels */ for (i = 0; i < no_of_not_fixed_nodes; i++) { v1 = (long int) VECTOR(node_order)[i]; /* Count the weights corresponding to different labels */ igraph_vector_clear(&dominant_labels); igraph_vector_clear(&nonzero_labels); max_count = 0.0; if (weights) { ineis = igraph_inclist_get(&il, v1); num_neis = igraph_vector_int_size(ineis); for (j = 0; j < num_neis; j++) { k = (long int) VECTOR(*membership)[ (long)IGRAPH_OTHER(graph, VECTOR(*ineis)[j], v1) ]; if (k == 0) { continue; /* skip if it has no label yet */ } was_zero = (VECTOR(label_counters)[k] == 0); VECTOR(label_counters)[k] += VECTOR(*weights)[(long)VECTOR(*ineis)[j]]; if (was_zero && VECTOR(label_counters)[k] != 0) { /* counter just became nonzero */ IGRAPH_CHECK(igraph_vector_push_back(&nonzero_labels, k)); } if (max_count < VECTOR(label_counters)[k]) { max_count = VECTOR(label_counters)[k]; IGRAPH_CHECK(igraph_vector_resize(&dominant_labels, 1)); VECTOR(dominant_labels)[0] = k; } else if (max_count == VECTOR(label_counters)[k]) { IGRAPH_CHECK(igraph_vector_push_back(&dominant_labels, k)); } } } else { neis = igraph_adjlist_get(&al, v1); num_neis = igraph_vector_int_size(neis); for (j = 0; j < num_neis; j++) { k = (long int) VECTOR(*membership)[(long)VECTOR(*neis)[j]]; if (k == 0) { continue; /* skip if it has no label yet */ } VECTOR(label_counters)[k]++; if (VECTOR(label_counters)[k] == 1) { /* counter just became nonzero */ IGRAPH_CHECK(igraph_vector_push_back(&nonzero_labels, k)); } if (max_count < VECTOR(label_counters)[k]) { max_count = VECTOR(label_counters)[k]; IGRAPH_CHECK(igraph_vector_resize(&dominant_labels, 1)); VECTOR(dominant_labels)[0] = k; } else if (max_count == VECTOR(label_counters)[k]) { IGRAPH_CHECK(igraph_vector_push_back(&dominant_labels, k)); } } } if (igraph_vector_size(&dominant_labels) > 0) { /* Select randomly from the dominant labels */ k = RNG_INTEGER(0, igraph_vector_size(&dominant_labels) - 1); k = (long int) VECTOR(dominant_labels)[k]; /* Check if the _current_ label of the node is also dominant */ if (VECTOR(label_counters)[(long)VECTOR(*membership)[v1]] != max_count) { /* Nope, we need at least one more iteration */ running = 1; } VECTOR(*membership)[v1] = k; } /* Clear the nonzero elements in label_counters */ num_neis = igraph_vector_size(&nonzero_labels); for (j = 0; j < num_neis; j++) { VECTOR(label_counters)[(long int)VECTOR(nonzero_labels)[j]] = 0; } } } RNG_END(); /* Shift back the membership vector, permute labels in increasing order */ /* We recycle label_counters here :) */ igraph_vector_fill(&label_counters, -1); j = 0; for (i = 0; i < no_of_nodes; i++) { k = (long)VECTOR(*membership)[i] - 1; if (k >= 0) { if (VECTOR(label_counters)[k] == -1) { /* We have seen this label for the first time */ VECTOR(label_counters)[k] = j; k = j; j++; } else { k = (long int) VECTOR(label_counters)[k]; } } else { /* This is an unlabeled vertex */ } VECTOR(*membership)[i] = k; } if (weights) { igraph_inclist_destroy(&il); } else { igraph_adjlist_destroy(&al); } IGRAPH_FINALLY_CLEAN(1); if (modularity) { IGRAPH_CHECK(igraph_modularity(graph, membership, modularity, weights)); } igraph_vector_destroy(&node_order); igraph_vector_destroy(&label_counters); igraph_vector_destroy(&dominant_labels); igraph_vector_destroy(&nonzero_labels); IGRAPH_FINALLY_CLEAN(4); return 0; } /********************************************************************/ /* Structure storing a community */ typedef struct { igraph_integer_t size; /* Size of the community */ igraph_real_t weight_inside; /* Sum of edge weights inside community */ igraph_real_t weight_all; /* Sum of edge weights starting/ending in the community */ } igraph_i_multilevel_community; /* Global community list structure */ typedef struct { long int communities_no, vertices_no; /* Number of communities, number of vertices */ igraph_real_t weight_sum; /* Sum of edges weight in the whole graph */ igraph_i_multilevel_community *item; /* List of communities */ igraph_vector_t *membership; /* Community IDs */ igraph_vector_t *weights; /* Graph edge weights */ } igraph_i_multilevel_community_list; /* Computes the modularity of a community partitioning */ igraph_real_t igraph_i_multilevel_community_modularity( const igraph_i_multilevel_community_list *communities) { igraph_real_t result = 0; long int i; igraph_real_t m = communities->weight_sum; for (i = 0; i < communities->vertices_no; i++) { if (communities->item[i].size > 0) { result += (communities->item[i].weight_inside - communities->item[i].weight_all * communities->item[i].weight_all / m) / m; } } return result; } typedef struct { long int from; long int to; long int id; } igraph_i_multilevel_link; int igraph_i_multilevel_link_cmp(const void *a, const void *b) { long int r = (((igraph_i_multilevel_link*)a)->from - ((igraph_i_multilevel_link*)b)->from); if (r != 0) { return (int) r; } return (int) (((igraph_i_multilevel_link*)a)->to - ((igraph_i_multilevel_link*)b)->to); } /* removes multiple edges and returns new edge id's for each edge in |E|log|E| */ int igraph_i_multilevel_simplify_multiple(igraph_t *graph, igraph_vector_t *eids) { long int ecount = igraph_ecount(graph); long int i, l = -1, last_from = -1, last_to = -1; igraph_bool_t directed = igraph_is_directed(graph); igraph_integer_t from, to; igraph_vector_t edges; igraph_i_multilevel_link *links; /* Make sure there's enough space in eids to store the new edge IDs */ IGRAPH_CHECK(igraph_vector_resize(eids, ecount)); links = igraph_Calloc(ecount, igraph_i_multilevel_link); if (links == 0) { IGRAPH_ERROR("multi-level community structure detection failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, links); for (i = 0; i < ecount; i++) { igraph_edge(graph, (igraph_integer_t) i, &from, &to); links[i].from = from; links[i].to = to; links[i].id = i; } qsort((void*)links, (size_t) ecount, sizeof(igraph_i_multilevel_link), igraph_i_multilevel_link_cmp); IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); for (i = 0; i < ecount; i++) { if (links[i].from == last_from && links[i].to == last_to) { VECTOR(*eids)[links[i].id] = l; continue; } last_from = links[i].from; last_to = links[i].to; igraph_vector_push_back(&edges, last_from); igraph_vector_push_back(&edges, last_to); l++; VECTOR(*eids)[links[i].id] = l; } free(links); IGRAPH_FINALLY_CLEAN(1); igraph_destroy(graph); IGRAPH_CHECK(igraph_create(graph, &edges, igraph_vcount(graph), directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } typedef struct { long int community; igraph_real_t weight; } igraph_i_multilevel_community_link; int igraph_i_multilevel_community_link_cmp(const void *a, const void *b) { return (int) (((igraph_i_multilevel_community_link*)a)->community - ((igraph_i_multilevel_community_link*)b)->community); } /** * Given a graph, a community structure and a vertex ID, this method * calculates: * * - edges: the list of edge IDs that are incident on the vertex * - weight_all: the total weight of these edges * - weight_inside: the total weight of edges that stay within the same * community where the given vertex is right now, excluding loop edges * - weight_loop: the total weight of loop edges * - links_community and links_weight: together these two vectors list the * communities incident on this vertex and the total weight of edges * pointing to these communities */ int igraph_i_multilevel_community_links(const igraph_t *graph, const igraph_i_multilevel_community_list *communities, igraph_integer_t vertex, igraph_vector_t *edges, igraph_real_t *weight_all, igraph_real_t *weight_inside, igraph_real_t *weight_loop, igraph_vector_t *links_community, igraph_vector_t *links_weight) { long int i, n, last = -1, c = -1; igraph_real_t weight = 1; long int to, to_community; long int community = (long int) VECTOR(*(communities->membership))[(long int)vertex]; igraph_i_multilevel_community_link *links; *weight_all = *weight_inside = *weight_loop = 0; igraph_vector_clear(links_community); igraph_vector_clear(links_weight); /* Get the list of incident edges */ igraph_incident(graph, edges, vertex, IGRAPH_ALL); n = igraph_vector_size(edges); links = igraph_Calloc(n, igraph_i_multilevel_community_link); if (links == 0) { IGRAPH_ERROR("multi-level community structure detection failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, links); for (i = 0; i < n; i++) { long int eidx = (long int) VECTOR(*edges)[i]; weight = VECTOR(*communities->weights)[eidx]; to = IGRAPH_OTHER(graph, eidx, vertex); *weight_all += weight; if (to == vertex) { *weight_loop += weight; links[i].community = community; links[i].weight = 0; continue; } to_community = (long int)VECTOR(*(communities->membership))[to]; if (community == to_community) { *weight_inside += weight; } /* debug("Link %ld (C: %ld) <-> %ld (C: %ld)\n", vertex, community, to, to_community); */ links[i].community = to_community; links[i].weight = weight; } /* Sort links by community ID and merge the same */ qsort((void*)links, (size_t) n, sizeof(igraph_i_multilevel_community_link), igraph_i_multilevel_community_link_cmp); for (i = 0; i < n; i++) { to_community = links[i].community; if (to_community != last) { igraph_vector_push_back(links_community, to_community); igraph_vector_push_back(links_weight, links[i].weight); last = to_community; c++; } else { VECTOR(*links_weight)[c] += links[i].weight; } } igraph_free(links); IGRAPH_FINALLY_CLEAN(1); return 0; } igraph_real_t igraph_i_multilevel_community_modularity_gain( const igraph_i_multilevel_community_list *communities, igraph_integer_t community, igraph_integer_t vertex, igraph_real_t weight_all, igraph_real_t weight_inside) { IGRAPH_UNUSED(vertex); return weight_inside - communities->item[(long int)community].weight_all * weight_all / communities->weight_sum; } /* Shrinks communities into single vertices, keeping all the edges. * This method is internal because it destroys the graph in-place and * creates a new one -- this is fine for the multilevel community * detection where a copy of the original graph is used anyway. * The membership vector will also be rewritten by the underlying * igraph_membership_reindex call */ int igraph_i_multilevel_shrink(igraph_t *graph, igraph_vector_t *membership) { igraph_vector_t edges; long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_bool_t directed = igraph_is_directed(graph); long int i; igraph_eit_t eit; if (no_of_nodes == 0) { return 0; } if (igraph_vector_size(membership) < no_of_nodes) { IGRAPH_ERROR("cannot shrink graph, membership vector too short", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(&edges, no_of_edges * 2); IGRAPH_CHECK(igraph_reindex_membership(membership, 0, NULL)); /* Create the new edgelist */ igraph_eit_create(graph, igraph_ess_all(IGRAPH_EDGEORDER_ID), &eit); IGRAPH_FINALLY(igraph_eit_destroy, &eit); i = 0; while (!IGRAPH_EIT_END(eit)) { igraph_integer_t from, to; IGRAPH_CHECK(igraph_edge(graph, IGRAPH_EIT_GET(eit), &from, &to)); VECTOR(edges)[i++] = VECTOR(*membership)[(long int) from]; VECTOR(edges)[i++] = VECTOR(*membership)[(long int) to]; IGRAPH_EIT_NEXT(eit); } igraph_eit_destroy(&eit); IGRAPH_FINALLY_CLEAN(1); /* Create the new graph */ igraph_destroy(graph); no_of_nodes = (long int) igraph_vector_max(membership) + 1; IGRAPH_CHECK(igraph_create(graph, &edges, (igraph_integer_t) no_of_nodes, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \ingroup communities * \function igraph_i_community_multilevel_step * \brief Performs a single step of the multi-level modularity optimization method * * This function implements a single step of the multi-level modularity optimization * algorithm for finding community structure, see VD Blondel, J-L Guillaume, * R Lambiotte and E Lefebvre: Fast unfolding of community hierarchies in large * networks, http://arxiv.org/abs/0803.0476 for the details. * * This function was contributed by Tom Gregorovic. * * \param graph The input graph. It must be an undirected graph. * \param weights Numeric vector containing edge weights. If \c NULL, every edge * has equal weight. The weights are expected to be non-negative. * \param membership The membership vector, the result is returned here. * For each vertex it gives the ID of its community. * \param modularity The modularity of the partition is returned here. * \c NULL means that the modularity is not needed. * \return Error code. * * Time complexity: in average near linear on sparse graphs. */ int igraph_i_community_multilevel_step(igraph_t *graph, igraph_vector_t *weights, igraph_vector_t *membership, igraph_real_t *modularity) { long int i, j; long int vcount = igraph_vcount(graph); long int ecount = igraph_ecount(graph); igraph_integer_t ffrom, fto; igraph_real_t q, pass_q; int pass; igraph_bool_t changed = 0; igraph_vector_t links_community; igraph_vector_t links_weight; igraph_vector_t edges; igraph_vector_t temp_membership; igraph_i_multilevel_community_list communities; /* Initial sanity checks on the input parameters */ if (igraph_is_directed(graph)) { IGRAPH_ERROR("multi-level community detection works for undirected graphs only", IGRAPH_UNIMPLEMENTED); } if (igraph_vector_size(weights) < igraph_ecount(graph)) { IGRAPH_ERROR("multi-level community detection: weight vector too short", IGRAPH_EINVAL); } if (igraph_vector_any_smaller(weights, 0)) { IGRAPH_ERROR("weights must be positive", IGRAPH_EINVAL); } /* Initialize data structures */ IGRAPH_VECTOR_INIT_FINALLY(&links_community, 0); IGRAPH_VECTOR_INIT_FINALLY(&links_weight, 0); IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_VECTOR_INIT_FINALLY(&temp_membership, vcount); IGRAPH_CHECK(igraph_vector_resize(membership, vcount)); /* Initialize list of communities from graph vertices */ communities.vertices_no = vcount; communities.communities_no = vcount; communities.weights = weights; communities.weight_sum = 2 * igraph_vector_sum(weights); communities.membership = membership; communities.item = igraph_Calloc(vcount, igraph_i_multilevel_community); if (communities.item == 0) { IGRAPH_ERROR("multi-level community structure detection failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, communities.item); /* Still initializing the communities data structure */ for (i = 0; i < vcount; i++) { VECTOR(*communities.membership)[i] = i; communities.item[i].size = 1; communities.item[i].weight_inside = 0; communities.item[i].weight_all = 0; } /* Some more initialization :) */ for (i = 0; i < ecount; i++) { igraph_real_t weight = 1; igraph_edge(graph, (igraph_integer_t) i, &ffrom, &fto); weight = VECTOR(*weights)[i]; communities.item[(long int) ffrom].weight_all += weight; communities.item[(long int) fto].weight_all += weight; if (ffrom == fto) { communities.item[(long int) ffrom].weight_inside += 2 * weight; } } q = igraph_i_multilevel_community_modularity(&communities); pass = 1; do { /* Pass begin */ long int temp_communities_no = communities.communities_no; pass_q = q; changed = 0; /* Save the current membership, it will be restored in case of worse result */ IGRAPH_CHECK(igraph_vector_update(&temp_membership, communities.membership)); for (i = 0; i < vcount; i++) { /* Exclude vertex from its current community */ igraph_real_t weight_all = 0; igraph_real_t weight_inside = 0; igraph_real_t weight_loop = 0; igraph_real_t max_q_gain = 0; igraph_real_t max_weight; long int old_id, new_id, n; igraph_i_multilevel_community_links(graph, &communities, (igraph_integer_t) i, &edges, &weight_all, &weight_inside, &weight_loop, &links_community, &links_weight); old_id = (long int)VECTOR(*(communities.membership))[i]; new_id = old_id; /* Update old community */ igraph_vector_set(communities.membership, i, -1); communities.item[old_id].size--; if (communities.item[old_id].size == 0) { communities.communities_no--; } communities.item[old_id].weight_all -= weight_all; communities.item[old_id].weight_inside -= 2 * weight_inside + weight_loop; /* debug("Remove %ld all: %lf Inside: %lf\n", i, -weight_all, -2*weight_inside + weight_loop); */ /* Find new community to join with the best modification gain */ max_q_gain = 0; max_weight = weight_inside; n = igraph_vector_size(&links_community); for (j = 0; j < n; j++) { long int c = (long int) VECTOR(links_community)[j]; igraph_real_t w = VECTOR(links_weight)[j]; igraph_real_t q_gain = igraph_i_multilevel_community_modularity_gain(&communities, (igraph_integer_t) c, (igraph_integer_t) i, weight_all, w); /* debug("Link %ld -> %ld weight: %lf gain: %lf\n", i, c, (double) w, (double) q_gain); */ if (q_gain > max_q_gain) { new_id = c; max_q_gain = q_gain; max_weight = w; } } /* debug("Added vertex %ld to community %ld (gain %lf).\n", i, new_id, (double) max_q_gain); */ /* Add vertex to "new" community and update it */ igraph_vector_set(communities.membership, i, new_id); if (communities.item[new_id].size == 0) { communities.communities_no++; } communities.item[new_id].size++; communities.item[new_id].weight_all += weight_all; communities.item[new_id].weight_inside += 2 * max_weight + weight_loop; if (new_id != old_id) { changed++; } } q = igraph_i_multilevel_community_modularity(&communities); if (changed && (q > pass_q)) { /* debug("Pass %d (changed: %d) Communities: %ld Modularity from %lf to %lf\n", pass, changed, communities.communities_no, (double) pass_q, (double) q); */ pass++; } else { /* No changes or the modularity became worse, restore last membership */ IGRAPH_CHECK(igraph_vector_update(communities.membership, &temp_membership)); communities.communities_no = temp_communities_no; break; } IGRAPH_ALLOW_INTERRUPTION(); } while (changed && (q > pass_q)); /* Pass end */ if (modularity) { *modularity = q; } /* debug("Result Communities: %ld Modularity: %lf\n", communities.communities_no, (double) q); */ IGRAPH_CHECK(igraph_reindex_membership(membership, 0, NULL)); /* Shrink the nodes of the graph according to the present community structure * and simplify the resulting graph */ /* TODO: check if we really need to copy temp_membership */ IGRAPH_CHECK(igraph_vector_update(&temp_membership, membership)); IGRAPH_CHECK(igraph_i_multilevel_shrink(graph, &temp_membership)); igraph_vector_destroy(&temp_membership); IGRAPH_FINALLY_CLEAN(1); /* Update edge weights after shrinking and simplification */ /* Here we reuse the edges vector as we don't need the previous contents anymore */ /* TODO: can we use igraph_simplify here? */ IGRAPH_CHECK(igraph_i_multilevel_simplify_multiple(graph, &edges)); /* We reuse the links_weight vector to store the old edge weights */ IGRAPH_CHECK(igraph_vector_update(&links_weight, weights)); igraph_vector_fill(weights, 0); for (i = 0; i < ecount; i++) { VECTOR(*weights)[(long int)VECTOR(edges)[i]] += VECTOR(links_weight)[i]; } igraph_free(communities.item); igraph_vector_destroy(&links_community); igraph_vector_destroy(&links_weight); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(4); return 0; } /** * \ingroup communities * \function igraph_community_multilevel * \brief Finding community structure by multi-level optimization of modularity * * This function implements the multi-level modularity optimization * algorithm for finding community structure, see * VD Blondel, J-L Guillaume, R Lambiotte and E Lefebvre: Fast unfolding of * community hierarchies in large networks, J Stat Mech P10008 (2008) * for the details (preprint: http://arxiv.org/abs/arXiv:0803.0476). * * It is based on the modularity measure and a hierarchical approach. * Initially, each vertex is assigned to a community on its own. In every step, * vertices are re-assigned to communities in a local, greedy way: each vertex * is moved to the community with which it achieves the highest contribution to * modularity. When no vertices can be reassigned, each community is considered * a vertex on its own, and the process starts again with the merged communities. * The process stops when there is only a single vertex left or when the modularity * cannot be increased any more in a step. * * This function was contributed by Tom Gregorovic. * * \param graph The input graph. It must be an undirected graph. * \param weights Numeric vector containing edge weights. If \c NULL, every edge * has equal weight. The weights are expected to be non-negative. * \param membership The membership vector, the result is returned here. * For each vertex it gives the ID of its community. The vector * must be initialized and it will be resized accordingly. * \param memberships Numeric matrix that will contain the membership * vector after each level, if not \c NULL. It must be initialized and * it will be resized accordingly. * \param modularity Numeric vector that will contain the modularity score * after each level, if not \c NULL. It must be initialized and it * will be resized accordingly. * \return Error code. * * Time complexity: in average near linear on sparse graphs. * * \example examples/simple/igraph_community_multilevel.c */ int igraph_community_multilevel(const igraph_t *graph, const igraph_vector_t *weights, igraph_vector_t *membership, igraph_matrix_t *memberships, igraph_vector_t *modularity) { igraph_t g; igraph_vector_t w, m, level_membership; igraph_real_t prev_q = -1, q = -1; int i, level = 1; long int vcount = igraph_vcount(graph); /* Make a copy of the original graph, we will do the merges on the copy */ IGRAPH_CHECK(igraph_copy(&g, graph)); IGRAPH_FINALLY(igraph_destroy, &g); if (weights) { IGRAPH_CHECK(igraph_vector_copy(&w, weights)); IGRAPH_FINALLY(igraph_vector_destroy, &w); } else { IGRAPH_VECTOR_INIT_FINALLY(&w, igraph_ecount(&g)); igraph_vector_fill(&w, 1); } IGRAPH_VECTOR_INIT_FINALLY(&m, vcount); IGRAPH_VECTOR_INIT_FINALLY(&level_membership, vcount); if (memberships || membership) { /* Put each vertex in its own community */ for (i = 0; i < vcount; i++) { VECTOR(level_membership)[i] = i; } } if (memberships) { /* Resize the membership matrix to have vcount columns and no rows */ IGRAPH_CHECK(igraph_matrix_resize(memberships, 0, vcount)); } if (modularity) { /* Clear the modularity vector */ igraph_vector_clear(modularity); } while (1) { /* Remember the previous modularity and vertex count, do a single step */ igraph_integer_t step_vcount = igraph_vcount(&g); prev_q = q; IGRAPH_CHECK(igraph_i_community_multilevel_step(&g, &w, &m, &q)); /* Were there any merges? If not, we have to stop the process */ if (igraph_vcount(&g) == step_vcount || q < prev_q) { break; } if (memberships || membership) { for (i = 0; i < vcount; i++) { /* Readjust the membership vector */ VECTOR(level_membership)[i] = VECTOR(m)[(long int) VECTOR(level_membership)[i]]; } } if (modularity) { /* If we have to return the modularity scores, add it to the modularity vector */ IGRAPH_CHECK(igraph_vector_push_back(modularity, q)); } if (memberships) { /* If we have to return the membership vectors at each level, store the new * membership vector */ IGRAPH_CHECK(igraph_matrix_add_rows(memberships, 1)); IGRAPH_CHECK(igraph_matrix_set_row(memberships, &level_membership, level - 1)); } /* debug("Level: %d Communities: %ld Modularity: %f\n", level, (long int) igraph_vcount(&g), (double) q); */ /* Increase the level counter */ level++; } /* It might happen that there are no merges, so every vertex is in its own community. We still might want the modularity score for that. */ if (modularity && igraph_vector_size(modularity) == 0) { igraph_vector_t tmp; igraph_real_t mod; int i; IGRAPH_VECTOR_INIT_FINALLY(&tmp, vcount); for (i = 0; i < vcount; i++) { VECTOR(tmp)[i] = i; } IGRAPH_CHECK(igraph_modularity(graph, &tmp, &mod, weights)); igraph_vector_destroy(&tmp); IGRAPH_FINALLY_CLEAN(1); IGRAPH_CHECK(igraph_vector_resize(modularity, 1)); VECTOR(*modularity)[0] = mod; } /* If we need the final membership vector, copy it to the output */ if (membership) { IGRAPH_CHECK(igraph_vector_resize(membership, vcount)); for (i = 0; i < vcount; i++) { VECTOR(*membership)[i] = VECTOR(level_membership)[i]; } } /* Destroy the copy of the graph */ igraph_destroy(&g); /* Destroy the temporary vectors */ igraph_vector_destroy(&m); igraph_vector_destroy(&w); igraph_vector_destroy(&level_membership); IGRAPH_FINALLY_CLEAN(4); return 0; } int igraph_i_compare_communities_vi(const igraph_vector_t *v1, const igraph_vector_t *v2, igraph_real_t* result); int igraph_i_compare_communities_nmi(const igraph_vector_t *v1, const igraph_vector_t *v2, igraph_real_t* result); int igraph_i_compare_communities_rand(const igraph_vector_t *v1, const igraph_vector_t *v2, igraph_real_t* result, igraph_bool_t adjust); int igraph_i_split_join_distance(const igraph_vector_t *v1, const igraph_vector_t *v2, igraph_integer_t* distance12, igraph_integer_t* distance21); /** * \ingroup communities * \function igraph_compare_communities * \brief Compares community structures using various metrics * * This function assesses the distance between two community structures * using the variation of information (VI) metric of Meila (2003), the * normalized mutual information (NMI) of Danon et al (2005), the * split-join distance of van Dongen (2000), the Rand index of Rand (1971) * or the adjusted Rand index of Hubert and Arabie (1985). * * * References: * * * Meila M: Comparing clusterings by the variation of information. * In: Schölkopf B, Warmuth MK (eds.). Learning Theory and Kernel Machines: * 16th Annual Conference on Computational Learning Theory and 7th Kernel * Workshop, COLT/Kernel 2003, Washington, DC, USA. Lecture Notes in Computer * Science, vol. 2777, Springer, 2003. ISBN: 978-3-540-40720-1. * * * Danon L, Diaz-Guilera A, Duch J, Arenas A: Comparing community structure * identification. J Stat Mech P09008, 2005. * * * van Dongen S: Performance criteria for graph clustering and Markov cluster * experiments. Technical Report INS-R0012, National Research Institute for * Mathematics and Computer Science in the Netherlands, Amsterdam, May 2000. * * * Rand WM: Objective criteria for the evaluation of clustering methods. * J Am Stat Assoc 66(336):846-850, 1971. * * * Hubert L and Arabie P: Comparing partitions. Journal of Classification * 2:193-218, 1985. * * \param comm1 the membership vector of the first community structure * \param comm2 the membership vector of the second community structure * \param result the result is stored here. * \param method the comparison method to use. \c IGRAPH_COMMCMP_VI * selects the variation of information (VI) metric of * Meila (2003), \c IGRAPH_COMMCMP_NMI selects the * normalized mutual information measure proposed by * Danon et al (2005), \c IGRAPH_COMMCMP_SPLIT_JOIN * selects the split-join distance of van Dongen (2000), * \c IGRAPH_COMMCMP_RAND selects the unadjusted Rand * index (1971) and \c IGRAPH_COMMCMP_ADJUSTED_RAND * selects the adjusted Rand index. * * \return Error code. * * Time complexity: O(n log(n)). */ int igraph_compare_communities(const igraph_vector_t *comm1, const igraph_vector_t *comm2, igraph_real_t* result, igraph_community_comparison_t method) { igraph_vector_t c1, c2; if (igraph_vector_size(comm1) != igraph_vector_size(comm2)) { IGRAPH_ERROR("community membership vectors have different lengths", IGRAPH_EINVAL); } /* Copy and reindex membership vectors to make sure they are continuous */ IGRAPH_CHECK(igraph_vector_copy(&c1, comm1)); IGRAPH_FINALLY(igraph_vector_destroy, &c1); IGRAPH_CHECK(igraph_vector_copy(&c2, comm2)); IGRAPH_FINALLY(igraph_vector_destroy, &c2); IGRAPH_CHECK(igraph_reindex_membership(&c1, 0, NULL)); IGRAPH_CHECK(igraph_reindex_membership(&c2, 0, NULL)); switch (method) { case IGRAPH_COMMCMP_VI: IGRAPH_CHECK(igraph_i_compare_communities_vi(&c1, &c2, result)); break; case IGRAPH_COMMCMP_NMI: IGRAPH_CHECK(igraph_i_compare_communities_nmi(&c1, &c2, result)); break; case IGRAPH_COMMCMP_SPLIT_JOIN: { igraph_integer_t d12, d21; IGRAPH_CHECK(igraph_i_split_join_distance(&c1, &c2, &d12, &d21)); *result = d12 + d21; } break; case IGRAPH_COMMCMP_RAND: case IGRAPH_COMMCMP_ADJUSTED_RAND: IGRAPH_CHECK(igraph_i_compare_communities_rand(&c1, &c2, result, method == IGRAPH_COMMCMP_ADJUSTED_RAND)); break; default: IGRAPH_ERROR("unknown community comparison method", IGRAPH_EINVAL); } /* Clean up everything */ igraph_vector_destroy(&c1); igraph_vector_destroy(&c2); IGRAPH_FINALLY_CLEAN(2); return 0; } /** * \ingroup communities * \function igraph_split_join_distance * \brief Calculates the split-join distance of two community structures * * The split-join distance between partitions A and B is the sum of the * projection distance of A from B and the projection distance of B from * A. The projection distance is an asymmetric measure and it is defined * as follows: * * * First, each set in partition A is evaluated against all sets in partition * B. For each set in partition A, the best matching set in partition B is * found and the overlap size is calculated. (Matching is quantified by the * size of the overlap between the two sets). Then, the maximal overlap sizes * for each set in A are summed together and subtracted from the number of * elements in A. * * * The split-join distance will be returned in two arguments, \c distance12 * will contain the projection distance of the first partition from the * second, while \c distance21 will be the projection distance of the second * partition from the first. This makes it easier to detect whether a * partition is a subpartition of the other, since in this case, the * corresponding distance will be zero. * * * Reference: * * * van Dongen S: Performance criteria for graph clustering and Markov cluster * experiments. Technical Report INS-R0012, National Research Institute for * Mathematics and Computer Science in the Netherlands, Amsterdam, May 2000. * * \param comm1 the membership vector of the first community structure * \param comm2 the membership vector of the second community structure * \param distance12 pointer to an \c igraph_integer_t, the projection distance * of the first community structure from the second one will be * returned here. * \param distance21 pointer to an \c igraph_integer_t, the projection distance * of the second community structure from the first one will be * returned here. * \return Error code. * * \see \ref igraph_compare_communities() with the \c IGRAPH_COMMCMP_SPLIT_JOIN * method if you are not interested in the individual distances but only the sum * of them. * * Time complexity: O(n log(n)). */ int igraph_split_join_distance(const igraph_vector_t *comm1, const igraph_vector_t *comm2, igraph_integer_t *distance12, igraph_integer_t *distance21) { igraph_vector_t c1, c2; if (igraph_vector_size(comm1) != igraph_vector_size(comm2)) { IGRAPH_ERROR("community membership vectors have different lengths", IGRAPH_EINVAL); } /* Copy and reindex membership vectors to make sure they are continuous */ IGRAPH_CHECK(igraph_vector_copy(&c1, comm1)); IGRAPH_FINALLY(igraph_vector_destroy, &c1); IGRAPH_CHECK(igraph_vector_copy(&c2, comm2)); IGRAPH_FINALLY(igraph_vector_destroy, &c2); IGRAPH_CHECK(igraph_reindex_membership(&c1, 0, NULL)); IGRAPH_CHECK(igraph_reindex_membership(&c2, 0, NULL)); IGRAPH_CHECK(igraph_i_split_join_distance(&c1, &c2, distance12, distance21)); /* Clean up everything */ igraph_vector_destroy(&c1); igraph_vector_destroy(&c2); IGRAPH_FINALLY_CLEAN(2); return 0; } /** * Calculates the entropy and the mutual information for two reindexed community * membership vectors v1 and v2. This is needed by both Meila's and Danon's * community comparison measure. */ int igraph_i_entropy_and_mutual_information(const igraph_vector_t* v1, const igraph_vector_t* v2, double* h1, double* h2, double* mut_inf) { long int i, n = igraph_vector_size(v1); long int k1 = (long int)igraph_vector_max(v1) + 1; long int k2 = (long int)igraph_vector_max(v2) + 1; double *p1, *p2; igraph_spmatrix_t m; igraph_spmatrix_iter_t mit; p1 = igraph_Calloc(k1, double); if (p1 == 0) { IGRAPH_ERROR("igraph_i_entropy_and_mutual_information failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, p1); p2 = igraph_Calloc(k2, double); if (p2 == 0) { IGRAPH_ERROR("igraph_i_entropy_and_mutual_information failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, p2); /* Calculate the entropy of v1 */ *h1 = 0.0; for (i = 0; i < n; i++) { p1[(long int)VECTOR(*v1)[i]]++; } for (i = 0; i < k1; i++) { p1[i] /= n; *h1 -= p1[i] * log(p1[i]); } /* Calculate the entropy of v2 */ *h2 = 0.0; for (i = 0; i < n; i++) { p2[(long int)VECTOR(*v2)[i]]++; } for (i = 0; i < k2; i++) { p2[i] /= n; *h2 -= p2[i] * log(p2[i]); } /* We will only need the logs of p1 and p2 from now on */ for (i = 0; i < k1; i++) { p1[i] = log(p1[i]); } for (i = 0; i < k2; i++) { p2[i] = log(p2[i]); } /* Calculate the mutual information of v1 and v2 */ *mut_inf = 0.0; IGRAPH_CHECK(igraph_spmatrix_init(&m, k1, k2)); IGRAPH_FINALLY(igraph_spmatrix_destroy, &m); for (i = 0; i < n; i++) { IGRAPH_CHECK(igraph_spmatrix_add_e(&m, (int)VECTOR(*v1)[i], (int)VECTOR(*v2)[i], 1)); } IGRAPH_CHECK(igraph_spmatrix_iter_create(&mit, &m)); IGRAPH_FINALLY(igraph_spmatrix_iter_destroy, &mit); while (!igraph_spmatrix_iter_end(&mit)) { double p = mit.value / n; *mut_inf += p * (log(p) - p1[mit.ri] - p2[mit.ci]); igraph_spmatrix_iter_next(&mit); } igraph_spmatrix_iter_destroy(&mit); igraph_spmatrix_destroy(&m); free(p1); free(p2); IGRAPH_FINALLY_CLEAN(4); return 0; } /** * Implementation of the normalized mutual information (NMI) measure of * Danon et al. This function assumes that the community membership * vectors have already been normalized using igraph_reindex_communities(). * * * Reference: Danon L, Diaz-Guilera A, Duch J, Arenas A: Comparing community * structure identification. J Stat Mech P09008, 2005. * * * Time complexity: O(n log(n)) */ int igraph_i_compare_communities_nmi(const igraph_vector_t *v1, const igraph_vector_t *v2, igraph_real_t* result) { double h1, h2, mut_inf; IGRAPH_CHECK(igraph_i_entropy_and_mutual_information(v1, v2, &h1, &h2, &mut_inf)); if (h1 == 0 && h2 == 0) { *result = 1; } else { *result = 2 * mut_inf / (h1 + h2); } return IGRAPH_SUCCESS; } /** * Implementation of the variation of information metric (VI) of * Meila et al. This function assumes that the community membership * vectors have already been normalized using igraph_reindex_communities(). * * * Reference: Meila M: Comparing clusterings by the variation of information. * In: Schölkopf B, Warmuth MK (eds.). Learning Theory and Kernel Machines: * 16th Annual Conference on Computational Learning Theory and 7th Kernel * Workshop, COLT/Kernel 2003, Washington, DC, USA. Lecture Notes in Computer * Science, vol. 2777, Springer, 2003. ISBN: 978-3-540-40720-1. * * * Time complexity: O(n log(n)) */ int igraph_i_compare_communities_vi(const igraph_vector_t *v1, const igraph_vector_t *v2, igraph_real_t* result) { double h1, h2, mut_inf; IGRAPH_CHECK(igraph_i_entropy_and_mutual_information(v1, v2, &h1, &h2, &mut_inf)); *result = h1 + h2 - 2 * mut_inf; return IGRAPH_SUCCESS; } /** * \brief Calculates the confusion matrix for two clusterings. * * * This function assumes that the community membership vectors have already * been normalized using igraph_reindex_communities(). * * * Time complexity: O(n log(max(k1, k2))), where n is the number of vertices, k1 * and k2 are the number of clusters in each of the clusterings. */ int igraph_i_confusion_matrix(const igraph_vector_t *v1, const igraph_vector_t *v2, igraph_spmatrix_t *m) { long int k1 = (long int)igraph_vector_max(v1) + 1; long int k2 = (long int)igraph_vector_max(v2) + 1; long int i, n = igraph_vector_size(v1); IGRAPH_CHECK(igraph_spmatrix_resize(m, k1, k2)); for (i = 0; i < n; i++) { IGRAPH_CHECK(igraph_spmatrix_add_e(m, (int)VECTOR(*v1)[i], (int)VECTOR(*v2)[i], 1)); } return IGRAPH_SUCCESS; } /** * Implementation of the split-join distance of van Dongen. * * * This function assumes that the community membership vectors have already * been normalized using igraph_reindex_communities(). * * * Reference: van Dongen S: Performance criteria for graph clustering and Markov * cluster experiments. Technical Report INS-R0012, National Research Institute * for Mathematics and Computer Science in the Netherlands, Amsterdam, May 2000. * * * Time complexity: O(n log(max(k1, k2))), where n is the number of vertices, k1 * and k2 are the number of clusters in each of the clusterings. */ int igraph_i_split_join_distance(const igraph_vector_t *v1, const igraph_vector_t *v2, igraph_integer_t* distance12, igraph_integer_t* distance21) { long int n = igraph_vector_size(v1); igraph_vector_t rowmax, colmax; igraph_spmatrix_t m; igraph_spmatrix_iter_t mit; /* Calculate the confusion matrix */ IGRAPH_CHECK(igraph_spmatrix_init(&m, 1, 1)); IGRAPH_FINALLY(igraph_spmatrix_destroy, &m); IGRAPH_CHECK(igraph_i_confusion_matrix(v1, v2, &m)); /* Initialize vectors that will store the row/columnwise maxima */ IGRAPH_VECTOR_INIT_FINALLY(&rowmax, igraph_spmatrix_nrow(&m)); IGRAPH_VECTOR_INIT_FINALLY(&colmax, igraph_spmatrix_ncol(&m)); /* Find the row/columnwise maxima */ IGRAPH_CHECK(igraph_spmatrix_iter_create(&mit, &m)); IGRAPH_FINALLY(igraph_spmatrix_iter_destroy, &mit); while (!igraph_spmatrix_iter_end(&mit)) { if (mit.value > VECTOR(rowmax)[mit.ri]) { VECTOR(rowmax)[mit.ri] = mit.value; } if (mit.value > VECTOR(colmax)[mit.ci]) { VECTOR(colmax)[mit.ci] = mit.value; } igraph_spmatrix_iter_next(&mit); } igraph_spmatrix_iter_destroy(&mit); IGRAPH_FINALLY_CLEAN(1); /* Calculate the distances */ *distance12 = (igraph_integer_t) (n - igraph_vector_sum(&rowmax)); *distance21 = (igraph_integer_t) (n - igraph_vector_sum(&colmax)); igraph_vector_destroy(&rowmax); igraph_vector_destroy(&colmax); igraph_spmatrix_destroy(&m); IGRAPH_FINALLY_CLEAN(3); return IGRAPH_SUCCESS; } /** * Implementation of the adjusted and unadjusted Rand indices. * * * This function assumes that the community membership vectors have already * been normalized using igraph_reindex_communities(). * * * References: * * * Rand WM: Objective criteria for the evaluation of clustering methods. J Am * Stat Assoc 66(336):846-850, 1971. * * * Hubert L and Arabie P: Comparing partitions. Journal of Classification * 2:193-218, 1985. * * * Time complexity: O(n log(max(k1, k2))), where n is the number of vertices, k1 * and k2 are the number of clusters in each of the clusterings. */ int igraph_i_compare_communities_rand(const igraph_vector_t *v1, const igraph_vector_t *v2, igraph_real_t *result, igraph_bool_t adjust) { igraph_spmatrix_t m; igraph_spmatrix_iter_t mit; igraph_vector_t rowsums, colsums; long int i, nrow, ncol; double rand, n; double frac_pairs_in_1, frac_pairs_in_2; /* Calculate the confusion matrix */ IGRAPH_CHECK(igraph_spmatrix_init(&m, 1, 1)); IGRAPH_FINALLY(igraph_spmatrix_destroy, &m); IGRAPH_CHECK(igraph_i_confusion_matrix(v1, v2, &m)); /* The unadjusted Rand index is defined as (a+d) / (a+b+c+d), where: * * - a is the number of pairs in the same cluster both in v1 and v2. This * equals the sum of n(i,j) choose 2 for all i and j. * * - b is the number of pairs in the same cluster in v1 and in different * clusters in v2. This is sum n(i,*) choose 2 for all i minus a. * n(i,*) is the number of elements in cluster i in v1. * * - c is the number of pairs in the same cluster in v2 and in different * clusters in v1. This is sum n(*,j) choose 2 for all j minus a. * n(*,j) is the number of elements in cluster j in v2. * * - d is (n choose 2) - a - b - c. * * Therefore, a+d = (n choose 2) - b - c * = (n choose 2) - sum (n(i,*) choose 2) * - sum (n(*,j) choose 2) * + 2 * sum (n(i,j) choose 2). * * Since a+b+c+d = (n choose 2) and this goes in the denominator, we can * just as well start dividing each term in a+d by (n choose 2), which * yields: * * 1 - sum( n(i,*)/n * (n(i,*)-1)/(n-1) ) * - sum( n(*,i)/n * (n(*,i)-1)/(n-1) ) * + sum( n(i,j)/n * (n(i,j)-1)/(n-1) ) * 2 */ /* Calculate row and column sums */ nrow = igraph_spmatrix_nrow(&m); ncol = igraph_spmatrix_ncol(&m); n = igraph_vector_size(v1) + 0.0; IGRAPH_VECTOR_INIT_FINALLY(&rowsums, nrow); IGRAPH_VECTOR_INIT_FINALLY(&colsums, ncol); IGRAPH_CHECK(igraph_spmatrix_rowsums(&m, &rowsums)); IGRAPH_CHECK(igraph_spmatrix_colsums(&m, &colsums)); /* Start calculating the unadjusted Rand index */ rand = 0.0; IGRAPH_CHECK(igraph_spmatrix_iter_create(&mit, &m)); IGRAPH_FINALLY(igraph_spmatrix_iter_destroy, &mit); while (!igraph_spmatrix_iter_end(&mit)) { rand += (mit.value / n) * (mit.value - 1) / (n - 1); igraph_spmatrix_iter_next(&mit); } igraph_spmatrix_iter_destroy(&mit); IGRAPH_FINALLY_CLEAN(1); frac_pairs_in_1 = frac_pairs_in_2 = 0.0; for (i = 0; i < nrow; i++) { frac_pairs_in_1 += (VECTOR(rowsums)[i] / n) * (VECTOR(rowsums)[i] - 1) / (n - 1); } for (i = 0; i < ncol; i++) { frac_pairs_in_2 += (VECTOR(colsums)[i] / n) * (VECTOR(colsums)[i] - 1) / (n - 1); } rand = 1.0 + 2 * rand - frac_pairs_in_1 - frac_pairs_in_2; if (adjust) { double expected = frac_pairs_in_1 * frac_pairs_in_2 + (1 - frac_pairs_in_1) * (1 - frac_pairs_in_2); rand = (rand - expected) / (1 - expected); } igraph_vector_destroy(&rowsums); igraph_vector_destroy(&colsums); igraph_spmatrix_destroy(&m); IGRAPH_FINALLY_CLEAN(3); *result = rand; return IGRAPH_SUCCESS; } python-igraph-0.8.0/vendor/source/igraph/src/games.c0000644000076500000240000053177313614300625022656 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph R library. Copyright (C) 2003-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_interface.h" #include "igraph_games.h" #include "igraph_random.h" #include "igraph_memory.h" #include "igraph_interrupt_internal.h" #include "igraph_attributes.h" #include "igraph_constructors.h" #include "igraph_nongraph.h" #include "igraph_conversion.h" #include "igraph_psumtree.h" #include "igraph_dqueue.h" #include "igraph_adjlist.h" #include "igraph_iterators.h" #include "igraph_progress.h" #include "igraph_topology.h" #include "igraph_types_internal.h" #include "config.h" #include typedef struct { long int no; igraph_psumtree_t *sumtrees; } igraph_i_citing_cited_type_game_struct_t; void igraph_i_citing_cited_type_game_free ( igraph_i_citing_cited_type_game_struct_t *s); /** * \section about_games * * Games are randomized graph generators. Randomization means that * they generate a different graph every time you call them. */ int igraph_i_barabasi_game_bag(igraph_t *graph, igraph_integer_t n, igraph_integer_t m, const igraph_vector_t *outseq, igraph_bool_t outpref, igraph_bool_t directed, const igraph_t *start_from); int igraph_i_barabasi_game_psumtree_multiple(igraph_t *graph, igraph_integer_t n, igraph_real_t power, igraph_integer_t m, const igraph_vector_t *outseq, igraph_bool_t outpref, igraph_real_t A, igraph_bool_t directed, const igraph_t *start_from); int igraph_i_barabasi_game_psumtree(igraph_t *graph, igraph_integer_t n, igraph_real_t power, igraph_integer_t m, const igraph_vector_t *outseq, igraph_bool_t outpref, igraph_real_t A, igraph_bool_t directed, const igraph_t *start_from); int igraph_i_barabasi_game_bag(igraph_t *graph, igraph_integer_t n, igraph_integer_t m, const igraph_vector_t *outseq, igraph_bool_t outpref, igraph_bool_t directed, const igraph_t *start_from) { long int no_of_nodes = n; long int no_of_neighbors = m; long int *bag; long int bagp = 0; igraph_vector_t edges = IGRAPH_VECTOR_NULL; long int resp; long int i, j, k; long int bagsize, start_nodes, start_edges, new_edges, no_of_edges; if (!directed) { outpref = 1; } start_nodes = start_from ? igraph_vcount(start_from) : 1; start_edges = start_from ? igraph_ecount(start_from) : 0; if (outseq) { if (igraph_vector_size(outseq) > 1) { new_edges = (long int) (igraph_vector_sum(outseq) - VECTOR(*outseq)[0]); } else { new_edges = 0; } } else { new_edges = (no_of_nodes - start_nodes) * no_of_neighbors; } no_of_edges = start_edges + new_edges; resp = start_edges * 2; bagsize = no_of_nodes + no_of_edges + (outpref ? no_of_edges : 0); IGRAPH_VECTOR_INIT_FINALLY(&edges, no_of_edges * 2); bag = igraph_Calloc(bagsize, long int); if (bag == 0) { IGRAPH_ERROR("barabasi_game failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, bag); /* TODO: hack */ /* The first node(s) in the bag */ if (start_from) { igraph_vector_t deg; long int ii, jj, sn = igraph_vcount(start_from); igraph_neimode_t mm = outpref ? IGRAPH_ALL : IGRAPH_IN; IGRAPH_VECTOR_INIT_FINALLY(°, sn); IGRAPH_CHECK(igraph_degree(start_from, °, igraph_vss_all(), mm, IGRAPH_LOOPS)); for (ii = 0; ii < sn; ii++) { long int d = (long int) VECTOR(deg)[ii]; for (jj = 0; jj <= d; jj++) { bag[bagp++] = ii; } } igraph_vector_destroy(°); IGRAPH_FINALLY_CLEAN(1); } else { bag[bagp++] = 0; } /* Initialize the edges vector */ if (start_from) { IGRAPH_CHECK(igraph_get_edgelist(start_from, &edges, /* bycol= */ 0)); igraph_vector_resize(&edges, no_of_edges * 2); } RNG_BEGIN(); /* and the others */ for (i = (start_from ? start_nodes : 1), k = (start_from ? 0 : 1); i < no_of_nodes; i++, k++) { /* draw edges */ if (outseq) { no_of_neighbors = (long int) VECTOR(*outseq)[k]; } for (j = 0; j < no_of_neighbors; j++) { long int to = bag[RNG_INTEGER(0, bagp - 1)]; VECTOR(edges)[resp++] = i; VECTOR(edges)[resp++] = to; } /* update bag */ bag[bagp++] = i; for (j = 0; j < no_of_neighbors; j++) { bag[bagp++] = (long int) VECTOR(edges)[resp - 2 * j - 1]; if (outpref) { bag[bagp++] = i; } } } RNG_END(); igraph_Free(bag); IGRAPH_CHECK(igraph_create(graph, &edges, (igraph_integer_t) no_of_nodes, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(2); return 0; } int igraph_i_barabasi_game_psumtree_multiple(igraph_t *graph, igraph_integer_t n, igraph_real_t power, igraph_integer_t m, const igraph_vector_t *outseq, igraph_bool_t outpref, igraph_real_t A, igraph_bool_t directed, const igraph_t *start_from) { long int no_of_nodes = n; long int no_of_neighbors = m; igraph_vector_t edges; long int i, j, k; igraph_psumtree_t sumtree; long int edgeptr = 0; igraph_vector_t degree; long int start_nodes, start_edges, new_edges, no_of_edges; if (!directed) { outpref = 1; } start_nodes = start_from ? igraph_vcount(start_from) : 1; start_edges = start_from ? igraph_ecount(start_from) : 0; if (outseq) { if (igraph_vector_size(outseq) > 1) { new_edges = (long int) (igraph_vector_sum(outseq) - VECTOR(*outseq)[0]); } else { new_edges = 0; } } else { new_edges = (no_of_nodes - start_nodes) * no_of_neighbors; } no_of_edges = start_edges + new_edges; edgeptr = start_edges * 2; IGRAPH_VECTOR_INIT_FINALLY(&edges, no_of_edges * 2); IGRAPH_CHECK(igraph_psumtree_init(&sumtree, no_of_nodes)); IGRAPH_FINALLY(igraph_psumtree_destroy, &sumtree); IGRAPH_VECTOR_INIT_FINALLY(°ree, no_of_nodes); /* first node(s) */ if (start_from) { long int ii, sn = igraph_vcount(start_from); igraph_neimode_t mm = outpref ? IGRAPH_ALL : IGRAPH_IN; IGRAPH_CHECK(igraph_degree(start_from, °ree, igraph_vss_all(), mm, IGRAPH_LOOPS)); IGRAPH_CHECK(igraph_vector_resize(°ree, no_of_nodes)); for (ii = 0; ii < sn; ii++) { igraph_psumtree_update(&sumtree, ii, pow(VECTOR(degree)[ii], power) + A); } } else { igraph_psumtree_update(&sumtree, 0, A); } /* Initialize the edges vector */ if (start_from) { IGRAPH_CHECK(igraph_get_edgelist(start_from, &edges, /* bycol= */ 0)); igraph_vector_resize(&edges, no_of_edges * 2); } RNG_BEGIN(); /* and the rest */ for (i = (start_from ? start_nodes : 1), k = (start_from ? 0 : 1); i < no_of_nodes; i++, k++) { igraph_real_t sum = igraph_psumtree_sum(&sumtree); long int to; if (outseq) { no_of_neighbors = (long int) VECTOR(*outseq)[k]; } for (j = 0; j < no_of_neighbors; j++) { igraph_psumtree_search(&sumtree, &to, RNG_UNIF(0, sum)); VECTOR(degree)[to]++; VECTOR(edges)[edgeptr++] = i; VECTOR(edges)[edgeptr++] = to; } /* update probabilities */ for (j = 0; j < no_of_neighbors; j++) { long int nn = (long int) VECTOR(edges)[edgeptr - 2 * j - 1]; igraph_psumtree_update(&sumtree, nn, pow(VECTOR(degree)[nn], power) + A); } if (outpref) { VECTOR(degree)[i] += no_of_neighbors; igraph_psumtree_update(&sumtree, i, pow(VECTOR(degree)[i], power) + A); } else { igraph_psumtree_update(&sumtree, i, A); } } RNG_END(); igraph_psumtree_destroy(&sumtree); igraph_vector_destroy(°ree); IGRAPH_FINALLY_CLEAN(2); IGRAPH_CHECK(igraph_create(graph, &edges, n, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_i_barabasi_game_psumtree(igraph_t *graph, igraph_integer_t n, igraph_real_t power, igraph_integer_t m, const igraph_vector_t *outseq, igraph_bool_t outpref, igraph_real_t A, igraph_bool_t directed, const igraph_t *start_from) { long int no_of_nodes = n; long int no_of_neighbors = m; igraph_vector_t edges; long int i, j, k; igraph_psumtree_t sumtree; long int edgeptr = 0; igraph_vector_t degree; long int start_nodes, start_edges, new_edges, no_of_edges; if (!directed) { outpref = 1; } start_nodes = start_from ? igraph_vcount(start_from) : 1; start_edges = start_from ? igraph_ecount(start_from) : 0; if (outseq) { if (igraph_vector_size(outseq) > 1) { new_edges = (long int) (igraph_vector_sum(outseq) - VECTOR(*outseq)[0]); } else { new_edges = 0; } } else { new_edges = (no_of_nodes - start_nodes) * no_of_neighbors; } no_of_edges = start_edges + new_edges; edgeptr = start_edges * 2; IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_CHECK(igraph_vector_reserve(&edges, no_of_edges * 2)); IGRAPH_CHECK(igraph_psumtree_init(&sumtree, no_of_nodes)); IGRAPH_FINALLY(igraph_psumtree_destroy, &sumtree); IGRAPH_VECTOR_INIT_FINALLY(°ree, no_of_nodes); RNG_BEGIN(); /* first node(s) */ if (start_from) { long int ii, sn = igraph_vcount(start_from); igraph_neimode_t mm = outpref ? IGRAPH_ALL : IGRAPH_IN; IGRAPH_CHECK(igraph_degree(start_from, °ree, igraph_vss_all(), mm, IGRAPH_LOOPS)); IGRAPH_CHECK(igraph_vector_resize(°ree, no_of_nodes)); for (ii = 0; ii < sn; ii++) { igraph_psumtree_update(&sumtree, ii, pow(VECTOR(degree)[ii], power) + A); } } else { igraph_psumtree_update(&sumtree, 0, A); } /* Initialize the edges vector */ if (start_from) { IGRAPH_CHECK(igraph_get_edgelist(start_from, &edges, /* bycol= */ 0)); } /* and the rest */ for (i = (start_from ? start_nodes : 1), k = (start_from ? 0 : 1); i < no_of_nodes; i++, k++) { igraph_real_t sum; long int to; if (outseq) { no_of_neighbors = (long int) VECTOR(*outseq)[k]; } if (no_of_neighbors >= i) { /* All existing vertices are cited */ for (to = 0; to < i; to++) { VECTOR(degree)[to]++; igraph_vector_push_back(&edges, i); igraph_vector_push_back(&edges, to); edgeptr += 2; igraph_psumtree_update(&sumtree, to, pow(VECTOR(degree)[to], power) + A); } } else { for (j = 0; j < no_of_neighbors; j++) { sum = igraph_psumtree_sum(&sumtree); igraph_psumtree_search(&sumtree, &to, RNG_UNIF(0, sum)); VECTOR(degree)[to]++; igraph_vector_push_back(&edges, i); igraph_vector_push_back(&edges, to); edgeptr += 2; igraph_psumtree_update(&sumtree, to, 0.0); } /* update probabilities */ for (j = 0; j < no_of_neighbors; j++) { long int nn = (long int) VECTOR(edges)[edgeptr - 2 * j - 1]; igraph_psumtree_update(&sumtree, nn, pow(VECTOR(degree)[nn], power) + A); } } if (outpref) { VECTOR(degree)[i] += no_of_neighbors > i ? i : no_of_neighbors; igraph_psumtree_update(&sumtree, i, pow(VECTOR(degree)[i], power) + A); } else { igraph_psumtree_update(&sumtree, i, A); } } RNG_END(); igraph_psumtree_destroy(&sumtree); igraph_vector_destroy(°ree); IGRAPH_FINALLY_CLEAN(2); IGRAPH_CHECK(igraph_create(graph, &edges, n, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \ingroup generators * \function igraph_barabasi_game * \brief Generates a graph based on the Barabási-Albert model. * * \param graph An uninitialized graph object. * \param n The number of vertices in the graph. * \param power Power of the preferential attachment. The probability * that a vertex is cited is proportional to d^power+A, where * d is its degree (see also the \p outpref argument), power * and A are given by arguments. In the classic preferential * attachment model power=1. * \param m The number of outgoing edges generated for each * vertex. (Only if \p outseq is \c NULL.) * \param outseq Gives the (out-)degrees of the vertices. If this is * constant, this can be a NULL pointer or an empty (but * initialized!) vector, in this case \p m contains * the constant out-degree. The very first vertex has by definition * no outgoing edges, so the first number in this vector is * ignored. * \param outpref Boolean, if true not only the in- but also the out-degree * of a vertex increases its citation probability. Ie. the * citation probability is determined by the total degree of * the vertices. Ignored and assumed to be true if the graph * being generated is undirected. * \param A The probability that a vertex is cited is proportional to * d^power+A, where d is its degree (see also the \p outpref * argument), power and A are given by arguments. In the * previous versions of the function this parameter was * implicitly set to one. * \param directed Boolean, whether to generate a directed graph. * \param algo The algorithm to use to generate the network. Possible * values: * \clist * \cli IGRAPH_BARABASI_BAG * This is the algorithm that was previously (before version * 0.6) solely implemented in igraph. It works by putting the * ids of the vertices into a bag (multiset, really), exactly * as many times as their (in-)degree, plus once more. Then * the required number of cited vertices are drawn from the * bag, with replacement. This method might generate multiple * edges. It only works if power=1 and A=1. * \cli IGRAPH_BARABASI_PSUMTREE * This algorithm uses a partial prefix-sum tree to generate * the graph. It does not generate multiple edges and * works for any power and A values. * \cli IGRAPH_BARABASI_PSUMTREE_MULTIPLE * This algorithm also uses a partial prefix-sum tree to * generate the graph. The difference is, that now multiple * edges are allowed. This method was implemented under the * name \c igraph_nonlinear_barabasi_game before version 0.6. * \endclist * \param start_from Either a null pointer, or a graph. In the former * case, the starting configuration is a clique of size \p m. * In the latter case, the graph is a starting configuration. * The graph must be non-empty, i.e. it must have at least one * vertex. If a graph is supplied here and the \p outseq * argument is also given, then \p outseq should only contain * information on the vertices that are not in the \p * start_from graph. * \return Error code: * \c IGRAPH_EINVAL: invalid \p n, * \p m or \p outseq parameter. * * Time complexity: O(|V|+|E|), the * number of vertices plus the number of edges. * * \example examples/simple/igraph_barabasi_game.c * \example examples/simple/igraph_barabasi_game2.c */ int igraph_barabasi_game(igraph_t *graph, igraph_integer_t n, igraph_real_t power, igraph_integer_t m, const igraph_vector_t *outseq, igraph_bool_t outpref, igraph_real_t A, igraph_bool_t directed, igraph_barabasi_algorithm_t algo, const igraph_t *start_from) { long int start_nodes = start_from ? igraph_vcount(start_from) : 0; long int newn = start_from ? n - start_nodes : n; /* Fix obscure parameterizations */ if (outseq && igraph_vector_size(outseq) == 0) { outseq = 0; } if (!directed) { outpref = 1; } /* Check arguments */ if (algo != IGRAPH_BARABASI_BAG && algo != IGRAPH_BARABASI_PSUMTREE && algo != IGRAPH_BARABASI_PSUMTREE_MULTIPLE) { IGRAPH_ERROR("Invalid algorithm", IGRAPH_EINVAL); } if (n < 0) { IGRAPH_ERROR("Invalid number of vertices", IGRAPH_EINVAL); } else if (newn < 0) { IGRAPH_ERROR("Starting graph has too many vertices", IGRAPH_EINVAL); } if (start_from && start_nodes == 0) { IGRAPH_ERROR("Cannot start from an empty graph", IGRAPH_EINVAL); } if (outseq != 0 && igraph_vector_size(outseq) != 0 && igraph_vector_size(outseq) != newn) { IGRAPH_ERROR("Invalid out degree sequence length", IGRAPH_EINVAL); } if ( (outseq == 0 || igraph_vector_size(outseq) == 0) && m < 0) { IGRAPH_ERROR("Invalid out degree", IGRAPH_EINVAL); } if (outseq && igraph_vector_min(outseq) < 0) { IGRAPH_ERROR("Negative out degree in sequence", IGRAPH_EINVAL); } if (!outpref && A <= 0) { IGRAPH_ERROR("Constant attractiveness (A) must be positive", IGRAPH_EINVAL); } if (outpref && A < 0) { IGRAPH_ERROR("Constant attractiveness (A) must be non-negative", IGRAPH_EINVAL); } if (algo == IGRAPH_BARABASI_BAG) { if (power != 1) { IGRAPH_ERROR("Power must be one for 'bag' algorithm", IGRAPH_EINVAL); } if (A != 1) { IGRAPH_ERROR("Constant attractiveness (A) must be one for bag algorithm", IGRAPH_EINVAL); } } if (start_from && directed != igraph_is_directed(start_from)) { IGRAPH_WARNING("Directedness of the start graph and the output graph" " mismatch"); } if (start_from && !igraph_is_directed(start_from) && !outpref) { IGRAPH_ERROR("`outpref' must be true if starting from an undirected " "graph", IGRAPH_EINVAL); } if (n == 0) { return igraph_empty(graph, 0, directed); } if (algo == IGRAPH_BARABASI_BAG) { return igraph_i_barabasi_game_bag(graph, n, m, outseq, outpref, directed, start_from); } else if (algo == IGRAPH_BARABASI_PSUMTREE) { return igraph_i_barabasi_game_psumtree(graph, n, power, m, outseq, outpref, A, directed, start_from); } else if (algo == IGRAPH_BARABASI_PSUMTREE_MULTIPLE) { return igraph_i_barabasi_game_psumtree_multiple(graph, n, power, m, outseq, outpref, A, directed, start_from); } return 0; } /** * \ingroup internal */ int igraph_erdos_renyi_game_gnp(igraph_t *graph, igraph_integer_t n, igraph_real_t p, igraph_bool_t directed, igraph_bool_t loops) { long int no_of_nodes = n; igraph_vector_t edges = IGRAPH_VECTOR_NULL; igraph_vector_t s = IGRAPH_VECTOR_NULL; int retval = 0; if (n < 0) { IGRAPH_ERROR("Invalid number of vertices", IGRAPH_EINVAL); } if (p < 0.0 || p > 1.0) { IGRAPH_ERROR("Invalid probability given", IGRAPH_EINVAL); } if (p == 0.0 || no_of_nodes <= 1) { IGRAPH_CHECK(retval = igraph_empty(graph, n, directed)); } else if (p == 1.0) { IGRAPH_CHECK(retval = igraph_full(graph, n, directed, loops)); } else { long int i; double maxedges = n, last; if (directed && loops) { maxedges *= n; } else if (directed && !loops) { maxedges *= (n - 1); } else if (!directed && loops) { maxedges *= (n + 1) / 2.0; } else { maxedges *= (n - 1) / 2.0; } IGRAPH_VECTOR_INIT_FINALLY(&s, 0); IGRAPH_CHECK(igraph_vector_reserve(&s, (long int) (maxedges * p * 1.1))); RNG_BEGIN(); last = RNG_GEOM(p); while (last < maxedges) { IGRAPH_CHECK(igraph_vector_push_back(&s, last)); last += RNG_GEOM(p); last += 1; } RNG_END(); IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_CHECK(igraph_vector_reserve(&edges, igraph_vector_size(&s) * 2)); if (directed && loops) { for (i = 0; i < igraph_vector_size(&s); i++) { long int to = (long int) floor(VECTOR(s)[i] / no_of_nodes); long int from = (long int) (VECTOR(s)[i] - ((igraph_real_t)to) * no_of_nodes); igraph_vector_push_back(&edges, from); igraph_vector_push_back(&edges, to); } } else if (directed && !loops) { for (i = 0; i < igraph_vector_size(&s); i++) { long int to = (long int) floor(VECTOR(s)[i] / no_of_nodes); long int from = (long int) (VECTOR(s)[i] - ((igraph_real_t)to) * no_of_nodes); if (from == to) { to = no_of_nodes - 1; } igraph_vector_push_back(&edges, from); igraph_vector_push_back(&edges, to); } } else if (!directed && loops) { for (i = 0; i < igraph_vector_size(&s); i++) { long int to = (long int) floor((sqrt(8 * VECTOR(s)[i] + 1) - 1) / 2); long int from = (long int) (VECTOR(s)[i] - (((igraph_real_t)to) * (to + 1)) / 2); igraph_vector_push_back(&edges, from); igraph_vector_push_back(&edges, to); } } else { /* !directed && !loops */ for (i = 0; i < igraph_vector_size(&s); i++) { long int to = (long int) floor((sqrt(8 * VECTOR(s)[i] + 1) + 1) / 2); long int from = (long int) (VECTOR(s)[i] - (((igraph_real_t)to) * (to - 1)) / 2); igraph_vector_push_back(&edges, from); igraph_vector_push_back(&edges, to); } } igraph_vector_destroy(&s); IGRAPH_FINALLY_CLEAN(1); IGRAPH_CHECK(retval = igraph_create(graph, &edges, n, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); } return retval; } int igraph_erdos_renyi_game_gnm(igraph_t *graph, igraph_integer_t n, igraph_real_t m, igraph_bool_t directed, igraph_bool_t loops) { igraph_integer_t no_of_nodes = n; igraph_integer_t no_of_edges = (igraph_integer_t) m; igraph_vector_t edges = IGRAPH_VECTOR_NULL; igraph_vector_t s = IGRAPH_VECTOR_NULL; int retval = 0; if (n < 0) { IGRAPH_ERROR("Invalid number of vertices", IGRAPH_EINVAL); } if (m < 0) { IGRAPH_ERROR("Invalid number of edges", IGRAPH_EINVAL); } if (m == 0.0 || no_of_nodes <= 1) { IGRAPH_CHECK(retval = igraph_empty(graph, n, directed)); } else { long int i; double maxedges = n; if (directed && loops) { maxedges *= n; } else if (directed && !loops) { maxedges *= (n - 1); } else if (!directed && loops) { maxedges *= (n + 1) / 2.0; } else { maxedges *= (n - 1) / 2.0; } if (no_of_edges > maxedges) { IGRAPH_ERROR("Invalid number (too large) of edges", IGRAPH_EINVAL); } if (maxedges == no_of_edges) { retval = igraph_full(graph, n, directed, loops); } else { long int slen; IGRAPH_VECTOR_INIT_FINALLY(&s, 0); IGRAPH_CHECK(igraph_random_sample(&s, 0, maxedges - 1, (igraph_integer_t) no_of_edges)); IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_CHECK(igraph_vector_reserve(&edges, igraph_vector_size(&s) * 2)); slen = igraph_vector_size(&s); if (directed && loops) { for (i = 0; i < slen; i++) { long int to = (long int) floor(VECTOR(s)[i] / no_of_nodes); long int from = (long int) (VECTOR(s)[i] - ((igraph_real_t)to) * no_of_nodes); igraph_vector_push_back(&edges, from); igraph_vector_push_back(&edges, to); } } else if (directed && !loops) { for (i = 0; i < slen; i++) { long int from = (long int) floor(VECTOR(s)[i] / (no_of_nodes - 1)); long int to = (long int) (VECTOR(s)[i] - ((igraph_real_t)from) * (no_of_nodes - 1)); if (from == to) { to = no_of_nodes - 1; } igraph_vector_push_back(&edges, from); igraph_vector_push_back(&edges, to); } } else if (!directed && loops) { for (i = 0; i < slen; i++) { long int to = (long int) floor((sqrt(8 * VECTOR(s)[i] + 1) - 1) / 2); long int from = (long int) (VECTOR(s)[i] - (((igraph_real_t)to) * (to + 1)) / 2); igraph_vector_push_back(&edges, from); igraph_vector_push_back(&edges, to); } } else { /* !directed && !loops */ for (i = 0; i < slen; i++) { long int to = (long int) floor((sqrt(8 * VECTOR(s)[i] + 1) + 1) / 2); long int from = (long int) (VECTOR(s)[i] - (((igraph_real_t)to) * (to - 1)) / 2); igraph_vector_push_back(&edges, from); igraph_vector_push_back(&edges, to); } } igraph_vector_destroy(&s); IGRAPH_FINALLY_CLEAN(1); retval = igraph_create(graph, &edges, n, directed); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); } } return retval; } /** * \ingroup generators * \function igraph_erdos_renyi_game * \brief Generates a random (Erdos-Renyi) graph. * * \param graph Pointer to an uninitialized graph object. * \param type The type of the random graph, possible values: * \clist * \cli IGRAPH_ERDOS_RENYI_GNM * G(n,m) graph, * m edges are * selected uniformly randomly in a graph with * n vertices. * \cli IGRAPH_ERDOS_RENYI_GNP * G(n,p) graph, * every possible edge is included in the graph with * probability p. * \endclist * \param n The number of vertices in the graph. * \param p_or_m This is the p parameter for * G(n,p) graphs and the * m * parameter for G(n,m) graphs. * \param directed Logical, whether to generate a directed graph. * \param loops Logical, whether to generate loops (self) edges. * \return Error code: * \c IGRAPH_EINVAL: invalid * \p type, \p n, * \p p or \p m * parameter. * \c IGRAPH_ENOMEM: there is not enough * memory for the operation. * * Time complexity: O(|V|+|E|), the * number of vertices plus the number of edges in the graph. * * \sa \ref igraph_barabasi_game(), \ref igraph_growing_random_game() * * \example examples/simple/igraph_erdos_renyi_game.c */ int igraph_erdos_renyi_game(igraph_t *graph, igraph_erdos_renyi_t type, igraph_integer_t n, igraph_real_t p_or_m, igraph_bool_t directed, igraph_bool_t loops) { int retval = 0; if (type == IGRAPH_ERDOS_RENYI_GNP) { retval = igraph_erdos_renyi_game_gnp(graph, n, p_or_m, directed, loops); } else if (type == IGRAPH_ERDOS_RENYI_GNM) { retval = igraph_erdos_renyi_game_gnm(graph, n, p_or_m, directed, loops); } else { IGRAPH_ERROR("Invalid type", IGRAPH_EINVAL); } return retval; } int igraph_degree_sequence_game_simple(igraph_t *graph, const igraph_vector_t *out_seq, const igraph_vector_t *in_seq); int igraph_degree_sequence_game_simple(igraph_t *graph, const igraph_vector_t *out_seq, const igraph_vector_t *in_seq) { long int outsum = 0, insum = 0; igraph_bool_t directed = (in_seq != 0 && igraph_vector_size(in_seq) != 0); igraph_bool_t degseq_ok; long int no_of_nodes, no_of_edges; long int *bag1 = 0, *bag2 = 0; long int bagp1 = 0, bagp2 = 0; igraph_vector_t edges = IGRAPH_VECTOR_NULL; long int i, j; IGRAPH_CHECK(igraph_is_degree_sequence(out_seq, in_seq, °seq_ok)); if (!degseq_ok) { IGRAPH_ERROR(in_seq ? "No directed graph can realize the given degree sequences" : "No undirected graph can realize the given degree sequence", IGRAPH_EINVAL); } outsum = (long int) igraph_vector_sum(out_seq); if (directed) { insum = (long int) igraph_vector_sum(in_seq); } no_of_nodes = igraph_vector_size(out_seq); no_of_edges = directed ? outsum : outsum / 2; bag1 = igraph_Calloc(outsum, long int); if (bag1 == 0) { IGRAPH_ERROR("degree sequence game (simple)", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, bag1); /* TODO: hack */ for (i = 0; i < no_of_nodes; i++) { for (j = 0; j < VECTOR(*out_seq)[i]; j++) { bag1[bagp1++] = i; } } if (directed) { bag2 = igraph_Calloc(insum, long int); if (bag2 == 0) { IGRAPH_ERROR("degree sequence game (simple)", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, bag2); for (i = 0; i < no_of_nodes; i++) { for (j = 0; j < VECTOR(*in_seq)[i]; j++) { bag2[bagp2++] = i; } } } IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_CHECK(igraph_vector_reserve(&edges, no_of_edges * 2)); RNG_BEGIN(); if (directed) { for (i = 0; i < no_of_edges; i++) { long int from = RNG_INTEGER(0, bagp1 - 1); long int to = RNG_INTEGER(0, bagp2 - 1); igraph_vector_push_back(&edges, bag1[from]); /* safe, already reserved */ igraph_vector_push_back(&edges, bag2[to]); /* ditto */ bag1[from] = bag1[bagp1 - 1]; bag2[to] = bag2[bagp2 - 1]; bagp1--; bagp2--; } } else { for (i = 0; i < no_of_edges; i++) { long int from = RNG_INTEGER(0, bagp1 - 1); long int to; igraph_vector_push_back(&edges, bag1[from]); /* safe, already reserved */ bag1[from] = bag1[bagp1 - 1]; bagp1--; to = RNG_INTEGER(0, bagp1 - 1); igraph_vector_push_back(&edges, bag1[to]); /* ditto */ bag1[to] = bag1[bagp1 - 1]; bagp1--; } } RNG_END(); igraph_Free(bag1); IGRAPH_FINALLY_CLEAN(1); if (directed) { igraph_Free(bag2); IGRAPH_FINALLY_CLEAN(1); } IGRAPH_CHECK(igraph_create(graph, &edges, (igraph_integer_t) no_of_nodes, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_degree_sequence_game_no_multiple_undirected( igraph_t *graph, const igraph_vector_t *seq) { igraph_vector_t stubs = IGRAPH_VECTOR_NULL; igraph_vector_int_t *neis; igraph_vector_t residual_degrees = IGRAPH_VECTOR_NULL; igraph_set_t incomplete_vertices; igraph_adjlist_t al; igraph_bool_t finished, failed; igraph_integer_t from, to, dummy; long int i, j, k; long int no_of_nodes, outsum = 0; igraph_bool_t degseq_ok; IGRAPH_CHECK(igraph_is_graphical_degree_sequence(seq, 0, °seq_ok)); if (!degseq_ok) { IGRAPH_ERROR("No simple undirected graph can realize the given degree sequence", IGRAPH_EINVAL); } outsum = (long int) igraph_vector_sum(seq); no_of_nodes = igraph_vector_size(seq); /* Allocate required data structures */ IGRAPH_CHECK(igraph_adjlist_init_empty(&al, (igraph_integer_t) no_of_nodes)); IGRAPH_FINALLY(igraph_adjlist_destroy, &al); IGRAPH_VECTOR_INIT_FINALLY(&stubs, 0); IGRAPH_CHECK(igraph_vector_reserve(&stubs, outsum)); IGRAPH_VECTOR_INIT_FINALLY(&residual_degrees, no_of_nodes); IGRAPH_CHECK(igraph_set_init(&incomplete_vertices, 0)); IGRAPH_FINALLY(igraph_set_destroy, &incomplete_vertices); /* Start the RNG */ RNG_BEGIN(); /* Outer loop; this will try to construct a graph several times from scratch * until it finally succeeds. */ finished = 0; while (!finished) { /* Be optimistic :) */ failed = 0; /* Clear the adjacency list to get rid of the previous attempt (if any) */ igraph_adjlist_clear(&al); /* Initialize the residual degrees from the degree sequence */ IGRAPH_CHECK(igraph_vector_update(&residual_degrees, seq)); /* While there are some unconnected stubs left... */ while (!finished && !failed) { /* Construct the initial stub vector */ igraph_vector_clear(&stubs); for (i = 0; i < no_of_nodes; i++) { for (j = 0; j < VECTOR(residual_degrees)[i]; j++) { igraph_vector_push_back(&stubs, i); } } /* Clear the skipped stub counters and the set of incomplete vertices */ igraph_vector_null(&residual_degrees); igraph_set_clear(&incomplete_vertices); /* Shuffle the stubs in-place */ igraph_vector_shuffle(&stubs); /* Connect the stubs where possible */ k = igraph_vector_size(&stubs); for (i = 0; i < k; ) { from = (igraph_integer_t) VECTOR(stubs)[i++]; to = (igraph_integer_t) VECTOR(stubs)[i++]; if (from > to) { dummy = from; from = to; to = dummy; } neis = igraph_adjlist_get(&al, from); if (from == to || igraph_vector_int_binsearch(neis, to, &j)) { /* Edge exists already */ VECTOR(residual_degrees)[from]++; VECTOR(residual_degrees)[to]++; IGRAPH_CHECK(igraph_set_add(&incomplete_vertices, from)); IGRAPH_CHECK(igraph_set_add(&incomplete_vertices, to)); } else { /* Insert the edge */ IGRAPH_CHECK(igraph_vector_int_insert(neis, j, to)); } } finished = igraph_set_empty(&incomplete_vertices); if (!finished) { /* We are not done yet; check if the remaining stubs are feasible. This * is done by enumerating all possible pairs and checking whether at * least one feasible pair is found. */ i = 0; failed = 1; while (failed && igraph_set_iterate(&incomplete_vertices, &i, &from)) { j = 0; while (igraph_set_iterate(&incomplete_vertices, &j, &to)) { if (from == to) { /* This is used to ensure that each pair is checked once only */ break; } if (from > to) { dummy = from; from = to; to = dummy; } neis = igraph_adjlist_get(&al, from); if (!igraph_vector_int_binsearch(neis, to, 0)) { /* Found a suitable pair, so we can continue */ failed = 0; break; } } } } } } /* Finish the RNG */ RNG_END(); /* Clean up */ igraph_set_destroy(&incomplete_vertices); igraph_vector_destroy(&residual_degrees); igraph_vector_destroy(&stubs); IGRAPH_FINALLY_CLEAN(3); /* Create the graph. We cannot use IGRAPH_ALL here for undirected graphs * because we did not add edges in both directions in the adjacency list. * We will use igraph_to_undirected in an extra step. */ IGRAPH_CHECK(igraph_adjlist(graph, &al, IGRAPH_OUT, 1)); IGRAPH_CHECK(igraph_to_undirected(graph, IGRAPH_TO_UNDIRECTED_EACH, 0)); /* Clear the adjacency list */ igraph_adjlist_destroy(&al); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } int igraph_degree_sequence_game_no_multiple_directed(igraph_t *graph, const igraph_vector_t *out_seq, const igraph_vector_t *in_seq) { igraph_adjlist_t al; igraph_bool_t deg_seq_ok, failed, finished; igraph_vector_t in_stubs = IGRAPH_VECTOR_NULL; igraph_vector_t out_stubs = IGRAPH_VECTOR_NULL; igraph_vector_int_t *neis; igraph_vector_t residual_in_degrees = IGRAPH_VECTOR_NULL; igraph_vector_t residual_out_degrees = IGRAPH_VECTOR_NULL; igraph_set_t incomplete_in_vertices; igraph_set_t incomplete_out_vertices; igraph_integer_t from, to; long int i, j, k; long int no_of_nodes, outsum; IGRAPH_CHECK(igraph_is_graphical_degree_sequence(out_seq, in_seq, °_seq_ok)); if (!deg_seq_ok) { IGRAPH_ERROR("No simple directed graph can realize the given degree sequence", IGRAPH_EINVAL); } outsum = (long int) igraph_vector_sum(out_seq); no_of_nodes = igraph_vector_size(out_seq); /* Allocate required data structures */ IGRAPH_CHECK(igraph_adjlist_init_empty(&al, (igraph_integer_t) no_of_nodes)); IGRAPH_FINALLY(igraph_adjlist_destroy, &al); IGRAPH_VECTOR_INIT_FINALLY(&out_stubs, 0); IGRAPH_CHECK(igraph_vector_reserve(&out_stubs, outsum)); IGRAPH_VECTOR_INIT_FINALLY(&in_stubs, 0); IGRAPH_CHECK(igraph_vector_reserve(&in_stubs, outsum)); IGRAPH_VECTOR_INIT_FINALLY(&residual_out_degrees, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&residual_in_degrees, no_of_nodes); IGRAPH_CHECK(igraph_set_init(&incomplete_out_vertices, 0)); IGRAPH_FINALLY(igraph_set_destroy, &incomplete_out_vertices); IGRAPH_CHECK(igraph_set_init(&incomplete_in_vertices, 0)); IGRAPH_FINALLY(igraph_set_destroy, &incomplete_in_vertices); /* Start the RNG */ RNG_BEGIN(); /* Outer loop; this will try to construct a graph several times from scratch * until it finally succeeds. */ finished = 0; while (!finished) { /* Be optimistic :) */ failed = 0; /* Clear the adjacency list to get rid of the previous attempt (if any) */ igraph_adjlist_clear(&al); /* Initialize the residual degrees from the degree sequences */ IGRAPH_CHECK(igraph_vector_update(&residual_out_degrees, out_seq)); IGRAPH_CHECK(igraph_vector_update(&residual_in_degrees, in_seq)); /* While there are some unconnected stubs left... */ while (!finished && !failed) { /* Construct the initial stub vectors */ igraph_vector_clear(&out_stubs); igraph_vector_clear(&in_stubs); for (i = 0; i < no_of_nodes; i++) { for (j = 0; j < VECTOR(residual_out_degrees)[i]; j++) { igraph_vector_push_back(&out_stubs, i); } for (j = 0; j < VECTOR(residual_in_degrees)[i]; j++) { igraph_vector_push_back(&in_stubs, i); } } /* Clear the skipped stub counters and the set of incomplete vertices */ igraph_vector_null(&residual_out_degrees); igraph_vector_null(&residual_in_degrees); igraph_set_clear(&incomplete_out_vertices); igraph_set_clear(&incomplete_in_vertices); outsum = 0; /* Shuffle the out-stubs in-place */ igraph_vector_shuffle(&out_stubs); /* Connect the stubs where possible */ k = igraph_vector_size(&out_stubs); for (i = 0; i < k; i++) { from = (igraph_integer_t) VECTOR(out_stubs)[i]; to = (igraph_integer_t) VECTOR(in_stubs)[i]; neis = igraph_adjlist_get(&al, from); if (from == to || igraph_vector_int_binsearch(neis, to, &j)) { /* Edge exists already */ VECTOR(residual_out_degrees)[from]++; VECTOR(residual_in_degrees)[to]++; IGRAPH_CHECK(igraph_set_add(&incomplete_out_vertices, from)); IGRAPH_CHECK(igraph_set_add(&incomplete_in_vertices, to)); } else { /* Insert the edge */ IGRAPH_CHECK(igraph_vector_int_insert(neis, j, to)); } } /* Are we finished? */ finished = igraph_set_empty(&incomplete_out_vertices); if (!finished) { /* We are not done yet; check if the remaining stubs are feasible. This * is done by enumerating all possible pairs and checking whether at * least one feasible pair is found. */ i = 0; failed = 1; while (failed && igraph_set_iterate(&incomplete_out_vertices, &i, &from)) { j = 0; while (igraph_set_iterate(&incomplete_in_vertices, &j, &to)) { neis = igraph_adjlist_get(&al, from); if (from != to && !igraph_vector_int_binsearch(neis, to, 0)) { /* Found a suitable pair, so we can continue */ failed = 0; break; } } } } } } /* Finish the RNG */ RNG_END(); /* Clean up */ igraph_set_destroy(&incomplete_in_vertices); igraph_set_destroy(&incomplete_out_vertices); igraph_vector_destroy(&residual_in_degrees); igraph_vector_destroy(&residual_out_degrees); igraph_vector_destroy(&in_stubs); igraph_vector_destroy(&out_stubs); IGRAPH_FINALLY_CLEAN(6); /* Create the graph */ IGRAPH_CHECK(igraph_adjlist(graph, &al, IGRAPH_OUT, 1)); /* Clear the adjacency list */ igraph_adjlist_destroy(&al); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } int igraph_degree_sequence_game_no_multiple_undirected_uniform(igraph_t *graph, const igraph_vector_t *degseq) { igraph_vector_int_t stubs; igraph_vector_t edges; igraph_bool_t degseq_ok; igraph_vector_ptr_t adjlist; long i, j, k; long vcount, ecount, stub_count; IGRAPH_CHECK(igraph_is_graphical_degree_sequence(degseq, 0, °seq_ok)); if (!degseq_ok) { IGRAPH_ERROR("No simple undirected graph can realize the given degree sequence", IGRAPH_EINVAL); } stub_count = (long) igraph_vector_sum(degseq); ecount = stub_count / 2; vcount = igraph_vector_size(degseq); IGRAPH_VECTOR_INT_INIT_FINALLY(&stubs, stub_count); IGRAPH_VECTOR_INIT_FINALLY(&edges, stub_count); k = 0; for (i = 0; i < vcount; ++i) { long deg = (long) VECTOR(*degseq)[i]; for (j = 0; j < deg; ++j) { VECTOR(stubs)[k++] = i; } } IGRAPH_CHECK(igraph_vector_ptr_init(&adjlist, vcount)); IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(&adjlist, igraph_set_destroy); for (i = 0; i < vcount; ++i) { igraph_set_t *set = igraph_malloc(sizeof(igraph_set_t)); if (! set) { IGRAPH_ERROR("Out of memory", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_set_init(set, 0)); VECTOR(adjlist)[i] = set; IGRAPH_CHECK(igraph_set_reserve(set, (long) VECTOR(*degseq)[i])); } IGRAPH_FINALLY(igraph_vector_ptr_destroy_all, &adjlist); RNG_BEGIN(); for (;;) { igraph_bool_t success = 1; IGRAPH_CHECK(igraph_vector_int_shuffle(&stubs)); for (i = 0; i < ecount; ++i) { igraph_integer_t from = VECTOR(stubs)[2 * i]; igraph_integer_t to = VECTOR(stubs)[2 * i + 1]; /* loop edge, fail */ if (to == from) { success = 0; break; } /* multi-edge, fail */ if (igraph_set_contains((igraph_set_t *) VECTOR(adjlist)[to], from)) { success = 0; break; } /* sets are already reserved */ igraph_set_add((igraph_set_t *) VECTOR(adjlist)[to], from); igraph_set_add((igraph_set_t *) VECTOR(adjlist)[from], to); /* register edge */ VECTOR(edges)[2 * i] = from; VECTOR(edges)[2 * i + 1] = to; } if (success) { break; } IGRAPH_ALLOW_INTERRUPTION(); for (j = 0; j < vcount; ++j) { igraph_set_clear((igraph_set_t *) VECTOR(adjlist)[j]); } } RNG_END(); igraph_vector_ptr_destroy_all(&adjlist); igraph_vector_int_destroy(&stubs); IGRAPH_FINALLY_CLEAN(2); IGRAPH_CHECK(igraph_create(graph, &edges, vcount, /* directed = */ 0)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } int igraph_degree_sequence_game_no_multiple_directed_uniform( igraph_t *graph, const igraph_vector_t *out_deg, const igraph_vector_t *in_deg) { igraph_vector_int_t out_stubs, in_stubs; igraph_vector_t edges; igraph_bool_t degseq_ok; igraph_vector_ptr_t adjlist; long i, j, k, l; long vcount, ecount; IGRAPH_CHECK(igraph_is_graphical_degree_sequence(out_deg, in_deg, °seq_ok)); if (!degseq_ok) { IGRAPH_ERROR("No simple directed graph can realize the given degree sequence", IGRAPH_EINVAL); } ecount = (long) igraph_vector_sum(out_deg); vcount = igraph_vector_size(out_deg); IGRAPH_VECTOR_INT_INIT_FINALLY(&out_stubs, ecount); IGRAPH_VECTOR_INT_INIT_FINALLY(&in_stubs, ecount); IGRAPH_VECTOR_INIT_FINALLY(&edges, 2 * ecount); k = 0; l = 0; for (i = 0; i < vcount; ++i) { long dout, din; dout = (long) VECTOR(*out_deg)[i]; for (j = 0; j < dout; ++j) { VECTOR(out_stubs)[k++] = i; } din = (long) VECTOR(*in_deg)[i]; for (j = 0; j < din; ++j) { VECTOR(in_stubs)[l++] = i; } } IGRAPH_CHECK(igraph_vector_ptr_init(&adjlist, vcount)); IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(&adjlist, igraph_set_destroy); for (i = 0; i < vcount; ++i) { igraph_set_t *set = igraph_malloc(sizeof(igraph_set_t)); if (! set) { IGRAPH_ERROR("Out of memory", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_set_init(set, 0)); VECTOR(adjlist)[i] = set; IGRAPH_CHECK(igraph_set_reserve(set, (long) VECTOR(*out_deg)[i])); } IGRAPH_FINALLY(igraph_vector_ptr_destroy_all, &adjlist); RNG_BEGIN(); for (;;) { igraph_bool_t success = 1; IGRAPH_CHECK(igraph_vector_int_shuffle(&out_stubs)); for (i = 0; i < ecount; ++i) { igraph_integer_t from = VECTOR(out_stubs)[i]; igraph_integer_t to = VECTOR(in_stubs)[i]; igraph_set_t *set; /* loop edge, fail */ if (to == from) { success = 0; break; } /* multi-edge, fail */ set = (igraph_set_t *) VECTOR(adjlist)[from]; if (igraph_set_contains(set, to)) { success = 0; break; } /* sets are already reserved */ igraph_set_add(set, to); /* register edge */ VECTOR(edges)[2 * i] = from; VECTOR(edges)[2 * i + 1] = to; } if (success) { break; } IGRAPH_ALLOW_INTERRUPTION(); for (j = 0; j < vcount; ++j) { igraph_set_clear((igraph_set_t *) VECTOR(adjlist)[j]); } } RNG_END(); igraph_vector_ptr_destroy_all(&adjlist); igraph_vector_int_destroy(&out_stubs); igraph_vector_int_destroy(&in_stubs); IGRAPH_FINALLY_CLEAN(3); IGRAPH_CHECK(igraph_create(graph, &edges, vcount, /* directed = */ 1)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } /* This is in gengraph_mr-connected.cpp */ int igraph_degree_sequence_game_vl(igraph_t *graph, const igraph_vector_t *out_seq, const igraph_vector_t *in_seq); /** * \ingroup generators * \function igraph_degree_sequence_game * \brief Generates a random graph with a given degree sequence * * \param graph Pointer to an uninitialized graph object. * \param out_deg The degree sequence for an undirected graph (if * \p in_seq is of length zero), or the out-degree * sequence of a directed graph (if \p in_deq is not * of length zero. * \param in_deg It is either a zero-length vector or * \c NULL (if an undirected * graph is generated), or the in-degree sequence. * \param method The method to generate the graph. Possible values: * \clist * \cli IGRAPH_DEGSEQ_SIMPLE * This method implements the configuration model. * For undirected graphs, it puts all vertex IDs in a bag * such that the multiplicity of a vertex in the bag is the same as * its degree. Then it draws pairs from the bag until the bag becomes * empty. This method can generate both loop (self) edges and multiple * edges. For directed graphs, the algorithm is basically the same, * but two separate bags are used for the in- and out-degrees. * Undirected graphs are generated with probability proportional to * (\prod_{i<j} A_{ij} ! \prod_i A_{ii} !!)^{-1}, * where \c A denotes the adjacency matrix and !! denotes * the double factorial. * The corresponding expression for directed ones is * (\prod_{i,j} A_{ij}!)^{-1}. * Thus the probability of all simple graphs (which only have 0s and 1s * in the adjacency matrix) is the same, while that of * non-simple ones depends on their structure. * \cli IGRAPH_DEGSEQ_SIMPLE_NO_MULTIPLE * This method is similar to \c IGRAPH_DEGSEQ_SIMPLE * but tries to avoid multiple and loop edges and restarts the * generation from scratch if it gets stuck. It is not guaranteed * to sample uniformly from the space of all possible graphs with * the given sequence, but it is relatively fast and it will * eventually succeed if the provided degree sequence is graphical, * but there is no upper bound on the number of iterations. * \cli IGRAPH_DEGSEQ_SIMPLE_NO_MULTIPLE_UNIFORM * This method is identical to \c IGRAPH_DEGSEQ_SIMPLE, but if the * generated graph is not simple, it rejects it and re-starts the * generation. It samples all simple graphs with the same probability. * \cli IGRAPH_DEGSEQ_VL * This method is a much more sophisticated generator than the * previous ones. It can sample undirected, connected simple graphs * uniformly and uses Monte-Carlo methods to randomize the graphs. * This generator should be favoured if undirected and connected * graphs are to be generated and execution time is not a concern. * igraph uses the original implementation of Fabien Viger; for the algorithm, * see https://www-complexnetworks.lip6.fr/~latapy/FV/generation.html * and the paper https://arxiv.org/abs/cs/0502085 * \endclist * \return Error code: * \c IGRAPH_ENOMEM: there is not enough * memory to perform the operation. * \c IGRAPH_EINVAL: invalid method parameter, or * invalid in- and/or out-degree vectors. The degree vectors * should be non-negative, \p out_deg should sum * up to an even integer for undirected graphs; the length * and sum of \p out_deg and * \p in_deg * should match for directed graphs. * * Time complexity: O(|V|+|E|), the number of vertices plus the number of edges * for \c IGRAPH_DEGSEQ_SIMPLE. The time complexity of the * other modes is not known. * * \sa \ref igraph_barabasi_game(), \ref igraph_erdos_renyi_game(), * \ref igraph_is_degree_sequence(), * \ref igraph_is_graphical_degree_sequence() * * \example examples/simple/igraph_degree_sequence_game.c */ int igraph_degree_sequence_game(igraph_t *graph, const igraph_vector_t *out_deg, const igraph_vector_t *in_deg, igraph_degseq_t method) { if (in_deg && igraph_vector_empty(in_deg) && !igraph_vector_empty(out_deg)) { in_deg = 0; } switch (method) { case IGRAPH_DEGSEQ_SIMPLE: return igraph_degree_sequence_game_simple(graph, out_deg, in_deg); case IGRAPH_DEGSEQ_VL: return igraph_degree_sequence_game_vl(graph, out_deg, in_deg); case IGRAPH_DEGSEQ_SIMPLE_NO_MULTIPLE: if (in_deg == 0) { return igraph_degree_sequence_game_no_multiple_undirected(graph, out_deg); } else { return igraph_degree_sequence_game_no_multiple_directed(graph, out_deg, in_deg); } case IGRAPH_DEGSEQ_SIMPLE_NO_MULTIPLE_UNIFORM: if (in_deg == 0) { return igraph_degree_sequence_game_no_multiple_undirected_uniform(graph, out_deg); } else { return igraph_degree_sequence_game_no_multiple_directed_uniform(graph, out_deg, in_deg); } default: IGRAPH_ERROR("Invalid degree sequence game method", IGRAPH_EINVAL); } } /** * \ingroup generators * \function igraph_growing_random_game * \brief Generates a growing random graph. * * * This function simulates a growing random graph. In each discrete * time step a new vertex is added and a number of new edges are also * added. These graphs are known to be different from standard (not * growing) random graphs. * \param graph Uninitialized graph object. * \param n The number of vertices in the graph. * \param m The number of edges to add in a time step (ie. after * adding a vertex). * \param directed Boolean, whether to generate a directed graph. * \param citation Boolean, if \c TRUE, the edges always * originate from the most recently added vertex. * \return Error code: * \c IGRAPH_EINVAL: invalid * \p n or \p m * parameter. * * Time complexity: O(|V|+|E|), the * number of vertices plus the number of edges. * * \example examples/simple/igraph_growing_random_game.c */ int igraph_growing_random_game(igraph_t *graph, igraph_integer_t n, igraph_integer_t m, igraph_bool_t directed, igraph_bool_t citation) { long int no_of_nodes = n; long int no_of_neighbors = m; long int no_of_edges; igraph_vector_t edges = IGRAPH_VECTOR_NULL; long int resp = 0; long int i, j; if (n < 0) { IGRAPH_ERROR("Invalid number of vertices", IGRAPH_EINVAL); } if (m < 0) { IGRAPH_ERROR("Invalid number of edges per step (m)", IGRAPH_EINVAL); } no_of_edges = (no_of_nodes - 1) * no_of_neighbors; IGRAPH_VECTOR_INIT_FINALLY(&edges, no_of_edges * 2); RNG_BEGIN(); for (i = 1; i < no_of_nodes; i++) { for (j = 0; j < no_of_neighbors; j++) { if (citation) { long int to = RNG_INTEGER(0, i - 1); VECTOR(edges)[resp++] = i; VECTOR(edges)[resp++] = to; } else { long int from = RNG_INTEGER(0, i); long int to = RNG_INTEGER(1, i); VECTOR(edges)[resp++] = from; VECTOR(edges)[resp++] = to; } } } RNG_END(); IGRAPH_CHECK(igraph_create(graph, &edges, n, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_callaway_traits_game * \brief Simulate a growing network with vertex types. * * * The different types of vertices prefer to connect other types of * vertices with a given probability. * * * The simulation goes like this: in each discrete time step a new * vertex is added to the graph. The type of this vertex is generated * based on \p type_dist. Then two vertices are selected uniformly * randomly from the graph. The probability that they will be * connected depends on the types of these vertices and is taken from * \p pref_matrix. Then another two vertices are selected and this is * repeated \p edges_per_step times in each time step. * \param graph Pointer to an uninitialized graph. * \param nodes The number of nodes in the graph. * \param types Number of node types. * \param edges_per_step The number of edges to be add per time step. * \param type_dist Vector giving the distribution of the vertex * types. * \param pref_matrix Matrix giving the connection probabilities for * the vertex types. * \param directed Logical, whether to generate a directed graph. * \return Error code. * * Added in version 0.2. * * Time complexity: O(|V|e*log(|V|)), |V| is the number of vertices, e * is \p edges_per_step. */ int igraph_callaway_traits_game (igraph_t *graph, igraph_integer_t nodes, igraph_integer_t types, igraph_integer_t edges_per_step, igraph_vector_t *type_dist, igraph_matrix_t *pref_matrix, igraph_bool_t directed) { long int i, j; igraph_vector_t edges; igraph_vector_t cumdist; igraph_real_t maxcum; igraph_vector_t nodetypes; /* TODO: parameter checks */ IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_VECTOR_INIT_FINALLY(&cumdist, types + 1); IGRAPH_VECTOR_INIT_FINALLY(&nodetypes, nodes); VECTOR(cumdist)[0] = 0; for (i = 0; i < types; i++) { VECTOR(cumdist)[i + 1] = VECTOR(cumdist)[i] + VECTOR(*type_dist)[i]; } maxcum = igraph_vector_tail(&cumdist); RNG_BEGIN(); for (i = 0; i < nodes; i++) { igraph_real_t uni = RNG_UNIF(0, maxcum); long int type; igraph_vector_binsearch(&cumdist, uni, &type); VECTOR(nodetypes)[i] = type - 1; } for (i = 1; i < nodes; i++) { for (j = 0; j < edges_per_step; j++) { long int node1 = RNG_INTEGER(0, i); long int node2 = RNG_INTEGER(0, i); long int type1 = (long int) VECTOR(nodetypes)[node1]; long int type2 = (long int) VECTOR(nodetypes)[node2]; /* printf("unif: %f, %f, types: %li, %li\n", uni1, uni2, type1, type2); */ if (RNG_UNIF01() < MATRIX(*pref_matrix, type1, type2)) { IGRAPH_CHECK(igraph_vector_push_back(&edges, node1)); IGRAPH_CHECK(igraph_vector_push_back(&edges, node2)); } } } RNG_END(); igraph_vector_destroy(&nodetypes); igraph_vector_destroy(&cumdist); IGRAPH_FINALLY_CLEAN(2); IGRAPH_CHECK(igraph_create(graph, &edges, nodes, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_establishment_game * \brief Generates a graph with a simple growing model with vertex types. * * * The simulation goes like this: a single vertex is added at each * time step. This new vertex tries to connect to \p k vertices in the * graph. The probability that such a connection is realized depends * on the types of the vertices involved. * * \param graph Pointer to an uninitialized graph. * \param nodes The number of vertices in the graph. * \param types The number of vertex types. * \param k The number of connections tried in each time step. * \param type_dist Vector giving the distribution of vertex types. * \param pref_matrix Matrix giving the connection probabilities for * different vertex types. * \param directed Logical, whether to generate a directed graph. * \return Error code. * * Added in version 0.2. * * Time complexity: O(|V|*k*log(|V|)), |V| is the number of vertices * and k is the \p k parameter. */ int igraph_establishment_game(igraph_t *graph, igraph_integer_t nodes, igraph_integer_t types, igraph_integer_t k, igraph_vector_t *type_dist, igraph_matrix_t *pref_matrix, igraph_bool_t directed) { long int i, j; igraph_vector_t edges; igraph_vector_t cumdist; igraph_vector_t potneis; igraph_real_t maxcum; igraph_vector_t nodetypes; IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_VECTOR_INIT_FINALLY(&cumdist, types + 1); IGRAPH_VECTOR_INIT_FINALLY(&potneis, k); IGRAPH_VECTOR_INIT_FINALLY(&nodetypes, nodes); VECTOR(cumdist)[0] = 0; for (i = 0; i < types; i++) { VECTOR(cumdist)[i + 1] = VECTOR(cumdist)[i] + VECTOR(*type_dist)[i]; } maxcum = igraph_vector_tail(&cumdist); RNG_BEGIN(); for (i = 0; i < nodes; i++) { igraph_real_t uni = RNG_UNIF(0, maxcum); long int type; igraph_vector_binsearch(&cumdist, uni, &type); VECTOR(nodetypes)[i] = type - 1; } for (i = k; i < nodes; i++) { long int type1 = (long int) VECTOR(nodetypes)[i]; igraph_random_sample(&potneis, 0, i - 1, k); for (j = 0; j < k; j++) { long int type2 = (long int) VECTOR(nodetypes)[(long int)VECTOR(potneis)[j]]; if (RNG_UNIF01() < MATRIX(*pref_matrix, type1, type2)) { IGRAPH_CHECK(igraph_vector_push_back(&edges, i)); IGRAPH_CHECK(igraph_vector_push_back(&edges, VECTOR(potneis)[j])); } } } RNG_END(); igraph_vector_destroy(&nodetypes); igraph_vector_destroy(&potneis); igraph_vector_destroy(&cumdist); IGRAPH_FINALLY_CLEAN(3); IGRAPH_CHECK(igraph_create(graph, &edges, nodes, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_recent_degree_game * \brief Stochastic graph generator based on the number of incident edges a node has gained recently * * \param graph Pointer to an uninitialized graph object. * \param n The number of vertices in the graph, this is the same as * the number of time steps. * \param power The exponent, the probability that a node gains a * new edge is proportional to the number of edges it has * gained recently (in the last \p window time steps) to \p * power. * \param window Integer constant, the size of the time window to use * to count the number of recent edges. * \param m Integer constant, the number of edges to add per time * step if the \p outseq parameter is a null pointer or a * zero-length vector. * \param outseq The number of edges to add in each time step. This * argument is ignored if it is a null pointer or a zero length * vector, is this case the constant \p m parameter is used. * \param outpref Logical constant, if true the edges originated by a * vertex also count as recent incident edges. It is false in * most cases. * \param zero_appeal Constant giving the attractiveness of the * vertices which haven't gained any edge recently. * \param directed Logical constant, whether to generate a directed * graph. * \return Error code. * * Time complexity: O(|V|*log(|V|)+|E|), |V| is the number of * vertices, |E| is the number of edges in the graph. * */ int igraph_recent_degree_game(igraph_t *graph, igraph_integer_t n, igraph_real_t power, igraph_integer_t window, igraph_integer_t m, const igraph_vector_t *outseq, igraph_bool_t outpref, igraph_real_t zero_appeal, igraph_bool_t directed) { long int no_of_nodes = n; long int no_of_neighbors = m; long int no_of_edges; igraph_vector_t edges; long int i, j; igraph_psumtree_t sumtree; long int edgeptr = 0; igraph_vector_t degree; long int time_window = window; igraph_dqueue_t history; if (n < 0) { IGRAPH_ERROR("Invalid number of vertices", IGRAPH_EINVAL); } if (outseq != 0 && igraph_vector_size(outseq) != 0 && igraph_vector_size(outseq) != n) { IGRAPH_ERROR("Invalid out degree sequence length", IGRAPH_EINVAL); } if ( (outseq == 0 || igraph_vector_size(outseq) == 0) && m < 0) { IGRAPH_ERROR("Invalid out degree", IGRAPH_EINVAL); } if (outseq == 0 || igraph_vector_size(outseq) == 0) { no_of_neighbors = m; no_of_edges = (no_of_nodes - 1) * no_of_neighbors; } else { no_of_edges = 0; for (i = 1; i < igraph_vector_size(outseq); i++) { no_of_edges += VECTOR(*outseq)[i]; } } IGRAPH_VECTOR_INIT_FINALLY(&edges, no_of_edges * 2); IGRAPH_CHECK(igraph_psumtree_init(&sumtree, no_of_nodes)); IGRAPH_FINALLY(igraph_psumtree_destroy, &sumtree); IGRAPH_VECTOR_INIT_FINALLY(°ree, no_of_nodes); IGRAPH_CHECK(igraph_dqueue_init(&history, time_window * (no_of_neighbors + 1) + 10)); IGRAPH_FINALLY(igraph_dqueue_destroy, &history); RNG_BEGIN(); /* first node */ igraph_psumtree_update(&sumtree, 0, zero_appeal); igraph_dqueue_push(&history, -1); /* and the rest */ for (i = 1; i < no_of_nodes; i++) { igraph_real_t sum; long int to; if (outseq != 0 && igraph_vector_size(outseq) != 0) { no_of_neighbors = (long int) VECTOR(*outseq)[i]; } if (i >= time_window) { while ((j = (long int) igraph_dqueue_pop(&history)) != -1) { VECTOR(degree)[j] -= 1; igraph_psumtree_update(&sumtree, j, pow(VECTOR(degree)[j], power) + zero_appeal); } } sum = igraph_psumtree_sum(&sumtree); for (j = 0; j < no_of_neighbors; j++) { igraph_psumtree_search(&sumtree, &to, RNG_UNIF(0, sum)); VECTOR(degree)[to]++; VECTOR(edges)[edgeptr++] = i; VECTOR(edges)[edgeptr++] = to; igraph_dqueue_push(&history, to); } igraph_dqueue_push(&history, -1); /* update probabilities */ for (j = 0; j < no_of_neighbors; j++) { long int nn = (long int) VECTOR(edges)[edgeptr - 2 * j - 1]; igraph_psumtree_update(&sumtree, nn, pow(VECTOR(degree)[nn], power) + zero_appeal); } if (outpref) { VECTOR(degree)[i] += no_of_neighbors; igraph_psumtree_update(&sumtree, i, pow(VECTOR(degree)[i], power) + zero_appeal); } else { igraph_psumtree_update(&sumtree, i, zero_appeal); } } RNG_END(); igraph_dqueue_destroy(&history); igraph_psumtree_destroy(&sumtree); igraph_vector_destroy(°ree); IGRAPH_FINALLY_CLEAN(3); IGRAPH_CHECK(igraph_create(graph, &edges, n, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_barabasi_aging_game * \brief Preferential attachment with aging of vertices * * * In this game, the probability that a node gains a new edge is * given by its (in-)degree (k) and age (l). This probability has a * degree dependent component multiplied by an age dependent * component. The degree dependent part is: \p deg_coef times k to the * power of \p pa_exp plus \p zero_deg_appeal; and the age dependent * part is \p age_coef times l to the power of \p aging_exp plus \p * zero_age_appeal. * * * The age is based on the number of vertices in the * network and the \p aging_bin argument: vertices grew one unit older * after each \p aging_bin vertices added to the network. * \param graph Pointer to an uninitialized graph object. * \param nodes The number of vertices in the graph. * \param m The number of edges to add in each time step. If the \p * outseq argument is not a null vector and not a zero-length * vector. * \param outseq The number of edges to add in each time step. If it * is a null pointer or a zero-length vector then it is ignored * and the \p m argument is used instead. * \param outpref Logical constant, whether the edges * initiated by a vertex contribute to the probability to gain * a new edge. * \param pa_exp The exponent of the preferential attachment, a small * positive number usually, the value 1 yields the classic * linear preferential attachment. * \param aging_exp The exponent of the aging, this is a negative * number usually. * \param aging_bin Integer constant, the number of vertices to add * before vertices in the network grew one unit older. * \param zero_deg_appeal The degree dependent part of the * attractiveness of the zero degree vertices. * \param zero_age_appeal The age dependent part of the attractiveness * of the vertices of age zero. This parameter is usually zero. * \param deg_coef The coefficient for the degree. * \param age_coef The coefficient for the age. * \param directed Logical constant, whether to generate a directed * graph. * \return Error code. * * Time complexity: O((|V|+|V|/aging_bin)*log(|V|)+|E|). |V| is the number * of vertices, |E| the number of edges. */ int igraph_barabasi_aging_game(igraph_t *graph, igraph_integer_t nodes, igraph_integer_t m, const igraph_vector_t *outseq, igraph_bool_t outpref, igraph_real_t pa_exp, igraph_real_t aging_exp, igraph_integer_t aging_bin, igraph_real_t zero_deg_appeal, igraph_real_t zero_age_appeal, igraph_real_t deg_coef, igraph_real_t age_coef, igraph_bool_t directed) { long int no_of_nodes = nodes; long int no_of_neighbors = m; long int binwidth = nodes / aging_bin + 1; long int no_of_edges; igraph_vector_t edges; long int i, j, k; igraph_psumtree_t sumtree; long int edgeptr = 0; igraph_vector_t degree; if (no_of_nodes < 0) { IGRAPH_ERROR("Invalid number of vertices", IGRAPH_EINVAL); } if (outseq != 0 && igraph_vector_size(outseq) != 0 && igraph_vector_size(outseq) != no_of_nodes) { IGRAPH_ERROR("Invalid out degree sequence length", IGRAPH_EINVAL); } if ( (outseq == 0 || igraph_vector_size(outseq) == 0) && m < 0) { IGRAPH_ERROR("Invalid out degree", IGRAPH_EINVAL); } if (aging_bin <= 0) { IGRAPH_ERROR("Invalid aging bin", IGRAPH_EINVAL); } if (outseq == 0 || igraph_vector_size(outseq) == 0) { no_of_neighbors = m; no_of_edges = (no_of_nodes - 1) * no_of_neighbors; } else { no_of_edges = 0; for (i = 1; i < igraph_vector_size(outseq); i++) { no_of_edges += VECTOR(*outseq)[i]; } } IGRAPH_VECTOR_INIT_FINALLY(&edges, no_of_edges * 2); IGRAPH_CHECK(igraph_psumtree_init(&sumtree, no_of_nodes)); IGRAPH_FINALLY(igraph_psumtree_destroy, &sumtree); IGRAPH_VECTOR_INIT_FINALLY(°ree, no_of_nodes); RNG_BEGIN(); /* first node */ igraph_psumtree_update(&sumtree, 0, zero_deg_appeal * (1 + zero_age_appeal)); /* and the rest */ for (i = 1; i < no_of_nodes; i++) { igraph_real_t sum; long int to; if (outseq != 0 && igraph_vector_size(outseq) != 0) { no_of_neighbors = (long int) VECTOR(*outseq)[i]; } sum = igraph_psumtree_sum(&sumtree); for (j = 0; j < no_of_neighbors; j++) { igraph_psumtree_search(&sumtree, &to, RNG_UNIF(0, sum)); VECTOR(degree)[to]++; VECTOR(edges)[edgeptr++] = i; VECTOR(edges)[edgeptr++] = to; } /* update probabilities */ for (j = 0; j < no_of_neighbors; j++) { long int n = (long int) VECTOR(edges)[edgeptr - 2 * j - 1]; long int age = (i - n) / binwidth; igraph_psumtree_update(&sumtree, n, (deg_coef * pow(VECTOR(degree)[n], pa_exp) + zero_deg_appeal)* (age_coef * pow(age + 1, aging_exp) + zero_age_appeal)); } if (outpref) { VECTOR(degree)[i] += no_of_neighbors; igraph_psumtree_update(&sumtree, i, (zero_age_appeal + 1)* (deg_coef * pow(VECTOR(degree)[i], pa_exp) + zero_deg_appeal)); } else { igraph_psumtree_update(&sumtree, i, (1 + zero_age_appeal)*zero_deg_appeal); } /* aging */ for (k = 1; i - binwidth * k + 1 >= 1; k++) { long int shnode = i - binwidth * k; long int deg = (long int) VECTOR(degree)[shnode]; long int age = (i - shnode) / binwidth; /* igraph_real_t old=igraph_psumtree_get(&sumtree, shnode); */ igraph_psumtree_update(&sumtree, shnode, (deg_coef * pow(deg, pa_exp) + zero_deg_appeal) * (age_coef * pow(age + 2, aging_exp) + zero_age_appeal)); } } RNG_END(); igraph_vector_destroy(°ree); igraph_psumtree_destroy(&sumtree); IGRAPH_FINALLY_CLEAN(2); IGRAPH_CHECK(igraph_create(graph, &edges, nodes, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_recent_degree_aging_game * \brief Preferential attachment based on the number of edges gained recently, with aging of vertices * * * This game is very similar to \ref igraph_barabasi_aging_game(), * except that instead of the total number of incident edges the * number of edges gained in the last \p time_window time steps are * counted. * * The degree dependent part of the attractiveness is * given by k to the power of \p pa_exp plus \p zero_appeal; the age * dependent part is l to the power to \p aging_exp. * k is the number of edges gained in the last \p time_window time * steps, l is the age of the vertex. * \param graph Pointer to an uninitialized graph object. * \param nodes The number of vertices in the graph. * \param m The number of edges to add in each time step. If the \p * outseq argument is not a null vector or a zero-length vector * then it is ignored. * \param outseq Vector giving the number of edges to add in each time * step. If it is a null pointer or a zero-length vector then * it is ignored and the \p m argument is used. * \param outpref Logical constant, if true the edges initiated by a * vertex are also counted. Normally it is false. * \param pa_exp The exponent for the preferential attachment. * \param aging_exp The exponent for the aging, normally it is * negative: old vertices gain edges with less probability. * \param aging_bin Integer constant, gives the scale of the aging. * The age of the vertices is incremented by one after every \p * aging_bin vertex added. * \param time_window The time window to use to count the number of * incident edges for the vertices. * \param zero_appeal The degree dependent part of the attractiveness * for zero degree vertices. * \param directed Logical constant, whether to create a directed * graph. * \return Error code. * * Time complexity: O((|V|+|V|/aging_bin)*log(|V|)+|E|). |V| is the number * of vertices, |E| the number of edges. */ int igraph_recent_degree_aging_game(igraph_t *graph, igraph_integer_t nodes, igraph_integer_t m, const igraph_vector_t *outseq, igraph_bool_t outpref, igraph_real_t pa_exp, igraph_real_t aging_exp, igraph_integer_t aging_bin, igraph_integer_t time_window, igraph_real_t zero_appeal, igraph_bool_t directed) { long int no_of_nodes = nodes; long int no_of_neighbors = m; long int binwidth = nodes / aging_bin + 1; long int no_of_edges; igraph_vector_t edges; long int i, j, k; igraph_psumtree_t sumtree; long int edgeptr = 0; igraph_vector_t degree; igraph_dqueue_t history; if (no_of_nodes < 0) { IGRAPH_ERROR("Invalid number of vertices", IGRAPH_EINVAL); } if (outseq != 0 && igraph_vector_size(outseq) != 0 && igraph_vector_size(outseq) != no_of_nodes) { IGRAPH_ERROR("Invalid out degree sequence length", IGRAPH_EINVAL); } if ( (outseq == 0 || igraph_vector_size(outseq) == 0) && m < 0) { IGRAPH_ERROR("Invalid out degree", IGRAPH_EINVAL); } if (aging_bin <= 0) { IGRAPH_ERROR("Invalid aging bin", IGRAPH_EINVAL); } if (outseq == 0 || igraph_vector_size(outseq) == 0) { no_of_neighbors = m; no_of_edges = (no_of_nodes - 1) * no_of_neighbors; } else { no_of_edges = 0; for (i = 1; i < igraph_vector_size(outseq); i++) { no_of_edges += VECTOR(*outseq)[i]; } } IGRAPH_VECTOR_INIT_FINALLY(&edges, no_of_edges * 2); IGRAPH_CHECK(igraph_psumtree_init(&sumtree, no_of_nodes)); IGRAPH_FINALLY(igraph_psumtree_destroy, &sumtree); IGRAPH_VECTOR_INIT_FINALLY(°ree, no_of_nodes); IGRAPH_CHECK(igraph_dqueue_init(&history, time_window * (no_of_neighbors + 1) + 10)); IGRAPH_FINALLY(igraph_dqueue_destroy, &history); RNG_BEGIN(); /* first node */ igraph_psumtree_update(&sumtree, 0, zero_appeal); igraph_dqueue_push(&history, -1); /* and the rest */ for (i = 1; i < no_of_nodes; i++) { igraph_real_t sum; long int to; if (outseq != 0 && igraph_vector_size(outseq) != 0) { no_of_neighbors = (long int) VECTOR(*outseq)[i]; } if (i >= time_window) { while ((j = (long int) igraph_dqueue_pop(&history)) != -1) { long int age = (i - j) / binwidth; VECTOR(degree)[j] -= 1; igraph_psumtree_update(&sumtree, j, (pow(VECTOR(degree)[j], pa_exp) + zero_appeal)* pow(age + 1, aging_exp)); } } sum = igraph_psumtree_sum(&sumtree); for (j = 0; j < no_of_neighbors; j++) { igraph_psumtree_search(&sumtree, &to, RNG_UNIF(0, sum)); VECTOR(degree)[to]++; VECTOR(edges)[edgeptr++] = i; VECTOR(edges)[edgeptr++] = to; igraph_dqueue_push(&history, to); } igraph_dqueue_push(&history, -1); /* update probabilities */ for (j = 0; j < no_of_neighbors; j++) { long int n = (long int) VECTOR(edges)[edgeptr - 2 * j - 1]; long int age = (i - n) / binwidth; igraph_psumtree_update(&sumtree, n, (pow(VECTOR(degree)[n], pa_exp) + zero_appeal)* pow(age + 1, aging_exp)); } if (outpref) { VECTOR(degree)[i] += no_of_neighbors; igraph_psumtree_update(&sumtree, i, pow(VECTOR(degree)[i], pa_exp) + zero_appeal); } else { igraph_psumtree_update(&sumtree, i, zero_appeal); } /* aging */ for (k = 1; i - binwidth * k + 1 >= 1; k++) { long int shnode = i - binwidth * k; long int deg = (long int) VECTOR(degree)[shnode]; long int age = (i - shnode) / binwidth; igraph_psumtree_update(&sumtree, shnode, (pow(deg, pa_exp) + zero_appeal) * pow(age + 2, aging_exp)); } } RNG_END(); igraph_dqueue_destroy(&history); igraph_vector_destroy(°ree); igraph_psumtree_destroy(&sumtree); IGRAPH_FINALLY_CLEAN(3); IGRAPH_CHECK(igraph_create(graph, &edges, nodes, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_grg_game * \brief Generating geometric random graphs. * * A geometric random graph is created by dropping points (=vertices) * randomly to the unit square and then connecting all those pairs * which are less than \c radius apart in Euclidean norm. * * * Original code contributed by Keith Briggs, thanks Keith. * \param graph Pointer to an uninitialized graph object, * \param nodes The number of vertices in the graph. * \param radius The radius within which the vertices will be connected. * \param torus Logical constant, if true periodic boundary conditions * will be used, ie. the vertices are assumed to be on a torus * instead of a square. * \return Error code. * * Time complexity: TODO, less than O(|V|^2+|E|). * * \example examples/simple/igraph_grg_game.c */ int igraph_grg_game(igraph_t *graph, igraph_integer_t nodes, igraph_real_t radius, igraph_bool_t torus, igraph_vector_t *x, igraph_vector_t *y) { long int i; igraph_vector_t myx, myy, *xx = &myx, *yy = &myy, edges; igraph_real_t r2 = radius * radius; IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_CHECK(igraph_vector_reserve(&edges, nodes)); if (x) { xx = x; IGRAPH_CHECK(igraph_vector_resize(xx, nodes)); } else { IGRAPH_VECTOR_INIT_FINALLY(xx, nodes); } if (y) { yy = y; IGRAPH_CHECK(igraph_vector_resize(yy, nodes)); } else { IGRAPH_VECTOR_INIT_FINALLY(yy, nodes); } RNG_BEGIN(); for (i = 0; i < nodes; i++) { VECTOR(*xx)[i] = RNG_UNIF01(); VECTOR(*yy)[i] = RNG_UNIF01(); } RNG_END(); igraph_vector_sort(xx); if (!torus) { for (i = 0; i < nodes; i++) { igraph_real_t xx1 = VECTOR(*xx)[i]; igraph_real_t yy1 = VECTOR(*yy)[i]; long int j = i + 1; igraph_real_t dx, dy; while ( j < nodes && (dx = VECTOR(*xx)[j] - xx1) < radius) { dy = VECTOR(*yy)[j] - yy1; if (dx * dx + dy * dy < r2) { IGRAPH_CHECK(igraph_vector_push_back(&edges, i)); IGRAPH_CHECK(igraph_vector_push_back(&edges, j)); } j++; } } } else { for (i = 0; i < nodes; i++) { igraph_real_t xx1 = VECTOR(*xx)[i]; igraph_real_t yy1 = VECTOR(*yy)[i]; long int j = i + 1; igraph_real_t dx, dy; while ( j < nodes && (dx = VECTOR(*xx)[j] - xx1) < radius) { dy = fabs(VECTOR(*yy)[j] - yy1); if (dx > 0.5) { dx = 1 - dx; } if (dy > 0.5) { dy = 1 - dy; } if (dx * dx + dy * dy < r2) { IGRAPH_CHECK(igraph_vector_push_back(&edges, i)); IGRAPH_CHECK(igraph_vector_push_back(&edges, j)); } j++; } if (j == nodes) { j = 0; while (j < i && (dx = 1 - xx1 + VECTOR(*xx)[j]) < radius && xx1 - VECTOR(*xx)[j] >= radius) { dy = fabs(VECTOR(*yy)[j] - yy1); if (dy > 0.5) { dy = 1 - dy; } if (dx * dx + dy * dy < r2) { IGRAPH_CHECK(igraph_vector_push_back(&edges, i)); IGRAPH_CHECK(igraph_vector_push_back(&edges, j)); } j++; } } } } if (!y) { igraph_vector_destroy(yy); IGRAPH_FINALLY_CLEAN(1); } if (!x) { igraph_vector_destroy(xx); IGRAPH_FINALLY_CLEAN(1); } IGRAPH_CHECK(igraph_create(graph, &edges, nodes, IGRAPH_UNDIRECTED)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } void igraph_i_preference_game_free_vids_by_type(igraph_vector_ptr_t *vecs); void igraph_i_preference_game_free_vids_by_type(igraph_vector_ptr_t *vecs) { int i = 0, n; igraph_vector_t *v; n = (int) igraph_vector_ptr_size(vecs); for (i = 0; i < n; i++) { v = (igraph_vector_t*)VECTOR(*vecs)[i]; if (v) { igraph_vector_destroy(v); } } igraph_vector_ptr_destroy_all(vecs); } /** * \function igraph_preference_game * \brief Generates a graph with vertex types and connection preferences * * * This is practically the nongrowing variant of \ref * igraph_establishment_game. A given number of vertices are * generated. Every vertex is assigned to a vertex type according to * the given type probabilities. Finally, every * vertex pair is evaluated and an edge is created between them with a * probability depending on the types of the vertices involved. * * * In other words, this function generates a graph according to a * block-model. Vertices are divided into groups (or blocks), and * the probability the two vertices are connected depends on their * groups only. * * \param graph Pointer to an uninitialized graph. * \param nodes The number of vertices in the graph. * \param types The number of vertex types. * \param type_dist Vector giving the distribution of vertex types. If * \c NULL, all vertex types will have equal probability. See also the * \c fixed_sizes argument. * \param fixed_sizes Boolean. If true, then the number of vertices with a * given vertex type is fixed and the \c type_dist argument gives these * numbers for each vertex type. If true, and \c type_dist is \c NULL, * then the function tries to make vertex groups of the same size. If this * is not possible, then some groups will have an extra vertex. * \param pref_matrix Matrix giving the connection probabilities for * different vertex types. This should be symmetric if the requested * graph is undirected. * \param node_type_vec A vector where the individual generated vertex types * will be stored. If \c NULL , the vertex types won't be saved. * \param directed Logical, whether to generate a directed graph. If undirected * graphs are requested, only the lower left triangle of the preference * matrix is considered. * \param loops Logical, whether loop edges are allowed. * \return Error code. * * Added in version 0.3. * * Time complexity: O(|V|+|E|), the * number of vertices plus the number of edges in the graph. * * \sa igraph_establishment_game() * * \example examples/simple/igraph_preference_game.c */ int igraph_preference_game(igraph_t *graph, igraph_integer_t nodes, igraph_integer_t types, const igraph_vector_t *type_dist, igraph_bool_t fixed_sizes, const igraph_matrix_t *pref_matrix, igraph_vector_t *node_type_vec, igraph_bool_t directed, igraph_bool_t loops) { long int i, j; igraph_vector_t edges, s; igraph_vector_t* nodetypes; igraph_vector_ptr_t vids_by_type; igraph_real_t maxcum, maxedges; if (types < 1) { IGRAPH_ERROR("types must be >= 1", IGRAPH_EINVAL); } if (nodes < 0) { IGRAPH_ERROR("nodes must be >= 0", IGRAPH_EINVAL); } if (type_dist && igraph_vector_size(type_dist) != types) { if (igraph_vector_size(type_dist) > types) { IGRAPH_WARNING("length of type_dist > types, type_dist will be trimmed"); } else { IGRAPH_ERROR("type_dist vector too short", IGRAPH_EINVAL); } } if (igraph_matrix_nrow(pref_matrix) < types || igraph_matrix_ncol(pref_matrix) < types) { IGRAPH_ERROR("pref_matrix too small", IGRAPH_EINVAL); } if (fixed_sizes && type_dist) { if (igraph_vector_sum(type_dist) != nodes) { IGRAPH_ERROR("Invalid group sizes, their sum must match the number" " of vertices", IGRAPH_EINVAL); } } if (node_type_vec) { IGRAPH_CHECK(igraph_vector_resize(node_type_vec, nodes)); nodetypes = node_type_vec; } else { nodetypes = igraph_Calloc(1, igraph_vector_t); if (nodetypes == 0) { IGRAPH_ERROR("preference_game failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, nodetypes); IGRAPH_VECTOR_INIT_FINALLY(nodetypes, nodes); } IGRAPH_CHECK(igraph_vector_ptr_init(&vids_by_type, types)); IGRAPH_FINALLY(igraph_vector_ptr_destroy_all, &vids_by_type); for (i = 0; i < types; i++) { VECTOR(vids_by_type)[i] = igraph_Calloc(1, igraph_vector_t); if (VECTOR(vids_by_type)[i] == 0) { IGRAPH_ERROR("preference_game failed", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_init(VECTOR(vids_by_type)[i], 0)); } IGRAPH_FINALLY_CLEAN(1); /* removing igraph_vector_ptr_destroy_all */ IGRAPH_FINALLY(igraph_i_preference_game_free_vids_by_type, &vids_by_type); RNG_BEGIN(); if (!fixed_sizes) { igraph_vector_t cumdist; IGRAPH_VECTOR_INIT_FINALLY(&cumdist, types + 1); VECTOR(cumdist)[0] = 0; if (type_dist) { for (i = 0; i < types; i++) { VECTOR(cumdist)[i + 1] = VECTOR(cumdist)[i] + VECTOR(*type_dist)[i]; } } else { for (i = 0; i < types; i++) { VECTOR(cumdist)[i + 1] = i + 1; } } maxcum = igraph_vector_tail(&cumdist); for (i = 0; i < nodes; i++) { long int type1; igraph_real_t uni1 = RNG_UNIF(0, maxcum); igraph_vector_binsearch(&cumdist, uni1, &type1); VECTOR(*nodetypes)[i] = type1 - 1; IGRAPH_CHECK(igraph_vector_push_back( (igraph_vector_t*)VECTOR(vids_by_type)[type1 - 1], i)); } igraph_vector_destroy(&cumdist); IGRAPH_FINALLY_CLEAN(1); } else { int an = 0; if (type_dist) { for (i = 0; i < types; i++) { int no = (int) VECTOR(*type_dist)[i]; igraph_vector_t *v = VECTOR(vids_by_type)[i]; for (j = 0; j < no && an < nodes; j++) { VECTOR(*nodetypes)[an] = i; IGRAPH_CHECK(igraph_vector_push_back(v, an)); an++; } } } else { int fixno = (int) ceil( (double)nodes / types); for (i = 0; i < types; i++) { igraph_vector_t *v = VECTOR(vids_by_type)[i]; for (j = 0; j < fixno && an < nodes; j++) { VECTOR(*nodetypes)[an++] = i; IGRAPH_CHECK(igraph_vector_push_back(v, an)); an++; } } } } IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_VECTOR_INIT_FINALLY(&s, 0); for (i = 0; i < types; i++) { for (j = 0; j < types; j++) { /* Generating the random subgraph between vertices of type i and j */ long int k, l; igraph_real_t p, last; igraph_vector_t *v1, *v2; long int v1_size, v2_size; IGRAPH_ALLOW_INTERRUPTION(); v1 = (igraph_vector_t*)VECTOR(vids_by_type)[i]; v2 = (igraph_vector_t*)VECTOR(vids_by_type)[j]; v1_size = igraph_vector_size(v1); v2_size = igraph_vector_size(v2); p = MATRIX(*pref_matrix, i, j); igraph_vector_clear(&s); if (i != j) { /* The two vertex sets are disjoint, this is the easier case */ if (i > j && !directed) { continue; } maxedges = v1_size * v2_size; } else { if (directed && loops) { maxedges = v1_size * v1_size; } else if (directed && !loops) { maxedges = v1_size * (v1_size - 1); } else if (!directed && loops) { maxedges = v1_size * (v1_size + 1) / 2; } else { maxedges = v1_size * (v1_size - 1) / 2; } } IGRAPH_CHECK(igraph_vector_reserve(&s, (long int) (maxedges * p * 1.1))); last = RNG_GEOM(p); while (last < maxedges) { IGRAPH_CHECK(igraph_vector_push_back(&s, last)); last += RNG_GEOM(p); last += 1; } l = igraph_vector_size(&s); IGRAPH_CHECK(igraph_vector_reserve(&edges, igraph_vector_size(&edges) + l * 2)); if (i != j) { /* Generating the subgraph between vertices of type i and j */ for (k = 0; k < l; k++) { long int to = (long int) floor(VECTOR(s)[k] / v1_size); long int from = (long int) (VECTOR(s)[k] - ((igraph_real_t)to) * v1_size); igraph_vector_push_back(&edges, VECTOR(*v1)[from]); igraph_vector_push_back(&edges, VECTOR(*v2)[to]); } } else { /* Generating the subgraph among vertices of type i */ if (directed && loops) { for (k = 0; k < l; k++) { long int to = (long int) floor(VECTOR(s)[k] / v1_size); long int from = (long int) (VECTOR(s)[k] - ((igraph_real_t)to) * v1_size); igraph_vector_push_back(&edges, VECTOR(*v1)[from]); igraph_vector_push_back(&edges, VECTOR(*v1)[to]); } } else if (directed && !loops) { for (k = 0; k < l; k++) { long int to = (long int) floor(VECTOR(s)[k] / v1_size); long int from = (long int) (VECTOR(s)[k] - ((igraph_real_t)to) * v1_size); if (from == to) { to = v1_size - 1; } igraph_vector_push_back(&edges, VECTOR(*v1)[from]); igraph_vector_push_back(&edges, VECTOR(*v1)[to]); } } else if (!directed && loops) { for (k = 0; k < l; k++) { long int to = (long int) floor((sqrt(8 * VECTOR(s)[k] + 1) - 1) / 2); long int from = (long int) (VECTOR(s)[k] - (((igraph_real_t)to) * (to + 1)) / 2); igraph_vector_push_back(&edges, VECTOR(*v1)[from]); igraph_vector_push_back(&edges, VECTOR(*v1)[to]); } } else { for (k = 0; k < l; k++) { long int to = (long int) floor((sqrt(8 * VECTOR(s)[k] + 1) + 1) / 2); long int from = (long int) (VECTOR(s)[k] - (((igraph_real_t)to) * (to - 1)) / 2); igraph_vector_push_back(&edges, VECTOR(*v1)[from]); igraph_vector_push_back(&edges, VECTOR(*v1)[to]); } } } } } RNG_END(); igraph_vector_destroy(&s); igraph_i_preference_game_free_vids_by_type(&vids_by_type); IGRAPH_FINALLY_CLEAN(2); if (node_type_vec == 0) { igraph_vector_destroy(nodetypes); igraph_Free(nodetypes); IGRAPH_FINALLY_CLEAN(2); } IGRAPH_CHECK(igraph_create(graph, &edges, nodes, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_asymmetric_preference_game * \brief Generates a graph with asymmetric vertex types and connection preferences * * * This is the asymmetric variant of \ref igraph_preference_game() . * A given number of vertices are generated. Every vertex is assigned to an * "incoming" and an "outgoing" vertex type according to the given joint * type probabilities. Finally, every vertex pair is evaluated and a * directed edge is created between them with a probability depending on the * "outgoing" type of the source vertex and the "incoming" type of the target * vertex. * * \param graph Pointer to an uninitialized graph. * \param nodes The number of vertices in the graph. * \param types The number of vertex types. * \param type_dist_matrix Matrix giving the joint distribution of vertex types. * If null, incoming and outgoing vertex types are independent and uniformly * distributed. * \param pref_matrix Matrix giving the connection probabilities for * different vertex types. * \param node_type_in_vec A vector where the individual generated "incoming" * vertex types will be stored. If NULL, the vertex types won't be saved. * \param node_type_out_vec A vector where the individual generated "outgoing" * vertex types will be stored. If NULL, the vertex types won't be saved. * \param loops Logical, whether loop edges are allowed. * \return Error code. * * Added in version 0.3. * * Time complexity: O(|V|+|E|), the * number of vertices plus the number of edges in the graph. * * \sa \ref igraph_preference_game() */ int igraph_asymmetric_preference_game(igraph_t *graph, igraph_integer_t nodes, igraph_integer_t types, igraph_matrix_t *type_dist_matrix, igraph_matrix_t *pref_matrix, igraph_vector_t *node_type_in_vec, igraph_vector_t *node_type_out_vec, igraph_bool_t loops) { long int i, j, k; igraph_vector_t edges, cumdist, s, intersect; igraph_vector_t *nodetypes_in; igraph_vector_t *nodetypes_out; igraph_vector_ptr_t vids_by_intype, vids_by_outtype; igraph_real_t maxcum, maxedges; if (types < 1) { IGRAPH_ERROR("types must be >= 1", IGRAPH_EINVAL); } if (nodes < 0) { IGRAPH_ERROR("nodes must be >= 0", IGRAPH_EINVAL); } if (type_dist_matrix) { if (igraph_matrix_nrow(type_dist_matrix) < types || igraph_matrix_ncol(type_dist_matrix) < types) { IGRAPH_ERROR("type_dist_matrix too small", IGRAPH_EINVAL); } else if (igraph_matrix_nrow(type_dist_matrix) > types || igraph_matrix_ncol(type_dist_matrix) > types) { IGRAPH_WARNING("type_dist_matrix will be trimmed"); } } if (igraph_matrix_nrow(pref_matrix) < types || igraph_matrix_ncol(pref_matrix) < types) { IGRAPH_ERROR("pref_matrix too small", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(&cumdist, types * types + 1); if (node_type_in_vec) { nodetypes_in = node_type_in_vec; IGRAPH_CHECK(igraph_vector_resize(nodetypes_in, nodes)); } else { nodetypes_in = igraph_Calloc(1, igraph_vector_t); if (nodetypes_in == 0) { IGRAPH_ERROR("asymmetric_preference_game failed", IGRAPH_ENOMEM); } IGRAPH_VECTOR_INIT_FINALLY(nodetypes_in, nodes); } if (node_type_out_vec) { nodetypes_out = node_type_out_vec; IGRAPH_CHECK(igraph_vector_resize(nodetypes_out, nodes)); } else { nodetypes_out = igraph_Calloc(1, igraph_vector_t); if (nodetypes_out == 0) { IGRAPH_ERROR("asymmetric_preference_game failed", IGRAPH_ENOMEM); } IGRAPH_VECTOR_INIT_FINALLY(nodetypes_out, nodes); } IGRAPH_CHECK(igraph_vector_ptr_init(&vids_by_intype, types)); IGRAPH_FINALLY(igraph_vector_ptr_destroy_all, &vids_by_intype); IGRAPH_CHECK(igraph_vector_ptr_init(&vids_by_outtype, types)); IGRAPH_FINALLY(igraph_vector_ptr_destroy_all, &vids_by_outtype); for (i = 0; i < types; i++) { VECTOR(vids_by_intype)[i] = igraph_Calloc(1, igraph_vector_t); VECTOR(vids_by_outtype)[i] = igraph_Calloc(1, igraph_vector_t); if (VECTOR(vids_by_intype)[i] == 0 || VECTOR(vids_by_outtype)[i] == 0) { IGRAPH_ERROR("asymmetric_preference_game failed", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_init(VECTOR(vids_by_intype)[i], 0)); IGRAPH_CHECK(igraph_vector_init(VECTOR(vids_by_outtype)[i], 0)); } IGRAPH_FINALLY_CLEAN(2); /* removing igraph_vector_ptr_destroy_all */ IGRAPH_FINALLY(igraph_i_preference_game_free_vids_by_type, &vids_by_intype); IGRAPH_FINALLY(igraph_i_preference_game_free_vids_by_type, &vids_by_outtype); VECTOR(cumdist)[0] = 0; if (type_dist_matrix) { for (i = 0, k = 0; i < types; i++) { for (j = 0; j < types; j++, k++) { VECTOR(cumdist)[k + 1] = VECTOR(cumdist)[k] + MATRIX(*type_dist_matrix, i, j); } } } else { for (i = 0; i < types * types; i++) { VECTOR(cumdist)[i + 1] = i + 1; } } maxcum = igraph_vector_tail(&cumdist); RNG_BEGIN(); for (i = 0; i < nodes; i++) { long int type1, type2; igraph_real_t uni1 = RNG_UNIF(0, maxcum); igraph_vector_binsearch(&cumdist, uni1, &type1); type2 = (type1 - 1) % (int)types; type1 = (type1 - 1) / (int)types; VECTOR(*nodetypes_in)[i] = type1; VECTOR(*nodetypes_out)[i] = type2; IGRAPH_CHECK(igraph_vector_push_back( (igraph_vector_t*)VECTOR(vids_by_intype)[type1], i)); IGRAPH_CHECK(igraph_vector_push_back( (igraph_vector_t*)VECTOR(vids_by_outtype)[type2], i)); } igraph_vector_destroy(&cumdist); IGRAPH_FINALLY_CLEAN(1); IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_VECTOR_INIT_FINALLY(&s, 0); IGRAPH_VECTOR_INIT_FINALLY(&intersect, 0); for (i = 0; i < types; i++) { for (j = 0; j < types; j++) { long int kk, l, c; igraph_real_t p, last; igraph_vector_t *v1, *v2; long int v1_size, v2_size; IGRAPH_ALLOW_INTERRUPTION(); v1 = (igraph_vector_t*)VECTOR(vids_by_outtype)[i]; v2 = (igraph_vector_t*)VECTOR(vids_by_intype)[j]; v1_size = igraph_vector_size(v1); v2_size = igraph_vector_size(v2); maxedges = v1_size * v2_size; if (!loops) { IGRAPH_CHECK(igraph_vector_intersect_sorted(v1, v2, &intersect)); c = igraph_vector_size(&intersect); maxedges -= c; } p = MATRIX(*pref_matrix, i, j); igraph_vector_clear(&s); IGRAPH_CHECK(igraph_vector_reserve(&s, (long int) (maxedges * p * 1.1))); last = RNG_GEOM(p); while (last < maxedges) { IGRAPH_CHECK(igraph_vector_push_back(&s, last)); last += RNG_GEOM(p); last += 1; } l = igraph_vector_size(&s); IGRAPH_CHECK(igraph_vector_reserve(&edges, igraph_vector_size(&edges) + l * 2)); if (!loops && c > 0) { for (kk = 0; kk < l; kk++) { long int to = (long int) floor(VECTOR(s)[kk] / v1_size); long int from = (long int) (VECTOR(s)[kk] - ((igraph_real_t)to) * v1_size); if (VECTOR(*v1)[from] == VECTOR(*v2)[to]) { /* remap loop edges */ to = v2_size - 1; igraph_vector_binsearch(&intersect, VECTOR(*v1)[from], &c); from = v1_size - 1; if (VECTOR(*v1)[from] == VECTOR(*v2)[to]) { from--; } while (c > 0) { c--; from--; if (VECTOR(*v1)[from] == VECTOR(*v2)[to]) { from--; } } } igraph_vector_push_back(&edges, VECTOR(*v1)[from]); igraph_vector_push_back(&edges, VECTOR(*v2)[to]); } } else { for (kk = 0; kk < l; kk++) { long int to = (long int) floor(VECTOR(s)[kk] / v1_size); long int from = (long int) (VECTOR(s)[kk] - ((igraph_real_t)to) * v1_size); igraph_vector_push_back(&edges, VECTOR(*v1)[from]); igraph_vector_push_back(&edges, VECTOR(*v2)[to]); } } } } RNG_END(); igraph_vector_destroy(&s); igraph_vector_destroy(&intersect); igraph_i_preference_game_free_vids_by_type(&vids_by_intype); igraph_i_preference_game_free_vids_by_type(&vids_by_outtype); IGRAPH_FINALLY_CLEAN(4); if (node_type_out_vec == 0) { igraph_vector_destroy(nodetypes_out); igraph_Free(nodetypes_out); IGRAPH_FINALLY_CLEAN(1); } if (node_type_in_vec == 0) { igraph_vector_destroy(nodetypes_in); igraph_Free(nodetypes_in); IGRAPH_FINALLY_CLEAN(1); } IGRAPH_CHECK(igraph_create(graph, &edges, nodes, 1)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_i_rewire_edges_no_multiple(igraph_t *graph, igraph_real_t prob, igraph_bool_t loops, igraph_vector_t *edges); int igraph_i_rewire_edges_no_multiple(igraph_t *graph, igraph_real_t prob, igraph_bool_t loops, igraph_vector_t *edges) { int no_verts = igraph_vcount(graph); int no_edges = igraph_ecount(graph); igraph_vector_t eorder, tmp; igraph_vector_int_t first, next, prev, marked; int i, to_rewire, last_other = -1; /* Create our special graph representation */ # define ADD_STUB(vertex, stub) do { \ if (VECTOR(first)[(vertex)]) { \ VECTOR(prev)[(int) VECTOR(first)[(vertex)]-1]=(stub)+1; \ } \ VECTOR(next)[(stub)]=VECTOR(first)[(vertex)]; \ VECTOR(prev)[(stub)]=0; \ VECTOR(first)[(vertex)]=(stub)+1; \ } while (0) # define DEL_STUB(vertex, stub) do { \ if (VECTOR(next)[(stub)]) { \ VECTOR(prev)[VECTOR(next)[(stub)]-1]=VECTOR(prev)[(stub)]; \ } \ if (VECTOR(prev)[(stub)]) { \ VECTOR(next)[VECTOR(prev)[(stub)]-1]=VECTOR(next)[(stub)]; \ } else { \ VECTOR(first)[(vertex)]=VECTOR(next)[(stub)]; \ } \ } while (0) # define MARK_NEIGHBORS(vertex) do { \ int xxx_ =VECTOR(first)[(vertex)]; \ while (xxx_) { \ int o= (int) VECTOR(*edges)[xxx_ % 2 ? xxx_ : xxx_-2]; \ VECTOR(marked)[o]=other+1; \ xxx_=VECTOR(next)[xxx_-1]; \ } \ } while (0) IGRAPH_CHECK(igraph_vector_int_init(&first, no_verts)); IGRAPH_FINALLY(igraph_vector_int_destroy, &first); IGRAPH_CHECK(igraph_vector_int_init(&next, no_edges * 2)); IGRAPH_FINALLY(igraph_vector_int_destroy, &next); IGRAPH_CHECK(igraph_vector_int_init(&prev, no_edges * 2)); IGRAPH_FINALLY(igraph_vector_int_destroy, &prev); IGRAPH_CHECK(igraph_get_edgelist(graph, edges, /*bycol=*/ 0)); IGRAPH_VECTOR_INIT_FINALLY(&eorder, no_edges); IGRAPH_VECTOR_INIT_FINALLY(&tmp, no_edges); for (i = 0; i < no_edges; i++) { int idx1 = 2 * i, idx2 = idx1 + 1, from = (int) VECTOR(*edges)[idx1], to = (int) VECTOR(*edges)[idx2]; VECTOR(tmp)[i] = from; ADD_STUB(from, idx1); ADD_STUB(to, idx2); } IGRAPH_CHECK(igraph_vector_order1(&tmp, &eorder, no_verts)); igraph_vector_destroy(&tmp); IGRAPH_FINALLY_CLEAN(1); IGRAPH_CHECK(igraph_vector_int_init(&marked, no_verts)); IGRAPH_FINALLY(igraph_vector_int_destroy, &marked); /* Rewire the stubs, part I */ to_rewire = (int) RNG_GEOM(prob); while (to_rewire < no_edges) { int stub = (int) (2 * VECTOR(eorder)[to_rewire] + 1); int v = (int) VECTOR(*edges)[stub]; int ostub = stub - 1; int other = (int) VECTOR(*edges)[ostub]; int pot; if (last_other != other) { MARK_NEIGHBORS(other); } /* Do the rewiring */ do { if (loops) { pot = (int) RNG_INTEGER(0, no_verts - 1); } else { pot = (int) RNG_INTEGER(0, no_verts - 2); pot = pot != other ? pot : no_verts - 1; } } while (VECTOR(marked)[pot] == other + 1 && pot != v); if (pot != v) { DEL_STUB(v, stub); ADD_STUB(pot, stub); VECTOR(marked)[v] = 0; VECTOR(marked)[pot] = other + 1; VECTOR(*edges)[stub] = pot; } to_rewire += RNG_GEOM(prob) + 1; last_other = other; } /* Create the new index, from the potentially rewired stubs */ IGRAPH_VECTOR_INIT_FINALLY(&tmp, no_edges); for (i = 0; i < no_edges; i++) { VECTOR(tmp)[i] = VECTOR(*edges)[2 * i + 1]; } IGRAPH_CHECK(igraph_vector_order1(&tmp, &eorder, no_verts)); igraph_vector_destroy(&tmp); IGRAPH_FINALLY_CLEAN(1); /* Rewire the stubs, part II */ igraph_vector_int_null(&marked); last_other = -1; to_rewire = (int) RNG_GEOM(prob); while (to_rewire < no_edges) { int stub = (int) (2 * VECTOR(eorder)[to_rewire]); int v = (int) VECTOR(*edges)[stub]; int ostub = stub + 1; int other = (int) VECTOR(*edges)[ostub]; int pot; if (last_other != other) { MARK_NEIGHBORS(other); } /* Do the rewiring */ do { if (loops) { pot = (int) RNG_INTEGER(0, no_verts - 1); } else { pot = (int) RNG_INTEGER(0, no_verts - 2); pot = pot != other ? pot : no_verts - 1; } } while (VECTOR(marked)[pot] == other + 1 && pot != v); if (pot != v) { DEL_STUB(v, stub); ADD_STUB(pot, stub); VECTOR(marked)[v] = 0; VECTOR(marked)[pot] = other + 1; VECTOR(*edges)[stub] = pot; } to_rewire += RNG_GEOM(prob) + 1; last_other = other; } igraph_vector_int_destroy(&marked); igraph_vector_int_destroy(&prev); igraph_vector_int_destroy(&next); igraph_vector_int_destroy(&first); igraph_vector_destroy(&eorder); IGRAPH_FINALLY_CLEAN(5); return 0; } #undef ADD_STUB #undef DEL_STUB #undef MARK_NEIGHBORS /** * \function igraph_rewire_edges * \brief Rewire the edges of a graph with constant probability * * This function rewires the edges of a graph with a constant * probability. More precisely each end point of each edge is rewired * to a uniformly randomly chosen vertex with constant probability \p * prob. * * Note that this function modifies the input \p graph, * call \ref igraph_copy() if you want to keep it. * * \param graph The input graph, this will be rewired, it can be * directed or undirected. * \param prob The rewiring probability a constant between zero and * one (inclusive). * \param loops Boolean, whether loop edges are allowed in the new * graph, or not. * \param multiple Boolean, whether multiple edges are allowed in the * new graph. * \return Error code. * * \sa \ref igraph_watts_strogatz_game() uses this function for the * rewiring. * * Time complexity: O(|V|+|E|). */ int igraph_rewire_edges(igraph_t *graph, igraph_real_t prob, igraph_bool_t loops, igraph_bool_t multiple) { igraph_t newgraph; long int no_of_edges = igraph_ecount(graph); long int no_of_nodes = igraph_vcount(graph); long int endpoints = no_of_edges * 2; long int to_rewire; igraph_vector_t edges; if (prob < 0 || prob > 1) { IGRAPH_ERROR("Rewiring probability should be between zero and one", IGRAPH_EINVAL); } if (prob == 0) { /* This is easy, just leave things as they are */ return IGRAPH_SUCCESS; } IGRAPH_VECTOR_INIT_FINALLY(&edges, endpoints); RNG_BEGIN(); if (prob != 0 && no_of_edges > 0) { if (multiple) { /* If multiple edges are allowed, then there is an easy and fast method. Each endpoint of an edge is rewired with probability p, so the "skips" between the really rewired endpoints follow a geometric distribution. */ IGRAPH_CHECK(igraph_get_edgelist(graph, &edges, 0)); to_rewire = (long int) RNG_GEOM(prob); while (to_rewire < endpoints) { if (loops) { VECTOR(edges)[to_rewire] = RNG_INTEGER(0, no_of_nodes - 1); } else { long int opos = to_rewire % 2 ? to_rewire - 1 : to_rewire + 1; long int nei = (long int) VECTOR(edges)[opos]; long int r = RNG_INTEGER(0, no_of_nodes - 2); VECTOR(edges)[ to_rewire ] = (r != nei ? r : no_of_nodes - 1); } to_rewire += RNG_GEOM(prob) + 1; } } else { IGRAPH_CHECK(igraph_i_rewire_edges_no_multiple(graph, prob, loops, &edges)); } } RNG_END(); IGRAPH_CHECK(igraph_create(&newgraph, &edges, (igraph_integer_t) no_of_nodes, igraph_is_directed(graph))); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); IGRAPH_FINALLY(igraph_destroy, &newgraph); IGRAPH_I_ATTRIBUTE_DESTROY(&newgraph); IGRAPH_I_ATTRIBUTE_COPY(&newgraph, graph, 1, 1, 1); IGRAPH_FINALLY_CLEAN(1); igraph_destroy(graph); *graph = newgraph; return 0; } /** * \function igraph_rewire_directed_edges * \brief Rewire the chosen endpoint of directed edges * * This function rewires either the start or end of directed edges in a graph * with a constant probability. Correspondingly, either the in-degree sequence * or the out-degree sequence of the graph will be preserved. * * Note that this function modifies the input \p graph, * call \ref igraph_copy() if you want to keep it. * * \param graph The input graph, this will be rewired, it can be * directed or undirected. If it is directed, \ref igraph_rewire_edges() * will be called. * \param prob The rewiring probability, a constant between zero and * one (inclusive). * \param loops Boolean, whether loop edges are allowed in the new * graph, or not. * \param mode The endpoints of directed edges to rewire. It is ignored for * undirected graphs. Possible values: * \clist * \cli IGRAPH_OUT * rewire the end of each directed edge * \cli IGRAPH_IN * rewire the start of each directed edge * \cli IGRAPH_ALL * rewire both endpoints of each edge * \endclist * \return Error code. * * \sa \ref igraph_rewire_edges(), \ref igraph_rewire() * * Time complexity: O(|E|). */ int igraph_rewire_directed_edges(igraph_t *graph, igraph_real_t prob, igraph_bool_t loops, igraph_neimode_t mode) { if (prob < 0 || prob > 1) { IGRAPH_ERROR("Rewiring probability should be between zero and one", IGRAPH_EINVAL); } if (mode != IGRAPH_OUT && mode != IGRAPH_IN && mode != IGRAPH_ALL) { IGRAPH_ERROR("Invalid mode argument", IGRAPH_EINVMODE); } if (prob == 0) { return IGRAPH_SUCCESS; } if (igraph_is_directed(graph) && mode != IGRAPH_ALL) { igraph_t newgraph; long int no_of_edges = igraph_ecount(graph); long int no_of_nodes = igraph_vcount(graph); long int to_rewire; long int offset; igraph_vector_t edges; IGRAPH_VECTOR_INIT_FINALLY(&edges, 2 * no_of_edges); switch (mode) { case IGRAPH_IN: offset = 0; break; case IGRAPH_OUT: offset = 1; break; case IGRAPH_ALL: break; /* suppress compiler warning */ } IGRAPH_CHECK(igraph_get_edgelist(graph, &edges, 0)); RNG_BEGIN(); to_rewire = RNG_GEOM(prob); while (to_rewire < no_of_edges) { if (loops) { VECTOR(edges)[2 * to_rewire + offset] = RNG_INTEGER(0, no_of_nodes - 1); } else { long int nei = (long int) VECTOR(edges)[2 * to_rewire + (1 - offset)]; long int r = RNG_INTEGER(0, no_of_nodes - 2); VECTOR(edges)[2 * to_rewire + offset] = (r != nei ? r : no_of_nodes - 1); } to_rewire += RNG_GEOM(prob) + 1; } RNG_END(); IGRAPH_CHECK(igraph_create(&newgraph, &edges, (igraph_integer_t) no_of_nodes, igraph_is_directed(graph))); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); IGRAPH_FINALLY(igraph_destroy, &newgraph); IGRAPH_I_ATTRIBUTE_DESTROY(&newgraph); IGRAPH_I_ATTRIBUTE_COPY(&newgraph, graph, 1, 1, 1); IGRAPH_FINALLY_CLEAN(1); igraph_destroy(graph); *graph = newgraph; } else { IGRAPH_CHECK(igraph_rewire_edges(graph, prob, loops, /* multiple = */ 0)); } return 0; } /** * \function igraph_watts_strogatz_game * \brief The Watts-Strogatz small-world model * * This function generates a graph according to the Watts-Strogatz * model of small-world networks. The graph is obtained by creating a * circular undirected lattice and then rewire the edges randomly with * a constant probability. * * See also: Duncan J Watts and Steven H Strogatz: * Collective dynamics of small world networks, Nature * 393, 440-442, 1998. * \param graph The graph to initialize. * \param dim The dimension of the lattice. * \param size The size of the lattice along each dimension. * \param nei The size of the neighborhood for each vertex. This is * the same as the \p nei argument of \ref * igraph_connect_neighborhood(). * \param p The rewiring probability. A real number between zero and * one (inclusive). * \param loops Logical, whether to generate loop edges. * \param multiple Logical, whether to allow multiple edges in the * generated graph. * \return Error code. * * \sa \ref igraph_lattice(), \ref igraph_connect_neighborhood() and * \ref igraph_rewire_edges() can be used if more flexibility is * needed, eg. a different type of lattice. * * Time complexity: O(|V|*d^o+|E|), |V| and |E| are the number of * vertices and edges, d is the average degree, o is the \p nei * argument. */ int igraph_watts_strogatz_game(igraph_t *graph, igraph_integer_t dim, igraph_integer_t size, igraph_integer_t nei, igraph_real_t p, igraph_bool_t loops, igraph_bool_t multiple) { igraph_vector_t dimvector; long int i; if (dim < 1) { IGRAPH_ERROR("WS game: dimension should be at least one", IGRAPH_EINVAL); } if (size < 1) { IGRAPH_ERROR("WS game: lattice size should be at least one", IGRAPH_EINVAL); } if (p < 0 || p > 1) { IGRAPH_ERROR("WS game: rewiring probability should be between 0 and 1", IGRAPH_EINVAL); } /* Create the lattice first */ IGRAPH_VECTOR_INIT_FINALLY(&dimvector, dim); for (i = 0; i < dim; i++) { VECTOR(dimvector)[i] = size; } IGRAPH_CHECK(igraph_lattice(graph, &dimvector, nei, IGRAPH_UNDIRECTED, 0 /* mutual */, 1 /* circular */)); igraph_vector_destroy(&dimvector); IGRAPH_FINALLY_CLEAN(1); IGRAPH_FINALLY(igraph_destroy, graph); /* Rewire the edges then */ IGRAPH_CHECK(igraph_rewire_edges(graph, p, loops, multiple)); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_lastcit_game * \brief Simulate citation network, based on time passed since the last citation. * * This is a quite special stochastic graph generator, it models an * evolving graph. In each time step a single vertex is added to the * network and it cites a number of other vertices (as specified by * the \p edges_per_step argument). The cited vertices are selected * based on the last time they were cited. Time is measured by the * addition of vertices and it is binned into \p pagebins bins. * So if the current time step is \c t and the last citation to a * given \c i vertex was made in time step \c t0, then \c * (t-t0)/binwidth is calculated where binwidth is \c nodes/pagebins+1, * in the last expression '/' denotes integer division, so the * fraction part is omitted. * * * The \p preference argument specifies the preferences for the * citation lags, ie. its first elements contains the attractivity * of the very recently cited vertices, etc. The last element is * special, it contains the attractivity of the vertices which were * never cited. This element should be bigger than zero. * * * Note that this function generates networks with multiple edges if * \p edges_per_step is bigger than one, call \ref igraph_simplify() * on the result to get rid of these edges. * \param graph Pointer to an uninitialized graph object, the result * will be stored here. * \param node The number of vertices in the network. * \param edges_per_node The number of edges to add in each time * step. * \param pagebins The number of age bins to use. * \param preference Pointer to an initialized vector of length * \c pagebins+1. This contains the `attractivity' of the various * age bins, the last element is the attractivity of the vertices * which were never cited, and it should be greater than zero. * It is a good idea to have all positive values in this vector. * \param directed Logical constant, whether to create directed * networks. * \return Error code. * * \sa \ref igraph_barabasi_aging_game(). * * Time complexity: O(|V|*a+|E|*log|V|), |V| is the number of vertices, * |E| is the total number of edges, a is the \p pagebins parameter. */ int igraph_lastcit_game(igraph_t *graph, igraph_integer_t nodes, igraph_integer_t edges_per_node, igraph_integer_t pagebins, const igraph_vector_t *preference, igraph_bool_t directed) { long int no_of_nodes = nodes; igraph_psumtree_t sumtree; igraph_vector_t edges; long int i, j, k; long int *lastcit; long int *index; long int agebins = pagebins; long int binwidth = no_of_nodes / agebins + 1; if (agebins != igraph_vector_size(preference) - 1) { IGRAPH_ERROR("`preference' vector should be of length `agebins' plus one", IGRAPH_EINVAL); } if (agebins <= 1 ) { IGRAPH_ERROR("at least two age bins are need for lastcit game", IGRAPH_EINVAL); } if (VECTOR(*preference)[agebins] <= 0) { IGRAPH_ERROR("the last element of the `preference' vector needs to be positive", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); lastcit = igraph_Calloc(no_of_nodes, long int); if (!lastcit) { IGRAPH_ERROR("lastcit game failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, lastcit); index = igraph_Calloc(no_of_nodes + 1, long int); if (!index) { IGRAPH_ERROR("lastcit game failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, index); IGRAPH_CHECK(igraph_psumtree_init(&sumtree, nodes)); IGRAPH_FINALLY(igraph_psumtree_destroy, &sumtree); IGRAPH_CHECK(igraph_vector_reserve(&edges, nodes * edges_per_node)); /* The first node */ igraph_psumtree_update(&sumtree, 0, VECTOR(*preference)[agebins]); index[0] = 0; index[1] = 0; RNG_BEGIN(); for (i = 1; i < no_of_nodes; i++) { /* Add new edges */ for (j = 0; j < edges_per_node; j++) { long int to; igraph_real_t sum = igraph_psumtree_sum(&sumtree); igraph_psumtree_search(&sumtree, &to, RNG_UNIF(0, sum)); igraph_vector_push_back(&edges, i); igraph_vector_push_back(&edges, to); lastcit[to] = i + 1; igraph_psumtree_update(&sumtree, to, VECTOR(*preference)[0]); } /* Add the node itself */ igraph_psumtree_update(&sumtree, i, VECTOR(*preference)[agebins]); index[i + 1] = index[i] + edges_per_node; /* Update the preference of some vertices if they got to another bin. We need to know the citations of some older vertices, this is in the index. */ for (k = 1; i - binwidth * k >= 1; k++) { long int shnode = i - binwidth * k; long int m = index[shnode], n = index[shnode + 1]; for (j = 2 * m; j < 2 * n; j += 2) { long int cnode = (long int) VECTOR(edges)[j + 1]; if (lastcit[cnode] == shnode + 1) { igraph_psumtree_update(&sumtree, cnode, VECTOR(*preference)[k]); } } } } RNG_END(); igraph_psumtree_destroy(&sumtree); igraph_free(index); igraph_free(lastcit); IGRAPH_FINALLY_CLEAN(3); IGRAPH_CHECK(igraph_create(graph, &edges, nodes, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_cited_type_game * \brief Simulate a citation based on vertex types. * * Function to create a network based on some vertex categories. This * function creates a citation network, in each step a single vertex * and \p edges_per_step citating edges are added, nodes with * different categories (may) have different probabilities to get * cited, as given by the \p pref vector. * * * Note that this function might generate networks with multiple edges * if \p edges_per_step is greater than one. You might want to call * \ref igraph_simplify() on the result to remove multiple edges. * \param graph Pointer to an uninitialized graph object. * \param nodes The number of vertices in the network. * \param types Numeric vector giving the categories of the vertices, * so it should contain \p nodes non-negative integer * numbers. Types are numbered from zero. * \param pref The attractivity of the different vertex categories in * a vector. Its length should be the maximum element in \p types * plus one (types are numbered from zero). * \param edges_per_step Integer constant, the number of edges to add * in each time step. * \param directed Logical constant, whether to create a directed * network. * \return Error code. * * \sa \ref igraph_citing_cited_type_game() for a bit more general * game. * * Time complexity: O((|V|+|E|)log|V|), |V| and |E| are number of * vertices and edges, respectively. */ int igraph_cited_type_game(igraph_t *graph, igraph_integer_t nodes, const igraph_vector_t *types, const igraph_vector_t *pref, igraph_integer_t edges_per_step, igraph_bool_t directed) { igraph_vector_t edges; igraph_vector_t cumsum; igraph_real_t sum; long int i, j, nnval, type; if (igraph_vector_size(types) != nodes) { IGRAPH_ERROR("Invalid size of types", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); /* return an empty graph is nodes is zero */ if (nodes == 0) { igraph_create(graph, &edges, nodes, directed); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } IGRAPH_VECTOR_INIT_FINALLY(&cumsum, 2); IGRAPH_CHECK(igraph_vector_reserve(&cumsum, nodes + 1)); IGRAPH_CHECK(igraph_vector_reserve(&edges, nodes * edges_per_step)); /* first node */ VECTOR(cumsum)[0] = 0; type = (long int) VECTOR(*types)[0]; if (type >= igraph_vector_size(pref)) { IGRAPH_ERROR("pref is too short for the given types", IGRAPH_EINVAL); } nnval = VECTOR(*pref)[type]; if (nnval < 0) { IGRAPH_ERROR("pref contains negative entries", IGRAPH_EINVAL); } sum = VECTOR(cumsum)[1] = nnval; RNG_BEGIN(); for (i = 1; i < nodes; i++) { for (j = 0; j < edges_per_step; j++) { long int to; if (sum > 0) { igraph_vector_binsearch(&cumsum, RNG_UNIF(0, sum), &to); } else { to = i + 1; } igraph_vector_push_back(&edges, i); igraph_vector_push_back(&edges, to - 1); } type = (long int) VECTOR(*types)[i]; if (type >= igraph_vector_size(pref)) { IGRAPH_ERROR("pref is too short for the given types", IGRAPH_EINVAL); } nnval = VECTOR(*pref)[type]; if (nnval < 0) { IGRAPH_ERROR("pref contains negative entries", IGRAPH_EINVAL); } sum += nnval; igraph_vector_push_back(&cumsum, sum); } RNG_END(); igraph_vector_destroy(&cumsum); IGRAPH_FINALLY_CLEAN(1); IGRAPH_CHECK(igraph_create(graph, &edges, nodes, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } void igraph_i_citing_cited_type_game_free(igraph_i_citing_cited_type_game_struct_t *s) { long int i; if (!s->sumtrees) { return; } for (i = 0; i < s->no; i++) { igraph_psumtree_destroy(&s->sumtrees[i]); } } /** * \function igraph_citing_cited_type_game * \brief Simulate a citation network based on vertex types. * * This game is similar to \ref igraph_cited_type_game() but here the * category of the citing vertex is also considered. * * * An evolving citation network is modeled here, a single vertex and * its \p edges_per_step citation are added in each time step. The * odds the a given vertex is cited by the new vertex depends on the * category of both the citing and the cited vertex and is given in * the \p pref matrix. The categories of the citing vertex correspond * to the rows, the categories of the cited vertex to the columns of * this matrix. Ie. the element in row \c i and column \c j gives the * probability that a \c j vertex is cited, if the category of the * citing vertex is \c i. * * * Note that this function might generate networks with multiple edges * if \p edges_per_step is greater than one. You might want to call * \ref igraph_simplify() on the result to remove multiple edges. * \param graph Pointer to an uninitialized graph object. * \param nodes The number of vertices in the network. * \param types A numeric matrix of length \p nodes, containing the * categories of the vertices. The categories are numbered from * zero. * \param pref The preference matrix, a square matrix is required, * both the number of rows and columns should be the maximum * element in \p types plus one (types are numbered from zero). * \param directed Logical constant, whether to create a directed * network. * \return Error code. * * Time complexity: O((|V|+|E|)log|V|), |V| and |E| are number of * vertices and edges, respectively. */ int igraph_citing_cited_type_game(igraph_t *graph, igraph_integer_t nodes, const igraph_vector_t *types, const igraph_matrix_t *pref, igraph_integer_t edges_per_step, igraph_bool_t directed) { igraph_vector_t edges; igraph_i_citing_cited_type_game_struct_t str = { 0, 0 }; igraph_psumtree_t *sumtrees; igraph_vector_t sums; long int nocats; long int i, j; if (igraph_vector_size(types) != nodes) { IGRAPH_ERROR("Invalid size of types", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); /* return an empty graph is nodes is zero */ if (nodes == 0) { igraph_create(graph, &edges, nodes, directed); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(2); /* str and edges */ return 0; } nocats = igraph_matrix_ncol(pref); str.sumtrees = sumtrees = igraph_Calloc(nocats, igraph_psumtree_t); if (!sumtrees) { IGRAPH_ERROR("Citing-cited type game failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_i_citing_cited_type_game_free, &str); for (i = 0; i < nocats; i++) { IGRAPH_CHECK(igraph_psumtree_init(&sumtrees[i], nodes)); str.no++; } IGRAPH_VECTOR_INIT_FINALLY(&sums, nocats); IGRAPH_CHECK(igraph_vector_reserve(&edges, nodes * edges_per_step)); /* First node */ for (i = 0; i < nocats; i++) { long int type = (long int) VECTOR(*types)[0]; if ( MATRIX(*pref, i, type) < 0) { IGRAPH_ERROR("pref contains negative entries", IGRAPH_EINVAL); } igraph_psumtree_update(&sumtrees[i], 0, MATRIX(*pref, i, type)); VECTOR(sums)[i] = MATRIX(*pref, i, type); } RNG_BEGIN(); for (i = 1; i < nodes; i++) { long int type = (long int) VECTOR(*types)[i]; igraph_real_t sum = VECTOR(sums)[type]; for (j = 0; j < edges_per_step; j++) { long int to; igraph_psumtree_search(&sumtrees[type], &to, RNG_UNIF(0, sum)); igraph_vector_push_back(&edges, i); igraph_vector_push_back(&edges, to); } /* add i */ for (j = 0; j < nocats; j++) { if ( MATRIX(*pref, j, type) < 0) { IGRAPH_ERROR("pref contains negative entries", IGRAPH_EINVAL); } igraph_psumtree_update(&sumtrees[j], i, MATRIX(*pref, j, type)); VECTOR(sums)[j] += MATRIX(*pref, j, type); } } RNG_END(); igraph_i_citing_cited_type_game_free(&str); IGRAPH_FINALLY_CLEAN(1); igraph_create(graph, &edges, nodes, directed); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \ingroup generators * \function igraph_simple_interconnected_islands_game * \brief Generates a random graph made of several interconnected islands, each island being a random graph. * * \param graph Pointer to an uninitialized graph object. * \param islands_n The number of islands in the graph. * \param islands_size The size of islands in the graph. * \param islands_pin The probability to create each possible edge into each island . * \param n_inter The number of edges to create between two islands . * \return Error code: * \c IGRAPH_EINVAL: invalid parameter * \c IGRAPH_ENOMEM: there is not enough * memory for the operation. * * Time complexity: O(|V|+|E|), the * number of vertices plus the number of edges in the graph. * */ int igraph_simple_interconnected_islands_game( igraph_t *graph, igraph_integer_t islands_n, igraph_integer_t islands_size, igraph_real_t islands_pin, igraph_integer_t n_inter) { igraph_vector_t edges = IGRAPH_VECTOR_NULL; igraph_vector_t s = IGRAPH_VECTOR_NULL; int retval = 0; int nbNodes; double maxpossibleedgesPerIsland; double maxedgesPerIsland; int nbEdgesInterIslands; double maxedges; int startIsland = 0; int endIsland = 0; int i, j, is; double myrand, last; if (islands_n < 0) { IGRAPH_ERROR("Invalid number of islands", IGRAPH_EINVAL); } if (islands_size < 0) { IGRAPH_ERROR("Invalid size for islands", IGRAPH_EINVAL); } if (islands_pin < 0 || islands_pin > 1) { IGRAPH_ERROR("Invalid probability for islands", IGRAPH_EINVAL); } if ( (n_inter < 0) || (n_inter > islands_size) ) { IGRAPH_ERROR("Invalid number of inter-islands links", IGRAPH_EINVAL); } // how much memory ? nbNodes = islands_n * islands_size; maxpossibleedgesPerIsland = ((double)islands_size * ((double)islands_size - (double)1)) / (double)2; maxedgesPerIsland = islands_pin * maxpossibleedgesPerIsland; nbEdgesInterIslands = n_inter * (islands_n * (islands_n - 1)) / 2; maxedges = maxedgesPerIsland * islands_n + nbEdgesInterIslands; // debug&tests : printf("total nodes %d, maxedgesperisland %f, maxedgesinterislands %d, maxedges %f\n", nbNodes, maxedgesPerIsland, nbEdgesInterIslands, maxedges); // reserve enough place for all the edges, thanks ! IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_CHECK(igraph_vector_reserve(&edges, (long int) maxedges)); RNG_BEGIN(); // first create all the islands for (is = 1; is <= islands_n; is++) { // for each island // index for start and end of nodes in this island startIsland = islands_size * (is - 1); endIsland = startIsland + islands_size - 1; // debug&tests : printf("start %d,end %d\n", startIsland, endIsland); // create the random numbers to be used (into s) IGRAPH_VECTOR_INIT_FINALLY(&s, 0); IGRAPH_CHECK(igraph_vector_reserve(&s, (long int) maxedgesPerIsland)); last = RNG_GEOM(islands_pin); // debug&tests : printf("last=%f \n", last); while (last < maxpossibleedgesPerIsland) { // maxedgesPerIsland IGRAPH_CHECK(igraph_vector_push_back(&s, last)); myrand = RNG_GEOM(islands_pin); last += myrand; //RNG_GEOM(islands_pin); //printf("myrand=%f , last=%f \n", myrand, last); last += 1; } // change this to edges ! for (i = 0; i < igraph_vector_size(&s); i++) { long int to = (long int) floor((sqrt(8 * VECTOR(s)[i] + 1) + 1) / 2); long int from = (long int) (VECTOR(s)[i] - (((igraph_real_t)to) * (to - 1)) / 2); to += startIsland; from += startIsland; // debug&tests : printf("from %d to %d\n", from, to); igraph_vector_push_back(&edges, from); igraph_vector_push_back(&edges, to); } // clear the memory used for random number for this island igraph_vector_destroy(&s); IGRAPH_FINALLY_CLEAN(1); // create the links with other islands for (i = is + 1; i <= islands_n; i++) { // for each other island (not the previous ones) // debug&tests : printf("link islands %d and %d\n", is, i); for (j = 0; j < n_inter; j++) { // for each link between islands long int from = (long int) RNG_UNIF(startIsland, endIsland); long int to = (long int) RNG_UNIF((i - 1) * islands_size, i * islands_size); //printf("from %d to %d\n", from, to); igraph_vector_push_back(&edges, from); igraph_vector_push_back(&edges, to); } } } RNG_END(); // actually fill the graph object IGRAPH_CHECK(retval = igraph_create(graph, &edges, nbNodes, 0)); // an clear remaining things igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return retval; } /** * \ingroup generators * \function igraph_static_fitness_game * \brief Generates a non-growing random graph with edge probabilities * proportional to node fitness scores. * * This game generates a directed or undirected random graph where the * probability of an edge between vertices i and j depends on the fitness * scores of the two vertices involved. For undirected graphs, each vertex * has a single fitness score. For directed graphs, each vertex has an out- * and an in-fitness, and the probability of an edge from i to j depends on * the out-fitness of vertex i and the in-fitness of vertex j. * * * The generation process goes as follows. We start from N disconnected nodes * (where N is given by the length of the fitness vector). Then we randomly * select two vertices i and j, with probabilities proportional to their * fitnesses. (When the generated graph is directed, i is selected according to * the out-fitnesses and j is selected according to the in-fitnesses). If the * vertices are not connected yet (or if multiple edges are allowed), we * connect them; otherwise we select a new pair. This is repeated until the * desired number of links are created. * * * It can be shown that the \em expected degree of each vertex will be * proportional to its fitness, although the actual, observed degree will not * be. If you need to generate a graph with an exact degree sequence, consider * \ref igraph_degree_sequence_game instead. * * * This model is commonly used to generate static scale-free networks. To * achieve this, you have to draw the fitness scores from the desired power-law * distribution. Alternatively, you may use \ref igraph_static_power_law_game * which generates the fitnesses for you with a given exponent. * * * Reference: Goh K-I, Kahng B, Kim D: Universal behaviour of load distribution * in scale-free networks. Phys Rev Lett 87(27):278701, 2001. * * \param graph Pointer to an uninitialized graph object. * \param fitness_out A numeric vector containing the fitness of each vertex. * For directed graphs, this specifies the out-fitness * of each vertex. * \param fitness_in If \c NULL, the generated graph will be undirected. * If not \c NULL, this argument specifies the in-fitness * of each vertex. * \param no_of_edges The number of edges in the generated graph. * \param loops Whether to allow loop edges in the generated graph. * \param multiple Whether to allow multiple edges in the generated graph. * * \return Error code: * \c IGRAPH_EINVAL: invalid parameter * \c IGRAPH_ENOMEM: there is not enough * memory for the operation. * * Time complexity: O(|V| + |E| log |E|). */ int igraph_static_fitness_game(igraph_t *graph, igraph_integer_t no_of_edges, igraph_vector_t* fitness_out, igraph_vector_t* fitness_in, igraph_bool_t loops, igraph_bool_t multiple) { igraph_vector_t edges = IGRAPH_VECTOR_NULL; igraph_integer_t no_of_nodes; igraph_integer_t outnodes, innodes, nodes; igraph_vector_t cum_fitness_in, cum_fitness_out; igraph_vector_t *p_cum_fitness_in, *p_cum_fitness_out; igraph_real_t x, max_in, max_out; igraph_real_t max_no_of_edges; igraph_bool_t is_directed = (fitness_in != 0); float num_steps; igraph_integer_t step_counter = 0; long int i, from, to, pos; if (fitness_out == 0) { IGRAPH_ERROR("fitness_out must not be null", IGRAPH_EINVAL); } if (no_of_edges < 0) { IGRAPH_ERROR("Invalid number of edges", IGRAPH_EINVAL); } no_of_nodes = (int) igraph_vector_size(fitness_out); if (no_of_nodes == 0) { IGRAPH_CHECK(igraph_empty(graph, 0, is_directed)); return IGRAPH_SUCCESS; } if (is_directed && igraph_vector_size(fitness_in) != no_of_nodes) { IGRAPH_ERROR("fitness_in must have the same size as fitness_out", IGRAPH_EINVAL); } /* Sanity checks for the fitnesses */ if (igraph_vector_min(fitness_out) < 0) { IGRAPH_ERROR("Fitness scores must be non-negative", IGRAPH_EINVAL); } if (fitness_in != 0 && igraph_vector_min(fitness_in) < 0) { IGRAPH_ERROR("Fitness scores must be non-negative", IGRAPH_EINVAL); } /* Avoid getting into an infinite loop when too many edges are requested */ if (!multiple) { if (is_directed) { outnodes = innodes = nodes = 0; for (i = 0; i < no_of_nodes; i++) { if (VECTOR(*fitness_out)[i] != 0) { outnodes++; } if (VECTOR(*fitness_in)[i] != 0) { innodes++; } if (VECTOR(*fitness_out)[i] != 0 && VECTOR(*fitness_in)[i] != 0) { nodes++; } } max_no_of_edges = ((igraph_real_t) outnodes) * innodes - (loops ? 0 : nodes); } else { nodes = 0; for (i = 0; i < no_of_nodes; i++) { if (VECTOR(*fitness_out)[i] != 0) { nodes++; } } max_no_of_edges = loops ? nodes * ((igraph_real_t)nodes + 1) / 2 : nodes * ((igraph_real_t)nodes - 1) / 2; } if (no_of_edges > max_no_of_edges) { IGRAPH_ERROR("Too many edges requested", IGRAPH_EINVAL); } } /* Calculate the cumulative fitness scores */ IGRAPH_VECTOR_INIT_FINALLY(&cum_fitness_out, no_of_nodes); IGRAPH_CHECK(igraph_vector_cumsum(&cum_fitness_out, fitness_out)); max_out = igraph_vector_tail(&cum_fitness_out); p_cum_fitness_out = &cum_fitness_out; if (is_directed) { IGRAPH_VECTOR_INIT_FINALLY(&cum_fitness_in, no_of_nodes); IGRAPH_CHECK(igraph_vector_cumsum(&cum_fitness_in, fitness_in)); max_in = igraph_vector_tail(&cum_fitness_in); p_cum_fitness_in = &cum_fitness_in; } else { max_in = max_out; p_cum_fitness_in = &cum_fitness_out; } RNG_BEGIN(); num_steps = no_of_edges; if (multiple) { /* Generating when multiple edges are allowed */ IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_CHECK(igraph_vector_reserve(&edges, 2 * no_of_edges)); while (no_of_edges > 0) { /* Report progress after every 10000 edges */ if ((step_counter++) % 10000 == 0) { IGRAPH_PROGRESS("Static fitness game", 100.0 * (1 - no_of_edges / num_steps), NULL); IGRAPH_ALLOW_INTERRUPTION(); } x = RNG_UNIF(0, max_out); igraph_vector_binsearch(p_cum_fitness_out, x, &from); x = RNG_UNIF(0, max_in); igraph_vector_binsearch(p_cum_fitness_in, x, &to); /* Skip if loop edge and loops = false */ if (!loops && from == to) { continue; } igraph_vector_push_back(&edges, from); igraph_vector_push_back(&edges, to); no_of_edges--; } /* Create the graph */ IGRAPH_CHECK(igraph_create(graph, &edges, no_of_nodes, is_directed)); /* Clear the edge list */ igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); } else { /* Multiple edges are disallowed */ igraph_adjlist_t al; igraph_vector_int_t* neis; IGRAPH_CHECK(igraph_adjlist_init_empty(&al, no_of_nodes)); IGRAPH_FINALLY(igraph_adjlist_destroy, &al); while (no_of_edges > 0) { /* Report progress after every 10000 edges */ if ((step_counter++) % 10000 == 0) { IGRAPH_PROGRESS("Static fitness game", 100.0 * (1 - no_of_edges / num_steps), NULL); IGRAPH_ALLOW_INTERRUPTION(); } x = RNG_UNIF(0, max_out); igraph_vector_binsearch(p_cum_fitness_out, x, &from); x = RNG_UNIF(0, max_in); igraph_vector_binsearch(p_cum_fitness_in, x, &to); /* Skip if loop edge and loops = false */ if (!loops && from == to) { continue; } /* For undirected graphs, ensure that from < to */ if (!is_directed && from > to) { pos = from; from = to; to = pos; } /* Is there already an edge? If so, try again */ neis = igraph_adjlist_get(&al, from); if (igraph_vector_int_binsearch(neis, to, &pos)) { continue; } /* Insert the edge */ IGRAPH_CHECK(igraph_vector_int_insert(neis, pos, to)); no_of_edges--; } /* Create the graph. We cannot use IGRAPH_ALL here for undirected graphs * because we did not add edges in both directions in the adjacency list. * We will use igraph_to_undirected in an extra step. */ IGRAPH_CHECK(igraph_adjlist(graph, &al, IGRAPH_OUT, 1)); if (!is_directed) { IGRAPH_CHECK(igraph_to_undirected(graph, IGRAPH_TO_UNDIRECTED_EACH, 0)); } /* Clear the adjacency list */ igraph_adjlist_destroy(&al); IGRAPH_FINALLY_CLEAN(1); } RNG_END(); IGRAPH_PROGRESS("Static fitness game", 100.0, NULL); /* Cleanup before we create the graph */ if (is_directed) { igraph_vector_destroy(&cum_fitness_in); IGRAPH_FINALLY_CLEAN(1); } igraph_vector_destroy(&cum_fitness_out); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } /** * \ingroup generators * \function igraph_static_power_law_game * \brief Generates a non-growing random graph with expected power-law degree distributions. * * This game generates a directed or undirected random graph where the * degrees of vertices follow power-law distributions with prescribed * exponents. For directed graphs, the exponents of the in- and out-degree * distributions may be specified separately. * * * The game simply uses \ref igraph_static_fitness_game with appropriately * constructed fitness vectors. In particular, the fitness of vertex i * is i-alpha, where alpha = 1/(gamma-1) * and gamma is the exponent given in the arguments. * * * To remove correlations between in- and out-degrees in case of directed * graphs, the in-fitness vector will be shuffled after it has been set up * and before \ref igraph_static_fitness_game is called. * * * Note that significant finite size effects may be observed for exponents * smaller than 3 in the original formulation of the game. This function * provides an argument that lets you remove the finite size effects by * assuming that the fitness of vertex i is * (i+i0-1)-alpha, * where i0 is a constant chosen appropriately to ensure that the maximum * degree is less than the square root of the number of edges times the * average degree; see the paper of Chung and Lu, and Cho et al for more * details. * * * References: * * * Goh K-I, Kahng B, Kim D: Universal behaviour of load distribution * in scale-free networks. Phys Rev Lett 87(27):278701, 2001. * * * Chung F and Lu L: Connected components in a random graph with given * degree sequences. Annals of Combinatorics 6, 125-145, 2002. * * * Cho YS, Kim JS, Park J, Kahng B, Kim D: Percolation transitions in * scale-free networks under the Achlioptas process. Phys Rev Lett * 103:135702, 2009. * * \param graph Pointer to an uninitialized graph object. * \param no_of_nodes The number of nodes in the generated graph. * \param no_of_edges The number of edges in the generated graph. * \param exponent_out The power law exponent of the degree distribution. * For directed graphs, this specifies the exponent of the * out-degree distribution. It must be greater than or * equal to 2. If you pass \c IGRAPH_INFINITY here, you * will get back an Erdos-Renyi random network. * \param exponent_in If negative, the generated graph will be undirected. * If greater than or equal to 2, this argument specifies * the exponent of the in-degree distribution. If * non-negative but less than 2, an error will be * generated. * \param loops Whether to allow loop edges in the generated graph. * \param multiple Whether to allow multiple edges in the generated graph. * \param finite_size_correction Whether to use the proposed finite size * correction of Cho et al. * * \return Error code: * \c IGRAPH_EINVAL: invalid parameter * \c IGRAPH_ENOMEM: there is not enough * memory for the operation. * * Time complexity: O(|V| + |E| log |E|). */ int igraph_static_power_law_game(igraph_t *graph, igraph_integer_t no_of_nodes, igraph_integer_t no_of_edges, igraph_real_t exponent_out, igraph_real_t exponent_in, igraph_bool_t loops, igraph_bool_t multiple, igraph_bool_t finite_size_correction) { igraph_vector_t fitness_out, fitness_in; igraph_real_t alpha_out = 0.0, alpha_in = 0.0; long int i; igraph_real_t j; if (no_of_nodes < 0) { IGRAPH_ERROR("Invalid number of nodes", IGRAPH_EINVAL); } /* Calculate alpha_out */ if (exponent_out < 2) { IGRAPH_ERROR("out-degree exponent must be >= 2", IGRAPH_EINVAL); } else if (igraph_finite(exponent_out)) { alpha_out = -1.0 / (exponent_out - 1); } else { alpha_out = 0.0; } /* Construct the out-fitnesses */ IGRAPH_VECTOR_INIT_FINALLY(&fitness_out, no_of_nodes); j = no_of_nodes; if (finite_size_correction && alpha_out < -0.5) { /* See the Cho et al paper, first page first column + footnote 7 */ j += pow(no_of_nodes, 1 + 0.5 / alpha_out) * pow(10 * sqrt(2) * (1 + alpha_out), -1.0 / alpha_out) - 1; } if (j < no_of_nodes) { j = no_of_nodes; } for (i = 0; i < no_of_nodes; i++, j--) { VECTOR(fitness_out)[i] = pow(j, alpha_out); } if (exponent_in >= 0) { if (exponent_in < 2) { IGRAPH_ERROR("in-degree exponent must be >= 2; use negative numbers " "for undirected graphs", IGRAPH_EINVAL); } else if (igraph_finite(exponent_in)) { alpha_in = -1.0 / (exponent_in - 1); } else { alpha_in = 0.0; } IGRAPH_VECTOR_INIT_FINALLY(&fitness_in, no_of_nodes); j = no_of_nodes; if (finite_size_correction && alpha_in < -0.5) { /* See the Cho et al paper, first page first column + footnote 7 */ j += pow(no_of_nodes, 1 + 0.5 / alpha_in) * pow(10 * sqrt(2) * (1 + alpha_in), -1.0 / alpha_in) - 1; } if (j < no_of_nodes) { j = no_of_nodes; } for (i = 0; i < no_of_nodes; i++, j--) { VECTOR(fitness_in)[i] = pow(j, alpha_in); } IGRAPH_CHECK(igraph_vector_shuffle(&fitness_in)); IGRAPH_CHECK(igraph_static_fitness_game(graph, no_of_edges, &fitness_out, &fitness_in, loops, multiple)); igraph_vector_destroy(&fitness_in); IGRAPH_FINALLY_CLEAN(1); } else { IGRAPH_CHECK(igraph_static_fitness_game(graph, no_of_edges, &fitness_out, 0, loops, multiple)); } igraph_vector_destroy(&fitness_out); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } /** * \ingroup generators * \function igraph_k_regular_game * \brief Generates a random graph where each vertex has the same degree. * * This game generates a directed or undirected random graph where the * degrees of vertices are equal to a predefined constant k. For undirected * graphs, at least one of k and the number of vertices must be even. * * * The game simply uses \ref igraph_degree_sequence_game with appropriately * constructed degree sequences. * * \param graph Pointer to an uninitialized graph object. * \param no_of_nodes The number of nodes in the generated graph. * \param k The degree of each vertex in an undirected graph, or * the out-degree and in-degree of each vertex in a * directed graph. * \param directed Whether the generated graph will be directed. * \param multiple Whether to allow multiple edges in the generated graph. * * \return Error code: * \c IGRAPH_EINVAL: invalid parameter; e.g., negative number of nodes, * or odd number of nodes and odd k for undirected * graphs. * \c IGRAPH_ENOMEM: there is not enough memory for the operation. * * Time complexity: O(|V|+|E|) if \c multiple is true, otherwise not known. */ int igraph_k_regular_game(igraph_t *graph, igraph_integer_t no_of_nodes, igraph_integer_t k, igraph_bool_t directed, igraph_bool_t multiple) { igraph_vector_t degseq; igraph_degseq_t mode = multiple ? IGRAPH_DEGSEQ_SIMPLE : IGRAPH_DEGSEQ_SIMPLE_NO_MULTIPLE; /* Note to self: we are not using IGRAPH_DEGSEQ_VL when multiple = false * because the VL method is not really good at generating k-regular graphs. * Actually, that's why we have added SIMPLE_NO_MULTIPLE. */ if (no_of_nodes < 0) { IGRAPH_ERROR("number of nodes must be non-negative", IGRAPH_EINVAL); } if (k < 0) { IGRAPH_ERROR("degree must be non-negative", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(°seq, no_of_nodes); igraph_vector_fill(°seq, k); IGRAPH_CHECK(igraph_degree_sequence_game(graph, °seq, directed ? °seq : 0, mode)); igraph_vector_destroy(°seq); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } /** * \function igraph_correlated_game * Generate pairs of correlated random graphs * * Sample a new graph by perturbing the adjacency matrix of a * given graph and shuffling its vertices. * * \param old_graph The original graph. * \param new_graph The new graph will be stored here. * \param corr A scalar in the unit interval, the target Pearson * correlation between the adjacency matrices of the original the * generated graph (the adjacency matrix being used as a vector). * \param p A numeric scalar, the probability of an edge between two * vertices, it must in the open (0,1) interval. * \param permutation A permutation to apply to the vertices of the * generated graph. It can also be a null pointer, in which case * the vertices will not be permuted. * \return Error code * * \sa \ref igraph_correlated_pair_game() for generating a pair * of correlated random graphs in one go. */ int igraph_correlated_game(const igraph_t *old_graph, igraph_t *new_graph, igraph_real_t corr, igraph_real_t p, const igraph_vector_t *permutation) { int no_of_nodes = igraph_vcount(old_graph); int no_of_edges = igraph_ecount(old_graph); igraph_bool_t directed = igraph_is_directed(old_graph); igraph_real_t no_of_all = directed ? no_of_nodes * (no_of_nodes - 1) : no_of_nodes * (no_of_nodes - 1) / 2; igraph_real_t no_of_missing = no_of_all - no_of_edges; igraph_real_t q = p + corr * (1 - p); igraph_real_t p_del = 1 - q; igraph_real_t p_add = ((1 - q) * (p / (1 - p))); igraph_vector_t add, delete, edges, newedges; igraph_real_t last; int p_e = 0, p_a = 0, p_d = 0, no_add, no_del; igraph_real_t inf = IGRAPH_INFINITY; igraph_real_t next_e, next_a, next_d; int i; if (corr < -1 || corr > 1) { IGRAPH_ERROR("Correlation must be in [-1,1] in correlated " "Erdos-Renyi game", IGRAPH_EINVAL); } if (p <= 0 || p >= 1) { IGRAPH_ERROR("Edge probability must be in (0,1) in correlated " "Erdos-Renyi game", IGRAPH_EINVAL); } if (permutation) { if (igraph_vector_size(permutation) != no_of_nodes) { IGRAPH_ERROR("Invalid permutation length in correlated Erdos-Renyi game", IGRAPH_EINVAL); } } /* Special cases */ if (corr == 0) { return igraph_erdos_renyi_game(new_graph, IGRAPH_ERDOS_RENYI_GNP, no_of_nodes, p, directed, IGRAPH_NO_LOOPS); } if (corr == 1) { /* We don't copy, because we don't need the attributes.... */ IGRAPH_VECTOR_INIT_FINALLY(&edges, no_of_edges * 2); IGRAPH_CHECK(igraph_get_edgelist(old_graph, &edges, /* bycol= */ 0)); if (permutation) { int newec = igraph_vector_size(&edges); for (i = 0; i < newec; i++) { int tmp = VECTOR(edges)[i]; VECTOR(edges)[i] = VECTOR(*permutation)[tmp]; } } IGRAPH_CHECK(igraph_create(new_graph, &edges, no_of_nodes, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } IGRAPH_VECTOR_INIT_FINALLY(&newedges, 0); IGRAPH_VECTOR_INIT_FINALLY(&add, 0); IGRAPH_VECTOR_INIT_FINALLY(&delete, 0); IGRAPH_VECTOR_INIT_FINALLY(&edges, no_of_edges * 2); IGRAPH_CHECK(igraph_get_edgelist(old_graph, &edges, /* bycol= */ 0)); RNG_BEGIN(); if (p_del > 0) { last = RNG_GEOM(p_del); while (last < no_of_edges) { IGRAPH_CHECK(igraph_vector_push_back(&delete, last)); last += RNG_GEOM(p_del); last += 1; } } no_del = igraph_vector_size(&delete); if (p_add > 0) { last = RNG_GEOM(p_add); while (last < no_of_missing) { IGRAPH_CHECK(igraph_vector_push_back(&add, last)); last += RNG_GEOM(p_add); last += 1; } } no_add = igraph_vector_size(&add); RNG_END(); IGRAPH_CHECK(igraph_get_edgelist(old_graph, &edges, /* bycol= */ 0)); /* Now we are merging the original edges, the edges that are removed, and the new edges. We have the following pointers: - p_a: the next edge to add - p_d: the next edge to delete - p_e: the next original edge - next_e: the code of the next edge in 'edges' - next_a: the code of the next edge to add - next_d: the code of the next edge to delete */ #define D_CODE(f,t) (((t)==no_of_nodes-1 ? f : t) * no_of_nodes + (f)) #define U_CODE(f,t) ((t) * ((t)-1) / 2 + (f)) #define CODE(f,t) (directed ? D_CODE(f,t) : U_CODE(f,t)) #define CODEE() (CODE(VECTOR(edges)[2*p_e], VECTOR(edges)[2*p_e+1])) /* First we (re)code the edges to delete */ for (i = 0; i < no_del; i++) { int td = VECTOR(delete)[i]; int from = VECTOR(edges)[2 * td]; int to = VECTOR(edges)[2 * td + 1]; VECTOR(delete)[i] = CODE(from, to); } IGRAPH_CHECK(igraph_vector_reserve(&newedges, (no_of_edges - no_del + no_add) * 2)); /* Now we can do the merge. Additional edges are tricky, because the code must be shifted by the edges in the original graph. */ #define UPD_E() \ { if (p_e < no_of_edges) { next_e=CODEE(); } else { next_e = inf; } } #define UPD_A() \ { if (p_a < no_add) { \ next_a = VECTOR(add)[p_a] + p_e; } else { next_a = inf; } } #define UPD_D() \ { if (p_d < no_del) { \ next_d = VECTOR(delete)[p_d]; } else { next_d = inf; } } UPD_E(); UPD_A(); UPD_D(); while (next_e != inf || next_a != inf || next_d != inf) { if (next_e <= next_a && next_e < next_d) { /* keep an edge */ IGRAPH_CHECK(igraph_vector_push_back(&newedges, VECTOR(edges)[2 * p_e])); IGRAPH_CHECK(igraph_vector_push_back(&newedges, VECTOR(edges)[2 * p_e + 1])); p_e ++; UPD_E(); UPD_A() } else if (next_e <= next_a && next_e == next_d) { /* delete an edge */ p_e ++; UPD_E(); UPD_A(); p_d++; UPD_D(); } else { /* add an edge */ int to, from; if (directed) { to = (int) floor(next_a / no_of_nodes); from = (int) (next_a - ((igraph_real_t)to) * no_of_nodes); if (from == to) { to = no_of_nodes - 1; } } else { to = (int) floor((sqrt(8 * next_a + 1) + 1) / 2); from = (int) (next_a - (((igraph_real_t)to) * (to - 1)) / 2); } IGRAPH_CHECK(igraph_vector_push_back(&newedges, from)); IGRAPH_CHECK(igraph_vector_push_back(&newedges, to)); p_a++; UPD_A(); } } igraph_vector_destroy(&edges); igraph_vector_destroy(&add); igraph_vector_destroy(&delete); IGRAPH_FINALLY_CLEAN(3); if (permutation) { int newec = igraph_vector_size(&newedges); for (i = 0; i < newec; i++) { int tmp = VECTOR(newedges)[i]; VECTOR(newedges)[i] = VECTOR(*permutation)[tmp]; } } IGRAPH_CHECK(igraph_create(new_graph, &newedges, no_of_nodes, directed)); igraph_vector_destroy(&newedges); IGRAPH_FINALLY_CLEAN(1); return 0; } #undef D_CODE #undef U_CODE #undef CODE #undef CODEE #undef UPD_E #undef UPD_A #undef UPD_D /** * \function igraph_correlated_pair_game * Generate pairs of correlated random graphs * * Sample two random graphs, with given correlation. * * \param graph1 The first graph will be stored here. * \param graph2 The second graph will be stored here. * \param n The number of vertices in both graphs. * \param corr A scalar in the unit interval, the target Pearson * correlation between the adjacency matrices of the original the * generated graph (the adjacency matrix being used as a vector). * \param p A numeric scalar, the probability of an edge between two * vertices, it must in the open (0,1) interval. * \param directed Whether to generate directed graphs. * \param permutation A permutation to apply to the vertices of the * second graph. It can also be a null pointer, in which case * the vertices will not be permuted. * \return Error code * * \sa \ref igraph_correlated_game() for generating a correlated pair * to a given graph. */ int igraph_correlated_pair_game(igraph_t *graph1, igraph_t *graph2, int n, igraph_real_t corr, igraph_real_t p, igraph_bool_t directed, const igraph_vector_t *permutation) { IGRAPH_CHECK(igraph_erdos_renyi_game(graph1, IGRAPH_ERDOS_RENYI_GNP, n, p, directed, IGRAPH_NO_LOOPS)); IGRAPH_CHECK(igraph_correlated_game(graph1, graph2, corr, p, permutation)); return 0; } /* Uniform sampling of labelled trees (igraph_tree_game) */ /* The following implementation uniformly samples Prufer trees and converts * them to trees. */ static int igraph_i_tree_game_prufer(igraph_t *graph, igraph_integer_t n, igraph_bool_t directed) { igraph_vector_int_t prufer; long i; if (directed) { IGRAPH_ERROR("The Prufer method for random tree generation does not support directed trees", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_vector_int_init(&prufer, n - 2)); IGRAPH_FINALLY(igraph_vector_int_destroy, &prufer); RNG_BEGIN(); for (i = 0; i < n - 2; ++i) { VECTOR(prufer)[i] = RNG_INTEGER(0, n - 1); } RNG_END(); IGRAPH_CHECK(igraph_from_prufer(graph, &prufer)); igraph_vector_int_destroy(&prufer); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } /* The following implementation is based on loop-erased random walks and Wilson's algorithm * for uniformly sampling spanning trees. We effectively sample spanning trees of the complete * graph. */ /* swap two elements of a vector_int */ #define SWAP_INT_ELEM(vec, i, j) \ { \ igraph_integer_t temp; \ temp = VECTOR(vec)[i]; \ VECTOR(vec)[i] = VECTOR(vec)[j]; \ VECTOR(vec)[j] = temp; \ } static int igraph_i_tree_game_loop_erased_random_walk(igraph_t *graph, igraph_integer_t n, igraph_bool_t directed) { igraph_vector_t edges; igraph_vector_int_t vertices; igraph_vector_bool_t visited; long i, j, k; IGRAPH_VECTOR_INIT_FINALLY(&edges, 2 * (n - 1)); IGRAPH_CHECK(igraph_vector_bool_init(&visited, n)); IGRAPH_FINALLY(igraph_vector_bool_destroy, &visited); /* The vertices vector contains visited vertices between 0..k-1, unvisited ones between k..n-1. */ IGRAPH_CHECK(igraph_vector_int_init_seq(&vertices, 0, n - 1)); IGRAPH_FINALLY(igraph_vector_int_destroy, &vertices); RNG_BEGIN(); /* A simple implementation could be as below. This is for illustration only. * The actually implemented algorithm avoids unnecessary walking on the already visited * portion of the vertex set. */ /* // pick starting point for the walk i = RNG_INTEGER(0, n-1); VECTOR(visited)[i] = 1; k=1; while (k < n) { // pick next vertex in the walk j = RNG_INTEGER(0, n-1); // if it has not been visited before, connect to the previous vertex in the sequence if (! VECTOR(visited)[j]) { VECTOR(edges)[2*k - 2] = i; VECTOR(edges)[2*k - 1] = j; VECTOR(visited)[j] = 1; k++; } i=j; } */ i = RNG_INTEGER(0, n - 1); VECTOR(visited)[i] = 1; SWAP_INT_ELEM(vertices, 0, i); for (k = 1; k < n; ++k) { j = RNG_INTEGER(0, n - 1); if (VECTOR(visited)[VECTOR(vertices)[j]]) { i = VECTOR(vertices)[j]; j = RNG_INTEGER(k, n - 1); } VECTOR(visited)[VECTOR(vertices)[j]] = 1; SWAP_INT_ELEM(vertices, k, j); VECTOR(edges)[2 * k - 2] = i; i = VECTOR(vertices)[k]; VECTOR(edges)[2 * k - 1] = i; } RNG_END(); IGRAPH_CHECK(igraph_create(graph, &edges, n, directed)); igraph_vector_int_destroy(&vertices); igraph_vector_bool_destroy(&visited); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(3); return IGRAPH_SUCCESS; } #undef SWAP_INT_ELEM /** * \ingroup generators * \function igraph_tree_game * \brief Generates a random tree with the given number of nodes * * This function samples uniformly from the set of labelled trees, * i.e. it can generate each labelled tree with the same probability. * * \param graph Pointer to an uninitialized graph object. * \param n The number of nodes in the tree. * \param directed Whether to create a directed tree. The edges are oriented away from the root. * \param method The algorithm to use to generate the tree. Possible values: * \clist * \cli IGRAPH_RANDOM_TREE_PRUFER * This algorithm samples Prüfer sequences unformly, then converts them to trees. * Directed trees are not currently supported. * \cli IGRAPH_RANDOM_LERW * This algorithm effectively performs a loop-erased random walk on the complete graph * to uniformly sample its spanning trees (Wilson's algorithm). * \endclist * \return Error code: * \c IGRAPH_ENOMEM: there is not enough * memory to perform the operation. * \c IGRAPH_EINVAL: invalid tree size * * \sa \ref igraph_from_prufer() * */ int igraph_tree_game(igraph_t *graph, igraph_integer_t n, igraph_bool_t directed, igraph_random_tree_t method) { if (n < 2) { IGRAPH_CHECK(igraph_empty(graph, n, directed)); return IGRAPH_SUCCESS; } switch (method) { case IGRAPH_RANDOM_TREE_PRUFER: return igraph_i_tree_game_prufer(graph, n, directed); case IGRAPH_RANDOM_TREE_LERW: return igraph_i_tree_game_loop_erased_random_walk(graph, n, directed); default: IGRAPH_ERROR("Invalid method for random tree construction", IGRAPH_EINVAL); } } python-igraph-0.8.0/vendor/source/igraph/src/foreign-gml-parser.y0000644000076500000240000001641513524616145025306 0ustar tamasstaff00000000000000/* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ %{ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include #include "igraph_error.h" #include "igraph_memory.h" #include "config.h" #include "igraph_hacks_internal.h" #include "igraph_math.h" #include "igraph_gml_tree.h" #include "foreign-gml-header.h" #include "foreign-gml-parser.h" #define yyscan_t void* int igraph_gml_yylex(YYSTYPE* lvalp, YYLTYPE* llocp, void *scanner); int igraph_gml_yyerror(YYLTYPE* locp, igraph_i_gml_parsedata_t *context, const char *s); char *igraph_gml_yyget_text (yyscan_t yyscanner ); int igraph_gml_yyget_leng (yyscan_t yyscanner ); void igraph_i_gml_get_keyword(char *s, int len, void *res); void igraph_i_gml_get_string(char *s, int len, void *res); double igraph_i_gml_get_real(char *s, int len); igraph_gml_tree_t *igraph_i_gml_make_numeric(char* s, int len, double value); igraph_gml_tree_t *igraph_i_gml_make_numeric2(char* s, int len, char *v, int vlen); igraph_gml_tree_t *igraph_i_gml_make_string(char* s, int len, char *value, int valuelen); igraph_gml_tree_t *igraph_i_gml_make_list(char* s, int len, igraph_gml_tree_t *list); igraph_gml_tree_t *igraph_i_gml_merge(igraph_gml_tree_t *t1, igraph_gml_tree_t* t2); #define scanner context->scanner #define USE(x) /*(x)*/ %} %pure-parser %output="y.tab.c" %name-prefix="igraph_gml_yy" %defines %locations %error-verbose %parse-param { igraph_i_gml_parsedata_t* context } %lex-param { void *scanner } %union { struct { char *s; int len; } str; void *tree; double real; } %type list; %type keyvalue; %type key; %type num; %type string; %token STRING %token NUM %token KEYWORD %token LISTOPEN %token LISTCLOSE %token EOFF %token ERROR %destructor { igraph_Free($$.s); } string key KEYWORD; %destructor { igraph_gml_tree_destroy($$); } list keyvalue; %% input: list { context->tree=$1; } | list EOFF { context->tree=$1; } ; list: keyvalue { $$=$1; } | list keyvalue { $$=igraph_i_gml_merge($1, $2); }; keyvalue: key num { $$=igraph_i_gml_make_numeric($1.s, $1.len, $2); } | key string { $$=igraph_i_gml_make_string($1.s, $1.len, $2.s, $2.len); } | key LISTOPEN list LISTCLOSE { $$=igraph_i_gml_make_list($1.s, $1.len, $3); } | key key { $$=igraph_i_gml_make_numeric2($1.s, $1.len, $2.s, $2.len); } ; key: KEYWORD { igraph_i_gml_get_keyword(igraph_gml_yyget_text(scanner), igraph_gml_yyget_leng(scanner), &$$); USE($1) }; num : NUM { $$=igraph_i_gml_get_real(igraph_gml_yyget_text(scanner), igraph_gml_yyget_leng(scanner)); }; string: STRING { igraph_i_gml_get_string(igraph_gml_yyget_text(scanner), igraph_gml_yyget_leng(scanner), &$$); }; %% int igraph_gml_yyerror(YYLTYPE* locp, igraph_i_gml_parsedata_t *context, const char *s) { snprintf(context->errmsg, sizeof(context->errmsg)/sizeof(char)-1, "Parse error in GML file, line %i (%s)", locp->first_line, s); return 0; } void igraph_i_gml_get_keyword(char *s, int len, void *res) { struct { char *s; int len; } *p=res; p->s=igraph_Calloc(len+1, char); if (!p->s) { igraph_error("Cannot read GML file", __FILE__, __LINE__, IGRAPH_PARSEERROR); } memcpy(p->s, s, sizeof(char)*len); p->s[len]='\0'; p->len=len; } void igraph_i_gml_get_string(char *s, int len, void *res) { struct { char *s; int len; } *p=res; p->s=igraph_Calloc(len-1, char); if (!p->s) { igraph_error("Cannot read GML file", __FILE__, __LINE__, IGRAPH_PARSEERROR); } memcpy(p->s, s+1, sizeof(char)*(len-2)); p->s[len-2]='\0'; p->len=len-2; } double igraph_i_gml_get_real(char *s, int len) { igraph_real_t num; char tmp=s[len]; s[len]='\0'; sscanf(s, "%lf", &num); s[len]=tmp; return num; } igraph_gml_tree_t *igraph_i_gml_make_numeric(char* s, int len, double value) { igraph_gml_tree_t *t=igraph_Calloc(1, igraph_gml_tree_t); if (!t) { igraph_error("Cannot build GML tree", __FILE__, __LINE__, IGRAPH_ENOMEM); return 0; } if (floor(value)==value) { igraph_gml_tree_init_integer(t, s, len, value); } else { igraph_gml_tree_init_real(t, s, len, value); } return t; } igraph_gml_tree_t *igraph_i_gml_make_numeric2(char* s, int len, char *v, int vlen) { igraph_gml_tree_t *t=igraph_Calloc(1, igraph_gml_tree_t); char tmp=v[vlen]; igraph_real_t value=0; if (!t) { igraph_error("Cannot build GML tree", __FILE__, __LINE__, IGRAPH_ENOMEM); return 0; } v[vlen]='\0'; if (strcasecmp(v, "inf")) { value=IGRAPH_INFINITY; } else if (strcasecmp(v, "nan")) { value=IGRAPH_NAN; } else { igraph_error("Parse error", __FILE__, __LINE__, IGRAPH_PARSEERROR); } v[vlen]=tmp; igraph_gml_tree_init_real(t, s, len, value); return t; } igraph_gml_tree_t *igraph_i_gml_make_string(char* s, int len, char *value, int valuelen) { igraph_gml_tree_t *t=igraph_Calloc(1, igraph_gml_tree_t); if (!t) { igraph_error("Cannot build GML tree", __FILE__, __LINE__, IGRAPH_ENOMEM); return 0; } igraph_gml_tree_init_string(t, s, len, value, valuelen); return t; } igraph_gml_tree_t *igraph_i_gml_make_list(char* s, int len, igraph_gml_tree_t *list) { igraph_gml_tree_t *t=igraph_Calloc(1, igraph_gml_tree_t); if (!t) { igraph_error("Cannot build GML tree", __FILE__, __LINE__, IGRAPH_ENOMEM); return 0; } igraph_gml_tree_init_tree(t, s, len, list); return t; } igraph_gml_tree_t *igraph_i_gml_merge(igraph_gml_tree_t *t1, igraph_gml_tree_t* t2) { igraph_gml_tree_mergedest(t1, t2); igraph_Free(t2); return t1; } python-igraph-0.8.0/vendor/source/igraph/src/maximal_cliques.c0000644000076500000240000004344013614300625024724 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2013 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_cliques.h" #include "igraph_constants.h" #include "igraph_interface.h" #include "igraph_community.h" #include "igraph_adjlist.h" #include "igraph_interrupt_internal.h" #include "igraph_memory.h" #include "igraph_progress.h" #include "igraph_math.h" #define CONCAT2x(a,b) a ## b #define CONCAT2(a,b) CONCAT2x(a,b) #define FUNCTION(name,sfx) CONCAT2(name,sfx) int igraph_i_maximal_cliques_reorder_adjlists( const igraph_vector_int_t *PX, int PS, int PE, int XS, int XE, const igraph_vector_int_t *pos, igraph_adjlist_t *adjlist); int igraph_i_maximal_cliques_select_pivot(const igraph_vector_int_t *PX, int PS, int PE, int XS, int XE, const igraph_vector_int_t *pos, const igraph_adjlist_t *adjlist, int *pivot, igraph_vector_int_t *nextv, int oldPS, int oldXE); int igraph_i_maximal_cliques_down(igraph_vector_int_t *PX, int PS, int PE, int XS, int XE, igraph_vector_int_t *pos, igraph_adjlist_t *adjlist, int mynextv, igraph_vector_int_t *R, int *newPS, int *newXE); int igraph_i_maximal_cliques_PX(igraph_vector_int_t *PX, int PS, int *PE, int *XS, int XE, igraph_vector_int_t *pos, igraph_adjlist_t *adjlist, int v, igraph_vector_int_t *H); int igraph_i_maximal_cliques_up(igraph_vector_int_t *PX, int PS, int PE, int XS, int XE, igraph_vector_int_t *pos, igraph_adjlist_t *adjlist, igraph_vector_int_t *R, igraph_vector_int_t *H); #define PRINT_PX do { \ int j; \ printf("PX="); \ for (j=0; j= sPS && avneipos <= sPE) { if (pp != avnei) { int tmp = *avnei; *avnei = *pp; *pp = tmp; } pp++; } } } return 0; } int igraph_i_maximal_cliques_select_pivot(const igraph_vector_int_t *PX, int PS, int PE, int XS, int XE, const igraph_vector_int_t *pos, const igraph_adjlist_t *adjlist, int *pivot, igraph_vector_int_t *nextv, int oldPS, int oldXE) { igraph_vector_int_t *pivotvectneis; int i, pivotvectlen, j, usize = -1; int soldPS = oldPS + 1, soldXE = oldXE + 1, sPS = PS + 1, sPE = PE + 1; /* Choose a pivotvect, and bring up P vertices at the same time */ for (i = PS; i <= XE; i++) { int av = VECTOR(*PX)[i]; igraph_vector_int_t *avneis = igraph_adjlist_get(adjlist, av); int *avp = VECTOR(*avneis); int avlen = igraph_vector_int_size(avneis); int *ave = avp + avlen; int *avnei = avp, *pp = avp; for (; avnei < ave; avnei++) { int avneipos = VECTOR(*pos)[(int)(*avnei)]; if (avneipos < soldPS || avneipos > soldXE) { break; } if (avneipos >= sPS && avneipos <= sPE) { if (pp != avnei) { int tmp = *avnei; *avnei = *pp; *pp = tmp; } pp++; } } if ((j = pp - avp) > usize) { *pivot = av; usize = j; } } igraph_vector_int_push_back(nextv, -1); pivotvectneis = igraph_adjlist_get(adjlist, *pivot); pivotvectlen = igraph_vector_int_size(pivotvectneis); for (j = PS; j <= PE; j++) { int vcand = VECTOR(*PX)[j]; igraph_bool_t nei = 0; int k = 0; for (k = 0; k < pivotvectlen; k++) { int unv = VECTOR(*pivotvectneis)[k]; int unvpos = VECTOR(*pos)[unv]; if (unvpos < sPS || unvpos > sPE) { break; } if (unv == vcand) { nei = 1; break; } } if (!nei) { igraph_vector_int_push_back(nextv, vcand); } } return 0; } #define SWAP(p1,p2) do { \ int v1=VECTOR(*PX)[p1]; \ int v2=VECTOR(*PX)[p2]; \ VECTOR(*PX)[p1] = v2; \ VECTOR(*PX)[p2] = v1; \ VECTOR(*pos)[v1] = (p2)+1; \ VECTOR(*pos)[v2] = (p1)+1; \ } while (0) int igraph_i_maximal_cliques_down(igraph_vector_int_t *PX, int PS, int PE, int XS, int XE, igraph_vector_int_t *pos, igraph_adjlist_t *adjlist, int mynextv, igraph_vector_int_t *R, int *newPS, int *newXE) { igraph_vector_int_t *vneis = igraph_adjlist_get(adjlist, mynextv); int j, vneislen = igraph_vector_int_size(vneis); int sPS = PS + 1, sPE = PE + 1, sXS = XS + 1, sXE = XE + 1; *newPS = PE + 1; *newXE = XS - 1; for (j = 0; j < vneislen; j++) { int vnei = VECTOR(*vneis)[j]; int vneipos = VECTOR(*pos)[vnei]; if (vneipos >= sPS && vneipos <= sPE) { (*newPS)--; SWAP(vneipos - 1, *newPS); } else if (vneipos >= sXS && vneipos <= sXE) { (*newXE)++; SWAP(vneipos - 1, *newXE); } } igraph_vector_int_push_back(R, mynextv); return 0; } #undef SWAP int igraph_i_maximal_cliques_PX(igraph_vector_int_t *PX, int PS, int *PE, int *XS, int XE, igraph_vector_int_t *pos, igraph_adjlist_t *adjlist, int v, igraph_vector_int_t *H) { int vpos = VECTOR(*pos)[v] - 1; int tmp = VECTOR(*PX)[*PE]; VECTOR(*PX)[vpos] = tmp; VECTOR(*PX)[*PE] = v; VECTOR(*pos)[v] = (*PE) + 1; VECTOR(*pos)[tmp] = vpos + 1; (*PE)--; (*XS)--; igraph_vector_int_push_back(H, v); return 0; } int igraph_i_maximal_cliques_up(igraph_vector_int_t *PX, int PS, int PE, int XS, int XE, igraph_vector_int_t *pos, igraph_adjlist_t *adjlist, igraph_vector_int_t *R, igraph_vector_int_t *H) { int vv; igraph_vector_int_pop_back(R); while ((vv = igraph_vector_int_pop_back(H)) != -1) { int vvpos = VECTOR(*pos)[vv]; int tmp = VECTOR(*PX)[XS]; VECTOR(*PX)[XS] = vv; VECTOR(*PX)[vvpos - 1] = tmp; VECTOR(*pos)[vv] = XS + 1; VECTOR(*pos)[tmp] = vvpos; PE++; XS++; } return 0; } /** * \function igraph_maximal_cliques * \brief Find all maximal cliques of a graph * * * A maximal clique is a clique which can't be extended any more by * adding a new vertex to it. * * * If you are only interested in the size of the largest clique in the * graph, use \ref igraph_clique_number() instead. * * * The current implementation uses a modified Bron-Kerbosch * algorithm to find the maximal cliques, see: David Eppstein, * Maarten Löffler, Darren Strash: Listing All Maximal Cliques in * Sparse Graphs in Near-Optimal Time. Algorithms and Computation, * Lecture Notes in Computer Science Volume 6506, 2010, pp 403-414. * * The implementation of this function changed between * igraph 0.5 and 0.6 and also between 0.6 and 0.7, so the order of * the cliques and the order of vertices within the cliques will * almost surely be different between these three versions. * * \param graph The input graph. * \param res Pointer to a pointer vector, the result will be stored * here, ie. \c res will contain pointers to \c igraph_vector_t * objects which contain the indices of vertices involved in a clique. * The pointer vector will be resized if needed but note that the * objects in the pointer vector will not be freed. Note that vertices * of a clique may be returned in arbitrary order. * \param min_size Integer giving the minimum size of the cliques to be * returned. If negative or zero, no lower bound will be used. * \param max_size Integer giving the maximum size of the cliques to be * returned. If negative or zero, no upper bound will be used. * \return Error code. * * \sa \ref igraph_maximal_independent_vertex_sets(), \ref * igraph_clique_number() * * Time complexity: O(d(n-d)3^(d/3)) worst case, d is the degeneracy * of the graph, this is typically small for sparse graphs. * * \example examples/simple/igraph_maximal_cliques.c */ int igraph_maximal_cliques(const igraph_t *graph, igraph_vector_ptr_t *res, igraph_integer_t min_size, igraph_integer_t max_size); #define IGRAPH_MC_ORIG #include "maximal_cliques_template.h" #undef IGRAPH_MC_ORIG /** * \function igraph_maximal_cliques_count * Count the number of maximal cliques in a graph * * * The current implementation uses a modified Bron-Kerbosch * algorithm to find the maximal cliques, see: David Eppstein, * Maarten Löffler, Darren Strash: Listing All Maximal Cliques in * Sparse Graphs in Near-Optimal Time. Algorithms and Computation, * Lecture Notes in Computer Science Volume 6506, 2010, pp 403-414. * * \param graph The input graph. * \param res Pointer to an \c igraph_integer_t; the number of maximal * cliques will be stored here. * \param min_size Integer giving the minimum size of the cliques to be * returned. If negative or zero, no lower bound will be used. * \param max_size Integer giving the maximum size of the cliques to be * returned. If negative or zero, no upper bound will be used. * \return Error code. * * \sa \ref igraph_maximal_cliques(). * * Time complexity: O(d(n-d)3^(d/3)) worst case, d is the degeneracy * of the graph, this is typically small for sparse graphs. * * \example examples/simple/igraph_maximal_cliques.c */ int igraph_maximal_cliques_count(const igraph_t *graph, igraph_integer_t *res, igraph_integer_t min_size, igraph_integer_t max_size); #define IGRAPH_MC_COUNT #include "maximal_cliques_template.h" #undef IGRAPH_MC_COUNT /** * \function igraph_maximal_cliques_file * Find maximal cliques and write them to a file * * TODO */ int igraph_maximal_cliques_file(const igraph_t *graph, FILE *outfile, igraph_integer_t min_size, igraph_integer_t max_size); #define IGRAPH_MC_FILE #include "maximal_cliques_template.h" #undef IGRAPH_MC_FILE /** * \function igraph_maximal_cliques_subset * Maximal cliques for a subset of initial vertices * * TODO */ int igraph_maximal_cliques_subset(const igraph_t *graph, igraph_vector_int_t *subset, igraph_vector_ptr_t *res, igraph_integer_t *no, FILE *outfile, igraph_integer_t min_size, igraph_integer_t max_size); #define IGRAPH_MC_FULL #include "maximal_cliques_template.h" #undef IGRAPH_MC_FULL /** * \function igraph_maximal_cliques_callback * \brief Finds maximal cliques in a graph and calls a function for each one * * This function enumerates all maximal cliques within the given size range * and calls \p cliquehandler_fn for each of them. The cliques are passed to the * callback function as an igraph_vector_t *. Destroying and * freeing this vector is left up to the user. Use \ref igraph_vector_destroy() * to destroy it first, then free it using \ref igraph_free(). * * * * Edge directions are ignored. * * * * \param graph The input graph. * \param cliquehandler_fn Callback function to be called for each clique. * See also \ref igraph_clique_handler_t. * \param arg Extra argument to supply to \p cliquehandler_fn. * \param min_size Integer giving the minimum size of the cliques to be * returned. If negative or zero, no lower bound will be used. * \param max_size Integer giving the maximum size of the cliques to be * returned. If negative or zero, no upper bound will be used. * \return Error code. * * \sa \ref igraph_maximal_cliques(). * * Time complexity: O(d(n-d)3^(d/3)) worst case, d is the degeneracy * of the graph, this is typically small for sparse graphs. * */ int igraph_maximal_cliques_callback(const igraph_t *graph, igraph_clique_handler_t *cliquehandler_fn, void *arg, igraph_integer_t min_size, igraph_integer_t max_size); #define IGRAPH_MC_CALLBACK #include "maximal_cliques_template.h" #undef IGRAPH_MC_CALLBACK /** * \function igraph_maximal_cliques_hist * \brief Count the number of maximal cliques of each size in a graph. * * This function counts how many maximal cliques of each size are present in * the graph. Size-1 maximal cliques are simply isolated vertices. * * * * Edge directions are ignored. * * * * \param graph The input graph. * \param hist Pointer to an initialized vector. The result will be stored * here. The first element will store the number of size-1 maximal cliques, * the second element the number of size-2 maximal cliques, etc. * For cliques smaller than \c min_size, zero counts will be returned. * \param min_size Integer giving the minimum size of the cliques to be * returned. If negative or zero, no lower bound will be used. * \param max_size Integer giving the maximum size of the cliques to be * returned. If negative or zero, no upper bound will be used. * \return Error code. * * \sa \ref igraph_maximal_cliques(). * * Time complexity: O(d(n-d)3^(d/3)) worst case, d is the degeneracy * of the graph, this is typically small for sparse graphs. * */ int igraph_maximal_cliques_hist(const igraph_t *graph, igraph_vector_t *hist, igraph_integer_t min_size, igraph_integer_t max_size); #define IGRAPH_MC_HIST #include "maximal_cliques_template.h" #undef IGRAPH_MC_HIST python-igraph-0.8.0/vendor/source/igraph/src/cocitation.c0000644000076500000240000007054313614300625023707 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph R package. Copyright (C) 2005-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_cocitation.h" #include "igraph_memory.h" #include "igraph_adjlist.h" #include "igraph_interrupt_internal.h" #include "igraph_interface.h" #include "config.h" #include int igraph_cocitation_real(const igraph_t *graph, igraph_matrix_t *res, igraph_vs_t vids, igraph_neimode_t mode, igraph_vector_t *weights); /** * \ingroup structural * \function igraph_cocitation * \brief Cocitation coupling. * * * Two vertices are cocited if there is another vertex citing both of * them. \ref igraph_cocitation() simply counts how many times two vertices are * cocited. * The cocitation score for each given vertex and all other vertices * in the graph will be calculated. * \param graph The graph object to analyze. * \param res Pointer to a matrix, the result of the calculation will * be stored here. The number of its rows is the same as the * number of vertex ids in \p vids, the number of * columns is the number of vertices in the graph. * \param vids The vertex ids of the vertices for which the * calculation will be done. * \return Error code: * \c IGRAPH_EINVVID: invalid vertex id. * * Time complexity: O(|V|d^2), |V| is * the number of vertices in the graph, * d is the (maximum) degree of * the vertices in the graph. * * \sa \ref igraph_bibcoupling() * * \example examples/simple/igraph_cocitation.c */ int igraph_cocitation(const igraph_t *graph, igraph_matrix_t *res, const igraph_vs_t vids) { return igraph_cocitation_real(graph, res, vids, IGRAPH_OUT, 0); } /** * \ingroup structural * \function igraph_bibcoupling * \brief Bibliographic coupling. * * * The bibliographic coupling of two vertices is the number * of other vertices they both cite, \ref igraph_bibcoupling() calculates * this. * The bibliographic coupling score for each given vertex and all * other vertices in the graph will be calculated. * \param graph The graph object to analyze. * \param res Pointer to a matrix, the result of the calculation will * be stored here. The number of its rows is the same as the * number of vertex ids in \p vids, the number of * columns is the number of vertices in the graph. * \param vids The vertex ids of the vertices for which the * calculation will be done. * \return Error code: * \c IGRAPH_EINVVID: invalid vertex id. * * Time complexity: O(|V|d^2), * |V| is the number of vertices in * the graph, d is the (maximum) * degree of the vertices in the graph. * * \sa \ref igraph_cocitation() */ int igraph_bibcoupling(const igraph_t *graph, igraph_matrix_t *res, const igraph_vs_t vids) { return igraph_cocitation_real(graph, res, vids, IGRAPH_IN, 0); } /** * \ingroup structural * \function igraph_similarity_inverse_log_weighted * \brief Vertex similarity based on the inverse logarithm of vertex degrees. * * * The inverse log-weighted similarity of two vertices is the number of * their common neighbors, weighted by the inverse logarithm of their degrees. * It is based on the assumption that two vertices should be considered * more similar if they share a low-degree common neighbor, since high-degree * common neighbors are more likely to appear even by pure chance. * * * Isolated vertices will have zero similarity to any other vertex. * Self-similarities are not calculated. * * * See the following paper for more details: Lada A. Adamic and Eytan Adar: * Friends and neighbors on the Web. Social Networks, 25(3):211-230, 2003. * * \param graph The graph object to analyze. * \param res Pointer to a matrix, the result of the calculation will * be stored here. The number of its rows is the same as the * number of vertex ids in \p vids, the number of * columns is the number of vertices in the graph. * \param vids The vertex ids of the vertices for which the * calculation will be done. * \param mode The type of neighbors to be used for the calculation in * directed graphs. Possible values: * \clist * \cli IGRAPH_OUT * the outgoing edges will be considered for each node. Nodes * will be weighted according to their in-degree. * \cli IGRAPH_IN * the incoming edges will be considered for each node. Nodes * will be weighted according to their out-degree. * \cli IGRAPH_ALL * the directed graph is considered as an undirected one for the * computation. Every node is weighted according to its undirected * degree. * \endclist * \return Error code: * \c IGRAPH_EINVVID: invalid vertex id. * * Time complexity: O(|V|d^2), * |V| is the number of vertices in * the graph, d is the (maximum) * degree of the vertices in the graph. * * \example examples/simple/igraph_similarity.c */ int igraph_similarity_inverse_log_weighted(const igraph_t *graph, igraph_matrix_t *res, const igraph_vs_t vids, igraph_neimode_t mode) { igraph_vector_t weights; igraph_neimode_t mode0; long int i, no_of_nodes; switch (mode) { case IGRAPH_OUT: mode0 = IGRAPH_IN; break; case IGRAPH_IN: mode0 = IGRAPH_OUT; break; default: mode0 = IGRAPH_ALL; } no_of_nodes = igraph_vcount(graph); IGRAPH_VECTOR_INIT_FINALLY(&weights, no_of_nodes); IGRAPH_CHECK(igraph_degree(graph, &weights, igraph_vss_all(), mode0, 1)); for (i = 0; i < no_of_nodes; i++) { if (VECTOR(weights)[i] > 1) { VECTOR(weights)[i] = 1.0 / log(VECTOR(weights)[i]); } } IGRAPH_CHECK(igraph_cocitation_real(graph, res, vids, mode0, &weights)); igraph_vector_destroy(&weights); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_cocitation_real(const igraph_t *graph, igraph_matrix_t *res, igraph_vs_t vids, igraph_neimode_t mode, igraph_vector_t *weights) { long int no_of_nodes = igraph_vcount(graph); long int no_of_vids; long int from, i, j, k, l, u, v; igraph_vector_t neis = IGRAPH_VECTOR_NULL; igraph_vector_t vid_reverse_index; igraph_vit_t vit; IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); no_of_vids = IGRAPH_VIT_SIZE(vit); /* Create a mapping from vertex IDs to the row of the matrix where * the result for this vertex will appear */ IGRAPH_VECTOR_INIT_FINALLY(&vid_reverse_index, no_of_nodes); igraph_vector_fill(&vid_reverse_index, -1); for (IGRAPH_VIT_RESET(vit), i = 0; !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit), i++) { v = IGRAPH_VIT_GET(vit); if (v < 0 || v >= no_of_nodes) { IGRAPH_ERROR("invalid vertex ID in vertex selector", IGRAPH_EINVAL); } VECTOR(vid_reverse_index)[v] = i; } IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); IGRAPH_CHECK(igraph_matrix_resize(res, no_of_vids, no_of_nodes)); igraph_matrix_null(res); /* The result */ for (from = 0; from < no_of_nodes; from++) { igraph_real_t weight = 1; IGRAPH_ALLOW_INTERRUPTION(); IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) from, mode)); if (weights) { weight = VECTOR(*weights)[from]; } for (i = 0; i < igraph_vector_size(&neis) - 1; i++) { u = (long int) VECTOR(neis)[i]; k = (long int) VECTOR(vid_reverse_index)[u]; for (j = i + 1; j < igraph_vector_size(&neis); j++) { v = (long int) VECTOR(neis)[j]; l = (long int) VECTOR(vid_reverse_index)[v]; if (k != -1) { MATRIX(*res, k, v) += weight; } if (l != -1) { MATRIX(*res, l, u) += weight; } } } } /* Clean up */ igraph_vector_destroy(&neis); igraph_vector_destroy(&vid_reverse_index); igraph_vit_destroy(&vit); IGRAPH_FINALLY_CLEAN(3); return 0; } int igraph_i_neisets_intersect(const igraph_vector_t *v1, const igraph_vector_t *v2, long int *len_union, long int *len_intersection); int igraph_i_neisets_intersect(const igraph_vector_t *v1, const igraph_vector_t *v2, long int *len_union, long int *len_intersection) { /* ASSERT: v1 and v2 are sorted */ long int i, j, i0, jj0; i0 = igraph_vector_size(v1); jj0 = igraph_vector_size(v2); *len_union = i0 + jj0; *len_intersection = 0; i = 0; j = 0; while (i < i0 && j < jj0) { if (VECTOR(*v1)[i] == VECTOR(*v2)[j]) { (*len_intersection)++; (*len_union)--; i++; j++; } else if (VECTOR(*v1)[i] < VECTOR(*v2)[j]) { i++; } else { j++; } } return 0; } /** * \ingroup structural * \function igraph_similarity_jaccard * \brief Jaccard similarity coefficient for the given vertices. * * * The Jaccard similarity coefficient of two vertices is the number of common * neighbors divided by the number of vertices that are neighbors of at * least one of the two vertices being considered. This function calculates * the pairwise Jaccard similarities for some (or all) of the vertices. * * \param graph The graph object to analyze * \param res Pointer to a matrix, the result of the calculation will * be stored here. The number of its rows and columns is the same * as the number of vertex ids in \p vids. * \param vids The vertex ids of the vertices for which the * calculation will be done. * \param mode The type of neighbors to be used for the calculation in * directed graphs. Possible values: * \clist * \cli IGRAPH_OUT * the outgoing edges will be considered for each node. * \cli IGRAPH_IN * the incoming edges will be considered for each node. * \cli IGRAPH_ALL * the directed graph is considered as an undirected one for the * computation. * \endclist * \param loops Whether to include the vertices themselves in the neighbor * sets. * \return Error code: * \clist * \cli IGRAPH_ENOMEM * not enough memory for temporary data. * \cli IGRAPH_EINVVID * invalid vertex id passed. * \cli IGRAPH_EINVMODE * invalid mode argument. * \endclist * * Time complexity: O(|V|^2 d), * |V| is the number of vertices in the vertex iterator given, d is the * (maximum) degree of the vertices in the graph. * * \sa \ref igraph_similarity_dice(), a measure very similar to the Jaccard * coefficient * * \example examples/simple/igraph_similarity.c */ int igraph_similarity_jaccard(const igraph_t *graph, igraph_matrix_t *res, const igraph_vs_t vids, igraph_neimode_t mode, igraph_bool_t loops) { igraph_lazy_adjlist_t al; igraph_vit_t vit, vit2; long int i, j, k; long int len_union, len_intersection; igraph_vector_t *v1, *v2; IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit2)); IGRAPH_FINALLY(igraph_vit_destroy, &vit2); IGRAPH_CHECK(igraph_lazy_adjlist_init(graph, &al, mode, IGRAPH_SIMPLIFY)); IGRAPH_FINALLY(igraph_lazy_adjlist_destroy, &al); IGRAPH_CHECK(igraph_matrix_resize(res, IGRAPH_VIT_SIZE(vit), IGRAPH_VIT_SIZE(vit))); if (loops) { for (IGRAPH_VIT_RESET(vit); !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit)) { i = IGRAPH_VIT_GET(vit); v1 = igraph_lazy_adjlist_get(&al, (igraph_integer_t) i); if (!igraph_vector_binsearch(v1, i, &k)) { igraph_vector_insert(v1, k, i); } } } for (IGRAPH_VIT_RESET(vit), i = 0; !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit), i++) { MATRIX(*res, i, i) = 1.0; for (IGRAPH_VIT_RESET(vit2), j = 0; !IGRAPH_VIT_END(vit2); IGRAPH_VIT_NEXT(vit2), j++) { if (j <= i) { continue; } v1 = igraph_lazy_adjlist_get(&al, IGRAPH_VIT_GET(vit)); v2 = igraph_lazy_adjlist_get(&al, IGRAPH_VIT_GET(vit2)); igraph_i_neisets_intersect(v1, v2, &len_union, &len_intersection); if (len_union > 0) { MATRIX(*res, i, j) = ((igraph_real_t)len_intersection) / len_union; } else { MATRIX(*res, i, j) = 0.0; } MATRIX(*res, j, i) = MATRIX(*res, i, j); } } igraph_lazy_adjlist_destroy(&al); igraph_vit_destroy(&vit); igraph_vit_destroy(&vit2); IGRAPH_FINALLY_CLEAN(3); return 0; } /** * \ingroup structural * \function igraph_similarity_jaccard_pairs * \brief Jaccard similarity coefficient for given vertex pairs. * * * The Jaccard similarity coefficient of two vertices is the number of common * neighbors divided by the number of vertices that are neighbors of at * least one of the two vertices being considered. This function calculates * the pairwise Jaccard similarities for a list of vertex pairs. * * \param graph The graph object to analyze * \param res Pointer to a vector, the result of the calculation will * be stored here. The number of elements is the same as the number * of pairs in \p pairs. * \param pairs A vector that contains the pairs for which the similarity * will be calculated. Each pair is defined by two consecutive elements, * i.e. the first and second element of the vector specifies the first * pair, the third and fourth element specifies the second pair and so on. * \param mode The type of neighbors to be used for the calculation in * directed graphs. Possible values: * \clist * \cli IGRAPH_OUT * the outgoing edges will be considered for each node. * \cli IGRAPH_IN * the incoming edges will be considered for each node. * \cli IGRAPH_ALL * the directed graph is considered as an undirected one for the * computation. * \endclist * \param loops Whether to include the vertices themselves in the neighbor * sets. * \return Error code: * \clist * \cli IGRAPH_ENOMEM * not enough memory for temporary data. * \cli IGRAPH_EINVVID * invalid vertex id passed. * \cli IGRAPH_EINVMODE * invalid mode argument. * \endclist * * Time complexity: O(nd), n is the number of pairs in the given vector, d is * the (maximum) degree of the vertices in the graph. * * \sa \ref igraph_similarity_jaccard() to calculate the Jaccard similarity * between all pairs of a vertex set, or \ref igraph_similarity_dice() and * \ref igraph_similarity_dice_pairs() for a measure very similar to the * Jaccard coefficient * * \example examples/simple/igraph_similarity.c */ int igraph_similarity_jaccard_pairs(const igraph_t *graph, igraph_vector_t *res, const igraph_vector_t *pairs, igraph_neimode_t mode, igraph_bool_t loops) { igraph_lazy_adjlist_t al; long int i, j, k, u, v; long int len_union, len_intersection; igraph_vector_t *v1, *v2; igraph_bool_t *seen; k = igraph_vector_size(pairs); if (k % 2 != 0) { IGRAPH_ERROR("number of elements in `pairs' must be even", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_vector_resize(res, k / 2)); IGRAPH_CHECK(igraph_lazy_adjlist_init(graph, &al, mode, IGRAPH_SIMPLIFY)); IGRAPH_FINALLY(igraph_lazy_adjlist_destroy, &al); if (loops) { /* Add the loop edges */ i = igraph_vcount(graph); seen = igraph_Calloc(i, igraph_bool_t); if (seen == 0) { IGRAPH_ERROR("cannot calculate Jaccard similarity", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, seen); for (i = 0; i < k; i++) { j = (long int) VECTOR(*pairs)[i]; if (seen[j]) { continue; } seen[j] = 1; v1 = igraph_lazy_adjlist_get(&al, (igraph_integer_t) j); if (!igraph_vector_binsearch(v1, j, &u)) { igraph_vector_insert(v1, u, j); } } free(seen); IGRAPH_FINALLY_CLEAN(1); } for (i = 0, j = 0; i < k; i += 2, j++) { u = (long int) VECTOR(*pairs)[i]; v = (long int) VECTOR(*pairs)[i + 1]; if (u == v) { VECTOR(*res)[j] = 1.0; continue; } v1 = igraph_lazy_adjlist_get(&al, (igraph_integer_t) u); v2 = igraph_lazy_adjlist_get(&al, (igraph_integer_t) v); igraph_i_neisets_intersect(v1, v2, &len_union, &len_intersection); if (len_union > 0) { VECTOR(*res)[j] = ((igraph_real_t)len_intersection) / len_union; } else { VECTOR(*res)[j] = 0.0; } } igraph_lazy_adjlist_destroy(&al); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \ingroup structural * \function igraph_similarity_jaccard_es * \brief Jaccard similarity coefficient for a given edge selector. * * * The Jaccard similarity coefficient of two vertices is the number of common * neighbors divided by the number of vertices that are neighbors of at * least one of the two vertices being considered. This function calculates * the pairwise Jaccard similarities for the endpoints of edges in a given edge * selector. * * \param graph The graph object to analyze * \param res Pointer to a vector, the result of the calculation will * be stored here. The number of elements is the same as the number * of edges in \p es. * \param es An edge selector that specifies the edges to be included in the * result. * \param mode The type of neighbors to be used for the calculation in * directed graphs. Possible values: * \clist * \cli IGRAPH_OUT * the outgoing edges will be considered for each node. * \cli IGRAPH_IN * the incoming edges will be considered for each node. * \cli IGRAPH_ALL * the directed graph is considered as an undirected one for the * computation. * \endclist * \param loops Whether to include the vertices themselves in the neighbor * sets. * \return Error code: * \clist * \cli IGRAPH_ENOMEM * not enough memory for temporary data. * \cli IGRAPH_EINVVID * invalid vertex id passed. * \cli IGRAPH_EINVMODE * invalid mode argument. * \endclist * * Time complexity: O(nd), n is the number of edges in the edge selector, d is * the (maximum) degree of the vertices in the graph. * * \sa \ref igraph_similarity_jaccard() and \ref igraph_similarity_jaccard_pairs() * to calculate the Jaccard similarity between all pairs of a vertex set or * some selected vertex pairs, or \ref igraph_similarity_dice(), * \ref igraph_similarity_dice_pairs() and \ref igraph_similarity_dice_es() for a * measure very similar to the Jaccard coefficient * * \example examples/simple/igraph_similarity.c */ int igraph_similarity_jaccard_es(const igraph_t *graph, igraph_vector_t *res, const igraph_es_t es, igraph_neimode_t mode, igraph_bool_t loops) { igraph_vector_t v; igraph_eit_t eit; IGRAPH_VECTOR_INIT_FINALLY(&v, 0); IGRAPH_CHECK(igraph_eit_create(graph, es, &eit)); IGRAPH_FINALLY(igraph_eit_destroy, &eit); while (!IGRAPH_EIT_END(eit)) { long int eid = IGRAPH_EIT_GET(eit); igraph_vector_push_back(&v, IGRAPH_FROM(graph, eid)); igraph_vector_push_back(&v, IGRAPH_TO(graph, eid)); IGRAPH_EIT_NEXT(eit); } igraph_eit_destroy(&eit); IGRAPH_FINALLY_CLEAN(1); IGRAPH_CHECK(igraph_similarity_jaccard_pairs(graph, res, &v, mode, loops)); igraph_vector_destroy(&v); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } /** * \ingroup structural * \function igraph_similarity_dice * \brief Dice similarity coefficient. * * * The Dice similarity coefficient of two vertices is twice the number of common * neighbors divided by the sum of the degrees of the vertices. This function * calculates the pairwise Dice similarities for some (or all) of the vertices. * * \param graph The graph object to analyze * \param res Pointer to a matrix, the result of the calculation will * be stored here. The number of its rows and columns is the same * as the number of vertex ids in \p vids. * \param vids The vertex ids of the vertices for which the * calculation will be done. * \param mode The type of neighbors to be used for the calculation in * directed graphs. Possible values: * \clist * \cli IGRAPH_OUT * the outgoing edges will be considered for each node. * \cli IGRAPH_IN * the incoming edges will be considered for each node. * \cli IGRAPH_ALL * the directed graph is considered as an undirected one for the * computation. * \endclist * \param loops Whether to include the vertices themselves as their own * neighbors. * \return Error code: * \clist * \cli IGRAPH_ENOMEM * not enough memory for temporary data. * \cli IGRAPH_EINVVID * invalid vertex id passed. * \cli IGRAPH_EINVMODE * invalid mode argument. * \endclist * * Time complexity: O(|V|^2 d), * |V| is the number of vertices in the vertex iterator given, d is the * (maximum) degree of the vertices in the graph. * * \sa \ref igraph_similarity_jaccard(), a measure very similar to the Dice * coefficient * * \example examples/simple/igraph_similarity.c */ int igraph_similarity_dice(const igraph_t *graph, igraph_matrix_t *res, const igraph_vs_t vids, igraph_neimode_t mode, igraph_bool_t loops) { long int i, j, nr, nc; IGRAPH_CHECK(igraph_similarity_jaccard(graph, res, vids, mode, loops)); nr = igraph_matrix_nrow(res); nc = igraph_matrix_ncol(res); for (i = 0; i < nr; i++) { for (j = 0; j < nc; j++) { igraph_real_t x = MATRIX(*res, i, j); MATRIX(*res, i, j) = 2 * x / (1 + x); } } return IGRAPH_SUCCESS; } /** * \ingroup structural * \function igraph_similarity_dice_pairs * \brief Dice similarity coefficient for given vertex pairs. * * * The Dice similarity coefficient of two vertices is twice the number of common * neighbors divided by the sum of the degrees of the vertices. This function * calculates the pairwise Dice similarities for a list of vertex pairs. * * \param graph The graph object to analyze * \param res Pointer to a vector, the result of the calculation will * be stored here. The number of elements is the same as the number * of pairs in \p pairs. * \param pairs A vector that contains the pairs for which the similarity * will be calculated. Each pair is defined by two consecutive elements, * i.e. the first and second element of the vector specifies the first * pair, the third and fourth element specifies the second pair and so on. * \param mode The type of neighbors to be used for the calculation in * directed graphs. Possible values: * \clist * \cli IGRAPH_OUT * the outgoing edges will be considered for each node. * \cli IGRAPH_IN * the incoming edges will be considered for each node. * \cli IGRAPH_ALL * the directed graph is considered as an undirected one for the * computation. * \endclist * \param loops Whether to include the vertices themselves as their own * neighbors. * \return Error code: * \clist * \cli IGRAPH_ENOMEM * not enough memory for temporary data. * \cli IGRAPH_EINVVID * invalid vertex id passed. * \cli IGRAPH_EINVMODE * invalid mode argument. * \endclist * * Time complexity: O(nd), n is the number of pairs in the given vector, d is * the (maximum) degree of the vertices in the graph. * * \sa \ref igraph_similarity_dice() to calculate the Dice similarity * between all pairs of a vertex set, or \ref igraph_similarity_jaccard(), * \ref igraph_similarity_jaccard_pairs() and \ref igraph_similarity_jaccard_es() * for a measure very similar to the Dice coefficient * * \example examples/simple/igraph_similarity.c */ int igraph_similarity_dice_pairs(const igraph_t *graph, igraph_vector_t *res, const igraph_vector_t *pairs, igraph_neimode_t mode, igraph_bool_t loops) { long int i, n; IGRAPH_CHECK(igraph_similarity_jaccard_pairs(graph, res, pairs, mode, loops)); n = igraph_vector_size(res); for (i = 0; i < n; i++) { igraph_real_t x = VECTOR(*res)[i]; VECTOR(*res)[i] = 2 * x / (1 + x); } return IGRAPH_SUCCESS; } /** * \ingroup structural * \function igraph_similarity_dice_es * \brief Dice similarity coefficient for a given edge selector. * * * The Dice similarity coefficient of two vertices is twice the number of common * neighbors divided by the sum of the degrees of the vertices. This function * calculates the pairwise Dice similarities for the endpoints of edges in a given * edge selector. * * \param graph The graph object to analyze * \param res Pointer to a vector, the result of the calculation will * be stored here. The number of elements is the same as the number * of edges in \p es. * \param es An edge selector that specifies the edges to be included in the * result. * \param mode The type of neighbors to be used for the calculation in * directed graphs. Possible values: * \clist * \cli IGRAPH_OUT * the outgoing edges will be considered for each node. * \cli IGRAPH_IN * the incoming edges will be considered for each node. * \cli IGRAPH_ALL * the directed graph is considered as an undirected one for the * computation. * \endclist * \param loops Whether to include the vertices themselves as their own * neighbors. * \return Error code: * \clist * \cli IGRAPH_ENOMEM * not enough memory for temporary data. * \cli IGRAPH_EINVVID * invalid vertex id passed. * \cli IGRAPH_EINVMODE * invalid mode argument. * \endclist * * Time complexity: O(nd), n is the number of pairs in the given vector, d is * the (maximum) degree of the vertices in the graph. * * \sa \ref igraph_similarity_dice() and \ref igraph_similarity_dice_pairs() * to calculate the Dice similarity between all pairs of a vertex set or * some selected vertex pairs, or \ref igraph_similarity_jaccard(), * \ref igraph_similarity_jaccard_pairs() and \ref igraph_similarity_jaccard_es() * for a measure very similar to the Dice coefficient * * \example examples/simple/igraph_similarity.c */ int igraph_similarity_dice_es(const igraph_t *graph, igraph_vector_t *res, const igraph_es_t es, igraph_neimode_t mode, igraph_bool_t loops) { long int i, n; IGRAPH_CHECK(igraph_similarity_jaccard_es(graph, res, es, mode, loops)); n = igraph_vector_size(res); for (i = 0; i < n; i++) { igraph_real_t x = VECTOR(*res)[i]; VECTOR(*res)[i] = 2 * x / (1 + x); } return IGRAPH_SUCCESS; } python-igraph-0.8.0/vendor/source/igraph/src/igraph_estack.c0000644000076500000240000000413013614300625024344 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_estack.h" int igraph_estack_init(igraph_estack_t *s, long int setsize, long int stacksize) { IGRAPH_CHECK(igraph_vector_bool_init(&s->isin, setsize)); IGRAPH_FINALLY(igraph_vector_bool_destroy, &s->isin); IGRAPH_CHECK(igraph_stack_long_init(&s->stack, stacksize)); IGRAPH_FINALLY_CLEAN(1); return 0; } void igraph_estack_destroy(igraph_estack_t *s) { igraph_stack_long_destroy(&s->stack); igraph_vector_bool_destroy(&s->isin); } int igraph_estack_push(igraph_estack_t *s, long int elem) { if ( !VECTOR(s->isin)[elem] ) { IGRAPH_CHECK(igraph_stack_long_push(&s->stack, elem)); VECTOR(s->isin)[elem] = 1; } return 0; } long int igraph_estack_pop(igraph_estack_t *s) { long int elem = igraph_stack_long_pop(&s->stack); VECTOR(s->isin)[elem] = 0; return elem; } igraph_bool_t igraph_estack_iselement(const igraph_estack_t *s, long int elem) { return VECTOR(s->isin)[elem]; } long int igraph_estack_size(const igraph_estack_t *s) { return igraph_stack_long_size(&s->stack); } #ifndef USING_R int igraph_estack_print(const igraph_estack_t *s) { return igraph_stack_long_print(&s->stack); } #endif python-igraph-0.8.0/vendor/source/igraph/src/layout_dh.c0000644000076500000240000004461513614300625023544 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph R package. Copyright (C) 2014 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_layout.h" #include "igraph_interface.h" #include "igraph_random.h" #include "igraph_math.h" #include igraph_bool_t igraph_i_segments_intersect(float p0_x, float p0_y, float p1_x, float p1_y, float p2_x, float p2_y, float p3_x, float p3_y) { float s1_x = p1_x - p0_x; float s1_y = p1_y - p0_y; float s2_x = p3_x - p2_x; float s2_y = p3_y - p2_y; float s1, s2, t1, t2, s, t; s1 = (-s1_y * (p0_x - p2_x) + s1_x * (p0_y - p2_y)); s2 = (-s2_x * s1_y + s1_x * s2_y); if (s2 == 0) { return 0; } t1 = ( s2_x * (p0_y - p2_y) - s2_y * (p0_x - p2_x)); t2 = (-s2_x * s1_y + s1_x * s2_y); s = s1 / s2; t = t1 / t2; return s >= 0 && s <= 1 && t >= 0 && t <= 1 ? 1 : 0; } float igraph_i_point_segment_dist2(float v_x, float v_y, float u1_x, float u1_y, float u2_x, float u2_y) { float dx = u2_x - u1_x; float dy = u2_y - u1_y; float l2 = dx * dx + dy * dy; float t, p_x, p_y; if (l2 == 0) { return (v_x - u1_x) * (v_x - u1_x) + (v_y - u1_y) * (v_y - u1_y); } t = ((v_x - u1_x) * dx + (v_y - u1_y) * dy) / l2; if (t < 0.0) { return (v_x - u1_x) * (v_x - u1_x) + (v_y - u1_y) * (v_y - u1_y); } else if (t > 1.0) { return (v_x - u2_x) * (v_x - u2_x) + (v_y - u2_y) * (v_y - u2_y); } p_x = u1_x + t * dx; p_y = u1_y + t * dy; return (v_x - p_x) * (v_x - p_x) + (v_y - p_y) * (v_y - p_y); } /** * \function igraph_layout_davidson_harel * Davidson-Harel layout algorithm * * This function implements the algorithm by Davidson and Harel, * see Ron Davidson, David Harel: Drawing Graphs Nicely Using * Simulated Annealing. ACM Transactions on Graphics 15(4), * pp. 301-331, 1996. * * * The algorithm uses simulated annealing and a sophisticated * energy function, which is unfortunately hard to parameterize * for different graphs. The original publication did not disclose any * parameter values, and the ones below were determined by * experimentation. * * * The algorithm consists of two phases, an annealing phase, and a * fine-tuning phase. There is no simulated annealing in the second * phase. * * * Our implementation tries to follow the original publication, as * much as possible. The only major difference is that coordinates are * explicitly kept within the bounds of the rectangle of the layout. * * \param graph The input graph, edge directions are ignored. * \param res A matrix, the result is stored here. It can be used to * supply start coordinates, see \p use_seed. * \param use_seed Boolean, whether to use the supplied \p res as * start coordinates. * \param maxiter The maximum number of annealing iterations. A * reasonable value for smaller graphs is 10. * \param fineiter The number of fine tuning iterations. A reasonable * value is max(10, log2(n)) where n is the number of vertices. * \param cool_fact Cooling factor. A reasonable value is 0.75. * \param weight_node_dist Weight for the node-node distances * component of the energy function. Reasonable value: 1.0. * \param weight_border Weight for the distance from the border * component of the energy function. It can be set to zero, if * vertices are allowed to sit on the border. * \param weight_edge_lengths Weight for the edge length component * of the energy function, a reasonable value is the density of * the graph divided by 10. * \param weight_edge_crossings Weight for the edge crossing component * of the energy function, a reasonable default is 1 minus the * square root of the density of the graph. * \param weight_node_edge_dist Weight for the node-edge distance * component of the energy function. A reasonable value is * 1 minus the density, divided by 5. * \return Error code. * * Time complexity: one first phase iteration has time complexity * O(n^2+m^2), one fine tuning iteration has time complexity O(mn). * Time complexity might be smaller if some of the weights of the * components of the energy function are set to zero. * */ int igraph_layout_davidson_harel(const igraph_t *graph, igraph_matrix_t *res, igraph_bool_t use_seed, igraph_integer_t maxiter, igraph_integer_t fineiter, igraph_real_t cool_fact, igraph_real_t weight_node_dist, igraph_real_t weight_border, igraph_real_t weight_edge_lengths, igraph_real_t weight_edge_crossings, igraph_real_t weight_node_edge_dist) { igraph_integer_t no_nodes = igraph_vcount(graph); igraph_integer_t no_edges = igraph_ecount(graph); float width = sqrt(no_nodes) * 10, height = width; igraph_vector_int_t perm; igraph_bool_t fine_tuning = 0; igraph_integer_t round, i; igraph_vector_float_t try_x, try_y; igraph_vector_int_t try_idx; float move_radius = width / 2; float fine_tuning_factor = 0.01; igraph_vector_t neis; float min_x = width / 2, max_x = -width / 2, min_y = height / 2, max_y = -height / 2; igraph_integer_t no_tries = 30; float w_node_dist = weight_node_dist ; /* 1.0 */ float w_borderlines = weight_border; /* 0.0 */ float w_edge_lengths = weight_edge_lengths; /* 0.0001; */ float w_edge_crossings = weight_edge_crossings; /* 1.0 */ float w_node_edge_dist = weight_node_edge_dist; /* 0.2 */ if (use_seed && (igraph_matrix_nrow(res) != no_nodes || igraph_matrix_ncol(res) != 2)) { IGRAPH_ERROR("Invalid start position matrix size in " "Davidson-Harel layout", IGRAPH_EINVAL); } if (maxiter < 0) { IGRAPH_ERROR("Number of iterations must be non-negative in " "Davidson-Harel layout", IGRAPH_EINVAL); } if (fineiter < 0) { IGRAPH_ERROR("Number of fine tuning iterations must be non-negative in " "Davidson-Harel layout", IGRAPH_EINVAL); } if (cool_fact <= 0 || cool_fact >= 1) { IGRAPH_ERROR("Cooling factor must be in (0,1) in " "Davidson-Harel layout", IGRAPH_EINVAL); } if (no_nodes == 0) { return 0; } IGRAPH_CHECK(igraph_vector_int_init_seq(&perm, 0, no_nodes - 1)); IGRAPH_FINALLY(igraph_vector_int_destroy, &perm); IGRAPH_CHECK(igraph_vector_float_init(&try_x, no_tries)); IGRAPH_FINALLY(igraph_vector_float_destroy, &try_x); IGRAPH_CHECK(igraph_vector_float_init(&try_y, no_tries)); IGRAPH_FINALLY(igraph_vector_float_destroy, &try_y); IGRAPH_CHECK(igraph_vector_int_init_seq(&try_idx, 0, no_tries - 1)); IGRAPH_FINALLY(igraph_vector_int_destroy, &try_idx); IGRAPH_VECTOR_INIT_FINALLY(&neis, 100); RNG_BEGIN(); if (!use_seed) { IGRAPH_CHECK(igraph_matrix_resize(res, no_nodes, 2)); for (i = 0; i < no_nodes; i++) { float x, y; x = MATRIX(*res, i, 0) = RNG_UNIF(-width / 2, width / 2); y = MATRIX(*res, i, 1) = RNG_UNIF(-height / 2, height / 2); if (x < min_x) { min_x = x; } else if (x > max_x) { max_x = x; } if (y < min_y) { min_y = y; } else if (y > max_y) { max_y = y; } } } else { min_x = IGRAPH_INFINITY; max_x = IGRAPH_NEGINFINITY; min_y = IGRAPH_INFINITY; max_y = IGRAPH_NEGINFINITY; for (i = 0; i < no_nodes; i++) { float x = MATRIX(*res, i, 0); float y = MATRIX(*res, i, 1); if (x < min_x) { min_x = x; } else if (x > max_x) { max_x = x; } if (y < min_y) { min_y = y; } else if (y > max_y) { max_y = y; } } } for (i = 0; i < no_tries; i++) { float phi = 2 * M_PI / no_tries * i; VECTOR(try_x)[i] = cos(phi); VECTOR(try_y)[i] = sin(phi); } for (round = 0; round < maxiter + fineiter; round++) { igraph_integer_t p; igraph_vector_int_shuffle(&perm); fine_tuning = round >= maxiter; if (fine_tuning) { float fx = fine_tuning_factor * (max_x - min_x); float fy = fine_tuning_factor * (max_y - min_y); move_radius = fx < fy ? fx : fy; } for (p = 0; p < no_nodes; p++) { igraph_integer_t t; igraph_integer_t v = VECTOR(perm)[p]; igraph_vector_int_shuffle(&try_idx); for (t = 0; t < no_tries; t++) { float diff_energy = 0.0; int ti = VECTOR(try_idx)[t]; /* Try moving it */ float old_x = MATRIX(*res, v, 0); float old_y = MATRIX(*res, v, 1); float new_x = old_x + move_radius * VECTOR(try_x)[ti]; float new_y = old_y + move_radius * VECTOR(try_y)[ti]; if (new_x < -width / 2) { new_x = -width / 2 - 1e-6; } if (new_x > width / 2) { new_x = width / 2 - 1e-6; } if (new_y < -height / 2) { new_y = -height / 2 - 1e-6; } if (new_y > height / 2) { new_y = height / 2 - 1e-6; } if (w_node_dist != 0) { igraph_integer_t u; for (u = 0; u < no_nodes; u++) { float odx, ody, odist2, dx, dy, dist2; if (u == v) { continue; } odx = old_x - MATRIX(*res, u, 0); ody = old_y - MATRIX(*res, u, 1); dx = new_x - MATRIX(*res, u, 0); dy = new_y - MATRIX(*res, u, 1); odist2 = odx * odx + ody * ody; dist2 = dx * dx + dy * dy; diff_energy += w_node_dist / dist2 - w_node_dist / odist2; } } if (w_borderlines != 0) { float odx1 = width / 2 - old_x, odx2 = old_x + width / 2; float ody1 = height / 2 - old_y, ody2 = old_y + height / 2; float dx1 = width / 2 - new_x, dx2 = new_x + width / 2; float dy1 = height / 2 - new_y, dy2 = new_y + height / 2; if (odx1 < 0) { odx1 = 2; } if (odx2 < 0) { odx2 = 2; } if (ody1 < 0) { ody1 = 2; } if (ody2 < 0) { ody2 = 2; } if (dx1 < 0) { dx1 = 2; } if (dx2 < 0) { dx2 = 2; } if (dy1 < 0) { dy1 = 2; } if (dy2 < 0) { dy2 = 2; } diff_energy -= w_borderlines * (1.0 / (odx1 * odx1) + 1.0 / (odx2 * odx2) + 1.0 / (ody1 * ody1) + 1.0 / (ody2 * ody2)); diff_energy += w_borderlines * (1.0 / (dx1 * dx1) + 1.0 / (dx2 * dx2) + 1.0 / (dy1 * dy1) + 1.0 / (dy2 * dy2)); } if (w_edge_lengths != 0) { igraph_integer_t len, j; igraph_neighbors(graph, &neis, v, IGRAPH_ALL); len = igraph_vector_size(&neis); for (j = 0; j < len; j++) { igraph_integer_t u = VECTOR(neis)[j]; float odx = old_x - MATRIX(*res, u, 0); float ody = old_y - MATRIX(*res, u, 1); float odist2 = odx * odx + ody * ody; float dx = new_x - MATRIX(*res, u, 0); float dy = new_y - MATRIX(*res, u, 1); float dist2 = dx * dx + dy * dy; diff_energy += w_edge_lengths * (dist2 - odist2); } } if (w_edge_crossings != 0) { igraph_integer_t len, j, no = 0; igraph_neighbors(graph, &neis, v, IGRAPH_ALL); len = igraph_vector_size(&neis); for (j = 0; j < len; j++) { igraph_integer_t u = VECTOR(neis)[j]; float u_x = MATRIX(*res, u, 0); float u_y = MATRIX(*res, u, 1); igraph_integer_t e; for (e = 0; e < no_edges; e++) { igraph_integer_t u1 = IGRAPH_FROM(graph, e); igraph_integer_t u2 = IGRAPH_TO(graph, e); float u1_x, u1_y, u2_x, u2_y; if (u1 == v || u2 == v || u1 == u || u2 == u) { continue; } u1_x = MATRIX(*res, u1, 0); u1_y = MATRIX(*res, u1, 1); u2_x = MATRIX(*res, u2, 0); u2_y = MATRIX(*res, u2, 1); no -= igraph_i_segments_intersect(old_x, old_y, u_x, u_y, u1_x, u1_y, u2_x, u2_y); no += igraph_i_segments_intersect(new_x, new_y, u_x, u_y, u1_x, u1_y, u2_x, u2_y); } } diff_energy += w_edge_crossings * no; } if (w_node_edge_dist != 0 && fine_tuning) { igraph_integer_t e, no; /* All non-incident edges from the moved 'v' */ for (e = 0; e < no_edges; e++) { igraph_integer_t u1 = IGRAPH_FROM(graph, e); igraph_integer_t u2 = IGRAPH_TO(graph, e); float u1_x, u1_y, u2_x, u2_y, d_ev; if (u1 == v || u2 == v) { continue; } u1_x = MATRIX(*res, u1, 0); u1_y = MATRIX(*res, u1, 1); u2_x = MATRIX(*res, u2, 0); u2_y = MATRIX(*res, u2, 1); d_ev = igraph_i_point_segment_dist2(old_x, old_y, u1_x, u1_y, u2_x, u2_y); diff_energy -= w_node_edge_dist / d_ev; d_ev = igraph_i_point_segment_dist2(new_x, new_y, u1_x, u1_y, u2_x, u2_y); diff_energy += w_node_edge_dist / d_ev; } /* All other nodes from all of v's incident edges */ igraph_incident(graph, &neis, v, IGRAPH_ALL); no = igraph_vector_size(&neis); for (e = 0; e < no; e++) { igraph_integer_t mye = VECTOR(neis)[e]; igraph_integer_t u = IGRAPH_OTHER(graph, mye, v); float u_x = MATRIX(*res, u, 0); float u_y = MATRIX(*res, u, 1); igraph_integer_t w; for (w = 0; w < no_nodes; w++) { float w_x, w_y, d_ev; if (w == v || w == u) { continue; } w_x = MATRIX(*res, w, 0); w_y = MATRIX(*res, w, 1); d_ev = igraph_i_point_segment_dist2(w_x, w_y, old_x, old_y, u_x, u_y); diff_energy -= w_node_edge_dist / d_ev; d_ev = igraph_i_point_segment_dist2(w_x, w_y, new_x, new_y, u_x, u_y); diff_energy += w_node_edge_dist / d_ev; } } } /* w_node_edge_dist != 0 && fine_tuning */ if (diff_energy < 0 || (!fine_tuning && RNG_UNIF01() < exp(-diff_energy / move_radius))) { MATRIX(*res, v, 0) = new_x; MATRIX(*res, v, 1) = new_y; if (new_x < min_x) { min_x = new_x; } else if (new_x > max_x) { max_x = new_x; } if (new_y < min_y) { min_y = new_y; } else if (new_y > max_y) { max_y = new_y; } } } /* t < no_tries */ } /* p < no_nodes */ move_radius *= cool_fact; } /* round < maxiter */ RNG_END(); igraph_vector_destroy(&neis); igraph_vector_int_destroy(&try_idx); igraph_vector_float_destroy(&try_x); igraph_vector_float_destroy(&try_y); igraph_vector_int_destroy(&perm); IGRAPH_FINALLY_CLEAN(5); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/pottsmodel_2.cpp0000644000076500000240000024541313614300625024526 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ /* The original version of this file was written by Jörg Reichardt This file was modified by Vincent Traag The original copyright notice follows here */ /*************************************************************************** pottsmodel.cpp - description ------------------- begin : Fri May 28 2004 copyright : (C) 2004 by email : ***************************************************************************/ /*************************************************************************** * * * This program is free software; you can redistribute it and/or modify * * it under the terms of the GNU General Public License as published by * * the Free Software Foundation; either version 2 of the License, or * * (at your option) any later version. * * * ***************************************************************************/ #include #include #include #include #include "pottsmodel_2.h" #include "NetRoutines.h" using namespace std; #include "igraph_random.h" #include "igraph_interrupt_internal.h" #include "config.h" //################################################################################################# PottsModel::PottsModel(network *n, unsigned int qvalue, int m) : acceptance(0) { DLList_Iter iter; NNode *n_cur; unsigned int *i_ptr; net = n; q = qvalue; operation_mode = m; k_max = 0; //needed in calculating modularity Qa = new double[q + 1]; //weights for each spin state needed in Monte Carlo process weights = new double[q + 1]; //bookkeeping of occupation numbers of spin states or the number of links in community color_field = new double[q + 1]; neighbours = new double[q + 1]; num_of_nodes = net->node_list->Size(); num_of_links = net->link_list->Size(); n_cur = iter.First(net->node_list); //these lists are needed to keep track of spin states for parallel update mode new_spins = new DL_Indexed_List(); previous_spins = new DL_Indexed_List(); while (!iter.End()) { if (k_max < n_cur->Get_Degree()) { k_max = n_cur->Get_Degree(); } i_ptr = new unsigned int; *i_ptr = 0; new_spins->Push(i_ptr); i_ptr = new unsigned int; *i_ptr = 0; previous_spins->Push(i_ptr); n_cur = iter.Next(); } return; } //####################################################### //Destructor of PottsModel //######################################################## PottsModel::~PottsModel() { /* The DLItem destructor does not delete its item currently, because of some bad design. As a workaround, we delete them here by hand */ new_spins->delete_items(); previous_spins->delete_items(); delete new_spins; delete previous_spins; delete [] Qa; delete [] weights; delete [] color_field; delete [] neighbours; return; } //##################################################### //Assing an initial random configuration of spins to nodes //if called with negative argument or the spin used as argument //when called with positve one. //This may be handy, if you want to warm up the network. //#################################################### unsigned long PottsModel::assign_initial_conf(int spin) { int s; DLList_Iter iter; DLList_Iter l_iter; NNode *n_cur; NLink *l_cur; double sum_weight; double av_k_squared = 0.0; double av_k = 0.0; // printf("Assigning initial configuration...\n"); // initialize colorfield for (unsigned int i = 0; i <= q; i++) { color_field[i] = 0.0; } // total_degree_sum = 0.0; n_cur = iter.First(net->node_list); while (!iter.End()) { if (spin < 0) { s = RNG_INTEGER(1, q); } else { s = spin; } n_cur->Set_ClusterIndex(s); l_cur = l_iter.First(n_cur->Get_Links()); sum_weight = 0; while (!l_iter.End()) { sum_weight += l_cur->Get_Weight(); //weight should be one, in case we are not using it. l_cur = l_iter.Next(); } // we set the sum of the weights or the degree as the weight of the node, this way // we do not have to calculate it again. n_cur->Set_Weight(sum_weight); av_k_squared += sum_weight * sum_weight; av_k += sum_weight; // in case we want all links to be contribute equally - parameter gamm=fixed if (operation_mode == 0) { color_field[s]++; } else { color_field[s] += sum_weight; } // or in case we want to use a weight of each link that is proportional to k_i\times k_j total_degree_sum += sum_weight; n_cur = iter.Next(); } av_k_squared /= double(net->node_list->Size()); av_k /= double(net->node_list->Size()); // total_degree_sum-=av_k_squared/av_k; // printf("Total Degree Sum=2M=%f\n",total_degree_sum); return net->node_list->Size(); } //##################################################################### //If I ever manage to write a decent LookUp function, it will be here //##################################################################### unsigned long PottsModel::initialize_lookup(double kT, double gamma) { IGRAPH_UNUSED(kT); IGRAPH_UNUSED(gamma); /* double beta; // the look-up table contains all entries of exp(-beta(-neighbours+gamma*h)) // as needed in the HeatBath algorithm beta=1.0/kT; for (long w=0; w<=k_max+num_of_nodes; w++) { neg_lookup[w]=exp(-beta*-w } delta_ij[0]=1.0; for (long w=-num_of_nodes-k_max; w<=k_max+num_of_nodes; w++) { } // wenn wir spaeter exp(-1/kT*gamma*(nk+1-nj) fuer eine spin-flip von j nach k benoetigen schauen wir nur noch hier nach for (unsigned long n=1; n<=num_of_nodes; n++) { gamma_term[n]=exp(-double(n)/kT*gamma); } gamma_term[0]=1.0; */ return 1; } //##################################################################### // Q denotes the modulary of the network // This function calculates it initially // In the event of a spin changing its state, it only needs updating // Note that Qmatrix and Qa are only counting! The normalization // by num_of_links is done later //#################################################################### double PottsModel::initialize_Qmatrix(void) { DLList_Iter l_iter; NLink *l_cur; unsigned int i, j; //initialize with zeros num_of_links = net->link_list->Size(); for (i = 0; i <= q; i++) { Qa[i] = 0.0; for (j = i; j <= q; j++) { Qmatrix[i][j] = 0.0; Qmatrix[j][i] = 0.0; } } //go over all links and make corresponding entries in Q matrix //An edge connecting state i wiht state j will get an entry in Qij and Qji l_cur = l_iter.First(net->link_list); while (!l_iter.End()) { i = l_cur->Get_Start()->Get_ClusterIndex(); j = l_cur->Get_End()->Get_ClusterIndex(); //printf("%d %d\n",i,j); Qmatrix[i][j] += l_cur->Get_Weight(); Qmatrix[j][i] += l_cur->Get_Weight(); l_cur = l_iter.Next(); } //Finally, calculate sum over rows and keep in Qa for (i = 0; i <= q; i++) { for (j = 0; j <= q; j++) { Qa[i] += Qmatrix[i][j]; } } return calculate_Q(); } //#################################################################### // This function does the actual calculation of Q from the matrix // The normalization by num_of_links is done here //#################################################################### double PottsModel::calculate_Q() { double Q = 0.0; for (unsigned int i = 0; i <= q; i++) { Q += Qmatrix[i][i] - Qa[i] * Qa[i] / double(2.0 * net->sum_weights); if ((Qa[i] < 0.0) || Qmatrix[i][i] < 0.0) { // printf("Negatives Qa oder Qii\n\n\n"); //printf("Press any key to continue\n\n"); //cin >> Q; } } Q /= double(2.0 * net->sum_weights); return Q; } double PottsModel::calculate_genQ(double gamma) { double Q = 0.0; for (unsigned int i = 0; i <= q; i++) { Q += Qmatrix[i][i] - gamma * Qa[i] * Qa[i] / double(2.0 * net->sum_weights); if ((Qa[i] < 0.0) || Qmatrix[i][i] < 0.0) { // printf("Negatives Qa oder Qii\n\n\n"); //printf("Press any key to continue\n\n"); //cin >> Q; } } Q /= double(2.0 * net->sum_weights); return Q; } //####################################################################### // This function calculates the Energy for the standard Hamiltonian // given a particular value of gamma and the current spin states // ##################################################################### double PottsModel::calculate_energy(double gamma) { double e = 0.0; DLList_Iter l_iter; NLink *l_cur; l_cur = l_iter.First(net->link_list); //every in-cluster edge contributes -1 while (!l_iter.End()) { if (l_cur->Get_Start()->Get_ClusterIndex() == l_cur->Get_End()->Get_ClusterIndex()) { e--; }; l_cur = l_iter.Next(); } //and the penalty term contributes according to cluster sizes for (unsigned int i = 1; i <= q; i++) { e += gamma * 0.5 * double(color_field[i]) * double((color_field[i] - 1)); } energy = e; return e; } //########################################################################## // We would like to start from a temperature with at least 95 of all proposed // spin changes accepted in 50 sweeps over the network // The function returns the Temperature found //######################################################################### double PottsModel::FindStartTemp(double gamma, double prob, double ts) { double kT; kT = ts; //assing random initial condition assign_initial_conf(-1); //initialize Modularity matrix, from now on, it will be updated at every spin change initialize_Qmatrix(); // the factor 1-1/q is important, since even, at infinite temperature, // only 1-1/q of all spins do change their state, since a randomly chooses new // state is with prob. 1/q the old state. while (acceptance < (1.0 - 1.0 / double(q)) * 0.95) { //want 95% acceptance kT = kT * 1.1; // if I ever have a lookup table, it will need initialization for every kT //initialize_lookup(kT,k_max,net->node_list->Size()); HeatBathParallelLookup(gamma, prob, kT, 50); // printf("kT=%f acceptance=%f\n", kT, acceptance); } kT *= 1.1; // just to be sure... // printf("Starting with acceptance ratio: %1.6f bei kT=%2.4f\n",acceptance,kT); return kT; } //############################################################## //This function does a parallel update at zero T //Hence, it is really fast on easy problems //max sweeps is the maximum number of sweeps it should perform, //if it does not converge earlier //############################################################## long PottsModel::HeatBathParallelLookupZeroTemp(double gamma, double prob, unsigned int max_sweeps) { DLList_Iter iter, net_iter; DLList_Iter l_iter; DLList_Iter i_iter, i_iter2; NNode *node, *n_cur; NLink *l_cur; unsigned int *SPIN, *P_SPIN, new_spin, spin_opt, old_spin, spin, sweep; // long h; // degree; unsigned long changes; double h, delta = 0, deltaE, deltaEmin, w, degree; //HugeArray neighbours; bool cyclic = 0; sweep = 0; changes = 1; while (sweep < max_sweeps && changes) { cyclic = true; sweep++; changes = 0; //Loop over all nodes node = net_iter.First(net->node_list); SPIN = i_iter.First(new_spins); while (!net_iter.End()) { // How many neigbors of each type? // set them all zero for (unsigned int i = 0; i <= q; i++) { neighbours[i] = 0; } degree = node->Get_Weight(); //Loop over all links (=neighbours) l_cur = l_iter.First(node->Get_Links()); while (!l_iter.End()) { //printf("%s %s\n",node->Get_Name(),n_cur->Get_Name()); w = l_cur->Get_Weight(); if (node == l_cur->Get_Start()) { n_cur = l_cur->Get_End(); } else { n_cur = l_cur->Get_Start(); } neighbours[n_cur->Get_ClusterIndex()] += w; l_cur = l_iter.Next(); } //Search optimal Spin old_spin = node->Get_ClusterIndex(); //degree=node->Get_Degree(); switch (operation_mode) { case 0: { delta = 1.0; break; } case 1: { //newman modularity prob = degree / total_degree_sum; delta = degree; break; } } spin_opt = old_spin; deltaEmin = 0.0; for (spin = 1; spin <= q; spin++) { // all possible spin states if (spin != old_spin) { h = color_field[spin] + delta - color_field[old_spin]; deltaE = double(neighbours[old_spin] - neighbours[spin]) + gamma * prob * double(h); if (deltaE < deltaEmin) { spin_opt = spin; deltaEmin = deltaE; } } } // for spin //Put optimal spin on list for later update *SPIN = spin_opt; node = net_iter.Next(); SPIN = i_iter.Next(); } // while !net_iter.End() //------------------------------- //Now set all spins to new values node = net_iter.First(net->node_list); SPIN = i_iter.First(new_spins); P_SPIN = i_iter2.First(previous_spins); while (!net_iter.End()) { old_spin = node->Get_ClusterIndex(); new_spin = *SPIN; if (new_spin != old_spin) { // Do we really have a change?? changes++; node->Set_ClusterIndex(new_spin); //this is important!! //In Parallel update, there occur cyclic attractors of size two //which then make the program run for ever if (new_spin != *P_SPIN) { cyclic = false; } *P_SPIN = old_spin; color_field[old_spin]--; color_field[new_spin]++; //Qmatrix update //iteration over all neighbours l_cur = l_iter.First(node->Get_Links()); while (!l_iter.End()) { w = l_cur->Get_Weight(); if (node == l_cur->Get_Start()) { n_cur = l_cur->Get_End(); } else { n_cur = l_cur->Get_Start(); } Qmatrix[old_spin][n_cur->Get_ClusterIndex()] -= w; Qmatrix[new_spin][n_cur->Get_ClusterIndex()] += w; Qmatrix[n_cur->Get_ClusterIndex()][old_spin] -= w; Qmatrix[n_cur->Get_ClusterIndex()][new_spin] += w; Qa[old_spin] -= w; Qa[new_spin] += w; l_cur = l_iter.Next(); } // while l_iter } node = net_iter.Next(); SPIN = i_iter.Next(); P_SPIN = i_iter2.Next(); } // while (!net_iter.End()) } // while markov // In case of a cyclic attractor, we want to interrupt if (cyclic) { // printf("Cyclic attractor!\n"); acceptance = 0.0; return 0; } else { acceptance = double(changes) / double(num_of_nodes); return changes; } } //################################################################################### //The same function as before, but rather than parallel update, it pics the nodes to update //randomly //################################################################################### double PottsModel::HeatBathLookupZeroTemp(double gamma, double prob, unsigned int max_sweeps) { DLList_Iter iter; DLList_Iter l_iter; DLList_Iter i_iter, i_iter2; NNode *node, *n_cur; NLink *l_cur; unsigned int new_spin, spin_opt, old_spin, spin, sweep; long r;// degree; unsigned long changes; double delta = 0, h, deltaE, deltaEmin, w, degree; //HugeArray neighbours; sweep = 0; changes = 0; while (sweep < max_sweeps) { sweep++; //ueber alle Knoten im Netz for (unsigned long n = 0; n < num_of_nodes; n++) { r = -1; while ((r < 0) || (r > (long)num_of_nodes - 1)) { r = RNG_INTEGER(0, num_of_nodes - 1); } /* r=long(double(num_of_nodes*double(rand())/double(RAND_MAX+1.0)));*/ node = net->node_list->Get(r); // Wir zaehlen, wieviele Nachbarn von jedem spin vorhanden sind // erst mal alles Null setzen for (unsigned int i = 0; i <= q; i++) { neighbours[i] = 0; } degree = node->Get_Weight(); //Loop over all links (=neighbours) l_cur = l_iter.First(node->Get_Links()); while (!l_iter.End()) { //printf("%s %s\n",node->Get_Name(),n_cur->Get_Name()); w = l_cur->Get_Weight(); if (node == l_cur->Get_Start()) { n_cur = l_cur->Get_End(); } else { n_cur = l_cur->Get_Start(); } neighbours[n_cur->Get_ClusterIndex()] += w; l_cur = l_iter.Next(); } //Search optimal Spin old_spin = node->Get_ClusterIndex(); //degree=node->Get_Degree(); switch (operation_mode) { case 0: { delta = 1.0; break; } case 1: { //newman modularity prob = degree / total_degree_sum; delta = degree; break; } } spin_opt = old_spin; deltaEmin = 0.0; for (spin = 1; spin <= q; spin++) { // alle moeglichen Spins if (spin != old_spin) { h = color_field[spin] + delta - color_field[old_spin]; deltaE = double(neighbours[old_spin] - neighbours[spin]) + gamma * prob * double(h); if (deltaE < deltaEmin) { spin_opt = spin; deltaEmin = deltaE; } } } // for spin //------------------------------- //Now update the spins new_spin = spin_opt; if (new_spin != old_spin) { // Did we really change something?? changes++; node->Set_ClusterIndex(new_spin); color_field[old_spin] -= delta; color_field[new_spin] += delta; //Qmatrix update //iteration over all neighbours l_cur = l_iter.First(node->Get_Links()); while (!l_iter.End()) { w = l_cur->Get_Weight(); if (node == l_cur->Get_Start()) { n_cur = l_cur->Get_End(); } else { n_cur = l_cur->Get_Start(); } Qmatrix[old_spin][n_cur->Get_ClusterIndex()] -= w; Qmatrix[new_spin][n_cur->Get_ClusterIndex()] += w; Qmatrix[n_cur->Get_ClusterIndex()][old_spin] -= w; Qmatrix[n_cur->Get_ClusterIndex()][new_spin] += w; Qa[old_spin] -= w; Qa[new_spin] += w; l_cur = l_iter.Next(); } // while l_iter } } // for n } // while markov acceptance = double(changes) / double(num_of_nodes) / double(sweep); return acceptance; } //##################################################################################### //This function performs a parallel update at Terperature T //##################################################################################### long PottsModel::HeatBathParallelLookup(double gamma, double prob, double kT, unsigned int max_sweeps) { DLList_Iter iter, net_iter; DLList_Iter l_iter; DLList_Iter i_iter, i_iter2; NNode *node, *n_cur; NLink *l_cur; unsigned int new_spin, spin_opt, old_spin; unsigned int *SPIN, *P_SPIN; unsigned int sweep; long max_q; unsigned long changes, /*degree,*/ problemcount; //HugeArray neighbours; double h, delta = 0, norm, r, beta, minweight, prefac = 0, w, degree; bool cyclic = 0, found; unsigned long num_of_nodes; sweep = 0; changes = 1; num_of_nodes = net->node_list->Size(); while (sweep < max_sweeps && changes) { cyclic = true; sweep++; changes = 0; //Loop over all nodes node = net_iter.First(net->node_list); SPIN = i_iter.First(new_spins); while (!net_iter.End()) { // Initialize neighbours and weights problemcount = 0; for (unsigned int i = 0; i <= q; i++) { neighbours[i] = 0; weights[i] = 0; } norm = 0.0; degree = node->Get_Weight(); //Loop over all links (=neighbours) l_cur = l_iter.First(node->Get_Links()); while (!l_iter.End()) { //printf("%s %s\n",node->Get_Name(),n_cur->Get_Name()); w = l_cur->Get_Weight(); if (node == l_cur->Get_Start()) { n_cur = l_cur->Get_End(); } else { n_cur = l_cur->Get_Start(); } neighbours[n_cur->Get_ClusterIndex()] += w; l_cur = l_iter.Next(); } //Search optimal Spin old_spin = node->Get_ClusterIndex(); //degree=node->Get_Degree(); switch (operation_mode) { case 0: { prefac = 1.0; delta = 1.0; break; } case 1: { //newman modularity prefac = 1.0; prob = degree / total_degree_sum; delta = degree; break; } } spin_opt = old_spin; beta = 1.0 / kT * prefac; minweight = 0.0; weights[old_spin] = 0.0; for (unsigned spin = 1; spin <= q; spin++) { // loop over all possible new spins if (spin != old_spin) { // only if we have a different than old spin! h = color_field[spin] + delta - color_field[old_spin]; weights[spin] = double(neighbours[old_spin] - neighbours[spin]) + gamma * prob * double(h); if (weights[spin] < minweight) { minweight = weights[spin]; } } } // for spin for (unsigned spin = 1; spin <= q; spin++) { // loop over all possibe spins weights[spin] -= minweight; // subtract minweight // to avoid numerical problems with large exponents weights[spin] = exp(-beta * weights[spin]); norm += weights[spin]; } // for spin //now choose a new spin r = RNG_UNIF(0, norm); /* norm*double(rand())/double(RAND_MAX + 1.0); */ new_spin = 1; found = false; while (!found && new_spin <= q) { if (r <= weights[new_spin]) { spin_opt = new_spin; found = true; break; } else { r -= weights[new_spin]; } new_spin++; } if (!found) { // printf("."); problemcount++; } //Put new spin on list *SPIN = spin_opt; node = net_iter.Next(); SPIN = i_iter.Next(); } // while !net_iter.End() //------------------------------- //now update all spins node = net_iter.First(net->node_list); SPIN = i_iter.First(new_spins); P_SPIN = i_iter2.First(previous_spins); while (!net_iter.End()) { old_spin = node->Get_ClusterIndex(); new_spin = *SPIN; if (new_spin != old_spin) { // Did we really change something?? changes++; node->Set_ClusterIndex(new_spin); if (new_spin != *P_SPIN) { cyclic = false; } *P_SPIN = old_spin; color_field[old_spin] -= delta; color_field[new_spin] += delta; //Qmatrix update //iteration over all neighbours l_cur = l_iter.First(node->Get_Links()); while (!l_iter.End()) { w = l_cur->Get_Weight(); if (node == l_cur->Get_Start()) { n_cur = l_cur->Get_End(); } else { n_cur = l_cur->Get_Start(); } Qmatrix[old_spin][n_cur->Get_ClusterIndex()] -= w; Qmatrix[new_spin][n_cur->Get_ClusterIndex()] += w; Qmatrix[n_cur->Get_ClusterIndex()][old_spin] -= w; Qmatrix[n_cur->Get_ClusterIndex()][new_spin] += w; Qa[old_spin] -= w; Qa[new_spin] += w; l_cur = l_iter.Next(); } // while l_iter } node = net_iter.Next(); SPIN = i_iter.Next(); P_SPIN = i_iter2.Next(); } // while (!net_iter.End()) } // while markov max_q = 0; for (unsigned int i = 1; i <= q; i++) if (color_field[i] > max_q) { max_q = long(color_field[i]); } //again, we would not like to end up in cyclic attractors if (cyclic && changes) { // printf("Cyclic attractor!\n"); acceptance = double(changes) / double(num_of_nodes); return 0; } else { acceptance = double(changes) / double(num_of_nodes); return changes; } } //############################################################## // This is the function generally used for optimisation, // as the parallel update has its flaws, due to the cyclic attractors //############################################################## double PottsModel::HeatBathLookup(double gamma, double prob, double kT, unsigned int max_sweeps) { DLList_Iter iter; DLList_Iter l_iter; DLList_Iter i_iter, i_iter2; NNode *node, *n_cur; NLink *l_cur; unsigned int new_spin, spin_opt, old_spin; unsigned int sweep; long max_q, rn; unsigned long changes, /*degree,*/ problemcount; double degree, w, delta = 0, h; //HugeArray neighbours; double norm, r, beta, minweight, prefac = 0; bool found; long int num_of_nodes; sweep = 0; changes = 0; num_of_nodes = net->node_list->Size(); while (sweep < max_sweeps) { sweep++; //loop over all nodes in network for (int n = 0; n < num_of_nodes; n++) { rn = -1; while ((rn < 0) || (rn > num_of_nodes - 1)) { rn = RNG_INTEGER(0, num_of_nodes - 1); } /* rn=long(double(num_of_nodes*double(rand())/double(RAND_MAX+1.0))); */ node = net->node_list->Get(rn); // initialize the neighbours and the weights problemcount = 0; for (unsigned int i = 0; i <= q; i++) { neighbours[i] = 0.0; weights[i] = 0.0; } norm = 0.0; degree = node->Get_Weight(); //Loop over all links (=neighbours) l_cur = l_iter.First(node->Get_Links()); while (!l_iter.End()) { //printf("%s %s\n",node->Get_Name(),n_cur->Get_Name()); w = l_cur->Get_Weight(); if (node == l_cur->Get_Start()) { n_cur = l_cur->Get_End(); } else { n_cur = l_cur->Get_Start(); } neighbours[n_cur->Get_ClusterIndex()] += w; l_cur = l_iter.Next(); } //Look for optimal spin old_spin = node->Get_ClusterIndex(); //degree=node->Get_Degree(); switch (operation_mode) { case 0: { prefac = 1.0; delta = 1.0; break; } case 1: {//newman modularity prefac = 1.0; prob = degree / total_degree_sum; delta = degree; break; } } spin_opt = old_spin; beta = 1.0 / kT * prefac; minweight = 0.0; weights[old_spin] = 0.0; for (unsigned spin = 1; spin <= q; spin++) { // all possible new spins if (spin != old_spin) { // except the old one! h = color_field[spin] - (color_field[old_spin] - delta); weights[spin] = neighbours[old_spin] - neighbours[spin] + gamma * prob * h; if (weights[spin] < minweight) { minweight = weights[spin]; } } } // for spin for (unsigned spin = 1; spin <= q; spin++) { // all possible new spins weights[spin] -= minweight; // subtract minweigt // for numerical stability weights[spin] = exp(-beta * weights[spin]); norm += weights[spin]; } // for spin //choose a new spin /* r = norm*double(rand())/double(RAND_MAX + 1.0); */ r = RNG_UNIF(0, norm); new_spin = 1; found = false; while (!found && new_spin <= q) { if (r <= weights[new_spin]) { spin_opt = new_spin; found = true; break; } else { r -= weights[new_spin]; } new_spin++; } if (!found) { // printf("."); problemcount++; } //------------------------------- //now set the new spin new_spin = spin_opt; if (new_spin != old_spin) { // Did we really change something?? changes++; node->Set_ClusterIndex(new_spin); color_field[old_spin] -= delta; color_field[new_spin] += delta; //Qmatrix update //iteration over all neighbours l_cur = l_iter.First(node->Get_Links()); while (!l_iter.End()) { w = l_cur->Get_Weight(); if (node == l_cur->Get_Start()) { n_cur = l_cur->Get_End(); } else { n_cur = l_cur->Get_Start(); } Qmatrix[old_spin][n_cur->Get_ClusterIndex()] -= w; Qmatrix[new_spin][n_cur->Get_ClusterIndex()] += w; Qmatrix[n_cur->Get_ClusterIndex()][old_spin] -= w; Qmatrix[n_cur->Get_ClusterIndex()][new_spin] += w; Qa[old_spin] -= w; Qa[new_spin] += w; l_cur = l_iter.Next(); } // while l_iter } } // for n } // while markov max_q = 0; for (unsigned int i = 1; i <= q; i++) if (color_field[i] > max_q) { max_q = long(color_field[i] + 0.5); } acceptance = double(changes) / double(num_of_nodes) / double(sweep); return acceptance; } //############################################################################################### //# Here we try to minimize the affinity to the rest of the network //############################################################################################### double PottsModel::FindCommunityFromStart(double gamma, double prob, char *nodename, igraph_vector_t *result, igraph_real_t *cohesion, igraph_real_t *adhesion, igraph_integer_t *my_inner_links, igraph_integer_t *my_outer_links) { DLList_Iter iter, iter2; DLList_Iter l_iter; DLList* to_do; DLList* community; NNode *start_node = 0, *n_cur, *neighbor, *max_aff_node, *node; NLink *l_cur; bool found = false, add = false, remove = false; double degree, delta_aff_add, delta_aff_rem, max_delta_aff, Ks = 0.0, Kr = 0, kis, kir, w; long community_marker = 5; long to_do_marker = 10; double inner_links = 0, outer_links = 0, aff_r, aff_s; IGRAPH_UNUSED(prob); to_do = new DLList; community = new DLList; // find the node in the network n_cur = iter.First(net->node_list); while (!found && !iter.End()) { if (0 == strcmp(n_cur->Get_Name(), nodename)) { start_node = n_cur; found = true; start_node->Set_Affinity(0.0); community->Push(start_node); start_node->Set_Marker(community_marker); Ks = start_node->Get_Weight(); Kr = total_degree_sum - start_node->Get_Weight(); } n_cur = iter.Next(); } if (!found) { // printf("%s not found found. Aborting.\n",nodename); // fprintf(file,"%s not found found. Aborting.\n",nodename); delete to_do; delete community; return -1; } //############################# // initialize the to_do list and community with the neighbours of start node //############################# neighbor = iter.First(start_node->Get_Neighbours()); while (!iter.End()) { // printf("Adding node %s to comunity.\n",neighbor->Get_Name()); community->Push(neighbor); neighbor->Set_Marker(community_marker); Ks += neighbor->Get_Weight(); Kr -= neighbor->Get_Weight(); neighbor = iter.Next(); } node = iter.First(community); while (!iter.End()) { //now add at the second neighbors to the to_do list neighbor = iter2.First(node->Get_Neighbours()); while (!iter2.End()) { if ((long)neighbor->Get_Marker() != community_marker && (long)neighbor->Get_Marker() != to_do_marker) { to_do->Push(neighbor); neighbor->Set_Marker(to_do_marker); // printf("Adding node %s to to_do list.\n",neighbor->Get_Name()); } neighbor = iter2.Next(); } node = iter.Next(); } //############# //repeat, as long as we are still adding nodes to the communtiy //############# add = true; remove = true; while (add || remove) { //############################# //calculate the affinity changes of all nodes for adding every node in the to_do list to the community //############################## IGRAPH_ALLOW_INTERRUPTION(); /* This is not clean.... */ max_delta_aff = 0.0; max_aff_node = NULL; add = false; node = iter.First(to_do); while (!iter.End()) { //printf("Checking Links of %s\n",node->Get_Name()); degree = node->Get_Weight(); kis = 0.0; kir = 0.0; // For every of the neighbors, check, count the links to the community l_cur = l_iter.First(node->Get_Links()); while (!l_iter.End()) { w = l_cur->Get_Weight(); if (node == l_cur->Get_Start()) { n_cur = l_cur->Get_End(); } else { n_cur = l_cur->Get_Start(); } if ((long)n_cur->Get_Marker() == community_marker) { kis += w; //the weight/number of links to the community } else { kir += w; //the weight/number of links to the rest of the network } l_cur = l_iter.Next(); } aff_r = kir - gamma / total_degree_sum * (Kr - degree) * degree; aff_s = kis - gamma / total_degree_sum * Ks * degree; delta_aff_add = aff_r - aff_s; // if (aff_s>=aff_r && delta_aff_add<=max_delta_aff) { if (delta_aff_add <= max_delta_aff) { node->Set_Affinity(aff_s); max_delta_aff = delta_aff_add; max_aff_node = node; add = true; } //printf("%s in to_do list with affinity %f\n",node->Get_Name(),node->Get_Affinity()); node = iter.Next(); } //################ //calculate the affinity changes for removing every single node from the community //################ inner_links = 0; outer_links = 0; remove = false; node = iter.First(community); while (!iter.End()) { //printf("Checking Links of %s\n",node->Get_Name()); degree = node->Get_Weight(); kis = 0.0; kir = 0.0; // For every of the neighbors, check, count the links to the community l_cur = l_iter.First(node->Get_Links()); while (!l_iter.End()) { w = l_cur->Get_Weight(); if (node == l_cur->Get_Start()) { n_cur = l_cur->Get_End(); } else { n_cur = l_cur->Get_Start(); } if ((long)n_cur->Get_Marker() == community_marker) { kis += w; inner_links += w; //summing all w gives twice the number of inner links(weights) } else { kir += w; outer_links += w; } l_cur = l_iter.Next(); } // if (kir+kis!=degree) { printf("error kir=%f\tkis=%f\tk=%f\n",kir,kis,degree); } aff_r = kir - gamma / total_degree_sum * Kr * degree; aff_s = kis - gamma / total_degree_sum * (Ks - degree) * degree; delta_aff_rem = aff_s - aff_r; node->Set_Affinity(aff_s); // we should not remove the nodes, we have just added if (delta_aff_rem < max_delta_aff) { max_delta_aff = delta_aff_rem ; max_aff_node = node; remove = true; add = false; } //printf("%s in to_do list with affinity %f\n",node->Get_Name(),node->Get_Affinity()); node = iter.Next(); } inner_links = inner_links * 0.5; //################ // Now check, whether we want to remove or add a node //################ if (add) { //################ //add the node of maximum affinity to the community //############### community->Push(max_aff_node); max_aff_node->Set_Marker(community_marker); //delete node from to_do to_do->fDelete(max_aff_node); //update the sum of degrees in the community Ks += max_aff_node->Get_Weight(); Kr -= max_aff_node->Get_Weight(); // printf("Adding node %s to community with affinity of %f delta_aff: %f.\n",max_aff_node->Get_Name(), max_aff_node->Get_Affinity(),max_delta_aff); //now add all neighbors of this node, that are not already //in the to_do list or in the community neighbor = iter.First(max_aff_node->Get_Neighbours()); while (!iter.End()) { if ((long)neighbor->Get_Marker() != community_marker && (long)neighbor->Get_Marker() != to_do_marker) { to_do->Push(neighbor); neighbor->Set_Marker(to_do_marker); //printf("Adding node %s to to_do list.\n",neighbor->Get_Name()); } neighbor = iter.Next(); } } if (remove) { //################ //remove those with negative affinities //################ community->fDelete(max_aff_node); max_aff_node->Set_Marker(to_do_marker); //update the sum of degrees in the community Ks -= max_aff_node->Get_Weight(); Kr += max_aff_node->Get_Weight(); //add the node to to_do again to_do->Push(max_aff_node); // printf("Removing node %s from community with affinity of %f delta_aff: %f.\n",max_aff_node->Get_Name(), max_aff_node->Get_Affinity(),max_delta_aff); } IGRAPH_ALLOW_INTERRUPTION(); /* This is not clean.... */ } //################### //write the node in the community to a file //################### // TODO return this instead of writing it // fprintf(file,"Number_of_nodes:\t%d\n",community->Size()); // fprintf(file,"Inner_Links:\t%f\n",inner_links); // fprintf(file,"Outer_Links:\t%f\n",Ks-2*inner_links); // fprintf(file,"Cohesion:\t%f\n",inner_links-gamma/total_degree_sum*Ks*Ks*0.5); // fprintf(file,"Adhesion:\t%f\n",outer_links-gamma/total_degree_sum*Ks*Kr); // fprintf(file,"\n"); if (cohesion) { *cohesion = inner_links - gamma / total_degree_sum * Ks * Ks * 0.5; } if (adhesion) { *adhesion = outer_links - gamma / total_degree_sum * Ks * Kr; } if (my_inner_links) { *my_inner_links = inner_links; } if (my_outer_links) { *my_outer_links = outer_links; } if (result) { node = iter.First(community); igraph_vector_resize(result, 0); while (!iter.End()) { // printf("%s in community.\n",node->Get_Name()); // fprintf(file,"%s\t%f\n",node->Get_Name(),node->Get_Affinity()); IGRAPH_CHECK(igraph_vector_push_back(result, node->Get_Index())); node = iter.Next(); } } // printf("%d nodes in community around %s\n",community->Size(),start_node->Get_Name()); // fclose(file); unsigned int size = community->Size(); delete to_do; delete community; return size; } //################################################################################################ // this Function writes the clusters to disk //################################################################################################ long PottsModel::WriteClusters(igraph_real_t *modularity, igraph_real_t *temperature, igraph_vector_t *csize, igraph_vector_t *membership, double kT, double gamma) { NNode *n_cur, *n_cur2; /* double a1,a2,a3,p,p1,p2; long n,N,lin,lout; */ DLList_Iter iter, iter2; HugeArray inner_links; HugeArray outer_links; HugeArray nodes; //den Header schreiben // p=2.0*double(num_of_links)/double(num_of_nodes)/double(num_of_nodes-1); // fprintf(file," Nodes=\t%lu\n",num_of_nodes); // fprintf(file," Links=\t%lu\n",num_of_links); // fprintf(file," q=\t%d\n",q); // fprintf(file," p=\t%f\n",p); // fprintf(file," Modularity=\t%f\n",calculate_Q()); // fprintf(file,"Temperature=\t%f\n", kT); // fprintf(file,"Cluster\tNodes\tInnerLinks\tOuterLinks\tp_in\tp_out\t\n"); if (temperature) { *temperature = kT; } if (csize || membership || modularity) { // TODO: count the number of clusters for (unsigned int spin = 1; spin <= q; spin++) { inner_links[spin] = 0; outer_links[spin] = 0; nodes[spin] = 0; n_cur = iter.First(net->node_list); while (!iter.End()) { if (n_cur->Get_ClusterIndex() == spin) { nodes[spin]++; n_cur2 = iter2.First(n_cur->Get_Neighbours()); while (!iter2.End()) { if (n_cur2->Get_ClusterIndex() == spin) { inner_links[spin]++; } else { outer_links[spin]++; } n_cur2 = iter2.Next(); } } n_cur = iter.Next(); } } } if (modularity) { *modularity = 0.0; for (unsigned int spin = 1; spin <= q; spin++) { if (nodes[spin] > 0) { double t1 = inner_links[spin] / net->sum_weights / 2.0; double t2 = (inner_links[spin] + outer_links[spin]) / net->sum_weights / 2.0; *modularity += t1; *modularity -= gamma * t2 * t2; } } } if (csize) { igraph_vector_resize(csize, 0); for (unsigned int spin = 1; spin <= q; spin++) { if (nodes[spin] > 0) { inner_links[spin] /= 2; // fprintf(file,"Cluster\tNodes\tInnerLinks\tOuterLinks\tp_in\tp_out\n"); /* N=num_of_nodes; n=nodes[spin]; lin=inner_links[spin]; lout=outer_links[spin]; a1=N*log((double)N)-n*log((double)n)*(N-n)*log((double)N-n); if ((lin==long(n*(n-1)*0.5+0.5)) || (n==1)) a2=0.0; else a2=(n*(n-1)*0.5 )*log((double)n*(n-1)*0.5 )-(n*(n-1)*0.5 )- (n*(n-1)*0.5-lin)*log((double)n*(n-1)*0.5-lin)+(n*(n-1)*0.5-lin)- lin*log((double)lin )+lin; */ /* if ((lout==n*(N-n)) || n==N) a3=0.0; else a3=(n*(N-n) )*log((double)n*(N-n) )-(n*(N-n))- (n*(N-n)-lout)*log((double)n*(N-n)-lout)+(n*(N-n)-lout)- lout*log((double)lout )+lout; */ /* p1=(lin+lout)*log((double)p); p2=(0.5*n*(n-1)-lin + n*(N-n)-lout)*log((double)1.0-p); */ // fprintf(file,"%d\t%d\t%d\t%d\t%f\t%f\t%f\n",spin,nodes[spin], inner_links[spin], outer_links[spin], p_in, p_out,log_num_exp); IGRAPH_CHECK(igraph_vector_push_back(csize, nodes[spin])); } } // fprintf(file,"\n"); } //die Elemente der Cluster if (membership) { long int no = -1; IGRAPH_CHECK(igraph_vector_resize(membership, num_of_nodes)); for (unsigned int spin = 1; spin <= q; spin++) { if (nodes[spin] > 0) { no++; } n_cur = iter.First(net->node_list); while (!iter.End()) { if (n_cur->Get_ClusterIndex() == spin) { // fprintf(file,"%d\t%s\n",spin,n_cur->Get_Name()); VECTOR(*membership)[ n_cur->Get_Index() ] = no; } n_cur = iter.Next(); } } } return num_of_nodes; } //################################################################################################ //This function writes the soft clusters after a gamma sweep //that is, it groups every node together that was found in // more than threshold percent together with the other node // in the same cluster //################################################################################################ // Does not work at the moment !!! //################################################################################################ // long PottsModel::WriteSoftClusters(char *filename, double threshold) // { // FILE *file; // NNode *n_cur, *n_cur2; // DLList_Iter iter, iter2; // DL_Indexed_List*> *cl_list, *old_clusterlist; // ClusterList *cl_cur; // double max; // file=fopen(filename,"w"); // if (!file) { // printf("Could not open %s for writing.\n",filename); // return -1; // } // max=correlation[0]->Get(0); // //printf("max=%f\n",max); // cl_list=new DL_Indexed_List*>(); // n_cur=iter.First(net->node_list); // while (!iter.End()) // { // cl_cur=new ClusterList(); // cl_list->Push(cl_cur); // n_cur2=iter2.First(net->node_list); // while (!iter2.End()) // { // if (double(correlation[n_cur->Get_Index()]->Get(n_cur2->Get_Index()))/max>threshold) // cl_cur->Push(n_cur2); // n_cur2=iter2.Next(); // } // n_cur=iter.Next(); // } // old_clusterlist=net->cluster_list; // net->cluster_list=cl_list; // clear_all_markers(net); // //printf("Es gibt %d Cluster\n",cl_list->Size()); // reduce_cliques2(net, false, 15); // //printf("Davon bleiben %d Cluster uebrig\n",cl_list->Size()); // clear_all_markers(net); // while (net->cluster_list->Size()){ // cl_cur=net->cluster_list->Pop(); // while (cl_cur->Size()) // { // n_cur=cl_cur->Pop(); // fprintf(file,"%s\n",n_cur->Get_Name()); // //printf("%s\n",n_cur->Get_Name()); // } // fprintf(file,"\n"); // } // net->cluster_list=old_clusterlist; // fclose(file); // return 1; // } //############################################################################# // Performs a gamma sweep //############################################################################# double PottsModel::GammaSweep(double gamma_start, double gamma_stop, double prob, unsigned int steps, bool non_parallel, int repetitions) { double stepsize; double kT, kT_start; long changes; double gamma, acc; NNode *n_cur, *n_cur2; DLList_Iter iter, iter2; stepsize = (gamma_stop - gamma_start) / double(steps); n_cur = iter.First(net->node_list); while (!iter.End()) { correlation[n_cur->Get_Index()] = new HugeArray(); n_cur2 = iter2.First(net->node_list); while (!iter2.End()) { correlation[n_cur->Get_Index()]->Set(n_cur->Get_Index()) = 0.0; n_cur2 = iter2.Next(); } n_cur = iter.Next(); } for (unsigned int n = 0; n <= steps; n++) { assign_initial_conf(-1); initialize_Qmatrix(); gamma = gamma_start + stepsize * n; kT = 0.5; acceptance = 0.5; while (acceptance < (1.0 - 1.0 / double(q)) * 0.95) { //wollen 95% Acceptance kT *= 1.1; //initialize_lookup(kT,kmax,net->node_list->Size()); if (!non_parallel) { HeatBathParallelLookup(gamma, prob, kT, 25); } else { HeatBathLookup(gamma, prob, kT, 25); } // printf("kT=%f acceptance=%f\n", kT, acceptance); } // printf("Starting with gamma=%f\n", gamma); kT_start = kT; for (int i = 0; i < repetitions; i++) { changes = 1; kT = kT_start; assign_initial_conf(-1); initialize_Qmatrix(); while ((changes > 0) && (kT > 0.01)) { kT = kT * 0.99; //initialize_lookup(kT,kmax,net->node_list->Size()); if (!non_parallel) { changes = HeatBathParallelLookup(gamma, prob, kT, 50); // printf("kT: %f \t Changes %li\n",kT, changes); } else { acc = HeatBathLookup(gamma, prob, kT, 50); if (acc > (1.0 - 1.0 / double(q)) * 0.01) { changes = 1; } else { changes = 0; } // printf("kT: %f Acceptance: %f\n",kT, acc); } } // printf("Finisched with acceptance: %1.6f bei kT=%2.4f und gamma=%2.4f\n",acceptance,kT, gamma); // fprintf(file,"%f\t%f\n",gamma_,acceptance); // fprintf(file2,"%f\t%f\n",gamma_,kT); // fprintf(file3,"%f\t%d\n",gamma_,count_clusters(5)); //Die Correlation berechnen n_cur = iter.First(net->node_list); while (!iter.End()) { n_cur2 = iter2.First(net->node_list); while (!iter2.End()) { if (n_cur->Get_ClusterIndex() == n_cur2->Get_ClusterIndex()) { correlation[n_cur->Get_Index()]->Set(n_cur2->Get_Index()) += 0.5; } n_cur2 = iter2.Next(); } n_cur = iter.Next(); } } // for i } //for n return kT; } //############################################################################# //Performs a Gamma sweep at zero T //############################################################################# double PottsModel::GammaSweepZeroTemp(double gamma_start, double gamma_stop, double prob, unsigned int steps, bool non_parallel, int repetitions) { double stepsize; long changes; double gamma, acc; long runs; NNode *n_cur, *n_cur2; DLList_Iter iter, iter2; stepsize = (gamma_stop - gamma_start) / double(steps); n_cur = iter.First(net->node_list); while (!iter.End()) { correlation[n_cur->Get_Index()] = new HugeArray(); n_cur2 = iter2.First(net->node_list); while (!iter2.End()) { correlation[n_cur->Get_Index()]->Set(n_cur->Get_Index()) = 0.0; n_cur2 = iter2.Next(); } n_cur = iter.Next(); } for (unsigned int n = 0; n <= steps; n++) { assign_initial_conf(-1); initialize_Qmatrix(); gamma = gamma_start + stepsize * n; // printf("Starting with gamma=%f\n", gamma); for (int i = 0; i < repetitions; i++) { changes = 1; assign_initial_conf(-1); initialize_Qmatrix(); runs = 0; while (changes > 0 && runs < 250) { //initialize_lookup(kT,kmax,net->node_list->Size()); if (!non_parallel) { changes = HeatBathParallelLookupZeroTemp(gamma, prob, 1); // printf("Changes %li\n", changes); } else { acc = HeatBathLookupZeroTemp(gamma, prob, 1); if (acc > (1.0 - 1.0 / double(q)) * 0.01) { changes = 1; } else { changes = 0; } // printf("Acceptance: %f\n", acc); } runs++; } // printf("Finisched with Modularity: %1.6f bei Gamma=%1.6f\n",calculate_Q(), gamma); // fprintf(file,"%f\t%f\n",gamma_,acceptance); // fprintf(file2,"%f\t%f\n",gamma_,kT); // fprintf(file3,"%f\t%d\n",gamma_,count_clusters(5)); //Die Correlation berechnen n_cur = iter.First(net->node_list); while (!iter.End()) { n_cur2 = iter2.First(net->node_list); while (!iter2.End()) { if (n_cur->Get_ClusterIndex() == n_cur2->Get_ClusterIndex()) { correlation[n_cur->Get_Index()]->Set(n_cur2->Get_Index()) += 0.5; correlation[n_cur2->Get_Index()]->Set(n_cur->Get_Index()) += 0.5; } n_cur2 = iter2.Next(); } n_cur = iter.Next(); } } // for i } //for n return gamma; } //####################################################################### //----------------------------------------------------------------------- //####################################################################### // This function writes the Correlation Matrix that results from a // Gamma-Sweep, this matrix is used to make ps files of it. // ###################################################################### // long PottsModel::WriteCorrelationMatrix(char *filename) // { // FILE *file, *file2; // char filename2[255]; // NNode *n_cur, *n_cur2; // DLList_Iter iter, iter2; // sprintf(filename2,"%s.mat",filename); // file=fopen(filename,"w"); // if (!file) { // printf("Could not open %s for writing.\n",filename); // return -1; // } // file2=fopen(filename2,"w"); // if (!file2) { // printf("Could not open %s for writing.\n",filename2); // return -1; // } // //write the header in one line // n_cur=iter.First(net->node_list); // while (!iter.End()) // { // fprintf(file, "\t%s",n_cur->Get_Name()); // n_cur=iter.Next(); // } // fprintf(file, "\n"); // //fprintf(file, "%d\t%d\n",net->node_list->Size(),net->node_list->Size()); // long r=0,c=0; // n_cur=iter.First(net->node_list); // while (!iter.End()) // { // fprintf(file, "%s",n_cur->Get_Name()); // r++; // n_cur2=iter2.First(net->node_list); // while (!iter2.End()) // { // c++; // fprintf(file,"\t%f",correlation[n_cur->Get_Index()]->Get(n_cur2->Get_Index())); // fprintf(file2,"%li\t%li\t%f\n",r,c,correlation[n_cur->Get_Index()]->Get(n_cur2->Get_Index())); // n_cur2=iter2.Next(); // } // fprintf(file,"\n"); // n_cur=iter.Next(); // } // fclose(file); // fclose(file2); // return 1; // } //############################################################################## //################################################################################################# PottsModelN::PottsModelN(network *n, unsigned int num_communities, bool directed) { //Set internal variable net = n; q = num_communities; is_directed = directed; is_init = false; num_nodes = net->node_list->Size(); } //####################################################### //Destructor of PottsModel //######################################################## PottsModelN::~PottsModelN() { delete degree_pos_in; delete degree_neg_in; delete degree_pos_out; delete degree_neg_out; delete degree_community_pos_in; delete degree_community_neg_in; delete degree_community_pos_out; delete degree_community_neg_out; delete weights; delete neighbours; delete csize; delete spin; return; } void PottsModelN::assign_initial_conf(bool init_spins) { #ifdef DEBUG printf("Start assigning.\n"); #endif int s; DLList_Iter iter; DLList_Iter l_iter; NNode *n_cur; NLink *l_cur; if (init_spins) { #ifdef DEBUG printf("Initializing spin.\n"); #endif //Bookkeeping of the various degrees (positive/negative) and (in/out) degree_pos_in = new double[num_nodes]; //Postive indegree of the nodes (or sum of weights) degree_neg_in = new double[num_nodes]; //Negative indegree of the nodes (or sum of weights) degree_pos_out = new double[num_nodes]; //Postive outdegree of the nodes (or sum of weights) degree_neg_out = new double[num_nodes]; //Negative outdegree of the nodes (or sum of weights) spin = new unsigned int[num_nodes]; //The spin state of each node } if (is_init) { delete degree_community_pos_in; delete degree_community_neg_in; delete degree_community_pos_out; delete degree_community_neg_out; delete weights; delete neighbours; delete csize; } is_init = true; //Bookkeep of occupation numbers of spin states or the number of links in community... degree_community_pos_in = new double[q + 1]; //Positive sum of indegree for communities degree_community_neg_in = new double[q + 1]; //Negative sum of indegree for communities degree_community_pos_out = new double[q + 1]; //Positive sum of outegree for communities degree_community_neg_out = new double[q + 1]; //Negative sum of outdegree for communities //...and of weights and neighbours for in the HeathBathLookup weights = new double[q + 1]; //The weights for changing to another spin state neighbours = new double[q + 1]; //The number of neighbours (or weights) in different spin states csize = new unsigned int[q + 1]; //The number of nodes in each community //Initialize communities for (unsigned int i = 0; i <= q; i++) { degree_community_pos_in[i] = 0.0; degree_community_neg_in[i] = 0.0; degree_community_pos_out[i] = 0.0; degree_community_neg_out[i] = 0.0; csize[i] = 0; } //Initialize vectors if (init_spins) { for (unsigned int i = 0; i < num_nodes; i++) { degree_pos_in[i] = 0.0; degree_neg_in[i] = 0.0; degree_pos_out[i] = 0.0; degree_neg_out[i] = 0.0; #ifdef DEBUG printf("Initializing spin %d", i); #endif spin[i] = 0; } } m_p = 0.0; m_n = 0.0; //Set community for each node, and //correctly store it in the bookkeeping double sum_weight_pos_in, sum_weight_pos_out, sum_weight_neg_in, sum_weight_neg_out; //double av_w = 0.0, av_k=0.0; //int l = 0; #ifdef DEBUG printf("Visiting each node.\n"); #endif for (unsigned int v = 0; v < num_nodes; v++) { if (init_spins) { s = RNG_INTEGER(1, q); //The new spin s spin[v] = (unsigned int)s; } else { s = spin[v]; } #ifdef DEBUG printf("Spin %d assigned to node %d.\n", s, v); #endif n_cur = net->node_list->Get(v); l_cur = l_iter.First(n_cur->Get_Links()); sum_weight_pos_in = 0.0; sum_weight_pos_out = 0.0; sum_weight_neg_in = 0.0; sum_weight_neg_out = 0.0; while (!l_iter.End()) { double w = l_cur->Get_Weight(); //av_w = (av_w*l + w)/(l+1); //Average weight //l++; if (l_cur->Get_Start() == n_cur) //From this to other, so outgoing link if (w > 0) { sum_weight_pos_out += w; //Increase positive outgoing weight } else { sum_weight_neg_out -= w; //Increase negative outgoing weight } else if (w > 0) { sum_weight_pos_in += w; //Increase positive incoming weight } else { sum_weight_neg_in -= w; //Increase negative incoming weight } l_cur = l_iter.Next(); } if (!is_directed) { double sum_weight_pos = sum_weight_pos_out + sum_weight_pos_in; sum_weight_pos_out = sum_weight_pos; sum_weight_pos_in = sum_weight_pos; double sum_weight_neg = sum_weight_neg_out + sum_weight_neg_in; sum_weight_neg_out = sum_weight_neg; sum_weight_neg_in = sum_weight_neg; } //av_k = (av_k*l + sum_weight_pos_in)/(l+1); //Average k if (init_spins) { //Set the degrees correctly degree_pos_in[v] = sum_weight_pos_in; degree_neg_in[v] = sum_weight_neg_in; degree_pos_out[v] = sum_weight_pos_out; degree_neg_out[v] = sum_weight_neg_out; } //Correct the community bookkeeping degree_community_pos_in[s] += sum_weight_pos_in; degree_community_neg_in[s] += sum_weight_neg_in; degree_community_pos_out[s] += sum_weight_pos_out; degree_community_neg_out[s] += sum_weight_neg_out; //Community just increased csize[s]++; //Sum the weights (notice that sum of indegrees equals sum of outdegrees) m_p += sum_weight_pos_in; m_n += sum_weight_neg_in; } #ifdef DEBUG printf("Done assigning.\n"); #endif return; } //############################################################## // This is the function generally used for optimisation, // as the parallel update has its flaws, due to the cyclic attractors //############################################################## double PottsModelN::HeatBathLookup(double gamma, double lambda, double t, unsigned int max_sweeps) { #ifdef DEBUG printf("Starting sweep at temperature %f.\n", t); #endif DLList_Iter iter; DLList_Iter l_iter; DLList_Iter i_iter, i_iter2; NNode *node, *n_cur; NLink *l_cur; /* The new_spin contains the spin to which we will update, * the spin_opt is the optional spin we will consider and * the old_spin is the spin of the node we are currently * changing. */ unsigned int new_spin, spin_opt, old_spin; unsigned int sweep; //current sweep unsigned long changes, problemcount; //Number of changes and number of problems encountered double exp_old_spin; //The expectation value for the old spin double exp_spin; //The expectation value for the other spin(s) int v; //The node we will be investigating //The variables required for the calculations double delta_pos_out, delta_pos_in, delta_neg_out, delta_neg_in; double k_v_pos_out, k_v_pos_in, k_v_neg_out, k_v_neg_in; //weight of edge double w; double beta = 1 / t; //Weight for probabilities double r = 0.0; //random number used for assigning new spin double maxweight = 0.0; double sum_weights = 0.0; //sum_weights for normalizing the probabilities sweep = 0; changes = 0; double m_pt = m_p; double m_nt = m_n; if (m_pt < 0.001) { m_pt = 1; } if (m_nt < 0.001) { m_nt = 1; } while (sweep < max_sweeps) { sweep++; //loop over all nodes in network for (unsigned int n = 0; n < num_nodes; n++) { //Look for a random node v = RNG_INTEGER(0, num_nodes - 1); //We will be investigating node v node = net->node_list->Get(v); /*******************************************/ // initialize the neighbours and the weights problemcount = 0; for (unsigned int i = 0; i <= q; i++) { neighbours[i] = 0.0; weights[i] = 0.0; } //Loop over all links (=neighbours) l_cur = l_iter.First(node->Get_Links()); while (!l_iter.End()) { w = l_cur->Get_Weight(); if (node == l_cur->Get_Start()) { n_cur = l_cur->Get_End(); } else { n_cur = l_cur->Get_Start(); } //Add the link to the correct cluster neighbours[spin[n_cur->Get_Index()]] += w; l_cur = l_iter.Next(); } //We now have the weight of the (in and out) neighbours //in each cluster available to us. /*******************************************/ old_spin = spin[v]; //Look for optimal spin //Set the appropriate variable delta_pos_out = degree_pos_out[v]; delta_pos_in = degree_pos_in[v]; delta_neg_out = degree_neg_out[v]; delta_neg_in = degree_neg_in[v]; k_v_pos_out = gamma * delta_pos_out / m_pt; k_v_pos_in = gamma * delta_pos_in / m_pt; k_v_neg_out = lambda * delta_neg_out / m_nt; k_v_neg_in = lambda * delta_neg_in / m_nt; //The expectation value for the old spin if (is_directed) exp_old_spin = (k_v_pos_out * (degree_community_pos_in[old_spin] - delta_pos_in) - k_v_neg_out * (degree_community_neg_in[old_spin] - delta_neg_in)) + (k_v_pos_in * (degree_community_pos_out[old_spin] - delta_pos_out) - k_v_neg_in * (degree_community_neg_out[old_spin] - delta_neg_out)); else exp_old_spin = (k_v_pos_out * (degree_community_pos_in[old_spin] - delta_pos_in) - k_v_neg_out * (degree_community_neg_in[old_spin] - delta_neg_in)); /*******************************************/ //Calculating probabilities for each transition to another //community. maxweight = 0.0; weights[old_spin] = 0.0; for (spin_opt = 1; spin_opt <= q; spin_opt++) { // all possible new spins if (spin_opt != old_spin) { // except the old one! if (is_directed) exp_spin = (k_v_pos_out * degree_community_pos_in[spin_opt] - k_v_neg_out * degree_community_neg_in[spin_opt]) + (k_v_pos_in * degree_community_pos_out[spin_opt] - k_v_neg_in * degree_community_neg_out[spin_opt]); else { exp_spin = (k_v_pos_out * degree_community_pos_in[spin_opt] - k_v_neg_out * degree_community_neg_in[spin_opt]); } weights[spin_opt] = (neighbours[spin_opt] - exp_spin) - (neighbours[old_spin] - exp_old_spin); if (weights[spin_opt] > maxweight) { maxweight = weights[spin_opt]; } } } // for spin //Calculate exp. prob. an sum_weights = 0.0; for (spin_opt = 1; spin_opt <= q; spin_opt++) { // all possible new spins weights[spin_opt] -= maxweight; //subtract maxweight for numerical stability (otherwise overflow). weights[spin_opt] = exp((double)(beta * weights[spin_opt])); sum_weights += weights[spin_opt]; } // for spin /*******************************************/ /*******************************************/ //Choose a new spin dependent on the calculated probabilities r = RNG_UNIF(0, sum_weights); new_spin = 1; bool found = false; while (!found && new_spin <= q) { if (r <= weights[new_spin]) { spin_opt = new_spin; //We have found are new spin found = true; break; } else { r -= weights[new_spin]; //Perhaps the next spin is the one we want } new_spin++; } //Some weird thing happened. We haven't found a new spin //while that shouldn't be the case. Numerical problems? if (!found) { problemcount++; } new_spin = spin_opt; //If there wasn't a problem we should have found //our new spin. /*******************************************/ /*******************************************/ //The new spin is available to us, so change //all the appropriate counters. if (new_spin != old_spin) { // Did we really change something?? changes++; spin[v] = new_spin; //The new spin increase by one, and the old spin decreases by one csize[new_spin]++; csize[old_spin]--; //Change the sums of degree for the old spin... degree_community_pos_in[old_spin] -= delta_pos_in; degree_community_neg_in[old_spin] -= delta_neg_in; degree_community_pos_out[old_spin] -= delta_pos_out; degree_community_neg_out[old_spin] -= delta_neg_out; //...and for the new spin degree_community_pos_in[new_spin] += delta_pos_in; degree_community_neg_in[new_spin] += delta_neg_in; degree_community_pos_out[new_spin] += delta_pos_out; degree_community_neg_out[new_spin] += delta_neg_out; } //We have no change a node from old_spin to new_spin /*******************************************/ } // for n } // while sweep #ifdef DEBUG printf("Done %d sweeps.\n", max_sweeps); printf("%d changes made for %d nodes.\n", changes, num_nodes); printf("Last node is %d and last random number is %f with sum of weights %f with spin %d.\n", v, r, sum_weights, old_spin); #endif return (double(changes) / double(num_nodes) / double(sweep)); } //We need to begin at a suitable temperature. That is, a temperature at which //enough nodes may change their initially assigned communties double PottsModelN::FindStartTemp(double gamma, double lambda, double ts) { double kT; kT = ts; //assing random initial condition assign_initial_conf(true); // the factor 1-1/q is important, since even, at infinite temperature, // only 1-1/q of all spins do change their state, since a randomly chooses new // state is with prob. 1/q the old state. double acceptance = 0.0; while (acceptance < (1.0 - 1.0 / double(q)) * 0.95) { //want 95% acceptance kT = kT * 1.1; acceptance = HeatBathLookup(gamma, lambda, kT, 50); } kT *= 1.1; // just to be sure... return kT; } long PottsModelN::WriteClusters(igraph_real_t *modularity, igraph_real_t *temperature, igraph_vector_t *community_size, igraph_vector_t *membership, igraph_matrix_t *adhesion, igraph_matrix_t *normalised_adhesion, igraph_real_t *polarization, double t, double d_p, double d_n, double gamma, double lambda) { IGRAPH_UNUSED(gamma); IGRAPH_UNUSED(lambda); #ifdef DEBUG printf("Start writing clusters.\n"); #endif //Reassign each community so that we retrieve a community assignment 1 through num_communities unsigned int *cluster_assign = new unsigned int[q + 1]; for (unsigned int i = 0; i <= q; i++) { cluster_assign[i] = 0; } int num_clusters = 0; //Find out what the new communities will be for (unsigned int i = 0; i < num_nodes; i++) { int s = spin[i]; if (cluster_assign[s] == 0) { num_clusters++; cluster_assign[s] = num_clusters; #ifdef DEBUG printf("Setting cluster %d to %d.\n", s, num_clusters); #endif } } /* DLList_Iter iter; NNode *n_cur=iter.First(net->node_list); n_cur = iter.First(net->node_list); */ //And now assign each node to its new community q = num_clusters; for (unsigned int i = 0; i < num_nodes; i++) { #ifdef DEBUG printf("Setting node %d to %d.\n", i, cluster_assign[spin[i]]); #endif unsigned int s = cluster_assign[spin[i]]; spin[i] = s; #ifdef DEBUG printf("Have set node %d to %d.\n", i, s); #endif } assign_initial_conf(false); delete[] cluster_assign; if (temperature) { *temperature = t; } if (community_size) { //Initialize the vector IGRAPH_CHECK(igraph_vector_resize(community_size, q)); for (unsigned int spin_opt = 1; spin_opt <= q; spin_opt++) { //Set the community size VECTOR(*community_size)[spin_opt - 1] = csize[spin_opt]; } } //Set the membership if (membership) { IGRAPH_CHECK(igraph_vector_resize(membership, num_nodes)); for (unsigned int i = 0; i < num_nodes; i++) { VECTOR(*membership)[ i ] = spin[i] - 1; } } double Q = 0.0; //Modularity if (adhesion) { IGRAPH_CHECK(igraph_matrix_resize(adhesion, q, q)); IGRAPH_CHECK(igraph_matrix_resize(normalised_adhesion, q, q)); double **num_links_pos = 0; double **num_links_neg = 0; //memory allocated for elements of rows. num_links_pos = new double *[q + 1] ; num_links_neg = new double *[q + 1] ; //memory allocated for elements of each column. for ( unsigned int i = 0 ; i < q + 1 ; i++) { num_links_pos[i] = new double[q + 1]; num_links_neg[i] = new double[q + 1]; } //Init num_links for (unsigned int i = 0; i <= q; i++) { for (unsigned int j = 0; j <= q; j++) { num_links_pos[i][j] = 0.0; num_links_neg[i][j] = 0.0; } } DLList_Iter iter_l; NLink *l_cur = iter_l.First(net->link_list); double w = 0.0; while (!iter_l.End()) { w = l_cur->Get_Weight(); unsigned int a = spin[l_cur->Get_Start()->Get_Index()]; unsigned int b = spin[l_cur->Get_End()->Get_Index()]; if (w > 0) { num_links_pos[a][b] += w; if (!is_directed && a != b) { //Only one edge is defined in case it is undirected num_links_pos[b][a] += w; } } else { num_links_neg[a][b] -= w; if (!is_directed && a != b) { //Only one edge is defined in case it is undirected num_links_neg[b][a] -= w; } } l_cur = iter_l.Next(); } //while links #ifdef DEBUG printf("d_p: %f\n", d_p); printf("d_n: %f\n", d_n); #endif double expected = 0.0; double a = 0.0; double normal_a = 0.0; double delta, u_p, u_n; double max_expected, max_a; //We don't take into account the lambda or gamma for //computing the modularity and adhesion, since they //are then incomparable to other definitions. for (unsigned int i = 1; i <= q; i++) { for (unsigned int j = 1; j <= q; j++) { if (!is_directed && i == j) expected = degree_community_pos_out[i] * degree_community_pos_in[j] / (m_p == 0 ? 1 : 2 * m_p) - degree_community_neg_out[i] * degree_community_neg_in[j] / (m_n == 0 ? 1 : 2 * m_n); else expected = degree_community_pos_out[i] * degree_community_pos_in[j] / (m_p == 0 ? 1 : m_p) - degree_community_neg_out[i] * degree_community_neg_in[j] / (m_n == 0 ? 1 : m_n); a = (num_links_pos[i][j] - num_links_neg[i][j]) - expected; if (i == j) { //cohesion if (is_directed) { delta = d_p * csize[i] * (csize[i] - 1); //Maximum amount } else { delta = d_p * csize[i] * (csize[i] - 1) / 2; //Maximum amount } u_p = delta - num_links_pos[i][i]; //Add as many positive links we can u_n = -num_links_neg[i][i]; //Delete as many negative links we can Q += a; } else { //adhesion if (is_directed) { delta = d_n * csize[i] * csize[j] * 2; //Maximum amount } else { delta = d_n * csize[i] * csize[j]; //Maximum amount } u_p = -num_links_pos[i][j]; //Delete as many positive links we can u_n = delta - num_links_neg[i][j]; //Add as many negative links we can } if (!is_directed && i == j) max_expected = (degree_community_pos_out[i] + u_p) * (degree_community_pos_in[j] + u_p) / ((m_p + u_p) == 0 ? 1 : 2 * (m_p + u_p)) - (degree_community_neg_out[i] - u_n) * (degree_community_neg_in[j] + u_n) / ((m_n + u_n) == 0 ? 1 : 2 * (m_n + u_n)); else max_expected = (degree_community_pos_out[i] + u_p) * (degree_community_pos_in[j] + u_p) / ((m_p + u_p) == 0 ? 1 : m_p + u_p) - (degree_community_neg_out[i] - u_n) * (degree_community_neg_in[j] + u_n) / ((m_n + u_n) == 0 ? 1 : m_n + u_n); //printf("%f/%f %d/%d\t", num_links_pos[i][j], num_links_neg[i][j], csize[i], csize[j]); //printf("%f/%f - %f(%f)\t", u_p, u_n, expected, max_expected); max_a = ((num_links_pos[i][j] + u_p) - (num_links_neg[i][j] + u_n)) - max_expected; //In cases where we haven't actually found a ground state //the adhesion/cohesion *might* not be negative/positive, //hence the maximum adhesion and cohesion might behave quite //strangely. In order to prevent that, we limit them to 1 in //absolute value, and prevent from dividing by zero (even if //chuck norris would). if (i == j) { normal_a = a / (max_a == 0 ? a : max_a); } else { normal_a = -a / (max_a == 0 ? a : max_a); } if (normal_a > 1) { normal_a = 1; } else if (normal_a < -1) { normal_a = -1; } MATRIX(*adhesion, i - 1, j - 1) = a; MATRIX(*normalised_adhesion, i - 1, j - 1) = normal_a; } //for j //printf("\n"); } //for i //free the allocated memory for ( unsigned int i = 0 ; i < q + 1 ; i++ ) { delete [] num_links_pos[i] ; delete [] num_links_neg[i]; } delete [] num_links_pos ; delete [] num_links_neg ; } //adhesion if (modularity) { if (is_directed) { *modularity = Q / (m_p + m_n); } else { *modularity = 2 * Q / (m_p + m_n); //Correction for the way m_p and m_n are counted. Modularity is 1/m, not 1/2m } } if (polarization) { double sum_ad = 0.0; for (unsigned int i = 0; i < q; i++) { for (unsigned int j = 0; j < q; j++) { if (i != j) { sum_ad -= MATRIX(*normalised_adhesion, i, j); } } } *polarization = sum_ad / (q * q - q); } #ifdef DEBUG printf("Finished writing cluster.\n"); #endif return num_nodes; } python-igraph-0.8.0/vendor/source/igraph/src/drl_graph_3d.h0000644000076500000240000001061013614300625024075 0ustar tamasstaff00000000000000/* * Copyright 2007 Sandia Corporation. Under the terms of Contract * DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains * certain rights in this software. * * All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are * met: * * * Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * Neither the name of Sandia National Laboratories nor the names of * its contributors may be used to endorse or promote products derived from * this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT * OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED * TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF * LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING * NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. */ // The graph class contains the methods necessary to draw the // graph. It calls on the density server class to obtain // position and density information #include "DensityGrid_3d.h" #include "igraph_layout.h" namespace drl3d { // layout schedule information struct layout_schedule { int iterations; float temperature; float attraction; float damping_mult; time_t time_elapsed; }; class graph { public: // Methods void init_parms ( int rand_seed, float edge_cut, float real_parm ); void init_parms ( const igraph_layout_drl_options_t *options ); int read_real ( const igraph_matrix_t *real_mat, const igraph_vector_bool_t *fixed); int draw_graph (igraph_matrix_t *res); float get_tot_energy ( ); // Con/Decon graph( const igraph_t *igraph, const igraph_layout_drl_options_t *options, const igraph_vector_t *weights); ~graph( ) { } private: // Methods int ReCompute ( ); void update_nodes ( ); float Compute_Node_Energy ( int node_ind ); void Solve_Analytic ( int node_ind, float &pos_x, float &pos_y, float &pos_z ); void get_positions ( vector &node_indices, float return_positions[3 * MAX_PROCS] ); void update_density ( vector &node_indices, float old_positions[3 * MAX_PROCS], float new_positions[3 * MAX_PROCS] ); void update_node_pos ( int node_ind, float old_positions[3 * MAX_PROCS], float new_positions[3 * MAX_PROCS] ); // MPI information int myid, num_procs; // graph decomposition information int num_nodes; // number of nodes in graph float highest_sim; // highest sim for normalization map id_catalog; // id_catalog[file id] = internal id map > neighbors; // neighbors of nodes on this proc. // graph layout information vector positions; DensityGrid density_server; // original VxOrd information int STAGE, iterations; float temperature, attraction, damping_mult; float min_edges, CUT_END, cut_length_end, cut_off_length, cut_rate; bool first_add, fine_first_add, fineDensity; // scheduling variables layout_schedule liquid; layout_schedule expansion; layout_schedule cooldown; layout_schedule crunch; layout_schedule simmer; // timing statistics time_t start_time, stop_time; // online clustering information int real_iterations; // number of iterations to hold .real input fixed int tot_iterations; int tot_expected_iterations; // for progress bar bool real_fixed; }; } // namespace drl3d python-igraph-0.8.0/vendor/source/igraph/src/foreign-pajek-parser.y0000644000076500000240000005367513524616145025632 0ustar tamasstaff00000000000000/* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ %{ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include "igraph_hacks_internal.h" #include "igraph_types.h" #include "igraph_types_internal.h" #include "igraph_memory.h" #include "igraph_error.h" #include "igraph_attributes.h" #include "config.h" #include "igraph_math.h" #include #include "foreign-pajek-header.h" #include "foreign-pajek-parser.h" #define yyscan_t void* int igraph_pajek_yylex(YYSTYPE* lvalp, YYLTYPE* llocp, void* scanner); int igraph_pajek_yyerror(YYLTYPE* locp, igraph_i_pajek_parsedata_t *context, const char *s); char *igraph_pajek_yyget_text (yyscan_t yyscanner ); int igraph_pajek_yyget_leng (yyscan_t yyscanner ); int igraph_i_pajek_add_string_vertex_attribute(const char *name, const char *value, int len, igraph_i_pajek_parsedata_t *context); int igraph_i_pajek_add_string_edge_attribute(const char *name, const char *value, int len, igraph_i_pajek_parsedata_t *context); int igraph_i_pajek_add_numeric_vertex_attribute(const char *name, igraph_real_t value, igraph_i_pajek_parsedata_t *context); int igraph_i_pajek_add_numeric_edge_attribute(const char *name, igraph_real_t value, igraph_i_pajek_parsedata_t *context); int igraph_i_pajek_add_numeric_attribute(igraph_trie_t *names, igraph_vector_ptr_t *attrs, long int count, const char *attrname, igraph_integer_t vid, igraph_real_t number); int igraph_i_pajek_add_string_attribute(igraph_trie_t *names, igraph_vector_ptr_t *attrs, long int count, const char *attrname, igraph_integer_t vid, const char *str); int igraph_i_pajek_add_bipartite_type(igraph_i_pajek_parsedata_t *context); int igraph_i_pajek_check_bipartite(igraph_i_pajek_parsedata_t *context); extern igraph_real_t igraph_pajek_get_number(const char *str, long int len); extern long int igraph_i_pajek_actvertex; extern long int igraph_i_pajek_actedge; #define scanner context->scanner %} %pure-parser %output="y.tab.c" %name-prefix="igraph_pajek_yy" %defines %locations %error-verbose %parse-param { igraph_i_pajek_parsedata_t* context } %lex-param { void *scanner } %union { long int intnum; double realnum; struct { char *str; int len; } string; } %type longint; %type arcfrom; %type arcto; %type edgefrom; %type edgeto; %type number; %type word; %type vpwordpar; %type epwordpar; %type vertex; %token NEWLINE %token NUM %token ALNUM %token QSTR %token PSTR %token NETWORKLINE %token VERTICESLINE %token ARCSLINE %token EDGESLINE %token ARCSLISTLINE %token EDGESLISTLINE %token MATRIXLINE %token ERROR %token VP_X_FACT %token VP_Y_FACT %token VP_IC %token VP_BC %token VP_LC %token VP_LR %token VP_LPHI %token VP_BW %token VP_FOS %token VP_PHI %token VP_R %token VP_Q %token VP_LA %token VP_FONT %token VP_URL %token VP_SIZE %token EP_C %token EP_S %token EP_A %token EP_W %token EP_H1 %token EP_H2 %token EP_A1 %token EP_A2 %token EP_K1 %token EP_K2 %token EP_AP %token EP_P %token EP_L %token EP_LP %token EP_LR %token EP_LPHI %token EP_LC %token EP_LA %token EP_SIZE %token EP_FOS %% input: nethead vertices edgeblock { if (context->vcount2 > 0) { igraph_i_pajek_check_bipartite(context); } }; nethead: /* empty */ | NETWORKLINE words NEWLINE; vertices: verticeshead NEWLINE vertdefs; verticeshead: VERTICESLINE longint { context->vcount=$2; context->vcount2=0; } | VERTICESLINE longint longint { context->vcount=$2; context->vcount2=$3; igraph_i_pajek_add_bipartite_type(context); }; vertdefs: /* empty */ | vertdefs vertexline; vertexline: NEWLINE | vertex NEWLINE | vertex { context->actvertex=$1; } vertexid vertexcoords shape params NEWLINE { } ; vertex: longint { $$=$1; context->mode=1; }; vertexid: word { igraph_i_pajek_add_string_vertex_attribute("id", $1.str, $1.len, context); igraph_i_pajek_add_string_vertex_attribute("name", $1.str, $1.len, context); }; vertexcoords: /* empty */ | number number { igraph_i_pajek_add_numeric_vertex_attribute("x", $1, context); igraph_i_pajek_add_numeric_vertex_attribute("y", $2, context); } | number number number { igraph_i_pajek_add_numeric_vertex_attribute("x", $1, context); igraph_i_pajek_add_numeric_vertex_attribute("y", $2, context); igraph_i_pajek_add_numeric_vertex_attribute("z", $3, context); }; shape: /* empty */ | word { igraph_i_pajek_add_string_vertex_attribute("shape", $1.str, $1.len, context); }; params: /* empty */ | params param; param: vpword | VP_X_FACT number { igraph_i_pajek_add_numeric_vertex_attribute("xfact", $2, context); } | VP_Y_FACT number { igraph_i_pajek_add_numeric_vertex_attribute("yfact", $2, context); } | VP_IC number number number { /* RGB color */ igraph_i_pajek_add_numeric_vertex_attribute("color-red", $2, context); igraph_i_pajek_add_numeric_vertex_attribute("color-green", $3, context); igraph_i_pajek_add_numeric_vertex_attribute("color-blue", $4, context); } | VP_BC number number number { igraph_i_pajek_add_numeric_vertex_attribute("framecolor-red", $2, context); igraph_i_pajek_add_numeric_vertex_attribute("framecolor-green", $3, context); igraph_i_pajek_add_numeric_vertex_attribute("framecolor-blue", $4, context); } | VP_LC number number number { igraph_i_pajek_add_numeric_vertex_attribute("labelcolor-red", $2, context); igraph_i_pajek_add_numeric_vertex_attribute("labelcolor-green", $3, context); igraph_i_pajek_add_numeric_vertex_attribute("labelcolor-blue", $4, context); } | VP_LR number { igraph_i_pajek_add_numeric_vertex_attribute("labeldist", $2, context); } | VP_LPHI number { igraph_i_pajek_add_numeric_vertex_attribute("labeldegree2", $2, context); } | VP_BW number { igraph_i_pajek_add_numeric_vertex_attribute("framewidth", $2, context); } | VP_FOS number { igraph_i_pajek_add_numeric_vertex_attribute("fontsize", $2, context); } | VP_PHI number { igraph_i_pajek_add_numeric_vertex_attribute("rotation", $2, context); } | VP_R number { igraph_i_pajek_add_numeric_vertex_attribute("radius", $2, context); } | VP_Q number { igraph_i_pajek_add_numeric_vertex_attribute("diamondratio", $2, context); } | VP_LA number { igraph_i_pajek_add_numeric_vertex_attribute("labeldegree", $2, context); } | VP_SIZE number { igraph_i_pajek_add_numeric_vertex_attribute("vertexsize", $2, context); } ; vpword: VP_FONT { context->mode=3; } vpwordpar { context->mode=1; igraph_i_pajek_add_string_vertex_attribute("font", $3.str, $3.len, context); } | VP_URL { context->mode=3; } vpwordpar { context->mode=1; igraph_i_pajek_add_string_vertex_attribute("url", $3.str, $3.len, context); } | VP_IC { context->mode=3; } vpwordpar { context->mode=1; igraph_i_pajek_add_string_vertex_attribute("color", $3.str, $3.len, context); } | VP_BC { context->mode=3; } vpwordpar { context->mode=1; igraph_i_pajek_add_string_vertex_attribute("framecolor", $3.str, $3.len, context); } | VP_LC { context->mode=3; } vpwordpar { context->mode=1; igraph_i_pajek_add_string_vertex_attribute("labelcolor", $3.str, $3.len, context); } ; vpwordpar: word { $$=$1; }; edgeblock: /* empty */ | edgeblock arcs | edgeblock edges | edgeblock arcslist | edgeblock edgeslist | edgeblock adjmatrix; arcs: ARCSLINE NEWLINE arcsdefs { context->directed=1; } | ARCSLINE number NEWLINE arcsdefs { context->directed=1; }; arcsdefs: /* empty */ | arcsdefs arcsline; arcsline: NEWLINE | arcfrom arcto { context->actedge++; context->mode=2; } weight edgeparams NEWLINE { igraph_vector_push_back(context->vector, $1-1); igraph_vector_push_back(context->vector, $2-1); } ; arcfrom: longint; arcto: longint; edges: EDGESLINE NEWLINE edgesdefs { context->directed=0; } | EDGESLINE number NEWLINE edgesdefs { context->directed=0; } edgesdefs: /* empty */ | edgesdefs edgesline; edgesline: NEWLINE | edgefrom edgeto { context->actedge++; context->mode=2; } weight edgeparams NEWLINE { igraph_vector_push_back(context->vector, $1-1); igraph_vector_push_back(context->vector, $2-1); } ; edgefrom: longint; edgeto: longint; weight: /* empty */ | number { igraph_i_pajek_add_numeric_edge_attribute("weight", $1, context); }; edgeparams: /* empty */ | edgeparams edgeparam; edgeparam: epword | EP_C number number number { igraph_i_pajek_add_numeric_edge_attribute("color-red", $2, context); igraph_i_pajek_add_numeric_edge_attribute("color-green", $3, context); igraph_i_pajek_add_numeric_edge_attribute("color-blue", $4, context); } | EP_S number { igraph_i_pajek_add_numeric_edge_attribute("arrowsize", $2, context); } | EP_W number { igraph_i_pajek_add_numeric_edge_attribute("edgewidth", $2, context); } | EP_H1 number { igraph_i_pajek_add_numeric_edge_attribute("hook1", $2, context); } | EP_H2 number { igraph_i_pajek_add_numeric_edge_attribute("hook2", $2, context); } | EP_A1 number { igraph_i_pajek_add_numeric_edge_attribute("angle1", $2, context); } | EP_A2 number { igraph_i_pajek_add_numeric_edge_attribute("angle2", $2, context); } | EP_K1 number { igraph_i_pajek_add_numeric_edge_attribute("velocity1", $2, context); } | EP_K2 number { igraph_i_pajek_add_numeric_edge_attribute("velocity2", $2, context); } | EP_AP number { igraph_i_pajek_add_numeric_edge_attribute("arrowpos", $2, context); } | EP_LP number { igraph_i_pajek_add_numeric_edge_attribute("labelpos", $2, context); } | EP_LR number { igraph_i_pajek_add_numeric_edge_attribute("labelangle", $2, context); } | EP_LPHI number { igraph_i_pajek_add_numeric_edge_attribute("labelangle2", $2, context); } | EP_LA number { igraph_i_pajek_add_numeric_edge_attribute("labeldegree", $2, context); } | EP_SIZE number { /* what is this??? */ igraph_i_pajek_add_numeric_edge_attribute("arrowsize", $2, context); } | EP_FOS number { igraph_i_pajek_add_numeric_edge_attribute("fontsize", $2, context); } ; epword: EP_A { context->mode=4; } epwordpar { context->mode=2; igraph_i_pajek_add_string_edge_attribute("arrowtype", $3.str, $3.len, context); } | EP_P { context->mode=4; } epwordpar { context->mode=2; igraph_i_pajek_add_string_edge_attribute("linepattern", $3.str, $3.len, context); } | EP_L { context->mode=4; } epwordpar { context->mode=2; igraph_i_pajek_add_string_edge_attribute("label", $3.str, $3.len, context); } | EP_LC { context->mode=4; } epwordpar { context->mode=2; igraph_i_pajek_add_string_edge_attribute("labelcolor", $3.str, $3.len, context); } | EP_C { context->mode=4; } epwordpar { context->mode=2; igraph_i_pajek_add_string_edge_attribute("color", $3.str, $3.len, context); } ; epwordpar: word { context->mode=2; $$=$1; }; arcslist: ARCSLISTLINE NEWLINE arcslistlines { context->directed=1; }; arcslistlines: /* empty */ | arcslistlines arclistline; arclistline: NEWLINE | arclistfrom arctolist NEWLINE; arctolist: /* empty */ | arctolist arclistto; arclistfrom: longint { context->mode=0; context->actfrom=labs($1)-1; }; arclistto: longint { igraph_vector_push_back(context->vector, context->actfrom); igraph_vector_push_back(context->vector, labs($1)-1); }; edgeslist: EDGESLISTLINE NEWLINE edgelistlines { context->directed=0; }; edgelistlines: /* empty */ | edgelistlines edgelistline; edgelistline: NEWLINE | edgelistfrom edgetolist NEWLINE; edgetolist: /* empty */ | edgetolist edgelistto; edgelistfrom: longint { context->mode=0; context->actfrom=labs($1)-1; }; edgelistto: longint { igraph_vector_push_back(context->vector, context->actfrom); igraph_vector_push_back(context->vector, labs($1)-1); }; /* -----------------------------------------------------*/ adjmatrix: matrixline NEWLINE adjmatrixlines; matrixline: MATRIXLINE { context->actfrom=0; context->actto=0; context->directed=(context->vcount2==0); }; adjmatrixlines: /* empty */ | adjmatrixlines adjmatrixline; adjmatrixline: adjmatrixnumbers NEWLINE { context->actfrom++; context->actto=0; }; adjmatrixnumbers: /* empty */ | adjmatrixentry adjmatrixnumbers; adjmatrixentry: number { if ($1 != 0) { if (context->vcount2==0) { context->actedge++; igraph_i_pajek_add_numeric_edge_attribute("weight", $1, context); igraph_vector_push_back(context->vector, context->actfrom); igraph_vector_push_back(context->vector, context->actto); } else if (context->vcount2 + context->actto < context->vcount) { context->actedge++; igraph_i_pajek_add_numeric_edge_attribute("weight", $1, context); igraph_vector_push_back(context->vector, context->actfrom); igraph_vector_push_back(context->vector, context->vcount2+context->actto); } } context->actto++; }; /* -----------------------------------------------------*/ longint: NUM { $$=igraph_pajek_get_number(igraph_pajek_yyget_text(scanner), igraph_pajek_yyget_leng(scanner)); }; number: NUM { $$=igraph_pajek_get_number(igraph_pajek_yyget_text(scanner), igraph_pajek_yyget_leng(scanner)); }; words: /* empty */ | words word; word: ALNUM { $$.str=igraph_pajek_yyget_text(scanner); $$.len=igraph_pajek_yyget_leng(scanner); } | NUM { $$.str=igraph_pajek_yyget_text(scanner); $$.len=igraph_pajek_yyget_leng(scanner); } | QSTR { $$.str=igraph_pajek_yyget_text(scanner)+1; $$.len=igraph_pajek_yyget_leng(scanner)-2; }; %% int igraph_pajek_yyerror(YYLTYPE* locp, igraph_i_pajek_parsedata_t *context, const char *s) { snprintf(context->errmsg, sizeof(context->errmsg)/sizeof(char)-1, "Parse error in Pajek file, line %i (%s)", locp->first_line, s); return 0; } igraph_real_t igraph_pajek_get_number(const char *str, long int length) { igraph_real_t num; char *tmp=igraph_Calloc(length+1, char); strncpy(tmp, str, length); tmp[length]='\0'; sscanf(tmp, "%lf", &num); igraph_Free(tmp); return num; } /* TODO: NA's */ int igraph_i_pajek_add_numeric_attribute(igraph_trie_t *names, igraph_vector_ptr_t *attrs, long int count, const char *attrname, igraph_integer_t vid, igraph_real_t number) { long int attrsize=igraph_trie_size(names); long int id; igraph_vector_t *na; igraph_attribute_record_t *rec; igraph_trie_get(names, attrname, &id); if (id == attrsize) { /* add a new attribute */ rec=igraph_Calloc(1, igraph_attribute_record_t); na=igraph_Calloc(1, igraph_vector_t); igraph_vector_init(na, count); rec->name=strdup(attrname); rec->type=IGRAPH_ATTRIBUTE_NUMERIC; rec->value=na; igraph_vector_ptr_push_back(attrs, rec); } rec=VECTOR(*attrs)[id]; na=(igraph_vector_t*)rec->value; if (igraph_vector_size(na) == vid) { IGRAPH_CHECK(igraph_vector_push_back(na, number)); } else if (igraph_vector_size(na) < vid) { long int origsize=igraph_vector_size(na); IGRAPH_CHECK(igraph_vector_resize(na, (long int)vid+1)); for (;origsizename=strdup(attrname); rec->type=IGRAPH_ATTRIBUTE_STRING; rec->value=na; igraph_vector_ptr_push_back(attrs, rec); } rec=VECTOR(*attrs)[id]; na=(igraph_strvector_t*)rec->value; if (igraph_strvector_size(na) <= vid) { long int origsize=igraph_strvector_size(na); IGRAPH_CHECK(igraph_strvector_resize(na, vid+1)); for (;origsizevertex_attribute_names, context->vertex_attributes, context->vcount, name, context->actvertex-1, tmp); igraph_Free(tmp); IGRAPH_FINALLY_CLEAN(1); return ret; } int igraph_i_pajek_add_string_edge_attribute(const char *name, const char *value, int len, igraph_i_pajek_parsedata_t *context) { char *tmp; int ret; tmp=igraph_Calloc(len+1, char); if (tmp==0) { IGRAPH_ERROR("cannot add element to hash table", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, tmp); strncpy(tmp, value, len); tmp[len]='\0'; ret=igraph_i_pajek_add_string_attribute(context->edge_attribute_names, context->edge_attributes, context->actedge, name, context->actedge-1, tmp); igraph_Free(tmp); IGRAPH_FINALLY_CLEAN(1); return ret; } int igraph_i_pajek_add_numeric_vertex_attribute(const char *name, igraph_real_t value, igraph_i_pajek_parsedata_t *context) { return igraph_i_pajek_add_numeric_attribute(context->vertex_attribute_names, context->vertex_attributes, context->vcount, name, context->actvertex-1, value); } int igraph_i_pajek_add_numeric_edge_attribute(const char *name, igraph_real_t value, igraph_i_pajek_parsedata_t *context) { return igraph_i_pajek_add_numeric_attribute(context->edge_attribute_names, context->edge_attributes, context->actedge, name, context->actedge-1, value); } int igraph_i_pajek_add_bipartite_type(igraph_i_pajek_parsedata_t *context) { const char *attrname="type"; igraph_trie_t *names=context->vertex_attribute_names; igraph_vector_ptr_t *attrs=context->vertex_attributes; int i, n=context->vcount, n1=context->vcount2; long int attrid, attrsize=igraph_trie_size(names); igraph_attribute_record_t *rec; igraph_vector_t *na; if (n1 > n) { IGRAPH_ERROR("Invalid number of vertices in bipartite Pajek file", IGRAPH_PARSEERROR); } igraph_trie_get(names, attrname, &attrid); if (attrid != attrsize) { IGRAPH_ERROR("Duplicate 'type' attribute in Pajek file, " "this should not happen", IGRAPH_EINTERNAL); } /* add a new attribute */ rec=igraph_Calloc(1, igraph_attribute_record_t); na=igraph_Calloc(1, igraph_vector_t); igraph_vector_init(na, n); rec->name=strdup(attrname); rec->type=IGRAPH_ATTRIBUTE_NUMERIC; rec->value=na; igraph_vector_ptr_push_back(attrs, rec); for (i=0; ivector; int i, n1=context->vcount2; int ne=igraph_vector_size(edges); for (i=0; i n1 && v2 > n1) ) { IGRAPH_WARNING("Invalid edge in bipartite graph"); } } return 0; } python-igraph-0.8.0/vendor/source/igraph/src/drl_layout.h0000644000076500000240000000564213614300625023734 0ustar tamasstaff00000000000000/* * Copyright 2007 Sandia Corporation. Under the terms of Contract * DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains * certain rights in this software. * * All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are * met: * * * Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * Neither the name of Sandia National Laboratories nor the names of * its contributors may be used to endorse or promote products derived from * this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT * OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED * TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF * LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING * NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. */ // This file contains compile time parameters which affect the entire // DrL program. #define DRL_VERSION "3.2 5/5/2006" // compile time parameters for MPI message passing #define MAX_PROCS 256 // maximum number of processors #define MAX_FILE_NAME 250 // max length of filename #define MAX_INT_LENGTH 4 // max length of integer suffix of intermediate .coord file // Compile time adjustable parameters for the Density grid #define GRID_SIZE 1000 // size of Density grid #define VIEW_SIZE 4000.0 // actual physical size of layout plane // these values use more memory but have // little effect on performance or layout #define RADIUS 10 // radius for density fall-off: // larger values tends to slow down // the program and clump the data #define HALF_VIEW 2000 // 1/2 of VIEW_SIZE #define VIEW_TO_GRID .25 // ratio of GRID_SIZE to VIEW_SIZE /* // original values for VxOrd #define GRID_SIZE 400 // size of VxOrd Density grid #define VIEW_SIZE 1600.0 // actual physical size of VxOrd plane #define RADIUS 10 // radius for density fall-off #define HALF_VIEW 800 // 1/2 of VIEW_SIZE #define VIEW_TO_GRID .25 // ratio of GRID_SIZE to VIEW_SIZE */ python-igraph-0.8.0/vendor/source/igraph/src/gengraph_mr-connected.cpp0000644000076500000240000001455013614300625026340 0ustar tamasstaff00000000000000/* * * gengraph - generation of random simple connected graphs with prescribed * degree sequence * * Copyright (C) 2006 Fabien Viger * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #include "gengraph_header.h" #include "gengraph_graph_molloy_optimized.h" #include "gengraph_graph_molloy_hash.h" #include "gengraph_degree_sequence.h" #include "gengraph_random.h" #include "igraph_datatype.h" #include "igraph_types.h" #include "igraph_error.h" namespace gengraph { // return negative number if program should exit int parse_options(int &argc, char** &argv); // options static const bool MONITOR_TIME = false; static const int SHUFFLE_TYPE = FINAL_HEURISTICS; static const bool RAW_DEGREES = false; static const FILE *Fdeg = stdin; //_________________________________________________________________________ // int main(int argc, char** argv) { // // options // SET_VERBOSE(VERBOSE_NONE); // if(parse_options(argc, argv) < 0) return -1; // //Read degree distribution // degree_sequence dd(Fdeg, !RAW_DEGREES); // //Allocate memory // if(VERBOSE()) fprintf(stderr,"Allocate memory for graph..."); // graph_molloy_opt g(dd); // dd.~degree_sequence(); // //Realize degree sequence // if(VERBOSE()) fprintf(stderr,"done\nRealize degree sequence..."); // bool FAILED = !g.havelhakimi(); // if(VERBOSE()) fprintf(stderr," %s\n", FAILED ? "Failed" : "Success"); // if(FAILED) return 2; // //Merge connected components together // if(VERBOSE()) fprintf(stderr,"Connecting..."); // FAILED = !g.make_connected(); // if(VERBOSE()) fprintf(stderr," %s\n", FAILED ? "Failed" : "Success"); // if(FAILED) return 3; // //Convert graph_molloy_opt to graph_molloy_hash // if(VERBOSE()) fprintf(stderr,"Convert adjacency lists into hash tables..."); // int *hc = g.hard_copy(); // g.~graph_molloy_opt(); // graph_molloy_hash gh(hc); // delete[] hc; // if(VERBOSE()) fprintf(stderr,"Done\n"); // //Shuffle // gh.shuffle(5*gh.nbarcs(), SHUFFLE_TYPE); // //Output // gh.print(); // if(MONITOR_TIME) { // double t = double(clock()) / double(CLOCKS_PER_SEC); // fprintf(stderr,"Time used: %f\n", t); // } // return 0; // } //_________________________________________________________________________ // int parse_options(int &argc, char** &argv) { // bool HELP = false; // int argc0 = argc; // argc = 1; // for(int a=1; a %s returns a graph in its standard output\n",argv[0]); // fprintf(stderr," If no file is given, %s reads its standard input\n",argv[0]); // fprintf(stderr," [-v] and [-vv] options causes extra verbose.\n"); // fprintf(stderr," [-g] option uses the Gkantsidis heuristics.\n"); // fprintf(stderr," [-b] option uses the Brute Force heuristics.\n"); // fprintf(stderr," [-f] option uses the Modified Gkantsidis heuristics.\n"); // fprintf(stderr," [-o] option uses the Optimal Gkantsidis heuristics.\n"); // fprintf(stderr," [-t] option monitors computation time\n"); // fprintf(stderr," [-s] does a srandom(0) to get a constant random graph\n"); // fprintf(stderr," [-raw] is to take raw degree sequences as input\n"); // return -1; // } // return 0; // } } // namespace gengraph using namespace gengraph; extern "C" { int igraph_degree_sequence_game_vl(igraph_t *graph, const igraph_vector_t *out_seq, const igraph_vector_t *in_seq) { long int sum = igraph_vector_sum(out_seq); if (sum % 2 != 0) { IGRAPH_ERROR("Sum of degrees should be even", IGRAPH_EINVAL); } RNG_BEGIN(); if (in_seq && igraph_vector_size(in_seq) != 0) { RNG_END(); IGRAPH_ERROR("This generator works with undirected graphs only", IGRAPH_EINVAL); } degree_sequence *dd = new degree_sequence(out_seq); graph_molloy_opt *g = new graph_molloy_opt(*dd); delete dd; if (!g->havelhakimi()) { delete g; RNG_END(); IGRAPH_ERROR("Cannot realize the given degree sequence as an undirected, simple graph", IGRAPH_EINVAL); } if (!g->make_connected()) { delete g; RNG_END(); IGRAPH_ERROR("Cannot make a connected graph from the given degree sequence", IGRAPH_EINVAL); } int *hc = g->hard_copy(); delete g; graph_molloy_hash *gh = new graph_molloy_hash(hc); delete [] hc; gh->shuffle(5 * gh->nbarcs(), 100 * gh->nbarcs(), SHUFFLE_TYPE); IGRAPH_CHECK(gh->print(graph)); delete gh; RNG_END(); return 0; } } python-igraph-0.8.0/vendor/source/igraph/src/sugiyama.c0000644000076500000240000015157113614300625023373 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "config.h" #include "igraph_centrality.h" #include "igraph_components.h" #include "igraph_constants.h" #include "igraph_constructors.h" #include "igraph_datatype.h" #include "igraph_error.h" #include "igraph_glpk_support.h" #include "igraph_interface.h" #include "igraph_memory.h" #include "igraph_structural.h" #include "igraph_types.h" #include /* #define SUGIYAMA_DEBUG */ #ifdef _MSC_VER /* MSVC does not support variadic macros */ #include static void debug(const char* fmt, ...) { va_list args; va_start(args, fmt); #ifdef SUGIYAMA_DEBUG vfprintf(stderr, fmt, args); #endif va_end(args); } #else #ifdef SUGIYAMA_DEBUG #define debug(...) fprintf(stderr, __VA_ARGS__) #else #define debug(...) #endif #endif /* MSVC uses __forceinline instead of inline */ #ifdef _MSC_VER #define INLINE __forceinline #else #define INLINE inline #endif /* * Implementation of the Sugiyama layout algorithm as described in: * * [1] K. Sugiyama, S. Tagawa and M. Toda, "Methods for Visual Understanding of * Hierarchical Systems". IEEE Transactions on Systems, Man and Cybernetics * 11(2):109-125, 1981. * * The layering (if not given in advance) is calculated by ... TODO * * [2] TODO * * The X coordinates of nodes within a layer are calculated using the method of * Brandes & Köpf: * * [3] U. Brandes and B. Köpf, "Fast and Simple Horizontal Coordinate * Assignment". In: Lecture Notes in Computer Science 2265:31-44, 2002. * * Layer compaction is done according to: * * [4] N.S. Nikolov and A. Tarassov, "Graph layering by promotion of nodes". * Journal of Discrete Applied Mathematics, special issue: IV ALIO/EURO * workshop on applied combinatorial optimization, 154(5). * * The steps of the algorithm are as follows: * * 1. Cycle removal by finding an approximately minimal feedback arc set * and reversing the direction of edges in the set. Algorithms for * finding minimal feedback arc sets are as follows: * * - Find a cycle and find its minimum weight edge. Decrease the weight * of all the edges by w. Remove those edges whose weight became zero. * Repeat until there are no cycles. Re-introduce removed edges in * decreasing order of weights, ensuring that no cycles are created. * * - Order the vertices somehow and remove edges which point backwards * in the ordering. Eades et al proposed the following procedure: * * 1. Iteratively remove sinks and prepend them to a vertex sequence * s2. * * 2. Iteratively remove sources and append them to a vertex sequence * s1. * * 3. Choose a vertex u s.t. the difference between the number of * rightward arcs and the number of leftward arcs is the largest, * remove u and append it to s1. Goto step 1 if there are still * more vertices. * * 4. Concatenate s1 with s2. * * This algorithm is known to produce feedback arc sets at most the * size of m/2 - n/6, where m is the number of edges. Further * improvements are possible in step 3 which bring down the size of * the set to at most m/4 for cubic directed graphs, see Eades (1995). * * - For undirected graphs, find a maximum weight spanning tree and * remove all the edges not in the spanning tree. For directed graphs, * find minimal cuts iteratively and remove edges pointing from A to * B or from B to A in the cut, depending on which one is smaller. Yes, * this is time-consuming. * * 2. Assigning vertices to layers according to [2]. * * 3. Extracting weakly connected components. The remaining steps are * executed for each component. * * 4. Compacting the layering using the method of [4]. TODO * Steps 2-4 are performed only when no layering is given in advance. * * 5. Adding dummy nodes to ensure that each edge spans at most one layer * only. * * 6. Finding an optimal ordering of vertices within a layer using the * Sugiyama framework [1]. * * 7. Assigning horizontal coordinates to each vertex using [3]. * * 8. ??? * * 9. Profit! */ /** * Data structure to store a layering of the graph. */ typedef struct { igraph_vector_ptr_t layers; } igraph_i_layering_t; /** * Initializes a layering. */ int igraph_i_layering_init(igraph_i_layering_t* layering, const igraph_vector_t* membership) { long int i, n, num_layers; if (igraph_vector_size(membership) == 0) { num_layers = 0; } else { num_layers = (long int) igraph_vector_max(membership) + 1; } IGRAPH_CHECK(igraph_vector_ptr_init(&layering->layers, num_layers)); IGRAPH_FINALLY(igraph_vector_ptr_destroy_all, &layering->layers); for (i = 0; i < num_layers; i++) { igraph_vector_t* vec = igraph_Calloc(1, igraph_vector_t); IGRAPH_VECTOR_INIT_FINALLY(vec, 0); VECTOR(layering->layers)[i] = vec; IGRAPH_FINALLY_CLEAN(1); } IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(&layering->layers, igraph_vector_destroy); n = igraph_vector_size(membership); for (i = 0; i < n; i++) { long int l = (long int) VECTOR(*membership)[i]; igraph_vector_t* vec = VECTOR(layering->layers)[l]; IGRAPH_CHECK(igraph_vector_push_back(vec, i)); } IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } /** * Destroys a layering. */ void igraph_i_layering_destroy(igraph_i_layering_t* layering) { igraph_vector_ptr_destroy_all(&layering->layers); } /** * Returns the number of layers in a layering. */ int igraph_i_layering_num_layers(const igraph_i_layering_t* layering) { return (int) igraph_vector_ptr_size(&layering->layers); } /** * Returns the list of vertices in a given layer */ igraph_vector_t* igraph_i_layering_get(const igraph_i_layering_t* layering, long int index) { return (igraph_vector_t*)VECTOR(layering->layers)[index]; } /** * Forward declarations */ static int igraph_i_layout_sugiyama_place_nodes_vertically(const igraph_t* graph, const igraph_vector_t* weights, igraph_vector_t* membership); static int igraph_i_layout_sugiyama_order_nodes_horizontally(const igraph_t* graph, igraph_matrix_t* layout, const igraph_i_layering_t* layering, long int maxiter); static int igraph_i_layout_sugiyama_place_nodes_horizontally(const igraph_t* graph, igraph_matrix_t* layout, const igraph_i_layering_t* layering, igraph_real_t hgap, igraph_integer_t no_of_real_nodes); /** * Calculated the median of four numbers (not necessarily sorted). */ static INLINE igraph_real_t igraph_i_median_4(igraph_real_t x1, igraph_real_t x2, igraph_real_t x3, igraph_real_t x4) { igraph_real_t arr[4] = { x1, x2, x3, x4 }; igraph_vector_t vec; igraph_vector_view(&vec, arr, 4); igraph_vector_sort(&vec); return (arr[1] + arr[2]) / 2.0; } /** * \ingroup layout * \function igraph_layout_sugiyama * \brief Sugiyama layout algorithm for layered directed acyclic graphs. * * * This layout algorithm is designed for directed acyclic graphs where each * vertex is assigned to a layer. Layers are indexed from zero, and vertices * of the same layer will be placed on the same horizontal line. The X coordinates * of vertices within each layer are decided by the heuristic proposed by * Sugiyama et al to minimize edge crossings. * * * You can also try to lay out undirected graphs, graphs containing cycles, or * graphs without an a priori layered assignment with this algorithm. igraph * will try to eliminate cycles and assign vertices to layers, but there is no * guarantee on the quality of the layout in such cases. * * * The Sugiyama layout may introduce "bends" on the edges in order to obtain a * visually more pleasing layout. This is achieved by adding dummy nodes to * edges spanning more than one layer. The resulting layout assigns coordinates * not only to the nodes of the original graph but also to the dummy nodes. * The layout algorithm will also return the extended graph with the dummy nodes. * An edge in the original graph may either be mapped to a single edge in the * extended graph or a \em path that starts and ends in the original * source and target vertex and passes through multiple dummy vertices. In * such cases, the user may also request the mapping of the edges of the extended * graph back to the edges of the original graph. * * * For more details, see K. Sugiyama, S. Tagawa and M. Toda, "Methods for Visual * Understanding of Hierarchical Systems". IEEE Transactions on Systems, Man and * Cybernetics 11(2):109-125, 1981. * * \param graph Pointer to an initialized graph object. * \param res Pointer to an initialized matrix object. This will contain * the result and will be resized as needed. The first |V| rows * of the layout will contain the coordinates of the original graph, * the remaining rows contain the positions of the dummy nodes. * Therefore, you can use the result both with \p graph or with * \p extended_graph. * \param extended_graph Pointer to an uninitialized graph object or \c NULL. * The extended graph with the added dummy nodes will be * returned here. In this graph, each edge points downwards * to lower layers, spans exactly one layer and the first * |V| vertices coincide with the vertices of the * original graph. * \param extd_to_orig_eids Pointer to a vector or \c NULL. If not \c NULL, the * mapping from the edge IDs of the extended graph back * to the edge IDs of the original graph will be stored * here. * \param layers The layer index for each vertex or \c NULL if the layers should * be determined automatically by igraph. * \param hgap The preferred minimum horizontal gap between vertices in the same * layer. * \param vgap The distance between layers. * \param maxiter Maximum number of iterations in the crossing minimization stage. * 100 is a reasonable default; if you feel that you have too * many edge crossings, increase this. * \param weights Weights of the edges. These are used only if the graph contains * cycles; igraph will tend to reverse edges with smaller * weights when breaking the cycles. */ int igraph_layout_sugiyama(const igraph_t *graph, igraph_matrix_t *res, igraph_t *extd_graph, igraph_vector_t *extd_to_orig_eids, const igraph_vector_t* layers, igraph_real_t hgap, igraph_real_t vgap, long int maxiter, const igraph_vector_t *weights) { long int i, j, k, l, m, nei; long int no_of_nodes = (long int)igraph_vcount(graph); long int comp_idx; long int next_extd_vertex_id = no_of_nodes; igraph_bool_t directed = igraph_is_directed(graph); igraph_integer_t no_of_components; /* number of components of the original graph */ igraph_vector_t membership; /* components of the original graph */ igraph_vector_t extd_edgelist; /* edge list of the extended graph */ igraph_vector_t layers_own; /* layer indices after having eliminated empty layers */ igraph_real_t dx = 0, dx2 = 0; /* displacement of the current component on the X axis */ igraph_vector_t layer_to_y; /* mapping from layer indices to final Y coordinates */ if (layers && igraph_vector_size(layers) != no_of_nodes) { IGRAPH_ERROR("layer vector too short or too long", IGRAPH_EINVAL); } if (extd_graph != 0) { IGRAPH_VECTOR_INIT_FINALLY(&extd_edgelist, 0); if (extd_to_orig_eids != 0) { igraph_vector_clear(extd_to_orig_eids); } } IGRAPH_CHECK(igraph_matrix_resize(res, no_of_nodes, 2)); IGRAPH_VECTOR_INIT_FINALLY(&membership, 0); IGRAPH_VECTOR_INIT_FINALLY(&layer_to_y, 0); /* 1. Find a feedback arc set if we don't have a layering yet. If we do have * a layering, we can leave all the edges as is as they will be re-oriented * to point downwards only anyway. */ if (layers == 0) { IGRAPH_VECTOR_INIT_FINALLY(&layers_own, no_of_nodes); IGRAPH_CHECK(igraph_i_layout_sugiyama_place_nodes_vertically( graph, weights, &layers_own)); } else { IGRAPH_CHECK(igraph_vector_copy(&layers_own, layers)); IGRAPH_FINALLY(igraph_vector_destroy, &layers_own); } /* Normalize layering, eliminate empty layers */ if (no_of_nodes > 0) { igraph_vector_t inds; IGRAPH_VECTOR_INIT_FINALLY(&inds, 0); IGRAPH_CHECK((int) igraph_vector_qsort_ind(&layers_own, &inds, 0)); j = -1; dx = VECTOR(layers_own)[(long int)VECTOR(inds)[0]] - 1; for (i = 0; i < no_of_nodes; i++) { k = (long int)VECTOR(inds)[i]; if (VECTOR(layers_own)[k] > dx) { /* New layer starts here */ dx = VECTOR(layers_own)[k]; j++; IGRAPH_CHECK(igraph_vector_push_back(&layer_to_y, dx * vgap)); } VECTOR(layers_own)[k] = j; } igraph_vector_destroy(&inds); IGRAPH_FINALLY_CLEAN(1); } /* 2. Find the connected components. */ IGRAPH_CHECK(igraph_clusters(graph, &membership, 0, &no_of_components, IGRAPH_WEAK)); /* 3. For each component... */ dx = 0; for (comp_idx = 0; comp_idx < no_of_components; comp_idx++) { /* Extract the edges of the comp_idx'th component and add dummy nodes for edges * spanning more than one layer. */ long int component_size, next_new_vertex_id; igraph_vector_t old2new_vertex_ids; igraph_vector_t new2old_vertex_ids; igraph_vector_t new_layers; igraph_vector_t edgelist; igraph_vector_t neis; IGRAPH_VECTOR_INIT_FINALLY(&edgelist, 0); IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); IGRAPH_VECTOR_INIT_FINALLY(&new2old_vertex_ids, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&old2new_vertex_ids, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&new_layers, 0); igraph_vector_fill(&old2new_vertex_ids, -1); /* Construct a mapping from the old vertex ids to the new ones */ for (i = 0, next_new_vertex_id = 0; i < no_of_nodes; i++) { if (VECTOR(membership)[i] == comp_idx) { IGRAPH_CHECK(igraph_vector_push_back(&new_layers, VECTOR(layers_own)[i])); VECTOR(new2old_vertex_ids)[next_new_vertex_id] = i; VECTOR(old2new_vertex_ids)[i] = next_new_vertex_id; next_new_vertex_id++; } } component_size = next_new_vertex_id; /* Construct a proper layering of the component in new_graph where each edge * points downwards and spans exactly one layer. */ for (i = 0; i < no_of_nodes; i++) { if (VECTOR(membership)[i] != comp_idx) { continue; } /* Okay, this vertex is in the component we are considering. * Add the neighbors of this vertex, excluding loops */ IGRAPH_CHECK(igraph_incident(graph, &neis, (igraph_integer_t) i, IGRAPH_OUT)); j = igraph_vector_size(&neis); for (k = 0; k < j; k++) { long int eid = (long int) VECTOR(neis)[k]; if (directed) { nei = IGRAPH_TO(graph, eid); } else { nei = IGRAPH_OTHER(graph, eid, i); if (nei < i) { /* to avoid considering edges twice */ continue; } } if (VECTOR(layers_own)[i] == VECTOR(layers_own)[nei]) { /* Edge goes within the same layer, we don't need this in the * layered graph, but we need it in the extended graph */ if (extd_graph != 0) { IGRAPH_CHECK(igraph_vector_push_back(&extd_edgelist, i)); IGRAPH_CHECK(igraph_vector_push_back(&extd_edgelist, nei)); if (extd_to_orig_eids != 0) { IGRAPH_CHECK(igraph_vector_push_back(extd_to_orig_eids, eid)); } } } else if (VECTOR(layers_own)[i] > VECTOR(layers_own)[nei]) { /* Edge goes upwards, we have to flip it */ IGRAPH_CHECK(igraph_vector_push_back(&edgelist, VECTOR(old2new_vertex_ids)[nei])); for (l = (long int) VECTOR(layers_own)[nei] + 1; l < VECTOR(layers_own)[i]; l++) { IGRAPH_CHECK(igraph_vector_push_back(&new_layers, l)); IGRAPH_CHECK(igraph_vector_push_back(&edgelist, next_new_vertex_id)); IGRAPH_CHECK(igraph_vector_push_back(&edgelist, next_new_vertex_id++)); } IGRAPH_CHECK(igraph_vector_push_back(&edgelist, VECTOR(old2new_vertex_ids)[i])); /* Also add the edge to the extended graph if needed, but this time * with the proper orientation */ if (extd_graph != 0) { IGRAPH_CHECK(igraph_vector_push_back(&extd_edgelist, i)); next_extd_vertex_id += VECTOR(layers_own)[i] - VECTOR(layers_own)[nei] - 1; for (l = (long int) VECTOR(layers_own)[i] - 1, m = 1; l > VECTOR(layers_own)[nei]; l--, m++) { IGRAPH_CHECK(igraph_vector_push_back(&extd_edgelist, next_extd_vertex_id - m)); IGRAPH_CHECK(igraph_vector_push_back(&extd_edgelist, next_extd_vertex_id - m)); if (extd_to_orig_eids != 0) { IGRAPH_CHECK(igraph_vector_push_back(extd_to_orig_eids, eid)); } } IGRAPH_CHECK(igraph_vector_push_back(&extd_edgelist, nei)); if (extd_to_orig_eids != 0) { IGRAPH_CHECK(igraph_vector_push_back(extd_to_orig_eids, eid)); } } } else { /* Edge goes downwards */ IGRAPH_CHECK(igraph_vector_push_back(&edgelist, VECTOR(old2new_vertex_ids)[i])); for (l = (long int) VECTOR(layers_own)[i] + 1; l < VECTOR(layers_own)[nei]; l++) { IGRAPH_CHECK(igraph_vector_push_back(&new_layers, l)); IGRAPH_CHECK(igraph_vector_push_back(&edgelist, next_new_vertex_id)); IGRAPH_CHECK(igraph_vector_push_back(&edgelist, next_new_vertex_id++)); } IGRAPH_CHECK(igraph_vector_push_back(&edgelist, VECTOR(old2new_vertex_ids)[nei])); /* Also add the edge to the extended graph */ if (extd_graph != 0) { IGRAPH_CHECK(igraph_vector_push_back(&extd_edgelist, i)); for (l = (long int) VECTOR(layers_own)[i] + 1; l < VECTOR(layers_own)[nei]; l++) { IGRAPH_CHECK(igraph_vector_push_back(&extd_edgelist, next_extd_vertex_id)); IGRAPH_CHECK(igraph_vector_push_back(&extd_edgelist, next_extd_vertex_id++)); if (extd_to_orig_eids != 0) { IGRAPH_CHECK(igraph_vector_push_back(extd_to_orig_eids, eid)); } } IGRAPH_CHECK(igraph_vector_push_back(&extd_edgelist, nei)); if (extd_to_orig_eids != 0) { IGRAPH_CHECK(igraph_vector_push_back(extd_to_orig_eids, eid)); } } } } } /* At this point, we have the subgraph with the dummy nodes and * edges, so we can run Sugiyama's algorithm on it. */ { igraph_matrix_t layout; igraph_i_layering_t layering; igraph_t subgraph; IGRAPH_CHECK(igraph_matrix_init(&layout, next_new_vertex_id, 2)); IGRAPH_FINALLY(igraph_matrix_destroy, &layout); IGRAPH_CHECK(igraph_create(&subgraph, &edgelist, (igraph_integer_t) next_new_vertex_id, 1)); IGRAPH_FINALLY(igraph_destroy, &subgraph); /* igraph_vector_print(&edgelist); igraph_vector_print(&new_layers); */ /* Assign the vertical coordinates */ for (i = 0; i < next_new_vertex_id; i++) { MATRIX(layout, i, 1) = VECTOR(new_layers)[i]; } /* Create a layering */ IGRAPH_CHECK(igraph_i_layering_init(&layering, &new_layers)); IGRAPH_FINALLY(igraph_i_layering_destroy, &layering); /* Find the order in which the nodes within a layer should be placed */ IGRAPH_CHECK(igraph_i_layout_sugiyama_order_nodes_horizontally(&subgraph, &layout, &layering, maxiter)); /* Assign the horizontal coordinates. This is according to the algorithm * of Brandes & Köpf */ IGRAPH_CHECK(igraph_i_layout_sugiyama_place_nodes_horizontally(&subgraph, &layout, &layering, hgap, (igraph_integer_t) component_size)); /* Re-assign rows into the result matrix, and at the same time, */ /* adjust dx so that the next component does not overlap this one */ j = next_new_vertex_id - component_size; k = igraph_matrix_nrow(res); IGRAPH_CHECK(igraph_matrix_add_rows(res, j)); dx2 = dx; for (i = 0; i < component_size; i++) { l = (long int)VECTOR(new2old_vertex_ids)[i]; MATRIX(*res, l, 0) = MATRIX(layout, i, 0) + dx; MATRIX(*res, l, 1) = VECTOR(layer_to_y)[(long)MATRIX(layout, i, 1)]; if (dx2 < MATRIX(*res, l, 0)) { dx2 = MATRIX(*res, l, 0); } } for (i = component_size; i < next_new_vertex_id; i++) { MATRIX(*res, k, 0) = MATRIX(layout, i, 0) + dx; MATRIX(*res, k, 1) = VECTOR(layer_to_y)[(long)MATRIX(layout, i, 1)]; if (dx2 < MATRIX(*res, k, 0)) { dx2 = MATRIX(*res, k, 0); } k++; } dx = dx2 + hgap; igraph_destroy(&subgraph); igraph_i_layering_destroy(&layering); igraph_matrix_destroy(&layout); IGRAPH_FINALLY_CLEAN(3); } igraph_vector_destroy(&new_layers); igraph_vector_destroy(&old2new_vertex_ids); igraph_vector_destroy(&new2old_vertex_ids); igraph_vector_destroy(&edgelist); igraph_vector_destroy(&neis); IGRAPH_FINALLY_CLEAN(5); } igraph_vector_destroy(&layers_own); igraph_vector_destroy(&layer_to_y); igraph_vector_destroy(&membership); IGRAPH_FINALLY_CLEAN(3); if (extd_graph != 0) { IGRAPH_CHECK(igraph_create(extd_graph, &extd_edgelist, (igraph_integer_t) next_extd_vertex_id, igraph_is_directed(graph))); igraph_vector_destroy(&extd_edgelist); IGRAPH_FINALLY_CLEAN(1); } return IGRAPH_SUCCESS; } static int igraph_i_layout_sugiyama_place_nodes_vertically(const igraph_t* graph, const igraph_vector_t* weights, igraph_vector_t* membership) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); IGRAPH_CHECK(igraph_vector_resize(membership, no_of_nodes)); if (no_of_edges == 0) { igraph_vector_fill(membership, 0); return IGRAPH_SUCCESS; } #ifdef HAVE_GLPK if (igraph_is_directed(graph) && no_of_nodes <= 1000) { /* Network simplex algorithm of Gansner et al, using the original linear * programming formulation */ long int i, j; igraph_vector_t outdegs, indegs, feedback_edges; glp_prob *ip; glp_smcp parm; /* Allocate storage and create the problem */ ip = glp_create_prob(); IGRAPH_FINALLY(glp_delete_prob, ip); IGRAPH_VECTOR_INIT_FINALLY(&feedback_edges, 0); IGRAPH_VECTOR_INIT_FINALLY(&outdegs, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&indegs, no_of_nodes); /* Find an approximate feedback edge set */ IGRAPH_CHECK(igraph_i_feedback_arc_set_eades(graph, &feedback_edges, weights, 0)); igraph_vector_sort(&feedback_edges); /* Calculate in- and out-strengths for the remaining edges */ IGRAPH_CHECK(igraph_strength(graph, &indegs, igraph_vss_all(), IGRAPH_IN, 1, weights)); IGRAPH_CHECK(igraph_strength(graph, &outdegs, igraph_vss_all(), IGRAPH_IN, 1, weights)); j = igraph_vector_size(&feedback_edges); for (i = 0; i < j; i++) { long int eid = (long int) VECTOR(feedback_edges)[i]; long int from = IGRAPH_FROM(graph, eid); long int to = IGRAPH_TO(graph, eid); VECTOR(outdegs)[from] -= weights ? VECTOR(*weights)[eid] : 1; VECTOR(indegs)[to] -= weights ? VECTOR(*weights)[eid] : 1; } /* Configure GLPK */ glp_term_out(GLP_OFF); glp_init_smcp(&parm); parm.msg_lev = GLP_MSG_OFF; parm.presolve = GLP_OFF; /* Set up variables and objective function coefficients */ glp_set_obj_dir(ip, GLP_MIN); glp_add_cols(ip, (int) no_of_nodes); IGRAPH_CHECK(igraph_vector_sub(&outdegs, &indegs)); for (i = 1; i <= no_of_nodes; i++) { glp_set_col_kind(ip, (int) i, GLP_IV); glp_set_col_bnds(ip, (int) i, GLP_LO, 0.0, 0.0); glp_set_obj_coef(ip, (int) i, VECTOR(outdegs)[i - 1]); } igraph_vector_destroy(&indegs); igraph_vector_destroy(&outdegs); IGRAPH_FINALLY_CLEAN(2); /* Add constraints */ glp_add_rows(ip, (int) no_of_edges); IGRAPH_CHECK(igraph_vector_push_back(&feedback_edges, -1)); j = 0; for (i = 0; i < no_of_edges; i++) { int ind[3]; double val[3] = {0, -1, 1}; ind[1] = IGRAPH_FROM(graph, i) + 1; ind[2] = IGRAPH_TO(graph, i) + 1; if (ind[1] == ind[2]) { if (VECTOR(feedback_edges)[j] == i) { j++; } continue; } if (VECTOR(feedback_edges)[j] == i) { /* This is a feedback edge, add it reversed */ glp_set_row_bnds(ip, (int) i + 1, GLP_UP, -1, -1); j++; } else { glp_set_row_bnds(ip, (int) i + 1, GLP_LO, 1, 1); } glp_set_mat_row(ip, (int) i + 1, 2, ind, val); } /* Solve the problem */ IGRAPH_GLPK_CHECK(glp_simplex(ip, &parm), "Vertical arrangement step using IP failed"); /* The problem is totally unimodular, therefore the output of the simplex * solver can be converted to an integer solution easily */ for (i = 0; i < no_of_nodes; i++) { VECTOR(*membership)[i] = floor(glp_get_col_prim(ip, (int) i + 1)); } glp_delete_prob(ip); igraph_vector_destroy(&feedback_edges); IGRAPH_FINALLY_CLEAN(2); } else if (igraph_is_directed(graph)) { IGRAPH_CHECK(igraph_i_feedback_arc_set_eades(graph, 0, weights, membership)); } else { IGRAPH_CHECK(igraph_i_feedback_arc_set_undirected(graph, 0, weights, membership)); } #else if (igraph_is_directed(graph)) { IGRAPH_CHECK(igraph_i_feedback_arc_set_eades(graph, 0, weights, membership)); } else { IGRAPH_CHECK(igraph_i_feedback_arc_set_undirected(graph, 0, weights, membership)); } #endif return IGRAPH_SUCCESS; } static int igraph_i_layout_sugiyama_calculate_barycenters(const igraph_t* graph, const igraph_i_layering_t* layering, long int layer_index, igraph_neimode_t direction, const igraph_matrix_t* layout, igraph_vector_t* barycenters) { long int i, j, m, n; igraph_vector_t* layer_members = igraph_i_layering_get(layering, layer_index); igraph_vector_t neis; IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); n = igraph_vector_size(layer_members); IGRAPH_CHECK(igraph_vector_resize(barycenters, n)); igraph_vector_null(barycenters); for (i = 0; i < n; i++) { IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) VECTOR(*layer_members)[i], direction)); m = igraph_vector_size(&neis); if (m == 0) { /* No neighbors in this direction. Just use the current X coordinate */ VECTOR(*barycenters)[i] = MATRIX(*layout, i, 0); } else { for (j = 0; j < m; j++) { VECTOR(*barycenters)[i] += MATRIX(*layout, (long)VECTOR(neis)[j], 0); } VECTOR(*barycenters)[i] /= m; } } igraph_vector_destroy(&neis); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } /** * Given a properly layered graph where each edge points downwards and spans * exactly one layer, arranges the nodes in each layer horizontally in a way * that strives to minimize edge crossings. */ static int igraph_i_layout_sugiyama_order_nodes_horizontally(const igraph_t* graph, igraph_matrix_t* layout, const igraph_i_layering_t* layering, long int maxiter) { long int i, n, nei; long int no_of_vertices = igraph_vcount(graph); long int no_of_layers = igraph_i_layering_num_layers(layering); long int iter, layer_index; igraph_vector_t* layer_members; igraph_vector_t neis, barycenters, sort_indices; igraph_bool_t changed; /* The first column of the matrix will serve as the ordering */ /* Start with a first-seen ordering within each layer */ { long int *xs = igraph_Calloc(no_of_layers, long int); if (xs == 0) { IGRAPH_ERROR("cannot order nodes horizontally", IGRAPH_ENOMEM); } for (i = 0; i < no_of_vertices; i++) { MATRIX(*layout, i, 0) = xs[(long int)MATRIX(*layout, i, 1)]++; } free(xs); } IGRAPH_VECTOR_INIT_FINALLY(&barycenters, 0); IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); IGRAPH_VECTOR_INIT_FINALLY(&sort_indices, 0); /* Start the effective part of the Sugiyama algorithm */ iter = 0; changed = 1; while (changed && iter < maxiter) { changed = 0; /* Phase 1 */ /* Moving downwards and sorting by upper barycenters */ for (layer_index = 1; layer_index < no_of_layers; layer_index++) { layer_members = igraph_i_layering_get(layering, layer_index); n = igraph_vector_size(layer_members); igraph_i_layout_sugiyama_calculate_barycenters(graph, layering, layer_index, IGRAPH_IN, layout, &barycenters); #ifdef SUGIYAMA_DEBUG printf("Layer %ld, aligning to upper barycenters\n", layer_index); printf("Vertices: "); igraph_vector_print(layer_members); printf("Barycenters: "); igraph_vector_print(&barycenters); #endif IGRAPH_CHECK((int) igraph_vector_qsort_ind(&barycenters, &sort_indices, 0)); for (i = 0; i < n; i++) { nei = (long)VECTOR(*layer_members)[(long)VECTOR(sort_indices)[i]]; VECTOR(barycenters)[i] = nei; MATRIX(*layout, nei, 0) = i; } if (!igraph_vector_all_e(layer_members, &barycenters)) { IGRAPH_CHECK(igraph_vector_update(layer_members, &barycenters)); #ifdef SUGIYAMA_DEBUG printf("New vertex order: "); igraph_vector_print(layer_members); #endif changed = 1; } else { #ifdef SUGIYAMA_DEBUG printf("Order did not change.\n"); #endif } } /* Moving upwards and sorting by lower barycenters */ for (layer_index = no_of_layers - 2; layer_index >= 0; layer_index--) { layer_members = igraph_i_layering_get(layering, layer_index); n = igraph_vector_size(layer_members); igraph_i_layout_sugiyama_calculate_barycenters(graph, layering, layer_index, IGRAPH_OUT, layout, &barycenters); #ifdef SUGIYAMA_DEBUG printf("Layer %ld, aligning to lower barycenters\n", layer_index); printf("Vertices: "); igraph_vector_print(layer_members); printf("Barycenters: "); igraph_vector_print(&barycenters); #endif IGRAPH_CHECK((int) igraph_vector_qsort_ind(&barycenters, &sort_indices, 0)); for (i = 0; i < n; i++) { nei = (long)VECTOR(*layer_members)[(long)VECTOR(sort_indices)[i]]; VECTOR(barycenters)[i] = nei; MATRIX(*layout, nei, 0) = i; } if (!igraph_vector_all_e(layer_members, &barycenters)) { IGRAPH_CHECK(igraph_vector_update(layer_members, &barycenters)); #ifdef SUGIYAMA_DEBUG printf("New vertex order: "); igraph_vector_print(layer_members); #endif changed = 1; } else { #ifdef SUGIYAMA_DEBUG printf("Order did not change.\n"); #endif } } #ifdef SUGIYAMA_DEBUG printf("==== Finished iteration %ld\n", iter); #endif iter++; } igraph_vector_destroy(&barycenters); igraph_vector_destroy(&neis); igraph_vector_destroy(&sort_indices); IGRAPH_FINALLY_CLEAN(3); return IGRAPH_SUCCESS; } #define IS_DUMMY(v) ((v >= no_of_real_nodes)) #define IS_INNER_SEGMENT(u, v) (IS_DUMMY(u) && IS_DUMMY(v)) #define X_POS(v) (MATRIX(*layout, v, 0)) static int igraph_i_layout_sugiyama_vertical_alignment(const igraph_t* graph, const igraph_i_layering_t* layering, const igraph_matrix_t* layout, const igraph_vector_bool_t* ignored_edges, igraph_bool_t reverse, igraph_bool_t align_right, igraph_vector_t* roots, igraph_vector_t* align); static int igraph_i_layout_sugiyama_horizontal_compaction(const igraph_t* graph, const igraph_vector_t* vertex_to_the_left, const igraph_vector_t* roots, const igraph_vector_t* align, igraph_real_t hgap, igraph_vector_t* xs); static int igraph_i_layout_sugiyama_horizontal_compaction_place_block(long int v, const igraph_vector_t* vertex_to_the_left, const igraph_vector_t* roots, const igraph_vector_t* align, igraph_vector_t* sinks, igraph_vector_t* shifts, igraph_real_t hgap, igraph_vector_t* xs); static int igraph_i_layout_sugiyama_place_nodes_horizontally(const igraph_t* graph, igraph_matrix_t* layout, const igraph_i_layering_t* layering, igraph_real_t hgap, igraph_integer_t no_of_real_nodes) { long int i, j, k, l, n; long int no_of_layers = igraph_i_layering_num_layers(layering); long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_vector_t neis1, neis2; igraph_vector_t xs[4]; igraph_vector_t roots, align; igraph_vector_t vertex_to_the_left; igraph_vector_bool_t ignored_edges; /* { igraph_vector_t edgelist; IGRAPH_VECTOR_INIT_FINALLY(&edgelist, 0); IGRAPH_CHECK(igraph_get_edgelist(graph, &edgelist, 0)); igraph_vector_print(&edgelist); igraph_vector_destroy(&edgelist); IGRAPH_FINALLY_CLEAN(1); for (i = 0; i < no_of_layers; i++) { igraph_vector_t* layer = igraph_i_layering_get(layering, i); igraph_vector_print(layer); } } */ IGRAPH_CHECK(igraph_vector_bool_init(&ignored_edges, no_of_edges)); IGRAPH_FINALLY(igraph_vector_bool_destroy, &ignored_edges); IGRAPH_VECTOR_INIT_FINALLY(&vertex_to_the_left, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&neis1, 0); IGRAPH_VECTOR_INIT_FINALLY(&neis2, 0); /* First, find all type 1 conflicts and mark one of the edges participating * in the conflict as being ignored. If one of the edges in the conflict * is a non-inner segment and the other is an inner segment, we ignore the * non-inner segment as we want to keep inner segments vertical. */ for (i = 0; i < no_of_layers - 1; i++) { igraph_vector_t* vertices = igraph_i_layering_get(layering, i); n = igraph_vector_size(vertices); /* Find all the edges from this layer to the next */ igraph_vector_clear(&neis1); for (j = 0; j < n; j++) { IGRAPH_CHECK(igraph_neighbors(graph, &neis2, (igraph_integer_t) VECTOR(*vertices)[j], IGRAPH_OUT)); IGRAPH_CHECK(igraph_vector_append(&neis1, &neis2)); } /* Consider all pairs of edges and check whether they are in a type 1 * conflict */ n = igraph_vector_size(&neis1); for (j = 0; j < n; j++) { long int u = IGRAPH_FROM(graph, j); long int v = IGRAPH_TO(graph, j); igraph_bool_t j_inner = IS_INNER_SEGMENT(u, v); igraph_bool_t crossing; for (k = j + 1; k < n; k++) { long int w = IGRAPH_FROM(graph, k); long int x = IGRAPH_TO(graph, k); if (IS_INNER_SEGMENT(w, x) == j_inner) { continue; } /* Do the u --> v and w --> x edges cross? */ crossing = (u == w || v == x); if (!crossing) { if (X_POS(u) <= X_POS(w)) { crossing = X_POS(v) >= X_POS(x); } else { crossing = X_POS(v) <= X_POS(x); } } if (crossing) { if (j_inner) { VECTOR(ignored_edges)[k] = 1; } else { VECTOR(ignored_edges)[j] = 1; } } } } } igraph_vector_destroy(&neis1); igraph_vector_destroy(&neis2); IGRAPH_FINALLY_CLEAN(2); /* * Prepare vertex_to_the_left where the ith element stores * the index of the vertex to the left of vertex i, or i itself if the * vertex is the leftmost vertex in a layer. */ for (i = 0; i < no_of_layers; i++) { igraph_vector_t* vertices = igraph_i_layering_get(layering, i); n = igraph_vector_size(vertices); if (n == 0) { continue; } k = l = (long int)VECTOR(*vertices)[0]; VECTOR(vertex_to_the_left)[k] = k; for (j = 1; j < n; j++) { k = (long int)VECTOR(*vertices)[j]; VECTOR(vertex_to_the_left)[k] = l; l = k; } } /* Type 1 conflicts found, ignored edges chosen, vertex_to_the_left * prepared. Run vertical alignment for all four combinations */ for (i = 0; i < 4; i++) { IGRAPH_VECTOR_INIT_FINALLY(&xs[i], no_of_nodes); } IGRAPH_VECTOR_INIT_FINALLY(&roots, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&align, no_of_nodes); for (i = 0; i < 4; i++) { IGRAPH_CHECK(igraph_i_layout_sugiyama_vertical_alignment(graph, layering, layout, &ignored_edges, /* reverse = */ (igraph_bool_t) i / 2, /* align_right = */ i % 2, &roots, &align)); IGRAPH_CHECK(igraph_i_layout_sugiyama_horizontal_compaction(graph, &vertex_to_the_left, &roots, &align, hgap, &xs[i])); } { igraph_real_t width, min_width, mins[4], maxs[4], diff; /* Find the alignment with the minimum width */ min_width = IGRAPH_INFINITY; j = 0; for (i = 0; i < 4; i++) { mins[i] = igraph_vector_min(&xs[i]); maxs[i] = igraph_vector_max(&xs[i]); width = maxs[i] - mins[i]; if (width < min_width) { min_width = width; j = i; } } /* Leftmost alignments: align them s.t. the min X coordinate is equal to * the minimum X coordinate of the alignment with the smallest width. * Rightmost alignments: align them s.t. the max X coordinate is equal to * the max X coordinate of the alignment with the smallest width. */ for (i = 0; i < 4; i++) { if (j == i) { continue; } if (i % 2 == 0) { /* Leftmost alignment */ diff = mins[j] - mins[i]; } else { /* Rightmost alignment */ diff = maxs[j] - maxs[i]; } igraph_vector_add_constant(&xs[i], diff); } } /* For every vertex, find the median of the X coordinates in the four * alignments */ for (i = 0; i < no_of_nodes; i++) { X_POS(i) = igraph_i_median_4(VECTOR(xs[0])[i], VECTOR(xs[1])[i], VECTOR(xs[2])[i], VECTOR(xs[3])[i]); } igraph_vector_destroy(&roots); igraph_vector_destroy(&align); IGRAPH_FINALLY_CLEAN(2); for (i = 0; i < 4; i++) { igraph_vector_destroy(&xs[i]); } IGRAPH_FINALLY_CLEAN(4); igraph_vector_destroy(&vertex_to_the_left); IGRAPH_FINALLY_CLEAN(1); igraph_vector_bool_destroy(&ignored_edges); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } static int igraph_i_layout_sugiyama_vertical_alignment(const igraph_t* graph, const igraph_i_layering_t* layering, const igraph_matrix_t* layout, const igraph_vector_bool_t* ignored_edges, igraph_bool_t reverse, igraph_bool_t align_right, igraph_vector_t* roots, igraph_vector_t* align) { long int i, j, k, n, di, dj, i_limit, j_limit, r; long int no_of_layers = igraph_i_layering_num_layers(layering); long int no_of_nodes = igraph_vcount(graph); igraph_neimode_t neimode = (reverse ? IGRAPH_OUT : IGRAPH_IN); igraph_vector_t neis, xs, inds; IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); IGRAPH_VECTOR_INIT_FINALLY(&xs, 0); IGRAPH_VECTOR_INIT_FINALLY(&inds, 0); IGRAPH_CHECK(igraph_vector_resize(roots, no_of_nodes)); IGRAPH_CHECK(igraph_vector_resize(align, no_of_nodes)); for (i = 0; i < no_of_nodes; i++) { VECTOR(*roots)[i] = VECTOR(*align)[i] = i; } /* When reverse = False, we are aligning "upwards" in the tree, hence we * have to loop i from 1 to no_of_layers-1 (inclusive) and use neimode=IGRAPH_IN. * When reverse = True, we are aligning "downwards", hence we have to loop * i from no_of_layers-2 to 0 (inclusive) and use neimode=IGRAPH_OUT. */ i = reverse ? (no_of_layers - 2) : 1; di = reverse ? -1 : 1; i_limit = reverse ? -1 : no_of_layers; for (; i != i_limit; i += di) { igraph_vector_t *layer = igraph_i_layering_get(layering, i); /* r = 0 in the paper, but C arrays are indexed from 0 */ r = align_right ? LONG_MAX : -1; /* If align_right is 1, we have to process the layer in reverse order */ j = align_right ? (igraph_vector_size(layer) - 1) : 0; dj = align_right ? -1 : 1; j_limit = align_right ? -1 : igraph_vector_size(layer); for (; j != j_limit; j += dj) { long int medians[2]; long int vertex = (long int) VECTOR(*layer)[j]; long int pos; if (VECTOR(*align)[vertex] != vertex) /* This vertex is already aligned with some other vertex, * so there's nothing to do */ { continue; } /* Find the neighbors of vertex j in layer i */ IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) vertex, neimode)); n = igraph_vector_size(&neis); if (n == 0) /* No neighbors in this direction, continue */ { continue; } if (n == 1) { /* Just one neighbor; the median is trivial */ medians[0] = (long int) VECTOR(neis)[0]; medians[1] = -1; } else { /* Sort the neighbors by their X coordinates */ IGRAPH_CHECK(igraph_vector_resize(&xs, n)); for (k = 0; k < n; k++) { VECTOR(xs)[k] = X_POS((long int)VECTOR(neis)[k]); } IGRAPH_CHECK((int) igraph_vector_qsort_ind(&xs, &inds, 0)); if (n % 2 == 1) { /* Odd number of neighbors, so the median is unique */ medians[0] = (long int) VECTOR(neis)[(long int)VECTOR(inds)[n / 2]]; medians[1] = -1; } else { /* Even number of neighbors, so we have two medians. The order * depends on whether we are processing the layer in leftmost * or rightmost fashion. */ if (align_right) { medians[0] = (long int) VECTOR(neis)[(long int)VECTOR(inds)[n / 2]]; medians[1] = (long int) VECTOR(neis)[(long int)VECTOR(inds)[n / 2 - 1]]; } else { medians[0] = (long int) VECTOR(neis)[(long int)VECTOR(inds)[n / 2 - 1]]; medians[1] = (long int) VECTOR(neis)[(long int)VECTOR(inds)[n / 2]]; } } } /* Try aligning with the medians */ for (k = 0; k < 2; k++) { igraph_integer_t eid; if (medians[k] < 0) { continue; } if (VECTOR(*align)[vertex] != vertex) { /* Vertex already aligned, continue */ continue; } /* Is the edge between medians[k] and vertex ignored * because of a type 1 conflict? */ IGRAPH_CHECK(igraph_get_eid(graph, &eid, (igraph_integer_t) vertex, (igraph_integer_t) medians[k], 0, 1)); if (VECTOR(*ignored_edges)[(long int)eid]) { continue; } /* Okay, align with the median if possible */ pos = (long int) X_POS(medians[k]); if ((align_right && r > pos) || (!align_right && r < pos)) { VECTOR(*align)[medians[k]] = vertex; VECTOR(*roots)[vertex] = VECTOR(*roots)[medians[k]]; VECTOR(*align)[vertex] = VECTOR(*roots)[medians[k]]; r = pos; } } } } igraph_vector_destroy(&inds); igraph_vector_destroy(&neis); igraph_vector_destroy(&xs); IGRAPH_FINALLY_CLEAN(3); return IGRAPH_SUCCESS; } /* * Runs a horizontal compaction given a vertical alignment (in `align`) * and the roots (in `roots`). These come out directly from * igraph_i_layout_sugiyama_vertical_alignment. * * Returns the X coordinates for each vertex in `xs`. * * `graph` is the input graph, `layering` is the layering on which we operate. * `hgap` is the preferred horizontal gap between vertices. */ static int igraph_i_layout_sugiyama_horizontal_compaction(const igraph_t* graph, const igraph_vector_t* vertex_to_the_left, const igraph_vector_t* roots, const igraph_vector_t* align, igraph_real_t hgap, igraph_vector_t* xs) { long int i; long int no_of_nodes = igraph_vcount(graph); igraph_vector_t sinks, shifts, old_xs; igraph_real_t shift; /* Initialization */ IGRAPH_VECTOR_INIT_FINALLY(&sinks, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&shifts, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&old_xs, no_of_nodes); IGRAPH_CHECK(igraph_vector_resize(xs, no_of_nodes)); for (i = 0; i < no_of_nodes; i++) { VECTOR(sinks)[i] = i; } igraph_vector_fill(&shifts, IGRAPH_INFINITY); igraph_vector_fill(xs, -1); /* Calculate the coordinates of the vertices relative to their sinks * in their own class. At the end of this for loop, xs will contain the * relative displacement of a vertex from its sink, while the shifts list * will contain the absolute displacement of the sinks. * (For the sinks only, of course, the rest is undefined and unused) */ for (i = 0; i < no_of_nodes; i++) { if (VECTOR(*roots)[i] == i) { IGRAPH_CHECK( igraph_i_layout_sugiyama_horizontal_compaction_place_block(i, vertex_to_the_left, roots, align, &sinks, &shifts, hgap, xs) ); } } /* In "sinks", only those indices `i` matter for which `i` is in `roots`. * All the other values will never be touched. */ /* Calculate the absolute coordinates */ IGRAPH_CHECK(igraph_vector_update(&old_xs, xs)); for (i = 0; i < no_of_nodes; i++) { long int root = (long int) VECTOR(*roots)[i]; VECTOR(*xs)[i] = VECTOR(old_xs)[root]; shift = VECTOR(shifts)[(long int)VECTOR(sinks)[root]]; if (shift < IGRAPH_INFINITY) { VECTOR(*xs)[i] += shift; } } igraph_vector_destroy(&sinks); igraph_vector_destroy(&shifts); igraph_vector_destroy(&old_xs); IGRAPH_FINALLY_CLEAN(3); return IGRAPH_SUCCESS; } static int igraph_i_layout_sugiyama_horizontal_compaction_place_block(long int v, const igraph_vector_t* vertex_to_the_left, const igraph_vector_t* roots, const igraph_vector_t* align, igraph_vector_t* sinks, igraph_vector_t* shifts, igraph_real_t hgap, igraph_vector_t* xs) { long int u, w; long int u_sink, v_sink; if (VECTOR(*xs)[v] >= 0) { return IGRAPH_SUCCESS; } VECTOR(*xs)[v] = 0; w = v; do { /* Check whether vertex w is the leftmost in its own layer */ u = (long int) VECTOR(*vertex_to_the_left)[w]; if (u != w) { /* Get the root of u (proceeding all the way upwards in the block) */ u = (long int) VECTOR(*roots)[u]; /* Place the block of u recursively */ IGRAPH_CHECK( igraph_i_layout_sugiyama_horizontal_compaction_place_block(u, vertex_to_the_left, roots, align, sinks, shifts, hgap, xs) ); u_sink = (long int) VECTOR(*sinks)[u]; v_sink = (long int) VECTOR(*sinks)[v]; /* If v is its own sink yet, set its sink to the sink of u */ if (v_sink == v) { VECTOR(*sinks)[v] = v_sink = u_sink; } /* If v and u have different sinks (i.e. they are in different classes), * shift the sink of u so that the two blocks are separated by the * preferred gap */ if (v_sink != u_sink) { if (VECTOR(*shifts)[u_sink] > VECTOR(*xs)[v] - VECTOR(*xs)[u] - hgap) { VECTOR(*shifts)[u_sink] = VECTOR(*xs)[v] - VECTOR(*xs)[u] - hgap; } } else { /* v and u have the same sink, i.e. they are in the same class. Make sure * that v is separated from u by at least hgap. */ if (VECTOR(*xs)[v] < VECTOR(*xs)[u] + hgap) { VECTOR(*xs)[v] = VECTOR(*xs)[u] + hgap; } } } /* Follow the alignment */ w = (long int) VECTOR(*align)[w]; } while (w != v); return IGRAPH_SUCCESS; } #undef IS_INNER_SEGMENT #undef IS_DUMMY #undef X_POS #ifdef SUGIYAMA_DEBUG #undef SUGIYAMA_DEBUG #endif python-igraph-0.8.0/vendor/source/igraph/src/progress.c0000644000076500000240000001340613614300625023412 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_progress.h" #include "config.h" static IGRAPH_THREAD_LOCAL igraph_progress_handler_t *igraph_i_progress_handler = 0; static IGRAPH_THREAD_LOCAL char igraph_i_progressmsg_buffer[1000]; /** * \function igraph_progress * Report progress * * Note that the usual way to report progress is the \ref IGRAPH_PROGRESS * macro, as that takes care of the return value of the progress * handler. * \param message A string describing the function or algorithm * that is reporting the progress. Current igraph functions * always use the name \p message argument if reporting from the * same function. * \param percent Numeric, the percentage that was completed by the * algorithm or function. * \param data User-defined data. Current igraph functions that * report progress pass a null pointer here. Users can * write their own progress handlers and functions with progress * reporting, and then pass some meaningfull context here. * \return If there is a progress handler installed and * it does not return \c IGRAPH_SUCCESS, then \c IGRAPH_INTERRUPTED * is returned. * * Time complexity: O(1). */ int igraph_progress(const char *message, igraph_real_t percent, void *data) { if (igraph_i_progress_handler) { if (igraph_i_progress_handler(message, percent, data) != IGRAPH_SUCCESS) { return IGRAPH_INTERRUPTED; } } return IGRAPH_SUCCESS; } /** * \function igraph_progressf * Report progress, printf-like version * * This is a more flexible version of \ref igraph_progress(), with * a printf-like template string. First the template string * is filled with the additional arguments and then \ref * igraph_progress() is called. * * Note that there is an upper limit for the length of * the \p message string, currently 1000 characters. * \param message A string describing the function or algorithm * that is reporting the progress. For this function this is a * template string, using the same syntax as the standard * \c libc \c printf function. * \param percent Numeric, the percentage that was completed by the * algorithm or function. * \param data User-defined data. Current igraph functions that * report progress pass a null pointer here. Users can * write their own progress handlers and functions with progress * reporting, and then pass some meaningfull context here. * \param ... Additional argument that were specified in the * \p message argument. * \return If there is a progress handler installed and * it does not return \c IGRAPH_SUCCESS, then \c IGRAPH_INTERRUPTED * is returned. * \return */ int igraph_progressf(const char *message, igraph_real_t percent, void *data, ...) { va_list ap; va_start(ap, data); vsnprintf(igraph_i_progressmsg_buffer, sizeof(igraph_i_progressmsg_buffer) / sizeof(char), message, ap); return igraph_progress(igraph_i_progressmsg_buffer, percent, data); } #ifndef USING_R /** * \function igraph_progress_handler_stderr * A simple predefined progress handler * * This simple progress handler first prints \p message, and then * the percentage complete value in a short message to standard error. * \param message A string describing the function or algorithm * that is reporting the progress. Current igraph functions * always use the name \p message argument if reporting from the * same function. * \param percent Numeric, the percentage that was completed by the * algorithm or function. * \param data User-defined data. Current igraph functions that * report progress pass a null pointer here. Users can * write their own progress handlers and functions with progress * reporting, and then pass some meaningfull context here. * \return This function always returns with \c IGRAPH_SUCCESS. * * Time complexity: O(1). */ int igraph_progress_handler_stderr(const char *message, igraph_real_t percent, void* data) { IGRAPH_UNUSED(data); fputs(message, stderr); fprintf(stderr, "%.1f percent ready\n", (double)percent); return 0; } #endif /** * \function igraph_set_progress_handler * Install a progress handler, or remove the current handler * * There is a single simple predefined progress handler: * \ref igraph_progress_handler_stderr(). * \param new_handler Pointer to a function of type * \ref igraph_progress_handler_t, the progress handler function to * install. To uninstall the current progress handler, this argument * can be a null pointer. * \return Pointer to the previously installed progress handler function. * * Time complexity: O(1). */ igraph_progress_handler_t * igraph_set_progress_handler(igraph_progress_handler_t new_handler) { igraph_progress_handler_t *previous_handler = igraph_i_progress_handler; igraph_i_progress_handler = new_handler; return previous_handler; } python-igraph-0.8.0/vendor/source/igraph/src/hacks.c0000644000076500000240000000317213614300625022636 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include #include "igraph_hacks_internal.h" /* These are implementations of common C functions that may be missing from some * compilers; for instance, icc does not provide stpcpy so we implement it * here. */ /** * Drop-in replacement for strdup. * Used only in compilers that do not have strdup or _strdup */ char* igraph_i_strdup(const char *s) { size_t n = strlen(s) + 1; char* result = (char*)malloc(sizeof(char) * n); if (result) { memcpy(result, s, n); } return result; } /** * Drop-in replacement for stpcpy. * Used only in compilers that do not have stpcpy */ char* igraph_i_stpcpy(char* s1, const char* s2) { char* result = strcpy(s1, s2); return result + strlen(s1); } python-igraph-0.8.0/vendor/source/igraph/src/scg_utils.c0000644000076500000240000000577613614300625023555 0ustar tamasstaff00000000000000/* * SCGlib : A C library for the spectral coarse graining of matrices * as described in the paper: Shrinking Matrices while preserving their * eigenpairs with Application to the Spectral Coarse Graining of Graphs. * Preprint available at * * Copyright (C) 2008 David Morton de Lachapelle * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 2 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA * 02110-1301 USA * * DESCRIPTION * ----------- * This files contains the data structures and error handing * functions used throughout the SCGlib. */ #include "igraph_error.h" #include "igraph_memory.h" #include "scg_headers.h" /*to be used with qsort and struct ind_val arrays */ int igraph_i_compare_ind_val(const void *a, const void *b) { igraph_i_scg_indval_t *arg1 = (igraph_i_scg_indval_t *) a; igraph_i_scg_indval_t *arg2 = (igraph_i_scg_indval_t *) b; if ( arg1->val < arg2->val ) { return -1; } else if ( arg1->val == arg2->val ) { return 0; } else { return 1; } } /*to be used with qsort and struct groups*/ int igraph_i_compare_groups(const void *a, const void *b) { igraph_i_scg_groups_t *arg1 = (igraph_i_scg_groups_t *) a; igraph_i_scg_groups_t *arg2 = (igraph_i_scg_groups_t *) b; int i; for (i = 0; i < arg1->n; i++) { if (arg1->gr[i] > arg2->gr[i]) { return 1; } else if (arg1->gr[i] < arg2->gr[i]) { return -1; } } return 0; } /*to be used with qsort and real_vectors */ int igraph_i_compare_real(const void *a, const void *b) { igraph_real_t arg1 = * (igraph_real_t *) a; igraph_real_t arg2 = * (igraph_real_t *) b; if (arg1 < arg2) { return -1; } else if (arg1 == arg2) { return 0; } else { return 1; } } /*to be used with qsort and integer vectors */ int igraph_i_compare_int(const void *a, const void *b) { int arg1 = * (int *) a; int arg2 = * (int *) b; return (arg1 - arg2); } /* allocate a igraph_real_t symmetrix matrix with dimension size x size in vector format*/ igraph_real_t *igraph_i_real_sym_matrix(const int size) { igraph_real_t *S = igraph_Calloc(size * (size + 1) / 2, igraph_real_t); if (!S) { igraph_error("allocation failure in real_sym_matrix()", __FILE__, __LINE__, IGRAPH_ENOMEM); } return S; } python-igraph-0.8.0/vendor/source/igraph/src/scg_headers.h0000644000076500000240000001153513614300625024023 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ /* * SCGlib : A C library for the spectral coarse graining of matrices * as described in the paper: Shrinking Matrices while preserving their * eigenpairs with Application to the Spectral Coarse Graining of Graphs. * Preprint available at * * Copyright (C) 2008 David Morton de Lachapelle * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 2 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA * 02110-1301 USA * * DESCRIPTION * ----------- * This file contains the headers of the library SCGlib. * For use with R software define * the constant R_COMPIL and refer to the R documentation to compile * a dynamic library. The scg_r_wrapper function should be useful. */ #ifndef SCG_HEADERS_H #define SCG_HEADERS_H #include #include #include "igraph_types.h" #include "igraph_vector.h" typedef struct ind_val { int ind; igraph_real_t val; } igraph_i_scg_indval_t; int igraph_i_compare_ind_val(const void *a, const void *b); typedef struct groups { int ind; int n; int* gr; } igraph_i_scg_groups_t; /*------------------------------------------------- ------------DEFINED IN scg_approximate_methods.c--- ---------------------------------------------------*/ int igraph_i_breaks_computation(const igraph_vector_t *v, igraph_vector_t *breaks, int nb, int method); int igraph_i_intervals_plus_kmeans(const igraph_vector_t *v, int *gr, int n, int n_interv, int maxiter); int igraph_i_intervals_method(const igraph_vector_t *v, int *gr, int n, int n_interv); /*------------------------------------------------- ------------DEFINED IN scg_optimal_method.c-------- ---------------------------------------------------*/ int igraph_i_cost_matrix(igraph_real_t *Cv, const igraph_i_scg_indval_t *vs, int n, int matrix, const igraph_vector_t *ps); int igraph_i_optimal_partition(const igraph_real_t *v, int *gr, int n, int nt, int matrix, const igraph_real_t *p, igraph_real_t *value); /*------------------------------------------------- ------------DEFINED IN scg_kmeans.c---------------- ---------------------------------------------------*/ int igraph_i_kmeans_Lloyd(const igraph_vector_t *x, int n, int p, igraph_vector_t *centers, int k, int *cl, int maxiter); /*------------------------------------------------- ------------DEFINED IN scg_exact_scg.c------------- ---------------------------------------------------*/ int igraph_i_exact_coarse_graining(const igraph_real_t *v, int *gr, int n); /*------------------------------------------------- ------------DEFINED IN scg_utils.c----------------- ---------------------------------------------------*/ int igraph_i_compare_groups(const void *a, const void *b); int igraph_i_compare_real(const void *a, const void *b); int igraph_i_compare_int(const void *a, const void *b); igraph_real_t *igraph_i_real_sym_matrix(int size); #define igraph_i_real_sym_mat_get(S,i,j) S[i+j*(j+1)/2] #define igraph_i_real_sym_mat_set(S,i,j,val) S[i+j*(j+1)/2] = val #define igraph_i_free_real_sym_matrix(S) igraph_Free(S) #endif python-igraph-0.8.0/vendor/source/igraph/src/igraph_marked_queue.h0000644000076500000240000000470413614300625025555 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_MARKED_QUEUE_H #define IGRAPH_MARKED_QUEUE_H #include "igraph_vector.h" #include "igraph_dqueue.h" #include /* This is essentially a double ended queue, with some extra features: (1) The is-element? operation is fast, O(1). This requires that we know a limit for the number of elements in the queue. (2) We can insert elements in batches, and the whole batch can be removed at once. Currently only the top-end operations are implemented, so the queue is essentially a stack. */ typedef struct igraph_marked_queue_t { igraph_dqueue_t Q; igraph_vector_long_t set; long int mark; long int size; } igraph_marked_queue_t; int igraph_marked_queue_init(igraph_marked_queue_t *q, long int size); void igraph_marked_queue_destroy(igraph_marked_queue_t *q); void igraph_marked_queue_reset(igraph_marked_queue_t *q); igraph_bool_t igraph_marked_queue_empty(const igraph_marked_queue_t *q); long int igraph_marked_queue_size(const igraph_marked_queue_t *q); int igraph_marked_queue_print(const igraph_marked_queue_t *q); int igraph_marked_queue_fprint(const igraph_marked_queue_t *q, FILE *file); igraph_bool_t igraph_marked_queue_iselement(const igraph_marked_queue_t *q, long int elem); int igraph_marked_queue_push(igraph_marked_queue_t *q, long int elem); int igraph_marked_queue_start_batch(igraph_marked_queue_t *q); void igraph_marked_queue_pop_back_batch(igraph_marked_queue_t *q); int igraph_marked_queue_as_vector(const igraph_marked_queue_t *q, igraph_vector_t *vec); #endif python-igraph-0.8.0/vendor/source/igraph/src/stack.pmt0000644000076500000240000001647713614300625023244 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2003-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_types.h" #include "igraph_memory.h" #include "igraph_error.h" #include "config.h" #include #include /* memcpy & co. */ #include /** * \ingroup stack * \function igraph_stack_init * \brief Initializes a stack. * * The initialized stack is always empty. * \param s Pointer to an uninitialized stack. * \param size The number of elements to allocate memory for. * \return Error code. * * Time complexity: O(\p size). */ int FUNCTION(igraph_stack, init) (TYPE(igraph_stack)* s, long int size) { long int alloc_size = size > 0 ? size : 1; assert (s != NULL); if (size < 0) { size = 0; } s->stor_begin = igraph_Calloc(alloc_size, BASE); if (s->stor_begin == 0) { IGRAPH_ERROR("stack init failed", IGRAPH_ENOMEM); } s->stor_end = s->stor_begin + alloc_size; s->end = s->stor_begin; return 0; } /** * \ingroup stack * \function igraph_stack_destroy * \brief Destroys a stack object. * * Deallocate the memory used for a stack. * It is possible to reinitialize a destroyed stack again by * \ref igraph_stack_init(). * \param s The stack to destroy. * * Time complexity: O(1). */ void FUNCTION(igraph_stack, destroy) (TYPE(igraph_stack)* s) { assert( s != NULL); if (s->stor_begin != 0) { igraph_Free(s->stor_begin); s->stor_begin = NULL; } } /** * \ingroup stack * \function igraph_stack_reserve * \brief Reserve memory. * * Reserve memory for future use. The actual size of the stack is * unchanged. * \param s The stack object. * \param size The number of elements to reserve memory for. If it is * not bigger than the current size then nothing happens. * \return Error code. * * Time complexity: should be around O(n), the new allocated size of * the stack. */ int FUNCTION(igraph_stack, reserve) (TYPE(igraph_stack)* s, long int size) { long int actual_size = FUNCTION(igraph_stack, size)(s); BASE *tmp; assert(s != NULL); assert(s->stor_begin != NULL); if (size <= actual_size) { return 0; } tmp = igraph_Realloc(s->stor_begin, (size_t) size, BASE); if (tmp == 0) { IGRAPH_ERROR("stack reserve failed", IGRAPH_ENOMEM); } s->stor_begin = tmp; s->stor_end = s->stor_begin + size; s->end = s->stor_begin + actual_size; return 0; } /** * \ingroup stack * \function igraph_stack_empty * \brief Decides whether a stack object is empty. * * \param s The stack object. * \return Boolean, \c TRUE if the stack is empty, \c FALSE * otherwise. * * Time complexity: O(1). */ igraph_bool_t FUNCTION(igraph_stack, empty) (TYPE(igraph_stack)* s) { assert (s != NULL); assert (s->stor_begin != NULL); assert (s->end != NULL); return s->stor_begin == s->end; } /** * \ingroup stack * \function igraph_stack_size * \brief Returns the number of elements in a stack. * * \param s The stack object. * \return The number of elements in the stack. * * Time complexity: O(1). */ long int FUNCTION(igraph_stack, size) (const TYPE(igraph_stack)* s) { assert (s != NULL); assert (s->stor_begin != NULL); return s->end - s->stor_begin; } /** * \ingroup stack * \function igraph_stack_clear * \brief Removes all elements from a stack. * * \param s The stack object. * * Time complexity: O(1). */ void FUNCTION(igraph_stack, clear) (TYPE(igraph_stack)* s) { assert (s != NULL); assert (s->stor_begin != NULL); s->end = s->stor_begin; } /** * \ingroup stack * \function igraph_stack_push * \brief Places an element on the top of a stack. * * The capacity of the stack is increased, if needed. * \param s The stack object. * \param elem The element to push. * \return Error code. * * Time complexity: O(1) is no reallocation is needed, O(n) * otherwise, but it is ensured that n push operations are performed * in O(n) time. */ int FUNCTION(igraph_stack, push)(TYPE(igraph_stack)* s, BASE elem) { assert (s != NULL); assert (s->stor_begin != NULL); if (s->end == s->stor_end) { /* full, allocate more storage */ BASE *bigger = NULL, *old = s->stor_begin; bigger = igraph_Calloc(2 * FUNCTION(igraph_stack, size)(s) + 1, BASE); if (bigger == 0) { IGRAPH_ERROR("stack push failed", IGRAPH_ENOMEM); } memcpy(bigger, s->stor_begin, (size_t) FUNCTION(igraph_stack, size)(s)*sizeof(BASE)); s->end = bigger + (s->stor_end - s->stor_begin); s->stor_end = bigger + 2 * (s->stor_end - s->stor_begin) + 1; s->stor_begin = bigger; *(s->end) = elem; (s->end) += 1; igraph_Free(old); } else { *(s->end) = elem; (s->end) += 1; } return 0; } /** * \ingroup stack * \function igraph_stack_pop * \brief Removes and returns an element from the top of a stack. * * The stack must contain at least one element, call \ref * igraph_stack_empty() to make sure of this. * \param s The stack object. * \return The removed top element. * * Time complexity: O(1). */ BASE FUNCTION(igraph_stack, pop) (TYPE(igraph_stack)* s) { assert (s != NULL); assert (s->stor_begin != NULL); assert (s->end != NULL); assert (s->end != s->stor_begin); (s->end)--; return *(s->end); } /** * \ingroup stack * \function igraph_stack_top * \brief Query top element. * * Returns the top element of the stack, without removing it. * The stack must be non-empty. * \param s The stack. * \return The top element. * * Time complexity: O(1). */ BASE FUNCTION(igraph_stack, top) (const TYPE(igraph_stack)* s) { assert (s != NULL); assert (s->stor_begin != NULL); assert (s->end != NULL); assert (s->end != s->stor_begin); return *(s->end - 1); } #if defined (OUT_FORMAT) #ifndef USING_R int FUNCTION(igraph_stack, print)(const TYPE(igraph_stack) *s) { long int i, n = FUNCTION(igraph_stack, size)(s); if (n != 0) { printf(OUT_FORMAT, s->stor_begin[0]); } for (i = 1; i < n; i++) { printf(" " OUT_FORMAT, s->stor_begin[i]); } printf("\n"); return 0; } #endif int FUNCTION(igraph_stack, fprint)(const TYPE(igraph_stack) *s, FILE *file) { long int i, n = FUNCTION(igraph_stack, size)(s); if (n != 0) { fprintf(file, OUT_FORMAT, s->stor_begin[0]); } for (i = 1; i < n; i++) { fprintf(file, " " OUT_FORMAT, s->stor_begin[i]); } fprintf(file, "\n"); return 0; } #endif python-igraph-0.8.0/vendor/source/igraph/src/infomap_FlowGraph.cc0000644000076500000240000003120313614300625025306 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "infomap_FlowGraph.h" #define plogp( x ) ( (x) > 0.0 ? (x)*log(x) : 0.0 ) void FlowGraph::init(int n, const igraph_vector_t *v_weights) { alpha = 0.15; beta = 1.0 - alpha; Nnode = n; node = new Node*[Nnode]; if (v_weights) { for (int i = 0; i < Nnode; i++) { node[i] = new Node(i, (double)VECTOR(*v_weights)[i]); } } else { for (int i = 0; i < Nnode; i++) { node[i] = new Node(i, 1.0); } } } FlowGraph::FlowGraph(int n) { init(n, NULL); } FlowGraph::FlowGraph(int n, const igraph_vector_t *v_weights) { init(n, v_weights); } /* Build the graph from igraph_t object */ FlowGraph::FlowGraph(const igraph_t * graph, const igraph_vector_t *e_weights, const igraph_vector_t *v_weights) { int n = (int)igraph_vcount(graph); init(n, v_weights); int directed = (int) igraph_is_directed(graph); double linkWeight = 1.0; igraph_integer_t from, to; long int Nlinks = (long int) igraph_ecount(graph); if (!directed) { Nlinks = Nlinks * 2 ; } for (int i = 0; i < Nlinks; i++) { if (!directed) { // not directed if (i % 2 == 0) { linkWeight = e_weights ? (double)VECTOR(*e_weights)[i / 2] : 1.0; igraph_edge(graph, i / 2, &from, &to); } else { igraph_edge(graph, (i - 1) / 2, &to, &from); } } else { // directed linkWeight = e_weights ? (double)VECTOR(*e_weights)[i] : 1.0; igraph_edge(graph, i, &from, &to); } // Populate node from igraph_graph if (linkWeight > 0.0) { if (from != to) { node[(int) from]->outLinks.push_back(make_pair((int)to, linkWeight)); node[(int) to]->inLinks.push_back(make_pair((int) from, linkWeight)); } } } } FlowGraph::FlowGraph(FlowGraph * fgraph) { int n = fgraph->Nnode; init(n, NULL); for (int i = 0; i < n; i++) { cpyNode(node[i], fgraph->node[i]); } //XXX: quid de danglings et Ndanglings? alpha = fgraph->alpha ; beta = fgraph->beta ; exit = fgraph->exit; exitFlow = fgraph->exitFlow; exit_log_exit = fgraph->exit_log_exit; size_log_size = fgraph->size_log_size ; nodeSize_log_nodeSize = fgraph->nodeSize_log_nodeSize; codeLength = fgraph->codeLength; } /** construct a graph by extracting a subgraph from the given graph */ FlowGraph::FlowGraph(FlowGraph * fgraph, int sub_Nnode, int * sub_members) { init(sub_Nnode, NULL); //XXX: use set of integer to ensure that elements are sorted set sub_mem; for (int j = 0 ; j < sub_Nnode ; j++) { sub_mem.insert(sub_members[j]); } set::iterator it_mem = sub_mem.begin(); vector sub_renumber = vector(fgraph->Nnode); // id --> sub_id for (int j = 0; j < fgraph->Nnode; j++) { sub_renumber[j] = -1; } for (int j = 0; j < sub_Nnode; j++) { //int orig_nr = sub_members[j]; int orig_nr = (*it_mem); node[j]->teleportWeight = fgraph->node[orig_nr]->teleportWeight; node[j]->selfLink = fgraph->node[orig_nr]->selfLink; // Take care of self-link int orig_NoutLinks = fgraph->node[orig_nr]->outLinks.size(); int orig_NinLinks = fgraph->node[orig_nr]->inLinks.size(); sub_renumber[orig_nr] = j; for (int k = 0; k < orig_NoutLinks; k++) { int to = fgraph->node[orig_nr]->outLinks[k].first; int to_newnr = sub_renumber[to]; double link_weight = fgraph->node[orig_nr]->outLinks[k].second; if (to < orig_nr) { // we add links if the destination (to) has already be seen // (ie. smaller than current id) => orig if (sub_mem.find(to) != sub_mem.end()) { // printf("%2d | %4d to %4d\n", j, orig_nr, to); // printf("from %4d (%4d:%1.5f) to %4d (%4d)\n", j, orig_nr, // node[j]->selfLink, to_newnr, to); node[j]->outLinks.push_back(make_pair(to_newnr, link_weight)); node[to_newnr]->inLinks.push_back(make_pair(j, link_weight)); } } } for (int k = 0; k < orig_NinLinks; k++) { int to = fgraph->node[orig_nr]->inLinks[k].first; int to_newnr = sub_renumber[to]; double link_weight = fgraph->node[orig_nr]->inLinks[k].second; if (to < orig_nr) { if (sub_mem.find(to) != sub_mem.end()) { node[j]->inLinks.push_back(make_pair(to_newnr, link_weight)); node[to_newnr]->outLinks.push_back(make_pair(j, link_weight)); } } } it_mem++; } } FlowGraph::~FlowGraph() { //printf("delete FlowGraph !\n"); for (int i = 0; i < Nnode; i++) { delete node[i]; } delete [] node; } void delete_FlowGraph(FlowGraph *fgraph) { delete fgraph; } /** Swap the graph with the one given the graph is "re" calibrate but NOT the given one. */ void FlowGraph::swap(FlowGraph * fgraph) { Node ** node_tmp = fgraph->node; int Nnode_tmp = fgraph->Nnode; fgraph->node = node; fgraph->Nnode = Nnode; node = node_tmp; Nnode = Nnode_tmp; calibrate(); } /** Initialisation of the graph, compute the flow inside the graph * - count danglings nodes * - normalized edge weights * - Call eigenvector() to compute steady state distribution * - call calibrate to compute codelenght */ void FlowGraph::initiate() { // Take care of dangling nodes, normalize outLinks, and calculate // total teleport weight Ndanglings = 0; double totTeleportWeight = 0.0; for (int i = 0; i < Nnode; i++) { totTeleportWeight += node[i]->teleportWeight; } for (int i = 0; i < Nnode; i++) { node[i]->teleportWeight /= totTeleportWeight; // normalize teleportation weight if (node[i]->outLinks.empty() && (node[i]->selfLink <= 0.0)) { danglings.push_back(i); Ndanglings++; } else { // Normalize the weights int NoutLinks = node[i]->outLinks.size(); double sum = node[i]->selfLink; // Take care of self-links for (int j = 0; j < NoutLinks; j++) { sum += node[i]->outLinks[j].second; } node[i]->selfLink /= sum; for (int j = 0; j < NoutLinks; j++) { node[i]->outLinks[j].second /= sum; } } } // Calculate steady state matrix eigenvector(); // Update links to represent flow for (int i = 0; i < Nnode; i++) { node[i]->selfLink = beta * node[i]->size * node[i]->selfLink; // (1 - \tau) * \pi_i * P_{ii} if (!node[i]->outLinks.empty()) { int NoutLinks = node[i]->outLinks.size(); for (int j = 0; j < NoutLinks; j++) { node[i]->outLinks[j].second = beta * node[i]->size * node[i]->outLinks[j].second; // (1 - \tau) * \pi_i * P_{ij} } // Update values for corresponding inlink for (int j = 0; j < NoutLinks; j++) { int NinLinks = node[node[i]->outLinks[j].first]->inLinks.size(); for (int k = 0; k < NinLinks; k++) { if (node[node[i]->outLinks[j].first]->inLinks[k].first == i) { node[node[i]->outLinks[j].first]->inLinks[k].second = node[i]->outLinks[j].second; k = NinLinks; } } } } } // To be able to handle dangling nodes efficiently for (int i = 0; i < Nnode; i++) if (node[i]->outLinks.empty() && (node[i]->selfLink <= 0.0)) { node[i]->danglingSize = node[i]->size; } else { node[i]->danglingSize = 0.0; } nodeSize_log_nodeSize = 0.0 ; // The exit flow from each node at initiation for (int i = 0; i < Nnode; i++) { node[i]->exit = node[i]->size // Proba to be on i - (alpha * node[i]->size + beta * node[i]->danglingSize) * node[i]->teleportWeight // Proba teleport back to i - node[i]->selfLink; // Proba stay on i // node[i]->exit == q_{i\exit} nodeSize_log_nodeSize += plogp(node[i]->size); } calibrate(); } /* Compute steady state distribution (ie. PageRank) over the network * (for all i update node[i]->size) */ void FlowGraph::eigenvector() { vector size_tmp = vector(Nnode, 1.0 / Nnode); int Niterations = 0; double danglingSize; double sqdiff = 1.0; double sqdiff_old; double sum; do { // Calculate dangling size danglingSize = 0.0; for (int i = 0; i < Ndanglings; i++) { danglingSize += size_tmp[danglings[i]]; } // Flow from teleportation for (int i = 0; i < Nnode; i++) { node[i]->size = (alpha + beta * danglingSize) * node[i]->teleportWeight; } // Flow from network steps for (int i = 0; i < Nnode; i++) { node[i]->size += beta * node[i]->selfLink * size_tmp[i]; int Nlinks = node[i]->outLinks.size(); for (int j = 0; j < Nlinks; j++) node[node[i]->outLinks[j].first]->size += beta * node[i]->outLinks[j].second * size_tmp[i]; } // Normalize sum = 0.0; for (int i = 0; i < Nnode; i++) { sum += node[i]->size; } sqdiff_old = sqdiff; sqdiff = 0.0; for (int i = 0; i < Nnode; i++) { node[i]->size /= sum; sqdiff += fabs(node[i]->size - size_tmp[i]); size_tmp[i] = node[i]->size; } Niterations++; if (sqdiff == sqdiff_old) { alpha += 1.0e-10; beta = 1.0 - alpha; } } while ((Niterations < 200) && (sqdiff > 1.0e-15 || Niterations < 50)); danglingSize = 0.0; for (int i = 0; i < Ndanglings; i++) { danglingSize += size_tmp[danglings[i]]; } // cout << "done! (the error is " << sqdiff << " after " << Niterations // << " iterations)" << endl; } /* Compute the codeLength of the given network * note: (in **node, one node == one module) */ void FlowGraph::calibrate() { exit_log_exit = 0.0; exitFlow = 0.0; size_log_size = 0.0; for (int i = 0; i < Nnode; i++) { // For each module // own node/module codebook size_log_size += plogp(node[i]->exit + node[i]->size); // use of index codebook exitFlow += node[i]->exit; exit_log_exit += plogp(node[i]->exit); } exit = plogp(exitFlow); codeLength = exit - 2.0 * exit_log_exit + size_log_size - nodeSize_log_nodeSize; } /* Restore the data from the given FlowGraph object */ void FlowGraph::back_to(FlowGraph * fgraph) { // delete current nodes for (int i = 0 ; i < Nnode ; i++) { delete node[i]; } delete [] node; Nnode = fgraph->Nnode; // copy original ones node = new Node*[Nnode]; for (int i = 0; i < Nnode; i++) { node[i] = new Node(); cpyNode(node[i], fgraph->node[i]); } // restore atributs alpha = fgraph->alpha ; beta = fgraph->beta ; exit = fgraph->exit; exitFlow = fgraph->exitFlow; exit_log_exit = fgraph->exit_log_exit; size_log_size = fgraph->size_log_size ; nodeSize_log_nodeSize = fgraph->nodeSize_log_nodeSize; codeLength = fgraph->codeLength; } python-igraph-0.8.0/vendor/source/igraph/src/igraph_set.c0000644000076500000240000002074013614300625023672 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_types.h" #include "igraph_memory.h" #include "igraph_error.h" #include "igraph_types_internal.h" #include "config.h" #include #include /* memmove */ #define SET(s) ((s).stor_begin) /** * \ingroup set * \function igraph_set_init * \brief Initializes a set. * * \param set pointer to the set to be initialized * \param size the expected number of elements in the set * * \return error code: * \c IGRAPH_ENOMEM if there is not enough memory. * * Time complexity: operating system dependent, should be around * O(n), n is the expected size of the set. */ int igraph_set_init(igraph_set_t *set, int long size) { long int alloc_size = size > 0 ? size : 1; if (size < 0) { size = 0; } set->stor_begin = igraph_Calloc(alloc_size, igraph_integer_t); set->stor_end = set->stor_begin + alloc_size; set->end = set->stor_begin; return 0; } /** * \ingroup set * \function igraph_set_destroy * \brief Destroys a set object. * * \param set pointer to the set to be destroyed * * Time complexity: operating system dependent. */ void igraph_set_destroy(igraph_set_t* set) { assert(set != 0); if (set->stor_begin != 0) { igraph_Free(set->stor_begin); set->stor_begin = NULL; } } /** * \ingroup set * \function igraph_set_inited * \brief Determines whether a set is initialized or not. * * This function checks whether the internal storage for the members of the * set has been allocated or not, and it assumes that the pointer for the * internal storage area contains \c NULL if the area is not initialized yet. * This only applies if you have allocated an array of sets with \c igraph_Calloc or * if you used the \c IGRAPH_SET_NULL constant to initialize the set. * * \param set The set object. * * Time complexity: O(1) */ igraph_bool_t igraph_set_inited(igraph_set_t* set) { return (set->stor_begin != 0); } /** * \ingroup set * \function igraph_set_reserve * \brief Reserve memory for a set. * * \param set The set object. * \param size the new \em allocated size of the set. * * Time complexity: operating system dependent, should be around * O(n), n is the new allocated size of the set. */ int igraph_set_reserve(igraph_set_t* set, long int size) { long int actual_size = igraph_set_size(set); igraph_integer_t *tmp; assert(set != NULL); assert(set->stor_begin != NULL); if (size <= actual_size) { return 0; } tmp = igraph_Realloc(set->stor_begin, (size_t) size, igraph_integer_t); if (tmp == 0) { IGRAPH_ERROR("cannot reserve space for set", IGRAPH_ENOMEM); } set->stor_begin = tmp; set->stor_end = set->stor_begin + size; set->end = set->stor_begin + actual_size; return 0; } /** * \ingroup set * \function igraph_set_empty * \brief Decides whether the size of the set is zero. * * \param set The set object. * \return Non-zero number if the size of the set is not zero and * zero otherwise. * * Time complexity: O(1). */ igraph_bool_t igraph_set_empty(const igraph_set_t* set) { assert(set != NULL); assert(set->stor_begin != NULL); return set->stor_begin == set->end; } /** * \ingroup set * \function igraph_set_clear * \brief Removes all elements from a set. * * * This function simply sets the size of the set to zero, it does * not free any allocated memory. For that you have to call * \ref igraph_set_destroy(). * \param v The set object. * * Time complexity: O(1). */ void igraph_set_clear(igraph_set_t* set) { assert(set != NULL); assert(set->stor_begin != NULL); set->end = set->stor_begin; } /** * \ingroup set * \function igraph_set_size * \brief Gives the size (=length) of the set. * * \param v The set object * \return The size of the set. * * Time complexity: O(1). */ long int igraph_set_size(const igraph_set_t* set) { assert(set != NULL); assert(set->stor_begin != NULL); return set->end - set->stor_begin; } /** * \ingroup set * \function igraph_set_add * \brief Adds an element to the set. * * \param set The set object. * \param e The element to be added. * \return Error code: * \c IGRAPH_ENOMEM: not enough memory. * * Time complexity: O(log(n)), n is the number of elements in \p set. */ int igraph_set_add(igraph_set_t* set, igraph_integer_t e) { long int left, right, middle; long int size; assert(set != NULL); assert(set->stor_begin != NULL); size = igraph_set_size(set); /* search where to insert the new element */ left = 0; right = size - 1; while (left < right - 1) { middle = (left + right) / 2; if (SET(*set)[middle] > e) { right = middle; } else if (SET(*set)[middle] < e) { left = middle; } else { left = middle; break; } } if (right >= 0 && SET(*set)[left] != e && SET(*set)[right] == e) { left = right; } while (left < size && set->stor_begin[left] < e) { left++; } if (left >= size || set->stor_begin[left] != e) { /* full, allocate more storage */ if (set->stor_end == set->end) { long int new_size = size * 2; if (new_size == 0) { new_size = 1; } IGRAPH_CHECK(igraph_set_reserve(set, new_size)); } /* Element should be inserted at position 'left' */ if (left < size) memmove(set->stor_begin + left + 1, set->stor_begin + left, (size_t) (size - left)*sizeof(set->stor_begin[0])); set->stor_begin[left] = e; set->end += 1; } return 0; } /** * \ingroup set * \function igraph_set_contains * \brief Checks whether a given element is in the set or not. * * \param set The set object. * \param e The element being sought. * \return Positive integer (true) if \p e is found, zero (false) otherwise. * * Time complexity: O(log(n)), n is the number of elements in \p set. */ int igraph_set_contains(igraph_set_t* set, igraph_integer_t e) { long int left, right, middle; assert(set != NULL); assert(set->stor_begin != NULL); left = 0; right = igraph_set_size(set) - 1; if (right == -1) { return 0; /* the set is empty */ } /* search for the new element */ while (left < right - 1) { middle = (left + right) / 2; if (SET(*set)[middle] > e) { right = middle; } else if (SET(*set)[middle] < e) { left = middle; } else { return 1; } } return SET(*set)[left] == e || SET(*set)[right] == e; } /** * \ingroup set * \function igraph_set_iterate * \brief Iterates through the element to the set. * * Elements are returned in an arbitrary order. * * \param set The set object. * \param state Internal state of the iteration. * This should be a pointer to a \c long variable * which must be zero for the first invocation. * The object should not be adjusted and its value should * not be used for anything during the iteration. * \param element The next element or \c NULL (if the iteration * has ended) is returned here. * * \return Nonzero if there are more elements, zero otherwise. */ igraph_bool_t igraph_set_iterate(igraph_set_t* set, long int* state, igraph_integer_t* element) { assert(set != 0); assert(set->stor_begin != 0); assert(state != 0); assert(element != 0); if (*state < igraph_set_size(set)) { *element = set->stor_begin[*state]; *state = *state + 1; return 1; } else { *element = 0; return 0; } } python-igraph-0.8.0/vendor/source/igraph/src/types.c0000644000076500000240000001033013614300625022703 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_types.h" #include #ifdef _MSC_VER #define snprintf _snprintf #endif #ifdef DBL_DIG /* Use DBL_DIG to determine the maximum precision used for %g */ #define STRINGIFY_HELPER(x) #x #define STRINGIFY(x) STRINGIFY_HELPER(x) #define IGRAPH_REAL_PRINTF_PRECISE_FORMAT "%." STRINGIFY(DBL_DIG) "g" #else /* Assume a precision of 10 digits for %g */ #define IGRAPH_REAL_PRINTF_PRECISE_FORMAT "%.10g" #endif #ifndef USING_R int igraph_real_printf(igraph_real_t val) { if (igraph_finite(val)) { return printf("%g", val); } else if (igraph_is_nan(val)) { return printf("NaN"); } else if (igraph_is_inf(val)) { if (val < 0) { return printf("-Inf"); } else { return printf("Inf"); } } else { /* fallback */ return printf("%g", val); } } #endif int igraph_real_fprintf(FILE *file, igraph_real_t val) { if (igraph_finite(val)) { return fprintf(file, "%g", val); } else if (igraph_is_nan(val)) { return fprintf(file, "NaN"); } else if (igraph_is_inf(val)) { if (val < 0) { return fprintf(file, "-Inf"); } else { return fprintf(file, "Inf"); } } else { /* fallback */ return fprintf(file, "%g", val); } } int igraph_real_snprintf(char* str, size_t size, igraph_real_t val) { if (igraph_finite(val)) { return snprintf(str, size, "%g", val); } else if (igraph_is_nan(val)) { return snprintf(str, size, "NaN"); } else if (igraph_is_inf(val)) { if (val < 0) { return snprintf(str, size, "-Inf"); } else { return snprintf(str, size, "Inf"); } } else { /* fallback */ return snprintf(str, size, "%g", val); } } #ifndef USING_R int igraph_real_printf_precise(igraph_real_t val) { if (igraph_finite(val)) { return printf(IGRAPH_REAL_PRINTF_PRECISE_FORMAT, val); } else if (igraph_is_nan(val)) { return printf("NaN"); } else if (igraph_is_inf(val)) { if (val < 0) { return printf("-Inf"); } else { return printf("Inf"); } } else { /* fallback */ return printf(IGRAPH_REAL_PRINTF_PRECISE_FORMAT, val); } } #endif int igraph_real_fprintf_precise(FILE *file, igraph_real_t val) { if (igraph_finite(val)) { return fprintf(file, IGRAPH_REAL_PRINTF_PRECISE_FORMAT, val); } else if (igraph_is_nan(val)) { return fprintf(file, "NaN"); } else if (igraph_is_inf(val)) { if (val < 0) { return fprintf(file, "-Inf"); } else { return fprintf(file, "Inf"); } } else { /* fallback */ return fprintf(file, IGRAPH_REAL_PRINTF_PRECISE_FORMAT, val); } } int igraph_real_snprintf_precise(char* str, size_t size, igraph_real_t val) { if (igraph_finite(val)) { return snprintf(str, size, IGRAPH_REAL_PRINTF_PRECISE_FORMAT, val); } else if (igraph_is_nan(val)) { return snprintf(str, size, "NaN"); } else if (igraph_is_inf(val)) { if (val < 0) { return snprintf(str, size, "-Inf"); } else { return snprintf(str, size, "Inf"); } } else { /* fallback */ return snprintf(str, size, IGRAPH_REAL_PRINTF_PRECISE_FORMAT, val); } } python-igraph-0.8.0/vendor/source/igraph/src/atlas.c0000644000076500000240000000541013614300625022646 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph R package. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_constructors.h" #include "atlas-edges.h" #include "config.h" /** * \function igraph_atlas * \brief Create a small graph from the \quote Graph Atlas \endquote. * * * The number of the graph is given as a parameter. * The graphs are listed: \olist * \oli in increasing order of number of nodes; * \oli for a fixed number of nodes, in increasing order of the * number of edges; * \oli for fixed numbers of nodes and edges, in increasing * order of the degree sequence, for example 111223 < 112222; * \oli for fixed degree sequence, in increasing number of * automorphisms. * \endolist * * * The data was converted from the NetworkX software package, * see http://networkx.github.io . * * * See \emb An Atlas of Graphs \eme by Ronald C. Read and Robin J. Wilson, * Oxford University Press, 1998. * * \param graph Pointer to an uninitialized graph object. * \param number The number of the graph to generate. * * Added in version 0.2. * * Time complexity: O(|V|+|E|), the number of vertices plus the number of * edges. * * \example examples/simple/igraph_atlas.c */ int igraph_atlas(igraph_t *graph, int number) { igraph_integer_t pos, n, e; igraph_vector_t v = IGRAPH_VECTOR_NULL; if (number < 0 || number >= (int) (sizeof(igraph_i_atlas_edges_pos) / sizeof(long int))) { IGRAPH_ERROR("No such graph in atlas", IGRAPH_EINVAL); } pos = (igraph_integer_t) igraph_i_atlas_edges_pos[number]; n = (igraph_integer_t) igraph_i_atlas_edges[pos]; e = (igraph_integer_t) igraph_i_atlas_edges[pos + 1]; IGRAPH_CHECK(igraph_create(graph, igraph_vector_view(&v, igraph_i_atlas_edges + pos + 2, e * 2), n, IGRAPH_UNDIRECTED)); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/distances.c0000644000076500000240000001626013614300625023524 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_datatype.h" #include "igraph_dqueue.h" #include "igraph_iterators.h" #include "igraph_interrupt_internal.h" #include "igraph_vector.h" #include "igraph_interface.h" #include "igraph_adjlist.h" int igraph_i_eccentricity(const igraph_t *graph, igraph_vector_t *res, igraph_vs_t vids, igraph_neimode_t mode, const igraph_adjlist_t *adjlist) { int no_of_nodes = igraph_vcount(graph); igraph_dqueue_long_t q; igraph_vit_t vit; igraph_vector_int_t counted; int i, mark = 1; igraph_vector_t vneis; igraph_vector_int_t *neis; IGRAPH_CHECK(igraph_dqueue_long_init(&q, 100)); IGRAPH_FINALLY(igraph_dqueue_long_destroy, &q); IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); IGRAPH_CHECK(igraph_vector_int_init(&counted, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_int_destroy, &counted); if (!adjlist) { IGRAPH_VECTOR_INIT_FINALLY(&vneis, 0); } IGRAPH_CHECK(igraph_vector_resize(res, IGRAPH_VIT_SIZE(vit))); igraph_vector_fill(res, -1); for (i = 0, IGRAPH_VIT_RESET(vit); !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit), mark++, i++) { long int source; source = IGRAPH_VIT_GET(vit); IGRAPH_CHECK(igraph_dqueue_long_push(&q, source)); IGRAPH_CHECK(igraph_dqueue_long_push(&q, 0)); VECTOR(counted)[source] = mark; IGRAPH_ALLOW_INTERRUPTION(); while (!igraph_dqueue_long_empty(&q)) { long int act = igraph_dqueue_long_pop(&q); long int dist = igraph_dqueue_long_pop(&q); int j, n; if (dist > VECTOR(*res)[i]) { VECTOR(*res)[i] = dist; } if (adjlist) { neis = igraph_adjlist_get(adjlist, act); n = (int) igraph_vector_int_size(neis); for (j = 0; j < n; j++) { int nei = (int) VECTOR(*neis)[j]; if (VECTOR(counted)[nei] != mark) { VECTOR(counted)[nei] = mark; IGRAPH_CHECK(igraph_dqueue_long_push(&q, nei)); IGRAPH_CHECK(igraph_dqueue_long_push(&q, dist + 1)); } } } else { IGRAPH_CHECK(igraph_neighbors(graph, &vneis, (igraph_integer_t) act, mode)); n = (int) igraph_vector_size(&vneis); for (j = 0; j < n; j++) { int nei = (int) VECTOR(vneis)[j]; if (VECTOR(counted)[nei] != mark) { VECTOR(counted)[nei] = mark; IGRAPH_CHECK(igraph_dqueue_long_push(&q, nei)); IGRAPH_CHECK(igraph_dqueue_long_push(&q, dist + 1)); } } } } /* while !igraph_dqueue_long_empty(dqueue) */ } /* for IGRAPH_VIT_NEXT(vit) */ if (!adjlist) { igraph_vector_destroy(&vneis); IGRAPH_FINALLY_CLEAN(1); } igraph_vector_int_destroy(&counted); igraph_vit_destroy(&vit); igraph_dqueue_long_destroy(&q); IGRAPH_FINALLY_CLEAN(3); return 0; } /** * \function igraph_eccentricity * Eccentricity of some vertices * * The eccentricity of a vertex is calculated by measuring the shortest * distance from (or to) the vertex, to (or from) all vertices in the * graph, and taking the maximum. * * * This implementation ignores vertex pairs that are in different * components. Isolated vertices have eccentricity zero. * * \param graph The input graph, it can be directed or undirected. * \param res Pointer to an initialized vector, the result is stored * here. * \param vids The vertices for which the eccentricity is calculated. * \param mode What kind of paths to consider for the calculation: * \c IGRAPH_OUT, paths that follow edge directions; * \c IGRAPH_IN, paths that follow the opposite directions; and * \c IGRAPH_ALL, paths that ignore edge directions. This argument * is ignored for undirected graphs. * \return Error code. * * Time complexity: O(v*(|V|+|E|)), where |V| is the number of * vertices, |E| is the number of edges and v is the number of * vertices for which eccentricity is calculated. * * \sa \ref igraph_radius(). * * \example examples/simple/igraph_eccentricity.c */ int igraph_eccentricity(const igraph_t *graph, igraph_vector_t *res, igraph_vs_t vids, igraph_neimode_t mode) { return igraph_i_eccentricity(graph, res, vids, mode, /*adjlist=*/ 0); } /** * \function igraph_radius * Radius of a graph * * The radius of a graph is the defined as the minimum eccentricity of * its vertices, see \ref igraph_eccentricity(). * * \param graph The input graph, it can be directed or undirected. * \param radius Pointer to a real variable, the result is stored * here. * \param mode What kind of paths to consider for the calculation: * \c IGRAPH_OUT, paths that follow edge directions; * \c IGRAPH_IN, paths that follow the opposite directions; and * \c IGRAPH_ALL, paths that ignore edge directions. This argument * is ignored for undirected graphs. * \return Error code. * * Time complexity: O(|V|(|V|+|E|)), where |V| is the number of * vertices and |E| is the number of edges. * * \sa \ref igraph_eccentricity(). * * \example examples/simple/igraph_radius.c */ int igraph_radius(const igraph_t *graph, igraph_real_t *radius, igraph_neimode_t mode) { int no_of_nodes = igraph_vcount(graph); if (no_of_nodes == 0) { *radius = IGRAPH_NAN; } else { igraph_adjlist_t adjlist; igraph_vector_t ecc; IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist, mode)); IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist); IGRAPH_VECTOR_INIT_FINALLY(&ecc, igraph_vcount(graph)); IGRAPH_CHECK(igraph_i_eccentricity(graph, &ecc, igraph_vss_all(), mode, &adjlist)); *radius = igraph_vector_min(&ecc); igraph_vector_destroy(&ecc); igraph_adjlist_destroy(&adjlist); IGRAPH_FINALLY_CLEAN(2); } return 0; } python-igraph-0.8.0/vendor/source/igraph/src/other.c0000644000076500000240000003743213614300625022674 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2005-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_nongraph.h" #include "igraph_types.h" #include "igraph_memory.h" #include "igraph_interrupt_internal.h" #include "igraph_types_internal.h" #include "config.h" #include "plfit/error.h" #include "plfit/plfit.h" #include #include #include /** * \ingroup nongraph * \function igraph_running_mean * \brief Calculates the running mean of a vector. * * * The running mean is defined by the mean of the * previous \p binwidth values. * \param data The vector containing the data. * \param res The vector containing the result. This should be * initialized before calling this function and will be * resized. * \param binwidth Integer giving the width of the bin for the running * mean calculation. * \return Error code. * * Time complexity: O(n), * n is the length of * the data vector. */ int igraph_running_mean(const igraph_vector_t *data, igraph_vector_t *res, igraph_integer_t binwidth) { double sum = 0; long int i; /* Check */ if (igraph_vector_size(data) < binwidth) { IGRAPH_ERROR("Vector too short for this binwidth", IGRAPH_EINVAL); } /* Memory for result */ IGRAPH_CHECK(igraph_vector_resize(res, (long int)(igraph_vector_size(data) - binwidth + 1))); /* Initial bin */ for (i = 0; i < binwidth; i++) { sum += VECTOR(*data)[i]; } VECTOR(*res)[0] = sum / binwidth; for (i = 1; i < igraph_vector_size(data) - binwidth + 1; i++) { IGRAPH_ALLOW_INTERRUPTION(); sum -= VECTOR(*data)[i - 1]; sum += VECTOR(*data)[ (long int)(i + binwidth - 1)]; VECTOR(*res)[i] = sum / binwidth; } return 0; } /** * \ingroup nongraph * \function igraph_convex_hull * \brief Determines the convex hull of a given set of points in the 2D plane * * * The convex hull is determined by the Graham scan algorithm. * See the following reference for details: * * * Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford * Stein. Introduction to Algorithms, Second Edition. MIT Press and * McGraw-Hill, 2001. ISBN 0262032937. Pages 949-955 of section 33.3: * Finding the convex hull. * * \param data vector containing the coordinates. The length of the * vector must be even, since it contains X-Y coordinate pairs. * \param resverts the vector containing the result, e.g. the vector of * vertex indices used as the corners of the convex hull. Supply * \c NULL here if you are only interested in the coordinates of * the convex hull corners. * \param rescoords the matrix containing the coordinates of the selected * corner vertices. Supply \c NULL here if you are only interested in * the vertex indices. * \return Error code: * \c IGRAPH_ENOMEM: not enough memory * * Time complexity: O(n log(n)) where n is the number of vertices * * \example examples/simple/igraph_convex_hull.c */ int igraph_convex_hull(const igraph_matrix_t *data, igraph_vector_t *resverts, igraph_matrix_t *rescoords) { igraph_integer_t no_of_nodes; long int i, pivot_idx = 0, last_idx, before_last_idx, next_idx, j; igraph_vector_t angles, stack, order; igraph_real_t px, py, cp; no_of_nodes = (igraph_integer_t) igraph_matrix_nrow(data); if (igraph_matrix_ncol(data) != 2) { IGRAPH_ERROR("matrix must have 2 columns", IGRAPH_EINVAL); } if (no_of_nodes == 0) { if (resverts != 0) { IGRAPH_CHECK(igraph_vector_resize(resverts, 0)); } if (rescoords != 0) { IGRAPH_CHECK(igraph_matrix_resize(rescoords, 0, 2)); } /**************************** this is an exit here *********/ return 0; } IGRAPH_VECTOR_INIT_FINALLY(&angles, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&stack, 0); /* Search for the pivot vertex */ for (i = 1; i < no_of_nodes; i++) { if (MATRIX(*data, i, 1) < MATRIX(*data, pivot_idx, 1)) { pivot_idx = i; } else if (MATRIX(*data, i, 1) == MATRIX(*data, pivot_idx, 1) && MATRIX(*data, i, 0) < MATRIX(*data, pivot_idx, 0)) { pivot_idx = i; } } px = MATRIX(*data, pivot_idx, 0); py = MATRIX(*data, pivot_idx, 1); /* Create angle array */ for (i = 0; i < no_of_nodes; i++) { if (i == pivot_idx) { /* We can't calculate the angle of the pivot point with itself, * so we use 10 here. This way, after sorting the angle vector, * the pivot point will always be the first one, since the range * of atan2 is -3.14..3.14 */ VECTOR(angles)[i] = 10; } else { VECTOR(angles)[i] = atan2(MATRIX(*data, i, 1) - py, MATRIX(*data, i, 0) - px); } } /* Sort points by angles */ IGRAPH_VECTOR_INIT_FINALLY(&order, no_of_nodes); IGRAPH_CHECK(igraph_vector_qsort_ind(&angles, &order, 0)); /* Check if two points have the same angle. If so, keep only the point that * is farthest from the pivot */ j = 0; last_idx = (long int) VECTOR(order)[0]; pivot_idx = (long int) VECTOR(order)[no_of_nodes - 1]; for (i = 1; i < no_of_nodes; i++) { next_idx = (long int) VECTOR(order)[i]; if (VECTOR(angles)[last_idx] == VECTOR(angles)[next_idx]) { /* Keep the vertex that is farther from the pivot, drop the one that is * closer */ px = pow(MATRIX(*data, last_idx, 0) - MATRIX(*data, pivot_idx, 0), 2) + pow(MATRIX(*data, last_idx, 1) - MATRIX(*data, pivot_idx, 1), 2); py = pow(MATRIX(*data, next_idx, 0) - MATRIX(*data, pivot_idx, 0), 2) + pow(MATRIX(*data, next_idx, 1) - MATRIX(*data, pivot_idx, 1), 2); if (px > py) { VECTOR(order)[i] = -1; } else { VECTOR(order)[j] = -1; last_idx = next_idx; j = i; } } else { last_idx = next_idx; j = i; } } j = 0; last_idx = -1; before_last_idx = -1; while (!igraph_vector_empty(&order)) { next_idx = (long int)VECTOR(order)[igraph_vector_size(&order) - 1]; if (next_idx < 0) { /* This vertex should be skipped; was excluded in an earlier step */ igraph_vector_pop_back(&order); continue; } /* Determine whether we are at a left or right turn */ if (j < 2) { /* Pretend that we are turning into the right direction if we have less * than two items in the stack */ cp = -1; } else { cp = (MATRIX(*data, last_idx, 0) - MATRIX(*data, before_last_idx, 0)) * (MATRIX(*data, next_idx, 1) - MATRIX(*data, before_last_idx, 1)) - (MATRIX(*data, next_idx, 0) - MATRIX(*data, before_last_idx, 0)) * (MATRIX(*data, last_idx, 1) - MATRIX(*data, before_last_idx, 1)); } /* printf("B L N cp: %ld, %ld, %ld, %f [", before_last_idx, last_idx, next_idx, (float)cp); for (int k=0; k= 2) ? (long int) VECTOR(stack)[j - 2] : -1; } } /* Create result vector */ if (resverts != 0) { igraph_vector_clear(resverts); IGRAPH_CHECK(igraph_vector_append(resverts, &stack)); } if (rescoords != 0) { igraph_matrix_select_rows(data, rescoords, &stack); } /* Free everything */ igraph_vector_destroy(&order); igraph_vector_destroy(&stack); igraph_vector_destroy(&angles); IGRAPH_FINALLY_CLEAN(3); return 0; } static const char* igraph_i_plfit_error_message = 0; static void igraph_i_plfit_error_handler_store(const char *reason, const char *file, int line, int plfit_errno) { igraph_i_plfit_error_message = reason; } /** * \ingroup nongraph * \function igraph_power_law_fit * \brief Fits a power-law distribution to a vector of numbers * * This function fits a power-law distribution to a vector containing samples * from a distribution (that is assumed to follow a power-law of course). In * a power-law distribution, it is generally assumed that P(X=x) is * proportional to x-alpha, where x is a positive number and alpha * is greater than 1. In many real-world cases, the power-law behaviour kicks * in only above a threshold value \em xmin. The goal of this functions is to * determine \em alpha if \em xmin is given, or to determine \em xmin and the * corresponding value of \em alpha. * * * The function uses the maximum likelihood principle to determine \em alpha * for a given \em xmin; in other words, the function will return the \em alpha * value for which the probability of drawing the given sample is the highest. * When \em xmin is not given in advance, the algorithm will attempt to find * the optimal \em xmin value for which the p-value of a Kolmogorov-Smirnov * test between the fitted distribution and the original sample is the largest. * The function uses the method of Clauset, Shalizi and Newman to calculate the * parameters of the fitted distribution. See the following reference for * details: * * * Aaron Clauset, Cosma R .Shalizi and Mark E.J. Newman: Power-law * distributions in empirical data. SIAM Review 51(4):661-703, 2009. * * \param data vector containing the samples for which a power-law distribution * is to be fitted. Note that you have to provide the \em samples, * not the probability density function or the cumulative * distribution function. For example, if you wish to fit * a power-law to the degrees of a graph, you can use the output of * \ref igraph_degree directly as an input argument to * \ref igraph_power_law_fit * \param result the result of the fitting algorithm. See \ref igraph_plfit_result_t * for more details. * \param xmin the minimum value in the sample vector where the power-law * behaviour is expected to kick in. Samples smaller than \c xmin * will be ignored by the algoritm. Pass zero here if you want to * include all the samples. If \c xmin is negative, the algorithm * will attempt to determine its best value automatically. * \param force_continuous assume that the samples in the \c data argument come * from a continuous distribution even if the sample vector * contains integer values only (by chance). If this argument is * false, igraph will assume a continuous distribution if at least * one sample is non-integer and assume a discrete distribution * otherwise. * \return Error code: * \c IGRAPH_ENOMEM: not enough memory * \c IGRAPH_EINVAL: one of the arguments is invalid * \c IGRAPH_EOVERFLOW: overflow during the fitting process * \c IGRAPH_EUNDERFLOW: underflow during the fitting process * \c IGRAPH_FAILURE: the underlying algorithm signaled a failure * without returning a more specific error code * * Time complexity: in the continuous case, O(n log(n)) if \c xmin is given. * In the discrete case, the time complexity is dominated by the complexity of * the underlying L-BFGS algorithm that is used to optimize alpha. If \c xmin * is not given, the time complexity is multiplied by the number of unique * samples in the input vector (although it should be faster in practice). * * \example examples/simple/igraph_power_law_fit.c */ int igraph_power_law_fit(const igraph_vector_t* data, igraph_plfit_result_t* result, igraph_real_t xmin, igraph_bool_t force_continuous) { plfit_error_handler_t* plfit_stored_error_handler; plfit_result_t plfit_result; plfit_continuous_options_t cont_options; plfit_discrete_options_t disc_options; igraph_bool_t discrete = force_continuous ? 0 : 1; igraph_bool_t finite_size_correction; int retval; size_t i, n; n = (size_t) igraph_vector_size(data); finite_size_correction = (n < 50); if (discrete) { /* Does the vector contain discrete values only? */ for (i = 0; i < n; i++) { if ((long int)(VECTOR(*data)[i]) != VECTOR(*data)[i]) { discrete = 0; break; } } } plfit_stored_error_handler = plfit_set_error_handler(igraph_i_plfit_error_handler_store); if (discrete) { plfit_discrete_options_init(&disc_options); disc_options.finite_size_correction = (plfit_bool_t) finite_size_correction; if (xmin >= 0) { retval = plfit_estimate_alpha_discrete(VECTOR(*data), n, xmin, &disc_options, &plfit_result); } else { retval = plfit_discrete(VECTOR(*data), n, &disc_options, &plfit_result); } } else { plfit_continuous_options_init(&cont_options); cont_options.finite_size_correction = (plfit_bool_t) finite_size_correction; if (xmin >= 0) { retval = plfit_estimate_alpha_continuous(VECTOR(*data), n, xmin, &cont_options, &plfit_result); } else { retval = plfit_continuous(VECTOR(*data), n, &cont_options, &plfit_result); } } plfit_set_error_handler(plfit_stored_error_handler); switch (retval) { case PLFIT_FAILURE: IGRAPH_ERROR(igraph_i_plfit_error_message, IGRAPH_FAILURE); break; case PLFIT_EINVAL: IGRAPH_ERROR(igraph_i_plfit_error_message, IGRAPH_EINVAL); break; case PLFIT_UNDRFLOW: IGRAPH_ERROR(igraph_i_plfit_error_message, IGRAPH_EUNDERFLOW); break; case PLFIT_OVERFLOW: IGRAPH_ERROR(igraph_i_plfit_error_message, IGRAPH_EOVERFLOW); break; case PLFIT_ENOMEM: IGRAPH_ERROR(igraph_i_plfit_error_message, IGRAPH_ENOMEM); break; default: break; } if (result) { result->continuous = !discrete; result->alpha = plfit_result.alpha; result->xmin = plfit_result.xmin; result->L = plfit_result.L; result->D = plfit_result.D; result->p = plfit_result.p; } return 0; } /** * Internal function, floating point division * Used only in compilers not supporting INFINITY and HUGE_VAL to create * infinity values */ double igraph_i_fdiv(const double a, const double b) { return a / b; } python-igraph-0.8.0/vendor/source/igraph/src/gengraph_random.h0000644000076500000240000001651513614300625024712 0ustar tamasstaff00000000000000/* * * gengraph - generation of random simple connected graphs with prescribed * degree sequence * * Copyright (C) 2006 Fabien Viger * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #ifndef RNG_H #define RNG_H #include "igraph_random.h" #include using namespace std; namespace KW_RNG { typedef signed int sint; typedef unsigned int uint; typedef signed long slong; typedef unsigned long ulong; class RNG { public: RNG() { } RNG(ulong z_, ulong w_, ulong jsr_, ulong jcong_ ) { IGRAPH_UNUSED(z_); IGRAPH_UNUSED(w_); IGRAPH_UNUSED(jsr_); IGRAPH_UNUSED(jcong_); }; ~RNG() { } void init(ulong z_, ulong w_, ulong jsr_, ulong jcong_ ) { IGRAPH_UNUSED(z_); IGRAPH_UNUSED(w_); IGRAPH_UNUSED(jsr_); IGRAPH_UNUSED(jcong_); } long rand_int31() { return RNG_INT31(); } double rand_halfopen01() { // (0,1] return RNG_UNIF01(); } int binomial(double pp, int n) { return RNG_BINOM(n, pp); } }; } // namespace KW_RNG /* This was the original RNG, but now we use the igraph version */ // __________________________________________________________________________ // random.h - a Random Number Generator Class // random.cpp - contains the non-inline class methods // __________________________________________________________________________ // This C++ code uses the simple, very fast "KISS" (Keep It Simple // Stupid) random number generator suggested by George Marsaglia in a // Usenet posting from 1999. He describes it as "one of my favorite // generators". It generates high-quality random numbers that // apparently pass all commonly used tests for randomness. In fact, it // generates random numbers by combining the results of three other good // random number generators that have different periods and are // constructed from completely different algorithms. It does not have // the ultra-long period of some other generators - a "problem" that can // be fixed fairly easily - but that seems to be its only potential // problem. The period is about 2^123. // The ziggurat method of Marsaglia is used to generate exponential and // normal variates. The method as well as source code can be found in // the article "The Ziggurat Method for Generating Random Variables" by // Marsaglia and Tsang, Journal of Statistical Software 5, 2000. // The method for generating gamma variables appears in "A Simple Method // for Generating Gamma Variables" by Marsaglia and Tsang, ACM // Transactions on Mathematical Software, Vol. 26, No 3, Sep 2000, pages // 363-372. // The code for Poisson and Binomial random numbers comes from // Numerical Recipes in C. // Some of this code is unlikely to work correctly as is on 64 bit // machines. // #include // #include // #ifdef _WIN32 // #include // #define getpid _getpid // #else // #include // #endif // //#ifdef _WIN32 // static const double PI = 3.1415926535897932; // static const double AD_l = 0.6931471805599453; // static const double AD_a = 5.7133631526454228; // static const double AD_b = 3.4142135623730950; // static const double AD_c = -1.6734053240284925; // static const double AD_p = 0.9802581434685472; // static const double AD_A = 5.6005707569738080; // static const double AD_B = 3.3468106480569850; // static const double AD_H = 0.0026106723602095; // static const double AD_D = 0.0857864376269050; // //#endif //_WIN32 // namespace KW_RNG { // class RNG // { // private: // ulong z, w, jsr, jcong; // Seeds // ulong kn[128], ke[256]; // double wn[128],fn[128], we[256],fe[256]; // /* // #ifndef _WIN32 // static const double PI = 3.1415926535897932; // static const double AD_l = 0.6931471805599453; // static const double AD_a = 5.7133631526454228; // static const double AD_b = 3.4142135623730950; // static const double AD_c = -1.6734053240284925; // static const double AD_p = 0.9802581434685472; // static const double AD_A = 5.6005707569738080; // static const double AD_B = 3.3468106480569850; // static const double AD_H = 0.0026106723602095; // static const double AD_D = 0.0857864376269050; // #endif //_WIN32 // */ // public: // RNG() { init(); zigset(); } // RNG(ulong z_, ulong w_, ulong jsr_, ulong jcong_ ) : // z(z_), w(w_), jsr(jsr_), jcong(jcong_) { zigset(); } // ~RNG() { } // inline ulong znew() // { return (z = 36969 * (z & 65535) + (z >> 16)); } // inline ulong wnew() // { return (w = 18000 * (w & 65535) + (w >> 16)); } // inline ulong MWC() // { return (((znew() & 65535) << 16) + wnew()); } // inline ulong SHR3() // { jsr ^= ((jsr & 32767) << 17); jsr ^= (jsr >> 13); return (jsr ^= ((jsr << 5) & 0xFFFFFFFF)); } // inline ulong CONG() // { return (jcong = (69069 * jcong + 1234567) & 0xFFFFFFFF); } // inline double RNOR() { // slong h = rand_int32(); // ulong i = h & 127; // return (((ulong) abs((sint) h) < kn[i]) ? h * wn[i] : nfix(h, i)); // } // inline double REXP() { // ulong j = rand_int32(); // ulong i = j & 255; // return ((j < ke[i]) ? j * we[i] : efix(j, i)); // } // double nfix(slong h, ulong i); // double efix(ulong j, ulong i); // void zigset(); // inline void init() // { ulong yo = time(0) + getpid(); // z = w = jsr = jcong = yo; } // inline void init(ulong z_, ulong w_, ulong jsr_, ulong jcong_ ) // { z = z_; w = w_; jsr = jsr_; jcong = jcong_; } // inline ulong rand_int32() // [0,2^32-1] // { return ((MWC() ^ CONG()) + SHR3()) & 0xFFFFFFFF; } // inline long rand_int31() // [0,2^31-1] // { return long(rand_int32() >> 1);} // inline double rand_closed01() // [0,1] // { return ((double) rand_int32() / 4294967295.0); } // inline double rand_open01() // (0,1) // { return (((double) rand_int32() + 0.5) / 4294967296.0); } // inline double rand_halfclosed01() // [0,1) // { return ((double) rand_int32() / 4294967296.0); } // inline double rand_halfopen01() // (0,1] // { return (((double) rand_int32() + 0.5) / 4294967295.5); } // // Continuous Distributions // inline double uniform(double x = 0.0, double y = 1.0) // { return rand_closed01() * (y - x) + x; } // inline double normal(double mu = 0.0, double sd = 1.0) // { return RNOR() * sd + mu; } // inline double exponential(double lambda = 1) // { return REXP() / lambda; } // double gamma(double shape = 1, double scale = 1); // double chi_square(double df) // { return gamma(df / 2.0, 0.5); } // double beta(double a1, double a2) // { double x1 = gamma(a1, 1); return (x1 / (x1 + gamma(a2, 1))); } // // Discrete Distributions // double poisson(double lambda); // int binomial(double pp, int n); // }; // class RNG // } // namespace #endif // RNG_H python-igraph-0.8.0/vendor/source/igraph/src/igraph_trie.c0000644000076500000240000002766413614300625024056 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2003-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_types.h" #include "igraph_types_internal.h" #include "igraph_memory.h" #include "igraph_random.h" #include "igraph_error.h" #include "config.h" #include #include /* memcpy & co. */ #include /** * \ingroup igraphtrie * \brief Creates a trie node (not to be called directly) * \return Error code: errors by igraph_strvector_init(), * igraph_vector_ptr_init() and igraph_vector_init() might be returned. */ int igraph_i_trie_init_node(igraph_trie_node_t *t) { IGRAPH_STRVECTOR_INIT_FINALLY(&t->strs, 0); IGRAPH_VECTOR_PTR_INIT_FINALLY(&t->children, 0); IGRAPH_VECTOR_INIT_FINALLY(&t->values, 0); IGRAPH_FINALLY_CLEAN(3); return 0; } void igraph_i_trie_destroy_node(igraph_trie_node_t *t, igraph_bool_t sfree); /** * \ingroup igraphtrie * \brief Creates a trie. * \return Error code: errors by igraph_strvector_init(), * igraph_vector_ptr_init() and igraph_vector_init() might be returned. */ int igraph_trie_init(igraph_trie_t *t, igraph_bool_t storekeys) { t->maxvalue = -1; t->storekeys = storekeys; IGRAPH_CHECK(igraph_i_trie_init_node( (igraph_trie_node_t *)t )); IGRAPH_FINALLY(igraph_i_trie_destroy_node, t); if (storekeys) { IGRAPH_CHECK(igraph_strvector_init(&t->keys, 0)); } IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \ingroup igraphtrie * \brief Destroys a node of a trie (not to be called directly). */ void igraph_i_trie_destroy_node(igraph_trie_node_t *t, igraph_bool_t sfree) { long int i; igraph_strvector_destroy(&t->strs); for (i = 0; i < igraph_vector_ptr_size(&t->children); i++) { igraph_trie_node_t *child = VECTOR(t->children)[i]; if (child != 0) { igraph_i_trie_destroy_node(child, 1); } } igraph_vector_ptr_destroy(&t->children); igraph_vector_destroy(&t->values); if (sfree) { igraph_Free(t); } } /** * \ingroup igraphtrie * \brief Destroys a trie (frees allocated memory). */ void igraph_trie_destroy(igraph_trie_t *t) { if (t->storekeys) { igraph_strvector_destroy(&t->keys); } igraph_i_trie_destroy_node( (igraph_trie_node_t*) t, 0); } /** * \ingroup igraphtrie * \brief Internal helping function for igraph_trie_t */ long int igraph_i_strdiff(const char *str, const char *key) { long int diff = 0; while (key[diff] != '\0' && str[diff] != '\0' && str[diff] == key[diff]) { diff++; } return diff; } /** * \ingroup igraphtrie * \brief Search/insert in a trie (not to be called directly). * * @return Error code: * - IGRAPH_ENOMEM: out of memory */ int igraph_trie_get_node(igraph_trie_node_t *t, const char *key, igraph_real_t newvalue, long int *id) { char *str; long int i; igraph_bool_t add; /* If newvalue is negative, we don't add the node if nonexistent, only check * for its existence */ add = (newvalue >= 0); for (i = 0; i < igraph_strvector_size(&t->strs); i++) { long int diff; igraph_strvector_get(&t->strs, i, &str); diff = igraph_i_strdiff(str, key); if (diff == 0) { /* ------------------------------------ */ /* No match, next */ } else if (str[diff] == '\0' && key[diff] == '\0') { /* ------------------------------------ */ /* They are exactly the same */ if (VECTOR(t->values)[i] != -1) { *id = (long int) VECTOR(t->values)[i]; return 0; } else { VECTOR(t->values)[i] = newvalue; *id = (long int) newvalue; return 0; } } else if (str[diff] == '\0') { /* ------------------------------------ */ /* str is prefix of key, follow its link if there is one */ igraph_trie_node_t *node = VECTOR(t->children)[i]; if (node != 0) { return igraph_trie_get_node(node, key + diff, newvalue, id); } else if (add) { igraph_trie_node_t *node = igraph_Calloc(1, igraph_trie_node_t); if (node == 0) { IGRAPH_ERROR("cannot add to trie", IGRAPH_ENOMEM); } IGRAPH_STRVECTOR_INIT_FINALLY(&node->strs, 1); IGRAPH_VECTOR_PTR_INIT_FINALLY(&node->children, 1); IGRAPH_VECTOR_INIT_FINALLY(&node->values, 1); IGRAPH_CHECK(igraph_strvector_set(&node->strs, 0, key + diff)); VECTOR(node->children)[0] = 0; VECTOR(node->values)[0] = newvalue; VECTOR(t->children)[i] = node; *id = (long int) newvalue; IGRAPH_FINALLY_CLEAN(3); return 0; } else { *id = -1; return 0; } } else if (key[diff] == '\0' && add) { /* ------------------------------------ */ /* key is prefix of str, the node has to be cut */ char *str2; igraph_trie_node_t *node = igraph_Calloc(1, igraph_trie_node_t); if (node == 0) { IGRAPH_ERROR("cannot add to trie", IGRAPH_ENOMEM); } IGRAPH_STRVECTOR_INIT_FINALLY(&node->strs, 1); IGRAPH_VECTOR_PTR_INIT_FINALLY(&node->children, 1); IGRAPH_VECTOR_INIT_FINALLY(&node->values, 1); IGRAPH_CHECK(igraph_strvector_set(&node->strs, 0, str + diff)); VECTOR(node->children)[0] = VECTOR(t->children)[i]; VECTOR(node->values)[0] = VECTOR(t->values)[i]; str2 = strdup(str); if (str2 == 0) { IGRAPH_ERROR("cannot add to trie", IGRAPH_ENOMEM); } str2[diff] = '\0'; IGRAPH_FINALLY(free, str2); IGRAPH_CHECK(igraph_strvector_set(&t->strs, i, str2)); free(str2); IGRAPH_FINALLY_CLEAN(4); VECTOR(t->values)[i] = newvalue; VECTOR(t->children)[i] = node; *id = (long int) newvalue; return 0; } else if (add) { /* ------------------------------------ */ /* the first diff characters match */ char *str2; igraph_trie_node_t *node = igraph_Calloc(1, igraph_trie_node_t); if (node == 0) { IGRAPH_ERROR("cannot add to trie", IGRAPH_ENOMEM); } IGRAPH_STRVECTOR_INIT_FINALLY(&node->strs, 2); IGRAPH_VECTOR_PTR_INIT_FINALLY(&node->children, 2); IGRAPH_VECTOR_INIT_FINALLY(&node->values, 2); IGRAPH_CHECK(igraph_strvector_set(&node->strs, 0, str + diff)); IGRAPH_CHECK(igraph_strvector_set(&node->strs, 1, key + diff)); VECTOR(node->children)[0] = VECTOR(t->children)[i]; VECTOR(node->children)[1] = 0; VECTOR(node->values)[0] = VECTOR(t->values)[i]; VECTOR(node->values)[1] = newvalue; str2 = strdup(str); if (str2 == 0) { IGRAPH_ERROR("cannot add to trie", IGRAPH_ENOMEM); } str2[diff] = '\0'; IGRAPH_FINALLY(free, str2); IGRAPH_CHECK(igraph_strvector_set(&t->strs, i, str2)); free(str2); IGRAPH_FINALLY_CLEAN(4); VECTOR(t->values)[i] = -1; VECTOR(t->children)[i] = node; *id = (long int) newvalue; return 0; } else { /* ------------------------------------------------- */ /* No match, but we requested not to add the new key */ *id = -1; return 0; } } /* ------------------------------------ */ /* Nothing matches */ if (add) { IGRAPH_CHECK(igraph_vector_ptr_reserve(&t->children, igraph_vector_ptr_size(&t->children) + 1)); IGRAPH_CHECK(igraph_vector_reserve(&t->values, igraph_vector_size(&t->values) + 1)); IGRAPH_CHECK(igraph_strvector_add(&t->strs, key)); igraph_vector_ptr_push_back(&t->children, 0); /* allocated */ igraph_vector_push_back(&t->values, newvalue); /* allocated */ *id = (long int) newvalue; } else { *id = -1; } return 0; } /** * \ingroup igraphtrie * \brief Search/insert in a trie. */ int igraph_trie_get(igraph_trie_t *t, const char *key, long int *id) { if (!t->storekeys) { IGRAPH_CHECK(igraph_trie_get_node( (igraph_trie_node_t*) t, key, t->maxvalue + 1, id)); if (*id > t->maxvalue) { t->maxvalue = *id; } return 0; } else { int ret; igraph_error_handler_t *oldhandler; oldhandler = igraph_set_error_handler(igraph_error_handler_ignore); /* Add it to the string vector first, we can undo this later */ ret = igraph_strvector_add(&t->keys, key); if (ret != 0) { igraph_set_error_handler(oldhandler); IGRAPH_ERROR("cannot get element from trie", ret); } ret = igraph_trie_get_node( (igraph_trie_node_t*) t, key, t->maxvalue + 1, id); if (ret != 0) { igraph_strvector_resize(&t->keys, igraph_strvector_size(&t->keys) - 1); igraph_set_error_handler(oldhandler); IGRAPH_ERROR("cannot get element from trie", ret); } /* everything is fine */ if (*id > t->maxvalue) { t->maxvalue = *id; } else { igraph_strvector_resize(&t->keys, igraph_strvector_size(&t->keys) - 1); } igraph_set_error_handler(oldhandler); } return 0; } /** * \ingroup igraphtrie * \brief Search/insert in a trie (for internal use). * * @return Error code: * - IGRAPH_ENOMEM: out of memory */ int igraph_trie_get2(igraph_trie_t *t, const char *key, long int length, long int *id) { char *tmp = igraph_Calloc(length + 1, char); if (tmp == 0) { IGRAPH_ERROR("Cannot get from trie", IGRAPH_ENOMEM); } strncpy(tmp, key, length); tmp[length] = '\0'; IGRAPH_FINALLY(free, tmp); IGRAPH_CHECK(igraph_trie_get(t, tmp, id)); igraph_Free(tmp); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \ingroup igraphtrie * \brief Search in a trie. * This variant does not add \c key to the trie if it does not exist. * In this case, a negative id is returned. */ int igraph_trie_check(igraph_trie_t *t, const char *key, long int *id) { IGRAPH_CHECK(igraph_trie_get_node( (igraph_trie_node_t*) t, key, -1, id)); return 0; } /** * \ingroup igraphtrie * \brief Get an element of a trie based on its index. */ void igraph_trie_idx(igraph_trie_t *t, long int idx, char **str) { igraph_strvector_get(&t->keys, idx, str); } /** * \ingroup igraphtrie * \brief Returns the size of a trie. */ long int igraph_trie_size(igraph_trie_t *t) { return t->maxvalue + 1; } /* Hmmm, very dirty.... */ int igraph_trie_getkeys(igraph_trie_t *t, const igraph_strvector_t **strv) { *strv = &t->keys; return 0; } python-igraph-0.8.0/vendor/source/igraph/src/structure_generators.c0000644000076500000240000025405713614300625026050 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2005-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_constructors.h" #include "igraph_structural.h" #include "igraph_memory.h" #include "igraph_interface.h" #include "igraph_attributes.h" #include "igraph_adjlist.h" #include "igraph_interrupt_internal.h" #include "igraph_dqueue.h" #include "config.h" #include #include #include /** * \section about_generators * * Graph generators create graphs. * * Almost all functions which create graph objects are documented * here. The exceptions are \ref igraph_subgraph() and alike, these * create graphs based on another graph. */ /** * \ingroup generators * \function igraph_create * \brief Creates a graph with the specified edges. * * \param graph An uninitialized graph object. * \param edges The edges to add, the first two elements are the first * edge, etc. * \param n The number of vertices in the graph, if smaller or equal * to the highest vertex id in the \p edges vector it * will be increased automatically. So it is safe to give 0 * here. * \param directed Boolean, whether to create a directed graph or * not. If yes, then the first edge points from the first * vertex id in \p edges to the second, etc. * \return Error code: * \c IGRAPH_EINVEVECTOR: invalid edges * vector (odd number of vertices). * \c IGRAPH_EINVVID: invalid (negative) * vertex id. * * Time complexity: O(|V|+|E|), * |V| is the number of vertices, * |E| the number of edges in the * graph. * * \example examples/simple/igraph_create.c */ int igraph_create(igraph_t *graph, const igraph_vector_t *edges, igraph_integer_t n, igraph_bool_t directed) { igraph_bool_t has_edges = igraph_vector_size(edges) > 0; igraph_real_t max = has_edges ? igraph_vector_max(edges) + 1 : 0; if (igraph_vector_size(edges) % 2 != 0) { IGRAPH_ERROR("Invalid (odd) edges vector", IGRAPH_EINVEVECTOR); } if (has_edges && !igraph_vector_isininterval(edges, 0, max - 1)) { IGRAPH_ERROR("Invalid (negative) vertex id", IGRAPH_EINVVID); } IGRAPH_CHECK(igraph_empty(graph, n, directed)); IGRAPH_FINALLY(igraph_destroy, graph); if (has_edges) { igraph_integer_t vc = igraph_vcount(graph); if (vc < max) { IGRAPH_CHECK(igraph_add_vertices(graph, (igraph_integer_t) (max - vc), 0)); } IGRAPH_CHECK(igraph_add_edges(graph, edges, 0)); } IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_i_adjacency_directed(igraph_matrix_t *adjmatrix, igraph_vector_t *edges); int igraph_i_adjacency_max(igraph_matrix_t *adjmatrix, igraph_vector_t *edges); int igraph_i_adjacency_upper(igraph_matrix_t *adjmatrix, igraph_vector_t *edges); int igraph_i_adjacency_lower(igraph_matrix_t *adjmatrix, igraph_vector_t *edges); int igraph_i_adjacency_min(igraph_matrix_t *adjmatrix, igraph_vector_t *edges); int igraph_i_adjacency_directed(igraph_matrix_t *adjmatrix, igraph_vector_t *edges) { long int no_of_nodes = igraph_matrix_nrow(adjmatrix); long int i, j, k; for (i = 0; i < no_of_nodes; i++) { for (j = 0; j < no_of_nodes; j++) { long int M = (long int) MATRIX(*adjmatrix, i, j); for (k = 0; k < M; k++) { IGRAPH_CHECK(igraph_vector_push_back(edges, i)); IGRAPH_CHECK(igraph_vector_push_back(edges, j)); } } } return 0; } int igraph_i_adjacency_max(igraph_matrix_t *adjmatrix, igraph_vector_t *edges) { long int no_of_nodes = igraph_matrix_nrow(adjmatrix); long int i, j, k; for (i = 0; i < no_of_nodes; i++) { for (j = i; j < no_of_nodes; j++) { long int M1 = (long int) MATRIX(*adjmatrix, i, j); long int M2 = (long int) MATRIX(*adjmatrix, j, i); if (M1 < M2) { M1 = M2; } for (k = 0; k < M1; k++) { IGRAPH_CHECK(igraph_vector_push_back(edges, i)); IGRAPH_CHECK(igraph_vector_push_back(edges, j)); } } } return 0; } int igraph_i_adjacency_upper(igraph_matrix_t *adjmatrix, igraph_vector_t *edges) { long int no_of_nodes = igraph_matrix_nrow(adjmatrix); long int i, j, k; for (i = 0; i < no_of_nodes; i++) { for (j = i; j < no_of_nodes; j++) { long int M = (long int) MATRIX(*adjmatrix, i, j); for (k = 0; k < M; k++) { IGRAPH_CHECK(igraph_vector_push_back(edges, i)); IGRAPH_CHECK(igraph_vector_push_back(edges, j)); } } } return 0; } int igraph_i_adjacency_lower(igraph_matrix_t *adjmatrix, igraph_vector_t *edges) { long int no_of_nodes = igraph_matrix_nrow(adjmatrix); long int i, j, k; for (i = 0; i < no_of_nodes; i++) { for (j = 0; j <= i; j++) { long int M = (long int) MATRIX(*adjmatrix, i, j); for (k = 0; k < M; k++) { IGRAPH_CHECK(igraph_vector_push_back(edges, i)); IGRAPH_CHECK(igraph_vector_push_back(edges, j)); } } } return 0; } int igraph_i_adjacency_min(igraph_matrix_t *adjmatrix, igraph_vector_t *edges) { long int no_of_nodes = igraph_matrix_nrow(adjmatrix); long int i, j, k; for (i = 0; i < no_of_nodes; i++) { for (j = i; j < no_of_nodes; j++) { long int M1 = (long int) MATRIX(*adjmatrix, i, j); long int M2 = (long int) MATRIX(*adjmatrix, j, i); if (M1 > M2) { M1 = M2; } for (k = 0; k < M1; k++) { IGRAPH_CHECK(igraph_vector_push_back(edges, i)); IGRAPH_CHECK(igraph_vector_push_back(edges, j)); } } } return 0; } /** * \ingroup generators * \function igraph_adjacency * \brief Creates a graph object from an adjacency matrix. * * The order of the vertices in the matrix is preserved, i.e. the vertex * corresponding to the first row/column will be vertex with id 0, the * next row is for vertex 1, etc. * \param graph Pointer to an uninitialized graph object. * \param adjmatrix The adjacency matrix. How it is interpreted * depends on the \p mode argument. * \param mode Constant to specify how the given matrix is interpreted * as an adjacency matrix. Possible values * (A(i,j) * is the element in row i and column * j in the adjacency matrix * \p adjmatrix): * \clist * \cli IGRAPH_ADJ_DIRECTED * the graph will be directed and * an element gives the number of edges between two vertices. * \cli IGRAPH_ADJ_UNDIRECTED * this is the same as \c IGRAPH_ADJ_MAX, * for convenience. * \cli IGRAPH_ADJ_MAX * undirected graph will be created * and the number of edges between vertices * i and * j is * max(A(i,j), A(j,i)). * \cli IGRAPH_ADJ_MIN * undirected graph will be created * with min(A(i,j), A(j,i)) * edges between vertices * i and * j. * \cli IGRAPH_ADJ_PLUS * undirected graph will be created * with A(i,j)+A(j,i) edges * between vertices * i and * j. * \cli IGRAPH_ADJ_UPPER * undirected graph will be created, * only the upper right triangle (including the diagonal) is * used for the number of edges. * \cli IGRAPH_ADJ_LOWER * undirected graph will be created, * only the lower left triangle (including the diagonal) is * used for creating the edges. * \endclist * \return Error code, * \c IGRAPH_NONSQUARE: non-square matrix. * * Time complexity: O(|V||V|), * |V| is the number of vertices in the graph. * * \example examples/simple/igraph_adjacency.c */ int igraph_adjacency(igraph_t *graph, igraph_matrix_t *adjmatrix, igraph_adjacency_t mode) { igraph_vector_t edges = IGRAPH_VECTOR_NULL; long int no_of_nodes; /* Some checks */ if (igraph_matrix_nrow(adjmatrix) != igraph_matrix_ncol(adjmatrix)) { IGRAPH_ERROR("Non-square matrix", IGRAPH_NONSQUARE); } IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); /* Collect the edges */ no_of_nodes = igraph_matrix_nrow(adjmatrix); switch (mode) { case IGRAPH_ADJ_DIRECTED: IGRAPH_CHECK(igraph_i_adjacency_directed(adjmatrix, &edges)); break; case IGRAPH_ADJ_MAX: IGRAPH_CHECK(igraph_i_adjacency_max(adjmatrix, &edges)); break; case IGRAPH_ADJ_UPPER: IGRAPH_CHECK(igraph_i_adjacency_upper(adjmatrix, &edges)); break; case IGRAPH_ADJ_LOWER: IGRAPH_CHECK(igraph_i_adjacency_lower(adjmatrix, &edges)); break; case IGRAPH_ADJ_MIN: IGRAPH_CHECK(igraph_i_adjacency_min(adjmatrix, &edges)); break; case IGRAPH_ADJ_PLUS: IGRAPH_CHECK(igraph_i_adjacency_directed(adjmatrix, &edges)); break; } IGRAPH_CHECK(igraph_create(graph, &edges, (igraph_integer_t) no_of_nodes, (mode == IGRAPH_ADJ_DIRECTED))); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_i_weighted_adjacency_directed(const igraph_matrix_t *adjmatrix, igraph_vector_t *edges, igraph_vector_t *weights, igraph_bool_t loops); int igraph_i_weighted_adjacency_plus(const igraph_matrix_t *adjmatrix, igraph_vector_t *edges, igraph_vector_t *weights, igraph_bool_t loops); int igraph_i_weighted_adjacency_max(const igraph_matrix_t *adjmatrix, igraph_vector_t *edges, igraph_vector_t *weights, igraph_bool_t loops); int igraph_i_weighted_adjacency_upper(const igraph_matrix_t *adjmatrix, igraph_vector_t *edges, igraph_vector_t *weights, igraph_bool_t loops); int igraph_i_weighted_adjacency_lower(const igraph_matrix_t *adjmatrix, igraph_vector_t *edges, igraph_vector_t *weights, igraph_bool_t loops); int igraph_i_weighted_adjacency_min(const igraph_matrix_t *adjmatrix, igraph_vector_t *edges, igraph_vector_t *weights, igraph_bool_t loops); int igraph_i_weighted_adjacency_directed(const igraph_matrix_t *adjmatrix, igraph_vector_t *edges, igraph_vector_t *weights, igraph_bool_t loops) { long int no_of_nodes = igraph_matrix_nrow(adjmatrix); long int i, j; for (i = 0; i < no_of_nodes; i++) { for (j = 0; j < no_of_nodes; j++) { igraph_real_t M = MATRIX(*adjmatrix, i, j); if (M == 0.0) { continue; } if (i == j && !loops) { continue; } IGRAPH_CHECK(igraph_vector_push_back(edges, i)); IGRAPH_CHECK(igraph_vector_push_back(edges, j)); IGRAPH_CHECK(igraph_vector_push_back(weights, M)); } } return 0; } int igraph_i_weighted_adjacency_plus(const igraph_matrix_t *adjmatrix, igraph_vector_t *edges, igraph_vector_t *weights, igraph_bool_t loops) { long int no_of_nodes = igraph_matrix_nrow(adjmatrix); long int i, j; for (i = 0; i < no_of_nodes; i++) { for (j = i; j < no_of_nodes; j++) { igraph_real_t M = MATRIX(*adjmatrix, i, j) + MATRIX(*adjmatrix, j, i); if (M == 0.0) { continue; } if (i == j && !loops) { continue; } if (i == j) { M /= 2; } IGRAPH_CHECK(igraph_vector_push_back(edges, i)); IGRAPH_CHECK(igraph_vector_push_back(edges, j)); IGRAPH_CHECK(igraph_vector_push_back(weights, M)); } } return 0; } int igraph_i_weighted_adjacency_max(const igraph_matrix_t *adjmatrix, igraph_vector_t *edges, igraph_vector_t *weights, igraph_bool_t loops) { long int no_of_nodes = igraph_matrix_nrow(adjmatrix); long int i, j; for (i = 0; i < no_of_nodes; i++) { for (j = i; j < no_of_nodes; j++) { igraph_real_t M1 = MATRIX(*adjmatrix, i, j); igraph_real_t M2 = MATRIX(*adjmatrix, j, i); if (M1 < M2) { M1 = M2; } if (M1 == 0.0) { continue; } if (i == j && !loops) { continue; } IGRAPH_CHECK(igraph_vector_push_back(edges, i)); IGRAPH_CHECK(igraph_vector_push_back(edges, j)); IGRAPH_CHECK(igraph_vector_push_back(weights, M1)); } } return 0; } int igraph_i_weighted_adjacency_upper(const igraph_matrix_t *adjmatrix, igraph_vector_t *edges, igraph_vector_t *weights, igraph_bool_t loops) { long int no_of_nodes = igraph_matrix_nrow(adjmatrix); long int i, j; for (i = 0; i < no_of_nodes; i++) { for (j = i; j < no_of_nodes; j++) { igraph_real_t M = MATRIX(*adjmatrix, i, j); if (M == 0.0) { continue; } if (i == j && !loops) { continue; } IGRAPH_CHECK(igraph_vector_push_back(edges, i)); IGRAPH_CHECK(igraph_vector_push_back(edges, j)); IGRAPH_CHECK(igraph_vector_push_back(weights, M)); } } return 0; } int igraph_i_weighted_adjacency_lower(const igraph_matrix_t *adjmatrix, igraph_vector_t *edges, igraph_vector_t *weights, igraph_bool_t loops) { long int no_of_nodes = igraph_matrix_nrow(adjmatrix); long int i, j; for (i = 0; i < no_of_nodes; i++) { for (j = 0; j <= i; j++) { igraph_real_t M = MATRIX(*adjmatrix, i, j); if (M == 0.0) { continue; } if (i == j && !loops) { continue; } IGRAPH_CHECK(igraph_vector_push_back(edges, i)); IGRAPH_CHECK(igraph_vector_push_back(edges, j)); IGRAPH_CHECK(igraph_vector_push_back(weights, M)); } } return 0; } int igraph_i_weighted_adjacency_min(const igraph_matrix_t *adjmatrix, igraph_vector_t *edges, igraph_vector_t *weights, igraph_bool_t loops) { long int no_of_nodes = igraph_matrix_nrow(adjmatrix); long int i, j; for (i = 0; i < no_of_nodes; i++) { for (j = i; j < no_of_nodes; j++) { igraph_real_t M1 = MATRIX(*adjmatrix, i, j); igraph_real_t M2 = MATRIX(*adjmatrix, j, i); if (M1 > M2) { M1 = M2; } if (M1 == 0.0) { continue; } if (i == j && !loops) { continue; } IGRAPH_CHECK(igraph_vector_push_back(edges, i)); IGRAPH_CHECK(igraph_vector_push_back(edges, j)); IGRAPH_CHECK(igraph_vector_push_back(weights, M1)); } } return 0; } /** * \ingroup generators * \function igraph_weighted_adjacency * \brief Creates a graph object from a weighted adjacency matrix. * * The order of the vertices in the matrix is preserved, i.e. the vertex * corresponding to the first row/column will be vertex with id 0, the * next row is for vertex 1, etc. * \param graph Pointer to an uninitialized graph object. * \param adjmatrix The weighted adjacency matrix. How it is interpreted * depends on the \p mode argument. The common feature is that * edges with zero weights are considered nonexistent (however, * negative weights are permitted). * \param mode Constant to specify how the given matrix is interpreted * as an adjacency matrix. Possible values * (A(i,j) * is the element in row i and column * j in the adjacency matrix * \p adjmatrix): * \clist * \cli IGRAPH_ADJ_DIRECTED * the graph will be directed and * an element gives the weight of the edge between two vertices. * \cli IGRAPH_ADJ_UNDIRECTED * this is the same as \c IGRAPH_ADJ_MAX, * for convenience. * \cli IGRAPH_ADJ_MAX * undirected graph will be created * and the weight of the edge between vertices * i and * j is * max(A(i,j), A(j,i)). * \cli IGRAPH_ADJ_MIN * undirected graph will be created * with edge weight min(A(i,j), A(j,i)) * between vertices * i and * j. * \cli IGRAPH_ADJ_PLUS * undirected graph will be created * with edge weight A(i,j)+A(j,i) * between vertices * i and * j. * \cli IGRAPH_ADJ_UPPER * undirected graph will be created, * only the upper right triangle (including the diagonal) is * used for the edge weights. * \cli IGRAPH_ADJ_LOWER * undirected graph will be created, * only the lower left triangle (including the diagonal) is * used for the edge weights. * \endclist * \param attr the name of the attribute that will store the edge weights. * If \c NULL , it will use \c weight as the attribute name. * \param loops Logical scalar, whether to ignore the diagonal elements * in the adjacency matrix. * \return Error code, * \c IGRAPH_NONSQUARE: non-square matrix. * * Time complexity: O(|V||V|), * |V| is the number of vertices in the graph. * * \example examples/simple/igraph_weighted_adjacency.c */ int igraph_weighted_adjacency(igraph_t *graph, igraph_matrix_t *adjmatrix, igraph_adjacency_t mode, const char* attr, igraph_bool_t loops) { igraph_vector_t edges = IGRAPH_VECTOR_NULL; igraph_vector_t weights = IGRAPH_VECTOR_NULL; const char* default_attr = "weight"; igraph_vector_ptr_t attr_vec; igraph_attribute_record_t attr_rec; long int no_of_nodes; /* Some checks */ if (igraph_matrix_nrow(adjmatrix) != igraph_matrix_ncol(adjmatrix)) { IGRAPH_ERROR("Non-square matrix", IGRAPH_NONSQUARE); } IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_VECTOR_INIT_FINALLY(&weights, 0); IGRAPH_VECTOR_PTR_INIT_FINALLY(&attr_vec, 1); /* Collect the edges */ no_of_nodes = igraph_matrix_nrow(adjmatrix); switch (mode) { case IGRAPH_ADJ_DIRECTED: IGRAPH_CHECK(igraph_i_weighted_adjacency_directed(adjmatrix, &edges, &weights, loops)); break; case IGRAPH_ADJ_MAX: IGRAPH_CHECK(igraph_i_weighted_adjacency_max(adjmatrix, &edges, &weights, loops)); break; case IGRAPH_ADJ_UPPER: IGRAPH_CHECK(igraph_i_weighted_adjacency_upper(adjmatrix, &edges, &weights, loops)); break; case IGRAPH_ADJ_LOWER: IGRAPH_CHECK(igraph_i_weighted_adjacency_lower(adjmatrix, &edges, &weights, loops)); break; case IGRAPH_ADJ_MIN: IGRAPH_CHECK(igraph_i_weighted_adjacency_min(adjmatrix, &edges, &weights, loops)); break; case IGRAPH_ADJ_PLUS: IGRAPH_CHECK(igraph_i_weighted_adjacency_plus(adjmatrix, &edges, &weights, loops)); break; } /* Prepare attribute record */ attr_rec.name = attr ? attr : default_attr; attr_rec.type = IGRAPH_ATTRIBUTE_NUMERIC; attr_rec.value = &weights; VECTOR(attr_vec)[0] = &attr_rec; /* Create graph */ IGRAPH_CHECK(igraph_empty(graph, (igraph_integer_t) no_of_nodes, (mode == IGRAPH_ADJ_DIRECTED))); IGRAPH_FINALLY(igraph_destroy, graph); if (igraph_vector_size(&edges) > 0) { IGRAPH_CHECK(igraph_add_edges(graph, &edges, &attr_vec)); } IGRAPH_FINALLY_CLEAN(1); /* Cleanup */ igraph_vector_destroy(&edges); igraph_vector_destroy(&weights); igraph_vector_ptr_destroy(&attr_vec); IGRAPH_FINALLY_CLEAN(3); return 0; } /** * \ingroup generators * \function igraph_star * \brief Creates a \em star graph, every vertex connects only to the center. * * \param graph Pointer to an uninitialized graph object, this will * be the result. * \param n Integer constant, the number of vertices in the graph. * \param mode Constant, gives the type of the star graph to * create. Possible values: * \clist * \cli IGRAPH_STAR_OUT * directed star graph, edges point * \em from the center to the other vertices. * \cli IGRAPH_STAR_IN * directed star graph, edges point * \em to the center from the other vertices. * \cli IGRAPH_STAR_MUTUAL * directed star graph with mutual edges. * \cli IGRAPH_STAR_UNDIRECTED * an undirected star graph is * created. * \endclist * \param center Id of the vertex which will be the center of the * graph. * \return Error code: * \clist * \cli IGRAPH_EINVVID * invalid number of vertices. * \cli IGRAPH_EINVAL * invalid center vertex. * \cli IGRAPH_EINVMODE * invalid mode argument. * \endclist * * Time complexity: O(|V|), the * number of vertices in the graph. * * \sa \ref igraph_lattice(), \ref igraph_ring(), \ref igraph_tree() * for creating other regular structures. * * \example examples/simple/igraph_star.c */ int igraph_star(igraph_t *graph, igraph_integer_t n, igraph_star_mode_t mode, igraph_integer_t center) { igraph_vector_t edges = IGRAPH_VECTOR_NULL; long int i; if (n < 0) { IGRAPH_ERROR("Invalid number of vertices", IGRAPH_EINVVID); } if (center < 0 || center > n - 1) { IGRAPH_ERROR("Invalid center vertex", IGRAPH_EINVAL); } if (mode != IGRAPH_STAR_OUT && mode != IGRAPH_STAR_IN && mode != IGRAPH_STAR_MUTUAL && mode != IGRAPH_STAR_UNDIRECTED) { IGRAPH_ERROR("invalid mode", IGRAPH_EINVMODE); } if (mode != IGRAPH_STAR_MUTUAL) { IGRAPH_VECTOR_INIT_FINALLY(&edges, (n - 1) * 2); } else { IGRAPH_VECTOR_INIT_FINALLY(&edges, (n - 1) * 2 * 2); } if (mode == IGRAPH_STAR_OUT) { for (i = 0; i < center; i++) { VECTOR(edges)[2 * i] = center; VECTOR(edges)[2 * i + 1] = i; } for (i = center + 1; i < n; i++) { VECTOR(edges)[2 * (i - 1)] = center; VECTOR(edges)[2 * (i - 1) + 1] = i; } } else if (mode == IGRAPH_STAR_MUTUAL) { for (i = 0; i < center; i++) { VECTOR(edges)[4 * i] = center; VECTOR(edges)[4 * i + 1] = i; VECTOR(edges)[4 * i + 2] = i; VECTOR(edges)[4 * i + 3] = center; } for (i = center + 1; i < n; i++) { VECTOR(edges)[4 * i - 4] = center; VECTOR(edges)[4 * i - 3] = i; VECTOR(edges)[4 * i - 2] = i; VECTOR(edges)[4 * i - 1] = center; } } else { for (i = 0; i < center; i++) { VECTOR(edges)[2 * i + 1] = center; VECTOR(edges)[2 * i] = i; } for (i = center + 1; i < n; i++) { VECTOR(edges)[2 * (i - 1) + 1] = center; VECTOR(edges)[2 * (i - 1)] = i; } } IGRAPH_CHECK(igraph_create(graph, &edges, 0, (mode != IGRAPH_STAR_UNDIRECTED))); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \ingroup generators * \function igraph_lattice * \brief Creates most kinds of lattices. * * \param graph An uninitialized graph object. * \param dimvector Vector giving the sizes of the lattice in each of * its dimensions. Ie. the dimension of the lattice will be the * same as the length of this vector. * \param nei Integer value giving the distance (number of steps) * within which two vertices will be connected. * \param directed Boolean, whether to create a directed graph. The * direction of the edges is determined by the generation * algorithm and is unlikely to suit you, so this isn't a very * useful option. * \param mutual Boolean, if the graph is directed this gives whether * to create all connections as mutual. * \param circular Boolean, defines whether the generated lattice is * periodic. * \return Error code: * \c IGRAPH_EINVAL: invalid (negative) * dimension vector. * * Time complexity: if \p nei is less than two then it is O(|V|+|E|) (as * far as I remember), |V| and |E| are the number of vertices * and edges in the generated graph. Otherwise it is O(|V|*d^o+|E|), d * is the average degree of the graph, o is the \p nei argument. */ int igraph_lattice(igraph_t *graph, const igraph_vector_t *dimvector, igraph_integer_t nei, igraph_bool_t directed, igraph_bool_t mutual, igraph_bool_t circular) { long int dims = igraph_vector_size(dimvector); long int no_of_nodes = (long int) igraph_vector_prod(dimvector); igraph_vector_t edges = IGRAPH_VECTOR_NULL; long int *coords, *weights; long int i, j; int carry, pos; if (igraph_vector_any_smaller(dimvector, 0)) { IGRAPH_ERROR("Invalid dimension vector", IGRAPH_EINVAL); } /* init coords & weights */ coords = igraph_Calloc(dims, long int); if (coords == 0) { IGRAPH_ERROR("lattice failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, coords); /* TODO: hack */ weights = igraph_Calloc(dims, long int); if (weights == 0) { IGRAPH_ERROR("lattice failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, weights); if (dims > 0) { weights[0] = 1; for (i = 1; i < dims; i++) { weights[i] = weights[i - 1] * (long int) VECTOR(*dimvector)[i - 1]; } } IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_CHECK(igraph_vector_reserve(&edges, no_of_nodes * dims + mutual * directed * no_of_nodes * dims)); for (i = 0; i < no_of_nodes; i++) { IGRAPH_ALLOW_INTERRUPTION(); for (j = 0; j < dims; j++) { if (circular || coords[j] != VECTOR(*dimvector)[j] - 1) { long int new_nei; if (coords[j] != VECTOR(*dimvector)[j] - 1) { new_nei = i + weights[j] + 1; } else { new_nei = i - (long int) (VECTOR(*dimvector)[j] - 1) * weights[j] + 1; } if (new_nei != i + 1 && (VECTOR(*dimvector)[j] != 2 || coords[j] != 1 || directed)) { igraph_vector_push_back(&edges, i); /* reserved */ igraph_vector_push_back(&edges, new_nei - 1); /* reserved */ } } /* if circular || coords[j] */ if (mutual && directed && (circular || coords[j] != 0)) { long int new_nei; if (coords[j] != 0) { new_nei = i - weights[j] + 1; } else { new_nei = i + (long int) (VECTOR(*dimvector)[j] - 1) * weights[j] + 1; } if (new_nei != i + 1 && (VECTOR(*dimvector)[j] != 2 || !circular)) { igraph_vector_push_back(&edges, i); /* reserved */ igraph_vector_push_back(&edges, new_nei - 1); /* reserved */ } } /* if circular || coords[0] */ } /* for j= 2) { IGRAPH_CHECK(igraph_connect_neighborhood(graph, nei, IGRAPH_ALL)); } /* clean up */ igraph_Free(coords); igraph_Free(weights); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(3); return 0; } /** * \ingroup generators * \function igraph_ring * \brief Creates a \em ring graph, a one dimensional lattice. * * An undirected (circular) ring on n vertices is commonly known in graph * theory as the cycle graph C_n. * * \param graph Pointer to an uninitialized graph object. * \param n The number of vertices in the ring. * \param directed Logical, whether to create a directed ring. * \param mutual Logical, whether to create mutual edges in a directed * ring. It is ignored for undirected graphs. * \param circular Logical, if false, the ring will be open (this is * not a real \em ring actually). * \return Error code: * \c IGRAPH_EINVAL: invalid number of vertices. * * Time complexity: O(|V|), the * number of vertices in the graph. * * \sa \ref igraph_lattice() for generating more general lattices. * * \example examples/simple/igraph_ring.c */ int igraph_ring(igraph_t *graph, igraph_integer_t n, igraph_bool_t directed, igraph_bool_t mutual, igraph_bool_t circular) { igraph_vector_t v = IGRAPH_VECTOR_NULL; if (n < 0) { IGRAPH_ERROR("negative number of vertices", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(&v, 1); VECTOR(v)[0] = n; IGRAPH_CHECK(igraph_lattice(graph, &v, 1, directed, mutual, circular)); igraph_vector_destroy(&v); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \ingroup generators * \function igraph_tree * \brief Creates a tree in which almost all vertices have the same number of children. * * \param graph Pointer to an uninitialized graph object. * \param n Integer, the number of vertices in the graph. * \param children Integer, the number of children of a vertex in the * tree. * \param type Constant, gives whether to create a directed tree, and * if this is the case, also its orientation. Possible values: * \clist * \cli IGRAPH_TREE_OUT * directed tree, the edges point * from the parents to their children, * \cli IGRAPH_TREE_IN * directed tree, the edges point from * the children to their parents. * \cli IGRAPH_TREE_UNDIRECTED * undirected tree. * \endclist * \return Error code: * \c IGRAPH_EINVAL: invalid number of vertices. * \c IGRAPH_INVMODE: invalid mode argument. * * Time complexity: O(|V|+|E|), the * number of vertices plus the number of edges in the graph. * * \sa \ref igraph_lattice(), \ref igraph_star() for creating other regular * structures; \ref igraph_from_prufer() for creating arbitrary trees; * \ref igraph_tree_game() for uniform random sampling of trees. * * \example examples/simple/igraph_tree.c */ int igraph_tree(igraph_t *graph, igraph_integer_t n, igraph_integer_t children, igraph_tree_mode_t type) { igraph_vector_t edges = IGRAPH_VECTOR_NULL; long int i, j; long int idx = 0; long int to = 1; if (n < 0 || children <= 0) { IGRAPH_ERROR("Invalid number of vertices or children", IGRAPH_EINVAL); } if (type != IGRAPH_TREE_OUT && type != IGRAPH_TREE_IN && type != IGRAPH_TREE_UNDIRECTED) { IGRAPH_ERROR("Invalid mode argument", IGRAPH_EINVMODE); } IGRAPH_VECTOR_INIT_FINALLY(&edges, 2 * (n - 1)); i = 0; if (type == IGRAPH_TREE_OUT) { while (idx < 2 * (n - 1)) { for (j = 0; j < children && idx < 2 * (n - 1); j++) { VECTOR(edges)[idx++] = i; VECTOR(edges)[idx++] = to++; } i++; } } else { while (idx < 2 * (n - 1)) { for (j = 0; j < children && idx < 2 * (n - 1); j++) { VECTOR(edges)[idx++] = to++; VECTOR(edges)[idx++] = i; } i++; } } IGRAPH_CHECK(igraph_create(graph, &edges, n, type != IGRAPH_TREE_UNDIRECTED)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \ingroup generators * \function igraph_full * \brief Creates a full graph (directed or undirected, with or without loops). * * * In a full graph every possible edge is present, every vertex is * connected to every other vertex. A full graph in \c igraph should be * distinguished from the concept of complete graphs as used in graph theory. * If n is a positive integer, then the complete graph K_n on n vertices is * the undirected simple graph with the following property. For any distinct * pair (u,v) of vertices in K_n, uv (or equivalently vu) is an edge of K_n. * In \c igraph, a full graph on n vertices can be K_n, a directed version of * K_n, or K_n with at least one loop edge. In any case, if F is a full graph * on n vertices as generated by \c igraph, then K_n is a subgraph of the * undirected version of F. * * \param graph Pointer to an uninitialized graph object. * \param n Integer, the number of vertices in the graph. * \param directed Logical, whether to create a directed graph. * \param loops Logical, whether to include self-edges (loops). * \return Error code: * \c IGRAPH_EINVAL: invalid number of vertices. * * Time complexity: O(|V|+|E|), * |V| is the number of vertices, * |E| the number of edges in the * graph. Of course this is the same as * O(|E|)=O(|V||V|) * here. * * \sa \ref igraph_lattice(), \ref igraph_star(), \ref igraph_tree() * for creating other regular structures. * * \example examples/simple/igraph_full.c */ int igraph_full(igraph_t *graph, igraph_integer_t n, igraph_bool_t directed, igraph_bool_t loops) { igraph_vector_t edges = IGRAPH_VECTOR_NULL; long int i, j; if (n < 0) { IGRAPH_ERROR("invalid number of vertices", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); if (directed && loops) { IGRAPH_CHECK(igraph_vector_reserve(&edges, n * n)); for (i = 0; i < n; i++) { for (j = 0; j < n; j++) { igraph_vector_push_back(&edges, i); /* reserved */ igraph_vector_push_back(&edges, j); /* reserved */ } } } else if (directed && !loops) { IGRAPH_CHECK(igraph_vector_reserve(&edges, n * (n - 1))); for (i = 0; i < n; i++) { for (j = 0; j < i; j++) { igraph_vector_push_back(&edges, i); /* reserved */ igraph_vector_push_back(&edges, j); /* reserved */ } for (j = i + 1; j < n; j++) { igraph_vector_push_back(&edges, i); /* reserved */ igraph_vector_push_back(&edges, j); /* reserved */ } } } else if (!directed && loops) { IGRAPH_CHECK(igraph_vector_reserve(&edges, n * (n + 1) / 2)); for (i = 0; i < n; i++) { for (j = i; j < n; j++) { igraph_vector_push_back(&edges, i); /* reserved */ igraph_vector_push_back(&edges, j); /* reserved */ } } } else { IGRAPH_CHECK(igraph_vector_reserve(&edges, n * (n - 1) / 2)); for (i = 0; i < n; i++) { for (j = i + 1; j < n; j++) { igraph_vector_push_back(&edges, i); /* reserved */ igraph_vector_push_back(&edges, j); /* reserved */ } } } IGRAPH_CHECK(igraph_create(graph, &edges, n, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_full_citation * Creates a full citation graph * * This is a directed graph, where every i->j edge is * present if and only if j<i. * If the \c directed argument is zero then an undirected graph is * created, and it is just a full graph. * \param graph Pointer to an uninitialized graph object, the result * is stored here. * \param n The number of vertices. * \param directed Whether to created a directed graph. If zero an * undirected graph is created. * \return Error code. * * Time complexity: O(|V|^2), as we have many edges. */ int igraph_full_citation(igraph_t *graph, igraph_integer_t n, igraph_bool_t directed) { igraph_vector_t edges; long int i, j, ptr = 0; IGRAPH_VECTOR_INIT_FINALLY(&edges, n * (n - 1)); for (i = 1; i < n; i++) { for (j = 0; j < i; j++) { VECTOR(edges)[ptr++] = i; VECTOR(edges)[ptr++] = j; } } IGRAPH_CHECK(igraph_create(graph, &edges, n, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_small * \brief Shorthand to create a short graph, giving the edges as arguments. * * * This function is handy when a relatively small graph needs to be created. * Instead of giving the edges as a vector, they are given simply as * arguments and a '-1' needs to be given after the last meaningful * edge argument. * * Note that only graphs which have vertices less than * the highest value of the 'int' type can be created this way. If you * give larger values then the result is undefined. * * \param graph Pointer to an uninitialized graph object. The result * will be stored here. * \param n The number of vertices in the graph; a nonnegative integer. * \param directed Logical constant; gives whether the graph should be * directed. Supported values are: * \clist * \cli IGRAPH_DIRECTED * The graph to be created will be \em directed. * \cli IGRAPH_UNDIRECTED * The graph to be created will be \em undirected. * \endclist * \param ... The additional arguments giving the edges of the * graph. Don't forget to supply an additional '-1' after the last * (meaningful) argument. * \return Error code. * * Time complexity: O(|V|+|E|), the number of vertices plus the number * of edges in the graph to create. * * \example examples/simple/igraph_small.c */ int igraph_small(igraph_t *graph, igraph_integer_t n, igraph_bool_t directed, ...) { igraph_vector_t edges; va_list ap; IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); va_start(ap, directed); while (1) { int num = va_arg(ap, int); if (num == -1) { break; } igraph_vector_push_back(&edges, num); } IGRAPH_CHECK(igraph_create(graph, &edges, n, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_extended_chordal_ring * Create an extended chordal ring * * An extended chordal ring is a cycle graph with additional chords * connecting its vertices. * * Each row \c L of the matrix \p W specifies a set of chords to be * inserted, in the following way: vertex \c i will connect to a vertex * L[(i mod p)] steps ahead of it along the cycle, where * \c p is the length of \c L. * In other words, vertex \c i will be connected to vertex * (i + L[(i mod p)]) mod nodes. * * * See also Kotsis, G: Interconnection Topologies for Parallel Processing * Systems, PARS Mitteilungen 11, 1-6, 1993. * * \param graph Pointer to an uninitialized graph object, the result * will be stored here. * \param nodes Integer constant, the number of vertices in the * graph. It must be at least 3. * \param W The matrix specifying the extra edges. The number of * columns should divide the number of total vertices. * \param directed Whether the graph should be directed. * \return Error code. * * \sa \ref igraph_ring(), \ref igraph_lcf(), \ref igraph_lcf_vector() * * Time complexity: O(|V|+|E|), the number of vertices plus the number * of edges. */ int igraph_extended_chordal_ring( igraph_t *graph, igraph_integer_t nodes, const igraph_matrix_t *W, igraph_bool_t directed) { igraph_vector_t edges; long int period = igraph_matrix_ncol(W); long int nrow = igraph_matrix_nrow(W); long int i, j, mpos = 0, epos = 0; if (nodes < 3) { IGRAPH_ERROR("An extended chordal ring has at least 3 nodes", IGRAPH_EINVAL); } if ((long int)nodes % period != 0) { IGRAPH_ERROR("The period (number of columns in W) should divide the " "number of nodes", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(&edges, 2 * (nodes + nodes * nrow)); for (i = 0; i < nodes - 1; i++) { VECTOR(edges)[epos++] = i; VECTOR(edges)[epos++] = i + 1; } VECTOR(edges)[epos++] = nodes - 1; VECTOR(edges)[epos++] = 0; if (nrow > 0) { for (i = 0; i < nodes; i++) { for (j = 0; j < nrow; j++) { long int offset = (long int) MATRIX(*W, j, mpos); long int v = (i + offset) % nodes; if (v < 0) { v += nodes; /* handle negative offsets */ } VECTOR(edges)[epos++] = i; VECTOR(edges)[epos++] = v; } mpos++; if (mpos == period) { mpos = 0; } } } IGRAPH_CHECK(igraph_create(graph, &edges, nodes, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } /** * \function igraph_connect_neighborhood * \brief Connects every vertex to its neighborhood * * This function adds new edges to the input graph. Each vertex is connected * to all vertices reachable by at most \p order steps from it * (unless a connection already existed). In other words, the \p order power of * the graph is computed. * * Note that the input graph is modified in place, no * new graph is created. Call \ref igraph_copy() if you want to keep * the original graph as well. * * For undirected graphs reachability is always * symmetric: if vertex A can be reached from vertex B in at * most \p order steps, then the opposite is also true. Only one * undirected (A,B) edge will be added in this case. * \param graph The input graph, this is the output graph as well. * \param order Integer constant, it gives the distance within which * the vertices will be connected to the source vertex. * \param mode Constant, it specifies how the neighborhood search is * performed for directed graphs. If \c IGRAPH_OUT then vertices * reachable from the source vertex will be connected, \c IGRAPH_IN * is the opposite. If \c IGRAPH_ALL then the directed graph is * considered as an undirected one. * \return Error code. * * \sa \ref igraph_lattice() uses this function to connect the * neighborhood of the vertices. * * Time complexity: O(|V|*d^k), |V| is the number of vertices in the * graph, d is the average degree and k is the \p order argument. */ int igraph_connect_neighborhood(igraph_t *graph, igraph_integer_t order, igraph_neimode_t mode) { long int no_of_nodes = igraph_vcount(graph); igraph_dqueue_t q; igraph_vector_t edges; long int i, j, in; long int *added; igraph_vector_t neis; if (order < 0) { IGRAPH_ERROR("Negative order, cannot connect neighborhood", IGRAPH_EINVAL); } if (order < 2) { IGRAPH_WARNING("Order smaller than two, graph will be unchanged"); } if (!igraph_is_directed(graph)) { mode = IGRAPH_ALL; } IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); added = igraph_Calloc(no_of_nodes, long int); if (added == 0) { IGRAPH_ERROR("Cannot connect neighborhood", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, added); IGRAPH_DQUEUE_INIT_FINALLY(&q, 100); IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); for (i = 0; i < no_of_nodes; i++) { added[i] = i + 1; igraph_neighbors(graph, &neis, (igraph_integer_t) i, mode); in = igraph_vector_size(&neis); if (order > 1) { for (j = 0; j < in; j++) { long int nei = (long int) VECTOR(neis)[j]; added[nei] = i + 1; igraph_dqueue_push(&q, nei); igraph_dqueue_push(&q, 1); } } while (!igraph_dqueue_empty(&q)) { long int actnode = (long int) igraph_dqueue_pop(&q); long int actdist = (long int) igraph_dqueue_pop(&q); long int n; igraph_neighbors(graph, &neis, (igraph_integer_t) actnode, mode); n = igraph_vector_size(&neis); if (actdist < order - 1) { for (j = 0; j < n; j++) { long int nei = (long int) VECTOR(neis)[j]; if (added[nei] != i + 1) { added[nei] = i + 1; IGRAPH_CHECK(igraph_dqueue_push(&q, nei)); IGRAPH_CHECK(igraph_dqueue_push(&q, actdist + 1)); if (mode != IGRAPH_ALL || i < nei) { if (mode == IGRAPH_IN) { IGRAPH_CHECK(igraph_vector_push_back(&edges, nei)); IGRAPH_CHECK(igraph_vector_push_back(&edges, i)); } else { IGRAPH_CHECK(igraph_vector_push_back(&edges, i)); IGRAPH_CHECK(igraph_vector_push_back(&edges, nei)); } } } } } else { for (j = 0; j < n; j++) { long int nei = (long int) VECTOR(neis)[j]; if (added[nei] != i + 1) { added[nei] = i + 1; if (mode != IGRAPH_ALL || i < nei) { if (mode == IGRAPH_IN) { IGRAPH_CHECK(igraph_vector_push_back(&edges, nei)); IGRAPH_CHECK(igraph_vector_push_back(&edges, i)); } else { IGRAPH_CHECK(igraph_vector_push_back(&edges, i)); IGRAPH_CHECK(igraph_vector_push_back(&edges, nei)); } } } } } } /* while q not empty */ } /* for i < no_of_nodes */ igraph_vector_destroy(&neis); igraph_dqueue_destroy(&q); igraph_free(added); IGRAPH_FINALLY_CLEAN(3); IGRAPH_CHECK(igraph_add_edges(graph, &edges, 0)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_de_bruijn * \brief Generate a de Bruijn graph. * * A de Bruijn graph represents relationships between strings. An alphabet * of \c m letters are used and strings of length \c n are considered. * A vertex corresponds to every possible string and there is a directed edge * from vertex \c v to vertex \c w if the string of \c v can be transformed into * the string of \c w by removing its first letter and appending a letter to it. * * * Please note that the graph will have \c m to the power \c n vertices and * even more edges, so probably you don't want to supply too big numbers for * \c m and \c n. * * * De Bruijn graphs have some interesting properties, please see another source, * eg. Wikipedia for details. * * \param graph Pointer to an uninitialized graph object, the result will be * stored here. * \param m Integer, the number of letters in the alphabet. * \param n Integer, the length of the strings. * \return Error code. * * \sa \ref igraph_kautz(). * * Time complexity: O(|V|+|E|), the number of vertices plus the number of edges. */ int igraph_de_bruijn(igraph_t *graph, igraph_integer_t m, igraph_integer_t n) { /* m - number of symbols */ /* n - length of strings */ long int no_of_nodes, no_of_edges; igraph_vector_t edges; long int i, j; long int mm = m; if (m < 0 || n < 0) { IGRAPH_ERROR("`m' and `n' should be non-negative in a de Bruijn graph", IGRAPH_EINVAL); } if (n == 0) { return igraph_empty(graph, 1, IGRAPH_DIRECTED); } if (m == 0) { return igraph_empty(graph, 0, IGRAPH_DIRECTED); } no_of_nodes = (long int) pow(m, n); no_of_edges = no_of_nodes * m; IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_CHECK(igraph_vector_reserve(&edges, no_of_edges * 2)); for (i = 0; i < no_of_nodes; i++) { long int basis = (i * mm) % no_of_nodes; for (j = 0; j < m; j++) { igraph_vector_push_back(&edges, i); igraph_vector_push_back(&edges, basis + j); } } IGRAPH_CHECK(igraph_create(graph, &edges, (igraph_integer_t) no_of_nodes, IGRAPH_DIRECTED)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_kautz * \brief Generate a Kautz graph. * * A Kautz graph is a labeled graph, vertices are labeled by strings * of length \c n+1 above an alphabet with \c m+1 letters, with * the restriction that every two consecutive letters in the string * must be different. There is a directed edge from a vertex \c v to * another vertex \c w if it is possible to transform the string of * \c v into the string of \c w by removing the first letter and * appending a letter to it. * * * Kautz graphs have some interesting properties, see eg. Wikipedia * for details. * * * Vincent Matossian wrote the first version of this function in R, * thanks. * \param graph Pointer to an uninitialized graph object, the result * will be stored here. * \param m Integer, \c m+1 is the number of letters in the alphabet. * \param n Integer, \c n+1 is the length of the strings. * \return Error code. * * \sa \ref igraph_de_bruijn(). * * Time complexity: O(|V|* [(m+1)/m]^n +|E|), in practice it is more * like O(|V|+|E|). |V| is the number of vertices, |E| is the number * of edges and \c m and \c n are the corresponding arguments. */ int igraph_kautz(igraph_t *graph, igraph_integer_t m, igraph_integer_t n) { /* m+1 - number of symbols */ /* n+1 - length of strings */ long int mm = m; long int no_of_nodes, no_of_edges; long int allstrings; long int i, j, idx = 0; igraph_vector_t edges; igraph_vector_long_t digits, table; igraph_vector_long_t index1, index2; long int actb = 0; long int actvalue = 0; if (m < 0 || n < 0) { IGRAPH_ERROR("`m' and `n' should be non-negative in a Kautz graph", IGRAPH_EINVAL); } if (n == 0) { return igraph_full(graph, m + 1, IGRAPH_DIRECTED, IGRAPH_NO_LOOPS); } if (m == 0) { return igraph_empty(graph, 0, IGRAPH_DIRECTED); } no_of_nodes = (long int) ((m + 1) * pow(m, n)); no_of_edges = no_of_nodes * m; allstrings = (long int) pow(m + 1, n + 1); IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_CHECK(igraph_vector_long_init(&table, n + 1)); IGRAPH_FINALLY(igraph_vector_long_destroy, &table); j = 1; for (i = n; i >= 0; i--) { VECTOR(table)[i] = j; j *= (m + 1); } IGRAPH_CHECK(igraph_vector_long_init(&digits, n + 1)); IGRAPH_FINALLY(igraph_vector_long_destroy, &digits); IGRAPH_CHECK(igraph_vector_long_init(&index1, (long int) pow(m + 1, n + 1))); IGRAPH_FINALLY(igraph_vector_long_destroy, &index1); IGRAPH_CHECK(igraph_vector_long_init(&index2, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_long_destroy, &index2); /* Fill the index tables*/ while (1) { /* at the beginning of the loop, 0:actb contain the valid prefix */ /* we might need to fill it to get a valid string */ long int z = 0; if (VECTOR(digits)[actb] == 0) { z = 1; } for (actb++; actb <= n; actb++) { VECTOR(digits)[actb] = z; actvalue += z * VECTOR(table)[actb]; z = 1 - z; } actb = n; /* ok, we have a valid string now */ VECTOR(index1)[actvalue] = idx + 1; VECTOR(index2)[idx] = actvalue; idx++; /* finished? */ if (idx >= no_of_nodes) { break; } /* not yet, we need a valid prefix now */ while (1) { /* try to increase digits at position actb */ long int next = VECTOR(digits)[actb] + 1; if (actb != 0 && VECTOR(digits)[actb - 1] == next) { next++; } if (next <= m) { /* ok, no problem */ actvalue += (next - VECTOR(digits)[actb]) * VECTOR(table)[actb]; VECTOR(digits)[actb] = next; break; } else { /* bad luck, try the previous digit */ actvalue -= VECTOR(digits)[actb] * VECTOR(table)[actb]; actb--; } } } IGRAPH_CHECK(igraph_vector_reserve(&edges, no_of_edges * 2)); /* Now come the edges at last */ for (i = 0; i < no_of_nodes; i++) { long int fromvalue = VECTOR(index2)[i]; long int lastdigit = fromvalue % (mm + 1); long int basis = (fromvalue * (mm + 1)) % allstrings; for (j = 0; j <= m; j++) { long int tovalue, to; if (j == lastdigit) { continue; } tovalue = basis + j; to = VECTOR(index1)[tovalue] - 1; if (to < 0) { continue; } igraph_vector_push_back(&edges, i); igraph_vector_push_back(&edges, to); } } igraph_vector_long_destroy(&index2); igraph_vector_long_destroy(&index1); igraph_vector_long_destroy(&digits); igraph_vector_long_destroy(&table); IGRAPH_FINALLY_CLEAN(4); IGRAPH_CHECK(igraph_create(graph, &edges, (igraph_integer_t) no_of_nodes, IGRAPH_DIRECTED)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_lcf_vector * \brief Create a graph from LCF notation * * This function is essentially the same as \ref igraph_lcf(), only * the way for giving the arguments is different. See \ref * igraph_lcf() for details. * \param graph Pointer to an uninitialized graph object. * \param n Integer constant giving the number of vertices. * \param shifts A vector giving the shifts. * \param repeats An integer constant giving the number of repeats * for the shifts. * \return Error code. * * \sa \ref igraph_lcf(), \ref igraph_extended_chordal_ring() * * Time complexity: O(|V|+|E|), linear in the number of vertices plus * the number of edges. */ int igraph_lcf_vector(igraph_t *graph, igraph_integer_t n, const igraph_vector_t *shifts, igraph_integer_t repeats) { igraph_vector_t edges; long int no_of_shifts = igraph_vector_size(shifts); long int ptr = 0, i, sptr = 0; long int no_of_nodes = n; long int no_of_edges = n + no_of_shifts * repeats; if (repeats < 0) { IGRAPH_ERROR("number of repeats must be positive", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(&edges, 2 * no_of_edges); if (no_of_nodes > 0) { /* Create a ring first */ for (i = 0; i < no_of_nodes; i++) { VECTOR(edges)[ptr++] = i; VECTOR(edges)[ptr++] = i + 1; } VECTOR(edges)[ptr - 1] = 0; } /* Then add the rest */ while (ptr < 2 * no_of_edges) { long int sh = (long int) VECTOR(*shifts)[sptr % no_of_shifts]; long int from = sptr % no_of_nodes; long int to = (no_of_nodes + sptr + sh) % no_of_nodes; VECTOR(edges)[ptr++] = from; VECTOR(edges)[ptr++] = to; sptr++; } IGRAPH_CHECK(igraph_create(graph, &edges, (igraph_integer_t) no_of_nodes, IGRAPH_UNDIRECTED)); IGRAPH_CHECK(igraph_simplify(graph, 1 /* true */, 1 /* true */, NULL)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_lcf * \brief Create a graph from LCF notation * * * LCF is short for Lederberg-Coxeter-Frucht, it is a concise notation for * 3-regular Hamiltonian graphs. It consists of three parameters: the * number of vertices in the graph, a list of shifts giving additional * edges to a cycle backbone, and another integer giving how many times * the shifts should be performed. See * http://mathworld.wolfram.com/LCFNotation.html for details. * * \param graph Pointer to an uninitialized graph object. * \param n Integer, the number of vertices in the graph. * \param ... The shifts and the number of repeats for the shifts, * plus an additional 0 to mark the end of the arguments. * \return Error code. * * \sa See \ref igraph_lcf_vector() for a similar function using a * vector_t instead of the variable length argument list. * * Time complexity: O(|V|+|E|), the number of vertices plus the number * of edges. * * \example examples/simple/igraph_lcf.c */ int igraph_lcf(igraph_t *graph, igraph_integer_t n, ...) { igraph_vector_t shifts; igraph_integer_t repeats; va_list ap; IGRAPH_VECTOR_INIT_FINALLY(&shifts, 0); va_start(ap, n); while (1) { int num = va_arg(ap, int); if (num == 0) { break; } IGRAPH_CHECK(igraph_vector_push_back(&shifts, num)); } if (igraph_vector_size(&shifts) == 0) { repeats = 0; } else { repeats = (igraph_integer_t) igraph_vector_pop_back(&shifts); } IGRAPH_CHECK(igraph_lcf_vector(graph, n, &shifts, repeats)); igraph_vector_destroy(&shifts); IGRAPH_FINALLY_CLEAN(1); return 0; } const igraph_real_t igraph_i_famous_bull[] = { 5, 5, 0, 0, 1, 0, 2, 1, 2, 1, 3, 2, 4 }; const igraph_real_t igraph_i_famous_chvatal[] = { 12, 24, 0, 5, 6, 6, 7, 7, 8, 8, 9, 5, 9, 4, 5, 4, 8, 2, 8, 2, 6, 0, 6, 0, 9, 3, 9, 3, 7, 1, 7, 1, 5, 1, 10, 4, 10, 4, 11, 2, 11, 0, 10, 0, 11, 3, 11, 3, 10, 1, 2 }; const igraph_real_t igraph_i_famous_coxeter[] = { 28, 42, 0, 0, 1, 0, 2, 0, 7, 1, 4, 1, 13, 2, 3, 2, 8, 3, 6, 3, 9, 4, 5, 4, 12, 5, 6, 5, 11, 6, 10, 7, 19, 7, 24, 8, 20, 8, 23, 9, 14, 9, 22, 10, 15, 10, 21, 11, 16, 11, 27, 12, 17, 12, 26, 13, 18, 13, 25, 14, 17, 14, 18, 15, 18, 15, 19, 16, 19, 16, 20, 17, 20, 21, 23, 21, 26, 22, 24, 22, 27, 23, 25, 24, 26, 25, 27 }; const igraph_real_t igraph_i_famous_cubical[] = { 8, 12, 0, 0, 1, 1, 2, 2, 3, 0, 3, 4, 5, 5, 6, 6, 7, 4, 7, 0, 4, 1, 5, 2, 6, 3, 7 }; const igraph_real_t igraph_i_famous_diamond[] = { 4, 5, 0, 0, 1, 0, 2, 1, 2, 1, 3, 2, 3 }; const igraph_real_t igraph_i_famous_dodecahedron[] = { 20, 30, 0, 0, 1, 0, 4, 0, 5, 1, 2, 1, 6, 2, 3, 2, 7, 3, 4, 3, 8, 4, 9, 5, 10, 5, 11, 6, 10, 6, 14, 7, 13, 7, 14, 8, 12, 8, 13, 9, 11, 9, 12, 10, 15, 11, 16, 12, 17, 13, 18, 14, 19, 15, 16, 15, 19, 16, 17, 17, 18, 18, 19 }; const igraph_real_t igraph_i_famous_folkman[] = { 20, 40, 0, 0, 5, 0, 8, 0, 10, 0, 13, 1, 7, 1, 9, 1, 12, 1, 14, 2, 6, 2, 8, 2, 11, 2, 13, 3, 5, 3, 7, 3, 10, 3, 12, 4, 6, 4, 9, 4, 11, 4, 14, 5, 15, 5, 19, 6, 15, 6, 16, 7, 16, 7, 17, 8, 17, 8, 18, 9, 18, 9, 19, 10, 15, 10, 19, 11, 15, 11, 16, 12, 16, 12, 17, 13, 17, 13, 18, 14, 18, 14, 19 }; const igraph_real_t igraph_i_famous_franklin[] = { 12, 18, 0, 0, 1, 0, 2, 0, 6, 1, 3, 1, 7, 2, 4, 2, 10, 3, 5, 3, 11, 4, 5, 4, 6, 5, 7, 6, 8, 7, 9, 8, 9, 8, 11, 9, 10, 10, 11 }; const igraph_real_t igraph_i_famous_frucht[] = { 12, 18, 0, 0, 1, 0, 2, 0, 11, 1, 3, 1, 6, 2, 5, 2, 10, 3, 4, 3, 6, 4, 8, 4, 11, 5, 9, 5, 10, 6, 7, 7, 8, 7, 9, 8, 9, 10, 11 }; const igraph_real_t igraph_i_famous_grotzsch[] = { 11, 20, 0, 0, 1, 0, 2, 0, 7, 0, 10, 1, 3, 1, 6, 1, 9, 2, 4, 2, 6, 2, 8, 3, 4, 3, 8, 3, 10, 4, 7, 4, 9, 5, 6, 5, 7, 5, 8, 5, 9, 5, 10 }; const igraph_real_t igraph_i_famous_heawood[] = { 14, 21, 0, 0, 1, 0, 5, 0, 13, 1, 2, 1, 10, 2, 3, 2, 7, 3, 4, 3, 12, 4, 5, 4, 9, 5, 6, 6, 7, 6, 11, 7, 8, 8, 9, 8, 13, 9, 10, 10, 11, 11, 12, 12, 13 }; const igraph_real_t igraph_i_famous_herschel[] = { 11, 18, 0, 0, 2, 0, 3, 0, 4, 0, 5, 1, 2, 1, 3, 1, 6, 1, 7, 2, 10, 3, 9, 4, 8, 4, 9, 5, 8, 5, 10, 6, 8, 6, 9, 7, 8, 7, 10 }; const igraph_real_t igraph_i_famous_house[] = { 5, 6, 0, 0, 1, 0, 2, 1, 3, 2, 3, 2, 4, 3, 4 }; const igraph_real_t igraph_i_famous_housex[] = { 5, 8, 0, 0, 1, 0, 2, 0, 3, 1, 2, 1, 3, 2, 3, 2, 4, 3, 4 }; const igraph_real_t igraph_i_famous_icosahedron[] = { 12, 30, 0, 0, 1, 0, 2, 0, 3, 0, 4, 0, 8, 1, 2, 1, 6, 1, 7, 1, 8, 2, 4, 2, 5, 2, 6, 3, 4, 3, 8, 3, 9, 3, 11, 4, 5, 4, 11, 5, 6, 5, 10, 5, 11, 6, 7, 6, 10, 7, 8, 7, 9, 7, 10, 8, 9, 9, 10, 9, 11, 10, 11 }; const igraph_real_t igraph_i_famous_krackhardt_kite[] = { 10, 18, 0, 0, 1, 0, 2, 0, 3, 0, 5, 1, 3, 1, 4, 1, 6, 2, 3, 2, 5, 3, 4, 3, 5, 3, 6, 4, 6, 5, 6, 5, 7, 6, 7, 7, 8, 8, 9 }; const igraph_real_t igraph_i_famous_levi[] = { 30, 45, 0, 0, 1, 0, 7, 0, 29, 1, 2, 1, 24, 2, 3, 2, 11, 3, 4, 3, 16, 4, 5, 4, 21, 5, 6, 5, 26, 6, 7, 6, 13, 7, 8, 8, 9, 8, 17, 9, 10, 9, 22, 10, 11, 10, 27, 11, 12, 12, 13, 12, 19, 13, 14, 14, 15, 14, 23, 15, 16, 15, 28, 16, 17, 17, 18, 18, 19, 18, 25, 19, 20, 20, 21, 20, 29, 21, 22, 22, 23, 23, 24, 24, 25, 25, 26, 26, 27, 27, 28, 28, 29 }; const igraph_real_t igraph_i_famous_mcgee[] = { 24, 36, 0, 0, 1, 0, 7, 0, 23, 1, 2, 1, 18, 2, 3, 2, 14, 3, 4, 3, 10, 4, 5, 4, 21, 5, 6, 5, 17, 6, 7, 6, 13, 7, 8, 8, 9, 8, 20, 9, 10, 9, 16, 10, 11, 11, 12, 11, 23, 12, 13, 12, 19, 13, 14, 14, 15, 15, 16, 15, 22, 16, 17, 17, 18, 18, 19, 19, 20, 20, 21, 21, 22, 22, 23 }; const igraph_real_t igraph_i_famous_meredith[] = { 70, 140, 0, 0, 4, 0, 5, 0, 6, 1, 4, 1, 5, 1, 6, 2, 4, 2, 5, 2, 6, 3, 4, 3, 5, 3, 6, 7, 11, 7, 12, 7, 13, 8, 11, 8, 12, 8, 13, 9, 11, 9, 12, 9, 13, 10, 11, 10, 12, 10, 13, 14, 18, 14, 19, 14, 20, 15, 18, 15, 19, 15, 20, 16, 18, 16, 19, 16, 20, 17, 18, 17, 19, 17, 20, 21, 25, 21, 26, 21, 27, 22, 25, 22, 26, 22, 27, 23, 25, 23, 26, 23, 27, 24, 25, 24, 26, 24, 27, 28, 32, 28, 33, 28, 34, 29, 32, 29, 33, 29, 34, 30, 32, 30, 33, 30, 34, 31, 32, 31, 33, 31, 34, 35, 39, 35, 40, 35, 41, 36, 39, 36, 40, 36, 41, 37, 39, 37, 40, 37, 41, 38, 39, 38, 40, 38, 41, 42, 46, 42, 47, 42, 48, 43, 46, 43, 47, 43, 48, 44, 46, 44, 47, 44, 48, 45, 46, 45, 47, 45, 48, 49, 53, 49, 54, 49, 55, 50, 53, 50, 54, 50, 55, 51, 53, 51, 54, 51, 55, 52, 53, 52, 54, 52, 55, 56, 60, 56, 61, 56, 62, 57, 60, 57, 61, 57, 62, 58, 60, 58, 61, 58, 62, 59, 60, 59, 61, 59, 62, 63, 67, 63, 68, 63, 69, 64, 67, 64, 68, 64, 69, 65, 67, 65, 68, 65, 69, 66, 67, 66, 68, 66, 69, 2, 50, 1, 51, 9, 57, 8, 58, 16, 64, 15, 65, 23, 36, 22, 37, 30, 43, 29, 44, 3, 21, 7, 24, 14, 31, 0, 17, 10, 28, 38, 42, 35, 66, 59, 63, 52, 56, 45, 49 }; const igraph_real_t igraph_i_famous_noperfectmatching[] = { 16, 27, 0, 0, 1, 0, 2, 0, 3, 1, 2, 1, 3, 2, 3, 2, 4, 3, 4, 4, 5, 5, 6, 5, 7, 6, 12, 6, 13, 7, 8, 7, 9, 8, 9, 8, 10, 8, 11, 9, 10, 9, 11, 10, 11, 12, 13, 12, 14, 12, 15, 13, 14, 13, 15, 14, 15 }; const igraph_real_t igraph_i_famous_nonline[] = { 50, 72, 0, 0, 1, 0, 2, 0, 3, 4, 6, 4, 7, 5, 6, 5, 7, 6, 7, 7, 8, 9, 11, 9, 12, 9, 13, 10, 11, 10, 12, 10, 13, 11, 12, 11, 13, 12, 13, 14, 15, 15, 16, 15, 17, 16, 17, 16, 18, 17, 18, 18, 19, 20, 21, 20, 22, 20, 23, 21, 22, 21, 23, 21, 24, 22, 23, 22, 24, 24, 25, 26, 27, 26, 28, 26, 29, 27, 28, 27, 29, 27, 30, 27, 31, 28, 29, 28, 30, 28, 31, 30, 31, 32, 34, 32, 35, 32, 36, 33, 34, 33, 35, 33, 37, 34, 35, 36, 37, 38, 39, 38, 40, 38, 43, 39, 40, 39, 41, 39, 42, 39, 43, 40, 41, 41, 42, 42, 43, 44, 45, 44, 46, 45, 46, 45, 47, 46, 47, 46, 48, 47, 48, 47, 49, 48, 49 }; const igraph_real_t igraph_i_famous_octahedron[] = { 6, 12, 0, 0, 1, 0, 2, 1, 2, 3, 4, 3, 5, 4, 5, 0, 3, 0, 5, 1, 3, 1, 4, 2, 4, 2, 5 }; const igraph_real_t igraph_i_famous_petersen[] = { 10, 15, 0, 0, 1, 0, 4, 0, 5, 1, 2, 1, 6, 2, 3, 2, 7, 3, 4, 3, 8, 4, 9, 5, 7, 5, 8, 6, 8, 6, 9, 7, 9 }; const igraph_real_t igraph_i_famous_robertson[] = { 19, 38, 0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7, 7, 8, 8, 9, 9, 10, 10, 11, 11, 12, 12, 13, 13, 14, 14, 15, 15, 16, 16, 17, 17, 18, 0, 18, 0, 4, 4, 9, 9, 13, 13, 17, 2, 17, 2, 6, 6, 10, 10, 15, 0, 15, 1, 8, 8, 16, 5, 16, 5, 12, 1, 12, 7, 18, 7, 14, 3, 14, 3, 11, 11, 18 }; const igraph_real_t igraph_i_famous_smallestcyclicgroup[] = { 9, 15, 0, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 1, 2, 1, 3, 1, 7, 1, 8, 2, 5, 2, 6, 2, 7, 3, 8, 4, 5, 6, 7 }; const igraph_real_t igraph_i_famous_tetrahedron[] = { 4, 6, 0, 0, 3, 1, 3, 2, 3, 0, 1, 1, 2, 0, 2 }; const igraph_real_t igraph_i_famous_thomassen[] = { 34, 52, 0, 0, 2, 0, 3, 1, 3, 1, 4, 2, 4, 5, 7, 5, 8, 6, 8, 6, 9, 7, 9, 10, 12, 10, 13, 11, 13, 11, 14, 12, 14, 15, 17, 15, 18, 16, 18, 16, 19, 17, 19, 9, 19, 4, 14, 24, 25, 25, 26, 20, 26, 20, 21, 21, 22, 22, 23, 23, 27, 27, 28, 28, 29, 29, 30, 30, 31, 31, 32, 32, 33, 24, 33, 5, 24, 6, 25, 7, 26, 8, 20, 0, 20, 1, 21, 2, 22, 3, 23, 10, 27, 11, 28, 12, 29, 13, 30, 15, 30, 16, 31, 17, 32, 18, 33 }; const igraph_real_t igraph_i_famous_tutte[] = { 46, 69, 0, 0, 10, 0, 11, 0, 12, 1, 2, 1, 7, 1, 19, 2, 3, 2, 41, 3, 4, 3, 27, 4, 5, 4, 33, 5, 6, 5, 45, 6, 9, 6, 29, 7, 8, 7, 21, 8, 9, 8, 22, 9, 24, 10, 13, 10, 14, 11, 26, 11, 28, 12, 30, 12, 31, 13, 15, 13, 21, 14, 15, 14, 18, 15, 16, 16, 17, 16, 20, 17, 18, 17, 23, 18, 24, 19, 25, 19, 40, 20, 21, 20, 22, 22, 23, 23, 24, 25, 26, 25, 38, 26, 34, 27, 28, 27, 39, 28, 34, 29, 30, 29, 44, 30, 35, 31, 32, 31, 35, 32, 33, 32, 42, 33, 43, 34, 36, 35, 37, 36, 38, 36, 39, 37, 42, 37, 44, 38, 40, 39, 41, 40, 41, 42, 43, 43, 45, 44, 45 }; const igraph_real_t igraph_i_famous_uniquely3colorable[] = { 12, 22, 0, 0, 1, 0, 3, 0, 6, 0, 8, 1, 4, 1, 7, 1, 9, 2, 3, 2, 6, 2, 7, 2, 9, 2, 11, 3, 4, 3, 10, 4, 5, 4, 11, 5, 6, 5, 7, 5, 8, 5, 10, 8, 11, 9, 10 }; const igraph_real_t igraph_i_famous_walther[] = { 25, 31, 0, 0, 1, 1, 2, 1, 8, 2, 3, 2, 13, 3, 4, 3, 16, 4, 5, 5, 6, 5, 19, 6, 7, 6, 20, 7, 21, 8, 9, 8, 13, 9, 10, 9, 22, 10, 11, 10, 20, 11, 12, 13, 14, 14, 15, 14, 23, 15, 16, 15, 17, 17, 18, 18, 19, 18, 24, 20, 24, 22, 23, 23, 24 }; const igraph_real_t igraph_i_famous_zachary[] = { 34, 78, 0, 0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 0, 7, 0, 8, 0, 10, 0, 11, 0, 12, 0, 13, 0, 17, 0, 19, 0, 21, 0, 31, 1, 2, 1, 3, 1, 7, 1, 13, 1, 17, 1, 19, 1, 21, 1, 30, 2, 3, 2, 7, 2, 27, 2, 28, 2, 32, 2, 9, 2, 8, 2, 13, 3, 7, 3, 12, 3, 13, 4, 6, 4, 10, 5, 6, 5, 10, 5, 16, 6, 16, 8, 30, 8, 32, 8, 33, 9, 33, 13, 33, 14, 32, 14, 33, 15, 32, 15, 33, 18, 32, 18, 33, 19, 33, 20, 32, 20, 33, 22, 32, 22, 33, 23, 25, 23, 27, 23, 32, 23, 33, 23, 29, 24, 25, 24, 27, 24, 31, 25, 31, 26, 29, 26, 33, 27, 33, 28, 31, 28, 33, 29, 32, 29, 33, 30, 32, 30, 33, 31, 32, 31, 33, 32, 33 }; int igraph_i_famous(igraph_t *graph, const igraph_real_t *data); int igraph_i_famous(igraph_t *graph, const igraph_real_t *data) { long int no_of_nodes = (long int) data[0]; long int no_of_edges = (long int) data[1]; igraph_bool_t directed = (igraph_bool_t) data[2]; igraph_vector_t edges; igraph_vector_view(&edges, data + 3, 2 * no_of_edges); IGRAPH_CHECK(igraph_create(graph, &edges, (igraph_integer_t) no_of_nodes, directed)); return 0; } /** * \function igraph_famous * \brief Create a famous graph by simply providing its name * * * The name of the graph can be simply supplied as a string. * Note that this function creates graphs which don't take any parameters, * there are separate functions for graphs with parameters, eg. \ref * igraph_full() for creating a full graph. * * * The following graphs are supported: * \clist * \cli Bull * The bull graph, 5 vertices, 5 edges, resembles the * head of a bull if drawn properly. * \cli Chvatal * This is the smallest triangle-free graph that is * both 4-chromatic and 4-regular. According to the Grunbaum * conjecture there exists an m-regular, m-chromatic graph * with n vertices for every m>1 and n>2. The Chvatal graph * is an example for m=4 and n=12. It has 24 edges. * \cli Coxeter * A non-Hamiltonian cubic symmetric graph with 28 * vertices and 42 edges. * \cli Cubical * The Platonic graph of the cube. A convex regular * polyhedron with 8 vertices and 12 edges. * \cli Diamond * A graph with 4 vertices and 5 edges, resembles a * schematic diamond if drawn properly. * \cli Dodecahedral, Dodecahedron * Another Platonic solid * with 20 vertices and 30 edges. * \cli Folkman * The semisymmetric graph with minimum number of * vertices, 20 and 40 edges. A semisymmetric graph is * regular, edge transitive and not vertex transitive. * \cli Franklin * This is a graph whose embedding to the Klein * bottle can be colored with six colors, it is a * counterexample to the necessity of the Heawood * conjecture on a Klein bottle. It has 12 vertices and 18 * edges. * \cli Frucht * The Frucht Graph is the smallest cubical graph * whose automorphism group consists only of the identity * element. It has 12 vertices and 18 edges. * \cli Grotzsch * The Grötzsch graph is a triangle-free graph with * 11 vertices, 20 edges, and chromatic number 4. It is named after * German mathematician Herbert Grötzsch, and its existence * demonstrates that the assumption of planarity is necessary in * Grötzsch's theorem that every triangle-free planar * graph is 3-colorable. * \cli Heawood * The Heawood graph is an undirected graph with 14 * vertices and 21 edges. The graph is cubic, and all cycles in the * graph have six or more edges. Every smaller cubic graph has shorter * cycles, so this graph is the 6-cage, the smallest cubic graph of * girth 6. * \cli Herschel * The Herschel graph is the smallest * nonhamiltonian polyhedral graph. It is the * unique such graph on 11 nodes, and has 18 edges. * \cli House * The house graph is a 5-vertex, 6-edge graph, the * schematic draw of a house if drawn properly, basically a * triangle on top of a square. * \cli HouseX * The same as the house graph with an X in the square. 5 * vertices and 8 edges. * \cli Icosahedral, Icosahedron * A Platonic solid with 12 * vertices and 30 edges. * \cli Krackhardt_Kite * A social network with 10 vertices and 18 edges. * Krackhardt, D. Assessing the Political Landscape: * Structure, Cognition, and Power in Organizations. * Admin. Sci. Quart. 35, 342-369, 1990. * \cli Levi * The graph is a 4-arc transitive cubic graph, it has * 30 vertices and 45 edges. * \cli McGee * The McGee graph is the unique 3-regular 7-cage * graph, it has 24 vertices and 36 edges. * \cli Meredith * The Meredith graph is a quartic graph on 70 * nodes and 140 edges that is a counterexample to the conjecture that * every 4-regular 4-connected graph is Hamiltonian. * \cli Noperfectmatching * A connected graph with 16 vertices and * 27 edges containing no perfect matching. A matching in a graph * is a set of pairwise non-incident edges; that is, no two edges * share a common vertex. A perfect matching is a matching * which covers all vertices of the graph. * \cli Nonline * A graph whose connected components are the 9 * graphs whose presence as a vertex-induced subgraph in a * graph makes a nonline graph. It has 50 vertices and 72 edges. * \cli Octahedral, Octahedron * Platonic solid with 6 * vertices and 12 edges. * \cli Petersen * A 3-regular graph with 10 vertices and 15 edges. It is * the smallest hypohamiltonian graph, ie. it is * non-hamiltonian but removing any single vertex from it makes it * Hamiltonian. * \cli Robertson * The unique (4,5)-cage graph, ie. a 4-regular * graph of girth 5. It has 19 vertices and 38 edges. * \cli Smallestcyclicgroup * A smallest nontrivial graph * whose automorphism group is cyclic. It has 9 vertices and * 15 edges. * \cli Tetrahedral, Tetrahedron * Platonic solid with 4 * vertices and 6 edges. * \cli Thomassen * The smallest hypotraceable graph, * on 34 vertices and 52 edges. A hypotracable graph does * not contain a Hamiltonian path but after removing any * single vertex from it the remainder always contains a * Hamiltonian path. A graph containing a Hamiltonian path * is called traceable. * \cli Tutte * Tait's Hamiltonian graph conjecture states that * every 3-connected 3-regular planar graph is Hamiltonian. * This graph is a counterexample. It has 46 vertices and 69 * edges. * \cli Uniquely3colorable * Returns a 12-vertex, triangle-free * graph with chromatic number 3 that is uniquely * 3-colorable. * \cli Walther * An identity graph with 25 vertices and 31 * edges. An identity graph has a single graph automorphism, * the trivial one. * \cli Zachary * Social network of friendships between 34 members of a * karate club at a US university in the 1970s. See * W. W. Zachary, An information flow model for conflict and * fission in small groups, Journal of Anthropological * Research 33, 452-473 (1977). * \endclist * * \param graph Pointer to an uninitialized graph object. * \param name Character constant, the name of the graph to be * created, it is case insensitive. * \return Error code, IGRAPH_EINVAL if there is no graph with the * given name. * * \sa Other functions for creating graph structures: * \ref igraph_ring(), \ref igraph_tree(), \ref igraph_lattice(), \ref * igraph_full(). * * Time complexity: O(|V|+|E|), the number of vertices plus the number * of edges in the graph. */ int igraph_famous(igraph_t *graph, const char *name) { if (!strcasecmp(name, "bull")) { return igraph_i_famous(graph, igraph_i_famous_bull); } else if (!strcasecmp(name, "chvatal")) { return igraph_i_famous(graph, igraph_i_famous_chvatal); } else if (!strcasecmp(name, "coxeter")) { return igraph_i_famous(graph, igraph_i_famous_coxeter); } else if (!strcasecmp(name, "cubical")) { return igraph_i_famous(graph, igraph_i_famous_cubical); } else if (!strcasecmp(name, "diamond")) { return igraph_i_famous(graph, igraph_i_famous_diamond); } else if (!strcasecmp(name, "dodecahedral") || !strcasecmp(name, "dodecahedron")) { return igraph_i_famous(graph, igraph_i_famous_dodecahedron); } else if (!strcasecmp(name, "folkman")) { return igraph_i_famous(graph, igraph_i_famous_folkman); } else if (!strcasecmp(name, "franklin")) { return igraph_i_famous(graph, igraph_i_famous_franklin); } else if (!strcasecmp(name, "frucht")) { return igraph_i_famous(graph, igraph_i_famous_frucht); } else if (!strcasecmp(name, "grotzsch")) { return igraph_i_famous(graph, igraph_i_famous_grotzsch); } else if (!strcasecmp(name, "heawood")) { return igraph_i_famous(graph, igraph_i_famous_heawood); } else if (!strcasecmp(name, "herschel")) { return igraph_i_famous(graph, igraph_i_famous_herschel); } else if (!strcasecmp(name, "house")) { return igraph_i_famous(graph, igraph_i_famous_house); } else if (!strcasecmp(name, "housex")) { return igraph_i_famous(graph, igraph_i_famous_housex); } else if (!strcasecmp(name, "icosahedral") || !strcasecmp(name, "icosahedron")) { return igraph_i_famous(graph, igraph_i_famous_icosahedron); } else if (!strcasecmp(name, "krackhardt_kite")) { return igraph_i_famous(graph, igraph_i_famous_krackhardt_kite); } else if (!strcasecmp(name, "levi")) { return igraph_i_famous(graph, igraph_i_famous_levi); } else if (!strcasecmp(name, "mcgee")) { return igraph_i_famous(graph, igraph_i_famous_mcgee); } else if (!strcasecmp(name, "meredith")) { return igraph_i_famous(graph, igraph_i_famous_meredith); } else if (!strcasecmp(name, "noperfectmatching")) { return igraph_i_famous(graph, igraph_i_famous_noperfectmatching); } else if (!strcasecmp(name, "nonline")) { return igraph_i_famous(graph, igraph_i_famous_nonline); } else if (!strcasecmp(name, "octahedral") || !strcasecmp(name, "octahedron")) { return igraph_i_famous(graph, igraph_i_famous_octahedron); } else if (!strcasecmp(name, "petersen")) { return igraph_i_famous(graph, igraph_i_famous_petersen); } else if (!strcasecmp(name, "robertson")) { return igraph_i_famous(graph, igraph_i_famous_robertson); } else if (!strcasecmp(name, "smallestcyclicgroup")) { return igraph_i_famous(graph, igraph_i_famous_smallestcyclicgroup); } else if (!strcasecmp(name, "tetrahedral") || !strcasecmp(name, "tetrahedron")) { return igraph_i_famous(graph, igraph_i_famous_tetrahedron); } else if (!strcasecmp(name, "thomassen")) { return igraph_i_famous(graph, igraph_i_famous_thomassen); } else if (!strcasecmp(name, "tutte")) { return igraph_i_famous(graph, igraph_i_famous_tutte); } else if (!strcasecmp(name, "uniquely3colorable")) { return igraph_i_famous(graph, igraph_i_famous_uniquely3colorable); } else if (!strcasecmp(name, "walther")) { return igraph_i_famous(graph, igraph_i_famous_walther); } else if (!strcasecmp(name, "zachary")) { return igraph_i_famous(graph, igraph_i_famous_zachary); } else { IGRAPH_ERROR("Unknown graph, see documentation", IGRAPH_EINVAL); } return 0; } /** * \function igraph_adjlist * Create a graph from an adjacency list * * An adjacency list is a list of vectors, containing the neighbors * of all vertices. For operations that involve many changes to the * graph structure, it is recommended that you convert the graph into * an adjacency list via \ref igraph_adjlist_init(), perform the * modifications (these are cheap for an adjacency list) and then * recreate the igraph graph via this function. * * \param graph Pointer to an uninitialized graph object. * \param adjlist The adjacency list. * \param mode Whether or not to create a directed graph. \c IGRAPH_ALL * means an undirected graph, \c IGRAPH_OUT means a * directed graph from an out-adjacency list (i.e. each * list contains the successors of the corresponding * vertices), \c IGRAPH_IN means a directed graph from an * in-adjacency list * \param duplicate Logical, for undirected graphs this specified * whether each edge is included twice, in the vectors of * both adjacent vertices. If this is false (0), then it is * assumed that every edge is included only once. This argument * is ignored for directed graphs. * \return Error code. * * \sa \ref igraph_adjlist_init() for the opposite operation. * * Time complexity: O(|V|+|E|). * */ int igraph_adjlist(igraph_t *graph, const igraph_adjlist_t *adjlist, igraph_neimode_t mode, igraph_bool_t duplicate) { long int no_of_nodes = igraph_adjlist_size(adjlist); long int no_of_edges = 0; long int i; igraph_vector_t edges; long int edgeptr = 0; duplicate = duplicate && (mode == IGRAPH_ALL); /* only duplicate if undirected */ for (i = 0; i < no_of_nodes; i++) { no_of_edges += igraph_vector_int_size(igraph_adjlist_get(adjlist, i)); } if (duplicate) { no_of_edges /= 2; } IGRAPH_VECTOR_INIT_FINALLY(&edges, 2 * no_of_edges); for (i = 0; i < no_of_nodes; i++) { igraph_vector_int_t *neis = igraph_adjlist_get(adjlist, i); long int j, n = igraph_vector_int_size(neis); long int loops = 0; for (j = 0; j < n; j++) { long int nei = (long int) VECTOR(*neis)[j]; if (nei == i) { loops++; } else { if (! duplicate || nei > i) { if (edgeptr + 2 > 2 * no_of_edges) { IGRAPH_ERROR("Invalid adjacency list, most probably not correctly" " duplicated edges for an undirected graph", IGRAPH_EINVAL); } if (mode == IGRAPH_IN) { VECTOR(edges)[edgeptr++] = nei; VECTOR(edges)[edgeptr++] = i; } else { VECTOR(edges)[edgeptr++] = i; VECTOR(edges)[edgeptr++] = nei; } } } } /* loops */ if (duplicate) { loops = loops / 2; } if (edgeptr + 2 * loops > 2 * no_of_edges) { IGRAPH_ERROR("Invalid adjacency list, most probably not correctly" " duplicated edges for an undirected graph", IGRAPH_EINVAL); } for (j = 0; j < loops; j++) { VECTOR(edges)[edgeptr++] = i; VECTOR(edges)[edgeptr++] = i; } } if (mode == IGRAPH_ALL) IGRAPH_CHECK(igraph_create(graph, &edges, (igraph_integer_t) no_of_nodes, 0)); else IGRAPH_CHECK(igraph_create(graph, &edges, (igraph_integer_t) no_of_nodes, 1)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \ingroup generators * \function igraph_from_prufer * \brief Generates a tree from a Prüfer sequence * * A Prüfer sequence is a unique sequence of integers associated * with a labelled tree. A tree on n vertices can be represented by a * sequence of n-2 integers, each between 0 and n-1 (inclusive). * * The algorithm used by this function is based on * Paulius Micikevičius, Saverio Caminiti, Narsingh Deo: * Linear-time Algorithms for Encoding Trees as Sequences of Node Labels * * \param graph Pointer to an uninitialized graph object. * \param prufer The Prüfer sequence * \return Error code: * \clist * \cli IGRAPH_ENOMEM * there is not enough memory to perform the operation. * \cli IGRAPH_EINVAL * invalid Prüfer sequence given * \endclist * * \sa \ref igraph_tree(), \ref igraph_tree_game() * */ int igraph_from_prufer(igraph_t *graph, const igraph_vector_int_t *prufer) { igraph_vector_int_t degree; igraph_vector_t edges; long n; long i, k; long u, v; /* vertices */ long ec; n = igraph_vector_int_size(prufer) + 2; IGRAPH_VECTOR_INT_INIT_FINALLY(°ree, n); /* initializes vector to zeros */ IGRAPH_VECTOR_INIT_FINALLY(&edges, 2 * (n - 1)); /* build out-degree vector (i.e. number of child vertices) and verify Prufer sequence */ for (i = 0; i < n - 2; ++i) { long u = VECTOR(*prufer)[i]; if (u >= n || u < 0) { IGRAPH_ERROR("Invalid Prufer sequence", IGRAPH_EINVAL); } VECTOR(degree)[u] += 1; } v = 0; /* initialize v now, in case Prufer sequence is empty */ k = 0; /* index into the Prufer vector */ ec = 0; /* index into the edges vector */ for (i = 0; i < n; ++i) { u = i; while (k < n - 2 && u <= i && (VECTOR(degree)[u] == 0)) { /* u is a leaf here */ v = VECTOR(*prufer)[k]; /* parent of u */ /* add edge */ VECTOR(edges)[ec++] = v; VECTOR(edges)[ec++] = u; k += 1; VECTOR(degree)[v] -= 1; u = v; } if (k == n - 2) { break; } } /* find u for last edge, v is already set */ for (u = i + 1; u < n; ++u) if ((VECTOR(degree)[u] == 0) && u != v) { break; } /* add last edge */ VECTOR(edges)[ec++] = v; VECTOR(edges)[ec++] = u; IGRAPH_CHECK(igraph_create(graph, &edges, (igraph_integer_t) n, /* directed = */ 0)); igraph_vector_destroy(&edges); igraph_vector_int_destroy(°ree); IGRAPH_FINALLY_CLEAN(2); return IGRAPH_SUCCESS; } python-igraph-0.8.0/vendor/source/igraph/src/matching.c0000644000076500000240000012242013614300625023335 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include "config.h" #include "igraph_adjlist.h" #include "igraph_constructors.h" #include "igraph_conversion.h" #include "igraph_dqueue.h" #include "igraph_flow.h" #include "igraph_interface.h" #include "igraph_matching.h" #include "igraph_structural.h" /* #define MATCHING_DEBUG */ #ifdef _MSC_VER /* MSVC does not support variadic macros */ #include static void debug(const char* fmt, ...) { va_list args; va_start(args, fmt); #ifdef MATCHING_DEBUG vfprintf(stderr, fmt, args); #endif va_end(args); } #else #ifdef MATCHING_DEBUG #define debug(...) fprintf(stderr, __VA_ARGS__) #else #define debug(...) #endif #endif /** * \function igraph_is_matching * Checks whether the given matching is valid for the given graph. * * This function checks a matching vector and verifies whether its length * matches the number of vertices in the given graph, its values are between * -1 (inclusive) and the number of vertices (exclusive), and whether there * exists a corresponding edge in the graph for every matched vertex pair. * For bipartite graphs, it also verifies whether the matched vertices are * in different parts of the graph. * * \param graph The input graph. It can be directed but the edge directions * will be ignored. * \param types If the graph is bipartite and you are interested in bipartite * matchings only, pass the vertex types here. If the graph is * non-bipartite, simply pass \c NULL. * \param matching The matching itself. It must be a vector where element i * contains the ID of the vertex that vertex i is matched to, * or -1 if vertex i is unmatched. * \param result Pointer to a boolean variable, the result will be returned * here. * * \sa \ref igraph_is_maximal_matching() if you are also interested in whether * the matching is maximal (i.e. non-extendable). * * Time complexity: O(|V|+|E|) where |V| is the number of vertices and * |E| is the number of edges. * * \example examples/simple/igraph_maximum_bipartite_matching.c */ int igraph_is_matching(const igraph_t* graph, const igraph_vector_bool_t* types, const igraph_vector_long_t* matching, igraph_bool_t* result) { long int i, j, no_of_nodes = igraph_vcount(graph); igraph_bool_t conn; /* Checking match vector length */ if (igraph_vector_long_size(matching) != no_of_nodes) { *result = 0; return IGRAPH_SUCCESS; } for (i = 0; i < no_of_nodes; i++) { j = VECTOR(*matching)[i]; /* Checking range of each element in the match vector */ if (j < -1 || j >= no_of_nodes) { *result = 0; return IGRAPH_SUCCESS; } /* When i is unmatched, we're done */ if (j == -1) { continue; } /* Matches must be mutual */ if (VECTOR(*matching)[j] != i) { *result = 0; return IGRAPH_SUCCESS; } /* Matched vertices must be connected */ IGRAPH_CHECK(igraph_are_connected(graph, (igraph_integer_t) i, (igraph_integer_t) j, &conn)); if (!conn) { /* Try the other direction -- for directed graphs */ IGRAPH_CHECK(igraph_are_connected(graph, (igraph_integer_t) j, (igraph_integer_t) i, &conn)); if (!conn) { *result = 0; return IGRAPH_SUCCESS; } } } if (types != 0) { /* Matched vertices must be of different types */ for (i = 0; i < no_of_nodes; i++) { j = VECTOR(*matching)[i]; if (j == -1) { continue; } if (VECTOR(*types)[i] == VECTOR(*types)[j]) { *result = 0; return IGRAPH_SUCCESS; } } } *result = 1; return IGRAPH_SUCCESS; } /** * \function igraph_is_maximal_matching * Checks whether a matching in a graph is maximal. * * A matching is maximal if and only if there exists no unmatched vertex in a * graph such that one of its neighbors is also unmatched. * * \param graph The input graph. It can be directed but the edge directions * will be ignored. * \param types If the graph is bipartite and you are interested in bipartite * matchings only, pass the vertex types here. If the graph is * non-bipartite, simply pass \c NULL. * \param matching The matching itself. It must be a vector where element i * contains the ID of the vertex that vertex i is matched to, * or -1 if vertex i is unmatched. * \param result Pointer to a boolean variable, the result will be returned * here. * * \sa \ref igraph_is_matching() if you are only interested in whether a * matching vector is valid for a given graph. * * Time complexity: O(|V|+|E|) where |V| is the number of vertices and * |E| is the number of edges. * * \example examples/simple/igraph_maximum_bipartite_matching.c */ int igraph_is_maximal_matching(const igraph_t* graph, const igraph_vector_bool_t* types, const igraph_vector_long_t* matching, igraph_bool_t* result) { long int i, j, n, no_of_nodes = igraph_vcount(graph); igraph_vector_t neis; igraph_bool_t valid; IGRAPH_CHECK(igraph_is_matching(graph, types, matching, &valid)); if (!valid) { *result = 0; return IGRAPH_SUCCESS; } IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); valid = 1; for (i = 0; i < no_of_nodes; i++) { j = VECTOR(*matching)[i]; if (j != -1) { continue; } IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) i, IGRAPH_ALL)); n = igraph_vector_size(&neis); for (j = 0; j < n; j++) { if (VECTOR(*matching)[(long int)VECTOR(neis)[j]] == -1) { if (types == 0 || VECTOR(*types)[i] != VECTOR(*types)[(long int)VECTOR(neis)[j]]) { valid = 0; break; } } } } igraph_vector_destroy(&neis); IGRAPH_FINALLY_CLEAN(1); *result = valid; return IGRAPH_SUCCESS; } int igraph_i_maximum_bipartite_matching_unweighted(const igraph_t* graph, const igraph_vector_bool_t* types, igraph_integer_t* matching_size, igraph_vector_long_t* matching); int igraph_i_maximum_bipartite_matching_weighted(const igraph_t* graph, const igraph_vector_bool_t* types, igraph_integer_t* matching_size, igraph_real_t* matching_weight, igraph_vector_long_t* matching, const igraph_vector_t* weights, igraph_real_t eps); #define MATCHED(v) (VECTOR(match)[v] != -1) #define UNMATCHED(v) (!MATCHED(v)) /** * \function igraph_maximum_bipartite_matching * Calculates a maximum matching in a bipartite graph. * * A matching in a bipartite graph is a partial assignment of vertices * of the first kind to vertices of the second kind such that each vertex of * the first kind is matched to at most one vertex of the second kind and * vice versa, and matched vertices must be connected by an edge in the graph. * The size (or cardinality) of a matching is the number of edges. * A matching is a maximum matching if there exists no other matching with * larger cardinality. For weighted graphs, a maximum matching is a matching * whose edges have the largest possible total weight among all possible * matchings. * * * Maximum matchings in bipartite graphs are found by the push-relabel algorithm * with greedy initialization and a global relabeling after every n/2 steps where * n is the number of vertices in the graph. * * * References: Cherkassky BV, Goldberg AV, Martin P, Setubal JC and Stolfi J: * Augment or push: A computational study of bipartite matching and * unit-capacity flow algorithms. ACM Journal of Experimental Algorithmics 3, * 1998. * * * Kaya K, Langguth J, Manne F and Ucar B: Experiments on push-relabel-based * maximum cardinality matching algorithms for bipartite graphs. Technical * Report TR/PA/11/33 of the Centre Europeen de Recherche et de Formation * Avancee en Calcul Scientifique, 2011. * * \param graph The input graph. It can be directed but the edge directions * will be ignored. * \param types Boolean vector giving the vertex types of the graph. * \param matching_size The size of the matching (i.e. the number of matched * vertex pairs will be returned here). It may be \c NULL * if you don't need this. * \param matching_weight The weight of the matching if the edges are weighted, * or the size of the matching again if the edges are * unweighted. It may be \c NULL if you don't need this. * \param matching The matching itself. It must be a vector where element i * contains the ID of the vertex that vertex i is matched to, * or -1 if vertex i is unmatched. * \param weights A null pointer (=no edge weights), or a vector giving the * weights of the edges. Note that the algorithm is stable * only for integer weights. * \param eps A small real number used in equality tests in the weighted * bipartite matching algorithm. Two real numbers are considered * equal in the algorithm if their difference is smaller than * \c eps. This is required to avoid the accumulation of numerical * errors. It is advised to pass a value derived from the * \c DBL_EPSILON constant in \c float.h here. If you are * running the algorithm with no \c weights vector, this argument * is ignored. * \return Error code. * * Time complexity: O(sqrt(|V|) |E|) for unweighted graphs (according to the * technical report referenced above), O(|V||E|) for weighted graphs. * * \example examples/simple/igraph_maximum_bipartite_matching.c */ int igraph_maximum_bipartite_matching(const igraph_t* graph, const igraph_vector_bool_t* types, igraph_integer_t* matching_size, igraph_real_t* matching_weight, igraph_vector_long_t* matching, const igraph_vector_t* weights, igraph_real_t eps) { /* Sanity checks */ if (igraph_vector_bool_size(types) < igraph_vcount(graph)) { IGRAPH_ERROR("types vector too short", IGRAPH_EINVAL); } if (weights && igraph_vector_size(weights) < igraph_ecount(graph)) { IGRAPH_ERROR("weights vector too short", IGRAPH_EINVAL); } if (weights == 0) { IGRAPH_CHECK(igraph_i_maximum_bipartite_matching_unweighted(graph, types, matching_size, matching)); if (matching_weight != 0) { *matching_weight = *matching_size; } return IGRAPH_SUCCESS; } else { IGRAPH_CHECK(igraph_i_maximum_bipartite_matching_weighted(graph, types, matching_size, matching_weight, matching, weights, eps)); return IGRAPH_SUCCESS; } } int igraph_i_maximum_bipartite_matching_unweighted_relabel(const igraph_t* graph, const igraph_vector_bool_t* types, igraph_vector_t* labels, igraph_vector_long_t* matching, igraph_bool_t smaller_set); /** * Finding maximum bipartite matchings on bipartite graphs using the * push-relabel algorithm. * * The implementation follows the pseudocode in Algorithm 1 of the * following paper: * * Kaya K, Langguth J, Manne F and Ucar B: Experiments on push-relabel-based * maximum cardinality matching algorithms for bipartite graphs. Technical * Report TR/PA/11/33 of CERFACS (Centre Européen de Recherche et de Formation * Avancée en Calcul Scientifique). * http://www.cerfacs.fr/algor/reports/2011/TR_PA_11_33.pdf */ int igraph_i_maximum_bipartite_matching_unweighted(const igraph_t* graph, const igraph_vector_bool_t* types, igraph_integer_t* matching_size, igraph_vector_long_t* matching) { long int i, j, k, n, no_of_nodes = igraph_vcount(graph); long int num_matched; /* number of matched vertex pairs */ igraph_vector_long_t match; /* will store the matching */ igraph_vector_t labels; /* will store the labels */ igraph_vector_t neis; /* used to retrieve the neighbors of a node */ igraph_dqueue_long_t q; /* a FIFO for push ordering */ igraph_bool_t smaller_set; /* denotes which part of the bipartite graph is smaller */ long int label_changed = 0; /* Counter to decide when to run a global relabeling */ long int relabeling_freq = no_of_nodes / 2; /* We will use: * - FIFO push ordering * - global relabeling frequency: n/2 steps where n is the number of nodes * - simple greedy matching for initialization */ /* (1) Initialize data structures */ IGRAPH_CHECK(igraph_vector_long_init(&match, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_long_destroy, &match); IGRAPH_VECTOR_INIT_FINALLY(&labels, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); IGRAPH_CHECK(igraph_dqueue_long_init(&q, 0)); IGRAPH_FINALLY(igraph_dqueue_long_destroy, &q); /* (2) Initially, every node is unmatched */ igraph_vector_long_fill(&match, -1); /* (3) Find an initial matching in a greedy manner. * At the same time, find which side of the graph is smaller. */ num_matched = 0; j = 0; for (i = 0; i < no_of_nodes; i++) { if (VECTOR(*types)[i]) { j++; } if (MATCHED(i)) { continue; } IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) i, IGRAPH_ALL)); n = igraph_vector_size(&neis); for (j = 0; j < n; j++) { k = (long int) VECTOR(neis)[j]; if (VECTOR(*types)[k] == VECTOR(*types)[i]) { IGRAPH_ERROR("Graph is not bipartite with supplied types vector", IGRAPH_EINVAL); } if (UNMATCHED(k)) { /* We match vertex i to vertex VECTOR(neis)[j] */ VECTOR(match)[k] = i; VECTOR(match)[i] = k; num_matched++; break; } } } smaller_set = (j <= no_of_nodes / 2); /* (4) Set the initial labeling -- lines 1 and 2 in the tech report */ IGRAPH_CHECK(igraph_i_maximum_bipartite_matching_unweighted_relabel( graph, types, &labels, &match, smaller_set)); /* (5) Fill the push queue with the unmatched nodes from the smaller set. */ for (i = 0; i < no_of_nodes; i++) { if (UNMATCHED(i) && VECTOR(*types)[i] == smaller_set) { IGRAPH_CHECK(igraph_dqueue_long_push(&q, i)); } } /* (6) Main loop from the referenced tech report -- lines 4--13 */ label_changed = 0; while (!igraph_dqueue_long_empty(&q)) { long int v = igraph_dqueue_long_pop(&q); /* Line 13 */ long int u = -1, label_u = 2 * no_of_nodes; long int w; if (label_changed >= relabeling_freq) { /* Run global relabeling */ IGRAPH_CHECK(igraph_i_maximum_bipartite_matching_unweighted_relabel( graph, types, &labels, &match, smaller_set)); label_changed = 0; } debug("Considering vertex %ld\n", v); /* Line 5: find row u among the neighbors of v s.t. label(u) is minimal */ IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) v, IGRAPH_ALL)); n = igraph_vector_size(&neis); for (i = 0; i < n; i++) { if (VECTOR(labels)[(long int)VECTOR(neis)[i]] < label_u) { u = (long int) VECTOR(neis)[i]; label_u = (long int) VECTOR(labels)[u]; label_changed++; } } debug(" Neighbor with smallest label: %ld (label=%ld)\n", u, label_u); if (label_u < no_of_nodes) { /* Line 6 */ VECTOR(labels)[v] = VECTOR(labels)[u] + 1; /* Line 7 */ if (MATCHED(u)) { /* Line 8 */ w = VECTOR(match)[u]; debug(" Vertex %ld is matched to %ld, performing a double push\n", u, w); if (w != v) { VECTOR(match)[u] = -1; VECTOR(match)[w] = -1; /* Line 9 */ IGRAPH_CHECK(igraph_dqueue_long_push(&q, w)); /* Line 10 */ debug(" Unmatching & activating vertex %ld\n", w); num_matched--; } } VECTOR(match)[u] = v; VECTOR(match)[v] = u; /* Line 11 */ num_matched++; VECTOR(labels)[u] += 2; /* Line 12 */ label_changed++; } } /* Fill the output parameters */ if (matching != 0) { IGRAPH_CHECK(igraph_vector_long_update(matching, &match)); } if (matching_size != 0) { *matching_size = (igraph_integer_t) num_matched; } /* Release everything */ igraph_dqueue_long_destroy(&q); igraph_vector_destroy(&neis); igraph_vector_destroy(&labels); igraph_vector_long_destroy(&match); IGRAPH_FINALLY_CLEAN(4); return IGRAPH_SUCCESS; } int igraph_i_maximum_bipartite_matching_unweighted_relabel(const igraph_t* graph, const igraph_vector_bool_t* types, igraph_vector_t* labels, igraph_vector_long_t* match, igraph_bool_t smaller_set) { long int i, j, n, no_of_nodes = igraph_vcount(graph), matched_to; igraph_dqueue_long_t q; igraph_vector_t neis; debug("Running global relabeling.\n"); /* Set all the labels to no_of_nodes first */ igraph_vector_fill(labels, no_of_nodes); /* Allocate vector for neighbors */ IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); /* Create a FIFO for the BFS and initialize it with the unmatched rows * (i.e. members of the larger set) */ IGRAPH_CHECK(igraph_dqueue_long_init(&q, 0)); IGRAPH_FINALLY(igraph_dqueue_long_destroy, &q); for (i = 0; i < no_of_nodes; i++) { if (VECTOR(*types)[i] != smaller_set && VECTOR(*match)[i] == -1) { IGRAPH_CHECK(igraph_dqueue_long_push(&q, i)); VECTOR(*labels)[i] = 0; } } /* Run the BFS */ while (!igraph_dqueue_long_empty(&q)) { long int v = igraph_dqueue_long_pop(&q); long int w; IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) v, IGRAPH_ALL)); n = igraph_vector_size(&neis); for (j = 0; j < n; j++) { w = (long int) VECTOR(neis)[j]; if (VECTOR(*labels)[w] == no_of_nodes) { VECTOR(*labels)[w] = VECTOR(*labels)[v] + 1; matched_to = VECTOR(*match)[w]; if (matched_to != -1 && VECTOR(*labels)[matched_to] == no_of_nodes) { IGRAPH_CHECK(igraph_dqueue_long_push(&q, matched_to)); VECTOR(*labels)[matched_to] = VECTOR(*labels)[w] + 1; } } } } igraph_dqueue_long_destroy(&q); igraph_vector_destroy(&neis); IGRAPH_FINALLY_CLEAN(2); return IGRAPH_SUCCESS; } /** * Finding maximum bipartite matchings on bipartite graphs using the * Hungarian algorithm (a.k.a. Kuhn-Munkres algorithm). * * The algorithm uses a maximum cardinality matching on a subset of * tight edges as a starting point. This is achieved by * \c igraph_i_maximum_bipartite_matching_unweighted on the restricted * graph. * * The algorithm works reliably only if the weights are integers. The * \c eps parameter should specity a very small number; if the slack on * an edge falls below \c eps, it will be considered tight. If all your * weights are integers, you can safely set \c eps to zero. */ int igraph_i_maximum_bipartite_matching_weighted(const igraph_t* graph, const igraph_vector_bool_t* types, igraph_integer_t* matching_size, igraph_real_t* matching_weight, igraph_vector_long_t* matching, const igraph_vector_t* weights, igraph_real_t eps) { long int i, j, k, n, no_of_nodes, no_of_edges; igraph_integer_t u, v, w, msize; igraph_t newgraph; igraph_vector_long_t match; /* will store the matching */ igraph_vector_t slack; /* will store the slack on each edge */ igraph_vector_t parent; /* parent vertices during a BFS */ igraph_vector_t vec1, vec2; /* general temporary vectors */ igraph_vector_t labels; /* will store the labels */ igraph_dqueue_long_t q; /* a FIFO for BST */ igraph_bool_t smaller_set_type; /* denotes which part of the bipartite graph is smaller */ igraph_vector_t smaller_set; /* stores the vertex IDs of the smaller set */ igraph_vector_t larger_set; /* stores the vertex IDs of the larger set */ long int smaller_set_size; /* size of the smaller set */ long int larger_set_size; /* size of the larger set */ igraph_real_t dual; /* solution of the dual problem */ igraph_adjlist_t tight_phantom_edges; /* adjacency list to manage tight phantom edges */ igraph_integer_t alternating_path_endpoint; igraph_vector_int_t* neis; igraph_vector_int_t *neis2; igraph_inclist_t inclist; /* incidence list of the original graph */ /* The Hungarian algorithm is originally for complete bipartite graphs. * For non-complete bipartite graphs, a phantom edge of weight zero must be * added between every pair of non-connected vertices. We don't do this * explicitly of course. See the comments below about how phantom edges * are taken into account. */ no_of_nodes = igraph_vcount(graph); no_of_edges = igraph_ecount(graph); if (eps < 0) { IGRAPH_WARNING("negative epsilon given, clamping to zero"); eps = 0; } /* (1) Initialize data structures */ IGRAPH_CHECK(igraph_vector_long_init(&match, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_long_destroy, &match); IGRAPH_CHECK(igraph_vector_init(&slack, no_of_edges)); IGRAPH_FINALLY(igraph_vector_destroy, &slack); IGRAPH_VECTOR_INIT_FINALLY(&vec1, 0); IGRAPH_VECTOR_INIT_FINALLY(&vec2, 0); IGRAPH_VECTOR_INIT_FINALLY(&labels, no_of_nodes); IGRAPH_CHECK(igraph_dqueue_long_init(&q, 0)); IGRAPH_FINALLY(igraph_dqueue_long_destroy, &q); IGRAPH_VECTOR_INIT_FINALLY(&parent, no_of_nodes); IGRAPH_CHECK(igraph_adjlist_init_empty(&tight_phantom_edges, (igraph_integer_t) no_of_nodes)); IGRAPH_FINALLY(igraph_adjlist_destroy, &tight_phantom_edges); IGRAPH_CHECK(igraph_inclist_init(graph, &inclist, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_inclist_destroy, &inclist); IGRAPH_VECTOR_INIT_FINALLY(&smaller_set, 0); IGRAPH_VECTOR_INIT_FINALLY(&larger_set, 0); /* (2) Find which set is the smaller one */ j = 0; for (i = 0; i < no_of_nodes; i++) { if (VECTOR(*types)[i] == 0) { j++; } } smaller_set_type = (j > no_of_nodes / 2); smaller_set_size = smaller_set_type ? (no_of_nodes - j) : j; larger_set_size = no_of_nodes - smaller_set_size; IGRAPH_CHECK(igraph_vector_reserve(&smaller_set, smaller_set_size)); IGRAPH_CHECK(igraph_vector_reserve(&larger_set, larger_set_size)); for (i = 0; i < no_of_nodes; i++) { if (VECTOR(*types)[i] == smaller_set_type) { IGRAPH_CHECK(igraph_vector_push_back(&smaller_set, i)); } else { IGRAPH_CHECK(igraph_vector_push_back(&larger_set, i)); } } /* (3) Calculate the initial labeling and the set of tight edges. Use the * smaller set only. Here we can assume that there are no phantom edges * among the tight ones. */ dual = 0; for (i = 0; i < no_of_nodes; i++) { igraph_real_t max_weight = 0; if (VECTOR(*types)[i] != smaller_set_type) { VECTOR(labels)[i] = 0; continue; } neis = igraph_inclist_get(&inclist, i); n = igraph_vector_int_size(neis); for (j = 0, k = 0; j < n; j++) { k = (long int) VECTOR(*neis)[j]; u = IGRAPH_OTHER(graph, k, i); if (VECTOR(*types)[u] == VECTOR(*types)[i]) { IGRAPH_ERROR("Graph is not bipartite with supplied types vector", IGRAPH_EINVAL); } if (VECTOR(*weights)[k] > max_weight) { max_weight = VECTOR(*weights)[k]; } } VECTOR(labels)[i] = max_weight; dual += max_weight; } igraph_vector_clear(&vec1); IGRAPH_CHECK(igraph_get_edgelist(graph, &vec2, 0)); #define IS_TIGHT(i) (VECTOR(slack)[i] <= eps) for (i = 0, j = 0; i < no_of_edges; i++, j += 2) { u = (igraph_integer_t) VECTOR(vec2)[j]; v = (igraph_integer_t) VECTOR(vec2)[j + 1]; VECTOR(slack)[i] = VECTOR(labels)[u] + VECTOR(labels)[v] - VECTOR(*weights)[i]; if (IS_TIGHT(i)) { IGRAPH_CHECK(igraph_vector_push_back(&vec1, u)); IGRAPH_CHECK(igraph_vector_push_back(&vec1, v)); } } igraph_vector_clear(&vec2); /* (4) Construct a temporary graph on which the initial maximum matching * will be calculated (only on the subset of tight edges) */ IGRAPH_CHECK(igraph_create(&newgraph, &vec1, (igraph_integer_t) no_of_nodes, 0)); IGRAPH_FINALLY(igraph_destroy, &newgraph); IGRAPH_CHECK(igraph_maximum_bipartite_matching(&newgraph, types, &msize, 0, &match, 0, 0)); igraph_destroy(&newgraph); IGRAPH_FINALLY_CLEAN(1); /* (5) Main loop until the matching becomes maximal */ while (msize < smaller_set_size) { igraph_real_t min_slack, min_slack_2; igraph_integer_t min_slack_u, min_slack_v; /* (7) Fill the push queue with the unmatched nodes from the smaller set. */ igraph_vector_clear(&vec1); igraph_vector_clear(&vec2); igraph_vector_fill(&parent, -1); for (j = 0; j < smaller_set_size; j++) { i = VECTOR(smaller_set)[j]; if (UNMATCHED(i)) { IGRAPH_CHECK(igraph_dqueue_long_push(&q, i)); VECTOR(parent)[i] = i; IGRAPH_CHECK(igraph_vector_push_back(&vec1, i)); } } #ifdef MATCHING_DEBUG debug("Matching:"); igraph_vector_long_print(&match); debug("Unmatched vertices are marked by non-negative numbers:\n"); igraph_vector_print(&parent); debug("Labeling:"); igraph_vector_print(&labels); debug("Slacks:"); igraph_vector_print(&slack); #endif /* (8) Run the BFS */ alternating_path_endpoint = -1; while (!igraph_dqueue_long_empty(&q)) { v = (int) igraph_dqueue_long_pop(&q); debug("Considering vertex %ld\n", (long int)v); /* v is always in the smaller set. Find the neighbors of v, which * are all in the larger set. Find the pairs of these nodes in * the smaller set and push them to the queue. Mark the traversed * nodes as seen. * * Here we have to be careful as there are two types of incident * edges on v: real edges and phantom ones. Real edges are * given by igraph_inclist_get. Phantom edges are not given so we * (ab)use an adjacency list data structure that lists the * vertices connected to v by phantom edges only. */ neis = igraph_inclist_get(&inclist, v); n = igraph_vector_int_size(neis); for (i = 0; i < n; i++) { j = (long int) VECTOR(*neis)[i]; /* We only care about tight edges */ if (!IS_TIGHT(j)) { continue; } /* Have we seen the other endpoint already? */ u = IGRAPH_OTHER(graph, j, v); if (VECTOR(parent)[u] >= 0) { continue; } debug(" Reached vertex %ld via edge %ld\n", (long)u, (long)j); VECTOR(parent)[u] = v; IGRAPH_CHECK(igraph_vector_push_back(&vec2, u)); w = (int) VECTOR(match)[u]; if (w == -1) { /* u is unmatched and it is in the larger set. Therefore, we * could improve the matching by following the parents back * from u to the root. */ alternating_path_endpoint = u; break; /* since we don't need any more endpoints that come from v */ } else { IGRAPH_CHECK(igraph_dqueue_long_push(&q, w)); VECTOR(parent)[w] = u; } IGRAPH_CHECK(igraph_vector_push_back(&vec1, w)); } /* Now do the same with the phantom edges */ neis2 = igraph_adjlist_get(&tight_phantom_edges, v); n = igraph_vector_int_size(neis2); for (i = 0; i < n; i++) { u = (igraph_integer_t) VECTOR(*neis2)[i]; /* Have we seen u already? */ if (VECTOR(parent)[u] >= 0) { continue; } /* Check if the edge is really tight; it might have happened that the * edge became non-tight in the meanwhile. We do not remove these from * tight_phantom_edges at the moment, so we check them once again here. */ if (fabs(VECTOR(labels)[(long int)v] + VECTOR(labels)[(long int)u]) > eps) { continue; } debug(" Reached vertex %ld via tight phantom edge\n", (long)u); VECTOR(parent)[u] = v; IGRAPH_CHECK(igraph_vector_push_back(&vec2, u)); w = (int) VECTOR(match)[u]; if (w == -1) { /* u is unmatched and it is in the larger set. Therefore, we * could improve the matching by following the parents back * from u to the root. */ alternating_path_endpoint = u; break; /* since we don't need any more endpoints that come from v */ } else { IGRAPH_CHECK(igraph_dqueue_long_push(&q, w)); VECTOR(parent)[w] = u; } IGRAPH_CHECK(igraph_vector_push_back(&vec1, w)); } } /* Okay; did we have an alternating path? */ if (alternating_path_endpoint != -1) { #ifdef MATCHING_DEBUG debug("BFS parent tree:"); igraph_vector_print(&parent); #endif /* Increase the size of the matching with the alternating path. */ v = alternating_path_endpoint; u = (igraph_integer_t) VECTOR(parent)[v]; debug("Extending matching with alternating path ending in %ld.\n", (long int)v); while (u != v) { w = (int) VECTOR(match)[v]; if (w != -1) { VECTOR(match)[w] = -1; } VECTOR(match)[v] = u; VECTOR(match)[v] = u; w = (int) VECTOR(match)[u]; if (w != -1) { VECTOR(match)[w] = -1; } VECTOR(match)[u] = v; v = (igraph_integer_t) VECTOR(parent)[u]; u = (igraph_integer_t) VECTOR(parent)[v]; } msize++; #ifdef MATCHING_DEBUG debug("New matching after update:"); igraph_vector_long_print(&match); debug("Matching size is now: %ld\n", (long)msize); #endif continue; } #ifdef MATCHING_DEBUG debug("Vertices reachable from unmatched ones via tight edges:\n"); igraph_vector_print(&vec1); igraph_vector_print(&vec2); #endif /* At this point, vec1 contains the nodes in the smaller set (A) * reachable from unmatched nodes in A via tight edges only, while vec2 * contains the nodes in the larger set (B) reachable from unmatched * nodes in A via tight edges only. Also, parent[i] >= 0 if node i * is reachable */ /* Check the edges between reachable nodes in A and unreachable * nodes in B, and find the minimum slack on them. * * Since the weights are positive, we do no harm if we first * assume that there are no "real" edges between the two sets * mentioned above and determine an upper bound for min_slack * based on this. */ min_slack = IGRAPH_INFINITY; min_slack_u = min_slack_v = 0; n = igraph_vector_size(&vec1); for (j = 0; j < larger_set_size; j++) { i = VECTOR(larger_set)[j]; if (VECTOR(labels)[i] < min_slack) { min_slack = VECTOR(labels)[i]; min_slack_v = (igraph_integer_t) i; } } min_slack_2 = IGRAPH_INFINITY; for (i = 0; i < n; i++) { u = (igraph_integer_t) VECTOR(vec1)[i]; /* u is surely from the smaller set, but we are interested in it * only if it is reachable from an unmatched vertex */ if (VECTOR(parent)[u] < 0) { continue; } if (VECTOR(labels)[u] < min_slack_2) { min_slack_2 = VECTOR(labels)[u]; min_slack_u = u; } } min_slack += min_slack_2; debug("Starting approximation for min_slack = %.4f (based on vertex pair %ld--%ld)\n", min_slack, (long int)min_slack_u, (long int)min_slack_v); n = igraph_vector_size(&vec1); for (i = 0; i < n; i++) { u = (igraph_integer_t) VECTOR(vec1)[i]; /* u is a reachable node in A; get its incident edges. * * There are two types of incident edges: 1) real edges, * 2) phantom edges. Phantom edges were treated earlier * when we determined the initial value for min_slack. */ debug("Trying to expand along vertex %ld\n", (long int)u); neis = igraph_inclist_get(&inclist, u); k = igraph_vector_int_size(neis); for (j = 0; j < k; j++) { /* v is the vertex sitting at the other end of an edge incident * on u; check whether it was reached */ v = IGRAPH_OTHER(graph, VECTOR(*neis)[j], u); debug(" Edge %ld -- %ld (ID=%ld)\n", (long int)u, (long int)v, (long int)VECTOR(*neis)[j]); if (VECTOR(parent)[v] >= 0) { /* v was reached, so we are not interested in it */ debug(" %ld was reached, so we are not interested in it\n", (long int)v); continue; } /* v is the ID of the edge from now on */ v = (igraph_integer_t) VECTOR(*neis)[j]; if (VECTOR(slack)[v] < min_slack) { min_slack = VECTOR(slack)[v]; min_slack_u = u; min_slack_v = IGRAPH_OTHER(graph, v, u); } debug(" Slack of this edge: %.4f, min slack is now: %.4f\n", VECTOR(slack)[v], min_slack); } } debug("Minimum slack: %.4f on edge %d--%d\n", min_slack, (int)min_slack_u, (int)min_slack_v); if (min_slack > 0) { /* Decrease the label of reachable nodes in A by min_slack. * Also update the dual solution */ n = igraph_vector_size(&vec1); for (i = 0; i < n; i++) { u = (igraph_integer_t) VECTOR(vec1)[i]; VECTOR(labels)[u] -= min_slack; neis = igraph_inclist_get(&inclist, u); k = igraph_vector_int_size(neis); for (j = 0; j < k; j++) { debug(" Decreasing slack of edge %ld (%ld--%ld) by %.4f\n", (long)VECTOR(*neis)[j], (long)u, (long)IGRAPH_OTHER(graph, VECTOR(*neis)[j], u), min_slack); VECTOR(slack)[(long int)VECTOR(*neis)[j]] -= min_slack; } dual -= min_slack; } /* Increase the label of reachable nodes in B by min_slack. * Also update the dual solution */ n = igraph_vector_size(&vec2); for (i = 0; i < n; i++) { u = (igraph_integer_t) VECTOR(vec2)[i]; VECTOR(labels)[u] += min_slack; neis = igraph_inclist_get(&inclist, u); k = igraph_vector_int_size(neis); for (j = 0; j < k; j++) { debug(" Increasing slack of edge %ld (%ld--%ld) by %.4f\n", (long)VECTOR(*neis)[j], (long)u, (long)IGRAPH_OTHER(graph, (long)VECTOR(*neis)[j], u), min_slack); VECTOR(slack)[(long int)VECTOR(*neis)[j]] += min_slack; } dual += min_slack; } } /* Update the set of tight phantom edges. * Note that we must do it even if min_slack is zero; the reason is that * it can happen that min_slack is zero in the first step if there are * isolated nodes in the input graph. * * TODO: this is O(n^2) here. Can we do it faster? */ for (i = 0; i < smaller_set_size; i++) { u = VECTOR(smaller_set)[i]; for (j = 0; j < larger_set_size; j++) { v = VECTOR(larger_set)[j]; if (VECTOR(labels)[(long int)u] + VECTOR(labels)[(long int)v] <= eps) { /* Tight phantom edge found. Note that we don't have to check whether * u and v are connected; if they were, then the slack of this edge * would be negative. */ neis2 = igraph_adjlist_get(&tight_phantom_edges, u); if (!igraph_vector_int_binsearch(neis2, v, &k)) { debug("New tight phantom edge: %ld -- %ld\n", (long)u, (long)v); IGRAPH_CHECK(igraph_vector_int_insert(neis2, k, v)); } } } } #ifdef MATCHING_DEBUG debug("New labels:"); igraph_vector_print(&labels); debug("Slacks after updating with min_slack:"); igraph_vector_print(&slack); #endif } /* Cleanup: remove phantom edges from the matching */ for (i = 0; i < smaller_set_size; i++) { u = VECTOR(smaller_set)[i]; v = VECTOR(match)[u]; if (v != -1) { neis2 = igraph_adjlist_get(&tight_phantom_edges, u); if (igraph_vector_int_binsearch(neis2, v, 0)) { VECTOR(match)[u] = VECTOR(match)[v] = -1; msize--; } } } /* Fill the output parameters */ if (matching != 0) { IGRAPH_CHECK(igraph_vector_long_update(matching, &match)); } if (matching_size != 0) { *matching_size = msize; } if (matching_weight != 0) { *matching_weight = 0; for (i = 0; i < no_of_edges; i++) { if (IS_TIGHT(i)) { IGRAPH_CHECK(igraph_edge(graph, (igraph_integer_t) i, &u, &v)); if (VECTOR(match)[u] == v) { *matching_weight += VECTOR(*weights)[i]; } } } } /* Release everything */ #undef IS_TIGHT igraph_vector_destroy(&larger_set); igraph_vector_destroy(&smaller_set); igraph_inclist_destroy(&inclist); igraph_adjlist_destroy(&tight_phantom_edges); igraph_vector_destroy(&parent); igraph_dqueue_long_destroy(&q); igraph_vector_destroy(&labels); igraph_vector_destroy(&vec1); igraph_vector_destroy(&vec2); igraph_vector_destroy(&slack); igraph_vector_long_destroy(&match); IGRAPH_FINALLY_CLEAN(11); return IGRAPH_SUCCESS; } int igraph_maximum_matching(const igraph_t* graph, igraph_integer_t* matching_size, igraph_real_t* matching_weight, igraph_vector_long_t* matching, const igraph_vector_t* weights) { IGRAPH_UNUSED(graph); IGRAPH_UNUSED(matching_size); IGRAPH_UNUSED(matching_weight); IGRAPH_UNUSED(matching); IGRAPH_UNUSED(weights); IGRAPH_ERROR("maximum matching on general graphs not implemented yet", IGRAPH_UNIMPLEMENTED); } #ifdef MATCHING_DEBUG #undef MATCHING_DEBUG #endif python-igraph-0.8.0/vendor/source/igraph/src/foreign-graphml.c0000644000076500000240000021135513614300625024632 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph R package. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include "igraph_foreign.h" #include "config.h" #include /* isnan */ #include "igraph_math.h" #include "igraph_attributes.h" #include "igraph_interface.h" #include "igraph_types_internal.h" #include /* isspace */ #include #include "igraph_memory.h" #include /* va_start & co */ #define GRAPHML_NAMESPACE_URI "http://graphml.graphdrawing.org/xmlns" #if HAVE_LIBXML == 1 #include #include xmlEntity blankEntityStruct = { #ifndef XML_WITHOUT_CORBA 0, #endif XML_ENTITY_DECL, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, XML_EXTERNAL_GENERAL_PARSED_ENTITY, 0, 0, 0, 0, 0, 1 }; xmlEntityPtr blankEntity = &blankEntityStruct; #define GRAPHML_PARSE_ERROR_WITH_CODE(state, msg, code) do { \ if (state->successful) { \ igraph_error(msg, __FILE__, __LINE__, code); \ igraph_i_graphml_sax_handler_error(state, msg); \ } \ } while (0) #define GRAPHML_PARSE_ERROR(state, msg) \ GRAPHML_PARSE_ERROR_WITH_CODE(state, msg, IGRAPH_PARSEERROR) #define RETURN_GRAPHML_PARSE_ERROR_WITH_CODE(state, msg, code) do { \ GRAPHML_PARSE_ERROR_WITH_CODE(state, msg, code); \ return; \ } while (1) #define RETURN_GRAPHML_PARSE_ERROR(state, msg) do { \ GRAPHML_PARSE_ERROR(state, msg); \ return; \ } while (1) /* TODO: proper error handling */ typedef struct igraph_i_graphml_attribute_record_t { const char *id; /* GraphML id */ enum { I_GRAPHML_BOOLEAN, I_GRAPHML_INTEGER, I_GRAPHML_LONG, I_GRAPHML_FLOAT, I_GRAPHML_DOUBLE, I_GRAPHML_STRING, I_GRAPHML_UNKNOWN_TYPE } type; /* GraphML type */ union { igraph_real_t as_numeric; igraph_bool_t as_boolean; char* as_string; } default_value; /* Default value of the attribute, if any */ igraph_attribute_record_t record; } igraph_i_graphml_attribute_record_t; struct igraph_i_graphml_parser_state { enum { START, INSIDE_GRAPHML, INSIDE_GRAPH, INSIDE_NODE, INSIDE_EDGE, INSIDE_KEY, INSIDE_DEFAULT, INSIDE_DATA, FINISH, UNKNOWN, ERROR } st; igraph_t *g; igraph_trie_t node_trie; igraph_strvector_t edgeids; igraph_vector_t edgelist; igraph_vector_int_t prev_state_stack; unsigned int unknown_depth; int index; igraph_bool_t successful, edges_directed, destroyed; igraph_trie_t v_names; igraph_vector_ptr_t v_attrs; igraph_trie_t e_names; igraph_vector_ptr_t e_attrs; igraph_trie_t g_names; igraph_vector_ptr_t g_attrs; igraph_i_graphml_attribute_record_t* current_attr_record; xmlChar *data_key; igraph_attribute_elemtype_t data_type; char *error_message; char *data_char; long int act_node; igraph_bool_t ignore_namespaces; }; static void igraph_i_report_unhandled_attribute_target(const char* target, const char* file, int line) { igraph_warningf("Attribute target '%s' is not handled; ignoring corresponding " "attribute specifications", file, line, 0, target); } igraph_real_t igraph_i_graphml_parse_numeric(const char* char_data, igraph_real_t default_value) { double result; if (char_data == 0) { return default_value; } if (sscanf(char_data, "%lf", &result) == 0) { return default_value; } return result; } igraph_bool_t igraph_i_graphml_parse_boolean(const char* char_data, igraph_bool_t default_value) { int value; if (char_data == 0) { return default_value; } if (!strcasecmp("true", char_data)) { return 1; } if (!strcasecmp("yes", char_data)) { return 1; } if (!strcasecmp("false", char_data)) { return 0; } if (!strcasecmp("no", char_data)) { return 0; } if (sscanf(char_data, "%d", &value) == 0) { return default_value; } return value != 0; } void igraph_i_graphml_attribute_record_destroy(igraph_i_graphml_attribute_record_t* rec) { if (rec->record.type == IGRAPH_ATTRIBUTE_NUMERIC) { if (rec->record.value != 0) { igraph_vector_destroy((igraph_vector_t*)rec->record.value); igraph_Free(rec->record.value); } } else if (rec->record.type == IGRAPH_ATTRIBUTE_STRING) { if (rec->record.value != 0) { igraph_strvector_destroy((igraph_strvector_t*)rec->record.value); if (rec->default_value.as_string != 0) { igraph_Free(rec->default_value.as_string); } igraph_Free(rec->record.value); } } else if (rec->record.type == IGRAPH_ATTRIBUTE_BOOLEAN) { if (rec->record.value != 0) { igraph_vector_bool_destroy((igraph_vector_bool_t*)rec->record.value); igraph_Free(rec->record.value); } } if (rec->id != 0) { igraph_Free(rec->id); } if (rec->record.name != 0) { igraph_Free(rec->record.name); } } void igraph_i_graphml_destroy_state(struct igraph_i_graphml_parser_state* state) { if (state->destroyed) { return; } state->destroyed = 1; igraph_trie_destroy(&state->node_trie); igraph_strvector_destroy(&state->edgeids); igraph_trie_destroy(&state->v_names); igraph_trie_destroy(&state->e_names); igraph_trie_destroy(&state->g_names); igraph_vector_destroy(&state->edgelist); igraph_vector_int_destroy(&state->prev_state_stack); if (state->error_message) { free(state->error_message); } if (state->data_key) { free(state->data_key); } if (state->data_char) { free(state->data_char); } igraph_vector_ptr_destroy_all(&state->v_attrs); igraph_vector_ptr_destroy_all(&state->e_attrs); igraph_vector_ptr_destroy_all(&state->g_attrs); IGRAPH_FINALLY_CLEAN(1); } void igraph_i_graphml_sax_handler_error(void *state0, const char* msg, ...) { struct igraph_i_graphml_parser_state *state = (struct igraph_i_graphml_parser_state*)state0; va_list ap; va_start(ap, msg); if (state->error_message == 0) { state->error_message = igraph_Calloc(4096, char); } state->successful = 0; state->st = ERROR; vsnprintf(state->error_message, 4096, msg, ap); va_end(ap); } xmlEntityPtr igraph_i_graphml_sax_handler_get_entity(void *state0, const xmlChar* name) { xmlEntityPtr predef = xmlGetPredefinedEntity(name); IGRAPH_UNUSED(state0); if (predef != NULL) { return predef; } IGRAPH_WARNING("unknown XML entity found\n"); return blankEntity; } void igraph_i_graphml_handle_unknown_start_tag(struct igraph_i_graphml_parser_state *state) { if (state->st != UNKNOWN) { igraph_vector_int_push_back(&state->prev_state_stack, state->st); state->st = UNKNOWN; state->unknown_depth = 1; } else { state->unknown_depth++; } } void igraph_i_graphml_sax_handler_start_document(void *state0) { struct igraph_i_graphml_parser_state *state = (struct igraph_i_graphml_parser_state*)state0; int ret; state->st = START; state->successful = 1; state->edges_directed = 0; state->destroyed = 0; state->data_key = 0; state->error_message = 0; state->data_char = 0; state->unknown_depth = 0; state->ignore_namespaces = 0; ret = igraph_vector_int_init(&state->prev_state_stack, 0); if (ret) { RETURN_GRAPHML_PARSE_ERROR_WITH_CODE(state, "Cannot parse GraphML file", ret); } ret = igraph_vector_int_reserve(&state->prev_state_stack, 32); if (ret) { RETURN_GRAPHML_PARSE_ERROR_WITH_CODE(state, "Cannot parse GraphML file", ret); } IGRAPH_FINALLY(igraph_vector_int_destroy, &state->prev_state_stack); ret = igraph_vector_ptr_init(&state->v_attrs, 0); if (ret) { RETURN_GRAPHML_PARSE_ERROR_WITH_CODE(state, "Cannot parse GraphML file", ret); } IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(&state->v_attrs, igraph_i_graphml_attribute_record_destroy); IGRAPH_FINALLY(igraph_vector_ptr_destroy, &state->v_attrs); ret = igraph_vector_ptr_init(&state->e_attrs, 0); if (ret) { RETURN_GRAPHML_PARSE_ERROR_WITH_CODE(state, "Cannot parse GraphML file", ret); } IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(&state->e_attrs, igraph_i_graphml_attribute_record_destroy); IGRAPH_FINALLY(igraph_vector_ptr_destroy, &state->e_attrs); ret = igraph_vector_ptr_init(&state->g_attrs, 0); if (ret) { RETURN_GRAPHML_PARSE_ERROR_WITH_CODE(state, "Cannot parse GraphML file", ret); } IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(&state->g_attrs, igraph_i_graphml_attribute_record_destroy); IGRAPH_FINALLY(igraph_vector_ptr_destroy, &state->g_attrs); ret = igraph_vector_init(&state->edgelist, 0); if (ret) { RETURN_GRAPHML_PARSE_ERROR_WITH_CODE(state, "Cannot parse GraphML file", ret); } IGRAPH_FINALLY(igraph_vector_destroy, &state->edgelist); ret = igraph_trie_init(&state->node_trie, 1); if (ret) { RETURN_GRAPHML_PARSE_ERROR_WITH_CODE(state, "Cannot parse GraphML file", ret); } IGRAPH_FINALLY(igraph_trie_destroy, &state->node_trie); ret = igraph_strvector_init(&state->edgeids, 0); if (ret) { RETURN_GRAPHML_PARSE_ERROR_WITH_CODE(state, "Cannot parse GraphML file", ret); } IGRAPH_FINALLY(igraph_strvector_destroy, &state->edgeids); ret = igraph_trie_init(&state->v_names, 0); if (ret) { RETURN_GRAPHML_PARSE_ERROR_WITH_CODE(state, "Cannot parse GraphML file", ret); } IGRAPH_FINALLY(igraph_trie_destroy, &state->v_names); ret = igraph_trie_init(&state->e_names, 0); if (ret) { RETURN_GRAPHML_PARSE_ERROR_WITH_CODE(state, "Cannot parse GraphML file", ret); } IGRAPH_FINALLY(igraph_trie_destroy, &state->e_names); ret = igraph_trie_init(&state->g_names, 0); if (ret) { RETURN_GRAPHML_PARSE_ERROR_WITH_CODE(state, "Cannot parse GraphML file", ret); } IGRAPH_FINALLY(igraph_trie_destroy, &state->g_names); IGRAPH_FINALLY_CLEAN(10); IGRAPH_FINALLY(igraph_i_graphml_destroy_state, state); } void igraph_i_graphml_sax_handler_end_document(void *state0) { struct igraph_i_graphml_parser_state *state = (struct igraph_i_graphml_parser_state*)state0; long i, l; int r; igraph_attribute_record_t idrec, eidrec; const char *idstr = "id"; igraph_bool_t already_has_vertex_id = 0, already_has_edge_id = 0; if (!state->successful) { return; } if (state->index < 0) { igraph_vector_ptr_t vattr, eattr, gattr; long int esize = igraph_vector_ptr_size(&state->e_attrs); const void **tmp; r = igraph_vector_ptr_init(&vattr, igraph_vector_ptr_size(&state->v_attrs) + 1); if (r) { igraph_error("Cannot parse GraphML file", __FILE__, __LINE__, r); igraph_i_graphml_sax_handler_error(state, "Cannot parse GraphML file"); return; } IGRAPH_FINALLY(igraph_vector_ptr_destroy, &vattr); if (igraph_strvector_size(&state->edgeids) != 0) { esize++; } r = igraph_vector_ptr_init(&eattr, esize); if (r) { igraph_error("Cannot parse GraphML file", __FILE__, __LINE__, r); igraph_i_graphml_sax_handler_error(state, "Cannot parse GraphML file"); return; } IGRAPH_FINALLY(igraph_vector_ptr_destroy, &eattr); r = igraph_vector_ptr_init(&gattr, igraph_vector_ptr_size(&state->g_attrs)); if (r) { igraph_error("Cannot parse GraphML file", __FILE__, __LINE__, r); igraph_i_graphml_sax_handler_error(state, "Cannot parse GraphML file"); return; } IGRAPH_FINALLY(igraph_vector_ptr_destroy, &gattr); for (i = 0; i < igraph_vector_ptr_size(&state->v_attrs); i++) { igraph_i_graphml_attribute_record_t *graphmlrec = VECTOR(state->v_attrs)[i]; igraph_attribute_record_t *rec = &graphmlrec->record; /* Check that the name of the vertex attribute is not 'id'. If it is then we cannot the complimentary 'id' attribute. */ if (! strcmp(rec->name, idstr)) { already_has_vertex_id = 1; } if (rec->type == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_vector_t *vec = (igraph_vector_t*)rec->value; long int origsize = igraph_vector_size(vec); long int nodes = igraph_trie_size(&state->node_trie); igraph_vector_resize(vec, nodes); for (l = origsize; l < nodes; l++) { VECTOR(*vec)[l] = graphmlrec->default_value.as_numeric; } } else if (rec->type == IGRAPH_ATTRIBUTE_STRING) { igraph_strvector_t *strvec = (igraph_strvector_t*)rec->value; long int origsize = igraph_strvector_size(strvec); long int nodes = igraph_trie_size(&state->node_trie); igraph_strvector_resize(strvec, nodes); for (l = origsize; l < nodes; l++) { igraph_strvector_set(strvec, l, graphmlrec->default_value.as_string); } } else if (rec->type == IGRAPH_ATTRIBUTE_BOOLEAN) { igraph_vector_bool_t *boolvec = (igraph_vector_bool_t*)rec->value; long int origsize = igraph_vector_bool_size(boolvec); long int nodes = igraph_trie_size(&state->node_trie); igraph_vector_bool_resize(boolvec, nodes); for (l = origsize; l < nodes; l++) { VECTOR(*boolvec)[l] = graphmlrec->default_value.as_boolean; } } VECTOR(vattr)[i] = rec; } if (!already_has_vertex_id) { idrec.name = idstr; idrec.type = IGRAPH_ATTRIBUTE_STRING; tmp = &idrec.value; igraph_trie_getkeys(&state->node_trie, (const igraph_strvector_t **)tmp); VECTOR(vattr)[i] = &idrec; } else { igraph_vector_ptr_pop_back(&vattr); } for (i = 0; i < igraph_vector_ptr_size(&state->e_attrs); i++) { igraph_i_graphml_attribute_record_t *graphmlrec = VECTOR(state->e_attrs)[i]; igraph_attribute_record_t *rec = &graphmlrec->record; if (! strcmp(rec->name, idstr)) { already_has_edge_id = 1; } if (rec->type == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_vector_t *vec = (igraph_vector_t*)rec->value; long int origsize = igraph_vector_size(vec); long int edges = igraph_vector_size(&state->edgelist) / 2; igraph_vector_resize(vec, edges); for (l = origsize; l < edges; l++) { VECTOR(*vec)[l] = graphmlrec->default_value.as_numeric; } } else if (rec->type == IGRAPH_ATTRIBUTE_STRING) { igraph_strvector_t *strvec = (igraph_strvector_t*)rec->value; long int origsize = igraph_strvector_size(strvec); long int edges = igraph_vector_size(&state->edgelist) / 2; igraph_strvector_resize(strvec, edges); for (l = origsize; l < edges; l++) { igraph_strvector_set(strvec, l, graphmlrec->default_value.as_string); } } else if (rec->type == IGRAPH_ATTRIBUTE_BOOLEAN) { igraph_vector_bool_t *boolvec = (igraph_vector_bool_t*)rec->value; long int origsize = igraph_vector_bool_size(boolvec); long int edges = igraph_vector_size(&state->edgelist) / 2; igraph_vector_bool_resize(boolvec, edges); for (l = origsize; l < edges; l++) { VECTOR(*boolvec)[l] = graphmlrec->default_value.as_boolean; } } VECTOR(eattr)[i] = rec; } if (igraph_strvector_size(&state->edgeids) != 0) { if (!already_has_edge_id) { long int origsize = igraph_strvector_size(&state->edgeids); eidrec.name = idstr; eidrec.type = IGRAPH_ATTRIBUTE_STRING; igraph_strvector_resize(&state->edgeids, igraph_vector_size(&state->edgelist) / 2); for (; origsize < igraph_strvector_size(&state->edgeids); origsize++) { igraph_strvector_set(&state->edgeids, origsize, ""); } eidrec.value = &state->edgeids; VECTOR(eattr)[(long int)igraph_vector_ptr_size(&eattr) - 1] = &eidrec; } else { igraph_vector_ptr_pop_back(&eattr); IGRAPH_WARNING("Could not add edge ids, " "there is already an 'id' edge attribute"); } } for (i = 0; i < igraph_vector_ptr_size(&state->g_attrs); i++) { igraph_i_graphml_attribute_record_t *graphmlrec = VECTOR(state->g_attrs)[i]; igraph_attribute_record_t *rec = &graphmlrec->record; if (rec->type == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_vector_t *vec = (igraph_vector_t*)rec->value; long int origsize = igraph_vector_size(vec); igraph_vector_resize(vec, 1); for (l = origsize; l < 1; l++) { VECTOR(*vec)[l] = graphmlrec->default_value.as_numeric; } } else if (rec->type == IGRAPH_ATTRIBUTE_STRING) { igraph_strvector_t *strvec = (igraph_strvector_t*)rec->value; long int origsize = igraph_strvector_size(strvec); igraph_strvector_resize(strvec, 1); for (l = origsize; l < 1; l++) { igraph_strvector_set(strvec, l, graphmlrec->default_value.as_string); } } else if (rec->type == IGRAPH_ATTRIBUTE_BOOLEAN) { igraph_vector_bool_t *boolvec = (igraph_vector_bool_t*)rec->value; long int origsize = igraph_vector_bool_size(boolvec); igraph_vector_bool_resize(boolvec, 1); for (l = origsize; l < 1; l++) { VECTOR(*boolvec)[l] = graphmlrec->default_value.as_boolean; } } VECTOR(gattr)[i] = rec; } igraph_empty_attrs(state->g, 0, state->edges_directed, &gattr); igraph_add_vertices(state->g, (igraph_integer_t) igraph_trie_size(&state->node_trie), &vattr); igraph_add_edges(state->g, &state->edgelist, &eattr); igraph_vector_ptr_destroy(&vattr); igraph_vector_ptr_destroy(&eattr); igraph_vector_ptr_destroy(&gattr); IGRAPH_FINALLY_CLEAN(3); } igraph_i_graphml_destroy_state(state); } #define toXmlChar(a) (BAD_CAST(a)) #define fromXmlChar(a) ((char *)(a)) /* not the most elegant way... */ #define XML_ATTR_LOCALNAME(it) (*(it)) #define XML_ATTR_PREFIX(it) (*(it+1)) #define XML_ATTR_URI(it) (*(it+2)) #define XML_ATTR_VALUE_START(it) (*(it+3)) #define XML_ATTR_VALUE_END(it) (*(it+4)) #define XML_ATTR_VALUE(it) *(it+3), (*(it+4))-(*(it+3)) igraph_i_graphml_attribute_record_t* igraph_i_graphml_add_attribute_key( const xmlChar** attrs, int nb_attrs, struct igraph_i_graphml_parser_state *state) { xmlChar **it; xmlChar *localname; igraph_trie_t *trie = 0; igraph_vector_ptr_t *ptrvector = 0; long int id; unsigned short int skip = 0; int i, ret; igraph_i_graphml_attribute_record_t *rec; if (!state->successful) { return 0; } rec = igraph_Calloc(1, igraph_i_graphml_attribute_record_t); if (rec == 0) { GRAPHML_PARSE_ERROR_WITH_CODE(state, "Cannot parse GraphML file", IGRAPH_ENOMEM); return 0; } IGRAPH_FINALLY(igraph_free, rec); rec->type = I_GRAPHML_UNKNOWN_TYPE; for (i = 0, it = (xmlChar**)attrs; i < nb_attrs; i++, it += 5) { if (XML_ATTR_URI(it) != 0 && !xmlStrEqual(toXmlChar(GRAPHML_NAMESPACE_URI), XML_ATTR_URI(it))) { continue; } localname = XML_ATTR_LOCALNAME(it); if (xmlStrEqual(localname, toXmlChar("id"))) { rec->id = fromXmlChar(xmlStrndup(XML_ATTR_VALUE(it))); } else if (xmlStrEqual(localname, toXmlChar("attr.name"))) { rec->record.name = fromXmlChar(xmlStrndup(XML_ATTR_VALUE(it))); } else if (xmlStrEqual(localname, toXmlChar("attr.type"))) { if (!xmlStrncmp(toXmlChar("boolean"), XML_ATTR_VALUE(it))) { rec->type = I_GRAPHML_BOOLEAN; rec->record.type = IGRAPH_ATTRIBUTE_BOOLEAN; rec->default_value.as_boolean = 0; } else if (!xmlStrncmp(toXmlChar("string"), XML_ATTR_VALUE(it))) { rec->type = I_GRAPHML_STRING; rec->record.type = IGRAPH_ATTRIBUTE_STRING; rec->default_value.as_string = strdup(""); } else if (!xmlStrncmp(toXmlChar("float"), XML_ATTR_VALUE(it))) { rec->type = I_GRAPHML_FLOAT; rec->record.type = IGRAPH_ATTRIBUTE_NUMERIC; rec->default_value.as_numeric = IGRAPH_NAN; } else if (!xmlStrncmp(toXmlChar("double"), XML_ATTR_VALUE(it))) { rec->type = I_GRAPHML_DOUBLE; rec->record.type = IGRAPH_ATTRIBUTE_NUMERIC; rec->default_value.as_numeric = IGRAPH_NAN; } else if (!xmlStrncmp(toXmlChar("int"), XML_ATTR_VALUE(it))) { rec->type = I_GRAPHML_INTEGER; rec->record.type = IGRAPH_ATTRIBUTE_NUMERIC; rec->default_value.as_numeric = IGRAPH_NAN; } else if (!xmlStrncmp(toXmlChar("long"), XML_ATTR_VALUE(it))) { rec->type = I_GRAPHML_LONG; rec->record.type = IGRAPH_ATTRIBUTE_NUMERIC; rec->default_value.as_numeric = IGRAPH_NAN; } else { GRAPHML_PARSE_ERROR(state, "Cannot parse GraphML file, unknown attribute type"); return 0; } } else if (xmlStrEqual(*it, toXmlChar("for"))) { /* graph, vertex or edge attribute? */ if (!xmlStrncmp(toXmlChar("graph"), XML_ATTR_VALUE(it))) { trie = &state->g_names; ptrvector = &state->g_attrs; } else if (!xmlStrncmp(toXmlChar("node"), XML_ATTR_VALUE(it))) { trie = &state->v_names; ptrvector = &state->v_attrs; } else if (!xmlStrncmp(toXmlChar("edge"), XML_ATTR_VALUE(it))) { trie = &state->e_names; ptrvector = &state->e_attrs; } else if (!xmlStrncmp(toXmlChar("graphml"), XML_ATTR_VALUE(it))) { igraph_i_report_unhandled_attribute_target("graphml", __FILE__, __LINE__); skip = 1; } else if (!xmlStrncmp(toXmlChar("hyperedge"), XML_ATTR_VALUE(it))) { igraph_i_report_unhandled_attribute_target("hyperedge", __FILE__, __LINE__); skip = 1; } else if (!xmlStrncmp(toXmlChar("port"), XML_ATTR_VALUE(it))) { igraph_i_report_unhandled_attribute_target("port", __FILE__, __LINE__); skip = 1; } else if (!xmlStrncmp(toXmlChar("endpoint"), XML_ATTR_VALUE(it))) { igraph_i_report_unhandled_attribute_target("endpoint", __FILE__, __LINE__); skip = 1; } else if (!xmlStrncmp(toXmlChar("all"), XML_ATTR_VALUE(it))) { /* TODO: we should handle this */ igraph_i_report_unhandled_attribute_target("all", __FILE__, __LINE__); skip = 1; } else { GRAPHML_PARSE_ERROR(state, "Cannot parse GraphML file, unknown value in the 'for' attribute of a tag"); return 0; } } } /* throw an error if there is no ID; this is a clear violation of the GraphML * DTD */ if (rec->id == 0) { GRAPHML_PARSE_ERROR(state, "Found tag with no 'id' attribute"); return 0; } /* in case of a missing attr.name attribute, use the id as the attribute name */ if (rec->record.name == 0) { rec->record.name = strdup(rec->id); } /* if the attribute type is missing, throw an error */ if (!skip && rec->type == I_GRAPHML_UNKNOWN_TYPE) { igraph_warningf("Ignoring because of a missing or unknown 'attr.type' attribute", __FILE__, __LINE__, 0, rec->id); skip = 1; } /* if the value of the 'for' attribute was unknown, throw an error */ if (!skip && trie == 0) { GRAPHML_PARSE_ERROR(state, "Cannot parse GraphML file, missing 'for' attribute in a tag"); return 0; } /* if the code above requested skipping the attribute, free everything and * return */ if (skip) { igraph_free(rec); IGRAPH_FINALLY_CLEAN(1); return 0; } /* add to trie, attribues */ igraph_trie_get(trie, rec->id, &id); if (id != igraph_trie_size(trie) - 1) { GRAPHML_PARSE_ERROR(state, "Cannot parse GraphML file, duplicate attribute"); return 0; } ret = igraph_vector_ptr_push_back(ptrvector, rec); if (ret) { GRAPHML_PARSE_ERROR_WITH_CODE(state, "Cannot read GraphML file", ret); return 0; } /* Ownership of 'rec' is now taken by ptrvector so we can clean the * finally stack */ IGRAPH_FINALLY_CLEAN(1); /* rec */ /* create the attribute values */ switch (rec->record.type) { igraph_vector_t *vec; igraph_vector_bool_t *boolvec; igraph_strvector_t *strvec; case IGRAPH_ATTRIBUTE_BOOLEAN: boolvec = igraph_Calloc(1, igraph_vector_bool_t); if (boolvec == 0) { GRAPHML_PARSE_ERROR_WITH_CODE(state, "Cannot parse GraphML file", IGRAPH_ENOMEM); return 0; } rec->record.value = boolvec; igraph_vector_bool_init(boolvec, 0); break; case IGRAPH_ATTRIBUTE_NUMERIC: vec = igraph_Calloc(1, igraph_vector_t); if (vec == 0) { GRAPHML_PARSE_ERROR_WITH_CODE(state, "Cannot parse GraphML file", IGRAPH_ENOMEM); return 0; } rec->record.value = vec; igraph_vector_init(vec, 0); break; case IGRAPH_ATTRIBUTE_STRING: strvec = igraph_Calloc(1, igraph_strvector_t); if (strvec == 0) { GRAPHML_PARSE_ERROR_WITH_CODE(state, "Cannot parse GraphML file", IGRAPH_ENOMEM); return 0; } rec->record.value = strvec; igraph_strvector_init(strvec, 0); break; default: break; } return rec; } void igraph_i_graphml_attribute_data_setup(struct igraph_i_graphml_parser_state *state, const xmlChar **attrs, int nb_attrs, igraph_attribute_elemtype_t type) { xmlChar **it; int i; if (!state->successful) { return; } for (i = 0, it = (xmlChar**)attrs; i < nb_attrs; i++, it += 5) { if (XML_ATTR_URI(it) != 0 && !xmlStrEqual(toXmlChar(GRAPHML_NAMESPACE_URI), XML_ATTR_URI(it))) { continue; } if (xmlStrEqual(*it, toXmlChar("key"))) { if (state->data_key) { free(state->data_key); } state->data_key = xmlStrndup(XML_ATTR_VALUE(it)); if (state->data_char) { free(state->data_char); } state->data_char = 0; state->data_type = type; } else { /* ignore */ } } } void igraph_i_graphml_append_to_data_char(struct igraph_i_graphml_parser_state *state, const xmlChar *data, int len) { long int data_char_new_start = 0; if (!state->successful) { return; } if (state->data_char) { data_char_new_start = (long int) strlen(state->data_char); state->data_char = igraph_Realloc(state->data_char, (size_t)(data_char_new_start + len + 1), char); } else { state->data_char = igraph_Calloc((size_t) len + 1, char); } if (state->data_char == 0) { RETURN_GRAPHML_PARSE_ERROR_WITH_CODE(state, "Cannot parse GraphML file", IGRAPH_ENOMEM); } memcpy(state->data_char + data_char_new_start, data, (size_t) len * sizeof(xmlChar)); state->data_char[data_char_new_start + len] = '\0'; } void igraph_i_graphml_attribute_data_finish(struct igraph_i_graphml_parser_state *state) { const char *key = fromXmlChar(state->data_key); igraph_attribute_elemtype_t type = state->data_type; igraph_trie_t *trie = 0; igraph_vector_ptr_t *ptrvector = 0; igraph_i_graphml_attribute_record_t *graphmlrec; igraph_attribute_record_t *rec; long int recid, id = 0; int ret; switch (type) { case IGRAPH_ATTRIBUTE_GRAPH: trie = &state->g_names; ptrvector = &state->g_attrs; id = 0; break; case IGRAPH_ATTRIBUTE_VERTEX: trie = &state->v_names; ptrvector = &state->v_attrs; id = state->act_node; break; case IGRAPH_ATTRIBUTE_EDGE: trie = &state->e_names; ptrvector = &state->e_attrs; id = igraph_vector_size(&state->edgelist) / 2 - 1; /* hack */ break; default: /* impossible */ break; } if (key == 0) { /* no key specified, issue a warning */ igraph_warningf( "missing attribute key in a tag, ignoring attribute", __FILE__, __LINE__, 0, key ); igraph_Free(state->data_char); return; } igraph_trie_check(trie, key, &recid); if (recid < 0) { /* no such attribute key, issue a warning */ igraph_warningf( "unknown attribute key '%s' in a tag, ignoring attribute", __FILE__, __LINE__, 0, key ); igraph_Free(state->data_char); return; } graphmlrec = VECTOR(*ptrvector)[recid]; rec = &graphmlrec->record; switch (rec->type) { igraph_vector_bool_t *boolvec; igraph_vector_t *vec; igraph_strvector_t *strvec; long int s, i; const char* strvalue; case IGRAPH_ATTRIBUTE_BOOLEAN: boolvec = (igraph_vector_bool_t *)rec->value; s = igraph_vector_bool_size(boolvec); if (id >= s) { ret = igraph_vector_bool_resize(boolvec, id + 1); if (ret) { RETURN_GRAPHML_PARSE_ERROR_WITH_CODE(state, "Cannot parse GraphML file", ret); } for (i = s; i < id; i++) { VECTOR(*boolvec)[i] = graphmlrec->default_value.as_boolean; } } VECTOR(*boolvec)[id] = igraph_i_graphml_parse_boolean(state->data_char, graphmlrec->default_value.as_boolean); break; case IGRAPH_ATTRIBUTE_NUMERIC: vec = (igraph_vector_t *)rec->value; s = igraph_vector_size(vec); if (id >= s) { ret = igraph_vector_resize(vec, id + 1); if (ret) { RETURN_GRAPHML_PARSE_ERROR_WITH_CODE(state, "Cannot parse GraphML file", ret); } for (i = s; i < id; i++) { VECTOR(*vec)[i] = graphmlrec->default_value.as_numeric; } } VECTOR(*vec)[id] = igraph_i_graphml_parse_numeric(state->data_char, graphmlrec->default_value.as_numeric); break; case IGRAPH_ATTRIBUTE_STRING: strvec = (igraph_strvector_t *)rec->value; s = igraph_strvector_size(strvec); if (id >= s) { ret = igraph_strvector_resize(strvec, id + 1); if (ret) { RETURN_GRAPHML_PARSE_ERROR_WITH_CODE(state, "Cannot parse GraphML file", ret); } strvalue = graphmlrec->default_value.as_string; for (i = s; i < id; i++) { igraph_strvector_set(strvec, i, strvalue); } } if (state->data_char) { strvalue = state->data_char; } else { strvalue = graphmlrec->default_value.as_string; } ret = igraph_strvector_set(strvec, id, strvalue); if (ret) { RETURN_GRAPHML_PARSE_ERROR_WITH_CODE(state, "Cannot parse GraphML file", ret); } break; default: break; } if (state->data_char) { igraph_Free(state->data_char); } } void igraph_i_graphml_attribute_default_value_finish( struct igraph_i_graphml_parser_state *state) { igraph_i_graphml_attribute_record_t *graphmlrec = state->current_attr_record; if (graphmlrec == 0) { igraph_warning("state->current_attr_record was null where it should have been " "non-null; this is probably a bug. Please notify the developers!", __FILE__, __LINE__, 0); return; } if (state->data_char == 0) { return; } switch (graphmlrec->record.type) { case IGRAPH_ATTRIBUTE_BOOLEAN: graphmlrec->default_value.as_boolean = igraph_i_graphml_parse_boolean( state->data_char, 0); break; case IGRAPH_ATTRIBUTE_NUMERIC: graphmlrec->default_value.as_numeric = igraph_i_graphml_parse_numeric( state->data_char, IGRAPH_NAN); break; case IGRAPH_ATTRIBUTE_STRING: if (state->data_char) { if (graphmlrec->default_value.as_string != 0) { free(graphmlrec->default_value.as_string); } graphmlrec->default_value.as_string = strdup(state->data_char); } break; default: break; } if (state->data_char) { igraph_Free(state->data_char); } } void igraph_i_graphml_sax_handler_start_element_ns( void *state0, const xmlChar* localname, const xmlChar* prefix, const xmlChar* uri, int nb_namespaces, const xmlChar** namespaces, int nb_attributes, int nb_defaulted, const xmlChar** attributes) { struct igraph_i_graphml_parser_state *state = (struct igraph_i_graphml_parser_state*)state0; xmlChar** it; char* attr_value; long int id1, id2; int i; igraph_bool_t tag_is_unknown = 0; if (!state->successful) { return; } if (uri) { if (!xmlStrEqual(toXmlChar(GRAPHML_NAMESPACE_URI), uri)) { /* Tag is in a different namespace, so treat it as an unknown start * tag irrespectively of our state */ tag_is_unknown = 1; } } else { /* No namespace URI. If we are in lenient mode, accept it and proceed * as if we are in the GraphML namespace to handle lots of naive * non-namespace-aware GraphML files floating out there. If we are not * in lenient mode _but_ we are in the START state, accept it as well * and see whether the root tag is (in which case we will * enter lenient mode). Otherwise, reject the tag */ if (!state->ignore_namespaces && state->st != START) { tag_is_unknown = 1; } } if (tag_is_unknown) { igraph_i_graphml_handle_unknown_start_tag(state); return; } switch (state->st) { case START: /* If we are in the START state and received a graphml tag, * change to INSIDE_GRAPHML state. Otherwise, change to UNKNOWN. */ if (xmlStrEqual(localname, toXmlChar("graphml"))) { if (uri == 0) { state->ignore_namespaces = 1; } state->st = INSIDE_GRAPHML; } else { igraph_i_graphml_handle_unknown_start_tag(state); } break; case INSIDE_GRAPHML: /* If we are in the INSIDE_GRAPHML state and received a graph tag, * change to INSIDE_GRAPH state if the state->index counter reached * zero (this is to handle multiple graphs in the same file). * Otherwise, change to UNKNOWN. */ if (xmlStrEqual(localname, toXmlChar("graph"))) { if (state->index == 0) { state->st = INSIDE_GRAPH; for (i = 0, it = (xmlChar**)attributes; i < nb_attributes; i++, it += 5) { if (XML_ATTR_URI(it) != 0 && !xmlStrEqual(toXmlChar(GRAPHML_NAMESPACE_URI), XML_ATTR_URI(it))) { /* Attribute is from a different namespace, so skip it */ continue; } if (xmlStrEqual(*it, toXmlChar("edgedefault"))) { if (!xmlStrncmp(toXmlChar("directed"), XML_ATTR_VALUE(it))) { state->edges_directed = 1; } else if (!xmlStrncmp(toXmlChar("undirected"), XML_ATTR_VALUE(it))) { state->edges_directed = 0; } } } } state->index--; } else if (xmlStrEqual(localname, toXmlChar("key"))) { state->current_attr_record = igraph_i_graphml_add_attribute_key(attributes, nb_attributes, state); state->st = INSIDE_KEY; } else { igraph_i_graphml_handle_unknown_start_tag(state); } break; case INSIDE_KEY: /* If we are in the INSIDE_KEY state, check for default tag */ if (xmlStrEqual(localname, toXmlChar("default"))) { state->st = INSIDE_DEFAULT; } else { igraph_i_graphml_handle_unknown_start_tag(state); } break; case INSIDE_DEFAULT: /* If we are in the INSIDE_DEFAULT state, every further tag will be unknown */ igraph_i_graphml_handle_unknown_start_tag(state); break; case INSIDE_GRAPH: /* If we are in the INSIDE_GRAPH state, check for node and edge tags */ if (xmlStrEqual(localname, toXmlChar("edge"))) { id1 = -1; id2 = -1; for (i = 0, it = (xmlChar**)attributes; i < nb_attributes; i++, it += 5) { if (XML_ATTR_URI(it) != 0 && !xmlStrEqual(toXmlChar(GRAPHML_NAMESPACE_URI), XML_ATTR_URI(it))) { /* Attribute is from a different namespace, so skip it */ continue; } if (xmlStrEqual(*it, toXmlChar("source"))) { attr_value = fromXmlChar(xmlStrndup(XML_ATTR_VALUE(it))); igraph_trie_get(&state->node_trie, attr_value, &id1); free(attr_value); } else if (xmlStrEqual(*it, toXmlChar("target"))) { attr_value = fromXmlChar(xmlStrndup(XML_ATTR_VALUE(it))); igraph_trie_get(&state->node_trie, attr_value, &id2); free(attr_value); } else if (xmlStrEqual(*it, toXmlChar("id"))) { long int edges = igraph_vector_size(&state->edgelist) / 2 + 1; long int origsize = igraph_strvector_size(&state->edgeids); attr_value = fromXmlChar(xmlStrndup(XML_ATTR_VALUE(it))); igraph_strvector_resize(&state->edgeids, edges); for (; origsize < edges - 1; origsize++) { igraph_strvector_set(&state->edgeids, origsize, ""); } igraph_strvector_set(&state->edgeids, edges - 1, attr_value); free(attr_value); } } if (id1 >= 0 && id2 >= 0) { igraph_vector_push_back(&state->edgelist, id1); igraph_vector_push_back(&state->edgelist, id2); } else { igraph_i_graphml_sax_handler_error(state, "Edge with missing source or target encountered"); return; } state->st = INSIDE_EDGE; } else if (xmlStrEqual(localname, toXmlChar("node"))) { id1 = -1; for (i = 0, it = (xmlChar**)attributes; i < nb_attributes; i++, it += 5) { if (XML_ATTR_URI(it) != 0 && !xmlStrEqual(toXmlChar(GRAPHML_NAMESPACE_URI), XML_ATTR_URI(it))) { /* Attribute is from a different namespace, so skip it */ continue; } if (xmlStrEqual(XML_ATTR_LOCALNAME(it), toXmlChar("id"))) { attr_value = fromXmlChar(xmlStrndup(XML_ATTR_VALUE(it))); igraph_trie_get(&state->node_trie, attr_value, &id1); free(attr_value); break; } } if (id1 >= 0) { state->act_node = id1; } else { state->act_node = -1; igraph_i_graphml_sax_handler_error(state, "Node with missing id encountered"); return; } state->st = INSIDE_NODE; } else if (xmlStrEqual(localname, toXmlChar("data"))) { igraph_i_graphml_attribute_data_setup(state, attributes, nb_attributes, IGRAPH_ATTRIBUTE_GRAPH); igraph_vector_int_push_back(&state->prev_state_stack, state->st); state->st = INSIDE_DATA; } else { igraph_i_graphml_handle_unknown_start_tag(state); } break; case INSIDE_NODE: if (xmlStrEqual(localname, toXmlChar("data"))) { igraph_i_graphml_attribute_data_setup(state, attributes, nb_attributes, IGRAPH_ATTRIBUTE_VERTEX); igraph_vector_int_push_back(&state->prev_state_stack, state->st); state->st = INSIDE_DATA; } break; case INSIDE_EDGE: if (xmlStrEqual(localname, toXmlChar("data"))) { igraph_i_graphml_attribute_data_setup(state, attributes, nb_attributes, IGRAPH_ATTRIBUTE_EDGE); igraph_vector_int_push_back(&state->prev_state_stack, state->st); state->st = INSIDE_DATA; } break; case INSIDE_DATA: /* We do not expect any new tags within a tag */ igraph_i_graphml_handle_unknown_start_tag(state); break; case UNKNOWN: igraph_i_graphml_handle_unknown_start_tag(state); break; default: break; } } void igraph_i_graphml_sax_handler_end_element_ns(void *state0, const xmlChar* localname, const xmlChar* prefix, const xmlChar* uri) { struct igraph_i_graphml_parser_state *state = (struct igraph_i_graphml_parser_state*)state0; if (!state->successful) { return; } IGRAPH_UNUSED(localname); IGRAPH_UNUSED(prefix); IGRAPH_UNUSED(uri); switch (state->st) { case INSIDE_GRAPHML: state->st = FINISH; break; case INSIDE_GRAPH: state->st = INSIDE_GRAPHML; break; case INSIDE_KEY: state->current_attr_record = 0; state->st = INSIDE_GRAPHML; break; case INSIDE_DEFAULT: igraph_i_graphml_attribute_default_value_finish(state); state->st = INSIDE_KEY; break; case INSIDE_NODE: state->st = INSIDE_GRAPH; break; case INSIDE_EDGE: state->st = INSIDE_GRAPH; break; case INSIDE_DATA: igraph_i_graphml_attribute_data_finish(state); state->st = igraph_vector_int_pop_back(&state->prev_state_stack); break; case UNKNOWN: state->unknown_depth--; if (!state->unknown_depth) { state->st = igraph_vector_int_pop_back(&state->prev_state_stack); } break; default: break; } } void igraph_i_graphml_sax_handler_chars(void* state0, const xmlChar* ch, int len) { struct igraph_i_graphml_parser_state *state = (struct igraph_i_graphml_parser_state*)state0; if (!state->successful) { return; } switch (state->st) { case INSIDE_KEY: break; case INSIDE_DATA: case INSIDE_DEFAULT: igraph_i_graphml_append_to_data_char(state, ch, len); break; default: /* just ignore it */ break; } } static xmlSAXHandler igraph_i_graphml_sax_handler = { /* internalSubset = */ 0, /* isStandalone = */ 0, /* hasInternalSubset = */ 0, /* hasExternalSubset = */ 0, /* resolveEntity = */ 0, /* getEntity = */ igraph_i_graphml_sax_handler_get_entity, /* entityDecl = */ 0, /* notationDecl = */ 0, /* attributeDecl = */ 0, /* elementDecl = */ 0, /* unparsedEntityDecl = */ 0, /* setDocumentLocator = */ 0, /* startDocument = */ igraph_i_graphml_sax_handler_start_document, /* endDocument = */ igraph_i_graphml_sax_handler_end_document, /* startElement = */ 0, /* endElement = */ 0, /* reference = */ 0, /* characters = */ igraph_i_graphml_sax_handler_chars, /* ignorableWhitespaceFunc = */ 0, /* processingInstruction = */ 0, /* comment = */ 0, /* warning = */ igraph_i_graphml_sax_handler_error, /* error = */ igraph_i_graphml_sax_handler_error, /* fatalError = */ igraph_i_graphml_sax_handler_error, /* getParameterEntity = */ 0, /* cdataBlock = */ 0, /* externalSubset = */ 0, /* initialized = */ XML_SAX2_MAGIC, /* _private = */ 0, /* startElementNs = */ igraph_i_graphml_sax_handler_start_element_ns, /* endElementNs = */ igraph_i_graphml_sax_handler_end_element_ns, /* serror = */ 0 }; #endif #define IS_FORBIDDEN_CONTROL_CHAR(x) ((x) < ' ' && (x) != '\t' && (x) != '\r' && (x) != '\n') int igraph_i_xml_escape(char* src, char** dest) { long int destlen = 0; char *s, *d; unsigned char ch; for (s = src; *s; s++, destlen++) { ch = (unsigned char)(*s); if (ch == '&') { destlen += 4; } else if (ch == '<') { destlen += 3; } else if (ch == '>') { destlen += 3; } else if (ch == '"') { destlen += 5; } else if (ch == '\'') { destlen += 5; } else if (IS_FORBIDDEN_CONTROL_CHAR(ch)) { char msg[4096]; snprintf(msg, 4096, "Forbidden control character 0x%02X found in igraph_i_xml_escape", ch); IGRAPH_ERROR(msg, IGRAPH_EINVAL); } } *dest = igraph_Calloc(destlen + 1, char); if (!*dest) { IGRAPH_ERROR("Not enough memory", IGRAPH_ENOMEM); } for (s = src, d = *dest; *s; s++, d++) { ch = (unsigned char)(*s); switch (ch) { case '&': strcpy(d, "&"); d += 4; break; case '<': strcpy(d, "<"); d += 3; break; case '>': strcpy(d, ">"); d += 3; break; case '"': strcpy(d, """); d += 5; break; case '\'': strcpy(d, "'"); d += 5; break; default: *d = ch; } } *d = 0; return 0; } /** * \ingroup loadsave * \function igraph_read_graph_graphml * \brief Reads a graph from a GraphML file. * * * GraphML is an XML-based file format for representing various types of * graphs. Currently only the most basic import functionality is implemented * in igraph: it can read GraphML files without nested graphs and hyperedges. * Attributes of the graph are loaded only if an attribute interface * is attached, ie. if you use igraph from R or Python. * * * Graph attribute names are taken from the \c attr.name attributes of the * \c key tags in the GraphML file. Since \c attr.name is not mandatory, * igraph will fall back to the \c id attribute of the \c key tag if * \c attr.name is missing. * * \param graph Pointer to an uninitialized graph object. * \param instream A stream, it should be readable. * \param index If the GraphML file contains more than one graph, the one * specified by this index will be loaded. Indices start from * zero, so supply zero here if your GraphML file contains only * a single graph. * * \return Error code: * \c IGRAPH_PARSEERROR: if there is a * problem reading the file, or the file is syntactically * incorrect. * \c IGRAPH_UNIMPLEMENTED: the GraphML functionality was disabled * at compile-time * * \example examples/simple/graphml.c */ int igraph_read_graph_graphml(igraph_t *graph, FILE *instream, int index) { #if HAVE_LIBXML == 1 xmlParserCtxtPtr ctxt; struct igraph_i_graphml_parser_state state; int res; char buffer[4096]; if (index < 0) { IGRAPH_ERROR("Graph index must be non-negative", IGRAPH_EINVAL); } xmlInitParser(); /* Create a progressive parser context */ state.g = graph; state.index = index < 0 ? 0 : index; res = (int) fread(buffer, 1, 4096, instream); ctxt = xmlCreatePushParserCtxt(&igraph_i_graphml_sax_handler, &state, buffer, res, NULL); /* ctxt=xmlCreateIOParserCtxt(&igraph_i_graphml_sax_handler, &state, */ /* igraph_i_libxml2_read_callback, */ /* igraph_i_libxml2_close_callback, */ /* instream, XML_CHAR_ENCODING_NONE); */ if (ctxt == NULL) { IGRAPH_ERROR("Can't create progressive parser context", IGRAPH_PARSEERROR); } /* Set parsing options */ if (xmlCtxtUseOptions(ctxt, XML_PARSE_NOENT | XML_PARSE_NOBLANKS | XML_PARSE_NONET | XML_PARSE_NSCLEAN | XML_PARSE_NOCDATA | XML_PARSE_HUGE )) { IGRAPH_ERROR("Cannot set options for the parser context", IGRAPH_EINVAL); } /* Parse the file */ while ((res = (int) fread(buffer, 1, 4096, instream)) > 0) { xmlParseChunk(ctxt, buffer, res, 0); if (!state.successful) { break; } } xmlParseChunk(ctxt, buffer, res, 1); /* Free the context */ xmlFreeParserCtxt(ctxt); if (!state.successful) { if (state.error_message != 0) { IGRAPH_ERROR(state.error_message, IGRAPH_PARSEERROR); } else { IGRAPH_ERROR("Malformed GraphML file", IGRAPH_PARSEERROR); } } if (state.index >= 0) { IGRAPH_ERROR("Graph index was too large", IGRAPH_EINVAL); } return 0; #else IGRAPH_ERROR("GraphML support is disabled", IGRAPH_UNIMPLEMENTED); #endif } /** * \ingroup loadsave * \function igraph_write_graph_graphml * \brief Writes the graph to a file in GraphML format * * * GraphML is an XML-based file format for representing various types of * graphs. See the GraphML Primer (http://graphml.graphdrawing.org/primer/graphml-primer.html) * for detailed format description. * * \param graph The graph to write. * \param outstream The stream object to write to, it should be * writable. * \param prefixattr Logical value, whether to put a prefix in front of the * attribute names to ensure uniqueness if the graph has vertex and * edge (or graph) attributes with the same name. * \return Error code: * \c IGRAPH_EFILE if there is an error * writing the file. * * Time complexity: O(|V|+|E|) otherwise. All * file operations are expected to have time complexity * O(1). * * \example examples/simple/graphml.c */ int igraph_write_graph_graphml(const igraph_t *graph, FILE *outstream, igraph_bool_t prefixattr) { int ret; igraph_integer_t l, vc; igraph_eit_t it; igraph_strvector_t gnames, vnames, enames; igraph_vector_t gtypes, vtypes, etypes; long int i; igraph_vector_t numv; igraph_strvector_t strv; igraph_vector_bool_t boolv; const char *gprefix = prefixattr ? "g_" : ""; const char *vprefix = prefixattr ? "v_" : ""; const char *eprefix = prefixattr ? "e_" : ""; /* set standard C locale lest we sometimes get commas instead of dots */ char *saved_locale = strdup(setlocale(LC_NUMERIC, NULL)); if (saved_locale == NULL) { IGRAPH_ERROR("Not enough memory", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, saved_locale); setlocale(LC_NUMERIC, "C"); ret = fprintf(outstream, "\n"); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } ret = fprintf(outstream, "\n", GRAPHML_NAMESPACE_URI); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } ret = fprintf(outstream, "\n"); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } /* dump the elements if any */ IGRAPH_VECTOR_INIT_FINALLY(&numv, 1); IGRAPH_STRVECTOR_INIT_FINALLY(&strv, 1); IGRAPH_VECTOR_BOOL_INIT_FINALLY(&boolv, 1); IGRAPH_STRVECTOR_INIT_FINALLY(&gnames, 0); IGRAPH_STRVECTOR_INIT_FINALLY(&vnames, 0); IGRAPH_STRVECTOR_INIT_FINALLY(&enames, 0); IGRAPH_VECTOR_INIT_FINALLY(>ypes, 0); IGRAPH_VECTOR_INIT_FINALLY(&vtypes, 0); IGRAPH_VECTOR_INIT_FINALLY(&etypes, 0); igraph_i_attribute_get_info(graph, &gnames, >ypes, &vnames, &vtypes, &enames, &etypes); /* graph attributes */ for (i = 0; i < igraph_vector_size(>ypes); i++) { char *name, *name_escaped; igraph_strvector_get(&gnames, i, &name); IGRAPH_CHECK(igraph_i_xml_escape(name, &name_escaped)); if (VECTOR(gtypes)[i] == IGRAPH_ATTRIBUTE_STRING) { ret = fprintf(outstream, " \n", gprefix, name_escaped, name_escaped); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } } else if (VECTOR(gtypes)[i] == IGRAPH_ATTRIBUTE_NUMERIC) { ret = fprintf(outstream, " \n", gprefix, name_escaped, name_escaped); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } } else if (VECTOR(gtypes)[i] == IGRAPH_ATTRIBUTE_BOOLEAN) { ret = fprintf(outstream, " \n", gprefix, name_escaped, name_escaped); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } } igraph_Free(name_escaped); } /* vertex attributes */ for (i = 0; i < igraph_vector_size(&vtypes); i++) { char *name, *name_escaped; igraph_strvector_get(&vnames, i, &name); IGRAPH_CHECK(igraph_i_xml_escape(name, &name_escaped)); if (VECTOR(vtypes)[i] == IGRAPH_ATTRIBUTE_STRING) { ret = fprintf(outstream, " \n", vprefix, name_escaped, name_escaped); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } } else if (VECTOR(vtypes)[i] == IGRAPH_ATTRIBUTE_NUMERIC) { ret = fprintf(outstream, " \n", vprefix, name_escaped, name_escaped); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } } else if (VECTOR(vtypes)[i] == IGRAPH_ATTRIBUTE_BOOLEAN) { ret = fprintf(outstream, " \n", vprefix, name_escaped, name_escaped); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } } igraph_Free(name_escaped); } /* edge attributes */ for (i = 0; i < igraph_vector_size(&etypes); i++) { char *name, *name_escaped; igraph_strvector_get(&enames, i, &name); IGRAPH_CHECK(igraph_i_xml_escape(name, &name_escaped)); if (VECTOR(etypes)[i] == IGRAPH_ATTRIBUTE_STRING) { ret = fprintf(outstream, " \n", eprefix, name_escaped, name_escaped); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } } else if (VECTOR(etypes)[i] == IGRAPH_ATTRIBUTE_NUMERIC) { ret = fprintf(outstream, " \n", eprefix, name_escaped, name_escaped); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } } else if (VECTOR(etypes)[i] == IGRAPH_ATTRIBUTE_BOOLEAN) { ret = fprintf(outstream, " \n", eprefix, name_escaped, name_escaped); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } } igraph_Free(name_escaped); } ret = fprintf(outstream, " \n", (igraph_is_directed(graph) ? "directed" : "undirected")); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } /* Write the graph atributes before anything else */ for (i = 0; i < igraph_vector_size(>ypes); i++) { char *name, *name_escaped; if (VECTOR(gtypes)[i] == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_strvector_get(&gnames, i, &name); IGRAPH_CHECK(igraph_i_attribute_get_numeric_graph_attr(graph, name, &numv)); if (!isnan(VECTOR(numv)[0])) { IGRAPH_CHECK(igraph_i_xml_escape(name, &name_escaped)); ret = fprintf(outstream, " ", gprefix, name_escaped); igraph_Free(name_escaped); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } ret = igraph_real_fprintf_precise(outstream, VECTOR(numv)[0]); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } ret = fprintf(outstream, "\n"); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } } } else if (VECTOR(gtypes)[i] == IGRAPH_ATTRIBUTE_STRING) { char *s, *s_escaped; igraph_strvector_get(&gnames, i, &name); IGRAPH_CHECK(igraph_i_xml_escape(name, &name_escaped)); ret = fprintf(outstream, " ", gprefix, name_escaped); igraph_Free(name_escaped); IGRAPH_CHECK(igraph_i_attribute_get_string_graph_attr(graph, name, &strv)); igraph_strvector_get(&strv, 0, &s); IGRAPH_CHECK(igraph_i_xml_escape(s, &s_escaped)); ret = fprintf(outstream, "%s", s_escaped); igraph_Free(s_escaped); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } ret = fprintf(outstream, "\n"); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } } else if (VECTOR(gtypes)[i] == IGRAPH_ATTRIBUTE_BOOLEAN) { igraph_strvector_get(&gnames, i, &name); IGRAPH_CHECK(igraph_i_attribute_get_bool_graph_attr(graph, name, &boolv)); IGRAPH_CHECK(igraph_i_xml_escape(name, &name_escaped)); ret = fprintf(outstream, " %s\n", gprefix, name_escaped, VECTOR(boolv)[0] ? "true" : "false"); igraph_Free(name_escaped); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } } } /* Let's dump the nodes first */ vc = igraph_vcount(graph); for (l = 0; l < vc; l++) { char *name, *name_escaped; ret = fprintf(outstream, " \n", (long)l); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } for (i = 0; i < igraph_vector_size(&vtypes); i++) { if (VECTOR(vtypes)[i] == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_strvector_get(&vnames, i, &name); IGRAPH_CHECK(igraph_i_attribute_get_numeric_vertex_attr(graph, name, igraph_vss_1(l), &numv)); if (!isnan(VECTOR(numv)[0])) { IGRAPH_CHECK(igraph_i_xml_escape(name, &name_escaped)); ret = fprintf(outstream, " ", vprefix, name_escaped); igraph_Free(name_escaped); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } ret = igraph_real_fprintf_precise(outstream, VECTOR(numv)[0]); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } ret = fprintf(outstream, "\n"); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } } } else if (VECTOR(vtypes)[i] == IGRAPH_ATTRIBUTE_STRING) { char *s, *s_escaped; igraph_strvector_get(&vnames, i, &name); IGRAPH_CHECK(igraph_i_xml_escape(name, &name_escaped)); ret = fprintf(outstream, " ", vprefix, name_escaped); igraph_Free(name_escaped); IGRAPH_CHECK(igraph_i_attribute_get_string_vertex_attr(graph, name, igraph_vss_1(l), &strv)); igraph_strvector_get(&strv, 0, &s); IGRAPH_CHECK(igraph_i_xml_escape(s, &s_escaped)); ret = fprintf(outstream, "%s", s_escaped); igraph_Free(s_escaped); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } ret = fprintf(outstream, "\n"); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } } else if (VECTOR(vtypes)[i] == IGRAPH_ATTRIBUTE_BOOLEAN) { igraph_strvector_get(&vnames, i, &name); IGRAPH_CHECK(igraph_i_attribute_get_bool_vertex_attr(graph, name, igraph_vss_1(l), &boolv)); IGRAPH_CHECK(igraph_i_xml_escape(name, &name_escaped)); ret = fprintf(outstream, " %s\n", vprefix, name_escaped, VECTOR(boolv)[0] ? "true" : "false"); igraph_Free(name_escaped); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } } } ret = fprintf(outstream, " \n"); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } } /* Now the edges */ IGRAPH_CHECK(igraph_eit_create(graph, igraph_ess_all(0), &it)); IGRAPH_FINALLY(igraph_eit_destroy, &it); while (!IGRAPH_EIT_END(it)) { igraph_integer_t from, to; char *name, *name_escaped; long int edge = IGRAPH_EIT_GET(it); igraph_edge(graph, (igraph_integer_t) edge, &from, &to); ret = fprintf(outstream, " \n", (long int)from, (long int)to); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } for (i = 0; i < igraph_vector_size(&etypes); i++) { if (VECTOR(etypes)[i] == IGRAPH_ATTRIBUTE_NUMERIC) { igraph_strvector_get(&enames, i, &name); IGRAPH_CHECK(igraph_i_attribute_get_numeric_edge_attr(graph, name, igraph_ess_1((igraph_integer_t) edge), &numv)); if (!isnan(VECTOR(numv)[0])) { IGRAPH_CHECK(igraph_i_xml_escape(name, &name_escaped)); ret = fprintf(outstream, " ", eprefix, name_escaped); igraph_Free(name_escaped); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } ret = igraph_real_fprintf_precise(outstream, VECTOR(numv)[0]); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } ret = fprintf(outstream, "\n"); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } } } else if (VECTOR(etypes)[i] == IGRAPH_ATTRIBUTE_STRING) { char *s, *s_escaped; igraph_strvector_get(&enames, i, &name); IGRAPH_CHECK(igraph_i_xml_escape(name, &name_escaped)); ret = fprintf(outstream, " ", eprefix, name_escaped); igraph_Free(name_escaped); IGRAPH_CHECK(igraph_i_attribute_get_string_edge_attr(graph, name, igraph_ess_1((igraph_integer_t) edge), &strv)); igraph_strvector_get(&strv, 0, &s); IGRAPH_CHECK(igraph_i_xml_escape(s, &s_escaped)); ret = fprintf(outstream, "%s", s_escaped); igraph_Free(s_escaped); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } ret = fprintf(outstream, "\n"); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } } else if (VECTOR(etypes)[i] == IGRAPH_ATTRIBUTE_BOOLEAN) { igraph_strvector_get(&enames, i, &name); IGRAPH_CHECK(igraph_i_attribute_get_bool_edge_attr(graph, name, igraph_ess_1((igraph_integer_t) edge), &boolv)); IGRAPH_CHECK(igraph_i_xml_escape(name, &name_escaped)); ret = fprintf(outstream, " %s\n", eprefix, name_escaped, VECTOR(boolv)[0] ? "true" : "false"); igraph_Free(name_escaped); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } } } ret = fprintf(outstream, " \n"); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } IGRAPH_EIT_NEXT(it); } igraph_eit_destroy(&it); IGRAPH_FINALLY_CLEAN(1); ret = fprintf(outstream, " \n"); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } fprintf(outstream, "\n"); if (ret < 0) { IGRAPH_ERROR("Write failed", IGRAPH_EFILE); } /* reset locale to whatever was before this function */ setlocale(LC_NUMERIC, saved_locale); igraph_free(saved_locale); igraph_strvector_destroy(&gnames); igraph_strvector_destroy(&vnames); igraph_strvector_destroy(&enames); igraph_vector_destroy(>ypes); igraph_vector_destroy(&vtypes); igraph_vector_destroy(&etypes); igraph_vector_destroy(&numv); igraph_strvector_destroy(&strv); igraph_vector_bool_destroy(&boolv); IGRAPH_FINALLY_CLEAN(10); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/igraph_stack.c0000644000076500000240000000417613614300625024211 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_types.h" #include "igraph_stack.h" #define BASE_IGRAPH_REAL #include "igraph_pmt.h" #include "stack.pmt" #include "igraph_pmt_off.h" #undef BASE_IGRAPH_REAL #define BASE_LONG #include "igraph_pmt.h" #include "stack.pmt" #include "igraph_pmt_off.h" #undef BASE_LONG #define BASE_INT #include "igraph_pmt.h" #include "stack.pmt" #include "igraph_pmt_off.h" #undef BASE_INT #define BASE_CHAR #include "igraph_pmt.h" #include "stack.pmt" #include "igraph_pmt_off.h" #undef BASE_CHAR #define BASE_BOOL #include "igraph_pmt.h" #include "stack.pmt" #include "igraph_pmt_off.h" #undef BASE_BOOL #define BASE_PTR #include "igraph_pmt.h" #include "stack.pmt" #include "igraph_pmt_off.h" #undef BASE_PTR /** * \ingroup stack * \brief Calls free() on all elements of a pointer stack. */ void igraph_stack_ptr_free_all (igraph_stack_ptr_t* v) { void **ptr; assert(v != 0); assert(v->stor_begin != 0); for (ptr = v->stor_begin; ptr < v->end; ptr++) { igraph_Free(*ptr); } } /** * \ingroup stack * \brief Calls free() on all elements and destroys the stack. */ void igraph_stack_ptr_destroy_all (igraph_stack_ptr_t* v) { assert(v != 0); assert(v->stor_begin != 0); igraph_stack_ptr_free_all(v); igraph_stack_ptr_destroy(v); } python-igraph-0.8.0/vendor/source/igraph/src/foreign-ncol-lexer.l0000644000076500000240000000602113524616145025260 0ustar tamasstaff00000000000000/* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ %{ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "config.h" #include #include "foreign-ncol-header.h" #include "foreign-ncol-parser.h" #define YY_EXTRA_TYPE igraph_i_ncol_parsedata_t* #define YY_USER_ACTION yylloc->first_line = yylineno; /* We assume that 'file' is 'stderr' here. */ #ifdef USING_R #define fprintf(file, msg, ...) (1) #endif #ifdef stdout # undef stdout #endif #define stdout 0 #define exit(code) igraph_error("Fatal error in DL parser", __FILE__, \ __LINE__, IGRAPH_PARSEERROR); %} %option noyywrap %option prefix="igraph_ncol_yy" %option outfile="lex.yy.c" %option nounput %option noinput %option nodefault %option reentrant %option bison-bridge %option bison-locations alnum [^ \t\n\r] %% /* ------------------------------------------------whitespace------*/ [ \t]* { } /* ---------------------------------------------------newline------*/ \n\r|\r\n|\n|\r { return NEWLINE; } /* ----------------------------------------------alphanumeric------*/ {alnum}+ { return ALNUM; } <> { if (yyextra->eof) { yyterminate(); } else { yyextra->eof=1; return NEWLINE; } } /* ---------------------------------------------anything else------*/ . { return ERROR; } %% python-igraph-0.8.0/vendor/source/igraph/src/SuiteSparse_config/0000755000076500000240000000000013617375001025175 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/src/SuiteSparse_config/SuiteSparse_config.c0000644000076500000240000001354513524616144031150 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === SuiteSparse_config =================================================== */ /* ========================================================================== */ /* Copyright (c) 2012, Timothy A. Davis. No licensing restrictions * apply to this file or to the SuiteSparse_config directory. * Author: Timothy A. Davis. */ #include "SuiteSparse_config.h" /* -------------------------------------------------------------------------- */ /* SuiteSparse_malloc: malloc wrapper */ /* -------------------------------------------------------------------------- */ void *SuiteSparse_malloc /* pointer to allocated block of memory */ ( size_t nitems, /* number of items to malloc (>=1 is enforced) */ size_t size_of_item, /* sizeof each item */ int *ok, /* TRUE if successful, FALSE otherwise */ SuiteSparse_config *config /* SuiteSparse-wide configuration */ ) { void *p ; if (nitems < 1) nitems = 1 ; if (nitems * size_of_item != ((double) nitems) * size_of_item) { /* Int overflow */ *ok = 0 ; return (NULL) ; } if (!config || config->malloc_memory == NULL) { /* use malloc by default */ p = (void *) malloc (nitems * size_of_item) ; } else { /* use the pointer to malloc in the config */ p = (void *) (config->malloc_memory) (nitems * size_of_item) ; } *ok = (p != NULL) ; return (p) ; } /* -------------------------------------------------------------------------- */ /* SuiteSparse_free: free wrapper */ /* -------------------------------------------------------------------------- */ void *SuiteSparse_free /* always returns NULL */ ( void *p, /* block to free */ SuiteSparse_config *config /* SuiteSparse-wide configuration */ ) { if (p) { if (!config || config->free_memory == NULL) { /* use free by default */ free (p) ; } else { /* use the pointer to free in the config */ (config->free_memory) (p) ; } } return (NULL) ; } /* -------------------------------------------------------------------------- */ /* SuiteSparse_tic: return current wall clock time */ /* -------------------------------------------------------------------------- */ /* Returns the number of seconds (tic [0]) and nanoseconds (tic [1]) since some * unspecified but fixed time in the past. If no timer is installed, zero is * returned. A scalar double precision value for 'tic' could be used, but this * might cause loss of precision because clock_getttime returns the time from * some distant time in the past. Thus, an array of size 2 is used. * * The timer is enabled by default. To disable the timer, compile with * -DNTIMER. If enabled on a POSIX C 1993 system, the timer requires linking * with the -lrt library. * * example: * * double tic [2], r, s, t ; * SuiteSparse_tic (tic) ; // start the timer * // do some work A * t = SuiteSparse_toc (tic) ; // t is time for work A, in seconds * // do some work B * s = SuiteSparse_toc (tic) ; // s is time for work A and B, in seconds * SuiteSparse_tic (tic) ; // restart the timer * // do some work C * r = SuiteSparse_toc (tic) ; // s is time for work C, in seconds * * A double array of size 2 is used so that this routine can be more easily * ported to non-POSIX systems. The caller does not rely on the POSIX * include file. */ #ifdef SUITESPARSE_TIMER_ENABLED #include void SuiteSparse_tic ( double tic [2] /* output, contents undefined on input */ ) { /* POSIX C 1993 timer, requires -librt */ struct timespec t ; clock_gettime (CLOCK_MONOTONIC, &t) ; tic [0] = (double) (t.tv_sec) ; tic [1] = (double) (t.tv_nsec) ; } #else void SuiteSparse_tic ( double tic [2] /* output, contents undefined on input */ ) { /* no timer installed */ tic [0] = 0 ; tic [1] = 0 ; } #endif /* -------------------------------------------------------------------------- */ /* SuiteSparse_toc: return time since last tic */ /* -------------------------------------------------------------------------- */ /* Assuming SuiteSparse_tic is accurate to the nanosecond, this function is * accurate down to the nanosecond for 2^53 nanoseconds since the last call to * SuiteSparse_tic, which is sufficient for SuiteSparse (about 104 days). If * additional accuracy is required, the caller can use two calls to * SuiteSparse_tic and do the calculations differently. */ double SuiteSparse_toc /* returns time in seconds since last tic */ ( double tic [2] /* input, not modified from last call to SuiteSparse_tic */ ) { double toc [2] ; SuiteSparse_tic (toc) ; return ((toc [0] - tic [0]) + 1e-9 * (toc [1] - tic [1])) ; } /* -------------------------------------------------------------------------- */ /* SuiteSparse_time: return current wallclock time in seconds */ /* -------------------------------------------------------------------------- */ /* This function might not be accurate down to the nanosecond. */ double SuiteSparse_time /* returns current wall clock time in seconds */ ( void ) { double toc [2] ; SuiteSparse_tic (toc) ; return (toc [0] + 1e-9 * toc [1]) ; } /* -------------------------------------------------------------------------- */ /* SuiteSparse_version: return the current version of SuiteSparse */ /* -------------------------------------------------------------------------- */ int SuiteSparse_version ( int version [3] ) { if (version != NULL) { version [0] = SUITESPARSE_MAIN_VERSION ; version [1] = SUITESPARSE_SUB_VERSION ; version [2] = SUITESPARSE_SUBSUB_VERSION ; } return (SUITESPARSE_VERSION) ; } python-igraph-0.8.0/vendor/source/igraph/src/SuiteSparse_config/Makefile0000644000076500000240000000216713524616144026646 0ustar tamasstaff00000000000000#------------------------------------------------------------------------------- # SuiteSparse_config Makefile #------------------------------------------------------------------------------- VERSION = 4.2.1 default: ccode include SuiteSparse_config.mk ccode: libsuitesparseconfig.a all: libsuitesparseconfig.a library: libsuitesparseconfig.a libsuitesparseconfig.a: SuiteSparse_config.c SuiteSparse_config.h $(CC) $(CF) -c SuiteSparse_config.c $(ARCHIVE) libsuitesparseconfig.a SuiteSparse_config.o $(RANLIB) libsuitesparseconfig.a - $(RM) SuiteSparse_config.o distclean: purge purge: clean - $(RM) *.o *.a clean: - $(RM) -r $(CLEAN) # install SuiteSparse_config install: $(CP) libsuitesparseconfig.a $(INSTALL_LIB)/libsuitesparseconfig.$(VERSION).a ( cd $(INSTALL_LIB) ; ln -sf libsuitesparseconfig.$(VERSION).a libsuitesparseconfig.a ) $(CP) SuiteSparse_config.h $(INSTALL_INCLUDE) chmod 644 $(INSTALL_LIB)/libsuitesparseconfig*.a chmod 644 $(INSTALL_INCLUDE)/SuiteSparse_config.h # uninstall SuiteSparse_config uninstall: $(RM) $(INSTALL_LIB)/libsuitesparseconfig*.a $(RM) $(INSTALL_INCLUDE)/SuiteSparse_config.h python-igraph-0.8.0/vendor/source/igraph/src/SuiteSparse_config/SuiteSparse_config.mk0000644000076500000240000003467313524616144031342 0ustar tamasstaff00000000000000#=============================================================================== # SuiteSparse_config.mk: common configuration file for the SuiteSparse #=============================================================================== # This file contains all configuration settings for all packages authored or # co-authored by Tim Davis: # # Package Version Description # ------- ------- ----------- # AMD 1.2 or later approximate minimum degree ordering # COLAMD 2.4 or later column approximate minimum degree ordering # CCOLAMD 1.0 or later constrained column approximate minimum degree ordering # CAMD any constrained approximate minimum degree ordering # UMFPACK 4.5 or later sparse LU factorization, with the BLAS # CHOLMOD any sparse Cholesky factorization, update/downdate # KLU 0.8 or later sparse LU factorization, BLAS-free # BTF 0.8 or later permutation to block triangular form # LDL 1.2 or later concise sparse LDL' # CXSparse any extended version of CSparse (int/long, real/complex) # SuiteSparseQR any sparse QR factorization # RBio 2.0 or later read/write sparse matrices in Rutherford-Boeing format # # By design, this file is NOT included in the CSparse makefile. # That package is fully stand-alone. CSparse is primarily for teaching; # production code should use CXSparse. # # The SuiteSparse_config directory and the above packages should all appear in # a single directory, in order for the Makefile's within each package to find # this file. # # To enable an option of the form "# OPTION = ...", edit this file and # delete the "#" in the first column of the option you wish to use. # # The use of METIS 4.0.1 is optional. To exclude METIS, you must compile with # CHOLMOD_CONFIG set to -DNPARTITION. See below for details. However, if you # do not have a metis-4.0 directory inside the SuiteSparse directory, the # */Makefile's that optionally rely on METIS will automatically detect this # and compile without METIS. #------------------------------------------------------------------------------ # Generic configuration #------------------------------------------------------------------------------ # Using standard definitions from the make environment, typically: # # CC cc C compiler # CXX g++ C++ compiler # CFLAGS [ ] flags for C and C++ compiler # CPPFLAGS [ ] flags for C and C++ compiler # TARGET_ARCH [ ] target architecture # FFLAGS [ ] flags for Fortran compiler # RM rm -f delete a file # AR ar create a static *.a library archive # ARFLAGS rv flags for ar # MAKE make make itself (sometimes called gmake) # # You can redefine them here, but by default they are used from the # default make environment. # C and C++ compiler flags. The first three are standard for *.c and *.cpp # Add -DNTIMER if you do use any timing routines (otherwise -lrt is required). # CF = $(CFLAGS) $(CPPFLAGS) $(TARGET_ARCH) -O3 -fexceptions -fPIC -DNTIMER CF = $(CFLAGS) $(CPPFLAGS) $(TARGET_ARCH) -O3 -fexceptions -fPIC # ranlib, and ar, for generating libraries. If you don't need ranlib, # just change it to RANLAB = echo RANLIB = ranlib ARCHIVE = $(AR) $(ARFLAGS) # copy and delete a file CP = cp -f MV = mv -f # Fortran compiler (not required for 'make' or 'make library') F77 = gfortran F77FLAGS = $(FFLAGS) -O F77LIB = # C and Fortran libraries. Remove -lrt if you don't have it. LIB = -lm -lrt # Using the following requires CF = ... -DNTIMER on POSIX C systems. # LIB = -lm # For "make install" INSTALL_LIB = /usr/local/lib INSTALL_INCLUDE = /usr/local/include # Which version of MAKE you are using (default is "make") # MAKE = make # MAKE = gmake #------------------------------------------------------------------------------ # BLAS and LAPACK configuration: #------------------------------------------------------------------------------ # UMFPACK and CHOLMOD both require the BLAS. CHOLMOD also requires LAPACK. # See Kazushige Goto's BLAS at http://www.cs.utexas.edu/users/flame/goto/ or # http://www.tacc.utexas.edu/~kgoto/ for the best BLAS to use with CHOLMOD. # LAPACK is at http://www.netlib.org/lapack/ . You can use the standard # Fortran LAPACK along with Goto's BLAS to obtain very good performance. # CHOLMOD gets a peak numeric factorization rate of 3.6 Gflops on a 3.2 GHz # Pentium 4 (512K cache, 4GB main memory) with the Goto BLAS, and 6 Gflops # on a 2.5Ghz dual-core AMD Opteron. # These settings will probably not work, since there is no fixed convention for # naming the BLAS and LAPACK library (*.a or *.so) files. # This is probably slow ... it might connect to the Standard Reference BLAS: BLAS = -lblas -lgfortran LAPACK = -llapack # NOTE: this next option for the "Goto BLAS" has nothing to do with a "goto" # statement. Rather, the Goto BLAS is written by Dr. Kazushige Goto. # Using the Goto BLAS: # BLAS = -lgoto -lgfortran -lgfortranbegin # BLAS = -lgoto2 -lgfortran -lgfortranbegin -lpthread # Using non-optimized versions: # BLAS = -lblas_plain -lgfortran -lgfortranbegin # LAPACK = -llapack_plain # BLAS = -lblas_plain -lgfortran -lgfortranbegin # LAPACK = -llapack # The BLAS might not contain xerbla, an error-handling routine for LAPACK and # the BLAS. Also, the standard xerbla requires the Fortran I/O library, and # stops the application program if an error occurs. A C version of xerbla # distributed with this software (SuiteSparse_config/xerbla/libcerbla.a) # includes a Fortran-callable xerbla routine that prints nothing and does not # stop the application program. This is optional. # XERBLA = ../../SuiteSparse_config/xerbla/libcerbla.a # If you wish to use the XERBLA in LAPACK and/or the BLAS instead, # use this option: XERBLA = # If you wish to use the Fortran SuiteSparse_config/xerbla/xerbla.f instead, # use this: # XERBLA = ../../SuiteSparse_config/xerbla/libxerbla.a #------------------------------------------------------------------------------ # GPU configuration for CHOLMOD, using the CUDA BLAS #------------------------------------------------------------------------------ # no cuda GPU_BLAS_PATH = GPU_CONFIG = # with cuda BLAS acceleration for CHOLMOD # GPU_BLAS_PATH=/usr/local/cuda # GPU_CONFIG=-DGPU_BLAS -I$(GPU_BLAS_PATH)/include #------------------------------------------------------------------------------ # METIS, optionally used by CHOLMOD #------------------------------------------------------------------------------ # If you do not have METIS, or do not wish to use it in CHOLMOD, you must # compile CHOLMOD with the -DNPARTITION flag. # The path is relative to where it is used, in CHOLMOD/Lib, CHOLMOD/MATLAB, etc. # You may wish to use an absolute path. METIS is optional. Compile # CHOLMOD with -DNPARTITION if you do not wish to use METIS. METIS_PATH = ../../metis-4.0 METIS = ../../metis-4.0/libmetis.a #------------------------------------------------------------------------------ # UMFPACK configuration: #------------------------------------------------------------------------------ # Configuration flags for UMFPACK. See UMFPACK/Source/umf_config.h for details. # # -DNBLAS do not use the BLAS. UMFPACK will be very slow. # -D'LONGBLAS=long' or -DLONGBLAS='long long' defines the integers used by # LAPACK and the BLAS (defaults to 'int') # -DNSUNPERF do not use the Sun Perf. Library (default is use it on Solaris) # -DNRECIPROCAL do not multiply by the reciprocal # -DNO_DIVIDE_BY_ZERO do not divide by zero # -DNCHOLMOD do not use CHOLMOD as a ordering method. If -DNCHOLMOD is # included in UMFPACK_CONFIG, then UMFPACK does not rely on # CHOLMOD, CAMD, CCOLAMD, COLAMD, and METIS. UMFPACK_CONFIG = # uncomment this line to compile UMFPACK without CHOLMOD: # UMFPACK_CONFIG = -DNCHOLMOD #------------------------------------------------------------------------------ # CHOLMOD configuration #------------------------------------------------------------------------------ # CHOLMOD Library Modules, which appear in libcholmod.a: # Core requires: none # Check requires: Core # Cholesky requires: Core, AMD, COLAMD. optional: Partition, Supernodal # MatrixOps requires: Core # Modify requires: Core # Partition requires: Core, CCOLAMD, METIS. optional: Cholesky # Supernodal requires: Core, BLAS, LAPACK # # CHOLMOD test/demo Modules (all are GNU GPL, do not appear in libcholmod.a): # Tcov requires: Core, Check, Cholesky, MatrixOps, Modify, Supernodal # optional: Partition # Valgrind same as Tcov # Demo requires: Core, Check, Cholesky, MatrixOps, Supernodal # optional: Partition # # Configuration flags: # -DNCHECK do not include the Check module. License GNU LGPL # -DNCHOLESKY do not include the Cholesky module. License GNU LGPL # -DNPARTITION do not include the Partition module. License GNU LGPL # also do not include METIS. # -DNCAMD do not use CAMD, etc from Partition module. GNU LGPL # -DNGPL do not include any GNU GPL Modules in the CHOLMOD library: # -DNMATRIXOPS do not include the MatrixOps module. License GNU GPL # -DNMODIFY do not include the Modify module. License GNU GPL # -DNSUPERNODAL do not include the Supernodal module. License GNU GPL # # -DNPRINT do not print anything. # -D'LONGBLAS=long' or -DLONGBLAS='long long' defines the integers used by # LAPACK and the BLAS (defaults to 'int') # -DNSUNPERF for Solaris only. If defined, do not use the Sun # Performance Library CHOLMOD_CONFIG = $(GPU_CONFIG) # uncomment this line to compile CHOLMOD without METIS: # CHOLMOD_CONFIG = -DNPARTITION #------------------------------------------------------------------------------ # SuiteSparseQR configuration: #------------------------------------------------------------------------------ # The SuiteSparseQR library can be compiled with the following options: # # -DNPARTITION do not include the CHOLMOD partition module # -DNEXPERT do not include the functions in SuiteSparseQR_expert.cpp # -DHAVE_TBB enable the use of Intel's Threading Building Blocks (TBB) # default, without timing, without TBB: SPQR_CONFIG = # with TBB: # SPQR_CONFIG = -DHAVE_TBB # This is needed for IBM AIX: (but not for and C codes, just C++) # SPQR_CONFIG = -DBLAS_NO_UNDERSCORE # with TBB, you must select this: # TBB = -ltbb # without TBB: TBB = #------------------------------------------------------------------------------ # Linux #------------------------------------------------------------------------------ # Using default compilers: # CC = gcc # CF = $(CFLAGS) -O3 -fexceptions # alternatives: # CF = $(CFLAGS) -g -fexceptions \ -Wall -W -Wshadow -Wmissing-prototypes -Wstrict-prototypes \ -Wredundant-decls -Wnested-externs -Wdisabled-optimization -ansi \ -funit-at-a-time # CF = $(CFLAGS) -O3 -fexceptions \ -Wall -W -Werror -Wshadow -Wmissing-prototypes -Wstrict-prototypes \ -Wredundant-decls -Wnested-externs -Wdisabled-optimization -ansi # CF = $(CFLAGS) -O3 -fexceptions -D_FILE_OFFSET_BITS=64 -D_LARGEFILE64_SOURCE # CF = $(CFLAGS) -O3 # CF = $(CFLAGS) -O3 -g -fexceptions # CF = $(CFLAGS) -g -fexceptions \ -Wall -W -Wshadow \ -Wredundant-decls -Wdisabled-optimization -ansi # consider: # -fforce-addr -fmove-all-movables -freduce-all-givs -ftsp-ordering # -frename-registers -ffast-math -funroll-loops # Using the Goto BLAS: # BLAS = -lgoto -lfrtbegin -lg2c $(XERBLA) -lpthread # Using Intel's icc and ifort compilers: # (does not work for mexFunctions unless you add a mexopts.sh file) # F77 = ifort # CC = icc # CF = $(CFLAGS) -O3 -xN -vec_report=0 # CF = $(CFLAGS) -g # 64bit: # F77FLAGS = -O -m64 # CF = $(CFLAGS) -O3 -fexceptions -m64 # BLAS = -lgoto64 -lfrtbegin -lg2c -lpthread $(XERBLA) # LAPACK = -llapack64 # SUSE Linux 10.1, AMD Opteron, with GOTO Blas # F77 = gfortran # BLAS = -lgoto_opteron64 -lgfortran # SUSE Linux 10.1, Intel Pentium, with GOTO Blas # F77 = gfortran # BLAS = -lgoto -lgfortran #------------------------------------------------------------------------------ # Mac #------------------------------------------------------------------------------ # As recommended by macports, http://suitesparse.darwinports.com/ # I've tested them myself on Mac OSX 10.6.1 and 10.6.8 (Snow Leopard), # on my MacBook Air, and they work fine. # F77 = gfortran # CF = $(CFLAGS) -O3 -fno-common -fexceptions -DNTIMER # BLAS = -framework Accelerate # LAPACK = -framework Accelerate # LIB = -lm #------------------------------------------------------------------------------ # Solaris #------------------------------------------------------------------------------ # 32-bit # CF = $(CFLAGS) -KPIC -dalign -xc99=%none -Xc -xlibmieee -xO5 -xlibmil -m32 # 64-bit # CF = $(CFLAGS) -fast -KPIC -xc99=%none -xlibmieee -xlibmil -m64 -Xc # FFLAGS = -fast -KPIC -dalign -xlibmil -m64 # The Sun Performance Library includes both LAPACK and the BLAS: # BLAS = -xlic_lib=sunperf # LAPACK = #------------------------------------------------------------------------------ # Compaq Alpha #------------------------------------------------------------------------------ # 64-bit mode only # CF = $(CFLAGS) -O2 -std1 # BLAS = -ldxml # LAPACK = #------------------------------------------------------------------------------ # IBM RS 6000 #------------------------------------------------------------------------------ # BLAS = -lessl # LAPACK = # 32-bit mode: # CF = $(CFLAGS) -O4 -qipa -qmaxmem=16384 -qproto # F77FLAGS = -O4 -qipa -qmaxmem=16384 # 64-bit mode: # CF = $(CFLAGS) -O4 -qipa -qmaxmem=16384 -q64 -qproto # F77FLAGS = -O4 -qipa -qmaxmem=16384 -q64 #------------------------------------------------------------------------------ # SGI IRIX #------------------------------------------------------------------------------ # BLAS = -lscsl # LAPACK = # 32-bit mode # CF = $(CFLAGS) -O # 64-bit mode (32 bit int's and 64-bit long's): # CF = $(CFLAGS) -64 # F77FLAGS = -64 # SGI doesn't have ranlib # RANLIB = echo #------------------------------------------------------------------------------ # AMD Opteron (64 bit) #------------------------------------------------------------------------------ # BLAS = -lgoto_opteron64 -lg2c # LAPACK = -llapack_opteron64 # SUSE Linux 10.1, AMD Opteron # F77 = gfortran # BLAS = -lgoto_opteron64 -lgfortran # LAPACK = -llapack_opteron64 #------------------------------------------------------------------------------ # remove object files and profile output #------------------------------------------------------------------------------ CLEAN = *.o *.obj *.ln *.bb *.bbg *.da *.tcov *.gcov gmon.out *.bak *.d *.gcda *.gcno python-igraph-0.8.0/vendor/source/igraph/src/SuiteSparse_config/SuiteSparse_config_Mac.mk0000644000076500000240000003511513524616144032112 0ustar tamasstaff00000000000000#=============================================================================== # SuiteSparse_config_Mac.mk: Mac configuration file for the SuiteSparse # To use this configuration, delete the SuiteSparse_config.mk file that # comes with SuiteSparse and rename this file as SuiteSparse_config.mk . #=============================================================================== # This file contains all configuration settings for all packages authored or # co-authored by Tim Davis: # # Package Version Description # ------- ------- ----------- # AMD 1.2 or later approximate minimum degree ordering # COLAMD 2.4 or later column approximate minimum degree ordering # CCOLAMD 1.0 or later constrained column approximate minimum degree ordering # CAMD any constrained approximate minimum degree ordering # UMFPACK 4.5 or later sparse LU factorization, with the BLAS # CHOLMOD any sparse Cholesky factorization, update/downdate # KLU 0.8 or later sparse LU factorization, BLAS-free # BTF 0.8 or later permutation to block triangular form # LDL 1.2 or later concise sparse LDL' # CXSparse any extended version of CSparse (int/long, real/complex) # SuiteSparseQR any sparse QR factorization # RBio 2.0 or later read/write sparse matrices in Rutherford-Boeing format # # By design, this file is NOT included in the CSparse makefile. # That package is fully stand-alone. CSparse is primarily for teaching; # production code should use CXSparse. # # The SuiteSparse_config directory and the above packages should all appear in # a single directory, in order for the Makefile's within each package to find # this file. # # To enable an option of the form "# OPTION = ...", edit this file and # delete the "#" in the first column of the option you wish to use. # # The use of METIS 4.0.1 is optional. To exclude METIS, you must compile with # CHOLMOD_CONFIG set to -DNPARTITION. See below for details. However, if you # do not have a metis-4.0 directory inside the SuiteSparse directory, the # */Makefile's that optionally rely on METIS will automatically detect this # and compile without METIS. #------------------------------------------------------------------------------ # Generic configuration #------------------------------------------------------------------------------ # Using standard definitions from the make environment, typically: # # CC cc C compiler # CXX g++ C++ compiler # CFLAGS [ ] flags for C and C++ compiler # CPPFLAGS [ ] flags for C and C++ compiler # TARGET_ARCH [ ] target architecture # FFLAGS [ ] flags for Fortran compiler # RM rm -f delete a file # AR ar create a static *.a library archive # ARFLAGS rv flags for ar # MAKE make make itself (sometimes called gmake) # # You can redefine them here, but by default they are used from the # default make environment. # C and C++ compiler flags. The first three are standard for *.c and *.cpp # Add -DNTIMER if you do use any timing routines (otherwise -lrt is required). # CF = $(CFLAGS) $(CPPFLAGS) $(TARGET_ARCH) -O3 -fexceptions -fPIC -DNTIMER CF = $(CFLAGS) $(CPPFLAGS) $(TARGET_ARCH) -O3 -fexceptions -fPIC # ranlib, and ar, for generating libraries. If you don't need ranlib, # just change it to RANLAB = echo RANLIB = ranlib ARCHIVE = $(AR) $(ARFLAGS) # copy and delete a file CP = cp -f MV = mv -f # Fortran compiler (not required for 'make' or 'make library') F77 = gfortran F77FLAGS = $(FFLAGS) -O F77LIB = # C and Fortran libraries. Remove -lrt if you don't have it. LIB = -lm -lrt # Using the following requires CF = ... -DNTIMER on POSIX C systems. # LIB = -lm # For "make install" INSTALL_LIB = /usr/local/lib INSTALL_INCLUDE = /usr/local/include # Which version of MAKE you are using (default is "make") # MAKE = make # MAKE = gmake #------------------------------------------------------------------------------ # BLAS and LAPACK configuration: #------------------------------------------------------------------------------ # UMFPACK and CHOLMOD both require the BLAS. CHOLMOD also requires LAPACK. # See Kazushige Goto's BLAS at http://www.cs.utexas.edu/users/flame/goto/ or # http://www.tacc.utexas.edu/~kgoto/ for the best BLAS to use with CHOLMOD. # LAPACK is at http://www.netlib.org/lapack/ . You can use the standard # Fortran LAPACK along with Goto's BLAS to obtain very good performance. # CHOLMOD gets a peak numeric factorization rate of 3.6 Gflops on a 3.2 GHz # Pentium 4 (512K cache, 4GB main memory) with the Goto BLAS, and 6 Gflops # on a 2.5Ghz dual-core AMD Opteron. # These settings will probably not work, since there is no fixed convention for # naming the BLAS and LAPACK library (*.a or *.so) files. # This is probably slow ... it might connect to the Standard Reference BLAS: BLAS = -lblas -lgfortran LAPACK = -llapack # NOTE: this next option for the "Goto BLAS" has nothing to do with a "goto" # statement. Rather, the Goto BLAS is written by Dr. Kazushige Goto. # Using the Goto BLAS: # BLAS = -lgoto -lgfortran -lgfortranbegin # BLAS = -lgoto2 -lgfortran -lgfortranbegin -lpthread # Using non-optimized versions: # BLAS = -lblas_plain -lgfortran -lgfortranbegin # LAPACK = -llapack_plain # BLAS = -lblas_plain -lgfortran -lgfortranbegin # LAPACK = -llapack # The BLAS might not contain xerbla, an error-handling routine for LAPACK and # the BLAS. Also, the standard xerbla requires the Fortran I/O library, and # stops the application program if an error occurs. A C version of xerbla # distributed with this software (SuiteSparse_config/xerbla/libcerbla.a) # includes a Fortran-callable xerbla routine that prints nothing and does not # stop the application program. This is optional. # XERBLA = ../../SuiteSparse_config/xerbla/libcerbla.a # If you wish to use the XERBLA in LAPACK and/or the BLAS instead, # use this option: XERBLA = # If you wish to use the Fortran SuiteSparse_config/xerbla/xerbla.f instead, # use this: # XERBLA = ../../SuiteSparse_config/xerbla/libxerbla.a #------------------------------------------------------------------------------ # GPU configuration for CHOLMOD, using the CUDA BLAS #------------------------------------------------------------------------------ # no cuda GPU_BLAS_PATH = GPU_CONFIG = # with cuda BLAS acceleration for CHOLMOD # GPU_BLAS_PATH=/usr/local/cuda # GPU_CONFIG=-DGPU_BLAS -I$(GPU_BLAS_PATH)/include #------------------------------------------------------------------------------ # METIS, optionally used by CHOLMOD #------------------------------------------------------------------------------ # If you do not have METIS, or do not wish to use it in CHOLMOD, you must # compile CHOLMOD with the -DNPARTITION flag. # The path is relative to where it is used, in CHOLMOD/Lib, CHOLMOD/MATLAB, etc. # You may wish to use an absolute path. METIS is optional. Compile # CHOLMOD with -DNPARTITION if you do not wish to use METIS. METIS_PATH = ../../metis-4.0 METIS = ../../metis-4.0/libmetis.a #------------------------------------------------------------------------------ # UMFPACK configuration: #------------------------------------------------------------------------------ # Configuration flags for UMFPACK. See UMFPACK/Source/umf_config.h for details. # # -DNBLAS do not use the BLAS. UMFPACK will be very slow. # -D'LONGBLAS=long' or -DLONGBLAS='long long' defines the integers used by # LAPACK and the BLAS (defaults to 'int') # -DNSUNPERF do not use the Sun Perf. Library (default is use it on Solaris) # -DNRECIPROCAL do not multiply by the reciprocal # -DNO_DIVIDE_BY_ZERO do not divide by zero # -DNCHOLMOD do not use CHOLMOD as a ordering method. If -DNCHOLMOD is # included in UMFPACK_CONFIG, then UMFPACK does not rely on # CHOLMOD, CAMD, CCOLAMD, COLAMD, and METIS. UMFPACK_CONFIG = # uncomment this line to compile UMFPACK without CHOLMOD: # UMFPACK_CONFIG = -DNCHOLMOD #------------------------------------------------------------------------------ # CHOLMOD configuration #------------------------------------------------------------------------------ # CHOLMOD Library Modules, which appear in libcholmod.a: # Core requires: none # Check requires: Core # Cholesky requires: Core, AMD, COLAMD. optional: Partition, Supernodal # MatrixOps requires: Core # Modify requires: Core # Partition requires: Core, CCOLAMD, METIS. optional: Cholesky # Supernodal requires: Core, BLAS, LAPACK # # CHOLMOD test/demo Modules (all are GNU GPL, do not appear in libcholmod.a): # Tcov requires: Core, Check, Cholesky, MatrixOps, Modify, Supernodal # optional: Partition # Valgrind same as Tcov # Demo requires: Core, Check, Cholesky, MatrixOps, Supernodal # optional: Partition # # Configuration flags: # -DNCHECK do not include the Check module. License GNU LGPL # -DNCHOLESKY do not include the Cholesky module. License GNU LGPL # -DNPARTITION do not include the Partition module. License GNU LGPL # also do not include METIS. # -DNCAMD do not use CAMD, etc from Partition module. GNU LGPL # -DNGPL do not include any GNU GPL Modules in the CHOLMOD library: # -DNMATRIXOPS do not include the MatrixOps module. License GNU GPL # -DNMODIFY do not include the Modify module. License GNU GPL # -DNSUPERNODAL do not include the Supernodal module. License GNU GPL # # -DNPRINT do not print anything. # -D'LONGBLAS=long' or -DLONGBLAS='long long' defines the integers used by # LAPACK and the BLAS (defaults to 'int') # -DNSUNPERF for Solaris only. If defined, do not use the Sun # Performance Library CHOLMOD_CONFIG = $(GPU_CONFIG) # uncomment this line to compile CHOLMOD without METIS: # CHOLMOD_CONFIG = -DNPARTITION #------------------------------------------------------------------------------ # SuiteSparseQR configuration: #------------------------------------------------------------------------------ # The SuiteSparseQR library can be compiled with the following options: # # -DNPARTITION do not include the CHOLMOD partition module # -DNEXPERT do not include the functions in SuiteSparseQR_expert.cpp # -DHAVE_TBB enable the use of Intel's Threading Building Blocks (TBB) # default, without timing, without TBB: SPQR_CONFIG = # with TBB: # SPQR_CONFIG = -DHAVE_TBB # This is needed for IBM AIX: (but not for and C codes, just C++) # SPQR_CONFIG = -DBLAS_NO_UNDERSCORE # with TBB, you must select this: # TBB = -ltbb # without TBB: TBB = #------------------------------------------------------------------------------ # Linux #------------------------------------------------------------------------------ # Using default compilers: # CC = gcc # CF = $(CFLAGS) -O3 -fexceptions # alternatives: # CF = $(CFLAGS) -g -fexceptions \ -Wall -W -Wshadow -Wmissing-prototypes -Wstrict-prototypes \ -Wredundant-decls -Wnested-externs -Wdisabled-optimization -ansi \ -funit-at-a-time # CF = $(CFLAGS) -O3 -fexceptions \ -Wall -W -Werror -Wshadow -Wmissing-prototypes -Wstrict-prototypes \ -Wredundant-decls -Wnested-externs -Wdisabled-optimization -ansi # CF = $(CFLAGS) -O3 -fexceptions -D_FILE_OFFSET_BITS=64 -D_LARGEFILE64_SOURCE # CF = $(CFLAGS) -O3 # CF = $(CFLAGS) -O3 -g -fexceptions # CF = $(CFLAGS) -g -fexceptions \ -Wall -W -Wshadow \ -Wredundant-decls -Wdisabled-optimization -ansi # consider: # -fforce-addr -fmove-all-movables -freduce-all-givs -ftsp-ordering # -frename-registers -ffast-math -funroll-loops # Using the Goto BLAS: # BLAS = -lgoto -lfrtbegin -lg2c $(XERBLA) -lpthread # Using Intel's icc and ifort compilers: # (does not work for mexFunctions unless you add a mexopts.sh file) # F77 = ifort # CC = icc # CF = $(CFLAGS) -O3 -xN -vec_report=0 # CF = $(CFLAGS) -g # 64bit: # F77FLAGS = -O -m64 # CF = $(CFLAGS) -O3 -fexceptions -m64 # BLAS = -lgoto64 -lfrtbegin -lg2c -lpthread $(XERBLA) # LAPACK = -llapack64 # SUSE Linux 10.1, AMD Opteron, with GOTO Blas # F77 = gfortran # BLAS = -lgoto_opteron64 -lgfortran # SUSE Linux 10.1, Intel Pentium, with GOTO Blas # F77 = gfortran # BLAS = -lgoto -lgfortran #------------------------------------------------------------------------------ # Mac #------------------------------------------------------------------------------ # As recommended by macports, http://suitesparse.darwinports.com/ # I've tested them myself on Mac OSX 10.6.1 and 10.6.8 (Snow Leopard), # on my MacBook Air, and they work fine. F77 = gfortran CF = $(CFLAGS) -O3 -fno-common -fexceptions -DNTIMER BLAS = -framework Accelerate LAPACK = -framework Accelerate LIB = -lm #------------------------------------------------------------------------------ # Solaris #------------------------------------------------------------------------------ # 32-bit # CF = $(CFLAGS) -KPIC -dalign -xc99=%none -Xc -xlibmieee -xO5 -xlibmil -m32 # 64-bit # CF = $(CFLAGS) -fast -KPIC -xc99=%none -xlibmieee -xlibmil -m64 -Xc # FFLAGS = -fast -KPIC -dalign -xlibmil -m64 # The Sun Performance Library includes both LAPACK and the BLAS: # BLAS = -xlic_lib=sunperf # LAPACK = #------------------------------------------------------------------------------ # Compaq Alpha #------------------------------------------------------------------------------ # 64-bit mode only # CF = $(CFLAGS) -O2 -std1 # BLAS = -ldxml # LAPACK = #------------------------------------------------------------------------------ # IBM RS 6000 #------------------------------------------------------------------------------ # BLAS = -lessl # LAPACK = # 32-bit mode: # CF = $(CFLAGS) -O4 -qipa -qmaxmem=16384 -qproto # F77FLAGS = -O4 -qipa -qmaxmem=16384 # 64-bit mode: # CF = $(CFLAGS) -O4 -qipa -qmaxmem=16384 -q64 -qproto # F77FLAGS = -O4 -qipa -qmaxmem=16384 -q64 #------------------------------------------------------------------------------ # SGI IRIX #------------------------------------------------------------------------------ # BLAS = -lscsl # LAPACK = # 32-bit mode # CF = $(CFLAGS) -O # 64-bit mode (32 bit int's and 64-bit long's): # CF = $(CFLAGS) -64 # F77FLAGS = -64 # SGI doesn't have ranlib # RANLIB = echo #------------------------------------------------------------------------------ # AMD Opteron (64 bit) #------------------------------------------------------------------------------ # BLAS = -lgoto_opteron64 -lg2c # LAPACK = -llapack_opteron64 # SUSE Linux 10.1, AMD Opteron # F77 = gfortran # BLAS = -lgoto_opteron64 -lgfortran # LAPACK = -llapack_opteron64 #------------------------------------------------------------------------------ # remove object files and profile output #------------------------------------------------------------------------------ CLEAN = *.o *.obj *.ln *.bb *.bbg *.da *.tcov *.gcov gmon.out *.bak *.d *.gcda *.gcno python-igraph-0.8.0/vendor/source/igraph/src/SuiteSparse_config/SuiteSparse_config_GPU.mk0000644000076500000240000003467713524616144032061 0ustar tamasstaff00000000000000#=============================================================================== # SuiteSparse_config.mk: common configuration file for the SuiteSparse #=============================================================================== # This file contains all configuration settings for all packages authored or # co-authored by Tim Davis: # # Package Version Description # ------- ------- ----------- # AMD 1.2 or later approximate minimum degree ordering # COLAMD 2.4 or later column approximate minimum degree ordering # CCOLAMD 1.0 or later constrained column approximate minimum degree ordering # CAMD any constrained approximate minimum degree ordering # UMFPACK 4.5 or later sparse LU factorization, with the BLAS # CHOLMOD any sparse Cholesky factorization, update/downdate # KLU 0.8 or later sparse LU factorization, BLAS-free # BTF 0.8 or later permutation to block triangular form # LDL 1.2 or later concise sparse LDL' # CXSparse any extended version of CSparse (int/long, real/complex) # SuiteSparseQR any sparse QR factorization # RBio 2.0 or later read/write sparse matrices in Rutherford-Boeing format # # By design, this file is NOT included in the CSparse makefile. # That package is fully stand-alone. CSparse is primarily for teaching; # production code should use CXSparse. # # The SuiteSparse_config directory and the above packages should all appear in # a single directory, in order for the Makefile's within each package to find # this file. # # To enable an option of the form "# OPTION = ...", edit this file and # delete the "#" in the first column of the option you wish to use. # # The use of METIS 4.0.1 is optional. To exclude METIS, you must compile with # CHOLMOD_CONFIG set to -DNPARTITION. See below for details. However, if you # do not have a metis-4.0 directory inside the SuiteSparse directory, the # */Makefile's that optionally rely on METIS will automatically detect this # and compile without METIS. #------------------------------------------------------------------------------ # Generic configuration #------------------------------------------------------------------------------ # Using standard definitions from the make environment, typically: # # CC cc C compiler # CXX g++ C++ compiler # CFLAGS [ ] flags for C and C++ compiler # CPPFLAGS [ ] flags for C and C++ compiler # TARGET_ARCH [ ] target architecture # FFLAGS [ ] flags for Fortran compiler # RM rm -f delete a file # AR ar create a static *.a library archive # ARFLAGS rv flags for ar # MAKE make make itself (sometimes called gmake) # # You can redefine them here, but by default they are used from the # default make environment. # C and C++ compiler flags. The first three are standard for *.c and *.cpp # Add -DNTIMER if you do use any timing routines (otherwise -lrt is required). # CF = $(CFLAGS) $(CPPFLAGS) $(TARGET_ARCH) -O3 -fexceptions -fPIC -DNTIMER CF = $(CFLAGS) $(CPPFLAGS) $(TARGET_ARCH) -O3 -fexceptions -fPIC # ranlib, and ar, for generating libraries. If you don't need ranlib, # just change it to RANLAB = echo RANLIB = ranlib ARCHIVE = $(AR) $(ARFLAGS) # copy and delete a file CP = cp -f MV = mv -f # Fortran compiler (not required for 'make' or 'make library') F77 = gfortran F77FLAGS = $(FFLAGS) -O F77LIB = # C and Fortran libraries. Remove -lrt if you don't have it. LIB = -lm -lrt # Using the following requires CF = ... -DNTIMER on POSIX C systems. # LIB = -lm # For "make install" INSTALL_LIB = /usr/local/lib INSTALL_INCLUDE = /usr/local/include # Which version of MAKE you are using (default is "make") # MAKE = make # MAKE = gmake #------------------------------------------------------------------------------ # BLAS and LAPACK configuration: #------------------------------------------------------------------------------ # UMFPACK and CHOLMOD both require the BLAS. CHOLMOD also requires LAPACK. # See Kazushige Goto's BLAS at http://www.cs.utexas.edu/users/flame/goto/ or # http://www.tacc.utexas.edu/~kgoto/ for the best BLAS to use with CHOLMOD. # LAPACK is at http://www.netlib.org/lapack/ . You can use the standard # Fortran LAPACK along with Goto's BLAS to obtain very good performance. # CHOLMOD gets a peak numeric factorization rate of 3.6 Gflops on a 3.2 GHz # Pentium 4 (512K cache, 4GB main memory) with the Goto BLAS, and 6 Gflops # on a 2.5Ghz dual-core AMD Opteron. # These settings will probably not work, since there is no fixed convention for # naming the BLAS and LAPACK library (*.a or *.so) files. # This is probably slow ... it might connect to the Standard Reference BLAS: BLAS = -lblas -lgfortran LAPACK = -llapack # NOTE: this next option for the "Goto BLAS" has nothing to do with a "goto" # statement. Rather, the Goto BLAS is written by Dr. Kazushige Goto. # Using the Goto BLAS: # BLAS = -lgoto -lgfortran -lgfortranbegin # BLAS = -lgoto2 -lgfortran -lgfortranbegin -lpthread # Using non-optimized versions: # BLAS = -lblas_plain -lgfortran -lgfortranbegin # LAPACK = -llapack_plain # BLAS = -lblas_plain -lgfortran -lgfortranbegin # LAPACK = -llapack # The BLAS might not contain xerbla, an error-handling routine for LAPACK and # the BLAS. Also, the standard xerbla requires the Fortran I/O library, and # stops the application program if an error occurs. A C version of xerbla # distributed with this software (SuiteSparse_config/xerbla/libcerbla.a) # includes a Fortran-callable xerbla routine that prints nothing and does not # stop the application program. This is optional. # XERBLA = ../../SuiteSparse_config/xerbla/libcerbla.a # If you wish to use the XERBLA in LAPACK and/or the BLAS instead, # use this option: XERBLA = # If you wish to use the Fortran SuiteSparse_config/xerbla/xerbla.f instead, # use this: # XERBLA = ../../SuiteSparse_config/xerbla/libxerbla.a #------------------------------------------------------------------------------ # GPU configuration for CHOLMOD, using the CUDA BLAS #------------------------------------------------------------------------------ # no cuda # GPU_BLAS_PATH = # GPU_CONFIG = # with cuda BLAS acceleration for CHOLMOD GPU_BLAS_PATH=/usr/local/cuda GPU_CONFIG=-DGPU_BLAS -I$(GPU_BLAS_PATH)/include #------------------------------------------------------------------------------ # METIS, optionally used by CHOLMOD #------------------------------------------------------------------------------ # If you do not have METIS, or do not wish to use it in CHOLMOD, you must # compile CHOLMOD with the -DNPARTITION flag. # The path is relative to where it is used, in CHOLMOD/Lib, CHOLMOD/MATLAB, etc. # You may wish to use an absolute path. METIS is optional. Compile # CHOLMOD with -DNPARTITION if you do not wish to use METIS. METIS_PATH = ../../metis-4.0 METIS = ../../metis-4.0/libmetis.a #------------------------------------------------------------------------------ # UMFPACK configuration: #------------------------------------------------------------------------------ # Configuration flags for UMFPACK. See UMFPACK/Source/umf_config.h for details. # # -DNBLAS do not use the BLAS. UMFPACK will be very slow. # -D'LONGBLAS=long' or -DLONGBLAS='long long' defines the integers used by # LAPACK and the BLAS (defaults to 'int') # -DNSUNPERF do not use the Sun Perf. Library (default is use it on Solaris) # -DNRECIPROCAL do not multiply by the reciprocal # -DNO_DIVIDE_BY_ZERO do not divide by zero # -DNCHOLMOD do not use CHOLMOD as a ordering method. If -DNCHOLMOD is # included in UMFPACK_CONFIG, then UMFPACK does not rely on # CHOLMOD, CAMD, CCOLAMD, COLAMD, and METIS. UMFPACK_CONFIG = # uncomment this line to compile UMFPACK without CHOLMOD: # UMFPACK_CONFIG = -DNCHOLMOD #------------------------------------------------------------------------------ # CHOLMOD configuration #------------------------------------------------------------------------------ # CHOLMOD Library Modules, which appear in libcholmod.a: # Core requires: none # Check requires: Core # Cholesky requires: Core, AMD, COLAMD. optional: Partition, Supernodal # MatrixOps requires: Core # Modify requires: Core # Partition requires: Core, CCOLAMD, METIS. optional: Cholesky # Supernodal requires: Core, BLAS, LAPACK # # CHOLMOD test/demo Modules (all are GNU GPL, do not appear in libcholmod.a): # Tcov requires: Core, Check, Cholesky, MatrixOps, Modify, Supernodal # optional: Partition # Valgrind same as Tcov # Demo requires: Core, Check, Cholesky, MatrixOps, Supernodal # optional: Partition # # Configuration flags: # -DNCHECK do not include the Check module. License GNU LGPL # -DNCHOLESKY do not include the Cholesky module. License GNU LGPL # -DNPARTITION do not include the Partition module. License GNU LGPL # also do not include METIS. # -DNCAMD do not use CAMD, etc from Partition module. GNU LGPL # -DNGPL do not include any GNU GPL Modules in the CHOLMOD library: # -DNMATRIXOPS do not include the MatrixOps module. License GNU GPL # -DNMODIFY do not include the Modify module. License GNU GPL # -DNSUPERNODAL do not include the Supernodal module. License GNU GPL # # -DNPRINT do not print anything. # -D'LONGBLAS=long' or -DLONGBLAS='long long' defines the integers used by # LAPACK and the BLAS (defaults to 'int') # -DNSUNPERF for Solaris only. If defined, do not use the Sun # Performance Library CHOLMOD_CONFIG = $(GPU_CONFIG) # uncomment this line to compile CHOLMOD without METIS: # CHOLMOD_CONFIG = -DNPARTITION #------------------------------------------------------------------------------ # SuiteSparseQR configuration: #------------------------------------------------------------------------------ # The SuiteSparseQR library can be compiled with the following options: # # -DNPARTITION do not include the CHOLMOD partition module # -DNEXPERT do not include the functions in SuiteSparseQR_expert.cpp # -DHAVE_TBB enable the use of Intel's Threading Building Blocks (TBB) # default, without timing, without TBB: SPQR_CONFIG = # with TBB: # SPQR_CONFIG = -DHAVE_TBB # This is needed for IBM AIX: (but not for and C codes, just C++) # SPQR_CONFIG = -DBLAS_NO_UNDERSCORE # with TBB, you must select this: # TBB = -ltbb # without TBB: TBB = #------------------------------------------------------------------------------ # Linux #------------------------------------------------------------------------------ # Using default compilers: # CC = gcc # CF = $(CFLAGS) -O3 -fexceptions # alternatives: # CF = $(CFLAGS) -g -fexceptions \ -Wall -W -Wshadow -Wmissing-prototypes -Wstrict-prototypes \ -Wredundant-decls -Wnested-externs -Wdisabled-optimization -ansi \ -funit-at-a-time # CF = $(CFLAGS) -O3 -fexceptions \ -Wall -W -Werror -Wshadow -Wmissing-prototypes -Wstrict-prototypes \ -Wredundant-decls -Wnested-externs -Wdisabled-optimization -ansi # CF = $(CFLAGS) -O3 -fexceptions -D_FILE_OFFSET_BITS=64 -D_LARGEFILE64_SOURCE # CF = $(CFLAGS) -O3 # CF = $(CFLAGS) -O3 -g -fexceptions # CF = $(CFLAGS) -g -fexceptions \ -Wall -W -Wshadow \ -Wredundant-decls -Wdisabled-optimization -ansi # consider: # -fforce-addr -fmove-all-movables -freduce-all-givs -ftsp-ordering # -frename-registers -ffast-math -funroll-loops # Using the Goto BLAS: # BLAS = -lgoto -lfrtbegin -lg2c $(XERBLA) -lpthread # Using Intel's icc and ifort compilers: # (does not work for mexFunctions unless you add a mexopts.sh file) # F77 = ifort # CC = icc # CF = $(CFLAGS) -O3 -xN -vec_report=0 # CF = $(CFLAGS) -g # 64bit: # F77FLAGS = -O -m64 # CF = $(CFLAGS) -O3 -fexceptions -m64 # BLAS = -lgoto64 -lfrtbegin -lg2c -lpthread $(XERBLA) # LAPACK = -llapack64 # SUSE Linux 10.1, AMD Opteron, with GOTO Blas # F77 = gfortran # BLAS = -lgoto_opteron64 -lgfortran # SUSE Linux 10.1, Intel Pentium, with GOTO Blas # F77 = gfortran # BLAS = -lgoto -lgfortran #------------------------------------------------------------------------------ # Mac #------------------------------------------------------------------------------ # As recommended by macports, http://suitesparse.darwinports.com/ # I've tested them myself on Mac OSX 10.6.1 and 10.6.8 (Snow Leopard), # on my MacBook Air, and they work fine. # F77 = gfortran # CF = $(CFLAGS) -O3 -fno-common -fexceptions -DNTIMER # BLAS = -framework Accelerate # LAPACK = -framework Accelerate # LIB = -lm #------------------------------------------------------------------------------ # Solaris #------------------------------------------------------------------------------ # 32-bit # CF = $(CFLAGS) -KPIC -dalign -xc99=%none -Xc -xlibmieee -xO5 -xlibmil -m32 # 64-bit # CF = $(CFLAGS) -fast -KPIC -xc99=%none -xlibmieee -xlibmil -m64 -Xc # FFLAGS = -fast -KPIC -dalign -xlibmil -m64 # The Sun Performance Library includes both LAPACK and the BLAS: # BLAS = -xlic_lib=sunperf # LAPACK = #------------------------------------------------------------------------------ # Compaq Alpha #------------------------------------------------------------------------------ # 64-bit mode only # CF = $(CFLAGS) -O2 -std1 # BLAS = -ldxml # LAPACK = #------------------------------------------------------------------------------ # IBM RS 6000 #------------------------------------------------------------------------------ # BLAS = -lessl # LAPACK = # 32-bit mode: # CF = $(CFLAGS) -O4 -qipa -qmaxmem=16384 -qproto # F77FLAGS = -O4 -qipa -qmaxmem=16384 # 64-bit mode: # CF = $(CFLAGS) -O4 -qipa -qmaxmem=16384 -q64 -qproto # F77FLAGS = -O4 -qipa -qmaxmem=16384 -q64 #------------------------------------------------------------------------------ # SGI IRIX #------------------------------------------------------------------------------ # BLAS = -lscsl # LAPACK = # 32-bit mode # CF = $(CFLAGS) -O # 64-bit mode (32 bit int's and 64-bit long's): # CF = $(CFLAGS) -64 # F77FLAGS = -64 # SGI doesn't have ranlib # RANLIB = echo #------------------------------------------------------------------------------ # AMD Opteron (64 bit) #------------------------------------------------------------------------------ # BLAS = -lgoto_opteron64 -lg2c # LAPACK = -llapack_opteron64 # SUSE Linux 10.1, AMD Opteron # F77 = gfortran # BLAS = -lgoto_opteron64 -lgfortran # LAPACK = -llapack_opteron64 #------------------------------------------------------------------------------ # remove object files and profile output #------------------------------------------------------------------------------ CLEAN = *.o *.obj *.ln *.bb *.bbg *.da *.tcov *.gcov gmon.out *.bak *.d *.gcda *.gcno python-igraph-0.8.0/vendor/source/igraph/src/SuiteSparse_config/SuiteSparse_config.h0000644000076500000240000001576313524616144031161 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === SuiteSparse_config =================================================== */ /* ========================================================================== */ /* Configuration file for SuiteSparse: a Suite of Sparse matrix packages * (AMD, COLAMD, CCOLAMD, CAMD, CHOLMOD, UMFPACK, CXSparse, and others). * * SuiteSparse_config.h provides the definition of the long integer. On most * systems, a C program can be compiled in LP64 mode, in which long's and * pointers are both 64-bits, and int's are 32-bits. Windows 64, however, uses * the LLP64 model, in which int's and long's are 32-bits, and long long's and * pointers are 64-bits. * * SuiteSparse packages that include long integer versions are * intended for the LP64 mode. However, as a workaround for Windows 64 * (and perhaps other systems), the long integer can be redefined. * * If _WIN64 is defined, then the __int64 type is used instead of long. * * The long integer can also be defined at compile time. For example, this * could be added to SuiteSparse_config.mk: * * CFLAGS = -O -D'SuiteSparse_long=long long' \ * -D'SuiteSparse_long_max=9223372036854775801' -D'SuiteSparse_long_idd="lld"' * * This file defines SuiteSparse_long as either long (on all but _WIN64) or * __int64 on Windows 64. The intent is that a SuiteSparse_long is always a * 64-bit integer in a 64-bit code. ptrdiff_t might be a better choice than * long; it is always the same size as a pointer. * * This file also defines the SUITESPARSE_VERSION and related definitions. * * Copyright (c) 2012, Timothy A. Davis. No licensing restrictions apply * to this file or to the SuiteSparse_config directory. * Author: Timothy A. Davis. */ #ifndef _SUITESPARSECONFIG_H #define _SUITESPARSECONFIG_H #ifdef __cplusplus extern "C" { #endif #include #include /* ========================================================================== */ /* === SuiteSparse_long ===================================================== */ /* ========================================================================== */ #ifndef SuiteSparse_long #ifdef _WIN64 #define SuiteSparse_long __int64 #define SuiteSparse_long_max _I64_MAX #define SuiteSparse_long_idd "I64d" #else #define SuiteSparse_long long #define SuiteSparse_long_max LONG_MAX #define SuiteSparse_long_idd "ld" #endif #define SuiteSparse_long_id "%" SuiteSparse_long_idd #endif /* For backward compatibility with prior versions of SuiteSparse. The UF_* * macros are deprecated and will be removed in a future version. */ #ifndef UF_long #define UF_long SuiteSparse_long #define UF_long_max SuiteSparse_long_max #define UF_long_idd SuiteSparse_long_idd #define UF_long_id SuiteSparse_long_id #endif /* ========================================================================== */ /* === SuiteSparse_config parameters and functions ========================== */ /* ========================================================================== */ /* SuiteSparse-wide parameters will be placed in this struct. */ typedef struct SuiteSparse_config_struct { void *(*malloc_memory) (size_t) ; /* pointer to malloc */ void *(*realloc_memory) (void *, size_t) ; /* pointer to realloc */ void (*free_memory) (void *) ; /* pointer to free */ void *(*calloc_memory) (size_t, size_t) ; /* pointer to calloc */ } SuiteSparse_config ; void *SuiteSparse_malloc /* pointer to allocated block of memory */ ( size_t nitems, /* number of items to malloc (>=1 is enforced) */ size_t size_of_item, /* sizeof each item */ int *ok, /* TRUE if successful, FALSE otherwise */ SuiteSparse_config *config /* SuiteSparse-wide configuration */ ) ; void *SuiteSparse_free /* always returns NULL */ ( void *p, /* block to free */ SuiteSparse_config *config /* SuiteSparse-wide configuration */ ) ; void SuiteSparse_tic /* start the timer */ ( double tic [2] /* output, contents undefined on input */ ) ; double SuiteSparse_toc /* return time in seconds since last tic */ ( double tic [2] /* input: from last call to SuiteSparse_tic */ ) ; double SuiteSparse_time /* returns current wall clock time in seconds */ ( void ) ; /* determine which timer to use, if any */ #ifndef NTIMER #ifdef _POSIX_C_SOURCE #if _POSIX_C_SOURCE >= 199309L #define SUITESPARSE_TIMER_ENABLED #endif #endif #endif /* ========================================================================== */ /* === SuiteSparse version ================================================== */ /* ========================================================================== */ /* SuiteSparse is not a package itself, but a collection of packages, some of * which must be used together (UMFPACK requires AMD, CHOLMOD requires AMD, * COLAMD, CAMD, and CCOLAMD, etc). A version number is provided here for the * collection itself. The versions of packages within each version of * SuiteSparse are meant to work together. Combining one packge from one * version of SuiteSparse, with another package from another version of * SuiteSparse, may or may not work. * * SuiteSparse contains the following packages: * * SuiteSparse_config version 4.2.1 (version always the same as SuiteSparse) * AMD version 2.3.1 * BTF version 1.2.0 * CAMD version 2.3.1 * CCOLAMD version 2.8.0 * CHOLMOD version 2.1.2 * COLAMD version 2.8.0 * CSparse version 3.1.2 * CXSparse version 3.1.2 * KLU version 1.2.1 * LDL version 2.1.0 * RBio version 2.1.1 * SPQR version 1.3.1 (full name is SuiteSparseQR) * UMFPACK version 5.6.2 * MATLAB_Tools various packages & M-files * * Other package dependencies: * BLAS required by CHOLMOD and UMFPACK * LAPACK required by CHOLMOD * METIS 4.0.1 required by CHOLMOD (optional) and KLU (optional) */ int SuiteSparse_version /* returns SUITESPARSE_VERSION */ ( /* output, not defined on input. Not used if NULL. Returns the three version codes in version [0..2]: version [0] is SUITESPARSE_MAIN_VERSION version [1] is SUITESPARSE_SUB_VERSION version [2] is SUITESPARSE_SUBSUB_VERSION */ int version [3] ) ; /* Versions prior to 4.2.0 do not have the above function. The following code fragment will work with any version of SuiteSparse: #ifdef SUITESPARSE_HAS_VERSION_FUNCTION v = SuiteSparse_version (NULL) ; #else v = SUITESPARSE_VERSION ; #endif */ #define SUITESPARSE_HAS_VERSION_FUNCTION #define SUITESPARSE_DATE "April 25, 2013" #define SUITESPARSE_VER_CODE(main,sub) ((main) * 1000 + (sub)) #define SUITESPARSE_MAIN_VERSION 4 #define SUITESPARSE_SUB_VERSION 2 #define SUITESPARSE_SUBSUB_VERSION 1 #define SUITESPARSE_VERSION \ SUITESPARSE_VER_CODE(SUITESPARSE_MAIN_VERSION,SUITESPARSE_SUB_VERSION) #ifdef __cplusplus } #endif #endif python-igraph-0.8.0/vendor/source/igraph/src/SuiteSparse_config/README.txt0000644000076500000240000000451313524616144026701 0ustar tamasstaff00000000000000SuiteSparse_config, 2013, Timothy A. Davis, http://www.suitesparse.com (formerly the UFconfig package) SuiteSparse_config contains configuration settings for all many of the software packages that I develop or co-author. Note that older versions of some of these packages do not require SuiteSparse_config. Package Description ------- ----------- AMD approximate minimum degree ordering CAMD constrained AMD COLAMD column approximate minimum degree ordering CCOLAMD constrained approximate minimum degree ordering UMFPACK sparse LU factorization, with the BLAS CXSparse int/long/real/complex version of CSparse CHOLMOD sparse Cholesky factorization, update/downdate KLU sparse LU factorization, BLAS-free BTF permutation to block triangular form LDL concise sparse LDL' LPDASA LP Dual Active Set Algorithm RBio read/write files in Rutherford/Boeing format SPQR sparse QR factorization (full name: SuiteSparseQR) SuiteSparse_config is not required by these packages: CSparse a Concise Sparse matrix package MATLAB_Tools toolboxes for use in MATLAB In addition, the xerbla/ directory contains Fortan and C versions of the BLAS/LAPACK xerbla routine, which is called when an invalid input is passed to the BLAS or LAPACK. The xerbla provided here does not print any message, so the entire Fortran I/O library does not need to be linked into a C application. Most versions of the BLAS contain xerbla, but those from K. Goto do not. Use this if you need too. If you edit this directory (SuiteSparse_config.mk in particular) then you must do "make purge ; make" in the parent directory to recompile all of SuiteSparse. Otherwise, the changes will not necessarily be applied. -------------------------------------------------------------------------------- A note on the update to SuiteSparse Version 4.0.0: The SuiteSparse_long macro defines an integer that is 64-bits in size on 64-bit platforms, and 32-bits on 32-bit platforms. It was formerly called UF_long, but UF_long has been removed because of potential name conflicts. UF_long is still available to user codes, but it can now be safely #undef'd in case of name conflicts in user code. Future codes should use SuiteSparse_long in place of UF_long. -------------------------------------------------------------------------------- python-igraph-0.8.0/vendor/source/igraph/src/gengraph_graph_molloy_hash.h0000644000076500000240000001765613614300625027140 0ustar tamasstaff00000000000000/* * * gengraph - generation of random simple connected graphs with prescribed * degree sequence * * Copyright (C) 2006 Fabien Viger * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #ifndef GRAPH_MOLLOY_HASH_H #define GRAPH_MOLLOY_HASH_H #include "gengraph_definitions.h" #include "gengraph_hash.h" #include "gengraph_degree_sequence.h" #include #include // This class handles graphs with a constant degree sequence. #define FINAL_HEURISTICS 0 #define GKAN_HEURISTICS 1 #define FAB_HEURISTICS 2 #define OPTIMAL_HEURISTICS 3 #define BRUTE_FORCE_HEURISTICS 4 namespace gengraph { //**************************** // class graph_molloy_hash //**************************** class graph_molloy_hash { private: // Number of vertices int n; //Number of arcs ( = #edges * 2 ) int a; //Total size of links[] int size; // The degree sequence of the graph int *deg; // The array containing all links int *links; // The array containing pointers to adjacency list of every vertices int **neigh; // Counts total size void compute_size(); // Build neigh with deg and links void compute_neigh(); // Allocate memory according to degree_sequence (for constructor use only!!) int alloc(degree_sequence &); // Add edge (a,b). Return FALSE if vertex a is already full. // WARNING : only to be used by havelhakimi(), restore() or constructors inline bool add_edge(int a, int b, int *realdeg) { int deg_a = realdeg[a]; if (deg_a == deg[a]) { return false; } // Check that edge was not already inserted assert(fast_search(neigh[a], int((a == n - 1 ? links + size : neigh[a + 1]) - neigh[a]), b) == NULL); assert(fast_search(neigh[b], int((b == n - 1 ? links + size : neigh[b + 1]) - neigh[b]), a) == NULL); assert(deg[a] < deg_a); int deg_b = realdeg[b]; if (IS_HASH(deg_a)) { *H_add(neigh[a], HASH_EXPAND(deg_a), b) = b; } else { neigh[a][deg[a]] = b; } if (IS_HASH(deg_b)) { *H_add(neigh[b], HASH_EXPAND(deg_b), a) = a; } else { neigh[b][deg[b]] = a; } deg[a]++; deg[b]++; // Check that edge was actually inserted assert(fast_search(neigh[a], int((a == n - 1 ? links + size : neigh[a + 1]) - neigh[a]), b) != NULL); assert(fast_search(neigh[b], int((b == n - 1 ? links + size : neigh[b + 1]) - neigh[b]), a) != NULL); return true; } // Swap edges inline void swap_edges(int from1, int to1, int from2, int to2) { H_rpl(neigh[from1], deg[from1], to1, to2); H_rpl(neigh[from2], deg[from2], to2, to1); H_rpl(neigh[to1], deg[to1], from1, from2); H_rpl(neigh[to2], deg[to2], from2, from1); } // Backup graph [sizeof(int) bytes per edge] int* backup(); // Test if vertex is in an isolated component of size dmax. void depth_isolated(int v, long &calls, int &left_to_explore, int dmax, int * &Kbuff, bool *visited); public: //degree of v inline int degree(const int v) { return deg[v]; }; // For debug purposes : verify validity of the graph (symetry, simplicity) bool verify(); // Destroy deg[], neigh[] and links[] ~graph_molloy_hash(); // Allocate memory for the graph. Create deg and links. No edge is created. graph_molloy_hash(degree_sequence &); // Create graph from hard copy graph_molloy_hash(int *); // Create hard copy of graph int *hard_copy(); // Restore from backup void restore(int* back); //Clear hash tables void init(); // nb arcs inline int nbarcs() { return a; }; // nb vertices inline int nbvertices() { return n; }; // print graph in SUCC_LIST mode, in stdout void print(FILE *f = stdout); int print(igraph_t *graph); // Test if graph is connected bool is_connected(); // is edge ? inline bool is_edge(int a, int b) { assert(H_is(neigh[a], deg[a], b) == (fast_search(neigh[a], HASH_SIZE(deg[a]), b) != NULL)); assert(H_is(neigh[b], deg[b], a) == (fast_search(neigh[b], HASH_SIZE(deg[b]), a) != NULL)); assert(H_is(neigh[a], deg[a], b) == H_is(neigh[b], deg[b], a)); if (deg[a] < deg[b]) { return H_is(neigh[a], deg[a], b); } else { return H_is(neigh[b], deg[b], a); } } // Random edge swap ATTEMPT. Return 1 if attempt was a succes, 0 otherwise int random_edge_swap(int K = 0, int *Kbuff = NULL, bool *visited = NULL); // Connected Shuffle unsigned long shuffle(unsigned long, unsigned long, int type); // Optimal window for the gkantsidis heuristics int optimal_window(); // Average unitary cost per post-validated edge swap, for some window double average_cost(int T, int *back, double min_cost); // Get caracteristic K double eval_K(int quality = 100); // Get effective K double effective_K(int K, int quality = 10000); // Try to shuffle T times. Return true if at the end, the graph was still connected. bool try_shuffle(int T, int K, int *back = NULL); /*_____________________________________________________________________________ Not to use anymore : use graph_molloy_opt class instead private: // breadth-first search. Store the distance (modulo 3) in dist[]. Returns eplorated component size. int width_search(unsigned char *dist, int *buff, int v0=0); public: // Create graph graph_molloy_hash(FILE *f); // Bind the graph avoiding multiple edges or self-edges (return false if fail) bool havelhakimi(); // Get the graph connected (return false if fail) bool make_connected(); // "Fab" Shuffle (Optimized heuristic of Gkantsidis algo.) long long fab_connected_shuffle(long long); // Naive Shuffle long long slow_connected_shuffle(long long); // Maximum degree int max_degree(); // compute vertex betweenness : for each vertex, a unique random shortest path is chosen. // this choice is consistent (if shortest path from a to c goes through b and then d, // then shortest path from a to d goes through b). If(trivial path), also count all the // shortest paths where vertex is an extremity int *vertex_betweenness_rsp(bool trivial_path); // same, but when multiple shortest path are possible, average the weights. double *vertex_betweenness_asp(bool trivial_path); //___________________________________________________________________________________ //*/ }; } // namespace gengraph #endif //GRAPH_MOLLOY_HASH_H python-igraph-0.8.0/vendor/source/igraph/src/walktrap_communities.h0000644000076500000240000001553513614300625026021 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ /* The original version of this file was written by Pascal Pons The original copyright notice follows here. The FSF address was fixed by Tamas Nepusz */ // File: communities.h //----------------------------------------------------------------------------- // Walktrap v0.2 -- Finds community structure of networks using random walks // Copyright (C) 2004-2005 Pascal Pons // // This program is free software; you can redistribute it and/or modify // it under the terms of the GNU General Public License as published by // the Free Software Foundation; either version 2 of the License, or // (at your option) any later version. // // This program is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU General Public License for more details. // // You should have received a copy of the GNU General Public License // along with this program; if not, write to the Free Software // Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA // 02110-1301 USA //----------------------------------------------------------------------------- // Author : Pascal Pons // Email : pascal.pons@gmail.com // Web page : http://www-rp.lip6.fr/~latapy/PP/walktrap.html // Location : Paris, France // Time : June 2005 //----------------------------------------------------------------------------- // see readme.txt for more details #ifndef COMMUNITIES_H #define COMMUNITIES_H #include "walktrap_graph.h" #include "walktrap_heap.h" #include "igraph_community.h" #include "config.h" namespace igraph { namespace walktrap { class Communities; class Probabilities { public: static IGRAPH_THREAD_LOCAL float* tmp_vector1; // static IGRAPH_THREAD_LOCAL float* tmp_vector2; // static IGRAPH_THREAD_LOCAL int* id; // static IGRAPH_THREAD_LOCAL int* vertices1; // static IGRAPH_THREAD_LOCAL int* vertices2; // static IGRAPH_THREAD_LOCAL int current_id; // static IGRAPH_THREAD_LOCAL Communities* C; // pointer to all the communities static IGRAPH_THREAD_LOCAL int length; // length of the random walks int size; // number of probabilities stored int* vertices; // the vertices corresponding to the stored probabilities, 0 if all the probabilities are stored float* P; // the probabilities long memory(); // the memory (in Bytes) used by the object double compute_distance(const Probabilities* P2) const; // compute the squared distance r^2 between this probability vector and P2 Probabilities(int community); // compute the probability vector of a community Probabilities(int community1, int community2); // merge the probability vectors of two communities in a new one // the two communities must have their probability vectors stored ~Probabilities(); // destructor }; class Community { public: Neighbor* first_neighbor; // first item of the list of adjacent communities Neighbor* last_neighbor; // last item of the list of adjacent communities int this_community; // number of this community int first_member; // number of the first vertex of the community int last_member; // number of the last vertex of the community int size; // number of members of the community Probabilities* P; // the probability vector, 0 if not stored. float sigma; // sigma(C) of the community float internal_weight; // sum of the weight of the internal edges float total_weight; // sum of the weight of all the edges of the community (an edge between two communities is a half-edge for each community) int sub_communities[2]; // the two sub sommunities, -1 if no sub communities; int sub_community_of; // number of the community in which this community has been merged // 0 if the community is active // -1 if the community is not used void merge(Community &C1, Community &C2); // create a new community by merging C1 an C2 void add_neighbor(Neighbor* N); void remove_neighbor(Neighbor* N); float min_delta_sigma(); // compute the minimal delta sigma among all the neighbors of this community Community(); // create an empty community ~Community(); // destructor }; class Communities { private: long max_memory; // size in Byte of maximal memory usage, -1 for no limit igraph_matrix_t *merges; long int mergeidx; igraph_vector_t *modularity; public: long memory_used; // in bytes Min_delta_sigma_heap* min_delta_sigma; // the min delta_sigma of the community with a saved probability vector (for memory management) Graph* G; // the graph int* members; // the members of each community represented as a chained list. // a community points to the first_member the array which contains // the next member (-1 = end of the community) Neighbor_heap* H; // the distances between adjacent communities. Community* communities; // array of the communities int nb_communities; // number of valid communities int nb_active_communities; // number of active communities Communities(Graph* G, int random_walks_length = 3, long max_memory = -1, igraph_matrix_t *merges = 0, igraph_vector_t *modularity = 0); // Constructor ~Communities(); // Destructor void merge_communities(Neighbor* N); // create a community by merging two existing communities double merge_nearest_communities(); double compute_delta_sigma(int c1, int c2); // compute delta_sigma(c1,c2) void remove_neighbor(Neighbor* N); void add_neighbor(Neighbor* N); void update_neighbor(Neighbor* N, float new_delta_sigma); void manage_memory(); }; } } /* end of namespaces */ #endif python-igraph-0.8.0/vendor/source/igraph/src/igraph_interrupt_internal.h0000644000076500000240000000401413614300625027030 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2003-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_INTERRUPT_INTERNAL_H #define IGRAPH_INTERRUPT_INTERNAL_H #include "config.h" #include "igraph_interrupt.h" #undef __BEGIN_DECLS #undef __END_DECLS #ifdef __cplusplus #define __BEGIN_DECLS extern "C" { #define __END_DECLS } #else #define __BEGIN_DECLS /* empty */ #define __END_DECLS /* empty */ #endif __BEGIN_DECLS extern IGRAPH_THREAD_LOCAL igraph_interruption_handler_t *igraph_i_interruption_handler; /** * \define IGRAPH_ALLOW_INTERRUPTION * \brief * * This macro should be called when interruption is allowed. It calls * \ref igraph_allow_interruption() with the proper parameters and if that returns * anything but \c IGRAPH_SUCCESS then * the macro returns the "calling" function as well, with the proper * error code (\c IGRAPH_INTERRUPTED). */ #define IGRAPH_ALLOW_INTERRUPTION() \ do { \ if (igraph_i_interruption_handler) { if (igraph_allow_interruption(NULL) != IGRAPH_SUCCESS) return IGRAPH_INTERRUPTED; \ } } while (0) #define IGRAPH_ALLOW_INTERRUPTION_NORETURN() \ do { \ if (igraph_i_interruption_handler) { igraph_allow_interruption(NULL); } \ } while (0) __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/src/operators.c0000644000076500000240000013116013614300625023562 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_operators.h" #include "igraph_error.h" #include "igraph_memory.h" #include "igraph_interrupt_internal.h" #include "igraph_interface.h" #include "igraph_constructors.h" #include "igraph_adjlist.h" #include "igraph_attributes.h" #include "igraph_conversion.h" #include "igraph_qsort.h" #include #include "config.h" /** * \function igraph_disjoint_union * \brief Creates the union of two disjoint graphs * * * First the vertices of the second graph will be relabeled with new * vertex ids to have two disjoint sets of vertex ids, then the union * of the two graphs will be formed. * If the two graphs have |V1| and |V2| vertices and |E1| and |E2| * edges respectively then the new graph will have |V1|+|V2| vertices * and |E1|+|E2| edges. * * * Both graphs need to have the same directedness, ie. either both * directed or both undirected. * * * The current version of this function cannot handle graph, vertex * and edge attributes, they will be lost. * * \param res Pointer to an uninitialized graph object, the result * will stored here. * \param left The first graph. * \param right The second graph. * \return Error code. * \sa \ref igraph_disjoint_union_many() for creating the disjoint union * of more than two graphs, \ref igraph_union() for non-disjoint * union. * * Time complexity: O(|V1|+|V2|+|E1|+|E2|). * * \example examples/simple/igraph_disjoint_union.c */ int igraph_disjoint_union(igraph_t *res, const igraph_t *left, const igraph_t *right) { long int no_of_nodes_left = igraph_vcount(left); long int no_of_nodes_right = igraph_vcount(right); long int no_of_edges_left = igraph_ecount(left); long int no_of_edges_right = igraph_ecount(right); igraph_vector_t edges; igraph_bool_t directed_left = igraph_is_directed(left); igraph_integer_t from, to; long int i; if (directed_left != igraph_is_directed(right)) { IGRAPH_ERROR("Cannot union directed and undirected graphs", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_CHECK(igraph_vector_reserve(&edges, 2 * (no_of_edges_left + no_of_edges_right))); for (i = 0; i < no_of_edges_left; i++) { igraph_edge(left, (igraph_integer_t) i, &from, &to); igraph_vector_push_back(&edges, from); igraph_vector_push_back(&edges, to); } for (i = 0; i < no_of_edges_right; i++) { igraph_edge(right, (igraph_integer_t) i, &from, &to); igraph_vector_push_back(&edges, from + no_of_nodes_left); igraph_vector_push_back(&edges, to + no_of_nodes_left); } IGRAPH_CHECK(igraph_create(res, &edges, (igraph_integer_t) (no_of_nodes_left + no_of_nodes_right), directed_left)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_disjoint_union_many * \brief The disjint union of many graphs. * * * First the vertices in the graphs will be relabeled with new vertex * ids to have pairwise disjoint vertex id sets and then the union of * the graphs is formed. * The number of vertices and edges in the result is the total number * of vertices and edges in the graphs. * * * Both graphs need to have the same directedness, ie. either both * directed or both undirected. * * * The current version of this function cannot handle graph, vertex * and edge attributes, they will be lost. * * \param res Pointer to an uninitialized graph object, the result of * the operation will be stored here. * \param graphs Pointer vector, contains pointers to initialized * graph objects. * \return Error code. * \sa \ref igraph_disjoint_union() for an easier syntax if you have * only two graphs, \ref igraph_union_many() for non-disjoint union. * * Time complexity: O(|V|+|E|), the number of vertices plus the number * of edges in the result. */ int igraph_disjoint_union_many(igraph_t *res, const igraph_vector_ptr_t *graphs) { long int no_of_graphs = igraph_vector_ptr_size(graphs); igraph_bool_t directed = 1; igraph_vector_t edges; long int no_of_edges = 0; long int shift = 0; igraph_t *graph; long int i, j; igraph_integer_t from, to; if (no_of_graphs != 0) { graph = VECTOR(*graphs)[0]; directed = igraph_is_directed(graph); for (i = 0; i < no_of_graphs; i++) { graph = VECTOR(*graphs)[i]; no_of_edges += igraph_ecount(graph); if (directed != igraph_is_directed(graph)) { IGRAPH_ERROR("Cannot union directed and undirected graphs", IGRAPH_EINVAL); } } } IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_CHECK(igraph_vector_reserve(&edges, 2 * no_of_edges)); for (i = 0; i < no_of_graphs; i++) { long int ec; graph = VECTOR(*graphs)[i]; ec = igraph_ecount(graph); for (j = 0; j < ec; j++) { igraph_edge(graph, (igraph_integer_t) j, &from, &to); igraph_vector_push_back(&edges, from + shift); igraph_vector_push_back(&edges, to + shift); } shift += igraph_vcount(graph); } IGRAPH_CHECK(igraph_create(res, &edges, (igraph_integer_t) shift, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_i_order_edgelist_cmp(void *edges, const void *e1, const void *e2) { igraph_vector_t *edgelist = edges; long int edge1 = (*(const long int*) e1) * 2; long int edge2 = (*(const long int*) e2) * 2; long int from1 = VECTOR(*edgelist)[edge1]; long int from2 = VECTOR(*edgelist)[edge2]; if (from1 < from2) { return -1; } else if (from1 > from2) { return 1; } else { long int to1 = VECTOR(*edgelist)[edge1 + 1]; long int to2 = VECTOR(*edgelist)[edge2 + 1]; if (to1 < to2) { return -1; } else if (to1 > to2) { return 1; } else { return 0; } } } #define IGRAPH_MODE_UNION 1 #define IGRAPH_MODE_INTERSECTION 2 int igraph_i_merge(igraph_t *res, int mode, const igraph_t *left, const igraph_t *right, igraph_vector_t *edge_map1, igraph_vector_t *edge_map2) { long int no_of_nodes_left = igraph_vcount(left); long int no_of_nodes_right = igraph_vcount(right); long int no_of_nodes; long int no_edges_left = igraph_ecount(left); long int no_edges_right = igraph_ecount(right); igraph_bool_t directed = igraph_is_directed(left); igraph_vector_t edges; igraph_vector_t edges1, edges2; igraph_vector_long_t order1, order2; long int i, j, eptr = 0; long int idx1, idx2, edge1 = -1, edge2 = -1, from1 = -1, from2 = -1, to1 = -1, to2 = -1; igraph_bool_t l; if (directed != igraph_is_directed(right)) { IGRAPH_ERROR("Cannot make union or intersection of directed " "and undirected graph", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_VECTOR_INIT_FINALLY(&edges1, no_edges_left * 2); IGRAPH_VECTOR_INIT_FINALLY(&edges2, no_edges_right * 2); IGRAPH_CHECK(igraph_vector_long_init(&order1, no_edges_left)); IGRAPH_FINALLY(igraph_vector_long_destroy, &order1); IGRAPH_CHECK(igraph_vector_long_init(&order2, no_edges_right)); IGRAPH_FINALLY(igraph_vector_long_destroy, &order2); if (edge_map1) { switch (mode) { case IGRAPH_MODE_UNION: IGRAPH_CHECK(igraph_vector_resize(edge_map1, no_edges_left)); break; case IGRAPH_MODE_INTERSECTION: igraph_vector_clear(edge_map1); break; } } if (edge_map2) { switch (mode) { case IGRAPH_MODE_UNION: IGRAPH_CHECK(igraph_vector_resize(edge_map2, no_edges_right)); break; case IGRAPH_MODE_INTERSECTION: igraph_vector_clear(edge_map2); break; } } no_of_nodes = no_of_nodes_left > no_of_nodes_right ? no_of_nodes_left : no_of_nodes_right; /* We merge the two edge lists. We need to sort them first. For undirected graphs, we also need to make sure that for every edge, that larger (non-smaller) vertex id is in the second column. */ IGRAPH_CHECK(igraph_get_edgelist(left, &edges1, /*bycol=*/ 0)); IGRAPH_CHECK(igraph_get_edgelist(right, &edges2, /*bycol=*/ 0)); if (!directed) { for (i = 0, j = 0; i < no_edges_left; i++, j += 2) { if (VECTOR(edges1)[j] > VECTOR(edges1)[j + 1]) { long int tmp = VECTOR(edges1)[j]; VECTOR(edges1)[j] = VECTOR(edges1)[j + 1]; VECTOR(edges1)[j + 1] = tmp; } } for (i = 0, j = 0; i < no_edges_right; i++, j += 2) { if (VECTOR(edges2)[j] > VECTOR(edges2)[j + 1]) { long int tmp = VECTOR(edges2)[j]; VECTOR(edges2)[j] = VECTOR(edges2)[j + 1]; VECTOR(edges2)[j + 1] = tmp; } } } for (i = 0; i < no_edges_left; i++) { VECTOR(order1)[i] = i; } for (i = 0; i < no_edges_right; i++) { VECTOR(order2)[i] = i; } igraph_qsort_r(VECTOR(order1), no_edges_left, sizeof(VECTOR(order1)[0]), &edges1, igraph_i_order_edgelist_cmp); igraph_qsort_r(VECTOR(order2), no_edges_right, sizeof(VECTOR(order2)[0]), &edges2, igraph_i_order_edgelist_cmp); #define INC1() if ( (++idx1) < no_edges_left) { \ edge1 = VECTOR(order1)[idx1]; \ from1 = VECTOR(edges1)[2*edge1]; \ to1 = VECTOR(edges1)[2*edge1+1]; \ } #define INC2() if ( (++idx2) < no_edges_right) { \ edge2 = VECTOR(order2)[idx2]; \ from2 = VECTOR(edges2)[2*edge2]; \ to2 = VECTOR(edges2)[2*edge2+1]; \ } idx1 = idx2 = -1; INC1(); INC2(); #define CONT() switch (mode) { \ case IGRAPH_MODE_UNION: \ l = idx1 < no_edges_left || idx2 < no_edges_right; \ break; \ case IGRAPH_MODE_INTERSECTION: \ l = idx1 < no_edges_left && idx2 < no_edges_right; \ break; \ } CONT(); while (l) { if (idx2 >= no_edges_right || (idx1 < no_edges_left && from1 < from2) || (idx1 < no_edges_left && from1 == from2 && to1 < to2)) { /* Edge from first graph */ if (mode == IGRAPH_MODE_UNION) { IGRAPH_CHECK(igraph_vector_push_back(&edges, from1)); IGRAPH_CHECK(igraph_vector_push_back(&edges, to1)); if (edge_map1) { VECTOR(*edge_map1)[edge1] = eptr; } eptr++; } INC1(); } else if (idx1 >= no_edges_left || (idx2 < no_edges_right && from2 < from1) || (idx2 < no_edges_right && from1 == from2 && to2 < to1)) { /* Edge from second graph */ if (mode == IGRAPH_MODE_UNION) { IGRAPH_CHECK(igraph_vector_push_back(&edges, from2)); IGRAPH_CHECK(igraph_vector_push_back(&edges, to2)); if (edge_map2) { VECTOR(*edge_map2)[edge2] = eptr; } eptr++; } INC2(); } else { /* Edge from both */ IGRAPH_CHECK(igraph_vector_push_back(&edges, from1)); IGRAPH_CHECK(igraph_vector_push_back(&edges, to1)); if (mode == IGRAPH_MODE_UNION) { if (edge_map1) { VECTOR(*edge_map1)[edge1] = eptr; } if (edge_map2) { VECTOR(*edge_map2)[edge2] = eptr; } } else if (mode == IGRAPH_MODE_INTERSECTION) { if (edge_map1) { IGRAPH_CHECK(igraph_vector_push_back(edge_map1, edge1)); } if (edge_map2) { IGRAPH_CHECK(igraph_vector_push_back(edge_map2, edge2)); } } eptr++; INC1(); INC2(); } CONT(); } #undef INC1 #undef INC2 igraph_vector_long_destroy(&order2); igraph_vector_long_destroy(&order1); igraph_vector_destroy(&edges2); igraph_vector_destroy(&edges1); IGRAPH_FINALLY_CLEAN(4); IGRAPH_CHECK(igraph_create(res, &edges, no_of_nodes, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_intersection * \brief Collect the common edges from two graphs. * * * The result graph contains only edges present both in the first and * the second graph. The number of vertices in the result graph is the * same as the larger from the two arguments. * * \param res Pointer to an uninitialized graph object. This will * contain the result of the operation. * \param left The first operand, a graph object. * \param right The second operand, a graph object. * \param edge_map1 Null pointer, or an initialized \type igraph_vector_t. * If the latter, then a mapping from the edges of the result graph, to * the edges of the \p left input graph is stored here. * \param edge_map2 Null pointer, or an \type igraph_vector_t. The same * as \p edge_map1, but for the \p right input graph. * \return Error code. * \sa \ref igraph_intersection_many() to calculate the intersection * of many graphs at once, \ref igraph_union(), \ref * igraph_difference() for other operators. * * Time complexity: O(|V|+|E|), |V| is the number of nodes, |E| * is the number of edges in the smaller graph of the two. (The one * containing less vertices is considered smaller.) * * \example examples/simple/igraph_intersection.c */ int igraph_intersection(igraph_t *res, const igraph_t *left, const igraph_t *right, igraph_vector_t *edge_map1, igraph_vector_t *edge_map2) { return igraph_i_merge(res, IGRAPH_MODE_INTERSECTION, left, right, edge_map1, edge_map2); } void igraph_i_union_many_free(igraph_vector_ptr_t *v) { long int i, n = igraph_vector_ptr_size(v); for (i = 0; i < n; i++) { if (VECTOR(*v)[i] != 0) { igraph_vector_destroy(VECTOR(*v)[i]); igraph_Free(VECTOR(*v)[i]); } } igraph_vector_ptr_destroy(v); } void igraph_i_union_many_free2(igraph_vector_ptr_t *v) { long int i, n = igraph_vector_ptr_size(v); for (i = 0; i < n; i++) { if (VECTOR(*v)[i] != 0) { igraph_vector_long_destroy(VECTOR(*v)[i]); igraph_Free(VECTOR(*v)[i]); } } igraph_vector_ptr_destroy(v); } void igraph_i_union_many_free3(igraph_vector_ptr_t *v) { long int i, n = igraph_vector_ptr_size(v); for (i = 0; i < n; i++) { if (VECTOR(*v)[i] != 0) { igraph_vector_destroy(VECTOR(*v)[i]); igraph_Free(VECTOR(*v)[i]); } } } /** * \function igraph_intersection_many * \brief The intersection of more than two graphs. * * * This function calculates the intersection of the graphs stored in * the \c graphs argument. Only those edges will be included in the * result graph which are part of every graph in \c graphs. * * * The number of vertices in the result graph will be the maximum * number of vertices in the argument graphs. * * \param res Pointer to an uninitialized graph object, the result of * the operation will be stored here. * \param graphs Pointer vector, contains pointers to graphs objects, * the operands of the intersection operator. * \param edgemaps If not a null pointer, then it must be an initialized * pointer vector and the mappings of edges from the graphs to the * result graph will be stored here, in the same order as * \p graphs. Each mapping is stored in a separate * \type igraph_vector_t object. For the edges that are not in * the intersection, -1 is stored. * \return Error code. * \sa \ref igraph_intersection() for the intersection of two graphs, * \ref igraph_union_many(), \ref igraph_union() and \ref * igraph_difference() for other operators. * * Time complexity: O(|V|+|E|), |V| is the number of vertices, * |E| is the number of edges in the smallest graph (ie. the graph having * the less vertices). */ int igraph_intersection_many(igraph_t *res, const igraph_vector_ptr_t *graphs, igraph_vector_ptr_t *edgemaps) { long int no_of_graphs = igraph_vector_ptr_size(graphs); long int no_of_nodes = 0; igraph_bool_t directed = 1; igraph_vector_t edges; igraph_vector_ptr_t edge_vects, order_vects; long int i, j, tailfrom = no_of_graphs > 0 ? 0 : -1, tailto = -1; igraph_vector_long_t no_edges; igraph_bool_t allne = no_of_graphs == 0 ? 0 : 1, allsame = 0; long int idx = 0; /* Check directedness */ if (no_of_graphs != 0) { directed = igraph_is_directed(VECTOR(*graphs)[0]); } for (i = 1; i < no_of_graphs; i++) { if (directed != igraph_is_directed(VECTOR(*graphs)[i])) { IGRAPH_ERROR("Cannot intersect directed and undirected graphs", IGRAPH_EINVAL); } } if (edgemaps) { IGRAPH_CHECK(igraph_vector_ptr_resize(edgemaps, no_of_graphs)); igraph_vector_ptr_null(edgemaps); IGRAPH_FINALLY(igraph_i_union_many_free3, edgemaps); } IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_CHECK(igraph_vector_long_init(&no_edges, no_of_graphs)); IGRAPH_FINALLY(igraph_vector_long_destroy, &no_edges); /* Calculate number of nodes, query number of edges */ for (i = 0; i < no_of_graphs; i++) { long int n = igraph_vcount(VECTOR(*graphs)[i]); if (n > no_of_nodes) { no_of_nodes = n; } VECTOR(no_edges)[i] = igraph_ecount(VECTOR(*graphs)[i]); allne = allne && VECTOR(no_edges)[i] > 0; } if (edgemaps) { for (i = 0; i < no_of_graphs; i++) { VECTOR(*edgemaps)[i] = igraph_Calloc(1, igraph_vector_t); if (!VECTOR(*edgemaps)[i]) { IGRAPH_ERROR("Cannot intersect graphs", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_init(VECTOR(*edgemaps)[i], VECTOR(no_edges)[i])); igraph_vector_fill(VECTOR(*edgemaps)[i], -1); } } /* Allocate memory for the edge lists and their index vectors */ if (no_of_graphs != 0) { IGRAPH_CHECK(igraph_vector_ptr_init(&edge_vects, no_of_graphs)); IGRAPH_FINALLY(igraph_i_union_many_free, &edge_vects); IGRAPH_CHECK(igraph_vector_ptr_init(&order_vects, no_of_graphs)); IGRAPH_FINALLY(igraph_i_union_many_free2, &order_vects); } for (i = 0; i < no_of_graphs; i++) { VECTOR(edge_vects)[i] = igraph_Calloc(1, igraph_vector_t); VECTOR(order_vects)[i] = igraph_Calloc(1, igraph_vector_long_t); if (! VECTOR(edge_vects)[i] || ! VECTOR(order_vects)[i]) { IGRAPH_ERROR("Cannot intersect graphs", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_init(VECTOR(edge_vects)[i], 2 * VECTOR(no_edges)[i])); IGRAPH_CHECK(igraph_vector_long_init(VECTOR(order_vects)[i], VECTOR(no_edges)[i])); } /* Query and sort the edge lists */ for (i = 0; i < no_of_graphs; i++) { long int k, j, n = VECTOR(no_edges)[i]; igraph_vector_t *edges = VECTOR(edge_vects)[i]; igraph_vector_long_t *order = VECTOR(order_vects)[i]; IGRAPH_CHECK(igraph_get_edgelist(VECTOR(*graphs)[i], edges, /*bycol=*/0)); if (!directed) { for (k = 0, j = 0; k < n; k++, j += 2) { if (VECTOR(*edges)[j] > VECTOR(*edges)[j + 1]) { long int tmp = VECTOR(*edges)[j]; VECTOR(*edges)[j] = VECTOR(*edges)[j + 1]; VECTOR(*edges)[j + 1] = tmp; } } } for (k = 0; k < n; k++) { VECTOR(*order)[k] = k; } igraph_qsort_r(VECTOR(*order), n, sizeof(VECTOR(*order)[0]), edges, igraph_i_order_edgelist_cmp); } /* Do the merge. We work from the end of the edge lists, because then we don't have to keep track of where we are right now in the edge and order lists. We find the "largest" edge, and if it is present in all graphs, then we copy it to the result. We remove all instances of this edge. */ while (allne) { /* Look for the smallest tail element */ for (j = 0, tailfrom = LONG_MAX, tailto = LONG_MAX; j < no_of_graphs; j++) { long int edge = igraph_vector_long_tail(VECTOR(order_vects)[j]); igraph_vector_t *ev = VECTOR(edge_vects)[j]; long int from = VECTOR(*ev)[2 * edge]; long int to = VECTOR(*ev)[2 * edge + 1]; if (from < tailfrom || (from == tailfrom && to < tailto)) { tailfrom = from; tailto = to; } } /* OK, now remove all elements from the tail(s) that are bigger than the smallest tail element. */ for (j = 0, allsame = 1; j < no_of_graphs; j++) { long int from = -1, to = -1; while (1) { long int edge = igraph_vector_long_tail(VECTOR(order_vects)[j]); igraph_vector_t *ev = VECTOR(edge_vects)[j]; from = VECTOR(*ev)[2 * edge]; to = VECTOR(*ev)[2 * edge + 1]; if (from > tailfrom || (from == tailfrom && to > tailto)) { igraph_vector_long_pop_back(VECTOR(order_vects)[j]); if (igraph_vector_long_empty(VECTOR(order_vects)[j])) { allne = 0; break; } } else { break; } } if (from != tailfrom || to != tailto) { allsame = 0; } } /* Add the edge, if the smallest tail element was present in all graphs. */ if (allsame) { IGRAPH_CHECK(igraph_vector_push_back(&edges, tailfrom)); IGRAPH_CHECK(igraph_vector_push_back(&edges, tailto)); } /* Drop edges matching the smalles tail elements from the order vectors, build edge maps */ if (allne) { for (j = 0; j < no_of_graphs; j++) { long int edge = igraph_vector_long_tail(VECTOR(order_vects)[j]); igraph_vector_t *ev = VECTOR(edge_vects)[j]; long int from = VECTOR(*ev)[2 * edge]; long int to = VECTOR(*ev)[2 * edge + 1]; if (from == tailfrom && to == tailto) { igraph_vector_long_pop_back(VECTOR(order_vects)[j]); if (igraph_vector_long_empty(VECTOR(order_vects)[j])) { allne = 0; } if (edgemaps && allsame) { igraph_vector_t *map = VECTOR(*edgemaps)[j]; VECTOR(*map)[edge] = idx; } } } if (allsame) { idx++; } } } /* while allne */ if (no_of_graphs > 0) { igraph_i_union_many_free2(&order_vects); igraph_i_union_many_free(&edge_vects); IGRAPH_FINALLY_CLEAN(2); } igraph_vector_long_destroy(&no_edges); IGRAPH_FINALLY_CLEAN(1); IGRAPH_CHECK(igraph_create(res, &edges, (igraph_integer_t) no_of_nodes, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); if (edgemaps) { IGRAPH_FINALLY_CLEAN(1); } return 0; } /** * \function igraph_union * \brief Calculates the union of two graphs. * * * The number of vertices in the result is that of the larger graph * from the two arguments. The result graph contains edges which are * present in at least one of the operand graphs. * * \param res Pointer to an uninitialized graph object, the result * will be stored here. * \param left The first graph. * \param right The second graph. * \param edge_map1 Pointer to an initialized vector or a null pointer. * If not a null pointer, it will contain a mapping from the edges * of the first argument graph (\p left) to the edges of the * result graph. * \param edge_map2 The same as \p edge_map1, but for the second * graph, \p right. * \return Error code. * \sa \ref igraph_union_many() for the union of many graphs, * \ref igraph_intersection() and \ref igraph_difference() for other * operators. * * Time complexity: O(|V|+|E|), |V| is the number of * vertices, |E| the number of edges in the result graph. * * \example examples/simple/igraph_union.c */ int igraph_union(igraph_t *res, const igraph_t *left, const igraph_t *right, igraph_vector_t *edge_map1, igraph_vector_t *edge_map2) { return igraph_i_merge(res, IGRAPH_MODE_UNION, left, right, edge_map1, edge_map2); } /** * \function igraph_union_many * \brief Creates the union of many graphs. * * * The result graph will contain as many vertices as the largest graph * among the arguments does, and an edge will be included in it if it * is part of at least one operand graph. * * * The directedness of the operand graphs must be the same. * * \param res Pointer to an uninitialized graph object, this will * contain the result. * \param graphs Pointer vector, contains pointers to the operands of * the union operator, graph objects of course. * \param edgemaps If not a null pointer, then it must be an initialized * pointer vector and the mappings of edges from the graphs to the * result graph will be stored here, in the same order as * \p graphs. Each mapping is stored in a separate * \type igraph_vector_t object. * \return Error code. * \sa \ref igraph_union() for the union of two graphs, \ref * igraph_intersection_many(), \ref igraph_intersection() and \ref * igraph_difference for other operators. * * * Time complexity: O(|V|+|E|), |V| is the number of vertices * in largest graph and |E| is the number of edges in the result graph. * * \example examples/simple/igraph_union.c */ int igraph_union_many(igraph_t *res, const igraph_vector_ptr_t *graphs, igraph_vector_ptr_t *edgemaps) { long int no_of_graphs = igraph_vector_ptr_size(graphs); long int no_of_nodes = 0; igraph_bool_t directed = 1; igraph_vector_t edges; igraph_vector_ptr_t edge_vects, order_vects; igraph_vector_long_t no_edges; long int i, j, tailfrom = no_of_graphs > 0 ? 0 : -1, tailto = -1; long int idx = 0; /* Check directedness */ if (no_of_graphs != 0) { directed = igraph_is_directed(VECTOR(*graphs)[0]); no_of_nodes = igraph_vcount(VECTOR(*graphs)[0]); } for (i = 1; i < no_of_graphs; i++) { if (directed != igraph_is_directed(VECTOR(*graphs)[i])) { IGRAPH_ERROR("Cannot union directed and undirected graphs", IGRAPH_EINVAL); } } if (edgemaps) { IGRAPH_CHECK(igraph_vector_ptr_resize(edgemaps, no_of_graphs)); igraph_vector_ptr_null(edgemaps); IGRAPH_FINALLY(igraph_i_union_many_free3, edgemaps); } IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_CHECK(igraph_vector_long_init(&no_edges, no_of_graphs)); IGRAPH_FINALLY(igraph_vector_long_destroy, &no_edges); /* Calculate number of nodes, query number of edges */ for (i = 0; i < no_of_graphs; i++) { long int n = igraph_vcount(VECTOR(*graphs)[i]); if (n > no_of_nodes) { no_of_nodes = n; } VECTOR(no_edges)[i] = igraph_ecount(VECTOR(*graphs)[i]); } if (edgemaps) { for (i = 0; i < no_of_graphs; i++) { VECTOR(*edgemaps)[i] = igraph_Calloc(1, igraph_vector_t); if (!VECTOR(*edgemaps)[i]) { IGRAPH_ERROR("Cannot union graphs", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_init(VECTOR(*edgemaps)[i], VECTOR(no_edges)[i])); } } /* Allocate memory for the edge lists and their index vectors */ if (no_of_graphs != 0) { IGRAPH_CHECK(igraph_vector_ptr_init(&edge_vects, no_of_graphs)); IGRAPH_FINALLY(igraph_i_union_many_free, &edge_vects); IGRAPH_CHECK(igraph_vector_ptr_init(&order_vects, no_of_graphs)); IGRAPH_FINALLY(igraph_i_union_many_free2, &order_vects); } for (i = 0; i < no_of_graphs; i++) { VECTOR(edge_vects)[i] = igraph_Calloc(1, igraph_vector_t); VECTOR(order_vects)[i] = igraph_Calloc(1, igraph_vector_long_t); if (! VECTOR(edge_vects)[i] || ! VECTOR(order_vects)[i]) { IGRAPH_ERROR("Cannot union graphs", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_init(VECTOR(edge_vects)[i], 2 * VECTOR(no_edges)[i])); IGRAPH_CHECK(igraph_vector_long_init(VECTOR(order_vects)[i], VECTOR(no_edges)[i])); } /* Query and sort the edge lists */ for (i = 0; i < no_of_graphs; i++) { long int k, j, n = VECTOR(no_edges)[i]; igraph_vector_t *edges = VECTOR(edge_vects)[i]; igraph_vector_long_t *order = VECTOR(order_vects)[i]; IGRAPH_CHECK(igraph_get_edgelist(VECTOR(*graphs)[i], edges, /*bycol=*/0)); if (!directed) { for (k = 0, j = 0; k < n; k++, j += 2) { if (VECTOR(*edges)[j] > VECTOR(*edges)[j + 1]) { long int tmp = VECTOR(*edges)[j]; VECTOR(*edges)[j] = VECTOR(*edges)[j + 1]; VECTOR(*edges)[j + 1] = tmp; } } } for (k = 0; k < n; k++) { VECTOR(*order)[k] = k; } igraph_qsort_r(VECTOR(*order), n, sizeof(VECTOR(*order)[0]), edges, igraph_i_order_edgelist_cmp); } while (tailfrom >= 0) { /* Get the largest tail element */ tailfrom = tailto = -1; for (j = 0; j < no_of_graphs; j++) { if (!igraph_vector_long_empty(VECTOR(order_vects)[j])) { long int edge = igraph_vector_long_tail(VECTOR(order_vects)[j]); igraph_vector_t *ev = VECTOR(edge_vects)[j]; long int from = VECTOR(*ev)[2 * edge]; long int to = VECTOR(*ev)[2 * edge + 1]; if (from > tailfrom || (from == tailfrom && to > tailto)) { tailfrom = from; tailto = to; } } } if (tailfrom < 0) { continue; } /* add the edge */ IGRAPH_CHECK(igraph_vector_push_back(&edges, tailfrom)); IGRAPH_CHECK(igraph_vector_push_back(&edges, tailto)); /* update edge lists, we just modify the 'order' vectors */ for (j = 0; j < no_of_graphs; j++) { if (!igraph_vector_long_empty(VECTOR(order_vects)[j])) { long int edge = igraph_vector_long_tail(VECTOR(order_vects)[j]); igraph_vector_t *ev = VECTOR(edge_vects)[j]; long int from = VECTOR(*ev)[2 * edge]; long int to = VECTOR(*ev)[2 * edge + 1]; if (from == tailfrom && to == tailto) { igraph_vector_long_pop_back(VECTOR(order_vects)[j]); if (edgemaps) { igraph_vector_t *map = VECTOR(*edgemaps)[j]; VECTOR(*map)[edge] = idx; } } } } idx++; } if (no_of_graphs > 0) { igraph_i_union_many_free2(&order_vects); igraph_i_union_many_free(&edge_vects); IGRAPH_FINALLY_CLEAN(2); } igraph_vector_long_destroy(&no_edges); IGRAPH_FINALLY_CLEAN(1); IGRAPH_CHECK(igraph_create(res, &edges, (igraph_integer_t) no_of_nodes, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); if (edgemaps) { IGRAPH_FINALLY_CLEAN(1); } return 0; } /** * \function igraph_difference * \brief Calculate the difference of two graphs * * * The number of vertices in the result is the number of vertices in * the original graph, ie. the left, first operand. In the results * graph only edges will be included from \c orig which are not * present in \c sub. * * \param res Pointer to an uninitialized graph object, the result * will be stored here. * \param orig The left operand of the operator, a graph object. * \param sub The right operand of the operator, a graph object. * \return Error code. * \sa \ref igraph_intersection() and \ref igraph_union() for other * operators. * * Time complexity: O(|V|+|E|), |V| is the number vertices in * the smaller graph, |E| is the * number of edges in the result graph. * * \example examples/simple/igraph_difference.c */ int igraph_difference(igraph_t *res, const igraph_t *orig, const igraph_t *sub) { /* Quite nasty, but we will use that an edge adjacency list contains the vertices according to the order of the vertex ids at the "other" end of the edge. */ long int no_of_nodes_orig = igraph_vcount(orig); long int no_of_nodes_sub = igraph_vcount(sub); long int no_of_nodes = no_of_nodes_orig; long int smaller_nodes; igraph_bool_t directed = igraph_is_directed(orig); igraph_vector_t edges; igraph_vector_t edge_ids; igraph_vector_int_t *nei1, *nei2; igraph_inclist_t inc_orig, inc_sub; long int i; igraph_integer_t v1, v2; if (directed != igraph_is_directed(sub)) { IGRAPH_ERROR("Cannot subtract directed and undirected graphs", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(&edge_ids, 0); IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_CHECK(igraph_inclist_init(orig, &inc_orig, IGRAPH_OUT)); IGRAPH_FINALLY(igraph_inclist_destroy, &inc_orig); IGRAPH_CHECK(igraph_inclist_init(sub, &inc_sub, IGRAPH_OUT)); IGRAPH_FINALLY(igraph_inclist_destroy, &inc_sub); smaller_nodes = no_of_nodes_orig > no_of_nodes_sub ? no_of_nodes_sub : no_of_nodes_orig; for (i = 0; i < smaller_nodes; i++) { long int n1, n2, e1, e2; IGRAPH_ALLOW_INTERRUPTION(); nei1 = igraph_inclist_get(&inc_orig, i); nei2 = igraph_inclist_get(&inc_sub, i); n1 = igraph_vector_int_size(nei1) - 1; n2 = igraph_vector_int_size(nei2) - 1; while (n1 >= 0 && n2 >= 0) { e1 = (long int) VECTOR(*nei1)[n1]; e2 = (long int) VECTOR(*nei2)[n2]; v1 = IGRAPH_OTHER(orig, e1, i); v2 = IGRAPH_OTHER(sub, e2, i); if (!directed && v1 < i) { n1--; } else if (!directed && v2 < i) { n2--; } else if (v1 > v2) { IGRAPH_CHECK(igraph_vector_push_back(&edge_ids, e1)); IGRAPH_CHECK(igraph_vector_push_back(&edges, i)); IGRAPH_CHECK(igraph_vector_push_back(&edges, v1)); n1--; } else if (v2 > v1) { n2--; } else { n1--; n2--; } } /* Copy remaining edges */ while (n1 >= 0) { e1 = (long int) VECTOR(*nei1)[n1]; v1 = IGRAPH_OTHER(orig, e1, i); if (directed || v1 >= i) { IGRAPH_CHECK(igraph_vector_push_back(&edge_ids, e1)); IGRAPH_CHECK(igraph_vector_push_back(&edges, i)); IGRAPH_CHECK(igraph_vector_push_back(&edges, v1)); } n1--; } } /* copy remaining edges, use the previous value of 'i' */ for (; i < no_of_nodes_orig; i++) { long int n1, e1; nei1 = igraph_inclist_get(&inc_orig, i); n1 = igraph_vector_int_size(nei1) - 1; while (n1 >= 0) { e1 = (long int) VECTOR(*nei1)[n1]; v1 = IGRAPH_OTHER(orig, e1, i); if (directed || v1 >= i) { IGRAPH_CHECK(igraph_vector_push_back(&edge_ids, e1)); IGRAPH_CHECK(igraph_vector_push_back(&edges, i)); IGRAPH_CHECK(igraph_vector_push_back(&edges, v1)); } n1--; } } igraph_inclist_destroy(&inc_sub); igraph_inclist_destroy(&inc_orig); IGRAPH_FINALLY_CLEAN(2); IGRAPH_CHECK(igraph_create(res, &edges, (igraph_integer_t) no_of_nodes, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); /* Attributes */ if (orig->attr) { IGRAPH_I_ATTRIBUTE_DESTROY(res); IGRAPH_I_ATTRIBUTE_COPY(res, orig, /*graph=*/1, /*vertex=*/1, /*edge=*/0); IGRAPH_CHECK(igraph_i_attribute_permute_edges(orig, res, &edge_ids)); } igraph_vector_destroy(&edge_ids); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_complementer * \brief Create the complementer of a graph * * The complementer graph means that all edges which are * not part of the original graph will be included in the result. * * \param res Pointer to an uninitialized graph object. * \param graph The original graph. * \param loops Whether to add loop edges to the complementer graph. * \return Error code. * \sa \ref igraph_union(), \ref igraph_intersection() and \ref * igraph_difference(). * * Time complexity: O(|V|+|E1|+|E2|), |V| is the number of * vertices in the graph, |E1| is the number of edges in the original * and |E2| in the complementer graph. * * \example examples/simple/igraph_complementer.c */ int igraph_complementer(igraph_t *res, const igraph_t *graph, igraph_bool_t loops) { long int no_of_nodes = igraph_vcount(graph); igraph_vector_t edges; igraph_vector_t neis; long int i, j; long int zero = 0, *limit; IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); if (igraph_is_directed(graph)) { limit = &zero; } else { limit = &i; } for (i = 0; i < no_of_nodes; i++) { IGRAPH_ALLOW_INTERRUPTION(); IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) i, IGRAPH_OUT)); if (loops) { for (j = no_of_nodes - 1; j >= *limit; j--) { if (igraph_vector_empty(&neis) || j > igraph_vector_tail(&neis)) { IGRAPH_CHECK(igraph_vector_push_back(&edges, i)); IGRAPH_CHECK(igraph_vector_push_back(&edges, j)); } else { igraph_vector_pop_back(&neis); } } } else { for (j = no_of_nodes - 1; j >= *limit; j--) { if (igraph_vector_empty(&neis) || j > igraph_vector_tail(&neis)) { if (i != j) { IGRAPH_CHECK(igraph_vector_push_back(&edges, i)); IGRAPH_CHECK(igraph_vector_push_back(&edges, j)); } } else { igraph_vector_pop_back(&neis); } } } } IGRAPH_CHECK(igraph_create(res, &edges, (igraph_integer_t) no_of_nodes, igraph_is_directed(graph))); igraph_vector_destroy(&edges); igraph_vector_destroy(&neis); IGRAPH_I_ATTRIBUTE_DESTROY(res); IGRAPH_I_ATTRIBUTE_COPY(res, graph, /*graph=*/1, /*vertex=*/1, /*edge=*/0); IGRAPH_FINALLY_CLEAN(2); return 0; } /** * \function igraph_compose * \brief Calculates the composition of two graphs * * The composition of graphs contains the same number of vertices as * the bigger graph of the two operands. It contains an (i,j) edge if * and only if there is a k vertex, such that the first graphs * contains an (i,k) edge and the second graph a (k,j) edge. * * This is of course exactly the composition of two * binary relations. * * Two two graphs must have the same directedness, * otherwise the function returns with an error message. * Note that for undirected graphs the two relations are by definition * symmetric. * * \param res Pointer to an uninitialized graph object, the result * will be stored here. * \param g1 The firs operand, a graph object. * \param g2 The second operand, another graph object. * \param edge_map1 If not a null pointer, then it must be a pointer * to an initialized vector, and a mapping from the edges of * the result graph to the edges of the first graph is stored * here. * \param edge_map1 If not a null pointer, then it must be a pointer * to an initialized vector, and a mapping from the edges of * the result graph to the edges of the second graph is stored * here. * \return Error code. * * Time complexity: O(|V|*d1*d2), |V| is the number of vertices in the * first graph, d1 and d2 the average degree in the first and second * graphs. * * \example examples/simple/igraph_compose.c */ int igraph_compose(igraph_t *res, const igraph_t *g1, const igraph_t *g2, igraph_vector_t *edge_map1, igraph_vector_t *edge_map2) { long int no_of_nodes_left = igraph_vcount(g1); long int no_of_nodes_right = igraph_vcount(g2); long int no_of_nodes; igraph_bool_t directed = igraph_is_directed(g1); igraph_vector_t edges; igraph_vector_t neis1, neis2; long int i; if (directed != igraph_is_directed(g2)) { IGRAPH_ERROR("Cannot compose directed and undirected graph", IGRAPH_EINVAL); } no_of_nodes = no_of_nodes_left > no_of_nodes_right ? no_of_nodes_left : no_of_nodes_right; IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_VECTOR_INIT_FINALLY(&neis1, 0); IGRAPH_VECTOR_INIT_FINALLY(&neis2, 0); if (edge_map1) { igraph_vector_clear(edge_map1); } if (edge_map2) { igraph_vector_clear(edge_map2); } for (i = 0; i < no_of_nodes_left; i++) { IGRAPH_ALLOW_INTERRUPTION(); IGRAPH_CHECK(igraph_incident(g1, &neis1, (igraph_integer_t) i, IGRAPH_OUT)); while (!igraph_vector_empty(&neis1)) { long int con = (long int) igraph_vector_pop_back(&neis1); long int v1 = IGRAPH_OTHER(g1, con, i); if (v1 < no_of_nodes_right) { IGRAPH_CHECK(igraph_incident(g2, &neis2, (igraph_integer_t) v1, IGRAPH_OUT)); } else { continue; } while (!igraph_vector_empty(&neis2)) { long int con2 = igraph_vector_pop_back(&neis2); long int v2 = IGRAPH_OTHER(g2, con2, v1); IGRAPH_CHECK(igraph_vector_push_back(&edges, i)); IGRAPH_CHECK(igraph_vector_push_back(&edges, v2)); if (edge_map1) { IGRAPH_CHECK(igraph_vector_push_back(edge_map1, con)); } if (edge_map2) { IGRAPH_CHECK(igraph_vector_push_back(edge_map2, con2)); } } } } igraph_vector_destroy(&neis1); igraph_vector_destroy(&neis2); IGRAPH_FINALLY_CLEAN(2); IGRAPH_CHECK(igraph_create(res, &edges, (igraph_integer_t) no_of_nodes, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/cores.c0000644000076500000240000001210513614300625022654 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_community.h" #include "igraph_memory.h" #include "igraph_interface.h" #include "igraph_iterators.h" #include "config.h" /** * \function igraph_coreness * \brief Finding the coreness of the vertices in a network. * * The k-core of a graph is a maximal subgraph in which each vertex * has at least degree k. (Degree here means the degree in the * subgraph of course.). The coreness of a vertex is the highest order * of a k-core containing the vertex. * * * This function implements the algorithm presented in Vladimir * Batagelj, Matjaz Zaversnik: An O(m) Algorithm for Cores * Decomposition of Networks. * \param graph The input graph. * \param cores Pointer to an initialized vector, the result of the * computation will be stored here. It will be resized as * needed. For each vertex it contains the highest order of a * core containing the vertex. * \param mode For directed graph it specifies whether to calculate * in-cores, out-cores or the undirected version. It is ignored * for undirected graphs. Possible values: \c IGRAPH_ALL * undirected version, \c IGRAPH_IN in-cores, \c IGRAPH_OUT * out-cores. * \return Error code. * * Time complexity: O(|E|), the number of edges. */ int igraph_coreness(const igraph_t *graph, igraph_vector_t *cores, igraph_neimode_t mode) { long int no_of_nodes = igraph_vcount(graph); long int *bin, *vert, *pos; long int maxdeg; long int i, j = 0; igraph_vector_t neis; igraph_neimode_t omode; if (mode != IGRAPH_ALL && mode != IGRAPH_OUT && mode != IGRAPH_IN) { IGRAPH_ERROR("Invalid mode in k-cores", IGRAPH_EINVAL); } if (!igraph_is_directed(graph) || mode == IGRAPH_ALL) { mode = omode = IGRAPH_ALL; } else if (mode == IGRAPH_IN) { omode = IGRAPH_OUT; } else { omode = IGRAPH_IN; } vert = igraph_Calloc(no_of_nodes, long int); if (vert == 0) { IGRAPH_ERROR("Cannot calculate k-cores", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, vert); pos = igraph_Calloc(no_of_nodes, long int); if (pos == 0) { IGRAPH_ERROR("Cannot calculate k-cores", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, pos); /* maximum degree + degree of vertices */ IGRAPH_CHECK(igraph_degree(graph, cores, igraph_vss_all(), mode, IGRAPH_LOOPS)); maxdeg = (long int) igraph_vector_max(cores); bin = igraph_Calloc(maxdeg + 1, long int); if (bin == 0) { IGRAPH_ERROR("Cannot calculate k-cores", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, bin); /* degree histogram */ for (i = 0; i < no_of_nodes; i++) { bin[ (long int)VECTOR(*cores)[i] ] += 1; } /* start pointers */ j = 0; for (i = 0; i <= maxdeg; i++) { long int k = bin[i]; bin[i] = j; j += k; } /* sort in vert (and corrupt bin) */ for (i = 0; i < no_of_nodes; i++) { pos[i] = bin[(long int)VECTOR(*cores)[i]]; vert[pos[i]] = i; bin[(long int)VECTOR(*cores)[i]] += 1; } /* correct bin */ for (i = maxdeg; i > 0; i--) { bin[i] = bin[i - 1]; } bin[0] = 0; /* this is the main algorithm */ IGRAPH_VECTOR_INIT_FINALLY(&neis, maxdeg); for (i = 0; i < no_of_nodes; i++) { long int v = vert[i]; IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) v, omode)); for (j = 0; j < igraph_vector_size(&neis); j++) { long int u = (long int) VECTOR(neis)[j]; if (VECTOR(*cores)[u] > VECTOR(*cores)[v]) { long int du = (long int) VECTOR(*cores)[u]; long int pu = pos[u]; long int pw = bin[du]; long int w = vert[pw]; if (u != w) { pos[u] = pw; pos[w] = pu; vert[pu] = w; vert[pw] = u; } bin[du] += 1; VECTOR(*cores)[u] -= 1; } } } igraph_vector_destroy(&neis); IGRAPH_FINALLY_CLEAN(1); igraph_free(bin); igraph_free(pos); igraph_free(vert); IGRAPH_FINALLY_CLEAN(3); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/version.c0000644000076500000240000000423513614300625023233 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2008-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_version.h" #include static const char *igraph_version_string = IGRAPH_VERSION; /** * \function igraph_version * Return the version of the igraph C library * * \param version_string Pointer to a string pointer. If not null, it * is set to the igraph version string, e.g. "0.6" or "0.5.3". This * string should not be modified or deallocated. * \param major If not a null pointer, then it is set to the major * igraph version. E.g. for version "0.5.3" this is 0. * \param minor If not a null pointer, then it is set to the minor * igraph version. E.g. for version "0.5.3" this is 5. * \param subminor If not a null pointer, then it is set to the * subminor igraph version. E.g. for version "0.5.3" this is 3. * \return Error code. * * Time complexity: O(1). * * \example examples/simple/igraph_version.c */ int igraph_version(const char **version_string, int *major, int *minor, int *subminor) { int i1, i2, i3; int *p1 = major ? major : &i1, *p2 = minor ? minor : &i2, *p3 = subminor ? subminor : &i3; if (version_string) { *version_string = igraph_version_string; } *p1 = *p2 = *p3 = 0; sscanf(IGRAPH_VERSION, "%i.%i.%i", p1, p2, p3); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/layout_kk.c0000644000076500000240000006447413614300625023563 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph R package. Copyright (C) 2014 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_layout.h" #include "igraph_interface.h" #include "igraph_paths.h" #include "igraph_random.h" /** * \ingroup layout * \function igraph_layout_kamada_kawai * \brief Places the vertices on a plane according the Kamada-Kawai algorithm. * * * This is a force directed layout, see Kamada, T. and Kawai, S.: An * Algorithm for Drawing General Undirected Graphs. Information * Processing Letters, 31/1, 7--15, 1989. * \param graph A graph object. * \param res Pointer to an initialized matrix object. This will * contain the result (x-positions in column zero and * y-positions in column one) and will be resized if needed. * \param use_seed Boolean, whether to use the values supplied in the * \p res argument as the initial configuration. If zero then a * random initial configuration is used. * \param maxiter The maximum number of iterations to perform. A reasonable * default value is at least ten (or more) times the number of * vertices. * \param epsilon Stop the iteration, if the maximum delta value of the * algorithm is smaller than still. It is safe to leave it at zero, * and then \p maxiter iterations are performed. * \param kkconst The Kamada-Kawai vertex attraction constant. * Typical value: number of vertices. * \param weights Edge weights, larger values will result longer edges. * \param minx Pointer to a vector, or a \c NULL pointer. If not a * \c NULL pointer then the vector gives the minimum * \quote x \endquote coordinate for every vertex. * \param maxx Same as \p minx, but the maximum \quote x \endquote * coordinates. * \param miny Pointer to a vector, or a \c NULL pointer. If not a * \c NULL pointer then the vector gives the minimum * \quote y \endquote coordinate for every vertex. * \param maxy Same as \p miny, but the maximum \quote y \endquote * coordinates. * \return Error code. * * Time complexity: O(|V|) for each iteration, after an O(|V|^2 * log|V|) initialization step. |V| is the number of vertices in the * graph. */ int igraph_layout_kamada_kawai(const igraph_t *graph, igraph_matrix_t *res, igraph_bool_t use_seed, igraph_integer_t maxiter, igraph_real_t epsilon, igraph_real_t kkconst, const igraph_vector_t *weights, const igraph_vector_t *minx, const igraph_vector_t *maxx, const igraph_vector_t *miny, const igraph_vector_t *maxy) { igraph_integer_t no_nodes = igraph_vcount(graph); igraph_integer_t no_edges = igraph_ecount(graph); igraph_real_t L, L0 = sqrt(no_nodes); igraph_matrix_t dij, lij, kij; igraph_real_t max_dij; igraph_vector_t D1, D2; igraph_integer_t i, j, m; if (maxiter < 0) { IGRAPH_ERROR("Number of iterations must be non-negatice in " "Kamada-Kawai layout", IGRAPH_EINVAL); } if (kkconst <= 0) { IGRAPH_ERROR("`K' constant must be positive in Kamada-Kawai layout", IGRAPH_EINVAL); } if (use_seed && (igraph_matrix_nrow(res) != no_nodes || igraph_matrix_ncol(res) != 2)) { IGRAPH_ERROR("Invalid start position matrix size in " "Kamada-Kawai layout", IGRAPH_EINVAL); } if (weights && igraph_vector_size(weights) != no_edges) { IGRAPH_ERROR("Invalid weight vector length", IGRAPH_EINVAL); } if (minx && igraph_vector_size(minx) != no_nodes) { IGRAPH_ERROR("Invalid minx vector length", IGRAPH_EINVAL); } if (maxx && igraph_vector_size(maxx) != no_nodes) { IGRAPH_ERROR("Invalid maxx vector length", IGRAPH_EINVAL); } if (minx && maxx && !igraph_vector_all_le(minx, maxx)) { IGRAPH_ERROR("minx must not be greater than maxx", IGRAPH_EINVAL); } if (miny && igraph_vector_size(miny) != no_nodes) { IGRAPH_ERROR("Invalid miny vector length", IGRAPH_EINVAL); } if (maxy && igraph_vector_size(maxy) != no_nodes) { IGRAPH_ERROR("Invalid maxy vector length", IGRAPH_EINVAL); } if (miny && maxy && !igraph_vector_all_le(miny, maxy)) { IGRAPH_ERROR("miny must not be greater than maxy", IGRAPH_EINVAL); } if (!use_seed) { if (minx || maxx || miny || maxy) { const igraph_real_t width = sqrt(no_nodes), height = width; IGRAPH_CHECK(igraph_matrix_resize(res, no_nodes, 2)); RNG_BEGIN(); for (i = 0; i < no_nodes; i++) { igraph_real_t x1 = minx ? VECTOR(*minx)[i] : -width / 2; igraph_real_t x2 = maxx ? VECTOR(*maxx)[i] : width / 2; igraph_real_t y1 = miny ? VECTOR(*miny)[i] : -height / 2; igraph_real_t y2 = maxy ? VECTOR(*maxy)[i] : height / 2; if (!igraph_finite(x1)) { x1 = -width / 2; } if (!igraph_finite(x2)) { x2 = width / 2; } if (!igraph_finite(y1)) { y1 = -height / 2; } if (!igraph_finite(y2)) { y2 = height / 2; } MATRIX(*res, i, 0) = RNG_UNIF(x1, x2); MATRIX(*res, i, 1) = RNG_UNIF(y1, y2); } RNG_END(); } else { igraph_layout_circle(graph, res, /* order= */ igraph_vss_all()); } } if (no_nodes <= 1) { return 0; } IGRAPH_MATRIX_INIT_FINALLY(&dij, no_nodes, no_nodes); IGRAPH_MATRIX_INIT_FINALLY(&kij, no_nodes, no_nodes); IGRAPH_MATRIX_INIT_FINALLY(&lij, no_nodes, no_nodes); if (weights && igraph_vector_min(weights) < 0) { IGRAPH_CHECK(igraph_shortest_paths_bellman_ford(graph, &dij, igraph_vss_all(), igraph_vss_all(), weights, IGRAPH_ALL)); } else { IGRAPH_CHECK(igraph_shortest_paths_dijkstra(graph, &dij, igraph_vss_all(), igraph_vss_all(), weights, IGRAPH_ALL)); } max_dij = 0.0; for (i = 0; i < no_nodes; i++) { for (j = i + 1; j < no_nodes; j++) { if (!igraph_finite(MATRIX(dij, i, j))) { continue; } if (MATRIX(dij, i, j) > max_dij) { max_dij = MATRIX(dij, i, j); } } } for (i = 0; i < no_nodes; i++) { for (j = 0; j < no_nodes; j++) { if (MATRIX(dij, i, j) > max_dij) { MATRIX(dij, i, j) = max_dij; } } } L = L0 / max_dij; for (i = 0; i < no_nodes; i++) { for (j = 0; j < no_nodes; j++) { igraph_real_t tmp = MATRIX(dij, i, j) * MATRIX(dij, i, j); if (i == j) { continue; } MATRIX(kij, i, j) = kkconst / tmp; MATRIX(lij, i, j) = L * MATRIX(dij, i, j); } } /* Initialize delta */ IGRAPH_VECTOR_INIT_FINALLY(&D1, no_nodes); IGRAPH_VECTOR_INIT_FINALLY(&D2, no_nodes); for (m = 0; m < no_nodes; m++) { igraph_real_t myD1 = 0.0, myD2 = 0.0; for (i = 0; i < no_nodes; i++) { igraph_real_t dx, dy, mi_dist; if (i == m) { continue; } dx = MATRIX(*res, m, 0) - MATRIX(*res, i, 0); dy = MATRIX(*res, m, 1) - MATRIX(*res, i, 1); mi_dist = sqrt(dx * dx + dy * dy); myD1 += MATRIX(kij, m, i) * (dx - MATRIX(lij, m, i) * dx / mi_dist); myD2 += MATRIX(kij, m, i) * (dy - MATRIX(lij, m, i) * dy / mi_dist); } VECTOR(D1)[m] = myD1; VECTOR(D2)[m] = myD2; } for (j = 0; j < maxiter; j++) { igraph_real_t myD1, myD2, A, B, C; igraph_real_t max_delta, delta_x, delta_y; igraph_real_t old_x, old_y, new_x, new_y; myD1 = 0.0, myD2 = 0.0, A = 0.0, B = 0.0, C = 0.0; /* Select maximal delta */ m = 0; max_delta = -1; for (i = 0; i < no_nodes; i++) { igraph_real_t delta = (VECTOR(D1)[i] * VECTOR(D1)[i] + VECTOR(D2)[i] * VECTOR(D2)[i]); if (delta > max_delta) { m = i; max_delta = delta; } } if (max_delta < epsilon) { break; } old_x = MATRIX(*res, m, 0); old_y = MATRIX(*res, m, 1); /* Calculate D1 and D2, A, B, C */ for (i = 0; i < no_nodes; i++) { igraph_real_t dx, dy, dist, den; if (i == m) { continue; } dx = old_x - MATRIX(*res, i, 0); dy = old_y - MATRIX(*res, i, 1); dist = sqrt(dx * dx + dy * dy); den = dist * (dx * dx + dy * dy); A += MATRIX(kij, m, i) * (1 - MATRIX(lij, m, i) * dy * dy / den); B += MATRIX(kij, m, i) * MATRIX(lij, m, i) * dx * dy / den; C += MATRIX(kij, m, i) * (1 - MATRIX(lij, m, i) * dx * dx / den); } myD1 = VECTOR(D1)[m]; myD2 = VECTOR(D2)[m]; /* Need to solve some linear equations */ delta_y = (B * myD1 - myD2 * A) / (C * A - B * B); delta_x = - (myD1 + B * delta_y) / A; new_x = old_x + delta_x; new_y = old_y + delta_y; /* Limits, if given */ if (minx && new_x < VECTOR(*minx)[m]) { new_x = VECTOR(*minx)[m]; } if (maxx && new_x > VECTOR(*maxx)[m]) { new_x = VECTOR(*maxx)[m]; } if (miny && new_y < VECTOR(*miny)[m]) { new_y = VECTOR(*miny)[m]; } if (maxy && new_y > VECTOR(*maxy)[m]) { new_y = VECTOR(*maxy)[m]; } /* Update delta, only with/for the affected node */ VECTOR(D1)[m] = VECTOR(D2)[m] = 0.0; for (i = 0; i < no_nodes; i++) { igraph_real_t old_dx, old_dy, old_mi, new_dx, new_dy, new_mi_dist, old_mi_dist; if (i == m) { continue; } old_dx = old_x - MATRIX(*res, i, 0); old_dy = old_y - MATRIX(*res, i, 1); old_mi_dist = sqrt(old_dx * old_dx + old_dy * old_dy); new_dx = new_x - MATRIX(*res, i, 0); new_dy = new_y - MATRIX(*res, i, 1); new_mi_dist = sqrt(new_dx * new_dx + new_dy * new_dy); VECTOR(D1)[i] -= MATRIX(kij, m, i) * (-old_dx + MATRIX(lij, m, i) * old_dx / old_mi_dist); VECTOR(D2)[i] -= MATRIX(kij, m, i) * (-old_dy + MATRIX(lij, m, i) * old_dy / old_mi_dist); VECTOR(D1)[i] += MATRIX(kij, m, i) * (-new_dx + MATRIX(lij, m, i) * new_dx / new_mi_dist); VECTOR(D2)[i] += MATRIX(kij, m, i) * (-new_dy + MATRIX(lij, m, i) * new_dy / new_mi_dist); VECTOR(D1)[m] += MATRIX(kij, m, i) * (new_dx - MATRIX(lij, m, i) * new_dx / new_mi_dist); VECTOR(D2)[m] += MATRIX(kij, m, i) * (new_dy - MATRIX(lij, m, i) * new_dy / new_mi_dist); } /* Update coordinates*/ MATRIX(*res, m, 0) = new_x; MATRIX(*res, m, 1) = new_y; } igraph_vector_destroy(&D2); igraph_vector_destroy(&D1); igraph_matrix_destroy(&lij); igraph_matrix_destroy(&kij); igraph_matrix_destroy(&dij); IGRAPH_FINALLY_CLEAN(5); return 0; } /** * \ingroup layout * \function igraph_layout_kamada_kawai_3d * \brief 3D version of the Kamada-Kawai layout generator * * * This is a force directed layout, see Kamada, T. and Kawai, S.: An * Algorithm for Drawing General Undirected Graphs. Information * Processing Letters, 31/1, 7--15, 1989. * \param graph A graph object. * \param res Pointer to an initialized matrix object. This will * contain the result (x-positions in column zero and * y-positions in column one) and will be resized if needed. * \param use_seed Boolean, whether to use the values supplied in the * \p res argument as the initial configuration. If zero then a * random initial configuration is used. * \param maxiter The maximum number of iterations to perform. A reasonable * default value is at least ten (or more) times the number of * vertices. * \param epsilon Stop the iteration, if the maximum delta value of the * algorithm is smaller than still. It is safe to leave it at zero, * and then \p maxiter iterations are performed. * \param kkconst The Kamada-Kawai vertex attraction constant. * Typical value: number of vertices. * \param weights Edge weights, larger values will result longer edges. * \param minx Pointer to a vector, or a \c NULL pointer. If not a * \c NULL pointer then the vector gives the minimum * \quote x \endquote coordinate for every vertex. * \param maxx Same as \p minx, but the maximum \quote x \endquote * coordinates. * \param miny Pointer to a vector, or a \c NULL pointer. If not a * \c NULL pointer then the vector gives the minimum * \quote y \endquote coordinate for every vertex. * \param maxy Same as \p miny, but the maximum \quote y \endquote * coordinates. * \param minz Pointer to a vector, or a \c NULL pointer. If not a * \c NULL pointer then the vector gives the minimum * \quote z \endquote coordinate for every vertex. * \param maxz Same as \p minz, but the maximum \quote z \endquote * coordinates. * \return Error code. * * Time complexity: O(|V|) for each iteration, after an O(|V|^2 * log|V|) initialization step. |V| is the number of vertices in the * graph. */ int igraph_layout_kamada_kawai_3d(const igraph_t *graph, igraph_matrix_t *res, igraph_bool_t use_seed, igraph_integer_t maxiter, igraph_real_t epsilon, igraph_real_t kkconst, const igraph_vector_t *weights, const igraph_vector_t *minx, const igraph_vector_t *maxx, const igraph_vector_t *miny, const igraph_vector_t *maxy, const igraph_vector_t *minz, const igraph_vector_t *maxz) { igraph_integer_t no_nodes = igraph_vcount(graph); igraph_integer_t no_edges = igraph_ecount(graph); igraph_real_t L, L0 = sqrt(no_nodes); igraph_matrix_t dij, lij, kij; igraph_real_t max_dij; igraph_vector_t D1, D2, D3; igraph_integer_t i, j, m; if (maxiter < 0) { IGRAPH_ERROR("Number of iterations must be non-negatice in " "Kamada-Kawai layout", IGRAPH_EINVAL); } if (kkconst <= 0) { IGRAPH_ERROR("`K' constant must be positive in Kamada-Kawai layout", IGRAPH_EINVAL); } if (use_seed && (igraph_matrix_nrow(res) != no_nodes || igraph_matrix_ncol(res) != 3)) { IGRAPH_ERROR("Invalid start position matrix size in " "3d Kamada-Kawai layout", IGRAPH_EINVAL); } if (weights && igraph_vector_size(weights) != no_edges) { IGRAPH_ERROR("Invalid weight vector length", IGRAPH_EINVAL); } if (minx && igraph_vector_size(minx) != no_nodes) { IGRAPH_ERROR("Invalid minx vector length", IGRAPH_EINVAL); } if (maxx && igraph_vector_size(maxx) != no_nodes) { IGRAPH_ERROR("Invalid maxx vector length", IGRAPH_EINVAL); } if (minx && maxx && !igraph_vector_all_le(minx, maxx)) { IGRAPH_ERROR("minx must not be greater than maxx", IGRAPH_EINVAL); } if (miny && igraph_vector_size(miny) != no_nodes) { IGRAPH_ERROR("Invalid miny vector length", IGRAPH_EINVAL); } if (maxy && igraph_vector_size(maxy) != no_nodes) { IGRAPH_ERROR("Invalid maxy vector length", IGRAPH_EINVAL); } if (miny && maxy && !igraph_vector_all_le(miny, maxy)) { IGRAPH_ERROR("miny must not be greater than maxy", IGRAPH_EINVAL); } if (minz && igraph_vector_size(minz) != no_nodes) { IGRAPH_ERROR("Invalid minz vector length", IGRAPH_EINVAL); } if (maxz && igraph_vector_size(maxz) != no_nodes) { IGRAPH_ERROR("Invalid maxz vector length", IGRAPH_EINVAL); } if (minz && maxz && !igraph_vector_all_le(minz, maxz)) { IGRAPH_ERROR("minz must not be greater than maxz", IGRAPH_EINVAL); } if (!use_seed) { if (minx || maxx || miny || maxy || minz || maxz) { const igraph_real_t width = sqrt(no_nodes), height = width, depth = width; IGRAPH_CHECK(igraph_matrix_resize(res, no_nodes, 3)); RNG_BEGIN(); for (i = 0; i < no_nodes; i++) { igraph_real_t x1 = minx ? VECTOR(*minx)[i] : -width / 2; igraph_real_t x2 = maxx ? VECTOR(*maxx)[i] : width / 2; igraph_real_t y1 = miny ? VECTOR(*miny)[i] : -height / 2; igraph_real_t y2 = maxy ? VECTOR(*maxy)[i] : height / 2; igraph_real_t z1 = minz ? VECTOR(*minz)[i] : -depth / 2; igraph_real_t z2 = maxz ? VECTOR(*maxz)[i] : depth / 2; if (!igraph_finite(x1)) { x1 = -width / 2; } if (!igraph_finite(x2)) { x2 = width / 2; } if (!igraph_finite(y1)) { y1 = -height / 2; } if (!igraph_finite(y2)) { y2 = height / 2; } if (!igraph_finite(z1)) { z1 = -depth / 2; } if (!igraph_finite(z2)) { z2 = depth / 2; } MATRIX(*res, i, 0) = RNG_UNIF(x1, x2); MATRIX(*res, i, 1) = RNG_UNIF(y1, y2); MATRIX(*res, i, 2) = RNG_UNIF(z1, z2); } RNG_END(); } else { igraph_layout_sphere(graph, res); } } if (no_nodes <= 1) { return 0; } IGRAPH_MATRIX_INIT_FINALLY(&dij, no_nodes, no_nodes); IGRAPH_MATRIX_INIT_FINALLY(&kij, no_nodes, no_nodes); IGRAPH_MATRIX_INIT_FINALLY(&lij, no_nodes, no_nodes); IGRAPH_CHECK(igraph_shortest_paths_dijkstra(graph, &dij, igraph_vss_all(), igraph_vss_all(), weights, IGRAPH_ALL)); max_dij = 0.0; for (i = 0; i < no_nodes; i++) { for (j = i + 1; j < no_nodes; j++) { if (!igraph_finite(MATRIX(dij, i, j))) { continue; } if (MATRIX(dij, i, j) > max_dij) { max_dij = MATRIX(dij, i, j); } } } for (i = 0; i < no_nodes; i++) { for (j = 0; j < no_nodes; j++) { if (MATRIX(dij, i, j) > max_dij) { MATRIX(dij, i, j) = max_dij; } } } L = L0 / max_dij; for (i = 0; i < no_nodes; i++) { for (j = 0; j < no_nodes; j++) { igraph_real_t tmp = MATRIX(dij, i, j) * MATRIX(dij, i, j); if (i == j) { continue; } MATRIX(kij, i, j) = kkconst / tmp; MATRIX(lij, i, j) = L * MATRIX(dij, i, j); } } /* Initialize delta */ IGRAPH_VECTOR_INIT_FINALLY(&D1, no_nodes); IGRAPH_VECTOR_INIT_FINALLY(&D2, no_nodes); IGRAPH_VECTOR_INIT_FINALLY(&D3, no_nodes); for (m = 0; m < no_nodes; m++) { igraph_real_t dx, dy, dz, mi_dist; igraph_real_t myD1 = 0.0, myD2 = 0.0, myD3 = 0.0; for (i = 0; i < no_nodes; i++) { if (i == m) { continue; } dx = MATRIX(*res, m, 0) - MATRIX(*res, i, 0); dy = MATRIX(*res, m, 1) - MATRIX(*res, i, 1); dz = MATRIX(*res, m, 2) - MATRIX(*res, i, 2); mi_dist = sqrt(dx * dx + dy * dy + dz * dz); myD1 += MATRIX(kij, m, i) * (dx - MATRIX(lij, m, i) * dx / mi_dist); myD2 += MATRIX(kij, m, i) * (dy - MATRIX(lij, m, i) * dy / mi_dist); myD3 += MATRIX(kij, m, i) * (dz - MATRIX(lij, m, i) * dz / mi_dist); } VECTOR(D1)[m] = myD1; VECTOR(D2)[m] = myD2; VECTOR(D3)[m] = myD3; } for (j = 0; j < maxiter; j++) { igraph_real_t Ax = 0.0, Ay = 0.0, Az = 0.0; igraph_real_t Axx = 0.0, Axy = 0.0, Axz = 0.0, Ayy = 0.0, Ayz = 0.0, Azz = 0.0; igraph_real_t max_delta, delta_x, delta_y, delta_z; igraph_real_t old_x, old_y, old_z, new_x, new_y, new_z; igraph_real_t detnum; /* Select maximal delta */ m = 0; max_delta = -1; for (i = 0; i < no_nodes; i++) { igraph_real_t delta = (VECTOR(D1)[i] * VECTOR(D1)[i] + VECTOR(D2)[i] * VECTOR(D2)[i] + VECTOR(D3)[i] * VECTOR(D3)[i]); if (delta > max_delta) { m = i; max_delta = delta; } } if (max_delta < epsilon) { break; } old_x = MATRIX(*res, m, 0); old_y = MATRIX(*res, m, 1); old_z = MATRIX(*res, m, 2); /* Calculate D1, D2 and D3, and other coefficients */ for (i = 0; i < no_nodes; i++) { igraph_real_t dx, dy, dz, dist, den, k_mi, l_mi; if (i == m) { continue; } dx = old_x - MATRIX(*res, i, 0); dy = old_y - MATRIX(*res, i, 1); dz = old_z - MATRIX(*res, i, 2); dist = sqrt(dx * dx + dy * dy + dz * dz); den = dist * (dx * dx + dy * dy + dz * dz); k_mi = MATRIX(kij, m, i); l_mi = MATRIX(lij, m, i); Axx += k_mi * (1 - l_mi * (dy * dy + dz * dz) / den); Ayy += k_mi * (1 - l_mi * (dx * dx + dz * dz) / den); Azz += k_mi * (1 - l_mi * (dx * dx + dy * dy) / den); Axy += k_mi * l_mi * dx * dy / den; Axz += k_mi * l_mi * dx * dz / den; Ayz += k_mi * l_mi * dy * dz / den; } Ax = -VECTOR(D1)[m]; Ay = -VECTOR(D2)[m]; Az = -VECTOR(D3)[m]; /* Need to solve some linear equations, we just use Cramer's rule */ #define DET(a,b,c,d,e,f,g,h,i) ((a*e*i+b*f*g+c*d*h)-(c*e*g+b*d*i+a*f*h)) detnum = DET(Axx, Axy, Axz, Axy, Ayy, Ayz, Axz, Ayz, Azz); delta_x = DET(Ax, Ay, Az, Axy, Ayy, Ayz, Axz, Ayz, Azz) / detnum; delta_y = DET(Axx, Axy, Axz, Ax, Ay, Az, Axz, Ayz, Azz) / detnum; delta_z = DET(Axx, Axy, Axz, Axy, Ayy, Ayz, Ax, Ay, Az ) / detnum; new_x = old_x + delta_x; new_y = old_y + delta_y; new_z = old_z + delta_z; /* Limits, if given */ if (minx && new_x < VECTOR(*minx)[m]) { new_x = VECTOR(*minx)[m]; } if (maxx && new_x > VECTOR(*maxx)[m]) { new_x = VECTOR(*maxx)[m]; } if (miny && new_y < VECTOR(*miny)[m]) { new_y = VECTOR(*miny)[m]; } if (maxy && new_y > VECTOR(*maxy)[m]) { new_y = VECTOR(*maxy)[m]; } if (minz && new_z < VECTOR(*minz)[m]) { new_z = VECTOR(*minz)[m]; } if (maxz && new_z > VECTOR(*maxz)[m]) { new_z = VECTOR(*maxz)[m]; } /* Update delta, only with/for the affected node */ VECTOR(D1)[m] = VECTOR(D2)[m] = VECTOR(D3)[m] = 0.0; for (i = 0; i < no_nodes; i++) { igraph_real_t old_dx, old_dy, old_dz, old_mi_dist, new_dx, new_dy, new_dz, new_mi_dist; if (i == m) { continue; } old_dx = old_x - MATRIX(*res, i, 0); old_dy = old_y - MATRIX(*res, i, 1); old_dz = old_z - MATRIX(*res, i, 2); old_mi_dist = sqrt(old_dx * old_dx + old_dy * old_dy + old_dz * old_dz); new_dx = new_x - MATRIX(*res, i, 0); new_dy = new_y - MATRIX(*res, i, 1); new_dz = new_z - MATRIX(*res, i, 2); new_mi_dist = sqrt(new_dx * new_dx + new_dy * new_dy + new_dz * new_dz); VECTOR(D1)[i] -= MATRIX(kij, m, i) * (-old_dx + MATRIX(lij, m, i) * old_dx / old_mi_dist); VECTOR(D2)[i] -= MATRIX(kij, m, i) * (-old_dy + MATRIX(lij, m, i) * old_dy / old_mi_dist); VECTOR(D3)[i] -= MATRIX(kij, m, i) * (-old_dz + MATRIX(lij, m, i) * old_dz / old_mi_dist); VECTOR(D1)[i] += MATRIX(kij, m, i) * (-new_dx + MATRIX(lij, m, i) * new_dx / new_mi_dist); VECTOR(D2)[i] += MATRIX(kij, m, i) * (-new_dy + MATRIX(lij, m, i) * new_dy / new_mi_dist); VECTOR(D3)[i] += MATRIX(kij, m, i) * (-new_dz + MATRIX(lij, m, i) * new_dz / new_mi_dist); VECTOR(D1)[m] += MATRIX(kij, m, i) * (new_dx - MATRIX(lij, m, i) * new_dx / new_mi_dist); VECTOR(D2)[m] += MATRIX(kij, m, i) * (new_dy - MATRIX(lij, m, i) * new_dy / new_mi_dist); VECTOR(D3)[m] += MATRIX(kij, m, i) * (new_dz - MATRIX(lij, m, i) * new_dz / new_mi_dist); } /* Update coordinates*/ MATRIX(*res, m, 0) = new_x; MATRIX(*res, m, 1) = new_y; MATRIX(*res, m, 2) = new_z; } igraph_vector_destroy(&D3); igraph_vector_destroy(&D2); igraph_vector_destroy(&D1); igraph_matrix_destroy(&lij); igraph_matrix_destroy(&kij); igraph_matrix_destroy(&dij); IGRAPH_FINALLY_CLEAN(6); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/heap.pmt0000644000076500000240000002256613614300625023050 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_memory.h" #include "igraph_error.h" #include "config.h" #include #include /* memcpy & co. */ #include #define PARENT(x) (((x)+1)/2-1) #define LEFTCHILD(x) (((x)+1)*2-1) #define RIGHTCHILD(x) (((x)+1)*2) /** * \ingroup heap * \function igraph_heap_init * \brief Initializes an empty heap object. * * Creates an empty heap, but allocates size for some elements. * \param h Pointer to an uninitialized heap object. * \param alloc_size Number of elements to allocate memory for. * \return Error code. * * Time complexity: O(\p alloc_size), assuming memory allocation is a * linear operation. */ int FUNCTION(igraph_heap, init)(TYPE(igraph_heap)* h, long int alloc_size) { if (alloc_size <= 0 ) { alloc_size = 1; } h->stor_begin = igraph_Calloc(alloc_size, BASE); if (h->stor_begin == 0) { IGRAPH_ERROR("heap init failed", IGRAPH_ENOMEM); } h->stor_end = h->stor_begin + alloc_size; h->end = h->stor_begin; h->destroy = 1; return 0; } /** * \ingroup heap * \function igraph_heap_init_array * \brief Build a heap from an array. * * Initializes a heap object from an array, the heap is also * built of course (constructor). * \param h Pointer to an uninitialized heap object. * \param data Pointer to an array of base data type. * \param len The length of the array at \p data. * \return Error code. * * Time complexity: O(n), the number of elements in the heap. */ int FUNCTION(igraph_heap, init_array)(TYPE(igraph_heap) *h, BASE* data, long int len) { h->stor_begin = igraph_Calloc(len, BASE); if (h->stor_begin == 0) { IGRAPH_ERROR("heap init from array failed", IGRAPH_ENOMEM); } h->stor_end = h->stor_begin + len; h->end = h->stor_end; h->destroy = 1; memcpy(h->stor_begin, data, (size_t) len * sizeof(igraph_real_t)); FUNCTION(igraph_heap, i_build) (h->stor_begin, h->end - h->stor_begin, 0); return 0; } /** * \ingroup heap * \function igraph_heap_destroy * \brief Destroys an initialized heap object. * * \param h The heap object. * * Time complexity: O(1). */ void FUNCTION(igraph_heap, destroy)(TYPE(igraph_heap)* h) { if (h->destroy) { if (h->stor_begin != 0) { igraph_Free(h->stor_begin); h->stor_begin = 0; } } } /** * \ingroup heap * \function igraph_heap_empty * \brief Decides whether a heap object is empty. * * \param h The heap object. * \return \c TRUE if the heap is empty, \c FALSE otherwise. * * TIme complexity: O(1). */ igraph_bool_t FUNCTION(igraph_heap, empty)(TYPE(igraph_heap)* h) { assert(h != NULL); assert(h->stor_begin != NULL); return h->stor_begin == h->end; } /** * \ingroup heap * \function igraph_heap_push * \brief Add an element. * * Adds an element to the heap. * \param h The heap object. * \param elem The element to add. * \return Error code. * * Time complexity: O(log n), n is the number of elements in the * heap if no reallocation is needed, O(n) otherwise. It is ensured * that n push operations are performed in O(n log n) time. */ int FUNCTION(igraph_heap, push)(TYPE(igraph_heap)* h, BASE elem) { assert(h != NULL); assert(h->stor_begin != NULL); /* full, allocate more storage */ if (h->stor_end == h->end) { long int new_size = FUNCTION(igraph_heap, size)(h) * 2; if (new_size == 0) { new_size = 1; } IGRAPH_CHECK(FUNCTION(igraph_heap, reserve)(h, new_size)); } *(h->end) = elem; h->end += 1; /* maintain heap */ FUNCTION(igraph_heap, i_shift_up)(h->stor_begin, FUNCTION(igraph_heap, size)(h), FUNCTION(igraph_heap, size)(h) - 1); return 0; } /** * \ingroup heap * \function igraph_heap_top * \brief Top element. * * For maximum heaps this is the largest, for minimum heaps the * smallest element of the heap. * \param h The heap object. * \return The top element. * * Time complexity: O(1). */ BASE FUNCTION(igraph_heap, top)(TYPE(igraph_heap)* h) { assert(h != NULL); assert(h->stor_begin != NULL); assert(h->stor_begin != h->end); return h->stor_begin[0]; } /** * \ingroup heap * \function igraph_heap_delete_top * \brief Return and removes the top element * * Removes and returns the top element of the heap. For maximum heaps * this is the largest, for minimum heaps the smallest element. * \param h The heap object. * \return The top element. * * Time complexity: O(log n), n is the number of elements in the * heap. */ BASE FUNCTION(igraph_heap, delete_top)(TYPE(igraph_heap)* h) { BASE tmp; assert(h != NULL); assert(h->stor_begin != NULL); tmp = h->stor_begin[0]; FUNCTION(igraph_heap, i_switch)(h->stor_begin, 0, FUNCTION(igraph_heap, size)(h) - 1); h->end -= 1; FUNCTION(igraph_heap, i_sink)(h->stor_begin, h->end - h->stor_begin, 0); return tmp; } /** * \ingroup heap * \function igraph_heap_size * \brief Number of elements * * Gives the number of elements in a heap. * \param h The heap object. * \return The number of elements in the heap. * * Time complexity: O(1). */ long int FUNCTION(igraph_heap, size)(TYPE(igraph_heap)* h) { assert(h != NULL); assert(h->stor_begin != NULL); return h->end - h->stor_begin; } /** * \ingroup heap * \function igraph_heap_reserve * \brief Allocate more memory * * Allocates memory for future use. The size of the heap is * unchanged. If the heap is larger than the \p size parameter then * nothing happens. * \param h The heap object. * \param size The number of elements to allocate memory for. * \return Error code. * * Time complexity: O(\p size) if \p size is larger than the current * number of elements. O(1) otherwise. */ int FUNCTION(igraph_heap, reserve)(TYPE(igraph_heap)* h, long int size) { long int actual_size = FUNCTION(igraph_heap, size)(h); BASE *tmp; assert(h != NULL); assert(h->stor_begin != NULL); if (size <= actual_size) { return 0; } tmp = igraph_Realloc(h->stor_begin, (size_t) size, BASE); if (tmp == 0) { IGRAPH_ERROR("heap reserve failed", IGRAPH_ENOMEM); } h->stor_begin = tmp; h->stor_end = h->stor_begin + size; h->end = h->stor_begin + actual_size; return 0; } /** * \ingroup heap * \brief Build a heap, this should not be called directly. */ void FUNCTION(igraph_heap, i_build)(BASE* arr, long int size, long int head) { if (RIGHTCHILD(head) < size) { /* both subtrees */ FUNCTION(igraph_heap, i_build)(arr, size, LEFTCHILD(head) ); FUNCTION(igraph_heap, i_build)(arr, size, RIGHTCHILD(head)); FUNCTION(igraph_heap, i_sink)(arr, size, head); } else if (LEFTCHILD(head) < size) { /* only left */ FUNCTION(igraph_heap, i_build)(arr, size, LEFTCHILD(head)); FUNCTION(igraph_heap, i_sink)(arr, size, head); } else { /* none */ } } /** * \ingroup heap * \brief Shift an element upwards in a heap, this should not be * called directly. */ void FUNCTION(igraph_heap, i_shift_up)(BASE* arr, long int size, long int elem) { if (elem == 0 || arr[elem] HEAPLESS arr[PARENT(elem)]) { /* at the top */ } else { FUNCTION(igraph_heap, i_switch)(arr, elem, PARENT(elem)); FUNCTION(igraph_heap, i_shift_up)(arr, size, PARENT(elem)); } } /** * \ingroup heap * \brief Moves an element down in a heap, this function should not be * called directly. */ void FUNCTION(igraph_heap, i_sink)(BASE* arr, long int size, long int head) { if (LEFTCHILD(head) >= size) { /* no subtrees */ } else if (RIGHTCHILD(head) == size || arr[LEFTCHILD(head)] HEAPMOREEQ arr[RIGHTCHILD(head)]) { /* sink to the left if needed */ if (arr[head] HEAPLESS arr[LEFTCHILD(head)]) { FUNCTION(igraph_heap, i_switch)(arr, head, LEFTCHILD(head)); FUNCTION(igraph_heap, i_sink)(arr, size, LEFTCHILD(head)); } } else { /* sink to the right */ if (arr[head] HEAPLESS arr[RIGHTCHILD(head)]) { FUNCTION(igraph_heap, i_switch)(arr, head, RIGHTCHILD(head)); FUNCTION(igraph_heap, i_sink)(arr, size, RIGHTCHILD(head)); } } } /** * \ingroup heap * \brief Switches two elements in a heap, this function should not be * called directly. */ void FUNCTION(igraph_heap, i_switch)(BASE* arr, long int e1, long int e2) { if (e1 != e2) { BASE tmp = arr[e1]; arr[e1] = arr[e2]; arr[e2] = tmp; } } python-igraph-0.8.0/vendor/source/igraph/src/lsap.c0000644000076500000240000003365513614300625022515 0ustar tamasstaff00000000000000 #include "igraph_lsap.h" #include "igraph_error.h" #include #include #include #include /* INT_MAX */ #include /* DBL_MAX */ #include #include /* constants used for improving readability of code */ #define COVERED 1 #define UNCOVERED 0 #define ASSIGNED 1 #define UNASSIGNED 0 #define TRUE 1 #define FALSE 0 #define MARKED 1 #define UNMARKED 0 #define REDUCE 1 #define NOREDUCE 0 typedef struct { int n; /* order of problem */ double **C; /* cost matrix */ double **c; /* reduced cost matrix */ int *s; /* assignment */ int *f; /* column i is assigned to f[i] */ int na; /* number of assigned items; */ int runs; /* number of iterations */ double cost; /* minimum cost */ time_t rtime; /* time */ } AP; /* public interface */ /* constructors and destructor */ AP *ap_create_problem(double *t, int n); AP *ap_create_problem_from_matrix(double **t, int n); AP *ap_read_problem(char *file); void ap_free(AP *p); int ap_assignment(AP *p, int *res); int ap_costmatrix(AP *p, double **m); int ap_datamatrix(AP *p, double **m); int ap_iterations(AP *p); int ap_hungarian(AP *p); double ap_mincost(AP *p); void ap_print_solution(AP *p); void ap_show_data(AP *p); int ap_size(AP *p); int ap_time(AP *p); /* error reporting */ void ap_error(char *message); /* private functions */ void preprocess(AP *p); void preassign(AP *p); int cover(AP *p, int *ri, int *ci); void reduce(AP *p, int *ri, int *ci); int ap_hungarian(AP *p) { int n; /* size of problem */ int *ri; /* covered rows */ int *ci; /* covered columns */ time_t start, end; /* timer */ int i, j, ok; start = time(0); n = p->n; p->runs = 0; /* allocate memory */ p->s = calloc(1 + n, sizeof(int)); p->f = calloc(1 + n, sizeof(int)); ri = calloc(1 + n, sizeof(int)); ci = calloc(1 + n, sizeof(int)); if (ri == NULL || ci == NULL || p->s == NULL || p->f == NULL) { IGRAPH_ERROR("ap_hungarian: could not allocate memory", IGRAPH_ENOMEM); } preprocess(p); preassign(p); while (p->na < n) { if (REDUCE == cover(p, ri, ci)) { reduce(p, ri, ci); } ++p->runs; } end = time(0); p->rtime = end - start; /* check if assignment is a permutation of (1..n) */ for (i = 1; i <= n; i++) { ok = 0; for (j = 1; j <= n; j++) if (p->s[j] == i) { ++ok; } if (ok != 1) IGRAPH_ERROR("ap_hungarian: error in assigment, is not a permutation", IGRAPH_EINVAL); } /* calculate cost of assignment */ p->cost = 0; for (i = 1; i <= n; i++) { p->cost += p->C[i][p->s[i]]; } /* reset result back to base-0 indexing */ for (i = 1; i <= n; i++) { p->s[i - 1] = p->s[i] - 1; } /* free memory */ free(ri); free(ci); return 0; } /* abbreviated interface */ int ap_assignment(AP *p, int *res) { int i; if (p->s == NULL) { ap_hungarian(p); } for (i = 0; i < p->n; i++) { res[i] = p->s[i]; } return p->n; } /*******************************************************************/ /* constructors */ /* read data from file */ /*******************************************************************/ AP *ap_read_problem(char *file) { FILE *f; int i, j, c; int m, n; double x; double **t; int nrow, ncol; AP *p; f = fopen(file, "r"); if (f == NULL) { return NULL; } t = (double **)malloc(sizeof(double*)); m = 0; n = 0; nrow = 0; ncol = 0; while (EOF != (i = fscanf(f, "%lf", &x))) { if (i == 1) { if (n == 0) { t = (double **) realloc(t, (m + 1) * sizeof(double *)); t[m] = (double *) malloc(sizeof(double)); } else { t[m] = (double *) realloc(t[m], (n + 1) * sizeof(double)); } t[m][n++] = x; ncol = (ncol < n) ? n : ncol; c = fgetc(f); if (c == '\n') { n = 0; ++m; nrow = (nrow < m) ? m : nrow; } } } fclose(f); /* prepare data */ if (nrow != ncol) { /* fprintf(stderr,"ap_read_problem: problem not quadratic\nrows =%d, cols = %d\n",nrow,ncol); */ igraph_warningf("ap_read_problem: problem not quadratic\nrows = %d, cols = %d\n", __FILE__, __LINE__, -1, nrow, ncol); return NULL; } p = (AP*) malloc(sizeof(AP)); p->n = ncol; p->C = (double **) malloc((1 + nrow) * sizeof(double *)); p->c = (double **) malloc((1 + nrow) * sizeof(double *)); if (p->C == NULL || p->c == NULL) { return NULL; } for (i = 1; i <= nrow; i++) { p->C[i] = (double *) calloc(ncol + 1, sizeof(double)); p->c[i] = (double *) calloc(ncol + 1, sizeof(double)); if (p->C[i] == NULL || p->c[i] == NULL) { return NULL; } } for (i = 1; i <= nrow; i++) for ( j = 1; j <= ncol; j++) { p->C[i][j] = t[i - 1][j - 1]; p->c[i][j] = t[i - 1][j - 1]; } for (i = 0; i < nrow; i++) { free(t[i]); } free(t); p->cost = 0; p->s = NULL; p->f = NULL; return p; } AP *ap_create_problem_from_matrix(double **t, int n) { int i, j; AP *p; p = (AP*) malloc(sizeof(AP)); if (p == NULL) { return NULL; } p->n = n; p->C = (double **) malloc((n + 1) * sizeof(double *)); p->c = (double **) malloc((n + 1) * sizeof(double *)); if (p->C == NULL || p->c == NULL) { return NULL; } for (i = 1; i <= n; i++) { p->C[i] = (double *) calloc(n + 1, sizeof(double)); p->c[i] = (double *) calloc(n + 1, sizeof(double)); if (p->C[i] == NULL || p->c[i] == NULL) { return NULL; } } for (i = 1; i <= n; i++) for ( j = 1; j <= n; j++) { p->C[i][j] = t[i - 1][j - 1]; p->c[i][j] = t[i - 1][j - 1]; } p->cost = 0; p->s = NULL; p->f = NULL; return p; } /* read data from vector */ AP *ap_create_problem(double *t, int n) { int i, j; AP *p; p = (AP*) malloc(sizeof(AP)); if (p == NULL) { return NULL; } p->n = n; p->C = (double **) malloc((n + 1) * sizeof(double *)); p->c = (double **) malloc((n + 1) * sizeof(double *)); if (p->C == NULL || p->c == NULL) { return NULL; } for (i = 1; i <= n; i++) { p->C[i] = (double *) calloc(n + 1, sizeof(double)); p->c[i] = (double *) calloc(n + 1, sizeof(double)); if (p->C[i] == NULL || p->c[i] == NULL) { return NULL; } } for (i = 1; i <= n; i++) for ( j = 1; j <= n; j++) { p->C[i][j] = t[n * (j - 1) + i - 1]; p->c[i][j] = t[n * (j - 1) + i - 1]; } p->cost = 0; p->s = NULL; p->f = NULL; return p; } /* destructor */ void ap_free(AP *p) { int i; free(p->s); free(p->f); for (i = 1; i <= p->n; i++) { free(p->C[i]); free(p->c[i]); } free(p->C); free(p->c); free(p); } /* set + get functions */ /* void ap_show_data(AP *p) { int i, j; for(i = 1; i <= p->n; i++){ for(j = 1; j <= p->n; j++) printf("%6.2f ", p->c[i][j]); printf("\n"); } } */ double ap_mincost(AP *p) { if (p->s == NULL) { ap_hungarian(p); } return p->cost; } int ap_size(AP *p) { return p->n; } int ap_time(AP *p) { return (int) p->rtime; } int ap_iterations(AP *p) { return p->runs; } /* void ap_print_solution(AP *p) { int i; printf("%d itertations, %d secs.\n",p->runs, (int)p->rtime); printf("Min Cost: %10.4f\n",p->cost); for(i = 0; i < p->n; i++) printf("%4d",p->s[i]); printf("\n"); } */ int ap_costmatrix(AP *p, double **m) { int i, j; for (i = 0; i < p->n; i++) for (j = 0; j < p->n; j++) { m[i][j] = p->C[i + 1][j + 1]; } return p->n; } int ap_datamatrix(AP *p, double **m) { int i, j; for (i = 0; i < p->n; i++) for (j = 0; j < p->n; j++) { m[i][j] = p->c[i + 1][j + 1]; } return p->n; } /* error reporting */ /* void ap_error(char *message) { fprintf(stderr,"%s\n",message); exit(1); } */ /*************************************************************/ /* these functions are used internally */ /* by ap_hungarian */ /*************************************************************/ int cover(AP *p, int *ri, int *ci) { int *mr, i, r; int n; n = p->n; mr = calloc(1 + p->n, sizeof(int)); /* reset cover indices */ for (i = 1; i <= n; i++) { if (p->s[i] == UNASSIGNED) { ri[i] = UNCOVERED; mr[i] = MARKED; } else { ri[i] = COVERED; } ci[i] = UNCOVERED; } while (TRUE) { /* find marked row */ r = 0; for (i = 1; i <= n; i++) if (mr[i] == MARKED) { r = i; break; } if (r == 0) { break; } for (i = 1; i <= n; i++) if (p->c[r][i] == 0 && ci[i] == UNCOVERED) { if (p->f[i]) { ri[p->f[i]] = UNCOVERED; mr[p->f[i]] = MARKED; ci[i] = COVERED; } else { if (p->s[r] == UNASSIGNED) { ++p->na; } p->f[p->s[r]] = 0; p->f[i] = r; p->s[r] = i; free(mr); return NOREDUCE; } } mr[r] = UNMARKED; } free(mr); return REDUCE; } void reduce(AP *p, int *ri, int *ci) { int i, j, n; double min; n = p->n; /* find minimum in uncovered c-matrix */ min = DBL_MAX; for (i = 1; i <= n; i++) for (j = 1; j <= n; j++) if (ri[i] == UNCOVERED && ci[j] == UNCOVERED) { if (p->c[i][j] < min) { min = p->c[i][j]; } } /* subtract min from each uncovered element and add it to each element */ /* which is covered twice */ for (i = 1; i <= n; i++) for (j = 1; j <= n; j++) { if (ri[i] == UNCOVERED && ci[j] == UNCOVERED) { p->c[i][j] -= min; } if (ri[i] == COVERED && ci[j] == COVERED) { p->c[i][j] += min; } } } void preassign(AP *p) { int i, j, min, r, c, n, count; int *ri, *ci, *rz, *cz; n = p->n; p->na = 0; /* row and column markers */ ri = calloc(1 + n, sizeof(int)); ci = calloc(1 + n, sizeof(int)); /* row and column counts of zeroes */ rz = calloc(1 + n, sizeof(int)); cz = calloc(1 + n, sizeof(int)); for (i = 1; i <= n; i++) { count = 0; for (j = 1; j <= n; j++) if (p->c[i][j] == 0) { ++count; } rz[i] = count; } for (i = 1; i <= n; i++) { count = 0; for (j = 1; j <= n; j++) if (p->c[j][i] == 0) { ++count; } cz[i] = count; } while (TRUE) { /* find unassigned row with least number of zeroes > 0 */ min = INT_MAX; r = 0; for (i = 1; i <= n; i++) if (rz[i] > 0 && rz[i] < min && ri[i] == UNASSIGNED) { min = rz[i]; r = i; } /* check if we are done */ if (r == 0) { break; } /* find unassigned column in row r with least number of zeroes */ c = 0; min = INT_MAX; for (i = 1; i <= n; i++) if (p->c[r][i] == 0 && cz[i] < min && ci[i] == UNASSIGNED) { min = cz[i]; c = i; } if (c) { ++p->na; p->s[r] = c; p->f[c] = r; ri[r] = ASSIGNED; ci[c] = ASSIGNED; /* adjust zero counts */ cz[c] = 0; for (i = 1; i <= n; i++) if (p->c[i][c] == 0) { --rz[i]; } } } /* free memory */ free(ri); free(ci); free(rz); free(cz); } void preprocess(AP *p) { int i, j, n; double min; n = p->n; /* subtract column minima in each row */ for (i = 1; i <= n; i++) { min = p->c[i][1]; for (j = 2; j <= n; j++) if (p->c[i][j] < min) { min = p->c[i][j]; } for (j = 1; j <= n; j++) { p->c[i][j] -= min; } } /* subtract row minima in each column */ for (i = 1; i <= n; i++) { min = p->c[1][i]; for (j = 2; j <= n; j++) if (p->c[j][i] < min) { min = p->c[j][i]; } for (j = 1; j <= n; j++) { p->c[j][i] -= min; } } } int igraph_solve_lsap(igraph_matrix_t *c, igraph_integer_t n, igraph_vector_int_t *p) { AP *ap; IGRAPH_CHECK(igraph_vector_int_resize(p, n)); igraph_vector_int_null(p); ap = ap_create_problem(&MATRIX(*c, 0, 0), n); ap_hungarian(ap); ap_assignment(ap, VECTOR(*p)); ap_free(ap); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/walktrap_heap.cpp0000644000076500000240000001522213614300625024726 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ /* The original version of this file was written by Pascal Pons The original copyright notice follows here. The FSF address was fixed by Tamas Nepusz */ // File: heap.cpp //----------------------------------------------------------------------------- // Walktrap v0.2 -- Finds community structure of networks using random walks // Copyright (C) 2004-2005 Pascal Pons // // This program is free software; you can redistribute it and/or modify // it under the terms of the GNU General Public License as published by // the Free Software Foundation; either version 2 of the License, or // (at your option) any later version. // // This program is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU General Public License for more details. // // You should have received a copy of the GNU General Public License // along with this program; if not, write to the Free Software // Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA // 02110-1301 USA //----------------------------------------------------------------------------- // Author : Pascal Pons // Email : pascal.pons@gmail.com // Web page : http://www-rp.lip6.fr/~latapy/PP/walktrap.html // Location : Paris, France // Time : June 2005 //----------------------------------------------------------------------------- // see readme.txt for more details #include "walktrap_heap.h" #include #include using namespace std; using namespace igraph::walktrap; void Neighbor_heap::move_up(int index) { while (H[index / 2]->delta_sigma > H[index]->delta_sigma) { Neighbor* tmp = H[index / 2]; H[index]->heap_index = index / 2; H[index / 2] = H[index]; tmp->heap_index = index; H[index] = tmp; index = index / 2; } } void Neighbor_heap::move_down(int index) { while (true) { int min = index; if ((2 * index < size) && (H[2 * index]->delta_sigma < H[min]->delta_sigma)) { min = 2 * index; } if (2 * index + 1 < size && H[2 * index + 1]->delta_sigma < H[min]->delta_sigma) { min = 2 * index + 1; } if (min != index) { Neighbor* tmp = H[min]; H[index]->heap_index = min; H[min] = H[index]; tmp->heap_index = index; H[index] = tmp; index = min; } else { break; } } } Neighbor* Neighbor_heap::get_first() { if (size == 0) { return 0; } else { return H[0]; } } void Neighbor_heap::remove(Neighbor* N) { if (N->heap_index == -1 || size == 0) { return; } Neighbor* last_N = H[--size]; H[N->heap_index] = last_N; last_N->heap_index = N->heap_index; move_up(last_N->heap_index); move_down(last_N->heap_index); N->heap_index = -1; } void Neighbor_heap::add(Neighbor* N) { if (size >= max_size) { return; } N->heap_index = size++; H[N->heap_index] = N; move_up(N->heap_index); } void Neighbor_heap::update(Neighbor* N) { if (N->heap_index == -1) { return; } move_up(N->heap_index); move_down(N->heap_index); } long Neighbor_heap::memory() { return (sizeof(Neighbor_heap) + long(max_size) * sizeof(Neighbor*)); } Neighbor_heap::Neighbor_heap(int max_s) { max_size = max_s; size = 0; H = new Neighbor*[max_s]; } Neighbor_heap::~Neighbor_heap() { delete[] H; } bool Neighbor_heap::is_empty() { return (size == 0); } //################################################################# void Min_delta_sigma_heap::move_up(int index) { while (delta_sigma[H[index / 2]] < delta_sigma[H[index]]) { int tmp = H[index / 2]; I[H[index]] = index / 2; H[index / 2] = H[index]; I[tmp] = index; H[index] = tmp; index = index / 2; } } void Min_delta_sigma_heap::move_down(int index) { while (true) { int max = index; if (2 * index < size && delta_sigma[H[2 * index]] > delta_sigma[H[max]]) { max = 2 * index; } if (2 * index + 1 < size && delta_sigma[H[2 * index + 1]] > delta_sigma[H[max]]) { max = 2 * index + 1; } if (max != index) { int tmp = H[max]; I[H[index]] = max; H[max] = H[index]; I[tmp] = index; H[index] = tmp; index = max; } else { break; } } } int Min_delta_sigma_heap::get_max_community() { if (size == 0) { return -1; } else { return H[0]; } } void Min_delta_sigma_heap::remove_community(int community) { if (I[community] == -1 || size == 0) { return; } int last_community = H[--size]; H[I[community]] = last_community; I[last_community] = I[community]; move_up(I[last_community]); move_down(I[last_community]); I[community] = -1; } void Min_delta_sigma_heap::update(int community) { if (community < 0 || community >= max_size) { return; } if (I[community] == -1) { I[community] = size++; H[I[community]] = community; } move_up(I[community]); move_down(I[community]); } long Min_delta_sigma_heap::memory() { return (sizeof(Min_delta_sigma_heap) + long(max_size) * (2 * sizeof(int) + sizeof(float))); } Min_delta_sigma_heap::Min_delta_sigma_heap(int max_s) { max_size = max_s; size = 0; H = new int[max_s]; I = new int[max_s]; delta_sigma = new float[max_s]; for (int i = 0; i < max_size; i++) { I[i] = -1; delta_sigma[i] = 1.; } } Min_delta_sigma_heap::~Min_delta_sigma_heap() { delete[] H; delete[] I; delete[] delta_sigma; } bool Min_delta_sigma_heap::is_empty() { return (size == 0); } python-igraph-0.8.0/vendor/source/igraph/src/prpack/0000755000076500000240000000000013617375001022661 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/src/prpack/prpack_preprocessed_scc_graph.h0000644000076500000240000000220313524616145031102 0ustar tamasstaff00000000000000#ifndef PRPACK_PREPROCESSED_SCC_GRAPH #define PRPACK_PREPROCESSED_SCC_GRAPH #include "prpack_preprocessed_graph.h" #include "prpack_base_graph.h" namespace prpack { // Pre-processed graph class class prpack_preprocessed_scc_graph : public prpack_preprocessed_graph { private: // helper methods void initialize(); void initialize_weighted(const prpack_base_graph* bg); void initialize_unweighted(const prpack_base_graph* bg); public: // instance variables int num_es_inside; int* heads_inside; int* tails_inside; double* vals_inside; int num_es_outside; int* heads_outside; int* tails_outside; double* vals_outside; double* ii; double* num_outlinks; int num_comps; int* divisions; int* encoding; int* decoding; // constructors prpack_preprocessed_scc_graph(const prpack_base_graph* bg); // destructor ~prpack_preprocessed_scc_graph(); }; }; #endif python-igraph-0.8.0/vendor/source/igraph/src/prpack/prpack_utils.cpp0000644000076500000240000000262613524616145026077 0ustar tamasstaff00000000000000/** * @file prpack_utils.cpp * An assortment of utility functions for reporting errors, checking time, * and working with vectors. */ #include #include "prpack_utils.h" #include #include #include using namespace prpack; using namespace std; #ifdef PRPACK_IGRAPH_SUPPORT #include "igraph_error.h" #endif #if defined(_WIN32) || defined(_WIN64) #ifndef WIN32_LEAN_AND_MEAN #define WIN32_LEAN_AND_MEAN #include #endif double prpack_utils::get_time() { LARGE_INTEGER t, freq; QueryPerformanceCounter(&t); QueryPerformanceFrequency(&freq); return double(t.QuadPart)/double(freq.QuadPart); } #else #include #include double prpack_utils::get_time() { struct timeval t; gettimeofday(&t, 0); return (t.tv_sec*1.0 + t.tv_usec/1000000.0); } #endif // Fails and outputs 'msg' if 'condition' is false. void prpack_utils::validate(const bool condition, const string& msg) { if (!condition) { #ifdef PRPACK_IGRAPH_SUPPORT igraph_error("Internal error in PRPACK", __FILE__, __LINE__, IGRAPH_EINTERNAL); #else cerr << msg << endl; exit(-1); #endif } } // Permute a vector. double* prpack_utils::permute(const int length, const double* a, const int* coding) { double* ret = new double[length]; for (int i = 0; i < length; ++i) ret[coding[i]] = a[i]; return ret; } python-igraph-0.8.0/vendor/source/igraph/src/prpack/prpack_preprocessed_ge_graph.h0000644000076500000240000000136313524616145030733 0ustar tamasstaff00000000000000#ifndef PRPACK_PREPROCESSED_GE_GRAPH #define PRPACK_PREPROCESSED_GE_GRAPH #include "prpack_preprocessed_graph.h" #include "prpack_base_graph.h" namespace prpack { // Pre-processed graph class class prpack_preprocessed_ge_graph : public prpack_preprocessed_graph { private: // helper methods void initialize(); void initialize_weighted(const prpack_base_graph* bg); void initialize_unweighted(const prpack_base_graph* bg); public: // instance variables double* matrix; // constructors prpack_preprocessed_ge_graph(const prpack_base_graph* bg); // destructor ~prpack_preprocessed_ge_graph(); }; }; #endif python-igraph-0.8.0/vendor/source/igraph/src/prpack/prpack_preprocessed_scc_graph.cpp0000644000076500000240000001600113524616145031436 0ustar tamasstaff00000000000000#include "prpack_preprocessed_scc_graph.h" #include #include #include using namespace prpack; using namespace std; void prpack_preprocessed_scc_graph::initialize() { heads_inside = NULL; tails_inside = NULL; vals_inside = NULL; heads_outside = NULL; tails_outside = NULL; vals_outside = NULL; ii = NULL; d = NULL; num_outlinks = NULL; divisions = NULL; encoding = NULL; decoding = NULL; } void prpack_preprocessed_scc_graph::initialize_weighted(const prpack_base_graph* bg) { vals_inside = new double[num_es]; vals_outside = new double[num_es]; d = new double[num_vs]; fill(d, d + num_vs, 1); for (int comp_i = 0; comp_i < num_comps; ++comp_i) { const int start_i = divisions[comp_i]; const int end_i = (comp_i + 1 != num_comps) ? divisions[comp_i + 1] : num_vs; for (int i = start_i; i < end_i; ++i) { ii[i] = 0; const int decoded = decoding[i]; const int start_j = bg->tails[decoded]; const int end_j = (decoded + 1 != num_vs) ? bg->tails[decoded + 1] : bg->num_es; tails_inside[i] = num_es_inside; tails_outside[i] = num_es_outside; for (int j = start_j; j < end_j; ++j) { const int h = encoding[bg->heads[j]]; if (h == i) { ii[i] += bg->vals[j]; } else { if (start_i <= h && h < end_i) { heads_inside[num_es_inside] = h; vals_inside[num_es_inside] = bg->vals[j]; ++num_es_inside; } else { heads_outside[num_es_outside] = h; vals_outside[num_es_outside] = bg->vals[j]; ++num_es_outside; } } d[h] -= bg->vals[j]; } } } } void prpack_preprocessed_scc_graph::initialize_unweighted(const prpack_base_graph* bg) { num_outlinks = new double[num_vs]; fill(num_outlinks, num_outlinks + num_vs, 0); for (int comp_i = 0; comp_i < num_comps; ++comp_i) { const int start_i = divisions[comp_i]; const int end_i = (comp_i + 1 != num_comps) ? divisions[comp_i + 1] : num_vs; for (int i = start_i; i < end_i; ++i) { ii[i] = 0; const int decoded = decoding[i]; const int start_j = bg->tails[decoded]; const int end_j = (decoded + 1 != num_vs) ? bg->tails[decoded + 1] : bg->num_es; tails_inside[i] = num_es_inside; tails_outside[i] = num_es_outside; for (int j = start_j; j < end_j; ++j) { const int h = encoding[bg->heads[j]]; if (h == i) { ++ii[i]; } else { if (start_i <= h && h < end_i) heads_inside[num_es_inside++] = h; else heads_outside[num_es_outside++] = h; } ++num_outlinks[h]; } } } for (int i = 0; i < num_vs; ++i) { if (num_outlinks[i] == 0) num_outlinks[i] = -1; ii[i] /= num_outlinks[i]; } } prpack_preprocessed_scc_graph::prpack_preprocessed_scc_graph(const prpack_base_graph* bg) { initialize(); // initialize instance variables num_vs = bg->num_vs; num_es = bg->num_es - bg->num_self_es; // initialize Tarjan's algorithm variables num_comps = 0; int mn = 0; // the number of vertices seen so far int sz = 0; // size of st int decoding_i = 0; // size of decoding currently filled in decoding = new int[num_vs]; int* scc = new int[num_vs]; // the strongly connected component this vertex is in int* low = new int[num_vs]; // the lowest index this vertex can reach int* num = new int[num_vs]; // the index of this vertex in the dfs traversal int* st = new int[num_vs]; // a stack for the dfs memset(num, -1, num_vs*sizeof(num[0])); memset(scc, -1, num_vs*sizeof(scc[0])); int* cs1 = new int[num_vs]; // call stack variable for dfs int* cs2 = new int[num_vs]; // call stack variable for dfs // run iterative Tarjan's algorithm for (int root = 0; root < num_vs; ++root) { if (num[root] != -1) continue; int csz = 1; cs1[0] = root; cs2[0] = bg->tails[root]; // dfs while (csz) { const int p = cs1[csz - 1]; // node we're dfs-ing on int& it = cs2[csz - 1]; // iteration of the for loop if (it == bg->tails[p]) { low[p] = num[p] = mn++; st[sz++] = p; } else { low[p] = min(low[p], low[bg->heads[it - 1]]); } bool done = false; int end_it = (p + 1 != num_vs) ? bg->tails[p + 1] : bg->num_es; for (; it < end_it; ++it) { int h = bg->heads[it]; if (scc[h] == -1) { if (num[h] == -1) { // dfs(h, p); cs1[csz] = h; cs2[csz++] = bg->tails[h]; ++it; done = true; break; } low[p] = min(low[p], low[h]); } } if (done) continue; // if p is the first explored vertex of a scc if (low[p] == num[p]) { cs1[num_vs - 1 - num_comps] = decoding_i; while (scc[p] != num_comps) { scc[st[--sz]] = num_comps; decoding[decoding_i++] = st[sz]; } ++num_comps; } --csz; } } // set up other instance variables divisions = new int[num_comps]; divisions[0] = 0; for (int i = 1; i < num_comps; ++i) divisions[i] = cs1[num_vs - 1 - i]; encoding = num; for (int i = 0; i < num_vs; ++i) encoding[decoding[i]] = i; // fill in inside and outside instance variables ii = new double[num_vs]; tails_inside = cs1; heads_inside = new int[num_es]; tails_outside = cs2; heads_outside = new int[num_es]; num_es_inside = num_es_outside = 0; // continue initialization based off of weightedness if (bg->vals != NULL) initialize_weighted(bg); else initialize_unweighted(bg); // free memory // do not free num <==> encoding // do not free cs1 <==> tails_inside // do not free cs2 <==> tails_outside delete[] scc; delete[] low; delete[] st; } prpack_preprocessed_scc_graph::~prpack_preprocessed_scc_graph() { delete[] heads_inside; delete[] tails_inside; delete[] vals_inside; delete[] heads_outside; delete[] tails_outside; delete[] vals_outside; delete[] ii; delete[] d; delete[] num_outlinks; delete[] divisions; delete[] encoding; delete[] decoding; } python-igraph-0.8.0/vendor/source/igraph/src/prpack/prpack_preprocessed_ge_graph.cpp0000644000076500000240000000376113524616145031272 0ustar tamasstaff00000000000000#include "prpack_preprocessed_ge_graph.h" #include using namespace prpack; using namespace std; void prpack_preprocessed_ge_graph::initialize() { matrix = NULL; d = NULL; } void prpack_preprocessed_ge_graph::initialize_weighted(const prpack_base_graph* bg) { // initialize d fill(d, d + num_vs, 1); // fill in the matrix for (int i = 0, inum_vs = 0; i < num_vs; ++i, inum_vs += num_vs) { const int start_j = bg->tails[i]; const int end_j = (i + 1 != num_vs) ? bg->tails[i + 1] : bg->num_es; for (int j = start_j; j < end_j; ++j) d[bg->heads[j]] -= matrix[inum_vs + bg->heads[j]] = bg->vals[j]; } } void prpack_preprocessed_ge_graph::initialize_unweighted(const prpack_base_graph* bg) { // fill in the matrix for (int i = 0, inum_vs = 0; i < num_vs; ++i, inum_vs += num_vs) { const int start_j = bg->tails[i]; const int end_j = (i + 1 != num_vs) ? bg->tails[i + 1] : bg->num_es; for (int j = start_j; j < end_j; ++j) ++matrix[inum_vs + bg->heads[j]]; } // normalize the columns for (int j = 0; j < num_vs; ++j) { double sum = 0; for (int inum_vs = 0; inum_vs < num_vs*num_vs; inum_vs += num_vs) sum += matrix[inum_vs + j]; if (sum > 0) { d[j] = 0; const double coeff = 1/sum; for (int inum_vs = 0; inum_vs < num_vs*num_vs; inum_vs += num_vs) matrix[inum_vs + j] *= coeff; } else { d[j] = 1; } } } prpack_preprocessed_ge_graph::prpack_preprocessed_ge_graph(const prpack_base_graph* bg) { initialize(); num_vs = bg->num_vs; num_es = bg->num_es; matrix = new double[num_vs*num_vs]; d = new double[num_vs]; fill(matrix, matrix + num_vs*num_vs, 0); if (bg->vals != NULL) initialize_weighted(bg); else initialize_unweighted(bg); } prpack_preprocessed_ge_graph::~prpack_preprocessed_ge_graph() { delete[] matrix; delete[] d; } python-igraph-0.8.0/vendor/source/igraph/src/prpack/prpack.h0000644000076500000240000000031213524616145024312 0ustar tamasstaff00000000000000#ifndef PRPACK #define PRPACK #include "prpack_csc.h" #include "prpack_csr.h" #include "prpack_edge_list.h" #include "prpack_base_graph.h" #include "prpack_solver.h" #include "prpack_result.h" #endif python-igraph-0.8.0/vendor/source/igraph/src/prpack/prpack_base_graph.cpp0000644000076500000240000002265713524616145027040 0ustar tamasstaff00000000000000#include "prpack_base_graph.h" #include "prpack_utils.h" #include #include #include #include #include #include using namespace prpack; using namespace std; void prpack_base_graph::initialize() { heads = NULL; tails = NULL; vals = NULL; } prpack_base_graph::prpack_base_graph() { initialize(); num_vs = num_es = 0; } prpack_base_graph::prpack_base_graph(const prpack_csc* g) { initialize(); num_vs = g->num_vs; num_es = g->num_es; // fill in heads and tails num_self_es = 0; int* hs = g->heads; int* ts = g->tails; tails = new int[num_vs]; memset(tails, 0, num_vs*sizeof(tails[0])); for (int h = 0; h < num_vs; ++h) { const int start_ti = hs[h]; const int end_ti = (h + 1 != num_vs) ? hs[h + 1] : num_es; for (int ti = start_ti; ti < end_ti; ++ti) { const int t = ts[ti]; ++tails[t]; if (h == t) ++num_self_es; } } for (int i = 0, sum = 0; i < num_vs; ++i) { const int temp = sum; sum += tails[i]; tails[i] = temp; } heads = new int[num_es]; int* osets = new int[num_vs]; memset(osets, 0, num_vs*sizeof(osets[0])); for (int h = 0; h < num_vs; ++h) { const int start_ti = hs[h]; const int end_ti = (h + 1 != num_vs) ? hs[h + 1] : num_es; for (int ti = start_ti; ti < end_ti; ++ti) { const int t = ts[ti]; heads[tails[t] + osets[t]++] = h; } } // clean up delete[] osets; } prpack_base_graph::prpack_base_graph(const prpack_int64_csc* g) { initialize(); // TODO remove the assert and add better behavior assert(num_vs <= std::numeric_limits::max()); num_vs = (int)g->num_vs; num_es = (int)g->num_es; // fill in heads and tails num_self_es = 0; int64_t* hs = g->heads; int64_t* ts = g->tails; tails = new int[num_vs]; memset(tails, 0, num_vs*sizeof(tails[0])); for (int h = 0; h < num_vs; ++h) { const int start_ti = (int)hs[h]; const int end_ti = (h + 1 != num_vs) ? (int)hs[h + 1] : num_es; for (int ti = start_ti; ti < end_ti; ++ti) { const int t = (int)ts[ti]; ++tails[t]; if (h == t) ++num_self_es; } } for (int i = 0, sum = 0; i < num_vs; ++i) { const int temp = sum; sum += tails[i]; tails[i] = temp; } heads = new int[num_es]; int* osets = new int[num_vs]; memset(osets, 0, num_vs*sizeof(osets[0])); for (int h = 0; h < num_vs; ++h) { const int start_ti = (int)hs[h]; const int end_ti = (h + 1 != num_vs) ? (int)hs[h + 1] : num_es; for (int ti = start_ti; ti < end_ti; ++ti) { const int t = (int)ts[ti]; heads[tails[t] + osets[t]++] = h; } } // clean up delete[] osets; } prpack_base_graph::prpack_base_graph(const prpack_csr* g) { initialize(); assert(false); // TODO } prpack_base_graph::prpack_base_graph(const prpack_edge_list* g) { initialize(); num_vs = g->num_vs; num_es = g->num_es; // fill in heads and tails num_self_es = 0; int* hs = g->heads; int* ts = g->tails; tails = new int[num_vs]; memset(tails, 0, num_vs*sizeof(tails[0])); for (int i = 0; i < num_es; ++i) { ++tails[ts[i]]; if (hs[i] == ts[i]) ++num_self_es; } for (int i = 0, sum = 0; i < num_vs; ++i) { const int temp = sum; sum += tails[i]; tails[i] = temp; } heads = new int[num_es]; int* osets = new int[num_vs]; memset(osets, 0, num_vs*sizeof(osets[0])); for (int i = 0; i < num_es; ++i) heads[tails[ts[i]] + osets[ts[i]]++] = hs[i]; // clean up delete[] osets; } prpack_base_graph::prpack_base_graph(const char* filename, const char* format, const bool weighted) { initialize(); FILE* f = fopen(filename, "r"); const string s(filename); const string t(format); const string ext = (t == "") ? s.substr(s.rfind('.') + 1) : t; if (ext == "smat") { read_smat(f, weighted); } else { prpack_utils::validate(!weighted, "Error: graph format is not compatible with weighted option."); if (ext == "edges" || ext == "eg2") { read_edges(f); } else if (ext == "graph-txt") { read_ascii(f); } else { prpack_utils::validate(false, "Error: invalid graph format."); } } fclose(f); } prpack_base_graph::~prpack_base_graph() { delete[] heads; delete[] tails; delete[] vals; } void prpack_base_graph::read_smat(FILE* f, const bool weighted) { // read in header double ignore = 0.0; assert(fscanf(f, "%d %lf %d", &num_vs, &ignore, &num_es) == 3); // fill in heads and tails num_self_es = 0; int* hs = new int[num_es]; int* ts = new int[num_es]; heads = new int[num_es]; tails = new int[num_vs]; double* vs = NULL; if (weighted) { vs = new double[num_es]; vals = new double[num_es]; } memset(tails, 0, num_vs*sizeof(tails[0])); for (int i = 0; i < num_es; ++i) { assert(fscanf(f, "%d %d %lf", &hs[i], &ts[i], &((weighted) ? vs[i] : ignore)) == 3); ++tails[ts[i]]; if (hs[i] == ts[i]) ++num_self_es; } for (int i = 0, sum = 0; i < num_vs; ++i) { const int temp = sum; sum += tails[i]; tails[i] = temp; } int* osets = new int[num_vs]; memset(osets, 0, num_vs*sizeof(osets[0])); for (int i = 0; i < num_es; ++i) { const int idx = tails[ts[i]] + osets[ts[i]]++; heads[idx] = hs[i]; if (weighted) vals[idx] = vs[i]; } // clean up delete[] hs; delete[] ts; delete[] vs; delete[] osets; } void prpack_base_graph::read_edges(FILE* f) { vector > al; int h, t; num_es = num_self_es = 0; while (fscanf(f, "%d %d", &h, &t) == 2) { const int m = (h < t) ? t : h; if ((int) al.size() < m + 1) al.resize(m + 1); al[t].push_back(h); ++num_es; if (h == t) ++num_self_es; } num_vs = al.size(); heads = new int[num_es]; tails = new int[num_vs]; for (int tails_i = 0, heads_i = 0; tails_i < num_vs; ++tails_i) { tails[tails_i] = heads_i; for (int j = 0; j < (int) al[tails_i].size(); ++j) heads[heads_i++] = al[tails_i][j]; } } void prpack_base_graph::read_ascii(FILE* f) { assert(fscanf(f, "%d", &num_vs) == 1); while (getc(f) != '\n'); vector* al = new vector[num_vs]; num_es = num_self_es = 0; char s[32]; for (int h = 0; h < num_vs; ++h) { bool line_ended = false; while (!line_ended) { for (int i = 0; ; ++i) { s[i] = getc(f); if ('9' < s[i] || s[i] < '0') { line_ended = s[i] == '\n'; if (i != 0) { s[i] = '\0'; const int t = atoi(s); al[t].push_back(h); ++num_es; if (h == t) ++num_self_es; } break; } } } } heads = new int[num_es]; tails = new int[num_vs]; for (int tails_i = 0, heads_i = 0; tails_i < num_vs; ++tails_i) { tails[tails_i] = heads_i; for (int j = 0; j < (int) al[tails_i].size(); ++j) heads[heads_i++] = al[tails_i][j]; } delete[] al; } prpack_base_graph::prpack_base_graph(int nverts, int nedges, std::pair* edges) { initialize(); num_vs = nverts; num_es = nedges; // fill in heads and tails num_self_es = 0; int* hs = new int[num_es]; int* ts = new int[num_es]; tails = new int[num_vs]; memset(tails, 0, num_vs*sizeof(tails[0])); for (int i = 0; i < num_es; ++i) { assert(edges[i].first >= 0 && edges[i].first < num_vs); assert(edges[i].second >= 0 && edges[i].second < num_vs); hs[i] = edges[i].first; ts[i] = edges[i].second; ++tails[ts[i]]; if (hs[i] == ts[i]) ++num_self_es; } for (int i = 0, sum = 0; i < num_vs; ++i) { int temp = sum; sum += tails[i]; tails[i] = temp; } heads = new int[num_es]; int* osets = new int[num_vs]; memset(osets, 0, num_vs*sizeof(osets[0])); for (int i = 0; i < num_es; ++i) heads[tails[ts[i]] + osets[ts[i]]++] = hs[i]; // clean up delete[] hs; delete[] ts; delete[] osets; } /** Normalize the edge weights to sum to one. */ void prpack_base_graph::normalize_weights() { if (!vals) { // skip normalizing weights if not using values return; } std::vector rowsums(num_vs,0.); // the graph is in a compressed in-edge list. for (int i=0; i #include using namespace prpack; using namespace std; void prpack_preprocessed_schur_graph::initialize() { heads = NULL; tails = NULL; vals = NULL; ii = NULL; d = NULL; num_outlinks = NULL; encoding = NULL; decoding = NULL; } void prpack_preprocessed_schur_graph::initialize_weighted(const prpack_base_graph* bg) { // permute d ii = d; d = new double[num_vs]; for (int i = 0; i < num_vs; ++i) d[encoding[i]] = ii[i]; // convert bg to head/tail format for (int tails_i = 0, heads_i = 0; tails_i < num_vs; ++tails_i) { ii[tails_i] = 0; tails[tails_i] = heads_i; const int decoded = decoding[tails_i]; const int start_i = bg->tails[decoded]; const int end_i = (decoded + 1 != num_vs) ? bg->tails[decoded + 1] : bg->num_es; for (int i = start_i; i < end_i; ++i) { if (decoded == bg->heads[i]) ii[tails_i] += bg->vals[i]; else { heads[heads_i] = encoding[bg->heads[i]]; vals[heads_i] = bg->vals[i]; ++heads_i; } } } } void prpack_preprocessed_schur_graph::initialize_unweighted(const prpack_base_graph* bg) { // permute num_outlinks ii = num_outlinks; num_outlinks = new double[num_vs]; for (int i = 0; i < num_vs; ++i) num_outlinks[encoding[i]] = (ii[i] == 0) ? -1 : ii[i]; // convert bg to head/tail format for (int tails_i = 0, heads_i = 0; tails_i < num_vs; ++tails_i) { ii[tails_i] = 0; tails[tails_i] = heads_i; const int decoded = decoding[tails_i]; const int start_i = bg->tails[decoded]; const int end_i = (decoded + 1 != num_vs) ? bg->tails[decoded + 1] : bg->num_es; for (int i = start_i; i < end_i; ++i) { if (decoded == bg->heads[i]) ++ii[tails_i]; else heads[heads_i++] = encoding[bg->heads[i]]; } if (ii[tails_i] > 0) ii[tails_i] /= num_outlinks[tails_i]; } } prpack_preprocessed_schur_graph::prpack_preprocessed_schur_graph(const prpack_base_graph* bg) { initialize(); // initialize instance variables num_vs = bg->num_vs; num_es = bg->num_es - bg->num_self_es; tails = new int[num_vs]; heads = new int[num_es]; const bool weighted = bg->vals != NULL; if (weighted) { vals = new double[num_vs]; d = new double[num_vs]; fill(d, d + num_vs, 1); for (int i = 0; i < bg->num_es; ++i) d[bg->heads[i]] -= bg->vals[i]; } else { num_outlinks = new double[num_vs]; fill(num_outlinks, num_outlinks + num_vs, 0); for (int i = 0; i < bg->num_es; ++i) ++num_outlinks[bg->heads[i]]; } // permute no-inlink vertices to the beginning, and no-outlink vertices to the end encoding = new int[num_vs]; decoding = new int[num_vs]; num_no_in_vs = num_no_out_vs = 0; for (int i = 0; i < num_vs; ++i) { if (bg->tails[i] == ((i + 1 != num_vs) ? bg->tails[i + 1] : bg->num_es)) { decoding[encoding[i] = num_no_in_vs] = i; ++num_no_in_vs; } else if ((weighted) ? (d[i] == 1) : (num_outlinks[i] == 0)) { decoding[encoding[i] = num_vs - 1 - num_no_out_vs] = i; ++num_no_out_vs; } } // permute everything else for (int i = 0, p = num_no_in_vs; i < num_vs; ++i) if (bg->tails[i] < ((i + 1 != num_vs) ? bg->tails[i + 1] : bg->num_es) && ((weighted) ? (d[i] < 1) : (num_outlinks[i] > 0))) decoding[encoding[i] = p++] = i; // continue initialization based off of weightedness if (weighted) initialize_weighted(bg); else initialize_unweighted(bg); } prpack_preprocessed_schur_graph::~prpack_preprocessed_schur_graph() { delete[] heads; delete[] tails; delete[] vals; delete[] ii; delete[] d; delete[] num_outlinks; delete[] encoding; delete[] decoding; } python-igraph-0.8.0/vendor/source/igraph/src/prpack/prpack_preprocessed_gs_graph.h0000644000076500000240000000153313524616145030750 0ustar tamasstaff00000000000000#ifndef PRPACK_PREPROCESSED_GS_GRAPH #define PRPACK_PREPROCESSED_GS_GRAPH #include "prpack_preprocessed_graph.h" #include "prpack_base_graph.h" namespace prpack { // Pre-processed graph class class prpack_preprocessed_gs_graph : public prpack_preprocessed_graph { private: // helper methods void initialize(); void initialize_weighted(const prpack_base_graph* bg); void initialize_unweighted(const prpack_base_graph* bg); public: // instance variables int* heads; int* tails; double* vals; double* ii; double* num_outlinks; // constructors prpack_preprocessed_gs_graph(const prpack_base_graph* bg); // destructor ~prpack_preprocessed_gs_graph(); }; }; #endif python-igraph-0.8.0/vendor/source/igraph/src/prpack/prpack_utils.h0000644000076500000240000000171613524616145025543 0ustar tamasstaff00000000000000#ifndef PRPACK_UTILS #define PRPACK_UTILS #ifdef MATLAB_MEX_FILE #include "mex.h" #endif #include // Computes the time taken to do X and stores it in T. #define TIME(T, X) \ (T) = prpack_utils::get_time(); \ (X); \ (T) = prpack_utils::get_time() - (T) // Computes S += A using C as a carry-over. // This is a macro over a function as it is faster this way. #define COMPENSATED_SUM(S, A, C) \ double compensated_sum_y = (A) - (C); \ double compensated_sum_t = (S) + compensated_sum_y; \ (C) = compensated_sum_t - (S) - compensated_sum_y; \ (S) = compensated_sum_t namespace prpack { class prpack_utils { public: static double get_time(); static void validate(const bool condition, const std::string& msg); static double* permute(const int length, const double* a, const int* coding); }; }; #endif python-igraph-0.8.0/vendor/source/igraph/src/prpack/prpack_igraph_graph.cpp0000644000076500000240000000765413524616145027400 0ustar tamasstaff00000000000000#include "prpack_igraph_graph.h" #include #include using namespace prpack; using namespace std; #ifdef PRPACK_IGRAPH_SUPPORT prpack_igraph_graph::prpack_igraph_graph(const igraph_t* g, const igraph_vector_t* weights, igraph_bool_t directed) { const igraph_bool_t treat_as_directed = igraph_is_directed(g) && directed; igraph_es_t es; igraph_eit_t eit; igraph_vector_t neis; long int i, j, eid, sum, temp, num_ignored_es; int *p_head, *p_head_copy; double* p_weight; // Get the number of vertices and edges. For undirected graphs, we add // an edge in both directions. num_vs = igraph_vcount(g); num_es = igraph_ecount(g); num_self_es = 0; if (!treat_as_directed) { num_es *= 2; } // Allocate memory for heads and tails p_head = heads = new int[num_es]; tails = new int[num_vs]; memset(tails, 0, num_vs * sizeof(tails[0])); // Allocate memory for weights if needed if (weights != 0) { p_weight = vals = new double[num_es]; } // Count the number of ignored edges (those with negative or zero weight) num_ignored_es = 0; if (treat_as_directed) { // Select all the edges and iterate over them by the source vertices es = igraph_ess_all(IGRAPH_EDGEORDER_TO); // Add the edges igraph_eit_create(g, es, &eit); while (!IGRAPH_EIT_END(eit)) { eid = IGRAPH_EIT_GET(eit); IGRAPH_EIT_NEXT(eit); // Handle the weight if (weights != 0) { // Does this edge have zero or negative weight? if (VECTOR(*weights)[eid] <= 0) { // Ignore it. num_ignored_es++; continue; } *p_weight = VECTOR(*weights)[eid]; ++p_weight; } *p_head = IGRAPH_FROM(g, eid); ++p_head; ++tails[IGRAPH_TO(g, eid)]; if (IGRAPH_FROM(g, eid) == IGRAPH_TO(g, eid)) { ++num_self_es; } } igraph_eit_destroy(&eit); } else { // Select all the edges and iterate over them by the target vertices igraph_vector_init(&neis, 0); for (i = 0; i < num_vs; i++) { igraph_incident(g, &neis, i, IGRAPH_ALL); temp = igraph_vector_size(&neis); // TODO: should loop edges be added in both directions? p_head_copy = p_head; for (j = 0; j < temp; j++) { if (weights != 0) { if (VECTOR(*weights)[(long int)VECTOR(neis)[j]] <= 0) { // Ignore num_ignored_es++; continue; } *p_weight = VECTOR(*weights)[(long int)VECTOR(neis)[j]]; ++p_weight; } *p_head = IGRAPH_OTHER(g, VECTOR(neis)[j], i); if (i == *p_head) { num_self_es++; } ++p_head; } tails[i] = p_head - p_head_copy; } igraph_vector_destroy(&neis); } // Decrease num_es by the number of ignored edges num_es -= num_ignored_es; // Finalize the tails vector for (i = 0, sum = 0; i < num_vs; ++i) { temp = sum; sum += tails[i]; tails[i] = temp; } // Normalize the weights normalize_weights(); // Debug /* printf("Heads:"); for (i = 0; i < num_es; ++i) { printf(" %d", heads[i]); } printf("\n"); printf("Tails:"); for (i = 0; i < num_vs; ++i) { printf(" %d", tails[i]); } printf("\n"); if (vals) { printf("Vals:"); for (i = 0; i < num_es; ++i) { printf(" %.4f", vals[i]); } printf("\n"); } printf("===========================\n"); */ } // PRPACK_IGRAPH_SUPPORT #endif python-igraph-0.8.0/vendor/source/igraph/src/prpack/prpack_csr.h0000644000076500000240000000032513524616145025165 0ustar tamasstaff00000000000000#ifndef PRPACK_CSR #define PRPACK_CSR namespace prpack { class prpack_csr { public: int num_vs; int num_es; int* heads; int* tails; }; }; #endif python-igraph-0.8.0/vendor/source/igraph/src/prpack/prpack_preprocessed_gs_graph.cpp0000644000076500000240000000461613524616145031310 0ustar tamasstaff00000000000000#include "prpack_preprocessed_gs_graph.h" #include using namespace prpack; using namespace std; void prpack_preprocessed_gs_graph::initialize() { heads = NULL; tails = NULL; vals = NULL; ii = NULL; d = NULL; num_outlinks = NULL; } void prpack_preprocessed_gs_graph::initialize_weighted(const prpack_base_graph* bg) { vals = new double[num_es]; d = new double[num_vs]; fill(d, d + num_vs, 1); for (int tails_i = 0, heads_i = 0; tails_i < num_vs; ++tails_i) { tails[tails_i] = heads_i; ii[tails_i] = 0; const int start_j = bg->tails[tails_i]; const int end_j = (tails_i + 1 != num_vs) ? bg->tails[tails_i + 1]: bg->num_es; for (int j = start_j; j < end_j; ++j) { if (tails_i == bg->heads[j]) ii[tails_i] += bg->vals[j]; else { heads[heads_i] = bg->heads[j]; vals[heads_i] = bg->vals[j]; ++heads_i; } d[bg->heads[j]] -= bg->vals[j]; } } } void prpack_preprocessed_gs_graph::initialize_unweighted(const prpack_base_graph* bg) { num_outlinks = new double[num_vs]; fill(num_outlinks, num_outlinks + num_vs, 0); for (int tails_i = 0, heads_i = 0; tails_i < num_vs; ++tails_i) { tails[tails_i] = heads_i; ii[tails_i] = 0; const int start_j = bg->tails[tails_i]; const int end_j = (tails_i + 1 != num_vs) ? bg->tails[tails_i + 1]: bg->num_es; for (int j = start_j; j < end_j; ++j) { if (tails_i == bg->heads[j]) ++ii[tails_i]; else heads[heads_i++] = bg->heads[j]; ++num_outlinks[bg->heads[j]]; } } for (int i = 0; i < num_vs; ++i) { if (num_outlinks[i] == 0) num_outlinks[i] = -1; ii[i] /= num_outlinks[i]; } } prpack_preprocessed_gs_graph::prpack_preprocessed_gs_graph(const prpack_base_graph* bg) { initialize(); num_vs = bg->num_vs; num_es = bg->num_es - bg->num_self_es; heads = new int[num_es]; tails = new int[num_vs]; ii = new double[num_vs]; if (bg->vals != NULL) initialize_weighted(bg); else initialize_unweighted(bg); } prpack_preprocessed_gs_graph::~prpack_preprocessed_gs_graph() { delete[] heads; delete[] tails; delete[] vals; delete[] ii; delete[] d; delete[] num_outlinks; } python-igraph-0.8.0/vendor/source/igraph/src/prpack/prpack_preprocessed_schur_graph.h0000644000076500000240000000167413524616145031471 0ustar tamasstaff00000000000000#ifndef PRPACK_PREPROCESSED_SCHUR_GRAPH #define PRPACK_PREPROCESSED_SCHUR_GRAPH #include "prpack_preprocessed_graph.h" #include "prpack_base_graph.h" namespace prpack { class prpack_preprocessed_schur_graph : public prpack_preprocessed_graph { private: // helper methods void initialize(); void initialize_weighted(const prpack_base_graph* bg); void initialize_unweighted(const prpack_base_graph* bg); public: // instance variables int num_no_in_vs; int num_no_out_vs; int* heads; int* tails; double* vals; double* ii; double* num_outlinks; int* encoding; int* decoding; // constructors prpack_preprocessed_schur_graph(const prpack_base_graph* bg); // destructor ~prpack_preprocessed_schur_graph(); }; }; #endif python-igraph-0.8.0/vendor/source/igraph/src/prpack/prpack_edge_list.h0000644000076500000240000000034713524616145026341 0ustar tamasstaff00000000000000#ifndef PRPACK_EDGE_LIST #define PRPACK_EDGE_LIST namespace prpack { class prpack_edge_list { public: int num_vs; int num_es; int* heads; int* tails; }; }; #endif python-igraph-0.8.0/vendor/source/igraph/src/prpack/prpack_base_graph.h0000644000076500000240000000241013524616145026466 0ustar tamasstaff00000000000000#ifndef PRPACK_ADJACENCY_LIST #define PRPACK_ADJACENCY_LIST #include "prpack_csc.h" #include "prpack_csr.h" #include "prpack_edge_list.h" #include #include namespace prpack { class prpack_base_graph { private: // helper methods void initialize(); void read_smat(std::FILE* f, const bool weighted); void read_edges(std::FILE* f); void read_ascii(std::FILE* f); public: // instance variables int num_vs; int num_es; int num_self_es; int* heads; int* tails; double* vals; // constructors prpack_base_graph(); // only to support inheritance prpack_base_graph(const prpack_csc* g); prpack_base_graph(const prpack_int64_csc* g); prpack_base_graph(const prpack_csr* g); prpack_base_graph(const prpack_edge_list* g); prpack_base_graph(const char* filename, const char* format, const bool weighted); prpack_base_graph(int nverts, int nedges, std::pair* edges); // destructor ~prpack_base_graph(); // operations void normalize_weights(); }; }; #endif python-igraph-0.8.0/vendor/source/igraph/src/prpack/prpack_result.cpp0000644000076500000240000000025613524616145026252 0ustar tamasstaff00000000000000#include "prpack_result.h" #include using namespace prpack; prpack_result::prpack_result() { x = NULL; } prpack_result::~prpack_result() { delete[] x; } python-igraph-0.8.0/vendor/source/igraph/src/prpack/prpack_solver.h0000644000076500000240000001547213524616145025721 0ustar tamasstaff00000000000000#ifndef PRPACK_SOLVER #define PRPACK_SOLVER #include "prpack_base_graph.h" #include "prpack_csc.h" #include "prpack_csr.h" #include "prpack_edge_list.h" #include "prpack_preprocessed_ge_graph.h" #include "prpack_preprocessed_gs_graph.h" #include "prpack_preprocessed_scc_graph.h" #include "prpack_preprocessed_schur_graph.h" #include "prpack_result.h" // TODO Make this a user configurable variable #define PRPACK_SOLVER_MAX_ITERS 1000000 namespace prpack { // Solver class. class prpack_solver { private: // instance variables double read_time; prpack_base_graph* bg; prpack_preprocessed_ge_graph* geg; prpack_preprocessed_gs_graph* gsg; prpack_preprocessed_schur_graph* sg; prpack_preprocessed_scc_graph* sccg; bool owns_bg; // methods void initialize(); static prpack_result* solve_via_ge( const double alpha, const double tol, const int num_vs, const double* matrix, const double* uv); static prpack_result* solve_via_ge_uv( const double alpha, const double tol, const int num_vs, const double* matrix, const double* d, const double* u, const double* v); static prpack_result* solve_via_gs( const double alpha, const double tol, const int num_vs, const int num_es, const int* heads, const int* tails, const double* vals, const double* ii, const double* d, const double* num_outlinks, const double* u, const double* v); static prpack_result* solve_via_gs_err( const double alpha, const double tol, const int num_vs, const int num_es, const int* heads, const int* tails, const double* ii, const double* num_outlinks, const double* u, const double* v); static prpack_result* solve_via_schur_gs( const double alpha, const double tol, const int num_vs, const int num_no_in_vs, const int num_no_out_vs, const int num_es, const int* heads, const int* tails, const double* vals, const double* ii, const double* d, const double* num_outlinks, const double* uv, const int* encoding, const int* decoding, const bool should_normalize = true); static prpack_result* solve_via_schur_gs_uv( const double alpha, const double tol, const int num_vs, const int num_no_in_vs, const int num_no_out_vs, const int num_es, const int* heads, const int* tails, const double* vals, const double* ii, const double* d, const double* num_outlinks, const double* u, const double* v, const int* encoding, const int* decoding); static prpack_result* solve_via_scc_gs( const double alpha, const double tol, const int num_vs, const int num_es_inside, const int* heads_inside, const int* tails_inside, const double* vals_inside, const int num_es_outside, const int* heads_outside, const int* tails_outside, const double* vals_outside, const double* ii, const double* d, const double* num_outlinks, const double* uv, const int num_comps, const int* divisions, const int* encoding, const int* decoding, const bool should_normalize = true); static prpack_result* solve_via_scc_gs_uv( const double alpha, const double tol, const int num_vs, const int num_es_inside, const int* heads_inside, const int* tails_inside, const double* vals_inside, const int num_es_outside, const int* heads_outside, const int* tails_outside, const double* vals_outside, const double* ii, const double* d, const double* num_outlinks, const double* u, const double* v, const int num_comps, const int* divisions, const int* encoding, const int* decoding); static void ge(const int sz, double* A, double* b); static void normalize(const int length, double* x); static prpack_result* combine_uv( const int num_vs, const double* d, const double* num_outlinks, const int* encoding, const double alpha, const prpack_result* ret_u, const prpack_result* ret_v); public: // constructors prpack_solver(const prpack_csc* g); prpack_solver(const prpack_int64_csc* g); prpack_solver(const prpack_csr* g); prpack_solver(const prpack_edge_list* g); prpack_solver(prpack_base_graph* g, bool owns_bg=true); prpack_solver(const char* filename, const char* format, const bool weighted); // destructor ~prpack_solver(); // methods int get_num_vs(); prpack_result* solve(const double alpha, const double tol, const char* method); prpack_result* solve( const double alpha, const double tol, const double* u, const double* v, const char* method); }; }; #endif python-igraph-0.8.0/vendor/source/igraph/src/prpack/prpack_igraph_graph.h0000644000076500000240000000075013524616145027033 0ustar tamasstaff00000000000000#ifndef PRPACK_IGRAPH_GRAPH #define PRPACK_IGRAPH_GRAPH #ifdef PRPACK_IGRAPH_SUPPORT #include "igraph_interface.h" #include "prpack_base_graph.h" namespace prpack { class prpack_igraph_graph : public prpack_base_graph { public: // constructors explicit prpack_igraph_graph(const igraph_t* g, const igraph_vector_t* weights = 0, igraph_bool_t directed = true); }; }; // PRPACK_IGRAPH_SUPPORT #endif // PRPACK_IGRAPH_GRAPH #endif python-igraph-0.8.0/vendor/source/igraph/src/prpack/prpack.inc0000644000076500000240000000166213524616145024645 0ustar tamasstaff00000000000000PRPACK = prpack/prpack_base_graph.cpp \ prpack/prpack_igraph_graph.cpp \ prpack/prpack_preprocessed_ge_graph.cpp \ prpack/prpack_preprocessed_gs_graph.cpp \ prpack/prpack_preprocessed_scc_graph.cpp \ prpack/prpack_preprocessed_schur_graph.cpp \ prpack/prpack_result.cpp \ prpack/prpack_solver.cpp \ prpack/prpack_utils.cpp \ prpack/prpack.h \ prpack/prpack_base_graph.h \ prpack/prpack_csc.h \ prpack/prpack_csr.h \ prpack/prpack_edge_list.h \ prpack/prpack_igraph_graph.h \ prpack/prpack_preprocessed_ge_graph.h \ prpack/prpack_preprocessed_graph.h \ prpack/prpack_preprocessed_gs_graph.h \ prpack/prpack_preprocessed_scc_graph.h \ prpack/prpack_preprocessed_schur_graph.h \ prpack/prpack_result.h \ prpack/prpack_solver.h \ prpack/prpack_utils.h python-igraph-0.8.0/vendor/source/igraph/src/prpack/prpack_solver.cpp0000644000076500000240000007270713524616145026260 0ustar tamasstaff00000000000000#include "prpack_solver.h" #include "prpack_utils.h" #include #include #include #include using namespace prpack; using namespace std; void prpack_solver::initialize() { geg = NULL; gsg = NULL; sg = NULL; sccg = NULL; owns_bg = true; } prpack_solver::prpack_solver(const prpack_csc* g) { initialize(); TIME(read_time, bg = new prpack_base_graph(g)); } prpack_solver::prpack_solver(const prpack_int64_csc* g) { initialize(); TIME(read_time, bg = new prpack_base_graph(g)); } prpack_solver::prpack_solver(const prpack_csr* g) { initialize(); TIME(read_time, bg = new prpack_base_graph(g)); } prpack_solver::prpack_solver(const prpack_edge_list* g) { initialize(); TIME(read_time, bg = new prpack_base_graph(g)); } prpack_solver::prpack_solver(prpack_base_graph* g, bool owns_bg) { initialize(); this->owns_bg = owns_bg; TIME(read_time, bg = g); } prpack_solver::prpack_solver(const char* filename, const char* format, const bool weighted) { initialize(); TIME(read_time, bg = new prpack_base_graph(filename, format, weighted)); } prpack_solver::~prpack_solver() { if (owns_bg) { delete bg; } delete geg; delete gsg; delete sg; delete sccg; } int prpack_solver::get_num_vs() { return bg->num_vs; } prpack_result* prpack_solver::solve(const double alpha, const double tol, const char* method) { return solve(alpha, tol, NULL, NULL, method); } prpack_result* prpack_solver::solve( const double alpha, const double tol, const double* u, const double* v, const char* method) { double preprocess_time = 0; double compute_time = 0; prpack_result* ret = NULL; // decide which method to run string m; if (strcmp(method, "") != 0) m = string(method); else { if (bg->num_vs < 128) m = "ge"; else if (sccg != NULL) m = "sccgs"; else if (sg != NULL) m = "sg"; else m = "sccgs"; if (u != v) m += "_uv"; } // run the appropriate method if (m == "ge") { if (geg == NULL) { TIME(preprocess_time, geg = new prpack_preprocessed_ge_graph(bg)); } TIME(compute_time, ret = solve_via_ge( alpha, tol, geg->num_vs, geg->matrix, u)); } else if (m == "ge_uv") { if (geg == NULL) { TIME(preprocess_time, geg = new prpack_preprocessed_ge_graph(bg)); } TIME(compute_time, ret = solve_via_ge_uv( alpha, tol, geg->num_vs, geg->matrix, geg->d, u, v)); } else if (m == "gs") { if (gsg == NULL) { TIME(preprocess_time, gsg = new prpack_preprocessed_gs_graph(bg)); } TIME(compute_time, ret = solve_via_gs( alpha, tol, gsg->num_vs, gsg->num_es, gsg->heads, gsg->tails, gsg->vals, gsg->ii, gsg->d, gsg->num_outlinks, u, v)); } else if (m == "gserr") { if (gsg == NULL) { TIME(preprocess_time, gsg = new prpack_preprocessed_gs_graph(bg)); } TIME(compute_time, ret = solve_via_gs_err( alpha, tol, gsg->num_vs, gsg->num_es, gsg->heads, gsg->tails, gsg->ii, gsg->num_outlinks, u, v)); } else if (m == "sgs") { if (sg == NULL) { TIME(preprocess_time, sg = new prpack_preprocessed_schur_graph(bg)); } TIME(compute_time, ret = solve_via_schur_gs( alpha, tol, sg->num_vs, sg->num_no_in_vs, sg->num_no_out_vs, sg->num_es, sg->heads, sg->tails, sg->vals, sg->ii, sg->d, sg->num_outlinks, u, sg->encoding, sg->decoding)); } else if (m == "sgs_uv") { if (sg == NULL) { TIME(preprocess_time, sg = new prpack_preprocessed_schur_graph(bg)); } TIME(compute_time, ret = solve_via_schur_gs_uv( alpha, tol, sg->num_vs, sg->num_no_in_vs, sg->num_no_out_vs, sg->num_es, sg->heads, sg->tails, sg->vals, sg->ii, sg->d, sg->num_outlinks, u, v, sg->encoding, sg->decoding)); } else if (m == "sccgs") { if (sccg == NULL) { TIME(preprocess_time, sccg = new prpack_preprocessed_scc_graph(bg)); } TIME(compute_time, ret = solve_via_scc_gs( alpha, tol, sccg->num_vs, sccg->num_es_inside, sccg->heads_inside, sccg->tails_inside, sccg->vals_inside, sccg->num_es_outside, sccg->heads_outside, sccg->tails_outside, sccg->vals_outside, sccg->ii, sccg->d, sccg->num_outlinks, u, sccg->num_comps, sccg->divisions, sccg->encoding, sccg->decoding)); } else if (m == "sccgs_uv") { if (sccg == NULL) { TIME(preprocess_time, sccg = new prpack_preprocessed_scc_graph(bg)); } TIME(compute_time, ret = solve_via_scc_gs_uv( alpha, tol, sccg->num_vs, sccg->num_es_inside, sccg->heads_inside, sccg->tails_inside, sccg->vals_inside, sccg->num_es_outside, sccg->heads_outside, sccg->tails_outside, sccg->vals_outside, sccg->ii, sccg->d, sccg->num_outlinks, u, v, sccg->num_comps, sccg->divisions, sccg->encoding, sccg->decoding)); } else { // TODO: throw exception } ret->method = m.c_str(); ret->read_time = read_time; ret->preprocess_time = preprocess_time; ret->compute_time = compute_time; ret->num_vs = bg->num_vs; ret->num_es = bg->num_es; return ret; } // VARIOUS SOLVING METHODS //////////////////////////////////////////////////////////////////////// prpack_result* prpack_solver::solve_via_ge( const double alpha, const double tol, const int num_vs, const double* matrix, const double* uv) { prpack_result* ret = new prpack_result(); // initialize uv values const double uv_const = 1.0/num_vs; const int uv_exists = (uv) ? 1 : 0; uv = (uv) ? uv : &uv_const; // create matrix A double* A = new double[num_vs*num_vs]; for (int i = 0; i < num_vs*num_vs; ++i) A[i] = -alpha*matrix[i]; for (int i = 0; i < num_vs*num_vs; i += num_vs + 1) ++A[i]; // create vector b double* b = new double[num_vs]; for (int i = 0; i < num_vs; ++i) b[i] = uv[uv_exists*i]; // solve and normalize ge(num_vs, A, b); normalize(num_vs, b); // clean up and return delete[] A; ret->num_es_touched = -1; ret->x = b; return ret; } prpack_result* prpack_solver::solve_via_ge_uv( const double alpha, const double tol, const int num_vs, const double* matrix, const double* d, const double* u, const double* v) { prpack_result* ret = new prpack_result(); // initialize u and v values const double u_const = 1.0/num_vs; const double v_const = 1.0/num_vs; const int u_exists = (u) ? 1 : 0; const int v_exists = (v) ? 1 : 0; u = (u) ? u : &u_const; v = (v) ? v : &v_const; // create matrix A double* A = new double[num_vs*num_vs]; for (int i = 0; i < num_vs*num_vs; ++i) A[i] = -alpha*matrix[i]; for (int i = 0, inum_vs = 0; i < num_vs; ++i, inum_vs += num_vs) for (int j = 0; j < num_vs; ++j) A[inum_vs + j] -= alpha*u[u_exists*i]*d[j]; for (int i = 0; i < num_vs*num_vs; i += num_vs + 1) ++A[i]; // create vector b double* b = new double[num_vs]; for (int i = 0; i < num_vs; ++i) b[i] = (1 - alpha)*v[v_exists*i]; // solve ge(num_vs, A, b); // clean up and return delete[] A; ret->num_es_touched = -1; ret->x = b; return ret; } // Vanilla Gauss-Seidel. prpack_result* prpack_solver::solve_via_gs( const double alpha, const double tol, const int num_vs, const int num_es, const int* heads, const int* tails, const double* vals, const double* ii, const double* d, const double* num_outlinks, const double* u, const double* v) { prpack_result* ret = new prpack_result(); const bool weighted = vals != NULL; // initialize u and v values const double u_const = 1.0/num_vs; const double v_const = 1.0/num_vs; const int u_exists = (u) ? 1 : 0; const int v_exists = (v) ? 1 : 0; u = (u) ? u : &u_const; v = (v) ? v : &v_const; // initialize the eigenvector (and use personalization vector) double* x = new double[num_vs]; for (int i = 0; i < num_vs; ++i) x[i] = 0; // initialize delta double delta = 0; // run Gauss-Seidel ret->num_es_touched = 0; double err = 1, c = 0; do { if (weighted) { for (int i = 0; i < num_vs; ++i) { double new_val = 0; const int start_j = tails[i]; const int end_j = (i + 1 != num_vs) ? tails[i + 1] : num_es; for (int j = start_j; j < end_j; ++j) // TODO: might want to use compensation summation for large: end_j - start_j new_val += x[heads[j]]*vals[j]; new_val = alpha*new_val + (1 - alpha)*v[v_exists*i]; delta -= alpha*x[i]*d[i]; new_val += delta*u[u_exists*i]; new_val /= 1 - alpha*(d[i]*u[u_exists*i] + (1 - d[i])*ii[i]); delta += alpha*new_val*d[i]; COMPENSATED_SUM(err, x[i] - new_val, c); x[i] = new_val; } } else { for (int i = 0; i < num_vs; ++i) { const double old_val = x[i]*num_outlinks[i]; double new_val = 0; const int start_j = tails[i]; const int end_j = (i + 1 != num_vs) ? tails[i + 1] : num_es; for (int j = start_j; j < end_j; ++j) // TODO: might want to use compensation summation for large: end_j - start_j new_val += x[heads[j]]; new_val = alpha*new_val + (1 - alpha)*v[v_exists*i]; if (num_outlinks[i] < 0) { delta -= alpha*old_val; new_val += delta*u[u_exists*i]; new_val /= 1 - alpha*u[u_exists*i]; delta += alpha*new_val; } else { new_val += delta*u[u_exists*i]; new_val /= 1 - alpha*ii[i]; } COMPENSATED_SUM(err, old_val - new_val, c); x[i] = new_val/num_outlinks[i]; } } // update iteration index ret->num_es_touched += num_es; } while (err >= tol); // undo num_outlinks transformation if (!weighted) for (int i = 0; i < num_vs; ++i) x[i] *= num_outlinks[i]; // return results ret->x = x; return ret; } // Implement a gauss-seidel-like process with a strict error bound // we return a solution with 1-norm error less than tol. prpack_result* prpack_solver::solve_via_gs_err( const double alpha, const double tol, const int num_vs, const int num_es, const int* heads, const int* tails, const double* ii, const double* num_outlinks, const double* u, const double* v) { prpack_result* ret = new prpack_result(); // initialize u and v values const double u_const = 1.0/num_vs; const double v_const = 1.0/num_vs; const int u_exists = (u) ? 1 : 0; const int v_exists = (v) ? 1 : 0; u = (u) ? u : &u_const; v = (v) ? v : &v_const; // Note to Dave, we can't rescale v because we could be running this // same routine from multiple threads. // initialize the eigenvector (and use personalization vector) double* x = new double[num_vs]; for (int i = 0; i < num_vs; ++i) { x[i] = 0.; } // initialize delta double delta = 0.; // run Gauss-Seidel, note that we store x/deg[i] throughout this // iteration. int64_t maxedges = (int64_t)((double)num_es*std::min( log(tol)/log(alpha), (double)PRPACK_SOLVER_MAX_ITERS)); ret->num_es_touched = 0; double err=1., c = 0.; do { // iterate through vertices for (int i = 0; i < num_vs; ++i) { double old_val = x[i]*num_outlinks[i]; // adjust back to the "true" value. double new_val = 0.; int start_j = tails[i], end_j = (i + 1 != num_vs) ? tails[i + 1] : num_es; for (int j = start_j; j < end_j; ++j) { // TODO: might want to use compensation summation for large: end_j - start_j new_val += x[heads[j]]; } new_val = alpha*new_val + alpha*ii[i]*old_val + (1.0-alpha)*v[v_exists*i]; new_val += delta*u[u_exists*i]; // add the dangling node adjustment if (num_outlinks[i] < 0) { delta += alpha*(new_val - old_val); } // note that new_val > old_val, but the fabs is just for COMPENSATED_SUM(err, -(new_val - old_val), c); x[i] = new_val/num_outlinks[i]; } // update iteration index ret->num_es_touched += num_es; } while (err >= tol && ret->num_es_touched < maxedges); if (err >= tol) { ret->converged = 0; } else { ret->converged = 1; } // undo num_outlinks transformation for (int i = 0; i < num_vs; ++i) x[i] *= num_outlinks[i]; // return results ret->x = x; return ret; } // Gauss-Seidel using the Schur complement to separate dangling nodes. prpack_result* prpack_solver::solve_via_schur_gs( const double alpha, const double tol, const int num_vs, const int num_no_in_vs, const int num_no_out_vs, const int num_es, const int* heads, const int* tails, const double* vals, const double* ii, const double* d, const double* num_outlinks, const double* uv, const int* encoding, const int* decoding, const bool should_normalize) { prpack_result* ret = new prpack_result(); const bool weighted = vals != NULL; // initialize uv values const double uv_const = 1.0/num_vs; const int uv_exists = (uv) ? 1 : 0; uv = (uv) ? prpack_utils::permute(num_vs, uv, encoding) : &uv_const; // initialize the eigenvector (and use personalization vector) double* x = new double[num_vs]; for (int i = 0; i < num_vs - num_no_out_vs; ++i) x[i] = uv[uv_exists*i]/(1 - alpha*ii[i])/((weighted) ? 1 : num_outlinks[i]); // run Gauss-Seidel for the top left part of (I - alpha*P)*x = uv ret->num_es_touched = 0; double err, c; do { // iterate through vertices int num_es_touched = 0; err = c = 0; #pragma omp parallel for firstprivate(c) reduction(+:err, num_es_touched) schedule(dynamic, 64) for (int i = num_no_in_vs; i < num_vs - num_no_out_vs; ++i) { double new_val = 0; const int start_j = tails[i]; const int end_j = (i + 1 != num_vs) ? tails[i + 1] : num_es; if (weighted) { for (int j = start_j; j < end_j; ++j) // TODO: might want to use compensation summation for large: end_j - start_j new_val += x[heads[j]]*vals[j]; COMPENSATED_SUM(err, fabs(uv[uv_exists*i] + alpha*new_val - (1 - alpha*ii[i])*x[i]), c); new_val = (alpha*new_val + uv[uv_exists*i])/(1 - alpha*ii[i]); x[i] = new_val; } else { for (int j = start_j; j < end_j; ++j) // TODO: might want to use compensation summation for large: end_j - start_j new_val += x[heads[j]]; COMPENSATED_SUM(err, fabs(uv[uv_exists*i] + alpha*new_val - (1 - alpha*ii[i])*x[i]*num_outlinks[i]), c); new_val = (alpha*new_val + uv[uv_exists*i])/(1 - alpha*ii[i]); x[i] = new_val/num_outlinks[i]; } num_es_touched += end_j - start_j; } // update iteration index ret->num_es_touched += num_es_touched; } while (err/(1 - alpha) >= tol); // solve for the dangling nodes int num_es_touched = 0; #pragma omp parallel for reduction(+:num_es_touched) schedule(dynamic, 64) for (int i = num_vs - num_no_out_vs; i < num_vs; ++i) { x[i] = 0; const int start_j = tails[i]; const int end_j = (i + 1 != num_vs) ? tails[i + 1] : num_es; for (int j = start_j; j < end_j; ++j) x[i] += x[heads[j]]*((weighted) ? vals[j] : 1); x[i] = (alpha*x[i] + uv[uv_exists*i])/(1 - alpha*ii[i]); num_es_touched += end_j - start_j; } ret->num_es_touched += num_es_touched; // undo num_outlinks transformation if (!weighted) for (int i = 0; i < num_vs - num_no_out_vs; ++i) x[i] *= num_outlinks[i]; // normalize x to get the solution for: (I - alpha*P - alpha*u*d')*x = (1 - alpha)*v if (should_normalize) normalize(num_vs, x); // return results ret->x = prpack_utils::permute(num_vs, x, decoding); delete[] x; if (uv_exists) delete[] uv; return ret; } prpack_result* prpack_solver::solve_via_schur_gs_uv( const double alpha, const double tol, const int num_vs, const int num_no_in_vs, const int num_no_out_vs, const int num_es, const int* heads, const int* tails, const double* vals, const double* ii, const double* d, const double* num_outlinks, const double* u, const double* v, const int* encoding, const int* decoding) { // solve uv = u prpack_result* ret_u = solve_via_schur_gs( alpha, tol, num_vs, num_no_in_vs, num_no_out_vs, num_es, heads, tails, vals, ii, d, num_outlinks, u, encoding, decoding, false); // solve uv = v prpack_result* ret_v = solve_via_schur_gs( alpha, tol, num_vs, num_no_in_vs, num_no_out_vs, num_es, heads, tails, vals, ii, d, num_outlinks, v, encoding, decoding, false); // combine the u and v cases return combine_uv(num_vs, d, num_outlinks, encoding, alpha, ret_u, ret_v); } /** Gauss-Seidel using strongly connected components. * Notes: * If not weighted, then we store x[i] = "x[i]/outdegree" to * avoid additional arithmetic. We don't do this for the weighted * case because the adjustment may not be constant. */ prpack_result* prpack_solver::solve_via_scc_gs( const double alpha, const double tol, const int num_vs, const int num_es_inside, const int* heads_inside, const int* tails_inside, const double* vals_inside, const int num_es_outside, const int* heads_outside, const int* tails_outside, const double* vals_outside, const double* ii, const double* d, const double* num_outlinks, const double* uv, const int num_comps, const int* divisions, const int* encoding, const int* decoding, const bool should_normalize) { prpack_result* ret = new prpack_result(); const bool weighted = vals_inside != NULL; // initialize uv values const double uv_const = 1.0/num_vs; const int uv_exists = (uv) ? 1 : 0; uv = (uv) ? prpack_utils::permute(num_vs, uv, encoding) : &uv_const; // CHECK initialize the solution with one iteration of GS from x=0. double* x = new double[num_vs]; for (int i = 0; i < num_vs; ++i) x[i] = uv[uv_exists*i]/(1 - alpha*ii[i])/((weighted) ? 1 : num_outlinks[i]); // create x_outside double* x_outside = new double[num_vs]; // run Gauss-Seidel for (I - alpha*P)*x = uv ret->num_es_touched = 0; for (int comp_i = 0; comp_i < num_comps; ++comp_i) { const int start_comp = divisions[comp_i]; const int end_comp = (comp_i + 1 != num_comps) ? divisions[comp_i + 1] : num_vs; const bool parallelize = end_comp - start_comp > 512; // initialize relevant x_outside values for (int i = start_comp; i < end_comp; ++i) { x_outside[i] = 0; const int start_j = tails_outside[i]; const int end_j = (i + 1 != num_vs) ? tails_outside[i + 1] : num_es_outside; for (int j = start_j; j < end_j; ++j) x_outside[i] += x[heads_outside[j]]*((weighted) ? vals_outside[j] : 1.); ret->num_es_touched += end_j - start_j; } double err, c; do { int num_es_touched = 0; err = c = 0; if (parallelize) { // iterate through vertices #pragma omp parallel for firstprivate(c) reduction(+:err, num_es_touched) schedule(dynamic, 64) for (int i = start_comp; i < end_comp; ++i) { double new_val = x_outside[i]; const int start_j = tails_inside[i]; const int end_j = (i + 1 != num_vs) ? tails_inside[i + 1] : num_es_inside; if (weighted) { for (int j = start_j; j < end_j; ++j) { // TODO: might want to use compensation summation for large: end_j - start_j new_val += x[heads_inside[j]]*vals_inside[j]; } COMPENSATED_SUM(err, fabs(uv[uv_exists*i] + alpha*new_val - (1 - alpha*ii[i])*x[i]), c); x[i] = (alpha*new_val + uv[uv_exists*i])/(1 - alpha*ii[i]); } else { for (int j = start_j; j < end_j; ++j) { // TODO: might want to use compensation summation for large: end_j - start_j new_val += x[heads_inside[j]]; } COMPENSATED_SUM(err, fabs(uv[uv_exists*i] + alpha*new_val - (1 - alpha*ii[i])*x[i]*num_outlinks[i]), c); x[i] = (alpha*new_val + uv[uv_exists*i])/(1 - alpha*ii[i])/num_outlinks[i]; } num_es_touched += end_j - start_j; } } else { for (int i = start_comp; i < end_comp; ++i) { double new_val = x_outside[i]; const int start_j = tails_inside[i]; const int end_j = (i + 1 != num_vs) ? tails_inside[i + 1] : num_es_inside; if (weighted) { for (int j = start_j; j < end_j; ++j) { // TODO: might want to use compensation summation for large: end_j - start_j new_val += x[heads_inside[j]]*vals_inside[j]; } COMPENSATED_SUM(err, fabs(uv[uv_exists*i] + alpha*new_val - (1 - alpha*ii[i])*x[i]), c); x[i] = (alpha*new_val + uv[uv_exists*i])/(1 - alpha*ii[i]); } else { for (int j = start_j; j < end_j; ++j) { // TODO: might want to use compensation summation for large: end_j - start_j new_val += x[heads_inside[j]]; } COMPENSATED_SUM(err, fabs(uv[uv_exists*i] + alpha*new_val - (1 - alpha*ii[i])*x[i]*num_outlinks[i]), c); x[i] = (alpha*new_val + uv[uv_exists*i])/(1 - alpha*ii[i])/num_outlinks[i]; } num_es_touched += end_j - start_j; } } // update iteration index ret->num_es_touched += num_es_touched; } while (err/(1 - alpha) >= tol*(end_comp - start_comp)/num_vs); } // undo num_outlinks transformation if (!weighted) for (int i = 0; i < num_vs; ++i) x[i] *= num_outlinks[i]; // normalize x to get the solution for: (I - alpha*P - alpha*u*d')*x = (1 - alpha)*v if (should_normalize) normalize(num_vs, x); // return results ret->x = prpack_utils::permute(num_vs, x, decoding); delete[] x; delete[] x_outside; if (uv_exists) delete[] uv; return ret; } prpack_result* prpack_solver::solve_via_scc_gs_uv( const double alpha, const double tol, const int num_vs, const int num_es_inside, const int* heads_inside, const int* tails_inside, const double* vals_inside, const int num_es_outside, const int* heads_outside, const int* tails_outside, const double* vals_outside, const double* ii, const double* d, const double* num_outlinks, const double* u, const double* v, const int num_comps, const int* divisions, const int* encoding, const int* decoding) { // solve uv = u prpack_result* ret_u = solve_via_scc_gs( alpha, tol, num_vs, num_es_inside, heads_inside, tails_inside, vals_inside, num_es_outside, heads_outside, tails_outside, vals_outside, ii, d, num_outlinks, u, num_comps, divisions, encoding, decoding, false); // solve uv = v prpack_result* ret_v = solve_via_scc_gs( alpha, tol, num_vs, num_es_inside, heads_inside, tails_inside, vals_inside, num_es_outside, heads_outside, tails_outside, vals_outside, ii, d, num_outlinks, v, num_comps, divisions, encoding, decoding, false); // combine u and v return combine_uv(num_vs, d, num_outlinks, encoding, alpha, ret_u, ret_v); } // VARIOUS HELPER METHODS ///////////////////////////////////////////////////////////////////////// // Run Gaussian-Elimination (note: this changes A and returns the solution in b) void prpack_solver::ge(const int sz, double* A, double* b) { // put into triangular form for (int i = 0, isz = 0; i < sz; ++i, isz += sz) for (int k = 0, ksz = 0; k < i; ++k, ksz += sz) if (A[isz + k] != 0) { const double coeff = A[isz + k]/A[ksz + k]; A[isz + k] = 0; for (int j = k + 1; j < sz; ++j) A[isz + j] -= coeff*A[ksz + j]; b[i] -= coeff*b[k]; } // backwards substitution for (int i = sz - 1, isz = (sz - 1)*sz; i >= 0; --i, isz -= sz) { for (int j = i + 1; j < sz; ++j) b[i] -= A[isz + j]*b[j]; b[i] /= A[isz + i]; } } // Normalize a vector to sum to 1. void prpack_solver::normalize(const int length, double* x) { double norm = 0, c = 0; for (int i = 0; i < length; ++i) { COMPENSATED_SUM(norm, x[i], c); } norm = 1/norm; for (int i = 0; i < length; ++i) x[i] *= norm; } // Combine u and v results. prpack_result* prpack_solver::combine_uv( const int num_vs, const double* d, const double* num_outlinks, const int* encoding, const double alpha, const prpack_result* ret_u, const prpack_result* ret_v) { prpack_result* ret = new prpack_result(); const bool weighted = d != NULL; double delta_u = 0; double delta_v = 0; for (int i = 0; i < num_vs; ++i) { if ((weighted) ? (d[encoding[i]] == 1) : (num_outlinks[encoding[i]] < 0)) { delta_u += ret_u->x[i]; delta_v += ret_v->x[i]; } } const double s = ((1 - alpha)*alpha*delta_v)/(1 - alpha*delta_u); const double t = 1 - alpha; ret->x = new double[num_vs]; for (int i = 0; i < num_vs; ++i) ret->x[i] = s*ret_u->x[i] + t*ret_v->x[i]; ret->num_es_touched = ret_u->num_es_touched + ret_v->num_es_touched; // clean up and return delete ret_u; delete ret_v; return ret; } python-igraph-0.8.0/vendor/source/igraph/src/prpack/prpack_result.h0000644000076500000240000000105313524616145025713 0ustar tamasstaff00000000000000#ifndef PRPACK_RESULT #define PRPACK_RESULT namespace prpack { // Result class. class prpack_result { public: // instance variables int num_vs; int num_es; double* x; double read_time; double preprocess_time; double compute_time; long num_es_touched; const char* method; int converged; // constructor prpack_result(); // destructor ~prpack_result(); }; }; #endif python-igraph-0.8.0/vendor/source/igraph/src/prpack/prpack_csc.h0000644000076500000240000000102613524616145025145 0ustar tamasstaff00000000000000#ifndef PRPACK_CSC #define PRPACK_CSC #if !defined(_MSC_VER) && !defined (__MINGW32__) && !defined (__MINGW64__) # include #else # include typedef __int64 int64_t; #endif namespace prpack { class prpack_csc { public: int num_vs; int num_es; int* heads; int* tails; }; class prpack_int64_csc { public: int64_t num_vs; int64_t num_es; int64_t* heads; int64_t* tails; }; }; #endif python-igraph-0.8.0/vendor/source/igraph/src/prpack/prpack_preprocessed_graph.h0000644000076500000240000000051613524616145030257 0ustar tamasstaff00000000000000#ifndef PRPACK_PREPROCESSED_GRAPH #define PRPACK_PREPROCESSED_GRAPH namespace prpack { // TODO: this class should not be seeable by the users of the library. // Super graph class. class prpack_preprocessed_graph { public: int num_vs; int num_es; double* d; }; }; #endif python-igraph-0.8.0/vendor/source/igraph/src/triangles_template1.h0000644000076500000240000000531013614300625025512 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2005-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ long int no_of_nodes = igraph_vcount(graph); igraph_vit_t vit; long int nodes_to_calc; igraph_vector_t *neis1, *neis2; igraph_real_t triangles; long int i, j, k; long int neilen1, neilen2; long int *neis; igraph_lazy_adjlist_t adjlist; IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); nodes_to_calc = IGRAPH_VIT_SIZE(vit); neis = igraph_Calloc(no_of_nodes, long int); if (neis == 0) { IGRAPH_ERROR("local undirected transitivity failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, neis); IGRAPH_CHECK(igraph_vector_resize(res, nodes_to_calc)); igraph_lazy_adjlist_init(graph, &adjlist, IGRAPH_ALL, IGRAPH_SIMPLIFY); IGRAPH_FINALLY(igraph_lazy_adjlist_destroy, &adjlist); for (i = 0; !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit), i++) { long int node = IGRAPH_VIT_GET(vit); IGRAPH_ALLOW_INTERRUPTION(); neis1 = igraph_lazy_adjlist_get(&adjlist, (igraph_integer_t) node); neilen1 = igraph_vector_size(neis1); for (j = 0; j < neilen1; j++) { neis[ (long int)VECTOR(*neis1)[j] ] = i + 1; } triangles = 0; for (j = 0; j < neilen1; j++) { long int v = (long int) VECTOR(*neis1)[j]; neis2 = igraph_lazy_adjlist_get(&adjlist, (igraph_integer_t) v); neilen2 = igraph_vector_size(neis2); for (k = 0; k < neilen2; k++) { long int v2 = (long int) VECTOR(*neis2)[k]; if (neis[v2] == i + 1) { triangles += 1.0; } } } #ifdef TRANSIT if (mode == IGRAPH_TRANSITIVITY_ZERO && neilen1 < 2) { VECTOR(*res)[i] = 0.0; } else { VECTOR(*res)[i] = triangles / neilen1 / (neilen1 - 1); } #else VECTOR(*res)[i] = triangles / 2; #endif } igraph_lazy_adjlist_destroy(&adjlist); igraph_Free(neis); igraph_vit_destroy(&vit); IGRAPH_FINALLY_CLEAN(3); python-igraph-0.8.0/vendor/source/igraph/src/infomap_Node.h0000644000076500000240000000256313614300625024153 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef NODE_H #define NODE_H #include #include #include "igraph_interface.h" class Node; using namespace std; class Node { public: Node(); Node(int modulenr, double tpweight); vector members; vector< pair > inLinks; vector< pair > outLinks; double selfLink; double teleportWeight; double danglingSize; double exit; double size; }; void cpyNode(Node *newNode, Node *oldNode); #endif python-igraph-0.8.0/vendor/source/igraph/src/pstdint.h0000644000076500000240000007244213614300625023245 0ustar tamasstaff00000000000000/* A portable stdint.h **************************************************************************** * BSD License: **************************************************************************** * * Copyright (c) 2005-2007 Paul Hsieh * All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions * are met: * * 1. Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * 2. Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * 3. The name of the author may not be used to endorse or promote products * derived from this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. * **************************************************************************** * * Version 0.1.11 * * The ANSI C standard committee, for the C99 standard, specified the * inclusion of a new standard include file called stdint.h. This is * a very useful and long desired include file which contains several * very precise definitions for integer scalar types that is * critically important for making portable several classes of * applications including cryptography, hashing, variable length * integer libraries and so on. But for most developers its likely * useful just for programming sanity. * * The problem is that most compiler vendors have decided not to * implement the C99 standard, and the next C++ language standard * (which has a lot more mindshare these days) will be a long time in * coming and its unknown whether or not it will include stdint.h or * how much adoption it will have. Either way, it will be a long time * before all compilers come with a stdint.h and it also does nothing * for the extremely large number of compilers available today which * do not include this file, or anything comparable to it. * * So that's what this file is all about. Its an attempt to build a * single universal include file that works on as many platforms as * possible to deliver what stdint.h is supposed to. A few things * that should be noted about this file: * * 1) It is not guaranteed to be portable and/or present an identical * interface on all platforms. The extreme variability of the * ANSI C standard makes this an impossibility right from the * very get go. Its really only meant to be useful for the vast * majority of platforms that possess the capability of * implementing usefully and precisely defined, standard sized * integer scalars. Systems which are not intrinsically 2s * complement may produce invalid constants. * * 2) There is an unavoidable use of non-reserved symbols. * * 3) Other standard include files are invoked. * * 4) This file may come in conflict with future platforms that do * include stdint.h. The hope is that one or the other can be * used with no real difference. * * 5) In the current verison, if your platform can't represent * int32_t, int16_t and int8_t, it just dumps out with a compiler * error. * * 6) 64 bit integers may or may not be defined. Test for their * presence with the test: #ifdef INT64_MAX or #ifdef UINT64_MAX. * Note that this is different from the C99 specification which * requires the existence of 64 bit support in the compiler. If * this is not defined for your platform, yet it is capable of * dealing with 64 bits then it is because this file has not yet * been extended to cover all of your system's capabilities. * * 7) (u)intptr_t may or may not be defined. Test for its presence * with the test: #ifdef PTRDIFF_MAX. If this is not defined * for your platform, then it is because this file has not yet * been extended to cover all of your system's capabilities, not * because its optional. * * 8) The following might not been defined even if your platform is * capable of defining it: * * WCHAR_MIN * WCHAR_MAX * (u)int64_t * PTRDIFF_MIN * PTRDIFF_MAX * (u)intptr_t * * 9) The following have not been defined: * * WINT_MIN * WINT_MAX * * 10) The criteria for defining (u)int_least(*)_t isn't clear, * except for systems which don't have a type that precisely * defined 8, 16, or 32 bit types (which this include file does * not support anyways). Default definitions have been given. * * 11) The criteria for defining (u)int_fast(*)_t isn't something I * would trust to any particular compiler vendor or the ANSI C * committee. It is well known that "compatible systems" are * commonly created that have very different performance * characteristics from the systems they are compatible with, * especially those whose vendors make both the compiler and the * system. Default definitions have been given, but its strongly * recommended that users never use these definitions for any * reason (they do *NOT* deliver any serious guarantee of * improved performance -- not in this file, nor any vendor's * stdint.h). * * 12) The following macros: * * PRINTF_INTMAX_MODIFIER * PRINTF_INT64_MODIFIER * PRINTF_INT32_MODIFIER * PRINTF_INT16_MODIFIER * PRINTF_LEAST64_MODIFIER * PRINTF_LEAST32_MODIFIER * PRINTF_LEAST16_MODIFIER * PRINTF_INTPTR_MODIFIER * * are strings which have been defined as the modifiers required * for the "d", "u" and "x" printf formats to correctly output * (u)intmax_t, (u)int64_t, (u)int32_t, (u)int16_t, (u)least64_t, * (u)least32_t, (u)least16_t and (u)intptr_t types respectively. * PRINTF_INTPTR_MODIFIER is not defined for some systems which * provide their own stdint.h. PRINTF_INT64_MODIFIER is not * defined if INT64_MAX is not defined. These are an extension * beyond what C99 specifies must be in stdint.h. * * In addition, the following macros are defined: * * PRINTF_INTMAX_HEX_WIDTH * PRINTF_INT64_HEX_WIDTH * PRINTF_INT32_HEX_WIDTH * PRINTF_INT16_HEX_WIDTH * PRINTF_INT8_HEX_WIDTH * PRINTF_INTMAX_DEC_WIDTH * PRINTF_INT64_DEC_WIDTH * PRINTF_INT32_DEC_WIDTH * PRINTF_INT16_DEC_WIDTH * PRINTF_INT8_DEC_WIDTH * * Which specifies the maximum number of characters required to * print the number of that type in either hexadecimal or decimal. * These are an extension beyond what C99 specifies must be in * stdint.h. * * Compilers tested (all with 0 warnings at their highest respective * settings): Borland Turbo C 2.0, WATCOM C/C++ 11.0 (16 bits and 32 * bits), Microsoft Visual C++ 6.0 (32 bit), Microsoft Visual Studio * .net (VC7), Intel C++ 4.0, GNU gcc v3.3.3 * * This file should be considered a work in progress. Suggestions for * improvements, especially those which increase coverage are strongly * encouraged. * * Acknowledgements * * The following people have made significant contributions to the * development and testing of this file: * * Chris Howie * John Steele Scott * Dave Thorup * */ #include #include #include /* * For gcc with _STDINT_H, fill in the PRINTF_INT*_MODIFIER macros, and * do nothing else. On the Mac OS X version of gcc this is _STDINT_H_. */ #if ((defined(__STDC__) && __STDC__ && __STDC_VERSION__ >= 199901L) || (defined (__WATCOMC__) && (defined (_STDINT_H_INCLUDED) || __WATCOMC__ >= 1250)) || (defined(__GNUC__) && (defined(_STDINT_H) || defined(_STDINT_H_)) )) && !defined (_PSTDINT_H_INCLUDED) #include #define _PSTDINT_H_INCLUDED #ifndef PRINTF_INT64_MODIFIER #define PRINTF_INT64_MODIFIER "ll" #endif #ifndef PRINTF_INT32_MODIFIER #define PRINTF_INT32_MODIFIER "l" #endif #ifndef PRINTF_INT16_MODIFIER #define PRINTF_INT16_MODIFIER "h" #endif #ifndef PRINTF_INTMAX_MODIFIER #define PRINTF_INTMAX_MODIFIER PRINTF_INT64_MODIFIER #endif #ifndef PRINTF_INT64_HEX_WIDTH #define PRINTF_INT64_HEX_WIDTH "16" #endif #ifndef PRINTF_INT32_HEX_WIDTH #define PRINTF_INT32_HEX_WIDTH "8" #endif #ifndef PRINTF_INT16_HEX_WIDTH #define PRINTF_INT16_HEX_WIDTH "4" #endif #ifndef PRINTF_INT8_HEX_WIDTH #define PRINTF_INT8_HEX_WIDTH "2" #endif #ifndef PRINTF_INT64_DEC_WIDTH #define PRINTF_INT64_DEC_WIDTH "20" #endif #ifndef PRINTF_INT32_DEC_WIDTH #define PRINTF_INT32_DEC_WIDTH "10" #endif #ifndef PRINTF_INT16_DEC_WIDTH #define PRINTF_INT16_DEC_WIDTH "5" #endif #ifndef PRINTF_INT8_DEC_WIDTH #define PRINTF_INT8_DEC_WIDTH "3" #endif #ifndef PRINTF_INTMAX_HEX_WIDTH #define PRINTF_INTMAX_HEX_WIDTH PRINTF_INT64_HEX_WIDTH #endif #ifndef PRINTF_INTMAX_DEC_WIDTH #define PRINTF_INTMAX_DEC_WIDTH PRINTF_INT64_DEC_WIDTH #endif /* * Something really weird is going on with Open Watcom. Just pull some of * these duplicated definitions from Open Watcom's stdint.h file for now. */ #if defined (__WATCOMC__) && __WATCOMC__ >= 1250 #if !defined (INT64_C) #define INT64_C(x) (x + (INT64_MAX - INT64_MAX)) #endif #if !defined (UINT64_C) #define UINT64_C(x) (x + (UINT64_MAX - UINT64_MAX)) #endif #if !defined (INT32_C) #define INT32_C(x) (x + (INT32_MAX - INT32_MAX)) #endif #if !defined (UINT32_C) #define UINT32_C(x) (x + (UINT32_MAX - UINT32_MAX)) #endif #if !defined (INT16_C) #define INT16_C(x) (x) #endif #if !defined (UINT16_C) #define UINT16_C(x) (x) #endif #if !defined (INT8_C) #define INT8_C(x) (x) #endif #if !defined (UINT8_C) #define UINT8_C(x) (x) #endif #if !defined (UINT64_MAX) #define UINT64_MAX 18446744073709551615ULL #endif #if !defined (INT64_MAX) #define INT64_MAX 9223372036854775807LL #endif #if !defined (UINT32_MAX) #define UINT32_MAX 4294967295UL #endif #if !defined (INT32_MAX) #define INT32_MAX 2147483647L #endif #if !defined (INTMAX_MAX) #define INTMAX_MAX INT64_MAX #endif #if !defined (INTMAX_MIN) #define INTMAX_MIN INT64_MIN #endif #endif #endif #ifndef _PSTDINT_H_INCLUDED #define _PSTDINT_H_INCLUDED #ifndef SIZE_MAX #define SIZE_MAX (~(size_t)0) #endif /* * Deduce the type assignments from limits.h under the assumption that * integer sizes in bits are powers of 2, and follow the ANSI * definitions. */ #ifndef UINT8_MAX #define UINT8_MAX 0xff #endif #ifndef uint8_t #if (UCHAR_MAX == UINT8_MAX) || defined (S_SPLINT_S) typedef unsigned char uint8_t; #define UINT8_C(v) ((uint8_t) v) #else # error "Platform not supported" #endif #endif #ifndef INT8_MAX #define INT8_MAX 0x7f #endif #ifndef INT8_MIN #define INT8_MIN INT8_C(0x80) #endif #ifndef int8_t #if (SCHAR_MAX == INT8_MAX) || defined (S_SPLINT_S) typedef signed char int8_t; #define INT8_C(v) ((int8_t) v) #else # error "Platform not supported" #endif #endif #ifndef UINT16_MAX #define UINT16_MAX 0xffff #endif #ifndef uint16_t #if (UINT_MAX == UINT16_MAX) || defined (S_SPLINT_S) typedef unsigned int uint16_t; #ifndef PRINTF_INT16_MODIFIER #define PRINTF_INT16_MODIFIER "" #endif #define UINT16_C(v) ((uint16_t) (v)) #elif (USHRT_MAX == UINT16_MAX) typedef unsigned short uint16_t; #define UINT16_C(v) ((uint16_t) (v)) #ifndef PRINTF_INT16_MODIFIER #define PRINTF_INT16_MODIFIER "h" #endif #else #error "Platform not supported" #endif #endif #ifndef INT16_MAX #define INT16_MAX 0x7fff #endif #ifndef INT16_MIN #define INT16_MIN INT16_C(0x8000) #endif #ifndef int16_t #if (INT_MAX == INT16_MAX) || defined (S_SPLINT_S) typedef signed int int16_t; #define INT16_C(v) ((int16_t) (v)) #ifndef PRINTF_INT16_MODIFIER #define PRINTF_INT16_MODIFIER "" #endif #elif (SHRT_MAX == INT16_MAX) typedef signed short int16_t; #define INT16_C(v) ((int16_t) (v)) #ifndef PRINTF_INT16_MODIFIER #define PRINTF_INT16_MODIFIER "h" #endif #else #error "Platform not supported" #endif #endif #ifndef UINT32_MAX #define UINT32_MAX (0xffffffffUL) #endif #ifndef uint32_t #if (ULONG_MAX == UINT32_MAX) || defined (S_SPLINT_S) typedef unsigned long uint32_t; #define UINT32_C(v) v ## UL #ifndef PRINTF_INT32_MODIFIER #define PRINTF_INT32_MODIFIER "l" #endif #elif (UINT_MAX == UINT32_MAX) typedef unsigned int uint32_t; #ifndef PRINTF_INT32_MODIFIER #define PRINTF_INT32_MODIFIER "" #endif #define UINT32_C(v) v ## U #elif (USHRT_MAX == UINT32_MAX) typedef unsigned short uint32_t; #define UINT32_C(v) ((unsigned short) (v)) #ifndef PRINTF_INT32_MODIFIER #define PRINTF_INT32_MODIFIER "" #endif #else #error "Platform not supported" #endif #endif #ifndef INT32_MAX #define INT32_MAX (0x7fffffffL) #endif #ifndef INT32_MIN #define INT32_MIN INT32_C(0x80000000) #endif #ifndef int32_t #if (LONG_MAX == INT32_MAX) || defined (S_SPLINT_S) typedef signed long int32_t; #define INT32_C(v) v ## L #ifndef PRINTF_INT32_MODIFIER #define PRINTF_INT32_MODIFIER "l" #endif #elif (INT_MAX == INT32_MAX) typedef signed int int32_t; #define INT32_C(v) v #ifndef PRINTF_INT32_MODIFIER #define PRINTF_INT32_MODIFIER "" #endif #elif (SHRT_MAX == INT32_MAX) typedef signed short int32_t; #define INT32_C(v) ((short) (v)) #ifndef PRINTF_INT32_MODIFIER #define PRINTF_INT32_MODIFIER "" #endif #else #error "Platform not supported" #endif #endif /* * The macro stdint_int64_defined is temporarily used to record * whether or not 64 integer support is available. It must be * defined for any 64 integer extensions for new platforms that are * added. */ #undef stdint_int64_defined #if (defined(__STDC__) && defined(__STDC_VERSION__)) || defined (S_SPLINT_S) #if (__STDC__ && __STDC_VERSION >= 199901L) || defined (S_SPLINT_S) #define stdint_int64_defined typedef long long int64_t; typedef unsigned long long uint64_t; #define UINT64_C(v) v ## ULL #define INT64_C(v) v ## LL #ifndef PRINTF_INT64_MODIFIER #define PRINTF_INT64_MODIFIER "ll" #endif #endif #endif #if !defined (stdint_int64_defined) #if defined(__GNUC__) #define stdint_int64_defined __extension__ typedef long long int64_t; __extension__ typedef unsigned long long uint64_t; #define UINT64_C(v) v ## ULL #define INT64_C(v) v ## LL #ifndef PRINTF_INT64_MODIFIER #define PRINTF_INT64_MODIFIER "ll" #endif #elif defined(__MWERKS__) || defined (__SUNPRO_C) || defined (__SUNPRO_CC) || defined (__APPLE_CC__) || defined (_LONG_LONG) || defined (_CRAYC) || defined (S_SPLINT_S) #define stdint_int64_defined typedef long long int64_t; typedef unsigned long long uint64_t; #define UINT64_C(v) v ## ULL #define INT64_C(v) v ## LL #ifndef PRINTF_INT64_MODIFIER #define PRINTF_INT64_MODIFIER "ll" #endif #elif (defined(__WATCOMC__) && defined(__WATCOM_INT64__)) || (defined(_MSC_VER) && _INTEGRAL_MAX_BITS >= 64) || (defined (__BORLANDC__) && __BORLANDC__ > 0x460) || defined (__alpha) || defined (__DECC) #define stdint_int64_defined typedef __int64 int64_t; typedef unsigned __int64 uint64_t; #define UINT64_C(v) v ## UI64 #define INT64_C(v) v ## I64 #ifndef PRINTF_INT64_MODIFIER #define PRINTF_INT64_MODIFIER "I64" #endif #endif #endif #if !defined (LONG_LONG_MAX) && defined (INT64_C) #define LONG_LONG_MAX INT64_C (9223372036854775807) #endif #ifndef ULONG_LONG_MAX #define ULONG_LONG_MAX UINT64_C (18446744073709551615) #endif #if !defined (INT64_MAX) && defined (INT64_C) #define INT64_MAX INT64_C (9223372036854775807) #endif #if !defined (INT64_MIN) && defined (INT64_C) #define INT64_MIN INT64_C (-9223372036854775808) #endif #if !defined (UINT64_MAX) && defined (INT64_C) #define UINT64_MAX UINT64_C (18446744073709551615) #endif /* * Width of hexadecimal for number field. */ #ifndef PRINTF_INT64_HEX_WIDTH #define PRINTF_INT64_HEX_WIDTH "16" #endif #ifndef PRINTF_INT32_HEX_WIDTH #define PRINTF_INT32_HEX_WIDTH "8" #endif #ifndef PRINTF_INT16_HEX_WIDTH #define PRINTF_INT16_HEX_WIDTH "4" #endif #ifndef PRINTF_INT8_HEX_WIDTH #define PRINTF_INT8_HEX_WIDTH "2" #endif #ifndef PRINTF_INT64_DEC_WIDTH #define PRINTF_INT64_DEC_WIDTH "20" #endif #ifndef PRINTF_INT32_DEC_WIDTH #define PRINTF_INT32_DEC_WIDTH "10" #endif #ifndef PRINTF_INT16_DEC_WIDTH #define PRINTF_INT16_DEC_WIDTH "5" #endif #ifndef PRINTF_INT8_DEC_WIDTH #define PRINTF_INT8_DEC_WIDTH "3" #endif /* * Ok, lets not worry about 128 bit integers for now. Moore's law says * we don't need to worry about that until about 2040 at which point * we'll have bigger things to worry about. */ #ifdef stdint_int64_defined typedef int64_t intmax_t; typedef uint64_t uintmax_t; #define INTMAX_MAX INT64_MAX #define INTMAX_MIN INT64_MIN #define UINTMAX_MAX UINT64_MAX #define UINTMAX_C(v) UINT64_C(v) #define INTMAX_C(v) INT64_C(v) #ifndef PRINTF_INTMAX_MODIFIER #define PRINTF_INTMAX_MODIFIER PRINTF_INT64_MODIFIER #endif #ifndef PRINTF_INTMAX_HEX_WIDTH #define PRINTF_INTMAX_HEX_WIDTH PRINTF_INT64_HEX_WIDTH #endif #ifndef PRINTF_INTMAX_DEC_WIDTH #define PRINTF_INTMAX_DEC_WIDTH PRINTF_INT64_DEC_WIDTH #endif #else typedef int32_t intmax_t; typedef uint32_t uintmax_t; #define INTMAX_MAX INT32_MAX #define UINTMAX_MAX UINT32_MAX #define UINTMAX_C(v) UINT32_C(v) #define INTMAX_C(v) INT32_C(v) #ifndef PRINTF_INTMAX_MODIFIER #define PRINTF_INTMAX_MODIFIER PRINTF_INT32_MODIFIER #endif #ifndef PRINTF_INTMAX_HEX_WIDTH #define PRINTF_INTMAX_HEX_WIDTH PRINTF_INT32_HEX_WIDTH #endif #ifndef PRINTF_INTMAX_DEC_WIDTH #define PRINTF_INTMAX_DEC_WIDTH PRINTF_INT32_DEC_WIDTH #endif #endif /* * Because this file currently only supports platforms which have * precise powers of 2 as bit sizes for the default integers, the * least definitions are all trivial. Its possible that a future * version of this file could have different definitions. */ #ifndef stdint_least_defined typedef int8_t int_least8_t; typedef uint8_t uint_least8_t; typedef int16_t int_least16_t; typedef uint16_t uint_least16_t; typedef int32_t int_least32_t; typedef uint32_t uint_least32_t; #define PRINTF_LEAST32_MODIFIER PRINTF_INT32_MODIFIER #define PRINTF_LEAST16_MODIFIER PRINTF_INT16_MODIFIER #define UINT_LEAST8_MAX UINT8_MAX #define INT_LEAST8_MAX INT8_MAX #define UINT_LEAST16_MAX UINT16_MAX #define INT_LEAST16_MAX INT16_MAX #define UINT_LEAST32_MAX UINT32_MAX #define INT_LEAST32_MAX INT32_MAX #define INT_LEAST8_MIN INT8_MIN #define INT_LEAST16_MIN INT16_MIN #define INT_LEAST32_MIN INT32_MIN #ifdef stdint_int64_defined typedef int64_t int_least64_t; typedef uint64_t uint_least64_t; #define PRINTF_LEAST64_MODIFIER PRINTF_INT64_MODIFIER #define UINT_LEAST64_MAX UINT64_MAX #define INT_LEAST64_MAX INT64_MAX #define INT_LEAST64_MIN INT64_MIN #endif #endif #undef stdint_least_defined /* * The ANSI C committee pretending to know or specify anything about * performance is the epitome of misguided arrogance. The mandate of * this file is to *ONLY* ever support that absolute minimum * definition of the fast integer types, for compatibility purposes. * No extensions, and no attempt to suggest what may or may not be a * faster integer type will ever be made in this file. Developers are * warned to stay away from these types when using this or any other * stdint.h. */ typedef int_least8_t int_fast8_t; typedef uint_least8_t uint_fast8_t; typedef int_least16_t int_fast16_t; typedef uint_least16_t uint_fast16_t; typedef int_least32_t int_fast32_t; typedef uint_least32_t uint_fast32_t; #define UINT_FAST8_MAX UINT_LEAST8_MAX #define INT_FAST8_MAX INT_LEAST8_MAX #define UINT_FAST16_MAX UINT_LEAST16_MAX #define INT_FAST16_MAX INT_LEAST16_MAX #define UINT_FAST32_MAX UINT_LEAST32_MAX #define INT_FAST32_MAX INT_LEAST32_MAX #define INT_FAST8_MIN INT_LEAST8_MIN #define INT_FAST16_MIN INT_LEAST16_MIN #define INT_FAST32_MIN INT_LEAST32_MIN #ifdef stdint_int64_defined typedef int_least64_t int_fast64_t; typedef uint_least64_t uint_fast64_t; #define UINT_FAST64_MAX UINT_LEAST64_MAX #define INT_FAST64_MAX INT_LEAST64_MAX #define INT_FAST64_MIN INT_LEAST64_MIN #endif #undef stdint_int64_defined /* * Whatever piecemeal, per compiler thing we can do about the wchar_t * type limits. */ #if defined(__WATCOMC__) || defined(_MSC_VER) || defined (__GNUC__) #include #ifndef WCHAR_MIN #define WCHAR_MIN 0 #endif #ifndef WCHAR_MAX #define WCHAR_MAX ((wchar_t)-1) #endif #endif /* * Whatever piecemeal, per compiler/platform thing we can do about the * (u)intptr_t types and limits. */ #if defined (_MSC_VER) && defined (_UINTPTR_T_DEFINED) #define STDINT_H_UINTPTR_T_DEFINED #endif #ifndef STDINT_H_UINTPTR_T_DEFINED #if defined (__alpha__) || defined (__ia64__) || defined (__x86_64__) || defined (_WIN64) #define stdint_intptr_bits 64 #elif defined (__WATCOMC__) || defined (__TURBOC__) #if defined(__TINY__) || defined(__SMALL__) || defined(__MEDIUM__) #define stdint_intptr_bits 16 #else #define stdint_intptr_bits 32 #endif #elif defined (__i386__) || defined (_WIN32) || defined (WIN32) #define stdint_intptr_bits 32 #elif defined (__INTEL_COMPILER) /* TODO -- what will Intel do about x86-64? */ #endif #ifdef stdint_intptr_bits #define stdint_intptr_glue3_i(a,b,c) a##b##c #define stdint_intptr_glue3(a,b,c) stdint_intptr_glue3_i(a,b,c) #ifndef PRINTF_INTPTR_MODIFIER #define PRINTF_INTPTR_MODIFIER stdint_intptr_glue3(PRINTF_INT,stdint_intptr_bits,_MODIFIER) #endif #ifndef PTRDIFF_MAX #define PTRDIFF_MAX stdint_intptr_glue3(INT,stdint_intptr_bits,_MAX) #endif #ifndef PTRDIFF_MIN #define PTRDIFF_MIN stdint_intptr_glue3(INT,stdint_intptr_bits,_MIN) #endif #ifndef UINTPTR_MAX #define UINTPTR_MAX stdint_intptr_glue3(UINT,stdint_intptr_bits,_MAX) #endif #ifndef INTPTR_MAX #define INTPTR_MAX stdint_intptr_glue3(INT,stdint_intptr_bits,_MAX) #endif #ifndef INTPTR_MIN #define INTPTR_MIN stdint_intptr_glue3(INT,stdint_intptr_bits,_MIN) #endif #ifndef INTPTR_C #define INTPTR_C(x) stdint_intptr_glue3(INT,stdint_intptr_bits,_C)(x) #endif #ifndef UINTPTR_C #define UINTPTR_C(x) stdint_intptr_glue3(UINT,stdint_intptr_bits,_C)(x) #endif typedef stdint_intptr_glue3(uint, stdint_intptr_bits, _t) uintptr_t; typedef stdint_intptr_glue3( int, stdint_intptr_bits, _t) intptr_t; #else /* TODO -- This following is likely wrong for some platforms, and does nothing for the definition of uintptr_t. */ typedef ptrdiff_t intptr_t; #endif #define STDINT_H_UINTPTR_T_DEFINED #endif /* * Assumes sig_atomic_t is signed and we have a 2s complement machine. */ #ifndef SIG_ATOMIC_MAX #define SIG_ATOMIC_MAX ((((sig_atomic_t) 1) << (sizeof (sig_atomic_t)*CHAR_BIT-1)) - 1) #endif #endif #if defined (__TEST_PSTDINT_FOR_CORRECTNESS) /* * Please compile with the maximum warning settings to make sure macros are not * defined more than once. */ #include #include #include #define glue3_aux(x,y,z) x ## y ## z #define glue3(x,y,z) glue3_aux(x,y,z) #define DECLU(bits) glue3(uint,bits,_t) glue3(u,bits,=) glue3(UINT,bits,_C) (0); #define DECLI(bits) glue3(int,bits,_t) glue3(i,bits,=) glue3(INT,bits,_C) (0); #define DECL(us,bits) glue3(DECL,us,) (bits) #define TESTUMAX(bits) glue3(u,bits,=) glue3(~,u,bits); if (glue3(UINT,bits,_MAX) glue3(!=,u,bits)) printf ("Something wrong with UINT%d_MAX\n", bits) int main () { DECL(I, 8) DECL(U, 8) DECL(I, 16) DECL(U, 16) DECL(I, 32) DECL(U, 32) #ifdef INT64_MAX DECL(I, 64) DECL(U, 64) #endif intmax_t imax = INTMAX_C(0); uintmax_t umax = UINTMAX_C(0); char str0[256], str1[256]; sprintf (str0, "%d %x\n", 0, ~0); sprintf (str1, "%d %x\n", i8, ~0); if (0 != strcmp (str0, str1)) { printf ("Something wrong with i8 : %s\n", str1); } sprintf (str1, "%u %x\n", u8, ~0); if (0 != strcmp (str0, str1)) { printf ("Something wrong with u8 : %s\n", str1); } sprintf (str1, "%d %x\n", i16, ~0); if (0 != strcmp (str0, str1)) { printf ("Something wrong with i16 : %s\n", str1); } sprintf (str1, "%u %x\n", u16, ~0); if (0 != strcmp (str0, str1)) { printf ("Something wrong with u16 : %s\n", str1); } sprintf (str1, "%" PRINTF_INT32_MODIFIER "d %x\n", i32, ~0); if (0 != strcmp (str0, str1)) { printf ("Something wrong with i32 : %s\n", str1); } sprintf (str1, "%" PRINTF_INT32_MODIFIER "u %x\n", u32, ~0); if (0 != strcmp (str0, str1)) { printf ("Something wrong with u32 : %s\n", str1); } #ifdef INT64_MAX sprintf (str1, "%" PRINTF_INT64_MODIFIER "d %x\n", i64, ~0); if (0 != strcmp (str0, str1)) { printf ("Something wrong with i64 : %s\n", str1); } #endif sprintf (str1, "%" PRINTF_INTMAX_MODIFIER "d %x\n", imax, ~0); if (0 != strcmp (str0, str1)) { printf ("Something wrong with imax : %s\n", str1); } sprintf (str1, "%" PRINTF_INTMAX_MODIFIER "u %x\n", umax, ~0); if (0 != strcmp (str0, str1)) { printf ("Something wrong with umax : %s\n", str1); } TESTUMAX(8); TESTUMAX(16); TESTUMAX(32); #ifdef INT64_MAX TESTUMAX(64); #endif return EXIT_SUCCESS; } #endif python-igraph-0.8.0/vendor/source/igraph/src/gengraph_graph_molloy_optimized.cpp0000644000076500000240000020504313614300625030541 0ustar tamasstaff00000000000000/* * * gengraph - generation of random simple connected graphs with prescribed * degree sequence * * Copyright (C) 2006 Fabien Viger * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #include "gengraph_definitions.h" #include #include #include #include #include "gengraph_qsort.h" #include "gengraph_box_list.h" #include "gengraph_vertex_cover.h" #include "gengraph_degree_sequence.h" #include "gengraph_graph_molloy_optimized.h" #include "igraph_error.h" #include "igraph_statusbar.h" #include "igraph_progress.h" #ifndef register #define register #endif using namespace std; namespace gengraph { void graph_molloy_opt::breadth_search(int *dist, int v0, int *buff) { bool tmpbuff = (buff == NULL); if (tmpbuff) { buff = new int[n]; } for (int i = 0; i < n; i++) { dist[i] = -1; } dist[v0] = 0; int *visited = buff; int *to_visit = buff; *to_visit++ = v0; while (visited != to_visit) { int v = *visited++; int *w = neigh[v]; int dd = dist[v] + 1; for (int d = deg[v]; d--; w++) if (dist[*w] < 0) { dist[*w] = dd; *to_visit++ = *w; } } if (tmpbuff) { delete[] buff; } } int graph_molloy_opt::max_degree() { int m = 0; for (int k = 0; k < n; k++) if (deg[k] > m) { m = deg[k]; } return m; } void graph_molloy_opt::compute_neigh() { int *p = links; for (int i = 0; i < n; i++) { neigh[i] = p; p += deg[i]; } } void graph_molloy_opt::alloc(degree_sequence °s) { n = degs.size(); a = degs.sum(); assert(a % 2 == 0); deg = new int[n + a]; for (int i = 0; i < n; i++) { deg[i] = degs[i]; } links = deg + n; neigh = new int*[n]; compute_neigh(); } graph_molloy_opt::graph_molloy_opt(degree_sequence °s) { alloc(degs); } // graph_molloy_opt::graph_molloy_opt(FILE *f) { // char *buff = new char[FBUFF_SIZE]; // // How many vertices ? // if(VERBOSE()) fprintf(stderr,"Read file: #vertices="); // int i; // int n=0; // while(fgets(buff,FBUFF_SIZE,f)) if(sscanf(buff,"%d",&i)==1 && i>n) n=i; // n++; // // degrees ? // if(VERBOSE()) fprintf(stderr,"%d, #edges=",n); // int *degs = new int[n]; // for(i=0; i= i) { *(c++) = *p; } } } assert(c == b + (a / 2)); return b; } int *graph_molloy_opt::hard_copy() { int *hc = new int[2 + n + a / 2]; // to store n,a,deg[] and links[] hc[0] = n; hc[1] = a; memcpy(hc + 2, deg, sizeof(int)*n); int *c = hc + 2 + n; for (int i = 0; i < n; i++) { int *p = neigh[i]; for (int d = deg[i]; d--; p++) { assert(*p != i); if (*p >= i) { *(c++) = *p; } } } assert(c == hc + 2 + n + a / 2); return hc; } void graph_molloy_opt::restore(int* b) { int i; for (i = 0; i < n; i++) { deg[i] = 0; } int *p = links; for (i = 0; i < n - 1; i++) { p += deg[i]; deg[i] = int(neigh[i + 1] - neigh[i]); assert((neigh[i] + deg[i]) == neigh[i + 1]); while (p != neigh[i + 1]) { // b points to the current 'j' neigh[*b][deg[*b]++] = i; *(p++) = *(b++); } } } int* graph_molloy_opt::backup_degs(int *b) { if (b == NULL) { b = new int[n]; } memcpy(b, deg, sizeof(int)*n); return b; } void graph_molloy_opt::restore_degs_only(int *b) { memcpy(deg, b, sizeof(int)*n); refresh_nbarcs(); } void graph_molloy_opt::restore_degs_and_neigh(int *b) { restore_degs_only(b); compute_neigh(); } void graph_molloy_opt::restore_degs(int last_degree) { a = last_degree; deg[n - 1] = last_degree; for (int i = n - 2; i >= 0; i--) { a += (deg[i] = int(neigh[i + 1] - neigh[i])); } refresh_nbarcs(); } void graph_molloy_opt::clean() { int *b = hard_copy(); replace(b); delete[] b; } void graph_molloy_opt::replace(int *_hardcopy) { delete[] deg; n = *(_hardcopy++); a = *(_hardcopy++); deg = new int[a + n]; memcpy(deg, _hardcopy, sizeof(int)*n); links = deg + n; compute_neigh(); restore(_hardcopy + n); } int* graph_molloy_opt::components(int *comp) { int i; // breadth-first search buffer int *buff = new int[n]; // comp[i] will contain the index of the component that contains vertex i if (comp == NULL) { comp = new int[n]; } memset(comp, 0, sizeof(int)*n); // current component index int curr_comp = 0; // loop over all non-visited vertices... for (int v0 = 0; v0 < n; v0++) if (comp[v0] == 0) { curr_comp++; // initiate breadth-first search int *to_visit = buff; int *visited = buff; *(to_visit++) = v0; comp[v0] = curr_comp; // breadth-first search while (visited != to_visit) { int v = *(visited++); int d = deg[v]; for (int *w = neigh[v]; d--; w++) if (comp[*w] == 0) { comp[*w] = curr_comp; *(to_visit++) = *w; } } } // compute component sizes and store them in buff[] int nb_comp = 0; memset(buff, 0, sizeof(int)*n); for (i = 0; i < n; i++) if (buff[comp[i] - 1]++ == 0 && comp[i] > nb_comp) { nb_comp = comp[i]; } // box-sort sizes int offset = 0; int *box = pre_boxsort(buff, nb_comp, offset); for (i = nb_comp - 1; i >= 0; i--) { buff[i] = --box[buff[i] - offset]; } delete[] box; // reassign component indexes for (int *c = comp + n; comp != c--; *c = buff[*c - 1]) { } // clean.. at last! delete[] buff; return comp; } void graph_molloy_opt::giant_comp() { int *comp = components(); // Clear edges of all vertices that do not belong to comp 0 for (int i = 0; i < n; i++) if (comp[i] != 0) { deg[i] = 0; } // Clean comp[] delete[] comp; } int graph_molloy_opt::nbvertices_comp() { int *comp = components(); // Count all vertices that belong to comp 0 int nb = 0; for (int i = 0; i < n; i++) if (comp[i] == 0) { nb++; } // Clean comp[] delete[] comp; return nb; } int graph_molloy_opt::nbarcs_comp() { int *comp = components(); // Count all vertices that belong to comp 0 int nb = 0; for (int i = 0; i < n; i++) if (comp[i] == 0) { nb += deg[i]; } // Clean comp[] delete[] comp; return nb; } bool graph_molloy_opt::havelhakimi() { int i; int dmax = max_degree() + 1; // Sort vertices using basket-sort, in descending degrees int *nb = new int[dmax]; int *sorted = new int[n]; // init basket for (i = 0; i < dmax; i++) { nb[i] = 0; } // count basket for (i = 0; i < n; i++) { nb[deg[i]]++; } // cumul int c = 0; for (i = dmax - 1; i >= 0; i--) { c += nb[i]; nb[i] = -nb[i] + c; } // sort for (i = 0; i < n; i++) { sorted[nb[deg[i]]++] = i; } // Binding process starts int first = 0; // vertex with biggest residual degree int d = dmax - 1; // maximum residual degree available for (c = a / 2; c > 0; ) { // pick a vertex. we could pick any, but here we pick the one with biggest degree int v = sorted[first]; // look for current degree of v while (nb[d] <= first) { d--; } // store it in dv int dv = d; // bind it ! c -= dv; int dc = d; // residual degree of vertices we bind to int fc = ++first; // position of the first vertex with degree dc while (dv > 0 && dc > 0) { int lc = nb[dc]; if (lc != fc) { while (dv > 0 && lc > fc) { // binds v with sorted[--lc] dv--; int w = sorted[--lc]; *(neigh[v]++) = w; *(neigh[w]++) = v; } fc = nb[dc]; nb[dc] = lc; } dc--; } if (dv != 0) { // We couldn't bind entirely v delete[] nb; delete[] sorted; compute_neigh(); igraph_errorf("Error in graph_molloy_opt::havelhakimi():" " Couldn't bind vertex %d entirely " "(%d edges remaining)", __FILE__, __LINE__, IGRAPH_EINTERNAL, v, dv); return false; } } assert(c == 0); compute_neigh(); delete[] nb; delete[] sorted; return true; } bool graph_molloy_opt::is_connected() { bool *visited = new bool[n]; for (int i = n; i > 0; visited[--i] = false) { } int *to_visit = new int[n]; int *stop = to_visit; int left = n - 1; *(to_visit++) = 0; visited[0] = true; while (left > 0 && to_visit != stop) { int v = *(--to_visit); int *w = neigh[v]; for (int k = deg[v]; k--; w++) if (!visited[*w]) { visited[*w] = true; left--; *(to_visit++) = *w; } } delete[] visited; delete[] stop; assert(left >= 0); return (left == 0); } bool graph_molloy_opt::make_connected() { //assert(verify()); if (a / 2 < n - 1) { // fprintf(stderr,"\ngraph::make_connected() failed : #edges < #vertices-1\n"); return false; } int i; // Data struct for the visit : // - buff[] contains vertices to visit // - dist[V] is V's distance modulo 4 to the root of its comp, or -1 if it hasn't been visited yet #define MC_BUFF_SIZE (n+2) int *buff = new int[MC_BUFF_SIZE]; unsigned char * dist = new unsigned char[n]; #define NOT_VISITED 255 #define FORBIDDEN 254 for (i = n; i > 0; dist[--i] = NOT_VISITED) { } // Data struct to store components : either surplus trees or surplus edges are stored at buff[]'s end // - A Tree is coded by one of its vertices // - An edge (a,b) is coded by the TWO ints a and b int *ffub = buff + MC_BUFF_SIZE; edge *edges = (edge *) ffub; int *trees = ffub; int *min_ffub = buff + 1 + (MC_BUFF_SIZE % 2 ? 0 : 1); // There will be only one "fatty" component, and trees. edge fatty_edge = { -1, -1 }; bool enough_edges = false; // start main loop for (int v0 = 0; v0 < n; v0++) if (dist[v0] == NOT_VISITED) { // is v0 an isolated vertex? if (deg[v0] == 0) { delete[] dist; delete[] buff; igraph_errorf("graph_molloy_opt::make_connected() returned FALSE : " "vertex %d has degree 0", __FILE__, __LINE__, IGRAPH_EINTERNAL, v0); return false; } dist[v0] = 0; // root int *to_visit = buff; int *current = buff; *(to_visit++) = v0; // explore component connected to v0 bool is_a_tree = true; while (current != to_visit) { int v = *(current++); unsigned char current_dist = dist[v]; unsigned char next_dist = (current_dist + 1) & 0x03; //unsigned char prev_dist = (current_dist-1) & 0x03; int* ww = neigh[v]; int w; for (int k = deg[v]; k--; ww++) { if (dist[w = *ww] == NOT_VISITED) { // we didn't visit *w yet dist[w] = next_dist; *(to_visit++) = w; if (to_visit > min_ffub) { min_ffub += 2; // update limit of ffub's storage } //assert(verify()); } else if (dist[w] == next_dist || (w >= v && dist[w] == current_dist)) { // we found a removable edge if (trees != ffub) { // some trees still.. Let's merge with them! assert(trees >= min_ffub); assert(edges == (edge *)ffub); swap_edges(v, w, *trees, neigh[*trees][0]); trees++; //assert(verify()); } else if (is_a_tree) { // we must merge with the fatty component is_a_tree = false; if (fatty_edge.from < 0) { // we ARE the first component! fatty is us fatty_edge.from = v; fatty_edge.to = w; } else { // we connect to fatty swap_edges(fatty_edge.from, fatty_edge.to, v, w); fatty_edge.to = w; //assert(verify()); } } else if (!enough_edges) { // Store the removable edge for future use if (edges <= (edge *)min_ffub + 1) { enough_edges = true; } else { edges--; edges->from = v; edges->to = w; } } } } } // Mark component while (to_visit != buff) { dist[*(--to_visit)] = FORBIDDEN; } // Check if it is a tree if (is_a_tree ) { assert(deg[v0] != 0); if (edges != (edge *)ffub) { // let's bind the tree we found with a removable edge in stock assert(trees == ffub); if (edges < (edge *)min_ffub) { edges = (edge *)min_ffub; } swap_edges(v0, neigh[v0][0], edges->from, edges->to); edges++; assert(verify()); } else if (fatty_edge.from >= 0) { // if there is a fatty component, let's merge with it ! and discard fatty :-/ assert(trees == ffub); swap_edges(v0, neigh[v0][0], fatty_edge.from, fatty_edge.to); fatty_edge.from = -1; fatty_edge.to = -1; assert(verify()); } else { // add the tree to the list of trees assert(trees > min_ffub); *(--trees) = v0; assert(verify()); } } } delete[] buff; delete[] dist; // Should ALWAYS return true : either we have no tree left, or we are a unique, big tree return (trees == ffub || ((trees + 1) == ffub && fatty_edge.from < 0)); } bool graph_molloy_opt::swap_edges_simple(int from1, int to1, int from2, int to2) { if (from1 == to1 || from1 == from2 || from1 == to2 || to1 == from2 || to1 == to2 || from2 == to2) { return false; } if (is_edge(from1, to2) || is_edge(from2, to1)) { return false; } swap_edges(from1, to1, from2, to2); return true; } long graph_molloy_opt::fab_connected_shuffle(long times) { //assert(verify()); long nb_swaps = 0; double T = double(min(a, times)) / 10.0; double q1 = 1.131; double q2 = 0.9237; while (times > 0) { long iperiod = max(1, long(T)); // Backup graph int *save = backup(); //assert(verify()); // Swaps long swaps = 0; for (long i = iperiod; i > 0; i--) { // Pick two random vertices int f1 = links[my_random() % a]; int f2 = links[my_random() % a]; if (f1 == f2) { continue; } // Pick two random neighbours int *f1t1 = neigh[f1] + my_random() % deg[f1]; int *f2t2 = neigh[f2] + my_random() % deg[f2]; int t1 = *f1t1; int t2 = *f2t2; // test simplicity if (t1 != t2 && f1 != t2 && f2 != t1 && is_edge(f1, t2) && !is_edge(f2, t1)) { // swap *f1t1 = t2; *f2t2 = t1; fast_rpl(neigh[t1], f1, f2); fast_rpl(neigh[t2], f2, f1); swaps++; } } //assert(verify()); // test connectivity if (is_connected()) { nb_swaps += swaps; times -= iperiod; // adjust T T *= q1; } else { restore(save); //assert(verify()); T *= q2; } delete[] save; } return nb_swaps; } long graph_molloy_opt::opt_fab_connected_shuffle(long times) { //assert(verify()); long nb_swaps = 0; double T = double(min(a, times)) / 10.0; double q1 = 1.131; double q2 = 0.9237; while (times > 0) { long iperiod = max(1, long(T)); // Backup graph int *save = backup(); //assert(verify()); // Swaps long swaps = 0; for (long i = iperiod; i > 0; i--) { // Pick two random vertices int f1 = links[my_random() % a]; int f2 = links[my_random() % a]; if (f1 == f2) { continue; } // Pick two random neighbours int *f1t1 = neigh[f1] + my_random() % deg[f1]; int *f2t2 = neigh[f2] + my_random() % deg[f2]; int t1 = *f1t1; int t2 = *f2t2; if ( // test simplicity t1 != t2 && f1 != t2 && f2 != t1 && is_edge(f1, t2) && !is_edge(f2, t1) && // test isolated pair (deg[f1] > 1 || deg[t2] > 1) && (deg[f2] > 1 || deg[t1] > 1) ) { // swap *f1t1 = t2; *f2t2 = t1; fast_rpl(neigh[t1], f1, f2); fast_rpl(neigh[t2], f2, f1); swaps++; } } //assert(verify()); // test connectivity if (is_connected()) { nb_swaps += swaps; times -= iperiod; // adjust T T *= q1; } else { restore(save); //assert(verify()); T *= q2; } delete[] save; } return nb_swaps; } long graph_molloy_opt::gkantsidis_connected_shuffle(long times) { //assert(verify()); long nb_swaps = 0; long T = min(a, times) / 10; while (times > 0) { // Backup graph int *save = backup(); //assert(verify()); // Swaps long swaps = 0; for (int i = T; i > 0; i--) { // Pick two random vertices int f1 = links[my_random() % a]; int f2 = links[my_random() % a]; if (f1 == f2) { continue; } // Pick two random neighbours int *f1t1 = neigh[f1] + my_random() % deg[f1]; int *f2t2 = neigh[f2] + my_random() % deg[f2]; int t1 = *f1t1; int t2 = *f2t2; // test simplicity if (t1 != t2 && f1 != t2 && f2 != t1 && is_edge(f1, t2) && !is_edge(f2, t1)) { // swap *f1t1 = t2; *f2t2 = t1; fast_rpl(neigh[t1], f1, f2); fast_rpl(neigh[t2], f2, f1); swaps++; } } //assert(verify()); // test connectivity if (is_connected()) { nb_swaps += swaps; times -= T; // adjust T T++; } else { restore(save); //assert(verify()); T /= 2; if (T == 0) T = 1; } delete[] save; } return nb_swaps; } long graph_molloy_opt::slow_connected_shuffle(long times) { //assert(verify()); long nb_swaps = 0; while (times--) { // Pick two random vertices int f1 = links[my_random() % a]; int f2 = links[my_random() % a]; if (f1 == f2) { continue; } // Pick two random neighbours int *f1t1 = neigh[f1] + my_random() % deg[f1]; int *f2t2 = neigh[f2] + my_random() % deg[f2]; int t1 = *f1t1; int t2 = *f2t2; // test simplicity if (t1 != t2 && f1 != t2 && f2 != t1 && is_edge(f1, t2) && !is_edge(f2, t1)) { // swap *f1t1 = t2; *f2t2 = t1; int *t1f1 = fast_rpl(neigh[t1], f1, f2); int *t2f2 = fast_rpl(neigh[t2], f2, f1); // test connectivity if (is_connected()) { nb_swaps++; } else { // undo swap *t1f1 = f1; *t2f2 = f2; *f1t1 = t1; *f2t2 = t2; } } } return nb_swaps; } void graph_molloy_opt::print(FILE *f, bool NOZERO) { int i, j; for (i = 0; i < n; i++) { if (!NOZERO || deg[i] > 0) { fprintf(f, "%d", i); for (j = 0; j < deg[i]; j++) { fprintf(f, " %d", neigh[i][j]); } fprintf(f, "\n"); } } } long graph_molloy_opt::effective_isolated(int v, int K, int *Kbuff, bool *visited) { int i; for (i = 0; i < K; i++) { Kbuff[i] = -1; } long count = 0; int left = K; int *KB = Kbuff; //yapido = (my_random()%1000 == 0); depth_isolated(v, count, left, K, KB, visited); while (KB-- != Kbuff) { visited[*KB] = false; } //if(yapido) fprintf(stderr,"\n"); return count; } void graph_molloy_opt::depth_isolated(int v, long &calls, int &left_to_explore, int dmax, int * &Kbuff, bool *visited) { if (left_to_explore == 0) { return; } // if(yapido) fprintf(stderr,"%d ",deg[v]); if (--left_to_explore == 0) { return; } if (deg[v] + 1 >= dmax) { left_to_explore = 0; return; } *(Kbuff++) = v; visited[v] = true; calls++; int *w = neigh[v]; qsort(deg, w, deg[v]); w += deg[v]; for (int i = deg[v]; i--; ) { if (visited[*--w]) { calls++; } else { depth_isolated(*w, calls, left_to_explore, dmax, Kbuff, visited); } if (left_to_explore == 0) { break; } } } int graph_molloy_opt::depth_search(bool *visited, int *buff, int v0) { for (int i = 0; i < n; i++) { visited[i] = false; } int *to_visit = buff; int nb_visited = 1; visited[v0] = true; *(to_visit++) = v0; while (to_visit != buff && nb_visited < n) { int v = *(--to_visit); int *ww = neigh[v]; int w; for (int k = deg[v]; k--; ww++) if (!visited[w = *ww]) { visited[w] = true; nb_visited++; *(to_visit++) = w; } } return nb_visited; } int graph_molloy_opt::width_search(unsigned char *dist, int *buff, int v0, int toclear) { if (toclear >= 0) for (int i = 0; i < toclear; i++) { dist[buff[i]] = 0; } else for (int i = 0; i < n; i++) { dist[i] = 0; } int *to_visit = buff; int *to_add = buff; int nb_visited = 1; dist[v0] = 1; *(to_add++) = v0; while (to_visit != to_add && nb_visited < n) { int v = *(to_visit++); int *ww = neigh[v]; int w; unsigned char d = next_dist(dist[v]); for (int k = deg[v]; k--; ww++) if (dist[w = *ww] == 0) { dist[w] = d; nb_visited++; *(to_add++) = w; } } return nb_visited; } double graph_molloy_opt::avg_dist(unsigned char *dist, int *buff, int v0, int &nb_visited, int toclear) { nb_visited = width_search(dist, buff, v0, toclear); unsigned char curr_dist = 1; assert(curr_dist == dist[v0]); double total_dist = 0.0; int current_dist = 0; for (int p = 0; p < nb_visited; p++) { v0 = buff[p]; if (dist[v0] != curr_dist) { current_dist++; curr_dist = dist[v0]; } total_dist += double(current_dist); } nb_visited--; return total_dist / double(nb_visited); } void graph_molloy_opt::add_traceroute_edge(int v, int k, int *newdeg, double **edge_redudancy, double red) { int *ww = neigh[v] + k; int w = *ww; int k2 = 0; // Is neigh[v][k] a new edge ? if (k >= newdeg[v]) { int *p = neigh[v] + (newdeg[v]++); *ww = *p; *p = w; // Now, add the dual edge ww = neigh[w]; p = ww + (newdeg[w]); while (ww != p && *ww != v) { ww++; k2++; } if (ww == p) { // dual edge was not discovered.. search it and add it. while (*ww != v) { ww++; k2++; } *ww = *p; *p = v; newdeg[w]++; } } // if edge redudancy is asked, look for dual edge else if (edge_redudancy != NULL) for (int *ww = neigh[w]; * (ww++) != v; k2++) { } // add edge redudancy if (edge_redudancy != NULL) { edge_redudancy[v][k] += red; edge_redudancy[w][k2] += red; } assert(newdeg[v] <= deg[v]); } // dist[] MUST be full of zeros !!!! int graph_molloy_opt::breadth_path_search(int src, int *buff, double *paths, unsigned char *dist) { unsigned char last_dist = 0; unsigned char curr_dist = 1; int *to_visit = buff; int *visited = buff; *(to_visit++) = src; paths[src] = 1.0; dist[src] = curr_dist; int nb_visited = 1; while (visited != to_visit) { int v = *(visited++); if (last_dist == (curr_dist = dist[v])) { break; } unsigned char nd = next_dist(curr_dist); int *ww = neigh[v]; double p = paths[v]; for (int k = deg[v]; k--;) { int w = *(ww++); unsigned char d = dist[w]; if (d == 0) { // not visited yet ! *(to_visit++) = w; dist[w] = nd; paths[w] = p; // is it the last one ? if (++nb_visited == n) { last_dist = nd; } } else if (d == nd) if ((paths[w] += p) == numeric_limits::infinity()) { IGRAPH_ERROR("Fatal error : too many (>MAX_DOUBLE) possible" " paths in graph", IGRAPH_EOVERFLOW); } } } assert(to_visit == buff + nb_visited); return nb_visited; } // dist[] MUST be full of zeros !!!! void graph_molloy_opt::explore_usp(double *target, int nb_vertices, int *buff, double *paths, unsigned char *dist, int *newdeg, double **edge_redudancy) { while (--nb_vertices) { int v = buff[nb_vertices]; if (target[v] > 0.0) { unsigned char pd = prev_dist(dist[v]); int *ww = neigh[v]; int k = 0; // pick ONE father at random double father_index = my_random01() * paths[v]; double f = 0.0; int father = -1; while (f < father_index) { while (dist[father = ww[k++]] != pd) { } f += paths[father]; } // increase target[] of father target[father] += target[v]; // add edge, if necessary if (newdeg != NULL) { add_traceroute_edge(v, k - 1, newdeg, edge_redudancy, target[v]); } } // clear dist[] dist[v] = 0; } dist[buff[0]] = 0; } // dist[] MUST be full of zeros !!!! void graph_molloy_opt::explore_asp(double *target, int nb_vertices, int *buff, double *paths, unsigned char *dist, int *newdeg, double **edge_redudancy) { while (--nb_vertices) { int v = buff[nb_vertices]; if (target[v] > 0.0) { unsigned char pd = prev_dist(dist[v]); int *ww = neigh[v]; int dv = deg[v]; double f = target[v] / paths[v]; // pick ALL fathers register int father; for (int k = 0; k < dv; k++) if (dist[father = ww[k]] == pd) { // increase target[] of father target[father] += paths[father] * f; // add edge, if necessary if (newdeg != NULL) { add_traceroute_edge(v, k, newdeg, edge_redudancy, target[v]); } } } // clear dist[] dist[v] = 0; } dist[buff[0]] = 0; } // dist[] MUST be full of zeros !!!! void graph_molloy_opt::explore_rsp(double *target, int nb_vertices, int *buff, double *paths, unsigned char *dist, int *newdeg, double** edge_redudancy) { while (--nb_vertices) { int v = buff[nb_vertices]; if (target[v] > 0.0) { unsigned char pd = prev_dist(dist[v]); int *ww = neigh[v]; // for all fathers : do we take it ? int paths_left = int(target[v]); double father_index = paths[v]; int father; for (int k = 0; k < deg[v]; k++) if (dist[father = ww[k]] == pd) { double pf = paths[father]; int to_add_to_father = my_binomial(pf / father_index, paths_left); father_index -= pf; if (to_add_to_father > 0) { paths_left -= to_add_to_father; // increase target[] of father target[father] += to_add_to_father; // add edge, if necessary if (newdeg != NULL) { add_traceroute_edge(v, k, newdeg, edge_redudancy, target[v]); } } } } // clear dist[] dist[v] = 0; } dist[buff[0]] = 0; } double *graph_molloy_opt::vertex_betweenness(int mode, bool trivial_paths) { char MODES[3] = {'U', 'A', 'R'}; igraph_statusf("Computing vertex betweenness %cSP...", 0, MODES[mode]); // breadth-first search vertex fifo int *buff = new int[n]; // breadth-first search path count double *paths = new double[n]; // breadth-first search distance vector unsigned char *dist = new unsigned char[n]; // global betweenness double *b = new double[n]; // local betweenness (for one source) double *target = new double[n]; // init all int progress = 0; memset(dist, 0, sizeof(unsigned char)*n); for (double *yo = target + n; (yo--) != target; *yo = 1.0) { } for (double *yo = b + n; (yo--) != b; *yo = 0.0) { } int progress_steps = max(1000, n / 10); // Main loop for (int v0 = 0; v0 < n; v0++) { // Verbose if (v0 > (progress * n) / progress_steps) { progress++; igraph_progressf("Computing vertex betweenness %cSP", 100.0 * double(progress) / double(progress_steps), 0, MODES[mode]); } // Breadth-first search int nb_vertices = breadth_path_search(v0, buff, paths, dist); // initialize target[vertices in component] to 1 //for(int *yo = buff+nb_vertices; (yo--)!=buff; target[*yo]=1.0); // backwards-cumulative exploration switch (mode) { case MODE_USP: explore_usp(target, nb_vertices, buff, paths, dist); break; case MODE_ASP: explore_asp(target, nb_vertices, buff, paths, dist); break; case MODE_RSP: explore_rsp(target, nb_vertices, buff, paths, dist); break; default: IGRAPH_WARNING("graph_molloy_opt::vertex_betweenness() " "called with Invalid Mode"); } // add targets[vertices in component] to global betweenness and reset targets[] if (nb_vertices == n) { // cache optimization if all vertices are in component double *bb = b; double *tt_end = target + n; if (trivial_paths) for (double *yo = target; yo != tt_end; * (bb++) += *(yo++)) {} else { for (double *yo = target; yo != tt_end; * (bb++) += (*(yo++) - 1.0)) { } b[*buff] -= (target[*buff] - 1.0); } for (double *yo = target; yo != tt_end; * (yo++) = 1.0) { } } else { if (trivial_paths) for (int *yo = buff + nb_vertices; (yo--) != buff; b[*yo] += target[*yo]) { } else for (int *yo = buff + nb_vertices; (--yo) != buff; b[*yo] += (target[*yo] - 1.0)) { } for (int *yo = buff + nb_vertices; (yo--) != buff; target[*yo] = 1.0) { } } } // Clean all & return delete[] target; delete[] dist; delete[] buff; delete[] paths; igraph_status("Done\n", 0); return b; } double graph_molloy_opt::traceroute_sample(int mode, int nb_src, int *src, int nb_dst, int* dst, double *redudancy, double **edge_redudancy) { // verify & verbose assert(verify()); char MODES[3] = {'U', 'A', 'R'}; igraph_statusf("traceroute %cSP on G(N=%d,M=%d) with %d src and %d dst...", 0, MODES[mode], nbvertices_real(), nbarcs(), nb_src, nb_dst); // create dst[] buffer if necessary bool newdist = dst == NULL; if (newdist) { dst = new int[n]; } // breadth-first search vertex fifo int *buff = new int[n]; // breadth-first search path count double *paths = new double[n]; // breadth-first search distance vector unsigned char *dist = new unsigned char[n]; // newdeg[] allows to tag discovered edges int *newdeg = new int[n]; // target[v] is > 0 if v is a destination double *target = new double[n]; // init all int i; memset(dist, 0, sizeof(unsigned char)*n); memset(newdeg, 0, sizeof(int)*n); for (double *yo = target + n; (yo--) != target; *yo = 0.0) { } if (redudancy != NULL) for (double *yo = redudancy + n; (yo--) != redudancy; *yo = 0.0) { } // src_0 counts the number of sources having degree 0 int src_0 = 0; // nopath counts the number of pairs (src,dst) having no possible path int nopath = 0; // nb_paths & total_dist are for the average distance estimator int nb_paths = 0; double total_dist = 0; // s will be the current source int s; while (nb_src--) if (deg[s = *(src++)] == 0) { src_0++; } else { // breadth-first search int nb_vertices = breadth_path_search(s, buff, paths, dist); // do we have to pick new destinations ? if (newdist) { pick_random_dst(double(nb_dst), NULL, dst); } // mark reachable destinations as "targets" for (i = 0; i < nb_dst; i++) { if (dist[dst[i]] != 0) { target[dst[i]] = 1.0; } else { nopath++; } } // compute avg_dist estimator int current_dist = 0; unsigned char curr_dist = 1; for (int p = 1; p < nb_vertices; p++) { int v = buff[p]; if (dist[v] != curr_dist) { curr_dist = dist[v]; current_dist++; } if (target[v] > 0.0) { total_dist += double(current_dist); nb_paths++; } } // substract target[] to redudancy if needed if (redudancy != NULL) for (i = 1; i < nb_vertices; i++) { redudancy[buff[i]] -= (target[buff[i]]); } // traceroute exploration switch (mode) { case MODE_USP: explore_usp(target, nb_vertices, buff, paths, dist, newdeg, edge_redudancy); break; case MODE_ASP: explore_asp(target, nb_vertices, buff, paths, dist, newdeg, edge_redudancy); break; case MODE_RSP: explore_rsp(target, nb_vertices, buff, paths, dist, newdeg, edge_redudancy); break; default: IGRAPH_WARNING("graph_molloy_opt::traceroute_sample() called " "with Invalid Mode"); } // add target[] to redudancy[] if needed if (redudancy != NULL) for (i = 1; i < nb_vertices; i++) { redudancy[buff[i]] += (target[buff[i]]); } // clear target[] for (int *yo = buff + nb_vertices; yo-- != buff; target[*yo] = 0.0) { } } // update degrees for (i = 0; i < n; i++) { deg[i] = newdeg[i]; } refresh_nbarcs(); // clean all delete[] buff; delete[] paths; delete[] dist; delete[] newdeg; delete[] target; if (newdist) { delete[] dst; } { igraph_statusf("discovered %d vertices and %d edges\n", 0, nbvertices_real(), nbarcs()); if (src_0) igraph_warningf("%d sources had degree 0\n", __FILE__, __LINE__, -1, src_0); if (nopath) igraph_warningf("%d (src,dst) pairs had no possible path\n", __FILE__, __LINE__, -1, nopath); } return total_dist / double(nb_paths); } int graph_molloy_opt::disconnecting_edges() { int removed = 0; while (is_connected()) { // replace random edge by loops int i; do { i = pick_random_vertex(); } while (i < 0 || deg[i] < 1); int *p = neigh[i] + (my_random() % deg[i]); int j = *p; *p = i; fast_rpl(neigh[j], i, j); removed++; } return removed; } void graph_molloy_opt::vertex_covering() { vertex_cover(n, links, deg, neigh); } // optimisations a faire : // 1/ arreter le breadth-first search qd on a vu toutes les dst // 2/ faire une seule redescente pour toutes les dst. double graph_molloy_opt::path_sampling(int *nb_dst, int *dst, double* redudancies, double **edge_redudancies) { assert(verify()); // do we have to store the destinations (for one src) in a temp buffer? bool NOMEM = (dst == NULL); if (NOMEM) { dst = new int[n]; } int i; int next_step = n + 1; { igraph_status("Sampling paths", 0); next_step = 0; } // breadth-first search buffers buff[] and dist[] int *buff = new int[n]; unsigned char *dist = new unsigned char[n]; for (i = 0; i < n; i++) { dist[i] = 0; } // nb_pos[] counts the number of possible paths to get to a vertex int *nb_pos = new int[n]; for (i = 0; i < n; i++) { nb_pos[i] = 0; } // newdeg[i] is the number of edges of vertex i "seen" by traceroute int *newdeg = new int[n]; for (i = 0; i < n; i++) { newdeg[i] = 0; } // src_0 counts the number of sources having degree 0 int src_0 = 0; // nopath counts the number of pairs (src,dst) having no possible path int nopath = 0; // nb_paths & total_dist are for the average distance estimator int nb_paths = 0; unsigned int total_dist = 0; unsigned int total_dist64 = 0; // s is the source of the breadth-first search for (int s = 0; s < n; s++) if (nb_dst[s] > 0) { if (deg[s] == 0) { src_0++; } else { if (s > next_step) { next_step = s + (n / 1000) + 1; igraph_progress("Sampling paths", double(s) / double(n), 0); } int v; // breadth-first search int *to_visit = buff; int *visited = buff; *(to_visit++) = s; dist[s] = 1; nb_pos[s] = 1; while (visited != to_visit) { v = *(visited++); unsigned char n_dist = next_dist(dist[v]); int *w0 = neigh[v]; for (int *w = w0 + deg[v]; w-- != w0; ) { unsigned char d2 = dist[*w]; if (d2 == 0) { dist[*w] = d2 = n_dist; *(to_visit++) = *w; } if (d2 == n_dist) { nb_pos[*w] += nb_pos[v]; } } } // for every target, pick a random path. int t_index = nb_dst[s]; // create dst[] if necessary if (NOMEM) { pick_random_src(double(t_index), NULL, dst); } while (t_index--) if (dist[v = *(dst++)] == 0) { nopath++; } else { #ifdef _DEBUG igraph_statusf("Sampling path %d -> %d\n", 0, s, v); #endif //_DEBUG nb_paths++; // while we haven't reached the source.. while (v != s) { // pick a random father int index = my_random() % nb_pos[v]; unsigned char p_dist = prev_dist(dist[v]); int *w = neigh[v]; int k = 0; int new_father; while (dist[new_father = w[k]] != p_dist || (index -= nb_pos[new_father]) >= 0) { k++; } // add edge add_traceroute_edge(v, k, newdeg, edge_redudancies, 1.0); if (redudancies != NULL && new_father != s) { redudancies[new_father] += 1.0; } // step down to father v = new_father; // increase total distance total_dist++; if (total_dist == 0) { total_dist64++; } } } // reset (int *)dst if necessary if (NOMEM) { dst -= nb_dst[s]; } // clear breadth-first search buffers while (visited != buff) { v = *(--visited); dist[v] = 0; nb_pos[v] = 0; } } } // update degrees for (i = 0; i < n; i++) { deg[i] = newdeg[i]; } refresh_nbarcs(); // clean delete[] newdeg; delete[] buff; delete[] dist; delete[] nb_pos; if (NOMEM) { delete[] dst; } if (VERBOSE()) { igraph_status("Sampling paths : Done \n", 0); if (src_0) igraph_warningf("%d sources had degree 0", __FILE__, __LINE__, -1, src_0); if (nopath) igraph_warningf("%d (src,dst) pairs had no possible path", __FILE__, __LINE__, -1, nopath); } double tdist = double(total_dist64); if (total_dist64 > 0) { tdist *= 4294967296.0; } tdist += double(total_dist); return tdist / double(nb_paths); } int *graph_molloy_opt::vertices_real(int &nb_v) { int *yo; if (nb_v < 0) { nb_v = 0; for (yo = deg; yo != deg + n; ) if (*(yo++) > 0) { nb_v++; } } if (nb_v == 0) { IGRAPH_WARNING("graph is empty"); return NULL; } int *buff = new int[nb_v]; yo = buff; for (int i = 0; i < n; i++) if (deg[i] > 0) { *(yo++) = i; } if (yo != buff + nb_v) { igraph_warningf("wrong #vertices in graph_molloy_opt::vertices_real(%d)", __FILE__, __LINE__, -1, nb_v); delete[] buff; return NULL; } else { return buff; } } int *graph_molloy_opt::pick_random_vertices(int &k, int *output, int nb_v, int *among) { int i; bool CREATED_AMONG = false; if (among == NULL && k > 0) { among = vertices_real(nb_v); CREATED_AMONG = true; } if (k > nb_v) { igraph_warningf("Warning : tried to pick %d among %d vertices. " "Picked only %d", __FILE__, __LINE__, -1, k, nb_v, nb_v); k = nb_v; } if (k > 0) { if (output == NULL) { output = new int[k]; } for (i = 0; i < k; i++) { int tmp = i + my_random() % (nb_v - i); output[i] = among[tmp]; among[tmp] = among[i]; among[i] = output[i]; } } if (CREATED_AMONG) { delete[] among; } return output; } int *graph_molloy_opt::pick_random_src(double k, int *nb, int* buff, int nb_v, int* among) { bool AMONG_CREATED = false; if (among == NULL || nb_v < 0) { AMONG_CREATED = true; among = vertices_real(nb_v); } int kk = int(floor(0.5 + (k >= 1.0 ? k : k * double(nb_v)))); if (kk == 0) { kk = 1; } int *yo = pick_random_vertices(kk, buff, nb_v, among); if (nb != NULL) { *nb = kk; } if (AMONG_CREATED) { delete[] among; } return yo; } int *graph_molloy_opt::pick_random_dst(double k, int *nb, int* buff, int nb_v, int* among) { bool AMONG_CREATED = false; if (among == NULL || nb_v < 0) { AMONG_CREATED = true; among = vertices_real(nb_v); } int kk = int(floor(0.5 + (k > 1.0 ? k : k * double(nb_v)))); if (kk == 0) { kk = 1; } int *yo = pick_random_vertices(kk, buff, nb_v, among); if (nb != NULL) { *nb = kk; } if (AMONG_CREATED) { delete[] among; } return yo; } int graph_molloy_opt::core() { box_list b(n, deg); int v; int removed = 0; while ((v = b.get_one()) >= 0) { b.pop_vertex(v, neigh); deg[v] = 0; removed++; } refresh_nbarcs(); return removed; } int graph_molloy_opt::try_disconnect(int K, int max_tries) { bool *visited = new bool[n]; for (bool *p = visited + n; p != visited; * (--p) = false) { } int *Kbuff = new int[K]; int tries = 0; int next_step = -1; if (VERBOSE()) { next_step = 0; } bool yo = true; while (yo && tries < max_tries) { if (tries == next_step) { igraph_statusf("Trying to disconnect the graph... " "%d edges swaps done so far", 0, tries); next_step += 100; } int v1 = pick_random_vertex(); int v2 = pick_random_vertex(); int w1 = *(random_neighbour(v1)); int w2 = *(random_neighbour(v2)); if (swap_edges_simple(v1, w1, v2, w2)) { tries++; yo = (!isolated(v1, K, Kbuff, visited) && !isolated(v2, K, Kbuff, visited) && !is_connected()); swap_edges(v1, w2, v2, w1); } } delete[] visited; delete[] Kbuff; return tries; } bool graph_molloy_opt::isolated(int v, int K, int *Kbuff, bool *visited) { if (K < 2) { return false; } #ifdef OPT_ISOLATED if (K <= deg[v] + 1) { return false; } #endif //OPT_ISOLATED int *seen = Kbuff; int *known = Kbuff; int *max = Kbuff + (K - 1); *(known++) = v; visited[v] = true; bool is_isolated = true; while (known != seen) { v = *(seen++); int *w = neigh[v]; for (int d = deg[v]; d--; w++) if (!visited[*w]) { #ifdef OPT_ISOLATED if (K <= deg[*w] + 1 || known == max) { #else //OPT_ISOLATED if (known == max) { #endif //OPT_ISOLATED is_isolated = false; goto end_isolated; } visited[*w] = true; *(known++) = *w; } } end_isolated: // Undo the changes to visited[]... while (known != Kbuff) { visited[*(--known)] = false; } return is_isolated; } double graph_molloy_opt::rho(int mode, int nb_src, int *src, int nb_dst, int *dst) { assert(verify()); // create dst[] buffer if necessary bool newdist = dst == NULL; if (newdist) { dst = new int[n]; } // breadth-first search vertex fifo int *buff = new int[n]; // breadth-first search path count double *paths = new double[n]; // breadth-first search distance vector unsigned char *dist = new unsigned char[n]; // target[v] is > 0 if v is a destination double *target = new double[n]; // times_seen count the times we saw each vertex int *times_seen = new int[n]; // init all int i; memset(dist, 0, sizeof(unsigned char)*n); memset(times_seen, 0, sizeof(int)*n); for (double *yo = target + n; (yo--) != target; *yo = 0.0) { } // src_0 counts the number of sources having degree 0 int src_0 = 0; // nopath counts the number of pairs (src,dst) having no possible path int nopath = 0; // s will be the current source int s; for (int nsrc = 0; nsrc < nb_src; nsrc++) if (deg[s = *(src++)] == 0) { src_0++; } else { // breadth-first search int nb_vertices = breadth_path_search(s, buff, paths, dist); // do we have to pick new destinations ? if (newdist) { pick_random_dst(double(nb_dst), NULL, dst); } // mark reachable destinations as "targets" and substract one time_seen for (i = 0; i < nb_dst; i++) { if (dist[dst[i]] != 0) { target[dst[i]] = 1.0; } else { nopath++; } } // traceroute exploration switch (mode) { case MODE_USP: explore_usp(target, nb_vertices, buff, paths, dist); break; case MODE_ASP: explore_asp(target, nb_vertices, buff, paths, dist); break; case MODE_RSP: explore_rsp(target, nb_vertices, buff, paths, dist); break; default: IGRAPH_WARNING("graph_molloy_opt::rho() called with Invalid Mode"); } // remove destinations that weren't discovered by a path coming through for (i = 0; i < nb_dst; i++) { int yo = dst[i]; if (target[yo] == 1.0) { target[yo] = 0.0; } } // add target[] to times_seen[] for (i = 1; i < nb_vertices; i++) { int yo = buff[i]; if (target[yo] != 0.0) { target[yo] = 0.0; times_seen[yo]++; } } // also clear the source target[buff[0]] = 0.0; } // clean all delete[] buff; delete[] paths; delete[] dist; delete[] target; if (newdist) { delete[] dst; } // compute rho double sum_nij = 0.0; double sum_ni = 0.0; for (i = 0; i < n; i++) { double d = double(times_seen[i]); sum_ni += d; sum_nij += d * d; } delete[] times_seen; { igraph_status("done\n", 0); if (src_0) igraph_warningf("%d sources had degree 0", __FILE__, __LINE__, -1, src_0); if (nopath) igraph_warningf("%d (src,dst) pairs had no possible path", __FILE__, __LINE__, -1, nopath); } return (sum_nij - sum_ni) * double(n) * double(nb_src) / (sum_ni * sum_ni * double(nb_src - 1)); } void graph_molloy_opt::sort() { for (int v = 0; v < n; v++) { qsort(neigh[v], deg[v]); } } int* graph_molloy_opt::sort_vertices(int *buff) { // pre-sort vertices by degrees buff = boxsort(deg, n, buff); // sort vertices having the same degrees int i = 0; while (i < n) { int d = deg[buff[i]]; int j = i + 1; while (j < n && deg[buff[j]] == d) { j++; } lex_qsort(neigh, buff + i, j - i, d); i = j; } return buff; } int graph_molloy_opt::cycles(int v) { return v; } // void graph_molloy_opt::remove_vertex(int v) { // fprintf(stderr,"Warning : graph_molloy_opt::remove_vertex(%d) called",v); // } bool graph_molloy_opt::verify(int mode) { int i, j, k; assert(neigh[0] == links); // verify edges count if ((mode & VERIFY_NOARCS) == 0) { int sum = 0; for (i = 0; i < n; i++) { sum += deg[i]; } assert(sum == a); } // verify neigh[] and deg[] compatibility if ((mode & VERIFY_NONEIGH) == 0) for (i = 0; i < n - 1; i++) { assert(neigh[i] + deg[i] == neigh[i + 1]); } // verify vertex range for (i = 0; i < a; i++) { assert(links[i] >= 0 && links[i] < n); } // verify simplicity // for(i=0; i 0); } return true; } /*___________________________________________________________________________________ Not to use anymore : use graph_molloy_hash class instead void graph_molloy_opt::shuffle(long times) { while(times) { int f1 = links[my_random()%a]; int f2 = links[my_random()%a]; int t1 = neigh[f1][my_random()%deg[f1]]; int t2 = neigh[f2][my_random()%deg[f2]]; if(swap_edges_simple(f1,t1,f2,t2)) times--; } } long graph_molloy_opt::connected_shuffle(long times) { //assert(verify()); #ifdef PERFORMANCE_MONITOR long failures = 0; long successes = 0; double avg_K = 0.0; long avg_T = 0; #endif //PERFORMANCE_MONITOR long nb_swaps = 0; long T = min(a,times)/10; double double_K = 1.0; int K = int(double_K); double Q1 = 1.35; double Q2 = 1.01; int *Kbuff = new int[K]; bool *visited = new bool[n]; for(int i=0; inb_swaps) { // Backup graph #ifdef PERFORMANCE_MONITOR avg_K+=double_K; avg_T+=T; #endif //PERFORMANCE_MONITOR int *save = backup(); //assert(verify()); // Swaps long swaps = 0; for(int i=T; i>0; i--) { // Pick two random vertices int f1 = pick_random_vertex(); int f2 = pick_random_vertex(); if(f1==f2) continue; // Pick two random neighbours int *f1t1 = random_neighbour(f1); int t1 = *f1t1; int *f2t2 = random_neighbour(f2); int t2 = *f2t2; // test simplicity if(t1!=t2 && f1!=t2 && f2!=t1 && !is_edge(f1,t2) && !is_edge(f2,t1)) { // swap *f1t1 = t2; *f2t2 = t1; int *t1f1 = fast_rpl(neigh[t1],f1,f2); int *t2f2 = fast_rpl(neigh[t2],f2,f1); // isolation test if(isolated(f1, K, Kbuff, visited) || isolated(f2, K, Kbuff, visited)) { // undo swap *t1f1 = f1; *t2f2 = f2; *f1t1 = t1; *f2t2 = t2; } else swaps++; } } //assert(verify()); // test connectivity bool ok = is_connected(); #ifdef PERFORMANCE_MONITOR if(ok) successes++; else failures++; #endif //PERFORMANCE_MONITOR if(ok) { nb_swaps += swaps; // adjust K and T if((K+10)*T>5*a) { double_K/=Q2; K = int(double_K); } else T*=2; } else { restore(save); //assert(verify()); double_K*=Q1; K = int(double_K); delete[] Kbuff; Kbuff = new int[K]; } delete[] save; } #ifdef PERFORMANCE_MONITOR fprintf(stderr,"\n*** Performance Monitor ***\n"); fprintf(stderr," - Connectivity test successes : %ld\n",successes); fprintf(stderr," - Connectivity test failures : %ld\n",failures); fprintf(stderr," - Average window : %ld\n",avg_T/long(successes+failures)); fprintf(stderr," - Average isolation test width : %f\n",avg_K/double(successes+failures)); #endif //PERFORMANCE_MONITOR return nb_swaps; } bool graph_molloy_opt::try_shuffle(int T, int K) { int i; int *Kbuff = NULL; if(K>0) Kbuff = new int[K]; bool *visited = new bool[n]; for(i=0; i0; i--) { // Pick two random vertices int f1 = pick_random_vertex(); int f2 = pick_random_vertex(); if(f1==f2) continue; // Pick two random neighbours int *f1t1 = random_neighbour(f1); int t1 = *f1t1; int *f2t2 = random_neighbour(f2); int t2 = *f2t2; // test simplicity if(t1!=t2 && f1!=t2 && f2!=t1 && is_edge(f1,t2) && !is_edge(f2,t1)) { // swap *f1t1 = t2; *f2t2 = t1; int *t1f1 = fast_rpl(neigh[t1],f1,f2); int *t2f2 = fast_rpl(neigh[t2],f2,f1); // isolation test if(isolated(f1, K, Kbuff, visited) || isolated(f2, K, Kbuff, visited)) { // undo swap *t1f1 = f1; *t2f2 = f2; *f1t1 = t1; *f2t2 = t2; } } } delete[] visited; if(Kbuff != NULL) delete[] Kbuff; bool yo = is_connected(); restore(back); delete[] back; return yo; } double graph_molloy_opt::window(int K, double ratio) { int steps = 100; double T = double(a*10); double q2 = 0.1; double q1 = pow(q2,(ratio-1.0)/ratio); int failures = 0; int successes = 0; int *Kbuff = new int[K]; bool *visited = new bool[n]; while(successes<10*steps) { int *back=backup(); for(int i=int(T); i>0; i--) { // Pick two random vertices int f1 = links[my_random()%a]; int f2 = links[my_random()%a]; if(f1==f2) continue; // Pick two random neighbours int *f1t1 = neigh[f1]+my_random()%deg[f1]; int *f2t2 = neigh[f2]+my_random()%deg[f2]; int t1 = *f1t1; int t2 = *f2t2; // test simplicity if(t1!=t2 && f1!=t2 && f2!=t1 && is_edge(f1,t2) && !is_edge(f2,t1)) { // swap *f1t1 = t2; *f2t2 = t1; int *t1f1 = fast_rpl(neigh[t1],f1,f2); int *t2f2 = fast_rpl(neigh[t2],f2,f1); // isolation test if(isolated(f1, K, Kbuff, visited) || isolated(f2, K, Kbuff, visited)) { // undo swap *t1f1 = f1; *t2f2 = f2; *f1t1 = t1; *f2t2 = t2; } } } if(is_connected()) { T *= q1; if(T>double(5*a)) T=double(5*a); successes++; if((successes%steps)==0) { q2 = sqrt(q2); q1 = sqrt(q1); } } else { T*=q2; failures++; } if(VERBOSE()) fprintf(stderr,"."); restore(back); delete[] back; } delete[] Kbuff; delete[] visited; if(VERBOSE()) fprintf(stderr,"Failures:%d Successes:%d\n",failures, successes); return T; } double graph_molloy_opt::eval_K(int quality) { double K = 5.0; double avg_K = 1.0; for(int i=quality; i--; ) { int int_K = int(floor(K+0.5)); if(try_shuffle(a/(int_K+1),int_K)) { K*=0.8; fprintf(stderr,"+"); } else { K*=1.25; fprintf(stderr,"-"); } if(ideg[t2] ? f1 : t2, K, Kbuff, visited); sum_K += effective_isolated(deg[f2]>deg[t1] ? f2 : t1, K, Kbuff, visited); // undo swap swap_edges(f1,t2,f2,t1); // assert(verify()); } delete[] Kbuff; delete[] visited; return double(sum_K)/double(2*quality); } //___________________________________________________________________________________ //*/ /***** NOT USED ANYMORE (Modif 22/04/2005) ****** int64_t *graph_molloy_opt::vertex_betweenness_usp(bool trivial_paths) { if(VERBOSE()) fprintf(stderr,"Computing vertex betweenness USP..."); int i; unsigned char *dist = new unsigned char[n]; int *buff = new int[n]; int64_t *b = new int64_t[n]; int *bb = new int[n]; int *dd = new int[max_degree()]; for(i=0; i(progress*n)/1000) { progress++; fprintf(stderr,"\rComputing vertex betweenness USP : %d.%d%% ",progress/10,progress%10); } int nb_vertices = width_search(dist, buff, v0); int nv = nb_vertices; for(i=0; i(progress*n)/1000) { progress++; fprintf(stderr,"\rComputing vertex betweenness RSP : %d.%d%% ",progress/10,progress%10); } int nb_vertices = width_search(dist, buff, v0); int nv = nb_vertices; for(i=0; i1 && to_give>2*n_father) { int o = rng.binomial(1.0/n_father,to_give); to_give -= o; bb[dd[--n_father]]+=o; } if(n_father==1) bb[dd[0]]+=to_give; else { while(to_give--) bb[dd[my_random()%n_father]]++; } } if(trivial_paths) bb[v]++; } for(i=0; i0) { if(VERBOSE()==VERBOSE_LOTS && v0>(progress*n)/1000) { progress++; fprintf(stderr,"\rComputing vertex betweenness ASP : %d.%d%% ",progress/10,progress%10); } int nb_vertices = width_search(dist, buff, v0); if(!trivial_paths) dist[v0]=2; int nv = nb_vertices; for(i=0; i 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_BIGINT_H #define IGRAPH_BIGINT_H #undef __BEGIN_DECLS #undef __END_DECLS #ifdef __cplusplus #define __BEGIN_DECLS extern "C" { #define __END_DECLS } #else #define __BEGIN_DECLS /* empty */ #define __END_DECLS /* empty */ #endif #include "igraph_types.h" #include "igraph_vector.h" #include "bignum.h" #include /* Arbitrary precision integer */ #define BASE_LIMB #include "igraph_pmt.h" #include "igraph_vector_type.h" #include "igraph_vector_pmt.h" #include "igraph_pmt_off.h" #undef BASE_LIMB __BEGIN_DECLS typedef struct igraph_biguint_t { igraph_vector_limb_t v; } igraph_biguint_t; #define IGRAPH_BIGUINT_DEFAULT_SIZE 5 int igraph_biguint_init(igraph_biguint_t *b); void igraph_biguint_destroy(igraph_biguint_t *b); int igraph_biguint_copy(igraph_biguint_t *to, igraph_biguint_t *from); int igraph_biguint_extend(igraph_biguint_t *b, limb_t l); int igraph_biguint_size(igraph_biguint_t *b); int igraph_biguint_resize(igraph_biguint_t *b, int newlength); int igraph_biguint_reserve(igraph_biguint_t *b, int length); int igraph_biguint_zero(igraph_biguint_t *b); int igraph_biguint_set_limb(igraph_biguint_t *b, int value); igraph_real_t igraph_biguint_get(igraph_biguint_t *b); int igraph_biguint_compare_limb(igraph_biguint_t *b, limb_t l); int igraph_biguint_compare(igraph_biguint_t *left, igraph_biguint_t *right); igraph_bool_t igraph_biguint_equal(igraph_biguint_t *left, igraph_biguint_t *right); igraph_bool_t igraph_biguint_bigger(igraph_biguint_t *left, igraph_biguint_t *right); igraph_bool_t igraph_biguint_biggerorequal(igraph_biguint_t *left, igraph_biguint_t *right); int igraph_biguint_inc(igraph_biguint_t *res, igraph_biguint_t *b); int igraph_biguint_dec(igraph_biguint_t *res, igraph_biguint_t *b); int igraph_biguint_add_limb(igraph_biguint_t *res, igraph_biguint_t *b, limb_t l); int igraph_biguint_sub_limb(igraph_biguint_t *res, igraph_biguint_t *b, limb_t l); int igraph_biguint_mul_limb(igraph_biguint_t *res, igraph_biguint_t *b, limb_t l); int igraph_biguint_add(igraph_biguint_t *res, igraph_biguint_t *left, igraph_biguint_t *right); int igraph_biguint_sub(igraph_biguint_t *res, igraph_biguint_t *left, igraph_biguint_t *right); int igraph_biguint_mul(igraph_biguint_t *res, igraph_biguint_t *left, igraph_biguint_t *right); int igraph_biguint_div(igraph_biguint_t *q, igraph_biguint_t *r, igraph_biguint_t *u, igraph_biguint_t *v); int igraph_biguint_print(igraph_biguint_t *b); int igraph_biguint_fprint(igraph_biguint_t *b, FILE *file); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/src/igraph_hacks_internal.h0000644000076500000240000000277513614300625026101 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2003-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_HACKS_INTERNAL_H #define IGRAPH_HACKS_INTERNAL_H #include "config.h" #undef __BEGIN_DECLS #undef __END_DECLS #ifdef __cplusplus #define __BEGIN_DECLS extern "C" { #define __END_DECLS } #else #define __BEGIN_DECLS /* empty */ #define __END_DECLS /* empty */ #endif __BEGIN_DECLS #ifndef HAVE_STRDUP #define strdup igraph_i_strdup char* igraph_i_strdup(const char *s); #endif #ifndef HAVE_STPCPY #define stpcpy igraph_i_stpcpy char* igraph_i_stpcpy(char* s1, const char* s2); #else #ifndef HAVE_STPCPY_SIGNATURE char* stpcpy(char* s1, const char* s2); #endif #endif __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/src/drl_Node_3d.h0000644000076500000240000000442713614300625023672 0ustar tamasstaff00000000000000/* * Copyright 2007 Sandia Corporation. Under the terms of Contract * DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains * certain rights in this software. * * All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are * met: * * * Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * Neither the name of Sandia National Laboratories nor the names of * its contributors may be used to endorse or promote products derived from * this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT * OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED * TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF * LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING * NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. */ #ifndef __NODE_H__ #define __NODE_H__ // The node class contains information about a given node for // use by the density server process. // structure coord used to pass position information between // density server and graph class namespace drl3d { class Node { public: bool fixed; // if true do not change the // position of this node int id; float x, y, z; float sub_x, sub_y, sub_z; float energy; public: Node( int node_id ) { x = y = z = 0.0; fixed = false; id = node_id; } ~Node() { } }; } // namespace drl3d #endif //__NODE_H__ python-igraph-0.8.0/vendor/source/igraph/src/igraph_types_internal.h0000644000076500000240000003701213614300625026144 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef IGRAPH_TYPES_INTERNAL_H #define IGRAPH_TYPES_INTERNAL_H #undef __BEGIN_DECLS #undef __END_DECLS #ifdef __cplusplus #define __BEGIN_DECLS extern "C" { #define __END_DECLS } #else #define __BEGIN_DECLS /* empty */ #define __END_DECLS /* empty */ #endif #include "igraph_types.h" #include "igraph_matrix.h" #include "igraph_stack.h" #include "igraph_strvector.h" #include "igraph_vector.h" #include "igraph_vector_ptr.h" __BEGIN_DECLS /* -------------------------------------------------- */ /* Indexed heap */ /* -------------------------------------------------- */ /** * Indexed heap data type. * \ingroup internal */ typedef struct s_indheap { igraph_real_t* stor_begin; igraph_real_t* stor_end; igraph_real_t* end; int destroy; long int* index_begin; } igraph_indheap_t; #define IGRAPH_INDHEAP_NULL { 0,0,0,0,0 } int igraph_indheap_init (igraph_indheap_t* h, long int size); int igraph_indheap_init_array (igraph_indheap_t *t, igraph_real_t* data, long int len); void igraph_indheap_destroy (igraph_indheap_t* h); int igraph_indheap_clear(igraph_indheap_t *h); igraph_bool_t igraph_indheap_empty (igraph_indheap_t* h); int igraph_indheap_push (igraph_indheap_t* h, igraph_real_t elem); int igraph_indheap_push_with_index(igraph_indheap_t* h, long int idx, igraph_real_t elem); int igraph_indheap_modify(igraph_indheap_t* h, long int idx, igraph_real_t elem); igraph_real_t igraph_indheap_max (igraph_indheap_t* h); igraph_real_t igraph_indheap_delete_max(igraph_indheap_t* h); long int igraph_indheap_size (igraph_indheap_t* h); int igraph_indheap_reserve (igraph_indheap_t* h, long int size); long int igraph_indheap_max_index(igraph_indheap_t *h); void igraph_indheap_i_build(igraph_indheap_t* h, long int head); void igraph_indheap_i_shift_up(igraph_indheap_t* h, long int elem); void igraph_indheap_i_sink(igraph_indheap_t* h, long int head); void igraph_indheap_i_switch(igraph_indheap_t* h, long int e1, long int e2); /* -------------------------------------------------- */ /* Doubly indexed heap */ /* -------------------------------------------------- */ /* This is a heap containing double elements and two indices, its intended usage is the storage of weighted edges. */ /** * Doubly indexed heap data type. * \ingroup internal */ typedef struct s_indheap_d { igraph_real_t* stor_begin; igraph_real_t* stor_end; igraph_real_t* end; int destroy; long int* index_begin; long int* index2_begin; } igraph_d_indheap_t; #define IGRAPH_D_INDHEAP_NULL { 0,0,0,0,0,0 } int igraph_d_indheap_init (igraph_d_indheap_t* h, long int size); void igraph_d_indheap_destroy (igraph_d_indheap_t* h); igraph_bool_t igraph_d_indheap_empty (igraph_d_indheap_t* h); int igraph_d_indheap_push (igraph_d_indheap_t* h, igraph_real_t elem, long int idx, long int idx2); igraph_real_t igraph_d_indheap_max (igraph_d_indheap_t* h); igraph_real_t igraph_d_indheap_delete_max(igraph_d_indheap_t* h); long int igraph_d_indheap_size (igraph_d_indheap_t* h); int igraph_d_indheap_reserve (igraph_d_indheap_t* h, long int size); void igraph_d_indheap_max_index(igraph_d_indheap_t *h, long int *idx, long int *idx2); void igraph_d_indheap_i_build(igraph_d_indheap_t* h, long int head); void igraph_d_indheap_i_shift_up(igraph_d_indheap_t* h, long int elem); void igraph_d_indheap_i_sink(igraph_d_indheap_t* h, long int head); void igraph_d_indheap_i_switch(igraph_d_indheap_t* h, long int e1, long int e2); /* -------------------------------------------------- */ /* Two-way indexed heap */ /* -------------------------------------------------- */ /* This is a smart indexed heap. In addition to the "normal" indexed heap it allows to access every element through its index in O(1) time. In other words, for this heap the _modify operation is O(1), the normal heap does this in O(n) time.... */ typedef struct igraph_2wheap_t { long int size; igraph_vector_t data; igraph_vector_long_t index; igraph_vector_long_t index2; } igraph_2wheap_t; int igraph_2wheap_init(igraph_2wheap_t *h, long int size); void igraph_2wheap_destroy(igraph_2wheap_t *h); int igraph_2wheap_clear(igraph_2wheap_t *h); int igraph_2wheap_push_with_index(igraph_2wheap_t *h, long int idx, igraph_real_t elem); igraph_bool_t igraph_2wheap_empty(const igraph_2wheap_t *h); long int igraph_2wheap_size(const igraph_2wheap_t *h); long int igraph_2wheap_max_size(const igraph_2wheap_t *h); igraph_real_t igraph_2wheap_max(const igraph_2wheap_t *h); long int igraph_2wheap_max_index(const igraph_2wheap_t *h); igraph_real_t igraph_2wheap_deactivate_max(igraph_2wheap_t *h); igraph_bool_t igraph_2wheap_has_elem(const igraph_2wheap_t *h, long int idx); igraph_bool_t igraph_2wheap_has_active(const igraph_2wheap_t *h, long int idx); igraph_real_t igraph_2wheap_get(const igraph_2wheap_t *h, long int idx); igraph_real_t igraph_2wheap_delete_max(igraph_2wheap_t *h); igraph_real_t igraph_2wheap_delete_max_index(igraph_2wheap_t *h, long int *idx); int igraph_2wheap_modify(igraph_2wheap_t *h, long int idx, igraph_real_t elem); int igraph_2wheap_check(igraph_2wheap_t *h); /** * Trie data type * \ingroup internal */ typedef struct s_igraph_trie_node { igraph_strvector_t strs; igraph_vector_ptr_t children; igraph_vector_t values; } igraph_trie_node_t; typedef struct s_igraph_trie { igraph_strvector_t strs; igraph_vector_ptr_t children; igraph_vector_t values; long int maxvalue; igraph_bool_t storekeys; igraph_strvector_t keys; } igraph_trie_t; #define IGRAPH_TRIE_NULL { IGRAPH_STRVECTOR_NULL, IGRAPH_VECTOR_PTR_NULL, \ IGRAPH_VECTOR_NULL, 0, 0, IGRAPH_STRVECTOR_NULL } #define IGRAPH_TRIE_INIT_FINALLY(tr, sk) \ do { IGRAPH_CHECK(igraph_trie_init(tr, sk)); \ IGRAPH_FINALLY(igraph_trie_destroy, tr); } while (0) int igraph_trie_init(igraph_trie_t *t, igraph_bool_t storekeys); void igraph_trie_destroy(igraph_trie_t *t); int igraph_trie_get(igraph_trie_t *t, const char *key, long int *id); int igraph_trie_check(igraph_trie_t *t, const char *key, long int *id); int igraph_trie_get2(igraph_trie_t *t, const char *key, long int length, long int *id); void igraph_trie_idx(igraph_trie_t *t, long int idx, char **str); int igraph_trie_getkeys(igraph_trie_t *t, const igraph_strvector_t **strv); long int igraph_trie_size(igraph_trie_t *t); /** * 2d grid containing points */ typedef struct igraph_2dgrid_t { igraph_matrix_t *coords; igraph_real_t minx, maxx, deltax; igraph_real_t miny, maxy, deltay; long int stepsx, stepsy; igraph_matrix_t startidx; igraph_vector_t next; igraph_vector_t prev; igraph_real_t massx, massy; /* The sum of the coordinates */ long int vertices; /* Number of active vertices */ } igraph_2dgrid_t; int igraph_2dgrid_init(igraph_2dgrid_t *grid, igraph_matrix_t *coords, igraph_real_t minx, igraph_real_t maxx, igraph_real_t deltax, igraph_real_t miny, igraph_real_t maxy, igraph_real_t deltay); void igraph_2dgrid_destroy(igraph_2dgrid_t *grid); void igraph_2dgrid_add(igraph_2dgrid_t *grid, long int elem, igraph_real_t xc, igraph_real_t yc); void igraph_2dgrid_add2(igraph_2dgrid_t *grid, long int elem); void igraph_2dgrid_move(igraph_2dgrid_t *grid, long int elem, igraph_real_t xc, igraph_real_t yc); void igraph_2dgrid_getcenter(const igraph_2dgrid_t *grid, igraph_real_t *massx, igraph_real_t *massy); igraph_bool_t igraph_2dgrid_in(const igraph_2dgrid_t *grid, long int elem); igraph_real_t igraph_2dgrid_dist(const igraph_2dgrid_t *grid, long int e1, long int e2); int igraph_2dgrid_neighbors(igraph_2dgrid_t *grid, igraph_vector_t *eids, igraph_integer_t vid, igraph_real_t r); typedef struct igraph_2dgrid_iterator_t { long int vid, x, y; long int nei; long int nx[4], ny[4], ncells; } igraph_2dgrid_iterator_t; void igraph_2dgrid_reset(igraph_2dgrid_t *grid, igraph_2dgrid_iterator_t *it); igraph_integer_t igraph_2dgrid_next(igraph_2dgrid_t *grid, igraph_2dgrid_iterator_t *it); igraph_integer_t igraph_2dgrid_next_nei(igraph_2dgrid_t *grid, igraph_2dgrid_iterator_t *it); /* Another type of grid, each cell is owned by exactly one graph */ typedef struct igraph_i_layout_mergegrid_t { long int *data; long int stepsx, stepsy; igraph_real_t minx, maxx, deltax; igraph_real_t miny, maxy, deltay; } igraph_i_layout_mergegrid_t; int igraph_i_layout_mergegrid_init(igraph_i_layout_mergegrid_t *grid, igraph_real_t minx, igraph_real_t maxx, long int stepsx, igraph_real_t miny, igraph_real_t maxy, long int stepsy); void igraph_i_layout_mergegrid_destroy(igraph_i_layout_mergegrid_t *grid); int igraph_i_layout_merge_place_sphere(igraph_i_layout_mergegrid_t *grid, igraph_real_t x, igraph_real_t y, igraph_real_t r, long int id); long int igraph_i_layout_mergegrid_get(igraph_i_layout_mergegrid_t *grid, igraph_real_t x, igraph_real_t y); long int igraph_i_layout_mergegrid_get_sphere(igraph_i_layout_mergegrid_t *g, igraph_real_t x, igraph_real_t y, igraph_real_t r); /* string -> string hash table */ typedef struct igraph_hashtable_t { igraph_trie_t keys; igraph_strvector_t elements; igraph_strvector_t defaults; } igraph_hashtable_t; int igraph_hashtable_init(igraph_hashtable_t *ht); void igraph_hashtable_destroy(igraph_hashtable_t *ht); int igraph_hashtable_addset(igraph_hashtable_t *ht, const char *key, const char *def, const char *elem); int igraph_hashtable_addset2(igraph_hashtable_t *ht, const char *key, const char *def, const char *elem, int elemlen); int igraph_hashtable_get(igraph_hashtable_t *ht, const char *key, char **elem); int igraph_hashtable_getkeys(igraph_hashtable_t *ht, const igraph_strvector_t **sv); int igraph_hashtable_reset(igraph_hashtable_t *ht); /* Buckets, needed for the maximum flow algorithm */ typedef struct igraph_buckets_t { igraph_vector_long_t bptr; igraph_vector_long_t buckets; igraph_integer_t max, no; } igraph_buckets_t; int igraph_buckets_init(igraph_buckets_t *b, long int bsize, long int size); void igraph_buckets_destroy(igraph_buckets_t *b); void igraph_buckets_clear(igraph_buckets_t *b); long int igraph_buckets_popmax(igraph_buckets_t *b); long int igraph_buckets_pop(igraph_buckets_t *b, long int bucket); igraph_bool_t igraph_buckets_empty(const igraph_buckets_t *b); igraph_bool_t igraph_buckets_empty_bucket(const igraph_buckets_t *b, long int bucket); void igraph_buckets_add(igraph_buckets_t *b, long int bucket, long int elem); typedef struct igraph_dbuckets_t { igraph_vector_long_t bptr; igraph_vector_long_t next, prev; igraph_integer_t max, no; } igraph_dbuckets_t; int igraph_dbuckets_init(igraph_dbuckets_t *b, long int bsize, long int size); void igraph_dbuckets_destroy(igraph_dbuckets_t *b); void igraph_dbuckets_clear(igraph_dbuckets_t *b); long int igraph_dbuckets_popmax(igraph_dbuckets_t *b); long int igraph_dbuckets_pop(igraph_dbuckets_t *b, long int bucket); igraph_bool_t igraph_dbuckets_empty(const igraph_dbuckets_t *b); igraph_bool_t igraph_dbuckets_empty_bucket(const igraph_dbuckets_t *b, long int bucket); void igraph_dbuckets_add(igraph_dbuckets_t *b, long int bucket, long int elem); void igraph_dbuckets_delete(igraph_dbuckets_t *b, long int bucket, long int elem); /* Special maximum heap, needed for the minimum cut algorithm */ typedef struct igraph_i_cutheap_t { igraph_vector_t heap; igraph_vector_t index; igraph_vector_t hptr; long int dnodes; } igraph_i_cutheap_t; int igraph_i_cutheap_init(igraph_i_cutheap_t *ch, igraph_integer_t nodes); void igraph_i_cutheap_destroy(igraph_i_cutheap_t *ch); igraph_bool_t igraph_i_cutheap_empty(igraph_i_cutheap_t *ch); igraph_integer_t igraph_i_cutheap_active_size(igraph_i_cutheap_t *ch); igraph_integer_t igraph_i_cutheap_size(igraph_i_cutheap_t *ch); igraph_real_t igraph_i_cutheap_maxvalue(igraph_i_cutheap_t *ch); igraph_integer_t igraph_i_cutheap_popmax(igraph_i_cutheap_t *ch); int igraph_i_cutheap_update(igraph_i_cutheap_t *ch, igraph_integer_t index, igraph_real_t add); int igraph_i_cutheap_reset_undefine(igraph_i_cutheap_t *ch, long int vertex); /* -------------------------------------------------- */ /* Flexible set */ /* -------------------------------------------------- */ /** * Set containing integer numbers regardless of the order * \ingroup types */ typedef struct s_set { igraph_integer_t* stor_begin; igraph_integer_t* stor_end; igraph_integer_t* end; } igraph_set_t; #define IGRAPH_SET_NULL { 0,0,0 } #define IGRAPH_SET_INIT_FINALLY(v, size) \ do { IGRAPH_CHECK(igraph_set_init(v, size)); \ IGRAPH_FINALLY(igraph_set_destroy, v); } while (0) int igraph_set_init (igraph_set_t* set, long int size); void igraph_set_destroy (igraph_set_t* set); igraph_bool_t igraph_set_inited (igraph_set_t* set); int igraph_set_reserve (igraph_set_t* set, long int size); igraph_bool_t igraph_set_empty (const igraph_set_t* set); void igraph_set_clear (igraph_set_t* set); long int igraph_set_size (const igraph_set_t* set); int igraph_set_add (igraph_set_t* v, igraph_integer_t e); igraph_bool_t igraph_set_contains (igraph_set_t* set, igraph_integer_t e); igraph_bool_t igraph_set_iterate (igraph_set_t* set, long int* state, igraph_integer_t* element); /* -------------------------------------------------- */ /* Vectorlist, fixed length */ /* -------------------------------------------------- */ typedef struct igraph_fixed_vectorlist_t { igraph_vector_t *vecs; igraph_vector_ptr_t v; long int length; } igraph_fixed_vectorlist_t; void igraph_fixed_vectorlist_destroy(igraph_fixed_vectorlist_t *l); int igraph_fixed_vectorlist_convert(igraph_fixed_vectorlist_t *l, const igraph_vector_t *from, long int size); __END_DECLS #endif python-igraph-0.8.0/vendor/source/igraph/src/vector_ptr.c0000644000076500000240000004732313614300625023742 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2003-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_types.h" #include "igraph_vector_ptr.h" #include "igraph_memory.h" #include "igraph_random.h" #include "igraph_error.h" #include "config.h" #include #include /* memcpy & co. */ #include /** * \section about_igraph_vector_ptr_objects Pointer vectors * (igraph_vector_ptr_t) * * The \type igraph_vector_ptr_t data type is very similar to * the \type igraph_vector_t type, but it stores generic pointers instead of * real numbers. * * This type has the same space complexity as \type * igraph_vector_t, and most implemented operations work the same way * as for \type igraph_vector_t. * * This type is mostly used to pass to or receive from a set of * graphs to some \a igraph functions, such as \ref * igraph_decompose(), which decomposes a graph to connected * components. * * The same \ref VECTOR macro used for ordinary vectors can be * used for pointer vectors as well, please note that a typeless * generic pointer will be provided by this macro and you may need to * cast it to a specific pointer before starting to work with it. * * Pointer vectors may have an associated item destructor function * which takes a pointer and returns nothing. The item destructor will * be called on each item in the pointer vector when it is destroyed by * \ref igraph_vector_ptr_destroy() or \ref igraph_vector_ptr_destroy_all(), * or when its elements are freed by \ref igraph_vector_ptr_free_all(). * Note that the semantics of an item destructor does not coincide with * C++ destructors; for instance, when a pointer vector is resized to a * smaller size, the extra items will \em not be destroyed automatically! * Nevertheless, item destructors may become handy in many cases; for * instance, a vector of graphs generated by \ref igraph_decompose() can * be destroyed with a single call to \ref igraph_vector_ptr_destroy_all() * if the item destructor is set to \ref igraph_destroy(). */ /** * \ingroup vectorptr * \function igraph_vector_ptr_init * \brief Initialize a pointer vector (constructor). * * * This is the constructor of the pointer vector data type. All * pointer vectors constructed this way should be destroyed via * calling \ref igraph_vector_ptr_destroy(). * \param v Pointer to an uninitialized * igraph_vector_ptr_t object, to be created. * \param size Integer, the size of the pointer vector. * \return Error code: * \c IGRAPH_ENOMEM if out of memory * * Time complexity: operating system dependent, the amount of \quote * time \endquote required to allocate \p size elements. */ int igraph_vector_ptr_init (igraph_vector_ptr_t* v, int long size) { long int alloc_size = size > 0 ? size : 1; assert(v != NULL); if (size < 0) { size = 0; } v->stor_begin = igraph_Calloc(alloc_size, void*); if (v->stor_begin == 0) { IGRAPH_ERROR("vector ptr init failed", IGRAPH_ENOMEM); } v->stor_end = v->stor_begin + alloc_size; v->end = v->stor_begin + size; v->item_destructor = 0; return 0; } /** */ const igraph_vector_ptr_t *igraph_vector_ptr_view (const igraph_vector_ptr_t *v, void *const *data, long int length) { igraph_vector_ptr_t *v2 = (igraph_vector_ptr_t*) v; v2->stor_begin = (void **)data; v2->stor_end = (void**)data + length; v2->end = v2->stor_end; v2->item_destructor = 0; return v; } /** * \ingroup vectorptr * \function igraph_vector_ptr_destroy * \brief Destroys a pointer vector. * * * The destructor for pointer vectors. * \param v Pointer to the pointer vector to destroy. * * Time complexity: operating system dependent, the \quote time * \endquote required to deallocate O(n) bytes, n is the number of * elements allocated for the pointer vector (not necessarily the * number of elements in the vector). */ void igraph_vector_ptr_destroy (igraph_vector_ptr_t* v) { assert(v != 0); if (v->stor_begin != 0) { igraph_Free(v->stor_begin); v->stor_begin = NULL; } } void igraph_i_vector_ptr_call_item_destructor_all(igraph_vector_ptr_t* v) { void **ptr; if (v->item_destructor != 0) { for (ptr = v->stor_begin; ptr < v->end; ptr++) { if (*ptr != 0) { v->item_destructor(*ptr); } } } } /** * \ingroup vectorptr * \function igraph_vector_ptr_free_all * \brief Frees all the elements of a pointer vector. * * If an item destructor is set for this pointer vector, this function will * first call the destructor on all elements of the vector and then * free all the elements using free(). If an item destructor is not set, * the elements will simply be freed. * * \param v Pointer to the pointer vector whose elements will be freed. * * Time complexity: operating system dependent, the \quote time * \endquote required to call the destructor n times and then * deallocate O(n) pointers, each pointing to a memory area of * arbitrary size. n is the number of elements in the pointer vector. */ void igraph_vector_ptr_free_all (igraph_vector_ptr_t* v) { void **ptr; assert(v != 0); assert(v->stor_begin != 0); igraph_i_vector_ptr_call_item_destructor_all(v); for (ptr = v->stor_begin; ptr < v->end; ptr++) { igraph_Free(*ptr); } } /** * \ingroup vectorptr * \function igraph_vector_ptr_destroy_all * \brief Frees all the elements and destroys the pointer vector. * * This function is equivalent to \ref igraph_vector_ptr_free_all() * followed by \ref igraph_vector_ptr_destroy(). * * \param v Pointer to the pointer vector to destroy. * * Time complexity: operating system dependent, the \quote time * \endquote required to deallocate O(n) pointers, each pointing to * a memory area of arbitrary size, plus the \quote time \endquote * required to deallocate O(n) bytes, n being the number of elements * allocated for the pointer vector (not necessarily the number of * elements in the vector). */ void igraph_vector_ptr_destroy_all (igraph_vector_ptr_t* v) { assert(v != 0); assert(v->stor_begin != 0); igraph_vector_ptr_free_all(v); igraph_vector_ptr_set_item_destructor(v, 0); igraph_vector_ptr_destroy(v); } /** * \ingroup vectorptr * \brief Reserves memory for a pointer vector for later use. * * @return Error code: * - IGRAPH_ENOMEM: out of memory */ int igraph_vector_ptr_reserve (igraph_vector_ptr_t* v, long int size) { long int actual_size = igraph_vector_ptr_size(v); void **tmp; assert(v != NULL); assert(v->stor_begin != NULL); if (size <= igraph_vector_ptr_size(v)) { return 0; } tmp = igraph_Realloc(v->stor_begin, (size_t) size, void*); if (tmp == 0) { IGRAPH_ERROR("vector ptr reserve failed", IGRAPH_ENOMEM); } v->stor_begin = tmp; v->stor_end = v->stor_begin + size; v->end = v->stor_begin + actual_size; return 0; } /** * \ingroup vectorptr * \brief Decides whether the pointer vector is empty. */ igraph_bool_t igraph_vector_ptr_empty (const igraph_vector_ptr_t* v) { assert(v != NULL); assert(v->stor_begin != NULL); return v->stor_begin == v->end; } /** * \ingroup vectorptr * \function igraph_vector_ptr_size * \brief Gives the number of elements in the pointer vector. * * \param v The pointer vector object. * \return The size of the object, ie. the number of pointers stored. * * Time complexity: O(1). */ long int igraph_vector_ptr_size (const igraph_vector_ptr_t* v) { assert(v != NULL); /* assert(v->stor_begin != NULL); */ /* TODO */ return v->end - v->stor_begin; } /** * \ingroup vectorptr * \function igraph_vector_ptr_clear * \brief Removes all elements from a pointer vector. * * * This function resizes a pointer to vector to zero length. Note that * the pointed objects are \em not deallocated, you should call * free() on them, or make sure that their allocated memory is freed * in some other way, you'll get memory leaks otherwise. If you have * set up an item destructor earlier, the destructor will be called * on every element. * * * Note that the current implementation of this function does * \em not deallocate the memory required for storing the * pointers, so making a pointer vector smaller this way does not give * back any memory. This behavior might change in the future. * \param v The pointer vector to clear. * * Time complexity: O(1). */ void igraph_vector_ptr_clear (igraph_vector_ptr_t* v) { assert(v != NULL); assert(v->stor_begin != NULL); igraph_i_vector_ptr_call_item_destructor_all(v); v->end = v->stor_begin; } /** * \ingroup vectorptr * \function igraph_vector_ptr_push_back * \brief Appends an element to the back of a pointer vector. * * \param v The pointer vector. * \param e The new element to include in the pointer vector. * \return Error code. * \sa igraph_vector_push_back() for the corresponding operation of * the ordinary vector type. * * Time complexity: O(1) or O(n), n is the number of elements in the * vector. The pointer vector implementation ensures that n subsequent * push_back operations need O(n) time to complete. */ int igraph_vector_ptr_push_back (igraph_vector_ptr_t* v, void* e) { assert(v != NULL); assert(v->stor_begin != NULL); /* full, allocate more storage */ if (v->stor_end == v->end) { long int new_size = igraph_vector_ptr_size(v) * 2; if (new_size == 0) { new_size = 1; } IGRAPH_CHECK(igraph_vector_ptr_reserve(v, new_size)); } *(v->end) = e; v->end += 1; return 0; } void *igraph_vector_ptr_pop_back (igraph_vector_ptr_t *v) { assert(v != NULL); assert(v->stor_begin != NULL); assert(v->stor_begin != v->end); v->end -= 1; return *(v->end); } /** * \ingroup vectorptr * \function igraph_vector_ptr_insert * \brief Inserts a single element into a pointer vector. * * Note that this function does not do range checking. Insertion will shift the * elements from the position given to the end of the vector one position to the * right, and the new element will be inserted in the empty space created at * the given position. The size of the vector will increase by one. * * \param v The pointer vector object. * \param pos The position where the new element is inserted. * \param e The inserted element */ int igraph_vector_ptr_insert(igraph_vector_ptr_t* v, long int pos, void* e) { long int size = igraph_vector_ptr_size(v); IGRAPH_CHECK(igraph_vector_ptr_resize(v, size + 1)); if (pos < size) { memmove(v->stor_begin + pos + 1, v->stor_begin + pos, sizeof(void*) * (size_t) (size - pos)); } v->stor_begin[pos] = e; return 0; } /** * \ingroup vectorptr * \function igraph_vector_ptr_e * \brief Access an element of a pointer vector. * * \param v Pointer to a pointer vector. * \param pos The index of the pointer to return. * \return The pointer at \p pos position. * * Time complexity: O(1). */ void* igraph_vector_ptr_e (const igraph_vector_ptr_t* v, long int pos) { assert(v != NULL); assert(v->stor_begin != NULL); return * (v->stor_begin + pos); } /** * \ingroup vectorptr * \function igraph_vector_ptr_set * \brief Assign to an element of a pointer vector. * * \param v Pointer to a pointer vector. * \param pos The index of the pointer to update. * \param value The new pointer to set in the vector. * * Time complexity: O(1). */ void igraph_vector_ptr_set (igraph_vector_ptr_t* v, long int pos, void* value) { assert(v != NULL); assert(v->stor_begin != NULL); *(v->stor_begin + pos) = value; } /** * \ingroup vectorptr * \brief Set all elements of a pointer vector to the NULL pointer. */ void igraph_vector_ptr_null (igraph_vector_ptr_t* v) { assert(v != NULL); assert(v->stor_begin != NULL); if (igraph_vector_ptr_size(v) > 0) { memset(v->stor_begin, 0, sizeof(void*) * (size_t) igraph_vector_ptr_size(v)); } } /** * \ingroup vectorptr * \function igraph_vector_ptr_resize * \brief Resizes a pointer vector. * * * Note that if a vector is made smaller the pointed object are not * deallocated by this function and the item destructor is not called * on the extra elements. * * \param v A pointer vector. * \param newsize The new size of the pointer vector. * \return Error code. * * Time complexity: O(1) if the vector if made smaller. Operating * system dependent otherwise, the amount of \quote time \endquote * needed to allocate the memory for the vector elements. */ int igraph_vector_ptr_resize(igraph_vector_ptr_t* v, long int newsize) { IGRAPH_CHECK(igraph_vector_ptr_reserve(v, newsize)); v->end = v->stor_begin + newsize; return 0; } /** * \ingroup vectorptr * \brief Initializes a pointer vector from an array (constructor). * * \return Error code: * \c IGRAPH_ENOMEM if out of memory */ int igraph_vector_ptr_init_copy(igraph_vector_ptr_t *v, void * *data, long int length) { v->stor_begin = igraph_Calloc(length, void*); if (v->stor_begin == 0) { IGRAPH_ERROR("cannot init ptr vector from array", IGRAPH_ENOMEM); } v->stor_end = v->stor_begin + length; v->end = v->stor_end; v->item_destructor = 0; memcpy(v->stor_begin, data, (size_t) length * sizeof(void*)); return 0; } /** * \ingroup vectorptr * \brief Copy the contents of a pointer vector to a regular C array. */ void igraph_vector_ptr_copy_to(const igraph_vector_ptr_t *v, void** to) { assert(v != NULL); assert(v->stor_begin != NULL); if (v->end != v->stor_begin) { memcpy(to, v->stor_begin, sizeof(void*) * (size_t) (v->end - v->stor_begin)); } } /** * \ingroup vectorptr * \function igraph_vector_ptr_copy * \brief Copy a pointer vector (constructor). * * * This function creates a pointer vector by copying another one. This * is shallow copy, only the pointers in the vector will be copied. * * * It is potentially dangerous to copy a pointer vector with an associated * item destructor. The copied vector will inherit the item destructor, * which may cause problems when both vectors are destroyed as the items * might get destroyed twice. Make sure you know what you are doing when * copying a pointer vector with an item destructor, or unset the item * destructor on one of the vectors later. * * \param to Pointer to an uninitialized pointer vector object. * \param from A pointer vector object. * \return Error code: * \c IGRAPH_ENOMEM if out of memory * * Time complexity: O(n) if allocating memory for n elements can be * done in O(n) time. */ int igraph_vector_ptr_copy(igraph_vector_ptr_t *to, const igraph_vector_ptr_t *from) { assert(from != NULL); /* assert(from->stor_begin != NULL); */ /* TODO */ to->stor_begin = igraph_Calloc(igraph_vector_ptr_size(from), void*); if (to->stor_begin == 0) { IGRAPH_ERROR("cannot copy ptr vector", IGRAPH_ENOMEM); } to->stor_end = to->stor_begin + igraph_vector_ptr_size(from); to->end = to->stor_end; to->item_destructor = from->item_destructor; memcpy(to->stor_begin, from->stor_begin, (size_t) igraph_vector_ptr_size(from)*sizeof(void*)); return 0; } /** * \ingroup vectorptr * \brief Remove an element from a pointer vector. */ void igraph_vector_ptr_remove(igraph_vector_ptr_t *v, long int pos) { assert(v != NULL); assert(v->stor_begin != NULL); if (pos + 1 < igraph_vector_ptr_size(v)) { /* TOOD: why is this needed */ memmove(v->stor_begin + pos, v->stor_begin + pos + 1, sizeof(void*) * (size_t) (igraph_vector_ptr_size(v) - pos - 1)); } v->end--; } /** * \ingroup vectorptr * \brief Sort the pointer vector based on an external comparison function * * Sometimes it is necessary to sort the pointers in the vector based on * the property of the element being referenced by the pointer. This * function allows us to sort the vector based on an arbitrary external * comparison function which accepts two \c void* pointers \c p1 and \c p2 * and returns an integer less than, equal to or greater than zero if the * first argument is considered to be respectively less than, equal to, or * greater than the second. \c p1 and \c p2 will point to the pointer in the * vector, so they have to be double-dereferenced if one wants to get access * to the underlying object the address of which is stored in \c v . */ void igraph_vector_ptr_sort(igraph_vector_ptr_t *v, int (*compar)(const void*, const void*)) { qsort(v->stor_begin, (size_t) igraph_vector_ptr_size(v), sizeof(void*), compar); } int igraph_vector_ptr_index_int(igraph_vector_ptr_t *v, const igraph_vector_int_t *idx) { void **tmp; int i, n = igraph_vector_int_size(idx); tmp = igraph_Calloc(n, void*); if (!tmp) { IGRAPH_ERROR("Cannot index pointer vector", IGRAPH_ENOMEM); } for (i = 0; i < n; i++) { tmp[i] = VECTOR(*v)[ VECTOR(*idx)[i] ]; } igraph_Free(v->stor_begin); v->stor_begin = tmp; v->stor_end = v->end = tmp + n; return 0; } int igraph_vector_ptr_append (igraph_vector_ptr_t *to, const igraph_vector_ptr_t *from) { long int origsize = igraph_vector_ptr_size(to); long int othersize = igraph_vector_ptr_size(from); long int i; IGRAPH_CHECK(igraph_vector_ptr_resize(to, origsize + othersize)); for (i = 0; i < othersize; i++, origsize++) { to->stor_begin[origsize] = from->stor_begin[i]; } return 0; } /** * \ingroup vectorptr * \function igraph_vector_ptr_set_item_destructor * \brief Sets the item destructor for this pointer vector. * * The item destructor is a function which will be called on every non-null * pointer stored in this vector when \ref igraph_vector_ptr_destroy(), * igraph_vector_ptr_destroy_all() or \ref igraph_vector_ptr_free_all() * is called. * * \return The old item destructor. * * Time complexity: O(1). */ igraph_finally_func_t* igraph_vector_ptr_set_item_destructor( igraph_vector_ptr_t *v, igraph_finally_func_t *func) { igraph_finally_func_t* result = v->item_destructor; v->item_destructor = func; return result; } /** * \ingroup vectorptr * \function igraph_vector_ptr_get_item_destructor * \brief Gets the current item destructor for this pointer vector. * * The item destructor is a function which will be called on every non-null * pointer stored in this vector when \ref igraph_vector_ptr_destroy(), * igraph_vector_ptr_destroy_all() or \ref igraph_vector_ptr_free_all() * is called. * * \return The current item destructor. * * Time complexity: O(1). */ igraph_finally_func_t* igraph_vector_ptr_get_item_destructor(const igraph_vector_ptr_t *v) { assert(v != 0); return v->item_destructor; } python-igraph-0.8.0/vendor/source/igraph/src/foreign-lgl-header.h0000644000076500000240000000216413614300625025205 0ustar tamasstaff00000000000000/* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard street, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_vector.h" #include "igraph_types_internal.h" typedef struct { void *scanner; int eof; char errmsg[300]; int has_weights; igraph_vector_t *vector; igraph_vector_t *weights; igraph_trie_t *trie; int actvertex; } igraph_i_lgl_parsedata_t; python-igraph-0.8.0/vendor/source/igraph/src/foreign-pajek-lexer.l0000644000076500000240000001522613524616145025426 0ustar tamasstaff00000000000000/* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ %{ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "config.h" #include #include "foreign-pajek-header.h" #include "foreign-pajek-parser.h" #define YY_EXTRA_TYPE igraph_i_pajek_parsedata_t* #define YY_USER_ACTION yylloc->first_line = yylineno; /* We assume that 'file' is 'stderr' here. */ #ifdef USING_R #define fprintf(file, msg, ...) (1) #endif #ifdef stdout # undef stdout #endif #define stdout 0 #define exit(code) igraph_error("Fatal error in DL parser", __FILE__, \ __LINE__, IGRAPH_PARSEERROR); %} %option noyywrap %option prefix="igraph_pajek_yy" %option outfile="lex.yy.c" %option nounput %option noinput %option nodefault %option reentrant %option bison-bridge %option bison-locations digit [0-9] word [^ \t\r\n] %% [ \t]* { } %[^\n]*\n[\r]* { } %[^\n]*\r[\n]* { } \*[Nn][eE][Tt] { return NETWORKLINE; } \*[Nn][Ee][Tt][Ww][Oo][Rr][Kk] { return NETWORKLINE; } \*[Vv][Ee][Rr][Tt][Ii][Cc][Ee][Ss] { return VERTICESLINE; } \*[Aa][Rr][Cc][Ss] { return ARCSLINE; } \*[Ee][Dd][Gg][Ee][Ss] { return EDGESLINE; } \*[Aa][Rr][Cc][Ss][Ll][Ii][Ss][Tt] { return ARCSLISTLINE; } \*[Ee][Dd][Gg][Ee][Ss][Ll][Ii][Ss][Tt] { return EDGESLISTLINE; } \*[Mm][Aa][Tt][Rr][Ii][Xx] { return MATRIXLINE; } \n\r|\r\n|\n|\r { yyextra->mode=0; return NEWLINE; } \"[^\"]*\" { return QSTR; } \([^\)]*\) { return PSTR; } \-?{digit}+(\.{digit}+)?([eE](\+|\-)?{digit}+)? { return NUM; } [Xx]_[Ff][Aa][Cc][Tt]/[ \t\n\r] { if (yyextra->mode==1) { return VP_X_FACT; } else { return ALNUM; } } [Yy]_[Ff][Aa][Cc][Tt]/[ \t\n\r] { if (yyextra->mode==1) { return VP_Y_FACT; } else { return ALNUM; } } [Ii][Cc]/[ \t\n\r] { if (yyextra->mode==1) { return VP_IC; } else { return ALNUM; } } [Bb][Cc]/[ \t\n\r] { if (yyextra->mode==1) { return VP_BC; } else { return ALNUM; } } [Bb][Ww]/[ \t\n\r] { if (yyextra->mode==1) { return VP_BW; } else { return ALNUM; } } [Pp][Hh][Ii]/[ \t\n\r] { if (yyextra->mode==1) { return VP_PHI; } else { return ALNUM; } } [Rr]/[ \t\n\r] { if (yyextra->mode==1) { return VP_R; } else { return ALNUM; } } [Qq]/[ \t\n\r] { if (yyextra->mode==1) { return VP_Q; } else { return ALNUM; } } [Ff][Oo][Nn][Tt]/[ \t\n\r] { if (yyextra->mode==1) { return VP_FONT; } else { return ALNUM; } } [Uu][Rr][Ll]/[ \t\n\r] { if (yyextra->mode==1) { return VP_URL; } else { return ALNUM; } } [Cc]/[ \t\n\r] { if (yyextra->mode==2) { return EP_C; } else { return ALNUM; } } [Pp]/[ \t\n\r] { if (yyextra->mode==2) { return EP_P; } else { return ALNUM; } } [Ss]/[ \t\n\r] { if (yyextra->mode==2) { return EP_S; } else { return ALNUM; } } [Aa]/[ \t\n\r] { if (yyextra->mode==2) { return EP_A; } else { return ALNUM; } } [Ww]/[ \t\n\r] { if (yyextra->mode==2) { return EP_W; } else { return ALNUM; } } [Hh]1/[ \t\n\r] { if (yyextra->mode==2) { return EP_H1; } else { return ALNUM; } } [Hh]2/[ \t\n\r] { if (yyextra->mode==2) { return EP_H2; } else { return ALNUM; } } [Aa]1/[ \t\n\r] { if (yyextra->mode==2) { return EP_A1; } else { return ALNUM; } } [Aa]2/[ \t\n\r] { if (yyextra->mode==2) { return EP_A2; } else { return ALNUM; } } [Kk]1/[ \t\n\r] { if (yyextra->mode==2) { return EP_K1; } else { return ALNUM; } } [Kk]2/[ \t\n\r] { if (yyextra->mode==2) { return EP_K2; } else { return ALNUM; } } [Aa][Pp]/[ \t\n\r] { if (yyextra->mode==2) { return EP_AP; } else { return ALNUM; } } [Ll]/[ \t\n\r] { if (yyextra->mode==2) { return EP_L; } else { return ALNUM; } } [Ll][Pp]/[ \t\n\r] { if (yyextra->mode==2) { return EP_LP; } else { return ALNUM; } } [Ll][Pp][Hh][Ii]/[ \t\n\r] { if (yyextra->mode==1) { return VP_LPHI; } else if (yyextra->mode==2) { return EP_LPHI; } else { return ALNUM; } } [Ll][Cc]/[ \t\n\r] { if (yyextra->mode==1) { return VP_LC; } else if (yyextra->mode==2) { return EP_LC; } else { return ALNUM; } } [Ll][Rr]/[ \t\n\r] { if (yyextra->mode==1) { return VP_LR; } else if (yyextra->mode==2) { return EP_LR; } else { return ALNUM; } } [Ll][Aa]/[ \t\n\r] { if (yyextra->mode==1) { return VP_LA; } else if (yyextra->mode==2) { return EP_LA; } else { return ALNUM; } } [Ss][Ii][Zz][Ee]/[ \t\n\r] { if (yyextra->mode==1) { return VP_SIZE; } else if (yyextra->mode==2) { return EP_SIZE; } else { return ALNUM; } } [Ff][Oo][Ss]/[ \t\n\r] { if (yyextra->mode==1) { return VP_FOS; } else if (yyextra->mode==2) { return EP_FOS; } else { return ALNUM; } } {word}+ { return ALNUM; } <> { if (yyextra->eof) { yyterminate(); } else { yyextra->eof=1; return NEWLINE; } } . { return ERROR; } %% python-igraph-0.8.0/vendor/source/igraph/src/zeroin.c0000644000076500000240000001740513614300625023057 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ /* from GNU R's zeroin.c, minor modifications by Gabor Csardi */ /* from NETLIB c/brent.shar with max.iter, add'l info and convergence details hacked in by Peter Dalgaard */ /************************************************************************* * C math library * function ZEROIN - obtain a function zero within the given range * * Input * double zeroin(ax,bx,f,info,Tol,Maxit) * double ax; Root will be seeked for within * double bx; a range [ax,bx] * double (*f)(double x, void *info); Name of the function whose zero * will be seeked for * void *info; Add'l info passed to f * double *Tol; Acceptable tolerance for the root * value. * May be specified as 0.0 to cause * the program to find the root as * accurate as possible * * int *Maxit; Max. iterations * * * Output * Zeroin returns an estimate for the root with accuracy * 4*EPSILON*abs(x) + tol * *Tol returns estimated precision * *Maxit returns actual # of iterations, or -1 if maxit was * reached without convergence. * * Algorithm * G.Forsythe, M.Malcolm, C.Moler, Computer methods for mathematical * computations. M., Mir, 1980, p.180 of the Russian edition * * The function makes use of the bisection procedure combined with * the linear or quadric inverse interpolation. * At every step program operates on three abscissae - a, b, and c. * b - the last and the best approximation to the root * a - the last but one approximation * c - the last but one or even earlier approximation than a that * 1) |f(b)| <= |f(c)| * 2) f(b) and f(c) have opposite signs, i.e. b and c confine * the root * At every step Zeroin selects one of the two new approximations, the * former being obtained by the bisection procedure and the latter * resulting in the interpolation (if a,b, and c are all different * the quadric interpolation is utilized, otherwise the linear one). * If the latter (i.e. obtained by the interpolation) point is * reasonable (i.e. lies within the current interval [b,c] not being * too close to the boundaries) it is accepted. The bisection result * is used in the other case. Therefore, the range of uncertainty is * ensured to be reduced at least by the factor 1.6 * ************************************************************************ */ #include "igraph_types.h" #include "igraph_interrupt_internal.h" #include #include #define EPSILON DBL_EPSILON int igraph_zeroin( /* An estimate of the root */ igraph_real_t *ax, /* Left border | of the range */ igraph_real_t *bx, /* Right border| the root is seeked*/ igraph_real_t (*f)(igraph_real_t x, void *info), /* Function under investigation */ void *info, /* Add'l info passed on to f */ igraph_real_t *Tol, /* Acceptable tolerance */ int *Maxit, /* Max # of iterations */ igraph_real_t *res) { /* Result is stored here */ igraph_real_t a, b, c, /* Abscissae, descr. see above */ fa, fb, fc; /* f(a), f(b), f(c) */ igraph_real_t tol; int maxit; a = *ax; b = *bx; fa = (*f)(a, info); fb = (*f)(b, info); c = a; fc = fa; maxit = *Maxit + 1; tol = * Tol; /* First test if we have found a root at an endpoint */ if (fa == 0.0) { *Tol = 0.0; *Maxit = 0; *res = a; return 0; } if (fb == 0.0) { *Tol = 0.0; *Maxit = 0; *res = b; return 0; } while (maxit--) { /* Main iteration loop */ igraph_real_t prev_step = b - a; /* Distance from the last but one to the last approximation */ igraph_real_t tol_act; /* Actual tolerance */ igraph_real_t p; /* Interpolation step is calcu- */ igraph_real_t q; /* lated in the form p/q; divi- * sion operations is delayed * until the last moment */ igraph_real_t new_step; /* Step at this iteration */ IGRAPH_ALLOW_INTERRUPTION(); if ( fabs(fc) < fabs(fb) ) { /* Swap data for b to be the */ a = b; b = c; c = a; /* best approximation */ fa = fb; fb = fc; fc = fa; } tol_act = 2 * EPSILON * fabs(b) + tol / 2; new_step = (c - b) / 2; if ( fabs(new_step) <= tol_act || fb == (igraph_real_t)0 ) { *Maxit -= maxit; *Tol = fabs(c - b); *res = b; return 0; /* Acceptable approx. is found */ } /* Decide if the interpolation can be tried */ if ( fabs(prev_step) >= tol_act /* If prev_step was large enough*/ && fabs(fa) > fabs(fb) ) { /* and was in true direction, * Interpolation may be tried */ register igraph_real_t t1, cb, t2; cb = c - b; if ( a == c ) { /* If we have only two distinct */ /* points linear interpolation */ t1 = fb / fa; /* can only be applied */ p = cb * t1; q = 1.0 - t1; } else { /* Quadric inverse interpolation*/ q = fa / fc; t1 = fb / fc; t2 = fb / fa; p = t2 * ( cb * q * (q - t1) - (b - a) * (t1 - 1.0) ); q = (q - 1.0) * (t1 - 1.0) * (t2 - 1.0); } if ( p > (igraph_real_t)0 ) { /* p was calculated with the */ q = -q; /* opposite sign; make p positive */ } else { /* and assign possible minus to */ p = -p; /* q */ } if ( p < (0.75 * cb * q - fabs(tol_act * q) / 2) /* If b+p/q falls in [b,c]*/ && p < fabs(prev_step * q / 2) ) { /* and isn't too large */ new_step = p / q; } /* it is accepted * If p/q is too large then the * bisection procedure can * reduce [b,c] range to more * extent */ } if ( fabs(new_step) < tol_act) { /* Adjust the step to be not less*/ if ( new_step > (igraph_real_t)0 ) { /* than tolerance */ new_step = tol_act; } else { new_step = -tol_act; } } a = b; fa = fb; /* Save the previous approx. */ b += new_step; fb = (*f)(b, info); /* Do step to a new approxim. */ if ( (fb > 0 && fc > 0) || (fb < 0 && fc < 0) ) { /* Adjust c for it to have a sign opposite to that of b */ c = a; fc = fa; } } /* failed! */ *Tol = fabs(c - b); *Maxit = -1; *res = b; return IGRAPH_DIVERGED; } python-igraph-0.8.0/vendor/source/igraph/src/st-cuts.c0000644000076500000240000016036613614300625023160 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_flow.h" #include "igraph_flow_internal.h" #include "igraph_error.h" #include "igraph_memory.h" #include "igraph_constants.h" #include "igraph_interface.h" #include "igraph_adjlist.h" #include "igraph_conversion.h" #include "igraph_constructors.h" #include "igraph_structural.h" #include "igraph_components.h" #include "igraph_types_internal.h" #include "config.h" #include "igraph_math.h" #include "igraph_dqueue.h" #include "igraph_visitor.h" #include "igraph_marked_queue.h" #include "igraph_stack.h" #include "igraph_estack.h" /* * \function igraph_even_tarjan_reduction * Even-Tarjan reduction of a graph * * \example examples/simple/even_tarjan.c */ int igraph_even_tarjan_reduction(const igraph_t *graph, igraph_t *graphbar, igraph_vector_t *capacity) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); long int new_no_of_nodes = no_of_nodes * 2; long int new_no_of_edges = no_of_nodes + no_of_edges * 2; igraph_vector_t edges; long int edgeptr = 0, capptr = 0; long int i; IGRAPH_VECTOR_INIT_FINALLY(&edges, new_no_of_edges * 2); if (capacity) { IGRAPH_CHECK(igraph_vector_resize(capacity, new_no_of_edges)); } /* Every vertex 'i' is replaced by two vertices, i' and i'' */ /* id[i'] := id[i] ; id[i''] := id[i] + no_of_nodes */ /* One edge for each original vertex, for i, we add (i',i'') */ for (i = 0; i < no_of_nodes; i++) { VECTOR(edges)[edgeptr++] = i; VECTOR(edges)[edgeptr++] = i + no_of_nodes; if (capacity) { VECTOR(*capacity)[capptr++] = 1.0; } } /* Two news edges for each original edge (from,to) becomes (from'',to'), (to'',from') */ for (i = 0; i < no_of_edges; i++) { long int from = IGRAPH_FROM(graph, i); long int to = IGRAPH_TO(graph, i); VECTOR(edges)[edgeptr++] = from + no_of_nodes; VECTOR(edges)[edgeptr++] = to; VECTOR(edges)[edgeptr++] = to + no_of_nodes; VECTOR(edges)[edgeptr++] = from; if (capacity) { VECTOR(*capacity)[capptr++] = no_of_nodes; /* TODO: should be Inf */ VECTOR(*capacity)[capptr++] = no_of_nodes; /* TODO: should be Inf */ } } IGRAPH_CHECK(igraph_create(graphbar, &edges, (igraph_integer_t) new_no_of_nodes, IGRAPH_DIRECTED)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_i_residual_graph(const igraph_t *graph, const igraph_vector_t *capacity, igraph_t *residual, igraph_vector_t *residual_capacity, const igraph_vector_t *flow, igraph_vector_t *tmp) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); long int i, no_new_edges = 0; long int edgeptr = 0, capptr = 0; for (i = 0; i < no_of_edges; i++) { if (VECTOR(*flow)[i] < VECTOR(*capacity)[i]) { no_new_edges++; } } IGRAPH_CHECK(igraph_vector_resize(tmp, no_new_edges * 2)); if (residual_capacity) { IGRAPH_CHECK(igraph_vector_resize(residual_capacity, no_new_edges)); } for (i = 0; i < no_of_edges; i++) { if (VECTOR(*capacity)[i] - VECTOR(*flow)[i] > 0) { long int from = IGRAPH_FROM(graph, i); long int to = IGRAPH_TO(graph, i); igraph_real_t c = VECTOR(*capacity)[i]; VECTOR(*tmp)[edgeptr++] = from; VECTOR(*tmp)[edgeptr++] = to; if (residual_capacity) { VECTOR(*residual_capacity)[capptr++] = c; } } } IGRAPH_CHECK(igraph_create(residual, tmp, (igraph_integer_t) no_of_nodes, IGRAPH_DIRECTED)); return 0; } int igraph_residual_graph(const igraph_t *graph, const igraph_vector_t *capacity, igraph_t *residual, igraph_vector_t *residual_capacity, const igraph_vector_t *flow) { igraph_vector_t tmp; long int no_of_edges = igraph_ecount(graph); if (igraph_vector_size(capacity) != no_of_edges) { IGRAPH_ERROR("Invalid `capacity' vector size", IGRAPH_EINVAL); } if (igraph_vector_size(flow) != no_of_edges) { IGRAPH_ERROR("Invalid `flow' vector size", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(&tmp, 0); IGRAPH_CHECK(igraph_i_residual_graph(graph, capacity, residual, residual_capacity, flow, &tmp)); igraph_vector_destroy(&tmp); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_i_reverse_residual_graph(const igraph_t *graph, const igraph_vector_t *capacity, igraph_t *residual, const igraph_vector_t *flow, igraph_vector_t *tmp) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); long int i, no_new_edges = 0; long int edgeptr = 0; for (i = 0; i < no_of_edges; i++) { igraph_real_t cap = capacity ? VECTOR(*capacity)[i] : 1.0; if (VECTOR(*flow)[i] > 0) { no_new_edges++; } if (VECTOR(*flow)[i] < cap) { no_new_edges++; } } IGRAPH_CHECK(igraph_vector_resize(tmp, no_new_edges * 2)); for (i = 0; i < no_of_edges; i++) { long int from = IGRAPH_FROM(graph, i); long int to = IGRAPH_TO(graph, i); igraph_real_t cap = capacity ? VECTOR(*capacity)[i] : 1.0; if (VECTOR(*flow)[i] > 0) { VECTOR(*tmp)[edgeptr++] = from; VECTOR(*tmp)[edgeptr++] = to; } if (VECTOR(*flow)[i] < cap) { VECTOR(*tmp)[edgeptr++] = to; VECTOR(*tmp)[edgeptr++] = from; } } IGRAPH_CHECK(igraph_create(residual, tmp, (igraph_integer_t) no_of_nodes, IGRAPH_DIRECTED)); return 0; } int igraph_reverse_residual_graph(const igraph_t *graph, const igraph_vector_t *capacity, igraph_t *residual, const igraph_vector_t *flow) { igraph_vector_t tmp; long int no_of_edges = igraph_ecount(graph); if (capacity && igraph_vector_size(capacity) != no_of_edges) { IGRAPH_ERROR("Invalid `capacity' vector size", IGRAPH_EINVAL); } if (igraph_vector_size(flow) != no_of_edges) { IGRAPH_ERROR("Invalid `flow' vector size", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(&tmp, 0); IGRAPH_CHECK(igraph_i_reverse_residual_graph(graph, capacity, residual, flow, &tmp)); igraph_vector_destroy(&tmp); IGRAPH_FINALLY_CLEAN(1); return 0; } typedef struct igraph_i_dbucket_t { igraph_vector_long_t head; igraph_vector_long_t next; } igraph_i_dbucket_t; int igraph_i_dbucket_init(igraph_i_dbucket_t *buck, long int size) { IGRAPH_CHECK(igraph_vector_long_init(&buck->head, size)); IGRAPH_FINALLY(igraph_vector_long_destroy, &buck->head); IGRAPH_CHECK(igraph_vector_long_init(&buck->next, size)); IGRAPH_FINALLY_CLEAN(1); return 0; } void igraph_i_dbucket_destroy(igraph_i_dbucket_t *buck) { igraph_vector_long_destroy(&buck->head); igraph_vector_long_destroy(&buck->next); } int igraph_i_dbucket_insert(igraph_i_dbucket_t *buck, long int bid, long int elem) { /* Note: we can do this, since elem is not in any buckets */ VECTOR(buck->next)[elem] = VECTOR(buck->head)[bid]; VECTOR(buck->head)[bid] = elem + 1; return 0; } long int igraph_i_dbucket_empty(const igraph_i_dbucket_t *buck, long int bid) { return VECTOR(buck->head)[bid] == 0; } long int igraph_i_dbucket_delete(igraph_i_dbucket_t *buck, long int bid) { long int elem = VECTOR(buck->head)[bid] - 1; VECTOR(buck->head)[bid] = VECTOR(buck->next)[elem]; return elem; } int igraph_i_dominator_LINK(long int v, long int w, igraph_vector_long_t *ancestor) { VECTOR(*ancestor)[w] = v + 1; return 0; } /* TODO: don't always reallocate path */ int igraph_i_dominator_COMPRESS(long int v, igraph_vector_long_t *ancestor, igraph_vector_long_t *label, igraph_vector_long_t *semi) { igraph_stack_long_t path; long int w = v; long int top, pretop; IGRAPH_CHECK(igraph_stack_long_init(&path, 10)); IGRAPH_FINALLY(igraph_stack_long_destroy, &path); while (VECTOR(*ancestor)[w] != 0) { IGRAPH_CHECK(igraph_stack_long_push(&path, w)); w = VECTOR(*ancestor)[w] - 1; } top = igraph_stack_long_pop(&path); while (!igraph_stack_long_empty(&path)) { pretop = igraph_stack_long_pop(&path); if (VECTOR(*semi)[VECTOR(*label)[top]] < VECTOR(*semi)[VECTOR(*label)[pretop]]) { VECTOR(*label)[pretop] = VECTOR(*label)[top]; } VECTOR(*ancestor)[pretop] = VECTOR(*ancestor)[top]; top = pretop; } igraph_stack_long_destroy(&path); IGRAPH_FINALLY_CLEAN(1); return 0; } long int igraph_i_dominator_EVAL(long int v, igraph_vector_long_t *ancestor, igraph_vector_long_t *label, igraph_vector_long_t *semi) { if (VECTOR(*ancestor)[v] == 0) { return v; } else { igraph_i_dominator_COMPRESS(v, ancestor, label, semi); return VECTOR(*label)[v]; } } /* TODO: implement the faster version. */ /** * \function igraph_dominator_tree * Calculates the dominator tree of a flowgraph * * A flowgraph is a directed graph with a distinguished start (or * root) vertex r, such that for any vertex v, there is a path from r * to v. A vertex v dominates another vertex w (not equal to v), if * every path from r to w contains v. Vertex v is the immediate * dominator or w, v=idom(w), if v dominates w and every other * dominator of w dominates v. The edges {(idom(w), w)| w is not r} * form a directed tree, rooted at r, called the dominator tree of the * graph. Vertex v dominates vertex w if and only if v is an ancestor * of w in the dominator tree. * * This function implements the Lengauer-Tarjan algorithm * to construct the dominator tree of a directed graph. For details * please see Thomas Lengauer, Robert Endre Tarjan: A fast algorithm * for finding dominators in a flowgraph, ACM Transactions on * Programming Languages and Systems (TOPLAS) I/1, 121--141, 1979. * * \param graph A directed graph. If it is not a flowgraph, and it * contains some vertices not reachable from the root vertex, * then these vertices will be collected in the \c leftout * vector. * \param root The id of the root (or source) vertex, this will be the * root of the tree. * \param dom Pointer to an initialized vector or a null pointer. If * not a null pointer, then the immediate dominator of each * vertex will be stored here. For vertices that are not * reachable from the root, \c IGRAPH_NAN is stored here. For * the root vertex itself, -1 is added. * \param domtree Pointer to an uninitialized igraph_t, or NULL. If * not a null pointer, then the dominator tree is returned * here. The graph contains the vertices that are unreachable * from the root (if any), these will be isolates. * \param leftout Pointer to an initialized vector object, or NULL. If * not NULL, then the ids of the vertices that are unreachable * from the root vertex (and thus not part of the dominator * tree) are stored here. * \param mode Constant, must be \c IGRAPH_IN or \c IGRAPH_OUT. If it * is \c IGRAPH_IN, then all directions are considered as * opposite to the original one in the input graph. * \return Error code. * * Time complexity: very close to O(|E|+|V|), linear in the number of * edges and vertices. More precisely, it is O(|V|+|E|alpha(|E|,|V|)), * where alpha(|E|,|V|) is a functional inverse of Ackermann's * function. * * \example examples/simple/dominator_tree.c */ int igraph_dominator_tree(const igraph_t *graph, igraph_integer_t root, igraph_vector_t *dom, igraph_t *domtree, igraph_vector_t *leftout, igraph_neimode_t mode) { long int no_of_nodes = igraph_vcount(graph); igraph_adjlist_t succ, pred; igraph_vector_t parent; igraph_vector_long_t semi; /* +1 always */ igraph_vector_t vertex; /* +1 always */ igraph_i_dbucket_t bucket; igraph_vector_long_t ancestor; igraph_vector_long_t label; igraph_neimode_t invmode = mode == IGRAPH_IN ? IGRAPH_OUT : IGRAPH_IN; long int i; igraph_vector_t vdom, *mydom = dom; long int component_size = 0; if (root < 0 || root >= no_of_nodes) { IGRAPH_ERROR("Invalid root vertex id for dominator tree", IGRAPH_EINVAL); } if (!igraph_is_directed(graph)) { IGRAPH_ERROR("Dominator tree of an undirected graph requested", IGRAPH_EINVAL); } if (mode == IGRAPH_ALL) { IGRAPH_ERROR("Invalid neighbor mode for dominator tree", IGRAPH_EINVAL); } if (dom) { IGRAPH_CHECK(igraph_vector_resize(dom, no_of_nodes)); } else { mydom = &vdom; IGRAPH_VECTOR_INIT_FINALLY(mydom, no_of_nodes); } igraph_vector_fill(mydom, IGRAPH_NAN); IGRAPH_CHECK(igraph_vector_init(&parent, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_destroy, &parent); IGRAPH_CHECK(igraph_vector_long_init(&semi, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_long_destroy, &semi); IGRAPH_CHECK(igraph_vector_init(&vertex, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_destroy, &vertex); IGRAPH_CHECK(igraph_vector_long_init(&ancestor, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_long_destroy, &ancestor); IGRAPH_CHECK(igraph_vector_long_init_seq(&label, 0, no_of_nodes - 1)); IGRAPH_FINALLY(igraph_vector_long_destroy, &label); IGRAPH_CHECK(igraph_adjlist_init(graph, &succ, mode)); IGRAPH_FINALLY(igraph_adjlist_destroy, &succ); IGRAPH_CHECK(igraph_adjlist_init(graph, &pred, invmode)); IGRAPH_FINALLY(igraph_adjlist_destroy, &pred); IGRAPH_CHECK(igraph_i_dbucket_init(&bucket, no_of_nodes)); IGRAPH_FINALLY(igraph_i_dbucket_destroy, &bucket); /* DFS first, to set semi, vertex and parent, step 1 */ IGRAPH_CHECK(igraph_dfs(graph, root, mode, /*unreachable=*/ 0, /*order=*/ &vertex, /*order_out=*/ 0, /*father=*/ &parent, /*dist=*/ 0, /*in_callback=*/ 0, /*out_callback=*/ 0, /*extra=*/ 0)); for (i = 0; i < no_of_nodes; i++) { if (IGRAPH_FINITE(VECTOR(vertex)[i])) { long int t = (long int) VECTOR(vertex)[i]; VECTOR(semi)[t] = component_size + 1; VECTOR(vertex)[component_size] = t + 1; component_size++; } } if (leftout) { long int n = no_of_nodes - component_size; long int p = 0, j; IGRAPH_CHECK(igraph_vector_resize(leftout, n)); for (j = 0; j < no_of_nodes && p < n; j++) { if (!IGRAPH_FINITE(VECTOR(parent)[j])) { VECTOR(*leftout)[p++] = j; } } } /* We need to go over 'pred' because it should contain only the edges towards the target vertex. */ for (i = 0; i < no_of_nodes; i++) { igraph_vector_int_t *v = igraph_adjlist_get(&pred, i); long int j, n = igraph_vector_int_size(v); for (j = 0; j < n; ) { long int v2 = (long int) VECTOR(*v)[j]; if (IGRAPH_FINITE(VECTOR(parent)[v2])) { j++; } else { VECTOR(*v)[j] = VECTOR(*v)[n - 1]; igraph_vector_int_pop_back(v); n--; } } } /* Now comes the main algorithm, steps 2 & 3 */ for (i = component_size - 1; i > 0; i--) { long int w = (long int) VECTOR(vertex)[i] - 1; igraph_vector_int_t *predw = igraph_adjlist_get(&pred, w); long int j, n = igraph_vector_int_size(predw); for (j = 0; j < n; j++) { long int v = (long int) VECTOR(*predw)[j]; long int u = igraph_i_dominator_EVAL(v, &ancestor, &label, &semi); if (VECTOR(semi)[u] < VECTOR(semi)[w]) { VECTOR(semi)[w] = VECTOR(semi)[u]; } } igraph_i_dbucket_insert(&bucket, (long int) VECTOR(vertex)[ VECTOR(semi)[w] - 1 ] - 1, w); igraph_i_dominator_LINK((long int) VECTOR(parent)[w], w, &ancestor); while (!igraph_i_dbucket_empty(&bucket, (long int) VECTOR(parent)[w])) { long int v = igraph_i_dbucket_delete(&bucket, (long int) VECTOR(parent)[w]); long int u = igraph_i_dominator_EVAL(v, &ancestor, &label, &semi); VECTOR(*mydom)[v] = VECTOR(semi)[u] < VECTOR(semi)[v] ? u : VECTOR(parent)[w]; } } /* Finally, step 4 */ for (i = 1; i < component_size; i++) { long int w = (long int) VECTOR(vertex)[i] - 1; if (VECTOR(*mydom)[w] != VECTOR(vertex)[VECTOR(semi)[w] - 1] - 1) { VECTOR(*mydom)[w] = VECTOR(*mydom)[(long int)VECTOR(*mydom)[w]]; } } VECTOR(*mydom)[(long int)root] = -1; igraph_i_dbucket_destroy(&bucket); igraph_adjlist_destroy(&pred); igraph_adjlist_destroy(&succ); igraph_vector_long_destroy(&label); igraph_vector_long_destroy(&ancestor); igraph_vector_destroy(&vertex); igraph_vector_long_destroy(&semi); igraph_vector_destroy(&parent); IGRAPH_FINALLY_CLEAN(8); if (domtree) { igraph_vector_t edges; long int ptr = 0; IGRAPH_VECTOR_INIT_FINALLY(&edges, component_size * 2 - 2); for (i = 0; i < no_of_nodes; i++) { if (i != root && IGRAPH_FINITE(VECTOR(*mydom)[i])) { if (mode == IGRAPH_OUT) { VECTOR(edges)[ptr++] = VECTOR(*mydom)[i]; VECTOR(edges)[ptr++] = i; } else { VECTOR(edges)[ptr++] = i; VECTOR(edges)[ptr++] = VECTOR(*mydom)[i]; } } } IGRAPH_CHECK(igraph_create(domtree, &edges, (igraph_integer_t) no_of_nodes, IGRAPH_DIRECTED)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); IGRAPH_I_ATTRIBUTE_DESTROY(domtree); IGRAPH_I_ATTRIBUTE_COPY(domtree, graph, /*graph=*/ 1, /*vertex=*/ 1, /*edge=*/ 0); } if (!dom) { igraph_vector_destroy(&vdom); IGRAPH_FINALLY_CLEAN(1); } return 0; } typedef struct igraph_i_all_st_cuts_minimal_dfs_data_t { igraph_stack_t *stack; igraph_vector_bool_t *nomark; const igraph_vector_bool_t *GammaX; long int root; const igraph_vector_t *map; } igraph_i_all_st_cuts_minimal_dfs_data_t; igraph_bool_t igraph_i_all_st_cuts_minimal_dfs_incb(const igraph_t *graph, igraph_integer_t vid, igraph_integer_t dist, void *extra) { igraph_i_all_st_cuts_minimal_dfs_data_t *data = extra; igraph_stack_t *stack = data->stack; igraph_vector_bool_t *nomark = data->nomark; const igraph_vector_bool_t *GammaX = data->GammaX; const igraph_vector_t *map = data->map; long int realvid = (long int) VECTOR(*map)[(long int)vid]; IGRAPH_UNUSED(graph); IGRAPH_UNUSED(dist); if (VECTOR(*GammaX)[(long int)realvid]) { if (!igraph_stack_empty(stack)) { long int top = (long int) igraph_stack_top(stack); VECTOR(*nomark)[top] = 1; /* we just found a smaller one */ } igraph_stack_push(stack, realvid); /* TODO: error check */ } return 0; } igraph_bool_t igraph_i_all_st_cuts_minimal_dfs_otcb(const igraph_t *graph, igraph_integer_t vid, igraph_integer_t dist, void *extra) { igraph_i_all_st_cuts_minimal_dfs_data_t *data = extra; igraph_stack_t *stack = data->stack; const igraph_vector_t *map = data->map; long int realvid = (long int) VECTOR(*map)[(long int)vid]; IGRAPH_UNUSED(graph); IGRAPH_UNUSED(dist); if (!igraph_stack_empty(stack) && igraph_stack_top(stack) == realvid) { igraph_stack_pop(stack); } return 0; } int igraph_i_all_st_cuts_minimal(const igraph_t *graph, const igraph_t *domtree, long int root, const igraph_marked_queue_t *X, const igraph_vector_bool_t *GammaX, const igraph_vector_t *invmap, igraph_vector_t *minimal) { long int no_of_nodes = igraph_vcount(graph); igraph_stack_t stack; igraph_vector_bool_t nomark; igraph_i_all_st_cuts_minimal_dfs_data_t data; long int i; IGRAPH_UNUSED(X); IGRAPH_CHECK(igraph_stack_init(&stack, 10)); IGRAPH_FINALLY(igraph_stack_destroy, &stack); IGRAPH_CHECK(igraph_vector_bool_init(&nomark, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_bool_destroy, &nomark); data.stack = &stack; data.nomark = &nomark; data.GammaX = GammaX; data.root = root; data.map = invmap; /* We mark all GammaX elements as minimal first. TODO: actually, we could just use GammaX to return the minimal elements. */ for (i = 0; i < no_of_nodes; i++) { VECTOR(nomark)[i] = VECTOR(*GammaX)[i] == 0 ? 1 : 0; } /* We do a reverse DFS from root. If, along a path we find a GammaX vertex after (=below) another GammaX vertex, we mark the higher one as non-minimal. */ IGRAPH_CHECK(igraph_dfs(domtree, (igraph_integer_t) root, IGRAPH_IN, /*unreachable=*/ 0, /*order=*/ 0, /*order_out=*/ 0, /*father=*/ 0, /*dist=*/ 0, /*in_callback=*/ igraph_i_all_st_cuts_minimal_dfs_incb, /*out_callback=*/ igraph_i_all_st_cuts_minimal_dfs_otcb, /*extra=*/ &data)); igraph_vector_clear(minimal); for (i = 0; i < no_of_nodes; i++) { if (!VECTOR(nomark)[i]) { IGRAPH_CHECK(igraph_vector_push_back(minimal, i)); } } igraph_vector_bool_destroy(&nomark); igraph_stack_destroy(&stack); IGRAPH_FINALLY_CLEAN(2); return 0; } int igraph_i_all_st_cuts_pivot(const igraph_t *graph, const igraph_marked_queue_t *S, const igraph_estack_t *T, long int source, long int target, long int *v, igraph_vector_t *Isv, void *arg) { long int no_of_nodes = igraph_vcount(graph); igraph_t Sbar; igraph_vector_t Sbar_map, Sbar_invmap; igraph_vector_t keep; igraph_t domtree; igraph_vector_t leftout; long int i, nomin, n; long int root; igraph_vector_t M; igraph_vector_bool_t GammaS; igraph_vector_t Nuv; igraph_vector_t Isv_min; igraph_vector_t GammaS_vec; long int Sbar_size; IGRAPH_UNUSED(arg); /* We need to create the graph induced by Sbar */ IGRAPH_VECTOR_INIT_FINALLY(&Sbar_map, 0); IGRAPH_VECTOR_INIT_FINALLY(&Sbar_invmap, 0); IGRAPH_VECTOR_INIT_FINALLY(&keep, 0); for (i = 0; i < no_of_nodes; i++) { if (!igraph_marked_queue_iselement(S, i)) { IGRAPH_CHECK(igraph_vector_push_back(&keep, i)); } } Sbar_size = igraph_vector_size(&keep); IGRAPH_CHECK(igraph_induced_subgraph_map(graph, &Sbar, igraph_vss_vector(&keep), IGRAPH_SUBGRAPH_AUTO, /* map= */ &Sbar_map, /* invmap= */ &Sbar_invmap)); igraph_vector_destroy(&keep); IGRAPH_FINALLY_CLEAN(1); IGRAPH_FINALLY(igraph_destroy, &Sbar); root = (long int) VECTOR(Sbar_map)[target] - 1; /* -------------------------------------------------------------*/ /* Construct the dominator tree of Sbar */ IGRAPH_VECTOR_INIT_FINALLY(&leftout, 0); IGRAPH_CHECK(igraph_dominator_tree(&Sbar, (igraph_integer_t) root, /*dom=*/ 0, &domtree, &leftout, IGRAPH_IN)); IGRAPH_FINALLY(igraph_destroy, &domtree); /* -------------------------------------------------------------*/ /* Identify the set M of minimal elements of Gamma(S) with respect to the dominator relation. */ /* First we create GammaS */ /* TODO: use the adjacency list, instead of neighbors() */ IGRAPH_CHECK(igraph_vector_bool_init(&GammaS, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_bool_destroy, &GammaS); if (igraph_marked_queue_size(S) == 0) { VECTOR(GammaS)[(long int) VECTOR(Sbar_map)[source] - 1] = 1; } else { for (i = 0; i < no_of_nodes; i++) { if (igraph_marked_queue_iselement(S, i)) { igraph_vector_t neis; long int j; IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) i, IGRAPH_OUT)); n = igraph_vector_size(&neis); for (j = 0; j < n; j++) { long int nei = (long int) VECTOR(neis)[j]; if (!igraph_marked_queue_iselement(S, nei)) { VECTOR(GammaS)[nei] = 1; } } igraph_vector_destroy(&neis); IGRAPH_FINALLY_CLEAN(1); } } } /* Relabel left out vertices (set K in Provan & Shier) to correspond to node labelling of graph instead of SBar. At the same time ensure that GammaS is a proper subset of L, where L are the nodes in the dominator tree. */ n = igraph_vector_size(&leftout); for (i = 0; i < n; i++) { VECTOR(leftout)[i] = VECTOR(Sbar_invmap)[(long int)VECTOR(leftout)[i]]; VECTOR(GammaS)[(long int)VECTOR(leftout)[i]] = 0; } IGRAPH_VECTOR_INIT_FINALLY(&M, 0); if (igraph_ecount(&domtree) > 0) { IGRAPH_CHECK(igraph_i_all_st_cuts_minimal(graph, &domtree, root, S, &GammaS, &Sbar_invmap, &M)); } igraph_vector_clear(Isv); IGRAPH_VECTOR_INIT_FINALLY(&Nuv, 0); IGRAPH_VECTOR_INIT_FINALLY(&Isv_min, 0); IGRAPH_VECTOR_INIT_FINALLY(&GammaS_vec, 0); for (i = 0; i < no_of_nodes; i++) { if (VECTOR(GammaS)[i]) { IGRAPH_CHECK(igraph_vector_push_back(&GammaS_vec, i)); } } nomin = igraph_vector_size(&M); for (i = 0; i < nomin; i++) { /* -------------------------------------------------------------*/ /* For each v in M find the set Nu(v)=dom(Sbar, v)-K Nu(v) contains all vertices that are dominated by v, for every v, this is a subtree of the dominator tree, rooted at v. The different subtrees are disjoint. */ long int min = (long int) VECTOR(Sbar_map)[(long int) VECTOR(M)[i] ] - 1; long int nuvsize, isvlen, j; IGRAPH_CHECK(igraph_dfs(&domtree, (igraph_integer_t) min, IGRAPH_IN, /*unreachable=*/ 0, /*order=*/ &Nuv, /*order_out=*/ 0, /*father=*/ 0, /*dist=*/ 0, /*in_callback=*/ 0, /*out_callback=*/ 0, /*extra=*/ 0)); /* Remove the NAN values from the end of the vector */ for (nuvsize = 0; nuvsize < Sbar_size; nuvsize++) { igraph_real_t t = VECTOR(Nuv)[nuvsize]; if (IGRAPH_FINITE(t)) { VECTOR(Nuv)[nuvsize] = VECTOR(Sbar_invmap)[(long int) t]; } else { break; } } igraph_vector_resize(&Nuv, nuvsize); /* -------------------------------------------------------------*/ /* By a BFS search of determine I(S,v)-K. I(S,v) contains all vertices that are in Nu(v) and that are reachable from Gamma(S) via a path in Nu(v). */ IGRAPH_CHECK(igraph_bfs(graph, /*root=*/ -1, /*roots=*/ &GammaS_vec, /*mode=*/ IGRAPH_OUT, /*unreachable=*/ 0, /*restricted=*/ &Nuv, /*order=*/ &Isv_min, /*rank=*/ 0, /*father=*/ 0, /*pred=*/ 0, /*succ=*/ 0, /*dist=*/ 0, /*callback=*/ 0, /*extra=*/ 0)); for (isvlen = 0; isvlen < no_of_nodes; isvlen++) { if (!IGRAPH_FINITE(VECTOR(Isv_min)[isvlen])) { break; } } igraph_vector_resize(&Isv_min, isvlen); /* -------------------------------------------------------------*/ /* For each c in M check whether Isv-K is included in Tbar. If such a v is found, compute Isv={x|v[Nu(v) U K]x} and return v and Isv; otherwise return Isv={}. */ for (j = 0; j < isvlen; j++) { long int v = (long int) VECTOR(Isv_min)[j]; if (igraph_estack_iselement(T, v) || v == target) { break; } } /* We might have found one */ if (j == isvlen) { *v = (long int) VECTOR(M)[i]; /* Calculate real Isv */ IGRAPH_CHECK(igraph_vector_append(&Nuv, &leftout)); IGRAPH_CHECK(igraph_bfs(graph, /*root=*/ (igraph_integer_t) *v, /*roots=*/ 0, /*mode=*/ IGRAPH_OUT, /*unreachable=*/ 0, /*restricted=*/ &Nuv, /*order=*/ &Isv_min, /*rank=*/ 0, /*father=*/ 0, /*pred=*/ 0, /*succ=*/ 0, /*dist=*/ 0, /*callback=*/ 0, /*extra=*/ 0)); for (isvlen = 0; isvlen < no_of_nodes; isvlen++) { if (!IGRAPH_FINITE(VECTOR(Isv_min)[isvlen])) { break; } } igraph_vector_resize(&Isv_min, isvlen); igraph_vector_update(Isv, &Isv_min); break; } } igraph_vector_destroy(&GammaS_vec); igraph_vector_destroy(&Isv_min); igraph_vector_destroy(&Nuv); IGRAPH_FINALLY_CLEAN(3); igraph_vector_destroy(&M); igraph_vector_bool_destroy(&GammaS); igraph_destroy(&domtree); igraph_vector_destroy(&leftout); igraph_destroy(&Sbar); igraph_vector_destroy(&Sbar_map); igraph_vector_destroy(&Sbar_invmap); IGRAPH_FINALLY_CLEAN(7); return 0; } /* TODO: This is a temporary recursive version, without proper error handling */ int igraph_provan_shier_list(const igraph_t *graph, igraph_marked_queue_t *S, igraph_estack_t *T, long int source, long int target, igraph_vector_ptr_t *result, igraph_provan_shier_pivot_t *pivot, void *pivot_arg) { long int no_of_nodes = igraph_vcount(graph); igraph_vector_t Isv; long int v = 0; long int i, n; igraph_vector_init(&Isv, 0); pivot(graph, S, T, source, target, &v, &Isv, pivot_arg); if (igraph_vector_size(&Isv) == 0) { if (igraph_marked_queue_size(S) != 0 && igraph_marked_queue_size(S) != no_of_nodes) { igraph_vector_t *vec = igraph_Calloc(1, igraph_vector_t); igraph_vector_init(vec, igraph_marked_queue_size(S)); igraph_marked_queue_as_vector(S, vec); IGRAPH_CHECK(igraph_vector_ptr_push_back(result, vec)); } } else { /* Put v into T */ igraph_estack_push(T, v); /* Go down left in the search tree */ igraph_provan_shier_list(graph, S, T, source, target, result, pivot, pivot_arg); /* Take out v from T */ igraph_estack_pop(T); /* Add Isv to S */ igraph_marked_queue_start_batch(S); n = igraph_vector_size(&Isv); for (i = 0; i < n; i++) { if (!igraph_marked_queue_iselement(S, (long int) VECTOR(Isv)[i])) { igraph_marked_queue_push(S, (long int) VECTOR(Isv)[i]); } } /* Go down right in the search tree */ igraph_provan_shier_list(graph, S, T, source, target, result, pivot, pivot_arg); /* Take out Isv from S */ igraph_marked_queue_pop_back_batch(S); } igraph_vector_destroy(&Isv); return 0; } /** * \function igraph_all_st_cuts * List all edge-cuts between two vertices in a directed graph * * This function lists all edge-cuts between a source and a target * vertex. Every cut is listed exactly once. The implemented algorithm * is described in JS Provan and DR Shier: A Paradigm for listing * (s,t)-cuts in graphs, Algorithmica 15, 351--372, 1996. * * \param graph The input graph, is must be directed. * \param cuts An initialized pointer vector, the cuts are stored * here. It is a list of pointers to igraph_vector_t * objects. Each vector will contain the ids of the edges in * the cut. This argument is ignored if it is a null pointer. * To free all memory allocated for \c cuts, you need call * \ref igraph_vector_destroy() and then \ref igraph_free() on * each element, before destroying the pointer vector itself. * \param partition1s An initialized pointer vector, the list of * vertex sets, generating the actual edge cuts, are stored * here. Each vector contains a set of vertex ids. If X is such * a set, then all edges going from X to the complement of X * form an (s,t) edge-cut in the graph. This argument is * ignored if it is a null pointer. * To free all memory allocated for \c partition1s, you need call * \ref igraph_vector_destroy() and then \ref igraph_free() on * each element, before destroying the pointer vector itself. * \param source The id of the source vertex. * \param target The id of the target vertex. * \return Error code. * * Time complexity: O(n(|V|+|E|)), where |V| is the number of * vertices, |E| is the number of edges, and n is the number of cuts. * * \example examples/simple/igraph_all_st_cuts.c */ int igraph_all_st_cuts(const igraph_t *graph, igraph_vector_ptr_t *cuts, igraph_vector_ptr_t *partition1s, igraph_integer_t source, igraph_integer_t target) { /* S is a special stack, in which elements are pushed in batches. It is then possible to remove the whole batch in one step. T is a stack with an is-element operation. Every element is included at most once. */ long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_marked_queue_t S; igraph_estack_t T; igraph_vector_ptr_t *mypartition1s = partition1s, vpartition1s; long int i, nocuts; if (!igraph_is_directed(graph)) { IGRAPH_ERROR("Listing all s-t cuts only implemented for " "directed graphs", IGRAPH_UNIMPLEMENTED); } if (!partition1s) { mypartition1s = &vpartition1s; IGRAPH_CHECK(igraph_vector_ptr_init(mypartition1s, 0)); IGRAPH_FINALLY(igraph_vector_ptr_destroy, mypartition1s); } else { igraph_vector_ptr_clear(mypartition1s); } IGRAPH_CHECK(igraph_marked_queue_init(&S, no_of_nodes)); IGRAPH_FINALLY(igraph_marked_queue_destroy, &S); IGRAPH_CHECK(igraph_estack_init(&T, no_of_nodes, 0)); IGRAPH_FINALLY(igraph_estack_destroy, &T); if (cuts) { igraph_vector_ptr_clear(cuts); } /* We call it with S={}, T={} */ IGRAPH_CHECK(igraph_provan_shier_list(graph, &S, &T, source, target, mypartition1s, igraph_i_all_st_cuts_pivot, /*pivot_arg=*/ 0)); nocuts = igraph_vector_ptr_size(mypartition1s); if (cuts) { igraph_vector_long_t inS; IGRAPH_CHECK(igraph_vector_long_init(&inS, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_long_destroy, &inS); IGRAPH_CHECK(igraph_vector_ptr_resize(cuts, nocuts)); for (i = 0; i < nocuts; i++) { igraph_vector_t *cut; igraph_vector_t *part = VECTOR(*mypartition1s)[i]; long int cutsize = 0; long int j, partlen = igraph_vector_size(part); /* Mark elements */ for (j = 0; j < partlen; j++) { long int v = (long int) VECTOR(*part)[j]; VECTOR(inS)[v] = i + 1; } /* Check how many edges */ for (j = 0; j < no_of_edges; j++) { long int from = IGRAPH_FROM(graph, j); long int to = IGRAPH_TO(graph, j); long int pfrom = VECTOR(inS)[from]; long int pto = VECTOR(inS)[to]; if (pfrom == i + 1 && pto != i + 1) { cutsize++; } } /* Add the edges */ cut = igraph_Calloc(1, igraph_vector_t); if (!cut) { IGRAPH_ERROR("Cannot calculate s-t cuts", IGRAPH_ENOMEM); } IGRAPH_VECTOR_INIT_FINALLY(cut, cutsize); cutsize = 0; for (j = 0; j < no_of_edges; j++) { long int from = IGRAPH_FROM(graph, j); long int to = IGRAPH_TO(graph, j); long int pfrom = VECTOR(inS)[from]; long int pto = VECTOR(inS)[to]; if ((pfrom == i + 1 && pto != i + 1)) { VECTOR(*cut)[cutsize++] = j; } } VECTOR(*cuts)[i] = cut; IGRAPH_FINALLY_CLEAN(1); } igraph_vector_long_destroy(&inS); IGRAPH_FINALLY_CLEAN(1); } igraph_estack_destroy(&T); igraph_marked_queue_destroy(&S); IGRAPH_FINALLY_CLEAN(2); if (!partition1s) { for (i = 0; i < nocuts; i++) { igraph_vector_t *cut = VECTOR(*mypartition1s)[i]; igraph_vector_destroy(cut); igraph_free(cut); VECTOR(*mypartition1s)[i] = 0; } igraph_vector_ptr_destroy(mypartition1s); IGRAPH_FINALLY_CLEAN(1); } return 0; } /* We need to find the minimal active elements of Sbar. I.e. all active Sbar elements 'v', s.t. there is no other 'w' active Sbar element from which 'v' is reachable. (Not necessarily through active vertices.) We calculate the in-degree of all vertices in Sbar first. Then we look at the vertices with zero in-degree. If these are active, then they are minimal. If they are are not active, then we remove them from the graph, and check whether they resulted in more zero-indegree vertices. */ int igraph_i_all_st_mincuts_minimal(const igraph_t *Sbar, const igraph_vector_bool_t *active, const igraph_vector_t *invmap, igraph_vector_t *minimal) { long int no_of_nodes = igraph_vcount(Sbar); igraph_vector_t indeg; long int i, minsize; igraph_vector_t neis; IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); IGRAPH_VECTOR_INIT_FINALLY(&indeg, no_of_nodes); IGRAPH_CHECK(igraph_degree(Sbar, &indeg, igraph_vss_all(), IGRAPH_IN, /*loops=*/ 1)); #define ACTIVE(x) (VECTOR(*active)[(long int)VECTOR(*invmap)[(x)]]) #define ZEROIN(x) (VECTOR(indeg)[(x)]==0) for (i = 0; i < no_of_nodes; i++) { if (!ACTIVE(i)) { long int j, n; IGRAPH_CHECK(igraph_neighbors(Sbar, &neis, (igraph_integer_t) i, IGRAPH_OUT)); n = igraph_vector_size(&neis); for (j = 0; j < n; j++) { long int nei = (long int) VECTOR(neis)[j]; VECTOR(indeg)[nei] -= 1; } } } for (minsize = 0, i = 0; i < no_of_nodes; i++) { if (ACTIVE(i) && ZEROIN(i)) { minsize++; } } IGRAPH_CHECK(igraph_vector_resize(minimal, minsize)); for (minsize = 0, i = 0; i < no_of_nodes; i++) { if (ACTIVE(i) && ZEROIN(i)) { VECTOR(*minimal)[minsize++] = i; } } #undef ACTIVE #undef ZEROIN igraph_vector_destroy(&indeg); igraph_vector_destroy(&neis); IGRAPH_FINALLY_CLEAN(3); return 0; } typedef struct igraph_i_all_st_mincuts_data_t { const igraph_vector_bool_t *active; } igraph_i_all_st_mincuts_data_t; int igraph_i_all_st_mincuts_pivot(const igraph_t *graph, const igraph_marked_queue_t *S, const igraph_estack_t *T, long int source, long int target, long int *v, igraph_vector_t *Isv, void *arg) { igraph_i_all_st_mincuts_data_t *data = arg; const igraph_vector_bool_t *active = data->active; long int no_of_nodes = igraph_vcount(graph); long int i, j; igraph_vector_t Sbar_map, Sbar_invmap; igraph_vector_t keep; igraph_t Sbar; igraph_vector_t M; long int nomin; IGRAPH_UNUSED(source); IGRAPH_UNUSED(target); if (igraph_marked_queue_size(S) == no_of_nodes) { igraph_vector_clear(Isv); return 0; } /* Create the graph induced by Sbar */ IGRAPH_VECTOR_INIT_FINALLY(&Sbar_map, 0); IGRAPH_VECTOR_INIT_FINALLY(&Sbar_invmap, 0); IGRAPH_VECTOR_INIT_FINALLY(&keep, 0); for (i = 0; i < no_of_nodes; i++) { if (!igraph_marked_queue_iselement(S, i)) { IGRAPH_CHECK(igraph_vector_push_back(&keep, i)); } } /* TODO: it is not even necessary to create Sbar explicitly, we just need to find the M elements efficiently. See the Provan-Shier paper for details. */ IGRAPH_CHECK(igraph_induced_subgraph_map(graph, &Sbar, igraph_vss_vector(&keep), IGRAPH_SUBGRAPH_AUTO, /* map= */ &Sbar_map, /* invmap= */ &Sbar_invmap)); IGRAPH_FINALLY(igraph_destroy, &Sbar); /* ------------------------------------------------------------- */ /* Identify the set M of minimal elements that are active */ IGRAPH_VECTOR_INIT_FINALLY(&M, 0); IGRAPH_CHECK(igraph_i_all_st_mincuts_minimal(&Sbar, active, &Sbar_invmap, &M)); /* ------------------------------------------------------------- */ /* Now find a minimal element that is not in T */ igraph_vector_clear(Isv); nomin = igraph_vector_size(&M); for (i = 0; i < nomin; i++) { long int min = (long int) VECTOR(Sbar_invmap)[ (long int) VECTOR(M)[i] ]; if (min != target) if (!igraph_estack_iselement(T, min)) { break; } } if (i != nomin) { /* OK, we found a pivot element. I(S,v) contains all elements that can reach the pivot element */ igraph_vector_t Isv_min; IGRAPH_VECTOR_INIT_FINALLY(&Isv_min, 0); *v = (long int) VECTOR(Sbar_invmap)[ (long int) VECTOR(M)[i] ]; /* TODO: restricted == keep ? */ IGRAPH_CHECK(igraph_bfs(graph, /*root=*/ (igraph_integer_t) *v,/*roots=*/ 0, /*mode=*/ IGRAPH_IN, /*unreachable=*/ 0, /*restricted=*/ &keep, /*order=*/ &Isv_min, /*rank=*/ 0, /*father=*/ 0, /*pred=*/ 0, /*succ=*/ 0, /*dist=*/ 0, /*callback=*/ 0, /*extra=*/ 0)); for (j = 0; j < no_of_nodes; j++) { igraph_real_t u = VECTOR(Isv_min)[j]; if (!IGRAPH_FINITE(u)) { break; } if (!igraph_estack_iselement(T, u)) { IGRAPH_CHECK(igraph_vector_push_back(Isv, u)); } } igraph_vector_destroy(&Isv_min); IGRAPH_FINALLY_CLEAN(1); } igraph_vector_destroy(&M); igraph_destroy(&Sbar); igraph_vector_destroy(&keep); igraph_vector_destroy(&Sbar_invmap); igraph_vector_destroy(&Sbar_map); IGRAPH_FINALLY_CLEAN(5); return 0; } /** * \function igraph_all_st_mincuts * All minimum s-t cuts of a directed graph * * This function lists all minimum edge cuts between two vertices, in a * directed graph. The implemented algorithm * is described in JS Provan and DR Shier: A Paradigm for listing * (s,t)-cuts in graphs, Algorithmica 15, 351--372, 1996. * * \param graph The input graph, it must be directed. * \param value Pointer to a real number, the value of the minimum cut * is stored here, unless it is a null pointer. * \param cuts An initialized pointer vector, the cuts are stored * here. It is a list of pointers to igraph_vector_t * objects. Each vector will contain the ids of the edges in * the cut. This argument is ignored if it is a null pointer. * To free all memory allocated for \c cuts, you need call * \ref igraph_vector_destroy() and then \ref igraph_free() on * each element, before destroying the pointer vector itself. * \param partition1s An initialized pointer vector, the list of * vertex sets, generating the actual edge cuts, are stored * here. Each vector contains a set of vertex ids. If X is such * a set, then all edges going from X to the complement of X * form an (s,t) edge-cut in the graph. This argument is * ignored if it is a null pointer. * \param source The id of the source vertex. * \param target The id of the target vertex. * \param capacity Vector of edge capacities. If this is a null * pointer, then all edges are assumed to have capacity one. * \return Error code. * * Time complexity: O(n(|V|+|E|))+O(F), where |V| is the number of * vertices, |E| is the number of edges, and n is the number of cuts; * O(F) is the time complexity of the maximum flow algorithm, see \ref * igraph_maxflow(). * * \example examples/simple/igraph_all_st_mincuts.c */ int igraph_all_st_mincuts(const igraph_t *graph, igraph_real_t *value, igraph_vector_ptr_t *cuts, igraph_vector_ptr_t *partition1s, igraph_integer_t source, igraph_integer_t target, const igraph_vector_t *capacity) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_vector_t flow; igraph_t residual; igraph_vector_t NtoL; long int newsource, newtarget; igraph_marked_queue_t S; igraph_estack_t T; igraph_i_all_st_mincuts_data_t pivot_data; igraph_vector_bool_t VE1bool; igraph_vector_t VE1; long int VE1size = 0; long int i, nocuts; igraph_integer_t proj_nodes; igraph_vector_t revmap_ptr, revmap_next; igraph_vector_ptr_t closedsets; igraph_vector_ptr_t *mypartition1s = partition1s, vpartition1s; igraph_maxflow_stats_t stats; /* -------------------------------------------------------------------- */ /* Error checks */ if (!igraph_is_directed(graph)) { IGRAPH_ERROR("S-t cuts can only be listed in directed graphs", IGRAPH_UNIMPLEMENTED); } if (source < 0 || source >= no_of_nodes) { IGRAPH_ERROR("Invalid `source' vertex", IGRAPH_EINVAL); } if (target < 0 || target >= no_of_nodes) { IGRAPH_ERROR("Invalid `target' vertex", IGRAPH_EINVAL); } if (source == target) { IGRAPH_ERROR("`source' and 'target' are the same vertex", IGRAPH_EINVAL); } if (!partition1s) { mypartition1s = &vpartition1s; IGRAPH_CHECK(igraph_vector_ptr_init(mypartition1s, 0)); IGRAPH_FINALLY(igraph_vector_ptr_destroy, mypartition1s); } /* -------------------------------------------------------------------- */ /* We need to calculate the maximum flow first */ IGRAPH_VECTOR_INIT_FINALLY(&flow, 0); IGRAPH_CHECK(igraph_maxflow(graph, value, &flow, /*cut=*/ 0, /*partition1=*/ 0, /*partition2=*/ 0, /*source=*/ source, /*target=*/ target, capacity, &stats)); /* -------------------------------------------------------------------- */ /* Then we need the reverse residual graph */ IGRAPH_CHECK(igraph_reverse_residual_graph(graph, capacity, &residual, &flow)); IGRAPH_FINALLY(igraph_destroy, &residual); /* -------------------------------------------------------------------- */ /* We shrink it to its strongly connected components */ IGRAPH_VECTOR_INIT_FINALLY(&NtoL, 0); IGRAPH_CHECK(igraph_clusters(&residual, /*membership=*/ &NtoL, /*csize=*/ 0, /*no=*/ &proj_nodes, IGRAPH_STRONG)); IGRAPH_CHECK(igraph_contract_vertices(&residual, /*mapping=*/ &NtoL, /*vertex_comb=*/ 0)); IGRAPH_CHECK(igraph_simplify(&residual, /*multiple=*/ 1, /*loops=*/ 1, /*edge_comb=*/ 0)); newsource = (long int) VECTOR(NtoL)[(long int)source]; newtarget = (long int) VECTOR(NtoL)[(long int)target]; /* TODO: handle the newsource == newtarget case */ /* -------------------------------------------------------------------- */ /* Determine the active vertices in the projection */ IGRAPH_VECTOR_INIT_FINALLY(&VE1, 0); IGRAPH_CHECK(igraph_vector_bool_init(&VE1bool, proj_nodes)); IGRAPH_FINALLY(igraph_vector_bool_destroy, &VE1bool); for (i = 0; i < no_of_edges; i++) { if (VECTOR(flow)[i] > 0) { long int from = IGRAPH_FROM(graph, i); long int to = IGRAPH_TO(graph, i); long int pfrom = (long int) VECTOR(NtoL)[from]; long int pto = (long int) VECTOR(NtoL)[to]; if (!VECTOR(VE1bool)[pfrom]) { VECTOR(VE1bool)[pfrom] = 1; VE1size++; } if (!VECTOR(VE1bool)[pto]) { VECTOR(VE1bool)[pto] = 1; VE1size++; } } } IGRAPH_CHECK(igraph_vector_reserve(&VE1, VE1size)); for (i = 0; i < proj_nodes; i++) { if (VECTOR(VE1bool)[i]) { igraph_vector_push_back(&VE1, i); } } if (cuts) { igraph_vector_ptr_clear(cuts); } if (partition1s) { igraph_vector_ptr_clear(partition1s); } /* -------------------------------------------------------------------- */ /* Everything is ready, list the cuts, using the right PIVOT function */ IGRAPH_CHECK(igraph_marked_queue_init(&S, no_of_nodes)); IGRAPH_FINALLY(igraph_marked_queue_destroy, &S); IGRAPH_CHECK(igraph_estack_init(&T, no_of_nodes, 0)); IGRAPH_FINALLY(igraph_estack_destroy, &T); pivot_data.active = &VE1bool; IGRAPH_CHECK(igraph_vector_ptr_init(&closedsets, 0)); IGRAPH_FINALLY(igraph_vector_ptr_destroy, &closedsets); /* TODO */ IGRAPH_CHECK(igraph_provan_shier_list(&residual, &S, &T, newsource, newtarget, &closedsets, igraph_i_all_st_mincuts_pivot, &pivot_data)); /* Convert the closed sets in the contracted graphs to cutsets in the original graph */ IGRAPH_VECTOR_INIT_FINALLY(&revmap_ptr, igraph_vcount(&residual)); IGRAPH_VECTOR_INIT_FINALLY(&revmap_next, no_of_nodes); for (i = 0; i < no_of_nodes; i++) { long int id = (long int) VECTOR(NtoL)[i]; VECTOR(revmap_next)[i] = VECTOR(revmap_ptr)[id]; VECTOR(revmap_ptr)[id] = i + 1; } /* Create partitions in original graph */ nocuts = igraph_vector_ptr_size(&closedsets); igraph_vector_ptr_clear(mypartition1s); IGRAPH_CHECK(igraph_vector_ptr_reserve(mypartition1s, nocuts)); for (i = 0; i < nocuts; i++) { igraph_vector_t *supercut = VECTOR(closedsets)[i]; long int j, supercutsize = igraph_vector_size(supercut); igraph_vector_t *cut = igraph_Calloc(1, igraph_vector_t); IGRAPH_VECTOR_INIT_FINALLY(cut, 0); /* TODO: better allocation */ for (j = 0; j < supercutsize; j++) { long int vtx = (long int) VECTOR(*supercut)[j]; long int ovtx = (long int) VECTOR(revmap_ptr)[vtx]; while (ovtx != 0) { ovtx--; IGRAPH_CHECK(igraph_vector_push_back(cut, ovtx)); ovtx = (long int) VECTOR(revmap_next)[ovtx]; } } igraph_vector_ptr_push_back(mypartition1s, cut); IGRAPH_FINALLY_CLEAN(1); igraph_vector_destroy(supercut); igraph_free(supercut); VECTOR(closedsets)[i] = 0; } igraph_vector_destroy(&revmap_next); igraph_vector_destroy(&revmap_ptr); igraph_vector_ptr_destroy(&closedsets); IGRAPH_FINALLY_CLEAN(3); /* Create cuts in original graph */ if (cuts) { igraph_vector_long_t memb; IGRAPH_CHECK(igraph_vector_long_init(&memb, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_long_destroy, &memb); IGRAPH_CHECK(igraph_vector_ptr_resize(cuts, nocuts)); for (i = 0; i < nocuts; i++) { igraph_vector_t *part = VECTOR(*mypartition1s)[i]; long int j, n = igraph_vector_size(part); igraph_vector_t *v; v = igraph_Calloc(1, igraph_vector_t); if (!v) { IGRAPH_ERROR("Cannot list minimum s-t cuts", IGRAPH_ENOMEM); } IGRAPH_VECTOR_INIT_FINALLY(v, 0); for (j = 0; j < n; j++) { long int vtx = (long int) VECTOR(*part)[j]; VECTOR(memb)[vtx] = i + 1; } for (j = 0; j < no_of_edges; j++) { if (VECTOR(flow)[j] > 0) { long int from = IGRAPH_FROM(graph, j); long int to = IGRAPH_TO(graph, j); if (VECTOR(memb)[from] == i + 1 && VECTOR(memb)[to] != i + 1) { IGRAPH_CHECK(igraph_vector_push_back(v, j)); /* TODO: allocation */ } } } VECTOR(*cuts)[i] = v; IGRAPH_FINALLY_CLEAN(1); } igraph_vector_long_destroy(&memb); IGRAPH_FINALLY_CLEAN(1); } igraph_estack_destroy(&T); igraph_marked_queue_destroy(&S); igraph_vector_bool_destroy(&VE1bool); igraph_vector_destroy(&VE1); igraph_vector_destroy(&NtoL); igraph_destroy(&residual); igraph_vector_destroy(&flow); IGRAPH_FINALLY_CLEAN(7); if (!partition1s) { for (i = 0; i < nocuts; i++) { igraph_vector_t *cut = VECTOR(*mypartition1s)[i]; igraph_vector_destroy(cut); igraph_free(cut); VECTOR(*mypartition1s)[i] = 0; } igraph_vector_ptr_destroy(mypartition1s); IGRAPH_FINALLY_CLEAN(1); } return 0; } python-igraph-0.8.0/vendor/source/igraph/src/fortran_intrinsics.c0000644000076500000240000000243213614300625025463 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-12 Gabor Csardi 334 Harvard street, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include double digitsdbl_(double x) { return (double) DBL_MANT_DIG; } double epsilondbl_(double x) { return DBL_EPSILON; } double hugedbl_(double x) { return DBL_MAX; } double tinydbl_(double x) { return DBL_MIN; } int maxexponentdbl_(double x) { return DBL_MAX_EXP; } int minexponentdbl_(double x) { return DBL_MIN_EXP; } double radixdbl_(double x) { return (double) FLT_RADIX; } python-igraph-0.8.0/vendor/source/igraph/src/igraph_lapack_internal.h0000644000076500000240000001546613614300625026244 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef LAPACK_INTERNAL_H #define LAPACK_INTERNAL_H /* Note: only files calling the LAPACK routines directly need to include this header. */ #include "igraph_types.h" #include "config.h" #ifndef INTERNAL_LAPACK #define igraphdgeevx_ dgeevx_ #define igraphdgeev_ dgeev_ #define igraphdgebak_ dgebak_ #define igraphxerbla_ xerbla_ #define igraphdgebal_ dgebal_ #define igraphdisnan_ disnan_ #define igraphdlaisnan_ dlaisnan_ #define igraphdgehrd_ dgehrd_ #define igraphdgehd2_ dgehd2_ #define igraphdlarf_ dlarf_ #define igraphiladlc_ iladlc_ #define igraphiladlr_ iladlr_ #define igraphdlarfg_ dlarfg_ #define igraphdlapy2_ dlapy2_ #define igraphdlahr2_ dlahr2_ #define igraphdlacpy_ dlacpy_ #define igraphdlarfb_ dlarfb_ #define igraphilaenv_ ilaenv_ #define igraphieeeck_ ieeeck_ #define igraphiparmq_ iparmq_ #define igraphdhseqr_ dhseqr_ #define igraphdlahqr_ dlahqr_ #define igraphdlabad_ dlabad_ #define igraphdlanv2_ dlanv2_ #define igraphdlaqr0_ dlaqr0_ #define igraphdlaqr3_ dlaqr3_ #define igraphdlaqr4_ dlaqr4_ #define igraphdlaqr2_ dlaqr2_ #define igraphdlaset_ dlaset_ #define igraphdormhr_ dormhr_ #define igraphdormqr_ dormqr_ #define igraphdlarft_ dlarft_ #define igraphdorm2r_ dorm2r_ #define igraphdtrexc_ dtrexc_ #define igraphdlaexc_ dlaexc_ #define igraphdlange_ dlange_ #define igraphdlassq_ dlassq_ #define igraphdlarfx_ dlarfx_ #define igraphdlartg_ dlartg_ #define igraphdlasy2_ dlasy2_ #define igraphdlaqr5_ dlaqr5_ #define igraphdlaqr1_ dlaqr1_ #define igraphdlascl_ dlascl_ #define igraphdorghr_ dorghr_ #define igraphdorgqr_ dorgqr_ #define igraphdorg2r_ dorg2r_ #define igraphdtrevc_ dtrevc_ #define igraphdlaln2_ dlaln2_ #define igraphdladiv_ dladiv_ #define igraphdsyevr_ dsyevr_ #define igraphdsyrk_ dsyrk_ #define igraphdlansy_ dlansy_ #define igraphdormtr_ dormtr_ #define igraphdormql_ dormql_ #define igraphdorm2l_ dorm2l_ #define igraphdstebz_ dstebz_ #define igraphdlaebz_ dlaebz_ #define igraphdstein_ dstein_ #define igraphdlagtf_ dlagtf_ #define igraphdlagts_ dlagts_ #define igraphdlarnv_ dlarnv_ #define igraphdlaruv_ dlaruv_ #define igraphdstemr_ dstemr_ #define igraphdlae2_ dlae2_ #define igraphdlaev2_ dlaev2_ #define igraphdlanst_ dlanst_ #define igraphdlarrc_ dlarrc_ #define igraphdlarre_ dlarre_ #define igraphdlarra_ dlarra_ #define igraphdlarrb_ dlarrb_ #define igraphdlaneg_ dlaneg_ #define igraphdlarrd_ dlarrd_ #define igraphdlarrk_ dlarrk_ #define igraphdlasq2_ dlasq2_ #define igraphdlasq3_ dlasq3_ #define igraphdlasq4_ dlasq4_ #define igraphdlasq5_ dlasq5_ #define igraphdlasq6_ dlasq6_ #define igraphdlasrt_ dlasrt_ #define igraphdlarrj_ dlarrj_ #define igraphdlarrr_ dlarrr_ #define igraphdlarrv_ dlarrv_ #define igraphdlar1v_ dlar1v_ #define igraphdlarrf_ dlarrf_ #define igraphdpotrf_ dpotrf_ #define igraphdsterf_ dsterf_ #define igraphdsytrd_ dsytrd_ #define igraphdlatrd_ dlatrd_ #define igraphdsytd2_ dsytd2_ #define igraphdlanhs_ dlanhs_ #define igraphdgeqr2_ dgeqr2_ #define igraphdtrsen_ dtrsen_ #define igraphdlacn2_ dlacn2_ #define igraphdtrsyl_ dtrsyl_ #define igraphdlasr_ dlasr_ #define igraphdsteqr_ dsteqr_ #define igraphdgesv_ dgesv_ #define igraphdgetrf_ dgetrf_ #define igraphdgetf2_ dgetf2_ #define igraphdlaswp_ dlaswp_ #define igraphdgetrs_ dgetrs_ #define igraphlen_trim_ len_trim_ #define igraph_dlamc1_ dlamc1_ #define igraph_dlamc2_ dlamc2_ #define igraph_dlamc3_ dlamc3_ #define igraph_dlamc4_ dlamc4_ #define igraph_dlamc5_ dlamc5_ #define igraphddot_ ddot_ #endif int igraphdgetrf_(int *m, int *n, igraph_real_t *a, int *lda, int *ipiv, int *info); int igraphdgetrs_(char *trans, int *n, int *nrhs, igraph_real_t *a, int *lda, int *ipiv, igraph_real_t *b, int *ldb, int *info); int igraphdgesv_(int *n, int *nrhs, igraph_real_t *a, int *lda, int *ipiv, igraph_real_t *b, int *ldb, int *info); igraph_real_t igraphdlapy2_(igraph_real_t *x, igraph_real_t *y); int igraphdsyevr_(char *jobz, char *range, char *uplo, int *n, igraph_real_t *a, int *lda, igraph_real_t *vl, igraph_real_t *vu, int * il, int *iu, igraph_real_t *abstol, int *m, igraph_real_t *w, igraph_real_t *z, int *ldz, int *isuppz, igraph_real_t *work, int *lwork, int *iwork, int *liwork, int *info); int igraphdgeev_(char *jobvl, char *jobvr, int *n, igraph_real_t *a, int *lda, igraph_real_t *wr, igraph_real_t *wi, igraph_real_t *vl, int *ldvl, igraph_real_t *vr, int *ldvr, igraph_real_t *work, int *lwork, int *info); int igraphdgeevx_(char *balanc, char *jobvl, char *jobvr, char *sense, int *n, igraph_real_t *a, int *lda, igraph_real_t *wr, igraph_real_t *wi, igraph_real_t *vl, int *ldvl, igraph_real_t *vr, int *ldvr, int *ilo, int *ihi, igraph_real_t *scale, igraph_real_t *abnrm, igraph_real_t *rconde, igraph_real_t *rcondv, igraph_real_t *work, int *lwork, int *iwork, int *info); int igraphdgehrd_(int *n, int *ilo, int *ihi, igraph_real_t *A, int *lda, igraph_real_t *tau, igraph_real_t *work, int *lwork, int *info); igraph_real_t igraphddot_(int *n, igraph_real_t *dx, int *incx, igraph_real_t *dy, int *incy); #endif python-igraph-0.8.0/vendor/source/igraph/src/foreign-ncol-header.h0000644000076500000240000000214213614300625025356 0ustar tamasstaff00000000000000/* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard street, Cambridge MA, 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_vector.h" #include "igraph_types_internal.h" typedef struct { void *scanner; int eof; char errmsg[300]; int has_weights; igraph_vector_t *vector; igraph_vector_t *weights; igraph_trie_t *trie; } igraph_i_ncol_parsedata_t; python-igraph-0.8.0/vendor/source/igraph/src/separators.c0000644000076500000240000007357313614300625023744 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_separators.h" #include "igraph_memory.h" #include "igraph_adjlist.h" #include "igraph_dqueue.h" #include "igraph_vector.h" #include "igraph_interface.h" #include "igraph_flow.h" #include "igraph_flow_internal.h" #include "igraph_components.h" #include "igraph_structural.h" #include "igraph_constructors.h" #include "igraph_stack.h" #include "igraph_interrupt_internal.h" int igraph_i_is_separator(const igraph_t *graph, igraph_vit_t *vit, long int except, igraph_bool_t *res, igraph_vector_bool_t *removed, igraph_dqueue_t *Q, igraph_vector_t *neis, long int no_of_nodes) { long int start = 0; if (IGRAPH_VIT_SIZE(*vit) >= no_of_nodes - 1) { /* Just need to check that we really have at least n-1 vertices in it */ igraph_vector_bool_t hit; long int nohit = 0; IGRAPH_CHECK(igraph_vector_bool_init(&hit, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_bool_destroy, &hit); for (IGRAPH_VIT_RESET(*vit); !IGRAPH_VIT_END(*vit); IGRAPH_VIT_NEXT(*vit)) { long int v = IGRAPH_VIT_GET(*vit); if (!VECTOR(hit)[v]) { nohit++; VECTOR(hit)[v] = 1; } } igraph_vector_bool_destroy(&hit); IGRAPH_FINALLY_CLEAN(1); if (nohit >= no_of_nodes - 1) { *res = 0; return 0; } } /* Remove the given vertices from the graph, do a breadth-first search and check the number of components */ if (except < 0) { for (IGRAPH_VIT_RESET(*vit); !IGRAPH_VIT_END(*vit); IGRAPH_VIT_NEXT(*vit)) { VECTOR(*removed)[ (long int) IGRAPH_VIT_GET(*vit) ] = 1; } } else { /* There is an exception */ long int i; for (i = 0, IGRAPH_VIT_RESET(*vit); i < except; i++, IGRAPH_VIT_NEXT(*vit)) { VECTOR(*removed)[ (long int) IGRAPH_VIT_GET(*vit) ] = 1; } for (IGRAPH_VIT_NEXT(*vit); !IGRAPH_VIT_END(*vit); IGRAPH_VIT_NEXT(*vit)) { VECTOR(*removed)[ (long int) IGRAPH_VIT_GET(*vit) ] = 1; } } /* Look for the first node that is not removed */ while (start < no_of_nodes && VECTOR(*removed)[start]) { start++; } if (start == no_of_nodes) { IGRAPH_ERROR("All vertices are included in the separator", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_dqueue_push(Q, start)); VECTOR(*removed)[start] = 1; while (!igraph_dqueue_empty(Q)) { long int node = (long int) igraph_dqueue_pop(Q); long int j, n; IGRAPH_CHECK(igraph_neighbors(graph, neis, (igraph_integer_t) node, IGRAPH_ALL)); n = igraph_vector_size(neis); for (j = 0; j < n; j++) { long int nei = (long int) VECTOR(*neis)[j]; if (!VECTOR(*removed)[nei]) { IGRAPH_CHECK(igraph_dqueue_push(Q, nei)); VECTOR(*removed)[nei] = 1; } } } /* Look for the next node that was neighter removed, not visited */ while (start < no_of_nodes && VECTOR(*removed)[start]) { start++; } /* If there is another component, then we have a separator */ *res = (start < no_of_nodes); return 0; } /** * \function igraph_is_separator * Decides whether the removal of a set of vertices disconnects the graph * * \param graph The input graph. It may be directed, but edge * directions are ignored. * \param condidate The candidate separator. It must not contain all * vertices. * \param res Pointer to a boolean variable, the result is stored here. * \return Error code. * * Time complexity: O(|V|+|E|), linear in the number vertices and edges. * * \example examples/simple/igraph_is_separator.c */ int igraph_is_separator(const igraph_t *graph, const igraph_vs_t candidate, igraph_bool_t *res) { long int no_of_nodes = igraph_vcount(graph); igraph_vector_bool_t removed; igraph_dqueue_t Q; igraph_vector_t neis; igraph_vit_t vit; IGRAPH_CHECK(igraph_vit_create(graph, candidate, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); IGRAPH_CHECK(igraph_vector_bool_init(&removed, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_bool_destroy, &removed); IGRAPH_CHECK(igraph_dqueue_init(&Q, 100)); IGRAPH_FINALLY(igraph_dqueue_destroy, &Q); IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); IGRAPH_CHECK(igraph_i_is_separator(graph, &vit, -1, res, &removed, &Q, &neis, no_of_nodes)); igraph_vector_destroy(&neis); igraph_dqueue_destroy(&Q); igraph_vector_bool_destroy(&removed); igraph_vit_destroy(&vit); IGRAPH_FINALLY_CLEAN(4); return 0; } /** * \function igraph_is_minimal_separator * Decides whether a set of vertices is a minimal separator * * A set of vertices is a minimal separator, if the removal of the * vertices disconnects the graph, and this is not true for any subset * of the set. * * This implementation first checks that the given * candidate is a separator, by calling \ref * igraph_is_separator(). If it is a separator, then it checks that * each subset of size n-1, where n is the size of the candidate, is * not a separator. * \param graph The input graph. It may be directed, but edge * directions are ignored. * \param candidate Pointer to a vector of long integers, the * candidate minimal separator. * \param res Pointer to a boolean variable, the result is stored * here. * \return Error code. * * Time complexity: O(n(|V|+|E|)), |V| is the number of vertices, |E| * is the number of edges, n is the number vertices in the candidate * separator. * * \example examples/simple/igraph_is_minimal_separator.c */ int igraph_is_minimal_separator(const igraph_t *graph, const igraph_vs_t candidate, igraph_bool_t *res) { long int no_of_nodes = igraph_vcount(graph); igraph_vector_bool_t removed; igraph_dqueue_t Q; igraph_vector_t neis; long int candsize; igraph_vit_t vit; IGRAPH_CHECK(igraph_vit_create(graph, candidate, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); candsize = IGRAPH_VIT_SIZE(vit); IGRAPH_CHECK(igraph_vector_bool_init(&removed, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_bool_destroy, &removed); IGRAPH_CHECK(igraph_dqueue_init(&Q, 100)); IGRAPH_FINALLY(igraph_dqueue_destroy, &Q); IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); /* Is it a separator at all? */ IGRAPH_CHECK(igraph_i_is_separator(graph, &vit, -1, res, &removed, &Q, &neis, no_of_nodes)); if (!(*res)) { /* Not a separator at all, nothing to do, *res is already set */ } else if (candsize == 0) { /* Nothing to do, minimal, *res is already set */ } else { /* General case, we need to remove each vertex from 'candidate' * and check whether the remainder is a separator. If this is * false for all vertices, then 'candidate' is a minimal * separator. */ long int i; for (i = 0, *res = 0; i < candsize && (!*res); i++) { igraph_vector_bool_null(&removed); IGRAPH_CHECK(igraph_i_is_separator(graph, &vit, i, res, &removed, &Q, &neis, no_of_nodes)); } (*res) = (*res) ? 0 : 1; /* opposite */ } igraph_vector_destroy(&neis); igraph_dqueue_destroy(&Q); igraph_vector_bool_destroy(&removed); igraph_vit_destroy(&vit); IGRAPH_FINALLY_CLEAN(4); return 0; } /* --------------------------------------------------------------------*/ #define UPDATEMARK() do { \ (*mark)++; \ if (!(*mark)) { \ igraph_vector_null(leaveout); \ (*mark)=1; \ } \ } while (0) int igraph_i_clusters_leaveout(const igraph_adjlist_t *adjlist, igraph_vector_t *components, igraph_vector_t *leaveout, unsigned long int *mark, igraph_dqueue_t *Q) { /* Another trick: we use the same 'leaveout' vector to mark the * vertices that were already found in the BFS */ long int i, no_of_nodes = igraph_adjlist_size(adjlist); igraph_dqueue_clear(Q); igraph_vector_clear(components); for (i = 0; i < no_of_nodes; i++) { if (VECTOR(*leaveout)[i] == *mark) { continue; } VECTOR(*leaveout)[i] = *mark; igraph_dqueue_push(Q, i); igraph_vector_push_back(components, i); while (!igraph_dqueue_empty(Q)) { long int act_node = (long int) igraph_dqueue_pop(Q); igraph_vector_int_t *neis = igraph_adjlist_get(adjlist, act_node); long int j, n = igraph_vector_int_size(neis); for (j = 0; j < n; j++) { long int nei = (long int) VECTOR(*neis)[j]; if (VECTOR(*leaveout)[nei] == *mark) { continue; } IGRAPH_CHECK(igraph_dqueue_push(Q, nei)); VECTOR(*leaveout)[nei] = *mark; igraph_vector_push_back(components, nei); } } igraph_vector_push_back(components, -1); } UPDATEMARK(); return 0; } igraph_bool_t igraph_i_separators_newsep(const igraph_vector_ptr_t *comps, const igraph_vector_t *newc) { long int co, nocomps = igraph_vector_ptr_size(comps); for (co = 0; co < nocomps; co++) { igraph_vector_t *act = VECTOR(*comps)[co]; if (igraph_vector_all_e(act, newc)) { return 0; } } /* If not found, then it is new */ return 1; } int igraph_i_separators_store(igraph_vector_ptr_t *separators, const igraph_adjlist_t *adjlist, igraph_vector_t *components, igraph_vector_t *leaveout, unsigned long int *mark, igraph_vector_t *sorter) { /* We need to stote N(C), the neighborhood of C, but only if it is * not already stored among the separators. */ long int cptr = 0, next, complen = igraph_vector_size(components); while (cptr < complen) { long int saved = cptr; igraph_vector_clear(sorter); /* Calculate N(C) for the next C */ while ( (next = (long int) VECTOR(*components)[cptr++]) != -1) { VECTOR(*leaveout)[next] = *mark; } cptr = saved; while ( (next = (long int) VECTOR(*components)[cptr++]) != -1) { igraph_vector_int_t *neis = igraph_adjlist_get(adjlist, next); long int j, nn = igraph_vector_int_size(neis); for (j = 0; j < nn; j++) { long int nei = (long int) VECTOR(*neis)[j]; if (VECTOR(*leaveout)[nei] != *mark) { igraph_vector_push_back(sorter, nei); VECTOR(*leaveout)[nei] = *mark; } } } igraph_vector_sort(sorter); UPDATEMARK(); /* Add it to the list of separators, if it is new */ if (igraph_i_separators_newsep(separators, sorter)) { igraph_vector_t *newc = igraph_Calloc(1, igraph_vector_t); if (!newc) { IGRAPH_ERROR("Cannot calculate minimal separators", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newc); igraph_vector_copy(newc, sorter); IGRAPH_FINALLY(igraph_vector_destroy, newc); IGRAPH_CHECK(igraph_vector_ptr_push_back(separators, newc)); IGRAPH_FINALLY_CLEAN(2); } } /* while cptr < complen */ return 0; } void igraph_i_separators_free(igraph_vector_ptr_t *separators) { long int i, n = igraph_vector_ptr_size(separators); for (i = 0; i < n; i++) { igraph_vector_t *vec = VECTOR(*separators)[i]; if (vec) { igraph_vector_destroy(vec); igraph_Free(vec); } } } /** * \function igraph_all_minimal_st_separators * List all vertex sets that are minimal (s,t) separators for some s and t * * This function lists all vertex sets that are minimal (s,t) * separators for some (s,t) vertex pair. * * See more about the implemented algorithm in * Anne Berry, Jean-Paul Bordat and Olivier Cogis: Generating All the * Minimal Separators of a Graph, In: Peter Widmayer, Gabriele Neyer * and Stephan Eidenbenz (editors): Graph-theoretic concepts in * computer science, 1665, 167--172, 1999. Springer. * * \param graph The input graph. It may be directed, but edge * directions are ignored. * \param separators An initialized pointer vector, the separators * are stored here. It is a list of pointers to igraph_vector_t * objects. Each vector will contain the ids of the vertices in * the separator. * To free all memory allocated for \c separators, you need call * \ref igraph_vector_destroy() and then \ref igraph_free() on * each element, before destroying the pointer vector itself. * \return Error code. * * Time complexity: O(n|V|^3), |V| is the number of vertices, n is the * number of separators. * * \example examples/simple/igraph_minimal_separators.c */ int igraph_all_minimal_st_separators(const igraph_t *graph, igraph_vector_ptr_t *separators) { /* * Some notes about the tricks used here. For finding the components * of the graph after removing some vertices, we do the * following. First we mark the vertices with the actual mark stamp * (mark), then run breadth-first search on the graph, but not * considering the marked vertices. Then we increase the mark. If * there is integer overflow here, then we zero out the mark and set * it to one. (We might as well just always zero it out.) * * For each separator the vertices are stored in vertex id order. * This facilitates the comparison of the separators when we find a * potential new candidate. * * To keep track of which separator we already used as a basis, we * keep a boolean vector (already_tried). The try_next pointer show * the next separator to try as a basis. */ long int no_of_nodes = igraph_vcount(graph); igraph_vector_t leaveout; igraph_vector_bool_t already_tried; long int try_next = 0; unsigned long int mark = 1; long int v; igraph_adjlist_t adjlist; igraph_vector_t components; igraph_dqueue_t Q; igraph_vector_t sorter; igraph_vector_ptr_clear(separators); IGRAPH_FINALLY(igraph_i_separators_free, separators); IGRAPH_CHECK(igraph_vector_init(&leaveout, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_destroy, &leaveout); IGRAPH_CHECK(igraph_vector_bool_init(&already_tried, 0)); IGRAPH_FINALLY(igraph_vector_bool_destroy, &already_tried); IGRAPH_CHECK(igraph_vector_init(&components, 0)); IGRAPH_FINALLY(igraph_vector_destroy, &components); IGRAPH_CHECK(igraph_vector_reserve(&components, no_of_nodes * 2)); IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist); IGRAPH_CHECK(igraph_dqueue_init(&Q, 100)); IGRAPH_FINALLY(igraph_dqueue_destroy, &Q); IGRAPH_CHECK(igraph_vector_init(&sorter, 0)); IGRAPH_FINALLY(igraph_vector_destroy, &sorter); IGRAPH_CHECK(igraph_vector_reserve(&sorter, no_of_nodes)); /* --------------------------------------------------------------- * INITIALIZATION, we check whether the neighborhoods of the * vertices separate the graph. The ones that do will form the * initial basis. */ for (v = 0; v < no_of_nodes; v++) { /* Mark v and its neighbors */ igraph_vector_int_t *neis = igraph_adjlist_get(&adjlist, v); long int i, n = igraph_vector_int_size(neis); VECTOR(leaveout)[v] = mark; for (i = 0; i < n; i++) { long int nei = (long int) VECTOR(*neis)[i]; VECTOR(leaveout)[nei] = mark; } /* Find the components */ IGRAPH_CHECK(igraph_i_clusters_leaveout(&adjlist, &components, &leaveout, &mark, &Q)); /* Store the corresponding separators, N(C) for each component C */ IGRAPH_CHECK(igraph_i_separators_store(separators, &adjlist, &components, &leaveout, &mark, &sorter)); } /* --------------------------------------------------------------- * GENERATION, we need to use all already found separators as * basis and see if they generate more separators */ while (try_next < igraph_vector_ptr_size(separators)) { igraph_vector_t *basis = VECTOR(*separators)[try_next]; long int b, basislen = igraph_vector_size(basis); for (b = 0; b < basislen; b++) { /* Remove N(x) U basis */ long int x = (long int) VECTOR(*basis)[b]; igraph_vector_int_t *neis = igraph_adjlist_get(&adjlist, x); long int i, n = igraph_vector_int_size(neis); for (i = 0; i < basislen; i++) { long int sn = (long int) VECTOR(*basis)[i]; VECTOR(leaveout)[sn] = mark; } for (i = 0; i < n; i++) { long int nei = (long int) VECTOR(*neis)[i]; VECTOR(leaveout)[nei] = mark; } /* Find the components */ IGRAPH_CHECK(igraph_i_clusters_leaveout(&adjlist, &components, &leaveout, &mark, &Q)); /* Store the corresponding separators, N(C) for each component C */ IGRAPH_CHECK(igraph_i_separators_store(separators, &adjlist, &components, &leaveout, &mark, &sorter)); } try_next++; } /* --------------------------------------------------------------- */ igraph_vector_destroy(&sorter); igraph_dqueue_destroy(&Q); igraph_adjlist_destroy(&adjlist); igraph_vector_destroy(&components); igraph_vector_bool_destroy(&already_tried); igraph_vector_destroy(&leaveout); IGRAPH_FINALLY_CLEAN(7); /* +1 for separators */ return 0; } #undef UPDATEMARK int igraph_i_minimum_size_separators_append(igraph_vector_ptr_t *old, igraph_vector_ptr_t *new) { long int olen = igraph_vector_ptr_size(old); long int nlen = igraph_vector_ptr_size(new); long int i; for (i = 0; i < nlen; i++) { igraph_vector_t *newvec = VECTOR(*new)[i]; long int j; for (j = 0; j < olen; j++) { igraph_vector_t *oldvec = VECTOR(*old)[j]; if (igraph_vector_all_e(oldvec, newvec)) { break; } } if (j == olen) { IGRAPH_CHECK(igraph_vector_ptr_push_back(old, newvec)); olen++; } else { igraph_vector_destroy(newvec); igraph_free(newvec); } VECTOR(*new)[i] = 0; } igraph_vector_ptr_clear(new); return 0; } int igraph_i_minimum_size_separators_topkdeg(const igraph_t *graph, igraph_vector_t *res, long int k) { long int no_of_nodes = igraph_vcount(graph); igraph_vector_t deg, order; long int i; IGRAPH_VECTOR_INIT_FINALLY(°, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&order, no_of_nodes); IGRAPH_CHECK(igraph_degree(graph, °, igraph_vss_all(), IGRAPH_ALL, /*loops=*/ 0)); IGRAPH_CHECK(igraph_vector_order1(°, &order, no_of_nodes)); IGRAPH_CHECK(igraph_vector_resize(res, k)); for (i = 0; i < k; i++) { VECTOR(*res)[i] = VECTOR(order)[no_of_nodes - 1 - i]; } igraph_vector_destroy(&order); igraph_vector_destroy(°); IGRAPH_FINALLY_CLEAN(2); return 0; } void igraph_i_separators_stcuts_free(igraph_vector_ptr_t *p) { long int i, n = igraph_vector_ptr_size(p); for (i = 0; i < n; i++) { igraph_vector_t *v = VECTOR(*p)[i]; if (v) { igraph_vector_destroy(v); igraph_free(v); VECTOR(*p)[i] = 0; } } igraph_vector_ptr_destroy(p); } /** * \function igraph_minimum_size_separators * Find all minimum size separating vertex sets * * This function lists all separator vertex sets of minimum size. * A vertex set is a separator if its removal disconnects the graph. * * The implementation is based on the following paper: * Arkady Kanevsky: Finding all minimum-size separating vertex sets in * a graph, Networks 23, 533--541, 1993. * * \param graph The input graph, which must be undirected. * \param separators An initialized pointer vector, the separators * are stored here. It is a list of pointers to igraph_vector_t * objects. Each vector will contain the ids of the vertices in * the separator. * To free all memory allocated for \c separators, you need call * \ref igraph_vector_destroy() and then \ref igraph_free() on * each element, before destroying the pointer vector itself. * \return Error code. * * Time complexity: TODO. * * \example examples/simple/igraph_minimum_size_separators.c */ int igraph_minimum_size_separators(const igraph_t *graph, igraph_vector_ptr_t *separators) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_integer_t conn; long int k; igraph_vector_t X; long int i, j; igraph_bool_t issepX; igraph_t Gbar; igraph_vector_t phi; igraph_t graph_copy; igraph_vector_t capacity; igraph_maxflow_stats_t stats; if (igraph_is_directed(graph)) { IGRAPH_ERROR("Minimum size separators currently only works on undirected graphs", IGRAPH_EINVAL); } igraph_vector_ptr_clear(separators); IGRAPH_FINALLY(igraph_i_separators_free, separators); /* ---------------------------------------------------------------- */ /* 1 Find the vertex connectivity of 'graph' */ IGRAPH_CHECK(igraph_vertex_connectivity(graph, &conn, /* checks= */ 1)); k = conn; /* Special cases for low connectivity, two exits here! */ if (conn == 0) { /* Nothing to do */ IGRAPH_FINALLY_CLEAN(1); /* separators */ return 0; } else if (conn == 1) { igraph_vector_t ap; long int i, n; IGRAPH_VECTOR_INIT_FINALLY(&ap, 0); IGRAPH_CHECK(igraph_articulation_points(graph, &ap)); n = igraph_vector_size(&ap); IGRAPH_CHECK(igraph_vector_ptr_resize(separators, n)); igraph_vector_ptr_null(separators); for (i = 0; i < n; i++) { igraph_vector_t *v = igraph_Calloc(1, igraph_vector_t); if (!v) { IGRAPH_ERROR("Minimum size separators failed", IGRAPH_ENOMEM); } IGRAPH_VECTOR_INIT_FINALLY(v, 1); VECTOR(*v)[0] = VECTOR(ap)[i]; VECTOR(*separators)[i] = v; IGRAPH_FINALLY_CLEAN(1); } igraph_vector_destroy(&ap); IGRAPH_FINALLY_CLEAN(2); /* +1 for separators */ return 0; } else if (conn == no_of_nodes - 1) { long int k; IGRAPH_CHECK(igraph_vector_ptr_resize(separators, no_of_nodes)); igraph_vector_ptr_null(separators); for (i = 0; i < no_of_nodes; i++) { igraph_vector_t *v = igraph_Calloc(1, igraph_vector_t); if (!v) { IGRAPH_ERROR("Cannot list minimum size separators", IGRAPH_ENOMEM); } IGRAPH_VECTOR_INIT_FINALLY(v, no_of_nodes - 1); for (j = 0, k = 0; j < no_of_nodes; j++) { if (j != i) { VECTOR(*v)[k++] = j; } } VECTOR(*separators)[i] = v; IGRAPH_FINALLY_CLEAN(1); } IGRAPH_FINALLY_CLEAN(1); /* separators */ return 0; } /* Work on a copy of 'graph' */ IGRAPH_CHECK(igraph_copy(&graph_copy, graph)); IGRAPH_FINALLY(igraph_destroy, &graph_copy); /* ---------------------------------------------------------------- */ /* 2 Find k vertices with the largest degrees (x1;..,xk). Check if these k vertices form a separating k-set of G */ IGRAPH_CHECK(igraph_vector_init(&X, conn)); IGRAPH_FINALLY(igraph_vector_destroy, &X); IGRAPH_CHECK(igraph_i_minimum_size_separators_topkdeg(graph, &X, k)); IGRAPH_CHECK(igraph_is_separator(&graph_copy, igraph_vss_vector(&X), &issepX)); if (issepX) { igraph_vector_t *v = igraph_Calloc(1, igraph_vector_t); if (!v) { IGRAPH_ERROR("Cannot find minimal size separators", IGRAPH_ENOMEM); } IGRAPH_VECTOR_INIT_FINALLY(v, k); for (i = 0; i < k; i++) { VECTOR(*v)[i] = VECTOR(X)[i]; } IGRAPH_CHECK(igraph_vector_ptr_push_back(separators, v)); IGRAPH_FINALLY_CLEAN(1); } /* Create Gbar, the Even-Tarjan reduction of graph */ IGRAPH_VECTOR_INIT_FINALLY(&capacity, 0); IGRAPH_CHECK(igraph_even_tarjan_reduction(&graph_copy, &Gbar, &capacity)); IGRAPH_FINALLY(igraph_destroy, &Gbar); IGRAPH_VECTOR_INIT_FINALLY(&phi, no_of_edges); /* ---------------------------------------------------------------- */ /* 3 If v[j] != x[i] and v[j] is not adjacent to x[i] then */ for (i = 0; i < k; i++) { IGRAPH_ALLOW_INTERRUPTION(); for (j = 0; j < no_of_nodes; j++) { long int ii = (long int) VECTOR(X)[i]; igraph_real_t phivalue; igraph_bool_t conn; if (ii == j) { continue; /* the same vertex */ } igraph_are_connected(&graph_copy, (igraph_integer_t) ii, (igraph_integer_t) j, &conn); if (conn) { continue; /* they are connected */ } /* --------------------------------------------------------------- */ /* 4 Compute a maximum flow phi in Gbar from x[i] to v[j]. If |phi|=k, then */ IGRAPH_CHECK(igraph_maxflow(&Gbar, &phivalue, &phi, /*cut=*/ 0, /*partition=*/ 0, /*partition2=*/ 0, /* source= */ (igraph_integer_t) (ii + no_of_nodes), /* target= */ (igraph_integer_t) j, &capacity, &stats)); if (phivalue == k) { /* ------------------------------------------------------------- */ /* 5-6-7. Find all k-sets separating x[i] and v[j]. */ igraph_vector_ptr_t stcuts; IGRAPH_CHECK(igraph_vector_ptr_init(&stcuts, 0)); IGRAPH_FINALLY(igraph_i_separators_stcuts_free, &stcuts); IGRAPH_CHECK(igraph_all_st_mincuts(&Gbar, /*value=*/ 0, /*cuts=*/ &stcuts, /*partition1s=*/ 0, /*source=*/ (igraph_integer_t) (ii + no_of_nodes), /*target=*/ (igraph_integer_t) j, /*capacity=*/ &capacity)); IGRAPH_CHECK(igraph_i_minimum_size_separators_append(separators, &stcuts)); igraph_vector_ptr_destroy(&stcuts); IGRAPH_FINALLY_CLEAN(1); } /* if phivalue == k */ /* --------------------------------------------------------------- */ /* 8 Add edge (x[i],v[j]) to G. */ IGRAPH_CHECK(igraph_add_edge(&graph_copy, (igraph_integer_t) ii, (igraph_integer_t) j)); IGRAPH_CHECK(igraph_add_edge(&Gbar, (igraph_integer_t) (ii + no_of_nodes), (igraph_integer_t) j)); IGRAPH_CHECK(igraph_add_edge(&Gbar, (igraph_integer_t) (j + no_of_nodes), (igraph_integer_t) ii)); IGRAPH_CHECK(igraph_vector_push_back(&capacity, no_of_nodes)); IGRAPH_CHECK(igraph_vector_push_back(&capacity, no_of_nodes)); } /* for j 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "config.h" #include "igraph_types.h" #include "igraph_statusbar.h" #include "igraph_error.h" #include #include static IGRAPH_THREAD_LOCAL igraph_status_handler_t *igraph_i_status_handler = 0; /** * \function igraph_status * Report status from an igraph function. * * It calls the installed status handler function, if there is * one. Otherwise it does nothing. Note that the standard way to * report the status from an igraph function is the * \ref IGRAPH_STATUS or \ref IGRAPH_STATUSF macro, as these * take care of the termination of the calling function if the * status handler returns with \c IGRAPH_INTERRUPTED. * \param message The status message. * \param data Additional context, with user-defined semantics. * Existing igraph functions pass a null pointer here. * \return Error code. If a status handler function was called * and it did not return with \c IGRAPH_SUCCESS, then * \c IGRAPH_INTERRUPTED is returned by \c igraph_status(). * * Time complexity: O(1). */ int igraph_status(const char *message, void *data) { if (igraph_i_status_handler) { if (igraph_i_status_handler(message, data) != IGRAPH_SUCCESS) { return IGRAPH_INTERRUPTED; } } return IGRAPH_SUCCESS; } /** * \function igraph_statusf * Report status, more flexible printf-like version. * * This is the more flexible version of \ref igraph_status(), * that has a syntax similar to the \c printf standard C library function. * It substitutes the values of the additional arguments into the * \p message template string and calls \ref igraph_status(). * \param message Status message template string, the syntax is the same * as for the \c printf function. * \param data Additional context, with user-defined semantics. * Existing igraph functions pass a null pointer here. * \param ... The additional arguments to fill the template given in the * \p message argument. * \return Error code. If a status handler function was called * and it did not return with \c IGRAPH_SUCCESS, then * \c IGRAPH_INTERRUPTED is returned by \c igraph_status(). */ int igraph_statusf(const char *message, void *data, ...) { char buffer[300]; va_list ap; va_start(ap, data); vsnprintf(buffer, sizeof(buffer) - 1, message, ap); return igraph_status(buffer, data); } #ifndef USING_R /** * \function igraph_status_handler_stderr * A simple predefined status handler function. * * A simple status handler function, that writes the status * message to the standard errror. * \param message The status message. * \param data Additional context, with user-defined semantics. * Existing igraph functions pass a null pointer here. * \return Error code. * * Time complexity: O(1). */ int igraph_status_handler_stderr(const char *message, void *data) { IGRAPH_UNUSED(data); fputs(message, stderr); return 0; } #endif /** * \function igraph_set_status_handler * Install of uninstall a status handler function. * * To uninstall the currently installed status handler, call * this function with a null pointer. * \param new_handler The status handler function to install. * \return The previously installed status handler function. * * Time complexity: O(1). */ igraph_status_handler_t * igraph_set_status_handler(igraph_status_handler_t new_handler) { igraph_status_handler_t *previous_handler = igraph_i_status_handler; igraph_i_status_handler = new_handler; return previous_handler; } python-igraph-0.8.0/vendor/source/igraph/src/DensityGrid_3d.cpp0000644000076500000240000002416213614300625024722 0ustar tamasstaff00000000000000/* * Copyright 2007 Sandia Corporation. Under the terms of Contract * DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains * certain rights in this software. * * All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are * met: * * * Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * Neither the name of Sandia National Laboratories nor the names of * its contributors may be used to endorse or promote products derived from * this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT * OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED * TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF * LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING * NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. */ // This file contains the member definitions of the DensityGrid.h class // This code is modified from the original code by B.N. Wylie #include #include #include #include #include using namespace std; #include "drl_Node_3d.h" #include "DensityGrid_3d.h" #include "igraph_error.h" #define GET_BIN(z, y, x) (Bins[(z*GRID_SIZE+y)*GRID_SIZE+x]) namespace drl3d { //******************************************************* // Density Grid Destructor -- deallocates memory used // for Density matrix, fall_off matrix, and node deque. DensityGrid::~DensityGrid () { delete[] Density; delete[] fall_off; delete[] Bins; } /********************************************* * Function: Density_Grid::Reset * * Description: Reset the density grid * *********************************************/ // changed from reset to init since we will only // call this once in the parallel version of layout void DensityGrid::Init() { try { Density = new float[GRID_SIZE][GRID_SIZE][GRID_SIZE]; fall_off = new float[RADIUS * 2 + 1][RADIUS * 2 + 1][RADIUS * 2 + 1]; Bins = new deque[GRID_SIZE * GRID_SIZE * GRID_SIZE]; } catch (bad_alloc errora) { // cout << "Error: Out of memory! Program stopped." << endl; #ifdef MUSE_MPI MPI_Abort ( MPI_COMM_WORLD, 1 ); #else igraph_error("DrL is out of memory", __FILE__, __LINE__, IGRAPH_ENOMEM); return; #endif } // Clear Grid int i; for (i = 0; i < GRID_SIZE; i++) for (int j = 0; j < GRID_SIZE; j++) for (int k = 0; k < GRID_SIZE; k++) { Density[i][j][k] = 0; GET_BIN(i, j, k).erase(GET_BIN(i, j, k).begin(), GET_BIN(i, j, k).end()); } // Compute fall off for (i = -RADIUS; i <= RADIUS; i++) for (int j = -RADIUS; j <= RADIUS; j++) for (int k = -RADIUS; k <= RADIUS; k++) { fall_off[i + RADIUS][j + RADIUS][k + RADIUS] = (float)((RADIUS - fabs((float)i)) / RADIUS) * (float)((RADIUS - fabs((float)j)) / RADIUS) * (float)((RADIUS - fabs((float)k)) / RADIUS); } } /*************************************************** * Function: DensityGrid::GetDensity * * Description: Get_Density from density grid * **************************************************/ float DensityGrid::GetDensity(float Nx, float Ny, float Nz, bool fineDensity) { deque::iterator BI; int x_grid, y_grid, z_grid; float x_dist, y_dist, z_dist, distance, density = 0; int boundary = 10; // boundary around plane /* Where to look */ x_grid = (int)((Nx + HALF_VIEW + .5) * VIEW_TO_GRID); y_grid = (int)((Ny + HALF_VIEW + .5) * VIEW_TO_GRID); z_grid = (int)((Nz + HALF_VIEW + .5) * VIEW_TO_GRID); // Check for edges of density grid (10000 is arbitrary high density) if (x_grid > GRID_SIZE - boundary || x_grid < boundary) { return 10000; } if (y_grid > GRID_SIZE - boundary || y_grid < boundary) { return 10000; } if (z_grid > GRID_SIZE - boundary || z_grid < boundary) { return 10000; } // Fine density? if (fineDensity) { // Go through nearest bins for (int k = z_grid - 1; k <= z_grid + 1; k++) for (int i = y_grid - 1; i <= y_grid + 1; i++) for (int j = x_grid - 1; j <= x_grid + 1; j++) { // Look through bin and add fine repulsions for (BI = GET_BIN(k, i, j).begin(); BI < GET_BIN(k, i, j).end(); ++BI) { x_dist = Nx - (BI->x); y_dist = Ny - (BI->y); z_dist = Nz - (BI->z); distance = x_dist * x_dist + y_dist * y_dist + z_dist * z_dist; density += 1e-4 / (distance + 1e-50); } } // Course density } else { // Add rough estimate density = Density[z_grid][y_grid][x_grid]; density *= density; } return density; } /// Wrapper functions for the Add and subtract methods /// Nodes should all be passed by constant ref void DensityGrid::Add(Node &n, bool fineDensity) { if (fineDensity) { fineAdd(n); } else { Add(n); } } void DensityGrid::Subtract( Node &n, bool first_add, bool fine_first_add, bool fineDensity) { if ( fineDensity && !fine_first_add ) { fineSubtract (n); } else if ( !first_add ) { Subtract(n); } } /*************************************************** * Function: DensityGrid::Subtract * * Description: Subtract a node from density grid * **************************************************/ void DensityGrid::Subtract(Node &N) { int x_grid, y_grid, z_grid, diam; float *den_ptr, *fall_ptr; /* Where to subtract */ x_grid = (int)((N.sub_x + HALF_VIEW + .5) * VIEW_TO_GRID); y_grid = (int)((N.sub_y + HALF_VIEW + .5) * VIEW_TO_GRID); z_grid = (int)((N.sub_z + HALF_VIEW + .5) * VIEW_TO_GRID); x_grid -= RADIUS; y_grid -= RADIUS; z_grid -= RADIUS; diam = 2 * RADIUS; // check to see that we are inside grid if ( (x_grid >= GRID_SIZE) || (x_grid < 0) || (y_grid >= GRID_SIZE) || (y_grid < 0) || (z_grid >= GRID_SIZE) || (z_grid < 0) ) { #ifdef MUSE_MPI MPI_Abort ( MPI_COMM_WORLD, 1 ); #else igraph_error("Exceeded density grid in DrL", __FILE__, __LINE__, IGRAPH_EDRL); return; #endif } /* Subtract density values */ den_ptr = &Density[z_grid][y_grid][x_grid]; fall_ptr = &fall_off[0][0][0]; for (int i = 0; i <= diam; i++) { for (int j = 0; j <= diam; j++) for (int k = 0; k <= diam; k++) { *den_ptr++ -= *fall_ptr++; } den_ptr += GRID_SIZE - (diam + 1); } } /*************************************************** * Function: DensityGrid::Add * * Description: Add a node to the density grid * **************************************************/ void DensityGrid::Add(Node &N) { int x_grid, y_grid, z_grid, diam; float *den_ptr, *fall_ptr; /* Where to add */ x_grid = (int)((N.x + HALF_VIEW + .5) * VIEW_TO_GRID); y_grid = (int)((N.y + HALF_VIEW + .5) * VIEW_TO_GRID); z_grid = (int)((N.z + HALF_VIEW + .5) * VIEW_TO_GRID); N.sub_x = N.x; N.sub_y = N.y; N.sub_z = N.z; x_grid -= RADIUS; y_grid -= RADIUS; z_grid -= RADIUS; diam = 2 * RADIUS; // check to see that we are inside grid if ( (x_grid >= GRID_SIZE) || (x_grid < 0) || (y_grid >= GRID_SIZE) || (y_grid < 0) || (z_grid >= GRID_SIZE) || (z_grid < 0) ) { #ifdef MUSE_MPI MPI_Abort ( MPI_COMM_WORLD, 1 ); #else igraph_error("Exceeded density grid in DrL", __FILE__, __LINE__, IGRAPH_EDRL); return; #endif } /* Add density values */ den_ptr = &Density[z_grid][y_grid][x_grid]; fall_ptr = &fall_off[0][0][0]; for (int i = 0; i <= diam; i++) { for (int j = 0; j <= diam; j++) for (int k = 0; k <= diam; k++) { *den_ptr++ += *fall_ptr++; } den_ptr += GRID_SIZE - (diam + 1); } } /*************************************************** * Function: DensityGrid::fineSubtract * * Description: Subtract a node from bins * **************************************************/ void DensityGrid::fineSubtract(Node &N) { int x_grid, y_grid, z_grid; /* Where to subtract */ x_grid = (int)((N.sub_x + HALF_VIEW + .5) * VIEW_TO_GRID); y_grid = (int)((N.sub_y + HALF_VIEW + .5) * VIEW_TO_GRID); z_grid = (int)((N.sub_z + HALF_VIEW + .5) * VIEW_TO_GRID); GET_BIN(z_grid, y_grid, x_grid).pop_front(); } /*************************************************** * Function: DensityGrid::fineAdd * * Description: Add a node to the bins * **************************************************/ void DensityGrid::fineAdd(Node &N) { int x_grid, y_grid, z_grid; /* Where to add */ x_grid = (int)((N.x + HALF_VIEW + .5) * VIEW_TO_GRID); y_grid = (int)((N.y + HALF_VIEW + .5) * VIEW_TO_GRID); z_grid = (int)((N.z + HALF_VIEW + .5) * VIEW_TO_GRID); N.sub_x = N.x; N.sub_y = N.y; N.sub_z = N.z; GET_BIN(z_grid, y_grid, x_grid).push_back(N); } } // namespace drl3d python-igraph-0.8.0/vendor/source/igraph/src/igraph_f2c.h0000644000076500000240000001206713614300625023561 0ustar tamasstaff00000000000000/* f2c.h -- Standard Fortran to C header file */ /** barf [ba:rf] 2. "He suggested using FORTRAN, and everybody barfed." - From The Shogakukan DICTIONARY OF NEW ENGLISH (Second edition) */ #ifndef F2C_INCLUDE #define F2C_INCLUDE typedef long int integer; typedef unsigned long int uinteger; typedef char *address; typedef short int shortint; typedef float real; typedef double doublereal; typedef struct { real r, i; } complex; typedef struct { doublereal r, i; } doublecomplex; typedef long int logical; typedef short int shortlogical; typedef char logical1; typedef char integer1; #ifdef INTEGER_STAR_8 /* Adjust for integer*8. */ typedef long long longint; /* system-dependent */ typedef unsigned long long ulongint; /* system-dependent */ #define qbit_clear(a,b) ((a) & ~((ulongint)1 << (b))) #define qbit_set(a,b) ((a) | ((ulongint)1 << (b))) #endif #define TRUE_ (1) #define FALSE_ (0) /* Extern is for use with -E */ #ifndef Extern #define Extern extern #endif /* I/O stuff */ #ifdef f2c_i2 /* for -i2 */ typedef short flag; typedef short ftnlen; typedef short ftnint; #else typedef long int flag; typedef long int ftnlen; typedef long int ftnint; #endif /*external read, write*/ typedef struct { flag cierr; ftnint ciunit; flag ciend; char *cifmt; ftnint cirec; } cilist; /*internal read, write*/ typedef struct { flag icierr; char *iciunit; flag iciend; char *icifmt; ftnint icirlen; ftnint icirnum; } icilist; /*open*/ typedef struct { flag oerr; ftnint ounit; char *ofnm; ftnlen ofnmlen; char *osta; char *oacc; char *ofm; ftnint orl; char *oblnk; } olist; /*close*/ typedef struct { flag cerr; ftnint cunit; char *csta; } cllist; /*rewind, backspace, endfile*/ typedef struct { flag aerr; ftnint aunit; } alist; /* inquire */ typedef struct { flag inerr; ftnint inunit; char *infile; ftnlen infilen; ftnint *inex; /*parameters in standard's order*/ ftnint *inopen; ftnint *innum; ftnint *innamed; char *inname; ftnlen innamlen; char *inacc; ftnlen inacclen; char *inseq; ftnlen inseqlen; char *indir; ftnlen indirlen; char *infmt; ftnlen infmtlen; char *inform; ftnint informlen; char *inunf; ftnlen inunflen; ftnint *inrecl; ftnint *innrec; char *inblank; ftnlen inblanklen; } inlist; #define VOID void union Multitype { /* for multiple entry points */ integer1 g; shortint h; integer i; /* longint j; */ real r; doublereal d; complex c; doublecomplex z; }; typedef union Multitype Multitype; /*typedef long int Long;*/ /* No longer used; formerly in Namelist */ struct Vardesc { /* for Namelist */ char *name; char *addr; ftnlen *dims; int type; }; typedef struct Vardesc Vardesc; struct Namelist { char *name; Vardesc **vars; int nvars; }; typedef struct Namelist Namelist; #define abs(x) ((x) >= 0 ? (x) : -(x)) #define dabs(x) (doublereal)abs(x) #define min(a,b) ((a) <= (b) ? (a) : (b)) #define max(a,b) ((a) >= (b) ? (a) : (b)) #define dmin(a,b) (doublereal)min(a,b) #define dmax(a,b) (doublereal)max(a,b) #define bit_test(a,b) ((a) >> (b) & 1) #define bit_clear(a,b) ((a) & ~((uinteger)1 << (b))) #define bit_set(a,b) ((a) | ((uinteger)1 << (b))) /* procedure parameter types for -A and -C++ */ #define F2C_proc_par_types 1 #ifdef __cplusplus typedef int /* Unknown procedure type */ (*U_fp)(...); typedef shortint (*J_fp)(...); typedef integer (*I_fp)(...); typedef real (*R_fp)(...); typedef doublereal (*D_fp)(...), (*E_fp)(...); typedef /* Complex */ VOID (*C_fp)(...); typedef /* Double Complex */ VOID (*Z_fp)(...); typedef logical (*L_fp)(...); typedef shortlogical (*K_fp)(...); typedef /* Character */ VOID (*H_fp)(...); typedef /* Subroutine */ int (*S_fp)(...); #else typedef int /* Unknown procedure type */ (*U_fp)(); typedef shortint (*J_fp)(); typedef integer (*I_fp)(); typedef real (*R_fp)(); typedef doublereal (*D_fp)(), (*E_fp)(); typedef /* Complex */ VOID (*C_fp)(); typedef /* Double Complex */ VOID (*Z_fp)(); typedef logical (*L_fp)(); typedef shortlogical (*K_fp)(); typedef /* Character */ VOID (*H_fp)(); typedef /* Subroutine */ int (*S_fp)(); #endif /* E_fp is for real functions when -R is not specified */ typedef VOID C_f; /* complex function */ typedef VOID H_f; /* character function */ typedef VOID Z_f; /* double complex function */ typedef doublereal E_f; /* real function with -R not specified */ /* undef any lower-case symbols that your C compiler predefines, e.g.: */ #ifndef Skip_f2c_Undefs #undef cray #undef gcos #undef mc68010 #undef mc68020 #undef mips #undef pdp11 #undef sgi #undef sparc #undef sun #undef sun2 #undef sun3 #undef sun4 #undef u370 #undef u3b #undef u3b2 #undef u3b5 #undef unix #undef vax #endif #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD.diff0000644000076500000240000000550713524616144023332 0ustar tamasstaff00000000000000diff -r -x '*.o' -x '*.lo' -x .deps -x .dirstamp -x .libs CHOLMOD-orig/Include/cholmod_blas.h CHOLMOD/Include/cholmod_blas.h 108,115c108,115 < #define BLAS_DTRSV dtrsv < #define BLAS_DGEMV dgemv < #define BLAS_DTRSM dtrsm < #define BLAS_DGEMM dgemm < #define BLAS_DSYRK dsyrk < #define BLAS_DGER dger < #define BLAS_DSCAL dscal < #define LAPACK_DPOTRF dpotrf --- > #define BLAS_DTRSV igraphdtrsv > #define BLAS_DGEMV igraphdgemv > #define BLAS_DTRSM igraphdtrsm > #define BLAS_DGEMM igraphdgemm > #define BLAS_DSYRK igraphdsyrk > #define BLAS_DGER igraphdger > #define BLAS_DSCAL igraphdscal > #define LAPACK_DPOTRF igraphdpotrf 128,135c128,135 < #define BLAS_DTRSV dtrsv_ < #define BLAS_DGEMV dgemv_ < #define BLAS_DTRSM dtrsm_ < #define BLAS_DGEMM dgemm_ < #define BLAS_DSYRK dsyrk_ < #define BLAS_DGER dger_ < #define BLAS_DSCAL dscal_ < #define LAPACK_DPOTRF dpotrf_ --- > #define BLAS_DTRSV igraphdtrsv_ > #define BLAS_DGEMV igraphdgemv_ > #define BLAS_DTRSM igraphdtrsm_ > #define BLAS_DGEMM igraphdgemm_ > #define BLAS_DSYRK igraphdsyrk_ > #define BLAS_DGER igraphdger_ > #define BLAS_DSCAL igraphdscal_ > #define LAPACK_DPOTRF igraphdpotrf_ diff -r -x '*.o' -x '*.lo' -x .deps -x .dirstamp -x .libs CHOLMOD-orig/Supernodal/cholmod_super_numeric.c CHOLMOD/Supernodal/cholmod_super_numeric.c 79,82c79,82 < #define COMPLEX < #include "t_cholmod_super_numeric.c" < #define ZOMPLEX < #include "t_cholmod_super_numeric.c" --- > /* #define COMPLEX */ > /* #include "t_cholmod_super_numeric.c" */ > /* #define ZOMPLEX */ > /* #include "t_cholmod_super_numeric.c" */ 283,290c283,290 < case CHOLMOD_COMPLEX: < ok = c_cholmod_super_numeric (A, F, beta, L, C, Common) ; < break ; < < case CHOLMOD_ZOMPLEX: < /* This operates on complex L, not zomplex */ < ok = z_cholmod_super_numeric (A, F, beta, L, C, Common) ; < break ; --- > /* case CHOLMOD_COMPLEX: */ > /* ok = c_cholmod_super_numeric (A, F, beta, L, C, Common) ; */ > /* break ; */ > > /* case CHOLMOD_ZOMPLEX: */ > /* /\* This operates on complex L, not zomplex *\/ */ > /* ok = z_cholmod_super_numeric (A, F, beta, L, C, Common) ; */ > /* break ; */ diff -r -x '*.o' -x '*.lo' -x .deps -x .dirstamp -x .libs CHOLMOD-orig/Supernodal/cholmod_super_solve.c CHOLMOD/Supernodal/cholmod_super_solve.c 29,30c29,30 < #define COMPLEX < #include "t_cholmod_super_solve.c" --- > /* #define COMPLEX */ > /* #include "t_cholmod_super_solve.c" */ 112,114c112,114 < case CHOLMOD_COMPLEX: < c_cholmod_super_lsolve (L, X, E, Common) ; < break ; --- > /* case CHOLMOD_COMPLEX: */ > /* c_cholmod_super_lsolve (L, X, E, Common) ; */ > /* break ; */ 205,207c205,207 < case CHOLMOD_COMPLEX: < c_cholmod_super_ltsolve (L, X, E, Common) ; < break ; --- > /* case CHOLMOD_COMPLEX: */ > /* c_cholmod_super_ltsolve (L, X, E, Common) ; */ > /* break ; */ python-igraph-0.8.0/vendor/source/igraph/src/cliquer/0000755000076500000240000000000013617375001023045 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/src/cliquer/cliquer.c0000644000076500000240000013056113524616144024666 0ustar tamasstaff00000000000000 /* * This file contains the clique searching routines. * * Copyright (C) 2002 Sampo Niskanen, Patric Östergård. * Licensed under the GNU GPL, read the file LICENSE for details. */ #include #include #include /* #include #include #include */ #include "cliquer.h" #include "config.h" #ifdef USING_R #include #endif /* Default cliquer options */ IGRAPH_THREAD_LOCAL clique_options clique_default_options = { reorder_by_default, NULL, /*clique_print_time*/ NULL, NULL, NULL, NULL, NULL, 0 }; /* Calculate d/q, rounding result upwards/downwards. */ #define DIV_UP(d,q) (((d)+(q)-1)/(q)) #define DIV_DOWN(d,q) ((int)((d)/(q))) /* Global variables used: */ /* These must be saved and restored in re-entrance. */ static IGRAPH_THREAD_LOCAL int *clique_size; /* c[i] == max. clique size in {0,1,...,i-1} */ static IGRAPH_THREAD_LOCAL set_t current_clique; /* Current clique being searched. */ static IGRAPH_THREAD_LOCAL set_t best_clique; /* Largest/heaviest clique found so far. */ /*static struct tms cputimer;*/ /* Timer for opts->time_function() */ /*static struct timeval realtimer;*/ /* Timer for opts->time_function() */ static IGRAPH_THREAD_LOCAL int clique_list_count=0; /* No. of cliques in opts->clique_list[] */ static IGRAPH_THREAD_LOCAL int weight_multiplier=1; /* Weights multiplied by this when passing * to time_function(). */ /* List cache (contains memory blocks of size g->n * sizeof(int)) */ static IGRAPH_THREAD_LOCAL int **temp_list=NULL; static IGRAPH_THREAD_LOCAL int temp_count=0; /* * Macros for re-entrance. ENTRANCE_SAVE() must be called immediately * after variable definitions, ENTRANCE_RESTORE() restores global * variables to original values. entrance_level should be increased * and decreased accordingly. */ static IGRAPH_THREAD_LOCAL int entrance_level=0; /* How many levels for entrance have occurred? */ #define ENTRANCE_SAVE() \ int *old_clique_size = clique_size; \ set_t old_current_clique = current_clique; \ set_t old_best_clique = best_clique; \ int old_clique_list_count = clique_list_count; \ int old_weight_multiplier = weight_multiplier; \ int **old_temp_list = temp_list; \ int old_temp_count = temp_count; \ /*struct tms old_cputimer; \ struct timeval old_realtimer; \ memcpy(&old_cputimer,&cputimer,sizeof(struct tms)); \ memcpy(&old_realtimer,&realtimer,sizeof(struct timeval));*/ #define ENTRANCE_RESTORE() \ clique_size = old_clique_size; \ current_clique = old_current_clique; \ best_clique = old_best_clique; \ clique_list_count = old_clique_list_count; \ weight_multiplier = old_weight_multiplier; \ temp_list = old_temp_list; \ temp_count = old_temp_count; \ /*memcpy(&cputimer,&old_cputimer,sizeof(struct tms)); \ memcpy(&realtimer,&old_realtimer,sizeof(struct timeval));*/ /* Number of clock ticks per second (as returned by sysconf(_SC_CLK_TCK)) */ /*static int clocks_per_sec=0;*/ /* Recursion and helper functions */ static boolean sub_unweighted_single(int *table, int size, int min_size, graph_t *g); static int sub_unweighted_all(int *table, int size, int min_size, int max_size, boolean maximal, graph_t *g, clique_options *opts); static int sub_weighted_all(int *table, int size, int weight, int current_weight, int prune_low, int prune_high, int min_weight, int max_weight, boolean maximal, graph_t *g, clique_options *opts); static boolean store_clique(set_t clique, graph_t *g, clique_options *opts); static boolean is_maximal(set_t clique, graph_t *g); static boolean false_function(set_t clique,graph_t *g,clique_options *opts); /***** Unweighted searches *****/ /* * Unweighted searches are done separately from weighted searches because * some effective pruning methods can be used when the vertex weights * are all 1. Single and all clique finding routines are separated, * because the single clique finding routine can store the found clique * while it is returning from the recursion, thus requiring no implicit * storing of the current clique. When searching for all cliques the * current clique must be stored. */ /* * unweighted_clique_search_single() * * Searches for a single clique of size min_size. Stores maximum clique * sizes into clique_size[]. * * table - the order of the vertices in g to use * min_size - minimum size of clique to search for. If min_size==0, * searches for a maximum clique. * g - the graph * opts - time printing options * * opts->time_function is called after each base-level recursion, if * non-NULL. * * Returns the size of the clique found, or 0 if min_size>0 and a clique * of that size was not found (or if time_function aborted the search). * The largest clique found is stored in current_clique. * * Note: Does NOT use opts->user_function of opts->clique_list. */ static int unweighted_clique_search_single(int *table, int min_size, graph_t *g, clique_options *opts) { /* struct tms tms; struct timeval timeval; */ int i,j; int v,w; int *newtable; int newsize; v=table[0]; clique_size[v]=1; set_empty(current_clique); SET_ADD_ELEMENT(current_clique,v); if (min_size==1) return 1; if (temp_count) { temp_count--; newtable=temp_list[temp_count]; } else { newtable=malloc(g->n * sizeof(int)); } for (i=1; i < g->n; i++) { w=v; v=table[i]; newsize=0; for (j=0; jtime_function) { gettimeofday(&timeval,NULL); times(&tms); if (!opts->time_function(entrance_level, i+1,g->n,clique_size[v] * weight_multiplier, (double)(tms.tms_utime- cputimer.tms_utime)/ clocks_per_sec, timeval.tv_sec- realtimer.tv_sec+ (double)(timeval.tv_usec- realtimer.tv_usec)/ 1000000,opts)) { temp_list[temp_count++]=newtable; return 0; } } */ if (min_size) { if (clique_size[v]>=min_size) { temp_list[temp_count++]=newtable; return clique_size[v]; } if (clique_size[v]+g->n-i-1 < min_size) { temp_list[temp_count++]=newtable; return 0; } } } temp_list[temp_count++]=newtable; if (min_size) return 0; return clique_size[v]; } /* * sub_unweighted_single() * * Recursion function for searching for a single clique of size min_size. * * table - subset of the vertices in graph * size - size of table * min_size - size of clique to look for within the subgraph * (decreased with every recursion) * g - the graph * * Returns TRUE if a clique of size min_size is found, FALSE otherwise. * If a clique of size min_size is found, it is stored in current_clique. * * clique_size[] for all values in table must be defined and correct, * otherwise inaccurate results may occur. */ static boolean sub_unweighted_single(int *table, int size, int min_size, graph_t *g) { int i; int v; int *newtable; int *p1, *p2; /* Zero or one vertices needed anymore. */ if (min_size <= 1) { if (size>0 && min_size==1) { set_empty(current_clique); SET_ADD_ELEMENT(current_clique,table[0]); return TRUE; } if (min_size==0) { set_empty(current_clique); return TRUE; } return FALSE; } if (size < min_size) return FALSE; /* Dynamic memory allocation with cache */ if (temp_count) { temp_count--; newtable=temp_list[temp_count]; } else { newtable=malloc(g->n * sizeof(int)); } for (i = size-1; i >= 0; i--) { v = table[i]; if (clique_size[v] < min_size) break; /* This is faster when compiling with gcc than placing * this in the for-loop condition. */ if (i+1 < min_size) break; /* Very ugly code, but works faster than "for (i=...)" */ p1 = newtable; for (p2=table; p2 < table+i; p2++) { int w = *p2; if (GRAPH_IS_EDGE(g, v, w)) { *p1 = w; p1++; } } /* Avoid unneccessary loops (next size == p1-newtable) */ if (p1-newtable < min_size-1) continue; /* Now p1-newtable >= min_size-1 >= 2-1 == 1, so we can use * p1-newtable-1 safely. */ if (clique_size[newtable[p1-newtable-1]] < min_size-1) continue; if (sub_unweighted_single(newtable,p1-newtable, min_size-1,g)) { /* Clique found. */ SET_ADD_ELEMENT(current_clique,v); temp_list[temp_count++]=newtable; return TRUE; } } temp_list[temp_count++]=newtable; return FALSE; } /* * unweighted_clique_search_all() * * Searches for all cliques with size at least min_size and at most * max_size. Stores the cliques as opts declares. * * table - the order of the vertices in g to search * start - first index where the subgraph table[0], ..., table[start] * might include a requested kind of clique * min_size - minimum size of clique to search for. min_size > 0 ! * max_size - maximum size of clique to search for. If no upper limit * is desired, use eg. INT_MAX * maximal - requires cliques to be maximal * g - the graph * opts - time printing and clique storage options * * Cliques found are stored as defined by opts->user_function and * opts->clique_list. opts->time_function is called after each * base-level recursion, if non-NULL. * * clique_size[] must be defined and correct for all values of * table[0], ..., table[start-1]. * * Returns the number of cliques stored (not neccessarily number of cliques * in graph, if user/time_function aborts). */ static int unweighted_clique_search_all(int *table, int start, int min_size, int max_size, boolean maximal, graph_t *g, clique_options *opts) { /* struct timeval timeval; struct tms tms; */ int i,j; int v; int *newtable; int newsize; int count=0; if (temp_count) { temp_count--; newtable=temp_list[temp_count]; } else { newtable=malloc(g->n * sizeof(int)); } clique_list_count=0; set_empty(current_clique); for (i=start; i < g->n; i++) { v=table[i]; clique_size[v]=min_size; /* Do not prune here. */ newsize=0; for (j=0; jtime_function) { gettimeofday(&timeval,NULL); times(&tms); if (!opts->time_function(entrance_level, i+1,g->n,min_size * weight_multiplier, (double)(tms.tms_utime- cputimer.tms_utime)/ clocks_per_sec, timeval.tv_sec- realtimer.tv_sec+ (double)(timeval.tv_usec- realtimer.tv_usec)/ 1000000,opts)) { /* Abort. */ break; } } #endif } temp_list[temp_count++]=newtable; return count; } /* * sub_unweighted_all() * * Recursion function for searching for all cliques of given size. * * table - subset of vertices of graph g * size - size of table * min_size - minimum size of cliques to search for (decreased with * every recursion) * max_size - maximum size of cliques to search for (decreased with * every recursion). If no upper limit is desired, use * eg. INT_MAX * maximal - require cliques to be maximal (passed through) * g - the graph * opts - storage options * * All cliques of suitable size found are stored according to opts. * * Returns the number of cliques found. If user_function returns FALSE, * then the number of cliques is returned negative. * * Uses current_clique to store the currently-being-searched clique. * clique_size[] for all values in table must be defined and correct, * otherwise inaccurate results may occur. */ static int sub_unweighted_all(int *table, int size, int min_size, int max_size, boolean maximal, graph_t *g, clique_options *opts) { int i; int v; int n; int *newtable; int *p1, *p2; int count=0; /* Amount of cliques found */ if (min_size <= 0) { if ((!maximal) || is_maximal(current_clique,g)) { /* We've found one. Store it. */ count++; if (!store_clique(current_clique,g,opts)) { return -count; } } if (max_size <= 0) { /* If we add another element, size will be too big. */ return count; } } if (size < min_size) { return count; } /* Dynamic memory allocation with cache */ if (temp_count) { temp_count--; newtable=temp_list[temp_count]; } else { newtable=malloc(g->n * sizeof(int)); } for (i=size-1; i>=0; i--) { v = table[i]; if (clique_size[v] < min_size) { break; } if (i+1 < min_size) { break; } /* Very ugly code, but works faster than "for (i=...)" */ p1 = newtable; for (p2=table; p2 < table+i; p2++) { int w = *p2; if (GRAPH_IS_EDGE(g, v, w)) { *p1 = w; p1++; } } /* Avoid unneccessary loops (next size == p1-newtable) */ if (p1-newtable < min_size-1) { continue; } SET_ADD_ELEMENT(current_clique,v); n=sub_unweighted_all(newtable,p1-newtable, min_size-1,max_size-1,maximal,g,opts); SET_DEL_ELEMENT(current_clique,v); if (n < 0) { /* Abort. */ count -= n; count = -count; break; } count+=n; } temp_list[temp_count++]=newtable; return count; } /***** Weighted clique searches *****/ /* * Weighted clique searches can use the same recursive routine, because * in both cases (single/all) they have to search through all potential * permutations searching for heavier cliques. */ /* * weighted_clique_search_single() * * Searches for a single clique of weight at least min_weight, and at * most max_weight. Stores maximum clique sizes into clique_size[] * (or min_weight-1, whichever is smaller). * * table - the order of the vertices in g to use * min_weight - minimum weight of clique to search for. If min_weight==0, * then searches for a maximum weight clique * max_weight - maximum weight of clique to search for. If no upper limit * is desired, use eg. INT_MAX * g - the graph * opts - time printing options * * opts->time_function is called after each base-level recursion, if * non-NULL. * * Returns 0 if a clique of requested weight was not found (also if * time_function requested an abort), otherwise returns >= 1. * If min_weight==0 (search for maximum-weight clique), then the return * value is the weight of the clique found. The found clique is stored * in best_clique. * * Note: Does NOT use opts->user_function of opts->clique_list. */ static int weighted_clique_search_single(int *table, int min_weight, int max_weight, graph_t *g, clique_options *opts) { /* struct timeval timeval; struct tms tms; */ int i,j; int v; int *newtable; int newsize; int newweight; int search_weight; int min_w; clique_options localopts; if (min_weight==0) min_w=INT_MAX; else min_w=min_weight; if (min_weight==1) { /* min_weight==1 may cause trouble in the routine, and * it's trivial to check as it's own case. * We write nothing to clique_size[]. */ for (i=0; i < g->n; i++) { if (g->weights[table[i]] <= max_weight) { set_empty(best_clique); SET_ADD_ELEMENT(best_clique,table[i]); return g->weights[table[i]]; } } return 0; } localopts.time_function=NULL; localopts.reorder_function=NULL; localopts.reorder_map=NULL; localopts.user_function=false_function; localopts.user_data=NULL; localopts.clique_list=&best_clique; localopts.clique_list_length=1; clique_list_count=0; v=table[0]; set_empty(best_clique); SET_ADD_ELEMENT(best_clique,v); search_weight=g->weights[v]; if (min_weight && (search_weight >= min_weight)) { if (search_weight <= max_weight) { /* Found suitable clique. */ return search_weight; } search_weight=min_weight-1; } clique_size[v]=search_weight; set_empty(current_clique); if (temp_count) { temp_count--; newtable=temp_list[temp_count]; } else { newtable=malloc(g->n * sizeof(int)); } for (i = 1; i < g->n; i++) { v=table[i]; newsize=0; newweight=0; for (j=0; jweights[table[j]]; newtable[newsize]=table[j]; newsize++; } } SET_ADD_ELEMENT(current_clique,v); search_weight=sub_weighted_all(newtable,newsize,newweight, g->weights[v],search_weight, clique_size[table[i-1]] + g->weights[v], min_w,max_weight,FALSE, g,&localopts); SET_DEL_ELEMENT(current_clique,v); if (search_weight < 0) { break; } clique_size[v]=search_weight; /* if (opts->time_function) { gettimeofday(&timeval,NULL); times(&tms); if (!opts->time_function(entrance_level, i+1,g->n,clique_size[v] * weight_multiplier, (double)(tms.tms_utime- cputimer.tms_utime)/ clocks_per_sec, timeval.tv_sec- realtimer.tv_sec+ (double)(timeval.tv_usec- realtimer.tv_usec)/ 1000000,opts)) { set_free(current_clique); current_clique=NULL; break; } } */ } temp_list[temp_count++]=newtable; if (min_weight && (search_weight > 0)) { /* Requested clique has not been found. */ return 0; } return clique_size[table[i-1]]; } /* * weighted_clique_search_all() * * Searches for all cliques with weight at least min_weight and at most * max_weight. Stores the cliques as opts declares. * * table - the order of the vertices in g to search * start - first index where the subgraph table[0], ..., table[start] * might include a requested kind of clique * min_weight - minimum weight of clique to search for. min_weight > 0 ! * max_weight - maximum weight of clique to search for. If no upper limit * is desired, use eg. INT_MAX * maximal - search only for maximal cliques * g - the graph * opts - time printing and clique storage options * * Cliques found are stored as defined by opts->user_function and * opts->clique_list. opts->time_function is called after each * base-level recursion, if non-NULL. * * clique_size[] must be defined and correct for all values of * table[0], ..., table[start-1]. * * Returns the number of cliques stored (not neccessarily number of cliques * in graph, if user/time_function aborts). */ static int weighted_clique_search_all(int *table, int start, int min_weight, int max_weight, boolean maximal, graph_t *g, clique_options *opts) { /* struct timeval timeval; struct tms tms; */ int i,j; int v; int *newtable; int newsize; int newweight; if (temp_count) { temp_count--; newtable=temp_list[temp_count]; } else { newtable=malloc(g->n * sizeof(int)); } clique_list_count=0; set_empty(current_clique); for (i=start; i < g->n; i++) { v=table[i]; clique_size[v]=min_weight; /* Do not prune here. */ newsize=0; newweight=0; for (j=0; jweights[table[j]]; newsize++; } } SET_ADD_ELEMENT(current_clique,v); j=sub_weighted_all(newtable,newsize,newweight, g->weights[v],min_weight-1,INT_MAX, min_weight,max_weight,maximal,g,opts); SET_DEL_ELEMENT(current_clique,v); if (j<0) { /* Abort. */ break; } /* if (opts->time_function) { gettimeofday(&timeval,NULL); times(&tms); if (!opts->time_function(entrance_level, i+1,g->n,clique_size[v] * weight_multiplier, (double)(tms.tms_utime- cputimer.tms_utime)/ clocks_per_sec, timeval.tv_sec- realtimer.tv_sec+ (double)(timeval.tv_usec- realtimer.tv_usec)/ 1000000,opts)) { set_free(current_clique); current_clique=NULL; break; } } */ } temp_list[temp_count++]=newtable; return clique_list_count; } /* * sub_weighted_all() * * Recursion function for searching for all cliques of given weight. * * table - subset of vertices of graph g * size - size of table * weight - total weight of vertices in table * current_weight - weight of clique found so far * prune_low - ignore all cliques with weight less or equal to this value * (often heaviest clique found so far) (passed through) * prune_high - maximum weight possible for clique in this subgraph * (passed through) * min_size - minimum weight of cliques to search for (passed through) * Must be greater than 0. * max_size - maximum weight of cliques to search for (passed through) * If no upper limit is desired, use eg. INT_MAX * maximal - search only for maximal cliques * g - the graph * opts - storage options * * All cliques of suitable weight found are stored according to opts. * * Returns weight of heaviest clique found (prune_low if a heavier clique * hasn't been found); if a clique with weight at least min_size is found * then min_size-1 is returned. If clique storage failed, -1 is returned. * * The largest clique found smaller than max_weight is stored in * best_clique, if non-NULL. * * Uses current_clique to store the currently-being-searched clique. * clique_size[] for all values in table must be defined and correct, * otherwise inaccurate results may occur. * * To search for a single maximum clique, use min_weight==max_weight==INT_MAX, * with best_clique non-NULL. To search for a single given-weight clique, * use opts->clique_list and opts->user_function=false_function. When * searching for all cliques, min_weight should be given the minimum weight * desired. */ static int sub_weighted_all(int *table, int size, int weight, int current_weight, int prune_low, int prune_high, int min_weight, int max_weight, boolean maximal, graph_t *g, clique_options *opts) { int i; int v,w; int *newtable; int *p1, *p2; int newweight; if (current_weight >= min_weight) { if ((current_weight <= max_weight) && ((!maximal) || is_maximal(current_clique,g))) { /* We've found one. Store it. */ if (!store_clique(current_clique,g,opts)) { return -1; } } if (current_weight >= max_weight) { /* Clique too heavy. */ return min_weight-1; } } if (size <= 0) { /* current_weight < min_weight, prune_low < min_weight, * so return value is always < min_weight. */ if (current_weight>prune_low) { if (best_clique) { best_clique = set_copy(best_clique,current_clique); } if (current_weight < min_weight) return current_weight; else return min_weight-1; } else { return prune_low; } } /* Dynamic memory allocation with cache */ if (temp_count) { temp_count--; newtable=temp_list[temp_count]; } else { newtable=malloc(g->n * sizeof(int)); } for (i = size-1; i >= 0; i--) { v = table[i]; if (current_weight+clique_size[v] <= prune_low) { /* Dealing with subset without heavy enough clique. */ break; } if (current_weight+weight <= prune_low) { /* Even if all elements are added, won't do. */ break; } /* Very ugly code, but works faster than "for (i=...)" */ p1 = newtable; newweight = 0; for (p2=table; p2 < table+i; p2++) { w = *p2; if (GRAPH_IS_EDGE(g, v, w)) { *p1 = w; newweight += g->weights[w]; p1++; } } w=g->weights[v]; weight-=w; /* Avoid a few unneccessary loops */ if (current_weight+w+newweight <= prune_low) { continue; } SET_ADD_ELEMENT(current_clique,v); prune_low=sub_weighted_all(newtable,p1-newtable, newweight, current_weight+w, prune_low,prune_high, min_weight,max_weight,maximal, g,opts); SET_DEL_ELEMENT(current_clique,v); if ((prune_low<0) || (prune_low>=prune_high)) { /* Impossible to find larger clique. */ break; } } temp_list[temp_count++]=newtable; return prune_low; } /***** Helper functions *****/ /* * store_clique() * * Stores a clique according to given user options. * * clique - the clique to store * opts - storage options * * Returns FALSE if opts->user_function() returned FALSE; otherwise * returns TRUE. */ static boolean store_clique(set_t clique, graph_t *g, clique_options *opts) { clique_list_count++; /* clique_list[] */ if (opts->clique_list) { /* * This has been a major source of bugs: * Has clique_list_count been set to 0 before calling * the recursions? */ if (clique_list_count <= 0) { #ifdef USING_R error("CLIQUER INTERNAL ERROR: ", "clique_list_count has negative value!"); #else fprintf(stderr,"CLIQUER INTERNAL ERROR: " "clique_list_count has negative value!\n"); fprintf(stderr,"Please report as a bug.\n"); abort(); #endif } if (clique_list_count <= opts->clique_list_length) opts->clique_list[clique_list_count-1] = set_copy(opts->clique_list[clique_list_count-1], clique); } /* user_function() */ if (opts->user_function) { if (!opts->user_function(clique,g,opts)) { /* User function requested abort. */ return FALSE; } } return TRUE; } /* * maximalize_clique() * * Adds greedily all possible vertices in g to set s to make it a maximal * clique. * * s - clique of vertices to make maximal * g - graph * * Note: Not very optimized (uses a simple O(n^2) routine), but is called * at maximum once per clique_xxx() call, so it shouldn't matter. */ static void maximalize_clique(set_t s,graph_t *g) { int i,j; boolean add; for (i=0; i < g->n; i++) { add=TRUE; for (j=0; j < g->n; j++) { if (SET_CONTAINS_FAST(s,j) && !GRAPH_IS_EDGE(g,i,j)) { add=FALSE; break; } } if (add) { SET_ADD_ELEMENT(s,i); } } return; } /* * is_maximal() * * Check whether a clique is maximal or not. * * clique - set of vertices in clique * g - graph * * Returns TRUE is clique is a maximal clique of g, otherwise FALSE. */ static boolean is_maximal(set_t clique, graph_t *g) { int i,j; int *table; int len; boolean addable; if (temp_count) { temp_count--; table=temp_list[temp_count]; } else { table=malloc(g->n * sizeof(int)); } len=0; for (i=0; i < g->n; i++) if (SET_CONTAINS_FAST(clique,i)) table[len++]=i; for (i=0; i < g->n; i++) { addable=TRUE; for (j=0; jtime_function() requests abort). * * The returned clique is newly allocated and can be freed by set_free(). * * Note: Does NOT use opts->user_function() or opts->clique_list[]. */ set_t clique_unweighted_find_single(graph_t *g,int min_size,int max_size, boolean maximal, clique_options *opts) { int i; int *table; set_t s; ENTRANCE_SAVE(); entrance_level++; if (opts==NULL) opts=&clique_default_options; ASSERT((sizeof(setelement)*8)==ELEMENTSIZE); ASSERT(g!=NULL); ASSERT(min_size>=0); ASSERT(max_size>=0); ASSERT((max_size==0) || (min_size <= max_size)); ASSERT(!((min_size==0) && (max_size>0))); ASSERT((opts->reorder_function==NULL) || (opts->reorder_map==NULL)); if ((max_size>0) && (min_size>max_size)) { /* state was not changed */ entrance_level--; return NULL; } /* if (clocks_per_sec==0) clocks_per_sec=sysconf(_SC_CLK_TCK); ASSERT(clocks_per_sec>0); */ /* Dynamic allocation */ current_clique=set_new(g->n); clique_size=malloc(g->n * sizeof(int)); /* table allocated later */ temp_list=malloc((g->n+2)*sizeof(int *)); temp_count=0; /* "start clock" */ /* gettimeofday(&realtimer,NULL); times(&cputimer); */ /* reorder */ if (opts->reorder_function) { table=opts->reorder_function(g,FALSE); } else if (opts->reorder_map) { table=reorder_duplicate(opts->reorder_map,g->n); } else { table=reorder_ident(g->n); } ASSERT(reorder_is_bijection(table,g->n)); if (unweighted_clique_search_single(table,min_size,g,opts)==0) { set_free(current_clique); current_clique=NULL; goto cleanreturn; } if (maximal && (min_size>0)) { maximalize_clique(current_clique,g); if ((max_size > 0) && (set_size(current_clique) > max_size)) { clique_options localopts; s = set_new(g->n); localopts.time_function = opts->time_function; localopts.output = opts->output; localopts.user_function = false_function; localopts.clique_list = &s; localopts.clique_list_length = 1; for (i=0; i < g->n-1; i++) if (clique_size[table[i]]>=min_size) break; if (unweighted_clique_search_all(table,i,min_size, max_size,maximal, g,&localopts)) { set_free(current_clique); current_clique=s; } else { set_free(current_clique); current_clique=NULL; } } } cleanreturn: s=current_clique; /* Free resources */ for (i=0; i < temp_count; i++) free(temp_list[i]); free(temp_list); free(table); free(clique_size); ENTRANCE_RESTORE(); entrance_level--; return s; } /* * clique_unweighted_find_all() * * Find all cliques with size at least min_size and at most max_size. * * g - the graph * min_size - minimum size of cliques to search for. If min_size==0, * searches for maximum cliques. * max_size - maximum size of cliques to search for. If max_size==0, no * upper limit is used. If min_size==0, this must also be 0. * maximal - require cliques to be maximal cliques * opts - time printing and clique storage options * * Returns the number of cliques found. This can be less than the number * of cliques in the graph iff opts->time_function() or opts->user_function() * returns FALSE (request abort). * * The cliques found are stored in opts->clique_list[] and * opts->user_function() is called with them (if non-NULL). The cliques * stored in opts->clique_list[] are newly allocated, and can be freed * by set_free(). */ int clique_unweighted_find_all(graph_t *g, int min_size, int max_size, boolean maximal, clique_options *opts) { int i; int *table; int count; ENTRANCE_SAVE(); entrance_level++; if (opts==NULL) opts=&clique_default_options; ASSERT((sizeof(setelement)*8)==ELEMENTSIZE); ASSERT(g!=NULL); ASSERT(min_size>=0); ASSERT(max_size>=0); ASSERT((max_size==0) || (min_size <= max_size)); ASSERT(!((min_size==0) && (max_size>0))); ASSERT((opts->reorder_function==NULL) || (opts->reorder_map==NULL)); if ((max_size>0) && (min_size>max_size)) { /* state was not changed */ entrance_level--; return 0; } /* if (clocks_per_sec==0) clocks_per_sec=sysconf(_SC_CLK_TCK); ASSERT(clocks_per_sec>0); */ /* Dynamic allocation */ current_clique=set_new(g->n); clique_size=malloc(g->n * sizeof(int)); /* table allocated later */ temp_list=malloc((g->n+2)*sizeof(int *)); temp_count=0; clique_list_count=0; memset(clique_size,0,g->n * sizeof(int)); /* "start clock" */ /* gettimeofday(&realtimer,NULL); times(&cputimer); */ /* reorder */ if (opts->reorder_function) { table=opts->reorder_function(g,FALSE); } else if (opts->reorder_map) { table=reorder_duplicate(opts->reorder_map,g->n); } else { table=reorder_ident(g->n); } ASSERT(reorder_is_bijection(table,g->n)); /* Search as normal until there is a chance to find a suitable * clique. */ if (unweighted_clique_search_single(table,min_size,g,opts)==0) { count=0; goto cleanreturn; } if (min_size==0 && max_size==0) { min_size=max_size=clique_size[table[g->n-1]]; maximal=FALSE; /* No need to test, since we're searching * for maximum cliques. */ } if (max_size==0) { max_size=INT_MAX; } for (i=0; i < g->n-1; i++) if (clique_size[table[i]] >= min_size) break; count=unweighted_clique_search_all(table,i,min_size,max_size, maximal,g,opts); cleanreturn: /* Free resources */ for (i=0; itime_function() requests abort). * * The returned clique is newly allocated and can be freed by set_free(). * * Note: Does NOT use opts->user_function() or opts->clique_list[]. * Note: Automatically uses clique_unweighted_find_single if all vertex * weights are the same. */ set_t clique_find_single(graph_t *g,int min_weight,int max_weight, boolean maximal, clique_options *opts) { int i; int *table; set_t s; ENTRANCE_SAVE(); entrance_level++; if (opts==NULL) opts=&clique_default_options; ASSERT((sizeof(setelement)*8)==ELEMENTSIZE); ASSERT(g!=NULL); ASSERT(min_weight>=0); ASSERT(max_weight>=0); ASSERT((max_weight==0) || (min_weight <= max_weight)); ASSERT(!((min_weight==0) && (max_weight>0))); ASSERT((opts->reorder_function==NULL) || (opts->reorder_map==NULL)); if ((max_weight>0) && (min_weight>max_weight)) { /* state was not changed */ entrance_level--; return NULL; } /* if (clocks_per_sec==0) clocks_per_sec=sysconf(_SC_CLK_TCK); ASSERT(clocks_per_sec>0); */ /* Check whether we can use unweighted routines. */ if (!graph_weighted(g)) { min_weight=DIV_UP(min_weight,g->weights[0]); if (max_weight) { max_weight=DIV_DOWN(max_weight,g->weights[0]); if (max_weight < min_weight) { /* state was not changed */ entrance_level--; return NULL; } } weight_multiplier = g->weights[0]; entrance_level--; s=clique_unweighted_find_single(g,min_weight,max_weight, maximal,opts); ENTRANCE_RESTORE(); return s; } /* Dynamic allocation */ current_clique=set_new(g->n); best_clique=set_new(g->n); clique_size=malloc(g->n * sizeof(int)); memset(clique_size, 0, g->n * sizeof(int)); /* table allocated later */ temp_list=malloc((g->n+2)*sizeof(int *)); temp_count=0; clique_list_count=0; /* "start clock" */ /* gettimeofday(&realtimer,NULL); times(&cputimer); */ /* reorder */ if (opts->reorder_function) { table=opts->reorder_function(g,TRUE); } else if (opts->reorder_map) { table=reorder_duplicate(opts->reorder_map,g->n); } else { table=reorder_ident(g->n); } ASSERT(reorder_is_bijection(table,g->n)); if (max_weight==0) max_weight=INT_MAX; if (weighted_clique_search_single(table,min_weight,max_weight, g,opts)==0) { /* Requested clique has not been found. */ set_free(best_clique); best_clique=NULL; goto cleanreturn; } if (maximal && (min_weight>0)) { maximalize_clique(best_clique,g); if (graph_subgraph_weight(g,best_clique) > max_weight) { clique_options localopts; localopts.time_function = opts->time_function; localopts.output = opts->output; localopts.user_function = false_function; localopts.clique_list = &best_clique; localopts.clique_list_length = 1; for (i=0; i < g->n-1; i++) if ((clique_size[table[i]] >= min_weight) || (clique_size[table[i]] == 0)) break; if (!weighted_clique_search_all(table,i,min_weight, max_weight,maximal, g,&localopts)) { set_free(best_clique); best_clique=NULL; } } } cleanreturn: s=best_clique; /* Free resources */ for (i=0; i < temp_count; i++) free(temp_list[i]); free(temp_list); temp_list=NULL; temp_count=0; free(table); set_free(current_clique); current_clique=NULL; free(clique_size); clique_size=NULL; ENTRANCE_RESTORE(); entrance_level--; return s; } /* * clique_find_all() * * Find all cliques with weight at least min_weight and at most max_weight. * * g - the graph * min_weight - minimum weight of cliques to search for. If min_weight==0, * searches for maximum weight cliques. * max_weight - maximum weight of cliques to search for. If max_weight==0, * no upper limit is used. If min_weight==0, max_weight must * also be 0. * maximal - require cliques to be maximal cliques * opts - time printing and clique storage options * * Returns the number of cliques found. This can be less than the number * of cliques in the graph iff opts->time_function() or opts->user_function() * returns FALSE (request abort). * * The cliques found are stored in opts->clique_list[] and * opts->user_function() is called with them (if non-NULL). The cliques * stored in opts->clique_list[] are newly allocated, and can be freed * by set_free(). * * Note: Automatically uses clique_unweighted_find_all if all vertex * weights are the same. */ int clique_find_all(graph_t *g, int min_weight, int max_weight, boolean maximal, clique_options *opts) { int i,n; int *table; ENTRANCE_SAVE(); entrance_level++; if (opts==NULL) opts=&clique_default_options; ASSERT((sizeof(setelement)*8)==ELEMENTSIZE); ASSERT(g!=NULL); ASSERT(min_weight>=0); ASSERT(max_weight>=0); ASSERT((max_weight==0) || (min_weight <= max_weight)); ASSERT(!((min_weight==0) && (max_weight>0))); ASSERT((opts->reorder_function==NULL) || (opts->reorder_map==NULL)); if ((max_weight>0) && (min_weight>max_weight)) { /* state was not changed */ entrance_level--; return 0; } /* if (clocks_per_sec==0) clocks_per_sec=sysconf(_SC_CLK_TCK); ASSERT(clocks_per_sec>0); */ if (!graph_weighted(g)) { min_weight=DIV_UP(min_weight,g->weights[0]); if (max_weight) { max_weight=DIV_DOWN(max_weight,g->weights[0]); if (max_weight < min_weight) { /* state was not changed */ entrance_level--; return 0; } } weight_multiplier = g->weights[0]; entrance_level--; i=clique_unweighted_find_all(g,min_weight,max_weight,maximal, opts); ENTRANCE_RESTORE(); return i; } /* Dynamic allocation */ current_clique=set_new(g->n); best_clique=set_new(g->n); clique_size=malloc(g->n * sizeof(int)); memset(clique_size, 0, g->n * sizeof(int)); /* table allocated later */ temp_list=malloc((g->n+2)*sizeof(int *)); temp_count=0; /* "start clock" */ /* gettimeofday(&realtimer,NULL); times(&cputimer); */ /* reorder */ if (opts->reorder_function) { table=opts->reorder_function(g,TRUE); } else if (opts->reorder_map) { table=reorder_duplicate(opts->reorder_map,g->n); } else { table=reorder_ident(g->n); } ASSERT(reorder_is_bijection(table,g->n)); /* First phase */ n=weighted_clique_search_single(table,min_weight,INT_MAX,g,opts); if (n==0) { /* Requested clique has not been found. */ goto cleanreturn; } if (min_weight==0) { min_weight=n; max_weight=n; maximal=FALSE; /* They're maximum cliques already. */ } if (max_weight==0) max_weight=INT_MAX; for (i=0; i < g->n; i++) if ((clique_size[table[i]] >= min_weight) || (clique_size[table[i]] == 0)) break; /* Second phase */ n=weighted_clique_search_all(table,i,min_weight,max_weight,maximal, g,opts); cleanreturn: /* Free resources */ for (i=0; i < temp_count; i++) free(temp_list[i]); free(temp_list); free(table); set_free(current_clique); set_free(best_clique); free(clique_size); ENTRANCE_RESTORE(); entrance_level--; return n; } #if 0 /* * clique_print_time() * * Reports current running information every 0.1 seconds or when values * change. * * level - re-entrance level * i - current recursion level * n - maximum recursion level * max - weight of heaviest clique found * cputime - CPU time used in algorithm so far * realtime - real time used in algorithm so far * opts - prints information to (FILE *)opts->output (or stdout if NULL) * * Returns always TRUE (ie. never requests abort). */ boolean clique_print_time(int level, int i, int n, int max, double cputime, double realtime, clique_options *opts) { static float prev_time=100; static int prev_i=100; static int prev_max=100; static int prev_level=0; FILE *fp=opts->output; int j; if (fp==NULL) fp=stdout; if (ABS(prev_time-realtime)>0.1 || i==n || ioutput (or stdout if NULL) * * Returns always TRUE (ie. never requests abort). */ boolean clique_print_time_always(int level, int i, int n, int max, double cputime, double realtime, clique_options *opts) { static float prev_time=100; static int prev_i=100; FILE *fp=opts->output; int j; if (fp==NULL) fp=stdout; for (j=1; j #include #ifndef ASSERT #ifdef USING_R #include #define ASSERT(expr) \ if (!(expr)) { \ error("cliquer file %s: line %d: assertion failed: " \ "(%s)\n",__FILE__,__LINE__,#expr); \ } #else #define ASSERT(expr) \ if (!(expr)) { \ fprintf(stderr,"cliquer file %s: line %d: assertion failed: " \ "(%s)\n",__FILE__,__LINE__,#expr); \ abort(); \ } #endif #endif /* !ASSERT */ #ifndef FALSE #define FALSE (0) #endif #ifndef TRUE #define TRUE (!FALSE) #endif #ifndef MIN #define MIN(a,b) (((a)<(b))?(a):(b)) #endif #ifndef MAX #define MAX(a,b) (((a)>(b))?(a):(b)) #endif #ifndef ABS #define ABS(v) (((v)<0)?(-(v)):(v)) #endif #endif /* !CLIQUER_MISC_H */ python-igraph-0.8.0/vendor/source/igraph/src/cliquer/graph.h0000644000076500000240000000376213524616144024332 0ustar tamasstaff00000000000000 #ifndef CLIQUER_GRAPH_H #define CLIQUER_GRAPH_H #include "set.h" typedef struct _graph_t graph_t; struct _graph_t { int n; /* Vertices numbered 0...n-1 */ set_t *edges; /* A list of n sets (the edges). */ int *weights; /* A list of n vertex weights. */ }; #define GRAPH_IS_EDGE_FAST(g,i,j) (SET_CONTAINS_FAST((g)->edges[(i)],(j))) #define GRAPH_IS_EDGE(g,i,j) (((i)<((g)->n))?SET_CONTAINS((g)->edges[(i)], \ (j)):FALSE) #define GRAPH_ADD_EDGE(g,i,j) do { \ SET_ADD_ELEMENT((g)->edges[(i)],(j)); \ SET_ADD_ELEMENT((g)->edges[(j)],(i)); \ } while (FALSE) #define GRAPH_DEL_EDGE(g,i,j) do { \ SET_DEL_ELEMENT((g)->edges[(i)],(j)); \ SET_DEL_ELEMENT((g)->edges[(j)],(i)); \ } while (FALSE) extern graph_t *graph_new(int n); extern void graph_free(graph_t *g); extern void graph_resize(graph_t *g, int size); extern void graph_crop(graph_t *g); extern boolean graph_weighted(graph_t *g); extern int graph_edge_count(graph_t *g); /* extern graph_t *graph_read_dimacs(FILE *fp); extern graph_t *graph_read_dimacs_file(char *file); extern boolean graph_write_dimacs_ascii(graph_t *g, char *comment,FILE *fp); extern boolean graph_write_dimacs_ascii_file(graph_t *g,char *comment, char *file); extern boolean graph_write_dimacs_binary(graph_t *g, char *comment,FILE *fp); extern boolean graph_write_dimacs_binary_file(graph_t *g, char *comment, char *file); */ extern void graph_print(graph_t *g); extern boolean graph_test(graph_t *g, FILE *output); extern int graph_test_regular(graph_t *g); UNUSED_FUNCTION INLINE static int graph_subgraph_weight(graph_t *g,set_t s) { int i,j; int count=0; setelement e; for (i=0; iweights[i*ELEMENTSIZE+j]; e = e>>1; } } } return count; } UNUSED_FUNCTION INLINE static int graph_vertex_degree(graph_t *g, int v) { return set_size(g->edges[v]); } #endif /* !CLIQUER_GRAPH_H */ python-igraph-0.8.0/vendor/source/igraph/src/cliquer/reorder.h0000644000076500000240000000172413524616144024667 0ustar tamasstaff00000000000000 #ifndef CLIQUER_REORDER_H #define CLIQUER_REORDER_H #include "set.h" #include "graph.h" extern void reorder_set(set_t s,int *order); extern void reorder_graph(graph_t *g, int *order); extern int *reorder_duplicate(int *order,int n); extern void reorder_invert(int *order,int n); extern void reorder_reverse(int *order,int n); extern int *reorder_ident(int n); extern boolean reorder_is_bijection(int *order,int n); #define reorder_by_default reorder_by_greedy_coloring extern int *reorder_by_greedy_coloring(graph_t *g, boolean weighted); extern int *reorder_by_weighted_greedy_coloring(graph_t *g, boolean weighted); extern int *reorder_by_unweighted_greedy_coloring(graph_t *g,boolean weighted); extern int *reorder_by_degree(graph_t *g, boolean weighted); extern int *reorder_by_random(graph_t *g, boolean weighted); extern int *reorder_by_ident(graph_t *g, boolean weighted); extern int *reorder_by_reverse(graph_t *g, boolean weighted); #endif /* !CLIQUER_REORDER_H */ python-igraph-0.8.0/vendor/source/igraph/src/cliquer/README0000644000076500000240000000377613524616144023745 0ustar tamasstaff00000000000000 Cliquer - routines for clique searching --------------------------------------- Cliquer is a set of C routines for finding cliques in an arbitrary weighted graph. It uses an exact branch-and-bound algorithm recently developed by Patric Ostergard. It is designed with the aim of being efficient while still being flexible and easy to use. Cliquer was developed on Linux, and it should compile without modification on most modern UNIX systems. Other operating systems may require minor changes to the source code. Features: * support for both weighted and unweighted graphs (faster routines for unweighted graphs) * search for maximum clique / maximum-weight clique * search for clique with size / weight within a given range * restrict search to maximal cliques * store found cliques in memory * call a user-defined function for every clique found * Cliquer is re-entrant, so you can use the clique-searching functions from within the callback function The full documentation can be obtained via the www page of Cliquer . License Cliquer is Copyright (C) 2002 Sampo Niskanen, Patric Ostergard. Cliquer is licensed under the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. The full license is included in the file LICENSE. Basically, you can use Cliquer for any purpose, provided that any programs or modifications you make and distribute are also licensed under the GNU GPL. ABSOLUTELY NO GUARANTEES OR WARRANTIES are made concerning the suitability, correctness, or any other aspect of these routines. Contact Cliquer was mainly written by Sampo Niskanen . For bug-fixes, feedback, and, in particular, for putting your name on the mailing list for important information regarding Cliquer, please contact: Patric Ostergard Department of Communications and Networking Aalto University P.O. Box 13000, 00076 Aalto FINLAND python-igraph-0.8.0/vendor/source/igraph/src/cliquer/cliquer.h0000644000076500000240000000340713524616144024671 0ustar tamasstaff00000000000000 #ifndef CLIQUER_H #define CLIQUER_H #include #include "set.h" #include "graph.h" #include "reorder.h" typedef struct _clique_options clique_options; struct _clique_options { int *(*reorder_function)(graph_t *, boolean); int *reorder_map; /* arguments: level, n, max, user_time, system_time, opts */ boolean (*time_function)(int,int,int,int,double,double, clique_options *); FILE *output; boolean (*user_function)(set_t,graph_t *,clique_options *); void *user_data; set_t *clique_list; int clique_list_length; }; /* Weighted clique functions */ extern int clique_max_weight(graph_t *g,clique_options *opts); extern set_t clique_find_single(graph_t *g,int min_weight,int max_weight, boolean maximal, clique_options *opts); extern int clique_find_all(graph_t *g, int req_weight, boolean exact, boolean maximal, clique_options *opts); /* Unweighted clique functions */ #define clique_unweighted_max_size clique_unweighted_max_weight extern int clique_unweighted_max_weight(graph_t *g, clique_options *opts); extern set_t clique_unweighted_find_single(graph_t *g,int min_size, int max_size,boolean maximal, clique_options *opts); extern int clique_unweighted_find_all(graph_t *g, int min_size, int max_size, boolean maximal, clique_options *opts); /* Time printing functions */ /* extern boolean clique_print_time(int level, int i, int n, int max, double cputime, double realtime, clique_options *opts); extern boolean clique_print_time_always(int level, int i, int n, int max, double cputime, double realtime, clique_options *opts); */ /* Alternate spelling (let's be a little forgiving): */ #define cliquer_options clique_options #define cliquer_default_options clique_default_options #endif /* !CLIQUER_H */ python-igraph-0.8.0/vendor/source/igraph/src/cliquer/cliquerconf.h0000644000076500000240000000361213524616144025535 0ustar tamasstaff00000000000000 #ifndef CLIQUERCONF_H #define CLIQUERCONF_H /* * setelement is the basic memory type used in sets. It is often fastest * to be as large as can fit into the CPU registers. * * ELEMENTSIZE is the size of one setelement, measured in bits. It must * be either 16, 32 or 64 (otherwise additional changes must be made to * the source). * * The default is to use "unsigned long int" and attempt to guess the * size using , which should work pretty well. Check functioning * with "make test". */ /* typedef unsigned long int setelement; */ /* #define ELEMENTSIZE 64 */ /* * INLINE is a command prepended to function declarations to instruct the * compiler to inline the function. If inlining is not desired, define blank. * * The default is to use "inline", which is recognized by most compilers. */ /* #define INLINE */ /* #define INLINE __inline__ */ #if __STDC_VERSION__ >= 199901L #define INLINE inline #else #if defined(_MSC_VER) #define INLINE __inline #elif defined(__GNUC__) #define INLINE __inline__ #else #define INLINE #endif #endif /* * Set handling functions are defined as static functions in set.h for * performance reasons. This may cause unnecessary warnings from the * compiler. Some compilers (such as GCC) have the possibility to turn * off the warnings on a per-function basis using a flag prepended to * the function declaration. * * The default is to use the correct attribute when compiling with GCC, * or no flag otherwise. */ /* #define UNUSED_FUNCTION __attribute__((unused)) */ /* #define UNUSED_FUNCTION */ /* * Uncommenting the following will disable all assertions (checks that * function arguments and other variables are correct). This is highly * discouraged, as it allows bugs to go unnoticed easier. The assertions * are set so that they do not slow down programs notably. */ /* #define ASSERT(x) */ #endif /* !CLIQUERCONF_H */ python-igraph-0.8.0/vendor/source/igraph/src/cliquer/reorder.c0000644000076500000240000002140613524616144024661 0ustar tamasstaff00000000000000 /* * This file contains the vertex reordering routines. * * Copyright (C) 2002 Sampo Niskanen, Patric Östergård. * Licensed under the GNU GPL, read the file LICENSE for details. */ #include "reorder.h" #include #include #include /* * reorder_set() * * Reorders the set s with a function i -> order[i]. * * Note: Assumes that order is the same size as SET_MAX_SIZE(s). */ void reorder_set(set_t s,int *order) { set_t tmp; int i,j; setelement e; ASSERT(reorder_is_bijection(order,SET_MAX_SIZE(s))); tmp=set_new(SET_MAX_SIZE(s)); for (i=0; i<(SET_MAX_SIZE(s)/ELEMENTSIZE); i++) { e=s[i]; if (e==0) continue; for (j=0; j>1; } } if (SET_MAX_SIZE(s)%ELEMENTSIZE) { e=s[i]; for (j=0; j<(SET_MAX_SIZE(s)%ELEMENTSIZE); j++) { if (e&1) { SET_ADD_ELEMENT(tmp,order[i*ELEMENTSIZE+j]); } e = e>>1; } } set_copy(s,tmp); set_free(tmp); return; } /* * reorder_graph() * * Reorders the vertices in the graph with function i -> order[i]. * * Note: Assumes that order is of size g->n. */ void reorder_graph(graph_t *g, int *order) { int i; set_t *tmp_e; int *tmp_w; ASSERT(reorder_is_bijection(order,g->n)); tmp_e=malloc(g->n * sizeof(set_t)); tmp_w=malloc(g->n * sizeof(int)); for (i=0; in; i++) { reorder_set(g->edges[i],order); tmp_e[order[i]]=g->edges[i]; tmp_w[order[i]]=g->weights[i]; } for (i=0; in; i++) { g->edges[i]=tmp_e[i]; g->weights[i]=tmp_w[i]; } free(tmp_e); free(tmp_w); return; } /* * reorder_duplicate() * * Returns a newly allocated duplicate of the given ordering. */ int *reorder_duplicate(int *order,int n) { int *new; new=malloc(n*sizeof(int)); memcpy(new,order,n*sizeof(int)); return new; } /* * reorder_invert() * * Inverts the given ordering so that new[old[i]]==i. * * Note: Asserts that order is a bijection. */ void reorder_invert(int *order,int n) { int *new; int i; ASSERT(reorder_is_bijection(order,n)); new=malloc(n*sizeof(int)); for (i=0; i {0,...,n-1}. * * Returns TRUE if it is a bijection, FALSE otherwise. */ boolean reorder_is_bijection(int *order,int n) { boolean *used; int i; used=calloc(n,sizeof(boolean)); for (i=0; i=n) { free(used); return FALSE; } if (used[order[i]]) { free(used); return FALSE; } used[order[i]]=TRUE; } for (i=0; in); } /* * reorder_by_reverse() * * Returns a reverse identity ordering. */ int *reorder_by_reverse(graph_t *g,boolean weighted) { int i; int *order; order=malloc(g->n * sizeof(int)); for (i=0; i < g->n; i++) order[i]=g->n-i-1; return order; } /* * reorder_by_greedy_coloring() * * Equivalent to reorder_by_weighted_greedy_coloring or * reorder_by_unweighted_greedy_coloring according to the value of weighted. */ int *reorder_by_greedy_coloring(graph_t *g,boolean weighted) { if (weighted) return reorder_by_weighted_greedy_coloring(g,weighted); else return reorder_by_unweighted_greedy_coloring(g,weighted); } /* * reorder_by_unweighted_greedy_coloring() * * Returns an ordering for the graph g by coloring the clique one * color at a time, always adding the vertex of largest degree within * the uncolored graph, and numbering these vertices 0, 1, ... * * Experimentally efficient for use with unweighted graphs. */ int *reorder_by_unweighted_greedy_coloring(graph_t *g,boolean weighted) { int i,j,v; boolean *tmp_used; int *degree; /* -1 for used vertices */ int *order; int maxdegree,maxvertex=0; boolean samecolor; tmp_used=calloc(g->n,sizeof(boolean)); degree=calloc(g->n,sizeof(int)); order=calloc(g->n,sizeof(int)); for (i=0; i < g->n; i++) { for (j=0; j < g->n; j++) { ASSERT(!((i==j) && GRAPH_IS_EDGE(g,i,j))); if (GRAPH_IS_EDGE(g,i,j)) degree[i]++; } } v=0; while (v < g->n) { /* Reset tmp_used. */ memset(tmp_used,0,g->n * sizeof(boolean)); do { /* Find vertex to be colored. */ maxdegree=0; samecolor=FALSE; for (i=0; i < g->n; i++) { if (!tmp_used[i] && degree[i] >= maxdegree) { maxvertex=i; maxdegree=degree[i]; samecolor=TRUE; } } if (samecolor) { order[v]=maxvertex; degree[maxvertex]=-1; v++; /* Mark neighbors not to color with same * color and update neighbor degrees. */ for (i=0; i < g->n; i++) { if (GRAPH_IS_EDGE(g,maxvertex,i)) { tmp_used[i]=TRUE; degree[i]--; } } } } while (samecolor); } free(tmp_used); free(degree); return order; } /* * reorder_by_weighted_greedy_coloring() * * Returns an ordering for the graph g by coloring the clique one * color at a time, always adding the vertex that (in order of importance): * 1. has the minimum weight in the remaining graph * 2. has the largest sum of weights surrounding the vertex * * Experimentally efficient for use with weighted graphs. */ int *reorder_by_weighted_greedy_coloring(graph_t *g, boolean weighted) { int i,j,p=0; int cnt; int *nwt; /* Sum of surrounding vertices' weights */ int min_wt,max_nwt; boolean *used; int *order; nwt=malloc(g->n * sizeof(int)); order=malloc(g->n * sizeof(int)); used=calloc(g->n,sizeof(boolean)); for (i=0; i < g->n; i++) { nwt[i]=0; for (j=0; j < g->n; j++) if (GRAPH_IS_EDGE(g, i, j)) nwt[i] += g->weights[j]; } for (cnt=0; cnt < g->n; cnt++) { min_wt=INT_MAX; max_nwt=-1; for (i=g->n-1; i>=0; i--) if ((!used[i]) && (g->weights[i] < min_wt)) min_wt=g->weights[i]; for (i=g->n-1; i>=0; i--) { if (used[i] || (g->weights[i] > min_wt)) continue; if (nwt[i] > max_nwt) { max_nwt=nwt[i]; p=i; } } order[cnt]=p; used[p]=TRUE; for (j=0; j < g->n; j++) if ((!used[j]) && (GRAPH_IS_EDGE(g, p, j))) nwt[j] -= g->weights[p]; } free(nwt); free(used); ASSERT(reorder_is_bijection(order,g->n)); return order; } /* * reorder_by_degree() * * Returns a reordering of the graph g so that the vertices with largest * degrees (most neighbors) are first. */ int *reorder_by_degree(graph_t *g, boolean weighted) { int i,j,v; int *degree; int *order; int maxdegree,maxvertex=0; degree=calloc(g->n,sizeof(int)); order=calloc(g->n,sizeof(int)); for (i=0; i < g->n; i++) { for (j=0; j < g->n; j++) { ASSERT(!((i==j) && GRAPH_IS_EDGE(g,i,j))); if (GRAPH_IS_EDGE(g,i,j)) degree[i]++; } } for (v=0; v < g->n; v++) { maxdegree=0; for (i=0; i < g->n; i++) { if (degree[i] >= maxdegree) { maxvertex=i; maxdegree=degree[i]; } } order[v]=maxvertex; degree[maxvertex]=-1; /* used */ /*** Max. degree withing unselected graph: for (i=0; i < g->n; i++) { if (GRAPH_IS_EDGE(g,maxvertex,i)) degree[i]--; } ***/ } free(degree); return order; } /* * reorder_by_random() * * Returns a random reordering for graph g. * Note: Used the functions rand() and srand() to generate the random * numbers. srand() is re-initialized every time reorder_by_random() * is called using the system time. */ int *reorder_by_random(graph_t *g, boolean weighted) { int i,r; int *new; boolean *used; new=calloc(g->n, sizeof(int)); used=calloc(g->n, sizeof(boolean)); for (i=0; i < g->n; i++) { do { r = igraph_rng_get_integer(igraph_rng_default(), 0, g->n - 1); } while (used[r]); new[i]=r; used[r]=TRUE; } free(used); return new; } python-igraph-0.8.0/vendor/source/igraph/src/cliquer/cliquer_graph.c0000644000076500000240000004006413524616144026045 0ustar tamasstaff00000000000000 /* * This file contains the graph handling routines. * * Copyright (C) 2002 Sampo Niskanen, Patric Östergård. * Licensed under the GNU GPL, read the file LICENSE for details. */ #include #include #include #include "graph.h" #ifdef USING_R #include #endif /* static graph_t *graph_read_dimacs_binary(FILE *fp,char *firstline); static graph_t *graph_read_dimacs_ascii(FILE *fp,char *firstline); */ /* * graph_new() * * Returns a newly allocated graph with n vertices all with weight 1, * and no edges. */ graph_t *graph_new(int n) { graph_t *g; int i; ASSERT((sizeof(setelement)*8)==ELEMENTSIZE); ASSERT(n>0); g=malloc(sizeof(graph_t)); g->n=n; g->edges=malloc(g->n * sizeof(set_t)); g->weights=malloc(g->n * sizeof(int)); for (i=0; i < g->n; i++) { g->edges[i]=set_new(n); g->weights[i]=1; } return g; } /* * graph_free() * * Frees the memory associated with the graph g. */ void graph_free(graph_t *g) { int i; ASSERT((sizeof(setelement)*8)==ELEMENTSIZE); ASSERT(g!=NULL); ASSERT(g->n > 0); for (i=0; i < g->n; i++) { set_free(g->edges[i]); } free(g->weights); free(g->edges); free(g); return; } /* * graph_resize() * * Resizes graph g to given size. If size > g->n, the new vertices are * not connected to any others and their weights are set to 1. * If size < g->n, the last g->n - size vertices are removed. */ void graph_resize(graph_t *g, int size) { int i; ASSERT(g!=NULL); ASSERT(g->n > 0); ASSERT(size > 0); if (g->n == size) return; /* Free/alloc extra edge-sets */ for (i=size; i < g->n; i++) set_free(g->edges[i]); g->edges=realloc(g->edges, size * sizeof(set_t)); for (i=g->n; i < size; i++) g->edges[i]=set_new(size); /* Resize original sets */ for (i=0; i < MIN(g->n,size); i++) { g->edges[i]=set_resize(g->edges[i],size); } /* Weights */ g->weights=realloc(g->weights,size * sizeof(int)); for (i=g->n; iweights[i]=1; g->n=size; return; } /* * graph_crop() * * Resizes the graph so as to remove all highest-valued isolated vertices. */ void graph_crop(graph_t *g) { int i; for (i=g->n-1; i>=1; i--) if (set_size(g->edges[i])>0) break; graph_resize(g,i+1); return; } /* * graph_weighted() * * Returns TRUE if all vertex weights of graph g are all the same. * * Note: Does NOT require weights to be 1. */ boolean graph_weighted(graph_t *g) { int i,w; w=g->weights[0]; for (i=1; i < g->n; i++) if (g->weights[i] != w) return TRUE; return FALSE; } /* * graph_edge_count() * * Returns the number of edges in graph g. */ int graph_edge_count(graph_t *g) { int i; int count=0; for (i=0; i < g->n; i++) { count += set_size(g->edges[i]); } return count/2; } #if 0 /* * graph_write_dimacs_ascii_file() * * Writes an ASCII dimacs-format file of graph g, with comment, to * given file. * * Returns TRUE if successful, FALSE if an error occurred. */ boolean graph_write_dimacs_ascii_file(graph_t *g, char *comment, char *file) { FILE *fp; ASSERT((sizeof(setelement)*8)==ELEMENTSIZE); ASSERT(file!=NULL); if ((fp=fopen(file,"wb"))==NULL) return FALSE; if (!graph_write_dimacs_ascii(g,comment,fp)) { fclose(fp); return FALSE; } fclose(fp); return TRUE; } /* * graph_write_dimacs_ascii() * * Writes an ASCII dimacs-format file of graph g, with comment, to the * file stream fp. * * Returns TRUE if successful, FALSE if an error occurred. */ boolean graph_write_dimacs_ascii(graph_t *g, char *comment, FILE *fp) { int i,j; ASSERT((sizeof(setelement)*8)==ELEMENTSIZE); ASSERT(graph_test(g,NULL)); ASSERT(fp!=NULL); if (comment) fprintf(fp,"c %s\n",comment); fprintf(fp,"p edge %d %d\n",g->n,graph_edge_count(g)); for (i=0; i < g->n; i++) if (g->weights[i]!=1) fprintf(fp,"n %d %d\n",i+1,g->weights[i]); for (i=0; i < g->n; i++) for (j=0; j= headersize) { \ headersize+=1024; \ header=realloc(header,headersize); \ } \ strncat(header,s,1000); \ headerlength+=strlen(s); boolean graph_write_dimacs_binary(graph_t *g, char *comment,FILE *fp) { char *buf; char *header=NULL; int headersize=0; int headerlength=0; int i,j; ASSERT((sizeof(setelement)*8)==ELEMENTSIZE); ASSERT(graph_test(g,NULL)); ASSERT(fp!=NULL); buf=malloc(MAX(1024,g->n/8+1)); header=malloc(1024); header[0]=0; headersize=1024; if (comment) { strcpy(buf,"c "); strncat(buf,comment,1000); strcat(buf,"\n"); STR_APPEND(buf); } sprintf(buf,"p edge %d %d\n",g->n,graph_edge_count(g)); STR_APPEND(buf); for (i=0; i < g->n; i++) { if (g->weights[i]!=1) { sprintf(buf,"n %d %d\n",i+1,g->weights[i]); STR_APPEND(buf); } } fprintf(fp,"%d\n",(int)strlen(header)); fprintf(fp,"%s",header); free(header); for (i=0; i < g->n; i++) { memset(buf,0,i/8+1); for (j=0; j=strlen(str)) /* blank line */ return TRUE; if (str[i+1]!=0 && !isspace(str[i+1])) /* not 1-char field */ return FALSE; switch (str[i]) { case 'c': return TRUE; case 'p': if (g->n != 0) return FALSE; if (sscanf(str," p %15s %d %d %2s",tmp,&(g->n),&i,tmp)!=3) return FALSE; if (g->n <= 0) return FALSE; g->edges=calloc(g->n,sizeof(set_t)); for (i=0; in; i++) g->edges[i]=set_new(g->n); g->weights=calloc(g->n,sizeof(int)); for (i=0; in; i++) g->weights[i]=1; return TRUE; case 'n': if ((g->n <= 0) || (g->weights == NULL)) return FALSE; if (sscanf(str," n %d %d %2s",&i,&w,tmp)!=2) return FALSE; if (i<1 || i>g->n) return FALSE; if (w<=0) return FALSE; g->weights[i-1]=w; return TRUE; case 'e': if ((g->n <= 0) || (g->edges == NULL)) return FALSE; if (sscanf(str," e %d %d %2s",&i,&j,tmp)!=2) return FALSE; if (i<1 || j<1 || i>g->n || j>g->n) return FALSE; if (i==j) /* We want antireflexive graphs. */ return TRUE; GRAPH_ADD_EDGE(g,i-1,j-1); return TRUE; case 'd': case 'v': case 'x': return TRUE; default: fprintf(stderr,"Warning: ignoring field '%c' in " "input.\n",str[i]); return TRUE; } } /* * graph_read_dimacs_binary() * * Reads a dimacs-format binary file from file stream fp with the first * line being firstline. * * Returns the newly-allocated graph or NULL if an error occurred. * * TODO: This function leaks memory when reading erroneous files. */ static graph_t *graph_read_dimacs_binary(FILE *fp,char *firstline) { int length=0; graph_t *g; int i,j; char *buffer; char *start; char *end; char **buf; char tmp[10]; if (sscanf(firstline," %d %2s",&length,tmp)!=1) return NULL; if (length<=0) { fprintf(stderr,"Malformed preamble: preamble size < 0.\n"); return NULL; } buffer=malloc(length+2); if (fread(buffer,1,length,fp)n <= 0) { fprintf(stderr,"Malformed preamble: number of " "vertices <= 0\n"); free(g); return NULL; } /* Binary part. */ buf=calloc(g->n,sizeof(char*)); for (i=0; i < g->n; i++) { buf[i]=calloc(g->n,1); if (fread(buf[i],1,i/8+1,fp) < (i/8+1)) { fprintf(stderr,"Unexpected end of file when " "reading graph.\n"); return NULL; } } for (i=0; i < g->n; i++) { for (j=0; jn <= 0) { free(g); fprintf(stderr,"Unexpected end of file when reading graph.\n"); return NULL; } return g; } #endif #ifndef USING_R /* * graph_print() * * Prints a representation of the graph g to stdout (along with any errors * noticed). Mainly useful for debugging purposes and trivial output. * * The output consists of a first line describing the dimensions and then * one line per vertex containing the vertex number (numbered 0,...,n-1), * the vertex weight (if the graph is weighted), "->" and then a list * of all vertices it is adjacent to. */ void graph_print(graph_t *g) { int i,j; int asymm=0; int refl=0; int nonpos=0; int extra=0; unsigned int weight=0; boolean weighted; ASSERT((sizeof(setelement)*8)==ELEMENTSIZE); if (g==NULL) { printf(" WARNING: Graph pointer is NULL!\n"); return; } if (g->n <= 0) { printf(" WARNING: Graph has %d vertices " "(should be positive)!\n",g->n); return; } weighted=graph_weighted(g); printf("%s graph has %d vertices, %d edges (density %.2f).\n", weighted?"Weighted":((g->weights[0]==1)? "Unweighted":"Semi-weighted"), g->n,graph_edge_count(g), (float)graph_edge_count(g)/((float)(g->n - 1)*(g->n)/2)); for (i=0; i < g->n; i++) { printf("%2d",i); if (weighted) { printf(" w=%d",g->weights[i]); if (g->weights[i] <= 0) { printf("*NON-POSITIVE*"); nonpos++; } } if (weight < INT_MAX) weight+=g->weights[i]; printf(" ->"); for (j=0; j < g->n; j++) { if (SET_CONTAINS_FAST(g->edges[i],j)) { printf(" %d",j); if (i==j) { printf("*REFLEXIVE*"); refl++; } if (!SET_CONTAINS_FAST(g->edges[j],i)) { printf("*ASYMMERTIC*"); asymm++; } } } for (j=g->n; j < SET_ARRAY_LENGTH(g->edges[i])*ELEMENTSIZE; j++) { if (SET_CONTAINS_FAST(g->edges[i],j)) { printf(" %d*NON-EXISTENT*",j); extra++; } } printf("\n"); } if (asymm) printf(" WARNING: Graph contained %d asymmetric edges!\n", asymm); if (refl) printf(" WARNING: Graph contained %d reflexive edges!\n", refl); if (nonpos) printf(" WARNING: Graph contained %d non-positive vertex " "weights!\n",nonpos); if (extra) printf(" WARNING: Graph contained %d edges to " "non-existent vertices!\n",extra); if (weight>=INT_MAX) printf(" WARNING: Total graph weight >= INT_MAX!\n"); return; } #endif /* * graph_test() * * Tests graph g to be valid. Checks that g is non-NULL, the edges are * symmetric and anti-reflexive, and that all vertex weights are positive. * If output is non-NULL, prints a few lines telling the status of the graph * to file descriptor output. * * Returns TRUE if the graph is valid, FALSE otherwise. */ boolean graph_test(graph_t *g,FILE *output) { int i,j; int edges=0; int asymm=0; int nonpos=0; int refl=0; int extra=0; unsigned int weight=0; boolean weighted; ASSERT((sizeof(setelement)*8)==ELEMENTSIZE); if (g==NULL) { if (output) fprintf(output," WARNING: Graph pointer is NULL!\n"); return FALSE; } weighted=graph_weighted(g); for (i=0; i < g->n; i++) { if (g->edges[i]==NULL) { if (output) fprintf(output," WARNING: Graph edge set " "NULL!\n" " (further warning suppressed)\n"); return FALSE; } if (SET_MAX_SIZE(g->edges[i]) < g->n) { if (output) fprintf(output," WARNING: Graph edge set " "too small!\n" " (further warnings suppressed)\n"); return FALSE; } for (j=0; j < g->n; j++) { if (SET_CONTAINS_FAST(g->edges[i],j)) { edges++; if (i==j) { refl++; } if (!SET_CONTAINS_FAST(g->edges[j],i)) { asymm++; } } } for (j=g->n; j < SET_ARRAY_LENGTH(g->edges[i])*ELEMENTSIZE; j++) { if (SET_CONTAINS_FAST(g->edges[i],j)) extra++; } if (g->weights[i] <= 0) nonpos++; if (weightweights[i]; } edges/=2; /* Each is counted twice. */ if (output) { /* Semi-weighted means all weights are equal, but not 1. */ fprintf(output,"%s graph has %d vertices, %d edges " "(density %.2f).\n", weighted?"Weighted": ((g->weights[0]==1)?"Unweighted":"Semi-weighted"), g->n,edges,(float)edges/((float)(g->n - 1)*(g->n)/2)); if (asymm) fprintf(output," WARNING: Graph contained %d " "asymmetric edges!\n",asymm); if (refl) fprintf(output," WARNING: Graph contained %d " "reflexive edges!\n",refl); if (nonpos) fprintf(output," WARNING: Graph contained %d " "non-positive vertex weights!\n",nonpos); if (extra) fprintf(output," WARNING: Graph contained %d edges " "to non-existent vertices!\n",extra); if (weight>=INT_MAX) fprintf(output," WARNING: Total graph weight >= " "INT_MAX!\n"); if (asymm==0 && refl==0 && nonpos==0 && extra==0 && weight=INT_MAX) return FALSE; return TRUE; } /* * graph_test_regular() * * Returns the vertex degree for regular graphs, or -1 if the graph is * not regular. */ int graph_test_regular(graph_t *g) { int i,n; n=set_size(g->edges[0]); for (i=1; i < g->n; i++) { if (set_size(g->edges[i]) != n) return -1; } return n; } python-igraph-0.8.0/vendor/source/igraph/src/cliquer/set.h0000644000076500000240000002225713524616144024024 0ustar tamasstaff00000000000000 /* * This file contains the set handling routines. * * Copyright (C) 2002 Sampo Niskanen, Patric Östergård. * Licensed under the GNU GPL, read the file LICENSE for details. */ #ifndef CLIQUER_SET_H #define CLIQUER_SET_H #include #include #include #include #include "misc.h" /* * Sets are arrays of setelement's (typically unsigned long int's) with * representative bits for each value they can contain. The values * are numbered 0,...,n-1. */ /*** Variable types and constants. ***/ /* * If setelement hasn't been declared: * - use "unsigned long int" as setelement * - try to deduce size from ULONG_MAX */ #ifndef ELEMENTSIZE typedef unsigned long int setelement; # if (ULONG_MAX == 65535) # define ELEMENTSIZE 16 # elif (ULONG_MAX == 4294967295) # define ELEMENTSIZE 32 # else # define ELEMENTSIZE 64 # endif #endif /* !ELEMENTSIZE */ typedef setelement * set_t; /*** Counting amount of 1 bits in a setelement ***/ /* Array for amount of 1 bits in a byte. */ static int set_bit_count[256] = { 0,1,1,2,1,2,2,3,1,2,2,3,2,3,3,4, 1,2,2,3,2,3,3,4,2,3,3,4,3,4,4,5, 1,2,2,3,2,3,3,4,2,3,3,4,3,4,4,5, 2,3,3,4,3,4,4,5,3,4,4,5,4,5,5,6, 1,2,2,3,2,3,3,4,2,3,3,4,3,4,4,5, 2,3,3,4,3,4,4,5,3,4,4,5,4,5,5,6, 2,3,3,4,3,4,4,5,3,4,4,5,4,5,5,6, 3,4,4,5,4,5,5,6,4,5,5,6,5,6,6,7, 1,2,2,3,2,3,3,4,2,3,3,4,3,4,4,5, 2,3,3,4,3,4,4,5,3,4,4,5,4,5,5,6, 2,3,3,4,3,4,4,5,3,4,4,5,4,5,5,6, 3,4,4,5,4,5,5,6,4,5,5,6,5,6,6,7, 2,3,3,4,3,4,4,5,3,4,4,5,4,5,5,6, 3,4,4,5,4,5,5,6,4,5,5,6,5,6,6,7, 3,4,4,5,4,5,5,6,4,5,5,6,5,6,6,7, 4,5,5,6,5,6,6,7,5,6,6,7,6,7,7,8 }; /* The following macros assume that all higher bits are 0. * They may in some cases be useful also on with other ELEMENTSIZE's, * so we define them all. */ #define SET_ELEMENT_BIT_COUNT_8(a) (set_bit_count[(a)]) #define SET_ELEMENT_BIT_COUNT_16(a) (set_bit_count[(a)>>8] + \ set_bit_count[(a)&0xFF]) #define SET_ELEMENT_BIT_COUNT_32(a) (set_bit_count[(a)>>24] + \ set_bit_count[((a)>>16)&0xFF] + \ set_bit_count[((a)>>8)&0xFF] + \ set_bit_count[(a)&0xFF]) #define SET_ELEMENT_BIT_COUNT_64(a) (set_bit_count[(a)>>56] + \ set_bit_count[((a)>>48)&0xFF] + \ set_bit_count[((a)>>40)&0xFF] + \ set_bit_count[((a)>>32)&0xFF] + \ set_bit_count[((a)>>24)&0xFF] + \ set_bit_count[((a)>>16)&0xFF] + \ set_bit_count[((a)>>8)&0xFF] + \ set_bit_count[(a)&0xFF]) #if (ELEMENTSIZE==64) # define SET_ELEMENT_BIT_COUNT(a) SET_ELEMENT_BIT_COUNT_64(a) # define FULL_ELEMENT ((setelement)0xFFFFFFFFFFFFFFFF) #elif (ELEMENTSIZE==32) # define SET_ELEMENT_BIT_COUNT(a) SET_ELEMENT_BIT_COUNT_32(a) # define FULL_ELEMENT ((setelement)0xFFFFFFFF) #elif (ELEMENTSIZE==16) # define SET_ELEMENT_BIT_COUNT(a) SET_ELEMENT_BIT_COUNT_16(a) # define FULL_ELEMENT ((setelement)0xFFFF) #else # error "SET_ELEMENT_BIT_COUNT(a) not defined for current ELEMENTSIZE" #endif /*** Macros and functions ***/ /* * Gives a value with bit x (counting from lsb up) set. * * Making this as a table might speed up things on some machines * (though on most modern machines it's faster to shift instead of * using memory). Making it a macro makes it easy to change. */ #define SET_BIT_MASK(x) ((setelement)1<<(x)) /* Set element handling macros */ #define SET_ELEMENT_INTERSECT(a,b) ((a)&(b)) #define SET_ELEMENT_UNION(a,b) ((a)|(b)) #define SET_ELEMENT_DIFFERENCE(a,b) ((a)&(~(b))) #define SET_ELEMENT_CONTAINS(e,v) ((e)&SET_BIT_MASK(v)) /* Set handling macros */ #define SET_ADD_ELEMENT(s,a) \ ((s)[(a)/ELEMENTSIZE] |= SET_BIT_MASK((a)%ELEMENTSIZE)) #define SET_DEL_ELEMENT(s,a) \ ((s)[(a)/ELEMENTSIZE] &= ~SET_BIT_MASK((a)%ELEMENTSIZE)) #define SET_CONTAINS_FAST(s,a) (SET_ELEMENT_CONTAINS((s)[(a)/ELEMENTSIZE], \ (a)%ELEMENTSIZE)) #define SET_CONTAINS(s,a) (((a)0); n=(size/ELEMENTSIZE+1)+1; s=calloc(n,sizeof(setelement)); s[0]=size; return &(s[1]); } /* * set_free() * * Free the memory associated with set s. */ UNUSED_FUNCTION INLINE static void set_free(set_t s) { ASSERT(s!=NULL); free(&(s[-1])); } /* * set_resize() * * Resizes set s to given size. If the size is less than SET_MAX_SIZE(s), * the last elements are dropped. * * Returns a pointer to the new set. */ UNUSED_FUNCTION INLINE static set_t set_resize(set_t s, int size) { int n; ASSERT(size>0); n=(size/ELEMENTSIZE+1); s=((setelement *)realloc(s-1,(n+1)*sizeof(setelement)))+1; if (n>SET_ARRAY_LENGTH(s)) memset(s+SET_ARRAY_LENGTH(s),0, (n-SET_ARRAY_LENGTH(s))*sizeof(setelement)); if (size < SET_MAX_SIZE(s)) s[(size-1)/ELEMENTSIZE] &= (FULL_ELEMENT >> (ELEMENTSIZE-size%ELEMENTSIZE)); s[-1]=size; return s; } /* * set_size() * * Returns the number of elements in set s. */ UNUSED_FUNCTION INLINE static int set_size(set_t s) { int count=0; setelement *c; for (c=s; c < s+SET_ARRAY_LENGTH(s); c++) count+=SET_ELEMENT_BIT_COUNT(*c); return count; } /* * set_duplicate() * * Returns a newly allocated duplicate of set s. */ UNUSED_FUNCTION INLINE static set_t set_duplicate(set_t s) { set_t new; new=set_new(SET_MAX_SIZE(s)); memcpy(new,s,SET_ARRAY_LENGTH(s)*sizeof(setelement)); return new; } /* * set_copy() * * Copies set src to dest. If dest is NULL, is equal to set_duplicate. * If dest smaller than src, it is freed and a new set of the same size as * src is returned. */ UNUSED_FUNCTION INLINE static set_t set_copy(set_t dest,set_t src) { if (dest==NULL) return set_duplicate(src); if (SET_MAX_SIZE(dest)=0) { * // i is in set s * } */ UNUSED_FUNCTION INLINE static int set_return_next(set_t s, int n) { if (n<0) n=0; else n++; if (n >= SET_MAX_SIZE(s)) return -1; while (n%ELEMENTSIZE) { if (SET_CONTAINS(s,n)) return n; n++; if (n >= SET_MAX_SIZE(s)) return -1; } while (s[n/ELEMENTSIZE]==0) { n+=ELEMENTSIZE; if (n >= SET_MAX_SIZE(s)) return -1; } while (!SET_CONTAINS(s,n)) { n++; if (n >= SET_MAX_SIZE(s)) return -1; } return n; } /* * set_print() * * Prints the size and contents of set s to stdout. * Mainly useful for debugging purposes and trivial output. */ /* UNUSED_FUNCTION static void set_print(set_t s) { int i; printf("size=%d(max %d)",set_size(s),(int)SET_MAX_SIZE(s)); for (i=0; i 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_paths.h" #include "igraph_adjlist.h" #include "igraph_interface.h" #include "igraph_random.h" #include "igraph_memory.h" #include "igraph_interrupt_internal.h" /** * \function igraph_random_walk * Perform a random walk on a graph * * Performs a random walk with a given length on a graph, from the given * start vertex. Edge directions are (potentially) considered, depending on * the \p mode argument. * * \param graph The input graph, it can be directed or undirected. * Multiple edges are respected, so are loop edges. * \param walk An allocated vector, the result is stored here. * It will be resized as needed. * \param start The start vertex for the walk. * \param steps The number of steps to take. If the random walk gets * stuck, then the \p stuck argument specifies what happens. * \param mode How to walk along the edges in direted graphs. * \c IGRAPH_OUT means following edge directions, \c IGRAPH_IN means * going opposite the edge directions, \c IGRAPH_ALL means ignoring * edge directions. This argument is ignored for undirected graphs. * \param stuck What to do if the random walk gets stuck. * \c IGRAPH_RANDOM_WALK_STUCK_RETURN means that the function returns * with a shorter walk; \c IGRAPH_RANDOM_WALK_STUCK_ERROR means * that an error is reported. In both cases \p walk is truncated * to contain the actual interrupted walk. * \return Error code. * * Time complexity: O(l + d), where \c l is the length of the * walk, and \c d is the total degree of the visited nodes. */ int igraph_random_walk(const igraph_t *graph, igraph_vector_t *walk, igraph_integer_t start, igraph_neimode_t mode, igraph_integer_t steps, igraph_random_walk_stuck_t stuck) { /* TODO: - multiple walks potentially from multiple start vertices - weights */ igraph_lazy_adjlist_t adj; igraph_integer_t vc = igraph_vcount(graph); igraph_integer_t i; if (start < 0 || start >= vc) { IGRAPH_ERROR("Invalid start vertex", IGRAPH_EINVAL); } if (steps < 0) { IGRAPH_ERROR("Invalid number of steps", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_lazy_adjlist_init(graph, &adj, mode, IGRAPH_DONT_SIMPLIFY)); IGRAPH_FINALLY(igraph_lazy_adjlist_destroy, &adj); IGRAPH_CHECK(igraph_vector_resize(walk, steps)); RNG_BEGIN(); VECTOR(*walk)[0] = start; for (i = 1; i < steps; i++) { igraph_vector_t *neis; igraph_integer_t nn; neis = igraph_lazy_adjlist_get(&adj, start); nn = igraph_vector_size(neis); if (IGRAPH_UNLIKELY(nn == 0)) { igraph_vector_resize(walk, i); if (stuck == IGRAPH_RANDOM_WALK_STUCK_RETURN) { break; } else { IGRAPH_ERROR("Random walk got stuck", IGRAPH_ERWSTUCK); } } start = VECTOR(*walk)[i] = VECTOR(*neis)[ RNG_INTEGER(0, nn - 1) ]; } RNG_END(); igraph_lazy_adjlist_destroy(&adj); IGRAPH_FINALLY_CLEAN(1); return 0; } /* Used as item destructor for 'cdfs' in igraph_random_edge_walk(). */ static void vec_destr(igraph_vector_t *vec) { if (vec != NULL) { igraph_vector_destroy(vec); } } /** * \function igraph_random_edge_walk * \brief Perform a random walk on a graph and return the traversed edges * * Performs a random walk with a given length on a graph, from the given * start vertex. Edge directions are (potentially) considered, depending on * the \p mode argument. * * \param graph The input graph, it can be directed or undirected. * Multiple edges are respected, so are loop edges. * \param weights A vector of non-negative edge weights. * It is assumed that at least one strictly positive weight is found among the * outgoing edges of each vertex. If it is a NULL pointer, all edges are considered * to have equal weight. * \param edgewalk An initialized vector; the indices of traversed edges are stored here. * It will be resized as needed. * \param start The start vertex for the walk. * \param steps The number of steps to take. If the random walk gets * stuck, then the \p stuck argument specifies what happens. * \param mode How to walk along the edges in direted graphs. * \c IGRAPH_OUT means following edge directions, \c IGRAPH_IN means * going opposite the edge directions, \c IGRAPH_ALL means ignoring * edge directions. This argument is ignored for undirected graphs. * \param stuck What to do if the random walk gets stuck. * \c IGRAPH_RANDOM_WALK_STUCK_RETURN means that the function returns * with a shorter walk; \c IGRAPH_RANDOM_WALK_STUCK_ERROR means * that an error is reported. In both cases, \p edgewalk is truncated * to contain the actual interrupted walk. * * \return Error code. * */ int igraph_random_edge_walk(const igraph_t *graph, const igraph_vector_t *weights, igraph_vector_t *edgewalk, igraph_integer_t start, igraph_neimode_t mode, igraph_integer_t steps, igraph_random_walk_stuck_t stuck) { igraph_integer_t vc = igraph_vcount(graph); igraph_integer_t ec = igraph_ecount(graph); igraph_integer_t i; igraph_inclist_t il; igraph_vector_t weight_temp; igraph_vector_ptr_t cdfs; /* cumulative distribution vectors for each node, used for weighted choice */ /* the fourth igraph_neimode_t value, IGRAPH_TOTAL, is disallowed */ if (! (mode == IGRAPH_ALL || mode == IGRAPH_IN || mode == IGRAPH_OUT)) { IGRAPH_ERROR("Invalid mode parameter", IGRAPH_EINVMODE); } /* ref switch statement at end of main loop */ if (! igraph_is_directed(graph)) { mode = IGRAPH_ALL; } if (start < 0 || start >= vc) { IGRAPH_ERROR("Invalid start vertex", IGRAPH_EINVAL); } if (steps < 0) { IGRAPH_ERROR("Invalid number of steps", IGRAPH_EINVAL); } if (weights) { if (igraph_vector_size(weights) != ec) { IGRAPH_ERROR("Invalid weight vector length", IGRAPH_EINVAL); } if (igraph_vector_min(weights) < 0) { IGRAPH_ERROR("Weights must be non-negative", IGRAPH_EINVAL); } } IGRAPH_CHECK(igraph_vector_resize(edgewalk, steps)); IGRAPH_CHECK(igraph_inclist_init(graph, &il, mode)); IGRAPH_FINALLY(igraph_inclist_destroy, &il); IGRAPH_VECTOR_INIT_FINALLY(&weight_temp, 0); /* cdf vectors will be computed lazily */ IGRAPH_CHECK(igraph_vector_ptr_init(&cdfs, vc)); IGRAPH_FINALLY(igraph_vector_ptr_destroy_all, &cdfs); IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(&cdfs, vec_destr); for (i = 0; i < vc; ++i) { VECTOR(cdfs)[i] = NULL; } RNG_BEGIN(); for (i = 0; i < steps; ++i) { long degree, edge, idx; igraph_vector_int_t *edges = igraph_inclist_get(&il, start); degree = igraph_vector_int_size(edges); /* are we stuck? */ if (IGRAPH_UNLIKELY(degree == 0)) { igraph_vector_resize(edgewalk, i); /* can't fail since size is reduced, skip IGRAPH_CHECK */ if (stuck == IGRAPH_RANDOM_WALK_STUCK_RETURN) { break; } else { IGRAPH_ERROR("Random walk got stuck", IGRAPH_ERWSTUCK); } } if (weights) { /* weighted: choose an out-edge with probability proportional to its weight */ igraph_real_t r; igraph_vector_t **cd = (igraph_vector_t **) & (VECTOR(cdfs)[start]); /* compute out-edge cdf for this node if not already done */ if (IGRAPH_UNLIKELY(! *cd)) { long j; *cd = igraph_malloc(sizeof(igraph_vector_t)); if (*cd == NULL) { IGRAPH_ERROR("random edge walk failed", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_init(*cd, degree)); IGRAPH_CHECK(igraph_vector_resize(&weight_temp, degree)); for (j = 0; j < degree; ++j) { VECTOR(weight_temp)[j] = VECTOR(*weights)[ VECTOR(*edges)[j] ]; } IGRAPH_CHECK(igraph_vector_cumsum(*cd, &weight_temp)); } r = RNG_UNIF(0, VECTOR( **cd )[degree - 1]); igraph_vector_binsearch(*cd, r, &idx); } else { /* unweighted: choose an out-edge at random */ idx = RNG_INTEGER(0, degree - 1); } edge = VECTOR(*edges)[idx]; VECTOR(*edgewalk)[i] = edge; /* travel along edge in a direction specified by 'mode' */ /* note: 'mode' is always set to IGRAPH_ALL for undirected graphs */ switch (mode) { case IGRAPH_OUT: start = IGRAPH_TO(graph, edge); break; case IGRAPH_IN: start = IGRAPH_FROM(graph, edge); break; case IGRAPH_ALL: start = IGRAPH_OTHER(graph, edge, start); break; } IGRAPH_ALLOW_INTERRUPTION(); } RNG_END(); igraph_vector_ptr_destroy_all(&cdfs); igraph_vector_destroy(&weight_temp); igraph_inclist_destroy(&il); IGRAPH_FINALLY_CLEAN(3); return IGRAPH_SUCCESS; } python-igraph-0.8.0/vendor/source/igraph/src/centrality.c0000644000076500000240000040264213614300625023730 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include /* memset */ #include #include "igraph_centrality.h" #include "igraph_math.h" #include "igraph_memory.h" #include "igraph_random.h" #include "igraph_adjlist.h" #include "igraph_interface.h" #include "igraph_progress.h" #include "igraph_interrupt_internal.h" #include "igraph_topology.h" #include "igraph_types_internal.h" #include "igraph_stack.h" #include "igraph_dqueue.h" #include "config.h" #include "bigint.h" #include "prpack.h" int igraph_personalized_pagerank_arpack(const igraph_t *graph, igraph_vector_t *vector, igraph_real_t *value, const igraph_vs_t vids, igraph_bool_t directed, igraph_real_t damping, igraph_vector_t *reset, const igraph_vector_t *weights, igraph_arpack_options_t *options); igraph_bool_t igraph_i_vector_mostly_negative(const igraph_vector_t *vector) { /* Many of the centrality measures correspond to the eigenvector of some * matrix. When v is an eigenvector, c*v is also an eigenvector, therefore * it may happen that all the scores in the eigenvector are negative, in which * case we want to negate them since the centrality scores should be positive. * However, since ARPACK is not always stable, sometimes it happens that * *some* of the centrality scores are small negative numbers. This function * helps distinguish between the two cases; it should return true if most of * the values are relatively large negative numbers, in which case we should * negate the eigenvector. */ long int i, n = igraph_vector_size(vector); igraph_real_t mi, ma; if (n == 0) { return 0; } mi = ma = VECTOR(*vector)[0]; for (i = 1; i < n; i++) { if (VECTOR(*vector)[i] < mi) { mi = VECTOR(*vector)[i]; } if (VECTOR(*vector)[i] > ma) { ma = VECTOR(*vector)[i]; } } if (mi >= 0) { return 0; } if (ma <= 0) { return 1; } mi /= ma; return (mi < 1e-5) ? 1 : 0; } int igraph_i_eigenvector_centrality(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_adjlist_t *adjlist = extra; igraph_vector_int_t *neis; long int i, j, nlen; for (i = 0; i < n; i++) { neis = igraph_adjlist_get(adjlist, i); nlen = igraph_vector_int_size(neis); to[i] = 0.0; for (j = 0; j < nlen; j++) { long int nei = (long int) VECTOR(*neis)[j]; to[i] += from[nei]; } } return 0; } typedef struct igraph_i_eigenvector_centrality_t { const igraph_t *graph; const igraph_inclist_t *inclist; const igraph_vector_t *weights; } igraph_i_eigenvector_centrality_t; int igraph_i_eigenvector_centrality2(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_i_eigenvector_centrality_t *data = extra; const igraph_t *graph = data->graph; const igraph_inclist_t *inclist = data->inclist; const igraph_vector_t *weights = data->weights; igraph_vector_int_t *edges; long int i, j, nlen; for (i = 0; i < n; i++) { edges = igraph_inclist_get(inclist, i); nlen = igraph_vector_int_size(edges); to[i] = 0.0; for (j = 0; j < nlen; j++) { long int edge = VECTOR(*edges)[j]; long int nei = IGRAPH_OTHER(graph, edge, i); igraph_real_t w = VECTOR(*weights)[edge]; to[i] += w * from[nei]; } } return 0; } int igraph_i_eigenvector_centrality_loop(igraph_adjlist_t *adjlist) { long int i, j, k, nlen, n = igraph_adjlist_size(adjlist); igraph_vector_int_t *neis; for (i = 0; i < n; i++) { neis = igraph_adjlist_get(adjlist, i); nlen = igraph_vector_int_size(neis); for (j = 0; j < nlen && VECTOR(*neis)[j] < i; j++) ; for (k = j; k < nlen && VECTOR(*neis)[k] == i; k++) ; if (k != j) { /* First loop edge is 'j', first non-loop edge is 'k' */ igraph_vector_int_remove_section(neis, j + (k - j) / 2, k); } } return 0; } int igraph_eigenvector_centrality_undirected(const igraph_t *graph, igraph_vector_t *vector, igraph_real_t *value, igraph_bool_t scale, const igraph_vector_t *weights, igraph_arpack_options_t *options) { igraph_vector_t values; igraph_matrix_t vectors; igraph_vector_t degree; long int i; options->n = igraph_vcount(graph); options->start = 1; /* no random start vector */ if (igraph_ecount(graph) == 0) { /* special case: empty graph */ if (value) { *value = 0; } if (vector) { igraph_vector_resize(vector, igraph_vcount(graph)); igraph_vector_fill(vector, 1); } return IGRAPH_SUCCESS; } if (weights) { igraph_real_t min, max; if (igraph_vector_size(weights) != igraph_ecount(graph)) { IGRAPH_ERROR("Invalid length of weights vector when calculating " "eigenvector centrality", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_vector_minmax(weights, &min, &max)); if (min == 0 && max == 0) { /* special case: all weights are zeros */ if (value) { *value = 0; } if (vector) { igraph_vector_resize(vector, igraph_vcount(graph)); igraph_vector_fill(vector, 1); } return IGRAPH_SUCCESS; } } IGRAPH_VECTOR_INIT_FINALLY(&values, 0); IGRAPH_MATRIX_INIT_FINALLY(&vectors, options->n, 1); IGRAPH_VECTOR_INIT_FINALLY(°ree, options->n); IGRAPH_CHECK(igraph_degree(graph, °ree, igraph_vss_all(), IGRAPH_ALL, /*loops=*/ 0)); RNG_BEGIN(); for (i = 0; i < options->n; i++) { if (VECTOR(degree)[i]) { MATRIX(vectors, i, 0) = VECTOR(degree)[i] + RNG_UNIF(-1e-4, 1e-4); } else { MATRIX(vectors, i, 0) = 1.0; } } RNG_END(); igraph_vector_destroy(°ree); IGRAPH_FINALLY_CLEAN(1); options->n = igraph_vcount(graph); options->nev = 1; options->ncv = 0; /* 0 means "automatic" in igraph_arpack_rssolve */ options->which[0] = 'L'; options->which[1] = 'A'; options->start = 1; /* no random start vector */ if (!weights) { igraph_adjlist_t adjlist; IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist); IGRAPH_CHECK(igraph_i_eigenvector_centrality_loop(&adjlist)); IGRAPH_CHECK(igraph_arpack_rssolve(igraph_i_eigenvector_centrality, &adjlist, options, 0, &values, &vectors)); igraph_adjlist_destroy(&adjlist); IGRAPH_FINALLY_CLEAN(1); } else { igraph_inclist_t inclist; igraph_i_eigenvector_centrality_t data = { graph, &inclist, weights }; IGRAPH_CHECK(igraph_inclist_init(graph, &inclist, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_inclist_destroy, &inclist); IGRAPH_CHECK(igraph_inclist_remove_duplicate(graph, &inclist)); IGRAPH_CHECK(igraph_arpack_rssolve(igraph_i_eigenvector_centrality2, &data, options, 0, &values, &vectors)); igraph_inclist_destroy(&inclist); IGRAPH_FINALLY_CLEAN(1); } if (value) { *value = VECTOR(values)[0]; } if (vector) { igraph_real_t amax = 0; long int which = 0; long int i; IGRAPH_CHECK(igraph_vector_resize(vector, options->n)); if (VECTOR(values)[0] <= 0) { /* Pathological case: largest eigenvalue is zero, therefore all the * scores can also be zeros, this will be a valid eigenvector. * This usually happens with graphs that have lots of sinks and * sources only. */ igraph_vector_fill(vector, 0); } else { for (i = 0; i < options->n; i++) { igraph_real_t tmp; VECTOR(*vector)[i] = MATRIX(vectors, i, 0); tmp = fabs(VECTOR(*vector)[i]); if (tmp > amax) { amax = tmp; which = i; } } if (scale && amax != 0) { igraph_vector_scale(vector, 1 / VECTOR(*vector)[which]); } else if (igraph_i_vector_mostly_negative(vector)) { igraph_vector_scale(vector, -1.0); } /* Correction for numeric inaccuracies (eliminating -0.0) */ for (i = 0; i < options->n; i++) { if (VECTOR(*vector)[i] < 0) { VECTOR(*vector)[i] = 0; } } } } if (options->info) { IGRAPH_WARNING("Non-zero return code from ARPACK routine!"); } igraph_matrix_destroy(&vectors); igraph_vector_destroy(&values); IGRAPH_FINALLY_CLEAN(2); return 0; } /* int igraph_i_evcent_dir(igraph_real_t *to, const igraph_real_t *from, */ /* long int n, void *extra) { */ /* /\* TODO *\/ */ /* return 0; */ /* } */ /* int igraph_i_evcent_dir2(igraph_real_t *to, const igraph_real_t *from, */ /* long int n, void *extra) { */ /* /\* TODO *\/ */ /* return 0; */ /* } */ int igraph_eigenvector_centrality_directed(const igraph_t *graph, igraph_vector_t *vector, igraph_real_t *value, igraph_bool_t scale, const igraph_vector_t *weights, igraph_arpack_options_t *options) { igraph_matrix_t values; igraph_matrix_t vectors; igraph_vector_t indegree; igraph_bool_t dag; long int i; if (igraph_ecount(graph) == 0) { /* special case: empty graph */ if (value) { *value = 0; } if (vector) { igraph_vector_resize(vector, igraph_vcount(graph)); igraph_vector_fill(vector, 1); } return IGRAPH_SUCCESS; } /* Quick check: if the graph is a DAG, all the eigenvector centralities are * zeros, and so is the eigenvalue */ IGRAPH_CHECK(igraph_is_dag(graph, &dag)); if (dag) { /* special case: graph is a DAG */ IGRAPH_WARNING("graph is directed and acyclic; eigenvector centralities " "will be zeros"); if (value) { *value = 0; } if (vector) { igraph_vector_resize(vector, igraph_vcount(graph)); igraph_vector_fill(vector, 0); } return IGRAPH_SUCCESS; } if (weights) { igraph_real_t min, max; if (igraph_vector_size(weights) != igraph_ecount(graph)) { IGRAPH_ERROR("Invalid length of weights vector when calculating " "eigenvector centrality", IGRAPH_EINVAL); } if (igraph_is_directed(graph)) { IGRAPH_WARNING("Weighted directed graph in eigenvector centrality"); } IGRAPH_CHECK(igraph_vector_minmax(weights, &min, &max)); if (min < 0.0) { IGRAPH_WARNING("Negative weights, eigenpair might be complex"); } if (min == 0.0 && max == 0.0) { /* special case: all weights are zeros */ if (value) { *value = 0; } if (vector) { igraph_vector_resize(vector, igraph_vcount(graph)); igraph_vector_fill(vector, 1); } return IGRAPH_SUCCESS; } } options->n = igraph_vcount(graph); options->start = 1; options->nev = 1; options->ncv = 0; /* 0 means "automatic" in igraph_arpack_rnsolve */ /* LM mode is not OK here because +1 and -1 can be eigenvalues at the * same time, e.g.: a -> b -> a, c -> a */ options->which[0] = 'L' ; options->which[1] = 'R'; IGRAPH_MATRIX_INIT_FINALLY(&values, 0, 0); IGRAPH_MATRIX_INIT_FINALLY(&vectors, options->n, 1); IGRAPH_VECTOR_INIT_FINALLY(&indegree, options->n); IGRAPH_CHECK(igraph_strength(graph, &indegree, igraph_vss_all(), IGRAPH_IN, /*loops=*/ 1, weights)); RNG_BEGIN(); for (i = 0; i < options->n; i++) { if (VECTOR(indegree)[i]) { MATRIX(vectors, i, 0) = VECTOR(indegree)[i] + RNG_UNIF(-1e-4, 1e-4); } else { MATRIX(vectors, i, 0) = 1.0; } } RNG_END(); igraph_vector_destroy(&indegree); IGRAPH_FINALLY_CLEAN(1); if (!weights) { igraph_adjlist_t adjlist; IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist, IGRAPH_IN)); IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist); IGRAPH_CHECK(igraph_arpack_rnsolve(igraph_i_eigenvector_centrality, &adjlist, options, 0, &values, &vectors)); igraph_adjlist_destroy(&adjlist); IGRAPH_FINALLY_CLEAN(1); } else { igraph_inclist_t inclist; igraph_i_eigenvector_centrality_t data = { graph, &inclist, weights }; IGRAPH_CHECK(igraph_inclist_init(graph, &inclist, IGRAPH_IN)); IGRAPH_FINALLY(igraph_inclist_destroy, &inclist); IGRAPH_CHECK(igraph_arpack_rnsolve(igraph_i_eigenvector_centrality2, &data, options, 0, &values, &vectors)); igraph_inclist_destroy(&inclist); IGRAPH_FINALLY_CLEAN(1); } if (value) { *value = MATRIX(values, 0, 0); } if (vector) { igraph_real_t amax = 0; long int which = 0; long int i; IGRAPH_CHECK(igraph_vector_resize(vector, options->n)); if (MATRIX(values, 0, 0) <= 0) { /* Pathological case: largest eigenvalue is zero, therefore all the * scores can also be zeros, this will be a valid eigenvector. * This usually happens with graphs that have lots of sinks and * sources only. */ igraph_vector_fill(vector, 0); MATRIX(values, 0, 0) = 0; } else { for (i = 0; i < options->n; i++) { igraph_real_t tmp; VECTOR(*vector)[i] = MATRIX(vectors, i, 0); tmp = fabs(VECTOR(*vector)[i]); if (tmp > amax) { amax = tmp; which = i; } } if (scale && amax != 0) { igraph_vector_scale(vector, 1 / VECTOR(*vector)[which]); } else if (igraph_i_vector_mostly_negative(vector)) { igraph_vector_scale(vector, -1.0); } } /* Correction for numeric inaccuracies (eliminating -0.0) */ for (i = 0; i < options->n; i++) { if (VECTOR(*vector)[i] < 0) { VECTOR(*vector)[i] = 0; } } } if (options->info) { IGRAPH_WARNING("Non-zero return code from ARPACK routine!"); } igraph_matrix_destroy(&vectors); igraph_matrix_destroy(&values); IGRAPH_FINALLY_CLEAN(2); return 0; } /** * \function igraph_eigenvector_centrality * Eigenvector centrality of the vertices * * Eigenvector centrality is a measure of the importance of a node in a * network. It assigns relative scores to all nodes in the network based * on the principle that connections to high-scoring nodes contribute * more to the score of the node in question than equal connections to * low-scoring nodes. In practice, this is determined by calculating the * eigenvector corresponding to the largest positive eigenvalue of the * adjacency matrix. The centrality scores returned by igraph are always * normalized such that the largest eigenvector centrality score is one * (with one exception, see below). * * * Since the eigenvector centrality scores of nodes in different components * do not affect each other, it may be beneficial for large graphs to * decompose it first into weakly connected components and calculate the * centrality scores individually for each component. * * * Also note that the adjacency matrix of a directed acyclic graph or the * adjacency matrix of an empty graph does not possess positive eigenvalues, * therefore the eigenvector centrality is not defined for these graphs. * igraph will return an eigenvalue of zero in such cases. The eigenvector * centralities will all be equal for an empty graph and will all be zeros * for a directed acyclic graph. Such pathological cases can be detected * by asking igraph to calculate the eigenvalue as well (using the \p value * parameter, see below) and checking whether the eigenvalue is very close * to zero. * * \param graph The input graph. It might be directed. * \param vector Pointer to an initialized vector, it will be resized * as needed. The result of the computation is stored here. It can * be a null pointer, then it is ignored. * \param value If not a null pointer, then the eigenvalue * corresponding to the found eigenvector is stored here. * \param directed Boolean scalar, whether to consider edge directions * in a directed graph. It is ignored for undirected graphs. * \param scale If not zero then the result will be scaled such that * the absolute value of the maximum centrality is one. * \param weights A null pointer (=no edge weights), or a vector * giving the weights of the edges. The algorithm might result * complex numbers is some weights are negative. In this case only * the real part is reported. * \param options Options to ARPACK. See \ref igraph_arpack_options_t * for details. Note that the function overwrites the * n (number of vertices) parameter and * it always starts the calculation from a non-random vector * calculated based on the degree of the vertices. * \return Error code. * * Time complexity: depends on the input graph, usually it is O(|V|+|E|). * * \sa \ref igraph_pagerank and \ref igraph_personalized_pagerank for * modifications of eigenvector centrality. * * \example examples/simple/eigenvector_centrality.c */ int igraph_eigenvector_centrality(const igraph_t *graph, igraph_vector_t *vector, igraph_real_t *value, igraph_bool_t directed, igraph_bool_t scale, const igraph_vector_t *weights, igraph_arpack_options_t *options) { if (directed && igraph_is_directed(graph)) { return igraph_eigenvector_centrality_directed(graph, vector, value, scale, weights, options); } else { return igraph_eigenvector_centrality_undirected(graph, vector, value, scale, weights, options); } } /* struct for the unweighted variant of the HITS algorithm */ typedef struct igraph_i_kleinberg_data_t { igraph_adjlist_t *in; igraph_adjlist_t *out; igraph_vector_t *tmp; } igraph_i_kleinberg_data_t; /* struct for the weighted variant of the HITS algorithm */ typedef struct igraph_i_kleinberg_data2_t { const igraph_t *graph; igraph_inclist_t *in; igraph_inclist_t *out; igraph_vector_t *tmp; const igraph_vector_t *weights; } igraph_i_kleinberg_data2_t; /* ARPACK auxiliary routine for the unweighted HITS algorithm */ int igraph_i_kleinberg_unweighted(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_i_kleinberg_data_t *data = (igraph_i_kleinberg_data_t*)extra; igraph_adjlist_t *in = data->in; igraph_adjlist_t *out = data->out; igraph_vector_t *tmp = data->tmp; igraph_vector_int_t *neis; long int i, j, nlen; for (i = 0; i < n; i++) { neis = igraph_adjlist_get(in, i); nlen = igraph_vector_int_size(neis); VECTOR(*tmp)[i] = 0.0; for (j = 0; j < nlen; j++) { long int nei = (long int) VECTOR(*neis)[j]; VECTOR(*tmp)[i] += from[nei]; } } for (i = 0; i < n; i++) { neis = igraph_adjlist_get(out, i); nlen = igraph_vector_int_size(neis); to[i] = 0.0; for (j = 0; j < nlen; j++) { long int nei = (long int) VECTOR(*neis)[j]; to[i] += VECTOR(*tmp)[nei]; } } return 0; } /* ARPACK auxiliary routine for the weighted HITS algorithm */ int igraph_i_kleinberg_weighted(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_i_kleinberg_data2_t *data = (igraph_i_kleinberg_data2_t*)extra; igraph_inclist_t *in = data->in; igraph_inclist_t *out = data->out; igraph_vector_t *tmp = data->tmp; const igraph_vector_t *weights = data->weights; const igraph_t *g = data->graph; igraph_vector_int_t *neis; long int i, j, nlen; for (i = 0; i < n; i++) { neis = igraph_inclist_get(in, i); nlen = igraph_vector_int_size(neis); VECTOR(*tmp)[i] = 0.0; for (j = 0; j < nlen; j++) { long int nei_edge = (long int) VECTOR(*neis)[j]; long int nei = IGRAPH_OTHER(g, nei_edge, i); VECTOR(*tmp)[i] += from[nei] * VECTOR(*weights)[nei_edge]; } } for (i = 0; i < n; i++) { neis = igraph_inclist_get(out, i); nlen = igraph_vector_int_size(neis); to[i] = 0.0; for (j = 0; j < nlen; j++) { long int nei_edge = (long int) VECTOR(*neis)[j]; long int nei = IGRAPH_OTHER(g, nei_edge, i); to[i] += VECTOR(*tmp)[nei] * VECTOR(*weights)[nei_edge]; } } return 0; } int igraph_i_kleinberg(const igraph_t *graph, igraph_vector_t *vector, igraph_real_t *value, igraph_bool_t scale, const igraph_vector_t *weights, igraph_arpack_options_t *options, int inout) { igraph_adjlist_t myinadjlist, myoutadjlist; igraph_inclist_t myininclist, myoutinclist; igraph_adjlist_t *inadjlist, *outadjlist; igraph_inclist_t *ininclist, *outinclist; igraph_vector_t tmp; igraph_vector_t values; igraph_matrix_t vectors; igraph_i_kleinberg_data_t extra; igraph_i_kleinberg_data2_t extra2; long int i; if (igraph_ecount(graph) == 0 || igraph_vcount(graph) == 1) { /* special case: empty graph or single vertex */ if (value) { *value = igraph_ecount(graph) ? 1.0 : IGRAPH_NAN; } if (vector) { igraph_vector_resize(vector, igraph_vcount(graph)); igraph_vector_fill(vector, 1); } return IGRAPH_SUCCESS; } if (weights) { igraph_real_t min, max; if (igraph_vector_size(weights) != igraph_ecount(graph)) { IGRAPH_ERROR("Invalid length of weights vector when calculating " "hub or authority scores", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_vector_minmax(weights, &min, &max)); if (min == 0 && max == 0) { /* special case: all weights are zeros */ if (value) { *value = IGRAPH_NAN; } if (vector) { igraph_vector_resize(vector, igraph_vcount(graph)); igraph_vector_fill(vector, 1); } return IGRAPH_SUCCESS; } } options->n = igraph_vcount(graph); options->start = 1; /* no random start vector */ IGRAPH_VECTOR_INIT_FINALLY(&values, 0); IGRAPH_MATRIX_INIT_FINALLY(&vectors, options->n, 1); IGRAPH_VECTOR_INIT_FINALLY(&tmp, options->n); if (inout == 0) { inadjlist = &myinadjlist; outadjlist = &myoutadjlist; ininclist = &myininclist; outinclist = &myoutinclist; } else if (inout == 1) { inadjlist = &myoutadjlist; outadjlist = &myinadjlist; ininclist = &myoutinclist; outinclist = &myininclist; } else { /* This should not happen */ IGRAPH_ERROR("Invalid 'inout' argument, please do not call " "this function directly", IGRAPH_FAILURE); } if (weights == 0) { IGRAPH_CHECK(igraph_adjlist_init(graph, &myinadjlist, IGRAPH_IN)); IGRAPH_FINALLY(igraph_adjlist_destroy, &myinadjlist); IGRAPH_CHECK(igraph_adjlist_init(graph, &myoutadjlist, IGRAPH_OUT)); IGRAPH_FINALLY(igraph_adjlist_destroy, &myoutadjlist); } else { IGRAPH_CHECK(igraph_inclist_init(graph, &myininclist, IGRAPH_IN)); IGRAPH_FINALLY(igraph_inclist_destroy, &myininclist); IGRAPH_CHECK(igraph_inclist_init(graph, &myoutinclist, IGRAPH_OUT)); IGRAPH_FINALLY(igraph_inclist_destroy, &myoutinclist); } IGRAPH_CHECK(igraph_degree(graph, &tmp, igraph_vss_all(), IGRAPH_ALL, 0)); for (i = 0; i < options->n; i++) { if (VECTOR(tmp)[i] != 0) { MATRIX(vectors, i, 0) = VECTOR(tmp)[i]; } else { MATRIX(vectors, i, 0) = 1.0; } } extra.in = inadjlist; extra.out = outadjlist; extra.tmp = &tmp; extra2.in = ininclist; extra2.out = outinclist; extra2.tmp = &tmp; extra2.graph = graph; extra2.weights = weights; options->nev = 1; options->ncv = 0; /* 0 means "automatic" in igraph_arpack_rssolve */ options->which[0] = 'L'; options->which[1] = 'M'; if (weights == 0) { IGRAPH_CHECK(igraph_arpack_rssolve(igraph_i_kleinberg_unweighted, &extra, options, 0, &values, &vectors)); igraph_adjlist_destroy(&myoutadjlist); igraph_adjlist_destroy(&myinadjlist); IGRAPH_FINALLY_CLEAN(2); } else { IGRAPH_CHECK(igraph_arpack_rssolve(igraph_i_kleinberg_weighted, &extra2, options, 0, &values, &vectors)); igraph_inclist_destroy(&myoutinclist); igraph_inclist_destroy(&myininclist); IGRAPH_FINALLY_CLEAN(2); } igraph_vector_destroy(&tmp); IGRAPH_FINALLY_CLEAN(1); if (value) { *value = VECTOR(values)[0]; } if (vector) { igraph_real_t amax = 0; long int which = 0; long int i; IGRAPH_CHECK(igraph_vector_resize(vector, options->n)); for (i = 0; i < options->n; i++) { igraph_real_t tmp; VECTOR(*vector)[i] = MATRIX(vectors, i, 0); tmp = fabs(VECTOR(*vector)[i]); if (tmp > amax) { amax = tmp; which = i; } } if (scale && amax != 0) { igraph_vector_scale(vector, 1 / VECTOR(*vector)[which]); } else if (igraph_i_vector_mostly_negative(vector)) { igraph_vector_scale(vector, -1.0); } /* Correction for numeric inaccuracies (eliminating -0.0) */ for (i = 0; i < options->n; i++) { if (VECTOR(*vector)[i] < 0) { VECTOR(*vector)[i] = 0; } } } if (options->info) { IGRAPH_WARNING("Non-zero return code from ARPACK routine!"); } igraph_matrix_destroy(&vectors); igraph_vector_destroy(&values); IGRAPH_FINALLY_CLEAN(2); return 0; } /** * \function igraph_hub_score * Kleinberg's hub scores * * The hub scores of the vertices are defined as the principal * eigenvector of A*A^T, where A is the adjacency * matrix of the graph, A^T is its transposed. * * See the following reference on the meaning of this score: * J. Kleinberg. Authoritative sources in a hyperlinked * environment. \emb Proc. 9th ACM-SIAM Symposium on Discrete * Algorithms, \eme 1998. Extended version in \emb Journal of the * ACM \eme 46(1999). Also appears as IBM Research Report RJ 10076, May * 1997. * \param graph The input graph. Can be directed and undirected. * \param vector Pointer to an initialized vector, the result is * stored here. If a null pointer then it is ignored. * \param value If not a null pointer then the eigenvalue * corresponding to the calculated eigenvector is stored here. * \param scale If not zero then the result will be scaled such that * the absolute value of the maximum centrality is one. * \param weights A null pointer (=no edge weights), or a vector * giving the weights of the edges. * \param options Options to ARPACK. See \ref igraph_arpack_options_t * for details. Note that the function overwrites the * n (number of vertices) parameter and * it always starts the calculation from a non-random vector * calculated based on the degree of the vertices. * \return Error code. * * Time complexity: depends on the input graph, usually it is O(|V|), * the number of vertices. * * \sa \ref igraph_authority_score() for the companion measure, * \ref igraph_pagerank(), \ref igraph_personalized_pagerank(), * \ref igraph_eigenvector_centrality() for similar measures. */ int igraph_hub_score(const igraph_t *graph, igraph_vector_t *vector, igraph_real_t *value, igraph_bool_t scale, const igraph_vector_t *weights, igraph_arpack_options_t *options) { return igraph_i_kleinberg(graph, vector, value, scale, weights, options, 0); } /** * \function igraph_authority_score * Kleinerg's authority scores * * The authority scores of the vertices are defined as the principal * eigenvector of A^T*A, where A is the adjacency * matrix of the graph, A^T is its transposed. * * See the following reference on the meaning of this score: * J. Kleinberg. Authoritative sources in a hyperlinked * environment. \emb Proc. 9th ACM-SIAM Symposium on Discrete * Algorithms, \eme 1998. Extended version in \emb Journal of the * ACM \eme 46(1999). Also appears as IBM Research Report RJ 10076, May * 1997. * \param graph The input graph. Can be directed and undirected. * \param vector Pointer to an initialized vector, the result is * stored here. If a null pointer then it is ignored. * \param value If not a null pointer then the eigenvalue * corresponding to the calculated eigenvector is stored here. * \param scale If not zero then the result will be scaled such that * the absolute value of the maximum centrality is one. * \param weights A null pointer (=no edge weights), or a vector * giving the weights of the edges. * \param options Options to ARPACK. See \ref igraph_arpack_options_t * for details. Note that the function overwrites the * n (number of vertices) parameter and * it always starts the calculation from a non-random vector * calculated based on the degree of the vertices. * \return Error code. * * Time complexity: depends on the input graph, usually it is O(|V|), * the number of vertices. * * \sa \ref igraph_hub_score() for the companion measure, * \ref igraph_pagerank(), \ref igraph_personalized_pagerank(), * \ref igraph_eigenvector_centrality() for similar measures. */ int igraph_authority_score(const igraph_t *graph, igraph_vector_t *vector, igraph_real_t *value, igraph_bool_t scale, const igraph_vector_t *weights, igraph_arpack_options_t *options) { return igraph_i_kleinberg(graph, vector, value, scale, weights, options, 1); } typedef struct igraph_i_pagerank_data_t { const igraph_t *graph; igraph_adjlist_t *adjlist; igraph_real_t damping; igraph_vector_t *outdegree; igraph_vector_t *tmp; igraph_vector_t *reset; } igraph_i_pagerank_data_t; typedef struct igraph_i_pagerank_data2_t { const igraph_t *graph; igraph_inclist_t *inclist; const igraph_vector_t *weights; igraph_real_t damping; igraph_vector_t *outdegree; igraph_vector_t *tmp; igraph_vector_t *reset; } igraph_i_pagerank_data2_t; int igraph_i_pagerank(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_i_pagerank_data_t *data = extra; igraph_adjlist_t *adjlist = data->adjlist; igraph_vector_t *outdegree = data->outdegree; igraph_vector_t *tmp = data->tmp; igraph_vector_t *reset = data->reset; igraph_vector_int_t *neis; long int i, j, nlen; igraph_real_t sumfrom = 0.0; igraph_real_t fact = 1 - data->damping; /* Calculate p(x) / outdegree(x) in advance for all the vertices. * Note that we may divide by zero here; this is intentional since * we won't use those values and we save a comparison this way. * At the same time, we calculate the global probability of a * random jump in `sumfrom`. For vertices with no outgoing edges, * we will surely jump from there if we are there, hence those * vertices contribute p(x) to the teleportation probability. * For vertices with some outgoing edges, we jump from there with * probability `fact` if we are there, hence they contribute * p(x)*fact */ for (i = 0; i < n; i++) { sumfrom += VECTOR(*outdegree)[i] != 0 ? from[i] * fact : from[i]; VECTOR(*tmp)[i] = from[i] / VECTOR(*outdegree)[i]; } /* Here we calculate the part of the `to` vector that results from * moving along links (and not from teleportation) */ for (i = 0; i < n; i++) { neis = igraph_adjlist_get(adjlist, i); nlen = igraph_vector_int_size(neis); to[i] = 0.0; for (j = 0; j < nlen; j++) { long int nei = (long int) VECTOR(*neis)[j]; to[i] += VECTOR(*tmp)[nei]; } to[i] *= data->damping; } /* Now we add the contribution from random jumps. `reset` is a vector * that defines the probability of ending up in vertex i after a jump. * `sumfrom` is the global probability of jumping as mentioned above. */ /* printf("sumfrom = %.6f\n", (float)sumfrom); */ if (reset) { /* Running personalized PageRank */ for (i = 0; i < n; i++) { to[i] += sumfrom * VECTOR(*reset)[i]; } } else { /* Traditional PageRank with uniform reset vector */ sumfrom /= n; for (i = 0; i < n; i++) { to[i] += sumfrom; } } return 0; } int igraph_i_pagerank2(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_i_pagerank_data2_t *data = extra; const igraph_t *graph = data->graph; igraph_inclist_t *inclist = data->inclist; const igraph_vector_t *weights = data->weights; igraph_vector_t *outdegree = data->outdegree; igraph_vector_t *tmp = data->tmp; igraph_vector_t *reset = data->reset; long int i, j, nlen; igraph_real_t sumfrom = 0.0; igraph_vector_int_t *neis; igraph_real_t fact = 1 - data->damping; /* printf("PageRank weighted: multiplying vector: "); for (i=0; idamping; } /* printf("sumfrom = %.6f\n", (float)sumfrom); */ if (reset) { /* Running personalized PageRank */ for (i = 0; i < n; i++) { to[i] += sumfrom * VECTOR(*reset)[i]; } } else { /* Traditional PageRank with uniform reset vector */ sumfrom /= n; for (i = 0; i < n; i++) { to[i] += sumfrom; } } /* printf("PageRank weighted: multiplied vector: "); for (i=0; i * Please note that the PageRank of a given vertex depends on the PageRank * of all other vertices, so even if you want to calculate the PageRank for * only some of the vertices, all of them must be calculated. Requesting * the PageRank for only some of the vertices does not result in any * performance increase at all. * * * * For the explanation of the PageRank algorithm, see the following * webpage: * http://infolab.stanford.edu/~backrub/google.html , or the * following reference: * * * * Sergey Brin and Larry Page: The Anatomy of a Large-Scale Hypertextual * Web Search Engine. Proceedings of the 7th World-Wide Web Conference, * Brisbane, Australia, April 1998. * * * \param graph The graph object. * \param algo The PageRank implementation to use. Possible values: * \c IGRAPH_PAGERANK_ALGO_POWER, \c IGRAPH_PAGERANK_ALGO_ARPACK, * \c IGRAPH_PAGERANK_ALGO_PRPACK. * \param vector Pointer to an initialized vector, the result is * stored here. It is resized as needed. * \param value Pointer to a real variable, the eigenvalue * corresponding to the PageRank vector is stored here. It should * be always exactly one. * \param vids The vertex ids for which the PageRank is returned. * \param directed Boolean, whether to consider the directedness of * the edges. This is ignored for undirected graphs. * \param damping The damping factor ("d" in the original paper) * \param weights Optional edge weights, it is either a null pointer, * then the edges are not weighted, or a vector of the same length * as the number of edges. * \param options Options to the power method or ARPACK. For the power * method, \c IGRAPH_PAGERANK_ALGO_POWER it must be a pointer to * a \ref igraph_pagerank_power_options_t object. * For \c IGRAPH_PAGERANK_ALGO_ARPACK it must be a pointer to an * \ref igraph_arpack_options_t object. See \ref igraph_arpack_options_t * for details. Note that the function overwrites the * n (number of vertices), nev (1), * ncv (3) and which (LM) parameters and * it always starts the calculation from a non-random vector * calculated based on the degree of the vertices. * \return Error code: * \c IGRAPH_ENOMEM, not enough memory for * temporary data. * \c IGRAPH_EINVVID, invalid vertex id in * \p vids. * * Time complexity: depends on the input graph, usually it is O(|E|), * the number of edges. * * \sa \ref igraph_pagerank_old() for the old implementation, * \ref igraph_personalized_pagerank() and \ref igraph_personalized_pagerank_vs() * for the personalized PageRank measure, \ref igraph_arpack_rssolve() and * \ref igraph_arpack_rnsolve() for the underlying machinery. * * \example examples/simple/igraph_pagerank.c */ int igraph_pagerank(const igraph_t *graph, igraph_pagerank_algo_t algo, igraph_vector_t *vector, igraph_real_t *value, const igraph_vs_t vids, igraph_bool_t directed, igraph_real_t damping, const igraph_vector_t *weights, void *options) { return igraph_personalized_pagerank(graph, algo, vector, value, vids, directed, damping, 0, weights, options); } /** * \function igraph_personalized_pagerank_vs * \brief Calculates the personalized Google PageRank for the specified vertices. * * The personalized PageRank is similar to the original PageRank measure, but the * random walk is reset in every step with probability 1-damping to a non-uniform * distribution (instead of the uniform distribution in the original PageRank measure. * * * This simplified interface takes a vertex sequence and resets the random walk to * one of the vertices in the specified vertex sequence, chosen uniformly. A typical * application of personalized PageRank is when the random walk is reset to the same * vertex every time - this can easily be achieved using \ref igraph_vss_1() which * generates a vertex sequence containing only a single vertex. * * * Please note that the personalized PageRank of a given vertex depends on the * personalized PageRank of all other vertices, so even if you want to calculate * the personalized PageRank for only some of the vertices, all of them must be * calculated. Requesting the personalized PageRank for only some of the vertices * does not result in any performance increase at all. * * * * \param graph The graph object. * \param algo The PageRank implementation to use. Possible values: * \c IGRAPH_PAGERANK_ALGO_POWER, \c IGRAPH_PAGERANK_ALGO_ARPACK, * \c IGRAPH_PAGERANK_ALGO_PRPACK. * \param vector Pointer to an initialized vector, the result is * stored here. It is resized as needed. * \param value Pointer to a real variable, the eigenvalue * corresponding to the PageRank vector is stored here. It should * be always exactly one. * \param vids The vertex ids for which the PageRank is returned. * \param directed Boolean, whether to consider the directedness of * the edges. This is ignored for undirected graphs. * \param damping The damping factor ("d" in the original paper) * \param reset_vids IDs of the vertices used when resetting the random walk. * \param weights Optional edge weights, it is either a null pointer, * then the edges are not weighted, or a vector of the same length * as the number of edges. * \param options Options to the power method or ARPACK. For the power * method, \c IGRAPH_PAGERANK_ALGO_POWER it must be a pointer to * a \ref igraph_pagerank_power_options_t object. * For \c IGRAPH_PAGERANK_ALGO_ARPACK it must be a pointer to an * \ref igraph_arpack_options_t object. See \ref igraph_arpack_options_t * for details. Note that the function overwrites the * n (number of vertices), nev (1), * ncv (3) and which (LM) parameters and * it always starts the calculation from a non-random vector * calculated based on the degree of the vertices. * \return Error code: * \c IGRAPH_ENOMEM, not enough memory for * temporary data. * \c IGRAPH_EINVVID, invalid vertex id in * \p vids or an empty reset vertex sequence in * \p vids_reset. * * Time complexity: depends on the input graph, usually it is O(|E|), * the number of edges. * * \sa \ref igraph_pagerank() for the non-personalized implementation, * \ref igraph_arpack_rssolve() and \ref igraph_arpack_rnsolve() for * the underlying machinery. */ int igraph_personalized_pagerank_vs(const igraph_t *graph, igraph_pagerank_algo_t algo, igraph_vector_t *vector, igraph_real_t *value, const igraph_vs_t vids, igraph_bool_t directed, igraph_real_t damping, igraph_vs_t reset_vids, const igraph_vector_t *weights, void *options) { igraph_vector_t reset; igraph_vit_t vit; IGRAPH_VECTOR_INIT_FINALLY(&reset, igraph_vcount(graph)); IGRAPH_CHECK(igraph_vit_create(graph, reset_vids, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); while (!IGRAPH_VIT_END(vit)) { VECTOR(reset)[(long int)IGRAPH_VIT_GET(vit)]++; IGRAPH_VIT_NEXT(vit); } igraph_vit_destroy(&vit); IGRAPH_FINALLY_CLEAN(1); IGRAPH_CHECK(igraph_personalized_pagerank(graph, algo, vector, value, vids, directed, damping, &reset, weights, options)); igraph_vector_destroy(&reset); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_personalized_pagerank * \brief Calculates the personalized Google PageRank for the specified vertices. * * The personalized PageRank is similar to the original PageRank measure, but the * random walk is reset in every step with probability 1-damping to a non-uniform * distribution (instead of the uniform distribution in the original PageRank measure. * * * Please note that the personalized PageRank of a given vertex depends on the * personalized PageRank of all other vertices, so even if you want to calculate * the personalized PageRank for only some of the vertices, all of them must be * calculated. Requesting the personalized PageRank for only some of the vertices * does not result in any performance increase at all. * * * * \param graph The graph object. * \param algo The PageRank implementation to use. Possible values: * \c IGRAPH_PAGERANK_ALGO_POWER, \c IGRAPH_PAGERANK_ALGO_ARPACK, * \c IGRAPH_PAGERANK_ALGO_PRPACK. * \param vector Pointer to an initialized vector, the result is * stored here. It is resized as needed. * \param value Pointer to a real variable, the eigenvalue * corresponding to the PageRank vector is stored here. It should * be always exactly one. * \param vids The vertex ids for which the PageRank is returned. * \param directed Boolean, whether to consider the directedness of * the edges. This is ignored for undirected graphs. * \param damping The damping factor ("d" in the original paper) * \param reset The probability distribution over the vertices used when * resetting the random walk. It is either a null pointer (denoting * a uniform choice that results in the original PageRank measure) * or a vector of the same length as the number of vertices. * \param weights Optional edge weights, it is either a null pointer, * then the edges are not weighted, or a vector of the same length * as the number of edges. * \param options Options to the power method or ARPACK. For the power * method, \c IGRAPH_PAGERANK_ALGO_POWER it must be a pointer to * a \ref igraph_pagerank_power_options_t object. * For \c IGRAPH_PAGERANK_ALGO_ARPACK it must be a pointer to an * \ref igraph_arpack_options_t object. See \ref igraph_arpack_options_t * for details. Note that the function overwrites the * n (number of vertices), nev (1), * ncv (3) and which (LM) parameters and * it always starts the calculation from a non-random vector * calculated based on the degree of the vertices. * \return Error code: * \c IGRAPH_ENOMEM, not enough memory for * temporary data. * \c IGRAPH_EINVVID, invalid vertex id in * \p vids or an invalid reset vector in \p reset. * * Time complexity: depends on the input graph, usually it is O(|E|), * the number of edges. * * \sa \ref igraph_pagerank() for the non-personalized implementation, * \ref igraph_arpack_rssolve() and \ref igraph_arpack_rnsolve() for * the underlying machinery. */ int igraph_personalized_pagerank(const igraph_t *graph, igraph_pagerank_algo_t algo, igraph_vector_t *vector, igraph_real_t *value, const igraph_vs_t vids, igraph_bool_t directed, igraph_real_t damping, igraph_vector_t *reset, const igraph_vector_t *weights, void *options) { if (algo == IGRAPH_PAGERANK_ALGO_POWER) { igraph_pagerank_power_options_t *o = (igraph_pagerank_power_options_t *) options; if (reset) { IGRAPH_WARNING("Cannot use weights with power method, " "weights will be ignored"); } return igraph_pagerank_old(graph, vector, vids, directed, o->niter, o->eps, damping, /*old=*/ 0); } else if (algo == IGRAPH_PAGERANK_ALGO_ARPACK) { igraph_arpack_options_t *o = (igraph_arpack_options_t*) options; return igraph_personalized_pagerank_arpack(graph, vector, value, vids, directed, damping, reset, weights, o); } else if (algo == IGRAPH_PAGERANK_ALGO_PRPACK) { return igraph_personalized_pagerank_prpack(graph, vector, value, vids, directed, damping, reset, weights); } else { IGRAPH_ERROR("Unknown PageRank algorithm", IGRAPH_EINVAL); } return 0; } /* * ARPACK-based implementation of \c igraph_personalized_pagerank. * * See \c igraph_personalized_pagerank for the documentation of the parameters. */ int igraph_personalized_pagerank_arpack(const igraph_t *graph, igraph_vector_t *vector, igraph_real_t *value, const igraph_vs_t vids, igraph_bool_t directed, igraph_real_t damping, igraph_vector_t *reset, const igraph_vector_t *weights, igraph_arpack_options_t *options) { igraph_matrix_t values; igraph_matrix_t vectors; igraph_neimode_t dirmode; igraph_vector_t outdegree; igraph_vector_t indegree; igraph_vector_t tmp; long int i; long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); if (no_of_edges == 0) { /* special case: empty graph */ if (value) { *value = 1.0; } if (vector) { igraph_vector_resize(vector, no_of_nodes); igraph_vector_fill(vector, 1.0 / no_of_nodes); } return IGRAPH_SUCCESS; } options->n = (int) no_of_nodes; options->nev = 1; options->ncv = 0; /* 0 means "automatic" in igraph_arpack_rnsolve */ options->which[0] = 'L'; options->which[1] = 'M'; options->start = 1; /* no random start vector */ directed = directed && igraph_is_directed(graph); if (weights) { igraph_real_t min, max; if (igraph_vector_size(weights) != no_of_edges) { IGRAPH_ERROR("Invalid length of weights vector when calculating " "PageRank scores", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_vector_minmax(weights, &min, &max)); if (min == 0 && max == 0) { /* special case: all weights are zeros */ if (value) { *value = 1.0; } if (vector) { igraph_vector_resize(vector, igraph_vcount(graph)); igraph_vector_fill(vector, 1.0 / no_of_nodes); } return IGRAPH_SUCCESS; } } if (reset && igraph_vector_size(reset) != no_of_nodes) { IGRAPH_ERROR("Invalid length of reset vector when calculating " "personalized PageRank scores", IGRAPH_EINVAL); } IGRAPH_MATRIX_INIT_FINALLY(&values, 0, 0); IGRAPH_MATRIX_INIT_FINALLY(&vectors, options->n, 1); if (directed) { dirmode = IGRAPH_IN; } else { dirmode = IGRAPH_ALL; } IGRAPH_VECTOR_INIT_FINALLY(&indegree, options->n); IGRAPH_VECTOR_INIT_FINALLY(&outdegree, options->n); IGRAPH_VECTOR_INIT_FINALLY(&tmp, options->n); RNG_BEGIN(); if (reset) { /* Normalize reset vector so the sum is 1 */ double reset_sum; if (igraph_vector_min(reset) < 0) { IGRAPH_ERROR("the reset vector must not contain negative elements", IGRAPH_EINVAL); } reset_sum = igraph_vector_sum(reset); if (reset_sum == 0) { IGRAPH_ERROR("the sum of the elements in the reset vector must not be zero", IGRAPH_EINVAL); } igraph_vector_scale(reset, 1.0 / reset_sum); } if (!weights) { igraph_adjlist_t adjlist; igraph_i_pagerank_data_t data = { graph, &adjlist, damping, &outdegree, &tmp, reset }; IGRAPH_CHECK(igraph_degree(graph, &outdegree, igraph_vss_all(), directed ? IGRAPH_OUT : IGRAPH_ALL, /*loops=*/ 0)); IGRAPH_CHECK(igraph_degree(graph, &indegree, igraph_vss_all(), directed ? IGRAPH_IN : IGRAPH_ALL, /*loops=*/ 0)); /* Set up an appropriate starting vector. We start from the in-degrees * plus some small random noise to avoid convergence problems */ for (i = 0; i < options->n; i++) { if (VECTOR(indegree)[i]) { MATRIX(vectors, i, 0) = VECTOR(indegree)[i] + RNG_UNIF(-1e-4, 1e-4); } else { MATRIX(vectors, i, 0) = 1; } } IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist, dirmode)); IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist); IGRAPH_CHECK(igraph_arpack_rnsolve(igraph_i_pagerank, &data, options, 0, &values, &vectors)); igraph_adjlist_destroy(&adjlist); IGRAPH_FINALLY_CLEAN(1); } else { igraph_inclist_t inclist; igraph_bool_t negative_weight_warned = 0; igraph_i_pagerank_data2_t data = { graph, &inclist, weights, damping, &outdegree, &tmp, reset }; IGRAPH_CHECK(igraph_inclist_init(graph, &inclist, dirmode)); IGRAPH_FINALLY(igraph_inclist_destroy, &inclist); /* Weighted degree */ for (i = 0; i < no_of_edges; i++) { long int from = IGRAPH_FROM(graph, i); long int to = IGRAPH_TO(graph, i); igraph_real_t weight = VECTOR(*weights)[i]; if (weight < 0 && !negative_weight_warned) { IGRAPH_WARNING("replacing negative weights with zeros"); weight = 0; negative_weight_warned = 1; } VECTOR(outdegree)[from] += weight; VECTOR(indegree) [to] += weight; if (!directed) { VECTOR(outdegree)[to] += weight; VECTOR(indegree) [from] += weight; } } /* Set up an appropriate starting vector. We start from the in-degrees * plus some small random noise to avoid convergence problems */ for (i = 0; i < options->n; i++) { if (VECTOR(indegree)[i]) { MATRIX(vectors, i, 0) = VECTOR(indegree)[i] + RNG_UNIF(-1e-4, 1e-4); } else { MATRIX(vectors, i, 0) = 1; } } IGRAPH_CHECK(igraph_arpack_rnsolve(igraph_i_pagerank2, &data, options, 0, &values, &vectors)); igraph_inclist_destroy(&inclist); IGRAPH_FINALLY_CLEAN(1); } RNG_END(); igraph_vector_destroy(&tmp); igraph_vector_destroy(&outdegree); igraph_vector_destroy(&indegree); IGRAPH_FINALLY_CLEAN(3); if (value) { *value = MATRIX(values, 0, 0); } if (vector) { long int i; igraph_vit_t vit; long int nodes_to_calc; igraph_real_t sum = 0; for (i = 0; i < no_of_nodes; i++) { sum += MATRIX(vectors, i, 0); } IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); nodes_to_calc = IGRAPH_VIT_SIZE(vit); IGRAPH_CHECK(igraph_vector_resize(vector, nodes_to_calc)); for (IGRAPH_VIT_RESET(vit), i = 0; !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit), i++) { VECTOR(*vector)[i] = MATRIX(vectors, (long int)IGRAPH_VIT_GET(vit), 0); VECTOR(*vector)[i] /= sum; } igraph_vit_destroy(&vit); IGRAPH_FINALLY_CLEAN(1); } if (options->info) { IGRAPH_WARNING("Non-zero return code from ARPACK routine!"); } igraph_matrix_destroy(&vectors); igraph_matrix_destroy(&values); IGRAPH_FINALLY_CLEAN(2); return 0; } /** * \ingroup structural * \function igraph_betweenness * \brief Betweenness centrality of some vertices. * * * The betweenness centrality of a vertex is the number of geodesics * going through it. If there are more than one geodesic between two * vertices, the value of these geodesics are weighted by one over the * number of geodesics. * \param graph The graph object. * \param res The result of the computation, a vector containing the * betweenness scores for the specified vertices. * \param vids The vertices of which the betweenness centrality scores * will be calculated. * \param directed Logical, if true directed paths will be considered * for directed graphs. It is ignored for undirected graphs. * \param weights An optional vector containing edge weights for * calculating weighted betweenness. Supply a null pointer here * for unweighted betweenness. * \param nobigint Logical, if true, then we don't use big integers * for the calculation, setting this to 1 (=true) should * work for most graphs. It is currently ignored for weighted * graphs. * \return Error code: * \c IGRAPH_ENOMEM, not enough memory for * temporary data. * \c IGRAPH_EINVVID, invalid vertex id passed in * \p vids. * * Time complexity: O(|V||E|), * |V| and * |E| are the number of vertices and * edges in the graph. * Note that the time complexity is independent of the number of * vertices for which the score is calculated. * * \sa Other centrality types: \ref igraph_degree(), \ref igraph_closeness(). * See \ref igraph_edge_betweenness() for calculating the betweenness score * of the edges in a graph. See \ref igraph_betweenness_estimate() to * estimate the betweenness score of the vertices in a graph. * * \example examples/simple/igraph_betweenness.c */ int igraph_betweenness(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, igraph_bool_t directed, const igraph_vector_t* weights, igraph_bool_t nobigint) { return igraph_betweenness_estimate(graph, res, vids, directed, -1, weights, nobigint); } int igraph_i_betweenness_estimate_weighted(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, igraph_bool_t directed, igraph_real_t cutoff, const igraph_vector_t *weights, igraph_bool_t nobigint) { igraph_real_t minweight; igraph_integer_t no_of_nodes = (igraph_integer_t) igraph_vcount(graph); igraph_integer_t no_of_edges = (igraph_integer_t) igraph_ecount(graph); igraph_2wheap_t Q; igraph_inclist_t inclist; igraph_adjlist_t fathers; long int source, j; igraph_stack_t S; igraph_neimode_t mode = directed ? IGRAPH_OUT : IGRAPH_ALL; igraph_vector_t dist, nrgeo, tmpscore; igraph_vector_t v_tmpres, *tmpres = &v_tmpres; igraph_vit_t vit; int cmp_result; const double eps = IGRAPH_SHORTEST_PATH_EPSILON; IGRAPH_UNUSED(nobigint); if (igraph_vector_size(weights) != no_of_edges) { IGRAPH_ERROR("Weight vector length does not match", IGRAPH_EINVAL); } minweight = igraph_vector_min(weights); if (minweight <= 0) { IGRAPH_ERROR("Weight vector must be positive", IGRAPH_EINVAL); } else if (minweight <= eps) { IGRAPH_WARNING("Some weights are smaller than epsilon, calculations may suffer from numerical precision."); } IGRAPH_CHECK(igraph_2wheap_init(&Q, no_of_nodes)); IGRAPH_FINALLY(igraph_2wheap_destroy, &Q); IGRAPH_CHECK(igraph_inclist_init(graph, &inclist, mode)); IGRAPH_FINALLY(igraph_inclist_destroy, &inclist); IGRAPH_CHECK(igraph_adjlist_init_empty(&fathers, no_of_nodes)); IGRAPH_FINALLY(igraph_adjlist_destroy, &fathers); IGRAPH_CHECK(igraph_stack_init(&S, no_of_nodes)); IGRAPH_FINALLY(igraph_stack_destroy, &S); IGRAPH_VECTOR_INIT_FINALLY(&dist, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&tmpscore, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&nrgeo, no_of_nodes); if (igraph_vs_is_all(&vids)) { IGRAPH_CHECK(igraph_vector_resize(res, no_of_nodes)); igraph_vector_null(res); tmpres = res; } else { IGRAPH_VECTOR_INIT_FINALLY(tmpres, no_of_nodes); } for (source = 0; source < no_of_nodes; source++) { IGRAPH_PROGRESS("Betweenness centrality: ", 100.0 * source / no_of_nodes, 0); IGRAPH_ALLOW_INTERRUPTION(); igraph_2wheap_push_with_index(&Q, source, -1.0); VECTOR(dist)[source] = 1.0; VECTOR(nrgeo)[source] = 1; while (!igraph_2wheap_empty(&Q)) { long int minnei = igraph_2wheap_max_index(&Q); igraph_real_t mindist = -igraph_2wheap_delete_max(&Q); igraph_vector_int_t *neis; long int nlen; igraph_stack_push(&S, minnei); if (cutoff > 0 && VECTOR(dist)[minnei] >= cutoff + 1.0) { continue; } /* Now check all neighbors of 'minnei' for a shorter path */ neis = igraph_inclist_get(&inclist, minnei); nlen = igraph_vector_int_size(neis); for (j = 0; j < nlen; j++) { long int edge = (long int) VECTOR(*neis)[j]; long int to = IGRAPH_OTHER(graph, edge, minnei); igraph_real_t altdist = mindist + VECTOR(*weights)[edge]; igraph_real_t curdist = VECTOR(dist)[to]; if (curdist == 0) { /* this means curdist is infinity */ cmp_result = -1; } else { cmp_result = igraph_cmp_epsilon(altdist, curdist, eps); } if (curdist == 0) { /* This is the first non-infinite distance */ igraph_vector_int_t *v = igraph_adjlist_get(&fathers, to); igraph_vector_int_resize(v, 1); VECTOR(*v)[0] = minnei; VECTOR(nrgeo)[to] = VECTOR(nrgeo)[minnei]; VECTOR(dist)[to] = altdist; IGRAPH_CHECK(igraph_2wheap_push_with_index(&Q, to, -altdist)); } else if (cmp_result < 0) { /* This is a shorter path */ igraph_vector_int_t *v = igraph_adjlist_get(&fathers, to); igraph_vector_int_resize(v, 1); VECTOR(*v)[0] = minnei; VECTOR(nrgeo)[to] = VECTOR(nrgeo)[minnei]; VECTOR(dist)[to] = altdist; IGRAPH_CHECK(igraph_2wheap_modify(&Q, to, -altdist)); } else if (cmp_result == 0) { igraph_vector_int_t *v = igraph_adjlist_get(&fathers, to); igraph_vector_int_push_back(v, minnei); VECTOR(nrgeo)[to] += VECTOR(nrgeo)[minnei]; } } } /* !igraph_2wheap_empty(&Q) */ while (!igraph_stack_empty(&S)) { long int w = (long int) igraph_stack_pop(&S); igraph_vector_int_t *fatv = igraph_adjlist_get(&fathers, w); long int fatv_len = igraph_vector_int_size(fatv); for (j = 0; j < fatv_len; j++) { long int f = (long int) VECTOR(*fatv)[j]; VECTOR(tmpscore)[f] += VECTOR(nrgeo)[f] / VECTOR(nrgeo)[w] * (1 + VECTOR(tmpscore)[w]); } if (w != source) { VECTOR(*tmpres)[w] += VECTOR(tmpscore)[w]; } VECTOR(tmpscore)[w] = 0; VECTOR(dist)[w] = 0; VECTOR(nrgeo)[w] = 0; igraph_vector_int_clear(igraph_adjlist_get(&fathers, w)); } } /* source < no_of_nodes */ if (!igraph_vs_is_all(&vids)) { IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); IGRAPH_CHECK(igraph_vector_resize(res, IGRAPH_VIT_SIZE(vit))); for (j = 0, IGRAPH_VIT_RESET(vit); !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit), j++) { long int node = IGRAPH_VIT_GET(vit); VECTOR(*res)[j] = VECTOR(*tmpres)[node]; } no_of_nodes = (igraph_integer_t) j; igraph_vit_destroy(&vit); igraph_vector_destroy(tmpres); IGRAPH_FINALLY_CLEAN(2); } if (!directed || !igraph_is_directed(graph)) { for (j = 0; j < no_of_nodes; j++) { VECTOR(*res)[j] /= 2.0; } } IGRAPH_PROGRESS("Betweenness centrality: ", 100.0, 0); igraph_vector_destroy(&nrgeo); igraph_vector_destroy(&tmpscore); igraph_vector_destroy(&dist); igraph_stack_destroy(&S); igraph_adjlist_destroy(&fathers); igraph_inclist_destroy(&inclist); igraph_2wheap_destroy(&Q); IGRAPH_FINALLY_CLEAN(7); return 0; } void igraph_i_destroy_biguints(igraph_biguint_t *p) { igraph_biguint_t *p2 = p; while ( *((long int*)(p)) ) { igraph_biguint_destroy(p); p++; } igraph_Free(p2); } /** * \ingroup structural * \function igraph_betweenness_estimate * \brief Estimated betweenness centrality of some vertices. * * * The betweenness centrality of a vertex is the number of geodesics * going through it. If there are more than one geodesic between two * vertices, the value of these geodesics are weighted by one over the * number of geodesics. When estimating betweenness centrality, igraph * takes into consideration only those paths that are shorter than or * equal to a prescribed length. Note that the estimated centrality * will always be less than the real one. * * \param graph The graph object. * \param res The result of the computation, a vector containing the * estimated betweenness scores for the specified vertices. * \param vids The vertices of which the betweenness centrality scores * will be estimated. * \param directed Logical, if true directed paths will be considered * for directed graphs. It is ignored for undirected graphs. * \param cutoff The maximal length of paths that will be considered. * If zero or negative, the exact betweenness will be calculated * (no upper limit on path lengths). * \param weights An optional vector containing edge weights for * calculating weighted betweenness. Supply a null pointer here * for unweighted betweenness. * \param nobigint Logical, if true, then we don't use big integers * for the calculation, setting this to 1 (=true) should * work for most graphs. It is currently ignored for weighted * graphs. * \return Error code: * \c IGRAPH_ENOMEM, not enough memory for * temporary data. * \c IGRAPH_EINVVID, invalid vertex id passed in * \p vids. * * Time complexity: O(|V||E|), * |V| and * |E| are the number of vertices and * edges in the graph. * Note that the time complexity is independent of the number of * vertices for which the score is calculated. * * \sa Other centrality types: \ref igraph_degree(), \ref igraph_closeness(). * See \ref igraph_edge_betweenness() for calculating the betweenness score * of the edges in a graph. */ int igraph_betweenness_estimate(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, igraph_bool_t directed, igraph_real_t cutoff, const igraph_vector_t *weights, igraph_bool_t nobigint) { long int no_of_nodes = igraph_vcount(graph); igraph_dqueue_t q = IGRAPH_DQUEUE_NULL; long int *distance; unsigned long long int *nrgeo = 0; /* must be long long; consider grid graphs for example */ igraph_biguint_t *big_nrgeo = 0; double *tmpscore; igraph_stack_t stack = IGRAPH_STACK_NULL; long int source; long int j, k, nneis; igraph_vector_int_t *neis; igraph_vector_t v_tmpres, *tmpres = &v_tmpres; igraph_vit_t vit; igraph_adjlist_t adjlist_out, adjlist_in; igraph_adjlist_t *adjlist_out_p, *adjlist_in_p; igraph_biguint_t D, R, T; if (weights) { return igraph_i_betweenness_estimate_weighted(graph, res, vids, directed, cutoff, weights, nobigint); } if (!igraph_vs_is_all(&vids)) { /* subset */ IGRAPH_VECTOR_INIT_FINALLY(tmpres, no_of_nodes); } else { /* only */ IGRAPH_CHECK(igraph_vector_resize(res, no_of_nodes)); igraph_vector_null(res); tmpres = res; } directed = directed && igraph_is_directed(graph); if (directed) { IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist_out, IGRAPH_OUT)); IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist_out); IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist_in, IGRAPH_IN)); IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist_in); adjlist_out_p = &adjlist_out; adjlist_in_p = &adjlist_in; } else { IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist_out, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist_out); IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist_in, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist_in); adjlist_out_p = &adjlist_out; adjlist_in_p = &adjlist_in; } for (j = 0; j < no_of_nodes; j++) { igraph_vector_int_clear(igraph_adjlist_get(adjlist_in_p, j)); } distance = igraph_Calloc(no_of_nodes, long int); if (distance == 0) { IGRAPH_ERROR("betweenness failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, distance); if (nobigint) { nrgeo = igraph_Calloc(no_of_nodes, unsigned long long int); if (nrgeo == 0) { IGRAPH_ERROR("betweenness failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, nrgeo); } else { /* +1 is to have one containing zeros, when we free it, we stop at the zero */ big_nrgeo = igraph_Calloc(no_of_nodes + 1, igraph_biguint_t); if (!big_nrgeo) { IGRAPH_ERROR("betweenness failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_i_destroy_biguints, big_nrgeo); for (j = 0; j < no_of_nodes; j++) { IGRAPH_CHECK(igraph_biguint_init(&big_nrgeo[j])); } IGRAPH_CHECK(igraph_biguint_init(&D)); IGRAPH_FINALLY(igraph_biguint_destroy, &D); IGRAPH_CHECK(igraph_biguint_init(&R)); IGRAPH_FINALLY(igraph_biguint_destroy, &R); IGRAPH_CHECK(igraph_biguint_init(&T)); IGRAPH_FINALLY(igraph_biguint_destroy, &T); } tmpscore = igraph_Calloc(no_of_nodes, double); if (tmpscore == 0) { IGRAPH_ERROR("betweenness failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, tmpscore); IGRAPH_DQUEUE_INIT_FINALLY(&q, 100); igraph_stack_init(&stack, no_of_nodes); IGRAPH_FINALLY(igraph_stack_destroy, &stack); /* here we go */ for (source = 0; source < no_of_nodes; source++) { IGRAPH_PROGRESS("Betweenness centrality: ", 100.0 * source / no_of_nodes, 0); IGRAPH_ALLOW_INTERRUPTION(); IGRAPH_CHECK(igraph_dqueue_push(&q, source)); if (nobigint) { nrgeo[source] = 1; } else { igraph_biguint_set_limb(&big_nrgeo[source], 1); } distance[source] = 1; while (!igraph_dqueue_empty(&q)) { long int actnode = (long int) igraph_dqueue_pop(&q); IGRAPH_CHECK(igraph_stack_push(&stack, actnode)); if (cutoff > 0 && distance[actnode] >= cutoff + 1) { continue; } neis = igraph_adjlist_get(adjlist_out_p, actnode); nneis = igraph_vector_int_size(neis); for (j = 0; j < nneis; j++) { long int neighbor = (long int) VECTOR(*neis)[j]; if (distance[neighbor] == 0) { distance[neighbor] = distance[actnode] + 1; IGRAPH_CHECK(igraph_dqueue_push(&q, neighbor)); } if (distance[neighbor] == distance[actnode] + 1) { igraph_vector_int_t *v = igraph_adjlist_get(adjlist_in_p, neighbor); igraph_vector_int_push_back(v, actnode); if (nobigint) { nrgeo[neighbor] += nrgeo[actnode]; } else { IGRAPH_CHECK(igraph_biguint_add(&big_nrgeo[neighbor], &big_nrgeo[neighbor], &big_nrgeo[actnode])); } } } } /* while !igraph_dqueue_empty */ /* Ok, we've the distance of each node and also the number of shortest paths to them. Now we do an inverse search, starting with the farthest nodes. */ while (!igraph_stack_empty(&stack)) { long int actnode = (long int) igraph_stack_pop(&stack); neis = igraph_adjlist_get(adjlist_in_p, actnode); nneis = igraph_vector_int_size(neis); for (j = 0; j < nneis; j++) { long int neighbor = (long int) VECTOR(*neis)[j]; if (nobigint) { tmpscore[neighbor] += (tmpscore[actnode] + 1) * ((double)(nrgeo[neighbor])) / nrgeo[actnode]; } else { if (!igraph_biguint_compare_limb(&big_nrgeo[actnode], 0)) { tmpscore[neighbor] = IGRAPH_INFINITY; } else { double div; limb_t shift = 1000000000L; IGRAPH_CHECK(igraph_biguint_mul_limb(&T, &big_nrgeo[neighbor], shift)); igraph_biguint_div(&D, &R, &T, &big_nrgeo[actnode]); div = igraph_biguint_get(&D) / shift; tmpscore[neighbor] += (tmpscore[actnode] + 1) * div; } } } if (actnode != source) { VECTOR(*tmpres)[actnode] += tmpscore[actnode]; } distance[actnode] = 0; if (nobigint) { nrgeo[actnode] = 0; } else { igraph_biguint_set_limb(&big_nrgeo[actnode], 0); } tmpscore[actnode] = 0; igraph_vector_int_clear(igraph_adjlist_get(adjlist_in_p, actnode)); } } /* for source < no_of_nodes */ IGRAPH_PROGRESS("Betweenness centrality: ", 100.0, 0); /* clean */ igraph_Free(distance); if (nobigint) { igraph_Free(nrgeo); } else { igraph_biguint_destroy(&T); igraph_biguint_destroy(&R); igraph_biguint_destroy(&D); IGRAPH_FINALLY_CLEAN(3); igraph_i_destroy_biguints(big_nrgeo); } igraph_Free(tmpscore); igraph_dqueue_destroy(&q); igraph_stack_destroy(&stack); IGRAPH_FINALLY_CLEAN(5); /* Keep only the requested vertices */ if (!igraph_vs_is_all(&vids)) { IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); IGRAPH_CHECK(igraph_vector_resize(res, IGRAPH_VIT_SIZE(vit))); for (k = 0, IGRAPH_VIT_RESET(vit); !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit), k++) { long int node = IGRAPH_VIT_GET(vit); VECTOR(*res)[k] = VECTOR(*tmpres)[node]; } igraph_vit_destroy(&vit); igraph_vector_destroy(tmpres); IGRAPH_FINALLY_CLEAN(2); } /* divide by 2 for undirected graph */ if (!directed) { nneis = igraph_vector_size(res); for (j = 0; j < nneis; j++) { VECTOR(*res)[j] /= 2.0; } } igraph_adjlist_destroy(&adjlist_out); igraph_adjlist_destroy(&adjlist_in); IGRAPH_FINALLY_CLEAN(2); return 0; } int igraph_i_edge_betweenness_estimate_weighted(const igraph_t *graph, igraph_vector_t *result, igraph_bool_t directed, igraph_real_t cutoff, const igraph_vector_t *weights) { igraph_real_t minweight; igraph_integer_t no_of_nodes = (igraph_integer_t) igraph_vcount(graph); igraph_integer_t no_of_edges = (igraph_integer_t) igraph_ecount(graph); igraph_2wheap_t Q; igraph_inclist_t inclist; igraph_inclist_t fathers; igraph_neimode_t mode = directed ? IGRAPH_OUT : IGRAPH_ALL; igraph_vector_t distance, tmpscore; igraph_vector_long_t nrgeo; long int source, j; int cmp_result; const double eps = IGRAPH_SHORTEST_PATH_EPSILON; igraph_stack_t S; if (igraph_vector_size(weights) != no_of_edges) { IGRAPH_ERROR("Weight vector length does not match", IGRAPH_EINVAL); } minweight = igraph_vector_min(weights); if (minweight <= 0) { IGRAPH_ERROR("Weight vector must be positive", IGRAPH_EINVAL); } else if (minweight <= eps) { IGRAPH_WARNING("Some weights are smaller than epsilon, calculations may suffer from numerical precision."); } IGRAPH_CHECK(igraph_inclist_init(graph, &inclist, mode)); IGRAPH_FINALLY(igraph_inclist_destroy, &inclist); IGRAPH_CHECK(igraph_inclist_init_empty(&fathers, no_of_nodes)); IGRAPH_FINALLY(igraph_inclist_destroy, &fathers); IGRAPH_VECTOR_INIT_FINALLY(&distance, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&tmpscore, no_of_nodes); IGRAPH_CHECK(igraph_vector_long_init(&nrgeo, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_long_destroy, &nrgeo); IGRAPH_CHECK(igraph_2wheap_init(&Q, no_of_nodes)); IGRAPH_FINALLY(igraph_2wheap_destroy, &Q); IGRAPH_CHECK(igraph_stack_init(&S, no_of_nodes)); IGRAPH_FINALLY(igraph_stack_destroy, &S); IGRAPH_CHECK(igraph_vector_resize(result, no_of_edges)); igraph_vector_null(result); for (source = 0; source < no_of_nodes; source++) { IGRAPH_PROGRESS("Edge betweenness centrality: ", 100.0 * source / no_of_nodes, 0); IGRAPH_ALLOW_INTERRUPTION(); /* printf("source: %li\n", source); */ igraph_vector_null(&distance); igraph_vector_null(&tmpscore); igraph_vector_long_null(&nrgeo); igraph_2wheap_push_with_index(&Q, source, -1.0); VECTOR(distance)[source] = 1.0; VECTOR(nrgeo)[source] = 1; while (!igraph_2wheap_empty(&Q)) { long int minnei = igraph_2wheap_max_index(&Q); igraph_real_t mindist = -igraph_2wheap_delete_max(&Q); igraph_vector_int_t *neis; long int nlen; /* printf("SP to %li is final, dist: %g, nrgeo: %li\n", minnei, */ /* VECTOR(distance)[minnei]-1.0, VECTOR(nrgeo)[minnei]); */ igraph_stack_push(&S, minnei); if (cutoff > 0 && VECTOR(distance)[minnei] >= cutoff + 1.0) { continue; } neis = igraph_inclist_get(&inclist, minnei); nlen = igraph_vector_int_size(neis); for (j = 0; j < nlen; j++) { long int edge = (long int) VECTOR(*neis)[j]; long int to = IGRAPH_OTHER(graph, edge, minnei); igraph_real_t altdist = mindist + VECTOR(*weights)[edge]; igraph_real_t curdist = VECTOR(distance)[to]; if (curdist == 0) { /* this means curdist is infinity */ cmp_result = -1; } else { cmp_result = igraph_cmp_epsilon(altdist, curdist, eps); } /* printf("to=%ld, altdist = %lg, curdist = %lg, cmp = %d\n", to, altdist, curdist-1, cmp_result); */ if (curdist == 0) { /* This is the first finite distance to 'to' */ igraph_vector_int_t *v = igraph_inclist_get(&fathers, to); /* printf("Found first path to %li (from %li)\n", to, minnei); */ igraph_vector_int_resize(v, 1); VECTOR(*v)[0] = edge; VECTOR(nrgeo)[to] = VECTOR(nrgeo)[minnei]; VECTOR(distance)[to] = altdist; IGRAPH_CHECK(igraph_2wheap_push_with_index(&Q, to, -altdist)); } else if (cmp_result < 0) { /* This is a shorter path */ igraph_vector_int_t *v = igraph_inclist_get(&fathers, to); /* printf("Found a shorter path to %li (from %li)\n", to, minnei); */ igraph_vector_int_resize(v, 1); VECTOR(*v)[0] = edge; VECTOR(nrgeo)[to] = VECTOR(nrgeo)[minnei]; VECTOR(distance)[to] = altdist; IGRAPH_CHECK(igraph_2wheap_modify(&Q, to, -altdist)); } else if (cmp_result == 0) { igraph_vector_int_t *v = igraph_inclist_get(&fathers, to); /* printf("Found a second SP to %li (from %li)\n", to, minnei); */ igraph_vector_int_push_back(v, edge); VECTOR(nrgeo)[to] += VECTOR(nrgeo)[minnei]; } } } /* igraph_2wheap_empty(&Q) */ while (!igraph_stack_empty(&S)) { long int w = (long int) igraph_stack_pop(&S); igraph_vector_int_t *fatv = igraph_inclist_get(&fathers, w); long int fatv_len = igraph_vector_int_size(fatv); /* printf("Popping %li.\n", w); */ for (j = 0; j < fatv_len; j++) { long int fedge = (long int) VECTOR(*fatv)[j]; long int neighbor = IGRAPH_OTHER(graph, fedge, w); VECTOR(tmpscore)[neighbor] += ((double)VECTOR(nrgeo)[neighbor]) / VECTOR(nrgeo)[w] * (1.0 + VECTOR(tmpscore)[w]); /* printf("Scoring %li (edge %li)\n", neighbor, fedge); */ VECTOR(*result)[fedge] += ((VECTOR(tmpscore)[w] + 1) * VECTOR(nrgeo)[neighbor]) / VECTOR(nrgeo)[w]; } VECTOR(tmpscore)[w] = 0; VECTOR(distance)[w] = 0; VECTOR(nrgeo)[w] = 0; igraph_vector_int_clear(fatv); } } /* source < no_of_nodes */ if (!directed || !igraph_is_directed(graph)) { for (j = 0; j < no_of_edges; j++) { VECTOR(*result)[j] /= 2.0; } } IGRAPH_PROGRESS("Edge betweenness centrality: ", 100.0, 0); igraph_stack_destroy(&S); igraph_2wheap_destroy(&Q); IGRAPH_FINALLY_CLEAN(2); igraph_inclist_destroy(&inclist); igraph_inclist_destroy(&fathers); igraph_vector_destroy(&distance); igraph_vector_destroy(&tmpscore); igraph_vector_long_destroy(&nrgeo); IGRAPH_FINALLY_CLEAN(5); return 0; } /** * \ingroup structural * \function igraph_edge_betweenness * \brief Betweenness centrality of the edges. * * * The betweenness centrality of an edge is the number of geodesics * going through it. If there are more than one geodesics between two * vertices, the value of these geodesics are weighted by one over the * number of geodesics. * \param graph The graph object. * \param result The result of the computation, vector containing the * betweenness scores for the edges. * \param directed Logical, if true directed paths will be considered * for directed graphs. It is ignored for undirected graphs. * \param weights An optional weight vector for weighted edge * betweenness. Supply a null pointer here for the unweighted * version. * \return Error code: * \c IGRAPH_ENOMEM, not enough memory for * temporary data. * * Time complexity: O(|V||E|), * |V| and * |E| are the number of vertices and * edges in the graph. * * \sa Other centrality types: \ref igraph_degree(), \ref igraph_closeness(). * See \ref igraph_edge_betweenness() for calculating the betweenness score * of the edges in a graph. See \ref igraph_edge_betweenness_estimate() to * estimate the betweenness score of the edges in a graph. * * \example examples/simple/igraph_edge_betweenness.c */ int igraph_edge_betweenness(const igraph_t *graph, igraph_vector_t *result, igraph_bool_t directed, const igraph_vector_t *weights) { return igraph_edge_betweenness_estimate(graph, result, directed, -1, weights); } /** * \ingroup structural * \function igraph_edge_betweenness_estimate * \brief Estimated betweenness centrality of the edges. * * * The betweenness centrality of an edge is the number of geodesics * going through it. If there are more than one geodesics between two * vertices, the value of these geodesics are weighted by one over the * number of geodesics. When estimating betweenness centrality, igraph * takes into consideration only those paths that are shorter than or * equal to a prescribed length. Note that the estimated centrality * will always be less than the real one. * \param graph The graph object. * \param result The result of the computation, vector containing the * betweenness scores for the edges. * \param directed Logical, if true directed paths will be considered * for directed graphs. It is ignored for undirected graphs. * \param cutoff The maximal length of paths that will be considered. * If zero or negative, the exact betweenness will be calculated * (no upper limit on path lengths). * \param weights An optional weight vector for weighted * betweenness. Supply a null pointer here for unweighted * betweenness. * \return Error code: * \c IGRAPH_ENOMEM, not enough memory for * temporary data. * * Time complexity: O(|V||E|), * |V| and * |E| are the number of vertices and * edges in the graph. * * \sa Other centrality types: \ref igraph_degree(), \ref igraph_closeness(). * See \ref igraph_betweenness() for calculating the betweenness score * of the vertices in a graph. */ int igraph_edge_betweenness_estimate(const igraph_t *graph, igraph_vector_t *result, igraph_bool_t directed, igraph_real_t cutoff, const igraph_vector_t *weights) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_dqueue_t q = IGRAPH_DQUEUE_NULL; long int *distance; unsigned long long int *nrgeo; double *tmpscore; igraph_stack_t stack = IGRAPH_STACK_NULL; long int source; long int j; igraph_inclist_t elist_out, elist_in; igraph_inclist_t *elist_out_p, *elist_in_p; igraph_vector_int_t *neip; long int neino; long int i; if (weights) { return igraph_i_edge_betweenness_estimate_weighted(graph, result, directed, cutoff, weights); } directed = directed && igraph_is_directed(graph); if (directed) { IGRAPH_CHECK(igraph_inclist_init(graph, &elist_out, IGRAPH_OUT)); IGRAPH_FINALLY(igraph_inclist_destroy, &elist_out); IGRAPH_CHECK(igraph_inclist_init(graph, &elist_in, IGRAPH_IN)); IGRAPH_FINALLY(igraph_inclist_destroy, &elist_in); elist_out_p = &elist_out; elist_in_p = &elist_in; } else { IGRAPH_CHECK(igraph_inclist_init(graph, &elist_out, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_inclist_destroy, &elist_out); elist_out_p = elist_in_p = &elist_out; } distance = igraph_Calloc(no_of_nodes, long int); if (distance == 0) { IGRAPH_ERROR("edge betweenness failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, distance); nrgeo = igraph_Calloc(no_of_nodes, unsigned long long int); if (nrgeo == 0) { IGRAPH_ERROR("edge betweenness failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, nrgeo); tmpscore = igraph_Calloc(no_of_nodes, double); if (tmpscore == 0) { IGRAPH_ERROR("edge betweenness failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, tmpscore); IGRAPH_DQUEUE_INIT_FINALLY(&q, 100); IGRAPH_CHECK(igraph_stack_init(&stack, no_of_nodes)); IGRAPH_FINALLY(igraph_stack_destroy, &stack); IGRAPH_CHECK(igraph_vector_resize(result, no_of_edges)); igraph_vector_null(result); /* here we go */ for (source = 0; source < no_of_nodes; source++) { IGRAPH_PROGRESS("Edge betweenness centrality: ", 100.0 * source / no_of_nodes, 0); IGRAPH_ALLOW_INTERRUPTION(); memset(distance, 0, (size_t) no_of_nodes * sizeof(long int)); memset(nrgeo, 0, (size_t) no_of_nodes * sizeof(unsigned long long int)); memset(tmpscore, 0, (size_t) no_of_nodes * sizeof(double)); igraph_stack_clear(&stack); /* it should be empty anyway... */ IGRAPH_CHECK(igraph_dqueue_push(&q, source)); nrgeo[source] = 1; distance[source] = 0; while (!igraph_dqueue_empty(&q)) { long int actnode = (long int) igraph_dqueue_pop(&q); if (cutoff > 0 && distance[actnode] >= cutoff ) { continue; } /* check the neighbors and add to them to the queue if unseen before */ neip = igraph_inclist_get(elist_out_p, actnode); neino = igraph_vector_int_size(neip); for (i = 0; i < neino; i++) { igraph_integer_t edge = (igraph_integer_t) VECTOR(*neip)[i], from, to; long int neighbor; igraph_edge(graph, edge, &from, &to); neighbor = actnode != from ? from : to; if (nrgeo[neighbor] != 0) { /* we've already seen this node, another shortest path? */ if (distance[neighbor] == distance[actnode] + 1) { nrgeo[neighbor] += nrgeo[actnode]; } } else { /* we haven't seen this node yet */ nrgeo[neighbor] += nrgeo[actnode]; distance[neighbor] = distance[actnode] + 1; IGRAPH_CHECK(igraph_dqueue_push(&q, neighbor)); IGRAPH_CHECK(igraph_stack_push(&stack, neighbor)); } } } /* while !igraph_dqueue_empty */ /* Ok, we've the distance of each node and also the number of shortest paths to them. Now we do an inverse search, starting with the farthest nodes. */ while (!igraph_stack_empty(&stack)) { long int actnode = (long int) igraph_stack_pop(&stack); if (distance[actnode] < 1) { continue; /* skip source node */ } /* set the temporary score of the friends */ neip = igraph_inclist_get(elist_in_p, actnode); neino = igraph_vector_int_size(neip); for (i = 0; i < neino; i++) { igraph_integer_t from, to; long int neighbor; igraph_integer_t edgeno = (igraph_integer_t) VECTOR(*neip)[i]; igraph_edge(graph, edgeno, &from, &to); neighbor = actnode != from ? from : to; if (distance[neighbor] == distance[actnode] - 1 && nrgeo[neighbor] != 0) { tmpscore[neighbor] += (tmpscore[actnode] + 1) * nrgeo[neighbor] / nrgeo[actnode]; VECTOR(*result)[edgeno] += (tmpscore[actnode] + 1) * nrgeo[neighbor] / nrgeo[actnode]; } } } /* Ok, we've the scores for this source */ } /* for source <= no_of_nodes */ IGRAPH_PROGRESS("Edge betweenness centrality: ", 100.0, 0); /* clean and return */ igraph_Free(distance); igraph_Free(nrgeo); igraph_Free(tmpscore); igraph_dqueue_destroy(&q); igraph_stack_destroy(&stack); IGRAPH_FINALLY_CLEAN(5); if (directed) { igraph_inclist_destroy(&elist_out); igraph_inclist_destroy(&elist_in); IGRAPH_FINALLY_CLEAN(2); } else { igraph_inclist_destroy(&elist_out); IGRAPH_FINALLY_CLEAN(1); } /* divide by 2 for undirected graph */ if (!directed || !igraph_is_directed(graph)) { for (j = 0; j < igraph_vector_size(result); j++) { VECTOR(*result)[j] /= 2.0; } } return 0; } /** * \ingroup structural * \function igraph_closeness * \brief Closeness centrality calculations for some vertices. * * * The closeness centrality of a vertex measures how easily other * vertices can be reached from it (or the other way: how easily it * can be reached from the other vertices). It is defined as * the number of vertices minus one divided by the sum of the * lengths of all geodesics from/to the given vertex. * * * If the graph is not connected, and there is no path between two * vertices, the number of vertices is used instead the length of the * geodesic. This is longer than the longest possible geodesic in case * of unweighted graphs, but may not be so in weighted graphs, so it is * best not to use this function on weighted graphs. * * * If the graph has a single vertex only, the closeness centrality of * that single vertex will be NaN (because we are essentially dividing * zero with zero). * * \param graph The graph object. * \param res The result of the computation, a vector containing the * closeness centrality scores for the given vertices. * \param vids Vector giving the vertices for which the closeness * centrality scores will be computed. * \param mode The type of shortest paths to be used for the * calculation in directed graphs. Possible values: * \clist * \cli IGRAPH_OUT * the lengths of the outgoing paths are calculated. * \cli IGRAPH_IN * the lengths of the incoming paths are calculated. * \cli IGRAPH_ALL * the directed graph is considered as an * undirected one for the computation. * \endclist * \param weights An optional vector containing edge weights for * weighted closeness. Supply a null pointer here for * traditional, unweighted closeness. * \param normalized Boolean, whether to normalize results by multiplying * by the number of vertices minus one. * \return Error code: * \clist * \cli IGRAPH_ENOMEM * not enough memory for temporary data. * \cli IGRAPH_EINVVID * invalid vertex id passed. * \cli IGRAPH_EINVMODE * invalid mode argument. * \endclist * * Time complexity: O(n|E|), * n is the number * of vertices for which the calculation is done and * |E| is the number * of edges in the graph. * * \sa Other centrality types: \ref igraph_degree(), \ref igraph_betweenness(). * See \ref igraph_closeness_estimate() to estimate closeness values. */ int igraph_closeness(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, igraph_neimode_t mode, const igraph_vector_t *weights, igraph_bool_t normalized) { return igraph_closeness_estimate(graph, res, vids, mode, -1, weights, normalized); } int igraph_i_closeness_estimate_weighted(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, igraph_neimode_t mode, igraph_real_t cutoff, const igraph_vector_t *weights, igraph_bool_t normalized) { /* See igraph_shortest_paths_dijkstra() for the implementation details and the dirty tricks. */ igraph_real_t minweight; long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_2wheap_t Q; igraph_vit_t vit; long int nodes_to_calc; igraph_lazy_inclist_t inclist; long int i, j; igraph_vector_t dist; igraph_vector_long_t which; long int nodes_reached; int cmp_result; const double eps = IGRAPH_SHORTEST_PATH_EPSILON; igraph_real_t mindist; igraph_bool_t warning_shown = 0; if (igraph_vector_size(weights) != no_of_edges) { IGRAPH_ERROR("Invalid weight vector length", IGRAPH_EINVAL); } minweight = igraph_vector_min(weights); if (minweight <= 0) { IGRAPH_ERROR("Weight vector must be positive", IGRAPH_EINVAL); } else if (minweight <= eps) { IGRAPH_WARNING("Some weights are smaller than epsilon, calculations may suffer from numerical precision."); } IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); nodes_to_calc = IGRAPH_VIT_SIZE(vit); IGRAPH_CHECK(igraph_2wheap_init(&Q, no_of_nodes)); IGRAPH_FINALLY(igraph_2wheap_destroy, &Q); IGRAPH_CHECK(igraph_lazy_inclist_init(graph, &inclist, mode)); IGRAPH_FINALLY(igraph_lazy_inclist_destroy, &inclist); IGRAPH_VECTOR_INIT_FINALLY(&dist, no_of_nodes); IGRAPH_CHECK(igraph_vector_long_init(&which, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_long_destroy, &which); IGRAPH_CHECK(igraph_vector_resize(res, nodes_to_calc)); igraph_vector_null(res); for (i = 0; !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit), i++) { long int source = IGRAPH_VIT_GET(vit); igraph_2wheap_clear(&Q); igraph_2wheap_push_with_index(&Q, source, -1.0); VECTOR(which)[source] = i + 1; VECTOR(dist)[source] = 1.0; /* actual distance is zero but we need to store distance + 1 */ nodes_reached = 0; while (!igraph_2wheap_empty(&Q)) { igraph_integer_t minnei = (igraph_integer_t) igraph_2wheap_max_index(&Q); /* Now check all neighbors of minnei for a shorter path */ igraph_vector_t *neis = igraph_lazy_inclist_get(&inclist, minnei); long int nlen = igraph_vector_size(neis); mindist = -igraph_2wheap_delete_max(&Q); VECTOR(*res)[i] += (mindist - 1.0); nodes_reached++; if (cutoff > 0 && mindist >= cutoff + 1.0) { continue; /* NOT break!!! */ } for (j = 0; j < nlen; j++) { long int edge = (long int) VECTOR(*neis)[j]; long int to = IGRAPH_OTHER(graph, edge, minnei); igraph_real_t altdist = mindist + VECTOR(*weights)[edge]; igraph_real_t curdist = VECTOR(dist)[to]; if (curdist == 0) { /* this means curdist is infinity */ cmp_result = -1; } else { cmp_result = igraph_cmp_epsilon(altdist, curdist, eps); } if (VECTOR(which)[to] != i + 1) { /* First non-infinite distance */ VECTOR(which)[to] = i + 1; VECTOR(dist)[to] = altdist; IGRAPH_CHECK(igraph_2wheap_push_with_index(&Q, to, -altdist)); } else if (cmp_result < 0) { /* This is a shorter path */ VECTOR(dist)[to] = altdist; IGRAPH_CHECK(igraph_2wheap_modify(&Q, to, -altdist)); } } } /* !igraph_2wheap_empty(&Q) */ /* using igraph_real_t here instead of igraph_integer_t to avoid overflow */ VECTOR(*res)[i] += ((igraph_real_t)no_of_nodes * (no_of_nodes - nodes_reached)); VECTOR(*res)[i] = (no_of_nodes - 1) / VECTOR(*res)[i]; if (((cutoff > 0 && mindist < cutoff + 1.0) || (cutoff <= 0)) && nodes_reached < no_of_nodes && !warning_shown) { IGRAPH_WARNING("closeness centrality is not well-defined for disconnected graphs"); warning_shown = 1; } } /* !IGRAPH_VIT_END(vit) */ if (!normalized) { for (i = 0; i < nodes_to_calc; i++) { VECTOR(*res)[i] /= (no_of_nodes - 1); } } igraph_vector_long_destroy(&which); igraph_vector_destroy(&dist); igraph_lazy_inclist_destroy(&inclist); igraph_2wheap_destroy(&Q); igraph_vit_destroy(&vit); IGRAPH_FINALLY_CLEAN(5); return 0; } /** * \ingroup structural * \function igraph_closeness_estimate * \brief Closeness centrality estimations for some vertices. * * * The closeness centrality of a vertex measures how easily other * vertices can be reached from it (or the other way: how easily it * can be reached from the other vertices). It is defined as * the number of vertices minus one divided by the sum of the * lengths of all geodesics from/to the given vertex. When estimating * closeness centrality, igraph considers paths having a length less than * or equal to a prescribed cutoff value. * * * If the graph is not connected, and there is no such path between two * vertices, the number of vertices is used instead the length of the * geodesic. This is always longer than the longest possible geodesic. * * * Since the estimation considers vertex pairs with a distance greater than * the given value as disconnected, the resulting estimation will always be * lower than the actual closeness centrality. * * \param graph The graph object. * \param res The result of the computation, a vector containing the * closeness centrality scores for the given vertices. * \param vids Vector giving the vertices for which the closeness * centrality scores will be computed. * \param mode The type of shortest paths to be used for the * calculation in directed graphs. Possible values: * \clist * \cli IGRAPH_OUT * the lengths of the outgoing paths are calculated. * \cli IGRAPH_IN * the lengths of the incoming paths are calculated. * \cli IGRAPH_ALL * the directed graph is considered as an * undirected one for the computation. * \endclist * \param cutoff The maximal length of paths that will be considered. * If zero or negative, the exact closeness will be calculated * (no upper limit on path lengths). * \param weights An optional vector containing edge weights for * weighted closeness. Supply a null pointer here for * traditional, unweighted closeness. * \param normalized Boolean, whether to normalize results by multiplying * by the number of vertices minus one. * \return Error code: * \clist * \cli IGRAPH_ENOMEM * not enough memory for temporary data. * \cli IGRAPH_EINVVID * invalid vertex id passed. * \cli IGRAPH_EINVMODE * invalid mode argument. * \endclist * * Time complexity: O(n|E|), * n is the number * of vertices for which the calculation is done and * |E| is the number * of edges in the graph. * * \sa Other centrality types: \ref igraph_degree(), \ref igraph_betweenness(). */ int igraph_closeness_estimate(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, igraph_neimode_t mode, igraph_real_t cutoff, const igraph_vector_t *weights, igraph_bool_t normalized) { long int no_of_nodes = igraph_vcount(graph); igraph_vector_t already_counted; igraph_vector_int_t *neis; long int i, j; long int nodes_reached; long int actdist; igraph_adjlist_t allneis; igraph_dqueue_t q; long int nodes_to_calc; igraph_vit_t vit; igraph_bool_t warning_shown = 0; if (weights) { return igraph_i_closeness_estimate_weighted(graph, res, vids, mode, cutoff, weights, normalized); } IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); nodes_to_calc = IGRAPH_VIT_SIZE(vit); if (mode != IGRAPH_OUT && mode != IGRAPH_IN && mode != IGRAPH_ALL) { IGRAPH_ERROR("calculating closeness", IGRAPH_EINVMODE); } IGRAPH_VECTOR_INIT_FINALLY(&already_counted, no_of_nodes); IGRAPH_DQUEUE_INIT_FINALLY(&q, 100); IGRAPH_CHECK(igraph_adjlist_init(graph, &allneis, mode)); IGRAPH_FINALLY(igraph_adjlist_destroy, &allneis); IGRAPH_CHECK(igraph_vector_resize(res, nodes_to_calc)); igraph_vector_null(res); for (IGRAPH_VIT_RESET(vit), i = 0; !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit), i++) { igraph_dqueue_clear(&q); IGRAPH_CHECK(igraph_dqueue_push(&q, IGRAPH_VIT_GET(vit))); IGRAPH_CHECK(igraph_dqueue_push(&q, 0)); nodes_reached = 1; VECTOR(already_counted)[(long int)IGRAPH_VIT_GET(vit)] = i + 1; IGRAPH_PROGRESS("Closeness: ", 100.0 * i / no_of_nodes, NULL); IGRAPH_ALLOW_INTERRUPTION(); while (!igraph_dqueue_empty(&q)) { long int act = (long int) igraph_dqueue_pop(&q); actdist = (long int) igraph_dqueue_pop(&q); VECTOR(*res)[i] += actdist; if (cutoff > 0 && actdist >= cutoff) { continue; /* NOT break!!! */ } /* check the neighbors */ neis = igraph_adjlist_get(&allneis, act); for (j = 0; j < igraph_vector_int_size(neis); j++) { long int neighbor = (long int) VECTOR(*neis)[j]; if (VECTOR(already_counted)[neighbor] == i + 1) { continue; } VECTOR(already_counted)[neighbor] = i + 1; nodes_reached++; IGRAPH_CHECK(igraph_dqueue_push(&q, neighbor)); IGRAPH_CHECK(igraph_dqueue_push(&q, actdist + 1)); } } /* using igraph_real_t here instead of igraph_integer_t to avoid overflow */ VECTOR(*res)[i] += ((igraph_real_t)no_of_nodes * (no_of_nodes - nodes_reached)); VECTOR(*res)[i] = (no_of_nodes - 1) / VECTOR(*res)[i]; if (((cutoff > 0 && actdist < cutoff) || cutoff <= 0) && no_of_nodes > nodes_reached && !warning_shown) { IGRAPH_WARNING("closeness centrality is not well-defined for disconnected graphs"); warning_shown = 1; } } if (!normalized) { for (i = 0; i < nodes_to_calc; i++) { VECTOR(*res)[i] /= (no_of_nodes - 1); } } IGRAPH_PROGRESS("Closeness: ", 100.0, NULL); /* Clean */ igraph_dqueue_destroy(&q); igraph_vector_destroy(&already_counted); igraph_vit_destroy(&vit); igraph_adjlist_destroy(&allneis); IGRAPH_FINALLY_CLEAN(4); return 0; } /** * \function igraph_centralization * Calculate the centralization score from the node level scores * * For a centrality score defined on the vertices of a graph, it is * possible to define a graph level centralization index, by * calculating the sum of the deviation from the maximum centrality * score. Consequently, the higher the centralization index of the * graph, the more centralized the structure is. * * In order to make graphs of different sizes comparable, * the centralization index is usually normalized to a number between * zero and one, by dividing the (unnormalized) centralization score * of the most centralized structure with the same number of vertices. * * For most centrality indices the most centralized * structure is the star graph, a single center connected to all other * nodes in the network. There are some variation depending on whether * the graph is directed or not, whether loop edges are allowed, etc. * * * This function simply calculates the graph level index, if the node * level scores and the theoretical maximum are given. It is called by * all the measure-specific centralization functions. * * \param scores A vector containing the node-level centrality * scores. * \param theoretical_max The graph level centrality score of the most * centralized graph with the same number of vertices. Only used * if \c normalized set to true. * \param normalized Boolean, whether to normalize the centralization * by dividing the supplied theoretical maximum. * \return The graph level index. * * \sa \ref igraph_centralization_degree(), \ref * igraph_centralization_betweenness(), \ref * igraph_centralization_closeness(), and \ref * igraph_centralization_eigenvector_centrality() for specific * centralization functions. * * Time complexity: O(n), the length of the score vector. * * \example examples/simple/centralization.c */ igraph_real_t igraph_centralization(const igraph_vector_t *scores, igraph_real_t theoretical_max, igraph_bool_t normalized) { long int no_of_nodes = igraph_vector_size(scores); igraph_real_t maxscore = 0.0; igraph_real_t cent = 0.0; if (no_of_nodes != 0) { maxscore = igraph_vector_max(scores); cent = no_of_nodes * maxscore - igraph_vector_sum(scores); if (normalized) { cent = cent / theoretical_max; } } else { cent = IGRAPH_NAN; } return cent; } /** * \function igraph_centralization_degree * Calculate vertex degree and graph centralization * * This function calculates the degree of the vertices by passing its * arguments to \ref igraph_degree(); and it calculates the graph * level centralization index based on the results by calling \ref * igraph_centralization(). * \param graph The input graph. * \param res A vector if you need the node-level degree scores, or a * null pointer otherwise. * \param mode Constant the specifies the type of degree for directed * graphs. Possible values: \c IGRAPH_IN, \c IGRAPH_OUT and \c * IGRAPH_ALL. This argument is ignored for undirected graphs. * \param loops Boolean, whether to consider loop edges when * calculating the degree (and the centralization). * \param centralization Pointer to a real number, the centralization * score is placed here. * \param theoretical_max Pointer to real number or a null pointer. If * not a null pointer, then the theoretical maximum graph * centrality score for a graph with the same number vertices is * stored here. * \param normalized Boolean, whether to calculate a normalized * centralization score. See \ref igraph_centralization() for how * the normalization is done. * \return Error code. * * \sa \ref igraph_centralization(), \ref igraph_degree(). * * Time complexity: the complexity of \ref igraph_degree() plus O(n), * the number of vertices queried, for calculating the centralization * score. */ int igraph_centralization_degree(const igraph_t *graph, igraph_vector_t *res, igraph_neimode_t mode, igraph_bool_t loops, igraph_real_t *centralization, igraph_real_t *theoretical_max, igraph_bool_t normalized) { igraph_vector_t myscores; igraph_vector_t *scores = res; igraph_real_t *tmax = theoretical_max, mytmax; if (!tmax) { tmax = &mytmax; } if (!res) { scores = &myscores; IGRAPH_VECTOR_INIT_FINALLY(scores, 0); } IGRAPH_CHECK(igraph_degree(graph, scores, igraph_vss_all(), mode, loops)); IGRAPH_CHECK(igraph_centralization_degree_tmax(graph, 0, mode, loops, tmax)); *centralization = igraph_centralization(scores, *tmax, normalized); if (!res) { igraph_vector_destroy(scores); IGRAPH_FINALLY_CLEAN(1); } return 0; } /** * \function igraph_centralization_degree_tmax * Theoretical maximum for graph centralization based on degree * * This function returns the theoretical maximum graph centrality * based on vertex degree. * * * There are two ways to call this function, the first is to supply a * graph as the graph argument, and then the number of * vertices is taken from this object, and its directedness is * considered as well. The nodes argument is ignored in * this case. The mode argument is also ignored if the * supplied graph is undirected. * * * The other way is to supply a null pointer as the graph * argument. In this case the nodes and mode * arguments are considered. * * * The most centralized structure is the star. More specifically, for * undirected graphs it is the star, for directed graphs it is the * in-star or the out-star. * \param graph A graph object or a null pointer, see the description * above. * \param nodes The number of nodes. This is ignored if the * graph argument is not a null pointer. * \param mode Constant, whether the calculation is based on in-degree * (IGRAPH_IN), out-degree (IGRAPH_OUT) * or total degree (IGRAPH_ALL). This is ignored if * the graph argument is not a null pointer and the * given graph is undirected. * \param loops Boolean scalar, whether to consider loop edges in the * calculation. * \param res Pointer to a real variable, the result is stored here. * \return Error code. * * Time complexity: O(1). * * \sa \ref igraph_centralization_degree() and \ref * igraph_centralization(). */ int igraph_centralization_degree_tmax(const igraph_t *graph, igraph_integer_t nodes, igraph_neimode_t mode, igraph_bool_t loops, igraph_real_t *res) { igraph_bool_t directed = mode != IGRAPH_ALL; igraph_real_t real_nodes; if (graph) { directed = igraph_is_directed(graph); nodes = igraph_vcount(graph); } real_nodes = nodes; /* implicit cast to igraph_real_t */ if (directed) { switch (mode) { case IGRAPH_IN: case IGRAPH_OUT: if (!loops) { *res = (real_nodes - 1) * (real_nodes - 1); } else { *res = (real_nodes - 1) * real_nodes; } break; case IGRAPH_ALL: if (!loops) { *res = 2 * (real_nodes - 1) * (real_nodes - 2); } else { *res = 2 * (real_nodes - 1) * (real_nodes - 1); } break; } } else { if (!loops) { *res = (real_nodes - 1) * (real_nodes - 2); } else { *res = (real_nodes - 1) * real_nodes; } } return 0; } /** * \function igraph_centralization_betweenness * Calculate vertex betweenness and graph centralization * * This function calculates the betweenness centrality of the vertices * by passing its arguments to \ref igraph_betweenness(); and it * calculates the graph level centralization index based on the * results by calling \ref igraph_centralization(). * \param graph The input graph. * \param res A vector if you need the node-level betweenness scores, or a * null pointer otherwise. * \param directed Boolean, whether to consider directed paths when * calculating betweenness. * \param nobigint Logical, if true, then we don't use big integers * for the calculation, setting this to zero (=false) should * work for most graphs. It is currently ignored for weighted * graphs. * \param centralization Pointer to a real number, the centralization * score is placed here. * \param theoretical_max Pointer to real number or a null pointer. If * not a null pointer, then the theoretical maximum graph * centrality score for a graph with the same number vertices is * stored here. * \param normalized Boolean, whether to calculate a normalized * centralization score. See \ref igraph_centralization() for how * the normalization is done. * \return Error code. * * \sa \ref igraph_centralization(), \ref igraph_betweenness(). * * Time complexity: the complexity of \ref igraph_betweenness() plus * O(n), the number of vertices queried, for calculating the * centralization score. */ int igraph_centralization_betweenness(const igraph_t *graph, igraph_vector_t *res, igraph_bool_t directed, igraph_bool_t nobigint, igraph_real_t *centralization, igraph_real_t *theoretical_max, igraph_bool_t normalized) { igraph_vector_t myscores; igraph_vector_t *scores = res; igraph_real_t *tmax = theoretical_max, mytmax; if (!tmax) { tmax = &mytmax; } if (!res) { scores = &myscores; IGRAPH_VECTOR_INIT_FINALLY(scores, 0); } IGRAPH_CHECK(igraph_betweenness(graph, scores, igraph_vss_all(), directed, /*weights=*/ 0, nobigint)); IGRAPH_CHECK(igraph_centralization_betweenness_tmax(graph, 0, directed, tmax)); *centralization = igraph_centralization(scores, *tmax, normalized); if (!res) { igraph_vector_destroy(scores); IGRAPH_FINALLY_CLEAN(1); } return 0; } /** * \function igraph_centralization_betweenness_tmax * Theoretical maximum for graph centralization based on betweenness * * This function returns the theoretical maximum graph centrality * based on vertex betweenness. * * * There are two ways to call this function, the first is to supply a * graph as the graph argument, and then the number of * vertices is taken from this object, and its directedness is * considered as well. The nodes argument is ignored in * this case. The directed argument is also ignored if the * supplied graph is undirected. * * * The other way is to supply a null pointer as the graph * argument. In this case the nodes and directed * arguments are considered. * * * The most centralized structure is the star. * \param graph A graph object or a null pointer, see the description * above. * \param nodes The number of nodes. This is ignored if the * graph argument is not a null pointer. * \param directed Boolean scalar, whether to use directed paths in * the betweenness calculation. This argument is ignored if * graph is not a null pointer and it is undirected. * \param res Pointer to a real variable, the result is stored here. * \return Error code. * * Time complexity: O(1). * * \sa \ref igraph_centralization_betweenness() and \ref * igraph_centralization(). */ int igraph_centralization_betweenness_tmax(const igraph_t *graph, igraph_integer_t nodes, igraph_bool_t directed, igraph_real_t *res) { igraph_real_t real_nodes; if (graph) { directed = directed && igraph_is_directed(graph); nodes = igraph_vcount(graph); } real_nodes = nodes; /* implicit cast to igraph_real_t */ if (directed) { *res = (real_nodes - 1) * (real_nodes - 1) * (real_nodes - 2); } else { *res = (real_nodes - 1) * (real_nodes - 1) * (real_nodes - 2) / 2.0; } return 0; } /** * \function igraph_centralization_closeness * Calculate vertex closeness and graph centralization * * This function calculates the closeness centrality of the vertices * by passing its arguments to \ref igraph_closeness(); and it * calculates the graph level centralization index based on the * results by calling \ref igraph_centralization(). * \param graph The input graph. * \param res A vector if you need the node-level closeness scores, or a * null pointer otherwise. * \param mode Constant the specifies the type of closeness for directed * graphs. Possible values: \c IGRAPH_IN, \c IGRAPH_OUT and \c * IGRAPH_ALL. This argument is ignored for undirected graphs. See * \ref igraph_closeness() argument with the same name for more. * \param centralization Pointer to a real number, the centralization * score is placed here. * \param theoretical_max Pointer to real number or a null pointer. If * not a null pointer, then the theoretical maximum graph * centrality score for a graph with the same number vertices is * stored here. * \param normalized Boolean, whether to calculate a normalized * centralization score. See \ref igraph_centralization() for how * the normalization is done. * \return Error code. * * \sa \ref igraph_centralization(), \ref igraph_closeness(). * * Time complexity: the complexity of \ref igraph_closeness() plus * O(n), the number of vertices queried, for calculating the * centralization score. */ int igraph_centralization_closeness(const igraph_t *graph, igraph_vector_t *res, igraph_neimode_t mode, igraph_real_t *centralization, igraph_real_t *theoretical_max, igraph_bool_t normalized) { igraph_vector_t myscores; igraph_vector_t *scores = res; igraph_real_t *tmax = theoretical_max, mytmax; if (!tmax) { tmax = &mytmax; } if (!res) { scores = &myscores; IGRAPH_VECTOR_INIT_FINALLY(scores, 0); } IGRAPH_CHECK(igraph_closeness(graph, scores, igraph_vss_all(), mode, /*weights=*/ 0, /*normalize=*/ 1)); IGRAPH_CHECK(igraph_centralization_closeness_tmax(graph, 0, mode, tmax)); *centralization = igraph_centralization(scores, *tmax, normalized); if (!res) { igraph_vector_destroy(scores); IGRAPH_FINALLY_CLEAN(1); } return 0; } /** * \function igraph_centralization_closeness_tmax * Theoretical maximum for graph centralization based on closeness * * This function returns the theoretical maximum graph centrality * based on vertex closeness. * * * There are two ways to call this function, the first is to supply a * graph as the graph argument, and then the number of * vertices is taken from this object, and its directedness is * considered as well. The nodes argument is ignored in * this case. The mode argument is also ignored if the * supplied graph is undirected. * * * The other way is to supply a null pointer as the graph * argument. In this case the nodes and mode * arguments are considered. * * * The most centralized structure is the star. * \param graph A graph object or a null pointer, see the description * above. * \param nodes The number of nodes. This is ignored if the * graph argument is not a null pointer. * \param mode Constant, specifies what kinf of distances to consider * to calculate closeness. See the mode argument of * \ref igraph_closeness() for details. This argument is ignored * if graph is not a null pointer and it is * undirected. * \param res Pointer to a real variable, the result is stored here. * \return Error code. * * Time complexity: O(1). * * \sa \ref igraph_centralization_closeness() and \ref * igraph_centralization(). */ int igraph_centralization_closeness_tmax(const igraph_t *graph, igraph_integer_t nodes, igraph_neimode_t mode, igraph_real_t *res) { igraph_real_t real_nodes; if (graph) { nodes = igraph_vcount(graph); if (!igraph_is_directed(graph)) { mode = IGRAPH_ALL; } } real_nodes = nodes; /* implicit cast to igraph_real_t */ if (mode != IGRAPH_ALL) { *res = (real_nodes - 1) * (1.0 - 1.0 / real_nodes); } else { *res = (real_nodes - 1) * (real_nodes - 2) / (2.0 * real_nodes - 3); } return 0; } /** * \function igraph_centralization_eigenvector_centrality * Calculate eigenvector centrality scores and graph centralization * * This function calculates the eigenvector centrality of the vertices * by passing its arguments to \ref igraph_eigenvector_centrality); * and it calculates the graph level centralization index based on the * results by calling \ref igraph_centralization(). * \param graph The input graph. * \param vector A vector if you need the node-level eigenvector * centrality scores, or a null pointer otherwise. * \param value If not a null pointer, then the leading eigenvalue is * stored here. * \param scale If not zero then the result will be scaled, such that * the absolute value of the maximum centrality is one. * \param options Options to ARPACK. See \ref igraph_arpack_options_t * for details. Note that the function overwrites the * n (number of vertices) parameter and * it always starts the calculation from a non-random vector * calculated based on the degree of the vertices. * \param centralization Pointer to a real number, the centralization * score is placed here. * \param theoretical_max Pointer to real number or a null pointer. If * not a null pointer, then the theoretical maximum graph * centrality score for a graph with the same number vertices is * stored here. * \param normalized Boolean, whether to calculate a normalized * centralization score. See \ref igraph_centralization() for how * the normalization is done. * \return Error code. * * \sa \ref igraph_centralization(), \ref igraph_eigenvector_centrality(). * * Time complexity: the complexity of \ref * igraph_eigenvector_centrality() plus O(|V|), the number of vertices * for the calculating the centralization. */ int igraph_centralization_eigenvector_centrality( const igraph_t *graph, igraph_vector_t *vector, igraph_real_t *value, igraph_bool_t directed, igraph_bool_t scale, igraph_arpack_options_t *options, igraph_real_t *centralization, igraph_real_t *theoretical_max, igraph_bool_t normalized) { igraph_vector_t myscores; igraph_vector_t *scores = vector; igraph_real_t realvalue, *myvalue = value; igraph_real_t *tmax = theoretical_max, mytmax; if (!tmax) { tmax = &mytmax; } if (!vector) { scores = &myscores; IGRAPH_VECTOR_INIT_FINALLY(scores, 0); } if (!value) { myvalue = &realvalue; } IGRAPH_CHECK(igraph_eigenvector_centrality(graph, scores, myvalue, directed, scale, /*weights=*/ 0, options)); IGRAPH_CHECK(igraph_centralization_eigenvector_centrality_tmax( graph, 0, directed, scale, tmax)); *centralization = igraph_centralization(scores, *tmax, normalized); if (!vector) { igraph_vector_destroy(scores); IGRAPH_FINALLY_CLEAN(1); } return 0; } /** * \function igraph_centralization_eigenvector_centrality_tmax * Theoretical maximum centralization for eigenvector centrality * * This function returns the theoretical maximum graph centrality * based on vertex eigenvector centrality. * * * There are two ways to call this function, the first is to supply a * graph as the graph argument, and then the number of * vertices is taken from this object, and its directedness is * considered as well. The nodes argument is ignored in * this case. The directed argument is also ignored if the * supplied graph is undirected. * * * The other way is to supply a null pointer as the graph * argument. In this case the nodes and directed * arguments are considered. * * * The most centralized directed structure is the in-star. The most * centralized undirected structure is the graph with a single edge. * \param graph A graph object or a null pointer, see the description * above. * \param nodes The number of nodes. This is ignored if the * graph argument is not a null pointer. * \param directed Boolean scalar, whether to consider edge * directions. This argument is ignored if * graph is not a null pointer and it is undirected. * \param scale Whether to rescale the node-level centrality scores to * have a maximum of one. * \param res Pointer to a real variable, the result is stored here. * \return Error code. * * Time complexity: O(1). * * \sa \ref igraph_centralization_closeness() and \ref * igraph_centralization(). */ int igraph_centralization_eigenvector_centrality_tmax( const igraph_t *graph, igraph_integer_t nodes, igraph_bool_t directed, igraph_bool_t scale, igraph_real_t *res) { if (graph) { nodes = igraph_vcount(graph); directed = directed && igraph_is_directed(graph); } if (directed) { *res = nodes - 1; } else { if (scale) { *res = nodes - 2; } else { *res = (nodes - 2.0) / M_SQRT2; } } return 0; } python-igraph-0.8.0/vendor/source/igraph/src/igraph_strvector.c0000644000076500000240000004075513614300625025142 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2003-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_types.h" #include "igraph_strvector.h" #include "igraph_memory.h" #include "igraph_random.h" #include "igraph_error.h" #include "config.h" #include #include /* memcpy & co. */ #include /** * \section igraph_strvector_t * The igraph_strvector_t type is a vector of strings. * The current implementation is very simple and not too efficient. It * works fine for not too many strings, e.g. the list of attribute * names is returned in a string vector by \ref * igraph_cattribute_list(). Do not expect great performance from this * type. * * * \example examples/simple/igraph_strvector.c * */ /** * \ingroup strvector * \function igraph_strvector_init * \brief Initialize * * Reserves memory for the string vector, a string vector must be * first initialized before calling other functions on it. * All elements of the string vector are set to the empty string. * \param sv Pointer to an initialized string vector. * \param len The (initial) length of the string vector. * \return Error code. * * Time complexity: O(\p len). */ int igraph_strvector_init(igraph_strvector_t *sv, long int len) { long int i; sv->data = igraph_Calloc(len, char*); if (sv->data == 0) { IGRAPH_ERROR("strvector init failed", IGRAPH_ENOMEM); } for (i = 0; i < len; i++) { sv->data[i] = igraph_Calloc(1, char); if (sv->data[i] == 0) { igraph_strvector_destroy(sv); IGRAPH_ERROR("strvector init failed", IGRAPH_ENOMEM); } sv->data[i][0] = '\0'; } sv->len = len; return 0; } /** * \ingroup strvector * \function igraph_strvector_destroy * \brief Free allocated memory * * Destroy a string vector. It may be reinitialized with \ref * igraph_strvector_init() later. * \param sv The string vector. * * Time complexity: O(l), the total length of the strings, maybe less * depending on the memory manager. */ void igraph_strvector_destroy(igraph_strvector_t *sv) { long int i; assert(sv != 0); if (sv->data != 0) { for (i = 0; i < sv->len; i++) { if (sv->data[i] != 0) { igraph_Free(sv->data[i]); } } igraph_Free(sv->data); } } /** * \ingroup strvector * \function igraph_strvector_get * \brief Indexing * * Query an element of a string vector. See also the \ref STR macro * for an easier way. * \param sv The input string vector. * \param idx The index of the element to query. * \param Pointer to a char*, the address of the string * is stored here. * * Time complexity: O(1). */ void igraph_strvector_get(const igraph_strvector_t *sv, long int idx, char **value) { assert(sv != 0); assert(sv->data != 0); assert(sv->data[idx] != 0); *value = sv->data[idx]; } /** * \ingroup strvector * \function igraph_strvector_set * \brief Set an element * * The provided \p value is copied into the \p idx position in the * string vector. * \param sv The string vector. * \param idx The position to set. * \param value The new value. * \return Error code. * * Time complexity: O(l), the length of the new string. Maybe more, * depending on the memory management, if reallocation is needed. */ int igraph_strvector_set(igraph_strvector_t *sv, long int idx, const char *value) { assert(sv != 0); assert(sv->data != 0); if (sv->data[idx] == 0) { sv->data[idx] = igraph_Calloc(strlen(value) + 1, char); if (sv->data[idx] == 0) { IGRAPH_ERROR("strvector set failed", IGRAPH_ENOMEM); } } else { char *tmp = igraph_Realloc(sv->data[idx], strlen(value) + 1, char); if (tmp == 0) { IGRAPH_ERROR("strvector set failed", IGRAPH_ENOMEM); } sv->data[idx] = tmp; } strcpy(sv->data[idx], value); return 0; } /** * \ingroup strvector * \function igraph_strvector_set2 * \brief Sets an element * * This is almost the same as \ref igraph_strvector_set, but the new * value is not a zero terminated string, but its length is given. * \param sv The string vector. * \param idx The position to set. * \param value The new value. * \param len The length of the new value. * \return Error code. * * Time complexity: O(l), the length of the new string. Maybe more, * depending on the memory management, if reallocation is needed. */ int igraph_strvector_set2(igraph_strvector_t *sv, long int idx, const char *value, int len) { assert(sv != 0); assert(sv->data != 0); if (sv->data[idx] == 0) { sv->data[idx] = igraph_Calloc(len + 1, char); if (sv->data[idx] == 0) { IGRAPH_ERROR("strvector set failed", IGRAPH_ENOMEM); } } else { char *tmp = igraph_Realloc(sv->data[idx], (size_t) len + 1, char); if (tmp == 0) { IGRAPH_ERROR("strvector set failed", IGRAPH_ENOMEM); } sv->data[idx] = tmp; } memcpy(sv->data[idx], value, (size_t) len * sizeof(char)); sv->data[idx][len] = '\0'; return 0; } /** * \ingroup strvector * \function igraph_strvector_remove_section * \brief Removes a section from a string vector. * \todo repair realloc */ void igraph_strvector_remove_section(igraph_strvector_t *v, long int from, long int to) { long int i; /* char **tmp; */ assert(v != 0); assert(v->data != 0); for (i = from; i < to; i++) { if (v->data[i] != 0) { igraph_Free(v->data[i]); } } for (i = 0; i < v->len - to; i++) { v->data[from + i] = v->data[to + i]; } v->len -= (to - from); /* try to make it smaller */ /* tmp=igraph_Realloc(v->data, v->len, char*); */ /* if (tmp!=0) { */ /* v->data=tmp; */ /* } */ } /** * \ingroup strvector * \function igraph_strvector_remove * \brief Removes a single element from a string vector. * * The string will be one shorter. * \param The string vector. * \param elem The index of the element to remove. * * Time complexity: O(n), the length of the string. */ void igraph_strvector_remove(igraph_strvector_t *v, long int elem) { assert(v != 0); assert(v->data != 0); igraph_strvector_remove_section(v, elem, elem + 1); } /** * \ingroup strvector * \function igraph_strvector_move_interval * \brief Copies an interval of a string vector. */ void igraph_strvector_move_interval(igraph_strvector_t *v, long int begin, long int end, long int to) { long int i; assert(v != 0); assert(v->data != 0); for (i = to; i < to + end - begin; i++) { if (v->data[i] != 0) { igraph_Free(v->data[i]); } } for (i = 0; i < end - begin; i++) { if (v->data[begin + i] != 0) { size_t len = strlen(v->data[begin + i]) + 1; v->data[to + i] = igraph_Calloc(len, char); memcpy(v->data[to + i], v->data[begin + i], sizeof(char)*len); } } } /** * \ingroup strvector * \function igraph_strvector_copy * \brief Initialization by copying. * * Initializes a string vector by copying another string vector. * \param to Pointer to an uninitialized string vector. * \param from The other string vector, to be copied. * \return Error code. * * Time complexity: O(l), the total length of the strings in \p from. */ int igraph_strvector_copy(igraph_strvector_t *to, const igraph_strvector_t *from) { long int i; char *str; assert(from != 0); /* assert(from->data != 0); */ to->data = igraph_Calloc(from->len, char*); if (to->data == 0) { IGRAPH_ERROR("Cannot copy string vector", IGRAPH_ENOMEM); } to->len = from->len; for (i = 0; i < from->len; i++) { int ret; igraph_strvector_get(from, i, &str); ret = igraph_strvector_set(to, i, str); if (ret != 0) { igraph_strvector_destroy(to); IGRAPH_ERROR("cannot copy string vector", ret); } } return 0; } /** * \function igraph_strvector_append * Concatenate two string vectors. * * \param to The first string vector, the result is stored here. * \param from The second string vector, it is kept unchanged. * \return Error code. * * Time complexity: O(n+l2), n is the number of strings in the new * string vector, l2 is the total length of strings in the \p from * string vector. */ int igraph_strvector_append(igraph_strvector_t *to, const igraph_strvector_t *from) { long int len1 = igraph_strvector_size(to), len2 = igraph_strvector_size(from); long int i; igraph_bool_t error = 0; IGRAPH_CHECK(igraph_strvector_resize(to, len1 + len2)); for (i = 0; i < len2; i++) { if (from->data[i][0] != '\0') { igraph_Free(to->data[len1 + i]); to->data[len1 + i] = strdup(from->data[i]); if (!to->data[len1 + i]) { error = 1; break; } } } if (error) { igraph_strvector_resize(to, len1); IGRAPH_ERROR("Cannot append string vector", IGRAPH_ENOMEM); } return 0; } /** * \function igraph_strvector_clear * Remove all elements * * After this operation the string vector will be empty. * \param sv The string vector. * * Time complexity: O(l), the total length of strings, maybe less, * depending on the memory manager. */ void igraph_strvector_clear(igraph_strvector_t *sv) { long int i, n = igraph_strvector_size(sv); char **tmp; for (i = 0; i < n; i++) { igraph_Free(sv->data[i]); } sv->len = 0; /* try to give back some memory */ tmp = igraph_Realloc(sv->data, 1, char*); if (tmp != 0) { sv->data = tmp; } } /** * \ingroup strvector * \function igraph_strvector_resize * \brief Resize * * If the new size is bigger then empty strings are added, if it is * smaller then the unneeded elements are removed. * \param v The string vector. * \param newsize The new size. * \return Error code. * * Time complexity: O(n), the number of strings if the vector is made * bigger, O(l), the total length of the deleted strings if it is made * smaller, maybe less, depending on memory management. */ int igraph_strvector_resize(igraph_strvector_t* v, long int newsize) { long int toadd = newsize - v->len, i, j; char **tmp; long int reallocsize = newsize; if (reallocsize == 0) { reallocsize = 1; } assert(v != 0); assert(v->data != 0); /* printf("resize %li to %li\n", v->len, newsize); */ if (newsize < v->len) { for (i = newsize; i < v->len; i++) { igraph_Free(v->data[i]); } /* try to give back some space */ tmp = igraph_Realloc(v->data, (size_t) reallocsize, char*); /* printf("resize %li to %li, %p\n", v->len, newsize, tmp); */ if (tmp != 0) { v->data = tmp; } } else if (newsize > v->len) { igraph_bool_t error = 0; tmp = igraph_Realloc(v->data, (size_t) reallocsize, char*); if (tmp == 0) { IGRAPH_ERROR("cannot resize string vector", IGRAPH_ENOMEM); } v->data = tmp; for (i = 0; i < toadd; i++) { v->data[v->len + i] = igraph_Calloc(1, char); if (v->data[v->len + i] == 0) { error = 1; break; } v->data[v->len + i][0] = '\0'; } if (error) { /* There was an error, free everything we've allocated so far */ for (j = 0; j < i; j++) { if (v->data[v->len + i] != 0) { igraph_Free(v->data[v->len + i]); } } /* Try to give back space */ tmp = igraph_Realloc(v->data, (size_t) (v->len), char*); if (tmp != 0) { v->data = tmp; } IGRAPH_ERROR("Cannot resize string vector", IGRAPH_ENOMEM); } } v->len = newsize; return 0; } /** * \ingroup strvector * \function igraph_strvector_size * \brief Gives the size of a string vector. * * \param sv The string vector. * \return The length of the string vector. * * Time complexity: O(1). */ long int igraph_strvector_size(const igraph_strvector_t *sv) { assert(sv != 0); assert(sv->data != 0); return sv->len; } /** * \ingroup strvector * \function igraph_strvector_add * \brief Adds an element to the back of a string vector. * * \param v The string vector. * \param value The string to add, it will be copied. * \return Error code. * * Time complexity: O(n+l), n is the total number of strings, l is the * length of the new string. */ int igraph_strvector_add(igraph_strvector_t *v, const char *value) { long int s = igraph_strvector_size(v); char **tmp; assert(v != 0); assert(v->data != 0); tmp = igraph_Realloc(v->data, (size_t) s + 1, char*); if (tmp == 0) { IGRAPH_ERROR("cannot add string to string vector", IGRAPH_ENOMEM); } v->data = tmp; v->data[s] = igraph_Calloc(strlen(value) + 1, char); if (v->data[s] == 0) { IGRAPH_ERROR("cannot add string to string vector", IGRAPH_ENOMEM); } strcpy(v->data[s], value); v->len += 1; return 0; } /** * \ingroup strvector * \function igraph_strvector_permdelete * \brief Removes elements from a string vector (for internal use) */ void igraph_strvector_permdelete(igraph_strvector_t *v, const igraph_vector_t *index, long int nremove) { long int i; char **tmp; assert(v != 0); assert(v->data != 0); for (i = 0; i < igraph_strvector_size(v); i++) { if (VECTOR(*index)[i] != 0) { v->data[ (long int) VECTOR(*index)[i] - 1 ] = v->data[i]; } else { igraph_Free(v->data[i]); } } /* Try to make it shorter */ tmp = igraph_Realloc(v->data, v->len - nremove ? (size_t) (v->len - nremove) : 1, char*); if (tmp != 0) { v->data = tmp; } v->len -= nremove; } /** * \ingroup strvector * \function igraph_strvector_remove_negidx * \brief Removes elements from a string vector (for internal use) */ void igraph_strvector_remove_negidx(igraph_strvector_t *v, const igraph_vector_t *neg, long int nremove) { long int i, idx = 0; char **tmp; assert(v != 0); assert(v->data != 0); for (i = 0; i < igraph_strvector_size(v); i++) { if (VECTOR(*neg)[i] >= 0) { v->data[idx++] = v->data[i]; } else { igraph_Free(v->data[i]); } } /* Try to give back some memory */ tmp = igraph_Realloc(v->data, v->len - nremove ? (size_t) (v->len - nremove) : 1, char*); if (tmp != 0) { v->data = tmp; } v->len -= nremove; } int igraph_strvector_print(const igraph_strvector_t *v, FILE *file, const char *sep) { long int i, n = igraph_strvector_size(v); if (n != 0) { fprintf(file, "%s", STR(*v, 0)); } for (i = 1; i < n; i++) { fprintf(file, "%s%s", sep, STR(*v, i)); } return 0; } int igraph_strvector_index(const igraph_strvector_t *v, igraph_strvector_t *newv, const igraph_vector_t *idx) { long int i, newlen = igraph_vector_size(idx); IGRAPH_CHECK(igraph_strvector_resize(newv, newlen)); for (i = 0; i < newlen; i++) { long int j = (long int) VECTOR(*idx)[i]; char *str; igraph_strvector_get(v, j, &str); igraph_strvector_set(newv, i, str); } return 0; } python-igraph-0.8.0/vendor/source/igraph/src/infomap_FlowGraph.h0000644000076500000240000000407213614300625025154 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef FLOWGRAPH_H #define FLOWGRAPH_H #include #include #include "igraph_interface.h" #include "infomap_Node.h" class FlowGraph { private: void init(int n, const igraph_vector_t *nodeWeights); public: FlowGraph(int n); FlowGraph(int n, const igraph_vector_t *nodeWeights); FlowGraph(FlowGraph * fgraph); FlowGraph(FlowGraph * fgraph, int sub_Nnode, int * sub_members); FlowGraph(const igraph_t * graph, const igraph_vector_t *e_weights, const igraph_vector_t *v_weights); ~FlowGraph(); void swap(FlowGraph * fgraph); void initiate(); void eigenvector(); void calibrate(); void back_to(FlowGraph * fgraph); /*************************************************************************/ Node **node; int Nnode; double alpha, beta; int Ndanglings; vector danglings; // id of dangling nodes double exit; // double exitFlow; // double exit_log_exit; // double size_log_size; // double nodeSize_log_nodeSize; // \sum_{v in V} p log(p) double codeLength; }; void delete_FlowGraph(FlowGraph *fgraph); #endif python-igraph-0.8.0/vendor/source/igraph/src/igraph_arpack_internal.h0000644000076500000240000002036613614300625026245 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef ARPACK_INTERNAL_H #define ARPACK_INTERNAL_H /* Note: only files calling the arpack routines directly need to include this header. */ #include "igraph_types.h" #include "config.h" #ifndef INTERNAL_ARPACK #define igraphdsaupd_ dsaupd_ #define igraphdseupd_ dseupd_ #define igraphdsaup2_ dsaup2_ #define igraphdstats_ dstats_ #define igraphdsesrt_ dsesrt_ #define igraphdsortr_ dsortr_ #define igraphdsortc_ dsortc_ #define igraphdgetv0_ dgetv0_ #define igraphdsaitr_ dsaitr_ #define igraphdsapps_ dsapps_ #define igraphdsconv_ dsconv_ #define igraphdseigt_ dseigt_ #define igraphdsgets_ dsgets_ #define igraphdstqrb_ dstqrb_ #define igraphdmout_ dmout_ #define igraphivout_ ivout_ #define igraphsecond_ second_ #define igraphdvout_ dvout_ #define igraphdnaitr_ dnaitr_ #define igraphdnapps_ dnapps_ #define igraphdnaup2_ dnaup2_ #define igraphdnaupd_ dnaupd_ #define igraphdnconv_ dnconv_ #define igraphdlabad_ dlabad_ #define igraphdlanhs_ dlanhs_ #define igraphdsortc_ dsortc_ #define igraphdneigh_ dneigh_ #define igraphdngets_ dngets_ #define igraphdstatn_ dstatn_ #define igraphdlaqrb_ dlaqrb_ #define igraphdsaupd_ dsaupd_ #define igraphdseupd_ dseupd_ #define igraphdnaupd_ dnaupd_ #define igraphdneupd_ dneupd_ #endif #ifndef INTERNAL_LAPACK #define igraphdlarnv_ dlarnv_ #define igraphdlascl_ dlascl_ #define igraphdlartg_ dlartg_ #define igraphdlaset_ dlaset_ #define igraphdlae2_ dlae2_ #define igraphdlaev2_ dlaev2_ #define igraphdlasr_ dlasr_ #define igraphdlasrt_ dlasrt_ #define igraphdgeqr2_ dgeqr2_ #define igraphdlacpy_ dlacpy_ #define igraphdorm2r_ dorm2r_ #define igraphdsteqr_ dsteqr_ #define igraphdlanst_ dlanst_ #define igraphdlapy2_ dlapy2_ #define igraphdlamch_ dlamch_ #define igraphdlaruv_ dlaruv_ #define igraphdlarfg_ dlarfg_ #define igraphdlarf_ dlarf_ #define igraphdlassq_ dlassq_ #define igraphdlamc2_ dlamc2_ #define igraphdlamc1_ dlamc1_ #define igraphdlamc2_ dlamc2_ #define igraphdlamc3_ dlamc3_ #define igraphdlamc4_ dlamc4_ #define igraphdlamc5_ dlamc5_ #define igraphdlabad_ dlabad_ #define igraphdlanhs_ dlanhs_ #define igraphdtrevc_ dtrevc_ #define igraphdlanv2_ dlanv2_ #define igraphdlaln2_ dlaln2_ #define igraphdladiv_ dladiv_ #define igraphdtrsen_ dtrsen_ #define igraphdlahqr_ dlahqr_ #define igraphdtrsen_ dtrsen_ #define igraphdlacon_ dlacon_ #define igraphdtrsyl_ dtrsyl_ #define igraphdtrexc_ dtrexc_ #define igraphdlange_ dlange_ #define igraphdlaexc_ dlaexc_ #define igraphdlasy2_ dlasy2_ #define igraphdlarfx_ dlarfx_ #endif #if 0 /* internal f2c functions always used */ #define igraphd_sign d_sign #define igraphetime_ etime_ #define igraphpow_dd pow_dd #define igraphpow_di pow_di #define igraphs_cmp s_cmp #define igraphs_copy s_copy #define igraphd_lg10_ d_lg10_ #define igraphi_dnnt_ i_dnnt_ #endif #ifdef HAVE_GFORTRAN int igraphdsaupd_(int *ido, char *bmat, int *n, char *which, int *nev, igraph_real_t *tol, igraph_real_t *resid, int *ncv, igraph_real_t *v, int *ldv, int *iparam, int *ipntr, igraph_real_t *workd, igraph_real_t *workl, int *lworkl, int *info, int bmat_len, int which_len); int igraphdseupd_(int *rvec, char *howmny, int *select, igraph_real_t *d, igraph_real_t *z, int *ldz, igraph_real_t *sigma, char *bmat, int *n, char *which, int *nev, igraph_real_t *tol, igraph_real_t *resid, int *ncv, igraph_real_t *v, int *ldv, int *iparam, int *ipntr, igraph_real_t *workd, igraph_real_t *workl, int *lworkl, int *info, int howmny_len, int bmat_len, int which_len); int igraphdnaupd_(int *ido, char *bmat, int *n, char *which, int *nev, igraph_real_t *tol, igraph_real_t *resid, int *ncv, igraph_real_t *v, int *ldv, int *iparam, int *ipntr, igraph_real_t *workd, igraph_real_t *workl, int *lworkl, int *info, int bmat_len, int which_len); int igraphdneupd_(int *rvec, char *howmny, int *select, igraph_real_t *dr, igraph_real_t *di, igraph_real_t *z, int *ldz, igraph_real_t *sigmar, igraph_real_t *sigmai, igraph_real_t *workev, char *bmat, int *n, char *which, int *nev, igraph_real_t *tol, igraph_real_t *resid, int *ncv, igraph_real_t *v, int *ldv, int *iparam, int *ipntr, igraph_real_t *workd, igraph_real_t *workl, int *lworkl, int *info, int howmny_len, int bmat_len, int which_len); int igraphdsortr_(char *which, int *apply, int* n, igraph_real_t *x1, igraph_real_t *x2, int which_len); int igraphdsortc_(char *which, int *apply, int* n, igraph_real_t *xreal, igraph_real_t *ximag, igraph_real_t *y, int which_len); #else int igraphdsaupd_(int *ido, char *bmat, int *n, char *which, int *nev, igraph_real_t *tol, igraph_real_t *resid, int *ncv, igraph_real_t *v, int *ldv, int *iparam, int *ipntr, igraph_real_t *workd, igraph_real_t *workl, int *lworkl, int *info); int igraphdseupd_(int *rvec, char *howmny, int *select, igraph_real_t *d, igraph_real_t *z, int *ldz, igraph_real_t *sigma, char *bmat, int *n, char *which, int *nev, igraph_real_t *tol, igraph_real_t *resid, int *ncv, igraph_real_t *v, int *ldv, int *iparam, int *ipntr, igraph_real_t *workd, igraph_real_t *workl, int *lworkl, int *info); int igraphdnaupd_(int *ido, char *bmat, int *n, char *which, int *nev, igraph_real_t *tol, igraph_real_t *resid, int *ncv, igraph_real_t *v, int *ldv, int *iparam, int *ipntr, igraph_real_t *workd, igraph_real_t *workl, int *lworkl, int *info); int igraphdneupd_(int *rvec, char *howmny, int *select, igraph_real_t *dr, igraph_real_t *di, igraph_real_t *z, int *ldz, igraph_real_t *sigmar, igraph_real_t *sigmai, igraph_real_t *workev, char *bmat, int *n, char *which, int *nev, igraph_real_t *tol, igraph_real_t *resid, int *ncv, igraph_real_t *v, int *ldv, int *iparam, int *ipntr, igraph_real_t *workd, igraph_real_t *workl, int *lworkl, int *info); int igraphdsortr_(char *which, int *apply, int* n, igraph_real_t *x1, igraph_real_t *x2); int igraphdsortc_(char *which, int *apply, int* n, igraph_real_t *xreal, igraph_real_t *ximag, igraph_real_t *y); #endif #endif /* ARPACK_INTERNAL_H */ python-igraph-0.8.0/vendor/source/igraph/src/scg_kmeans.c0000644000076500000240000000661613614300625023665 0ustar tamasstaff00000000000000/* * SCGlib : A C library for the spectral coarse graining of matrices * as described in the paper: Shrinking Matrices while preserving their * eigenpairs with Application to the Spectral Coarse Graining of Graphs. * Preprint available at * * Copyright (C) 2008 David Morton de Lachapelle * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 2 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA * 02110-1301 USA * * DESCRIPTION * ----------- * The kmeans_Lloyd function is adapted from the R-stats package. * It perfoms Lloyd's k-means clustering on a p x n data matrix * stored row-wise in a vector 'x'. 'cen' contains k initial centers. * The group label to which each object belongs is stored in 'cl'. * Labels are positive consecutive integers starting from 0. * See also Section 5.3.3 of the above reference. */ #include "igraph_memory.h" #include "scg_headers.h" int igraph_i_kmeans_Lloyd(const igraph_vector_t *x, int n, int p, igraph_vector_t *cen, int k, int *cl, int maxiter) { int iter, i, j, c, it, inew = 0; igraph_real_t best, dd, tmp; int updated; igraph_vector_int_t nc; IGRAPH_CHECK(igraph_vector_int_init(&nc, k)); IGRAPH_FINALLY(igraph_vector_int_destroy, &nc); for (i = 0; i < n; i++) { cl[i] = -1; } for (iter = 0; iter < maxiter; iter++) { updated = 0; for (i = 0; i < n; i++) { /* find nearest centre for each point */ best = IGRAPH_INFINITY; for (j = 0; j < k; j++) { dd = 0.0; for (c = 0; c < p; c++) { tmp = VECTOR(*x)[i + n * c] - VECTOR(*cen)[j + k * c]; dd += tmp * tmp; } if (dd < best) { best = dd; inew = j + 1; } } if (cl[i] != inew) { updated = 1; cl[i] = inew; } } if (!updated) { break; } /* update each centre */ for (j = 0; j < k * p; j++) { VECTOR(*cen)[j] = 0.0; } for (j = 0; j < k; j++) { VECTOR(nc)[j] = 0; } for (i = 0; i < n; i++) { it = cl[i] - 1; VECTOR(nc)[it]++; for (c = 0; c < p; c++) { VECTOR(*cen)[it + c * k] += VECTOR(*x)[i + c * n]; } } for (j = 0; j < k * p; j++) { VECTOR(*cen)[j] /= VECTOR(nc)[j % k]; } } igraph_vector_int_destroy(&nc); IGRAPH_FINALLY_CLEAN(1); /* convervenge check */ if (iter >= maxiter - 1) { IGRAPH_ERROR("Lloyd k-means did not converge", IGRAPH_FAILURE); } return 0; } python-igraph-0.8.0/vendor/source/igraph/src/drl_Node.h0000644000076500000240000000440513614300625023300 0ustar tamasstaff00000000000000/* * Copyright 2007 Sandia Corporation. Under the terms of Contract * DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains * certain rights in this software. * * All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are * met: * * * Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * Neither the name of Sandia National Laboratories nor the names of * its contributors may be used to endorse or promote products derived from * this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT * OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED * TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF * LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING * NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. */ #ifndef __NODE_H__ #define __NODE_H__ // The node class contains information about a given node for // use by the density server process. // structure coord used to pass position information between // density server and graph class namespace drl { class Node { public: bool fixed; // if true do not change the // position of this node int id; float x, y; float sub_x, sub_y; float energy; public: Node( int node_id ) { x = y = 0.0; fixed = false; id = node_id; } ~Node() { } }; } // namespace drl #endif //__NODE_H__ python-igraph-0.8.0/vendor/source/igraph/src/blas.c0000644000076500000240000000752613614300625022475 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_blas.h" #include "igraph_blas_internal.h" #include /** * \function igraph_blas_dgemv * \brief Matrix-vector multiplication using BLAS, vector version. * * This function is a somewhat more user-friendly interface to * the \c dgemv function in BLAS. \c dgemv performs the operation * y = alpha*A*x + beta*y, where x and y are vectors and A is an * appropriately sized matrix (symmetric or unsymmetric). * * \param transpose whether to transpose the matrix \p A * \param alpha the constant \p alpha * \param a the matrix \p A * \param x the vector \p x * \param beta the constant \p beta * \param y the vector \p y (which will be modified in-place) * * Time complexity: O(nk) if the matrix is of size n x k * * \sa \ref igraph_blas_dgemv_array if you have arrays instead of * vectors. * * \example examples/simple/blas.c */ void igraph_blas_dgemv(igraph_bool_t transpose, igraph_real_t alpha, const igraph_matrix_t* a, const igraph_vector_t* x, igraph_real_t beta, igraph_vector_t* y) { char trans = transpose ? 'T' : 'N'; int m, n; int inc = 1; m = (int) igraph_matrix_nrow(a); n = (int) igraph_matrix_ncol(a); assert(igraph_vector_size(x) == transpose ? m : n); assert(igraph_vector_size(y) == transpose ? n : m); igraphdgemv_(&trans, &m, &n, &alpha, VECTOR(a->data), &m, VECTOR(*x), &inc, &beta, VECTOR(*y), &inc); } /** * \function igraph_blas_dgemv_array * \brief Matrix-vector multiplication using BLAS, array version. * * This function is a somewhat more user-friendly interface to * the \c dgemv function in BLAS. \c dgemv performs the operation * y = alpha*A*x + beta*y, where x and y are vectors and A is an * appropriately sized matrix (symmetric or unsymmetric). * * \param transpose whether to transpose the matrix \p A * \param alpha the constant \p alpha * \param a the matrix \p A * \param x the vector \p x as a regular C array * \param beta the constant \p beta * \param y the vector \p y as a regular C array * (which will be modified in-place) * * Time complexity: O(nk) if the matrix is of size n x k * * \sa \ref igraph_blas_dgemv if you have vectors instead of * arrays. */ void igraph_blas_dgemv_array(igraph_bool_t transpose, igraph_real_t alpha, const igraph_matrix_t* a, const igraph_real_t* x, igraph_real_t beta, igraph_real_t* y) { char trans = transpose ? 'T' : 'N'; int m, n; int inc = 1; m = (int) igraph_matrix_nrow(a); n = (int) igraph_matrix_ncol(a); igraphdgemv_(&trans, &m, &n, &alpha, VECTOR(a->data), &m, (igraph_real_t*)x, &inc, &beta, y, &inc); } igraph_real_t igraph_blas_dnrm2(const igraph_vector_t *v) { int n = igraph_vector_size(v); int one = 1; return igraphdnrm2_(&n, VECTOR(*v), &one); } python-igraph-0.8.0/vendor/source/igraph/src/hrg_dendro.h0000644000076500000240000002677613614300625023704 0ustar tamasstaff00000000000000/* -*- mode: C++ -*- */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ // **************************************************************************************************** // *** COPYRIGHT NOTICE ******************************************************************************* // dendro_eq.h - hierarchical random graph (hrg) data structure // Copyright (C) 2006-2008 Aaron Clauset // // This program is free software; you can redistribute it and/or modify // it under the terms of the GNU General Public License as published by // the Free Software Foundation; either version 2 of the License, or // (at your option) any later version. // // This program is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU General Public License for more details. // // You should have received a copy of the GNU General Public License // along with this program; if not, write to the Free Software // Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA // // See http://www.gnu.org/licenses/gpl.txt for more details. // // **************************************************************************************************** // Author : Aaron Clauset ( aaronc@santafe.edu | http://www.santafe.edu/~aaronc/ ) // Collaborators: Cristopher Moore and Mark E.J. Newman // Project : Hierarchical Random Graphs // Location : University of New Mexico, Dept. of Computer Science AND Santa Fe Institute // Created : 19 April 2006 // Modified : 19 May 2007 // : 19 May 2008 (cleaned up for public consumption) // // **************************************************************************************************** // // Maximum likelihood dendrogram data structure. This is the heart of the HRG algorithm: all // manipulations are done here and all data is stored here. The data structure uses the separate // graph data structure to store the basic adjacency information (in a dangerously mutable way). // // Note: This version (dendro_eq.h) differs from other versions because it includes methods for // doing the consensus dendrogram calculation. // // **************************************************************************************************** #ifndef IGRAPH_HRG_DENDRO #define IGRAPH_HRG_DENDRO #include #include #include #include #include "hrg_graph.h" #include "hrg_rbtree.h" #include "hrg_splittree_eq.h" #include "igraph_hrg.h" using namespace std; using namespace fitHRG; namespace fitHRG { // *********************************************************************** // ******** Basic Structures ********************************************* #ifndef IGRAPH_HRG_LIST #define IGRAPH_HRG_LIST class list { public: int x; // stored elementd in linked-list list* next; // pointer to next elementd list::list(): x(-1), next(0) { } list::~list() { } }; #endif enum {DENDRO, GRAPH, LEFT, RIGHT}; struct block { double x; int y; }; struct ipair { int x; int y; short int t; string sp; }; struct child { int index; short int type; child* next; }; // *********************************************************************** // ******** Cnode Class ************************************************** #ifndef IGRAPH_HRG_CNODE #define IGRAPH_HRG_CNODE class cnode { public: int index; // array index of this node int degree; // number of children in list int parent; // index of parent node double weight; // sampled posterior weight child* children; // list of children (and their types) child* lastChild; // pointer to last child in list cnode(): index(-1), degree(0), parent(-1), weight(0.0), children(0), lastChild(0) { } ~cnode() { child *curr, *prev; curr = children; while (curr != NULL) { prev = curr; curr = curr->next; delete prev; prev = NULL; } lastChild = NULL; } }; #endif // *********************************************************************** // ******** Split Class ************************************************** class split { public: string s; // partition assignment of leaf vertices split(): s("") { } ~split() { } void initializeSplit(const int n) { s = ""; for (int i = 0; i < n; i++) { s += "-"; } } bool checkSplit() { if (s.empty() || s.find("-", 0) != string::npos) { return false; } else { return true; } } }; // *********************************************************************** // ******** Internal Edge Class ****************************************** // The usefulness of this data structure is to provide an easy to way // maintain the set of internal edges, and the corresponding splits, // in the dendrogram D. It allows for the selection of a random // internal edge in O(1) time, and it takes O(1) time to update its // structure given an internal move. This structure does not provide // any means to directly manipulate the splits, but does allow them to // be replaced. A split has the form "int.int...int#int.int...int", // where all ints on the left side of the # are in the left partition // and all ints on the right side of the # marker are in the right // partition defined by the split. class interns { private: ipair* edgelist; // list of internal edges represented string* splitlist; // split representation of the internal edges int** indexLUT; // table of indices of internal edges in edgelist int q; // number of internal edges int count; // (for adding edges) edgelist index of new edge to add public: interns(const int); ~interns(); // add an internal edge, O(1) bool addEdge(const int, const int, const short int); // returns the ith edge of edgelist, O(1) ipair* getEdge(const int); // returns a uniformly random internal edge, O(1) ipair* getRandomEdge(); // returns the ith split of the splitlist, O(1) string getSplit(const int); // replace an existing split, O(1) bool replaceSplit(const int, const string); // swaps two edges, O(1) bool swapEdges(const int, const int, const short int, const int, const int, const short int); }; // *********************************************************************** // ******** Tree elementd Class ****************************************** class elementd { public: short int type; // either DENDRO or GRAPH double logL; // log-likelihood contribution of this internal node double p; // probability p_i that an edge exists between L and // R subtrees int e; // number of edges between L and R subtrees int n; // number of leafs in subtree rooted here int label; // subtree label: smallest leaf index int index; // index in containing array elementd *M; // pointer to parent node elementd *L; // pointer for L subtree elementd *R; // pointer for R subtree elementd(): type(DENDRO), logL(0.0), p(0.0), e(0), n(0), label(-1), index(-1), M(0), L(0), R(0) { } ~elementd() { } }; // *********************************************************************** // ******** Dendrogram Class ********************************************* class dendro { private: elementd* root; // root of the dendrogram elementd* internal; // array of n-1 internal vertices (the dendrogram D) elementd* leaf; // array of n leaf vertices (the graph G) int n; // number of leaf vertices to allocate interns* d; // list of internal edges of dendrogram D splittree* splithist; // histogram of cumulative split weights list** paths; // array of path-lists from root to leaf double L; // log-likelihood of graph G given dendrogram D rbtree subtreeL, subtreeR; // trees for computeEdgeCount() function cnode* ctree; // (consensus tree) array of internal tree nodes int* cancestor; // (consensus tree) oldest ancetor's index for // each leaf // insert node i according to binary search property void binarySearchInsert(elementd*, elementd*); // return path to root from leaf list* binarySearchFind(const double); // build split for this internal edge string buildSplit(elementd*); // compute number of edges between two internal subtrees int computeEdgeCount(const int, const short int, const int, const short int); // (consensus tree) counts children int countChildren(const string); // find internal node of D that is common ancestor of i,j elementd* findCommonAncestor(list**, const int, const int); // return reverse of path to leaf from root list* reversePathToRoot(const int); // quicksort functions void QsortMain(block*, int, int); int QsortPartition(block*, int, int, int); public: // underlying G (dangerously accessible) graph* g; // constructor / destructor dendro(); ~dendro(); // build dendrogram from g void buildDendrogram(); // delete dendrograph in prep for importDendrogramStructure void clearDendrograph(); // read dendrogram structure from HRG structure bool importDendrogramStructure(const igraph_hrg_t *hrg); // (consensus tree) delete splits with less than 0.5 weight void cullSplitHist(); // return size of consensus split int getConsensusSize(); // return split tree with consensus splits splittree* getConsensusSplits(); // return likelihood of G given D double getLikelihood(); // store splits in this splittree void getSplitList(splittree*); // return total weight of splittree double getSplitTotalWeight(); // make random G from D void makeRandomGraph(); // make single MCMC move bool monteCarloMove(double&, bool&, const double); // record consensus tree from splithist void recordConsensusTree(igraph_vector_t *parents, igraph_vector_t *weights); // record D structure void recordDendrogramStructure(igraph_hrg_t *hrg); // record G structure to igraph graph void recordGraphStructure(igraph_t *graph); // force refresh of log-likelihood value void refreshLikelihood(); // sample dendrogram edge likelihoods and update edge histograms void sampleAdjacencyLikelihoods(); // reset the dendrograph structures void resetDendrograph(); // sample dendrogram's splits and update the split histogram bool sampleSplitLikelihoods(int&); // reset splits histogram void resetAllSplits(); }; } // namespace fitHRG #endif python-igraph-0.8.0/vendor/source/igraph/src/layout_fr.c0000644000076500000240000006754013614300625023562 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph R package. Copyright (C) 2014 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_layout.h" #include "igraph_random.h" #include "igraph_interface.h" #include "igraph_components.h" #include "igraph_types_internal.h" int igraph_layout_i_fr(const igraph_t *graph, igraph_matrix_t *res, igraph_bool_t use_seed, igraph_integer_t niter, igraph_real_t start_temp, const igraph_vector_t *weight, const igraph_vector_t *minx, const igraph_vector_t *maxx, const igraph_vector_t *miny, const igraph_vector_t *maxy) { igraph_integer_t no_nodes = igraph_vcount(graph); igraph_integer_t no_edges = igraph_ecount(graph); igraph_integer_t i; igraph_vector_float_t dispx, dispy; igraph_real_t temp = start_temp; igraph_real_t difftemp = start_temp / niter; float width = sqrtf(no_nodes), height = width; igraph_bool_t conn = 1; float C; igraph_is_connected(graph, &conn, IGRAPH_WEAK); if (!conn) { C = no_nodes * sqrtf(no_nodes); } RNG_BEGIN(); if (!use_seed) { IGRAPH_CHECK(igraph_matrix_resize(res, no_nodes, 2)); for (i = 0; i < no_nodes; i++) { igraph_real_t x1 = minx ? VECTOR(*minx)[i] : -width / 2; igraph_real_t x2 = maxx ? VECTOR(*maxx)[i] : width / 2; igraph_real_t y1 = miny ? VECTOR(*miny)[i] : -height / 2; igraph_real_t y2 = maxy ? VECTOR(*maxy)[i] : height / 2; if (!igraph_finite(x1)) { x1 = -sqrt(no_nodes) / 2; } if (!igraph_finite(x2)) { x2 = sqrt(no_nodes) / 2; } if (!igraph_finite(y1)) { y1 = -sqrt(no_nodes) / 2; } if (!igraph_finite(y2)) { y2 = sqrt(no_nodes) / 2; } MATRIX(*res, i, 0) = RNG_UNIF(x1, x2); MATRIX(*res, i, 1) = RNG_UNIF(y1, y2); } } IGRAPH_CHECK(igraph_vector_float_init(&dispx, no_nodes)); IGRAPH_FINALLY(igraph_vector_float_destroy, &dispx); IGRAPH_CHECK(igraph_vector_float_init(&dispy, no_nodes)); IGRAPH_FINALLY(igraph_vector_float_destroy, &dispy); for (i = 0; i < niter; i++) { igraph_integer_t v, u, e; /* calculate repulsive forces, we have a special version for unconnected graphs */ igraph_vector_float_null(&dispx); igraph_vector_float_null(&dispy); if (conn) { for (v = 0; v < no_nodes; v++) { for (u = v + 1; u < no_nodes; u++) { float dx = MATRIX(*res, v, 0) - MATRIX(*res, u, 0); float dy = MATRIX(*res, v, 1) - MATRIX(*res, u, 1); float dlen = dx * dx + dy * dy; if (dlen == 0) { dx = RNG_UNIF01() * 1e-9; dy = RNG_UNIF01() * 1e-9; dlen = dx * dx + dy * dy; } VECTOR(dispx)[v] += dx / dlen; VECTOR(dispy)[v] += dy / dlen; VECTOR(dispx)[u] -= dx / dlen; VECTOR(dispy)[u] -= dy / dlen; } } } else { for (v = 0; v < no_nodes; v++) { for (u = v + 1; u < no_nodes; u++) { float dx = MATRIX(*res, v, 0) - MATRIX(*res, u, 0); float dy = MATRIX(*res, v, 1) - MATRIX(*res, u, 1); float dlen, rdlen; dlen = dx * dx + dy * dy; if (dlen == 0) { dx = RNG_UNIF(0, 1e-6); dy = RNG_UNIF(0, 1e-6); dlen = dx * dx + dy * dy; } rdlen = sqrt(dlen); VECTOR(dispx)[v] += dx * (C - dlen * rdlen) / (dlen * C); VECTOR(dispy)[v] += dy * (C - dlen * rdlen) / (dlen * C); VECTOR(dispx)[u] -= dx * (C - dlen * rdlen) / (dlen * C); VECTOR(dispy)[u] -= dy * (C - dlen * rdlen) / (dlen * C); } } } /* calculate attractive forces */ for (e = 0; e < no_edges; e++) { /* each edges is an ordered pair of vertices v and u */ igraph_integer_t v = IGRAPH_FROM(graph, e); igraph_integer_t u = IGRAPH_TO(graph, e); igraph_real_t dx = MATRIX(*res, v, 0) - MATRIX(*res, u, 0); igraph_real_t dy = MATRIX(*res, v, 1) - MATRIX(*res, u, 1); igraph_real_t w = weight ? VECTOR(*weight)[e] : 1.0; igraph_real_t dlen = sqrt(dx * dx + dy * dy) * w; VECTOR(dispx)[v] -= (dx * dlen); VECTOR(dispy)[v] -= (dy * dlen); VECTOR(dispx)[u] += (dx * dlen); VECTOR(dispy)[u] += (dy * dlen); } /* limit max displacement to temperature t and prevent from displacement outside frame */ for (v = 0; v < no_nodes; v++) { igraph_real_t dx = VECTOR(dispx)[v] + RNG_UNIF01() * 1e-9; igraph_real_t dy = VECTOR(dispy)[v] + RNG_UNIF01() * 1e-9; igraph_real_t displen = sqrt(dx * dx + dy * dy); igraph_real_t mx = fabs(dx) < temp ? dx : temp; igraph_real_t my = fabs(dy) < temp ? dy : temp; if (displen > 0) { MATRIX(*res, v, 0) += (dx / displen) * mx; MATRIX(*res, v, 1) += (dy / displen) * my; } if (minx && MATRIX(*res, v, 0) < VECTOR(*minx)[v]) { MATRIX(*res, v, 0) = VECTOR(*minx)[v]; } if (maxx && MATRIX(*res, v, 0) > VECTOR(*maxx)[v]) { MATRIX(*res, v, 0) = VECTOR(*maxx)[v]; } if (miny && MATRIX(*res, v, 1) < VECTOR(*miny)[v]) { MATRIX(*res, v, 1) = VECTOR(*miny)[v]; } if (maxy && MATRIX(*res, v, 1) > VECTOR(*maxy)[v]) { MATRIX(*res, v, 1) = VECTOR(*maxy)[v]; } } temp -= difftemp; } RNG_END(); igraph_vector_float_destroy(&dispx); igraph_vector_float_destroy(&dispy); IGRAPH_FINALLY_CLEAN(2); return 0; } int igraph_layout_i_grid_fr(const igraph_t *graph, igraph_matrix_t *res, igraph_bool_t use_seed, igraph_integer_t niter, igraph_real_t start_temp, const igraph_vector_t *weight, const igraph_vector_t *minx, const igraph_vector_t *maxx, const igraph_vector_t *miny, const igraph_vector_t *maxy) { igraph_integer_t no_nodes = igraph_vcount(graph); igraph_integer_t no_edges = igraph_ecount(graph); float width = sqrtf(no_nodes), height = width; igraph_2dgrid_t grid; igraph_vector_float_t dispx, dispy; igraph_real_t temp = start_temp; igraph_real_t difftemp = start_temp / niter; igraph_2dgrid_iterator_t vidit; igraph_integer_t i; const float cellsize = 2.0; RNG_BEGIN(); if (!use_seed) { IGRAPH_CHECK(igraph_matrix_resize(res, no_nodes, 2)); for (i = 0; i < no_nodes; i++) { igraph_real_t x1 = minx ? VECTOR(*minx)[i] : -width / 2; igraph_real_t x2 = maxx ? VECTOR(*maxx)[i] : width / 2; igraph_real_t y1 = miny ? VECTOR(*miny)[i] : -height / 2; igraph_real_t y2 = maxy ? VECTOR(*maxy)[i] : height / 2; if (!igraph_finite(x1)) { x1 = -sqrt(no_nodes) / 2; } if (!igraph_finite(x2)) { x2 = sqrt(no_nodes) / 2; } if (!igraph_finite(y1)) { y1 = -sqrt(no_nodes) / 2; } if (!igraph_finite(y2)) { y2 = sqrt(no_nodes) / 2; } MATRIX(*res, i, 0) = RNG_UNIF(x1, x2); MATRIX(*res, i, 1) = RNG_UNIF(y1, y2); } } /* make grid */ IGRAPH_CHECK(igraph_2dgrid_init(&grid, res, -width / 2, width / 2, cellsize, -height / 2, height / 2, cellsize)); IGRAPH_FINALLY(igraph_2dgrid_destroy, &grid); /* place vertices on grid */ for (i = 0; i < no_nodes; i++) { igraph_2dgrid_add2(&grid, i); } IGRAPH_CHECK(igraph_vector_float_init(&dispx, no_nodes)); IGRAPH_FINALLY(igraph_vector_float_destroy, &dispx); IGRAPH_CHECK(igraph_vector_float_init(&dispy, no_nodes)); IGRAPH_FINALLY(igraph_vector_float_destroy, &dispy); for (i = 0; i < niter; i++) { igraph_integer_t v, u, e; igraph_vector_float_null(&dispx); igraph_vector_float_null(&dispy); /* repulsion */ igraph_2dgrid_reset(&grid, &vidit); while ( (v = igraph_2dgrid_next(&grid, &vidit) - 1) != -1) { while ( (u = igraph_2dgrid_next_nei(&grid, &vidit) - 1) != -1) { float dx = MATRIX(*res, v, 0) - MATRIX(*res, u, 0); float dy = MATRIX(*res, v, 1) - MATRIX(*res, u, 1); float dlen = dx * dx + dy * dy; if (dlen < cellsize * cellsize) { VECTOR(dispx)[v] += dx / dlen; VECTOR(dispy)[v] += dy / dlen; VECTOR(dispx)[u] -= dx / dlen; VECTOR(dispy)[u] -= dy / dlen; } } } /* attraction */ for (e = 0; e < no_edges; e++) { igraph_integer_t v = IGRAPH_FROM(graph, e); igraph_integer_t u = IGRAPH_TO(graph, e); igraph_real_t dx = MATRIX(*res, v, 0) - MATRIX(*res, u, 0); igraph_real_t dy = MATRIX(*res, v, 1) - MATRIX(*res, u, 1); igraph_real_t w = weight ? VECTOR(*weight)[e] : 1.0; igraph_real_t dlen = sqrt(dx * dx + dy * dy) * w; VECTOR(dispx)[v] -= (dx * dlen); VECTOR(dispy)[v] -= (dy * dlen); VECTOR(dispx)[u] += (dx * dlen); VECTOR(dispy)[u] += (dy * dlen); } /* update */ for (v = 0; v < no_nodes; v++) { igraph_real_t dx = VECTOR(dispx)[v] + RNG_UNIF01() * 1e-9; igraph_real_t dy = VECTOR(dispy)[v] + RNG_UNIF01() * 1e-9; igraph_real_t displen = sqrt(dx * dx + dy * dy); igraph_real_t mx = fabs(dx) < temp ? dx : temp; igraph_real_t my = fabs(dy) < temp ? dy : temp; if (displen > 0) { MATRIX(*res, v, 0) += (dx / displen) * mx; MATRIX(*res, v, 1) += (dy / displen) * my; } if (minx && MATRIX(*res, v, 0) < VECTOR(*minx)[v]) { MATRIX(*res, v, 0) = VECTOR(*minx)[v]; } if (maxx && MATRIX(*res, v, 0) > VECTOR(*maxx)[v]) { MATRIX(*res, v, 0) = VECTOR(*maxx)[v]; } if (miny && MATRIX(*res, v, 1) < VECTOR(*miny)[v]) { MATRIX(*res, v, 1) = VECTOR(*miny)[v]; } if (maxy && MATRIX(*res, v, 1) > VECTOR(*maxy)[v]) { MATRIX(*res, v, 1) = VECTOR(*maxy)[v]; } } temp -= difftemp; } igraph_vector_float_destroy(&dispx); igraph_vector_float_destroy(&dispy); igraph_2dgrid_destroy(&grid); IGRAPH_FINALLY_CLEAN(3); return 0; } /** * \ingroup layout * \function igraph_layout_fruchterman_reingold * \brief Places the vertices on a plane according to the Fruchterman-Reingold algorithm. * * * This is a force-directed layout, see Fruchterman, T.M.J. and * Reingold, E.M.: Graph Drawing by Force-directed Placement. * Software -- Practice and Experience, 21/11, 1129--1164, * 1991. * \param graph Pointer to an initialized graph object. * \param res Pointer to an initialized matrix object. This will * contain the result and will be resized as needed. * \param use_seed Logical, if true the supplied values in the * \p res argument are used as an initial layout, if * false a random initial layout is used. * \param niter The number of iterations to do. A reasonable * default value is 500. * \param start_temp Start temperature. This is the maximum amount * of movement alloved along one axis, within one step, for a * vertex. Currently it is decreased linearly to zero during * the iteration. * \param grid Whether to use the (fast but less accurate) grid based * version of the algorithm. Possible values: \c * IGRAPH_LAYOUT_GRID, \c IGRAPH_LAYOUT_NOGRID, \c * IGRAPH_LAYOUT_AUTOGRID. The last one uses the grid based * version only for large graphs, currently the ones with * more than 1000 vertices. * \param weight Pointer to a vector containing edge weights, * the attraction along the edges will be multiplied by these. * It will be ignored if it is a null-pointer. * \param minx Pointer to a vector, or a \c NULL pointer. If not a * \c NULL pointer then the vector gives the minimum * \quote x \endquote coordinate for every vertex. * \param maxx Same as \p minx, but the maximum \quote x \endquote * coordinates. * \param miny Pointer to a vector, or a \c NULL pointer. If not a * \c NULL pointer then the vector gives the minimum * \quote y \endquote coordinate for every vertex. * \param maxy Same as \p miny, but the maximum \quote y \endquote * coordinates. * \return Error code. * * Time complexity: O(|V|^2) in each * iteration, |V| is the number of * vertices in the graph. */ int igraph_layout_fruchterman_reingold(const igraph_t *graph, igraph_matrix_t *res, igraph_bool_t use_seed, igraph_integer_t niter, igraph_real_t start_temp, igraph_layout_grid_t grid, const igraph_vector_t *weight, const igraph_vector_t *minx, const igraph_vector_t *maxx, const igraph_vector_t *miny, const igraph_vector_t *maxy) { igraph_integer_t no_nodes = igraph_vcount(graph); if (niter < 0) { IGRAPH_ERROR("Number of iterations must be non-negative in " "Fruchterman-Reingold layout", IGRAPH_EINVAL); } if (use_seed && (igraph_matrix_nrow(res) != no_nodes || igraph_matrix_ncol(res) != 2)) { IGRAPH_ERROR("Invalid start position matrix size in " "Fruchterman-Reingold layout", IGRAPH_EINVAL); } if (weight && igraph_vector_size(weight) != igraph_ecount(graph)) { IGRAPH_ERROR("Invalid weight vector length", IGRAPH_EINVAL); } if (minx && igraph_vector_size(minx) != no_nodes) { IGRAPH_ERROR("Invalid minx vector length", IGRAPH_EINVAL); } if (maxx && igraph_vector_size(maxx) != no_nodes) { IGRAPH_ERROR("Invalid maxx vector length", IGRAPH_EINVAL); } if (minx && maxx && !igraph_vector_all_le(minx, maxx)) { IGRAPH_ERROR("minx must not be greater than maxx", IGRAPH_EINVAL); } if (miny && igraph_vector_size(miny) != no_nodes) { IGRAPH_ERROR("Invalid miny vector length", IGRAPH_EINVAL); } if (maxy && igraph_vector_size(maxy) != no_nodes) { IGRAPH_ERROR("Invalid maxy vector length", IGRAPH_EINVAL); } if (miny && maxy && !igraph_vector_all_le(miny, maxy)) { IGRAPH_ERROR("miny must not be greater than maxy", IGRAPH_EINVAL); } if (grid == IGRAPH_LAYOUT_AUTOGRID) { if (no_nodes > 1000) { grid = IGRAPH_LAYOUT_GRID; } else { grid = IGRAPH_LAYOUT_NOGRID; } } if (grid == IGRAPH_LAYOUT_GRID) { return igraph_layout_i_grid_fr(graph, res, use_seed, niter, start_temp, weight, minx, maxx, miny, maxy); } else { return igraph_layout_i_fr(graph, res, use_seed, niter, start_temp, weight, minx, maxx, miny, maxy); } } /** * \function igraph_layout_fruchterman_reingold_3d * \brief 3D Fruchterman-Reingold algorithm. * * This is the 3D version of the force based * Fruchterman-Reingold layout (see \ref * igraph_layout_fruchterman_reingold for the 2D version * * \param graph Pointer to an initialized graph object. * \param res Pointer to an initialized matrix object. This will * contain the result and will be resized as needed. * \param use_seed Logical, if true the supplied values in the * \p res argument are used as an initial layout, if * false a random initial layout is used. * \param niter The number of iterations to do. A reasonable * default value is 500. * \param start_temp Start temperature. This is the maximum amount * of movement alloved along one axis, within one step, for a * vertex. Currently it is decreased linearly to zero during * the iteration. * \param weight Pointer to a vector containing edge weights, * the attraction along the edges will be multiplied by these. * It will be ignored if it is a null-pointer. * \param minx Pointer to a vector, or a \c NULL pointer. If not a * \c NULL pointer then the vector gives the minimum * \quote x \endquote coordinate for every vertex. * \param maxx Same as \p minx, but the maximum \quote x \endquote * coordinates. * \param miny Pointer to a vector, or a \c NULL pointer. If not a * \c NULL pointer then the vector gives the minimum * \quote y \endquote coordinate for every vertex. * \param maxy Same as \p miny, but the maximum \quote y \endquote * coordinates. * \param minz Pointer to a vector, or a \c NULL pointer. If not a * \c NULL pointer then the vector gives the minimum * \quote z \endquote coordinate for every vertex. * \param maxz Same as \p minz, but the maximum \quote z \endquote * coordinates. * \return Error code. * * Added in version 0.2. * * Time complexity: O(|V|^2) in each * iteration, |V| is the number of * vertices in the graph. * */ int igraph_layout_fruchterman_reingold_3d(const igraph_t *graph, igraph_matrix_t *res, igraph_bool_t use_seed, igraph_integer_t niter, igraph_real_t start_temp, const igraph_vector_t *weight, const igraph_vector_t *minx, const igraph_vector_t *maxx, const igraph_vector_t *miny, const igraph_vector_t *maxy, const igraph_vector_t *minz, const igraph_vector_t *maxz) { igraph_integer_t no_nodes = igraph_vcount(graph); igraph_integer_t no_edges = igraph_ecount(graph); igraph_integer_t i; igraph_vector_float_t dispx, dispy, dispz; igraph_real_t temp = start_temp; igraph_real_t difftemp = start_temp / niter; float width = sqrtf(no_nodes), height = width, depth = width; igraph_bool_t conn = 1; float C; if (niter < 0) { IGRAPH_ERROR("Number of iterations must be non-negative in " "Fruchterman-Reingold layout", IGRAPH_EINVAL); } if (use_seed && (igraph_matrix_nrow(res) != no_nodes || igraph_matrix_ncol(res) != 3)) { IGRAPH_ERROR("Invalid start position matrix size in " "Fruchterman-Reingold layout", IGRAPH_EINVAL); } if (weight && igraph_vector_size(weight) != igraph_ecount(graph)) { IGRAPH_ERROR("Invalid weight vector length", IGRAPH_EINVAL); } if (minx && igraph_vector_size(minx) != no_nodes) { IGRAPH_ERROR("Invalid minx vector length", IGRAPH_EINVAL); } if (maxx && igraph_vector_size(maxx) != no_nodes) { IGRAPH_ERROR("Invalid maxx vector length", IGRAPH_EINVAL); } if (minx && maxx && !igraph_vector_all_le(minx, maxx)) { IGRAPH_ERROR("minx must not be greater than maxx", IGRAPH_EINVAL); } if (miny && igraph_vector_size(miny) != no_nodes) { IGRAPH_ERROR("Invalid miny vector length", IGRAPH_EINVAL); } if (maxy && igraph_vector_size(maxy) != no_nodes) { IGRAPH_ERROR("Invalid maxy vector length", IGRAPH_EINVAL); } if (miny && maxy && !igraph_vector_all_le(miny, maxy)) { IGRAPH_ERROR("miny must not be greater than maxy", IGRAPH_EINVAL); } if (minz && igraph_vector_size(minz) != no_nodes) { IGRAPH_ERROR("Invalid minz vector length", IGRAPH_EINVAL); } if (maxz && igraph_vector_size(maxz) != no_nodes) { IGRAPH_ERROR("Invalid maxz vector length", IGRAPH_EINVAL); } if (minz && maxz && !igraph_vector_all_le(minz, maxz)) { IGRAPH_ERROR("minz must not be greater than maxz", IGRAPH_EINVAL); } igraph_is_connected(graph, &conn, IGRAPH_WEAK); if (!conn) { C = no_nodes * sqrtf(no_nodes); } RNG_BEGIN(); if (!use_seed) { IGRAPH_CHECK(igraph_matrix_resize(res, no_nodes, 3)); for (i = 0; i < no_nodes; i++) { igraph_real_t x1 = minx ? VECTOR(*minx)[i] : -width / 2; igraph_real_t x2 = maxx ? VECTOR(*maxx)[i] : width / 2; igraph_real_t y1 = miny ? VECTOR(*miny)[i] : -height / 2; igraph_real_t y2 = maxy ? VECTOR(*maxy)[i] : height / 2; igraph_real_t z1 = minz ? VECTOR(*minz)[i] : -depth / 2; igraph_real_t z2 = maxz ? VECTOR(*maxz)[i] : depth / 2; MATRIX(*res, i, 0) = RNG_UNIF(x1, x2); MATRIX(*res, i, 1) = RNG_UNIF(y1, y2); MATRIX(*res, i, 2) = RNG_UNIF(z1, z2); } } IGRAPH_CHECK(igraph_vector_float_init(&dispx, no_nodes)); IGRAPH_FINALLY(igraph_vector_float_destroy, &dispx); IGRAPH_CHECK(igraph_vector_float_init(&dispy, no_nodes)); IGRAPH_FINALLY(igraph_vector_float_destroy, &dispy); IGRAPH_CHECK(igraph_vector_float_init(&dispz, no_nodes)); IGRAPH_FINALLY(igraph_vector_float_destroy, &dispz); for (i = 0; i < niter; i++) { igraph_integer_t v, u, e; /* calculate repulsive forces, we have a special version for unconnected graphs */ igraph_vector_float_null(&dispx); igraph_vector_float_null(&dispy); igraph_vector_float_null(&dispz); if (conn) { for (v = 0; v < no_nodes; v++) { for (u = v + 1; u < no_nodes; u++) { float dx = MATRIX(*res, v, 0) - MATRIX(*res, u, 0); float dy = MATRIX(*res, v, 1) - MATRIX(*res, u, 1); float dz = MATRIX(*res, v, 2) - MATRIX(*res, u, 2); float dlen = dx * dx + dy * dy + dz * dz; if (dlen == 0) { dx = RNG_UNIF01() * 1e-9; dy = RNG_UNIF01() * 1e-9; dz = RNG_UNIF01() * 1e-9; dlen = dx * dx + dy * dy + dz * dz; } VECTOR(dispx)[v] += dx / dlen; VECTOR(dispy)[v] += dy / dlen; VECTOR(dispz)[v] += dz / dlen; VECTOR(dispx)[u] -= dx / dlen; VECTOR(dispy)[u] -= dy / dlen; VECTOR(dispz)[u] -= dz / dlen; } } } else { for (v = 0; v < no_nodes; v++) { for (u = v + 1; u < no_nodes; u++) { float dx = MATRIX(*res, v, 0) - MATRIX(*res, u, 0); float dy = MATRIX(*res, v, 1) - MATRIX(*res, u, 1); float dz = MATRIX(*res, v, 2) - MATRIX(*res, u, 2); float dlen, rdlen; dlen = dx * dx + dy * dy + dz * dz; if (dlen == 0) { dx = RNG_UNIF01() * 1e-9; dy = RNG_UNIF01() * 1e-9; dz = RNG_UNIF01() * 1e-9; dlen = dx * dx + dy * dy + dz * dz; } rdlen = sqrt(dlen); VECTOR(dispx)[v] += dx * (C - dlen * rdlen) / (dlen * C); VECTOR(dispy)[v] += dy * (C - dlen * rdlen) / (dlen * C); VECTOR(dispy)[v] += dz * (C - dlen * rdlen) / (dlen * C); VECTOR(dispx)[u] -= dx * (C - dlen * rdlen) / (dlen * C); VECTOR(dispy)[u] -= dy * (C - dlen * rdlen) / (dlen * C); VECTOR(dispz)[u] -= dz * (C - dlen * rdlen) / (dlen * C); } } } /* calculate attractive forces */ for (e = 0; e < no_edges; e++) { /* each edges is an ordered pair of vertices v and u */ igraph_integer_t v = IGRAPH_FROM(graph, e); igraph_integer_t u = IGRAPH_TO(graph, e); igraph_real_t dx = MATRIX(*res, v, 0) - MATRIX(*res, u, 0); igraph_real_t dy = MATRIX(*res, v, 1) - MATRIX(*res, u, 1); igraph_real_t dz = MATRIX(*res, v, 2) - MATRIX(*res, u, 2); igraph_real_t w = weight ? VECTOR(*weight)[e] : 1.0; igraph_real_t dlen = sqrt(dx * dx + dy * dy + dz * dz) * w; VECTOR(dispx)[v] -= (dx * dlen); VECTOR(dispy)[v] -= (dy * dlen); VECTOR(dispz)[v] -= (dz * dlen); VECTOR(dispx)[u] += (dx * dlen); VECTOR(dispy)[u] += (dy * dlen); VECTOR(dispz)[u] += (dz * dlen); } /* limit max displacement to temperature t and prevent from displacement outside frame */ for (v = 0; v < no_nodes; v++) { igraph_real_t dx = VECTOR(dispx)[v] + RNG_UNIF01() * 1e-9; igraph_real_t dy = VECTOR(dispy)[v] + RNG_UNIF01() * 1e-9; igraph_real_t dz = VECTOR(dispz)[v] + RNG_UNIF01() * 1e-9; igraph_real_t displen = sqrt(dx * dx + dy * dy + dz * dz); igraph_real_t mx = fabs(dx) < temp ? dx : temp; igraph_real_t my = fabs(dy) < temp ? dy : temp; igraph_real_t mz = fabs(dz) < temp ? dz : temp; if (displen > 0) { MATRIX(*res, v, 0) += (dx / displen) * mx; MATRIX(*res, v, 1) += (dy / displen) * my; MATRIX(*res, v, 2) += (dz / displen) * mz; } if (minx && MATRIX(*res, v, 0) < VECTOR(*minx)[v]) { MATRIX(*res, v, 0) = VECTOR(*minx)[v]; } if (maxx && MATRIX(*res, v, 0) > VECTOR(*maxx)[v]) { MATRIX(*res, v, 0) = VECTOR(*maxx)[v]; } if (miny && MATRIX(*res, v, 1) < VECTOR(*miny)[v]) { MATRIX(*res, v, 1) = VECTOR(*miny)[v]; } if (maxy && MATRIX(*res, v, 1) > VECTOR(*maxy)[v]) { MATRIX(*res, v, 1) = VECTOR(*maxy)[v]; } if (minz && MATRIX(*res, v, 2) < VECTOR(*minz)[v]) { MATRIX(*res, v, 2) = VECTOR(*minz)[v]; } if (maxz && MATRIX(*res, v, 2) > VECTOR(*maxz)[v]) { MATRIX(*res, v, 2) = VECTOR(*maxz)[v]; } } temp -= difftemp; } RNG_END(); igraph_vector_float_destroy(&dispx); igraph_vector_float_destroy(&dispy); igraph_vector_float_destroy(&dispz); IGRAPH_FINALLY_CLEAN(3); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/infomap_Greedy.h0000644000076500000240000000417413614300625024505 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2011-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef GREEDY_H #define GREEDY_H #include #include #include #include #include "igraph_random.h" #include "infomap_Node.h" #include "infomap_FlowGraph.h" class Greedy { public: Greedy(FlowGraph * fgraph); // initialise les attributs par rapport au graph ~Greedy(); void setMove(int *moveTo); //virtual void determMove(int *moveTo); bool optimize(); //virtual void move(bool &moved); void apply(bool sort); //virtual void level(Node ***, bool sort); void tune(void); /**************************************************************************/ FlowGraph * graph; int Nnode; double exit; double exitFlow; double exit_log_exit; double size_log_size; double nodeSize_log_nodeSize; double codeLength; double alpha, beta; // local copy of fgraph alpha, beta (=alpha - Nnode = graph->Nnode;1) vector node_index; // module number of each node int Nempty; vector mod_empty; vector mod_exit; // version tmp de node vector mod_size; vector mod_danglingSize; vector mod_teleportWeight; vector mod_members; }; void delete_Greedy(Greedy *greedy); #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/0000755000076500000240000000000013617375001022466 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Core/0000755000076500000240000000000013617375001023356 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Core/cholmod_dense.c0000644000076500000240000005042513524616144026336 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Core/cholmod_dense =================================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Core Module. Copyright (C) 2005-2013, * Univ. of Florida. Author: Timothy A. Davis * The CHOLMOD/Core Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Core utility routines for the cholmod_dense object: * * The solve routines and some of the MatrixOps and Modify routines use dense * matrices as inputs. These are held in column-major order. With a leading * dimension of d, the entry in row i and column j is held in x [i+j*d]. * * Primary routines: * ----------------- * cholmod_allocate_dense allocate a dense matrix * cholmod_free_dense free a dense matrix * * Secondary routines: * ------------------- * cholmod_zeros allocate a dense matrix of all zeros * cholmod_ones allocate a dense matrix of all ones * cholmod_eye allocate a dense identity matrix * cholmod_sparse_to_dense create a dense matrix copy of a sparse matrix * cholmod_dense_to_sparse create a sparse matrix copy of a dense matrix * cholmod_copy_dense create a copy of a dense matrix * cholmod_copy_dense2 copy a dense matrix (pre-allocated) * * All routines in this file can handle the real, complex, and zomplex cases. * Pattern-only dense matrices are not supported. cholmod_sparse_to_dense can * take a pattern-only input sparse matrix, however, and cholmod_dense_to_sparse * can generate a pattern-only output sparse matrix. */ #include "cholmod_internal.h" #include "cholmod_core.h" /* ========================================================================== */ /* === TEMPLATE ============================================================= */ /* ========================================================================== */ #define PATTERN #include "t_cholmod_dense.c" #define REAL #include "t_cholmod_dense.c" #define COMPLEX #include "t_cholmod_dense.c" #define ZOMPLEX #include "t_cholmod_dense.c" /* ========================================================================== */ /* === cholmod_allocate_dense =============================================== */ /* ========================================================================== */ /* Allocate a dense matrix with leading dimension d. The space is not * initialized. */ cholmod_dense *CHOLMOD(allocate_dense) ( /* ---- input ---- */ size_t nrow, /* # of rows of matrix */ size_t ncol, /* # of columns of matrix */ size_t d, /* leading dimension */ int xtype, /* CHOLMOD_REAL, _COMPLEX, or _ZOMPLEX */ /* --------------- */ cholmod_common *Common ) { cholmod_dense *X ; size_t nzmax, nzmax0 ; int ok = TRUE ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; if (d < nrow) { ERROR (CHOLMOD_INVALID, "leading dimension invalid") ; return (NULL) ; } if (xtype < CHOLMOD_REAL || xtype > CHOLMOD_ZOMPLEX) { ERROR (CHOLMOD_INVALID, "xtype invalid") ; return (NULL) ; } /* ensure the dimensions do not cause integer overflow */ (void) CHOLMOD(add_size_t) (ncol, 2, &ok) ; /* nzmax = MAX (1, d*ncol) ; */ nzmax = CHOLMOD(mult_size_t) (d, ncol, &ok) ; nzmax = MAX (1, nzmax) ; if (!ok || nrow > Int_max || ncol > Int_max || nzmax > Int_max) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return (NULL) ; } Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* allocate header */ /* ---------------------------------------------------------------------- */ X = CHOLMOD(malloc) (sizeof (cholmod_dense), 1, Common) ; if (Common->status < CHOLMOD_OK) { return (NULL) ; /* out of memory */ } PRINT1 (("cholmod_allocate_dense %d-by-%d nzmax %d xtype %d\n", nrow, ncol, nzmax, xtype)) ; X->nrow = nrow ; X->ncol = ncol ; X->nzmax = nzmax ; X->xtype = xtype ; X->dtype = DTYPE ; X->x = NULL ; X->z = NULL ; X->d = d ; /* ---------------------------------------------------------------------- */ /* allocate the matrix itself */ /* ---------------------------------------------------------------------- */ nzmax0 = 0 ; CHOLMOD(realloc_multiple) (nzmax, 0, xtype, NULL, NULL, &(X->x), &(X->z), &nzmax0, Common) ; if (Common->status < CHOLMOD_OK) { CHOLMOD(free_dense) (&X, Common) ; return (NULL) ; /* out of memory */ } return (X) ; } /* ========================================================================== */ /* === cholmod_zeros ======================================================== */ /* ========================================================================== */ /* Allocate a dense matrix and set it to zero */ cholmod_dense *CHOLMOD(zeros) ( /* ---- input ---- */ size_t nrow, /* # of rows of matrix */ size_t ncol, /* # of columns of matrix */ int xtype, /* CHOLMOD_REAL, _COMPLEX, or _ZOMPLEX */ /* --------------- */ cholmod_common *Common ) { cholmod_dense *X ; double *Xx, *Xz ; Int i, nz ; /* ---------------------------------------------------------------------- */ /* allocate a dense matrix and set it to zero */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; X = CHOLMOD(allocate_dense) (nrow, ncol, nrow, xtype, Common) ; if (Common->status < CHOLMOD_OK) { return (NULL) ; /* NULL Common, out of memory, or inputs invalid */ } Xx = X->x ; Xz = X->z ; nz = MAX (1, X->nzmax) ; switch (xtype) { case CHOLMOD_REAL: for (i = 0 ; i < nz ; i++) { Xx [i] = 0 ; } break ; case CHOLMOD_COMPLEX: for (i = 0 ; i < 2*nz ; i++) { Xx [i] = 0 ; } break ; case CHOLMOD_ZOMPLEX: for (i = 0 ; i < nz ; i++) { Xx [i] = 0 ; } for (i = 0 ; i < nz ; i++) { Xz [i] = 0 ; } break ; } return (X) ; } /* ========================================================================== */ /* === cholmod_ones ========================================================= */ /* ========================================================================== */ /* Allocate a dense matrix and set it to zero */ cholmod_dense *CHOLMOD(ones) ( /* ---- input ---- */ size_t nrow, /* # of rows of matrix */ size_t ncol, /* # of columns of matrix */ int xtype, /* CHOLMOD_REAL, _COMPLEX, or _ZOMPLEX */ /* --------------- */ cholmod_common *Common ) { cholmod_dense *X ; double *Xx, *Xz ; Int i, nz ; /* ---------------------------------------------------------------------- */ /* allocate a dense matrix and set it to all ones */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; X = CHOLMOD(allocate_dense) (nrow, ncol, nrow, xtype, Common) ; if (Common->status < CHOLMOD_OK) { return (NULL) ; /* NULL Common, out of memory, or inputs invalid */ } Xx = X->x ; Xz = X->z ; nz = MAX (1, X->nzmax) ; switch (xtype) { case CHOLMOD_REAL: for (i = 0 ; i < nz ; i++) { Xx [i] = 1 ; } break ; case CHOLMOD_COMPLEX: for (i = 0 ; i < nz ; i++) { Xx [2*i ] = 1 ; Xx [2*i+1] = 0 ; } break ; case CHOLMOD_ZOMPLEX: for (i = 0 ; i < nz ; i++) { Xx [i] = 1 ; } for (i = 0 ; i < nz ; i++) { Xz [i] = 0 ; } break ; } return (X) ; } /* ========================================================================== */ /* === cholmod_eye ========================================================== */ /* ========================================================================== */ /* Allocate a dense matrix and set it to the identity matrix */ cholmod_dense *CHOLMOD(eye) ( /* ---- input ---- */ size_t nrow, /* # of rows of matrix */ size_t ncol, /* # of columns of matrix */ int xtype, /* CHOLMOD_REAL, _COMPLEX, or _ZOMPLEX */ /* --------------- */ cholmod_common *Common ) { cholmod_dense *X ; double *Xx, *Xz ; Int i, n, nz ; /* ---------------------------------------------------------------------- */ /* allocate a dense matrix and set it to the identity matrix */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; X = CHOLMOD(zeros) (nrow, ncol, xtype, Common) ; if (Common->status < CHOLMOD_OK) { return (NULL) ; /* NULL Common, out of memory, or inputs invalid */ } nz = MAX (1, nrow*ncol) ; Xx = X->x ; Xz = X->z ; n = MIN (nrow, ncol) ; switch (xtype) { case CHOLMOD_REAL: case CHOLMOD_ZOMPLEX: for (i = 0 ; i < n ; i++) { Xx [i + i*nrow] = 1 ; } break ; case CHOLMOD_COMPLEX: for (i = 0 ; i < n ; i++) { Xx [2 * (i + i*nrow)] = 1 ; } break ; } return (X) ; } /* ========================================================================== */ /* === cholmod_free_dense =================================================== */ /* ========================================================================== */ /* free a dense matrix * * workspace: none */ int CHOLMOD(free_dense) ( /* ---- in/out --- */ cholmod_dense **XHandle, /* dense matrix to deallocate, NULL on output */ /* --------------- */ cholmod_common *Common ) { cholmod_dense *X ; RETURN_IF_NULL_COMMON (FALSE) ; if (XHandle == NULL) { /* nothing to do */ return (TRUE) ; } X = *XHandle ; if (X == NULL) { /* nothing to do */ return (TRUE) ; } switch (X->xtype) { case CHOLMOD_REAL: X->x = CHOLMOD(free) (X->nzmax, sizeof (double), X->x, Common) ; break ; case CHOLMOD_COMPLEX: X->x = CHOLMOD(free) (X->nzmax, 2*sizeof (double), X->x, Common) ; break ; case CHOLMOD_ZOMPLEX: X->x = CHOLMOD(free) (X->nzmax, sizeof (double), X->x, Common) ; X->z = CHOLMOD(free) (X->nzmax, sizeof (double), X->z, Common) ; break ; } *XHandle = CHOLMOD(free) (1, sizeof (cholmod_dense), (*XHandle), Common) ; return (TRUE) ; } /* ========================================================================== */ /* === cholmod_ensure_dense ================================================= */ /* ========================================================================== */ /* Ensure that the input matrix has a certain size and type. If not, free * the existing matrix and reallocate one of the right size and type. * Returns a pointer to the cholmod_dense matrix, possibly reallocated. * Also modifies the input matrix handle, XHandle, if necessary. */ cholmod_dense *CHOLMOD(ensure_dense) ( /* ---- input/output ---- */ cholmod_dense **XHandle, /* matrix handle to check */ /* ---- input ---- */ size_t nrow, /* # of rows of matrix */ size_t ncol, /* # of columns of matrix */ size_t d, /* leading dimension */ int xtype, /* CHOLMOD_REAL, _COMPLEX, or _ZOMPLEX */ /* --------------- */ cholmod_common *Common ) { cholmod_dense *X ; RETURN_IF_NULL_COMMON (NULL) ; if (XHandle == NULL) { ERROR (CHOLMOD_INVALID, "matrix invalid") ; return (NULL) ; } X = *XHandle ; if (X == NULL || X->nrow != nrow || X->ncol != ncol || X->d != d || X->xtype != xtype) { /* Matrix X is not allocated, or has the wrong size. Free it and * reallocate it in the right size and shape. If an error occurs * (out of memory or inputs nrow, etc invalid), then the error is * set in cholmod_allocate_dense and X is returned as NULL. */ #if 0 if (X == NULL) { printf ("oops, X was null\n") ; } else { printf ("oops, nrow %g %g ncol %g %g d %g %g xtype %g %g\n", (double) X->nrow, (double) nrow, (double) X->ncol, (double) ncol, (double) X->d, (double) d, (double) X->xtype, (double) xtype ) ; } #endif CHOLMOD(free_dense) (XHandle, Common) ; X = CHOLMOD(allocate_dense) (nrow, ncol, d, xtype, Common) ; *XHandle = X ; } return (X) ; } /* ========================================================================== */ /* === cholmod_sparse_to_dense ============================================== */ /* ========================================================================== */ /* Convert a sparse matrix to a dense matrix. * The output dense matrix has the same xtype as the input sparse matrix, * except that a pattern-only sparse matrix A is converted into a real dense * matrix X, with 1's and 0's. All xtypes are supported. */ cholmod_dense *CHOLMOD(sparse_to_dense) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to copy */ /* --------------- */ cholmod_common *Common ) { cholmod_dense *X = NULL ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; RETURN_IF_NULL (A, NULL) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, NULL) ; if (A->stype && A->nrow != A->ncol) { ERROR (CHOLMOD_INVALID, "matrix invalid") ; return (NULL) ; } Common->status = CHOLMOD_OK ; ASSERT (CHOLMOD(dump_sparse) (A, "A", Common) >= 0) ; /* ---------------------------------------------------------------------- */ /* convert the matrix, using template routine */ /* ---------------------------------------------------------------------- */ switch (A->xtype) { case CHOLMOD_PATTERN: X = p_cholmod_sparse_to_dense (A, Common) ; break ; case CHOLMOD_REAL: X = r_cholmod_sparse_to_dense (A, Common) ; break ; case CHOLMOD_COMPLEX: X = c_cholmod_sparse_to_dense (A, Common) ; break ; case CHOLMOD_ZOMPLEX: X = z_cholmod_sparse_to_dense (A, Common) ; break ; } return (X) ; } /* ========================================================================== */ /* === cholmod_dense_to_sparse ============================================== */ /* ========================================================================== */ /* Convert a dense matrix to a sparse matrix, similar to the MATLAB statements: * * C = sparse (X) values = TRUE * C = spones (sparse (X)) values = FALSE * * except that X must be double (it can be of many different types in MATLAB) * * The resulting sparse matrix C has the same numeric xtype as the input dense * matrix X, unless "values" is FALSE (in which case C is real, where C(i,j)=1 * if (i,j) is an entry in X. */ cholmod_sparse *CHOLMOD(dense_to_sparse) ( /* ---- input ---- */ cholmod_dense *X, /* matrix to copy */ int values, /* TRUE if values to be copied, FALSE otherwise */ /* --------------- */ cholmod_common *Common ) { cholmod_sparse *C = NULL ; DEBUG (CHOLMOD(dump_dense) (X, "X", Common)) ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; RETURN_IF_NULL (X, NULL) ; RETURN_IF_XTYPE_INVALID (X, CHOLMOD_REAL, CHOLMOD_ZOMPLEX, NULL) ; if (X->d < X->nrow) { ERROR (CHOLMOD_INVALID, "matrix invalid") ; return (NULL) ; } Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* convert the matrix, using template routine */ /* ---------------------------------------------------------------------- */ switch (X->xtype) { case CHOLMOD_REAL: C = r_cholmod_dense_to_sparse (X, values, Common) ; break ; case CHOLMOD_COMPLEX: C = c_cholmod_dense_to_sparse (X, values, Common) ; break ; case CHOLMOD_ZOMPLEX: C = z_cholmod_dense_to_sparse (X, values, Common) ; break ; } return (C) ; } /* ========================================================================== */ /* === cholmod_copy_dense2 ================================================== */ /* ========================================================================== */ /* Y = X, where X and Y are both already allocated. The leading dimensions of * X and Y may differ, but both must be >= the # of rows in X and Y. * Entries in rows nrow to d-1 are not copied from X, since the space might not * be initialized. Y->nzmax is unchanged. X->nzmax is typically * (X->d)*(X->ncol), but a user might modify that condition outside of any * CHOLMOD routine. * * The two dense matrices X and Y must have the same numeric xtype. */ int CHOLMOD(copy_dense2) ( /* ---- input ---- */ cholmod_dense *X, /* matrix to copy */ /* ---- output --- */ cholmod_dense *Y, /* copy of matrix X */ /* --------------- */ cholmod_common *Common ) { /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (X, FALSE) ; RETURN_IF_NULL (Y, FALSE) ; RETURN_IF_XTYPE_INVALID (X, CHOLMOD_REAL, CHOLMOD_ZOMPLEX, FALSE) ; RETURN_IF_XTYPE_INVALID (Y, CHOLMOD_REAL, CHOLMOD_ZOMPLEX, FALSE) ; if (X->nrow != Y->nrow || X->ncol != Y->ncol || X->xtype != Y->xtype) { ERROR (CHOLMOD_INVALID, "X and Y must have same dimensions and xtype") ; return (FALSE) ; } if (X->d < X->nrow || Y->d < Y->nrow || (X->d * X->ncol) > X->nzmax || (Y->d * Y->ncol) > Y->nzmax) { ERROR (CHOLMOD_INVALID, "X and/or Y invalid") ; return (FALSE) ; } Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* copy the matrix, using template routine */ /* ---------------------------------------------------------------------- */ switch (X->xtype) { case CHOLMOD_REAL: r_cholmod_copy_dense2 (X, Y) ; break ; case CHOLMOD_COMPLEX: c_cholmod_copy_dense2 (X, Y) ; break ; case CHOLMOD_ZOMPLEX: z_cholmod_copy_dense2 (X, Y) ; break ; } return (TRUE) ; } /* ========================================================================== */ /* === cholmod_copy_dense =================================================== */ /* ========================================================================== */ /* Y = X, copy a dense matrix */ cholmod_dense *CHOLMOD(copy_dense) ( /* ---- input ---- */ cholmod_dense *X, /* matrix to copy */ /* --------------- */ cholmod_common *Common ) { cholmod_dense *Y ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; RETURN_IF_NULL (X, NULL) ; RETURN_IF_XTYPE_INVALID (X, CHOLMOD_REAL, CHOLMOD_ZOMPLEX, NULL) ; Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* allocate result */ /* ---------------------------------------------------------------------- */ Y = CHOLMOD(allocate_dense) (X->nrow, X->ncol, X->d, X->xtype, Common) ; if (Common->status < CHOLMOD_OK) { return (NULL) ; /* out of memory or X invalid */ } /* ---------------------------------------------------------------------- */ /* Y = X */ /* ---------------------------------------------------------------------- */ /* This cannot fail (X and Y are allocated, and have the same nrow, ncol * d, and xtype) */ CHOLMOD(copy_dense2) (X, Y, Common) ; /* ---------------------------------------------------------------------- */ /* return result */ /* ---------------------------------------------------------------------- */ return (Y) ; } python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Core/t_cholmod_change_factor.c0000644000076500000240000003751313524616144030351 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Core/t_cholmod_change_factor ========================================= */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Core Module. Copyright (C) 2005-2006, * Univ. of Florida. Author: Timothy A. Davis * The CHOLMOD/Core Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Template routine for cholmod_change_factor. All xtypes supported. */ #include "cholmod_template.h" /* ========================================================================== */ /* === t_change_simplicial_numeric ========================================== */ /* ========================================================================== */ static void TEMPLATE (change_simplicial_numeric) ( cholmod_factor *L, Int to_ll, Int to_packed, Int *newLi, double *newLx, double *newLz, Int lnz, Int grow, double grow1, Int grow2, Int make_ll, Int make_monotonic, Int make_ldl, cholmod_common *Common ) { double xlen, dj [1], ljj [1], lj2 [1] ; double *Lx, *Lz ; Int *Lp, *Li, *Lnz ; Int n, j, len, pnew, pold, k, p, pend ; n = L->n ; Lp = L->p ; Li = L->i ; Lx = L->x ; Lz = L->z ; Lnz = L->nz ; if (make_ll) { L->minor = n ; } if (make_monotonic) { /* ------------------------------------------------------------------ */ /* reorder the columns to make them monotonic */ /* ------------------------------------------------------------------ */ pnew = 0 ; for (j = 0 ; j < n ; j++) { /* copy and pack column j */ len = Lnz [j] ; PRINT2 (("j: "ID" Lnz[j] "ID" len "ID" p "ID"\n", j, Lnz [j], len, pnew)) ; pold = Lp [j] ; ASSERT (Li [pold] == j) ; if (make_ll) { /* ---------------------------------------------------------- */ /* copy and convert LDL' to LL' */ /* ---------------------------------------------------------- */ /* dj = Lx [pold] ; */ ASSIGN_REAL (dj,0, Lx,pold) ; if (IS_LE_ZERO (dj [0])) { /* Conversion has failed; matrix is not positive definite. * Do not modify the column so that the LDL' factorization * can be restored if desired, by converting back to LDL'. * Continue the conversion, but flag the error. */ if (L->minor == (size_t) n) { ERROR (CHOLMOD_NOT_POSDEF, "L not positive definite") ; L->minor = j ; } for (k = 0 ; k < len ; k++) { newLi [pnew + k] = Li [pold + k] ; /* newLx [pnew + k] = Lx [pold + k] ; */ ASSIGN (newLx, newLz, pnew+k, Lx, Lz, pold+k) ; } } else { ljj [0] = sqrt (dj [0]) ; newLi [pnew] = j ; /* newLx [pnew] = ljj ; */ ASSIGN_REAL (newLx, pnew, ljj, 0) ; CLEAR_IMAG (newLx, newLz, pnew) ; for (k = 1 ; k < len ; k++) { newLi [pnew + k] = Li [pold + k] ; /* newLx [pnew + k] = Lx [pold + k] * ljj ; */ MULT_REAL (newLx, newLz, pnew+k, Lx, Lz, pold+k, ljj,0); } } } else if (make_ldl) { /* ---------------------------------------------------------- */ /* copy and convert LL' to LDL' */ /* ---------------------------------------------------------- */ /* ljj = Lx [pold] ; */ ASSIGN_REAL (ljj, 0, Lx, pold) ; if (ljj [0] <= 0) { /* matrix is not positive-definite; copy column as-is */ for (k = 0 ; k < len ; k++) { newLi [pnew + k] = Li [pold + k] ; /* newLx [pnew + k] = Lx [pold + k] ; */ ASSIGN (newLx, newLz, pnew+k, Lx, Lz, pold+k) ; } } else { newLi [pnew] = j ; /* newLx [pnew] = ljj*ljj ; */ lj2 [0] = ljj [0] * ljj [0] ; ASSIGN_REAL (newLx, pnew, lj2, 0) ; CLEAR_IMAG (newLx, newLz, pnew) ; for (k = 1 ; k < len ; k++) { newLi [pnew + k] = Li [pold + k] ; /* newLx [pnew + k] = Lx [pold + k] / ljj ; */ DIV_REAL (newLx, newLz, pnew+k, Lx, Lz, pold+k, ljj,0) ; } } } else { /* ---------------------------------------------------------- */ /* copy and leave LL' or LDL' as-is */ /* ---------------------------------------------------------- */ for (k = 0 ; k < len ; k++) { newLi [pnew + k] = Li [pold + k] ; /* newLx [pnew + k] = Lx [pold + k] ; */ ASSIGN (newLx, newLz, pnew+k, Lx, Lz, pold+k) ; } } Lp [j] = pnew ; /* compute len in double to avoid integer overflow */ if (grow) { xlen = (double) len ; xlen = grow1 * xlen + grow2 ; xlen = MIN (xlen, n-j) ; len = (Int) xlen ; } ASSERT (len >= Lnz [j] && len <= n-j) ; pnew += len ; ASSERT (pnew > 0) ; /* integer overflow case already covered */ } Lp [n] = pnew ; PRINT1 (("final pnew = "ID", lnz "ID" lnzmax %g\n", pnew, lnz, (double) L->nzmax)) ; ASSERT (pnew <= lnz) ; /* free the old L->i and L->x and replace with the new ones */ CHOLMOD(free) (L->nzmax, sizeof (Int), L->i, Common) ; #ifdef REAL CHOLMOD(free) (L->nzmax, sizeof (double), L->x, Common) ; #elif defined (COMPLEX) CHOLMOD(free) (L->nzmax, 2*sizeof (double), L->x, Common) ; #else CHOLMOD(free) (L->nzmax, sizeof (double), L->x, Common) ; CHOLMOD(free) (L->nzmax, sizeof (double), L->z, Common) ; #endif L->i = newLi ; L->x = newLx ; L->z = newLz ; L->nzmax = lnz ; /* reconstruct the link list */ natural_list (L) ; } else if (to_packed) { /* ------------------------------------------------------------------ */ /* already monotonic, just pack the columns of L */ /* ------------------------------------------------------------------ */ pnew = 0 ; if (make_ll) { /* -------------------------------------------------------------- */ /* pack and convert LDL' to LL' */ /* -------------------------------------------------------------- */ for (j = 0 ; j < n ; j++) { /* pack column j */ pold = Lp [j] ; len = Lnz [j] ; ASSERT (len > 0) ; ASSERT (Li [pold] == j) ; PRINT2 (("col "ID" pnew "ID" pold "ID"\n", j, pnew, pold)) ; /* dj = Lx [pold] ; */ ASSIGN_REAL (dj,0, Lx,pold) ; if (IS_LE_ZERO (dj [0])) { /* Conversion has failed; matrix is not positive definite. * Do not modify the column so that the LDL' factorization * can be restored if desired, by converting back to LDL'. * Continue the conversion, but flag the error. */ if (L->minor == (size_t) n) { ERROR (CHOLMOD_NOT_POSDEF, "L not positive definite") ; L->minor = j ; } for (k = 0 ; k < len ; k++) { Li [pnew + k] = Li [pold + k] ; /* Lx [pnew + k] = Lx [pold + k] ; */ ASSIGN (Lx, Lz, pnew+k, Lx, Lz, pold+k) ; } } else { ljj [0] = sqrt (dj [0]) ; Li [pnew] = j ; /* Lx [pnew] = ljj ; */ ASSIGN_REAL (Lx, pnew, ljj, 0) ; CLEAR_IMAG (Lx, Lz, pnew) ; for (k = 1 ; k < len ; k++) { Li [pnew + k] = Li [pold + k] ; /* Lx [pnew + k] = Lx [pold + k] * ljj ; */ MULT_REAL (Lx, Lz, pnew+k, Lx, Lz, pold+k, ljj,0) ; } } Lp [j] = pnew ; pnew += len ; } } else if (make_ldl) { /* -------------------------------------------------------------- */ /* pack and convert LL' to LDL' */ /* -------------------------------------------------------------- */ for (j = 0 ; j < n ; j++) { /* pack column j */ pold = Lp [j] ; len = Lnz [j] ; /* ljj = Lx [pold] ; */ ASSIGN_REAL (ljj, 0, Lx, pold) ; ASSERT (len > 0) ; PRINT2 (("col "ID" pnew "ID" pold "ID"\n", j, pnew, pold)) ; if (ljj [0] <= 0) { /* matrix is not positive-definite; pack column as-is */ for (k = 0 ; k < len ; k++) { Li [pnew + k] = Li [pold + k] ; /* Lx [pnew + k] = Lx [pold + k] ; */ ASSIGN (Lx, Lz, pnew+k, Lx, Lz, pold+k) ; } } else { Li [pnew] = Li [pold] ; /* Lx [pnew] = ljj*ljj ; */ lj2 [0] = ljj [0] * ljj [0] ; ASSIGN_REAL (Lx, pnew, lj2, 0) ; CLEAR_IMAG (Lx, Lz, pnew) ; for (k = 1 ; k < len ; k++) { Li [pnew + k] = Li [pold + k] ; /* Lx [pnew + k] = Lx [pold + k] / ljj ; */ DIV_REAL (Lx, Lz, pnew+k, Lx, Lz, pold+k, ljj,0) ; } } Lp [j] = pnew ; pnew += len ; } } else { /* ---------------------------------------------------------- */ /* pack and leave LL' or LDL' as-is */ /* ---------------------------------------------------------- */ for (j = 0 ; j < n ; j++) { /* pack column j */ pold = Lp [j] ; len = Lnz [j] ; ASSERT (len > 0) ; PRINT2 (("col "ID" pnew "ID" pold "ID"\n", j, pnew, pold)) ; if (pnew < pold) { PRINT2 ((" pack this column\n")) ; for (k = 0 ; k < len ; k++) { Li [pnew + k] = Li [pold + k] ; /* Lx [pnew + k] = Lx [pold + k] ; */ ASSIGN (Lx, Lz, pnew+k, Lx, Lz, pold+k) ; } Lp [j] = pnew ; } pnew += len ; } } Lp [n] = pnew ; PRINT2 (("Lp [n] = "ID"\n", pnew)) ; } else if (make_ll) { /* ------------------------------------------------------------------ */ /* convert LDL' to LL', but do so in-place */ /* ------------------------------------------------------------------ */ for (j = 0 ; j < n ; j++) { p = Lp [j] ; pend = p + Lnz [j] ; /* dj = Lx [p] ; */ ASSIGN_REAL (dj,0, Lx,p) ; if (IS_LE_ZERO (dj [0])) { /* Conversion has failed; matrix is not positive definite. * Do not modify the column so that the LDL' factorization * can be restored if desired, by converting back to LDL'. * Continue the conversion, but flag the error. */ if (L->minor == (size_t) n) { ERROR (CHOLMOD_NOT_POSDEF, "L not positive definite") ; L->minor = j ; } } else { ljj [0] = sqrt (dj [0]) ; /* Lx [p] = ljj ; */ ASSIGN_REAL (Lx,p, ljj,0) ; CLEAR_IMAG (Lx, Lz, p) ; for (p++ ; p < pend ; p++) { /* Lx [p] *= ljj ; */ MULT_REAL (Lx,Lz,p, Lx,Lz,p, ljj,0) ; } } } } else if (make_ldl) { /* ------------------------------------------------------------------ */ /* convert LL' to LDL', but do so in-place */ /* ------------------------------------------------------------------ */ for (j = 0 ; j < n ; j++) { p = Lp [j] ; pend = p + Lnz [j] ; /* ljj = Lx [p] ; */ ASSIGN_REAL (ljj, 0, Lx, p) ; if (ljj [0] > 0) { /* Lx [p] = ljj*ljj ; */ lj2 [0] = ljj [0] * ljj [0] ; ASSIGN_REAL (Lx, p, lj2, 0) ; CLEAR_IMAG (Lx, Lz, p) ; for (p++ ; p < pend ; p++) { /* Lx [p] /= ljj ; */ DIV_REAL (Lx,Lz,p, Lx,Lz,p, ljj,0) ; } } } } L->is_ll = to_ll ; DEBUG (CHOLMOD(dump_factor) (L, "done change simplicial numeric", Common)) ; } /* ========================================================================== */ /* === t_ll_super_to_simplicial_numeric ===================================== */ /* ========================================================================== */ /* A supernodal L can only be real or complex, not zomplex */ #ifndef ZOMPLEX static void TEMPLATE (ll_super_to_simplicial_numeric) ( cholmod_factor *L, Int to_packed, Int to_ll, cholmod_common *Common ) { double ljj [1], lj2 [1] ; double *Lx ; Int *Ls, *Lpi, *Lpx, *Super, *Lp, *Li, *Lnz ; Int n, lnz, s, nsuper, p, psi, psx, psend, nsrow, nscol, ii, jj, j, k1, k2, q ; L->is_ll = to_ll ; Lp = L->p ; Li = L->i ; Lx = L->x ; Lnz = L->nz ; lnz = L->nzmax ; n = L->n ; nsuper = L->nsuper ; Lpi = L->pi ; Lpx = L->px ; Ls = L->s ; Super = L->super ; p = 0 ; for (s = 0 ; s < nsuper ; s++) { k1 = Super [s] ; k2 = Super [s+1] ; psi = Lpi [s] ; psend = Lpi [s+1] ; psx = Lpx [s] ; nsrow = psend - psi ; nscol = k2 - k1 ; for (jj = 0 ; jj < nscol ; jj++) { /* column j of L starts here */ j = jj + k1 ; if (to_ll) { if (to_packed) { /* ------------------------------------------------------ */ /* convert to LL' packed */ /* ------------------------------------------------------ */ Lp [j] = p ; PRINT2 (("Col j "ID" p "ID"\n", j, p)) ; for (ii = jj ; ii < nsrow ; ii++) { /* get L(i,j) from supernode and store in column j */ ASSERT (p < (Int) (L->xsize) && p <= psx+ii+jj*nsrow) ; Li [p] = Ls [psi + ii] ; /* Lx [p] = Lx [psx + ii + jj*nsrow] ; */ q = psx + ii + jj*nsrow ; ASSIGN (Lx,-,p, Lx,-,q) ; PRINT2 ((" i "ID" ", Li [p])) ; XPRINT2 (Lx,-,q) ; PRINT2 (("\n")) ; p++ ; } Lnz [j] = p - Lp [j] ; } else { /* ------------------------------------------------------ */ /* convert to LL' unpacked */ /* ------------------------------------------------------ */ p = psx + jj + jj*nsrow ; Lp [j] = p ; Li [p] = j ; Lnz [j] = nsrow - jj ; p++ ; for (ii = jj + 1 ; ii < nsrow ; ii++) { /* get L(i,j) from supernode and store in column j */ Li [psx + ii + jj*nsrow] = Ls [psi + ii] ; } } } else { if (to_packed) { /* ------------------------------------------------------ */ /* convert to LDL' packed */ /* ------------------------------------------------------ */ Lp [j] = p ; PRINT2 (("Col j "ID" p "ID"\n", Lp [j], p)) ; /* ljj = Lx [psx + jj + jj*nsrow] ; */ ASSIGN_REAL (ljj, 0, Lx, psx + jj + jj*nsrow) ; if (ljj [0] <= 0) { /* the matrix is not positive definite; do not divide */ /* Lx [p] = ljj ; */ ASSIGN_REAL (Lx, p, ljj, 0) ; CLEAR_IMAG (Lx, Lz, p) ; ljj [0] = 1 ; } else { lj2 [0] = ljj [0] * ljj [0] ; /* Lx [p] = ljj*ljj ; */ ASSIGN_REAL (Lx, p, lj2, 0) ; CLEAR_IMAG (Lx, Lz, p) ; } Li [p] = j ; p++ ; for (ii = jj + 1 ; ii < nsrow ; ii++) { /* get L(i,j) from supernode and store in column j */ ASSERT (p < (Int) (L->xsize) && p <= psx+ii+jj*nsrow) ; Li [p] = Ls [psi + ii] ; /* Lx [p] = Lx [psx + ii + jj*nsrow] / ljj ; */ q = psx + ii + jj*nsrow ; DIV_REAL (Lx, Lz, p, Lx, Lz, q, ljj,0) ; PRINT2 ((" i "ID" %g\n", Li [p], Lx [p])) ; p++ ; } Lnz [j] = p - Lp [j] ; } else { /* ------------------------------------------------------ */ /* convert to LDL' unpacked */ /* ------------------------------------------------------ */ p = psx + jj + jj*nsrow ; Lp [j] = p ; /* ljj = Lx [p] ; */ ASSIGN_REAL (ljj,0, Lx,p) ; if (ljj [0] <= 0) { /* the matrix is not positive definite; do not divide */ /* Lx [p] = ljj ; */ ASSIGN_REAL (Lx, p, ljj, 0) ; CLEAR_IMAG (Lx, Lz, p) ; ljj [0] = 1 ; } else { lj2 [0] = ljj [0] * ljj [0] ; /* Lx [p] = ljj*ljj ; */ ASSIGN_REAL (Lx, p, lj2, 0) ; CLEAR_IMAG (Lx, Lz, p) ; } Li [p] = j ; Lnz [j] = nsrow - jj ; p++ ; for (ii = jj + 1 ; ii < nsrow ; ii++) { /* get L(i,j) from supernode and store in column j */ Li [psx + ii + jj*nsrow] = Ls [psi + ii] ; /* Lx [psx + ii + jj*nsrow] /= ljj ; */ q = psx + ii + jj*nsrow ; DIV_REAL (Lx, Lz, q, Lx, Lz, q, ljj,0) ; } } } } } if (to_packed) { Lp [n] = p ; PRINT1 (("Final Lp "ID" n "ID" lnz "ID"\n", p, n, lnz)) ; ASSERT (Lp [n] == lnz) ; ASSERT (lnz <= (Int) (L->xsize)) ; /* reduce size of L->x to match L->i. This cannot fail. */ L->x = CHOLMOD(realloc) (lnz, #ifdef COMPLEX 2 * #endif sizeof (double), L->x, &(L->xsize), Common) ; ASSERT (lnz == (Int) (L->xsize)) ; Common->status = CHOLMOD_OK ; } else { Lp [n] = Lpx [nsuper] ; ASSERT (MAX (1,Lp [n]) == (Int) (L->xsize)) ; ASSERT (MAX (1,Lp [n]) == (Int) (L->nzmax)) ; } } #endif #undef PATTERN #undef REAL #undef COMPLEX #undef ZOMPLEX python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Core/t_cholmod_triplet.c0000644000076500000240000001110313524616144027234 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Core/t_cholmod_triplet =============================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Core Module. Copyright (C) 2005-2006, * Univ. of Florida. Author: Timothy A. Davis * The CHOLMOD/Core Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Template routine for cholmod_triplet. All xtypes supported */ #include "cholmod_template.h" /* ========================================================================== */ /* === t_cholmod_triplet_to_sparse ========================================== */ /* ========================================================================== */ static size_t TEMPLATE (cholmod_triplet_to_sparse) ( /* ---- input ---- */ cholmod_triplet *T, /* matrix to copy */ /* ---- in/out --- */ cholmod_sparse *R, /* output matrix */ /* --------------- */ cholmod_common *Common ) { double *Rx, *Rz, *Tx, *Tz ; Int *Wj, *Rp, *Ri, *Rnz, *Ti, *Tj ; Int i, j, p, p1, p2, pdest, pj, k, stype, nrow, ncol, nz ; size_t anz ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ /* Wj contains a copy of Rp on input [ */ Wj = Common->Iwork ; /* size MAX (nrow,ncol). (i/l/l) */ Rp = R->p ; Ri = R->i ; Rnz = R->nz ; Rx = R->x ; Rz = R->z ; Ti = T->i ; Tj = T->j ; Tx = T->x ; Tz = T->z ; nz = T->nnz ; nrow = T->nrow ; ncol = T->ncol ; stype = SIGN (T->stype) ; /* ---------------------------------------------------------------------- */ /* construct the row form */ /* ---------------------------------------------------------------------- */ /* if Ti is jumbled, this part dominates the run time */ if (stype > 0) { for (k = 0 ; k < nz ; k++) { i = Ti [k] ; j = Tj [k] ; if (i < j) { /* place triplet (j,i,x) in column i of R */ p = Wj [i]++ ; Ri [p] = j ; } else { /* place triplet (i,j,x) in column j of R */ p = Wj [j]++ ; Ri [p] = i ; } ASSIGN (Rx, Rz, p, Tx, Tz, k) ; } } else if (stype < 0) { for (k = 0 ; k < nz ; k++) { i = Ti [k] ; j = Tj [k] ; if (i > j) { /* place triplet (j,i,x) in column i of R */ p = Wj [i]++ ; Ri [p] = j ; } else { /* place triplet (i,j,x) in column j of R */ p = Wj [j]++ ; Ri [p] = i ; } ASSIGN (Rx, Rz, p, Tx, Tz, k) ; } } else { for (k = 0 ; k < nz ; k++) { /* place triplet (i,j,x) in column i of R */ p = Wj [Ti [k]]++ ; Ri [p] = Tj [k] ; ASSIGN (Rx, Rz, p, Tx, Tz, k) ; } } /* done using Wj (i/l/l) as temporary row pointers ] */ /* ---------------------------------------------------------------------- */ /* sum up duplicates */ /* ---------------------------------------------------------------------- */ /* use Wj (i/l/l) of size ncol to keep track of duplicates in each row [ */ for (j = 0 ; j < ncol ; j++) { Wj [j] = EMPTY ; } anz = 0 ; for (i = 0 ; i < nrow ; i++) { p1 = Rp [i] ; p2 = Rp [i+1] ; pdest = p1 ; /* at this point Wj [j] < p1 holds true for all columns j, because * Ri/Rx is stored in row oriented manner */ for (p = p1 ; p < p2 ; p++) { j = Ri [p] ; pj = Wj [j] ; if (pj >= p1) { /* this column index j is already in row i at position pj; * sum up the duplicate entry */ /* Rx [pj] += Rx [p] ; */ ASSEMBLE (Rx, Rz, pj, Rx, Rz, p) ; } else { /* keep the entry and keep track in Wj [j] for case above */ Wj [j] = pdest ; if (pdest != p) { Ri [pdest] = j ; ASSIGN (Rx, Rz, pdest, Rx, Rz, p) ; } pdest++ ; } } Rnz [i] = pdest - p1 ; anz += (pdest - p1) ; } /* done using Wj to keep track of duplicate entries in each row ] */ /* ---------------------------------------------------------------------- */ /* return number of entries after summing up duplicates */ /* ---------------------------------------------------------------------- */ return (anz) ; } #undef PATTERN #undef REAL #undef COMPLEX #undef ZOMPLEX python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Core/cholmod_add.c0000644000076500000240000002024013524616144025760 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Core/cholmod_add ===================================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Core Module. Copyright (C) 2005-2006, * Univ. of Florida. Author: Timothy A. Davis * The CHOLMOD/Core Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* C = alpha*A + beta*B, or spones(A+B). Result is packed, with sorted or * unsorted columns. This routine is much faster and takes less memory if C * is allowed to have unsorted columns. * * If A and B are both symmetric (in upper form) then C is the same. Likewise, * if A and B are both symmetric (in lower form) then C is the same. * Otherwise, C is unsymmetric. A and B must have the same dimension. * * workspace: Flag (nrow), W (nrow) if values, Iwork (max (nrow,ncol)). * allocates temporary copies for A and B if they are symmetric. * allocates temporary copy of C if it is to be returned sorted. * * A and B can have an xtype of pattern or real. Complex or zomplex cases * are supported only if the "values" input parameter is FALSE. */ #include "cholmod_internal.h" #include "cholmod_core.h" cholmod_sparse *CHOLMOD(add) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to add */ cholmod_sparse *B, /* matrix to add */ double alpha [2], /* scale factor for A */ double beta [2], /* scale factor for B */ int values, /* if TRUE compute the numerical values of C */ int sorted, /* if TRUE, sort columns of C */ /* --------------- */ cholmod_common *Common ) { double *Ax, *Bx, *Cx, *W ; Int apacked, up, lo, nrow, ncol, bpacked, nzmax, pa, paend, pb, pbend, i, j, p, mark, nz ; Int *Ap, *Ai, *Anz, *Bp, *Bi, *Bnz, *Flag, *Cp, *Ci ; cholmod_sparse *A2, *B2, *C ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; RETURN_IF_NULL (A, NULL) ; RETURN_IF_NULL (B, NULL) ; values = values && (A->xtype != CHOLMOD_PATTERN) && (B->xtype != CHOLMOD_PATTERN) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, values ? CHOLMOD_REAL : CHOLMOD_ZOMPLEX, NULL) ; RETURN_IF_XTYPE_INVALID (B, CHOLMOD_PATTERN, values ? CHOLMOD_REAL : CHOLMOD_ZOMPLEX, NULL) ; if (A->nrow != B->nrow || A->ncol != B->ncol) { /* A and B must have the same dimensions */ ERROR (CHOLMOD_INVALID, "A and B dimesions do not match") ; return (NULL) ; } /* A and B must have the same numerical type if values is TRUE (both must * be CHOLMOD_REAL, this is implicitly checked above) */ Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ nrow = A->nrow ; ncol = A->ncol ; CHOLMOD(allocate_work) (nrow, MAX (nrow,ncol), values ? nrow : 0, Common) ; if (Common->status < CHOLMOD_OK) { return (NULL) ; /* out of memory */ } /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ if (nrow <= 1) { /* C will be implicitly sorted, so no need to sort it here */ sorted = FALSE ; } /* convert A or B to unsymmetric, if necessary */ A2 = NULL ; B2 = NULL ; if (A->stype != B->stype) { if (A->stype) { /* workspace: Iwork (max (nrow,ncol)) */ A2 = CHOLMOD(copy) (A, 0, values, Common) ; if (Common->status < CHOLMOD_OK) { return (NULL) ; /* out of memory */ } A = A2 ; } if (B->stype) { /* workspace: Iwork (max (nrow,ncol)) */ B2 = CHOLMOD(copy) (B, 0, values, Common) ; if (Common->status < CHOLMOD_OK) { CHOLMOD(free_sparse) (&A2, Common) ; return (NULL) ; /* out of memory */ } B = B2 ; } } /* get the A matrix */ ASSERT (A->stype == B->stype) ; up = (A->stype > 0) ; lo = (A->stype < 0) ; Ap = A->p ; Anz = A->nz ; Ai = A->i ; Ax = A->x ; apacked = A->packed ; /* get the B matrix */ Bp = B->p ; Bnz = B->nz ; Bi = B->i ; Bx = B->x ; bpacked = B->packed ; /* get workspace */ W = Common->Xwork ; /* size nrow, used if values is TRUE */ Flag = Common->Flag ; /* size nrow, Flag [0..nrow-1] < mark on input */ /* ---------------------------------------------------------------------- */ /* allocate the result C */ /* ---------------------------------------------------------------------- */ /* If integer overflow occurs, nzmax < 0 and the allocate fails properly * (likewise in most other matrix manipulation routines). */ nzmax = CHOLMOD(nnz) (A, Common) + CHOLMOD(nnz) (B, Common) ; C = CHOLMOD(allocate_sparse) (nrow, ncol, nzmax, FALSE, TRUE, SIGN (A->stype), values ? A->xtype : CHOLMOD_PATTERN, Common) ; if (Common->status < CHOLMOD_OK) { CHOLMOD(free_sparse) (&A2, Common) ; CHOLMOD(free_sparse) (&B2, Common) ; return (NULL) ; /* out of memory */ } Cp = C->p ; Ci = C->i ; Cx = C->x ; /* ---------------------------------------------------------------------- */ /* compute C = alpha*A + beta*B */ /* ---------------------------------------------------------------------- */ nz = 0 ; for (j = 0 ; j < ncol ; j++) { Cp [j] = nz ; /* clear the Flag array */ /* mark = CHOLMOD(clear_flag) (Common) ; */ CHOLMOD_CLEAR_FLAG (Common) ; mark = Common->mark ; /* scatter B into W */ pb = Bp [j] ; pbend = (bpacked) ? (Bp [j+1]) : (pb + Bnz [j]) ; for (p = pb ; p < pbend ; p++) { i = Bi [p] ; if ((up && i > j) || (lo && i < j)) { continue ; } Flag [i] = mark ; if (values) { W [i] = beta [0] * Bx [p] ; } } /* add A and gather from W into C(:,j) */ pa = Ap [j] ; paend = (apacked) ? (Ap [j+1]) : (pa + Anz [j]) ; for (p = pa ; p < paend ; p++) { i = Ai [p] ; if ((up && i > j) || (lo && i < j)) { continue ; } Flag [i] = EMPTY ; Ci [nz] = i ; if (values) { Cx [nz] = W [i] + alpha [0] * Ax [p] ; W [i] = 0 ; } nz++ ; } /* gather remaining entries into C(:,j), using pattern of B */ for (p = pb ; p < pbend ; p++) { i = Bi [p] ; if ((up && i > j) || (lo && i < j)) { continue ; } if (Flag [i] == mark) { Ci [nz] = i ; if (values) { Cx [nz] = W [i] ; W [i] = 0 ; } nz++ ; } } } Cp [ncol] = nz ; /* ---------------------------------------------------------------------- */ /* reduce C in size and free temporary matrices */ /* ---------------------------------------------------------------------- */ ASSERT (MAX (1,nz) <= C->nzmax) ; CHOLMOD(reallocate_sparse) (nz, C, Common) ; ASSERT (Common->status >= CHOLMOD_OK) ; /* clear the Flag array */ mark = CHOLMOD(clear_flag) (Common) ; CHOLMOD(free_sparse) (&A2, Common) ; CHOLMOD(free_sparse) (&B2, Common) ; /* ---------------------------------------------------------------------- */ /* sort C, if requested */ /* ---------------------------------------------------------------------- */ if (sorted) { /* workspace: Iwork (max (nrow,ncol)) */ if (!CHOLMOD(sort) (C, Common)) { CHOLMOD(free_sparse) (&C, Common) ; if (Common->status < CHOLMOD_OK) { return (NULL) ; /* out of memory */ } } } /* ---------------------------------------------------------------------- */ /* return result */ /* ---------------------------------------------------------------------- */ ASSERT (CHOLMOD(dump_sparse) (C, "add", Common) >= 0) ; return (C) ; } python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Core/cholmod_change_factor.c0000644000076500000240000011335513524616144030025 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Core/cholmod_change_factor =========================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Core Module. Copyright (C) 2005-2006, * Univ. of Florida. Author: Timothy A. Davis * The CHOLMOD/Core Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Change the numeric/symbolic, LL/LDL, simplicial/super, packed/unpacked, * monotonic/non-monotonic status of a cholmod_factor object. * * There are four basic classes of factor types: * * (1) simplicial symbolic: Consists of two size-n arrays: the fill-reducing * permutation (L->Perm) and the nonzero count for each column of L * (L->ColCount). All other factor types also include this information. * L->ColCount may be exact (obtained from the analysis routines), or * it may be a guess. During factorization, and certainly after update/ * downdate, the columns of L can have a different number of nonzeros. * L->ColCount is used to allocate space. L->ColCount is exact for the * supernodal factorizations. The nonzero pattern of L is not kept. * * (2) simplicial numeric: These represent L in a compressed column form. The * variants of this type are: * * LDL': L is unit diagonal. Row indices in column j are located in * L->i [L->p [j] ... L->p [j] + L->nz [j]], and corresponding numeric * values are in the same locations in L->x. The total number of * entries is the sum of L->nz [j]. The unit diagonal is not stored; * D is stored on the diagonal of L instead. L->p may or may not be * monotonic. The order of storage of the columns in L->i and L->x is * given by a doubly-linked list (L->prev and L->next). L->p is of * size n+1, but only the first n entries are used (it is used if L * is converted to a sparse matrix via cholmod_factor_to_sparse). * * For the complex case, L->x is stored interleaved with real/imag * parts, and is of size 2*lnz*sizeof(double). For the zomplex case, * L->x is of size lnz*sizeof(double) and holds the real part; L->z * is the same size and holds the imaginary part. * * LL': This is identical to the LDL' form, except that the non-unit * diagonal of L is stored as the first entry in each column of L. * * (3) supernodal symbolic: A representation of the nonzero pattern of the * supernodes for a supernodal factorization. There are L->nsuper * supernodes. Columns L->super [k] to L->super [k+1]-1 are in the kth * supernode. The row indices for the kth supernode are in * L->s [L->pi [k] ... L->pi [k+1]-1]. The numerical values are not * allocated (L->x), but when they are they will be located in * L->x [L->px [k] ... L->px [k+1]-1], and the L->px array is defined * in this factor type. * * For the complex case, L->x is stored interleaved with real/imag parts, * and is of size 2*L->xsize*sizeof(double). The zomplex supernodal case * is not supported, since it is not compatible with LAPACK and the BLAS. * * (4) supernodal numeric: Always an LL' factorization. L is non-unit * diagonal. L->x contains the numerical values of the supernodes, as * described above for the supernodal symbolic factor. * For the complex case, L->x is stored interleaved, and is of size * 2*L->xsize*sizeof(double). The zomplex supernodal case is not * supported, since it is not compatible with LAPACK and the BLAS. * * FUTURE WORK: support a supernodal LDL' factor. * * * In all cases, the row indices in each column (L->i for simplicial L and * L->s for supernodal L) are kept sorted from low indices to high indices. * This means the diagonal of L (or D for LDL' factors) is always kept as the * first entry in each column. * * The cholmod_change_factor routine can do almost all possible conversions. * It cannot do the following conversions: * * (1) Simplicial numeric types cannot be converted to a supernodal * symbolic type. This would simultaneously deallocate the * simplicial pattern and numeric values and reallocate uninitialized * space for the supernodal pattern. This isn't useful for the user, * and not needed by CHOLMOD's own routines either. * * (2) Only a symbolic factor (simplicial to supernodal) can be converted * to a supernodal numeric factor. * * Some conversions are meant only to be used internally by other CHOLMOD * routines, and should not be performed by the end user. They allocate space * whose contents are undefined: * * (1) converting from simplicial symbolic to supernodal symbolic. * (2) converting any factor to supernodal numeric. * * workspace: no conversion routine uses workspace in Common. No temporary * workspace is allocated. * * Supports all xtypes, except that there is no supernodal zomplex L. * * The to_xtype parameter is used only when converting from symbolic to numeric * or numeric to symbolic. It cannot be used to convert a numeric xtype (real, * complex, or zomplex) to a different numeric xtype. For that conversion, * use cholmod_factor_xtype instead. */ #include "cholmod_internal.h" #include "cholmod_core.h" static void natural_list (cholmod_factor *L) ; /* ========================================================================== */ /* === TEMPLATE ============================================================= */ /* ========================================================================== */ #define REAL #include "t_cholmod_change_factor.c" #define COMPLEX #include "t_cholmod_change_factor.c" #define ZOMPLEX #include "t_cholmod_change_factor.c" /* ========================================================================== */ /* === L_is_packed ========================================================== */ /* ========================================================================== */ /* Return TRUE if the columns of L are packed, FALSE otherwise. For debugging * only. */ #ifndef NDEBUG static int L_is_packed (cholmod_factor *L, cholmod_common *Common) { Int j ; Int *Lnz = L->nz ; Int *Lp = L->p ; Int n = L->n ; if (L->xtype == CHOLMOD_PATTERN || L->is_super) { return (TRUE) ; } if (Lnz == NULL || Lp == NULL) { return (TRUE) ; } for (j = 0 ; j < n ; j++) { PRINT3 (("j: "ID" Lnz "ID" Lp[j+1] "ID" Lp[j] "ID"\n", j, Lnz [j], Lp [j+1], Lp [j])) ; if (Lnz [j] != (Lp [j+1] - Lp [j])) { PRINT2 (("L is not packed\n")) ; return (FALSE) ; } } return (TRUE) ; } #endif /* ========================================================================== */ /* === natural_list ========================================================= */ /* ========================================================================== */ /* Create a naturally-ordered doubly-linked list of columns. */ static void natural_list (cholmod_factor *L) { Int head, tail, n, j ; Int *Lnext, *Lprev ; Lnext = L->next ; Lprev = L->prev ; ASSERT (Lprev != NULL && Lnext != NULL) ; n = L->n ; head = n+1 ; tail = n ; Lnext [head] = 0 ; Lprev [head] = EMPTY ; Lnext [tail] = EMPTY ; Lprev [tail] = n-1 ; for (j = 0 ; j < n ; j++) { Lnext [j] = j+1 ; Lprev [j] = j-1 ; } Lprev [0] = head ; L->is_monotonic = TRUE ; } /* ========================================================================== */ /* === allocate_simplicial_numeric ========================================== */ /* ========================================================================== */ /* Allocate O(n) arrays for simplicial numeric factorization. Initializes * the link lists only. Does not allocate the L->i, L->x, or L->z arrays. */ static int allocate_simplicial_numeric ( cholmod_factor *L, cholmod_common *Common ) { Int n ; Int *Lp, *Lnz, *Lprev, *Lnext ; size_t n1, n2 ; PRINT1 (("Allocate simplicial\n")) ; ASSERT (L->xtype == CHOLMOD_PATTERN || L->is_super) ; ASSERT (L->p == NULL) ; ASSERT (L->nz == NULL) ; ASSERT (L->prev == NULL) ; ASSERT (L->next == NULL) ; n = L->n ; /* this cannot cause size_t overflow */ n1 = ((size_t) n) + 1 ; n2 = ((size_t) n) + 2 ; Lp = CHOLMOD(malloc) (n1, sizeof (Int), Common) ; Lnz = CHOLMOD(malloc) (n, sizeof (Int), Common) ; Lprev = CHOLMOD(malloc) (n2, sizeof (Int), Common) ; Lnext = CHOLMOD(malloc) (n2, sizeof (Int), Common) ; if (Common->status < CHOLMOD_OK) { CHOLMOD(free) (n1, sizeof (Int), Lp, Common) ; CHOLMOD(free) (n, sizeof (Int), Lnz, Common) ; CHOLMOD(free) (n2, sizeof (Int), Lprev, Common) ; CHOLMOD(free) (n2, sizeof (Int), Lnext, Common) ; PRINT1 (("Allocate simplicial failed\n")) ; return (FALSE) ; /* out of memory */ } /* ============================================== commit the changes to L */ L->p = Lp ; L->nz = Lnz ; L->prev = Lprev ; L->next = Lnext ; /* initialize a doubly linked list for columns in natural order */ natural_list (L) ; PRINT1 (("Allocate simplicial done\n")) ; return (TRUE) ; } /* ========================================================================== */ /* === simplicial_symbolic_to_super_symbolic ================================ */ /* ========================================================================== */ /* Convert a simplicial symbolic factor supernodal symbolic factor. Does not * initialize the new space. */ static int simplicial_symbolic_to_super_symbolic ( cholmod_factor *L, cholmod_common *Common ) { Int nsuper, xsize, ssize ; Int *Lsuper, *Lpi, *Lpx, *Ls ; size_t nsuper1 ; ASSERT (L->xtype == CHOLMOD_PATTERN && !(L->is_super)) ; xsize = L->xsize ; ssize = L->ssize ; nsuper = L->nsuper ; nsuper1 = ((size_t) nsuper) + 1 ; PRINT1 (("simple sym to super sym: ssize "ID" xsize "ID" nsuper "ID"" " status %d\n", ssize, xsize, nsuper, Common->status)) ; /* O(nsuper) arrays, where nsuper <= n */ Lsuper = CHOLMOD(malloc) (nsuper1, sizeof (Int), Common) ; Lpi = CHOLMOD(malloc) (nsuper1, sizeof (Int), Common) ; Lpx = CHOLMOD(malloc) (nsuper1, sizeof (Int), Common) ; /* O(ssize) array, where ssize <= nnz(L), and usually much smaller */ Ls = CHOLMOD(malloc) (ssize, sizeof (Int), Common) ; if (Common->status < CHOLMOD_OK) { CHOLMOD(free) (nsuper1, sizeof (Int), Lsuper, Common) ; CHOLMOD(free) (nsuper1, sizeof (Int), Lpi, Common) ; CHOLMOD(free) (nsuper1, sizeof (Int), Lpx, Common) ; CHOLMOD(free) (ssize, sizeof (Int), Ls, Common) ; return (FALSE) ; /* out of memory */ } /* ============================================== commit the changes to L */ ASSERT (Lsuper != NULL && Lpi != NULL && Lpx != NULL && Ls != NULL) ; L->maxcsize = 0 ; L->maxesize = 0 ; L->super = Lsuper ; L->pi = Lpi ; L->px = Lpx ; L->s = Ls ; Ls [0] = EMPTY ; /* supernodal pattern undefined */ L->is_super = TRUE ; L->is_ll = TRUE ; /* supernodal LDL' not supported */ L->xtype = CHOLMOD_PATTERN ; L->dtype = DTYPE ; L->minor = L->n ; return (TRUE) ; } /* ========================================================================== */ /* === any_to_simplicial_symbolic =========================================== */ /* ========================================================================== */ /* Convert any factor L to a simplicial symbolic factor, leaving only L->Perm * and L->ColCount. Cannot fail. Any of the components of L (except Perm and * ColCount) may already be free'd. */ static void any_to_simplicial_symbolic ( cholmod_factor *L, int to_ll, cholmod_common *Common ) { Int n, lnz, xs, ss, s, e ; size_t n1, n2 ; /* ============================================== commit the changes to L */ n = L->n ; lnz = L->nzmax ; s = L->nsuper + 1 ; xs = (L->is_super) ? ((Int) (L->xsize)) : (lnz) ; e = (L->xtype == CHOLMOD_COMPLEX ? 2 : 1) ; ss = L->ssize ; /* this cannot cause size_t overflow */ n1 = ((size_t) n) + 1 ; n2 = ((size_t) n) + 2 ; /* free all but the symbolic analysis (Perm and ColCount) */ L->p = CHOLMOD(free) (n1, sizeof (Int), L->p, Common) ; L->i = CHOLMOD(free) (lnz, sizeof (Int), L->i, Common) ; L->x = CHOLMOD(free) (xs, e*sizeof (double), L->x, Common) ; L->z = CHOLMOD(free) (lnz, sizeof (double), L->z, Common) ; L->nz = CHOLMOD(free) (n, sizeof (Int), L->nz, Common) ; L->next = CHOLMOD(free) (n2, sizeof (Int), L->next, Common) ; L->prev = CHOLMOD(free) (n2, sizeof (Int), L->prev, Common) ; L->super = CHOLMOD(free) (s, sizeof (Int), L->super, Common) ; L->pi = CHOLMOD(free) (s, sizeof (Int), L->pi, Common) ; L->px = CHOLMOD(free) (s, sizeof (Int), L->px, Common) ; L->s = CHOLMOD(free) (ss, sizeof (Int), L->s, Common) ; L->nzmax = 0 ; L->is_super = FALSE ; L->xtype = CHOLMOD_PATTERN ; L->dtype = DTYPE ; L->minor = n ; L->is_ll = to_ll ; } /* ========================================================================== */ /* === ll_super_to_super_symbolic =========================================== */ /* ========================================================================== */ /* Convert a numerical supernodal L to symbolic supernodal. Cannot fail. */ static void ll_super_to_super_symbolic ( cholmod_factor *L, cholmod_common *Common ) { /* ============================================== commit the changes to L */ /* free all but the supernodal numerical factor */ ASSERT (L->xtype != CHOLMOD_PATTERN && L->is_super && L->is_ll) ; DEBUG (CHOLMOD(dump_factor) (L, "start to super symbolic", Common)) ; L->x = CHOLMOD(free) (L->xsize, (L->xtype == CHOLMOD_COMPLEX ? 2 : 1) * sizeof (double), L->x, Common) ; L->xtype = CHOLMOD_PATTERN ; L->dtype = DTYPE ; L->minor = L->n ; L->is_ll = TRUE ; /* supernodal LDL' not supported */ DEBUG (CHOLMOD(dump_factor) (L, "done to super symbolic", Common)) ; } /* ========================================================================== */ /* === simplicial_symbolic_to_simplicial_numeric ============================ */ /* ========================================================================== */ /* Convert a simplicial symbolic L to a simplicial numeric L; allocate space * for L using L->ColCount from symbolic analysis, and set L to identity. * * If packed < 0, then this routine is creating a copy of another factor * (via cholmod_copy_factor). In this case, the space is not initialized. */ static void simplicial_symbolic_to_simplicial_numeric ( cholmod_factor *L, int to_ll, int packed, int to_xtype, cholmod_common *Common ) { double grow0, grow1, xlen, xlnz ; double *Lx, *Lz ; Int *Li, *Lp, *Lnz, *ColCount ; Int n, grow, grow2, p, j, lnz, len, ok, e ; ASSERT (L->xtype == CHOLMOD_PATTERN && !(L->is_super)) ; if (!allocate_simplicial_numeric (L, Common)) { PRINT1 (("out of memory, allocate simplicial numeric\n")) ; return ; /* out of memory */ } ASSERT (L->ColCount != NULL && L->nz != NULL && L->p != NULL) ; ASSERT (L->x == NULL && L->z == NULL && L->i == NULL) ; ColCount = L->ColCount ; Lnz = L->nz ; Lp = L->p ; ok = TRUE ; n = L->n ; if (packed < 0) { /* ------------------------------------------------------------------ */ /* used by cholmod_copy_factor to allocate a copy of a factor object */ /* ------------------------------------------------------------------ */ lnz = L->nzmax ; L->nzmax = 0 ; } else if (packed) { /* ------------------------------------------------------------------ */ /* LDL' or LL' packed */ /* ------------------------------------------------------------------ */ PRINT1 (("convert to packed LL' or LDL'\n")) ; lnz = 0 ; for (j = 0 ; ok && j < n ; j++) { /* ensure len is in the range 1 to n-j */ len = ColCount [j] ; len = MAX (1, len) ; len = MIN (len, n-j) ; lnz += len ; ok = (lnz >= 0) ; } for (j = 0 ; j <= n ; j++) { Lp [j] = j ; } for (j = 0 ; j < n ; j++) { Lnz [j] = 1 ; } } else { /* ------------------------------------------------------------------ */ /* LDL' unpacked */ /* ------------------------------------------------------------------ */ PRINT1 (("convert to unpacked\n")) ; /* compute new lnzmax */ /* if any parameter is NaN, grow is false */ grow0 = Common->grow0 ; grow1 = Common->grow1 ; grow2 = Common->grow2 ; grow0 = IS_NAN (grow0) ? 1 : grow0 ; grow1 = IS_NAN (grow1) ? 1 : grow1 ; /* fl.pt. compare, but no NaN's: */ grow = (grow0 >= 1.0) && (grow1 >= 1.0) && (grow2 > 0) ; PRINT1 (("init, grow1 %g grow2 "ID"\n", grow1, grow2)) ; /* initialize Lp and Lnz for each column */ lnz = 0 ; for (j = 0 ; ok && j < n ; j++) { Lp [j] = lnz ; Lnz [j] = 1 ; /* ensure len is in the range 1 to n-j */ len = ColCount [j] ; len = MAX (1, len) ; len = MIN (len, n-j) ; /* compute len in double to avoid integer overflow */ PRINT1 (("ColCount ["ID"] = "ID"\n", j, len)) ; if (grow) { xlen = (double) len ; xlen = grow1 * xlen + grow2 ; xlen = MIN (xlen, n-j) ; len = (Int) xlen ; } ASSERT (len >= 1 && len <= n-j) ; lnz += len ; ok = (lnz >= 0) ; } if (ok) { Lp [n] = lnz ; if (grow) { /* add extra space */ xlnz = (double) lnz ; xlnz *= grow0 ; xlnz = MIN (xlnz, Size_max) ; xlnz = MIN (xlnz, ((double) n * (double) n + (double) n) / 2) ; lnz = (Int) xlnz ; } } } lnz = MAX (1, lnz) ; if (!ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; } /* allocate L->i, L->x, and L->z */ PRINT1 (("resizing from zero size to lnz "ID"\n", lnz)) ; ASSERT (L->nzmax == 0) ; e = (to_xtype == CHOLMOD_COMPLEX ? 2 : 1) ; if (!ok || !CHOLMOD(realloc_multiple) (lnz, 1, to_xtype, &(L->i), NULL, &(L->x), &(L->z), &(L->nzmax), Common)) { L->p = CHOLMOD(free) (n+1, sizeof (Int), L->p, Common) ; L->nz = CHOLMOD(free) (n, sizeof (Int), L->nz, Common) ; L->prev = CHOLMOD(free) (n+2, sizeof (Int), L->prev, Common) ; L->next = CHOLMOD(free) (n+2, sizeof (Int), L->next, Common) ; L->i = CHOLMOD(free) (lnz, sizeof (Int), L->i, Common) ; L->x = CHOLMOD(free) (lnz, e*sizeof (double), L->x, Common) ; L->z = CHOLMOD(free) (lnz, sizeof (double), L->z, Common) ; PRINT1 (("cannot realloc simplicial numeric\n")) ; return ; /* out of memory */ } /* ============================================== commit the changes to L */ /* initialize L to be the identity matrix */ L->xtype = to_xtype ; L->dtype = DTYPE ; L->minor = n ; Li = L->i ; Lx = L->x ; Lz = L->z ; #if 0 if (lnz == 1) { /* the user won't expect to access this entry, but some CHOLMOD * routines may. Set it to zero so that valgrind doesn't complain. */ switch (to_xtype) { case CHOLMOD_REAL: Lx [0] = 0 ; break ; case CHOLMOD_COMPLEX: Lx [0] = 0 ; Lx [1] = 0 ; break ; case CHOLMOD_ZOMPLEX: Lx [0] = 0 ; Lz [0] = 0 ; break ; } } #endif if (packed >= 0) { /* create the unit diagonal for either the LL' or LDL' case */ switch (L->xtype) { case CHOLMOD_REAL: for (j = 0 ; j < n ; j++) { ASSERT (Lp [j] < Lp [j+1]) ; p = Lp [j] ; Li [p] = j ; Lx [p] = 1 ; } break ; case CHOLMOD_COMPLEX: for (j = 0 ; j < n ; j++) { ASSERT (Lp [j] < Lp [j+1]) ; p = Lp [j] ; Li [p] = j ; Lx [2*p ] = 1 ; Lx [2*p+1] = 0 ; } break ; case CHOLMOD_ZOMPLEX: for (j = 0 ; j < n ; j++) { ASSERT (Lp [j] < Lp [j+1]) ; p = Lp [j] ; Li [p] = j ; Lx [p] = 1 ; Lz [p] = 0 ; } break ; } } L->is_ll = to_ll ; PRINT1 (("done convert simplicial symbolic to numeric\n")) ; } /* ========================================================================== */ /* === change_simplicial_numeric ============================================ */ /* ========================================================================== */ /* Change LL' to LDL', LDL' to LL', or leave as-is. * * If to_packed is TRUE, then the columns of L are packed and made monotonic * (to_monotonic is ignored; it is implicitly TRUE). * * If to_monotonic is TRUE but to_packed is FALSE, the columns of L are made * monotonic but not packed. * * If both to_packed and to_monotonic are FALSE, then the columns of L are * left as-is, and the conversion is done in place. * * If L is already monotonic, or if it is to be left non-monotonic, then this * conversion always succeeds. * * When converting an LDL' to LL' factorization, any column with a negative * or zero diagonal entry is not modified so that conversion back to LDL' will * succeed. This can result in a matrix L with a negative entry on the diagonal * If the kth entry on the diagonal of D is negative, it and the kth column of * L are left unchanged. A subsequent conversion back to an LDL' form will also * leave the column unchanged, so the correct LDL' factorization will be * restored. L->minor is set to the smallest k for which D (k,k) is negative. */ static void change_simplicial_numeric ( cholmod_factor *L, int to_ll, int to_packed, int to_monotonic, cholmod_common *Common ) { double grow0, grow1, xlen, xlnz ; void *newLi, *newLx, *newLz ; double *Lx, *Lz ; Int *Lp, *Li, *Lnz ; Int make_monotonic, grow2, n, j, lnz, len, grow, ok, make_ll, make_ldl ; size_t nzmax0 ; PRINT1 (("\n===Change simplicial numeric: %d %d %d\n", to_ll, to_packed, to_monotonic)) ; DEBUG (CHOLMOD(dump_factor) (L, "change simplicial numeric", Common)) ; ASSERT (L->xtype != CHOLMOD_PATTERN && !(L->is_super)) ; make_monotonic = ((to_packed || to_monotonic) && !(L->is_monotonic)) ; make_ll = (to_ll && !(L->is_ll)) ; make_ldl = (!to_ll && L->is_ll) ; n = L->n ; Lp = L->p ; Li = L->i ; Lx = L->x ; Lz = L->z ; Lnz = L->nz ; grow = FALSE ; grow0 = Common->grow0 ; grow1 = Common->grow1 ; grow2 = Common->grow2 ; grow0 = IS_NAN (grow0) ? 1 : grow0 ; grow1 = IS_NAN (grow1) ? 1 : grow1 ; ok = TRUE ; newLi = NULL ; newLx = NULL ; newLz = NULL ; lnz = 0 ; if (make_monotonic) { /* ------------------------------------------------------------------ */ /* Columns out of order, but will be reordered and optionally packed. */ /* ------------------------------------------------------------------ */ PRINT1 (("L is non-monotonic\n")) ; /* compute new L->nzmax */ if (!to_packed) { /* if any parameter is NaN, grow is false */ /* fl.pt. comparisons below are false if any parameter is NaN */ grow = (grow0 >= 1.0) && (grow1 >= 1.0) && (grow2 > 0) ; } for (j = 0 ; ok && j < n ; j++) { len = Lnz [j] ; ASSERT (len >= 1 && len <= n-j) ; /* compute len in double to avoid integer overflow */ if (grow) { xlen = (double) len ; xlen = grow1 * xlen + grow2 ; xlen = MIN (xlen, n-j) ; len = (Int) xlen ; } ASSERT (len >= Lnz [j] && len <= n-j) ; PRINT2 (("j: "ID" Lnz[j] "ID" len "ID" p "ID"\n", j, Lnz [j], len, lnz)) ; lnz += len ; ok = (lnz >= 0) ; } if (!ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return ; } if (grow) { xlnz = (double) lnz ; xlnz *= grow0 ; xlnz = MIN (xlnz, Size_max) ; xlnz = MIN (xlnz, ((double) n * (double) n + (double) n) / 2) ; lnz = (Int) xlnz ; } lnz = MAX (1, lnz) ; PRINT1 (("final lnz "ID"\n", lnz)) ; nzmax0 = 0 ; CHOLMOD(realloc_multiple) (lnz, 1, L->xtype, &newLi, NULL, &newLx, &newLz, &nzmax0, Common) ; if (Common->status < CHOLMOD_OK) { return ; /* out of memory */ } } /* ============================================== commit the changes to L */ /* ---------------------------------------------------------------------- */ /* convert the simplicial L, using template routine */ /* ---------------------------------------------------------------------- */ switch (L->xtype) { case CHOLMOD_REAL: r_change_simplicial_numeric (L, to_ll, to_packed, newLi, newLx, newLz, lnz, grow, grow1, grow2, make_ll, make_monotonic, make_ldl, Common) ; break ; case CHOLMOD_COMPLEX: c_change_simplicial_numeric (L, to_ll, to_packed, newLi, newLx, newLz, lnz, grow, grow1, grow2, make_ll, make_monotonic, make_ldl, Common) ; break ; case CHOLMOD_ZOMPLEX: z_change_simplicial_numeric (L, to_ll, to_packed, newLi, newLx, newLz, lnz, grow, grow1, grow2, make_ll, make_monotonic, make_ldl, Common) ; break ; } DEBUG (CHOLMOD(dump_factor) (L, "L simplicial changed", Common)) ; } /* ========================================================================== */ /* === ll_super_to_simplicial_numeric ======================================= */ /* ========================================================================== */ /* Convert a supernodal numeric factorization to any simplicial numeric one. * Leaves L->xtype unchanged (real or complex, not zomplex since there is * no supernodal zomplex L). */ static void ll_super_to_simplicial_numeric ( cholmod_factor *L, int to_packed, int to_ll, cholmod_common *Common ) { Int *Ls, *Lpi, *Lpx, *Super, *Li ; Int n, lnz, s, nsuper, psi, psend, nsrow, nscol, k1, k2, erows ; DEBUG (CHOLMOD(dump_factor) (L, "start LL super to simplicial", Common)) ; PRINT1 (("super -> simplicial (%d %d)\n", to_packed, to_ll)) ; ASSERT (L->xtype != CHOLMOD_PATTERN && L->is_ll && L->is_super) ; ASSERT (L->x != NULL && L->i == NULL) ; n = L->n ; nsuper = L->nsuper ; Lpi = L->pi ; Lpx = L->px ; Ls = L->s ; Super = L->super ; /* Int overflow cannot occur since supernodal L already exists */ if (to_packed) { /* count the number of nonzeros in L. Each supernode is of the form * * l . . . For this example, nscol = 4 (# columns). nsrow = 9. * l l . . The "." entries are allocated in the supernodal * l l l . factor, but not used. They are not copied to the * l l l l simplicial factor. Some "l" and "e" entries may be * e e e e numerically zero and even symbolically zero if a * e e e e tight simplicial factorization or resymbol were * e e e e done, because of numerical cancellation and relaxed * e e e e supernode amalgamation, respectively. * e e e e */ lnz = 0 ; for (s = 0 ; s < nsuper ; s++) { k1 = Super [s] ; k2 = Super [s+1] ; psi = Lpi [s] ; psend = Lpi [s+1] ; nsrow = psend - psi ; nscol = k2 - k1 ; ASSERT (nsrow >= nscol) ; erows = nsrow - nscol ; /* lower triangular part, including the diagonal, * counting the "l" terms in the figure above. */ lnz += nscol * (nscol+1) / 2 ; /* rectangular part, below the diagonal block (the "e" terms) */ lnz += nscol * erows ; } ASSERT (lnz <= (Int) (L->xsize)) ; } else { /* Li will be the same size as Lx */ lnz = L->xsize ; } ASSERT (lnz >= 0) ; PRINT1 (("simplicial lnz = "ID" to_packed: %d to_ll: %d L->xsize %g\n", lnz, to_ll, to_packed, (double) L->xsize)) ; Li = CHOLMOD(malloc) (lnz, sizeof (Int), Common) ; if (Common->status < CHOLMOD_OK) { return ; /* out of memory */ } if (!allocate_simplicial_numeric (L, Common)) { CHOLMOD(free) (lnz, sizeof (Int), Li, Common) ; return ; /* out of memory */ } /* ============================================== commit the changes to L */ L->i = Li ; L->nzmax = lnz ; /* ---------------------------------------------------------------------- */ /* convert the supernodal L, using template routine */ /* ---------------------------------------------------------------------- */ switch (L->xtype) { case CHOLMOD_REAL: r_ll_super_to_simplicial_numeric (L, to_packed, to_ll, Common) ; break ; case CHOLMOD_COMPLEX: c_ll_super_to_simplicial_numeric (L, to_packed, to_ll, Common) ; break ; } /* ---------------------------------------------------------------------- */ /* free unused parts of L */ /* ---------------------------------------------------------------------- */ L->super = CHOLMOD(free) (nsuper+1, sizeof (Int), L->super, Common) ; L->pi = CHOLMOD(free) (nsuper+1, sizeof (Int), L->pi, Common) ; L->px = CHOLMOD(free) (nsuper+1, sizeof (Int), L->px, Common) ; L->s = CHOLMOD(free) (L->ssize, sizeof (Int), L->s, Common) ; L->ssize = 0 ; L->xsize = 0 ; L->nsuper = 0 ; L->maxesize = 0 ; L->maxcsize = 0 ; L->is_super = FALSE ; DEBUG (CHOLMOD(dump_factor) (L, "done LL super to simplicial", Common)) ; } /* ========================================================================== */ /* === super_symbolic_to_ll_super =========================================== */ /* ========================================================================== */ /* Convert a supernodal symbolic factorization to a supernodal numeric * factorization by allocating L->x. Contents of L->x are undefined. */ static int super_symbolic_to_ll_super ( int to_xtype, cholmod_factor *L, cholmod_common *Common ) { double *Lx ; Int wentry = (to_xtype == CHOLMOD_REAL) ? 1 : 2 ; PRINT1 (("convert super sym to num\n")) ; ASSERT (L->xtype == CHOLMOD_PATTERN && L->is_super) ; Lx = CHOLMOD(malloc) (L->xsize, wentry * sizeof (double), Common) ; PRINT1 (("xsize %g\n", (double) L->xsize)) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; /* out of memory */ } /* ============================================== commit the changes to L */ if (L->xsize == 1) { /* the caller won't expect to access this entry, but some CHOLMOD * routines may. Set it to zero so that valgrind doesn't complain. */ switch (to_xtype) { case CHOLMOD_REAL: Lx [0] = 0 ; break ; case CHOLMOD_COMPLEX: Lx [0] = 0 ; Lx [1] = 0 ; break ; } } L->x = Lx ; L->xtype = to_xtype ; L->dtype = DTYPE ; L->minor = L->n ; return (TRUE) ; } /* ========================================================================== */ /* === cholmod_change_factor ================================================ */ /* ========================================================================== */ /* Convert a factor L. Some conversions simply allocate uninitialized space * that meant to be filled later. * * If the conversion fails, the factor is left in its original form, with one * exception. Converting a supernodal symbolic factor to a simplicial numeric * one (with L=D=I) may leave the factor in simplicial symbolic form. * * Memory allocated for each conversion is listed below. */ int CHOLMOD(change_factor) ( /* ---- input ---- */ int to_xtype, /* convert to CHOLMOD_PATTERN, _REAL, _COMPLEX, or * _ZOMPLEX */ int to_ll, /* TRUE: convert to LL', FALSE: LDL' */ int to_super, /* TRUE: convert to supernodal, FALSE: simplicial */ int to_packed, /* TRUE: pack simplicial columns, FALSE: do not pack */ int to_monotonic, /* TRUE: put simplicial columns in order, FALSE: not */ /* ---- in/out --- */ cholmod_factor *L, /* factor to modify */ /* --------------- */ cholmod_common *Common ) { /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (L, FALSE) ; RETURN_IF_XTYPE_INVALID (L, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; if (to_xtype < CHOLMOD_PATTERN || to_xtype > CHOLMOD_ZOMPLEX) { ERROR (CHOLMOD_INVALID, "xtype invalid") ; return (FALSE) ; } Common->status = CHOLMOD_OK ; PRINT1 (("-----convert from (%d,%d,%d,%d,%d) to (%d,%d,%d,%d,%d)\n", L->xtype, L->is_ll, L->is_super, L_is_packed (L, Common), L->is_monotonic, to_xtype, to_ll, to_super, to_packed, to_monotonic)) ; /* ensure all parameters are TRUE/FALSE */ to_ll = BOOLEAN (to_ll) ; to_super = BOOLEAN (to_super) ; ASSERT (BOOLEAN (L->is_ll) == L->is_ll) ; ASSERT (BOOLEAN (L->is_super) == L->is_super) ; if (to_super && to_xtype == CHOLMOD_ZOMPLEX) { ERROR (CHOLMOD_INVALID, "supernodal zomplex L not supported") ; return (FALSE) ; } /* ---------------------------------------------------------------------- */ /* convert */ /* ---------------------------------------------------------------------- */ if (to_xtype == CHOLMOD_PATTERN) { /* ------------------------------------------------------------------ */ /* convert to symbolic */ /* ------------------------------------------------------------------ */ if (!to_super) { /* -------------------------------------------------------------- */ /* convert any factor into a simplicial symbolic factor */ /* -------------------------------------------------------------- */ any_to_simplicial_symbolic (L, to_ll, Common) ; /* cannot fail */ } else { /* -------------------------------------------------------------- */ /* convert to a supernodal symbolic factor */ /* -------------------------------------------------------------- */ if (L->xtype != CHOLMOD_PATTERN && L->is_super) { /* convert from supernodal numeric to supernodal symbolic. * this preserves symbolic pattern of L, discards numeric * values */ ll_super_to_super_symbolic (L, Common) ; /* cannot fail */ } else if (L->xtype == CHOLMOD_PATTERN && !(L->is_super)) { /* convert from simplicial symbolic to supernodal symbolic. * contents of supernodal pattern are uninitialized. Not meant * for the end user. */ simplicial_symbolic_to_super_symbolic (L, Common) ; } else { /* cannot convert from simplicial numeric to supernodal * symbolic */ ERROR (CHOLMOD_INVALID, "cannot convert L to supernodal symbolic") ; } } } else { /* ------------------------------------------------------------------ */ /* convert to numeric */ /* ------------------------------------------------------------------ */ if (to_super) { /* -------------------------------------------------------------- */ /* convert to supernodal numeric factor */ /* -------------------------------------------------------------- */ if (L->xtype == CHOLMOD_PATTERN) { if (L->is_super) { /* Convert supernodal symbolic to supernodal numeric. * Contents of supernodal numeric values are uninitialized. * This is used by cholmod_super_numeric. Not meant for * the end user. */ super_symbolic_to_ll_super (to_xtype, L, Common) ; } else { /* Convert simplicial symbolic to supernodal numeric. * Contents not defined. This is used by * Core/cholmod_copy_factor only. Not meant for the end * user. */ if (!simplicial_symbolic_to_super_symbolic (L, Common)) { /* failure, convert back to simplicial symbolic */ any_to_simplicial_symbolic (L, to_ll, Common) ; } else { /* conversion to super symbolic OK, allocate numeric * part */ super_symbolic_to_ll_super (to_xtype, L, Common) ; } } } else { /* nothing to do if L is already in supernodal numeric form */ if (!(L->is_super)) { ERROR (CHOLMOD_INVALID, "cannot convert simplicial L to supernodal") ; } /* FUTURE WORK: convert to/from supernodal LL' and LDL' */ } } else { /* -------------------------------------------------------------- */ /* convert any factor to simplicial numeric */ /* -------------------------------------------------------------- */ if (L->xtype == CHOLMOD_PATTERN && !(L->is_super)) { /* ---------------------------------------------------------- */ /* convert simplicial symbolic to simplicial numeric (L=I,D=I)*/ /* ---------------------------------------------------------- */ simplicial_symbolic_to_simplicial_numeric (L, to_ll, to_packed, to_xtype, Common) ; } else if (L->xtype != CHOLMOD_PATTERN && L->is_super) { /* ---------------------------------------------------------- */ /* convert a supernodal LL' to simplicial numeric */ /* ---------------------------------------------------------- */ ll_super_to_simplicial_numeric (L, to_packed, to_ll, Common) ; } else if (L->xtype == CHOLMOD_PATTERN && L->is_super) { /* ---------------------------------------------------------- */ /* convert a supernodal symbolic to simplicial numeric (L=D=I)*/ /* ---------------------------------------------------------- */ any_to_simplicial_symbolic (L, to_ll, Common) ; /* if the following fails, it leaves the factor in simplicial * symbolic form */ simplicial_symbolic_to_simplicial_numeric (L, to_ll, to_packed, to_xtype, Common) ; } else { /* ---------------------------------------------------------- */ /* change a simplicial numeric factor */ /* ---------------------------------------------------------- */ /* change LL' to LDL', LDL' to LL', or leave as-is. pack the * columns of L, or leave as-is. Ensure the columns are * monotonic, or leave as-is. */ change_simplicial_numeric (L, to_ll, to_packed, to_monotonic, Common) ; } } } /* ---------------------------------------------------------------------- */ /* return result */ /* ---------------------------------------------------------------------- */ return (Common->status >= CHOLMOD_OK) ; } python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Core/cholmod_sparse.c0000644000076500000240000004277213524616144026543 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Core/cholmod_sparse ================================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Core Module. Copyright (C) 2005-2006, * Univ. of Florida. Author: Timothy A. Davis * The CHOLMOD/Core Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Core utility routines for the cholmod_sparse object: * * A sparse matrix is held in compressed column form. In the basic type * ("packed", which corresponds to a MATLAB sparse matrix), an n-by-n matrix * with nz entries is held in three arrays: p of size n+1, i of size nz, and x * of size nz. Row indices of column j are held in i [p [j] ... p [j+1]-1] and * in the same locations in x. There may be no duplicate entries in a column. * Row indices in each column may be sorted or unsorted (CHOLMOD keeps track). * * Primary routines: * ----------------- * cholmod_allocate_sparse allocate a sparse matrix * cholmod_free_sparse free a sparse matrix * * Secondary routines: * ------------------- * cholmod_reallocate_sparse change the size (# entries) of sparse matrix * cholmod_nnz number of nonzeros in a sparse matrix * cholmod_speye sparse identity matrix * cholmod_spzeros sparse zero matrix * cholmod_copy_sparse create a copy of a sparse matrix * * All xtypes are supported (pattern, real, complex, and zomplex) */ #include "cholmod_internal.h" #include "cholmod_core.h" /* ========================================================================== */ /* === cholmod_allocate_sparse ============================================== */ /* ========================================================================== */ /* Allocate space for a matrix. A->i and A->x are not initialized. A->p * (and A->nz if A is not packed) are set to zero, so a matrix containing no * entries (all zero) is returned. See also cholmod_spzeros. * * workspace: none */ cholmod_sparse *CHOLMOD(allocate_sparse) ( /* ---- input ---- */ size_t nrow, /* # of rows of A */ size_t ncol, /* # of columns of A */ size_t nzmax, /* max # of nonzeros of A */ int sorted, /* TRUE if columns of A sorted, FALSE otherwise */ int packed, /* TRUE if A will be packed, FALSE otherwise */ int stype, /* stype of A */ int xtype, /* CHOLMOD_PATTERN, _REAL, _COMPLEX, or _ZOMPLEX */ /* --------------- */ cholmod_common *Common ) { cholmod_sparse *A ; Int *Ap, *Anz ; size_t nzmax0 ; Int j ; int ok = TRUE ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; if (stype != 0 && nrow != ncol) { ERROR (CHOLMOD_INVALID, "rectangular matrix with stype != 0 invalid") ; return (NULL) ; } if (xtype < CHOLMOD_PATTERN || xtype > CHOLMOD_ZOMPLEX) { ERROR (CHOLMOD_INVALID, "xtype invalid") ; return (NULL) ; } /* ensure the dimensions do not cause integer overflow */ (void) CHOLMOD(add_size_t) (ncol, 2, &ok) ; if (!ok || nrow > Int_max || ncol > Int_max || nzmax > Int_max) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return (NULL) ; } Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* allocate header */ /* ---------------------------------------------------------------------- */ A = CHOLMOD(malloc) (sizeof (cholmod_sparse), 1, Common) ; if (Common->status < CHOLMOD_OK) { return (NULL) ; /* out of memory */ } PRINT1 (("cholmod_allocate_sparse %d-by-%d nzmax %d sorted %d packed %d" " xtype %d\n", nrow, ncol, nzmax, sorted, packed, xtype)) ; nzmax = MAX (1, nzmax) ; A->nrow = nrow ; A->ncol = ncol ; A->nzmax = nzmax ; A->packed = packed ; /* default is packed (A->nz not present) */ A->stype = stype ; A->itype = ITYPE ; A->xtype = xtype ; A->dtype = DTYPE ; A->nz = NULL ; A->p = NULL ; A->i = NULL ; A->x = NULL ; A->z = NULL ; /* A 1-by-m matrix always has sorted columns */ A->sorted = (nrow <= 1) ? TRUE : sorted ; /* ---------------------------------------------------------------------- */ /* allocate the matrix itself */ /* ---------------------------------------------------------------------- */ /* allocate O(ncol) space */ A->p = CHOLMOD(malloc) (((size_t) ncol)+1, sizeof (Int), Common) ; if (!packed) { A->nz = CHOLMOD(malloc) (ncol, sizeof (Int), Common) ; } /* allocate O(nz) space */ nzmax0 = 0 ; CHOLMOD(realloc_multiple) (nzmax, 1, xtype, &(A->i), NULL, &(A->x), &(A->z), &nzmax0, Common) ; if (Common->status < CHOLMOD_OK) { CHOLMOD(free_sparse) (&A, Common) ; return (NULL) ; /* out of memory */ } /* ---------------------------------------------------------------------- */ /* initialize A->p and A->nz so that A is an empty matrix */ /* ---------------------------------------------------------------------- */ Ap = A->p ; for (j = 0 ; j <= (Int) ncol ; j++) { Ap [j] = 0 ; } if (!packed) { Anz = A->nz ; for (j = 0 ; j < (Int) ncol ; j++) { Anz [j] = 0 ; } } return (A) ; } /* ========================================================================== */ /* === cholmod_free_sparse ================================================== */ /* ========================================================================== */ /* free a sparse matrix * * workspace: none */ int CHOLMOD(free_sparse) ( /* ---- in/out --- */ cholmod_sparse **AHandle, /* matrix to deallocate, NULL on output */ /* --------------- */ cholmod_common *Common ) { Int n, nz ; cholmod_sparse *A ; RETURN_IF_NULL_COMMON (FALSE) ; if (AHandle == NULL) { /* nothing to do */ return (TRUE) ; } A = *AHandle ; if (A == NULL) { /* nothing to do */ return (TRUE) ; } n = A->ncol ; nz = A->nzmax ; A->p = CHOLMOD(free) (n+1, sizeof (Int), A->p, Common) ; A->i = CHOLMOD(free) (nz, sizeof (Int), A->i, Common) ; A->nz = CHOLMOD(free) (n, sizeof (Int), A->nz, Common) ; switch (A->xtype) { case CHOLMOD_REAL: A->x = CHOLMOD(free) (nz, sizeof (double), A->x, Common) ; break ; case CHOLMOD_COMPLEX: A->x = CHOLMOD(free) (nz, 2*sizeof (double), A->x, Common) ; break ; case CHOLMOD_ZOMPLEX: A->x = CHOLMOD(free) (nz, sizeof (double), A->x, Common) ; A->z = CHOLMOD(free) (nz, sizeof (double), A->z, Common) ; break ; } *AHandle = CHOLMOD(free) (1, sizeof (cholmod_sparse), (*AHandle), Common) ; return (TRUE) ; } /* ========================================================================== */ /* === cholmod_reallocate_sparse ============================================ */ /* ========================================================================== */ /* Change the size of A->i, A->x, and A->z, or allocate them if their current * size is zero. A->x and A->z are not modified if A->xtype is CHOLMOD_PATTERN. * A->z is not modified unless A->xtype is CHOLMOD_ZOMPLEX. * * workspace: none */ int CHOLMOD(reallocate_sparse) ( /* ---- input ---- */ size_t nznew, /* new # of entries in A */ /* ---- in/out --- */ cholmod_sparse *A, /* matrix to reallocate */ /* --------------- */ cholmod_common *Common ) { /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (A, FALSE) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; Common->status = CHOLMOD_OK ; PRINT1 (("realloc matrix %d to %d, xtype: %d\n", A->nzmax, nznew, A->xtype)) ; /* ---------------------------------------------------------------------- */ /* resize the matrix */ /* ---------------------------------------------------------------------- */ CHOLMOD(realloc_multiple) (MAX (1,nznew), 1, A->xtype, &(A->i), NULL, &(A->x), &(A->z), &(A->nzmax), Common) ; return (Common->status == CHOLMOD_OK) ; } /* ========================================================================== */ /* === cholmod_speye ======================================================== */ /* ========================================================================== */ /* Return a sparse identity matrix. */ cholmod_sparse *CHOLMOD(speye) ( /* ---- input ---- */ size_t nrow, /* # of rows of A */ size_t ncol, /* # of columns of A */ int xtype, /* CHOLMOD_PATTERN, _REAL, _COMPLEX, or _ZOMPLEX */ /* --------------- */ cholmod_common *Common ) { double *Ax, *Az ; cholmod_sparse *A ; Int *Ap, *Ai ; Int j, n ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* allocate the matrix */ /* ---------------------------------------------------------------------- */ n = MIN (nrow, ncol) ; A = CHOLMOD(allocate_sparse) (nrow, ncol, n, TRUE, TRUE, 0, xtype, Common) ; if (Common->status < CHOLMOD_OK) { return (NULL) ; /* out of memory or inputs invalid */ } /* ---------------------------------------------------------------------- */ /* create the identity matrix */ /* ---------------------------------------------------------------------- */ Ap = A->p ; Ai = A->i ; Ax = A->x ; Az = A->z ; for (j = 0 ; j < n ; j++) { Ap [j] = j ; } for (j = n ; j <= ((Int) ncol) ; j++) { Ap [j] = n ; } for (j = 0 ; j < n ; j++) { Ai [j] = j ; } switch (xtype) { case CHOLMOD_REAL: for (j = 0 ; j < n ; j++) { Ax [j] = 1 ; } break ; case CHOLMOD_COMPLEX: for (j = 0 ; j < n ; j++) { Ax [2*j ] = 1 ; Ax [2*j+1] = 0 ; } break ; case CHOLMOD_ZOMPLEX: for (j = 0 ; j < n ; j++) { Ax [j] = 1 ; } for (j = 0 ; j < n ; j++) { Az [j] = 0 ; } break ; } return (A) ; } /* ========================================================================== */ /* === cholmod_spzeros ====================================================== */ /* ========================================================================== */ /* Return a sparse zero matrix. */ cholmod_sparse *CHOLMOD(spzeros) ( /* ---- input ---- */ size_t nrow, /* # of rows of A */ size_t ncol, /* # of columns of A */ size_t nzmax, /* max # of nonzeros of A */ int xtype, /* CHOLMOD_PATTERN, _REAL, _COMPLEX, or _ZOMPLEX */ /* --------------- */ cholmod_common *Common ) { /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* allocate the matrix */ /* ---------------------------------------------------------------------- */ return (CHOLMOD(allocate_sparse) (nrow, ncol, nzmax, TRUE, TRUE, 0, xtype, Common)) ; } /* ========================================================================== */ /* === cholmod_nnz ========================================================== */ /* ========================================================================== */ /* Return the number of entries in a sparse matrix. * * workspace: none * integer overflow cannot occur, since the matrix is already allocated. */ SuiteSparse_long CHOLMOD(nnz) ( /* ---- input ---- */ cholmod_sparse *A, /* --------------- */ cholmod_common *Common ) { Int *Ap, *Anz ; size_t nz ; Int j, ncol ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (EMPTY) ; RETURN_IF_NULL (A, EMPTY) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, EMPTY) ; Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* return nnz (A) */ /* ---------------------------------------------------------------------- */ ncol = A->ncol ; if (A->packed) { Ap = A->p ; RETURN_IF_NULL (Ap, EMPTY) ; nz = Ap [ncol] ; } else { Anz = A->nz ; RETURN_IF_NULL (Anz, EMPTY) ; nz = 0 ; for (j = 0 ; j < ncol ; j++) { nz += MAX (0, Anz [j]) ; } } return (nz) ; } /* ========================================================================== */ /* === cholmod_copy_sparse ================================================== */ /* ========================================================================== */ /* C = A. Create an exact copy of a sparse matrix, with one exception. * Entries in unused space are not copied (they might not be initialized, * and copying them would cause program checkers such as purify and * valgrind to complain). The xtype of the resulting matrix C is the same as * the xtype of the input matrix A. * * See also Core/cholmod_copy, which copies a matrix with possible changes * in stype, presence of diagonal entries, pattern vs. numerical values, * real and/or imaginary parts, and so on. */ cholmod_sparse *CHOLMOD(copy_sparse) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to copy */ /* --------------- */ cholmod_common *Common ) { double *Ax, *Cx, *Az, *Cz ; Int *Ap, *Ai, *Anz, *Cp, *Ci, *Cnz ; cholmod_sparse *C ; Int p, pend, j, ncol, packed, nzmax, nz, xtype ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; RETURN_IF_NULL (A, NULL) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, NULL) ; if (A->stype != 0 && A->nrow != A->ncol) { ERROR (CHOLMOD_INVALID, "rectangular matrix with stype != 0 invalid") ; return (NULL) ; } Common->status = CHOLMOD_OK ; ASSERT (CHOLMOD(dump_sparse) (A, "A original", Common) >= 0) ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ ncol = A->ncol ; nzmax = A->nzmax ; packed = A->packed ; Ap = A->p ; Ai = A->i ; Ax = A->x ; Az = A->z ; Anz = A->nz ; xtype = A->xtype ; /* ---------------------------------------------------------------------- */ /* allocate the copy */ /* ---------------------------------------------------------------------- */ C = CHOLMOD(allocate_sparse) (A->nrow, A->ncol, A->nzmax, A->sorted, A->packed, A->stype, A->xtype, Common) ; if (Common->status < CHOLMOD_OK) { return (NULL) ; /* out of memory */ } Cp = C->p ; Ci = C->i ; Cx = C->x ; Cz = C->z ; Cnz = C->nz ; /* ---------------------------------------------------------------------- */ /* copy the matrix */ /* ---------------------------------------------------------------------- */ for (j = 0 ; j <= ncol ; j++) { Cp [j] = Ap [j] ; } if (packed) { nz = Ap [ncol] ; for (p = 0 ; p < nz ; p++) { Ci [p] = Ai [p] ; } switch (xtype) { case CHOLMOD_REAL: for (p = 0 ; p < nz ; p++) { Cx [p] = Ax [p] ; } break ; case CHOLMOD_COMPLEX: for (p = 0 ; p < 2*nz ; p++) { Cx [p] = Ax [p] ; } break ; case CHOLMOD_ZOMPLEX: for (p = 0 ; p < nz ; p++) { Cx [p] = Ax [p] ; Cz [p] = Az [p] ; } break ; } } else { for (j = 0 ; j < ncol ; j++) { Cnz [j] = Anz [j] ; } switch (xtype) { case CHOLMOD_PATTERN: for (j = 0 ; j < ncol ; j++) { p = Ap [j] ; pend = p + Anz [j] ; for ( ; p < pend ; p++) { Ci [p] = Ai [p] ; } } break ; case CHOLMOD_REAL: for (j = 0 ; j < ncol ; j++) { p = Ap [j] ; pend = p + Anz [j] ; for ( ; p < pend ; p++) { Ci [p] = Ai [p] ; Cx [p] = Ax [p] ; } } break ; case CHOLMOD_COMPLEX: for (j = 0 ; j < ncol ; j++) { p = Ap [j] ; pend = p + Anz [j] ; for ( ; p < pend ; p++) { Ci [p] = Ai [p] ; Cx [2*p ] = Ax [2*p ] ; Cx [2*p+1] = Ax [2*p+1] ; } } break ; case CHOLMOD_ZOMPLEX: for (j = 0 ; j < ncol ; j++) { p = Ap [j] ; pend = p + Anz [j] ; for ( ; p < pend ; p++) { Ci [p] = Ai [p] ; Cx [p] = Ax [p] ; Cz [p] = Az [p] ; } } break ; } } /* ---------------------------------------------------------------------- */ /* return the result */ /* ---------------------------------------------------------------------- */ ASSERT (CHOLMOD(dump_sparse) (C, "C copy", Common) >= 0) ; return (C) ; } python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Core/cholmod_copy.c0000644000076500000240000002731513524616144026214 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Core/cholmod_copy ==================================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Core Module. Copyright (C) 2005-2006, * Univ. of Florida. Author: Timothy A. Davis * The CHOLMOD/Core Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* C = A, which allocates C and copies A into C, with possible change of * stype. The diagonal can optionally be removed. The numerical entries * can optionally be copied. This routine differs from cholmod_copy_sparse, * which makes an exact copy of a sparse matrix. * * A can be of any type (packed/unpacked, upper/lower/unsymmetric). C is * packed and can be of any stype (upper/lower/unsymmetric), except that if * A is rectangular C can only be unsymmetric. If the stype of A and C * differ, then the appropriate conversion is made. * * Symmetry of A (A->stype): * <0: lower: assume A is symmetric with just tril(A); the rest of A is ignored * 0 unsym: assume A is unsymmetric; consider all entries in A * >0 upper: assume A is symmetric with just triu(A); the rest of A is ignored * * Symmetry of C (stype parameter): * <0 lower: return just tril(C) * 0 unsym: return all of C * >0 upper: return just triu(C) * * In MATLAB: Using cholmod_copy: * ---------- ---------------------------- * C = A ; A unsymmetric, C unsymmetric * C = tril (A) ; A unsymmetric, C lower * C = triu (A) ; A unsymmetric, C upper * U = triu (A) ; L = tril (U',-1) ; C = L+U ; A upper, C unsymmetric * C = triu (A)' ; A upper, C lower * C = triu (A) ; A upper, C upper * L = tril (A) ; U = triu (L',1) ; C = L+U ; A lower, C unsymmetric * C = tril (A) ; A lower, C lower * C = tril (A)' ; A lower, C upper * * workspace: Iwork (max (nrow,ncol)) * * A can have an xtype of pattern or real. Complex and zomplex cases only * supported when mode <= 0 (in which case the numerical values are ignored). */ #include "cholmod_internal.h" #include "cholmod_core.h" /* ========================================================================== */ /* === copy_sym_to_unsym ==================================================== */ /* ========================================================================== */ /* Construct an unsymmetric copy of a symmetric sparse matrix. This does the * work for as C = cholmod_copy (A, 0, mode, Common) when A is symmetric. * In this case, extra space can be added to C. */ static cholmod_sparse *copy_sym_to_unsym ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to copy */ int mode, /* >0: numerical, 0: pattern, <0: pattern (no diag) * -2: pattern only, no diagonal, add 50% + n extra * space to C */ /* --------------- */ cholmod_common *Common ) { double aij ; double *Ax, *Cx ; Int *Ap, *Ai, *Anz, *Cp, *Ci, *Wj, *Iwork ; cholmod_sparse *C ; Int nrow, ncol, nz, packed, j, p, pend, i, pc, up, lo, values, diag, astype, extra ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ nrow = A->nrow ; ncol = A->ncol ; Ap = A->p ; Anz = A->nz ; Ai = A->i ; Ax = A->x ; packed = A->packed ; values = (mode > 0) && (A->xtype != CHOLMOD_PATTERN) ; diag = (mode >= 0) ; astype = SIGN (A->stype) ; up = (astype > 0) ; lo = (astype < 0) ; ASSERT (astype != 0) ; /* ---------------------------------------------------------------------- */ /* create an unsymmetric copy of a symmetric matrix */ /* ---------------------------------------------------------------------- */ Iwork = Common->Iwork ; Wj = Iwork ; /* size ncol (i/i/l) */ /* In MATLAB notation, for converting a symmetric/upper matrix: * U = triu (A) ; * L = tril (U',-1) ; * C = L + U ; * * For converting a symmetric/lower matrix to unsymmetric: * L = tril (A) ; * U = triu (L',1) ; * C = L + U ; */ ASSERT (up || lo) ; PRINT1 (("copy: convert symmetric to unsym\n")) ; /* count the number of entries in each column of C */ for (j = 0 ; j < ncol ; j++) { Wj [j] = 0 ; } for (j = 0 ; j < ncol ; j++) { p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { i = Ai [p] ; if (i == j) { /* the diagonal entry A(i,i) will appear just once * (unless it is excluded with mode < 0) */ if (diag) { Wj [j]++ ; } } else if ((up && i < j) || (lo && i > j)) { /* upper case: A(i,j) is in the strictly upper part; * A(j,i) will be added to the strictly lower part of C. * lower case is the opposite. */ Wj [j]++ ; Wj [i]++ ; } } } nz = 0 ; for (j = 0 ; j < ncol ; j++) { nz += Wj [j] ; } extra = (mode == -2) ? (nz/2 + ncol) : 0 ; /* allocate C. C is sorted if and only if A is sorted */ C = CHOLMOD(allocate_sparse) (nrow, ncol, nz + extra, A->sorted, TRUE, 0, values ? A->xtype : CHOLMOD_PATTERN, Common) ; if (Common->status < CHOLMOD_OK) { return (NULL) ; } Cp = C->p ; Ci = C->i ; Cx = C->x ; /* construct the column pointers for C */ p = 0 ; for (j = 0 ; j < ncol ; j++) { Cp [j] = p ; p += Wj [j] ; } Cp [ncol] = p ; for (j = 0 ; j < ncol ; j++) { Wj [j] = Cp [j] ; } /* construct C */ if (values) { /* pattern and values */ ASSERT (diag) ; for (j = 0 ; j < ncol ; j++) { p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { i = Ai [p] ; aij = Ax [p] ; if (i == j) { /* add diagonal entry A(i,i) to column i */ pc = Wj [i]++ ; Ci [pc] = i ; Cx [pc] = aij ; } else if ((up && i < j) || (lo && i > j)) { /* add A(i,j) to column j */ pc = Wj [j]++ ; Ci [pc] = i ; Cx [pc] = aij ; /* add A(j,i) to column i */ pc = Wj [i]++ ; Ci [pc] = j ; Cx [pc] = aij ; } } } } else { /* pattern only, possibly excluding the diagonal */ for (j = 0 ; j < ncol ; j++) { p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { i = Ai [p] ; if (i == j) { /* add diagonal entry A(i,i) to column i * (unless it is excluded with mode < 0) */ if (diag) { Ci [Wj [i]++] = i ; } } else if ((up && i < j) || (lo && i > j)) { /* add A(i,j) to column j */ Ci [Wj [j]++] = i ; /* add A(j,i) to column i */ Ci [Wj [i]++] = j ; } } } } /* ---------------------------------------------------------------------- */ /* return the result */ /* ---------------------------------------------------------------------- */ DEBUG (i = CHOLMOD(dump_sparse) (C, "copy_sym_to_unsym", Common)) ; PRINT1 (("mode %d nnzdiag "ID"\n", mode, i)) ; ASSERT (IMPLIES (mode < 0, i == 0)) ; return (C) ; } /* ========================================================================== */ /* === cholmod_copy ========================================================= */ /* ========================================================================== */ cholmod_sparse *CHOLMOD(copy) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to copy */ int stype, /* requested stype of C */ int mode, /* >0: numerical, 0: pattern, <0: pattern (no diag) */ /* --------------- */ cholmod_common *Common ) { cholmod_sparse *C ; Int nrow, ncol, up, lo, values, diag, astype ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; RETURN_IF_NULL (A, NULL) ; values = (mode > 0) && (A->xtype != CHOLMOD_PATTERN) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, values ? CHOLMOD_REAL : CHOLMOD_ZOMPLEX, NULL) ; nrow = A->nrow ; ncol = A->ncol ; if ((stype || A->stype) && nrow != ncol) { /* inputs invalid */ ERROR (CHOLMOD_INVALID, "matrix invalid") ; return (NULL) ; } Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ CHOLMOD(allocate_work) (0, MAX (nrow,ncol), 0, Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ return (NULL) ; } /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ diag = (mode >= 0) ; astype = SIGN (A->stype) ; stype = SIGN (stype) ; up = (astype > 0) ; lo = (astype < 0) ; /* ---------------------------------------------------------------------- */ /* copy the matrix */ /* ---------------------------------------------------------------------- */ if (astype == stype) { /* ------------------------------------------------------------------ */ /* symmetry of A and C are the same */ /* ------------------------------------------------------------------ */ /* copy A into C, keeping the same symmetry. If A is symmetric * entries in the ignored part of A are not copied into C */ C = CHOLMOD(band) (A, -nrow, ncol, mode, Common) ; } else if (!astype) { /* ------------------------------------------------------------------ */ /* convert unsymmetric matrix A into a symmetric matrix C */ /* ------------------------------------------------------------------ */ if (stype > 0) { /* C = triu (A) */ C = CHOLMOD(band) (A, 0, ncol, mode, Common) ; } else { /* C = tril (A) */ C = CHOLMOD(band) (A, -nrow, 0, mode, Common) ; } if (Common->status < CHOLMOD_OK) { /* out of memory */ return (NULL) ; } C->stype = stype ; } else if (astype == -stype) { /* ------------------------------------------------------------------ */ /* transpose a symmetric matrix */ /* ------------------------------------------------------------------ */ /* converting upper to lower or lower to upper */ /* workspace: Iwork (nrow) */ C = CHOLMOD(transpose) (A, values, Common) ; if (!diag) { /* remove diagonal, if requested */ CHOLMOD(band_inplace) (-nrow, ncol, -1, C, Common) ; } } else { /* ------------------------------------------------------------------ */ /* create an unsymmetric copy of a symmetric matrix */ /* ------------------------------------------------------------------ */ C = copy_sym_to_unsym (A, mode, Common) ; } /* ---------------------------------------------------------------------- */ /* return if error */ /* ---------------------------------------------------------------------- */ if (Common->status < CHOLMOD_OK) { /* out of memory */ return (NULL) ; } /* ---------------------------------------------------------------------- */ /* return the result */ /* ---------------------------------------------------------------------- */ DEBUG (diag = CHOLMOD(dump_sparse) (C, "copy", Common)) ; PRINT1 (("mode %d nnzdiag "ID"\n", mode, diag)) ; ASSERT (IMPLIES (mode < 0, diag == 0)) ; return (C) ; } python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Core/cholmod_memory.c0000644000076500000240000004301113524616144026541 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Core/cholmod_memory ================================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Core Module. Copyright (C) 2005-2013, * Univ. of Florida. Author: Timothy A. Davis * The CHOLMOD/Core Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Core memory management routines: * * Primary routines: * ----------------- * cholmod_malloc malloc wrapper * cholmod_free free wrapper * * Secondary routines: * ------------------- * cholmod_calloc calloc wrapper * cholmod_realloc realloc wrapper * cholmod_realloc_multiple realloc wrapper for multiple objects * * The user may make use of these, just like malloc and free. You can even * malloc an object and safely free it with cholmod_free, and visa versa * (except that the memory usage statistics will be corrupted). These routines * do differ from malloc and free. If cholmod_free is given a NULL pointer, * for example, it does nothing (unlike the ANSI free). cholmod_realloc does * not return NULL if given a non-NULL pointer and a nonzero size, even if it * fails (it sets an error code in Common->status instead). * * CHOLMOD keeps track of the amount of memory it has allocated, and so the * cholmod_free routine includes as a parameter the size of the object being * freed. This is only used for memory usage statistics, which are very useful * in finding memory leaks in your program. If you, the user of CHOLMOD, pass * the wrong size, the only consequence is that the memory usage statistics * will be invalid. This will causes assertions to fail if CHOLMOD is * compiled with debugging enabled, but otherwise it will cause no errors. * * The cholmod_free_* routines for each CHOLMOD object keep track of the size * of the blocks they free, so they do not require you to pass their sizes * as a parameter. * * If a block of size zero is requested, these routines allocate a block of * size one instead. */ #include "cholmod_internal.h" #include "cholmod_core.h" /* ========================================================================== */ /* === cholmod_add_size_t =================================================== */ /* ========================================================================== */ /* Safely compute a+b, and check for integer overflow. If overflow occurs, * return 0 and set OK to FALSE. Also return 0 if OK is FALSE on input. */ size_t CHOLMOD(add_size_t) (size_t a, size_t b, int *ok) { size_t s = a + b ; (*ok) = (*ok) && (s >= a) ; return ((*ok) ? s : 0) ; } /* ========================================================================== */ /* === cholmod_mult_size_t ================================================== */ /* ========================================================================== */ /* Safely compute a*k, where k should be small, and check for integer overflow. * If overflow occurs, return 0 and set OK to FALSE. Also return 0 if OK is * FALSE on input. */ size_t CHOLMOD(mult_size_t) (size_t a, size_t k, int *ok) { size_t p = 0, s ; while (*ok) { if (k % 2) { p = p + a ; (*ok) = (*ok) && (p >= a) ; } k = k / 2 ; if (!k) return (p) ; s = a + a ; (*ok) = (*ok) && (s >= a) ; a = s ; } return (0) ; } /* ========================================================================== */ /* === cholmod_malloc ======================================================= */ /* ========================================================================== */ /* Wrapper around malloc routine. Allocates space of size MAX(1,n)*size, where * size is normally a sizeof (...). * * This routine, cholmod_calloc, and cholmod_realloc do not set Common->status * to CHOLMOD_OK on success, so that a sequence of cholmod_malloc's, _calloc's, * or _realloc's can be used. If any of them fails, the Common->status will * hold the most recent error status. * * Usage, for a pointer to int: * * p = cholmod_malloc (n, sizeof (int), Common) * * Uses a pointer to the malloc routine (or its equivalent) defined in Common. */ void *CHOLMOD(malloc) /* returns pointer to the newly malloc'd block */ ( /* ---- input ---- */ size_t n, /* number of items */ size_t size, /* size of each item */ /* --------------- */ cholmod_common *Common ) { void *p ; size_t s ; int ok = TRUE ; RETURN_IF_NULL_COMMON (NULL) ; if (size == 0) { ERROR (CHOLMOD_INVALID, "sizeof(item) must be > 0") ; p = NULL ; } else if (n >= (Size_max / size) || n >= Int_max) { /* object is too big to allocate without causing integer overflow */ ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; p = NULL ; } else { /* call malloc, or its equivalent */ s = CHOLMOD(mult_size_t) (MAX (1,n), size, &ok) ; p = ok ? ((Common->malloc_memory) (s)) : NULL ; if (p == NULL) { /* failure: out of memory */ ERROR (CHOLMOD_OUT_OF_MEMORY, "out of memory") ; } else { /* success: increment the count of objects allocated */ Common->malloc_count++ ; Common->memory_inuse += (n * size) ; Common->memory_usage = MAX (Common->memory_usage, Common->memory_inuse) ; PRINTM (("cholmod_malloc %p %g cnt: %g inuse %g\n", p, (double) n*size, (double) Common->malloc_count, (double) Common->memory_inuse)) ; } } return (p) ; } /* ========================================================================== */ /* === cholmod_free ========================================================= */ /* ========================================================================== */ /* Wrapper around free routine. Returns NULL, which can be assigned to the * pointer being freed, as in: * * p = cholmod_free (n, sizeof (int), p, Common) ; * * In CHOLMOD, the syntax: * * cholmod_free (n, sizeof (int), p, Common) ; * * is used if p is a local pointer and the routine is returning shortly. * Uses a pointer to the free routine (or its equivalent) defined in Common. * Nothing is freed if the pointer is NULL. */ void *CHOLMOD(free) /* always returns NULL */ ( /* ---- input ---- */ size_t n, /* number of items */ size_t size, /* size of each item */ /* ---- in/out --- */ void *p, /* block of memory to free */ /* --------------- */ cholmod_common *Common ) { RETURN_IF_NULL_COMMON (NULL) ; if (p != NULL) { /* only free the object if the pointer is not NULL */ /* call free, or its equivalent */ (Common->free_memory) (p) ; Common->malloc_count-- ; Common->memory_inuse -= (n * size) ; PRINTM (("cholmod_free %p %g cnt: %g inuse %g\n", p, (double) n*size, (double) Common->malloc_count, (double) Common->memory_inuse)) ; /* This assertion will fail if the user calls cholmod_malloc and * cholmod_free with mismatched memory sizes. It shouldn't fail * otherwise. */ ASSERT (IMPLIES (Common->malloc_count == 0, Common->memory_inuse == 0)); } /* return NULL, and the caller should assign this to p. This avoids * freeing the same pointer twice. */ return (NULL) ; } /* ========================================================================== */ /* === cholmod_calloc ======================================================= */ /* ========================================================================== */ /* Wrapper around calloc routine. * * Uses a pointer to the calloc routine (or its equivalent) defined in Common. * This routine is identical to malloc, except that it zeros the newly allocated * block to zero. */ void *CHOLMOD(calloc) /* returns pointer to the newly calloc'd block */ ( /* ---- input ---- */ size_t n, /* number of items */ size_t size, /* size of each item */ /* --------------- */ cholmod_common *Common ) { void *p ; RETURN_IF_NULL_COMMON (NULL) ; if (size == 0) { ERROR (CHOLMOD_INVALID, "sizeof(item) must be > 0") ; p = NULL ; } else if (n >= (Size_max / size) || n >= Int_max) { /* object is too big to allocate without causing integer overflow */ ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; p = NULL ; } else { /* call calloc, or its equivalent */ p = (Common->calloc_memory) (MAX (1,n), size) ; if (p == NULL) { /* failure: out of memory */ ERROR (CHOLMOD_OUT_OF_MEMORY, "out of memory") ; } else { /* success: increment the count of objects allocated */ Common->malloc_count++ ; Common->memory_inuse += (n * size) ; Common->memory_usage = MAX (Common->memory_usage, Common->memory_inuse) ; PRINTM (("cholmod_malloc %p %g cnt: %g inuse %g\n", p, (double) n*size, (double) Common->malloc_count, (double) Common->memory_inuse)) ; } } return (p) ; } /* ========================================================================== */ /* === cholmod_realloc ====================================================== */ /* ========================================================================== */ /* Wrapper around realloc routine. Given a pointer p to a block of size * (*n)*size memory, it changes the size of the block pointed to by p to be * MAX(1,nnew)*size in size. It may return a pointer different than p. This * should be used as (for a pointer to int): * * p = cholmod_realloc (nnew, sizeof (int), p, *n, Common) ; * * If p is NULL, this is the same as p = cholmod_malloc (...). * A size of nnew=0 is treated as nnew=1. * * If the realloc fails, p is returned unchanged and Common->status is set * to CHOLMOD_OUT_OF_MEMORY. If successful, Common->status is not modified, * and p is returned (possibly changed) and pointing to a large block of memory. * * Uses a pointer to the realloc routine (or its equivalent) defined in Common. */ void *CHOLMOD(realloc) /* returns pointer to reallocated block */ ( /* ---- input ---- */ size_t nnew, /* requested # of items in reallocated block */ size_t size, /* size of each item */ /* ---- in/out --- */ void *p, /* block of memory to realloc */ size_t *n, /* current size on input, nnew on output if successful*/ /* --------------- */ cholmod_common *Common ) { size_t nold = (*n) ; void *pnew ; size_t s ; int ok = TRUE ; RETURN_IF_NULL_COMMON (NULL) ; if (size == 0) { ERROR (CHOLMOD_INVALID, "sizeof(item) must be > 0") ; p = NULL ; } else if (p == NULL) { /* A fresh object is being allocated. */ PRINT1 (("realloc fresh: %d %d\n", nnew, size)) ; p = CHOLMOD(malloc) (nnew, size, Common) ; *n = (p == NULL) ? 0 : nnew ; } else if (nold == nnew) { /* Nothing to do. Do not change p or n. */ PRINT1 (("realloc nothing: %d %d\n", nnew, size)) ; } else if (nnew >= (Size_max / size) || nnew >= Int_max) { /* failure: nnew is too big. Do not change p or n. */ ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; } else { /* The object exists, and is changing to some other nonzero size. */ /* call realloc, or its equivalent */ PRINT1 (("realloc : %d to %d, %d\n", nold, nnew, size)) ; pnew = NULL ; s = CHOLMOD(mult_size_t) (MAX (1,nnew), size, &ok) ; pnew = ok ? ((Common->realloc_memory) (p, s)) : NULL ; if (pnew == NULL) { /* Do not change p, since it still points to allocated memory */ if (nnew <= nold) { /* The attempt to reduce the size of the block from n to * nnew has failed. The current block is not modified, so * pretend to succeed, but do not change p. Do change * CHOLMOD's notion of the size of the block, however. */ *n = nnew ; PRINTM (("nnew <= nold failed, pretend to succeed\n")) ; PRINTM (("cholmod_free %p %g cnt: %g inuse %g\n" "cholmod_malloc %p %g cnt: %g inuse %g\n", p, (double) nold*size, (double) Common->malloc_count-1, (double) (Common->memory_inuse - nold*size), p, (double) nnew*size, (double) Common->malloc_count, (double) (Common->memory_inuse + (nnew-nold)*size))) ; Common->memory_inuse += ((nnew-nold) * size) ; } else { /* Increasing the size of the block has failed. * Do not change n. */ ERROR (CHOLMOD_OUT_OF_MEMORY, "out of memory") ; } } else { /* success: return revised p and change the size of the block */ PRINTM (("cholmod_free %p %g cnt: %g inuse %g\n" "cholmod_malloc %p %g cnt: %g inuse %g\n", p, (double) nold*size, (double) Common->malloc_count-1, (double) (Common->memory_inuse - nold*size), pnew, (double) nnew*size, (double) Common->malloc_count, (double) (Common->memory_inuse + (nnew-nold)*size))) ; p = pnew ; *n = nnew ; Common->memory_inuse += ((nnew-nold) * size) ; } Common->memory_usage = MAX (Common->memory_usage, Common->memory_inuse); } return (p) ; } /* ========================================================================== */ /* === cholmod_realloc_multiple ============================================= */ /* ========================================================================== */ /* reallocate multiple blocks of memory, all of the same size (up to two integer * and two real blocks). Either reallocations all succeed, or all are returned * in the original size (they are freed if the original size is zero). The nnew * blocks are of size 1 or more. */ int CHOLMOD(realloc_multiple) ( /* ---- input ---- */ size_t nnew, /* requested # of items in reallocated blocks */ int nint, /* number of int/SuiteSparse_long blocks */ int xtype, /* CHOLMOD_PATTERN, _REAL, _COMPLEX, or _ZOMPLEX */ /* ---- in/out --- */ void **Iblock, /* int or SuiteSparse_long block */ void **Jblock, /* int or SuiteSparse_long block */ void **Xblock, /* complex or double block */ void **Zblock, /* zomplex case only: double block */ size_t *nold_p, /* current size of the I,J,X,Z blocks on input, * nnew on output if successful */ /* --------------- */ cholmod_common *Common ) { double *xx, *zz ; size_t i, j, x, z, nold ; RETURN_IF_NULL_COMMON (FALSE) ; if (xtype < CHOLMOD_PATTERN || xtype > CHOLMOD_ZOMPLEX) { ERROR (CHOLMOD_INVALID, "invalid xtype") ; return (FALSE) ; } nold = *nold_p ; if (nint < 1 && xtype == CHOLMOD_PATTERN) { /* nothing to do */ return (TRUE) ; } i = nold ; j = nold ; x = nold ; z = nold ; if (nint > 0) { *Iblock = CHOLMOD(realloc) (nnew, sizeof (Int), *Iblock, &i, Common) ; } if (nint > 1) { *Jblock = CHOLMOD(realloc) (nnew, sizeof (Int), *Jblock, &j, Common) ; } switch (xtype) { case CHOLMOD_REAL: *Xblock = CHOLMOD(realloc) (nnew, sizeof (double), *Xblock, &x, Common) ; break ; case CHOLMOD_COMPLEX: *Xblock = CHOLMOD(realloc) (nnew, 2*sizeof (double), *Xblock, &x, Common) ; break ; case CHOLMOD_ZOMPLEX: *Xblock = CHOLMOD(realloc) (nnew, sizeof (double), *Xblock, &x, Common) ; *Zblock = CHOLMOD(realloc) (nnew, sizeof (double), *Zblock, &z, Common) ; break ; } if (Common->status < CHOLMOD_OK) { /* one or more realloc's failed. Resize all back down to nold. */ if (nold == 0) { if (nint > 0) { *Iblock = CHOLMOD(free) (i, sizeof (Int), *Iblock, Common) ; } if (nint > 1) { *Jblock = CHOLMOD(free) (j, sizeof (Int), *Jblock, Common) ; } switch (xtype) { case CHOLMOD_REAL: *Xblock = CHOLMOD(free) (x, sizeof (double), *Xblock, Common) ; break ; case CHOLMOD_COMPLEX: *Xblock = CHOLMOD(free) (x, 2*sizeof (double), *Xblock, Common) ; break ; case CHOLMOD_ZOMPLEX: *Xblock = CHOLMOD(free) (x, sizeof (double), *Xblock, Common) ; *Zblock = CHOLMOD(free) (x, sizeof (double), *Zblock, Common) ; break ; } } else { if (nint > 0) { *Iblock = CHOLMOD(realloc) (nold, sizeof (Int), *Iblock, &i, Common) ; } if (nint > 1) { *Jblock = CHOLMOD(realloc) (nold, sizeof (Int), *Jblock, &j, Common) ; } switch (xtype) { case CHOLMOD_REAL: *Xblock = CHOLMOD(realloc) (nold, sizeof (double), *Xblock, &x, Common) ; break ; case CHOLMOD_COMPLEX: *Xblock = CHOLMOD(realloc) (nold, 2*sizeof (double), *Xblock, &x, Common) ; break ; case CHOLMOD_ZOMPLEX: *Xblock = CHOLMOD(realloc) (nold, sizeof (double), *Xblock, &x, Common) ; *Zblock = CHOLMOD(realloc) (nold, sizeof (double), *Zblock, &z, Common) ; break ; } } return (FALSE) ; } if (nold == 0) { /* New space was allocated. Clear the first entry so that valgrind * doesn't complain about its access in change_complexity * (Core/cholmod_complex.c). */ xx = *Xblock ; zz = *Zblock ; switch (xtype) { case CHOLMOD_REAL: xx [0] = 0 ; break ; case CHOLMOD_COMPLEX: xx [0] = 0 ; xx [1] = 0 ; break ; case CHOLMOD_ZOMPLEX: xx [0] = 0 ; zz [0] = 0 ; break ; } } /* all realloc's succeeded, change size to reflect realloc'ed size. */ *nold_p = nnew ; return (TRUE) ; } python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Core/cholmod_triplet.c0000644000076500000240000005605113524616144026724 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Core/cholmod_triplet ================================================= */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Core Module. Copyright (C) 2005-2006, * Univ. of Florida. Author: Timothy A. Davis * The CHOLMOD/Core Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Core utility routines for the cholmod_triplet object: * * A sparse matrix held in triplet form is the simplest one for a user to * create. It consists of a list of nz entries in arbitrary order, held in * three arrays: i, j, and x, each of length nk. The kth entry is in row i[k], * column j[k], with value x[k]. There may be duplicate values; if A(i,j) * appears more than once, its value is the sum of the entries with those row * and column indices. * * Primary routines: * ----------------- * cholmod_allocate_triplet allocate a triplet matrix * cholmod_free_triplet free a triplet matrix * * Secondary routines: * ------------------- * cholmod_reallocate_triplet reallocate a triplet matrix * cholmod_sparse_to_triplet create a triplet matrix copy of a sparse matrix * cholmod_triplet_to_sparse create a sparse matrix copy of a triplet matrix * cholmod_copy_triplet create a copy of a triplet matrix * * The relationship between an m-by-n cholmod_sparse matrix A and a * cholmod_triplet matrix (i, j, and x) is identical to how they are used in * the MATLAB "sparse" and "find" functions: * * [i j x] = find (A) * [m n] = size (A) * A = sparse (i,j,x,m,n) * * with the exception that the cholmod_sparse matrix may be "unpacked", may * have either sorted or unsorted columns (depending on the option selected), * and may be symmetric with just the upper or lower triangular part stored. * Likewise, the cholmod_triplet matrix may contain just the entries in the * upper or lower triangular part of a symmetric matrix. * * MATLAB sparse matrices are always "packed", always have sorted columns, * and always store both parts of a symmetric matrix. In some cases, MATLAB * behaves like CHOLMOD by ignoring entries in the upper or lower triangular * part of a matrix that is otherwise assumed to be symmetric (such as the * input to chol). In CHOLMOD, that option is a characteristic of the object. * In MATLAB, that option is based on how a matrix is used as the input to * a function. * * The triplet matrix is provided to give the user a simple way of constructing * a sparse matrix. There are very few operations supported for triplet * matrices. The assumption is that they will be converted to cholmod_sparse * matrix form first. * * Adding two triplet matrices simply involves concatenating the contents of * the three arrays (i, j, and x). To permute a triplet matrix, just replace * the row and column indices with their permuted values. For example, if * P is a permutation vector, then P [k] = j means row/column j is the kth * row/column in C=P*A*P'. In MATLAB notation, C=A(p,p). If Pinv is an array * of size n and T is the triplet form of A, then: * * Ti = T->i ; * Tj = T->j ; * for (k = 0 ; k < n ; k++) Pinv [P [k]] = k ; * for (k = 0 ; k < nz ; k++) Ti [k] = Pinv [Ti [k]] ; * for (k = 0 ; k < nz ; k++) Tj [k] = Pinv [Tj [k]] ; * * overwrites T with the triplet form of C=P*A*P'. The conversion * * C = cholmod_triplet_to_sparse (T, 0, &Common) ; * * will then return the matrix C = P*A*P'. * * Note that T->stype > 0 means that entries in the lower triangular part of * T are transposed into the upper triangular part when T is converted to * sparse matrix (cholmod_sparse) form with cholmod_triplet_to_sparse. The * opposite is true for T->stype < 0. * * Since the triplet matrix T is so simple to generate, it's quite easy * to remove entries that you do not want, prior to converting T to the * cholmod_sparse form. So if you include these entries in T, CHOLMOD * assumes that there must be a reason (such as the one above). Thus, * no entry in a triplet matrix is ever ignored. * * Other operations, such as extacting a submatrix, horizontal and vertical * concatenation, multiply a triplet matrix times a dense matrix, are also * simple. Multiplying two triplet matrices is not trivial; the simplest * method is to convert them to cholmod_sparse matrices first. * * Supports all xtypes (pattern, real, complex, and zomplex). */ #include "cholmod_internal.h" #include "cholmod_core.h" /* ========================================================================== */ /* === TEMPLATE ============================================================= */ /* ========================================================================== */ #define PATTERN #include "t_cholmod_triplet.c" #define REAL #include "t_cholmod_triplet.c" #define COMPLEX #include "t_cholmod_triplet.c" #define ZOMPLEX #include "t_cholmod_triplet.c" /* ========================================================================== */ /* === cholmod_allocate_triplet ============================================= */ /* ========================================================================== */ /* allocate space for a triplet matrix * * workspace: none */ cholmod_triplet *CHOLMOD(allocate_triplet) ( /* ---- input ---- */ size_t nrow, /* # of rows of T */ size_t ncol, /* # of columns of T */ size_t nzmax, /* max # of nonzeros of T */ int stype, /* stype of T */ int xtype, /* CHOLMOD_PATTERN, _REAL, _COMPLEX, or _ZOMPLEX */ /* --------------- */ cholmod_common *Common ) { cholmod_triplet *T ; size_t nzmax0 ; int ok = TRUE ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; if (xtype < CHOLMOD_PATTERN || xtype > CHOLMOD_ZOMPLEX) { ERROR (CHOLMOD_INVALID, "xtype invalid") ; return (NULL) ; } /* ensure the dimensions do not cause integer overflow */ (void) CHOLMOD(add_size_t) (ncol, 2, &ok) ; if (!ok || nrow > Int_max || ncol > Int_max || nzmax > Int_max) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return (NULL) ; } Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* allocate header */ /* ---------------------------------------------------------------------- */ T = CHOLMOD(malloc) (sizeof (cholmod_triplet), 1, Common) ; if (Common->status < CHOLMOD_OK) { return (NULL) ; /* out of memory */ } PRINT1 (("cholmod_allocate_triplet %d-by-%d nzmax %d xtype %d\n", nrow, ncol, nzmax, xtype)) ; nzmax = MAX (1, nzmax) ; T->nrow = nrow ; T->ncol = ncol ; T->nzmax = nzmax ; T->nnz = 0 ; T->stype = stype ; T->itype = ITYPE ; T->xtype = xtype ; T->dtype = DTYPE ; T->j = NULL ; T->i = NULL ; T->x = NULL ; T->z = NULL ; /* ---------------------------------------------------------------------- */ /* allocate the matrix itself */ /* ---------------------------------------------------------------------- */ nzmax0 = 0 ; CHOLMOD(realloc_multiple) (nzmax, 2, xtype, &(T->i), &(T->j), &(T->x), &(T->z), &nzmax0, Common) ; if (Common->status < CHOLMOD_OK) { CHOLMOD(free_triplet) (&T, Common) ; return (NULL) ; /* out of memory */ } return (T) ; } /* ========================================================================== */ /* === cholmod_free_triplet ================================================= */ /* ========================================================================== */ /* free a triplet matrix * * workspace: none */ int CHOLMOD(free_triplet) ( /* ---- in/out --- */ cholmod_triplet **THandle, /* matrix to deallocate, NULL on output */ /* --------------- */ cholmod_common *Common ) { Int nz ; cholmod_triplet *T ; RETURN_IF_NULL_COMMON (FALSE) ; if (THandle == NULL) { /* nothing to do */ return (TRUE) ; } T = *THandle ; if (T == NULL) { /* nothing to do */ return (TRUE) ; } nz = T->nzmax ; T->j = CHOLMOD(free) (nz, sizeof (Int), T->j, Common) ; T->i = CHOLMOD(free) (nz, sizeof (Int), T->i, Common) ; if (T->xtype == CHOLMOD_REAL) { T->x = CHOLMOD(free) (nz, sizeof (double), T->x, Common) ; } else if (T->xtype == CHOLMOD_COMPLEX) { T->x = CHOLMOD(free) (nz, 2*sizeof (double), T->x, Common) ; } else if (T->xtype == CHOLMOD_ZOMPLEX) { T->x = CHOLMOD(free) (nz, sizeof (double), T->x, Common) ; T->z = CHOLMOD(free) (nz, sizeof (double), T->z, Common) ; } *THandle = CHOLMOD(free) (1, sizeof (cholmod_triplet), (*THandle), Common) ; return (TRUE) ; } /* ========================================================================== */ /* === cholmod_reallocate_triplet =========================================== */ /* ========================================================================== */ /* Change the size of T->i, T->j, and T->x, or allocate them if their current * size is zero. T->x is not modified if T->xtype is CHOLMOD_PATTERN. * * workspace: none */ int CHOLMOD(reallocate_triplet) ( /* ---- input ---- */ size_t nznew, /* new # of entries in T */ /* ---- in/out --- */ cholmod_triplet *T, /* triplet matrix to modify */ /* --------------- */ cholmod_common *Common ) { /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (T, FALSE) ; RETURN_IF_XTYPE_INVALID (T, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; Common->status = CHOLMOD_OK ; PRINT1 (("realloc triplet %d to %d, xtype: %d\n", T->nzmax, nznew, T->xtype)) ; /* ---------------------------------------------------------------------- */ /* resize the matrix */ /* ---------------------------------------------------------------------- */ CHOLMOD(realloc_multiple) (MAX (1,nznew), 2, T->xtype, &(T->i), &(T->j), &(T->x), &(T->z), &(T->nzmax), Common) ; return (Common->status == CHOLMOD_OK) ; } /* ========================================================================== */ /* === cholmod_triplet_to_sparse ============================================ */ /* ========================================================================== */ /* Convert a set of triplets into a cholmod_sparse matrix. In MATLAB notation, * for unsymmetric matrices: * * A = sparse (Ti, Tj, Tx, nrow, ncol, nzmax) ; * * For the symmetric upper case: * * A = sparse (min(Ti,Tj), max(Ti,Tj), Tx, nrow, ncol, nzmax) ; * * For the symmetric lower case: * * A = sparse (max(Ti,Tj), min(Ti,Tj), Tx, nrow, ncol, nzmax) ; * * If Tx is NULL, then A->x is not allocated, and only the pattern of A is * computed. A is returned in packed form, and can be of any stype * (upper/lower/unsymmetric). It has enough space to hold the values in T, * or nzmax, whichever is larger. * * workspace: Iwork (max (nrow,ncol)) * allocates a temporary copy of its output matrix. * * The resulting sparse matrix has the same xtype as the input triplet matrix. */ cholmod_sparse *CHOLMOD(triplet_to_sparse) ( /* ---- input ---- */ cholmod_triplet *T, /* matrix to copy */ size_t nzmax, /* allocate at least this much space in output matrix */ /* --------------- */ cholmod_common *Common ) { cholmod_sparse *R, *A = NULL ; Int *Wj, *Rp, *Ri, *Rnz, *Ti, *Tj ; Int i, j, p, k, stype, nrow, ncol, nz, ok ; size_t anz = 0 ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; RETURN_IF_NULL (T, NULL) ; Ti = T->i ; Tj = T->j ; RETURN_IF_NULL (Ti, NULL) ; RETURN_IF_NULL (Tj, NULL) ; RETURN_IF_XTYPE_INVALID (T, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, NULL) ; stype = SIGN (T->stype) ; if (stype && T->nrow != T->ncol) { /* inputs invalid */ ERROR (CHOLMOD_INVALID, "matrix invalid") ; return (NULL) ; } Common->status = CHOLMOD_OK ; DEBUG (CHOLMOD(dump_triplet) (T, "T", Common)) ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ nrow = T->nrow ; ncol = T->ncol ; nz = T->nnz ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ CHOLMOD(allocate_work) (0, MAX (nrow, ncol), 0, Common) ; if (Common->status < CHOLMOD_OK) { return (NULL) ; /* out of memory */ } /* ---------------------------------------------------------------------- */ /* allocate temporary matrix R */ /* ---------------------------------------------------------------------- */ R = CHOLMOD(allocate_sparse) (ncol, nrow, nz, FALSE, FALSE, -stype, T->xtype, Common) ; if (Common->status < CHOLMOD_OK) { return (NULL) ; /* out of memory */ } Rp = R->p ; Ri = R->i ; Rnz = R->nz ; /* ---------------------------------------------------------------------- */ /* count the entries in each row of A (also counting duplicates) */ /* ---------------------------------------------------------------------- */ for (i = 0 ; i < nrow ; i++) { Rnz [i] = 0 ; } if (stype > 0) { for (k = 0 ; k < nz ; k++) { i = Ti [k] ; j = Tj [k] ; if (i < 0 || i >= nrow || j < 0 || j >= ncol) { ERROR (CHOLMOD_INVALID, "index out of range") ; break ; } /* A will be symmetric with just the upper triangular part stored. * Create a matrix R that is lower triangular. Entries in the * upper part of R are transposed to the lower part. */ Rnz [MIN (i,j)]++ ; } } else if (stype < 0) { for (k = 0 ; k < nz ; k++) { i = Ti [k] ; j = Tj [k] ; if (i < 0 || i >= nrow || j < 0 || j >= ncol) { ERROR (CHOLMOD_INVALID, "index out of range") ; break ; } /* A will be symmetric with just the lower triangular part stored. * Create a matrix R that is upper triangular. Entries in the * lower part of R are transposed to the upper part. */ Rnz [MAX (i,j)]++ ; } } else { for (k = 0 ; k < nz ; k++) { i = Ti [k] ; j = Tj [k] ; if (i < 0 || i >= nrow || j < 0 || j >= ncol) { ERROR (CHOLMOD_INVALID, "index out of range") ; break ; } /* constructing an unsymmetric matrix */ Rnz [i]++ ; } } if (Common->status < CHOLMOD_OK) { /* triplet matrix is invalid */ CHOLMOD(free_sparse) (&R, Common) ; return (NULL) ; } /* ---------------------------------------------------------------------- */ /* construct the row pointers */ /* ---------------------------------------------------------------------- */ p = 0 ; for (i = 0 ; i < nrow ; i++) { Rp [i] = p ; p += Rnz [i] ; } Rp [nrow] = p ; /* use Wj (i/l/l) as temporary row pointers */ Wj = Common->Iwork ; /* size MAX (nrow,ncol) FUTURE WORK: (i/l/l) */ for (i = 0 ; i < nrow ; i++) { Wj [i] = Rp [i] ; } /* ---------------------------------------------------------------------- */ /* construct triplet matrix, using template routine */ /* ---------------------------------------------------------------------- */ switch (T->xtype) { case CHOLMOD_PATTERN: anz = p_cholmod_triplet_to_sparse (T, R, Common) ; break ; case CHOLMOD_REAL: anz = r_cholmod_triplet_to_sparse (T, R, Common) ; break ; case CHOLMOD_COMPLEX: anz = c_cholmod_triplet_to_sparse (T, R, Common) ; break ; case CHOLMOD_ZOMPLEX: anz = z_cholmod_triplet_to_sparse (T, R, Common) ; break ; } /* ---------------------------------------------------------------------- */ /* A = R' (array transpose, not complex conjugate transpose) */ /* ---------------------------------------------------------------------- */ /* workspace: Iwork (R->nrow), which is A->ncol */ ASSERT (CHOLMOD(dump_sparse) (R, "R", Common) >= 0) ; A = CHOLMOD(allocate_sparse) (nrow, ncol, MAX (anz, nzmax), TRUE, TRUE, stype, T->xtype, Common) ; if (stype) { ok = CHOLMOD(transpose_sym) (R, 1, NULL, A, Common) ; } else { ok = CHOLMOD(transpose_unsym) (R, 1, NULL, NULL, 0, A, Common) ; } CHOLMOD(free_sparse) (&R, Common) ; if (Common->status < CHOLMOD_OK) { CHOLMOD(free_sparse) (&A, Common) ; } /* ---------------------------------------------------------------------- */ /* return result */ /* ---------------------------------------------------------------------- */ ASSERT (CHOLMOD(dump_sparse) (A, "A = triplet(T) result", Common) >= 0) ; return (A) ; } /* ========================================================================== */ /* === cholmod_sparse_to_triplet ============================================ */ /* ========================================================================== */ /* Converts a sparse column-oriented matrix to triplet form. * The resulting triplet matrix has the same xtype as the sparse matrix. * * workspace: none */ cholmod_triplet *CHOLMOD(sparse_to_triplet) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to copy */ /* --------------- */ cholmod_common *Common ) { double *Ax, *Az, *Tx, *Tz ; Int *Ap, *Ai, *Ti, *Tj, *Anz ; cholmod_triplet *T ; Int i, xtype, p, pend, k, j, nrow, ncol, nz, stype, packed, up, lo, both ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; RETURN_IF_NULL (A, NULL) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, NULL) ; stype = SIGN (A->stype) ; nrow = A->nrow ; ncol = A->ncol ; if (stype && nrow != ncol) { /* inputs invalid */ ERROR (CHOLMOD_INVALID, "matrix invalid") ; return (NULL) ; } Ax = A->x ; Az = A->z ; xtype = A->xtype ; Common->status = CHOLMOD_OK ; ASSERT (CHOLMOD(dump_sparse) (A, "A", Common) >= 0) ; /* ---------------------------------------------------------------------- */ /* allocate triplet matrix */ /* ---------------------------------------------------------------------- */ nz = CHOLMOD(nnz) (A, Common) ; T = CHOLMOD(allocate_triplet) (nrow, ncol, nz, A->stype, A->xtype, Common) ; if (Common->status < CHOLMOD_OK) { return (NULL) ; /* out of memory */ } /* ---------------------------------------------------------------------- */ /* convert to a sparse matrix */ /* ---------------------------------------------------------------------- */ Ap = A->p ; Ai = A->i ; Anz = A->nz ; packed = A->packed ; Ti = T->i ; Tj = T->j ; Tx = T->x ; Tz = T->z ; T->stype = A->stype ; both = (A->stype == 0) ; up = (A->stype > 0) ; lo = (A->stype < 0) ; k = 0 ; for (j = 0 ; j < ncol ; j++) { p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { i = Ai [p] ; if (both || (up && i <= j) || (lo && i >= j)) { Ti [k] = Ai [p] ; Tj [k] = j ; if (xtype == CHOLMOD_REAL) { Tx [k] = Ax [p] ; } else if (xtype == CHOLMOD_COMPLEX) { Tx [2*k ] = Ax [2*p ] ; Tx [2*k+1] = Ax [2*p+1] ; } else if (xtype == CHOLMOD_ZOMPLEX) { Tx [k] = Ax [p] ; Tz [k] = Az [p] ; } k++ ; ASSERT (k <= nz) ; } } } T->nnz = k ; /* ---------------------------------------------------------------------- */ /* return result */ /* ---------------------------------------------------------------------- */ ASSERT (CHOLMOD(dump_triplet) (T, "T", Common)) ; return (T) ; } /* ========================================================================== */ /* === cholmod_copy_triplet ================================================= */ /* ========================================================================== */ /* Create an exact copy of a triplet matrix, except that entries in unused * space are not copied (they might not be initialized, and copying them would * cause program checkers such as purify and valgrind to complain). * The output triplet matrix has the same xtype as the input triplet matrix. */ cholmod_triplet *CHOLMOD(copy_triplet) ( /* ---- input ---- */ cholmod_triplet *T, /* matrix to copy */ /* --------------- */ cholmod_common *Common ) { double *Tx, *Tz, *Cx, *Cz ; Int *Ci, *Cj, *Ti, *Tj ; cholmod_triplet *C ; Int xtype, k, nz ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; RETURN_IF_NULL (T, NULL) ; RETURN_IF_XTYPE_INVALID (T, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, NULL) ; nz = T->nnz ; Ti = T->i ; Tj = T->j ; Tx = T->x ; Tz = T->z ; xtype = T->xtype ; RETURN_IF_NULL (Ti, NULL) ; RETURN_IF_NULL (Tj, NULL) ; Common->status = CHOLMOD_OK ; DEBUG (CHOLMOD(dump_triplet) (T, "T input", Common)) ; /* ---------------------------------------------------------------------- */ /* allocate copy */ /* ---------------------------------------------------------------------- */ C = CHOLMOD(allocate_triplet) (T->nrow, T->ncol, T->nzmax, T->stype, xtype, Common) ; if (Common->status < CHOLMOD_OK) { return (NULL) ; /* out of memory */ } /* ---------------------------------------------------------------------- */ /* copy the triplet matrix */ /* ---------------------------------------------------------------------- */ Ci = C->i ; Cj = C->j ; Cx = C->x ; Cz = C->z ; C->nnz = nz ; for (k = 0 ; k < nz ; k++) { Ci [k] = Ti [k] ; } for (k = 0 ; k < nz ; k++) { Cj [k] = Tj [k] ; } if (xtype == CHOLMOD_REAL) { for (k = 0 ; k < nz ; k++) { Cx [k] = Tx [k] ; } } else if (xtype == CHOLMOD_COMPLEX) { for (k = 0 ; k < nz ; k++) { Cx [2*k ] = Tx [2*k ] ; Cx [2*k+1] = Tx [2*k+1] ; } } else if (xtype == CHOLMOD_ZOMPLEX) { for (k = 0 ; k < nz ; k++) { Cx [k] = Tx [k] ; Cz [k] = Tz [k] ; } } /* ---------------------------------------------------------------------- */ /* return the result */ /* ---------------------------------------------------------------------- */ ASSERT (CHOLMOD(dump_triplet) (C, "C triplet copy", Common)) ; return (C) ; } python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Core/cholmod_transpose.c0000644000076500000240000007533713524616144027267 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Core/cholmod_transpose =============================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Core Module. Copyright (C) 2005-2006, * Univ. of Florida. Author: Timothy A. Davis * The CHOLMOD/Core Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Core utility routines for the cholmod_sparse object to * compute the transpose or permuted transpose of a matrix: * * Primary routines: * ----------------- * cholmod_transpose transpose sparse matrix * cholmod_ptranspose transpose and permute sparse matrix * cholmod_sort sort row indices in each column of sparse matrix * * Secondary routines: * ------------------- * cholmod_transpose_unsym transpose unsymmetric sparse matrix * cholmod_transpose_sym transpose symmetric sparse matrix * * All xtypes (pattern, real, complex, and zomplex) are supported. * * --------------------------------------- * Unsymmetric case: A->stype is zero. * --------------------------------------- * * Computes F = A', F = A (:,f)' or F = A (p,f)', except that the indexing by * f does not work the same as the MATLAB notation (see below). A->stype * is zero, which denotes that both the upper and lower triangular parts of * A are present (and used). A may in fact be symmetric in pattern and/or * value; A->stype just denotes which part of A are stored. A may be * rectangular. * * p is a permutation of 0:m-1, and f is a subset of 0:n-1, where A is m-by-n. * There can be no duplicate entries in p or f. * * The set f is held in fset and fsize. * fset = NULL means ":" in MATLAB. fsize is ignored. * fset != NULL means f = fset [0..fsize-1]. * fset != NULL and fsize = 0 means f is the empty set. * * Columns not in the set f are considered to be zero. That is, * if A is 5-by-10 then F = A (:,[3 4])' is not 2-by-5, but 10-by-5, and rows * 3 and 4 of F are equal to columns 3 and 4 of A (the other rows of F are * zero). More precisely, in MATLAB notation: * * [m n] = size (A) ; * F = A ; * notf = ones (1,n) ; * notf (f) = 0 ; * F (:, find (notf)) = 0 * F = F' * * If you want the MATLAB equivalent F=A(p,f) operation, use cholmod_submatrix * instead (which does not compute the transpose). * * F->nzmax must be large enough to hold the matrix F. It is not modified. * If F->nz is present then F->nz [j] = # of entries in column j of F. * * A can be sorted or unsorted, with packed or unpacked columns. * * If f is present and not sorted in ascending order, then F is unsorted * (that is, it may contain columns whose row indices do not appear in * ascending order). Otherwise, F is sorted (the row indices in each * column of F appear in strictly ascending order). * * F is returned in packed or unpacked form, depending on F->packed on input. * If F->packed is false, then F is returned in unpacked form (F->nz must be * present). Each row i of F is large enough to hold all the entries in row i * of A, even if f is provided. That is, F->i and * F->x [F->p [i] .. F->p [i] + F->nz [i] - 1] contain all entries in A (i,f), * but F->p [i+1] - F->p [i] is equal to the number of nonzeros in A (i,:), * not just A (i,f). * * The cholmod_transpose_unsym routine is the only operation in CHOLMOD that * can produce an unpacked matrix. * * --------------------------------------- * Symmetric case: A->stype is nonzero. * --------------------------------------- * * Computes F = A' or F = A(p,p)', the transpose or permuted transpose, where * A->stype is nonzero. * * If A->stype > 0, then A is a symmetric matrix where just the upper part * of the matrix is stored. Entries in the lower triangular part may be * present, but are ignored. A must be square. If F=A', then F is returned * sorted; otherwise F is unsorted for the F=A(p,p)' case. * * There can be no duplicate entries in p. * The fset and fsize parameters are not used. * * Three kinds of transposes are available, depending on the "values" parameter: * 0: do not transpose the numerical values; create a CHOLMOD_PATTERN matrix * 1: array transpose * 2: complex conjugate transpose (same as 2 if input is real or pattern) * * ----------------------------------------------------------------------------- * * For cholmod_transpose_unsym and cholmod_transpose_sym, the output matrix * F must already be pre-allocated by the caller, with the correct dimensions. * If F is not valid or has the wrong dimensions, it is not modified. * Otherwise, if F is too small, the transpose is not computed; the contents * of F->p contain the column pointers of the resulting matrix, where * F->p [F->ncol] > F->nzmax. In this case, the remaining contents of F are * not modified. F can still be properly free'd with cholmod_free_sparse. */ #include "cholmod_internal.h" #include "cholmod_core.h" /* ========================================================================== */ /* === TEMPLATE ============================================================= */ /* ========================================================================== */ #define PATTERN #include "t_cholmod_transpose.c" #define REAL #include "t_cholmod_transpose.c" #define COMPLEX #include "t_cholmod_transpose.c" #define COMPLEX #define NCONJUGATE #include "t_cholmod_transpose.c" #define ZOMPLEX #include "t_cholmod_transpose.c" #define ZOMPLEX #define NCONJUGATE #include "t_cholmod_transpose.c" /* ========================================================================== */ /* === cholmod_transpose_unsym ============================================== */ /* ========================================================================== */ /* Compute F = A', A (:,f)', or A (p,f)', where A is unsymmetric and F is * already allocated. See cholmod_transpose for a simpler routine. * * workspace: * Iwork (MAX (nrow,ncol)) if fset is present * Iwork (nrow) if fset is NULL * * The xtype of A and F must match, unless values is zero or F->xtype is * CHOLMOD_PATTERN (in which case only the pattern of A is transpose into F). */ int CHOLMOD(transpose_unsym) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to transpose */ int values, /* 2: complex conj. transpose, 1: array transpose, 0: do not transpose the numerical values */ Int *Perm, /* size nrow, if present (can be NULL) */ Int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ /* ---- output --- */ cholmod_sparse *F, /* F = A', A(:,f)', or A(p,f)' */ /* --------------- */ cholmod_common *Common ) { Int *Fp, *Fnz, *Ap, *Ai, *Anz, *Wi ; Int nrow, ncol, permute, use_fset, Apacked, Fpacked, p, pend, i, j, k, Fsorted, nf, jj, jlast ; size_t s ; int ok = TRUE ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (A, FALSE) ; RETURN_IF_NULL (F, FALSE) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; RETURN_IF_XTYPE_INVALID (F, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; if (A->nrow != F->ncol || A->ncol != F->nrow) { ERROR (CHOLMOD_INVALID, "F has the wrong dimensions") ; return (FALSE) ; } Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ nf = fsize ; use_fset = (fset != NULL) ; nrow = A->nrow ; ncol = A->ncol ; Ap = A->p ; /* size A->ncol+1, column pointers of A */ Ai = A->i ; /* size nz = Ap [A->ncol], row indices of A */ Anz = A->nz ; Apacked = A->packed ; ASSERT (IMPLIES (!Apacked, Anz != NULL)) ; permute = (Perm != NULL) ; Fp = F->p ; /* size A->nrow+1, row pointers of F */ Fnz = F->nz ; Fpacked = F->packed ; ASSERT (IMPLIES (!Fpacked, Fnz != NULL)) ; nf = (use_fset) ? nf : ncol ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ /* s = nrow + ((fset != NULL) ? ncol : 0) */ s = CHOLMOD(add_size_t) (nrow, ((fset != NULL) ? ncol : 0), &ok) ; if (!ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return (FALSE) ; } CHOLMOD(allocate_work) (0, s, 0, Common) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; /* out of memory */ } Wi = Common->Iwork ; /* size nrow (i/l/l) */ /* ---------------------------------------------------------------------- */ /* check Perm and fset */ /* ---------------------------------------------------------------------- */ if (permute) { for (i = 0 ; i < nrow ; i++) { Wi [i] = 1 ; } for (k = 0 ; k < nrow ; k++) { i = Perm [k] ; if (i < 0 || i > nrow || Wi [i] == 0) { ERROR (CHOLMOD_INVALID, "invalid permutation") ; return (FALSE) ; } Wi [i] = 0 ; } } if (use_fset) { for (j = 0 ; j < ncol ; j++) { Wi [j] = 1 ; } for (k = 0 ; k < nf ; k++) { j = fset [k] ; if (j < 0 || j > ncol || Wi [j] == 0) { ERROR (CHOLMOD_INVALID, "invalid fset") ; return (FALSE) ; } Wi [j] = 0 ; } } /* Perm and fset are now valid */ ASSERT (CHOLMOD(dump_perm) (Perm, nrow, nrow, "Perm", Common)) ; ASSERT (CHOLMOD(dump_perm) (fset, nf, ncol, "fset", Common)) ; /* ---------------------------------------------------------------------- */ /* count the entries in each row of A or A(:,f) */ /* ---------------------------------------------------------------------- */ for (i = 0 ; i < nrow ; i++) { Wi [i] = 0 ; } jlast = EMPTY ; Fsorted = TRUE ; if (use_fset) { /* count entries in each row of A(:,f) */ for (jj = 0 ; jj < nf ; jj++) { j = fset [jj] ; if (j <= jlast) { Fsorted = FALSE ; } p = Ap [j] ; pend = (Apacked) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { Wi [Ai [p]]++ ; } jlast = j ; } /* save the nz counts if F is unpacked, and recount all of A */ if (!Fpacked) { if (permute) { for (i = 0 ; i < nrow ; i++) { Fnz [i] = Wi [Perm [i]] ; } } else { for (i = 0 ; i < nrow ; i++) { Fnz [i] = Wi [i] ; } } for (i = 0 ; i < nrow ; i++) { Wi [i] = 0 ; } /* count entries in each row of A */ for (j = 0 ; j < ncol ; j++) { p = Ap [j] ; pend = (Apacked) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { Wi [Ai [p]]++ ; } } } } else { /* count entries in each row of A */ for (j = 0 ; j < ncol ; j++) { p = Ap [j] ; pend = (Apacked) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { Wi [Ai [p]]++ ; } } /* save the nz counts if F is unpacked */ if (!Fpacked) { if (permute) { for (i = 0 ; i < nrow ; i++) { Fnz [i] = Wi [Perm [i]] ; } } else { for (i = 0 ; i < nrow ; i++) { Fnz [i] = Wi [i] ; } } } } /* ---------------------------------------------------------------------- */ /* compute the row pointers */ /* ---------------------------------------------------------------------- */ p = 0 ; if (permute) { for (i = 0 ; i < nrow ; i++) { Fp [i] = p ; p += Wi [Perm [i]] ; } for (i = 0 ; i < nrow ; i++) { Wi [Perm [i]] = Fp [i] ; } } else { for (i = 0 ; i < nrow ; i++) { Fp [i] = p ; p += Wi [i] ; } for (i = 0 ; i < nrow ; i++) { Wi [i] = Fp [i] ; } } Fp [nrow] = p ; if (p > (Int) (F->nzmax)) { ERROR (CHOLMOD_INVALID, "F is too small") ; return (FALSE) ; } /* ---------------------------------------------------------------------- */ /* transpose matrix, using template routine */ /* ---------------------------------------------------------------------- */ ok = FALSE ; if (values == 0 || F->xtype == CHOLMOD_PATTERN) { ok = p_cholmod_transpose_unsym (A, Perm, fset, nf, F, Common) ; } else if (F->xtype == CHOLMOD_REAL) { ok = r_cholmod_transpose_unsym (A, Perm, fset, nf, F, Common) ; } else if (F->xtype == CHOLMOD_COMPLEX) { if (values == 1) { /* array transpose */ ok = ct_cholmod_transpose_unsym (A, Perm, fset, nf, F, Common) ; } else { /* complex conjugate transpose */ ok = c_cholmod_transpose_unsym (A, Perm, fset, nf, F, Common) ; } } else if (F->xtype == CHOLMOD_ZOMPLEX) { if (values == 1) { /* array transpose */ ok = zt_cholmod_transpose_unsym (A, Perm, fset, nf, F, Common) ; } else { /* complex conjugate transpose */ ok = z_cholmod_transpose_unsym (A, Perm, fset, nf, F, Common) ; } } /* ---------------------------------------------------------------------- */ /* finalize result F */ /* ---------------------------------------------------------------------- */ if (ok) { F->sorted = Fsorted ; } ASSERT (CHOLMOD(dump_sparse) (F, "output F unsym", Common) >= 0) ; return (ok) ; } /* ========================================================================== */ /* === cholmod_transpose_sym ================================================ */ /* ========================================================================== */ /* Compute F = A' or A (p,p)', where A is symmetric and F is already allocated. * See cholmod_transpose for a simpler routine. * * workspace: Iwork (nrow) if Perm NULL, Iwork (2*nrow) if Perm non-NULL. */ int CHOLMOD(transpose_sym) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to transpose */ int values, /* 2: complex conj. transpose, 1: array transpose, 0: do not transpose the numerical values */ Int *Perm, /* size nrow, if present (can be NULL) */ /* ---- output --- */ cholmod_sparse *F, /* F = A' or A(p,p)' */ /* --------------- */ cholmod_common *Common ) { Int *Ap, *Anz, *Ai, *Fp, *Wi, *Pinv, *Iwork ; Int p, pend, packed, upper, permute, jold, n, i, j, k, iold ; size_t s ; int ok = TRUE ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (A, FALSE) ; RETURN_IF_NULL (F, FALSE) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; RETURN_IF_XTYPE_INVALID (F, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; if (A->nrow != A->ncol || A->stype == 0) { /* this routine handles square symmetric matrices only */ ERROR (CHOLMOD_INVALID, "matrix must be symmetric") ; return (FALSE) ; } if (A->nrow != F->ncol || A->ncol != F->nrow) { ERROR (CHOLMOD_INVALID, "F has the wrong dimensions") ; return (FALSE) ; } Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ permute = (Perm != NULL) ; n = A->nrow ; Ap = A->p ; /* size A->ncol+1, column pointers of A */ Ai = A->i ; /* size nz = Ap [A->ncol], row indices of A */ Anz = A->nz ; packed = A->packed ; ASSERT (IMPLIES (!packed, Anz != NULL)) ; upper = (A->stype > 0) ; Fp = F->p ; /* size A->nrow+1, row pointers of F */ /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ /* s = (Perm != NULL) ? 2*n : n */ s = CHOLMOD(add_size_t) (n, ((Perm != NULL) ? n : 0), &ok) ; if (!ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return (FALSE) ; } CHOLMOD(allocate_work) (0, s, 0, Common) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; /* out of memory */ } /* ---------------------------------------------------------------------- */ /* get workspace */ /* ---------------------------------------------------------------------- */ Iwork = Common->Iwork ; Wi = Iwork ; /* size n (i/l/l) */ Pinv = Iwork + n ; /* size n (i/i/l) , unused if Perm NULL */ /* ---------------------------------------------------------------------- */ /* check Perm and construct inverse permutation */ /* ---------------------------------------------------------------------- */ if (permute) { for (i = 0 ; i < n ; i++) { Pinv [i] = EMPTY ; } for (k = 0 ; k < n ; k++) { i = Perm [k] ; if (i < 0 || i > n || Pinv [i] != EMPTY) { ERROR (CHOLMOD_INVALID, "invalid permutation") ; return (FALSE) ; } Pinv [i] = k ; } } /* Perm is now valid */ ASSERT (CHOLMOD(dump_perm) (Perm, n, n, "Perm", Common)) ; /* ---------------------------------------------------------------------- */ /* count the entries in each row of F */ /* ---------------------------------------------------------------------- */ for (i = 0 ; i < n ; i++) { Wi [i] = 0 ; } if (packed) { if (permute) { if (upper) { /* packed, permuted, upper */ for (j = 0 ; j < n ; j++) { jold = Perm [j] ; pend = Ap [jold+1] ; for (p = Ap [jold] ; p < pend ; p++) { iold = Ai [p] ; if (iold <= jold) { i = Pinv [iold] ; Wi [MIN (i, j)]++ ; } } } } else { /* packed, permuted, lower */ for (j = 0 ; j < n ; j++) { jold = Perm [j] ; pend = Ap [jold+1] ; for (p = Ap [jold] ; p < pend ; p++) { iold = Ai [p] ; if (iold >= jold) { i = Pinv [iold] ; Wi [MAX (i, j)]++ ; } } } } } else { if (upper) { /* packed, unpermuted, upper */ for (j = 0 ; j < n ; j++) { pend = Ap [j+1] ; for (p = Ap [j] ; p < pend ; p++) { i = Ai [p] ; if (i <= j) { Wi [i]++ ; } } } } else { /* packed, unpermuted, lower */ for (j = 0 ; j < n ; j++) { pend = Ap [j+1] ; for (p = Ap [j] ; p < pend ; p++) { i = Ai [p] ; if (i >= j) { Wi [i]++ ; } } } } } } else { if (permute) { if (upper) { /* unpacked, permuted, upper */ for (j = 0 ; j < n ; j++) { jold = Perm [j] ; p = Ap [jold] ; pend = p + Anz [jold] ; for ( ; p < pend ; p++) { iold = Ai [p] ; if (iold <= jold) { i = Pinv [iold] ; Wi [MIN (i, j)]++ ; } } } } else { /* unpacked, permuted, lower */ for (j = 0 ; j < n ; j++) { jold = Perm [j] ; p = Ap [jold] ; pend = p + Anz [jold] ; for ( ; p < pend ; p++) { iold = Ai [p] ; if (iold >= jold) { i = Pinv [iold] ; Wi [MAX (i, j)]++ ; } } } } } else { if (upper) { /* unpacked, unpermuted, upper */ for (j = 0 ; j < n ; j++) { p = Ap [j] ; pend = p + Anz [j] ; for ( ; p < pend ; p++) { i = Ai [p] ; if (i <= j) { Wi [i]++ ; } } } } else { /* unpacked, unpermuted, lower */ for (j = 0 ; j < n ; j++) { p = Ap [j] ; pend = p + Anz [j] ; for ( ; p < pend ; p++) { i = Ai [p] ; if (i >= j) { Wi [i]++ ; } } } } } } /* ---------------------------------------------------------------------- */ /* compute the row pointers */ /* ---------------------------------------------------------------------- */ p = 0 ; for (i = 0 ; i < n ; i++) { Fp [i] = p ; p += Wi [i] ; } Fp [n] = p ; for (i = 0 ; i < n ; i++) { Wi [i] = Fp [i] ; } if (p > (Int) (F->nzmax)) { ERROR (CHOLMOD_INVALID, "F is too small") ; return (FALSE) ; } /* ---------------------------------------------------------------------- */ /* transpose matrix, using template routine */ /* ---------------------------------------------------------------------- */ ok = FALSE ; if (values == 0 || F->xtype == CHOLMOD_PATTERN) { PRINT2 (("\n:::: p_transpose_sym Perm %p\n", Perm)) ; ok = p_cholmod_transpose_sym (A, Perm, F, Common) ; } else if (F->xtype == CHOLMOD_REAL) { PRINT2 (("\n:::: r_transpose_sym Perm %p\n", Perm)) ; ok = r_cholmod_transpose_sym (A, Perm, F, Common) ; } else if (F->xtype == CHOLMOD_COMPLEX) { if (values == 1) { /* array transpose */ PRINT2 (("\n:::: ct_transpose_sym Perm %p\n", Perm)) ; ok = ct_cholmod_transpose_sym (A, Perm, F, Common) ; } else { /* complex conjugate transpose */ PRINT2 (("\n:::: c_transpose_sym Perm %p\n", Perm)) ; ok = c_cholmod_transpose_sym (A, Perm, F, Common) ; } } else if (F->xtype == CHOLMOD_ZOMPLEX) { if (values == 1) { /* array transpose */ PRINT2 (("\n:::: zt_transpose_sym Perm %p\n", Perm)) ; ok = zt_cholmod_transpose_sym (A, Perm, F, Common) ; } else { /* complex conjugate transpose */ PRINT2 (("\n:::: z_transpose_sym Perm %p\n", Perm)) ; ok = z_cholmod_transpose_sym (A, Perm, F, Common) ; } } /* ---------------------------------------------------------------------- */ /* finalize result F */ /* ---------------------------------------------------------------------- */ /* F is sorted if there is no permutation vector */ if (ok) { F->sorted = !permute ; F->packed = TRUE ; F->stype = - SIGN (A->stype) ; /* flip the stype */ ASSERT (CHOLMOD(dump_sparse) (F, "output F sym", Common) >= 0) ; } return (ok) ; } /* ========================================================================== */ /* === cholmod_transpose ==================================================== */ /* ========================================================================== */ /* Returns A'. See also cholmod_ptranspose below. */ cholmod_sparse *CHOLMOD(transpose) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to transpose */ int values, /* 2: complex conj. transpose, 1: array transpose, 0: do not transpose the numerical values (returns its result as CHOLMOD_PATTERN) */ /* --------------- */ cholmod_common *Common ) { return (CHOLMOD(ptranspose) (A, values, NULL, NULL, 0, Common)) ; } /* ========================================================================== */ /* === cholmod_ptranspose =================================================== */ /* ========================================================================== */ /* Return A' or A(p,p)' if A is symmetric. Return A', A(:,f)', or A(p,f)' if * A is unsymmetric. * * workspace: * Iwork (MAX (nrow,ncol)) if unsymmetric and fset is non-NULL * Iwork (nrow) if unsymmetric and fset is NULL * Iwork (2*nrow) if symmetric and Perm is non-NULL. * Iwork (nrow) if symmetric and Perm is NULL. * * A simple worst-case upper bound on the workspace is nrow+ncol. */ cholmod_sparse *CHOLMOD(ptranspose) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to transpose */ int values, /* 2: complex conj. transpose, 1: array transpose, 0: do not transpose the numerical values */ Int *Perm, /* if non-NULL, F = A(p,f) or A(p,p) */ Int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ /* --------------- */ cholmod_common *Common ) { Int *Ap, *Anz ; cholmod_sparse *F ; Int nrow, ncol, use_fset, j, jj, fnz, packed, stype, nf, xtype ; size_t ineed ; int ok = TRUE ; nf = fsize ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; RETURN_IF_NULL (A, FALSE) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, NULL) ; stype = A->stype ; Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ nrow = A->nrow ; ncol = A->ncol ; if (stype != 0) { use_fset = FALSE ; if (Perm != NULL) { ineed = CHOLMOD(mult_size_t) (A->nrow, 2, &ok) ; } else { ineed = A->nrow ; } } else { use_fset = (fset != NULL) ; if (use_fset) { ineed = MAX (A->nrow, A->ncol) ; } else { ineed = A->nrow ; } } if (!ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return (NULL) ; } CHOLMOD(allocate_work) (0, ineed, 0, Common) ; if (Common->status < CHOLMOD_OK) { return (NULL) ; /* out of memory */ } /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ Ap = A->p ; Anz = A->nz ; packed = A->packed ; ASSERT (IMPLIES (!packed, Anz != NULL)) ; xtype = values ? A->xtype : CHOLMOD_PATTERN ; /* ---------------------------------------------------------------------- */ /* allocate F */ /* ---------------------------------------------------------------------- */ /* determine # of nonzeros in F */ if (stype != 0) { /* F=A' or F=A(p,p)', fset is ignored */ fnz = CHOLMOD(nnz) (A, Common) ; } else { nf = (use_fset) ? nf : ncol ; if (use_fset) { fnz = 0 ; /* F=A(:,f)' or F=A(p,f)' */ for (jj = 0 ; jj < nf ; jj++) { /* The fset is not yet checked; it will be thoroughly checked * in cholmod_transpose_unsym. For now, just make sure we don't * access Ap and Anz out of bounds. */ j = fset [jj] ; if (j >= 0 && j < ncol) { fnz += packed ? (Ap [j+1] - Ap [j]) : MAX (0, Anz [j]) ; } } } else { /* F=A' or F=A(p,:)' */ fnz = CHOLMOD(nnz) (A, Common) ; } } /* F is ncol-by-nrow, fnz nonzeros, sorted unless f is present and unsorted, * packed, of opposite stype as A, and with/without numerical values */ F = CHOLMOD(allocate_sparse) (ncol, nrow, fnz, TRUE, TRUE, -SIGN(stype), xtype, Common) ; if (Common->status < CHOLMOD_OK) { return (NULL) ; /* out of memory */ } /* ---------------------------------------------------------------------- */ /* transpose and optionally permute the matrix A */ /* ---------------------------------------------------------------------- */ if (stype != 0) { /* F = A (p,p)', using upper or lower triangular part of A only */ ok = CHOLMOD(transpose_sym) (A, values, Perm, F, Common) ; } else { /* F = A (p,f)' */ ok = CHOLMOD(transpose_unsym) (A, values, Perm, fset, nf, F, Common) ; } /* ---------------------------------------------------------------------- */ /* return the matrix F, or NULL if an error occured */ /* ---------------------------------------------------------------------- */ if (!ok) { CHOLMOD(free_sparse) (&F, Common) ; } return (F) ; } /* ========================================================================== */ /* === cholmod_sort ========================================================= */ /* ========================================================================== */ /* Sort the columns of A, in place. Returns A in packed form, even if it * starts as unpacked. Removes entries in the ignored part of a symmetric * matrix. * * workspace: Iwork (max (nrow,ncol)). Allocates additional workspace for a * temporary copy of A'. */ int CHOLMOD(sort) ( /* ---- in/out --- */ cholmod_sparse *A, /* matrix to sort */ /* --------------- */ cholmod_common *Common ) { Int *Ap ; cholmod_sparse *F ; Int anz, ncol, nrow, stype ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (A, FALSE) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; Common->status = CHOLMOD_OK ; nrow = A->nrow ; if (nrow <= 1) { /* a 1-by-n sparse matrix must be sorted */ A->sorted = TRUE ; return (TRUE) ; } /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ ncol = A->ncol ; CHOLMOD(allocate_work) (0, MAX (nrow, ncol), 0, Common) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; /* out of memory */ } /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ anz = CHOLMOD(nnz) (A, Common) ; stype = A->stype ; /* ---------------------------------------------------------------------- */ /* sort the columns of the matrix */ /* ---------------------------------------------------------------------- */ /* allocate workspace for transpose: ncol-by-nrow, same # of nonzeros as A, * sorted, packed, same stype as A, and of the same numeric type as A. */ F = CHOLMOD(allocate_sparse) (ncol, nrow, anz, TRUE, TRUE, stype, A->xtype, Common) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; /* out of memory */ } if (stype != 0) { /* F = A', upper or lower triangular part only */ CHOLMOD(transpose_sym) (A, 1, NULL, F, Common) ; A->packed = TRUE ; /* A = F' */ CHOLMOD(transpose_sym) (F, 1, NULL, A, Common) ; } else { /* F = A' */ CHOLMOD(transpose_unsym) (A, 1, NULL, NULL, 0, F, Common) ; A->packed = TRUE ; /* A = F' */ CHOLMOD(transpose_unsym) (F, 1, NULL, NULL, 0, A, Common) ; } ASSERT (A->sorted && A->packed) ; ASSERT (CHOLMOD(dump_sparse) (A, "Asorted", Common) >= 0) ; /* ---------------------------------------------------------------------- */ /* reduce A in size, if needed. This must succeed. */ /* ---------------------------------------------------------------------- */ Ap = A->p ; anz = Ap [ncol] ; ASSERT ((size_t) anz <= A->nzmax) ; CHOLMOD(reallocate_sparse) (anz, A, Common) ; ASSERT (Common->status >= CHOLMOD_OK) ; /* ---------------------------------------------------------------------- */ /* free workspace */ /* ---------------------------------------------------------------------- */ CHOLMOD(free_sparse) (&F, Common) ; return (TRUE) ; } python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Core/cholmod_common.c0000644000076500000240000005452013524616144026530 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Core/cholmod_common ================================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Core Module. Copyright (C) 2005-2006, * Univ. of Florida. Author: Timothy A. Davis * The CHOLMOD/Core Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Core utility routines for the cholmod_common object: * * Primary routines: * ----------------- * cholmod_start the first call to CHOLMOD * cholmod_finish the last call to CHOLMOD * * Secondary routines: * ------------------- * cholmod_defaults restore (most) default control parameters * cholmod_allocate_work allocate (or reallocate) workspace in Common * cholmod_free_work free workspace in Common * cholmod_clear_flag clear Common->Flag in workspace * cholmod_maxrank column dimension of Common->Xwork workspace * * The Common object is unique. It cannot be allocated or deallocated by * CHOLMOD, since it contains the definition of the memory management routines * used (pointers to malloc, free, realloc, and calloc, or their equivalent). * The Common object contains workspace that is used between calls to * CHOLMOD routines. This workspace allocated by CHOLMOD as needed, by * cholmod_allocate_work and cholmod_free_work. */ #include "cholmod_internal.h" #include "cholmod_core.h" /* ========================================================================== */ /* === cholmod_start ======================================================== */ /* ========================================================================== */ /* Initialize Common default parameters and statistics. Sets workspace * pointers to NULL. * * This routine must be called just once, prior to calling any other CHOLMOD * routine. Do not call this routine after any other CHOLMOD routine (except * cholmod_finish, to start a new CHOLMOD session), or a memory leak will * occur. * * workspace: none */ int CHOLMOD(start) ( cholmod_common *Common ) { int k ; if (Common == NULL) { return (FALSE) ; } /* ---------------------------------------------------------------------- */ /* user error handling routine */ /* ---------------------------------------------------------------------- */ Common->error_handler = NULL ; /* ---------------------------------------------------------------------- */ /* integer and numerical types */ /* ---------------------------------------------------------------------- */ Common->itype = ITYPE ; Common->dtype = DTYPE ; /* ---------------------------------------------------------------------- */ /* default control parameters */ /* ---------------------------------------------------------------------- */ CHOLMOD(defaults) (Common) ; Common->try_catch = FALSE ; /* ---------------------------------------------------------------------- */ /* memory management routines */ /* ---------------------------------------------------------------------- */ /* The user can replace cholmod's memory management routines by redefining * these function pointers. */ #ifndef NMALLOC /* stand-alone ANSI C program */ Common->malloc_memory = malloc ; Common->free_memory = free ; Common->realloc_memory = realloc ; Common->calloc_memory = calloc ; #else /* no memory manager defined at compile-time; MUST define one at run-time */ Common->malloc_memory = NULL ; Common->free_memory = NULL ; Common->realloc_memory = NULL ; Common->calloc_memory = NULL ; #endif /* ---------------------------------------------------------------------- */ /* complex arithmetic routines */ /* ---------------------------------------------------------------------- */ Common->complex_divide = CHOLMOD(divcomplex) ; Common->hypotenuse = CHOLMOD(hypot) ; /* ---------------------------------------------------------------------- */ /* print routine */ /* ---------------------------------------------------------------------- */ #ifndef NPRINT /* stand-alone ANSI C program */ Common->print_function = printf ; #else /* printing disabled */ Common->print_function = NULL ; #endif /* ---------------------------------------------------------------------- */ /* workspace */ /* ---------------------------------------------------------------------- */ /* This code assumes the workspace held in Common is not initialized. If * it is, then a memory leak will occur because the pointers are * overwritten with NULL. */ Common->nrow = 0 ; Common->mark = EMPTY ; Common->xworksize = 0 ; Common->iworksize = 0 ; Common->Flag = NULL ; Common->Head = NULL ; Common->Iwork = NULL ; Common->Xwork = NULL ; Common->no_workspace_reallocate = FALSE ; /* ---------------------------------------------------------------------- */ /* statistics */ /* ---------------------------------------------------------------------- */ /* fl and lnz are computed in cholmod_analyze and cholmod_rowcolcounts */ Common->fl = EMPTY ; Common->lnz = EMPTY ; /* modfl is computed in cholmod_updown, cholmod_rowadd, and cholmod_rowdel*/ Common->modfl = EMPTY ; /* all routines use status as their error-report code */ Common->status = CHOLMOD_OK ; Common->malloc_count = 0 ; /* # calls to malloc minus # calls to free */ Common->memory_usage = 0 ; /* peak memory usage (in bytes) */ Common->memory_inuse = 0 ; /* current memory in use (in bytes) */ Common->nrealloc_col = 0 ; Common->nrealloc_factor = 0 ; Common->ndbounds_hit = 0 ; Common->rowfacfl = 0 ; Common->aatfl = EMPTY ; /* Common->called_nd is TRUE if cholmod_analyze called or NESDIS */ Common->called_nd = FALSE ; Common->blas_ok = TRUE ; /* false if BLAS int overflow occurs */ /* ---------------------------------------------------------------------- */ /* default SuiteSparseQR knobs and statististics */ /* ---------------------------------------------------------------------- */ for (k = 0 ; k < 4 ; k++) Common->SPQR_xstat [k] = 0 ; for (k = 0 ; k < 10 ; k++) Common->SPQR_istat [k] = 0 ; for (k = 0 ; k < 10 ; k++) Common->other1 [k] = 0 ; for (k = 0 ; k < 6 ; k++) Common->other2 [k] = 0 ; for (k = 0 ; k < 10 ; k++) Common->other3 [k] = 0 ; for (k = 0 ; k < 16 ; k++) Common->other4 [k] = 0 ; for (k = 0 ; k < 16 ; k++) Common->other5 [k] = (void *) NULL ; Common->SPQR_grain = 1 ; /* no Intel TBB multitasking, by default */ Common->SPQR_small = 1e6 ; /* target min task size for TBB */ Common->SPQR_shrink = 1 ; /* controls SPQR shrink realloc */ Common->SPQR_nthreads = 0 ; /* 0: let TBB decide how many threads to use */ /* ---------------------------------------------------------------------- */ /* GPU initializations */ /* ---------------------------------------------------------------------- */ #ifdef GPU_BLAS Common->cublasHandle = NULL ; Common->cudaStreamSyrk = NULL ; Common->cudaStreamGemm = NULL ; Common->cudaStreamTrsm = NULL ; Common->cudaStreamPotrf [0] = NULL ; Common->cudaStreamPotrf [1] = NULL ; Common->cudaStreamPotrf [2] = NULL ; Common->cublasEventPotrf [0] = NULL ; Common->cublasEventPotrf [1] = NULL ; Common->HostPinnedMemory = NULL ; Common->devPotrfWork = NULL ; Common->devSyrkGemmPtrLx = NULL ; Common->devSyrkGemmPtrC = NULL ; Common->GemmUsed = 0 ; Common->SyrkUsed = 0 ; Common->syrkStart = 0 ; #endif DEBUG_INIT ("cholmod start", Common) ; return (TRUE) ; } /* ========================================================================== */ /* === cholmod_defaults ===================================================== */ /* ========================================================================== */ /* Set Common default parameters, except for the function pointers. * * workspace: none */ int CHOLMOD(defaults) ( cholmod_common *Common ) { Int i ; RETURN_IF_NULL_COMMON (FALSE) ; /* ---------------------------------------------------------------------- */ /* default control parameters */ /* ---------------------------------------------------------------------- */ Common->dbound = 0.0 ; Common->grow0 = 1.2 ; Common->grow1 = 1.2 ; Common->grow2 = 5 ; Common->maxrank = 8 ; Common->final_asis = TRUE ; Common->final_super = TRUE ; Common->final_ll = FALSE ; Common->final_pack = TRUE ; Common->final_monotonic = TRUE ; Common->final_resymbol = FALSE ; /* use simplicial factorization if flop/nnz(L) < 40, supernodal otherwise */ Common->supernodal = CHOLMOD_AUTO ; Common->supernodal_switch = 40 ; Common->nrelax [0] = 4 ; Common->nrelax [1] = 16 ; Common->nrelax [2] = 48 ; Common->zrelax [0] = 0.8 ; Common->zrelax [1] = 0.1 ; Common->zrelax [2] = 0.05 ; Common->prefer_zomplex = FALSE ; Common->prefer_upper = TRUE ; Common->prefer_binary = FALSE ; Common->quick_return_if_not_posdef = FALSE ; /* METIS workarounds */ Common->metis_memory = 0.0 ; /* > 0 for memory guard (2 is reasonable) */ Common->metis_nswitch = 3000 ; Common->metis_dswitch = 0.66 ; Common->print = 3 ; Common->precise = FALSE ; /* ---------------------------------------------------------------------- */ /* default ordering methods */ /* ---------------------------------------------------------------------- */ /* Note that if the Partition module is not installed, the CHOLMOD_METIS * and CHOLMOD_NESDIS methods will not be available. cholmod_analyze will * report the CHOLMOD_NOT_INSTALLED error, and safely skip over them. */ #if (CHOLMOD_MAXMETHODS < 9) #error "CHOLMOD_MAXMETHODS must be 9 or more (defined in cholmod_core.h)." #endif /* default strategy: try given, AMD, and then METIS if AMD reports high * fill-in. NESDIS can be used instead, if Common->default_nesdis is TRUE. */ Common->nmethods = 0 ; /* use default strategy */ Common->default_nesdis = FALSE ; /* use METIS in default strategy */ Common->current = 0 ; /* current method being tried */ Common->selected = 0 ; /* the best method selected */ /* first, fill each method with default parameters */ for (i = 0 ; i <= CHOLMOD_MAXMETHODS ; i++) { /* CHOLMOD's default method is AMD for A or AA' */ Common->method [i].ordering = CHOLMOD_AMD ; /* CHOLMOD nested dissection and minimum degree parameter */ Common->method [i].prune_dense = 10.0 ; /* dense row/col control */ /* min degree parameters (AMD, COLAMD, SYMAMD, CAMD, CCOLAMD, CSYMAMD)*/ Common->method [i].prune_dense2 = -1 ; /* COLAMD dense row control */ Common->method [i].aggressive = TRUE ; /* aggressive absorption */ Common->method [i].order_for_lu = FALSE ;/* order for Cholesky not LU */ /* CHOLMOD's nested dissection (METIS + constrained AMD) */ Common->method [i].nd_small = 200 ; /* small graphs aren't cut */ Common->method [i].nd_compress = TRUE ; /* compress graph & subgraphs */ Common->method [i].nd_camd = 1 ; /* use CAMD */ Common->method [i].nd_components = FALSE ; /* lump connected comp. */ Common->method [i].nd_oksep = 1.0 ; /* sep ok if < oksep*n */ /* statistics for each method are not yet computed */ Common->method [i].fl = EMPTY ; Common->method [i].lnz = EMPTY ; } Common->postorder = TRUE ; /* follow ordering with weighted postorder */ /* Next, define some methods. The first five use default parameters. */ Common->method [0].ordering = CHOLMOD_GIVEN ; /* skip if UserPerm NULL */ Common->method [1].ordering = CHOLMOD_AMD ; Common->method [2].ordering = CHOLMOD_METIS ; Common->method [3].ordering = CHOLMOD_NESDIS ; Common->method [4].ordering = CHOLMOD_NATURAL ; /* CHOLMOD's nested dissection with large leaves of separator tree */ Common->method [5].ordering = CHOLMOD_NESDIS ; Common->method [5].nd_small = 20000 ; /* CHOLMOD's nested dissection with tiny leaves, and no AMD ordering */ Common->method [6].ordering = CHOLMOD_NESDIS ; Common->method [6].nd_small = 4 ; Common->method [6].nd_camd = 0 ; /* no CSYMAMD or CAMD */ /* CHOLMOD's nested dissection with no dense node removal */ Common->method [7].ordering = CHOLMOD_NESDIS ; Common->method [7].prune_dense = -1. ; /* COLAMD for A*A', AMD for A */ Common->method [8].ordering = CHOLMOD_COLAMD ; return (TRUE) ; } /* ========================================================================== */ /* === cholmod_finish ======================================================= */ /* ========================================================================== */ /* The last call to CHOLMOD must be cholmod_finish. You may call this routine * more than once, and can safely call any other CHOLMOD routine after calling * it (including cholmod_start). * * The statistics and parameter settings in Common are preserved. The * workspace in Common is freed. This routine is just another name for * cholmod_free_work. */ int CHOLMOD(finish) ( cholmod_common *Common ) { return (CHOLMOD(free_work) (Common)) ; } /* ========================================================================== */ /* === cholmod_allocate_work ================================================ */ /* ========================================================================== */ /* Allocate and initialize workspace for CHOLMOD routines, or increase the size * of already-allocated workspace. If enough workspace is already allocated, * then nothing happens. * * workspace: Flag (nrow), Head (nrow+1), Iwork (iworksize), Xwork (xworksize) */ int CHOLMOD(allocate_work) ( /* ---- input ---- */ size_t nrow, /* # of rows in the matrix A */ size_t iworksize, /* size of Iwork */ size_t xworksize, /* size of Xwork */ /* --------------- */ cholmod_common *Common ) { double *W ; Int *Head ; Int i ; size_t nrow1 ; int ok = TRUE ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* Allocate Flag (nrow) and Head (nrow+1) */ /* ---------------------------------------------------------------------- */ nrow = MAX (1, nrow) ; /* nrow1 = nrow + 1 */ nrow1 = CHOLMOD(add_size_t) (nrow, 1, &ok) ; if (!ok) { /* nrow+1 causes size_t overflow ; problem is too large */ Common->status = CHOLMOD_TOO_LARGE ; CHOLMOD(free_work) (Common) ; return (FALSE) ; } if (nrow > Common->nrow) { if (Common->no_workspace_reallocate) { /* CHOLMOD is not allowed to change the workspace here */ Common->status = CHOLMOD_INVALID ; return (FALSE) ; } /* free the old workspace (if any) and allocate new space */ Common->Flag = CHOLMOD(free) (Common->nrow, sizeof (Int), Common->Flag, Common) ; Common->Head = CHOLMOD(free) (Common->nrow+1,sizeof (Int), Common->Head, Common) ; Common->Flag = CHOLMOD(malloc) (nrow, sizeof (Int), Common) ; Common->Head = CHOLMOD(malloc) (nrow1, sizeof (Int), Common) ; /* record the new size of Flag and Head */ Common->nrow = nrow ; if (Common->status < CHOLMOD_OK) { CHOLMOD(free_work) (Common) ; return (FALSE) ; } /* initialize Flag and Head */ Common->mark = EMPTY ; CHOLMOD(clear_flag) (Common) ; Head = Common->Head ; for (i = 0 ; i <= (Int) (nrow) ; i++) { Head [i] = EMPTY ; } } /* ---------------------------------------------------------------------- */ /* Allocate Iwork (iworksize) */ /* ---------------------------------------------------------------------- */ iworksize = MAX (1, iworksize) ; if (iworksize > Common->iworksize) { if (Common->no_workspace_reallocate) { /* CHOLMOD is not allowed to change the workspace here */ Common->status = CHOLMOD_INVALID ; return (FALSE) ; } /* free the old workspace (if any) and allocate new space. * integer overflow safely detected in cholmod_malloc */ CHOLMOD(free) (Common->iworksize, sizeof (Int), Common->Iwork, Common) ; Common->Iwork = CHOLMOD(malloc) (iworksize, sizeof (Int), Common) ; /* record the new size of Iwork */ Common->iworksize = iworksize ; if (Common->status < CHOLMOD_OK) { CHOLMOD(free_work) (Common) ; return (FALSE) ; } /* note that Iwork does not need to be initialized */ } /* ---------------------------------------------------------------------- */ /* Allocate Xwork (xworksize) and set it to ((double) 0.) */ /* ---------------------------------------------------------------------- */ /* make sure xworksize is >= 1 */ xworksize = MAX (1, xworksize) ; if (xworksize > Common->xworksize) { if (Common->no_workspace_reallocate) { /* CHOLMOD is not allowed to change the workspace here */ Common->status = CHOLMOD_INVALID ; return (FALSE) ; } /* free the old workspace (if any) and allocate new space */ CHOLMOD(free) (Common->xworksize, sizeof (double), Common->Xwork, Common) ; Common->Xwork = CHOLMOD(malloc) (xworksize, sizeof (double), Common) ; /* record the new size of Xwork */ Common->xworksize = xworksize ; if (Common->status < CHOLMOD_OK) { CHOLMOD(free_work) (Common) ; return (FALSE) ; } /* initialize Xwork */ W = Common->Xwork ; for (i = 0 ; i < (Int) xworksize ; i++) { W [i] = 0. ; } } return (TRUE) ; } /* ========================================================================== */ /* === cholmod_free_work ==================================================== */ /* ========================================================================== */ /* Deallocate the CHOLMOD workspace. * * workspace: deallocates all workspace in Common */ int CHOLMOD(free_work) ( cholmod_common *Common ) { RETURN_IF_NULL_COMMON (FALSE) ; Common->Flag = CHOLMOD(free) (Common->nrow, sizeof (Int), Common->Flag, Common) ; Common->Head = CHOLMOD(free) (Common->nrow+1, sizeof (Int), Common->Head, Common) ; Common->Iwork = CHOLMOD(free) (Common->iworksize, sizeof (Int), Common->Iwork, Common) ; Common->Xwork = CHOLMOD(free) (Common->xworksize, sizeof (double), Common->Xwork, Common) ; Common->nrow = 0 ; Common->iworksize = 0 ; Common->xworksize = 0 ; return (TRUE) ; } /* ========================================================================== */ /* === cholmod_clear_flag =================================================== */ /* ========================================================================== */ /* Increment mark to ensure Flag [0..nrow-1] < mark. If integer overflow * occurs, or mark was initially negative, reset the entire array. This is * not an error condition, but an intended function of the Flag workspace. * * workspace: Flag (nrow). Does not modify Flag if nrow is zero. */ SuiteSparse_long CHOLMOD(clear_flag) ( cholmod_common *Common ) { Int i, nrow, *Flag ; RETURN_IF_NULL_COMMON (-1) ; Common->mark++ ; if (Common->mark <= 0) { nrow = Common->nrow ; Flag = Common->Flag ; PRINT2 (("reset Flag: nrow "ID"\n", nrow)) ; PRINT2 (("reset Flag: mark %ld\n", Common->mark)) ; for (i = 0 ; i < nrow ; i++) { Flag [i] = EMPTY ; } Common->mark = 0 ; } return (Common->mark) ; } /* ========================================================================== */ /* ==== cholmod_maxrank ===================================================== */ /* ========================================================================== */ /* Find a valid value of Common->maxrank. Returns 0 if error, or 2, 4, or 8 * if successful. */ size_t CHOLMOD(maxrank) /* returns validated value of Common->maxrank */ ( /* ---- input ---- */ size_t n, /* A and L will have n rows */ /* --------------- */ cholmod_common *Common ) { size_t maxrank ; RETURN_IF_NULL_COMMON (0) ; maxrank = Common->maxrank ; if (n > 0) { /* Ensure maxrank*n*sizeof(double) does not result in integer overflow. * If n is so large that 2*n*sizeof(double) results in integer overflow * (n = 268,435,455 if an Int is 32 bits), then maxrank will be 0 or 1, * but maxrank will be set to 2 below. 2*n will not result in integer * overflow, and CHOLMOD will run out of memory or safely detect integer * overflow elsewhere. */ maxrank = MIN (maxrank, Size_max / (n * sizeof (double))) ; } if (maxrank <= 2) { maxrank = 2 ; } else if (maxrank <= 4) { maxrank = 4 ; } else { maxrank = 8 ; } return (maxrank) ; } /* ========================================================================== */ /* === cholmod_dbound ======================================================= */ /* ========================================================================== */ /* Ensure the absolute value of a diagonal entry, D (j,j), is greater than * Common->dbound. This routine is not meant for the user to call. It is used * by the various LDL' factorization and update/downdate routines. The * default value of Common->dbound is zero, and in that case this routine is not * called at all. No change is made if D (j,j) is NaN. CHOLMOD does not call * this routine if Common->dbound is NaN. */ double CHOLMOD(dbound) /* returns modified diagonal entry of D */ ( /* ---- input ---- */ double dj, /* diagonal entry of D, for LDL' factorization */ /* --------------- */ cholmod_common *Common ) { double dbound ; RETURN_IF_NULL_COMMON (0) ; if (!IS_NAN (dj)) { dbound = Common->dbound ; if (dj < 0) { if (dj > -dbound) { dj = -dbound ; Common->ndbounds_hit++ ; if (Common->status == CHOLMOD_OK) { ERROR (CHOLMOD_DSMALL, "diagonal below threshold") ; } } } else { if (dj < dbound) { dj = dbound ; Common->ndbounds_hit++ ; if (Common->status == CHOLMOD_OK) { ERROR (CHOLMOD_DSMALL, "diagonal below threshold") ; } } } } return (dj) ; } python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Core/cholmod_complex.c0000644000076500000240000003775113524616144026716 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Core/cholmod_complex ================================================= */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Core Module. Copyright (C) 2005-2006, * Univ. of Florida. Author: Timothy A. Davis * The CHOLMOD/Core Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* If you convert a matrix that contains uninitialized data, valgrind will * complain. This can occur in a factor L which has gaps (a partial * factorization, or after updates that change the nonzero pattern), an * unpacked sparse matrix, a dense matrix with leading dimension d > # of rows, * or any matrix (dense, sparse, triplet, or factor) with more space allocated * than is used. You can safely ignore any of these complaints by valgrind. */ #include "cholmod_internal.h" #include "cholmod_core.h" /* ========================================================================== */ /* === cholmod_hypot ======================================================== */ /* ========================================================================== */ /* There is an equivalent routine called hypot in , which conforms * to ANSI C99. However, CHOLMOD does not assume that ANSI C99 is available. * You can use the ANSI C99 hypot routine with: * * #include * Common->hypotenuse = hypot ; * * Default value of the Common->hypotenuse pointer is cholmod_hypot. * * s = hypot (x,y) computes s = sqrt (x*x + y*y) but does so more accurately. * The NaN cases for the double relops x >= y and x+y == x are safely ignored. * * Source: Algorithm 312, "Absolute value and square root of a complex number," * P. Friedland, Comm. ACM, vol 10, no 10, October 1967, page 665. */ double CHOLMOD(hypot) (double x, double y) { double s, r ; x = fabs (x) ; y = fabs (y) ; if (x >= y) { if (x + y == x) { s = x ; } else { r = y / x ; s = x * sqrt (1.0 + r*r) ; } } else { if (y + x == y) { s = y ; } else { r = x / y ; s = y * sqrt (1.0 + r*r) ; } } return (s) ; } /* ========================================================================== */ /* === cholmod_divcomplex =================================================== */ /* ========================================================================== */ /* c = a/b where c, a, and b are complex. The real and imaginary parts are * passed as separate arguments to this routine. The NaN case is ignored * for the double relop br >= bi. Returns 1 if the denominator is zero, * 0 otherwise. Note that this return value is the single exception to the * rule that all CHOLMOD routines that return int return TRUE if successful * or FALSE otherise. * * This uses ACM Algo 116, by R. L. Smith, 1962, which tries to avoid * underflow and overflow. * * c can be the same variable as a or b. * * Default value of the Common->complex_divide pointer is cholmod_divcomplex. */ int CHOLMOD(divcomplex) ( double ar, double ai, /* real and imaginary parts of a */ double br, double bi, /* real and imaginary parts of b */ double *cr, double *ci /* real and imaginary parts of c */ ) { double tr, ti, r, den ; if (fabs (br) >= fabs (bi)) { r = bi / br ; den = br + r * bi ; tr = (ar + ai * r) / den ; ti = (ai - ar * r) / den ; } else { r = br / bi ; den = r * br + bi ; tr = (ar * r + ai) / den ; ti = (ai * r - ar) / den ; } *cr = tr ; *ci = ti ; return (IS_ZERO (den)) ; } /* ========================================================================== */ /* === change_complexity ==================================================== */ /* ========================================================================== */ /* X and Z represent an array of size nz, with numeric xtype given by xtype_in. * * If xtype_in is: * CHOLMOD_PATTERN: X and Z must be NULL. * CHOLMOD_REAL: X is of size nz, Z must be NULL. * CHOLMOD_COMPLEX: X is of size 2*nz, Z must be NULL. * CHOLMOD_ZOMPLEX: X is of size nz, Z is of size nz. * * The array is changed into the numeric xtype given by xtype_out, with the * same definitions of X and Z above. Note that the input conditions, above, * are not checked. These are checked in the caller routine. * * Returns TRUE if successful, FALSE otherwise. X and Z are not modified if * not successful. */ static int change_complexity ( /* ---- input ---- */ Int nz, /* size of X and/or Z */ int xtype_in, /* xtype of X and Z on input */ int xtype_out, /* requested xtype of X and Z on output */ int xtype1, /* xtype_out must be in the range [xtype1 .. xtype2] */ int xtype2, /* ---- in/out --- */ void **XX, /* old X on input, new X on output */ void **ZZ, /* old Z on input, new Z on output */ /* --------------- */ cholmod_common *Common ) { double *Xold, *Zold, *Xnew, *Znew ; Int k ; size_t nz2 ; if (xtype_out < xtype1 || xtype_out > xtype2) { ERROR (CHOLMOD_INVALID, "invalid xtype") ; return (FALSE) ; } Common->status = CHOLMOD_OK ; Xold = *XX ; Zold = *ZZ ; switch (xtype_in) { /* ------------------------------------------------------------------ */ /* converting from pattern */ /* ------------------------------------------------------------------ */ case CHOLMOD_PATTERN: switch (xtype_out) { /* ---------------------------------------------------------- */ /* pattern -> real */ /* ---------------------------------------------------------- */ case CHOLMOD_REAL: /* allocate X and set to all ones */ Xnew = CHOLMOD(malloc) (nz, sizeof (double), Common) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; } for (k = 0 ; k < nz ; k++) { Xnew [k] = 1 ; } *XX = Xnew ; break ; /* ---------------------------------------------------------- */ /* pattern -> complex */ /* ---------------------------------------------------------- */ case CHOLMOD_COMPLEX: /* allocate X and set to all ones */ Xnew = CHOLMOD(malloc) (nz, 2*sizeof (double), Common) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; } for (k = 0 ; k < nz ; k++) { Xnew [2*k ] = 1 ; Xnew [2*k+1] = 0 ; } *XX = Xnew ; break ; /* ---------------------------------------------------------- */ /* pattern -> zomplex */ /* ---------------------------------------------------------- */ case CHOLMOD_ZOMPLEX: /* allocate X and Z and set to all ones */ Xnew = CHOLMOD(malloc) (nz, sizeof (double), Common) ; Znew = CHOLMOD(malloc) (nz, sizeof (double), Common) ; if (Common->status < CHOLMOD_OK) { CHOLMOD(free) (nz, sizeof (double), Xnew, Common) ; CHOLMOD(free) (nz, sizeof (double), Znew, Common) ; return (FALSE) ; } for (k = 0 ; k < nz ; k++) { Xnew [k] = 1 ; Znew [k] = 0 ; } *XX = Xnew ; *ZZ = Znew ; break ; } break ; /* ------------------------------------------------------------------ */ /* converting from real */ /* ------------------------------------------------------------------ */ case CHOLMOD_REAL: switch (xtype_out) { /* ---------------------------------------------------------- */ /* real -> pattern */ /* ---------------------------------------------------------- */ case CHOLMOD_PATTERN: /* free X */ *XX = CHOLMOD(free) (nz, sizeof (double), *XX, Common) ; break ; /* ---------------------------------------------------------- */ /* real -> complex */ /* ---------------------------------------------------------- */ case CHOLMOD_COMPLEX: /* allocate a new X and copy the old X */ Xnew = CHOLMOD(malloc) (nz, 2*sizeof (double), Common) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; } for (k = 0 ; k < nz ; k++) { Xnew [2*k ] = Xold [k] ; Xnew [2*k+1] = 0 ; } CHOLMOD(free) (nz, sizeof (double), *XX, Common) ; *XX = Xnew ; break ; /* ---------------------------------------------------------- */ /* real -> zomplex */ /* ---------------------------------------------------------- */ case CHOLMOD_ZOMPLEX: /* allocate a new Z and set it to zero */ Znew = CHOLMOD(malloc) (nz, sizeof (double), Common) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; } for (k = 0 ; k < nz ; k++) { Znew [k] = 0 ; } *ZZ = Znew ; break ; } break ; /* ------------------------------------------------------------------ */ /* converting from complex */ /* ------------------------------------------------------------------ */ case CHOLMOD_COMPLEX: switch (xtype_out) { /* ---------------------------------------------------------- */ /* complex -> pattern */ /* ---------------------------------------------------------- */ case CHOLMOD_PATTERN: /* free X */ *XX = CHOLMOD(free) (nz, 2*sizeof (double), *XX, Common) ; break ; /* ---------------------------------------------------------- */ /* complex -> real */ /* ---------------------------------------------------------- */ case CHOLMOD_REAL: /* pack the real part of X, discarding the imaginary part */ for (k = 0 ; k < nz ; k++) { Xold [k] = Xold [2*k] ; } /* shrink X in half (this cannot fail) */ nz2 = 2*nz ; *XX = CHOLMOD(realloc) (nz, sizeof (double), *XX, &nz2, Common) ; break ; /* ---------------------------------------------------------- */ /* complex -> zomplex */ /* ---------------------------------------------------------- */ case CHOLMOD_ZOMPLEX: /* allocate X and Z and copy the old X into them */ Xnew = CHOLMOD(malloc) (nz, sizeof (double), Common) ; Znew = CHOLMOD(malloc) (nz, sizeof (double), Common) ; if (Common->status < CHOLMOD_OK) { CHOLMOD(free) (nz, sizeof (double), Xnew, Common) ; CHOLMOD(free) (nz, sizeof (double), Znew, Common) ; return (FALSE) ; } for (k = 0 ; k < nz ; k++) { Xnew [k] = Xold [2*k ] ; Znew [k] = Xold [2*k+1] ; } CHOLMOD(free) (nz, 2*sizeof (double), *XX, Common) ; *XX = Xnew ; *ZZ = Znew ; break ; } break ; /* ------------------------------------------------------------------ */ /* converting from zomplex */ /* ------------------------------------------------------------------ */ case CHOLMOD_ZOMPLEX: switch (xtype_out) { /* ---------------------------------------------------------- */ /* zomplex -> pattern */ /* ---------------------------------------------------------- */ case CHOLMOD_PATTERN: /* free X and Z */ *XX = CHOLMOD(free) (nz, sizeof (double), *XX, Common) ; *ZZ = CHOLMOD(free) (nz, sizeof (double), *ZZ, Common) ; break ; /* ---------------------------------------------------------- */ /* zomplex -> real */ /* ---------------------------------------------------------- */ case CHOLMOD_REAL: /* free the imaginary part */ *ZZ = CHOLMOD(free) (nz, sizeof (double), *ZZ, Common) ; break ; /* ---------------------------------------------------------- */ /* zomplex -> complex */ /* ---------------------------------------------------------- */ case CHOLMOD_COMPLEX: Xnew = CHOLMOD(malloc) (nz, 2*sizeof (double), Common) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; } for (k = 0 ; k < nz ; k++) { Xnew [2*k ] = Xold [k] ; Xnew [2*k+1] = Zold [k] ; } CHOLMOD(free) (nz, sizeof (double), *XX, Common) ; CHOLMOD(free) (nz, sizeof (double), *ZZ, Common) ; *XX = Xnew ; *ZZ = NULL ; break ; } break ; } return (TRUE) ; } /* ========================================================================== */ /* === cholmod_sparse_xtype ================================================= */ /* ========================================================================== */ /* Change the numeric xtype of a sparse matrix. Supports any type on input * and output (pattern, real, complex, or zomplex). */ int CHOLMOD(sparse_xtype) ( /* ---- input ---- */ int to_xtype, /* requested xtype */ /* ---- in/out --- */ cholmod_sparse *A, /* sparse matrix to change */ /* --------------- */ cholmod_common *Common ) { Int ok ; RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (A, FALSE) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; ok = change_complexity (A->nzmax, A->xtype, to_xtype, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, &(A->x), &(A->z), Common) ; if (ok) { A->xtype = to_xtype ; } return (ok) ; } /* ========================================================================== */ /* === cholmod_triplet_xtype ================================================ */ /* ========================================================================== */ /* Change the numeric xtype of a triplet matrix. Supports any type on input * and output (pattern, real, complex, or zomplex). */ int CHOLMOD(triplet_xtype) ( /* ---- input ---- */ int to_xtype, /* requested xtype */ /* ---- in/out --- */ cholmod_triplet *T, /* triplet matrix to change */ /* --------------- */ cholmod_common *Common ) { Int ok ; RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (T, FALSE) ; RETURN_IF_XTYPE_INVALID (T, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; ok = change_complexity (T->nzmax, T->xtype, to_xtype, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, &(T->x), &(T->z), Common) ; if (ok) { T->xtype = to_xtype ; } return (ok) ; } /* ========================================================================== */ /* === cholmod_dense_xtype ================================================= */ /* ========================================================================== */ /* Change the numeric xtype of a dense matrix. Supports real, complex or * zomplex on input and output */ int CHOLMOD(dense_xtype) ( /* ---- input ---- */ int to_xtype, /* requested xtype */ /* ---- in/out --- */ cholmod_dense *X, /* dense matrix to change */ /* --------------- */ cholmod_common *Common ) { Int ok ; RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (X, FALSE) ; RETURN_IF_XTYPE_INVALID (X, CHOLMOD_REAL, CHOLMOD_ZOMPLEX, FALSE) ; ok = change_complexity (X->nzmax, X->xtype, to_xtype, CHOLMOD_REAL, CHOLMOD_ZOMPLEX, &(X->x), &(X->z), Common) ; if (ok) { X->xtype = to_xtype ; } return (ok) ; } /* ========================================================================== */ /* === cholmod_factor_xtype ================================================= */ /* ========================================================================== */ /* Change the numeric xtype of a factor. Supports real, complex or zomplex on * input and output. Supernodal zomplex factors are not supported. */ int CHOLMOD(factor_xtype) ( /* ---- input ---- */ int to_xtype, /* requested xtype */ /* ---- in/out --- */ cholmod_factor *L, /* factor to change */ /* --------------- */ cholmod_common *Common ) { Int ok ; RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (L, FALSE) ; RETURN_IF_XTYPE_INVALID (L, CHOLMOD_REAL, CHOLMOD_ZOMPLEX, FALSE) ; if (L->is_super && (L->xtype == CHOLMOD_ZOMPLEX || to_xtype == CHOLMOD_ZOMPLEX)) { ERROR (CHOLMOD_INVALID, "invalid xtype for supernodal L") ; return (FALSE) ; } ok = change_complexity ((L->is_super ? L->xsize : L->nzmax), L->xtype, to_xtype, CHOLMOD_REAL, CHOLMOD_ZOMPLEX, &(L->x), &(L->z), Common) ; if (ok) { L->xtype = to_xtype ; } return (ok) ; } python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Core/cholmod_factor.c0000644000076500000240000006552113524616144026521 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Core/cholmod_factor ================================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Core Module. Copyright (C) 2005-2013, * Univ. of Florida. Author: Timothy A. Davis * The CHOLMOD/Core Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Core utility routines for the cholmod_factor object: * * The data structure for an LL' or LDL' factorization is too complex to * describe in one sentence. This object can hold the symbolic analysis alone, * or in combination with a "simplicial" (similar to a sparse matrix) or * "supernodal" form of the numerical factorization. Only the routine to free * a factor is primary, since a factor object is created by the factorization * routine (cholmod_factorize). It must be freed with cholmod_free_factor. * * Primary routine: * ---------------- * cholmod_free_factor free a factor * * Secondary routines: * ------------------- * cholmod_allocate_factor allocate a symbolic factor (LL' or LDL') * cholmod_reallocate_factor change the # entries in a factor * cholmod_change_factor change the type of factor (e.g., LDL' to LL') * cholmod_pack_factor pack the columns of a factor * cholmod_reallocate_column resize a single column of a factor * cholmod_factor_to_sparse create a sparse matrix copy of a factor * cholmod_copy_factor create a copy of a factor * * Note that there is no cholmod_sparse_to_factor routine to create a factor * as a copy of a sparse matrix. It could be done, after a fashion, but a * lower triangular sparse matrix would not necessarily have a chordal graph, * which would break the many CHOLMOD routines that rely on this property. * * The cholmod_factor_to_sparse routine is provided so that matrix operations * in the MatrixOps module may be applied to L. Those operations operate on * cholmod_sparse objects, and they are not guaranteed to maintain the chordal * property of L. Such a modified L cannot be safely converted back to a * cholmod_factor object. */ #include "cholmod_internal.h" #include "cholmod_core.h" /* ========================================================================== */ /* === cholmod_allocate_factor ============================================== */ /* ========================================================================== */ /* Allocate a simplicial symbolic factor, with L->Perm and L->ColCount allocated * and initialized to "empty" values (Perm [k] = k, and ColCount[k] = 1). * The integer and numerical parts of L are not allocated. L->xtype is returned * as CHOLMOD_PATTERN and L->is_super are returned as FALSE. L->is_ll is also * returned FALSE, but this may be modified when the matrix is factorized. * * This is sufficient (but far from ideal) for input to cholmod_factorize, * since the simplicial LL' or LDL' factorization (cholmod_rowfac) can * reallocate the columns of L as needed. The primary purpose of this routine * is to allocate space for a symbolic factorization, for the "expert" user to * do his or her own symbolic analysis. The typical user should use * cholmod_analyze instead of this routine. * * workspace: none */ cholmod_factor *CHOLMOD(allocate_factor) ( /* ---- input ---- */ size_t n, /* L is n-by-n */ /* --------------- */ cholmod_common *Common ) { Int j ; Int *Perm, *ColCount ; cholmod_factor *L ; int ok = TRUE ; RETURN_IF_NULL_COMMON (FALSE) ; Common->status = CHOLMOD_OK ; /* ensure the dimension does not cause integer overflow */ (void) CHOLMOD(add_size_t) (n, 2, &ok) ; if (!ok || n > Int_max) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return (NULL) ; } L = CHOLMOD(malloc) (sizeof (cholmod_factor), 1, Common) ; if (Common->status < CHOLMOD_OK) { return (NULL) ; /* out of memory */ } L->n = n ; L->is_ll = FALSE ; L->is_super = FALSE ; L->is_monotonic = TRUE ; L->itype = ITYPE ; L->xtype = CHOLMOD_PATTERN ; L->dtype = DTYPE ; /* allocate the purely symbolic part of L */ L->ordering = CHOLMOD_NATURAL ; L->Perm = CHOLMOD(malloc) (n, sizeof (Int), Common) ; L->IPerm = NULL ; /* only created by cholmod_solve2 when needed */ L->ColCount = CHOLMOD(malloc) (n, sizeof (Int), Common) ; /* simplicial part of L is empty */ L->nzmax = 0 ; L->p = NULL ; L->i = NULL ; L->x = NULL ; L->z = NULL ; L->nz = NULL ; L->next = NULL ; L->prev = NULL ; /* supernodal part of L is also empty */ L->nsuper = 0 ; L->ssize = 0 ; L->xsize = 0 ; L->maxesize = 0 ; L->maxcsize = 0 ; L->super = NULL ; L->pi = NULL ; L->px = NULL ; L->s = NULL ; /* L has not been factorized */ L->minor = n ; if (Common->status < CHOLMOD_OK) { CHOLMOD(free_factor) (&L, Common) ; return (NULL) ; /* out of memory */ } /* initialize Perm and ColCount */ Perm = L->Perm ; for (j = 0 ; j < ((Int) n) ; j++) { Perm [j] = j ; } ColCount = L->ColCount ; for (j = 0 ; j < ((Int) n) ; j++) { ColCount [j] = 1 ; } return (L) ; } /* ========================================================================== */ /* === cholmod_free_factor ================================================== */ /* ========================================================================== */ /* Free a factor object. * * workspace: none */ int CHOLMOD(free_factor) ( /* ---- in/out --- */ cholmod_factor **LHandle, /* factor to free, NULL on output */ /* --------------- */ cholmod_common *Common ) { Int n, lnz, xs, ss, s ; cholmod_factor *L ; RETURN_IF_NULL_COMMON (FALSE) ; if (LHandle == NULL) { /* nothing to do */ return (TRUE) ; } L = *LHandle ; if (L == NULL) { /* nothing to do */ return (TRUE) ; } n = L->n ; lnz = L->nzmax ; s = L->nsuper + 1 ; xs = (L->is_super) ? ((Int) (L->xsize)) : (lnz) ; ss = L->ssize ; /* symbolic part of L */ CHOLMOD(free) (n, sizeof (Int), L->Perm, Common) ; CHOLMOD(free) (n, sizeof (Int), L->IPerm, Common) ; CHOLMOD(free) (n, sizeof (Int), L->ColCount, Common) ; /* simplicial form of L */ CHOLMOD(free) (n+1, sizeof (Int), L->p, Common) ; CHOLMOD(free) (lnz, sizeof (Int), L->i, Common) ; CHOLMOD(free) (n, sizeof (Int), L->nz, Common) ; CHOLMOD(free) (n+2, sizeof (Int), L->next, Common) ; CHOLMOD(free) (n+2, sizeof (Int), L->prev, Common) ; /* supernodal form of L */ CHOLMOD(free) (s, sizeof (Int), L->pi, Common) ; CHOLMOD(free) (s, sizeof (Int), L->px, Common) ; CHOLMOD(free) (s, sizeof (Int), L->super, Common) ; CHOLMOD(free) (ss, sizeof (Int), L->s, Common) ; /* numerical values for both simplicial and supernodal L */ if (L->xtype == CHOLMOD_REAL) { CHOLMOD(free) (xs, sizeof (double), L->x, Common) ; } else if (L->xtype == CHOLMOD_COMPLEX) { CHOLMOD(free) (xs, 2*sizeof (double), L->x, Common) ; } else if (L->xtype == CHOLMOD_ZOMPLEX) { CHOLMOD(free) (xs, sizeof (double), L->x, Common) ; CHOLMOD(free) (xs, sizeof (double), L->z, Common) ; } *LHandle = CHOLMOD(free) (1, sizeof (cholmod_factor), (*LHandle), Common) ; return (TRUE) ; } /* ========================================================================== */ /* === cholmod_reallocate_factor ============================================ */ /* ========================================================================== */ /* Change the size of L->i and L->x, or allocate them if their current size * is zero. L must be simplicial. * * workspace: none */ int CHOLMOD(reallocate_factor) ( /* ---- input ---- */ size_t nznew, /* new # of entries in L */ /* ---- in/out --- */ cholmod_factor *L, /* factor to modify */ /* --------------- */ cholmod_common *Common ) { /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (L, FALSE) ; RETURN_IF_XTYPE_INVALID (L, CHOLMOD_REAL, CHOLMOD_ZOMPLEX, FALSE) ; PRINT1 (("realloc factor: xtype %d\n", L->xtype)) ; if (L->is_super) { /* L must be simplicial, and not symbolic */ ERROR (CHOLMOD_INVALID, "L invalid") ; return (FALSE) ; } Common->status = CHOLMOD_OK ; PRINT1 (("realloc factor %g to %g\n", (double) L->nzmax, (double) nznew)) ; /* ---------------------------------------------------------------------- */ /* resize (or allocate) the L->i and L->x components of the factor */ /* ---------------------------------------------------------------------- */ CHOLMOD(realloc_multiple) (nznew, 1, L->xtype, &(L->i), NULL, &(L->x), &(L->z), &(L->nzmax), Common) ; return (Common->status == CHOLMOD_OK) ; } /* ========================================================================== */ /* === cholmod_reallocate_column =========================================== */ /* ========================================================================== */ /* Column j needs more space, reallocate it at the end of L->i and L->x. * If the reallocation fails, the factor is converted to a simplicial * symbolic factor (no pattern, just L->Perm and L->ColCount). * * workspace: none */ int CHOLMOD(reallocate_column) ( /* ---- input ---- */ size_t j, /* the column to reallocate */ size_t need, /* required size of column j */ /* ---- in/out --- */ cholmod_factor *L, /* factor to modify */ /* --------------- */ cholmod_common *Common ) { double xneed ; double *Lx, *Lz ; Int *Lp, *Lprev, *Lnext, *Li, *Lnz ; Int n, pold, pnew, len, k, tail ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (L, FALSE) ; RETURN_IF_XTYPE_INVALID (L, CHOLMOD_REAL, CHOLMOD_ZOMPLEX, FALSE) ; if (L->is_super) { ERROR (CHOLMOD_INVALID, "L must be simplicial") ; return (FALSE) ; } n = L->n ; if (j >= L->n || need == 0) { ERROR (CHOLMOD_INVALID, "j invalid") ; return (FALSE) ; /* j out of range */ } Common->status = CHOLMOD_OK ; DEBUG (CHOLMOD(dump_factor) (L, "start colrealloc", Common)) ; /* ---------------------------------------------------------------------- */ /* increase the size of L if needed */ /* ---------------------------------------------------------------------- */ /* head = n+1 ; */ tail = n ; Lp = L->p ; Lnz = L->nz ; Lprev = L->prev ; Lnext = L->next ; ASSERT (Lnz != NULL) ; ASSERT (Lnext != NULL && Lprev != NULL) ; PRINT1 (("col %g need %g\n", (double) j, (double) need)) ; /* column j cannot have more than n-j entries if all entries are present */ need = MIN (need, n-j) ; /* compute need in double to avoid integer overflow */ if (Common->grow1 >= 1.0) { xneed = (double) need ; xneed = Common->grow1 * xneed + Common->grow2 ; xneed = MIN (xneed, n-j) ; need = (Int) xneed ; } PRINT1 (("really new need %g current %g\n", (double) need, (double) (Lp [Lnext [j]] - Lp [j]))) ; ASSERT (need >= 1 && need <= n-j) ; if (Lp [Lnext [j]] - Lp [j] >= (Int) need) { /* no need to reallocate the column, it's already big enough */ PRINT1 (("colrealloc: quick return %g %g\n", (double) (Lp [Lnext [j]] - Lp [j]), (double) need)) ; return (TRUE) ; } if (Lp [tail] + need > L->nzmax) { /* use double to avoid integer overflow */ xneed = (double) need ; if (Common->grow0 < 1.2) /* fl. pt. compare, false if NaN */ { /* if grow0 is less than 1.2 or NaN, don't use it */ xneed = 1.2 * (((double) L->nzmax) + xneed + 1) ; } else { xneed = Common->grow0 * (((double) L->nzmax) + xneed + 1) ; } if (xneed > Size_max || !CHOLMOD(reallocate_factor) ((Int) xneed, L, Common)) { /* out of memory, convert to simplicial symbolic */ CHOLMOD(change_factor) (CHOLMOD_PATTERN, L->is_ll, FALSE, TRUE, TRUE, L, Common) ; ERROR (CHOLMOD_OUT_OF_MEMORY, "out of memory; L now symbolic") ; return (FALSE) ; /* out of memory */ } PRINT1 (("\n=== GROW L from %g to %g\n", (double) L->nzmax, (double) xneed)) ; /* pack all columns so that each column has at most grow2 free space */ CHOLMOD(pack_factor) (L, Common) ; ASSERT (Common->status == CHOLMOD_OK) ; Common->nrealloc_factor++ ; } /* ---------------------------------------------------------------------- */ /* reallocate the column */ /* ---------------------------------------------------------------------- */ Common->nrealloc_col++ ; Li = L->i ; Lx = L->x ; Lz = L->z ; /* remove j from its current position in the list */ Lnext [Lprev [j]] = Lnext [j] ; Lprev [Lnext [j]] = Lprev [j] ; /* place j at the end of the list */ Lnext [Lprev [tail]] = j ; Lprev [j] = Lprev [tail] ; Lnext [j] = n ; Lprev [tail] = j ; /* L is no longer monotonic; columns are out-of-order */ L->is_monotonic = FALSE ; /* allocate space for column j */ pold = Lp [j] ; pnew = Lp [tail] ; Lp [j] = pnew ; Lp [tail] += need ; /* copy column j to the new space */ len = Lnz [j] ; for (k = 0 ; k < len ; k++) { Li [pnew + k] = Li [pold + k] ; } if (L->xtype == CHOLMOD_REAL) { for (k = 0 ; k < len ; k++) { Lx [pnew + k] = Lx [pold + k] ; } } else if (L->xtype == CHOLMOD_COMPLEX) { for (k = 0 ; k < len ; k++) { Lx [2*(pnew + k) ] = Lx [2*(pold + k) ] ; Lx [2*(pnew + k)+1] = Lx [2*(pold + k)+1] ; } } else if (L->xtype == CHOLMOD_ZOMPLEX) { for (k = 0 ; k < len ; k++) { Lx [pnew + k] = Lx [pold + k] ; Lz [pnew + k] = Lz [pold + k] ; } } DEBUG (CHOLMOD(dump_factor) (L, "colrealloc done", Common)) ; /* successful reallocation of column j of L */ return (TRUE) ; } /* ========================================================================== */ /* === cholmod_pack_factor ================================================== */ /* ========================================================================== */ /* Pack the columns of a simplicial LDL' or LL' factor. This can be followed * by a call to cholmod_reallocate_factor to reduce the size of L to the exact * size required by the factor, if desired. Alternatively, you can leave the * size of L->i and L->x the same, to allow space for future updates/rowadds. * * Each column is reduced in size so that it has at most Common->grow2 free * space at the end of the column. * * Does nothing and returns silently if given any other type of factor. * * Does NOT force the columns of L to be monotonic. It thus differs from * cholmod_change_factor (xtype, -, FALSE, TRUE, TRUE, L, Common), which * packs the columns and ensures that they appear in monotonic order. */ int CHOLMOD(pack_factor) ( /* ---- in/out --- */ cholmod_factor *L, /* factor to modify */ /* --------------- */ cholmod_common *Common ) { double *Lx, *Lz ; Int *Lp, *Li, *Lnz, *Lnext ; Int pnew, j, k, pold, len, n, head, tail, grow2 ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (L, FALSE) ; RETURN_IF_XTYPE_INVALID (L, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; Common->status = CHOLMOD_OK ; DEBUG (CHOLMOD(dump_factor) (L, "start pack", Common)) ; PRINT1 (("PACK factor %d\n", L->is_super)) ; if (L->xtype == CHOLMOD_PATTERN || L->is_super) { /* nothing to do unless L is simplicial numeric */ return (TRUE) ; } /* ---------------------------------------------------------------------- */ /* pack */ /* ---------------------------------------------------------------------- */ grow2 = Common->grow2 ; PRINT1 (("\nPACK grow2 "ID"\n", grow2)) ; pnew = 0 ; n = L->n ; Lp = L->p ; Li = L->i ; Lx = L->x ; Lz = L->z ; Lnz = L->nz ; Lnext = L->next ; head = n+1 ; tail = n ; for (j = Lnext [head] ; j != tail ; j = Lnext [j]) { /* pack column j */ pold = Lp [j] ; len = Lnz [j] ; ASSERT (len > 0) ; PRINT2 (("col "ID" pnew "ID" pold "ID"\n", j, pnew, pold)) ; if (pnew < pold) { PRINT2 ((" pack this column\n")) ; for (k = 0 ; k < len ; k++) { Li [pnew + k] = Li [pold + k] ; } if (L->xtype == CHOLMOD_REAL) { for (k = 0 ; k < len ; k++) { Lx [pnew + k] = Lx [pold + k] ; } } else if (L->xtype == CHOLMOD_COMPLEX) { for (k = 0 ; k < len ; k++) { Lx [2*(pnew + k) ] = Lx [2*(pold + k) ] ; Lx [2*(pnew + k)+1] = Lx [2*(pold + k)+1] ; } } else if (L->xtype == CHOLMOD_ZOMPLEX) { for (k = 0 ; k < len ; k++) { Lx [pnew + k] = Lx [pold + k] ; Lz [pnew + k] = Lz [pold + k] ; } } Lp [j] = pnew ; } len = MIN (len + grow2, n - j) ; pnew = MIN (Lp [j] + len, Lp [Lnext [j]]) ; } PRINT2 (("final pnew = "ID"\n", pnew)) ; return (TRUE) ; } /* ========================================================================== */ /* === cholmod_factor_to_sparse ============================================= */ /* ========================================================================== */ /* Constructs a column-oriented sparse matrix containing the pattern and values * of a simplicial or supernodal numerical factor, and then converts the factor * into a simplicial symbolic factor. If L is already packed, monotonic, * and simplicial (which is the case when cholmod_factorize uses the simplicial * Cholesky factorization algorithm) then this routine requires only O(1) * memory and takes O(1) time. * * Only operates on numeric factors (real, complex, or zomplex). Does not * change the numeric L->xtype (the resulting sparse matrix has the same xtype * as L). If this routine fails, L is left unmodified. */ cholmod_sparse *CHOLMOD(factor_to_sparse) ( /* ---- in/out --- */ cholmod_factor *L, /* factor to copy, converted to symbolic on output */ /* --------------- */ cholmod_common *Common ) { cholmod_sparse *Lsparse ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; RETURN_IF_NULL (L, NULL) ; RETURN_IF_XTYPE_INVALID (L, CHOLMOD_REAL, CHOLMOD_ZOMPLEX, NULL) ; Common->status = CHOLMOD_OK ; DEBUG (CHOLMOD(dump_factor) (L, "start convert to matrix", Common)) ; /* ---------------------------------------------------------------------- */ /* convert to packed, monotonic, simplicial, numeric */ /* ---------------------------------------------------------------------- */ /* leave as LL or LDL' */ if (!CHOLMOD(change_factor) (L->xtype, L->is_ll, FALSE, TRUE, TRUE, L, Common)) { ERROR (CHOLMOD_INVALID, "cannot convert L") ; return (NULL) ; } /* ---------------------------------------------------------------------- */ /* create Lsparse */ /* ---------------------------------------------------------------------- */ /* allocate the header for Lsparse, the sparse matrix version of L */ Lsparse = CHOLMOD(malloc) (sizeof (cholmod_sparse), 1, Common) ; if (Common->status < CHOLMOD_OK) { return (NULL) ; /* out of memory */ } /* transfer the contents from L to Lsparse */ Lsparse->nrow = L->n ; Lsparse->ncol = L->n ; Lsparse->p = L->p ; Lsparse->i = L->i ; Lsparse->x = L->x ; Lsparse->z = L->z ; Lsparse->nz = NULL ; Lsparse->stype = 0 ; Lsparse->itype = L->itype ; Lsparse->xtype = L->xtype ; Lsparse->dtype = L->dtype ; Lsparse->sorted = TRUE ; Lsparse->packed = TRUE ; Lsparse->nzmax = L->nzmax ; ASSERT (CHOLMOD(dump_sparse) (Lsparse, "Lsparse", Common) >= 0) ; /* ---------------------------------------------------------------------- */ /* convert L to symbolic, but do not free contents transfered to Lsparse */ /* ---------------------------------------------------------------------- */ L->p = NULL ; L->i = NULL ; L->x = NULL ; L->z = NULL ; L->xtype = CHOLMOD_PATTERN ; CHOLMOD(change_factor) (CHOLMOD_PATTERN, FALSE, FALSE, TRUE, TRUE, L, Common) ; return (Lsparse) ; } /* ========================================================================== */ /* === cholmod_copy_factor ================================================== */ /* ========================================================================== */ /* Create an exact copy of a factor, with one exception: * * Entries in unused space are not copied (they might not be initialized, * and copying them would cause program checkers such as purify and * valgrind to complain). * * Note that a supernodal L cannot be zomplex. */ cholmod_factor *CHOLMOD(copy_factor) ( /* ---- input ---- */ cholmod_factor *L, /* factor to copy */ /* --------------- */ cholmod_common *Common ) { cholmod_factor *L2 ; double *Lx, *L2x, *Lz, *L2z ; Int *Perm, *ColCount, *Lp, *Li, *Lnz, *Lnext, *Lprev, *Lsuper, *Lpi, *Lpx, *Ls, *Perm2, *ColCount2, *L2p, *L2i, *L2nz, *L2next, *L2prev, *L2super, *L2pi, *L2px, *L2s ; Int n, j, p, pend, s, xsize, ssize, nsuper ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; RETURN_IF_NULL (L, NULL) ; RETURN_IF_XTYPE_INVALID (L, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, NULL) ; Common->status = CHOLMOD_OK ; DEBUG (CHOLMOD(dump_factor) (L, "start copy", Common)) ; n = L->n ; /* ---------------------------------------------------------------------- */ /* allocate a simplicial symbolic factor */ /* ---------------------------------------------------------------------- */ /* allocates L2->Perm and L2->ColCount */ L2 = CHOLMOD(allocate_factor) (n, Common) ; if (Common->status < CHOLMOD_OK) { return (NULL) ; /* out of memory */ } ASSERT (L2->xtype == CHOLMOD_PATTERN && !(L2->is_super)) ; Perm = L->Perm ; ColCount = L->ColCount ; Perm2 = L2->Perm ; ColCount2 = L2->ColCount ; L2->ordering = L->ordering ; for (j = 0 ; j < n ; j++) { Perm2 [j] = Perm [j] ; } for (j = 0 ; j < n ; j++) { ColCount2 [j] = ColCount [j] ; } L2->is_ll = L->is_ll ; /* ---------------------------------------------------------------------- */ /* copy the rest of the factor */ /* ---------------------------------------------------------------------- */ if (L->xtype != CHOLMOD_PATTERN && !(L->super)) { /* ------------------------------------------------------------------ */ /* allocate a simplicial numeric factor */ /* ------------------------------------------------------------------ */ /* allocate L2->p, L2->nz, L2->prev, L2->next, L2->i, and L2->x. * packed = -1 so that cholmod_change_factor allocates space of * size L2->nzmax */ L2->nzmax = L->nzmax ; if (!CHOLMOD(change_factor) (L->xtype, L->is_ll, FALSE, -1, TRUE, L2, Common)) { CHOLMOD(free_factor) (&L2, Common) ; return (NULL) ; /* out of memory */ } ASSERT (MAX (1, L->nzmax) == L2->nzmax) ; /* ------------------------------------------------------------------ */ /* copy the contents of a simplicial numeric factor */ /* ------------------------------------------------------------------ */ Lp = L->p ; Li = L->i ; Lx = L->x ; Lz = L->z ; Lnz = L->nz ; Lnext = L->next ; Lprev = L->prev ; L2p = L2->p ; L2i = L2->i ; L2x = L2->x ; L2z = L2->z ; L2nz = L2->nz ; L2next = L2->next ; L2prev = L2->prev ; L2->xtype = L->xtype ; L2->dtype = L->dtype ; for (j = 0 ; j <= n ; j++) { L2p [j] = Lp [j] ; } for (j = 0 ; j < n+2 ; j++) { L2prev [j] = Lprev [j] ; } for (j = 0 ; j < n+2 ; j++) { L2next [j] = Lnext [j] ; } for (j = 0 ; j < n ; j++) { L2nz [j] = Lnz [j] ; } for (j = 0 ; j < n ; j++) { p = Lp [j] ; pend = p + Lnz [j] ; for ( ; p < pend ; p++) { L2i [p] = Li [p] ; } p = Lp [j] ; if (L->xtype == CHOLMOD_REAL) { for ( ; p < pend ; p++) { L2x [p] = Lx [p] ; } } else if (L->xtype == CHOLMOD_COMPLEX) { for ( ; p < pend ; p++) { L2x [2*p ] = Lx [2*p ] ; L2x [2*p+1] = Lx [2*p+1] ; } } else if (L->xtype == CHOLMOD_ZOMPLEX) { for ( ; p < pend ; p++) { L2x [p] = Lx [p] ; L2z [p] = Lz [p] ; } } } } else if (L->is_super) { /* ------------------------------------------------------------------ */ /* copy a supernodal factor */ /* ------------------------------------------------------------------ */ xsize = L->xsize ; ssize = L->ssize ; nsuper = L->nsuper ; L2->xsize = xsize ; L2->ssize = ssize ; L2->nsuper = nsuper ; /* allocate L2->super, L2->pi, L2->px, and L2->s. Allocate L2->x if * L is numeric */ if (!CHOLMOD(change_factor) (L->xtype, TRUE, TRUE, TRUE, TRUE, L2, Common)) { CHOLMOD(free_factor) (&L2, Common) ; return (NULL) ; /* out of memory */ } ASSERT (L2->s != NULL) ; /* ------------------------------------------------------------------ */ /* copy the contents of a supernodal factor */ /* ------------------------------------------------------------------ */ Lsuper = L->super ; Lpi = L->pi ; Lpx = L->px ; Ls = L->s ; Lx = L->x ; L2super = L2->super ; L2pi = L2->pi ; L2px = L2->px ; L2s = L2->s ; L2x = L2->x ; L2->maxcsize = L->maxcsize ; L2->maxesize = L->maxesize ; for (s = 0 ; s <= nsuper ; s++) { L2super [s] = Lsuper [s] ; } for (s = 0 ; s <= nsuper ; s++) { L2pi [s] = Lpi [s] ; } for (s = 0 ; s <= nsuper ; s++) { L2px [s] = Lpx [s] ; } L2s [0] = 0 ; for (p = 0 ; p < ssize ; p++) { L2s [p] = Ls [p] ; } if (L->xtype == CHOLMOD_REAL) { for (p = 0 ; p < xsize ; p++) { L2x [p] = Lx [p] ; } } else if (L->xtype == CHOLMOD_COMPLEX) { for (p = 0 ; p < 2*xsize ; p++) { L2x [p] = Lx [p] ; } } } L2->minor = L->minor ; L2->is_monotonic = L->is_monotonic ; DEBUG (CHOLMOD(dump_factor) (L2, "L2 got copied", Common)) ; ASSERT (L2->xtype == L->xtype && L2->is_super == L->is_super) ; return (L2) ; } python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Core/cholmod_version.c0000644000076500000240000000262113524616144026720 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Core/cholmod_version ================================================= */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Core Module. Copyright (C) 2005-2013, * Univ. of Florida. Author: Timothy A. Davis * The CHOLMOD/Core Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Return the current version of CHOLMOD. Unlike all other functions in CHOLMOD, this function does not require the CHOLMOD Common. */ #include "cholmod_internal.h" #include "cholmod_core.h" int CHOLMOD(version) /* returns CHOLMOD_VERSION */ ( /* output, contents not defined on input. Not used if NULL. version [0] = CHOLMOD_MAIN_VERSION ; version [1] = CHOLMOD_SUB_VERSION ; version [2] = CHOLMOD_SUBSUB_VERSION ; */ int version [3] ) { if (version != NULL) { version [0] = CHOLMOD_MAIN_VERSION ; version [1] = CHOLMOD_SUB_VERSION ; version [2] = CHOLMOD_SUBSUB_VERSION ; } return (CHOLMOD_VERSION) ; } python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Core/lesser.txt0000644000076500000240000006350013524616144025423 0ustar tamasstaff00000000000000 GNU LESSER GENERAL PUBLIC LICENSE Version 2.1, February 1999 Copyright (C) 1991, 1999 Free Software Foundation, Inc. 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed. [This is the first released version of the Lesser GPL. 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Here is a sample; alter the names: Yoyodyne, Inc., hereby disclaims all copyright interest in the library `Frob' (a library for tweaking knobs) written by James Random Hacker. , 1 April 1990 Ty Coon, President of Vice That's all there is to it! python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Core/cholmod_error.c0000644000076500000240000000531413524616144026366 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Core/cholmod_error =================================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Core Module. Copyright (C) 2005-2006, * Univ. of Florida. Author: Timothy A. Davis * The CHOLMOD/Core Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* CHOLMOD error-handling routine. */ #include "cholmod_internal.h" #include "cholmod_core.h" /* ========================================================================== */ /* ==== cholmod_error ======================================================= */ /* ========================================================================== */ /* An error has occurred. Set the status, optionally print an error message, * and call the user error-handling routine (if it exists). If * Common->try_catch is TRUE, then CHOLMOD is inside a try/catch block. * The status is set, but no message is printed and the user error handler * is not called. This is not (yet) an error, since CHOLMOD may recover. * * In the current version, this try/catch mechanism is used internally only in * cholmod_analyze, which tries multiple ordering methods and picks the best * one. If one or more ordering method fails, it keeps going. Only one * ordering needs to succeed for cholmod_analyze to succeed. */ int CHOLMOD(error) ( /* ---- input ---- */ int status, /* error status */ const char *file, /* name of source code file where error occured */ int line, /* line number in source code file where error occured*/ const char *message, /* error message */ /* --------------- */ cholmod_common *Common ) { RETURN_IF_NULL_COMMON (FALSE) ; Common->status = status ; if (!(Common->try_catch)) { #ifndef NPRINT /* print a warning or error message */ if (Common->print_function != NULL) { if (status > 0 && Common->print > 1) { (Common->print_function) ("CHOLMOD warning: %s\n", message) ; fflush (stdout) ; fflush (stderr) ; } else if (Common->print > 0) { (Common->print_function) ("CHOLMOD error: %s\n", message) ; fflush (stdout) ; fflush (stderr) ; } } #endif /* call the user error handler, if it exists */ if (Common->error_handler != NULL) { Common->error_handler (status, file, line, message) ; } } return (TRUE) ; } python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Core/t_cholmod_dense.c0000644000076500000240000001621113524616144026654 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Core/t_cholmod_dense ================================================= */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Core Module. Copyright (C) 2005-2006, * Univ. of Florida. Author: Timothy A. Davis * The CHOLMOD/Core Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Template routine for cholmod_dense. All xtypes supported, except that there * are no dense matrices with an xtype of pattern. */ #include "cholmod_template.h" /* ========================================================================== */ /* === t_cholmod_sparse_to_dense ============================================ */ /* ========================================================================== */ static cholmod_dense *TEMPLATE (cholmod_sparse_to_dense) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to copy */ /* --------------- */ cholmod_common *Common ) { double *Ax, *Xx, *Az, *Xz ; Int *Ap, *Ai, *Anz ; cholmod_dense *X ; Int i, j, p, pend, nrow, ncol, packed ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ nrow = A->nrow ; ncol = A->ncol ; packed = A->packed ; Ap = A->p ; Ai = A->i ; Ax = A->x ; Az = A->z ; Anz = A->nz ; /* ---------------------------------------------------------------------- */ /* allocate result */ /* ---------------------------------------------------------------------- */ X = CHOLMOD(zeros) (nrow, ncol, XTYPE2, Common) ; if (Common->status < CHOLMOD_OK) { return (NULL) ; /* out of memory */ } Xx = X->x ; Xz = X->z ; /* ---------------------------------------------------------------------- */ /* copy into dense matrix */ /* ---------------------------------------------------------------------- */ if (A->stype < 0) { /* A is symmetric with lower stored, but both parts of X are present */ for (j = 0 ; j < ncol ; j++) { p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { i = Ai [p] ; if (i >= j) { ASSIGN2 (Xx, Xz, i+j*nrow, Ax, Az, p) ; ASSIGN2_CONJ (Xx, Xz, j+i*nrow, Ax, Az, p) ; } } } } else if (A->stype > 0) { /* A is symmetric with upper stored, but both parts of X are present */ for (j = 0 ; j < ncol ; j++) { p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { i = Ai [p] ; if (i <= j) { ASSIGN2 (Xx, Xz, i+j*nrow, Ax, Az, p) ; ASSIGN2_CONJ (Xx, Xz, j+i*nrow, Ax, Az, p) ; } } } } else { /* both parts of A and X are present */ for (j = 0 ; j < ncol ; j++) { p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { i = Ai [p] ; ASSIGN2 (Xx, Xz, i+j*nrow, Ax, Az, p) ; } } } return (X) ; } #ifndef PATTERN /* There are no dense matrices of xtype CHOLMOD_PATTERN */ /* ========================================================================== */ /* === t_cholmod_dense_to_sparse ============================================ */ /* ========================================================================== */ static cholmod_sparse *TEMPLATE (cholmod_dense_to_sparse) ( /* ---- input ---- */ cholmod_dense *X, /* matrix to copy */ int values, /* TRUE if values to be copied, FALSE otherwise */ /* --------------- */ cholmod_common *Common ) { double *Xx, *Cx, *Xz, *Cz ; Int *Ci, *Cp ; cholmod_sparse *C ; Int i, j, p, d, nrow, ncol, nz ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ nrow = X->nrow ; ncol = X->ncol ; d = X->d ; Xx = X->x ; Xz = X->z ; /* ---------------------------------------------------------------------- */ /* count the number of nonzeros in the result */ /* ---------------------------------------------------------------------- */ nz = 0 ; for (j = 0 ; j < ncol ; j++) { for (i = 0 ; i < nrow ; i++) { if (ENTRY_IS_NONZERO (Xx, Xz, i+j*d)) { nz++ ; } } } /* ---------------------------------------------------------------------- */ /* allocate the result C */ /* ---------------------------------------------------------------------- */ C = CHOLMOD(allocate_sparse) (nrow, ncol, nz, TRUE, TRUE, 0, values ? XTYPE : CHOLMOD_PATTERN, Common) ; if (Common->status < CHOLMOD_OK) { return (NULL) ; /* out of memory */ } Cp = C->p ; Ci = C->i ; Cx = C->x ; Cz = C->z ; /* ---------------------------------------------------------------------- */ /* copy the dense matrix X into the sparse matrix C */ /* ---------------------------------------------------------------------- */ p = 0 ; for (j = 0 ; j < ncol ; j++) { Cp [j] = p ; for (i = 0 ; i < nrow ; i++) { if (ENTRY_IS_NONZERO (Xx, Xz, i+j*d)) { Ci [p] = i ; if (values) { ASSIGN (Cx, Cz, p, Xx, Xz, i+j*d) ; } p++ ; } } } ASSERT (p == nz) ; Cp [ncol] = nz ; /* ---------------------------------------------------------------------- */ /* return result */ /* ---------------------------------------------------------------------- */ ASSERT (CHOLMOD(dump_sparse) (C, "C", Common) >= 0) ; return (C) ; } /* ========================================================================== */ /* === t_cholmod_copy_dense2 ================================================ */ /* ========================================================================== */ /* Y = X, where X and Y are both already allocated. */ static int TEMPLATE (cholmod_copy_dense2) ( /* ---- input ---- */ cholmod_dense *X, /* matrix to copy */ /* ---- output --- */ cholmod_dense *Y /* copy of matrix X */ ) { double *Xx, *Xz, *Yx, *Yz ; Int i, j, nrow, ncol, dy, dx ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ Xx = X->x ; Xz = X->z ; Yx = Y->x ; Yz = Y->z ; dx = X->d ; dy = Y->d ; nrow = X->nrow ; ncol = X->ncol ; /* ---------------------------------------------------------------------- */ /* copy */ /* ---------------------------------------------------------------------- */ CLEAR (Yx, Yz, 0) ; for (j = 0 ; j < ncol ; j++) { for (i = 0 ; i < nrow ; i++) { ASSIGN (Yx, Yz, i+j*dy, Xx, Xz, i+j*dx) ; } } return (TRUE) ; } #endif #undef PATTERN #undef REAL #undef COMPLEX #undef ZOMPLEX python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Core/cholmod_aat.c0000644000076500000240000002071513524616144026004 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Core/cholmod_aat ===================================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Core Module. Copyright (C) 2005-2006, * Univ. of Florida. Author: Timothy A. Davis * The CHOLMOD/Core Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* C = A*A' or C = A(:,f)*A(:,f)' * * A can be packed or unpacked, sorted or unsorted, but must be stored with * both upper and lower parts (A->stype of zero). C is returned as packed, * C->stype of zero (both upper and lower parts present), and unsorted. See * cholmod_ssmult in the MatrixOps Module for a more general matrix-matrix * multiply. * * You can trivially convert C into a symmetric upper/lower matrix by * changing C->stype = 1 or -1 after calling this routine. * * workspace: * Flag (A->nrow), * Iwork (max (A->nrow, A->ncol)) if fset present, * Iwork (A->nrow) if no fset, * W (A->nrow) if mode > 0, * allocates temporary copy for A'. * * A can be pattern or real. Complex or zomplex cases are supported only * if the mode is <= 0 (in which case the numerical values are ignored). */ #include "cholmod_internal.h" #include "cholmod_core.h" cholmod_sparse *CHOLMOD(aat) ( /* ---- input ---- */ cholmod_sparse *A, /* input matrix; C=A*A' is constructed */ Int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ int mode, /* >0: numerical, 0: pattern, <0: pattern (no diag) * -2: pattern only, no diagonal, add 50% + n extra * space to C */ /* --------------- */ cholmod_common *Common ) { double fjt ; double *Ax, *Fx, *Cx, *W ; Int *Ap, *Anz, *Ai, *Fp, *Fi, *Cp, *Ci, *Flag ; cholmod_sparse *C, *F ; Int packed, j, i, pa, paend, pf, pfend, n, mark, cnz, t, p, values, diag, extra ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; RETURN_IF_NULL (A, NULL) ; values = (mode > 0) && (A->xtype != CHOLMOD_PATTERN) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, values ? CHOLMOD_REAL : CHOLMOD_ZOMPLEX, NULL) ; if (A->stype) { ERROR (CHOLMOD_INVALID, "matrix cannot be symmetric") ; return (NULL) ; } Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ diag = (mode >= 0) ; n = A->nrow ; CHOLMOD(allocate_work) (n, MAX (A->ncol, A->nrow), values ? n : 0, Common) ; if (Common->status < CHOLMOD_OK) { return (NULL) ; /* out of memory */ } ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, values ? n : 0, Common)) ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ ASSERT (CHOLMOD(dump_sparse) (A, "A", Common) >= 0) ; /* get the A matrix */ Ap = A->p ; Anz = A->nz ; Ai = A->i ; Ax = A->x ; packed = A->packed ; /* get workspace */ W = Common->Xwork ; /* size n, unused if values is FALSE */ Flag = Common->Flag ; /* size n, Flag [0..n-1] < mark on input*/ /* ---------------------------------------------------------------------- */ /* F = A' or A(:,f)' */ /* ---------------------------------------------------------------------- */ /* workspace: Iwork (nrow if no fset; MAX (nrow,ncol) if fset)*/ F = CHOLMOD(ptranspose) (A, values, NULL, fset, fsize, Common) ; if (Common->status < CHOLMOD_OK) { return (NULL) ; /* out of memory */ } Fp = F->p ; Fi = F->i ; Fx = F->x ; /* ---------------------------------------------------------------------- */ /* count the number of entries in the result C */ /* ---------------------------------------------------------------------- */ cnz = 0 ; for (j = 0 ; j < n ; j++) { /* clear the Flag array */ /* mark = CHOLMOD(clear_flag) (Common) ; */ CHOLMOD_CLEAR_FLAG (Common) ; mark = Common->mark ; /* exclude the diagonal, if requested */ if (!diag) { Flag [j] = mark ; } /* for each nonzero F(t,j) in column j, do: */ pfend = Fp [j+1] ; for (pf = Fp [j] ; pf < pfend ; pf++) { /* F(t,j) is nonzero */ t = Fi [pf] ; /* add the nonzero pattern of A(:,t) to the pattern of C(:,j) */ pa = Ap [t] ; paend = (packed) ? (Ap [t+1]) : (pa + Anz [t]) ; for ( ; pa < paend ; pa++) { i = Ai [pa] ; if (Flag [i] != mark) { Flag [i] = mark ; cnz++ ; } } } if (cnz < 0) { break ; /* integer overflow case */ } } extra = (mode == -2) ? (cnz/2 + n) : 0 ; mark = CHOLMOD(clear_flag) (Common) ; /* ---------------------------------------------------------------------- */ /* check for integer overflow */ /* ---------------------------------------------------------------------- */ if (cnz < 0 || (cnz + extra) < 0) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; CHOLMOD(clear_flag) (Common) ; CHOLMOD(free_sparse) (&F, Common) ; return (NULL) ; /* problem too large */ } /* ---------------------------------------------------------------------- */ /* allocate C */ /* ---------------------------------------------------------------------- */ C = CHOLMOD(allocate_sparse) (n, n, cnz + extra, FALSE, TRUE, 0, values ? A->xtype : CHOLMOD_PATTERN, Common) ; if (Common->status < CHOLMOD_OK) { CHOLMOD(free_sparse) (&F, Common) ; return (NULL) ; /* out of memory */ } Cp = C->p ; Ci = C->i ; Cx = C->x ; /* ---------------------------------------------------------------------- */ /* C = A*A' */ /* ---------------------------------------------------------------------- */ cnz = 0 ; if (values) { /* pattern and values */ for (j = 0 ; j < n ; j++) { /* clear the Flag array */ mark = CHOLMOD(clear_flag) (Common) ; /* start column j of C */ Cp [j] = cnz ; /* for each nonzero F(t,j) in column j, do: */ pfend = Fp [j+1] ; for (pf = Fp [j] ; pf < pfend ; pf++) { /* F(t,j) is nonzero */ t = Fi [pf] ; fjt = Fx [pf] ; /* add the nonzero pattern of A(:,t) to the pattern of C(:,j) * and scatter the values into W */ pa = Ap [t] ; paend = (packed) ? (Ap [t+1]) : (pa + Anz [t]) ; for ( ; pa < paend ; pa++) { i = Ai [pa] ; if (Flag [i] != mark) { Flag [i] = mark ; Ci [cnz++] = i ; } W [i] += Ax [pa] * fjt ; } } /* gather the values into C(:,j) */ for (p = Cp [j] ; p < cnz ; p++) { i = Ci [p] ; Cx [p] = W [i] ; W [i] = 0 ; } } } else { /* pattern only */ for (j = 0 ; j < n ; j++) { /* clear the Flag array */ mark = CHOLMOD(clear_flag) (Common) ; /* exclude the diagonal, if requested */ if (!diag) { Flag [j] = mark ; } /* start column j of C */ Cp [j] = cnz ; /* for each nonzero F(t,j) in column j, do: */ pfend = Fp [j+1] ; for (pf = Fp [j] ; pf < pfend ; pf++) { /* F(t,j) is nonzero */ t = Fi [pf] ; /* add the nonzero pattern of A(:,t) to the pattern of C(:,j) */ pa = Ap [t] ; paend = (packed) ? (Ap [t+1]) : (pa + Anz [t]) ; for ( ; pa < paend ; pa++) { i = Ai [pa] ; if (Flag [i] != mark) { Flag [i] = mark ; Ci [cnz++] = i ; } } } } } Cp [n] = cnz ; ASSERT (IMPLIES (mode != -2, MAX (1,cnz) == C->nzmax)) ; /* ---------------------------------------------------------------------- */ /* clear workspace and free temporary matrices and return result */ /* ---------------------------------------------------------------------- */ CHOLMOD(free_sparse) (&F, Common) ; CHOLMOD(clear_flag) (Common) ; ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, values ? n : 0, Common)) ; DEBUG (i = CHOLMOD(dump_sparse) (C, "aat", Common)) ; ASSERT (IMPLIES (mode < 0, i == 0)) ; return (C) ; } python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Core/t_cholmod_transpose.c0000644000076500000240000002124413524616144027576 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Core/t_cholmod_transpose ============================================= */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Core Module. Copyright (C) 2005-2006, * Univ. of Florida. Author: Timothy A. Davis * The CHOLMOD/Core Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Template routine for cholmod_transpose. All xtypes are supported. For * complex matrices, either the array tranpose or complex conjugate transpose * can be computed. */ #include "cholmod_template.h" /* ========================================================================== */ /* === t_cholmod_transpose_unsym ============================================ */ /* ========================================================================== */ /* Compute F = A', A (:,f)', or A (p,f)', where A is unsymmetric and F is * already allocated. The complex case performs either the array transpose * or complex conjugate transpose. * * workspace: * Iwork (MAX (nrow,ncol)) if fset is present * Iwork (nrow) if fset is NULL */ static int TEMPLATE (cholmod_transpose_unsym) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to transpose */ Int *Perm, /* size nrow, if present (can be NULL) */ Int *fset, /* subset of 0:(A->ncol)-1 */ Int nf, /* size of fset */ /* ---- output --- */ cholmod_sparse *F, /* F = A', A(:,f)', or A(p,f)' */ /* --------------- */ cholmod_common *Common ) { double *Ax, *Az, *Fx, *Fz ; Int *Ap, *Anz, *Ai, *Fp, *Fnz, *Fj, *Wi, *Iwork ; Int j, p, pend, nrow, ncol, Apacked, use_fset, fp, Fpacked, jj, permute ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ /* ensure the xtype of A and F match (ignored if this is pattern version) */ if (!XTYPE_OK (A->xtype)) { ERROR (CHOLMOD_INVALID, "real/complex mismatch") ; return (FALSE) ; } /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ use_fset = (fset != NULL) ; nrow = A->nrow ; ncol = A->ncol ; Ap = A->p ; /* size A->ncol+1, column pointers of A */ Ai = A->i ; /* size nz = Ap [A->ncol], row indices of A */ Ax = A->x ; /* size nz, real values of A */ Az = A->z ; /* size nz, imag values of A */ Anz = A->nz ; Apacked = A->packed ; ASSERT (IMPLIES (!Apacked, Anz != NULL)) ; permute = (Perm != NULL) ; Fp = F->p ; /* size A->nrow+1, row pointers of F */ Fj = F->i ; /* size nz, column indices of F */ Fx = F->x ; /* size nz, real values of F */ Fz = F->z ; /* size nz, imag values of F */ Fnz = F->nz ; Fpacked = F->packed ; ASSERT (IMPLIES (!Fpacked, Fnz != NULL)) ; nf = (use_fset) ? nf : ncol ; /* ---------------------------------------------------------------------- */ /* get workspace */ /* ---------------------------------------------------------------------- */ Iwork = Common->Iwork ; Wi = Iwork ; /* size nrow (i/l/l) */ /* ---------------------------------------------------------------------- */ /* construct the transpose */ /* ---------------------------------------------------------------------- */ for (jj = 0 ; jj < nf ; jj++) { j = (use_fset) ? (fset [jj]) : jj ; p = Ap [j] ; pend = (Apacked) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { fp = Wi [Ai [p]]++ ; Fj [fp] = j ; #ifdef NCONJUGATE ASSIGN (Fx, Fz, fp, Ax, Az, p) ; #else ASSIGN_CONJ (Fx, Fz, fp, Ax, Az, p) ; #endif } } return (TRUE) ; } /* ========================================================================== */ /* === t_cholmod_transpose_sym ============================================== */ /* ========================================================================== */ /* Compute F = A' or A (p,p)', where A is symmetric and F is already allocated. * The complex case performs either the array transpose or complex conjugate * transpose. * * workspace: Iwork (nrow) if Perm NULL, Iwork (2*nrow) if Perm non-NULL. */ static int TEMPLATE (cholmod_transpose_sym) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to transpose */ Int *Perm, /* size n, if present (can be NULL) */ /* ---- output --- */ cholmod_sparse *F, /* F = A' or A(p,p)' */ /* --------------- */ cholmod_common *Common ) { double *Ax, *Az, *Fx, *Fz ; Int *Ap, *Anz, *Ai, *Fp, *Fj, *Wi, *Pinv, *Iwork ; Int p, pend, packed, fp, upper, permute, jold, n, i, j, iold ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ /* ensure the xtype of A and F match (ignored if this is pattern version) */ if (!XTYPE_OK (A->xtype)) { ERROR (CHOLMOD_INVALID, "real/complex mismatch") ; return (FALSE) ; } /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ permute = (Perm != NULL) ; n = A->nrow ; Ap = A->p ; /* size A->ncol+1, column pointers of A */ Ai = A->i ; /* size nz = Ap [A->ncol], row indices of A */ Ax = A->x ; /* size nz, real values of A */ Az = A->z ; /* size nz, imag values of A */ Anz = A->nz ; packed = A->packed ; ASSERT (IMPLIES (!packed, Anz != NULL)) ; upper = (A->stype > 0) ; Fp = F->p ; /* size A->nrow+1, row pointers of F */ Fj = F->i ; /* size nz, column indices of F */ Fx = F->x ; /* size nz, real values of F */ Fz = F->z ; /* size nz, imag values of F */ /* ---------------------------------------------------------------------- */ /* get workspace */ /* ---------------------------------------------------------------------- */ Iwork = Common->Iwork ; Wi = Iwork ; /* size n (i/l/l) */ Pinv = Iwork + n ; /* size n (i/i/l) , unused if Perm NULL */ /* ---------------------------------------------------------------------- */ /* construct the transpose */ /* ---------------------------------------------------------------------- */ if (permute) { if (upper) { /* permuted, upper */ for (j = 0 ; j < n ; j++) { jold = Perm [j] ; p = Ap [jold] ; pend = (packed) ? Ap [jold+1] : p + Anz [jold] ; for ( ; p < pend ; p++) { iold = Ai [p] ; if (iold <= jold) { i = Pinv [iold] ; if (i < j) { fp = Wi [i]++ ; Fj [fp] = j ; #ifdef NCONJUGATE ASSIGN (Fx, Fz, fp, Ax, Az, p) ; #else ASSIGN_CONJ (Fx, Fz, fp, Ax, Az, p) ; #endif } else { fp = Wi [j]++ ; Fj [fp] = i ; ASSIGN (Fx, Fz, fp, Ax, Az, p) ; } } } } } else { /* permuted, lower */ for (j = 0 ; j < n ; j++) { jold = Perm [j] ; p = Ap [jold] ; pend = (packed) ? Ap [jold+1] : p + Anz [jold] ; for ( ; p < pend ; p++) { iold = Ai [p] ; if (iold >= jold) { i = Pinv [iold] ; if (i > j) { fp = Wi [i]++ ; Fj [fp] = j ; #ifdef NCONJUGATE ASSIGN (Fx, Fz, fp, Ax, Az, p) ; #else ASSIGN_CONJ (Fx, Fz, fp, Ax, Az, p) ; #endif } else { fp = Wi [j]++ ; Fj [fp] = i ; ASSIGN (Fx, Fz, fp, Ax, Az, p) ; } } } } } } else { if (upper) { /* unpermuted, upper */ for (j = 0 ; j < n ; j++) { p = Ap [j] ; pend = (packed) ? Ap [j+1] : p + Anz [j] ; for ( ; p < pend ; p++) { i = Ai [p] ; if (i <= j) { fp = Wi [i]++ ; Fj [fp] = j ; #ifdef NCONJUGATE ASSIGN (Fx, Fz, fp, Ax, Az, p) ; #else ASSIGN_CONJ (Fx, Fz, fp, Ax, Az, p) ; #endif } } } } else { /* unpermuted, lower */ for (j = 0 ; j < n ; j++) { p = Ap [j] ; pend = (packed) ? Ap [j+1] : p + Anz [j] ; for ( ; p < pend ; p++) { i = Ai [p] ; if (i >= j) { fp = Wi [i]++ ; Fj [fp] = j ; #ifdef NCONJUGATE ASSIGN (Fx, Fz, fp, Ax, Az, p) ; #else ASSIGN_CONJ (Fx, Fz, fp, Ax, Az, p) ; #endif } } } } } return (TRUE) ; } #undef PATTERN #undef REAL #undef COMPLEX #undef ZOMPLEX #undef NCONJUGATE python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Core/License.txt0000644000076500000240000000207213524616144025505 0ustar tamasstaff00000000000000CHOLMOD/Core Module. Copyright (C) 2005-2006, Univ. of Florida. Author: Timothy A. Davis CHOLMOD is also available under other licenses; contact authors for details. http://www.suitesparse.com Note that this license is for the CHOLMOD/Core module only. All CHOLMOD modules are licensed separately. -------------------------------------------------------------------------------- This Module is free software; you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation; either version 2.1 of the License, or (at your option) any later version. This Module is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with this Module; if not, write to the Free Software Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Core/cholmod_band.c0000644000076500000240000002332013524616144026136 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Core/cholmod_band ==================================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Core Module. Copyright (C) 2005-2006, * Univ. of Florida. Author: Timothy A. Davis * The CHOLMOD/Core Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* C = tril (triu (A,k1), k2) * * C is a matrix consisting of the diagonals of A from k1 to k2. * * k=0 is the main diagonal of A, k=1 is the superdiagonal, k=-1 is the * subdiagonal, and so on. If A is m-by-n, then: * * k1=-m C = tril (A,k2) * k2=n C = triu (A,k1) * k1=0 and k2=0 C = diag(A), except C is a matrix, not a vector * * Values of k1 and k2 less than -m are treated as -m, and values greater * than n are treated as n. * * A can be of any symmetry (upper, lower, or unsymmetric); C is returned in * the same form, and packed. If A->stype > 0, entries in the lower * triangular part of A are ignored, and the opposite is true if * A->stype < 0. If A has sorted columns, then so does C. * C has the same size as A. * * If inplace is TRUE, then the matrix A is modified in place. * Only packed matrices can be converted in place. * * C can be returned as a numerical valued matrix (if A has numerical values * and mode > 0), as a pattern-only (mode == 0), or as a pattern-only but with * the diagonal entries removed (mode < 0). * * workspace: none * * A can have an xtype of pattern or real. Complex and zomplex cases supported * only if mode <= 0 (in which case the numerical values are ignored). */ #include "cholmod_internal.h" #include "cholmod_core.h" static cholmod_sparse *band /* returns C, or NULL if failure */ ( /* ---- input or in/out if inplace is TRUE --- */ cholmod_sparse *A, /* ---- input ---- */ SuiteSparse_long k1, /* ignore entries below the k1-st diagonal */ SuiteSparse_long k2, /* ignore entries above the k2-nd diagonal */ int mode, /* >0: numerical, 0: pattern, <0: pattern (no diagonal) */ int inplace, /* if TRUE, then convert A in place */ /* --------------- */ cholmod_common *Common ) { double *Ax, *Cx ; Int packed, nz, j, p, pend, i, ncol, nrow, jlo, jhi, ilo, ihi, sorted, values, diag ; Int *Ap, *Anz, *Ai, *Cp, *Ci ; cholmod_sparse *C ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; RETURN_IF_NULL (A, NULL) ; values = (mode > 0) && (A->xtype != CHOLMOD_PATTERN) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, values ? CHOLMOD_REAL : CHOLMOD_ZOMPLEX, NULL) ; packed = A->packed ; diag = (mode >= 0) ; if (inplace && !packed) { /* cannot operate on an unpacked matrix in place */ ERROR (CHOLMOD_INVALID, "cannot operate on unpacked matrix in-place") ; return (NULL) ; } Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ PRINT1 (("k1 %ld k2 %ld\n", k1, k2)) ; Ap = A->p ; Anz = A->nz ; Ai = A->i ; Ax = A->x ; sorted = A->sorted ; if (A->stype > 0) { /* ignore any entries in strictly lower triangular part of A */ k1 = MAX (k1, 0) ; } if (A->stype < 0) { /* ignore any entries in strictly upper triangular part of A */ k2 = MIN (k2, 0) ; } ncol = A->ncol ; nrow = A->nrow ; /* ensure k1 and k2 are in the range -nrow to +ncol to * avoid possible integer overflow if k1 and k2 are huge */ k1 = MAX (-nrow, k1) ; k1 = MIN (k1, ncol) ; k2 = MAX (-nrow, k2) ; k2 = MIN (k2, ncol) ; /* consider columns jlo to jhi. columns outside this range are empty */ jlo = MAX (k1, 0) ; jhi = MIN (k2+nrow, ncol) ; if (k1 > k2) { /* nothing to do */ jlo = ncol ; jhi = ncol ; } /* ---------------------------------------------------------------------- */ /* allocate C, or operate on A in place */ /* ---------------------------------------------------------------------- */ if (inplace) { /* convert A in place */ C = A ; } else { /* count the number of entries in the result C */ nz = 0 ; if (sorted) { for (j = jlo ; j < jhi ; j++) { ilo = j-k2 ; ihi = j-k1 ; p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { i = Ai [p] ; if (i > ihi) { break ; } if (i >= ilo && (diag || i != j)) { nz++ ; } } } } else { for (j = jlo ; j < jhi ; j++) { ilo = j-k2 ; ihi = j-k1 ; p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { i = Ai [p] ; if (i >= ilo && i <= ihi && (diag || i != j)) { nz++ ; } } } } /* allocate C; A will not be modified. C is sorted if A is sorted */ C = CHOLMOD(allocate_sparse) (A->nrow, ncol, nz, sorted, TRUE, A->stype, values ? A->xtype : CHOLMOD_PATTERN, Common) ; if (Common->status < CHOLMOD_OK) { return (NULL) ; /* out of memory */ } } Cp = C->p ; Ci = C->i ; Cx = C->x ; /* ---------------------------------------------------------------------- */ /* construct C */ /* ---------------------------------------------------------------------- */ /* columns 0 to jlo-1 are empty */ for (j = 0 ; j < jlo ; j++) { Cp [j] = 0 ; } nz = 0 ; if (sorted) { if (values) { /* pattern and values */ ASSERT (diag) ; for (j = jlo ; j < jhi ; j++) { ilo = j-k2 ; ihi = j-k1 ; p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; Cp [j] = nz ; for ( ; p < pend ; p++) { i = Ai [p] ; if (i > ihi) { break ; } if (i >= ilo) { Ci [nz] = i ; Cx [nz] = Ax [p] ; nz++ ; } } } } else { /* pattern only, perhaps with no diagonal */ for (j = jlo ; j < jhi ; j++) { ilo = j-k2 ; ihi = j-k1 ; p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; Cp [j] = nz ; for ( ; p < pend ; p++) { i = Ai [p] ; if (i > ihi) { break ; } if (i >= ilo && (diag || i != j)) { Ci [nz++] = i ; } } } } } else { if (values) { /* pattern and values */ ASSERT (diag) ; for (j = jlo ; j < jhi ; j++) { ilo = j-k2 ; ihi = j-k1 ; p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; Cp [j] = nz ; for ( ; p < pend ; p++) { i = Ai [p] ; if (i >= ilo && i <= ihi) { Ci [nz] = i ; Cx [nz] = Ax [p] ; nz++ ; } } } } else { /* pattern only, perhaps with no diagonal */ for (j = jlo ; j < jhi ; j++) { ilo = j-k2 ; ihi = j-k1 ; p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; Cp [j] = nz ; for ( ; p < pend ; p++) { i = Ai [p] ; if (i >= ilo && i <= ihi && (diag || i != j)) { Ci [nz++] = i ; } } } } } /* columns jhi to ncol-1 are empty */ for (j = jhi ; j <= ncol ; j++) { Cp [j] = nz ; } /* ---------------------------------------------------------------------- */ /* reduce A in size if done in place */ /* ---------------------------------------------------------------------- */ if (inplace) { /* free the unused parts of A, and reduce A->i and A->x in size */ ASSERT (MAX (1,nz) <= A->nzmax) ; CHOLMOD(reallocate_sparse) (nz, A, Common) ; ASSERT (Common->status >= CHOLMOD_OK) ; } /* ---------------------------------------------------------------------- */ /* return the result C */ /* ---------------------------------------------------------------------- */ DEBUG (i = CHOLMOD(dump_sparse) (C, "band", Common)) ; ASSERT (IMPLIES (mode < 0, i == 0)) ; return (C) ; } /* ========================================================================== */ /* === cholmod_band ========================================================= */ /* ========================================================================== */ cholmod_sparse *CHOLMOD(band) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to extract band matrix from */ SuiteSparse_long k1, /* ignore entries below the k1-st diagonal */ SuiteSparse_long k2, /* ignore entries above the k2-nd diagonal */ int mode, /* >0: numerical, 0: pattern, <0: pattern (no diag) */ /* --------------- */ cholmod_common *Common ) { return (band (A, k1, k2, mode, FALSE, Common)) ; } /* ========================================================================== */ /* === cholmod_band_inplace ================================================= */ /* ========================================================================== */ int CHOLMOD(band_inplace) ( /* ---- input ---- */ SuiteSparse_long k1, /* ignore entries below the k1-st diagonal */ SuiteSparse_long k2, /* ignore entries above the k2-nd diagonal */ int mode, /* >0: numerical, 0: pattern, <0: pattern (no diag) */ /* ---- in/out --- */ cholmod_sparse *A, /* matrix from which entries not in band are removed */ /* --------------- */ cholmod_common *Common ) { return (band (A, k1, k2, mode, TRUE, Common) != NULL) ; } python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Makefile0000644000076500000240000000372513524616144024140 0ustar tamasstaff00000000000000#------------------------------------------------------------------------------- # CHOLMOD Makefile #------------------------------------------------------------------------------- VERSION = 2.1.2 # Note: If you do not have METIS, or do not wish to use it in CHOLMOD, you must # compile CHOLMOD with the -DNPARTITION flag. # See ../SuiteSparse_config/SuiteSparse_config.mk . default: all include ../SuiteSparse_config/SuiteSparse_config.mk # Compile the C-callable libraries and the Demo programs. all: ( cd Demo ; $(MAKE) ) # Compile the C-callable libraries only. library: ( cd Lib ; $(MAKE) ) # Remove all files not in the original distribution purge: ( cd Tcov ; $(MAKE) purge ) ( cd Lib ; $(MAKE) purge ) ( cd Valgrind ; $(MAKE) dopurge ) ( cd Demo ; $(MAKE) purge ) ( cd Doc ; $(MAKE) purge ) ( cd MATLAB ; $(RM) $(CLEAN) rename.h *.mex* ) # Remove all files not in the original distribution, except keep the # compiled libraries. clean: ( cd Tcov ; $(MAKE) clean ) ( cd Lib ; $(MAKE) clean ) ( cd Valgrind ; $(MAKE) clean ) ( cd Demo ; $(MAKE) clean ) ( cd MATLAB ; $(RM) $(CLEAN) ) distclean: purge ccode: all # Run the test coverage suite. Takes about 40 minutes on a 3.2GHz Pentium. # Requires Linux (gcc, gcov). cov: ( cd Tcov ; $(MAKE) ) # Run the test coverage suite using Valgrind. This takes a *** long *** time. valgrind: ( cd Valgrind ; $(MAKE) ) # Compile the C-callable libraries and the Demo programs. demos: ( cd Demo ; $(MAKE) ) # create PDF documents for the original distribution docs: ( cd Doc ; $(MAKE) ) # install CHOLMOD install: $(CP) Lib/libcholmod.a $(INSTALL_LIB)/libcholmod.$(VERSION).a ( cd $(INSTALL_LIB) ; ln -sf libcholmod.$(VERSION).a libcholmod.a ) $(CP) Include/cholmod*.h $(INSTALL_INCLUDE) $(RM) $(INSTALL_INCLUDE)/cholmod_internal.h chmod 644 $(INSTALL_LIB)/libcholmod*.a chmod 644 $(INSTALL_INCLUDE)/cholmod*.h # uninstall CHOLMOD uninstall: $(RM) $(INSTALL_LIB)/libcholmod*.a $(RM) $(INSTALL_INCLUDE)/cholmod*.h python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Include/0000755000076500000240000000000013617375001024051 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Include/cholmod_supernodal.h0000644000076500000240000001445013524616144030112 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Include/cholmod_supernodal.h ========================================= */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Include/cholmod_supernodal.h. * Copyright (C) 2005-2006, Timothy A. Davis * CHOLMOD/Include/cholmod_supernodal.h is licensed under Version 2.0 of the GNU * General Public License. See gpl.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * http://www.suitesparse.com * -------------------------------------------------------------------------- */ /* CHOLMOD Supernodal module. * * Supernodal analysis, factorization, and solve. The simplest way to use * these routines is via the Cholesky module. It does not provide any * fill-reducing orderings, but does accept the orderings computed by the * Cholesky module. It does not require the Cholesky module itself, however. * * Primary routines: * ----------------- * cholmod_super_symbolic supernodal symbolic analysis * cholmod_super_numeric supernodal numeric factorization * cholmod_super_lsolve supernodal Lx=b solve * cholmod_super_ltsolve supernodal L'x=b solve * * Prototypes for the BLAS and LAPACK routines that CHOLMOD uses are listed * below, including how they are used in CHOLMOD. * * BLAS routines: * -------------- * dtrsv solve Lx=b or L'x=b, L non-unit diagonal, x and b stride-1 * dtrsm solve LX=B or L'X=b, L non-unit diagonal * dgemv y=y-A*x or y=y-A'*x (x and y stride-1) * dgemm C=A*B', C=C-A*B, or C=C-A'*B * dsyrk C=tril(A*A') * * LAPACK routines: * ---------------- * dpotrf LAPACK: A=chol(tril(A)) * * Requires the Core module, and two external packages: LAPACK and the BLAS. * Optionally used by the Cholesky module. */ #ifndef CHOLMOD_SUPERNODAL_H #define CHOLMOD_SUPERNODAL_H #include "cholmod_core.h" /* -------------------------------------------------------------------------- */ /* cholmod_super_symbolic */ /* -------------------------------------------------------------------------- */ /* Analyzes A, AA', or A(:,f)*A(:,f)' in preparation for a supernodal numeric * factorization. The user need not call this directly; cholmod_analyze is * a "simple" wrapper for this routine. */ int cholmod_super_symbolic ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to analyze */ cholmod_sparse *F, /* F = A' or A(:,f)' */ int *Parent, /* elimination tree */ /* ---- in/out --- */ cholmod_factor *L, /* simplicial symbolic on input, * supernodal symbolic on output */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_super_symbolic (cholmod_sparse *, cholmod_sparse *, SuiteSparse_long *, cholmod_factor *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_super_symbolic2 */ /* -------------------------------------------------------------------------- */ /* Analyze for supernodal Cholesky or multifrontal QR. CHOLMOD itself always * analyzes for supernodal Cholesky, of course. This "for_cholesky = TRUE" * option is used by SuiteSparseQR only. Added for V1.7 */ int cholmod_super_symbolic2 ( /* ---- input ---- */ int for_cholesky, /* Cholesky if TRUE, QR if FALSE */ cholmod_sparse *A, /* matrix to analyze */ cholmod_sparse *F, /* F = A' or A(:,f)' */ int *Parent, /* elimination tree */ /* ---- in/out --- */ cholmod_factor *L, /* simplicial symbolic on input, * supernodal symbolic on output */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_super_symbolic2 (int, cholmod_sparse *, cholmod_sparse *, SuiteSparse_long *, cholmod_factor *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_super_numeric */ /* -------------------------------------------------------------------------- */ /* Computes the numeric LL' factorization of A, AA', or A(:,f)*A(:,f)' using * a BLAS-based supernodal method. The user need not call this directly; * cholmod_factorize is a "simple" wrapper for this routine. */ int cholmod_super_numeric ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to factorize */ cholmod_sparse *F, /* F = A' or A(:,f)' */ double beta [2], /* beta*I is added to diagonal of matrix to factorize */ /* ---- in/out --- */ cholmod_factor *L, /* factorization */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_super_numeric (cholmod_sparse *, cholmod_sparse *, double *, cholmod_factor *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_super_lsolve */ /* -------------------------------------------------------------------------- */ /* Solve Lx=b where L is from a supernodal numeric factorization. The user * need not call this routine directly. cholmod_solve is a "simple" wrapper * for this routine. */ int cholmod_super_lsolve ( /* ---- input ---- */ cholmod_factor *L, /* factor to use for the forward solve */ /* ---- output ---- */ cholmod_dense *X, /* b on input, solution to Lx=b on output */ /* ---- workspace */ cholmod_dense *E, /* workspace of size nrhs*(L->maxesize) */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_super_lsolve (cholmod_factor *, cholmod_dense *, cholmod_dense *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_super_ltsolve */ /* -------------------------------------------------------------------------- */ /* Solve L'x=b where L is from a supernodal numeric factorization. The user * need not call this routine directly. cholmod_solve is a "simple" wrapper * for this routine. */ int cholmod_super_ltsolve ( /* ---- input ---- */ cholmod_factor *L, /* factor to use for the backsolve */ /* ---- output ---- */ cholmod_dense *X, /* b on input, solution to L'x=b on output */ /* ---- workspace */ cholmod_dense *E, /* workspace of size nrhs*(L->maxesize) */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_super_ltsolve (cholmod_factor *, cholmod_dense *, cholmod_dense *, cholmod_common *) ; #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Include/cholmod_modify.h0000644000076500000240000003132113524616144027221 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Include/cholmod_modify.h ============================================= */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Include/cholmod_modify.h. * Copyright (C) 2005-2006, Timothy A. Davis and William W. Hager * CHOLMOD/Include/cholmod_modify.h is licensed under Version 2.0 of the GNU * General Public License. See gpl.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * http://www.suitesparse.com * -------------------------------------------------------------------------- */ /* CHOLMOD Modify module. * * Sparse Cholesky modification routines: update / downdate / rowadd / rowdel. * Can also modify a corresponding solution to Lx=b when L is modified. This * module is most useful when applied on a Cholesky factorization computed by * the Cholesky module, but it does not actually require the Cholesky module. * The Core module can create an identity Cholesky factorization (LDL' where * L=D=I) that can then by modified by these routines. * * Primary routines: * ----------------- * * cholmod_updown multiple rank update/downdate * cholmod_rowadd add a row to an LDL' factorization * cholmod_rowdel delete a row from an LDL' factorization * * Secondary routines: * ------------------- * * cholmod_updown_solve update/downdate, and modify solution to Lx=b * cholmod_updown_mark update/downdate, and modify solution to partial Lx=b * cholmod_updown_mask update/downdate for LPDASA * cholmod_rowadd_solve add a row, and update solution to Lx=b * cholmod_rowadd_mark add a row, and update solution to partial Lx=b * cholmod_rowdel_solve delete a row, and downdate Lx=b * cholmod_rowdel_mark delete a row, and downdate solution to partial Lx=b * * Requires the Core module. Not required by any other CHOLMOD module. */ #ifndef CHOLMOD_MODIFY_H #define CHOLMOD_MODIFY_H #include "cholmod_core.h" /* -------------------------------------------------------------------------- */ /* cholmod_updown: multiple rank update/downdate */ /* -------------------------------------------------------------------------- */ /* Compute the new LDL' factorization of LDL'+CC' (an update) or LDL'-CC' * (a downdate). The factor object L need not be an LDL' factorization; it * is converted to one if it isn't. */ int cholmod_updown ( /* ---- input ---- */ int update, /* TRUE for update, FALSE for downdate */ cholmod_sparse *C, /* the incoming sparse update */ /* ---- in/out --- */ cholmod_factor *L, /* factor to modify */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_updown (int, cholmod_sparse *, cholmod_factor *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_updown_solve: update/downdate, and modify solution to Lx=b */ /* -------------------------------------------------------------------------- */ /* Does the same as cholmod_updown, except that it also updates/downdates the * solution to Lx=b+DeltaB. x and b must be n-by-1 dense matrices. b is not * need as input to this routine, but a sparse change to b is (DeltaB). Only * entries in DeltaB corresponding to columns modified in L are accessed; the * rest must be zero. */ int cholmod_updown_solve ( /* ---- input ---- */ int update, /* TRUE for update, FALSE for downdate */ cholmod_sparse *C, /* the incoming sparse update */ /* ---- in/out --- */ cholmod_factor *L, /* factor to modify */ cholmod_dense *X, /* solution to Lx=b (size n-by-1) */ cholmod_dense *DeltaB, /* change in b, zero on output */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_updown_solve (int, cholmod_sparse *, cholmod_factor *, cholmod_dense *, cholmod_dense *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_updown_mark: update/downdate, and modify solution to partial Lx=b */ /* -------------------------------------------------------------------------- */ /* Does the same as cholmod_updown_solve, except only part of L is used in * the update/downdate of the solution to Lx=b. This routine is an "expert" * routine. It is meant for use in LPDASA only. See cholmod_updown.c for * a description of colmark. */ int cholmod_updown_mark ( /* ---- input ---- */ int update, /* TRUE for update, FALSE for downdate */ cholmod_sparse *C, /* the incoming sparse update */ int *colmark, /* int array of size n. See cholmod_updown.c */ /* ---- in/out --- */ cholmod_factor *L, /* factor to modify */ cholmod_dense *X, /* solution to Lx=b (size n-by-1) */ cholmod_dense *DeltaB, /* change in b, zero on output */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_updown_mark (int, cholmod_sparse *, SuiteSparse_long *, cholmod_factor *, cholmod_dense *, cholmod_dense *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_updown_mask: update/downdate, for LPDASA */ /* -------------------------------------------------------------------------- */ /* Does the same as cholmod_updown_mark, except has an additional "mask" * argument. This routine is an "expert" routine. It is meant for use in * LPDASA only. See cholmod_updown.c for a description of mask. */ int cholmod_updown_mask ( /* ---- input ---- */ int update, /* TRUE for update, FALSE for downdate */ cholmod_sparse *C, /* the incoming sparse update */ int *colmark, /* int array of size n. See cholmod_updown.c */ int *mask, /* size n */ /* ---- in/out --- */ cholmod_factor *L, /* factor to modify */ cholmod_dense *X, /* solution to Lx=b (size n-by-1) */ cholmod_dense *DeltaB, /* change in b, zero on output */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_updown_mask (int, cholmod_sparse *, SuiteSparse_long *, SuiteSparse_long *, cholmod_factor *, cholmod_dense *, cholmod_dense *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_rowadd: add a row to an LDL' factorization (a rank-2 update) */ /* -------------------------------------------------------------------------- */ /* cholmod_rowadd adds a row to the LDL' factorization. It computes the kth * row and kth column of L, and then updates the submatrix L (k+1:n,k+1:n) * accordingly. The kth row and column of L must originally be equal to the * kth row and column of the identity matrix. The kth row/column of L is * computed as the factorization of the kth row/column of the matrix to * factorize, which is provided as a single n-by-1 sparse matrix R. */ int cholmod_rowadd ( /* ---- input ---- */ size_t k, /* row/column index to add */ cholmod_sparse *R, /* row/column of matrix to factorize (n-by-1) */ /* ---- in/out --- */ cholmod_factor *L, /* factor to modify */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_rowadd (size_t, cholmod_sparse *, cholmod_factor *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_rowadd_solve: add a row, and update solution to Lx=b */ /* -------------------------------------------------------------------------- */ /* Does the same as cholmod_rowadd, and also updates the solution to Lx=b * See cholmod_updown for a description of how Lx=b is updated. There is on * additional parameter: bk specifies the new kth entry of b. */ int cholmod_rowadd_solve ( /* ---- input ---- */ size_t k, /* row/column index to add */ cholmod_sparse *R, /* row/column of matrix to factorize (n-by-1) */ double bk [2], /* kth entry of the right-hand-side b */ /* ---- in/out --- */ cholmod_factor *L, /* factor to modify */ cholmod_dense *X, /* solution to Lx=b (size n-by-1) */ cholmod_dense *DeltaB, /* change in b, zero on output */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_rowadd_solve (size_t, cholmod_sparse *, double *, cholmod_factor *, cholmod_dense *, cholmod_dense *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_rowadd_mark: add a row, and update solution to partial Lx=b */ /* -------------------------------------------------------------------------- */ /* Does the same as cholmod_rowadd_solve, except only part of L is used in * the update/downdate of the solution to Lx=b. This routine is an "expert" * routine. It is meant for use in LPDASA only. */ int cholmod_rowadd_mark ( /* ---- input ---- */ size_t k, /* row/column index to add */ cholmod_sparse *R, /* row/column of matrix to factorize (n-by-1) */ double bk [2], /* kth entry of the right hand side, b */ int *colmark, /* int array of size n. See cholmod_updown.c */ /* ---- in/out --- */ cholmod_factor *L, /* factor to modify */ cholmod_dense *X, /* solution to Lx=b (size n-by-1) */ cholmod_dense *DeltaB, /* change in b, zero on output */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_rowadd_mark (size_t, cholmod_sparse *, double *, SuiteSparse_long *, cholmod_factor *, cholmod_dense *, cholmod_dense *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_rowdel: delete a row from an LDL' factorization (a rank-2 update) */ /* -------------------------------------------------------------------------- */ /* Sets the kth row and column of L to be the kth row and column of the identity * matrix, and updates L(k+1:n,k+1:n) accordingly. To reduce the running time, * the caller can optionally provide the nonzero pattern (or an upper bound) of * kth row of L, as the sparse n-by-1 vector R. Provide R as NULL if you want * CHOLMOD to determine this itself, which is easier for the caller, but takes * a little more time. */ int cholmod_rowdel ( /* ---- input ---- */ size_t k, /* row/column index to delete */ cholmod_sparse *R, /* NULL, or the nonzero pattern of kth row of L */ /* ---- in/out --- */ cholmod_factor *L, /* factor to modify */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_rowdel (size_t, cholmod_sparse *, cholmod_factor *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_rowdel_solve: delete a row, and downdate Lx=b */ /* -------------------------------------------------------------------------- */ /* Does the same as cholmod_rowdel, but also downdates the solution to Lx=b. * When row/column k of A is "deleted" from the system A*y=b, this can induce * a change to x, in addition to changes arising when L and b are modified. * If this is the case, the kth entry of y is required as input (yk) */ int cholmod_rowdel_solve ( /* ---- input ---- */ size_t k, /* row/column index to delete */ cholmod_sparse *R, /* NULL, or the nonzero pattern of kth row of L */ double yk [2], /* kth entry in the solution to A*y=b */ /* ---- in/out --- */ cholmod_factor *L, /* factor to modify */ cholmod_dense *X, /* solution to Lx=b (size n-by-1) */ cholmod_dense *DeltaB, /* change in b, zero on output */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_rowdel_solve (size_t, cholmod_sparse *, double *, cholmod_factor *, cholmod_dense *, cholmod_dense *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_rowdel_mark: delete a row, and downdate solution to partial Lx=b */ /* -------------------------------------------------------------------------- */ /* Does the same as cholmod_rowdel_solve, except only part of L is used in * the update/downdate of the solution to Lx=b. This routine is an "expert" * routine. It is meant for use in LPDASA only. */ int cholmod_rowdel_mark ( /* ---- input ---- */ size_t k, /* row/column index to delete */ cholmod_sparse *R, /* NULL, or the nonzero pattern of kth row of L */ double yk [2], /* kth entry in the solution to A*y=b */ int *colmark, /* int array of size n. See cholmod_updown.c */ /* ---- in/out --- */ cholmod_factor *L, /* factor to modify */ cholmod_dense *X, /* solution to Lx=b (size n-by-1) */ cholmod_dense *DeltaB, /* change in b, zero on output */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_rowdel_mark (size_t, cholmod_sparse *, double *, SuiteSparse_long *, cholmod_factor *, cholmod_dense *, cholmod_dense *, cholmod_common *) ; #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Include/cholmod_blas.h0000644000076500000240000003334413524616144026662 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Include/cholmod_blas.h =============================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Include/cholmod_blas.h. * Copyright (C) 2005-2006, Univ. of Florida. Author: Timothy A. Davis * CHOLMOD/Include/cholmod_blas.h is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* This does not need to be included in the user's program. */ #ifndef CHOLMOD_BLAS_H #define CHOLMOD_BLAS_H /* ========================================================================== */ /* === Architecture ========================================================= */ /* ========================================================================== */ #if defined (__sun) || defined (MSOL2) || defined (ARCH_SOL2) #define CHOLMOD_SOL2 #define CHOLMOD_ARCHITECTURE "Sun Solaris" #elif defined (__sgi) || defined (MSGI) || defined (ARCH_SGI) #define CHOLMOD_SGI #define CHOLMOD_ARCHITECTURE "SGI Irix" #elif defined (__linux) || defined (MGLNX86) || defined (ARCH_GLNX86) #define CHOLMOD_LINUX #define CHOLMOD_ARCHITECTURE "Linux" #elif defined (__APPLE__) #define CHOLMOD_MAC #define CHOLMOD_ARCHITECTURE "Mac" #elif defined (_AIX) || defined (MIBM_RS) || defined (ARCH_IBM_RS) #define CHOLMOD_AIX #define CHOLMOD_ARCHITECTURE "IBM AIX" /* recent reports from IBM AIX seem to indicate that this is not needed: */ /* #define BLAS_NO_UNDERSCORE */ #elif defined (__alpha) || defined (MALPHA) || defined (ARCH_ALPHA) #define CHOLMOD_ALPHA #define CHOLMOD_ARCHITECTURE "Compaq Alpha" #elif defined (_WIN32) || defined (WIN32) || defined (_WIN64) || defined (WIN64) #if defined (__MINGW32__) || defined (__MINGW32__) #define CHOLMOD_MINGW #elif defined (__CYGWIN32__) || defined (__CYGWIN32__) #define CHOLMOD_CYGWIN #else #define CHOLMOD_WINDOWS //#define BLAS_NO_UNDERSCORE #endif #define CHOLMOD_ARCHITECTURE "Microsoft Windows" #elif defined (__hppa) || defined (__hpux) || defined (MHPUX) || defined (ARCH_HPUX) #define CHOLMOD_HP #define CHOLMOD_ARCHITECTURE "HP Unix" #define BLAS_NO_UNDERSCORE #elif defined (__hp700) || defined (MHP700) || defined (ARCH_HP700) #define CHOLMOD_HP #define CHOLMOD_ARCHITECTURE "HP 700 Unix" #define BLAS_NO_UNDERSCORE #else /* If the architecture is unknown, and you call the BLAS, you may need to */ /* define BLAS_BY_VALUE, BLAS_NO_UNDERSCORE, and/or BLAS_CHAR_ARG yourself. */ #define CHOLMOD_ARCHITECTURE "unknown" #endif /* ========================================================================== */ /* === BLAS and LAPACK names ================================================ */ /* ========================================================================== */ /* Prototypes for the various versions of the BLAS. */ /* Determine if the 64-bit Sun Performance BLAS is to be used */ #if defined(CHOLMOD_SOL2) && !defined(NSUNPERF) && defined(BLAS64) #define SUN64 #endif #ifdef SUN64 #define BLAS_DTRSV dtrsv_64_ #define BLAS_DGEMV dgemv_64_ #define BLAS_DTRSM dtrsm_64_ #define BLAS_DGEMM dgemm_64_ #define BLAS_DSYRK dsyrk_64_ #define BLAS_DGER dger_64_ #define BLAS_DSCAL dscal_64_ #define LAPACK_DPOTRF dpotrf_64_ #define BLAS_ZTRSV ztrsv_64_ #define BLAS_ZGEMV zgemv_64_ #define BLAS_ZTRSM ztrsm_64_ #define BLAS_ZGEMM zgemm_64_ #define BLAS_ZHERK zherk_64_ #define BLAS_ZGER zgeru_64_ #define BLAS_ZSCAL zscal_64_ #define LAPACK_ZPOTRF zpotrf_64_ #elif defined (BLAS_NO_UNDERSCORE) #define BLAS_DTRSV igraphdtrsv #define BLAS_DGEMV igraphdgemv #define BLAS_DTRSM igraphdtrsm #define BLAS_DGEMM igraphdgemm #define BLAS_DSYRK igraphdsyrk #define BLAS_DGER igraphdger #define BLAS_DSCAL igraphdscal #define LAPACK_DPOTRF igraphdpotrf #define BLAS_ZTRSV ztrsv #define BLAS_ZGEMV zgemv #define BLAS_ZTRSM ztrsm #define BLAS_ZGEMM zgemm #define BLAS_ZHERK zherk #define BLAS_ZGER zgeru #define BLAS_ZSCAL zscal #define LAPACK_ZPOTRF zpotrf #else #define BLAS_DTRSV igraphdtrsv_ #define BLAS_DGEMV igraphdgemv_ #define BLAS_DTRSM igraphdtrsm_ #define BLAS_DGEMM igraphdgemm_ #define BLAS_DSYRK igraphdsyrk_ #define BLAS_DGER igraphdger_ #define BLAS_DSCAL igraphdscal_ #define LAPACK_DPOTRF igraphdpotrf_ #define BLAS_ZTRSV ztrsv_ #define BLAS_ZGEMV zgemv_ #define BLAS_ZTRSM ztrsm_ #define BLAS_ZGEMM zgemm_ #define BLAS_ZHERK zherk_ #define BLAS_ZGER zgeru_ #define BLAS_ZSCAL zscal_ #define LAPACK_ZPOTRF zpotrf_ #endif /* ========================================================================== */ /* === BLAS and LAPACK integer arguments ==================================== */ /* ========================================================================== */ /* Compile CHOLMOD, UMFPACK, and SPQR with -DBLAS64 if you have a BLAS that * uses 64-bit integers */ #if defined (LONGBLAS) || defined (BLAS64) #define BLAS_INT SuiteSparse_long #else #define BLAS_INT int #endif /* If the BLAS integer is smaller than the basic CHOLMOD integer, then we need * to check for integer overflow when converting from Int to BLAS_INT. If * any integer overflows, the externally-defined BLAS_OK variable is * set to FALSE. BLAS_OK should be set to TRUE before calling any * BLAS_* macro. */ #define CHECK_BLAS_INT (sizeof (BLAS_INT) < sizeof (Int)) #define EQ(K,k) (((BLAS_INT) K) == ((Int) k)) /* ========================================================================== */ /* === BLAS and LAPACK prototypes and macros ================================ */ /* ========================================================================== */ int BLAS_DGEMV (char *trans, BLAS_INT *m, BLAS_INT *n, double *alpha, double *A, BLAS_INT *lda, double *X, BLAS_INT *incx, double *beta, double *Y, BLAS_INT *incy) ; #define BLAS_dgemv(trans,m,n,alpha,A,lda,X,incx,beta,Y,incy) \ { \ BLAS_INT M = m, N = n, LDA = lda, INCX = incx, INCY = incy ; \ if (CHECK_BLAS_INT && !(EQ (M,m) && EQ (N,n) && EQ (LDA,lda) && \ EQ (INCX,incx) && EQ (INCY,incy))) \ { \ BLAS_OK = FALSE ; \ } \ if (!CHECK_BLAS_INT || BLAS_OK) \ { \ BLAS_DGEMV (trans, &M, &N, alpha, A, &LDA, X, &INCX, beta, Y, &INCY) ; \ } \ } void BLAS_ZGEMV (char *trans, BLAS_INT *m, BLAS_INT *n, double *alpha, double *A, BLAS_INT *lda, double *X, BLAS_INT *incx, double *beta, double *Y, BLAS_INT *incy) ; #define BLAS_zgemv(trans,m,n,alpha,A,lda,X,incx,beta,Y,incy) \ { \ BLAS_INT M = m, N = n, LDA = lda, INCX = incx, INCY = incy ; \ if (CHECK_BLAS_INT && !(EQ (M,m) && EQ (N,n) && EQ (LDA,lda) && \ EQ (INCX,incx) && EQ (INCY,incy))) \ { \ BLAS_OK = FALSE ; \ } \ if (!CHECK_BLAS_INT || BLAS_OK) \ { \ BLAS_ZGEMV (trans, &M, &N, alpha, A, &LDA, X, &INCX, beta, Y, &INCY) ; \ } \ } void BLAS_DTRSV (char *uplo, char *trans, char *diag, BLAS_INT *n, double *A, BLAS_INT *lda, double *X, BLAS_INT *incx) ; #define BLAS_dtrsv(uplo,trans,diag,n,A,lda,X,incx) \ { \ BLAS_INT N = n, LDA = lda, INCX = incx ; \ if (CHECK_BLAS_INT && !(EQ (N,n) && EQ (LDA,lda) && EQ (INCX,incx))) \ { \ BLAS_OK = FALSE ; \ } \ if (!CHECK_BLAS_INT || BLAS_OK) \ { \ BLAS_DTRSV (uplo, trans, diag, &N, A, &LDA, X, &INCX) ; \ } \ } void BLAS_ZTRSV (char *uplo, char *trans, char *diag, BLAS_INT *n, double *A, BLAS_INT *lda, double *X, BLAS_INT *incx) ; #define BLAS_ztrsv(uplo,trans,diag,n,A,lda,X,incx) \ { \ BLAS_INT N = n, LDA = lda, INCX = incx ; \ if (CHECK_BLAS_INT && !(EQ (N,n) && EQ (LDA,lda) && EQ (INCX,incx))) \ { \ BLAS_OK = FALSE ; \ } \ if (!CHECK_BLAS_INT || BLAS_OK) \ { \ BLAS_ZTRSV (uplo, trans, diag, &N, A, &LDA, X, &INCX) ; \ } \ } void BLAS_DTRSM (char *side, char *uplo, char *transa, char *diag, BLAS_INT *m, BLAS_INT *n, double *alpha, double *A, BLAS_INT *lda, double *B, BLAS_INT *ldb) ; #define BLAS_dtrsm(side,uplo,transa,diag,m,n,alpha,A,lda,B,ldb) \ { \ BLAS_INT M = m, N = n, LDA = lda, LDB = ldb ; \ if (CHECK_BLAS_INT && !(EQ (M,m) && EQ (N,n) && EQ (LDA,lda) && \ EQ (LDB,ldb))) \ { \ BLAS_OK = FALSE ; \ } \ if (!CHECK_BLAS_INT || BLAS_OK) \ { \ BLAS_DTRSM (side, uplo, transa, diag, &M, &N, alpha, A, &LDA, B, &LDB);\ } \ } void BLAS_ZTRSM (char *side, char *uplo, char *transa, char *diag, BLAS_INT *m, BLAS_INT *n, double *alpha, double *A, BLAS_INT *lda, double *B, BLAS_INT *ldb) ; #define BLAS_ztrsm(side,uplo,transa,diag,m,n,alpha,A,lda,B,ldb) \ { \ BLAS_INT M = m, N = n, LDA = lda, LDB = ldb ; \ if (CHECK_BLAS_INT && !(EQ (M,m) && EQ (N,n) && EQ (LDA,lda) && \ EQ (LDB,ldb))) \ { \ BLAS_OK = FALSE ; \ } \ if (!CHECK_BLAS_INT || BLAS_OK) \ { \ BLAS_ZTRSM (side, uplo, transa, diag, &M, &N, alpha, A, &LDA, B, &LDB);\ } \ } int BLAS_DGEMM (char *transa, char *transb, BLAS_INT *m, BLAS_INT *n, BLAS_INT *k, double *alpha, double *A, BLAS_INT *lda, double *B, BLAS_INT *ldb, double *beta, double *C, BLAS_INT *ldc) ; #define BLAS_dgemm(transa,transb,m,n,k,alpha,A,lda,B,ldb,beta,C,ldc) \ { \ BLAS_INT M = m, N = n, K = k, LDA = lda, LDB = ldb, LDC = ldc ; \ if (CHECK_BLAS_INT && !(EQ (M,m) && EQ (N,n) && EQ (K,k) && \ EQ (LDA,lda) && EQ (LDB,ldb) && EQ (LDC,ldc))) \ { \ BLAS_OK = FALSE ; \ } \ if (!CHECK_BLAS_INT || BLAS_OK) \ { \ BLAS_DGEMM (transa, transb, &M, &N, &K, alpha, A, &LDA, B, &LDB, beta, \ C, &LDC) ; \ } \ } void BLAS_ZGEMM (char *transa, char *transb, BLAS_INT *m, BLAS_INT *n, BLAS_INT *k, double *alpha, double *A, BLAS_INT *lda, double *B, BLAS_INT *ldb, double *beta, double *C, BLAS_INT *ldc) ; #define BLAS_zgemm(transa,transb,m,n,k,alpha,A,lda,B,ldb,beta,C,ldc) \ { \ BLAS_INT M = m, N = n, K = k, LDA = lda, LDB = ldb, LDC = ldc ; \ if (CHECK_BLAS_INT && !(EQ (M,m) && EQ (N,n) && EQ (K,k) && \ EQ (LDA,lda) && EQ (LDB,ldb) && EQ (LDC,ldc))) \ { \ BLAS_OK = FALSE ; \ } \ if (!CHECK_BLAS_INT || BLAS_OK) \ { \ BLAS_ZGEMM (transa, transb, &M, &N, &K, alpha, A, &LDA, B, &LDB, beta, \ C, &LDC) ; \ } \ } void BLAS_DSYRK (char *uplo, char *trans, BLAS_INT *n, BLAS_INT *k, double *alpha, double *A, BLAS_INT *lda, double *beta, double *C, BLAS_INT *ldc) ; #define BLAS_dsyrk(uplo,trans,n,k,alpha,A,lda,beta,C,ldc) \ { \ BLAS_INT N = n, K = k, LDA = lda, LDC = ldc ; \ if (CHECK_BLAS_INT && !(EQ (N,n) && EQ (K,k) && EQ (LDA,lda) && \ EQ (LDC,ldc))) \ { \ BLAS_OK = FALSE ; \ } \ if (!CHECK_BLAS_INT || BLAS_OK) \ { \ BLAS_DSYRK (uplo, trans, &N, &K, alpha, A, &LDA, beta, C, &LDC) ; \ } \ } \ void BLAS_ZHERK (char *uplo, char *trans, BLAS_INT *n, BLAS_INT *k, double *alpha, double *A, BLAS_INT *lda, double *beta, double *C, BLAS_INT *ldc) ; #define BLAS_zherk(uplo,trans,n,k,alpha,A,lda,beta,C,ldc) \ { \ BLAS_INT N = n, K = k, LDA = lda, LDC = ldc ; \ if (CHECK_BLAS_INT && !(EQ (N,n) && EQ (K,k) && EQ (LDA,lda) && \ EQ (LDC,ldc))) \ { \ BLAS_OK = FALSE ; \ } \ if (!CHECK_BLAS_INT || BLAS_OK) \ { \ BLAS_ZHERK (uplo, trans, &N, &K, alpha, A, &LDA, beta, C, &LDC) ; \ } \ } \ void LAPACK_DPOTRF (char *uplo, BLAS_INT *n, double *A, BLAS_INT *lda, BLAS_INT *info) ; #define LAPACK_dpotrf(uplo,n,A,lda,info) \ { \ BLAS_INT N = n, LDA = lda, INFO = 1 ; \ if (CHECK_BLAS_INT && !(EQ (N,n) && EQ (LDA,lda))) \ { \ BLAS_OK = FALSE ; \ } \ if (!CHECK_BLAS_INT || BLAS_OK) \ { \ LAPACK_DPOTRF (uplo, &N, A, &LDA, &INFO) ; \ } \ info = INFO ; \ } void LAPACK_ZPOTRF (char *uplo, BLAS_INT *n, double *A, BLAS_INT *lda, BLAS_INT *info) ; #define LAPACK_zpotrf(uplo,n,A,lda,info) \ { \ BLAS_INT N = n, LDA = lda, INFO = 1 ; \ if (CHECK_BLAS_INT && !(EQ (N,n) && EQ (LDA,lda))) \ { \ BLAS_OK = FALSE ; \ } \ if (!CHECK_BLAS_INT || BLAS_OK) \ { \ LAPACK_ZPOTRF (uplo, &N, A, &LDA, &INFO) ; \ } \ info = INFO ; \ } /* ========================================================================== */ void BLAS_DSCAL (BLAS_INT *n, double *alpha, double *Y, BLAS_INT *incy) ; #define BLAS_dscal(n,alpha,Y,incy) \ { \ BLAS_INT N = n, INCY = incy ; \ if (CHECK_BLAS_INT && !(EQ (N,n) && EQ (INCY,incy))) \ { \ BLAS_OK = FALSE ; \ } \ if (!CHECK_BLAS_INT || BLAS_OK) \ { \ BLAS_DSCAL (&N, alpha, Y, &INCY) ; \ } \ } void BLAS_ZSCAL (BLAS_INT *n, double *alpha, double *Y, BLAS_INT *incy) ; #define BLAS_zscal(n,alpha,Y,incy) \ { \ BLAS_INT N = n, INCY = incy ; \ if (CHECK_BLAS_INT && !(EQ (N,n) && EQ (INCY,incy))) \ { \ BLAS_OK = FALSE ; \ } \ if (!CHECK_BLAS_INT || BLAS_OK) \ { \ BLAS_ZSCAL (&N, alpha, Y, &INCY) ; \ } \ } void BLAS_DGER (BLAS_INT *m, BLAS_INT *n, double *alpha, double *X, BLAS_INT *incx, double *Y, BLAS_INT *incy, double *A, BLAS_INT *lda) ; #define BLAS_dger(m,n,alpha,X,incx,Y,incy,A,lda) \ { \ BLAS_INT M = m, N = n, LDA = lda, INCX = incx, INCY = incy ; \ if (CHECK_BLAS_INT && !(EQ (M,m) && EQ (N,n) && EQ (LDA,lda) && \ EQ (INCX,incx) && EQ (INCY,incy))) \ { \ BLAS_OK = FALSE ; \ } \ if (!CHECK_BLAS_INT || BLAS_OK) \ { \ BLAS_DGER (&M, &N, alpha, X, &INCX, Y, &INCY, A, &LDA) ; \ } \ } void BLAS_ZGER (BLAS_INT *m, BLAS_INT *n, double *alpha, double *X, BLAS_INT *incx, double *Y, BLAS_INT *incy, double *A, BLAS_INT *lda) ; #define BLAS_zgeru(m,n,alpha,X,incx,Y,incy,A,lda) \ { \ BLAS_INT M = m, N = n, LDA = lda, INCX = incx, INCY = incy ; \ if (CHECK_BLAS_INT && !(EQ (M,m) && EQ (N,n) && EQ (LDA,lda) && \ EQ (INCX,incx) && EQ (INCY,incy))) \ { \ BLAS_OK = FALSE ; \ } \ if (!CHECK_BLAS_INT || BLAS_OK) \ { \ BLAS_ZGER (&M, &N, alpha, X, &INCX, Y, &INCY, A, &LDA) ; \ } \ } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Include/cholmod_internal.h0000644000076500000240000003531713524616144027557 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Include/cholmod_internal.h =========================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Include/cholmod_internal.h. * Copyright (C) 2005-2013, Univ. of Florida. Author: Timothy A. Davis * CHOLMOD/Include/cholmod_internal.h is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* CHOLMOD internal include file. * * This file contains internal definitions for CHOLMOD, not meant to be included * in user code. They define macros that are not prefixed with CHOLMOD_. This * file can safely #include'd in user code if you want to make use of the * macros defined here, and don't mind the possible name conflicts with your * code, however. * * Required by all CHOLMOD routines. Not required by any user routine that * uses CHOLMOMD. Unless debugging is enabled, this file does not require any * CHOLMOD module (not even the Core module). * * If debugging is enabled, all CHOLMOD modules require the Check module. * Enabling debugging requires that this file be editted. Debugging cannot be * enabled with a compiler flag. This is because CHOLMOD is exceedingly slow * when debugging is enabled. Debugging is meant for development of CHOLMOD * itself, not by users of CHOLMOD. */ #ifndef CHOLMOD_INTERNAL_H #define CHOLMOD_INTERNAL_H /* ========================================================================== */ /* === large file I/O ======================================================= */ /* ========================================================================== */ /* Definitions for large file I/O must come before any other #includes. If * this causes problems (may not be portable to all platforms), then compile * CHOLMOD with -DNLARGEFILE. You must do this for MATLAB 6.5 and earlier, * for example. */ #include "cholmod_io64.h" /* ========================================================================== */ /* === debugging and basic includes ========================================= */ /* ========================================================================== */ /* turn off debugging */ #ifndef NDEBUG #define NDEBUG #endif /* Uncomment this line to enable debugging. CHOLMOD will be very slow. #undef NDEBUG */ #ifdef MATLAB_MEX_FILE #include "mex.h" #endif #if !defined(NPRINT) || !defined(NDEBUG) #include #endif #include #include #include #include #include /* ========================================================================== */ /* === basic definitions ==================================================== */ /* ========================================================================== */ /* Some non-conforming compilers insist on defining TRUE and FALSE. */ #undef TRUE #undef FALSE #define TRUE 1 #define FALSE 0 #define BOOLEAN(x) ((x) ? TRUE : FALSE) /* NULL should already be defined, but ensure it is here. */ #ifndef NULL #define NULL ((void *) 0) #endif /* FLIP is a "negation about -1", and is used to mark an integer i that is * normally non-negative. FLIP (EMPTY) is EMPTY. FLIP of a number > EMPTY * is negative, and FLIP of a number < EMTPY is positive. FLIP (FLIP (i)) = i * for all integers i. UNFLIP (i) is >= EMPTY. */ #define EMPTY (-1) #define FLIP(i) (-(i)-2) #define UNFLIP(i) (((i) < EMPTY) ? FLIP (i) : (i)) /* MAX and MIN are not safe to use for NaN's */ #define MAX(a,b) (((a) > (b)) ? (a) : (b)) #define MAX3(a,b,c) (((a) > (b)) ? (MAX (a,c)) : (MAX (b,c))) #define MAX4(a,b,c,d) (((a) > (b)) ? (MAX3 (a,c,d)) : (MAX3 (b,c,d))) #define MIN(a,b) (((a) < (b)) ? (a) : (b)) #define IMPLIES(p,q) (!(p) || (q)) /* find the sign: -1 if x < 0, 1 if x > 0, zero otherwise. * Not safe for NaN's */ #define SIGN(x) (((x) < 0) ? (-1) : (((x) > 0) ? 1 : 0)) /* round up an integer x to a multiple of s */ #define ROUNDUP(x,s) ((s) * (((x) + ((s) - 1)) / (s))) #define ERROR(status,msg) \ CHOLMOD(error) (status, __FILE__, __LINE__, msg, Common) /* Check a pointer and return if null. Set status to invalid, unless the * status is already "out of memory" */ #define RETURN_IF_NULL(A,result) \ { \ if ((A) == NULL) \ { \ if (Common->status != CHOLMOD_OUT_OF_MEMORY) \ { \ ERROR (CHOLMOD_INVALID, "argument missing") ; \ } \ return (result) ; \ } \ } /* Return if Common is NULL or invalid */ #define RETURN_IF_NULL_COMMON(result) \ { \ if (Common == NULL) \ { \ return (result) ; \ } \ if (Common->itype != ITYPE || Common->dtype != DTYPE) \ { \ Common->status = CHOLMOD_INVALID ; \ return (result) ; \ } \ } #define IS_NAN(x) CHOLMOD_IS_NAN(x) #define IS_ZERO(x) CHOLMOD_IS_ZERO(x) #define IS_NONZERO(x) CHOLMOD_IS_NONZERO(x) #define IS_LT_ZERO(x) CHOLMOD_IS_LT_ZERO(x) #define IS_GT_ZERO(x) CHOLMOD_IS_GT_ZERO(x) #define IS_LE_ZERO(x) CHOLMOD_IS_LE_ZERO(x) /* 1e308 is a huge number that doesn't take many characters to print in a * file, in CHOLMOD/Check/cholmod_read and _write. Numbers larger than this * are interpretted as Inf, since sscanf doesn't read in Inf's properly. * This assumes IEEE double precision arithmetic. DBL_MAX would be a little * better, except that it takes too many digits to print in a file. */ #define HUGE_DOUBLE 1e308 /* ========================================================================== */ /* === int/long and double/float definitions ================================ */ /* ========================================================================== */ /* CHOLMOD is designed for 3 types of integer variables: * * (1) all integers are int * (2) most integers are int, some are SuiteSparse_long * (3) all integers are SuiteSparse_long * * and two kinds of floating-point values: * * (1) double * (2) float * * the complex types (ANSI-compatible complex, and MATLAB-compatable zomplex) * are based on the double or float type, and are not selected here. They * are typically selected via template routines. * * This gives 6 different modes in which CHOLMOD can be compiled (only the * first two are currently supported): * * DINT double, int prefix: cholmod_ * DLONG double, SuiteSparse_long prefix: cholmod_l_ * DMIX double, mixed int/SuiteSparse_long prefix: cholmod_m_ * SINT float, int prefix: cholmod_si_ * SLONG float, SuiteSparse_long prefix: cholmod_sl_ * SMIX float, mixed int/log prefix: cholmod_sm_ * * These are selected with compile time flags (-DDLONG, for example). If no * flag is selected, the default is DINT. * * All six versions use the same include files. The user-visible include files * are completely independent of which int/long/double/float version is being * used. The integer / real types in all data structures (sparse, triplet, * dense, common, and triplet) are defined at run-time, not compile-time, so * there is only one "cholmod_sparse" data type. Void pointers are used inside * that data structure to point to arrays of the proper type. Each data * structure has an itype and dtype field which determines the kind of basic * types used. These are defined in Include/cholmod_core.h. * * FUTURE WORK: support all six types (float, and mixed int/long) * * SuiteSparse_long is normally defined as long. However, for WIN64 it is * __int64. It can also be redefined for other platforms, by modifying * SuiteSparse_config.h. */ #include "SuiteSparse_config.h" /* -------------------------------------------------------------------------- */ /* Size_max: the largest value of size_t */ /* -------------------------------------------------------------------------- */ #define Size_max ((size_t) (-1)) /* routines for doing arithmetic on size_t, and checking for overflow */ size_t cholmod_add_size_t (size_t a, size_t b, int *ok) ; size_t cholmod_mult_size_t (size_t a, size_t k, int *ok) ; size_t cholmod_l_add_size_t (size_t a, size_t b, int *ok) ; size_t cholmod_l_mult_size_t (size_t a, size_t k, int *ok) ; /* -------------------------------------------------------------------------- */ /* double (also complex double), SuiteSparse_long */ /* -------------------------------------------------------------------------- */ #ifdef DLONG #define Real double #define Int SuiteSparse_long #define Int_max SuiteSparse_long_max #define CHOLMOD(name) cholmod_l_ ## name #define LONG #define DOUBLE #define ITYPE CHOLMOD_LONG #define DTYPE CHOLMOD_DOUBLE #define ID SuiteSparse_long_id /* -------------------------------------------------------------------------- */ /* double, int/SuiteSparse_long */ /* -------------------------------------------------------------------------- */ #elif defined (DMIX) #error "mixed int/SuiteSparse_long not yet supported" /* -------------------------------------------------------------------------- */ /* single, int */ /* -------------------------------------------------------------------------- */ #elif defined (SINT) #error "single-precision not yet supported" /* -------------------------------------------------------------------------- */ /* single, SuiteSparse_long */ /* -------------------------------------------------------------------------- */ #elif defined (SLONG) #error "single-precision not yet supported" /* -------------------------------------------------------------------------- */ /* single, int/SuiteSparse_long */ /* -------------------------------------------------------------------------- */ #elif defined (SMIX) #error "single-precision not yet supported" /* -------------------------------------------------------------------------- */ /* double (also complex double), int: this is the default */ /* -------------------------------------------------------------------------- */ #else #ifndef DINT #define DINT #endif #define INT #define DOUBLE #define Real double #define Int int #define Int_max INT_MAX #define CHOLMOD(name) cholmod_ ## name #define ITYPE CHOLMOD_INT #define DTYPE CHOLMOD_DOUBLE #define ID "%d" #endif /* ========================================================================== */ /* === real/complex arithmetic ============================================== */ /* ========================================================================== */ #include "cholmod_complexity.h" /* ========================================================================== */ /* === Architecture and BLAS ================================================ */ /* ========================================================================== */ #define BLAS_OK Common->blas_ok #include "cholmod_blas.h" /* ========================================================================== */ /* === debugging definitions ================================================ */ /* ========================================================================== */ #ifndef NDEBUG #include #include "cholmod.h" /* The cholmod_dump routines are in the Check module. No CHOLMOD routine * calls the cholmod_check_* or cholmod_print_* routines in the Check module, * since they use Common workspace that may already be in use. Instead, they * use the cholmod_dump_* routines defined there, which allocate their own * workspace if they need it. */ #ifndef EXTERN #define EXTERN extern #endif /* double, int */ EXTERN int cholmod_dump ; EXTERN int cholmod_dump_malloc ; SuiteSparse_long cholmod_dump_sparse (cholmod_sparse *, const char *, cholmod_common *) ; int cholmod_dump_factor (cholmod_factor *, const char *, cholmod_common *) ; int cholmod_dump_triplet (cholmod_triplet *, const char *, cholmod_common *) ; int cholmod_dump_dense (cholmod_dense *, const char *, cholmod_common *) ; int cholmod_dump_subset (int *, size_t, size_t, const char *, cholmod_common *) ; int cholmod_dump_perm (int *, size_t, size_t, const char *, cholmod_common *) ; int cholmod_dump_parent (int *, size_t, const char *, cholmod_common *) ; void cholmod_dump_init (const char *, cholmod_common *) ; int cholmod_dump_mem (const char *, SuiteSparse_long, cholmod_common *) ; void cholmod_dump_real (const char *, Real *, SuiteSparse_long, SuiteSparse_long, int, int, cholmod_common *) ; void cholmod_dump_super (SuiteSparse_long, int *, int *, int *, int *, double *, int, cholmod_common *) ; int cholmod_dump_partition (SuiteSparse_long, int *, int *, int *, int *, SuiteSparse_long, cholmod_common *) ; int cholmod_dump_work(int, int, SuiteSparse_long, cholmod_common *) ; /* double, SuiteSparse_long */ EXTERN int cholmod_l_dump ; EXTERN int cholmod_l_dump_malloc ; SuiteSparse_long cholmod_l_dump_sparse (cholmod_sparse *, const char *, cholmod_common *) ; int cholmod_l_dump_factor (cholmod_factor *, const char *, cholmod_common *) ; int cholmod_l_dump_triplet (cholmod_triplet *, const char *, cholmod_common *); int cholmod_l_dump_dense (cholmod_dense *, const char *, cholmod_common *) ; int cholmod_l_dump_subset (SuiteSparse_long *, size_t, size_t, const char *, cholmod_common *) ; int cholmod_l_dump_perm (SuiteSparse_long *, size_t, size_t, const char *, cholmod_common *) ; int cholmod_l_dump_parent (SuiteSparse_long *, size_t, const char *, cholmod_common *) ; void cholmod_l_dump_init (const char *, cholmod_common *) ; int cholmod_l_dump_mem (const char *, SuiteSparse_long, cholmod_common *) ; void cholmod_l_dump_real (const char *, Real *, SuiteSparse_long, SuiteSparse_long, int, int, cholmod_common *) ; void cholmod_l_dump_super (SuiteSparse_long, SuiteSparse_long *, SuiteSparse_long *, SuiteSparse_long *, SuiteSparse_long *, double *, int, cholmod_common *) ; int cholmod_l_dump_partition (SuiteSparse_long, SuiteSparse_long *, SuiteSparse_long *, SuiteSparse_long *, SuiteSparse_long *, SuiteSparse_long, cholmod_common *) ; int cholmod_l_dump_work(int, int, SuiteSparse_long, cholmod_common *) ; #define DEBUG_INIT(s,Common) { CHOLMOD(dump_init)(s, Common) ; } #define ASSERT(expression) (assert (expression)) #define PRK(k,params) \ { \ if (CHOLMOD(dump) >= (k) && Common->print_function != NULL) \ { \ (Common->print_function) params ; \ } \ } #define PRINT0(params) PRK (0, params) #define PRINT1(params) PRK (1, params) #define PRINT2(params) PRK (2, params) #define PRINT3(params) PRK (3, params) #define PRINTM(params) \ { \ if (CHOLMOD(dump_malloc) > 0) \ { \ printf params ; \ } \ } #define DEBUG(statement) statement #else /* Debugging disabled (the normal case) */ #define PRK(k,params) #define DEBUG_INIT(s,Common) #define PRINT0(params) #define PRINT1(params) #define PRINT2(params) #define PRINT3(params) #define PRINTM(params) #define ASSERT(expression) #define DEBUG(statement) #endif #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Include/cholmod_core.h0000644000076500000240000030506713524616144026675 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Include/cholmod_core.h =============================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Include/cholmod_core.h. * Copyright (C) 2005-2013, Univ. of Florida. Author: Timothy A. Davis * CHOLMOD/Include/cholmod_core.h is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* CHOLMOD Core module: basic CHOLMOD objects and routines. * Required by all CHOLMOD modules. Requires no other module or package. * * The CHOLMOD modules are: * * Core basic data structures and definitions * Check check/print the 5 CHOLMOD objects, & 3 types of integer vectors * Cholesky sparse Cholesky factorization * Modify sparse Cholesky update/downdate/row-add/row-delete * MatrixOps sparse matrix functions (add, multiply, norm, ...) * Supernodal supernodal sparse Cholesky factorization * Partition graph-partitioning based orderings * * The CHOLMOD objects: * -------------------- * * cholmod_common parameters, statistics, and workspace * cholmod_sparse a sparse matrix in compressed column form * cholmod_factor an LL' or LDL' factorization * cholmod_dense a dense matrix * cholmod_triplet a sparse matrix in "triplet" form * * The Core module described here defines the CHOLMOD data structures, and * basic operations on them. To create and solve a sparse linear system Ax=b, * the user must create A and b, populate them with values, and then pass them * to the routines in the CHOLMOD Cholesky module. There are two primary * methods for creating A: (1) allocate space for a column-oriented sparse * matrix and fill it with pattern and values, or (2) create a triplet form * matrix and convert it to a sparse matrix. The latter option is simpler. * * The matrices b and x are typically dense matrices, but can also be sparse. * You can allocate and free them as dense matrices with the * cholmod_allocate_dense and cholmod_free_dense routines. * * The cholmod_factor object contains the symbolic and numeric LL' or LDL' * factorization of sparse symmetric matrix. The matrix must be positive * definite for an LL' factorization. It need only be symmetric and have well- * conditioned leading submatrices for it to have an LDL' factorization * (CHOLMOD does not pivot for numerical stability). It is typically created * with the cholmod_factorize routine in the Cholesky module, but can also * be initialized to L=D=I in the Core module and then modified by the Modify * module. It must be freed with cholmod_free_factor, defined below. * * The Core routines for each object are described below. Each list is split * into two parts: the primary routines and secondary routines. * * ============================================================================ * === cholmod_common ========================================================= * ============================================================================ * * The Common object contains control parameters, statistics, and * You must call cholmod_start before calling any other CHOLMOD routine, and * must call cholmod_finish as your last call to CHOLMOD, with two exceptions: * you may call cholmod_print_common and cholmod_check_common in the Check * module after calling cholmod_finish. * * cholmod_start first call to CHOLMOD * cholmod_finish last call to CHOLMOD * ----------------------------- * cholmod_defaults restore default parameters * cholmod_maxrank maximum rank for update/downdate * cholmod_allocate_work allocate workspace in Common * cholmod_free_work free workspace in Common * cholmod_clear_flag clear Flag workspace in Common * cholmod_error called when CHOLMOD encounters an error * cholmod_dbound for internal use in CHOLMOD only * cholmod_hypot compute sqrt (x*x + y*y) accurately * cholmod_divcomplex complex division, c = a/b * * ============================================================================ * === cholmod_sparse ========================================================= * ============================================================================ * * A sparse matrix is held in compressed column form. In the basic type * ("packed", which corresponds to a MATLAB sparse matrix), an n-by-n matrix * with nz entries is held in three arrays: p of size n+1, i of size nz, and x * of size nz. Row indices of column j are held in i [p [j] ... p [j+1]-1] and * in the same locations in x. There may be no duplicate entries in a column. * Row indices in each column may be sorted or unsorted (CHOLMOD keeps track). * A->stype determines the storage mode: 0 if both upper/lower parts are stored, * -1 if A is symmetric and just tril(A) is stored, +1 if symmetric and triu(A) * is stored. * * cholmod_allocate_sparse allocate a sparse matrix * cholmod_free_sparse free a sparse matrix * ----------------------------- * cholmod_reallocate_sparse change the size (# entries) of sparse matrix * cholmod_nnz number of nonzeros in a sparse matrix * cholmod_speye sparse identity matrix * cholmod_spzeros sparse zero matrix * cholmod_transpose transpose a sparse matrix * cholmod_ptranspose transpose/permute a sparse matrix * cholmod_transpose_unsym transpose/permute an unsymmetric sparse matrix * cholmod_transpose_sym transpose/permute a symmetric sparse matrix * cholmod_sort sort row indices in each column of sparse matrix * cholmod_band C = tril (triu (A,k1), k2) * cholmod_band_inplace A = tril (triu (A,k1), k2) * cholmod_aat C = A*A' * cholmod_copy_sparse C = A, create an exact copy of a sparse matrix * cholmod_copy C = A, with possible change of stype * cholmod_add C = alpha*A + beta*B * cholmod_sparse_xtype change the xtype of a sparse matrix * * ============================================================================ * === cholmod_factor ========================================================= * ============================================================================ * * The data structure for an LL' or LDL' factorization is too complex to * describe in one sentence. This object can hold the symbolic analysis alone, * or in combination with a "simplicial" (similar to a sparse matrix) or * "supernodal" form of the numerical factorization. Only the routine to free * a factor is primary, since a factor object is created by the factorization * routine (cholmod_factorize). It must be freed with cholmod_free_factor. * * cholmod_free_factor free a factor * ----------------------------- * cholmod_allocate_factor allocate a factor (LL' or LDL') * cholmod_reallocate_factor change the # entries in a factor * cholmod_change_factor change the type of factor (e.g., LDL' to LL') * cholmod_pack_factor pack the columns of a factor * cholmod_reallocate_column resize a single column of a factor * cholmod_factor_to_sparse create a sparse matrix copy of a factor * cholmod_copy_factor create a copy of a factor * cholmod_factor_xtype change the xtype of a factor * * Note that there is no cholmod_sparse_to_factor routine to create a factor * as a copy of a sparse matrix. It could be done, after a fashion, but a * lower triangular sparse matrix would not necessarily have a chordal graph, * which would break the many CHOLMOD routines that rely on this property. * * ============================================================================ * === cholmod_dense ========================================================== * ============================================================================ * * The solve routines and some of the MatrixOps and Modify routines use dense * matrices as inputs. These are held in column-major order. With a leading * dimension of d, the entry in row i and column j is held in x [i+j*d]. * * cholmod_allocate_dense allocate a dense matrix * cholmod_free_dense free a dense matrix * ----------------------------- * cholmod_zeros allocate a dense matrix of all zeros * cholmod_ones allocate a dense matrix of all ones * cholmod_eye allocate a dense identity matrix * cholmod_sparse_to_dense create a dense matrix copy of a sparse matrix * cholmod_dense_to_sparse create a sparse matrix copy of a dense matrix * cholmod_copy_dense create a copy of a dense matrix * cholmod_copy_dense2 copy a dense matrix (pre-allocated) * cholmod_dense_xtype change the xtype of a dense matrix * cholmod_ensure_dense ensure a dense matrix has a given size and type * * ============================================================================ * === cholmod_triplet ======================================================== * ============================================================================ * * A sparse matrix held in triplet form is the simplest one for a user to * create. It consists of a list of nz entries in arbitrary order, held in * three arrays: i, j, and x, each of length nk. The kth entry is in row i[k], * column j[k], with value x[k]. There may be duplicate values; if A(i,j) * appears more than once, its value is the sum of the entries with those row * and column indices. * * cholmod_allocate_triplet allocate a triplet matrix * cholmod_triplet_to_sparse create a sparse matrix copy of a triplet matrix * cholmod_free_triplet free a triplet matrix * ----------------------------- * cholmod_reallocate_triplet change the # of entries in a triplet matrix * cholmod_sparse_to_triplet create a triplet matrix copy of a sparse matrix * cholmod_copy_triplet create a copy of a triplet matrix * cholmod_triplet_xtype change the xtype of a triplet matrix * * ============================================================================ * === memory management ====================================================== * ============================================================================ * * cholmod_malloc malloc wrapper * cholmod_calloc calloc wrapper * cholmod_free free wrapper * cholmod_realloc realloc wrapper * cholmod_realloc_multiple realloc wrapper for multiple objects * * ============================================================================ * === Core CHOLMOD prototypes ================================================ * ============================================================================ * * All CHOLMOD routines (in all modules) use the following protocol for return * values, with one exception: * * int TRUE (1) if successful, or FALSE (0) otherwise. * (exception: cholmod_divcomplex) * SuiteSparse_long a value >= 0 if successful, or -1 otherwise. * double a value >= 0 if successful, or -1 otherwise. * size_t a value > 0 if successful, or 0 otherwise. * void * a non-NULL pointer to newly allocated memory if * successful, or NULL otherwise. * cholmod_sparse * a non-NULL pointer to a newly allocated matrix * if successful, or NULL otherwise. * cholmod_factor * a non-NULL pointer to a newly allocated factor * if successful, or NULL otherwise. * cholmod_triplet * a non-NULL pointer to a newly allocated triplet * matrix if successful, or NULL otherwise. * cholmod_dense * a non-NULL pointer to a newly allocated triplet * matrix if successful, or NULL otherwise. * * The last parameter to all routines is always a pointer to the CHOLMOD * Common object. * * TRUE and FALSE are not defined here, since they may conflict with the user * program. A routine that described here returning TRUE or FALSE returns 1 * or 0, respectively. Any TRUE/FALSE parameter is true if nonzero, false if * zero. */ #ifndef CHOLMOD_CORE_H #define CHOLMOD_CORE_H /* ========================================================================== */ /* === CHOLMOD version ====================================================== */ /* ========================================================================== */ /* All versions of CHOLMOD will include the following definitions. * As an example, to test if the version you are using is 1.3 or later: * * if (CHOLMOD_VERSION >= CHOLMOD_VER_CODE (1,3)) ... * * This also works during compile-time: * * #if CHOLMOD_VERSION >= CHOLMOD_VER_CODE (1,3) * printf ("This is version 1.3 or later\n") ; * #else * printf ("This is version is earlier than 1.3\n") ; * #endif */ #define CHOLMOD_HAS_VERSION_FUNCTION #define CHOLMOD_DATE "April 25, 2013" #define CHOLMOD_VER_CODE(main,sub) ((main) * 1000 + (sub)) #define CHOLMOD_MAIN_VERSION 2 #define CHOLMOD_SUB_VERSION 1 #define CHOLMOD_SUBSUB_VERSION 2 #define CHOLMOD_VERSION \ CHOLMOD_VER_CODE(CHOLMOD_MAIN_VERSION,CHOLMOD_SUB_VERSION) /* ========================================================================== */ /* === non-CHOLMOD include files ============================================ */ /* ========================================================================== */ /* This is the only non-CHOLMOD include file imposed on the user program. * It required for size_t definition used here. CHOLMOD itself includes other * ANSI C89 standard #include files, but does not expose them to the user. * * CHOLMOD assumes that your C compiler is ANSI C89 compliant. It does not make * use of ANSI C99 features. */ #include #include /* ========================================================================== */ /* === CUDA BLAS for the GPU ================================================ */ /* ========================================================================== */ #ifdef GPU_BLAS #include #include #endif /* ========================================================================== */ /* === CHOLMOD objects ====================================================== */ /* ========================================================================== */ /* Each CHOLMOD object has its own type code. */ #define CHOLMOD_COMMON 0 #define CHOLMOD_SPARSE 1 #define CHOLMOD_FACTOR 2 #define CHOLMOD_DENSE 3 #define CHOLMOD_TRIPLET 4 /* ========================================================================== */ /* === CHOLMOD Common ======================================================= */ /* ========================================================================== */ /* itype defines the types of integer used: */ #define CHOLMOD_INT 0 /* all integer arrays are int */ #define CHOLMOD_INTLONG 1 /* most are int, some are SuiteSparse_long */ #define CHOLMOD_LONG 2 /* all integer arrays are SuiteSparse_long */ /* The itype of all parameters for all CHOLMOD routines must match. * FUTURE WORK: CHOLMOD_INTLONG is not yet supported. */ /* dtype defines what the numerical type is (double or float): */ #define CHOLMOD_DOUBLE 0 /* all numerical values are double */ #define CHOLMOD_SINGLE 1 /* all numerical values are float */ /* The dtype of all parameters for all CHOLMOD routines must match. * * Scalar floating-point values are always passed as double arrays of size 2 * (for the real and imaginary parts). They are typecast to float as needed. * FUTURE WORK: the float case is not supported yet. */ /* xtype defines the kind of numerical values used: */ #define CHOLMOD_PATTERN 0 /* pattern only, no numerical values */ #define CHOLMOD_REAL 1 /* a real matrix */ #define CHOLMOD_COMPLEX 2 /* a complex matrix (ANSI C99 compatible) */ #define CHOLMOD_ZOMPLEX 3 /* a complex matrix (MATLAB compatible) */ /* The xtype of all parameters for all CHOLMOD routines must match. * * CHOLMOD_PATTERN: x and z are ignored. * CHOLMOD_DOUBLE: x is non-null of size nzmax, z is ignored. * CHOLMOD_COMPLEX: x is non-null of size 2*nzmax doubles, z is ignored. * CHOLMOD_ZOMPLEX: x and z are non-null of size nzmax * * In the real case, z is ignored. The kth entry in the matrix is x [k]. * There are two methods for the complex case. In the ANSI C99-compatible * CHOLMOD_COMPLEX case, the real and imaginary parts of the kth entry * are in x [2*k] and x [2*k+1], respectively. z is ignored. In the * MATLAB-compatible CHOLMOD_ZOMPLEX case, the real and imaginary * parts of the kth entry are in x [k] and z [k]. * * Scalar floating-point values are always passed as double arrays of size 2 * (real and imaginary parts). The imaginary part of a scalar is ignored if * the routine operates on a real matrix. * * These Modules support complex and zomplex matrices, with a few exceptions: * * Check all routines * Cholesky all routines * Core all except cholmod_aat, add, band, copy * Demo all routines * Partition all routines * Supernodal all routines support any real, complex, or zomplex input. * There will never be a supernodal zomplex L; a complex * supernodal L is created if A is zomplex. * Tcov all routines * Valgrind all routines * * These Modules provide partial support for complex and zomplex matrices: * * MATLAB all routines support real and zomplex only, not complex, * with the exception of ldlupdate, which supports * real matrices only. This is a minor constraint since * MATLAB's matrices are all real or zomplex. * MatrixOps only norm_dense, norm_sparse, and sdmult support complex * and zomplex * * These Modules do not support complex and zomplex matrices at all: * * Modify all routines support real matrices only */ /* Definitions for cholmod_common: */ #define CHOLMOD_MAXMETHODS 9 /* maximum number of different methods that */ /* cholmod_analyze can try. Must be >= 9. */ /* Common->status values. zero means success, negative means a fatal error, * positive is a warning. */ #define CHOLMOD_OK 0 /* success */ #define CHOLMOD_NOT_INSTALLED (-1) /* failure: method not installed */ #define CHOLMOD_OUT_OF_MEMORY (-2) /* failure: out of memory */ #define CHOLMOD_TOO_LARGE (-3) /* failure: integer overflow occured */ #define CHOLMOD_INVALID (-4) /* failure: invalid input */ #define CHOLMOD_GPU_PROBLEM (-5) /* failure: GPU fatal error */ #define CHOLMOD_NOT_POSDEF (1) /* warning: matrix not pos. def. */ #define CHOLMOD_DSMALL (2) /* warning: D for LDL' or diag(L) or */ /* LL' has tiny absolute value */ /* ordering method (also used for L->ordering) */ #define CHOLMOD_NATURAL 0 /* use natural ordering */ #define CHOLMOD_GIVEN 1 /* use given permutation */ #define CHOLMOD_AMD 2 /* use minimum degree (AMD) */ #define CHOLMOD_METIS 3 /* use METIS' nested dissection */ #define CHOLMOD_NESDIS 4 /* use CHOLMOD's version of nested dissection:*/ /* node bisector applied recursively, followed * by constrained minimum degree (CSYMAMD or * CCOLAMD) */ #define CHOLMOD_COLAMD 5 /* use AMD for A, COLAMD for A*A' */ /* POSTORDERED is not a method, but a result of natural ordering followed by a * weighted postorder. It is used for L->ordering, not method [ ].ordering. */ #define CHOLMOD_POSTORDERED 6 /* natural ordering, postordered. */ /* supernodal strategy (for Common->supernodal) */ #define CHOLMOD_SIMPLICIAL 0 /* always do simplicial */ #define CHOLMOD_AUTO 1 /* select simpl/super depending on matrix */ #define CHOLMOD_SUPERNODAL 2 /* always do supernodal */ typedef struct cholmod_common_struct { /* ---------------------------------------------------------------------- */ /* parameters for symbolic/numeric factorization and update/downdate */ /* ---------------------------------------------------------------------- */ double dbound ; /* Smallest absolute value of diagonal entries of D * for LDL' factorization and update/downdate/rowadd/ * rowdel, or the diagonal of L for an LL' factorization. * Entries in the range 0 to dbound are replaced with dbound. * Entries in the range -dbound to 0 are replaced with -dbound. No * changes are made to the diagonal if dbound <= 0. Default: zero */ double grow0 ; /* For a simplicial factorization, L->i and L->x can * grow if necessary. grow0 is the factor by which * it grows. For the initial space, L is of size MAX (1,grow0) times * the required space. If L runs out of space, the new size of L is * MAX(1.2,grow0) times the new required space. If you do not plan on * modifying the LDL' factorization in the Modify module, set grow0 to * zero (or set grow2 to 0, see below). Default: 1.2 */ double grow1 ; size_t grow2 ; /* For a simplicial factorization, each column j of L * is initialized with space equal to * grow1*L->ColCount[j] + grow2. If grow0 < 1, grow1 < 1, or grow2 == 0, * then the space allocated is exactly equal to L->ColCount[j]. If the * column j runs out of space, it increases to grow1*need + grow2 in * size, where need is the total # of nonzeros in that column. If you do * not plan on modifying the factorization in the Modify module, set * grow2 to zero. Default: grow1 = 1.2, grow2 = 5. */ size_t maxrank ; /* rank of maximum update/downdate. Valid values: * 2, 4, or 8. A value < 2 is set to 2, and a * value > 8 is set to 8. It is then rounded up to the next highest * power of 2, if not already a power of 2. Workspace (Xwork, below) of * size nrow-by-maxrank double's is allocated for the update/downdate. * If an update/downdate of rank-k is requested, with k > maxrank, * it is done in steps of maxrank. Default: 8, which is fastest. * Memory usage can be reduced by setting maxrank to 2 or 4. */ double supernodal_switch ; /* supernodal vs simplicial factorization */ int supernodal ; /* If Common->supernodal <= CHOLMOD_SIMPLICIAL * (0) then cholmod_analyze performs a * simplicial analysis. If >= CHOLMOD_SUPERNODAL (2), then a supernodal * analysis is performed. If == CHOLMOD_AUTO (1) and * flop/nnz(L) < Common->supernodal_switch, then a simplicial analysis * is done. A supernodal analysis done otherwise. * Default: CHOLMOD_AUTO. Default supernodal_switch = 40 */ int final_asis ; /* If TRUE, then ignore the other final_* parameters * (except for final_pack). * The factor is left as-is when done. Default: TRUE.*/ int final_super ; /* If TRUE, leave a factor in supernodal form when * supernodal factorization is finished. If FALSE, * then convert to a simplicial factor when done. * Default: TRUE */ int final_ll ; /* If TRUE, leave factor in LL' form when done. * Otherwise, leave in LDL' form. Default: FALSE */ int final_pack ; /* If TRUE, pack the columns when done. If TRUE, and * cholmod_factorize is called with a symbolic L, L is * allocated with exactly the space required, using L->ColCount. If you * plan on modifying the factorization, set Common->final_pack to FALSE, * and each column will be given a little extra slack space for future * growth in fill-in due to updates. Default: TRUE */ int final_monotonic ; /* If TRUE, ensure columns are monotonic when done. * Default: TRUE */ int final_resymbol ;/* if cholmod_factorize performed a supernodal * factorization, final_resymbol is true, and * final_super is FALSE (convert a simplicial numeric factorization), * then numerically zero entries that resulted from relaxed supernodal * amalgamation are removed. This does not remove entries that are zero * due to exact numeric cancellation, since doing so would break the * update/downdate rowadd/rowdel routines. Default: FALSE. */ /* supernodal relaxed amalgamation parameters: */ double zrelax [3] ; size_t nrelax [3] ; /* Let ns be the total number of columns in two adjacent supernodes. * Let z be the fraction of zero entries in the two supernodes if they * are merged (z includes zero entries from prior amalgamations). The * two supernodes are merged if: * (ns <= nrelax [0]) || (no new zero entries added) || * (ns <= nrelax [1] && z < zrelax [0]) || * (ns <= nrelax [2] && z < zrelax [1]) || (z < zrelax [2]) * * Default parameters result in the following rule: * (ns <= 4) || (no new zero entries added) || * (ns <= 16 && z < 0.8) || (ns <= 48 && z < 0.1) || (z < 0.05) */ int prefer_zomplex ; /* X = cholmod_solve (sys, L, B, Common) computes * x=A\b or solves a related system. If L and B are * both real, then X is real. Otherwise, X is returned as * CHOLMOD_COMPLEX if Common->prefer_zomplex is FALSE, or * CHOLMOD_ZOMPLEX if Common->prefer_zomplex is TRUE. This parameter * is needed because there is no supernodal zomplex L. Suppose the * caller wants all complex matrices to be stored in zomplex form * (MATLAB, for example). A supernodal L is returned in complex form * if A is zomplex. B can be real, and thus X = cholmod_solve (L,B) * should return X as zomplex. This cannot be inferred from the input * arguments L and B. Default: FALSE, since all data types are * supported in CHOLMOD_COMPLEX form and since this is the native type * of LAPACK and the BLAS. Note that the MATLAB/cholmod.c mexFunction * sets this parameter to TRUE, since MATLAB matrices are in * CHOLMOD_ZOMPLEX form. */ int prefer_upper ; /* cholmod_analyze and cholmod_factorize work * fastest when a symmetric matrix is stored in * upper triangular form when a fill-reducing ordering is used. In * MATLAB, this corresponds to how x=A\b works. When the matrix is * ordered as-is, they work fastest when a symmetric matrix is in lower * triangular form. In MATLAB, R=chol(A) does the opposite. This * parameter affects only how cholmod_read returns a symmetric matrix. * If TRUE (the default case), a symmetric matrix is always returned in * upper-triangular form (A->stype = 1). */ int quick_return_if_not_posdef ; /* if TRUE, the supernodal numeric * factorization will return quickly if * the matrix is not positive definite. Default: FALSE. */ /* ---------------------------------------------------------------------- */ /* printing and error handling options */ /* ---------------------------------------------------------------------- */ int print ; /* print level. Default: 3 */ int precise ; /* if TRUE, print 16 digits. Otherwise print 5 */ int (*print_function) (const char *, ...) ; /* pointer to printf */ int try_catch ; /* if TRUE, then ignore errors; CHOLMOD is in the middle * of a try/catch block. No error message is printed * and the Common->error_handler function is not called. */ void (*error_handler) (int status, const char *file, int line, const char *message) ; /* Common->error_handler is the user's error handling routine. If not * NULL, this routine is called if an error occurs in CHOLMOD. status * can be CHOLMOD_OK (0), negative for a fatal error, and positive for * a warning. file is a string containing the name of the source code * file where the error occured, and line is the line number in that * file. message is a string describing the error in more detail. */ /* ---------------------------------------------------------------------- */ /* ordering options */ /* ---------------------------------------------------------------------- */ /* The cholmod_analyze routine can try many different orderings and select * the best one. It can also try one ordering method multiple times, with * different parameter settings. The default is to use three orderings, * the user's permutation (if provided), AMD which is the fastest ordering * and generally gives good fill-in, and METIS. CHOLMOD's nested dissection * (METIS with a constrained AMD) usually gives a better ordering than METIS * alone (by about 5% to 10%) but it takes more time. * * If you know the method that is best for your matrix, set Common->nmethods * to 1 and set Common->method [0] to the set of parameters for that method. * If you set it to 1 and do not provide a permutation, then only AMD will * be called. * * If METIS is not available, the default # of methods tried is 2 (the user * permutation, if any, and AMD). * * To try other methods, set Common->nmethods to the number of methods you * want to try. The suite of default methods and their parameters is * described in the cholmod_defaults routine, and summarized here: * * Common->method [i]: * i = 0: user-provided ordering (cholmod_analyze_p only) * i = 1: AMD (for both A and A*A') * i = 2: METIS * i = 3: CHOLMOD's nested dissection (NESDIS), default parameters * i = 4: natural * i = 5: NESDIS with nd_small = 20000 * i = 6: NESDIS with nd_small = 4, no constrained minimum degree * i = 7: NESDIS with no dense node removal * i = 8: AMD for A, COLAMD for A*A' * * You can modify the suite of methods you wish to try by modifying * Common.method [...] after calling cholmod_start or cholmod_defaults. * * For example, to use AMD, followed by a weighted postordering: * * Common->nmethods = 1 ; * Common->method [0].ordering = CHOLMOD_AMD ; * Common->postorder = TRUE ; * * To use the natural ordering (with no postordering): * * Common->nmethods = 1 ; * Common->method [0].ordering = CHOLMOD_NATURAL ; * Common->postorder = FALSE ; * * If you are going to factorize hundreds or more matrices with the same * nonzero pattern, you may wish to spend a great deal of time finding a * good permutation. In this case, try setting Common->nmethods to 9. * The time spent in cholmod_analysis will be very high, but you need to * call it only once. * * cholmod_analyze sets Common->current to a value between 0 and nmethods-1. * Each ordering method uses the set of options defined by this parameter. */ int nmethods ; /* The number of ordering methods to try. Default: 0. * nmethods = 0 is a special case. cholmod_analyze * will try the user-provided ordering (if given) and AMD. Let fl and * lnz be the flop count and nonzeros in L from AMD's ordering. Let * anz be the number of nonzeros in the upper or lower triangular part * of the symmetric matrix A. If fl/lnz < 500 or lnz/anz < 5, then this * is a good ordering, and METIS is not attempted. Otherwise, METIS is * tried. The best ordering found is used. If nmethods > 0, the * methods used are given in the method[ ] array, below. The first * three methods in the default suite of orderings is (1) use the given * permutation (if provided), (2) use AMD, and (3) use METIS. Maximum * allowed value is CHOLMOD_MAXMETHODS. */ int current ; /* The current method being tried. Default: 0. Valid * range is 0 to nmethods-1. */ int selected ; /* The best method found. */ /* The suite of ordering methods and parameters: */ struct cholmod_method_struct { /* statistics for this method */ double lnz ; /* nnz(L) excl. zeros from supernodal amalgamation, * for a "pure" L */ double fl ; /* flop count for a "pure", real simplicial LL' * factorization, with no extra work due to * amalgamation. Subtract n to get the LDL' flop count. Multiply * by about 4 if the matrix is complex or zomplex. */ /* ordering method parameters */ double prune_dense ;/* dense row/col control for AMD, SYMAMD, CSYMAMD, * and NESDIS (cholmod_nested_dissection). For a * symmetric n-by-n matrix, rows/columns with more than * MAX (16, prune_dense * sqrt (n)) entries are removed prior to * ordering. They appear at the end of the re-ordered matrix. * * If prune_dense < 0, only completely dense rows/cols are removed. * * This paramater is also the dense column control for COLAMD and * CCOLAMD. For an m-by-n matrix, columns with more than * MAX (16, prune_dense * sqrt (MIN (m,n))) entries are removed prior * to ordering. They appear at the end of the re-ordered matrix. * CHOLMOD factorizes A*A', so it calls COLAMD and CCOLAMD with A', * not A. Thus, this parameter affects the dense *row* control for * CHOLMOD's matrix, and the dense *column* control for COLAMD and * CCOLAMD. * * Removing dense rows and columns improves the run-time of the * ordering methods. It has some impact on ordering quality * (usually minimal, sometimes good, sometimes bad). * * Default: 10. */ double prune_dense2 ;/* dense row control for COLAMD and CCOLAMD. * Rows with more than MAX (16, dense2 * sqrt (n)) * for an m-by-n matrix are removed prior to ordering. CHOLMOD's * matrix is transposed before ordering it with COLAMD or CCOLAMD, * so this controls the dense *columns* of CHOLMOD's matrix, and * the dense *rows* of COLAMD's or CCOLAMD's matrix. * * If prune_dense2 < 0, only completely dense rows/cols are removed. * * Default: -1. Note that this is not the default for COLAMD and * CCOLAMD. -1 is best for Cholesky. 10 is best for LU. */ double nd_oksep ; /* in NESDIS, when a node separator is computed, it * discarded if nsep >= nd_oksep*n, where nsep is * the number of nodes in the separator, and n is the size of the * graph being cut. Valid range is 0 to 1. If 1 or greater, the * separator is discarded if it consists of the entire graph. * Default: 1 */ double other_1 [4] ; /* future expansion */ size_t nd_small ; /* do not partition graphs with fewer nodes than * nd_small, in NESDIS. Default: 200 (same as * METIS) */ size_t other_2 [4] ; /* future expansion */ int aggressive ; /* Aggresive absorption in AMD, COLAMD, SYMAMD, * CCOLAMD, and CSYMAMD. Default: TRUE */ int order_for_lu ; /* CCOLAMD can be optimized to produce an ordering * for LU or Cholesky factorization. CHOLMOD only * performs a Cholesky factorization. However, you may wish to use * CHOLMOD as an interface for CCOLAMD but use it for your own LU * factorization. In this case, order_for_lu should be set to FALSE. * When factorizing in CHOLMOD itself, you should *** NEVER *** set * this parameter FALSE. Default: TRUE. */ int nd_compress ; /* If TRUE, compress the graph and subgraphs before * partitioning them in NESDIS. Default: TRUE */ int nd_camd ; /* If 1, follow the nested dissection ordering * with a constrained minimum degree ordering that * respects the partitioning just found (using CAMD). If 2, use * CSYMAMD instead. If you set nd_small very small, you may not need * this ordering, and can save time by setting it to zero (no * constrained minimum degree ordering). Default: 1. */ int nd_components ; /* The nested dissection ordering finds a node * separator that splits the graph into two parts, * which may be unconnected. If nd_components is TRUE, each of * these connected components is split independently. If FALSE, * each part is split as a whole, even if it consists of more than * one connected component. Default: FALSE */ /* fill-reducing ordering to use */ int ordering ; size_t other_3 [4] ; /* future expansion */ } method [CHOLMOD_MAXMETHODS + 1] ; int postorder ; /* If TRUE, cholmod_analyze follows the ordering with a * weighted postorder of the elimination tree. Improves * supernode amalgamation. Does not affect fundamental nnz(L) and * flop count. Default: TRUE. */ /* ---------------------------------------------------------------------- */ /* memory management routines */ /* ---------------------------------------------------------------------- */ void *(*malloc_memory) (size_t) ; /* pointer to malloc */ void *(*realloc_memory) (void *, size_t) ; /* pointer to realloc */ void (*free_memory) (void *) ; /* pointer to free */ void *(*calloc_memory) (size_t, size_t) ; /* pointer to calloc */ /* ---------------------------------------------------------------------- */ /* routines for complex arithmetic */ /* ---------------------------------------------------------------------- */ int (*complex_divide) (double ax, double az, double bx, double bz, double *cx, double *cz) ; /* flag = complex_divide (ax, az, bx, bz, &cx, &cz) computes the complex * division c = a/b, where ax and az hold the real and imaginary part * of a, and b and c are stored similarly. flag is returned as 1 if * a divide-by-zero occurs, or 0 otherwise. By default, the function * pointer Common->complex_divide is set equal to cholmod_divcomplex. */ double (*hypotenuse) (double x, double y) ; /* s = hypotenuse (x,y) computes s = sqrt (x*x + y*y), but does so more * accurately. By default, the function pointer Common->hypotenuse is * set equal to cholmod_hypot. See also the hypot function in the C99 * standard, which has an identical syntax and function. If you have * a C99-compliant compiler, you can set Common->hypotenuse = hypot. */ /* ---------------------------------------------------------------------- */ /* METIS workarounds */ /* ---------------------------------------------------------------------- */ double metis_memory ; /* This is a parameter for CHOLMOD's interface to * METIS, not a parameter to METIS itself. METIS * uses an amount of memory that is difficult to estimate precisely * beforehand. If it runs out of memory, it terminates your program. * All routines in CHOLMOD except for CHOLMOD's interface to METIS * return an error status and safely return to your program if they run * out of memory. To mitigate this problem, the CHOLMOD interface * can allocate a single block of memory equal in size to an empirical * upper bound of METIS's memory usage times the Common->metis_memory * parameter, and then immediately free it. It then calls METIS. If * this pre-allocation fails, it is possible that METIS will fail as * well, and so CHOLMOD returns with an out-of-memory condition without * calling METIS. * * METIS_NodeND (used in the CHOLMOD_METIS ordering option) with its * default parameter settings typically uses about (4*nz+40n+4096) * times sizeof(int) memory, where nz is equal to the number of entries * in A for the symmetric case or AA' if an unsymmetric matrix is * being ordered (where nz includes both the upper and lower parts * of A or AA'). The observed "upper bound" (with 2 exceptions), * measured in an instrumented copy of METIS 4.0.1 on thousands of * matrices, is (10*nz+50*n+4096) * sizeof(int). Two large matrices * exceeded this bound, one by almost a factor of 2 (Gupta/gupta2). * * If your program is terminated by METIS, try setting metis_memory to * 2.0, or even higher if needed. By default, CHOLMOD assumes that METIS * does not have this problem (so that CHOLMOD will work correctly when * this issue is fixed in METIS). Thus, the default value is zero. * This work-around is not guaranteed anyway. * * If a matrix exceeds this predicted memory usage, AMD is attempted * instead. It, too, may run out of memory, but if it does so it will * not terminate your program. */ double metis_dswitch ; /* METIS_NodeND in METIS 4.0.1 gives a seg */ size_t metis_nswitch ; /* fault with one matrix of order n = 3005 and * nz = 6,036,025. This is a very dense graph. * The workaround is to use AMD instead of METIS for matrices of dimension * greater than Common->metis_nswitch (default 3000) or more and with * density of Common->metis_dswitch (default 0.66) or more. * cholmod_nested_dissection has no problems with the same matrix, even * though it uses METIS_NodeComputeSeparator on this matrix. If this * seg fault does not affect you, set metis_nswitch to zero or less, * and CHOLMOD will not switch to AMD based just on the density of the * matrix (it will still switch to AMD if the metis_memory parameter * causes the switch). */ /* ---------------------------------------------------------------------- */ /* workspace */ /* ---------------------------------------------------------------------- */ /* CHOLMOD has several routines that take less time than the size of * workspace they require. Allocating and initializing the workspace would * dominate the run time, unless workspace is allocated and initialized * just once. CHOLMOD allocates this space when needed, and holds it here * between calls to CHOLMOD. cholmod_start sets these pointers to NULL * (which is why it must be the first routine called in CHOLMOD). * cholmod_finish frees the workspace (which is why it must be the last * call to CHOLMOD). */ size_t nrow ; /* size of Flag and Head */ SuiteSparse_long mark ; /* mark value for Flag array */ size_t iworksize ; /* size of Iwork. Upper bound: 6*nrow+ncol */ size_t xworksize ; /* size of Xwork, in bytes. * maxrank*nrow*sizeof(double) for update/downdate. * 2*nrow*sizeof(double) otherwise */ /* initialized workspace: contents needed between calls to CHOLMOD */ void *Flag ; /* size nrow, an integer array. Kept cleared between * calls to cholmod rouines (Flag [i] < mark) */ void *Head ; /* size nrow+1, an integer array. Kept cleared between * calls to cholmod routines (Head [i] = EMPTY) */ void *Xwork ; /* a double array. Its size varies. It is nrow for * most routines (cholmod_rowfac, cholmod_add, * cholmod_aat, cholmod_norm, cholmod_ssmult) for the real case, twice * that when the input matrices are complex or zomplex. It is of size * 2*nrow for cholmod_rowadd and cholmod_rowdel. For cholmod_updown, * its size is maxrank*nrow where maxrank is 2, 4, or 8. Kept cleared * between calls to cholmod (set to zero). */ /* uninitialized workspace, contents not needed between calls to CHOLMOD */ void *Iwork ; /* size iworksize, 2*nrow+ncol for most routines, * up to 6*nrow+ncol for cholmod_analyze. */ int itype ; /* If CHOLMOD_LONG, Flag, Head, and Iwork are * SuiteSparse_long. Otherwise all three are int. */ int dtype ; /* double or float */ /* Common->itype and Common->dtype are used to define the types of all * sparse matrices, triplet matrices, dense matrices, and factors * created using this Common struct. The itypes and dtypes of all * parameters to all CHOLMOD routines must match. */ int no_workspace_reallocate ; /* this is an internal flag, used as a * precaution by cholmod_analyze. It is normally false. If true, * cholmod_allocate_work is not allowed to reallocate any workspace; * they must use the existing workspace in Common (Iwork, Flag, Head, * and Xwork). Added for CHOLMOD v1.1 */ /* ---------------------------------------------------------------------- */ /* statistics */ /* ---------------------------------------------------------------------- */ /* fl and lnz are set only in cholmod_analyze and cholmod_rowcolcounts, * in the Cholesky modudle. modfl is set only in the Modify module. */ int status ; /* error code */ double fl ; /* LL' flop count from most recent analysis */ double lnz ; /* fundamental nz in L */ double anz ; /* nonzeros in tril(A) if A is symmetric/lower, * triu(A) if symmetric/upper, or tril(A*A') if * unsymmetric, in last call to cholmod_analyze. */ double modfl ; /* flop count from most recent update/downdate/ * rowadd/rowdel (excluding flops to modify the * solution to Lx=b, if computed) */ size_t malloc_count ; /* # of objects malloc'ed minus the # free'd*/ size_t memory_usage ; /* peak memory usage in bytes */ size_t memory_inuse ; /* current memory usage in bytes */ double nrealloc_col ; /* # of column reallocations */ double nrealloc_factor ;/* # of factor reallocations due to col. reallocs */ double ndbounds_hit ; /* # of times diagonal modified by dbound */ double rowfacfl ; /* # of flops in last call to cholmod_rowfac */ double aatfl ; /* # of flops to compute A(:,f)*A(:,f)' */ /* ---------------------------------------------------------------------- */ /* statistics, parameters, and future expansion */ /* ---------------------------------------------------------------------- */ /* The goal for future expansion is to keep sizeof(Common) unchanged. */ double other1 [10] ; /* [0..9] for CHOLMOD GPU/CPU numerical factorization statistics, and [0..3] used by SuiteSparseQR statistics */ double SPQR_xstat [4] ; /* for SuiteSparseQR statistics */ /* SuiteSparseQR control parameters: */ double SPQR_grain ; /* task size is >= max (total flops / grain) */ double SPQR_small ; /* task size is >= small */ /* ---------------------------------------------------------------------- */ SuiteSparse_long SPQR_istat [10] ; /* for SuiteSparseQR statistics */ SuiteSparse_long other2 [6] ; /* unused (for future expansion) */ /* ---------------------------------------------------------------------- */ int other3 [10] ; /* unused (for future expansion) */ int prefer_binary ; /* cholmod_read_triplet converts a symmetric * pattern-only matrix into a real matrix. If * prefer_binary is FALSE, the diagonal entries are set to 1 + the degree * of the row/column, and off-diagonal entries are set to -1 (resulting * in a positive definite matrix if the diagonal is zero-free). Most * symmetric patterns are the pattern a positive definite matrix. If * this parameter is TRUE, then the matrix is returned with a 1 in each * entry, instead. Default: FALSE. Added in v1.3. */ /* control parameter (added for v1.2): */ int default_nesdis ; /* Default: FALSE. If FALSE, then the default * ordering strategy (when Common->nmethods == 0) * is to try the given ordering (if present), AMD, and then METIS if AMD * reports high fill-in. If Common->default_nesdis is TRUE then NESDIS * is used instead in the default strategy. */ /* statistic (added for v1.2): */ int called_nd ; /* TRUE if the last call to * cholmod_analyze called NESDIS or METIS. */ int blas_ok ; /* FALSE if BLAS int overflow; TRUE otherwise */ /* SuiteSparseQR control parameters: */ int SPQR_shrink ; /* controls stack realloc method */ int SPQR_nthreads ; /* number of TBB threads, 0 = auto */ /* ---------------------------------------------------------------------- */ size_t other4 [16] ; /* [0..7] for CHOLMOD GPU/CPU numerical factorization statistics, remainder unused (for future expansion) */ /* ---------------------------------------------------------------------- */ void *other5 [16] ; /* unused (for future expansion) */ /* ---------------------------------------------------------------------- */ /* GPU configuration */ /* ---------------------------------------------------------------------- */ #ifdef GPU_BLAS /* gpuConfig_t gpuConfig ; */ cublasHandle_t cublasHandle ; cudaStream_t cudaStreamSyrk ; cudaStream_t cudaStreamGemm ; cudaStream_t cudaStreamTrsm ; cudaStream_t cudaStreamPotrf [3] ; cudaEvent_t cublasEventPotrf [2] ; void *HostPinnedMemory ; void *devPotrfWork ; void *devSyrkGemmPtrLx ; void *devSyrkGemmPtrC ; int GemmUsed ; /* TRUE if cuda dgemm used, false otherwise */ int SyrkUsed ; /* TRUE if cuda dsyrk used, false otherwise */ double syrkStart ; /* time syrk started */ #endif } cholmod_common ; /* size_t BLAS statistcs in Common: */ #define CHOLMOD_CPU_GEMM_CALLS other4 [0] #define CHOLMOD_CPU_SYRK_CALLS other4 [1] #define CHOLMOD_CPU_TRSM_CALLS other4 [2] #define CHOLMOD_CPU_POTRF_CALLS other4 [3] #define CHOLMOD_GPU_GEMM_CALLS other4 [4] #define CHOLMOD_GPU_SYRK_CALLS other4 [5] #define CHOLMOD_GPU_TRSM_CALLS other4 [6] #define CHOLMOD_GPU_POTRF_CALLS other4 [7] /* double BLAS statistics in Common: */ #define CHOLMOD_CPU_GEMM_TIME other1 [0] #define CHOLMOD_CPU_SYRK_TIME other1 [1] #define CHOLMOD_CPU_TRSM_TIME other1 [2] #define CHOLMOD_CPU_POTRF_TIME other1 [3] #define CHOLMOD_GPU_GEMM_TIME other1 [4] #define CHOLMOD_GPU_SYRK_TIME other1 [5] #define CHOLMOD_GPU_TRSM_TIME other1 [6] #define CHOLMOD_GPU_POTRF_TIME other1 [7] #define CHOLMOD_ASSEMBLE_TIME other1 [8] #define CHOLMOD_ASSEMBLE_TIME2 other1 [9] /* -------------------------------------------------------------------------- */ /* cholmod_start: first call to CHOLMOD */ /* -------------------------------------------------------------------------- */ int cholmod_start ( cholmod_common *Common ) ; int cholmod_l_start (cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_finish: last call to CHOLMOD */ /* -------------------------------------------------------------------------- */ int cholmod_finish ( cholmod_common *Common ) ; int cholmod_l_finish (cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_defaults: restore default parameters */ /* -------------------------------------------------------------------------- */ int cholmod_defaults ( cholmod_common *Common ) ; int cholmod_l_defaults (cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_maxrank: return valid maximum rank for update/downdate */ /* -------------------------------------------------------------------------- */ size_t cholmod_maxrank /* returns validated value of Common->maxrank */ ( /* ---- input ---- */ size_t n, /* A and L will have n rows */ /* --------------- */ cholmod_common *Common ) ; size_t cholmod_l_maxrank (size_t, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_allocate_work: allocate workspace in Common */ /* -------------------------------------------------------------------------- */ int cholmod_allocate_work ( /* ---- input ---- */ size_t nrow, /* size: Common->Flag (nrow), Common->Head (nrow+1) */ size_t iworksize, /* size of Common->Iwork */ size_t xworksize, /* size of Common->Xwork */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_allocate_work (size_t, size_t, size_t, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_free_work: free workspace in Common */ /* -------------------------------------------------------------------------- */ int cholmod_free_work ( cholmod_common *Common ) ; int cholmod_l_free_work (cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_clear_flag: clear Flag workspace in Common */ /* -------------------------------------------------------------------------- */ /* use a macro for speed */ #define CHOLMOD_CLEAR_FLAG(Common) \ { \ Common->mark++ ; \ if (Common->mark <= 0) \ { \ Common->mark = EMPTY ; \ CHOLMOD (clear_flag) (Common) ; \ } \ } SuiteSparse_long cholmod_clear_flag ( cholmod_common *Common ) ; SuiteSparse_long cholmod_l_clear_flag (cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_error: called when CHOLMOD encounters an error */ /* -------------------------------------------------------------------------- */ int cholmod_error ( /* ---- input ---- */ int status, /* error status */ const char *file, /* name of source code file where error occured */ int line, /* line number in source code file where error occured*/ const char *message,/* error message */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_error (int, const char *, int, const char *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_dbound: for internal use in CHOLMOD only */ /* -------------------------------------------------------------------------- */ double cholmod_dbound /* returns modified diagonal entry of D or L */ ( /* ---- input ---- */ double dj, /* diagonal entry of D for LDL' or L for LL' */ /* --------------- */ cholmod_common *Common ) ; double cholmod_l_dbound (double, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_hypot: compute sqrt (x*x + y*y) accurately */ /* -------------------------------------------------------------------------- */ double cholmod_hypot ( /* ---- input ---- */ double x, double y ) ; double cholmod_l_hypot (double, double) ; /* -------------------------------------------------------------------------- */ /* cholmod_divcomplex: complex division, c = a/b */ /* -------------------------------------------------------------------------- */ int cholmod_divcomplex /* return 1 if divide-by-zero, 0 otherise */ ( /* ---- input ---- */ double ar, double ai, /* real and imaginary parts of a */ double br, double bi, /* real and imaginary parts of b */ /* ---- output --- */ double *cr, double *ci /* real and imaginary parts of c */ ) ; int cholmod_l_divcomplex (double, double, double, double, double *, double *) ; /* ========================================================================== */ /* === Core/cholmod_sparse ================================================== */ /* ========================================================================== */ /* A sparse matrix stored in compressed-column form. */ typedef struct cholmod_sparse_struct { size_t nrow ; /* the matrix is nrow-by-ncol */ size_t ncol ; size_t nzmax ; /* maximum number of entries in the matrix */ /* pointers to int or SuiteSparse_long: */ void *p ; /* p [0..ncol], the column pointers */ void *i ; /* i [0..nzmax-1], the row indices */ /* for unpacked matrices only: */ void *nz ; /* nz [0..ncol-1], the # of nonzeros in each col. In * packed form, the nonzero pattern of column j is in * A->i [A->p [j] ... A->p [j+1]-1]. In unpacked form, column j is in * A->i [A->p [j] ... A->p [j]+A->nz[j]-1] instead. In both cases, the * numerical values (if present) are in the corresponding locations in * the array x (or z if A->xtype is CHOLMOD_ZOMPLEX). */ /* pointers to double or float: */ void *x ; /* size nzmax or 2*nzmax, if present */ void *z ; /* size nzmax, if present */ int stype ; /* Describes what parts of the matrix are considered: * * 0: matrix is "unsymmetric": use both upper and lower triangular parts * (the matrix may actually be symmetric in pattern and value, but * both parts are explicitly stored and used). May be square or * rectangular. * >0: matrix is square and symmetric, use upper triangular part. * Entries in the lower triangular part are ignored. * <0: matrix is square and symmetric, use lower triangular part. * Entries in the upper triangular part are ignored. * * Note that stype>0 and stype<0 are different for cholmod_sparse and * cholmod_triplet. See the cholmod_triplet data structure for more * details. */ int itype ; /* CHOLMOD_INT: p, i, and nz are int. * CHOLMOD_INTLONG: p is SuiteSparse_long, * i and nz are int. * CHOLMOD_LONG: p, i, and nz are SuiteSparse_long */ int xtype ; /* pattern, real, complex, or zomplex */ int dtype ; /* x and z are double or float */ int sorted ; /* TRUE if columns are sorted, FALSE otherwise */ int packed ; /* TRUE if packed (nz ignored), FALSE if unpacked * (nz is required) */ } cholmod_sparse ; /* -------------------------------------------------------------------------- */ /* cholmod_allocate_sparse: allocate a sparse matrix */ /* -------------------------------------------------------------------------- */ cholmod_sparse *cholmod_allocate_sparse ( /* ---- input ---- */ size_t nrow, /* # of rows of A */ size_t ncol, /* # of columns of A */ size_t nzmax, /* max # of nonzeros of A */ int sorted, /* TRUE if columns of A sorted, FALSE otherwise */ int packed, /* TRUE if A will be packed, FALSE otherwise */ int stype, /* stype of A */ int xtype, /* CHOLMOD_PATTERN, _REAL, _COMPLEX, or _ZOMPLEX */ /* --------------- */ cholmod_common *Common ) ; cholmod_sparse *cholmod_l_allocate_sparse (size_t, size_t, size_t, int, int, int, int, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_free_sparse: free a sparse matrix */ /* -------------------------------------------------------------------------- */ int cholmod_free_sparse ( /* ---- in/out --- */ cholmod_sparse **A, /* matrix to deallocate, NULL on output */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_free_sparse (cholmod_sparse **, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_reallocate_sparse: change the size (# entries) of sparse matrix */ /* -------------------------------------------------------------------------- */ int cholmod_reallocate_sparse ( /* ---- input ---- */ size_t nznew, /* new # of entries in A */ /* ---- in/out --- */ cholmod_sparse *A, /* matrix to reallocate */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_reallocate_sparse ( size_t, cholmod_sparse *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_nnz: return number of nonzeros in a sparse matrix */ /* -------------------------------------------------------------------------- */ SuiteSparse_long cholmod_nnz ( /* ---- input ---- */ cholmod_sparse *A, /* --------------- */ cholmod_common *Common ) ; SuiteSparse_long cholmod_l_nnz (cholmod_sparse *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_speye: sparse identity matrix */ /* -------------------------------------------------------------------------- */ cholmod_sparse *cholmod_speye ( /* ---- input ---- */ size_t nrow, /* # of rows of A */ size_t ncol, /* # of columns of A */ int xtype, /* CHOLMOD_PATTERN, _REAL, _COMPLEX, or _ZOMPLEX */ /* --------------- */ cholmod_common *Common ) ; cholmod_sparse *cholmod_l_speye (size_t, size_t, int, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_spzeros: sparse zero matrix */ /* -------------------------------------------------------------------------- */ cholmod_sparse *cholmod_spzeros ( /* ---- input ---- */ size_t nrow, /* # of rows of A */ size_t ncol, /* # of columns of A */ size_t nzmax, /* max # of nonzeros of A */ int xtype, /* CHOLMOD_PATTERN, _REAL, _COMPLEX, or _ZOMPLEX */ /* --------------- */ cholmod_common *Common ) ; cholmod_sparse *cholmod_l_spzeros (size_t, size_t, size_t, int, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_transpose: transpose a sparse matrix */ /* -------------------------------------------------------------------------- */ /* Return A' or A.' The "values" parameter is 0, 1, or 2 to denote the pattern * transpose, the array transpose (A.'), and the complex conjugate transpose * (A'). */ cholmod_sparse *cholmod_transpose ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to transpose */ int values, /* 0: pattern, 1: array transpose, 2: conj. transpose */ /* --------------- */ cholmod_common *Common ) ; cholmod_sparse *cholmod_l_transpose (cholmod_sparse *, int, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_transpose_unsym: transpose an unsymmetric sparse matrix */ /* -------------------------------------------------------------------------- */ /* Compute F = A', A (:,f)', or A (p,f)', where A is unsymmetric and F is * already allocated. See cholmod_transpose for a simpler routine. */ int cholmod_transpose_unsym ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to transpose */ int values, /* 0: pattern, 1: array transpose, 2: conj. transpose */ int *Perm, /* size nrow, if present (can be NULL) */ int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ /* ---- output --- */ cholmod_sparse *F, /* F = A', A(:,f)', or A(p,f)' */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_transpose_unsym (cholmod_sparse *, int, SuiteSparse_long *, SuiteSparse_long *, size_t, cholmod_sparse *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_transpose_sym: transpose a symmetric sparse matrix */ /* -------------------------------------------------------------------------- */ /* Compute F = A' or A (p,p)', where A is symmetric and F is already allocated. * See cholmod_transpose for a simpler routine. */ int cholmod_transpose_sym ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to transpose */ int values, /* 0: pattern, 1: array transpose, 2: conj. transpose */ int *Perm, /* size nrow, if present (can be NULL) */ /* ---- output --- */ cholmod_sparse *F, /* F = A' or A(p,p)' */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_transpose_sym (cholmod_sparse *, int, SuiteSparse_long *, cholmod_sparse *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_ptranspose: transpose a sparse matrix */ /* -------------------------------------------------------------------------- */ /* Return A' or A(p,p)' if A is symmetric. Return A', A(:,f)', or A(p,f)' if * A is unsymmetric. */ cholmod_sparse *cholmod_ptranspose ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to transpose */ int values, /* 0: pattern, 1: array transpose, 2: conj. transpose */ int *Perm, /* if non-NULL, F = A(p,f) or A(p,p) */ int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ /* --------------- */ cholmod_common *Common ) ; cholmod_sparse *cholmod_l_ptranspose (cholmod_sparse *, int, SuiteSparse_long *, SuiteSparse_long *, size_t, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_sort: sort row indices in each column of sparse matrix */ /* -------------------------------------------------------------------------- */ int cholmod_sort ( /* ---- in/out --- */ cholmod_sparse *A, /* matrix to sort */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_sort (cholmod_sparse *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_band: C = tril (triu (A,k1), k2) */ /* -------------------------------------------------------------------------- */ cholmod_sparse *cholmod_band ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to extract band matrix from */ SuiteSparse_long k1, /* ignore entries below the k1-st diagonal */ SuiteSparse_long k2, /* ignore entries above the k2-nd diagonal */ int mode, /* >0: numerical, 0: pattern, <0: pattern (no diag) */ /* --------------- */ cholmod_common *Common ) ; cholmod_sparse *cholmod_l_band (cholmod_sparse *, SuiteSparse_long, SuiteSparse_long, int, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_band_inplace: A = tril (triu (A,k1), k2) */ /* -------------------------------------------------------------------------- */ int cholmod_band_inplace ( /* ---- input ---- */ SuiteSparse_long k1, /* ignore entries below the k1-st diagonal */ SuiteSparse_long k2, /* ignore entries above the k2-nd diagonal */ int mode, /* >0: numerical, 0: pattern, <0: pattern (no diag) */ /* ---- in/out --- */ cholmod_sparse *A, /* matrix from which entries not in band are removed */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_band_inplace (SuiteSparse_long, SuiteSparse_long, int, cholmod_sparse *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_aat: C = A*A' or A(:,f)*A(:,f)' */ /* -------------------------------------------------------------------------- */ cholmod_sparse *cholmod_aat ( /* ---- input ---- */ cholmod_sparse *A, /* input matrix; C=A*A' is constructed */ int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ int mode, /* >0: numerical, 0: pattern, <0: pattern (no diag), * -2: pattern only, no diagonal, add 50%+n extra * space to C */ /* --------------- */ cholmod_common *Common ) ; cholmod_sparse *cholmod_l_aat (cholmod_sparse *, SuiteSparse_long *, size_t, int, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_copy_sparse: C = A, create an exact copy of a sparse matrix */ /* -------------------------------------------------------------------------- */ cholmod_sparse *cholmod_copy_sparse ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to copy */ /* --------------- */ cholmod_common *Common ) ; cholmod_sparse *cholmod_l_copy_sparse (cholmod_sparse *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_copy: C = A, with possible change of stype */ /* -------------------------------------------------------------------------- */ cholmod_sparse *cholmod_copy ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to copy */ int stype, /* requested stype of C */ int mode, /* >0: numerical, 0: pattern, <0: pattern (no diag) */ /* --------------- */ cholmod_common *Common ) ; cholmod_sparse *cholmod_l_copy (cholmod_sparse *, int, int, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_add: C = alpha*A + beta*B */ /* -------------------------------------------------------------------------- */ cholmod_sparse *cholmod_add ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to add */ cholmod_sparse *B, /* matrix to add */ double alpha [2], /* scale factor for A */ double beta [2], /* scale factor for B */ int values, /* if TRUE compute the numerical values of C */ int sorted, /* if TRUE, sort columns of C */ /* --------------- */ cholmod_common *Common ) ; cholmod_sparse *cholmod_l_add (cholmod_sparse *, cholmod_sparse *, double *, double *, int, int, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_sparse_xtype: change the xtype of a sparse matrix */ /* -------------------------------------------------------------------------- */ int cholmod_sparse_xtype ( /* ---- input ---- */ int to_xtype, /* requested xtype (pattern, real, complex, zomplex) */ /* ---- in/out --- */ cholmod_sparse *A, /* sparse matrix to change */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_sparse_xtype (int, cholmod_sparse *, cholmod_common *) ; /* ========================================================================== */ /* === Core/cholmod_factor ================================================== */ /* ========================================================================== */ /* A symbolic and numeric factorization, either simplicial or supernodal. * In all cases, the row indices in the columns of L are kept sorted. */ typedef struct cholmod_factor_struct { /* ---------------------------------------------------------------------- */ /* for both simplicial and supernodal factorizations */ /* ---------------------------------------------------------------------- */ size_t n ; /* L is n-by-n */ size_t minor ; /* If the factorization failed, L->minor is the column * at which it failed (in the range 0 to n-1). A value * of n means the factorization was successful or * the matrix has not yet been factorized. */ /* ---------------------------------------------------------------------- */ /* symbolic ordering and analysis */ /* ---------------------------------------------------------------------- */ void *Perm ; /* size n, permutation used */ void *ColCount ; /* size n, column counts for simplicial L */ void *IPerm ; /* size n, inverse permutation. Only created by * cholmod_solve2 if Bset is used. */ /* ---------------------------------------------------------------------- */ /* simplicial factorization */ /* ---------------------------------------------------------------------- */ size_t nzmax ; /* size of i and x */ void *p ; /* p [0..ncol], the column pointers */ void *i ; /* i [0..nzmax-1], the row indices */ void *x ; /* x [0..nzmax-1], the numerical values */ void *z ; void *nz ; /* nz [0..ncol-1], the # of nonzeros in each column. * i [p [j] ... p [j]+nz[j]-1] contains the row indices, * and the numerical values are in the same locatins * in x. The value of i [p [k]] is always k. */ void *next ; /* size ncol+2. next [j] is the next column in i/x */ void *prev ; /* size ncol+2. prev [j] is the prior column in i/x. * head of the list is ncol+1, and the tail is ncol. */ /* ---------------------------------------------------------------------- */ /* supernodal factorization */ /* ---------------------------------------------------------------------- */ /* Note that L->x is shared with the simplicial data structure. L->x has * size L->nzmax for a simplicial factor, and size L->xsize for a supernodal * factor. */ size_t nsuper ; /* number of supernodes */ size_t ssize ; /* size of s, integer part of supernodes */ size_t xsize ; /* size of x, real part of supernodes */ size_t maxcsize ; /* size of largest update matrix */ size_t maxesize ; /* max # of rows in supernodes, excl. triangular part */ void *super ; /* size nsuper+1, first col in each supernode */ void *pi ; /* size nsuper+1, pointers to integer patterns */ void *px ; /* size nsuper+1, pointers to real parts */ void *s ; /* size ssize, integer part of supernodes */ /* ---------------------------------------------------------------------- */ /* factorization type */ /* ---------------------------------------------------------------------- */ int ordering ; /* ordering method used */ int is_ll ; /* TRUE if LL', FALSE if LDL' */ int is_super ; /* TRUE if supernodal, FALSE if simplicial */ int is_monotonic ; /* TRUE if columns of L appear in order 0..n-1. * Only applicable to simplicial numeric types. */ /* There are 8 types of factor objects that cholmod_factor can represent * (only 6 are used): * * Numeric types (xtype is not CHOLMOD_PATTERN) * -------------------------------------------- * * simplicial LDL': (is_ll FALSE, is_super FALSE). Stored in compressed * column form, using the simplicial components above (nzmax, p, i, * x, z, nz, next, and prev). The unit diagonal of L is not stored, * and D is stored in its place. There are no supernodes. * * simplicial LL': (is_ll TRUE, is_super FALSE). Uses the same storage * scheme as the simplicial LDL', except that D does not appear. * The first entry of each column of L is the diagonal entry of * that column of L. * * supernodal LDL': (is_ll FALSE, is_super TRUE). Not used. * FUTURE WORK: add support for supernodal LDL' * * supernodal LL': (is_ll TRUE, is_super TRUE). A supernodal factor, * using the supernodal components described above (nsuper, ssize, * xsize, maxcsize, maxesize, super, pi, px, s, x, and z). * * * Symbolic types (xtype is CHOLMOD_PATTERN) * ----------------------------------------- * * simplicial LDL': (is_ll FALSE, is_super FALSE). Nothing is present * except Perm and ColCount. * * simplicial LL': (is_ll TRUE, is_super FALSE). Identical to the * simplicial LDL', except for the is_ll flag. * * supernodal LDL': (is_ll FALSE, is_super TRUE). Not used. * FUTURE WORK: add support for supernodal LDL' * * supernodal LL': (is_ll TRUE, is_super TRUE). A supernodal symbolic * factorization. The simplicial symbolic information is present * (Perm and ColCount), as is all of the supernodal factorization * except for the numerical values (x and z). */ int itype ; /* The integer arrays are Perm, ColCount, p, i, nz, * next, prev, super, pi, px, and s. If itype is * CHOLMOD_INT, all of these are int arrays. * CHOLMOD_INTLONG: p, pi, px are SuiteSparse_long, others int. * CHOLMOD_LONG: all integer arrays are SuiteSparse_long. */ int xtype ; /* pattern, real, complex, or zomplex */ int dtype ; /* x and z double or float */ } cholmod_factor ; /* -------------------------------------------------------------------------- */ /* cholmod_allocate_factor: allocate a factor (symbolic LL' or LDL') */ /* -------------------------------------------------------------------------- */ cholmod_factor *cholmod_allocate_factor ( /* ---- input ---- */ size_t n, /* L is n-by-n */ /* --------------- */ cholmod_common *Common ) ; cholmod_factor *cholmod_l_allocate_factor (size_t, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_free_factor: free a factor */ /* -------------------------------------------------------------------------- */ int cholmod_free_factor ( /* ---- in/out --- */ cholmod_factor **L, /* factor to free, NULL on output */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_free_factor (cholmod_factor **, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_reallocate_factor: change the # entries in a factor */ /* -------------------------------------------------------------------------- */ int cholmod_reallocate_factor ( /* ---- input ---- */ size_t nznew, /* new # of entries in L */ /* ---- in/out --- */ cholmod_factor *L, /* factor to modify */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_reallocate_factor (size_t, cholmod_factor *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_change_factor: change the type of factor (e.g., LDL' to LL') */ /* -------------------------------------------------------------------------- */ int cholmod_change_factor ( /* ---- input ---- */ int to_xtype, /* to CHOLMOD_PATTERN, _REAL, _COMPLEX, _ZOMPLEX */ int to_ll, /* TRUE: convert to LL', FALSE: LDL' */ int to_super, /* TRUE: convert to supernodal, FALSE: simplicial */ int to_packed, /* TRUE: pack simplicial columns, FALSE: do not pack */ int to_monotonic, /* TRUE: put simplicial columns in order, FALSE: not */ /* ---- in/out --- */ cholmod_factor *L, /* factor to modify */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_change_factor ( int, int, int, int, int, cholmod_factor *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_pack_factor: pack the columns of a factor */ /* -------------------------------------------------------------------------- */ /* Pack the columns of a simplicial factor. Unlike cholmod_change_factor, * it can pack the columns of a factor even if they are not stored in their * natural order (non-monotonic). */ int cholmod_pack_factor ( /* ---- in/out --- */ cholmod_factor *L, /* factor to modify */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_pack_factor (cholmod_factor *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_reallocate_column: resize a single column of a factor */ /* -------------------------------------------------------------------------- */ int cholmod_reallocate_column ( /* ---- input ---- */ size_t j, /* the column to reallocate */ size_t need, /* required size of column j */ /* ---- in/out --- */ cholmod_factor *L, /* factor to modify */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_reallocate_column (size_t, size_t, cholmod_factor *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_factor_to_sparse: create a sparse matrix copy of a factor */ /* -------------------------------------------------------------------------- */ /* Only operates on numeric factors, not symbolic ones */ cholmod_sparse *cholmod_factor_to_sparse ( /* ---- in/out --- */ cholmod_factor *L, /* factor to copy, converted to symbolic on output */ /* --------------- */ cholmod_common *Common ) ; cholmod_sparse *cholmod_l_factor_to_sparse (cholmod_factor *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_copy_factor: create a copy of a factor */ /* -------------------------------------------------------------------------- */ cholmod_factor *cholmod_copy_factor ( /* ---- input ---- */ cholmod_factor *L, /* factor to copy */ /* --------------- */ cholmod_common *Common ) ; cholmod_factor *cholmod_l_copy_factor (cholmod_factor *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_factor_xtype: change the xtype of a factor */ /* -------------------------------------------------------------------------- */ int cholmod_factor_xtype ( /* ---- input ---- */ int to_xtype, /* requested xtype (real, complex, or zomplex) */ /* ---- in/out --- */ cholmod_factor *L, /* factor to change */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_factor_xtype (int, cholmod_factor *, cholmod_common *) ; /* ========================================================================== */ /* === Core/cholmod_dense =================================================== */ /* ========================================================================== */ /* A dense matrix in column-oriented form. It has no itype since it contains * no integers. Entry in row i and column j is located in x [i+j*d]. */ typedef struct cholmod_dense_struct { size_t nrow ; /* the matrix is nrow-by-ncol */ size_t ncol ; size_t nzmax ; /* maximum number of entries in the matrix */ size_t d ; /* leading dimension (d >= nrow must hold) */ void *x ; /* size nzmax or 2*nzmax, if present */ void *z ; /* size nzmax, if present */ int xtype ; /* pattern, real, complex, or zomplex */ int dtype ; /* x and z double or float */ } cholmod_dense ; /* -------------------------------------------------------------------------- */ /* cholmod_allocate_dense: allocate a dense matrix (contents uninitialized) */ /* -------------------------------------------------------------------------- */ cholmod_dense *cholmod_allocate_dense ( /* ---- input ---- */ size_t nrow, /* # of rows of matrix */ size_t ncol, /* # of columns of matrix */ size_t d, /* leading dimension */ int xtype, /* CHOLMOD_REAL, _COMPLEX, or _ZOMPLEX */ /* --------------- */ cholmod_common *Common ) ; cholmod_dense *cholmod_l_allocate_dense (size_t, size_t, size_t, int, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_zeros: allocate a dense matrix and set it to zero */ /* -------------------------------------------------------------------------- */ cholmod_dense *cholmod_zeros ( /* ---- input ---- */ size_t nrow, /* # of rows of matrix */ size_t ncol, /* # of columns of matrix */ int xtype, /* CHOLMOD_REAL, _COMPLEX, or _ZOMPLEX */ /* --------------- */ cholmod_common *Common ) ; cholmod_dense *cholmod_l_zeros (size_t, size_t, int, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_ones: allocate a dense matrix and set it to all ones */ /* -------------------------------------------------------------------------- */ cholmod_dense *cholmod_ones ( /* ---- input ---- */ size_t nrow, /* # of rows of matrix */ size_t ncol, /* # of columns of matrix */ int xtype, /* CHOLMOD_REAL, _COMPLEX, or _ZOMPLEX */ /* --------------- */ cholmod_common *Common ) ; cholmod_dense *cholmod_l_ones (size_t, size_t, int, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_eye: allocate a dense matrix and set it to the identity matrix */ /* -------------------------------------------------------------------------- */ cholmod_dense *cholmod_eye ( /* ---- input ---- */ size_t nrow, /* # of rows of matrix */ size_t ncol, /* # of columns of matrix */ int xtype, /* CHOLMOD_REAL, _COMPLEX, or _ZOMPLEX */ /* --------------- */ cholmod_common *Common ) ; cholmod_dense *cholmod_l_eye (size_t, size_t, int, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_free_dense: free a dense matrix */ /* -------------------------------------------------------------------------- */ int cholmod_free_dense ( /* ---- in/out --- */ cholmod_dense **X, /* dense matrix to deallocate, NULL on output */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_free_dense (cholmod_dense **, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_ensure_dense: ensure a dense matrix has a given size and type */ /* -------------------------------------------------------------------------- */ cholmod_dense *cholmod_ensure_dense ( /* ---- input/output ---- */ cholmod_dense **XHandle, /* matrix handle to check */ /* ---- input ---- */ size_t nrow, /* # of rows of matrix */ size_t ncol, /* # of columns of matrix */ size_t d, /* leading dimension */ int xtype, /* CHOLMOD_REAL, _COMPLEX, or _ZOMPLEX */ /* --------------- */ cholmod_common *Common ) ; cholmod_dense *cholmod_l_ensure_dense (cholmod_dense **, size_t, size_t, size_t, int, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_sparse_to_dense: create a dense matrix copy of a sparse matrix */ /* -------------------------------------------------------------------------- */ cholmod_dense *cholmod_sparse_to_dense ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to copy */ /* --------------- */ cholmod_common *Common ) ; cholmod_dense *cholmod_l_sparse_to_dense (cholmod_sparse *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_dense_to_sparse: create a sparse matrix copy of a dense matrix */ /* -------------------------------------------------------------------------- */ cholmod_sparse *cholmod_dense_to_sparse ( /* ---- input ---- */ cholmod_dense *X, /* matrix to copy */ int values, /* TRUE if values to be copied, FALSE otherwise */ /* --------------- */ cholmod_common *Common ) ; cholmod_sparse *cholmod_l_dense_to_sparse (cholmod_dense *, int, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_copy_dense: create a copy of a dense matrix */ /* -------------------------------------------------------------------------- */ cholmod_dense *cholmod_copy_dense ( /* ---- input ---- */ cholmod_dense *X, /* matrix to copy */ /* --------------- */ cholmod_common *Common ) ; cholmod_dense *cholmod_l_copy_dense (cholmod_dense *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_copy_dense2: copy a dense matrix (pre-allocated) */ /* -------------------------------------------------------------------------- */ int cholmod_copy_dense2 ( /* ---- input ---- */ cholmod_dense *X, /* matrix to copy */ /* ---- output --- */ cholmod_dense *Y, /* copy of matrix X */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_copy_dense2 (cholmod_dense *, cholmod_dense *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_dense_xtype: change the xtype of a dense matrix */ /* -------------------------------------------------------------------------- */ int cholmod_dense_xtype ( /* ---- input ---- */ int to_xtype, /* requested xtype (real, complex,or zomplex) */ /* ---- in/out --- */ cholmod_dense *X, /* dense matrix to change */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_dense_xtype (int, cholmod_dense *, cholmod_common *) ; /* ========================================================================== */ /* === Core/cholmod_triplet ================================================= */ /* ========================================================================== */ /* A sparse matrix stored in triplet form. */ typedef struct cholmod_triplet_struct { size_t nrow ; /* the matrix is nrow-by-ncol */ size_t ncol ; size_t nzmax ; /* maximum number of entries in the matrix */ size_t nnz ; /* number of nonzeros in the matrix */ void *i ; /* i [0..nzmax-1], the row indices */ void *j ; /* j [0..nzmax-1], the column indices */ void *x ; /* size nzmax or 2*nzmax, if present */ void *z ; /* size nzmax, if present */ int stype ; /* Describes what parts of the matrix are considered: * * 0: matrix is "unsymmetric": use both upper and lower triangular parts * (the matrix may actually be symmetric in pattern and value, but * both parts are explicitly stored and used). May be square or * rectangular. * >0: matrix is square and symmetric. Entries in the lower triangular * part are transposed and added to the upper triangular part when * the matrix is converted to cholmod_sparse form. * <0: matrix is square and symmetric. Entries in the upper triangular * part are transposed and added to the lower triangular part when * the matrix is converted to cholmod_sparse form. * * Note that stype>0 and stype<0 are different for cholmod_sparse and * cholmod_triplet. The reason is simple. You can permute a symmetric * triplet matrix by simply replacing a row and column index with their * new row and column indices, via an inverse permutation. Suppose * P = L->Perm is your permutation, and Pinv is an array of size n. * Suppose a symmetric matrix A is represent by a triplet matrix T, with * entries only in the upper triangular part. Then the following code: * * Ti = T->i ; * Tj = T->j ; * for (k = 0 ; k < n ; k++) Pinv [P [k]] = k ; * for (k = 0 ; k < nz ; k++) Ti [k] = Pinv [Ti [k]] ; * for (k = 0 ; k < nz ; k++) Tj [k] = Pinv [Tj [k]] ; * * creates the triplet form of C=P*A*P'. However, if T initially * contains just the upper triangular entries (T->stype = 1), after * permutation it has entries in both the upper and lower triangular * parts. These entries should be transposed when constructing the * cholmod_sparse form of A, which is what cholmod_triplet_to_sparse * does. Thus: * * C = cholmod_triplet_to_sparse (T, 0, &Common) ; * * will return the matrix C = P*A*P'. * * Since the triplet matrix T is so simple to generate, it's quite easy * to remove entries that you do not want, prior to converting T to the * cholmod_sparse form. So if you include these entries in T, CHOLMOD * assumes that there must be a reason (such as the one above). Thus, * no entry in a triplet matrix is ever ignored. */ int itype ; /* CHOLMOD_LONG: i and j are SuiteSparse_long. Otherwise int */ int xtype ; /* pattern, real, complex, or zomplex */ int dtype ; /* x and z are double or float */ } cholmod_triplet ; /* -------------------------------------------------------------------------- */ /* cholmod_allocate_triplet: allocate a triplet matrix */ /* -------------------------------------------------------------------------- */ cholmod_triplet *cholmod_allocate_triplet ( /* ---- input ---- */ size_t nrow, /* # of rows of T */ size_t ncol, /* # of columns of T */ size_t nzmax, /* max # of nonzeros of T */ int stype, /* stype of T */ int xtype, /* CHOLMOD_PATTERN, _REAL, _COMPLEX, or _ZOMPLEX */ /* --------------- */ cholmod_common *Common ) ; cholmod_triplet *cholmod_l_allocate_triplet (size_t, size_t, size_t, int, int, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_free_triplet: free a triplet matrix */ /* -------------------------------------------------------------------------- */ int cholmod_free_triplet ( /* ---- in/out --- */ cholmod_triplet **T, /* triplet matrix to deallocate, NULL on output */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_free_triplet (cholmod_triplet **, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_reallocate_triplet: change the # of entries in a triplet matrix */ /* -------------------------------------------------------------------------- */ int cholmod_reallocate_triplet ( /* ---- input ---- */ size_t nznew, /* new # of entries in T */ /* ---- in/out --- */ cholmod_triplet *T, /* triplet matrix to modify */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_reallocate_triplet (size_t, cholmod_triplet *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_sparse_to_triplet: create a triplet matrix copy of a sparse matrix*/ /* -------------------------------------------------------------------------- */ cholmod_triplet *cholmod_sparse_to_triplet ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to copy */ /* --------------- */ cholmod_common *Common ) ; cholmod_triplet *cholmod_l_sparse_to_triplet (cholmod_sparse *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_triplet_to_sparse: create a sparse matrix copy of a triplet matrix*/ /* -------------------------------------------------------------------------- */ cholmod_sparse *cholmod_triplet_to_sparse ( /* ---- input ---- */ cholmod_triplet *T, /* matrix to copy */ size_t nzmax, /* allocate at least this much space in output matrix */ /* --------------- */ cholmod_common *Common ) ; cholmod_sparse *cholmod_l_triplet_to_sparse (cholmod_triplet *, size_t, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_copy_triplet: create a copy of a triplet matrix */ /* -------------------------------------------------------------------------- */ cholmod_triplet *cholmod_copy_triplet ( /* ---- input ---- */ cholmod_triplet *T, /* matrix to copy */ /* --------------- */ cholmod_common *Common ) ; cholmod_triplet *cholmod_l_copy_triplet (cholmod_triplet *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_triplet_xtype: change the xtype of a triplet matrix */ /* -------------------------------------------------------------------------- */ int cholmod_triplet_xtype ( /* ---- input ---- */ int to_xtype, /* requested xtype (pattern, real, complex,or zomplex)*/ /* ---- in/out --- */ cholmod_triplet *T, /* triplet matrix to change */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_triplet_xtype (int, cholmod_triplet *, cholmod_common *) ; /* ========================================================================== */ /* === Core/cholmod_memory ================================================== */ /* ========================================================================== */ /* The user may make use of these, just like malloc and free. You can even * malloc an object and safely free it with cholmod_free, and visa versa * (except that the memory usage statistics will be corrupted). These routines * do differ from malloc and free. If cholmod_free is given a NULL pointer, * for example, it does nothing (unlike the ANSI free). cholmod_realloc does * not return NULL if given a non-NULL pointer and a nonzero size, even if it * fails (it returns the original pointer and sets an error code in * Common->status instead). * * CHOLMOD keeps track of the amount of memory it has allocated, and so the * cholmod_free routine also takes the size of the object being freed. This * is only used for statistics. If you, the user of CHOLMOD, pass the wrong * size, the only consequence is that the memory usage statistics will be * corrupted. */ void *cholmod_malloc /* returns pointer to the newly malloc'd block */ ( /* ---- input ---- */ size_t n, /* number of items */ size_t size, /* size of each item */ /* --------------- */ cholmod_common *Common ) ; void *cholmod_l_malloc (size_t, size_t, cholmod_common *) ; void *cholmod_calloc /* returns pointer to the newly calloc'd block */ ( /* ---- input ---- */ size_t n, /* number of items */ size_t size, /* size of each item */ /* --------------- */ cholmod_common *Common ) ; void *cholmod_l_calloc (size_t, size_t, cholmod_common *) ; void *cholmod_free /* always returns NULL */ ( /* ---- input ---- */ size_t n, /* number of items */ size_t size, /* size of each item */ /* ---- in/out --- */ void *p, /* block of memory to free */ /* --------------- */ cholmod_common *Common ) ; void *cholmod_l_free (size_t, size_t, void *, cholmod_common *) ; void *cholmod_realloc /* returns pointer to reallocated block */ ( /* ---- input ---- */ size_t nnew, /* requested # of items in reallocated block */ size_t size, /* size of each item */ /* ---- in/out --- */ void *p, /* block of memory to realloc */ size_t *n, /* current size on input, nnew on output if successful*/ /* --------------- */ cholmod_common *Common ) ; void *cholmod_l_realloc (size_t, size_t, void *, size_t *, cholmod_common *) ; int cholmod_realloc_multiple ( /* ---- input ---- */ size_t nnew, /* requested # of items in reallocated blocks */ int nint, /* number of int/SuiteSparse_long blocks */ int xtype, /* CHOLMOD_PATTERN, _REAL, _COMPLEX, or _ZOMPLEX */ /* ---- in/out --- */ void **Iblock, /* int or SuiteSparse_long block */ void **Jblock, /* int or SuiteSparse_long block */ void **Xblock, /* complex, double, or float block */ void **Zblock, /* zomplex case only: double or float block */ size_t *n, /* current size of the I,J,X,Z blocks on input, * nnew on output if successful */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_realloc_multiple (size_t, int, int, void **, void **, void **, void **, size_t *, cholmod_common *) ; /* ========================================================================== */ /* === version control ====================================================== */ /* ========================================================================== */ int cholmod_version /* returns CHOLMOD_VERSION */ ( /* output, contents not defined on input. Not used if NULL. version [0] = CHOLMOD_MAIN_VERSION version [1] = CHOLMOD_SUB_VERSION version [2] = CHOLMOD_SUBSUB_VERSION */ int version [3] ) ; int cholmod_l_version (int version [3]) ; /* Versions prior to 2.1.1 do not have the above function. The following code fragment will work with any version of CHOLMOD: #ifdef CHOLMOD_HAS_VERSION_FUNCTION v = cholmod_version (NULL) ; #else v = CHOLMOD_VERSION ; #endif */ /* ========================================================================== */ /* === symmetry types ======================================================= */ /* ========================================================================== */ #define CHOLMOD_MM_RECTANGULAR 1 #define CHOLMOD_MM_UNSYMMETRIC 2 #define CHOLMOD_MM_SYMMETRIC 3 #define CHOLMOD_MM_HERMITIAN 4 #define CHOLMOD_MM_SKEW_SYMMETRIC 5 #define CHOLMOD_MM_SYMMETRIC_POSDIAG 6 #define CHOLMOD_MM_HERMITIAN_POSDIAG 7 /* ========================================================================== */ /* === Numerical relop macros =============================================== */ /* ========================================================================== */ /* These macros correctly handle the NaN case. * * CHOLMOD_IS_NAN(x): * True if x is NaN. False otherwise. The commonly-existing isnan(x) * function could be used, but it's not in Kernighan & Ritchie 2nd edition * (ANSI C89). It may appear in , but I'm not certain about * portability. The expression x != x is true if and only if x is NaN, * according to the IEEE 754 floating-point standard. * * CHOLMOD_IS_ZERO(x): * True if x is zero. False if x is nonzero, NaN, or +/- Inf. * This is (x == 0) if the compiler is IEEE 754 compliant. * * CHOLMOD_IS_NONZERO(x): * True if x is nonzero, NaN, or +/- Inf. False if x zero. * This is (x != 0) if the compiler is IEEE 754 compliant. * * CHOLMOD_IS_LT_ZERO(x): * True if x is < zero or -Inf. False if x is >= 0, NaN, or +Inf. * This is (x < 0) if the compiler is IEEE 754 compliant. * * CHOLMOD_IS_GT_ZERO(x): * True if x is > zero or +Inf. False if x is <= 0, NaN, or -Inf. * This is (x > 0) if the compiler is IEEE 754 compliant. * * CHOLMOD_IS_LE_ZERO(x): * True if x is <= zero or -Inf. False if x is > 0, NaN, or +Inf. * This is (x <= 0) if the compiler is IEEE 754 compliant. */ #ifdef CHOLMOD_WINDOWS /* Yes, this is exceedingly ugly. Blame Microsoft, which hopelessly */ /* violates the IEEE 754 floating-point standard in a bizarre way. */ /* If you're using an IEEE 754-compliant compiler, then x != x is true */ /* iff x is NaN. For Microsoft, (x < x) is true iff x is NaN. */ /* So either way, this macro safely detects a NaN. */ #define CHOLMOD_IS_NAN(x) (((x) != (x)) || (((x) < (x)))) #define CHOLMOD_IS_ZERO(x) (((x) == 0.) && !CHOLMOD_IS_NAN(x)) #define CHOLMOD_IS_NONZERO(x) (((x) != 0.) || CHOLMOD_IS_NAN(x)) #define CHOLMOD_IS_LT_ZERO(x) (((x) < 0.) && !CHOLMOD_IS_NAN(x)) #define CHOLMOD_IS_GT_ZERO(x) (((x) > 0.) && !CHOLMOD_IS_NAN(x)) #define CHOLMOD_IS_LE_ZERO(x) (((x) <= 0.) && !CHOLMOD_IS_NAN(x)) #else /* These all work properly, according to the IEEE 754 standard ... except on */ /* a PC with windows. Works fine in Linux on the same PC... */ #define CHOLMOD_IS_NAN(x) ((x) != (x)) #define CHOLMOD_IS_ZERO(x) ((x) == 0.) #define CHOLMOD_IS_NONZERO(x) ((x) != 0.) #define CHOLMOD_IS_LT_ZERO(x) ((x) < 0.) #define CHOLMOD_IS_GT_ZERO(x) ((x) > 0.) #define CHOLMOD_IS_LE_ZERO(x) ((x) <= 0.) #endif #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Include/cholmod_config.h0000644000076500000240000000630613524616144027204 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Include/cholmod_config.h ============================================= */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Include/cholmod_config.h. * Copyright (C) 2005-2013, Univ. of Florida. Author: Timothy A. Davis * CHOLMOD/Include/cholmod_config.h is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* CHOLMOD configuration file, for inclusion in user programs. * * You do not have to edit any CHOLMOD files to compile and install CHOLMOD. * However, if you do not use all of CHOLMOD's modules, you need to compile * with the appropriate flag, or edit this file to add the appropriate #define. * * If you wish to use CHOLMOD under the GNU LGPL license only, then you must * compile CHOLMOD with -DNMATRIXOPS -DNSUPERNODAL and -DNMODIFY. This can * be done using just -DNGPL. * * Compiler flags for CHOLMOD: * * -DNCHECK do not include the Check module. License: GNU LGPL * -DNCHOLESKY do not include the Cholesky module. License: GNU LGPL * -DNPARTITION do not include the Partition module. License: GNU LGPL * -DNCAMD do not include the interfaces to CAMD, * CCOLAMD, CSYMAND in Partition module. License: GNU LGPL * * -DNGPL do not include any GNU GPL Modules in the CHOLMOD library. * -DNMATRIXOPS do not include the MatrixOps module. License: GNU GPL * -DNMODIFY do not include the Modify module. License: GNU GPL * -DNSUPERNODAL do not include the Supernodal module. License: GNU GPL * * -DNPRINT do not print anything * * -D'LONGBLAS=long' or -DLONGBLAS='long long' defines the integers used by * LAPACK and the BLAS. Use LONGBLAS=long on Solaris to use * the 64-bit Sun Performance BLAS in cholmod_l_* routines. * You may need to use -D'LONGBLAS=long long' on the SGI * (this is not tested). * * -DNSUNPERF for Solaris only. If defined, do not use the Sun * Performance Library. The default is to use SunPerf. * You must compile CHOLMOD with -xlic_lib=sunperf. * * The Core Module (License GNU LGPL) is always included in the CHOLMOD library. */ #ifndef CHOLMOD_CONFIG_H #define CHOLMOD_CONFIG_H /* Use the compiler flag, or uncomment the definition(s), if you want to use * one or more non-default installation options: */ /* #define NCHECK #define NCHOLESKY #define NCAMD #define NPARTITION #define NGPL #define NMATRIXOPS #define NMODIFY #define NSUPERNODAL #define NPRINT #define LONGBLAS long #define LONGBLAS long long #define NSUNPERF */ /* -------------------------------------------------------------------------- */ /* if NGPL is defined, disable all GNU GPL Modules */ /* -------------------------------------------------------------------------- */ #ifdef NGPL #define NMATRIXOPS #define NMODIFY #define NSUPERNODAL #endif #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Include/cholmod_io64.h0000644000076500000240000000320213524616144026510 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Include/cholmod_io64 ================================================= */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Include/cholmod_io64.h. * Copyright (C) 2005-2006, Univ. of Florida. Author: Timothy A. Davis * CHOLMOD/Include/cholmod_io64.h is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Definitions required for large file I/O, which must come before any other * #includes. These are not used if -DNLARGEFILE is defined at compile time. * Large file support may not be portable across all platforms and compilers; * if you encounter an error here, compile your code with -DNLARGEFILE. In * particular, you must use -DNLARGEFILE for MATLAB 6.5 or earlier (which does * not have the io64.h include file). */ #ifndef CHOLMOD_IO_H #define CHOLMOD_IO_H /* skip all of this if NLARGEFILE is defined at the compiler command line */ #ifndef NLARGEFILE #if defined(MATLAB_MEX_FILE) || defined(MATHWORKS) /* CHOLMOD is being compiled as a MATLAB mexFunction, or for use in MATLAB */ #include "io64.h" #else /* CHOLMOD is being compiled in a stand-alone library */ #undef _LARGEFILE64_SOURCE #define _LARGEFILE64_SOURCE #undef _FILE_OFFSET_BITS #define _FILE_OFFSET_BITS 64 #endif #endif #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Include/cholmod_check.h0000644000076500000240000003535413524616144027021 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Include/cholmod_check.h ============================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Include/cholmod_check.h. Copyright (C) 2005-2006, Timothy A. Davis * CHOLMOD/Include/cholmod_check.h is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * http://www.suitesparse.com * -------------------------------------------------------------------------- */ /* CHOLMOD Check module. * * Routines that check and print the 5 basic data types in CHOLMOD, and 3 kinds * of integer vectors (subset, perm, and parent), and read in matrices from a * file: * * cholmod_check_common check/print the Common object * cholmod_print_common * * cholmod_check_sparse check/print a sparse matrix in column-oriented form * cholmod_print_sparse * * cholmod_check_dense check/print a dense matrix * cholmod_print_dense * * cholmod_check_factor check/print a Cholesky factorization * cholmod_print_factor * * cholmod_check_triplet check/print a sparse matrix in triplet form * cholmod_print_triplet * * cholmod_check_subset check/print a subset (integer vector in given range) * cholmod_print_subset * * cholmod_check_perm check/print a permutation (an integer vector) * cholmod_print_perm * * cholmod_check_parent check/print an elimination tree (an integer vector) * cholmod_print_parent * * cholmod_read_triplet read a matrix in triplet form (any Matrix Market * "coordinate" format, or a generic triplet format). * * cholmod_read_sparse read a matrix in sparse form (same file format as * cholmod_read_triplet). * * cholmod_read_dense read a dense matrix (any Matrix Market "array" * format, or a generic dense format). * * cholmod_write_sparse write a sparse matrix to a Matrix Market file. * * cholmod_write_dense write a dense matrix to a Matrix Market file. * * cholmod_print_common and cholmod_check_common are the only two routines that * you may call after calling cholmod_finish. * * Requires the Core module. Not required by any CHOLMOD module, except when * debugging is enabled (in which case all modules require the Check module). * * See cholmod_read.c for a description of the file formats supported by the * cholmod_read_* routines. */ #ifndef CHOLMOD_CHECK_H #define CHOLMOD_CHECK_H #include "cholmod_core.h" #include /* -------------------------------------------------------------------------- */ /* cholmod_check_common: check the Common object */ /* -------------------------------------------------------------------------- */ int cholmod_check_common ( cholmod_common *Common ) ; int cholmod_l_check_common (cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_print_common: print the Common object */ /* -------------------------------------------------------------------------- */ int cholmod_print_common ( /* ---- input ---- */ const char *name, /* printed name of Common object */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_print_common (const char *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_gpu_stats: print the GPU / CPU statistics */ /* -------------------------------------------------------------------------- */ int cholmod_gpu_stats (cholmod_common *) ; int cholmod_l_gpu_stats (cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_check_sparse: check a sparse matrix */ /* -------------------------------------------------------------------------- */ int cholmod_check_sparse ( /* ---- input ---- */ cholmod_sparse *A, /* sparse matrix to check */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_check_sparse (cholmod_sparse *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_print_sparse */ /* -------------------------------------------------------------------------- */ int cholmod_print_sparse ( /* ---- input ---- */ cholmod_sparse *A, /* sparse matrix to print */ const char *name, /* printed name of sparse matrix */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_print_sparse (cholmod_sparse *, const char *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_check_dense: check a dense matrix */ /* -------------------------------------------------------------------------- */ int cholmod_check_dense ( /* ---- input ---- */ cholmod_dense *X, /* dense matrix to check */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_check_dense (cholmod_dense *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_print_dense: print a dense matrix */ /* -------------------------------------------------------------------------- */ int cholmod_print_dense ( /* ---- input ---- */ cholmod_dense *X, /* dense matrix to print */ const char *name, /* printed name of dense matrix */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_print_dense (cholmod_dense *, const char *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_check_factor: check a factor */ /* -------------------------------------------------------------------------- */ int cholmod_check_factor ( /* ---- input ---- */ cholmod_factor *L, /* factor to check */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_check_factor (cholmod_factor *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_print_factor: print a factor */ /* -------------------------------------------------------------------------- */ int cholmod_print_factor ( /* ---- input ---- */ cholmod_factor *L, /* factor to print */ const char *name, /* printed name of factor */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_print_factor (cholmod_factor *, const char *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_check_triplet: check a sparse matrix in triplet form */ /* -------------------------------------------------------------------------- */ int cholmod_check_triplet ( /* ---- input ---- */ cholmod_triplet *T, /* triplet matrix to check */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_check_triplet (cholmod_triplet *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_print_triplet: print a triplet matrix */ /* -------------------------------------------------------------------------- */ int cholmod_print_triplet ( /* ---- input ---- */ cholmod_triplet *T, /* triplet matrix to print */ const char *name, /* printed name of triplet matrix */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_print_triplet (cholmod_triplet *, const char *, cholmod_common *); /* -------------------------------------------------------------------------- */ /* cholmod_check_subset: check a subset */ /* -------------------------------------------------------------------------- */ int cholmod_check_subset ( /* ---- input ---- */ int *Set, /* Set [0:len-1] is a subset of 0:n-1. Duplicates OK */ SuiteSparse_long len, /* size of Set (an integer array) */ size_t n, /* 0:n-1 is valid range */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_check_subset (SuiteSparse_long *, SuiteSparse_long, size_t, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_print_subset: print a subset */ /* -------------------------------------------------------------------------- */ int cholmod_print_subset ( /* ---- input ---- */ int *Set, /* Set [0:len-1] is a subset of 0:n-1. Duplicates OK */ SuiteSparse_long len, /* size of Set (an integer array) */ size_t n, /* 0:n-1 is valid range */ const char *name, /* printed name of Set */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_print_subset (SuiteSparse_long *, SuiteSparse_long, size_t, const char *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_check_perm: check a permutation */ /* -------------------------------------------------------------------------- */ int cholmod_check_perm ( /* ---- input ---- */ int *Perm, /* Perm [0:len-1] is a permutation of subset of 0:n-1 */ size_t len, /* size of Perm (an integer array) */ size_t n, /* 0:n-1 is valid range */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_check_perm (SuiteSparse_long *, size_t, size_t, cholmod_common *); /* -------------------------------------------------------------------------- */ /* cholmod_print_perm: print a permutation vector */ /* -------------------------------------------------------------------------- */ int cholmod_print_perm ( /* ---- input ---- */ int *Perm, /* Perm [0:len-1] is a permutation of subset of 0:n-1 */ size_t len, /* size of Perm (an integer array) */ size_t n, /* 0:n-1 is valid range */ const char *name, /* printed name of Perm */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_print_perm (SuiteSparse_long *, size_t, size_t, const char *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_check_parent: check an elimination tree */ /* -------------------------------------------------------------------------- */ int cholmod_check_parent ( /* ---- input ---- */ int *Parent, /* Parent [0:n-1] is an elimination tree */ size_t n, /* size of Parent */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_check_parent (SuiteSparse_long *, size_t, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_print_parent */ /* -------------------------------------------------------------------------- */ int cholmod_print_parent ( /* ---- input ---- */ int *Parent, /* Parent [0:n-1] is an elimination tree */ size_t n, /* size of Parent */ const char *name, /* printed name of Parent */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_print_parent (SuiteSparse_long *, size_t, const char *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_read_sparse: read a sparse matrix from a file */ /* -------------------------------------------------------------------------- */ cholmod_sparse *cholmod_read_sparse ( /* ---- input ---- */ FILE *f, /* file to read from, must already be open */ /* --------------- */ cholmod_common *Common ) ; cholmod_sparse *cholmod_l_read_sparse (FILE *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_read_triplet: read a triplet matrix from a file */ /* -------------------------------------------------------------------------- */ cholmod_triplet *cholmod_read_triplet ( /* ---- input ---- */ FILE *f, /* file to read from, must already be open */ /* --------------- */ cholmod_common *Common ) ; cholmod_triplet *cholmod_l_read_triplet (FILE *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_read_dense: read a dense matrix from a file */ /* -------------------------------------------------------------------------- */ cholmod_dense *cholmod_read_dense ( /* ---- input ---- */ FILE *f, /* file to read from, must already be open */ /* --------------- */ cholmod_common *Common ) ; cholmod_dense *cholmod_l_read_dense (FILE *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_read_matrix: read a sparse or dense matrix from a file */ /* -------------------------------------------------------------------------- */ void *cholmod_read_matrix ( /* ---- input ---- */ FILE *f, /* file to read from, must already be open */ int prefer, /* If 0, a sparse matrix is always return as a * cholmod_triplet form. It can have any stype * (symmetric-lower, unsymmetric, or * symmetric-upper). * If 1, a sparse matrix is returned as an unsymmetric * cholmod_sparse form (A->stype == 0), with both * upper and lower triangular parts present. * This is what the MATLAB mread mexFunction does, * since MATLAB does not have an stype. * If 2, a sparse matrix is returned with an stype of 0 * or 1 (unsymmetric, or symmetric with upper part * stored). * This argument has no effect for dense matrices. */ /* ---- output---- */ int *mtype, /* CHOLMOD_TRIPLET, CHOLMOD_SPARSE or CHOLMOD_DENSE */ /* --------------- */ cholmod_common *Common ) ; void *cholmod_l_read_matrix (FILE *, int, int *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_write_sparse: write a sparse matrix to a file */ /* -------------------------------------------------------------------------- */ int cholmod_write_sparse ( /* ---- input ---- */ FILE *f, /* file to write to, must already be open */ cholmod_sparse *A, /* matrix to print */ cholmod_sparse *Z, /* optional matrix with pattern of explicit zeros */ const char *comments, /* optional filename of comments to include */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_write_sparse (FILE *, cholmod_sparse *, cholmod_sparse *, const char *c, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_write_dense: write a dense matrix to a file */ /* -------------------------------------------------------------------------- */ int cholmod_write_dense ( /* ---- input ---- */ FILE *f, /* file to write to, must already be open */ cholmod_dense *X, /* matrix to print */ const char *comments, /* optional filename of comments to include */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_write_dense (FILE *, cholmod_dense *, const char *, cholmod_common *) ; #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Include/cholmod_partition.h0000644000076500000240000001512713524616144027751 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Include/cholmod_partition.h ========================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Include/cholmod_partition.h. * Copyright (C) 2005-2013, Univ. of Florida. Author: Timothy A. Davis * CHOLMOD/Include/cholmod_partition.h is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* CHOLMOD Partition module. * * Graph partitioning and graph-partition-based orderings. Includes an * interface to CCOLAMD and CSYMAMD, constrained minimum degree ordering * methods which order a matrix following constraints determined via nested * dissection. * * These functions require METIS: * cholmod_nested_dissection CHOLMOD nested dissection ordering * cholmod_metis METIS nested dissection ordering (METIS_NodeND) * cholmod_bisect graph partitioner (currently based on METIS) * cholmod_metis_bisector direct interface to METIS_NodeComputeSeparator * * Requires the Core and Cholesky modules, and three packages: METIS, CAMD, * and CCOLAMD. Optionally used by the Cholesky module. * * Note that METIS does not have a version that uses SuiteSparse_long integers. * If you try to use cholmod_nested_dissection, cholmod_metis, cholmod_bisect, * or cholmod_metis_bisector on a matrix that is too large, an error code will * be returned. METIS does have an "idxtype", which could be redefined as * SuiteSparse_long, if you wish to edit METIS or use compile-time flags to * redefine idxtype. */ #ifndef CHOLMOD_PARTITION_H #define CHOLMOD_PARTITION_H #include "cholmod_core.h" #include "cholmod_camd.h" /* -------------------------------------------------------------------------- */ /* cholmod_nested_dissection */ /* -------------------------------------------------------------------------- */ /* Order A, AA', or A(:,f)*A(:,f)' using CHOLMOD's nested dissection method * (METIS's node bisector applied recursively to compute the separator tree * and constraint sets, followed by CCOLAMD using the constraints). Usually * finds better orderings than METIS_NodeND, but takes longer. */ SuiteSparse_long cholmod_nested_dissection /* returns # of components */ ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to order */ int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ /* ---- output --- */ int *Perm, /* size A->nrow, output permutation */ int *CParent, /* size A->nrow. On output, CParent [c] is the parent * of component c, or EMPTY if c is a root, and where * c is in the range 0 to # of components minus 1 */ int *Cmember, /* size A->nrow. Cmember [j] = c if node j of A is * in component c */ /* --------------- */ cholmod_common *Common ) ; SuiteSparse_long cholmod_l_nested_dissection (cholmod_sparse *, SuiteSparse_long *, size_t, SuiteSparse_long *, SuiteSparse_long *, SuiteSparse_long *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_metis */ /* -------------------------------------------------------------------------- */ /* Order A, AA', or A(:,f)*A(:,f)' using METIS_NodeND. */ int cholmod_metis ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to order */ int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ int postorder, /* if TRUE, follow with etree or coletree postorder */ /* ---- output --- */ int *Perm, /* size A->nrow, output permutation */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_metis (cholmod_sparse *, SuiteSparse_long *, size_t, int, SuiteSparse_long *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_bisect */ /* -------------------------------------------------------------------------- */ /* Finds a node bisector of A, A*A', A(:,f)*A(:,f)'. */ SuiteSparse_long cholmod_bisect /* returns # of nodes in separator */ ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to bisect */ int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ int compress, /* if TRUE, compress the graph first */ /* ---- output --- */ int *Partition, /* size A->nrow. Node i is in the left graph if * Partition [i] = 0, the right graph if 1, and in the * separator if 2. */ /* --------------- */ cholmod_common *Common ) ; SuiteSparse_long cholmod_l_bisect (cholmod_sparse *, SuiteSparse_long *, size_t, int, SuiteSparse_long *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_metis_bisector */ /* -------------------------------------------------------------------------- */ /* Find a set of nodes that bisects the graph of A or AA' (direct interface * to METIS_NodeComputeSeparator). */ SuiteSparse_long cholmod_metis_bisector /* returns separator size */ ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to bisect */ int *Anw, /* size A->nrow, node weights */ int *Aew, /* size nz, edge weights */ /* ---- output --- */ int *Partition, /* size A->nrow. see cholmod_bisect above. */ /* --------------- */ cholmod_common *Common ) ; SuiteSparse_long cholmod_l_metis_bisector (cholmod_sparse *, SuiteSparse_long *, SuiteSparse_long *, SuiteSparse_long *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_collapse_septree */ /* -------------------------------------------------------------------------- */ /* Collapse nodes in a separator tree. */ SuiteSparse_long cholmod_collapse_septree ( /* ---- input ---- */ size_t n, /* # of nodes in the graph */ size_t ncomponents, /* # of nodes in the separator tree (must be <= n) */ double nd_oksep, /* collapse if #sep >= nd_oksep * #nodes in subtree */ size_t nd_small, /* collapse if #nodes in subtree < nd_small */ /* ---- in/out --- */ int *CParent, /* size ncomponents; from cholmod_nested_dissection */ int *Cmember, /* size n; from cholmod_nested_dissection */ /* --------------- */ cholmod_common *Common ) ; SuiteSparse_long cholmod_l_collapse_septree (size_t, size_t, double, size_t, SuiteSparse_long *, SuiteSparse_long *, cholmod_common *) ; #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Include/cholmod_camd.h0000644000076500000240000000717713524616144026652 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Include/cholmod_camd.h =============================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Include/cholmod_camd.h. * Copyright (C) 2005-2013, Univ. of Florida. Author: Timothy A. Davis * CHOLMOD/Include/cholmod_partition.h is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* CHOLMOD Partition module, interface to CAMD, CCOLAMD, and CSYMAMD * * An interface to CCOLAMD and CSYMAMD, constrained minimum degree ordering * methods which order a matrix following constraints determined via nested * dissection. * * These functions do not require METIS. They are installed unless NCAMD * is defined: * cholmod_ccolamd interface to CCOLAMD ordering * cholmod_csymamd interface to CSYMAMD ordering * cholmod_camd interface to CAMD ordering * * Requires the Core and Cholesky modules, and two packages: CAMD, * and CCOLAMD. Used by functions in the Partition Module. */ #ifndef CHOLMOD_CAMD_H #define CHOLMOD_CAMD_H #include "cholmod_core.h" /* -------------------------------------------------------------------------- */ /* cholmod_ccolamd */ /* -------------------------------------------------------------------------- */ /* Order AA' or A(:,f)*A(:,f)' using CCOLAMD. */ int cholmod_ccolamd ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to order */ int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ int *Cmember, /* size A->nrow. Cmember [i] = c if row i is in the * constraint set c. c must be >= 0. The # of * constraint sets is max (Cmember) + 1. If Cmember is * NULL, then it is interpretted as Cmember [i] = 0 for * all i */ /* ---- output --- */ int *Perm, /* size A->nrow, output permutation */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_ccolamd (cholmod_sparse *, SuiteSparse_long *, size_t, SuiteSparse_long *, SuiteSparse_long *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_csymamd */ /* -------------------------------------------------------------------------- */ /* Order A using CSYMAMD. */ int cholmod_csymamd ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to order */ /* ---- output --- */ int *Cmember, /* size nrow. see cholmod_ccolamd above */ int *Perm, /* size A->nrow, output permutation */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_csymamd (cholmod_sparse *, SuiteSparse_long *, SuiteSparse_long *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_camd */ /* -------------------------------------------------------------------------- */ /* Order A using CAMD. */ int cholmod_camd ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to order */ int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ /* ---- output --- */ int *Cmember, /* size nrow. see cholmod_ccolamd above */ int *Perm, /* size A->nrow, output permutation */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_camd (cholmod_sparse *, SuiteSparse_long *, size_t, SuiteSparse_long *, SuiteSparse_long *, cholmod_common *) ; #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Include/cholmod_matrixops.h0000644000076500000240000002076313524616144027770 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Include/cholmod_matrixops.h ========================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Include/cholmod_matrixops.h. * Copyright (C) 2005-2006, Timothy A. Davis * CHOLMOD/Include/cholmod_matrixops.h is licensed under Version 2.0 of the GNU * General Public License. See gpl.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * http://www.suitesparse.com * -------------------------------------------------------------------------- */ /* CHOLMOD MatrixOps module. * * Basic operations on sparse and dense matrices. * * cholmod_drop A = entries in A with abs. value >= tol * cholmod_norm_dense s = norm (X), 1-norm, inf-norm, or 2-norm * cholmod_norm_sparse s = norm (A), 1-norm or inf-norm * cholmod_horzcat C = [A,B] * cholmod_scale A = diag(s)*A, A*diag(s), s*A or diag(s)*A*diag(s) * cholmod_sdmult Y = alpha*(A*X) + beta*Y or alpha*(A'*X) + beta*Y * cholmod_ssmult C = A*B * cholmod_submatrix C = A (i,j), where i and j are arbitrary vectors * cholmod_vertcat C = [A ; B] * * A, B, C: sparse matrices (cholmod_sparse) * X, Y: dense matrices (cholmod_dense) * s: scalar or vector * * Requires the Core module. Not required by any other CHOLMOD module. */ #ifndef CHOLMOD_MATRIXOPS_H #define CHOLMOD_MATRIXOPS_H #include "cholmod_core.h" /* -------------------------------------------------------------------------- */ /* cholmod_drop: drop entries with small absolute value */ /* -------------------------------------------------------------------------- */ int cholmod_drop ( /* ---- input ---- */ double tol, /* keep entries with absolute value > tol */ /* ---- in/out --- */ cholmod_sparse *A, /* matrix to drop entries from */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_drop (double, cholmod_sparse *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_norm_dense: s = norm (X), 1-norm, inf-norm, or 2-norm */ /* -------------------------------------------------------------------------- */ double cholmod_norm_dense ( /* ---- input ---- */ cholmod_dense *X, /* matrix to compute the norm of */ int norm, /* type of norm: 0: inf. norm, 1: 1-norm, 2: 2-norm */ /* --------------- */ cholmod_common *Common ) ; double cholmod_l_norm_dense (cholmod_dense *, int, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_norm_sparse: s = norm (A), 1-norm or inf-norm */ /* -------------------------------------------------------------------------- */ double cholmod_norm_sparse ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to compute the norm of */ int norm, /* type of norm: 0: inf. norm, 1: 1-norm */ /* --------------- */ cholmod_common *Common ) ; double cholmod_l_norm_sparse (cholmod_sparse *, int, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_horzcat: C = [A,B] */ /* -------------------------------------------------------------------------- */ cholmod_sparse *cholmod_horzcat ( /* ---- input ---- */ cholmod_sparse *A, /* left matrix to concatenate */ cholmod_sparse *B, /* right matrix to concatenate */ int values, /* if TRUE compute the numerical values of C */ /* --------------- */ cholmod_common *Common ) ; cholmod_sparse *cholmod_l_horzcat (cholmod_sparse *, cholmod_sparse *, int, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_scale: A = diag(s)*A, A*diag(s), s*A or diag(s)*A*diag(s) */ /* -------------------------------------------------------------------------- */ /* scaling modes, selected by the scale input parameter: */ #define CHOLMOD_SCALAR 0 /* A = s*A */ #define CHOLMOD_ROW 1 /* A = diag(s)*A */ #define CHOLMOD_COL 2 /* A = A*diag(s) */ #define CHOLMOD_SYM 3 /* A = diag(s)*A*diag(s) */ int cholmod_scale ( /* ---- input ---- */ cholmod_dense *S, /* scale factors (scalar or vector) */ int scale, /* type of scaling to compute */ /* ---- in/out --- */ cholmod_sparse *A, /* matrix to scale */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_scale (cholmod_dense *, int, cholmod_sparse *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_sdmult: Y = alpha*(A*X) + beta*Y or alpha*(A'*X) + beta*Y */ /* -------------------------------------------------------------------------- */ /* Sparse matrix times dense matrix */ int cholmod_sdmult ( /* ---- input ---- */ cholmod_sparse *A, /* sparse matrix to multiply */ int transpose, /* use A if 0, or A' otherwise */ double alpha [2], /* scale factor for A */ double beta [2], /* scale factor for Y */ cholmod_dense *X, /* dense matrix to multiply */ /* ---- in/out --- */ cholmod_dense *Y, /* resulting dense matrix */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_sdmult (cholmod_sparse *, int, double *, double *, cholmod_dense *, cholmod_dense *Y, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_ssmult: C = A*B */ /* -------------------------------------------------------------------------- */ /* Sparse matrix times sparse matrix */ cholmod_sparse *cholmod_ssmult ( /* ---- input ---- */ cholmod_sparse *A, /* left matrix to multiply */ cholmod_sparse *B, /* right matrix to multiply */ int stype, /* requested stype of C */ int values, /* TRUE: do numerical values, FALSE: pattern only */ int sorted, /* if TRUE then return C with sorted columns */ /* --------------- */ cholmod_common *Common ) ; cholmod_sparse *cholmod_l_ssmult (cholmod_sparse *, cholmod_sparse *, int, int, int, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_submatrix: C = A (r,c), where i and j are arbitrary vectors */ /* -------------------------------------------------------------------------- */ /* rsize < 0 denotes ":" in MATLAB notation, or more precisely 0:(A->nrow)-1. * In this case, r can be NULL. An rsize of zero, or r = NULL and rsize >= 0, * denotes "[ ]" in MATLAB notation (the empty set). * Similar rules hold for csize. */ cholmod_sparse *cholmod_submatrix ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to subreference */ int *rset, /* set of row indices, duplicates OK */ SuiteSparse_long rsize, /* size of r; rsize < 0 denotes ":" */ int *cset, /* set of column indices, duplicates OK */ SuiteSparse_long csize, /* size of c; csize < 0 denotes ":" */ int values, /* if TRUE compute the numerical values of C */ int sorted, /* if TRUE then return C with sorted columns */ /* --------------- */ cholmod_common *Common ) ; cholmod_sparse *cholmod_l_submatrix (cholmod_sparse *, SuiteSparse_long *, SuiteSparse_long, SuiteSparse_long *, SuiteSparse_long, int, int, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_vertcat: C = [A ; B] */ /* -------------------------------------------------------------------------- */ cholmod_sparse *cholmod_vertcat ( /* ---- input ---- */ cholmod_sparse *A, /* left matrix to concatenate */ cholmod_sparse *B, /* right matrix to concatenate */ int values, /* if TRUE compute the numerical values of C */ /* --------------- */ cholmod_common *Common ) ; cholmod_sparse *cholmod_l_vertcat (cholmod_sparse *, cholmod_sparse *, int, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_symmetry: determine if a sparse matrix is symmetric */ /* -------------------------------------------------------------------------- */ int cholmod_symmetry ( /* ---- input ---- */ cholmod_sparse *A, int option, /* ---- output ---- */ int *xmatched, int *pmatched, int *nzoffdiag, int *nzdiag, /* --------------- */ cholmod_common *Common ) ; int cholmod_l_symmetry (cholmod_sparse *, int, SuiteSparse_long *, SuiteSparse_long *, SuiteSparse_long *, SuiteSparse_long *, cholmod_common *) ; #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Include/cholmod_template.h0000644000076500000240000002200113524616144027540 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Include/cholmod_template.h =========================================== */ /* ========================================================================== */ /* -------------------------------------------------------------------------- */ /* undefine current xtype macros, and then define macros for current type */ /* -------------------------------------------------------------------------- */ #undef TEMPLATE #undef XTYPE #undef XTYPE2 #undef XTYPE_OK #undef ENTRY_IS_NONZERO #undef ENTRY_IS_ZERO #undef ENTRY_IS_ONE #undef IMAG_IS_NONZERO #undef ASSEMBLE #undef ASSIGN #undef ASSIGN_CONJ #undef ASSIGN2 #undef ASSIGN2_CONJ #undef ASSIGN_REAL #undef MULT #undef MULTADD #undef ADD #undef ADD_REAL #undef MULTSUB #undef MULTADDCONJ #undef MULTSUBCONJ #undef LLDOT #undef CLEAR #undef DIV #undef DIV_REAL #undef MULT_REAL #undef CLEAR_IMAG #undef LDLDOT #undef PREFIX #undef ENTRY_SIZE #undef XPRINT0 #undef XPRINT1 #undef XPRINT2 #undef XPRINT3 /* -------------------------------------------------------------------------- */ /* pattern */ /* -------------------------------------------------------------------------- */ #ifdef PATTERN #define PREFIX p_ #define TEMPLATE(name) P_TEMPLATE(name) #define XTYPE CHOLMOD_PATTERN #define XTYPE2 CHOLMOD_REAL #define XTYPE_OK(type) (TRUE) #define ENTRY_IS_NONZERO(ax,az,q) (TRUE) #define ENTRY_IS_ZERO(ax,az,q) (FALSE) #define ENTRY_IS_ONE(ax,az,q) (TRUE) #define IMAG_IS_NONZERO(ax,az,q) (FALSE) #define ENTRY_SIZE 0 #define ASSEMBLE(x,z,p,ax,az,q) #define ASSIGN(x,z,p,ax,az,q) #define ASSIGN_CONJ(x,z,p,ax,az,q) #define ASSIGN2(x,z,p,ax,az,q) P_ASSIGN2(x,z,p,ax,az,q) #define ASSIGN2_CONJ(x,z,p,ax,az,q) P_ASSIGN2(x,z,p,ax,az,q) #define ASSIGN_REAL(x,p,ax,q) #define MULT(x,z,p,ax,az,q,bx,bz,pb) #define MULTADD(x,z,p,ax,az,q,bx,bz,pb) #define ADD(x,z,p,ax,az,q,bx,bz,pb) #define ADD_REAL(x,p, ax,q, bx,r) #define MULTSUB(x,z,p,ax,az,q,bx,bz,pb) #define MULTADDCONJ(x,z,p,ax,az,q,bx,bz,pb) #define MULTSUBCONJ(x,z,p,ax,az,q,bx,bz,pb) #define LLDOT(x,p,ax,az,q) #define CLEAR(x,z,p) #define CLEAR_IMAG(x,z,p) #define DIV(x,z,p,ax,az,q) #define DIV_REAL(x,z,p, ax,az,q, bx,r) #define MULT_REAL(x,z,p, ax,az,q, bx,r) #define LDLDOT(x,p, ax,az,q, bx,r) #define XPRINT0(x,z,p) P_PRINT(0,x,z,p) #define XPRINT1(x,z,p) P_PRINT(1,x,z,p) #define XPRINT2(x,z,p) P_PRINT(2,x,z,p) #define XPRINT3(x,z,p) P_PRINT(3,x,z,p) /* -------------------------------------------------------------------------- */ /* real */ /* -------------------------------------------------------------------------- */ #elif defined (REAL) #define PREFIX r_ #define TEMPLATE(name) R_TEMPLATE(name) #define XTYPE CHOLMOD_REAL #define XTYPE2 CHOLMOD_REAL #define XTYPE_OK(type) R_XTYPE_OK(type) #define ENTRY_IS_NONZERO(ax,az,q) R_IS_NONZERO(ax,az,q) #define ENTRY_IS_ZERO(ax,az,q) R_IS_ZERO(ax,az,q) #define ENTRY_IS_ONE(ax,az,q) R_IS_ONE(ax,az,q) #define IMAG_IS_NONZERO(ax,az,q) (FALSE) #define ENTRY_SIZE 1 #define ASSEMBLE(x,z,p,ax,az,q) R_ASSEMBLE(x,z,p,ax,az,q) #define ASSIGN(x,z,p,ax,az,q) R_ASSIGN(x,z,p,ax,az,q) #define ASSIGN_CONJ(x,z,p,ax,az,q) R_ASSIGN(x,z,p,ax,az,q) #define ASSIGN2(x,z,p,ax,az,q) R_ASSIGN(x,z,p,ax,az,q) #define ASSIGN2_CONJ(x,z,p,ax,az,q) R_ASSIGN(x,z,p,ax,az,q) #define ASSIGN_REAL(x,p,ax,q) R_ASSIGN_REAL(x,p,ax,q) #define MULT(x,z,p,ax,az,q,bx,bz,pb) R_MULT(x,z,p,ax,az,q,bx,bz,pb) #define MULTADD(x,z,p,ax,az,q,bx,bz,pb) R_MULTADD(x,z,p,ax,az,q,bx,bz,pb) #define ADD(x,z,p,ax,az,q,bx,bz,pb) R_ADD(x,z,p,ax,az,q,bx,bz,pb) #define ADD_REAL(x,p, ax,q, bx,r) R_ADD_REAL(x,p, ax,q, bx,r) #define MULTSUB(x,z,p,ax,az,q,bx,bz,pb) R_MULTSUB(x,z,p,ax,az,q,bx,bz,pb) #define MULTADDCONJ(x,z,p,ax,az,q,bx,bz,pb) \ R_MULTADDCONJ(x,z,p,ax,az,q,bx,bz,pb) #define MULTSUBCONJ(x,z,p,ax,az,q,bx,bz,pb) \ R_MULTSUBCONJ(x,z,p,ax,az,q,bx,bz,pb) #define LLDOT(x,p,ax,az,q) R_LLDOT(x,p,ax,az,q) #define CLEAR(x,z,p) R_CLEAR(x,z,p) #define CLEAR_IMAG(x,z,p) R_CLEAR_IMAG(x,z,p) #define DIV(x,z,p,ax,az,q) R_DIV(x,z,p,ax,az,q) #define DIV_REAL(x,z,p, ax,az,q, bx,r) R_DIV_REAL(x,z,p, ax,az,q, bx,r) #define MULT_REAL(x,z,p, ax,az,q, bx,r) R_MULT_REAL(x,z,p, ax,az,q, bx,r) #define LDLDOT(x,p, ax,az,q, bx,r) R_LDLDOT(x,p, ax,az,q, bx,r) #define XPRINT0(x,z,p) R_PRINT(0,x,z,p) #define XPRINT1(x,z,p) R_PRINT(1,x,z,p) #define XPRINT2(x,z,p) R_PRINT(2,x,z,p) #define XPRINT3(x,z,p) R_PRINT(3,x,z,p) /* -------------------------------------------------------------------------- */ /* complex */ /* -------------------------------------------------------------------------- */ #elif defined (COMPLEX) #define PREFIX c_ #ifdef NCONJUGATE #define TEMPLATE(name) CT_TEMPLATE(name) #else #define TEMPLATE(name) C_TEMPLATE(name) #endif #define ASSEMBLE(x,z,p,ax,az,q) C_ASSEMBLE(x,z,p,ax,az,q) #define ASSIGN(x,z,p,ax,az,q) C_ASSIGN(x,z,p,ax,az,q) #define ASSIGN_CONJ(x,z,p,ax,az,q) C_ASSIGN_CONJ(x,z,p,ax,az,q) #define ASSIGN2(x,z,p,ax,az,q) C_ASSIGN(x,z,p,ax,az,q) #define ASSIGN2_CONJ(x,z,p,ax,az,q) C_ASSIGN_CONJ(x,z,p,ax,az,q) #define ASSIGN_REAL(x,p,ax,q) C_ASSIGN_REAL(x,p,ax,q) #define XTYPE CHOLMOD_COMPLEX #define XTYPE2 CHOLMOD_COMPLEX #define XTYPE_OK(type) C_XTYPE_OK(type) #define ENTRY_IS_NONZERO(ax,az,q) C_IS_NONZERO(ax,az,q) #define ENTRY_IS_ZERO(ax,az,q) C_IS_ZERO(ax,az,q) #define ENTRY_IS_ONE(ax,az,q) C_IS_ONE(ax,az,q) #define IMAG_IS_NONZERO(ax,az,q) C_IMAG_IS_NONZERO(ax,az,q) #define ENTRY_SIZE 2 #define MULTADD(x,z,p,ax,az,q,bx,bz,pb) C_MULTADD(x,z,p,ax,az,q,bx,bz,pb) #define MULT(x,z,p,ax,az,q,bx,bz,pb) C_MULT(x,z,p,ax,az,q,bx,bz,pb) #define ADD(x,z,p,ax,az,q,bx,bz,pb) C_ADD(x,z,p,ax,az,q,bx,bz,pb) #define ADD_REAL(x,p, ax,q, bx,r) C_ADD_REAL(x,p, ax,q, bx,r) #define MULTSUB(x,z,p,ax,az,q,bx,bz,pb) C_MULTSUB(x,z,p,ax,az,q,bx,bz,pb) #define MULTADDCONJ(x,z,p,ax,az,q,bx,bz,pb) \ C_MULTADDCONJ(x,z,p,ax,az,q,bx,bz,pb) #define MULTSUBCONJ(x,z,p,ax,az,q,bx,bz,pb) \ C_MULTSUBCONJ(x,z,p,ax,az,q,bx,bz,pb) #define LLDOT(x,p,ax,az,q) C_LLDOT(x,p,ax,az,q) #define CLEAR(x,z,p) C_CLEAR(x,z,p) #define CLEAR_IMAG(x,z,p) C_CLEAR_IMAG(x,z,p) #define DIV(x,z,p,ax,az,q) C_DIV(x,z,p,ax,az,q) #define DIV_REAL(x,z,p, ax,az,q, bx,r) C_DIV_REAL(x,z,p, ax,az,q, bx,r) #define MULT_REAL(x,z,p, ax,az,q, bx,r) C_MULT_REAL(x,z,p, ax,az,q, bx,r) #define LDLDOT(x,p, ax,az,q, bx,r) C_LDLDOT(x,p, ax,az,q, bx,r) #define XPRINT0(x,z,p) C_PRINT(0,x,z,p) #define XPRINT1(x,z,p) C_PRINT(1,x,z,p) #define XPRINT2(x,z,p) C_PRINT(2,x,z,p) #define XPRINT3(x,z,p) C_PRINT(3,x,z,p) /* -------------------------------------------------------------------------- */ /* zomplex */ /* -------------------------------------------------------------------------- */ #elif defined (ZOMPLEX) #define PREFIX z_ #ifdef NCONJUGATE #define TEMPLATE(name) ZT_TEMPLATE(name) #else #define TEMPLATE(name) Z_TEMPLATE(name) #endif #define ASSEMBLE(x,z,p,ax,az,q) Z_ASSEMBLE(x,z,p,ax,az,q) #define ASSIGN(x,z,p,ax,az,q) Z_ASSIGN(x,z,p,ax,az,q) #define ASSIGN_CONJ(x,z,p,ax,az,q) Z_ASSIGN_CONJ(x,z,p,ax,az,q) #define ASSIGN2(x,z,p,ax,az,q) Z_ASSIGN(x,z,p,ax,az,q) #define ASSIGN2_CONJ(x,z,p,ax,az,q) Z_ASSIGN_CONJ(x,z,p,ax,az,q) #define ASSIGN_REAL(x,p,ax,q) Z_ASSIGN_REAL(x,p,ax,q) #define XTYPE CHOLMOD_ZOMPLEX #define XTYPE2 CHOLMOD_ZOMPLEX #define XTYPE_OK(type) Z_XTYPE_OK(type) #define ENTRY_IS_NONZERO(ax,az,q) Z_IS_NONZERO(ax,az,q) #define ENTRY_IS_ZERO(ax,az,q) Z_IS_ZERO(ax,az,q) #define ENTRY_IS_ONE(ax,az,q) Z_IS_ONE(ax,az,q) #define IMAG_IS_NONZERO(ax,az,q) Z_IMAG_IS_NONZERO(ax,az,q) #define ENTRY_SIZE 1 #define MULTADD(x,z,p,ax,az,q,bx,bz,pb) Z_MULTADD(x,z,p,ax,az,q,bx,bz,pb) #define MULT(x,z,p,ax,az,q,bx,bz,pb) Z_MULT(x,z,p,ax,az,q,bx,bz,pb) #define ADD(x,z,p,ax,az,q,bx,bz,pb) Z_ADD(x,z,p,ax,az,q,bx,bz,pb) #define ADD_REAL(x,p, ax,q, bx,r) Z_ADD_REAL(x,p, ax,q, bx,r) #define MULTSUB(x,z,p,ax,az,q,bx,bz,pb) Z_MULTSUB(x,z,p,ax,az,q,bx,bz,pb) #define MULTADDCONJ(x,z,p,ax,az,q,bx,bz,pb) \ Z_MULTADDCONJ(x,z,p,ax,az,q,bx,bz,pb) #define MULTSUBCONJ(x,z,p,ax,az,q,bx,bz,pb) \ Z_MULTSUBCONJ(x,z,p,ax,az,q,bx,bz,pb) #define LLDOT(x,p,ax,az,q) Z_LLDOT(x,p,ax,az,q) #define CLEAR(x,z,p) Z_CLEAR(x,z,p) #define CLEAR_IMAG(x,z,p) Z_CLEAR_IMAG(x,z,p) #define DIV(x,z,p,ax,az,q) Z_DIV(x,z,p,ax,az,q) #define DIV_REAL(x,z,p, ax,az,q, bx,r) Z_DIV_REAL(x,z,p, ax,az,q, bx,r) #define MULT_REAL(x,z,p, ax,az,q, bx,r) Z_MULT_REAL(x,z,p, ax,az,q, bx,r) #define LDLDOT(x,p, ax,az,q, bx,r) Z_LDLDOT(x,p, ax,az,q, bx,r) #define XPRINT0(x,z,p) Z_PRINT(0,x,z,p) #define XPRINT1(x,z,p) Z_PRINT(1,x,z,p) #define XPRINT2(x,z,p) Z_PRINT(2,x,z,p) #define XPRINT3(x,z,p) Z_PRINT(3,x,z,p) #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Include/README.txt0000644000076500000240000000240513524616144025553 0ustar tamasstaff00000000000000CHOLMOD: a sparse Cholesky factorization package. http://www.suitesparse.com The Include/*.h files in this directory provide a basic documentation of all user-callable routines and user-visible data structures in the CHOLMOD package. Start with cholmod.h, which describes the general structure of the parameter lists of CHOLMOD routines. cholmod_core.h describes the data structures and basic operations on them (creating and deleting them). cholmod.h single include file for all user programs cholmod_config.h CHOLMOD compile-time configuration cholmod_core.h Core module: data structures and basic support routines cholmod_check.h Check module: check/print CHOLMOD data structures cholmod_cholesky.h Cholesky module: LL' and LDL' factorization cholmod_matrixops.h MatrixOps module: sparse matrix operators (add, mult,..) cholmod_modify.h Modify module: update/downdate/... cholmod_partition.h Partition module: nested dissection ordering cholmod_supernodal.h Supernodal module: supernodal Cholesky These include files are not used in user programs, but in CHOLMOD only: cholmod_blas.h BLAS definitions cholmod_complexity.h complex arithmetic cholmod_template.h complex arithmetic for template routines cholmod_internal.h internal definitions, not visible to user program python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Include/cholmod_complexity.h0000644000076500000240000002224413524616144030133 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Include/cholmod_complexity.h ========================================= */ /* ========================================================================== */ /* Define operations on pattern, real, complex, and zomplex objects. * * The xtype of an object defines it numerical type. A qttern object has no * numerical values (A->x and A->z are NULL). A real object has no imaginary * qrt (A->x is used, A->z is NULL). A complex object has an imaginary qrt * that is stored interleaved with its real qrt (A->x is of size 2*nz, A->z * is NULL). A zomplex object has both real and imaginary qrts, which are * stored seqrately, as in MATLAB (A->x and A->z are both used). * * XTYPE is CHOLMOD_PATTERN, _REAL, _COMPLEX or _ZOMPLEX, and is the xtype of * the template routine under construction. XTYPE2 is equal to XTYPE, except * if XTYPE is CHOLMOD_PATTERN, in which case XTYPE is CHOLMOD_REAL. * XTYPE and XTYPE2 are defined in cholmod_template.h. */ /* -------------------------------------------------------------------------- */ /* pattern */ /* -------------------------------------------------------------------------- */ #define P_TEMPLATE(name) p_ ## name #define P_ASSIGN2(x,z,p,ax,az,q) x [p] = 1 #define P_PRINT(k,x,z,p) PRK(k, ("1")) /* -------------------------------------------------------------------------- */ /* real */ /* -------------------------------------------------------------------------- */ #define R_TEMPLATE(name) r_ ## name #define R_ASSEMBLE(x,z,p,ax,az,q) x [p] += ax [q] #define R_ASSIGN(x,z,p,ax,az,q) x [p] = ax [q] #define R_ASSIGN_CONJ(x,z,p,ax,az,q) x [p] = ax [q] #define R_ASSIGN_REAL(x,p,ax,q) x [p] = ax [q] #define R_XTYPE_OK(type) ((type) == CHOLMOD_REAL) #define R_IS_NONZERO(ax,az,q) IS_NONZERO (ax [q]) #define R_IS_ZERO(ax,az,q) IS_ZERO (ax [q]) #define R_IS_ONE(ax,az,q) (ax [q] == 1) #define R_MULT(x,z,p, ax,az,q, bx,bz,r) x [p] = ax [q] * bx [r] #define R_MULTADD(x,z,p, ax,az,q, bx,bz,r) x [p] += ax [q] * bx [r] #define R_MULTSUB(x,z,p, ax,az,q, bx,bz,r) x [p] -= ax [q] * bx [r] #define R_MULTADDCONJ(x,z,p, ax,az,q, bx,bz,r) x [p] += ax [q] * bx [r] #define R_MULTSUBCONJ(x,z,p, ax,az,q, bx,bz,r) x [p] -= ax [q] * bx [r] #define R_ADD(x,z,p, ax,az,q, bx,bz,r) x [p] = ax [q] + bx [r] #define R_ADD_REAL(x,p, ax,q, bx,r) x [p] = ax [q] + bx [r] #define R_CLEAR(x,z,p) x [p] = 0 #define R_CLEAR_IMAG(x,z,p) #define R_DIV(x,z,p,ax,az,q) x [p] /= ax [q] #define R_LLDOT(x,p, ax,az,q) x [p] -= ax [q] * ax [q] #define R_PRINT(k,x,z,p) PRK(k, ("%24.16e", x [p])) #define R_DIV_REAL(x,z,p, ax,az,q, bx,r) x [p] = ax [q] / bx [r] #define R_MULT_REAL(x,z,p, ax,az,q, bx,r) x [p] = ax [q] * bx [r] #define R_LDLDOT(x,p, ax,az,q, bx,r) x [p] -=(ax[q] * ax[q])/ bx[r] /* -------------------------------------------------------------------------- */ /* complex */ /* -------------------------------------------------------------------------- */ #define C_TEMPLATE(name) c_ ## name #define CT_TEMPLATE(name) ct_ ## name #define C_ASSEMBLE(x,z,p,ax,az,q) \ x [2*(p) ] += ax [2*(q) ] ; \ x [2*(p)+1] += ax [2*(q)+1] #define C_ASSIGN(x,z,p,ax,az,q) \ x [2*(p) ] = ax [2*(q) ] ; \ x [2*(p)+1] = ax [2*(q)+1] #define C_ASSIGN_REAL(x,p,ax,q) x [2*(p)] = ax [2*(q)] #define C_ASSIGN_CONJ(x,z,p,ax,az,q) \ x [2*(p) ] = ax [2*(q) ] ; \ x [2*(p)+1] = -ax [2*(q)+1] #define C_XTYPE_OK(type) ((type) == CHOLMOD_COMPLEX) #define C_IS_NONZERO(ax,az,q) \ (IS_NONZERO (ax [2*(q)]) || IS_NONZERO (ax [2*(q)+1])) #define C_IS_ZERO(ax,az,q) \ (IS_ZERO (ax [2*(q)]) && IS_ZERO (ax [2*(q)+1])) #define C_IS_ONE(ax,az,q) \ ((ax [2*(q)] == 1) && IS_ZERO (ax [2*(q)+1])) #define C_IMAG_IS_NONZERO(ax,az,q) (IS_NONZERO (ax [2*(q)+1])) #define C_MULT(x,z,p, ax,az,q, bx,bz,r) \ x [2*(p) ] = ax [2*(q) ] * bx [2*(r)] - ax [2*(q)+1] * bx [2*(r)+1] ; \ x [2*(p)+1] = ax [2*(q)+1] * bx [2*(r)] + ax [2*(q) ] * bx [2*(r)+1] #define C_MULTADD(x,z,p, ax,az,q, bx,bz,r) \ x [2*(p) ] += ax [2*(q) ] * bx [2*(r)] - ax [2*(q)+1] * bx [2*(r)+1] ; \ x [2*(p)+1] += ax [2*(q)+1] * bx [2*(r)] + ax [2*(q) ] * bx [2*(r)+1] #define C_MULTSUB(x,z,p, ax,az,q, bx,bz,r) \ x [2*(p) ] -= ax [2*(q) ] * bx [2*(r)] - ax [2*(q)+1] * bx [2*(r)+1] ; \ x [2*(p)+1] -= ax [2*(q)+1] * bx [2*(r)] + ax [2*(q) ] * bx [2*(r)+1] /* s += conj(a)*b */ #define C_MULTADDCONJ(x,z,p, ax,az,q, bx,bz,r) \ x [2*(p) ] += ax [2*(q) ] * bx [2*(r)] + ax [2*(q)+1] * bx [2*(r)+1] ; \ x [2*(p)+1] += (-ax [2*(q)+1]) * bx [2*(r)] + ax [2*(q) ] * bx [2*(r)+1] /* s -= conj(a)*b */ #define C_MULTSUBCONJ(x,z,p, ax,az,q, bx,bz,r) \ x [2*(p) ] -= ax [2*(q) ] * bx [2*(r)] + ax [2*(q)+1] * bx [2*(r)+1] ; \ x [2*(p)+1] -= (-ax [2*(q)+1]) * bx [2*(r)] + ax [2*(q) ] * bx [2*(r)+1] #define C_ADD(x,z,p, ax,az,q, bx,bz,r) \ x [2*(p) ] = ax [2*(q) ] + bx [2*(r) ] ; \ x [2*(p)+1] = ax [2*(q)+1] + bx [2*(r)+1] #define C_ADD_REAL(x,p, ax,q, bx,r) \ x [2*(p)] = ax [2*(q)] + bx [2*(r)] #define C_CLEAR(x,z,p) \ x [2*(p) ] = 0 ; \ x [2*(p)+1] = 0 #define C_CLEAR_IMAG(x,z,p) \ x [2*(p)+1] = 0 /* s = s / a */ #define C_DIV(x,z,p,ax,az,q) \ Common->complex_divide ( \ x [2*(p)], x [2*(p)+1], \ ax [2*(q)], ax [2*(q)+1], \ &x [2*(p)], &x [2*(p)+1]) /* s -= conj(a)*a ; note that the result of conj(a)*a is real */ #define C_LLDOT(x,p, ax,az,q) \ x [2*(p)] -= ax [2*(q)] * ax [2*(q)] + ax [2*(q)+1] * ax [2*(q)+1] #define C_PRINT(k,x,z,p) PRK(k, ("(%24.16e,%24.16e)", x [2*(p)], x [2*(p)+1])) #define C_DIV_REAL(x,z,p, ax,az,q, bx,r) \ x [2*(p) ] = ax [2*(q) ] / bx [2*(r)] ; \ x [2*(p)+1] = ax [2*(q)+1] / bx [2*(r)] #define C_MULT_REAL(x,z,p, ax,az,q, bx,r) \ x [2*(p) ] = ax [2*(q) ] * bx [2*(r)] ; \ x [2*(p)+1] = ax [2*(q)+1] * bx [2*(r)] /* s -= conj(a)*a/t */ #define C_LDLDOT(x,p, ax,az,q, bx,r) \ x [2*(p)] -= (ax [2*(q)] * ax [2*(q)] + ax [2*(q)+1] * ax [2*(q)+1]) / bx[r] /* -------------------------------------------------------------------------- */ /* zomplex */ /* -------------------------------------------------------------------------- */ #define Z_TEMPLATE(name) z_ ## name #define ZT_TEMPLATE(name) zt_ ## name #define Z_ASSEMBLE(x,z,p,ax,az,q) \ x [p] += ax [q] ; \ z [p] += az [q] #define Z_ASSIGN(x,z,p,ax,az,q) \ x [p] = ax [q] ; \ z [p] = az [q] #define Z_ASSIGN_REAL(x,p,ax,q) x [p] = ax [q] #define Z_ASSIGN_CONJ(x,z,p,ax,az,q) \ x [p] = ax [q] ; \ z [p] = -az [q] #define Z_XTYPE_OK(type) ((type) == CHOLMOD_ZOMPLEX) #define Z_IS_NONZERO(ax,az,q) \ (IS_NONZERO (ax [q]) || IS_NONZERO (az [q])) #define Z_IS_ZERO(ax,az,q) \ (IS_ZERO (ax [q]) && IS_ZERO (az [q])) #define Z_IS_ONE(ax,az,q) \ ((ax [q] == 1) && IS_ZERO (az [q])) #define Z_IMAG_IS_NONZERO(ax,az,q) (IS_NONZERO (az [q])) #define Z_MULT(x,z,p, ax,az,q, bx,bz,r) \ x [p] = ax [q] * bx [r] - az [q] * bz [r] ; \ z [p] = az [q] * bx [r] + ax [q] * bz [r] #define Z_MULTADD(x,z,p, ax,az,q, bx,bz,r) \ x [p] += ax [q] * bx [r] - az [q] * bz [r] ; \ z [p] += az [q] * bx [r] + ax [q] * bz [r] #define Z_MULTSUB(x,z,p, ax,az,q, bx,bz,r) \ x [p] -= ax [q] * bx [r] - az [q] * bz [r] ; \ z [p] -= az [q] * bx [r] + ax [q] * bz [r] #define Z_MULTADDCONJ(x,z,p, ax,az,q, bx,bz,r) \ x [p] += ax [q] * bx [r] + az [q] * bz [r] ; \ z [p] += (-az [q]) * bx [r] + ax [q] * bz [r] #define Z_MULTSUBCONJ(x,z,p, ax,az,q, bx,bz,r) \ x [p] -= ax [q] * bx [r] + az [q] * bz [r] ; \ z [p] -= (-az [q]) * bx [r] + ax [q] * bz [r] #define Z_ADD(x,z,p, ax,az,q, bx,bz,r) \ x [p] = ax [q] + bx [r] ; \ z [p] = az [q] + bz [r] #define Z_ADD_REAL(x,p, ax,q, bx,r) \ x [p] = ax [q] + bx [r] #define Z_CLEAR(x,z,p) \ x [p] = 0 ; \ z [p] = 0 #define Z_CLEAR_IMAG(x,z,p) \ z [p] = 0 /* s = s/a */ #define Z_DIV(x,z,p,ax,az,q) \ Common->complex_divide (x [p], z [p], ax [q], az [q], &x [p], &z [p]) /* s -= conj(a)*a ; note that the result of conj(a)*a is real */ #define Z_LLDOT(x,p, ax,az,q) \ x [p] -= ax [q] * ax [q] + az [q] * az [q] #define Z_PRINT(k,x,z,p) PRK(k, ("(%24.16e,%24.16e)", x [p], z [p])) #define Z_DIV_REAL(x,z,p, ax,az,q, bx,r) \ x [p] = ax [q] / bx [r] ; \ z [p] = az [q] / bx [r] #define Z_MULT_REAL(x,z,p, ax,az,q, bx,r) \ x [p] = ax [q] * bx [r] ; \ z [p] = az [q] * bx [r] /* s -= conj(a)*a/t */ #define Z_LDLDOT(x,p, ax,az,q, bx,r) \ x [p] -= (ax [q] * ax [q] + az [q] * az [q]) / bx[r] /* -------------------------------------------------------------------------- */ /* all classes */ /* -------------------------------------------------------------------------- */ /* Check if A->xtype and the two arrays A->x and A->z are valid. Set status to * invalid, unless status is already "out of memory". A can be a sparse matrix, * dense matrix, factor, or triplet. */ #define RETURN_IF_XTYPE_INVALID(A,xtype1,xtype2,result) \ { \ if ((A)->xtype < (xtype1) || (A)->xtype > (xtype2) || \ ((A)->xtype != CHOLMOD_PATTERN && ((A)->x) == NULL) || \ ((A)->xtype == CHOLMOD_ZOMPLEX && ((A)->z) == NULL)) \ { \ if (Common->status != CHOLMOD_OUT_OF_MEMORY) \ { \ ERROR (CHOLMOD_INVALID, "invalid xtype") ; \ } \ return (result) ; \ } \ } python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Include/License.txt0000644000076500000240000000041213524616144026174 0ustar tamasstaff00000000000000CHOLMOD/Include/* files. Copyright (C) 2005-2006, either Univ. of Florida or T. Davis, depending on the file. Refer to each include file in this directory; each file is licensed separately, according to the Module for which it contains definitions and prototypes. python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Include/cholmod_cholesky.h0000644000076500000240000005330713524616144027563 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Include/cholmod_cholesky.h =========================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Include/cholmod_cholesky.h. Copyright (C) 2005-2013, Timothy A. Davis * CHOLMOD/Include/cholmod_cholesky.h is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * http://www.suitesparse.com * -------------------------------------------------------------------------- */ /* CHOLMOD Cholesky module. * * Sparse Cholesky routines: analysis, factorization, and solve. * * The primary routines are all that a user requires to order, analyze, and * factorize a sparse symmetric positive definite matrix A (or A*A'), and * to solve Ax=b (or A*A'x=b). The primary routines rely on the secondary * routines, the CHOLMOD Core module, and the AMD and COLAMD packages. They * make optional use of the CHOLMOD Supernodal and Partition modules, the * METIS package, and the CCOLAMD package. * * Primary routines: * ----------------- * * cholmod_analyze order and analyze (simplicial or supernodal) * cholmod_factorize simplicial or supernodal Cholesky factorization * cholmod_solve solve a linear system (simplicial or supernodal) * cholmod_solve2 like cholmod_solve, but reuse workspace * cholmod_spsolve solve a linear system (sparse x and b) * * Secondary routines: * ------------------ * * cholmod_analyze_p analyze, with user-provided permutation or f set * cholmod_factorize_p factorize, with user-provided permutation or f * cholmod_analyze_ordering analyze a fill-reducing ordering * cholmod_etree find the elimination tree * cholmod_rowcolcounts compute the row/column counts of L * cholmod_amd order using AMD * cholmod_colamd order using COLAMD * cholmod_rowfac incremental simplicial factorization * cholmod_rowfac_mask rowfac, specific to LPDASA * cholmod_row_subtree find the nonzero pattern of a row of L * cholmod_resymbol recompute the symbolic pattern of L * cholmod_resymbol_noperm recompute the symbolic pattern of L, no L->Perm * cholmod_postorder postorder a tree * * Requires the Core module, and two packages: AMD and COLAMD. * Optionally uses the Supernodal and Partition modules. * Required by the Partition module. */ #ifndef CHOLMOD_CHOLESKY_H #define CHOLMOD_CHOLESKY_H #include "cholmod_config.h" #include "cholmod_core.h" #ifndef NPARTITION #include "cholmod_partition.h" #endif #ifndef NSUPERNODAL #include "cholmod_supernodal.h" #endif /* -------------------------------------------------------------------------- */ /* cholmod_analyze: order and analyze (simplicial or supernodal) */ /* -------------------------------------------------------------------------- */ /* Orders and analyzes A, AA', PAP', or PAA'P' and returns a symbolic factor * that can later be passed to cholmod_factorize. */ cholmod_factor *cholmod_analyze ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to order and analyze */ /* --------------- */ cholmod_common *Common ) ; cholmod_factor *cholmod_l_analyze (cholmod_sparse *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_analyze_p: analyze, with user-provided permutation or f set */ /* -------------------------------------------------------------------------- */ /* Orders and analyzes A, AA', PAP', PAA'P', FF', or PFF'P and returns a * symbolic factor that can later be passed to cholmod_factorize, where * F = A(:,fset) if fset is not NULL and A->stype is zero. * UserPerm is tried if non-NULL. */ cholmod_factor *cholmod_analyze_p ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to order and analyze */ int *UserPerm, /* user-provided permutation, size A->nrow */ int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ /* --------------- */ cholmod_common *Common ) ; cholmod_factor *cholmod_l_analyze_p (cholmod_sparse *, SuiteSparse_long *, SuiteSparse_long *, size_t, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_analyze_p2: analyze for sparse Cholesky or sparse QR */ /* -------------------------------------------------------------------------- */ cholmod_factor *cholmod_analyze_p2 ( /* ---- input ---- */ int for_cholesky, /* if TRUE, then analyze for Cholesky; else for QR */ cholmod_sparse *A, /* matrix to order and analyze */ int *UserPerm, /* user-provided permutation, size A->nrow */ int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ /* --------------- */ cholmod_common *Common ) ; cholmod_factor *cholmod_l_analyze_p2 (int, cholmod_sparse *, SuiteSparse_long *, SuiteSparse_long *, size_t, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_factorize: simplicial or supernodal Cholesky factorization */ /* -------------------------------------------------------------------------- */ /* Factorizes PAP' (or PAA'P' if A->stype is 0), using a factor obtained * from cholmod_analyze. The analysis can be re-used simply by calling this * routine a second time with another matrix. A must have the same nonzero * pattern as that passed to cholmod_analyze. */ int cholmod_factorize ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to factorize */ /* ---- in/out --- */ cholmod_factor *L, /* resulting factorization */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_factorize (cholmod_sparse *, cholmod_factor *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_factorize_p: factorize, with user-provided permutation or fset */ /* -------------------------------------------------------------------------- */ /* Same as cholmod_factorize, but with more options. */ int cholmod_factorize_p ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to factorize */ double beta [2], /* factorize beta*I+A or beta*I+A'*A */ int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ /* ---- in/out --- */ cholmod_factor *L, /* resulting factorization */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_factorize_p (cholmod_sparse *, double *, SuiteSparse_long *, size_t, cholmod_factor *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_solve: solve a linear system (simplicial or supernodal) */ /* -------------------------------------------------------------------------- */ /* Solves one of many linear systems with a dense right-hand-side, using the * factorization from cholmod_factorize (or as modified by any other CHOLMOD * routine). D is identity for LL' factorizations. */ #define CHOLMOD_A 0 /* solve Ax=b */ #define CHOLMOD_LDLt 1 /* solve LDL'x=b */ #define CHOLMOD_LD 2 /* solve LDx=b */ #define CHOLMOD_DLt 3 /* solve DL'x=b */ #define CHOLMOD_L 4 /* solve Lx=b */ #define CHOLMOD_Lt 5 /* solve L'x=b */ #define CHOLMOD_D 6 /* solve Dx=b */ #define CHOLMOD_P 7 /* permute x=Px */ #define CHOLMOD_Pt 8 /* permute x=P'x */ cholmod_dense *cholmod_solve /* returns the solution X */ ( /* ---- input ---- */ int sys, /* system to solve */ cholmod_factor *L, /* factorization to use */ cholmod_dense *B, /* right-hand-side */ /* --------------- */ cholmod_common *Common ) ; cholmod_dense *cholmod_l_solve (int, cholmod_factor *, cholmod_dense *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_solve2: like cholmod_solve, but with reusable workspace */ /* -------------------------------------------------------------------------- */ int cholmod_solve2 /* returns TRUE on success, FALSE on failure */ ( /* ---- input ---- */ int sys, /* system to solve */ cholmod_factor *L, /* factorization to use */ cholmod_dense *B, /* right-hand-side */ cholmod_sparse *Bset, /* ---- output --- */ cholmod_dense **X_Handle, /* solution, allocated if need be */ cholmod_sparse **Xset_Handle, /* ---- workspace */ cholmod_dense **Y_Handle, /* workspace, or NULL */ cholmod_dense **E_Handle, /* workspace, or NULL */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_solve2 (int, cholmod_factor *, cholmod_dense *, cholmod_sparse *, cholmod_dense **, cholmod_sparse **, cholmod_dense **, cholmod_dense **, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_spsolve: solve a linear system with a sparse right-hand-side */ /* -------------------------------------------------------------------------- */ cholmod_sparse *cholmod_spsolve ( /* ---- input ---- */ int sys, /* system to solve */ cholmod_factor *L, /* factorization to use */ cholmod_sparse *B, /* right-hand-side */ /* --------------- */ cholmod_common *Common ) ; cholmod_sparse *cholmod_l_spsolve (int, cholmod_factor *, cholmod_sparse *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_etree: find the elimination tree of A or A'*A */ /* -------------------------------------------------------------------------- */ int cholmod_etree ( /* ---- input ---- */ cholmod_sparse *A, /* ---- output --- */ int *Parent, /* size ncol. Parent [j] = p if p is the parent of j */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_etree (cholmod_sparse *, SuiteSparse_long *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_rowcolcounts: compute the row/column counts of L */ /* -------------------------------------------------------------------------- */ int cholmod_rowcolcounts ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to analyze */ int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ int *Parent, /* size nrow. Parent [i] = p if p is the parent of i */ int *Post, /* size nrow. Post [k] = i if i is the kth node in * the postordered etree. */ /* ---- output --- */ int *RowCount, /* size nrow. RowCount [i] = # entries in the ith row of * L, including the diagonal. */ int *ColCount, /* size nrow. ColCount [i] = # entries in the ith * column of L, including the diagonal. */ int *First, /* size nrow. First [i] = k is the least postordering * of any descendant of i. */ int *Level, /* size nrow. Level [i] is the length of the path from * i to the root, with Level [root] = 0. */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_rowcolcounts (cholmod_sparse *, SuiteSparse_long *, size_t, SuiteSparse_long *, SuiteSparse_long *, SuiteSparse_long *, SuiteSparse_long *, SuiteSparse_long *, SuiteSparse_long *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_analyze_ordering: analyze a fill-reducing ordering */ /* -------------------------------------------------------------------------- */ int cholmod_analyze_ordering ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to analyze */ int ordering, /* ordering method used */ int *Perm, /* size n, fill-reducing permutation to analyze */ int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ /* ---- output --- */ int *Parent, /* size n, elimination tree */ int *Post, /* size n, postordering of elimination tree */ int *ColCount, /* size n, nnz in each column of L */ /* ---- workspace */ int *First, /* size nworkspace for cholmod_postorder */ int *Level, /* size n workspace for cholmod_postorder */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_analyze_ordering (cholmod_sparse *, int, SuiteSparse_long *, SuiteSparse_long *, size_t, SuiteSparse_long *, SuiteSparse_long *, SuiteSparse_long *, SuiteSparse_long *, SuiteSparse_long *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_amd: order using AMD */ /* -------------------------------------------------------------------------- */ /* Finds a permutation P to reduce fill-in in the factorization of P*A*P' * or P*A*A'P' */ int cholmod_amd ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to order */ int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ /* ---- output --- */ int *Perm, /* size A->nrow, output permutation */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_amd (cholmod_sparse *, SuiteSparse_long *, size_t, SuiteSparse_long *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_colamd: order using COLAMD */ /* -------------------------------------------------------------------------- */ /* Finds a permutation P to reduce fill-in in the factorization of P*A*A'*P'. * Orders F*F' where F = A (:,fset) if fset is not NULL */ int cholmod_colamd ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to order */ int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ int postorder, /* if TRUE, follow with a coletree postorder */ /* ---- output --- */ int *Perm, /* size A->nrow, output permutation */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_colamd (cholmod_sparse *, SuiteSparse_long *, size_t, int, SuiteSparse_long *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_rowfac: incremental simplicial factorization */ /* -------------------------------------------------------------------------- */ /* Partial or complete simplicial factorization. Rows and columns kstart:kend-1 * of L and D must be initially equal to rows/columns kstart:kend-1 of the * identity matrix. Row k can only be factorized if all descendants of node * k in the elimination tree have been factorized. */ int cholmod_rowfac ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to factorize */ cholmod_sparse *F, /* used for A*A' case only. F=A' or A(:,fset)' */ double beta [2], /* factorize beta*I+A or beta*I+A'*A */ size_t kstart, /* first row to factorize */ size_t kend, /* last row to factorize is kend-1 */ /* ---- in/out --- */ cholmod_factor *L, /* --------------- */ cholmod_common *Common ) ; int cholmod_l_rowfac (cholmod_sparse *, cholmod_sparse *, double *, size_t, size_t, cholmod_factor *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_rowfac_mask: incremental simplicial factorization */ /* -------------------------------------------------------------------------- */ /* cholmod_rowfac_mask is a version of cholmod_rowfac that is specific to * LPDASA. It is unlikely to be needed by any other application. */ int cholmod_rowfac_mask ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to factorize */ cholmod_sparse *F, /* used for A*A' case only. F=A' or A(:,fset)' */ double beta [2], /* factorize beta*I+A or beta*I+A'*A */ size_t kstart, /* first row to factorize */ size_t kend, /* last row to factorize is kend-1 */ int *mask, /* if mask[i] >= 0, then set row i to zero */ int *RLinkUp, /* link list of rows to compute */ /* ---- in/out --- */ cholmod_factor *L, /* --------------- */ cholmod_common *Common ) ; int cholmod_l_rowfac_mask (cholmod_sparse *, cholmod_sparse *, double *, size_t, size_t, SuiteSparse_long *, SuiteSparse_long *, cholmod_factor *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_row_subtree: find the nonzero pattern of a row of L */ /* -------------------------------------------------------------------------- */ /* Find the nonzero pattern of x for the system Lx=b where L = (0:k-1,0:k-1) * and b = kth column of A or A*A' (rows 0 to k-1 only) */ int cholmod_row_subtree ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to analyze */ cholmod_sparse *F, /* used for A*A' case only. F=A' or A(:,fset)' */ size_t k, /* row k of L */ int *Parent, /* elimination tree */ /* ---- output --- */ cholmod_sparse *R, /* pattern of L(k,:), n-by-1 with R->nzmax >= n */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_row_subtree (cholmod_sparse *, cholmod_sparse *, size_t, SuiteSparse_long *, cholmod_sparse *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_lsolve_pattern: find the nonzero pattern of x=L\b */ /* -------------------------------------------------------------------------- */ int cholmod_lsolve_pattern ( /* ---- input ---- */ cholmod_sparse *B, /* sparse right-hand-side (a single sparse column) */ cholmod_factor *L, /* the factor L from which parent(i) is derived */ /* ---- output --- */ cholmod_sparse *X, /* pattern of X=L\B, n-by-1 with X->nzmax >= n */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_lsolve_pattern (cholmod_sparse *, cholmod_factor *, cholmod_sparse *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_row_lsubtree: find the nonzero pattern of a row of L */ /* -------------------------------------------------------------------------- */ /* Identical to cholmod_row_subtree, except that it finds the elimination tree * from L itself. */ int cholmod_row_lsubtree ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to analyze */ int *Fi, size_t fnz, /* nonzero pattern of kth row of A', not required * for the symmetric case. Need not be sorted. */ size_t k, /* row k of L */ cholmod_factor *L, /* the factor L from which parent(i) is derived */ /* ---- output --- */ cholmod_sparse *R, /* pattern of L(k,:), n-by-1 with R->nzmax >= n */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_row_lsubtree (cholmod_sparse *, SuiteSparse_long *, size_t, size_t, cholmod_factor *, cholmod_sparse *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_resymbol: recompute the symbolic pattern of L */ /* -------------------------------------------------------------------------- */ /* Remove entries from L that are not in the factorization of P*A*P', P*A*A'*P', * or P*F*F'*P' (depending on A->stype and whether fset is NULL or not). * * cholmod_resymbol is the same as cholmod_resymbol_noperm, except that it * first permutes A according to L->Perm. A can be upper/lower/unsymmetric, * in contrast to cholmod_resymbol_noperm (which can be lower or unsym). */ int cholmod_resymbol ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to analyze */ int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ int pack, /* if TRUE, pack the columns of L */ /* ---- in/out --- */ cholmod_factor *L, /* factorization, entries pruned on output */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_resymbol (cholmod_sparse *, SuiteSparse_long *, size_t, int, cholmod_factor *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_resymbol_noperm: recompute the symbolic pattern of L, no L->Perm */ /* -------------------------------------------------------------------------- */ /* Remove entries from L that are not in the factorization of A, A*A', * or F*F' (depending on A->stype and whether fset is NULL or not). */ int cholmod_resymbol_noperm ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to analyze */ int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ int pack, /* if TRUE, pack the columns of L */ /* ---- in/out --- */ cholmod_factor *L, /* factorization, entries pruned on output */ /* --------------- */ cholmod_common *Common ) ; int cholmod_l_resymbol_noperm (cholmod_sparse *, SuiteSparse_long *, size_t, int, cholmod_factor *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_rcond: compute rough estimate of reciprocal of condition number */ /* -------------------------------------------------------------------------- */ double cholmod_rcond /* return min(diag(L)) / max(diag(L)) */ ( /* ---- input ---- */ cholmod_factor *L, /* --------------- */ cholmod_common *Common ) ; double cholmod_l_rcond (cholmod_factor *, cholmod_common *) ; /* -------------------------------------------------------------------------- */ /* cholmod_postorder: Compute the postorder of a tree */ /* -------------------------------------------------------------------------- */ SuiteSparse_long cholmod_postorder /* return # of nodes postordered */ ( /* ---- input ---- */ int *Parent, /* size n. Parent [j] = p if p is the parent of j */ size_t n, int *Weight_p, /* size n, optional. Weight [j] is weight of node j */ /* ---- output --- */ int *Post, /* size n. Post [k] = j is kth in postordered tree */ /* --------------- */ cholmod_common *Common ) ; SuiteSparse_long cholmod_l_postorder (SuiteSparse_long *, size_t, SuiteSparse_long *, SuiteSparse_long *, cholmod_common *) ; #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Include/cholmod.h0000644000076500000240000000746313524616144025664 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Include/cholmod.h ==================================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Include/cholmod.h. * Copyright (C) 2005-2013, Univ. of Florida. Author: Timothy A. Davis * CHOLMOD/Include/cholmod.h is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * http://www.suitesparse.com * * Portions of CHOLMOD (the Core and Partition Modules) are copyrighted by the * University of Florida. The Modify Module is co-authored by William W. * Hager, Univ. of Florida. * * Acknowledgements: this work was supported in part by the National Science * Foundation (NFS CCR-0203270 and DMS-9803599), and a grant from Sandia * National Laboratories (Dept. of Energy) which supported the development of * CHOLMOD's Partition Module. * -------------------------------------------------------------------------- */ /* CHOLMOD include file, for inclusion user programs. * * The include files listed below include a short description of each user- * callable routine. Each routine in CHOLMOD has a consistent interface. * More details about the CHOLMOD data types is in the cholmod_core.h file. * * Naming convention: * ------------------ * * All routine names, data types, and CHOLMOD library files use the * cholmod_ prefix. All macros and other #define's use the CHOLMOD * prefix. * * Return value: * ------------- * * Most CHOLMOD routines return an int (TRUE (1) if successful, or FALSE * (0) otherwise. A SuiteSparse_long or double return value is >= 0 if * successful, or -1 otherwise. A size_t return value is > 0 if * successful, or 0 otherwise. * * If a routine returns a pointer, it is a pointer to a newly allocated * object or NULL if a failure occured, with one exception. cholmod_free * always returns NULL. * * "Common" parameter: * ------------------ * * The last parameter in all CHOLMOD routines is a pointer to the CHOLMOD * "Common" object. This contains control parameters, statistics, and * workspace used between calls to CHOLMOD. It is always an input/output * parameter. * * Input, Output, and Input/Output parameters: * ------------------------------------------- * * Input parameters are listed first. They are not modified by CHOLMOD. * * Input/output are listed next. They must be defined on input, and * are modified on output. * * Output parameters are listed next. If they are pointers, they must * point to allocated space on input, but their contents are not defined * on input. * * Workspace parameters appear next. They are used in only two routines * in the Supernodal module. * * The cholmod_common *Common parameter always appears as the last * parameter. It is always an input/output parameter. */ #ifndef CHOLMOD_H #define CHOLMOD_H /* make it easy for C++ programs to include CHOLMOD */ #ifdef __cplusplus extern "C" { #endif /* assume large file support. If problems occur, compile with -DNLARGEFILE */ #include "cholmod_io64.h" #include "SuiteSparse_config.h" #include "cholmod_config.h" /* CHOLMOD always includes the Core module. */ #include "cholmod_core.h" #ifndef NCHECK #include "cholmod_check.h" #endif #ifndef NCHOLESKY #include "cholmod_cholesky.h" #endif #ifndef NMATRIXOPS #include "cholmod_matrixops.h" #endif #ifndef NMODIFY #include "cholmod_modify.h" #endif #ifndef NCAMD #include "cholmod_camd.h" #endif #ifndef NPARTITION #include "cholmod_partition.h" #endif #ifndef NSUPERNODAL #include "cholmod_supernodal.h" #endif #ifdef __cplusplus } #endif #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Modify/0000755000076500000240000000000013617375001023715 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Modify/t_cholmod_updown_numkr.c0000644000076500000240000005165213524616144030655 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Modify/t_cholmod_updown_numkr ======================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Modify Module. Copyright (C) 2005-2006, * Timothy A. Davis and William W. Hager. * The CHOLMOD/Modify Module is licensed under Version 2.0 of the GNU * General Public License. See gpl.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * http://www.suitesparse.com * -------------------------------------------------------------------------- */ /* Supernodal numerical update/downdate of rank K = RANK, along a single path. * This routine operates on a simplicial factor, but operates on adjacent * columns of L that would fit within a single supernode. "Adjacent" means * along a single path in the elimination tree; they may or may not be * adjacent in the matrix L. * * external defines: NUMERIC, WDIM, RANK. * * WDIM is 1, 2, 4, or 8. RANK can be 1 to WDIM. * * A simple method is included (#define SIMPLE). The code works, but is slow. * It is meant only to illustrate what this routine is doing. * * A rank-K update proceeds along a single path, using single-column, dual- * column, or quad-column updates of L. If a column j and the next column * in the path (its parent) do not have the same nonzero pattern, a single- * column update is used. If they do, but the 3rd and 4th column from j do * not have the same pattern, a dual-column update is used, in which the two * columns are treated as if they were a single supernode of two columns. If * there are 4 columns in the path that all have the same nonzero pattern, then * a quad-column update is used. All three kinds of updates can be used along * a single path, in a single call to this function. * * Single-column update: * * When updating a single column of L, each iteration of the for loop, * below, processes four rows of W (all columns involved) and one column * of L. Suppose we have a rank-5 update, and columns 2 through 6 of W * are involved. In this case, W in this routine is a pointer to column * 2 of the matrix W in the caller. W (in the caller, shown as 'W') is * held in row-major order, and is 8-by-n (a dense matrix storage format), * but shown below in column form to match the column of L. Suppose there * are 13 nonzero entries in column 27 of L, with row indices 27 (the * diagonal, D), 28, 30, 31, 42, 43, 44, 50, 51, 67, 81, 83, and 84. This * pattern is held in Li [Lp [27] ... Lp [27 + Lnz [27] - 1], where * Lnz [27] = 13. The modification of the current column j of L is done * in the following order. A dot (.) means the entry of W is not accessed. * * W0 points to row 27 of W, and G is a 1-by-8 temporary vector. * * G[0] G[4] * G x x x x x . . . * * W0 * | * v * 27 . . x x x x x . W0 points to W (27,2) * * * row 'W' W column j = 27 * | | | of L * v v v | * first iteration of for loop: v * * 28 . . 1 5 9 13 17 . x * 30 . . 2 6 10 14 18 . x * 31 . . 3 7 11 15 19 . x * 42 . . 4 8 12 16 20 . x * * second iteration of for loop: * * 43 . . 1 5 9 13 17 . x * 44 . . 2 6 10 14 18 . x * 50 . . 3 7 11 15 19 . x * 51 . . 4 8 12 16 20 . x * * third iteration of for loop: * * 67 . . 1 5 9 13 17 . x * 81 . . 2 6 10 14 18 . x * 83 . . 3 7 11 15 19 . x * 84 . . 4 8 12 16 20 . x * * If the number of offdiagonal nonzeros in column j of L is not divisible * by 4, then the switch-statement does the work for the first nz % 4 rows. * * Dual-column update: * * In this case, two columns of L that are adjacent in the path are being * updated, by 1 to 8 columns of W. Suppose columns j=27 and j=28 are * adjacent columns in the path (they need not be j and j+1). Two rows * of G and W are used as coefficients during the update: (G0, G1) and * (W0, W1). * * G0 x x x x x . . . * G1 x x x x x . . . * * 27 . . x x x x x . W0 points to W (27,2) * 28 . . x x x x x . W1 points to W (28,2) * * * row 'W' W0,W1 column j = 27 * | | | of L * v v v | * | |-- column j = 28 of L * v v * update L (j1,j): * * 28 . . 1 2 3 4 5 . x - ("-" is not stored in L) * * cleanup iteration since length is odd: * * 30 . . 1 2 3 4 5 . x x * * then each iteration does two rows of both columns of L: * * 31 . . 1 3 5 7 9 . x x * 42 . . 2 4 6 8 10 . x x * * 43 . . 1 3 5 7 9 . x x * 44 . . 2 4 6 8 10 . x x * * 50 . . 1 3 5 7 9 . x x * 51 . . 2 4 6 8 10 . x x * * 67 . . 1 3 5 7 9 . x x * 81 . . 2 4 6 8 10 . x x * * 83 . . 1 3 5 7 9 . x x * 84 . . 2 4 6 8 10 . x x * * If the number of offdiagonal nonzeros in column j of L is not even, * then the cleanup iteration does the work for the first row. * * Quad-column update: * * In this case, four columns of L that are adjacent in the path are being * updated, by 1 to 8 columns of W. Suppose columns j=27, 28, 30, and 31 * are adjacent columns in the path (they need not be j, j+1, ...). Four * rows of G and W are used as coefficients during the update: (G0 through * G3) and (W0 through W3). j=27, j1=28, j2=30, and j3=31. * * G0 x x x x x . . . * G1 x x x x x . . . * G3 x x x x x . . . * G4 x x x x x . . . * * 27 . . x x x x x . W0 points to W (27,2) * 28 . . x x x x x . W1 points to W (28,2) * 30 . . x x x x x . W2 points to W (30,2) * 31 . . x x x x x . W3 points to W (31,2) * * * row 'W' W0,W1,.. column j = 27 * | | | of L * v v v | * | |-- column j = 28 of L * | | |-- column j = 30 of L * | | | |-- column j = 31 of L * v v v v * update L (j1,j): * 28 . . 1 2 3 4 5 . x - - - * * update L (j2,j): * 30 . . 1 2 3 4 5 . # x - - (# denotes modified) * * update L (j2,j1) * 30 . . 1 2 3 4 5 . x # - - * * update L (j3,j) * 31 . . 1 2 3 4 5 . # x x - * * update L (j3,j1) * 31 . . 1 2 3 4 5 . x # x - * * update L (j3,j2) * 31 . . 1 2 3 4 5 . x x # - * * cleanup iteration since length is odd: * 42 . . 1 2 3 4 5 . x x x x * * * ----- CHOLMOD v1.1.1 did the following -------------------------------------- * then each iteration does two rows of all four colummns of L: * * 43 . . 1 3 5 7 9 . x x x x * 44 . . 2 4 6 8 10 . x x x x * * 50 . . 1 3 5 7 9 . x x x x * 51 . . 2 4 6 8 10 . x x x x * * 67 . . 1 3 5 7 9 . x x x x * 81 . . 2 4 6 8 10 . x x x x * * 83 . . 1 3 5 7 9 . x x x x * 84 . . 2 4 6 8 10 . x x x x * * ----- CHOLMOD v1.2.0 does the following ------------------------------------- * then each iteration does one rows of all four colummns of L: * * 43 . . 1 2 3 4 5 . x x x x * 44 . . 1 2 3 4 5 . x x x x * 50 . . 1 3 5 4 5 . x x x x * 51 . . 1 2 3 4 5 . x x x x * 67 . . 1 3 5 4 5 . x x x x * 81 . . 1 2 3 4 5 . x x x x * 83 . . 1 3 5 4 5 . x x x x * 84 . . 1 2 3 4 5 . x x x x * * This file is included in t_cholmod_updown.c, only. * It is not compiled separately. It contains no user-callable routines. * * workspace: Xwork (WDIM*nrow) */ /* ========================================================================== */ /* === loop unrolling macros ================================================ */ /* ========================================================================== */ #undef RANK1 #undef RANK2 #undef RANK3 #undef RANK4 #undef RANK5 #undef RANK6 #undef RANK7 #undef RANK8 #define RANK1(statement) statement #if RANK < 2 #define RANK2(statement) #else #define RANK2(statement) statement #endif #if RANK < 3 #define RANK3(statement) #else #define RANK3(statement) statement #endif #if RANK < 4 #define RANK4(statement) #else #define RANK4(statement) statement #endif #if RANK < 5 #define RANK5(statement) #else #define RANK5(statement) statement #endif #if RANK < 6 #define RANK6(statement) #else #define RANK6(statement) statement #endif #if RANK < 7 #define RANK7(statement) #else #define RANK7(statement) statement #endif #if RANK < 8 #define RANK8(statement) #else #define RANK8(statement) statement #endif #define FOR_ALL_K \ RANK1 (DO (0)) \ RANK2 (DO (1)) \ RANK3 (DO (2)) \ RANK4 (DO (3)) \ RANK5 (DO (4)) \ RANK6 (DO (5)) \ RANK7 (DO (6)) \ RANK8 (DO (7)) /* ========================================================================== */ /* === alpha/gamma ========================================================== */ /* ========================================================================== */ #undef ALPHA_GAMMA #define ALPHA_GAMMA(Dj,Alpha,Gamma,W) \ { \ double dj = Dj ; \ if (update) \ { \ for (k = 0 ; k < RANK ; k++) \ { \ double w = W [k] ; \ double alpha = Alpha [k] ; \ double a = alpha + (w * w) / dj ; \ dj *= a ; \ Alpha [k] = a ; \ Gamma [k] = (- w / dj) ; \ dj /= alpha ; \ } \ } \ else \ { \ for (k = 0 ; k < RANK ; k++) \ { \ double w = W [k] ; \ double alpha = Alpha [k] ; \ double a = alpha - (w * w) / dj ; \ dj *= a ; \ Alpha [k] = a ; \ Gamma [k] = w / dj ; \ dj /= alpha ; \ } \ } \ Dj = ((use_dbound) ? (CHOLMOD(dbound) (dj, Common)) : (dj)) ; \ } /* ========================================================================== */ /* === numeric update/downdate along one path =============================== */ /* ========================================================================== */ static void NUMERIC (WDIM, RANK) ( int update, /* TRUE for update, FALSE for downdate */ Int j, /* first column in the path */ Int e, /* last column in the path */ double Alpha [ ], /* alpha, for each column of W */ double W [ ], /* W is an n-by-WDIM array, stored in row-major order */ cholmod_factor *L, /* with unit diagonal (diagonal not stored) */ cholmod_common *Common ) { #ifdef SIMPLE #define w(row,col) W [WDIM*(row) + (col)] /* ---------------------------------------------------------------------- */ /* concise but slow version for illustration only */ /* ---------------------------------------------------------------------- */ double Gamma [WDIM] ; double *Lx ; Int *Li, *Lp, *Lnz ; Int p, k ; Int use_dbound = IS_GT_ZERO (Common->dbound) ; Li = L->i ; Lx = L->x ; Lp = L->p ; Lnz = L->nz ; /* walk up the etree from node j to its ancestor e */ for ( ; j <= e ; j = (Lnz [j] > 1) ? (Li [Lp [j] + 1]) : Int_max) { /* update the diagonal entry D (j,j) with each column of W */ ALPHA_GAMMA (Lx [Lp [j]], Alpha, Gamma, (&(w (j,0)))) ; /* update column j of L */ for (p = Lp [j] + 1 ; p < Lp [j] + Lnz [j] ; p++) { /* update row Li [p] of column j of L with each column of W */ Int i = Li [p] ; for (k = 0 ; k < RANK ; k++) { w (i,k) -= w (j,k) * Lx [p] ; Lx [p] -= Gamma [k] * w (i,k) ; } } /* clear workspace W */ for (k = 0 ; k < RANK ; k++) { w (j,k) = 0 ; } } #else /* ---------------------------------------------------------------------- */ /* dynamic supernodal version: supernodes detected dynamically */ /* ---------------------------------------------------------------------- */ double G0 [RANK], G1 [RANK], G2 [RANK], G3 [RANK] ; double Z0 [RANK], Z1 [RANK], Z2 [RANK], Z3 [RANK] ; double *W0, *W1, *W2, *W3, *Lx ; Int *Li, *Lp, *Lnz ; Int j1, j2, j3, p0, p1, p2, p3, parent, lnz, pend, k ; Int use_dbound = IS_GT_ZERO (Common->dbound) ; Li = L->i ; Lx = L->x ; Lp = L->p ; Lnz = L->nz ; /* walk up the etree from node j to its ancestor e */ for ( ; j <= e ; j = parent) { p0 = Lp [j] ; /* col j is Li,Lx [p0 ... p0+lnz-1] */ lnz = Lnz [j] ; W0 = W + WDIM * j ; /* pointer to row j of W */ pend = p0 + lnz ; /* for k = 0 to RANK-1 do: */ #define DO(k) Z0 [k] = W0 [k] ; FOR_ALL_K #undef DO /* for k = 0 to RANK-1 do: */ #define DO(k) W0 [k] = 0 ; FOR_ALL_K #undef DO /* update D (j,j) */ ALPHA_GAMMA (Lx [p0], Alpha, G0, Z0) ; p0++ ; /* determine how many columns of L to update at the same time */ parent = (lnz > 1) ? (Li [p0]) : Int_max ; if (parent <= e && lnz == Lnz [parent] + 1) { /* -------------------------------------------------------------- */ /* node j and its parent j1 can be updated at the same time */ /* -------------------------------------------------------------- */ j1 = parent ; j2 = (lnz > 2) ? (Li [p0+1]) : Int_max ; j3 = (lnz > 3) ? (Li [p0+2]) : Int_max ; W1 = W + WDIM * j1 ; /* pointer to row j1 of W */ p1 = Lp [j1] ; /* for k = 0 to RANK-1 do: */ #define DO(k) Z1 [k] = W1 [k] ; FOR_ALL_K #undef DO /* for k = 0 to RANK-1 do: */ #define DO(k) W1 [k] = 0 ; FOR_ALL_K #undef DO /* update L (j1,j) */ { double lx = Lx [p0] ; /* for k = 0 to RANK-1 do: */ #define DO(k) \ Z1 [k] -= Z0 [k] * lx ; \ lx -= G0 [k] * Z1 [k] ; FOR_ALL_K #undef DO Lx [p0++] = lx ; } /* update D (j1,j1) */ ALPHA_GAMMA (Lx [p1], Alpha, G1, Z1) ; p1++ ; /* -------------------------------------------------------------- */ /* update 2 or 4 columns of L */ /* -------------------------------------------------------------- */ if ((j2 <= e) && /* j2 in the current path */ (j3 <= e) && /* j3 in the current path */ (lnz == Lnz [j2] + 2) && /* column j2 matches */ (lnz == Lnz [j3] + 3)) /* column j3 matches */ { /* ---------------------------------------------------------- */ /* update 4 columns of L */ /* ---------------------------------------------------------- */ /* p0 and p1 currently point to row j2 in cols j and j1 of L */ parent = (lnz > 4) ? (Li [p0+2]) : Int_max ; W2 = W + WDIM * j2 ; /* pointer to row j2 of W */ W3 = W + WDIM * j3 ; /* pointer to row j3 of W */ p2 = Lp [j2] ; p3 = Lp [j3] ; /* for k = 0 to RANK-1 do: */ #define DO(k) Z2 [k] = W2 [k] ; FOR_ALL_K #undef DO /* for k = 0 to RANK-1 do: */ #define DO(k) Z3 [k] = W3 [k] ; FOR_ALL_K #undef DO /* for k = 0 to RANK-1 do: */ #define DO(k) W2 [k] = 0 ; FOR_ALL_K #undef DO /* for k = 0 to RANK-1 do: */ #define DO(k) W3 [k] = 0 ; FOR_ALL_K #undef DO /* update L (j2,j) and update L (j2,j1) */ { double lx [2] ; lx [0] = Lx [p0] ; lx [1] = Lx [p1] ; /* for k = 0 to RANK-1 do: */ #define DO(k) \ Z2 [k] -= Z0 [k] * lx [0] ; lx [0] -= G0 [k] * Z2 [k] ; \ Z2 [k] -= Z1 [k] * lx [1] ; lx [1] -= G1 [k] * Z2 [k] ; FOR_ALL_K #undef DO Lx [p0++] = lx [0] ; Lx [p1++] = lx [1] ; } /* update D (j2,j2) */ ALPHA_GAMMA (Lx [p2], Alpha, G2, Z2) ; p2++ ; /* update L (j3,j), L (j3,j1), and L (j3,j2) */ { double lx [3] ; lx [0] = Lx [p0] ; lx [1] = Lx [p1] ; lx [2] = Lx [p2] ; /* for k = 0 to RANK-1 do: */ #define DO(k) \ Z3 [k] -= Z0 [k] * lx [0] ; lx [0] -= G0 [k] * Z3 [k] ; \ Z3 [k] -= Z1 [k] * lx [1] ; lx [1] -= G1 [k] * Z3 [k] ; \ Z3 [k] -= Z2 [k] * lx [2] ; lx [2] -= G2 [k] * Z3 [k] ; FOR_ALL_K #undef DO Lx [p0++] = lx [0] ; Lx [p1++] = lx [1] ; Lx [p2++] = lx [2] ; } /* update D (j3,j3) */ ALPHA_GAMMA (Lx [p3], Alpha, G3, Z3) ; p3++ ; /* each iteration updates L (i, [j j1 j2 j3]) */ for ( ; p0 < pend ; p0++, p1++, p2++, p3++) { double lx [4], *w0 ; lx [0] = Lx [p0] ; lx [1] = Lx [p1] ; lx [2] = Lx [p2] ; lx [3] = Lx [p3] ; w0 = W + WDIM * Li [p0] ; /* for k = 0 to RANK-1 do: */ #define DO(k) \ w0 [k] -= Z0 [k] * lx [0] ; lx [0] -= G0 [k] * w0 [k] ; \ w0 [k] -= Z1 [k] * lx [1] ; lx [1] -= G1 [k] * w0 [k] ; \ w0 [k] -= Z2 [k] * lx [2] ; lx [2] -= G2 [k] * w0 [k] ; \ w0 [k] -= Z3 [k] * lx [3] ; lx [3] -= G3 [k] * w0 [k] ; FOR_ALL_K #undef DO Lx [p0] = lx [0] ; Lx [p1] = lx [1] ; Lx [p2] = lx [2] ; Lx [p3] = lx [3] ; } } else { /* ---------------------------------------------------------- */ /* update 2 columns of L */ /* ---------------------------------------------------------- */ parent = j2 ; /* cleanup iteration if length is odd */ if ((lnz - 2) % 2) { double lx [2] , *w0 ; lx [0] = Lx [p0] ; lx [1] = Lx [p1] ; w0 = W + WDIM * Li [p0] ; /* for k = 0 to RANK-1 do: */ #define DO(k) \ w0 [k] -= Z0 [k] * lx [0] ; lx [0] -= G0 [k] * w0 [k] ; \ w0 [k] -= Z1 [k] * lx [1] ; lx [1] -= G1 [k] * w0 [k] ; FOR_ALL_K #undef DO Lx [p0++] = lx [0] ; Lx [p1++] = lx [1] ; } for ( ; p0 < pend ; p0 += 2, p1 += 2) { double lx [2][2], w [2], *w0, *w1 ; lx [0][0] = Lx [p0 ] ; lx [1][0] = Lx [p0+1] ; lx [0][1] = Lx [p1 ] ; lx [1][1] = Lx [p1+1] ; w0 = W + WDIM * Li [p0 ] ; w1 = W + WDIM * Li [p0+1] ; /* for k = 0 to RANK-1 do: */ #define DO(k) \ w [0] = w0 [k] - Z0 [k] * lx [0][0] ; \ w [1] = w1 [k] - Z0 [k] * lx [1][0] ; \ lx [0][0] -= G0 [k] * w [0] ; \ lx [1][0] -= G0 [k] * w [1] ; \ w0 [k] = w [0] -= Z1 [k] * lx [0][1] ; \ w1 [k] = w [1] -= Z1 [k] * lx [1][1] ; \ lx [0][1] -= G1 [k] * w [0] ; \ lx [1][1] -= G1 [k] * w [1] ; FOR_ALL_K #undef DO Lx [p0 ] = lx [0][0] ; Lx [p0+1] = lx [1][0] ; Lx [p1 ] = lx [0][1] ; Lx [p1+1] = lx [1][1] ; } } } else { /* -------------------------------------------------------------- */ /* update one column of L */ /* -------------------------------------------------------------- */ /* cleanup iteration if length is not a multiple of 4 */ switch ((lnz - 1) % 4) { case 1: { double lx , *w0 ; lx = Lx [p0] ; w0 = W + WDIM * Li [p0] ; /* for k = 0 to RANK-1 do: */ #define DO(k) \ w0 [k] -= Z0 [k] * lx ; lx -= G0 [k] * w0 [k] ; FOR_ALL_K #undef DO Lx [p0++] = lx ; } break ; case 2: { double lx [2], *w0, *w1 ; lx [0] = Lx [p0 ] ; lx [1] = Lx [p0+1] ; w0 = W + WDIM * Li [p0 ] ; w1 = W + WDIM * Li [p0+1] ; /* for k = 0 to RANK-1 do: */ #define DO(k) \ w0 [k] -= Z0 [k] * lx [0] ; \ w1 [k] -= Z0 [k] * lx [1] ; \ lx [0] -= G0 [k] * w0 [k] ; \ lx [1] -= G0 [k] * w1 [k] ; FOR_ALL_K #undef DO Lx [p0++] = lx [0] ; Lx [p0++] = lx [1] ; } break ; case 3: { double lx [3], *w0, *w1, *w2 ; lx [0] = Lx [p0 ] ; lx [1] = Lx [p0+1] ; lx [2] = Lx [p0+2] ; w0 = W + WDIM * Li [p0 ] ; w1 = W + WDIM * Li [p0+1] ; w2 = W + WDIM * Li [p0+2] ; /* for k = 0 to RANK-1 do: */ #define DO(k) \ w0 [k] -= Z0 [k] * lx [0] ; \ w1 [k] -= Z0 [k] * lx [1] ; \ w2 [k] -= Z0 [k] * lx [2] ; \ lx [0] -= G0 [k] * w0 [k] ; \ lx [1] -= G0 [k] * w1 [k] ; \ lx [2] -= G0 [k] * w2 [k] ; FOR_ALL_K #undef DO Lx [p0++] = lx [0] ; Lx [p0++] = lx [1] ; Lx [p0++] = lx [2] ; } } for ( ; p0 < pend ; p0 += 4) { double lx [4], *w0, *w1, *w2, *w3 ; lx [0] = Lx [p0 ] ; lx [1] = Lx [p0+1] ; lx [2] = Lx [p0+2] ; lx [3] = Lx [p0+3] ; w0 = W + WDIM * Li [p0 ] ; w1 = W + WDIM * Li [p0+1] ; w2 = W + WDIM * Li [p0+2] ; w3 = W + WDIM * Li [p0+3] ; /* for k = 0 to RANK-1 do: */ #define DO(k) \ w0 [k] -= Z0 [k] * lx [0] ; \ w1 [k] -= Z0 [k] * lx [1] ; \ w2 [k] -= Z0 [k] * lx [2] ; \ w3 [k] -= Z0 [k] * lx [3] ; \ lx [0] -= G0 [k] * w0 [k] ; \ lx [1] -= G0 [k] * w1 [k] ; \ lx [2] -= G0 [k] * w2 [k] ; \ lx [3] -= G0 [k] * w3 [k] ; FOR_ALL_K #undef DO Lx [p0 ] = lx [0] ; Lx [p0+1] = lx [1] ; Lx [p0+2] = lx [2] ; Lx [p0+3] = lx [3] ; } } } #endif } /* prepare this file for another inclusion in t_cholmod_updown.c: */ #undef RANK python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Modify/cholmod_rowdel.c0000644000076500000240000003173013524616144027071 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Modify/cholmod_rowdel ================================================ */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Modify Module. * Copyright (C) 2005-2006, Timothy A. Davis and William W. Hager. * The CHOLMOD/Modify Module is licensed under Version 2.0 of the GNU * General Public License. See gpl.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * http://www.suitesparse.com * -------------------------------------------------------------------------- */ /* Deletes a row and column from an LDL' factorization. The row and column k * is set to the kth row and column of the identity matrix. Optionally * downdates the solution to Lx=b. * * workspace: Flag (nrow), Head (nrow+1), W (nrow*2), Iwork (2*nrow) * * Only real matrices are supported (exception: since only the pattern of R * is used, it can have any valid xtype). */ #ifndef NMODIFY #include "cholmod_internal.h" #include "cholmod_modify.h" /* ========================================================================== */ /* === cholmod_rowdel ======================================================= */ /* ========================================================================== */ /* Sets the kth row and column of L to be the kth row and column of the identity * matrix, and updates L(k+1:n,k+1:n) accordingly. To reduce the running time, * the caller can optionally provide the nonzero pattern (or an upper bound) of * kth row of L, as the sparse n-by-1 vector R. Provide R as NULL if you want * CHOLMOD to determine this itself, which is easier for the caller, but takes * a little more time. */ int CHOLMOD(rowdel) ( /* ---- input ---- */ size_t k, /* row/column index to delete */ cholmod_sparse *R, /* NULL, or the nonzero pattern of kth row of L */ /* ---- in/out --- */ cholmod_factor *L, /* factor to modify */ /* --------------- */ cholmod_common *Common ) { double yk [2] ; yk [0] = 0. ; yk [1] = 0. ; return (CHOLMOD(rowdel_mark) (k, R, yk, NULL, L, NULL, NULL, Common)) ; } /* ========================================================================== */ /* === cholmod_rowdel_solve ================================================= */ /* ========================================================================== */ /* Does the same as cholmod_rowdel, but also downdates the solution to Lx=b. * When row/column k of A is "deleted" from the system A*y=b, this can induce * a change to x, in addition to changes arising when L and b are modified. * If this is the case, the kth entry of y is required as input (yk) */ int CHOLMOD(rowdel_solve) ( /* ---- input ---- */ size_t k, /* row/column index to delete */ cholmod_sparse *R, /* NULL, or the nonzero pattern of kth row of L */ double yk [2], /* kth entry in the solution to A*y=b */ /* ---- in/out --- */ cholmod_factor *L, /* factor to modify */ cholmod_dense *X, /* solution to Lx=b (size n-by-1) */ cholmod_dense *DeltaB, /* change in b, zero on output */ /* --------------- */ cholmod_common *Common ) { return (CHOLMOD(rowdel_mark) (k, R, yk, NULL, L, X, DeltaB, Common)) ; } /* ========================================================================== */ /* === cholmod_rowdel_mark ================================================== */ /* ========================================================================== */ /* Does the same as cholmod_rowdel_solve, except only part of L is used in * the update/downdate of the solution to Lx=b. This routine is an "expert" * routine. It is meant for use in LPDASA only. * * if R == NULL then columns 0:k-1 of L are searched for row k. Otherwise, it * searches columns in the set defined by the pattern of the first column of R. * This is meant to be the pattern of row k of L (a superset of that pattern is * OK too). R must be a permutation of a subset of 0:k-1. */ int CHOLMOD(rowdel_mark) ( /* ---- input ---- */ size_t kdel, /* row/column index to delete */ cholmod_sparse *R, /* NULL, or the nonzero pattern of kth row of L */ double yk [2], /* kth entry in the solution to A*y=b */ Int *colmark, /* Int array of size 1. See cholmod_updown.c */ /* ---- in/out --- */ cholmod_factor *L, /* factor to modify */ cholmod_dense *X, /* solution to Lx=b (size n-by-1) */ cholmod_dense *DeltaB, /* change in b, zero on output */ /* --------------- */ cholmod_common *Common ) { double dk, sqrt_dk, xk, dj, fl ; double *Lx, *Cx, *W, *Xx, *Nx ; Int *Li, *Lp, *Lnz, *Ci, *Rj, *Rp, *Iwork ; cholmod_sparse *C, Cmatrix ; Int j, p, pend, kk, lnz, n, Cp [2], do_solve, do_update, left, k, right, middle, i, klast, given_row, rnz ; size_t s ; int ok = TRUE ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (L, FALSE) ; RETURN_IF_XTYPE_INVALID (L, CHOLMOD_PATTERN, CHOLMOD_REAL, FALSE) ; n = L->n ; k = kdel ; if (kdel >= L->n || k < 0) { ERROR (CHOLMOD_INVALID, "k invalid") ; return (FALSE) ; } if (R == NULL) { Rj = NULL ; rnz = EMPTY ; } else { RETURN_IF_XTYPE_INVALID (R, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; if (R->ncol != 1 || R->nrow != L->n) { ERROR (CHOLMOD_INVALID, "R invalid") ; return (FALSE) ; } Rj = R->i ; Rp = R->p ; rnz = Rp [1] ; } do_solve = (X != NULL) && (DeltaB != NULL) ; if (do_solve) { RETURN_IF_XTYPE_INVALID (X, CHOLMOD_REAL, CHOLMOD_REAL, FALSE) ; RETURN_IF_XTYPE_INVALID (DeltaB, CHOLMOD_REAL, CHOLMOD_REAL, FALSE) ; Xx = X->x ; Nx = DeltaB->x ; if (X->nrow != L->n || X->ncol != 1 || DeltaB->nrow != L->n || DeltaB->ncol != 1 || Xx == NULL || Nx == NULL) { ERROR (CHOLMOD_INVALID, "X and/or DeltaB invalid") ; return (FALSE) ; } } else { Xx = NULL ; Nx = NULL ; } Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ /* s = 2*n */ s = CHOLMOD(mult_size_t) (n, 2, &ok) ; if (!ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return (FALSE) ; } CHOLMOD(allocate_work) (n, s, s, Common) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; } ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 2*n, Common)) ; /* ---------------------------------------------------------------------- */ /* convert to simplicial numeric LDL' factor, if not already */ /* ---------------------------------------------------------------------- */ if (L->xtype == CHOLMOD_PATTERN || L->is_super || L->is_ll) { /* can only update/downdate a simplicial LDL' factorization */ CHOLMOD(change_factor) (CHOLMOD_REAL, FALSE, FALSE, FALSE, FALSE, L, Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory, L is returned unchanged */ return (FALSE) ; } } /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ /* inputs, not modified on output: */ Lp = L->p ; /* size n+1 */ /* outputs, contents defined on input for incremental case only: */ Lnz = L->nz ; /* size n */ Li = L->i ; /* size L->nzmax. Can change in size. */ Lx = L->x ; /* size L->nzmax. Can change in size. */ ASSERT (L->nz != NULL) ; /* ---------------------------------------------------------------------- */ /* get workspace */ /* ---------------------------------------------------------------------- */ W = Common->Xwork ; /* size n, used only in cholmod_updown */ Cx = W + n ; /* use 2nd column of Xwork for C (size n) */ Iwork = Common->Iwork ; Ci = Iwork + n ; /* size n (i/i/l) */ /* NOTE: cholmod_updown uses Iwork [0..n-1] (i/i/l) as Stack */ /* ---------------------------------------------------------------------- */ /* prune row k from all columns of L */ /* ---------------------------------------------------------------------- */ given_row = (rnz >= 0) ; klast = given_row ? rnz : k ; PRINT2 (("given_row "ID"\n", given_row)) ; for (kk = 0 ; kk < klast ; kk++) { /* either search j = 0:k-1 or j = Rj [0:rnz-1] */ j = given_row ? (Rj [kk]) : (kk) ; if (j < 0 || j >= k) { ERROR (CHOLMOD_INVALID, "R invalid") ; return (FALSE) ; } PRINT2 (("Prune col j = "ID":\n", j)) ; lnz = Lnz [j] ; dj = Lx [Lp [j]] ; ASSERT (Lnz [j] > 0 && Li [Lp [j]] == j) ; if (lnz > 1) { left = Lp [j] ; pend = left + lnz ; right = pend - 1 ; i = Li [right] ; if (i < k) { /* row k is not in column j */ continue ; } else if (i == k) { /* k is the last row index in this column (quick delete) */ if (do_solve) { Xx [j] -= yk [0] * dj * Lx [right] ; } Lx [right] = 0 ; } else { /* binary search for row k in column j */ PRINT2 (("\nBinary search: lnz "ID" k = "ID"\n", lnz, k)) ; while (left < right) { middle = (left + right) / 2 ; PRINT2 (("left "ID" right "ID" middle "ID": ["ID" "ID"" ""ID"]\n", left, right, middle, Li [left], Li [middle], Li [right])) ; if (k > Li [middle]) { left = middle + 1 ; } else { right = middle ; } } ASSERT (left >= Lp [j] && left < pend) ; #ifndef NDEBUG /* brute force, linear-time search */ { Int p3 = Lp [j] ; i = EMPTY ; PRINT2 (("Brute force:\n")) ; for ( ; p3 < pend ; p3++) { i = Li [p3] ; PRINT2 (("p "ID" ["ID"]\n", p3, i)) ; if (i >= k) { break ; } } if (i == k) { ASSERT (k == Li [p3]) ; ASSERT (p3 == left) ; } } #endif if (k == Li [left]) { if (do_solve) { Xx [j] -= yk [0] * dj * Lx [left] ; } /* found row k in column j. Prune it from the column.*/ Lx [left] = 0 ; } } } } #ifndef NDEBUG /* ensure that row k has been deleted from the matrix L */ for (j = 0 ; j < k ; j++) { Int lasti ; lasti = EMPTY ; p = Lp [j] ; pend = p + Lnz [j] ; /* look for row k in column j */ PRINT1 (("Pruned column "ID"\n", j)) ; for ( ; p < pend ; p++) { i = Li [p] ; PRINT2 ((" "ID"", i)) ; PRINT2 ((" %g\n", Lx [p])) ; ASSERT (IMPLIES (i == k, Lx [p] == 0)) ; ASSERT (i > lasti) ; lasti = i ; } PRINT1 (("\n")) ; } #endif /* ---------------------------------------------------------------------- */ /* set diagonal and clear column k of L */ /* ---------------------------------------------------------------------- */ lnz = Lnz [k] - 1 ; ASSERT (Lnz [k] > 0) ; /* ---------------------------------------------------------------------- */ /* update/downdate */ /* ---------------------------------------------------------------------- */ /* update or downdate L (k+1:n, k+1:n) with the vector * C = L (:,k) * sqrt (abs (D [k])) * Do a numeric update if D[k] > 0, numeric downdate otherwise. */ PRINT1 (("rowdel downdate lnz = "ID"\n", lnz)) ; /* store the new unit diagonal */ p = Lp [k] ; pend = p + lnz + 1 ; dk = Lx [p] ; Lx [p++] = 1 ; PRINT2 (("D [k = "ID"] = %g\n", k, dk)) ; ok = TRUE ; fl = 0 ; if (lnz > 0) { /* compute DeltaB for updown (in DeltaB) */ if (do_solve) { xk = Xx [k] - yk [0] * dk ; for ( ; p < pend ; p++) { Nx [Li [p]] += Lx [p] * xk ; } } do_update = IS_GT_ZERO (dk) ; if (!do_update) { dk = -dk ; } sqrt_dk = sqrt (dk) ; p = Lp [k] + 1 ; for (kk = 0 ; kk < lnz ; kk++, p++) { Ci [kk] = Li [p] ; Cx [kk] = Lx [p] * sqrt_dk ; Lx [p] = 0 ; /* clear column k */ } fl = lnz + 1 ; /* create a n-by-1 sparse matrix to hold the single column */ C = &Cmatrix ; C->nrow = n ; C->ncol = 1 ; C->nzmax = lnz ; C->sorted = TRUE ; C->packed = TRUE ; C->p = Cp ; C->i = Ci ; C->x = Cx ; C->nz = NULL ; C->itype = L->itype ; C->xtype = L->xtype ; C->dtype = L->dtype ; C->z = NULL ; C->stype = 0 ; Cp [0] = 0 ; Cp [1] = lnz ; /* numeric update if dk > 0, and with Lx=b change */ /* workspace: Flag (nrow), Head (nrow+1), W (nrow), Iwork (2*nrow) */ ok = CHOLMOD(updown_mark) (do_update ? (1) : (0), C, colmark, L, X, DeltaB, Common) ; /* clear workspace */ for (kk = 0 ; kk < lnz ; kk++) { Cx [kk] = 0 ; } } Common->modfl += fl ; if (do_solve) { /* kth equation becomes identity, so X(k) is now Y(k) */ Xx [k] = yk [0] ; } DEBUG (CHOLMOD(dump_factor) (L, "LDL factorization, L:", Common)) ; ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 2*n, Common)) ; return (ok) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Modify/gpl.txt0000644000076500000240000004313313524616144025247 0ustar tamasstaff00000000000000 GNU GENERAL PUBLIC LICENSE Version 2, June 1991 Copyright (C) 1989, 1991 Free Software Foundation, Inc. 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed. Preamble The licenses for most software are designed to take away your freedom to share and change it. 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If the program is interactive, make it output a short notice like this when it starts in an interactive mode: Gnomovision version 69, Copyright (C) year name of author Gnomovision comes with ABSOLUTELY NO WARRANTY; for details type `show w'. This is free software, and you are welcome to redistribute it under certain conditions; type `show c' for details. The hypothetical commands `show w' and `show c' should show the appropriate parts of the General Public License. Of course, the commands you use may be called something other than `show w' and `show c'; they could even be mouse-clicks or menu items--whatever suits your program. You should also get your employer (if you work as a programmer) or your school, if any, to sign a "copyright disclaimer" for the program, if necessary. Here is a sample; alter the names: Yoyodyne, Inc., hereby disclaims all copyright interest in the program `Gnomovision' (which makes passes at compilers) written by James Hacker. , 1 April 1989 Ty Coon, President of Vice This General Public License does not permit incorporating your program into proprietary programs. If your program is a subroutine library, you may consider it more useful to permit linking proprietary applications with the library. If this is what you want to do, use the GNU Library General Public License instead of this License. python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Modify/cholmod_updown.c0000644000076500000240000014336113524616144027115 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Modify/cholmod_updown ================================================ */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Modify Module. * Copyright (C) 2005-2006, Timothy A. Davis and William W. Hager. * The CHOLMOD/Modify Module is licensed under Version 2.0 of the GNU * General Public License. See gpl.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * http://www.suitesparse.com * -------------------------------------------------------------------------- */ /* Updates/downdates the LDL' factorization (symbolic, then numeric), by * computing a new factorization of * * Lnew * Dnew * Lnew' = Lold * Dold * Lold' +/- C*C' * * C must be sorted. It can be either packed or unpacked. As in all CHOLMOD * routines, the columns of L are sorted on input, and also on output. * * If the factor is not an unpacked LDL' or dynamic LDL', it is converted * to an LDL' dynamic factor. An unpacked LDL' factor may be updated, but if * any one column runs out of space, the factor is converted to an LDL' * dynamic one. If the initial conversion fails, the factor is returned * unchanged. * * If memory runs out during the update, the factor is returned as a simplicial * symbolic factor. That is, everything is freed except for the fill-reducing * ordering and its corresponding column counts (typically computed by * cholmod_analyze). * * Note that the fill-reducing permutation L->Perm is NOT used. The row * indices of C refer to the rows of L, not A. If your original system is * LDL' = PAP' (where P = L->Perm), and you want to compute the LDL' * factorization of A+CC', then you must permute C first. That is: * * PAP' = LDL' * P(A+CC')P' = PAP'+PCC'P' = LDL' + (PC)(PC)' = LDL' + Cnew*Cnew' * where Cnew = P*C. * * You can use the cholmod_submatrix routine in the MatrixOps module * to permute C, with: * * Cnew = cholmod_submatrix (C, L->Perm, L->n, NULL, -1, TRUE, TRUE, Common) ; * * Note that the sorted input parameter to cholmod_submatrix must be TRUE, * because cholmod_updown requires C with sorted columns. * * The system Lx=b can also be updated/downdated. The old system was Lold*x=b. * The new system is Lnew*xnew = b + deltab. The old solution x is overwritten * with xnew. Note that as in the update/downdate of L itself, the fill- * reducing permutation L->Perm is not used. x and b are in the permuted * ordering, not your original ordering. x and b are n-by-1; this routine * does not handle multiple right-hand-sides. * * workspace: Flag (nrow), Head (nrow+1), W (maxrank*nrow), Iwork (nrow), * where maxrank is 2, 4, or 8. * * Only real matrices are supported. A symbolic L is converted into a * numeric identity matrix. */ #ifndef NMODIFY #include "cholmod_internal.h" #include "cholmod_modify.h" /* ========================================================================== */ /* === cholmod_updown ======================================================= */ /* ========================================================================== */ /* Compute the new LDL' factorization of LDL'+CC' (an update) or LDL'-CC' * (a downdate). The factor object L need not be an LDL' factorization; it * is converted to one if it isn't. */ int CHOLMOD(updown) ( /* ---- input ---- */ int update, /* TRUE for update, FALSE for downdate */ cholmod_sparse *C, /* the incoming sparse update */ /* ---- in/out --- */ cholmod_factor *L, /* factor to modify */ /* --------------- */ cholmod_common *Common ) { return (CHOLMOD(updown_mask) (update, C, NULL, NULL, L, NULL, NULL, Common)) ; } /* ========================================================================== */ /* === cholmod_updown_solve ================================================= */ /* ========================================================================== */ /* Does the same as cholmod_updown, except that it also updates/downdates the * solution to Lx=b+DeltaB. x and b must be n-by-1 dense matrices. b is not * need as input to this routine, but a sparse change to b is (DeltaB). Only * entries in DeltaB corresponding to columns modified in L are accessed; the * rest are ignored. */ int CHOLMOD(updown_solve) ( /* ---- input ---- */ int update, /* TRUE for update, FALSE for downdate */ cholmod_sparse *C, /* the incoming sparse update */ /* ---- in/out --- */ cholmod_factor *L, /* factor to modify */ cholmod_dense *X, /* solution to Lx=b (size n-by-1) */ cholmod_dense *DeltaB, /* change in b, zero on output */ /* --------------- */ cholmod_common *Common ) { return (CHOLMOD(updown_mask) (update, C, NULL, NULL, L, X, DeltaB, Common)) ; } /* ========================================================================== */ /* === Power2 =============================================================== */ /* ========================================================================== */ /* Power2 [i] is smallest power of 2 that is >= i (for i in range 0 to 8) */ static Int Power2 [ ] = { /* 0 1 2 3 4 5 6 7 8 */ 0, 1, 2, 4, 4, 8, 8, 8, 8 } ; /* ========================================================================== */ /* === debug routines ======================================================= */ /* ========================================================================== */ #ifndef NDEBUG static void dump_set (Int s, Int **Set_ps1, Int **Set_ps2, Int j, Int n, cholmod_common *Common) { Int *p, len, i, ilast ; if (CHOLMOD(dump) < -1) { /* no checks if debug level is -2 or less */ return ; } len = Set_ps2 [s] - Set_ps1 [s] ; PRINT2 (("Set s: "ID" len: "ID":", s, len)) ; ASSERT (len > 0) ; ilast = j ; for (p = Set_ps1 [s] ; p < Set_ps2 [s] ; p++) { i = *p ; PRINT3 ((" "ID"", i)) ; ASSERT (i > ilast && i < n) ; ilast = i ; } PRINT3 (("\n")) ; } static void dump_col ( char *w, Int j, Int p1, Int p2, Int *Li, double *Lx, Int n, cholmod_common *Common ) { Int p, row, lastrow ; if (CHOLMOD(dump) < -1) { /* no checks if debug level is -2 or less */ return ; } PRINT3 (("\n\nDUMP COL==== j = "ID" %s: p1="ID" p2="ID" \n", j, w, p1,p2)); lastrow = -1 ; for (p = p1 ; p < p2 ; p++) { PRINT3 ((" "ID": ", p)) ; row = Li [p] ; PRINT3 ((""ID" ", Li [p])) ; PRINT3 (("%g ", Lx [p])) ; PRINT3 (("\n")) ; ASSERT (row > lastrow && row < n) ; lastrow = row ; } ASSERT (p1 < p2) ; ASSERT (Li [p1] == j) ; PRINT3 (("\n")) ; } #endif /* ========================================================================== */ /* === a path =============================================================== */ /* ========================================================================== */ /* A path is a set of nodes of the etree which are all affected by the same * columns of C. */ typedef struct Path_struct { Int start ; /* column at which to start, or EMPTY if initial */ Int end ; /* column at which to end, or EMPTY if initial */ Int ccol ; /* column of C to which path refers */ Int parent ; /* parent path */ Int c ; /* child of j along this path */ Int next ; /* next path in link list */ Int rank ; /* number of rank-1 paths merged onto this path */ Int order ; /* dfs order of this path */ Int wfirst ; /* first column of W to affect this path */ Int pending ; /* column at which the path is pending */ Int botrow ; /* for partial update/downdate of solution to Lx=b */ } Path_type ; /* ========================================================================== */ /* === dfs ================================================================== */ /* ========================================================================== */ /* Compute the DFS order of the set of paths. This can be recursive because * there are at most 23 paths to sort: one for each column of C (8 at most), * and one for each node in a balanced binary tree with 8 leaves (15). * Stack overflow is thus not a problem. */ static void dfs ( Path_type *Path, /* the set of Paths */ Int k, /* the rank of the update/downdate */ Int path, /* which path to work on */ Int *path_order, /* the current path order */ Int *w_order, /* the current order of the columns of W */ Int depth, Int npaths /* total number of paths */ ) { Int c ; /* child path */ ASSERT (path >= 0 && path < npaths) ; if (path < k) { /* this is a leaf node, corresponding to column W (:,path) */ /* and column C (:, Path [path].ccol) */ ASSERT (Path [path].ccol >= 0) ; Path [path].wfirst = *w_order ; Path [path].order = *w_order ; (*w_order)++ ; } else { /* this is a non-leaf path, within the tree */ ASSERT (Path [path].c != EMPTY) ; ASSERT (Path [path].ccol == EMPTY) ; /* order each child path */ for (c = Path [path].c ; c != EMPTY ; c = Path [c].next) { dfs (Path, k, c, path_order, w_order, depth+1, npaths) ; if (Path [path].wfirst == EMPTY) { Path [path].wfirst = Path [c].wfirst ; } } /* order this path next */ Path [path].order = (*path_order)++ ; } } /* ========================================================================== */ /* === numeric update/downdate routines ===================================== */ /* ========================================================================== */ #define WDIM 1 #include "t_cholmod_updown.c" #define WDIM 2 #include "t_cholmod_updown.c" #define WDIM 4 #include "t_cholmod_updown.c" #define WDIM 8 #include "t_cholmod_updown.c" /* ========================================================================== */ /* === cholmod_updown_mark ================================================== */ /* ========================================================================== */ /* Update/downdate LDL' +/- C*C', and update/downdate selected portions of the * solution to Lx=b. * * The original system is L*x = b. The new system is Lnew*xnew = b + deltab. * deltab(i) can be nonzero only if column i of L is modified by the update/ * downdate. If column i is not modified, the deltab(i) is not accessed. * * The solution to Lx=b is not modified if either X or DeltaB are NULL. * * Rowmark and colmark: * -------------------- * * rowmark and colmark affect which portions of L take part in the update/ * downdate of the solution to Lx=b. They do not affect how L itself is * updated/downdated. They are both ignored if X or DeltaB are NULL. * * If not NULL, rowmark is an integer array of size n where L is n-by-n. * rowmark [j] defines the part of column j of L that takes part in the update/ * downdate of the forward solve, Lx=b. Specifically, if i = rowmark [j], * then L(j:i-1,j) is used, and L(i:end,j) is ignored. * * If not NULL, colmark is an integer array of size C->ncol. colmark [ccol] * for a column C(:,ccol) redefines those parts of L that take part in the * update/downdate of Lx=b. Each column of C affects a set of columns of L. * If column ccol of C affects column j of L, then the new rowmark [j] of * column j of L is defined as colmark [ccol]. In a multiple-rank update/ * downdate, if two or more columns of C affect column j, its new rowmark [j] * is the colmark of the least-numbered column of C. colmark is ignored if * it is NULL, in which case rowmark is not modified. If colmark [ccol] is * EMPTY (-1), then rowmark is not modified for that particular column of C. * colmark is ignored if it is NULL, or rowmark, X, or DeltaB are NULL. * * The algorithm for modifying the solution to Lx=b when rowmark and colmark * are NULL is as follows: * * for each column j of L that is modified: * deltab (j:end) += L (j:end,j) * x(j) * modify L * for each column j of L that is modified: * x (j) = deltab (j) * deltab (j) = 0 * deltab (j+1:end) -= L (j+1:end,j) * x(j) * * If rowmark is non-NULL but colmark is NULL: * * for each column j of L that is modified: * deltab (j:rowmark(j)-1) += L (j:rowmark(j)-1,j) * x(j) * modify L * for each column j of L that is modified: * x (j) = deltab (j) * deltab (j) = 0 * deltab (j+1:rowmark(j)-1) -= L (j+1:rowmark(j)-1,j) * x(j) * * If both rowmark and colmark are non-NULL: * * for each column j of L that is modified: * deltab (j:rowmark(j)-1) += L (j:rowmark(j)-1,j) * x(j) * modify L * for each column j of L that is modified: * modify rowmark (j) according to colmark * for each column j of L that is modified: * x (j) = deltab (j) * deltab (j) = 0 * deltab (j+1:rowmark(j)-1) -= L (j+1:rowmark(j)-1,j) * x(j) * * Note that if the rank of C exceeds k = Common->maxrank (which is 2, 4, or 8), * then the update/downdate is done as a series of rank-k updates. In this * case, the above algorithm is repeated for each block of k columns of C. * * Unless it leads to no changes in rowmark, colmark should be used only if * C->ncol <= Common->maxrank, because the update/downdate is done with maxrank * columns at a time. Otherwise, the results are undefined. * * This routine is an "expert" routine. It is meant for use in LPDASA only. */ int CHOLMOD(updown_mark) ( /* ---- input ---- */ int update, /* TRUE for update, FALSE for downdate */ cholmod_sparse *C, /* the incoming sparse update */ Int *colmark, /* Int array of size n. */ /* ---- in/out --- */ cholmod_factor *L, /* factor to modify */ cholmod_dense *X, /* solution to Lx=b (size n-by-1) */ cholmod_dense *DeltaB, /* change in b, zero on output */ /* --------------- */ cholmod_common *Common ) { return (CHOLMOD(updown_mask) (update, C, colmark, NULL, L, X, DeltaB, Common)) ; } /* ========================================================================== */ /* === cholmod_updown_mask ================================================== */ /* ========================================================================== */ int CHOLMOD(updown_mask) ( /* ---- input ---- */ int update, /* TRUE for update, FALSE for downdate */ cholmod_sparse *C, /* the incoming sparse update */ Int *colmark, /* Int array of size n. See cholmod_updown.c */ Int *mask, /* size n */ /* ---- in/out --- */ cholmod_factor *L, /* factor to modify */ cholmod_dense *X, /* solution to Lx=b (size n-by-1) */ cholmod_dense *DeltaB, /* change in b, zero on output */ /* --------------- */ cholmod_common *Common ) { double xj, fl ; double *Lx, *W, *Xx, *Nx ; Int *Li, *Lp, *Lnz, *Cp, *Ci, *Cnz, *Head, *Flag, *Stack, *Lnext, *Iwork, *Set_ps1 [32], *Set_ps2 [32], *ps1, *ps2 ; size_t maxrank ; Path_type OrderedPath [32], Path [32] ; Int n, wdim, k1, k2, npaths, i, j, row, packed, ccol, p, cncol, do_solve, mark, jj, j2, kk, nextj, p1, p2, c, use_colmark, newlnz, k, newpath, path_order, w_order, scattered, path, newparent, pp1, pp2, smax, maxrow, row1, nsets, s, p3, newlnz1, Set [32], top, len, lnz, m, botrow ; size_t w ; int ok = TRUE ; DEBUG (Int oldparent) ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (C, FALSE) ; RETURN_IF_NULL (L, FALSE) ; RETURN_IF_XTYPE_INVALID (L, CHOLMOD_PATTERN, CHOLMOD_REAL, FALSE) ; RETURN_IF_XTYPE_INVALID (C, CHOLMOD_REAL, CHOLMOD_REAL, FALSE) ; n = L->n ; cncol = C->ncol ; if (!(C->sorted)) { ERROR (CHOLMOD_INVALID, "C must have sorted columns") ; return (FALSE) ; } if (n != (Int) (C->nrow)) { ERROR (CHOLMOD_INVALID, "C and L dimensions do not match") ; return (FALSE) ; } do_solve = (X != NULL) && (DeltaB != NULL) ; if (do_solve) { RETURN_IF_XTYPE_INVALID (X, CHOLMOD_REAL, CHOLMOD_REAL, FALSE) ; RETURN_IF_XTYPE_INVALID (DeltaB, CHOLMOD_REAL, CHOLMOD_REAL, FALSE) ; Xx = X->x ; Nx = DeltaB->x ; if (X->nrow != L->n || X->ncol != 1 || DeltaB->nrow != L->n || DeltaB->ncol != 1 || Xx == NULL || Nx == NULL) { ERROR (CHOLMOD_INVALID, "X and/or DeltaB invalid") ; return (FALSE) ; } } else { Xx = NULL ; Nx = NULL ; } Common->status = CHOLMOD_OK ; Common->modfl = 0 ; fl = 0 ; use_colmark = (colmark != NULL) ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ /* Note: cholmod_rowadd and cholmod_rowdel use the second n doubles in * Common->Xwork for Cx, and then perform a rank-1 update here, which uses * the first n doubles in Common->Xwork. Both the rowadd and rowdel * routines allocate enough workspace so that Common->Xwork isn't destroyed * below. Also, both cholmod_rowadd and cholmod_rowdel use the second n * ints in Common->Iwork for Ci. */ /* make sure maxrank is in the proper range */ maxrank = CHOLMOD(maxrank) (n, Common) ; k = MIN (cncol, (Int) maxrank) ; /* maximum k is wdim */ wdim = Power2 [k] ; /* number of columns needed in W */ ASSERT (wdim <= (Int) maxrank) ; PRINT1 (("updown wdim final "ID" k "ID"\n", wdim, k)) ; /* w = wdim * n */ w = CHOLMOD(mult_size_t) (n, wdim, &ok) ; if (!ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return (FALSE) ; } CHOLMOD(allocate_work) (n, n, w, Common) ; if (Common->status < CHOLMOD_OK || maxrank == 0) { /* out of memory, L is returned unchanged */ return (FALSE) ; } /* ---------------------------------------------------------------------- */ /* convert to simplicial numeric LDL' factor, if not already */ /* ---------------------------------------------------------------------- */ if (L->xtype == CHOLMOD_PATTERN || L->is_super || L->is_ll) { /* can only update/downdate a simplicial LDL' factorization */ CHOLMOD(change_factor) (CHOLMOD_REAL, FALSE, FALSE, FALSE, FALSE, L, Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory, L is returned unchanged */ return (FALSE) ; } } /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ /* mark = CHOLMOD(clear_flag) (Common) ; */ CHOLMOD_CLEAR_FLAG (Common) ; mark = Common->mark ; PRINT1 (("updown, rank %g update %d\n", (double) C->ncol, update)) ; DEBUG (CHOLMOD(dump_factor) (L, "input L for updown", Common)) ; ASSERT (CHOLMOD(dump_sparse) (C, "input C for updown", Common) >= 0) ; Ci = C->i ; Cp = C->p ; Cnz = C->nz ; packed = C->packed ; ASSERT (IMPLIES (!packed, Cnz != NULL)) ; /* ---------------------------------------------------------------------- */ /* quick return */ /* ---------------------------------------------------------------------- */ if (cncol <= 0 || n == 0) { /* nothing to do */ return (TRUE) ; } /* ---------------------------------------------------------------------- */ /* get L */ /* ---------------------------------------------------------------------- */ Li = L->i ; Lx = L->x ; Lp = L->p ; Lnz = L->nz ; Lnext = L->next ; ASSERT (Lnz != NULL) ; /* ---------------------------------------------------------------------- */ /* get workspace */ /* ---------------------------------------------------------------------- */ Flag = Common->Flag ; /* size n, Flag [i] <= mark must hold */ Head = Common->Head ; /* size n, Head [i] == EMPTY must hold */ W = Common->Xwork ; /* size n-by-wdim, zero on input and output*/ /* note that Iwork [n .. 2*n-1] (i/i/l) may be in use in rowadd/rowdel: */ Iwork = Common->Iwork ; Stack = Iwork ; /* size n, uninitialized (i/i/l) */ /* ---------------------------------------------------------------------- */ /* entire rank-cncol update, done as a sequence of rank-k updates */ /* ---------------------------------------------------------------------- */ ps1 = NULL ; ps2 = NULL ; for (k1 = 0 ; k1 < cncol ; k1 += k) { /* ------------------------------------------------------------------ */ /* get the next k columns of C for the update/downdate */ /* ------------------------------------------------------------------ */ /* the last update/downdate might be less than rank-k */ if (k > cncol - k1) { k = cncol - k1 ; wdim = Power2 [k] ; } k2 = k1 + k - 1 ; /* workspaces are in the following state, on input and output */ ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, wdim, Common)) ; /* ------------------------------------------------------------------ */ /* create a zero-length path for each column of W */ /* ------------------------------------------------------------------ */ nextj = n ; path = 0 ; for (ccol = k1 ; ccol <= k2 ; ccol++) { PRINT1 (("Column ["ID"]: "ID"\n", path, ccol)) ; ASSERT (ccol >= 0 && ccol <= cncol) ; pp1 = Cp [ccol] ; pp2 = (packed) ? (Cp [ccol+1]) : (pp1 + Cnz [ccol]) ; /* get the row index j of the first entry in C (:,ccol) */ if (pp2 > pp1) { /* Column ccol of C has at least one entry. */ j = Ci [pp1] ; } else { /* Column ccol of C is empty. Pretend it has one entry in * the last column with numerical value of zero. */ j = n-1 ; } ASSERT (j >= 0 && j < n) ; /* find first column to work on */ nextj = MIN (nextj, j) ; Path [path].ccol = ccol ; /* which column of C this path is for */ Path [path].start = EMPTY ; /* paths for C have zero length */ Path [path].end = EMPTY ; Path [path].parent = EMPTY ; /* no parent yet */ Path [path].rank = 1 ; /* one column of W */ Path [path].c = EMPTY ; /* no child of this path (case A) */ Path [path].next = Head [j] ; /* this path is pending at col j */ Path [path].pending = j ; /* this path is pending at col j */ Head [j] = path ; /* this path is pending at col j */ PRINT1(("Path "ID" starts: start "ID" end "ID" parent "ID" c "ID"" "j "ID" ccol "ID"\n", path, Path [path].start, Path [path].end, Path [path].parent, Path [path].c, j, ccol)) ; /* initialize botrow for this path */ Path [path].botrow = (use_colmark) ? colmark [ccol] : n ; path++ ; } /* we start with paths 0 to k-1. Next one (now unused) is npaths */ npaths = k ; j = nextj ; ASSERT (j < n) ; scattered = FALSE ; /* ------------------------------------------------------------------ */ /* symbolic update of columns of L */ /* ------------------------------------------------------------------ */ while (j < n) { ASSERT (j >= 0 && j < n && Lnz [j] > 0) ; /* the old column, Li [p1..p2-1]. D (j,j) is stored in Lx [p1] */ p1 = Lp [j] ; newlnz = Lnz [j] ; p2 = p1 + newlnz ; #ifndef NDEBUG PRINT1 (("\n=========Column j="ID" p1 "ID" p2 "ID" lnz "ID" \n", j, p1, p2, newlnz)) ; dump_col ("Old", j, p1, p2, Li, Lx, n, Common) ; oldparent = (Lnz [j] > 1) ? (Li [p1 + 1]) : EMPTY ; ASSERT (CHOLMOD(dump_work) (TRUE, FALSE, 0, Common)) ; ASSERT (!scattered) ; PRINT1 (("Col "ID": Checking paths, npaths: "ID"\n", j, npaths)) ; for (kk = 0 ; kk < npaths ; kk++) { Int kk2, found, j3 = Path [kk].pending ; PRINT2 (("Path "ID" pending at "ID".\n", kk, j3)) ; if (j3 != EMPTY) { /* Path kk must be somewhere in link list for column j3 */ ASSERT (Head [j3] != EMPTY) ; PRINT3 ((" List at "ID": ", j3)) ; found = FALSE ; for (kk2 = Head [j3] ; kk2 != EMPTY ; kk2 = Path [kk2].next) { PRINT3 ((""ID" ", kk2)) ; ASSERT (Path [kk2].pending == j3) ; found = found || (kk2 == kk) ; } PRINT3 (("\n")) ; ASSERT (found) ; } } PRINT1 (("\nCol "ID": Paths at this column, head "ID"\n", j, Head [j])); ASSERT (Head [j] != EMPTY) ; for (kk = Head [j] ; kk != EMPTY ; kk = Path [kk].next) { PRINT1 (("path "ID": (c="ID" j="ID") npaths "ID"\n", kk, Path[kk].c, j, npaths)) ; ASSERT (kk >= 0 && kk < npaths) ; ASSERT (Path [kk].pending == j) ; } #endif /* -------------------------------------------------------------- */ /* determine the path we're on */ /* -------------------------------------------------------------- */ /* get the first old path at column j */ path = Head [j] ; /* -------------------------------------------------------------- */ /* update/downdate of forward solve, Lx=b */ /* -------------------------------------------------------------- */ if (do_solve) { xj = Xx [j] ; if (IS_NONZERO (xj)) { xj = Xx [j] ; /* This is first time column j has been seen for entire */ /* rank-k update/downdate. */ /* DeltaB += Lold (j:botrow-1,j) * X (j) */ Nx [j] += xj ; /* diagonal of L */ /* find the botrow for this column */ botrow = (use_colmark) ? Path [path].botrow : n ; for (p = p1 + 1 ; p < p2 ; p++) { i = Li [p] ; if (i >= botrow) { break ; } Nx [i] += Lx [p] * xj ; } /* clear X[j] to flag col j of Lold as having been seen. If * X (j) was initially zero, then the above code is never * executed for column j. This is safe, since if xj=0 the * code above does not do anything anyway. */ Xx [j] = 0.0 ; } } /* -------------------------------------------------------------- */ /* start a new path at this column if two or more paths merge */ /* -------------------------------------------------------------- */ newpath = /* start a new path if paths have merged */ (Path [path].next != EMPTY) /* or if j is the first node on a path (case A). */ || (Path [path].c == EMPTY) ; if (newpath) { /* get the botrow of the first path at column j */ botrow = (use_colmark) ? Path [path].botrow : n ; path = npaths++ ; ASSERT (npaths <= 3*k) ; Path [path].ccol = EMPTY ; /* no single col of C for this path*/ Path [path].start = j ; /* path starts at this column j */ Path [path].end = EMPTY ; /* don't know yet where it ends */ Path [path].parent = EMPTY ;/* don't know parent path yet */ Path [path].rank = 0 ; /* rank is sum of child path ranks */ PRINT1 (("Path "ID" starts: start "ID" end "ID" parent "ID"\n", path, Path [path].start, Path [path].end, Path [path].parent)) ; /* set the botrow of the new path */ Path [path].botrow = (use_colmark) ? botrow : n ; } /* -------------------------------------------------------------- */ /* for each path kk pending at column j */ /* -------------------------------------------------------------- */ /* make a list of the sets that need to be merged into column j */ nsets = 0 ; for (kk = Head [j] ; kk != EMPTY ; kk = Path [kk].next) { /* ---------------------------------------------------------- */ /* path kk is at (c,j) */ /* ---------------------------------------------------------- */ c = Path [kk].c ; ASSERT (c < j) ; PRINT1 (("TUPLE on path "ID" (c="ID" j="ID")\n", kk, c, j)) ; ASSERT (Path [kk].pending == j) ; if (newpath) { /* finalize path kk and find rank of this path */ Path [kk].end = c ; /* end of old path is previous node c */ Path [kk].parent = path ; /* parent is this path */ Path [path].rank += Path [kk].rank ; /* sum up ranks */ Path [kk].pending = EMPTY ; PRINT1 (("Path "ID" done:start "ID" end "ID" parent "ID"\n", kk, Path [kk].start, Path [kk].end, Path [kk].parent)) ; } if (c == EMPTY) { /* ------------------------------------------------------ */ /* CASE A: first node in path */ /* ------------------------------------------------------ */ /* update: add pattern of incoming column */ /* Column ccol of C is in Ci [pp1 ... pp2-1] */ ccol = Path [kk].ccol ; pp1 = Cp [ccol] ; pp2 = (packed) ? (Cp [ccol+1]) : (pp1 + Cnz [ccol]) ; PRINT1 (("Case A, ccol = "ID" len "ID"\n", ccol, pp2-pp1)) ; ASSERT (IMPLIES (pp2 > pp1, Ci [pp1] == j)) ; if (!scattered) { /* scatter the original pattern of column j of L */ for (p = p1 ; p < p2 ; p++) { Flag [Li [p]] = mark ; } scattered = TRUE ; } /* scatter column ccol of C (skip first entry, j) */ newlnz1 = newlnz ; for (p = pp1 + 1 ; p < pp2 ; p++) { row = Ci [p] ; if (Flag [row] < mark) { /* this is a new entry in Lj' */ Flag [row] = mark ; newlnz++ ; } } if (newlnz1 != newlnz) { /* column ccol of C adds something to column j of L */ Set [nsets++] = FLIP (ccol) ; } } else if (Head [c] == 1) { /* ------------------------------------------------------ */ /* CASE B: c is old, but changed, child of j */ /* CASE C: new child of j */ /* ------------------------------------------------------ */ /* Head [c] is 1 if col c of L has new entries, * EMPTY otherwise */ Flag [c] = 0 ; Head [c] = EMPTY ; /* update: add Lc' */ /* column c of L is in Li [pp1 .. pp2-1] */ pp1 = Lp [c] ; pp2 = pp1 + Lnz [c] ; PRINT1 (("Case B/C: c = "ID"\n", c)) ; DEBUG (dump_col ("Child", c, pp1, pp2, Li, Lx, n, Common)) ; ASSERT (j == Li [pp1 + 1]) ; /* j is new parent of c */ if (!scattered) { /* scatter the original pattern of column j of L */ for (p = p1 ; p < p2 ; p++) { Flag [Li [p]] = mark ; } scattered = TRUE ; } /* scatter column c of L (skip first two entries, c and j)*/ newlnz1 = newlnz ; for (p = pp1 + 2 ; p < pp2 ; p++) { row = Li [p] ; if (Flag [row] < mark) { /* this is a new entry in Lj' */ Flag [row] = mark ; newlnz++ ; } } PRINT2 (("\n")) ; if (newlnz1 != newlnz) { /* column c of L adds something to column j of L */ Set [nsets++] = c ; } } } /* -------------------------------------------------------------- */ /* update the pattern of column j of L */ /* -------------------------------------------------------------- */ /* Column j of L will be in Li/Lx [p1 .. p3-1] */ p3 = p1 + newlnz ; ASSERT (IMPLIES (nsets == 0, newlnz == Lnz [j])) ; PRINT1 (("p1 "ID" p2 "ID" p3 "ID" nsets "ID"\n", p1, p2, p3,nsets)); /* -------------------------------------------------------------- */ /* ensure we have enough space for the longer column */ /* -------------------------------------------------------------- */ if (nsets > 0 && p3 > Lp [Lnext [j]]) { PRINT1 (("Col realloc: j "ID" newlnz "ID"\n", j, newlnz)) ; if (!CHOLMOD(reallocate_column) (j, newlnz, L, Common)) { /* out of memory, L is now simplicial symbolic */ CHOLMOD(clear_flag) (Common) ; for (j = 0 ; j <= n ; j++) { Head [j] = EMPTY ; } ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, wdim, Common)) ; return (FALSE) ; } /* L->i and L->x may have moved. Column j has moved too */ Li = L->i ; Lx = L->x ; p1 = Lp [j] ; p2 = p1 + Lnz [j] ; p3 = p1 + newlnz ; } /* -------------------------------------------------------------- */ /* create set pointers */ /* -------------------------------------------------------------- */ for (s = 0 ; s < nsets ; s++) { /* Pattern of Set s is *(Set_ps1 [s] ... Set_ps2 [s]-1) */ c = Set [s] ; if (c < EMPTY) { /* column ccol of C, skip first entry (j) */ ccol = FLIP (c) ; pp1 = Cp [ccol] ; pp2 = (packed) ? (Cp [ccol+1]) : (pp1 + Cnz [ccol]) ; ASSERT (pp2 - pp1 > 1) ; Set_ps1 [s] = &(Ci [pp1 + 1]) ; Set_ps2 [s] = &(Ci [pp2]) ; PRINT1 (("set "ID" is ccol "ID"\n", s, ccol)) ; } else { /* column c of L, skip first two entries (c and j) */ pp1 = Lp [c] ; pp2 = pp1 + Lnz [c] ; ASSERT (Lnz [c] > 2) ; Set_ps1 [s] = &(Li [pp1 + 2]) ; Set_ps2 [s] = &(Li [pp2]) ; PRINT1 (("set "ID" is L "ID"\n", s, c)) ; } DEBUG (dump_set (s, Set_ps1, Set_ps2, j, n, Common)) ; } /* -------------------------------------------------------------- */ /* multiset merge */ /* -------------------------------------------------------------- */ /* Merge the sets into a single sorted set, Lj'. Before the merge * starts, column j is located in Li/Lx [p1 ... p2-1] and the * space Li/Lx [p2 ... p3-1] is empty. p1 is Lp [j], p2 is * Lp [j] + Lnz [j] (the old length of the column), and p3 is * Lp [j] + newlnz (the new and longer length of the column). * * The sets 0 to nsets-1 are defined by the Set_ps1 and Set_ps2 * pointers. Set s is located in *(Set_ps1 [s] ... Set_ps2 [s]-1). * It may be a column of C, or a column of L. All row indices i in * the sets are in the range i > j and i < n. All sets are sorted. * * The merge into column j of L is done in place. * * During the merge, p2 and p3 are updated. Li/Lx [p1..p2-1] * reflects the indices of the old column j of L that are yet to * be merged into the new column. Entries in their proper place in * the new column j of L are located in Li/Lx [p3 ... p1+newlnz-1]. * The merge finishes when p2 == p3. * * During the merge, set s consumed as it is merged into column j of * L. Its unconsumed contents are *(Set_ps1 [s] ... Set_ps2 [s]-1). * When a set is completely consumed, it is removed from the set of * sets, and nsets is decremented. * * The multiset merge and 2-set merge finishes when p2 == p3. */ PRINT1 (("Multiset merge p3 "ID" p2 "ID" nsets "ID"\n", p3, p2, nsets)) ; while (p3 > p2 && nsets > 1) { #ifndef NDEBUG PRINT2 (("\nMultiset merge. nsets = "ID"\n", nsets)) ; PRINT2 (("Source col p1 = "ID", p2 = "ID", p3= "ID"\n", p1, p2, p3)) ; for (p = p1 + 1 ; p < p2 ; p++) { PRINT2 ((" p: "ID" source row "ID" %g\n", p, Li[p], Lx[p])) ; ASSERT (Li [p] > j && Li [p] < n) ; } PRINT2 (("---\n")) ; for (p = p3 ; p < p1 + newlnz ; p++) { PRINT2 ((" p: "ID" target row "ID" %g\n", p, Li[p], Lx[p])) ; ASSERT (Li [p] > j && Li [p] < n) ; } for (s = 0 ; s < nsets ; s++) { dump_set (s, Set_ps1, Set_ps2, j, n, Common) ; } #endif /* get the entry at the tail end of source column Lj */ row1 = Li [p2 - 1] ; ASSERT (row1 >= j && p2 >= p1) ; /* find the largest row in all the sets */ maxrow = row1 ; smax = EMPTY ; for (s = nsets-1 ; s >= 0 ; s--) { ASSERT (Set_ps1 [s] < Set_ps2 [s]) ; row = *(Set_ps2 [s] - 1) ; if (row == maxrow) { /* skip past this entry in set s (it is a duplicate) */ Set_ps2 [s]-- ; if (Set_ps1 [s] == Set_ps2 [s]) { /* nothing more in this set */ nsets-- ; Set_ps1 [s] = Set_ps1 [nsets] ; Set_ps2 [s] = Set_ps2 [nsets] ; if (smax == nsets) { /* Set smax redefined; it is now this set */ smax = s ; } } } else if (row > maxrow) { maxrow = row ; smax = s ; } } ASSERT (maxrow > j) ; /* move the row onto the stack of the target column */ if (maxrow == row1) { /* next entry is in Lj, move to the bottom of Lj' */ ASSERT (smax == EMPTY) ; p2-- ; p3-- ; Li [p3] = maxrow ; Lx [p3] = Lx [p2] ; } else { /* new entry in Lj' */ ASSERT (smax >= 0 && smax < nsets) ; Set_ps2 [smax]-- ; p3-- ; Li [p3] = maxrow ; Lx [p3] = 0.0 ; if (Set_ps1 [smax] == Set_ps2 [smax]) { /* nothing more in this set */ nsets-- ; Set_ps1 [smax] = Set_ps1 [nsets] ; Set_ps2 [smax] = Set_ps2 [nsets] ; PRINT1 (("Set "ID" now empty\n", smax)) ; } } } /* -------------------------------------------------------------- */ /* 2-set merge: */ /* -------------------------------------------------------------- */ /* This the same as the multi-set merge, except there is only one * set s = 0 left. The source column j and the set 0 are being * merged into the target column j. */ if (nsets > 0) { ps1 = Set_ps1 [0] ; ps2 = Set_ps2 [0] ; } while (p3 > p2) { #ifndef NDEBUG PRINT2 (("\n2-set merge.\n")) ; ASSERT (nsets == 1) ; PRINT2 (("Source col p1 = "ID", p2 = "ID", p3= "ID"\n", p1, p2, p3)) ; for (p = p1 + 1 ; p < p2 ; p++) { PRINT2 ((" p: "ID" source row "ID" %g\n", p, Li[p], Lx[p])) ; ASSERT (Li [p] > j && Li [p] < n) ; } PRINT2 (("---\n")) ; for (p = p3 ; p < p1 + newlnz ; p++) { PRINT2 ((" p: "ID" target row "ID" %g\n", p, Li[p], Lx[p])) ; ASSERT (Li [p] > j && Li [p] < n) ; } dump_set (0, Set_ps1, Set_ps2, j, n, Common) ; #endif if (p2 == p1 + 1) { /* the top of Lj is empty; copy the set and quit */ while (p3 > p2) { /* new entry in Lj' */ row = *(--ps2) ; p3-- ; Li [p3] = row ; Lx [p3] = 0.0 ; } } else { /* get the entry at the tail end of Lj */ row1 = Li [p2 - 1] ; ASSERT (row1 > j && row1 < n) ; /* get the entry at the tail end of the incoming set */ ASSERT (ps1 < ps2) ; row = *(ps2-1) ; ASSERT (row > j && row1 < n) ; /* move the larger of the two entries to the target set */ if (row1 >= row) { /* next entry is in Lj, move to the bottom */ if (row1 == row) { /* skip past this entry in the set */ ps2-- ; } p2-- ; p3-- ; Li [p3] = row1 ; Lx [p3] = Lx [p2] ; } else { /* new entry in Lj' */ ps2-- ; p3-- ; Li [p3] = row ; Lx [p3] = 0.0 ; } } } /* -------------------------------------------------------------- */ /* The new column j of L is now in Li/Lx [p1 ... p2-1] */ /* -------------------------------------------------------------- */ p2 = p1 + newlnz ; DEBUG (dump_col ("After merge: ", j, p1, p2, Li, Lx, n, Common)) ; fl += Path [path].rank * (6 + 4 * (double) newlnz) ; /* -------------------------------------------------------------- */ /* clear Flag; original pattern of column j L no longer marked */ /* -------------------------------------------------------------- */ mark = CHOLMOD(clear_flag) (Common) ; scattered = FALSE ; /* -------------------------------------------------------------- */ /* find the new parent */ /* -------------------------------------------------------------- */ newparent = (newlnz > 1) ? (Li [p1 + 1]) : EMPTY ; PRINT1 (("\nNew parent, Lnz: "ID": "ID" "ID"\n", j, newparent,newlnz)); ASSERT (oldparent == EMPTY || newparent <= oldparent) ; /* -------------------------------------------------------------- */ /* go to the next node in the path */ /* -------------------------------------------------------------- */ /* path moves to (j,nextj) unless j is a root */ nextj = (newparent == EMPTY) ? n : newparent ; /* place path at head of list for nextj, or terminate the path */ PRINT1 (("\n j = "ID" nextj = "ID"\n\n", j, nextj)) ; Path [path].c = j ; if (nextj < n) { /* put path on link list of pending paths at column nextj */ Path [path].next = Head [nextj] ; Path [path].pending = nextj ; Head [nextj] = path ; PRINT1 (("Path "ID" continues to ("ID","ID"). Rank "ID"\n", path, Path [path].c, nextj, Path [path].rank)) ; } else { /* path has ended here, at a root */ Path [path].next = EMPTY ; Path [path].pending = EMPTY ; Path [path].end = j ; PRINT1 (("Path "ID" ends at root ("ID"). Rank "ID"\n", path, Path [path].end, Path [path].rank)) ; } /* The link list Head [j] can now be emptied. Set Head [j] to 1 * if column j has changed (it is no longer used as a link list). */ PRINT1 (("column "ID", oldlnz = "ID"\n", j, Lnz [j])) ; Head [j] = (Lnz [j] != newlnz) ? 1 : EMPTY ; Lnz [j] = newlnz ; PRINT1 (("column "ID", newlnz = "ID"\n", j, newlnz)) ; DEBUG (dump_col ("New", j, p1, p2, Li, Lx, n, Common)) ; /* move to the next column */ if (k == Path [path].rank) { /* only one path left */ j = nextj ; } else { /* The current path is moving from column j to column nextj * (nextj is n if the path has ended). However, there may be * other paths pending in columns j+1 to nextj-1. There are * two methods for looking for the next column with a pending * update. The first one looks at all columns j+1 to nextj-1 * for a non-empty link list. This can be costly if j and * nextj differ by a large amount (it can be O(n), but this * entire routine may take Omega(1) time). The second method * looks at all paths and finds the smallest column at which any * path is pending. It takes O(# of paths), which is bounded * by 23: one for each column of C (up to 8), and then 15 for a * balanced binary tree with 8 leaves. However, if j and * nextj differ by a tiny amount (nextj is often j+1 near * the end of the matrix), looking at columns j+1 to nextj * would be faster. Both methods give the same answer. */ if (nextj - j < npaths) { /* there are fewer columns to search than paths */ PRINT1 (("check j="ID" to nextj="ID"\n", j, nextj)) ; for (j2 = j + 1 ; j2 < nextj ; j2++) { PRINT1 (("check j="ID" "ID"\n", j2, Head [j2])) ; if (Head [j2] != EMPTY) { PRINT1 (("found, j="ID"\n", j2)) ; ASSERT (Path [Head [j2]].pending == j2) ; break ; } } } else { /* there are fewer paths than columns to search */ j2 = nextj ; for (kk = 0 ; kk < npaths ; kk++) { jj = Path [kk].pending ; PRINT2 (("Path "ID" pending at "ID"\n", kk, jj)) ; if (jj != EMPTY) j2 = MIN (j2, jj) ; } } j = j2 ; } } /* ensure workspaces are back to the values required on input */ ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, TRUE, Common)) ; /* ------------------------------------------------------------------ */ /* depth-first-search of tree to order the paths */ /* ------------------------------------------------------------------ */ /* create lists of child paths */ PRINT1 (("\n\nDFS search:\n\n")) ; for (path = 0 ; path < npaths ; path++) { Path [path].c = EMPTY ; /* first child of path */ Path [path].next = EMPTY ; /* next sibling of path */ Path [path].order = EMPTY ; /* path is not ordered yet */ Path [path].wfirst = EMPTY ; /* 1st column of W not found yet */ #ifndef NDEBUG j = Path [path].start ; PRINT1 (("Path "ID" : start "ID" end "ID" parent "ID" ccol "ID"\n", path, j, Path [path].end, Path [path].parent, Path [path].ccol)) ; for ( ; ; ) { PRINT1 ((" column "ID"\n", j)) ; ASSERT (j == EMPTY || (j >= 0 && j < n)) ; if (j == Path [path].end) { break ; } ASSERT (j >= 0 && j < n) ; j = (Lnz [j] > 1) ? (Li [Lp [j] + 1]) : EMPTY ; } #endif } for (path = 0 ; path < npaths ; path++) { p = Path [path].parent ; /* add path to child list of parent */ if (p != EMPTY) { ASSERT (p < npaths) ; Path [path].next = Path [p].c ; Path [p].c = path ; } } path_order = k ; w_order = 0 ; for (path = npaths-1 ; path >= 0 ; path--) { if (Path [path].order == EMPTY) { /* this path is the root of a subtree of Tbar */ PRINT1 (("Root path "ID"\n", path)) ; ASSERT (path >= k) ; dfs (Path, k, path, &path_order, &w_order, 0, npaths) ; } } ASSERT (path_order == npaths) ; ASSERT (w_order == k) ; /* reorder the paths */ for (path = 0 ; path < npaths ; path++) { /* old order is path, new order is Path [path].order */ OrderedPath [Path [path].order] = Path [path] ; } #ifndef NDEBUG for (path = 0 ; path < npaths ; path++) { PRINT1 (("Ordered Path "ID": start "ID" end "ID" wfirst "ID" rank " ""ID" ccol "ID"\n", path, OrderedPath [path].start, OrderedPath [path].end, OrderedPath [path].wfirst, OrderedPath [path].rank, OrderedPath [path].ccol)) ; if (path < k) { ASSERT (OrderedPath [path].ccol >= 0) ; } else { ASSERT (OrderedPath [path].ccol == EMPTY) ; } } #endif /* ------------------------------------------------------------------ */ /* numeric update/downdate for all paths */ /* ------------------------------------------------------------------ */ ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, wdim, Common)) ; switch (wdim) { case 1: updown_1_r (update, C, k, L, W, OrderedPath, npaths, mask, Common) ; break ; case 2: updown_2_r (update, C, k, L, W, OrderedPath, npaths, mask, Common) ; break ; case 4: updown_4_r (update, C, k, L, W, OrderedPath, npaths, mask, Common) ; break ; case 8: updown_8_r (update, C, k, L, W, OrderedPath, npaths, mask, Common) ; break ; } ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, wdim, Common)) ; } /* ---------------------------------------------------------------------- */ /* update/downdate the forward solve */ /* ---------------------------------------------------------------------- */ if (do_solve) { /* We now have DeltaB += Lold (:,j) * X (j) for all columns j in union * of all paths seen during the entire rank-cncol update/downdate. For * each j in path, do DeltaB -= Lnew (:,j)*DeltaB(j) * in topological order. */ #ifndef NDEBUG PRINT1 (("\ndo_solve, DeltaB + Lold(:,Path)*X(Path):\n")) ; for (i = 0 ; i < n ; i++) { PRINT1 (("do_solve: "ID" %30.20e\n", i, Nx [i])) ; } #endif /* Note that the downdate, if it deleted entries, would need to compute * the Stack prior to doing any downdates. */ /* find the union of all the paths in the new L */ top = n ; /* "top" is stack pointer, not a row or column index */ for (ccol = 0 ; ccol < cncol ; ccol++) { /* -------------------------------------------------------------- */ /* j = first row index of C (:,ccol) */ /* -------------------------------------------------------------- */ pp1 = Cp [ccol] ; pp2 = (packed) ? (Cp [ccol+1]) : (pp1 + Cnz [ccol]) ; if (pp2 > pp1) { /* Column ccol of C has at least one entry. */ j = Ci [pp1] ; } else { /* Column ccol of C is empty */ j = n-1 ; } PRINT1 (("\ndo_solve: ccol= "ID"\n", ccol)) ; ASSERT (j >= 0 && j < n) ; len = 0 ; /* -------------------------------------------------------------- */ /* find the new rowmark */ /* -------------------------------------------------------------- */ /* Each column of C can redefine the region of L that takes part in * the update/downdate of the triangular solve Lx=b. If * i = colmark [ccol] for column C(:,ccol), then i = rowmark [j] is * redefined for all columns along the path modified by C(:,ccol). * If more than one column modifies any given column j of L, then * the rowmark of j is determined by the colmark of the least- * numbered column that affects column j. That is, if both * C(:,ccol1) and C(:,ccol2) affect column j of L, then * rowmark [j] = colmark [MIN (ccol1, ccol2)]. * * rowmark [j] is not modified if rowmark or colmark are NULL, * or if colmark [ccol] is EMPTY. */ botrow = (use_colmark) ? (colmark [ccol]) : EMPTY ; /* -------------------------------------------------------------- */ /* traverse from j towards root, stopping if node already visited */ /* -------------------------------------------------------------- */ while (j != EMPTY && Flag [j] < mark) { PRINT1 (("do_solve: subpath j= "ID"\n", j)) ; ASSERT (j >= 0 && j < n) ; Stack [len++] = j ; /* place j on the stack */ Flag [j] = mark ; /* flag j as visited */ /* if using colmark, mark column j with botrow */ ASSERT (Li [Lp [j]] == j) ; /* diagonal is always present */ if (use_colmark) { Li [Lp [j]] = botrow ; /* use the space for botrow */ } /* go up the tree, to the parent of j */ j = (Lnz [j] > 1) ? (Li [Lp [j] + 1]) : EMPTY ; } /* -------------------------------------------------------------- */ /* move the path down to the bottom of the stack */ /* -------------------------------------------------------------- */ ASSERT (len <= top) ; while (len > 0) { Stack [--top] = Stack [--len] ; } } #ifndef NDEBUG /* Union of paths now in Stack [top..n-1] in topological order */ PRINT1 (("\nTopological order:\n")) ; for (i = top ; i < n ; i++) { PRINT1 (("column "ID" in full path\n", Stack [i])) ; } #endif /* Do the forward solve for the full path part of L */ for (m = top ; m < n ; m++) { j = Stack [m] ; ASSERT (j >= 0 && j < n) ; PRINT1 (("do_solve: path j= "ID"\n", j)) ; p1 = Lp [j] ; lnz = Lnz [j] ; p2 = p1 + lnz ; xj = Nx [j] ; /* copy new solution onto old one, for all cols in full path */ Xx [j] = xj ; Nx [j] = 0. ; /* DeltaB -= Lnew (j+1:botrow-1,j) * deltab(j) */ if (use_colmark) { botrow = Li [p1] ; /* get botrow */ Li [p1] = j ; /* restore diagonal entry */ for (p = p1 + 1 ; p < p2 ; p++) { i = Li [p] ; if (i >= botrow) break ; Nx [i] -= Lx [p] * xj ; } } else { for (p = p1 + 1 ; p < p2 ; p++) { Nx [Li [p]] -= Lx [p] * xj ; } } } /* clear the Flag */ mark = CHOLMOD(clear_flag) (Common) ; } /* ---------------------------------------------------------------------- */ /* successful update/downdate */ /* ---------------------------------------------------------------------- */ Common->modfl = fl ; DEBUG (for (j = 0 ; j < n ; j++) ASSERT (IMPLIES (do_solve, Nx[j] == 0.))) ; ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, TRUE, Common)) ; DEBUG (CHOLMOD(dump_factor) (L, "output L for updown", Common)) ; return (TRUE) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Modify/License.txt0000644000076500000240000000204613524616144026045 0ustar tamasstaff00000000000000CHOLMOD/Modify Module. Copyright (C) 2005-2006, Timothy A. Davis and William W. Hager CHOLMOD is also available under other licenses; contact authors for details. http://www.suitesparse.com Note that this license is for the CHOLMOD/Modify module only. All CHOLMOD modules are licensed separately. -------------------------------------------------------------------------------- This Module is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This Module is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this Module; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Modify/t_cholmod_updown.c0000644000076500000240000001504513524616144027435 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Modify/t_cholmod_updown ============================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Modify Module. Copyright (C) 2005-2006, * Timothy A. Davis and William W. Hager. * The CHOLMOD/Modify Module is licensed under Version 2.0 of the GNU * General Public License. See gpl.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * http://www.suitesparse.com * -------------------------------------------------------------------------- */ /* Updates/downdates the LDL' factorization, by computing a new factorization of * * Lnew * Dnew * Lnew' = Lold * Dold * Lold' +/- C*C' * * This file is not compiled separately. It is included into * cholmod_updown.c. There are no user-callable routines in this file. * * The next include statements, below, create the numerical update/downdate * kernels from t_cholmod_updown_numkr.c. There are 4 compiled versions of this * file, one for each value of WDIM in the set 1, 2, 4, and 8. Each calls * multiple versions of t_cholmod_updown_numkr; the number of versions of each * is equal to WDIM. Each t_cholmod_updown_numkr version is included as a * static function within its t_cholmod_updown.c caller routine. Thus: * * t*_updown.c creates these versions of t_cholmod_updown_numkr.c: * --------- --------------------------------------------------- * * updown_1_r updown_1_1 * * updown_2_r updown_2_1 updown_2_2 * * updown_4_r updown_4_1 updown_4_2 updown_4_3 updown_4_4 * * updown_8_r updown_8_1 updown_8_2 updown_8_3 updown_8_4 * updown_8_5 updown_8_6 updown_8_7 updown_8_8 * * workspace: Xwork (nrow*wdim) */ /* ========================================================================== */ /* === routines for numeric update/downdate along one path ================== */ /* ========================================================================== */ #undef FORM_NAME #undef NUMERIC #define FORM_NAME(k,rank) updown_ ## k ## _ ## rank #define NUMERIC(k,rank) FORM_NAME(k,rank) #define RANK 1 #include "t_cholmod_updown_numkr.c" #if WDIM >= 2 #define RANK 2 #include "t_cholmod_updown_numkr.c" #endif #if WDIM >= 4 #define RANK 3 #include "t_cholmod_updown_numkr.c" #define RANK 4 #include "t_cholmod_updown_numkr.c" #endif #if WDIM == 8 #define RANK 5 #include "t_cholmod_updown_numkr.c" #define RANK 6 #include "t_cholmod_updown_numkr.c" #define RANK 7 #include "t_cholmod_updown_numkr.c" #define RANK 8 #include "t_cholmod_updown_numkr.c" #endif /* ========================================================================== */ /* === numeric update/downdate for all paths ================================ */ /* ========================================================================== */ static void NUMERIC (WDIM, r) ( int update, /* TRUE for update, FALSE for downdate */ cholmod_sparse *C, /* in packed or unpacked, and sorted form */ /* no empty columns */ Int rank, /* rank of the update/downdate */ cholmod_factor *L, /* with unit diagonal (diagonal not stored) */ /* temporary workspaces: */ double W [ ], /* n-by-WDIM dense matrix, initially zero */ Path_type Path [ ], Int npaths, Int mask [ ], /* size n */ cholmod_common *Common ) { double Alpha [8] ; double *Cx, *Wpath, *W1, *a ; Int i, j, p, ccol, pend, wfirst, e, path, packed ; Int *Ci, *Cp, *Cnz ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ Ci = C->i ; Cx = C->x ; Cp = C->p ; Cnz = C->nz ; packed = C->packed ; ASSERT (IMPLIES (!packed, Cnz != NULL)) ; ASSERT (L->n == C->nrow) ; DEBUG (CHOLMOD(dump_real) ("num_d: in W:", W, WDIM, L->n, FALSE, 1,Common)); /* ---------------------------------------------------------------------- */ /* scatter C into W */ /* ---------------------------------------------------------------------- */ for (path = 0 ; path < rank ; path++) { /* W (:, path) = C (:, Path [path].col) */ ccol = Path [path].ccol ; Wpath = W + path ; PRINT1 (("Ordered Columns [path = "ID"] = "ID"\n", path, ccol)) ; p = Cp [ccol] ; pend = (packed) ? (Cp [ccol+1]) : (p + Cnz [ccol]) ; /* column C can be empty */ for ( ; p < pend ; p++) { i = Ci [p] ; ASSERT (i >= 0 && i < (Int) (C->nrow)) ; if (mask == NULL || mask [i] < 0) { Wpath [WDIM * i] = Cx [p] ; } PRINT1 ((" row "ID" : %g mask "ID"\n", i, Cx [p], (mask) ? mask [i] : 0)) ; } Alpha [path] = 1.0 ; } DEBUG (CHOLMOD(dump_real) ("num_d: W:", W, WDIM, L->n, FALSE, 1,Common)) ; /* ---------------------------------------------------------------------- */ /* numeric update/downdate of the paths */ /* ---------------------------------------------------------------------- */ /* for each disjoint subpath in Tbar in DFS order do */ for (path = rank ; path < npaths ; path++) { /* determine which columns of W to use */ wfirst = Path [path].wfirst ; e = Path [path].end ; j = Path [path].start ; ASSERT (e >= 0 && e < (Int) (L->n)) ; ASSERT (j >= 0 && j < (Int) (L->n)) ; W1 = W + wfirst ; /* pointer to row 0, column wfirst of W */ a = Alpha + wfirst ; /* pointer to Alpha [wfirst] */ PRINT1 (("Numerical update/downdate of path "ID"\n", path)) ; PRINT1 (("start "ID" end "ID" wfirst "ID" rank "ID" ccol "ID"\n", j, e, wfirst, Path [path].rank, Path [path].ccol)) ; #if WDIM == 1 NUMERIC (WDIM,1) (update, j, e, a, W1, L, Common) ; #else switch (Path [path].rank) { case 1: NUMERIC (WDIM,1) (update, j, e, a, W1, L, Common) ; break ; #if WDIM >= 2 case 2: NUMERIC (WDIM,2) (update, j, e, a, W1, L, Common) ; break ; #endif #if WDIM >= 4 case 3: NUMERIC (WDIM,3) (update, j, e, a, W1, L, Common) ; break ; case 4: NUMERIC (WDIM,4) (update, j, e, a, W1, L, Common) ; break ; #endif #if WDIM == 8 case 5: NUMERIC (WDIM,5) (update, j, e, a, W1, L, Common) ; break ; case 6: NUMERIC (WDIM,6) (update, j, e, a, W1, L, Common) ; break ; case 7: NUMERIC (WDIM,7) (update, j, e, a, W1, L, Common) ; break ; case 8: NUMERIC (WDIM,8) (update, j, e, a, W1, L, Common) ; break ; #endif } #endif } } /* prepare for the next inclusion of this file in cholmod_updown.c */ #undef WDIM python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Modify/cholmod_rowadd.c0000644000076500000240000004643013524616144027060 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Modify/cholmod_rowadd ================================================ */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Modify Module. * Copyright (C) 2005-2006, Timothy A. Davis and William W. Hager. * The CHOLMOD/Modify Module is licensed under Version 2.0 of the GNU * General Public License. See gpl.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * http://www.suitesparse.com * -------------------------------------------------------------------------- */ /* Adds a row and column to an LDL' factorization, and optionally updates the * solution to Lx=b. * * workspace: Flag (nrow), Head (nrow+1), W (2*nrow), Iwork (2*nrow) * * Only real matrices are supported. A symbolic L is converted into a * numeric identity matrix before the row is added. */ #ifndef NMODIFY #include "cholmod_internal.h" #include "cholmod_modify.h" /* ========================================================================== */ /* === cholmod_rowadd ======================================================= */ /* ========================================================================== */ /* cholmod_rowadd adds a row to the LDL' factorization. It computes the kth * row and kth column of L, and then updates the submatrix L (k+1:n,k+1:n) * accordingly. The kth row and column of L should originally be equal to the * kth row and column of the identity matrix (they are treated as such, if they * are not). The kth row/column of L is computed as the factorization of the * kth row/column of the matrix to factorize, which is provided as a single * n-by-1 sparse matrix R. The sparse vector R need not be sorted. */ int CHOLMOD(rowadd) ( /* ---- input ---- */ size_t k, /* row/column index to add */ cholmod_sparse *R, /* row/column of matrix to factorize (n-by-1) */ /* ---- in/out --- */ cholmod_factor *L, /* factor to modify */ /* --------------- */ cholmod_common *Common ) { double bk [2] ; bk [0] = 0. ; bk [1] = 0. ; return (CHOLMOD(rowadd_mark) (k, R, bk, NULL, L, NULL, NULL, Common)) ; } /* ========================================================================== */ /* === cholmod_rowadd_solve ================================================= */ /* ========================================================================== */ /* Does the same as cholmod_rowadd, and also updates the solution to Lx=b * See cholmod_updown for a description of how Lx=b is updated. There is on * additional parameter: bk specifies the new kth entry of b. */ int CHOLMOD(rowadd_solve) ( /* ---- input ---- */ size_t k, /* row/column index to add */ cholmod_sparse *R, /* row/column of matrix to factorize (n-by-1) */ double bk [2], /* kth entry of the right-hand-side b */ /* ---- in/out --- */ cholmod_factor *L, /* factor to modify */ cholmod_dense *X, /* solution to Lx=b (size n-by-1) */ cholmod_dense *DeltaB, /* change in b, zero on output */ /* --------------- */ cholmod_common *Common ) { return (CHOLMOD(rowadd_mark) (k, R, bk, NULL, L, X, DeltaB, Common)) ; } /* ========================================================================== */ /* === icomp ================================================================ */ /* ========================================================================== */ /* for sorting by qsort */ static int icomp (Int *i, Int *j) { if (*i < *j) { return (-1) ; } else { return (1) ; } } /* ========================================================================== */ /* === cholmod_rowadd_mark ================================================== */ /* ========================================================================== */ /* Does the same as cholmod_rowadd_solve, except only part of L is used in * the update/downdate of the solution to Lx=b. This routine is an "expert" * routine. It is meant for use in LPDASA only. */ int CHOLMOD(rowadd_mark) ( /* ---- input ---- */ size_t kadd, /* row/column index to add */ cholmod_sparse *R, /* row/column of matrix to factorize (n-by-1) */ double bk [2], /* kth entry of the right hand side, b */ Int *colmark, /* Int array of size 1. See cholmod_updown.c */ /* ---- in/out --- */ cholmod_factor *L, /* factor to modify */ cholmod_dense *X, /* solution to Lx=b (size n-by-1) */ cholmod_dense *DeltaB, /* change in b, zero on output */ /* --------------- */ cholmod_common *Common ) { double dk, yj, l_kj, lx, l_ij, sqrt_dk, dj, xk, rnz, fl ; double *Lx, *W, *Cx, *Rx, *Xx, *Nx ; Int *Li, *Lp, *Lnz, *Flag, *Stack, *Ci, *Rj, *Rp, *Lnext, *Iwork, *Rnz ; cholmod_sparse *C, Cmatrix ; Int i, j, p, pend, top, len, kk, li, lnz, mark, k, n, parent, Cp [2], do_solve, do_update ; size_t s ; int ok = TRUE ; DEBUG (Int lastrow) ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (L, FALSE) ; RETURN_IF_NULL (R, FALSE) ; RETURN_IF_XTYPE_INVALID (L, CHOLMOD_PATTERN, CHOLMOD_REAL, FALSE) ; RETURN_IF_XTYPE_INVALID (R, CHOLMOD_REAL, CHOLMOD_REAL, FALSE) ; n = L->n ; k = kadd ; if (kadd >= L->n || k < 0) { ERROR (CHOLMOD_INVALID, "k invalid") ; return (FALSE) ; } if (R->ncol != 1 || R->nrow != L->n) { ERROR (CHOLMOD_INVALID, "R invalid") ; return (FALSE) ; } Rj = R->i ; Rx = R->x ; Rp = R->p ; Rnz = R->nz ; rnz = (R->packed) ? (Rp [1]) : (Rnz [0]) ; do_solve = (X != NULL) && (DeltaB != NULL) ; if (do_solve) { RETURN_IF_XTYPE_INVALID (X, CHOLMOD_REAL, CHOLMOD_REAL, FALSE) ; RETURN_IF_XTYPE_INVALID (DeltaB, CHOLMOD_REAL, CHOLMOD_REAL, FALSE) ; Xx = X->x ; Nx = DeltaB->x ; if (X->nrow != L->n || X->ncol != 1 || DeltaB->nrow != L->n || DeltaB->ncol != 1 || Xx == NULL || Nx == NULL) { ERROR (CHOLMOD_INVALID, "X and/or DeltaB invalid") ; return (FALSE) ; } } else { Xx = NULL ; Nx = NULL ; } Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ /* s = 2*n */ s = CHOLMOD(mult_size_t) (n, 2, &ok) ; if (!ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return (FALSE) ; } CHOLMOD(allocate_work) (n, s, s, Common) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; } ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, s, Common)) ; /* ---------------------------------------------------------------------- */ /* convert to simplicial numeric LDL' factor, if not already */ /* ---------------------------------------------------------------------- */ if (L->xtype == CHOLMOD_PATTERN || L->is_super || L->is_ll) { /* can only update/downdate a simplicial LDL' factorization */ CHOLMOD(change_factor) (CHOLMOD_REAL, FALSE, FALSE, FALSE, FALSE, L, Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory, L is returned unchanged */ return (FALSE) ; } } /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ /* inputs, not modified on output: */ Lp = L->p ; /* size n+1. input, not modified on output */ /* outputs, contents defined on input for incremental case only: */ Lnz = L->nz ; /* size n */ Li = L->i ; /* size L->nzmax. Can change in size. */ Lx = L->x ; /* size L->nzmax. Can change in size. */ Lnext = L->next ; /* size n+2 */ ASSERT (L->nz != NULL) ; PRINT1 (("rowadd:\n")) ; fl = 0 ; #if 0 #ifndef NDEBUG /* column k of L should be zero, except for the diagonal. This test is * overly cautious. */ for (p = Lp [k] + 1 ; p < Lp [k] + Lnz [k] ; p++) ASSERT (Lx [p] == 0) ; #endif #endif /* ---------------------------------------------------------------------- */ /* get workspace */ /* ---------------------------------------------------------------------- */ Flag = Common->Flag ; /* size n */ W = Common->Xwork ; /* size n */ Cx = W + n ; /* size n (use 2nd column of Xwork for C) */ Iwork = Common->Iwork ; Stack = Iwork ; /* size n (i/i/l), also in cholmod_updown */ Ci = Iwork + n ; /* size n (i/i/l) */ /* NOTE: cholmod_updown uses Iwork [0..n-1] (i/i/l) as Stack as well */ mark = Common->mark ; /* copy Rj/Rx into W/Ci */ for (p = 0 ; p < rnz ; p++) { i = Rj [p] ; ASSERT (i >= 0 && i < n) ; W [i] = Rx [p] ; Ci [p] = i ; } /* At this point, W [Ci [0..rnz-1]] holds the sparse vector to add */ /* The nonzero pattern of column W is held in Ci (it may be unsorted). */ /* ---------------------------------------------------------------------- */ /* symbolic factorization to get pattern of kth row of L */ /* ---------------------------------------------------------------------- */ DEBUG (for (p = 0 ; p < rnz ; p++) PRINT1 (("C ("ID",%g)\n", Ci [p], W [Ci [p]]))) ; ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; /* flag the diagonal */ Flag [k] = mark ; /* find the union of all the paths */ top = n ; lnz = 0 ; /* # of nonzeros in column k of L, excluding diagonal */ for (p = 0 ; p < rnz ; p++) { i = Ci [p] ; if (i < k) { /* walk from i = entry in Ci to root (and stop if i marked)*/ PRINT2 (("\nwalk from i = "ID" towards k = "ID"\n", i, k)) ; len = 0 ; /* walk up tree, but stop if we go below the diagonal */ while (i < k && i != EMPTY && Flag [i] < mark) { PRINT2 ((" Add "ID" to path\n", i)) ; ASSERT (i >= 0 && i < k) ; Stack [len++] = i ; /* place i on the stack */ Flag [i] = mark ; /* mark i as visited */ /* parent is the first entry in the column after the diagonal */ ASSERT (Lnz [i] > 0) ; parent = (Lnz [i] > 1) ? (Li [Lp [i] + 1]) : EMPTY ; PRINT2 ((" parent: "ID"\n", parent)) ; i = parent ; /* go up the tree */ } ASSERT (len <= top) ; /* move the path down to the bottom of the stack */ /* this shifts Stack [0..len-1] down to [ ... oldtop-1] */ while (len > 0) { Stack [--top] = Stack [--len] ; } } else if (i > k) { /* prune the diagonal and upper triangular entries from Ci */ Ci [lnz++] = i ; Flag [i] = mark ; } } #ifndef NDEBUG PRINT1 (("length of S after prune: "ID"\n", lnz)) ; for (p = 0 ; p < lnz ; p++) { PRINT1 (("After prune Ci ["ID"] = "ID"\n", p, Ci [p])) ; ASSERT (Ci [p] > k) ; } #endif /* ---------------------------------------------------------------------- */ /* ensure each column of L has enough space to grow */ /* ---------------------------------------------------------------------- */ for (kk = top ; kk < n ; kk++) { /* could skip this if we knew column j already included row k */ j = Stack [kk] ; if (Lp [j] + Lnz [j] >= Lp [Lnext [j]]) { PRINT1 (("Col "ID" realloc, old Lnz "ID"\n", j, Lnz [j])) ; if (!CHOLMOD(reallocate_column) (j, Lnz [j] + 1, L, Common)) { /* out of memory, L is now simplicial symbolic */ /* CHOLMOD(clear_flag) (Common) ; */ CHOLMOD_CLEAR_FLAG (Common) ; for (i = 0 ; i < n ; i++) { W [i] = 0 ; } return (FALSE) ; } /* L->i and L->x may have moved */ Li = L->i ; Lx = L->x ; } ASSERT (Lp [j] + Lnz [j] < Lp [Lnext [j]] || (Lp [Lnext [j]] - Lp [j] == n-j)) ; } /* ---------------------------------------------------------------------- */ /* compute kth row of L and store in column form */ /* ---------------------------------------------------------------------- */ /* solve L (1:k-1, 1:k-1) * y (1:k-1) = b (1:k-1) */ /* where b (1:k) is in W and Ci */ /* L (k, 1:k-1) = y (1:k-1) ./ D (1:k-1) */ /* D (k) = B (k,k) - L (k, 1:k-1) * y (1:k-1) */ PRINT2 (("\nForward solve: "ID" to "ID"\n", top, n)) ; ASSERT (Lnz [k] >= 1 && Li [Lp [k]] == k) ; DEBUG (for (i = top ; i < n ; i++) PRINT2 ((" Path: "ID"\n", Stack [i]))) ; dk = W [k] ; W [k] = 0.0 ; /* if do_solve: compute x (k) = b (k) - L (k, 1:k-1) * x (1:k-1) */ xk = bk [0] ; PRINT2 (("B [k] = %g\n", xk)) ; for (kk = top ; kk < n ; kk++) { j = Stack [kk] ; i = j ; PRINT2 (("Forward solve col j = "ID":\n", j)) ; ASSERT (j >= 0 && j < k) ; /* forward solve using L (j+1:k-1,j) */ yj = W [j] ; W [j] = 0.0 ; p = Lp [j] ; pend = p + Lnz [j] ; ASSERT (Lnz [j] > 0) ; dj = Lx [p++] ; for ( ; p < pend ; p++) { i = Li [p] ; PRINT2 ((" row "ID"\n", i)) ; ASSERT (i > j) ; ASSERT (i < n) ; /* stop at row k */ if (i >= k) { break ; } W [i] -= Lx [p] * yj ; } /* each iteration of the above for loop did 2 flops, and 3 flops * are done below. so: fl += 2 * (Lp [j] - p - 1) + 3 becomes: */ fl += 2 * (Lp [j] - p) + 1 ; /* scale L (k,1:k-1) and compute dot product for D (k,k) */ l_kj = yj / dj ; dk -= l_kj * yj ; /* compute dot product for X(k) */ if (do_solve) { xk -= l_kj * Xx [j] ; } /* store l_kj in the jth column of L */ /* and shift the rest of the column down */ li = k ; lx = l_kj ; if (i == k) { /* no need to modify the nonzero pattern of L, since it already * contains row index k. */ ASSERT (Li [p] == k) ; Lx [p] = l_kj ; for (p++ ; p < pend ; p++) { i = Li [p] ; l_ij = Lx [p] ; ASSERT (i > k && i < n) ; PRINT2 ((" apply to row "ID" of column k of L\n", i)) ; /* add to the pattern of the kth column of L */ if (Flag [i] < mark) { PRINT2 ((" add Ci["ID"] = "ID"\n", lnz, i)) ; ASSERT (i > k) ; Ci [lnz++] = i ; Flag [i] = mark ; } /* apply the update to the kth column of L */ /* yj is equal to l_kj * d_j */ W [i] -= l_ij * yj ; } } else { PRINT2 (("Shift col j = "ID", apply saxpy to col k of L\n", j)) ; for ( ; p < pend ; p++) { /* swap (Li [p],Lx [p]) with (li,lx) */ i = Li [p] ; l_ij = Lx [p] ; Li [p] = li ; Lx [p] = lx ; li = i ; lx = l_ij ; ASSERT (i > k && i < n) ; PRINT2 ((" apply to row "ID" of column k of L\n", i)) ; /* add to the pattern of the kth column of L */ if (Flag [i] < mark) { PRINT2 ((" add Ci["ID"] = "ID"\n", lnz, i)) ; ASSERT (i > k) ; Ci [lnz++] = i ; Flag [i] = mark ; } /* apply the update to the kth column of L */ /* yj is equal to l_kj * d_j */ W [i] -= l_ij * yj ; } /* store the last value in the jth column of L */ Li [p] = li ; Lx [p] = lx ; Lnz [j]++ ; } } /* ---------------------------------------------------------------------- */ /* merge C with the pattern of the existing column of L */ /* ---------------------------------------------------------------------- */ /* This column should be zero, but it may contain explicit zero entries. * These entries should be kept, not dropped. */ p = Lp [k] ; pend = p + Lnz [k] ; for (p++ ; p < pend ; p++) { i = Li [p] ; /* add to the pattern of the kth column of L */ if (Flag [i] < mark) { PRINT2 ((" add Ci["ID"] = "ID" from existing col k\n", lnz, i)) ; ASSERT (i > k) ; Ci [lnz++] = i ; Flag [i] = mark ; } } /* ---------------------------------------------------------------------- */ if (do_solve) { Xx [k] = xk ; PRINT2 (("Xx [k] = %g\n", Xx [k])) ; } /* ---------------------------------------------------------------------- */ /* ensure abs (dk) >= dbound, if dbound is given */ /* ---------------------------------------------------------------------- */ dk = (IS_GT_ZERO (Common->dbound)) ? (CHOLMOD(dbound) (dk, Common)) : dk ; PRINT2 (("D [k = "ID"] = %g\n", k, dk)) ; /* ---------------------------------------------------------------------- */ /* store the kth column of L */ /* ---------------------------------------------------------------------- */ /* ensure the new column of L has enough space */ if (Lp [k] + lnz + 1 > Lp [Lnext [k]]) { PRINT1 (("New Col "ID" realloc, old Lnz "ID"\n", k, Lnz [k])) ; if (!CHOLMOD(reallocate_column) (k, lnz + 1, L, Common)) { /* out of memory, L is now simplicial symbolic */ CHOLMOD(clear_flag) (Common) ; for (i = 0 ; i < n ; i++) { W [i] = 0 ; } return (FALSE) ; } /* L->i and L->x may have moved */ Li = L->i ; Lx = L->x ; } ASSERT (Lp [k] + lnz + 1 <= Lp [Lnext [k]]) ; #ifndef NDEBUG PRINT2 (("\nPrior to sort: lnz "ID" (excluding diagonal)\n", lnz)) ; for (kk = 0 ; kk < lnz ; kk++) { i = Ci [kk] ; PRINT2 (("L ["ID"] kept: "ID" %e\n", kk, i, W [i] / dk)) ; } #endif /* sort Ci */ qsort (Ci, lnz, sizeof (Int), (int (*) (const void *, const void *)) icomp); /* store the kth column of L */ DEBUG (lastrow = k) ; p = Lp [k] ; Lx [p++] = dk ; Lnz [k] = lnz + 1 ; fl += lnz ; for (kk = 0 ; kk < lnz ; kk++, p++) { i = Ci [kk] ; PRINT2 (("L ["ID"] after sort: "ID", %e\n", kk, i, W [i] / dk)) ; ASSERT (i > lastrow) ; Li [p] = i ; Lx [p] = W [i] / dk ; W [i] = 0.0 ; DEBUG (lastrow = i) ; } /* compute DeltaB for updown (in DeltaB) */ if (do_solve) { p = Lp [k] ; pend = p + Lnz [k] ; for (p++ ; p < pend ; p++) { ASSERT (Li [p] > k) ; Nx [Li [p]] -= Lx [p] * xk ; } } /* clear the flag for the update */ mark = CHOLMOD(clear_flag) (Common) ; /* workspaces are now cleared */ ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 2*n, Common)) ; /* ---------------------------------------------------------------------- */ /* update/downdate */ /* ---------------------------------------------------------------------- */ /* update or downdate L (k+1:n, k+1:n) with the vector * C = L (:,k) * sqrt (abs (D [k])). * Do a numeric update if D[k] < 0, numeric downdate otherwise. */ ok = TRUE ; Common->modfl = 0 ; PRINT1 (("rowadd update lnz = "ID"\n", lnz)) ; if (lnz > 0) { do_update = IS_LT_ZERO (dk) ; if (do_update) { dk = -dk ; } sqrt_dk = sqrt (dk) ; p = Lp [k] + 1 ; for (kk = 0 ; kk < lnz ; kk++, p++) { Cx [kk] = Lx [p] * sqrt_dk ; } fl += lnz + 1 ; /* create a n-by-1 sparse matrix to hold the single column */ C = &Cmatrix ; C->nrow = n ; C->ncol = 1 ; C->nzmax = lnz ; C->sorted = TRUE ; C->packed = TRUE ; C->p = Cp ; C->i = Ci ; C->x = Cx ; C->nz = NULL ; C->itype = L->itype ; C->xtype = L->xtype ; C->dtype = L->dtype ; C->z = NULL ; C->stype = 0 ; Cp [0] = 0 ; Cp [1] = lnz ; /* numeric downdate if dk > 0, and optional Lx=b change */ /* workspace: Flag (nrow), Head (nrow+1), W (nrow), Iwork (2*nrow) */ ok = CHOLMOD(updown_mark) (do_update ? (1) : (0), C, colmark, L, X, DeltaB, Common) ; /* clear workspace */ for (kk = 0 ; kk < lnz ; kk++) { Cx [kk] = 0 ; } } Common->modfl += fl ; DEBUG (CHOLMOD(dump_factor) (L, "LDL factorization, L:", Common)) ; ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 2*n, Common)) ; return (ok) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Cholesky/0000755000076500000240000000000013617375001024247 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Cholesky/cholmod_factorize.c0000644000076500000240000003430113524616144030112 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Cholesky/cholmod_factorize =========================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Cholesky Module. Copyright (C) 2005-2006, Timothy A. Davis * The CHOLMOD/Cholesky Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Computes the numerical factorization of a symmetric matrix. The primary * inputs to this routine are a sparse matrix A and the symbolic factor L from * cholmod_analyze or a prior numerical factor L. If A is symmetric, this * routine factorizes A(p,p)+beta*I (beta can be zero), where p is the * fill-reducing permutation (L->Perm). If A is unsymmetric, either * A(p,:)*A(p,:)'+beta*I or A(p,f)*A(p,f)'+beta*I is factorized. The set f and * the nonzero pattern of the matrix A must be the same as the matrix passed to * cholmod_analyze for the supernodal case. For the simplicial case, it can * be different, but it should be the same for best performance. beta is real. * * A simplicial factorization or supernodal factorization is chosen, based on * the type of the factor L. If L->is_super is TRUE, a supernodal LL' * factorization is computed. Otherwise, a simplicial numeric factorization * is computed, either LL' or LDL', depending on Common->final_ll. * * Once the factorization is complete, it can be left as is or optionally * converted into any simplicial numeric type, depending on the * Common->final_* parameters. If converted from a supernodal to simplicial * type, and the Common->final_resymbol parameter is true, then numerically * zero entries in L due to relaxed supernodal amalgamation are removed from * the simplicial factor (they are always left in the supernodal form of L). * Entries that are numerically zero but present in the simplicial symbolic * pattern of L are left in place (that is, the graph of L remains chordal). * This is required for the update/downdate/rowadd/rowdel routines to work * properly. * * workspace: Flag (nrow), Head (nrow+1), * if symmetric: Iwork (2*nrow+2*nsuper) * if unsymmetric: Iwork (2*nrow+MAX(2*nsuper,ncol)) * where nsuper is 0 if simplicial, or the # of relaxed supernodes in * L otherwise (nsuper <= nrow). * if simplicial: W (nrow). * Allocates up to two temporary copies of its input matrix (including * both pattern and numerical values). * * If the matrix is not positive definite the routine returns TRUE, but * sets Common->status to CHOLMOD_NOT_POSDEF and L->minor is set to the * column at which the failure occurred. Columns L->minor to L->n-1 are * set to zero. * * Supports any xtype (pattern, real, complex, or zomplex), except that the * input matrix A cannot be pattern-only. If L is simplicial, its numeric * xtype matches A on output. If L is supernodal, its xtype is real if A is * real, or complex if A is complex or zomplex. */ #ifndef NCHOLESKY #include "cholmod_internal.h" #include "cholmod_cholesky.h" #ifndef NSUPERNODAL #include "cholmod_supernodal.h" #endif /* ========================================================================== */ /* === cholmod_factorize ==================================================== */ /* ========================================================================== */ /* Factorizes PAP' (or PAA'P' if A->stype is 0), using a factor obtained * from cholmod_analyze. The analysis can be re-used simply by calling this * routine a second time with another matrix. A must have the same nonzero * pattern as that passed to cholmod_analyze. */ int CHOLMOD(factorize) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to factorize */ /* ---- in/out --- */ cholmod_factor *L, /* resulting factorization */ /* --------------- */ cholmod_common *Common ) { double zero [2] ; zero [0] = 0 ; zero [1] = 0 ; return (CHOLMOD(factorize_p) (A, zero, NULL, 0, L, Common)) ; } /* ========================================================================== */ /* === cholmod_factorize_p ================================================== */ /* ========================================================================== */ /* Same as cholmod_factorize, but with more options. */ int CHOLMOD(factorize_p) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to factorize */ double beta [2], /* factorize beta*I+A or beta*I+A'*A */ Int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ /* ---- in/out --- */ cholmod_factor *L, /* resulting factorization */ /* --------------- */ cholmod_common *Common ) { cholmod_sparse *S, *F, *A1, *A2 ; Int nrow, ncol, stype, convert, n, nsuper, grow2, status ; size_t s, t, uncol ; int ok = TRUE ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (A, FALSE) ; RETURN_IF_NULL (L, FALSE) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_REAL, CHOLMOD_ZOMPLEX, FALSE) ; RETURN_IF_XTYPE_INVALID (L, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; nrow = A->nrow ; ncol = A->ncol ; n = L->n ; stype = A->stype ; if (L->n != A->nrow) { ERROR (CHOLMOD_INVALID, "A and L dimensions do not match") ; return (FALSE) ; } if (stype != 0 && nrow != ncol) { ERROR (CHOLMOD_INVALID, "matrix invalid") ; return (FALSE) ; } DEBUG (CHOLMOD(dump_sparse) (A, "A for cholmod_factorize", Common)) ; Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ nsuper = (L->is_super ? L->nsuper : 0) ; uncol = ((stype != 0) ? 0 : ncol) ; /* s = 2*nrow + MAX (uncol, 2*nsuper) */ s = CHOLMOD(mult_size_t) (nsuper, 2, &ok) ; s = MAX (uncol, s) ; t = CHOLMOD(mult_size_t) (nrow, 2, &ok) ; s = CHOLMOD(add_size_t) (s, t, &ok) ; if (!ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return (FALSE) ; } CHOLMOD(allocate_work) (nrow, s, 0, Common) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; } S = NULL ; F = NULL ; A1 = NULL ; A2 = NULL ; /* convert to another form when done, if requested */ convert = !(Common->final_asis) ; /* ---------------------------------------------------------------------- */ /* perform supernodal LL' or simplicial LDL' factorization */ /* ---------------------------------------------------------------------- */ if (L->is_super) { #ifndef NSUPERNODAL /* ------------------------------------------------------------------ */ /* supernodal factorization */ /* ------------------------------------------------------------------ */ if (L->ordering == CHOLMOD_NATURAL) { /* -------------------------------------------------------------- */ /* natural ordering */ /* -------------------------------------------------------------- */ if (stype > 0) { /* S = tril (A'), F not needed */ /* workspace: Iwork (nrow) */ A1 = CHOLMOD(ptranspose) (A, 2, NULL, NULL, 0, Common) ; S = A1 ; } else if (stype < 0) { /* This is the fastest option for the natural ordering */ /* S = A; F not needed */ S = A ; } else { /* F = A(:,f)' */ /* workspace: Iwork (nrow) */ /* workspace: Iwork (nrow if no fset; MAX (nrow,ncol) if fset)*/ A1 = CHOLMOD(ptranspose) (A, 2, NULL, fset, fsize, Common) ; F = A1 ; /* S = A */ S = A ; } } else { /* -------------------------------------------------------------- */ /* permute the input matrix before factorization */ /* -------------------------------------------------------------- */ if (stype > 0) { /* This is the fastest option for factoring a permuted matrix */ /* S = tril (PAP'); F not needed */ /* workspace: Iwork (2*nrow) */ A1 = CHOLMOD(ptranspose) (A, 2, L->Perm, NULL, 0, Common) ; S = A1 ; } else if (stype < 0) { /* A2 = triu (PAP') */ /* workspace: Iwork (2*nrow) */ A2 = CHOLMOD(ptranspose) (A, 2, L->Perm, NULL, 0, Common) ; /* S = tril (A2'); F not needed */ /* workspace: Iwork (nrow) */ A1 = CHOLMOD(ptranspose) (A2, 2, NULL, NULL, 0, Common) ; S = A1 ; CHOLMOD(free_sparse) (&A2, Common) ; ASSERT (A2 == NULL) ; } else { /* F = A(p,f)' */ /* workspace: Iwork (nrow if no fset; MAX (nrow,ncol) if fset)*/ A1 = CHOLMOD(ptranspose) (A, 2, L->Perm, fset, fsize, Common) ; F = A1 ; /* S = F' */ /* workspace: Iwork (nrow) */ A2 = CHOLMOD(ptranspose) (F, 2, NULL, NULL, 0, Common) ; S = A2 ; } } /* ------------------------------------------------------------------ */ /* supernodal factorization */ /* ------------------------------------------------------------------ */ /* workspace: Flag (nrow), Head (nrow+1), Iwork (2*nrow+2*nsuper) */ if (Common->status == CHOLMOD_OK) { CHOLMOD(super_numeric) (S, F, beta, L, Common) ; } status = Common->status ; ASSERT (IMPLIES (status >= CHOLMOD_OK, L->xtype != CHOLMOD_PATTERN)) ; /* ------------------------------------------------------------------ */ /* convert to final form, if requested */ /* ------------------------------------------------------------------ */ if (Common->status >= CHOLMOD_OK && convert) { /* workspace: none */ ok = CHOLMOD(change_factor) (L->xtype, Common->final_ll, Common->final_super, Common->final_pack, Common->final_monotonic, L, Common) ; if (ok && Common->final_resymbol && !(L->is_super)) { /* workspace: Flag (nrow), Head (nrow+1), * if symmetric: Iwork (2*nrow) * if unsymmetric: Iwork (2*nrow+ncol) */ CHOLMOD(resymbol_noperm) (S, fset, fsize, Common->final_pack, L, Common) ; } } #else /* ------------------------------------------------------------------ */ /* CHOLMOD Supernodal module not installed */ /* ------------------------------------------------------------------ */ status = CHOLMOD_NOT_INSTALLED ; ERROR (CHOLMOD_NOT_INSTALLED,"Supernodal module not installed") ; #endif } else { /* ------------------------------------------------------------------ */ /* simplicial LDL' factorization */ /* ------------------------------------------------------------------ */ /* Permute the input matrix A if necessary. cholmod_rowfac requires * triu(A) in column form for the symmetric case, and A in column form * for the unsymmetric case (the matrix S). The unsymmetric case * requires A in row form, or equivalently A' in column form (the * matrix F). */ if (L->ordering == CHOLMOD_NATURAL) { /* -------------------------------------------------------------- */ /* natural ordering */ /* -------------------------------------------------------------- */ if (stype > 0) { /* F is not needed, S = A */ S = A ; } else if (stype < 0) { /* F is not needed, S = A' */ /* workspace: Iwork (nrow) */ A2 = CHOLMOD(ptranspose) (A, 2, NULL, NULL, 0, Common) ; S = A2 ; } else { /* F = A (:,f)' */ /* workspace: Iwork (nrow if no fset; MAX (nrow,ncol) if fset)*/ A1 = CHOLMOD(ptranspose) (A, 2, NULL, fset, fsize, Common) ; F = A1 ; S = A ; } } else { /* -------------------------------------------------------------- */ /* permute the input matrix before factorization */ /* -------------------------------------------------------------- */ if (stype > 0) { /* F = tril (A (p,p)') */ /* workspace: Iwork (2*nrow) */ A1 = CHOLMOD(ptranspose) (A, 2, L->Perm, NULL, 0, Common) ; /* A2 = triu (F') */ /* workspace: Iwork (nrow) */ A2 = CHOLMOD(ptranspose) (A1, 2, NULL, NULL, 0, Common) ; /* the symmetric case does not need F, free it and set to NULL*/ CHOLMOD(free_sparse) (&A1, Common) ; } else if (stype < 0) { /* A2 = triu (A (p,p)'), F not needed. This is the fastest * way to factorize a matrix using the simplicial routine * (cholmod_rowfac). */ /* workspace: Iwork (2*nrow) */ A2 = CHOLMOD(ptranspose) (A, 2, L->Perm, NULL, 0, Common) ; } else { /* F = A (p,f)' */ /* workspace: Iwork (nrow if no fset; MAX (nrow,ncol) if fset)*/ A1 = CHOLMOD(ptranspose) (A, 2, L->Perm, fset, fsize, Common) ; F = A1 ; /* A2 = F' */ /* workspace: Iwork (nrow) */ A2 = CHOLMOD(ptranspose) (F, 2, NULL, NULL, 0, Common) ; } S = A2 ; } /* ------------------------------------------------------------------ */ /* simplicial LDL' or LL' factorization */ /* ------------------------------------------------------------------ */ /* factorize beta*I+S (symmetric) or beta*I+F*F' (unsymmetric) */ /* workspace: Flag (nrow), W (nrow), Iwork (2*nrow) */ if (Common->status == CHOLMOD_OK) { grow2 = Common->grow2 ; L->is_ll = BOOLEAN (Common->final_ll) ; if (L->xtype == CHOLMOD_PATTERN && Common->final_pack) { /* allocate a factor with exactly the space required */ Common->grow2 = 0 ; } CHOLMOD(rowfac) (S, F, beta, 0, nrow, L, Common) ; Common->grow2 = grow2 ; } status = Common->status ; /* ------------------------------------------------------------------ */ /* convert to final form, if requested */ /* ------------------------------------------------------------------ */ if (Common->status >= CHOLMOD_OK && convert) { /* workspace: none */ CHOLMOD(change_factor) (L->xtype, L->is_ll, FALSE, Common->final_pack, Common->final_monotonic, L, Common) ; } } /* ---------------------------------------------------------------------- */ /* free A1 and A2 if they exist */ /* ---------------------------------------------------------------------- */ CHOLMOD(free_sparse) (&A1, Common) ; CHOLMOD(free_sparse) (&A2, Common) ; Common->status = MAX (Common->status, status) ; return (Common->status >= CHOLMOD_OK) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Cholesky/cholmod_postorder.c0000644000076500000240000002275013524616144030152 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Cholesky/cholmod_postorder =========================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Cholesky Module. Copyright (C) 2005-2006, Timothy A. Davis * The CHOLMOD/Cholesky Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Compute the postorder of a tree. */ #ifndef NCHOLESKY #include "cholmod_internal.h" #include "cholmod_cholesky.h" /* ========================================================================== */ /* === dfs ================================================================== */ /* ========================================================================== */ /* The code below includes both a recursive and non-recursive depth-first-search * of a tree. The recursive code is simpler, but can lead to stack overflow. * It is left here for reference, to understand what the non-recursive code * is computing. To try the recursive version, uncomment the following * #define, or compile the code with -DRECURSIVE. Be aware that stack * overflow may occur. #define RECURSIVE */ #ifdef RECURSIVE /* recursive version: a working code for reference only, not actual use */ static Int dfs /* return the new value of k */ ( Int p, /* start a DFS at node p */ Int k, /* start the node numbering at k */ Int Post [ ], /* Post ordering, modified on output */ Int Head [ ], /* Head [p] = youngest child of p; EMPTY on output */ Int Next [ ], /* Next [j] = sibling of j; unmodified */ Int Pstack [ ] /* unused */ ) { Int j ; /* start a DFS at each child of node p */ for (j = Head [p] ; j != EMPTY ; j = Next [j]) { /* start a DFS at child node j */ k = dfs (j, k, Post, Head, Next, Pstack) ; } Post [k++] = p ; /* order node p as the kth node */ Head [p] = EMPTY ; /* link list p no longer needed */ return (k) ; /* the next node will be numbered k */ } #else /* non-recursive version for actual use */ static Int dfs /* return the new value of k */ ( Int p, /* start the DFS at a root node p */ Int k, /* start the node numbering at k */ Int Post [ ], /* Post ordering, modified on output */ Int Head [ ], /* Head [p] = youngest child of p; EMPTY on output */ Int Next [ ], /* Next [j] = sibling of j; unmodified */ Int Pstack [ ] /* workspace of size n, undefined on input or output */ ) { Int j, phead ; /* put the root node on the stack */ Pstack [0] = p ; phead = 0 ; /* while the stack is not empty, do: */ while (phead >= 0) { /* grab the node p from top of the stack and get its youngest child j */ p = Pstack [phead] ; j = Head [p] ; if (j == EMPTY) { /* all children of p ordered. remove p from stack and order it */ phead-- ; Post [k++] = p ; /* order node p as the kth node */ } else { /* leave p on the stack. Start a DFS at child node j by putting * j on the stack and removing j from the list of children of p. */ Head [p] = Next [j] ; Pstack [++phead] = j ; } } return (k) ; /* the next node will be numbered k */ } #endif /* ========================================================================== */ /* === cholmod_postorder ==================================================== */ /* ========================================================================== */ /* Postorder a tree. The tree is either an elimination tree (the output from * from cholmod_etree) or a component tree (from cholmod_nested_dissection). * * An elimination tree is a complete tree of n nodes with Parent [j] > j or * Parent [j] = EMPTY if j is a root. On output Post [0..n-1] is a complete * permutation vector. * * A component tree is a subset of 0..n-1. Parent [j] = -2 if node j is not * in the component tree. Parent [j] = EMPTY if j is a root of the component * tree, and Parent [j] is in the range 0 to n-1 if j is in the component * tree but not a root. On output, Post [k] is defined only for nodes in * the component tree. Post [k] = j if node j is the kth node in the * postordered component tree, where k is in the range 0 to the number of * components minus 1. * * Node j is ignored and not included in the postorder if Parent [j] < EMPTY. * * As a result, check_parent (Parent, n,...) may fail on input, since * cholmod_check_parent assumes Parent is an elimination tree. Similarly, * cholmod_check_perm (Post, ...) may fail on output, since Post is a partial * permutation if Parent is a component tree. * * An optional node weight can be given. When starting a postorder at node j, * the children of j are ordered in increasing order of their weight. * If no weights are given (Weight is NULL) then children are ordered in * increasing order of their node number. The weight of a node must be in the * range 0 to n-1. Weights outside that range are silently converted to that * range (weights < 0 are treated as zero, and weights >= n are treated as n-1). * * * workspace: Head (n), Iwork (2*n) */ SuiteSparse_long CHOLMOD(postorder) /* return # of nodes postordered */ ( /* ---- input ---- */ Int *Parent, /* size n. Parent [j] = p if p is the parent of j */ size_t n, Int *Weight, /* size n, optional. Weight [j] is weight of node j */ /* ---- output --- */ Int *Post, /* size n. Post [k] = j is kth in postordered tree */ /* --------------- */ cholmod_common *Common ) { Int *Head, *Next, *Pstack, *Iwork ; Int j, p, k, w, nextj ; size_t s ; int ok = TRUE ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (EMPTY) ; RETURN_IF_NULL (Parent, EMPTY) ; RETURN_IF_NULL (Post, EMPTY) ; Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ /* s = 2*n */ s = CHOLMOD(mult_size_t) (n, 2, &ok) ; if (!ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return (EMPTY) ; } CHOLMOD(allocate_work) (n, s, 0, Common) ; if (Common->status < CHOLMOD_OK) { return (EMPTY) ; } ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ Head = Common->Head ; /* size n+1, initially all EMPTY */ Iwork = Common->Iwork ; Next = Iwork ; /* size n (i/i/l) */ Pstack = Iwork + n ; /* size n (i/i/l) */ /* ---------------------------------------------------------------------- */ /* construct a link list of children for each node */ /* ---------------------------------------------------------------------- */ if (Weight == NULL) { /* in reverse order so children are in ascending order in each list */ for (j = n-1 ; j >= 0 ; j--) { p = Parent [j] ; if (p >= 0 && p < ((Int) n)) { /* add j to the list of children for node p */ Next [j] = Head [p] ; Head [p] = j ; } } /* Head [p] = j if j is the youngest (least-numbered) child of p */ /* Next [j1] = j2 if j2 is the next-oldest sibling of j1 */ } else { /* First, construct a set of link lists according to Weight. * * Whead [w] = j if node j is the first node in bucket w. * Next [j1] = j2 if node j2 follows j1 in a link list. */ Int *Whead = Pstack ; /* use Pstack as workspace for Whead [ */ for (w = 0 ; w < ((Int) n) ; w++) { Whead [w] = EMPTY ; } /* do in forward order, so nodes that ties are ordered by node index */ for (j = 0 ; j < ((Int) n) ; j++) { p = Parent [j] ; if (p >= 0 && p < ((Int) n)) { w = Weight [j] ; w = MAX (0, w) ; w = MIN (w, ((Int) n) - 1) ; /* place node j at the head of link list for weight w */ Next [j] = Whead [w] ; Whead [w] = j ; } } /* traverse weight buckets, placing each node in its parent's list */ for (w = n-1 ; w >= 0 ; w--) { for (j = Whead [w] ; j != EMPTY ; j = nextj) { nextj = Next [j] ; /* put node j in the link list of its parent */ p = Parent [j] ; ASSERT (p >= 0 && p < ((Int) n)) ; Next [j] = Head [p] ; Head [p] = j ; } } /* Whead no longer needed ] */ /* Head [p] = j if j is the lightest child of p */ /* Next [j1] = j2 if j2 is the next-heaviest sibling of j1 */ } /* ---------------------------------------------------------------------- */ /* start a DFS at each root node of the etree */ /* ---------------------------------------------------------------------- */ k = 0 ; for (j = 0 ; j < ((Int) n) ; j++) { if (Parent [j] == EMPTY) { /* j is the root of a tree; start a DFS here */ k = dfs (j, k, Post, Head, Next, Pstack) ; } } /* this would normally be EMPTY already, unless Parent is invalid */ for (j = 0 ; j < ((Int) n) ; j++) { Head [j] = EMPTY ; } PRINT1 (("postordered "ID" nodes\n", k)) ; ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; return (k) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Cholesky/cholmod_rowcolcounts.c0000644000076500000240000004365613524616144030702 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Cholesky/cholmod_rowcolcounts ======================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Cholesky Module. Copyright (C) 2005-2006, Timothy A. Davis * The CHOLMOD/Cholesky Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Compute the row and column counts of the Cholesky factor L of the matrix * A or A*A'. The etree and its postordering must already be computed (see * cholmod_etree and cholmod_postorder) and given as inputs to this routine. * * For the symmetric case (LL'=A), A is accessed by column. Only the lower * triangular part of A is used. Entries not in this part of the matrix are * ignored. This is the same as storing the upper triangular part of A by * rows, with entries in the lower triangular part being ignored. NOTE: this * representation is the TRANSPOSE of the input to cholmod_etree. * * For the unsymmetric case (LL'=AA'), A is accessed by column. Equivalently, * if A is viewed as a matrix in compressed-row form, this routine computes * the row and column counts for L where LL'=A'A. If the input vector f is * present, then F*F' is analyzed instead, where F = A(:,f). * * The set f is held in fset and fsize. * fset = NULL means ":" in MATLAB. fset is ignored. * fset != NULL means f = fset [0..fset-1]. * fset != NULL and fsize = 0 means f is the empty set. * Common->status is set to CHOLMOD_INVALID if fset is invalid. * * In both cases, the columns of A need not be sorted. * A can be packed or unpacked. * * References: * J. Gilbert, E. Ng, B. Peyton, "An efficient algorithm to compute row and * column counts for sparse Cholesky factorization", SIAM J. Matrix Analysis & * Applic., vol 15, 1994, pp. 1075-1091. * * J. Gilbert, X. Li, E. Ng, B. Peyton, "Computing row and column counts for * sparse QR and LU factorization", BIT, vol 41, 2001, pp. 693-710. * * workspace: * if symmetric: Flag (nrow), Iwork (2*nrow) * if unsymmetric: Flag (nrow), Iwork (2*nrow+ncol), Head (nrow+1) * * Supports any xtype (pattern, real, complex, or zomplex). */ #ifndef NCHOLESKY #include "cholmod_internal.h" #include "cholmod_cholesky.h" /* ========================================================================== */ /* === initialize_node ====================================================== */ /* ========================================================================== */ static int initialize_node /* initial work for kth node in postordered etree */ ( Int k, /* at the kth step of the algorithm (and kth node) */ Int Post [ ], /* Post [k] = i, the kth node in postordered etree */ Int Parent [ ], /* Parent [i] is the parent of i in the etree */ Int ColCount [ ], /* ColCount [c] is the current weight of node c */ Int PrevNbr [ ] /* PrevNbr [u] = k if u was last considered at step k */ ) { Int p, parent ; /* determine p, the kth node in the postordered etree */ p = Post [k] ; /* adjust the weight if p is not a root of the etree */ parent = Parent [p] ; if (parent != EMPTY) { ColCount [parent]-- ; } /* flag node p to exclude self edges (p,p) */ PrevNbr [p] = k ; return (p) ; } /* ========================================================================== */ /* === process_edge ========================================================= */ /* ========================================================================== */ /* edge (p,u) is being processed. p < u is a descendant of its ancestor u in * the etree. node p is the kth node in the postordered etree. */ static void process_edge ( Int p, /* process edge (p,u) of the matrix */ Int u, Int k, /* we are at the kth node in the postordered etree */ Int First [ ], /* First [i] = k if the postordering of first * descendent of node i is k */ Int PrevNbr [ ], /* u was last considered at step k = PrevNbr [u] */ Int ColCount [ ], /* ColCount [c] is the current weight of node c */ Int PrevLeaf [ ], /* s = PrevLeaf [u] means that s was the last leaf * seen in the subtree rooted at u. */ Int RowCount [ ], /* RowCount [i] is # of nonzeros in row i of L, * including the diagonal. Not computed if NULL. */ Int SetParent [ ], /* the FIND/UNION data structure, which forms a set * of trees. A root i has i = SetParent [i]. Following * a path from i to the root q of the subtree containing * i means that q is the SetParent representative of i. * All nodes in the tree could have their SetParent * equal to the root q; the tree representation is used * to save time. When a path is traced from i to its * root q, the path is re-traversed to set the SetParent * of the whole path to be the root q. */ Int Level [ ] /* Level [i] = length of path from node i to root */ ) { Int prevleaf, q, s, sparent ; if (First [p] > PrevNbr [u]) { /* p is a leaf of the subtree of u */ ColCount [p]++ ; prevleaf = PrevLeaf [u] ; if (prevleaf == EMPTY) { /* p is the first leaf of subtree of u; RowCount will be incremented * by the length of the path in the etree from p up to u. */ q = u ; } else { /* q = FIND (prevleaf): find the root q of the * SetParent tree containing prevleaf */ for (q = prevleaf ; q != SetParent [q] ; q = SetParent [q]) { ; } /* the root q has been found; re-traverse the path and * perform path compression */ s = prevleaf ; for (s = prevleaf ; s != q ; s = sparent) { sparent = SetParent [s] ; SetParent [s] = q ; } /* adjust the RowCount and ColCount; RowCount will be incremented by * the length of the path from p to the SetParent root q, and * decrement the ColCount of q by one. */ ColCount [q]-- ; } if (RowCount != NULL) { /* if RowCount is being computed, increment it by the length of * the path from p to q */ RowCount [u] += (Level [p] - Level [q]) ; } /* p is a leaf of the subtree of u, so mark PrevLeaf [u] to be p */ PrevLeaf [u] = p ; } /* flag u has having been processed at step k */ PrevNbr [u] = k ; } /* ========================================================================== */ /* === finalize_node ======================================================== */ /* ========================================================================== */ static void finalize_node /* compute UNION (p, Parent [p]) */ ( Int p, Int Parent [ ], /* Parent [p] is the parent of p in the etree */ Int SetParent [ ] /* see process_edge, above */ ) { /* all nodes in the SetParent tree rooted at p now have as their final * root the node Parent [p]. This computes UNION (p, Parent [p]) */ if (Parent [p] != EMPTY) { SetParent [p] = Parent [p] ; } } /* ========================================================================== */ /* === cholmod_rowcolcounts ================================================= */ /* ========================================================================== */ int CHOLMOD(rowcolcounts) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to analyze */ Int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ Int *Parent, /* size nrow. Parent [i] = p if p is the parent of i */ Int *Post, /* size nrow. Post [k] = i if i is the kth node in * the postordered etree. */ /* ---- output --- */ Int *RowCount, /* size nrow. RowCount [i] = # entries in the ith row of * L, including the diagonal. */ Int *ColCount, /* size nrow. ColCount [i] = # entries in the ith * column of L, including the diagonal. */ Int *First, /* size nrow. First [i] = k is the least postordering * of any descendant of i. */ Int *Level, /* size nrow. Level [i] is the length of the path from * i to the root, with Level [root] = 0. */ /* --------------- */ cholmod_common *Common ) { double fl, ff ; Int *Ap, *Ai, *Anz, *PrevNbr, *SetParent, *Head, *PrevLeaf, *Anext, *Ipost, *Iwork ; Int i, j, r, k, len, s, p, pend, inew, stype, nf, anz, inode, parent, nrow, ncol, packed, use_fset, jj ; size_t w ; int ok = TRUE ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (A, FALSE) ; RETURN_IF_NULL (Parent, FALSE) ; RETURN_IF_NULL (Post, FALSE) ; RETURN_IF_NULL (ColCount, FALSE) ; RETURN_IF_NULL (First, FALSE) ; RETURN_IF_NULL (Level, FALSE) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; stype = A->stype ; if (stype > 0) { /* symmetric with upper triangular part not supported */ ERROR (CHOLMOD_INVALID, "symmetric upper not supported") ; return (FALSE) ; } Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ nrow = A->nrow ; /* the number of rows of A */ ncol = A->ncol ; /* the number of columns of A */ /* w = 2*nrow + (stype ? 0 : ncol) */ w = CHOLMOD(mult_size_t) (nrow, 2, &ok) ; w = CHOLMOD(add_size_t) (w, (stype ? 0 : ncol), &ok) ; if (!ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return (FALSE) ; } CHOLMOD(allocate_work) (nrow, w, 0, Common) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; } ASSERT (CHOLMOD(dump_perm) (Post, nrow, nrow, "Post", Common)) ; ASSERT (CHOLMOD(dump_parent) (Parent, nrow, "Parent", Common)) ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ Ap = A->p ; /* size ncol+1, column pointers for A */ Ai = A->i ; /* the row indices of A, of size nz=Ap[ncol+1] */ Anz = A->nz ; packed = A->packed ; ASSERT (IMPLIES (!packed, Anz != NULL)) ; /* ---------------------------------------------------------------------- */ /* get workspace */ /* ---------------------------------------------------------------------- */ Iwork = Common->Iwork ; SetParent = Iwork ; /* size nrow (i/i/l) */ PrevNbr = Iwork + nrow ; /* size nrow (i/i/l) */ Anext = Iwork + 2*((size_t) nrow) ; /* size ncol (i/i/l) (unsym only) */ PrevLeaf = Common->Flag ; /* size nrow */ Head = Common->Head ; /* size nrow+1 (unsym only)*/ /* ---------------------------------------------------------------------- */ /* find the first descendant and level of each node in the tree */ /* ---------------------------------------------------------------------- */ /* First [i] = k if the postordering of first descendent of node i is k */ /* Level [i] = length of path from node i to the root (Level [root] = 0) */ for (i = 0 ; i < nrow ; i++) { First [i] = EMPTY ; } /* postorder traversal of the etree */ for (k = 0 ; k < nrow ; k++) { /* node i of the etree is the kth node in the postordered etree */ i = Post [k] ; /* i is a leaf if First [i] is still EMPTY */ /* ColCount [i] starts at 1 if i is a leaf, zero otherwise */ ColCount [i] = (First [i] == EMPTY) ? 1 : 0 ; /* traverse the path from node i to the root, stopping if we find a * node r whose First [r] is already defined. */ len = 0 ; for (r = i ; (r != EMPTY) && (First [r] == EMPTY) ; r = Parent [r]) { First [r] = k ; len++ ; } if (r == EMPTY) { /* we hit a root node, the level of which is zero */ len-- ; } else { /* we stopped at node r, where Level [r] is already defined */ len += Level [r] ; } /* re-traverse the path from node i to r; set the level of each node */ for (s = i ; s != r ; s = Parent [s]) { Level [s] = len-- ; } } /* ---------------------------------------------------------------------- */ /* AA' case: sort columns of A according to first postordered row index */ /* ---------------------------------------------------------------------- */ fl = 0.0 ; if (stype == 0) { /* [ use PrevNbr [0..nrow-1] as workspace for Ipost */ Ipost = PrevNbr ; /* Ipost [i] = k if i is the kth node in the postordered etree. */ for (k = 0 ; k < nrow ; k++) { Ipost [Post [k]] = k ; } use_fset = (fset != NULL) ; if (use_fset) { nf = fsize ; /* clear Anext to check fset */ for (j = 0 ; j < ncol ; j++) { Anext [j] = -2 ; } /* find the first postordered row in each column of A (post,f) * and place the column in the corresponding link list */ for (jj = 0 ; jj < nf ; jj++) { j = fset [jj] ; if (j < 0 || j > ncol || Anext [j] != -2) { /* out-of-range or duplicate entry in fset */ ERROR (CHOLMOD_INVALID, "fset invalid") ; return (FALSE) ; } /* flag column j as having been seen */ Anext [j] = EMPTY ; } /* fset is now valid */ ASSERT (CHOLMOD(dump_perm) (fset, nf, ncol, "fset", Common)) ; } else { nf = ncol ; } for (jj = 0 ; jj < nf ; jj++) { j = (use_fset) ? (fset [jj]) : jj ; /* column j is in the fset; find the smallest row (if any) */ p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; ff = (double) MAX (0, pend - p) ; fl += ff*ff + ff ; if (pend > p) { k = Ipost [Ai [p]] ; for ( ; p < pend ; p++) { inew = Ipost [Ai [p]] ; k = MIN (k, inew) ; } /* place column j in link list k */ ASSERT (k >= 0 && k < nrow) ; Anext [j] = Head [k] ; Head [k] = j ; } } /* Ipost no longer needed for inverse postordering ] * Head [k] contains a link list of all columns whose first * postordered row index is equal to k, for k = 0 to nrow-1. */ } /* ---------------------------------------------------------------------- */ /* compute the row counts and node weights */ /* ---------------------------------------------------------------------- */ if (RowCount != NULL) { for (i = 0 ; i < nrow ; i++) { RowCount [i] = 1 ; } } for (i = 0 ; i < nrow ; i++) { PrevLeaf [i] = EMPTY ; PrevNbr [i] = EMPTY ; SetParent [i] = i ; /* every node is in its own set, by itself */ } if (stype != 0) { /* ------------------------------------------------------------------ */ /* symmetric case: LL' = A */ /* ------------------------------------------------------------------ */ /* also determine the number of entries in triu(A) */ anz = nrow ; for (k = 0 ; k < nrow ; k++) { /* j is the kth node in the postordered etree */ j = initialize_node (k, Post, Parent, ColCount, PrevNbr) ; /* for all nonzeros A(i,j) below the diagonal, in column j of A */ p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { i = Ai [p] ; if (i > j) { /* j is a descendant of i in etree(A) */ anz++ ; process_edge (j, i, k, First, PrevNbr, ColCount, PrevLeaf, RowCount, SetParent, Level) ; } } /* update SetParent: UNION (j, Parent [j]) */ finalize_node (j, Parent, SetParent) ; } Common->anz = anz ; } else { /* ------------------------------------------------------------------ */ /* unsymmetric case: LL' = AA' */ /* ------------------------------------------------------------------ */ for (k = 0 ; k < nrow ; k++) { /* inode is the kth node in the postordered etree */ inode = initialize_node (k, Post, Parent, ColCount, PrevNbr) ; /* for all cols j whose first postordered row is k: */ for (j = Head [k] ; j != EMPTY ; j = Anext [j]) { /* k is the first postordered row in column j of A */ /* for all rows i in column j: */ p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { i = Ai [p] ; /* has i already been considered at this step k */ if (PrevNbr [i] < k) { /* inode is a descendant of i in etree(AA') */ /* process edge (inode,i) and set PrevNbr[i] to k */ process_edge (inode, i, k, First, PrevNbr, ColCount, PrevLeaf, RowCount, SetParent, Level) ; } } } /* clear link list k */ Head [k] = EMPTY ; /* update SetParent: UNION (inode, Parent [inode]) */ finalize_node (inode, Parent, SetParent) ; } } /* ---------------------------------------------------------------------- */ /* finish computing the column counts */ /* ---------------------------------------------------------------------- */ for (j = 0 ; j < nrow ; j++) { parent = Parent [j] ; if (parent != EMPTY) { /* add the ColCount of j to its parent */ ColCount [parent] += ColCount [j] ; } } /* ---------------------------------------------------------------------- */ /* clear workspace */ /* ---------------------------------------------------------------------- */ Common->mark = EMPTY ; /* CHOLMOD(clear_flag) (Common) ; */ CHOLMOD_CLEAR_FLAG (Common) ; ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; /* ---------------------------------------------------------------------- */ /* flop count and nnz(L) for subsequent LL' numerical factorization */ /* ---------------------------------------------------------------------- */ /* use double to avoid integer overflow. lnz cannot be NaN. */ Common->aatfl = fl ; Common->lnz = 0. ; fl = 0 ; for (j = 0 ; j < nrow ; j++) { ff = (double) (ColCount [j]) ; Common->lnz += ff ; fl += ff*ff ; } Common->fl = fl ; PRINT1 (("rowcol fl %g lnz %g\n", Common->fl, Common->lnz)) ; return (TRUE) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Cholesky/cholmod_rcond.c0000644000076500000240000001144213524616144027232 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Cholesky/cholmod_rcond =============================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Cholesky Module. Copyright (C) 2005-2006, Timothy A. Davis * The CHOLMOD/Cholesky Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Return a rough estimate of the reciprocal of the condition number: * the minimum entry on the diagonal of L (or absolute entry of D for an LDL' * factorization) divided by the maximum entry (squared for LL'). L can be * real, complex, or zomplex. Returns -1 on error, 0 if the matrix is singular * or has a zero entry on the diagonal of L, 1 if the matrix is 0-by-0, or * min(diag(L))/max(diag(L)) otherwise. Never returns NaN; if L has a NaN on * the diagonal it returns zero instead. * * For an LL' factorization, (min(diag(L))/max(diag(L)))^2 is returned. * For an LDL' factorization, (min(diag(D))/max(diag(D))) is returned. */ #ifndef NCHOLESKY #include "cholmod_internal.h" #include "cholmod_cholesky.h" /* ========================================================================== */ /* === LMINMAX ============================================================== */ /* ========================================================================== */ /* Update lmin and lmax for one entry L(j,j) */ #define FIRST_LMINMAX(Ljj,lmin,lmax) \ { \ double ljj = Ljj ; \ if (IS_NAN (ljj)) \ { \ return (0) ; \ } \ lmin = ljj ; \ lmax = ljj ; \ } #define LMINMAX(Ljj,lmin,lmax) \ { \ double ljj = Ljj ; \ if (IS_NAN (ljj)) \ { \ return (0) ; \ } \ if (ljj < lmin) \ { \ lmin = ljj ; \ } \ else if (ljj > lmax) \ { \ lmax = ljj ; \ } \ } /* ========================================================================== */ /* === cholmod_rcond ======================================================== */ /* ========================================================================== */ double CHOLMOD(rcond) /* return min(diag(L)) / max(diag(L)) */ ( /* ---- input ---- */ cholmod_factor *L, /* --------------- */ cholmod_common *Common ) { double lmin, lmax, rcond ; double *Lx ; Int *Lpi, *Lpx, *Super, *Lp ; Int n, e, nsuper, s, k1, k2, psi, psend, psx, nsrow, nscol, jj, j ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (EMPTY) ; RETURN_IF_NULL (L, EMPTY) ; RETURN_IF_XTYPE_INVALID (L, CHOLMOD_REAL, CHOLMOD_ZOMPLEX, EMPTY) ; Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ n = L->n ; if (n == 0) { return (1) ; } if (L->minor < L->n) { return (0) ; } e = (L->xtype == CHOLMOD_COMPLEX) ? 2 : 1 ; if (L->is_super) { /* L is supernodal */ nsuper = L->nsuper ; /* number of supernodes in L */ Lpi = L->pi ; /* column pointers for integer pattern */ Lpx = L->px ; /* column pointers for numeric values */ Super = L->super ; /* supernode sizes */ Lx = L->x ; /* numeric values */ FIRST_LMINMAX (Lx [0], lmin, lmax) ; /* first diagonal entry of L */ for (s = 0 ; s < nsuper ; s++) { k1 = Super [s] ; /* first column in supernode s */ k2 = Super [s+1] ; /* last column in supernode is k2-1 */ psi = Lpi [s] ; /* first row index is L->s [psi] */ psend = Lpi [s+1] ; /* last row index is L->s [psend-1] */ psx = Lpx [s] ; /* first numeric entry is Lx [psx] */ nsrow = psend - psi ; /* supernode is nsrow-by-nscol */ nscol = k2 - k1 ; for (jj = 0 ; jj < nscol ; jj++) { LMINMAX (Lx [e * (psx + jj + jj*nsrow)], lmin, lmax) ; } } } else { /* L is simplicial */ Lp = L->p ; Lx = L->x ; if (L->is_ll) { /* LL' factorization */ FIRST_LMINMAX (Lx [Lp [0]], lmin, lmax) ; for (j = 1 ; j < n ; j++) { LMINMAX (Lx [e * Lp [j]], lmin, lmax) ; } } else { /* LDL' factorization, the diagonal might be negative */ FIRST_LMINMAX (fabs (Lx [Lp [0]]), lmin, lmax) ; for (j = 1 ; j < n ; j++) { LMINMAX (fabs (Lx [e * Lp [j]]), lmin, lmax) ; } } } rcond = lmin / lmax ; if (L->is_ll) { rcond = rcond*rcond ; } return (rcond) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Cholesky/cholmod_resymbol.c0000644000076500000240000004441413524616144027766 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Cholesky/cholmod_resymbol ============================================ */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Cholesky Module. Copyright (C) 2005-2006, Timothy A. Davis * The CHOLMOD/Cholesky Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Recompute the symbolic pattern of L. Entries not in the symbolic pattern * are dropped. L->Perm can be used (or not) to permute the input matrix A. * * These routines are used after a supernodal factorization is converted into * a simplicial one, to remove zero entries that were added due to relaxed * supernode amalgamation. They can also be used after a series of downdates * to remove entries that would no longer be present if the matrix were * factorized from scratch. A downdate (cholmod_updown) does not remove any * entries from L. * * workspace: Flag (nrow), Head (nrow+1), * if symmetric: Iwork (2*nrow) * if unsymmetric: Iwork (2*nrow+ncol). * Allocates up to 2 copies of its input matrix A (pattern only). */ #ifndef NCHOLESKY #include "cholmod_internal.h" #include "cholmod_cholesky.h" /* ========================================================================== */ /* === cholmod_resymbol ===================================================== */ /* ========================================================================== */ /* Remove entries from L that are not in the factorization of P*A*P', P*A*A'*P', * or P*F*F'*P' (depending on A->stype and whether fset is NULL or not). * * cholmod_resymbol is the same as cholmod_resymbol_noperm, except that it * first permutes A according to L->Perm. A can be upper/lower/unsymmetric, * in contrast to cholmod_resymbol_noperm (which can be lower or unsym). */ int CHOLMOD(resymbol) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to analyze */ Int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ int pack, /* if TRUE, pack the columns of L */ /* ---- in/out --- */ cholmod_factor *L, /* factorization, entries pruned on output */ /* --------------- */ cholmod_common *Common ) { cholmod_sparse *H, *F, *G ; Int stype, nrow, ncol ; size_t s ; int ok = TRUE ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (A, FALSE) ; RETURN_IF_NULL (L, FALSE) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; RETURN_IF_XTYPE_INVALID (L, CHOLMOD_REAL, CHOLMOD_ZOMPLEX, FALSE) ; Common->status = CHOLMOD_OK ; if (L->is_super) { /* cannot operate on a supernodal factorization */ ERROR (CHOLMOD_INVALID, "cannot operate on supernodal L") ; return (FALSE) ; } if (L->n != A->nrow) { /* dimensions must agree */ ERROR (CHOLMOD_INVALID, "A and L dimensions do not match") ; return (FALSE) ; } /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ stype = A->stype ; nrow = A->nrow ; ncol = A->ncol ; /* s = 2*nrow + (stype ? 0 : ncol) */ s = CHOLMOD(mult_size_t) (nrow, 2, &ok) ; s = CHOLMOD(add_size_t) (s, (stype ? 0 : ncol), &ok) ; if (!ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return (FALSE) ; } CHOLMOD(allocate_work) (nrow, s, 0, Common) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; } /* ---------------------------------------------------------------------- */ /* permute the input matrix if necessary */ /* ---------------------------------------------------------------------- */ H = NULL ; G = NULL ; if (stype > 0) { if (L->ordering == CHOLMOD_NATURAL) { /* F = triu(A)' */ /* workspace: Iwork (nrow) */ G = CHOLMOD(ptranspose) (A, 0, NULL, NULL, 0, Common) ; } else { /* F = triu(A(p,p))' */ /* workspace: Iwork (2*nrow) */ G = CHOLMOD(ptranspose) (A, 0, L->Perm, NULL, 0, Common) ; } F = G ; } else if (stype < 0) { if (L->ordering == CHOLMOD_NATURAL) { F = A ; } else { /* G = triu(A(p,p))' */ /* workspace: Iwork (2*nrow) */ G = CHOLMOD(ptranspose) (A, 0, L->Perm, NULL, 0, Common) ; /* H = G' */ /* workspace: Iwork (nrow) */ H = CHOLMOD(ptranspose) (G, 0, NULL, NULL, 0, Common) ; F = H ; } } else { if (L->ordering == CHOLMOD_NATURAL) { F = A ; } else { /* G = A(p,f)' */ /* workspace: Iwork (nrow if no fset; MAX (nrow,ncol) if fset)*/ G = CHOLMOD(ptranspose) (A, 0, L->Perm, fset, fsize, Common) ; /* H = G' */ /* workspace: Iwork (ncol) */ H = CHOLMOD(ptranspose) (G, 0, NULL, NULL, 0, Common) ; F = H ; } } /* No need to check for failure here. cholmod_resymbol_noperm will return * FALSE if F is NULL. */ /* ---------------------------------------------------------------------- */ /* resymbol */ /* ---------------------------------------------------------------------- */ ok = CHOLMOD(resymbol_noperm) (F, fset, fsize, pack, L, Common) ; /* ---------------------------------------------------------------------- */ /* free the temporary matrices, if they exist */ /* ---------------------------------------------------------------------- */ CHOLMOD(free_sparse) (&H, Common) ; CHOLMOD(free_sparse) (&G, Common) ; return (ok) ; } /* ========================================================================== */ /* === cholmod_resymbol_noperm ============================================== */ /* ========================================================================== */ /* Redo symbolic LDL' or LL' factorization of I + F*F' or I+A, where F=A(:,f). * * L already exists, but is a superset of the true dynamic pattern (simple * column downdates and row deletions haven't pruned anything). Just redo the * symbolic factorization and drop entries that are no longer there. The * diagonal is not modified. The number of nonzeros in column j of L * (L->nz[j]) can decrease. The column pointers (L->p[j]) remain unchanged if * pack is FALSE or if L is not monotonic. Otherwise, the columns of L are * packed in place. * * For the symmetric case, the columns of the lower triangular part of A * are accessed by column. NOTE that this the transpose of the general case. * * For the unsymmetric case, F=A(:,f) is accessed by column. * * A need not be sorted, and can be packed or unpacked. If L->Perm is not * identity, then A must already be permuted according to the permutation used * to factorize L. The advantage of using this routine is that it does not * need to create permuted copies of A first. * * This routine can be called if L is only partially factored via cholmod_rowfac * since all it does is prune. If an entry is in F*F' or A, but not in L, it * isn't added to L. * * L must be simplicial LDL' or LL'; it cannot be supernodal or symbolic. * * The set f is held in fset and fsize. * fset = NULL means ":" in MATLAB. fset is ignored. * fset != NULL means f = fset [0..fset-1]. * fset != NULL and fsize = 0 means f is the empty set. * There can be no duplicates in fset. * Common->status is set to CHOLMOD_INVALID if fset is invalid. * * workspace: Flag (nrow), Head (nrow+1), * if symmetric: Iwork (2*nrow) * if unsymmetric: Iwork (2*nrow+ncol). * Unlike cholmod_resymbol, this routine does not allocate any temporary * copies of its input matrix. */ int CHOLMOD(resymbol_noperm) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to analyze */ Int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ int pack, /* if TRUE, pack the columns of L */ /* ---- in/out --- */ cholmod_factor *L, /* factorization, entries pruned on output */ /* --------------- */ cholmod_common *Common ) { double *Lx, *Lz ; Int i, j, k, row, parent, p, pend, pdest, ncol, apacked, sorted, nrow, nf, use_fset, mark, jj, stype, xtype ; Int *Ap, *Ai, *Anz, *Li, *Lp, *Lnz, *Flag, *Head, *Link, *Anext, *Iwork ; size_t s ; int ok = TRUE ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (A, FALSE) ; RETURN_IF_NULL (L, FALSE) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; RETURN_IF_XTYPE_INVALID (L, CHOLMOD_REAL, CHOLMOD_ZOMPLEX, FALSE) ; ncol = A->ncol ; nrow = A->nrow ; stype = A->stype ; ASSERT (IMPLIES (stype != 0, nrow == ncol)) ; if (stype > 0) { /* symmetric, with upper triangular part, not supported */ ERROR (CHOLMOD_INVALID, "symmetric upper not supported ") ; return (FALSE) ; } if (L->is_super) { /* cannot operate on a supernodal or symbolic factorization */ ERROR (CHOLMOD_INVALID, "cannot operate on supernodal L") ; return (FALSE) ; } if (L->n != A->nrow) { /* dimensions must agree */ ERROR (CHOLMOD_INVALID, "A and L dimensions do not match") ; return (FALSE) ; } Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ /* s = 2*nrow + (stype ? 0 : ncol) */ s = CHOLMOD(mult_size_t) (nrow, 2, &ok) ; if (stype != 0) { s = CHOLMOD(add_size_t) (s, ncol, &ok) ; } if (!ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return (FALSE) ; } CHOLMOD(allocate_work) (nrow, s, 0, Common) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; /* out of memory */ } ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ Ai = A->i ; Ap = A->p ; Anz = A->nz ; apacked = A->packed ; sorted = A->sorted ; Li = L->i ; Lx = L->x ; Lz = L->z ; Lp = L->p ; Lnz = L->nz ; xtype = L->xtype ; /* If L is monotonic on input, then it can be packed or * unpacked on output, depending on the pack input parameter. */ /* cannot pack a non-monotonic matrix */ if (!(L->is_monotonic)) { pack = FALSE ; } ASSERT (L->nzmax >= (size_t) (Lp [L->n])) ; pdest = 0 ; PRINT1 (("\n\n===================== Resymbol pack %d Apacked %d\n", pack, A->packed)) ; ASSERT (CHOLMOD(dump_sparse) (A, "ReSymbol A:", Common) >= 0) ; DEBUG (CHOLMOD(dump_factor) (L, "ReSymbol initial L (i, x):", Common)) ; /* ---------------------------------------------------------------------- */ /* get workspace */ /* ---------------------------------------------------------------------- */ Flag = Common->Flag ; /* size nrow */ Head = Common->Head ; /* size nrow+1 */ Iwork = Common->Iwork ; Link = Iwork ; /* size nrow (i/i/l) [ */ Lnz = Iwork + nrow ; /* size nrow (i/i/l), if L not packed */ Anext = Iwork + 2*((size_t) nrow) ; /* size ncol (i/i/l), unsym. only */ for (j = 0 ; j < nrow ; j++) { Link [j] = EMPTY ; } /* use Lnz in L itself */ Lnz = L->nz ; ASSERT (Lnz != NULL) ; /* ---------------------------------------------------------------------- */ /* for the unsymmetric case, queue each column of A (:,f) */ /* ---------------------------------------------------------------------- */ /* place each column of the basis set on the link list corresponding to */ /* the smallest row index in that column */ if (stype == 0) { use_fset = (fset != NULL) ; if (use_fset) { nf = fsize ; /* This is the only O(ncol) loop in cholmod_resymbol. * It is required only to check the fset. */ for (j = 0 ; j < ncol ; j++) { Anext [j] = -2 ; } for (jj = 0 ; jj < nf ; jj++) { j = fset [jj] ; if (j < 0 || j > ncol || Anext [j] != -2) { /* out-of-range or duplicate entry in fset */ ERROR (CHOLMOD_INVALID, "fset invalid") ; ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; return (FALSE) ; } /* flag column j as having been seen */ Anext [j] = EMPTY ; } /* the fset is now valid */ ASSERT (CHOLMOD(dump_perm) (fset, nf, ncol, "fset", Common)) ; } else { nf = ncol ; } for (jj = 0 ; jj < nf ; jj++) { j = (use_fset) ? (fset [jj]) : jj ; /* column j is the fset; find the smallest row (if any) */ p = Ap [j] ; pend = (apacked) ? (Ap [j+1]) : (p + Anz [j]) ; if (pend > p) { k = Ai [p] ; if (!sorted) { for ( ; p < pend ; p++) { k = MIN (k, Ai [p]) ; } } /* place column j on link list k */ ASSERT (k >= 0 && k < nrow) ; Anext [j] = Head [k] ; Head [k] = j ; } } } /* ---------------------------------------------------------------------- */ /* recompute symbolic LDL' factorization */ /* ---------------------------------------------------------------------- */ for (k = 0 ; k < nrow ; k++) { #ifndef NDEBUG PRINT1 (("\n\n================== Initial column k = "ID"\n", k)) ; for (p = Lp [k] ; p < Lp [k] + Lnz [k] ; p++) { PRINT1 ((" row: "ID" value: ", Li [p])) ; PRINT1 (("\n")) ; } PRINT1 (("Recomputing LDL, column k = "ID"\n", k)) ; #endif /* ------------------------------------------------------------------ */ /* compute column k of I+F*F' or I+A */ /* ------------------------------------------------------------------ */ /* flag the diagonal entry */ /* mark = CHOLMOD(clear_flag) (Common) ; */ CHOLMOD_CLEAR_FLAG (Common) ; mark = Common->mark ; Flag [k] = mark ; PRINT1 ((" row: "ID" (diagonal)\n", k)) ; if (stype != 0) { /* merge column k of A into Flag (lower triangular part only) */ p = Ap [k] ; pend = (apacked) ? (Ap [k+1]) : (p + Anz [k]) ; for ( ; p < pend ; p++) { i = Ai [p] ; if (i > k) { Flag [i] = mark ; } } } else { /* for each column j whos first row index is in row k */ for (j = Head [k] ; j != EMPTY ; j = Anext [j]) { /* merge column j of A into Flag */ PRINT1 ((" ---- A column "ID"\n", j)) ; p = Ap [j] ; pend = (apacked) ? (Ap [j+1]) : (p + Anz [j]) ; PRINT1 ((" length "ID" adding\n", pend-p)) ; for ( ; p < pend ; p++) { #ifndef NDEBUG ASSERT (Ai [p] >= k && Ai [p] < nrow) ; if (Flag [Ai [p]] < mark) PRINT1 ((" row "ID"\n", Ai [p])) ; #endif Flag [Ai [p]] = mark ; } } /* clear the kth link list */ Head [k] = EMPTY ; } /* ------------------------------------------------------------------ */ /* compute pruned pattern of kth column of L = union of children */ /* ------------------------------------------------------------------ */ /* for each column j of L whose parent is k */ for (j = Link [k] ; j != EMPTY ; j = Link [j]) { /* merge column j of L into Flag */ PRINT1 ((" ---- L column "ID"\n", k)) ; ASSERT (j < k) ; ASSERT (Lnz [j] > 0) ; p = Lp [j] ; pend = p + Lnz [j] ; ASSERT (Li [p] == j && Li [p+1] == k) ; p++ ; /* skip past the diagonal entry */ for ( ; p < pend ; p++) { /* add to pattern */ ASSERT (Li [p] >= k && Li [p] < nrow) ; Flag [Li [p]] = mark ; } } /* ------------------------------------------------------------------ */ /* prune the kth column of L */ /* ------------------------------------------------------------------ */ PRINT1 (("Final column of L:\n")) ; p = Lp [k] ; pend = p + Lnz [k] ; if (pack) { /* shift column k upwards */ Lp [k] = pdest ; } else { /* leave column k in place, just reduce Lnz [k] */ pdest = p ; } for ( ; p < pend ; p++) { ASSERT (pdest < pend) ; ASSERT (pdest <= p) ; row = Li [p] ; ASSERT (row >= k && row < nrow) ; if (Flag [row] == mark) { /* keep this entry */ Li [pdest] = row ; if (xtype == CHOLMOD_REAL) { Lx [pdest] = Lx [p] ; } else if (xtype == CHOLMOD_COMPLEX) { Lx [2*pdest ] = Lx [2*p ] ; Lx [2*pdest+1] = Lx [2*p+1] ; } else if (xtype == CHOLMOD_ZOMPLEX) { Lx [pdest] = Lx [p] ; Lz [pdest] = Lz [p] ; } pdest++ ; } } /* ------------------------------------------------------------------ */ /* prepare this column for its parent */ /* ------------------------------------------------------------------ */ Lnz [k] = pdest - Lp [k] ; PRINT1 ((" L("ID") length "ID"\n", k, Lnz [k])) ; ASSERT (Lnz [k] > 0) ; /* parent is the first entry in the column after the diagonal */ parent = (Lnz [k] > 1) ? (Li [Lp [k] + 1]) : EMPTY ; PRINT1 (("parent ("ID") = "ID"\n", k, parent)) ; ASSERT ((parent > k && parent < nrow) || (parent == EMPTY)) ; if (parent != EMPTY) { Link [k] = Link [parent] ; Link [parent] = k ; } } /* done using Iwork for Link, Lnz (if needed), and Anext ] */ /* ---------------------------------------------------------------------- */ /* convert L to packed, if requested */ /* ---------------------------------------------------------------------- */ if (pack) { /* finalize Lp */ Lp [nrow] = pdest ; /* Shrink L to be just large enough. It cannot fail. */ /* workspace: none */ ASSERT ((size_t) (Lp [nrow]) <= L->nzmax) ; CHOLMOD(reallocate_factor) (Lp [nrow], L, Common) ; ASSERT (Common->status >= CHOLMOD_OK) ; } /* ---------------------------------------------------------------------- */ /* clear workspace */ /* ---------------------------------------------------------------------- */ /* CHOLMOD(clear_flag) (Common) ; */ CHOLMOD_CLEAR_FLAG (Common) ; DEBUG (CHOLMOD(dump_factor) (L, "ReSymbol final L (i, x):", Common)) ; ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; return (TRUE) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Cholesky/t_cholmod_solve.c0000644000076500000240000001242313524616144027600 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Cholesky/t_cholmod_solve ============================================= */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Cholesky Module. Copyright (C) 2005-2013, Timothy A. Davis * The CHOLMOD/Cholesky Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Template routine for cholmod_solve. Supports any numeric xtype (real, * complex, or zomplex). The xtypes of all matrices (L and Y) must match. */ #include "cholmod_template.h" /* ========================================================================== */ /* === simplicial template solvers ========================================== */ /* ========================================================================== */ /* LL': solve Lx=b with non-unit diagonal */ #define LL #include "t_cholmod_lsolve.c" /* LDL': solve LDx=b */ #define LD #include "t_cholmod_lsolve.c" /* LDL': solve Lx=b with unit diagonal */ #include "t_cholmod_lsolve.c" /* LL': solve L'x=b with non-unit diagonal */ #define LL #include "t_cholmod_ltsolve.c" /* LDL': solve DL'x=b */ #define LD #include "t_cholmod_ltsolve.c" /* LDL': solve L'x=b with unit diagonal */ #include "t_cholmod_ltsolve.c" /* ========================================================================== */ /* === t_ldl_dsolve ========================================================= */ /* ========================================================================== */ /* Solve Dx=b for an LDL' factorization, where Y holds b' on input and x' on * output. * * The number of right-hand-sides (nrhs) is not restricted, even if Yseti * is present. */ static void TEMPLATE (ldl_dsolve) ( cholmod_factor *L, cholmod_dense *Y, /* nr-by-n with leading dimension nr */ Int *Yseti, Int ysetlen ) { double d [1] ; double *Lx, *Yx, *Yz ; Int *Lp ; Int n, nrhs, k, p, k1, k2, kk, kkiters ; ASSERT (L->xtype == Y->xtype) ; /* L and Y must have the same xtype */ ASSERT (L->n == Y->ncol) ; /* dimensions must match */ ASSERT (Y->nrow == Y->d) ; /* leading dimension of Y = # rows of Y */ ASSERT (L->xtype != CHOLMOD_PATTERN) ; /* L is not symbolic */ ASSERT (!(L->is_super) && !(L->is_ll)) ; /* L is simplicial LDL' */ nrhs = Y->nrow ; n = L->n ; Lp = L->p ; Lx = L->x ; Yx = Y->x ; Yz = Y->z ; kkiters = Yseti ? ysetlen : n ; for (kk = 0 ; kk < kkiters ; kk++) { k = Yseti ? Yseti [kk] : kk ; k1 = k*nrhs ; k2 = (k+1)*nrhs ; ASSIGN_REAL (d,0, Lx,Lp[k]) ; for (p = k1 ; p < k2 ; p++) { DIV_REAL (Yx,Yz,p, Yx,Yz,p, d,0) ; } } } /* ========================================================================== */ /* === t_simplicial_solver ================================================== */ /* ========================================================================== */ /* Solve a linear system, where Y' contains the (array-transposed) right-hand * side on input, and the solution on output. No permutations are applied; * these must have already been applied to Y on input. * * Yseti [0..ysetlen-1] is an optional list of indices from * cholmod_lsolve_pattern. The solve is performed only on the columns of L * corresponding to entries in Yseti. Ignored if NULL. If present, most * functions require that Y' consist of a single dense column. */ static void TEMPLATE (simplicial_solver) ( int sys, /* system to solve */ cholmod_factor *L, /* factor to use, a simplicial LL' or LDL' */ cholmod_dense *Y, /* right-hand-side on input, solution on output */ Int *Yseti, Int ysetlen ) { if (L->is_ll) { /* The factorization is LL' */ if (sys == CHOLMOD_A || sys == CHOLMOD_LDLt) { /* Solve Ax=b or LL'x=b */ TEMPLATE (ll_lsolve_k) (L, Y, Yseti, ysetlen) ; TEMPLATE (ll_ltsolve_k) (L, Y, Yseti, ysetlen) ; } else if (sys == CHOLMOD_L || sys == CHOLMOD_LD) { /* Solve Lx=b */ TEMPLATE (ll_lsolve_k) (L, Y, Yseti, ysetlen) ; } else if (sys == CHOLMOD_Lt || sys == CHOLMOD_DLt) { /* Solve L'x=b */ TEMPLATE (ll_ltsolve_k) (L, Y, Yseti, ysetlen) ; } } else { /* The factorization is LDL' */ if (sys == CHOLMOD_A || sys == CHOLMOD_LDLt) { /* Solve Ax=b or LDL'x=b */ TEMPLATE (ldl_lsolve_k) (L, Y, Yseti, ysetlen) ; TEMPLATE (ldl_dltsolve_k) (L, Y, Yseti, ysetlen) ; } else if (sys == CHOLMOD_LD) { /* Solve LDx=b */ TEMPLATE (ldl_ldsolve_k) (L, Y, Yseti, ysetlen) ; } else if (sys == CHOLMOD_L) { /* Solve Lx=b */ TEMPLATE (ldl_lsolve_k) (L, Y, Yseti, ysetlen) ; } else if (sys == CHOLMOD_Lt) { /* Solve L'x=b */ TEMPLATE (ldl_ltsolve_k) (L, Y, Yseti, ysetlen) ; } else if (sys == CHOLMOD_DLt) { /* Solve DL'x=b */ TEMPLATE (ldl_dltsolve_k) (L, Y, Yseti, ysetlen) ; } else if (sys == CHOLMOD_D) { /* Solve Dx=b */ TEMPLATE (ldl_dsolve) (L, Y, Yseti, ysetlen) ; } } } #undef PATTERN #undef REAL #undef COMPLEX #undef ZOMPLEX python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Cholesky/cholmod_etree.c0000644000076500000240000001577013524616144027241 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Cholesky/cholmod_etree =============================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Cholesky Module. Copyright (C) 2005-2006, Timothy A. Davis * The CHOLMOD/Cholesky Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Compute the elimination tree of A or A'*A * * In the symmetric case, the upper triangular part of A is used. Entries not * in this part of the matrix are ignored. Computing the etree of a symmetric * matrix from just its lower triangular entries is not supported. * * In the unsymmetric case, all of A is used, and the etree of A'*A is computed. * * References: * * J. Liu, "A compact row storage scheme for Cholesky factors", ACM Trans. * Math. Software, vol 12, 1986, pp. 127-148. * * J. Liu, "The role of elimination trees in sparse factorization", SIAM J. * Matrix Analysis & Applic., vol 11, 1990, pp. 134-172. * * J. Gilbert, X. Li, E. Ng, B. Peyton, "Computing row and column counts for * sparse QR and LU factorization", BIT, vol 41, 2001, pp. 693-710. * * workspace: symmetric: Iwork (nrow), unsymmetric: Iwork (nrow+ncol) * * Supports any xtype (pattern, real, complex, or zomplex) */ #ifndef NCHOLESKY #include "cholmod_internal.h" #include "cholmod_cholesky.h" /* ========================================================================== */ /* === update_etree ========================================================= */ /* ========================================================================== */ static void update_etree ( /* inputs, not modified */ Int k, /* process the edge (k,i) in the input graph */ Int i, /* inputs, modified on output */ Int Parent [ ], /* Parent [t] = p if p is the parent of t */ Int Ancestor [ ] /* Ancestor [t] is the ancestor of node t in the partially-constructed etree */ ) { Int a ; for ( ; ; ) /* traverse the path from k to the root of the tree */ { a = Ancestor [k] ; if (a == i) { /* final ancestor reached; no change to tree */ return ; } /* perform path compression */ Ancestor [k] = i ; if (a == EMPTY) { /* final ancestor undefined; this is a new edge in the tree */ Parent [k] = i ; return ; } /* traverse up to the ancestor of k */ k = a ; } } /* ========================================================================== */ /* === cholmod_etree ======================================================== */ /* ========================================================================== */ /* Find the elimination tree of A or A'*A */ int CHOLMOD(etree) ( /* ---- input ---- */ cholmod_sparse *A, /* ---- output --- */ Int *Parent, /* size ncol. Parent [j] = p if p is the parent of j */ /* --------------- */ cholmod_common *Common ) { Int *Ap, *Ai, *Anz, *Ancestor, *Prev, *Iwork ; Int i, j, jprev, p, pend, nrow, ncol, packed, stype ; size_t s ; int ok = TRUE ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (A, FALSE) ; RETURN_IF_NULL (Parent, FALSE) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ stype = A->stype ; /* s = A->nrow + (stype ? 0 : A->ncol) */ s = CHOLMOD(add_size_t) (A->nrow, (stype ? 0 : A->ncol), &ok) ; if (!ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return (FALSE) ; } CHOLMOD(allocate_work) (0, s, 0, Common) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; /* out of memory */ } ASSERT (CHOLMOD(dump_sparse) (A, "etree", Common) >= 0) ; Iwork = Common->Iwork ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ ncol = A->ncol ; /* the number of columns of A */ nrow = A->nrow ; /* the number of rows of A */ Ap = A->p ; /* size ncol+1, column pointers for A */ Ai = A->i ; /* the row indices of A */ Anz = A->nz ; /* number of nonzeros in each column of A */ packed = A->packed ; Ancestor = Iwork ; /* size ncol (i/i/l) */ for (j = 0 ; j < ncol ; j++) { Parent [j] = EMPTY ; Ancestor [j] = EMPTY ; } /* ---------------------------------------------------------------------- */ /* compute the etree */ /* ---------------------------------------------------------------------- */ if (stype > 0) { /* ------------------------------------------------------------------ */ /* symmetric (upper) case: compute etree (A) */ /* ------------------------------------------------------------------ */ for (j = 0 ; j < ncol ; j++) { /* for each row i in column j of triu(A), excluding the diagonal */ p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { i = Ai [p] ; if (i < j) { update_etree (i, j, Parent, Ancestor) ; } } } } else if (stype == 0) { /* ------------------------------------------------------------------ */ /* unsymmetric case: compute etree (A'*A) */ /* ------------------------------------------------------------------ */ Prev = Iwork + ncol ; /* size nrow (i/i/l) */ for (i = 0 ; i < nrow ; i++) { Prev [i] = EMPTY ; } for (j = 0 ; j < ncol ; j++) { /* for each row i in column j of A */ p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { /* a graph is constructed dynamically with one path per row * of A. If the ith row of A contains column indices * (j1,j2,j3,j4) then the new graph has edges (j1,j2), (j2,j3), * and (j3,j4). When at node i of this path-graph, all edges * (jprev,j) are considered, where jprevncol)-1 */ size_t fsize, /* size of fset */ int postorder, /* if TRUE, follow with a coletree postorder */ /* ---- output --- */ Int *Perm, /* size A->nrow, output permutation */ /* --------------- */ cholmod_common *Common ) { double knobs [COLAMD_KNOBS] ; cholmod_sparse *C ; Int *NewPerm, *Parent, *Post, *Work2n ; Int k, nrow, ncol ; size_t s, alen ; int ok = TRUE ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (A, FALSE) ; RETURN_IF_NULL (Perm, FALSE) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; if (A->stype != 0) { ERROR (CHOLMOD_INVALID, "matrix must be unsymmetric") ; return (FALSE) ; } Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ nrow = A->nrow ; ncol = A->ncol ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ /* Note: this is less than the space used in cholmod_analyze, so if * cholmod_colamd is being called by that routine, no space will be * allocated. */ /* s = 4*nrow + ncol */ s = CHOLMOD(mult_size_t) (nrow, 4, &ok) ; s = CHOLMOD(add_size_t) (s, ncol, &ok) ; #ifdef LONG alen = colamd_l_recommended (A->nzmax, ncol, nrow) ; colamd_l_set_defaults (knobs) ; #else alen = colamd_recommended (A->nzmax, ncol, nrow) ; colamd_set_defaults (knobs) ; #endif if (!ok || alen == 0) { ERROR (CHOLMOD_TOO_LARGE, "matrix invalid or too large") ; return (FALSE) ; } CHOLMOD(allocate_work) (0, s, 0, Common) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; } /* ---------------------------------------------------------------------- */ /* allocate COLAMD workspace */ /* ---------------------------------------------------------------------- */ /* colamd_printf is only available in colamd v2.4 or later */ colamd_printf = Common->print_function ; C = CHOLMOD(allocate_sparse) (ncol, nrow, alen, TRUE, TRUE, 0, CHOLMOD_PATTERN, Common) ; /* ---------------------------------------------------------------------- */ /* copy (and transpose) the input matrix A into the colamd workspace */ /* ---------------------------------------------------------------------- */ /* C = A (:,f)', which also packs A if needed. */ /* workspace: Iwork (nrow if no fset; MAX (nrow,ncol) if fset) */ ok = CHOLMOD(transpose_unsym) (A, 0, NULL, fset, fsize, C, Common) ; /* ---------------------------------------------------------------------- */ /* order the matrix (destroys the contents of C->i and C->p) */ /* ---------------------------------------------------------------------- */ /* get parameters */ if (Common->current < 0 || Common->current >= CHOLMOD_MAXMETHODS) { /* this is the CHOLMOD default, not the COLAMD default */ knobs [COLAMD_DENSE_ROW] = -1 ; } else { /* get the knobs from the Common parameters */ knobs [COLAMD_DENSE_COL] = Common->method[Common->current].prune_dense ; knobs [COLAMD_DENSE_ROW] = Common->method[Common->current].prune_dense2; knobs [COLAMD_AGGRESSIVE] = Common->method[Common->current].aggressive ; } if (ok) { Int *Cp ; Int stats [COLAMD_STATS] ; Cp = C->p ; #ifdef LONG colamd_l (ncol, nrow, alen, C->i, Cp, knobs, stats) ; #else colamd (ncol, nrow, alen, C->i, Cp, knobs, stats) ; #endif ok = stats [COLAMD_STATUS] ; ok = (ok == COLAMD_OK || ok == COLAMD_OK_BUT_JUMBLED) ; /* permutation returned in C->p, if the ordering succeeded */ for (k = 0 ; k < nrow ; k++) { Perm [k] = Cp [k] ; } } CHOLMOD(free_sparse) (&C, Common) ; /* ---------------------------------------------------------------------- */ /* column etree postordering */ /* ---------------------------------------------------------------------- */ if (postorder) { /* use the last 2*n space in Iwork for Parent and Post */ Work2n = Common->Iwork ; Work2n += 2*((size_t) nrow) + ncol ; Parent = Work2n ; /* size nrow (i/i/l) */ Post = Work2n + nrow ; /* size nrow (i/i/l) */ /* workspace: Iwork (2*nrow+ncol), Flag (nrow), Head (nrow+1) */ ok = ok && CHOLMOD(analyze_ordering) (A, CHOLMOD_COLAMD, Perm, fset, fsize, Parent, Post, NULL, NULL, NULL, Common) ; /* combine the colamd permutation with its postordering */ if (ok) { NewPerm = Common->Iwork ; /* size nrow (i/i/l) */ for (k = 0 ; k < nrow ; k++) { NewPerm [k] = Perm [Post [k]] ; } for (k = 0 ; k < nrow ; k++) { Perm [k] = NewPerm [k] ; } } } return (ok) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Cholesky/t_cholmod_rowfac.c0000644000076500000240000003227013524616144027733 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Cholesky/t_cholmod_rowfac ============================================ */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Cholesky Module. Copyright (C) 2005-2006, Timothy A. Davis * The CHOLMOD/Cholesky Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Template routine for cholmod_rowfac. Supports any numeric xtype * (real, complex, or zomplex). * * workspace: Iwork (n), Flag (n), Xwork (n if real, 2*n if complex) */ #include "cholmod_template.h" #ifdef MASK static int TEMPLATE (cholmod_rowfac_mask) #else static int TEMPLATE (cholmod_rowfac) #endif ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to factorize */ cholmod_sparse *F, /* used for A*A' case only. F=A' or A(:,f)' */ double beta [2], /* factorize beta*I+A or beta*I+AA' (beta [0] only) */ size_t kstart, /* first row to factorize */ size_t kend, /* last row to factorize is kend-1 */ #ifdef MASK /* These inputs are used for cholmod_rowfac_mask only */ Int *mask, /* size A->nrow. if mask[i] then W(i) is set to zero */ Int *RLinkUp, /* size A->nrow. link list of rows to compute */ #endif /* ---- in/out --- */ cholmod_factor *L, /* --------------- */ cholmod_common *Common ) { double yx [2], lx [2], fx [2], dk [1], di [1], fl = 0 ; #ifdef ZOMPLEX double yz [1], lz [1], fz [1] ; #endif double *Ax, *Az, *Lx, *Lz, *Wx, *Wz, *Fx, *Fz ; Int *Ap, *Anz, *Ai, *Lp, *Lnz, *Li, *Lnext, *Flag, *Stack, *Fp, *Fi, *Fnz, *Iwork ; Int i, p, k, t, pf, pfend, top, s, mark, pend, n, lnz, is_ll, multadds, use_dbound, packed, stype, Fpacked, sorted, nzmax, len, parent ; #ifndef REAL Int dk_imaginary ; #endif /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ PRINT1 (("\nin cholmod_rowfac, kstart %d kend %d stype %d\n", kstart, kend, A->stype)) ; DEBUG (CHOLMOD(dump_factor) (L, "Initial L", Common)) ; n = A->nrow ; stype = A->stype ; if (stype > 0) { /* symmetric upper case: F is not needed. It may be NULL */ Fp = NULL ; Fi = NULL ; Fx = NULL ; Fz = NULL ; Fnz = NULL ; Fpacked = TRUE ; } else { /* unsymmetric case: F is required. */ Fp = F->p ; Fi = F->i ; Fx = F->x ; Fz = F->z ; Fnz = F->nz ; Fpacked = F->packed ; } Ap = A->p ; /* size A->ncol+1, column pointers of A */ Ai = A->i ; /* size nz = Ap [A->ncol], row indices of A */ Ax = A->x ; /* size nz, numeric values of A */ Az = A->z ; Anz = A->nz ; packed = A->packed ; sorted = A->sorted ; use_dbound = IS_GT_ZERO (Common->dbound) ; /* get the current factors L (and D for LDL'); allocate space if needed */ is_ll = L->is_ll ; if (L->xtype == CHOLMOD_PATTERN) { /* ------------------------------------------------------------------ */ /* L is symbolic only; allocate and initialize L (and D for LDL') */ /* ------------------------------------------------------------------ */ /* workspace: none */ CHOLMOD(change_factor) (A->xtype, is_ll, FALSE, FALSE, TRUE, L, Common); if (Common->status < CHOLMOD_OK) { /* out of memory */ return (FALSE) ; } ASSERT (L->minor == (size_t) n) ; } else if (kstart == 0 && kend == (size_t) n) { /* ------------------------------------------------------------------ */ /* refactorization; reset L->nz and L->minor to restart factorization */ /* ------------------------------------------------------------------ */ L->minor = n ; Lnz = L->nz ; for (k = 0 ; k < n ; k++) { Lnz [k] = 1 ; } } ASSERT (is_ll == L->is_ll) ; ASSERT (L->xtype != CHOLMOD_PATTERN) ; DEBUG (CHOLMOD(dump_factor) (L, "L ready", Common)) ; DEBUG (CHOLMOD(dump_sparse) (A, "A ready", Common)) ; DEBUG (if (stype == 0) CHOLMOD(dump_sparse) (F, "F ready", Common)) ; /* inputs, can be modified on output: */ Lp = L->p ; /* size n+1 */ ASSERT (Lp != NULL) ; /* outputs, contents defined on input for incremental case only: */ Lnz = L->nz ; /* size n */ Lnext = L->next ; /* size n+2 */ Li = L->i ; /* size L->nzmax, can change in size */ Lx = L->x ; /* size L->nzmax or 2*L->nzmax, can change in size */ Lz = L->z ; /* size L->nzmax for zomplex case, can change in size */ nzmax = L->nzmax ; ASSERT (Lnz != NULL && Li != NULL && Lx != NULL) ; /* ---------------------------------------------------------------------- */ /* get workspace */ /* ---------------------------------------------------------------------- */ Iwork = Common->Iwork ; Stack = Iwork ; /* size n (i/i/l) */ Flag = Common->Flag ; /* size n, Flag [i] < mark must hold */ Wx = Common->Xwork ; /* size n if real, 2*n if complex or * zomplex. Xwork [i] == 0 must hold. */ Wz = Wx + n ; /* size n for zomplex case only */ mark = Common->mark ; ASSERT ((Int) Common->xworksize >= (L->xtype == CHOLMOD_REAL ? 1:2)*n) ; /* ---------------------------------------------------------------------- */ /* compute LDL' or LL' factorization by rows */ /* ---------------------------------------------------------------------- */ #ifdef MASK #define NEXT(k) k = RLinkUp [k] #else #define NEXT(k) k++ #endif for (k = kstart ; k < ((Int) kend) ; NEXT(k)) { PRINT1 (("\n===============K "ID" Lnz [k] "ID"\n", k, Lnz [k])) ; /* ------------------------------------------------------------------ */ /* compute pattern of kth row of L and scatter kth input column */ /* ------------------------------------------------------------------ */ /* column k of L is currently empty */ ASSERT (Lnz [k] == 1) ; ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 2*n, Common)) ; top = n ; /* Stack is empty */ Flag [k] = mark ; /* do not include diagonal entry in Stack */ /* use Li [Lp [i]+1] for etree */ #define PARENT(i) (Lnz [i] > 1) ? (Li [Lp [i] + 1]) : EMPTY if (stype > 0) { /* scatter kth col of triu (beta*I+AA'), get pattern L(k,:) */ p = Ap [k] ; pend = (packed) ? (Ap [k+1]) : (p + Anz [k]) ; /* W [i] = Ax [i] ; scatter column of A */ #define SCATTER ASSIGN(Wx,Wz,i, Ax,Az,p) SUBTREE ; #undef SCATTER } else { /* scatter kth col of triu (beta*I+AA'), get pattern L(k,:) */ pf = Fp [k] ; pfend = (Fpacked) ? (Fp [k+1]) : (pf + Fnz [k]) ; for ( ; pf < pfend ; pf++) { /* get nonzero entry F (t,k) */ t = Fi [pf] ; /* fk = Fx [pf] */ ASSIGN (fx, fz, 0, Fx, Fz, pf) ; p = Ap [t] ; pend = (packed) ? (Ap [t+1]) : (p + Anz [t]) ; multadds = 0 ; /* W [i] += Ax [p] * fx ; scatter column of A*A' */ #define SCATTER MULTADD (Wx,Wz,i, Ax,Az,p, fx,fz,0) ; multadds++ ; SUBTREE ; #undef SCATTER #ifdef REAL fl += 2 * ((double) multadds) ; #else fl += 8 * ((double) multadds) ; #endif } } #undef PARENT /* ------------------------------------------------------------------ */ /* if mask is present, set the corresponding entries in W to zero */ /* ------------------------------------------------------------------ */ #ifdef MASK /* remove the dead element of Wx */ if (mask != NULL) { #if 0 /* older version */ for (p = n; p > top;) { i = Stack [--p] ; if ( mask [i] >= 0 ) { CLEAR (Wx,Wz,i) ; /* set W(i) to zero */ } } #endif for (s = top ; s < n ; s++) { i = Stack [s] ; if (mask [i] >= 0) { CLEAR (Wx,Wz,i) ; /* set W(i) to zero */ } } } #endif /* nonzero pattern of kth row of L is now in Stack [top..n-1]. * Flag [Stack [top..n-1]] is equal to mark, but no longer needed */ /* mark = CHOLMOD(clear_flag) (Common) ; */ CHOLMOD_CLEAR_FLAG (Common) ; mark = Common->mark ; /* ------------------------------------------------------------------ */ /* compute kth row of L and store in column form */ /* ------------------------------------------------------------------ */ /* Solve L (0:k-1, 0:k-1) * y (0:k-1) = b (0:k-1) where * b (0:k) = A (0:k,k) or A(0:k,:) * F(:,k) is in W and Stack. * * For LDL' factorization: * L (k, 0:k-1) = y (0:k-1) ./ D (0:k-1) * D (k) = b (k) - L (k, 0:k-1) * y (0:k-1) * * For LL' factorization: * L (k, 0:k-1) = y (0:k-1) * L (k,k) = sqrt (b (k) - L (k, 0:k-1) * L (0:k-1, k)) */ /* dk = W [k] + beta */ ADD_REAL (dk,0, Wx,k, beta,0) ; #ifndef REAL /* In the unsymmetric case, the imaginary part of W[k] must be real, * since F is assumed to be the complex conjugate transpose of A. In * the symmetric case, W[k] is the diagonal of A. If the imaginary part * of W[k] is nonzero, then the Cholesky factorization cannot be * computed; A is not positive definite */ dk_imaginary = (stype > 0) ? (IMAG_IS_NONZERO (Wx,Wz,k)) : FALSE ; #endif /* W [k] = 0.0 ; */ CLEAR (Wx,Wz,k) ; for (s = top ; s < n ; s++) { /* get i for each nonzero entry L(k,i) */ i = Stack [s] ; /* y = W [i] ; */ ASSIGN (yx,yz,0, Wx,Wz,i) ; /* W [i] = 0.0 ; */ CLEAR (Wx,Wz,i) ; lnz = Lnz [i] ; p = Lp [i] ; ASSERT (lnz > 0 && Li [p] == i) ; pend = p + lnz ; /* di = Lx [p] ; the diagonal entry L or D(i,i), which is real */ ASSIGN_REAL (di,0, Lx,p) ; if (i >= (Int) L->minor || IS_ZERO (di [0])) { /* For the LL' factorization, L(i,i) is zero. For the LDL', * D(i,i) is zero. Skip column i of L, and set L(k,i) = 0. */ CLEAR (lx,lz,0) ; p = pend ; } else if (is_ll) { #ifdef REAL fl += 2 * ((double) (pend - p - 1)) + 3 ; #else fl += 8 * ((double) (pend - p - 1)) + 6 ; #endif /* forward solve using L (i:(k-1),i) */ /* divide by L(i,i), which must be real and nonzero */ /* y /= di [0] */ DIV_REAL (yx,yz,0, yx,yz,0, di,0) ; for (p++ ; p < pend ; p++) { /* W [Li [p]] -= Lx [p] * y ; */ MULTSUB (Wx,Wz,Li[p], Lx,Lz,p, yx,yz,0) ; } /* do not scale L; compute dot product for L(k,k) */ /* L(k,i) = conj(y) ; */ ASSIGN_CONJ (lx,lz,0, yx,yz,0) ; /* d -= conj(y) * y ; */ LLDOT (dk,0, yx,yz,0) ; } else { #ifdef REAL fl += 2 * ((double) (pend - p - 1)) + 3 ; #else fl += 8 * ((double) (pend - p - 1)) + 6 ; #endif /* forward solve using D (i,i) and L ((i+1):(k-1),i) */ for (p++ ; p < pend ; p++) { /* W [Li [p]] -= Lx [p] * y ; */ MULTSUB (Wx,Wz,Li[p], Lx,Lz,p, yx,yz,0) ; } /* Scale L (k,0:k-1) for LDL' factorization, compute D (k,k)*/ #ifdef REAL /* L(k,i) = y/d */ lx [0] = yx [0] / di [0] ; /* d -= L(k,i) * y */ dk [0] -= lx [0] * yx [0] ; #else /* L(k,i) = conj(y) ; */ ASSIGN_CONJ (lx,lz,0, yx,yz,0) ; /* L(k,i) /= di ; */ DIV_REAL (lx,lz,0, lx,lz,0, di,0) ; /* d -= conj(y) * y / di */ LDLDOT (dk,0, yx,yz,0, di,0) ; #endif } /* determine if column i of L can hold the new L(k,i) entry */ if (p >= Lp [Lnext [i]]) { /* column i needs to grow */ PRINT1 (("Factor Colrealloc "ID", old Lnz "ID"\n", i, Lnz [i])); if (!CHOLMOD(reallocate_column) (i, lnz + 1, L, Common)) { /* out of memory, L is now simplicial symbolic */ for (i = 0 ; i < n ; i++) { /* W [i] = 0 ; */ CLEAR (Wx,Wz,i) ; } ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, n, Common)) ; return (FALSE) ; } Li = L->i ; /* L->i, L->x, L->z may have moved */ Lx = L->x ; Lz = L->z ; p = Lp [i] + lnz ; /* contents of L->p changed */ ASSERT (p < Lp [Lnext [i]]) ; } /* store L (k,i) in the column form matrix of L */ Li [p] = k ; /* Lx [p] = L(k,i) ; */ ASSIGN (Lx,Lz,p, lx,lz,0) ; Lnz [i]++ ; } /* ------------------------------------------------------------------ */ /* ensure abs (d) >= dbound if dbound is given, and store it in L */ /* ------------------------------------------------------------------ */ p = Lp [k] ; Li [p] = k ; if (k >= (Int) L->minor) { /* the matrix is already not positive definite */ dk [0] = 0 ; } else if (use_dbound) { /* modify the diagonal to force LL' or LDL' to exist */ dk [0] = CHOLMOD(dbound) (is_ll ? fabs (dk [0]) : dk [0], Common) ; } else if ((is_ll ? (IS_LE_ZERO (dk [0])) : (IS_ZERO (dk [0]))) #ifndef REAL || dk_imaginary #endif ) { /* the matrix has just been found to be not positive definite */ dk [0] = 0 ; L->minor = k ; ERROR (CHOLMOD_NOT_POSDEF, "not positive definite") ; } if (is_ll) { /* this is counted as one flop, below */ dk [0] = sqrt (dk [0]) ; } /* Lx [p] = D(k,k) = d ; real part only */ ASSIGN_REAL (Lx,p, dk,0) ; CLEAR_IMAG (Lx,Lz,p) ; } #undef NEXT if (is_ll) fl += MAX ((Int) kend - (Int) kstart, 0) ; /* count sqrt's */ Common->rowfacfl = fl ; DEBUG (CHOLMOD(dump_factor) (L, "final cholmod_rowfac", Common)) ; ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, n, Common)) ; return (TRUE) ; } #undef PATTERN #undef REAL #undef COMPLEX #undef ZOMPLEX python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Cholesky/cholmod_solve.c0000644000076500000240000014160513524616144027262 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Cholesky/cholmod_solve =============================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Cholesky Module. Copyright (C) 2005-2013, Timothy A. Davis * The CHOLMOD/Cholesky Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Solve one of the following systems. D is identity for an LL' factorization, * in which the D operation is skipped: * * Ax=b 0: CHOLMOD_A x = P' * (L' \ (D \ (L \ (P * b)))) * LDL'x=b 1: CHOLMOD_LDLt x = (L' \ (D \ (L \ ( b)))) * LDx=b 2: CHOLMOD_LD x = ( (D \ (L \ ( b)))) * DL'x=b 3: CHOLMOD_DLt x = (L' \ (D \ ( ( b)))) * Lx=b 4: CHOLMOD_L x = ( ( (L \ ( b)))) * L'x=b 5: CHOLMOD_Lt x = (L' \ ( ( ( b)))) * Dx=b 6: CHOLMOD_D x = ( (D \ ( ( b)))) * x=Pb 7: CHOLMOD_P x = ( ( ( (P * b)))) * x=P'b 8: CHOLMOD_Pt x = P' * ( ( ( ( b)))) * * The factorization can be simplicial LDL', simplicial LL', or supernodal LL'. * For an LL' factorization, D is the identity matrix. Thus CHOLMOD_LD and * CHOLMOD_L solve the same system if an LL' factorization was performed, * for example. * * The supernodal solver uses BLAS routines dtrsv, dgemv, dtrsm, and dgemm, * or their complex counterparts ztrsv, zgemv, ztrsm, and zgemm. * * If both L and B are real, then X is returned real. If either is complex * or zomplex, X is returned as either complex or zomplex, depending on the * Common->prefer_zomplex parameter. * * Supports any numeric xtype (pattern-only matrices not supported). * * This routine does not check to see if the diagonal of L or D is zero, * because sometimes a partial solve can be done with indefinite or singular * matrix. If you wish to check in your own code, test L->minor. If * L->minor == L->n, then the matrix has no zero diagonal entries. * If k = L->minor < L->n, then L(k,k) is zero for an LL' factorization, or * D(k,k) is zero for an LDL' factorization. * * This routine returns X as NULL only if it runs out of memory. If L is * indefinite or singular, then X may contain Inf's or NaN's, but it will * exist on output. */ #ifndef NCHOLESKY #include "cholmod_internal.h" #include "cholmod_cholesky.h" #ifndef NSUPERNODAL #include "cholmod_supernodal.h" #endif /* ========================================================================== */ /* === TEMPLATE ============================================================= */ /* ========================================================================== */ #define REAL #include "t_cholmod_solve.c" #define COMPLEX #include "t_cholmod_solve.c" #define ZOMPLEX #include "t_cholmod_solve.c" /* ========================================================================== */ /* === Permutation macro ==================================================== */ /* ========================================================================== */ /* If Perm is NULL, it is interpretted as the identity permutation */ #define P(k) ((Perm == NULL) ? (k) : Perm [k]) /* ========================================================================== */ /* === perm ================================================================= */ /* ========================================================================== */ /* Y = B (P (1:nrow), k1 : min (k1+ncols,ncol)-1) where B is nrow-by-ncol. * * Creates a permuted copy of a contiguous set of columns of B. * Y is already allocated on input. Y must be of sufficient size. Let nk be * the number of columns accessed in B. Y->xtype determines the complexity of * the result. * * If B is real and Y is complex (or zomplex), only the real part of B is * copied into Y. The imaginary part of Y is set to zero. * * If B is complex (or zomplex) and Y is real, both the real and imaginary and * parts of B are returned in Y. Y is returned as nrow-by-2*nk. The even * columns of Y contain the real part of B and the odd columns contain the * imaginary part of B. Y->nzmax must be >= 2*nrow*nk. Otherise, Y is * returned as nrow-by-nk with leading dimension nrow. Y->nzmax must be >= * nrow*nk. * * The case where the input (B) is real and the output (Y) is zomplex is * not used. */ static void perm ( /* ---- input ---- */ cholmod_dense *B, /* input matrix B */ Int *Perm, /* optional input permutation (can be NULL) */ Int k1, /* first column of B to copy */ Int ncols, /* last column to copy is min(k1+ncols,B->ncol)-1 */ /* ---- in/out --- */ cholmod_dense *Y /* output matrix Y, already allocated */ ) { double *Yx, *Yz, *Bx, *Bz ; Int k2, nk, p, k, j, nrow, ncol, d, dual, dj, j2 ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ ncol = B->ncol ; nrow = B->nrow ; k2 = MIN (k1+ncols, ncol) ; nk = MAX (k2 - k1, 0) ; dual = (Y->xtype == CHOLMOD_REAL && B->xtype != CHOLMOD_REAL) ? 2 : 1 ; d = B->d ; Bx = B->x ; Bz = B->z ; Yx = Y->x ; Yz = Y->z ; Y->nrow = nrow ; Y->ncol = dual*nk ; Y->d = nrow ; ASSERT (((Int) Y->nzmax) >= nrow*nk*dual) ; /* ---------------------------------------------------------------------- */ /* Y = B (P (1:nrow), k1:k2-1) */ /* ---------------------------------------------------------------------- */ switch (Y->xtype) { case CHOLMOD_REAL: switch (B->xtype) { case CHOLMOD_REAL: /* Y real, B real */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = nrow * (j-k1) ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Yx [k + j2] = Bx [p] ; /* real */ } } break ; case CHOLMOD_COMPLEX: /* Y real, B complex. Y is nrow-by-2*nk */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = nrow * 2 * (j-k1) ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Yx [k + j2 ] = Bx [2*p ] ; /* real */ Yx [k + j2 + nrow] = Bx [2*p+1] ; /* imag */ } } break ; case CHOLMOD_ZOMPLEX: /* Y real, B zomplex. Y is nrow-by-2*nk */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = nrow * 2 * (j-k1) ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Yx [k + j2 ] = Bx [p] ; /* real */ Yx [k + j2 + nrow] = Bz [p] ; /* imag */ } } break ; } break ; case CHOLMOD_COMPLEX: switch (B->xtype) { case CHOLMOD_REAL: /* Y complex, B real */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = nrow * 2 * (j-k1) ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Yx [2*k + j2] = Bx [p] ; /* real */ Yx [2*k+1 + j2] = 0 ; /* imag */ } } break ; case CHOLMOD_COMPLEX: /* Y complex, B complex */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = nrow * 2 * (j-k1) ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Yx [2*k + j2] = Bx [2*p ] ; /* real */ Yx [2*k+1 + j2] = Bx [2*p+1] ; /* imag */ } } break ; case CHOLMOD_ZOMPLEX: /* Y complex, B zomplex */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = nrow * 2 * (j-k1) ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Yx [2*k + j2] = Bx [p] ; /* real */ Yx [2*k+1 + j2] = Bz [p] ; /* imag */ } } break ; } break ; case CHOLMOD_ZOMPLEX: switch (B->xtype) { #if 0 case CHOLMOD_REAL: /* this case is not used */ break ; #endif case CHOLMOD_COMPLEX: /* Y zomplex, B complex */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = nrow * (j-k1) ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Yx [k + j2] = Bx [2*p ] ; /* real */ Yz [k + j2] = Bx [2*p+1] ; /* imag */ } } break ; case CHOLMOD_ZOMPLEX: /* Y zomplex, B zomplex */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = nrow * (j-k1) ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Yx [k + j2] = Bx [p] ; /* real */ Yz [k + j2] = Bz [p] ; /* imag */ } } break ; } break ; } } /* ========================================================================== */ /* === iperm ================================================================ */ /* ========================================================================== */ /* X (P (1:nrow), k1 : min (k1+ncols,ncol)-1) = Y where X is nrow-by-ncol. * * Copies and permutes Y into a contiguous set of columns of X. X is already * allocated on input. Y must be of sufficient size. Let nk be the number * of columns accessed in X. X->xtype determines the complexity of the result. * * If X is real and Y is complex (or zomplex), only the real part of B is * copied into X. The imaginary part of Y is ignored. * * If X is complex (or zomplex) and Y is real, both the real and imaginary and * parts of Y are returned in X. Y is nrow-by-2*nk. The even * columns of Y contain the real part of B and the odd columns contain the * imaginary part of B. Y->nzmax must be >= 2*nrow*nk. Otherise, Y is * nrow-by-nk with leading dimension nrow. Y->nzmax must be >= nrow*nk. * * The case where the input (Y) is complex and the output (X) is real, * and the case where the input (Y) is zomplex and the output (X) is real, * are not used. */ static void iperm ( /* ---- input ---- */ cholmod_dense *Y, /* input matrix Y */ Int *Perm, /* optional input permutation (can be NULL) */ Int k1, /* first column of B to copy */ Int ncols, /* last column to copy is min(k1+ncols,B->ncol)-1 */ /* ---- in/out --- */ cholmod_dense *X /* output matrix X, already allocated */ ) { double *Yx, *Yz, *Xx, *Xz ; Int k2, nk, p, k, j, nrow, ncol, d, dj, j2 ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ ncol = X->ncol ; nrow = X->nrow ; k2 = MIN (k1+ncols, ncol) ; nk = MAX (k2 - k1, 0) ; d = X->d ; Xx = X->x ; Xz = X->z ; Yx = Y->x ; Yz = Y->z ; ASSERT (((Int) Y->nzmax) >= nrow*nk* ((X->xtype != CHOLMOD_REAL && Y->xtype == CHOLMOD_REAL) ? 2:1)) ; /* ---------------------------------------------------------------------- */ /* X (P (1:nrow), k1:k2-1) = Y */ /* ---------------------------------------------------------------------- */ switch (Y->xtype) { case CHOLMOD_REAL: switch (X->xtype) { case CHOLMOD_REAL: /* Y real, X real */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = nrow * (j-k1) ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Xx [p] = Yx [k + j2] ; /* real */ } } break ; case CHOLMOD_COMPLEX: /* Y real, X complex. Y is nrow-by-2*nk */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = nrow * 2 * (j-k1) ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Xx [2*p ] = Yx [k + j2 ] ; /* real */ Xx [2*p+1] = Yx [k + j2 + nrow] ; /* imag */ } } break ; case CHOLMOD_ZOMPLEX: /* Y real, X zomplex. Y is nrow-by-2*nk */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = nrow * 2 * (j-k1) ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Xx [p] = Yx [k + j2 ] ; /* real */ Xz [p] = Yx [k + j2 + nrow] ; /* imag */ } } break ; } break ; case CHOLMOD_COMPLEX: switch (X->xtype) { #if 0 case CHOLMOD_REAL: /* this case is not used */ break ; #endif case CHOLMOD_COMPLEX: /* Y complex, X complex */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = nrow * 2 * (j-k1) ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Xx [2*p ] = Yx [2*k + j2] ; /* real */ Xx [2*p+1] = Yx [2*k+1 + j2] ; /* imag */ } } break ; case CHOLMOD_ZOMPLEX: /* Y complex, X zomplex */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = nrow * 2 * (j-k1) ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Xx [p] = Yx [2*k + j2] ; /* real */ Xz [p] = Yx [2*k+1 + j2] ; /* imag */ } } break ; } break ; case CHOLMOD_ZOMPLEX: switch (X->xtype) { #if 0 case CHOLMOD_REAL: /* this case is not used */ break ; #endif case CHOLMOD_COMPLEX: /* Y zomplex, X complex */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = nrow * (j-k1) ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Xx [2*p ] = Yx [k + j2] ; /* real */ Xx [2*p+1] = Yz [k + j2] ; /* imag */ } } break ; case CHOLMOD_ZOMPLEX: /* Y zomplex, X zomplex */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = nrow * (j-k1) ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Xx [p] = Yx [k + j2] ; /* real */ Xz [p] = Yz [k + j2] ; /* imag */ } } break ; } break ; } } /* ========================================================================== */ /* === ptrans =============================================================== */ /* ========================================================================== */ /* Y = B (P (1:nrow), k1 : min (k1+ncols,ncol)-1)' where B is nrow-by-ncol. * * Creates a permuted and transposed copy of a contiguous set of columns of B. * Y is already allocated on input. Y must be of sufficient size. Let nk be * the number of columns accessed in B. Y->xtype determines the complexity of * the result. * * If B is real and Y is complex (or zomplex), only the real part of B is * copied into Y. The imaginary part of Y is set to zero. * * If B is complex (or zomplex) and Y is real, both the real and imaginary and * parts of B are returned in Y. Y is returned as 2*nk-by-nrow. The even * rows of Y contain the real part of B and the odd rows contain the * imaginary part of B. Y->nzmax must be >= 2*nrow*nk. Otherise, Y is * returned as nk-by-nrow with leading dimension nk. Y->nzmax must be >= * nrow*nk. * * The array transpose is performed, not the complex conjugate transpose. */ static void ptrans ( /* ---- input ---- */ cholmod_dense *B, /* input matrix B */ Int *Perm, /* optional input permutation (can be NULL) */ Int k1, /* first column of B to copy */ Int ncols, /* last column to copy is min(k1+ncols,B->ncol)-1 */ /* ---- in/out --- */ cholmod_dense *Y /* output matrix Y, already allocated */ ) { double *Yx, *Yz, *Bx, *Bz ; Int k2, nk, p, k, j, nrow, ncol, d, dual, dj, j2 ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ ncol = B->ncol ; nrow = B->nrow ; k2 = MIN (k1+ncols, ncol) ; nk = MAX (k2 - k1, 0) ; dual = (Y->xtype == CHOLMOD_REAL && B->xtype != CHOLMOD_REAL) ? 2 : 1 ; d = B->d ; Bx = B->x ; Bz = B->z ; Yx = Y->x ; Yz = Y->z ; Y->nrow = dual*nk ; Y->ncol = nrow ; Y->d = dual*nk ; ASSERT (((Int) Y->nzmax) >= nrow*nk*dual) ; /* ---------------------------------------------------------------------- */ /* Y = B (P (1:nrow), k1:k2-1)' */ /* ---------------------------------------------------------------------- */ switch (Y->xtype) { case CHOLMOD_REAL: switch (B->xtype) { case CHOLMOD_REAL: /* Y real, B real */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = j-k1 ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Yx [j2 + k*nk] = Bx [p] ; /* real */ } } break ; case CHOLMOD_COMPLEX: /* Y real, B complex. Y is 2*nk-by-nrow */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = 2*(j-k1) ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Yx [j2 + k*2*nk] = Bx [2*p ] ; /* real */ Yx [j2+1 + k*2*nk] = Bx [2*p+1] ; /* imag */ } } break ; case CHOLMOD_ZOMPLEX: /* Y real, B zomplex. Y is 2*nk-by-nrow */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = 2*(j-k1) ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Yx [j2 + k*2*nk] = Bx [p] ; /* real */ Yx [j2+1 + k*2*nk] = Bz [p] ; /* imag */ } } break ; } break ; case CHOLMOD_COMPLEX: switch (B->xtype) { case CHOLMOD_REAL: /* Y complex, B real */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = 2*(j-k1) ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Yx [j2 + k*2*nk] = Bx [p] ; /* real */ Yx [j2+1 + k*2*nk] = 0 ; /* imag */ } } break ; case CHOLMOD_COMPLEX: /* Y complex, B complex */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = 2*(j-k1) ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Yx [j2 + k*2*nk] = Bx [2*p ] ; /* real */ Yx [j2+1 + k*2*nk] = Bx [2*p+1] ; /* imag */ } } break ; case CHOLMOD_ZOMPLEX: /* Y complex, B zomplex */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = 2*(j-k1) ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Yx [j2 + k*2*nk] = Bx [p] ; /* real */ Yx [j2+1 + k*2*nk] = Bz [p] ; /* imag */ } } break ; } break ; case CHOLMOD_ZOMPLEX: switch (B->xtype) { case CHOLMOD_REAL: /* Y zomplex, B real */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = j-k1 ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Yx [j2 + k*nk] = Bx [p] ; /* real */ Yz [j2 + k*nk] = 0 ; /* imag */ } } break ; case CHOLMOD_COMPLEX: /* Y zomplex, B complex */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = j-k1 ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Yx [j2 + k*nk] = Bx [2*p ] ; /* real */ Yz [j2 + k*nk] = Bx [2*p+1] ; /* imag */ } } break ; case CHOLMOD_ZOMPLEX: /* Y zomplex, B zomplex */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = j-k1 ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Yx [j2 + k*nk] = Bx [p] ; /* real */ Yz [j2 + k*nk] = Bz [p] ; /* imag */ } } break ; } break ; } } /* ========================================================================== */ /* === iptrans ============================================================== */ /* ========================================================================== */ /* X (P (1:nrow), k1 : min (k1+ncols,ncol)-1) = Y' where X is nrow-by-ncol. * * Copies into a permuted and transposed contiguous set of columns of X. * X is already allocated on input. Y must be of sufficient size. Let nk be * the number of columns accessed in X. X->xtype determines the complexity of * the result. * * If X is real and Y is complex (or zomplex), only the real part of Y is * copied into X. The imaginary part of Y is ignored. * * If X is complex (or zomplex) and Y is real, both the real and imaginary and * parts of X are returned in Y. Y is 2*nk-by-nrow. The even * rows of Y contain the real part of X and the odd rows contain the * imaginary part of X. Y->nzmax must be >= 2*nrow*nk. Otherise, Y is * nk-by-nrow with leading dimension nk. Y->nzmax must be >= nrow*nk. * * The case where Y is complex or zomplex, and X is real, is not used. * * The array transpose is performed, not the complex conjugate transpose. */ static void iptrans ( /* ---- input ---- */ cholmod_dense *Y, /* input matrix Y */ Int *Perm, /* optional input permutation (can be NULL) */ Int k1, /* first column of X to copy into */ Int ncols, /* last column to copy is min(k1+ncols,X->ncol)-1 */ /* ---- in/out --- */ cholmod_dense *X /* output matrix X, already allocated */ ) { double *Yx, *Yz, *Xx, *Xz ; Int k2, nk, p, k, j, nrow, ncol, d, dj, j2 ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ ncol = X->ncol ; nrow = X->nrow ; k2 = MIN (k1+ncols, ncol) ; nk = MAX (k2 - k1, 0) ; d = X->d ; Xx = X->x ; Xz = X->z ; Yx = Y->x ; Yz = Y->z ; ASSERT (((Int) Y->nzmax) >= nrow*nk* ((X->xtype != CHOLMOD_REAL && Y->xtype == CHOLMOD_REAL) ? 2:1)) ; /* ---------------------------------------------------------------------- */ /* X (P (1:nrow), k1:k2-1) = Y' */ /* ---------------------------------------------------------------------- */ switch (Y->xtype) { case CHOLMOD_REAL: switch (X->xtype) { case CHOLMOD_REAL: /* Y real, X real */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = j-k1 ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Xx [p] = Yx [j2 + k*nk] ; /* real */ } } break ; case CHOLMOD_COMPLEX: /* Y real, X complex. Y is 2*nk-by-nrow */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = 2*(j-k1) ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Xx [2*p ] = Yx [j2 + k*2*nk] ; /* real */ Xx [2*p+1] = Yx [j2+1 + k*2*nk] ; /* imag */ } } break ; case CHOLMOD_ZOMPLEX: /* Y real, X zomplex. Y is 2*nk-by-nrow */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = 2*(j-k1) ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Xx [p] = Yx [j2 + k*2*nk] ; /* real */ Xz [p] = Yx [j2+1 + k*2*nk] ; /* imag */ } } break ; } break ; case CHOLMOD_COMPLEX: switch (X->xtype) { #if 0 case CHOLMOD_REAL: /* this case is not used */ break ; #endif case CHOLMOD_COMPLEX: /* Y complex, X complex */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = 2*(j-k1) ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Xx [2*p ] = Yx [j2 + k*2*nk] ; /* real */ Xx [2*p+1] = Yx [j2+1 + k*2*nk] ; /* imag */ } } break ; case CHOLMOD_ZOMPLEX: /* Y complex, X zomplex */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = 2*(j-k1) ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Xx [p] = Yx [j2 + k*2*nk] ; /* real */ Xz [p] = Yx [j2+1 + k*2*nk] ; /* imag */ } } break ; } break ; case CHOLMOD_ZOMPLEX: switch (X->xtype) { #if 0 case CHOLMOD_REAL: /* this case is not used */ break ; #endif case CHOLMOD_COMPLEX: /* Y zomplex, X complex */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = j-k1 ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Xx [2*p ] = Yx [j2 + k*nk] ; /* real */ Xx [2*p+1] = Yz [j2 + k*nk] ; /* imag */ } } break ; case CHOLMOD_ZOMPLEX: /* Y zomplex, X zomplex */ for (j = k1 ; j < k2 ; j++) { dj = d*j ; j2 = j-k1 ; for (k = 0 ; k < nrow ; k++) { p = P(k) + dj ; Xx [p] = Yx [j2 + k*nk] ; /* real */ Xz [p] = Yz [j2 + k*nk] ; /* imag */ } } break ; } break ; } } /* ========================================================================== */ /* === cholmod_solve ======================================================== */ /* ========================================================================== */ /* Solve a linear system. * * The factorization can be simplicial LDL', simplicial LL', or supernodal LL'. * The Dx=b solve returns silently for the LL' factorizations (it is implicitly * identity). */ cholmod_dense *CHOLMOD(solve) ( /* ---- input ---- */ int sys, /* system to solve */ cholmod_factor *L, /* factorization to use */ cholmod_dense *B, /* right-hand-side */ /* --------------- */ cholmod_common *Common ) { cholmod_dense *Y = NULL, *X = NULL ; cholmod_dense *E = NULL ; int ok ; /* do the solve, allocating workspaces as needed */ ok = CHOLMOD (solve2) (sys, L, B, NULL, &X, NULL, &Y, &E, Common) ; /* free workspaces if allocated, and free result if an error occured */ CHOLMOD(free_dense) (&Y, Common) ; CHOLMOD(free_dense) (&E, Common) ; if (!ok) { CHOLMOD(free_dense) (&X, Common) ; } return (X) ; } /* ========================================================================== */ /* === cholmod_solve2 ======================================================= */ /* ========================================================================== */ /* This function acts just like cholmod_solve, except that the solution X and * the internal workspace (Y and E) can be passed in preallocated. If the * solution X or any required workspaces are not allocated on input, or if they * are the wrong size or type, then this function frees them and reallocates * them as the proper size and type. Thus, if you have a sequence of solves to * do, you can let this function allocate X, Y, and E on the first call. * Subsequent calls to cholmod_solve2 can then reuse this space. You must * then free the workspaces Y and E (and X if desired) when you are finished. * For example, the first call to cholmod_l_solve2, below, will solve the * requested system. The next 2 calls (with different right-hand-sides but * the same value of "sys") will resuse the workspace and solution X from the * first call. Finally, when all solves are done, you must free the workspaces * Y and E (otherwise you will have a memory leak), and you should also free X * when you are done with it. Note that on input, X, Y, and E must be either * valid cholmod_dense matrices, or initialized to NULL. You cannot pass in an * uninitialized X, Y, or E. * * cholmod_dense *X = NULL, *Y = NULL, *E = NULL ; * ... * cholmod_l_solve2 (sys, L, B1, NULL, &X, NULL, &Y, &E, Common) ; * cholmod_l_solve2 (sys, L, B2, NULL, &X, NULL, &Y, &E, Common) ; * cholmod_l_solve2 (sys, L, B3, NULL, &X, NULL, &Y, &E, Common) ; * cholmod_l_free_dense (&X, Common) ; * cholmod_l_free_dense (&Y, Common) ; * cholmod_l_free_dense (&E, Common) ; * * The equivalent when using cholmod_l_solve is: * * cholmod_dense *X = NULL, *Y = NULL, *E = NULL ; * ... * X = cholmod_l_solve (sys, L, B1, Common) ; * cholmod_l_free_dense (&X, Common) ; * X = cholmod_l_solve (sys, L, B2, Common) ; * cholmod_l_free_dense (&X, Common) ; * X = cholmod_l_solve (sys, L, B3, Common) ; * cholmod_l_free_dense (&X, Common) ; * * Both methods work fine, but in the 2nd method with cholmod_solve, the * internal workspaces (Y and E) are allocated and freed on each call. * * Bset is an optional sparse column (pattern only) that specifies a set * of row indices. It is ignored if NULL, or if sys is CHOLMOD_P or * CHOLMOD_Pt. If it is present and not ignored, B must be a dense column * vector, and only entries B(i) where i is in the pattern of Bset are * considered. All others are treated as if they were zero (they are not * accessed). L must be a simplicial factorization, not supernodal. L is * converted from supernodal to simplicial if necessary. The solution X is * defined only for entries in the output sparse pattern of Xset. * The xtype (real/complex/zomplex) of L and B must match. * * NOTE: If Bset is present and L is supernodal, it is converted to simplicial * on output. */ int CHOLMOD(solve2) /* returns TRUE on success, FALSE on failure */ ( /* ---- input ---- */ int sys, /* system to solve */ cholmod_factor *L, /* factorization to use */ cholmod_dense *B, /* right-hand-side */ cholmod_sparse *Bset, /* ---- output --- */ cholmod_dense **X_Handle, /* solution, allocated if need be */ cholmod_sparse **Xset_Handle, /* ---- workspace */ cholmod_dense **Y_Handle, /* workspace, or NULL */ cholmod_dense **E_Handle, /* workspace, or NULL */ /* --------------- */ cholmod_common *Common ) { double *Yx, *Yz, *Bx, *Bz, *Xx, *Xz ; cholmod_dense *Y = NULL, *X = NULL ; cholmod_sparse *C, *Yset, C_header, Yset_header, *Xset ; Int *Perm = NULL, *IPerm = NULL ; Int n, nrhs, ncols, ctype, xtype, k1, nr, ytype, k, blen, p, i, d, nrow ; Int Cp [2], Ysetp [2], *Ci, *Yseti, ysetlen ; Int *Bsetp, *Bseti, *Bsetnz, *Xseti, *Xsetp, *Iwork ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (L, FALSE) ; RETURN_IF_NULL (B, FALSE) ; RETURN_IF_XTYPE_INVALID (L, CHOLMOD_REAL, CHOLMOD_ZOMPLEX, FALSE) ; RETURN_IF_XTYPE_INVALID (B, CHOLMOD_REAL, CHOLMOD_ZOMPLEX, FALSE) ; if (sys < CHOLMOD_A || sys > CHOLMOD_Pt) { ERROR (CHOLMOD_INVALID, "invalid system") ; return (FALSE) ; } DEBUG (CHOLMOD(dump_factor) (L, "L", Common)) ; DEBUG (CHOLMOD(dump_dense) (B, "B", Common)) ; nrhs = B->ncol ; n = (Int) L->n ; d = (Int) B->d ; nrow = (Int) B->nrow ; if (d < n || nrow != n) { ERROR (CHOLMOD_INVALID, "dimensions of L and B do not match") ; return (FALSE) ; } if (Bset) { if (nrhs != 1) { ERROR (CHOLMOD_INVALID, "Bset requires a single right-hand side") ; return (FALSE) ; } if (L->xtype != B->xtype) { ERROR (CHOLMOD_INVALID, "Bset requires xtype of L and B to match") ; return (FALSE) ; } DEBUG (CHOLMOD(dump_sparse) (Bset, "Bset", Common)) ; } Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ if ((sys == CHOLMOD_P || sys == CHOLMOD_Pt || sys == CHOLMOD_A) && L->ordering != CHOLMOD_NATURAL) { /* otherwise, Perm is NULL, and the identity permutation is used */ Perm = L->Perm ; } /* ---------------------------------------------------------------------- */ /* allocate the result X (or resuse the space from a prior call) */ /* ---------------------------------------------------------------------- */ ctype = (Common->prefer_zomplex) ? CHOLMOD_ZOMPLEX : CHOLMOD_COMPLEX ; if (Bset) { xtype = L->xtype ; } else if (sys == CHOLMOD_P || sys == CHOLMOD_Pt) { /* x=Pb and x=P'b return X real if B is real; X is the preferred * complex/zcomplex type if B is complex or zomplex */ xtype = (B->xtype == CHOLMOD_REAL) ? CHOLMOD_REAL : ctype ; } else if (L->xtype == CHOLMOD_REAL && B->xtype == CHOLMOD_REAL) { /* X is real if both L and B are real */ xtype = CHOLMOD_REAL ; } else { /* X is complex, use the preferred complex/zomplex type */ xtype = ctype ; } /* ensure X has the right size and type */ X = CHOLMOD(ensure_dense) (X_Handle, n, nrhs, n, xtype, Common) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; } /* ---------------------------------------------------------------------- */ /* solve using L, D, L', P, or some combination */ /* ---------------------------------------------------------------------- */ if (Bset) { /* ------------------------------------------------------------------ */ /* solve for a subset of x, with a sparse b */ /* ------------------------------------------------------------------ */ Int save_realloc_state ; #ifndef NSUPERNODAL /* convert a supernodal L to simplicial when using Bset */ if (L->is_super) { /* Can only use Bset on a simplicial factorization. The supernodal * factor L is converted to simplicial, leaving the xtype unchanged * (real, complex, or zomplex). Since the supernodal factorization * is already LL', it is left in that form. This conversion uses * the ll_super_to_simplicial_numeric function in * cholmod_change_factor. */ CHOLMOD(change_factor) ( CHOLMOD_REAL, /* ignored, since L is already numeric */ TRUE, /* convert to LL' (no change to num. values) */ FALSE, /* convert to simplicial */ FALSE, /* do not pack the columns of L */ FALSE, /* (ignored) */ L, Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory, L is returned unchanged */ return (FALSE) ; } } #endif /* L, X, and B are all the same xtype */ /* ensure Y is the the right size */ Y = CHOLMOD(ensure_dense) (Y_Handle, 1, n, 1, L->xtype, Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ return (FALSE) ; } /* ------------------------------------------------------------------ */ /* get the inverse permutation, constructing it if needed */ /* ------------------------------------------------------------------ */ DEBUG (CHOLMOD (dump_perm) (Perm, n,n, "Perm", Common)) ; if ((sys == CHOLMOD_A || sys == CHOLMOD_P) && Perm != NULL) { /* The inverse permutation IPerm is used for the c=Pb step, which is needed only for solving Ax=b or x=Pb. No other steps should use IPerm */ if (L->IPerm == NULL) { /* construct the inverse permutation. This is done only once * and then stored in L permanently. */ L->IPerm = CHOLMOD(malloc) (n, sizeof (Int), Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ return (FALSE) ; } IPerm = L->IPerm ; for (k = 0 ; k < n ; k++) { IPerm [Perm [k]] = k ; } } /* x=A\b and x=Pb both need IPerm */ IPerm = L->IPerm ; } if (sys == CHOLMOD_P) { /* x=Pb needs to turn off the subsequent x=P'b permutation */ Perm = NULL ; } DEBUG (CHOLMOD (dump_perm) (Perm, n,n, "Perm", Common)) ; DEBUG (CHOLMOD (dump_perm) (IPerm, n,n, "IPerm", Common)) ; /* ------------------------------------------------------------------ */ /* ensure Xset is the right size and type */ /* ------------------------------------------------------------------ */ /* Xset is n-by-1, nzmax >= n, pattern-only, packed, unsorted */ Xset = *Xset_Handle ; if (Xset == NULL || (Int) Xset->nrow != n || (Int) Xset->ncol != 1 || (Int) Xset->nzmax < n || Xset->itype != CHOLMOD_PATTERN) { /* this is done only once, for the 1st call to cholmod_solve */ CHOLMOD(free_sparse) (Xset_Handle, Common) ; Xset = CHOLMOD(allocate_sparse) (n, 1, n, FALSE, TRUE, 0, CHOLMOD_PATTERN, Common) ; *Xset_Handle = Xset ; } Xset->sorted = FALSE ; Xset->stype = 0 ; if (Common->status < CHOLMOD_OK) { /* out of memory */ return (FALSE) ; } /* -------------------------------------------------------------- */ /* ensure Flag of size n, and 3*n Int workspace is available */ /* -------------------------------------------------------------- */ /* does no work if prior calls already allocated enough space */ CHOLMOD(allocate_work) (n, 3*n, 0, Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ return (FALSE) ; } /* [ use Iwork (n:3n-1) for Ci and Yseti */ Iwork = Common->Iwork ; /* Iwork (0:n-1) is not used because it is used by check_perm, print_perm, check_sparse, and print_sparse */ Ci = Iwork + n ; Yseti = Ci + n ; /* reallocating workspace would break Ci and Yseti */ save_realloc_state = Common->no_workspace_reallocate ; Common->no_workspace_reallocate = TRUE ; /* -------------------------------------------------------------- */ /* C = permuted Bset, to correspond to the permutation of L */ /* -------------------------------------------------------------- */ /* C = IPerm (Bset) */ DEBUG (CHOLMOD(dump_sparse) (Bset, "Bset", Common)) ; Bsetp = Bset->p ; Bseti = Bset->i ; Bsetnz = Bset->nz ; blen = (Bset->packed) ? Bsetp [1] : Bsetnz [0] ; /* C = spones (P*B) or C = spones (B) if IPerm is NULL */ C = &C_header ; C->nrow = n ; C->ncol = 1 ; C->nzmax = n ; C->packed = TRUE ; C->stype = 0 ; C->itype = ITYPE ; C->xtype = CHOLMOD_PATTERN ; C->dtype = CHOLMOD_DOUBLE ; C->nz = NULL ; C->p = Cp ; C->i = Ci ; C->x = NULL ; C->z = NULL ; C->sorted = FALSE ; Cp [0] = 0 ; Cp [1] = blen ; for (p = 0 ; p < blen ; p++) { Int iold = Bseti [p] ; Ci [p] = IPerm ? IPerm [iold] : iold ; } DEBUG (CHOLMOD (dump_sparse) (C, "C", Common)) ; /* create a sparse column Yset from Iwork (n:2n-1) */ Yset = &Yset_header ; Yset->nrow = n ; Yset->ncol = 1 ; Yset->nzmax = n ; Yset->packed = TRUE ; Yset->stype = 0 ; Yset->itype = ITYPE ; Yset->xtype = CHOLMOD_PATTERN ; Yset->dtype = CHOLMOD_DOUBLE ; Yset->nz = NULL ; Yset->p = Ysetp ; Yset->i = Yseti ; Yset->x = NULL ; Yset->z = NULL ; Yset->sorted = FALSE ; Ysetp [0] = 0 ; Ysetp [1] = 0 ; DEBUG (CHOLMOD (dump_sparse) (Yset, "Yset empty", Common)) ; /* -------------------------------------------------------------- */ /* Yset = nonzero pattern of L\C, or just C itself */ /* -------------------------------------------------------------- */ /* this takes O(ysetlen) time */ if (sys == CHOLMOD_P || sys == CHOLMOD_Pt || sys == CHOLMOD_D) { Ysetp [1] = blen ; for (p = 0 ; p < blen ; p++) { Yseti [p] = Ci [p] ; } } else { if (!CHOLMOD(lsolve_pattern) (C, L, Yset, Common)) { Common->no_workspace_reallocate = save_realloc_state ; return (FALSE) ; } } DEBUG (CHOLMOD (dump_sparse) (Yset, "Yset", Common)) ; /* -------------------------------------------------------------- */ /* clear the parts of Y that we will use in the solve */ /* -------------------------------------------------------------- */ Yx = Y->x ; Yz = Y->z ; ysetlen = Ysetp [1] ; switch (L->xtype) { case CHOLMOD_REAL: for (p = 0 ; p < ysetlen ; p++) { i = Yseti [p] ; Yx [i] = 0 ; } break ; case CHOLMOD_COMPLEX: for (p = 0 ; p < ysetlen ; p++) { i = Yseti [p] ; Yx [2*i ] = 0 ; Yx [2*i+1] = 0 ; } break ; case CHOLMOD_ZOMPLEX: for (p = 0 ; p < ysetlen ; p++) { i = Yseti [p] ; Yx [i] = 0 ; Yz [i] = 0 ; } break ; } DEBUG (CHOLMOD (dump_dense) (Y, "Y (Yset) = 0", Common)) ; /* -------------------------------------------------------------- */ /* scatter and permute B into Y */ /* -------------------------------------------------------------- */ /* Y (C) = B (Bset) */ Bx = B->x ; Bz = B->z ; switch (L->xtype) { case CHOLMOD_REAL: for (p = 0 ; p < blen ; p++) { Int iold = Bseti [p] ; Int inew = Ci [p] ; Yx [inew] = Bx [iold] ; } break ; case CHOLMOD_COMPLEX: for (p = 0 ; p < blen ; p++) { Int iold = Bseti [p] ; Int inew = Ci [p] ; Yx [2*inew ] = Bx [2*iold ] ; Yx [2*inew+1] = Bx [2*iold+1] ; } break ; case CHOLMOD_ZOMPLEX: for (p = 0 ; p < blen ; p++) { Int iold = Bseti [p] ; Int inew = Ci [p] ; Yx [inew] = Bx [iold] ; Yz [inew] = Bz [iold] ; } break ; } DEBUG (CHOLMOD (dump_dense) (Y, "Y (C) = B (Bset)", Common)) ; /* -------------------------------------------------------------- */ /* solve Y = (L' \ (L \ Y'))', or other system, with template */ /* -------------------------------------------------------------- */ /* the solve only iterates over columns in Yseti [0...ysetlen-1] */ if (! (sys == CHOLMOD_P || sys == CHOLMOD_Pt)) { switch (L->xtype) { case CHOLMOD_REAL: r_simplicial_solver (sys, L, Y, Yseti, ysetlen) ; break ; case CHOLMOD_COMPLEX: c_simplicial_solver (sys, L, Y, Yseti, ysetlen) ; break ; case CHOLMOD_ZOMPLEX: z_simplicial_solver (sys, L, Y, Yseti, ysetlen) ; break ; } } DEBUG (CHOLMOD (dump_dense) (Y, "Y after solve", Common)) ; /* -------------------------------------------------------------- */ /* X = P'*Y, but only for rows in Yset, and create Xset */ /* -------------------------------------------------------------- */ /* X (Perm (Yset)) = Y (Yset) */ Xx = X->x ; Xz = X->z ; Xseti = Xset->i ; Xsetp = Xset->p ; switch (L->xtype) { case CHOLMOD_REAL: for (p = 0 ; p < ysetlen ; p++) { Int inew = Yseti [p] ; Int iold = Perm ? Perm [inew] : inew ; Xx [iold] = Yx [inew] ; Xseti [p] = iold ; } break ; case CHOLMOD_COMPLEX: for (p = 0 ; p < ysetlen ; p++) { Int inew = Yseti [p] ; Int iold = Perm ? Perm [inew] : inew ; Xx [2*iold ] = Yx [2*inew] ; Xx [2*iold+1] = Yx [2*inew+1] ; Xseti [p] = iold ; } break ; case CHOLMOD_ZOMPLEX: for (p = 0 ; p < ysetlen ; p++) { Int inew = Yseti [p] ; Int iold = Perm ? Perm [inew] : inew ; Xx [iold] = Yx [inew] ; Xz [iold] = Yz [inew] ; Xseti [p] = iold ; } break ; } Xsetp [0] = 0 ; Xsetp [1] = ysetlen ; DEBUG (CHOLMOD(dump_sparse) (Xset, "Xset", Common)) ; DEBUG (CHOLMOD(dump_dense) (X, "X", Common)) ; Common->no_workspace_reallocate = save_realloc_state ; /* done using Iwork (n:3n-1) for Ci and Yseti ] */ } else if (sys == CHOLMOD_P) { /* ------------------------------------------------------------------ */ /* x = P*b */ /* ------------------------------------------------------------------ */ perm (B, Perm, 0, nrhs, X) ; } else if (sys == CHOLMOD_Pt) { /* ------------------------------------------------------------------ */ /* x = P'*b */ /* ------------------------------------------------------------------ */ iperm (B, Perm, 0, nrhs, X) ; } else if (L->is_super) { /* ------------------------------------------------------------------ */ /* solve using a supernodal LL' factorization */ /* ------------------------------------------------------------------ */ #ifndef NSUPERNODAL /* allocate workspace */ cholmod_dense *E ; Int dual ; Common->blas_ok = TRUE ; dual = (L->xtype == CHOLMOD_REAL && B->xtype != CHOLMOD_REAL) ? 2 : 1 ; Y = CHOLMOD(ensure_dense) (Y_Handle, n, dual*nrhs, n, L->xtype, Common); E = CHOLMOD(ensure_dense) (E_Handle, dual*nrhs, L->maxesize, dual*nrhs, L->xtype, Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ return (FALSE) ; } perm (B, Perm, 0, nrhs, Y) ; /* Y = P*B */ if (sys == CHOLMOD_A || sys == CHOLMOD_LDLt) { CHOLMOD(super_lsolve) (L, Y, E, Common) ; /* Y = L\Y */ CHOLMOD(super_ltsolve) (L, Y, E, Common) ; /* Y = L'\Y*/ } else if (sys == CHOLMOD_L || sys == CHOLMOD_LD) { CHOLMOD(super_lsolve) (L, Y, E, Common) ; /* Y = L\Y */ } else if (sys == CHOLMOD_Lt || sys == CHOLMOD_DLt) { CHOLMOD(super_ltsolve) (L, Y, E, Common) ; /* Y = L'\Y*/ } iperm (Y, Perm, 0, nrhs, X) ; /* X = P'*Y */ if (CHECK_BLAS_INT && !Common->blas_ok) { /* Integer overflow in the BLAS. This is probably impossible, * since the BLAS were used to create the supernodal factorization. * It might be possible for the calls to the BLAS to differ between * factorization and forward/backsolves, however. This statement * is untested; it does not appear in the compiled code if * CHECK_BLAS_INT is true (when the same integer is used in * CHOLMOD and the BLAS. */ return (FALSE) ; } #else /* CHOLMOD Supernodal module not installed */ ERROR (CHOLMOD_NOT_INSTALLED,"Supernodal module not installed") ; #endif } else { /* ------------------------------------------------------------------ */ /* solve using a simplicial LL' or LDL' factorization */ /* ------------------------------------------------------------------ */ if (L->xtype == CHOLMOD_REAL && B->xtype == CHOLMOD_REAL) { /* L, B, and Y are all real */ /* solve with up to 4 columns of B at a time */ ncols = 4 ; nr = MAX (4, nrhs) ; ytype = CHOLMOD_REAL ; } else if (L->xtype == CHOLMOD_REAL) { /* L is real and B is complex or zomplex */ /* solve with one column of B (real/imag), at a time */ ncols = 1 ; nr = 2 ; ytype = CHOLMOD_REAL ; } else { /* L is complex or zomplex, B is real/complex/zomplex, Y has the * same complexity as L. Solve with one column of B at a time. */ ncols = 1 ; nr = 1 ; ytype = L->xtype ; } Y = CHOLMOD(ensure_dense) (Y_Handle, nr, n, nr, ytype, Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ return (FALSE) ; } for (k1 = 0 ; k1 < nrhs ; k1 += ncols) { /* -------------------------------------------------------------- */ /* Y = B (P, k1:k1+ncols-1)' = (P * B (:,...))' */ /* -------------------------------------------------------------- */ ptrans (B, Perm, k1, ncols, Y) ; /* -------------------------------------------------------------- */ /* solve Y = (L' \ (L \ Y'))', or other system, with template */ /* -------------------------------------------------------------- */ switch (L->xtype) { case CHOLMOD_REAL: r_simplicial_solver (sys, L, Y, NULL, 0) ; break ; case CHOLMOD_COMPLEX: c_simplicial_solver (sys, L, Y, NULL, 0) ; break ; case CHOLMOD_ZOMPLEX: z_simplicial_solver (sys, L, Y, NULL, 0) ; break ; } /* -------------------------------------------------------------- */ /* X (P, k1:k2+ncols-1) = Y' */ /* -------------------------------------------------------------- */ iptrans (Y, Perm, k1, ncols, X) ; } } /* printf ("bye from solve2\n") ; */ DEBUG (CHOLMOD(dump_dense) (X, "X result", Common)) ; return (TRUE) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Cholesky/cholmod_amd.c0000644000076500000240000001606213524616144026671 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Cholesky/cholmod_amd ================================================= */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Cholesky Module. Copyright (C) 2005-2006, Timothy A. Davis * The CHOLMOD/Cholesky Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* CHOLMOD interface to the AMD ordering routine. Orders A if the matrix is * symmetric. On output, Perm [k] = i if row/column i of A is the kth * row/column of P*A*P'. This corresponds to A(p,p) in MATLAB notation. * * If A is unsymmetric, cholmod_amd orders A*A'. On output, Perm [k] = i if * row/column i of A*A' is the kth row/column of P*A*A'*P'. This corresponds to * A(p,:)*A(p,:)' in MATLAB notation. If f is present, A(p,f)*A(p,f)' is * ordered. * * Computes the flop count for a subsequent LL' factorization, the number * of nonzeros in L, and the number of nonzeros in the matrix ordered (A, * A*A' or A(:,f)*A(:,f)'). * * workspace: Iwork (6*nrow). Head (nrow). * * Allocates a temporary copy of A+A' or A*A' (with * both upper and lower triangular parts) as input to AMD. * * Supports any xtype (pattern, real, complex, or zomplex) */ #ifndef NCHOLESKY #include "cholmod_internal.h" #include "amd.h" #include "cholmod_cholesky.h" #if (!defined (AMD_VERSION) || (AMD_VERSION < AMD_VERSION_CODE (2,0))) #error "AMD v2.0 or later is required" #endif /* ========================================================================== */ /* === cholmod_amd ========================================================== */ /* ========================================================================== */ int CHOLMOD(amd) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to order */ Int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ /* ---- output --- */ Int *Perm, /* size A->nrow, output permutation */ /* --------------- */ cholmod_common *Common ) { double Info [AMD_INFO], Control2 [AMD_CONTROL], *Control ; Int *Cp, *Len, *Nv, *Head, *Elen, *Degree, *Wi, *Iwork, *Next ; cholmod_sparse *C ; Int j, n, cnz ; size_t s ; int ok = TRUE ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (A, FALSE) ; n = A->nrow ; RETURN_IF_NULL (Perm, FALSE) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; Common->status = CHOLMOD_OK ; if (n == 0) { /* nothing to do */ Common->fl = 0 ; Common->lnz = 0 ; Common->anz = 0 ; return (TRUE) ; } /* ---------------------------------------------------------------------- */ /* get workspace */ /* ---------------------------------------------------------------------- */ /* Note: this is less than the space used in cholmod_analyze, so if * cholmod_amd is being called by that routine, no space will be * allocated. */ /* s = MAX (6*n, A->ncol) */ s = CHOLMOD(mult_size_t) (n, 6, &ok) ; if (!ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return (FALSE) ; } s = MAX (s, A->ncol) ; CHOLMOD(allocate_work) (n, s, 0, Common) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; } Iwork = Common->Iwork ; Degree = Iwork ; /* size n */ Wi = Iwork + n ; /* size n */ Len = Iwork + 2*((size_t) n) ; /* size n */ Nv = Iwork + 3*((size_t) n) ; /* size n */ Next = Iwork + 4*((size_t) n) ; /* size n */ Elen = Iwork + 5*((size_t) n) ; /* size n */ Head = Common->Head ; /* size n+1, but only n is used */ /* ---------------------------------------------------------------------- */ /* construct the input matrix for AMD */ /* ---------------------------------------------------------------------- */ if (A->stype == 0) { /* C = A*A' or A(:,f)*A(:,f)', add extra space of nnz(C)/2+n to C */ C = CHOLMOD(aat) (A, fset, fsize, -2, Common) ; } else { /* C = A+A', but use only the upper triangular part of A if A->stype = 1 * and only the lower part of A if A->stype = -1. Add extra space of * nnz(C)/2+n to C. */ C = CHOLMOD(copy) (A, 0, -2, Common) ; } if (Common->status < CHOLMOD_OK) { /* out of memory, fset invalid, or other error */ return (FALSE) ; } Cp = C->p ; for (j = 0 ; j < n ; j++) { Len [j] = Cp [j+1] - Cp [j] ; } /* C does not include the diagonal, and both upper and lower parts. * Common->anz includes the diagonal, and just the lower part of C */ cnz = Cp [n] ; Common->anz = cnz / 2 + n ; /* ---------------------------------------------------------------------- */ /* order C using AMD */ /* ---------------------------------------------------------------------- */ /* get parameters */ if (Common->current < 0 || Common->current >= CHOLMOD_MAXMETHODS) { /* use AMD defaults */ Control = NULL ; } else { Control = Control2 ; Control [AMD_DENSE] = Common->method [Common->current].prune_dense ; Control [AMD_AGGRESSIVE] = Common->method [Common->current].aggressive ; } /* AMD_2 does not use amd_malloc and amd_free, but set these pointers just * be safe. */ amd_malloc = Common->malloc_memory ; amd_free = Common->free_memory ; amd_calloc = Common->calloc_memory ; amd_realloc = Common->realloc_memory ; /* AMD_2 doesn't print anything either, but future versions might, * so set the amd_printf pointer too. */ amd_printf = Common->print_function ; #ifdef LONG amd_l2 (n, C->p, C->i, Len, C->nzmax, cnz, Nv, Next, Perm, Head, Elen, Degree, Wi, Control, Info) ; #else amd_2 (n, C->p, C->i, Len, C->nzmax, cnz, Nv, Next, Perm, Head, Elen, Degree, Wi, Control, Info) ; #endif /* LL' flop count. Need to subtract n for LL' flop count. Note that this * is a slight upper bound which is often exact (see AMD/Source/amd_2.c for * details). cholmod_analyze computes an exact flop count and fill-in. */ Common->fl = Info [AMD_NDIV] + 2 * Info [AMD_NMULTSUBS_LDL] + n ; /* Info [AMD_LNZ] excludes the diagonal */ Common->lnz = n + Info [AMD_LNZ] ; /* ---------------------------------------------------------------------- */ /* free the AMD workspace and clear the persistent workspace in Common */ /* ---------------------------------------------------------------------- */ ASSERT (IMPLIES (Common->status == CHOLMOD_OK, CHOLMOD(dump_perm) (Perm, n, n, "AMD2 perm", Common))) ; CHOLMOD(free_sparse) (&C, Common) ; for (j = 0 ; j <= n ; j++) { Head [j] = EMPTY ; } return (TRUE) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Cholesky/t_cholmod_ltsolve.c0000644000076500000240000005463313524616144030151 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Cholesky/t_cholmod_ltsolve =========================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Cholesky Module. Copyright (C) 2005-2013, Timothy A. Davis * The CHOLMOD/Cholesky Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Template routine to solve L'x=b with unit or non-unit diagonal, or * solve DL'x=b. * * The numeric xtype of L and Y must match. Y contains b on input and x on * output, stored in row-form. Y is nrow-by-n, where nrow must equal 1 for the * complex or zomplex cases, and nrow <= 4 for the real case. * * This file is not compiled separately. It is included in t_cholmod_solve.c * instead. It contains no user-callable routines. * * workspace: none * * Supports real, complex, and zomplex factors. */ /* undefine all prior definitions */ #undef FORM_NAME #undef LSOLVE #undef DIAG /* -------------------------------------------------------------------------- */ /* define the method */ /* -------------------------------------------------------------------------- */ #ifdef LL /* LL': solve Lx=b with non-unit diagonal */ #define FORM_NAME(prefix,rank) prefix ## ll_ltsolve_ ## rank #define DIAG #elif defined (LD) /* LDL': solve LDx=b */ #define FORM_NAME(prefix,rank) prefix ## ldl_dltsolve_ ## rank #define DIAG #else /* LDL': solve Lx=b with unit diagonal */ #define FORM_NAME(prefix,rank) prefix ## ldl_ltsolve_ ## rank #endif /* LSOLVE(k) defines the name of a routine for an n-by-k right-hand-side. */ #define LSOLVE(prefix,rank) FORM_NAME(prefix,rank) #ifdef REAL /* ========================================================================== */ /* === LSOLVE (1) =========================================================== */ /* ========================================================================== */ /* Solve L'x=b, where b has 1 column */ static void LSOLVE (PREFIX,1) ( cholmod_factor *L, double X [ ] /* n-by-1 in row form */ ) { double *Lx = L->x ; Int *Li = L->i ; Int *Lp = L->p ; Int *Lnz = L->nz ; Int j, n = L->n ; for (j = n-1 ; j >= 0 ; ) { /* get the start, end, and length of column j */ Int p = Lp [j] ; Int lnz = Lnz [j] ; Int pend = p + lnz ; /* find a chain of supernodes (up to j, j-1, and j-2) */ if (j < 4 || lnz != Lnz [j-1] - 1 || Li [Lp [j-1]+1] != j) { /* -------------------------------------------------------------- */ /* solve with a single column of L */ /* -------------------------------------------------------------- */ double y = X [j] ; #ifdef DIAG double d = Lx [p] ; #endif #ifdef LD y /= d ; #endif for (p++ ; p < pend ; p++) { y -= Lx [p] * X [Li [p]] ; } #ifdef LL X [j] = y / d ; #else X [j] = y ; #endif j-- ; /* advance to the next column of L */ } else if (lnz != Lnz [j-2]-2 || Li [Lp [j-2]+2] != j) { /* -------------------------------------------------------------- */ /* solve with a supernode of two columns of L */ /* -------------------------------------------------------------- */ double y [2], t ; Int q = Lp [j-1] ; #ifdef DIAG double d [2] ; d [0] = Lx [p] ; d [1] = Lx [q] ; #endif t = Lx [q+1] ; #ifdef LD y [0] = X [j ] / d [0] ; y [1] = X [j-1] / d [1] ; #else y [0] = X [j ] ; y [1] = X [j-1] ; #endif for (p++, q += 2 ; p < pend ; p++, q++) { Int i = Li [p] ; y [0] -= Lx [p] * X [i] ; y [1] -= Lx [q] * X [i] ; } #ifdef LL y [0] /= d [0] ; y [1] = (y [1] - t * y [0]) / d [1] ; #else y [1] -= t * y [0] ; #endif X [j ] = y [0] ; X [j-1] = y [1] ; j -= 2 ; /* advance to the next column of L */ } else { /* -------------------------------------------------------------- */ /* solve with a supernode of three columns of L */ /* -------------------------------------------------------------- */ double y [3], t [3] ; Int q = Lp [j-1] ; Int r = Lp [j-2] ; #ifdef DIAG double d [3] ; d [0] = Lx [p] ; d [1] = Lx [q] ; d [2] = Lx [r] ; #endif t [0] = Lx [q+1] ; t [1] = Lx [r+1] ; t [2] = Lx [r+2] ; #ifdef LD y [0] = X [j] / d [0] ; y [1] = X [j-1] / d [1] ; y [2] = X [j-2] / d [2] ; #else y [0] = X [j] ; y [1] = X [j-1] ; y [2] = X [j-2] ; #endif for (p++, q += 2, r += 3 ; p < pend ; p++, q++, r++) { Int i = Li [p] ; y [0] -= Lx [p] * X [i] ; y [1] -= Lx [q] * X [i] ; y [2] -= Lx [r] * X [i] ; } #ifdef LL y [0] /= d [0] ; y [1] = (y [1] - t [0] * y [0]) / d [1] ; y [2] = (y [2] - t [2] * y [0] - t [1] * y [1]) / d [2] ; #else y [1] -= t [0] * y [0] ; y [2] -= t [2] * y [0] + t [1] * y [1] ; #endif X [j-2] = y [2] ; X [j-1] = y [1] ; X [j ] = y [0] ; j -= 3 ; /* advance to the next column of L */ } } } /* ========================================================================== */ /* === LSOLVE (2) =========================================================== */ /* ========================================================================== */ /* Solve L'x=b, where b has 2 columns */ static void LSOLVE (PREFIX,2) ( cholmod_factor *L, double X [ ][2] /* n-by-2 in row form */ ) { double *Lx = L->x ; Int *Li = L->i ; Int *Lp = L->p ; Int *Lnz = L->nz ; Int j, n = L->n ; for (j = n-1 ; j >= 0 ; ) { /* get the start, end, and length of column j */ Int p = Lp [j] ; Int lnz = Lnz [j] ; Int pend = p + lnz ; /* find a chain of supernodes (up to j, j-1, and j-2) */ if (j < 4 || lnz != Lnz [j-1] - 1 || Li [Lp [j-1]+1] != j) { /* -------------------------------------------------------------- */ /* solve with a single column of L */ /* -------------------------------------------------------------- */ double y [2] ; #ifdef DIAG double d = Lx [p] ; #endif #ifdef LD y [0] = X [j][0] / d ; y [1] = X [j][1] / d ; #else y [0] = X [j][0] ; y [1] = X [j][1] ; #endif for (p++ ; p < pend ; p++) { Int i = Li [p] ; y [0] -= Lx [p] * X [i][0] ; y [1] -= Lx [p] * X [i][1] ; } #ifdef LL X [j][0] = y [0] / d ; X [j][1] = y [1] / d ; #else X [j][0] = y [0] ; X [j][1] = y [1] ; #endif j-- ; /* advance to the next column of L */ } else if (lnz != Lnz [j-2]-2 || Li [Lp [j-2]+2] != j) { /* -------------------------------------------------------------- */ /* solve with a supernode of two columns of L */ /* -------------------------------------------------------------- */ double y [2][2], t ; Int q = Lp [j-1] ; #ifdef DIAG double d [2] ; d [0] = Lx [p] ; d [1] = Lx [q] ; #endif t = Lx [q+1] ; #ifdef LD y [0][0] = X [j ][0] / d [0] ; y [0][1] = X [j ][1] / d [0] ; y [1][0] = X [j-1][0] / d [1] ; y [1][1] = X [j-1][1] / d [1] ; #else y [0][0] = X [j ][0] ; y [0][1] = X [j ][1] ; y [1][0] = X [j-1][0] ; y [1][1] = X [j-1][1] ; #endif for (p++, q += 2 ; p < pend ; p++, q++) { Int i = Li [p] ; y [0][0] -= Lx [p] * X [i][0] ; y [0][1] -= Lx [p] * X [i][1] ; y [1][0] -= Lx [q] * X [i][0] ; y [1][1] -= Lx [q] * X [i][1] ; } #ifdef LL y [0][0] /= d [0] ; y [0][1] /= d [0] ; y [1][0] = (y [1][0] - t * y [0][0]) / d [1] ; y [1][1] = (y [1][1] - t * y [0][1]) / d [1] ; #else y [1][0] -= t * y [0][0] ; y [1][1] -= t * y [0][1] ; #endif X [j ][0] = y [0][0] ; X [j ][1] = y [0][1] ; X [j-1][0] = y [1][0] ; X [j-1][1] = y [1][1] ; j -= 2 ; /* advance to the next column of L */ } else { /* -------------------------------------------------------------- */ /* solve with a supernode of three columns of L */ /* -------------------------------------------------------------- */ double y [3][2], t [3] ; Int q = Lp [j-1] ; Int r = Lp [j-2] ; #ifdef DIAG double d [3] ; d [0] = Lx [p] ; d [1] = Lx [q] ; d [2] = Lx [r] ; #endif t [0] = Lx [q+1] ; t [1] = Lx [r+1] ; t [2] = Lx [r+2] ; #ifdef LD y [0][0] = X [j ][0] / d [0] ; y [0][1] = X [j ][1] / d [0] ; y [1][0] = X [j-1][0] / d [1] ; y [1][1] = X [j-1][1] / d [1] ; y [2][0] = X [j-2][0] / d [2] ; y [2][1] = X [j-2][1] / d [2] ; #else y [0][0] = X [j ][0] ; y [0][1] = X [j ][1] ; y [1][0] = X [j-1][0] ; y [1][1] = X [j-1][1] ; y [2][0] = X [j-2][0] ; y [2][1] = X [j-2][1] ; #endif for (p++, q += 2, r += 3 ; p < pend ; p++, q++, r++) { Int i = Li [p] ; y [0][0] -= Lx [p] * X [i][0] ; y [0][1] -= Lx [p] * X [i][1] ; y [1][0] -= Lx [q] * X [i][0] ; y [1][1] -= Lx [q] * X [i][1] ; y [2][0] -= Lx [r] * X [i][0] ; y [2][1] -= Lx [r] * X [i][1] ; } #ifdef LL y [0][0] /= d [0] ; y [0][1] /= d [0] ; y [1][0] = (y [1][0] - t [0] * y [0][0]) / d [1] ; y [1][1] = (y [1][1] - t [0] * y [0][1]) / d [1] ; y [2][0] = (y [2][0] - t [2] * y [0][0] - t [1] * y [1][0]) / d [2]; y [2][1] = (y [2][1] - t [2] * y [0][1] - t [1] * y [1][1]) / d [2]; #else y [1][0] -= t [0] * y [0][0] ; y [1][1] -= t [0] * y [0][1] ; y [2][0] -= t [2] * y [0][0] + t [1] * y [1][0] ; y [2][1] -= t [2] * y [0][1] + t [1] * y [1][1] ; #endif X [j ][0] = y [0][0] ; X [j ][1] = y [0][1] ; X [j-1][0] = y [1][0] ; X [j-1][1] = y [1][1] ; X [j-2][0] = y [2][0] ; X [j-2][1] = y [2][1] ; j -= 3 ; /* advance to the next column of L */ } } } /* ========================================================================== */ /* === LSOLVE (3) =========================================================== */ /* ========================================================================== */ /* Solve L'x=b, where b has 3 columns */ static void LSOLVE (PREFIX,3) ( cholmod_factor *L, double X [ ][3] /* n-by-3 in row form */ ) { double *Lx = L->x ; Int *Li = L->i ; Int *Lp = L->p ; Int *Lnz = L->nz ; Int j, n = L->n ; for (j = n-1 ; j >= 0 ; ) { /* get the start, end, and length of column j */ Int p = Lp [j] ; Int lnz = Lnz [j] ; Int pend = p + lnz ; /* find a chain of supernodes (up to j, j-1, and j-2) */ if (j < 4 || lnz != Lnz [j-1] - 1 || Li [Lp [j-1]+1] != j) { /* -------------------------------------------------------------- */ /* solve with a single column of L */ /* -------------------------------------------------------------- */ double y [3] ; #ifdef DIAG double d = Lx [p] ; #endif #ifdef LD y [0] = X [j][0] / d ; y [1] = X [j][1] / d ; y [2] = X [j][2] / d ; #else y [0] = X [j][0] ; y [1] = X [j][1] ; y [2] = X [j][2] ; #endif for (p++ ; p < pend ; p++) { Int i = Li [p] ; y [0] -= Lx [p] * X [i][0] ; y [1] -= Lx [p] * X [i][1] ; y [2] -= Lx [p] * X [i][2] ; } #ifdef LL X [j][0] = y [0] / d ; X [j][1] = y [1] / d ; X [j][2] = y [2] / d ; #else X [j][0] = y [0] ; X [j][1] = y [1] ; X [j][2] = y [2] ; #endif j-- ; /* advance to the next column of L */ } else if (lnz != Lnz [j-2]-2 || Li [Lp [j-2]+2] != j) { /* -------------------------------------------------------------- */ /* solve with a supernode of two columns of L */ /* -------------------------------------------------------------- */ double y [2][3], t ; Int q = Lp [j-1] ; #ifdef DIAG double d [2] ; d [0] = Lx [p] ; d [1] = Lx [q] ; #endif t = Lx [q+1] ; #ifdef LD y [0][0] = X [j ][0] / d [0] ; y [0][1] = X [j ][1] / d [0] ; y [0][2] = X [j ][2] / d [0] ; y [1][0] = X [j-1][0] / d [1] ; y [1][1] = X [j-1][1] / d [1] ; y [1][2] = X [j-1][2] / d [1] ; #else y [0][0] = X [j ][0] ; y [0][1] = X [j ][1] ; y [0][2] = X [j ][2] ; y [1][0] = X [j-1][0] ; y [1][1] = X [j-1][1] ; y [1][2] = X [j-1][2] ; #endif for (p++, q += 2 ; p < pend ; p++, q++) { Int i = Li [p] ; y [0][0] -= Lx [p] * X [i][0] ; y [0][1] -= Lx [p] * X [i][1] ; y [0][2] -= Lx [p] * X [i][2] ; y [1][0] -= Lx [q] * X [i][0] ; y [1][1] -= Lx [q] * X [i][1] ; y [1][2] -= Lx [q] * X [i][2] ; } #ifdef LL y [0][0] /= d [0] ; y [0][1] /= d [0] ; y [0][2] /= d [0] ; y [1][0] = (y [1][0] - t * y [0][0]) / d [1] ; y [1][1] = (y [1][1] - t * y [0][1]) / d [1] ; y [1][2] = (y [1][2] - t * y [0][2]) / d [1] ; #else y [1][0] -= t * y [0][0] ; y [1][1] -= t * y [0][1] ; y [1][2] -= t * y [0][2] ; #endif X [j ][0] = y [0][0] ; X [j ][1] = y [0][1] ; X [j ][2] = y [0][2] ; X [j-1][0] = y [1][0] ; X [j-1][1] = y [1][1] ; X [j-1][2] = y [1][2] ; j -= 2 ; /* advance to the next column of L */ } else { /* -------------------------------------------------------------- */ /* solve with a supernode of three columns of L */ /* -------------------------------------------------------------- */ double y [3][3], t [3] ; Int q = Lp [j-1] ; Int r = Lp [j-2] ; #ifdef DIAG double d [3] ; d [0] = Lx [p] ; d [1] = Lx [q] ; d [2] = Lx [r] ; #endif t [0] = Lx [q+1] ; t [1] = Lx [r+1] ; t [2] = Lx [r+2] ; #ifdef LD y [0][0] = X [j ][0] / d [0] ; y [0][1] = X [j ][1] / d [0] ; y [0][2] = X [j ][2] / d [0] ; y [1][0] = X [j-1][0] / d [1] ; y [1][1] = X [j-1][1] / d [1] ; y [1][2] = X [j-1][2] / d [1] ; y [2][0] = X [j-2][0] / d [2] ; y [2][1] = X [j-2][1] / d [2] ; y [2][2] = X [j-2][2] / d [2] ; #else y [0][0] = X [j ][0] ; y [0][1] = X [j ][1] ; y [0][2] = X [j ][2] ; y [1][0] = X [j-1][0] ; y [1][1] = X [j-1][1] ; y [1][2] = X [j-1][2] ; y [2][0] = X [j-2][0] ; y [2][1] = X [j-2][1] ; y [2][2] = X [j-2][2] ; #endif for (p++, q += 2, r += 3 ; p < pend ; p++, q++, r++) { Int i = Li [p] ; y [0][0] -= Lx [p] * X [i][0] ; y [0][1] -= Lx [p] * X [i][1] ; y [0][2] -= Lx [p] * X [i][2] ; y [1][0] -= Lx [q] * X [i][0] ; y [1][1] -= Lx [q] * X [i][1] ; y [1][2] -= Lx [q] * X [i][2] ; y [2][0] -= Lx [r] * X [i][0] ; y [2][1] -= Lx [r] * X [i][1] ; y [2][2] -= Lx [r] * X [i][2] ; } #ifdef LL y [0][0] /= d [0] ; y [0][1] /= d [0] ; y [0][2] /= d [0] ; y [1][0] = (y [1][0] - t [0] * y [0][0]) / d [1] ; y [1][1] = (y [1][1] - t [0] * y [0][1]) / d [1] ; y [1][2] = (y [1][2] - t [0] * y [0][2]) / d [1] ; y [2][0] = (y [2][0] - t [2] * y [0][0] - t [1] * y [1][0]) / d [2]; y [2][1] = (y [2][1] - t [2] * y [0][1] - t [1] * y [1][1]) / d [2]; y [2][2] = (y [2][2] - t [2] * y [0][2] - t [1] * y [1][2]) / d [2]; #else y [1][0] -= t [0] * y [0][0] ; y [1][1] -= t [0] * y [0][1] ; y [1][2] -= t [0] * y [0][2] ; y [2][0] -= t [2] * y [0][0] + t [1] * y [1][0] ; y [2][1] -= t [2] * y [0][1] + t [1] * y [1][1] ; y [2][2] -= t [2] * y [0][2] + t [1] * y [1][2] ; #endif X [j ][0] = y [0][0] ; X [j ][1] = y [0][1] ; X [j ][2] = y [0][2] ; X [j-1][0] = y [1][0] ; X [j-1][1] = y [1][1] ; X [j-1][2] = y [1][2] ; X [j-2][0] = y [2][0] ; X [j-2][1] = y [2][1] ; X [j-2][2] = y [2][2] ; j -= 3 ; /* advance to the next column of L */ } } } /* ========================================================================== */ /* === LSOLVE (4) =========================================================== */ /* ========================================================================== */ /* Solve L'x=b, where b has 4 columns */ static void LSOLVE (PREFIX,4) ( cholmod_factor *L, double X [ ][4] /* n-by-4 in row form */ ) { double *Lx = L->x ; Int *Li = L->i ; Int *Lp = L->p ; Int *Lnz = L->nz ; Int j, n = L->n ; for (j = n-1 ; j >= 0 ; ) { /* get the start, end, and length of column j */ Int p = Lp [j] ; Int lnz = Lnz [j] ; Int pend = p + lnz ; /* find a chain of supernodes (up to j, j-1, and j-2) */ if (j < 4 || lnz != Lnz [j-1] - 1 || Li [Lp [j-1]+1] != j) { /* -------------------------------------------------------------- */ /* solve with a single column of L */ /* -------------------------------------------------------------- */ double y [4] ; #ifdef DIAG double d = Lx [p] ; #endif #ifdef LD y [0] = X [j][0] / d ; y [1] = X [j][1] / d ; y [2] = X [j][2] / d ; y [3] = X [j][3] / d ; #else y [0] = X [j][0] ; y [1] = X [j][1] ; y [2] = X [j][2] ; y [3] = X [j][3] ; #endif for (p++ ; p < pend ; p++) { Int i = Li [p] ; y [0] -= Lx [p] * X [i][0] ; y [1] -= Lx [p] * X [i][1] ; y [2] -= Lx [p] * X [i][2] ; y [3] -= Lx [p] * X [i][3] ; } #ifdef LL X [j][0] = y [0] / d ; X [j][1] = y [1] / d ; X [j][2] = y [2] / d ; X [j][3] = y [3] / d ; #else X [j][0] = y [0] ; X [j][1] = y [1] ; X [j][2] = y [2] ; X [j][3] = y [3] ; #endif j-- ; /* advance to the next column of L */ } else /* if (j == 1 || lnz != Lnz [j-2]-2 || Li [Lp [j-2]+2] != j) */ { /* -------------------------------------------------------------- */ /* solve with a supernode of two columns of L */ /* -------------------------------------------------------------- */ double y [2][4], t ; Int q = Lp [j-1] ; #ifdef DIAG double d [2] ; d [0] = Lx [p] ; d [1] = Lx [q] ; #endif t = Lx [q+1] ; #ifdef LD y [0][0] = X [j ][0] / d [0] ; y [0][1] = X [j ][1] / d [0] ; y [0][2] = X [j ][2] / d [0] ; y [0][3] = X [j ][3] / d [0] ; y [1][0] = X [j-1][0] / d [1] ; y [1][1] = X [j-1][1] / d [1] ; y [1][2] = X [j-1][2] / d [1] ; y [1][3] = X [j-1][3] / d [1] ; #else y [0][0] = X [j ][0] ; y [0][1] = X [j ][1] ; y [0][2] = X [j ][2] ; y [0][3] = X [j ][3] ; y [1][0] = X [j-1][0] ; y [1][1] = X [j-1][1] ; y [1][2] = X [j-1][2] ; y [1][3] = X [j-1][3] ; #endif for (p++, q += 2 ; p < pend ; p++, q++) { Int i = Li [p] ; y [0][0] -= Lx [p] * X [i][0] ; y [0][1] -= Lx [p] * X [i][1] ; y [0][2] -= Lx [p] * X [i][2] ; y [0][3] -= Lx [p] * X [i][3] ; y [1][0] -= Lx [q] * X [i][0] ; y [1][1] -= Lx [q] * X [i][1] ; y [1][2] -= Lx [q] * X [i][2] ; y [1][3] -= Lx [q] * X [i][3] ; } #ifdef LL y [0][0] /= d [0] ; y [0][1] /= d [0] ; y [0][2] /= d [0] ; y [0][3] /= d [0] ; y [1][0] = (y [1][0] - t * y [0][0]) / d [1] ; y [1][1] = (y [1][1] - t * y [0][1]) / d [1] ; y [1][2] = (y [1][2] - t * y [0][2]) / d [1] ; y [1][3] = (y [1][3] - t * y [0][3]) / d [1] ; #else y [1][0] -= t * y [0][0] ; y [1][1] -= t * y [0][1] ; y [1][2] -= t * y [0][2] ; y [1][3] -= t * y [0][3] ; #endif X [j ][0] = y [0][0] ; X [j ][1] = y [0][1] ; X [j ][2] = y [0][2] ; X [j ][3] = y [0][3] ; X [j-1][0] = y [1][0] ; X [j-1][1] = y [1][1] ; X [j-1][2] = y [1][2] ; X [j-1][3] = y [1][3] ; j -= 2 ; /* advance to the next column of L */ } /* NOTE: with 4 right-hand-sides, it suffices to exploit dynamic * supernodes of just size 1 and 2. 3-column supernodes are not * needed. */ } } #endif /* ========================================================================== */ /* === LSOLVE (k) =========================================================== */ /* ========================================================================== */ static void LSOLVE (PREFIX,k) ( cholmod_factor *L, cholmod_dense *Y, /* nr-by-n where nr is 1 to 4 */ Int *Yseti, Int ysetlen ) { #ifdef DIAG double d [1] ; #endif double yx [2] ; #ifdef ZOMPLEX double yz [1] ; double *Lz = L->z ; double *Xz = Y->z ; #endif double *Lx = L->x ; double *Xx = Y->x ; Int *Li = L->i ; Int *Lp = L->p ; Int *Lnz = L->nz ; Int n = L->n, jj, jjiters ; ASSERT (L->xtype == Y->xtype) ; /* L and Y must have the same xtype */ ASSERT (L->n == Y->ncol) ; /* dimensions must match */ ASSERT (Y->nrow == Y->d) ; /* leading dimension of Y = # rows of Y */ ASSERT (L->xtype != CHOLMOD_PATTERN) ; /* L is not symbolic */ ASSERT (!(L->is_super)) ; /* L is simplicial LL' or LDL' */ #ifdef REAL if (Yseti == NULL) { /* ------------------------------------------------------------------ */ /* real case, no Yseti, with 1 to 4 RHS's and dynamic supernodes */ /* ------------------------------------------------------------------ */ ASSERT (Y->nrow <= 4) ; switch (Y->nrow) { case 1: LSOLVE (PREFIX,1) (L, Y->x) ; break ; case 2: LSOLVE (PREFIX,2) (L, Y->x) ; break ; case 3: LSOLVE (PREFIX,3) (L, Y->x) ; break ; case 4: LSOLVE (PREFIX,4) (L, Y->x) ; break ; } } else #endif { /* ------------------------------------------------------------------ */ /* solve a complex linear system or solve with Yseti */ /* ------------------------------------------------------------------ */ ASSERT (Y->nrow == 1) ; jjiters = Yseti ? ysetlen : n ; for (jj = jjiters-1 ; jj >= 0 ; jj--) { Int j = Yseti ? Yseti [jj] : jj ; /* get the start, end, and length of column j */ Int p = Lp [j] ; Int lnz = Lnz [j] ; Int pend = p + lnz ; /* y = X [j] ; */ ASSIGN (yx,yz,0, Xx,Xz,j) ; #ifdef DIAG /* d = Lx [p] ; */ ASSIGN_REAL (d,0, Lx,p) ; #endif #ifdef LD /* y /= d ; */ DIV_REAL (yx,yz,0, yx,yz,0, d,0) ; #endif for (p++ ; p < pend ; p++) { /* y -= conj (Lx [p]) * X [Li [p]] ; */ Int i = Li [p] ; MULTSUBCONJ (yx,yz,0, Lx,Lz,p, Xx,Xz,i) ; } #ifdef LL /* X [j] = y / d ; */ DIV_REAL (Xx,Xz,j, yx,yz,0, d,0) ; #else /* X [j] = y ; */ ASSIGN (Xx,Xz,j, yx,yz,0) ; #endif } } } /* prepare for the next inclusion of this file in cholmod_solve.c */ #undef LL #undef LD python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Cholesky/cholmod_rowfac.c0000644000076500000240000005652513524616144027421 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Cholesky/cholmod_rowfac ============================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Cholesky Module. Copyright (C) 2005-2013, Timothy A. Davis * The CHOLMOD/Cholesky Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Full or incremental numerical LDL' or LL' factorization (simplicial, not * supernodal) cholmod_factorize is the "easy" wrapper for this code, but it * does not provide access to incremental factorization. * * cholmod_rowfac computes the full or incremental LDL' or LL' factorization of * A+beta*I (where A is symmetric) or A*F+beta*I (where A and F are unsymmetric * and only the upper triangular part of A*F+beta*I is used). It computes * L (and D, for LDL') one row at a time. beta is real. * * A is nrow-by-ncol or nrow-by-nrow. In "packed" form it is a conventional * column-oriented sparse matrix. Row indices of column j are in * Ai [Ap [j] ... Ap [j+1]-1] and values in the same locations of Ax. * will be faster if A has sorted columns. In "unpacked" form the column * of A ends at Ap [j] + Anz [j] - 1 instead of Ap [j+1] - 1. * * Row indices in each column of A can be sorted or unsorted, but the routine * routine works fastest if A is sorted, or if only triu(A) is provided * for the symmetric case. * * The unit-diagonal nrow-by-nrow output matrix L is returned in "unpacked" * column form, with row indices of column j in Li [Lp [j] ... * Lp [j] + Lnz [j] - 1] and values in the same location in Lx. The row * indices in each column of L are in sorted order. The unit diagonal of L * is not stored. * * L can be a simplicial symbolic or numeric (L->is_super must be FALSE). * A symbolic factor is converted immediately into a numeric factor containing * the identity matrix. * * For a full factorization, kstart = 0 and kend = nrow. The existing nonzero * entries (numerical values in L->x and L->z for the zomplex case, and indices * in L->i), if any, are overwritten. * * To compute an incremental factorization, select kstart and kend as the range * of rows of L you wish to compute. A correct factorization will be computed * only if all descendants of all nodes k = kstart to kend-1 in the etree have * been factorized by a prior call to this routine, and if rows kstart to kend-1 * have not been factorized. This condition is NOT checked on input. * * --------------- * Symmetric case: * --------------- * * The factorization (in MATLAB notation) is: * * S = beta*I + A * S = triu (S) + triu (S,1)' * L*D*L' = S, or L*L' = S * * A is a conventional sparse matrix in compressed column form. Only the * diagonal and upper triangular part of A is accessed; the lower * triangular part is ignored and assumed to be equal to the upper * triangular part. For an incremental factorization, only columns kstart * to kend-1 of A are accessed. F is not used. * * --------------- * Unsymmetric case: * --------------- * * The factorization (in MATLAB notation) is: * * S = beta*I + A*F * S = triu (S) + triu (S,1)' * L*D*L' = S, or L*L' = S * * The typical case is F=A'. Alternatively, if F=A(:,f)', then this * routine factorizes S = beta*I + A(:,f)*A(:,f)'. * * All of A and F are accessed, but only the upper triangular part of A*F * is used. F must be of size A->ncol by A->nrow. F is used for the * unsymmetric case only. F can be packed or unpacked and it need not be * sorted. * * For a complete factorization of beta*I + A*A', * this routine performs a number of flops exactly equal to: * * sum (for each column j of A) of (Anz (j)^2 + Anz (j)), to form S * + * sum (for each column j of L) of (Lnz (j)^2 + 3*Lnz (j)), to factorize S * * where Anz (j) is the number of nonzeros in column j of A, and Lnz (j) * is the number of nonzero in column j of L below the diagonal. * * * workspace: Flag (nrow), W (nrow if real, 2*nrow if complex/zomplex), * Iwork (nrow) * * Supports any xtype, except a pattern-only input matrix A cannot be * factorized. */ #ifndef NCHOLESKY #include "cholmod_internal.h" #include "cholmod_cholesky.h" /* ========================================================================== */ /* === subtree ============================================================== */ /* ========================================================================== */ /* Compute the nonzero pattern of the sparse triangular solve Lx=b, where L in * this case is L(0:k-1,0:k-1), and b is a column of A. This is done by * traversing the kth row-subtree of the elimination tree of L, starting from * each nonzero entry in b. The pattern is returned postordered, and is valid * for a subsequent numerical triangular solve of Lx=b. The elimination tree * can be provided in a Parent array, or extracted from the pattern of L itself. * * The pattern of x = inv(L)*b is returned in Stack [top...]. * Also scatters b, or a multiple of b, into the work vector W. * * The SCATTER macro is defines how the numerical values of A or A*A' are to be * scattered. * * PARENT(i) is a macro the defines how the etree is accessed. It is either: * #define PARENT(i) Parent [i] * #define PARENT(i) (Lnz [i] > 1) ? (Li [Lp [i] + 1]) : EMPTY */ #define SUBTREE \ for ( ; p < pend ; p++) \ { \ i = Ai [p] ; \ if (i <= k) \ { \ /* scatter the column of A, or A*A' into Wx and Wz */ \ SCATTER ; \ /* start at node i and traverse up the subtree, stop at node k */ \ for (len = 0 ; i < k && i != EMPTY && Flag [i] < mark ; i = parent) \ { \ /* L(k,i) is nonzero, and seen for the first time */ \ Stack [len++] = i ; /* place i on the stack */ \ Flag [i] = mark ; /* mark i as visited */ \ parent = PARENT (i) ; /* traverse up the etree to the parent */ \ } \ /* move the path down to the bottom of the stack */ \ while (len > 0) \ { \ Stack [--top] = Stack [--len] ; \ } \ } \ else if (sorted) \ { \ break ; \ } \ } /* ========================================================================== */ /* === TEMPLATE ============================================================= */ /* ========================================================================== */ #define REAL #include "t_cholmod_rowfac.c" #define COMPLEX #include "t_cholmod_rowfac.c" #define ZOMPLEX #include "t_cholmod_rowfac.c" #define MASK #define REAL #include "t_cholmod_rowfac.c" #define COMPLEX #include "t_cholmod_rowfac.c" #define ZOMPLEX #include "t_cholmod_rowfac.c" #undef MASK /* ========================================================================== */ /* === cholmod_row_subtree ================================================== */ /* ========================================================================== */ /* Compute the nonzero pattern of the solution to the lower triangular system * L(0:k-1,0:k-1) * x = A (0:k-1,k) if A is symmetric, or * L(0:k-1,0:k-1) * x = A (0:k-1,:) * A (:,k)' if A is unsymmetric. * This gives the nonzero pattern of row k of L (excluding the diagonal). * The pattern is returned postordered. * * The symmetric case requires A to be in symmetric-upper form. * * The result is returned in R, a pre-allocated sparse matrix of size nrow-by-1, * with R->nzmax >= nrow. R is assumed to be packed (Rnz [0] is not updated); * the number of entries in R is given by Rp [0]. * * FUTURE WORK: a very minor change to this routine could allow it to compute * the nonzero pattern of x for any system Lx=b. The SUBTREE macro would need * to change, to eliminate its dependence on k. * * workspace: Flag (nrow) */ int CHOLMOD(row_subtree) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to analyze */ cholmod_sparse *F, /* used for A*A' case only. F=A' or A(:,f)' */ size_t krow, /* row k of L */ Int *Parent, /* elimination tree */ /* ---- output --- */ cholmod_sparse *R, /* pattern of L(k,:), 1-by-n with R->nzmax >= n */ /* --------------- */ cholmod_common *Common ) { Int *Rp, *Stack, *Flag, *Ap, *Ai, *Anz, *Fp, *Fi, *Fnz ; Int p, pend, parent, t, stype, nrow, k, pf, pfend, Fpacked, packed, sorted, top, len, i, mark ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (A, FALSE) ; RETURN_IF_NULL (R, FALSE) ; RETURN_IF_NULL (Parent, FALSE) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; RETURN_IF_XTYPE_INVALID (R, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; stype = A->stype ; if (stype == 0) { RETURN_IF_NULL (F, FALSE) ; RETURN_IF_XTYPE_INVALID (F, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; } if (krow >= A->nrow) { ERROR (CHOLMOD_INVALID, "subtree: k invalid") ; return (FALSE) ; } if (R->ncol != 1 || A->nrow != R->nrow || A->nrow > R->nzmax) { ERROR (CHOLMOD_INVALID, "subtree: R invalid") ; return (FALSE) ; } Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ nrow = A->nrow ; CHOLMOD(allocate_work) (nrow, 0, 0, Common) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; } ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ if (stype > 0) { /* symmetric upper case: F is not needed. It may be NULL */ Fp = NULL ; Fi = NULL ; Fnz = NULL ; Fpacked = TRUE ; } else if (stype == 0) { /* unsymmetric case: F is required. */ Fp = F->p ; Fi = F->i ; Fnz = F->nz ; Fpacked = F->packed ; } else { /* symmetric lower triangular form not supported */ ERROR (CHOLMOD_INVALID, "symmetric lower not supported") ; return (FALSE) ; } Ap = A->p ; Ai = A->i ; Anz = A->nz ; packed = A->packed ; sorted = A->sorted ; k = krow ; Stack = R->i ; /* ---------------------------------------------------------------------- */ /* get workspace */ /* ---------------------------------------------------------------------- */ Flag = Common->Flag ; /* size nrow, Flag [i] < mark must hold */ /* mark = CHOLMOD(clear_flag) (Common) ; */ CHOLMOD_CLEAR_FLAG (Common) ; mark = Common->mark ; /* ---------------------------------------------------------------------- */ /* compute the pattern of L(k,:) */ /* ---------------------------------------------------------------------- */ top = nrow ; /* Stack is empty */ Flag [k] = mark ; /* do not include diagonal entry in Stack */ #define SCATTER /* do not scatter numerical values */ #define PARENT(i) Parent [i] /* use Parent for etree */ if (stype != 0) { /* scatter kth col of triu (A), get pattern L(k,:) */ p = Ap [k] ; pend = (packed) ? (Ap [k+1]) : (p + Anz [k]) ; SUBTREE ; } else { /* scatter kth col of triu (beta*I+AA'), get pattern L(k,:) */ pf = Fp [k] ; pfend = (Fpacked) ? (Fp [k+1]) : (pf + Fnz [k]) ; for ( ; pf < pfend ; pf++) { /* get nonzero entry F (t,k) */ t = Fi [pf] ; p = Ap [t] ; pend = (packed) ? (Ap [t+1]) : (p + Anz [t]) ; SUBTREE ; } } #undef SCATTER #undef PARENT /* shift the stack upwards, to the first part of R */ len = nrow - top ; for (i = 0 ; i < len ; i++) { Stack [i] = Stack [top + i] ; } Rp = R->p ; Rp [0] = 0 ; Rp [1] = len ; R->sorted = FALSE ; CHOLMOD(clear_flag) (Common) ; ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; return (TRUE) ; } /* ========================================================================== */ /* === cholmod_lsolve_pattern =============================================== */ /* ========================================================================== */ /* Compute the nonzero pattern of Y=L\B. L must be simplicial, and B * must be a single sparse column vector with B->stype = 0. The values of * B are not used; it just specifies a nonzero pattern. The pattern of * Y is not sorted, but is in topological order instead (suitable for a * sparse forward/backsolve). */ int CHOLMOD(lsolve_pattern) ( /* ---- input ---- */ cholmod_sparse *B, /* sparse right-hand-side (a single sparse column) */ cholmod_factor *L, /* the factor L from which parent(i) is derived */ /* ---- output --- */ cholmod_sparse *Yset, /* pattern of Y=L\B, n-by-1 with Y->nzmax >= n */ /* --------------- */ cholmod_common *Common ) { size_t krow ; RETURN_IF_NULL (B, FALSE) ; krow = B->nrow ; return (CHOLMOD(row_lsubtree) (B, NULL, 0, krow, L, Yset, Common)) ; } /* ========================================================================== */ /* === cholmod_row_lsubtree ================================================= */ /* ========================================================================== */ /* Identical to cholmod_row_subtree, except that the elimination tree is * obtained from L itself, as the first off-diagonal entry in each column. * L must be simplicial, not supernodal. * * If krow = A->nrow, then A must be a single sparse column vector, (A->stype * must be zero), and the nonzero pattern of x=L\b is computed, where b=A(:,0) * is the single sparse right-hand-side. The inputs Fi and fnz are ignored. * See CHOLMOD(lsolve_pattern) above for a simpler interface for this case. */ int CHOLMOD(row_lsubtree) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to analyze */ Int *Fi, size_t fnz, /* nonzero pattern of kth row of A', not required * for the symmetric case. Need not be sorted. */ size_t krow, /* row k of L */ cholmod_factor *L, /* the factor L from which parent(i) is derived */ /* ---- output --- */ cholmod_sparse *R, /* pattern of L(k,:), n-by-1 with R->nzmax >= n */ /* --------------- */ cholmod_common *Common ) { Int *Rp, *Stack, *Flag, *Ap, *Ai, *Anz, *Lp, *Li, *Lnz ; Int p, pend, parent, t, stype, nrow, k, pf, packed, sorted, top, len, i, mark, ka ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (A, FALSE) ; RETURN_IF_NULL (R, FALSE) ; RETURN_IF_NULL (L, FALSE) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; RETURN_IF_XTYPE_INVALID (R, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; RETURN_IF_XTYPE_INVALID (L, CHOLMOD_REAL, CHOLMOD_ZOMPLEX, FALSE) ; nrow = A->nrow ; stype = A->stype ; if (stype < 0) { /* symmetric lower triangular form not supported */ ERROR (CHOLMOD_INVALID, "symmetric lower not supported") ; return (FALSE) ; } if (krow > nrow) { ERROR (CHOLMOD_INVALID, "lsubtree: krow invalid") ; return (FALSE) ; } else if (krow == nrow) { /* find pattern of x=L\b where b=A(:,0) */ k = nrow ; /* compute all of the result; don't stop in SUBTREE */ ka = 0 ; /* use column A(:,0) */ if (stype != 0 || A->ncol != 1) { /* A must be unsymmetric (it's a single sparse column vector) */ ERROR (CHOLMOD_INVALID, "lsubtree: A invalid") ; return (FALSE) ; } } else { /* find pattern of L(k,:) using A(:,k) and Fi if A unsymmetric */ k = krow ; /* which row of L to compute */ ka = k ; /* which column of A to use */ if (stype == 0) { RETURN_IF_NULL (Fi, FALSE) ; } } if (R->ncol != 1 || nrow != R->nrow || nrow > R->nzmax || ka >= A->ncol) { ERROR (CHOLMOD_INVALID, "lsubtree: R invalid") ; return (FALSE) ; } if (L->is_super) { ERROR (CHOLMOD_INVALID, "lsubtree: L invalid (cannot be supernodal)") ; return (FALSE) ; } Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ CHOLMOD(allocate_work) (nrow, 0, 0, Common) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; } ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ Ap = A->p ; Ai = A->i ; Anz = A->nz ; packed = A->packed ; sorted = A->sorted ; Stack = R->i ; Lp = L->p ; Li = L->i ; Lnz = L->nz ; /* ---------------------------------------------------------------------- */ /* get workspace */ /* ---------------------------------------------------------------------- */ Flag = Common->Flag ; /* size nrow, Flag [i] < mark must hold */ mark = CHOLMOD(clear_flag) (Common) ; /* ---------------------------------------------------------------------- */ /* compute the pattern of L(k,:) */ /* ---------------------------------------------------------------------- */ top = nrow ; /* Stack is empty */ if (k < nrow) { Flag [k] = mark ; /* do not include diagonal entry in Stack */ } #define SCATTER /* do not scatter numerical values */ #define PARENT(i) (Lnz [i] > 1) ? (Li [Lp [i] + 1]) : EMPTY if (krow == nrow || stype != 0) { /* scatter kth col of triu (A), get pattern L(k,:) */ p = Ap [ka] ; pend = (packed) ? (Ap [ka+1]) : (p + Anz [ka]) ; SUBTREE ; } else { /* scatter kth col of triu (beta*I+AA'), get pattern L(k,:) */ for (pf = 0 ; pf < (Int) fnz ; pf++) { /* get nonzero entry F (t,k) */ t = Fi [pf] ; p = Ap [t] ; pend = (packed) ? (Ap [t+1]) : (p + Anz [t]) ; SUBTREE ; } } #undef SCATTER #undef PARENT /* shift the stack upwards, to the first part of R */ len = nrow - top ; for (i = 0 ; i < len ; i++) { Stack [i] = Stack [top + i] ; } Rp = R->p ; Rp [0] = 0 ; Rp [1] = len ; R->sorted = FALSE ; CHOLMOD(clear_flag) (Common) ; ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; return (TRUE) ; } /* ========================================================================== */ /* === cholmod_rowfac ======================================================= */ /* ========================================================================== */ /* This is the incremental factorization for general purpose usage. */ int CHOLMOD(rowfac) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to factorize */ cholmod_sparse *F, /* used for A*A' case only. F=A' or A(:,f)' */ double beta [2], /* factorize beta*I+A or beta*I+AA' */ size_t kstart, /* first row to factorize */ size_t kend, /* last row to factorize is kend-1 */ /* ---- in/out --- */ cholmod_factor *L, /* --------------- */ cholmod_common *Common ) { return (CHOLMOD(rowfac_mask) (A, F, beta, kstart, kend, NULL, NULL, L, Common)) ; } /* ========================================================================== */ /* === cholmod_rowfac_mask ================================================== */ /* ========================================================================== */ /* This is meant for use in LPDASA only. */ int CHOLMOD(rowfac_mask) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to factorize */ cholmod_sparse *F, /* used for A*A' case only. F=A' or A(:,f)' */ double beta [2], /* factorize beta*I+A or beta*I+AA' */ size_t kstart, /* first row to factorize */ size_t kend, /* last row to factorize is kend-1 */ Int *mask, /* size A->nrow. if mask[i] >= 0 row i is set to zero */ Int *RLinkUp, /* size A->nrow. link list of rows to compute */ /* ---- in/out --- */ cholmod_factor *L, /* --------------- */ cholmod_common *Common ) { Int n ; size_t s ; int ok = TRUE ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (A, FALSE) ; RETURN_IF_NULL (L, FALSE) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_REAL, CHOLMOD_ZOMPLEX, FALSE) ; RETURN_IF_XTYPE_INVALID (L, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; if (L->xtype != CHOLMOD_PATTERN && A->xtype != L->xtype) { ERROR (CHOLMOD_INVALID, "xtype of A and L do not match") ; return (FALSE) ; } if (L->is_super) { ERROR (CHOLMOD_INVALID, "can only do simplicial factorization"); return (FALSE) ; } if (A->stype == 0) { RETURN_IF_NULL (F, FALSE) ; if (A->xtype != F->xtype) { ERROR (CHOLMOD_INVALID, "xtype of A and F do not match") ; return (FALSE) ; } } if (A->stype < 0) { /* symmetric lower triangular form not supported */ ERROR (CHOLMOD_INVALID, "symmetric lower not supported") ; return (FALSE) ; } if (kend > L->n) { ERROR (CHOLMOD_INVALID, "kend invalid") ; return (FALSE) ; } if (A->nrow != L->n) { ERROR (CHOLMOD_INVALID, "dimensions of A and L do not match") ; return (FALSE) ; } Common->status = CHOLMOD_OK ; Common->rowfacfl = 0 ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ /* Xwork is of size n for the real case, 2*n for complex/zomplex */ n = L->n ; /* s = ((A->xtype != CHOLMOD_REAL) ? 2:1)*n */ s = CHOLMOD(mult_size_t) (n, ((A->xtype != CHOLMOD_REAL) ? 2:1), &ok) ; if (!ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return (FALSE) ; } CHOLMOD(allocate_work) (n, n, s, Common) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; } ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, A->nrow, Common)) ; /* ---------------------------------------------------------------------- */ /* factorize the matrix, using template routine */ /* ---------------------------------------------------------------------- */ if (RLinkUp == NULL) { switch (A->xtype) { case CHOLMOD_REAL: ok = r_cholmod_rowfac (A, F, beta, kstart, kend, L, Common) ; break ; case CHOLMOD_COMPLEX: ok = c_cholmod_rowfac (A, F, beta, kstart, kend, L, Common) ; break ; case CHOLMOD_ZOMPLEX: ok = z_cholmod_rowfac (A, F, beta, kstart, kend, L, Common) ; break ; } } else { switch (A->xtype) { case CHOLMOD_REAL: ok = r_cholmod_rowfac_mask (A, F, beta, kstart, kend, mask, RLinkUp, L, Common) ; break ; case CHOLMOD_COMPLEX: ok = c_cholmod_rowfac_mask (A, F, beta, kstart, kend, mask, RLinkUp, L, Common) ; break ; case CHOLMOD_ZOMPLEX: ok = z_cholmod_rowfac_mask (A, F, beta, kstart, kend, mask, RLinkUp, L, Common) ; break ; } } return (ok) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Cholesky/t_cholmod_lsolve.c0000644000076500000240000006371213524616144027763 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Cholesky/t_cholmod_lsolve ============================================ */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Cholesky Module. Copyright (C) 2005-2013, Timothy A. Davis * The CHOLMOD/Cholesky Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Template routine to solve Lx=b with unit or non-unit diagonal, or * solve LDx=b. * * The numeric xtype of L and Y must match. Y contains b on input and x on * output, stored in row-form. Y is nrow-by-n, where nrow must equal 1 for the * complex or zomplex cases, and nrow <= 4 for the real case. * * This file is not compiled separately. It is included in t_cholmod_solve.c * instead. It contains no user-callable routines. * * workspace: none * * Supports real, complex, and zomplex factors. */ /* undefine all prior definitions */ #undef FORM_NAME #undef LSOLVE /* -------------------------------------------------------------------------- */ /* define the method */ /* -------------------------------------------------------------------------- */ #ifdef LL /* LL': solve Lx=b with non-unit diagonal */ #define FORM_NAME(prefix,rank) prefix ## ll_lsolve_ ## rank #elif defined (LD) /* LDL': solve LDx=b */ #define FORM_NAME(prefix,rank) prefix ## ldl_ldsolve_ ## rank #else /* LDL': solve Lx=b with unit diagonal */ #define FORM_NAME(prefix,rank) prefix ## ldl_lsolve_ ## rank #endif /* LSOLVE(k) defines the name of a routine for an n-by-k right-hand-side. */ #define LSOLVE(prefix,rank) FORM_NAME(prefix,rank) #ifdef REAL /* ========================================================================== */ /* === LSOLVE (1) =========================================================== */ /* ========================================================================== */ /* Solve Lx=b, where b has 1 column */ static void LSOLVE (PREFIX,1) ( cholmod_factor *L, double X [ ] /* n-by-1 in row form */ ) { double *Lx = L->x ; Int *Li = L->i ; Int *Lp = L->p ; Int *Lnz = L->nz ; Int j, n = L->n ; for (j = 0 ; j < n ; ) { /* get the start, end, and length of column j */ Int p = Lp [j] ; Int lnz = Lnz [j] ; Int pend = p + lnz ; /* find a chain of supernodes (up to j, j+1, and j+2) */ if (lnz < 4 || lnz != Lnz [j+1] + 1 || Li [p+1] != j+1) { /* -------------------------------------------------------------- */ /* solve with a single column of L */ /* -------------------------------------------------------------- */ double y = X [j] ; #ifdef LL y /= Lx [p] ; X [j] = y ; #elif defined (LD) X [j] = y / Lx [p] ; #endif for (p++ ; p < pend ; p++) { X [Li [p]] -= Lx [p] * y ; } j++ ; /* advance to next column of L */ } else if (lnz != Lnz [j+2] + 2 || Li [p+2] != j+2) { /* -------------------------------------------------------------- */ /* solve with a supernode of two columns of L */ /* -------------------------------------------------------------- */ double y [2] ; Int q = Lp [j+1] ; #ifdef LL y [0] = X [j] / Lx [p] ; y [1] = (X [j+1] - Lx [p+1] * y [0]) / Lx [q] ; X [j ] = y [0] ; X [j+1] = y [1] ; #elif defined (LD) y [0] = X [j] ; y [1] = X [j+1] - Lx [p+1] * y [0] ; X [j ] = y [0] / Lx [p] ; X [j+1] = y [1] / Lx [q] ; #else y [0] = X [j] ; y [1] = X [j+1] - Lx [p+1] * y [0] ; X [j+1] = y [1] ; #endif for (p += 2, q++ ; p < pend ; p++, q++) { X [Li [p]] -= Lx [p] * y [0] + Lx [q] * y [1] ; } j += 2 ; /* advance to next column of L */ } else { /* -------------------------------------------------------------- */ /* solve with a supernode of three columns of L */ /* -------------------------------------------------------------- */ double y [3] ; Int q = Lp [j+1] ; Int r = Lp [j+2] ; #ifdef LL y [0] = X [j] / Lx [p] ; y [1] = (X [j+1] - Lx [p+1] * y [0]) / Lx [q] ; y [2] = (X [j+2] - Lx [p+2] * y [0] - Lx [q+1] * y [1]) / Lx [r] ; X [j ] = y [0] ; X [j+1] = y [1] ; X [j+2] = y [2] ; #elif defined (LD) y [0] = X [j] ; y [1] = X [j+1] - Lx [p+1] * y [0] ; y [2] = X [j+2] - Lx [p+2] * y [0] - Lx [q+1] * y [1] ; X [j ] = y [0] / Lx [p] ; X [j+1] = y [1] / Lx [q] ; X [j+2] = y [2] / Lx [r] ; #else y [0] = X [j] ; y [1] = X [j+1] - Lx [p+1] * y [0] ; y [2] = X [j+2] - Lx [p+2] * y [0] - Lx [q+1] * y [1] ; X [j+1] = y [1] ; X [j+2] = y [2] ; #endif for (p += 3, q += 2, r++ ; p < pend ; p++, q++, r++) { X [Li [p]] -= Lx [p] * y [0] + Lx [q] * y [1] + Lx [r] * y [2] ; } j += 3 ; /* advance to next column of L */ } } } /* ========================================================================== */ /* === LSOLVE (2) =========================================================== */ /* ========================================================================== */ /* Solve Lx=b, where b has 2 columns */ static void LSOLVE (PREFIX,2) ( cholmod_factor *L, double X [ ][2] /* n-by-2 in row form */ ) { double *Lx = L->x ; Int *Li = L->i ; Int *Lp = L->p ; Int *Lnz = L->nz ; Int j, n = L->n ; for (j = 0 ; j < n ; ) { /* get the start, end, and length of column j */ Int p = Lp [j] ; Int lnz = Lnz [j] ; Int pend = p + lnz ; /* find a chain of supernodes (up to j, j+1, and j+2) */ if (lnz < 4 || lnz != Lnz [j+1] + 1 || Li [p+1] != j+1) { /* -------------------------------------------------------------- */ /* solve with a single column of L */ /* -------------------------------------------------------------- */ double y [2] ; y [0] = X [j][0] ; y [1] = X [j][1] ; #ifdef LL y [0] /= Lx [p] ; y [1] /= Lx [p] ; X [j][0] = y [0] ; X [j][1] = y [1] ; #elif defined (LD) X [j][0] = y [0] / Lx [p] ; X [j][1] = y [1] / Lx [p] ; #endif for (p++ ; p < pend ; p++) { Int i = Li [p] ; X [i][0] -= Lx [p] * y [0] ; X [i][1] -= Lx [p] * y [1] ; } j++ ; /* advance to next column of L */ } else if (lnz != Lnz [j+2] + 2 || Li [p+2] != j+2) { /* -------------------------------------------------------------- */ /* solve with a supernode of two columns of L */ /* -------------------------------------------------------------- */ double y [2][2] ; Int q = Lp [j+1] ; y [0][0] = X [j][0] ; y [0][1] = X [j][1] ; #ifdef LL y [0][0] /= Lx [p] ; y [0][1] /= Lx [p] ; y [1][0] = (X [j+1][0] - Lx [p+1] * y [0][0]) / Lx [q] ; y [1][1] = (X [j+1][1] - Lx [p+1] * y [0][1]) / Lx [q] ; X [j ][0] = y [0][0] ; X [j ][1] = y [0][1] ; X [j+1][0] = y [1][0] ; X [j+1][1] = y [1][1] ; #elif defined (LD) y [1][0] = X [j+1][0] - Lx [p+1] * y [0][0] ; y [1][1] = X [j+1][1] - Lx [p+1] * y [0][1] ; X [j ][0] = y [0][0] / Lx [p] ; X [j ][1] = y [0][1] / Lx [p] ; X [j+1][0] = y [1][0] / Lx [q] ; X [j+1][1] = y [1][1] / Lx [q] ; #else y [1][0] = X [j+1][0] - Lx [p+1] * y [0][0] ; y [1][1] = X [j+1][1] - Lx [p+1] * y [0][1] ; X [j+1][0] = y [1][0] ; X [j+1][1] = y [1][1] ; #endif for (p += 2, q++ ; p < pend ; p++, q++) { Int i = Li [p] ; X [i][0] -= Lx [p] * y [0][0] + Lx [q] * y [1][0] ; X [i][1] -= Lx [p] * y [0][1] + Lx [q] * y [1][1] ; } j += 2 ; /* advance to next column of L */ } else { /* -------------------------------------------------------------- */ /* solve with a supernode of three columns of L */ /* -------------------------------------------------------------- */ double y [3][2] ; Int q = Lp [j+1] ; Int r = Lp [j+2] ; y [0][0] = X [j][0] ; y [0][1] = X [j][1] ; #ifdef LL y [0][0] /= Lx [p] ; y [0][1] /= Lx [p] ; y [1][0] = (X [j+1][0] - Lx[p+1] * y[0][0]) / Lx [q] ; y [1][1] = (X [j+1][1] - Lx[p+1] * y[0][1]) / Lx [q] ; y [2][0] = (X [j+2][0] - Lx[p+2] * y[0][0] - Lx[q+1]*y[1][0])/Lx[r]; y [2][1] = (X [j+2][1] - Lx[p+2] * y[0][1] - Lx[q+1]*y[1][1])/Lx[r]; X [j ][0] = y [0][0] ; X [j ][1] = y [0][1] ; X [j+1][0] = y [1][0] ; X [j+1][1] = y [1][1] ; X [j+2][0] = y [2][0] ; X [j+2][1] = y [2][1] ; #elif defined (LD) y [1][0] = X [j+1][0] - Lx [p+1] * y [0][0] ; y [1][1] = X [j+1][1] - Lx [p+1] * y [0][1] ; y [2][0] = X [j+2][0] - Lx [p+2] * y [0][0] - Lx [q+1] * y [1][0] ; y [2][1] = X [j+2][1] - Lx [p+2] * y [0][1] - Lx [q+1] * y [1][1] ; X [j ][0] = y [0][0] / Lx [p] ; X [j ][1] = y [0][1] / Lx [p] ; X [j+1][0] = y [1][0] / Lx [q] ; X [j+1][1] = y [1][1] / Lx [q] ; X [j+2][0] = y [2][0] / Lx [r] ; X [j+2][1] = y [2][1] / Lx [r] ; #else y [1][0] = X [j+1][0] - Lx [p+1] * y [0][0] ; y [1][1] = X [j+1][1] - Lx [p+1] * y [0][1] ; y [2][0] = X [j+2][0] - Lx [p+2] * y [0][0] - Lx [q+1] * y [1][0] ; y [2][1] = X [j+2][1] - Lx [p+2] * y [0][1] - Lx [q+1] * y [1][1] ; X [j+1][0] = y [1][0] ; X [j+1][1] = y [1][1] ; X [j+2][0] = y [2][0] ; X [j+2][1] = y [2][1] ; #endif for (p += 3, q += 2, r++ ; p < pend ; p++, q++, r++) { Int i = Li [p] ; X[i][0] -= Lx[p] * y[0][0] + Lx[q] * y[1][0] + Lx[r] * y[2][0] ; X[i][1] -= Lx[p] * y[0][1] + Lx[q] * y[1][1] + Lx[r] * y[2][1] ; } j += 3 ; /* advance to next column of L */ } } } /* ========================================================================== */ /* === LSOLVE (3) =========================================================== */ /* ========================================================================== */ /* Solve Lx=b, where b has 3 columns */ static void LSOLVE (PREFIX,3) ( cholmod_factor *L, double X [ ][3] /* n-by-3 in row form */ ) { double *Lx = L->x ; Int *Li = L->i ; Int *Lp = L->p ; Int *Lnz = L->nz ; Int j, n = L->n ; for (j = 0 ; j < n ; ) { /* get the start, end, and length of column j */ Int p = Lp [j] ; Int lnz = Lnz [j] ; Int pend = p + lnz ; /* find a chain of supernodes (up to j, j+1, and j+2) */ if (lnz < 4 || lnz != Lnz [j+1] + 1 || Li [p+1] != j+1) { /* -------------------------------------------------------------- */ /* solve with a single column of L */ /* -------------------------------------------------------------- */ double y [3] ; y [0] = X [j][0] ; y [1] = X [j][1] ; y [2] = X [j][2] ; #ifdef LL y [0] /= Lx [p] ; y [1] /= Lx [p] ; y [2] /= Lx [p] ; X [j][0] = y [0] ; X [j][1] = y [1] ; X [j][2] = y [2] ; #elif defined (LD) X [j][0] = y [0] / Lx [p] ; X [j][1] = y [1] / Lx [p] ; X [j][2] = y [2] / Lx [p] ; #endif for (p++ ; p < pend ; p++) { Int i = Li [p] ; double lx = Lx [p] ; X [i][0] -= lx * y [0] ; X [i][1] -= lx * y [1] ; X [i][2] -= lx * y [2] ; } j++ ; /* advance to next column of L */ } else if (lnz != Lnz [j+2] + 2 || Li [p+2] != j+2) { /* -------------------------------------------------------------- */ /* solve with a supernode of two columns of L */ /* -------------------------------------------------------------- */ double y [2][3] ; Int q = Lp [j+1] ; y [0][0] = X [j][0] ; y [0][1] = X [j][1] ; y [0][2] = X [j][2] ; #ifdef LL y [0][0] /= Lx [p] ; y [0][1] /= Lx [p] ; y [0][2] /= Lx [p] ; y [1][0] = (X [j+1][0] - Lx [p+1] * y [0][0]) / Lx [q] ; y [1][1] = (X [j+1][1] - Lx [p+1] * y [0][1]) / Lx [q] ; y [1][2] = (X [j+1][2] - Lx [p+1] * y [0][2]) / Lx [q] ; X [j ][0] = y [0][0] ; X [j ][1] = y [0][1] ; X [j ][2] = y [0][2] ; X [j+1][0] = y [1][0] ; X [j+1][1] = y [1][1] ; X [j+1][2] = y [1][2] ; #elif defined (LD) y [1][0] = X [j+1][0] - Lx [p+1] * y [0][0] ; y [1][1] = X [j+1][1] - Lx [p+1] * y [0][1] ; y [1][2] = X [j+1][2] - Lx [p+1] * y [0][2] ; X [j ][0] = y [0][0] / Lx [p] ; X [j ][1] = y [0][1] / Lx [p] ; X [j ][2] = y [0][2] / Lx [p] ; X [j+1][0] = y [1][0] / Lx [q] ; X [j+1][1] = y [1][1] / Lx [q] ; X [j+1][2] = y [1][2] / Lx [q] ; #else y [1][0] = X [j+1][0] - Lx [p+1] * y [0][0] ; y [1][1] = X [j+1][1] - Lx [p+1] * y [0][1] ; y [1][2] = X [j+1][2] - Lx [p+1] * y [0][2] ; X [j+1][0] = y [1][0] ; X [j+1][1] = y [1][1] ; X [j+1][2] = y [1][2] ; #endif for (p += 2, q++ ; p < pend ; p++, q++) { Int i = Li [p] ; double lx [2] ; lx [0] = Lx [p] ; lx [1] = Lx [q] ; X [i][0] -= lx [0] * y [0][0] + lx [1] * y [1][0] ; X [i][1] -= lx [0] * y [0][1] + lx [1] * y [1][1] ; X [i][2] -= lx [0] * y [0][2] + lx [1] * y [1][2] ; } j += 2 ; /* advance to next column of L */ } else { /* -------------------------------------------------------------- */ /* solve with a supernode of three columns of L */ /* -------------------------------------------------------------- */ double y [3][3] ; Int q = Lp [j+1] ; Int r = Lp [j+2] ; y [0][0] = X [j][0] ; y [0][1] = X [j][1] ; y [0][2] = X [j][2] ; #ifdef LL y [0][0] /= Lx [p] ; y [0][1] /= Lx [p] ; y [0][2] /= Lx [p] ; y [1][0] = (X [j+1][0] - Lx[p+1] * y[0][0]) / Lx [q] ; y [1][1] = (X [j+1][1] - Lx[p+1] * y[0][1]) / Lx [q] ; y [1][2] = (X [j+1][2] - Lx[p+1] * y[0][2]) / Lx [q] ; y [2][0] = (X [j+2][0] - Lx[p+2] * y[0][0] - Lx[q+1]*y[1][0])/Lx[r]; y [2][1] = (X [j+2][1] - Lx[p+2] * y[0][1] - Lx[q+1]*y[1][1])/Lx[r]; y [2][2] = (X [j+2][2] - Lx[p+2] * y[0][2] - Lx[q+1]*y[1][2])/Lx[r]; X [j ][0] = y [0][0] ; X [j ][1] = y [0][1] ; X [j ][2] = y [0][2] ; X [j+1][0] = y [1][0] ; X [j+1][1] = y [1][1] ; X [j+1][2] = y [1][2] ; X [j+2][0] = y [2][0] ; X [j+2][1] = y [2][1] ; X [j+2][2] = y [2][2] ; #elif defined (LD) y [1][0] = X [j+1][0] - Lx [p+1] * y [0][0] ; y [1][1] = X [j+1][1] - Lx [p+1] * y [0][1] ; y [1][2] = X [j+1][2] - Lx [p+1] * y [0][2] ; y [2][0] = X [j+2][0] - Lx [p+2] * y [0][0] - Lx [q+1] * y [1][0] ; y [2][1] = X [j+2][1] - Lx [p+2] * y [0][1] - Lx [q+1] * y [1][1] ; y [2][2] = X [j+2][2] - Lx [p+2] * y [0][2] - Lx [q+1] * y [1][2] ; X [j ][0] = y [0][0] / Lx [p] ; X [j ][1] = y [0][1] / Lx [p] ; X [j ][2] = y [0][2] / Lx [p] ; X [j+1][0] = y [1][0] / Lx [q] ; X [j+1][1] = y [1][1] / Lx [q] ; X [j+1][2] = y [1][2] / Lx [q] ; X [j+2][0] = y [2][0] / Lx [r] ; X [j+2][1] = y [2][1] / Lx [r] ; X [j+2][2] = y [2][2] / Lx [r] ; #else y [1][0] = X [j+1][0] - Lx [p+1] * y [0][0] ; y [1][1] = X [j+1][1] - Lx [p+1] * y [0][1] ; y [1][2] = X [j+1][2] - Lx [p+1] * y [0][2] ; y [2][0] = X [j+2][0] - Lx [p+2] * y [0][0] - Lx [q+1] * y [1][0] ; y [2][1] = X [j+2][1] - Lx [p+2] * y [0][1] - Lx [q+1] * y [1][1] ; y [2][2] = X [j+2][2] - Lx [p+2] * y [0][2] - Lx [q+1] * y [1][2] ; X [j+1][0] = y [1][0] ; X [j+1][1] = y [1][1] ; X [j+1][2] = y [1][2] ; X [j+2][0] = y [2][0] ; X [j+2][1] = y [2][1] ; X [j+2][2] = y [2][2] ; #endif for (p += 3, q += 2, r++ ; p < pend ; p++, q++, r++) { Int i = Li [p] ; double lx [3] ; lx [0] = Lx [p] ; lx [1] = Lx [q] ; lx [2] = Lx [r] ; X [i][0] -= lx[0] * y[0][0] + lx[1] * y[1][0] + lx[2] * y[2][0]; X [i][1] -= lx[0] * y[0][1] + lx[1] * y[1][1] + lx[2] * y[2][1]; X [i][2] -= lx[0] * y[0][2] + lx[1] * y[1][2] + lx[2] * y[2][2]; } j += 3 ; /* advance to next column of L */ } } } /* ========================================================================== */ /* === LSOLVE (4) =========================================================== */ /* ========================================================================== */ /* Solve Lx=b, where b has 4 columns */ static void LSOLVE (PREFIX,4) ( cholmod_factor *L, double X [ ][4] /* n-by-4 in row form */ ) { double *Lx = L->x ; Int *Li = L->i ; Int *Lp = L->p ; Int *Lnz = L->nz ; Int j, n = L->n ; for (j = 0 ; j < n ; ) { /* get the start, end, and length of column j */ Int p = Lp [j] ; Int lnz = Lnz [j] ; Int pend = p + lnz ; /* find a chain of supernodes (up to j, j+1, and j+2) */ if (lnz < 4 || lnz != Lnz [j+1] + 1 || Li [p+1] != j+1) { /* -------------------------------------------------------------- */ /* solve with a single column of L */ /* -------------------------------------------------------------- */ double y [4] ; y [0] = X [j][0] ; y [1] = X [j][1] ; y [2] = X [j][2] ; y [3] = X [j][3] ; #ifdef LL y [0] /= Lx [p] ; y [1] /= Lx [p] ; y [2] /= Lx [p] ; y [3] /= Lx [p] ; X [j][0] = y [0] ; X [j][1] = y [1] ; X [j][2] = y [2] ; X [j][3] = y [3] ; #elif defined (LD) X [j][0] = y [0] / Lx [p] ; X [j][1] = y [1] / Lx [p] ; X [j][2] = y [2] / Lx [p] ; X [j][3] = y [3] / Lx [p] ; #endif for (p++ ; p < pend ; p++) { Int i = Li [p] ; double lx = Lx [p] ; X [i][0] -= lx * y [0] ; X [i][1] -= lx * y [1] ; X [i][2] -= lx * y [2] ; X [i][3] -= lx * y [3] ; } j++ ; /* advance to next column of L */ } else if (lnz != Lnz [j+2] + 2 || Li [p+2] != j+2) { /* -------------------------------------------------------------- */ /* solve with a supernode of two columns of L */ /* -------------------------------------------------------------- */ double y [2][4] ; Int q = Lp [j+1] ; y [0][0] = X [j][0] ; y [0][1] = X [j][1] ; y [0][2] = X [j][2] ; y [0][3] = X [j][3] ; #ifdef LL y [0][0] /= Lx [p] ; y [0][1] /= Lx [p] ; y [0][2] /= Lx [p] ; y [0][3] /= Lx [p] ; y [1][0] = (X [j+1][0] - Lx [p+1] * y [0][0]) / Lx [q] ; y [1][1] = (X [j+1][1] - Lx [p+1] * y [0][1]) / Lx [q] ; y [1][2] = (X [j+1][2] - Lx [p+1] * y [0][2]) / Lx [q] ; y [1][3] = (X [j+1][3] - Lx [p+1] * y [0][3]) / Lx [q] ; X [j ][0] = y [0][0] ; X [j ][1] = y [0][1] ; X [j ][2] = y [0][2] ; X [j ][3] = y [0][3] ; X [j+1][0] = y [1][0] ; X [j+1][1] = y [1][1] ; X [j+1][2] = y [1][2] ; X [j+1][3] = y [1][3] ; #elif defined (LD) y [1][0] = X [j+1][0] - Lx [p+1] * y [0][0] ; y [1][1] = X [j+1][1] - Lx [p+1] * y [0][1] ; y [1][2] = X [j+1][2] - Lx [p+1] * y [0][2] ; y [1][3] = X [j+1][3] - Lx [p+1] * y [0][3] ; X [j ][0] = y [0][0] / Lx [p] ; X [j ][1] = y [0][1] / Lx [p] ; X [j ][2] = y [0][2] / Lx [p] ; X [j ][3] = y [0][3] / Lx [p] ; X [j+1][0] = y [1][0] / Lx [q] ; X [j+1][1] = y [1][1] / Lx [q] ; X [j+1][2] = y [1][2] / Lx [q] ; X [j+1][3] = y [1][3] / Lx [q] ; #else y [1][0] = X [j+1][0] - Lx [p+1] * y [0][0] ; y [1][1] = X [j+1][1] - Lx [p+1] * y [0][1] ; y [1][2] = X [j+1][2] - Lx [p+1] * y [0][2] ; y [1][3] = X [j+1][3] - Lx [p+1] * y [0][3] ; X [j+1][0] = y [1][0] ; X [j+1][1] = y [1][1] ; X [j+1][2] = y [1][2] ; X [j+1][3] = y [1][3] ; #endif for (p += 2, q++ ; p < pend ; p++, q++) { Int i = Li [p] ; double lx [2] ; lx [0] = Lx [p] ; lx [1] = Lx [q] ; X [i][0] -= lx [0] * y [0][0] + lx [1] * y [1][0] ; X [i][1] -= lx [0] * y [0][1] + lx [1] * y [1][1] ; X [i][2] -= lx [0] * y [0][2] + lx [1] * y [1][2] ; X [i][3] -= lx [0] * y [0][3] + lx [1] * y [1][3] ; } j += 2 ; /* advance to next column of L */ } else { /* -------------------------------------------------------------- */ /* solve with a supernode of three columns of L */ /* -------------------------------------------------------------- */ double y [3][4] ; Int q = Lp [j+1] ; Int r = Lp [j+2] ; y [0][0] = X [j][0] ; y [0][1] = X [j][1] ; y [0][2] = X [j][2] ; y [0][3] = X [j][3] ; #ifdef LL y [0][0] /= Lx [p] ; y [0][1] /= Lx [p] ; y [0][2] /= Lx [p] ; y [0][3] /= Lx [p] ; y [1][0] = (X [j+1][0] - Lx[p+1] * y[0][0]) / Lx [q] ; y [1][1] = (X [j+1][1] - Lx[p+1] * y[0][1]) / Lx [q] ; y [1][2] = (X [j+1][2] - Lx[p+1] * y[0][2]) / Lx [q] ; y [1][3] = (X [j+1][3] - Lx[p+1] * y[0][3]) / Lx [q] ; y [2][0] = (X [j+2][0] - Lx[p+2] * y[0][0] - Lx[q+1]*y[1][0])/Lx[r]; y [2][1] = (X [j+2][1] - Lx[p+2] * y[0][1] - Lx[q+1]*y[1][1])/Lx[r]; y [2][2] = (X [j+2][2] - Lx[p+2] * y[0][2] - Lx[q+1]*y[1][2])/Lx[r]; y [2][3] = (X [j+2][3] - Lx[p+2] * y[0][3] - Lx[q+1]*y[1][3])/Lx[r]; X [j ][0] = y [0][0] ; X [j ][1] = y [0][1] ; X [j ][2] = y [0][2] ; X [j ][3] = y [0][3] ; X [j+1][0] = y [1][0] ; X [j+1][1] = y [1][1] ; X [j+1][2] = y [1][2] ; X [j+1][3] = y [1][3] ; X [j+2][0] = y [2][0] ; X [j+2][1] = y [2][1] ; X [j+2][2] = y [2][2] ; X [j+2][3] = y [2][3] ; #elif defined (LD) y [1][0] = X [j+1][0] - Lx [p+1] * y [0][0] ; y [1][1] = X [j+1][1] - Lx [p+1] * y [0][1] ; y [1][2] = X [j+1][2] - Lx [p+1] * y [0][2] ; y [1][3] = X [j+1][3] - Lx [p+1] * y [0][3] ; y [2][0] = X [j+2][0] - Lx [p+2] * y [0][0] - Lx [q+1] * y [1][0] ; y [2][1] = X [j+2][1] - Lx [p+2] * y [0][1] - Lx [q+1] * y [1][1] ; y [2][2] = X [j+2][2] - Lx [p+2] * y [0][2] - Lx [q+1] * y [1][2] ; y [2][3] = X [j+2][3] - Lx [p+2] * y [0][3] - Lx [q+1] * y [1][3] ; X [j ][0] = y [0][0] / Lx [p] ; X [j ][1] = y [0][1] / Lx [p] ; X [j ][2] = y [0][2] / Lx [p] ; X [j ][3] = y [0][3] / Lx [p] ; X [j+1][0] = y [1][0] / Lx [q] ; X [j+1][1] = y [1][1] / Lx [q] ; X [j+1][2] = y [1][2] / Lx [q] ; X [j+1][3] = y [1][3] / Lx [q] ; X [j+2][0] = y [2][0] / Lx [r] ; X [j+2][1] = y [2][1] / Lx [r] ; X [j+2][2] = y [2][2] / Lx [r] ; X [j+2][3] = y [2][3] / Lx [r] ; #else y [1][0] = X [j+1][0] - Lx [p+1] * y [0][0] ; y [1][1] = X [j+1][1] - Lx [p+1] * y [0][1] ; y [1][2] = X [j+1][2] - Lx [p+1] * y [0][2] ; y [1][3] = X [j+1][3] - Lx [p+1] * y [0][3] ; y [2][0] = X [j+2][0] - Lx [p+2] * y [0][0] - Lx [q+1] * y [1][0] ; y [2][1] = X [j+2][1] - Lx [p+2] * y [0][1] - Lx [q+1] * y [1][1] ; y [2][2] = X [j+2][2] - Lx [p+2] * y [0][2] - Lx [q+1] * y [1][2] ; y [2][3] = X [j+2][3] - Lx [p+2] * y [0][3] - Lx [q+1] * y [1][3] ; X [j+1][0] = y [1][0] ; X [j+1][1] = y [1][1] ; X [j+1][2] = y [1][2] ; X [j+1][3] = y [1][3] ; X [j+2][0] = y [2][0] ; X [j+2][1] = y [2][1] ; X [j+2][2] = y [2][2] ; X [j+2][3] = y [2][3] ; #endif for (p += 3, q += 2, r++ ; p < pend ; p++, q++, r++) { Int i = Li [p] ; double lx [3] ; lx [0] = Lx [p] ; lx [1] = Lx [q] ; lx [2] = Lx [r] ; X [i][0] -= lx[0] * y[0][0] + lx[1] * y[1][0] + lx[2] * y[2][0]; X [i][1] -= lx[0] * y[0][1] + lx[1] * y[1][1] + lx[2] * y[2][1]; X [i][2] -= lx[0] * y[0][2] + lx[1] * y[1][2] + lx[2] * y[2][2]; X [i][3] -= lx[0] * y[0][3] + lx[1] * y[1][3] + lx[2] * y[2][3]; } j += 3 ; /* advance to next column of L */ } } } #endif /* ========================================================================== */ /* === LSOLVE (k) =========================================================== */ /* ========================================================================== */ static void LSOLVE (PREFIX,k) ( cholmod_factor *L, cholmod_dense *Y, /* nr-by-n where nr is 1 to 4 */ Int *Yseti, Int ysetlen ) { double yx [2] ; #ifdef ZOMPLEX double yz [1] ; double *Lz = L->z ; double *Xz = Y->z ; #endif double *Lx = L->x ; double *Xx = Y->x ; Int *Li = L->i ; Int *Lp = L->p ; Int *Lnz = L->nz ; Int n = L->n, jj, jjiters ; ASSERT (L->xtype == Y->xtype) ; /* L and Y must have the same xtype */ ASSERT (L->n == Y->ncol) ; /* dimensions must match */ ASSERT (Y->nrow == Y->d) ; /* leading dimension of Y = # rows of Y */ ASSERT (L->xtype != CHOLMOD_PATTERN) ; /* L is not symbolic */ ASSERT (!(L->is_super)) ; /* L is simplicial LL' or LDL' */ #ifdef REAL if (Yseti == NULL) { /* ------------------------------------------------------------------ */ /* real case, no Yseti, with 1 to 4 RHS's and dynamic supernodes */ /* ------------------------------------------------------------------ */ ASSERT (Y->nrow <= 4) ; switch (Y->nrow) { case 1: LSOLVE (PREFIX,1) (L, Y->x) ; break ; case 2: LSOLVE (PREFIX,2) (L, Y->x) ; break ; case 3: LSOLVE (PREFIX,3) (L, Y->x) ; break ; case 4: LSOLVE (PREFIX,4) (L, Y->x) ; break ; } } else #endif { /* ------------------------------------------------------------------ */ /* solve a complex linear system or solve with Yseti */ /* ------------------------------------------------------------------ */ ASSERT (Y->nrow == 1) ; jjiters = Yseti ? ysetlen : n ; for (jj = 0 ; jj < jjiters ; jj++) { Int j = Yseti ? Yseti [jj] : jj ; /* get the start, end, and length of column j */ Int p = Lp [j] ; Int lnz = Lnz [j] ; Int pend = p + lnz ; /* y = X [j] ; */ ASSIGN (yx,yz,0, Xx,Xz,j) ; #ifdef LL /* y /= Lx [p] ; */ /* X [j] = y ; */ DIV_REAL (yx,yz,0, yx,yz,0, Lx,p) ; ASSIGN (Xx,Xz,j, yx,yz,0) ; #elif defined (LD) /* X [j] = y / Lx [p] ; */ DIV_REAL (Xx,Xz,j, yx,yz,0, Lx,p) ; #endif for (p++ ; p < pend ; p++) { /* X [Li [p]] -= Lx [p] * y ; */ Int i = Li [p] ; MULTSUB (Xx,Xz,i, Lx,Lz,p, yx,yz,0) ; } } } } /* prepare for the next inclusion of this file in cholmod_solve.c */ #undef LL #undef LD python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Cholesky/lesser.txt0000644000076500000240000006350013524616144026314 0ustar tamasstaff00000000000000 GNU LESSER GENERAL PUBLIC LICENSE Version 2.1, February 1999 Copyright (C) 1991, 1999 Free Software Foundation, Inc. 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed. 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To apply these terms, attach the following notices to the library. It is safest to attach them to the start of each source file to most effectively convey the exclusion of warranty; and each file should have at least the "copyright" line and a pointer to where the full notice is found. Copyright (C) This library is free software; you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation; either version 2.1 of the License, or (at your option) any later version. This library is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with this library; if not, write to the Free Software Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA Also add information on how to contact you by electronic and paper mail. You should also get your employer (if you work as a programmer) or your school, if any, to sign a "copyright disclaimer" for the library, if necessary. Here is a sample; alter the names: Yoyodyne, Inc., hereby disclaims all copyright interest in the library `Frob' (a library for tweaking knobs) written by James Random Hacker. , 1 April 1990 Ty Coon, President of Vice That's all there is to it! python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Cholesky/License.txt0000644000076500000240000000204713524616144026400 0ustar tamasstaff00000000000000CHOLMOD/Cholesky module, Copyright (C) 2005-2006, Timothy A. Davis CHOLMOD is also available under other licenses; contact authors for details. http://www.suitesparse.com Note that this license is for the CHOLMOD/Cholesky module only. All CHOLMOD modules are licensed separately. -------------------------------------------------------------------------------- This Module is free software; you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation; either version 2.1 of the License, or (at your option) any later version. This Module is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with this Module; if not, write to the Free Software Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Cholesky/cholmod_analyze.c0000644000076500000240000010023013524616144027562 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Cholesky/cholmod_analyze ============================================= */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Cholesky Module. Copyright (C) 2005-2013, Timothy A. Davis * The CHOLMOD/Cholesky Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Order and analyze a matrix (either simplicial or supernodal), in prepartion * for numerical factorization via cholmod_factorize or via the "expert" * routines cholmod_rowfac and cholmod_super_numeric. * * symmetric case: A or A(p,p) * unsymmetric case: AA', A(p,:)*A(p,:)', A(:,f)*A(:,f)', or A(p,f)*A(p,f)' * * For the symmetric case, only the upper or lower triangular part of A is * accessed (depending on the type of A). LL'=A (or permuted A) is analzed. * For the unsymmetric case (LL'=AA' or permuted A). * * There can be no duplicate entries in p or f. p is of length m if A is * m-by-n. f can be length 0 to n. * * In both cases, the columns of A need not be sorted. A can be in packed * or unpacked form. * * Ordering options include: * * natural: A is not permuted to reduce fill-in * given: a permutation can be provided to this routine (UserPerm) * AMD: approximate minumum degree (AMD for the symmetric case, * COLAMD for the AA' case). * METIS: nested dissection with METIS_NodeND * NESDIS: nested dissection using METIS_NodeComputeSeparator, * typically followed by a constrained minimum degree * (CAMD for the symmetric case, CCOLAMD for the AA' case). * * Multiple ordering options can be tried (up to 9 of them), and the best one * is selected (the one that gives the smallest number of nonzeros in the * simplicial factor L). If one method fails, cholmod_analyze keeps going, and * picks the best among the methods that succeeded. This routine fails (and * returns NULL) if either initial memory allocation fails, all ordering methods * fail, or the supernodal analysis (if requested) fails. By default, the 9 * methods available are: * * 1) given permutation (skipped if UserPerm is NULL) * 2) AMD (symmetric case) or COLAMD (unsymmetric case) * 3) METIS with default parameters * 4) NESDIS with default parameters (stopping the partitioning when * the graph is of size nd_small = 200 or less, remove nodes with * more than max (16, prune_dense * sqrt (n)) nodes where * prune_dense = 10, and follow partitioning with CCOLAMD, a * constrained minimum degree ordering). * 5) natural * 6) NESDIS, nd_small = 20000, prune_dense = 10 * 7) NESDIS, nd_small = 4, prune_dense = 10, no min degree * 8) NESDIS, nd_small = 200, prune_dense = 0 * 9) COLAMD for A*A' or AMD for A * * By default, the first two are tried, and METIS is tried if AMD reports a high * flop count and fill-in. Let fl denote the flop count for the AMD, ordering, * nnz(L) the # of nonzeros in L, and nnz(tril(A)) (or A*A'). If * fl/nnz(L) >= 500 and nnz(L)/nnz(tril(A)) >= 5, then METIS is attempted. The * best ordering is used (UserPerm if given, AMD, and METIS if attempted). If * you do not have METIS, only the first two will be tried (user permutation, * if provided, and AMD/COLAMD). This default behavior is obtained when * Common->nmethods is zero. In this case, methods 0, 1, and 2 in * Common->method [..] are reset to User-provided, AMD, and METIS (or NESDIS * if Common->default_nesdis is set to the non-default value of TRUE), * respectively. * * You can modify these 9 methods and the number of methods tried by changing * parameters in the Common argument. If you know the best ordering for your * matrix, set Common->nmethods to 1 and set Common->method[0].ordering to the * requested ordering method. Parameters for each method can also be modified * (refer to cholmod.h for details). * * Note that it is possible for METIS to terminate your program if it runs out * of memory. This is not the case for any CHOLMOD or minimum degree ordering * routine (AMD, COLAMD, CAMD, CCOLAMD, or CSYMAMD). Since NESDIS relies on * METIS, it too can terminate your program. * * The factor L is returned as simplicial symbolic (L->is_super FALSE) if * Common->supernodal <= CHOLMOD_SIMPLICIAL (0) or as supernodal symbolic if * Common->supernodal >= CHOLMOD_SUPERNODAL (2). If Common->supernodal is * equal to CHOLMOD_AUTO (1), then L is simplicial if the flop count per * nonzero in L is less than Common->supernodal_switch (default: 40), and * is returned as a supernodal factor otherwise. * * In both cases, L->xtype is CHOLMOD_PATTERN. * A subsequent call to cholmod_factorize will perform a * simplicial or supernodal factorization, depending on the type of L. * * For the simplicial case, L contains the fill-reducing permutation (L->Perm) * and the counts of nonzeros in each column of L (L->ColCount). For the * supernodal case, L also contains the nonzero pattern of each supernode. * * workspace: Flag (nrow), Head (nrow+1) * if symmetric: Iwork (6*nrow) * if unsymmetric: Iwork (6*nrow+ncol). * calls various ordering routines, which typically allocate O(nnz(A)) * temporary workspace ((2 to 3)*nnz(A) * sizeof (Int) is typical, but it * can be much higher if A*A' must be explicitly formed for METIS). Also * allocates up to 2 temporary (permuted/transpose) copies of the nonzero * pattern of A, and up to 3*n*sizeof(Int) additional workspace. * * Supports any xtype (pattern, real, complex, or zomplex) */ #ifndef NCHOLESKY #include "cholmod_internal.h" #include "cholmod_cholesky.h" #ifndef NSUPERNODAL #include "cholmod_supernodal.h" #endif #ifndef NPARTITION #include "cholmod_partition.h" #endif /* ========================================================================== */ /* === cholmod_analyze ====================================================== */ /* ========================================================================== */ /* Orders and analyzes A, AA', PAP', or PAA'P' and returns a symbolic factor * that can later be passed to cholmod_factorize. */ cholmod_factor *CHOLMOD(analyze) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to order and analyze */ /* --------------- */ cholmod_common *Common ) { return (CHOLMOD(analyze_p2) (TRUE, A, NULL, NULL, 0, Common)) ; } /* ========================================================================== */ /* === cholmod_analyze_p ==================================================== */ /* ========================================================================== */ /* Orders and analyzes A, AA', PAP', PAA'P', FF', or PFF'P and returns a * symbolic factor that can later be passed to cholmod_factorize, where * F = A(:,fset) if fset is not NULL and A->stype is zero. * UserPerm is tried if non-NULL. */ cholmod_factor *CHOLMOD(analyze_p) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to order and analyze */ Int *UserPerm, /* user-provided permutation, size A->nrow */ Int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ /* --------------- */ cholmod_common *Common ) { return (CHOLMOD(analyze_p2) (TRUE, A, UserPerm, fset, fsize, Common)) ; } /* ========================================================================== */ /* === permute_matrices ===================================================== */ /* ========================================================================== */ /* Permute and transpose a matrix. Allocates the A1 and A2 matrices, if needed, * or returns them as NULL if not needed. */ static int permute_matrices ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to permute */ Int ordering, /* ordering method used */ Int *Perm, /* fill-reducing permutation */ Int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ Int do_rowcolcounts,/* if TRUE, compute both S and F. If FALSE, only * S is needed for the symmetric case, and only F for * the unsymmetric case */ /* ---- output --- */ cholmod_sparse **A1_handle, /* see comments below for A1, A2, S, F */ cholmod_sparse **A2_handle, cholmod_sparse **S_handle, cholmod_sparse **F_handle, /* --------------- */ cholmod_common *Common ) { cholmod_sparse *A1, *A2, *S, *F ; *A1_handle = NULL ; *A2_handle = NULL ; *S_handle = NULL ; *F_handle = NULL ; A1 = NULL ; A2 = NULL ; if (ordering == CHOLMOD_NATURAL) { /* ------------------------------------------------------------------ */ /* natural ordering of A */ /* ------------------------------------------------------------------ */ if (A->stype < 0) { /* symmetric lower case: A already in lower form, so S=A' */ /* workspace: Iwork (nrow) */ A2 = CHOLMOD(ptranspose) (A, 0, NULL, NULL, 0, Common) ; F = A ; S = A2 ; } else if (A->stype > 0) { /* symmetric upper case: F = pattern of triu (A)', S = A */ /* workspace: Iwork (nrow) */ if (do_rowcolcounts) { /* F not needed for symmetric case if do_rowcolcounts FALSE */ A1 = CHOLMOD(ptranspose) (A, 0, NULL, fset, fsize, Common) ; } F = A1 ; S = A ; } else { /* unsymmetric case: F = pattern of A (:,f)', S = A */ /* workspace: Iwork (nrow if no fset, MAX(nrow,ncol) if fset) */ A1 = CHOLMOD(ptranspose) (A, 0, NULL, fset, fsize, Common) ; F = A1 ; S = A ; } } else { /* ------------------------------------------------------------------ */ /* A is permuted */ /* ------------------------------------------------------------------ */ if (A->stype < 0) { /* symmetric lower case: S = tril (A (p,p))' and F = S' */ /* workspace: Iwork (2*nrow) */ A2 = CHOLMOD(ptranspose) (A, 0, Perm, NULL, 0, Common) ; S = A2 ; /* workspace: Iwork (nrow) */ if (do_rowcolcounts) { /* F not needed for symmetric case if do_rowcolcounts FALSE */ A1 = CHOLMOD(ptranspose) (A2, 0, NULL, NULL, 0, Common) ; } F = A1 ; } else if (A->stype > 0) { /* symmetric upper case: F = triu (A (p,p))' and S = F' */ /* workspace: Iwork (2*nrow) */ A1 = CHOLMOD(ptranspose) (A, 0, Perm, NULL, 0, Common) ; F = A1 ; /* workspace: Iwork (nrow) */ A2 = CHOLMOD(ptranspose) (A1, 0, NULL, NULL, 0, Common) ; S = A2 ; } else { /* unsymmetric case: F = A (p,f)' and S = F' */ /* workspace: Iwork (nrow if no fset, MAX(nrow,ncol) if fset) */ A1 = CHOLMOD(ptranspose) (A, 0, Perm, fset, fsize, Common) ; F = A1 ; if (do_rowcolcounts) { /* S not needed for unsymmetric case if do_rowcolcounts FALSE */ /* workspace: Iwork (nrow) */ A2 = CHOLMOD(ptranspose) (A1, 0, NULL, NULL, 0, Common) ; } S = A2 ; } } /* If any cholmod_*transpose fails, one or more matrices will be NULL */ *A1_handle = A1 ; *A2_handle = A2 ; *S_handle = S ; *F_handle = F ; return (Common->status == CHOLMOD_OK) ; } /* ========================================================================== */ /* === cholmod_analyze_ordering ============================================= */ /* ========================================================================== */ /* Given a matrix A and its fill-reducing permutation, compute the elimination * tree, its (non-weighted) postordering, and the number of nonzeros in each * column of L. Also computes the flop count, the total nonzeros in L, and * the nonzeros in A (Common->fl, Common->lnz, and Common->anz). * * The column counts of L, flop count, and other statistics from * cholmod_rowcolcounts are not computed if ColCount is NULL. * * workspace: Iwork (2*nrow if symmetric, 2*nrow+ncol if unsymmetric), * Flag (nrow), Head (nrow+1) */ int CHOLMOD(analyze_ordering) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to analyze */ int ordering, /* ordering method used */ Int *Perm, /* size n, fill-reducing permutation to analyze */ Int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ /* ---- output --- */ Int *Parent, /* size n, elimination tree */ Int *Post, /* size n, postordering of elimination tree */ Int *ColCount, /* size n, nnz in each column of L */ /* ---- workspace */ Int *First, /* size n workspace for cholmod_postorder */ Int *Level, /* size n workspace for cholmod_postorder */ /* --------------- */ cholmod_common *Common ) { cholmod_sparse *A1, *A2, *S, *F ; Int n, ok, do_rowcolcounts ; /* check inputs */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (A, FALSE) ; n = A->nrow ; do_rowcolcounts = (ColCount != NULL) ; /* permute A according to Perm and fset */ ok = permute_matrices (A, ordering, Perm, fset, fsize, do_rowcolcounts, &A1, &A2, &S, &F, Common) ; /* find etree of S (symmetric upper/lower case) or F (unsym case) */ /* workspace: symmmetric: Iwork (nrow), unsym: Iwork (nrow+ncol) */ ok = ok && CHOLMOD(etree) (A->stype ? S:F, Parent, Common) ; /* postorder the etree (required by cholmod_rowcolcounts) */ /* workspace: Iwork (2*nrow) */ ok = ok && (CHOLMOD(postorder) (Parent, n, NULL, Post, Common) == n) ; /* cholmod_postorder doesn't set Common->status if it returns < n */ Common->status = (!ok && Common->status == CHOLMOD_OK) ? CHOLMOD_INVALID : Common->status ; /* analyze LL'=S or SS' or S(:,f)*S(:,f)' */ /* workspace: * if symmetric: Flag (nrow), Iwork (2*nrow) * if unsymmetric: Flag (nrow), Iwork (2*nrow+ncol), Head (nrow+1) */ if (do_rowcolcounts) { ok = ok && CHOLMOD(rowcolcounts) (A->stype ? F:S, fset, fsize, Parent, Post, NULL, ColCount, First, Level, Common) ; } /* free temporary matrices and return result */ CHOLMOD(free_sparse) (&A1, Common) ; CHOLMOD(free_sparse) (&A2, Common) ; return (ok) ; } /* ========================================================================== */ /* === Free workspace and return L ========================================== */ /* ========================================================================== */ #define FREE_WORKSPACE_AND_RETURN \ { \ Common->no_workspace_reallocate = FALSE ; \ CHOLMOD(free) (n, sizeof (Int), Lparent, Common) ; \ CHOLMOD(free) (n, sizeof (Int), Perm, Common) ; \ CHOLMOD(free) (n, sizeof (Int), ColCount, Common) ; \ if (Common->status < CHOLMOD_OK) \ { \ CHOLMOD(free_factor) (&L, Common) ; \ } \ ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; \ return (L) ; \ } /* ========================================================================== */ /* === cholmod_analyze_p2 =================================================== */ /* ========================================================================== */ /* Ordering and analysis for sparse Cholesky or sparse QR. CHOLMOD itself * always uses for_cholesky = TRUE. The for_cholesky = FALSE option is * for SuiteSparseQR only. */ cholmod_factor *CHOLMOD(analyze_p2) ( /* ---- input ---- */ int for_cholesky, /* if TRUE, then analyze for Cholesky; else for QR */ cholmod_sparse *A, /* matrix to order and analyze */ Int *UserPerm, /* user-provided permutation, size A->nrow */ Int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ /* --------------- */ cholmod_common *Common ) { double lnz_best ; Int *First, *Level, *Work4n, *Cmember, *CParent, *ColCount, *Lperm, *Parent, *Post, *Perm, *Lparent, *Lcolcount ; cholmod_factor *L ; Int k, n, ordering, method, nmethods, status, default_strategy, ncol, uncol, skip_analysis, skip_best ; Int amd_backup ; size_t s ; int ok = TRUE ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; RETURN_IF_NULL (A, NULL) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, NULL) ; Common->status = CHOLMOD_OK ; status = CHOLMOD_OK ; Common->selected = EMPTY ; Common->called_nd = FALSE ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ n = A->nrow ; ncol = A->ncol ; uncol = (A->stype == 0) ? (A->ncol) : 0 ; /* ---------------------------------------------------------------------- */ /* set the default strategy */ /* ---------------------------------------------------------------------- */ lnz_best = (double) EMPTY ; skip_best = FALSE ; nmethods = MIN (Common->nmethods, CHOLMOD_MAXMETHODS) ; nmethods = MAX (0, nmethods) ; #ifndef NDEBUG PRINT1 (("cholmod_analyze_p2 :: nmethods "ID"\n", nmethods)) ; for (method = 0 ; method < nmethods ; method++) { PRINT1 ((" "ID": ordering "ID"\n", method, Common->method [method].ordering)) ; } #endif default_strategy = (nmethods == 0) ; if (default_strategy) { /* default strategy: try UserPerm, if given. Try AMD for A, or AMD * to order A*A'. Try METIS for the symmetric case only if AMD reports * a high degree of fill-in and flop count. METIS is not tried if the * Partition Module isn't installed. If Common->default_nesdis is * TRUE, then NESDIS is used as the 3rd ordering instead. */ Common->method [0].ordering = CHOLMOD_GIVEN ;/* skip if UserPerm NULL */ Common->method [1].ordering = CHOLMOD_AMD ; Common->method [2].ordering = (Common->default_nesdis ? CHOLMOD_NESDIS : CHOLMOD_METIS) ; amd_backup = FALSE ; #ifndef NPARTITION nmethods = 3 ; #else nmethods = 2 ; #endif } else { /* If only METIS and NESDIS are selected, or if 2 or more methods are * being tried, then enable AMD backup */ amd_backup = (nmethods > 1) || (nmethods == 1 && (Common->method [0].ordering == CHOLMOD_METIS || Common->method [0].ordering == CHOLMOD_NESDIS)) ; } #ifdef NSUPERNODAL /* CHOLMOD Supernodal module not installed, just do simplicial analysis */ Common->supernodal = CHOLMOD_SIMPLICIAL ; #endif /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ /* Note: enough space needs to be allocated here so that routines called by * cholmod_analyze do not reallocate the space. */ /* s = 6*n + uncol */ s = CHOLMOD(mult_size_t) (n, 6, &ok) ; s = CHOLMOD(add_size_t) (s, uncol, &ok) ; if (!ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return (NULL) ; } CHOLMOD(allocate_work) (n, s, 0, Common) ; if (Common->status < CHOLMOD_OK) { return (NULL) ; /* out of memory */ } ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; /* ensure that subsequent routines, called by cholmod_analyze, do not * reallocate any workspace. This is set back to FALSE in the * FREE_WORKSPACE_AND_RETURN macro, which is the only way this function * returns to its caller. */ Common->no_workspace_reallocate = TRUE ; /* Use the last 4*n Int's in Iwork for Parent, First, Level, and Post, since * other CHOLMOD routines will use the first 2n+uncol space. The ordering * routines (cholmod_amd, cholmod_colamd, cholmod_ccolamd, cholmod_metis) * are an exception. They can use all 6n + ncol space, since the contents * of Parent, First, Level, and Post are not needed across calls to those * routines. */ Work4n = Common->Iwork ; Work4n += 2*((size_t) n) + uncol ; Parent = Work4n ; First = Work4n + n ; Level = Work4n + 2*((size_t) n) ; Post = Work4n + 3*((size_t) n) ; /* note that this assignment means that cholmod_nested_dissection, * cholmod_ccolamd, and cholmod_camd can use only the first 4n+uncol * space in Common->Iwork */ Cmember = Post ; CParent = Level ; /* ---------------------------------------------------------------------- */ /* allocate more workspace, and an empty simplicial symbolic factor */ /* ---------------------------------------------------------------------- */ L = CHOLMOD(allocate_factor) (n, Common) ; Lparent = CHOLMOD(malloc) (n, sizeof (Int), Common) ; Perm = CHOLMOD(malloc) (n, sizeof (Int), Common) ; ColCount = CHOLMOD(malloc) (n, sizeof (Int), Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ FREE_WORKSPACE_AND_RETURN ; } Lperm = L->Perm ; Lcolcount = L->ColCount ; Common->anz = EMPTY ; /* ---------------------------------------------------------------------- */ /* try all the requested ordering options and backup to AMD if needed */ /* ---------------------------------------------------------------------- */ /* turn off error handling [ */ Common->try_catch = TRUE ; for (method = 0 ; method <= nmethods ; method++) { /* ------------------------------------------------------------------ */ /* determine the method to try */ /* ------------------------------------------------------------------ */ Common->fl = EMPTY ; Common->lnz = EMPTY ; skip_analysis = FALSE ; if (method == nmethods) { /* All methods failed: backup to AMD */ if (Common->selected == EMPTY && amd_backup) { PRINT1 (("All methods requested failed: backup to AMD\n")) ; ordering = CHOLMOD_AMD ; } else { break ; } } else { ordering = Common->method [method].ordering ; } Common->current = method ; PRINT1 (("method "ID": Try method: "ID"\n", method, ordering)) ; /* ------------------------------------------------------------------ */ /* find the fill-reducing permutation */ /* ------------------------------------------------------------------ */ if (ordering == CHOLMOD_NATURAL) { /* -------------------------------------------------------------- */ /* natural ordering */ /* -------------------------------------------------------------- */ for (k = 0 ; k < n ; k++) { Perm [k] = k ; } } else if (ordering == CHOLMOD_GIVEN) { /* -------------------------------------------------------------- */ /* use given ordering of A, if provided */ /* -------------------------------------------------------------- */ if (UserPerm == NULL) { /* this is not an error condition */ PRINT1 (("skip, no user perm given\n")) ; continue ; } for (k = 0 ; k < n ; k++) { /* UserPerm is checked in cholmod_ptranspose */ Perm [k] = UserPerm [k] ; } } else if (ordering == CHOLMOD_AMD) { /* -------------------------------------------------------------- */ /* AMD ordering of A, A*A', or A(:,f)*A(:,f)' */ /* -------------------------------------------------------------- */ amd_backup = FALSE ; /* no need to try AMD twice ... */ CHOLMOD(amd) (A, fset, fsize, Perm, Common) ; skip_analysis = TRUE ; } else if (ordering == CHOLMOD_COLAMD) { /* -------------------------------------------------------------- */ /* AMD for symmetric case, COLAMD for A*A' or A(:,f)*A(:,f)' */ /* -------------------------------------------------------------- */ if (A->stype) { CHOLMOD(amd) (A, fset, fsize, Perm, Common) ; skip_analysis = TRUE ; } else { /* Alternative: CHOLMOD(ccolamd) (A, fset, fsize, NULL, Perm, Common) ; */ /* do not postorder, it is done later, below */ /* workspace: Iwork (4*nrow+uncol), Flag (nrow), Head (nrow+1)*/ CHOLMOD(colamd) (A, fset, fsize, FALSE, Perm, Common) ; } } else if (ordering == CHOLMOD_METIS) { /* -------------------------------------------------------------- */ /* use METIS_NodeND directly (via a CHOLMOD wrapper) */ /* -------------------------------------------------------------- */ #ifndef NPARTITION /* postorder parameter is false, because it will be later, below */ /* workspace: Iwork (4*nrow+uncol), Flag (nrow), Head (nrow+1) */ Common->called_nd = TRUE ; CHOLMOD(metis) (A, fset, fsize, FALSE, Perm, Common) ; #else Common->status = CHOLMOD_NOT_INSTALLED ; #endif } else if (ordering == CHOLMOD_NESDIS) { /* -------------------------------------------------------------- */ /* use CHOLMOD's nested dissection */ /* -------------------------------------------------------------- */ /* this method is based on METIS' node bissection routine * (METIS_NodeComputeSeparator). In contrast to METIS_NodeND, * it calls CAMD or CCOLAMD on the whole graph, instead of MMD * on just the leaves. */ #ifndef NPARTITION /* workspace: Flag (nrow), Head (nrow+1), Iwork (2*nrow) */ Common->called_nd = TRUE ; CHOLMOD(nested_dissection) (A, fset, fsize, Perm, CParent, Cmember, Common) ; #else Common->status = CHOLMOD_NOT_INSTALLED ; #endif } else { /* -------------------------------------------------------------- */ /* invalid ordering method */ /* -------------------------------------------------------------- */ Common->status = CHOLMOD_INVALID ; PRINT1 (("No such ordering: "ID"\n", ordering)) ; } ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; if (Common->status < CHOLMOD_OK) { /* out of memory, or method failed */ status = MIN (status, Common->status) ; Common->status = CHOLMOD_OK ; continue ; } /* ------------------------------------------------------------------ */ /* analyze the ordering */ /* ------------------------------------------------------------------ */ if (!skip_analysis) { if (!CHOLMOD(analyze_ordering) (A, ordering, Perm, fset, fsize, Parent, Post, ColCount, First, Level, Common)) { /* ordering method failed; clear status and try next method */ status = MIN (status, Common->status) ; Common->status = CHOLMOD_OK ; continue ; } } ASSERT (Common->fl >= 0 && Common->lnz >= 0) ; Common->method [method].fl = Common->fl ; Common->method [method].lnz = Common->lnz ; PRINT1 (("lnz %g fl %g\n", Common->lnz, Common->fl)) ; /* ------------------------------------------------------------------ */ /* pick the best method */ /* ------------------------------------------------------------------ */ /* fl.pt. compare, but lnz can never be NaN */ if (Common->selected == EMPTY || Common->lnz < lnz_best) { Common->selected = method ; PRINT1 (("this is best so far, method "ID"\n", method)) ; L->ordering = ordering ; lnz_best = Common->lnz ; for (k = 0 ; k < n ; k++) { Lperm [k] = Perm [k] ; } /* save the results of cholmod_analyze_ordering, if it was called */ skip_best = skip_analysis ; if (!skip_analysis) { /* save the column count; becomes permanent part of L */ for (k = 0 ; k < n ; k++) { Lcolcount [k] = ColCount [k] ; } /* Parent is needed for weighted postordering and for supernodal * analysis. Does not become a permanent part of L */ for (k = 0 ; k < n ; k++) { Lparent [k] = Parent [k] ; } } } /* ------------------------------------------------------------------ */ /* determine if METIS is to be skipped */ /* ------------------------------------------------------------------ */ if (default_strategy && ordering == CHOLMOD_AMD) { if ((Common->fl < 500 * Common->lnz) || (Common->lnz < 5 * Common->anz)) { /* AMD found an ordering with less than 500 flops per nonzero in * L, or one with a fill-in ratio (nnz(L)/nnz(A)) of less than * 5. This is pretty good, and it's unlikely that METIS will do * better (this heuristic is based on tests on all symmetric * positive definite matrices in the UF sparse matrix * collection, and it works well across a wide range of * problems). METIS can take much more time than AMD. */ break ; } } } /* turn error printing back on ] */ Common->try_catch = FALSE ; /* ---------------------------------------------------------------------- */ /* return if no ordering method succeeded */ /* ---------------------------------------------------------------------- */ if (Common->selected == EMPTY) { /* All methods failed. * If two or more methods failed, they may have failed for different * reasons. Both would clear Common->status and skip to the next * method. Common->status needs to be restored here to the worst error * obtained in any of the methods. CHOLMOD_INVALID is worse * than CHOLMOD_OUT_OF_MEMORY, since the former implies something may * be wrong with the user's input. CHOLMOD_OUT_OF_MEMORY is simply an * indication of lack of resources. */ if (status >= CHOLMOD_OK) { /* this can occur if nmethods = 1, ordering = CHOLMOD_GIVEN, but UserPerm is NULL */ status = CHOLMOD_INVALID ; } ERROR (status, "all methods failed") ; FREE_WORKSPACE_AND_RETURN ; } /* ---------------------------------------------------------------------- */ /* do the analysis for AMD, if skipped */ /* ---------------------------------------------------------------------- */ Common->fl = Common->method [Common->selected].fl ; Common->lnz = Common->method [Common->selected].lnz ; ASSERT (Common->lnz >= 0) ; if (skip_best) { if (!CHOLMOD(analyze_ordering) (A, L->ordering, Lperm, fset, fsize, Lparent, Post, Lcolcount, First, Level, Common)) { /* out of memory, or method failed */ FREE_WORKSPACE_AND_RETURN ; } } /* ---------------------------------------------------------------------- */ /* postorder the etree, weighted by the column counts */ /* ---------------------------------------------------------------------- */ if (Common->postorder) { /* combine the fill-reducing ordering with the weighted postorder */ /* workspace: Iwork (2*nrow) */ if (CHOLMOD(postorder) (Lparent, n, Lcolcount, Post, Common) == n) { /* use First and Level as workspace [ */ Int *Wi = First, *InvPost = Level ; Int newchild, oldchild, newparent, oldparent ; for (k = 0 ; k < n ; k++) { Wi [k] = Lperm [Post [k]] ; } for (k = 0 ; k < n ; k++) { Lperm [k] = Wi [k] ; } for (k = 0 ; k < n ; k++) { Wi [k] = Lcolcount [Post [k]] ; } for (k = 0 ; k < n ; k++) { Lcolcount [k] = Wi [k] ; } for (k = 0 ; k < n ; k++) { InvPost [Post [k]] = k ; } /* updated Lparent needed only for supernodal case */ for (newchild = 0 ; newchild < n ; newchild++) { oldchild = Post [newchild] ; oldparent = Lparent [oldchild] ; newparent = (oldparent == EMPTY) ? EMPTY : InvPost [oldparent] ; Wi [newchild] = newparent ; } for (k = 0 ; k < n ; k++) { Lparent [k] = Wi [k] ; } /* done using Iwork as workspace ] */ /* L is now postordered, no longer in natural ordering */ if (L->ordering == CHOLMOD_NATURAL) { L->ordering = CHOLMOD_POSTORDERED ; } } } /* ---------------------------------------------------------------------- */ /* supernodal analysis, if requested or if selected automatically */ /* ---------------------------------------------------------------------- */ #ifndef NSUPERNODAL if (Common->supernodal > CHOLMOD_AUTO || (Common->supernodal == CHOLMOD_AUTO && Common->lnz > 0 && (Common->fl / Common->lnz) >= Common->supernodal_switch)) { cholmod_sparse *S, *F, *A2, *A1 ; permute_matrices (A, L->ordering, Lperm, fset, fsize, TRUE, &A1, &A2, &S, &F, Common) ; /* workspace: Flag (nrow), Head (nrow), Iwork (5*nrow) */ CHOLMOD(super_symbolic2) (for_cholesky, S, F, Lparent, L, Common) ; PRINT1 (("status %d\n", Common->status)) ; CHOLMOD(free_sparse) (&A1, Common) ; CHOLMOD(free_sparse) (&A2, Common) ; } #endif /* ---------------------------------------------------------------------- */ /* free temporary matrices and workspace, and return result L */ /* ---------------------------------------------------------------------- */ FREE_WORKSPACE_AND_RETURN ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Cholesky/cholmod_spsolve.c0000644000076500000240000002364313524616144027626 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Cholesky/cholmod_spsolve ============================================= */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Cholesky Module. Copyright (C) 2005-2006, Timothy A. Davis * The CHOLMOD/Cholesky Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Given an LL' or LDL' factorization of A, solve one of the following systems: * * Ax=b 0: CHOLMOD_A also applies the permutation L->Perm * LDL'x=b 1: CHOLMOD_LDLt does not apply L->Perm * LDx=b 2: CHOLMOD_LD * DL'x=b 3: CHOLMOD_DLt * Lx=b 4: CHOLMOD_L * L'x=b 5: CHOLMOD_Lt * Dx=b 6: CHOLMOD_D * x=Pb 7: CHOLMOD_P apply a permutation (P is L->Perm) * x=P'b 8: CHOLMOD_Pt apply an inverse permutation * * where b and x are sparse. If L and b are real, then x is real. Otherwise, * x is complex or zomplex, depending on the Common->prefer_zomplex parameter. * All xtypes of x and b are supported (real, complex, and zomplex). */ #ifndef NCHOLESKY #include "cholmod_internal.h" #include "cholmod_cholesky.h" /* ========================================================================== */ /* === EXPAND_AS_NEEDED ===================================================== */ /* ========================================================================== */ /* Double the size of the sparse matrix X, if we have run out of space. */ #define EXPAND_AS_NEEDED \ if (xnz >= nzmax) \ { \ nzmax *= 2 ; \ CHOLMOD(reallocate_sparse) (nzmax, X, Common) ; \ if (Common->status < CHOLMOD_OK) \ { \ CHOLMOD(free_sparse) (&X, Common) ; \ CHOLMOD(free_dense) (&X4, Common) ; \ CHOLMOD(free_dense) (&B4, Common) ; \ return (NULL) ; \ } \ Xi = X->i ; \ Xx = X->x ; \ Xz = X->z ; \ } /* ========================================================================== */ /* === cholmod_spolve ======================================================= */ /* ========================================================================== */ cholmod_sparse *CHOLMOD(spsolve) /* returns the sparse solution X */ ( /* ---- input ---- */ int sys, /* system to solve */ cholmod_factor *L, /* factorization to use */ cholmod_sparse *B, /* right-hand-side */ /* --------------- */ cholmod_common *Common ) { double x, z ; cholmod_dense *X4, *B4 ; cholmod_sparse *X ; double *Bx, *Bz, *Xx, *Xz, *B4x, *B4z, *X4x, *X4z ; Int *Bi, *Bp, *Xp, *Xi, *Bnz ; Int n, nrhs, q, p, i, j, jfirst, jlast, packed, block, pend, j_n, xtype ; size_t xnz, nzmax ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; RETURN_IF_NULL (L, NULL) ; RETURN_IF_NULL (B, NULL) ; RETURN_IF_XTYPE_INVALID (L, CHOLMOD_REAL, CHOLMOD_ZOMPLEX, NULL) ; RETURN_IF_XTYPE_INVALID (B, CHOLMOD_REAL, CHOLMOD_ZOMPLEX, NULL) ; if (L->n != B->nrow) { ERROR (CHOLMOD_INVALID, "dimensions of L and B do not match") ; return (NULL) ; } if (B->stype) { ERROR (CHOLMOD_INVALID, "B cannot be stored in symmetric mode") ; return (NULL) ; } Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* allocate workspace B4 and initial result X */ /* ---------------------------------------------------------------------- */ n = L->n ; nrhs = B->ncol ; /* X is real if both L and B are real, complex/zomplex otherwise */ xtype = (L->xtype == CHOLMOD_REAL && B->xtype == CHOLMOD_REAL) ? CHOLMOD_REAL : (Common->prefer_zomplex ? CHOLMOD_ZOMPLEX : CHOLMOD_COMPLEX) ; /* solve up to 4 columns at a time */ block = MIN (nrhs, 4) ; /* initial size of X is at most 4*n */ nzmax = n*block ; X = CHOLMOD(spzeros) (n, nrhs, nzmax, xtype, Common) ; B4 = CHOLMOD(zeros) (n, block, B->xtype, Common) ; if (Common->status < CHOLMOD_OK) { CHOLMOD(free_sparse) (&X, Common) ; CHOLMOD(free_dense) (&B4, Common) ; return (NULL) ; } Bp = B->p ; Bi = B->i ; Bx = B->x ; Bz = B->z ; Bnz = B->nz ; packed = B->packed ; Xp = X->p ; Xi = X->i ; Xx = X->x ; Xz = X->z ; xnz = 0 ; B4x = B4->x ; B4z = B4->z ; /* ---------------------------------------------------------------------- */ /* solve in chunks of 4 columns at a time */ /* ---------------------------------------------------------------------- */ for (jfirst = 0 ; jfirst < nrhs ; jfirst += block) { /* ------------------------------------------------------------------ */ /* adjust the number of columns of B4 */ /* ------------------------------------------------------------------ */ jlast = MIN (nrhs, jfirst + block) ; B4->ncol = jlast - jfirst ; /* ------------------------------------------------------------------ */ /* scatter B(jfirst:jlast-1) into B4 */ /* ------------------------------------------------------------------ */ for (j = jfirst ; j < jlast ; j++) { p = Bp [j] ; pend = (packed) ? (Bp [j+1]) : (p + Bnz [j]) ; j_n = (j-jfirst)*n ; switch (B->xtype) { case CHOLMOD_REAL: for ( ; p < pend ; p++) { B4x [Bi [p] + j_n] = Bx [p] ; } break ; case CHOLMOD_COMPLEX: for ( ; p < pend ; p++) { q = Bi [p] + j_n ; B4x [2*q ] = Bx [2*p ] ; B4x [2*q+1] = Bx [2*p+1] ; } break ; case CHOLMOD_ZOMPLEX: for ( ; p < pend ; p++) { q = Bi [p] + j_n ; B4x [q] = Bx [p] ; B4z [q] = Bz [p] ; } break ; } } /* ------------------------------------------------------------------ */ /* solve the system (X4 = A\B4 or other system) */ /* ------------------------------------------------------------------ */ X4 = CHOLMOD(solve) (sys, L, B4, Common) ; if (Common->status < CHOLMOD_OK) { CHOLMOD(free_sparse) (&X, Common) ; CHOLMOD(free_dense) (&B4, Common) ; CHOLMOD(free_dense) (&X4, Common) ; return (NULL) ; } ASSERT (X4->xtype == xtype) ; X4x = X4->x ; X4z = X4->z ; /* ------------------------------------------------------------------ */ /* append the solution onto X */ /* ------------------------------------------------------------------ */ for (j = jfirst ; j < jlast ; j++) { Xp [j] = xnz ; j_n = (j-jfirst)*n ; if ( xnz + n <= nzmax) { /* ---------------------------------------------------------- */ /* X is guaranteed to be large enough */ /* ---------------------------------------------------------- */ switch (xtype) { case CHOLMOD_REAL: for (i = 0 ; i < n ; i++) { x = X4x [i + j_n] ; if (IS_NONZERO (x)) { Xi [xnz] = i ; Xx [xnz] = x ; xnz++ ; } } break ; case CHOLMOD_COMPLEX: for (i = 0 ; i < n ; i++) { x = X4x [2*(i + j_n) ] ; z = X4x [2*(i + j_n)+1] ; if (IS_NONZERO (x) || IS_NONZERO (z)) { Xi [xnz] = i ; Xx [2*xnz ] = x ; Xx [2*xnz+1] = z ; xnz++ ; } } break ; case CHOLMOD_ZOMPLEX: for (i = 0 ; i < n ; i++) { x = X4x [i + j_n] ; z = X4z [i + j_n] ; if (IS_NONZERO (x) || IS_NONZERO (z)) { Xi [xnz] = i ; Xx [xnz] = x ; Xz [xnz] = z ; xnz++ ; } } break ; } } else { /* ---------------------------------------------------------- */ /* X may need to increase in size */ /* ---------------------------------------------------------- */ switch (xtype) { case CHOLMOD_REAL: for (i = 0 ; i < n ; i++) { x = X4x [i + j_n] ; if (IS_NONZERO (x)) { EXPAND_AS_NEEDED ; Xi [xnz] = i ; Xx [xnz] = x ; xnz++ ; } } break ; case CHOLMOD_COMPLEX: for (i = 0 ; i < n ; i++) { x = X4x [2*(i + j_n) ] ; z = X4x [2*(i + j_n)+1] ; if (IS_NONZERO (x) || IS_NONZERO (z)) { EXPAND_AS_NEEDED ; Xi [xnz] = i ; Xx [2*xnz ] = x ; Xx [2*xnz+1] = z ; xnz++ ; } } break ; case CHOLMOD_ZOMPLEX: for (i = 0 ; i < n ; i++) { x = X4x [i + j_n] ; z = X4z [i + j_n] ; if (IS_NONZERO (x) || IS_NONZERO (z)) { EXPAND_AS_NEEDED ; Xi [xnz] = i ; Xx [xnz] = x ; Xz [xnz] = z ; xnz++ ; } } break ; } } } CHOLMOD(free_dense) (&X4, Common) ; /* ------------------------------------------------------------------ */ /* clear B4 for next iteration */ /* ------------------------------------------------------------------ */ if (jlast < nrhs) { for (j = jfirst ; j < jlast ; j++) { p = Bp [j] ; pend = (packed) ? (Bp [j+1]) : (p + Bnz [j]) ; j_n = (j-jfirst)*n ; switch (B->xtype) { case CHOLMOD_REAL: for ( ; p < pend ; p++) { B4x [Bi [p] + j_n] = 0 ; } break ; case CHOLMOD_COMPLEX: for ( ; p < pend ; p++) { q = Bi [p] + j_n ; B4x [2*q ] = 0 ; B4x [2*q+1] = 0 ; } break ; case CHOLMOD_ZOMPLEX: for ( ; p < pend ; p++) { q = Bi [p] + j_n ; B4x [q] = 0 ; B4z [q] = 0 ; } break ; } } } } Xp [nrhs] = xnz ; /* ---------------------------------------------------------------------- */ /* reduce X in size, free workspace, and return result */ /* ---------------------------------------------------------------------- */ ASSERT (xnz <= X->nzmax) ; CHOLMOD(reallocate_sparse) (xnz, X, Common) ; ASSERT (Common->status == CHOLMOD_OK) ; CHOLMOD(free_dense) (&B4, Common) ; return (X) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/README.txt0000644000076500000240000001002113524616144024161 0ustar tamasstaff00000000000000CHOLMOD: a sparse CHOLesky MODification package, Copyright (c) 2005-2012. http://www.suitesparse.com ----------------------------------------------- CHOLMOD is a set of routines for factorizing sparse symmetric positive definite matrices of the form A or AA', updating/downdating a sparse Cholesky factorization, solving linear systems, updating/downdating the solution to the triangular system Lx=b, and many other sparse matrix functions for both symmetric and unsymmetric matrices. Its supernodal Cholesky factorization relies on LAPACK and the Level-3 BLAS, and obtains a substantial fraction of the peak performance of the BLAS. Both real and complex matrices are supported. CHOLMOD is written in ANSI/ISO C, with both C and MATLAB interfaces. This code works on Microsoft Windows and many versions of Unix and Linux. Some Modules of CHOLMOD are copyrighted by the University of Florida (the Core and Partition Modules). The rest are copyrighted by the authors: Timothy A. Davis (all of them), and William W. Hager (the Modify Module). CHOLMOD relies on several other packages: AMD, CAMD, COLAMD, CCOLAMD, SuiteSparse_config, METIS, the BLAS, and LAPACK. All but METIS, the BLAS, and LAPACK are part of SuiteSparse. AMD is authored by T. Davis, Iain Duff, and Patrick Amestoy. COLAMD is authored by T. Davis and Stefan Larimore, with algorithmic design in collaboration with John Gilbert and Esmond Ng. CCOLAMD is authored by T. Davis and Siva Rajamanickam. CAMD is authored by T. Davis and Y. Chen. LAPACK and the BLAS are authored by Jack Dongarra and many others. LAPACK is available at http://www.netlib.org/lapack METIS is authored by George Karypis, Univ. of Minnesota. Its use in CHOLMOD is optional. See http://www-users.cs.umn.edu/~karypis/metis. Place a copy of the metis-4.0 directory in the same directory that contains the CHOLMOD, AMD, COLAMD, and CCOLAMD directories prior to compiling with "make". If you do not wish to use METIS, you must edit SuiteSparse_config and change the line: CHOLMOD_CONFIG = to CHOLMOD_CONFIG = -DNPARTITION The CHOLMOD, AMD, COLAMD, CCOLAMD, and SuiteSparse)config directories must all reside in a common parent directory. To compile all these libraries, edit SuiteSparse)config/SuiteSparse)config.mk to reflect your environment (C compiler, location of the BLAS, and so on) and then type "make" in either the CHOLMOD directory or in the parent directory of CHOLMOD. See each package for more details on how to compile them. For use in MATLAB (on any system, including Windows): start MATLAB, cd to the CHOLMOD/MATLAB directory, and type cholmod_make in the MATLAB Command Window. This is the best way to compile CHOLMOD for MATLAB; it provides a workaround for a METIS design feature, in which METIS terminates your program (and thus MATLAB) if it runs out of memory. Using cholmod_make also ensures your mexFunctions are compiled with -fexceptions, so that exceptions are handled properly (when hitting control-C in the MATLAB command window, for example). On the Pentium, do NOT use the Intel MKL BLAS prior to MKL Version 8.0 with CHOLMOD. Older versions (prior to 8.0) have a bug in dgemm when computing A*B'. The bug generates a NaN result, when the inputs are well-defined. Use the Goto BLAS or the MKL v8.0 BLAS instead. The Goto BLAS is faster and more reliable. See http://www.tacc.utexas.edu/~kgoto/ or http://www.cs.utexas.edu/users/flame/goto/. Sadly, the Intel MKL BLAS 7.x is the default for MATLAB 7.0.4. See http://www.mathworks.com/support/bugreports/details.html?rp=252103 for more details. To workaround this problem on Linux, set environment variable BLAS_VERSION to libmkl_p3.so:libguide.so. On Windows, set environment variable BLAS_VERSION to mkl_p3.dll. Better yet, get MATLAB 7sp3 (MATLAB 7.1) or later. Acknowledgements: this work was supported in part by the National Science Foundation (NFS CCR-0203270 and DMS-9803599), and a grant from Sandia National Laboratories (Dept. of Energy) which supported the development of CHOLMOD's Partition Module. python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Supernodal/0000755000076500000240000000000013617375001024602 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Supernodal/cholmod_super_symbolic.c0000644000076500000240000007176113524616144031531 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Supernodal/cholmod_super_symbolic ==================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Supernodal Module. Copyright (C) 2005-2006, Timothy A. Davis * The CHOLMOD/Supernodal Module is licensed under Version 2.0 of the GNU * General Public License. See gpl.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * http://www.suitesparse.com * -------------------------------------------------------------------------- */ /* Supernodal symbolic analysis of the LL' factorization of A, A*A', * A(:,f)*A(:,f)'. * * This routine must be preceded by a simplicial symbolic analysis * (cholmod_rowcolcounts). See cholmod_analyze.c for an example of how to use * this routine. * * The user need not call this directly; cholmod_analyze is a "simple" wrapper * for this routine. * * Symmetric case: * * A is stored in column form, with entries stored in the upper triangular * part. Entries in the lower triangular part are ignored. * * Unsymmetric case: * * A is stored in column form. If F is equal to the transpose of A, then * A*A' is analyzed. F can include a subset of the columns of A * (F=A(:,f)'), in which case F*F' is analyzed. * * Requires Parent and L->ColCount to be defined on input; these are the * simplicial Parent and ColCount arrays as computed by cholmod_rowcolcounts. * Does not use L->Perm; the input matrices A and F must already be properly * permuted. Allocates and computes the supernodal pattern of L (L->super, * L->pi, L->px, and L->s). Does not allocate the real part (L->x). * * Supports any xtype (pattern, real, complex, or zomplex). */ #ifndef NSUPERNODAL #include "cholmod_internal.h" #include "cholmod_supernodal.h" /* ========================================================================== */ /* === subtree ============================================================== */ /* ========================================================================== */ /* In the symmetric case, traverse the kth row subtree from the nonzeros in * A (0:k1-1,k) and add the new entries found to the pattern of the kth row * of L. The current supernode s contains the diagonal block k1:k2-1, so it * can be skipped. * * In the unsymmetric case, the nonzero pattern of A*F is computed one column * at a time (thus, the total time spent in this function is bounded below by * the time taken to multiply A*F, which can be high if A is tall and thin). * The kth column is A*F(:,k), or the set union of all columns A(:,j) for which * F(j,k) is nonzero. This routine is called once for each entry j. Only the * upper triangular part is needed, so only A (0:k1-1,j) is accessed, where * k1:k2-1 are the columns of the current supernode s (k is in the range k1 to * k2-1). * * If A is sorted, then the total time taken by this function is proportional * to the number of nonzeros in the strictly block upper triangular part of A, * plus the number of entries in the strictly block lower triangular part of * the supernodal part of L. This excludes entries in the diagonal blocks * corresponding to the columns in each supernode. That is, if k1:k2-1 are * in a single supernode, then only A (0:k1-1,k1:k2-1) are accessed. * * For the unsymmetric case, only the strictly block upper triangular part * of A*F is constructed. * * Only adds column indices corresponding to the leading columns of each * relaxed supernode. */ static void subtree ( /* inputs, not modified: */ Int j, /* j = k for symmetric case */ Int k, Int Ap [ ], Int Ai [ ], Int Anz [ ], Int SuperMap [ ], Int Sparent [ ], Int mark, Int sorted, /* true if the columns of A are sorted */ Int k1, /* only consider A (0:k1-1,k) */ /* input/output: */ Int Flag [ ], Int Ls [ ], Int Lpi2 [ ] ) { Int p, pend, i, si ; p = Ap [j] ; pend = (Anz == NULL) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { i = Ai [p] ; if (i < k1) { /* (i,k) is an entry in the upper triangular part of A or A*F'. * symmetric case: A(i,k) is nonzero (j=k). * unsymmetric case: A(i,j) and F(j,k) are both nonzero. * * Column i is in supernode si = SuperMap [i]. Follow path from si * to root of supernodal etree, stopping at the first flagged * supernode. The root of the row subtree is supernode SuperMap[k], * which is flagged already. This traversal will stop there, or it * might stop earlier if supernodes have been flagged by previous * calls to this routine for the same k. */ for (si = SuperMap [i] ; Flag [si] < mark ; si = Sparent [si]) { ASSERT (si <= SuperMap [k]) ; Ls [Lpi2 [si]++] = k ; Flag [si] = mark ; } } else if (sorted) { break ; } } } /* clear workspace used by cholmod_super_symbolic */ #define FREE_WORKSPACE \ { \ /* CHOLMOD(clear_flag) (Common) ; */ \ CHOLMOD_CLEAR_FLAG (Common) ; \ for (k = 0 ; k <= nfsuper ; k++) \ { \ Head [k] = EMPTY ; \ } \ ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; \ } \ /* ========================================================================== */ /* === cholmod_super_symbolic2 ============================================== */ /* ========================================================================== */ /* Analyze for supernodal Cholesky or multifrontal QR. CHOLMOD itself always * analyzes for supernodal Cholesky, of course. The "for_cholesky = TRUE" * option is used by SuiteSparseQR only. */ int CHOLMOD(super_symbolic2) ( /* ---- input ---- */ int for_cholesky, /* Cholesky if TRUE, QR if FALSE */ cholmod_sparse *A, /* matrix to analyze */ cholmod_sparse *F, /* F = A' or A(:,f)' */ Int *Parent, /* elimination tree */ /* ---- in/out --- */ cholmod_factor *L, /* simplicial symbolic on input, * supernodal symbolic on output */ /* --------------- */ cholmod_common *Common ) { double zrelax0, zrelax1, zrelax2, xxsize ; Int *Wi, *Wj, *Super, *Snz, *Ap, *Ai, *Flag, *Head, *Ls, *Lpi, *Lpx, *Fnz, *Sparent, *Anz, *SuperMap, *Merged, *Nscol, *Zeros, *Fp, *Fj, *ColCount, *Lpi2, *Lsuper, *Iwork ; Int nsuper, d, n, j, k, s, mark, parent, p, pend, k1, k2, packed, nscol, nsrow, ndrow1, ndrow2, stype, ssize, xsize, sparent, plast, slast, csize, maxcsize, ss, nscol0, nscol1, ns, nfsuper, newzeros, totzeros, merge, snext, esize, maxesize, nrelax0, nrelax1, nrelax2, Asorted ; size_t w ; int ok = TRUE ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (A, FALSE) ; RETURN_IF_NULL (L, FALSE) ; RETURN_IF_NULL (Parent, FALSE) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; RETURN_IF_XTYPE_INVALID (L, CHOLMOD_PATTERN, CHOLMOD_PATTERN, FALSE) ; stype = A->stype ; if (stype < 0) { /* invalid symmetry; symmetric lower form not supported */ ERROR (CHOLMOD_INVALID, "symmetric lower not supported") ; return (FALSE) ; } if (stype == 0) { /* F must be present in the unsymmetric case */ RETURN_IF_NULL (F, FALSE) ; } if (L->is_super) { /* L must be a simplicial symbolic factor */ ERROR (CHOLMOD_INVALID, "L must be symbolic on input") ; return (FALSE) ; } Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ n = A->nrow ; /* w = 5*n */ w = CHOLMOD(mult_size_t) (n, 5, &ok) ; if (!ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return (FALSE) ; } CHOLMOD(allocate_work) (n, w, 0, Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ return (FALSE) ; } ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ /* A is now either A or triu(A(p,p)) for the symmetric case. It is either * A or A(p,f) for the unsymmetric case (both in column form). It can be * either packed or unpacked, and either sorted or unsorted. Entries in * the lower triangular part may be present if A is symmetric, but these * are ignored. */ Ap = A->p ; Ai = A->i ; Anz = A->nz ; if (stype != 0) { /* F not accessed */ Fp = NULL ; Fj = NULL ; Fnz = NULL ; packed = TRUE ; } else { /* F = A(:,f) or A(p,f) in packed row form, either sorted or unsorted */ Fp = F->p ; Fj = F->i ; Fnz = F->nz ; packed = F->packed ; } ColCount = L->ColCount ; nrelax0 = Common->nrelax [0] ; nrelax1 = Common->nrelax [1] ; nrelax2 = Common->nrelax [2] ; zrelax0 = Common->zrelax [0] ; zrelax1 = Common->zrelax [1] ; zrelax2 = Common->zrelax [2] ; zrelax0 = IS_NAN (zrelax0) ? 0 : zrelax0 ; zrelax1 = IS_NAN (zrelax1) ? 0 : zrelax1 ; zrelax2 = IS_NAN (zrelax2) ? 0 : zrelax2 ; ASSERT (CHOLMOD(dump_parent) (Parent, n, "Parent", Common)) ; /* ---------------------------------------------------------------------- */ /* get workspace */ /* ---------------------------------------------------------------------- */ /* Sparent, Snz, and Merged could be allocated later, of size nfsuper */ Iwork = Common->Iwork ; Wi = Iwork ; /* size n (i/l/l). Lpi2 is i/l/l */ Wj = Iwork + n ; /* size n (i/l/l). Zeros is i/l/l */ Sparent = Iwork + 2*((size_t) n) ; /* size nfsuper <= n [ */ Snz = Iwork + 3*((size_t) n) ; /* size nfsuper <= n [ */ Merged = Iwork + 4*((size_t) n) ; /* size nfsuper <= n [ */ Flag = Common->Flag ; /* size n */ Head = Common->Head ; /* size n+1 */ /* ---------------------------------------------------------------------- */ /* find the fundamental supernodes */ /* ---------------------------------------------------------------------- */ /* count the number of children of each node, using Wi [ */ for (j = 0 ; j < n ; j++) { Wi [j] = 0 ; } for (j = 0 ; j < n ; j++) { parent = Parent [j] ; if (parent != EMPTY) { Wi [parent]++ ; } } Super = Head ; /* use Head [0..nfsuper] as workspace for Super list ( */ /* column 0 always starts a new supernode */ nfsuper = (n == 0) ? 0 : 1 ; /* number of fundamental supernodes */ Super [0] = 0 ; for (j = 1 ; j < n ; j++) { /* check if j starts new supernode, or in the same supernode as j-1 */ if (Parent [j-1] != j /* parent of j-1 is not j */ || (ColCount [j-1] != ColCount [j] + 1) /* j-1 not subset of j*/ || Wi [j] > 1) /* j has more than one child */ { /* j is the leading node of a supernode */ Super [nfsuper++] = j ; } } Super [nfsuper] = n ; /* contents of Wi no longer needed for child count ] */ Nscol = Wi ; /* use Wi as size-nfsuper workspace for Nscol [ */ /* ---------------------------------------------------------------------- */ /* find the mapping of fundamental nodes to supernodes */ /* ---------------------------------------------------------------------- */ SuperMap = Wj ; /* use Wj as workspace for SuperMap [ */ /* SuperMap [k] = s if column k is contained in supernode s */ for (s = 0 ; s < nfsuper ; s++) { for (k = Super [s] ; k < Super [s+1] ; k++) { SuperMap [k] = s ; } } /* ---------------------------------------------------------------------- */ /* construct the fundamental supernodal etree */ /* ---------------------------------------------------------------------- */ for (s = 0 ; s < nfsuper ; s++) { j = Super [s+1] - 1 ; /* last node in supernode s */ parent = Parent [j] ; /* parent of last node */ Sparent [s] = (parent == EMPTY) ? EMPTY : SuperMap [parent] ; PRINT1 (("Sparent ["ID"] = "ID"\n", s, Sparent [s])) ; } /* contents of Wj no longer needed as workspace for SuperMap ] * SuperMap will be recomputed below, for the relaxed supernodes. */ Zeros = Wj ; /* use Wj for Zeros, workspace of size nfsuper [ */ /* ---------------------------------------------------------------------- */ /* relaxed amalgamation */ /* ---------------------------------------------------------------------- */ for (s = 0 ; s < nfsuper ; s++) { Merged [s] = EMPTY ; /* s not merged into another */ Nscol [s] = Super [s+1] - Super [s] ; /* # of columns in s */ Zeros [s] = 0 ; /* # of zero entries in s */ ASSERT (s <= Super [s]) ; Snz [s] = ColCount [Super [s]] ; /* # of entries in leading col of s */ PRINT2 (("lnz ["ID"] "ID"\n", s, Snz [s])) ; } for (s = nfsuper-2 ; s >= 0 ; s--) { /* should supernodes s and s+1 merge into a new node s? */ PRINT1 (("\n========= Check relax of s "ID" and s+1 "ID"\n", s, s+1)) ; ss = Sparent [s] ; if (ss == EMPTY) { PRINT1 (("s "ID" is a root, no merge with s+1 = "ID"\n", s, s+1)) ; continue ; } /* find the current parent of s (perform path compression as needed) */ for (ss = Sparent [s] ; Merged [ss] != EMPTY ; ss = Merged [ss]) ; sparent = ss ; PRINT2 (("Current sparent of s "ID" is "ID"\n", s, sparent)) ; /* ss is the current parent of s */ for (ss = Sparent [s] ; Merged [ss] != EMPTY ; ss = snext) { snext = Merged [ss] ; PRINT2 (("ss "ID" is dead, merged into snext "ID"\n", ss, snext)) ; Merged [ss] = sparent ; } /* if s+1 is not the current parent of s, do not merge */ if (sparent != s+1) { continue ; } nscol0 = Nscol [s] ; /* # of columns in s */ nscol1 = Nscol [s+1] ; /* # of columns in s+1 */ ns = nscol0 + nscol1 ; PRINT2 (("ns "ID" nscol0 "ID" nscol1 "ID"\n", ns, nscol0, nscol1)) ; totzeros = Zeros [s+1] ; /* current # of zeros in s+1 */ /* determine if supernodes s and s+1 should merge */ if (ns <= nrelax0) { PRINT2 (("ns is tiny ("ID"), so go ahead and merge\n", ns)) ; merge = TRUE ; } else { /* use double to avoid integer overflow */ double lnz0 = Snz [s] ; /* # entries in leading column of s */ double lnz1 = Snz [s+1] ; /* # entries in leading column of s+1 */ double xnewzeros = nscol0 * (lnz1 + nscol0 - lnz0) ; /* use Int for the final update of Zeros [s] below */ newzeros = nscol0 * (Snz [s+1] + nscol0 - Snz [s]) ; ASSERT (newzeros == xnewzeros) ; PRINT2 (("lnz0 %g lnz1 %g xnewzeros %g\n", lnz0, lnz1, xnewzeros)) ; if (xnewzeros == 0) { /* no new zeros, so go ahead and merge */ PRINT2 (("no new fillin, so go ahead and merge\n")) ; merge = TRUE ; } else { /* # of zeros if merged */ double xtotzeros = ((double) totzeros) + xnewzeros ; /* xtotsize: total size of merged supernode, if merged: */ double xns = (double) ns ; double xtotsize = (xns * (xns+1) / 2) + xns * (lnz1 - nscol1) ; double z = xtotzeros / xtotsize ; Int totsize ; totsize = (ns * (ns+1) / 2) + ns * (Snz [s+1] - nscol1) ; PRINT2 (("oldzeros "ID" newzeros "ID" xtotsize %g z %g\n", Zeros [s+1], newzeros, xtotsize, z)) ; /* use Int for the final update of Zeros [s] below */ totzeros += newzeros ; /* do not merge if supernode would become too big * (Int overflow). Continue computing; not (yet) an error. */ /* fl.pt. compare, but no NaN's can occur here */ merge = ((ns <= nrelax1 && z < zrelax0) || (ns <= nrelax2 && z < zrelax1) || (z < zrelax2)) && (xtotsize < Int_max / sizeof (double)) ; } } if (merge) { PRINT1 (("Merge node s ("ID") and s+1 ("ID")\n", s, s+1)) ; Zeros [s] = totzeros ; Merged [s+1] = s ; Snz [s] = nscol0 + Snz [s+1] ; Nscol [s] += Nscol [s+1] ; } } /* contents of Wj no longer needed for Zeros ] */ /* contents of Wi no longer needed for Nscol ] */ /* contents of Sparent no longer needed (recomputed below) */ /* ---------------------------------------------------------------------- */ /* construct the relaxed supernode list */ /* ---------------------------------------------------------------------- */ nsuper = 0 ; for (s = 0 ; s < nfsuper ; s++) { if (Merged [s] == EMPTY) { PRINT1 (("live supernode: "ID" snz "ID"\n", s, Snz [s])) ; Super [nsuper] = Super [s] ; Snz [nsuper] = Snz [s] ; nsuper++ ; } } Super [nsuper] = n ; PRINT1 (("Fundamental supernodes: "ID" relaxed "ID"\n", nfsuper, nsuper)) ; /* Merged no longer needed ] */ /* ---------------------------------------------------------------------- */ /* find the mapping of relaxed nodes to supernodes */ /* ---------------------------------------------------------------------- */ /* use Wj as workspace for SuperMap { */ /* SuperMap [k] = s if column k is contained in supernode s */ for (s = 0 ; s < nsuper ; s++) { for (k = Super [s] ; k < Super [s+1] ; k++) { SuperMap [k] = s ; } } /* ---------------------------------------------------------------------- */ /* construct the relaxed supernodal etree */ /* ---------------------------------------------------------------------- */ for (s = 0 ; s < nsuper ; s++) { j = Super [s+1] - 1 ; /* last node in supernode s */ parent = Parent [j] ; /* parent of last node */ Sparent [s] = (parent == EMPTY) ? EMPTY : SuperMap [parent] ; PRINT1 (("new Sparent ["ID"] = "ID"\n", s, Sparent [s])) ; } /* ---------------------------------------------------------------------- */ /* determine the size of L->s and L->x */ /* ---------------------------------------------------------------------- */ ssize = 0 ; xsize = 0 ; xxsize = 0 ; for (s = 0 ; s < nsuper ; s++) { nscol = Super [s+1] - Super [s] ; nsrow = Snz [s] ; ASSERT (nscol > 0) ; ssize += nsrow ; if (for_cholesky) { xsize += nscol * nsrow ; /* also compute xsize in double to guard against Int overflow */ xxsize += ((double) nscol) * ((double) nsrow) ; } if (ssize < 0 || (for_cholesky && xxsize > Int_max)) { /* Int overflow, clear workspace and return. QR factorization will not use xxsize, so that error is ignored. For Cholesky factorization, however, memory of space xxsize will be allocated, so this is a failure. Both QR and Cholesky fail if ssize overflows. */ ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; FREE_WORKSPACE ; return (FALSE) ; } ASSERT (ssize > 0) ; ASSERT (IMPLIES (for_cholesky, xsize > 0)) ; } xsize = MAX (1, xsize) ; ssize = MAX (1, ssize) ; PRINT1 (("ix sizes: "ID" "ID" nsuper "ID"\n", ssize, xsize, nsuper)) ; /* ---------------------------------------------------------------------- */ /* allocate L (all except real part L->x) */ /* ---------------------------------------------------------------------- */ L->ssize = ssize ; L->xsize = xsize ; L->nsuper = nsuper ; CHOLMOD(change_factor) (CHOLMOD_PATTERN, TRUE, TRUE, TRUE, TRUE, L, Common); if (Common->status < CHOLMOD_OK) { /* out of memory; L is still a valid simplicial symbolic factor */ FREE_WORKSPACE ; return (FALSE) ; } DEBUG (CHOLMOD(dump_factor) (L, "L to symbolic super", Common)) ; ASSERT (L->is_ll && L->xtype == CHOLMOD_PATTERN && L->is_super) ; Lpi = L->pi ; Lpx = L->px ; Ls = L->s ; Ls [0] = 0 ; /* flag for cholmod_check_factor; supernodes are defined */ Lpx [0] = for_cholesky ? 0 : 123456 ; /* magic number for sparse QR */ Lsuper = L->super ; /* copy the list of relaxed supernodes into the final list in L */ for (s = 0 ; s <= nsuper ; s++) { Lsuper [s] = Super [s] ; } /* Head no longer needed as workspace for fundamental Super list ) */ Super = Lsuper ; /* Super is now the list of relaxed supernodes */ /* ---------------------------------------------------------------------- */ /* construct column pointers of relaxed supernodal pattern (L->pi) */ /* ---------------------------------------------------------------------- */ p = 0 ; for (s = 0 ; s < nsuper ; s++) { Lpi [s] = p ; p += Snz [s] ; PRINT1 (("Snz ["ID"] = "ID", Super ["ID"] = "ID"\n", s, Snz [s], s, Super[s])) ; } Lpi [nsuper] = p ; ASSERT ((Int) (L->ssize) == MAX (1,p)) ; /* ---------------------------------------------------------------------- */ /* construct pointers for supernodal values (L->px) */ /* ---------------------------------------------------------------------- */ if (for_cholesky) { /* L->px is not needed for QR factorization (it may lead to Int overflow, anyway, if xsize caused Int overflow above) */ p = 0 ; for (s = 0 ; s < nsuper ; s++) { nscol = Super [s+1] - Super [s] ; /* number of columns in s */ nsrow = Snz [s] ; /* # of rows, incl triangular part*/ Lpx [s] = p ; /* pointer to numerical part of s */ p += nscol * nsrow ; } Lpx [s] = p ; ASSERT ((Int) (L->xsize) == MAX (1,p)) ; } /* Snz no longer needed ] */ /* ---------------------------------------------------------------------- */ /* symbolic analysis to construct the relaxed supernodal pattern (L->s) */ /* ---------------------------------------------------------------------- */ Lpi2 = Wi ; /* copy Lpi into Lpi2, using Wi as workspace for Lpi2 [ */ for (s = 0 ; s < nsuper ; s++) { Lpi2 [s] = Lpi [s] ; } Asorted = A->sorted ; for (s = 0 ; s < nsuper ; s++) { /* sth supernode is in columns k1 to k2-1. * compute nonzero pattern of L (k1:k2-1,:). */ /* place rows k1 to k2-1 in leading column of supernode s */ k1 = Super [s] ; k2 = Super [s+1] ; PRINT1 (("=========>>> Supernode "ID" k1 "ID" k2-1 "ID"\n", s, k1, k2-1)) ; for (k = k1 ; k < k2 ; k++) { Ls [Lpi2 [s]++] = k ; } /* compute nonzero pattern each row k1 to k2-1 */ for (k = k1 ; k < k2 ; k++) { /* compute row k of L. In the symmetric case, the pattern of L(k,:) * is the set of nodes reachable in the supernodal etree from any * row i in the nonzero pattern of A(0:k,k). In the unsymmetric * case, the pattern of the kth column of A*A' is the set union * of all columns A(0:k,j) for each nonzero F(j,k). */ /* clear the Flag array and mark the current supernode */ /* mark = CHOLMOD(clear_flag) (Common) ; */ CHOLMOD_CLEAR_FLAG (Common) ; mark = Common->mark ; Flag [s] = mark ; ASSERT (s == SuperMap [k]) ; /* traverse the row subtree for each nonzero in A or AA' */ if (stype != 0) { subtree (k, k, Ap, Ai, Anz, SuperMap, Sparent, mark, Asorted, k1, Flag, Ls, Lpi2) ; } else { /* for each j nonzero in F (:,k) do */ p = Fp [k] ; pend = (packed) ? (Fp [k+1]) : (p + Fnz [k]) ; for ( ; p < pend ; p++) { subtree (Fj [p], k, Ap, Ai, Anz, SuperMap, Sparent, mark, Asorted, k1, Flag, Ls, Lpi2) ; } } } } #ifndef NDEBUG for (s = 0 ; s < nsuper ; s++) { PRINT1 (("Lpi2[s] "ID" Lpi[s+1] "ID"\n", Lpi2 [s], Lpi [s+1])) ; ASSERT (Lpi2 [s] == Lpi [s+1]) ; CHOLMOD(dump_super) (s, Super, Lpi, Ls, NULL, NULL, 0, Common) ; } #endif /* contents of Wi no longer needed for Lpi2 ] */ /* Sparent no longer needed ] */ /* ---------------------------------------------------------------------- */ /* determine the largest update matrix (L->maxcsize) */ /* ---------------------------------------------------------------------- */ /* maxcsize could be determined before L->s is allocated and defined, which * would mean that all memory requirements for both the symbolic and numeric * factorizations could be computed using O(nnz(A)+O(n)) space. However, it * would require a lot of extra work. The analysis phase, above, would need * to be duplicated, but with Ls not kept; instead, the algorithm would keep * track of the current s and slast for each supernode d, and update them * when a new row index appears in supernode d. An alternative would be to * do this computation only if the allocation of L->s failed, in which case * the following code would be skipped. * * The csize for a supernode is the size of its largest contribution to * a subsequent ancestor supernode. For example, suppose the rows of #'s * in the figure below correspond to the columns of a subsequent supernode, * and the dots are the entries in that ancestore. * * c * c c * c c c * x x x * x x x * # # # . * # # # . . * * * * . . * * * * . . * * * * . . * . . * * Then for this update, the csize is 3-by-2, or 6, because there are 3 * rows of *'s which is the number of rows in the update, and there are * 2 rows of #'s, which is the number columns in the update. The csize * of a supernode is the largest such contribution for any ancestor * supernode. maxcsize, for the whole matrix, has a rough upper bound of * the maximum size of any supernode. This bound is loose, because the * the contribution must be less than the size of the ancestor supernodal * that it's updating. maxcsize of a completely dense matrix, with one * supernode, is zero. * * maxesize is the column dimension for the workspace E needed for the * solve. E is of size nrhs-by-maxesize, where the nrhs is the number of * columns in the right-hand-side. The maxesize is the largest esize of * any supernode. The esize of a supernode is the number of row indices * it contains, excluding the column indices of the supernode itself. * For the following example, esize is 4: * * c * c c * c c c * x x x * x x x * x x x * x x x * * maxesize can be no bigger than n. */ maxcsize = 1 ; maxesize = 1 ; /* Do not need to guard csize against Int overflow since xsize is OK. */ if (for_cholesky) { /* this is not needed for QR factorization */ for (d = 0 ; d < nsuper ; d++) { nscol = Super [d+1] - Super [d] ; p = Lpi [d] + nscol ; plast = p ; pend = Lpi [d+1] ; esize = pend - p ; maxesize = MAX (maxesize, esize) ; slast = (p == pend) ? (EMPTY) : (SuperMap [Ls [p]]) ; for ( ; p <= pend ; p++) { s = (p == pend) ? (EMPTY) : (SuperMap [Ls [p]]) ; if (s != slast) { /* row i is the start of a new supernode */ ndrow1 = p - plast ; ndrow2 = pend - plast ; csize = ndrow2 * ndrow1 ; PRINT1 (("Supernode "ID" ancestor "ID" C: "ID"-by-"ID " csize "ID"\n", d, slast, ndrow1, ndrow2, csize)) ; maxcsize = MAX (maxcsize, csize) ; plast = p ; slast = s ; } } } PRINT1 (("max csize "ID"\n", maxcsize)) ; } /* Wj no longer needed for SuperMap } */ L->maxcsize = maxcsize ; L->maxesize = maxesize ; L->is_super = TRUE ; ASSERT (L->xtype == CHOLMOD_PATTERN && L->is_ll) ; /* ---------------------------------------------------------------------- */ /* supernodal symbolic factorization is complete */ /* ---------------------------------------------------------------------- */ FREE_WORKSPACE ; return (TRUE) ; } /* ========================================================================== */ /* === cholmod_super_symbolic =============================================== */ /* ========================================================================== */ /* Analyzes A, AA', or A(:,f)*A(:,f)' in preparation for a supernodal numeric * factorization. The user need not call this directly; cholmod_analyze is * a "simple" wrapper for this routine. * * This function does all the analysis for a supernodal Cholesky factorization. * * workspace: Flag (nrow), Head (nrow), Iwork (2*nrow), * and temporary space of size 3*nfsuper*sizeof(Int), where nfsuper <= n * is the number of fundamental supernodes. */ int CHOLMOD(super_symbolic) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to analyze */ cholmod_sparse *F, /* F = A' or A(:,f)' */ Int *Parent, /* elimination tree */ /* ---- in/out --- */ cholmod_factor *L, /* simplicial symbolic on input, * supernodal symbolic on output */ /* --------------- */ cholmod_common *Common ) { return (CHOLMOD(super_symbolic2) (TRUE, A, F, Parent, L, Common)) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Supernodal/t_cholmod_super_numeric.c0000644000076500000240000007774113524616144031701 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Supernodal/t_cholmod_super_numeric =================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Supernodal Module. Copyright (C) 2005-2012, Timothy A. Davis * The CHOLMOD/Supernodal Module is licensed under Version 2.0 of the GNU * General Public License. See gpl.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * http://www.suitesparse.com * -------------------------------------------------------------------------- */ /* Template routine for cholmod_super_numeric. All xtypes supported, except * that a zomplex A and F result in a complex L (there is no supernodal * zomplex L). */ /* ========================================================================== */ /* === complex arithmetic =================================================== */ /* ========================================================================== */ #include "cholmod_template.h" #ifdef USING_R #include #ifdef HAVE_F77_UNDERSCORE # define F77_CALL(x) x ## _ #else # define F77_CALL(x) x #endif #define F77_NAME(x) F77_CALL(x) #define F77_SUB(x) F77_CALL(x) #define F77_COM(x) F77_CALL(x) #define F77_COMDECL(x) F77_CALL(x) void F77_NAME(dsyrk)(const char *uplo, const char *trans, const int *n, const int *k, const double *alpha, const double *a, const int *lda, const double *beta, double *c, const int *ldc); void F77_NAME(dpotrf)(const char* uplo, const int* n, double* a, const int* lda, int* info); void F77_NAME(dtrsm)(const char *side, const char *uplo, const char *transa, const char *diag, const int *m, const int *n, const double *alpha, const double *a, const int *lda, double *b, const int *ldb); void F77_NAME(dtrsv)(const char *uplo, const char *trans, const char *diag, const int *n, const double *a, const int *lda, double *x, const int *incx); #endif #undef L_ENTRY #undef L_CLEAR #undef L_ASSIGN #undef L_MULTADD #undef L_ASSEMBLE #undef L_ASSEMBLESUB #ifdef REAL /* -------------------------------------------------------------------------- */ /* A, F, and L are all real */ /* -------------------------------------------------------------------------- */ #define L_ENTRY 1 #define L_CLEAR(Lx,p) Lx [p] = 0 #define L_ASSIGN(Lx,q, Ax,Az,p) Lx [q] = Ax [p] #define L_MULTADD(Lx,q, Ax,Az,p, f) Lx [q] += Ax [p] * f [0] #define L_ASSEMBLE(Lx,q,b) Lx [q] += b [0] #define L_ASSEMBLESUB(Lx,q,C,p) Lx [q] -= C [p] #else /* -------------------------------------------------------------------------- */ /* A and F are complex or zomplex, L and C are complex */ /* -------------------------------------------------------------------------- */ #define L_ENTRY 2 #define L_CLEAR(Lx,p) Lx [2*(p)] = 0 ; Lx [2*(p)+1] = 0 #define L_ASSEMBLE(Lx,q,b) Lx [2*(q)] += b [0] ; #define L_ASSEMBLESUB(Lx,q,C,p) \ Lx [2*(q) ] -= C [2*(p) ] ; \ Lx [2*(q)+1] -= C [2*(p)+1] ; #ifdef COMPLEX /* -------------------------------------------------------------------------- */ /* A, F, L, and C are all complex */ /* -------------------------------------------------------------------------- */ #define L_ASSIGN(Lx,q, Ax,Az,p) \ Lx [2*(q) ] = Ax [2*(p) ] ; \ Lx [2*(q)+1] = Ax [2*(p)+1] #define L_MULTADD(Lx,q, Ax,Az,p, f) \ Lx [2*(q) ] += Ax [2*(p) ] * f [0] - Ax [2*(p)+1] * f [1] ; \ Lx [2*(q)+1] += Ax [2*(p)+1] * f [0] + Ax [2*(p) ] * f [1] #else /* -------------------------------------------------------------------------- */ /* A and F are zomplex, L and C is complex */ /* -------------------------------------------------------------------------- */ #define L_ASSIGN(Lx,q, Ax,Az,p) \ Lx [2*(q) ] = Ax [p] ; \ Lx [2*(q)+1] = Az [p] ; #define L_MULTADD(Lx,q, Ax,Az,p, f) \ Lx [2*(q) ] += Ax [p] * f [0] - Az [p] * f [1] ; \ Lx [2*(q)+1] += Az [p] * f [0] + Ax [p] * f [1] #endif #endif /* ========================================================================== */ /* === t_cholmod_super_numeric ============================================== */ /* ========================================================================== */ /* This function returns FALSE only if integer overflow occurs in the BLAS. * It returns TRUE otherwise whether or not the matrix is positive definite. */ static int TEMPLATE (cholmod_super_numeric) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to factorize */ cholmod_sparse *F, /* F = A' or A(:,f)' */ double beta [2], /* beta*I is added to diagonal of matrix to factorize */ /* ---- in/out --- */ cholmod_factor *L, /* factorization */ /* -- workspace -- */ cholmod_dense *Cwork, /* size (L->maxcsize)-by-1 */ /* --------------- */ cholmod_common *Common ) { double one [2], zero [2], fjk [2], tstart ; double *Lx, *Ax, *Fx, *Az, *Fz, *C ; Int *Super, *Head, *Ls, *Lpi, *Lpx, *Map, *SuperMap, *RelativeMap, *Next, *Lpos, *Fp, *Fi, *Fnz, *Ap, *Ai, *Anz, *Iwork, *Next_save, *Lpos_save ; Int nsuper, n, j, i, k, s, p, pend, k1, k2, nscol, psi, psx, psend, nsrow, pj, d, kd1, kd2, info, ndcol, ndrow, pdi, pdx, pdend, pdi1, pdi2, pdx1, ndrow1, ndrow2, px, dancestor, sparent, dnext, nsrow2, ndrow3, pk, pf, pfend, stype, Apacked, Fpacked, q, imap, repeat_supernode, nscol2, ss, nscol_new = 0 ; /* If integer overflow occurs in the BLAS, Common->status is set to * CHOLMOD_TOO_LARGE, and the contents of Lx are undefined. */ Common->blas_ok = TRUE ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ nsuper = L->nsuper ; n = L->n ; C = Cwork->x ; /* workspace of size L->maxcsize */ one [0] = 1.0 ; /* ALPHA for *syrk, *herk, *gemm, and *trsm */ one [1] = 0. ; zero [0] = 0. ; /* BETA for *syrk, *herk, and *gemm */ zero [1] = 0. ; Iwork = Common->Iwork ; SuperMap = Iwork ; /* size n (i/i/l) */ RelativeMap = Iwork + n ; /* size n (i/i/l) */ Next = Iwork + 2*((size_t) n) ; /* size nsuper*/ Lpos = Iwork + 2*((size_t) n) + nsuper ; /* size nsuper*/ Next_save = Iwork + 2*((size_t) n) + 2*((size_t) nsuper) ;/* size nsuper*/ Lpos_save = Iwork + 2*((size_t) n) + 3*((size_t) nsuper) ;/* size nsuper*/ Map = Common->Flag ; /* size n, use Flag as workspace for Map array */ Head = Common->Head ; /* size n+1, only Head [0..nsuper-1] used */ Ls = L->s ; Lpi = L->pi ; Lpx = L->px ; Super = L->super ; Lx = L->x ; #ifdef GPU_BLAS TEMPLATE (CHOLMOD (gpu_init)) (C, L->maxcsize, Common) ; #endif #ifndef NTIMER /* clear GPU / CPU statistics */ Common->CHOLMOD_CPU_GEMM_CALLS = 0 ; Common->CHOLMOD_CPU_SYRK_CALLS = 0 ; Common->CHOLMOD_CPU_TRSM_CALLS = 0 ; Common->CHOLMOD_CPU_POTRF_CALLS = 0 ; Common->CHOLMOD_GPU_GEMM_CALLS = 0 ; Common->CHOLMOD_GPU_SYRK_CALLS = 0 ; Common->CHOLMOD_GPU_TRSM_CALLS = 0 ; Common->CHOLMOD_GPU_POTRF_CALLS = 0 ; Common->CHOLMOD_CPU_GEMM_TIME = 0 ; Common->CHOLMOD_CPU_SYRK_TIME = 0 ; Common->CHOLMOD_CPU_TRSM_TIME = 0 ; Common->CHOLMOD_CPU_POTRF_TIME = 0 ; Common->CHOLMOD_GPU_GEMM_TIME = 0 ; Common->CHOLMOD_GPU_SYRK_TIME = 0 ; Common->CHOLMOD_GPU_TRSM_TIME = 0 ; Common->CHOLMOD_GPU_POTRF_TIME = 0 ; Common->CHOLMOD_ASSEMBLE_TIME = 0 ; Common->CHOLMOD_ASSEMBLE_TIME2 = 0 ; #endif stype = A->stype ; if (stype != 0) { /* F not accessed */ Fp = NULL ; Fi = NULL ; Fx = NULL ; Fz = NULL ; Fnz = NULL ; Fpacked = TRUE ; } else { Fp = F->p ; Fi = F->i ; Fx = F->x ; Fz = F->z ; Fnz = F->nz ; Fpacked = F->packed ; } Ap = A->p ; Ai = A->i ; Ax = A->x ; Az = A->z ; Anz = A->nz ; Apacked = A->packed ; /* clear the Map so that changes in the pattern of A can be detected */ for (i = 0 ; i < n ; i++) { Map [i] = EMPTY ; } /* If the matrix is not positive definite, the supernode s containing the * first zero or negative diagonal entry of L is repeated (but factorized * only up to just before the problematic diagonal entry). The purpose is * to provide MATLAB with [R,p]=chol(A); columns 1 to p-1 of L=R' are * required, where L(p,p) is the problematic diagonal entry. The * repeat_supernode flag tells us whether this is the repeated supernode. * Once supernode s is repeated, the factorization is terminated. */ repeat_supernode = FALSE ; /* ---------------------------------------------------------------------- */ /* supernodal numerical factorization */ /* ---------------------------------------------------------------------- */ for (s = 0 ; s < nsuper ; s++) { /* ------------------------------------------------------------------ */ /* get the size of supernode s */ /* ------------------------------------------------------------------ */ k1 = Super [s] ; /* s contains columns k1 to k2-1 of L */ k2 = Super [s+1] ; nscol = k2 - k1 ; /* # of columns in all of s */ psi = Lpi [s] ; /* pointer to first row of s in Ls */ psx = Lpx [s] ; /* pointer to first row of s in Lx */ psend = Lpi [s+1] ; /* pointer just past last row of s in Ls */ nsrow = psend - psi ; /* # of rows in all of s */ PRINT1 (("====================================================\n" "S "ID" k1 "ID" k2 "ID" nsrow "ID" nscol "ID" psi "ID" psend " ""ID" psx "ID"\n", s, k1, k2, nsrow, nscol, psi, psend, psx)) ; /* ------------------------------------------------------------------ */ /* zero the supernode s */ /* ------------------------------------------------------------------ */ ASSERT ((size_t) (psx + nsrow*nscol) <= L->xsize) ; pend = psx + nsrow * nscol ; /* s is nsrow-by-nscol */ for (p = psx ; p < pend ; p++) { /* Lx [p] = 0 ; */ L_CLEAR (Lx,p) ; } /* ------------------------------------------------------------------ */ /* construct the scattered Map for supernode s */ /* ------------------------------------------------------------------ */ /* If row i is the kth row in s, then Map [i] = k. Similarly, if * column j is the kth column in s, then Map [j] = k. */ for (k = 0 ; k < nsrow ; k++) { PRINT1 ((" "ID" map "ID"\n", Ls [psi+k], k)) ; Map [Ls [psi + k]] = k ; } /* ------------------------------------------------------------------ */ /* copy matrix into supernode s (lower triangular part only) */ /* ------------------------------------------------------------------ */ pk = psx ; for (k = k1 ; k < k2 ; k++) { if (stype != 0) { /* copy the kth column of A into the supernode */ p = Ap [k] ; pend = (Apacked) ? (Ap [k+1]) : (p + Anz [k]) ; for ( ; p < pend ; p++) { /* row i of L is located in row Map [i] of s */ i = Ai [p] ; if (i >= k) { /* This test is here simply to avoid a segfault. If * the test is false, the numeric factorization of A * is undefined. It does not detect all invalid * entries, only some of them (when debugging is * enabled, and Map is cleared after each step, then * all entries not in the pattern of L are detected). */ imap = Map [i] ; if (imap >= 0 && imap < nsrow) { /* Lx [Map [i] + pk] = Ax [p] ; */ L_ASSIGN (Lx,(imap+pk), Ax,Az,p) ; } } } } else { /* copy the kth column of A*F into the supernode */ pf = Fp [k] ; pfend = (Fpacked) ? (Fp [k+1]) : (p + Fnz [k]) ; for ( ; pf < pfend ; pf++) { j = Fi [pf] ; /* fjk = Fx [pf] ; */ L_ASSIGN (fjk,0, Fx,Fz,pf) ; p = Ap [j] ; pend = (Apacked) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { i = Ai [p] ; if (i >= k) { /* See the discussion of imap above. */ imap = Map [i] ; if (imap >= 0 && imap < nsrow) { /* Lx [Map [i] + pk] += Ax [p] * fjk ; */ L_MULTADD (Lx,(imap+pk), Ax,Az,p, fjk) ; } } } } } pk += nsrow ; /* advance to the next column of the supernode */ } /* add beta to the diagonal of the supernode, if nonzero */ if (beta [0] != 0.0) { /* note that only the real part of beta is used */ pk = psx ; for (k = k1 ; k < k2 ; k++) { /* Lx [pk] += beta [0] ; */ L_ASSEMBLE (Lx,pk, beta) ; pk += nsrow + 1 ; /* advance to the next diagonal entry */ } } PRINT1 (("Supernode with just A: repeat: "ID"\n", repeat_supernode)) ; DEBUG (CHOLMOD(dump_super) (s, Super, Lpi, Ls, Lpx, Lx, L_ENTRY, Common)) ; PRINT1 (("\n\n")) ; /* ------------------------------------------------------------------ */ /* save/restore the list of supernodes */ /* ------------------------------------------------------------------ */ if (!repeat_supernode) { /* Save the list of pending descendants in case s is not positive * definite. Also save Lpos for each descendant d, so that we can * find which part of d is used to update s. */ for (d = Head [s] ; d != EMPTY ; d = Next [d]) { Lpos_save [d] = Lpos [d] ; Next_save [d] = Next [d] ; } } else { /* s is not positive definite, and is being repeated. Restore * the list of supernodes. This can be done with pointer assignment * because all 4 arrays are held within Common->Iwork. */ Lpos = Lpos_save ; Next = Next_save ; } /* ------------------------------------------------------------------ */ /* update supernode s with each pending descendant d */ /* ------------------------------------------------------------------ */ #ifndef NDEBUG for (d = Head [s] ; d != EMPTY ; d = Next [d]) { PRINT1 (("\nWill update "ID" with Child: "ID"\n", s, d)) ; DEBUG (CHOLMOD(dump_super) (d, Super, Lpi, Ls, Lpx, Lx, L_ENTRY, Common)) ; } PRINT1 (("\nNow factorizing supernode "ID":\n", s)) ; #endif for (d = Head [s] ; d != EMPTY ; d = dnext) { /* -------------------------------------------------------------- */ /* get the size of supernode d */ /* -------------------------------------------------------------- */ kd1 = Super [d] ; /* d contains cols kd1 to kd2-1 of L */ kd2 = Super [d+1] ; ndcol = kd2 - kd1 ; /* # of columns in all of d */ pdi = Lpi [d] ; /* pointer to first row of d in Ls */ pdx = Lpx [d] ; /* pointer to first row of d in Lx */ pdend = Lpi [d+1] ; /* pointer just past last row of d in Ls */ ndrow = pdend - pdi ; /* # rows in all of d */ PRINT1 (("Child: ")) ; DEBUG (CHOLMOD(dump_super) (d, Super, Lpi, Ls, Lpx, Lx, L_ENTRY, Common)) ; /* -------------------------------------------------------------- */ /* find the range of rows of d that affect rows k1 to k2-1 of s */ /* -------------------------------------------------------------- */ p = Lpos [d] ; /* offset of 1st row of d affecting s */ pdi1 = pdi + p ; /* ptr to 1st row of d affecting s in Ls */ pdx1 = pdx + p ; /* ptr to 1st row of d affecting s in Lx */ /* there must be at least one row remaining in d to update s */ ASSERT (pdi1 < pdend) ; PRINT1 (("Lpos[d] "ID" pdi1 "ID" Ls[pdi1] "ID"\n", Lpos[d], pdi1, Ls [pdi1])) ; ASSERT (Ls [pdi1] >= k1 && Ls [pdi1] < k2) ; for (pdi2 = pdi1 ; pdi2 < pdend && Ls [pdi2] < k2 ; pdi2++) ; ndrow1 = pdi2 - pdi1 ; /* # rows in first part of d */ ndrow2 = pdend - pdi1 ; /* # rows in remaining d */ /* rows Ls [pdi1 ... pdi2-1] are in the range k1 to k2-1. Since d * affects s, this set cannot be empty. */ ASSERT (pdi1 < pdi2 && pdi2 <= pdend) ; PRINT1 (("ndrow1 "ID" ndrow2 "ID"\n", ndrow1, ndrow2)) ; DEBUG (for (p = pdi1 ; p < pdi2 ; p++) PRINT1 (("Ls["ID"] "ID"\n", p, Ls[p]))) ; /* -------------------------------------------------------------- */ /* construct the update matrix C for this supernode d */ /* -------------------------------------------------------------- */ /* C = L (k1:n-1, kd1:kd2-1) * L (k1:k2-1, kd1:kd2-1)', except * that k1:n-1 refers to all of the rows in L, but many of the * rows are all zero. Supernode d holds columns kd1 to kd2-1 of L. * Nonzero rows in the range k1:k2-1 are in the list * Ls [pdi1 ... pdi2-1], of size ndrow1. Nonzero rows in the range * k2:n-1 are in the list Ls [pdi2 ... pdend], of size ndrow2. Let * L1 = L (Ls [pdi1 ... pdi2-1], kd1:kd2-1), and let * L2 = L (Ls [pdi2 ... pdend], kd1:kd2-1). C is ndrow2-by-ndrow1. * Let C1 be the first ndrow1 rows of C and let C2 be the last * ndrow2-ndrow1 rows of C. Only the lower triangular part of C1 * needs to be computed since C1 is symmetric. */ /* maxcsize is the largest size of C for all pairs (d,s) */ ASSERT (ndrow2 * ndrow1 <= ((Int) L->maxcsize)) ; /* compute leading ndrow1-by-ndrow1 lower triangular block of C, * C1 = L1*L1' */ ndrow3 = ndrow2 - ndrow1 ; /* number of rows of C2 */ ASSERT (ndrow3 >= 0) ; #ifdef GPU_BLAS if (!TEMPLATE (CHOLMOD (gpu_updateC)) (ndrow1, ndrow2, ndrow, ndcol, pdx1, Lx, C, Common)) #endif { #ifndef NTIMER Common->CHOLMOD_CPU_SYRK_CALLS++ ; tstart = SuiteSparse_time () ; #endif #ifdef REAL BLAS_dsyrk ("L", "N", ndrow1, ndcol, /* N, K: L1 is ndrow1-by-ndcol*/ one, /* ALPHA: 1 */ Lx + L_ENTRY*pdx1, ndrow, /* A, LDA: L1, ndrow */ zero, /* BETA: 0 */ C, ndrow2) ; /* C, LDC: C1 */ #else BLAS_zherk ("L", "N", ndrow1, ndcol, /* N, K: L1 is ndrow1-by-ndcol*/ one, /* ALPHA: 1 */ Lx + L_ENTRY*pdx1, ndrow, /* A, LDA: L1, ndrow */ zero, /* BETA: 0 */ C, ndrow2) ; /* C, LDC: C1 */ #endif #ifndef NTIMER Common->CHOLMOD_CPU_SYRK_TIME += SuiteSparse_time () - tstart ; #endif /* compute remaining (ndrow2-ndrow1)-by-ndrow1 block of C, * C2 = L2*L1' */ if (ndrow3 > 0) { #ifndef NTIMER Common->CHOLMOD_CPU_GEMM_CALLS++ ; tstart = SuiteSparse_time () ; #endif #ifdef REAL BLAS_dgemm ("N", "C", ndrow3, ndrow1, ndcol, /* M, N, K */ one, /* ALPHA: 1 */ Lx + L_ENTRY*(pdx1 + ndrow1), /* A, LDA: L2, ndrow */ ndrow, Lx + L_ENTRY*pdx1, /* B, LDB: L1, ndrow */ ndrow, zero, /* BETA: 0 */ C + L_ENTRY*ndrow1, /* C, LDC: C2 */ ndrow2) ; #else BLAS_zgemm ("N", "C", ndrow3, ndrow1, ndcol, /* M, N, K */ one, /* ALPHA: 1 */ Lx + L_ENTRY*(pdx1 + ndrow1),/* A, LDA: L2, ndrow */ ndrow, Lx + L_ENTRY*pdx1, /* B, LDB: L1, ndrow */ ndrow, zero, /* BETA: 0 */ C + L_ENTRY*ndrow1, /* C, LDC: C2 */ ndrow2) ; #endif #ifndef NTIMER Common->CHOLMOD_CPU_GEMM_TIME += SuiteSparse_time () - tstart ; #endif } } DEBUG (CHOLMOD(dump_real) ("C", C, ndrow2, ndrow1, TRUE, L_ENTRY, Common)) ; /* -------------------------------------------------------------- */ /* construct relative map to assemble d into s */ /* -------------------------------------------------------------- */ for (i = 0 ; i < ndrow2 ; i++) { RelativeMap [i] = Map [Ls [pdi1 + i]] ; ASSERT (RelativeMap [i] >= 0 && RelativeMap [i] < nsrow) ; } /* -------------------------------------------------------------- */ /* assemble C into supernode s using the relative map */ /* -------------------------------------------------------------- */ #ifdef GPU_BLAS TEMPLATE (CHOLMOD (gpu_syncSyrk)) (Common) ; if (ndrow3 <= 0) { #endif /* non-GPU version, or GPU version when ndrow3 is zero */ pj = 0 ; for (j = 0 ; j < ndrow1 ; j++) /* cols k1:k2-1 */ { ASSERT (RelativeMap [j] == Map [Ls [pdi1 + j]]) ; ASSERT (RelativeMap [j] >= 0 && RelativeMap [j] < nscol) ; px = psx + RelativeMap [j] * nsrow ; for (i = j ; i < ndrow2 ; i++) /* rows k1:n-1 */ { ASSERT (RelativeMap [i] == Map [Ls [pdi1 + i]]) ; ASSERT (RelativeMap [i] >= j && RelativeMap[i] < nsrow); /* Lx [px + RelativeMap [i]] -= C [i + pj] ; */ q = px + RelativeMap [i] ; L_ASSEMBLESUB (Lx,q, C, i+pj) ; } pj += ndrow2 ; } #ifdef GPU_BLAS } else { /* GPU version when ndrow3 > zero, splits into two parts */ #ifndef NTIMER tstart = SuiteSparse_time () ; #endif pj = 0 ; for (j = 0 ; j < ndrow1 ; j++) /* cols k1:k2-1 */ { ASSERT (RelativeMap [j] == Map [Ls [pdi1 + j]]) ; ASSERT (RelativeMap [j] >= 0 && RelativeMap [j] < nscol) ; px = psx + RelativeMap [j] * nsrow ; for (i = j ; i < ndrow1 ; i++) /* rows k1:k2-1 */ { ASSERT (RelativeMap [i] == Map [Ls [pdi1 + i]]) ; ASSERT (RelativeMap [i] >= j && RelativeMap[i] < nsrow); /* Lx [px + RelativeMap [i]] -= C [i + pj] ; */ q = px + RelativeMap [i] ; L_ASSEMBLESUB (Lx,q, C, i+pj) ; } pj += ndrow2 ; } #ifndef NTIMER Common->CHOLMOD_ASSEMBLE_TIME2 += SuiteSparse_time () - tstart ; #endif /* wait for dgemm to finish */ TEMPLATE (CHOLMOD (gpu_syncGemm)) (Common) ; pj = 0 ; for (j = 0 ; j < ndrow1 ; j++) /* cols k1:k2-1 */ { ASSERT (RelativeMap [j] == Map [Ls [pdi1 + j]]) ; ASSERT (RelativeMap [j] >= 0 && RelativeMap [j] < nscol) ; px = psx + RelativeMap [j] * nsrow ; for (i = ndrow1 ; i < ndrow2 ; i++) /* rows k2:n-1 */ { ASSERT (RelativeMap [i] == Map [Ls [pdi1 + i]]) ; ASSERT (RelativeMap [i] >= j && RelativeMap[i] < nsrow); /* Lx [px + RelativeMap [i]] -= C [i + pj] ; */ q = px + RelativeMap [i] ; L_ASSEMBLESUB (Lx,q, C, i+pj) ; } pj += ndrow2 ; } #ifndef NTIMER Common->CHOLMOD_ASSEMBLE_TIME += SuiteSparse_time () - tstart ; #endif } #endif /* -------------------------------------------------------------- */ /* prepare this supernode d for its next ancestor */ /* -------------------------------------------------------------- */ dnext = Next [d] ; if (!repeat_supernode) { /* If node s is being repeated, Head [dancestor] has already * been cleared (set to EMPTY). It must remain EMPTY. The * dancestor will not be factorized since the factorization * terminates at node s. */ Lpos [d] = pdi2 - pdi ; if (Lpos [d] < ndrow) { dancestor = SuperMap [Ls [pdi2]] ; ASSERT (dancestor > s && dancestor < nsuper) ; /* place d in the link list of its next ancestor */ Next [d] = Head [dancestor] ; Head [dancestor] = d ; } } } PRINT1 (("\nSupernode with contributions A: repeat: "ID"\n", repeat_supernode)) ; DEBUG (CHOLMOD(dump_super) (s, Super, Lpi, Ls, Lpx, Lx, L_ENTRY, Common)) ; PRINT1 (("\n\n")) ; /* ------------------------------------------------------------------ */ /* factorize diagonal block of supernode s in LL' */ /* ------------------------------------------------------------------ */ /* The current supernode s is ready to factorize. It has been updated * by all descendant supernodes. Let S = the current supernode, which * holds rows k1:n-1 and columns k1:k2-1 of the updated matrix. It * splits into two parts: the square diagonal block S1, and the * rectangular part S2. Here, S1 is factorized into L1*L1' and * overwritten by L1. * * If supernode s is being repeated, only factorize it up to but not * including the column containing the problematic entry. */ nscol2 = (repeat_supernode) ? (nscol_new) : (nscol) ; #ifdef GPU_BLAS if (!TEMPLATE (CHOLMOD (gpu_lower_potrf)) (nscol2, nsrow, psx, Lx, &info, Common)) #endif { #ifndef NTIMER Common->CHOLMOD_CPU_POTRF_CALLS++ ; tstart = SuiteSparse_time () ; #endif #ifdef REAL LAPACK_dpotrf ("L", nscol2, /* N: nscol2 */ Lx + L_ENTRY*psx, nsrow, /* A, LDA: S1, nsrow */ info) ; /* INFO */ #else LAPACK_zpotrf ("L", nscol2, /* N: nscol2 */ Lx + L_ENTRY*psx, nsrow, /* A, LDA: S1, nsrow */ info) ; /* INFO */ #endif #ifndef NTIMER Common->CHOLMOD_CPU_POTRF_TIME += SuiteSparse_time ()- tstart ; #endif } /* ------------------------------------------------------------------ */ /* check if the matrix is not positive definite */ /* ------------------------------------------------------------------ */ if (repeat_supernode) { /* the leading part has been refactorized; it must have succeeded */ info = 0 ; /* zero out the rest of this supernode */ p = psx + nsrow * nscol_new ; pend = psx + nsrow * nscol ; /* s is nsrow-by-nscol */ for ( ; p < pend ; p++) { /* Lx [p] = 0 ; */ L_CLEAR (Lx,p) ; } } /* info is set to one in LAPACK_*potrf if blas_ok is FALSE. It is * set to zero in dpotrf/zpotrf if the factorization was successful. */ if (CHECK_BLAS_INT && !Common->blas_ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large for the BLAS") ; } if (info != 0) { /* Matrix is not positive definite. dpotrf/zpotrf do NOT report an * error if the diagonal of L has NaN's, only if it has a zero. */ if (Common->status == CHOLMOD_OK) { ERROR (CHOLMOD_NOT_POSDEF, "matrix not positive definite") ; } /* L->minor is the column of L that contains a zero or negative * diagonal term. */ L->minor = k1 + info - 1 ; /* clear the link lists of all subsequent supernodes */ for (ss = s+1 ; ss < nsuper ; ss++) { Head [ss] = EMPTY ; } /* zero this supernode, and all remaining supernodes */ pend = L->xsize ; for (p = psx ; p < pend ; p++) { /* Lx [p] = 0. ; */ L_CLEAR (Lx,p) ; } /* If L is indefinite, it still contains useful information. * Supernodes 0 to s-1 are valid, similar to MATLAB [R,p]=chol(A), * where the 1-based p is identical to the 0-based L->minor. Since * L->minor is in the current supernode s, it and any columns to the * left of it in supernode s are also all zero. This differs from * [R,p]=chol(A), which contains nonzero rows 1 to p-1. Fix this * by setting repeat_supernode to TRUE, and repeating supernode s. * * If Common->quick_return_if_not_posdef is true, then the entire * supernode s is not factorized; it is left as all zero. */ if (info == 1 || Common->quick_return_if_not_posdef) { /* If the first column of supernode s contains a zero or * negative diagonal entry, then it is already properly set to * zero. Also, info will be 1 if integer overflow occured in * the BLAS. */ Head [s] = EMPTY ; #ifdef GPU_BLAS TEMPLATE (CHOLMOD (gpu_end)) (Common) ; #endif return (Common->status >= CHOLMOD_OK) ; } else { /* Repeat supernode s, but only factorize it up to but not * including the column containing the problematic diagonal * entry. */ repeat_supernode = TRUE ; s-- ; nscol_new = info - 1 ; continue ; } } /* ------------------------------------------------------------------ */ /* compute the subdiagonal block and prepare supernode for its parent */ /* ------------------------------------------------------------------ */ nsrow2 = nsrow - nscol2 ; if (nsrow2 > 0) { /* The current supernode is columns k1 to k2-1 of L. Let L1 be the * diagonal block (factorized by dpotrf/zpotrf above; rows/cols * k1:k2-1), and L2 be rows k2:n-1 and columns k1:k2-1 of L. The * triangular system to solve is L2*L1' = S2, where S2 is * overwritten with L2. More precisely, L2 = S2 / L1' in MATLAB * notation. */ #ifdef GPU_BLAS if (!TEMPLATE (CHOLMOD (gpu_triangular_solve)) (nsrow2, nscol2, nsrow, psx, Lx, Common)) #endif { #ifndef NTIMER Common->CHOLMOD_CPU_TRSM_CALLS++ ; tstart = SuiteSparse_time () ; #endif #ifdef REAL BLAS_dtrsm ("R", "L", "C", "N", nsrow2, nscol2, /* M, N */ one, /* ALPHA: 1 */ Lx + L_ENTRY*psx, nsrow, /* A, LDA: L1, nsrow */ Lx + L_ENTRY*(psx + nscol2), /* B, LDB, L2, nsrow */ nsrow) ; #else BLAS_ztrsm ("R", "L", "C", "N", nsrow2, nscol2, /* M, N */ one, /* ALPHA: 1 */ Lx + L_ENTRY*psx, nsrow, /* A, LDA: L1, nsrow */ Lx + L_ENTRY*(psx + nscol2), /* B, LDB, L2, nsrow */ nsrow) ; #endif #ifndef NTIMER Common->CHOLMOD_CPU_TRSM_TIME += SuiteSparse_time () - tstart ; #endif } if (CHECK_BLAS_INT && !Common->blas_ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large for the BLAS") ; } if (!repeat_supernode) { /* Lpos [s] is offset of first row of s affecting its parent */ Lpos [s] = nscol ; sparent = SuperMap [Ls [psi + nscol]] ; ASSERT (sparent != EMPTY) ; ASSERT (Ls [psi + nscol] >= Super [sparent]) ; ASSERT (Ls [psi + nscol] < Super [sparent+1]) ; ASSERT (SuperMap [Ls [psi + nscol]] == sparent) ; ASSERT (sparent > s && sparent < nsuper) ; /* place s in link list of its parent */ Next [s] = Head [sparent] ; Head [sparent] = s ; } } Head [s] = EMPTY ; /* link list for supernode s no longer needed */ /* clear the Map (debugging only, to detect changes in pattern of A) */ DEBUG (for (k = 0 ; k < nsrow ; k++) Map [Ls [psi + k]] = EMPTY) ; DEBUG (CHOLMOD(dump_super) (s, Super, Lpi, Ls, Lpx, Lx, L_ENTRY, Common)) ; if (repeat_supernode) { /* matrix is not positive definite; finished clean-up for supernode * containing negative diagonal */ #ifdef GPU_BLAS TEMPLATE (CHOLMOD (gpu_end)) (Common) ; #endif return (Common->status >= CHOLMOD_OK) ; } } /* success; matrix is positive definite */ L->minor = n ; #ifdef GPU_BLAS TEMPLATE (CHOLMOD (gpu_end)) (Common) ; #endif return (Common->status >= CHOLMOD_OK) ; } #undef PATTERN #undef REAL #undef COMPLEX #undef ZOMPLEX python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Supernodal/cholmod_super_numeric.c0000644000076500000240000002561113524616144031343 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Supernodal/cholmod_super_numeric ===================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Supernodal Module. Copyright (C) 2005-2006, Timothy A. Davis * The CHOLMOD/Supernodal Module is licensed under Version 2.0 of the GNU * General Public License. See gpl.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * http://www.suitesparse.com * -------------------------------------------------------------------------- */ /* Computes the Cholesky factorization of A+beta*I or A*F+beta*I. Only the * the lower triangular part of A+beta*I or A*F+beta*I is accessed. The * matrices A and F must already be permuted according to the fill-reduction * permutation L->Perm. cholmod_factorize is an "easy" wrapper for this code * which applies that permutation. beta is real. * * Symmetric case: A is a symmetric (lower) matrix. F is not accessed. * With a fill-reducing permutation, A(p,p) should be passed instead, where is * p is L->Perm. * * Unsymmetric case: A is unsymmetric, and F must be present. Normally, F=A'. * With a fill-reducing permutation, A(p,f) and A(p,f)' should be passed as A * and F, respectively, where f is a list of the subset of the columns of A. * * The input factorization L must be supernodal (L->is_super is TRUE). It can * either be symbolic or numeric. In the first case, L has been analyzed by * cholmod_analyze or cholmod_super_symbolic, but the matrix has not yet been * numerically factorized. The numerical values are allocated here and the * factorization is computed. In the second case, a prior matrix has been * analyzed and numerically factorized, and a new matrix is being factorized. * The numerical values of L are replaced with the new numerical factorization. * * L->is_ll is ignored, and set to TRUE. This routine always computes an LL' * factorization. Supernodal LDL' factorization is not (yet) supported. * FUTURE WORK: perform a supernodal LDL' factorization if L->is_ll is FALSE. * * Uses BLAS routines dsyrk, dgemm, dtrsm, and the LAPACK routine dpotrf. * The supernodal solver uses BLAS routines dtrsv, dgemv, dtrsm, and dgemm. * * If the matrix is not positive definite the routine returns TRUE, but sets * Common->status to CHOLMOD_NOT_POSDEF and L->minor is set to the column at * which the failure occurred. The supernode containing the non-positive * diagonal entry is set to zero (this includes columns to the left of L->minor * in the same supernode), as are all subsequent supernodes. * * workspace: Flag (nrow), Head (nrow+1), Iwork (2*nrow + 4*nsuper). * Allocates temporary space of size L->maxcsize * sizeof(double) * (twice that for the complex/zomplex case). * * If L is supernodal symbolic on input, it is converted to a supernodal numeric * factor on output, with an xtype of real if A is real, or complex if A is * complex or zomplex. If L is supernodal numeric on input, its xtype must * match A (except that L can be complex and A zomplex). The xtype of A and F * must match. */ #ifndef NSUPERNODAL #include "cholmod_internal.h" #include "cholmod_supernodal.h" #include "igraph_blas_internal.h" #include "igraph_lapack_internal.h" /* ========================================================================== */ /* === TEMPLATE codes for GPU and regular numeric factorization ============= */ /* ========================================================================== */ #ifdef GPU_BLAS #define REAL #include "t_cholmod_gpu.c" #define COMPLEX #include "t_cholmod_gpu.c" #define ZOMPLEX #include "t_cholmod_gpu.c" #endif #define REAL #include "t_cholmod_super_numeric.c" /* #define COMPLEX */ /* #include "t_cholmod_super_numeric.c" */ /* #define ZOMPLEX */ /* #include "t_cholmod_super_numeric.c" */ /* ========================================================================== */ /* === cholmod_super_numeric ================================================ */ /* ========================================================================== */ /* Returns TRUE if successful, or if the matrix is not positive definite. * Returns FALSE if out of memory, inputs are invalid, or other fatal error * occurs. */ int CHOLMOD(super_numeric) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to factorize */ cholmod_sparse *F, /* F = A' or A(:,f)' */ double beta [2], /* beta*I is added to diagonal of matrix to factorize */ /* ---- in/out --- */ cholmod_factor *L, /* factorization */ /* --------------- */ cholmod_common *Common ) { cholmod_dense *C ; Int *Super, *Map, *SuperMap ; size_t maxcsize ; Int nsuper, n, i, k, s, stype, nrow ; int ok = TRUE, symbolic ; size_t t, w ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (L, FALSE) ; RETURN_IF_NULL (A, FALSE) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_REAL, CHOLMOD_ZOMPLEX, FALSE) ; RETURN_IF_XTYPE_INVALID (L, CHOLMOD_PATTERN, CHOLMOD_COMPLEX, FALSE) ; stype = A->stype ; if (stype < 0) { if (A->nrow != A->ncol || A->nrow != L->n) { ERROR (CHOLMOD_INVALID, "invalid dimensions") ; return (FALSE) ; } } else if (stype == 0) { if (A->nrow != L->n) { ERROR (CHOLMOD_INVALID, "invalid dimensions") ; return (FALSE) ; } RETURN_IF_NULL (F, FALSE) ; RETURN_IF_XTYPE_INVALID (F, CHOLMOD_REAL, CHOLMOD_ZOMPLEX, FALSE) ; if (A->nrow != F->ncol || A->ncol != F->nrow || F->stype != 0) { ERROR (CHOLMOD_INVALID, "F invalid") ; return (FALSE) ; } if (A->xtype != F->xtype) { ERROR (CHOLMOD_INVALID, "A and F must have same xtype") ; return (FALSE) ; } } else { /* symmetric upper case not suppored */ ERROR (CHOLMOD_INVALID, "symmetric upper case not supported") ; return (FALSE) ; } if (!(L->is_super)) { ERROR (CHOLMOD_INVALID, "L not supernodal") ; return (FALSE) ; } if (L->xtype != CHOLMOD_PATTERN) { if (! ((A->xtype == CHOLMOD_REAL && L->xtype == CHOLMOD_REAL) || (A->xtype == CHOLMOD_COMPLEX && L->xtype == CHOLMOD_COMPLEX) || (A->xtype == CHOLMOD_ZOMPLEX && L->xtype == CHOLMOD_COMPLEX))) { ERROR (CHOLMOD_INVALID, "complex type mismatch") ; return (FALSE) ; } } Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* allocate workspace in Common */ /* ---------------------------------------------------------------------- */ nsuper = L->nsuper ; maxcsize = L->maxcsize ; nrow = A->nrow ; n = nrow ; PRINT1 (("nsuper "ID" maxcsize %g\n", nsuper, (double) maxcsize)) ; ASSERT (nsuper >= 0 && maxcsize > 0) ; /* w = 2*n + 4*nsuper */ w = CHOLMOD(mult_size_t) (n, 2, &ok) ; t = CHOLMOD(mult_size_t) (nsuper, 4, &ok) ; w = CHOLMOD(add_size_t) (w, t, &ok) ; if (!ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return (FALSE) ; } CHOLMOD(allocate_work) (n, w, 0, Common) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; } ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; /* ---------------------------------------------------------------------- */ /* get the current factor L and allocate numerical part, if needed */ /* ---------------------------------------------------------------------- */ Super = L->super ; symbolic = (L->xtype == CHOLMOD_PATTERN) ; if (symbolic) { /* convert to supernodal numeric by allocating L->x */ CHOLMOD(change_factor) ( (A->xtype == CHOLMOD_REAL) ? CHOLMOD_REAL : CHOLMOD_COMPLEX, TRUE, TRUE, TRUE, TRUE, L, Common) ; if (Common->status < CHOLMOD_OK) { /* the factor L remains in symbolic supernodal form */ return (FALSE) ; } } ASSERT (L->dtype == DTYPE) ; ASSERT (L->xtype == CHOLMOD_REAL || L->xtype == CHOLMOD_COMPLEX) ; /* supernodal LDL' is not supported */ L->is_ll = TRUE ; /* ---------------------------------------------------------------------- */ /* get more workspace */ /* ---------------------------------------------------------------------- */ C = CHOLMOD(allocate_dense) (maxcsize, 1, maxcsize, L->xtype, Common) ; if (Common->status < CHOLMOD_OK) { int status = Common->status ; if (symbolic) { /* Change L back to symbolic, since the numeric values are not * initialized. This cannot fail. */ CHOLMOD(change_factor) (CHOLMOD_PATTERN, TRUE, TRUE, TRUE, TRUE, L, Common) ; } /* the factor L is now back to the form it had on input */ Common->status = status ; return (FALSE) ; } /* ---------------------------------------------------------------------- */ /* get workspace */ /* ---------------------------------------------------------------------- */ SuperMap = Common->Iwork ; /* size n (i/i/l) */ Map = Common->Flag ; /* size n, use Flag as workspace for Map array */ for (i = 0 ; i < n ; i++) { Map [i] = EMPTY ; } /* ---------------------------------------------------------------------- */ /* find the mapping of nodes to relaxed supernodes */ /* ---------------------------------------------------------------------- */ /* SuperMap [k] = s if column k is contained in supernode s */ for (s = 0 ; s < nsuper ; s++) { PRINT1 (("Super ["ID"] "ID" ncols "ID"\n", s, Super[s], Super[s+1]-Super[s])); for (k = Super [s] ; k < Super [s+1] ; k++) { SuperMap [k] = s ; PRINT2 (("relaxed SuperMap ["ID"] = "ID"\n", k, SuperMap [k])) ; } } /* ---------------------------------------------------------------------- */ /* supernodal numerical factorization, using template routine */ /* ---------------------------------------------------------------------- */ switch (A->xtype) { case CHOLMOD_REAL: ok = r_cholmod_super_numeric (A, F, beta, L, C, Common) ; break ; /* case CHOLMOD_COMPLEX: */ /* ok = c_cholmod_super_numeric (A, F, beta, L, C, Common) ; */ /* break ; */ /* case CHOLMOD_ZOMPLEX: */ /* /\* This operates on complex L, not zomplex *\/ */ /* ok = z_cholmod_super_numeric (A, F, beta, L, C, Common) ; */ /* break ; */ } /* ---------------------------------------------------------------------- */ /* clear Common workspace, free temp workspace C, and return */ /* ---------------------------------------------------------------------- */ /* Flag array was used as workspace, clear it */ Common->mark = EMPTY ; /* CHOLMOD(clear_flag) (Common) ; */ CHOLMOD_CLEAR_FLAG (Common) ; ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; CHOLMOD(free_dense) (&C, Common) ; return (ok) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Supernodal/gpl.txt0000644000076500000240000004313313524616144026134 0ustar tamasstaff00000000000000 GNU GENERAL PUBLIC LICENSE Version 2, June 1991 Copyright (C) 1989, 1991 Free Software Foundation, Inc. 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed. Preamble The licenses for most software are designed to take away your freedom to share and change it. By contrast, the GNU General Public License is intended to guarantee your freedom to share and change free software--to make sure the software is free for all its users. This General Public License applies to most of the Free Software Foundation's software and to any other program whose authors commit to using it. (Some other Free Software Foundation software is covered by the GNU Library General Public License instead.) You can apply it to your programs, too. When we speak of free software, we are referring to freedom, not price. Our General Public Licenses are designed to make sure that you have the freedom to distribute copies of free software (and charge for this service if you wish), that you receive source code or can get it if you want it, that you can change the software or use pieces of it in new free programs; and that you know you can do these things. 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Here is a sample; alter the names: Yoyodyne, Inc., hereby disclaims all copyright interest in the program `Gnomovision' (which makes passes at compilers) written by James Hacker. , 1 April 1989 Ty Coon, President of Vice This General Public License does not permit incorporating your program into proprietary programs. If your program is a subroutine library, you may consider it more useful to permit linking proprietary applications with the library. If this is what you want to do, use the GNU Library General Public License instead of this License. python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Supernodal/cholmod_super_solve.c0000644000076500000240000001602413524616144031027 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Supernodal/cholmod_super_solve ======================================= */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Supernodal Module. Copyright (C) 2005-2006, Timothy A. Davis * The CHOLMOD/Supernodal Module is licensed under Version 2.0 of the GNU * General Public License. See gpl.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * http://www.suitesparse.com * -------------------------------------------------------------------------- */ /* Solve Lx=b or L'x=b for a supernodal factorization. These routines do not * apply the permutation L->Perm. See cholmod_solve for a more general * interface that performs that operation. */ #ifndef NSUPERNODAL #include "cholmod_internal.h" #include "cholmod_supernodal.h" #include "igraph_blas_internal.h" /* ========================================================================== */ /* === TEMPLATE ============================================================= */ /* ========================================================================== */ #define REAL #include "t_cholmod_super_solve.c" /* #define COMPLEX */ /* #include "t_cholmod_super_solve.c" */ /* ========================================================================== */ /* === cholmod_super_lsolve ================================================= */ /* ========================================================================== */ /* Solve Lx=b where x and b are of size n-by-nrhs. b is overwritten by the * solution x. On input, b is stored in col-major order with leading dimension * of d, and on output x is stored in the same manner. * * The contents of the workspace E are undefined on both input and output. * * workspace: none */ int CHOLMOD(super_lsolve) /* TRUE if OK, FALSE if BLAS overflow occured */ ( /* ---- input ---- */ cholmod_factor *L, /* factor to use for the forward solve */ /* ---- output ---- */ cholmod_dense *X, /* b on input, solution to Lx=b on output */ /* ---- workspace ---- */ cholmod_dense *E, /* workspace of size nrhs*(L->maxesize) */ /* --------------- */ cholmod_common *Common ) { /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (L, FALSE) ; RETURN_IF_NULL (X, FALSE) ; RETURN_IF_NULL (E, FALSE) ; RETURN_IF_XTYPE_INVALID (L, CHOLMOD_REAL, CHOLMOD_COMPLEX, FALSE) ; RETURN_IF_XTYPE_INVALID (X, CHOLMOD_REAL, CHOLMOD_COMPLEX, FALSE) ; RETURN_IF_XTYPE_INVALID (E, CHOLMOD_REAL, CHOLMOD_COMPLEX, FALSE) ; if (L->xtype != X->xtype) { ERROR (CHOLMOD_INVALID, "L and X must have the same xtype") ; return (FALSE) ; } if (L->xtype != E->xtype) { ERROR (CHOLMOD_INVALID, "L and E must have the same xtype") ; return (FALSE) ; } if (X->d < X->nrow || L->n != X->nrow) { ERROR (CHOLMOD_INVALID, "X and L dimensions must match") ; return (FALSE) ; } if (E->nzmax < X->ncol * (L->maxesize)) { ERROR (CHOLMOD_INVALID, "workspace E not large enough") ; return (FALSE) ; } if (!(L->is_ll) || !(L->is_super)) { ERROR (CHOLMOD_INVALID, "L not supernodal") ; return (FALSE) ; } Common->status = CHOLMOD_OK ; ASSERT (IMPLIES (L->n == 0, L->nsuper == 0)) ; if (L->n == 0 || X->ncol == 0) { /* nothing to do */ return (TRUE) ; } /* ---------------------------------------------------------------------- */ /* solve Lx=b using template routine */ /* ---------------------------------------------------------------------- */ switch (L->xtype) { case CHOLMOD_REAL: r_cholmod_super_lsolve (L, X, E, Common) ; break ; /* case CHOLMOD_COMPLEX: */ /* c_cholmod_super_lsolve (L, X, E, Common) ; */ /* break ; */ } if (CHECK_BLAS_INT && !Common->blas_ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large for the BLAS") ; } return (Common->blas_ok) ; } /* ========================================================================== */ /* === cholmod_super_ltsolve ================================================ */ /* ========================================================================== */ /* Solve L'x=b where x and b are of size n-by-nrhs. b is overwritten by the * solution x. On input, b is stored in col-major order with leading dimension * of d, and on output x is stored in the same manner. * * The contents of the workspace E are undefined on both input and output. * * workspace: none */ int CHOLMOD(super_ltsolve) /* TRUE if OK, FALSE if BLAS overflow occured */ ( /* ---- input ---- */ cholmod_factor *L, /* factor to use for the backsolve */ /* ---- output ---- */ cholmod_dense *X, /* b on input, solution to L'x=b on output */ /* ---- workspace ---- */ cholmod_dense *E, /* workspace of size nrhs*(L->maxesize) */ /* --------------- */ cholmod_common *Common ) { /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (L, FALSE) ; RETURN_IF_NULL (X, FALSE) ; RETURN_IF_NULL (E, FALSE) ; RETURN_IF_XTYPE_INVALID (L, CHOLMOD_REAL, CHOLMOD_COMPLEX, FALSE) ; RETURN_IF_XTYPE_INVALID (X, CHOLMOD_REAL, CHOLMOD_COMPLEX, FALSE) ; RETURN_IF_XTYPE_INVALID (E, CHOLMOD_REAL, CHOLMOD_COMPLEX, FALSE) ; if (L->xtype != X->xtype) { ERROR (CHOLMOD_INVALID, "L and X must have the same xtype") ; return (FALSE) ; } if (L->xtype != E->xtype) { ERROR (CHOLMOD_INVALID, "L and E must have the same xtype") ; return (FALSE) ; } if (X->d < X->nrow || L->n != X->nrow) { ERROR (CHOLMOD_INVALID, "X and L dimensions must match") ; return (FALSE) ; } if (E->nzmax < X->ncol * (L->maxesize)) { ERROR (CHOLMOD_INVALID, "workspace E not large enough") ; return (FALSE) ; } if (!(L->is_ll) || !(L->is_super)) { ERROR (CHOLMOD_INVALID, "L not supernodal") ; return (FALSE) ; } Common->status = CHOLMOD_OK ; ASSERT (IMPLIES (L->n == 0, L->nsuper == 0)) ; if (L->n == 0 || X->ncol == 0) { /* nothing to do */ return (TRUE) ; } /* ---------------------------------------------------------------------- */ /* solve Lx=b using template routine */ /* ---------------------------------------------------------------------- */ switch (L->xtype) { case CHOLMOD_REAL: r_cholmod_super_ltsolve (L, X, E, Common) ; break ; /* case CHOLMOD_COMPLEX: */ /* c_cholmod_super_ltsolve (L, X, E, Common) ; */ /* break ; */ } if (CHECK_BLAS_INT && !Common->blas_ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large for the BLAS") ; } return (Common->blas_ok) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Supernodal/License.txt0000644000076500000240000000203113524616144026724 0ustar tamasstaff00000000000000CHOLMOD/Supernodal Module. Copyright (C) 2005-2006, Timothy A. Davis CHOLMOD is also available under other licenses; contact authors for details. http://www.suitesparse.com Note that this license is for the CHOLMOD/Supernodal module only. All CHOLMOD modules are licensed separately. -------------------------------------------------------------------------------- This Module is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This Module is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this Module; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Supernodal/t_cholmod_super_solve.c0000644000076500000240000002753513524616144031363 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Supernodal/t_cholmod_super_solve ===================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Supernodal Module. Copyright (C) 2005-2006, Timothy A. Davis * The CHOLMOD/Supernodal Module is licensed under Version 2.0 of the GNU * General Public License. See gpl.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * http://www.suitesparse.com * -------------------------------------------------------------------------- */ /* Template routine for cholmod_super_solve. Supports real or complex L. */ #include "cholmod_template.h" #ifdef USING_R #include #ifdef HAVE_F77_UNDERSCORE # define F77_CALL(x) x ## _ #else # define F77_CALL(x) x #endif #define F77_NAME(x) F77_CALL(x) #define F77_SUB(x) F77_CALL(x) #define F77_COM(x) F77_CALL(x) #define F77_COMDECL(x) F77_CALL(x) void F77_NAME(dsyrk)(const char *uplo, const char *trans, const int *n, const int *k, const double *alpha, const double *a, const int *lda, const double *beta, double *c, const int *ldc); void F77_NAME(dpotrf)(const char* uplo, const int* n, double* a, const int* lda, int* info); void F77_NAME(dtrsm)(const char *side, const char *uplo, const char *transa, const char *diag, const int *m, const int *n, const double *alpha, const double *a, const int *lda, double *b, const int *ldb); void F77_NAME(dtrsv)(const char *uplo, const char *trans, const char *diag, const int *n, const double *a, const int *lda, double *x, const int *incx); #endif static void TEMPLATE (cholmod_super_lsolve) ( /* ---- input ---- */ cholmod_factor *L, /* factor to use for the forward solve */ /* ---- output ---- */ cholmod_dense *X, /* b on input, solution to Lx=b on output */ /* ---- workspace ---- */ cholmod_dense *E, /* workspace of size nrhs*(L->maxesize) */ /* --------------- */ cholmod_common *Common ) { double *Lx, *Xx, *Ex ; double minus_one [2], one [2] ; Int *Lpi, *Lpx, *Ls, *Super ; Int nsuper, k1, k2, psi, psend, psx, nsrow, nscol, ii, s, nsrow2, n, ps2, j, i, d, nrhs ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ nrhs = X->ncol ; Ex = E->x ; Xx = X->x ; n = L->n ; d = X->d ; nsuper = L->nsuper ; Lpi = L->pi ; Lpx = L->px ; Ls = L->s ; Super = L->super ; Lx = L->x ; minus_one [0] = -1.0 ; minus_one [1] = 0 ; one [0] = 1.0 ; one [1] = 0 ; /* ---------------------------------------------------------------------- */ /* solve Lx=b */ /* ---------------------------------------------------------------------- */ if (nrhs == 1) { for (s = 0 ; s < nsuper ; s++) { k1 = Super [s] ; k2 = Super [s+1] ; psi = Lpi [s] ; psend = Lpi [s+1] ; psx = Lpx [s] ; nsrow = psend - psi ; nscol = k2 - k1 ; nsrow2 = nsrow - nscol ; ps2 = psi + nscol ; ASSERT ((size_t) nsrow2 <= L->maxesize) ; /* L1 is nscol-by-nscol, lower triangular with non-unit diagonal. * L2 is nsrow2-by-nscol. L1 and L2 have leading dimension of * nsrow. x1 is nscol-by-nsrow, with leading dimension n. * E is nsrow2-by-1, with leading dimension nsrow2. */ /* gather X into E */ for (ii = 0 ; ii < nsrow2 ; ii++) { /* Ex [ii] = Xx [Ls [ps2 + ii]] ; */ ASSIGN (Ex,-,ii, Xx,-,Ls [ps2 + ii]) ; } #ifdef REAL /* solve L1*x1 (that is, x1 = L1\x1) */ BLAS_dtrsv ("L", "N", "N", nscol, /* N: L1 is nscol-by-nscol */ Lx + ENTRY_SIZE*psx, nsrow, /* A, LDA: L1 */ Xx + ENTRY_SIZE*k1, 1) ; /* X, INCX: x1 */ /* E = E - L2*x1 */ BLAS_dgemv ("N", nsrow2, nscol, /* M, N: L2 is nsrow2-by-nscol */ minus_one, /* ALPHA: -1 */ Lx + ENTRY_SIZE*(psx + nscol), /* A, LDA: L2 */ nsrow, Xx + ENTRY_SIZE*k1, 1, /* X, INCX: x1 */ one, /* BETA: 1 */ Ex, 1) ; /* Y, INCY: E */ #else /* solve L1*x1 (that is, x1 = L1\x1) */ BLAS_ztrsv ("L", "N", "N", nscol, /* N: L1 is nscol-by-nscol */ Lx + ENTRY_SIZE*psx, nsrow, /* A, LDA: L1 */ Xx + ENTRY_SIZE*k1, 1) ; /* X, INCX: x1 */ /* E = E - L2*x1 */ BLAS_zgemv ("N", nsrow2, nscol, /* M, N: L2 is nsrow2-by-nscol */ minus_one, /* ALPHA: -1 */ Lx + ENTRY_SIZE*(psx + nscol), /* A, LDA: L2 */ nsrow, Xx + ENTRY_SIZE*k1, 1, /* X, INCX: x1 */ one, /* BETA: 1 */ Ex, 1) ; /* Y, INCY: E */ #endif /* scatter E back into X */ for (ii = 0 ; ii < nsrow2 ; ii++) { /* Xx [Ls [ps2 + ii]] = Ex [ii] ; */ ASSIGN (Xx,-,Ls [ps2 + ii], Ex,-,ii) ; } } } else { for (s = 0 ; s < nsuper ; s++) { k1 = Super [s] ; k2 = Super [s+1] ; psi = Lpi [s] ; psend = Lpi [s+1] ; psx = Lpx [s] ; nsrow = psend - psi ; nscol = k2 - k1 ; nsrow2 = nsrow - nscol ; ps2 = psi + nscol ; ASSERT ((size_t) nsrow2 <= L->maxesize) ; /* E is nsrow2-by-nrhs, with leading dimension nsrow2. */ /* gather X into E */ for (ii = 0 ; ii < nsrow2 ; ii++) { i = Ls [ps2 + ii] ; for (j = 0 ; j < nrhs ; j++) { /* Ex [ii + j*nsrow2] = Xx [i + j*d] ; */ ASSIGN (Ex,-,ii+j*nsrow2, Xx,-,i+j*d) ; } } #ifdef REAL /* solve L1*x1 */ BLAS_dtrsm ("L", "L", "N", "N", nscol, nrhs, /* M, N: x1 is nscol-by-nrhs */ one, /* ALPHA: 1 */ Lx + ENTRY_SIZE*psx, nsrow, /* A, LDA: L1 */ Xx + ENTRY_SIZE*k1, d) ; /* B, LDB: x1 */ /* E = E - L2*x1 */ if (nsrow2 > 0) { BLAS_dgemm ("N", "N", nsrow2, nrhs, nscol, /* M, N, K */ minus_one, /* ALPHA: -1 */ Lx + ENTRY_SIZE*(psx + nscol), /* A, LDA: L2 */ nsrow, Xx + ENTRY_SIZE*k1, d, /* B, LDB: X1 */ one, /* BETA: 1 */ Ex, nsrow2) ; /* C, LDC: E */ } #else /* solve L1*x1 */ BLAS_ztrsm ("L", "L", "N", "N", nscol, nrhs, /* M, N: x1 is nscol-by-nrhs */ one, /* ALPHA: 1 */ Lx + ENTRY_SIZE*psx, nsrow, /* A, LDA: L1 */ Xx + ENTRY_SIZE*k1, d) ; /* B, LDB: x1 */ /* E = E - L2*x1 */ if (nsrow2 > 0) { BLAS_zgemm ("N", "N", nsrow2, nrhs, nscol, /* M, N, K */ minus_one, /* ALPHA: -1 */ Lx + ENTRY_SIZE*(psx + nscol), /* A, LDA: L2 */ nsrow, Xx + ENTRY_SIZE*k1, d, /* B, LDB: X1 */ one, /* BETA: 1 */ Ex, nsrow2) ; /* C, LDC: E */ } #endif /* scatter E back into X */ for (ii = 0 ; ii < nsrow2 ; ii++) { i = Ls [ps2 + ii] ; for (j = 0 ; j < nrhs ; j++) { /* Xx [i + j*d] = Ex [ii + j*nsrow2] ; */ ASSIGN (Xx,-,i+j*d, Ex,-,ii+j*nsrow2) ; } } } } } static void TEMPLATE (cholmod_super_ltsolve) ( /* ---- input ---- */ cholmod_factor *L, /* factor to use for the forward solve */ /* ---- output ---- */ cholmod_dense *X, /* b on input, solution to Lx=b on output */ /* ---- workspace ---- */ cholmod_dense *E, /* workspace of size nrhs*(L->maxesize) */ /* --------------- */ cholmod_common *Common ) { double *Lx, *Xx, *Ex ; double minus_one [2], one [2] ; Int *Lpi, *Lpx, *Ls, *Super ; Int nsuper, k1, k2, psi, psend, psx, nsrow, nscol, ii, s, nsrow2, n, ps2, j, i, d, nrhs ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ nrhs = X->ncol ; Ex = E->x ; Xx = X->x ; n = L->n ; d = X->d ; nsuper = L->nsuper ; Lpi = L->pi ; Lpx = L->px ; Ls = L->s ; Super = L->super ; Lx = L->x ; minus_one [0] = -1.0 ; minus_one [1] = 0 ; one [0] = 1.0 ; one [1] = 0 ; /* ---------------------------------------------------------------------- */ /* solve L'x=b */ /* ---------------------------------------------------------------------- */ if (nrhs == 1) { for (s = nsuper-1 ; s >= 0 ; s--) { k1 = Super [s] ; k2 = Super [s+1] ; psi = Lpi [s] ; psend = Lpi [s+1] ; psx = Lpx [s] ; nsrow = psend - psi ; nscol = k2 - k1 ; nsrow2 = nsrow - nscol ; ps2 = psi + nscol ; ASSERT ((size_t) nsrow2 <= L->maxesize) ; /* L1 is nscol-by-nscol, lower triangular with non-unit diagonal. * L2 is nsrow2-by-nscol. L1 and L2 have leading dimension of * nsrow. x1 is nscol-by-nsrow, with leading dimension n. * E is nsrow2-by-1, with leading dimension nsrow2. */ /* gather X into E */ for (ii = 0 ; ii < nsrow2 ; ii++) { /* Ex [ii] = Xx [Ls [ps2 + ii]] ; */ ASSIGN (Ex,-,ii, Xx,-,Ls [ps2 + ii]) ; } #ifdef REAL /* x1 = x1 - L2'*E */ BLAS_dgemv ("C", nsrow2, nscol, /* M, N: L2 is nsrow2-by-nscol */ minus_one, /* ALPHA: -1 */ Lx + ENTRY_SIZE*(psx + nscol), /* A, LDA: L2 */ nsrow, Ex, 1, /* X, INCX: Ex */ one, /* BETA: 1 */ Xx + ENTRY_SIZE*k1, 1) ; /* Y, INCY: x1 */ /* solve L1'*x1 */ BLAS_dtrsv ("L", "C", "N", nscol, /* N: L1 is nscol-by-nscol */ Lx + ENTRY_SIZE*psx, nsrow, /* A, LDA: L1 */ Xx + ENTRY_SIZE*k1, 1) ; /* X, INCX: x1 */ #else /* x1 = x1 - L2'*E */ BLAS_zgemv ("C", nsrow2, nscol, /* M, N: L2 is nsrow2-by-nscol */ minus_one, /* ALPHA: -1 */ Lx + ENTRY_SIZE*(psx + nscol), /* A, LDA: L2 */ nsrow, Ex, 1, /* X, INCX: Ex */ one, /* BETA: 1 */ Xx + ENTRY_SIZE*k1, 1) ; /* Y, INCY: x1 */ /* solve L1'*x1 */ BLAS_ztrsv ("L", "C", "N", nscol, /* N: L1 is nscol-by-nscol */ Lx + ENTRY_SIZE*psx, nsrow, /* A, LDA: L1 */ Xx + ENTRY_SIZE*k1, 1) ; /* X, INCX: x1 */ #endif } } else { for (s = nsuper-1 ; s >= 0 ; s--) { k1 = Super [s] ; k2 = Super [s+1] ; psi = Lpi [s] ; psend = Lpi [s+1] ; psx = Lpx [s] ; nsrow = psend - psi ; nscol = k2 - k1 ; nsrow2 = nsrow - nscol ; ps2 = psi + nscol ; ASSERT ((size_t) nsrow2 <= L->maxesize) ; /* E is nsrow2-by-nrhs, with leading dimension nsrow2. */ /* gather X into E */ for (ii = 0 ; ii < nsrow2 ; ii++) { i = Ls [ps2 + ii] ; for (j = 0 ; j < nrhs ; j++) { /* Ex [ii + j*nsrow2] = Xx [i + j*d] ; */ ASSIGN (Ex,-,ii+j*nsrow2, Xx,-,i+j*d) ; } } #ifdef REAL /* x1 = x1 - L2'*E */ if (nsrow2 > 0) { BLAS_dgemm ("C", "N", nscol, nrhs, nsrow2, /* M, N, K */ minus_one, /* ALPHA: -1 */ Lx + ENTRY_SIZE*(psx + nscol), /* A, LDA: L2 */ nsrow, Ex, nsrow2, /* B, LDB: E */ one, /* BETA: 1 */ Xx + ENTRY_SIZE*k1, d) ; /* C, LDC: x1 */ } /* solve L1'*x1 */ BLAS_dtrsm ("L", "L", "C", "N", nscol, nrhs, /* M, N: x1 is nscol-by-nrhs */ one, /* ALPHA: 1 */ Lx + ENTRY_SIZE*psx, nsrow, /* A, LDA: L1 */ Xx + ENTRY_SIZE*k1, d) ; /* B, LDB: x1 */ #else /* x1 = x1 - L2'*E */ if (nsrow2 > 0) { BLAS_zgemm ("C", "N", nscol, nrhs, nsrow2, /* M, N, K */ minus_one, /* ALPHA: -1 */ Lx + ENTRY_SIZE*(psx + nscol), /* A, LDA: L2 */ nsrow, Ex, nsrow2, /* B, LDB: E */ one, /* BETA: 1 */ Xx + ENTRY_SIZE*k1, d) ; /* C, LDC: x1 */ } /* solve L1'*x1 */ BLAS_ztrsm ("L", "L", "C", "N", nscol, nrhs, /* M, N: x1 is nscol-by-nrhs */ one, /* ALPHA: 1 */ Lx + ENTRY_SIZE*psx, nsrow, /* A, LDA: L1 */ Xx + ENTRY_SIZE*k1, d) ; /* B, LDB: x1 */ #endif } } } #undef PATTERN #undef REAL #undef COMPLEX #undef ZOMPLEX python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Supernodal/t_cholmod_gpu.c0000644000076500000240000010374613524616144027607 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Supernodal/t_cholmod_gpu ============================================= */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Supernodal Module. Copyright (C) 2005-2012, Timothy A. Davis * The CHOLMOD/Supernodal Module is licensed under Version 2.0 of the GNU * General Public License. See gpl.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * http://www.suitesparse.com * -------------------------------------------------------------------------- */ /* GPU BLAS template routine for cholmod_super_numeric. */ /* ========================================================================== */ /* === include files and definitions ======================================== */ /* ========================================================================== */ #include "cholmod_template.h" #undef L_ENTRY #ifdef REAL #define L_ENTRY 1 #else #define L_ENTRY 2 #endif /* #define GPU_Printf printf */ #define GPU_Printf #define PAGE_SIZE (4*1024) #define OK(cuda_operation) ((cuda_operation) == cudaSuccess) /* ========================================================================== */ /* === gpu_init ============================================================= */ /* ========================================================================== */ void TEMPLATE (CHOLMOD (gpu_init)) ( void *Cwork, Int maxSize, cholmod_common *Common ) { Int i ; cublasStatus_t cublasError ; cudaError_t cudaErr ; size_t maxBytesSize, HostPinnedSize ; Common->GemmUsed = 0 ; GPU_Printf ("gpu_init : %p\n", (void *) ((size_t) Cwork & ~(PAGE_SIZE-1))) ; if (!(Common->cublasHandle)) { /* ------------------------------------------------------------------ */ /* create the CUDA BLAS handle */ /* ------------------------------------------------------------------ */ cublasError = cublasCreate (&(Common->cublasHandle)) ; if (cublasError != CUBLAS_STATUS_SUCCESS) { ERROR (CHOLMOD_GPU_PROBLEM, "CUBLAS initialization") ; return ; } /* ------------------------------------------------------------------ */ /* create each CUDA stream */ /* ------------------------------------------------------------------ */ cudaErr = cudaStreamCreate (&(Common->cudaStreamSyrk)) ; if (cudaErr != cudaSuccess) { ERROR (CHOLMOD_GPU_PROBLEM, "CUDA stream initialization") ; return ; } cudaErr = cudaStreamCreate (&(Common->cudaStreamGemm)) ; if (cudaErr != cudaSuccess) { ERROR (CHOLMOD_GPU_PROBLEM, "CUDA stream initialization") ; return ; } cudaErr = cudaStreamCreate (&(Common->cudaStreamTrsm)) ; if (cudaErr != cudaSuccess) { ERROR (CHOLMOD_GPU_PROBLEM, "CUDA stream initialization") ; return ; } for (i = 0 ; i < 3 ; i++) { cudaErr = cudaStreamCreate (&(Common->cudaStreamPotrf [i])) ; if (cudaErr != cudaSuccess) { ERROR (CHOLMOD_GPU_PROBLEM, "CUDA stream initialization") ; return ; } } /* ------------------------------------------------------------------ */ /* create each CUDA event */ /* ------------------------------------------------------------------ */ for (i = 0 ; i < 2 ; i++) { cudaErr = cudaEventCreateWithFlags (&(Common->cublasEventPotrf [i]), cudaEventDisableTiming) ; if (cudaErr != cudaSuccess) { ERROR (CHOLMOD_GPU_PROBLEM, "CUDA event") ; return ; } } } /* ---------------------------------------------------------------------- */ /* pin the Host memory */ /* ---------------------------------------------------------------------- */ Common->HostPinnedMemory = (void *) ((size_t) Cwork & ~(PAGE_SIZE-1)) ; maxBytesSize = sizeof (double)*L_ENTRY*maxSize ; /* Align on a 4K page boundary (it is no more necessary in 4.1 */ HostPinnedSize = (((size_t) Cwork + maxBytesSize + PAGE_SIZE-1) & ~(PAGE_SIZE-1)) - (size_t) (Common->HostPinnedMemory) ; GPU_Printf ("gpu HostPinnedSize: %g %p\n", (double) HostPinnedSize, Common->HostPinnedMemory) ; cudaErr = cudaHostRegister (Common->HostPinnedMemory, HostPinnedSize, 0) ; if (cudaErr != cudaSuccess) { ERROR (CHOLMOD_GPU_PROBLEM, "CUDA Pinning Memory") ; Common->HostPinnedMemory = NULL ; } } /* ========================================================================== */ /* === gpu_end ============================================================== */ /* ========================================================================== */ void TEMPLATE (CHOLMOD (gpu_end)) ( cholmod_common *Common ) { int i; /* unpin the Host memory */ GPU_Printf ("gpu_end %p\n", Common->HostPinnedMemory) ; cudaError_t cudaErr = cudaHostUnregister (Common->HostPinnedMemory) ; if (cudaErr != cudaSuccess) { ERROR (CHOLMOD_GPU_PROBLEM, "CUDA Unpinning Memory") ; Common->HostPinnedMemory = NULL ; } /* ------------------------------------------------------------------ */ /* destroy Cublas Handle */ /* ------------------------------------------------------------------ */ if (Common->cublasHandle) { cublasDestroy(Common->cublasHandle); Common->cublasHandle = NULL ; } /* ------------------------------------------------------------------ */ /* destroy each CUDA stream */ /* ------------------------------------------------------------------ */ if (Common->cudaStreamSyrk) { cudaStreamDestroy (Common->cudaStreamSyrk) ; Common->cudaStreamSyrk = NULL ; } if (Common->cudaStreamGemm) { cudaStreamDestroy (Common->cudaStreamGemm) ; } if (Common->cudaStreamTrsm) { cudaStreamDestroy (Common->cudaStreamTrsm) ; Common->cudaStreamTrsm = NULL ; } for (i = 0 ; i < 3 ; i++) { if (Common->cudaStreamPotrf [i]) { cudaStreamDestroy(Common->cudaStreamPotrf [i]) ; Common->cudaStreamPotrf [i] = NULL ; } } /* ------------------------------------------------------------------ */ /* destroy each CUDA event */ /* ------------------------------------------------------------------ */ for (i = 0 ; i < 2 ; i++) { if (Common->cublasEventPotrf [i]) { cudaEventDestroy( Common->cublasEventPotrf [i] ) ; Common->cublasEventPotrf [i] = NULL ; } } } /* ========================================================================== */ /* === gpu_updateC ========================================================== */ /* ========================================================================== */ /* C = L (k1:n-1, kd1:kd2-1) * L (k1:k2-1, kd1:kd2-1)', except that k1:n-1 * refers to all of the rows in L, but many of the rows are all zero. * Supernode d holds columns kd1 to kd2-1 of L. Nonzero rows in the range * k1:k2-1 are in the list Ls [pdi1 ... pdi2-1], of size ndrow1. Nonzero rows * in the range k2:n-1 are in the list Ls [pdi2 ... pdend], of size ndrow2. * Let L1 = L (Ls [pdi1 ... pdi2-1], kd1:kd2-1), and let L2 = L (Ls [pdi2 ... * pdend], kd1:kd2-1). C is ndrow2-by-ndrow1. Let C1 be the first ndrow1 * rows of C and let C2 be the last ndrow2-ndrow1 rows of C. Only the lower * triangular part of C1 needs to be computed since C1 is symmetric. */ int TEMPLATE (CHOLMOD (gpu_updateC)) ( Int ndrow1, /* C is ndrow2-by-ndrow2 */ Int ndrow2, Int ndrow, /* leading dimension of Lx */ Int ndcol, /* L1 is ndrow1-by-ndcol */ Int pdx1, /* L1 starts at Lx + L_ENTRY*pdx1 */ /* L2 starts at Lx + L_ENTRY*(pdx1 + ndrow1) */ double *Lx, double *C, cholmod_common *Common ) { double *devPtrLx, *devPtrC ; double alpha, beta ; cublasStatus_t cublasStatus ; cudaError_t cudaStat [2] ; Int ndrow3 ; Common->SyrkUsed = 0 ; Common->GemmUsed = 0 ; if ((ndrow2 < 512) || (ndcol < 128)) { /* too small for the CUDA BLAS; use the CPU instead */ return (0) ; } ndrow3 = ndrow2 - ndrow1 ; #ifndef NTIMER Common->syrkStart = SuiteSparse_time ( ) ; #endif /* ---------------------------------------------------------------------- */ /* allocate workspace on the GPU */ /* ---------------------------------------------------------------------- */ cudaStat [0] = cudaMalloc ((void **) &devPtrLx, ndrow2 * ndcol * L_ENTRY * sizeof (devPtrLx [0])) ; cudaStat [1] = cudaMalloc ((void **) &devPtrC, ndrow2 * ndrow1 * L_ENTRY * sizeof (devPtrC [0])) ; Common->devSyrkGemmPtrLx = devPtrLx ; Common->devSyrkGemmPtrC = devPtrC ; if (cudaStat [0] || cudaStat [1]) { /* one or both cudaMalloc's failed */ if (devPtrLx) cudaFree (devPtrLx) ; if (devPtrC) cudaFree (devPtrC) ; GPU_Printf ("gpu malloc failed =%d,%d ndrow1=%d ndrow2=%d ndcol=%d\n", cudaStat [0], cudaStat [1], (int) ndrow1, (int) ndrow2, (int) ndcol) ; /* cudaMalloc failure is not an error, just bypass the GPU */ return (0) ; } Common->SyrkUsed = 1 ; #ifndef NTIMER Common->CHOLMOD_GPU_SYRK_CALLS++ ; #endif /* ---------------------------------------------------------------------- */ /* copy Lx to the GPU */ /* ---------------------------------------------------------------------- */ /* copy Lx in two steps on different streams. * (ldLx is shortened from ndrow to ndrow2) */ cudaStat [0] = cudaMemcpy2DAsync (devPtrLx, ndrow2 * L_ENTRY * sizeof (devPtrLx [0]), Lx + L_ENTRY * pdx1, ndrow * L_ENTRY * sizeof (Lx [0]), ndrow1 * L_ENTRY * sizeof (devPtrLx [0]), ndcol, cudaMemcpyHostToDevice, Common->cudaStreamSyrk) ; if (cudaStat [0]) { ERROR (CHOLMOD_GPU_PROBLEM, "GPU memcopy to device") ; } if (ndrow3 > 0) { Common->GemmUsed = 1 ; cudaStat [1] = cudaMemcpy2DAsync (devPtrLx + L_ENTRY*ndrow1, ndrow2 * L_ENTRY * sizeof (devPtrLx [0]), Lx + L_ENTRY * (pdx1 + ndrow1), ndrow * L_ENTRY * sizeof (Lx [0]), ndrow3 * L_ENTRY * sizeof (devPtrLx [0]), ndcol, cudaMemcpyHostToDevice, Common->cudaStreamGemm) ; if (cudaStat [1]) { ERROR (CHOLMOD_GPU_PROBLEM, "GPU memcopy to device") ; } } /* ---------------------------------------------------------------------- */ /* do the CUDA SYRK */ /* ---------------------------------------------------------------------- */ cublasStatus = cublasSetStream (Common->cublasHandle, Common->cudaStreamSyrk) ; if (cublasStatus != CUBLAS_STATUS_SUCCESS) { ERROR (CHOLMOD_GPU_PROBLEM, "GPU CUBLAS stream") ; } alpha = 1.0 ; beta = 0.0 ; #ifdef REAL cublasStatus = cublasDsyrk (Common->cublasHandle, CUBLAS_FILL_MODE_LOWER, CUBLAS_OP_N, (int) ndrow1, (int) ndcol, /* N, K: L1 is ndrow1-by-ndcol */ &alpha, /* ALPHA: 1 */ devPtrLx, ndrow2, /* A, LDA: L1, ndrow2 */ &beta, /* BETA: 0 */ devPtrC, ndrow2) ; /* C, LDC: C1 */ #else cublasStatus = cublasZherk (Common->cublasHandle, CUBLAS_FILL_MODE_LOWER, CUBLAS_OP_N, (int) ndrow1, (int) ndcol, /* N, K: L1 is ndrow1-by-ndcol*/ &alpha, /* ALPHA: 1 */ (const cuDoubleComplex *) devPtrLx, ndrow2, /* A, LDA: L1, ndrow2 */ &beta, /* BETA: 0 */ (cuDoubleComplex *) devPtrC, ndrow2) ; /* C, LDC: C1 */ #endif if (cublasStatus != CUBLAS_STATUS_SUCCESS) { ERROR (CHOLMOD_GPU_PROBLEM, "GPU CUBLAS routine failure") ; } /* ---------------------------------------------------------------------- */ /* partial copy of C to the GPU */ /* ---------------------------------------------------------------------- */ cudaStat [0] = cudaMemcpy2DAsync (C, ndrow2 * L_ENTRY * sizeof (C [0]), devPtrC, ndrow2 * L_ENTRY * sizeof (devPtrC [0]), ndrow1 * L_ENTRY * sizeof (devPtrC [0]), ndrow1, cudaMemcpyDeviceToHost, Common->cudaStreamSyrk) ; if (cudaStat [0]) { ERROR (CHOLMOD_GPU_PROBLEM, "GPU memcopy from device") ; } /* ---------------------------------------------------------------------- */ /* compute remaining (ndrow2-ndrow1)-by-ndrow1 block of C, C2 = L2*L1' */ /* ---------------------------------------------------------------------- */ if (ndrow3 > 0) { #ifndef REAL cuDoubleComplex calpha = {1.0,0.0} ; cuDoubleComplex cbeta = {0.0,0.0} ; #endif #ifndef NTIMER Common->CHOLMOD_GPU_GEMM_CALLS++ ; #endif cublasStatus = cublasSetStream (Common->cublasHandle, Common->cudaStreamGemm) ; if (cublasStatus != CUBLAS_STATUS_SUCCESS) { ERROR (CHOLMOD_GPU_PROBLEM, "GPU CUBLAS stream") ; } /* ------------------------------------------------------------------ */ /* do the CUDA BLAS dgemm */ /* ------------------------------------------------------------------ */ #ifdef REAL alpha = 1.0 ; beta = 0.0 ; cublasStatus = cublasDgemm (Common->cublasHandle, CUBLAS_OP_N, CUBLAS_OP_T, ndrow3, ndrow1, ndcol, /* M, N, K */ &alpha, /* ALPHA: 1 */ devPtrLx + L_ENTRY*(ndrow1), /* A, LDA: L2, ndrow */ ndrow2, devPtrLx, /* B, LDB: L1, ndrow */ ndrow2, &beta, /* BETA: 0 */ devPtrC + L_ENTRY*ndrow1, /* C, LDC: C2 */ ndrow2) ; #else cublasStatus = cublasZgemm (Common->cublasHandle, CUBLAS_OP_N, CUBLAS_OP_C, ndrow3, ndrow1, ndcol, /* M, N, K */ &calpha, /* ALPHA: 1 */ (const cuDoubleComplex *) devPtrLx + ndrow1, /* A, LDA: L2, ndrow */ ndrow2, (const cuDoubleComplex *) devPtrLx, /* B, LDB: L1, ndrow */ ndrow2, &cbeta, /* BETA: 0 */ (cuDoubleComplex *)devPtrC + ndrow1, /* C, LDC: C2 */ ndrow2) ; #endif if (cublasStatus != CUBLAS_STATUS_SUCCESS) { ERROR (CHOLMOD_GPU_PROBLEM, "GPU CUBLAS routine failure") ; } /* ------------------------------------------------------------------ */ /* finish copy of C */ /* ------------------------------------------------------------------ */ cudaStat [0] = cudaMemcpy2DAsync (C + L_ENTRY*ndrow1, ndrow2 * L_ENTRY * sizeof (C [0]), devPtrC+ L_ENTRY*ndrow1, ndrow2 * L_ENTRY * sizeof (devPtrC [0]), ndrow3 * L_ENTRY * sizeof (devPtrC [0]), ndrow1, cudaMemcpyDeviceToHost, Common->cudaStreamGemm) ; if (cudaStat [0]) { ERROR (CHOLMOD_GPU_PROBLEM, "GPU memcopy from device") ; } } return (1) ; } /* ========================================================================== */ /* === gpu_syncSyrk ========================================================= */ /* ========================================================================== */ /* synchronize with the CUDA BLAS dsyrk stream */ void TEMPLATE (CHOLMOD (gpu_syncSyrk)) ( cholmod_common *Common ) { if (Common->SyrkUsed) { cudaStreamSynchronize (Common->cudaStreamSyrk) ; if (!Common->GemmUsed) { cudaFree (Common->devSyrkGemmPtrLx) ; cudaFree (Common->devSyrkGemmPtrC) ; Common->devSyrkGemmPtrLx = NULL ; Common->devSyrkGemmPtrC = NULL ; #ifndef NTIMER /* this actually sums time spend on Syrk and Gemm */ Common->CHOLMOD_GPU_SYRK_TIME += SuiteSparse_time ( ) - Common->syrkStart ; #endif } } } /* ========================================================================== */ /* === gpu_syncGemm ========================================================= */ /* ========================================================================== */ /* synchronize with the CUDA BLAS dgemm stream */ void TEMPLATE (CHOLMOD (gpu_syncGemm)) ( cholmod_common *Common ) { if (Common->GemmUsed) { cudaStreamSynchronize (Common->cudaStreamGemm) ; cudaFree (Common->devSyrkGemmPtrLx) ; cudaFree (Common->devSyrkGemmPtrC) ; Common->devSyrkGemmPtrLx = NULL ; Common->devSyrkGemmPtrC = NULL ; #ifndef NTIMER /* this actually sums time spend on Syrk and Gemm */ Common->CHOLMOD_GPU_SYRK_TIME += SuiteSparse_time ( ) - Common->syrkStart ; #endif } } /* ========================================================================== */ /* === gpu_lower_potrf ====================================================== */ /* ========================================================================== */ /* Cholesky factorzation (dpotrf) of a matrix S, operating on the lower * triangular part only. S is nscol2-by-nscol2 with leading dimension nsrow. * * S is the top part of the supernode (the lower triangular matrx). * This function also copies the bottom rectangular part of the supernode (B) * onto the GPU, in preparation for gpu_triangular_solve. */ int TEMPLATE (CHOLMOD (gpu_lower_potrf)) ( Int nscol2, /* S is nscol2-by-nscol2 */ Int nsrow, /* leading dimension of S */ Int psx, /* S is located at Lx + L_Entry*psx */ double *Lx, /* contains S; overwritten with Cholesky factor */ Int *info, /* BLAS info return value */ cholmod_common *Common ) { double *devPtrA, *devPtrB, *A ; double alpha, beta ; cudaError_t cudaStat ; cublasStatus_t cublasStatus ; Int j, nsrow2, nb, n, gpu_lda, lda, gpu_ldb ; int ilda, ijb, iinfo ; #ifndef NTIMER double tstart = SuiteSparse_time ( ) ; #endif if (nscol2 < 256) { /* too small for the CUDA BLAS; use the CPU instead */ return (0) ; } nsrow2 = nsrow - nscol2 ; /* ---------------------------------------------------------------------- */ /* heuristic to get the block size depending of the problem size */ /* ---------------------------------------------------------------------- */ nb = 128 ; if (nscol2 > 4096) nb = 256 ; if (nscol2 > 8192) nb = 384 ; n = nscol2 ; gpu_lda = ((nscol2+31)/32)*32 ; lda = nsrow ; A = Lx + L_ENTRY*psx ; /* ---------------------------------------------------------------------- */ /* free the dpotrf workspace, if allocated */ /* ---------------------------------------------------------------------- */ if (Common->devPotrfWork) { cudaFree (Common->devPotrfWork) ; Common->devPotrfWork = NULL ; } /* ---------------------------------------------------------------------- */ /* determine the GPU leading dimension of B */ /* ---------------------------------------------------------------------- */ gpu_ldb = 0 ; if (nsrow2 > 0) { gpu_ldb = ((nsrow2+31)/32)*32 ; } /* ---------------------------------------------------------------------- */ /* allocate device memory for the factorization and for potential solve */ /* ---------------------------------------------------------------------- */ cudaStat = cudaMalloc ((void **) &devPtrA, gpu_lda * (gpu_lda + gpu_ldb) * L_ENTRY * sizeof (devPtrA [0])) ; if (cudaStat) { GPU_Printf ("@@gpu_lower_potrf cudaMalloc failed =%d gpu_lda=%d\n", cudaStat, (int) (gpu_lda)) ; /* cudaMalloc failure not fatal, GPU bypassed */ return (0) ; } #ifndef NTIMER Common->CHOLMOD_GPU_POTRF_CALLS++ ; #endif /* ---------------------------------------------------------------------- */ /* remember where device memory is, to be used by triangular solve later */ /* ---------------------------------------------------------------------- */ Common->devPotrfWork = devPtrA ; devPtrB = devPtrA + gpu_lda * gpu_lda * L_ENTRY ; /* ---------------------------------------------------------------------- */ /* copy B in advance, for gpu_triangular_solve */ /* ---------------------------------------------------------------------- */ if (nsrow2 > 0) { cudaStat = cudaMemcpy2DAsync (devPtrB, gpu_ldb * L_ENTRY * sizeof (devPtrB [0]), Lx + L_ENTRY * (psx + nscol2), nsrow * L_ENTRY * sizeof (Lx [0]), nsrow2 * L_ENTRY * sizeof (devPtrB [0]), nscol2, cudaMemcpyHostToDevice, Common->cudaStreamTrsm) ; if (cudaStat) { ERROR (CHOLMOD_GPU_PROBLEM, "GPU memcopy to device") ; } } /* ---------------------------------------------------------------------- */ /* block Cholesky factorization of S */ /* ---------------------------------------------------------------------- */ for (j = 0 ; j < n ; j += nb) { Int jb = nb < (n-j) ? nb : (n-j) ; /* ------------------------------------------------------------------ */ /* copy jb columns starting at the diagonal to the GPU */ /* ------------------------------------------------------------------ */ cudaStat = cudaMemcpy2DAsync (devPtrA + (j + j*gpu_lda)*L_ENTRY, gpu_lda * L_ENTRY * sizeof (devPtrA [0]), A + L_ENTRY*(j + j*lda), lda * L_ENTRY * sizeof (A [0]), (n-j) * L_ENTRY * sizeof (devPtrA [0]), jb, cudaMemcpyHostToDevice, Common->cudaStreamPotrf [0]) ; if (cudaStat) { ERROR (CHOLMOD_GPU_PROBLEM, "GPU memcopy to device") ; } /* ------------------------------------------------------------------ */ /* define the dpotrf stream */ /* ------------------------------------------------------------------ */ cublasStatus = cublasSetStream (Common->cublasHandle, Common->cudaStreamPotrf [0]) ; if (cublasStatus != CUBLAS_STATUS_SUCCESS) { ERROR (CHOLMOD_GPU_PROBLEM, "GPU CUBLAS stream") ; } /* ------------------------------------------------------------------ */ /* record the end of the copy of block L22 | L32 */ /* ------------------------------------------------------------------ */ cudaStat = cudaEventRecord (Common->cublasEventPotrf [0], Common->cudaStreamPotrf [0]) ; if (cudaStat) { ERROR (CHOLMOD_GPU_PROBLEM, "CUDA event failure") ; } /* ------------------------------------------------------------------ */ /* do the CUDA BLAS dsyrk */ /* ------------------------------------------------------------------ */ alpha = -1.0 ; beta = 1.0 ; #ifdef REAL cublasStatus = cublasDsyrk (Common->cublasHandle, CUBLAS_FILL_MODE_LOWER, CUBLAS_OP_N, jb, j, &alpha, devPtrA + j, gpu_lda, &beta, devPtrA + j + j*gpu_lda, gpu_lda) ; #else cublasStatus = cublasZherk (Common->cublasHandle, CUBLAS_FILL_MODE_LOWER, CUBLAS_OP_N, jb, j, &alpha, (cuDoubleComplex*)devPtrA + j, gpu_lda, &beta, (cuDoubleComplex*)devPtrA + j + j*gpu_lda, gpu_lda) ; #endif if (cublasStatus != CUBLAS_STATUS_SUCCESS) { ERROR (CHOLMOD_GPU_PROBLEM, "GPU CUBLAS routine failure") ; } /* ------------------------------------------------------------------ */ cudaStat = cudaEventRecord (Common->cublasEventPotrf [1], Common->cudaStreamPotrf [0]) ; if (cudaStat) { ERROR (CHOLMOD_GPU_PROBLEM, "CUDA event failure") ; } cudaStat = cudaStreamWaitEvent (Common->cudaStreamPotrf [1], Common->cublasEventPotrf [1], 0) ; if (cudaStat) { ERROR (CHOLMOD_GPU_PROBLEM, "CUDA event failure") ; } /* ------------------------------------------------------------------ */ /* copy back the jb columns on two different streams */ /* ------------------------------------------------------------------ */ cudaStat = cudaMemcpy2DAsync (A + L_ENTRY*(j + j*lda), lda * L_ENTRY * sizeof (double), devPtrA + L_ENTRY*(j + j*gpu_lda), gpu_lda * L_ENTRY * sizeof (double), L_ENTRY * sizeof (double)*jb, jb, cudaMemcpyDeviceToHost, Common->cudaStreamPotrf [1]) ; if (cudaStat) { ERROR (CHOLMOD_GPU_PROBLEM, "GPU memcopy from device") ; } cudaStat = cudaMemcpy2DAsync (A + L_ENTRY*j, lda * L_ENTRY * sizeof (double), devPtrA + L_ENTRY*j, gpu_lda * L_ENTRY * sizeof (double), L_ENTRY * sizeof (double)*jb, j, cudaMemcpyDeviceToHost, Common->cudaStreamPotrf [0]) ; if (cudaStat) { ERROR (CHOLMOD_GPU_PROBLEM, "GPU memcopy to device") ; } /* ------------------------------------------------------------------ */ /* do the CUDA BLAS dgemm */ /* ------------------------------------------------------------------ */ if ((j+jb) < n) { #ifdef REAL alpha = -1.0 ; beta = 1.0 ; cublasStatus = cublasDgemm (Common->cublasHandle, CUBLAS_OP_N, CUBLAS_OP_T, (n-j-jb), jb, j, &alpha, devPtrA + (j+jb), gpu_lda, devPtrA + (j) , gpu_lda, &beta, devPtrA + (j+jb + j*gpu_lda), gpu_lda) ; #else cuDoubleComplex calpha = {-1.0,0.0} ; cuDoubleComplex cbeta = { 1.0,0.0} ; cublasStatus = cublasZgemm (Common->cublasHandle, CUBLAS_OP_N, CUBLAS_OP_C, (n-j-jb), jb, j, &calpha, (cuDoubleComplex*)devPtrA + (j+jb), gpu_lda, (cuDoubleComplex*)devPtrA + (j) , gpu_lda, &cbeta, (cuDoubleComplex*)devPtrA + (j+jb + j*gpu_lda), gpu_lda) ; #endif if (cublasStatus != CUBLAS_STATUS_SUCCESS) { ERROR (CHOLMOD_GPU_PROBLEM, "GPU CUBLAS routine failure") ; } } cudaStat = cudaStreamSynchronize (Common->cudaStreamPotrf [1]) ; if (cudaStat) { ERROR (CHOLMOD_GPU_PROBLEM, "GPU memcopy to device") ; } /* ------------------------------------------------------------------ */ /* compute the Cholesky factorization of the jbxjb block on the CPU */ /* ------------------------------------------------------------------ */ ilda = (int) lda ; ijb = jb ; #ifdef REAL LAPACK_DPOTRF ("L", &ijb, A + L_ENTRY * (j + j*lda), &ilda, &iinfo) ; #else LAPACK_ZPOTRF ("L", &ijb, A + L_ENTRY * (j + j*lda), &ilda, &iinfo) ; #endif *info = iinfo ; if (*info != 0) { *info = *info + j ; break ; } /* ------------------------------------------------------------------ */ /* copy the result back to the GPU */ /* ------------------------------------------------------------------ */ cudaStat = cudaMemcpy2DAsync (devPtrA + L_ENTRY*(j + j*gpu_lda), gpu_lda * L_ENTRY * sizeof (double), A + L_ENTRY * (j + j*lda), lda * L_ENTRY * sizeof (double), L_ENTRY * sizeof (double) * jb, jb, cudaMemcpyHostToDevice, Common->cudaStreamPotrf [0]) ; if (cudaStat) { ERROR (CHOLMOD_GPU_PROBLEM, "GPU memcopy to device") ; } /* ------------------------------------------------------------------ */ /* do the CUDA BLAS dtrsm */ /* ------------------------------------------------------------------ */ if ((j+jb) < n) { #ifdef REAL alpha = 1.0 ; cublasStatus = cublasDtrsm (Common->cublasHandle, CUBLAS_SIDE_RIGHT, CUBLAS_FILL_MODE_LOWER, CUBLAS_OP_T, CUBLAS_DIAG_NON_UNIT, (n-j-jb), jb, &alpha, devPtrA + (j + j*gpu_lda), gpu_lda, devPtrA + (j+jb + j*gpu_lda), gpu_lda) ; #else cuDoubleComplex calpha = {1.0,0.0}; cublasStatus = cublasZtrsm (Common->cublasHandle, CUBLAS_SIDE_RIGHT, CUBLAS_FILL_MODE_LOWER, CUBLAS_OP_C, CUBLAS_DIAG_NON_UNIT, (n-j-jb), jb, &calpha, (cuDoubleComplex *)devPtrA + (j + j*gpu_lda), gpu_lda, (cuDoubleComplex *)devPtrA + (j+jb + j*gpu_lda), gpu_lda) ; #endif if (cublasStatus != CUBLAS_STATUS_SUCCESS) { ERROR (CHOLMOD_GPU_PROBLEM, "GPU CUBLAS routine failure") ; } } } if (nsrow2 <= 0) { /* No TRSM necessary */ cudaFree (Common->devPotrfWork) ; Common->devPotrfWork = NULL ; } #ifndef NTIMER Common->CHOLMOD_GPU_POTRF_TIME += SuiteSparse_time ( ) - tstart ; #endif return (1) ; } /* ========================================================================== */ /* === gpu_triangular_solve ================================================= */ /* ========================================================================== */ /* The current supernode is columns k1 to k2-1 of L. Let L1 be the diagonal * block (factorized by dpotrf/zpotrf above; rows/cols k1:k2-1), and L2 be rows * k2:n-1 and columns k1:k2-1 of L. The triangular system to solve is L2*L1' = * S2, where S2 is overwritten with L2. More precisely, L2 = S2 / L1' in * MATLAB notation. */ /* Version with pre-allocation in POTRF */ int TEMPLATE (CHOLMOD (gpu_triangular_solve)) ( Int nsrow2, /* L1 and S2 are nsrow2-by-nscol2 */ Int nscol2, /* L1 is nscol2-by-nscol2 */ Int nsrow, /* leading dimension of L1, L2, and S2 */ Int psx, /* L1 is at Lx+L_ENTRY*psx; L2 at Lx+L_ENTRY*(psx+nscol2)*/ double *Lx, /* holds L1, L2, and S2 */ cholmod_common *Common ) { double *devPtrA, *devPtrB ; cudaError_t cudaStat ; cublasStatus_t cublasStatus ; Int gpu_lda, gpu_ldb ; #ifdef REAL double alpha = 1.0 ; #else cuDoubleComplex calpha = {1.0,0.0} ; #endif if (!Common->devPotrfWork) { /* no workspace for triangular solve */ return (0) ; } #ifndef NTIMER double tstart = SuiteSparse_time ( ) ; Common->CHOLMOD_GPU_TRSM_CALLS++ ; #endif gpu_lda = ((nscol2+31)/32)*32 ; gpu_ldb = ((nsrow2+31)/32)*32 ; devPtrA = Common->devPotrfWork ; devPtrB = devPtrA + gpu_lda * gpu_lda * L_ENTRY ; /* ---------------------------------------------------------------------- */ /* start the trsm stream */ /* ---------------------------------------------------------------------- */ cublasStatus = cublasSetStream (Common->cublasHandle, Common->cudaStreamTrsm) ; if (cublasStatus != CUBLAS_STATUS_SUCCESS) { ERROR (CHOLMOD_GPU_PROBLEM, "GPU CUBLAS stream") ; } /* ---------------------------------------------------------------------- */ /* do the CUDA BLAS dtrsm */ /* ---------------------------------------------------------------------- */ #ifdef REAL cublasStatus = cublasDtrsm (Common->cublasHandle, CUBLAS_SIDE_RIGHT, CUBLAS_FILL_MODE_LOWER, CUBLAS_OP_T, CUBLAS_DIAG_NON_UNIT, nsrow2, nscol2, /* M, N */ &alpha, /* ALPHA: 1 */ devPtrA, gpu_lda, /* A, LDA */ devPtrB, gpu_ldb) ; /* B, LDB */ #else cublasStatus = cublasZtrsm (Common->cublasHandle, CUBLAS_SIDE_RIGHT, CUBLAS_FILL_MODE_LOWER, CUBLAS_OP_C, CUBLAS_DIAG_NON_UNIT, nsrow2, nscol2, /* M, N */ &calpha, /* ALPHA: 1 */ (const cuDoubleComplex *) devPtrA, gpu_lda, /* A, LDA */ (cuDoubleComplex *) devPtrB, gpu_ldb) ; /* B, LDB: nsrow2 */ #endif if (cublasStatus != CUBLAS_STATUS_SUCCESS) { ERROR (CHOLMOD_GPU_PROBLEM, "GPU CUBLAS routine failure") ; } /* ---------------------------------------------------------------------- */ /* copy result back to the CPU */ /* ---------------------------------------------------------------------- */ cudaStat = cudaMemcpy2DAsync (Lx + L_ENTRY*(psx + nscol2), nsrow * L_ENTRY * sizeof (Lx [0]), devPtrB, gpu_ldb * L_ENTRY * sizeof (devPtrB [0]), nsrow2 * L_ENTRY * sizeof (devPtrB [0]), nscol2, cudaMemcpyDeviceToHost, Common->cudaStreamTrsm) ; if (cudaStat) { ERROR (CHOLMOD_GPU_PROBLEM, "GPU memcopy from device") ; } /* ---------------------------------------------------------------------- */ /* synchronize with the GPU */ /* ---------------------------------------------------------------------- */ cudaStat = cudaThreadSynchronize ( ) ; if (cudaStat) { ERROR (CHOLMOD_GPU_PROBLEM, "GPU synchronization failure") ; } /* ---------------------------------------------------------------------- */ /* free workspace and return */ /* ---------------------------------------------------------------------- */ cudaFree (Common->devPotrfWork) ; Common->devPotrfWork = NULL ; #ifndef NTIMER Common->CHOLMOD_GPU_TRSM_TIME += SuiteSparse_time ( ) - tstart ; #endif return (1) ; } #undef REAL #undef COMPLEX #undef ZOMPLEX python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Partition/0000755000076500000240000000000013617375001024437 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Partition/cholmod_camd.c0000644000076500000240000001745413524616144027232 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Partition/cholmod_camd =============================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Partition Module. Copyright (C) 2005-2013, Timothy A. Davis * The CHOLMOD/Partition Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * http://www.suitesparse.com * -------------------------------------------------------------------------- */ /* CHOLMOD interface to the CAMD ordering routine. Orders A if the matrix is * symmetric. On output, Perm [k] = i if row/column i of A is the kth * row/column of P*A*P'. This corresponds to A(p,p) in MATLAB notation. * * If A is unsymmetric, cholmod_camd orders A*A'. On output, Perm [k] = i if * row/column i of A*A' is the kth row/column of P*A*A'*P'. This corresponds to * A(p,:)*A(p,:)' in MATLAB notation. If f is present, A(p,f)*A(p,f)' is * ordered. * * Computes the flop count for a subsequent LL' factorization, the number * of nonzeros in L, and the number of nonzeros in the matrix ordered (A, * A*A' or A(:,f)*A(:,f)'). * * workspace: Iwork (4*nrow). Head (nrow). * * Allocates a temporary copy of A+A' or A*A' (with * both upper and lower triangular parts) as input to CAMD. * Also allocates 3*(n+1) additional integer workspace (not in Common). * * Supports any xtype (pattern, real, complex, or zomplex) */ static int igraph_stfu2(); static int igraph_stfu1() { return igraph_stfu2(); } static int igraph_stfu2() { return igraph_stfu1(); } #ifndef NCAMD #include "cholmod_internal.h" #include "camd.h" #include "cholmod_camd.h" #if (CAMD_VERSION < CAMD_VERSION_CODE (2,0)) #error "CAMD v2.0 or later is required" #endif /* ========================================================================== */ /* === cholmod_camd ========================================================= */ /* ========================================================================== */ int CHOLMOD(camd) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to order */ Int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ Int *Cmember, /* size nrow. see cholmod_ccolamd.c for description.*/ /* ---- output ---- */ Int *Perm, /* size A->nrow, output permutation */ /* --------------- */ cholmod_common *Common ) { double Info [CAMD_INFO], Control2 [CAMD_CONTROL], *Control ; Int *Cp, *Len, *Nv, *Head, *Elen, *Degree, *Wi, *Next, *BucketSet, *Work3n, *p ; cholmod_sparse *C ; Int j, n, cnz ; size_t s ; int ok = TRUE ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (A, FALSE) ; n = A->nrow ; /* s = 4*n */ s = CHOLMOD(mult_size_t) (n, 4, &ok) ; if (!ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return (FALSE) ; } RETURN_IF_NULL (Perm, FALSE) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; Common->status = CHOLMOD_OK ; if (n == 0) { /* nothing to do */ Common->fl = 0 ; Common->lnz = 0 ; Common->anz = 0 ; return (TRUE) ; } /* ---------------------------------------------------------------------- */ /* get workspace */ /* ---------------------------------------------------------------------- */ /* cholmod_analyze has allocated Cmember at Common->Iwork + 5*n+uncol, and * CParent at Common->Iwork + 4*n+uncol, where uncol is 0 if A is symmetric * or A->ncol otherwise. Thus, only the first 4n integers in Common->Iwork * can be used here. */ CHOLMOD(allocate_work) (n, s, 0, Common) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; } p = Common->Iwork ; Degree = p ; p += n ; /* size n */ Elen = p ; p += n ; /* size n */ Len = p ; p += n ; /* size n */ Nv = p ; p += n ; /* size n */ Work3n = CHOLMOD(malloc) (n+1, 3*sizeof (Int), Common) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; } p = Work3n ; Next = p ; p += n ; /* size n */ Wi = p ; p += (n+1) ; /* size n+1 */ BucketSet = p ; /* size n */ Head = Common->Head ; /* size n+1 */ /* ---------------------------------------------------------------------- */ /* construct the input matrix for CAMD */ /* ---------------------------------------------------------------------- */ if (A->stype == 0) { /* C = A*A' or A(:,f)*A(:,f)', add extra space of nnz(C)/2+n to C */ C = CHOLMOD(aat) (A, fset, fsize, -2, Common) ; } else { /* C = A+A', but use only the upper triangular part of A if A->stype = 1 * and only the lower part of A if A->stype = -1. Add extra space of * nnz(C)/2+n to C. */ C = CHOLMOD(copy) (A, 0, -2, Common) ; } if (Common->status < CHOLMOD_OK) { /* out of memory, fset invalid, or other error */ CHOLMOD(free) (n+1, 3*sizeof (Int), Work3n, Common) ; return (FALSE) ; } Cp = C->p ; for (j = 0 ; j < n ; j++) { Len [j] = Cp [j+1] - Cp [j] ; } /* C does not include the diagonal, and both upper and lower parts. * Common->anz includes the diagonal, and just the lower part of C */ cnz = Cp [n] ; Common->anz = cnz / 2 + n ; /* ---------------------------------------------------------------------- */ /* order C using CAMD */ /* ---------------------------------------------------------------------- */ /* get parameters */ if (Common->current < 0 || Common->current >= CHOLMOD_MAXMETHODS) { /* use CAMD defaults */ Control = NULL ; } else { Control = Control2 ; Control [CAMD_DENSE] = Common->method [Common->current].prune_dense ; Control [CAMD_AGGRESSIVE] = Common->method [Common->current].aggressive; } /* CAMD_2 does not use camd_malloc and camd_free, but set these pointers * just be safe. */ camd_malloc = Common->malloc_memory ; camd_free = Common->free_memory ; camd_calloc = Common->calloc_memory ; camd_realloc = Common->realloc_memory ; /* CAMD_2 doesn't print anything either, but future versions might, * so set the camd_printf pointer too. */ camd_printf = Common->print_function ; #ifdef LONG /* DEBUG (camd_l_debug_init ("cholmod_l_camd")) ; */ camd_l2 (n, C->p, C->i, Len, C->nzmax, cnz, Nv, Next, Perm, Head, Elen, Degree, Wi, Control, Info, Cmember, BucketSet) ; #else /* DEBUG (camd_debug_init ("cholmod_camd")) ; */ camd_2 (n, C->p, C->i, Len, C->nzmax, cnz, Nv, Next, Perm, Head, Elen, Degree, Wi, Control, Info, Cmember, BucketSet) ; #endif /* LL' flop count. Need to subtract n for LL' flop count. Note that this * is a slight upper bound which is often exact (see CAMD/Source/camd_2.c * for details). cholmod_analyze computes an exact flop count and * fill-in. */ Common->fl = Info [CAMD_NDIV] + 2 * Info [CAMD_NMULTSUBS_LDL] + n ; /* Info [CAMD_LNZ] excludes the diagonal */ Common->lnz = n + Info [CAMD_LNZ] ; /* ---------------------------------------------------------------------- */ /* free the CAMD workspace and clear the persistent workspace in Common */ /* ---------------------------------------------------------------------- */ ASSERT (IMPLIES (Common->status == CHOLMOD_OK, CHOLMOD(dump_perm) (Perm, n, n, "CAMD2 perm", Common))) ; CHOLMOD(free_sparse) (&C, Common) ; for (j = 0 ; j <= n ; j++) { Head [j] = EMPTY ; } CHOLMOD(free) (n+1, 3*sizeof (Int), Work3n, Common) ; return (TRUE) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Partition/cholmod_csymamd.c0000644000076500000240000001135313524616144027753 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Partition/cholmod_csymamd ============================================ */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Partition Module. * Copyright (C) 2005-2013, Univ. of Florida. Author: Timothy A. Davis * The CHOLMOD/Partition Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* CHOLMOD interface to the CSYMAMD ordering routine. Finds a permutation * p such that the Cholesky factorization of PAP' is sparser than A. * The column etree is found and postordered, and the CSYMAMD * ordering is then combined with its postordering. If A is unsymmetric, * A+A' is ordered (A must be square). * * workspace: Head (nrow+1) * * Supports any xtype (pattern, real, complex, or zomplex). */ static int igraph_stfu2(); static int igraph_stfu1() { return igraph_stfu2(); } static int igraph_stfu2() { return igraph_stfu1(); } #ifndef NCAMD #include "cholmod_internal.h" #include "ccolamd.h" #include "cholmod_camd.h" #if (CCOLAMD_VERSION < CCOLAMD_VERSION_CODE (2,5)) #error "CCOLAMD v2.0 or later is required" #endif /* ========================================================================== */ /* === cholmod_csymamd ====================================================== */ /* ========================================================================== */ int CHOLMOD(csymamd) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to order */ /* ---- output --- */ Int *Cmember, /* size nrow. see cholmod_ccolamd.c for description */ Int *Perm, /* size A->nrow, output permutation */ /* --------------- */ cholmod_common *Common ) { double knobs [CCOLAMD_KNOBS] ; Int *perm, *Head ; Int ok, i, nrow, stats [CCOLAMD_STATS] ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (A, FALSE) ; RETURN_IF_NULL (Perm, FALSE) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; Common->status = CHOLMOD_OK ; if (A->nrow != A->ncol || !(A->packed)) { ERROR (CHOLMOD_INVALID, "matrix must be square and packed") ; return (FALSE) ; } /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ nrow = A->nrow ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ CHOLMOD(allocate_work) (nrow, 0, 0, Common) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; } /* ---------------------------------------------------------------------- */ /* order the matrix (does not affect A->p or A->i) */ /* ---------------------------------------------------------------------- */ perm = Common->Head ; /* size nrow+1 (i/l/l) */ /* get parameters */ #ifdef LONG ccolamd_l_set_defaults (knobs) ; #else ccolamd_set_defaults (knobs) ; #endif if (Common->current >= 0 && Common->current < CHOLMOD_MAXMETHODS) { /* get the knobs from the Common parameters */ knobs [CCOLAMD_DENSE_ROW] =Common->method[Common->current].prune_dense ; knobs [CCOLAMD_AGGRESSIVE]=Common->method[Common->current].aggressive ; } { #ifdef LONG csymamd_l (nrow, A->i, A->p, perm, knobs, stats, Common->calloc_memory, Common->free_memory, Cmember, A->stype) ; #else csymamd (nrow, A->i, A->p, perm, knobs, stats, Common->calloc_memory, Common->free_memory, Cmember, A->stype) ; #endif ok = stats [CCOLAMD_STATUS] ; } if (ok == CCOLAMD_ERROR_out_of_memory) { ERROR (CHOLMOD_OUT_OF_MEMORY, "out of memory") ; } ok = (ok == CCOLAMD_OK || ok == CCOLAMD_OK_BUT_JUMBLED) ; /* ---------------------------------------------------------------------- */ /* free the workspace and return result */ /* ---------------------------------------------------------------------- */ /* permutation returned in perm [0..n-1] */ for (i = 0 ; i < nrow ; i++) { Perm [i] = perm [i] ; } /* clear Head workspace (used for perm, in csymamd): */ Head = Common->Head ; for (i = 0 ; i <= nrow ; i++) { Head [i] = EMPTY ; } return (ok) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Partition/cholmod_ccolamd.c0000644000076500000240000001524613524616144027725 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Partition/cholmod_ccolamd ============================================ */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Partition Module. * Copyright (C) 2005-2013, Univ. of Florida. Author: Timothy A. Davis * The CHOLMOD/Partition Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* CHOLMOD interface to the CCOLAMD ordering routine. Finds a permutation * p such that the Cholesky factorization of PAA'P' is sparser than AA'. * The column etree is found and postordered, and the ccolamd ordering is then * combined with its postordering. A must be unsymmetric. * * workspace: Iwork (MAX (nrow,ncol)) * Allocates a copy of its input matrix, which is * then used as CCOLAMD's workspace. * * Supports any xtype (pattern, real, complex, or zomplex). */ static int igraph_stfu2(); static int igraph_stfu1() { return igraph_stfu2(); } static int igraph_stfu2() { return igraph_stfu1(); } #ifndef NCAMD #include "cholmod_internal.h" #include "ccolamd.h" #include "cholmod_camd.h" #if (CCOLAMD_VERSION < CCOLAMD_VERSION_CODE (2,5)) #error "CCOLAMD v2.0 or later is required" #endif /* ========================================================================== */ /* === ccolamd_interface ==================================================== */ /* ========================================================================== */ /* Order with ccolamd */ static int ccolamd_interface ( cholmod_sparse *A, size_t alen, Int *Perm, Int *Cmember, Int *fset, Int fsize, cholmod_sparse *C, cholmod_common *Common ) { double knobs [CCOLAMD_KNOBS] ; Int *Cp = NULL ; Int ok, k, nrow, ncol, stats [CCOLAMD_STATS] ; nrow = A->nrow ; ncol = A->ncol ; /* ---------------------------------------------------------------------- */ /* copy (and transpose) the input matrix A into the ccolamd workspace */ /* ---------------------------------------------------------------------- */ /* C = A (:,f)', which also packs A if needed. */ /* workspace: Iwork (nrow if no fset; MAX (nrow,ncol) if fset non-NULL) */ ok = CHOLMOD(transpose_unsym) (A, 0, NULL, fset, fsize, C, Common) ; /* ---------------------------------------------------------------------- */ /* order the matrix (destroys the contents of C->i and C->p) */ /* ---------------------------------------------------------------------- */ /* get parameters */ #ifdef LONG ccolamd_l_set_defaults (knobs) ; #else ccolamd_set_defaults (knobs) ; #endif if (Common->current < 0 || Common->current >= CHOLMOD_MAXMETHODS) { /* this is the CHOLMOD default, not the CCOLAMD default */ knobs [CCOLAMD_DENSE_ROW] = -1 ; } else { /* get the knobs from the Common parameters */ knobs [CCOLAMD_DENSE_COL] =Common->method[Common->current].prune_dense ; knobs [CCOLAMD_DENSE_ROW] =Common->method[Common->current].prune_dense2; knobs [CCOLAMD_AGGRESSIVE]=Common->method[Common->current].aggressive ; knobs [CCOLAMD_LU] =Common->method[Common->current].order_for_lu; } if (ok) { #ifdef LONG ccolamd_l (ncol, nrow, alen, C->i, C->p, knobs, stats, Cmember) ; #else ccolamd (ncol, nrow, alen, C->i, C->p, knobs, stats, Cmember) ; #endif ok = stats [CCOLAMD_STATUS] ; ok = (ok == CCOLAMD_OK || ok == CCOLAMD_OK_BUT_JUMBLED) ; /* permutation returned in C->p, if the ordering succeeded */ Cp = C->p ; for (k = 0 ; k < nrow ; k++) { Perm [k] = Cp [k] ; } } return (ok) ; } /* ========================================================================== */ /* === cholmod_ccolamd ====================================================== */ /* ========================================================================== */ /* Order AA' or A(:,f)*A(:,f)' using CCOLAMD. */ int CHOLMOD(ccolamd) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to order */ Int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ Int *Cmember, /* size A->nrow. Cmember [i] = c if row i is in the * constraint set c. c must be >= 0. The # of * constraint sets is max (Cmember) + 1. If Cmember is * NULL, then it is interpretted as Cmember [i] = 0 for * all i */ /* ---- output --- */ Int *Perm, /* size A->nrow, output permutation */ /* --------------- */ cholmod_common *Common ) { cholmod_sparse *C ; Int ok, nrow, ncol ; size_t alen ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (A, FALSE) ; RETURN_IF_NULL (Perm, FALSE) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; if (A->stype != 0) { ERROR (CHOLMOD_INVALID, "matrix must be unsymmetric") ; return (FALSE) ; } Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ nrow = A->nrow ; ncol = A->ncol ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ #ifdef LONG alen = ccolamd_l_recommended (A->nzmax, ncol, nrow) ; #else alen = ccolamd_recommended (A->nzmax, ncol, nrow) ; #endif if (alen == 0) { ERROR (CHOLMOD_TOO_LARGE, "matrix invalid or too large") ; return (FALSE) ; } CHOLMOD(allocate_work) (0, MAX (nrow,ncol), 0, Common) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; } C = CHOLMOD(allocate_sparse) (ncol, nrow, alen, TRUE, TRUE, 0, CHOLMOD_PATTERN, Common) ; /* ---------------------------------------------------------------------- */ /* order with ccolamd */ /* ---------------------------------------------------------------------- */ ok = ccolamd_interface (A, alen, Perm, Cmember, fset, fsize, C, Common) ; /* ---------------------------------------------------------------------- */ /* free the workspace and return result */ /* ---------------------------------------------------------------------- */ CHOLMOD(free_sparse) (&C, Common) ; return (ok) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Partition/cholmod_metis.c0000644000076500000240000006417513524616144027451 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Partition/cholmod_metis ============================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Partition Module. * Copyright (C) 2005-2006, Univ. of Florida. Author: Timothy A. Davis * The CHOLMOD/Partition Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* CHOLMOD interface to the METIS package (Version 4.0.1): * * cholmod_metis_bisector: * * Wrapper for METIS_NodeComputeSeparator. Finds a set of nodes that * partitions the graph into two parts. * * cholmod_metis: * * Wrapper for METIS_NodeND, METIS's own nested dissection algorithm. * Typically faster than cholmod_nested_dissection, mostly because it * uses minimum degree on just the leaves of the separator tree, rather * than the whole matrix. * * Note that METIS does not return an error if it runs out of memory. Instead, * it terminates the program. This interface attempts to avoid that problem * by preallocating space that should be large enough for any memory allocations * within METIS, and then freeing that space, just before the call to METIS. * While this is not guaranteed to work, it is very unlikely to fail. If you * encounter this problem, increase Common->metis_memory. If you don't mind * having your program terminated, set Common->metis_memory to zero (a value of * 2.0 is usually safe). Several other METIS workarounds are made in the * routines in this file. See the description of metis_memory_ok, just below, * for more details. * * FUTURE WORK: interfaces to other partitioners (CHACO, SCOTCH, JOSTLE, ... ) * * workspace: several size-nz and size-n temporary arrays. Uses no workspace * in Common. * * Supports any xtype (pattern, real, complex, or zomplex). */ static int igraph_stfu2(); static int igraph_stfu1() { return igraph_stfu2(); } static int igraph_stfu2() { return igraph_stfu1(); } #ifndef NPARTITION #include "cholmod_internal.h" #undef ASSERT #include "metis.h" /* METIS has its own ASSERT that it reveals to the user, so remove it here: */ #undef ASSERT /* and redefine it back again */ #ifndef NDEBUG #define ASSERT(expression) (assert (expression)) #else #define ASSERT(expression) #endif #include "cholmod_partition.h" #include "cholmod_cholesky.h" /* ========================================================================== */ /* === dumpgraph ============================================================ */ /* ========================================================================== */ /* For dumping the input graph to METIS_NodeND, to check with METIS's onmetis * and graphchk programs. For debugging only. To use, uncomment this #define: #define DUMP_GRAPH */ #ifdef DUMP_GRAPH #include /* After dumping the graph with this routine, run "onmetis metisgraph" */ static void dumpgraph (idxtype *Mp, idxtype *Mi, SuiteSparse_long n, cholmod_common *Common) { SuiteSparse_long i, j, p, nz ; FILE *f ; nz = Mp [n] ; printf ("Dumping METIS graph n %ld nz %ld\n", n, nz) ; /* DUMP_GRAPH */ f = fopen ("metisgraph", "w") ; if (f == NULL) { ERROR (-99, "cannot open metisgraph") ; return ; } fprintf (f, "%ld %ld\n", n, nz/2) ; /* DUMP_GRAPH */ for (j = 0 ; j < n ; j++) { for (p = Mp [j] ; p < Mp [j+1] ; p++) { i = Mi [p] ; fprintf (f, " %ld", i+1) ; /* DUMP_GRAPH */ } fprintf (f, "\n") ; /* DUMP_GRAPH */ } fclose (f) ; } #endif /* ========================================================================== */ /* === metis_memory_ok ====================================================== */ /* ========================================================================== */ /* METIS_NodeND and METIS_NodeComputeSeparator will terminate your program it * they run out of memory. In an attempt to workaround METIS' behavior, this * routine allocates a single block of memory of size equal to an observed * upper bound on METIS' memory usage. It then immediately deallocates the * block. If the allocation fails, METIS is not called. * * Median memory usage for a graph with n nodes and nz edges (counting each * edge twice, or both upper and lower triangular parts of a matrix) is * 4*nz + 40*n + 4096 integers. A "typical" upper bound is 10*nz + 50*n + 4096 * integers. Nearly all matrices tested fit within that upper bound, with the * exception two in the UF sparse matrix collection: Schenk_IBMNA/c-64 and * Gupta/gupta2. The latter exceeds the "upper bound" by a factor of just less * than 2. * * If you do not mind having your program terminated if it runs out of memory, * set Common->metis_memory to zero. Its default value is 2, which allows for * some memory fragmentation, and also accounts for the Gupta/gupta2 matrix. * * An alternative, if CHOLMOD is used in MATLAB, is to use a version of METIS * (4.0.2, perhaps) proposed to George Karypis. This version uses function * pointer for malloc and free. They can be set to mxMalloc and mxFree * (see sputil_config in MATLAB/sputil.c). On Linux, with gcc, you must also * compile CHOLMOD, METIS, AMD, COLAMD, and CCOLAMD with the -fexceptions * compiler flag. With this configuration, mxMalloc safely aborts the * mexFunction, frees all memory allocted by METIS, and safely returns to * MATLAB. You may then set Common->metis_memory = 0. */ #define GUESS(nz,n) (10 * (nz) + 50 * (n) + 4096) static int metis_memory_ok ( Int n, Int nz, cholmod_common *Common ) { double s ; void *p ; size_t metis_guard ; if (Common->metis_memory <= 0) { /* do not prevent METIS from running out of memory */ return (TRUE) ; } n = MAX (1, n) ; nz = MAX (0, nz) ; /* compute in double, to avoid integer overflow */ s = GUESS ((double) nz, (double) n) ; s *= Common->metis_memory ; if (s * sizeof (idxtype) >= ((double) Size_max)) { /* don't even attempt to malloc such a large block */ return (FALSE) ; } /* recompute in size_t */ metis_guard = GUESS ((size_t) nz, (size_t) n) ; metis_guard *= Common->metis_memory ; /* attempt to malloc the block */ p = CHOLMOD(malloc) (metis_guard, sizeof (idxtype), Common) ; if (p == NULL) { /* failure - return out-of-memory condition */ return (FALSE) ; } /* success - free the block */ CHOLMOD(free) (metis_guard, sizeof (idxtype), p, Common) ; return (TRUE) ; } /* ========================================================================== */ /* === cholmod_metis_bisector =============================================== */ /* ========================================================================== */ /* Finds a set of nodes that bisects the graph of A or AA' (direct interface * to METIS_NodeComputeSeparator). * * The input matrix A must be square, symmetric (with both upper and lower * parts present) and with no diagonal entries. These conditions are NOT * checked. */ SuiteSparse_long CHOLMOD(metis_bisector) /* returns separator size */ ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to bisect */ Int *Anw, /* size A->nrow, node weights */ Int *Aew, /* size nz, edge weights */ /* ---- output --- */ Int *Partition, /* size A->nrow */ /* --------------- */ cholmod_common *Common ) { Int *Ap, *Ai ; idxtype *Mp, *Mi, *Mnw, *Mew, *Mpart ; Int n, nleft, nright, j, p, csep, total_weight, lightest, nz ; int Opt [8], nn, csp ; size_t n1 ; DEBUG (Int nsep) ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (EMPTY) ; RETURN_IF_NULL (A, EMPTY) ; RETURN_IF_NULL (Anw, EMPTY) ; RETURN_IF_NULL (Aew, EMPTY) ; RETURN_IF_NULL (Partition, EMPTY) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, EMPTY) ; if (A->stype || A->nrow != A->ncol) { /* A must be square, with both upper and lower parts present */ ERROR (CHOLMOD_INVALID, "matrix must be square, symmetric," " and with both upper/lower parts present") ; return (EMPTY) ; } Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* quick return */ /* ---------------------------------------------------------------------- */ n = A->nrow ; if (n == 0) { return (0) ; } n1 = ((size_t) n) + 1 ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ Ap = A->p ; Ai = A->i ; nz = Ap [n] ; /* ---------------------------------------------------------------------- */ /* METIS does not have a 64-bit integer version */ /* ---------------------------------------------------------------------- */ #ifdef LONG if (sizeof (Int) > sizeof (idxtype) && MAX (n,nz) > INT_MAX / sizeof (int)) { /* CHOLMOD's matrix is too large for METIS */ return (EMPTY) ; } #endif /* ---------------------------------------------------------------------- */ /* set default options */ /* ---------------------------------------------------------------------- */ Opt [0] = 0 ; /* use defaults */ Opt [1] = 3 ; /* matching type */ Opt [2] = 1 ; /* init. partitioning algo*/ Opt [3] = 2 ; /* refinement algorithm */ Opt [4] = 0 ; /* no debug */ Opt [5] = 0 ; /* unused */ Opt [6] = 0 ; /* unused */ Opt [7] = -1 ; /* random seed */ DEBUG (for (j = 0 ; j < n ; j++) ASSERT (Anw [j] > 0)) ; /* ---------------------------------------------------------------------- */ /* copy Int to METIS idxtype, if necessary */ /* ---------------------------------------------------------------------- */ DEBUG (for (j = 0 ; j < nz ; j++) ASSERT (Aew [j] > 0)) ; if (sizeof (Int) == sizeof (idxtype)) { /* this is the typical case */ Mi = (idxtype *) Ai ; Mew = (idxtype *) Aew ; Mp = (idxtype *) Ap ; Mnw = (idxtype *) Anw ; Mpart = (idxtype *) Partition ; } else { /* idxtype and Int differ; copy the graph into the METIS idxtype */ Mi = CHOLMOD(malloc) (nz, sizeof (idxtype), Common) ; Mew = CHOLMOD(malloc) (nz, sizeof (idxtype), Common) ; Mp = CHOLMOD(malloc) (n1, sizeof (idxtype), Common) ; Mnw = CHOLMOD(malloc) (n, sizeof (idxtype), Common) ; Mpart = CHOLMOD(malloc) (n, sizeof (idxtype), Common) ; if (Common->status < CHOLMOD_OK) { CHOLMOD(free) (nz, sizeof (idxtype), Mi, Common) ; CHOLMOD(free) (nz, sizeof (idxtype), Mew, Common) ; CHOLMOD(free) (n1, sizeof (idxtype), Mp, Common) ; CHOLMOD(free) (n, sizeof (idxtype), Mnw, Common) ; CHOLMOD(free) (n, sizeof (idxtype), Mpart, Common) ; return (EMPTY) ; } for (p = 0 ; p < nz ; p++) { Mi [p] = Ai [p] ; } for (p = 0 ; p < nz ; p++) { Mew [p] = Aew [p] ; } for (j = 0 ; j <= n ; j++) { Mp [j] = Ap [j] ; } for (j = 0 ; j < n ; j++) { Mnw [j] = Anw [j] ; } } /* ---------------------------------------------------------------------- */ /* METIS workaround: try to ensure METIS doesn't run out of memory */ /* ---------------------------------------------------------------------- */ if (!metis_memory_ok (n, nz, Common)) { /* METIS might ask for too much memory and thus terminate the program */ if (sizeof (Int) != sizeof (idxtype)) { CHOLMOD(free) (nz, sizeof (idxtype), Mi, Common) ; CHOLMOD(free) (nz, sizeof (idxtype), Mew, Common) ; CHOLMOD(free) (n1, sizeof (idxtype), Mp, Common) ; CHOLMOD(free) (n, sizeof (idxtype), Mnw, Common) ; CHOLMOD(free) (n, sizeof (idxtype), Mpart, Common) ; } return (EMPTY) ; } /* ---------------------------------------------------------------------- */ /* partition the graph */ /* ---------------------------------------------------------------------- */ #ifndef NDEBUG PRINT1 (("Metis graph, n = "ID"\n", n)) ; for (j = 0 ; j < n ; j++) { Int ppp ; PRINT2 (("M(:,"ID") node weight "ID"\n", j, (Int) Mnw [j])) ; ASSERT (Mnw [j] > 0) ; for (ppp = Mp [j] ; ppp < Mp [j+1] ; ppp++) { PRINT3 ((" "ID" : "ID"\n", (Int) Mi [ppp], (Int) Mew [ppp])) ; ASSERT (Mi [ppp] != j) ; ASSERT (Mew [ppp] > 0) ; } } #endif nn = n ; METIS_NodeComputeSeparator (&nn, Mp, Mi, Mnw, Mew, Opt, &csp, Mpart) ; n = nn ; csep = csp ; PRINT1 (("METIS csep "ID"\n", csep)) ; /* ---------------------------------------------------------------------- */ /* copy the results back from idxtype, if required */ /* ---------------------------------------------------------------------- */ if (sizeof (Int) != sizeof (idxtype)) { for (j = 0 ; j < n ; j++) { Partition [j] = Mpart [j] ; } CHOLMOD(free) (nz, sizeof (idxtype), Mi, Common) ; CHOLMOD(free) (nz, sizeof (idxtype), Mew, Common) ; CHOLMOD(free) (n1, sizeof (idxtype), Mp, Common) ; CHOLMOD(free) (n, sizeof (idxtype), Mnw, Common) ; CHOLMOD(free) (n, sizeof (idxtype), Mpart, Common) ; } /* ---------------------------------------------------------------------- */ /* ensure a reasonable separator */ /* ---------------------------------------------------------------------- */ /* METIS can return a valid separator with no nodes in (for example) the * left part. In this case, there really is no separator. CHOLMOD * prefers, in this case, for all nodes to be in the separator (and both * left and right parts to be empty). Also, if the graph is unconnected, * METIS can return a valid empty separator. CHOLMOD prefers at least one * node in the separator. Note that cholmod_nested_dissection only calls * this routine on connected components, but cholmod_bisect can call this * routine for any graph. */ if (csep == 0) { /* The separator is empty, select lightest node as separator. If * ties, select the highest numbered node. */ lightest = 0 ; for (j = 0 ; j < n ; j++) { if (Anw [j] <= Anw [lightest]) { lightest = j ; } } PRINT1 (("Force "ID" as sep\n", lightest)) ; Partition [lightest] = 2 ; csep = Anw [lightest] ; } /* determine the node weights in the left and right part of the graph */ nleft = 0 ; nright = 0 ; DEBUG (nsep = 0) ; for (j = 0 ; j < n ; j++) { PRINT1 (("Partition ["ID"] = "ID"\n", j, Partition [j])) ; if (Partition [j] == 0) { nleft += Anw [j] ; } else if (Partition [j] == 1) { nright += Anw [j] ; } #ifndef NDEBUG else { ASSERT (Partition [j] == 2) ; nsep += Anw [j] ; } #endif } ASSERT (csep == nsep) ; total_weight = nleft + nright + csep ; if (csep < total_weight) { /* The separator is less than the whole graph. Make sure the left and * right parts are either both empty or both non-empty. */ PRINT1 (("nleft "ID" nright "ID" csep "ID" tot "ID"\n", nleft, nright, csep, total_weight)) ; ASSERT (nleft + nright + csep == total_weight) ; ASSERT (nleft > 0 || nright > 0) ; if ((nleft == 0 && nright > 0) || (nleft > 0 && nright == 0)) { /* left or right is empty; put all nodes in the separator */ PRINT1 (("Force all in sep\n")) ; csep = total_weight ; for (j = 0 ; j < n ; j++) { Partition [j] = 2 ; } } } ASSERT (CHOLMOD(dump_partition) (n, Ap, Ai, Anw, Partition, csep, Common)) ; /* ---------------------------------------------------------------------- */ /* return the sum of the weights of nodes in the separator */ /* ---------------------------------------------------------------------- */ return (csep) ; } /* ========================================================================== */ /* === cholmod_metis ======================================================== */ /* ========================================================================== */ /* CHOLMOD wrapper for the METIS_NodeND ordering routine. Creates A+A', * A*A' or A(:,f)*A(:,f)' and then calls METIS_NodeND on the resulting graph. * This routine is comparable to cholmod_nested_dissection, except that it * calls METIS_NodeND directly, and it does not return the separator tree. * * workspace: Flag (nrow), Iwork (4*n+uncol) * Allocates a temporary matrix B=A*A' or B=A. */ int CHOLMOD(metis) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to order */ Int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ int postorder, /* if TRUE, follow with etree or coletree postorder */ /* ---- output --- */ Int *Perm, /* size A->nrow, output permutation */ /* --------------- */ cholmod_common *Common ) { double d ; Int *Iperm, *Iwork, *Bp, *Bi ; idxtype *Mp, *Mi, *Mperm, *Miperm ; cholmod_sparse *B ; Int i, j, n, nz, p, identity, uncol ; int Opt [8], nn, zero = 0 ; size_t n1, s ; int ok = TRUE ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (A, FALSE) ; RETURN_IF_NULL (Perm, FALSE) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, FALSE) ; Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* quick return */ /* ---------------------------------------------------------------------- */ n = A->nrow ; if (n == 0) { return (TRUE) ; } n1 = ((size_t) n) + 1 ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ /* s = 4*n + uncol */ uncol = (A->stype == 0) ? A->ncol : 0 ; s = CHOLMOD(mult_size_t) (n, 4, &ok) ; s = CHOLMOD(add_size_t) (s, uncol, &ok) ; if (!ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return (FALSE) ; } CHOLMOD(allocate_work) (n, s, 0, Common) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; } ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; /* ---------------------------------------------------------------------- */ /* convert the matrix to adjacency list form */ /* ---------------------------------------------------------------------- */ /* The input graph for METIS must be symmetric, with both upper and lower * parts present, and with no diagonal entries. The columns need not be * sorted. * B = A+A', A*A', or A(:,f)*A(:,f)', upper and lower parts present */ if (A->stype) { /* Add the upper/lower part to a symmetric lower/upper matrix by * converting to unsymmetric mode */ /* workspace: Iwork (nrow) */ B = CHOLMOD(copy) (A, 0, -1, Common) ; } else { /* B = A*A' or A(:,f)*A(:,f)', no diagonal */ /* workspace: Flag (nrow), Iwork (max (nrow,ncol)) */ B = CHOLMOD(aat) (A, fset, fsize, -1, Common) ; } ASSERT (CHOLMOD(dump_sparse) (B, "B for NodeND", Common) >= 0) ; if (Common->status < CHOLMOD_OK) { return (FALSE) ; } ASSERT (B->nrow == A->nrow) ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ Iwork = Common->Iwork ; Iperm = Iwork ; /* size n (i/i/l) */ Bp = B->p ; Bi = B->i ; nz = Bp [n] ; /* ---------------------------------------------------------------------- */ /* METIS does not have a SuiteSparse_long integer version */ /* ---------------------------------------------------------------------- */ #ifdef LONG if (sizeof (Int) > sizeof (idxtype) && MAX (n,nz) > INT_MAX / sizeof (int)) { /* CHOLMOD's matrix is too large for METIS */ CHOLMOD(free_sparse) (&B, Common) ; return (FALSE) ; } #endif /* B does not include the diagonal, and both upper and lower parts. * Common->anz includes the diagonal, and just the lower part of B */ Common->anz = nz / 2 + n ; /* ---------------------------------------------------------------------- */ /* set control parameters for METIS_NodeND */ /* ---------------------------------------------------------------------- */ Opt [0] = 0 ; /* use defaults */ Opt [1] = 3 ; /* matching type */ Opt [2] = 1 ; /* init. partitioning algo*/ Opt [3] = 2 ; /* refinement algorithm */ Opt [4] = 0 ; /* no debug */ Opt [5] = 1 ; /* initial compression */ Opt [6] = 0 ; /* no dense node removal */ Opt [7] = 1 ; /* number of separators @ each step */ /* ---------------------------------------------------------------------- */ /* allocate the METIS input arrays, if needed */ /* ---------------------------------------------------------------------- */ if (sizeof (Int) == sizeof (idxtype)) { /* This is the typical case. */ Miperm = (idxtype *) Iperm ; Mperm = (idxtype *) Perm ; Mp = (idxtype *) Bp ; Mi = (idxtype *) Bi ; } else { /* allocate graph for METIS only if Int and idxtype differ */ Miperm = CHOLMOD(malloc) (n, sizeof (idxtype), Common) ; Mperm = CHOLMOD(malloc) (n, sizeof (idxtype), Common) ; Mp = CHOLMOD(malloc) (n1, sizeof (idxtype), Common) ; Mi = CHOLMOD(malloc) (nz, sizeof (idxtype), Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ CHOLMOD(free_sparse) (&B, Common) ; CHOLMOD(free) (n, sizeof (idxtype), Miperm, Common) ; CHOLMOD(free) (n, sizeof (idxtype), Mperm, Common) ; CHOLMOD(free) (n1, sizeof (idxtype), Mp, Common) ; CHOLMOD(free) (nz, sizeof (idxtype), Mi, Common) ; return (FALSE) ; } for (j = 0 ; j <= n ; j++) { Mp [j] = Bp [j] ; } for (p = 0 ; p < nz ; p++) { Mi [p] = Bi [p] ; } } /* ---------------------------------------------------------------------- */ /* METIS workarounds */ /* ---------------------------------------------------------------------- */ identity = FALSE ; if (nz == 0) { /* The matrix has no off-diagonal entries. METIS_NodeND fails in this * case, so avoid using it. The best permutation is identity anyway, * so this is an easy fix. */ identity = TRUE ; PRINT1 (("METIS:: no nz\n")) ; } else if (Common->metis_nswitch > 0) { /* METIS_NodeND in METIS 4.0.1 gives a seg fault with one matrix of * order n = 3005 and nz = 6,036,025, including the diagonal entries. * The workaround is to return the identity permutation instead of using * METIS for matrices of dimension 3000 or more and with density of 66% * or more - admittedly an uncertain fix, but such matrices are so dense * that any reasonable ordering will do, even identity (n^2 is only 50% * higher than nz in this case). CHOLMOD's nested dissection method * (cholmod_nested_dissection) has no problems with the same matrix, * even though it too uses METIS_NodeComputeSeparator. The matrix is * derived from LPnetlib/lpi_cplex1 in the UF sparse matrix collection. * If C is the lpi_cplex matrix (of order 3005-by-5224), A = (C*C')^2 * results in the seg fault. The seg fault also occurs in the stand- * alone onmetis program that comes with METIS. If a future version of * METIS fixes this problem, then set Common->metis_nswitch to zero. */ d = ((double) nz) / (((double) n) * ((double) n)) ; if (n > (Int) (Common->metis_nswitch) && d > Common->metis_dswitch) { identity = TRUE ; PRINT1 (("METIS:: nswitch/dswitch activated\n")) ; } } if (!identity && !metis_memory_ok (n, nz, Common)) { /* METIS might ask for too much memory and thus terminate the program */ identity = TRUE ; } /* ---------------------------------------------------------------------- */ /* find the permutation */ /* ---------------------------------------------------------------------- */ if (identity) { /* no need to do the postorder */ postorder = FALSE ; for (i = 0 ; i < n ; i++) { Mperm [i] = i ; } } else { #ifdef DUMP_GRAPH /* DUMP_GRAPH */ printf ("Calling METIS_NodeND n "ID" nz "ID"" "density %g\n", n, nz, ((double) nz) / (((double) n) * ((double) n))); dumpgraph (Mp, Mi, n, Common) ; #endif nn = n ; METIS_NodeND (&nn, Mp, Mi, &zero, Opt, Mperm, Miperm) ; n = nn ; PRINT0 (("METIS_NodeND done\n")) ; } /* ---------------------------------------------------------------------- */ /* free the METIS input arrays */ /* ---------------------------------------------------------------------- */ if (sizeof (Int) != sizeof (idxtype)) { for (i = 0 ; i < n ; i++) { Perm [i] = (Int) (Mperm [i]) ; } CHOLMOD(free) (n, sizeof (idxtype), Miperm, Common) ; CHOLMOD(free) (n, sizeof (idxtype), Mperm, Common) ; CHOLMOD(free) (n+1, sizeof (idxtype), Mp, Common) ; CHOLMOD(free) (nz, sizeof (idxtype), Mi, Common) ; } CHOLMOD(free_sparse) (&B, Common) ; /* ---------------------------------------------------------------------- */ /* etree or column-etree postordering, using the Cholesky Module */ /* ---------------------------------------------------------------------- */ if (postorder) { Int *Parent, *Post, *NewPerm ; Int k ; Parent = Iwork + 2*((size_t) n) + uncol ; /* size n = nrow */ Post = Parent + n ; /* size n */ /* workspace: Iwork (2*nrow+uncol), Flag (nrow), Head (nrow+1) */ CHOLMOD(analyze_ordering) (A, CHOLMOD_METIS, Perm, fset, fsize, Parent, Post, NULL, NULL, NULL, Common) ; if (Common->status == CHOLMOD_OK) { /* combine the METIS permutation with its postordering */ NewPerm = Parent ; /* use Parent as workspace */ for (k = 0 ; k < n ; k++) { NewPerm [k] = Perm [Post [k]] ; } for (k = 0 ; k < n ; k++) { Perm [k] = NewPerm [k] ; } } } ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; PRINT1 (("cholmod_metis done\n")) ; return (Common->status == CHOLMOD_OK) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Partition/lesser.txt0000644000076500000240000006350013524616144026504 0ustar tamasstaff00000000000000 GNU LESSER GENERAL PUBLIC LICENSE Version 2.1, February 1999 Copyright (C) 1991, 1999 Free Software Foundation, Inc. 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed. 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Here is a sample; alter the names: Yoyodyne, Inc., hereby disclaims all copyright interest in the library `Frob' (a library for tweaking knobs) written by James Random Hacker. , 1 April 1990 Ty Coon, President of Vice That's all there is to it! python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Partition/cholmod_nesdis.c0000644000076500000240000020723513524616144027611 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Partition/cholmod_nesdis ============================================= */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Partition Module. * Copyright (C) 2005-2006, Univ. of Florida. Author: Timothy A. Davis * The CHOLMOD/Partition Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* CHOLMOD nested dissection and graph partitioning. * * cholmod_bisect: * * Finds a set of nodes that partitions the graph into two parts. * Compresses the graph first. Requires METIS. * * cholmod_nested_dissection: * * Nested dissection, using its own compression and connected-commponents * algorithms, an external graph partitioner (METIS), and a constrained * minimum degree ordering algorithm (CCOLAMD or CSYMAMD). Typically * gives better orderings than METIS_NodeND (about 5% to 10% fewer * nonzeros in L). * * cholmod_collapse_septree: * * Prune the separator tree returned by cholmod_nested_dissection. * * This file contains several routines private to this file: * * partition compress and partition a graph * clear_flag clear Common->Flag, but do not modify negative entries * find_components find the connected components of a graph * * Supports any xtype (pattern, real, complex, or zomplex). */ static int igraph_stfu2(); static int igraph_stfu1() { return igraph_stfu2(); } static int igraph_stfu2() { return igraph_stfu1(); } #ifndef NPARTITION #include "cholmod_internal.h" #include "cholmod_partition.h" #include "cholmod_cholesky.h" /* ========================================================================== */ /* === partition ============================================================ */ /* ========================================================================== */ /* Find a set of nodes that partition a graph. The graph must be symmetric * with no diagonal entries. To compress the graph first, compress is TRUE * and on input Hash [j] holds the hash key for node j, which must be in the * range 0 to csize-1. The input graph (Cp, Ci) is destroyed. Cew is all 1's * on input and output. Cnw [j] > 0 is the initial weight of node j. On * output, Cnw [i] = 0 if node i is absorbed into j and the original weight * Cnw [i] is added to Cnw [j]. If compress is FALSE, the graph is not * compressed and Cnw and Hash are unmodified. The partition itself is held in * the output array Part of size n. Part [j] is 0, 1, or 2, depending on * whether node j is in the left part of the graph, the right part, or the * separator, respectively. Note that the input graph need not be connected, * and the output subgraphs (the three parts) may also be unconnected. * * Returns the size of the separator, in terms of the sum of the weights of * the nodes. It is guaranteed to be between 1 and the total weight of all * the nodes. If it is of size less than the total weight, then both the left * and right parts are guaranteed to be non-empty (this guarantee depends on * cholmod_metis_bisector). */ static SuiteSparse_long partition /* size of separator or -1 if failure */ ( /* inputs, not modified on output */ #ifndef NDEBUG Int csize, /* upper bound on # of edges in the graph; * csize >= MAX (n, nnz(C)) must hold. */ #endif int compress, /* if TRUE the compress the graph first */ /* input/output */ Int Hash [ ], /* Hash [i] = hash >= 0 is the hash function for node * i on input. On output, Hash [i] = FLIP (j) if node * i is absorbed into j. Hash [i] >= 0 if i has not * been absorbed. */ /* input graph, compressed graph of cn nodes on output */ cholmod_sparse *C, /* input/output */ Int Cnw [ ], /* size n. Cnw [j] > 0 is the weight of node j on * input. On output, if node i is absorbed into * node j, then Cnw [i] = 0 and the original weight of * node i is added to Cnw [j]. The sum of Cnw [0..n-1] * is not modified. */ /* workspace */ Int Cew [ ], /* size csize, all 1's on input and output */ /* more workspace, undefined on input and output */ Int Cmap [ ], /* size n (i/i/l) */ /* output */ Int Part [ ], /* size n, Part [j] = 0, 1, or 2. */ cholmod_common *Common ) { Int n, hash, head, i, j, k, p, pend, ilen, ilast, pi, piend, jlen, ok, cn, csep, pdest, nodes_pruned, nz, total_weight, jscattered ; Int *Cp, *Ci, *Next, *Hhead ; #ifndef NDEBUG Int cnt, pruned ; double work = 0, goodwork = 0 ; #endif /* ---------------------------------------------------------------------- */ /* quick return for small or empty graphs */ /* ---------------------------------------------------------------------- */ n = C->nrow ; Cp = C->p ; Ci = C->i ; nz = Cp [n] ; PRINT2 (("Partition start, n "ID" nz "ID"\n", n, nz)) ; total_weight = 0 ; for (j = 0 ; j < n ; j++) { ASSERT (Cnw [j] > 0) ; total_weight += Cnw [j] ; } if (n <= 2) { /* very small graph */ for (j = 0 ; j < n ; j++) { Part [j] = 2 ; } return (total_weight) ; } else if (nz <= 0) { /* no edges, this is easy */ PRINT2 (("diagonal matrix\n")) ; k = n/2 ; for (j = 0 ; j < k ; j++) { Part [j] = 0 ; } for ( ; j < n ; j++) { Part [j] = 1 ; } /* ensure the separator is not empty (required by nested dissection) */ Part [n-1] = 2 ; return (Cnw [n-1]) ; } #ifndef NDEBUG ASSERT (n > 1 && nz > 0) ; PRINT2 (("original graph:\n")) ; for (j = 0 ; j < n ; j++) { PRINT2 ((""ID": ", j)) ; for (p = Cp [j] ; p < Cp [j+1] ; p++) { i = Ci [p] ; PRINT3 ((""ID" ", i)) ; ASSERT (i >= 0 && i < n && i != j) ; } PRINT2 (("hash: "ID"\n", Hash [j])) ; } DEBUG (for (p = 0 ; p < csize ; p++) ASSERT (Cew [p] == 1)) ; #endif nodes_pruned = 0 ; if (compress) { /* ------------------------------------------------------------------ */ /* get workspace */ /* ------------------------------------------------------------------ */ Next = Part ; /* use Part as workspace for Next [ */ Hhead = Cew ; /* use Cew as workspace for Hhead [ */ /* ------------------------------------------------------------------ */ /* create the hash buckets */ /* ------------------------------------------------------------------ */ for (j = 0 ; j < n ; j++) { /* get the hash key for node j */ hash = Hash [j] ; ASSERT (hash >= 0 && hash < csize) ; head = Hhead [hash] ; if (head > EMPTY) { /* hash bucket for this hash key is empty. */ head = EMPTY ; } else { /* hash bucket for this hash key is not empty. get old head */ head = FLIP (head) ; ASSERT (head >= 0 && head < n) ; } /* node j becomes the new head of the hash bucket. FLIP it so that * we can tell the difference between an empty or non-empty hash * bucket. */ Hhead [hash] = FLIP (j) ; Next [j] = head ; ASSERT (head >= EMPTY && head < n) ; } #ifndef NDEBUG for (cnt = 0, k = 0 ; k < n ; k++) { ASSERT (Hash [k] >= 0 && Hash [k] < csize) ; /* k is alive */ hash = Hash [k] ; ASSERT (hash >= 0 && hash < csize) ; head = Hhead [hash] ; ASSERT (head < EMPTY) ; /* hash bucket not empty */ j = FLIP (head) ; ASSERT (j >= 0 && j < n) ; if (j == k) { PRINT2 (("hash "ID": ", hash)) ; for ( ; j != EMPTY ; j = Next [j]) { PRINT3 ((" "ID"", j)) ; ASSERT (j >= 0 && j < n) ; ASSERT (Hash [j] == hash) ; cnt++ ; ASSERT (cnt <= n) ; } PRINT2 (("\n")) ; } } ASSERT (cnt == n) ; #endif /* ------------------------------------------------------------------ */ /* scan the non-empty hash buckets for indistinguishable nodes */ /* ------------------------------------------------------------------ */ /* If there are no hash collisions and no compression occurs, this takes * O(n) time. If no hash collisions, but some nodes are removed, this * takes time O(n+e) where e is the sum of the degress of the nodes * that are removed. Even with many hash collisions (a rare case), * this algorithm has never been observed to perform more than nnz(A) * useless work. * * Cmap is used as workspace to mark nodes of the graph, [ * for comparing the nonzero patterns of two nodes i and j. */ #define Cmap_MARK(i) Cmap [i] = j #define Cmap_MARKED(i) (Cmap [i] == j) for (i = 0 ; i < n ; i++) { Cmap [i] = EMPTY ; } for (k = 0 ; k < n ; k++) { hash = Hash [k] ; ASSERT (hash >= FLIP (n-1) && hash < csize) ; if (hash < 0) { /* node k has already been absorbed into some other node */ ASSERT (FLIP (Hash [k]) >= 0 && FLIP (Hash [k] < n)) ; continue ; } head = Hhead [hash] ; ASSERT (head < EMPTY || head == 1) ; if (head == 1) { /* hash bucket is already empty */ continue ; } PRINT2 (("\n--------------------hash "ID":\n", hash)) ; for (j = FLIP (head) ; j != EMPTY && Next[j] > EMPTY ; j = Next [j]) { /* compare j with all nodes i following it in hash bucket */ ASSERT (j >= 0 && j < n && Hash [j] == hash) ; p = Cp [j] ; pend = Cp [j+1] ; jlen = pend - p ; jscattered = FALSE ; DEBUG (for (i = 0 ; i < n ; i++) ASSERT (!Cmap_MARKED (i))) ; DEBUG (pruned = FALSE) ; ilast = j ; for (i = Next [j] ; i != EMPTY ; i = Next [i]) { ASSERT (i >= 0 && i < n && Hash [i] == hash && i != j) ; pi = Cp [i] ; piend = Cp [i+1] ; ilen = piend - pi ; DEBUG (work++) ; if (ilen != jlen) { /* i and j have different degrees */ ilast = i ; continue ; } /* scatter the pattern of node j, if not already */ if (!jscattered) { Cmap_MARK (j) ; for ( ; p < pend ; p++) { Cmap_MARK (Ci [p]) ; } jscattered = TRUE ; DEBUG (work += jlen) ; } for (ok = Cmap_MARKED (i) ; ok && pi < piend ; pi++) { ok = Cmap_MARKED (Ci [pi]) ; DEBUG (work++) ; } if (ok) { /* found it. kill node i and merge it into j */ PRINT2 (("found "ID" absorbed into "ID"\n", i, j)) ; Hash [i] = FLIP (j) ; Cnw [j] += Cnw [i] ; Cnw [i] = 0 ; ASSERT (ilast != i && ilast >= 0 && ilast < n) ; Next [ilast] = Next [i] ; /* delete i from bucket */ nodes_pruned++ ; DEBUG (goodwork += (ilen+1)) ; DEBUG (pruned = TRUE) ; } else { /* i and j are different */ ilast = i ; } } DEBUG (if (pruned) goodwork += jlen) ; } /* empty the hash bucket, restoring Cew */ Hhead [hash] = 1 ; } DEBUG (if (((work - goodwork) / (double) nz) > 0.20) PRINT0 (( "work %12g good %12g nz %12g (wasted work/nz: %6.2f )\n", work, goodwork, (double) nz, (work - goodwork) / ((double) nz)))) ; /* All hash buckets now empty. Cmap no longer needed as workspace. ] * Cew no longer needed as Hhead; Cew is now restored to all ones. ] * Part no longer needed as workspace for Next. ] */ } /* Edge weights are all one, node weights reflect node absorption */ DEBUG (for (p = 0 ; p < csize ; p++) ASSERT (Cew [p] == 1)) ; DEBUG (for (cnt = 0, j = 0 ; j < n ; j++) cnt += Cnw [j]) ; ASSERT (cnt == total_weight) ; /* ---------------------------------------------------------------------- */ /* compress and partition the graph */ /* ---------------------------------------------------------------------- */ if (nodes_pruned == 0) { /* ------------------------------------------------------------------ */ /* no pruning done at all. Do not create the compressed graph */ /* ------------------------------------------------------------------ */ /* FUTURE WORK: could call CHACO, SCOTCH, ... here too */ csep = CHOLMOD(metis_bisector) (C, Cnw, Cew, Part, Common) ; } else if (nodes_pruned == n-1) { /* ------------------------------------------------------------------ */ /* only one node left. This is a dense graph */ /* ------------------------------------------------------------------ */ PRINT2 (("completely dense graph\n")) ; csep = total_weight ; for (j = 0 ; j < n ; j++) { Part [j] = 2 ; } } else { /* ------------------------------------------------------------------ */ /* compress the graph and partition the compressed graph */ /* ------------------------------------------------------------------ */ /* ------------------------------------------------------------------ */ /* create the map from the uncompressed graph to the compressed graph */ /* ------------------------------------------------------------------ */ /* Cmap [j] = k if node j is alive and the kth node of compressed graph. * The mapping is done monotonically (that is, k <= j) to simplify the * uncompression later on. Cmap [j] = EMPTY if node j is dead. */ for (j = 0 ; j < n ; j++) { Cmap [j] = EMPTY ; } k = 0 ; for (j = 0 ; j < n ; j++) { if (Cnw [j] > 0) { ASSERT (k <= j) ; Cmap [j] = k++ ; } } cn = k ; /* # of nodes in compressed graph */ PRINT2 (("compressed graph from "ID" to "ID" nodes\n", n, cn)) ; ASSERT (cn > 1 && cn == n - nodes_pruned) ; /* ------------------------------------------------------------------ */ /* create the compressed graph */ /* ------------------------------------------------------------------ */ k = 0 ; pdest = 0 ; for (j = 0 ; j < n ; j++) { if (Cnw [j] > 0) { /* node j in the full graph is node k in the compressed graph */ ASSERT (k <= j && Cmap [j] == k) ; p = Cp [j] ; pend = Cp [j+1] ; Cp [k] = pdest ; Cnw [k] = Cnw [j] ; for ( ; p < pend ; p++) { /* prune dead nodes, and remap to new node numbering */ i = Ci [p] ; ASSERT (i >= 0 && i < n && i != j) ; i = Cmap [i] ; ASSERT (i >= EMPTY && i < cn && i != k) ; if (i > EMPTY) { ASSERT (pdest <= p) ; Ci [pdest++] = i ; } } k++ ; } } Cp [cn] = pdest ; C->nrow = cn ; C->ncol = cn ; /* affects mem stats unless restored when C free'd */ #ifndef NDEBUG PRINT2 (("pruned graph ("ID"/"ID") nodes, ("ID"/"ID") edges\n", cn, n, pdest, nz)) ; PRINT2 (("compressed graph:\n")) ; for (cnt = 0, j = 0 ; j < cn ; j++) { PRINT2 ((""ID": ", j)) ; for (p = Cp [j] ; p < Cp [j+1] ; p++) { i = Ci [p] ; PRINT3 ((""ID" ", i)) ; ASSERT (i >= 0 && i < cn && i != j) ; } PRINT2 (("weight: "ID"\n", Cnw [j])) ; ASSERT (Cnw [j] > 0) ; cnt += Cnw [j] ; } ASSERT (cnt == total_weight) ; for (j = 0 ; j < n ; j++) PRINT2 (("Cmap ["ID"] = "ID"\n", j, Cmap[j])); ASSERT (k == cn) ; #endif /* ------------------------------------------------------------------ */ /* find the separator of the compressed graph */ /* ------------------------------------------------------------------ */ /* FUTURE WORK: could call CHACO, SCOTCH, ... here too */ csep = CHOLMOD(metis_bisector) (C, Cnw, Cew, Part, Common) ; if (csep < 0) { /* failed */ return (-1) ; } PRINT2 (("Part: ")) ; DEBUG (for (j = 0 ; j < cn ; j++) PRINT2 ((""ID" ", Part [j]))) ; PRINT2 (("\n")) ; /* Cp and Ci no longer needed */ /* ------------------------------------------------------------------ */ /* find the separator of the uncompressed graph */ /* ------------------------------------------------------------------ */ /* expand the separator to live nodes in the uncompressed graph */ for (j = n-1 ; j >= 0 ; j--) { /* do this in reverse order so that Cnw can be expanded in place */ k = Cmap [j] ; ASSERT (k >= EMPTY && k < n) ; if (k > EMPTY) { /* node k in compressed graph and is node j in full graph */ ASSERT (k <= j) ; ASSERT (Hash [j] >= EMPTY) ; Part [j] = Part [k] ; Cnw [j] = Cnw [k] ; } else { /* node j is a dead node */ Cnw [j] = 0 ; DEBUG (Part [j] = EMPTY) ; ASSERT (Hash [j] < EMPTY) ; } } /* find the components for the dead nodes */ for (i = 0 ; i < n ; i++) { if (Hash [i] < EMPTY) { /* node i has been absorbed into node j */ j = FLIP (Hash [i]) ; ASSERT (Part [i] == EMPTY && j >= 0 && j < n && Cnw [i] == 0) ; Part [i] = Part [j] ; } ASSERT (Part [i] >= 0 && Part [i] <= 2) ; } #ifndef NDEBUG PRINT2 (("Part: ")) ; for (cnt = 0, j = 0 ; j < n ; j++) { ASSERT (Part [j] != EMPTY) ; PRINT2 ((""ID" ", Part [j])) ; if (Part [j] == 2) cnt += Cnw [j] ; } PRINT2 (("\n")) ; PRINT2 (("csep "ID" "ID"\n", cnt, csep)) ; ASSERT (cnt == csep) ; for (cnt = 0, j = 0 ; j < n ; j++) cnt += Cnw [j] ; ASSERT (cnt == total_weight) ; #endif } /* ---------------------------------------------------------------------- */ /* return the separator (or -1 if error) */ /* ---------------------------------------------------------------------- */ PRINT2 (("Partition done, n "ID" csep "ID"\n", n, csep)) ; return (csep) ; } /* ========================================================================== */ /* === clear_flag =========================================================== */ /* ========================================================================== */ /* A node j has been removed from the graph if Flag [j] < EMPTY. * If Flag [j] >= EMPTY && Flag [j] < mark, then node j is alive but unmarked. * Flag [j] == mark means that node j is alive and marked. Incrementing mark * means that all nodes are either (still) dead, or live but unmarked. * * If Map is NULL, then on output, Common->mark < Common->Flag [i] for all i * from 0 to Common->nrow. This is the same output condition as * cholmod_clear_flag, except that this routine maintains the Flag [i] < EMPTY * condition as well, if that condition was true on input. * * If Map is non-NULL, then on output, Common->mark < Common->Flag [i] for all * i in the set Map [0..cn-1]. * * workspace: Flag (nrow) */ static SuiteSparse_long clear_flag (Int *Map, Int cn, cholmod_common *Common) { Int nrow, i ; Int *Flag ; PRINT2 (("old mark %ld\n", Common->mark)) ; Common->mark++ ; PRINT2 (("new mark %ld\n", Common->mark)) ; if (Common->mark <= 0) { nrow = Common->nrow ; Flag = Common->Flag ; if (Map != NULL) { for (i = 0 ; i < cn ; i++) { /* if Flag [Map [i]] < EMPTY, leave it alone */ if (Flag [Map [i]] >= EMPTY) { Flag [Map [i]] = EMPTY ; } } /* now Flag [Map [i]] <= EMPTY for all i */ } else { for (i = 0 ; i < nrow ; i++) { /* if Flag [i] < EMPTY, leave it alone */ if (Flag [i] >= EMPTY) { Flag [i] = EMPTY ; } } /* now Flag [i] <= EMPTY for all i */ } Common->mark = 0 ; } return (Common->mark) ; } /* ========================================================================== */ /* === find_components ====================================================== */ /* ========================================================================== */ /* Find all connected components of the current subgraph C. The subgraph C * consists of the nodes of B that appear in the set Map [0..cn-1]. If Map * is NULL, then it is assumed to be the identity mapping * (Map [0..cn-1] = 0..cn-1). * * A node j does not appear in B if it has been ordered (Flag [j] < EMPTY, * which means that j has been ordered and is "deleted" from B). * * If the size of a component is large, it is placed on the component stack, * Cstack. Otherwise, its nodes are ordered and it is not placed on the Cstack. * * A component S is defined by a "representative node" (repnode for short) * called the snode, which is one of the nodes in the subgraph. Likewise, the * subgraph C is defined by its repnode, called cnode. * * If Part is not NULL on input, then Part [i] determines how the components * are placed on the stack. Components containing nodes i with Part [i] == 0 * are placed first, followed by components with Part [i] == 1. * * The first node placed in each of the two parts is flipped when placed in * the Cstack. This allows the components of the two parts to be found simply * by traversing the Cstack. * * workspace: Flag (nrow) */ static void find_components ( /* inputs, not modified on output */ cholmod_sparse *B, Int Map [ ], /* size n, only Map [0..cn-1] used */ Int cn, /* # of nodes in C */ Int cnode, /* root node of component C, or EMPTY if C is the * entire graph B */ Int Part [ ], /* size cn, optional */ /* input/output */ Int Bnz [ ], /* size n. Bnz [j] = # nonzeros in column j of B. * Reduce since B is pruned of dead nodes. */ Int CParent [ ], /* CParent [i] = j if component with repnode j is * the parent of the component with repnode i. * CParent [i] = EMPTY if the component with * repnode i is a root of the separator tree. * CParent [i] is -2 if i is not a repnode. */ Int Cstack [ ], /* component stack for nested dissection */ Int *top, /* Cstack [0..top] contains root nodes of the * the components currently in the stack */ /* workspace, undefined on input and output: */ Int Queue [ ], /* size n, for breadth-first search */ cholmod_common *Common ) { Int n, mark, cj, j, sj, sn, p, i, snode, pstart, pdest, pend, nd_components, part, first, save_mark ; Int *Bp, *Bi, *Flag ; /* ---------------------------------------------------------------------- */ /* get workspace */ /* ---------------------------------------------------------------------- */ PRINT2 (("find components: cn %d\n", cn)) ; Flag = Common->Flag ; /* size n */ /* force initialization of Flag [Map [0..cn-1]] */ save_mark = Common->mark ; /* save the current mark */ Common->mark = EMPTY ; /* clear Flag; preserve Flag [Map [i]] if Flag [Map [i]] already < EMPTY */ /* this takes O(cn) time */ mark = clear_flag (Map, cn, Common) ; Bp = B->p ; Bi = B->i ; n = B->nrow ; ASSERT (cnode >= EMPTY && cnode < n) ; ASSERT (IMPLIES (cnode >= 0, Flag [cnode] < EMPTY)) ; /* get ordering parameters */ nd_components = Common->method [Common->current].nd_components ; /* ---------------------------------------------------------------------- */ /* find the connected components of C via a breadth-first search */ /* ---------------------------------------------------------------------- */ part = (Part == NULL) ? 0 : 1 ; /* examine each part (part 1 and then part 0) */ for (part = (Part == NULL) ? 0 : 1 ; part >= 0 ; part--) { /* first is TRUE for the first connected component in each part */ first = TRUE ; /* find all connected components in the current part */ for (cj = 0 ; cj < cn ; cj++) { /* get node snode, which is node cj of C. It might already be in * the separator of C (and thus ordered, with Flag [snode] < EMPTY) */ snode = (Map == NULL) ? (cj) : (Map [cj]) ; ASSERT (snode >= 0 && snode < n) ; if (Flag [snode] >= EMPTY && Flag [snode] < mark && ((Part == NULL) || Part [cj] == part)) { /* ---------------------------------------------------------- */ /* find new connected component S */ /* ---------------------------------------------------------- */ /* node snode is the repnode of a connected component S, the * parent of which is cnode, the repnode of C. If cnode is * EMPTY then C is the original graph B. */ PRINT2 (("----------:::snode "ID" cnode "ID"\n", snode, cnode)); ASSERT (CParent [snode] == -2) ; if (first || nd_components) { /* If this is the first node in this part, then it becomes * the repnode of all components in this part, and all * components in this part form a single node in the * separator tree. If nd_components is TRUE, then all * connected components form their own node in the * separator tree. */ CParent [snode] = cnode ; } /* place j in the queue and mark it */ Queue [0] = snode ; Flag [snode] = mark ; sn = 1 ; /* breadth-first traversal, starting at node j */ for (sj = 0 ; sj < sn ; sj++) { /* get node j from head of Queue and traverse its edges */ j = Queue [sj] ; PRINT2 ((" j: "ID"\n", j)) ; ASSERT (j >= 0 && j < n) ; ASSERT (Flag [j] == mark) ; pstart = Bp [j] ; pdest = pstart ; pend = pstart + Bnz [j] ; for (p = pstart ; p < pend ; p++) { i = Bi [p] ; if (i != j && Flag [i] >= EMPTY) { /* node is still in the graph */ Bi [pdest++] = i ; if (Flag [i] < mark) { /* node i is in this component S, and unflagged * (first time node i has been seen in this BFS) * place node i in the queue and mark it */ Queue [sn++] = i ; Flag [i] = mark ; } } } /* edges to dead nodes have been removed */ Bnz [j] = pdest - pstart ; } /* ---------------------------------------------------------- */ /* order S if it is small; place it on Cstack otherwise */ /* ---------------------------------------------------------- */ PRINT2 (("sn "ID"\n", sn)) ; /* place the new component on the Cstack. Flip the node if * is the first connected component of the current part, * or if all components are treated as their own node in * the separator tree. */ Cstack [++(*top)] = (first || nd_components) ? FLIP (snode) : snode ; first = FALSE ; } } } /* restore the flag (normally taking O(1) time except for Int overflow) */ Common->mark = save_mark++ ; clear_flag (NULL, 0, Common) ; DEBUG (for (i = 0 ; i < n ; i++) ASSERT (Flag [i] < Common->mark)) ; } /* ========================================================================== */ /* === cholmod_bisect ======================================================= */ /* ========================================================================== */ /* Finds a node bisector of A, A*A', A(:,f)*A(:,f)'. * * workspace: Flag (nrow), * Iwork (nrow if symmetric, max (nrow,ncol) if unsymmetric). * Allocates a temporary matrix B=A*A' or B=A, * and O(nnz(A)) temporary memory space. */ SuiteSparse_long CHOLMOD(bisect) /* returns # of nodes in separator */ ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to bisect */ Int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ int compress, /* if TRUE, compress the graph first */ /* ---- output --- */ Int *Partition, /* size A->nrow. Node i is in the left graph if * Partition [i] = 0, the right graph if 1, and in the * separator if 2. */ /* --------------- */ cholmod_common *Common ) { Int *Bp, *Bi, *Hash, *Cmap, *Bnw, *Bew, *Iwork ; cholmod_sparse *B ; unsigned Int hash ; Int j, n, bnz, sepsize, p, pend ; size_t csize, s ; int ok = TRUE ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (EMPTY) ; RETURN_IF_NULL (A, EMPTY) ; RETURN_IF_NULL (Partition, EMPTY) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, EMPTY) ; Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* quick return */ /* ---------------------------------------------------------------------- */ n = A->nrow ; if (n == 0) { return (0) ; } /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ /* s = n + MAX (n, A->ncol) */ s = CHOLMOD(add_size_t) (A->nrow, MAX (A->nrow, A->ncol), &ok) ; if (!ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return (EMPTY) ; } CHOLMOD(allocate_work) (n, s, 0, Common) ; if (Common->status < CHOLMOD_OK) { return (EMPTY) ; } ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; Iwork = Common->Iwork ; Hash = Iwork ; /* size n, (i/l/l) */ Cmap = Iwork + n ; /* size n, (i/i/l) */ /* ---------------------------------------------------------------------- */ /* convert the matrix to adjacency list form */ /* ---------------------------------------------------------------------- */ /* The input graph to must be symmetric, with no diagonal entries * present. The columns need not be sorted. */ /* B = A, A*A', or A(:,f)*A(:,f)', upper and lower parts present */ if (A->stype) { /* Add the upper/lower part to a symmetric lower/upper matrix by * converting to unsymmetric mode */ /* workspace: Iwork (nrow) */ B = CHOLMOD(copy) (A, 0, -1, Common) ; } else { /* B = A*A' or A(:,f)*A(:,f)', no diagonal */ /* workspace: Flag (nrow), Iwork (max (nrow,ncol)) */ B = CHOLMOD(aat) (A, fset, fsize, -1, Common) ; } if (Common->status < CHOLMOD_OK) { return (EMPTY) ; } Bp = B->p ; Bi = B->i ; bnz = Bp [n] ; ASSERT ((Int) (B->nrow) == n && (Int) (B->ncol) == n) ; /* B does not include the diagonal, and both upper and lower parts. * Common->anz includes the diagonal, and just the lower part of B */ Common->anz = bnz / 2 + ((double) n) ; /* Bew should be at least size n for the hash function to work well */ /* this cannot cause overflow, because the matrix is already created */ csize = MAX (((size_t) n) + 1, (size_t) bnz) ; /* create the graph using Flag as workspace for node weights [ */ Bnw = Common->Flag ; /* size n workspace */ /* compute hash for each node if compression requested */ if (compress) { for (j = 0 ; j < n ; j++) { hash = j ; pend = Bp [j+1] ; for (p = Bp [j] ; p < pend ; p++) { hash += Bi [p] ; ASSERT (Bi [p] != j) ; } /* finalize the hash key for node j */ hash %= csize ; Hash [j] = (Int) hash ; ASSERT (Hash [j] >= 0 && Hash [j] < csize) ; } } /* allocate edge weights */ Bew = CHOLMOD(malloc) (csize, sizeof (Int), Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ CHOLMOD(free_sparse) (&B, Common) ; CHOLMOD(free) (csize, sizeof (Int), Bew, Common) ; return (EMPTY) ; } /* graph has unit node and edge weights */ for (j = 0 ; j < n ; j++) { Bnw [j] = 1 ; } for (s = 0 ; s < csize ; s++) { Bew [s] = 1 ; } /* ---------------------------------------------------------------------- */ /* compress and partition the graph */ /* ---------------------------------------------------------------------- */ sepsize = partition ( #ifndef NDEBUG csize, #endif compress, Hash, B, Bnw, Bew, Cmap, Partition, Common) ; /* contents of Bp, Bi, Bnw, and Bew no longer needed ] */ /* If partition fails, free the workspace below and return sepsize < 0 */ /* ---------------------------------------------------------------------- */ /* free workspace */ /* ---------------------------------------------------------------------- */ B->ncol = n ; /* restore size for memory usage statistics */ CHOLMOD(free_sparse) (&B, Common) ; Common->mark = EMPTY ; CHOLMOD_CLEAR_FLAG (Common) ; CHOLMOD(free) (csize, sizeof (Int), Bew, Common) ; return (sepsize) ; } /* ========================================================================== */ /* === cholmod_nested_dissection ============================================ */ /* ========================================================================== */ /* This method uses a node bisector, applied recursively (but using a * non-recursive algorithm). Once the graph is partitioned, it calls a * constrained min degree code (CAMD or CSYMAMD for A+A', and CCOLAMD for A*A') * to order all the nodes in the graph - but obeying the constraints determined * by the separators. This routine is similar to METIS_NodeND, except for how * it treats the leaf nodes. METIS_NodeND orders the leaves of the separator * tree with MMD, ignoring the rest of the matrix when ordering a single leaf. * This routine orders the whole matrix with CSYMAMD or CCOLAMD, all at once, * when the graph partitioning is done. * * This function also returns a postorderd separator tree (CParent), and a * mapping of nodes in the graph to nodes in the separator tree (Cmember). * * workspace: Flag (nrow), Head (nrow+1), Iwork (4*nrow + (ncol if unsymmetric)) * Allocates a temporary matrix B=A*A' or B=A, * and O(nnz(A)) temporary memory space. * Allocates an additional 3*n*sizeof(Int) temporary workspace */ SuiteSparse_long CHOLMOD(nested_dissection) /* returns # of components, or -1 if error */ ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to order */ Int *fset, /* subset of 0:(A->ncol)-1 */ size_t fsize, /* size of fset */ /* ---- output --- */ Int *Perm, /* size A->nrow, output permutation */ Int *CParent, /* size A->nrow. On output, CParent [c] is the parent * of component c, or EMPTY if c is a root, and where * c is in the range 0 to # of components minus 1 */ Int *Cmember, /* size A->nrow. Cmember [j] = c if node j of A is * in component c */ /* --------------- */ cholmod_common *Common ) { double prune_dense, nd_oksep ; Int *Bp, *Bi, *Bnz, *Cstack, *Imap, *Map, *Flag, *Head, *Next, *Bnw, *Iwork, *Ipost, *NewParent, *Hash, *Cmap, *Cp, *Ci, *Cew, *Cnw, *Part, *Post, *Work3n ; unsigned Int hash ; Int n, bnz, top, i, j, k, cnode, cdense, p, cj, cn, ci, cnz, mark, c, uncol, sepsize, parent, ncomponents, threshold, ndense, pstart, pdest, pend, nd_compress, nd_camd, csize, jnext, nd_small, total_weight, nchild, child = EMPTY ; cholmod_sparse *B, *C ; size_t s ; int ok = TRUE ; DEBUG (Int cnt) ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (EMPTY) ; RETURN_IF_NULL (A, EMPTY) ; RETURN_IF_NULL (Perm, EMPTY) ; RETURN_IF_NULL (CParent, EMPTY) ; RETURN_IF_NULL (Cmember, EMPTY) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, EMPTY) ; Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* quick return */ /* ---------------------------------------------------------------------- */ n = A->nrow ; if (n == 0) { return (1) ; } /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ /* get ordering parameters */ prune_dense = Common->method [Common->current].prune_dense ; nd_compress = Common->method [Common->current].nd_compress ; nd_oksep = Common->method [Common->current].nd_oksep ; nd_oksep = MAX (0, nd_oksep) ; nd_oksep = MIN (1, nd_oksep) ; nd_camd = Common->method [Common->current].nd_camd ; nd_small = Common->method [Common->current].nd_small ; nd_small = MAX (4, nd_small) ; PRINT0 (("nd_components %d nd_small %d nd_oksep %g\n", Common->method [Common->current].nd_components, nd_small, nd_oksep)) ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ /* s = 4*n + uncol */ uncol = (A->stype == 0) ? A->ncol : 0 ; s = CHOLMOD(mult_size_t) (n, 4, &ok) ; s = CHOLMOD(add_size_t) (s, uncol, &ok) ; if (!ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return (EMPTY) ; } CHOLMOD(allocate_work) (n, s, 0, Common) ; if (Common->status < CHOLMOD_OK) { return (EMPTY) ; } ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; /* ---------------------------------------------------------------------- */ /* get workspace */ /* ---------------------------------------------------------------------- */ Flag = Common->Flag ; /* size n */ Head = Common->Head ; /* size n+1, all equal to -1 */ Iwork = Common->Iwork ; Imap = Iwork ; /* size n, same as Queue in find_components */ Map = Iwork + n ; /* size n */ Bnz = Iwork + 2*((size_t) n) ; /* size n */ Hash = Iwork + 3*((size_t) n) ; /* size n */ Work3n = CHOLMOD(malloc) (n, 3*sizeof (Int), Common) ; Part = Work3n ; /* size n */ Bnw = Part + n ; /* size n */ Cnw = Bnw + n ; /* size n */ Cstack = Perm ; /* size n, use Perm as workspace for Cstack [ */ Cmap = Cmember ; /* size n, use Cmember as workspace [ */ if (Common->status < CHOLMOD_OK) { return (EMPTY) ; } /* ---------------------------------------------------------------------- */ /* convert B to symmetric form with both upper/lower parts present */ /* ---------------------------------------------------------------------- */ /* B = A+A', A*A', or A(:,f)*A(:,f)', upper and lower parts present */ if (A->stype) { /* Add the upper/lower part to a symmetric lower/upper matrix by * converting to unsymmetric mode */ /* workspace: Iwork (nrow) */ B = CHOLMOD(copy) (A, 0, -1, Common) ; } else { /* B = A*A' or A(:,f)*A(:,f)', no diagonal */ /* workspace: Flag (nrow), Iwork (max (nrow,ncol)) */ B = CHOLMOD(aat) (A, fset, fsize, -1, Common) ; } if (Common->status < CHOLMOD_OK) { CHOLMOD(free) (3*n, sizeof (Int), Work3n, Common) ; return (EMPTY) ; } Bp = B->p ; Bi = B->i ; bnz = CHOLMOD(nnz) (B, Common) ; ASSERT ((Int) (B->nrow) == n && (Int) (B->ncol) == n) ; csize = MAX (n, bnz) ; ASSERT (CHOLMOD(dump_sparse) (B, "B for nd:", Common) >= 0) ; /* ---------------------------------------------------------------------- */ /* initializations */ /* ---------------------------------------------------------------------- */ /* all nodes start out unmarked and unordered (Type 4, see below) */ Common->mark = EMPTY ; CHOLMOD_CLEAR_FLAG (Common) ; ASSERT (Flag == Common->Flag) ; ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; for (j = 0 ; j < n ; j++) { CParent [j] = -2 ; } /* prune dense nodes from B */ if (IS_NAN (prune_dense) || prune_dense < 0) { /* only remove completely dense nodes */ threshold = n-2 ; } else { /* remove nodes with degree more than threshold */ threshold = (Int) (MAX (16, prune_dense * sqrt ((double) (n)))) ; threshold = MIN (n, threshold) ; } ndense = 0 ; cnode = EMPTY ; cdense = EMPTY ; for (j = 0 ; j < n ; j++) { Bnz [j] = Bp [j+1] - Bp [j] ; if (Bnz [j] > threshold) { /* node j is dense, prune it from B */ PRINT2 (("j is dense %d\n", j)) ; ndense++ ; if (cnode == EMPTY) { /* first dense node found becomes root of this component, * which contains all of the dense nodes found here */ cdense = j ; cnode = j ; CParent [cnode] = EMPTY ; } Flag [j] = FLIP (cnode) ; } } B->packed = FALSE ; ASSERT (B->nz == NULL) ; if (ndense == n) { /* all nodes removed: Perm is identity, all nodes in component zero, * and the separator tree has just one node. */ PRINT2 (("all nodes are dense\n")) ; for (k = 0 ; k < n ; k++) { Perm [k] = k ; Cmember [k] = 0 ; } CParent [0] = EMPTY ; CHOLMOD(free_sparse) (&B, Common) ; CHOLMOD(free) (3*n, sizeof (Int), Work3n, Common) ; Common->mark = EMPTY ; CHOLMOD_CLEAR_FLAG (Common) ; return (1) ; } /* Cp and Ci are workspace to construct the subgraphs to partition */ C = CHOLMOD(allocate_sparse) (n, n, csize, FALSE, TRUE, 0, CHOLMOD_PATTERN, Common) ; Cew = CHOLMOD(malloc) (csize, sizeof (Int), Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ CHOLMOD(free_sparse) (&C, Common) ; CHOLMOD(free_sparse) (&B, Common) ; CHOLMOD(free) (csize, sizeof (Int), Cew, Common) ; CHOLMOD(free) (3*n, sizeof (Int), Work3n, Common) ; Common->mark = EMPTY ; CHOLMOD_CLEAR_FLAG (Common) ; PRINT2 (("out of memory for C, etc\n")) ; return (EMPTY) ; } Cp = C->p ; Ci = C->i ; /* create initial unit node and edge weights */ for (j = 0 ; j < n ; j++) { Bnw [j] = 1 ; } for (p = 0 ; p < csize ; p++) { Cew [p] = 1 ; } /* push the initial connnected components of B onto the Cstack */ top = EMPTY ; /* Cstack is empty */ /* workspace: Flag (nrow), Iwork (nrow); use Imap as workspace for Queue [*/ find_components (B, NULL, n, cnode, NULL, Bnz, CParent, Cstack, &top, Imap, Common) ; /* done using Imap as workspace for Queue ] */ /* Nodes can now be of Type 0, 1, 2, or 4 (see definition below) */ /* ---------------------------------------------------------------------- */ /* while Cstack is not empty, do: */ /* ---------------------------------------------------------------------- */ while (top >= 0) { /* clear the Flag array, but do not modify negative entries in Flag */ mark = clear_flag (NULL, 0, Common) ; DEBUG (for (i = 0 ; i < n ; i++) Imap [i] = EMPTY) ; /* ------------------------------------------------------------------ */ /* get node(s) from the top of the Cstack */ /* ------------------------------------------------------------------ */ /* i is the repnode of its (unordered) connected component. Get * all repnodes for all connected components of a single part. If * each connected component is to be ordered separately (nd_components * is TRUE), then this while loop iterates just once. */ cnode = EMPTY ; cn = 0 ; while (cnode == EMPTY) { i = Cstack [top--] ; if (i < 0) { /* this is the last node in this component */ i = FLIP (i) ; cnode = i ; } ASSERT (i >= 0 && i < n && Flag [i] >= EMPTY) ; /* place i in the queue and mark it */ Map [cn] = i ; Flag [i] = mark ; Imap [i] = cn ; cn++ ; } ASSERT (cnode != EMPTY) ; /* During ordering, there are five kinds of nodes in the graph of B, * based on Flag [j] and CParent [j] for nodes j = 0 to n-1: * * Type 0: If cnode is a repnode of an unordered component, then * CParent [cnode] is in the range EMPTY to n-1 and * Flag [cnode] >= EMPTY. This is a "live" node. * * Type 1: If cnode is a repnode of an ordered separator component, * then Flag [cnode] < EMPTY and FLAG [cnode] = FLIP (cnode). * CParent [cnode] is in the range EMPTY to n-1. cnode is a root of * the separator tree if CParent [cnode] == EMPTY. This node is dead. * * Type 2: If node j isn't a repnode, has not been absorbed via * graph compression into another node, but is in an ordered separator * component, then cnode = FLIP (Flag [j]) gives the repnode of the * component that contains j and CParent [j] is -2. This node is dead. * Note that Flag [j] < EMPTY. * * Type 3: If node i has been absorbed via graph compression into some * other node j = FLIP (Flag [i]) where j is not a repnode. * CParent [j] is -2. Node i may or may not be in an ordered * component. This node is dead. Note that Flag [j] < EMPTY. * * Type 4: If node j is "live" (not in an ordered component, and not * absorbed into any other node), then Flag [j] >= EMPTY. * * Only "live" nodes (of type 0 or 4) are placed in a subgraph to be * partitioned. Node j is alive if Flag [j] >= EMPTY, and dead if * Flag [j] < EMPTY. */ /* ------------------------------------------------------------------ */ /* create the subgraph for this connected component C */ /* ------------------------------------------------------------------ */ /* Do a breadth-first search of the graph starting at cnode. * use Map [0..cn-1] for nodes in the component C [ * use Cnw and Cew for node and edge weights of the resulting subgraph [ * use Cp and Ci for the resulting subgraph [ * use Imap [i] for all nodes i in B that are in the component C [ */ cnz = 0 ; total_weight = 0 ; for (cj = 0 ; cj < cn ; cj++) { /* get node j from the head of the queue; it is node cj of C */ j = Map [cj] ; ASSERT (Flag [j] == mark) ; Cp [cj] = cnz ; Cnw [cj] = Bnw [j] ; ASSERT (Cnw [cj] >= 0) ; total_weight += Cnw [cj] ; pstart = Bp [j] ; pdest = pstart ; pend = pstart + Bnz [j] ; hash = cj ; for (p = pstart ; p < pend ; p++) { i = Bi [p] ; /* prune diagonal entries and dead edges from B */ if (i != j && Flag [i] >= EMPTY) { /* live node i is in the current component */ Bi [pdest++] = i ; if (Flag [i] != mark) { /* First time node i has been seen, it is a new node * of C. place node i in the queue and mark it */ Map [cn] = i ; Flag [i] = mark ; Imap [i] = cn ; cn++ ; } /* place the edge (cj,ci) in the adjacency list of cj */ ci = Imap [i] ; ASSERT (ci >= 0 && ci < cn && ci != cj && cnz < csize) ; Ci [cnz++] = ci ; hash += ci ; } } /* edges to dead nodes have been removed */ Bnz [j] = pdest - pstart ; /* finalize the hash key for column j */ hash %= csize ; Hash [cj] = (Int) hash ; ASSERT (Hash [cj] >= 0 && Hash [cj] < csize) ; } Cp [cn] = cnz ; C->nrow = cn ; C->ncol = cn ; /* affects mem stats unless restored when C free'd */ /* contents of Imap no longer needed ] */ #ifndef NDEBUG for (cj = 0 ; cj < cn ; cj++) { j = Map [cj] ; PRINT2 (("----------------------------C column cj: "ID" j: "ID"\n", cj, j)) ; ASSERT (j >= 0 && j < n) ; ASSERT (Flag [j] >= EMPTY) ; for (p = Cp [cj] ; p < Cp [cj+1] ; p++) { ci = Ci [p] ; i = Map [ci] ; PRINT3 (("ci: "ID" i: "ID"\n", ci, i)) ; ASSERT (ci != cj && ci >= 0 && ci < cn) ; ASSERT (i != j && i >= 0 && i < n) ; ASSERT (Flag [i] >= EMPTY) ; } } #endif PRINT0 (("consider cn %d nd_small %d ", cn, nd_small)) ; if (cn < nd_small) /* could be 'total_weight < nd_small' instead */ { /* place all nodes in the separator */ PRINT0 ((" too small\n")) ; sepsize = total_weight ; } else { /* Cp and Ci now contain the component, with cn nodes and cnz * nonzeros. The mapping of a node cj into node j the main graph * B is given by Map [cj] = j */ PRINT0 ((" cut\n")) ; /* -------------------------------------------------------------- */ /* compress and partition the graph C */ /* -------------------------------------------------------------- */ /* The edge weights Cew [0..csize-1] are all 1's on input to and * output from the partition routine. */ sepsize = partition ( #ifndef NDEBUG csize, #endif nd_compress, Hash, C, Cnw, Cew, Cmap, Part, Common) ; /* contents of Cp and Ci no longer needed ] */ if (sepsize < 0) { /* failed */ C->ncol = n ; /* restore size for memory usage statistics */ CHOLMOD(free_sparse) (&C, Common) ; CHOLMOD(free_sparse) (&B, Common) ; CHOLMOD(free) (csize, sizeof (Int), Cew, Common) ; CHOLMOD(free) (3*n, sizeof (Int), Work3n, Common) ; Common->mark = EMPTY ; CHOLMOD_CLEAR_FLAG (Common) ; return (EMPTY) ; } /* -------------------------------------------------------------- */ /* compress B based on how C was compressed */ /* -------------------------------------------------------------- */ for (ci = 0 ; ci < cn ; ci++) { if (Hash [ci] < EMPTY) { /* ci is dead in C, having been absorbed into cj */ cj = FLIP (Hash [ci]) ; PRINT2 (("In C, "ID" absorbed into "ID" (wgt now "ID")\n", ci, cj, Cnw [cj])) ; /* i is dead in B, having been absorbed into j */ i = Map [ci] ; j = Map [cj] ; PRINT2 (("In B, "ID" (wgt "ID") => "ID" (wgt "ID")\n", i, Bnw [i], j, Bnw [j], Cnw [cj])) ; /* more than one node may be absorbed into j. This is * accounted for in Cnw [cj]. Assign it here rather * than += Bnw [i] */ Bnw [i] = 0 ; Bnw [j] = Cnw [cj] ; Flag [i] = FLIP (j) ; } } DEBUG (for (cnt = 0, j = 0 ; j < n ; j++) cnt += Bnw [j]) ; ASSERT (cnt == n) ; } /* contents of Cnw [0..cn-1] no longer needed ] */ /* ------------------------------------------------------------------ */ /* order the separator, and stack the components when C is split */ /* ------------------------------------------------------------------ */ /* one more component has been found: either the separator of C, * or all of C */ ASSERT (sepsize >= 0 && sepsize <= total_weight) ; PRINT0 (("sepsize %d tot %d : %8.4f ", sepsize, total_weight, ((double) sepsize) / ((double) total_weight))) ; if (sepsize == total_weight || sepsize == 0 || sepsize > nd_oksep * total_weight) { /* Order the nodes in the component. The separator is too large, * or empty. Note that the partition routine cannot return a * sepsize of zero, but it can return a separator consisting of the * whole graph. The "sepsize == 0" test is kept, above, in case the * partition routine changes. In either case, this component * remains unsplit, and becomes a leaf of the separator tree. */ PRINT2 (("cnode %d sepsize zero or all of graph: "ID"\n", cnode, sepsize)) ; for (cj = 0 ; cj < cn ; cj++) { j = Map [cj] ; Flag [j] = FLIP (cnode) ; PRINT2 ((" node cj: "ID" j: "ID" ordered\n", cj, j)) ; } ASSERT (Flag [cnode] == FLIP (cnode)) ; ASSERT (cnode != EMPTY && Flag [cnode] < EMPTY) ; PRINT0 (("discarded\n")) ; } else { /* Order the nodes in the separator of C and find a new repnode * cnode that is in the separator of C. This requires the separator * to be non-empty. */ PRINT0 (("sepsize not tiny: "ID"\n", sepsize)) ; parent = CParent [cnode] ; ASSERT (parent >= EMPTY && parent < n) ; CParent [cnode] = -2 ; cnode = EMPTY ; for (cj = 0 ; cj < cn ; cj++) { j = Map [cj] ; if (Part [cj] == 2) { /* All nodes in the separator become part of a component * whose repnode is cnode */ PRINT2 (("node cj: "ID" j: "ID" ordered\n", cj, j)) ; if (cnode == EMPTY) { PRINT2(("------------new cnode: cj "ID" j "ID"\n", cj, j)) ; cnode = j ; } Flag [j] = FLIP (cnode) ; } else { PRINT2 ((" node cj: "ID" j: "ID" not ordered\n", cj, j)) ; } } ASSERT (cnode != EMPTY && Flag [cnode] < EMPTY) ; ASSERT (CParent [cnode] == -2) ; CParent [cnode] = parent ; /* find the connected components when C is split, and push * them on the Cstack. Use Imap as workspace for Queue. [ */ /* workspace: Flag (nrow) */ find_components (B, Map, cn, cnode, Part, Bnz, CParent, Cstack, &top, Imap, Common) ; /* done using Imap as workspace for Queue ] */ } /* contents of Map [0..cn-1] no longer needed ] */ } /* done using Cmember as workspace for Cmap ] */ /* done using Perm as workspace for Cstack ] */ /* ---------------------------------------------------------------------- */ /* place nodes removed via compression into their proper component */ /* ---------------------------------------------------------------------- */ /* At this point, all nodes are of Type 1, 2, or 3, as defined above. */ for (i = 0 ; i < n ; i++) { /* find the repnode cnode that contains node i */ j = FLIP (Flag [i]) ; PRINT2 (("\nfind component for "ID", in: "ID"\n", i, j)) ; ASSERT (j >= 0 && j < n) ; DEBUG (cnt = 0) ; while (CParent [j] == -2) { j = FLIP (Flag [j]) ; PRINT2 ((" walk up to "ID" ", j)) ; ASSERT (j >= 0 && j < n) ; PRINT2 ((" CParent "ID"\n", CParent [j])) ; ASSERT (cnt < n) ; DEBUG (cnt++) ; } cnode = j ; ASSERT (cnode >= 0 && cnode < n) ; ASSERT (CParent [cnode] >= EMPTY && CParent [cnode] < n) ; PRINT2 (("i "ID" is in component with cnode "ID"\n", i, cnode)) ; ASSERT (Flag [cnode] == FLIP (cnode)) ; /* Mark all nodes along the path from i to cnode as being in the * component whos repnode is cnode. Perform path compression. */ j = FLIP (Flag [i]) ; Flag [i] = FLIP (cnode) ; DEBUG (cnt = 0) ; while (CParent [j] == -2) { ASSERT (j >= 0 && j < n) ; jnext = FLIP (Flag [j]) ; PRINT2 ((" "ID" walk "ID" set cnode to "ID"\n", i, j, cnode)) ; ASSERT (cnt < n) ; DEBUG (cnt++) ; Flag [j] = FLIP (cnode) ; j = jnext ; } } /* At this point, all nodes fall into Types 1 or 2, as defined above. */ #ifndef NDEBUG for (j = 0 ; j < n ; j++) { PRINT2 (("j %d CParent %d ", j, CParent [j])) ; if (CParent [j] >= EMPTY && CParent [j] < n) { /* case 1: j is a repnode of a component */ cnode = j ; PRINT2 ((" a repnode\n")) ; } else { /* case 2: j is not a repnode of a component */ cnode = FLIP (Flag [j]) ; PRINT2 ((" repnode is %d\n", cnode)) ; ASSERT (cnode >= 0 && cnode < n) ; ASSERT (CParent [cnode] >= EMPTY && CParent [cnode] < n) ; } ASSERT (Flag [cnode] == FLIP (cnode)) ; /* case 3 no longer holds */ } #endif /* ---------------------------------------------------------------------- */ /* free workspace */ /* ---------------------------------------------------------------------- */ C->ncol = n ; /* restore size for memory usage statistics */ CHOLMOD(free_sparse) (&C, Common) ; CHOLMOD(free_sparse) (&B, Common) ; CHOLMOD(free) (csize, sizeof (Int), Cew, Common) ; CHOLMOD(free) (3*n, sizeof (Int), Work3n, Common) ; /* ---------------------------------------------------------------------- */ /* handle dense nodes */ /* ---------------------------------------------------------------------- */ /* The separator tree has nodes with either no children or two or more * children - with one exception. There may exist a single root node with * exactly one child, which holds the dense rows/columns of the matrix. * Delete this node if it exists. */ if (ndense > 0) { ASSERT (CParent [cdense] == EMPTY) ; /* cdense has no parent */ /* find the children of cdense */ nchild = 0 ; for (j = 0 ; j < n ; j++) { if (CParent [j] == cdense) { nchild++ ; child = j ; } } if (nchild == 1) { /* the cdense node has just one child; merge the two nodes */ PRINT1 (("root has one child\n")) ; CParent [cdense] = -2 ; /* cdense is deleted */ CParent [child] = EMPTY ; /* child becomes a root */ for (j = 0 ; j < n ; j++) { if (Flag [j] == FLIP (cdense)) { /* j is a dense node */ PRINT1 (("dense %d\n", j)) ; Flag [j] = FLIP (child) ; } } } } /* ---------------------------------------------------------------------- */ /* postorder the components */ /* ---------------------------------------------------------------------- */ DEBUG (for (cnt = 0, j = 0 ; j < n ; j++) if (CParent [j] != -2) cnt++) ; /* use Cmember as workspace for Post [ */ Post = Cmember ; /* cholmod_postorder uses Head and Iwork [0..2n]. It does not use Flag, * which here holds the mapping of nodes to repnodes. It ignores all nodes * for which CParent [j] < -1, so it operates just on the repnodes. */ /* workspace: Head (n), Iwork (2*n) */ ncomponents = CHOLMOD(postorder) (CParent, n, NULL, Post, Common) ; ASSERT (cnt == ncomponents) ; /* use Iwork [0..n-1] as workspace for Ipost ( */ Ipost = Iwork ; DEBUG (for (j = 0 ; j < n ; j++) Ipost [j] = EMPTY) ; /* compute inverse postorder */ for (c = 0 ; c < ncomponents ; c++) { cnode = Post [c] ; ASSERT (cnode >= 0 && cnode < n) ; Ipost [cnode] = c ; ASSERT (Head [c] == EMPTY) ; } /* adjust the parent array */ /* Iwork [n..2n-1] used for NewParent [ */ NewParent = Iwork + n ; for (c = 0 ; c < ncomponents ; c++) { parent = CParent [Post [c]] ; NewParent [c] = (parent == EMPTY) ? EMPTY : (Ipost [parent]) ; } for (c = 0 ; c < ncomponents ; c++) { CParent [c] = NewParent [c] ; } ASSERT (CHOLMOD(dump_parent) (CParent, ncomponents, "CParent", Common)) ; /* Iwork [n..2n-1] no longer needed for NewParent ] */ /* Cmember no longer needed for Post ] */ #ifndef NDEBUG /* count the number of children of each node */ for (c = 0 ; c < ncomponents ; c++) { Cmember [c] = 0 ; } for (c = 0 ; c < ncomponents ; c++) { if (CParent [c] != EMPTY) Cmember [CParent [c]]++ ; } for (c = 0 ; c < ncomponents ; c++) { /* a node is either a leaf, or has 2 or more children */ ASSERT (Cmember [c] == 0 || Cmember [c] >= 2) ; } #endif /* ---------------------------------------------------------------------- */ /* place each node in its component */ /* ---------------------------------------------------------------------- */ for (j = 0 ; j < n ; j++) { /* node j is in the cth component, whose repnode is cnode */ cnode = FLIP (Flag [j]) ; PRINT2 (("j "ID" flag "ID" cnode "ID"\n", j, Flag [j], FLIP (Flag [j]))) ; ASSERT (cnode >= 0 && cnode < n) ; c = Ipost [cnode] ; ASSERT (c >= 0 && c < ncomponents) ; Cmember [j] = c ; } /* Flag no longer needed for the node-to-component mapping */ /* done using Iwork [0..n-1] as workspace for Ipost ) */ /* ---------------------------------------------------------------------- */ /* clear the Flag array */ /* ---------------------------------------------------------------------- */ Common->mark = EMPTY ; CHOLMOD_CLEAR_FLAG (Common) ; ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; /* ---------------------------------------------------------------------- */ /* find the permutation */ /* ---------------------------------------------------------------------- */ PRINT1 (("nd_camd: %d A->stype %d\n", nd_camd, A->stype)) ; if (nd_camd) { /* ------------------------------------------------------------------ */ /* apply camd, csymamd, or ccolamd using the Cmember constraints */ /* ------------------------------------------------------------------ */ if (A->stype != 0) { /* ordering A+A', so fset and fsize are ignored. * Add the upper/lower part to a symmetric lower/upper matrix by * converting to unsymmetric mode * workspace: Iwork (nrow) */ B = CHOLMOD(copy) (A, 0, -1, Common) ; if (Common->status < CHOLMOD_OK) { PRINT0 (("make symmetric failed\n")) ; return (EMPTY) ; } ASSERT ((Int) (B->nrow) == n && (Int) (B->ncol) == n) ; PRINT2 (("nested dissection (2)\n")) ; B->stype = -1 ; if (nd_camd == 2) { /* workspace: Head (nrow+1), Iwork (nrow) if symmetric-upper */ ok = CHOLMOD(csymamd) (B, Cmember, Perm, Common) ; } else { /* workspace: Head (nrow), Iwork (4*nrow) */ ok = CHOLMOD(camd) (B, NULL, 0, Cmember, Perm, Common) ; } CHOLMOD(free_sparse) (&B, Common) ; if (!ok) { /* failed */ PRINT0 (("camd/csymamd failed\n")) ; return (EMPTY) ; } } else { /* ordering A*A' or A(:,f)*A(:,f)' */ /* workspace: Iwork (nrow if no fset; MAX(nrow,ncol) if fset) */ if (!CHOLMOD(ccolamd) (A, fset, fsize, Cmember, Perm, Common)) { /* ccolamd failed */ PRINT2 (("ccolamd failed\n")) ; return (EMPTY) ; } } } else { /* ------------------------------------------------------------------ */ /* natural ordering of each component */ /* ------------------------------------------------------------------ */ /* use Iwork [0..n-1] for Next [ */ Next = Iwork ; /* ------------------------------------------------------------------ */ /* place the nodes in link lists, one list per component */ /* ------------------------------------------------------------------ */ /* do so in reverse order, to preserve original ordering */ for (j = n-1 ; j >= 0 ; j--) { /* node j is in the cth component */ c = Cmember [j] ; ASSERT (c >= 0 && c < ncomponents) ; /* place node j in link list for component c */ Next [j] = Head [c] ; Head [c] = j ; } /* ------------------------------------------------------------------ */ /* order each node in each component */ /* ------------------------------------------------------------------ */ k = 0 ; for (c = 0 ; c < ncomponents ; c++) { for (j = Head [c] ; j != EMPTY ; j = Next [j]) { Perm [k++] = j ; } Head [c] = EMPTY ; } ASSERT (k == n) ; /* done using Iwork [0..n-1] for Next ] */ } /* ---------------------------------------------------------------------- */ /* clear workspace and return number of components */ /* ---------------------------------------------------------------------- */ ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; return (ncomponents) ; } /* ========================================================================== */ /* === cholmod_collapse_septree ============================================= */ /* ========================================================================== */ /* cholmod_nested_dissection returns the separator tree that was used in the * constrained minimum degree algorithm. Parameter settings (nd_small, * nd_oksep, etc) that give a good fill-reducing ordering may give too fine of * a separator tree for other uses (parallelism, multi-level LPDASA, etc). This * function takes as input the separator tree computed by * cholmod_nested_dissection, and collapses selected subtrees into single * nodes. A subtree is collapsed if its root node (the separator) is large * compared to the total number of nodes in the subtree, or if the subtree is * small. Note that the separator tree may actually be a forest. * * nd_oksep and nd_small act just like the ordering parameters in Common. * Returns the new number of nodes in the separator tree. */ SuiteSparse_long CHOLMOD(collapse_septree) ( /* ---- input ---- */ size_t n, /* # of nodes in the graph */ size_t ncomponents, /* # of nodes in the separator tree (must be <= n) */ double nd_oksep, /* collapse if #sep >= nd_oksep * #nodes in subtree */ size_t nd_small, /* collapse if #nodes in subtree < nd_small */ /* ---- in/out --- */ Int *CParent, /* size ncomponents; from cholmod_nested_dissection */ Int *Cmember, /* size n; from cholmod_nested_dissection */ /* --------------- */ cholmod_common *Common ) { Int *First, *Count, *Csubtree, *W, *Map ; Int c, j, k, nc, sepsize, total_weight, parent, nc_new, first ; int collapse = FALSE, ok = TRUE ; size_t s ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (EMPTY) ; RETURN_IF_NULL (CParent, EMPTY) ; RETURN_IF_NULL (Cmember, EMPTY) ; if (n < ncomponents) { ERROR (CHOLMOD_INVALID, "invalid separator tree") ; return (EMPTY) ; } Common->status = CHOLMOD_OK ; nc = ncomponents ; if (n <= 1 || ncomponents <= 1) { /* no change; tree is one node already */ return (nc) ; } nd_oksep = MAX (0, nd_oksep) ; nd_oksep = MIN (1, nd_oksep) ; nd_small = MAX (4, nd_small) ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ /* s = 3*ncomponents */ s = CHOLMOD(mult_size_t) (ncomponents, 3, &ok) ; if (!ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return (EMPTY) ; } CHOLMOD(allocate_work) (0, s, 0, Common) ; if (Common->status < CHOLMOD_OK) { return (EMPTY) ; } W = Common->Iwork ; Count = W ; W += ncomponents ; /* size ncomponents */ Csubtree = W ; W += ncomponents ; /* size ncomponents */ First = W ; W += ncomponents ; /* size ncomponents */ /* ---------------------------------------------------------------------- */ /* find the first descendant of each node of the separator tree */ /* ---------------------------------------------------------------------- */ for (c = 0 ; c < nc ; c++) { First [c] = EMPTY ; } for (k = 0 ; k < nc ; k++) { for (c = k ; c != EMPTY && First [c] == -1 ; c = CParent [c]) { ASSERT (c >= 0 && c < nc) ; First [c] = k ; } } /* ---------------------------------------------------------------------- */ /* find the number of nodes of the graph in each node of the tree */ /* ---------------------------------------------------------------------- */ for (c = 0 ; c < nc ; c++) { Count [c] = 0 ; } for (j = 0 ; j < (Int) n ; j++) { ASSERT (Cmember [j] >= 0 && Cmember [j] < nc) ; Count [Cmember [j]]++ ; } /* ---------------------------------------------------------------------- */ /* find the number of nodes in each subtree */ /* ---------------------------------------------------------------------- */ for (c = 0 ; c < nc ; c++) { /* each subtree includes its root */ Csubtree [c] = Count [c] ; PRINT1 ((ID" size "ID" parent "ID" first "ID"\n", c, Count [c], CParent [c], First [c])) ; } for (c = 0 ; c < nc ; c++) { /* add the subtree of the child, c, into the count of its parent */ parent = CParent [c] ; ASSERT (parent >= EMPTY && parent < nc) ; if (parent != EMPTY) { Csubtree [parent] += Csubtree [c] ; } } #ifndef NDEBUG /* the sum of the roots should be n */ j = 0 ; for (c = 0 ; c < nc ; c++) if (CParent [c] == EMPTY) j += Csubtree [c] ; ASSERT (j == (Int) n) ; #endif /* ---------------------------------------------------------------------- */ /* find subtrees to collapse */ /* ---------------------------------------------------------------------- */ /* consider all nodes in reverse post-order */ for (c = nc-1 ; c >= 0 ; c--) { /* consider the subtree rooted at node c */ sepsize = Count [c] ; total_weight = Csubtree [c] ; PRINT1 (("Node "ID" sepsize "ID" subtree "ID" ratio %g\n", c, sepsize, total_weight, ((double) sepsize)/((double) total_weight))) ; first = First [c] ; if (first < c && /* c must not be a leaf */ (sepsize > nd_oksep * total_weight || total_weight < (int) nd_small)) { /* this separator is too large, or the subtree is too small. * collapse the tree, by converting the entire subtree rooted at * c into a single node. The subtree consists of all nodes from * First[c] to the root c. Flag all nodes from First[c] to c-1 * as dead. */ collapse = TRUE ; for (k = first ; k < c ; k++) { CParent [k] = -2 ; PRINT1 ((" collapse node "ID"\n", k)) ; } /* continue at the next node, first-1 */ c = first ; } } PRINT1 (("collapse: %d\n", collapse)) ; /* ---------------------------------------------------------------------- */ /* compress the tree */ /* ---------------------------------------------------------------------- */ Map = Count ; /* Count no longer needed */ nc_new = nc ; if (collapse) { nc_new = 0 ; for (c = 0 ; c < nc ; c++) { Map [c] = nc_new ; if (CParent [c] >= EMPTY) { /* node c is alive, and becomes node Map[c] in the new tree. * Increment nc_new for the next node c. */ nc_new++ ; } } PRINT1 (("Collapse the tree from "ID" to "ID" nodes\n", nc, nc_new)) ; ASSERT (nc_new > 0) ; for (c = 0 ; c < nc ; c++) { parent = CParent [c] ; if (parent >= EMPTY) { /* node c is alive */ CParent [Map [c]] = (parent == EMPTY) ? EMPTY : Map [parent] ; } } for (j = 0 ; j < (Int) n ; j++) { PRINT1 (("j "ID" Cmember[j] "ID" Map[Cmember[j]] "ID"\n", j, Cmember [j], Map [Cmember [j]])) ; Cmember [j] = Map [Cmember [j]] ; } } /* ---------------------------------------------------------------------- */ /* return new size of separator tree */ /* ---------------------------------------------------------------------- */ return (nc_new) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Partition/License.txt0000644000076500000240000000210413524616144026562 0ustar tamasstaff00000000000000CHOLMOD/Partition Module. Copyright (C) 2005-2006, Univ. of Florida. Author: Timothy A. Davis CHOLMOD is also available under other licenses; contact authors for details. http://www.suitesparse.com Note that this license is for the CHOLMOD/Partition module only. All CHOLMOD modules are licensed separately. -------------------------------------------------------------------------------- This Module is free software; you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation; either version 2.1 of the License, or (at your option) any later version. This Module is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with this Module; if not, write to the Free Software Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/MatrixOps/0000755000076500000240000000000013617375001024414 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/MatrixOps/t_cholmod_sdmult.c0000644000076500000240000004456313524616144030137 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === MatrixOps/t_cholmod_sdmult =========================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/MatrixOps Module. Copyright (C) 2005-2006, Timothy A. Davis * The CHOLMOD/MatrixOps Module is licensed under Version 2.0 of the GNU * General Public License. See gpl.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * http://www.suitesparse.com * -------------------------------------------------------------------------- */ /* Template routine for cholmod_sdmult */ #include "cholmod_template.h" #undef ADVANCE #ifdef REAL #define ADVANCE(x,z,d) x += d #elif defined (COMPLEX) #define ADVANCE(x,z,d) x += 2*d #else #define ADVANCE(x,z,d) x += d ; z += d #endif /* ========================================================================== */ /* === t_cholmod_sdmult ===================================================== */ /* ========================================================================== */ static void TEMPLATE (cholmod_sdmult) ( /* ---- input ---- */ cholmod_sparse *A, /* sparse matrix to multiply */ int transpose, /* use A if 0, or A' otherwise */ double alpha [2], /* scale factor for A */ double beta [2], /* scale factor for Y */ cholmod_dense *X, /* dense matrix to multiply */ /* ---- in/out --- */ cholmod_dense *Y, /* resulting dense matrix */ /* -- workspace -- */ double *W /* size 4*nx if needed, twice that for c/zomplex case */ ) { double yx [8], xx [8], ax [2] ; #ifdef ZOMPLEX double yz [4], xz [4], az [1] ; double betaz [1], alphaz [1] ; #endif double *Ax, *Az, *Xx, *Xz, *Yx, *Yz, *w, *Wz ; Int *Ap, *Ai, *Anz ; size_t nx, ny, dx, dy ; Int packed, nrow, ncol, j, k, p, pend, kcol, i ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ #ifdef ZOMPLEX betaz [0] = beta [1] ; alphaz [0] = alpha [1] ; #endif ny = transpose ? A->ncol : A->nrow ; /* required length of Y */ nx = transpose ? A->nrow : A->ncol ; /* required length of X */ nrow = A->nrow ; ncol = A->ncol ; Ap = A->p ; Anz = A->nz ; Ai = A->i ; Ax = A->x ; Az = A->z ; packed = A->packed ; Xx = X->x ; Xz = X->z ; Yx = Y->x ; Yz = Y->z ; kcol = X->ncol ; dy = Y->d ; dx = X->d ; w = W ; Wz = W + 4*nx ; /* ---------------------------------------------------------------------- */ /* Y = beta * Y */ /* ---------------------------------------------------------------------- */ if (ENTRY_IS_ZERO (beta, betaz, 0)) { for (k = 0 ; k < kcol ; k++) { for (i = 0 ; i < ((Int) ny) ; i++) { /* y [i] = 0. ; */ CLEAR (Yx, Yz, i) ; } /* y += dy ; */ ADVANCE (Yx,Yz,dy) ; } } else if (!ENTRY_IS_ONE (beta, betaz, 0)) { for (k = 0 ; k < kcol ; k++) { for (i = 0 ; i < ((Int) ny) ; i++) { /* y [i] *= beta [0] ; */ MULT (Yx,Yz,i, Yx,Yz,i, beta,betaz, 0) ; } /* y += dy ; */ ADVANCE (Yx,Yz,dy) ; } } if (ENTRY_IS_ZERO (alpha, alphaz, 0)) { /* nothing else to do */ return ; } /* ---------------------------------------------------------------------- */ /* Y += alpha * op(A) * X, where op(A)=A or A' */ /* ---------------------------------------------------------------------- */ Yx = Y->x ; Yz = Y->z ; k = 0 ; if (A->stype == 0) { if (transpose) { /* -------------------------------------------------------------- */ /* Y += alpha * A' * x, unsymmetric case */ /* -------------------------------------------------------------- */ if (kcol % 4 == 1) { for (j = 0 ; j < ncol ; j++) { /* yj = 0. ; */ CLEAR (yx, yz, 0) ; p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { /* yj += conj(Ax [p]) * x [Ai [p]] ; */ i = Ai [p] ; ASSIGN_CONJ (ax,az,0, Ax,Az,p) ; MULTADD (yx,yz,0, ax,az,0, Xx,Xz,i) ; } /* y [j] += alpha [0] * yj ; */ MULTADD (Yx,Yz,j, alpha,alphaz,0, yx,yz,0) ; } /* y += dy ; */ /* x += dx ; */ ADVANCE (Yx,Yz,dy) ; ADVANCE (Xx,Xz,dx) ; k++ ; } else if (kcol % 4 == 2) { for (j = 0 ; j < ncol ; j++) { /* yj0 = 0. ; */ /* yj1 = 0. ; */ CLEAR (yx,yz,0) ; CLEAR (yx,yz,1) ; p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { i = Ai [p] ; /* aij = conj (Ax [p]) ; */ ASSIGN_CONJ (ax,az,0, Ax,Az,p) ; /* yj0 += aij * x [i ] ; */ /* yj1 += aij * x [i+dx] ; */ MULTADD (yx,yz,0, ax,az,0, Xx,Xz,i) ; MULTADD (yx,yz,1, ax,az,0, Xx,Xz,i+dx) ; } /* y [j ] += alpha [0] * yj0 ; */ /* y [j+dy] += alpha [0] * yj1 ; */ MULTADD (Yx,Yz,j, alpha,alphaz,0, yx,yz,0) ; MULTADD (Yx,Yz,j+dy, alpha,alphaz,0, yx,yz,1) ; } /* y += 2*dy ; */ /* x += 2*dx ; */ ADVANCE (Yx,Yz,2*dy) ; ADVANCE (Xx,Xz,2*dx) ; k += 2 ; } else if (kcol % 4 == 3) { for (j = 0 ; j < ncol ; j++) { /* yj0 = 0. ; */ /* yj1 = 0. ; */ /* yj2 = 0. ; */ CLEAR (yx,yz,0) ; CLEAR (yx,yz,1) ; CLEAR (yx,yz,2) ; p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { i = Ai [p] ; /* aij = conj (Ax [p]) ; */ ASSIGN_CONJ (ax,az,0, Ax,Az,p) ; /* yj0 += aij * x [i ] ; */ /* yj1 += aij * x [i+ dx] ; */ /* yj2 += aij * x [i+2*dx] ; */ MULTADD (yx,yz,0, ax,az,0, Xx,Xz,i) ; MULTADD (yx,yz,1, ax,az,0, Xx,Xz,i+dx) ; MULTADD (yx,yz,2, ax,az,0, Xx,Xz,i+2*dx) ; } /* y [j ] += alpha [0] * yj0 ; */ /* y [j+ dy] += alpha [0] * yj1 ; */ /* y [j+2*dy] += alpha [0] * yj2 ; */ MULTADD (Yx,Yz,j, alpha,alphaz,0, yx,yz,0) ; MULTADD (Yx,Yz,j+dy, alpha,alphaz,0, yx,yz,1) ; MULTADD (Yx,Yz,j+2*dy, alpha,alphaz,0, yx,yz,2) ; } /* y += 3*dy ; */ /* x += 3*dx ; */ ADVANCE (Yx,Yz,3*dy) ; ADVANCE (Xx,Xz,3*dx) ; k += 3 ; } for ( ; k < kcol ; k += 4) { for (j = 0 ; j < ncol ; j++) { /* yj0 = 0. ; */ /* yj1 = 0. ; */ /* yj2 = 0. ; */ /* yj3 = 0. ; */ CLEAR (yx,yz,0) ; CLEAR (yx,yz,1) ; CLEAR (yx,yz,2) ; CLEAR (yx,yz,3) ; p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { i = Ai [p] ; /* aij = conj(Ax [p]) ; */ ASSIGN_CONJ (ax,az,0, Ax,Az,p) ; /* yj0 += aij * x [i ] ; */ /* yj1 += aij * x [i+ dx] ; */ /* yj2 += aij * x [i+2*dx] ; */ /* yj3 += aij * x [i+3*dx] ; */ MULTADD (yx,yz,0, ax,az,0, Xx,Xz,i) ; MULTADD (yx,yz,1, ax,az,0, Xx,Xz,i+dx) ; MULTADD (yx,yz,2, ax,az,0, Xx,Xz,i+2*dx) ; MULTADD (yx,yz,3, ax,az,0, Xx,Xz,i+3*dx) ; } /* y [j ] += alpha [0] * yj0 ; */ /* y [j+ dy] += alpha [0] * yj1 ; */ /* y [j+2*dy] += alpha [0] * yj2 ; */ /* y [j+3*dy] += alpha [0] * yj3 ; */ MULTADD (Yx,Yz,j, alpha,alphaz,0, yx,yz,0) ; MULTADD (Yx,Yz,j+dy, alpha,alphaz,0, yx,yz,1) ; MULTADD (Yx,Yz,j+2*dy, alpha,alphaz,0, yx,yz,2) ; MULTADD (Yx,Yz,j+3*dy, alpha,alphaz,0, yx,yz,3) ; } /* y += 4*dy ; */ /* x += 4*dx ; */ ADVANCE (Yx,Yz,4*dy) ; ADVANCE (Xx,Xz,4*dx) ; } } else { /* -------------------------------------------------------------- */ /* Y += alpha * A * x, unsymmetric case */ /* -------------------------------------------------------------- */ if (kcol % 4 == 1) { for (j = 0 ; j < ncol ; j++) { /* xj = alpha [0] * x [j] ; */ MULT (xx,xz,0, alpha,alphaz,0, Xx,Xz,j) ; p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { /* y [Ai [p]] += Ax [p] * xj ; */ i = Ai [p] ; MULTADD (Yx,Yz,i, Ax,Az,p, xx,xz,0) ; } } /* y += dy ; */ /* x += dx ; */ ADVANCE (Yx,Yz,dy) ; ADVANCE (Xx,Xz,dx) ; k++ ; } else if (kcol % 4 == 2) { for (j = 0 ; j < ncol ; j++) { /* xj0 = alpha [0] * x [j ] ; */ /* xj1 = alpha [0] * x [j+dx] ; */ MULT (xx,xz,0, alpha,alphaz,0, Xx,Xz,j) ; MULT (xx,xz,1, alpha,alphaz,0, Xx,Xz,j+dx) ; p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { i = Ai [p] ; /* aij = Ax [p] ; */ ASSIGN (ax,az,0, Ax,Az,p) ; /* y [i ] += aij * xj0 ; */ /* y [i+dy] += aij * xj1 ; */ MULTADD (Yx,Yz,i, ax,az,0, xx,xz,0) ; MULTADD (Yx,Yz,i+dy, ax,az,0, xx,xz,1) ; } } /* y += 2*dy ; */ /* x += 2*dx ; */ ADVANCE (Yx,Yz,2*dy) ; ADVANCE (Xx,Xz,2*dx) ; k += 2 ; } else if (kcol % 4 == 3) { for (j = 0 ; j < ncol ; j++) { /* xj0 = alpha [0] * x [j ] ; */ /* xj1 = alpha [0] * x [j+ dx] ; */ /* xj2 = alpha [0] * x [j+2*dx] ; */ MULT (xx,xz,0, alpha,alphaz,0, Xx,Xz,j) ; MULT (xx,xz,1, alpha,alphaz,0, Xx,Xz,j+dx) ; MULT (xx,xz,2, alpha,alphaz,0, Xx,Xz,j+2*dx) ; p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { i = Ai [p] ; /* aij = Ax [p] ; */ ASSIGN (ax,az,0, Ax,Az,p) ; /* y [i ] += aij * xj0 ; */ /* y [i+ dy] += aij * xj1 ; */ /* y [i+2*dy] += aij * xj2 ; */ MULTADD (Yx,Yz,i, ax,az,0, xx,xz,0) ; MULTADD (Yx,Yz,i+dy, ax,az,0, xx,xz,1) ; MULTADD (Yx,Yz,i+2*dy, ax,az,0, xx,xz,2) ; } } /* y += 3*dy ; */ /* x += 3*dx ; */ ADVANCE (Yx,Yz,3*dy) ; ADVANCE (Xx,Xz,3*dx) ; k += 3 ; } for ( ; k < kcol ; k += 4) { for (j = 0 ; j < ncol ; j++) { /* xj0 = alpha [0] * x [j ] ; */ /* xj1 = alpha [0] * x [j+ dx] ; */ /* xj2 = alpha [0] * x [j+2*dx] ; */ /* xj3 = alpha [0] * x [j+3*dx] ; */ MULT (xx,xz,0, alpha,alphaz,0, Xx,Xz,j) ; MULT (xx,xz,1, alpha,alphaz,0, Xx,Xz,j+dx) ; MULT (xx,xz,2, alpha,alphaz,0, Xx,Xz,j+2*dx) ; MULT (xx,xz,3, alpha,alphaz,0, Xx,Xz,j+3*dx) ; p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { i = Ai [p] ; /* aij = Ax [p] ; */ ASSIGN (ax,az,0, Ax,Az,p) ; /* y [i ] += aij * xj0 ; */ /* y [i+ dy] += aij * xj1 ; */ /* y [i+2*dy] += aij * xj2 ; */ /* y [i+3*dy] += aij * xj3 ; */ MULTADD (Yx,Yz,i, ax,az,0, xx,xz,0) ; MULTADD (Yx,Yz,i+dy, ax,az,0, xx,xz,1) ; MULTADD (Yx,Yz,i+2*dy, ax,az,0, xx,xz,2) ; MULTADD (Yx,Yz,i+3*dy, ax,az,0, xx,xz,3) ; } } /* y += 4*dy ; */ /* x += 4*dx ; */ ADVANCE (Yx,Yz,4*dy) ; ADVANCE (Xx,Xz,4*dx) ; } } } else { /* ------------------------------------------------------------------ */ /* Y += alpha * (A or A') * x, symmetric case (upper/lower) */ /* ------------------------------------------------------------------ */ /* Only the upper/lower triangular part and the diagonal of A is used. * Since both x and y are written to in the innermost loop, this * code can experience cache bank conflicts if x is used directly. * Thus, a copy is made of x, four columns at a time, if x has * four or more columns. */ if (kcol % 4 == 1) { for (j = 0 ; j < ncol ; j++) { /* yj = 0. ; */ CLEAR (yx,yz,0) ; /* xj = alpha [0] * x [j] ; */ MULT (xx,xz,0, alpha,alphaz,0, Xx,Xz,j) ; p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { i = Ai [p] ; if (i == j) { /* y [i] += Ax [p] * xj ; */ MULTADD (Yx,Yz,i, Ax,Az,p, xx,xz,0) ; } else if ((A->stype > 0 && i < j) || (A->stype < 0 && i > j)) { /* aij = Ax [p] ; */ ASSIGN (ax,az,0, Ax,Az,p) ; /* y [i] += aij * xj ; */ /* yj += aij * x [i] ; */ MULTADD (Yx,Yz,i, ax,az,0, xx,xz,0) ; MULTADDCONJ (yx,yz,0, ax,az,0, Xx,Xz,i) ; } } /* y [j] += alpha [0] * yj ; */ MULTADD (Yx,Yz,j, alpha,alphaz,0, yx,yz,0) ; } /* y += dy ; */ /* x += dx ; */ ADVANCE (Yx,Yz,dy) ; ADVANCE (Xx,Xz,dx) ; k++ ; } else if (kcol % 4 == 2) { for (j = 0 ; j < ncol ; j++) { /* yj0 = 0. ; */ /* yj1 = 0. ; */ CLEAR (yx,yz,0) ; CLEAR (yx,yz,1) ; /* xj0 = alpha [0] * x [j ] ; */ /* xj1 = alpha [0] * x [j+dx] ; */ MULT (xx,xz,0, alpha,alphaz,0, Xx,Xz,j) ; MULT (xx,xz,1, alpha,alphaz,0, Xx,Xz,j+dx) ; p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { i = Ai [p] ; if (i == j) { /* aij = Ax [p] ; */ ASSIGN (ax,az,0, Ax,Az,p) ; /* y [i ] += aij * xj0 ; */ /* y [i+dy] += aij * xj1 ; */ MULTADD (Yx,Yz,i, ax,az,0, xx,xz,0) ; MULTADD (Yx,Yz,i+dy, ax,az,0, xx,xz,1) ; } else if ((A->stype > 0 && i < j) || (A->stype < 0 && i > j)) { /* aij = Ax [p] ; */ ASSIGN (ax,az,0, Ax,Az,p) ; /* y [i ] += aij * xj0 ; */ /* y [i+dy] += aij * xj1 ; */ /* yj0 += aij * x [i ] ; */ /* yj1 += aij * x [i+dx] ; */ MULTADD (Yx,Yz,i, ax,az,0, xx,xz,0) ; MULTADD (Yx,Yz,i+dy, ax,az,0, xx,xz,1) ; MULTADDCONJ (yx,yz,0, ax,az,0, Xx,Xz,i) ; MULTADDCONJ (yx,yz,1, ax,az,0, Xx,Xz,i+dx) ; } } /* y [j ] += alpha [0] * yj0 ; */ /* y [j+dy] += alpha [0] * yj1 ; */ MULTADD (Yx,Yz,j, alpha,alphaz,0, yx,yz,0) ; MULTADD (Yx,Yz,j+dy, alpha,alphaz,0, yx,yz,1) ; } /* y += 2*dy ; */ /* x += 2*dx ; */ ADVANCE (Yx,Yz,2*dy) ; ADVANCE (Xx,Xz,2*dx) ; k += 2 ; } else if (kcol % 4 == 3) { for (j = 0 ; j < ncol ; j++) { /* yj0 = 0. ; */ /* yj1 = 0. ; */ /* yj2 = 0. ; */ CLEAR (yx,yz,0) ; CLEAR (yx,yz,1) ; CLEAR (yx,yz,2) ; /* xj0 = alpha [0] * x [j ] ; */ /* xj1 = alpha [0] * x [j+ dx] ; */ /* xj2 = alpha [0] * x [j+2*dx] ; */ MULT (xx,xz,0, alpha,alphaz,0, Xx,Xz,j) ; MULT (xx,xz,1, alpha,alphaz,0, Xx,Xz,j+dx) ; MULT (xx,xz,2, alpha,alphaz,0, Xx,Xz,j+2*dx) ; p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { i = Ai [p] ; if (i == j) { /* aij = Ax [p] ; */ ASSIGN (ax,az,0, Ax,Az,p) ; /* y [i ] += aij * xj0 ; */ /* y [i+ dy] += aij * xj1 ; */ /* y [i+2*dy] += aij * xj2 ; */ MULTADD (Yx,Yz,i, ax,az,0, xx,xz,0) ; MULTADD (Yx,Yz,i+dy, ax,az,0, xx,xz,1) ; MULTADD (Yx,Yz,i+2*dy, ax,az,0, xx,xz,2) ; } else if ((A->stype > 0 && i < j) || (A->stype < 0 && i > j)) { /* aij = Ax [p] ; */ ASSIGN (ax,az,0, Ax,Az,p) ; /* y [i ] += aij * xj0 ; */ /* y [i+ dy] += aij * xj1 ; */ /* y [i+2*dy] += aij * xj2 ; */ /* yj0 += aij * x [i ] ; */ /* yj1 += aij * x [i+ dx] ; */ /* yj2 += aij * x [i+2*dx] ; */ MULTADD (Yx,Yz,i, ax,az,0, xx,xz,0) ; MULTADD (Yx,Yz,i+dy, ax,az,0, xx,xz,1) ; MULTADD (Yx,Yz,i+2*dy, ax,az,0, xx,xz,2) ; MULTADDCONJ (yx,yz,0, ax,az,0, Xx,Xz,i) ; MULTADDCONJ (yx,yz,1, ax,az,0, Xx,Xz,i+dx) ; MULTADDCONJ (yx,yz,2, ax,az,0, Xx,Xz,i+2*dx) ; } } /* y [j ] += alpha [0] * yj0 ; */ /* y [j+ dy] += alpha [0] * yj1 ; */ /* y [j+2*dy] += alpha [0] * yj2 ; */ MULTADD (Yx,Yz,j, alpha,alphaz,0, yx,yz,0) ; MULTADD (Yx,Yz,j+dy, alpha,alphaz,0, yx,yz,1) ; MULTADD (Yx,Yz,j+2*dy, alpha,alphaz,0, yx,yz,2) ; } /* y += 3*dy ; */ /* x += 3*dx ; */ ADVANCE (Yx,Yz,3*dy) ; ADVANCE (Xx,Xz,3*dx) ; k += 3 ; } /* copy four columns of X into W, and put in row form */ for ( ; k < kcol ; k += 4) { for (j = 0 ; j < ncol ; j++) { /* w [4*j ] = x [j ] ; */ /* w [4*j+1] = x [j+ dx] ; */ /* w [4*j+2] = x [j+2*dx] ; */ /* w [4*j+3] = x [j+3*dx] ; */ ASSIGN (w,Wz,4*j , Xx,Xz,j ) ; ASSIGN (w,Wz,4*j+1, Xx,Xz,j+dx ) ; ASSIGN (w,Wz,4*j+2, Xx,Xz,j+2*dx) ; ASSIGN (w,Wz,4*j+3, Xx,Xz,j+3*dx) ; } for (j = 0 ; j < ncol ; j++) { /* yj0 = 0. ; */ /* yj1 = 0. ; */ /* yj2 = 0. ; */ /* yj3 = 0. ; */ CLEAR (yx,yz,0) ; CLEAR (yx,yz,1) ; CLEAR (yx,yz,2) ; CLEAR (yx,yz,3) ; /* xj0 = alpha [0] * w [4*j ] ; */ /* xj1 = alpha [0] * w [4*j+1] ; */ /* xj2 = alpha [0] * w [4*j+2] ; */ /* xj3 = alpha [0] * w [4*j+3] ; */ MULT (xx,xz,0, alpha,alphaz,0, w,Wz,4*j) ; MULT (xx,xz,1, alpha,alphaz,0, w,Wz,4*j+1) ; MULT (xx,xz,2, alpha,alphaz,0, w,Wz,4*j+2) ; MULT (xx,xz,3, alpha,alphaz,0, w,Wz,4*j+3) ; p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { i = Ai [p] ; if (i == j) { /* aij = Ax [p] ; */ ASSIGN (ax,az,0, Ax,Az,p) ; /* y [i ] += aij * xj0 ; */ /* y [i+ dy] += aij * xj1 ; */ /* y [i+2*dy] += aij * xj2 ; */ /* y [i+3*dy] += aij * xj3 ; */ MULTADD (Yx,Yz,i , ax,az,0, xx,xz,0) ; MULTADD (Yx,Yz,i+dy , ax,az,0, xx,xz,1) ; MULTADD (Yx,Yz,i+2*dy, ax,az,0, xx,xz,2) ; MULTADD (Yx,Yz,i+3*dy, ax,az,0, xx,xz,3) ; } else if ((A->stype > 0 && i < j) || (A->stype < 0 && i > j)) { /* aij = Ax [p] ; */ ASSIGN (ax,az,0, Ax,Az,p) ; /* y [i ] += aij * xj0 ; */ /* y [i+ dy] += aij * xj1 ; */ /* y [i+2*dy] += aij * xj2 ; */ /* y [i+3*dy] += aij * xj3 ; */ /* yj0 += aij * w [4*i ] ; */ /* yj1 += aij * w [4*i+1] ; */ /* yj2 += aij * w [4*i+2] ; */ /* yj3 += aij * w [4*i+3] ; */ MULTADD (Yx,Yz,i, ax,az,0, xx,xz,0) ; MULTADD (Yx,Yz,i+dy, ax,az,0, xx,xz,1) ; MULTADD (Yx,Yz,i+2*dy, ax,az,0, xx,xz,2) ; MULTADD (Yx,Yz,i+3*dy, ax,az,0, xx,xz,3) ; MULTADDCONJ (yx,yz,0, ax,az,0, w,Wz,4*i) ; MULTADDCONJ (yx,yz,1, ax,az,0, w,Wz,4*i+1) ; MULTADDCONJ (yx,yz,2, ax,az,0, w,Wz,4*i+2) ; MULTADDCONJ (yx,yz,3, ax,az,0, w,Wz,4*i+3) ; } } /* y [j ] += alpha [0] * yj0 ; */ /* y [j+ dy] += alpha [0] * yj1 ; */ /* y [j+2*dy] += alpha [0] * yj2 ; */ /* y [j+3*dy] += alpha [0] * yj3 ; */ MULTADD (Yx,Yz,j , alpha,alphaz,0, yx,yz,0) ; MULTADD (Yx,Yz,j+dy , alpha,alphaz,0, yx,yz,1) ; MULTADD (Yx,Yz,j+2*dy, alpha,alphaz,0, yx,yz,2) ; MULTADD (Yx,Yz,j+3*dy, alpha,alphaz,0, yx,yz,3) ; } /* y += 4*dy ; */ /* x += 4*dx ; */ ADVANCE (Yx,Yz,4*dy) ; ADVANCE (Xx,Xz,4*dx) ; } } } #undef PATTERN #undef REAL #undef COMPLEX #undef ZOMPLEX python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/MatrixOps/cholmod_horzcat.c0000644000076500000240000001422213524616144027743 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === MatrixOps/cholmod_horzcat ============================================ */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/MatrixOps Module. Copyright (C) 2005-2006, Timothy A. Davis * The CHOLMOD/MatrixOps Module is licensed under Version 2.0 of the GNU * General Public License. See gpl.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * http://www.suitesparse.com * -------------------------------------------------------------------------- */ /* Horizontal concatenation, C = [A , B] in MATLAB notation. * * A and B can be up/lo/unsym; C is unsymmetric and packed. * A and B must have the same number of rows. * C is sorted if both A and B are sorted. * * workspace: Iwork (max (A->nrow, A->ncol, B->nrow, B->ncol)). * allocates temporary copies of A and B if they are symmetric. * * A and B must have the same numeric xtype, unless values is FALSE. * A and B cannot be complex or zomplex, unless values is FALSE. */ #ifndef NMATRIXOPS #include "cholmod_internal.h" #include "cholmod_matrixops.h" /* ========================================================================== */ /* === cholmod_horzcat ====================================================== */ /* ========================================================================== */ cholmod_sparse *CHOLMOD(horzcat) ( /* ---- input ---- */ cholmod_sparse *A, /* left matrix to concatenate */ cholmod_sparse *B, /* right matrix to concatenate */ int values, /* if TRUE compute the numerical values of C */ /* --------------- */ cholmod_common *Common ) { double *Ax, *Bx, *Cx ; Int *Ap, *Ai, *Anz, *Bp, *Bi, *Bnz, *Cp, *Ci ; cholmod_sparse *C, *A2, *B2 ; Int apacked, bpacked, ancol, bncol, ncol, nrow, anz, bnz, nz, j, p, pend, pdest ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; RETURN_IF_NULL (A, NULL) ; RETURN_IF_NULL (B, NULL) ; values = values && (A->xtype != CHOLMOD_PATTERN) && (B->xtype != CHOLMOD_PATTERN) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, values ? CHOLMOD_REAL : CHOLMOD_ZOMPLEX, NULL) ; RETURN_IF_XTYPE_INVALID (B, CHOLMOD_PATTERN, values ? CHOLMOD_REAL : CHOLMOD_ZOMPLEX, NULL) ; if (A->nrow != B->nrow) { /* A and B must have the same number of rows */ ERROR (CHOLMOD_INVALID, "A and B must have same # rows") ; return (NULL) ; } /* A and B must have the same numerical type if values is TRUE (both must * be CHOLMOD_REAL, this is implicitly checked above) */ Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ ancol = A->ncol ; bncol = B->ncol ; nrow = A->nrow ; CHOLMOD(allocate_work) (0, MAX3 (nrow, ancol, bncol), 0, Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ return (NULL) ; } /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ /* convert A to unsymmetric, if necessary */ A2 = NULL ; if (A->stype != 0) { /* workspace: Iwork (max (A->nrow,A->ncol)) */ A2 = CHOLMOD(copy) (A, 0, values, Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ return (NULL) ; } A = A2 ; } /* convert B to unsymmetric, if necessary */ B2 = NULL ; if (B->stype != 0) { /* workspace: Iwork (max (B->nrow,B->ncol)) */ B2 = CHOLMOD(copy) (B, 0, values, Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ CHOLMOD(free_sparse) (&A2, Common) ; return (NULL) ; } B = B2 ; } Ap = A->p ; Anz = A->nz ; Ai = A->i ; Ax = A->x ; apacked = A->packed ; Bp = B->p ; Bnz = B->nz ; Bi = B->i ; Bx = B->x ; bpacked = B->packed ; /* ---------------------------------------------------------------------- */ /* allocate C */ /* ---------------------------------------------------------------------- */ anz = CHOLMOD(nnz) (A, Common) ; bnz = CHOLMOD(nnz) (B, Common) ; ncol = ancol + bncol ; nz = anz + bnz ; C = CHOLMOD(allocate_sparse) (nrow, ncol, nz, A->sorted && B->sorted, TRUE, 0, values ? A->xtype : CHOLMOD_PATTERN, Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ CHOLMOD(free_sparse) (&A2, Common) ; CHOLMOD(free_sparse) (&B2, Common) ; return (NULL) ; } Cp = C->p ; Ci = C->i ; Cx = C->x ; /* ---------------------------------------------------------------------- */ /* C = [A , B] */ /* ---------------------------------------------------------------------- */ pdest = 0 ; /* copy A as the first A->ncol columns of C */ for (j = 0 ; j < ancol ; j++) { /* A(:,j) is the jth column of C */ p = Ap [j] ; pend = (apacked) ? (Ap [j+1]) : (p + Anz [j]) ; Cp [j] = pdest ; for ( ; p < pend ; p++) { Ci [pdest] = Ai [p] ; if (values) Cx [pdest] = Ax [p] ; pdest++ ; } } /* copy B as the next B->ncol columns of C */ for (j = 0 ; j < bncol ; j++) { /* B(:,j) is the (ancol+j)th column of C */ p = Bp [j] ; pend = (bpacked) ? (Bp [j+1]) : (p + Bnz [j]) ; Cp [ancol + j] = pdest ; for ( ; p < pend ; p++) { Ci [pdest] = Bi [p] ; if (values) Cx [pdest] = Bx [p] ; pdest++ ; } } Cp [ncol] = pdest ; ASSERT (pdest == anz + bnz) ; /* ---------------------------------------------------------------------- */ /* free the unsymmetric copies of A and B, and return C */ /* ---------------------------------------------------------------------- */ CHOLMOD(free_sparse) (&A2, Common) ; CHOLMOD(free_sparse) (&B2, Common) ; return (C) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/MatrixOps/cholmod_sdmult.c0000644000076500000240000001240213524616144027577 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === MatrixOps/cholmod_sdmult ============================================= */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/MatrixOps Module. Copyright (C) 2005-2006, Timothy A. Davis * The CHOLMOD/MatrixOps Module is licensed under Version 2.0 of the GNU * General Public License. See gpl.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * http://www.suitesparse.com * -------------------------------------------------------------------------- */ /* Sparse matrix times dense matrix: * Y = alpha*(A*X) + beta*Y or Y = alpha*(A'*X) + beta*Y, * where A is sparse and X and Y are dense. * * when using A, X has A->ncol columns and Y has A->nrow rows * when using A', X has A->nrow columns and Y has A->ncol rows * * workspace: none in Common. Temporary workspace of size 4*(X->nrow) is used * if A is stored in symmetric form and X has four columns or more. If the * workspace is not available, a slower method is used instead that requires * no workspace. * * transpose = 0: use A * otherwise, use A' (complex conjugate transpose) * * transpose is ignored if the matrix is symmetric or Hermitian. * (the array transpose A.' is not supported). * * Supports real, complex, and zomplex matrices, but the xtypes of A, X, and Y * must all match. */ #ifndef NMATRIXOPS #include "cholmod_internal.h" #include "cholmod_matrixops.h" /* ========================================================================== */ /* === TEMPLATE ============================================================= */ /* ========================================================================== */ #define REAL #include "t_cholmod_sdmult.c" #define COMPLEX #include "t_cholmod_sdmult.c" #define ZOMPLEX #include "t_cholmod_sdmult.c" /* ========================================================================== */ /* === cholmod_sdmult ======================================================= */ /* ========================================================================== */ int CHOLMOD(sdmult) ( /* ---- input ---- */ cholmod_sparse *A, /* sparse matrix to multiply */ int transpose, /* use A if 0, otherwise use A' */ double alpha [2], /* scale factor for A */ double beta [2], /* scale factor for Y */ cholmod_dense *X, /* dense matrix to multiply */ /* ---- in/out --- */ cholmod_dense *Y, /* resulting dense matrix */ /* --------------- */ cholmod_common *Common ) { double *w ; size_t nx, ny ; Int e ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (A, FALSE) ; RETURN_IF_NULL (X, FALSE) ; RETURN_IF_NULL (Y, FALSE) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_REAL, CHOLMOD_ZOMPLEX, FALSE) ; RETURN_IF_XTYPE_INVALID (X, CHOLMOD_REAL, CHOLMOD_ZOMPLEX, FALSE) ; RETURN_IF_XTYPE_INVALID (Y, CHOLMOD_REAL, CHOLMOD_ZOMPLEX, FALSE) ; ny = transpose ? A->ncol : A->nrow ; /* required length of Y */ nx = transpose ? A->nrow : A->ncol ; /* required length of X */ if (X->nrow != nx || X->ncol != Y->ncol || Y->nrow != ny) { /* X and/or Y have the wrong dimension */ ERROR (CHOLMOD_INVALID, "X and/or Y have wrong dimensions") ; return (FALSE) ; } if (A->xtype != X->xtype || A->xtype != Y->xtype) { ERROR (CHOLMOD_INVALID, "A, X, and Y must have same xtype") ; return (FALSE) ; } Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* allocate workspace, if required */ /* ---------------------------------------------------------------------- */ w = NULL ; e = (A->xtype == CHOLMOD_REAL ? 1:2) ; if (A->stype && X->ncol >= 4) { w = CHOLMOD(malloc) (nx, 4*e*sizeof (double), Common) ; } if (Common->status < CHOLMOD_OK) { return (FALSE) ; /* out of memory */ } /* ---------------------------------------------------------------------- */ /* Y = alpha*op(A)*X + beta*Y via template routine */ /* ---------------------------------------------------------------------- */ ASSERT (CHOLMOD(dump_sparse) (A, "A", Common) >= 0) ; DEBUG (CHOLMOD(dump_dense) (X, "X", Common)) ; DEBUG (if (IS_NONZERO (beta [0]) || (IS_NONZERO (beta [1]) && A->xtype != CHOLMOD_REAL)) CHOLMOD(dump_dense) (Y, "Y", Common)) ; switch (A->xtype) { case CHOLMOD_REAL: r_cholmod_sdmult (A, transpose, alpha, beta, X, Y, w) ; break ; case CHOLMOD_COMPLEX: c_cholmod_sdmult (A, transpose, alpha, beta, X, Y, w) ; break ; case CHOLMOD_ZOMPLEX: z_cholmod_sdmult (A, transpose, alpha, beta, X, Y, w) ; break ; } /* ---------------------------------------------------------------------- */ /* free workspace */ /* ---------------------------------------------------------------------- */ CHOLMOD(free) (4*nx, e*sizeof (double), w, Common) ; DEBUG (CHOLMOD(dump_dense) (Y, "Y", Common)) ; return (TRUE) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/MatrixOps/cholmod_symmetry.c0000644000076500000240000004020413524616144030161 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === MatrixOps/cholmod_symmetry =========================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/MatrixOps Module. Copyright (C) 2005-2006, Timothy A. Davis * The CHOLMOD/MatrixOps Module is licensed under Version 2.0 of the GNU * General Public License. See gpl.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * http://www.suitesparse.com * -------------------------------------------------------------------------- */ /* Determines if a sparse matrix is rectangular, unsymmetric, symmetric, * skew-symmetric, or Hermitian. It does so by looking at its numerical values * of both upper and lower triangular parts of a CHOLMOD "unsymmetric" * matrix, where A->stype == 0. The transpose of A is NOT constructed. * * If not unsymmetric, it also determines if the matrix has a diagonal whose * entries are all real and positive (and thus a candidate for sparse Cholesky * if A->stype is changed to a nonzero value). * * Note that a Matrix Market "general" matrix is either rectangular or * unsymmetric. * * The row indices in the column of each matrix MUST be sorted for this function * to work properly (A->sorted must be TRUE). This routine returns EMPTY if * A->stype is not zero, or if A->sorted is FALSE. The exception to this rule * is if A is rectangular. * * If option == 0, then this routine returns immediately when it finds a * non-positive diagonal entry (or one with nonzero imaginary part). If the * matrix is not a candidate for sparse Cholesky, it returns the value * CHOLMOD_MM_UNSYMMETRIC, even if the matrix might in fact be symmetric or * Hermitian. * * This routine is useful inside the MATLAB backslash, which must look at an * arbitrary matrix (A->stype == 0) and determine if it is a candidate for * sparse Cholesky. In that case, option should be 0. * * This routine is also useful when writing a MATLAB matrix to a file in * Rutherford/Boeing or Matrix Market format. Those formats require a * determination as to the symmetry of the matrix, and thus this routine should * not return upon encountering the first non-positive diagonal. In this case, * option should be 1. * * If option is 2, this function can be used to compute the numerical and * pattern symmetry, where 0 is a completely unsymmetric matrix, and 1 is a * perfectly symmetric matrix. This option is used when computing the following * statistics for the matrices in the UF Sparse Matrix Collection. * * numerical symmetry: number of matched offdiagonal nonzeros over * the total number of offdiagonal entries. A real entry A(i,j), i ~= j, * is matched if A (j,i) == A (i,j), but this is only counted if both * A(j,i) and A(i,j) are nonzero. This does not depend on Z. * (If A is complex, then the above test is modified; A (i,j) is matched * if conj (A (j,i)) == A (i,j)). * * Then numeric symmetry = xmatched / nzoffdiag, or 1 if nzoffdiag = 0. * * pattern symmetry: number of matched offdiagonal entries over the * total number of offdiagonal entries. An entry A(i,j), i ~= j, is * matched if A (j,i) is also an entry. * * Then pattern symmetry = pmatched / nzoffdiag, or 1 if nzoffdiag = 0. * * The symmetry of a matrix with no offdiagonal entries is equal to 1. * * A workspace of size ncol integers is allocated; EMPTY is returned if this * allocation fails. * * Summary of return values: * * EMPTY (-1) out of memory, stype not zero, A not sorted * CHOLMOD_MM_RECTANGULAR 1 A is rectangular * CHOLMOD_MM_UNSYMMETRIC 2 A is unsymmetric * CHOLMOD_MM_SYMMETRIC 3 A is symmetric, but with non-pos. diagonal * CHOLMOD_MM_HERMITIAN 4 A is Hermitian, but with non-pos. diagonal * CHOLMOD_MM_SKEW_SYMMETRIC 5 A is skew symmetric * CHOLMOD_MM_SYMMETRIC_POSDIAG 6 A is symmetric with positive diagonal * CHOLMOD_MM_HERMITIAN_POSDIAG 7 A is Hermitian with positive diagonal * * See also the spsym mexFunction, which is a MATLAB interface for this code. * * If the matrix is a candidate for sparse Cholesky, it will return a result * CHOLMOD_MM_SYMMETRIC_POSDIAG if real, or CHOLMOD_MM_HERMITIAN_POSDIAG if * complex. Otherwise, it will return a value less than this. This is true * regardless of the value of the option parameter. */ #ifndef NMATRIXOPS #include "cholmod_internal.h" #include "cholmod_matrixops.h" /* ========================================================================== */ /* === get_value ============================================================ */ /* ========================================================================== */ /* Get the pth value in the matrix. */ static void get_value ( double *Ax, /* real values, or real/imag. for CHOLMOD_COMPLEX type */ double *Az, /* imaginary values for CHOLMOD_ZOMPLEX type */ Int p, /* get the pth entry */ Int xtype, /* A->xtype: pattern, real, complex, or zomplex */ double *x, /* the real part */ double *z /* the imaginary part */ ) { switch (xtype) { case CHOLMOD_PATTERN: *x = 1 ; *z = 0 ; break ; case CHOLMOD_REAL: *x = Ax [p] ; *z = 0 ; break ; case CHOLMOD_COMPLEX: *x = Ax [2*p] ; *z = Ax [2*p+1] ; break ; case CHOLMOD_ZOMPLEX: *x = Ax [p] ; *z = Az [p] ; break ; } } /* ========================================================================== */ /* === cholmod_symmetry ===================================================== */ /* ========================================================================== */ /* Determine the symmetry of a matrix, and check its diagonal. * * option 0: Do not count # of matched pairs. Quick return if the * the matrix has a zero, negative, or imaginary diagonal entry. * * option 1: Do not count # of matched pairs. Do not return quickly if * the matrix has a zero, negative, or imaginary diagonal entry. * The result 1 to 7 is accurately computed: * * EMPTY (-1) out of memory, stype not zero, A not sorted * CHOLMOD_MM_RECTANGULAR 1 A is rectangular * CHOLMOD_MM_UNSYMMETRIC 2 A is unsymmetric * CHOLMOD_MM_SYMMETRIC 3 A is symmetric, with non-pos. diagonal * CHOLMOD_MM_HERMITIAN 4 A is Hermitian, with non-pos. diagonal * CHOLMOD_MM_SKEW_SYMMETRIC 5 A is skew symmetric * CHOLMOD_MM_SYMMETRIC_POSDIAG 6 is symmetric with positive diagonal * CHOLMOD_MM_HERMITIAN_POSDIAG 7 A is Hermitian with positive diagonal * * The routine returns as soon as the above is determined (that is, it * can return as soon as it determines the matrix is unsymmetric). * * option 2: All of the above, but also compute the number of matched off- * diagonal entries (of two types). xmatched is the number of * nonzero entries for which A(i,j) = conj(A(j,i)). pmatched is * the number of entries (i,j) for which A(i,j) and A(j,i) are both in * the pattern of A (the value doesn't matter). nzoffdiag is the total * number of off-diagonal entries in the pattern. nzdiag is the number of * diagonal entries in the pattern. * * With option 0 or 1, or if the matrix is rectangular, xmatched, pmatched, * nzoffdiag, and nzdiag are not computed. * * Note that a matched pair, A(i,j) and A(j,i) for i != j, is counted twice * (once per entry). */ int CHOLMOD(symmetry) ( /* ---- input ---- */ cholmod_sparse *A, int option, /* option 0, 1, or 2 (see above) */ /* ---- output --- */ /* outputs ignored if any are NULL */ Int *p_xmatched, /* # of matched numerical entries */ Int *p_pmatched, /* # of matched entries in pattern */ Int *p_nzoffdiag, /* # of off diagonal entries */ Int *p_nzdiag, /* # of diagonal entries */ /* --------------- */ cholmod_common *Common ) { double aij_real = 0, aij_imag = 0, aji_real = 0, aji_imag = 0 ; double *Ax, *Az ; Int *Ap, *Ai, *Anz, *munch ; Int packed, nrow, ncol, xtype, is_symmetric, is_skew, is_hermitian, posdiag, j, p, pend, i, piend, result, xmatched, pmatched, nzdiag, i2, found ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (EMPTY) ; RETURN_IF_NULL (A, EMPTY) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, EMPTY) ; Common->status = CHOLMOD_OK ; ASSERT (CHOLMOD(dump_sparse) (A, "cholmod_symmetry", Common) >= 0) ; if (p_xmatched == NULL || p_pmatched == NULL || p_nzoffdiag == NULL || p_nzdiag == NULL) { /* option 2 is not performed if any output parameter is NULL */ option = MAX (option, 1) ; } /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ Ap = A->p ; Ai = A->i ; Ax = A->x ; Az = A->z ; Anz = A->nz ; packed = A->packed ; ncol = A->ncol ; nrow = A->nrow ; xtype = A->xtype ; /* ---------------------------------------------------------------------- */ /* check if rectangular, unsorted, or stype is not zero */ /* ---------------------------------------------------------------------- */ if (nrow != ncol) { /* matrix is rectangular */ return (CHOLMOD_MM_RECTANGULAR) ; } if (!(A->sorted) || A->stype != 0) { /* this function cannot determine the type or symmetry */ return (EMPTY) ; } /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ /* this function requires uninitialized Int workspace of size ncol */ CHOLMOD(allocate_work) (0, ncol, 0, Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ return (EMPTY) ; } munch = Common->Iwork ; /* the munch array is size ncol */ /* ---------------------------------------------------------------------- */ /* determine symmetry of a square matrix */ /* ---------------------------------------------------------------------- */ /* a complex or zomplex matrix is Hermitian until proven otherwise */ is_hermitian = (xtype >= CHOLMOD_COMPLEX) ; /* any matrix is symmetric until proven otherwise */ is_symmetric = TRUE ; /* a non-pattern matrix is skew-symmetric until proven otherwise */ is_skew = (xtype != CHOLMOD_PATTERN) ; /* a matrix has positive diagonal entries until proven otherwise */ posdiag = TRUE ; /* munch pointers start at the top of each column */ for (j = 0 ; j < ncol ; j++) { munch [j] = Ap [j] ; } xmatched = 0 ; pmatched = 0 ; nzdiag = 0 ; for (j = 0 ; j < ncol ; j++) /* examine each column of A */ { /* ------------------------------------------------------------------ */ /* look at the entire munch column j */ /* ------------------------------------------------------------------ */ /* start at the munch point of column j, and go to end of the column */ p = munch [j] ; pend = (packed) ? (Ap [j+1]) : (Ap [j] + Anz [j]) ; for ( ; p < pend ; p++) { /* get the row index of A(i,j) */ i = Ai [p] ; if (i < j) { /* ---------------------------------------------------------- */ /* A(i,j) in triu(A), but matching A(j,i) not in tril(A) */ /* ---------------------------------------------------------- */ /* entry A(i,j) is unmatched; it appears in the upper triangular * part, but not the lower triangular part. The matrix is * unsymmetric. */ is_hermitian = FALSE ; is_symmetric = FALSE ; is_skew = FALSE ; } else if (i == j) { /* ---------------------------------------------------------- */ /* the diagonal A(j,j) is present; check its value */ /* ---------------------------------------------------------- */ get_value (Ax, Az, p, xtype, &aij_real, &aij_imag) ; if (aij_real != 0. || aij_imag != 0.) { /* diagonal is nonzero; matrix is not skew-symmetric */ nzdiag++ ; is_skew = FALSE ; } if (aij_real <= 0. || aij_imag != 0.) { /* diagonal negative or imaginary; not chol candidate */ posdiag = FALSE ; } if (aij_imag != 0.) { /* imaginary part is present; not Hermitian */ is_hermitian = FALSE ; } } else /* i > j */ { /* ---------------------------------------------------------- */ /* consider column i, up to and including row j */ /* ---------------------------------------------------------- */ /* munch the entry at top of column i up to and incl row j */ piend = (packed) ? (Ap [i+1]) : (Ap [i] + Anz [i]) ; found = FALSE ; for ( ; munch [i] < piend ; munch [i]++) { i2 = Ai [munch [i]] ; if (i2 < j) { /* -------------------------------------------------- */ /* A(i2,i) in triu(A) but A(i,i2) not in tril(A) */ /* -------------------------------------------------- */ /* The matrix is unsymmetric. */ is_hermitian = FALSE ; is_symmetric = FALSE ; is_skew = FALSE ; } else if (i2 == j) { /* -------------------------------------------------- */ /* both A(i,j) and A(j,i) exist in the matrix */ /* -------------------------------------------------- */ /* this is one more matching entry in the pattern */ pmatched += 2 ; found = TRUE ; /* get the value of A(i,j) */ get_value (Ax, Az, p, xtype, &aij_real, &aij_imag) ; /* get the value of A(j,i) */ get_value (Ax, Az, munch [i], xtype, &aji_real, &aji_imag) ; /* compare A(i,j) with A(j,i) */ if (aij_real != aji_real || aij_imag != aji_imag) { /* the matrix cannot be symmetric */ is_symmetric = FALSE ; } if (aij_real != -aji_real || aij_imag != aji_imag) { /* the matrix cannot be skew-symmetric */ is_skew = FALSE ; } if (aij_real != aji_real || aij_imag != -aji_imag) { /* the matrix cannot be Hermitian */ is_hermitian = FALSE ; } else { /* A(i,j) and A(j,i) are numerically matched */ xmatched += 2 ; } } else /* i2 > j */ { /* -------------------------------------------------- */ /* entry A(i2,i) is not munched; consider it later */ /* -------------------------------------------------- */ break ; } } if (!found) { /* A(i,j) in tril(A) but A(j,i) not in triu(A). * The matrix is unsymmetric. */ is_hermitian = FALSE ; is_symmetric = FALSE ; is_skew = FALSE ; } } if (option < 2 && !(is_symmetric || is_skew || is_hermitian)) { /* matrix is unsymmetric; terminate the test */ return (CHOLMOD_MM_UNSYMMETRIC) ; } } /* ------------------------------------------------------------------ */ /* quick return if not Cholesky candidate */ /* ------------------------------------------------------------------ */ if (option < 1 && (!posdiag || nzdiag < ncol)) { /* Diagonal entry not present, or present but negative or with * nonzero imaginary part. Quick return for option 0. */ return (CHOLMOD_MM_UNSYMMETRIC) ; } } /* ---------------------------------------------------------------------- */ /* return the results */ /* ---------------------------------------------------------------------- */ if (nzdiag < ncol) { /* not all diagonal entries are present */ posdiag = FALSE ; } if (option >= 2) { *p_xmatched = xmatched ; *p_pmatched = pmatched ; *p_nzoffdiag = CHOLMOD(nnz) (A, Common) - nzdiag ; *p_nzdiag = nzdiag ; } result = CHOLMOD_MM_UNSYMMETRIC ; if (is_hermitian) { /* complex Hermitian matrix, with either pos. or non-pos. diagonal */ result = posdiag ? CHOLMOD_MM_HERMITIAN_POSDIAG : CHOLMOD_MM_HERMITIAN ; } else if (is_symmetric) { /* real or complex symmetric matrix, with pos. or non-pos. diagonal */ result = posdiag ? CHOLMOD_MM_SYMMETRIC_POSDIAG : CHOLMOD_MM_SYMMETRIC ; } else if (is_skew) { /* real or complex skew-symmetric matrix */ result = CHOLMOD_MM_SKEW_SYMMETRIC ; } return (result) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/MatrixOps/cholmod_drop.c0000644000076500000240000001205513524616144027237 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === MatrixOps/cholmod_drop =============================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/MatrixOps Module. Copyright (C) 2005-2006, Timothy A. Davis * The CHOLMOD/MatrixOps Module is licensed under Version 2.0 of the GNU * General Public License. See gpl.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * http://www.suitesparse.com * -------------------------------------------------------------------------- */ /* Drop small entries from A, and entries in the ignored part of A if A * is symmetric. None of the matrix operations drop small numerical entries * from a matrix, except for this one. NaN's and Inf's are kept. * * workspace: none * * Supports pattern and real matrices, complex and zomplex not supported. */ #ifndef NMATRIXOPS #include "cholmod_internal.h" #include "cholmod_matrixops.h" /* ========================================================================== */ /* === cholmod_drop ========================================================= */ /* ========================================================================== */ int CHOLMOD(drop) ( /* ---- input ---- */ double tol, /* keep entries with absolute value > tol */ /* ---- in/out --- */ cholmod_sparse *A, /* matrix to drop entries from */ /* --------------- */ cholmod_common *Common ) { double aij ; double *Ax ; Int *Ap, *Ai, *Anz ; Int packed, i, j, nrow, ncol, p, pend, nz, values ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (A, FALSE) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_REAL, FALSE) ; Common->status = CHOLMOD_OK ; ASSERT (CHOLMOD(dump_sparse) (A, "A predrop", Common) >= 0) ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ Ap = A->p ; Ai = A->i ; Ax = A->x ; Anz = A->nz ; packed = A->packed ; ncol = A->ncol ; nrow = A->nrow ; values = (A->xtype != CHOLMOD_PATTERN) ; nz = 0 ; if (values) { /* ------------------------------------------------------------------ */ /* drop small numerical entries from A, and entries in ignored part */ /* ------------------------------------------------------------------ */ if (A->stype > 0) { /* -------------------------------------------------------------- */ /* A is symmetric, with just upper triangular part stored */ /* -------------------------------------------------------------- */ for (j = 0 ; j < ncol ; j++) { p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; Ap [j] = nz ; for ( ; p < pend ; p++) { i = Ai [p] ; aij = Ax [p] ; if (i <= j && (fabs (aij) > tol || IS_NAN (aij))) { Ai [nz] = i ; Ax [nz] = aij ; nz++ ; } } } } else if (A->stype < 0) { /* -------------------------------------------------------------- */ /* A is symmetric, with just lower triangular part stored */ /* -------------------------------------------------------------- */ for (j = 0 ; j < ncol ; j++) { p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; Ap [j] = nz ; for ( ; p < pend ; p++) { i = Ai [p] ; aij = Ax [p] ; if (i >= j && (fabs (aij) > tol || IS_NAN (aij))) { Ai [nz] = i ; Ax [nz] = aij ; nz++ ; } } } } else { /* -------------------------------------------------------------- */ /* both parts of A present, just drop small entries */ /* -------------------------------------------------------------- */ for (j = 0 ; j < ncol ; j++) { p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; Ap [j] = nz ; for ( ; p < pend ; p++) { i = Ai [p] ; aij = Ax [p] ; if (fabs (aij) > tol || IS_NAN (aij)) { Ai [nz] = i ; Ax [nz] = aij ; nz++ ; } } } } Ap [ncol] = nz ; /* reduce A->i and A->x in size */ ASSERT (MAX (1,nz) <= A->nzmax) ; CHOLMOD(reallocate_sparse) (nz, A, Common) ; ASSERT (Common->status >= CHOLMOD_OK) ; } else { /* ------------------------------------------------------------------ */ /* consider only the pattern of A */ /* ------------------------------------------------------------------ */ /* Note that cholmod_band_inplace calls cholmod_reallocate_sparse */ if (A->stype > 0) { CHOLMOD(band_inplace) (0, ncol, 0, A, Common) ; } else if (A->stype < 0) { CHOLMOD(band_inplace) (-nrow, 0, 0, A, Common) ; } } ASSERT (CHOLMOD(dump_sparse) (A, "A dropped", Common) >= 0) ; return (TRUE) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/MatrixOps/cholmod_submatrix.c0000644000076500000240000003164413524616144030316 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === MatrixOps/cholmod_submatrix ========================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/MatrixOps Module. Copyright (C) 2005-2006, Timothy A. Davis * The CHOLMOD/MatrixOps Module is licensed under Version 2.0 of the GNU * General Public License. See gpl.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * http://www.suitesparse.com * -------------------------------------------------------------------------- */ /* C = A (rset,cset), where C becomes length(rset)-by-length(cset) in dimension. * rset and cset can have duplicate entries. A and C must be unsymmetric. C * is packed. If the sorted flag is TRUE on input, or rset is sorted and A is * sorted, then C is sorted; otherwise C is unsorted. * * A NULL rset or cset means "[ ]" in MATLAB notation. * If the length of rset or cset is negative, it denotes ":" in MATLAB notation. * * For permuting a matrix, this routine is an alternative to cholmod_ptranspose * (which permutes and transposes a matrix and can work on symmetric matrices). * * The time taken by this routine is O(A->nrow) if the Common workspace needs * to be initialized, plus O(C->nrow + C->ncol + nnz (A (:,cset))). Thus, if C * is small and the workspace is not initialized, the time can be dominated by * the call to cholmod_allocate_work. However, once the workspace is * allocated, subsequent calls take less time. * * workspace: Iwork (max (A->nrow + length (rset), length (cset))). * allocates temporary copy of C if it is to be returned sorted. * * Future work: A common case occurs where A has sorted columns, and rset is in * the form lo:hi in MATLAB notation. This routine could exploit that case * to run even faster when the matrix is sorted, particularly when lo is small. * * Only pattern and real matrices are supported. Complex and zomplex matrices * are supported only when "values" is FALSE. */ #ifndef NMATRIXOPS #include "cholmod_internal.h" #include "cholmod_matrixops.h" /* ========================================================================== */ /* === check_subset ========================================================= */ /* ========================================================================== */ /* Check the rset or cset, and return TRUE if valid, FALSE if invalid */ static int check_subset (Int *set, Int len, Int n) { Int k ; if (set == NULL) { return (TRUE) ; } for (k = 0 ; k < len ; k++) { if (set [k] < 0 || set [k] >= n) { return (FALSE) ; } } return (TRUE) ; } /* ========================================================================== */ /* === cholmod_submatrix ==================================================== */ /* ========================================================================== */ cholmod_sparse *CHOLMOD(submatrix) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to subreference */ Int *rset, /* set of row indices, duplicates OK */ SuiteSparse_long rsize, /* size of rset, or -1 for ":" */ Int *cset, /* set of column indices, duplicates OK */ SuiteSparse_long csize, /* size of cset, or -1 for ":" */ int values, /* if TRUE compute the numerical values of C */ int sorted, /* if TRUE then return C with sorted columns */ /* --------------- */ cholmod_common *Common ) { double aij = 0 ; double *Ax, *Cx ; Int *Ap, *Ai, *Anz, *Ci, *Cp, *Head, *Rlen, *Rnext, *Iwork ; cholmod_sparse *C ; Int packed, ancol, anrow, cnrow, cncol, nnz, i, j, csorted, ilast, p, pend, pdest, ci, cj, head, nr, nc ; size_t s ; int ok = TRUE ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; RETURN_IF_NULL (A, NULL) ; values = (values && (A->xtype != CHOLMOD_PATTERN)) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, values ? CHOLMOD_REAL : CHOLMOD_ZOMPLEX, NULL) ; if (A->stype != 0) { /* A must be unsymmetric */ ERROR (CHOLMOD_INVALID, "symmetric upper or lower case not supported") ; return (NULL) ; } Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ ancol = A->ncol ; anrow = A->nrow ; nr = rsize ; nc = csize ; if (rset == NULL) { /* nr = 0 denotes rset = [ ], nr < 0 denotes rset = 0:anrow-1 */ nr = (nr < 0) ? (-1) : 0 ; } if (cset == NULL) { /* nr = 0 denotes cset = [ ], nr < 0 denotes cset = 0:ancol-1 */ nc = (nc < 0) ? (-1) : 0 ; } cnrow = (nr < 0) ? anrow : nr ; /* negative rset means rset = 0:anrow-1 */ cncol = (nc < 0) ? ancol : nc ; /* negative cset means cset = 0:ancol-1 */ if (nr < 0 && nc < 0) { /* ------------------------------------------------------------------ */ /* C = A (:,:), use cholmod_copy instead */ /* ------------------------------------------------------------------ */ /* workspace: Iwork (max (C->nrow,C->ncol)) */ PRINT1 (("submatrix C = A (:,:)\n")) ; C = CHOLMOD(copy) (A, 0, values, Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ return (NULL) ; } return (C) ; } PRINT1 (("submatrix nr "ID" nc "ID" Cnrow "ID" Cncol "ID"" " Anrow "ID" Ancol "ID"\n", nr, nc, cnrow, cncol, anrow, ancol)) ; /* s = MAX3 (anrow+MAX(0,nr), cncol, cnrow) ; */ s = CHOLMOD(add_size_t) (anrow, MAX (0,nr), &ok) ; if (!ok) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return (NULL) ; } s = MAX3 (s, ((size_t) cncol), ((size_t) cnrow)) ; CHOLMOD(allocate_work) (anrow, s, 0, Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ return (NULL) ; } ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ Ap = A->p ; Anz = A->nz ; Ai = A->i ; Ax = A->x ; packed = A->packed ; /* ---------------------------------------------------------------------- */ /* get workspace */ /* ---------------------------------------------------------------------- */ Head = Common->Head ; /* size anrow */ Iwork = Common->Iwork ; Rlen = Iwork ; /* size anrow (i/i/l) */ Rnext = Iwork + anrow ; /* size nr (i/i/l), not used if nr < 0 */ /* ---------------------------------------------------------------------- */ /* construct inverse of rset and compute nnz (C) */ /* ---------------------------------------------------------------------- */ PRINT1 (("nr "ID" nc "ID"\n", nr, nc)) ; PRINT1 (("anrow "ID" ancol "ID"\n", anrow, ancol)) ; PRINT1 (("cnrow "ID" cncol "ID"\n", cnrow, cncol)) ; DEBUG (for (i = 0 ; i < nr ; i++) PRINT2 (("rset ["ID"] = "ID"\n", i, rset [i]))); DEBUG (for (i = 0 ; i < nc ; i++) PRINT2 (("cset ["ID"] = "ID"\n", i, cset [i]))); /* C is sorted if A and rset are sorted, or if C has one row or less */ csorted = A->sorted || (cnrow <= 1) ; if (!check_subset (rset, nr, anrow)) { ERROR (CHOLMOD_INVALID, "invalid rset") ; return (NULL) ; } if (!check_subset (cset, nc, ancol)) { ERROR (CHOLMOD_INVALID, "invalid cset") ; return (NULL) ; } nnz = 0 ; if (nr < 0) { /* C = A (:,cset) where cset = [ ] or cset is not empty */ ASSERT (IMPLIES (cncol > 0, cset != NULL)) ; for (cj = 0 ; cj < cncol ; cj++) { /* construct column cj of C, which is column j of A */ j = cset [cj] ; nnz += (packed) ? (Ap [j+1] - Ap [j]) : MAX (0, Anz [j]) ; } } else { /* C = A (rset,cset), where rset is not empty but cset might be empty */ /* create link lists in reverse order to preserve natural order */ ilast = anrow ; for (ci = nr-1 ; ci >= 0 ; ci--) { /* row i of A becomes row ci of C; add ci to ith link list */ i = rset [ci] ; head = Head [i] ; Rlen [i] = (head == EMPTY) ? 1 : (Rlen [i] + 1) ; Rnext [ci] = head ; Head [i] = ci ; if (i > ilast) { /* row indices in columns of C will not be sorted */ csorted = FALSE ; } ilast = i ; } #ifndef NDEBUG for (i = 0 ; i < anrow ; i++) { Int k = 0 ; Int rlen = (Head [i] != EMPTY) ? Rlen [i] : -1 ; PRINT1 (("Row "ID" Rlen "ID": ", i, rlen)) ; for (ci = Head [i] ; ci != EMPTY ; ci = Rnext [ci]) { k++ ; PRINT2 ((""ID" ", ci)) ; } PRINT1 (("\n")) ; ASSERT (IMPLIES (Head [i] != EMPTY, k == Rlen [i])) ; } #endif /* count nonzeros in C */ for (cj = 0 ; cj < cncol ; cj++) { /* count rows in column cj of C, which is column j of A */ j = (nc < 0) ? cj : (cset [cj]) ; p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { /* row i of A becomes multiple rows (ci) of C */ i = Ai [p] ; ASSERT (i >= 0 && i < anrow) ; if (Head [i] != EMPTY) { nnz += Rlen [i] ; } } } } PRINT1 (("nnz (C) "ID"\n", nnz)) ; /* rset and cset are now valid */ DEBUG (CHOLMOD(dump_subset) (rset, rsize, anrow, "rset", Common)) ; DEBUG (CHOLMOD(dump_subset) (cset, csize, ancol, "cset", Common)) ; /* ---------------------------------------------------------------------- */ /* allocate C */ /* ---------------------------------------------------------------------- */ C = CHOLMOD(allocate_sparse) (cnrow, cncol, nnz, csorted, TRUE, 0, values ? A->xtype : CHOLMOD_PATTERN, Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ for (i = 0 ; i < anrow ; i++) { Head [i] = EMPTY ; } ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; return (NULL) ; } Cp = C->p ; Ci = C->i ; Cx = C->x ; /* ---------------------------------------------------------------------- */ /* C = A (rset,cset) */ /* ---------------------------------------------------------------------- */ pdest = 0 ; if (nnz == 0) { /* C has no nonzeros */ for (cj = 0 ; cj <= cncol ; cj++) { Cp [cj] = 0 ; } } else if (nr < 0) { /* C = A (:,cset), where cset is not empty */ for (cj = 0 ; cj < cncol ; cj++) { /* construct column cj of C, which is column j of A */ PRINT1 (("construct cj = j = "ID"\n", cj)) ; j = cset [cj] ; Cp [cj] = pdest ; p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { Ci [pdest] = Ai [p] ; if (values) { Cx [pdest] = Ax [p] ; } pdest++ ; ASSERT (pdest <= nnz) ; } } } else { /* C = A (rset,cset), where rset is not empty but cset might be empty */ for (cj = 0 ; cj < cncol ; cj++) { /* construct column cj of C, which is column j of A */ PRINT1 (("construct cj = "ID"\n", cj)) ; j = (nc < 0) ? cj : (cset [cj]) ; PRINT1 (("cj = "ID"\n", j)) ; Cp [cj] = pdest ; p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { /* row (Ai [p]) of A becomes multiple rows (ci) of C */ PRINT2 (("i: "ID" becomes: ", Ai [p])) ; if (values) { aij = Ax [p] ; } for (ci = Head [Ai [p]] ; ci != EMPTY ; ci = Rnext [ci]) { PRINT3 ((""ID" ", ci)) ; Ci [pdest] = ci ; if (values) { Cx [pdest] = aij ; } pdest++ ; ASSERT (pdest <= nnz) ; } PRINT2 (("\n")) ; } } } Cp [cncol] = pdest ; ASSERT (nnz == pdest) ; /* ---------------------------------------------------------------------- */ /* clear workspace */ /* ---------------------------------------------------------------------- */ for (ci = 0 ; ci < nr ; ci++) { Head [rset [ci]] = EMPTY ; } ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; /* ---------------------------------------------------------------------- */ /* sort C, if requested */ /* ---------------------------------------------------------------------- */ ASSERT (CHOLMOD(dump_sparse) (C , "C before sort", Common) >= 0) ; if (sorted && !csorted) { /* workspace: Iwork (max (C->nrow,C->ncol)) */ if (!CHOLMOD(sort) (C, Common)) { /* out of memory */ CHOLMOD(free_sparse) (&C, Common) ; ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; return (NULL) ; } } /* ---------------------------------------------------------------------- */ /* return result */ /* ---------------------------------------------------------------------- */ ASSERT (CHOLMOD(dump_sparse) (C , "Final C", Common) >= 0) ; ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, 0, Common)) ; return (C) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/MatrixOps/cholmod_norm.c0000644000076500000240000002637513524616144027260 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === MatrixOps/cholmod_norm =============================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/MatrixOps Module. Copyright (C) 2005-2006, Timothy A. Davis * The CHOLMOD/MatrixOps Module is licensed under Version 2.0 of the GNU * General Public License. See gpl.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * http://www.suitesparse.com * -------------------------------------------------------------------------- */ /* r = norm (A), compute the infinity-norm, 1-norm, or 2-norm of a sparse or * dense matrix. Can compute the 2-norm only for a dense column vector. * Returns -1 if an error occurs. * * Pattern, real, complex, and zomplex sparse matrices are supported. */ #ifndef NMATRIXOPS #include "cholmod_internal.h" #include "cholmod_matrixops.h" /* ========================================================================== */ /* === abs_value ============================================================ */ /* ========================================================================== */ /* Compute the absolute value of a real, complex, or zomplex value */ static double abs_value ( int xtype, double *Ax, double *Az, Int p, cholmod_common *Common ) { double s = 0 ; switch (xtype) { case CHOLMOD_PATTERN: s = 1 ; break ; case CHOLMOD_REAL: s = fabs (Ax [p]) ; break ; case CHOLMOD_COMPLEX: s = Common->hypotenuse (Ax [2*p], Ax [2*p+1]) ; break ; case CHOLMOD_ZOMPLEX: s = Common->hypotenuse (Ax [p], Az [p]) ; break ; } return (s) ; } /* ========================================================================== */ /* === cholmod_norm_dense =================================================== */ /* ========================================================================== */ double CHOLMOD(norm_dense) ( /* ---- input ---- */ cholmod_dense *X, /* matrix to compute the norm of */ int norm, /* type of norm: 0: inf. norm, 1: 1-norm, 2: 2-norm */ /* --------------- */ cholmod_common *Common ) { double xnorm, s, x, z ; double *Xx, *Xz, *W ; Int nrow, ncol, d, i, j, use_workspace, xtype ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (EMPTY) ; RETURN_IF_NULL (X, EMPTY) ; RETURN_IF_XTYPE_INVALID (X, CHOLMOD_REAL, CHOLMOD_ZOMPLEX, EMPTY) ; Common->status = CHOLMOD_OK ; ncol = X->ncol ; if (norm < 0 || norm > 2 || (norm == 2 && ncol > 1)) { ERROR (CHOLMOD_INVALID, "invalid norm") ; return (EMPTY) ; } /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ nrow = X->nrow ; d = X->d ; Xx = X->x ; Xz = X->z ; xtype = X->xtype ; /* ---------------------------------------------------------------------- */ /* allocate workspace, if needed */ /* ---------------------------------------------------------------------- */ W = NULL ; use_workspace = (norm == 0 && ncol > 4) ; if (use_workspace) { CHOLMOD(allocate_work) (0, 0, nrow, Common) ; W = Common->Xwork ; if (Common->status < CHOLMOD_OK) { /* oops, no workspace */ use_workspace = FALSE ; } } /* ---------------------------------------------------------------------- */ /* compute the norm */ /* ---------------------------------------------------------------------- */ xnorm = 0 ; if (use_workspace) { /* ------------------------------------------------------------------ */ /* infinity-norm = max row sum, using stride-1 access of X */ /* ------------------------------------------------------------------ */ DEBUG (for (i = 0 ; i < nrow ; i++) ASSERT (W [i] == 0)) ; /* this is faster than stride-d, but requires O(nrow) workspace */ for (j = 0 ; j < ncol ; j++) { for (i = 0 ; i < nrow ; i++) { W [i] += abs_value (xtype, Xx, Xz, i+j*d, Common) ; } } for (i = 0 ; i < nrow ; i++) { s = W [i] ; if ((IS_NAN (s) || s > xnorm) && !IS_NAN (xnorm)) { xnorm = s ; } W [i] = 0 ; } } else if (norm == 0) { /* ------------------------------------------------------------------ */ /* infinity-norm = max row sum, using stride-d access of X */ /* ------------------------------------------------------------------ */ for (i = 0 ; i < nrow ; i++) { s = 0 ; for (j = 0 ; j < ncol ; j++) { s += abs_value (xtype, Xx, Xz, i+j*d, Common) ; } if ((IS_NAN (s) || s > xnorm) && !IS_NAN (xnorm)) { xnorm = s ; } } } else if (norm == 1) { /* ------------------------------------------------------------------ */ /* 1-norm = max column sum */ /* ------------------------------------------------------------------ */ for (j = 0 ; j < ncol ; j++) { s = 0 ; for (i = 0 ; i < nrow ; i++) { s += abs_value (xtype, Xx, Xz, i+j*d, Common) ; } if ((IS_NAN (s) || s > xnorm) && !IS_NAN (xnorm)) { xnorm = s ; } } } else { /* ------------------------------------------------------------------ */ /* 2-norm = sqrt (sum (X.^2)) */ /* ------------------------------------------------------------------ */ switch (xtype) { case CHOLMOD_REAL: for (i = 0 ; i < nrow ; i++) { x = Xx [i] ; xnorm += x*x ; } break ; case CHOLMOD_COMPLEX: for (i = 0 ; i < nrow ; i++) { x = Xx [2*i ] ; z = Xx [2*i+1] ; xnorm += x*x + z*z ; } break ; case CHOLMOD_ZOMPLEX: for (i = 0 ; i < nrow ; i++) { x = Xx [i] ; z = Xz [i] ; xnorm += x*x + z*z ; } break ; } xnorm = sqrt (xnorm) ; } /* ---------------------------------------------------------------------- */ /* return result */ /* ---------------------------------------------------------------------- */ return (xnorm) ; } /* ========================================================================== */ /* === cholmod_norm_sparse ================================================== */ /* ========================================================================== */ double CHOLMOD(norm_sparse) ( /* ---- input ---- */ cholmod_sparse *A, /* matrix to compute the norm of */ int norm, /* type of norm: 0: inf. norm, 1: 1-norm */ /* --------------- */ cholmod_common *Common ) { double anorm, s ; double *Ax, *Az, *W ; Int *Ap, *Ai, *Anz ; Int i, j, p, pend, nrow, ncol, packed, xtype ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (EMPTY) ; RETURN_IF_NULL (A, EMPTY) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, EMPTY) ; Common->status = CHOLMOD_OK ; ncol = A->ncol ; nrow = A->nrow ; if (norm < 0 || norm > 1) { ERROR (CHOLMOD_INVALID, "invalid norm") ; return (EMPTY) ; } if (A->stype && nrow != ncol) { ERROR (CHOLMOD_INVALID, "matrix invalid") ; return (EMPTY) ; } /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ Ap = A->p ; Ai = A->i ; Ax = A->x ; Az = A->z ; Anz = A->nz ; packed = A->packed ; xtype = A->xtype ; /* ---------------------------------------------------------------------- */ /* allocate workspace, if needed */ /* ---------------------------------------------------------------------- */ W = NULL ; if (A->stype || norm == 0) { CHOLMOD(allocate_work) (0, 0, nrow, Common) ; W = Common->Xwork ; if (Common->status < CHOLMOD_OK) { /* out of memory */ return (EMPTY) ; } DEBUG (for (i = 0 ; i < nrow ; i++) ASSERT (W [i] == 0)) ; } /* ---------------------------------------------------------------------- */ /* compute the norm */ /* ---------------------------------------------------------------------- */ anorm = 0 ; if (A->stype > 0) { /* ------------------------------------------------------------------ */ /* A is symmetric with upper triangular part stored */ /* ------------------------------------------------------------------ */ /* infinity-norm = 1-norm = max row/col sum */ for (j = 0 ; j < ncol ; j++) { p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { i = Ai [p] ; s = abs_value (xtype, Ax, Az, p, Common) ; if (i == j) { W [i] += s ; } else if (i < j) { W [i] += s ; W [j] += s ; } } } } else if (A->stype < 0) { /* ------------------------------------------------------------------ */ /* A is symmetric with lower triangular part stored */ /* ------------------------------------------------------------------ */ /* infinity-norm = 1-norm = max row/col sum */ for (j = 0 ; j < ncol ; j++) { p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { i = Ai [p] ; s = abs_value (xtype, Ax, Az, p, Common) ; if (i == j) { W [i] += s ; } else if (i > j) { W [i] += s ; W [j] += s ; } } } } else if (norm == 0) { /* ------------------------------------------------------------------ */ /* A is unsymmetric, compute the infinity-norm */ /* ------------------------------------------------------------------ */ /* infinity-norm = max row sum */ for (j = 0 ; j < ncol ; j++) { p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { W [Ai [p]] += abs_value (xtype, Ax, Az, p, Common) ; } } } else { /* ------------------------------------------------------------------ */ /* A is unsymmetric, compute the 1-norm */ /* ------------------------------------------------------------------ */ /* 1-norm = max column sum */ for (j = 0 ; j < ncol ; j++) { p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; if (xtype == CHOLMOD_PATTERN) { s = pend - p ; } else { s = 0 ; for ( ; p < pend ; p++) { s += abs_value (xtype, Ax, Az, p, Common) ; } } if ((IS_NAN (s) || s > anorm) && !IS_NAN (anorm)) { anorm = s ; } } } /* ---------------------------------------------------------------------- */ /* compute the max row sum */ /* ---------------------------------------------------------------------- */ if (A->stype || norm == 0) { for (i = 0 ; i < nrow ; i++) { s = W [i] ; if ((IS_NAN (s) || s > anorm) && !IS_NAN (anorm)) { anorm = s ; } W [i] = 0 ; } } /* ---------------------------------------------------------------------- */ /* return result */ /* ---------------------------------------------------------------------- */ return (anorm) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/MatrixOps/gpl.txt0000644000076500000240000004313313524616144025746 0ustar tamasstaff00000000000000 GNU GENERAL PUBLIC LICENSE Version 2, June 1991 Copyright (C) 1989, 1991 Free Software Foundation, Inc. 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed. Preamble The licenses for most software are designed to take away your freedom to share and change it. By contrast, the GNU General Public License is intended to guarantee your freedom to share and change free software--to make sure the software is free for all its users. This General Public License applies to most of the Free Software Foundation's software and to any other program whose authors commit to using it. (Some other Free Software Foundation software is covered by the GNU Library General Public License instead.) You can apply it to your programs, too. When we speak of free software, we are referring to freedom, not price. Our General Public Licenses are designed to make sure that you have the freedom to distribute copies of free software (and charge for this service if you wish), that you receive source code or can get it if you want it, that you can change the software or use pieces of it in new free programs; and that you know you can do these things. To protect your rights, we need to make restrictions that forbid anyone to deny you these rights or to ask you to surrender the rights. These restrictions translate to certain responsibilities for you if you distribute copies of the software, or if you modify it. For example, if you distribute copies of such a program, whether gratis or for a fee, you must give the recipients all the rights that you have. You must make sure that they, too, receive or can get the source code. And you must show them these terms so they know their rights. We protect your rights with two steps: (1) copyright the software, and (2) offer you this license which gives you legal permission to copy, distribute and/or modify the software. Also, for each author's protection and ours, we want to make certain that everyone understands that there is no warranty for this free software. If the software is modified by someone else and passed on, we want its recipients to know that what they have is not the original, so that any problems introduced by others will not reflect on the original authors' reputations. Finally, any free program is threatened constantly by software patents. We wish to avoid the danger that redistributors of a free program will individually obtain patent licenses, in effect making the program proprietary. To prevent this, we have made it clear that any patent must be licensed for everyone's free use or not licensed at all. The precise terms and conditions for copying, distribution and modification follow. GNU GENERAL PUBLIC LICENSE TERMS AND CONDITIONS FOR COPYING, DISTRIBUTION AND MODIFICATION 0. This License applies to any program or other work which contains a notice placed by the copyright holder saying it may be distributed under the terms of this General Public License. The "Program", below, refers to any such program or work, and a "work based on the Program" means either the Program or any derivative work under copyright law: that is to say, a work containing the Program or a portion of it, either verbatim or with modifications and/or translated into another language. (Hereinafter, translation is included without limitation in the term "modification".) Each licensee is addressed as "you". Activities other than copying, distribution and modification are not covered by this License; they are outside its scope. The act of running the Program is not restricted, and the output from the Program is covered only if its contents constitute a work based on the Program (independent of having been made by running the Program). Whether that is true depends on what the Program does. 1. You may copy and distribute verbatim copies of the Program's source code as you receive it, in any medium, provided that you conspicuously and appropriately publish on each copy an appropriate copyright notice and disclaimer of warranty; keep intact all the notices that refer to this License and to the absence of any warranty; and give any other recipients of the Program a copy of this License along with the Program. You may charge a fee for the physical act of transferring a copy, and you may at your option offer warranty protection in exchange for a fee. 2. You may modify your copy or copies of the Program or any portion of it, thus forming a work based on the Program, and copy and distribute such modifications or work under the terms of Section 1 above, provided that you also meet all of these conditions: a) You must cause the modified files to carry prominent notices stating that you changed the files and the date of any change. b) You must cause any work that you distribute or publish, that in whole or in part contains or is derived from the Program or any part thereof, to be licensed as a whole at no charge to all third parties under the terms of this License. c) If the modified program normally reads commands interactively when run, you must cause it, when started running for such interactive use in the most ordinary way, to print or display an announcement including an appropriate copyright notice and a notice that there is no warranty (or else, saying that you provide a warranty) and that users may redistribute the program under these conditions, and telling the user how to view a copy of this License. (Exception: if the Program itself is interactive but does not normally print such an announcement, your work based on the Program is not required to print an announcement.) These requirements apply to the modified work as a whole. If identifiable sections of that work are not derived from the Program, and can be reasonably considered independent and separate works in themselves, then this License, and its terms, do not apply to those sections when you distribute them as separate works. But when you distribute the same sections as part of a whole which is a work based on the Program, the distribution of the whole must be on the terms of this License, whose permissions for other licensees extend to the entire whole, and thus to each and every part regardless of who wrote it. Thus, it is not the intent of this section to claim rights or contest your rights to work written entirely by you; rather, the intent is to exercise the right to control the distribution of derivative or collective works based on the Program. In addition, mere aggregation of another work not based on the Program with the Program (or with a work based on the Program) on a volume of a storage or distribution medium does not bring the other work under the scope of this License. 3. You may copy and distribute the Program (or a work based on it, under Section 2) in object code or executable form under the terms of Sections 1 and 2 above provided that you also do one of the following: a) Accompany it with the complete corresponding machine-readable source code, which must be distributed under the terms of Sections 1 and 2 above on a medium customarily used for software interchange; or, b) Accompany it with a written offer, valid for at least three years, to give any third party, for a charge no more than your cost of physically performing source distribution, a complete machine-readable copy of the corresponding source code, to be distributed under the terms of Sections 1 and 2 above on a medium customarily used for software interchange; or, c) Accompany it with the information you received as to the offer to distribute corresponding source code. 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If distribution of executable or object code is made by offering access to copy from a designated place, then offering equivalent access to copy the source code from the same place counts as distribution of the source code, even though third parties are not compelled to copy the source along with the object code. 4. You may not copy, modify, sublicense, or distribute the Program except as expressly provided under this License. Any attempt otherwise to copy, modify, sublicense or distribute the Program is void, and will automatically terminate your rights under this License. However, parties who have received copies, or rights, from you under this License will not have their licenses terminated so long as such parties remain in full compliance. 5. You are not required to accept this License, since you have not signed it. However, nothing else grants you permission to modify or distribute the Program or its derivative works. These actions are prohibited by law if you do not accept this License. Therefore, by modifying or distributing the Program (or any work based on the Program), you indicate your acceptance of this License to do so, and all its terms and conditions for copying, distributing or modifying the Program or works based on it. 6. Each time you redistribute the Program (or any work based on the Program), the recipient automatically receives a license from the original licensor to copy, distribute or modify the Program subject to these terms and conditions. You may not impose any further restrictions on the recipients' exercise of the rights granted herein. You are not responsible for enforcing compliance by third parties to this License. 7. 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If the distribution and/or use of the Program is restricted in certain countries either by patents or by copyrighted interfaces, the original copyright holder who places the Program under this License may add an explicit geographical distribution limitation excluding those countries, so that distribution is permitted only in or among countries not thus excluded. In such case, this License incorporates the limitation as if written in the body of this License. 9. The Free Software Foundation may publish revised and/or new versions of the General Public License from time to time. Such new versions will be similar in spirit to the present version, but may differ in detail to address new problems or concerns. Each version is given a distinguishing version number. If the Program specifies a version number of this License which applies to it and "any later version", you have the option of following the terms and conditions either of that version or of any later version published by the Free Software Foundation. If the Program does not specify a version number of this License, you may choose any version ever published by the Free Software Foundation. 10. If you wish to incorporate parts of the Program into other free programs whose distribution conditions are different, write to the author to ask for permission. For software which is copyrighted by the Free Software Foundation, write to the Free Software Foundation; we sometimes make exceptions for this. Our decision will be guided by the two goals of preserving the free status of all derivatives of our free software and of promoting the sharing and reuse of software generally. NO WARRANTY 11. BECAUSE THE PROGRAM IS LICENSED FREE OF CHARGE, THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING, REPAIR OR CORRECTION. 12. IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MAY MODIFY AND/OR REDISTRIBUTE THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS), EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES. END OF TERMS AND CONDITIONS How to Apply These Terms to Your New Programs If you develop a new program, and you want it to be of the greatest possible use to the public, the best way to achieve this is to make it free software which everyone can redistribute and change under these terms. To do so, attach the following notices to the program. It is safest to attach them to the start of each source file to most effectively convey the exclusion of warranty; and each file should have at least the "copyright" line and a pointer to where the full notice is found. Copyright (C) This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA Also add information on how to contact you by electronic and paper mail. If the program is interactive, make it output a short notice like this when it starts in an interactive mode: Gnomovision version 69, Copyright (C) year name of author Gnomovision comes with ABSOLUTELY NO WARRANTY; for details type `show w'. This is free software, and you are welcome to redistribute it under certain conditions; type `show c' for details. The hypothetical commands `show w' and `show c' should show the appropriate parts of the General Public License. Of course, the commands you use may be called something other than `show w' and `show c'; they could even be mouse-clicks or menu items--whatever suits your program. You should also get your employer (if you work as a programmer) or your school, if any, to sign a "copyright disclaimer" for the program, if necessary. Here is a sample; alter the names: Yoyodyne, Inc., hereby disclaims all copyright interest in the program `Gnomovision' (which makes passes at compilers) written by James Hacker. , 1 April 1989 Ty Coon, President of Vice This General Public License does not permit incorporating your program into proprietary programs. If your program is a subroutine library, you may consider it more useful to permit linking proprietary applications with the library. If this is what you want to do, use the GNU Library General Public License instead of this License. python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/MatrixOps/cholmod_scale.c0000644000076500000240000001437513524616144027371 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === MatrixOps/cholmod_scale ============================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/MatrixOps Module. Copyright (C) 2005-2006, Timothy A. Davis * The CHOLMOD/MatrixOps Module is licensed under Version 2.0 of the GNU * General Public License. See gpl.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * http://www.suitesparse.com * -------------------------------------------------------------------------- */ /* scale a matrix: A = diag(s)*A, A*diag(s), s*A, or diag(s)*A*diag(s) * * A can be of any type (packed/unpacked, upper/lower/unsymmetric). * The symmetry of A is ignored; all entries in the matrix are modified. * * If A is m-by-n unsymmetric but scaled symmtrically, the result is * A = diag (s (1:m)) * A * diag (s (1:n)). * * Note: diag(s) should be interpretted as spdiags(s,0,n,n) where n=length(s). * * Row or column scaling of a symmetric matrix still results in a symmetric * matrix, since entries are still ignored by other routines. * For example, when row-scaling a symmetric matrix where just the upper * triangular part is stored (and lower triangular entries ignored) * A = diag(s)*triu(A) is performed, where the result A is also * symmetric-upper. This has the effect of modifying the implicit lower * triangular part. In MATLAB notation: * * U = diag(s)*triu(A) ; * L = tril (U',-1) * A = L + U ; * * The scale parameter determines the kind of scaling to perform: * * CHOLMOD_SCALAR: s[0]*A * CHOLMOD_ROW: diag(s)*A * CHOLMOD_COL: A*diag(s) * CHOLMOD_SYM: diag(s)*A*diag(s) * * The size of S depends on the scale parameter: * * CHOLMOD_SCALAR: size 1 * CHOLMOD_ROW: size nrow-by-1 or 1-by-nrow * CHOLMOD_COL: size ncol-by-1 or 1-by-ncol * CHOLMOD_SYM: size max(nrow,ncol)-by-1, or 1-by-max(nrow,ncol) * * workspace: none * * Only real matrices are supported. */ #ifndef NMATRIXOPS #include "cholmod_internal.h" #include "cholmod_matrixops.h" /* ========================================================================== */ /* === cholmod_scale ======================================================== */ /* ========================================================================== */ int CHOLMOD(scale) ( /* ---- input ---- */ cholmod_dense *S, /* scale factors (scalar or vector) */ int scale, /* type of scaling to compute */ /* ---- in/out --- */ cholmod_sparse *A, /* matrix to scale */ /* --------------- */ cholmod_common *Common ) { double t ; double *Ax, *s ; Int *Ap, *Anz, *Ai ; Int packed, j, ncol, nrow, p, pend, sncol, snrow, nn, ok ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (A, FALSE) ; RETURN_IF_NULL (S, FALSE) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_REAL, CHOLMOD_REAL, FALSE) ; RETURN_IF_XTYPE_INVALID (S, CHOLMOD_REAL, CHOLMOD_REAL, FALSE) ; ncol = A->ncol ; nrow = A->nrow ; sncol = S->ncol ; snrow = S->nrow ; if (scale == CHOLMOD_SCALAR) { ok = (snrow == 1 && sncol == 1) ; } else if (scale == CHOLMOD_ROW) { ok = (snrow == nrow && sncol == 1) || (snrow == 1 && sncol == nrow) ; } else if (scale == CHOLMOD_COL) { ok = (snrow == ncol && sncol == 1) || (snrow == 1 && sncol == ncol) ; } else if (scale == CHOLMOD_SYM) { nn = MAX (nrow, ncol) ; ok = (snrow == nn && sncol == 1) || (snrow == 1 && sncol == nn) ; } else { /* scale invalid */ ERROR (CHOLMOD_INVALID, "invalid scaling option") ; return (FALSE) ; } if (!ok) { /* S is wrong size */ ERROR (CHOLMOD_INVALID, "invalid scale factors") ; return (FALSE) ; } Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ Ap = A->p ; Anz = A->nz ; Ai = A->i ; Ax = A->x ; packed = A->packed ; s = S->x ; /* ---------------------------------------------------------------------- */ /* scale the matrix */ /* ---------------------------------------------------------------------- */ if (scale == CHOLMOD_ROW) { /* ------------------------------------------------------------------ */ /* A = diag(s)*A, row scaling */ /* ------------------------------------------------------------------ */ for (j = 0 ; j < ncol ; j++) { p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { Ax [p] *= s [Ai [p]] ; } } } else if (scale == CHOLMOD_COL) { /* ------------------------------------------------------------------ */ /* A = A*diag(s), column scaling */ /* ------------------------------------------------------------------ */ for (j = 0 ; j < ncol ; j++) { t = s [j] ; p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { Ax [p] *= t ; } } } else if (scale == CHOLMOD_SYM) { /* ------------------------------------------------------------------ */ /* A = diag(s)*A*diag(s), symmetric scaling */ /* ------------------------------------------------------------------ */ for (j = 0 ; j < ncol ; j++) { t = s [j] ; p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { Ax [p] *= t * s [Ai [p]] ; } } } else if (scale == CHOLMOD_SCALAR) { /* ------------------------------------------------------------------ */ /* A = s[0] * A, scalar scaling */ /* ------------------------------------------------------------------ */ t = s [0] ; for (j = 0 ; j < ncol ; j++) { p = Ap [j] ; pend = (packed) ? (Ap [j+1]) : (p + Anz [j]) ; for ( ; p < pend ; p++) { Ax [p] *= t ; } } } ASSERT (CHOLMOD(dump_sparse) (A, "A scaled", Common) >= 0) ; return (TRUE) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/MatrixOps/License.txt0000644000076500000240000000203013524616144026535 0ustar tamasstaff00000000000000CHOLMOD/MatrixOps Module. Copyright (C) 2005-2006, Timothy A. Davis CHOLMOD is also available under other licenses; contact authors for details. http://www.suitesparse.com Note that this license is for the CHOLMOD/MatrixOps module only. All CHOLMOD modules are licensed separately. -------------------------------------------------------------------------------- This Module is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This Module is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this Module; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/MatrixOps/cholmod_ssmult.c0000644000076500000240000003400013524616144027614 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === MatrixOps/cholmod_ssmult ============================================= */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/MatrixOps Module. Copyright (C) 2005-2006, Timothy A. Davis * The CHOLMOD/MatrixOps Module is licensed under Version 2.0 of the GNU * General Public License. See gpl.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * http://www.suitesparse.com * -------------------------------------------------------------------------- */ /* C = A*B. Multiply two sparse matrices. * * A and B can be packed or unpacked, sorted or unsorted, and of any stype. * If A or B are symmetric, an internal unsymmetric copy is made first, however. * C is computed as if A and B are unsymmetric, and then if the stype input * parameter requests a symmetric form (upper or lower) the matrix is converted * into that form. * * C is returned as packed, and either unsorted or sorted, depending on the * "sorted" input parameter. If C is returned sorted, then either C = (B'*A')' * or C = (A*B)'' is computed, depending on the number of nonzeros in A, B, and * C. * * workspace: * if C unsorted: Flag (A->nrow), W (A->nrow) if values * if C sorted: Flag (B->ncol), W (B->ncol) if values * Iwork (max (A->ncol, A->nrow, B->nrow, B->ncol)) * allocates temporary copies for A, B, and C, if required. * * Only pattern and real matrices are supported. Complex and zomplex matrices * are supported only when the numerical values are not computed ("values" * is FALSE). */ #ifndef NMATRIXOPS #include "cholmod_internal.h" #include "cholmod_matrixops.h" /* ========================================================================== */ /* === cholmod_ssmult ======================================================= */ /* ========================================================================== */ cholmod_sparse *CHOLMOD(ssmult) ( /* ---- input ---- */ cholmod_sparse *A, /* left matrix to multiply */ cholmod_sparse *B, /* right matrix to multiply */ int stype, /* requested stype of C */ int values, /* TRUE: do numerical values, FALSE: pattern only */ int sorted, /* if TRUE then return C with sorted columns */ /* --------------- */ cholmod_common *Common ) { double bjt ; double *Ax, *Bx, *Cx, *W ; Int *Ap, *Anz, *Ai, *Bp, *Bnz, *Bi, *Cp, *Ci, *Flag ; cholmod_sparse *C, *A2, *B2, *A3, *B3, *C2 ; Int apacked, bpacked, j, i, pa, paend, pb, pbend, ncol, mark, cnz, t, p, nrow, anz, bnz, do_swap_and_transpose, n1, n2 ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; RETURN_IF_NULL (A, NULL) ; RETURN_IF_NULL (B, NULL) ; values = values && (A->xtype != CHOLMOD_PATTERN) && (B->xtype != CHOLMOD_PATTERN) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, values ? CHOLMOD_REAL : CHOLMOD_ZOMPLEX, NULL) ; RETURN_IF_XTYPE_INVALID (B, CHOLMOD_PATTERN, values ? CHOLMOD_REAL : CHOLMOD_ZOMPLEX, NULL) ; if (A->ncol != B->nrow) { /* inner dimensions must agree */ ERROR (CHOLMOD_INVALID, "A and B inner dimensions must match") ; return (NULL) ; } /* A and B must have the same numerical type if values is TRUE (both must * be CHOLMOD_REAL, this is implicitly checked above) */ Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ if (A->nrow <= 1) { /* C will be implicitly sorted, so no need to sort it here */ sorted = FALSE ; } if (sorted) { n1 = MAX (A->nrow, B->ncol) ; } else { n1 = A->nrow ; } n2 = MAX4 (A->ncol, A->nrow, B->nrow, B->ncol) ; CHOLMOD(allocate_work) (n1, n2, values ? n1 : 0, Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ return (NULL) ; } ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, values ? n1 : 0, Common)) ; /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ /* convert A to unsymmetric, if necessary */ A2 = NULL ; B2 = NULL ; if (A->stype) { /* workspace: Iwork (max (A->nrow,A->ncol)) */ A2 = CHOLMOD(copy) (A, 0, values, Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, values ? n1:0, Common)) ; return (NULL) ; } A = A2 ; } /* convert B to unsymmetric, if necessary */ if (B->stype) { /* workspace: Iwork (max (B->nrow,B->ncol)) */ B2 = CHOLMOD(copy) (B, 0, values, Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ CHOLMOD(free_sparse) (&A2, Common) ; ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, values ? n1:0, Common)) ; return (NULL) ; } B = B2 ; } ASSERT (CHOLMOD(dump_sparse) (A, "A", Common) >= 0) ; ASSERT (CHOLMOD(dump_sparse) (B, "B", Common) >= 0) ; /* get the A matrix */ Ap = A->p ; Anz = A->nz ; Ai = A->i ; Ax = A->x ; apacked = A->packed ; /* get the B matrix */ Bp = B->p ; Bnz = B->nz ; Bi = B->i ; Bx = B->x ; bpacked = B->packed ; /* get the size of C */ nrow = A->nrow ; ncol = B->ncol ; /* get workspace */ W = Common->Xwork ; /* size nrow, unused if values is FALSE */ Flag = Common->Flag ; /* size nrow, Flag [0..nrow-1] < mark on input*/ /* ---------------------------------------------------------------------- */ /* count the number of entries in the result C */ /* ---------------------------------------------------------------------- */ cnz = 0 ; for (j = 0 ; j < ncol ; j++) { /* clear the Flag array */ /* mark = CHOLMOD(clear_flag) (Common) ; */ CHOLMOD_CLEAR_FLAG (Common) ; mark = Common->mark ; /* for each nonzero B(t,j) in column j, do: */ pb = Bp [j] ; pbend = (bpacked) ? (Bp [j+1]) : (pb + Bnz [j]) ; for ( ; pb < pbend ; pb++) { /* B(t,j) is nonzero */ t = Bi [pb] ; /* add the nonzero pattern of A(:,t) to the pattern of C(:,j) */ pa = Ap [t] ; paend = (apacked) ? (Ap [t+1]) : (pa + Anz [t]) ; for ( ; pa < paend ; pa++) { i = Ai [pa] ; if (Flag [i] != mark) { Flag [i] = mark ; cnz++ ; } } } if (cnz < 0) { break ; /* integer overflow case */ } } /* mark = CHOLMOD(clear_flag) (Common) ; */ CHOLMOD_CLEAR_FLAG (Common) ; mark = Common->mark ; /* ---------------------------------------------------------------------- */ /* check for integer overflow */ /* ---------------------------------------------------------------------- */ if (cnz < 0) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; CHOLMOD(free_sparse) (&A2, Common) ; CHOLMOD(free_sparse) (&B2, Common) ; ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, values ? n1:0, Common)) ; return (NULL) ; } /* ---------------------------------------------------------------------- */ /* Determine how to return C sorted (if requested) */ /* ---------------------------------------------------------------------- */ do_swap_and_transpose = FALSE ; if (sorted) { /* Determine the best way to return C with sorted columns. Computing * C = (B'*A')' takes cnz + anz + bnz time (ignoring O(n) terms). * Sorting C when done, C = (A*B)'', takes 2*cnz time. Pick the one * with the least amount of work. */ anz = CHOLMOD(nnz) (A, Common) ; bnz = CHOLMOD(nnz) (B, Common) ; do_swap_and_transpose = (anz + bnz < cnz) ; if (do_swap_and_transpose) { /* -------------------------------------------------------------- */ /* C = (B'*A')' */ /* -------------------------------------------------------------- */ /* workspace: Iwork (A->nrow) */ A3 = CHOLMOD(ptranspose) (A, values, NULL, NULL, 0, Common) ; CHOLMOD(free_sparse) (&A2, Common) ; A2 = A3 ; if (Common->status < CHOLMOD_OK) { /* out of memory */ CHOLMOD(free_sparse) (&A2, Common) ; CHOLMOD(free_sparse) (&B2, Common) ; ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, values ? n1:0, Common)); return (NULL) ; } /* workspace: Iwork (B->nrow) */ B3 = CHOLMOD(ptranspose) (B, values, NULL, NULL, 0, Common) ; CHOLMOD(free_sparse) (&B2, Common) ; B2 = B3 ; if (Common->status < CHOLMOD_OK) { /* out of memory */ CHOLMOD(free_sparse) (&A2, Common) ; CHOLMOD(free_sparse) (&B2, Common) ; ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, values ? n1:0, Common)); return (NULL) ; } A = B2 ; B = A2 ; /* get the new A matrix */ Ap = A->p ; Anz = A->nz ; Ai = A->i ; Ax = A->x ; apacked = A->packed ; /* get the new B matrix */ Bp = B->p ; Bnz = B->nz ; Bi = B->i ; Bx = B->x ; bpacked = B->packed ; /* get the size of C' */ nrow = A->nrow ; ncol = B->ncol ; } } /* ---------------------------------------------------------------------- */ /* allocate C */ /* ---------------------------------------------------------------------- */ C = CHOLMOD(allocate_sparse) (nrow, ncol, cnz, FALSE, TRUE, 0, values ? A->xtype : CHOLMOD_PATTERN, Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ CHOLMOD(free_sparse) (&A2, Common) ; CHOLMOD(free_sparse) (&B2, Common) ; ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, values ? n1:0, Common)) ; return (NULL) ; } Cp = C->p ; Ci = C->i ; Cx = C->x ; /* ---------------------------------------------------------------------- */ /* C = A*B */ /* ---------------------------------------------------------------------- */ cnz = 0 ; if (values) { /* pattern and values */ for (j = 0 ; j < ncol ; j++) { /* clear the Flag array */ /* mark = CHOLMOD(clear_flag (Common)) ; */ CHOLMOD_CLEAR_FLAG (Common) ; mark = Common->mark ; /* start column j of C */ Cp [j] = cnz ; /* for each nonzero B(t,j) in column j, do: */ pb = Bp [j] ; pbend = (bpacked) ? (Bp [j+1]) : (pb + Bnz [j]) ; for ( ; pb < pbend ; pb++) { /* B(t,j) is nonzero */ t = Bi [pb] ; bjt = Bx [pb] ; /* add the nonzero pattern of A(:,t) to the pattern of C(:,j) * and scatter the values into W */ pa = Ap [t] ; paend = (apacked) ? (Ap [t+1]) : (pa + Anz [t]) ; for ( ; pa < paend ; pa++) { i = Ai [pa] ; if (Flag [i] != mark) { Flag [i] = mark ; Ci [cnz++] = i ; } W [i] += Ax [pa] * bjt ; } } /* gather the values into C(:,j) */ for (p = Cp [j] ; p < cnz ; p++) { i = Ci [p] ; Cx [p] = W [i] ; W [i] = 0 ; } } } else { /* pattern only */ for (j = 0 ; j < ncol ; j++) { /* clear the Flag array */ /* mark = CHOLMOD(clear_flag) (Common) ; */ CHOLMOD_CLEAR_FLAG (Common) ; mark = Common->mark ; /* start column j of C */ Cp [j] = cnz ; /* for each nonzero B(t,j) in column j, do: */ pb = Bp [j] ; pbend = (bpacked) ? (Bp [j+1]) : (pb + Bnz [j]) ; for ( ; pb < pbend ; pb++) { /* B(t,j) is nonzero */ t = Bi [pb] ; /* add the nonzero pattern of A(:,t) to the pattern of C(:,j) */ pa = Ap [t] ; paend = (apacked) ? (Ap [t+1]) : (pa + Anz [t]) ; for ( ; pa < paend ; pa++) { i = Ai [pa] ; if (Flag [i] != mark) { Flag [i] = mark ; Ci [cnz++] = i ; } } } } } Cp [ncol] = cnz ; ASSERT (MAX (1,cnz) == C->nzmax) ; /* ---------------------------------------------------------------------- */ /* clear workspace and free temporary matrices */ /* ---------------------------------------------------------------------- */ CHOLMOD(free_sparse) (&A2, Common) ; CHOLMOD(free_sparse) (&B2, Common) ; /* CHOLMOD(clear_flag) (Common) ; */ CHOLMOD_CLEAR_FLAG (Common) ; ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, values ? n1:0, Common)) ; /* ---------------------------------------------------------------------- */ /* convert C to a symmetric upper/lower matrix if requested */ /* ---------------------------------------------------------------------- */ /* convert C in place, which cannot fail since no memory is allocated */ if (stype > 0) { /* C = triu (C), in place */ (void) CHOLMOD(band_inplace) (0, ncol, values, C, Common) ; C->stype = 1 ; } else if (stype < 0) { /* C = tril (C), in place */ (void) CHOLMOD(band_inplace) (-nrow, 0, values, C, Common) ; C->stype = -1 ; } ASSERT (Common->status >= CHOLMOD_OK) ; /* ---------------------------------------------------------------------- */ /* sort C, if requested */ /* ---------------------------------------------------------------------- */ if (sorted) { if (do_swap_and_transpose) { /* workspace: Iwork (C->ncol), which is A->nrow since C=(B'*A') */ C2 = CHOLMOD(ptranspose) (C, values, NULL, NULL, 0, Common) ; CHOLMOD(free_sparse) (&C, Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, values ? n1:0, Common)); return (NULL) ; } C = C2 ; } else { /* workspace: Iwork (max (C->nrow,C->ncol)) */ if (!CHOLMOD(sort) (C, Common)) { /* out of memory */ CHOLMOD(free_sparse) (&C, Common) ; ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, values ? n1:0, Common)); return (NULL) ; } } } /* ---------------------------------------------------------------------- */ /* return result */ /* ---------------------------------------------------------------------- */ DEBUG (CHOLMOD(dump_sparse) (C, "ssmult", Common) >= 0) ; ASSERT (CHOLMOD(dump_work) (TRUE, TRUE, values ? n1:0, Common)) ; return (C) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/MatrixOps/cholmod_vertcat.c0000644000076500000240000001402313524616144027740 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === MatrixOps/cholmod_vertcat ============================================ */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/MatrixOps Module. Copyright (C) 2005-2006, Timothy A. Davis * The CHOLMOD/MatrixOps Module is licensed under Version 2.0 of the GNU * General Public License. See gpl.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * http://www.suitesparse.com * -------------------------------------------------------------------------- */ /* Vertical concatenation, C = [A ; B] in MATLAB notation. * * A and B can be up/lo/unsym; C is unsymmetric and packed. * A and B must have the same number of columns. * C is sorted if both A and B are sorted. * * workspace: Iwork (max (A->nrow, A->ncol, B->nrow, B->ncol)). * allocates temporary copies of A and B if they are symmetric. * * Only pattern and real matrices are supported. Complex and zomplex matrices * are supported only if "values" is FALSE. */ #ifndef NMATRIXOPS #include "cholmod_internal.h" #include "cholmod_matrixops.h" /* ========================================================================== */ /* === cholmod_vertcat ====================================================== */ /* ========================================================================== */ cholmod_sparse *CHOLMOD(vertcat) ( /* ---- input ---- */ cholmod_sparse *A, /* left matrix to concatenate */ cholmod_sparse *B, /* right matrix to concatenate */ int values, /* if TRUE compute the numerical values of C */ /* --------------- */ cholmod_common *Common ) { double *Ax, *Bx, *Cx ; Int *Ap, *Ai, *Anz, *Bp, *Bi, *Bnz, *Cp, *Ci ; cholmod_sparse *C, *A2, *B2 ; Int apacked, bpacked, anrow, bnrow, ncol, nrow, anz, bnz, nz, j, p, pend, pdest ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; RETURN_IF_NULL (A, NULL) ; RETURN_IF_NULL (B, NULL) ; values = values && (A->xtype != CHOLMOD_PATTERN) && (B->xtype != CHOLMOD_PATTERN) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, values ? CHOLMOD_REAL : CHOLMOD_ZOMPLEX, NULL) ; RETURN_IF_XTYPE_INVALID (B, CHOLMOD_PATTERN, values ? CHOLMOD_REAL : CHOLMOD_ZOMPLEX, NULL) ; if (A->ncol != B->ncol) { /* A and B must have the same number of columns */ ERROR (CHOLMOD_INVALID, "A and B must have same # of columns") ; return (NULL) ; } /* A and B must have the same numerical type if values is TRUE (both must * be CHOLMOD_REAL, this is implicitly checked above) */ Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ anrow = A->nrow ; bnrow = B->nrow ; ncol = A->ncol ; CHOLMOD(allocate_work) (0, MAX3 (anrow, bnrow, ncol), 0, Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ return (NULL) ; } /* ---------------------------------------------------------------------- */ /* get inputs */ /* ---------------------------------------------------------------------- */ /* convert A to unsymmetric, if necessary */ A2 = NULL ; if (A->stype != 0) { /* workspace: Iwork (max (A->nrow,A->ncol)) */ A2 = CHOLMOD(copy) (A, 0, values, Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ return (NULL) ; } A = A2 ; } /* convert B to unsymmetric, if necessary */ B2 = NULL ; if (B->stype != 0) { /* workspace: Iwork (max (B->nrow,B->ncol)) */ B2 = CHOLMOD(copy) (B, 0, values, Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ CHOLMOD(free_sparse) (&A2, Common) ; return (NULL) ; } B = B2 ; } Ap = A->p ; Anz = A->nz ; Ai = A->i ; Ax = A->x ; apacked = A->packed ; Bp = B->p ; Bnz = B->nz ; Bi = B->i ; Bx = B->x ; bpacked = B->packed ; /* ---------------------------------------------------------------------- */ /* allocate C */ /* ---------------------------------------------------------------------- */ anz = CHOLMOD(nnz) (A, Common) ; bnz = CHOLMOD(nnz) (B, Common) ; nrow = anrow + bnrow ; nz = anz + bnz ; C = CHOLMOD(allocate_sparse) (nrow, ncol, nz, A->sorted && B->sorted, TRUE, 0, values ? A->xtype : CHOLMOD_PATTERN, Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ CHOLMOD(free_sparse) (&A2, Common) ; CHOLMOD(free_sparse) (&B2, Common) ; return (NULL) ; } Cp = C->p ; Ci = C->i ; Cx = C->x ; /* ---------------------------------------------------------------------- */ /* C = [A ; B] */ /* ---------------------------------------------------------------------- */ pdest = 0 ; for (j = 0 ; j < ncol ; j++) { /* attach A(:,j) as the first part of C(:,j) */ p = Ap [j] ; pend = (apacked) ? (Ap [j+1]) : (p + Anz [j]) ; Cp [j] = pdest ; for ( ; p < pend ; p++) { Ci [pdest] = Ai [p] ; if (values) { Cx [pdest] = Ax [p] ; } pdest++ ; } /* attach B(:,j) as the second part of C(:,j) */ p = Bp [j] ; pend = (bpacked) ? (Bp [j+1]) : (p + Bnz [j]) ; for ( ; p < pend ; p++) { Ci [pdest] = Bi [p] + anrow ; if (values) { Cx [pdest] = Bx [p] ; } pdest++ ; } } Cp [ncol] = pdest ; ASSERT (pdest == nz) ; /* ---------------------------------------------------------------------- */ /* free the unsymmetric copies of A and B, and return C */ /* ---------------------------------------------------------------------- */ CHOLMOD(free_sparse) (&A2, Common) ; CHOLMOD(free_sparse) (&B2, Common) ; return (C) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Check/0000755000076500000240000000000013617375001023503 5ustar tamasstaff00000000000000python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Check/cholmod_check.c0000644000076500000240000020250413524616144026437 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Check/cholmod_check ================================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Check Module. Copyright (C) 2005-2013, Timothy A. Davis * The CHOLMOD/Check Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Routines to check and print the contents of the 5 CHOLMOD objects: * * No CHOLMOD routine calls the check or print routines. If a user wants to * check CHOLMOD's input parameters, a separate call to the appropriate check * routine should be used before calling other CHOLMOD routines. * * cholmod_check_common check statistics and workspace in Common * cholmod_check_sparse check sparse matrix in compressed column form * cholmod_check_dense check dense matrix * cholmod_check_factor check factorization * cholmod_check_triplet check sparse matrix in triplet form * * cholmod_print_common print statistics in Common * cholmod_print_sparse print sparse matrix in compressed column form * cholmod_print_dense print dense matrix * cholmod_print_factor print factorization * cholmod_print_triplet print sparse matrix in triplet form * * In addition, this file contains routines to check and print three types of * integer vectors: * * cholmod_check_perm check a permutation of 0:n-1 (no duplicates) * cholmod_check_subset check a subset of 0:n-1 (duplicates OK) * cholmod_check_parent check an elimination tree * * cholmod_print_perm print a permutation * cholmod_print_subset print a subset * cholmod_print_parent print an elimination tree * * Each Common->print level prints the items at or below the given level: * * 0: print nothing; just check the data structures and return TRUE/FALSE * 1: error messages * 2: warning messages * 3: one-line summary of each object printed * 4: short summary of each object (first and last few entries) * 5: entire contents of the object * * No CHOLMOD routine calls these routines, so no printing occurs unless * the user specifically calls a cholmod_print_* routine. Thus, the default * print level is 3. * * Common->precise controls the # of digits printed for numerical entries * (5 if FALSE, 15 if TRUE). * * If Common->print_function is NULL, then no printing occurs. The * cholmod_check_* and cholmod_print_* routines still check their inputs and * return TRUE/FALSE if the object is valid or not. * * This file also includes debugging routines that are enabled only when * NDEBUG is defined in cholmod_internal.h (cholmod_dump_*). */ #ifndef NCHECK #include "cholmod_internal.h" #include "cholmod_check.h" /* ========================================================================== */ /* === printing definitions ================================================= */ /* ========================================================================== */ #ifdef LONG #define I8 "%8ld" #define I_8 "%-8ld" #else #define I8 "%8d" #define I_8 "%-8d" #endif #define PR(i,format,arg) \ { \ if (print >= i && Common->print_function != NULL) \ { \ (Common->print_function) (format, arg) ; \ } \ } #define P1(format,arg) PR(1,format,arg) #define P2(format,arg) PR(2,format,arg) #define P3(format,arg) PR(3,format,arg) #define P4(format,arg) PR(4,format,arg) #define ERR(msg) \ { \ P1 ("\nCHOLMOD ERROR: %s: ", type) ; \ if (name != NULL) \ { \ P1 ("%s", name) ; \ } \ P1 (": %s\n", msg) ; \ ERROR (CHOLMOD_INVALID, "invalid") ; \ return (FALSE) ; \ } /* print a numerical value */ #define PRINTVALUE(value) \ { \ if (Common->precise) \ { \ P4 (" %23.15e", value) ; \ } \ else \ { \ P4 (" %.5g", value) ; \ } \ } /* start printing */ #define ETC_START(count,limit) \ { \ count = (init_print == 4) ? (limit) : (-1) ; \ } /* re-enable printing if condition is met */ #define ETC_ENABLE(condition,count,limit) \ { \ if ((condition) && init_print == 4) \ { \ count = limit ; \ print = 4 ; \ } \ } /* turn off printing if limit is reached */ #define ETC_DISABLE(count) \ { \ if ((count >= 0) && (count-- == 0) && print == 4) \ { \ P4 ("%s", " ...\n") ; \ print = 3 ; \ } \ } /* re-enable printing, or turn if off after limit is reached */ #define ETC(condition,count,limit) \ { \ ETC_ENABLE (condition, count, limit) ; \ ETC_DISABLE (count) ; \ } #define BOOLSTR(x) ((x) ? "true " : "false") /* ========================================================================== */ /* === print_value ========================================================== */ /* ========================================================================== */ static void print_value ( Int print, Int xtype, double *Xx, double *Xz, Int p, cholmod_common *Common) { if (xtype == CHOLMOD_REAL) { PRINTVALUE (Xx [p]) ; } else if (xtype == CHOLMOD_COMPLEX) { P4 ("%s", "(") ; PRINTVALUE (Xx [2*p ]) ; P4 ("%s", " , ") ; PRINTVALUE (Xx [2*p+1]) ; P4 ("%s", ")") ; } else if (xtype == CHOLMOD_ZOMPLEX) { P4 ("%s", "(") ; PRINTVALUE (Xx [p]) ; P4 ("%s", " , ") ; PRINTVALUE (Xz [p]) ; P4 ("%s", ")") ; } } /* ========================================================================== */ /* === cholmod_check_common ================================================= */ /* ========================================================================== */ /* Print and verify the contents of Common */ static int check_common ( Int print, const char *name, cholmod_common *Common ) { double fl, lnz ; double *Xwork ; Int *Flag, *Head ; SuiteSparse_long mark ; Int i, nrow, nmethods, ordering, xworksize, amd_backup, init_print ; const char *type = "common" ; /* ---------------------------------------------------------------------- */ /* print control parameters and statistics */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (FALSE) ; init_print = print ; P2 ("%s", "\n") ; P1 ("CHOLMOD version %d", CHOLMOD_MAIN_VERSION) ; P1 (".%d", CHOLMOD_SUB_VERSION) ; P1 (".%d", CHOLMOD_SUBSUB_VERSION) ; P1 (", %s: ", CHOLMOD_DATE) ; if (name != NULL) { P1 ("%s: ", name) ; } switch (Common->status) { case CHOLMOD_OK: P1 ("%s", "status: OK\n") ; break ; case CHOLMOD_OUT_OF_MEMORY: P1 ("%s", "status: ERROR, out of memory\n") ; break ; case CHOLMOD_INVALID: P1 ("%s", "status: ERROR, invalid parameter\n") ; break ; case CHOLMOD_TOO_LARGE: P1 ("%s", "status: ERROR, problem too large\n") ; break ; case CHOLMOD_NOT_INSTALLED: P1 ("%s", "status: ERROR, method not installed\n") ; break ; #if GPU_BLAS case CHOLMOD_GPU_PROBLEM: P1 ("%s", "status: ERROR, GPU had a fatal error\n") ; break ; #endif case CHOLMOD_NOT_POSDEF: P1 ("%s", "status: warning, matrix not positive definite\n") ; break ; case CHOLMOD_DSMALL: P1 ("%s", "status: warning, diagonal entry has tiny abs. value\n") ; break ; default: ERR ("unknown status") ; } P2 (" Architecture: %s\n", CHOLMOD_ARCHITECTURE) ; P3 (" sizeof(int): %d\n", (int) sizeof (int)) ; P3 (" sizeof(SuiteSparse_long): %d\n", (int) sizeof (SuiteSparse_long)); P3 (" sizeof(void *): %d\n", (int) sizeof (void *)) ; P3 (" sizeof(double): %d\n", (int) sizeof (double)) ; P3 (" sizeof(Int): %d (CHOLMOD's basic integer)\n", (int) sizeof (Int)) ; P3 (" sizeof(BLAS_INT): %d (integer used in the BLAS)\n", (int) sizeof (BLAS_INT)) ; if (Common->fl != EMPTY) { P2 ("%s", " Results from most recent analysis:\n") ; P2 (" Cholesky flop count: %.5g\n", Common->fl) ; P2 (" Nonzeros in L: %.5g\n", Common->lnz) ; } if (Common->modfl != EMPTY) { P2 (" Update/downdate flop count: %.5g\n", Common->modfl) ; } P2 (" memory blocks in use: %8.0f\n", (double) (Common->malloc_count)) ; P2 (" memory in use (MB): %8.1f\n", (double) (Common->memory_inuse) / 1048576.) ; P2 (" peak memory usage (MB): %8.1f\n", (double) (Common->memory_usage) / 1048576.) ; /* ---------------------------------------------------------------------- */ /* primary control parameters and related ordering statistics */ /* ---------------------------------------------------------------------- */ P3 (" maxrank: update/downdate rank: "ID"\n", (Int) CHOLMOD(maxrank) (0, Common)) ; P3 (" supernodal control: %d", Common->supernodal) ; P3 (" %g ", Common->supernodal_switch) ; if (Common->supernodal <= CHOLMOD_SIMPLICIAL) { P3 ("%s", "(always do simplicial)\n") ; } else if (Common->supernodal == CHOLMOD_AUTO) { P3 ("(supernodal if flops/lnz >= %g)\n", Common->supernodal_switch) ; } else { P3 ("%s", "(always do supernodal)\n") ; } nmethods = MIN (Common->nmethods, CHOLMOD_MAXMETHODS) ; nmethods = MAX (0, nmethods) ; if (nmethods > 0) { P3 ("%s", " nmethods: number of ordering methods to try: ") ; P3 (""ID"\n", nmethods) ; amd_backup = (nmethods > 1) || (nmethods == 1 && (Common->method [0].ordering == CHOLMOD_METIS || Common->method [0].ordering == CHOLMOD_NESDIS)) ; } else { P3 ("%s", " nmethods=0: default strategy: Try user permutation if " "given. Try AMD.\n") ; #ifndef NPARTITION if (Common->default_nesdis) { P3 ("%s", " Try NESDIS if AMD reports flops/nnz(L) >= 500 and " "nnz(L)/nnz(A) >= 5.\n") ; } else { P3 ("%s", " Try METIS if AMD reports flops/nnz(L) >= 500 and " "nnz(L)/nnz(A) >= 5.\n") ; } #endif P3 ("%s", " Select best ordering tried.\n") ; Common->method [0].ordering = CHOLMOD_GIVEN ; Common->method [1].ordering = CHOLMOD_AMD ; Common->method [2].ordering = (Common->default_nesdis ? CHOLMOD_NESDIS : CHOLMOD_METIS) ; amd_backup = FALSE ; #ifndef NPARTITION nmethods = 3 ; #else nmethods = 2 ; #endif } for (i = 0 ; i < nmethods ; i++) { P3 (" method "ID": ", i) ; ordering = Common->method [i].ordering ; fl = Common->method [i].fl ; lnz = Common->method [i].lnz ; switch (ordering) { case CHOLMOD_NATURAL: P3 ("%s", "natural\n") ; break ; case CHOLMOD_GIVEN: P3 ("%s", "user permutation (if given)\n") ; break ; case CHOLMOD_AMD: P3 ("%s", "AMD (or COLAMD if factorizing AA')\n") ; amd_backup = FALSE ; break ; case CHOLMOD_COLAMD: P3 ("%s", "AMD if factorizing A, COLAMD if factorizing AA')\n"); amd_backup = FALSE ; break ; case CHOLMOD_METIS: P3 ("%s", "METIS_NodeND nested dissection\n") ; break ; case CHOLMOD_NESDIS: P3 ("%s", "CHOLMOD nested dissection\n") ; P3 (" nd_small: # nodes in uncut subgraph: "ID"\n", (Int) (Common->method [i].nd_small)) ; P3 (" nd_compress: compress the graph: %s\n", BOOLSTR (Common->method [i].nd_compress)) ; P3 (" nd_camd: use constrained min degree: %s\n", BOOLSTR (Common->method [i].nd_camd)) ; break ; default: P3 (ID, ordering) ; ERR ("unknown ordering method") ; break ; } if (!(ordering == CHOLMOD_NATURAL || ordering == CHOLMOD_GIVEN)) { if (Common->method [i].prune_dense < 0) { P3 (" prune_dense: for pruning dense nodes: %s\n", " none pruned") ; } else { P3 (" prune_dense: for pruning dense nodes: " "%.5g\n", Common->method [i].prune_dense) ; P3 (" a dense node has degree " ">= max(16,(%.5g)*sqrt(n))\n", Common->method [i].prune_dense) ; } } if (ordering == CHOLMOD_COLAMD || ordering == CHOLMOD_NESDIS) { if (Common->method [i].prune_dense2 < 0) { P3 (" prune_dense2: for pruning dense rows for AA':" " %s\n", " none pruned") ; } else { P3 (" prune_dense2: for pruning dense rows for AA':" " %.5g\n", Common->method [i].prune_dense2) ; P3 (" a dense row has degree " ">= max(16,(%.5g)*sqrt(ncol))\n", Common->method [i].prune_dense2) ; } } if (fl != EMPTY) P3 (" flop count: %.5g\n", fl) ; if (lnz != EMPTY) P3 (" nnz(L): %.5g\n", lnz) ; } /* backup AMD results, if any */ if (amd_backup) { P3 ("%s", " backup method: ") ; P3 ("%s", "AMD (or COLAMD if factorizing AA')\n") ; fl = Common->method [nmethods].fl ; lnz = Common->method [nmethods].lnz ; if (fl != EMPTY) P3 (" AMD flop count: %.5g\n", fl) ; if (lnz != EMPTY) P3 (" AMD nnz(L): %.5g\n", lnz) ; } /* ---------------------------------------------------------------------- */ /* arcane control parameters */ /* ---------------------------------------------------------------------- */ if (Common->final_asis) { P4 ("%s", " final_asis: TRUE, leave as is\n") ; } else { P4 ("%s", " final_asis: FALSE, convert when done\n") ; if (Common->final_super) { P4 ("%s", " final_super: TRUE, leave in supernodal form\n") ; } else { P4 ("%s", " final_super: FALSE, convert to simplicial form\n") ; } if (Common->final_ll) { P4 ("%s", " final_ll: TRUE, convert to LL' form\n") ; } else { P4 ("%s", " final_ll: FALSE, convert to LDL' form\n") ; } if (Common->final_pack) { P4 ("%s", " final_pack: TRUE, pack when done\n") ; } else { P4 ("%s", " final_pack: FALSE, do not pack when done\n") ; } if (Common->final_monotonic) { P4 ("%s", " final_monotonic: TRUE, ensure L is monotonic\n") ; } else { P4 ("%s", " final_monotonic: FALSE, do not ensure L is monotonic\n") ; } P4 (" final_resymbol: remove zeros from amalgamation: %s\n", BOOLSTR (Common->final_resymbol)) ; } P4 (" dbound: LDL' diagonal threshold: % .5g\n Entries with abs. value" " less than dbound are replaced with +/- dbound.\n", Common->dbound) ; P4 (" grow0: memory reallocation: % .5g\n", Common->grow0) ; P4 (" grow1: memory reallocation: % .5g\n", Common->grow1) ; P4 (" grow2: memory reallocation: %g\n", (double) (Common->grow2)) ; P4 ("%s", " nrelax, zrelax: supernodal amalgamation rule:\n") ; P4 ("%s", " s = # columns in two adjacent supernodes\n") ; P4 ("%s", " z = % of zeros in new supernode if they are merged.\n") ; P4 ("%s", " Two supernodes are merged if") ; P4 (" (s <= %g) or (no new zero entries) or\n", (double) (Common->nrelax [0])) ; P4 (" (s <= %g and ", (double) (Common->nrelax [1])) ; P4 ("z < %.5g%%) or", Common->zrelax [0] * 100) ; P4 (" (s <= %g and ", (double) (Common->nrelax [2])) ; P4 ("z < %.5g%%) or", Common->zrelax [1] * 100) ; P4 (" (z < %.5g%%)\n", Common->zrelax [2] * 100) ; /* ---------------------------------------------------------------------- */ /* check workspace */ /* ---------------------------------------------------------------------- */ mark = Common->mark ; nrow = Common->nrow ; Flag = Common->Flag ; Head = Common->Head ; if (nrow > 0) { if (mark < 0 || Flag == NULL || Head == NULL) { ERR ("workspace corrupted (Flag and/or Head missing)") ; } for (i = 0 ; i < nrow ; i++) { if (Flag [i] >= mark) { PRINT0 (("Flag ["ID"]="ID", mark = %ld\n", i, Flag [i], mark)) ; ERR ("workspace corrupted (Flag)") ; } } for (i = 0 ; i <= nrow ; i++) { if (Head [i] != EMPTY) { PRINT0 (("Head ["ID"] = "ID",\n", i, Head [i])) ; ERR ("workspace corrupted (Head)") ; } } } xworksize = Common->xworksize ; Xwork = Common->Xwork ; if (xworksize > 0) { if (Xwork == NULL) { ERR ("workspace corrupted (Xwork missing)") ; } for (i = 0 ; i < xworksize ; i++) { if (Xwork [i] != 0.) { PRINT0 (("Xwork ["ID"] = %g\n", i, Xwork [i])) ; ERR ("workspace corrupted (Xwork)") ; } } } /* workspace and parameters are valid */ P3 ("%s", " OK\n") ; P4 ("%s", "\n") ; return (TRUE) ; } int CHOLMOD(check_common) ( cholmod_common *Common ) { return (check_common (0, NULL, Common)) ; } int CHOLMOD(print_common) ( /* ---- input ---- */ const char *name, /* printed name of Common object */ /* --------------- */ cholmod_common *Common ) { Int print = (Common == NULL) ? 3 : (Common->print) ; return (check_common (print, name, Common)) ; } /* ========================================================================== */ /* === cholmod_gpu_stats ==================================================== */ /* ========================================================================== */ /* Print CPU / GPU statistics. If the timer is not installed, the times are reported as zero, but this function still works. Likewise, the function still works if the GPU BLAS is not installed. */ int CHOLMOD(gpu_stats) ( cholmod_common *Common /* input */ ) { double cpu_time, gpu_time ; int print ; RETURN_IF_NULL_COMMON (FALSE) ; print = Common->print ; P2 ("%s", "\nCHOLMOD GPU/CPU statistics:\n") ; P2 ("SYRK CPU calls %12.0f", (double) Common->CHOLMOD_CPU_SYRK_CALLS) ; P2 (" time %12.4e\n", Common->CHOLMOD_CPU_SYRK_TIME) ; P2 (" GPU calls %12.0f", (double) Common->CHOLMOD_GPU_SYRK_CALLS) ; P2 (" time %12.4e\n", Common->CHOLMOD_GPU_SYRK_TIME) ; P2 ("GEMM CPU calls %12.0f", (double) Common->CHOLMOD_CPU_GEMM_CALLS) ; P2 (" time %12.4e\n", Common->CHOLMOD_CPU_GEMM_TIME) ; P2 (" GPU calls %12.0f", (double) Common->CHOLMOD_GPU_GEMM_CALLS) ; P2 (" time %12.4e\n", Common->CHOLMOD_GPU_GEMM_TIME) ; P2 ("POTRF CPU calls %12.0f", (double) Common->CHOLMOD_CPU_POTRF_CALLS) ; P2 (" time %12.4e\n", Common->CHOLMOD_CPU_POTRF_TIME) ; P2 (" GPU calls %12.0f", (double) Common->CHOLMOD_GPU_POTRF_CALLS) ; P2 (" time %12.4e\n", Common->CHOLMOD_GPU_POTRF_TIME) ; P2 ("TRSM CPU calls %12.0f", (double) Common->CHOLMOD_CPU_TRSM_CALLS) ; P2 (" time %12.4e\n", Common->CHOLMOD_CPU_TRSM_TIME) ; P2 (" GPU calls %12.0f", (double) Common->CHOLMOD_GPU_TRSM_CALLS) ; P2 (" time %12.4e\n", Common->CHOLMOD_GPU_TRSM_TIME) ; cpu_time = Common->CHOLMOD_CPU_SYRK_TIME + Common->CHOLMOD_CPU_TRSM_TIME + Common->CHOLMOD_CPU_GEMM_TIME + Common->CHOLMOD_CPU_POTRF_TIME ; gpu_time = Common->CHOLMOD_GPU_SYRK_TIME + Common->CHOLMOD_GPU_TRSM_TIME + Common->CHOLMOD_GPU_GEMM_TIME + Common->CHOLMOD_GPU_POTRF_TIME ; P2 ("time in the BLAS: CPU %12.4e", cpu_time) ; P2 (" GPU %12.4e", gpu_time) ; P2 (" total: %12.4e\n", cpu_time + gpu_time) ; P2 ("assembly time %12.4e", Common->CHOLMOD_ASSEMBLE_TIME) ; P2 (" %12.4e\n", Common->CHOLMOD_ASSEMBLE_TIME2) ; return (TRUE) ; } /* ========================================================================== */ /* === cholmod_check_sparse ================================================= */ /* ========================================================================== */ /* Ensure that a sparse matrix in column-oriented form is valid, and optionally * print it. Returns the number of entries on the diagonal or -1 if error. * * workspace: Iwork (nrow) */ static SuiteSparse_long check_sparse ( Int *Wi, Int print, const char *name, cholmod_sparse *A, SuiteSparse_long *nnzdiag, cholmod_common *Common ) { double *Ax, *Az ; Int *Ap, *Ai, *Anz ; Int nrow, ncol, nzmax, sorted, packed, j, p, pend, i, nz, ilast, space, init_print, dnz, count, xtype ; const char *type = "sparse" ; /* ---------------------------------------------------------------------- */ /* print header information */ /* ---------------------------------------------------------------------- */ P4 ("%s", "\n") ; P3 ("%s", "CHOLMOD sparse: ") ; if (name != NULL) { P3 ("%s: ", name) ; } if (A == NULL) { ERR ("null") ; } nrow = A->nrow ; ncol = A->ncol ; nzmax = A->nzmax ; sorted = A->sorted ; packed = A->packed ; xtype = A->xtype ; Ap = A->p ; Ai = A->i ; Ax = A->x ; Az = A->z ; Anz = A->nz ; nz = CHOLMOD(nnz) (A, Common) ; P3 (" "ID"", nrow) ; P3 ("-by-"ID", ", ncol) ; P3 ("nz "ID",", nz) ; if (A->stype > 0) { P3 ("%s", " upper.") ; } else if (A->stype < 0) { P3 ("%s", " lower.") ; } else { P3 ("%s", " up/lo.") ; } P4 ("\n nzmax "ID", ", nzmax) ; if (nz > nzmax) { ERR ("nzmax too small") ; } if (!sorted) { P4 ("%s", "un") ; } P4 ("%s", "sorted, ") ; if (!packed) { P4 ("%s", "un") ; } P4 ("%s", "packed, ") ; switch (A->itype) { case CHOLMOD_INT: P4 ("%s", "\n scalar types: int, ") ; break ; case CHOLMOD_INTLONG: ERR ("mixed int/long type unsupported") ; case CHOLMOD_LONG: P4 ("%s", "\n scalar types: SuiteSparse_long, "); break ; default: ERR ("unknown itype") ; } switch (A->xtype) { case CHOLMOD_PATTERN: P4 ("%s", "pattern") ; break ; case CHOLMOD_REAL: P4 ("%s", "real") ; break ; case CHOLMOD_COMPLEX: P4 ("%s", "complex") ; break ; case CHOLMOD_ZOMPLEX: P4 ("%s", "zomplex") ; break ; default: ERR ("unknown xtype") ; } switch (A->dtype) { case CHOLMOD_DOUBLE: P4 ("%s", ", double\n") ; break ; case CHOLMOD_SINGLE: ERR ("float unsupported") ; default: ERR ("unknown dtype") ; } if (A->itype != ITYPE || A->dtype != DTYPE) { ERR ("integer and real type must match routine") ; } if (A->stype && nrow != ncol) { ERR ("symmetric but not square") ; } /* check for existence of Ap, Ai, Anz, Ax, and Az arrays */ if (Ap == NULL) { ERR ("p array not present") ; } if (Ai == NULL) { ERR ("i array not present") ; } if (!packed && Anz == NULL) { ERR ("nz array not present") ; } if (xtype != CHOLMOD_PATTERN && Ax == NULL) { ERR ("x array not present") ; } if (xtype == CHOLMOD_ZOMPLEX && Az == NULL) { ERR ("z array not present") ; } /* packed matrices must start at Ap [0] = 0 */ if (packed && Ap [0] != 0) { ERR ("p [0] must be zero") ; } if (packed && (Ap [ncol] < Ap [0] || Ap [ncol] > nzmax)) { ERR ("p [ncol] invalid") ; } /* ---------------------------------------------------------------------- */ /* allocate workspace if needed */ /* ---------------------------------------------------------------------- */ if (!sorted) { if (Wi == NULL) { CHOLMOD(allocate_work) (0, nrow, 0, Common) ; Wi = Common->Iwork ; /* size nrow, (i/i/l) */ } if (Common->status < CHOLMOD_OK) { return (FALSE) ; /* out of memory */ } for (i = 0 ; i < nrow ; i++) { Wi [i] = EMPTY ; } } /* ---------------------------------------------------------------------- */ /* check and print each column */ /* ---------------------------------------------------------------------- */ init_print = print ; dnz = 0 ; ETC_START (count, 8) ; for (j = 0 ; j < ncol ; j++) { ETC (j == ncol-1, count, 4) ; p = Ap [j] ; if (packed) { pend = Ap [j+1] ; nz = pend - p ; } else { /* Note that Anz [j] < 0 is treated as zero */ nz = MAX (0, Anz [j]) ; pend = p + nz ; } /* Note that space can be negative if the matrix is non-monotonic */ space = Ap [j+1] - p ; P4 (" col "ID":", j) ; P4 (" nz "ID"", nz) ; P4 (" start "ID"", p) ; P4 (" end "ID"", pend) ; if (!packed) { P4 (" space "ID"", space) ; } P4 ("%s", ":\n") ; if (p < 0 || pend > nzmax) { ERR ("pointer invalid") ; } if (nz < 0 || nz > nrow) { ERR ("nz invalid") ; } ilast = EMPTY ; for ( ; p < pend ; p++) { ETC (j == ncol-1 && p >= pend-4, count, -1) ; i = Ai [p] ; P4 (" "I8":", i) ; print_value (print, xtype, Ax, Az, p, Common) ; if (i == j) { dnz++ ; } if (i < 0 || i >= nrow) { ERR ("row index out of range") ; } if (sorted && i <= ilast) { ERR ("row indices out of order") ; } if (!sorted && Wi [i] == j) { ERR ("duplicate row index") ; } P4 ("%s", "\n") ; ilast = i ; if (!sorted) { Wi [i] = j ; } } } /* matrix is valid */ P4 (" nnz on diagonal: "ID"\n", dnz) ; P3 ("%s", " OK\n") ; P4 ("%s", "\n") ; *nnzdiag = dnz ; return (TRUE) ; } int CHOLMOD(check_sparse) ( /* ---- input ---- */ cholmod_sparse *A, /* sparse matrix to check */ /* --------------- */ cholmod_common *Common ) { SuiteSparse_long nnzdiag ; RETURN_IF_NULL_COMMON (FALSE) ; Common->status = CHOLMOD_OK ; return (check_sparse (NULL, 0, NULL, A, &nnzdiag, Common)) ; } int CHOLMOD(print_sparse) ( /* ---- input ---- */ cholmod_sparse *A, /* sparse matrix to print */ const char *name, /* printed name of sparse matrix */ /* --------------- */ cholmod_common *Common ) { SuiteSparse_long nnzdiag ; RETURN_IF_NULL_COMMON (FALSE) ; Common->status = CHOLMOD_OK ; return (check_sparse (NULL, Common->print, name, A, &nnzdiag, Common)) ; } /* ========================================================================== */ /* === cholmod_check_dense ================================================== */ /* ========================================================================== */ /* Ensure a dense matrix is valid, and optionally print it. */ static int check_dense ( Int print, const char *name, cholmod_dense *X, cholmod_common *Common ) { double *Xx, *Xz ; Int i, j, d, nrow, ncol, nzmax, nz, init_print, count, xtype ; const char *type = "dense" ; /* ---------------------------------------------------------------------- */ /* print header information */ /* ---------------------------------------------------------------------- */ P4 ("%s", "\n") ; P3 ("%s", "CHOLMOD dense: ") ; if (name != NULL) { P3 ("%s: ", name) ; } if (X == NULL) { ERR ("null") ; } nrow = X->nrow ; ncol = X->ncol ; nzmax = X->nzmax ; d = X->d ; Xx = X->x ; Xz = X->z ; xtype = X->xtype ; P3 (" "ID"", nrow) ; P3 ("-by-"ID", ", ncol) ; P4 ("\n leading dimension "ID", ", d) ; P4 ("nzmax "ID", ", nzmax) ; if (d * ncol > nzmax) { ERR ("nzmax too small") ; } if (d < nrow) { ERR ("leading dimension must be >= # of rows") ; } if (Xx == NULL) { ERR ("null") ; } switch (X->xtype) { case CHOLMOD_PATTERN: ERR ("pattern unsupported") ; break ; case CHOLMOD_REAL: P4 ("%s", "real") ; break ; case CHOLMOD_COMPLEX: P4 ("%s", "complex") ; break ; case CHOLMOD_ZOMPLEX: P4 ("%s", "zomplex") ; break ; default: ERR ("unknown xtype") ; } switch (X->dtype) { case CHOLMOD_DOUBLE: P4 ("%s", ", double\n") ; break ; case CHOLMOD_SINGLE: ERR ("single unsupported") ; default: ERR ("unknown dtype") ; } /* ---------------------------------------------------------------------- */ /* check and print each entry */ /* ---------------------------------------------------------------------- */ if (print >= 4) { init_print = print ; ETC_START (count, 9) ; nz = nrow * ncol ; for (j = 0 ; j < ncol ; j++) { ETC (j == ncol-1, count, 5) ; P4 (" col "ID":\n", j) ; for (i = 0 ; i < nrow ; i++) { ETC (j == ncol-1 && i >= nrow-4, count, -1) ; P4 (" "I8":", i) ; print_value (print, xtype, Xx, Xz, i+j*d, Common) ; P4 ("%s", "\n") ; } } } /* dense is valid */ P3 ("%s", " OK\n") ; P4 ("%s", "\n") ; return (TRUE) ; } int CHOLMOD(check_dense) ( /* ---- input ---- */ cholmod_dense *X, /* dense matrix to check */ /* --------------- */ cholmod_common *Common ) { RETURN_IF_NULL_COMMON (FALSE) ; Common->status = CHOLMOD_OK ; return (check_dense (0, NULL, X, Common)) ; } int CHOLMOD(print_dense) ( /* ---- input ---- */ cholmod_dense *X, /* dense matrix to print */ const char *name, /* printed name of dense matrix */ /* --------------- */ cholmod_common *Common ) { RETURN_IF_NULL_COMMON (FALSE) ; Common->status = CHOLMOD_OK ; return (check_dense (Common->print, name, X, Common)) ; } /* ========================================================================== */ /* === cholmod_check_subset ================================================= */ /* ========================================================================== */ /* Ensure S (0:len-1) is a subset of 0:n-1. Duplicates are allowed. S may be * NULL. A negative len denotes the set 0:n-1. * * To check the rset and cset for A(rset,cset), where nc and nr are the length * of cset and rset respectively: * * cholmod_check_subset (cset, nc, A->ncol, Common) ; * cholmod_check_subset (rset, nr, A->nrow, Common) ; * * workspace: none */ static int check_subset ( Int *S, SuiteSparse_long len, size_t n, Int print, const char *name, cholmod_common *Common ) { Int i, k, init_print, count ; const char *type = "subset" ; init_print = print ; if (S == NULL) { /* zero len denotes S = [ ], negative len denotes S = 0:n-1 */ len = (len < 0) ? (-1) : 0 ; } P4 ("%s", "\n") ; P3 ("%s", "CHOLMOD subset: ") ; if (name != NULL) { P3 ("%s: ", name) ; } P3 (" len: %ld ", len) ; if (len < 0) { P3 ("%s", "(denotes 0:n-1) ") ; } P3 ("n: "ID"", (Int) n) ; P4 ("%s", "\n") ; if (len <= 0 || S == NULL) { P3 ("%s", " OK\n") ; P4 ("%s", "\n") ; return (TRUE) ; } if (print >= 4) { ETC_START (count, 8) ; for (k = 0 ; k < ((Int) len) ; k++) { ETC (k == ((Int) len) - 4, count, -1) ; i = S [k] ; P4 (" "I8":", k) ; P4 (" "ID"\n", i) ; if (i < 0 || i >= ((Int) n)) { ERR ("entry out range") ; } } } else { for (k = 0 ; k < ((Int) len) ; k++) { i = S [k] ; if (i < 0 || i >= ((Int) n)) { ERR ("entry out range") ; } } } P3 ("%s", " OK\n") ; P4 ("%s", "\n") ; return (TRUE) ; } int CHOLMOD(check_subset) ( /* ---- input ---- */ Int *Set, /* Set [0:len-1] is a subset of 0:n-1. Duplicates OK */ SuiteSparse_long len, /* size of Set (an integer array), or < 0 if 0:n-1 */ size_t n, /* 0:n-1 is valid range */ /* --------------- */ cholmod_common *Common ) { RETURN_IF_NULL_COMMON (FALSE) ; Common->status = CHOLMOD_OK ; return (check_subset (Set, len, n, 0, NULL, Common)) ; } int CHOLMOD(print_subset) ( /* ---- input ---- */ Int *Set, /* Set [0:len-1] is a subset of 0:n-1. Duplicates OK */ SuiteSparse_long len, /* size of Set (an integer array), or < 0 if 0:n-1 */ size_t n, /* 0:n-1 is valid range */ const char *name, /* printed name of Set */ /* --------------- */ cholmod_common *Common ) { RETURN_IF_NULL_COMMON (FALSE) ; Common->status = CHOLMOD_OK ; return (check_subset (Set, len, n, Common->print, name, Common)) ; } /* ========================================================================== */ /* === cholmod_check_perm =================================================== */ /* ========================================================================== */ /* Ensure that Perm [0..len-1] is a permutation of a subset of 0:n-1. Perm * may be NULL, which is interpreted as the identity permutation. There can * be no duplicate entries (len must be <= n). * * If n <= Common->nrow, then this routine takes O(len) time and does not * allocate any memory, by using Common->Flag. Otherwise, it takes O(n) time * and ensures that Common->Iwork is at least n*sizeof(Int) in size. * * To check the fset: cholmod_check_perm (fset, fsize, ncol, Common) ; * To check a permutation: cholmod_check_perm (Perm, n, n, Common) ; * * workspace: Flag (n) if n <= Common->nrow, Iwork (n) otherwise. */ static int check_perm ( Int *Wi, Int print, const char *name, Int *Perm, size_t len, size_t n, cholmod_common *Common ) { Int *Flag ; Int i, k, mark, init_print, count ; const char *type = "perm" ; /* ---------------------------------------------------------------------- */ /* checks that take O(1) time */ /* ---------------------------------------------------------------------- */ if (Perm == NULL || n == 0) { /* Perm is valid implicit identity, or empty */ return (TRUE) ; } /* ---------------------------------------------------------------------- */ /* checks that take O(n) time or require memory allocation */ /* ---------------------------------------------------------------------- */ init_print = print ; ETC_START (count, 8) ; if (Wi == NULL && n <= Common->nrow) { /* use the Common->Flag array if it's big enough */ mark = CHOLMOD(clear_flag) (Common) ; Flag = Common->Flag ; ASSERT (CHOLMOD(dump_work) (TRUE, FALSE, 0, Common)) ; if (print >= 4) { for (k = 0 ; k < ((Int) len) ; k++) { ETC (k >= ((Int) len) - 4, count, -1) ; i = Perm [k] ; P4 (" "I8":", k) ; P4 (""ID"\n", i) ; if (i < 0 || i >= ((Int) n) || Flag [i] == mark) { CHOLMOD(clear_flag) (Common) ; ERR ("invalid permutation") ; } Flag [i] = mark ; } } else { for (k = 0 ; k < ((Int) len) ; k++) { i = Perm [k] ; if (i < 0 || i >= ((Int) n) || Flag [i] == mark) { CHOLMOD(clear_flag) (Common) ; ERR ("invalid permutation") ; } Flag [i] = mark ; } } CHOLMOD(clear_flag) (Common) ; ASSERT (CHOLMOD(dump_work) (TRUE, FALSE, 0, Common)) ; } else { if (Wi == NULL) { /* use Common->Iwork instead, but initialize it first */ CHOLMOD(allocate_work) (0, n, 0, Common) ; Wi = Common->Iwork ; /* size n, (i/i/i) is OK */ } if (Common->status < CHOLMOD_OK) { return (FALSE) ; /* out of memory */ } for (i = 0 ; i < ((Int) n) ; i++) { Wi [i] = FALSE ; } if (print >= 4) { for (k = 0 ; k < ((Int) len) ; k++) { ETC (k >= ((Int) len) - 4, count, -1) ; i = Perm [k] ; P4 (" "I8":", k) ; P4 (""ID"\n", i) ; if (i < 0 || i >= ((Int) n) || Wi [i]) { ERR ("invalid permutation") ; } Wi [i] = TRUE ; } } else { for (k = 0 ; k < ((Int) len) ; k++) { i = Perm [k] ; if (i < 0 || i >= ((Int) n) || Wi [i]) { ERR ("invalid permutation") ; } Wi [i] = TRUE ; } } } /* perm is valid */ return (TRUE) ; } int CHOLMOD(check_perm) ( /* ---- input ---- */ Int *Perm, /* Perm [0:len-1] is a permutation of subset of 0:n-1 */ size_t len, /* size of Perm (an integer array) */ size_t n, /* 0:n-1 is valid range */ /* --------------- */ cholmod_common *Common ) { RETURN_IF_NULL_COMMON (FALSE) ; Common->status = CHOLMOD_OK ; return (check_perm (NULL, 0, NULL, Perm, len, n, Common)) ; } int CHOLMOD(print_perm) ( /* ---- input ---- */ Int *Perm, /* Perm [0:len-1] is a permutation of subset of 0:n-1 */ size_t len, /* size of Perm (an integer array) */ size_t n, /* 0:n-1 is valid range */ const char *name, /* printed name of Perm */ /* --------------- */ cholmod_common *Common ) { Int ok, print ; RETURN_IF_NULL_COMMON (FALSE) ; Common->status = CHOLMOD_OK ; print = Common->print ; P4 ("%s", "\n") ; P3 ("%s", "CHOLMOD perm: ") ; if (name != NULL) { P3 ("%s: ", name) ; } P3 (" len: "ID"", (Int) len) ; P3 (" n: "ID"", (Int) n) ; P4 ("%s", "\n") ; ok = check_perm (NULL, print, name, Perm, len, n, Common) ; if (ok) { P3 ("%s", " OK\n") ; P4 ("%s", "\n") ; } return (ok) ; } /* ========================================================================== */ /* === cholmod_check_parent ================================================= */ /* ========================================================================== */ /* Ensure that Parent is a valid elimination tree of nodes 0 to n-1. * If j is a root of the tree then Parent [j] is EMPTY (-1). * * NOTE: this check will fail if applied to the component tree (CParent) in * cholmod_nested_dissection, unless it has been postordered and renumbered. * * workspace: none */ static int check_parent ( Int *Parent, size_t n, Int print, const char *name, cholmod_common *Common ) { Int j, p, init_print, count ; const char *type = "parent" ; init_print = print ; P4 ("%s", "\n") ; P3 ("%s", "CHOLMOD parent: ") ; if (name != NULL) { P3 ("%s: ", name) ; } P3 (" n: "ID"", (Int) n) ; P4 ("%s", "\n") ; if (Parent == NULL) { ERR ("null") ; } /* ---------------------------------------------------------------------- */ /* checks that take O(n) time */ /* ---------------------------------------------------------------------- */ ETC_START (count, 8) ; for (j = 0 ; j < ((Int) n) ; j++) { ETC (j == ((Int) n) - 4, count, -1) ; p = Parent [j] ; P4 (" "I8":", j) ; P4 (" "ID"\n", p) ; if (!(p == EMPTY || p > j)) { ERR ("invalid") ; } } P3 ("%s", " OK\n") ; P4 ("%s", "\n") ; return (TRUE) ; } int CHOLMOD(check_parent) ( /* ---- input ---- */ Int *Parent, /* Parent [0:n-1] is an elimination tree */ size_t n, /* size of Parent */ /* --------------- */ cholmod_common *Common ) { RETURN_IF_NULL_COMMON (FALSE) ; Common->status = CHOLMOD_OK ; return (check_parent (Parent, n, 0, NULL, Common)) ; } int CHOLMOD(print_parent) ( /* ---- input ---- */ Int *Parent, /* Parent [0:n-1] is an elimination tree */ size_t n, /* size of Parent */ const char *name, /* printed name of Parent */ /* --------------- */ cholmod_common *Common ) { RETURN_IF_NULL_COMMON (FALSE) ; Common->status = CHOLMOD_OK ; return (check_parent (Parent, n, Common->print, name, Common)) ; } /* ========================================================================== */ /* === cholmod_check_factor ================================================= */ /* ========================================================================== */ static int check_factor ( Int *Wi, Int print, const char *name, cholmod_factor *L, cholmod_common *Common ) { double *Lx, *Lz ; Int *Lp, *Li, *Lnz, *Lnext, *Lprev, *Perm, *ColCount, *Lpi, *Lpx, *Super, *Ls ; Int n, nzmax, j, p, pend, i, nz, ordering, space, is_monotonic, minor, count, precise, init_print, ilast, lnz, head, tail, jprev, plast, jnext, examine_super, nsuper, s, k1, k2, psi, psend, psx, nsrow, nscol, ps2, psxend, ssize, xsize, maxcsize, maxesize, nsrow2, jj, ii, xtype ; Int for_cholesky ; const char *type = "factor" ; /* ---------------------------------------------------------------------- */ /* print header information */ /* ---------------------------------------------------------------------- */ P4 ("%s", "\n") ; P3 ("%s", "CHOLMOD factor: ") ; if (name != NULL) { P3 ("%s: ", name) ; } if (L == NULL) { ERR ("null") ; } n = L->n ; minor = L->minor ; ordering = L->ordering ; xtype = L->xtype ; Perm = L->Perm ; ColCount = L->ColCount ; lnz = 0 ; precise = Common->precise ; P3 (" "ID"", n) ; P3 ("-by-"ID"", n) ; if (minor < n) { P3 (" not positive definite (column "ID")", minor) ; } switch (L->itype) { case CHOLMOD_INT: P4 ("%s", "\n scalar types: int, ") ; break ; case CHOLMOD_INTLONG: ERR ("mixed int/long type unsupported") ; case CHOLMOD_LONG: P4 ("%s", "\n scalar types: SuiteSparse_long, "); break ; default: ERR ("unknown itype") ; } switch (L->xtype) { case CHOLMOD_PATTERN: P4 ("%s", "pattern") ; break ; case CHOLMOD_REAL: P4 ("%s", "real") ; break ; case CHOLMOD_COMPLEX: P4 ("%s", "complex") ; break ; case CHOLMOD_ZOMPLEX: P4 ("%s", "zomplex") ; break ; default: ERR ("unknown xtype") ; } switch (L->dtype) { case CHOLMOD_DOUBLE: P4 ("%s", ", double\n") ; break ; case CHOLMOD_SINGLE: ERR ("single unsupported") ; default: ERR ("unknown dtype") ; } if (L->itype != ITYPE || L->dtype != DTYPE) { ERR ("integer and real type must match routine") ; } if (L->is_super) { P3 ("%s", " supernodal") ; } else { P3 ("%s", " simplicial") ; } if (L->is_ll) { P3 ("%s", ", LL'.") ; } else { P3 ("%s", ", LDL'.") ; } P4 ("%s", "\n ordering method used: ") ; switch (L->ordering) { case CHOLMOD_POSTORDERED:P4 ("%s", "natural (postordered)") ; break ; case CHOLMOD_NATURAL: P4 ("%s", "natural") ; break ; case CHOLMOD_GIVEN: P4 ("%s", "user-provided") ; break ; case CHOLMOD_AMD: P4 ("%s", "AMD") ; break ; case CHOLMOD_COLAMD: P4 ("%s", "AMD for A, COLAMD for A*A'") ;break ; #ifndef NPARTITION case CHOLMOD_METIS: P4 ("%s", "METIS NodeND") ; break ; case CHOLMOD_NESDIS: P4 ("%s", "CHOLMOD nested dissection") ; break ; #endif default: ERR ("unknown ordering") ; } P4 ("%s", "\n") ; init_print = print ; if (L->is_super && L->xtype == CHOLMOD_ZOMPLEX) { ERR ("Supernodal zomplex L not supported") ; } /* ---------------------------------------------------------------------- */ /* check L->Perm */ /* ---------------------------------------------------------------------- */ if (!check_perm (Wi, print, name, Perm, n, n, Common)) { return (FALSE) ; } /* ---------------------------------------------------------------------- */ /* check L->ColCount */ /* ---------------------------------------------------------------------- */ if (ColCount == NULL) { ERR ("ColCount vector invalid") ; } ETC_START (count, 8) ; for (j = 0 ; j < n ; j++) { ETC (j >= n-4, count, -1) ; P4 (" col: "ID" ", j) ; nz = ColCount [j] ; P4 ("colcount: "ID"\n", nz) ; if (nz < 0 || nz > n-j) { ERR ("ColCount out of range") ; } } /* ---------------------------------------------------------------------- */ /* check factor */ /* ---------------------------------------------------------------------- */ if (L->xtype == CHOLMOD_PATTERN && !(L->is_super)) { /* ------------------------------------------------------------------ */ /* check simplicial symbolic factor */ /* ------------------------------------------------------------------ */ /* nothing else to do */ ; } else if (L->xtype != CHOLMOD_PATTERN && !(L->is_super)) { /* ------------------------------------------------------------------ */ /* check simplicial numerical factor */ /* ------------------------------------------------------------------ */ P4 ("monotonic: %d\n", L->is_monotonic) ; nzmax = L->nzmax ; P3 (" nzmax "ID".", nzmax) ; P4 ("%s", "\n") ; Lp = L->p ; Li = L->i ; Lx = L->x ; Lz = L->z ; Lnz = L->nz ; Lnext = L->next ; Lprev = L->prev ; /* check for existence of Lp, Li, Lnz, Lnext, Lprev, and Lx arrays */ if (Lp == NULL) { ERR ("p array not present") ; } if (Li == NULL) { ERR ("i array not present") ; } if (Lnz == NULL) { ERR ("nz array not present") ; } if (Lx == NULL) { ERR ("x array not present") ; } if (xtype == CHOLMOD_ZOMPLEX && Lz == NULL) { ERR ("z array not present") ; } if (Lnext == NULL) { ERR ("next array not present") ; } if (Lprev == NULL) { ERR ("prev array not present") ; } ETC_START (count, 8) ; /* check each column of L */ plast = 0 ; is_monotonic = TRUE ; for (j = 0 ; j < n ; j++) { ETC (j >= n-3, count, -1) ; p = Lp [j] ; nz = Lnz [j] ; pend = p + nz ; lnz += nz ; P4 (" col "ID":", j) ; P4 (" nz "ID"", nz) ; P4 (" start "ID"", p) ; P4 (" end "ID"", pend) ; if (Lnext [j] < 0 || Lnext [j] > n) { ERR ("invalid link list") ; } space = Lp [Lnext [j]] - p ; P4 (" space "ID"", space) ; P4 (" free "ID":\n", space - nz) ; if (p < 0 || pend > nzmax || space < 1) { ERR ("pointer invalid") ; } if (nz < 1 || nz > (n-j) || nz > space) { ERR ("nz invalid") ; } ilast = j-1 ; if (p < plast) { is_monotonic = FALSE ; } plast = p ; i = Li [p] ; P4 (" "I8":", i) ; if (i != j) { ERR ("diagonal missing") ; } print_value (print, xtype, Lx, Lz, p, Common) ; P4 ("%s", "\n") ; ilast = j ; for (p++ ; p < pend ; p++) { ETC_DISABLE (count) ; i = Li [p] ; P4 (" "I8":", i) ; if (i < j || i >= n) { ERR ("row index out of range") ; } if (i <= ilast) { ERR ("row indices out of order") ; } print_value (print, xtype, Lx, Lz, p, Common) ; P4 ("%s", "\n") ; ilast = i ; } } if (L->is_monotonic && !is_monotonic) { ERR ("columns not monotonic") ; } /* check the link list */ head = n+1 ; tail = n ; j = head ; jprev = EMPTY ; count = 0 ; for ( ; ; ) { if (j < 0 || j > n+1 || count > n+2) { ERR ("invalid link list") ; } jnext = Lnext [j] ; if (j >= 0 && j < n) { if (jprev != Lprev [j]) { ERR ("invalid link list") ; } } count++ ; if (j == tail) { break ; } jprev = j ; j = jnext ; } if (Lnext [tail] != EMPTY || count != n+2) { ERR ("invalid link list") ; } } else { /* ------------------------------------------------------------------ */ /* check supernodal numeric or symbolic factor */ /* ------------------------------------------------------------------ */ nsuper = L->nsuper ; ssize = L->ssize ; xsize = L->xsize ; maxcsize = L->maxcsize ; maxesize = L->maxesize ; Ls = L->s ; Lpi = L->pi ; Lpx = L->px ; Super = L->super ; Lx = L->x ; ETC_START (count, 8) ; P4 (" ssize "ID" ", ssize) ; P4 ("xsize "ID" ", xsize) ; P4 ("maxcsize "ID" ", maxcsize) ; P4 ("maxesize "ID"\n", maxesize) ; if (Ls == NULL) { ERR ("invalid: L->s missing") ; } if (Lpi == NULL) { ERR ("invalid: L->pi missing") ; } if (Lpx == NULL) { ERR ("invalid: L->px missing") ; } if (Super == NULL) { ERR ("invalid: L->super missing") ; } if (L->xtype != CHOLMOD_PATTERN) { /* numerical supernodal factor */ if (Lx == NULL) { ERR ("invalid: L->x missing") ; } if (Ls [0] == EMPTY) { ERR ("invalid: L->s not defined") ; } examine_super = TRUE ; } else { /* symbolic supernodal factor, but only if it has been computed */ examine_super = (Ls [0] != EMPTY) ; } if (examine_super) { if (Lpi [0] != 0 || MAX (1, Lpi [nsuper]) != ssize) { PRINT0 (("Lpi [0] "ID", Lpi [nsuper = "ID"] = "ID"\n", Lpi [0], nsuper, Lpi [nsuper])) ; ERR ("invalid: L->pi invalid") ; } for_cholesky = (Lpx [0] != 123456) ; if (for_cholesky && (Lpx [0] != 0 || MAX (1, Lpx[nsuper]) != xsize)) { ERR ("invalid: L->px invalid") ; } /* check and print each supernode */ for (s = 0 ; s < nsuper ; s++) { k1 = Super [s] ; k2 = Super [s+1] ; psi = Lpi [s] ; psend = Lpi [s+1] ; nsrow = psend - psi ; nscol = k2 - k1 ; nsrow2 = nsrow - nscol ; ps2 = psi + nscol ; if (for_cholesky) { psx = Lpx [s] ; psxend = Lpx [s+1] ; } ETC (s == nsuper-1, count, 4) ; P4 (" supernode "ID", ", s) ; P4 ("col "ID" ", k1) ; P4 ("to "ID". ", k2-1) ; P4 ("nz in first col: "ID".\n", nsrow) ; if (for_cholesky) { P4 (" values start "ID", ", psx) ; P4 ("end "ID"\n", psxend) ; } if (k1 > k2 || k1 < 0 || k2 > n || nsrow < nscol || nsrow2 < 0 || (for_cholesky && psxend - psx != nsrow * nscol)) { ERR ("invalid supernode") ; } lnz += nscol * nsrow - (nscol*nscol - nscol)/2 ; if (L->xtype != CHOLMOD_PATTERN) { /* print each column of the supernode */ for (jj = 0 ; jj < nscol ; jj++) { ETC_ENABLE (s == nsuper-1 && jj >= nscol-3, count, -1) ; j = k1 + jj ; P4 (" col "ID"\n", j) ; ilast = j ; i = Ls [psi + jj] ; P4 (" "I8":", i) ; if (i != j) { ERR ("row index invalid") ; } /* PRINTVALUE (Lx [psx + jj + jj*nsrow]) ; */ print_value (print, xtype, Lx, NULL, psx + jj + jj*nsrow, Common) ; P4 ("%s", "\n") ; for (ii = jj + 1 ; ii < nsrow ; ii++) { ETC_DISABLE (count) ; i = Ls [psi + ii] ; P4 (" "I8":", i) ; if (i <= ilast || i > n) { ERR ("row index out of range") ; } /* PRINTVALUE (Lx [psx + ii + jj*nsrow]) ; */ print_value (print, xtype, Lx, NULL, psx + ii + jj*nsrow, Common) ; P4 ("%s", "\n") ; ilast = i ; } } } else { /* just print the leading column of the supernode */ P4 (" col "ID"\n", k1) ; for (jj = 0 ; jj < nscol ; jj++) { ETC (s == nsuper-1 && jj >= nscol-3, count, -1) ; j = k1 + jj ; i = Ls [psi + jj] ; P4 (" "I8"", i) ; if (i != j) { ERR ("row index invalid") ; } P4 ("%s", "\n") ; } ilast = j ; for (ii = nscol ; ii < nsrow ; ii++) { ETC_DISABLE (count) ; i = Ls [psi + ii] ; P4 (" "I8"", i) ; if (i <= ilast || i > n) { ERR ("row index out of range") ; } P4 ("%s", "\n") ; ilast = i ; } } } } } /* factor is valid */ P3 (" nz "ID"", lnz) ; P3 ("%s", " OK\n") ; P4 ("%s", "\n") ; return (TRUE) ; } int CHOLMOD(check_factor) ( /* ---- input ---- */ cholmod_factor *L, /* factor to check */ /* --------------- */ cholmod_common *Common ) { RETURN_IF_NULL_COMMON (FALSE) ; Common->status = CHOLMOD_OK ; return (check_factor (NULL, 0, NULL, L, Common)) ; } int CHOLMOD(print_factor) ( /* ---- input ---- */ cholmod_factor *L, /* factor to print */ const char *name, /* printed name of factor */ /* --------------- */ cholmod_common *Common ) { RETURN_IF_NULL_COMMON (FALSE) ; Common->status = CHOLMOD_OK ; return (check_factor (NULL, Common->print, name, L, Common)) ; } /* ========================================================================== */ /* === cholmod_check_triplet ================================================ */ /* ========================================================================== */ /* Ensure a triplet matrix is valid, and optionally print it. */ static int check_triplet ( Int print, const char *name, cholmod_triplet *T, cholmod_common *Common ) { double *Tx, *Tz ; Int *Ti, *Tj ; Int i, j, p, nrow, ncol, nzmax, nz, xtype, init_print, count ; const char *type = "triplet" ; /* ---------------------------------------------------------------------- */ /* print header information */ /* ---------------------------------------------------------------------- */ P4 ("%s", "\n") ; P3 ("%s", "CHOLMOD triplet: ") ; if (name != NULL) { P3 ("%s: ", name) ; } if (T == NULL) { ERR ("null") ; } nrow = T->nrow ; ncol = T->ncol ; nzmax = T->nzmax ; nz = T->nnz ; Ti = T->i ; Tj = T->j ; Tx = T->x ; Tz = T->z ; xtype = T->xtype ; P3 (" "ID"", nrow) ; P3 ("-by-"ID", ", ncol) ; P3 ("nz "ID",", nz) ; if (T->stype > 0) { P3 ("%s", " upper.") ; } else if (T->stype < 0) { P3 ("%s", " lower.") ; } else { P3 ("%s", " up/lo.") ; } P4 ("\n nzmax "ID", ", nzmax) ; if (nz > nzmax) { ERR ("nzmax too small") ; } switch (T->itype) { case CHOLMOD_INT: P4 ("%s", "\n scalar types: int, ") ; break ; case CHOLMOD_INTLONG: ERR ("mixed int/long type unsupported") ; case CHOLMOD_LONG: P4 ("%s", "\n scalar types: SuiteSparse_long, "); break ; default: ERR ("unknown itype") ; } switch (T->xtype) { case CHOLMOD_PATTERN: P4 ("%s", "pattern") ; break ; case CHOLMOD_REAL: P4 ("%s", "real") ; break ; case CHOLMOD_COMPLEX: P4 ("%s", "complex") ; break ; case CHOLMOD_ZOMPLEX: P4 ("%s", "zomplex") ; break ; default: ERR ("unknown xtype") ; } switch (T->dtype) { case CHOLMOD_DOUBLE: P4 ("%s", ", double\n") ; break ; case CHOLMOD_SINGLE: ERR ("single unsupported") ; default: ERR ("unknown dtype") ; } if (T->itype != ITYPE || T->dtype != DTYPE) { ERR ("integer and real type must match routine") ; } if (T->stype && nrow != ncol) { ERR ("symmetric but not square") ; } /* check for existence of Ti, Tj, Tx arrays */ if (Tj == NULL) { ERR ("j array not present") ; } if (Ti == NULL) { ERR ("i array not present") ; } if (xtype != CHOLMOD_PATTERN && Tx == NULL) { ERR ("x array not present") ; } if (xtype == CHOLMOD_ZOMPLEX && Tz == NULL) { ERR ("z array not present") ; } /* ---------------------------------------------------------------------- */ /* check and print each entry */ /* ---------------------------------------------------------------------- */ init_print = print ; ETC_START (count, 8) ; for (p = 0 ; p < nz ; p++) { ETC (p >= nz-4, count, -1) ; i = Ti [p] ; P4 (" "I8":", p) ; P4 (" "I_8"", i) ; if (i < 0 || i >= nrow) { ERR ("row index out of range") ; } j = Tj [p] ; P4 (" "I_8"", j) ; if (j < 0 || j >= ncol) { ERR ("column index out of range") ; } print_value (print, xtype, Tx, Tz, p, Common) ; P4 ("%s", "\n") ; } /* triplet matrix is valid */ P3 ("%s", " OK\n") ; P4 ("%s", "\n") ; return (TRUE) ; } int CHOLMOD(check_triplet) ( /* ---- input ---- */ cholmod_triplet *T, /* triplet matrix to check */ /* --------------- */ cholmod_common *Common ) { RETURN_IF_NULL_COMMON (FALSE) ; Common->status = CHOLMOD_OK ; return (check_triplet (0, NULL, T, Common)) ; } int CHOLMOD(print_triplet) ( /* ---- input ---- */ cholmod_triplet *T, /* triplet matrix to print */ const char *name, /* printed name of triplet matrix */ /* --------------- */ cholmod_common *Common ) { RETURN_IF_NULL_COMMON (FALSE) ; Common->status = CHOLMOD_OK ; return (check_triplet (Common->print, name, T, Common)) ; } /* ========================================================================== */ /* === CHOLMOD debugging routines =========================================== */ /* ========================================================================== */ #ifndef NDEBUG /* The global variables present only when debugging enabled. */ int CHOLMOD(dump) = 0 ; int CHOLMOD(dump_malloc) = -1 ; /* workspace: no debug routines use workspace in Common */ /* ========================================================================== */ /* === cholmod_dump_init ==================================================== */ /* ========================================================================== */ void CHOLMOD(dump_init) (const char *s, cholmod_common *Common) { int i = 0 ; FILE *f ; f = fopen ("debug", "r") ; CHOLMOD(dump) = 0 ; if (f != NULL) { i = fscanf (f, "%d", &CHOLMOD(dump)) ; fclose (f) ; } PRINT1 (("%s: cholmod_dump_init, D = %d\n", s, CHOLMOD(dump))) ; } /* ========================================================================== */ /* === cholmod_dump_sparse ================================================== */ /* ========================================================================== */ /* returns nnz (diag (A)) or EMPTY if error */ SuiteSparse_long CHOLMOD(dump_sparse) ( cholmod_sparse *A, const char *name, cholmod_common *Common ) { Int *Wi ; SuiteSparse_long nnzdiag ; Int ok ; if (CHOLMOD(dump) < -1) { /* no checks if debug level is -2 or less */ return (0) ; } RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (A, FALSE) ; Wi = malloc (MAX (1, A->nrow) * sizeof (Int)) ; ok = check_sparse (Wi, CHOLMOD(dump), name, A, &nnzdiag, Common) ; if (Wi != NULL) free (Wi) ; return (ok ? nnzdiag : EMPTY) ; } /* ========================================================================== */ /* === cholmod_dump_factor ================================================== */ /* ========================================================================== */ int CHOLMOD(dump_factor) ( cholmod_factor *L, const char *name, cholmod_common *Common ) { Int *Wi ; int ok ; if (CHOLMOD(dump) < -1) { /* no checks if debug level is -2 or less */ return (TRUE) ; } RETURN_IF_NULL_COMMON (FALSE) ; RETURN_IF_NULL (L, FALSE) ; Wi = malloc (MAX (1, L->n) * sizeof (Int)) ; ok = check_factor (Wi, CHOLMOD(dump), name, L, Common) ; if (Wi != NULL) free (Wi) ; return (ok) ; } /* ========================================================================== */ /* === cholmod_dump_perm ==================================================== */ /* ========================================================================== */ int CHOLMOD(dump_perm) ( Int *Perm, size_t len, size_t n, const char *name, cholmod_common *Common ) { Int *Wi ; int ok ; if (CHOLMOD(dump) < -1) { /* no checks if debug level is -2 or less */ return (TRUE) ; } RETURN_IF_NULL_COMMON (FALSE) ; Wi = malloc (MAX (1, n) * sizeof (Int)) ; ok = check_perm (Wi, CHOLMOD(dump), name, Perm, len, n,Common) ; if (Wi != NULL) free (Wi) ; return (ok) ; } /* ========================================================================== */ /* === cholmod_dump_dense =================================================== */ /* ========================================================================== */ int CHOLMOD(dump_dense) ( cholmod_dense *X, const char *name, cholmod_common *Common ) { if (CHOLMOD(dump) < -1) { /* no checks if debug level is -2 or less */ return (TRUE) ; } RETURN_IF_NULL_COMMON (FALSE) ; return (check_dense (CHOLMOD(dump), name, X, Common)) ; } /* ========================================================================== */ /* === cholmod_dump_triplet ================================================= */ /* ========================================================================== */ int CHOLMOD(dump_triplet) ( cholmod_triplet *T, const char *name, cholmod_common *Common ) { if (CHOLMOD(dump) < -1) { /* no checks if debug level is -2 or less */ return (TRUE) ; } RETURN_IF_NULL_COMMON (FALSE) ; return (check_triplet (CHOLMOD(dump), name, T, Common)) ; } /* ========================================================================== */ /* === cholmod_dump_subset ================================================== */ /* ========================================================================== */ int CHOLMOD(dump_subset) ( Int *S, size_t len, size_t n, const char *name, cholmod_common *Common ) { if (CHOLMOD(dump) < -1) { /* no checks if debug level is -2 or less */ return (TRUE) ; } RETURN_IF_NULL_COMMON (FALSE) ; return (check_subset (S, len, n, CHOLMOD(dump), name, Common)) ; } /* ========================================================================== */ /* === cholmod_dump_parent ================================================== */ /* ========================================================================== */ int CHOLMOD(dump_parent) ( Int *Parent, size_t n, const char *name, cholmod_common *Common ) { if (CHOLMOD(dump) < -1) { /* no checks if debug level is -2 or less */ return (TRUE) ; } RETURN_IF_NULL_COMMON (FALSE) ; return (check_parent (Parent, n, CHOLMOD(dump), name, Common)) ; } /* ========================================================================== */ /* === cholmod_dump_real ==================================================== */ /* ========================================================================== */ void CHOLMOD(dump_real) ( const char *name, Real *X, SuiteSparse_long nrow, SuiteSparse_long ncol, int lower, int xentry, cholmod_common *Common ) { /* dump an nrow-by-ncol real dense matrix */ SuiteSparse_long i, j ; double x, z ; if (CHOLMOD(dump) < -1) { /* no checks if debug level is -2 or less */ return ; } PRINT1 (("%s: dump_real, nrow: %ld ncol: %ld lower: %d\n", name, nrow, ncol, lower)) ; for (j = 0 ; j < ncol ; j++) { PRINT2 ((" col %ld\n", j)) ; for (i = 0 ; i < nrow ; i++) { /* X is stored in column-major form */ if (lower && i < j) { PRINT2 ((" %5ld: -", i)) ; } else { x = *X ; PRINT2 ((" %5ld: %e", i, x)) ; if (xentry == 2) { z = *(X+1) ; PRINT2 ((", %e", z)) ; } } PRINT2 (("\n")) ; X += xentry ; } } } /* ========================================================================== */ /* === cholmod_dump_super =================================================== */ /* ========================================================================== */ void CHOLMOD(dump_super) ( SuiteSparse_long s, Int *Super, Int *Lpi, Int *Ls, Int *Lpx, double *Lx, int xentry, cholmod_common *Common ) { Int k1, k2, do_values, psi, psx, nsrow, nscol, psend, ilast, p, i ; if (CHOLMOD(dump) < -1) { /* no checks if debug level is -2 or less */ return ; } k1 = Super [s] ; k2 = Super [s+1] ; nscol = k2 - k1 ; do_values = (Lpx != NULL) && (Lx != NULL) ; psi = Lpi [s] ; psend = Lpi [s+1] ; nsrow = psend - psi ; PRINT1 (("\nSuper %ld, columns "ID" to "ID", "ID" rows "ID" cols\n", s, k1, k2-1, nsrow, nscol)) ; ilast = -1 ; for (p = psi ; p < psend ; p++) { i = Ls [p] ; PRINT2 ((" "ID" : p-psi "ID"\n", i, p-psi)) ; ASSERT (IMPLIES (p-psi < nscol, i == k1 + (p-psi))) ; if (p-psi == nscol-1) PRINT2 (("------\n")) ; ASSERT (i > ilast) ; ilast = i ; } if (do_values) { psx = Lpx [s] ; CHOLMOD(dump_real) ("Supernode", Lx + xentry*psx, nsrow, nscol, TRUE, xentry, Common) ; } } /* ========================================================================== */ /* === cholmod_dump_mem ===================================================== */ /* ========================================================================== */ int CHOLMOD(dump_mem) ( const char *where, SuiteSparse_long should, cholmod_common *Common ) { SuiteSparse_long diff = should - Common->memory_inuse ; if (diff != 0) { PRINT0 (("mem: %-15s peak %10g inuse %10g should %10g\n", where, (double) Common->memory_usage, (double) Common->memory_inuse, (double) should)) ; PRINT0 (("mem: %s diff %ld !\n", where, diff)) ; } return (diff == 0) ; } /* ========================================================================== */ /* === cholmod_dump_partition =============================================== */ /* ========================================================================== */ /* make sure we have a proper separator (for debugging only) * * workspace: none */ int CHOLMOD(dump_partition) ( SuiteSparse_long n, Int *Cp, Int *Ci, Int *Cnw, Int *Part, SuiteSparse_long sepsize, cholmod_common *Common ) { Int chek [3], which, ok, i, j, p ; PRINT1 (("bisect sepsize %ld\n", sepsize)) ; ok = TRUE ; chek [0] = 0 ; chek [1] = 0 ; chek [2] = 0 ; for (j = 0 ; j < n ; j++) { PRINT2 (("--------j "ID" in part "ID" nw "ID"\n", j, Part [j], Cnw[j])); which = Part [j] ; for (p = Cp [j] ; p < Cp [j+1] ; p++) { i = Ci [p] ; PRINT3 (("i "ID", part "ID"\n", i, Part [i])) ; if (which == 0) { if (Part [i] == 1) { PRINT0 (("Error! "ID" "ID"\n", i, j)) ; ok = FALSE ; } } else if (which == 1) { if (Part [i] == 0) { PRINT0 (("Error! "ID" "ID"\n", i, j)) ; ok = FALSE ; } } } if (which < 0 || which > 2) { PRINT0 (("Part out of range\n")) ; ok = FALSE ; } chek [which] += Cnw [j] ; } PRINT1 (("sepsize %ld check "ID" "ID" "ID"\n", sepsize, chek[0], chek[1],chek[2])); if (sepsize != chek[2]) { PRINT0 (("mismatch!\n")) ; ok = FALSE ; } return (ok) ; } /* ========================================================================== */ /* === cholmod_dump_work ==================================================== */ /* ========================================================================== */ int CHOLMOD(dump_work) (int flag, int head, SuiteSparse_long wsize, cholmod_common *Common) { double *W ; Int *Flag, *Head ; Int k, nrow, mark ; if (CHOLMOD(dump) < -1) { /* no checks if debug level is -2 or less */ return (TRUE) ; } RETURN_IF_NULL_COMMON (FALSE) ; nrow = Common->nrow ; Flag = Common->Flag ; Head = Common->Head ; W = Common->Xwork ; mark = Common->mark ; if (wsize < 0) { /* check all of Xwork */ wsize = Common->xworksize ; } else { /* check on the first wsize doubles in Xwork */ wsize = MIN (wsize, (Int) (Common->xworksize)) ; } if (flag) { for (k = 0 ; k < nrow ; k++) { if (Flag [k] >= mark) { PRINT0 (("Flag invalid, Flag ["ID"] = "ID", mark = "ID"\n", k, Flag [k], mark)) ; ASSERT (0) ; return (FALSE) ; } } } if (head) { for (k = 0 ; k < nrow ; k++) { if (Head [k] != EMPTY) { PRINT0 (("Head invalid, Head ["ID"] = "ID"\n", k, Head [k])) ; ASSERT (0) ; return (FALSE) ; } } } for (k = 0 ; k < wsize ; k++) { if (W [k] != 0.) { PRINT0 (("W invalid, W ["ID"] = %g\n", k, W [k])) ; ASSERT (0) ; return (FALSE) ; } } return (TRUE) ; } #endif #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Check/cholmod_read.c0000644000076500000240000011740113524616144026276 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Check/cholmod_read =================================================== */ /* ========================================================================== */ /* ----------------------------------------------------------------------------- * CHOLMOD/Check Module. Copyright (C) 2005-2006, Timothy A. Davis. * The CHOLMOD/Check Module is licensed under Version 2.1 of the GNU * Lesser General Public License. See lesser.txt for a text of the license. * CHOLMOD is also available under other licenses; contact authors for details. * -------------------------------------------------------------------------- */ /* Read a sparse matrix in triplet or dense form. A triplet matrix can be * returned as compressed-column sparse matrix. The file format is compatible * with all variations of the Matrix Market "coordinate" and "array" format * (http://www.nist.gov/MatrixMarket). The format supported by these routines * also allow other formats, where the Matrix Market header is optional. * * Although the Matrix Market header is optional, I recommend that users stick * with the strict Matrix Market format. The optional format appears here to * support the reading of symmetric matrices stored with just their upper * triangular parts present, for testing and development of the A->stype > 0 * format in CHOLMOD. That format is not included in the Matrix Market format. * * If the first line of the file starts with %%MatrixMarket, then it is * interpretted as a file in Matrix Market format. This line must have * the following format: * * %%MatrixMarket matrix * * is one of: coordinate or array. The former is a sparse matrix in * triplet form. The latter is a dense matrix in column-major form. * * is one of: real, complex, pattern, or integer. * The functions here convert the "integer" and "pattern" types to real. * * is one of: general, hermitian, symmetric, or skew-symmetric * * The strings are case-insensitive. Only the first character is * significant (or the first two for skew-symmetric). * * is ignored for all matrices; the actual type (real, complex, * or pattern) is inferred from the number of tokens in each line of the * file. For a "coordinate" matrix: 2: pattern, 3: real, 4: complex; for * a dense "array" matrix: 1: real, 2: complex. This is compatible with * the Matrix Market format, since pattern matrices must have two tokens * per line, real matrices must have 3, and complex matrices must have 4. * A storage of "general" implies an stype of zero (see below). * "symmetric" and "hermitian" imply an stype of -1. Skew-symmetric and * complex symmetric matrices are always returned with both upper and lower * triangular parts present, with an stype of zero, since CHOLMOD does not * have a method for representing skew-symmetric and complex symmetric * matrices. Real symmetric and complex Hermitian matrices may optionally * be returned with both parts present. * * Any other lines starting with "%" are treated as comments, and are ignored. * Blank lines are ignored. The Matrix Market header is optional in this * routine (it is not optional in the Matrix Market format). * * Note that complex matrices are always returned in CHOLMOD_COMPLEX format, * not CHOLMOD_ZOMPLEX. * * ----------------------------------------------------------------------------- * Triplet matrices: * ----------------------------------------------------------------------------- * * The first data line of a triplet matrix contains 3 or 4 integers: * * nrow ncol nnz stype * * where stype is optional (stype does not appear in the Matrix Market format). * The matrix is nrow-by-ncol. The following nnz lines (excluding comments * and blank lines) each contain a single entry. Duplicates are permitted, * and are summed in the output matrix. * * The stype is first derived from the Matrix Market header. If the stype * appears as the fourth integer in the first data line, it is determined from * that line. * * If stype is present, it denotes the storage format for the matrix. * stype = 0 denotes an unsymmetric matrix (same as Matrix Market "general"). * stype = -1 denotes a real symmetric or complex Hermitian matrix whose lower * triangular entries are stored. Entries may be present in the upper * triangular part, but these are ignored (same as Matrix Market * "real symmetric" and "complex Hermitian"). * stype = 1 denotes a real symmetric or complex Hermitian matrix whose upper * triangular entries are stored. Entries may be present in the lower * triangular part, but these are ignored. This option is not present * in the Matrix Market format. * * If stype is not present (no Matrix Market header and not in the first data * line) it is inferred from the rest of the data. If the matrix is * rectangular, or has entries in both the upper and lower triangular parts, * then it is assumed to be unsymmetric (stype=0). If only entries in the * lower triangular part are present, the matrix is assumed to have stype = -1. * If only entries in the upper triangular part are present, the matrix is * assumed to have stype = 1. * * After the first data line (with nrow, ncol, nnz, and optionally stype), * each nonzero consists of one line with 2, 3, or 4 entries. All lines must * have the same number of entries. The first two entries are the row and * column indices of the nonzero. If 3 entries are present, the 3rd entry is * the numerical value, and the matrix is real. If 4 entries are present, * the 3rd and 4th entries in the line are the real and imaginary parts of * a complex value. * * The matrix can be either 0-based or 1-based. It is first assumed to be * one-based (all matrices in the Matrix Market are one-based), with row indices * in the range 1 to ncol and column indices in the range 1 to nrow. If a row * or column index of zero is found, the matrix is assumed to be zero-based * (with row indices in the range 0 to ncol-1 and column indices in the range 0 * to nrow-1). * * If Common->prefer_binary is set to its default value of FALSE, then * for symmetric pattern-only matrices, the kth diagonal (if present) is set to * one plus the degree of the row/column k, and the off-diagonal entries are set * to -1. A symmetric pattern-only matrix with a zero-free diagonal is thus * converted into a symmetric positive definite matrix. All entries are set to * one for an unsymmetric pattern-only matrix. This differs from the * Matrix Market format (A = mmread ('file') returns a binary pattern for A for * symmetric pattern-only matrices). If Common->prefer_binary is TRUE, then * this function returns a binary matrix (just like mmread('file')). * * ----------------------------------------------------------------------------- * Dense matrices: * ----------------------------------------------------------------------------- * * A dense matrix is specified by the Matrix Market "array" format. The * Matrix Market header is optional; if not present, the matrix is assumed to * be in the Matrix Market "general" format. The first data line contains just * two integers: * * nrow ncol * * The can be real, integer, or complex (not pattern). These functions * convert an integer type to real. The entries in the matrix are stored in * column-major format, with one line per entry. Two entries are present in * each line for complex matrices, one for real and integer matrices. In * rectangular and unsymmetric matrices, all entries are present. For real * symmetric or complex Hermitian matrices, only entries in the lower triangular * part appear. For skew-symmetric matrices, only entries in the strictly * lower triangular part appear. * * Since CHOLMOD does not have a data structure for presenting dense symmetric/ * Hermitian matrices, these functions always return a dense matrix in its * general form, with both upper and lower parts present. */ #ifndef NCHECK #include "cholmod_internal.h" #include "cholmod_check.h" #include #include /* The MatrixMarket format specificies a maximum line length of 1024 */ #define MAXLINE 1030 /* ========================================================================== */ /* === get_line ============================================================= */ /* ========================================================================== */ /* Read one line of the file, return TRUE if successful, FALSE if EOF. */ static int get_line (FILE *f, char *buf) { buf [0] = '\0' ; buf [1] = '\0' ; buf [MAXLINE] = '\0' ; return (fgets (buf, MAXLINE, f) != NULL) ; } /* ========================================================================== */ /* === fix_inf ============================================================== */ /* ========================================================================== */ /* Replace huge values with +/- Inf's, since scanf and printf don't deal * with Inf's properly. */ static double fix_inf (double x) { if ((x >= HUGE_DOUBLE) || (x <= -HUGE_DOUBLE)) { /* treat this as +/- Inf (assume 2*x leads to overflow) */ x = 2*x ; } return (x) ; } /* ========================================================================== */ /* === is_blank_line ======================================================== */ /* ========================================================================== */ /* TRUE if s is a blank line or comment, FALSE otherwise */ static int is_blank_line ( char *s ) { int c, k ; if (s [0] == '%') { /* a comment line */ return (TRUE) ; } for (k = 0 ; k <= MAXLINE ; k++) { c = s [k] ; if (c == '\0') { /* end of line */ break ; } if (!isspace (c)) { /* non-space character */ return (FALSE) ; } } return (TRUE) ; } /* ========================================================================== */ /* === read_header ========================================================== */ /* ========================================================================== */ /* Read the header. This consists of zero or more comment lines (blank, or * starting with a "%" in the first column), followed by a single data line * containing up to four numerical values. * * The first line may optionally be a Matrix Market header line, of the form * * %%MatrixMarket matrix * * The first data line of a sparse matrix in triplet form consists of 3 or 4 * numerical values: * * nrow ncol nnz stype * * where stype is optional (it does not appear in the Matrix Market file * format). The first line of a dense matrix in column-major form consists of * two numerical values: * * nrow ncol * * The stype of the matrix is determine either from the Matrix Market header, * or (optionally) from the first data line. stypes of 0 to -3 directly * correlate with the Matrix Market format; stype = 1 is an extension to that * format. * * 999: unknown (will be inferred from the data) * 1: real symmetric or complex Hermitian with upper part stored * (not in the Matrix Market format) * 0: unsymmetric (same as Matrix Market "general") * -1: real symmetric or complex Hermitian, with lower part stored * (Matrix Market "real symmetric" or "complex hermitian") * -2: real or complex skew symmetric (lower part stored, can only be * specified by Matrix Market header) * -3: complex symmetric (lower part stored) * specified by Matrix Market header) * * The Matrix Market header is optional. If stype appears in the first data * line, it is determine by that data line. Otherwise, if the Matrix Market * header appears, stype is determined from that header. If stype does not * appear, it is set to "unknown" (999). */ #define STYPE_UNKNOWN 999 #define STYPE_SYMMETRIC_UPPER 1 #define STYPE_UNSYMMETRIC 0 #define STYPE_SYMMETRIC_LOWER -1 #define STYPE_SKEW_SYMMETRIC -2 #define STYPE_COMPLEX_SYMMETRIC_LOWER -3 static int read_header /* returns TRUE if successful, FALSE on error */ ( /* ---- input ---- */ FILE *f, /* file to read from */ /* ---- output --- */ char *buf, /* a character array of size MAXLINE+1 */ int *mtype, /* CHOLMOD_TRIPLET or CHOLMOD_DENSE */ size_t *nrow, /* number of rows in the matrix */ size_t *ncol, /* number of columns in the matrix */ size_t *nnz, /* number of entries in a triplet matrix (0 for dense)*/ int *stype /* stype (see above) */ ) { char *p ; int first = TRUE, got_mm_header = FALSE, c, c2, is_complex, nitems ; double l1, l2, l3, l4 ; *mtype = CHOLMOD_TRIPLET ; *nrow = 0 ; *ncol = 0 ; *nnz = 0 ; *stype = STYPE_UNKNOWN ; for ( ; ; ) { /* ------------------------------------------------------------------ */ /* get the next line */ /* ------------------------------------------------------------------ */ if (!get_line (f, buf)) { /* premature end of file */ return (FALSE) ; } if (first && (strncmp (buf, "%%MatrixMarket", 14) == 0)) { /* -------------------------------------------------------------- */ /* read a Matrix Market header */ /* -------------------------------------------------------------- */ got_mm_header = TRUE ; p = buf ; /* -------------------------------------------------------------- */ /* get "matrix" token */ /* -------------------------------------------------------------- */ while (*p && !isspace (*p)) p++ ; while (*p && isspace (*p)) p++ ; c = tolower (*p) ; if (c != 'm') { /* bad format */ return (FALSE) ; } /* -------------------------------------------------------------- */ /* get the fmt token ("coord" or "array") */ /* -------------------------------------------------------------- */ while (*p && !isspace (*p)) p++ ; while (*p && isspace (*p)) p++ ; c = tolower (*p) ; if (c == 'c') { *mtype = CHOLMOD_TRIPLET ; } else if (c == 'a') { *mtype = CHOLMOD_DENSE ; } else { /* bad format, neither "coordinate" nor "array" */ return (FALSE) ; } /* -------------------------------------------------------------- */ /* get type token (real, pattern, complex, integer) */ /* -------------------------------------------------------------- */ while (*p && !isspace (*p)) p++ ; while (*p && isspace (*p)) p++ ; c = tolower (*p) ; if (!(c == 'r' || c == 'p' || c == 'c' || c == 'i')) { /* bad format */ return (FALSE) ; } is_complex = (c == 'c') ; /* -------------------------------------------------------------- */ /* get storage token (general, hermitian, symmetric, skew) */ /* -------------------------------------------------------------- */ while (*p && !isspace (*p)) p++ ; while (*p && isspace (*p)) p++ ; c = tolower (*p) ; c2 = tolower (*(p+1)) ; if (c == 'g') { /* "general" storage (unsymmetric matrix), both parts present */ *stype = STYPE_UNSYMMETRIC ; } else if (c == 's' && c2 == 'y') { /* "symmetric" */ if (is_complex) { /* complex symmetric, lower triangular part present */ *stype = STYPE_COMPLEX_SYMMETRIC_LOWER ; } else { /* real symmetric, lower triangular part present */ *stype = STYPE_SYMMETRIC_LOWER ; } } else if (c == 'h') { /* "hermitian" matrix, lower triangular part present */ *stype = STYPE_SYMMETRIC_LOWER ; } else if (c == 's' && c2 == 'k') { /* "skew-symmetric" (real or complex), lower part present */ *stype = STYPE_SKEW_SYMMETRIC ; } else { /* bad format */ return (FALSE) ; } } else if (is_blank_line (buf)) { /* -------------------------------------------------------------- */ /* blank line or comment line */ /* -------------------------------------------------------------- */ continue ; } else { /* -------------------------------------------------------------- */ /* read the first data line and return */ /* -------------------------------------------------------------- */ /* format: nrow ncol nnz stype */ l1 = EMPTY ; l2 = EMPTY ; l3 = 0 ; l4 = 0 ; nitems = sscanf (buf, "%lg %lg %lg %lg\n", &l1, &l2, &l3, &l4) ; if (nitems < 2 || nitems > 4 || l1 > Int_max || l2 > Int_max) { /* invalid matrix */ return (FALSE) ; } *nrow = l1 ; *ncol = l2 ; if (nitems == 2) { /* a dense matrix */ if (!got_mm_header) { *mtype = CHOLMOD_DENSE ; *stype = STYPE_UNSYMMETRIC ; } } if (nitems == 3 || nitems == 4) { /* a sparse triplet matrix */ *nnz = l3 ; if (!got_mm_header) { *mtype = CHOLMOD_TRIPLET ; } } if (nitems == 4) { /* an stype specified here can only be 1, 0, or -1 */ if (l4 < 0) { *stype = STYPE_SYMMETRIC_LOWER ; } else if (l4 > 0) { *stype = STYPE_SYMMETRIC_UPPER ; } else { *stype = STYPE_UNSYMMETRIC ; } } if (*nrow != *ncol) { /* a rectangular matrix must be unsymmetric */ *stype = STYPE_UNSYMMETRIC ; } return (TRUE) ; } first = FALSE ; } } /* ========================================================================== */ /* === read_triplet ========================================================= */ /* ========================================================================== */ /* Header has already been read in, including first line (nrow ncol nnz stype). * Read the triplets. */ static cholmod_triplet *read_triplet ( /* ---- input ---- */ FILE *f, /* file to read from, must already be open */ size_t nrow, /* number of rows */ size_t ncol, /* number of columns */ size_t nnz, /* number of triplets in file to read */ int stype, /* stype from header, or "unknown" */ int prefer_unsym, /* if TRUE, always return T->stype of zero */ /* ---- workspace */ char *buf, /* of size MAXLINE+1 */ /* --------------- */ cholmod_common *Common ) { double x, z ; double *Tx ; Int *Ti, *Tj, *Rdeg, *Cdeg ; cholmod_triplet *T ; double l1, l2 ; Int nitems, xtype, unknown, k, nshould, is_lower, is_upper, one_based, i, j, imax, jmax, skew_symmetric, p, complex_symmetric ; size_t s, nnz2, extra ; int ok = TRUE ; /* ---------------------------------------------------------------------- */ /* quick return for empty matrix */ /* ---------------------------------------------------------------------- */ if (nrow == 0 || ncol == 0 || nnz == 0) { /* return an empty matrix */ return (CHOLMOD(allocate_triplet) (nrow, ncol, 0, 0, CHOLMOD_REAL, Common)) ; } /* ---------------------------------------------------------------------- */ /* special stype cases: unknown, skew symmetric, and complex symmetric */ /* ---------------------------------------------------------------------- */ unknown = (stype == STYPE_UNKNOWN) ; skew_symmetric = (stype == STYPE_SKEW_SYMMETRIC) ; complex_symmetric = (stype == STYPE_COMPLEX_SYMMETRIC_LOWER) ; extra = 0 ; if (stype < STYPE_SYMMETRIC_LOWER || (prefer_unsym && stype != STYPE_UNSYMMETRIC)) { /* 999: unknown might be converted to unsymmetric */ /* 1: symmetric upper converted to unsym. if prefer_unsym is TRUE */ /* -1: symmetric lower converted to unsym. if prefer_unsym is TRUE */ /* -2: real or complex skew symmetric converted to unsymmetric */ /* -3: complex symmetric converted to unsymmetric */ stype = STYPE_UNSYMMETRIC ; extra = nnz ; } nnz2 = CHOLMOD(add_size_t) (nnz, extra, &ok) ; /* ---------------------------------------------------------------------- */ /* allocate workspace */ /* ---------------------------------------------------------------------- */ /* s = nrow + ncol */ s = CHOLMOD(add_size_t) (nrow, ncol, &ok) ; if (!ok || nrow > Int_max || ncol > Int_max || nnz > Int_max) { ERROR (CHOLMOD_TOO_LARGE, "problem too large") ; return (NULL) ; } CHOLMOD(allocate_work) (0, s, 0, Common) ; Rdeg = Common->Iwork ; /* size nrow */ Cdeg = Rdeg + nrow ; /* size ncol */ /* ---------------------------------------------------------------------- */ /* read the triplets */ /* ---------------------------------------------------------------------- */ is_lower = TRUE ; is_upper = TRUE ; one_based = TRUE ; imax = 0 ; jmax = 0 ; Tx = NULL ; Ti = NULL ; Tj = NULL ; xtype = 999 ; nshould = 0 ; for (k = 0 ; k < (Int) nnz ; k++) { /* ------------------------------------------------------------------ */ /* get the next triplet, skipping blank lines and comment lines */ /* ------------------------------------------------------------------ */ l1 = EMPTY ; l2 = EMPTY ; x = 0 ; z = 0 ; for ( ; ; ) { if (!get_line (f, buf)) { /* premature end of file - not enough triplets read in */ ERROR (CHOLMOD_INVALID, "premature EOF") ; return (NULL) ; } if (is_blank_line (buf)) { /* blank line or comment */ continue ; } nitems = sscanf (buf, "%lg %lg %lg %lg\n", &l1, &l2, &x, &z) ; x = fix_inf (x) ; z = fix_inf (z) ; break ; } nitems = (nitems == EOF) ? 0 : nitems ; i = l1 ; j = l2 ; /* ------------------------------------------------------------------ */ /* for first triplet: determine type and allocate triplet matrix */ /* ------------------------------------------------------------------ */ if (k == 0) { if (nitems < 2 || nitems > 4) { /* invalid matrix */ ERROR (CHOLMOD_INVALID, "invalid format") ; return (NULL) ; } else if (nitems == 2) { /* this will be converted into a real matrix later */ xtype = CHOLMOD_PATTERN ; } else if (nitems == 3) { xtype = CHOLMOD_REAL ; } else if (nitems == 4) { xtype = CHOLMOD_COMPLEX ; } /* the rest of the lines should have the same number of entries */ nshould = nitems ; /* allocate triplet matrix */ T = CHOLMOD(allocate_triplet) (nrow, ncol, nnz2, stype, (xtype == CHOLMOD_PATTERN ? CHOLMOD_REAL : xtype), Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ return (NULL) ; } Ti = T->i ; Tj = T->j ; Tx = T->x ; T->nnz = nnz ; } /* ------------------------------------------------------------------ */ /* save the entry in the triplet matrix */ /* ------------------------------------------------------------------ */ if (nitems != nshould || i < 0 || j < 0) { /* wrong format, premature end-of-file, or negative indices */ CHOLMOD(free_triplet) (&T, Common) ; ERROR (CHOLMOD_INVALID, "invalid matrix file") ; return (NULL) ; } Ti [k] = i ; Tj [k] = j ; if (i < j) { /* this entry is in the upper triangular part */ is_lower = FALSE ; } if (i > j) { /* this entry is in the lower triangular part */ is_upper = FALSE ; } if (xtype == CHOLMOD_REAL) { Tx [k] = x ; } else if (xtype == CHOLMOD_COMPLEX) { Tx [2*k ] = x ; /* real part */ Tx [2*k+1] = z ; /* imaginary part */ } if (i == 0 || j == 0) { one_based = FALSE ; } imax = MAX (i, imax) ; jmax = MAX (j, jmax) ; } /* ---------------------------------------------------------------------- */ /* convert to zero-based */ /* ---------------------------------------------------------------------- */ if (one_based) { /* input matrix is one-based; convert matrix to zero-based */ for (k = 0 ; k < (Int) nnz ; k++) { Ti [k]-- ; Tj [k]-- ; } } if (one_based ? (imax > (Int) nrow || jmax > (Int) ncol) : (imax >= (Int) nrow || jmax >= (Int) ncol)) { /* indices out of range */ CHOLMOD(free_triplet) (&T, Common) ; ERROR (CHOLMOD_INVALID, "indices out of range") ; return (NULL) ; } /* ---------------------------------------------------------------------- */ /* determine the stype, if not yet known */ /* ---------------------------------------------------------------------- */ if (unknown) { if (is_lower && is_upper) { /* diagonal matrix, symmetric with upper part present */ stype = STYPE_SYMMETRIC_UPPER ; } else if (is_lower && !is_upper) { /* symmetric, lower triangular part present */ stype = STYPE_SYMMETRIC_LOWER ; } else if (!is_lower && is_upper) { /* symmetric, upper triangular part present */ stype = STYPE_SYMMETRIC_UPPER ; } else { /* unsymmetric */ stype = STYPE_UNSYMMETRIC ; extra = 0 ; } } /* ---------------------------------------------------------------------- */ /* add the remainder of symmetric, skew-symmetric or Hermitian matrices */ /* ---------------------------------------------------------------------- */ /* note that this step is not done for real symmetric or complex Hermitian * matrices, unless prefer_unsym is TRUE */ if (extra > 0) { p = nnz ; for (k = 0 ; k < (Int) nnz ; k++) { i = Ti [k] ; j = Tj [k] ; if (i != j) { Ti [p] = j ; Tj [p] = i ; if (xtype == CHOLMOD_REAL) { if (skew_symmetric) { Tx [p] = -Tx [k] ; } else { Tx [p] = Tx [k] ; } } else if (xtype == CHOLMOD_COMPLEX) { if (skew_symmetric) { Tx [2*p ] = -Tx [2*k ] ; Tx [2*p+1] = -Tx [2*k+1] ; } else if (complex_symmetric) { Tx [2*p ] = Tx [2*k ] ; Tx [2*p+1] = Tx [2*k+1] ; } else /* Hermitian */ { Tx [2*p ] = Tx [2*k ] ; Tx [2*p+1] = -Tx [2*k+1] ; } } p++ ; } } T->nnz = p ; nnz = p ; } T->stype = stype ; /* ---------------------------------------------------------------------- */ /* create values for a pattern-only matrix */ /* ---------------------------------------------------------------------- */ if (xtype == CHOLMOD_PATTERN) { if (stype == STYPE_UNSYMMETRIC || Common->prefer_binary) { /* unsymmetric case, or binary case */ for (k = 0 ; k < (Int) nnz ; k++) { Tx [k] = 1 ; } } else { /* compute the row and columm degrees (excluding the diagonal) */ for (i = 0 ; i < (Int) nrow ; i++) { Rdeg [i] = 0 ; } for (j = 0 ; j < (Int) ncol ; j++) { Cdeg [j] = 0 ; } for (k = 0 ; k < (Int) nnz ; k++) { i = Ti [k] ; j = Tj [k] ; if ((stype < 0 && i > j) || (stype > 0 && i < j)) { /* both a(i,j) and a(j,i) appear in the matrix */ Rdeg [i]++ ; Cdeg [j]++ ; Rdeg [j]++ ; Cdeg [i]++ ; } } /* assign the numerical values */ for (k = 0 ; k < (Int) nnz ; k++) { i = Ti [k] ; j = Tj [k] ; Tx [k] = (i == j) ? (1 + MAX (Rdeg [i], Cdeg [j])) : (-1) ; } } } /* ---------------------------------------------------------------------- */ /* return the new triplet matrix */ /* ---------------------------------------------------------------------- */ return (T) ; } /* ========================================================================== */ /* === read_dense =========================================================== */ /* ========================================================================== */ /* Header has already been read in, including first line (nrow ncol). * Read a dense matrix. */ static cholmod_dense *read_dense ( /* ---- input ---- */ FILE *f, /* file to read from, must already be open */ size_t nrow, /* number of rows */ size_t ncol, /* number of columns */ int stype, /* stype from header */ /* ---- workspace */ char *buf, /* of size MAXLINE+1 */ /* --------------- */ cholmod_common *Common ) { double x, z ; double *Xx = NULL ; cholmod_dense *X ; Int nitems, xtype = -1, nshould = 0, i, j, k, kup, first ; /* ---------------------------------------------------------------------- */ /* quick return for empty matrix */ /* ---------------------------------------------------------------------- */ if (nrow == 0 || ncol == 0) { /* return an empty dense matrix */ return (CHOLMOD(zeros) (nrow, ncol, CHOLMOD_REAL, Common)) ; } /* ---------------------------------------------------------------------- */ /* read the entries */ /* ---------------------------------------------------------------------- */ first = TRUE ; for (j = 0 ; j < (Int) ncol ; j++) { /* ------------------------------------------------------------------ */ /* get the row index of the first entry in the file for column j */ /* ------------------------------------------------------------------ */ if (stype == STYPE_UNSYMMETRIC) { i = 0 ; } else if (stype == STYPE_SKEW_SYMMETRIC) { i = j+1 ; } else /* real symmetric or complex Hermitian lower */ { i = j ; } /* ------------------------------------------------------------------ */ /* get column j */ /* ------------------------------------------------------------------ */ for ( ; i < (Int) nrow ; i++) { /* -------------------------------------------------------------- */ /* get the next entry, skipping blank lines and comment lines */ /* -------------------------------------------------------------- */ x = 0 ; z = 0 ; for ( ; ; ) { if (!get_line (f, buf)) { /* premature end of file - not enough entries read in */ ERROR (CHOLMOD_INVALID, "premature EOF") ; return (NULL) ; } if (is_blank_line (buf)) { /* blank line or comment */ continue ; } nitems = sscanf (buf, "%lg %lg\n", &x, &z) ; x = fix_inf (x) ; z = fix_inf (z) ; break ; } nitems = (nitems == EOF) ? 0 : nitems ; /* -------------------------------------------------------------- */ /* for first entry: determine type and allocate dense matrix */ /* -------------------------------------------------------------- */ if (first) { first = FALSE ; if (nitems < 1 || nitems > 2) { /* invalid matrix */ ERROR (CHOLMOD_INVALID, "invalid format") ; return (NULL) ; } else if (nitems == 1) { /* a real matrix */ xtype = CHOLMOD_REAL ; } else if (nitems == 2) { /* a complex matrix */ xtype = CHOLMOD_COMPLEX ; } /* the rest of the lines should have same number of entries */ nshould = nitems ; /* allocate the result */ X = CHOLMOD(zeros) (nrow, ncol, xtype, Common) ; if (Common->status < CHOLMOD_OK) { /* out of memory */ return (NULL) ; } Xx = X->x ; } /* -------------------------------------------------------------- */ /* save the entry in the dense matrix */ /* -------------------------------------------------------------- */ if (nitems != nshould) { /* wrong format or premature end-of-file */ CHOLMOD(free_dense) (&X, Common) ; ERROR (CHOLMOD_INVALID, "invalid matrix file") ; return (NULL) ; } k = i + j*nrow ; kup = j + i*nrow ; if (xtype == CHOLMOD_REAL) { /* real matrix */ Xx [k] = x ; if (k != kup) { if (stype == STYPE_SYMMETRIC_LOWER) { /* real symmetric matrix */ Xx [kup] = x ; } else if (stype == STYPE_SKEW_SYMMETRIC) { /* real skew symmetric matrix */ Xx [kup] = -x ; } } } else if (xtype == CHOLMOD_COMPLEX) { Xx [2*k ] = x ; /* real part */ Xx [2*k+1] = z ; /* imaginary part */ if (k != kup) { if (stype == STYPE_SYMMETRIC_LOWER) { /* complex Hermitian */ Xx [2*kup ] = x ; /* real part */ Xx [2*kup+1] = -z ; /* imaginary part */ } else if (stype == STYPE_SKEW_SYMMETRIC) { /* complex skew symmetric */ Xx [2*kup ] = -x ; /* real part */ Xx [2*kup+1] = -z ; /* imaginary part */ } if (stype == STYPE_COMPLEX_SYMMETRIC_LOWER) { /* complex symmetric */ Xx [2*kup ] = x ; /* real part */ Xx [2*kup+1] = z ; /* imaginary part */ } } } } } /* ---------------------------------------------------------------------- */ /* return the new dense matrix */ /* ---------------------------------------------------------------------- */ return (X) ; } /* ========================================================================== */ /* === cholmod_read_triplet ================================================= */ /* ========================================================================== */ /* Read in a triplet matrix from a file. */ cholmod_triplet *CHOLMOD(read_triplet) ( /* ---- input ---- */ FILE *f, /* file to read from, must already be open */ /* --------------- */ cholmod_common *Common ) { char buf [MAXLINE+1] ; size_t nrow, ncol, nnz ; int stype, mtype ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; RETURN_IF_NULL (f, NULL) ; Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* read the header and first data line */ /* ---------------------------------------------------------------------- */ if (!read_header (f, buf, &mtype, &nrow, &ncol, &nnz, &stype) || mtype != CHOLMOD_TRIPLET) { /* invalid matrix - this function can only read in a triplet matrix */ ERROR (CHOLMOD_INVALID, "invalid format") ; return (NULL) ; } /* ---------------------------------------------------------------------- */ /* read the triplet matrix */ /* ---------------------------------------------------------------------- */ return (read_triplet (f, nrow, ncol, nnz, stype, FALSE, buf, Common)) ; } /* ========================================================================== */ /* === cholmod_read_sparse ================================================== */ /* ========================================================================== */ /* Read a sparse matrix from a file. See cholmod_read_triplet for a discussion * of the file format. * * If Common->prefer_upper is TRUE (the default case), a symmetric matrix is * returned stored in upper-triangular form (A->stype == 1). */ cholmod_sparse *CHOLMOD(read_sparse) ( /* ---- input ---- */ FILE *f, /* file to read from, must already be open */ /* --------------- */ cholmod_common *Common ) { cholmod_sparse *A, *A2 ; cholmod_triplet *T ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; RETURN_IF_NULL (f, NULL) ; Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* convert to a sparse matrix in compressed-column form */ /* ---------------------------------------------------------------------- */ T = CHOLMOD(read_triplet) (f, Common) ; A = CHOLMOD(triplet_to_sparse) (T, 0, Common) ; CHOLMOD(free_triplet) (&T, Common) ; if (Common->prefer_upper && A != NULL && A->stype == -1) { /* A=A' */ A2 = CHOLMOD(transpose) (A, 2, Common) ; CHOLMOD(free_sparse) (&A, Common) ; A = A2 ; } return (A) ; } /* ========================================================================== */ /* === cholmod_read_dense =================================================== */ /* ========================================================================== */ /* Read a dense matrix from a file. */ cholmod_dense *CHOLMOD(read_dense) ( /* ---- input ---- */ FILE *f, /* file to read from, must already be open */ /* --------------- */ cholmod_common *Common ) { char buf [MAXLINE+1] ; size_t nrow, ncol, nnz ; int stype, mtype ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; RETURN_IF_NULL (f, NULL) ; Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* read the header and first data line */ /* ---------------------------------------------------------------------- */ if (!read_header (f, buf, &mtype, &nrow, &ncol, &nnz, &stype) || mtype != CHOLMOD_DENSE) { /* invalid matrix - this function can only read in a dense matrix */ ERROR (CHOLMOD_INVALID, "invalid format") ; return (NULL) ; } /* ---------------------------------------------------------------------- */ /* read the dense matrix */ /* ---------------------------------------------------------------------- */ return (read_dense (f, nrow, ncol, stype, buf, Common)) ; } /* ========================================================================== */ /* === cholmod_read_matrix ================================================== */ /* ========================================================================== */ /* Read a triplet matrix, sparse matrix or a dense matrix from a file. Returns * a void pointer to either a cholmod_triplet, cholmod_sparse, or cholmod_dense * object. The type of object is passed back to the caller as the mtype * argument. */ void *CHOLMOD(read_matrix) ( /* ---- input ---- */ FILE *f, /* file to read from, must already be open */ int prefer, /* If 0, a sparse matrix is always return as a * cholmod_triplet form. It can have any stype * (symmetric-lower, unsymmetric, or * symmetric-upper). * If 1, a sparse matrix is returned as an unsymmetric * cholmod_sparse form (A->stype == 0), with both * upper and lower triangular parts present. * This is what the MATLAB mread mexFunction does, * since MATLAB does not have an stype. * If 2, a sparse matrix is returned with an stype of 0 * or 1 (unsymmetric, or symmetric with upper part * stored). * This argument has no effect for dense matrices. */ /* ---- output---- */ int *mtype, /* CHOLMOD_TRIPLET, CHOLMOD_SPARSE or CHOLMOD_DENSE */ /* --------------- */ cholmod_common *Common ) { void *G = NULL ; cholmod_sparse *A, *A2 ; cholmod_triplet *T ; char buf [MAXLINE+1] ; size_t nrow, ncol, nnz ; int stype ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (NULL) ; RETURN_IF_NULL (f, NULL) ; RETURN_IF_NULL (mtype, NULL) ; Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* read the header to determine the mtype */ /* ---------------------------------------------------------------------- */ if (!read_header (f, buf, mtype, &nrow, &ncol, &nnz, &stype)) { /* invalid matrix */ ERROR (CHOLMOD_INVALID, "invalid format") ; return (NULL) ; } /* ---------------------------------------------------------------------- */ /* read a matrix */ /* ---------------------------------------------------------------------- */ if (*mtype == CHOLMOD_TRIPLET) { /* read in the triplet matrix, converting to unsymmetric format if * prefer == 1 */ T = read_triplet (f, nrow, ncol, nnz, stype, prefer == 1, buf, Common) ; if (prefer == 0) { /* return matrix in its original triplet form */ G = T ; } else { /* return matrix in a compressed-column form */ A = CHOLMOD(triplet_to_sparse) (T, 0, Common) ; CHOLMOD(free_triplet) (&T, Common) ; if (A != NULL && prefer == 2 && A->stype == -1) { /* convert A from symmetric-lower to symmetric-upper */ A2 = CHOLMOD(transpose) (A, 2, Common) ; CHOLMOD(free_sparse) (&A, Common) ; A = A2 ; } *mtype = CHOLMOD_SPARSE ; G = A ; } } else if (*mtype == CHOLMOD_DENSE) { /* return a dense matrix */ G = read_dense (f, nrow, ncol, stype, buf, Common) ; } return (G) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Check/lesser.txt0000644000076500000240000006350013524616144025550 0ustar tamasstaff00000000000000 GNU LESSER GENERAL PUBLIC LICENSE Version 2.1, February 1999 Copyright (C) 1991, 1999 Free Software Foundation, Inc. 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed. 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Here is a sample; alter the names: Yoyodyne, Inc., hereby disclaims all copyright interest in the library `Frob' (a library for tweaking knobs) written by James Random Hacker. , 1 April 1990 Ty Coon, President of Vice That's all there is to it! python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Check/cholmod_write.c0000644000076500000240000005124213524616144026515 0ustar tamasstaff00000000000000/* ========================================================================== */ /* === Check/cholmod_write ================================================== */ /* ========================================================================== */ /* Write a matrix to a file in Matrix Market form. * * A can be sparse or full. * * If present and non-empty, A and Z must have the same dimension. Z contains * the explicit zero entries in the matrix (which MATLAB drops). The entries * of Z appear as explicit zeros in the output file. Z is optional. If it is * an empty matrix it is ignored. Z must be sparse or empty, if present. * It is ignored if A is full. * * filename is the name of the output file. comments is file whose * contents are include after the Matrix Market header and before the first * data line. Ignored if an empty string or not present. * * Except for the workspace used by cholmod_symmetry (ncol integers) for * the sparse case, these routines use no workspace at all. */ #ifndef NCHECK #include "cholmod_internal.h" #include "cholmod_check.h" #include "cholmod_matrixops.h" #include #include #define MMLEN 1024 #define MAXLINE MMLEN+6 /* ========================================================================== */ /* === include_comments ===================================================== */ /* ========================================================================== */ /* Read in the comments file, if it exists, and copy it to the Matrix Market * file. A "%" is prepended to each line. Returns TRUE if successful, FALSE * otherwise. */ static int include_comments (FILE *f, const char *comments) { FILE *cf = NULL ; char buffer [MAXLINE] ; int ok = TRUE ; if (comments != NULL && comments [0] != '\0') { cf = fopen (comments, "r") ; if (cf == NULL) { return (FALSE) ; } while (ok && fgets (buffer, MAXLINE, cf) != NULL) { /* ensure the line is not too long */ buffer [MMLEN-1] = '\0' ; buffer [MMLEN-2] = '\n' ; ok = ok && (fprintf (f, "%%%s", buffer) > 0) ; } fclose (cf) ; } return (ok) ; } /* ========================================================================== */ /* === get_value ============================================================ */ /* ========================================================================== */ /* Get the pth value in the matrix. */ static void get_value ( double *Ax, /* real values, or real/imag. for CHOLMOD_COMPLEX type */ double *Az, /* imaginary values for CHOLMOD_ZOMPLEX type */ Int p, /* get the pth entry */ Int xtype, /* A->xtype: pattern, real, complex, or zomplex */ double *x, /* the real part */ double *z /* the imaginary part */ ) { switch (xtype) { case CHOLMOD_PATTERN: *x = 1 ; *z = 0 ; break ; case CHOLMOD_REAL: *x = Ax [p] ; *z = 0 ; break ; case CHOLMOD_COMPLEX: *x = Ax [2*p] ; *z = Ax [2*p+1] ; break ; case CHOLMOD_ZOMPLEX: *x = Ax [p] ; *z = Az [p] ; break ; } } /* ========================================================================== */ /* === print_value ========================================================== */ /* ========================================================================== */ /* Print a numeric value to the file, using the shortest format that ensures * the value is written precisely. Returns TRUE if successful, FALSE otherwise. */ static int print_value ( FILE *f, /* file to print to */ double x, /* value to print */ Int is_integer /* TRUE if printing as an integer */ ) { double y ; char s [MAXLINE], *p ; Int i, dest = 0, src = 0 ; int width, ok ; if (is_integer) { i = (Int) x ; ok = (fprintf (f, ID, i) > 0) ; return (ok) ; } /* ---------------------------------------------------------------------- */ /* handle Inf and NaN */ /* ---------------------------------------------------------------------- */ /* change -inf to -HUGE_DOUBLE, and change +inf and nan to +HUGE_DOUBLE */ if (CHOLMOD_IS_NAN (x) || x >= HUGE_DOUBLE) { x = HUGE_DOUBLE ; } else if (x <= -HUGE_DOUBLE) { x = -HUGE_DOUBLE ; } /* ---------------------------------------------------------------------- */ /* find the smallest acceptable precision */ /* ---------------------------------------------------------------------- */ for (width = 6 ; width < 20 ; width++) { sprintf (s, "%.*g", width, x) ; sscanf (s, "%lg", &y) ; if (x == y) break ; } /* ---------------------------------------------------------------------- */ /* shorten the string */ /* ---------------------------------------------------------------------- */ /* change "e+0" to "e", change "e+" to "e", and change "e-0" to "e-" */ for (i = 0 ; i < MAXLINE && s [i] != '\0' ; i++) { if (s [i] == 'e') { if (s [i+1] == '+') { dest = i+1 ; if (s [i+2] == '0') { /* delete characters s[i+1] and s[i+2] */ src = i+3 ; } else { /* delete characters s[i+1] */ src = i+2 ; } } else if (s [i+1] == '-') { dest = i+2 ; if (s [i+2] == '0') { /* delete character s[i+2] */ src = i+3 ; } else { /* no change */ break ; } } while (s [src] != '\0') { s [dest++] = s [src++] ; } s [dest] = '\0' ; break ; } } /* delete the leading "0" if present and not necessary */ p = s ; s [MAXLINE-1] = '\0' ; i = strlen (s) ; if (i > 2 && s [0] == '0' && s [1] == '.') { /* change "0.x" to ".x" */ p = s + 1 ; } else if (i > 3 && s [0] == '-' && s [1] == '0' && s [2] == '.') { /* change "-0.x" to "-.x" */ s [1] = '-' ; p = s + 1 ; } #if 0 /* double-check */ i = sscanf (p, "%lg", &z) ; if (i != 1 || y != z) { /* oops! something went wrong in the "e+0" edit, above. */ /* this "cannot" happen */ sprintf (s, "%.*g", width, x) ; p = s ; } #endif /* ---------------------------------------------------------------------- */ /* print the value to the file */ /* ---------------------------------------------------------------------- */ ok = (fprintf (f, "%s", p) > 0) ; return (ok) ; } /* ========================================================================== */ /* === print_triplet ======================================================== */ /* ========================================================================== */ /* Print a triplet, converting it to one-based. Returns TRUE if successful, * FALSE otherwise. */ static int print_triplet ( FILE *f, /* file to print to */ Int is_binary, /* TRUE if file is "pattern" */ Int is_complex, /* TRUE if file is "complex" */ Int is_integer, /* TRUE if file is "integer" */ Int i, /* row index (zero-based) */ Int j, /* column index (zero-based) */ double x, /* real part */ double z /* imaginary part */ ) { int ok ; ok = (fprintf (f, ID " " ID, 1+i, 1+j) > 0) ; if (!is_binary) { fprintf (f, " ") ; ok = ok && print_value (f, x, is_integer) ; if (is_complex) { fprintf (f, " ") ; ok = ok && print_value (f, z, is_integer) ; } } ok = ok && (fprintf (f, "\n") > 0) ; return (ok) ; } /* ========================================================================== */ /* === ntriplets ============================================================ */ /* ========================================================================== */ /* Compute the number of triplets that will be printed to the file * from the matrix A. */ static Int ntriplets ( cholmod_sparse *A, /* matrix that will be printed */ Int is_sym /* TRUE if the file is symmetric (lower part only)*/ ) { Int *Ap, *Ai, *Anz, packed, i, j, p, pend, ncol, stype, nz = 0 ; if (A == NULL) { /* the Z matrix is NULL */ return (0) ; } stype = A->stype ; Ap = A->p ; Ai = A->i ; Anz = A->nz ; packed = A->packed ; ncol = A->ncol ; for (j = 0 ; j < ncol ; j++) { p = Ap [j] ; pend = (packed) ? Ap [j+1] : p + Anz [j] ; for ( ; p < pend ; p++) { i = Ai [p] ; if ((stype < 0 && i >= j) || (stype == 0 && (i >= j || !is_sym))) { /* CHOLMOD matrix is symmetric-lower (and so is the file); * or CHOLMOD matrix is unsymmetric and either A(i,j) is in * the lower part or the file is unsymmetric. */ nz++ ; } else if (stype > 0 && i <= j) { /* CHOLMOD matrix is symmetric-upper, but the file is * symmetric-lower. Need to transpose the entry. */ nz++ ; } } } return (nz) ; } /* ========================================================================== */ /* === cholmod_write_sparse ================================================= */ /* ========================================================================== */ /* Write a sparse matrix to a file in Matrix Market format. Optionally include * comments, and print explicit zero entries given by the pattern of the Z * matrix. If not NULL, the Z matrix must have the same dimensions and stype * as A. * * Returns the symmetry in which the matrix was printed (1 to 7, see the * CHOLMOD_MM_* codes in CHOLMOD/Include/cholmod_core.h), or -1 on failure. * * If A and Z are sorted on input, and either unsymmetric (stype = 0) or * symmetric-lower (stype < 0), and if A and Z do not overlap, then the triplets * are sorted, first by column and then by row index within each column, with * no duplicate entries. If all the above holds except stype > 0, then the * triplets are sorted by row first and then column. */ int CHOLMOD(write_sparse) ( /* ---- input ---- */ FILE *f, /* file to write to, must already be open */ cholmod_sparse *A, /* matrix to print */ cholmod_sparse *Z, /* optional matrix with pattern of explicit zeros */ const char *comments, /* optional filename of comments to include */ /* --------------- */ cholmod_common *Common ) { double x = 0, z = 0 ; double *Ax, *Az ; Int *Ap, *Ai, *Anz, *Zp, *Zi, *Znz ; Int nrow, ncol, is_complex, symmetry, i, j, q, iz, p, nz, is_binary, stype, is_integer, asym, is_sym, xtype, apacked, zpacked, pend, qend, zsym ; int ok ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (EMPTY) ; RETURN_IF_NULL (f, EMPTY) ; RETURN_IF_NULL (A, EMPTY) ; RETURN_IF_XTYPE_INVALID (A, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, EMPTY) ; if (Z != NULL && (Z->nrow == 0 || Z->ncol == 0)) { /* Z is non-NULL but empty, so treat it as a NULL matrix */ Z = NULL ; } if (Z != NULL) { RETURN_IF_XTYPE_INVALID (Z, CHOLMOD_PATTERN, CHOLMOD_ZOMPLEX, EMPTY) ; if (Z->nrow != A->nrow || Z->ncol != A->ncol || Z->stype != A->stype) { ERROR (CHOLMOD_INVALID, "dimension or type of A and Z mismatch") ; return (EMPTY) ; } } Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* get the A matrix */ /* ---------------------------------------------------------------------- */ Ap = A->p ; Ai = A->i ; Ax = A->x ; Az = A->z ; Anz = A->nz ; nrow = A->nrow ; ncol = A->ncol ; xtype = A->xtype ; apacked = A->packed ; if (xtype == CHOLMOD_PATTERN) { /* a CHOLMOD pattern matrix is printed as "pattern" in the file */ is_binary = TRUE ; is_integer = FALSE ; is_complex = FALSE ; } else if (xtype == CHOLMOD_REAL) { /* determine if a real matrix is in fact binary or integer */ is_binary = TRUE ; is_integer = TRUE ; is_complex = FALSE ; for (j = 0 ; (is_binary || is_integer) && j < ncol ; j++) { p = Ap [j] ; pend = (apacked) ? Ap [j+1] : p + Anz [j] ; for ( ; (is_binary || is_integer) && p < pend ; p++) { x = Ax [p] ; if (x != 1) { is_binary = FALSE ; } /* convert to Int and then back to double */ i = (Int) x ; z = (double) i ; if (z != x) { is_integer = FALSE ; } } } } else { /* a CHOLMOD complex matrix is printed as "complex" in the file */ is_binary = FALSE ; is_integer = FALSE ; is_complex = TRUE ; } /* ---------------------------------------------------------------------- */ /* get the Z matrix (only consider the pattern) */ /* ---------------------------------------------------------------------- */ Zp = NULL ; Zi = NULL ; Znz = NULL ; zpacked = TRUE ; if (Z != NULL) { Zp = Z->p ; Zi = Z->i ; Znz = Z->nz ; zpacked = Z->packed ; } /* ---------------------------------------------------------------------- */ /* determine the symmetry of A and Z */ /* ---------------------------------------------------------------------- */ stype = A->stype ; if (A->nrow != A->ncol) { asym = CHOLMOD_MM_RECTANGULAR ; } else if (stype != 0) { /* CHOLMOD's A and Z matrices have a symmetric (and matching) stype. * Note that the diagonal is not checked. */ asym = is_complex ? CHOLMOD_MM_HERMITIAN : CHOLMOD_MM_SYMMETRIC ; } else if (!A->sorted) { /* A is in unsymmetric storage, but unsorted */ asym = CHOLMOD_MM_UNSYMMETRIC ; } else { /* CHOLMOD's stype is zero (stored in unsymmetric form) */ asym = EMPTY ; zsym = EMPTY ; #ifndef NMATRIXOPS /* determine if the matrices are in fact symmetric or Hermitian */ asym = CHOLMOD(symmetry) (A, 1, NULL, NULL, NULL, NULL, Common) ; zsym = (Z == NULL) ? 999 : CHOLMOD(symmetry) (Z, 1, NULL, NULL, NULL, NULL, Common) ; #endif if (asym == EMPTY || zsym <= CHOLMOD_MM_UNSYMMETRIC) { /* not computed, out of memory, or Z is unsymmetric */ asym = CHOLMOD_MM_UNSYMMETRIC ; } } /* ---------------------------------------------------------------------- */ /* write the Matrix Market header */ /* ---------------------------------------------------------------------- */ ok = fprintf (f, "%%%%MatrixMarket matrix coordinate") > 0 ; if (is_complex) { ok = ok && (fprintf (f, " complex") > 0) ; } else if (is_binary) { ok = ok && (fprintf (f, " pattern") > 0) ; } else if (is_integer) { ok = ok && (fprintf (f, " integer") > 0) ; } else { ok = ok && (fprintf (f, " real") > 0) ; } is_sym = FALSE ; switch (asym) { case CHOLMOD_MM_RECTANGULAR: case CHOLMOD_MM_UNSYMMETRIC: /* A is rectangular or unsymmetric */ ok = ok && (fprintf (f, " general\n") > 0) ; is_sym = FALSE ; symmetry = CHOLMOD_MM_UNSYMMETRIC ; break ; case CHOLMOD_MM_SYMMETRIC: case CHOLMOD_MM_SYMMETRIC_POSDIAG: /* A is symmetric */ ok = ok && (fprintf (f, " symmetric\n") > 0) ; is_sym = TRUE ; symmetry = CHOLMOD_MM_SYMMETRIC ; break ; case CHOLMOD_MM_HERMITIAN: case CHOLMOD_MM_HERMITIAN_POSDIAG: /* A is Hermitian */ ok = ok && (fprintf (f, " Hermitian\n") > 0) ; is_sym = TRUE ; symmetry = CHOLMOD_MM_HERMITIAN ; break ; case CHOLMOD_MM_SKEW_SYMMETRIC: /* A is skew symmetric */ ok = ok && (fprintf (f, " skew-symmetric\n") > 0) ; is_sym = TRUE ; symmetry = CHOLMOD_MM_SKEW_SYMMETRIC ; break ; } /* ---------------------------------------------------------------------- */ /* include the comments if present */ /* ---------------------------------------------------------------------- */ ok = ok && include_comments (f, comments) ; /* ---------------------------------------------------------------------- */ /* write a sparse matrix (A and Z) */ /* ---------------------------------------------------------------------- */ nz = ntriplets (A, is_sym) + ntriplets (Z, is_sym) ; /* write the first data line, with nrow, ncol, and # of triplets */ ok = ok && (fprintf (f, ID " " ID " " ID "\n", nrow, ncol, nz) > 0) ; for (j = 0 ; ok && j < ncol ; j++) { /* merge column of A and Z */ p = Ap [j] ; pend = (apacked) ? Ap [j+1] : p + Anz [j] ; q = (Z == NULL) ? 0 : Zp [j] ; qend = (Z == NULL) ? 0 : ((zpacked) ? Zp [j+1] : q + Znz [j]) ; while (ok) { /* get the next row index from A and Z */ i = (p < pend) ? Ai [p] : (nrow+1) ; iz = (q < qend) ? Zi [q] : (nrow+2) ; if (i <= iz) { /* get A(i,j), or quit if both A and Z are exhausted */ if (i == nrow+1) break ; get_value (Ax, Az, p, xtype, &x, &z) ; p++ ; } else { /* get Z(i,j) */ i = iz ; x = 0 ; z = 0 ; q++ ; } if ((stype < 0 && i >= j) || (stype == 0 && (i >= j || !is_sym))) { /* CHOLMOD matrix is symmetric-lower (and so is the file); * or CHOLMOD matrix is unsymmetric and either A(i,j) is in * the lower part or the file is unsymmetric. */ ok = ok && print_triplet (f, is_binary, is_complex, is_integer, i,j, x,z) ; } else if (stype > 0 && i <= j) { /* CHOLMOD matrix is symmetric-upper, but the file is * symmetric-lower. Need to transpose the entry. If the * matrix is real, the complex part is ignored. If the matrix * is complex, it Hermitian. */ ASSERT (IMPLIES (is_complex, asym == CHOLMOD_MM_HERMITIAN)) ; if (z != 0) { z = -z ; } ok = ok && print_triplet (f, is_binary, is_complex, is_integer, j,i, x,z) ; } } } if (!ok) { ERROR (CHOLMOD_INVALID, "error reading/writing file") ; return (EMPTY) ; } return (asym) ; } /* ========================================================================== */ /* === cholmod_write_dense ================================================== */ /* ========================================================================== */ /* Write a dense matrix to a file in Matrix Market format. Optionally include * comments. Returns > 0 if successful, -1 otherwise (1 if rectangular, 2 if * square). Future versions may return 1 to 7 on success (a CHOLMOD_MM_* code, * just as cholmod_write_sparse does). * * A dense matrix is written in "general" format; symmetric formats in the * Matrix Market standard are not exploited. */ int CHOLMOD(write_dense) ( /* ---- input ---- */ FILE *f, /* file to write to, must already be open */ cholmod_dense *X, /* matrix to print */ const char *comments, /* optional filename of comments to include */ /* --------------- */ cholmod_common *Common ) { double x = 0, z = 0 ; double *Xx, *Xz ; Int nrow, ncol, is_complex, i, j, xtype, p ; int ok ; /* ---------------------------------------------------------------------- */ /* check inputs */ /* ---------------------------------------------------------------------- */ RETURN_IF_NULL_COMMON (EMPTY) ; RETURN_IF_NULL (f, EMPTY) ; RETURN_IF_NULL (X, EMPTY) ; RETURN_IF_XTYPE_INVALID (X, CHOLMOD_REAL, CHOLMOD_ZOMPLEX, EMPTY) ; Common->status = CHOLMOD_OK ; /* ---------------------------------------------------------------------- */ /* get the X matrix */ /* ---------------------------------------------------------------------- */ Xx = X->x ; Xz = X->z ; nrow = X->nrow ; ncol = X->ncol ; xtype = X->xtype ; is_complex = (xtype == CHOLMOD_COMPLEX) || (xtype == CHOLMOD_ZOMPLEX) ; /* ---------------------------------------------------------------------- */ /* write the Matrix Market header */ /* ---------------------------------------------------------------------- */ ok = (fprintf (f, "%%%%MatrixMarket matrix array") > 0) ; if (is_complex) { ok = ok && (fprintf (f, " complex general\n") > 0) ; } else { ok = ok && (fprintf (f, " real general\n") > 0) ; } /* ---------------------------------------------------------------------- */ /* include the comments if present */ /* ---------------------------------------------------------------------- */ ok = ok && include_comments (f, comments) ; /* ---------------------------------------------------------------------- */ /* write a dense matrix */ /* ---------------------------------------------------------------------- */ /* write the first data line, with nrow and ncol */ ok = ok && (fprintf (f, ID " " ID "\n", nrow, ncol) > 0) ; Xx = X->x ; Xz = X->z ; for (j = 0 ; ok && j < ncol ; j++) { for (i = 0 ; ok && i < nrow ; i++) { p = i + j*nrow ; get_value (Xx, Xz, p, xtype, &x, &z) ; ok = ok && print_value (f, x, FALSE) ; if (is_complex) { ok = ok && (fprintf (f, " ") > 0) ; ok = ok && print_value (f, z, FALSE) ; } ok = ok && (fprintf (f, "\n") > 0) ; } } if (!ok) { ERROR (CHOLMOD_INVALID, "error reading/writing file") ; return (EMPTY) ; } return ((nrow == ncol) ? CHOLMOD_MM_UNSYMMETRIC : CHOLMOD_MM_RECTANGULAR) ; } #endif python-igraph-0.8.0/vendor/source/igraph/src/CHOLMOD/Check/License.txt0000644000076500000240000000204213524616144025627 0ustar tamasstaff00000000000000CHOLMOD/Check Module. Copyright (C) 2005-2006, Timothy A. Davis CHOLMOD is also available under other licenses; contact authors for details. http://www.suitesparse.com Note that this license is for the CHOLMOD/Check module only. All CHOLMOD modules are licensed separately. -------------------------------------------------------------------------------- This Module is free software; you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation; either version 2.1 of the License, or (at your option) any later version. This Module is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with this Module; if not, write to the Free Software Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA python-igraph-0.8.0/vendor/source/igraph/src/bignum.h0000644000076500000240000001134313614300625023032 0ustar tamasstaff00000000000000/***************************************************************************** * Entropy - Emerging Network To Reduce Orwellian Potency Yield * * Copyright (C) 2005 Juergen Buchmueller * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 2 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software Foundation, * Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA * * $Id: bignum.h,v 1.6 2005/08/11 17:57:39 pullmoll Exp $ *****************************************************************************/ #ifndef _bignum_h_ #define _bignum_h_ #include "config.h" #ifdef HAVE_STDINT_H #include #else #ifdef HAVE_SYS_INT_TYPES_H #include #else #include "pstdint.h" #endif #endif #include #include #include #ifndef NULL #define NULL 0 #endif #ifndef O_BINARY #define O_BINARY 0 #endif #ifndef HAVE_U64 #define HAVE_U64 1 #endif /* up to 512 limbs (512 * 32 = 16384 bits) numbers */ /* BN_MAXSIZE used to be 512 here, allowing us to go up to 512*32 = 16384 bits. * However, this has caused compilation problems with clang 7.3 (unless * compiling with -O2 -g). Since it is unlikely that we'll need that many bits, * I have changed this to 128, which still yields 4096 bits of precision but * does not cause problems with clang -- TN, 2016-04-18 */ #define BN_MAXSIZE 128 #define LIMBBITS 32 #define LIMBMASK 0xfffffffful #define HALFMASK 0x0000fffful #define DIGMSB 0x80000000ul #define DIGLSB 0x00000001ul typedef uint32_t count_t; typedef uint16_t half_t; typedef uint32_t limb_t; #if HAVE_U64 typedef uint64_t dlimb_t; #endif /* less significant half limb */ #define LSH(d) ((half_t)(d)) /* more significant half limb */ #define MSH(d) ((limb_t)(d)>>16) /* shift left half limb */ #define SHL(d) ((limb_t)(d)<<16) /* single limb functions */ limb_t sl_div(limb_t *q, limb_t *r, limb_t u[2], limb_t v); limb_t sl_gcd(limb_t x, limb_t y); int sl_modexp(limb_t *exp, limb_t x, limb_t n, limb_t d); int sl_modinv(limb_t *inv, limb_t u, limb_t v); int sl_modmul(limb_t *a, limb_t x, limb_t y, limb_t m); int sl_mul(limb_t p[2], limb_t x, limb_t y); /* big number functions (max. MAXSIZE limbs) */ void bn_zero(limb_t a[], count_t nlimb); void bn_limb(limb_t a[], limb_t d, count_t nlimb); void bn_copy(limb_t a[], limb_t b[], count_t nlimb); count_t bn_sizeof(limb_t a[], count_t nlimb); int bn_cmp_limb(limb_t a[], limb_t b, count_t nlimb); int bn_cmp(limb_t a[], limb_t b[], count_t nlimb); /* big number to hex, decimal, binary */ const char *bn2x(limb_t a[], count_t nlimb); const char *bn2d(limb_t a[], count_t nlimb); const char *bn2f(limb_t a[], count_t alimb, limb_t b[], count_t blimb); const char *bn2b(limb_t a[], count_t nlimb); /* big number with single limb operations */ limb_t bn_add_limb(limb_t w[], limb_t u[], limb_t v, count_t nlimb); limb_t bn_sub_limb(limb_t w[], limb_t u[], limb_t v, count_t nlimb); limb_t bn_div_limb(limb_t q[], limb_t u[], limb_t v, count_t nlimb); limb_t bn_mod_limb(limb_t u[], limb_t d, count_t nlimb); limb_t bn_mul_limb(limb_t w[], limb_t u[], limb_t v, count_t nlimb); /* big number with single limb <= HALFMASK operations */ limb_t bn_div_half(limb_t q[], limb_t u[], limb_t v, count_t nlimb); limb_t bn_mod_half(limb_t a[], limb_t d, count_t nlimb); /* big number operations */ limb_t bn_add(limb_t w[], limb_t u[], limb_t v[], count_t nlimb); limb_t bn_sub(limb_t w[], limb_t u[], limb_t v[], count_t nlimb); limb_t bn_shl(limb_t a[], limb_t b[], count_t x, count_t nlimb); limb_t bn_shr(limb_t a[], limb_t b[], count_t x, count_t nlimb); int bn_mul(limb_t w[], limb_t u[], limb_t v[], count_t nlimb); int bn_div(limb_t q[], limb_t r[], limb_t u[], limb_t v[], count_t ulimb, count_t vlimb); limb_t bn_mod(limb_t r[], limb_t u[], count_t ulimb, limb_t v[], count_t vlimb); int bn_gcd(limb_t g[], limb_t x[], limb_t y[], count_t nlimb); int bn_sqrt(limb_t g[], limb_t x[], limb_t y[], count_t rlimb, count_t nlimb); int bn_modexp(limb_t y[], limb_t x[], limb_t e[], limb_t m[], count_t nlimb); int bn_modinv(limb_t inv[], limb_t u[], limb_t v[], count_t nlimb); limb_t bn_modmul(limb_t a[], limb_t x[], limb_t y[], limb_t m[], count_t nlimb); #endif /* !defined(_bignum_h_) */ python-igraph-0.8.0/vendor/source/igraph/src/cliques.c0000644000076500000240000015255313614300625023222 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2005-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_cliques.h" #include "igraph_memory.h" #include "igraph_random.h" #include "igraph_constants.h" #include "igraph_adjlist.h" #include "igraph_interrupt_internal.h" #include "igraph_interface.h" #include "igraph_progress.h" #include "igraph_stack.h" #include "igraph_types_internal.h" #include "igraph_cliquer.h" #include "config.h" #include #include /* memset */ void igraph_i_cliques_free_res(igraph_vector_ptr_t *res) { long i, n; n = igraph_vector_ptr_size(res); for (i = 0; i < n; i++) { if (VECTOR(*res)[i] != 0) { igraph_vector_destroy(VECTOR(*res)[i]); igraph_free(VECTOR(*res)[i]); } } igraph_vector_ptr_clear(res); } int igraph_i_find_k_cliques(const igraph_t *graph, long int size, const igraph_real_t *member_storage, igraph_real_t **new_member_storage, long int old_clique_count, long int *clique_count, igraph_vector_t *neis, igraph_bool_t independent_vertices) { long int j, k, l, m, n, new_member_storage_size; const igraph_real_t *c1, *c2; igraph_real_t v1, v2; igraph_bool_t ok; /* Allocate the storage */ *new_member_storage = igraph_Realloc(*new_member_storage, (size_t) (size * old_clique_count), igraph_real_t); if (*new_member_storage == 0) { IGRAPH_ERROR("cliques failed", IGRAPH_ENOMEM); } new_member_storage_size = size * old_clique_count; IGRAPH_FINALLY(igraph_free, *new_member_storage); m = n = 0; /* Now consider all pairs of i-1-cliques and see if they can be merged */ for (j = 0; j < old_clique_count; j++) { for (k = j + 1; k < old_clique_count; k++) { IGRAPH_ALLOW_INTERRUPTION(); /* Since cliques are represented by their vertex indices in increasing * order, two cliques can be merged iff they have exactly the same * indices excluding one AND there is an edge between the two different * vertices */ c1 = member_storage + j * (size - 1); c2 = member_storage + k * (size - 1); /* Find the longest prefixes of c1 and c2 that are equal */ for (l = 0; l < size - 1 && c1[l] == c2[l]; l++) { (*new_member_storage)[m++] = c1[l]; } /* Now, if l == size-1, the two vectors are totally equal. This is a bug */ if (l == size - 1) { IGRAPH_WARNING("possible bug in igraph_cliques"); m = n; } else { /* Assuming that j (*new_member_storage)[m - 1]) { (*new_member_storage)[m++] = v2; n = m; } else { m = n; } } else { m = n; } } /* See if new_member_storage is full. If so, reallocate */ if (m == new_member_storage_size) { IGRAPH_FINALLY_CLEAN(1); *new_member_storage = igraph_Realloc(*new_member_storage, (size_t) new_member_storage_size * 2, igraph_real_t); if (*new_member_storage == 0) { IGRAPH_ERROR("cliques failed", IGRAPH_ENOMEM); } new_member_storage_size *= 2; IGRAPH_FINALLY(igraph_free, *new_member_storage); } } } } /* Calculate how many cliques have we found */ *clique_count = n / size; IGRAPH_FINALLY_CLEAN(1); return 0; } /* Internal function for calculating cliques or independent vertex sets. * They are practically the same except that the complementer of the graph * should be used in the latter case. */ int igraph_i_cliques(const igraph_t *graph, igraph_vector_ptr_t *res, igraph_integer_t min_size, igraph_integer_t max_size, igraph_bool_t independent_vertices) { igraph_integer_t no_of_nodes; igraph_vector_t neis; igraph_real_t *member_storage = 0, *new_member_storage, *c1; long int i, j, k, clique_count, old_clique_count; if (igraph_is_directed(graph)) { IGRAPH_WARNING("directionality of edges is ignored for directed graphs"); } no_of_nodes = igraph_vcount(graph); if (min_size < 0) { min_size = 0; } if (max_size > no_of_nodes || max_size <= 0) { max_size = no_of_nodes; } igraph_vector_ptr_clear(res); IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); IGRAPH_FINALLY(igraph_i_cliques_free_res, res); /* Will be resized later, if needed. */ member_storage = igraph_Calloc(1, igraph_real_t); if (member_storage == 0) { IGRAPH_ERROR("cliques failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, member_storage); /* Find all 1-cliques: every vertex will be a clique */ new_member_storage = igraph_Calloc(no_of_nodes, igraph_real_t); if (new_member_storage == 0) { IGRAPH_ERROR("cliques failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, new_member_storage); for (i = 0; i < no_of_nodes; i++) { new_member_storage[i] = i; } clique_count = no_of_nodes; old_clique_count = 0; /* Add size 1 cliques if requested */ if (min_size <= 1) { IGRAPH_CHECK(igraph_vector_ptr_resize(res, no_of_nodes)); igraph_vector_ptr_null(res); for (i = 0; i < no_of_nodes; i++) { igraph_vector_t *p = igraph_Calloc(1, igraph_vector_t); if (p == 0) { IGRAPH_ERROR("cliques failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, p); IGRAPH_CHECK(igraph_vector_init(p, 1)); VECTOR(*p)[0] = i; VECTOR(*res)[i] = p; IGRAPH_FINALLY_CLEAN(1); } } for (i = 2; i <= max_size && clique_count > 1; i++) { /* Here new_member_storage contains the cliques found in the previous iteration. Save this into member_storage, might be needed later */ c1 = member_storage; member_storage = new_member_storage; new_member_storage = c1; old_clique_count = clique_count; IGRAPH_ALLOW_INTERRUPTION(); /* Calculate the cliques */ IGRAPH_FINALLY_CLEAN(2); IGRAPH_CHECK(igraph_i_find_k_cliques(graph, i, member_storage, &new_member_storage, old_clique_count, &clique_count, &neis, independent_vertices)); IGRAPH_FINALLY(igraph_free, member_storage); IGRAPH_FINALLY(igraph_free, new_member_storage); /* Add the cliques just found to the result if requested */ if (i >= min_size && i <= max_size) { for (j = 0, k = 0; j < clique_count; j++, k += i) { igraph_vector_t *p = igraph_Calloc(1, igraph_vector_t); if (p == 0) { IGRAPH_ERROR("cliques failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, p); IGRAPH_CHECK(igraph_vector_init_copy(p, &new_member_storage[k], i)); IGRAPH_FINALLY(igraph_vector_destroy, p); IGRAPH_CHECK(igraph_vector_ptr_push_back(res, p)); IGRAPH_FINALLY_CLEAN(2); } } } /* i <= max_size && clique_count != 0 */ igraph_free(member_storage); igraph_free(new_member_storage); igraph_vector_destroy(&neis); IGRAPH_FINALLY_CLEAN(4); /* 3 here, +1 is igraph_i_cliques_free_res */ return 0; } /** * \function igraph_cliques * \brief Find all or some cliques in a graph * * * Cliques are fully connected subgraphs of a graph. * * * If you are only interested in the size of the largest clique in the graph, * use \ref igraph_clique_number() instead. * * The current implementation of this function searches * for maximal independent vertex sets (see \ref * igraph_maximal_independent_vertex_sets()) in the complementer graph * using the algorithm published in: * S. Tsukiyama, M. Ide, H. Ariyoshi and I. Shirawaka. A new algorithm * for generating all the maximal independent sets. SIAM J Computing, * 6:505--517, 1977. * * \param graph The input graph. * \param res Pointer to a pointer vector, the result will be stored * here, ie. \c res will contain pointers to \c igraph_vector_t * objects which contain the indices of vertices involved in a clique. * The pointer vector will be resized if needed but note that the * objects in the pointer vector will not be freed. * \param min_size Integer giving the minimum size of the cliques to be * returned. If negative or zero, no lower bound will be used. * \param max_size Integer giving the maximum size of the cliques to be * returned. If negative or zero, no upper bound will be used. * \return Error code. * * \sa \ref igraph_largest_cliques() and \ref igraph_clique_number(). * * Time complexity: TODO * * \example examples/simple/igraph_cliques.c */ int igraph_cliques(const igraph_t *graph, igraph_vector_ptr_t *res, igraph_integer_t min_size, igraph_integer_t max_size) { return igraph_i_cliquer_cliques(graph, res, min_size, max_size); } /** * \function igraph_clique_size_hist * \brief Count cliques of each size in the graph * * * Cliques are fully connected subgraphs of a graph. * * The current implementation of this function * uses version 1.21 of the Cliquer library by Sampo Niskanen and * Patric R. J. Östergård, http://users.aalto.fi/~pat/cliquer.html * * \param graph The input graph. * \param hist Pointer to an initialized vector. The result will be stored * here. The first element will store the number of size-1 cliques, the second * element the number of size-2 cliques, etc. For cliques smaller than \c min_size, * zero counts will be returned. * \param min_size Integer giving the minimum size of the cliques to be * returned. If negative or zero, no lower bound will be used. * \param max_size Integer giving the maximum size of the cliques to be * returned. If negative or zero, no upper bound will be used. * \return Error code. * * \sa \ref igraph_cliques() and \ref igraph_cliques_callback() * * Time complexity: Exponential * */ int igraph_clique_size_hist(const igraph_t *graph, igraph_vector_t *hist, igraph_integer_t min_size, igraph_integer_t max_size) { return igraph_i_cliquer_histogram(graph, hist, min_size, max_size); } /** * \function igraph_cliques_callback * \brief Calls a function for each clique in the graph. * * * Cliques are fully connected subgraphs of a graph. This function * enumerates all cliques within the given size range and calls * \p cliquehandler_fn for each of them. The cliques are passed to the * callback function as an igraph_vector_t *. Destroying and * freeing this vector is left up to the user. Use \ref igraph_vector_destroy() * to destroy it first, then free it using \ref igraph_free(). * * The current implementation of this function * uses version 1.21 of the Cliquer library by Sampo Niskanen and * Patric R. J. Östergård, http://users.aalto.fi/~pat/cliquer.html * * \param graph The input graph. * \param min_size Integer giving the minimum size of the cliques to be * returned. If negative or zero, no lower bound will be used. * \param max_size Integer giving the maximum size of the cliques to be * returned. If negative or zero, no upper bound will be used. * \param cliquehandler_fn Callback function to be called for each clique. * See also igraph_clique_handler_t. * \param arg Extra argument to supply to \p cliquehandler_fn. * \return Error code. * * \sa \ref igraph_cliques() * * Time complexity: Exponential * */ int igraph_cliques_callback(const igraph_t *graph, igraph_integer_t min_size, igraph_integer_t max_size, igraph_clique_handler_t *cliquehandler_fn, void *arg) { return igraph_i_cliquer_callback(graph, min_size, max_size, cliquehandler_fn, arg); } /** * \function igraph_weighted_cliques * \brief Find all cliques in a given weight range in a vertex weighted graph * * * Cliques are fully connected subgraphs of a graph. * The weight of a clique is the sum of the weights * of individual vertices within the clique. * * The current implementation of this function * uses version 1.21 of the Cliquer library by Sampo Niskanen and * Patric R. J. Östergård, http://users.aalto.fi/~pat/cliquer.html * * Only positive integer vertex weights are supported. * * \param graph The input graph. * \param vertex_weights A vector of vertex weights. The current implementation * will truncate all weights to their integer parts. * \param res Pointer to a pointer vector, the result will be stored * here, ie. \c res will contain pointers to \c igraph_vector_t * objects which contain the indices of vertices involved in a clique. * The pointer vector will be resized if needed but note that the * objects in the pointer vector will not be freed. * \param min_weight Integer giving the minimum weight of the cliques to be * returned. If negative or zero, no lower bound will be used. * \param max_weight Integer giving the maximum weight of the cliques to be * returned. If negative or zero, no upper bound will be used. * \param maximal If true, only maximal cliques will be returned * \return Error code. * * \sa \ref igraph_cliques(), \ref igraph_maximal_cliques() * * Time complexity: Exponential * */ int igraph_weighted_cliques(const igraph_t *graph, const igraph_vector_t *vertex_weights, igraph_vector_ptr_t *res, igraph_real_t min_weight, igraph_real_t max_weight, igraph_bool_t maximal) { return igraph_i_weighted_cliques(graph, vertex_weights, res, min_weight, max_weight, maximal); } /** * \function igraph_largest_weighted_cliques * \brief Finds the largest weight clique(s) in a graph. * * * Finds the clique(s) having the largest weight in the graph. * * The current implementation of this function * uses version 1.21 of the Cliquer library by Sampo Niskanen and * Patric R. J. Östergård, http://users.aalto.fi/~pat/cliquer.html * * Only positive integer vertex weights are supported. * * \param graph The input graph. * \param vertex_weights A vector of vertex weights. The current implementation * will truncate all weights to their integer parts. * \param res Pointer to a pointer vector, the result will be stored * here, ie. \c res will contain pointers to \c igraph_vector_t * objects which contain the indices of vertices involved in a clique. * The pointer vector will be resized if needed but note that the * objects in the pointer vector will not be freed. * \return Error code. * * \sa \ref igraph_weighted_cliques(), \ref igraph_weighted_clique_number(), \ref igraph_largest_cliques() * * Time complexity: TODO */ int igraph_largest_weighted_cliques(const igraph_t *graph, const igraph_vector_t *vertex_weights, igraph_vector_ptr_t *res) { return igraph_i_largest_weighted_cliques(graph, vertex_weights, res); } /** * \function igraph_weighted_clique_number * \brief Find the weight of the largest weight clique in the graph * * The current implementation of this function * uses version 1.21 of the Cliquer library by Sampo Niskanen and * Patric R. J. Östergård, http://users.aalto.fi/~pat/cliquer.html * * Only positive integer vertex weights are supported. * * \param graph The input graph. * \param vertex_weights A vector of vertex weights. The current implementation * will truncate all weights to their integer parts. * \param res The largest weight will be returned to the \c igraph_real_t * pointed to by this variable. * \return Error code. * * \sa \ref igraph_weighted_cliques(), \ref igraph_largest_weighted_cliques(), \ref igraph_clique_number() * * Time complexity: TODO * */ int igraph_weighted_clique_number(const igraph_t *graph, const igraph_vector_t *vertex_weights, igraph_real_t *res) { return igraph_i_weighted_clique_number(graph, vertex_weights, res); } typedef int(*igraph_i_maximal_clique_func_t)(const igraph_vector_t*, void*, igraph_bool_t*); typedef struct { igraph_vector_ptr_t* result; igraph_integer_t min_size; igraph_integer_t max_size; } igraph_i_maximal_clique_data_t; int igraph_i_maximal_cliques(const igraph_t *graph, igraph_i_maximal_clique_func_t func, void* data); int igraph_i_maximal_or_largest_cliques_or_indsets(const igraph_t *graph, igraph_vector_ptr_t *res, igraph_integer_t *clique_number, igraph_bool_t keep_only_largest, igraph_bool_t complementer); /** * \function igraph_independent_vertex_sets * \brief Find all independent vertex sets in a graph * * * A vertex set is considered independent if there are no edges between * them. * * * If you are interested in the size of the largest independent vertex set, * use \ref igraph_independence_number() instead. * * * The current implementation was ported to igraph from the Very Nauty Graph * Library by Keith Briggs and uses the algorithm from the paper * S. Tsukiyama, M. Ide, H. Ariyoshi and I. Shirawaka. A new algorithm * for generating all the maximal independent sets. SIAM J Computing, * 6:505--517, 1977. * * \param graph The input graph. * \param res Pointer to a pointer vector, the result will be stored * here, ie. \c res will contain pointers to \c igraph_vector_t * objects which contain the indices of vertices involved in an independent * vertex set. The pointer vector will be resized if needed but note that the * objects in the pointer vector will not be freed. * \param min_size Integer giving the minimum size of the sets to be * returned. If negative or zero, no lower bound will be used. * \param max_size Integer giving the maximum size of the sets to be * returned. If negative or zero, no upper bound will be used. * \return Error code. * * \sa \ref igraph_largest_independent_vertex_sets(), * \ref igraph_independence_number(). * * Time complexity: TODO * * \example examples/simple/igraph_independent_sets.c */ int igraph_independent_vertex_sets(const igraph_t *graph, igraph_vector_ptr_t *res, igraph_integer_t min_size, igraph_integer_t max_size) { return igraph_i_cliques(graph, res, min_size, max_size, 1); } /** * \function igraph_largest_independent_vertex_sets * \brief Finds the largest independent vertex set(s) in a graph. * * * An independent vertex set is largest if there is no other * independent vertex set with more vertices in the graph. * * * The current implementation was ported to igraph from the Very Nauty Graph * Library by Keith Briggs and uses the algorithm from the paper * S. Tsukiyama, M. Ide, H. Ariyoshi and I. Shirawaka. A new algorithm * for generating all the maximal independent sets. SIAM J Computing, * 6:505--517, 1977. * * \param graph The input graph. * \param res Pointer to a pointer vector, the result will be stored * here. It will be resized as needed. * \return Error code. * * \sa \ref igraph_independent_vertex_sets(), \ref * igraph_maximal_independent_vertex_sets(). * * Time complexity: TODO */ int igraph_largest_independent_vertex_sets(const igraph_t *graph, igraph_vector_ptr_t *res) { return igraph_i_maximal_or_largest_cliques_or_indsets(graph, res, 0, 1, 0); } typedef struct igraph_i_max_ind_vsets_data_t { igraph_integer_t matrix_size; igraph_adjlist_t adj_list; /* Adjacency list of the graph */ igraph_vector_t deg; /* Degrees of individual nodes */ igraph_set_t* buckets; /* Bucket array */ /* The IS value for each node. Still to be explained :) */ igraph_integer_t* IS; igraph_integer_t largest_set_size; /* Size of the largest set encountered */ igraph_bool_t keep_only_largest; /* True if we keep only the largest sets */ } igraph_i_max_ind_vsets_data_t; int igraph_i_maximal_independent_vertex_sets_backtrack(const igraph_t *graph, igraph_vector_ptr_t *res, igraph_i_max_ind_vsets_data_t *clqdata, igraph_integer_t level) { long int v1, v2, v3, c, j, k; igraph_vector_int_t *neis1, *neis2; igraph_bool_t f; igraph_integer_t j1; long int it_state; IGRAPH_ALLOW_INTERRUPTION(); if (level >= clqdata->matrix_size - 1) { igraph_integer_t size = 0; if (res) { igraph_vector_t *vec; vec = igraph_Calloc(1, igraph_vector_t); if (vec == 0) { IGRAPH_ERROR("igraph_i_maximal_independent_vertex_sets failed", IGRAPH_ENOMEM); } IGRAPH_VECTOR_INIT_FINALLY(vec, 0); for (v1 = 0; v1 < clqdata->matrix_size; v1++) if (clqdata->IS[v1] == 0) { IGRAPH_CHECK(igraph_vector_push_back(vec, v1)); } size = (igraph_integer_t) igraph_vector_size(vec); if (!clqdata->keep_only_largest) { IGRAPH_CHECK(igraph_vector_ptr_push_back(res, vec)); } else { if (size > clqdata->largest_set_size) { /* We are keeping only the largest sets, and we've found one that's * larger than all previous sets, so we have to clear the list */ j = igraph_vector_ptr_size(res); for (v1 = 0; v1 < j; v1++) { igraph_vector_destroy(VECTOR(*res)[v1]); free(VECTOR(*res)[v1]); } igraph_vector_ptr_clear(res); IGRAPH_CHECK(igraph_vector_ptr_push_back(res, vec)); } else if (size == clqdata->largest_set_size) { IGRAPH_CHECK(igraph_vector_ptr_push_back(res, vec)); } else { igraph_vector_destroy(vec); free(vec); } } IGRAPH_FINALLY_CLEAN(1); } else { for (v1 = 0, size = 0; v1 < clqdata->matrix_size; v1++) if (clqdata->IS[v1] == 0) { size++; } } if (size > clqdata->largest_set_size) { clqdata->largest_set_size = size; } } else { v1 = level + 1; /* Count the number of vertices with an index less than v1 that have * an IS value of zero */ neis1 = igraph_adjlist_get(&clqdata->adj_list, v1); c = 0; j = 0; while (j < VECTOR(clqdata->deg)[v1] && (v2 = (long int) VECTOR(*neis1)[j]) <= level) { if (clqdata->IS[v2] == 0) { c++; } j++; } if (c == 0) { /* If there are no such nodes... */ j = 0; while (j < VECTOR(clqdata->deg)[v1] && (v2 = (long int) VECTOR(*neis1)[j]) <= level) { clqdata->IS[v2]++; j++; } IGRAPH_CHECK(igraph_i_maximal_independent_vertex_sets_backtrack(graph, res, clqdata, (igraph_integer_t) v1)); j = 0; while (j < VECTOR(clqdata->deg)[v1] && (v2 = (long int) VECTOR(*neis1)[j]) <= level) { clqdata->IS[v2]--; j++; } } else { /* If there are such nodes, store the count in the IS value of v1 */ clqdata->IS[v1] = (igraph_integer_t) c; IGRAPH_CHECK(igraph_i_maximal_independent_vertex_sets_backtrack(graph, res, clqdata, (igraph_integer_t) v1)); clqdata->IS[v1] = 0; f = 1; j = 0; while (j < VECTOR(clqdata->deg)[v1] && (v2 = (long int) VECTOR(*neis1)[j]) <= level) { if (clqdata->IS[v2] == 0) { IGRAPH_CHECK(igraph_set_add(&clqdata->buckets[v1], (igraph_integer_t) j)); neis2 = igraph_adjlist_get(&clqdata->adj_list, v2); k = 0; while (k < VECTOR(clqdata->deg)[v2] && (v3 = (long int) VECTOR(*neis2)[k]) <= level) { clqdata->IS[v3]--; if (clqdata->IS[v3] == 0) { f = 0; } k++; } } clqdata->IS[v2]++; j++; } if (f) { IGRAPH_CHECK(igraph_i_maximal_independent_vertex_sets_backtrack(graph, res, clqdata, (igraph_integer_t) v1)); } j = 0; while (j < VECTOR(clqdata->deg)[v1] && (v2 = (long int) VECTOR(*neis1)[j]) <= level) { clqdata->IS[v2]--; j++; } it_state = 0; while (igraph_set_iterate(&clqdata->buckets[v1], &it_state, &j1)) { j = (long)j1; v2 = (long int) VECTOR(*neis1)[j]; neis2 = igraph_adjlist_get(&clqdata->adj_list, v2); k = 0; while (k < VECTOR(clqdata->deg)[v2] && (v3 = (long int) VECTOR(*neis2)[k]) <= level) { clqdata->IS[v3]++; k++; } } igraph_set_clear(&clqdata->buckets[v1]); } } return 0; } void igraph_i_free_set_array(igraph_set_t* array) { long int i = 0; while (igraph_set_inited(array + i)) { igraph_set_destroy(array + i); i++; } igraph_Free(array); } /** * \function igraph_maximal_independent_vertex_sets * \brief Find all maximal independent vertex sets of a graph * * * A maximal independent vertex set is an independent vertex set which * can't be extended any more by adding a new vertex to it. * * * The algorithm used here is based on the following paper: * S. Tsukiyama, M. Ide, H. Ariyoshi and I. Shirawaka. A new algorithm for * generating all the maximal independent sets. SIAM J Computing, * 6:505--517, 1977. * * * The implementation was originally written by Kevin O'Neill and modified * by K M Briggs in the Very Nauty Graph Library. I simply re-wrote it to * use igraph's data structures. * * * If you are interested in the size of the largest independent vertex set, * use \ref igraph_independence_number() instead. * * \param graph The input graph. * \param res Pointer to a pointer vector, the result will be stored * here, ie. \c res will contain pointers to \c igraph_vector_t * objects which contain the indices of vertices involved in an independent * vertex set. The pointer vector will be resized if needed but note that the * objects in the pointer vector will not be freed. * \return Error code. * * \sa \ref igraph_maximal_cliques(), \ref * igraph_independence_number() * * Time complexity: TODO. */ int igraph_maximal_independent_vertex_sets(const igraph_t *graph, igraph_vector_ptr_t *res) { igraph_i_max_ind_vsets_data_t clqdata; igraph_integer_t no_of_nodes = (igraph_integer_t) igraph_vcount(graph), i; if (igraph_is_directed(graph)) { IGRAPH_WARNING("directionality of edges is ignored for directed graphs"); } clqdata.matrix_size = no_of_nodes; clqdata.keep_only_largest = 0; IGRAPH_CHECK(igraph_adjlist_init(graph, &clqdata.adj_list, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_adjlist_destroy, &clqdata.adj_list); clqdata.IS = igraph_Calloc(no_of_nodes, igraph_integer_t); if (clqdata.IS == 0) { IGRAPH_ERROR("igraph_maximal_independent_vertex_sets failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, clqdata.IS); IGRAPH_VECTOR_INIT_FINALLY(&clqdata.deg, no_of_nodes); for (i = 0; i < no_of_nodes; i++) { VECTOR(clqdata.deg)[i] = igraph_vector_int_size(igraph_adjlist_get(&clqdata.adj_list, i)); } clqdata.buckets = igraph_Calloc(no_of_nodes + 1, igraph_set_t); if (clqdata.buckets == 0) { IGRAPH_ERROR("igraph_maximal_independent_vertex_sets failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_i_free_set_array, clqdata.buckets); for (i = 0; i < no_of_nodes; i++) { IGRAPH_CHECK(igraph_set_init(&clqdata.buckets[i], 0)); } igraph_vector_ptr_clear(res); /* Do the show */ clqdata.largest_set_size = 0; IGRAPH_CHECK(igraph_i_maximal_independent_vertex_sets_backtrack(graph, res, &clqdata, 0)); /* Cleanup */ for (i = 0; i < no_of_nodes; i++) { igraph_set_destroy(&clqdata.buckets[i]); } igraph_adjlist_destroy(&clqdata.adj_list); igraph_vector_destroy(&clqdata.deg); igraph_free(clqdata.IS); igraph_free(clqdata.buckets); IGRAPH_FINALLY_CLEAN(4); return 0; } /** * \function igraph_independence_number * \brief Find the independence number of the graph * * * The independence number of a graph is the cardinality of the largest * independent vertex set. * * * The current implementation was ported to igraph from the Very Nauty Graph * Library by Keith Briggs and uses the algorithm from the paper * S. Tsukiyama, M. Ide, H. Ariyoshi and I. Shirawaka. A new algorithm * for generating all the maximal independent sets. SIAM J Computing, * 6:505--517, 1977. * * \param graph The input graph. * \param no The independence number will be returned to the \c * igraph_integer_t pointed by this variable. * \return Error code. * * \sa \ref igraph_independent_vertex_sets(). * * Time complexity: TODO. */ int igraph_independence_number(const igraph_t *graph, igraph_integer_t *no) { igraph_i_max_ind_vsets_data_t clqdata; igraph_integer_t no_of_nodes = (igraph_integer_t) igraph_vcount(graph), i; if (igraph_is_directed(graph)) { IGRAPH_WARNING("directionality of edges is ignored for directed graphs"); } clqdata.matrix_size = no_of_nodes; clqdata.keep_only_largest = 0; IGRAPH_CHECK(igraph_adjlist_init(graph, &clqdata.adj_list, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_adjlist_destroy, &clqdata.adj_list); clqdata.IS = igraph_Calloc(no_of_nodes, igraph_integer_t); if (clqdata.IS == 0) { IGRAPH_ERROR("igraph_independence_number failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, clqdata.IS); IGRAPH_VECTOR_INIT_FINALLY(&clqdata.deg, no_of_nodes); for (i = 0; i < no_of_nodes; i++) { VECTOR(clqdata.deg)[i] = igraph_vector_int_size(igraph_adjlist_get(&clqdata.adj_list, i)); } clqdata.buckets = igraph_Calloc(no_of_nodes + 1, igraph_set_t); if (clqdata.buckets == 0) { IGRAPH_ERROR("igraph_independence_number failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_i_free_set_array, clqdata.buckets); for (i = 0; i < no_of_nodes; i++) { IGRAPH_CHECK(igraph_set_init(&clqdata.buckets[i], 0)); } /* Do the show */ clqdata.largest_set_size = 0; IGRAPH_CHECK(igraph_i_maximal_independent_vertex_sets_backtrack(graph, 0, &clqdata, 0)); *no = clqdata.largest_set_size; /* Cleanup */ for (i = 0; i < no_of_nodes; i++) { igraph_set_destroy(&clqdata.buckets[i]); } igraph_adjlist_destroy(&clqdata.adj_list); igraph_vector_destroy(&clqdata.deg); igraph_free(clqdata.IS); igraph_free(clqdata.buckets); IGRAPH_FINALLY_CLEAN(4); return 0; } /*************************************************************************/ /* MAXIMAL CLIQUES, LARGEST CLIQUES */ /*************************************************************************/ int igraph_i_maximal_cliques_store_max_size(const igraph_vector_t* clique, void* data, igraph_bool_t* cont) { igraph_integer_t* result = (igraph_integer_t*)data; IGRAPH_UNUSED(cont); if (*result < igraph_vector_size(clique)) { *result = (igraph_integer_t) igraph_vector_size(clique); } return IGRAPH_SUCCESS; } int igraph_i_maximal_cliques_store(const igraph_vector_t* clique, void* data, igraph_bool_t* cont) { igraph_vector_ptr_t* result = (igraph_vector_ptr_t*)data; igraph_vector_t* vec; IGRAPH_UNUSED(cont); vec = igraph_Calloc(1, igraph_vector_t); if (vec == 0) { IGRAPH_ERROR("cannot allocate memory for storing next clique", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_copy(vec, clique)); IGRAPH_CHECK(igraph_vector_ptr_push_back(result, vec)); return IGRAPH_SUCCESS; } int igraph_i_maximal_cliques_store_size_check(const igraph_vector_t* clique, void* data_, igraph_bool_t* cont) { igraph_i_maximal_clique_data_t* data = (igraph_i_maximal_clique_data_t*)data_; igraph_vector_t* vec; igraph_integer_t size = (igraph_integer_t) igraph_vector_size(clique); IGRAPH_UNUSED(cont); if (size < data->min_size || size > data->max_size) { return IGRAPH_SUCCESS; } vec = igraph_Calloc(1, igraph_vector_t); if (vec == 0) { IGRAPH_ERROR("cannot allocate memory for storing next clique", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_copy(vec, clique)); IGRAPH_CHECK(igraph_vector_ptr_push_back(data->result, vec)); return IGRAPH_SUCCESS; } int igraph_i_largest_cliques_store(const igraph_vector_t* clique, void* data, igraph_bool_t* cont) { igraph_vector_ptr_t* result = (igraph_vector_ptr_t*)data; igraph_vector_t* vec; long int i, n; IGRAPH_UNUSED(cont); /* Is the current clique at least as large as the others that we have found? */ if (!igraph_vector_ptr_empty(result)) { n = igraph_vector_size(clique); if (n < igraph_vector_size(VECTOR(*result)[0])) { return IGRAPH_SUCCESS; } if (n > igraph_vector_size(VECTOR(*result)[0])) { for (i = 0; i < igraph_vector_ptr_size(result); i++) { igraph_vector_destroy(VECTOR(*result)[i]); } igraph_vector_ptr_free_all(result); igraph_vector_ptr_resize(result, 0); } } vec = igraph_Calloc(1, igraph_vector_t); if (vec == 0) { IGRAPH_ERROR("cannot allocate memory for storing next clique", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_copy(vec, clique)); IGRAPH_CHECK(igraph_vector_ptr_push_back(result, vec)); return IGRAPH_SUCCESS; } /** * \function igraph_largest_cliques * \brief Finds the largest clique(s) in a graph. * * * A clique is largest (quite intuitively) if there is no other clique * in the graph which contains more vertices. * * * Note that this is not necessarily the same as a maximal clique, * ie. the largest cliques are always maximal but a maximal clique is * not always largest. * * The current implementation of this function searches * for maximal cliques using \ref igraph_maximal_cliques() and drops * those that are not the largest. * * The implementation of this function changed between * igraph 0.5 and 0.6, so the order of the cliques and the order of * vertices within the cliques will almost surely be different between * these two versions. * * \param graph The input graph. * \param res Pointer to an initialized pointer vector, the result * will be stored here. It will be resized as needed. Note that * vertices of a clique may be returned in arbitrary order. * \return Error code. * * \sa \ref igraph_cliques(), \ref igraph_maximal_cliques() * * Time complexity: O(3^(|V|/3)) worst case. */ int igraph_largest_cliques(const igraph_t *graph, igraph_vector_ptr_t *res) { igraph_vector_ptr_clear(res); IGRAPH_FINALLY(igraph_i_cliques_free_res, res); IGRAPH_CHECK(igraph_i_maximal_cliques(graph, &igraph_i_largest_cliques_store, (void*)res)); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } /** * \function igraph_clique_number * \brief Find the clique number of the graph * * * The clique number of a graph is the size of the largest clique. * * \param graph The input graph. * \param no The clique number will be returned to the \c igraph_integer_t * pointed by this variable. * \return Error code. * * \sa \ref igraph_cliques(), \ref igraph_largest_cliques(). * * Time complexity: O(3^(|V|/3)) worst case. */ int igraph_clique_number(const igraph_t *graph, igraph_integer_t *no) { *no = 0; return igraph_i_maximal_cliques(graph, &igraph_i_maximal_cliques_store_max_size, (void*)no); } typedef struct { igraph_vector_int_t cand; igraph_vector_int_t fini; igraph_vector_int_t cand_filtered; } igraph_i_maximal_cliques_stack_frame; void igraph_i_maximal_cliques_stack_frame_destroy(igraph_i_maximal_cliques_stack_frame *frame) { igraph_vector_int_destroy(&frame->cand); igraph_vector_int_destroy(&frame->fini); igraph_vector_int_destroy(&frame->cand_filtered); } void igraph_i_maximal_cliques_stack_destroy(igraph_stack_ptr_t *stack) { igraph_i_maximal_cliques_stack_frame *frame; while (!igraph_stack_ptr_empty(stack)) { frame = (igraph_i_maximal_cliques_stack_frame*)igraph_stack_ptr_pop(stack); igraph_i_maximal_cliques_stack_frame_destroy(frame); free(frame); } igraph_stack_ptr_destroy(stack); } int igraph_i_maximal_cliques(const igraph_t *graph, igraph_i_maximal_clique_func_t func, void* data) { int directed = igraph_is_directed(graph); long int i, j, k, l; igraph_integer_t no_of_nodes, nodes_to_check, nodes_done; igraph_integer_t best_cand = 0, best_cand_degree = 0, best_fini_cand_degree; igraph_adjlist_t adj_list; igraph_stack_ptr_t stack; igraph_i_maximal_cliques_stack_frame frame, *new_frame_ptr; igraph_vector_t clique; igraph_vector_int_t new_cand, new_fini, cn, best_cand_nbrs, best_fini_cand_nbrs; igraph_bool_t cont = 1; int assret; if (directed) { IGRAPH_WARNING("directionality of edges is ignored for directed graphs"); } no_of_nodes = igraph_vcount(graph); if (no_of_nodes == 0) { return IGRAPH_SUCCESS; } /* Construct an adjacency list representation */ IGRAPH_CHECK(igraph_adjlist_init(graph, &adj_list, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_adjlist_destroy, &adj_list); IGRAPH_CHECK(igraph_adjlist_simplify(&adj_list)); igraph_adjlist_sort(&adj_list); /* Initialize stack */ IGRAPH_CHECK(igraph_stack_ptr_init(&stack, 0)); IGRAPH_FINALLY(igraph_i_maximal_cliques_stack_destroy, &stack); /* Create the initial (empty) clique */ IGRAPH_VECTOR_INIT_FINALLY(&clique, 0); /* Initialize new_cand, new_fini, cn, best_cand_nbrs and best_fini_cand_nbrs (will be used later) */ igraph_vector_int_init(&new_cand, 0); IGRAPH_FINALLY(igraph_vector_int_destroy, &new_cand); igraph_vector_int_init(&new_fini, 0); IGRAPH_FINALLY(igraph_vector_int_destroy, &new_fini); igraph_vector_int_init(&cn, 0); IGRAPH_FINALLY(igraph_vector_int_destroy, &cn); igraph_vector_int_init(&best_cand_nbrs, 0); IGRAPH_FINALLY(igraph_vector_int_destroy, &best_cand_nbrs); igraph_vector_int_init(&best_fini_cand_nbrs, 0); IGRAPH_FINALLY(igraph_vector_int_destroy, &best_fini_cand_nbrs); /* Find the vertex with the highest degree */ best_cand = 0; best_cand_degree = (igraph_integer_t) igraph_vector_int_size(igraph_adjlist_get(&adj_list, 0)); for (i = 1; i < no_of_nodes; i++) { j = igraph_vector_int_size(igraph_adjlist_get(&adj_list, i)); if (j > best_cand_degree) { best_cand = (igraph_integer_t) i; best_cand_degree = (igraph_integer_t) j; } } /* Create the initial stack frame */ IGRAPH_CHECK(igraph_vector_int_init_seq(&frame.cand, 0, no_of_nodes - 1)); IGRAPH_FINALLY(igraph_vector_int_destroy, &frame.cand); IGRAPH_CHECK(igraph_vector_int_init(&frame.fini, 0)); IGRAPH_FINALLY(igraph_vector_int_destroy, &frame.fini); IGRAPH_CHECK(igraph_vector_int_init(&frame.cand_filtered, 0)); IGRAPH_FINALLY(igraph_vector_int_destroy, &frame.cand_filtered); IGRAPH_CHECK(igraph_vector_int_difference_sorted(&frame.cand, igraph_adjlist_get(&adj_list, best_cand), &frame.cand_filtered)); IGRAPH_FINALLY_CLEAN(3); IGRAPH_FINALLY(igraph_i_maximal_cliques_stack_frame_destroy, &frame); /* TODO: frame.cand and frame.fini should be a set instead of a vector */ /* Main loop starts here */ nodes_to_check = (igraph_integer_t) igraph_vector_int_size(&frame.cand_filtered); nodes_done = 0; while (!igraph_vector_int_empty(&frame.cand_filtered) || !igraph_stack_ptr_empty(&stack)) { if (igraph_vector_int_empty(&frame.cand_filtered)) { /* No candidates left to check in this stack frame, pop out the previous stack frame */ igraph_i_maximal_cliques_stack_frame *newframe = igraph_stack_ptr_pop(&stack); igraph_i_maximal_cliques_stack_frame_destroy(&frame); frame = *newframe; free(newframe); if (igraph_stack_ptr_size(&stack) == 1) { /* We will be using the next candidate node in the next iteration, so we can increase * nodes_done by 1 */ nodes_done++; } /* For efficiency reasons, we only check for interruption and show progress here */ IGRAPH_PROGRESS("Maximal cliques: ", 100.0 * nodes_done / nodes_to_check, NULL); IGRAPH_ALLOW_INTERRUPTION(); igraph_vector_pop_back(&clique); continue; } /* Try the next node in the clique */ i = (long int) igraph_vector_int_pop_back(&frame.cand_filtered); IGRAPH_CHECK(igraph_vector_push_back(&clique, i)); /* Remove the node from the candidate list */ assret = igraph_vector_int_binsearch(&frame.cand, i, &j); assert(assret); igraph_vector_int_remove(&frame.cand, j); /* Add the node to the finished list */ assret = !igraph_vector_int_binsearch(&frame.fini, i, &j); assert(assret); IGRAPH_CHECK(igraph_vector_int_insert(&frame.fini, j, i)); /* Create new_cand and new_fini */ IGRAPH_CHECK(igraph_vector_int_intersect_sorted(&frame.cand, igraph_adjlist_get(&adj_list, i), &new_cand)); IGRAPH_CHECK(igraph_vector_int_intersect_sorted(&frame.fini, igraph_adjlist_get(&adj_list, i), &new_fini)); /* Do we have anything more to search? */ if (igraph_vector_int_empty(&new_cand)) { if (igraph_vector_int_empty(&new_fini)) { /* We have a maximal clique here */ IGRAPH_CHECK(func(&clique, data, &cont)); if (!cont) { /* The callback function requested to stop the search */ break; } } igraph_vector_pop_back(&clique); continue; } if (igraph_vector_int_empty(&new_fini) && igraph_vector_int_size(&new_cand) == 1) { /* Shortcut: only one node left */ IGRAPH_CHECK(igraph_vector_push_back(&clique, VECTOR(new_cand)[0])); IGRAPH_CHECK(func(&clique, data, &cont)); if (!cont) { /* The callback function requested to stop the search */ break; } igraph_vector_pop_back(&clique); igraph_vector_pop_back(&clique); continue; } /* Find the next best candidate node in new_fini */ l = igraph_vector_int_size(&new_cand); best_cand_degree = -1; j = igraph_vector_int_size(&new_fini); for (i = 0; i < j; i++) { k = (long int)VECTOR(new_fini)[i]; IGRAPH_CHECK(igraph_vector_int_intersect_sorted(&new_cand, igraph_adjlist_get(&adj_list, k), &cn)); if (igraph_vector_int_size(&cn) > best_cand_degree) { best_cand_degree = (igraph_integer_t) igraph_vector_int_size(&cn); IGRAPH_CHECK(igraph_vector_int_update(&best_fini_cand_nbrs, &cn)); if (best_cand_degree == l) { /* Cool, we surely have the best candidate node here as best_cand_degree can't get any better */ break; } } } /* Shortcut here: we don't have to examine new_cand */ if (best_cand_degree == l) { igraph_vector_pop_back(&clique); continue; } /* Still finding best candidate node */ best_fini_cand_degree = best_cand_degree; best_cand_degree = -1; j = igraph_vector_int_size(&new_cand); l = l - 1; for (i = 0; i < j; i++) { k = (long int)VECTOR(new_cand)[i]; IGRAPH_CHECK(igraph_vector_int_intersect_sorted(&new_cand, igraph_adjlist_get(&adj_list, k), &cn)); if (igraph_vector_int_size(&cn) > best_cand_degree) { best_cand_degree = (igraph_integer_t) igraph_vector_int_size(&cn); IGRAPH_CHECK(igraph_vector_int_update(&best_cand_nbrs, &cn)); if (best_cand_degree == l) { /* Cool, we surely have the best candidate node here as best_cand_degree can't get any better */ break; } } } /* Create a new stack frame in case we back out later */ new_frame_ptr = igraph_Calloc(1, igraph_i_maximal_cliques_stack_frame); if (new_frame_ptr == 0) { IGRAPH_ERROR("cannot allocate new stack frame", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, new_frame_ptr); *new_frame_ptr = frame; memset(&frame, 0, sizeof(frame)); IGRAPH_CHECK(igraph_stack_ptr_push(&stack, new_frame_ptr)); IGRAPH_FINALLY_CLEAN(1); /* ownership of new_frame_ptr taken by the stack */ /* Ownership of the current frame and its vectors (frame.cand, frame.done, frame.cand_filtered) * is taken by the stack from now on. Vectors in frame must be re-initialized with new_cand, * new_fini and stuff. The old frame.cand and frame.fini won't be leaked because they are * managed by the stack now. */ frame.cand = new_cand; frame.fini = new_fini; IGRAPH_CHECK(igraph_vector_int_init(&new_cand, 0)); IGRAPH_CHECK(igraph_vector_int_init(&new_fini, 0)); IGRAPH_CHECK(igraph_vector_int_init(&frame.cand_filtered, 0)); /* Adjust frame.cand_filtered */ if (best_cand_degree < best_fini_cand_degree) { IGRAPH_CHECK(igraph_vector_int_difference_sorted(&frame.cand, &best_fini_cand_nbrs, &frame.cand_filtered)); } else { IGRAPH_CHECK(igraph_vector_int_difference_sorted(&frame.cand, &best_cand_nbrs, &frame.cand_filtered)); } } IGRAPH_PROGRESS("Maximal cliques: ", 100.0, NULL); igraph_adjlist_destroy(&adj_list); igraph_vector_destroy(&clique); igraph_vector_int_destroy(&new_cand); igraph_vector_int_destroy(&new_fini); igraph_vector_int_destroy(&cn); igraph_vector_int_destroy(&best_cand_nbrs); igraph_vector_int_destroy(&best_fini_cand_nbrs); igraph_i_maximal_cliques_stack_frame_destroy(&frame); igraph_i_maximal_cliques_stack_destroy(&stack); IGRAPH_FINALLY_CLEAN(9); return IGRAPH_SUCCESS; } int igraph_i_maximal_or_largest_cliques_or_indsets(const igraph_t *graph, igraph_vector_ptr_t *res, igraph_integer_t *clique_number, igraph_bool_t keep_only_largest, igraph_bool_t complementer) { igraph_i_max_ind_vsets_data_t clqdata; igraph_integer_t no_of_nodes = (igraph_integer_t) igraph_vcount(graph), i; if (igraph_is_directed(graph)) { IGRAPH_WARNING("directionality of edges is ignored for directed graphs"); } clqdata.matrix_size = no_of_nodes; clqdata.keep_only_largest = keep_only_largest; if (complementer) { IGRAPH_CHECK(igraph_adjlist_init_complementer(graph, &clqdata.adj_list, IGRAPH_ALL, 0)); } else { IGRAPH_CHECK(igraph_adjlist_init(graph, &clqdata.adj_list, IGRAPH_ALL)); } IGRAPH_FINALLY(igraph_adjlist_destroy, &clqdata.adj_list); clqdata.IS = igraph_Calloc(no_of_nodes, igraph_integer_t); if (clqdata.IS == 0) { IGRAPH_ERROR("igraph_i_maximal_or_largest_cliques_or_indsets failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, clqdata.IS); IGRAPH_VECTOR_INIT_FINALLY(&clqdata.deg, no_of_nodes); for (i = 0; i < no_of_nodes; i++) { VECTOR(clqdata.deg)[i] = igraph_vector_int_size(igraph_adjlist_get(&clqdata.adj_list, i)); } clqdata.buckets = igraph_Calloc(no_of_nodes + 1, igraph_set_t); if (clqdata.buckets == 0) { IGRAPH_ERROR("igraph_maximal_or_largest_cliques_or_indsets failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_i_free_set_array, clqdata.buckets); for (i = 0; i < no_of_nodes; i++) { IGRAPH_CHECK(igraph_set_init(&clqdata.buckets[i], 0)); } if (res) { igraph_vector_ptr_clear(res); } /* Do the show */ clqdata.largest_set_size = 0; IGRAPH_CHECK(igraph_i_maximal_independent_vertex_sets_backtrack(graph, res, &clqdata, 0)); /* Cleanup */ for (i = 0; i < no_of_nodes; i++) { igraph_set_destroy(&clqdata.buckets[i]); } igraph_adjlist_destroy(&clqdata.adj_list); igraph_vector_destroy(&clqdata.deg); igraph_free(clqdata.IS); igraph_free(clqdata.buckets); IGRAPH_FINALLY_CLEAN(4); if (clique_number) { *clique_number = clqdata.largest_set_size; } return 0; } python-igraph-0.8.0/vendor/source/igraph/src/gengraph_powerlaw.h0000644000076500000240000000571613614300625025273 0ustar tamasstaff00000000000000/* * * gengraph - generation of random simple connected graphs with prescribed * degree sequence * * Copyright (C) 2006 Fabien Viger * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #ifndef _POWERLAW_H #define _POWERLAW_H // pascalou #ifndef pascalou #include "gengraph_definitions.h" #endif // Discrete integer power-law : P(X=min+k) is proportionnal to (k+k0)^-alpha // - possibility to determine a range [Min, Max] of possible samples // - possibility to automatically compute k0 to obtain a given mean z namespace gengraph { #define POWERLAW_TABLE 10000 class powerlaw { private: double alpha; // Exponent int mini; // Minimum sample int maxi; // Maximum sample double offset; // Offset int tabulated; // Number of values to tabulate int *table; // Table containing cumulative distribution for k=mini..mini+tabulated-1 int *dt; // Table delimiters int max_dt; // number of delimiters - 1 double proba_big; // Probability to take a non-tabulated value double table_mul; // equal to (1-proba_big)/(RAND_MAX+1) // Sample a non-tabulated value >= mini+tabulated inline double big_sample(double randomfloat) { return double(mini) + pow(_a * randomfloat + _b, _exp) - offset; } inline double big_inv_sample(double s) { return (pow(s - double(mini) + offset, 1.0 / _exp) - _b) / _a; } double _exp, _a, _b; // Cached values used by big_sample(); // Dichotomic adjust of offset, so that to_adjust() returns value with // a precision of eps. Note that to_adjust() must be an increasing function of offset. void adjust_offset_mean(double value, double eps, double fac); public: int sample(); // Return a random integer double proba(int); // Return probability to return integer double error(); // Returns relative numerical error done by this class double mean(); // Returns mean of the sampler int median(); // Returns median of the sampler // Initialize the power-law sampler. void init_to_offset(double, int); // Same, but also returns the offset found double init_to_mean(double); double init_to_median(double); inline void init() { init_to_offset(double(mini), POWERLAW_TABLE); }; ~powerlaw(); powerlaw(double exponent, int mini, int maxi = -1); }; } // namespace gengraph #endif //_POWERLAW_H python-igraph-0.8.0/vendor/source/igraph/src/structural_properties.c0000644000076500000240000100603113614300625026227 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=4 sw=4 sts=4 et: */ /* IGraph library. Copyright (C) 2005-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_structural.h" #include "igraph_transitivity.h" #include "igraph_paths.h" #include "igraph_math.h" #include "igraph_memory.h" #include "igraph_random.h" #include "igraph_adjlist.h" #include "igraph_interface.h" #include "igraph_progress.h" #include "igraph_interrupt_internal.h" #include "igraph_centrality.h" #include "igraph_components.h" #include "igraph_constructors.h" #include "igraph_conversion.h" #include "igraph_types_internal.h" #include "igraph_dqueue.h" #include "igraph_attributes.h" #include "igraph_neighborhood.h" #include "igraph_topology.h" #include "igraph_qsort.h" #include "config.h" #include "structural_properties_internal.h" #include #include #include /** * \section about_structural * * These functions usually calculate some structural property * of a graph, like its diameter, the degree of the nodes, etc. */ /** * \ingroup structural * \function igraph_diameter * \brief Calculates the diameter of a graph (longest geodesic). * * \param graph The graph object. * \param pres Pointer to an integer, if not \c NULL then it will contain * the diameter (the actual distance). * \param pfrom Pointer to an integer, if not \c NULL it will be set to the * source vertex of the diameter path. * \param pto Pointer to an integer, if not \c NULL it will be set to the * target vertex of the diameter path. * \param path Pointer to an initialized vector. If not \c NULL the actual * longest geodesic path will be stored here. The vector will be * resized as needed. * \param directed Boolean, whether to consider directed * paths. Ignored for undirected graphs. * \param unconn What to do if the graph is not connected. If * \c TRUE the longest geodesic within a component * will be returned, otherwise the number of vertices is * returned. (The rationale behind the latter is that this is * always longer than the longest possible diameter in a * graph.) * \return Error code: * \c IGRAPH_ENOMEM, not enough memory for * temporary data. * * Time complexity: O(|V||E|), the * number of vertices times the number of edges. * * \example examples/simple/igraph_diameter.c */ int igraph_diameter(const igraph_t *graph, igraph_integer_t *pres, igraph_integer_t *pfrom, igraph_integer_t *pto, igraph_vector_t *path, igraph_bool_t directed, igraph_bool_t unconn) { long int no_of_nodes = igraph_vcount(graph); long int i, j, n; long int *already_added; long int nodes_reached; long int from = 0, to = 0; long int res = 0; igraph_dqueue_t q = IGRAPH_DQUEUE_NULL; igraph_vector_int_t *neis; igraph_neimode_t dirmode; igraph_adjlist_t allneis; if (directed) { dirmode = IGRAPH_OUT; } else { dirmode = IGRAPH_ALL; } already_added = igraph_Calloc(no_of_nodes, long int); if (already_added == 0) { IGRAPH_ERROR("diameter failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, already_added); IGRAPH_DQUEUE_INIT_FINALLY(&q, 100); IGRAPH_CHECK(igraph_adjlist_init(graph, &allneis, dirmode)); IGRAPH_FINALLY(igraph_adjlist_destroy, &allneis); for (i = 0; i < no_of_nodes; i++) { nodes_reached = 1; IGRAPH_CHECK(igraph_dqueue_push(&q, i)); IGRAPH_CHECK(igraph_dqueue_push(&q, 0)); already_added[i] = i + 1; IGRAPH_PROGRESS("Diameter: ", 100.0 * i / no_of_nodes, NULL); IGRAPH_ALLOW_INTERRUPTION(); while (!igraph_dqueue_empty(&q)) { long int actnode = (long int) igraph_dqueue_pop(&q); long int actdist = (long int) igraph_dqueue_pop(&q); if (actdist > res) { res = actdist; from = i; to = actnode; } neis = igraph_adjlist_get(&allneis, actnode); n = igraph_vector_int_size(neis); for (j = 0; j < n; j++) { long int neighbor = (long int) VECTOR(*neis)[j]; if (already_added[neighbor] == i + 1) { continue; } already_added[neighbor] = i + 1; nodes_reached++; IGRAPH_CHECK(igraph_dqueue_push(&q, neighbor)); IGRAPH_CHECK(igraph_dqueue_push(&q, actdist + 1)); } } /* while !igraph_dqueue_empty */ /* not connected, return largest possible */ if (nodes_reached != no_of_nodes && !unconn) { res = no_of_nodes; from = -1; to = -1; break; } } /* for i 0) { *res /= normfact; } else { *res = IGRAPH_NAN; } /* clean */ igraph_Free(already_added); igraph_dqueue_destroy(&q); igraph_adjlist_destroy(&allneis); IGRAPH_FINALLY_CLEAN(3); return 0; } /** * \function igraph_path_length_hist * Create a histogram of all shortest path lengths. * * This function calculates a histogram, by calculating the * shortest path length between each pair of vertices. For directed * graphs both directions might be considered and then every pair of vertices * appears twice in the histogram. * \param graph The input graph. * \param res Pointer to an initialized vector, the result is stored * here. The first (i.e. zeroth) element contains the number of * shortest paths of length 1, etc. The supplied vector is resized * as needed. * \param unconnected Pointer to a real number, the number of * pairs for which the second vertex is not reachable from the * first is stored here. * \param directed Whether to consider directed paths in a directed * graph (if not zero). This argument is ignored for undirected * graphs. * \return Error code. * * Time complexity: O(|V||E|), the number of vertices times the number * of edges. * * \sa \ref igraph_average_path_length() and \ref igraph_shortest_paths() */ int igraph_path_length_hist(const igraph_t *graph, igraph_vector_t *res, igraph_real_t *unconnected, igraph_bool_t directed) { long int no_of_nodes = igraph_vcount(graph); long int i, j, n; igraph_vector_long_t already_added; long int nodes_reached; igraph_dqueue_t q = IGRAPH_DQUEUE_NULL; igraph_vector_int_t *neis; igraph_neimode_t dirmode; igraph_adjlist_t allneis; igraph_real_t unconn = 0; long int ressize; if (directed) { dirmode = IGRAPH_OUT; } else { dirmode = IGRAPH_ALL; } IGRAPH_CHECK(igraph_vector_long_init(&already_added, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_long_destroy, &already_added); IGRAPH_DQUEUE_INIT_FINALLY(&q, 100); IGRAPH_CHECK(igraph_adjlist_init(graph, &allneis, dirmode)); IGRAPH_FINALLY(igraph_adjlist_destroy, &allneis); IGRAPH_CHECK(igraph_vector_resize(res, 0)); ressize = 0; for (i = 0; i < no_of_nodes; i++) { nodes_reached = 1; /* itself */ IGRAPH_CHECK(igraph_dqueue_push(&q, i)); IGRAPH_CHECK(igraph_dqueue_push(&q, 0)); VECTOR(already_added)[i] = i + 1; IGRAPH_PROGRESS("Path-hist: ", 100.0 * i / no_of_nodes, NULL); IGRAPH_ALLOW_INTERRUPTION(); while (!igraph_dqueue_empty(&q)) { long int actnode = (long int) igraph_dqueue_pop(&q); long int actdist = (long int) igraph_dqueue_pop(&q); neis = igraph_adjlist_get(&allneis, actnode); n = igraph_vector_int_size(neis); for (j = 0; j < n; j++) { long int neighbor = (long int) VECTOR(*neis)[j]; if (VECTOR(already_added)[neighbor] == i + 1) { continue; } VECTOR(already_added)[neighbor] = i + 1; nodes_reached++; if (actdist + 1 > ressize) { IGRAPH_CHECK(igraph_vector_resize(res, actdist + 1)); for (; ressize < actdist + 1; ressize++) { VECTOR(*res)[ressize] = 0; } } VECTOR(*res)[actdist] += 1; IGRAPH_CHECK(igraph_dqueue_push(&q, neighbor)); IGRAPH_CHECK(igraph_dqueue_push(&q, actdist + 1)); } } /* while !igraph_dqueue_empty */ unconn += (no_of_nodes - nodes_reached); } /* for i * If there is more than one geodesic between two vertices, this * function gives only one of them. * \param graph The graph object. * \param vertices The result, the ids of the vertices along the paths. * This is a pointer vector, each element points to a vector * object. These should be initialized before passing them to * the function, which will properly clear and/or resize them * and fill the ids of the vertices along the geodesics from/to * the vertices. Supply a null pointer here if you don't need * these vectors. * \param edges The result, the ids of the edges along the paths. * This is a pointer vector, each element points to a vector * object. These should be initialized before passing them to * the function, which will properly clear and/or resize them * and fill the ids of the vertices along the geodesics from/to * the vertices. Supply a null pointer here if you don't need * these vectors. * \param from The id of the vertex from/to which the geodesics are * calculated. * \param to Vertex sequence with the ids of the vertices to/from which the * shortest paths will be calculated. A vertex might be given multiple * times. * \param mode The type of shortest paths to be used for the * calculation in directed graphs. Possible values: * \clist * \cli IGRAPH_OUT * the outgoing paths are calculated. * \cli IGRAPH_IN * the incoming paths are calculated. * \cli IGRAPH_ALL * the directed graph is considered as an * undirected one for the computation. * \endclist * \param predecessors A pointer to an initialized igraph vector or null. * If not null, a vector containing the predecessor of each vertex in * the single source shortest path tree is returned here. The * predecessor of vertex i in the tree is the vertex from which vertex i * was reached. The predecessor of the start vertex (in the \c from * argument) is itself by definition. If the predecessor is -1, it means * that the given vertex was not reached from the source during the * search. Note that the search terminates if all the vertices in * \c to are reached. * \param inbound_edges A pointer to an initialized igraph vector or null. * If not null, a vector containing the inbound edge of each vertex in * the single source shortest path tree is returned here. The * inbound edge of vertex i in the tree is the edge via which vertex i * was reached. The start vertex and vertices that were not reached * during the search will have -1 in the corresponding entry of the * vector. Note that the search terminates if all the vertices in * \c to are reached. * * \return Error code: * \clist * \cli IGRAPH_ENOMEM * not enough memory for temporary data. * \cli IGRAPH_EINVVID * \p from is invalid vertex id, or the length of \p to is * not the same as the length of \p res. * \cli IGRAPH_EINVMODE * invalid mode argument. * \endclist * * Time complexity: O(|V|+|E|), * |V| is the number of vertices, * |E| the number of edges in the * graph. * * \sa \ref igraph_shortest_paths() if you only need the path length but * not the paths themselves. * * \example examples/simple/igraph_get_shortest_paths.c */ int igraph_get_shortest_paths(const igraph_t *graph, igraph_vector_ptr_t *vertices, igraph_vector_ptr_t *edges, igraph_integer_t from, const igraph_vs_t to, igraph_neimode_t mode, igraph_vector_long_t *predecessors, igraph_vector_long_t *inbound_edges) { /* TODO: use inclist_t if to is long (longer than 1?) */ long int no_of_nodes = igraph_vcount(graph); long int *father; igraph_dqueue_t q = IGRAPH_DQUEUE_NULL; long int i, j; igraph_vector_t tmp = IGRAPH_VECTOR_NULL; igraph_vit_t vit; long int to_reach; long int reached = 0; if (from < 0 || from >= no_of_nodes) { IGRAPH_ERROR("cannot get shortest paths", IGRAPH_EINVVID); } if (mode != IGRAPH_OUT && mode != IGRAPH_IN && mode != IGRAPH_ALL) { IGRAPH_ERROR("Invalid mode argument", IGRAPH_EINVMODE); } IGRAPH_CHECK(igraph_vit_create(graph, to, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); if (vertices && IGRAPH_VIT_SIZE(vit) != igraph_vector_ptr_size(vertices)) { IGRAPH_ERROR("Size of the `vertices' and the `to' should match", IGRAPH_EINVAL); } if (edges && IGRAPH_VIT_SIZE(vit) != igraph_vector_ptr_size(edges)) { IGRAPH_ERROR("Size of the `edges' and the `to' should match", IGRAPH_EINVAL); } father = igraph_Calloc(no_of_nodes, long int); if (father == 0) { IGRAPH_ERROR("cannot get shortest paths", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, father); IGRAPH_VECTOR_INIT_FINALLY(&tmp, 0); IGRAPH_DQUEUE_INIT_FINALLY(&q, 100); /* Mark the vertices we need to reach */ to_reach = IGRAPH_VIT_SIZE(vit); for (IGRAPH_VIT_RESET(vit); !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit)) { if (father[ (long int) IGRAPH_VIT_GET(vit) ] == 0) { father[ (long int) IGRAPH_VIT_GET(vit) ] = -1; } else { to_reach--; /* this node was given multiple times */ } } /* Meaning of father[i]: * * - If father[i] < 0, it means that vertex i has to be reached and has not * been reached yet. * * - If father[i] = 0, it means that vertex i does not have to be reached and * it has not been reached yet. * * - If father[i] = 1, it means that vertex i is the start vertex. * * - Otherwise, father[i] is the ID of the edge from which vertex i was * reached plus 2. */ IGRAPH_CHECK(igraph_dqueue_push(&q, from + 1)); if (father[ (long int) from ] < 0) { reached++; } father[ (long int)from ] = 1; while (!igraph_dqueue_empty(&q) && reached < to_reach) { long int act = (long int) igraph_dqueue_pop(&q) - 1; IGRAPH_CHECK(igraph_incident(graph, &tmp, (igraph_integer_t) act, mode)); for (j = 0; j < igraph_vector_size(&tmp); j++) { long int edge = (long int) VECTOR(tmp)[j]; long int neighbor = IGRAPH_OTHER(graph, edge, act); if (father[neighbor] > 0) { continue; } else if (father[neighbor] < 0) { reached++; } father[neighbor] = edge + 2; IGRAPH_CHECK(igraph_dqueue_push(&q, neighbor + 1)); } } if (reached < to_reach) { IGRAPH_WARNING("Couldn't reach some vertices"); } /* Create `predecessors' if needed */ if (predecessors) { IGRAPH_CHECK(igraph_vector_long_resize(predecessors, no_of_nodes)); for (i = 0; i < no_of_nodes; i++) { if (father[i] <= 0) { /* i was not reached */ VECTOR(*predecessors)[i] = -1; } else if (father[i] == 1) { /* i is the start vertex */ VECTOR(*predecessors)[i] = i; } else { /* i was reached via the edge with ID = father[i] - 2 */ VECTOR(*predecessors)[i] = IGRAPH_OTHER(graph, father[i] - 2, i); } } } /* Create `inbound_edges' if needed */ if (inbound_edges) { IGRAPH_CHECK(igraph_vector_long_resize(inbound_edges, no_of_nodes)); for (i = 0; i < no_of_nodes; i++) { if (father[i] <= 1) { /* i was not reached or i is the start vertex */ VECTOR(*inbound_edges)[i] = -1; } else { /* i was reached via the edge with ID = father[i] - 2 */ VECTOR(*inbound_edges)[i] = father[i] - 2; } } } /* Create `vertices' and `edges' if needed */ if (vertices || edges) { for (IGRAPH_VIT_RESET(vit), j = 0; !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit), j++) { long int node = IGRAPH_VIT_GET(vit); igraph_vector_t *vvec = 0, *evec = 0; if (vertices) { vvec = VECTOR(*vertices)[j]; igraph_vector_clear(vvec); } if (edges) { evec = VECTOR(*edges)[j]; igraph_vector_clear(evec); } IGRAPH_ALLOW_INTERRUPTION(); if (father[node] > 0) { long int act = node; long int size = 0; long int edge; while (father[act] > 1) { size++; edge = father[act] - 2; act = IGRAPH_OTHER(graph, edge, act); } if (vvec) { IGRAPH_CHECK(igraph_vector_resize(vvec, size + 1)); VECTOR(*vvec)[size] = node; } if (evec) { IGRAPH_CHECK(igraph_vector_resize(evec, size)); } act = node; while (father[act] > 1) { size--; edge = father[act] - 2; act = IGRAPH_OTHER(graph, edge, act); if (vvec) { VECTOR(*vvec)[size] = act; } if (evec) { VECTOR(*evec)[size] = edge; } } } } } /* Clean */ igraph_Free(father); igraph_dqueue_destroy(&q); igraph_vector_destroy(&tmp); igraph_vit_destroy(&vit); IGRAPH_FINALLY_CLEAN(4); return 0; } /** * \function igraph_get_shortest_path * Shortest path from one vertex to another one. * * Calculates and returns a single unweighted shortest path from a * given vertex to another one. If there are more than one shortest * paths between the two vertices, then an arbitrary one is returned. * * This function is a wrapper to \ref * igraph_get_shortest_paths(), for the special case when only one * target vertex is considered. * \param graph The input graph, it can be directed or * undirected. Directed paths are considered in directed * graphs. * \param vertices Pointer to an initialized vector or a null * pointer. If not a null pointer, then the vertex ids along * the path are stored here, including the source and target * vertices. * \param edges Pointer to an uninitialized vector or a null * pointer. If not a null pointer, then the edge ids along the * path are stored here. * \param from The id of the source vertex. * \param to The id of the target vertex. * \param mode A constant specifying how edge directions are * considered in directed graphs. Valid modes are: * \c IGRAPH_OUT, follows edge directions; * \c IGRAPH_IN, follows the opposite directions; and * \c IGRAPH_ALL, ignores edge directions. This argument is * ignored for undirected graphs. * \return Error code. * * Time complexity: O(|V|+|E|), linear in the number of vertices and * edges in the graph. * * \sa \ref igraph_get_shortest_paths() for the version with more target * vertices. */ int igraph_get_shortest_path(const igraph_t *graph, igraph_vector_t *vertices, igraph_vector_t *edges, igraph_integer_t from, igraph_integer_t to, igraph_neimode_t mode) { igraph_vector_ptr_t vertices2, *vp = &vertices2; igraph_vector_ptr_t edges2, *ep = &edges2; if (vertices) { IGRAPH_CHECK(igraph_vector_ptr_init(&vertices2, 1)); IGRAPH_FINALLY(igraph_vector_ptr_destroy, &vertices2); VECTOR(vertices2)[0] = vertices; } else { vp = 0; } if (edges) { IGRAPH_CHECK(igraph_vector_ptr_init(&edges2, 1)); IGRAPH_FINALLY(igraph_vector_ptr_destroy, &edges2); VECTOR(edges2)[0] = edges; } else { ep = 0; } IGRAPH_CHECK(igraph_get_shortest_paths(graph, vp, ep, from, igraph_vss_1(to), mode, 0, 0)); if (edges) { igraph_vector_ptr_destroy(&edges2); IGRAPH_FINALLY_CLEAN(1); } if (vertices) { igraph_vector_ptr_destroy(&vertices2); IGRAPH_FINALLY_CLEAN(1); } return 0; } void igraph_i_gasp_paths_destroy(igraph_vector_ptr_t *v); void igraph_i_gasp_paths_destroy(igraph_vector_ptr_t *v) { long int i; for (i = 0; i < igraph_vector_ptr_size(v); i++) { if (VECTOR(*v)[i] != 0) { igraph_vector_destroy(VECTOR(*v)[i]); igraph_Free(VECTOR(*v)[i]); } } igraph_vector_ptr_destroy(v); } /** * \function igraph_get_all_shortest_paths * \brief Finds all shortest paths (geodesics) from a vertex to all other vertices. * * \param graph The graph object. * \param res Pointer to an initialized pointer vector, the result * will be stored here in igraph_vector_t objects. Each vector * object contains the vertices along a shortest path from \p from * to another vertex. The vectors are ordered according to their * target vertex: first the shortest paths to vertex 0, then to * vertex 1, etc. No data is included for unreachable vertices. * \param nrgeo Pointer to an initialized igraph_vector_t object or * NULL. If not NULL the number of shortest paths from \p from are * stored here for every vertex in the graph. Note that the values * will be accurate only for those vertices that are in the target * vertex sequence (see \p to), since the search terminates as soon * as all the target vertices have been found. * \param from The id of the vertex from/to which the geodesics are * calculated. * \param to Vertex sequence with the ids of the vertices to/from which the * shortest paths will be calculated. A vertex might be given multiple * times. * \param mode The type of shortest paths to be use for the * calculation in directed graphs. Possible values: * \clist * \cli IGRAPH_OUT * the lengths of the outgoing paths are calculated. * \cli IGRAPH_IN * the lengths of the incoming paths are calculated. * \cli IGRAPH_ALL * the directed graph is considered as an * undirected one for the computation. * \endclist * \return Error code: * \clist * \cli IGRAPH_ENOMEM * not enough memory for temporary data. * \cli IGRAPH_EINVVID * \p from is invalid vertex id. * \cli IGRAPH_EINVMODE * invalid mode argument. * \endclist * * Added in version 0.2. * * Time complexity: O(|V|+|E|) for most graphs, O(|V|^2) in the worst * case. */ int igraph_get_all_shortest_paths(const igraph_t *graph, igraph_vector_ptr_t *res, igraph_vector_t *nrgeo, igraph_integer_t from, const igraph_vs_t to, igraph_neimode_t mode) { long int no_of_nodes = igraph_vcount(graph); long int *geodist; igraph_vector_ptr_t paths; igraph_dqueue_t q; igraph_vector_t *vptr; igraph_vector_t neis; igraph_vector_t ptrlist; igraph_vector_t ptrhead; long int n, j, i; long int to_reach, reached = 0, maxdist = 0; igraph_vit_t vit; if (from < 0 || from >= no_of_nodes) { IGRAPH_ERROR("cannot get shortest paths", IGRAPH_EINVVID); } if (mode != IGRAPH_OUT && mode != IGRAPH_IN && mode != IGRAPH_ALL) { IGRAPH_ERROR("Invalid mode argument", IGRAPH_EINVMODE); } IGRAPH_CHECK(igraph_vit_create(graph, to, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); /* paths will store the shortest paths during the search */ IGRAPH_CHECK(igraph_vector_ptr_init(&paths, 0)); IGRAPH_FINALLY(igraph_i_gasp_paths_destroy, &paths); /* neis is a temporary vector holding the neighbors of the * node being examined */ IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); /* ptrlist stores indices into the paths vector, in the order * of how they were found. ptrhead is a second-level index that * will be used to find paths that terminate in a given vertex */ IGRAPH_VECTOR_INIT_FINALLY(&ptrlist, 0); /* ptrhead contains indices into ptrlist. * ptrhead[i] = j means that element #j-1 in ptrlist contains * the shortest path from the root to node i. ptrhead[i] = 0 * means that node i was not reached so far */ IGRAPH_VECTOR_INIT_FINALLY(&ptrhead, no_of_nodes); /* geodist[i] == 0 if i was not reached yet and it is not in the * target vertex sequence, or -1 if i was not reached yet and it * is in the target vertex sequence. Otherwise it is * one larger than the length of the shortest path from the * source */ geodist = igraph_Calloc(no_of_nodes, long int); if (geodist == 0) { IGRAPH_ERROR("Cannot calculate shortest paths", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, geodist); /* dequeue to store the BFS queue -- odd elements are the vertex indices, * even elements are the distances from the root */ IGRAPH_CHECK(igraph_dqueue_init(&q, 100)); IGRAPH_FINALLY(igraph_dqueue_destroy, &q); if (nrgeo) { IGRAPH_CHECK(igraph_vector_resize(nrgeo, no_of_nodes)); igraph_vector_null(nrgeo); } /* use geodist to count how many vertices we have to reach */ to_reach = IGRAPH_VIT_SIZE(vit); for (IGRAPH_VIT_RESET(vit); !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit)) { if (geodist[ (long int) IGRAPH_VIT_GET(vit) ] == 0) { geodist[ (long int) IGRAPH_VIT_GET(vit) ] = -1; } else { to_reach--; /* this node was given multiple times */ } } if (geodist[ (long int) from ] < 0) { reached++; } /* from -> from */ vptr = igraph_Calloc(1, igraph_vector_t); /* TODO: dirty */ IGRAPH_CHECK(igraph_vector_ptr_push_back(&paths, vptr)); IGRAPH_CHECK(igraph_vector_init(vptr, 1)); VECTOR(*vptr)[0] = from; geodist[(long int)from] = 1; VECTOR(ptrhead)[(long int)from] = 1; IGRAPH_CHECK(igraph_vector_push_back(&ptrlist, 0)); if (nrgeo) { VECTOR(*nrgeo)[(long int)from] = 1; } /* Init queue */ IGRAPH_CHECK(igraph_dqueue_push(&q, from)); IGRAPH_CHECK(igraph_dqueue_push(&q, 0.0)); while (!igraph_dqueue_empty(&q)) { long int actnode = (long int) igraph_dqueue_pop(&q); long int actdist = (long int) igraph_dqueue_pop(&q); IGRAPH_ALLOW_INTERRUPTION(); if (reached >= to_reach) { /* all nodes were reached. Since we need all the shortest paths * to all these nodes, we can stop the search only if the distance * of the current node to the root is larger than the distance of * any of the nodes we wanted to reach */ if (actdist > maxdist) { /* safety check, maxdist should have been set when we reached the last node */ if (maxdist < 0) { IGRAPH_ERROR("possible bug in igraph_get_all_shortest_paths, " "maxdist is negative", IGRAPH_EINVAL); } break; } } IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) actnode, mode)); n = igraph_vector_size(&neis); for (j = 0; j < n; j++) { long int neighbor = (long int) VECTOR(neis)[j]; long int fatherptr; if (geodist[neighbor] > 0 && geodist[neighbor] - 1 < actdist + 1) { /* this node was reached via a shorter path before */ continue; } /* yay, found another shortest path to neighbor */ if (nrgeo) { /* the number of geodesics leading to neighbor must be * increased by the number of geodesics leading to actnode */ VECTOR(*nrgeo)[neighbor] += VECTOR(*nrgeo)[actnode]; } if (geodist[neighbor] <= 0) { /* this node was not reached yet, push it into the queue */ IGRAPH_CHECK(igraph_dqueue_push(&q, neighbor)); IGRAPH_CHECK(igraph_dqueue_push(&q, actdist + 1)); if (geodist[neighbor] < 0) { reached++; } if (reached == to_reach) { maxdist = actdist; } } geodist[neighbor] = actdist + 2; /* copy all existing paths to the parent */ fatherptr = (long int) VECTOR(ptrhead)[actnode]; while (fatherptr != 0) { /* allocate a new igraph_vector_t at the end of paths */ vptr = igraph_Calloc(1, igraph_vector_t); IGRAPH_CHECK(igraph_vector_ptr_push_back(&paths, vptr)); IGRAPH_CHECK(igraph_vector_copy(vptr, VECTOR(paths)[fatherptr - 1])); IGRAPH_CHECK(igraph_vector_reserve(vptr, actdist + 2)); IGRAPH_CHECK(igraph_vector_push_back(vptr, neighbor)); IGRAPH_CHECK(igraph_vector_push_back(&ptrlist, VECTOR(ptrhead)[neighbor])); VECTOR(ptrhead)[neighbor] = igraph_vector_size(&ptrlist); fatherptr = (long int) VECTOR(ptrlist)[fatherptr - 1]; } } } igraph_dqueue_destroy(&q); IGRAPH_FINALLY_CLEAN(1); /* mark the nodes for which we need the result */ memset(geodist, 0, sizeof(long int) * (size_t) no_of_nodes); for (IGRAPH_VIT_RESET(vit); !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit)) { geodist[ (long int) IGRAPH_VIT_GET(vit) ] = 1; } /* count the number of paths in the result */ n = 0; for (i = 0; i < no_of_nodes; i++) { long int fatherptr = (long int) VECTOR(ptrhead)[i]; if (geodist[i] > 0) { while (fatherptr != 0) { n++; fatherptr = (long int) VECTOR(ptrlist)[fatherptr - 1]; } } } IGRAPH_CHECK(igraph_vector_ptr_resize(res, n)); j = 0; for (i = 0; i < no_of_nodes; i++) { long int fatherptr = (long int) VECTOR(ptrhead)[i]; IGRAPH_ALLOW_INTERRUPTION(); /* do we need the paths leading to vertex i? */ if (geodist[i] > 0) { /* yes, copy them to the result vector */ while (fatherptr != 0) { VECTOR(*res)[j++] = VECTOR(paths)[fatherptr - 1]; fatherptr = (long int) VECTOR(ptrlist)[fatherptr - 1]; } } else { /* no, free them */ while (fatherptr != 0) { igraph_vector_destroy(VECTOR(paths)[fatherptr - 1]); igraph_Free(VECTOR(paths)[fatherptr - 1]); fatherptr = (long int) VECTOR(ptrlist)[fatherptr - 1]; } } } igraph_Free(geodist); igraph_vector_destroy(&ptrlist); igraph_vector_destroy(&ptrhead); igraph_vector_destroy(&neis); igraph_vector_ptr_destroy(&paths); igraph_vit_destroy(&vit); IGRAPH_FINALLY_CLEAN(6); return 0; } /** * \ingroup structural * \function igraph_subcomponent * \brief The vertices in the same component as a given vertex. * * \param graph The graph object. * \param res The result, vector with the ids of the vertices in the * same component. * \param vertex The id of the vertex of which the component is * searched. * \param mode Type of the component for directed graphs, possible * values: * \clist * \cli IGRAPH_OUT * the set of vertices reachable \em from the * \p vertex, * \cli IGRAPH_IN * the set of vertices from which the * \p vertex is reachable. * \cli IGRAPH_ALL * the graph is considered as an * undirected graph. Note that this is \em not the same * as the union of the previous two. * \endclist * \return Error code: * \clist * \cli IGRAPH_ENOMEM * not enough memory for temporary data. * \cli IGRAPH_EINVVID * \p vertex is an invalid vertex id * \cli IGRAPH_EINVMODE * invalid mode argument passed. * \endclist * * Time complexity: O(|V|+|E|), * |V| and * |E| are the number of vertices and * edges in the graph. * * \sa \ref igraph_subgraph() if you want a graph object consisting only * a given set of vertices and the edges between them. */ int igraph_subcomponent(const igraph_t *graph, igraph_vector_t *res, igraph_real_t vertex, igraph_neimode_t mode) { long int no_of_nodes = igraph_vcount(graph); igraph_dqueue_t q = IGRAPH_DQUEUE_NULL; char *already_added; long int i; igraph_vector_t tmp = IGRAPH_VECTOR_NULL; if (!IGRAPH_FINITE(vertex) || vertex < 0 || vertex >= no_of_nodes) { IGRAPH_ERROR("subcomponent failed", IGRAPH_EINVVID); } if (mode != IGRAPH_OUT && mode != IGRAPH_IN && mode != IGRAPH_ALL) { IGRAPH_ERROR("invalid mode argument", IGRAPH_EINVMODE); } already_added = igraph_Calloc(no_of_nodes, char); if (already_added == 0) { IGRAPH_ERROR("subcomponent failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, already_added); /* TODO: hack */ igraph_vector_clear(res); IGRAPH_VECTOR_INIT_FINALLY(&tmp, 0); IGRAPH_DQUEUE_INIT_FINALLY(&q, 100); IGRAPH_CHECK(igraph_dqueue_push(&q, vertex)); IGRAPH_CHECK(igraph_vector_push_back(res, vertex)); already_added[(long int)vertex] = 1; while (!igraph_dqueue_empty(&q)) { long int actnode = (long int) igraph_dqueue_pop(&q); IGRAPH_ALLOW_INTERRUPTION(); IGRAPH_CHECK(igraph_neighbors(graph, &tmp, (igraph_integer_t) actnode, mode)); for (i = 0; i < igraph_vector_size(&tmp); i++) { long int neighbor = (long int) VECTOR(tmp)[i]; if (already_added[neighbor]) { continue; } already_added[neighbor] = 1; IGRAPH_CHECK(igraph_vector_push_back(res, neighbor)); IGRAPH_CHECK(igraph_dqueue_push(&q, neighbor)); } } igraph_dqueue_destroy(&q); igraph_vector_destroy(&tmp); igraph_Free(already_added); IGRAPH_FINALLY_CLEAN(3); return 0; } /** * \ingroup structural * \function igraph_pagerank_old * \brief Calculates the Google PageRank for the specified vertices. * * This is an old implementation, * it is provided for compatibility with igraph versions earlier than * 0.5. Please use the new implementation \ref igraph_pagerank() in * new projects. * * * From version 0.7 this function is deprecated and its use gives a * warning message. * * * Please note that the PageRank of a given vertex depends on the PageRank * of all other vertices, so even if you want to calculate the PageRank for * only some of the vertices, all of them must be calculated. Requesting * the PageRank for only some of the vertices does not result in any * performance increase at all. * * * Since the calculation is an iterative * process, the algorithm is stopped after a given count of iterations * or if the PageRank value differences between iterations are less than * a predefined value. * * * * For the explanation of the PageRank algorithm, see the following * webpage: * http://infolab.stanford.edu/~backrub/google.html , or the * following reference: * * * * Sergey Brin and Larry Page: The Anatomy of a Large-Scale Hypertextual * Web Search Engine. Proceedings of the 7th World-Wide Web Conference, * Brisbane, Australia, April 1998. * * * \param graph The graph object. * \param res The result vector containing the PageRank values for the * given nodes. * \param vids Vector with the vertex ids * \param directed Logical, if true directed paths will be considered * for directed graphs. It is ignored for undirected graphs. * \param niter The maximum number of iterations to perform * \param eps The algorithm will consider the calculation as complete * if the difference of PageRank values between iterations change * less than this value for every node * \param damping The damping factor ("d" in the original paper) * \param old Boolean, whether to use the pre-igraph 0.5 way to * calculate page rank. Not recommended for new applications, * only included for compatibility. If this is non-zero then the damping * factor is not divided by the number of vertices before adding it * to the weighted page rank scores to calculate the * new scores. I.e. the formula in the original PageRank paper * is used. Furthermore, if this is non-zero then the PageRank * vector is renormalized after each iteration. * \return Error code: * \c IGRAPH_ENOMEM, not enough memory for * temporary data. * \c IGRAPH_EINVVID, invalid vertex id in * \p vids. * * Time complexity: O(|V|+|E|) per iteration. A handful iterations * should be enough. Note that if the old-style dumping is used then * the iteration might not converge at all. * * \sa \ref igraph_pagerank() for the new implementation. */ int igraph_pagerank_old(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, igraph_bool_t directed, igraph_integer_t niter, igraph_real_t eps, igraph_real_t damping, igraph_bool_t old) { long int no_of_nodes = igraph_vcount(graph); long int i, j, n, nodes_to_calc; igraph_real_t *prvec, *prvec_new, *prvec_aux, *prvec_scaled; igraph_vector_int_t *neis; igraph_vector_t outdegree; igraph_neimode_t dirmode; igraph_adjlist_t allneis; igraph_real_t maxdiff = eps; igraph_vit_t vit; IGRAPH_WARNING("igraph_pagerank_old is deprecated from igraph 0.7, " "use igraph_pagerank instead"); if (niter <= 0) { IGRAPH_ERROR("Invalid iteration count", IGRAPH_EINVAL); } if (eps <= 0) { IGRAPH_ERROR("Invalid epsilon value", IGRAPH_EINVAL); } if (damping <= 0 || damping >= 1) { IGRAPH_ERROR("Invalid damping factor", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); nodes_to_calc = IGRAPH_VIT_SIZE(vit); IGRAPH_CHECK(igraph_vector_resize(res, nodes_to_calc)); igraph_vector_null(res); IGRAPH_VECTOR_INIT_FINALLY(&outdegree, no_of_nodes); prvec = igraph_Calloc(no_of_nodes, igraph_real_t); if (prvec == 0) { IGRAPH_ERROR("pagerank failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, prvec); prvec_new = igraph_Calloc(no_of_nodes, igraph_real_t); if (prvec_new == 0) { IGRAPH_ERROR("pagerank failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, prvec_new); prvec_scaled = igraph_Calloc(no_of_nodes, igraph_real_t); if (prvec_scaled == 0) { IGRAPH_ERROR("pagerank failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, prvec_scaled); if (directed) { dirmode = IGRAPH_IN; } else { dirmode = IGRAPH_ALL; } igraph_adjlist_init(graph, &allneis, dirmode); IGRAPH_FINALLY(igraph_adjlist_destroy, &allneis); /* Calculate outdegrees for every node */ igraph_degree(graph, &outdegree, igraph_vss_all(), directed ? IGRAPH_OUT : IGRAPH_ALL, 0); /* Initialize PageRank values */ for (i = 0; i < no_of_nodes; i++) { prvec[i] = 1 - damping; /* The next line is necessary to avoid division by zero in the * calculation of prvec_scaled. This won't cause any problem, * since if a node doesn't have any outgoing links, its * prvec_scaled value won't be used anywhere */ if (VECTOR(outdegree)[i] == 0) { VECTOR(outdegree)[i] = 1; } } /* We will always calculate the new PageRank values into prvec_new * based on the existing values from prvec. To avoid unnecessary * copying from prvec_new to prvec at the end of every iteration, * the pointers are swapped after every iteration */ while (niter > 0 && maxdiff >= eps) { igraph_real_t sumfrom = 0, sum = 0; niter--; maxdiff = 0; /* Calculate the quotient of the actual PageRank value and the * outdegree for every node */ sumfrom = 0.0; sum = 0.0; for (i = 0; i < no_of_nodes; i++) { sumfrom += prvec[i]; prvec_scaled[i] = prvec[i] / VECTOR(outdegree)[i]; } /* Calculate new PageRank values based on the old ones */ for (i = 0; i < no_of_nodes; i++) { IGRAPH_ALLOW_INTERRUPTION(); prvec_new[i] = 0; neis = igraph_adjlist_get(&allneis, i); n = igraph_vector_int_size(neis); for (j = 0; j < n; j++) { long int neighbor = (long int) VECTOR(*neis)[j]; prvec_new[i] += prvec_scaled[neighbor]; } prvec_new[i] *= damping; if (!old) { prvec_new[i] += (1 - damping) / no_of_nodes; } else { prvec_new[i] += (1 - damping); } sum += prvec_new[i]; } for (i = 0; i < no_of_nodes; i++) { if (!old) { prvec_new[i] /= sum; } if (prvec_new[i] - prvec[i] > maxdiff) { maxdiff = prvec_new[i] - prvec[i]; } else if (prvec[i] - prvec_new[i] > maxdiff) { maxdiff = prvec[i] - prvec_new[i]; } } /* Swap the vectors */ prvec_aux = prvec_new; prvec_new = prvec; prvec = prvec_aux; } /* Copy results from prvec to res */ for (IGRAPH_VIT_RESET(vit), i = 0; !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit), i++) { long int vid = IGRAPH_VIT_GET(vit); VECTOR(*res)[i] = prvec[vid]; } igraph_adjlist_destroy(&allneis); igraph_vit_destroy(&vit); igraph_vector_destroy(&outdegree); igraph_Free(prvec); igraph_Free(prvec_new); igraph_Free(prvec_scaled); IGRAPH_FINALLY_CLEAN(6); return 0; } /* Not declared static so that the testsuite can use it, but not part of the public API. */ int igraph_rewire_core(igraph_t *graph, igraph_integer_t n, igraph_rewiring_t mode, igraph_bool_t use_adjlist) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); char message[256]; igraph_integer_t a, b, c, d, dummy, num_swaps, num_successful_swaps; igraph_vector_t eids, edgevec, alledges; igraph_bool_t directed, loops, ok; igraph_es_t es; igraph_adjlist_t al; if (no_of_nodes < 4) { IGRAPH_ERROR("graph unsuitable for rewiring", IGRAPH_EINVAL); } directed = igraph_is_directed(graph); loops = (mode & IGRAPH_REWIRING_SIMPLE_LOOPS); RNG_BEGIN(); IGRAPH_VECTOR_INIT_FINALLY(&eids, 2); if (use_adjlist) { /* As well as the sorted adjacency list, we maintain an unordered * list of edges for picking a random edge in constant time. */ IGRAPH_CHECK(igraph_adjlist_init(graph, &al, IGRAPH_OUT)); IGRAPH_FINALLY(igraph_adjlist_destroy, &al); IGRAPH_VECTOR_INIT_FINALLY(&alledges, no_of_edges * 2); igraph_get_edgelist(graph, &alledges, /*bycol=*/ 0); } else { IGRAPH_VECTOR_INIT_FINALLY(&edgevec, 4); es = igraph_ess_vector(&eids); } /* We don't want the algorithm to get stuck in an infinite loop when * it can't choose two edges satisfying the conditions. Instead of * this, we choose two arbitrary edges and if they have endpoints * in common, we just decrease the number of trials left and continue * (so unsuccessful rewirings still count as a trial) */ num_swaps = num_successful_swaps = 0; while (num_swaps < n) { IGRAPH_ALLOW_INTERRUPTION(); if (num_swaps % 1000 == 0) { snprintf(message, sizeof(message), "Random rewiring (%.2f%% of the trials were successful)", num_swaps > 0 ? ((100.0 * num_successful_swaps) / num_swaps) : 0.0); IGRAPH_PROGRESS(message, (100.0 * num_swaps) / n, 0); } switch (mode) { case IGRAPH_REWIRING_SIMPLE: case IGRAPH_REWIRING_SIMPLE_LOOPS: ok = 1; /* Choose two edges randomly */ VECTOR(eids)[0] = RNG_INTEGER(0, no_of_edges - 1); do { VECTOR(eids)[1] = RNG_INTEGER(0, no_of_edges - 1); } while (VECTOR(eids)[0] == VECTOR(eids)[1]); /* Get the endpoints */ if (use_adjlist) { a = VECTOR(alledges)[((igraph_integer_t)VECTOR(eids)[0]) * 2]; b = VECTOR(alledges)[(((igraph_integer_t)VECTOR(eids)[0]) * 2) + 1]; c = VECTOR(alledges)[((igraph_integer_t)VECTOR(eids)[1]) * 2]; d = VECTOR(alledges)[(((igraph_integer_t)VECTOR(eids)[1]) * 2) + 1]; } else { IGRAPH_CHECK(igraph_edge(graph, (igraph_integer_t) VECTOR(eids)[0], &a, &b)); IGRAPH_CHECK(igraph_edge(graph, (igraph_integer_t) VECTOR(eids)[1], &c, &d)); } /* For an undirected graph, we have two "variants" of each edge, i.e. * a -- b and b -- a. Since some rewirings can be performed only when we * "swap" the endpoints, we do it now with probability 0.5 */ if (!directed && RNG_UNIF01() < 0.5) { dummy = c; c = d; d = dummy; if (use_adjlist) { /* Flip the edge in the unordered edge-list, so the update later on * hits the correct end. */ VECTOR(alledges)[((igraph_integer_t)VECTOR(eids)[1]) * 2] = c; VECTOR(alledges)[(((igraph_integer_t)VECTOR(eids)[1]) * 2) + 1] = d; } } /* If we do not touch loops, check whether a == b or c == d and disallow * the swap if needed */ if (!loops && (a == b || c == d)) { ok = 0; } else { /* Check whether they are suitable for rewiring */ if (a == c || b == d) { /* Swapping would have no effect */ ok = 0; } else { /* a != c && b != d */ /* If a == d or b == c, the swap would generate at least one loop, so * we disallow them unless we want to have loops */ ok = loops || (a != d && b != c); /* Also, if a == b and c == d and we allow loops, doing the swap * would result in a multiple edge if the graph is undirected */ ok = ok && (directed || a != b || c != d); } } /* All good so far. Now check for the existence of a --> d and c --> b to * disallow the creation of multiple edges */ if (ok) { if (use_adjlist) { if (igraph_adjlist_has_edge(&al, a, d, directed)) { ok = 0; } } else { IGRAPH_CHECK(igraph_are_connected(graph, a, d, &ok)); ok = !ok; } } if (ok) { if (use_adjlist) { if (igraph_adjlist_has_edge(&al, c, b, directed)) { ok = 0; } } else { IGRAPH_CHECK(igraph_are_connected(graph, c, b, &ok)); ok = !ok; } } /* If we are still okay, we can perform the rewiring */ if (ok) { /* printf("Deleting: %ld -> %ld, %ld -> %ld\n", (long)a, (long)b, (long)c, (long)d); */ if (use_adjlist) { // Replace entry in sorted adjlist: IGRAPH_CHECK(igraph_adjlist_replace_edge(&al, a, b, d, directed)); IGRAPH_CHECK(igraph_adjlist_replace_edge(&al, c, d, b, directed)); // Also replace in unsorted edgelist: VECTOR(alledges)[(((igraph_integer_t)VECTOR(eids)[0]) * 2) + 1] = d; VECTOR(alledges)[(((igraph_integer_t)VECTOR(eids)[1]) * 2) + 1] = b; } else { IGRAPH_CHECK(igraph_delete_edges(graph, es)); VECTOR(edgevec)[0] = a; VECTOR(edgevec)[1] = d; VECTOR(edgevec)[2] = c; VECTOR(edgevec)[3] = b; /* printf("Adding: %ld -> %ld, %ld -> %ld\n", (long)a, (long)d, (long)c, (long)b); */ igraph_add_edges(graph, &edgevec, 0); } num_successful_swaps++; } break; default: RNG_END(); IGRAPH_ERROR("unknown rewiring mode", IGRAPH_EINVMODE); } num_swaps++; } if (use_adjlist) { /* Replace graph edges with the adjlist current state */ IGRAPH_CHECK(igraph_delete_edges(graph, igraph_ess_all(IGRAPH_EDGEORDER_ID))); IGRAPH_CHECK(igraph_add_edges(graph, &alledges, 0)); } IGRAPH_PROGRESS("Random rewiring: ", 100.0, 0); if (use_adjlist) { igraph_vector_destroy(&alledges); igraph_adjlist_destroy(&al); } else { igraph_vector_destroy(&edgevec); } igraph_vector_destroy(&eids); IGRAPH_FINALLY_CLEAN(use_adjlist ? 3 : 2); RNG_END(); return 0; } /** * \ingroup structural * \function igraph_rewire * \brief Randomly rewires a graph while preserving the degree distribution. * * * This function generates a new graph based on the original one by randomly * rewiring edges while preserving the original graph's degree distribution. * Please note that the rewiring is done "in place", so no new graph will * be allocated. If you would like to keep the original graph intact, use * \ref igraph_copy() beforehand. * * \param graph The graph object to be rewired. * \param n Number of rewiring trials to perform. * \param mode The rewiring algorithm to be used. It can be one of the following flags: * \clist * \cli IGRAPH_REWIRING_SIMPLE * Simple rewiring algorithm which chooses two arbitrary edges * in each step (namely (a,b) and (c,d)) and substitutes them * with (a,d) and (c,b) if they don't exist. The method will * neither destroy nor create self-loops. * \cli IGRAPH_REWIRING_SIMPLE_LOOPS * Same as \c IGRAPH_REWIRING_SIMPLE but allows the creation or * destruction of self-loops. * \endclist * * \return Error code: * \clist * \cli IGRAPH_EINVMODE * Invalid rewiring mode. * \cli IGRAPH_EINVAL * Graph unsuitable for rewiring (e.g. it has * less than 4 nodes in case of \c IGRAPH_REWIRING_SIMPLE) * \cli IGRAPH_ENOMEM * Not enough memory for temporary data. * \endclist * * Time complexity: TODO. * * \example examples/simple/igraph_rewire.c */ #define REWIRE_ADJLIST_THRESHOLD 10 int igraph_rewire(igraph_t *graph, igraph_integer_t n, igraph_rewiring_t mode) { igraph_bool_t use_adjlist = n >= REWIRE_ADJLIST_THRESHOLD; return igraph_rewire_core(graph, n, mode, use_adjlist); } /** * Subgraph creation, old version: it copies the graph and then deletes * unneeded vertices. */ int igraph_i_subgraph_copy_and_delete(const igraph_t *graph, igraph_t *res, const igraph_vs_t vids, igraph_vector_t *map, igraph_vector_t *invmap) { long int no_of_nodes = igraph_vcount(graph); igraph_vector_t delete = IGRAPH_VECTOR_NULL; char *remain; long int i; igraph_vit_t vit; IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); IGRAPH_VECTOR_INIT_FINALLY(&delete, 0); remain = igraph_Calloc(no_of_nodes, char); if (remain == 0) { IGRAPH_ERROR("subgraph failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, remain); /* TODO: hack */ IGRAPH_CHECK(igraph_vector_reserve(&delete, no_of_nodes - IGRAPH_VIT_SIZE(vit))); for (IGRAPH_VIT_RESET(vit); !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit)) { remain[ (long int) IGRAPH_VIT_GET(vit) ] = 1; } for (i = 0; i < no_of_nodes; i++) { IGRAPH_ALLOW_INTERRUPTION(); if (remain[i] == 0) { IGRAPH_CHECK(igraph_vector_push_back(&delete, i)); } } igraph_Free(remain); IGRAPH_FINALLY_CLEAN(1); /* must set res->attr to 0 before calling igraph_copy */ res->attr = 0; /* Why is this needed? TODO */ IGRAPH_CHECK(igraph_copy(res, graph)); IGRAPH_FINALLY(igraph_destroy, res); IGRAPH_CHECK(igraph_delete_vertices_idx(res, igraph_vss_vector(&delete), map, invmap)); igraph_vector_destroy(&delete); igraph_vit_destroy(&vit); IGRAPH_FINALLY_CLEAN(3); return 0; } /** * Subgraph creation, new version: creates the new graph instead of * copying the old one. */ int igraph_i_subgraph_create_from_scratch(const igraph_t *graph, igraph_t *res, const igraph_vs_t vids, igraph_vector_t *map, igraph_vector_t *invmap) { igraph_bool_t directed = igraph_is_directed(graph); long int no_of_nodes = igraph_vcount(graph); long int no_of_new_nodes = 0; long int i, j, n; long int to; igraph_integer_t eid; igraph_vector_t vids_old2new, vids_new2old; igraph_vector_t eids_new2old; igraph_vector_t nei_edges; igraph_vector_t new_edges; igraph_vit_t vit; igraph_vector_t *my_vids_old2new = &vids_old2new, *my_vids_new2old = &vids_new2old; /* The order of initialization is important here, they will be destroyed in the * opposite order */ IGRAPH_VECTOR_INIT_FINALLY(&eids_new2old, 0); if (invmap) { my_vids_new2old = invmap; igraph_vector_clear(my_vids_new2old); } else { IGRAPH_VECTOR_INIT_FINALLY(&vids_new2old, 0); } IGRAPH_VECTOR_INIT_FINALLY(&new_edges, 0); IGRAPH_VECTOR_INIT_FINALLY(&nei_edges, 0); if (map) { my_vids_old2new = map; IGRAPH_CHECK(igraph_vector_resize(map, no_of_nodes)); igraph_vector_null(map); } else { IGRAPH_VECTOR_INIT_FINALLY(&vids_old2new, no_of_nodes); } IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); /* Calculate the mapping from the old node IDs to the new ones. The other * igraph_simplify implementation in igraph_i_simplify_copy_and_delete * ensures that the order of vertex IDs is kept during remapping (i.e. * if the old ID of vertex A is less than the old ID of vertex B, then * the same will also be true for the new IDs). To ensure compatibility * with the other implementation, we have to fetch the vertex IDs into * a vector first and then sort it. We temporarily use new_edges for that. */ IGRAPH_CHECK(igraph_vit_as_vector(&vit, &nei_edges)); igraph_vit_destroy(&vit); IGRAPH_FINALLY_CLEAN(1); igraph_vector_sort(&nei_edges); n = igraph_vector_size(&nei_edges); for (i = 0; i < n; i++) { long int vid = (long int) VECTOR(nei_edges)[i]; if (VECTOR(*my_vids_old2new)[vid] == 0) { IGRAPH_CHECK(igraph_vector_push_back(my_vids_new2old, vid)); no_of_new_nodes++; VECTOR(*my_vids_old2new)[vid] = no_of_new_nodes; } } /* Create the new edge list */ for (i = 0; i < no_of_new_nodes; i++) { long int old_vid = (long int) VECTOR(*my_vids_new2old)[i]; long int new_vid = i; IGRAPH_CHECK(igraph_incident(graph, &nei_edges, old_vid, IGRAPH_OUT)); n = igraph_vector_size(&nei_edges); if (directed) { for (j = 0; j < n; j++) { eid = (igraph_integer_t) VECTOR(nei_edges)[j]; to = (long int) VECTOR(*my_vids_old2new)[ (long int)IGRAPH_TO(graph, eid) ]; if (!to) { continue; } IGRAPH_CHECK(igraph_vector_push_back(&new_edges, new_vid)); IGRAPH_CHECK(igraph_vector_push_back(&new_edges, to - 1)); IGRAPH_CHECK(igraph_vector_push_back(&eids_new2old, eid)); } } else { for (j = 0; j < n; j++) { eid = (igraph_integer_t) VECTOR(nei_edges)[j]; if (IGRAPH_FROM(graph, eid) != old_vid) { /* avoid processing edges twice */ continue; } to = (long int) VECTOR(*my_vids_old2new)[ (long int)IGRAPH_TO(graph, eid) ]; if (!to) { continue; } IGRAPH_CHECK(igraph_vector_push_back(&new_edges, new_vid)); IGRAPH_CHECK(igraph_vector_push_back(&new_edges, to - 1)); IGRAPH_CHECK(igraph_vector_push_back(&eids_new2old, eid)); } } } /* Get rid of some vectors that are not needed anymore */ if (!map) { igraph_vector_destroy(&vids_old2new); IGRAPH_FINALLY_CLEAN(1); } igraph_vector_destroy(&nei_edges); IGRAPH_FINALLY_CLEAN(1); /* Create the new graph */ IGRAPH_CHECK(igraph_create(res, &new_edges, (igraph_integer_t) no_of_new_nodes, directed)); IGRAPH_I_ATTRIBUTE_DESTROY(res); /* Now we can also get rid of the new_edges vector */ igraph_vector_destroy(&new_edges); IGRAPH_FINALLY_CLEAN(1); /* Make sure that the newly created graph is destroyed if something happens from * now on */ IGRAPH_FINALLY(igraph_destroy, res); /* Copy the graph attributes */ IGRAPH_CHECK(igraph_i_attribute_copy(res, graph, /* ga = */ 1, /* va = */ 0, /* ea = */ 0)); /* Copy the vertex attributes */ IGRAPH_CHECK(igraph_i_attribute_permute_vertices(graph, res, my_vids_new2old)); /* Copy the edge attributes */ IGRAPH_CHECK(igraph_i_attribute_permute_edges(graph, res, &eids_new2old)); if (!invmap) { igraph_vector_destroy(my_vids_new2old); IGRAPH_FINALLY_CLEAN(1); } igraph_vector_destroy(&eids_new2old); IGRAPH_FINALLY_CLEAN(2); /* 1 + 1 since we don't need to destroy res */ return 0; } /** * \ingroup structural * \function igraph_subgraph * \brief Creates a subgraph induced by the specified vertices. * * * This function is an alias to \ref igraph_induced_subgraph(), it is * left here to ensure API compatibility with igraph versions prior to 0.6. * * * This function collects the specified vertices and all edges between * them to a new graph. * As the vertex ids in a graph always start with zero, this function * very likely needs to reassign ids to the vertices. * \param graph The graph object. * \param res The subgraph, another graph object will be stored here, * do \em not initialize this object before calling this * function, and call \ref igraph_destroy() on it if you don't need * it any more. * \param vids A vertex selector describing which vertices to keep. * \return Error code: * \c IGRAPH_ENOMEM, not enough memory for * temporary data. * \c IGRAPH_EINVVID, invalid vertex id in * \p vids. * * Time complexity: O(|V|+|E|), * |V| and * |E| are the number of vertices and * edges in the original graph. * * \sa \ref igraph_delete_vertices() to delete the specified set of * vertices from a graph, the opposite of this function. */ int igraph_subgraph(const igraph_t *graph, igraph_t *res, const igraph_vs_t vids) { IGRAPH_WARNING("igraph_subgraph is deprecated from igraph 0.6, " "use igraph_induced_subgraph instead"); return igraph_induced_subgraph(graph, res, vids, IGRAPH_SUBGRAPH_AUTO); } /** * \ingroup structural * \function igraph_induced_subgraph * \brief Creates a subgraph induced by the specified vertices. * * * This function collects the specified vertices and all edges between * them to a new graph. * As the vertex ids in a graph always start with zero, this function * very likely needs to reassign ids to the vertices. * \param graph The graph object. * \param res The subgraph, another graph object will be stored here, * do \em not initialize this object before calling this * function, and call \ref igraph_destroy() on it if you don't need * it any more. * \param vids A vertex selector describing which vertices to keep. * \param impl This parameter selects which implementation should we * use when constructing the new graph. Basically there are two * possibilities: \c IGRAPH_SUBGRAPH_COPY_AND_DELETE copies the * existing graph and deletes the vertices that are not needed * in the new graph, while \c IGRAPH_SUBGRAPH_CREATE_FROM_SCRATCH * constructs the new graph from scratch without copying the old * one. The latter is more efficient if you are extracting a * relatively small subpart of a very large graph, while the * former is better if you want to extract a subgraph whose size * is comparable to the size of the whole graph. There is a third * possibility: \c IGRAPH_SUBGRAPH_AUTO will select one of the * two methods automatically based on the ratio of the number * of vertices in the new and the old graph. * * \return Error code: * \c IGRAPH_ENOMEM, not enough memory for * temporary data. * \c IGRAPH_EINVVID, invalid vertex id in * \p vids. * * Time complexity: O(|V|+|E|), * |V| and * |E| are the number of vertices and * edges in the original graph. * * \sa \ref igraph_delete_vertices() to delete the specified set of * vertices from a graph, the opposite of this function. */ int igraph_induced_subgraph(const igraph_t *graph, igraph_t *res, const igraph_vs_t vids, igraph_subgraph_implementation_t impl) { return igraph_induced_subgraph_map(graph, res, vids, impl, /* map= */ 0, /* invmap= */ 0); } int igraph_i_induced_subgraph_suggest_implementation( const igraph_t *graph, const igraph_vs_t vids, igraph_subgraph_implementation_t *result) { double ratio; igraph_integer_t num_vs; if (igraph_vs_is_all(&vids)) { ratio = 1.0; } else { IGRAPH_CHECK(igraph_vs_size(graph, &vids, &num_vs)); ratio = (igraph_real_t) num_vs / igraph_vcount(graph); } /* TODO: needs benchmarking; threshold was chosen totally arbitrarily */ if (ratio > 0.5) { *result = IGRAPH_SUBGRAPH_COPY_AND_DELETE; } else { *result = IGRAPH_SUBGRAPH_CREATE_FROM_SCRATCH; } return 0; } int igraph_induced_subgraph_map(const igraph_t *graph, igraph_t *res, const igraph_vs_t vids, igraph_subgraph_implementation_t impl, igraph_vector_t *map, igraph_vector_t *invmap) { if (impl == IGRAPH_SUBGRAPH_AUTO) { IGRAPH_CHECK(igraph_i_induced_subgraph_suggest_implementation(graph, vids, &impl)); } switch (impl) { case IGRAPH_SUBGRAPH_COPY_AND_DELETE: return igraph_i_subgraph_copy_and_delete(graph, res, vids, map, invmap); case IGRAPH_SUBGRAPH_CREATE_FROM_SCRATCH: return igraph_i_subgraph_create_from_scratch(graph, res, vids, map, invmap); default: IGRAPH_ERROR("unknown subgraph implementation type", IGRAPH_EINVAL); } return 0; } /** * \ingroup structural * \function igraph_subgraph_edges * \brief Creates a subgraph with the specified edges and their endpoints. * * * This function collects the specified edges and their endpoints to a new * graph. * As the vertex ids in a graph always start with zero, this function * very likely needs to reassign ids to the vertices. * \param graph The graph object. * \param res The subgraph, another graph object will be stored here, * do \em not initialize this object before calling this * function, and call \ref igraph_destroy() on it if you don't need * it any more. * \param eids An edge selector describing which edges to keep. * \param delete_vertices Whether to delete the vertices not incident on any * of the specified edges as well. If \c FALSE, the number of vertices * in the result graph will always be equal to the number of vertices * in the input graph. * \return Error code: * \c IGRAPH_ENOMEM, not enough memory for * temporary data. * \c IGRAPH_EINVEID, invalid edge id in * \p eids. * * Time complexity: O(|V|+|E|), * |V| and * |E| are the number of vertices and * edges in the original graph. * * \sa \ref igraph_delete_edges() to delete the specified set of * edges from a graph, the opposite of this function. */ int igraph_subgraph_edges(const igraph_t *graph, igraph_t *res, const igraph_es_t eids, igraph_bool_t delete_vertices) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_vector_t delete = IGRAPH_VECTOR_NULL; char *vremain, *eremain; long int i; igraph_eit_t eit; IGRAPH_CHECK(igraph_eit_create(graph, eids, &eit)); IGRAPH_FINALLY(igraph_eit_destroy, &eit); IGRAPH_VECTOR_INIT_FINALLY(&delete, 0); vremain = igraph_Calloc(no_of_nodes, char); if (vremain == 0) { IGRAPH_ERROR("subgraph_edges failed", IGRAPH_ENOMEM); } eremain = igraph_Calloc(no_of_edges, char); if (eremain == 0) { IGRAPH_ERROR("subgraph_edges failed", IGRAPH_ENOMEM); } IGRAPH_FINALLY(free, vremain); /* TODO: hack */ IGRAPH_FINALLY(free, eremain); /* TODO: hack */ IGRAPH_CHECK(igraph_vector_reserve(&delete, no_of_edges - IGRAPH_EIT_SIZE(eit))); /* Collect the vertex and edge IDs that will remain */ for (IGRAPH_EIT_RESET(eit); !IGRAPH_EIT_END(eit); IGRAPH_EIT_NEXT(eit)) { igraph_integer_t from, to; long int eid = (long int) IGRAPH_EIT_GET(eit); IGRAPH_CHECK(igraph_edge(graph, (igraph_integer_t) eid, &from, &to)); eremain[eid] = vremain[(long int)from] = vremain[(long int)to] = 1; } /* Collect the edge IDs to be deleted */ for (i = 0; i < no_of_edges; i++) { IGRAPH_ALLOW_INTERRUPTION(); if (eremain[i] == 0) { IGRAPH_CHECK(igraph_vector_push_back(&delete, i)); } } igraph_Free(eremain); IGRAPH_FINALLY_CLEAN(1); /* Delete the unnecessary edges */ /* must set res->attr to 0 before calling igraph_copy */ res->attr = 0; /* Why is this needed? TODO */ IGRAPH_CHECK(igraph_copy(res, graph)); IGRAPH_FINALLY(igraph_destroy, res); IGRAPH_CHECK(igraph_delete_edges(res, igraph_ess_vector(&delete))); if (delete_vertices) { /* Collect the vertex IDs to be deleted */ igraph_vector_clear(&delete); for (i = 0; i < no_of_nodes; i++) { IGRAPH_ALLOW_INTERRUPTION(); if (vremain[i] == 0) { IGRAPH_CHECK(igraph_vector_push_back(&delete, i)); } } } igraph_Free(vremain); IGRAPH_FINALLY_CLEAN(1); /* Delete the unnecessary vertices */ if (delete_vertices) { IGRAPH_CHECK(igraph_delete_vertices(res, igraph_vss_vector(&delete))); } igraph_vector_destroy(&delete); igraph_eit_destroy(&eit); IGRAPH_FINALLY_CLEAN(3); return 0; } void igraph_i_simplify_free(igraph_vector_ptr_t *p); void igraph_i_simplify_free(igraph_vector_ptr_t *p) { long int i, n = igraph_vector_ptr_size(p); for (i = 0; i < n; i++) { igraph_vector_t *v = VECTOR(*p)[i]; if (v) { igraph_vector_destroy(v); } } igraph_vector_ptr_destroy(p); } /** * \ingroup structural * \function igraph_simplify * \brief Removes loop and/or multiple edges from the graph. * * \param graph The graph object. * \param multiple Logical, if true, multiple edges will be removed. * \param loops Logical, if true, loops (self edges) will be removed. * \param edge_comb What to do with the edge attributes. See the igraph * manual section about attributes for details. * \return Error code: * \c IGRAPH_ENOMEM if we are out of memory. * * Time complexity: O(|V|+|E|). * * \example examples/simple/igraph_simplify.c */ int igraph_simplify(igraph_t *graph, igraph_bool_t multiple, igraph_bool_t loops, const igraph_attribute_combination_t *edge_comb) { igraph_vector_t edges = IGRAPH_VECTOR_NULL; long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); long int edge; igraph_bool_t attr = edge_comb && igraph_has_attribute_table(); long int from, to, pfrom = -1, pto = -2; igraph_t res; igraph_es_t es; igraph_eit_t eit; igraph_vector_t mergeinto; long int actedge; if (!multiple && !loops) /* nothing to do */ { return IGRAPH_SUCCESS; } if (!multiple) { /* removing loop edges only, this is simple. No need to combine anything * and the whole process can be done in-place */ IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_CHECK(igraph_es_all(&es, IGRAPH_EDGEORDER_ID)); IGRAPH_FINALLY(igraph_es_destroy, &es); IGRAPH_CHECK(igraph_eit_create(graph, es, &eit)); IGRAPH_FINALLY(igraph_eit_destroy, &eit); while (!IGRAPH_EIT_END(eit)) { edge = IGRAPH_EIT_GET(eit); from = IGRAPH_FROM(graph, edge); to = IGRAPH_TO(graph, edge); if (from == to) { IGRAPH_CHECK(igraph_vector_push_back(&edges, edge)); } IGRAPH_EIT_NEXT(eit); } igraph_eit_destroy(&eit); igraph_es_destroy(&es); IGRAPH_FINALLY_CLEAN(2); if (igraph_vector_size(&edges) > 0) { IGRAPH_CHECK(igraph_delete_edges(graph, igraph_ess_vector(&edges))); } igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } if (attr) { IGRAPH_VECTOR_INIT_FINALLY(&mergeinto, no_of_edges); } IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_CHECK(igraph_vector_reserve(&edges, no_of_edges * 2)); IGRAPH_CHECK(igraph_es_all(&es, IGRAPH_EDGEORDER_FROM)); IGRAPH_FINALLY(igraph_es_destroy, &es); IGRAPH_CHECK(igraph_eit_create(graph, es, &eit)); IGRAPH_FINALLY(igraph_eit_destroy, &eit); for (actedge = -1; !IGRAPH_EIT_END(eit); IGRAPH_EIT_NEXT(eit)) { edge = IGRAPH_EIT_GET(eit); from = IGRAPH_FROM(graph, edge); to = IGRAPH_TO(graph, edge); if (loops && from == to) { /* Loop edge to be removed */ if (attr) { VECTOR(mergeinto)[edge] = -1; } } else if (multiple && from == pfrom && to == pto) { /* Multiple edge to be contracted */ if (attr) { VECTOR(mergeinto)[edge] = actedge; } } else { /* Edge to be kept */ igraph_vector_push_back(&edges, from); igraph_vector_push_back(&edges, to); if (attr) { actedge++; VECTOR(mergeinto)[edge] = actedge; } } pfrom = from; pto = to; } igraph_eit_destroy(&eit); igraph_es_destroy(&es); IGRAPH_FINALLY_CLEAN(2); IGRAPH_CHECK(igraph_create(&res, &edges, (igraph_integer_t) no_of_nodes, igraph_is_directed(graph))); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); IGRAPH_FINALLY(igraph_destroy, &res); IGRAPH_I_ATTRIBUTE_DESTROY(&res); IGRAPH_I_ATTRIBUTE_COPY(&res, graph, /*graph=*/ 1, /*vertex=*/ 1, /*edge=*/ 0); if (attr) { igraph_fixed_vectorlist_t vl; IGRAPH_CHECK(igraph_fixed_vectorlist_convert(&vl, &mergeinto, actedge + 1)); IGRAPH_FINALLY(igraph_fixed_vectorlist_destroy, &vl); IGRAPH_CHECK(igraph_i_attribute_combine_edges(graph, &res, &vl.v, edge_comb)); igraph_fixed_vectorlist_destroy(&vl); igraph_vector_destroy(&mergeinto); IGRAPH_FINALLY_CLEAN(2); } IGRAPH_FINALLY_CLEAN(1); igraph_destroy(graph); *graph = res; return 0; } /** * \ingroup structural * \function igraph_reciprocity * \brief Calculates the reciprocity of a directed graph. * * * The measure of reciprocity defines the proportion of mutual * connections, in a directed graph. It is most commonly defined as * the probability that the opposite counterpart of a directed edge is * also included in the graph. In adjacency matrix notation: * sum(i, j, (A.*A')ij) / sum(i, j, Aij), where * A.*A' is the element-wise product of matrix * A and its transpose. This measure is * calculated if the \p mode argument is \c * IGRAPH_RECIPROCITY_DEFAULT. * * * Prior to igraph version 0.6, another measure was implemented, * defined as the probability of mutual connection between a vertex * pair if we know that there is a (possibly non-mutual) connection * between them. In other words, (unordered) vertex pairs are * classified into three groups: (1) disconnected, (2) * non-reciprocally connected, (3) reciprocally connected. * The result is the size of group (3), divided by the sum of group * sizes (2)+(3). This measure is calculated if \p mode is \c * IGRAPH_RECIPROCITY_RATIO. * * \param graph The graph object. * \param res Pointer to an \c igraph_real_t which will contain the result. * \param ignore_loops Whether to ignore loop edges. * \param mode Type of reciprocity to calculate, possible values are * \c IGRAPH_RECIPROCITY_DEFAULT and \c IGRAPH_RECIPROCITY_RATIO, * please see their description above. * \return Error code: * \c IGRAPH_EINVAL: graph has no edges * \c IGRAPH_ENOMEM: not enough memory for * temporary data. * * Time complexity: O(|V|+|E|), |V| is the number of vertices, * |E| is the number of edges. * * \example examples/simple/igraph_reciprocity.c */ int igraph_reciprocity(const igraph_t *graph, igraph_real_t *res, igraph_bool_t ignore_loops, igraph_reciprocity_t mode) { igraph_integer_t nonrec = 0, rec = 0, loops = 0; igraph_vector_t inneis, outneis; long int i; long int no_of_nodes = igraph_vcount(graph); if (mode != IGRAPH_RECIPROCITY_DEFAULT && mode != IGRAPH_RECIPROCITY_RATIO) { IGRAPH_ERROR("Invalid reciprocity type", IGRAPH_EINVAL); } /* THIS IS AN EXIT HERE !!!!!!!!!!!!!! */ if (!igraph_is_directed(graph)) { *res = 1.0; return 0; } IGRAPH_VECTOR_INIT_FINALLY(&inneis, 0); IGRAPH_VECTOR_INIT_FINALLY(&outneis, 0); for (i = 0; i < no_of_nodes; i++) { long int ip, op; igraph_neighbors(graph, &inneis, (igraph_integer_t) i, IGRAPH_IN); igraph_neighbors(graph, &outneis, (igraph_integer_t) i, IGRAPH_OUT); ip = op = 0; while (ip < igraph_vector_size(&inneis) && op < igraph_vector_size(&outneis)) { if (VECTOR(inneis)[ip] < VECTOR(outneis)[op]) { nonrec += 1; ip++; } else if (VECTOR(inneis)[ip] > VECTOR(outneis)[op]) { nonrec += 1; op++; } else { /* loop edge? */ if (VECTOR(inneis)[ip] == i) { loops += 1; if (!ignore_loops) { rec += 1; } } else { rec += 1; } ip++; op++; } } nonrec += (igraph_vector_size(&inneis) - ip) + (igraph_vector_size(&outneis) - op); } if (mode == IGRAPH_RECIPROCITY_DEFAULT) { if (ignore_loops) { *res = (igraph_real_t) rec / (igraph_ecount(graph) - loops); } else { *res = (igraph_real_t) rec / (igraph_ecount(graph)); } } else if (mode == IGRAPH_RECIPROCITY_RATIO) { *res = (igraph_real_t) rec / (rec + nonrec); } igraph_vector_destroy(&inneis); igraph_vector_destroy(&outneis); IGRAPH_FINALLY_CLEAN(2); return 0; } /** * \function igraph_constraint * \brief Burt's constraint scores. * * * This function calculates Burt's constraint scores for the given * vertices, also known as structural holes. * * * Burt's constraint is higher if ego has less, or mutually stronger * related (i.e. more redundant) contacts. Burt's measure of * constraint, C[i], of vertex i's ego network V[i], is defined for * directed and valued graphs, *
* C[i] = sum( sum( (p[i,q] p[q,j])^2, q in V[i], q != i,j ), j in * V[], j != i) *
* for a graph of order (ie. number of vertices) N, where proportional * tie strengths are defined as *
* p[i,j]=(a[i,j]+a[j,i]) / sum(a[i,k]+a[k,i], k in V[i], k != i), *
* a[i,j] are elements of A and * the latter being the graph adjacency matrix. For isolated vertices, * constraint is undefined. * * * Burt, R.S. (2004). Structural holes and good ideas. American * Journal of Sociology 110, 349-399. * * * The first R version of this function was contributed by Jeroen * Bruggeman. * \param graph A graph object. * \param res Pointer to an initialized vector, the result will be * stored here. The vector will be resized to have the * appropriate size for holding the result. * \param vids Vertex selector containing the vertices for which the * constraint should be calculated. * \param weights Vector giving the weights of the edges. If it is * \c NULL then each edge is supposed to have the same weight. * \return Error code. * * Time complexity: O(|V|+E|+n*d^2), n is the number of vertices for * which the constraint is calculated and d is the average degree, |V| * is the number of vertices, |E| the number of edges in the * graph. If the weights argument is \c NULL then the time complexity * is O(|V|+n*d^2). */ int igraph_constraint(const igraph_t *graph, igraph_vector_t *res, igraph_vs_t vids, const igraph_vector_t *weights) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_vit_t vit; long int nodes_to_calc; long int a, b, c, i, j, q; igraph_integer_t edge, from, to, edge2, from2, to2; igraph_vector_t contrib; igraph_vector_t degree; igraph_vector_t ineis_in, ineis_out, jneis_in, jneis_out; if (weights != 0 && igraph_vector_size(weights) != no_of_edges) { IGRAPH_ERROR("Invalid length of weight vector", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(&contrib, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(°ree, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&ineis_in, 0); IGRAPH_VECTOR_INIT_FINALLY(&ineis_out, 0); IGRAPH_VECTOR_INIT_FINALLY(&jneis_in, 0); IGRAPH_VECTOR_INIT_FINALLY(&jneis_out, 0); IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); nodes_to_calc = IGRAPH_VIT_SIZE(vit); if (weights == 0) { IGRAPH_CHECK(igraph_degree(graph, °ree, igraph_vss_all(), IGRAPH_ALL, IGRAPH_NO_LOOPS)); } else { for (a = 0; a < no_of_edges; a++) { igraph_edge(graph, (igraph_integer_t) a, &from, &to); if (from != to) { VECTOR(degree)[(long int) from] += VECTOR(*weights)[a]; VECTOR(degree)[(long int) to ] += VECTOR(*weights)[a]; } } } IGRAPH_CHECK(igraph_vector_resize(res, nodes_to_calc)); igraph_vector_null(res); for (a = 0; a < nodes_to_calc; a++, IGRAPH_VIT_NEXT(vit)) { i = IGRAPH_VIT_GET(vit); /* get neighbors of i */ IGRAPH_CHECK(igraph_incident(graph, &ineis_in, (igraph_integer_t) i, IGRAPH_IN)); IGRAPH_CHECK(igraph_incident(graph, &ineis_out, (igraph_integer_t) i, IGRAPH_OUT)); /* NaN for isolates */ if (igraph_vector_size(&ineis_in) == 0 && igraph_vector_size(&ineis_out) == 0) { VECTOR(*res)[a] = IGRAPH_NAN; } /* zero their contribution */ for (b = 0; b < igraph_vector_size(&ineis_in); b++) { edge = (igraph_integer_t) VECTOR(ineis_in)[b]; igraph_edge(graph, edge, &from, &to); if (to == i) { to = from; } j = to; VECTOR(contrib)[j] = 0.0; } for (b = 0; b < igraph_vector_size(&ineis_out); b++) { edge = (igraph_integer_t) VECTOR(ineis_out)[b]; igraph_edge(graph, edge, &from, &to); if (to == i) { to = from; } j = to; VECTOR(contrib)[j] = 0.0; } /* add the direct contributions, in-neighbors and out-neighbors */ for (b = 0; b < igraph_vector_size(&ineis_in); b++) { edge = (igraph_integer_t) VECTOR(ineis_in)[b]; igraph_edge(graph, edge, &from, &to); if (to == i) { to = from; } j = to; if (i != j) { /* excluding loops */ if (weights) { VECTOR(contrib)[j] += VECTOR(*weights)[(long int)edge] / VECTOR(degree)[i]; } else { VECTOR(contrib)[j] += 1.0 / VECTOR(degree)[i]; } } } if (igraph_is_directed(graph)) { for (b = 0; b < igraph_vector_size(&ineis_out); b++) { edge = (igraph_integer_t) VECTOR(ineis_out)[b]; igraph_edge(graph, edge, &from, &to); if (to == i) { to = from; } j = to; if (i != j) { if (weights) { VECTOR(contrib)[j] += VECTOR(*weights)[(long int)edge] / VECTOR(degree)[i]; } else { VECTOR(contrib)[j] += 1.0 / VECTOR(degree)[i]; } } } } /* add the indirect contributions, in-in, in-out, out-in, out-out */ for (b = 0; b < igraph_vector_size(&ineis_in); b++) { edge = (igraph_integer_t) VECTOR(ineis_in)[b]; igraph_edge(graph, edge, &from, &to); if (to == i) { to = from; } j = to; if (i == j) { continue; } IGRAPH_CHECK(igraph_incident(graph, &jneis_in, (igraph_integer_t) j, IGRAPH_IN)); IGRAPH_CHECK(igraph_incident(graph, &jneis_out, (igraph_integer_t) j, IGRAPH_OUT)); for (c = 0; c < igraph_vector_size(&jneis_in); c++) { edge2 = (igraph_integer_t) VECTOR(jneis_in)[c]; igraph_edge(graph, edge2, &from2, &to2); if (to2 == j) { to2 = from2; } q = to2; if (j != q) { if (weights) { VECTOR(contrib)[q] += VECTOR(*weights)[(long int)edge] * VECTOR(*weights)[(long int)edge2] / VECTOR(degree)[i] / VECTOR(degree)[j]; } else { VECTOR(contrib)[q] += 1 / VECTOR(degree)[i] / VECTOR(degree)[j]; } } } if (igraph_is_directed(graph)) { for (c = 0; c < igraph_vector_size(&jneis_out); c++) { edge2 = (igraph_integer_t) VECTOR(jneis_out)[c]; igraph_edge(graph, edge2, &from2, &to2); if (to2 == j) { to2 = from2; } q = to2; if (j != q) { if (weights) { VECTOR(contrib)[q] += VECTOR(*weights)[(long int)edge] * VECTOR(*weights)[(long int)edge2] / VECTOR(degree)[i] / VECTOR(degree)[j]; } else { VECTOR(contrib)[q] += 1 / VECTOR(degree)[i] / VECTOR(degree)[j]; } } } } } if (igraph_is_directed(graph)) { for (b = 0; b < igraph_vector_size(&ineis_out); b++) { edge = (igraph_integer_t) VECTOR(ineis_out)[b]; igraph_edge(graph, edge, &from, &to); if (to == i) { to = from; } j = to; if (i == j) { continue; } IGRAPH_CHECK(igraph_incident(graph, &jneis_in, (igraph_integer_t) j, IGRAPH_IN)); IGRAPH_CHECK(igraph_incident(graph, &jneis_out, (igraph_integer_t) j, IGRAPH_OUT)); for (c = 0; c < igraph_vector_size(&jneis_in); c++) { edge2 = (igraph_integer_t) VECTOR(jneis_in)[c]; igraph_edge(graph, edge2, &from2, &to2); if (to2 == j) { to2 = from2; } q = to2; if (j != q) { if (weights) { VECTOR(contrib)[q] += VECTOR(*weights)[(long int)edge] * VECTOR(*weights)[(long int)edge2] / VECTOR(degree)[i] / VECTOR(degree)[j]; } else { VECTOR(contrib)[q] += 1 / VECTOR(degree)[i] / VECTOR(degree)[j]; } } } for (c = 0; c < igraph_vector_size(&jneis_out); c++) { edge2 = (igraph_integer_t) VECTOR(jneis_out)[c]; igraph_edge(graph, edge2, &from2, &to2); if (to2 == j) { to2 = from2; } q = to2; if (j != q) { if (weights) { VECTOR(contrib)[q] += VECTOR(*weights)[(long int)edge] * VECTOR(*weights)[(long int)edge2] / VECTOR(degree)[i] / VECTOR(degree)[j]; } else { VECTOR(contrib)[q] += 1 / VECTOR(degree)[i] / VECTOR(degree)[j]; } } } } } /* squared sum of the contributions */ for (b = 0; b < igraph_vector_size(&ineis_in); b++) { edge = (igraph_integer_t) VECTOR(ineis_in)[b]; igraph_edge(graph, edge, &from, &to); if (to == i) { to = from; } j = to; if (i == j) { continue; } VECTOR(*res)[a] += VECTOR(contrib)[j] * VECTOR(contrib)[j]; VECTOR(contrib)[j] = 0.0; } if (igraph_is_directed(graph)) { for (b = 0; b < igraph_vector_size(&ineis_out); b++) { edge = (igraph_integer_t) VECTOR(ineis_out)[b]; igraph_edge(graph, edge, &from, &to); if (to == i) { to = from; } j = to; if (i == j) { continue; } VECTOR(*res)[a] += VECTOR(contrib)[j] * VECTOR(contrib)[j]; VECTOR(contrib)[j] = 0.0; } } } igraph_vit_destroy(&vit); igraph_vector_destroy(&jneis_out); igraph_vector_destroy(&jneis_in); igraph_vector_destroy(&ineis_out); igraph_vector_destroy(&ineis_in); igraph_vector_destroy(°ree); igraph_vector_destroy(&contrib); IGRAPH_FINALLY_CLEAN(7); return 0; } /** * \function igraph_maxdegree * \brief Calculate the maximum degree in a graph (or set of vertices). * * * The largest in-, out- or total degree of the specified vertices is * calculated. * \param graph The input graph. * \param res Pointer to an integer (\c igraph_integer_t), the result * will be stored here. * \param vids Vector giving the vertex IDs for which the maximum degree will * be calculated. * \param mode Defines the type of the degree. * \c IGRAPH_OUT, out-degree, * \c IGRAPH_IN, in-degree, * \c IGRAPH_ALL, total degree (sum of the * in- and out-degree). * This parameter is ignored for undirected graphs. * \param loops Boolean, gives whether the self-loops should be * counted. * \return Error code: * \c IGRAPH_EINVVID: invalid vertex id. * \c IGRAPH_EINVMODE: invalid mode argument. * * Time complexity: O(v) if * loops is * TRUE, and * O(v*d) * otherwise. v is the number * vertices for which the degree will be calculated, and * d is their (average) degree. */ int igraph_maxdegree(const igraph_t *graph, igraph_integer_t *res, igraph_vs_t vids, igraph_neimode_t mode, igraph_bool_t loops) { igraph_vector_t tmp; IGRAPH_VECTOR_INIT_FINALLY(&tmp, 0); igraph_degree(graph, &tmp, vids, mode, loops); *res = (igraph_integer_t) igraph_vector_max(&tmp); igraph_vector_destroy(&tmp); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_density * Calculate the density of a graph. * * The density of a graph is simply the ratio number of * edges and the number of possible edges. Note that density is * ill-defined for graphs with multiple and/or loop edges, so consider * calling \ref igraph_simplify() on the graph if you know that it * contains multiple or loop edges. * \param graph The input graph object. * \param res Pointer to a real number, the result will be stored * here. * \param loops Logical constant, whether to include loops in the * calculation. If this constant is TRUE then * loop edges are thought to be possible in the graph (this does not * necessarily mean that the graph really contains any loops). If * this is FALSE then the result is only correct if the graph does not * contain loops. * \return Error code. * * Time complexity: O(1). */ int igraph_density(const igraph_t *graph, igraph_real_t *res, igraph_bool_t loops) { igraph_integer_t no_of_nodes = igraph_vcount(graph); igraph_real_t no_of_edges = igraph_ecount(graph); igraph_bool_t directed = igraph_is_directed(graph); if (no_of_nodes == 0) { *res = IGRAPH_NAN; return 0; } if (!loops) { if (no_of_nodes == 1) { *res = IGRAPH_NAN; } else if (directed) { *res = no_of_edges / no_of_nodes / (no_of_nodes - 1); } else { *res = no_of_edges / no_of_nodes * 2.0 / (no_of_nodes - 1); } } else { if (directed) { *res = no_of_edges / no_of_nodes / no_of_nodes; } else { *res = no_of_edges / no_of_nodes * 2.0 / (no_of_nodes + 1); } } return 0; } /** * \function igraph_neighborhood_size * \brief Calculates the size of the neighborhood of a given vertex. * * The neighborhood of a given order of a vertex includes all vertices * which are closer to the vertex than the order. Ie. order 0 is * always the vertex itself, order 1 is the vertex plus its immediate * neighbors, order 2 is order 1 plus the immediate neighbors of the * vertices in order 1, etc. * * This function calculates the size of the neighborhood * of the given order for the given vertices. * \param graph The input graph. * \param res Pointer to an initialized vector, the result will be * stored here. It will be resized as needed. * \param vids The vertices for which the calculation is performed. * \param order Integer giving the order of the neighborhood. * \param mode Specifies how to use the direction of the edges if a * directed graph is analyzed. For \c IGRAPH_OUT only the outgoing * edges are followed, so all vertices reachable from the source * vertex in at most \c order steps are counted. For \c IGRAPH_IN * all vertices from which the source vertex is reachable in at most * \c order steps are counted. \c IGRAPH_ALL ignores the direction * of the edges. This argument is ignored for undirected graphs. * \param mindist The minimum distance to include a vertex in the counting. * If this is one, then the starting vertex is not counted. If this is * two, then its neighbors are not counted, either, etc. * \return Error code. * * \sa \ref igraph_neighborhood() for calculating the actual neighborhood, * \ref igraph_neighborhood_graphs() for creating separate graphs from * the neighborhoods. * * Time complexity: O(n*d*o), where n is the number vertices for which * the calculation is performed, d is the average degree, o is the order. */ int igraph_neighborhood_size(const igraph_t *graph, igraph_vector_t *res, igraph_vs_t vids, igraph_integer_t order, igraph_neimode_t mode, igraph_integer_t mindist) { long int no_of_nodes = igraph_vcount(graph); igraph_dqueue_t q; igraph_vit_t vit; long int i, j; long int *added; igraph_vector_t neis; if (order < 0) { IGRAPH_ERROR("Negative order in neighborhood size", IGRAPH_EINVAL); } if (mindist < 0 || mindist > order) { IGRAPH_ERROR("Minimum distance should be between zero and order", IGRAPH_EINVAL); } added = igraph_Calloc(no_of_nodes, long int); if (added == 0) { IGRAPH_ERROR("Cannot calculate neighborhood size", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, added); IGRAPH_DQUEUE_INIT_FINALLY(&q, 100); IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); IGRAPH_CHECK(igraph_vector_resize(res, IGRAPH_VIT_SIZE(vit))); for (i = 0; !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit), i++) { long int node = IGRAPH_VIT_GET(vit); long int size = mindist == 0 ? 1 : 0; added[node] = i + 1; igraph_dqueue_clear(&q); if (order > 0) { igraph_dqueue_push(&q, node); igraph_dqueue_push(&q, 0); } while (!igraph_dqueue_empty(&q)) { long int actnode = (long int) igraph_dqueue_pop(&q); long int actdist = (long int) igraph_dqueue_pop(&q); long int n; igraph_neighbors(graph, &neis, (igraph_integer_t) actnode, mode); n = igraph_vector_size(&neis); if (actdist < order - 1) { /* we add them to the q */ for (j = 0; j < n; j++) { long int nei = (long int) VECTOR(neis)[j]; if (added[nei] != i + 1) { added[nei] = i + 1; IGRAPH_CHECK(igraph_dqueue_push(&q, nei)); IGRAPH_CHECK(igraph_dqueue_push(&q, actdist + 1)); if (actdist + 1 >= mindist) { size++; } } } } else { /* we just count them, but don't add them */ for (j = 0; j < n; j++) { long int nei = (long int) VECTOR(neis)[j]; if (added[nei] != i + 1) { added[nei] = i + 1; if (actdist + 1 >= mindist) { size++; } } } } } /* while q not empty */ VECTOR(*res)[i] = size; } /* for VIT, i */ igraph_vector_destroy(&neis); igraph_vit_destroy(&vit); igraph_dqueue_destroy(&q); igraph_Free(added); IGRAPH_FINALLY_CLEAN(4); return 0; } /** * \function igraph_neighborhood * Calculate the neighborhood of vertices. * * The neighborhood of a given order of a vertex includes all vertices * which are closer to the vertex than the order. Ie. order 0 is * always the vertex itself, order 1 is the vertex plus its immediate * neighbors, order 2 is order 1 plus the immediate neighbors of the * vertices in order 1, etc. * * This function calculates the vertices within the * neighborhood of the specified vertices. * \param graph The input graph. * \param res An initialized pointer vector. Note that the objects * (pointers) in the vector will \em not be freed, but the pointer * vector will be resized as needed. The result of the calculation * will be stored here in \c vector_t objects. * \param vids The vertices for which the calculation is performed. * \param order Integer giving the order of the neighborhood. * \param mode Specifies how to use the direction of the edges if a * directed graph is analyzed. For \c IGRAPH_OUT only the outgoing * edges are followed, so all vertices reachable from the source * vertex in at most \c order steps are included. For \c IGRAPH_IN * all vertices from which the source vertex is reachable in at most * \c order steps are included. \c IGRAPH_ALL ignores the direction * of the edges. This argument is ignored for undirected graphs. * \param mindist The minimum distance to include a vertex in the counting. * If this is one, then the starting vertex is not counted. If this is * two, then its neighbors are not counted, either, etc. * \return Error code. * * \sa \ref igraph_neighborhood_size() to calculate the size of the * neighborhood, \ref igraph_neighborhood_graphs() for creating * graphs from the neighborhoods. * * Time complexity: O(n*d*o), n is the number of vertices for which * the calculation is performed, d is the average degree, o is the * order. */ int igraph_neighborhood(const igraph_t *graph, igraph_vector_ptr_t *res, igraph_vs_t vids, igraph_integer_t order, igraph_neimode_t mode, igraph_integer_t mindist) { long int no_of_nodes = igraph_vcount(graph); igraph_dqueue_t q; igraph_vit_t vit; long int i, j; long int *added; igraph_vector_t neis; igraph_vector_t tmp; igraph_vector_t *newv; if (order < 0) { IGRAPH_ERROR("Negative order in neighborhood size", IGRAPH_EINVAL); } if (mindist < 0 || mindist > order) { IGRAPH_ERROR("Minimum distance should be between zero and order", IGRAPH_EINVAL); } added = igraph_Calloc(no_of_nodes, long int); if (added == 0) { IGRAPH_ERROR("Cannot calculate neighborhood size", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, added); IGRAPH_DQUEUE_INIT_FINALLY(&q, 100); IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); IGRAPH_VECTOR_INIT_FINALLY(&tmp, 0); IGRAPH_CHECK(igraph_vector_ptr_resize(res, IGRAPH_VIT_SIZE(vit))); for (i = 0; !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit), i++) { long int node = IGRAPH_VIT_GET(vit); added[node] = i + 1; igraph_vector_clear(&tmp); if (mindist == 0) { IGRAPH_CHECK(igraph_vector_push_back(&tmp, node)); } if (order > 0) { igraph_dqueue_push(&q, node); igraph_dqueue_push(&q, 0); } while (!igraph_dqueue_empty(&q)) { long int actnode = (long int) igraph_dqueue_pop(&q); long int actdist = (long int) igraph_dqueue_pop(&q); long int n; igraph_neighbors(graph, &neis, (igraph_integer_t) actnode, mode); n = igraph_vector_size(&neis); if (actdist < order - 1) { /* we add them to the q */ for (j = 0; j < n; j++) { long int nei = (long int) VECTOR(neis)[j]; if (added[nei] != i + 1) { added[nei] = i + 1; IGRAPH_CHECK(igraph_dqueue_push(&q, nei)); IGRAPH_CHECK(igraph_dqueue_push(&q, actdist + 1)); if (actdist + 1 >= mindist) { IGRAPH_CHECK(igraph_vector_push_back(&tmp, nei)); } } } } else { /* we just count them but don't add them to q */ for (j = 0; j < n; j++) { long int nei = (long int) VECTOR(neis)[j]; if (added[nei] != i + 1) { added[nei] = i + 1; if (actdist + 1 >= mindist) { IGRAPH_CHECK(igraph_vector_push_back(&tmp, nei)); } } } } } /* while q not empty */ newv = igraph_Calloc(1, igraph_vector_t); if (newv == 0) { IGRAPH_ERROR("Cannot calculate neighborhood", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newv); IGRAPH_CHECK(igraph_vector_copy(newv, &tmp)); VECTOR(*res)[i] = newv; IGRAPH_FINALLY_CLEAN(1); } igraph_vector_destroy(&tmp); igraph_vector_destroy(&neis); igraph_vit_destroy(&vit); igraph_dqueue_destroy(&q); igraph_Free(added); IGRAPH_FINALLY_CLEAN(5); return 0; } /** * \function igraph_neighborhood_graphs * Create graphs from the neighborhood(s) of some vertex/vertices. * * The neighborhood of a given order of a vertex includes all vertices * which are closer to the vertex than the order. Ie. order 0 is * always the vertex itself, order 1 is the vertex plus its immediate * neighbors, order 2 is order 1 plus the immediate neighbors of the * vertices in order 1, etc. * * This function finds every vertex in the neighborhood * of a given parameter vertex and creates a graph from these * vertices. * * The first version of this function was written by * Vincent Matossian, thanks Vincent. * \param graph The input graph. * \param res Pointer to a pointer vector, the result will be stored * here, ie. \c res will contain pointers to \c igraph_t * objects. It will be resized if needed but note that the * objects in the pointer vector will not be freed. * \param vids The vertices for which the calculation is performed. * \param order Integer giving the order of the neighborhood. * \param mode Specifies how to use the direction of the edges if a * directed graph is analyzed. For \c IGRAPH_OUT only the outgoing * edges are followed, so all vertices reachable from the source * vertex in at most \c order steps are counted. For \c IGRAPH_IN * all vertices from which the source vertex is reachable in at most * \c order steps are counted. \c IGRAPH_ALL ignores the direction * of the edges. This argument is ignored for undirected graphs. * \param mindist The minimum distance to include a vertex in the counting. * If this is one, then the starting vertex is not counted. If this is * two, then its neighbors are not counted, either, etc. * \return Error code. * * \sa \ref igraph_neighborhood_size() for calculating the neighborhood * sizes only, \ref igraph_neighborhood() for calculating the * neighborhoods (but not creating graphs). * * Time complexity: O(n*(|V|+|E|)), where n is the number vertices for * which the calculation is performed, |V| and |E| are the number of * vertices and edges in the original input graph. */ int igraph_neighborhood_graphs(const igraph_t *graph, igraph_vector_ptr_t *res, igraph_vs_t vids, igraph_integer_t order, igraph_neimode_t mode, igraph_integer_t mindist) { long int no_of_nodes = igraph_vcount(graph); igraph_dqueue_t q; igraph_vit_t vit; long int i, j; long int *added; igraph_vector_t neis; igraph_vector_t tmp; igraph_t *newg; if (order < 0) { IGRAPH_ERROR("Negative order in neighborhood size", IGRAPH_EINVAL); } if (mindist < 0 || mindist > order) { IGRAPH_ERROR("Minimum distance should be between zero and order", IGRAPH_EINVAL); } added = igraph_Calloc(no_of_nodes, long int); if (added == 0) { IGRAPH_ERROR("Cannot calculate neighborhood size", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, added); IGRAPH_DQUEUE_INIT_FINALLY(&q, 100); IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); IGRAPH_VECTOR_INIT_FINALLY(&tmp, 0); IGRAPH_CHECK(igraph_vector_ptr_resize(res, IGRAPH_VIT_SIZE(vit))); for (i = 0; !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit), i++) { long int node = IGRAPH_VIT_GET(vit); added[node] = i + 1; igraph_vector_clear(&tmp); if (mindist == 0) { IGRAPH_CHECK(igraph_vector_push_back(&tmp, node)); } if (order > 0) { igraph_dqueue_push(&q, node); igraph_dqueue_push(&q, 0); } while (!igraph_dqueue_empty(&q)) { long int actnode = (long int) igraph_dqueue_pop(&q); long int actdist = (long int) igraph_dqueue_pop(&q); long int n; igraph_neighbors(graph, &neis, (igraph_integer_t) actnode, mode); n = igraph_vector_size(&neis); if (actdist < order - 1) { /* we add them to the q */ for (j = 0; j < n; j++) { long int nei = (long int) VECTOR(neis)[j]; if (added[nei] != i + 1) { added[nei] = i + 1; IGRAPH_CHECK(igraph_dqueue_push(&q, nei)); IGRAPH_CHECK(igraph_dqueue_push(&q, actdist + 1)); if (actdist + 1 >= mindist) { IGRAPH_CHECK(igraph_vector_push_back(&tmp, nei)); } } } } else { /* we just count them but don't add them to q */ for (j = 0; j < n; j++) { long int nei = (long int) VECTOR(neis)[j]; if (added[nei] != i + 1) { added[nei] = i + 1; if (actdist + 1 >= mindist) { IGRAPH_CHECK(igraph_vector_push_back(&tmp, nei)); } } } } } /* while q not empty */ newg = igraph_Calloc(1, igraph_t); if (newg == 0) { IGRAPH_ERROR("Cannot create neighborhood graph", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, newg); if (igraph_vector_size(&tmp) < no_of_nodes) { IGRAPH_CHECK(igraph_induced_subgraph(graph, newg, igraph_vss_vector(&tmp), IGRAPH_SUBGRAPH_AUTO)); } else { IGRAPH_CHECK(igraph_copy(newg, graph)); } VECTOR(*res)[i] = newg; IGRAPH_FINALLY_CLEAN(1); } igraph_vector_destroy(&tmp); igraph_vector_destroy(&neis); igraph_vit_destroy(&vit); igraph_dqueue_destroy(&q); igraph_Free(added); IGRAPH_FINALLY_CLEAN(5); return 0; } /** * \function igraph_topological_sorting * \brief Calculate a possible topological sorting of the graph. * * * A topological sorting of a directed acyclic graph is a linear ordering * of its nodes where each node comes before all nodes to which it has * edges. Every DAG has at least one topological sort, and may have many. * This function returns a possible topological sort among them. If the * graph is not acyclic (it has at least one cycle), a partial topological * sort is returned and a warning is issued. * * \param graph The input graph. * \param res Pointer to a vector, the result will be stored here. * It will be resized if needed. * \param mode Specifies how to use the direction of the edges. * For \c IGRAPH_OUT, the sorting order ensures that each node comes * before all nodes to which it has edges, so nodes with no incoming * edges go first. For \c IGRAPH_IN, it is quite the opposite: each * node comes before all nodes from which it receives edges. Nodes * with no outgoing edges go first. * \return Error code. * * Time complexity: O(|V|+|E|), where |V| and |E| are the number of * vertices and edges in the original input graph. * * \sa \ref igraph_is_dag() if you are only interested in whether a given * graph is a DAG or not, or \ref igraph_feedback_arc_set() to find a * set of edges whose removal makes the graph a DAG. * * \example examples/simple/igraph_topological_sorting.c */ int igraph_topological_sorting(const igraph_t* graph, igraph_vector_t *res, igraph_neimode_t mode) { long int no_of_nodes = igraph_vcount(graph); igraph_vector_t degrees, neis; igraph_dqueue_t sources; igraph_neimode_t deg_mode; long int node, i, j; if (mode == IGRAPH_ALL || !igraph_is_directed(graph)) { IGRAPH_ERROR("topological sorting does not make sense for undirected graphs", IGRAPH_EINVAL); } else if (mode == IGRAPH_OUT) { deg_mode = IGRAPH_IN; } else if (mode == IGRAPH_IN) { deg_mode = IGRAPH_OUT; } else { IGRAPH_ERROR("invalid mode", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(°rees, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); IGRAPH_CHECK(igraph_dqueue_init(&sources, 0)); IGRAPH_FINALLY(igraph_dqueue_destroy, &sources); IGRAPH_CHECK(igraph_degree(graph, °rees, igraph_vss_all(), deg_mode, 0)); igraph_vector_clear(res); /* Do we have nodes with no incoming vertices? */ for (i = 0; i < no_of_nodes; i++) { if (VECTOR(degrees)[i] == 0) { IGRAPH_CHECK(igraph_dqueue_push(&sources, i)); } } /* Take all nodes with no incoming vertices and remove them */ while (!igraph_dqueue_empty(&sources)) { igraph_real_t tmp = igraph_dqueue_pop(&sources); node = (long) tmp; /* Add the node to the result vector */ igraph_vector_push_back(res, node); /* Exclude the node from further source searches */ VECTOR(degrees)[node] = -1; /* Get the neighbors and decrease their degrees by one */ IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) node, mode)); j = igraph_vector_size(&neis); for (i = 0; i < j; i++) { VECTOR(degrees)[(long)VECTOR(neis)[i]]--; if (VECTOR(degrees)[(long)VECTOR(neis)[i]] == 0) { IGRAPH_CHECK(igraph_dqueue_push(&sources, VECTOR(neis)[i])); } } } if (igraph_vector_size(res) < no_of_nodes) { IGRAPH_WARNING("graph contains a cycle, partial result is returned"); } igraph_vector_destroy(°rees); igraph_vector_destroy(&neis); igraph_dqueue_destroy(&sources); IGRAPH_FINALLY_CLEAN(3); return 0; } /** * \function igraph_is_dag * Checks whether a graph is a directed acyclic graph (DAG) or not. * * * A directed acyclic graph (DAG) is a directed graph with no cycles. * * \param graph The input graph. * \param res Pointer to a boolean constant, the result * is stored here. * \return Error code. * * Time complexity: O(|V|+|E|), where |V| and |E| are the number of * vertices and edges in the original input graph. * * \sa \ref igraph_topological_sorting() to get a possible topological * sorting of a DAG. */ int igraph_is_dag(const igraph_t* graph, igraph_bool_t *res) { long int no_of_nodes = igraph_vcount(graph); igraph_vector_t degrees, neis; igraph_dqueue_t sources; long int node, i, j, nei, vertices_left; if (!igraph_is_directed(graph)) { *res = 0; return IGRAPH_SUCCESS; } IGRAPH_VECTOR_INIT_FINALLY(°rees, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); IGRAPH_CHECK(igraph_dqueue_init(&sources, 0)); IGRAPH_FINALLY(igraph_dqueue_destroy, &sources); IGRAPH_CHECK(igraph_degree(graph, °rees, igraph_vss_all(), IGRAPH_OUT, 1)); vertices_left = no_of_nodes; /* Do we have nodes with no incoming edges? */ for (i = 0; i < no_of_nodes; i++) { if (VECTOR(degrees)[i] == 0) { IGRAPH_CHECK(igraph_dqueue_push(&sources, i)); } } /* Take all nodes with no incoming edges and remove them */ while (!igraph_dqueue_empty(&sources)) { igraph_real_t tmp = igraph_dqueue_pop(&sources); node = (long) tmp; /* Exclude the node from further source searches */ VECTOR(degrees)[node] = -1; vertices_left--; /* Get the neighbors and decrease their degrees by one */ IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) node, IGRAPH_IN)); j = igraph_vector_size(&neis); for (i = 0; i < j; i++) { nei = (long)VECTOR(neis)[i]; if (nei == node) { continue; } VECTOR(degrees)[nei]--; if (VECTOR(degrees)[nei] == 0) { IGRAPH_CHECK(igraph_dqueue_push(&sources, nei)); } } } *res = (vertices_left == 0); if (vertices_left < 0) { IGRAPH_WARNING("vertices_left < 0 in igraph_is_dag, possible bug"); } igraph_vector_destroy(°rees); igraph_vector_destroy(&neis); igraph_dqueue_destroy(&sources); IGRAPH_FINALLY_CLEAN(3); return IGRAPH_SUCCESS; } /** * \function igraph_is_simple * \brief Decides whether the input graph is a simple graph. * * * A graph is a simple graph if it does not contain loop edges and * multiple edges. * * \param graph The input graph. * \param res Pointer to a boolean constant, the result * is stored here. * \return Error code. * * \sa \ref igraph_is_loop() and \ref igraph_is_multiple() to * find the loops and multiple edges, \ref igraph_simplify() to * get rid of them, or \ref igraph_has_multiple() to decide whether * there is at least one multiple edge. * * Time complexity: O(|V|+|E|). */ int igraph_is_simple(const igraph_t *graph, igraph_bool_t *res) { long int vc = igraph_vcount(graph); long int ec = igraph_ecount(graph); if (vc == 0 || ec == 0) { *res = 1; } else { igraph_vector_t neis; long int i, j, n; igraph_bool_t found = 0; IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); for (i = 0; i < vc; i++) { igraph_neighbors(graph, &neis, (igraph_integer_t) i, IGRAPH_OUT); n = igraph_vector_size(&neis); for (j = 0; j < n; j++) { if (VECTOR(neis)[j] == i) { found = 1; break; } if (j > 0 && VECTOR(neis)[j - 1] == VECTOR(neis)[j]) { found = 1; break; } } } *res = !found; igraph_vector_destroy(&neis); IGRAPH_FINALLY_CLEAN(1); } return 0; } /** * \function igraph_has_loop * \brief Returns whether the graph has at least one loop edge. * * * A loop edge is an edge from a vertex to itself. * \param graph The input graph. * \param res Pointer to an initialized boolean vector for storing the result. * * \sa \ref igraph_simplify() to get rid of loop edges. * * Time complexity: O(e), the number of edges to check. * * \example examples/simple/igraph_has_loop.c */ int igraph_has_loop(const igraph_t *graph, igraph_bool_t *res) { long int i, m = igraph_ecount(graph); *res = 0; for (i = 0; i < m; i++) { if (IGRAPH_FROM(graph, i) == IGRAPH_TO(graph, i)) { *res = 1; break; } } return 0; } /** * \function igraph_is_loop * \brief Find the loop edges in a graph. * * * A loop edge is an edge from a vertex to itself. * \param graph The input graph. * \param res Pointer to an initialized boolean vector for storing the result, * it will be resized as needed. * \param es The edges to check, for all edges supply \ref igraph_ess_all() here. * \return Error code. * * \sa \ref igraph_simplify() to get rid of loop edges. * * Time complexity: O(e), the number of edges to check. * * \example examples/simple/igraph_is_loop.c */ int igraph_is_loop(const igraph_t *graph, igraph_vector_bool_t *res, igraph_es_t es) { igraph_eit_t eit; long int i; IGRAPH_CHECK(igraph_eit_create(graph, es, &eit)); IGRAPH_FINALLY(igraph_eit_destroy, &eit); IGRAPH_CHECK(igraph_vector_bool_resize(res, IGRAPH_EIT_SIZE(eit))); for (i = 0; !IGRAPH_EIT_END(eit); i++, IGRAPH_EIT_NEXT(eit)) { long int e = IGRAPH_EIT_GET(eit); VECTOR(*res)[i] = (IGRAPH_FROM(graph, e) == IGRAPH_TO(graph, e)) ? 1 : 0; } igraph_eit_destroy(&eit); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_has_multiple * \brief Check whether the graph has at least one multiple edge. * * * An edge is a multiple edge if there is another * edge with the same head and tail vertices in the graph. * * \param graph The input graph. * \param res Pointer to a boolean variable, the result will be stored here. * \return Error code. * * \sa \ref igraph_count_multiple(), \ref igraph_is_multiple() and \ref igraph_simplify(). * * Time complexity: O(e*d), e is the number of edges to check and d is the * average degree (out-degree in directed graphs) of the vertices at the * tail of the edges. * * \example examples/simple/igraph_has_multiple.c */ int igraph_has_multiple(const igraph_t *graph, igraph_bool_t *res) { long int vc = igraph_vcount(graph); long int ec = igraph_ecount(graph); igraph_bool_t directed = igraph_is_directed(graph); if (vc == 0 || ec == 0) { *res = 0; } else { igraph_vector_t neis; long int i, j, n; igraph_bool_t found = 0; IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); for (i = 0; i < vc && !found; i++) { IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) i, IGRAPH_OUT)); n = igraph_vector_size(&neis); for (j = 1; j < n; j++) { if (VECTOR(neis)[j - 1] == VECTOR(neis)[j]) { /* If the graph is undirected, loop edges appear twice in the neighbor * list, so check the next item as well */ if (directed) { /* Directed, so this is a real multiple edge */ found = 1; break; } else if (VECTOR(neis)[j - 1] != i) { /* Undirected, but not a loop edge */ found = 1; break; } else if (j < n - 1 && VECTOR(neis)[j] == VECTOR(neis)[j + 1]) { /* Undirected, loop edge, multiple times */ found = 1; break; } } } } *res = found; igraph_vector_destroy(&neis); IGRAPH_FINALLY_CLEAN(1); } return 0; } /** * \function igraph_is_multiple * \brief Find the multiple edges in a graph. * * * An edge is a multiple edge if there is another * edge with the same head and tail vertices in the graph. * * * Note that this function returns true only for the second or more * appearances of the multiple edges. * \param graph The input graph. * \param res Pointer to a boolean vector, the result will be stored * here. It will be resized as needed. * \param es The edges to check. Supply \ref igraph_ess_all() if you want * to check all edges. * \return Error code. * * \sa \ref igraph_count_multiple(), \ref igraph_has_multiple() and \ref igraph_simplify(). * * Time complexity: O(e*d), e is the number of edges to check and d is the * average degree (out-degree in directed graphs) of the vertices at the * tail of the edges. * * \example examples/simple/igraph_is_multiple.c */ int igraph_is_multiple(const igraph_t *graph, igraph_vector_bool_t *res, igraph_es_t es) { igraph_eit_t eit; long int i; igraph_lazy_inclist_t inclist; IGRAPH_CHECK(igraph_eit_create(graph, es, &eit)); IGRAPH_FINALLY(igraph_eit_destroy, &eit); IGRAPH_CHECK(igraph_lazy_inclist_init(graph, &inclist, IGRAPH_OUT)); IGRAPH_FINALLY(igraph_lazy_inclist_destroy, &inclist); IGRAPH_CHECK(igraph_vector_bool_resize(res, IGRAPH_EIT_SIZE(eit))); for (i = 0; !IGRAPH_EIT_END(eit); i++, IGRAPH_EIT_NEXT(eit)) { long int e = IGRAPH_EIT_GET(eit); long int from = IGRAPH_FROM(graph, e); long int to = IGRAPH_TO(graph, e); igraph_vector_t *neis = igraph_lazy_inclist_get(&inclist, (igraph_integer_t) from); long int j, n = igraph_vector_size(neis); VECTOR(*res)[i] = 0; for (j = 0; j < n; j++) { long int e2 = (long int) VECTOR(*neis)[j]; long int to2 = IGRAPH_OTHER(graph, e2, from); if (to2 == to && e2 < e) { VECTOR(*res)[i] = 1; } } } igraph_lazy_inclist_destroy(&inclist); igraph_eit_destroy(&eit); IGRAPH_FINALLY_CLEAN(2); return 0; } /** * \function igraph_count_multiple * \brief Count the number of appearances of the edges in a graph. * * * If the graph has no multiple edges then the result vector will be * filled with ones. * (An edge is a multiple edge if there is another * edge with the same head and tail vertices in the graph.) * * * \param graph The input graph. * \param res Pointer to a vector, the result will be stored * here. It will be resized as needed. * \param es The edges to check. Supply \ref igraph_ess_all() if you want * to check all edges. * \return Error code. * * \sa \ref igraph_is_multiple() and \ref igraph_simplify(). * * Time complexity: O(e*d), e is the number of edges to check and d is the * average degree (out-degree in directed graphs) of the vertices at the * tail of the edges. */ int igraph_count_multiple(const igraph_t *graph, igraph_vector_t *res, igraph_es_t es) { igraph_eit_t eit; long int i; igraph_lazy_inclist_t inclist; IGRAPH_CHECK(igraph_eit_create(graph, es, &eit)); IGRAPH_FINALLY(igraph_eit_destroy, &eit); IGRAPH_CHECK(igraph_lazy_inclist_init(graph, &inclist, IGRAPH_OUT)); IGRAPH_FINALLY(igraph_lazy_inclist_destroy, &inclist); IGRAPH_CHECK(igraph_vector_resize(res, IGRAPH_EIT_SIZE(eit))); for (i = 0; !IGRAPH_EIT_END(eit); i++, IGRAPH_EIT_NEXT(eit)) { long int e = IGRAPH_EIT_GET(eit); long int from = IGRAPH_FROM(graph, e); long int to = IGRAPH_TO(graph, e); igraph_vector_t *neis = igraph_lazy_inclist_get(&inclist, (igraph_integer_t) from); long int j, n = igraph_vector_size(neis); VECTOR(*res)[i] = 0; for (j = 0; j < n; j++) { long int e2 = (long int) VECTOR(*neis)[j]; long int to2 = IGRAPH_OTHER(graph, e2, from); if (to2 == to) { VECTOR(*res)[i] += 1; } } /* for loop edges, divide the result by two */ if (to == from) { VECTOR(*res)[i] /= 2; } } igraph_lazy_inclist_destroy(&inclist); igraph_eit_destroy(&eit); IGRAPH_FINALLY_CLEAN(2); return 0; } /** * \function igraph_girth * \brief The girth of a graph is the length of the shortest circle in it. * * * The current implementation works for undirected graphs only, * directed graphs are treated as undirected graphs. Loop edges and * multiple edges are ignored. * * If the graph is a forest (ie. acyclic), then zero is returned. * * This implementation is based on Alon Itai and Michael Rodeh: * Finding a minimum circuit in a graph * \emb Proceedings of the ninth annual ACM symposium on Theory of * computing \eme, 1-10, 1977. The first implementation of this * function was done by Keith Briggs, thanks Keith. * \param graph The input graph. * \param girth Pointer to an integer, if not \c NULL then the result * will be stored here. * \param circle Pointer to an initialized vector, the vertex ids in * the shortest circle will be stored here. If \c NULL then it is * ignored. * \return Error code. * * Time complexity: O((|V|+|E|)^2), |V| is the number of vertices, |E| * is the number of edges in the general case. If the graph has no * circles at all then the function needs O(|V|+|E|) time to realize * this and then it stops. * * \example examples/simple/igraph_girth.c */ int igraph_girth(const igraph_t *graph, igraph_integer_t *girth, igraph_vector_t *circle) { long int no_of_nodes = igraph_vcount(graph); igraph_dqueue_t q; igraph_lazy_adjlist_t adjlist; long int mincirc = LONG_MAX, minvertex = 0; long int node; igraph_bool_t triangle = 0; igraph_vector_t *neis; igraph_vector_long_t level; long int stoplevel = no_of_nodes + 1; igraph_bool_t anycircle = 0; long int t1 = 0, t2 = 0; IGRAPH_CHECK(igraph_lazy_adjlist_init(graph, &adjlist, IGRAPH_ALL, IGRAPH_SIMPLIFY)); IGRAPH_FINALLY(igraph_lazy_adjlist_destroy, &adjlist); IGRAPH_DQUEUE_INIT_FINALLY(&q, 100); IGRAPH_CHECK(igraph_vector_long_init(&level, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_long_destroy, &level); for (node = 0; !triangle && node < no_of_nodes; node++) { /* Are there circles in this graph at all? */ if (node == 1 && anycircle == 0) { igraph_bool_t conn; IGRAPH_CHECK(igraph_is_connected(graph, &conn, IGRAPH_WEAK)); if (conn) { /* No, there are none */ break; } } anycircle = 0; igraph_dqueue_clear(&q); igraph_vector_long_null(&level); IGRAPH_CHECK(igraph_dqueue_push(&q, node)); VECTOR(level)[node] = 1; IGRAPH_ALLOW_INTERRUPTION(); while (!igraph_dqueue_empty(&q)) { long int actnode = (long int) igraph_dqueue_pop(&q); long int actlevel = VECTOR(level)[actnode]; long int i, n; if (actlevel >= stoplevel) { break; } neis = igraph_lazy_adjlist_get(&adjlist, (igraph_integer_t) actnode); n = igraph_vector_size(neis); for (i = 0; i < n; i++) { long int nei = (long int) VECTOR(*neis)[i]; long int neilevel = VECTOR(level)[nei]; if (neilevel != 0) { if (neilevel == actlevel - 1) { continue; } else { /* found circle */ stoplevel = neilevel; anycircle = 1; if (actlevel < mincirc) { /* Is it a minimum circle? */ mincirc = actlevel + neilevel - 1; minvertex = node; t1 = actnode; t2 = nei; if (neilevel == 2) { /* Is it a triangle? */ triangle = 1; } } if (neilevel == actlevel) { break; } } } else { igraph_dqueue_push(&q, nei); VECTOR(level)[nei] = actlevel + 1; } } } /* while q !empty */ } /* node */ if (girth) { if (mincirc == LONG_MAX) { *girth = mincirc = 0; } else { *girth = (igraph_integer_t) mincirc; } } /* Store the actual circle, if needed */ if (circle) { IGRAPH_CHECK(igraph_vector_resize(circle, mincirc)); if (mincirc != 0) { long int i, n, idx = 0; igraph_dqueue_clear(&q); igraph_vector_long_null(&level); /* used for father pointers */ #define FATHER(x) (VECTOR(level)[(x)]) IGRAPH_CHECK(igraph_dqueue_push(&q, minvertex)); FATHER(minvertex) = minvertex; while (FATHER(t1) == 0 || FATHER(t2) == 0) { long int actnode = (long int) igraph_dqueue_pop(&q); neis = igraph_lazy_adjlist_get(&adjlist, (igraph_integer_t) actnode); n = igraph_vector_size(neis); for (i = 0; i < n; i++) { long int nei = (long int) VECTOR(*neis)[i]; if (FATHER(nei) == 0) { FATHER(nei) = actnode + 1; igraph_dqueue_push(&q, nei); } } } /* while q !empty */ /* Ok, now use FATHER to create the path */ while (t1 != minvertex) { VECTOR(*circle)[idx++] = t1; t1 = FATHER(t1) - 1; } VECTOR(*circle)[idx] = minvertex; idx = mincirc - 1; while (t2 != minvertex) { VECTOR(*circle)[idx--] = t2; t2 = FATHER(t2) - 1; } } /* anycircle */ } /* circle */ #undef FATHER igraph_vector_long_destroy(&level); igraph_dqueue_destroy(&q); igraph_lazy_adjlist_destroy(&adjlist); IGRAPH_FINALLY_CLEAN(3); return 0; } int igraph_i_linegraph_undirected(const igraph_t *graph, igraph_t *linegraph); int igraph_i_linegraph_directed(const igraph_t *graph, igraph_t *linegraph); /* Note to self: tried using adjacency lists instead of igraph_incident queries, * with minimal performance improvements on a graph with 70K vertices and 360K * edges. (1.09s instead of 1.10s). I think it's not worth the fuss. */ int igraph_i_linegraph_undirected(const igraph_t *graph, igraph_t *linegraph) { long int no_of_edges = igraph_ecount(graph); long int i, j, n; igraph_vector_t adjedges, adjedges2; igraph_vector_t edges; long int prev = -1; IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_VECTOR_INIT_FINALLY(&adjedges, 0); IGRAPH_VECTOR_INIT_FINALLY(&adjedges2, 0); for (i = 0; i < no_of_edges; i++) { long int from = IGRAPH_FROM(graph, i); long int to = IGRAPH_TO(graph, i); IGRAPH_ALLOW_INTERRUPTION(); if (from != prev) { IGRAPH_CHECK(igraph_incident(graph, &adjedges, (igraph_integer_t) from, IGRAPH_ALL)); } n = igraph_vector_size(&adjedges); for (j = 0; j < n; j++) { long int e = (long int) VECTOR(adjedges)[j]; if (e < i) { IGRAPH_CHECK(igraph_vector_push_back(&edges, i)); IGRAPH_CHECK(igraph_vector_push_back(&edges, e)); } } IGRAPH_CHECK(igraph_incident(graph, &adjedges2, (igraph_integer_t) to, IGRAPH_ALL)); n = igraph_vector_size(&adjedges2); for (j = 0; j < n; j++) { long int e = (long int) VECTOR(adjedges2)[j]; if (e < i) { IGRAPH_CHECK(igraph_vector_push_back(&edges, i)); IGRAPH_CHECK(igraph_vector_push_back(&edges, e)); } } prev = from; } igraph_vector_destroy(&adjedges); igraph_vector_destroy(&adjedges2); IGRAPH_FINALLY_CLEAN(2); igraph_create(linegraph, &edges, (igraph_integer_t) no_of_edges, igraph_is_directed(graph)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_i_linegraph_directed(const igraph_t *graph, igraph_t *linegraph) { long int no_of_edges = igraph_ecount(graph); long int i, j, n; igraph_vector_t adjedges; igraph_vector_t edges; long int prev = -1; IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_VECTOR_INIT_FINALLY(&adjedges, 0); for (i = 0; i < no_of_edges; i++) { long int from = IGRAPH_FROM(graph, i); IGRAPH_ALLOW_INTERRUPTION(); if (from != prev) { IGRAPH_CHECK(igraph_incident(graph, &adjedges, (igraph_integer_t) from, IGRAPH_IN)); } n = igraph_vector_size(&adjedges); for (j = 0; j < n; j++) { long int e = (long int) VECTOR(adjedges)[j]; IGRAPH_CHECK(igraph_vector_push_back(&edges, e)); IGRAPH_CHECK(igraph_vector_push_back(&edges, i)); } prev = from; } igraph_vector_destroy(&adjedges); IGRAPH_FINALLY_CLEAN(1); igraph_create(linegraph, &edges, (igraph_integer_t) no_of_edges, igraph_is_directed(graph)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_linegraph * \brief Create the line graph of a graph. * * The line graph L(G) of a G undirected graph is defined as follows. * L(G) has one vertex for each edge in G and two vertices in L(G) are connected * by an edge if their corresponding edges share an end point. * * * The line graph L(G) of a G directed graph is slightly different, * L(G) has one vertex for each edge in G and two vertices in L(G) are connected * by a directed edge if the target of the first vertex's corresponding edge * is the same as the source of the second vertex's corresponding edge. * * * Edge \em i in the original graph will correspond to vertex \em i * in the line graph. * * * The first version of this function was contributed by Vincent Matossian, * thanks. * \param graph The input graph, may be directed or undirected. * \param linegraph Pointer to an uninitialized graph object, the * result is stored here. * \return Error code. * * Time complexity: O(|V|+|E|), the number of edges plus the number of vertices. */ int igraph_linegraph(const igraph_t *graph, igraph_t *linegraph) { if (igraph_is_directed(graph)) { return igraph_i_linegraph_directed(graph, linegraph); } else { return igraph_i_linegraph_undirected(graph, linegraph); } } /** * \function igraph_add_edge * \brief Adds a single edge to a graph. * * * For directed graphs the edge points from \p from to \p to. * * * Note that if you want to add many edges to a big graph, then it is * inefficient to add them one by one, it is better to collect them into * a vector and add all of them via a single \ref igraph_add_edges() call. * \param igraph The graph. * \param from The id of the first vertex of the edge. * \param to The id of the second vertex of the edge. * \return Error code. * * \sa \ref igraph_add_edges() to add many edges, \ref * igraph_delete_edges() to remove edges and \ref * igraph_add_vertices() to add vertices. * * Time complexity: O(|V|+|E|), the number of edges plus the number of * vertices. */ int igraph_add_edge(igraph_t *graph, igraph_integer_t from, igraph_integer_t to) { igraph_vector_t edges; int ret; IGRAPH_VECTOR_INIT_FINALLY(&edges, 2); VECTOR(edges)[0] = from; VECTOR(edges)[1] = to; IGRAPH_CHECK(ret = igraph_add_edges(graph, &edges, 0)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return ret; } /* * \example examples/simple/graph_convergence_degree.c */ int igraph_convergence_degree(const igraph_t *graph, igraph_vector_t *result, igraph_vector_t *ins, igraph_vector_t *outs) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); long int i, j, k, n; long int *geodist; igraph_vector_int_t *eids; igraph_vector_t *ins_p, *outs_p, ins_v, outs_v; igraph_dqueue_t q; igraph_inclist_t inclist; igraph_bool_t directed = igraph_is_directed(graph); if (result != 0) { IGRAPH_CHECK(igraph_vector_resize(result, no_of_edges)); } IGRAPH_CHECK(igraph_dqueue_init(&q, 100)); IGRAPH_FINALLY(igraph_dqueue_destroy, &q); if (ins == 0) { ins_p = &ins_v; IGRAPH_VECTOR_INIT_FINALLY(ins_p, no_of_edges); } else { ins_p = ins; IGRAPH_CHECK(igraph_vector_resize(ins_p, no_of_edges)); igraph_vector_null(ins_p); } if (outs == 0) { outs_p = &outs_v; IGRAPH_VECTOR_INIT_FINALLY(outs_p, no_of_edges); } else { outs_p = outs; IGRAPH_CHECK(igraph_vector_resize(outs_p, no_of_edges)); igraph_vector_null(outs_p); } geodist = igraph_Calloc(no_of_nodes, long int); if (geodist == 0) { IGRAPH_ERROR("Cannot calculate convergence degrees", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, geodist); /* Collect shortest paths originating from/to every node to correctly * determine input field sizes */ for (k = 0; k < (directed ? 2 : 1); k++) { igraph_neimode_t neimode = (k == 0) ? IGRAPH_OUT : IGRAPH_IN; igraph_real_t *vec; IGRAPH_CHECK(igraph_inclist_init(graph, &inclist, neimode)); IGRAPH_FINALLY(igraph_inclist_destroy, &inclist); vec = (k == 0) ? VECTOR(*ins_p) : VECTOR(*outs_p); for (i = 0; i < no_of_nodes; i++) { igraph_dqueue_clear(&q); memset(geodist, 0, sizeof(long int) * (size_t) no_of_nodes); geodist[i] = 1; IGRAPH_CHECK(igraph_dqueue_push(&q, i)); IGRAPH_CHECK(igraph_dqueue_push(&q, 0.0)); while (!igraph_dqueue_empty(&q)) { long int actnode = (long int) igraph_dqueue_pop(&q); long int actdist = (long int) igraph_dqueue_pop(&q); IGRAPH_ALLOW_INTERRUPTION(); eids = igraph_inclist_get(&inclist, actnode); n = igraph_vector_int_size(eids); for (j = 0; j < n; j++) { long int neighbor = IGRAPH_OTHER(graph, VECTOR(*eids)[j], actnode); if (geodist[neighbor] != 0) { /* we've already seen this node, another shortest path? */ if (geodist[neighbor] - 1 == actdist + 1) { /* Since this edge is in the BFS tree rooted at i, we must * increase either the size of the infield or the outfield */ if (!directed) { if (actnode < neighbor) { VECTOR(*ins_p)[(long int)VECTOR(*eids)[j]] += 1; } else { VECTOR(*outs_p)[(long int)VECTOR(*eids)[j]] += 1; } } else { vec[(long int)VECTOR(*eids)[j]] += 1; } } else if (geodist[neighbor] - 1 < actdist + 1) { continue; } } else { /* we haven't seen this node yet */ IGRAPH_CHECK(igraph_dqueue_push(&q, neighbor)); IGRAPH_CHECK(igraph_dqueue_push(&q, actdist + 1)); /* Since this edge is in the BFS tree rooted at i, we must * increase either the size of the infield or the outfield */ if (!directed) { if (actnode < neighbor) { VECTOR(*ins_p)[(long int)VECTOR(*eids)[j]] += 1; } else { VECTOR(*outs_p)[(long int)VECTOR(*eids)[j]] += 1; } } else { vec[(long int)VECTOR(*eids)[j]] += 1; } geodist[neighbor] = actdist + 2; } } } } igraph_inclist_destroy(&inclist); IGRAPH_FINALLY_CLEAN(1); } if (result != 0) { for (i = 0; i < no_of_edges; i++) VECTOR(*result)[i] = (VECTOR(*ins_p)[i] - VECTOR(*outs_p)[i]) / (VECTOR(*ins_p)[i] + VECTOR(*outs_p)[i]); if (!directed) { for (i = 0; i < no_of_edges; i++) if (VECTOR(*result)[i] < 0) { VECTOR(*result)[i] = -VECTOR(*result)[i]; } } } if (ins == 0) { igraph_vector_destroy(ins_p); IGRAPH_FINALLY_CLEAN(1); } if (outs == 0) { igraph_vector_destroy(outs_p); IGRAPH_FINALLY_CLEAN(1); } igraph_free(geodist); igraph_dqueue_destroy(&q); IGRAPH_FINALLY_CLEAN(2); return 0; } /** * \function igraph_shortest_paths_dijkstra * Weighted shortest paths from some sources. * * This function is Dijkstra's algorithm to find the weighted * shortest paths to all vertices from a single source. (It is run * independently for the given sources.) It uses a binary heap for * efficient implementation. * * \param graph The input graph, can be directed. * \param res The result, a matrix. A pointer to an initialized matrix * should be passed here. The matrix will be resized as needed. * Each row contains the distances from a single source, to the * vertices given in the \c to argument. * Unreachable vertices has distance * \c IGRAPH_INFINITY. * \param from The source vertices. * \param to The target vertices. It is not allowed to include a * vertex twice or more. * \param weights The edge weights. They must be all non-negative for * Dijkstra's algorithm to work. An error code is returned if there * is a negative edge weight in the weight vector. If this is a null * pointer, then the * unweighted version, \ref igraph_shortest_paths() is called. * \param mode For directed graphs; whether to follow paths along edge * directions (\c IGRAPH_OUT), or the opposite (\c IGRAPH_IN), or * ignore edge directions completely (\c IGRAPH_ALL). It is ignored * for undirected graphs. * \return Error code. * * Time complexity: O(s*|E|log|E|+|V|), where |V| is the number of * vertices, |E| the number of edges and s the number of sources. * * \sa \ref igraph_shortest_paths() for a (slightly) faster unweighted * version or \ref igraph_shortest_paths_bellman_ford() for a weighted * variant that works in the presence of negative edge weights (but no * negative loops). * * \example examples/simple/dijkstra.c */ int igraph_shortest_paths_dijkstra(const igraph_t *graph, igraph_matrix_t *res, const igraph_vs_t from, const igraph_vs_t to, const igraph_vector_t *weights, igraph_neimode_t mode) { /* Implementation details. This is the basic Dijkstra algorithm, with a binary heap. The heap is indexed, i.e. it stores not only the distances, but also which vertex they belong to. From now on we use a 2-way heap, so the distances can be queried directly from the heap. Dirty tricks: - the opposite of the distance is stored in the heap, as it is a maximum heap and we need a minimum heap. - we don't use IGRAPH_INFINITY in the res matrix during the computation, as IGRAPH_FINITE() might involve a function call and we want to spare that. -1 will denote infinity instead. */ long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_2wheap_t Q; igraph_vit_t fromvit, tovit; long int no_of_from, no_of_to; igraph_lazy_inclist_t inclist; long int i, j; igraph_real_t my_infinity = IGRAPH_INFINITY; igraph_bool_t all_to; igraph_vector_t indexv; if (!weights) { return igraph_shortest_paths(graph, res, from, to, mode); } if (igraph_vector_size(weights) != no_of_edges) { IGRAPH_ERROR("Weight vector length does not match", IGRAPH_EINVAL); } if (igraph_vector_min(weights) < 0) { IGRAPH_ERROR("Weight vector must be non-negative", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_vit_create(graph, from, &fromvit)); IGRAPH_FINALLY(igraph_vit_destroy, &fromvit); no_of_from = IGRAPH_VIT_SIZE(fromvit); IGRAPH_CHECK(igraph_2wheap_init(&Q, no_of_nodes)); IGRAPH_FINALLY(igraph_2wheap_destroy, &Q); IGRAPH_CHECK(igraph_lazy_inclist_init(graph, &inclist, mode)); IGRAPH_FINALLY(igraph_lazy_inclist_destroy, &inclist); if ( (all_to = igraph_vs_is_all(&to)) ) { no_of_to = no_of_nodes; } else { IGRAPH_VECTOR_INIT_FINALLY(&indexv, no_of_nodes); IGRAPH_CHECK(igraph_vit_create(graph, to, &tovit)); IGRAPH_FINALLY(igraph_vit_destroy, &tovit); no_of_to = IGRAPH_VIT_SIZE(tovit); for (i = 0; !IGRAPH_VIT_END(tovit); IGRAPH_VIT_NEXT(tovit)) { long int v = IGRAPH_VIT_GET(tovit); if (VECTOR(indexv)[v]) { IGRAPH_ERROR("Duplicate vertices in `to', this is not allowed", IGRAPH_EINVAL); } VECTOR(indexv)[v] = ++i; } } IGRAPH_CHECK(igraph_matrix_resize(res, no_of_from, no_of_to)); igraph_matrix_fill(res, my_infinity); for (IGRAPH_VIT_RESET(fromvit), i = 0; !IGRAPH_VIT_END(fromvit); IGRAPH_VIT_NEXT(fromvit), i++) { long int reached = 0; long int source = IGRAPH_VIT_GET(fromvit); igraph_2wheap_clear(&Q); igraph_2wheap_push_with_index(&Q, source, -1.0); while (!igraph_2wheap_empty(&Q)) { long int minnei = igraph_2wheap_max_index(&Q); igraph_real_t mindist = -igraph_2wheap_deactivate_max(&Q); igraph_vector_t *neis; long int nlen; if (all_to) { MATRIX(*res, i, minnei) = mindist - 1.0; } else { if (VECTOR(indexv)[minnei]) { MATRIX(*res, i, (long int)(VECTOR(indexv)[minnei] - 1)) = mindist - 1.0; reached++; if (reached == no_of_to) { igraph_2wheap_clear(&Q); break; } } } /* Now check all neighbors of 'minnei' for a shorter path */ neis = igraph_lazy_inclist_get(&inclist, (igraph_integer_t) minnei); nlen = igraph_vector_size(neis); for (j = 0; j < nlen; j++) { long int edge = (long int) VECTOR(*neis)[j]; long int tto = IGRAPH_OTHER(graph, edge, minnei); igraph_real_t altdist = mindist + VECTOR(*weights)[edge]; igraph_bool_t active = igraph_2wheap_has_active(&Q, tto); igraph_bool_t has = igraph_2wheap_has_elem(&Q, tto); igraph_real_t curdist = active ? -igraph_2wheap_get(&Q, tto) : 0.0; if (!has) { /* This is the first non-infinite distance */ IGRAPH_CHECK(igraph_2wheap_push_with_index(&Q, tto, -altdist)); } else if (altdist < curdist) { /* This is a shorter path */ IGRAPH_CHECK(igraph_2wheap_modify(&Q, tto, -altdist)); } } } /* !igraph_2wheap_empty(&Q) */ } /* !IGRAPH_VIT_END(fromvit) */ if (!all_to) { igraph_vit_destroy(&tovit); igraph_vector_destroy(&indexv); IGRAPH_FINALLY_CLEAN(2); } igraph_lazy_inclist_destroy(&inclist); igraph_2wheap_destroy(&Q); igraph_vit_destroy(&fromvit); IGRAPH_FINALLY_CLEAN(3); return 0; } /** * \ingroup structural * \function igraph_get_shortest_paths_dijkstra * \brief Calculates the weighted shortest paths from/to one vertex. * * * If there is more than one path with the smallest weight between two vertices, this * function gives only one of them. * \param graph The graph object. * \param vertices The result, the ids of the vertices along the paths. * This is a pointer vector, each element points to a vector * object. These should be initialized before passing them to * the function, which will properly clear and/or resize them * and fill the ids of the vertices along the geodesics from/to * the vertices. Supply a null pointer here if you don't need * these vectors. Normally, either this argument, or the \c * edges should be non-null, but no error or warning is given * if they are both null pointers. * \param edges The result, the ids of the edges along the paths. * This is a pointer vector, each element points to a vector * object. These should be initialized before passing them to * the function, which will properly clear and/or resize them * and fill the ids of the vertices along the geodesics from/to * the vertices. Supply a null pointer here if you don't need * these vectors. Normally, either this argument, or the \c * vertices should be non-null, but no error or warning is given * if they are both null pointers. * \param from The id of the vertex from/to which the geodesics are * calculated. * \param to Vertex sequence with the ids of the vertices to/from which the * shortest paths will be calculated. A vertex might be given multiple * times. * \param weights a vector holding the edge weights. All weights must be * positive. * \param mode The type of shortest paths to be use for the * calculation in directed graphs. Possible values: * \clist * \cli IGRAPH_OUT * the outgoing paths are calculated. * \cli IGRAPH_IN * the incoming paths are calculated. * \cli IGRAPH_ALL * the directed graph is considered as an * undirected one for the computation. * \endclist * \param predecessors A pointer to an initialized igraph vector or null. * If not null, a vector containing the predecessor of each vertex in * the single source shortest path tree is returned here. The * predecessor of vertex i in the tree is the vertex from which vertex i * was reached. The predecessor of the start vertex (in the \c from * argument) is itself by definition. If the predecessor is -1, it means * that the given vertex was not reached from the source during the * search. Note that the search terminates if all the vertices in * \c to are reached. * \param inbound_edges A pointer to an initialized igraph vector or null. * If not null, a vector containing the inbound edge of each vertex in * the single source shortest path tree is returned here. The * inbound edge of vertex i in the tree is the edge via which vertex i * was reached. The start vertex and vertices that were not reached * during the search will have -1 in the corresponding entry of the * vector. Note that the search terminates if all the vertices in * \c to are reached. * \return Error code: * \clist * \cli IGRAPH_ENOMEM * not enough memory for temporary data. * \cli IGRAPH_EINVVID * \p from is invalid vertex id, or the length of \p to is * not the same as the length of \p res. * \cli IGRAPH_EINVMODE * invalid mode argument. * \endclist * * Time complexity: O(|E|log|E|+|V|), where |V| is the number of * vertices and |E| is the number of edges * * \sa \ref igraph_shortest_paths_dijkstra() if you only need the path length but * not the paths themselves, \ref igraph_get_shortest_paths() if all edge * weights are equal. * * \example examples/simple/igraph_get_shortest_paths_dijkstra.c */ int igraph_get_shortest_paths_dijkstra(const igraph_t *graph, igraph_vector_ptr_t *vertices, igraph_vector_ptr_t *edges, igraph_integer_t from, igraph_vs_t to, const igraph_vector_t *weights, igraph_neimode_t mode, igraph_vector_long_t *predecessors, igraph_vector_long_t *inbound_edges) { /* Implementation details. This is the basic Dijkstra algorithm, with a binary heap. The heap is indexed, i.e. it stores not only the distances, but also which vertex they belong to. The other mapping, i.e. getting the distance for a vertex is not in the heap (that would by the double-indexed heap), but in the result matrix. Dirty tricks: - the opposite of the distance is stored in the heap, as it is a maximum heap and we need a minimum heap. - we don't use IGRAPH_INFINITY in the distance vector during the computation, as IGRAPH_FINITE() might involve a function call and we want to spare that. So we store distance+1.0 instead of distance, and zero denotes infinity. - `parents' assigns the inbound edge IDs of all vertices in the shortest path tree to the vertices. In this implementation, the edge ID + 1 is stored, zero means unreachable vertices. */ long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_vit_t vit; igraph_2wheap_t Q; igraph_lazy_inclist_t inclist; igraph_vector_t dists; long int *parents; igraph_bool_t *is_target; long int i, to_reach; if (!weights) { return igraph_get_shortest_paths(graph, vertices, edges, from, to, mode, predecessors, inbound_edges); } if (igraph_vector_size(weights) != no_of_edges) { IGRAPH_ERROR("Weight vector length does not match", IGRAPH_EINVAL); } if (igraph_vector_min(weights) < 0) { IGRAPH_ERROR("Weight vector must be non-negative", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_vit_create(graph, to, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); if (vertices && IGRAPH_VIT_SIZE(vit) != igraph_vector_ptr_size(vertices)) { IGRAPH_ERROR("Size of `vertices' and `to' should match", IGRAPH_EINVAL); } if (edges && IGRAPH_VIT_SIZE(vit) != igraph_vector_ptr_size(edges)) { IGRAPH_ERROR("Size of `edges' and `to' should match", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_2wheap_init(&Q, no_of_nodes)); IGRAPH_FINALLY(igraph_2wheap_destroy, &Q); IGRAPH_CHECK(igraph_lazy_inclist_init(graph, &inclist, mode)); IGRAPH_FINALLY(igraph_lazy_inclist_destroy, &inclist); IGRAPH_VECTOR_INIT_FINALLY(&dists, no_of_nodes); igraph_vector_fill(&dists, -1.0); parents = igraph_Calloc(no_of_nodes, long int); if (parents == 0) { IGRAPH_ERROR("Can't calculate shortest paths", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, parents); is_target = igraph_Calloc(no_of_nodes, igraph_bool_t); if (is_target == 0) { IGRAPH_ERROR("Can't calculate shortest paths", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, is_target); /* Mark the vertices we need to reach */ to_reach = IGRAPH_VIT_SIZE(vit); for (IGRAPH_VIT_RESET(vit); !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit)) { if (!is_target[ (long int) IGRAPH_VIT_GET(vit) ]) { is_target[ (long int) IGRAPH_VIT_GET(vit) ] = 1; } else { to_reach--; /* this node was given multiple times */ } } VECTOR(dists)[(long int)from] = 0.0; /* zero distance */ parents[(long int)from] = 0; igraph_2wheap_push_with_index(&Q, from, 0); while (!igraph_2wheap_empty(&Q) && to_reach > 0) { long int nlen, minnei = igraph_2wheap_max_index(&Q); igraph_real_t mindist = -igraph_2wheap_delete_max(&Q); igraph_vector_t *neis; IGRAPH_ALLOW_INTERRUPTION(); if (is_target[minnei]) { is_target[minnei] = 0; to_reach--; } /* Now check all neighbors of 'minnei' for a shorter path */ neis = igraph_lazy_inclist_get(&inclist, (igraph_integer_t) minnei); nlen = igraph_vector_size(neis); for (i = 0; i < nlen; i++) { long int edge = (long int) VECTOR(*neis)[i]; long int tto = IGRAPH_OTHER(graph, edge, minnei); igraph_real_t altdist = mindist + VECTOR(*weights)[edge]; igraph_real_t curdist = VECTOR(dists)[tto]; if (curdist < 0) { /* This is the first finite distance */ VECTOR(dists)[tto] = altdist; parents[tto] = edge + 1; IGRAPH_CHECK(igraph_2wheap_push_with_index(&Q, tto, -altdist)); } else if (altdist < curdist) { /* This is a shorter path */ VECTOR(dists)[tto] = altdist; parents[tto] = edge + 1; IGRAPH_CHECK(igraph_2wheap_modify(&Q, tto, -altdist)); } } } /* !igraph_2wheap_empty(&Q) */ if (to_reach > 0) { IGRAPH_WARNING("Couldn't reach some vertices"); } /* Create `predecessors' if needed */ if (predecessors) { IGRAPH_CHECK(igraph_vector_long_resize(predecessors, no_of_nodes)); for (i = 0; i < no_of_nodes; i++) { if (i == from) { /* i is the start vertex */ VECTOR(*predecessors)[i] = i; } else if (parents[i] <= 0) { /* i was not reached */ VECTOR(*predecessors)[i] = -1; } else { /* i was reached via the edge with ID = parents[i] - 1 */ VECTOR(*predecessors)[i] = IGRAPH_OTHER(graph, parents[i] - 1, i); } } } /* Create `inbound_edges' if needed */ if (inbound_edges) { IGRAPH_CHECK(igraph_vector_long_resize(inbound_edges, no_of_nodes)); for (i = 0; i < no_of_nodes; i++) { if (parents[i] <= 0) { /* i was not reached */ VECTOR(*inbound_edges)[i] = -1; } else { /* i was reached via the edge with ID = parents[i] - 1 */ VECTOR(*inbound_edges)[i] = parents[i] - 1; } } } /* Reconstruct the shortest paths based on vertex and/or edge IDs */ if (vertices || edges) { for (IGRAPH_VIT_RESET(vit), i = 0; !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit), i++) { long int node = IGRAPH_VIT_GET(vit); long int size, act, edge; igraph_vector_t *vvec = 0, *evec = 0; if (vertices) { vvec = VECTOR(*vertices)[i]; igraph_vector_clear(vvec); } if (edges) { evec = VECTOR(*edges)[i]; igraph_vector_clear(evec); } IGRAPH_ALLOW_INTERRUPTION(); size = 0; act = node; while (parents[act]) { size++; edge = parents[act] - 1; act = IGRAPH_OTHER(graph, edge, act); } if (vvec) { IGRAPH_CHECK(igraph_vector_resize(vvec, size + 1)); VECTOR(*vvec)[size] = node; } if (evec) { IGRAPH_CHECK(igraph_vector_resize(evec, size)); } act = node; while (parents[act]) { edge = parents[act] - 1; act = IGRAPH_OTHER(graph, edge, act); size--; if (vvec) { VECTOR(*vvec)[size] = act; } if (evec) { VECTOR(*evec)[size] = edge; } } } } igraph_lazy_inclist_destroy(&inclist); igraph_2wheap_destroy(&Q); igraph_vector_destroy(&dists); igraph_Free(is_target); igraph_Free(parents); igraph_vit_destroy(&vit); IGRAPH_FINALLY_CLEAN(6); return 0; } /** * \function igraph_get_shortest_path_dijkstra * Weighted shortest path from one vertex to another one. * * Calculates a single (positively) weighted shortest path from * a single vertex to another one, using Dijkstra's algorithm. * * This function is a special case (and a wrapper) to * \ref igraph_get_shortest_paths_dijkstra(). * * \param graph The input graph, it can be directed or undirected. * \param vertices Pointer to an initialized vector or a null * pointer. If not a null pointer, then the vertex ids along * the path are stored here, including the source and target * vertices. * \param edges Pointer to an uninitialized vector or a null * pointer. If not a null pointer, then the edge ids along the * path are stored here. * \param from The id of the source vertex. * \param to The id of the target vertex. * \param weights Vector of edge weights, in the order of edge * ids. They must be non-negative, otherwise the algorithm does * not work. * \param mode A constant specifying how edge directions are * considered in directed graphs. \c IGRAPH_OUT follows edge * directions, \c IGRAPH_IN follows the opposite directions, * and \c IGRAPH_ALL ignores edge directions. This argument is * ignored for undirected graphs. * \return Error code. * * Time complexity: O(|E|log|E|+|V|), |V| is the number of vertices, * |E| is the number of edges in the graph. * * \sa \ref igraph_get_shortest_paths_dijkstra() for the version with * more target vertices. */ int igraph_get_shortest_path_dijkstra(const igraph_t *graph, igraph_vector_t *vertices, igraph_vector_t *edges, igraph_integer_t from, igraph_integer_t to, const igraph_vector_t *weights, igraph_neimode_t mode) { igraph_vector_ptr_t vertices2, *vp = &vertices2; igraph_vector_ptr_t edges2, *ep = &edges2; if (vertices) { IGRAPH_CHECK(igraph_vector_ptr_init(&vertices2, 1)); IGRAPH_FINALLY(igraph_vector_ptr_destroy, &vertices2); VECTOR(vertices2)[0] = vertices; } else { vp = 0; } if (edges) { IGRAPH_CHECK(igraph_vector_ptr_init(&edges2, 1)); IGRAPH_FINALLY(igraph_vector_ptr_destroy, &edges2); VECTOR(edges2)[0] = edges; } else { ep = 0; } IGRAPH_CHECK(igraph_get_shortest_paths_dijkstra(graph, vp, ep, from, igraph_vss_1(to), weights, mode, 0, 0)); if (edges) { igraph_vector_ptr_destroy(&edges2); IGRAPH_FINALLY_CLEAN(1); } if (vertices) { igraph_vector_ptr_destroy(&vertices2); IGRAPH_FINALLY_CLEAN(1); } return 0; } int igraph_i_vector_tail_cmp(const void* path1, const void* path2); /* Compares two paths based on their last elements. Required by * igraph_get_all_shortest_paths_dijkstra to put the final result * in order. Assumes that both paths are pointers to igraph_vector_t * objects and that they are not empty */ int igraph_i_vector_tail_cmp(const void* path1, const void* path2) { return (int) (igraph_vector_tail(*(const igraph_vector_t**)path1) - igraph_vector_tail(*(const igraph_vector_t**)path2)); } /** * \ingroup structural * \function igraph_get_all_shortest_paths_dijkstra * \brief Finds all shortest paths (geodesics) from a vertex to all other vertices. * * \param graph The graph object. * \param res Pointer to an initialized pointer vector, the result * will be stored here in igraph_vector_t objects. Each vector * object contains the vertices along a shortest path from \p from * to another vertex. The vectors are ordered according to their * target vertex: first the shortest paths to vertex 0, then to * vertex 1, etc. No data is included for unreachable vertices. * \param nrgeo Pointer to an initialized igraph_vector_t object or * NULL. If not NULL the number of shortest paths from \p from are * stored here for every vertex in the graph. Note that the values * will be accurate only for those vertices that are in the target * vertex sequence (see \p to), since the search terminates as soon * as all the target vertices have been found. * \param from The id of the vertex from/to which the geodesics are * calculated. * \param to Vertex sequence with the ids of the vertices to/from which the * shortest paths will be calculated. A vertex might be given multiple * times. * \param weights a vector holding the edge weights. All weights must be * non-negative. * \param mode The type of shortest paths to be use for the * calculation in directed graphs. Possible values: * \clist * \cli IGRAPH_OUT * the outgoing paths are calculated. * \cli IGRAPH_IN * the incoming paths are calculated. * \cli IGRAPH_ALL * the directed graph is considered as an * undirected one for the computation. * \endclist * \return Error code: * \clist * \cli IGRAPH_ENOMEM * not enough memory for temporary data. * \cli IGRAPH_EINVVID * \p from is invalid vertex id, or the length of \p to is * not the same as the length of \p res. * \cli IGRAPH_EINVMODE * invalid mode argument. * \endclist * * Time complexity: O(|E|log|E|+|V|), where |V| is the number of * vertices and |E| is the number of edges * * \sa \ref igraph_shortest_paths_dijkstra() if you only need the path * length but not the paths themselves, \ref igraph_get_all_shortest_paths() * if all edge weights are equal. * * \example examples/simple/igraph_get_all_shortest_paths_dijkstra.c */ int igraph_get_all_shortest_paths_dijkstra(const igraph_t *graph, igraph_vector_ptr_t *res, igraph_vector_t *nrgeo, igraph_integer_t from, igraph_vs_t to, const igraph_vector_t *weights, igraph_neimode_t mode) { /* Implementation details: see igraph_get_shortest_paths_dijkstra, it's basically the same. */ long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_vit_t vit; igraph_2wheap_t Q; igraph_lazy_inclist_t inclist; igraph_vector_t dists, order; igraph_vector_ptr_t parents; unsigned char *is_target; long int i, n, to_reach; if (!weights) { return igraph_get_all_shortest_paths(graph, res, nrgeo, from, to, mode); } if (res == 0 && nrgeo == 0) { return IGRAPH_SUCCESS; } if (igraph_vector_size(weights) != no_of_edges) { IGRAPH_ERROR("Weight vector length does not match", IGRAPH_EINVAL); } if (igraph_vector_min(weights) < 0) { IGRAPH_ERROR("Weight vector must be non-negative", IGRAPH_EINVAL); } /* parents stores a vector for each vertex, listing the parent vertices * of each vertex in the traversal */ IGRAPH_CHECK(igraph_vector_ptr_init(&parents, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_ptr_destroy_all, &parents); igraph_vector_ptr_set_item_destructor(&parents, (igraph_finally_func_t*)igraph_vector_destroy); for (i = 0; i < no_of_nodes; i++) { igraph_vector_t* parent_vec; parent_vec = igraph_Calloc(1, igraph_vector_t); if (parent_vec == 0) { IGRAPH_ERROR("cannot run igraph_get_all_shortest_paths", IGRAPH_ENOMEM); } IGRAPH_CHECK(igraph_vector_init(parent_vec, 0)); VECTOR(parents)[i] = parent_vec; } /* distance of each vertex from the root */ IGRAPH_VECTOR_INIT_FINALLY(&dists, no_of_nodes); igraph_vector_fill(&dists, -1.0); /* order lists the order of vertices in which they were found during * the traversal */ IGRAPH_VECTOR_INIT_FINALLY(&order, 0); /* boolean array to mark whether a given vertex is a target or not */ is_target = igraph_Calloc(no_of_nodes, unsigned char); if (is_target == 0) { IGRAPH_ERROR("Can't calculate shortest paths", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, is_target); /* two-way heap storing vertices and distances */ IGRAPH_CHECK(igraph_2wheap_init(&Q, no_of_nodes)); IGRAPH_FINALLY(igraph_2wheap_destroy, &Q); /* lazy adjacency edge list to query neighbours efficiently */ IGRAPH_CHECK(igraph_lazy_inclist_init(graph, &inclist, mode)); IGRAPH_FINALLY(igraph_lazy_inclist_destroy, &inclist); /* Mark the vertices we need to reach */ IGRAPH_CHECK(igraph_vit_create(graph, to, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); to_reach = IGRAPH_VIT_SIZE(vit); for (IGRAPH_VIT_RESET(vit); !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit)) { if (!is_target[ (long int) IGRAPH_VIT_GET(vit) ]) { is_target[ (long int) IGRAPH_VIT_GET(vit) ] = 1; } else { to_reach--; /* this node was given multiple times */ } } igraph_vit_destroy(&vit); IGRAPH_FINALLY_CLEAN(1); VECTOR(dists)[(long int)from] = 0.0; /* zero distance */ igraph_2wheap_push_with_index(&Q, from, 0); while (!igraph_2wheap_empty(&Q) && to_reach > 0) { long int nlen, minnei = igraph_2wheap_max_index(&Q); igraph_real_t mindist = -igraph_2wheap_delete_max(&Q); igraph_vector_t *neis; IGRAPH_ALLOW_INTERRUPTION(); /* printf("Reached vertex %ld, is_target[%ld] = %d, %ld to go\n", minnei, minnei, (int)is_target[minnei], to_reach - is_target[minnei]); */ if (is_target[minnei]) { is_target[minnei] = 0; to_reach--; } /* Mark that we have reached this vertex */ IGRAPH_CHECK(igraph_vector_push_back(&order, minnei)); /* Now check all neighbors of 'minnei' for a shorter path */ neis = igraph_lazy_inclist_get(&inclist, (igraph_integer_t) minnei); nlen = igraph_vector_size(neis); for (i = 0; i < nlen; i++) { long int edge = (long int) VECTOR(*neis)[i]; long int tto = IGRAPH_OTHER(graph, edge, minnei); igraph_real_t altdist = mindist + VECTOR(*weights)[edge]; igraph_real_t curdist = VECTOR(dists)[tto]; igraph_vector_t *parent_vec; if (curdist < 0) { /* This is the first non-infinite distance */ VECTOR(dists)[tto] = altdist; parent_vec = (igraph_vector_t*)VECTOR(parents)[tto]; IGRAPH_CHECK(igraph_vector_push_back(parent_vec, minnei)); IGRAPH_CHECK(igraph_2wheap_push_with_index(&Q, tto, -altdist)); } else if (altdist == curdist && VECTOR(*weights)[edge] > 0) { /* This is an alternative path with exactly the same length. * Note that we consider this case only if the edge via which we * reached the node has a nonzero weight; otherwise we could create * infinite loops in undirected graphs by traversing zero-weight edges * back-and-forth */ parent_vec = (igraph_vector_t*)VECTOR(parents)[tto]; IGRAPH_CHECK(igraph_vector_push_back(parent_vec, minnei)); } else if (altdist < curdist) { /* This is a shorter path */ VECTOR(dists)[tto] = altdist; parent_vec = (igraph_vector_t*)VECTOR(parents)[tto]; igraph_vector_clear(parent_vec); IGRAPH_CHECK(igraph_vector_push_back(parent_vec, minnei)); IGRAPH_CHECK(igraph_2wheap_modify(&Q, tto, -altdist)); } } } /* !igraph_2wheap_empty(&Q) */ if (to_reach > 0) { IGRAPH_WARNING("Couldn't reach some vertices"); } /* we don't need these anymore */ igraph_lazy_inclist_destroy(&inclist); igraph_2wheap_destroy(&Q); IGRAPH_FINALLY_CLEAN(2); /* printf("Order:\n"); igraph_vector_print(&order); printf("Parent vertices:\n"); for (i = 0; i < no_of_nodes; i++) { if (igraph_vector_size(VECTOR(parents)[i]) > 0) { printf("[%ld]: ", (long int)i); igraph_vector_print(VECTOR(parents)[i]); } } */ if (nrgeo) { IGRAPH_CHECK(igraph_vector_resize(nrgeo, no_of_nodes)); igraph_vector_null(nrgeo); /* Theoretically, we could calculate nrgeo in parallel with the traversal. * However, that way we would have to check whether nrgeo is null or not * every time we want to update some element in nrgeo. Since we need the * order vector anyway for building the final result, we could just as well * build nrgeo here. */ VECTOR(*nrgeo)[(long int)from] = 1; n = igraph_vector_size(&order); for (i = 1; i < n; i++) { long int node, j, k; igraph_vector_t *parent_vec; node = (long int)VECTOR(order)[i]; /* now, take the parent vertices */ parent_vec = (igraph_vector_t*)VECTOR(parents)[node]; k = igraph_vector_size(parent_vec); for (j = 0; j < k; j++) { VECTOR(*nrgeo)[node] += VECTOR(*nrgeo)[(long int)VECTOR(*parent_vec)[j]]; } } } if (res) { igraph_vector_t *path, *paths_index, *parent_vec; igraph_stack_t stack; long int j, node; /* a shortest path from the starting vertex to vertex i can be * obtained by calculating the shortest paths from the "parents" * of vertex i in the traversal. Knowing which of the vertices * are "targets" (see is_target), we can collect for which other * vertices do we need to calculate the shortest paths. We reuse * is_target for that; is_target = 0 means that we don't need the * vertex, is_target = 1 means that the vertex is a target (hence * we need it), is_target = 2 means that the vertex is not a target * but it stands between a shortest path between the root and one * of the targets */ if (igraph_vs_is_all(&to)) { memset(is_target, 1, sizeof(unsigned char) * (size_t) no_of_nodes); } else { memset(is_target, 0, sizeof(unsigned char) * (size_t) no_of_nodes); IGRAPH_CHECK(igraph_stack_init(&stack, 0)); IGRAPH_FINALLY(igraph_stack_destroy, &stack); /* Add the target vertices to the queue */ IGRAPH_CHECK(igraph_vit_create(graph, to, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); for (IGRAPH_VIT_RESET(vit); !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit)) { i = (long int) IGRAPH_VIT_GET(vit); if (!is_target[i]) { is_target[i] = 1; IGRAPH_CHECK(igraph_stack_push(&stack, i)); } } igraph_vit_destroy(&vit); IGRAPH_FINALLY_CLEAN(1); while (!igraph_stack_empty(&stack)) { /* For each parent of node i, get its parents */ igraph_real_t el = igraph_stack_pop(&stack); parent_vec = (igraph_vector_t*)VECTOR(parents)[(long int) el]; i = igraph_vector_size(parent_vec); for (j = 0; j < i; j++) { /* For each parent, check if it's already in the stack. * If not, push it and mark it in is_target */ n = (long int) VECTOR(*parent_vec)[j]; if (!is_target[n]) { is_target[n] = 2; IGRAPH_CHECK(igraph_stack_push(&stack, n)); } } } igraph_stack_destroy(&stack); IGRAPH_FINALLY_CLEAN(1); } /* now, reconstruct the shortest paths from the parent list in the * order we've found the nodes during the traversal. * dists is being re-used as a vector where element i tells the * index in res where the shortest paths leading to vertex i * start, plus one (so that zero means that there are no paths * for a given vertex). */ paths_index = &dists; n = igraph_vector_size(&order); igraph_vector_null(paths_index); /* clear the paths vector */ igraph_vector_ptr_clear(res); igraph_vector_ptr_set_item_destructor(res, (igraph_finally_func_t*)igraph_vector_destroy); /* by definition, the shortest path leading to the starting vertex * consists of the vertex itself only */ path = igraph_Calloc(1, igraph_vector_t); if (path == 0) IGRAPH_ERROR("cannot run igraph_get_all_shortest_paths_dijkstra", IGRAPH_ENOMEM); IGRAPH_FINALLY(igraph_free, path); IGRAPH_CHECK(igraph_vector_init(path, 1)); IGRAPH_CHECK(igraph_vector_ptr_push_back(res, path)); IGRAPH_FINALLY_CLEAN(1); /* ownership of path passed to res */ VECTOR(*path)[0] = from; VECTOR(*paths_index)[(long int)from] = 1; for (i = 1; i < n; i++) { long int m, path_count; igraph_vector_t *parent_path; node = (long int) VECTOR(order)[i]; /* if we don't need the shortest paths for this node (because * it is not standing in a shortest path between the source * node and any of the target nodes), skip it */ if (!is_target[node]) { continue; } IGRAPH_ALLOW_INTERRUPTION(); /* we are calculating the shortest paths of node now. */ /* first, we update the paths_index */ path_count = igraph_vector_ptr_size(res); VECTOR(*paths_index)[node] = path_count + 1; /* res_end = (igraph_vector_t*)&(VECTOR(*res)[path_count]); */ /* now, take the parent vertices */ parent_vec = (igraph_vector_t*)VECTOR(parents)[node]; m = igraph_vector_size(parent_vec); /* printf("Calculating shortest paths to vertex %ld\n", node); printf("Parents are: "); igraph_vector_print(parent_vec); */ for (j = 0; j < m; j++) { /* for each parent, copy the shortest paths leading to that parent * and add the current vertex in the end */ long int parent_node = (long int) VECTOR(*parent_vec)[j]; long int parent_path_idx = (long int) VECTOR(*paths_index)[parent_node] - 1; /* printf(" Considering parent: %ld\n", parent_node); printf(" Paths to parent start at index %ld in res\n", parent_path_idx); */ assert(parent_path_idx >= 0); for (; parent_path_idx < path_count; parent_path_idx++) { parent_path = (igraph_vector_t*)VECTOR(*res)[parent_path_idx]; if (igraph_vector_tail(parent_path) != parent_node) { break; } path = igraph_Calloc(1, igraph_vector_t); if (path == 0) IGRAPH_ERROR("cannot run igraph_get_all_shortest_paths_dijkstra", IGRAPH_ENOMEM); IGRAPH_FINALLY(igraph_free, path); IGRAPH_CHECK(igraph_vector_copy(path, parent_path)); IGRAPH_CHECK(igraph_vector_ptr_push_back(res, path)); IGRAPH_FINALLY_CLEAN(1); /* ownership of path passed to res */ IGRAPH_CHECK(igraph_vector_push_back(path, node)); } } } /* remove the destructor from the path vector */ igraph_vector_ptr_set_item_destructor(res, 0); /* free those paths from the result vector which we won't need */ n = igraph_vector_ptr_size(res); j = 0; for (i = 0; i < n; i++) { igraph_real_t tmp; path = (igraph_vector_t*)VECTOR(*res)[i]; tmp = igraph_vector_tail(path); if (is_target[(long int)tmp] == 1) { /* we need this path, keep it */ VECTOR(*res)[j] = path; j++; } else { /* we don't need this path, free it */ igraph_vector_destroy(path); free(path); } } IGRAPH_CHECK(igraph_vector_ptr_resize(res, j)); /* sort the paths by the target vertices */ igraph_vector_ptr_sort(res, igraph_i_vector_tail_cmp); } /* free the allocated memory */ igraph_vector_destroy(&order); igraph_Free(is_target); igraph_vector_destroy(&dists); igraph_vector_ptr_destroy_all(&parents); IGRAPH_FINALLY_CLEAN(4); return 0; } /** * \function igraph_shortest_paths_bellman_ford * Weighted shortest paths from some sources allowing negative weights. * * This function is the Bellman-Ford algorithm to find the weighted * shortest paths to all vertices from a single source. (It is run * independently for the given sources.). If there are no negative * weights, you are better off with \ref igraph_shortest_paths_dijkstra() . * * \param graph The input graph, can be directed. * \param res The result, a matrix. A pointer to an initialized matrix * should be passed here, the matrix will be resized if needed. * Each row contains the distances from a single source, to all * vertices in the graph, in the order of vertex ids. For unreachable * vertices the matrix contains \c IGRAPH_INFINITY. * \param from The source vertices. * \param weights The edge weights. There mustn't be any closed loop in * the graph that has a negative total weight (since this would allow * us to decrease the weight of any path containing at least a single * vertex of this loop infinitely). If this is a null pointer, then the * unweighted version, \ref igraph_shortest_paths() is called. * \param mode For directed graphs; whether to follow paths along edge * directions (\c IGRAPH_OUT), or the opposite (\c IGRAPH_IN), or * ignore edge directions completely (\c IGRAPH_ALL). It is ignored * for undirected graphs. * \return Error code. * * Time complexity: O(s*|E|*|V|), where |V| is the number of * vertices, |E| the number of edges and s the number of sources. * * \sa \ref igraph_shortest_paths() for a faster unweighted version * or \ref igraph_shortest_paths_dijkstra() if you do not have negative * edge weights. * * \example examples/simple/bellman_ford.c */ int igraph_shortest_paths_bellman_ford(const igraph_t *graph, igraph_matrix_t *res, const igraph_vs_t from, const igraph_vs_t to, const igraph_vector_t *weights, igraph_neimode_t mode) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_lazy_inclist_t inclist; long int i, j, k; long int no_of_from, no_of_to; igraph_dqueue_t Q; igraph_vector_t clean_vertices; igraph_vector_t num_queued; igraph_vit_t fromvit, tovit; igraph_real_t my_infinity = IGRAPH_INFINITY; igraph_bool_t all_to; igraph_vector_t dist; /* - speedup: a vertex is marked clean if its distance from the source did not change during the last phase. Neighbors of a clean vertex are not relaxed again, since it would mean no change in the shortest path values. Dirty vertices are queued. Negative loops can be detected by checking whether a vertex has been queued at least n times. */ if (!weights) { return igraph_shortest_paths(graph, res, from, to, mode); } if (igraph_vector_size(weights) != no_of_edges) { IGRAPH_ERROR("Weight vector length does not match", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_vit_create(graph, from, &fromvit)); IGRAPH_FINALLY(igraph_vit_destroy, &fromvit); no_of_from = IGRAPH_VIT_SIZE(fromvit); IGRAPH_DQUEUE_INIT_FINALLY(&Q, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&clean_vertices, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&num_queued, no_of_nodes); IGRAPH_CHECK(igraph_lazy_inclist_init(graph, &inclist, mode)); IGRAPH_FINALLY(igraph_lazy_inclist_destroy, &inclist); if ( (all_to = igraph_vs_is_all(&to)) ) { no_of_to = no_of_nodes; } else { IGRAPH_CHECK(igraph_vit_create(graph, to, &tovit)); IGRAPH_FINALLY(igraph_vit_destroy, &tovit); no_of_to = IGRAPH_VIT_SIZE(tovit); } IGRAPH_VECTOR_INIT_FINALLY(&dist, no_of_nodes); IGRAPH_CHECK(igraph_matrix_resize(res, no_of_from, no_of_to)); for (IGRAPH_VIT_RESET(fromvit), i = 0; !IGRAPH_VIT_END(fromvit); IGRAPH_VIT_NEXT(fromvit), i++) { long int source = IGRAPH_VIT_GET(fromvit); igraph_vector_fill(&dist, my_infinity); VECTOR(dist)[source] = 0; igraph_vector_null(&clean_vertices); igraph_vector_null(&num_queued); /* Fill the queue with vertices to be checked */ for (j = 0; j < no_of_nodes; j++) { IGRAPH_CHECK(igraph_dqueue_push(&Q, j)); } while (!igraph_dqueue_empty(&Q)) { igraph_vector_t *neis; long int nlen; j = (long int) igraph_dqueue_pop(&Q); VECTOR(clean_vertices)[j] = 1; VECTOR(num_queued)[j] += 1; if (VECTOR(num_queued)[j] > no_of_nodes) { IGRAPH_ERROR("cannot run Bellman-Ford algorithm", IGRAPH_ENEGLOOP); } /* If we cannot get to j in finite time yet, there is no need to relax * its edges */ if (!IGRAPH_FINITE(VECTOR(dist)[j])) { continue; } neis = igraph_lazy_inclist_get(&inclist, (igraph_integer_t) j); nlen = igraph_vector_size(neis); for (k = 0; k < nlen; k++) { long int nei = (long int) VECTOR(*neis)[k]; long int target = IGRAPH_OTHER(graph, nei, j); if (VECTOR(dist)[target] > VECTOR(dist)[j] + VECTOR(*weights)[nei]) { /* relax the edge */ VECTOR(dist)[target] = VECTOR(dist)[j] + VECTOR(*weights)[nei]; if (VECTOR(clean_vertices)[target]) { VECTOR(clean_vertices)[target] = 0; IGRAPH_CHECK(igraph_dqueue_push(&Q, target)); } } } } /* Copy it to the result */ if (all_to) { igraph_matrix_set_row(res, &dist, i); } else { for (IGRAPH_VIT_RESET(tovit), j = 0; !IGRAPH_VIT_END(tovit); IGRAPH_VIT_NEXT(tovit), j++) { long int v = IGRAPH_VIT_GET(tovit); MATRIX(*res, i, j) = VECTOR(dist)[v]; } } } igraph_vector_destroy(&dist); IGRAPH_FINALLY_CLEAN(1); if (!all_to) { igraph_vit_destroy(&tovit); IGRAPH_FINALLY_CLEAN(1); } igraph_vit_destroy(&fromvit); igraph_dqueue_destroy(&Q); igraph_vector_destroy(&clean_vertices); igraph_vector_destroy(&num_queued); igraph_lazy_inclist_destroy(&inclist); IGRAPH_FINALLY_CLEAN(5); return 0; } /** * \function igraph_shortest_paths_johnson * Calculate shortest paths from some sources using Johnson's algorithm. * * See Wikipedia at http://en.wikipedia.org/wiki/Johnson's_algorithm * for Johnson's algorithm. This algorithm works even if the graph * contains negative edge weights, and it is worth using it if we * calculate the shortest paths from many sources. * * If no edge weights are supplied, then the unweighted * version, \ref igraph_shortest_paths() is called. * * If all the supplied edge weights are non-negative, * then Dijkstra's algorithm is used by calling * \ref igraph_shortest_paths_dijkstra(). * * \param graph The input graph, typically it is directed. * \param res Pointer to an initialized matrix, the result will be * stored here, one line for each source vertex, one column for each * target vertex. * \param from The source vertices. * \param to The target vertices. It is not allowed to include a * vertex twice or more. * \param weights Optional edge weights. If it is a null-pointer, then * the unweighted breadth-first search based \ref * igraph_shortest_paths() will be called. * \return Error code. * * Time complexity: O(s|V|log|V|+|V||E|), |V| and |E| are the number * of vertices and edges, s is the number of source vertices. * * \sa \ref igraph_shortest_paths() for a faster unweighted version * or \ref igraph_shortest_paths_dijkstra() if you do not have negative * edge weights, \ref igraph_shortest_paths_bellman_ford() if you only * need to calculate shortest paths from a couple of sources. */ int igraph_shortest_paths_johnson(const igraph_t *graph, igraph_matrix_t *res, const igraph_vs_t from, const igraph_vs_t to, const igraph_vector_t *weights) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_t newgraph; igraph_vector_t edges, newweights; igraph_matrix_t bfres; long int i, ptr; long int nr, nc; igraph_vit_t fromvit; /* If no weights, then we can just run the unweighted version */ if (!weights) { return igraph_shortest_paths(graph, res, from, to, IGRAPH_OUT); } if (igraph_vector_size(weights) != no_of_edges) { IGRAPH_ERROR("Weight vector length does not match", IGRAPH_EINVAL); } /* If no negative weights, then we can run Dijkstra's algorithm */ if (igraph_vector_min(weights) >= 0) { return igraph_shortest_paths_dijkstra(graph, res, from, to, weights, IGRAPH_OUT); } if (!igraph_is_directed(graph)) { IGRAPH_ERROR("Johnson's shortest path: undirected graph and negative weight", IGRAPH_EINVAL); } /* ------------------------------------------------------------ */ /* -------------------- Otherwise proceed --------------------- */ IGRAPH_MATRIX_INIT_FINALLY(&bfres, 0, 0); IGRAPH_VECTOR_INIT_FINALLY(&newweights, 0); IGRAPH_CHECK(igraph_empty(&newgraph, (igraph_integer_t) no_of_nodes + 1, igraph_is_directed(graph))); IGRAPH_FINALLY(igraph_destroy, &newgraph); /* Add a new node to the graph, plus edges from it to all the others. */ IGRAPH_VECTOR_INIT_FINALLY(&edges, no_of_edges * 2 + no_of_nodes * 2); igraph_get_edgelist(graph, &edges, /*bycol=*/ 0); igraph_vector_resize(&edges, no_of_edges * 2 + no_of_nodes * 2); for (i = 0, ptr = no_of_edges * 2; i < no_of_nodes; i++) { VECTOR(edges)[ptr++] = no_of_nodes; VECTOR(edges)[ptr++] = i; } IGRAPH_CHECK(igraph_add_edges(&newgraph, &edges, 0)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); IGRAPH_CHECK(igraph_vector_reserve(&newweights, no_of_edges + no_of_nodes)); igraph_vector_update(&newweights, weights); igraph_vector_resize(&newweights, no_of_edges + no_of_nodes); for (i = no_of_edges; i < no_of_edges + no_of_nodes; i++) { VECTOR(newweights)[i] = 0; } /* Run Bellmann-Ford algorithm on the new graph, starting from the new vertex. */ IGRAPH_CHECK(igraph_shortest_paths_bellman_ford(&newgraph, &bfres, igraph_vss_1((igraph_integer_t) no_of_nodes), igraph_vss_all(), &newweights, IGRAPH_OUT)); igraph_destroy(&newgraph); IGRAPH_FINALLY_CLEAN(1); /* Now the edges of the original graph are reweighted, using the values from the BF algorithm. Instead of w(u,v) we will have w(u,v) + h(u) - h(v) */ igraph_vector_resize(&newweights, no_of_edges); for (i = 0; i < no_of_edges; i++) { long int ffrom = IGRAPH_FROM(graph, i); long int tto = IGRAPH_TO(graph, i); VECTOR(newweights)[i] += MATRIX(bfres, 0, ffrom) - MATRIX(bfres, 0, tto); } /* Run Dijkstra's algorithm on the new weights */ IGRAPH_CHECK(igraph_shortest_paths_dijkstra(graph, res, from, to, &newweights, IGRAPH_OUT)); igraph_vector_destroy(&newweights); IGRAPH_FINALLY_CLEAN(1); /* Reweight the shortest paths */ nr = igraph_matrix_nrow(res); nc = igraph_matrix_ncol(res); IGRAPH_CHECK(igraph_vit_create(graph, from, &fromvit)); IGRAPH_FINALLY(igraph_vit_destroy, &fromvit); for (i = 0; i < nr; i++, IGRAPH_VIT_NEXT(fromvit)) { long int v1 = IGRAPH_VIT_GET(fromvit); if (igraph_vs_is_all(&to)) { long int v2; for (v2 = 0; v2 < nc; v2++) { igraph_real_t sub = MATRIX(bfres, 0, v1) - MATRIX(bfres, 0, v2); MATRIX(*res, i, v2) -= sub; } } else { long int j; igraph_vit_t tovit; IGRAPH_CHECK(igraph_vit_create(graph, to, &tovit)); IGRAPH_FINALLY(igraph_vit_destroy, &tovit); for (j = 0, IGRAPH_VIT_RESET(tovit); j < nc; j++, IGRAPH_VIT_NEXT(tovit)) { long int v2 = IGRAPH_VIT_GET(tovit); igraph_real_t sub = MATRIX(bfres, 0, v1) - MATRIX(bfres, 0, v2); MATRIX(*res, i, v2) -= sub; } igraph_vit_destroy(&tovit); IGRAPH_FINALLY_CLEAN(1); } } igraph_vit_destroy(&fromvit); igraph_matrix_destroy(&bfres); IGRAPH_FINALLY_CLEAN(2); return 0; } /** * \function igraph_unfold_tree * Unfolding a graph into a tree, by possibly multiplicating its vertices. * * A graph is converted into a tree (or forest, if it is unconnected), * by performing a breadth-first search on it, and replicating * vertices that were found a second, third, etc. time. * \param graph The input graph, it can be either directed or * undirected. * \param tree Pointer to an uninitialized graph object, the result is * stored here. * \param mode For directed graphs; whether to follow paths along edge * directions (\c IGRAPH_OUT), or the opposite (\c IGRAPH_IN), or * ignore edge directions completely (\c IGRAPH_ALL). It is ignored * for undirected graphs. * \param roots A numeric vector giving the root vertex, or vertices * (if the graph is not connected), to start from. * \param vertex_index Pointer to an initialized vector, or a null * pointer. If not a null pointer, then a mapping from the vertices * in the new graph to the ones in the original is created here. * \return Error code. * * Time complexity: O(n+m), linear in the number vertices and edges. * */ int igraph_unfold_tree(const igraph_t *graph, igraph_t *tree, igraph_neimode_t mode, const igraph_vector_t *roots, igraph_vector_t *vertex_index) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); long int no_of_roots = igraph_vector_size(roots); long int tree_vertex_count = no_of_nodes; igraph_vector_t edges; igraph_vector_bool_t seen_vertices; igraph_vector_bool_t seen_edges; igraph_dqueue_t Q; igraph_vector_t neis; long int i, n, r, v_ptr = no_of_nodes; /* TODO: handle not-connected graphs, multiple root vertices */ IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); igraph_vector_reserve(&edges, no_of_edges * 2); IGRAPH_DQUEUE_INIT_FINALLY(&Q, 100); IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); IGRAPH_VECTOR_BOOL_INIT_FINALLY(&seen_vertices, no_of_nodes); IGRAPH_VECTOR_BOOL_INIT_FINALLY(&seen_edges, no_of_edges); if (vertex_index) { IGRAPH_CHECK(igraph_vector_resize(vertex_index, no_of_nodes)); for (i = 0; i < no_of_nodes; i++) { VECTOR(*vertex_index)[i] = i; } } for (r = 0; r < no_of_roots; r++) { long int root = (long int) VECTOR(*roots)[r]; VECTOR(seen_vertices)[root] = 1; igraph_dqueue_push(&Q, root); while (!igraph_dqueue_empty(&Q)) { long int actnode = (long int) igraph_dqueue_pop(&Q); IGRAPH_CHECK(igraph_incident(graph, &neis, (igraph_integer_t) actnode, mode)); n = igraph_vector_size(&neis); for (i = 0; i < n; i++) { long int edge = (long int) VECTOR(neis)[i]; long int from = IGRAPH_FROM(graph, edge); long int to = IGRAPH_TO(graph, edge); long int nei = IGRAPH_OTHER(graph, edge, actnode); if (! VECTOR(seen_edges)[edge]) { VECTOR(seen_edges)[edge] = 1; if (! VECTOR(seen_vertices)[nei]) { igraph_vector_push_back(&edges, from); igraph_vector_push_back(&edges, to); VECTOR(seen_vertices)[nei] = 1; IGRAPH_CHECK(igraph_dqueue_push(&Q, nei)); } else { tree_vertex_count++; if (vertex_index) { IGRAPH_CHECK(igraph_vector_push_back(vertex_index, nei)); } if (from == nei) { igraph_vector_push_back(&edges, v_ptr++); igraph_vector_push_back(&edges, to); } else { igraph_vector_push_back(&edges, from); igraph_vector_push_back(&edges, v_ptr++); } } } } /* for i * * An undirected graph only has mutual edges, by definition. * * * Edge multiplicity is not considered here, e.g. if there are two * (A,B) edges and one (B,A) edge, then all three are considered to be * mutual. * * \param graph The input graph. * \param res Pointer to an initialized vector, the result is stored * here. * \param es The sequence of edges to check. Supply * igraph_ess_all() for all edges, see \ref * igraph_ess_all(). * \return Error code. * * Time complexity: O(n log(d)), n is the number of edges supplied, d * is the maximum in-degree of the vertices that are targets of the * supplied edges. An upper limit of the time complexity is O(n log(|E|)), * |E| is the number of edges in the graph. */ int igraph_is_mutual(igraph_t *graph, igraph_vector_bool_t *res, igraph_es_t es) { igraph_eit_t eit; igraph_lazy_adjlist_t adjlist; long int i; /* How many edges do we have? */ IGRAPH_CHECK(igraph_eit_create(graph, es, &eit)); IGRAPH_FINALLY(igraph_eit_destroy, &eit); IGRAPH_CHECK(igraph_vector_bool_resize(res, IGRAPH_EIT_SIZE(eit))); /* An undirected graph has mutual edges by definition, res is already properly resized */ if (! igraph_is_directed(graph)) { igraph_vector_bool_fill(res, 1); igraph_eit_destroy(&eit); IGRAPH_FINALLY_CLEAN(1); return 0; } IGRAPH_CHECK(igraph_lazy_adjlist_init(graph, &adjlist, IGRAPH_OUT, IGRAPH_DONT_SIMPLIFY)); IGRAPH_FINALLY(igraph_lazy_adjlist_destroy, &adjlist); for (i = 0; ! IGRAPH_EIT_END(eit); i++, IGRAPH_EIT_NEXT(eit)) { long int edge = IGRAPH_EIT_GET(eit); long int from = IGRAPH_FROM(graph, edge); long int to = IGRAPH_TO(graph, edge); /* Check whether there is a to->from edge, search for from in the out-list of to. We don't search an empty vector, because vector_binsearch seems to have a bug with this. */ igraph_vector_t *neis = igraph_lazy_adjlist_get(&adjlist, (igraph_integer_t) to); if (igraph_vector_empty(neis)) { VECTOR(*res)[i] = 0; } else { VECTOR(*res)[i] = igraph_vector_binsearch2(neis, from); } } igraph_lazy_adjlist_destroy(&adjlist); igraph_eit_destroy(&eit); IGRAPH_FINALLY_CLEAN(2); return 0; } int igraph_i_avg_nearest_neighbor_degree_weighted(const igraph_t *graph, igraph_vs_t vids, igraph_neimode_t mode, igraph_neimode_t neighbor_degree_mode, igraph_vector_t *knn, igraph_vector_t *knnk, const igraph_vector_t *weights); int igraph_i_avg_nearest_neighbor_degree_weighted(const igraph_t *graph, igraph_vs_t vids, igraph_neimode_t mode, igraph_neimode_t neighbor_degree_mode, igraph_vector_t *knn, igraph_vector_t *knnk, const igraph_vector_t *weights) { long int no_of_nodes = igraph_vcount(graph); igraph_vector_t neis, edge_neis; long int i, j, no_vids; igraph_vit_t vit; igraph_vector_t my_knn_v, *my_knn = knn; igraph_vector_t strength, deg; igraph_integer_t maxdeg; igraph_vector_t deghist; igraph_real_t mynan = IGRAPH_NAN; if (igraph_vector_size(weights) != igraph_ecount(graph)) { IGRAPH_ERROR("Invalid weight vector size", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); no_vids = IGRAPH_VIT_SIZE(vit); if (!knn) { IGRAPH_VECTOR_INIT_FINALLY(&my_knn_v, no_vids); my_knn = &my_knn_v; } else { IGRAPH_CHECK(igraph_vector_resize(knn, no_vids)); } // Get degree of neighbours IGRAPH_VECTOR_INIT_FINALLY(°, no_of_nodes); IGRAPH_CHECK(igraph_degree(graph, °, igraph_vss_all(), neighbor_degree_mode, IGRAPH_LOOPS)); IGRAPH_VECTOR_INIT_FINALLY(&strength, no_of_nodes); // Get strength of all nodes IGRAPH_CHECK(igraph_strength(graph, &strength, igraph_vss_all(), mode, IGRAPH_LOOPS, weights)); // Get maximum degree for initialization IGRAPH_CHECK(igraph_maxdegree(graph, &maxdeg, igraph_vss_all(), mode, IGRAPH_LOOPS)); IGRAPH_VECTOR_INIT_FINALLY(&neis, (long int)maxdeg); IGRAPH_VECTOR_INIT_FINALLY(&edge_neis, (long int)maxdeg); igraph_vector_resize(&neis, 0); igraph_vector_resize(&edge_neis, 0); if (knnk) { IGRAPH_CHECK(igraph_vector_resize(knnk, (long int)maxdeg)); igraph_vector_null(knnk); IGRAPH_VECTOR_INIT_FINALLY(°hist, (long int)maxdeg); } for (i = 0; !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit), i++) { igraph_real_t sum = 0.0; long int v = IGRAPH_VIT_GET(vit); long int nv; igraph_real_t str = VECTOR(strength)[v]; // Get neighbours and incident edges IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) v, mode)); IGRAPH_CHECK(igraph_incident(graph, &edge_neis, (igraph_integer_t) v, mode)); nv = igraph_vector_size(&neis); for (j = 0; j < nv; j++) { long int nei = (long int) VECTOR(neis)[j]; long int e = (long int) VECTOR(edge_neis)[j]; double w = VECTOR(*weights)[e]; sum += w * VECTOR(deg)[nei]; } if (str != 0.0) { VECTOR(*my_knn)[i] = sum / str; } else { VECTOR(*my_knn)[i] = mynan; } if (knnk && nv > 0) { VECTOR(*knnk)[nv - 1] += VECTOR(*my_knn)[i]; VECTOR(deghist)[nv - 1] += 1; } } if (knnk) { for (i = 0; i < maxdeg; i++) { igraph_real_t dh = VECTOR(deghist)[i]; if (dh != 0) { VECTOR(*knnk)[i] /= dh; } else { VECTOR(*knnk)[i] = mynan; } } igraph_vector_destroy(°hist); IGRAPH_FINALLY_CLEAN(1); } igraph_vector_destroy(&neis); igraph_vector_destroy(°); IGRAPH_FINALLY_CLEAN(2); if (!knn) { igraph_vector_destroy(&my_knn_v); IGRAPH_FINALLY_CLEAN(1); } igraph_vit_destroy(&vit); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_avg_nearest_neighbor_degree * Average nearest neighbor degree. * * Calculates the average degree of the neighbors for each vertex, and * optionally, the same quantity in the function of vertex degree. * * For isolate vertices \p knn is set to \c * IGRAPH_NAN. The same is done in \p knnk for vertex degrees that * don't appear in the graph. * * \param graph The input graph, it can be directed but the * directedness of the edges is ignored. * \param vids The vertices for which the calculation is performed. * \param mode The neighbors over which is averaged. * \param neighbor_degree_mode The degree of the neighbors which is * averaged. * \param vids The vertices for which the calculation is performed. * \param knn Pointer to an initialized vector, the result will be * stored here. It will be resized as needed. Supply a NULL pointer * here, if you only want to calculate \c knnk. * \param knnk Pointer to an initialized vector, the average nearest * neighbor degree in the function of vertex degree is stored * here. The first (zeroth) element is for degree one vertices, * etc. Supply a NULL pointer here if you don't want to calculate * this. * \param weights Optional edge weights. Supply a null pointer here * for the non-weighted version. The weighted version computes * a weighted average of the neighbor degrees, i.e. * * k_nn_i = 1/s_i sum_j w_ij k_j * * where s_i is the sum of the weights, the sum runs over * the neighbors as indicated by \c mode (with appropriate weights) * and k_j is the degree, specified by \c neighbor_degree_mode. * \return Error code. * * Time complexity: O(|V|+|E|), linear in the number of vertices and * edges. * * \example examples/simple/igraph_knn.c */ int igraph_avg_nearest_neighbor_degree(const igraph_t *graph, igraph_vs_t vids, igraph_neimode_t mode, igraph_neimode_t neighbor_degree_mode, igraph_vector_t *knn, igraph_vector_t *knnk, const igraph_vector_t *weights) { long int no_of_nodes = igraph_vcount(graph); igraph_vector_t neis; long int i, j, no_vids; igraph_vit_t vit; igraph_vector_t my_knn_v, *my_knn = knn; igraph_vector_t deg; igraph_integer_t maxdeg; igraph_vector_t deghist; igraph_real_t mynan = IGRAPH_NAN; igraph_bool_t simple; IGRAPH_CHECK(igraph_is_simple(graph, &simple)); if (!simple) { IGRAPH_ERROR("Average nearest neighbor degree works only with " "simple graphs", IGRAPH_EINVAL); } if (weights) { return igraph_i_avg_nearest_neighbor_degree_weighted(graph, vids, mode, neighbor_degree_mode, knn, knnk, weights); } IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); no_vids = IGRAPH_VIT_SIZE(vit); if (!knn) { IGRAPH_VECTOR_INIT_FINALLY(&my_knn_v, no_vids); my_knn = &my_knn_v; } else { IGRAPH_CHECK(igraph_vector_resize(knn, no_vids)); } IGRAPH_VECTOR_INIT_FINALLY(°, no_of_nodes); IGRAPH_CHECK(igraph_degree(graph, °, igraph_vss_all(), neighbor_degree_mode, IGRAPH_LOOPS)); igraph_maxdegree(graph, &maxdeg, igraph_vss_all(), mode, IGRAPH_LOOPS); IGRAPH_VECTOR_INIT_FINALLY(&neis, maxdeg); igraph_vector_resize(&neis, 0); if (knnk) { IGRAPH_CHECK(igraph_vector_resize(knnk, (long int)maxdeg)); igraph_vector_null(knnk); IGRAPH_VECTOR_INIT_FINALLY(°hist, (long int)maxdeg); } for (i = 0; !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit), i++) { igraph_real_t sum = 0.0; long int v = IGRAPH_VIT_GET(vit); long int nv; IGRAPH_CHECK(igraph_neighbors(graph, &neis, (igraph_integer_t) v, mode)); nv = igraph_vector_size(&neis); for (j = 0; j < nv; j++) { long int nei = (long int) VECTOR(neis)[j]; sum += VECTOR(deg)[nei]; } if (nv != 0) { VECTOR(*my_knn)[i] = sum / nv; } else { VECTOR(*my_knn)[i] = mynan; } if (knnk && nv > 0) { VECTOR(*knnk)[nv - 1] += VECTOR(*my_knn)[i]; VECTOR(deghist)[nv - 1] += 1; } } if (knnk) { for (i = 0; i < maxdeg; i++) { long int dh = (long int) VECTOR(deghist)[i]; if (dh != 0) { VECTOR(*knnk)[i] /= dh; } else { VECTOR(*knnk)[i] = mynan; } } igraph_vector_destroy(°hist); IGRAPH_FINALLY_CLEAN(1); } igraph_vector_destroy(&neis); igraph_vector_destroy(°); igraph_vit_destroy(&vit); IGRAPH_FINALLY_CLEAN(3); if (!knn) { igraph_vector_destroy(&my_knn_v); IGRAPH_FINALLY_CLEAN(1); } return 0; } /** * \function igraph_strength * Strength of the vertices, weighted vertex degree in other words. * * In a weighted network the strength of a vertex is the sum of the * weights of all incident edges. In a non-weighted network this is * exactly the vertex degree. * \param graph The input graph. * \param res Pointer to an initialized vector, the result is stored * here. It will be resized as needed. * \param vids The vertices for which the calculation is performed. * \param mode Gives whether to count only outgoing (\c IGRAPH_OUT), * incoming (\c IGRAPH_IN) edges or both (\c IGRAPH_ALL). * \param loops A logical scalar, whether to count loop edges as well. * \param weights A vector giving the edge weights. If this is a NULL * pointer, then \ref igraph_degree() is called to perform the * calculation. * \return Error code. * * Time complexity: O(|V|+|E|), linear in the number vertices and * edges. * * \sa \ref igraph_degree() for the traditional, non-weighted version. */ int igraph_strength(const igraph_t *graph, igraph_vector_t *res, const igraph_vs_t vids, igraph_neimode_t mode, igraph_bool_t loops, const igraph_vector_t *weights) { long int no_of_nodes = igraph_vcount(graph); igraph_vit_t vit; long int no_vids; igraph_vector_t neis; long int i; if (!weights) { return igraph_degree(graph, res, vids, mode, loops); } if (igraph_vector_size(weights) != igraph_ecount(graph)) { IGRAPH_ERROR("Invalid weight vector length", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); no_vids = IGRAPH_VIT_SIZE(vit); IGRAPH_VECTOR_INIT_FINALLY(&neis, 0); IGRAPH_CHECK(igraph_vector_reserve(&neis, no_of_nodes)); IGRAPH_CHECK(igraph_vector_resize(res, no_vids)); igraph_vector_null(res); if (loops) { for (i = 0; !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit), i++) { long int vid = IGRAPH_VIT_GET(vit); long int j, n; IGRAPH_CHECK(igraph_incident(graph, &neis, (igraph_integer_t) vid, mode)); n = igraph_vector_size(&neis); for (j = 0; j < n; j++) { long int edge = (long int) VECTOR(neis)[j]; VECTOR(*res)[i] += VECTOR(*weights)[edge]; } } } else { for (i = 0; !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit), i++) { long int vid = IGRAPH_VIT_GET(vit); long int j, n; IGRAPH_CHECK(igraph_incident(graph, &neis, (igraph_integer_t) vid, mode)); n = igraph_vector_size(&neis); for (j = 0; j < n; j++) { long int edge = (long int) VECTOR(neis)[j]; long int from = IGRAPH_FROM(graph, edge); long int to = IGRAPH_TO(graph, edge); if (from != to) { VECTOR(*res)[i] += VECTOR(*weights)[edge]; } } } } igraph_vit_destroy(&vit); igraph_vector_destroy(&neis); IGRAPH_FINALLY_CLEAN(2); return 0; } /** * \function igraph_diameter_dijkstra * Weighted diameter using Dijkstra's algorithm, non-negative weights only. * * The diameter of a graph is its longest geodesic. I.e. the * (weighted) shortest path is calculated for all pairs of vertices * and the longest one is the diameter. * \param graph The input graph, can be directed or undirected. * \param pres Pointer to a real number, if not \c NULL then it will contain * the diameter (the actual distance). * \param pfrom Pointer to an integer, if not \c NULL it will be set to the * source vertex of the diameter path. * \param pto Pointer to an integer, if not \c NULL it will be set to the * target vertex of the diameter path. * \param path Pointer to an initialized vector. If not \c NULL the actual * longest geodesic path will be stored here. The vector will be * resized as needed. * \param directed Boolean, whether to consider directed * paths. Ignored for undirected graphs. * \param unconn What to do if the graph is not connected. If * \c TRUE the longest geodesic within a component * will be returned, otherwise \c IGRAPH_INFINITY is * returned. * \return Error code. * * Time complexity: O(|V||E|*log|E|), |V| is the number of vertices, * |E| is the number of edges. */ int igraph_diameter_dijkstra(const igraph_t *graph, const igraph_vector_t *weights, igraph_real_t *pres, igraph_integer_t *pfrom, igraph_integer_t *pto, igraph_vector_t *path, igraph_bool_t directed, igraph_bool_t unconn) { /* Implementation details. This is the basic Dijkstra algorithm, with a binary heap. The heap is indexed, i.e. it stores not only the distances, but also which vertex they belong to. From now on we use a 2-way heap, so the distances can be queried directly from the heap. Dirty tricks: - the opposite of the distance is stored in the heap, as it is a maximum heap and we need a minimum heap. - we don't use IGRAPH_INFINITY during the computation, as IGRAPH_FINITE() might involve a function call and we want to spare that. -1 will denote infinity instead. */ long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_2wheap_t Q; igraph_inclist_t inclist; long int source, j; igraph_neimode_t dirmode = directed ? IGRAPH_OUT : IGRAPH_ALL; long int from = -1, to = -1; igraph_real_t res = 0; long int nodes_reached = 0; if (!weights) { igraph_integer_t diameter; IGRAPH_CHECK(igraph_diameter(graph, &diameter, pfrom, pto, path, directed, unconn)); if (pres) { *pres = diameter; } return IGRAPH_SUCCESS; } if (weights && igraph_vector_size(weights) != no_of_edges) { IGRAPH_ERROR("Invalid weight vector length", IGRAPH_EINVAL); } if (igraph_vector_min(weights) < 0) { IGRAPH_ERROR("Weight vector must be non-negative", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_2wheap_init(&Q, no_of_nodes)); IGRAPH_FINALLY(igraph_2wheap_destroy, &Q); IGRAPH_CHECK(igraph_inclist_init(graph, &inclist, dirmode)); IGRAPH_FINALLY(igraph_inclist_destroy, &inclist); for (source = 0; source < no_of_nodes; source++) { IGRAPH_PROGRESS("Weighted diameter: ", source * 100.0 / no_of_nodes, NULL); IGRAPH_ALLOW_INTERRUPTION(); igraph_2wheap_clear(&Q); igraph_2wheap_push_with_index(&Q, source, -1.0); nodes_reached = 0.0; while (!igraph_2wheap_empty(&Q)) { long int minnei = igraph_2wheap_max_index(&Q); igraph_real_t mindist = -igraph_2wheap_deactivate_max(&Q); igraph_vector_int_t *neis; long int nlen; if (mindist > res) { res = mindist; from = source; to = minnei; } nodes_reached++; /* Now check all neighbors of 'minnei' for a shorter path */ neis = igraph_inclist_get(&inclist, minnei); nlen = igraph_vector_int_size(neis); for (j = 0; j < nlen; j++) { long int edge = (long int) VECTOR(*neis)[j]; long int tto = IGRAPH_OTHER(graph, edge, minnei); igraph_real_t altdist = mindist + VECTOR(*weights)[edge]; igraph_bool_t active = igraph_2wheap_has_active(&Q, tto); igraph_bool_t has = igraph_2wheap_has_elem(&Q, tto); igraph_real_t curdist = active ? -igraph_2wheap_get(&Q, tto) : 0.0; if (!has) { /* First finite distance */ IGRAPH_CHECK(igraph_2wheap_push_with_index(&Q, tto, -altdist)); } else if (altdist < curdist) { /* A shorter path */ IGRAPH_CHECK(igraph_2wheap_modify(&Q, tto, -altdist)); } } } /* !igraph_2wheap_empty(&Q) */ /* not connected, return infinity */ if (nodes_reached != no_of_nodes && !unconn) { res = IGRAPH_INFINITY; from = to = -1; break; } } /* source < no_of_nodes */ /* Compensate for the +1 that we have added to distances */ res -= 1; igraph_inclist_destroy(&inclist); igraph_2wheap_destroy(&Q); IGRAPH_FINALLY_CLEAN(2); IGRAPH_PROGRESS("Weighted diameter: ", 100.0, NULL); if (pres) { *pres = res; } if (pfrom) { *pfrom = (igraph_integer_t) from; } if (pto) { *pto = (igraph_integer_t) to; } if (path) { if (!igraph_finite(res)) { igraph_vector_clear(path); } else { igraph_vector_ptr_t tmpptr; igraph_vector_ptr_init(&tmpptr, 1); IGRAPH_FINALLY(igraph_vector_ptr_destroy, &tmpptr); VECTOR(tmpptr)[0] = path; IGRAPH_CHECK(igraph_get_shortest_paths_dijkstra(graph, /*vertices=*/ &tmpptr, /*edges=*/ 0, (igraph_integer_t) from, igraph_vss_1((igraph_integer_t) to), weights, dirmode, /*predecessors=*/ 0, /*inbound_edges=*/ 0)); igraph_vector_ptr_destroy(&tmpptr); IGRAPH_FINALLY_CLEAN(1); } } return 0; } /** * \function igraph_sort_vertex_ids_by_degree * \brief Calculate a list of vertex ids sorted by degree of the corresponding vertex. * * The list of vertex ids is returned in a vector that is sorted * in ascending or descending order of vertex degree. * * \param graph The input graph. * \param outvids Pointer to an initialized vector that will be * resized and will contain the ordered vertex ids. * \param vids Input vertex selector of vertex ids to include in * calculation. * \param mode Defines the type of the degree. * \c IGRAPH_OUT, out-degree, * \c IGRAPH_IN, in-degree, * \c IGRAPH_ALL, total degree (sum of the * in- and out-degree). * This parameter is ignored for undirected graphs. * \param loops Boolean, gives whether the self-loops should be * counted. * \param order Specifies whether the ordering should be ascending * (\c IGRAPH_ASCENDING) or descending (\c IGRAPH_DESCENDING). * \param only_indices If true, then return a sorted list of indices * into a vector corresponding to \c vids, rather than a list * of vertex ids. This parameter is ignored if \c vids is set * to all vertices via igraph_vs_all() or igraph_vss_all(), * because in this case the indices and vertex ids are the * same. * \return Error code: * \c IGRAPH_EINVVID: invalid vertex id. * \c IGRAPH_EINVMODE: invalid mode argument. * */ int igraph_sort_vertex_ids_by_degree(const igraph_t *graph, igraph_vector_t *outvids, igraph_vs_t vids, igraph_neimode_t mode, igraph_bool_t loops, igraph_order_t order, igraph_bool_t only_indices) { long int i; igraph_vector_t degrees, vs_vec; IGRAPH_VECTOR_INIT_FINALLY(°rees, 0); IGRAPH_CHECK(igraph_degree(graph, °rees, vids, mode, loops)); IGRAPH_CHECK((int) igraph_vector_qsort_ind(°rees, outvids, order == IGRAPH_DESCENDING)); if (only_indices || igraph_vs_is_all(&vids) ) { igraph_vector_destroy(°rees); IGRAPH_FINALLY_CLEAN(1); } else { IGRAPH_VECTOR_INIT_FINALLY(&vs_vec, 0); IGRAPH_CHECK(igraph_vs_as_vector(graph, vids, &vs_vec)); for (i = 0; i < igraph_vector_size(outvids); i++) { VECTOR(*outvids)[i] = VECTOR(vs_vec)[(long int)VECTOR(*outvids)[i]]; } igraph_vector_destroy(&vs_vec); igraph_vector_destroy(°rees); IGRAPH_FINALLY_CLEAN(2); } return 0; } /** * \function igraph_contract_vertices * Replace multiple vertices with a single one. * * This function creates a new graph, by merging several * vertices into one. The vertices in the new graph correspond * to sets of vertices in the input graph. * \param graph The input graph, it can be directed or * undirected. * \param mapping A vector giving the mapping. For each * vertex in the original graph, it should contain * its id in the new graph. * \param vertex_comb What to do with the vertex attributes. * See the igraph manual section about attributes for * details. * \return Error code. * * Time complexity: O(|V|+|E|), linear in the number * or vertices plus edges. */ int igraph_contract_vertices(igraph_t *graph, const igraph_vector_t *mapping, const igraph_attribute_combination_t *vertex_comb) { igraph_vector_t edges; long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_bool_t vattr = vertex_comb && igraph_has_attribute_table(); igraph_t res; long int e, last = -1; long int no_new_vertices; if (igraph_vector_size(mapping) != no_of_nodes) { IGRAPH_ERROR("Invalid mapping vector length", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_CHECK(igraph_vector_reserve(&edges, no_of_edges * 2)); if (no_of_nodes > 0) { last = (long int) igraph_vector_max(mapping); } for (e = 0; e < no_of_edges; e++) { long int from = IGRAPH_FROM(graph, e); long int to = IGRAPH_TO(graph, e); long int nfrom = (long int) VECTOR(*mapping)[from]; long int nto = (long int) VECTOR(*mapping)[to]; igraph_vector_push_back(&edges, nfrom); igraph_vector_push_back(&edges, nto); if (nfrom > last) { last = nfrom; } if (nto > last) { last = nto; } } no_new_vertices = last + 1; IGRAPH_CHECK(igraph_create(&res, &edges, (igraph_integer_t) no_new_vertices, igraph_is_directed(graph))); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); IGRAPH_FINALLY(igraph_destroy, &res); IGRAPH_I_ATTRIBUTE_DESTROY(&res); IGRAPH_I_ATTRIBUTE_COPY(&res, graph, /*graph=*/ 1, /*vertex=*/ 0, /*edge=*/ 1); if (vattr) { long int i; igraph_vector_ptr_t merges; igraph_vector_t sizes; igraph_vector_t *vecs; vecs = igraph_Calloc(no_new_vertices, igraph_vector_t); if (!vecs) { IGRAPH_ERROR("Cannot combine attributes while contracting" " vertices", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, vecs); IGRAPH_CHECK(igraph_vector_ptr_init(&merges, no_new_vertices)); IGRAPH_FINALLY(igraph_i_simplify_free, &merges); IGRAPH_VECTOR_INIT_FINALLY(&sizes, no_new_vertices); for (i = 0; i < no_of_nodes; i++) { long int to = (long int) VECTOR(*mapping)[i]; VECTOR(sizes)[to] += 1; } for (i = 0; i < no_new_vertices; i++) { igraph_vector_t *v = &vecs[i]; IGRAPH_CHECK(igraph_vector_init(v, (long int) VECTOR(sizes)[i])); igraph_vector_clear(v); VECTOR(merges)[i] = v; } for (i = 0; i < no_of_nodes; i++) { long int to = (long int) VECTOR(*mapping)[i]; igraph_vector_t *v = &vecs[to]; igraph_vector_push_back(v, i); } IGRAPH_CHECK(igraph_i_attribute_combine_vertices(graph, &res, &merges, vertex_comb)); igraph_vector_destroy(&sizes); igraph_i_simplify_free(&merges); igraph_free(vecs); IGRAPH_FINALLY_CLEAN(3); } IGRAPH_FINALLY_CLEAN(1); igraph_destroy(graph); *graph = res; return 0; } /* Create the transitive closure of a tree graph. This is fairly simple, we just collect all ancestors of a vertex using a depth-first search. */ int igraph_transitive_closure_dag(const igraph_t *graph, igraph_t *closure) { long int no_of_nodes = igraph_vcount(graph); igraph_vector_t deg; igraph_vector_t new_edges; igraph_vector_t ancestors; long int root; igraph_vector_t neighbors; igraph_stack_t path; igraph_vector_bool_t done; if (!igraph_is_directed(graph)) { IGRAPH_ERROR("Tree transitive closure of a directed graph", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(&new_edges, 0); IGRAPH_VECTOR_INIT_FINALLY(°, no_of_nodes); IGRAPH_VECTOR_INIT_FINALLY(&ancestors, 0); IGRAPH_VECTOR_INIT_FINALLY(&neighbors, 0); IGRAPH_CHECK(igraph_stack_init(&path, 0)); IGRAPH_FINALLY(igraph_stack_destroy, &path); IGRAPH_CHECK(igraph_vector_bool_init(&done, no_of_nodes)); IGRAPH_FINALLY(igraph_vector_bool_destroy, &done); IGRAPH_CHECK(igraph_degree(graph, °, igraph_vss_all(), IGRAPH_OUT, IGRAPH_LOOPS)); #define STAR (-1) for (root = 0; root < no_of_nodes; root++) { if (VECTOR(deg)[root] != 0) { continue; } IGRAPH_CHECK(igraph_stack_push(&path, root)); while (!igraph_stack_empty(&path)) { long int node = (long int) igraph_stack_top(&path); if (node == STAR) { /* Leaving a node */ long int j, n; igraph_stack_pop(&path); node = (long int) igraph_stack_pop(&path); if (!VECTOR(done)[node]) { igraph_vector_pop_back(&ancestors); VECTOR(done)[node] = 1; } n = igraph_vector_size(&ancestors); for (j = 0; j < n; j++) { IGRAPH_CHECK(igraph_vector_push_back(&new_edges, node)); IGRAPH_CHECK(igraph_vector_push_back(&new_edges, VECTOR(ancestors)[j])); } } else { /* Getting into a node */ long int n, j; if (!VECTOR(done)[node]) { IGRAPH_CHECK(igraph_vector_push_back(&ancestors, node)); } IGRAPH_CHECK(igraph_neighbors(graph, &neighbors, (igraph_integer_t) node, IGRAPH_IN)); n = igraph_vector_size(&neighbors); IGRAPH_CHECK(igraph_stack_push(&path, STAR)); for (j = 0; j < n; j++) { long int nei = (long int) VECTOR(neighbors)[j]; IGRAPH_CHECK(igraph_stack_push(&path, nei)); } } } } #undef STAR igraph_vector_bool_destroy(&done); igraph_stack_destroy(&path); igraph_vector_destroy(&neighbors); igraph_vector_destroy(&ancestors); igraph_vector_destroy(°); IGRAPH_FINALLY_CLEAN(5); IGRAPH_CHECK(igraph_create(closure, &new_edges, (igraph_integer_t)no_of_nodes, IGRAPH_DIRECTED)); igraph_vector_destroy(&new_edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_diversity * Structural diversity index of the vertices * * This measure was defined in Nathan Eagle, Michael Macy and Rob * Claxton: Network Diversity and Economic Development, Science 328, * 1029--1031, 2010. * * * It is simply the (normalized) Shannon entropy of the * incident edges' weights. D(i)=H(i)/log(k[i]), and * H(i) = -sum(p[i,j] log(p[i,j]), j=1..k[i]), * where p[i,j]=w[i,j]/sum(w[i,l], l=1..k[i]), k[i] is the (total) * degree of vertex i, and w[i,j] is the weight of the edge(s) between * vertex i and j. * \param graph The input graph, edge directions are ignored. * \param weights The edge weights, in the order of the edge ids, must * have appropriate length. * \param res An initialized vector, the results are stored here. * \param vids Vector with the vertex ids for which to calculate the * measure. * \return Error code. * * Time complexity: O(|V|+|E|), linear. * */ int igraph_diversity(igraph_t *graph, const igraph_vector_t *weights, igraph_vector_t *res, const igraph_vs_t vids) { int no_of_nodes = igraph_vcount(graph); int no_of_edges = igraph_ecount(graph); igraph_vector_t incident; igraph_vit_t vit; igraph_real_t s, ent, w; int i, j, k; if (!weights) { IGRAPH_ERROR("Edge weights must be given", IGRAPH_EINVAL); } if (igraph_vector_size(weights) != no_of_edges) { IGRAPH_ERROR("Invalid edge weight vector length", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(&incident, 10); if (igraph_vs_is_all(&vids)) { IGRAPH_CHECK(igraph_vector_resize(res, no_of_nodes)); for (i = 0; i < no_of_nodes; i++) { s = ent = 0.0; IGRAPH_CHECK(igraph_incident(graph, &incident, i, /*mode=*/ IGRAPH_ALL)); for (j = 0, k = (int) igraph_vector_size(&incident); j < k; j++) { w = VECTOR(*weights)[(long int)VECTOR(incident)[j]]; s += w; ent += (w * log(w)); } VECTOR(*res)[i] = (log(s) - ent / s) / log(k); } } else { IGRAPH_CHECK(igraph_vector_resize(res, 0)); IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); for (IGRAPH_VIT_RESET(vit), i = 0; !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit), i++) { long int v = IGRAPH_VIT_GET(vit); s = ent = 0.0; IGRAPH_CHECK(igraph_incident(graph, &incident, (igraph_integer_t) v, /*mode=*/ IGRAPH_ALL)); for (j = 0, k = (int) igraph_vector_size(&incident); j < k; j++) { w = VECTOR(*weights)[(long int)VECTOR(incident)[j]]; s += w; ent += (w * log(w)); } IGRAPH_CHECK(igraph_vector_push_back(res, (log(s) - ent / s) / log(k))); } igraph_vit_destroy(&vit); IGRAPH_FINALLY_CLEAN(1); } igraph_vector_destroy(&incident); IGRAPH_FINALLY_CLEAN(1); return 0; } #define SUCCEED { \ if (res) { \ *res = 1; \ } \ return IGRAPH_SUCCESS; \ } #define FAIL { \ if (res) { \ *res = 0; \ } \ return IGRAPH_SUCCESS; \ } /** * \function igraph_is_degree_sequence * Determines whether a degree sequence is valid. * * A sequence of n integers is a valid degree sequence if there exists some * graph where the degree of the i-th vertex is equal to the i-th element of the * sequence. Note that the graph may contain multiple or loop edges; if you are * interested in whether the degrees of some \em simple graph may realize the * given sequence, use \ref igraph_is_graphical_degree_sequence. * * * In particular, the function checks whether all the degrees are non-negative. * For undirected graphs, it also checks whether the sum of degrees is even. * For directed graphs, the function checks whether the lengths of the two * degree vectors are equal and whether their sums are also equal. These are * known sufficient and necessary conditions for a degree sequence to be * valid. * * \param out_degrees an integer vector specifying the degree sequence for * undirected graphs or the out-degree sequence for directed graphs. * \param in_degrees an integer vector specifying the in-degrees of the * vertices for directed graphs. For undirected graphs, this must be null. * \param res pointer to a boolean variable, the result will be stored here * \return Error code. * * Time complexity: O(n), where n is the length of the degree sequence. */ int igraph_is_degree_sequence(const igraph_vector_t *out_degrees, const igraph_vector_t *in_degrees, igraph_bool_t *res) { /* degrees must be non-negative */ if (igraph_vector_any_smaller(out_degrees, 0)) { FAIL; } if (in_degrees && igraph_vector_any_smaller(in_degrees, 0)) { FAIL; } if (in_degrees == 0) { /* sum of degrees must be even */ if (((long int)igraph_vector_sum(out_degrees) % 2) != 0) { FAIL; } } else { /* length of the two degree vectors must be equal */ if (igraph_vector_size(out_degrees) != igraph_vector_size(in_degrees)) { FAIL; } /* sum of in-degrees must be equal to sum of out-degrees */ if (igraph_vector_sum(out_degrees) != igraph_vector_sum(in_degrees)) { FAIL; } } SUCCEED; return 0; } int igraph_i_is_graphical_degree_sequence_undirected( const igraph_vector_t *degrees, igraph_bool_t *res); int igraph_i_is_graphical_degree_sequence_directed( const igraph_vector_t *out_degrees, const igraph_vector_t *in_degrees, igraph_bool_t *res); /** * \function igraph_is_graphical_degree_sequence * Determines whether a sequence of integers can be a degree sequence of some * simple graph. * * * References: * * * Hakimi SL: On the realizability of a set of integers as degrees of the * vertices of a simple graph. J SIAM Appl Math 10:496-506, 1962. * * * PL Erdos, I Miklos and Z Toroczkai: A simple Havel-Hakimi type algorithm * to realize graphical degree sequences of directed graphs. The Electronic * Journal of Combinatorics 17(1):R66, 2010. * * * Z Kiraly: Recognizing graphic degree sequences and generating all * realizations. TR-2011-11, Egervary Research Group, H-1117, Budapest, * Hungary. ISSN 1587-4451, 2012. * * \param out_degrees an integer vector specifying the degree sequence for * undirected graphs or the out-degree sequence for directed graphs. * \param in_degrees an integer vector specifying the in-degrees of the * vertices for directed graphs. For undirected graphs, this must be null. * \param res pointer to a boolean variable, the result will be stored here * \return Error code. * * Time complexity: O(n log n) for undirected graphs, O(n^2) for directed * graphs, where n is the length of the degree sequence. */ int igraph_is_graphical_degree_sequence(const igraph_vector_t *out_degrees, const igraph_vector_t *in_degrees, igraph_bool_t *res) { IGRAPH_CHECK(igraph_is_degree_sequence(out_degrees, in_degrees, res)); if (!*res) { FAIL; } if (igraph_vector_size(out_degrees) == 0) { SUCCEED; } if (in_degrees == 0) { return igraph_i_is_graphical_degree_sequence_undirected(out_degrees, res); } else { return igraph_i_is_graphical_degree_sequence_directed(out_degrees, in_degrees, res); } } int igraph_i_is_graphical_degree_sequence_undirected( const igraph_vector_t *degrees, igraph_bool_t *res) { igraph_vector_t work; long int w, b, s, c, n, k; IGRAPH_CHECK(igraph_vector_copy(&work, degrees)); IGRAPH_FINALLY(igraph_vector_destroy, &work); igraph_vector_sort(&work); /* This algorithm is outlined in TR-2011-11 of the Egervary Research Group, * ISSN 1587-4451. The main loop of the algorithm is O(n) but it is dominated * by an O(n log n) quicksort; this could in theory be brought down to * O(n) with binsort but it's probably not worth the fuss. * * Variables names are mostly according to the technical report, apart from * the degrees themselves. w and k are zero-based here; in the technical * report they are 1-based */ *res = 1; n = igraph_vector_size(&work); w = n - 1; b = 0; s = 0; c = 0; for (k = 0; k < n; k++) { b += VECTOR(*degrees)[k]; c += w; while (w > k && VECTOR(*degrees)[w] <= k + 1) { s += VECTOR(*degrees)[w]; c -= (k + 1); w--; } if (b > c + s) { *res = 0; break; } if (w == k) { break; } } igraph_vector_destroy(&work); IGRAPH_FINALLY_CLEAN(1); return 0; } typedef struct { const igraph_vector_t* first; const igraph_vector_t* second; } igraph_i_qsort_dual_vector_cmp_data_t; int igraph_i_qsort_dual_vector_cmp_desc(void* data, const void *p1, const void *p2) { igraph_i_qsort_dual_vector_cmp_data_t* sort_data = (igraph_i_qsort_dual_vector_cmp_data_t*)data; long int index1 = *((long int*)p1); long int index2 = *((long int*)p2); if (VECTOR(*sort_data->first)[index1] < VECTOR(*sort_data->first)[index2]) { return 1; } if (VECTOR(*sort_data->first)[index1] > VECTOR(*sort_data->first)[index2]) { return -1; } if (VECTOR(*sort_data->second)[index1] < VECTOR(*sort_data->second)[index2]) { return 1; } if (VECTOR(*sort_data->second)[index1] > VECTOR(*sort_data->second)[index2]) { return -1; } return 0; } int igraph_i_is_graphical_degree_sequence_directed( const igraph_vector_t *out_degrees, const igraph_vector_t *in_degrees, igraph_bool_t *res) { igraph_vector_long_t index_array; long int i, j, vcount, lhs, rhs; igraph_i_qsort_dual_vector_cmp_data_t sort_data; /* Create an index vector that sorts the vertices by decreasing in-degree */ vcount = igraph_vector_size(out_degrees); IGRAPH_CHECK(igraph_vector_long_init_seq(&index_array, 0, vcount - 1)); IGRAPH_FINALLY(igraph_vector_long_destroy, &index_array); /* Set up the auxiliary struct for sorting */ sort_data.first = in_degrees; sort_data.second = out_degrees; /* Sort the index vector */ igraph_qsort_r(VECTOR(index_array), vcount, sizeof(long int), &sort_data, igraph_i_qsort_dual_vector_cmp_desc); /* Be optimistic, then check whether the Fulkerson–Chen–Anstee condition * holds for every k. In particular, for every k in [0; n), it must be true * that: * * \sum_{i=0}^k indegree[i] <= * \sum_{i=0}^k min(outdegree[i], k) + * \sum_{i=k+1}^{n-1} min(outdegree[i], k + 1) */ #define INDEGREE(x) (VECTOR(*in_degrees)[VECTOR(index_array)[x]]) #define OUTDEGREE(x) (VECTOR(*out_degrees)[VECTOR(index_array)[x]]) *res = 1; lhs = 0; for (i = 0; i < vcount; i++) { lhs += INDEGREE(i); /* It is enough to check for indexes where the in-degree is about to * decrease in the next step; see "Stronger condition" in the Wikipedia * entry for the Fulkerson-Chen-Anstee condition */ if (i != vcount - 1 && INDEGREE(i) == INDEGREE(i + 1)) { continue; } rhs = 0; for (j = 0; j <= i; j++) { rhs += OUTDEGREE(j) < i ? OUTDEGREE(j) : i; } for (j = i + 1; j < vcount; j++) { rhs += OUTDEGREE(j) < (i + 1) ? OUTDEGREE(j) : (i + 1); } if (lhs > rhs) { *res = 0; break; } } #undef INDEGREE #undef OUTDEGREE igraph_vector_long_destroy(&index_array); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } #undef SUCCEED #undef FAIL /* igraph_is_tree -- check if a graph is a tree */ /* count the number of vertices reachable from the root */ static int igraph_i_is_tree_visitor(igraph_integer_t root, const igraph_adjlist_t *al, igraph_integer_t *visited_count) { igraph_stack_int_t stack; igraph_vector_bool_t visited; long i; IGRAPH_CHECK(igraph_vector_bool_init(&visited, igraph_adjlist_size(al))); IGRAPH_FINALLY(igraph_vector_bool_destroy, &visited); IGRAPH_CHECK(igraph_stack_int_init(&stack, 0)); IGRAPH_FINALLY(igraph_stack_int_destroy, &stack); *visited_count = 0; /* push the root into the stack */ IGRAPH_CHECK(igraph_stack_int_push(&stack, root)); while (! igraph_stack_int_empty(&stack)) { igraph_integer_t u; igraph_vector_int_t *neighbors; long ncount; /* take a vertex from the stack, mark it as visited */ u = igraph_stack_int_pop(&stack); if (IGRAPH_LIKELY(! VECTOR(visited)[u])) { VECTOR(visited)[u] = 1; *visited_count += 1; } /* register all its yet-unvisited neighbours for future processing */ neighbors = igraph_adjlist_get(al, u); ncount = igraph_vector_int_size(neighbors); for (i = 0; i < ncount; ++i) { igraph_integer_t v = VECTOR(*neighbors)[i]; if (! VECTOR(visited)[v]) { IGRAPH_CHECK(igraph_stack_int_push(&stack, v)); } } } igraph_stack_int_destroy(&stack); igraph_vector_bool_destroy(&visited); IGRAPH_FINALLY_CLEAN(2); return IGRAPH_SUCCESS; } /** * \ingroup structural * \function igraph_is_tree * \brief Decides whether the graph is a tree. * * An undirected graph is a tree if it is connected and has no cycles. * * * In the directed case, a possible additional requirement is that all * edges are oriented away from a root (out-tree or arborescence) or all edges * are oriented towards a root (in-tree or anti-arborescence). * This test can be controlled using the \p mode parameter. * * * By convention, the null graph (i.e. the graph with no vertices) is considered not to be a tree. * * \param graph The graph object to analyze. * \param res Pointer to a logical variable, the result will be stored * here. * \param root If not \c NULL, the root node will be stored here. When \p mode * is \c IGRAPH_ALL or the graph is undirected, any vertex can be the root * and \p root is set to 0 (the first vertex). When \p mode is \c IGRAPH_OUT * or \c IGRAPH_IN, the root is set to the vertex with zero in- or out-degree, * respectively. * \param mode For a directed graph this specifies whether to test for an * out-tree, an in-tree or ignore edge directions. The respective * possible values are: * \c IGRAPH_OUT, \c IGRAPH_IN, \c IGRAPH_ALL. This argument is * ignored for undirected graphs. * \return Error code: * \c IGRAPH_EINVAL: invalid mode argument. * * Time complexity: At most O(|V|+|E|), the * number of vertices plus the number of edges in the graph. * * \sa igraph_is_weakly_connected() * * \example examples/simple/igraph_tree.c */ int igraph_is_tree(const igraph_t *graph, igraph_bool_t *res, igraph_integer_t *root, igraph_neimode_t mode) { igraph_adjlist_t al; igraph_integer_t iroot = 0; igraph_integer_t visited_count; igraph_integer_t vcount, ecount; vcount = igraph_vcount(graph); ecount = igraph_ecount(graph); /* A tree must have precisely vcount-1 edges. */ /* By convention, the zero-vertex graph will not be considered a tree. */ if (ecount != vcount - 1) { *res = 0; return IGRAPH_SUCCESS; } /* The single-vertex graph is a tree, provided it has no edges (checked in the previous if (..)) */ if (vcount == 1) { *res = 1; if (root) { *root = 0; } return IGRAPH_SUCCESS; } /* For higher vertex counts we cannot short-circuit due to the possibility * of loops or multi-edges even when the edge count is correct. */ /* Ignore mode for undirected graphs. */ if (! igraph_is_directed(graph)) { mode = IGRAPH_ALL; } IGRAPH_CHECK(igraph_adjlist_init(graph, &al, mode)); IGRAPH_FINALLY(igraph_adjlist_destroy, &al); /* The main algorithm: * We find a root and check that all other vertices are reachable from it. * We have already checked the number of edges, so with the additional * reachability condition we can verify if the graph is a tree. * * For directed graphs, the root is the node with no incoming/outgoing * connections, depending on 'mode'. For undirected, it is arbitrary, so * we choose 0. */ *res = 1; /* assume success */ switch (mode) { case IGRAPH_ALL: iroot = 0; break; case IGRAPH_IN: case IGRAPH_OUT: { igraph_vector_t degree; igraph_integer_t i; IGRAPH_CHECK(igraph_vector_init(°ree, 0)); IGRAPH_FINALLY(igraph_vector_destroy, °ree); IGRAPH_CHECK(igraph_degree(graph, °ree, igraph_vss_all(), mode == IGRAPH_IN ? IGRAPH_OUT : IGRAPH_IN, /* loops = */ 1)); for (i = 0; i < vcount; ++i) if (VECTOR(degree)[i] == 0) { break; } /* if no suitable root is found, the graph is not a tree */ if (i == vcount) { *res = 0; } else { iroot = i; } igraph_vector_destroy(°ree); IGRAPH_FINALLY_CLEAN(1); } break; default: IGRAPH_ERROR("Invalid mode", IGRAPH_EINVMODE); } /* if no suitable root was found, skip visting vertices */ if (*res) { IGRAPH_CHECK(igraph_i_is_tree_visitor(iroot, &al, &visited_count)); *res = visited_count == vcount; } if (root) { *root = iroot; } igraph_adjlist_destroy(&al); IGRAPH_FINALLY_CLEAN(1); return IGRAPH_SUCCESS; } python-igraph-0.8.0/vendor/source/igraph/src/walktrap_heap.h0000644000076500000240000001055713614300625024401 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ /* The original version of this file was written by Pascal Pons The original copyright notice follows here. The FSF address was fixed by Tamas Nepusz */ // File: heap.h //----------------------------------------------------------------------------- // Walktrap v0.2 -- Finds community structure of networks using random walks // Copyright (C) 2004-2005 Pascal Pons // // This program is free software; you can redistribute it and/or modify // it under the terms of the GNU General Public License as published by // the Free Software Foundation; either version 2 of the License, or // (at your option) any later version. // // This program is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU General Public License for more details. // // You should have received a copy of the GNU General Public License // along with this program; if not, write to the Free Software // Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA // 02110-1301 USA //----------------------------------------------------------------------------- // Author : Pascal Pons // Email : pons@liafa.jussieu.fr // Web page : http://www.liafa.jussieu.fr/~pons/ // Location : Paris, France // Time : June 2005 //----------------------------------------------------------------------------- // see readme.txt for more details #ifndef HEAP_H #define HEAP_H namespace igraph { namespace walktrap { class Neighbor { public: int community1; // the two adjacent communities int community2; // community1 < community2 float delta_sigma; // the delta sigma between the two communities float weight; // the total weight of the edges between the two communities bool exact; // true if delta_sigma is exact, false if it is only a lower bound Neighbor* next_community1; // pointers of two double Neighbor* previous_community1; // chained lists containing Neighbor* next_community2; // all the neighbors of Neighbor* previous_community2; // each communities. int heap_index; // Neighbor(); }; class Neighbor_heap { private: int size; int max_size; Neighbor** H; // the heap that contains a pointer to each Neighbor object stored void move_up(int index); void move_down(int index); public: void add(Neighbor* N); // add a new distance void update(Neighbor* N); // update a distance void remove(Neighbor* N); // remove a distance Neighbor* get_first(); // get the first item long memory(); bool is_empty(); Neighbor_heap(int max_size); ~Neighbor_heap(); }; class Min_delta_sigma_heap { private: int size; int max_size; int* H; // the heap that contains the number of each community int* I; // the index of each community in the heap (-1 = not stored) void move_up(int index); void move_down(int index); public: int get_max_community(); // return the community with the maximal delta_sigma void remove_community(int community); // remove a community; void update(int community); // update (or insert if necessary) the community long memory(); // the memory used in Bytes. bool is_empty(); float* delta_sigma; // the delta_sigma of the stored communities Min_delta_sigma_heap(int max_size); ~Min_delta_sigma_heap(); }; } } /* end of namespaces */ #endif python-igraph-0.8.0/vendor/source/igraph/src/attributes.c0000644000076500000240000003240513614300625023734 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2005-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_attributes.h" #include "igraph_memory.h" #include "config.h" #include #include /* Should you ever want to have a thread-local attribute handler table, prepend * IGRAPH_THREAD_LOCAL to the following declaration */ igraph_attribute_table_t *igraph_i_attribute_table = 0; int igraph_i_attribute_init(igraph_t *graph, void *attr) { graph->attr = 0; if (igraph_i_attribute_table) { return igraph_i_attribute_table->init(graph, attr); } else { return 0; } } void igraph_i_attribute_destroy(igraph_t *graph) { if (igraph_i_attribute_table) { igraph_i_attribute_table->destroy(graph); } } int igraph_i_attribute_copy(igraph_t *to, const igraph_t *from, igraph_bool_t ga, igraph_bool_t va, igraph_bool_t ea) { if (igraph_i_attribute_table) { return igraph_i_attribute_table->copy(to, from, ga, va, ea); } else { return 0; } } int igraph_i_attribute_add_vertices(igraph_t *graph, long int nv, void *attr) { if (igraph_i_attribute_table) { return igraph_i_attribute_table->add_vertices(graph, nv, attr); } else { return 0; } } int igraph_i_attribute_permute_vertices(const igraph_t *graph, igraph_t *newgraph, const igraph_vector_t *idx) { if (igraph_i_attribute_table) { return igraph_i_attribute_table->permute_vertices(graph, newgraph, idx); } else { return 0; } } int igraph_i_attribute_combine_vertices(const igraph_t *graph, igraph_t *newgraph, const igraph_vector_ptr_t *merges, const igraph_attribute_combination_t *comb) { if (igraph_i_attribute_table) { return igraph_i_attribute_table->combine_vertices(graph, newgraph, merges, comb); } else { return 0; } } int igraph_i_attribute_add_edges(igraph_t *graph, const igraph_vector_t *edges, void *attr) { if (igraph_i_attribute_table) { return igraph_i_attribute_table->add_edges(graph, edges, attr); } else { return 0; } } int igraph_i_attribute_permute_edges(const igraph_t *graph, igraph_t *newgraph, const igraph_vector_t *idx) { if (igraph_i_attribute_table) { return igraph_i_attribute_table->permute_edges(graph, newgraph, idx); } else { return 0; } } int igraph_i_attribute_combine_edges(const igraph_t *graph, igraph_t *newgraph, const igraph_vector_ptr_t *merges, const igraph_attribute_combination_t *comb) { if (igraph_i_attribute_table) { return igraph_i_attribute_table->combine_edges(graph, newgraph, merges, comb); } else { return 0; } } int igraph_i_attribute_get_info(const igraph_t *graph, igraph_strvector_t *gnames, igraph_vector_t *gtypes, igraph_strvector_t *vnames, igraph_vector_t *vtypes, igraph_strvector_t *enames, igraph_vector_t *etypes) { if (igraph_i_attribute_table) { return igraph_i_attribute_table->get_info(graph, gnames, gtypes, vnames, vtypes, enames, etypes); } else { return 0; } } igraph_bool_t igraph_i_attribute_has_attr(const igraph_t *graph, igraph_attribute_elemtype_t type, const char *name) { if (igraph_i_attribute_table) { return igraph_i_attribute_table->has_attr(graph, type, name); } else { return 0; } } int igraph_i_attribute_gettype(const igraph_t *graph, igraph_attribute_type_t *type, igraph_attribute_elemtype_t elemtype, const char *name) { if (igraph_i_attribute_table) { return igraph_i_attribute_table->gettype(graph, type, elemtype, name); } else { return 0; } } int igraph_i_attribute_get_numeric_graph_attr(const igraph_t *graph, const char *name, igraph_vector_t *value) { if (igraph_i_attribute_table) { return igraph_i_attribute_table->get_numeric_graph_attr(graph, name, value); } else { return 0; } } int igraph_i_attribute_get_numeric_vertex_attr(const igraph_t *graph, const char *name, igraph_vs_t vs, igraph_vector_t *value) { if (igraph_i_attribute_table) { return igraph_i_attribute_table->get_numeric_vertex_attr(graph, name, vs, value); } else { return 0; } } int igraph_i_attribute_get_numeric_edge_attr(const igraph_t *graph, const char *name, igraph_es_t es, igraph_vector_t *value) { if (igraph_i_attribute_table) { return igraph_i_attribute_table->get_numeric_edge_attr(graph, name, es, value); } else { return 0; } } int igraph_i_attribute_get_string_graph_attr(const igraph_t *graph, const char *name, igraph_strvector_t *value) { if (igraph_i_attribute_table) { return igraph_i_attribute_table->get_string_graph_attr(graph, name, value); } else { return 0; } } int igraph_i_attribute_get_string_vertex_attr(const igraph_t *graph, const char *name, igraph_vs_t vs, igraph_strvector_t *value) { if (igraph_i_attribute_table) { return igraph_i_attribute_table->get_string_vertex_attr(graph, name, vs, value); } else { return 0; } } int igraph_i_attribute_get_string_edge_attr(const igraph_t *graph, const char *name, igraph_es_t es, igraph_strvector_t *value) { if (igraph_i_attribute_table) { return igraph_i_attribute_table->get_string_edge_attr(graph, name, es, value); } else { return 0; } } int igraph_i_attribute_get_bool_graph_attr(const igraph_t *graph, const char *name, igraph_vector_bool_t *value) { if (igraph_i_attribute_table) { return igraph_i_attribute_table->get_bool_graph_attr(graph, name, value); } else { return 0; } } int igraph_i_attribute_get_bool_vertex_attr(const igraph_t *graph, const char *name, igraph_vs_t vs, igraph_vector_bool_t *value) { if (igraph_i_attribute_table) { return igraph_i_attribute_table->get_bool_vertex_attr(graph, name, vs, value); } else { return 0; } } int igraph_i_attribute_get_bool_edge_attr(const igraph_t *graph, const char *name, igraph_es_t es, igraph_vector_bool_t *value) { if (igraph_i_attribute_table) { return igraph_i_attribute_table->get_bool_edge_attr(graph, name, es, value); } else { return 0; } } /** * \function igraph_i_set_attribute_table * \brief Attach an attribute table. * * This function attaches attribute handling code to the igraph library. * Note that the attribute handler table is \em not thread-local even if * igraph is compiled in thread-local mode. In the vast majority of cases, * this is not a significant restriction. * * \param table Pointer to an \ref igraph_attribute_table_t object * containing the functions for attribute manipulation. Supply \c * NULL here if you don't want attributes. * \return Pointer to the old attribute handling table. * * Time complexity: O(1). */ igraph_attribute_table_t * igraph_i_set_attribute_table(const igraph_attribute_table_t * table) { igraph_attribute_table_t *old = igraph_i_attribute_table; igraph_i_attribute_table = (igraph_attribute_table_t*) table; return old; } igraph_bool_t igraph_has_attribute_table() { return igraph_i_attribute_table != 0; } int igraph_attribute_combination_init(igraph_attribute_combination_t *comb) { IGRAPH_CHECK(igraph_vector_ptr_init(&comb->list, 0)); return 0; } void igraph_attribute_combination_destroy(igraph_attribute_combination_t *comb) { long int i, n = igraph_vector_ptr_size(&comb->list); for (i = 0; i < n; i++) { igraph_attribute_combination_record_t *rec = VECTOR(comb->list)[i]; if (rec->name) { igraph_Free(rec->name); } igraph_Free(rec); } igraph_vector_ptr_destroy(&comb->list); } int igraph_attribute_combination_add(igraph_attribute_combination_t *comb, const char *name, igraph_attribute_combination_type_t type, igraph_function_pointer_t func) { long int i, n = igraph_vector_ptr_size(&comb->list); /* Search, in case it is already there */ for (i = 0; i < n; i++) { igraph_attribute_combination_record_t *r = VECTOR(comb->list)[i]; const char *n = r->name; if ( (!name && !n) || (name && n && !strcmp(n, name)) ) { r->type = type; r->func = func; break; } } if (i == n) { /* This is a new attribute name */ igraph_attribute_combination_record_t *rec = igraph_Calloc(1, igraph_attribute_combination_record_t); if (!rec) { IGRAPH_ERROR("Cannot create attribute combination data", IGRAPH_ENOMEM); } if (!name) { rec->name = 0; } else { rec->name = strdup(name); } rec->type = type; rec->func = func; IGRAPH_CHECK(igraph_vector_ptr_push_back(&comb->list, rec)); } return 0; } int igraph_attribute_combination_remove(igraph_attribute_combination_t *comb, const char *name) { long int i, n = igraph_vector_ptr_size(&comb->list); /* Search, in case it is already there */ for (i = 0; i < n; i++) { igraph_attribute_combination_record_t *r = VECTOR(comb->list)[i]; const char *n = r->name; if ( (!name && !n) || (name && n && !strcmp(n, name)) ) { break; } } if (i != n) { igraph_attribute_combination_record_t *r = VECTOR(comb->list)[i]; if (r->name) { igraph_Free(r->name); } igraph_Free(r); igraph_vector_ptr_remove(&comb->list, i); } else { /* It is not there, we don't do anything */ } return 0; } int igraph_attribute_combination_query(const igraph_attribute_combination_t *comb, const char *name, igraph_attribute_combination_type_t *type, igraph_function_pointer_t *func) { long int i, def = -1, len = igraph_vector_ptr_size(&comb->list); for (i = 0; i < len; i++) { igraph_attribute_combination_record_t *rec = VECTOR(comb->list)[i]; const char *n = rec->name; if ( (!name && !n) || (name && n && !strcmp(n, name)) ) { *type = rec->type; *func = rec->func; return 0; } if (!n) { def = i; } } if (def == -1) { /* Did not find anything */ *type = IGRAPH_ATTRIBUTE_COMBINE_DEFAULT; *func = 0; } else { igraph_attribute_combination_record_t *rec = VECTOR(comb->list)[def]; *type = rec->type; *func = rec->func; } return 0; } int igraph_attribute_combination(igraph_attribute_combination_t *comb, ...) { va_list ap; IGRAPH_CHECK(igraph_attribute_combination_init(comb)); va_start(ap, comb); while (1) { igraph_function_pointer_t func = 0; igraph_attribute_combination_type_t type; const char *name; name = va_arg(ap, const char *); if (name == IGRAPH_NO_MORE_ATTRIBUTES) { break; } type = (igraph_attribute_combination_type_t)va_arg(ap, int); if (type == IGRAPH_ATTRIBUTE_COMBINE_FUNCTION) { #if defined(__GNUC__) func = va_arg(ap, void (*)(void)); #else func = va_arg(ap, void*); #endif } if (strlen(name) == 0) { name = 0; } IGRAPH_CHECK(igraph_attribute_combination_add(comb, name, type, func)); } va_end(ap); return 0; } python-igraph-0.8.0/vendor/source/igraph/src/pottsmodel_2.h0000644000076500000240000001616013614300625024166 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ /* The original version of this file was written by Jörg Reichardt This file was modified by Vincent Traag The original copyright notice follows here */ /*************************************************************************** pottsmodel.h - description ------------------- begin : Fri May 28 2004 copyright : (C) 2004 by email : ***************************************************************************/ /*************************************************************************** * * * This program is free software; you can redistribute it and/or modify * * it under the terms of the GNU General Public License as published by * * the Free Software Foundation; either version 2 of the License, or * * (at your option) any later version. * * * ***************************************************************************/ #ifndef POTTSMODEL_H #define POTTSMODEL_H #include "NetDataTypes.h" #include "igraph_types.h" #include "igraph_vector.h" #include "igraph_matrix.h" #define qmax 500 class PottsModel { private: // HugeArray neg_gammalookup; // HugeArray pos_gammalookup; DL_Indexed_List *new_spins; DL_Indexed_List *previous_spins; HugeArray*> correlation; network *net; unsigned int q; unsigned int operation_mode; FILE *Qfile, *Magfile; double Qmatrix[qmax + 1][qmax + 1]; double* Qa; double* weights; double total_degree_sum; unsigned long num_of_nodes; unsigned long num_of_links; unsigned long k_max; double energy; double acceptance; double *neighbours; public: PottsModel(network *net, unsigned int q, int norm_by_degree); ~PottsModel(); double* color_field; unsigned long assign_initial_conf(int spin); unsigned long initialize_lookup(double kT, double gamma); double initialize_Qmatrix(void); double calculate_Q(void); double calculate_genQ(double gamma); double FindStartTemp(double gamma, double prob, double ts); long HeatBathParallelLookupZeroTemp(double gamma, double prob, unsigned int max_sweeps); double HeatBathLookupZeroTemp(double gamma, double prob, unsigned int max_sweeps); long HeatBathParallelLookup(double gamma, double prob, double kT, unsigned int max_sweeps); double HeatBathLookup(double gamma, double prob, double kT, unsigned int max_sweeps); double GammaSweep(double gamma_start, double gamma_stop, double prob, unsigned int steps, bool non_parallel = true, int repetitions = 1); double GammaSweepZeroTemp(double gamma_start, double gamma_stop, double prob, unsigned int steps, bool non_parallel = true, int repetitions = 1); long WriteCorrelationMatrix(char *filename); double calculate_energy(double gamma); long WriteClusters(igraph_real_t *modularity, igraph_real_t *temperature, igraph_vector_t *csize, igraph_vector_t *membership, double kT, double gamma); long WriteSoftClusters(char *filename, double threshold); double Get_Energy(void) { return energy; } double FindCommunityFromStart(double gamma, double prob, char *nodename, igraph_vector_t *result, igraph_real_t *cohesion, igraph_real_t *adhesion, igraph_integer_t *inner_links, igraph_integer_t *outer_links); }; class PottsModelN { private: // HugeArray neg_gammalookup; // HugeArray pos_gammalookup; DL_Indexed_List *new_spins; DL_Indexed_List *previous_spins; HugeArray*> correlation; network *net; unsigned int q; //number of communities double m_p; //number of positive ties (or sum of degrees), this equals the number of edges only if it is undirected and each edge has a weight of 1 double m_n; //number of negative ties (or sum of degrees) unsigned int num_nodes; //number of nodes bool is_directed; bool is_init; double *degree_pos_in; //Postive indegree of the nodes (or sum of weights) double *degree_neg_in; //Negative indegree of the nodes (or sum of weights) double *degree_pos_out; //Postive outdegree of the nodes (or sum of weights) double *degree_neg_out; //Negative outdegree of the nodes (or sum of weights) double *degree_community_pos_in; //Positive sum of indegree for communities double *degree_community_neg_in; //Negative sum of indegree for communities double *degree_community_pos_out; //Positive sum of outegree for communities double *degree_community_neg_out; //Negative sum of outdegree for communities unsigned int *csize; //The number of nodes in each community unsigned int *spin; //The membership of each node double *neighbours; //Array of neighbours of a vertex in each community double *weights; //Weights of all possible transitions to another community public: PottsModelN(network *n, unsigned int num_communities, bool directed); ~PottsModelN(); void assign_initial_conf(bool init_spins); double FindStartTemp(double gamma, double lambda, double ts); double HeatBathLookup(double gamma, double lambda, double t, unsigned int max_sweeps); double HeatBathJoin(double gamma, double lambda); double HeatBathLookupZeroTemp(double gamma, double lambda, unsigned int max_sweeps); long WriteClusters(igraph_real_t *modularity, igraph_real_t *temperature, igraph_vector_t *community_size, igraph_vector_t *membership, igraph_matrix_t *adhesion, igraph_matrix_t *normalised_adhesion, igraph_real_t *polarization, double t, double d_p, double d_n, double gamma, double lambda); }; #endif python-igraph-0.8.0/vendor/source/igraph/src/sparsemat.c0000644000076500000240000026310413614300625023547 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "config.h" #include "cs/cs.h" #include "igraph_sparsemat.h" #include "igraph_error.h" #include "igraph_interface.h" #include "igraph_constructors.h" #include "igraph_memory.h" #include "igraph_vector_ptr.h" #include "igraph_attributes.h" #include /** * \section about_sparsemat About sparse matrices * * * The igraph_sparsemat_t data type stores sparse matrices, * i.e. matrices in which the majority of the elements are zero. * * * The data type is essentially a wrapper to some of the * functions in the CXSparse library, by Tim Davis, see * http://faculty.cse.tamu.edu/davis/suitesparse.html * * * * Matrices can be stored in two formats: triplet and * column-compressed. The triplet format is intended for sparse matrix * initialization, as it is easy to add new (non-zero) elements to * it. Most of the computations are done on sparse matrices in * column-compressed format, after the user has converted the triplet * matrix to column-compressed, via \ref igraph_sparsemat_compress(). * * * * Both formats are dynamic, in the sense that new elements can be * added to them, possibly resulting the allocation of more memory. * * * * Row and column indices follow the C convention and are zero-based. * * * * \example examples/simple/igraph_sparsemat.c * \example examples/simple/igraph_sparsemat2.c * \example examples/simple/igraph_sparsemat3.c * \example examples/simple/igraph_sparsemat4.c * \example examples/simple/igraph_sparsemat5.c * \example examples/simple/igraph_sparsemat6.c * \example examples/simple/igraph_sparsemat7.c * \example examples/simple/igraph_sparsemat8.c * */ /** * \function igraph_sparsemat_init * Initialize a sparse matrix, in triplet format * * This is the most common way to create a sparse matrix, together * with the \ref igraph_sparsemat_entry() function, which can be used to * add the non-zero elements one by one. Once done, the user can call * \ref igraph_sparsemat_compress() to convert the matrix to * column-compressed, to allow computations with it. * * The user must call \ref igraph_sparsemat_destroy() on * the matrix to deallocate the memory, once the matrix is no more * needed. * \param A Pointer to a not yet initialized sparse matrix. * \param rows The number of rows in the matrix. * \param cols The number of columns. * \param nzmax The maximum number of non-zero elements in the * matrix. It is not compulsory to get this right, but it is * useful for the allocation of the proper amount of memory. * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_init(igraph_sparsemat_t *A, int rows, int cols, int nzmax) { if (rows < 0) { IGRAPH_ERROR("Negative number of rows", IGRAPH_EINVAL); } if (cols < 0) { IGRAPH_ERROR("Negative number of columns", IGRAPH_EINVAL); } A->cs = cs_spalloc( rows, cols, nzmax, /*values=*/ 1, /*triplet=*/ 1); if (!A->cs) { IGRAPH_ERROR("Cannot allocate memory for sparse matrix", IGRAPH_ENOMEM); } return 0; } /** * \function igraph_sparsemat_copy * Copy a sparse matrix * * Create a sparse matrix object, by copying another one. The source * matrix can be either in triplet or column-compressed format. * * * Exactly the same amount of memory will be allocated to the * copy matrix, as it is currently for the original one. * \param to Pointer to an uninitialized sparse matrix, the copy will * be created here. * \param from The sparse matrix to copy. * \return Error code. * * Time complexity: O(n+nzmax), the number of columns plus the maximum * number of non-zero elements. */ int igraph_sparsemat_copy(igraph_sparsemat_t *to, const igraph_sparsemat_t *from) { int ne = from->cs->nz == -1 ? from->cs->n + 1 : from->cs->nzmax; to->cs = cs_spalloc(from->cs->m, from->cs->n, from->cs->nzmax, /*values=*/ 1, /*triplet=*/ igraph_sparsemat_is_triplet(from)); to->cs->nzmax = from->cs->nzmax; to->cs->m = from->cs->m; to->cs->n = from->cs->n; to->cs->nz = from->cs->nz; memcpy(to->cs->p, from->cs->p, sizeof(int) * (size_t) ne); memcpy(to->cs->i, from->cs->i, sizeof(int) * (size_t) (from->cs->nzmax)); memcpy(to->cs->x, from->cs->x, sizeof(double) * (size_t) (from->cs->nzmax)); return 0; } /** * \function igraph_sparsemat_destroy * Deallocate memory used by a sparse matrix * * One destroyed, the sparse matrix must be initialized again, before * calling any other operation on it. * \param A The sparse matrix to destroy. * * Time complexity: O(1). */ void igraph_sparsemat_destroy(igraph_sparsemat_t *A) { cs_spfree(A->cs); } /** * \function igraph_sparsemat_realloc * Allocate more (or less) memory for a sparse matrix * * Sparse matrices automatically allocate more memory, as needed. To * control memory allocation, the user can call this function, to * allocate memory for a given number of non-zero elements. * \param A The sparse matrix, it can be in triplet or * column-compressed format. * \param nzmax The new maximum number of non-zero elements. * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_realloc(igraph_sparsemat_t *A, int nzmax) { return !cs_sprealloc(A->cs, nzmax); } /** * \function igraph_sparsemat_nrow * Number of rows * * \param A The input matrix, in triplet or column-compressed format. * \return The number of rows in the \p A matrix. * * Time complexity: O(1). */ long int igraph_sparsemat_nrow(const igraph_sparsemat_t *A) { return A->cs->m; } /** * \function igraph_sparsemat_ncol * Number of columns. * * \param A The input matrix, in triplet or column-compressed format. * \return The number of columns in the \p A matrix. * * Time complexity: O(1). */ long int igraph_sparsemat_ncol(const igraph_sparsemat_t *A) { return A->cs->n; } /** * \function igraph_sparsemat_type * Type of a sparse matrix (triplet or column-compressed) * * Gives whether a sparse matrix is stored in the triplet format or in * column-compressed format. * \param A The input matrix. * \return Either \c IGRAPH_SPARSEMAT_CC or \c * IGRAPH_SPARSEMAT_TRIPLET. * * Time complexity: O(1). */ igraph_sparsemat_type_t igraph_sparsemat_type(const igraph_sparsemat_t *A) { return A->cs->nz < 0 ? IGRAPH_SPARSEMAT_CC : IGRAPH_SPARSEMAT_TRIPLET; } /** * \function igraph_sparsemat_is_triplet * Is this sparse matrix in triplet format? * * Decides whether a sparse matrix is in triplet format. * \param A The input matrix. * \return One if the input matrix is in triplet format, zero * otherwise. * * Time complexity: O(1). */ igraph_bool_t igraph_sparsemat_is_triplet(const igraph_sparsemat_t *A) { return A->cs->nz >= 0; } /** * \function igraph_sparsemat_is_cc * Is this sparse matrix in column-compressed format? * * Decides whether a sparse matrix is in column-compressed format. * \param A The input matrix. * \return One if the input matrix is in column-compressed format, zero * otherwise. * * Time complexity: O(1). */ igraph_bool_t igraph_sparsemat_is_cc(const igraph_sparsemat_t *A) { return A->cs->nz < 0; } /** * \function igraph_sparsemat_permute * Permute the rows and columns of a sparse matrix * * \param A The input matrix, it must be in column-compressed format. * \param p Integer vector, giving the permutation of the rows. * \param q Integer vector, the permutation of the columns. * \param res Pointer to an uninitialized sparse matrix, the result is * stored here. * \return Error code. * * Time complexity: O(m+n+nz), the number of rows plus the number of * columns plus the number of non-zero elements in the matrix. */ int igraph_sparsemat_permute(const igraph_sparsemat_t *A, const igraph_vector_int_t *p, const igraph_vector_int_t *q, igraph_sparsemat_t *res) { long int nrow = A->cs->m, ncol = A->cs->n; igraph_vector_int_t pinv; long int i; if (nrow != igraph_vector_int_size(p)) { IGRAPH_ERROR("Invalid row permutation length", IGRAPH_FAILURE); } if (ncol != igraph_vector_int_size(q)) { IGRAPH_ERROR("Invalid column permutation length", IGRAPH_FAILURE); } /* We invert the permutation by hand */ IGRAPH_CHECK(igraph_vector_int_init(&pinv, nrow)); IGRAPH_FINALLY(igraph_vector_int_destroy, &pinv); for (i = 0; i < nrow; i++) { VECTOR(pinv)[ VECTOR(*p)[i] ] = (int) i; } /* And call the permutation routine */ if (! (res->cs = cs_permute(A->cs, VECTOR(pinv), VECTOR(*q), /*values=*/ 1))) { IGRAPH_ERROR("Cannot index sparse matrix", IGRAPH_FAILURE); } igraph_vector_int_destroy(&pinv); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_i_sparsemat_index_rows(const igraph_sparsemat_t *A, const igraph_vector_int_t *p, igraph_sparsemat_t *res, igraph_real_t *constres) { igraph_sparsemat_t II, II2; long int nrow = A->cs->m; long int idx_rows = igraph_vector_int_size(p); long int k; /* Create index matrix */ IGRAPH_CHECK(igraph_sparsemat_init(&II2, (int) idx_rows, (int) nrow, (int) idx_rows)); IGRAPH_FINALLY(igraph_sparsemat_destroy, &II2); for (k = 0; k < idx_rows; k++) { igraph_sparsemat_entry(&II2, (int) k, VECTOR(*p)[k], 1.0); } IGRAPH_CHECK(igraph_sparsemat_compress(&II2, &II)); igraph_sparsemat_destroy(&II2); IGRAPH_FINALLY_CLEAN(1); IGRAPH_FINALLY(igraph_sparsemat_destroy, &II); /* Multiply */ IGRAPH_CHECK(igraph_sparsemat_multiply(&II, A, res)); igraph_sparsemat_destroy(&II); IGRAPH_FINALLY_CLEAN(1); if (constres) { if (res->cs->p[1] != 0) { *constres = res->cs->x[0]; } else { *constres = 0.0; } } return 0; } int igraph_i_sparsemat_index_cols(const igraph_sparsemat_t *A, const igraph_vector_int_t *q, igraph_sparsemat_t *res, igraph_real_t *constres) { igraph_sparsemat_t JJ, JJ2; long int ncol = A->cs->n; long int idx_cols = igraph_vector_int_size(q); long int k; /* Create index matrix */ IGRAPH_CHECK(igraph_sparsemat_init(&JJ2, (int) ncol, (int) idx_cols, (int) idx_cols)); IGRAPH_FINALLY(igraph_sparsemat_destroy, &JJ2); for (k = 0; k < idx_cols; k++) { igraph_sparsemat_entry(&JJ2, VECTOR(*q)[k], (int) k, 1.0); } IGRAPH_CHECK(igraph_sparsemat_compress(&JJ2, &JJ)); igraph_sparsemat_destroy(&JJ2); IGRAPH_FINALLY_CLEAN(1); IGRAPH_FINALLY(igraph_sparsemat_destroy, &JJ); /* Multiply */ IGRAPH_CHECK(igraph_sparsemat_multiply(A, &JJ, res)); igraph_sparsemat_destroy(&JJ); IGRAPH_FINALLY_CLEAN(1); if (constres) { if (res->cs->p [1] != 0) { *constres = res->cs->x [0]; } else { *constres = 0.0; } } return 0; } /** * \function igraph_sparsemat_index * Index a sparse matrix, extract a submatrix, or a single element * * This function serves two purposes. First, it can extract * submatrices from a sparse matrix. Second, as a special case, it can * extract a single element from a sparse matrix. * \param A The input matrix, it must be in column-compressed format. * \param p An integer vector, or a null pointer. The selected row * index or indices. A null pointer selects all rows. * \param q An integer vector, or a null pointer. The selected column * index or indices. A null pointer selects all columns. * \param res Pointer to an uninitialized sparse matrix, or a null * pointer. If not a null pointer, then the selected submatrix is * stored here. * \param constres Pointer to a real variable or a null pointer. If * not a null pointer, then the first non-zero element in the * selected submatrix is stored here, if there is one. Otherwise * zero is stored here. This behavior is handy if one * wants to select a single entry from the matrix. * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_index(const igraph_sparsemat_t *A, const igraph_vector_int_t *p, const igraph_vector_int_t *q, igraph_sparsemat_t *res, igraph_real_t *constres) { igraph_sparsemat_t II, JJ, II2, JJ2, tmp; long int nrow = A->cs->m; long int ncol = A->cs->n; long int idx_rows = p ? igraph_vector_int_size(p) : -1; long int idx_cols = q ? igraph_vector_int_size(q) : -1; long int k; igraph_sparsemat_t *myres = res, mres; if (!p && !q) { IGRAPH_ERROR("No index vectors", IGRAPH_EINVAL); } if (!res && (idx_rows != 1 || idx_cols != 1)) { IGRAPH_ERROR("Sparse matrix indexing: must give `res' if not a " "single element is selected", IGRAPH_EINVAL); } if (!q) { return igraph_i_sparsemat_index_rows(A, p, res, constres); } if (!p) { return igraph_i_sparsemat_index_cols(A, q, res, constres); } if (!res) { myres = &mres; } /* Create first index matrix */ IGRAPH_CHECK(igraph_sparsemat_init(&II2, (int) idx_rows, (int) nrow, (int) idx_rows)); IGRAPH_FINALLY(igraph_sparsemat_destroy, &II2); for (k = 0; k < idx_rows; k++) { igraph_sparsemat_entry(&II2, (int) k, VECTOR(*p)[k], 1.0); } IGRAPH_CHECK(igraph_sparsemat_compress(&II2, &II)); igraph_sparsemat_destroy(&II2); IGRAPH_FINALLY_CLEAN(1); IGRAPH_FINALLY(igraph_sparsemat_destroy, &II); /* Create second index matrix */ IGRAPH_CHECK(igraph_sparsemat_init(&JJ2, (int) ncol, (int) idx_cols, (int) idx_cols)); IGRAPH_FINALLY(igraph_sparsemat_destroy, &JJ2); for (k = 0; k < idx_cols; k++) { igraph_sparsemat_entry(&JJ2, VECTOR(*q)[k], (int) k, 1.0); } IGRAPH_CHECK(igraph_sparsemat_compress(&JJ2, &JJ)); igraph_sparsemat_destroy(&JJ2); IGRAPH_FINALLY_CLEAN(1); IGRAPH_FINALLY(igraph_sparsemat_destroy, &JJ); /* Multiply */ IGRAPH_CHECK(igraph_sparsemat_multiply(&II, A, &tmp)); igraph_sparsemat_destroy(&II); IGRAPH_FINALLY_CLEAN(1); IGRAPH_FINALLY(igraph_sparsemat_destroy, &tmp); IGRAPH_CHECK(igraph_sparsemat_multiply(&tmp, &JJ, myres)); igraph_sparsemat_destroy(&tmp); igraph_sparsemat_destroy(&JJ); IGRAPH_FINALLY_CLEAN(2); if (constres) { if (myres->cs->p [1] != 0) { *constres = myres->cs->x [0]; } else { *constres = 0.0; } } if (!res) { igraph_sparsemat_destroy(myres); } return 0; } /** * \function igraph_sparsemat_entry * Add an element to a sparse matrix * * This function can be used to add the entries to a sparse matrix, * after initializing it with \ref igraph_sparsemat_init(). * \param A The input matrix, it must be in triplet format. * \param row The row index of the entry to add. * \param col The column index of the entry to add. * \param elem The value of the entry. * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_entry(igraph_sparsemat_t *A, int row, int col, igraph_real_t elem) { if (!cs_entry(A->cs, row, col, elem)) { IGRAPH_ERROR("Cannot add entry to sparse matrix", IGRAPH_FAILURE); } return 0; } /** * \function igraph_sparsemat_compress * Compress a sparse matrix, i.e. convert it to column-compress format * * Almost all sparse matrix operations require that the matrix is in * column-compressed format. * \param A The input matrix, it must be in triplet format. * \param res Pointer to an uninitialized sparse matrix object, the * compressed version of \p A is stored here. * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_compress(const igraph_sparsemat_t *A, igraph_sparsemat_t *res) { if (! (res->cs = cs_compress(A->cs)) ) { IGRAPH_ERROR("Cannot compress sparse matrix", IGRAPH_FAILURE); } return 0; } /** * \function igraph_sparsemat_transpose * Transpose a sparse matrix * * \param A The input matrix, column-compressed or triple format. * \param res Pointer to an uninitialized sparse matrix, the result is * stored here. * \param values If this is non-zero, the matrix transpose is * calculated the normal way. If it is zero, then only the pattern * of the input matrix is stored in the result, the values are not. * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_transpose(const igraph_sparsemat_t *A, igraph_sparsemat_t *res, int values) { if (A->cs->nz < 0) { /* column-compressed */ if (! (res->cs = cs_transpose(A->cs, values)) ) { IGRAPH_ERROR("Cannot transpose sparse matrix", IGRAPH_FAILURE); } } else { /* triplets */ int *tmp; IGRAPH_CHECK(igraph_sparsemat_copy(res, A)); tmp = res->cs->p; res->cs->p = res->cs->i; res->cs->i = tmp; } return 0; } igraph_bool_t igraph_i_sparsemat_is_symmetric_cc(const igraph_sparsemat_t *A) { igraph_sparsemat_t t, tt; igraph_bool_t res; int nz; IGRAPH_CHECK(igraph_sparsemat_transpose(A, &t, /*values=*/ 1)); IGRAPH_FINALLY(igraph_sparsemat_destroy, &t); IGRAPH_CHECK(igraph_sparsemat_dupl(&t)); IGRAPH_CHECK(igraph_sparsemat_transpose(&t, &tt, /*values=*/ 1)); igraph_sparsemat_destroy(&t); IGRAPH_FINALLY_CLEAN(1); IGRAPH_FINALLY(igraph_sparsemat_destroy, &tt); IGRAPH_CHECK(igraph_sparsemat_transpose(&tt, &t, /*values=*/ 1)); IGRAPH_FINALLY(igraph_sparsemat_destroy, &t); nz = t.cs->p[t.cs->n]; res = memcmp(t.cs->i, tt.cs->i, sizeof(int) * (size_t) nz) == 0; res = res && memcmp(t.cs->p, tt.cs->p, sizeof(int) * (size_t)(t.cs->n + 1)) == 0; res = res && memcmp(t.cs->x, tt.cs->x, sizeof(igraph_real_t) * (size_t)nz) == 0; igraph_sparsemat_destroy(&t); igraph_sparsemat_destroy(&tt); IGRAPH_FINALLY_CLEAN(2); return res; } igraph_bool_t igraph_i_sparsemat_is_symmetric_triplet(const igraph_sparsemat_t *A) { igraph_sparsemat_t tmp; igraph_bool_t res; IGRAPH_CHECK(igraph_sparsemat_compress(A, &tmp)); IGRAPH_FINALLY(igraph_sparsemat_destroy, &tmp); res = igraph_i_sparsemat_is_symmetric_cc(&tmp); igraph_sparsemat_destroy(&tmp); IGRAPH_FINALLY_CLEAN(1); return res; } igraph_bool_t igraph_sparsemat_is_symmetric(const igraph_sparsemat_t *A) { if (A->cs->m != A->cs->n) { return 0; } if (A->cs->nz < 0) { return igraph_i_sparsemat_is_symmetric_cc(A); } else { return igraph_i_sparsemat_is_symmetric_triplet(A); } } /** * \function igraph_sparsemat_dupl * Remove duplicate elements from a sparse matrix * * It is possible that a column-compressed sparse matrix stores a * single matrix entry in multiple pieces. The entry is then the sum * of all its pieces. (Some functions create matrices like this.) This * function eliminates the multiple pieces. * \param A The input matrix, in column-compressed format. * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_dupl(igraph_sparsemat_t *A) { if (!cs_dupl(A->cs)) { IGRAPH_ERROR("Cannot remove duplicates from sparse matrix", IGRAPH_FAILURE); } return 0; } /** * \function igraph_sparsemat_fkeep * Filter the elements of a sparse matrix * * This function can be used to filter the (non-zero) elements of a * sparse matrix. For all entries, it calls the supplied function and * depending on the return values either keeps, or deleted the element * from the matrix. * \param A The input matrix, in column-compressed format. * \param fkeep The filter function. It must take four arguments: the * first is an \c int, the row index of the entry, the second is * another \c int, the column index. The third is \c igraph_real_t, * the value of the entry. The fourth element is a \c void pointer, * the \p other argument is passed here. The function must return * an \c int. If this is zero, then the entry is deleted, otherwise * it is kept. * \param other A \c void pointer that is passed to the filtering * function. * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_fkeep(igraph_sparsemat_t *A, int (*fkeep)(int, int, igraph_real_t, void*), void *other) { if (!cs_fkeep(A->cs, fkeep, other)) { IGRAPH_ERROR("Cannot filter sparse matrix", IGRAPH_FAILURE); } return 0; } /** * \function igraph_sparsemat_dropzeros * Drop the zero elements from a sparse matrix * * As a result of matrix operations, some of the entries in a sparse * matrix might be zero. This function removes these entries. * \param A The input matrix, it must be in column-compressed format. * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_dropzeros(igraph_sparsemat_t *A) { if (!cs_dropzeros(A->cs)) { IGRAPH_ERROR("Cannot drop zeros from sparse matrix", IGRAPH_FAILURE); } return 0; } /** * \function igraph_sparsemat_droptol * Drop the almost zero elements of a sparse matrix * * This function is similar to \ref igraph_sparsemat_dropzeros(), but it * also drops entries that are closer to zero than the given tolerance * threshold. * \param A The input matrix, it must be in column-compressed format. * \param tol Real number, giving the tolerance threshold. * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_droptol(igraph_sparsemat_t *A, igraph_real_t tol) { if (!cs_droptol(A->cs, tol)) { IGRAPH_ERROR("Cannot drop (almost) zeros from sparse matrix", IGRAPH_FAILURE); } return 0; } /** * \function igraph_sparsemat_multiply * Matrix multiplication * * Multiplies two sparse matrices. * \param A The first input matrix (left hand side), in * column-compressed format. * \param B The second input matrix (right hand side), in * column-compressed format. * \param res Pointer to an uninitialized sparse matrix, the result is * stored here. * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_multiply(const igraph_sparsemat_t *A, const igraph_sparsemat_t *B, igraph_sparsemat_t *res) { if (! (res->cs = cs_multiply(A->cs, B->cs))) { IGRAPH_ERROR("Cannot multiply matrices", IGRAPH_FAILURE); } return 0; } /** * \function igraph_sparsemat_add * Sum of two sparse matrices * * \param A The first input matrix, in column-compressed format. * \param B The second input matrix, in column-compressed format. * \param alpha Real scalar, \p A is multiplied by \p alpha before the * addition. * \param beta Real scalar, \p B is multiplied by \p beta before the * addition. * \param res Pointer to an uninitialized sparse matrix, the result * is stored here. * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_add(const igraph_sparsemat_t *A, const igraph_sparsemat_t *B, igraph_real_t alpha, igraph_real_t beta, igraph_sparsemat_t *res) { if (! (res->cs = cs_add(A->cs, B->cs, alpha, beta))) { IGRAPH_ERROR("Cannot add matrices", IGRAPH_FAILURE); } return 0; } /** * \function igraph_sparsemat_gaxpy * Matrix-vector product, added to another vector. * * \param A The input matrix, in column-compressed format. * \param x The input vector, its size must match the number of * columns in \p A. * \param res This vector is added to the matrix-vector product * and it is overwritten by the result. * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_gaxpy(const igraph_sparsemat_t *A, const igraph_vector_t *x, igraph_vector_t *res) { if (A->cs->n != igraph_vector_size(x) || A->cs->m != igraph_vector_size(res)) { IGRAPH_ERROR("Invalid matrix/vector size for multiplication", IGRAPH_EINVAL); } if (! (cs_gaxpy(A->cs, VECTOR(*x), VECTOR(*res)))) { IGRAPH_ERROR("Cannot perform sparse matrix vector multiplication", IGRAPH_FAILURE); } return 0; } /** * \function igraph_sparsemat_lsolve * Solve a lower-triangular linear system * * Solve the Lx=b linear equation system, where the L coefficient * matrix is square and lower-triangular, with a zero-free diagonal. * \param L The input matrix, in column-compressed format. * \param b The right hand side of the linear system. * \param res An initialized vector, the result is stored here. * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_lsolve(const igraph_sparsemat_t *L, const igraph_vector_t *b, igraph_vector_t *res) { if (L->cs->m != L->cs->n) { IGRAPH_ERROR("Cannot perform lower triangular solve", IGRAPH_NONSQUARE); } if (res != b) { IGRAPH_CHECK(igraph_vector_update(res, b)); } if (! cs_lsolve(L->cs, VECTOR(*res))) { IGRAPH_ERROR("Cannot perform lower triangular solve", IGRAPH_FAILURE); } return 0; } /** * \function igraph_sparsemat_ltsolve * Solve an upper-triangular linear system * * Solve the L'x=b linear equation system, where the L * matrix is square and lower-triangular, with a zero-free diagonal. * \param L The input matrix, in column-compressed format. * \param b The right hand side of the linear system. * \param res An initialized vector, the result is stored here. * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_ltsolve(const igraph_sparsemat_t *L, const igraph_vector_t *b, igraph_vector_t *res) { if (L->cs->m != L->cs->n) { IGRAPH_ERROR("Cannot perform transposed lower triangular solve", IGRAPH_NONSQUARE); } if (res != b) { IGRAPH_CHECK(igraph_vector_update(res, b)); } if (!cs_ltsolve(L->cs, VECTOR(*res))) { IGRAPH_ERROR("Cannot perform lower triangular solve", IGRAPH_FAILURE); } return 0; } /** * \function igraph_sparsemat_usolve * Solve an upper-triangular linear system * * Solves the Ux=b upper triangular system. * \param U The input matrix, in column-compressed format. * \param b The right hand side of the linear system. * \param res An initialized vector, the result is stored here. * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_usolve(const igraph_sparsemat_t *U, const igraph_vector_t *b, igraph_vector_t *res) { if (U->cs->m != U->cs->n) { IGRAPH_ERROR("Cannot perform upper triangular solve", IGRAPH_NONSQUARE); } if (res != b) { IGRAPH_CHECK(igraph_vector_update(res, b)); } if (! cs_usolve(U->cs, VECTOR(*res))) { IGRAPH_ERROR("Cannot perform upper triangular solve", IGRAPH_FAILURE); } return 0; } /** * \function igraph_sparsemat_utsolve * Solve a lower-triangular linear system * * This is the same as \ref igraph_sparsemat_usolve(), but U'x=b is * solved, where the apostrophe denotes the transpose. * \param U The input matrix, in column-compressed format. * \param b The right hand side of the linear system. * \param res An initialized vector, the result is stored here. * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_utsolve(const igraph_sparsemat_t *U, const igraph_vector_t *b, igraph_vector_t *res) { if (U->cs->m != U->cs->n) { IGRAPH_ERROR("Cannot perform transposed upper triangular solve", IGRAPH_NONSQUARE); } if (res != b) { IGRAPH_CHECK(igraph_vector_update(res, b)); } if (!cs_utsolve(U->cs, VECTOR(*res))) { IGRAPH_ERROR("Cannot perform transposed upper triangular solve", IGRAPH_FAILURE); } return 0; } /** * \function igraph_sparsemat_cholsol * Solve a symmetric linear system via Cholesky decomposition * * Solve Ax=b, where A is a symmetric positive definite matrix. * \param A The input matrix, in column-compressed format. * \param v The right hand side. * \param res An initialized vector, the result is stored here. * \param order An integer giving the ordering method to use for the * factorization. Zero is the natural ordering; if it is one, then * the fill-reducing minimum-degree ordering of A+A' is used. * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_cholsol(const igraph_sparsemat_t *A, const igraph_vector_t *b, igraph_vector_t *res, int order) { if (A->cs->m != A->cs->n) { IGRAPH_ERROR("Cannot perform sparse symmetric solve", IGRAPH_NONSQUARE); } if (res != b) { IGRAPH_CHECK(igraph_vector_update(res, b)); } if (! cs_cholsol(order, A->cs, VECTOR(*res))) { IGRAPH_ERROR("Cannot perform sparse symmetric solve", IGRAPH_FAILURE); } return 0; } /** * \function igraph_sparsemat_lusol * Solve a linear system via LU decomposition * * Solve Ax=b, via LU factorization of A. * \param A The input matrix, in column-compressed format. * \param b The right hand side of the equation. * \param res An initialized vector, the result is stored here. * \param order The ordering method to use, zero means the natural * ordering, one means the fill-reducing minimum-degree ordering of * A+A', two means the ordering of A'*A, after removing the dense * rows from A. Three means the ordering of A'*A. * \param tol Real number, the tolerance limit to use for the numeric * LU factorization. * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_lusol(const igraph_sparsemat_t *A, const igraph_vector_t *b, igraph_vector_t *res, int order, igraph_real_t tol) { if (A->cs->m != A->cs->n) { IGRAPH_ERROR("Cannot perform LU solve", IGRAPH_NONSQUARE); } if (res != b) { IGRAPH_CHECK(igraph_vector_update(res, b)); } if (! cs_lusol(order, A->cs, VECTOR(*res), tol)) { IGRAPH_ERROR("Cannot perform LU solve", IGRAPH_FAILURE); } return 0; } int igraph_i_sparsemat_cc(igraph_t *graph, const igraph_sparsemat_t *A, igraph_bool_t directed) { igraph_vector_t edges; long int no_of_nodes = A->cs->m; long int no_of_edges = A->cs->p[A->cs->n]; int *p = A->cs->p; int *i = A->cs->i; long int from = 0; long int to = 0; long int e = 0; if (no_of_nodes != A->cs->n) { IGRAPH_ERROR("Cannot create graph object", IGRAPH_NONSQUARE); } IGRAPH_VECTOR_INIT_FINALLY(&edges, no_of_edges * 2); while (*p < no_of_edges) { while (to < * (p + 1)) { if (directed || from >= *i) { VECTOR(edges)[e++] = from; VECTOR(edges)[e++] = (*i); } to++; i++; } from++; p++; } igraph_vector_resize(&edges, e); IGRAPH_CHECK(igraph_create(graph, &edges, (igraph_integer_t) no_of_nodes, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_i_sparsemat_triplet(igraph_t *graph, const igraph_sparsemat_t *A, igraph_bool_t directed) { igraph_vector_t edges; long int no_of_nodes = A->cs->m; long int no_of_edges = A->cs->nz; int *i = A->cs->p; int *j = A->cs->i; long int e; if (no_of_nodes != A->cs->n) { IGRAPH_ERROR("Cannot create graph object", IGRAPH_NONSQUARE); } IGRAPH_VECTOR_INIT_FINALLY(&edges, no_of_edges * 2); for (e = 0; e < 2 * no_of_edges; i++, j++) { if (directed || *i >= *j) { VECTOR(edges)[e++] = (*i); VECTOR(edges)[e++] = (*j); } } igraph_vector_resize(&edges, e); IGRAPH_CHECK(igraph_create(graph, &edges, (igraph_integer_t) no_of_nodes, directed)); igraph_vector_destroy(&edges); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_sparsemat * Create an igraph graph from a sparse matrix * * One edge is created for each non-zero entry in the matrix. If you * have a symmetric matrix, and want to create an undirected graph, * then delete the entries in the upper diagonal first, or call \ref * igraph_simplify() on the result graph to eliminate the multiple * edges. * \param graph Pointer to an uninitialized igraph_t object, the * graphs is stored here. * \param A The input matrix, in triplet or column-compressed format. * \param directed Boolean scalar, whether to create a directed * graph. * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat(igraph_t *graph, const igraph_sparsemat_t *A, igraph_bool_t directed) { if (A->cs->nz < 0) { return (igraph_i_sparsemat_cc(graph, A, directed)); } else { return (igraph_i_sparsemat_triplet(graph, A, directed)); } } int igraph_i_weighted_sparsemat_cc(const igraph_sparsemat_t *A, igraph_bool_t directed, const char *attr, igraph_bool_t loops, igraph_vector_t *edges, igraph_vector_t *weights) { long int no_of_edges = A->cs->p[A->cs->n]; int *p = A->cs->p; int *i = A->cs->i; igraph_real_t *x = A->cs->x; long int from = 0; long int to = 0; long int e = 0, w = 0; IGRAPH_UNUSED(attr); igraph_vector_resize(edges, no_of_edges * 2); igraph_vector_resize(weights, no_of_edges); while (*p < no_of_edges) { while (to < * (p + 1)) { if ( (loops || from != *i) && (directed || from >= *i) && *x != 0) { VECTOR(*edges)[e++] = (*i); VECTOR(*edges)[e++] = from; VECTOR(*weights)[w++] = (*x); } to++; i++; x++; } from++; p++; } igraph_vector_resize(edges, e); igraph_vector_resize(weights, w); return 0; } int igraph_i_weighted_sparsemat_triplet(const igraph_sparsemat_t *A, igraph_bool_t directed, const char *attr, igraph_bool_t loops, igraph_vector_t *edges, igraph_vector_t *weights) { IGRAPH_UNUSED(A); IGRAPH_UNUSED(directed); IGRAPH_UNUSED(attr); IGRAPH_UNUSED(loops); IGRAPH_UNUSED(edges); IGRAPH_UNUSED(weights); /* TODO */ IGRAPH_ERROR("Triplet matrices are not implemented", IGRAPH_UNIMPLEMENTED); return 0; } int igraph_weighted_sparsemat(igraph_t *graph, const igraph_sparsemat_t *A, igraph_bool_t directed, const char *attr, igraph_bool_t loops) { igraph_vector_t edges, weights; int pot_edges = A->cs->nz < 0 ? A->cs->p[A->cs->n] : A->cs->nz; const char* default_attr = "weight"; igraph_vector_ptr_t attr_vec; igraph_attribute_record_t attr_rec; long int no_of_nodes = A->cs->m; if (no_of_nodes != A->cs->n) { IGRAPH_ERROR("Cannot create graph object", IGRAPH_NONSQUARE); } IGRAPH_VECTOR_INIT_FINALLY(&edges, pot_edges * 2); IGRAPH_VECTOR_INIT_FINALLY(&weights, pot_edges); IGRAPH_VECTOR_PTR_INIT_FINALLY(&attr_vec, 1); if (A->cs->nz < 0) { IGRAPH_CHECK(igraph_i_weighted_sparsemat_cc(A, directed, attr, loops, &edges, &weights)); } else { IGRAPH_CHECK(igraph_i_weighted_sparsemat_triplet(A, directed, attr, loops, &edges, &weights)); } /* Prepare attribute record */ attr_rec.name = attr ? attr : default_attr; attr_rec.type = IGRAPH_ATTRIBUTE_NUMERIC; attr_rec.value = &weights; VECTOR(attr_vec)[0] = &attr_rec; /* Create graph */ IGRAPH_CHECK(igraph_empty(graph, (igraph_integer_t) no_of_nodes, directed)); IGRAPH_FINALLY(igraph_destroy, graph); if (igraph_vector_size(&edges) > 0) { IGRAPH_CHECK(igraph_add_edges(graph, &edges, &attr_vec)); } IGRAPH_FINALLY_CLEAN(1); /* Cleanup */ igraph_vector_destroy(&edges); igraph_vector_destroy(&weights); igraph_vector_ptr_destroy(&attr_vec); IGRAPH_FINALLY_CLEAN(3); return 0; } /** * \function igraph_get_sparsemat * Convert an igraph graph to a sparse matrix * * If the graph is undirected, then a symmetric matrix is created. * \param graph The input graph. * \param res Pointer to an uninitialized sparse matrix. The result * will be stored here. * \return Error code. * * Time complexity: TODO. */ int igraph_get_sparsemat(const igraph_t *graph, igraph_sparsemat_t *res) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_bool_t directed = igraph_is_directed(graph); long int nzmax = directed ? no_of_edges : no_of_edges * 2; long int i; IGRAPH_CHECK(igraph_sparsemat_init(res, (igraph_integer_t) no_of_nodes, (igraph_integer_t) no_of_nodes, (igraph_integer_t) nzmax)); for (i = 0; i < no_of_edges; i++) { long int from = IGRAPH_FROM(graph, i); long int to = IGRAPH_TO(graph, i); IGRAPH_CHECK(igraph_sparsemat_entry(res, (int) from, (int) to, 1.0)); if (!directed && from != to) { IGRAPH_CHECK(igraph_sparsemat_entry(res, (int) to, (int) from, 1.0)); } } return 0; } #define CHECK(x) if ((x)<0) { IGRAPH_ERROR("Cannot write to file", IGRAPH_EFILE); } /** * \function igraph_sparsemat_print * Print a sparse matrix to a file * * Only the non-zero entries are printed. This function serves more as * a debugging utility, as currently there is no function that could * read back the printed matrix from the file. * \param A The input matrix, triplet or column-compressed format. * \param outstream The stream to print it to. * \return Error code. * * Time complexity: O(nz) for triplet matrices, O(n+nz) for * column-compressed matrices. nz is the number of non-zero elements, * n is the number columns in the matrix. */ int igraph_sparsemat_print(const igraph_sparsemat_t *A, FILE *outstream) { if (A->cs->nz < 0) { /* CC */ int j, p; for (j = 0; j < A->cs->n; j++) { CHECK(fprintf(outstream, "col %i: locations %i to %i\n", j, A->cs->p[j], A->cs->p[j + 1] - 1)); for (p = A->cs->p[j]; p < A->cs->p[j + 1]; p++) { CHECK(fprintf(outstream, "%i : %g\n", A->cs->i[p], A->cs->x[p])); } } } else { /* Triplet */ int p; for (p = 0; p < A->cs->nz; p++) { CHECK(fprintf(outstream, "%i %i : %g\n", A->cs->i[p], A->cs->p[p], A->cs->x[p])); } } return 0; } #undef CHECK int igraph_i_sparsemat_eye_triplet(igraph_sparsemat_t *A, int n, int nzmax, igraph_real_t value) { long int i; IGRAPH_CHECK(igraph_sparsemat_init(A, n, n, nzmax)); for (i = 0; i < n; i++) { igraph_sparsemat_entry(A, (int) i, (int) i, value); } return 0; } int igraph_i_sparsemat_eye_cc(igraph_sparsemat_t *A, int n, igraph_real_t value) { long int i; if (! (A->cs = cs_spalloc(n, n, n, /*values=*/ 1, /*triplet=*/ 0)) ) { IGRAPH_ERROR("Cannot create eye sparse matrix", IGRAPH_FAILURE); } for (i = 0; i < n; i++) { A->cs->p [i] = (int) i; A->cs->i [i] = (int) i; A->cs->x [i] = value; } A->cs->p [n] = n; return 0; } /** * \function igraph_sparsemat_eye * Create a sparse identity matrix * * \param A An uninitialized sparse matrix, the result is stored * here. * \param n The number of rows and number of columns in the matrix. * \param nzmax The maximum number of non-zero elements, this * essentially gives the amount of memory that will be allocated for * matrix elements. * \param value The value to store in the diagonal. * \param compress Whether to create a column-compressed matrix. If * false, then a triplet matrix is created. * \return Error code. * * Time complexity: O(n). */ int igraph_sparsemat_eye(igraph_sparsemat_t *A, int n, int nzmax, igraph_real_t value, igraph_bool_t compress) { if (compress) { return (igraph_i_sparsemat_eye_cc(A, n, value)); } else { return (igraph_i_sparsemat_eye_triplet(A, n, nzmax, value)); } } int igraph_i_sparsemat_diag_triplet(igraph_sparsemat_t *A, int nzmax, const igraph_vector_t *values) { int i, n = (int) igraph_vector_size(values); IGRAPH_CHECK(igraph_sparsemat_init(A, n, n, nzmax)); for (i = 0; i < n; i++) { igraph_sparsemat_entry(A, i, i, VECTOR(*values)[i]); } return 0; } int igraph_i_sparsemat_diag_cc(igraph_sparsemat_t *A, const igraph_vector_t *values) { int i, n = (int) igraph_vector_size(values); if (! (A->cs = cs_spalloc(n, n, n, /*values=*/ 1, /*triplet=*/ 0)) ) { IGRAPH_ERROR("Cannot create eye sparse matrix", IGRAPH_FAILURE); } for (i = 0; i < n; i++) { A->cs->p [i] = i; A->cs->i [i] = i; A->cs->x [i] = VECTOR(*values)[i]; } A->cs->p [n] = n; return 0; } /** * \function igraph_sparsemat_diag * Create a sparse diagonal matrix * * \param A An uninitialized sparse matrix, the result is stored * here. * \param nzmax The maximum number of non-zero elements, this * essentially gives the amount of memory that will be allocated for * matrix elements. * \param values The values to store in the diagonal, the size of the * matrix defined by the length of this vector. * \param compress Whether to create a column-compressed matrix. If * false, then a triplet matrix is created. * \return Error code. * * Time complexity: O(n), the length of the diagonal vector. */ int igraph_sparsemat_diag(igraph_sparsemat_t *A, int nzmax, const igraph_vector_t *values, igraph_bool_t compress) { if (compress) { return (igraph_i_sparsemat_diag_cc(A, values)); } else { return (igraph_i_sparsemat_diag_triplet(A, nzmax, values)); } } int igraph_i_sparsemat_arpack_multiply(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_sparsemat_t *A = extra; igraph_vector_t vto, vfrom; igraph_vector_view(&vto, to, n); igraph_vector_view(&vfrom, from, n); igraph_vector_null(&vto); IGRAPH_CHECK(igraph_sparsemat_gaxpy(A, &vfrom, &vto)); return 0; } typedef struct igraph_i_sparsemat_arpack_rssolve_data_t { igraph_sparsemat_symbolic_t *dis; igraph_sparsemat_numeric_t *din; igraph_real_t tol; igraph_sparsemat_solve_t method; } igraph_i_sparsemat_arpack_rssolve_data_t; int igraph_i_sparsemat_arpack_solve(igraph_real_t *to, const igraph_real_t *from, int n, void *extra) { igraph_i_sparsemat_arpack_rssolve_data_t *data = extra; igraph_vector_t vfrom, vto; igraph_vector_view(&vfrom, from, n); igraph_vector_view(&vto, to, n); if (data->method == IGRAPH_SPARSEMAT_SOLVE_LU) { IGRAPH_CHECK(igraph_sparsemat_luresol(data->dis, data->din, &vfrom, &vto)); } else if (data->method == IGRAPH_SPARSEMAT_SOLVE_QR) { IGRAPH_CHECK(igraph_sparsemat_qrresol(data->dis, data->din, &vfrom, &vto)); } return 0; } /** * \function igraph_sparsemat_arpack_rssolve * Eigenvalues and eigenvectors of a symmetric sparse matrix via ARPACK * * \param The input matrix, must be column-compressed. * \param options It is passed to \ref igraph_arpack_rssolve(). See * \ref igraph_arpack_options_t for the details. If \c mode is 1, * then ARPACK uses regular mode, if \c mode is 3, then shift and * invert mode is used and the \c sigma structure member defines * the shift. * \param storage Storage for ARPACK. See \ref * igraph_arpack_rssolve() and \ref igraph_arpack_storage_t for * details. * \param values An initialized vector or a null pointer, the * eigenvalues are stored here. * \param vectors An initialised matrix, or a null pointer, the * eigenvectors are stored here, in the columns. * \param solvemethod The method to solve the linear system, if \c * mode is 3, i.e. the shift and invert mode is used. * Possible values: * \clist * \cli IGRAPH_SPARSEMAT_SOLVE_LU * The linear system is solved using LU decomposition. * \cli IGRAPH_SPARSEMAT_SOLVE_QR * The linear system is solved using QR decomposition. * \endclist * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_arpack_rssolve(const igraph_sparsemat_t *A, igraph_arpack_options_t *options, igraph_arpack_storage_t *storage, igraph_vector_t *values, igraph_matrix_t *vectors, igraph_sparsemat_solve_t solvemethod) { int n = (int) igraph_sparsemat_nrow(A); if (n != igraph_sparsemat_ncol(A)) { IGRAPH_ERROR("Non-square matrix for ARPACK", IGRAPH_NONSQUARE); } options->n = n; if (options->mode == 1) { IGRAPH_CHECK(igraph_arpack_rssolve(igraph_i_sparsemat_arpack_multiply, (void*) A, options, storage, values, vectors)); } else if (options->mode == 3) { igraph_real_t sigma = options->sigma; igraph_sparsemat_t OP, eye; igraph_sparsemat_symbolic_t symb; igraph_sparsemat_numeric_t num; igraph_i_sparsemat_arpack_rssolve_data_t data; /*-----------------------------------*/ /* We need to factor the (A-sigma*I) */ /*-----------------------------------*/ /* Create (A-sigma*I) */ IGRAPH_CHECK(igraph_sparsemat_eye(&eye, /*n=*/ n, /*nzmax=*/ n, /*value=*/ -sigma, /*compress=*/ 1)); IGRAPH_FINALLY(igraph_sparsemat_destroy, &eye); IGRAPH_CHECK(igraph_sparsemat_add(/*A=*/ A, /*B=*/ &eye, /*alpha=*/ 1.0, /*beta=*/ 1.0, /*res=*/ &OP)); igraph_sparsemat_destroy(&eye); IGRAPH_FINALLY_CLEAN(1); IGRAPH_FINALLY(igraph_sparsemat_destroy, &OP); if (solvemethod == IGRAPH_SPARSEMAT_SOLVE_LU) { /* Symbolic analysis */ IGRAPH_CHECK(igraph_sparsemat_symblu(/*order=*/ 0, &OP, &symb)); IGRAPH_FINALLY(igraph_sparsemat_symbolic_destroy, &symb); /* Numeric LU factorization */ IGRAPH_CHECK(igraph_sparsemat_lu(&OP, &symb, &num, /*tol=*/ 0)); IGRAPH_FINALLY(igraph_sparsemat_numeric_destroy, &num); } else if (solvemethod == IGRAPH_SPARSEMAT_SOLVE_QR) { /* Symbolic analysis */ IGRAPH_CHECK(igraph_sparsemat_symbqr(/*order=*/ 0, &OP, &symb)); IGRAPH_FINALLY(igraph_sparsemat_symbolic_destroy, &symb); /* Numeric QR factorization */ IGRAPH_CHECK(igraph_sparsemat_qr(&OP, &symb, &num)); IGRAPH_FINALLY(igraph_sparsemat_numeric_destroy, &num); } data.dis = &symb; data.din = # data.tol = options->tol; data.method = solvemethod; IGRAPH_CHECK(igraph_arpack_rssolve(igraph_i_sparsemat_arpack_solve, (void*) &data, options, storage, values, vectors)); igraph_sparsemat_numeric_destroy(&num); igraph_sparsemat_symbolic_destroy(&symb); igraph_sparsemat_destroy(&OP); IGRAPH_FINALLY_CLEAN(3); } return 0; } /** * \function igraph_sparsemat_arpack_rnsolve * Eigenvalues and eigenvectors of a nonsymmetric sparse matrix via ARPACK * * Eigenvalues and/or eigenvectors of a nonsymmetric sparse matrix. * \param A The input matrix, in column-compressed mode. * \param options ARPACK options, it is passed to \ref * igraph_arpack_rnsolve(). See also \ref igraph_arpack_options_t * for details. * \param storage Storage for ARPACK, this is passed to \ref * igraph_arpack_rnsolve(). See \ref igraph_arpack_storage_t for * details. * \param values An initialized matrix, or a null pointer. If not a * null pointer, then the eigenvalues are stored here, the first * column is the real part, the second column is the imaginary * part. * \param vectors An initialized matrix, or a null pointer. If not a * null pointer, then the eigenvectors are stored here, please see * \ref igraph_arpack_rnsolve() for the format. * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_arpack_rnsolve(const igraph_sparsemat_t *A, igraph_arpack_options_t *options, igraph_arpack_storage_t *storage, igraph_matrix_t *values, igraph_matrix_t *vectors) { int n = (int) igraph_sparsemat_nrow(A); if (n != igraph_sparsemat_ncol(A)) { IGRAPH_ERROR("Non-square matrix for ARPACK", IGRAPH_NONSQUARE); } options->n = n; return igraph_arpack_rnsolve(igraph_i_sparsemat_arpack_multiply, (void*) A, options, storage, values, vectors); } /** * \function igraph_sparsemat_symbqr * Symbolic QR decomposition * * QR decomposition of sparse matrices involves two steps, the first * is calling this function, and then \ref * igraph_sparsemat_qr(). * \param order The ordering to use: 0 means natural ordering, 1 means * minimum degree ordering of A+A', 2 is minimum degree ordering of * A'A after removing the dense rows from A, and 3 is the minimum * degree ordering of A'A. * \param A The input matrix, in column-compressed format. * \param dis The result of the symbolic analysis is stored here. Once * not needed anymore, it must be destroyed by calling \ref * igraph_sparsemat_symbolic_destroy(). * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_symbqr(long int order, const igraph_sparsemat_t *A, igraph_sparsemat_symbolic_t *dis) { dis->symbolic = cs_sqr((int) order, A->cs, /*qr=*/ 1); if (!dis->symbolic) { IGRAPH_ERROR("Cannot do symbolic QR decomposition", IGRAPH_FAILURE); } return 0; } /** * \function igraph_sparsemat_symblu * Symbolic LU decomposition * * LU decomposition of sparse matrices involves two steps, the first * is calling this function, and then \ref igraph_sparsemat_lu(). * \param order The ordering to use: 0 means natural ordering, 1 means * minimum degree ordering of A+A', 2 is minimum degree ordering of * A'A after removing the dense rows from A, and 3 is the minimum * degree ordering of A'A. * \param A The input matrix, in column-compressed format. * \param dis The result of the symbolic analysis is stored here. Once * not needed anymore, it must be destroyed by calling \ref * igraph_sparsemat_symbolic_destroy(). * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_symblu(long int order, const igraph_sparsemat_t *A, igraph_sparsemat_symbolic_t *dis) { dis->symbolic = cs_sqr((int) order, A->cs, /*qr=*/ 0); if (!dis->symbolic) { IGRAPH_ERROR("Cannot do symbolic LU decomposition", IGRAPH_FAILURE); } return 0; } /** * \function igraph_sparsemat_lu * LU decomposition of a sparse matrix * * Performs numeric sparse LU decomposition of a matrix. * \param A The input matrix, in column-compressed format. * \param dis The symbolic analysis for LU decomposition, coming from * a call to the \ref igraph_sparsemat_symblu() function. * \param din The numeric decomposition, the result is stored here. It * can be used to solve linear systems with changing right hand * side vectors, by calling \ref igraph_sparsemat_luresol(). Once * not needed any more, it must be destroyed by calling \ref * igraph_sparsemat_symbolic_destroy() on it. * \param tol The tolerance for the numeric LU decomposition. * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_lu(const igraph_sparsemat_t *A, const igraph_sparsemat_symbolic_t *dis, igraph_sparsemat_numeric_t *din, double tol) { din->numeric = cs_lu(A->cs, dis->symbolic, tol); if (!din->numeric) { IGRAPH_ERROR("Cannot do LU decomposition", IGRAPH_FAILURE); } return 0; } /** * \function igraph_sparsemat_qr * QR decomposition of a sparse matrix * * Numeric QR decomposition of a sparse matrix. * \param A The input matrix, in column-compressed format. * \param dis The result of the symbolic QR analysis, from the * function \ref igraph_sparsemat_symbqr(). * \param din The result of the decomposition is stored here, it can * be used to solve many linear systems with the same coefficient * matrix and changing right hand sides, using the \ref * igraph_sparsemat_qrresol() function. Once not needed any more, * one should call \ref igraph_sparsemat_numeric_destroy() on it to * free the allocated memory. * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_qr(const igraph_sparsemat_t *A, const igraph_sparsemat_symbolic_t *dis, igraph_sparsemat_numeric_t *din) { din->numeric = cs_qr(A->cs, dis->symbolic); if (!din->numeric) { IGRAPH_ERROR("Cannot do QR decomposition", IGRAPH_FAILURE); } return 0; } /** * \function igraph_sparsemat_luresol * Solve linear system using a precomputed LU decomposition * * Uses the LU decomposition of a matrix to solve linear systems. * \param dis The symbolic analysis of the coefficient matrix, the * result of \ref igraph_sparsemat_symblu(). * \param din The LU decomposition, the result of a call to \ref * igraph_sparsemat_lu(). * \param b A vector that defines the right hand side of the linear * equation system. * \param res An initialized vector, the solution of the linear system * is stored here. * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_luresol(const igraph_sparsemat_symbolic_t *dis, const igraph_sparsemat_numeric_t *din, const igraph_vector_t *b, igraph_vector_t *res) { int n = din->numeric->L->n; igraph_real_t *workspace; if (res != b) { IGRAPH_CHECK(igraph_vector_update(res, b)); } workspace = igraph_Calloc(n, igraph_real_t); if (!workspace) { IGRAPH_ERROR("Cannot LU (re)solve sparse matrix", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, workspace); if (!cs_ipvec(din->numeric->pinv, VECTOR(*res), workspace, n)) { IGRAPH_ERROR("Cannot LU (re)solve sparse matrix", IGRAPH_FAILURE); } if (!cs_lsolve(din->numeric->L, workspace)) { IGRAPH_ERROR("Cannot LU (re)solve sparse matrix", IGRAPH_FAILURE); } if (!cs_usolve(din->numeric->U, workspace)) { IGRAPH_ERROR("Cannot LU (re)solve sparse matrix", IGRAPH_FAILURE); } if (!cs_ipvec(dis->symbolic->q, workspace, VECTOR(*res), n)) { IGRAPH_ERROR("Cannot LU (re)solve sparse matrix", IGRAPH_FAILURE); } igraph_Free(workspace); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_sparsemat_qrresol * Solve a linear system using a precomputed QR decomposition * * Solves a linear system using a QR decomposition of its coefficient * matrix. * \param dis Symbolic analysis of the coefficient matrix, the result * of \ref igraph_sparsemat_symbqr(). * \param din The QR decomposition of the coefficient matrix, the * result of \ref igraph_sparsemat_qr(). * \param b Vector, giving the right hand side of the linear equation * system. * \param res An initialized vector, the solution is stored here. It * is resized as needed. * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_qrresol(const igraph_sparsemat_symbolic_t *dis, const igraph_sparsemat_numeric_t *din, const igraph_vector_t *b, igraph_vector_t *res) { int n = din->numeric->L->n; igraph_real_t *workspace; int k; if (res != b) { IGRAPH_CHECK(igraph_vector_update(res, b)); } workspace = igraph_Calloc(dis->symbolic ? dis->symbolic->m2 : 1, igraph_real_t); if (!workspace) { IGRAPH_ERROR("Cannot QR (re)solve sparse matrix", IGRAPH_FAILURE); } IGRAPH_FINALLY(igraph_free, workspace); if (!cs_ipvec(dis->symbolic->pinv, VECTOR(*res), workspace, n)) { IGRAPH_ERROR("Cannot QR (re)solve sparse matrix", IGRAPH_FAILURE); } for (k = 0; k < n; k++) { if (!cs_happly(din->numeric->L, k, din->numeric->B[k], workspace)) { IGRAPH_ERROR("Cannot QR (re)solve sparse matrix", IGRAPH_FAILURE); } } if (!cs_usolve(din->numeric->U, workspace)) { IGRAPH_ERROR("Cannot QR (re)solve sparse matrix", IGRAPH_FAILURE); } if (!cs_ipvec(dis->symbolic->q, workspace, VECTOR(*res), n)) { IGRAPH_ERROR("Cannot QR (re)solve sparse matrix", IGRAPH_FAILURE); } igraph_Free(workspace); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_sparsemat_symbolic_destroy * Deallocate memory for a symbolic decomposition * * Frees the memory allocated by \ref igraph_sparsemat_symbqr() or * \ref igraph_sparsemat_symblu(). * \param dis The symbolic analysis. * * Time complexity: O(1). */ void igraph_sparsemat_symbolic_destroy(igraph_sparsemat_symbolic_t *dis) { cs_sfree(dis->symbolic); dis->symbolic = 0; } /** * \function igraph_sparsemat_numeric_destroy * Deallocate memory for a numeric decomposition * * Frees the memoty allocated by \ref igraph_sparsemat_qr() or \ref * igraph_sparsemat_lu(). * \param din The LU or QR decomposition. * * Time complexity: O(1). */ void igraph_sparsemat_numeric_destroy(igraph_sparsemat_numeric_t *din) { cs_nfree(din->numeric); din->numeric = 0; } /** * \function igraph_matrix_as_sparsemat * Convert a dense matrix to a sparse matrix * * \param res An uninitialized sparse matrix, the result is stored * here. * \param mat The dense input matrix. * \param tol Real scalar, the tolerance. Values closer than \p tol to * zero are considered as zero, and will not be included in the * sparse matrix. * \return Error code. * * Time complexity: O(mn), the number of elements in the dense * matrix. */ int igraph_matrix_as_sparsemat(igraph_sparsemat_t *res, const igraph_matrix_t *mat, igraph_real_t tol) { int nrow = (int) igraph_matrix_nrow(mat); int ncol = (int) igraph_matrix_ncol(mat); int i, j, nzmax = 0; for (i = 0; i < nrow; i++) { for (j = 0; j < ncol; j++) { if (fabs(MATRIX(*mat, i, j)) > tol) { nzmax++; } } } IGRAPH_CHECK(igraph_sparsemat_init(res, nrow, ncol, nzmax)); for (i = 0; i < nrow; i++) { for (j = 0; j < ncol; j++) { if (fabs(MATRIX(*mat, i, j)) > tol) { IGRAPH_CHECK(igraph_sparsemat_entry(res, i, j, MATRIX(*mat, i, j))); } } } return 0; } int igraph_i_sparsemat_as_matrix_cc(igraph_matrix_t *res, const igraph_sparsemat_t *spmat) { int nrow = (int) igraph_sparsemat_nrow(spmat); int ncol = (int) igraph_sparsemat_ncol(spmat); int *p = spmat->cs->p; int *i = spmat->cs->i; igraph_real_t *x = spmat->cs->x; int nzmax = spmat->cs->nzmax; int from = 0, to = 0; IGRAPH_CHECK(igraph_matrix_resize(res, nrow, ncol)); igraph_matrix_null(res); while (*p < nzmax) { while (to < * (p + 1)) { MATRIX(*res, *i, from) += *x; to++; i++; x++; } from++; p++; } return 0; } int igraph_i_sparsemat_as_matrix_triplet(igraph_matrix_t *res, const igraph_sparsemat_t *spmat) { int nrow = (int) igraph_sparsemat_nrow(spmat); int ncol = (int) igraph_sparsemat_ncol(spmat); int *i = spmat->cs->p; int *j = spmat->cs->i; igraph_real_t *x = spmat->cs->x; int nz = spmat->cs->nz; int e; IGRAPH_CHECK(igraph_matrix_resize(res, nrow, ncol)); igraph_matrix_null(res); for (e = 0; e < nz; e++, i++, j++, x++) { MATRIX(*res, *j, *i) += *x; } return 0; } /** * \function igraph_sparsemat_as_matrix * Convert a sparse matrix to a dense matrix * * \param res Pointer to an initialized matrix, the result is stored * here. It will be resized to the required size. * \param spmat The input sparse matrix, in triplet or * column-compressed format. * \return Error code. * * Time complexity: O(mn), the number of elements in the dense * matrix. */ int igraph_sparsemat_as_matrix(igraph_matrix_t *res, const igraph_sparsemat_t *spmat) { if (spmat->cs->nz < 0) { return (igraph_i_sparsemat_as_matrix_cc(res, spmat)); } else { return (igraph_i_sparsemat_as_matrix_triplet(res, spmat)); } } /** * \function igraph_sparsemat_max * Maximum of a sparse matrix * * \param A The input matrix, column-compressed. * \return The maximum in the input matrix, or \c IGRAPH_NEGINFINITY * if the matrix has zero elements. * * Time complexity: TODO. */ igraph_real_t igraph_sparsemat_max(igraph_sparsemat_t *A) { int i, n; igraph_real_t *ptr; igraph_real_t res; IGRAPH_CHECK(igraph_sparsemat_dupl(A)); ptr = A->cs->x; n = A->cs->nz == -1 ? A->cs->p[A->cs->n] : A->cs->nz; if (n == 0) { return IGRAPH_NEGINFINITY; } res = *ptr; for (i = 1; i < n; i++, ptr++) { if (*ptr > res) { res = *ptr; } } return res; } /* TODO: CC matrix don't actually need _dupl, because the elements are right beside each other. Same for max and minmax. */ /** * \function igraph_sparsemat_min * Minimum of a sparse matrix * * \param A The input matrix, column-compressed. * \return The minimum in the input matrix, or \c IGRAPH_POSINFINITY * if the matrix has zero elements. * * Time complexity: TODO. */ igraph_real_t igraph_sparsemat_min(igraph_sparsemat_t *A) { int i, n; igraph_real_t *ptr; igraph_real_t res; IGRAPH_CHECK(igraph_sparsemat_dupl(A)); ptr = A->cs->x; n = A->cs->nz == -1 ? A->cs->p[A->cs->n] : A->cs->nz; if (n == 0) { return IGRAPH_POSINFINITY; } res = *ptr; for (i = 1; i < n; i++, ptr++) { if (*ptr < res) { res = *ptr; } } return res; } /** * \function igraph_sparsemat_minmax * Minimum and maximum of a sparse matrix * * \param A The input matrix, column-compressed. * \param min The minimum in the input matrix is stored here, or \c * IGRAPH_POSINFINITY if the matrix has zero elements. * \param max The maximum in the input matrix is stored here, or \c * IGRAPH_NEGINFINITY if the matrix has zero elements. * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_minmax(igraph_sparsemat_t *A, igraph_real_t *min, igraph_real_t *max) { int i, n; igraph_real_t *ptr; IGRAPH_CHECK(igraph_sparsemat_dupl(A)); ptr = A->cs->x; n = A->cs->nz == -1 ? A->cs->p[A->cs->n] : A->cs->nz; if (n == 0) { *min = IGRAPH_POSINFINITY; *max = IGRAPH_NEGINFINITY; return 0; } *min = *max = *ptr; for (i = 1; i < n; i++, ptr++) { if (*ptr > *max) { *max = *ptr; } else if (*ptr < *min) { *min = *ptr; } } return 0; } /** * \function igraph_sparsemat_count_nonzero * Count nonzero elements of a sparse matrix * * \param A The input matrix, column-compressed. * \return Error code. * * Time complexity: TODO. */ long int igraph_sparsemat_count_nonzero(igraph_sparsemat_t *A) { int i, n; int res = 0; igraph_real_t *ptr; IGRAPH_CHECK(igraph_sparsemat_dupl(A)); ptr = A->cs->x; n = A->cs->nz == -1 ? A->cs->p[A->cs->n] : A->cs->nz; if (n == 0) { return 0; } for (i = 0; i < n; i++, ptr++) { if (*ptr) { res++; } } return res; } /** * \function igraph_sparsemat_count_nonzerotol * Count nonzero elements of a sparse matrix, ignoring elements close to zero * * Count the number of matrix entries that are closer to zero than \p * tol. * \param The input matrix, column-compressed. * \param Real scalar, the tolerance. * \return Error code. * * Time complexity: TODO. */ long int igraph_sparsemat_count_nonzerotol(igraph_sparsemat_t *A, igraph_real_t tol) { int i, n; int res = 0; igraph_real_t *ptr; IGRAPH_CHECK(igraph_sparsemat_dupl(A)); ptr = A->cs->x; n = A->cs->nz == -1 ? A->cs->p[A->cs->n] : A->cs->nz; if (n == 0) { return 0; } for (i = 0; i < n; i++, ptr++) { if (*ptr < - tol || *ptr > tol) { res++; } } return res; } int igraph_i_sparsemat_rowsums_triplet(const igraph_sparsemat_t *A, igraph_vector_t *res) { int i; int *pi = A->cs->i; double *px = A->cs->x; IGRAPH_CHECK(igraph_vector_resize(res, A->cs->m)); igraph_vector_null(res); for (i = 0; i < A->cs->nz; i++, pi++, px++) { VECTOR(*res)[ *pi ] += *px; } return 0; } int igraph_i_sparsemat_rowsums_cc(const igraph_sparsemat_t *A, igraph_vector_t *res) { int ne = A->cs->p[A->cs->n]; double *px = A->cs->x; int *pi = A->cs->i; IGRAPH_CHECK(igraph_vector_resize(res, A->cs->m)); igraph_vector_null(res); for (; pi < A->cs->i + ne; pi++, px++) { VECTOR(*res)[ *pi ] += *px; } return 0; } /** * \function igraph_sparsemat_rowsums * Row-wise sums. * * \param A The input matrix, in triplet or column-compressed format. * \param res An initialized vector, the result is stored here. It * will be resized as needed. * \return Error code. * * Time complexity: O(nz), the number of non-zero elements. */ int igraph_sparsemat_rowsums(const igraph_sparsemat_t *A, igraph_vector_t *res) { if (igraph_sparsemat_is_triplet(A)) { return igraph_i_sparsemat_rowsums_triplet(A, res); } else { return igraph_i_sparsemat_rowsums_cc(A, res); } } int igraph_i_sparsemat_rowmins_triplet(const igraph_sparsemat_t *A, igraph_vector_t *res) { int i; int *pi = A->cs->i; double *px = A->cs->x; double inf = IGRAPH_INFINITY; IGRAPH_CHECK(igraph_vector_resize(res, A->cs->m)); igraph_vector_fill(res, inf); for (i = 0; i < A->cs->nz; i++, pi++, px++) { if (*px < VECTOR(*res)[ *pi ]) { VECTOR(*res)[ *pi ] = *px; } } return 0; } int igraph_i_sparsemat_rowmins_cc(igraph_sparsemat_t *A, igraph_vector_t *res) { int ne; double *px; int *pi; double inf = IGRAPH_INFINITY; IGRAPH_CHECK(igraph_sparsemat_dupl(A)); ne = A->cs->p[A->cs->n]; px = A->cs->x; pi = A->cs->i; IGRAPH_CHECK(igraph_vector_resize(res, A->cs->m)); igraph_vector_fill(res, inf); for (; pi < A->cs->i + ne; pi++, px++) { if (*px < VECTOR(*res)[ *pi ]) { VECTOR(*res)[ *pi ] = *px; } } return 0; } int igraph_sparsemat_rowmins(igraph_sparsemat_t *A, igraph_vector_t *res) { if (igraph_sparsemat_is_triplet(A)) { return igraph_i_sparsemat_rowmins_triplet(A, res); } else { return igraph_i_sparsemat_rowmins_cc(A, res); } } int igraph_i_sparsemat_rowmaxs_triplet(const igraph_sparsemat_t *A, igraph_vector_t *res) { int i; int *pi = A->cs->i; double *px = A->cs->x; double inf = IGRAPH_NEGINFINITY; IGRAPH_CHECK(igraph_vector_resize(res, A->cs->m)); igraph_vector_fill(res, inf); for (i = 0; i < A->cs->nz; i++, pi++, px++) { if (*px > VECTOR(*res)[ *pi ]) { VECTOR(*res)[ *pi ] = *px; } } return 0; } int igraph_i_sparsemat_rowmaxs_cc(igraph_sparsemat_t *A, igraph_vector_t *res) { int ne; double *px; int *pi; double inf = IGRAPH_NEGINFINITY; IGRAPH_CHECK(igraph_sparsemat_dupl(A)); ne = A->cs->p[A->cs->n]; px = A->cs->x; pi = A->cs->i; IGRAPH_CHECK(igraph_vector_resize(res, A->cs->m)); igraph_vector_fill(res, inf); for (; pi < A->cs->i + ne; pi++, px++) { if (*px > VECTOR(*res)[ *pi ]) { VECTOR(*res)[ *pi ] = *px; } } return 0; } int igraph_sparsemat_rowmaxs(igraph_sparsemat_t *A, igraph_vector_t *res) { if (igraph_sparsemat_is_triplet(A)) { return igraph_i_sparsemat_rowmaxs_triplet(A, res); } else { return igraph_i_sparsemat_rowmaxs_cc(A, res); } } int igraph_i_sparsemat_colmins_triplet(const igraph_sparsemat_t *A, igraph_vector_t *res) { int i; int *pp = A->cs->p; double *px = A->cs->x; double inf = IGRAPH_INFINITY; IGRAPH_CHECK(igraph_vector_resize(res, A->cs->n)); igraph_vector_fill(res, inf); for (i = 0; i < A->cs->nz; i++, pp++, px++) { if (*px < VECTOR(*res)[ *pp ]) { VECTOR(*res)[ *pp ] = *px; } } return 0; } int igraph_i_sparsemat_colmins_cc(igraph_sparsemat_t *A, igraph_vector_t *res) { int n; double *px; int *pp; int *pi; double *pr; double inf = IGRAPH_INFINITY; IGRAPH_CHECK(igraph_sparsemat_dupl(A)); n = A->cs->n; px = A->cs->x; pp = A->cs->p; pi = A->cs->i; IGRAPH_CHECK(igraph_vector_resize(res, n)); igraph_vector_fill(res, inf); pr = VECTOR(*res); for (; pp < A->cs->p + n; pp++, pr++) { for (; pi < A->cs->i + * (pp + 1); pi++, px++) { if (*px < *pr) { *pr = *px; } } } return 0; } int igraph_sparsemat_colmins(igraph_sparsemat_t *A, igraph_vector_t *res) { if (igraph_sparsemat_is_triplet(A)) { return igraph_i_sparsemat_colmins_triplet(A, res); } else { return igraph_i_sparsemat_colmins_cc(A, res); } } int igraph_i_sparsemat_colmaxs_triplet(const igraph_sparsemat_t *A, igraph_vector_t *res) { int i; int *pp = A->cs->p; double *px = A->cs->x; double inf = IGRAPH_NEGINFINITY; IGRAPH_CHECK(igraph_vector_resize(res, A->cs->n)); igraph_vector_fill(res, inf); for (i = 0; i < A->cs->nz; i++, pp++, px++) { if (*px > VECTOR(*res)[ *pp ]) { VECTOR(*res)[ *pp ] = *px; } } return 0; } int igraph_i_sparsemat_colmaxs_cc(igraph_sparsemat_t *A, igraph_vector_t *res) { int n; double *px; int *pp; int *pi; double *pr; double inf = IGRAPH_NEGINFINITY; IGRAPH_CHECK(igraph_sparsemat_dupl(A)); n = A->cs->n; px = A->cs->x; pp = A->cs->p; pi = A->cs->i; IGRAPH_CHECK(igraph_vector_resize(res, n)); igraph_vector_fill(res, inf); pr = VECTOR(*res); for (; pp < A->cs->p + n; pp++, pr++) { for (; pi < A->cs->i + * (pp + 1); pi++, px++) { if (*px > *pr) { *pr = *px; } } } return 0; } int igraph_sparsemat_colmaxs(igraph_sparsemat_t *A, igraph_vector_t *res) { if (igraph_sparsemat_is_triplet(A)) { return igraph_i_sparsemat_colmaxs_triplet(A, res); } else { return igraph_i_sparsemat_colmaxs_cc(A, res); } } int igraph_i_sparsemat_which_min_rows_triplet(igraph_sparsemat_t *A, igraph_vector_t *res, igraph_vector_int_t *pos) { int i; int *pi = A->cs->i; int *pp = A->cs->p; double *px = A->cs->x; double inf = IGRAPH_INFINITY; IGRAPH_CHECK(igraph_vector_resize(res, A->cs->m)); IGRAPH_CHECK(igraph_vector_int_resize(pos, A->cs->m)); igraph_vector_fill(res, inf); igraph_vector_int_null(pos); for (i = 0; i < A->cs->nz; i++, pi++, px++, pp++) { if (*px < VECTOR(*res)[ *pi ]) { VECTOR(*res)[ *pi ] = *px; VECTOR(*pos)[ *pi ] = *pp; } } return 0; } int igraph_i_sparsemat_which_min_rows_cc(igraph_sparsemat_t *A, igraph_vector_t *res, igraph_vector_int_t *pos) { int n; double *px; int *pp; int *pi; double inf = IGRAPH_INFINITY; int j; IGRAPH_CHECK(igraph_sparsemat_dupl(A)); n = A->cs->n; px = A->cs->x; pp = A->cs->p; pi = A->cs->i; IGRAPH_CHECK(igraph_vector_resize(res, A->cs->m)); IGRAPH_CHECK(igraph_vector_int_resize(pos, A->cs->m)); igraph_vector_fill(res, inf); igraph_vector_int_null(pos); for (j = 0; pp < A->cs->p + n; pp++, j++) { for (; pi < A->cs->i + * (pp + 1); pi++, px++) { if (*px < VECTOR(*res)[ *pi ]) { VECTOR(*res)[ *pi ] = *px; VECTOR(*pos)[ *pi ] = j; } } } return 0; } int igraph_sparsemat_which_min_rows(igraph_sparsemat_t *A, igraph_vector_t *res, igraph_vector_int_t *pos) { if (igraph_sparsemat_is_triplet(A)) { return igraph_i_sparsemat_which_min_rows_triplet(A, res, pos); } else { return igraph_i_sparsemat_which_min_rows_cc(A, res, pos); } } int igraph_i_sparsemat_which_min_cols_triplet(igraph_sparsemat_t *A, igraph_vector_t *res, igraph_vector_int_t *pos) { int i; int *pi = A->cs->i; int *pp = A->cs->p; double *px = A->cs->x; double inf = IGRAPH_INFINITY; IGRAPH_CHECK(igraph_vector_resize(res, A->cs->n)); IGRAPH_CHECK(igraph_vector_int_resize(pos, A->cs->n)); igraph_vector_fill(res, inf); igraph_vector_int_null(pos); for (i = 0; i < A->cs->nz; i++, pi++, pp++, px++) { if (*px < VECTOR(*res)[ *pp ]) { VECTOR(*res)[ *pp ] = *px; VECTOR(*pos)[ *pp ] = *pi; } } return 0; } int igraph_i_sparsemat_which_min_cols_cc(igraph_sparsemat_t *A, igraph_vector_t *res, igraph_vector_int_t *pos) { int n, j, p; double *px; double *pr; int *ppos; double inf = IGRAPH_INFINITY; IGRAPH_CHECK(igraph_sparsemat_dupl(A)); n = A->cs->n; px = A->cs->x; IGRAPH_CHECK(igraph_vector_resize(res, n)); igraph_vector_fill(res, inf); pr = VECTOR(*res); IGRAPH_CHECK(igraph_vector_int_resize(pos, n)); igraph_vector_int_null(pos); ppos = VECTOR(*pos); for (j = 0; j < A->cs->n; j++, pr++, ppos++) { for (p = A->cs->p[j]; p < A->cs->p[j + 1]; p++, px++) { if (*px < *pr) { *pr = *px; *ppos = A->cs->i[p]; } } } return 0; } int igraph_sparsemat_which_min_cols(igraph_sparsemat_t *A, igraph_vector_t *res, igraph_vector_int_t *pos) { if (igraph_sparsemat_is_triplet(A)) { return igraph_i_sparsemat_which_min_cols_triplet(A, res, pos); } else { return igraph_i_sparsemat_which_min_cols_cc(A, res, pos); } } int igraph_i_sparsemat_colsums_triplet(const igraph_sparsemat_t *A, igraph_vector_t *res) { int i; int *pp = A->cs->p; double *px = A->cs->x; IGRAPH_CHECK(igraph_vector_resize(res, A->cs->n)); igraph_vector_null(res); for (i = 0; i < A->cs->nz; i++, pp++, px++) { VECTOR(*res)[ *pp ] += *px; } return 0; } int igraph_i_sparsemat_colsums_cc(const igraph_sparsemat_t *A, igraph_vector_t *res) { int n = A->cs->n; double *px = A->cs->x; int *pp = A->cs->p; int *pi = A->cs->i; double *pr; IGRAPH_CHECK(igraph_vector_resize(res, n)); igraph_vector_null(res); pr = VECTOR(*res); for (; pp < A->cs->p + n; pp++, pr++) { for (; pi < A->cs->i + * (pp + 1); pi++, px++) { *pr += *px; } } return 0; } /** * \function igraph_sparsemat_colsums * Column-wise sums * * \param A The input matrix, in triplet or column-compressed format. * \param res An initialized vector, the result is stored here. It * will be resized as needed. * \return Error code. * * Time complexity: O(nz) for triplet matrices, O(nz+n) for * column-compressed ones, nz is the number of non-zero elements, n is * the number of columns. */ int igraph_sparsemat_colsums(const igraph_sparsemat_t *A, igraph_vector_t *res) { if (igraph_sparsemat_is_triplet(A)) { return igraph_i_sparsemat_colsums_triplet(A, res); } else { return igraph_i_sparsemat_colsums_cc(A, res); } } /** * \function igraph_sparsemat_scale * Scale a sparse matrix * * Multiplies all elements of a sparse matrix, by the given scalar. * \param A The input matrix. * \param by The scaling factor. * \return Error code. * * Time complexity: O(nz), the number of non-zero elements in the * matrix. */ int igraph_sparsemat_scale(igraph_sparsemat_t *A, igraph_real_t by) { double *px = A->cs->x; int n = A->cs->nz == -1 ? A->cs->p[A->cs->n] : A->cs->nz; double *stop = px + n; for (; px < stop; px++) { *px *= by; } return 0; } /** * \function igraph_sparsemat_add_rows * Add rows to a sparse matrix * * The current matrix elements are retained and all elements in the * new rows are zero. * \param A The input matrix, in triplet or column-compressed format. * \param n The number of rows to add. * \return Error code. * * Time complexity: O(1). */ int igraph_sparsemat_add_rows(igraph_sparsemat_t *A, long int n) { A->cs->m += n; return 0; } /** * \function igraph_sparsemat_add_cols * Add columns to a sparse matrix * * The current matrix elements are retained, and all elements in the * new columns are zero. * \param A The input matrix, in triplet or column-compressed format. * \param n The number of columns to add. * \return Error code. * * Time complexity: TODO. */ int igraph_sparsemat_add_cols(igraph_sparsemat_t *A, long int n) { if (igraph_sparsemat_is_triplet(A)) { A->cs->n += n; } else { int *newp = realloc(A->cs->p, sizeof(int) * (size_t) (A->cs->n + n + 1)); int i; if (!newp) { IGRAPH_ERROR("Cannot add columns to sparse matrix", IGRAPH_ENOMEM); } if (newp != A->cs->p) { A->cs->p = newp; } for (i = A->cs->n + 1; i < A->cs->n + n + 1; i++) { A->cs->p[i] = A->cs->p[i - 1]; } A->cs->n += n; } return 0; } /** * \function igraph_sparsemat_resize * Resize a sparse matrix * * This function resizes a sparse matrix. The resized sparse matrix * will be empty. * * \param A The initialized sparse matrix to resize. * \param nrow The new number of rows. * \param ncol The new number of columns. * \param nzmax The new maximum number of elements. * \return Error code. * * Time complexity: O(nzmax), the maximum number of non-zero elements. */ int igraph_sparsemat_resize(igraph_sparsemat_t *A, long int nrow, long int ncol, int nzmax) { if (A->cs->nz < 0) { igraph_sparsemat_t tmp; IGRAPH_CHECK(igraph_sparsemat_init(&tmp, (int) nrow, (int) ncol, nzmax)); igraph_sparsemat_destroy(A); *A = tmp; } else { IGRAPH_CHECK(igraph_sparsemat_realloc(A, nzmax)); A->cs->m = (int) nrow; A->cs->n = (int) ncol; A->cs->nz = 0; } return 0; } int igraph_sparsemat_nonzero_storage(const igraph_sparsemat_t *A) { if (A->cs->nz < 0) { return A->cs->p[A->cs->n]; } else { return A->cs->nz; } } int igraph_sparsemat_getelements(const igraph_sparsemat_t *A, igraph_vector_int_t *i, igraph_vector_int_t *j, igraph_vector_t *x) { int nz = A->cs->nz; if (nz < 0) { nz = A->cs->p[A->cs->n]; IGRAPH_CHECK(igraph_vector_int_resize(i, nz)); IGRAPH_CHECK(igraph_vector_int_resize(j, A->cs->n + 1)); IGRAPH_CHECK(igraph_vector_resize(x, nz)); memcpy(VECTOR(*i), A->cs->i, (size_t) nz * sizeof(int)); memcpy(VECTOR(*j), A->cs->p, (size_t) (A->cs->n + 1) * sizeof(int)); memcpy(VECTOR(*x), A->cs->x, (size_t) nz * sizeof(igraph_real_t)); } else { IGRAPH_CHECK(igraph_vector_int_resize(i, nz)); IGRAPH_CHECK(igraph_vector_int_resize(j, nz)); IGRAPH_CHECK(igraph_vector_resize(x, nz)); memcpy(VECTOR(*i), A->cs->i, (size_t) nz * sizeof(int)); memcpy(VECTOR(*j), A->cs->p, (size_t) nz * sizeof(int)); memcpy(VECTOR(*x), A->cs->x, (size_t) nz * sizeof(igraph_real_t)); } return 0; } int igraph_sparsemat_scale_rows(igraph_sparsemat_t *A, const igraph_vector_t *fact) { int *i = A->cs->i; igraph_real_t *x = A->cs->x; int no_of_edges = A->cs->nz < 0 ? A->cs->p[A->cs->n] : A->cs->nz; int e; for (e = 0; e < no_of_edges; e++, x++, i++) { igraph_real_t f = VECTOR(*fact)[*i]; (*x) *= f; } return 0; } int igraph_i_sparsemat_scale_cols_cc(igraph_sparsemat_t *A, const igraph_vector_t *fact) { int *i = A->cs->i; igraph_real_t *x = A->cs->x; int no_of_edges = A->cs->p[A->cs->n]; int e; int c = 0; /* actual column */ for (e = 0; e < no_of_edges; e++, x++, i++) { igraph_real_t f; while (c < A->cs->n && A->cs->p[c + 1] == e) { c++; } f = VECTOR(*fact)[c]; (*x) *= f; } return 0; } int igraph_i_sparsemat_scale_cols_triplet(igraph_sparsemat_t *A, const igraph_vector_t *fact) { int *j = A->cs->p; igraph_real_t *x = A->cs->x; int no_of_edges = A->cs->nz; int e; for (e = 0; e < no_of_edges; e++, x++, j++) { igraph_real_t f = VECTOR(*fact)[*j]; (*x) *= f; } return 0; } int igraph_sparsemat_scale_cols(igraph_sparsemat_t *A, const igraph_vector_t *fact) { if (A->cs->nz < 0) { return igraph_i_sparsemat_scale_cols_cc(A, fact); } else { return igraph_i_sparsemat_scale_cols_triplet(A, fact); } } int igraph_sparsemat_multiply_by_dense(const igraph_sparsemat_t *A, const igraph_matrix_t *B, igraph_matrix_t *res) { int m = (int) igraph_sparsemat_nrow(A); int n = (int) igraph_sparsemat_ncol(A); int p = (int) igraph_matrix_ncol(B); int i; if (igraph_matrix_nrow(B) != n) { IGRAPH_ERROR("Invalid dimensions in sparse-dense matrix product", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_matrix_resize(res, m, p)); igraph_matrix_null(res); for (i = 0; i < p; i++) { if (!(cs_gaxpy(A->cs, &MATRIX(*B, 0, i), &MATRIX(*res, 0, i)))) { IGRAPH_ERROR("Cannot perform sparse-dense matrix multiplication", IGRAPH_FAILURE); } } return 0; } int igraph_sparsemat_dense_multiply(const igraph_matrix_t *A, const igraph_sparsemat_t *B, igraph_matrix_t *res) { int m = (int) igraph_matrix_nrow(A); int n = (int) igraph_matrix_ncol(A); int p = (int) igraph_sparsemat_ncol(B); int r, c; int *Bp = B->cs->p; if (igraph_sparsemat_nrow(B) != n) { IGRAPH_ERROR("Invalid dimensions in dense-sparse matrix product", IGRAPH_EINVAL); } if (!igraph_sparsemat_is_cc(B)) { IGRAPH_ERROR("Dense-sparse product is only implemented for " "column-compressed sparse matrices", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_matrix_resize(res, m, p)); igraph_matrix_null(res); for (c = 0; c < p; c++) { for (r = 0; r < m; r++) { int idx = *Bp; while (idx < * (Bp + 1)) { MATRIX(*res, r, c) += MATRIX(*A, r, B->cs->i[idx]) * B->cs->x[idx]; idx++; } } Bp++; } return 0; } int igraph_i_sparsemat_view(igraph_sparsemat_t *A, int nzmax, int m, int n, int *p, int *i, double *x, int nz) { A->cs = cs_calloc(1, sizeof(cs_di)); A->cs->nzmax = nzmax; A->cs->m = m; A->cs->n = n; A->cs->p = p; A->cs->i = i; A->cs->x = x; A->cs->nz = nz; return 0; } int igraph_sparsemat_sort(const igraph_sparsemat_t *A, igraph_sparsemat_t *sorted) { igraph_sparsemat_t tmp; IGRAPH_CHECK(igraph_sparsemat_transpose(A, &tmp, /*values=*/ 1)); IGRAPH_FINALLY(igraph_sparsemat_destroy, &tmp); IGRAPH_CHECK(igraph_sparsemat_transpose(&tmp, sorted, /*values=*/ 1)); igraph_sparsemat_destroy(&tmp); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_sparsemat_getelements_sorted(const igraph_sparsemat_t *A, igraph_vector_int_t *i, igraph_vector_int_t *j, igraph_vector_t *x) { if (A->cs->nz < 0) { igraph_sparsemat_t tmp; IGRAPH_CHECK(igraph_sparsemat_sort(A, &tmp)); IGRAPH_FINALLY(igraph_sparsemat_destroy, &tmp); IGRAPH_CHECK(igraph_sparsemat_getelements(&tmp, i, j, x)); igraph_sparsemat_destroy(&tmp); IGRAPH_FINALLY_CLEAN(1); } else { IGRAPH_CHECK(igraph_sparsemat_getelements(A, i, j, x)); } return 0; } int igraph_sparsemat_nzmax(const igraph_sparsemat_t *A) { return A->cs->nzmax; } int igraph_sparsemat_neg(igraph_sparsemat_t *A) { int i, nz = A->cs->nz == -1 ? A->cs->p[A->cs->n] : A->cs->nz; igraph_real_t *px = A->cs->x; for (i = 0; i < nz; i++, px++) { *px = - (*px); } return 0; } int igraph_sparsemat_iterator_init(igraph_sparsemat_iterator_t *it, igraph_sparsemat_t *sparsemat) { it->mat = sparsemat; igraph_sparsemat_iterator_reset(it); return 0; } int igraph_sparsemat_iterator_reset(igraph_sparsemat_iterator_t *it) { it->pos = 0; if (!igraph_sparsemat_is_triplet(it->mat)) { it->col = 0; while (it->col < it->mat->cs->n && it->mat->cs->p[it->col + 1] == it->pos) { it->col ++; } } return 0; } igraph_bool_t igraph_sparsemat_iterator_end(const igraph_sparsemat_iterator_t *it) { int nz = it->mat->cs->nz == -1 ? it->mat->cs->p[it->mat->cs->n] : it->mat->cs->nz; return it->pos >= nz; } int igraph_sparsemat_iterator_row(const igraph_sparsemat_iterator_t *it) { return it->mat->cs->i[it->pos]; } int igraph_sparsemat_iterator_col(const igraph_sparsemat_iterator_t *it) { if (igraph_sparsemat_is_triplet(it->mat)) { return it->mat->cs->p[it->pos]; } else { return it->col; } } igraph_real_t igraph_sparsemat_iterator_get(const igraph_sparsemat_iterator_t *it) { return it->mat->cs->x[it->pos]; } int igraph_sparsemat_iterator_next(igraph_sparsemat_iterator_t *it) { it->pos += 1; while (it->col < it->mat->cs->n && it->mat->cs->p[it->col + 1] == it->pos) { it->col++; } return it->pos; } int igraph_sparsemat_iterator_idx(const igraph_sparsemat_iterator_t *it) { return it->pos; } python-igraph-0.8.0/vendor/source/igraph/src/conversion.c0000644000076500000240000010201213614300625023723 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2005-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_conversion.h" #include "igraph_iterators.h" #include "igraph_interface.h" #include "igraph_attributes.h" #include "igraph_constructors.h" #include "igraph_structural.h" #include "igraph_types_internal.h" #include "igraph_sparsemat.h" #include "config.h" /** * \ingroup conversion * \function igraph_get_adjacency * \brief Returns the adjacency matrix of a graph * * * The result is an incidence matrix, it contains numbers greater * than one if there are multiple edges in the graph. * \param graph Pointer to the graph to convert * \param res Pointer to an initialized matrix object, it will be * resized if needed. * \param type Constant giving the type of the adjacency matrix to * create for undirected graphs. It is ignored for directed * graphs. Possible values: * \clist * \cli IGRAPH_GET_ADJACENCY_UPPER * the upper right triangle of the matrix is used. * \cli IGRAPH_GET_ADJACENCY_LOWER * the lower left triangle of the matrix is used. * \cli IGRAPH_GET_ADJACENCY_BOTH * the whole matrix is used, a symmetric matrix is returned. * \endclist * \param type eids Logical, if true, then the edges ids plus one * are stored in the adjacency matrix, instead of the number of * edges between the two vertices. (The plus one is needed, since * edge ids start from zero, and zero means no edge in this case.) * \return Error code: * \c IGRAPH_EINVAL invalid type argument. * * \sa igraph_get_adjacency_sparse if you want a sparse matrix representation * * Time complexity: O(|V||V|), * |V| is the * number of vertices in the graph. */ int igraph_get_adjacency(const igraph_t *graph, igraph_matrix_t *res, igraph_get_adjacency_t type, igraph_bool_t eids) { igraph_eit_t edgeit; long int no_of_nodes = igraph_vcount(graph); igraph_bool_t directed = igraph_is_directed(graph); int retval = 0; long int from, to; igraph_integer_t ffrom, fto; IGRAPH_CHECK(igraph_matrix_resize(res, no_of_nodes, no_of_nodes)); igraph_matrix_null(res); IGRAPH_CHECK(igraph_eit_create(graph, igraph_ess_all(0), &edgeit)); IGRAPH_FINALLY(igraph_eit_destroy, &edgeit); if (directed) { while (!IGRAPH_EIT_END(edgeit)) { long int edge = IGRAPH_EIT_GET(edgeit); igraph_edge(graph, (igraph_integer_t) edge, &ffrom, &fto); from = ffrom; to = fto; if (eids) { MATRIX(*res, from, to) = edge + 1; } else { MATRIX(*res, from, to) += 1; } IGRAPH_EIT_NEXT(edgeit); } } else if (type == IGRAPH_GET_ADJACENCY_UPPER) { while (!IGRAPH_EIT_END(edgeit)) { long int edge = IGRAPH_EIT_GET(edgeit); igraph_edge(graph, (igraph_integer_t) edge, &ffrom, &fto); from = ffrom; to = fto; if (to < from) { if (eids) { MATRIX(*res, to, from) = edge + 1; } else { MATRIX(*res, to, from) += 1; } } else { if (eids) { MATRIX(*res, from, to) = edge + 1; } else { MATRIX(*res, from, to) += 1; } } IGRAPH_EIT_NEXT(edgeit); } } else if (type == IGRAPH_GET_ADJACENCY_LOWER) { while (!IGRAPH_EIT_END(edgeit)) { long int edge = IGRAPH_EIT_GET(edgeit); igraph_edge(graph, (igraph_integer_t) edge, &ffrom, &fto); from = ffrom; to = fto; if (to < from) { if (eids) { MATRIX(*res, from, to) = edge + 1; } else { MATRIX(*res, from, to) += 1; } } else { if (eids) { MATRIX(*res, to, from) = edge + 1; } else { MATRIX(*res, to, from) += 1; } } IGRAPH_EIT_NEXT(edgeit); } } else if (type == IGRAPH_GET_ADJACENCY_BOTH) { while (!IGRAPH_EIT_END(edgeit)) { long int edge = IGRAPH_EIT_GET(edgeit); igraph_edge(graph, (igraph_integer_t) edge, &ffrom, &fto); from = ffrom; to = fto; if (eids) { MATRIX(*res, from, to) = edge + 1; } else { MATRIX(*res, from, to) += 1; } if (from != to) { if (eids) { MATRIX(*res, to, from) = edge + 1; } else { MATRIX(*res, to, from) += 1; } } IGRAPH_EIT_NEXT(edgeit); } } else { IGRAPH_ERROR("Invalid type argument", IGRAPH_EINVAL); } igraph_eit_destroy(&edgeit); IGRAPH_FINALLY_CLEAN(1); return retval; } /** * \ingroup conversion * \function igraph_get_adjacency_sparse * \brief Returns the adjacency matrix of a graph in sparse matrix format * * * The result is an incidence matrix, it contains numbers greater * than one if there are multiple edges in the graph. * \param graph Pointer to the graph to convert * \param res Pointer to an initialized sparse matrix object, it will be * resized if needed. * \param type Constant giving the type of the adjacency matrix to * create for undirected graphs. It is ignored for directed * graphs. Possible values: * \clist * \cli IGRAPH_GET_ADJACENCY_UPPER * the upper right triangle of the matrix is used. * \cli IGRAPH_GET_ADJACENCY_LOWER * the lower left triangle of the matrix is used. * \cli IGRAPH_GET_ADJACENCY_BOTH * the whole matrix is used, a symmetric matrix is returned. * \endclist * \return Error code: * \c IGRAPH_EINVAL invalid type argument. * * \sa igraph_get_adjacency if you would like to get a normal matrix * ( \type igraph_matrix_t ) * * Time complexity: O(|V||V|), * |V| is the * number of vertices in the graph. */ int igraph_get_adjacency_sparse(const igraph_t *graph, igraph_spmatrix_t *res, igraph_get_adjacency_t type) { igraph_eit_t edgeit; long int no_of_nodes = igraph_vcount(graph); igraph_bool_t directed = igraph_is_directed(graph); int retval = 0; long int from, to; igraph_integer_t ffrom, fto; igraph_spmatrix_null(res); IGRAPH_CHECK(igraph_spmatrix_resize(res, no_of_nodes, no_of_nodes)); IGRAPH_CHECK(igraph_eit_create(graph, igraph_ess_all(0), &edgeit)); IGRAPH_FINALLY(igraph_eit_destroy, &edgeit); if (directed) { while (!IGRAPH_EIT_END(edgeit)) { igraph_edge(graph, IGRAPH_EIT_GET(edgeit), &ffrom, &fto); from = ffrom; to = fto; igraph_spmatrix_add_e(res, from, to, 1); IGRAPH_EIT_NEXT(edgeit); } } else if (type == IGRAPH_GET_ADJACENCY_UPPER) { while (!IGRAPH_EIT_END(edgeit)) { igraph_edge(graph, IGRAPH_EIT_GET(edgeit), &ffrom, &fto); from = ffrom; to = fto; if (to < from) { igraph_spmatrix_add_e(res, to, from, 1); } else { igraph_spmatrix_add_e(res, from, to, 1); } IGRAPH_EIT_NEXT(edgeit); } } else if (type == IGRAPH_GET_ADJACENCY_LOWER) { while (!IGRAPH_EIT_END(edgeit)) { igraph_edge(graph, IGRAPH_EIT_GET(edgeit), &ffrom, &fto); from = ffrom; to = fto; if (to > from) { igraph_spmatrix_add_e(res, to, from, 1); } else { igraph_spmatrix_add_e(res, from, to, 1); } IGRAPH_EIT_NEXT(edgeit); } } else if (type == IGRAPH_GET_ADJACENCY_BOTH) { while (!IGRAPH_EIT_END(edgeit)) { igraph_edge(graph, IGRAPH_EIT_GET(edgeit), &ffrom, &fto); from = ffrom; to = fto; igraph_spmatrix_add_e(res, from, to, 1); if (from != to) { igraph_spmatrix_add_e(res, to, from, 1); } IGRAPH_EIT_NEXT(edgeit); } } else { IGRAPH_ERROR("Invalid type argument", IGRAPH_EINVAL); } igraph_eit_destroy(&edgeit); IGRAPH_FINALLY_CLEAN(1); return retval; } /** * \ingroup conversion * \function igraph_get_edgelist * \brief Returns the list of edges in a graph * * The order of the edges is given by the edge ids. * \param graph Pointer to the graph object * \param res Pointer to an initialized vector object, it will be * resized. * \param bycol Logical, if true, the edges will be returned * columnwise, eg. the first edge is * res[0]->res[|E|], the second is * res[1]->res[|E|+1], etc. * \return Error code. * * Time complexity: O(|E|), the * number of edges in the graph. */ int igraph_get_edgelist(const igraph_t *graph, igraph_vector_t *res, igraph_bool_t bycol) { igraph_eit_t edgeit; long int no_of_edges = igraph_ecount(graph); long int vptr = 0; igraph_integer_t from, to; IGRAPH_CHECK(igraph_vector_resize(res, no_of_edges * 2)); IGRAPH_CHECK(igraph_eit_create(graph, igraph_ess_all(IGRAPH_EDGEORDER_ID), &edgeit)); IGRAPH_FINALLY(igraph_eit_destroy, &edgeit); if (bycol) { while (!IGRAPH_EIT_END(edgeit)) { igraph_edge(graph, IGRAPH_EIT_GET(edgeit), &from, &to); VECTOR(*res)[vptr] = from; VECTOR(*res)[vptr + no_of_edges] = to; vptr++; IGRAPH_EIT_NEXT(edgeit); } } else { while (!IGRAPH_EIT_END(edgeit)) { igraph_edge(graph, IGRAPH_EIT_GET(edgeit), &from, &to); VECTOR(*res)[vptr++] = from; VECTOR(*res)[vptr++] = to; IGRAPH_EIT_NEXT(edgeit); } } igraph_eit_destroy(&edgeit); IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_to_directed * \brief Convert an undirected graph to a directed one * * * If the supplied graph is directed, this function does nothing. * \param graph The graph object to convert. * \param mode Constant, specifies the details of how exactly the * conversion is done. Possible values: \c * IGRAPH_TO_DIRECTED_ARBITRARY: the number of edges in the * graph stays the same, an arbitrarily directed edge is * created for each undirected edge; * \c IGRAPH_TO_DIRECTED_MUTUAL: two directed edges are * created for each undirected edge, one in each direction. * \return Error code. * * Time complexity: O(|V|+|E|), the number of vertices plus the number * of edges. */ int igraph_to_directed(igraph_t *graph, igraph_to_directed_t mode) { if (mode != IGRAPH_TO_DIRECTED_ARBITRARY && mode != IGRAPH_TO_DIRECTED_MUTUAL) { IGRAPH_ERROR("Cannot direct graph, invalid mode", IGRAPH_EINVAL); } if (igraph_is_directed(graph)) { return 0; } if (mode == IGRAPH_TO_DIRECTED_ARBITRARY) { igraph_t newgraph; igraph_vector_t edges; long int no_of_edges = igraph_ecount(graph); long int no_of_nodes = igraph_vcount(graph); long int size = no_of_edges * 2; IGRAPH_VECTOR_INIT_FINALLY(&edges, size); IGRAPH_CHECK(igraph_get_edgelist(graph, &edges, 0)); IGRAPH_CHECK(igraph_create(&newgraph, &edges, (igraph_integer_t) no_of_nodes, IGRAPH_DIRECTED)); IGRAPH_FINALLY(igraph_destroy, &newgraph); igraph_vector_destroy(&edges); IGRAPH_I_ATTRIBUTE_DESTROY(&newgraph); IGRAPH_I_ATTRIBUTE_COPY(&newgraph, graph, 1, 1, 1); IGRAPH_FINALLY_CLEAN(2); igraph_destroy(graph); *graph = newgraph; } else if (mode == IGRAPH_TO_DIRECTED_MUTUAL) { igraph_t newgraph; igraph_vector_t edges; igraph_vector_t index; long int no_of_edges = igraph_ecount(graph); long int no_of_nodes = igraph_vcount(graph); long int size = no_of_edges * 4; long int i; IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); IGRAPH_CHECK(igraph_vector_reserve(&edges, size)); IGRAPH_CHECK(igraph_get_edgelist(graph, &edges, 0)); IGRAPH_CHECK(igraph_vector_resize(&edges, no_of_edges * 4)); IGRAPH_VECTOR_INIT_FINALLY(&index, no_of_edges * 2); for (i = 0; i < no_of_edges; i++) { VECTOR(edges)[no_of_edges * 2 + i * 2] = VECTOR(edges)[i * 2 + 1]; VECTOR(edges)[no_of_edges * 2 + i * 2 + 1] = VECTOR(edges)[i * 2]; VECTOR(index)[i] = VECTOR(index)[no_of_edges + i] = i; } IGRAPH_CHECK(igraph_create(&newgraph, &edges, (igraph_integer_t) no_of_nodes, IGRAPH_DIRECTED)); IGRAPH_FINALLY(igraph_destroy, &newgraph); IGRAPH_I_ATTRIBUTE_DESTROY(&newgraph); IGRAPH_I_ATTRIBUTE_COPY(&newgraph, graph, 1, 1,/*edges=*/0); IGRAPH_CHECK(igraph_i_attribute_permute_edges(graph, &newgraph, &index)); igraph_vector_destroy(&index); igraph_vector_destroy(&edges); igraph_destroy(graph); IGRAPH_FINALLY_CLEAN(3); *graph = newgraph; } return 0; } /** * \function igraph_to_undirected * \brief Convert a directed graph to an undirected one. * * * If the supplied graph is undirected, this function does nothing. * \param graph The graph object to convert. * \param mode Constant, specifies the details of how exactly the * conversion is done. Possible values: \c * IGRAPH_TO_UNDIRECTED_EACH: the number of edges remains * constant, an undirected edge is created for each directed * one, this version might create graphs with multiple edges; * \c IGRAPH_TO_UNDIRECTED_COLLAPSE: one undirected edge will * be created for each pair of vertices which are connected * with at least one directed edge, no multiple edges will be * created. \c IGRAPH_TO_UNDIRECTED_MUTUAL creates an undirected * edge for each pair of mutual edges in the directed graph. * Non-mutual edges are lost. This mode might create multiple * edges. * \param edge_comb What to do with the edge attributes. See the igraph * manual section about attributes for details. * \return Error code. * * Time complexity: O(|V|+|E|), the number of vertices plus the number * of edges. * * \example examples/simple/igraph_to_undirected.c */ int igraph_to_undirected(igraph_t *graph, igraph_to_undirected_t mode, const igraph_attribute_combination_t *edge_comb) { long int no_of_nodes = igraph_vcount(graph); long int no_of_edges = igraph_ecount(graph); igraph_vector_t edges; igraph_t newgraph; igraph_bool_t attr = edge_comb && igraph_has_attribute_table(); if (mode != IGRAPH_TO_UNDIRECTED_EACH && mode != IGRAPH_TO_UNDIRECTED_COLLAPSE && mode != IGRAPH_TO_UNDIRECTED_MUTUAL) { IGRAPH_ERROR("Cannot undirect graph, invalid mode", IGRAPH_EINVAL); } if (!igraph_is_directed(graph)) { return 0; } IGRAPH_VECTOR_INIT_FINALLY(&edges, 0); if (mode == IGRAPH_TO_UNDIRECTED_EACH) { igraph_es_t es; igraph_eit_t eit; IGRAPH_CHECK(igraph_vector_reserve(&edges, no_of_edges * 2)); IGRAPH_CHECK(igraph_es_all(&es, IGRAPH_EDGEORDER_ID)); IGRAPH_FINALLY(igraph_es_destroy, &es); IGRAPH_CHECK(igraph_eit_create(graph, es, &eit)); IGRAPH_FINALLY(igraph_eit_destroy, &eit); while (!IGRAPH_EIT_END(eit)) { long int edge = IGRAPH_EIT_GET(eit); igraph_integer_t from, to; igraph_edge(graph, (igraph_integer_t) edge, &from, &to); IGRAPH_CHECK(igraph_vector_push_back(&edges, from)); IGRAPH_CHECK(igraph_vector_push_back(&edges, to)); IGRAPH_EIT_NEXT(eit); } igraph_eit_destroy(&eit); igraph_es_destroy(&es); IGRAPH_FINALLY_CLEAN(2); IGRAPH_CHECK(igraph_create(&newgraph, &edges, (igraph_integer_t) no_of_nodes, IGRAPH_UNDIRECTED)); IGRAPH_FINALLY(igraph_destroy, &newgraph); igraph_vector_destroy(&edges); IGRAPH_I_ATTRIBUTE_DESTROY(&newgraph); IGRAPH_I_ATTRIBUTE_COPY(&newgraph, graph, 1, 1, 1); IGRAPH_FINALLY_CLEAN(2); igraph_destroy(graph); *graph = newgraph; } else if (mode == IGRAPH_TO_UNDIRECTED_COLLAPSE) { igraph_vector_t inadj, outadj; long int i; igraph_vector_t mergeinto; long int actedge = 0; if (attr) { IGRAPH_VECTOR_INIT_FINALLY(&mergeinto, no_of_edges); } IGRAPH_CHECK(igraph_vector_reserve(&edges, no_of_edges * 2)); IGRAPH_VECTOR_INIT_FINALLY(&inadj, 0); IGRAPH_VECTOR_INIT_FINALLY(&outadj, 0); for (i = 0; i < no_of_nodes; i++) { long int n_out, n_in; long int p1 = -1, p2 = -1; long int e1 = 0, e2 = 0, n1 = 0, n2 = 0; IGRAPH_CHECK(igraph_incident(graph, &outadj, (igraph_integer_t) i, IGRAPH_OUT)); IGRAPH_CHECK(igraph_incident(graph, &inadj, (igraph_integer_t) i, IGRAPH_IN)); n_out = igraph_vector_size(&outadj); n_in = igraph_vector_size(&inadj); #define STEPOUT() if ( (++p1) < n_out) { \ e1 = (long int) VECTOR(outadj)[p1]; \ n1 = IGRAPH_TO(graph, e1); \ } #define STEPIN() if ( (++p2) < n_in) { \ e2 = (long int) VECTOR(inadj )[p2]; \ n2 = IGRAPH_FROM(graph, e2); \ } STEPOUT(); STEPIN(); while (p1 < n_out && n1 <= i && p2 < n_in && n2 <= i) { long int last; if (n1 == n2) { last = n1; IGRAPH_CHECK(igraph_vector_push_back(&edges, i)); IGRAPH_CHECK(igraph_vector_push_back(&edges, n1)); if (attr) { VECTOR(mergeinto)[e1] = actedge; VECTOR(mergeinto)[e2] = actedge; actedge++; } while (p1 < n_out && last == n1) { STEPOUT(); } while (p2 < n_in && last == n2) { STEPIN (); } } else if (n1 < n2) { last = n1; IGRAPH_CHECK(igraph_vector_push_back(&edges, i)); IGRAPH_CHECK(igraph_vector_push_back(&edges, n1)); if (attr) { VECTOR(mergeinto)[e1] = actedge; actedge++; } while (p1 < n_out && last == n1) { STEPOUT(); } } else { /* n2= 2 vertices can be represented by a * sequence of n-2 integers, each between 0 and n-1 (inclusive). * * \param graph Pointer to an initialized graph object which must be a tree on n >= 2 vertices. * \param prufer A pointer to the integer vector that should hold the Prüfer sequence; the vector must be initialized and will be resized to n - 2. * \return Error code: * \clist * \cli IGRAPH_ENOMEM * there is not enough memory to perform the operation. * \cli IGRAPH_EINVAL * the graph is not a tree or it is has less than vertices * \endclist * * \sa \ref igraph_from_prufer() * */ int igraph_to_prufer(const igraph_t *graph, igraph_vector_int_t* prufer) { /* For generating the Prüfer sequence, we enumerate the vertices u of the tree. We keep track of the degrees of all vertices, treating vertices of degree 0 as removed. We maintain the invariant that all leafs that are still contained in the tree are >= u. If u is a leaf, we remove it and add its unique neighbor to the prüfer sequence. If the removal of u turns the neighbor into a leaf which is < u, we repeat the procedure for the new leaf and so on. */ igraph_integer_t u; igraph_vector_t degrees, neighbors; igraph_integer_t prufer_index = 0; igraph_integer_t n = igraph_vcount(graph); igraph_bool_t is_tree = 0; IGRAPH_CHECK(igraph_is_tree(graph, &is_tree, NULL, IGRAPH_ALL)); if (!is_tree) { IGRAPH_ERROR("The graph must be a tree", IGRAPH_EINVAL); } if (n < 2) { IGRAPH_ERROR("The tree must have at least 2 vertices", IGRAPH_EINVAL); } IGRAPH_CHECK(igraph_vector_int_resize(prufer, n - 2)); IGRAPH_VECTOR_INIT_FINALLY(°rees, n); IGRAPH_VECTOR_INIT_FINALLY(&neighbors, 1); IGRAPH_CHECK(igraph_degree(graph, °rees, igraph_vss_all(), IGRAPH_ALL, IGRAPH_NO_LOOPS)); for (u = 0; u < n; ++u) { igraph_integer_t degree = VECTOR(degrees)[u]; igraph_integer_t leaf = u; while (degree == 1 && leaf <= u) { igraph_integer_t i; igraph_integer_t neighbor = 0; igraph_integer_t neighbor_count = 0; VECTOR(degrees)[leaf] = 0; /* mark leaf v as deleted */ IGRAPH_CHECK(igraph_neighbors(graph, &neighbors, leaf, IGRAPH_ALL)); /* Find the unique remaining neighbor of the leaf */ neighbor_count = igraph_vector_size(&neighbors); for (i = 0; i < neighbor_count; i++) { neighbor = VECTOR(neighbors)[i]; if (VECTOR(degrees)[neighbor] > 0) { break; } } /* remember that we have removed the leaf */ VECTOR(degrees)[neighbor]--; degree = VECTOR(degrees)[neighbor]; /* Add the neighbor to the prufer sequence unless it is the last vertex (i.e. degree == 0) */ if (degree > 0) { VECTOR(*prufer)[prufer_index] = neighbor; prufer_index++; } leaf = neighbor; } } igraph_vector_destroy(°rees); igraph_vector_destroy(&neighbors); IGRAPH_FINALLY_CLEAN(2); return IGRAPH_SUCCESS; } python-igraph-0.8.0/vendor/source/igraph/src/bfgs.c0000644000076500000240000001652613614300625022475 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_nongraph.h" #include "igraph_interrupt_internal.h" #include "igraph_statusbar.h" #include "memory.h" #include "config.h" #include /* This is from GNU R's optim.c, slightly adapted to igraph */ #define stepredn 0.2 #define acctol 0.0001 #define reltest 10.0 #define FALSE 0 #define TRUE 1 /* BFGS variable-metric method, based on Pascal code in J.C. Nash, `Compact Numerical Methods for Computers', 2nd edition, converted by p2c then re-crafted by B.D. Ripley */ int igraph_bfgs(igraph_vector_t *b, igraph_real_t *Fmin, igraph_scalar_function_t fminfn, igraph_vector_function_t fmingr, int maxit, int trace, igraph_real_t abstol, igraph_real_t reltol, int nREPORT, void *ex, igraph_integer_t *fncount, igraph_integer_t *grcount) { int n = (int) igraph_vector_size(b); igraph_bool_t accpoint, enough; igraph_vector_t g, t, X, c; igraph_matrix_t B; /* Lmatrix really */ int count, funcount, gradcount; igraph_real_t f, gradproj; int i, j, ilast, iter = 0; igraph_real_t s, steplength; igraph_real_t D1, D2; if (maxit <= 0) { *Fmin = fminfn(b, 0, ex); *fncount = 1; *grcount = 0; return 0; } if (nREPORT <= 0) { IGRAPH_ERROR("REPORT must be > 0 (method = \"BFGS\")", IGRAPH_EINVAL); } IGRAPH_VECTOR_INIT_FINALLY(&g, n); IGRAPH_VECTOR_INIT_FINALLY(&t, n); IGRAPH_VECTOR_INIT_FINALLY(&X, n); IGRAPH_VECTOR_INIT_FINALLY(&c, n); IGRAPH_MATRIX_INIT_FINALLY(&B, n, n); f = fminfn(b, 0, ex); if (!IGRAPH_FINITE(f)) { IGRAPH_ERROR("initial value in 'BFGS' is not finite", IGRAPH_DIVERGED); } if (trace) { igraph_statusf("initial value %f ", 0, f); } *Fmin = f; funcount = gradcount = 1; fmingr(b, 0, &g, ex); iter++; ilast = gradcount; do { IGRAPH_ALLOW_INTERRUPTION(); if (ilast == gradcount) { for (i = 0; i < n; i++) { for (j = 0; j < i; j++) { MATRIX(B, i, j) = 0.0; } MATRIX(B, i, i) = 1.0; } } for (i = 0; i < n; i++) { VECTOR(X)[i] = VECTOR(*b)[i]; VECTOR(c)[i] = VECTOR(g)[i]; } gradproj = 0.0; for (i = 0; i < n; i++) { s = 0.0; for (j = 0; j <= i; j++) { s -= MATRIX(B, i, j) * VECTOR(g)[j]; } for (j = i + 1; j < n; j++) { s -= MATRIX(B, j, i) * VECTOR(g)[j]; } VECTOR(t)[i] = s; gradproj += s * VECTOR(g)[i]; } if (gradproj < 0.0) { /* search direction is downhill */ steplength = 1.0; accpoint = FALSE; do { count = 0; for (i = 0; i < n; i++) { VECTOR(*b)[i] = VECTOR(X)[i] + steplength * VECTOR(t)[i]; if (reltest + VECTOR(X)[i] == reltest + VECTOR(*b)[i]) { /* no change */ count++; } } if (count < n) { f = fminfn(b, 0, ex); funcount++; accpoint = IGRAPH_FINITE(f) && (f <= *Fmin + gradproj * steplength * acctol); if (!accpoint) { steplength *= stepredn; } } } while (!(count == n || accpoint)); enough = (f > abstol) && fabs(f - *Fmin) > reltol * (fabs(*Fmin) + reltol); /* stop if value if small or if relative change is low */ if (!enough) { count = n; *Fmin = f; } if (count < n) {/* making progress */ *Fmin = f; fmingr(b, 0, &g, ex); gradcount++; iter++; D1 = 0.0; for (i = 0; i < n; i++) { VECTOR(t)[i] = steplength * VECTOR(t)[i]; VECTOR(c)[i] = VECTOR(g)[i] - VECTOR(c)[i]; D1 += VECTOR(t)[i] * VECTOR(c)[i]; } if (D1 > 0) { D2 = 0.0; for (i = 0; i < n; i++) { s = 0.0; for (j = 0; j <= i; j++) { s += MATRIX(B, i, j) * VECTOR(c)[j]; } for (j = i + 1; j < n; j++) { s += MATRIX(B, j, i) * VECTOR(c)[j]; } VECTOR(X)[i] = s; D2 += s * VECTOR(c)[i]; } D2 = 1.0 + D2 / D1; for (i = 0; i < n; i++) { for (j = 0; j <= i; j++) MATRIX(B, i, j) += (D2 * VECTOR(t)[i] * VECTOR(t)[j] - VECTOR(X)[i] * VECTOR(t)[j] - VECTOR(t)[i] * VECTOR(X)[j]) / D1; } } else { /* D1 < 0 */ ilast = gradcount; } } else { /* no progress */ if (ilast < gradcount) { count = 0; ilast = gradcount; } } } else { /* uphill search */ count = 0; if (ilast == gradcount) { count = n; } else { ilast = gradcount; } /* Resets unless has just been reset */ } if (trace && (iter % nREPORT == 0)) { igraph_statusf("iter%4d value %f", 0, iter, f); } if (iter >= maxit) { break; } if (gradcount - ilast > 2 * n) { ilast = gradcount; /* periodic restart */ } } while (count != n || ilast != gradcount); if (trace) { igraph_statusf("final value %f ", 0, *Fmin); if (iter < maxit) { igraph_status("converged", 0); } else { igraph_statusf("stopped after %i iterations", 0, iter); } } *fncount = funcount; *grcount = gradcount; igraph_matrix_destroy(&B); igraph_vector_destroy(&c); igraph_vector_destroy(&X); igraph_vector_destroy(&t); igraph_vector_destroy(&g); IGRAPH_FINALLY_CLEAN(5); return (iter < maxit) ? 0 : IGRAPH_DIVERGED; } python-igraph-0.8.0/vendor/source/igraph/src/walktrap_communities.cpp0000644000076500000240000010133213614300625026343 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ /* The original version of this file was written by Pascal Pons The original copyright notice follows here. The FSF address was fixed by Tamas Nepusz */ // File: communities.cpp //----------------------------------------------------------------------------- // Walktrap v0.2 -- Finds community structure of networks using random walks // Copyright (C) 2004-2005 Pascal Pons // // This program is free software; you can redistribute it and/or modify // it under the terms of the GNU General Public License as published by // the Free Software Foundation; either version 2 of the License, or // (at your option) any later version. // // This program is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU General Public License for more details. // // You should have received a copy of the GNU General Public License // along with this program; if not, write to the Free Software // Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA // 02110-1301 USA //----------------------------------------------------------------------------- // Author : Pascal Pons // Email : pascal.pons@gmail.com // Web page : http://www-rp.lip6.fr/~latapy/PP/walktrap.html // Location : Paris, France // Time : June 2005 //----------------------------------------------------------------------------- // see readme.txt for more details #include "walktrap_communities.h" #include #include #include #include #include "config.h" namespace igraph { namespace walktrap { IGRAPH_THREAD_LOCAL int Probabilities::length = 0; IGRAPH_THREAD_LOCAL Communities* Probabilities::C = 0; IGRAPH_THREAD_LOCAL float* Probabilities::tmp_vector1 = 0; IGRAPH_THREAD_LOCAL float* Probabilities::tmp_vector2 = 0; IGRAPH_THREAD_LOCAL int* Probabilities::id = 0; IGRAPH_THREAD_LOCAL int* Probabilities::vertices1 = 0; IGRAPH_THREAD_LOCAL int* Probabilities::vertices2 = 0; IGRAPH_THREAD_LOCAL int Probabilities::current_id = 0; Neighbor::Neighbor() { next_community1 = 0; previous_community1 = 0; next_community2 = 0; previous_community2 = 0; heap_index = -1; } Probabilities::~Probabilities() { C->memory_used -= memory(); if (P) { delete[] P; } if (vertices) { delete[] vertices; } } Probabilities::Probabilities(int community) { Graph* G = C->G; int nb_vertices1 = 0; int nb_vertices2 = 0; float initial_proba = 1. / float(C->communities[community].size); int last = C->members[C->communities[community].last_member]; for (int m = C->communities[community].first_member; m != last; m = C->members[m]) { tmp_vector1[m] = initial_proba; vertices1[nb_vertices1++] = m; } for (int t = 0; t < length; t++) { current_id++; if (nb_vertices1 > (G->nb_vertices / 2)) { nb_vertices2 = G->nb_vertices; for (int i = 0; i < G->nb_vertices; i++) { tmp_vector2[i] = 0.; } if (nb_vertices1 == G->nb_vertices) { for (int i = 0; i < G->nb_vertices; i++) { float proba = tmp_vector1[i] / G->vertices[i].total_weight; for (int j = 0; j < G->vertices[i].degree; j++) { tmp_vector2[G->vertices[i].edges[j].neighbor] += proba * G->vertices[i].edges[j].weight; } } } else { for (int i = 0; i < nb_vertices1; i++) { int v1 = vertices1[i]; float proba = tmp_vector1[v1] / G->vertices[v1].total_weight; for (int j = 0; j < G->vertices[v1].degree; j++) { tmp_vector2[G->vertices[v1].edges[j].neighbor] += proba * G->vertices[v1].edges[j].weight; } } } } else { nb_vertices2 = 0; for (int i = 0; i < nb_vertices1; i++) { int v1 = vertices1[i]; float proba = tmp_vector1[v1] / G->vertices[v1].total_weight; for (int j = 0; j < G->vertices[v1].degree; j++) { int v2 = G->vertices[v1].edges[j].neighbor; if (id[v2] == current_id) { tmp_vector2[v2] += proba * G->vertices[v1].edges[j].weight; } else { tmp_vector2[v2] = proba * G->vertices[v1].edges[j].weight; id[v2] = current_id; vertices2[nb_vertices2++] = v2; } } } } float* tmp = tmp_vector2; tmp_vector2 = tmp_vector1; tmp_vector1 = tmp; int* tmp2 = vertices2; vertices2 = vertices1; vertices1 = tmp2; nb_vertices1 = nb_vertices2; } if (nb_vertices1 > (G->nb_vertices / 2)) { P = new float[G->nb_vertices]; size = G->nb_vertices; vertices = 0; if (nb_vertices1 == G->nb_vertices) { for (int i = 0; i < G->nb_vertices; i++) { P[i] = tmp_vector1[i] / sqrt(G->vertices[i].total_weight); } } else { for (int i = 0; i < G->nb_vertices; i++) { P[i] = 0.; } for (int i = 0; i < nb_vertices1; i++) { P[vertices1[i]] = tmp_vector1[vertices1[i]] / sqrt(G->vertices[vertices1[i]].total_weight); } } } else { P = new float[nb_vertices1]; size = nb_vertices1; vertices = new int[nb_vertices1]; int j = 0; for (int i = 0; i < G->nb_vertices; i++) { if (id[i] == current_id) { P[j] = tmp_vector1[i] / sqrt(G->vertices[i].total_weight); vertices[j] = i; j++; } } } C->memory_used += memory(); } Probabilities::Probabilities(int community1, int community2) { // The two following probability vectors must exist. // Do not call this function if it is not the case. Probabilities* P1 = C->communities[community1].P; Probabilities* P2 = C->communities[community2].P; float w1 = float(C->communities[community1].size) / float(C->communities[community1].size + C->communities[community2].size); float w2 = float(C->communities[community2].size) / float(C->communities[community1].size + C->communities[community2].size); if (P1->size == C->G->nb_vertices) { P = new float[C->G->nb_vertices]; size = C->G->nb_vertices; vertices = 0; if (P2->size == C->G->nb_vertices) { // two full vectors for (int i = 0; i < C->G->nb_vertices; i++) { P[i] = P1->P[i] * w1 + P2->P[i] * w2; } } else { // P1 full vector, P2 partial vector int j = 0; for (int i = 0; i < P2->size; i++) { for (; j < P2->vertices[i]; j++) { P[j] = P1->P[j] * w1; } P[j] = P1->P[j] * w1 + P2->P[i] * w2; j++; } for (; j < C->G->nb_vertices; j++) { P[j] = P1->P[j] * w1; } } } else { if (P2->size == C->G->nb_vertices) { // P1 partial vector, P2 full vector P = new float[C->G->nb_vertices]; size = C->G->nb_vertices; vertices = 0; int j = 0; for (int i = 0; i < P1->size; i++) { for (; j < P1->vertices[i]; j++) { P[j] = P2->P[j] * w2; } P[j] = P1->P[i] * w1 + P2->P[j] * w2; j++; } for (; j < C->G->nb_vertices; j++) { P[j] = P2->P[j] * w2; } } else { // two partial vectors int i = 0; int j = 0; int nb_vertices1 = 0; while ((i < P1->size) && (j < P2->size)) { if (P1->vertices[i] < P2->vertices[j]) { tmp_vector1[P1->vertices[i]] = P1->P[i] * w1; vertices1[nb_vertices1++] = P1->vertices[i]; i++; continue; } if (P1->vertices[i] > P2->vertices[j]) { tmp_vector1[P2->vertices[j]] = P2->P[j] * w2; vertices1[nb_vertices1++] = P2->vertices[j]; j++; continue; } tmp_vector1[P1->vertices[i]] = P1->P[i] * w1 + P2->P[j] * w2; vertices1[nb_vertices1++] = P1->vertices[i]; i++; j++; } if (i == P1->size) { for (; j < P2->size; j++) { tmp_vector1[P2->vertices[j]] = P2->P[j] * w2; vertices1[nb_vertices1++] = P2->vertices[j]; } } else { for (; i < P1->size; i++) { tmp_vector1[P1->vertices[i]] = P1->P[i] * w1; vertices1[nb_vertices1++] = P1->vertices[i]; } } if (nb_vertices1 > (C->G->nb_vertices / 2)) { P = new float[C->G->nb_vertices]; size = C->G->nb_vertices; vertices = 0; for (int i = 0; i < C->G->nb_vertices; i++) { P[i] = 0.; } for (int i = 0; i < nb_vertices1; i++) { P[vertices1[i]] = tmp_vector1[vertices1[i]]; } } else { P = new float[nb_vertices1]; size = nb_vertices1; vertices = new int[nb_vertices1]; for (int i = 0; i < nb_vertices1; i++) { vertices[i] = vertices1[i]; P[i] = tmp_vector1[vertices1[i]]; } } } } C->memory_used += memory(); } double Probabilities::compute_distance(const Probabilities* P2) const { double r = 0.; if (vertices) { if (P2->vertices) { // two partial vectors int i = 0; int j = 0; while ((i < size) && (j < P2->size)) { if (vertices[i] < P2->vertices[j]) { r += P[i] * P[i]; i++; continue; } if (vertices[i] > P2->vertices[j]) { r += P2->P[j] * P2->P[j]; j++; continue; } r += (P[i] - P2->P[j]) * (P[i] - P2->P[j]); i++; j++; } if (i == size) { for (; j < P2->size; j++) { r += P2->P[j] * P2->P[j]; } } else { for (; i < size; i++) { r += P[i] * P[i]; } } } else { // P1 partial vector, P2 full vector int i = 0; for (int j = 0; j < size; j++) { for (; i < vertices[j]; i++) { r += P2->P[i] * P2->P[i]; } r += (P[j] - P2->P[i]) * (P[j] - P2->P[i]); i++; } for (; i < P2->size; i++) { r += P2->P[i] * P2->P[i]; } } } else { if (P2->vertices) { // P1 full vector, P2 partial vector int i = 0; for (int j = 0; j < P2->size; j++) { for (; i < P2->vertices[j]; i++) { r += P[i] * P[i]; } r += (P[i] - P2->P[j]) * (P[i] - P2->P[j]); i++; } for (; i < size; i++) { r += P[i] * P[i]; } } else { // two full vectors for (int i = 0; i < size; i++) { r += (P[i] - P2->P[i]) * (P[i] - P2->P[i]); } } } return r; } long Probabilities::memory() { if (vertices) { return (sizeof(Probabilities) + long(size) * (sizeof(float) + sizeof(int))); } else { return (sizeof(Probabilities) + long(size) * sizeof(float)); } } Community::Community() { P = 0; first_neighbor = 0; last_neighbor = 0; sub_community_of = -1; sub_communities[0] = -1; sub_communities[1] = -1; sigma = 0.; internal_weight = 0.; total_weight = 0.; } Community::~Community() { if (P) { delete P; } } Communities::Communities(Graph* graph, int random_walks_length, long m, igraph_matrix_t *pmerges, igraph_vector_t *pmodularity) { max_memory = m; memory_used = 0; G = graph; merges = pmerges; mergeidx = 0; modularity = pmodularity; Probabilities::C = this; Probabilities::length = random_walks_length; Probabilities::tmp_vector1 = new float[G->nb_vertices]; Probabilities::tmp_vector2 = new float[G->nb_vertices]; Probabilities::id = new int[G->nb_vertices]; for (int i = 0; i < G->nb_vertices; i++) { Probabilities::id[i] = 0; } Probabilities::vertices1 = new int[G->nb_vertices]; Probabilities::vertices2 = new int[G->nb_vertices]; Probabilities::current_id = 0; members = new int[G->nb_vertices]; for (int i = 0; i < G->nb_vertices; i++) { members[i] = -1; } H = new Neighbor_heap(G->nb_edges); communities = new Community[2 * G->nb_vertices]; // init the n single vertex communities if (max_memory != -1) { min_delta_sigma = new Min_delta_sigma_heap(G->nb_vertices * 2); } else { min_delta_sigma = 0; } for (int i = 0; i < G->nb_vertices; i++) { communities[i].this_community = i; communities[i].first_member = i; communities[i].last_member = i; communities[i].size = 1; communities[i].sub_community_of = 0; } nb_communities = G->nb_vertices; nb_active_communities = G->nb_vertices; for (int i = 0; i < G->nb_vertices; i++) for (int j = 0; j < G->vertices[i].degree; j++) if (i < G->vertices[i].edges[j].neighbor) { communities[i].total_weight += G->vertices[i].edges[j].weight / 2.; communities[G->vertices[i].edges[j].neighbor].total_weight += G->vertices[i].edges[j].weight / 2.; Neighbor* N = new Neighbor; N->community1 = i; N->community2 = G->vertices[i].edges[j].neighbor; N->delta_sigma = -1. / double(min(G->vertices[i].degree, G->vertices[G->vertices[i].edges[j].neighbor].degree)); N->weight = G->vertices[i].edges[j].weight; N->exact = false; add_neighbor(N); } if (max_memory != -1) { memory_used += min_delta_sigma->memory(); memory_used += 2 * long(G->nb_vertices) * sizeof(Community); memory_used += long(G->nb_vertices) * (2 * sizeof(float) + 3 * sizeof(int)); // the static data of Probabilities class memory_used += H->memory() + long(G->nb_edges) * sizeof(Neighbor); memory_used += G->memory(); } /* int c = 0; */ Neighbor* N = H->get_first(); if (N == 0) { return; /* this can happen if there are no edges */ } while (!N->exact) { update_neighbor(N, compute_delta_sigma(N->community1, N->community2)); N->exact = true; N = H->get_first(); if (max_memory != -1) { manage_memory(); } /* TODO: this could use igraph_progress */ /* if(!silent) { */ /* c++; */ /* for(int k = (500*(c-1))/G->nb_edges + 1; k <= (500*c)/G->nb_edges; k++) { */ /* if(k % 50 == 1) {cerr.width(2); cerr << endl << k/ 5 << "% ";} */ /* cerr << "."; */ /* } */ /* } */ } } Communities::~Communities() { delete[] members; delete[] communities; delete H; if (min_delta_sigma) { delete min_delta_sigma; } delete[] Probabilities::tmp_vector1; delete[] Probabilities::tmp_vector2; delete[] Probabilities::id; delete[] Probabilities::vertices1; delete[] Probabilities::vertices2; } float Community::min_delta_sigma() { float r = 1.; for (Neighbor* N = first_neighbor; N != 0;) { if (N->delta_sigma < r) { r = N->delta_sigma; } if (N->community1 == this_community) { N = N->next_community1; } else { N = N->next_community2; } } return r; } void Community::add_neighbor(Neighbor* N) { // add a new neighbor at the end of the list if (last_neighbor) { if (last_neighbor->community1 == this_community) { last_neighbor->next_community1 = N; } else { last_neighbor->next_community2 = N; } if (N->community1 == this_community) { N->previous_community1 = last_neighbor; } else { N->previous_community2 = last_neighbor; } } else { first_neighbor = N; if (N->community1 == this_community) { N->previous_community1 = 0; } else { N->previous_community2 = 0; } } last_neighbor = N; } void Community::remove_neighbor(Neighbor* N) { // remove a neighbor from the list if (N->community1 == this_community) { if (N->next_community1) { // if (N->next_community1->community1 == this_community) N->next_community1->previous_community1 = N->previous_community1; // else // N->next_community1->previous_community2 = N->previous_community1; } else { last_neighbor = N->previous_community1; } if (N->previous_community1) { if (N->previous_community1->community1 == this_community) { N->previous_community1->next_community1 = N->next_community1; } else { N->previous_community1->next_community2 = N->next_community1; } } else { first_neighbor = N->next_community1; } } else { if (N->next_community2) { if (N->next_community2->community1 == this_community) { N->next_community2->previous_community1 = N->previous_community2; } else { N->next_community2->previous_community2 = N->previous_community2; } } else { last_neighbor = N->previous_community2; } if (N->previous_community2) { // if (N->previous_community2->community1 == this_community) // N->previous_community2->next_community1 = N->next_community2; // else N->previous_community2->next_community2 = N->next_community2; } else { first_neighbor = N->next_community2; } } } void Communities::remove_neighbor(Neighbor* N) { communities[N->community1].remove_neighbor(N); communities[N->community2].remove_neighbor(N); H->remove(N); if (max_memory != -1) { if (N->delta_sigma == min_delta_sigma->delta_sigma[N->community1]) { min_delta_sigma->delta_sigma[N->community1] = communities[N->community1].min_delta_sigma(); if (communities[N->community1].P) { min_delta_sigma->update(N->community1); } } if (N->delta_sigma == min_delta_sigma->delta_sigma[N->community2]) { min_delta_sigma->delta_sigma[N->community2] = communities[N->community2].min_delta_sigma(); if (communities[N->community2].P) { min_delta_sigma->update(N->community2); } } } } void Communities::add_neighbor(Neighbor* N) { communities[N->community1].add_neighbor(N); communities[N->community2].add_neighbor(N); H->add(N); if (max_memory != -1) { if (N->delta_sigma < min_delta_sigma->delta_sigma[N->community1]) { min_delta_sigma->delta_sigma[N->community1] = N->delta_sigma; if (communities[N->community1].P) { min_delta_sigma->update(N->community1); } } if (N->delta_sigma < min_delta_sigma->delta_sigma[N->community2]) { min_delta_sigma->delta_sigma[N->community2] = N->delta_sigma; if (communities[N->community2].P) { min_delta_sigma->update(N->community2); } } } } void Communities::update_neighbor(Neighbor* N, float new_delta_sigma) { if (max_memory != -1) { if (new_delta_sigma < min_delta_sigma->delta_sigma[N->community1]) { min_delta_sigma->delta_sigma[N->community1] = new_delta_sigma; if (communities[N->community1].P) { min_delta_sigma->update(N->community1); } } if (new_delta_sigma < min_delta_sigma->delta_sigma[N->community2]) { min_delta_sigma->delta_sigma[N->community2] = new_delta_sigma; if (communities[N->community2].P) { min_delta_sigma->update(N->community2); } } float old_delta_sigma = N->delta_sigma; N->delta_sigma = new_delta_sigma; H->update(N); if (old_delta_sigma == min_delta_sigma->delta_sigma[N->community1]) { min_delta_sigma->delta_sigma[N->community1] = communities[N->community1].min_delta_sigma(); if (communities[N->community1].P) { min_delta_sigma->update(N->community1); } } if (old_delta_sigma == min_delta_sigma->delta_sigma[N->community2]) { min_delta_sigma->delta_sigma[N->community2] = communities[N->community2].min_delta_sigma(); if (communities[N->community2].P) { min_delta_sigma->update(N->community2); } } } else { N->delta_sigma = new_delta_sigma; H->update(N); } } void Communities::manage_memory() { while ((memory_used > max_memory) && !min_delta_sigma->is_empty()) { int c = min_delta_sigma->get_max_community(); delete communities[c].P; communities[c].P = 0; min_delta_sigma->remove_community(c); } } void Communities::merge_communities(Neighbor* merge_N) { int c1 = merge_N->community1; int c2 = merge_N->community2; communities[nb_communities].first_member = communities[c1].first_member; // merge the communities[nb_communities].last_member = communities[c2].last_member; // two lists members[communities[c1].last_member] = communities[c2].first_member; // of members communities[nb_communities].size = communities[c1].size + communities[c2].size; communities[nb_communities].this_community = nb_communities; communities[nb_communities].sub_community_of = 0; communities[nb_communities].sub_communities[0] = c1; communities[nb_communities].sub_communities[1] = c2; communities[nb_communities].total_weight = communities[c1].total_weight + communities[c2].total_weight; communities[nb_communities].internal_weight = communities[c1].internal_weight + communities[c2].internal_weight + merge_N->weight; communities[nb_communities].sigma = communities[c1].sigma + communities[c2].sigma + merge_N->delta_sigma; communities[c1].sub_community_of = nb_communities; communities[c2].sub_community_of = nb_communities; // update the new probability vector... if (communities[c1].P && communities[c2].P) { communities[nb_communities].P = new Probabilities(c1, c2); } if (communities[c1].P) { delete communities[c1].P; communities[c1].P = 0; if (max_memory != -1) { min_delta_sigma->remove_community(c1); } } if (communities[c2].P) { delete communities[c2].P; communities[c2].P = 0; if (max_memory != -1) { min_delta_sigma->remove_community(c2); } } if (max_memory != -1) { min_delta_sigma->delta_sigma[c1] = -1.; // to avoid to update the min_delta_sigma for these communities min_delta_sigma->delta_sigma[c2] = -1.; // min_delta_sigma->delta_sigma[nb_communities] = -1.; } // update the new neighbors // by enumerating all the neighbors of c1 and c2 Neighbor* N1 = communities[c1].first_neighbor; Neighbor* N2 = communities[c2].first_neighbor; while (N1 && N2) { int neighbor_community1; int neighbor_community2; if (N1->community1 == c1) { neighbor_community1 = N1->community2; } else { neighbor_community1 = N1->community1; } if (N2->community1 == c2) { neighbor_community2 = N2->community2; } else { neighbor_community2 = N2->community1; } if (neighbor_community1 < neighbor_community2) { Neighbor* tmp = N1; if (N1->community1 == c1) { N1 = N1->next_community1; } else { N1 = N1->next_community2; } remove_neighbor(tmp); Neighbor* N = new Neighbor; N->weight = tmp->weight; N->community1 = neighbor_community1; N->community2 = nb_communities; N->delta_sigma = (double(communities[c1].size + communities[neighbor_community1].size) * tmp->delta_sigma + double(communities[c2].size) * merge_N->delta_sigma) / (double(communities[c1].size + communities[c2].size + communities[neighbor_community1].size)); //compute_delta_sigma(neighbor_community1, nb_communities); N->exact = false; delete tmp; add_neighbor(N); } if (neighbor_community2 < neighbor_community1) { Neighbor* tmp = N2; if (N2->community1 == c2) { N2 = N2->next_community1; } else { N2 = N2->next_community2; } remove_neighbor(tmp); Neighbor* N = new Neighbor; N->weight = tmp->weight; N->community1 = neighbor_community2; N->community2 = nb_communities; N->delta_sigma = (double(communities[c1].size) * merge_N->delta_sigma + double(communities[c2].size + communities[neighbor_community2].size) * tmp->delta_sigma) / (double(communities[c1].size + communities[c2].size + communities[neighbor_community2].size)); //compute_delta_sigma(neighbor_community2, nb_communities); N->exact = false; delete tmp; add_neighbor(N); } if (neighbor_community1 == neighbor_community2) { Neighbor* tmp1 = N1; Neighbor* tmp2 = N2; bool exact = N1->exact && N2->exact; if (N1->community1 == c1) { N1 = N1->next_community1; } else { N1 = N1->next_community2; } if (N2->community1 == c2) { N2 = N2->next_community1; } else { N2 = N2->next_community2; } remove_neighbor(tmp1); remove_neighbor(tmp2); Neighbor* N = new Neighbor; N->weight = tmp1->weight + tmp2->weight; N->community1 = neighbor_community1; N->community2 = nb_communities; N->delta_sigma = (double(communities[c1].size + communities[neighbor_community1].size) * tmp1->delta_sigma + double(communities[c2].size + communities[neighbor_community1].size) * tmp2->delta_sigma - double(communities[neighbor_community1].size) * merge_N->delta_sigma) / (double(communities[c1].size + communities[c2].size + communities[neighbor_community1].size)); N->exact = exact; delete tmp1; delete tmp2; add_neighbor(N); } } if (!N1) { while (N2) { // double delta_sigma2 = N2->delta_sigma; int neighbor_community; if (N2->community1 == c2) { neighbor_community = N2->community2; } else { neighbor_community = N2->community1; } Neighbor* tmp = N2; if (N2->community1 == c2) { N2 = N2->next_community1; } else { N2 = N2->next_community2; } remove_neighbor(tmp); Neighbor* N = new Neighbor; N->weight = tmp->weight; N->community1 = neighbor_community; N->community2 = nb_communities; N->delta_sigma = (double(communities[c1].size) * merge_N->delta_sigma + double(communities[c2].size + communities[neighbor_community].size) * tmp->delta_sigma) / (double(communities[c1].size + communities[c2].size + communities[neighbor_community].size)); //compute_delta_sigma(neighbor_community, nb_communities); N->exact = false; delete tmp; add_neighbor(N); } } if (!N2) { while (N1) { // double delta_sigma1 = N1->delta_sigma; int neighbor_community; if (N1->community1 == c1) { neighbor_community = N1->community2; } else { neighbor_community = N1->community1; } Neighbor* tmp = N1; if (N1->community1 == c1) { N1 = N1->next_community1; } else { N1 = N1->next_community2; } remove_neighbor(tmp); Neighbor* N = new Neighbor; N->weight = tmp->weight; N->community1 = neighbor_community; N->community2 = nb_communities; N->delta_sigma = (double(communities[c1].size + communities[neighbor_community].size) * tmp->delta_sigma + double(communities[c2].size) * merge_N->delta_sigma) / (double(communities[c1].size + communities[c2].size + communities[neighbor_community].size)); //compute_delta_sigma(neighbor_community, nb_communities); N->exact = false; delete tmp; add_neighbor(N); } } if (max_memory != -1) { min_delta_sigma->delta_sigma[nb_communities] = communities[nb_communities].min_delta_sigma(); min_delta_sigma->update(nb_communities); } nb_communities++; nb_active_communities--; } double Communities::merge_nearest_communities() { Neighbor* N = H->get_first(); while (!N->exact) { update_neighbor(N, compute_delta_sigma(N->community1, N->community2)); N->exact = true; N = H->get_first(); if (max_memory != -1) { manage_memory(); } } double d = N->delta_sigma; remove_neighbor(N); merge_communities(N); if (max_memory != -1) { manage_memory(); } if (merges) { MATRIX(*merges, mergeidx, 0) = N->community1; MATRIX(*merges, mergeidx, 1) = N->community2; mergeidx++; } if (modularity) { float Q = 0.; for (int i = 0; i < nb_communities; i++) { if (communities[i].sub_community_of == 0) { Q += (communities[i].internal_weight - communities[i].total_weight * communities[i].total_weight / G->total_weight) / G->total_weight; } } VECTOR(*modularity)[mergeidx] = Q; } delete N; /* This could use igraph_progress */ /* if(!silent) { */ /* for(int k = (500*(G->nb_vertices - nb_active_communities - 1))/(G->nb_vertices-1) + 1; k <= (500*(G->nb_vertices - nb_active_communities))/(G->nb_vertices-1); k++) { */ /* if(k % 50 == 1) {cerr.width(2); cerr << endl << k/ 5 << "% ";} */ /* cerr << "."; */ /* } */ /* } */ return d; } double Communities::compute_delta_sigma(int community1, int community2) { if (!communities[community1].P) { communities[community1].P = new Probabilities(community1); if (max_memory != -1) { min_delta_sigma->update(community1); } } if (!communities[community2].P) { communities[community2].P = new Probabilities(community2); if (max_memory != -1) { min_delta_sigma->update(community2); } } return communities[community1].P->compute_distance(communities[community2].P) * double(communities[community1].size) * double(communities[community2].size) / double(communities[community1].size + communities[community2].size); } } } /* end of namespaces */ python-igraph-0.8.0/vendor/source/igraph/src/gengraph_powerlaw.cpp0000644000076500000240000001754213614300625025626 0ustar tamasstaff00000000000000/* * * gengraph - generation of random simple connected graphs with prescribed * degree sequence * * Copyright (C) 2006 Fabien Viger * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ // Pascalou ... #ifdef pascalou #define my_random() random() #define MY_RAND_MAX 0x7FFFFFFF #else #include "gengraph_definitions.h" #endif #include "gengraph_powerlaw.h" #include #include #include #include "igraph_error.h" namespace gengraph { // Destructor powerlaw::~powerlaw() { delete[] table; if (dt != NULL) { delete[] dt; } } // Constructor powerlaw::powerlaw(double _alpha, int _mini, int _maxi) { alpha = _alpha; mini = _mini; maxi = _maxi; if (alpha <= 2.0 && maxi < 0) igraph_warningf("powerlaw exponent %f should be > 2 when no " "Maximum is specified", __FILE__, __LINE__, -1, alpha); if (alpha <= 1.0 && maxi >= 0) igraph_warningf("powerlaw exponent %f should be > 1", __FILE__, __LINE__, -1, alpha); if (maxi >= 0 && mini > maxi) igraph_warningf("powerlaw max %d should be greater than min %d", __FILE__, __LINE__, -1, maxi, mini); table = new int[POWERLAW_TABLE]; tabulated = 0; dt = NULL; } // Sample int powerlaw::sample() { if (proba_big != 0 && test_proba(proba_big)) { return int(floor(0.5 + big_sample(random_float()))); } int r = my_random(); // table[] contains integer from MY_RAND_MAX downto 0, in blocks. Search block... if (r > (MY_RAND_MAX >> max_dt)) { return mini; } int k = 0; while (k < max_dt) { r <<= 1; r += random_bit(); k++; }; int a = 0; int b; while ((b = dt[k++]) < 0 || r < table[b]) { if (b >= 0) { a = b + 1; if (a == tabulated - 1) { break; } r <<= 1; r += random_bit(); } } // Now that we found the good block, run a dichotomy on this block [a,b] while (a < b) { int c = (a + b) / 2; if (r < table[c]) { a = c + 1; } else { b = c; } } return mini + a; } // Proba double powerlaw::proba(int k) { if (k < mini || (maxi >= 0 && k > maxi)) { return 0.0; } if (k >= mini + tabulated) { return proba_big * (big_inv_sample(double(k) - 0.5) - big_inv_sample(double(k) + 0.5)); } else { double div = table_mul; int prev_pos_in_table = k - mini - 1; if (prev_pos_in_table < 0) { return (double(MY_RAND_MAX) + 1.0 - double(table[0] >> max_dt)) * div; } // what block are we in ? int k = 0; while (k < max_dt) { div *= 0.5; k++; }; while (dt[k] < 0 || dt[k] < prev_pos_in_table) { k++; div *= 0.5; }; double prob2 = double(table[prev_pos_in_table + 1]); if (dt[k] == prev_pos_in_table) do { prob2 *= 0.5; } while (dt[++k] < 0); return (double(table[prev_pos_in_table]) - prob2) * div; } } // Relative Error double powerlaw::error() { return 1.0 / (double(tabulated) * double(tabulated)); } // Mean double powerlaw::mean() { double sum = 0.0; for (int i = mini + tabulated; --i >= mini; ) { sum += double(i) * proba(i); } // add proba_big * integral(big_sample(t),t=0..1) if (proba_big != 0) { sum += proba_big * ((pow(_a + _b, _exp + 1.0) - pow(_b, _exp + 1.0)) / (_a * (_exp + 1.0)) + double(mini) - offset - sum); } return sum; } // Median. Returns integer Med such that P(X<=Med) >= 1/2 int powerlaw::median() { if (proba_big > 0.5) { return int(floor(0.5 + big_sample(1.0 - 0.5 / proba_big))); } double sum = 0.0; int i = mini; while (sum < 0.5) { sum += proba(i++); } return i - 1; } void powerlaw::init_to_offset(double _offset, int _tabulated) { offset = _offset; tabulated = _tabulated; if (maxi >= 0 && tabulated > maxi - mini) { tabulated = maxi - mini + 1; } double sum = 0.0; double item = double(tabulated) + offset; // Compute sum of tabulated probabilities for (int i = tabulated; i--; ) { sum += pow(item -= 1.0, -alpha); } // Compute others parameters : proba_big, table_mul, _a, _b, _exp if (maxi > 0 && maxi <= mini + tabulated - 1) { proba_big = 0; table_mul = inv_RANDMAX; } else { if (maxi < 0) { _b = 0.0; } else { _b = pow(double(maxi - mini) + 0.5 + offset, 1.0 - alpha); } _a = pow(double(tabulated) - 0.5 + offset, 1.0 - alpha) - _b; _exp = 1.0 / (1.0 - alpha); double sum_big = _a * (-_exp); proba_big = sum_big / (sum + sum_big); table_mul = inv_RANDMAX * sum / (sum + sum_big); } // How many delimiters will be necessary for the table ? max_dt = max(0, int(floor(alpha * log(double(tabulated)) / log(2.0))) - 6); if (dt != NULL) { delete[] dt; } dt = new int[max_dt + 1]; // Create table as decreasing integers from MY_RAND_MAX+1 (in virtual position -1) down to 0 // Every time the index crosses a delimiter, numbers get doubled. double ssum = 0; double mul = (double(MY_RAND_MAX) + 1.0) * pow(2.0, max_dt) / sum; item = double(tabulated) + offset; int k = max_dt; dt[k--] = tabulated - 1; for (int i = tabulated; --i > 0; ) { table[i] = int(floor(0.5 + ssum)); ssum += mul * pow(item -= 1.0, -alpha); if (ssum > double(MY_RAND_MAX / 2) && k >= 0) { while ((ssum *= 0.5) > double(MY_RAND_MAX / 2)) { mul *= 0.5; dt[k--] = -1; }; mul *= 0.5; dt[k--] = i - 1; } } table[0] = int(floor(0.5 + ssum)); max_dt = k + 1; } void powerlaw::adjust_offset_mean(double _mean, double err, double factor) { // Set two bounds for offset double ol = offset; double oh = offset; if (mean() < _mean) { do { ol = oh; oh *= factor; init_to_offset(oh, tabulated); } while (mean() < _mean); } else { do { oh = ol; ol /= factor; init_to_offset(ol, tabulated); } while (mean() > _mean); } // Now, dichotomy while (fabs(oh - ol) > err * ol) { double oc = sqrt(oh * ol); init_to_offset(oc, tabulated); if (mean() < _mean) { ol = oc; } else { oh = oc; } } init_to_offset(sqrt(ol * oh), tabulated); } double powerlaw::init_to_mean(double _mean) { if (maxi >= 0 && _mean >= 0.5 * double((mini + maxi))) { igraph_errorf("Fatal error in powerlaw::init_to_mean(%f): " "Mean must be in ]min, (min+max)/2[ = ]%d, %d[", __FILE__, __LINE__, IGRAPH_EINVAL, _mean, mini, (mini + maxi) / 2); return (-1.0); } init_to_offset(_mean - double(mini), 100); adjust_offset_mean(_mean, 0.01, 2); init_to_offset(offset, POWERLAW_TABLE); double eps = 1.0 / (double(POWERLAW_TABLE)); adjust_offset_mean(_mean, eps * eps, 1.01); return offset; } } // namespace gengraph python-igraph-0.8.0/vendor/source/igraph/src/NetDataTypes.cpp0000644000076500000240000001557613614300625024465 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ /* The original version of this file was written by Jörg Reichardt The original copyright notice follows here */ /*************************************************************************** NetDataTypes.cpp - description ------------------- begin : Mon Oct 6 2003 copyright : (C) 2003 by Joerg Reichardt email : reichardt@mitte ***************************************************************************/ /*************************************************************************** * * * This program is free software; you can redistribute it and/or modify * * it under the terms of the GNU General Public License as published by * * the Free Software Foundation; either version 2 of the License, or * * (at your option) any later version. * * * ***************************************************************************/ #ifdef HAVE_CONFIG_H #include #endif #include #include #include #include "NetDataTypes.h" //################################################################################# //############################################################################### //Constructor NNode::NNode(unsigned long ind, unsigned long c_ind, DLList *ll, char* n, int states) { index = ind; cluster_index = c_ind; neighbours = new DLList(); n_links = new DLList(); global_link_list = ll; strcpy(name, n); color.red = 0; color.green = 0; color.blue = 0; strcpy(color.pajek_c, "Green"); clustering = 0.0; marker = 0; affiliations = 0; weight = 0.0; affinity = 0.0; distance = 0; max_states = states; state_history = new unsigned long[states + 1]; } //Destructor NNode::~NNode() { Disconnect_From_All(); delete neighbours; delete n_links; delete [] state_history; neighbours = NULL; n_links = NULL; state_history = NULL; } void NNode::Add_StateHistory(unsigned int state) { if (max_states >= state) { state_history[state]++; } } void NNode::Set_Color(RGBcolor c) { color.red = c.red; color.blue = c.blue; color.green = c.green; strcpy(color.pajek_c, c.pajek_c); } int NNode::Connect_To(NNode* neighbour, double weight) { NLink *link; //sollen doppelte Links erlaubt sein?? NEIN if (!neighbour) { return 0; } if (!(neighbours->Is_In_List(neighbour)) && (neighbour != this)) { neighbours->Push(neighbour); // nachbar hier eintragen neighbour->neighbours->Push(this); // diesen knoten beim nachbarn eintragen link = new NLink(this, neighbour, weight); //link erzeugen global_link_list->Push(link); // in globaler liste eintragen n_links->Push(link); // bei diesem Knoten eintragen neighbour->n_links->Push(link); // beim nachbarn eintragen return (1); } return (0); } NLink *NNode::Get_LinkToNeighbour(NNode* neighbour) { DLList_Iter iter; NLink *l_cur, *link = 0; bool found = false; // finde einen bestimmten Link aus der Liste der links eines Knotens l_cur = iter.First(n_links); while (!iter.End() && !found) { if (((l_cur->Get_Start() == this) && (l_cur->Get_End() == neighbour)) || ((l_cur->Get_End() == this) && (l_cur->Get_Start() == neighbour))) { found = true; link = l_cur; } l_cur = iter.Next(); } if (found) { return link; } else { return NULL; } } int NNode::Disconnect_From(NNode* neighbour) { //sollen doppelte Links erlaubt sein?? s.o. if (!neighbours) { return 0; } neighbours->fDelete(neighbour); n_links->fDelete(Get_LinkToNeighbour(neighbour)); neighbour->n_links->fDelete(neighbour->Get_LinkToNeighbour(this)); neighbour->neighbours->fDelete(this); return 1; } int NNode::Disconnect_From_All() { int number_of_neighbours = 0; while (neighbours->Size()) { Disconnect_From(neighbours->Pop()); number_of_neighbours++; } return (number_of_neighbours) ; } /* int NNode::Disconnect_From_All_Grandchildren() { int n_l=links->Size(); unsigned long pos=0; while ((n_l--)>1) { //alle bis auf das erste loeschen pos=(links->Get(n_l+1))->links->Is_In_List(this); // printf("%d %d\n",n_l,pos); (links->Get(n_l+1))->links->Delete(pos); } return(pos) ; } */ double NNode::Get_Links_Among_Neigbours(void) { // long neighbours1, neighbours2; double lam = 0; DLList_Iter iter1, iter2; // neighbours1=neighbours->Size(); //so viele Nachbarn hat die Betrachtete Node NNode *step1, *step2; step1 = iter1.First(neighbours); while (!iter1.End()) { // for (int n1=1;n1<=neighbours1; n1++) //step1=neighbours->Get(n1); //neighbours2=step1->neighbours->Size(); //so viele Nachbarn hat der n1-ste Nachbar step2 = iter2.First(step1->Get_Neighbours()); while (!iter2.End()) { //for (int n2=1;n2<=neighbours2; n2++) //step2=step1->neighbours->Get(n2); if (step2->Get_Neighbours()->Is_In_List(this)) { lam++; } step2 = iter2.Next(); } step1 = iter1.Next(); } return (lam / 2.0); } double NNode::Get_Clustering() { double c; unsigned long k; k = neighbours->Size(); if (k <= 1) { return (0); } c = 2.0 * Get_Links_Among_Neigbours() / double(k * k - k); return (c); } //+++++++++++++++++++++++++++++++++++++++++++++++++++++++ //Constructor NLink::NLink(NNode *s, NNode *e, double w) { start = s; end = e; weight = w; old_weight = 0; marker = 0; } //Destructor NLink::~NLink() { if (start && end) { start->Disconnect_From(end); } } python-igraph-0.8.0/vendor/source/igraph/src/matrix.c0000644000076500000240000001152113614300625023046 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_types.h" #include "igraph_matrix.h" #define BASE_IGRAPH_REAL #include "igraph_pmt.h" #include "matrix.pmt" #include "igraph_pmt_off.h" #undef BASE_IGRAPH_REAL #define BASE_INT #include "igraph_pmt.h" #include "matrix.pmt" #include "igraph_pmt_off.h" #undef BASE_INT #define BASE_LONG #include "igraph_pmt.h" #include "matrix.pmt" #include "igraph_pmt_off.h" #undef BASE_LONG #define BASE_CHAR #include "igraph_pmt.h" #include "matrix.pmt" #include "igraph_pmt_off.h" #undef BASE_CHAR #define BASE_BOOL #include "igraph_pmt.h" #include "matrix.pmt" #include "igraph_pmt_off.h" #undef BASE_BOOL #define BASE_COMPLEX #include "igraph_pmt.h" #include "matrix.pmt" #include "igraph_pmt_off.h" #undef BASE_COMPLEX #ifndef USING_R int igraph_matrix_complex_print(const igraph_matrix_complex_t *m) { long int nr = igraph_matrix_complex_nrow(m); long int nc = igraph_matrix_complex_ncol(m); long int i, j; for (i = 0; i < nr; i++) { for (j = 0; j < nc; j++) { igraph_complex_t z = MATRIX(*m, i, j); if (j != 0) { putchar(' '); } printf("%g%+gi", IGRAPH_REAL(z), IGRAPH_IMAG(z)); } printf("\n"); } return 0; } #endif int igraph_matrix_complex_fprint(const igraph_matrix_complex_t *m, FILE *file) { long int nr = igraph_matrix_complex_nrow(m); long int nc = igraph_matrix_complex_ncol(m); long int i, j; for (i = 0; i < nr; i++) { for (j = 0; j < nc; j++) { igraph_complex_t z = MATRIX(*m, i, j); if (j != 0) { fputc(' ', file); } fprintf(file, "%g%+gi", IGRAPH_REAL(z), IGRAPH_IMAG(z)); } fprintf(file, "\n"); } return 0; } int igraph_matrix_complex_real(const igraph_matrix_complex_t *v, igraph_matrix_t *real) { long int nrow = igraph_matrix_complex_nrow(v); long int ncol = igraph_matrix_complex_ncol(v); IGRAPH_CHECK(igraph_matrix_resize(real, nrow, ncol)); IGRAPH_CHECK(igraph_vector_complex_real(&v->data, &real->data)); return 0; } int igraph_matrix_complex_imag(const igraph_matrix_complex_t *v, igraph_matrix_t *imag) { long int nrow = igraph_matrix_complex_nrow(v); long int ncol = igraph_matrix_complex_ncol(v); IGRAPH_CHECK(igraph_matrix_resize(imag, nrow, ncol)); IGRAPH_CHECK(igraph_vector_complex_imag(&v->data, &imag->data)); return 0; } int igraph_matrix_complex_realimag(const igraph_matrix_complex_t *v, igraph_matrix_t *real, igraph_matrix_t *imag) { long int nrow = igraph_matrix_complex_nrow(v); long int ncol = igraph_matrix_complex_ncol(v); IGRAPH_CHECK(igraph_matrix_resize(real, nrow, ncol)); IGRAPH_CHECK(igraph_matrix_resize(imag, nrow, ncol)); IGRAPH_CHECK(igraph_vector_complex_realimag(&v->data, &real->data, &imag->data)); return 0; } int igraph_matrix_complex_create(igraph_matrix_complex_t *v, const igraph_matrix_t *real, const igraph_matrix_t *imag) { IGRAPH_CHECK(igraph_vector_complex_create(&v->data, &real->data, &imag->data)); return 0; } int igraph_matrix_complex_create_polar(igraph_matrix_complex_t *v, const igraph_matrix_t *r, const igraph_matrix_t *theta) { IGRAPH_CHECK(igraph_vector_complex_create_polar(&v->data, &r->data, &theta->data)); return 0; } igraph_bool_t igraph_matrix_all_e_tol(const igraph_matrix_t *lhs, const igraph_matrix_t *rhs, igraph_real_t tol) { return igraph_vector_e_tol(&lhs->data, &rhs->data, tol); } int igraph_matrix_zapsmall(igraph_matrix_t *m, igraph_real_t tol) { return igraph_vector_zapsmall(&m->data, tol); } python-igraph-0.8.0/vendor/source/igraph/src/adjlist.c0000644000076500000240000007235313614300625023206 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2003-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_adjlist.h" #include "igraph_memory.h" #include "igraph_interface.h" #include "igraph_interrupt_internal.h" #include "config.h" #include /* memset */ #include /** * \section about_adjlists * Sometimes it is easier to work with a graph which is in * adjacency list format: a list of vectors; each vector contains the * neighbor vertices or incident edges of a given vertex. Typically, * this representation is good if we need to iterate over the neighbors * of all vertices many times. E.g. when finding the shortest paths * between every pairs of vertices or calculating closeness centrality * for all the vertices. * * The igraph_adjlist_t stores the adjacency lists * of a graph. After creation it is independent of the original graph, * it can be modified freely with the usual vector operations, the * graph is not affected. E.g. the adjacency list can be used to * rewire the edges of a graph efficiently. If one used the * straightforward \ref igraph_delete_edges() and \ref * igraph_add_edges() combination for this that needs O(|V|+|E|) time * for every single deletion and insertion operation, it is thus very * slow if many edges are rewired. Extracting the graph into an * adjacency list, do all the rewiring operations on the vectors of * the adjacency list and then creating a new graph needs (depending * on how exactly the rewiring is done) typically O(|V|+|E|) time for * the whole rewiring process. * * Lazy adjacency lists are a bit different. When creating a * lazy adjacency list, the neighbors of the vertices are not queried, * only some memory is allocated for the vectors. When \ref * igraph_lazy_adjlist_get() is called for vertex v the first time, * the neighbors of v are queried and stored in a vector of the * adjacency list, so they don't need to be queried again. Lazy * adjacency lists are handy if you have an at least linear operation * (because initialization is generally linear in terms of number of * vertices), but you don't know how many vertices you will visit * during the computation. * * * * \example examples/simple/adjlist.c * */ /** * \function igraph_adjlist_init * Initialize an adjacency list of vertices from a given graph * * Create a list of vectors containing the neighbors of all vertices * in a graph. The adjacency list is independent of the graph after * creation, e.g. the graph can be destroyed and modified, the * adjacency list contains the state of the graph at the time of its * initialization. * \param graph The input graph. * \param al Pointer to an uninitialized igraph_adjlist_t object. * \param mode Constant specifying whether outgoing * (IGRAPH_OUT), incoming (IGRAPH_IN), * or both (IGRAPH_ALL) types of neighbors to include * in the adjacency list. It is ignored for undirected networks. * \return Error code. * * Time complexity: O(|V|+|E|), linear in the number of vertices and * edges. */ int igraph_adjlist_init(const igraph_t *graph, igraph_adjlist_t *al, igraph_neimode_t mode) { igraph_integer_t i; igraph_vector_t tmp; if (mode != IGRAPH_IN && mode != IGRAPH_OUT && mode != IGRAPH_ALL) { IGRAPH_ERROR("Cannot create adjlist view", IGRAPH_EINVMODE); } igraph_vector_init(&tmp, 0); IGRAPH_FINALLY(igraph_vector_destroy, &tmp); if (!igraph_is_directed(graph)) { mode = IGRAPH_ALL; } al->length = igraph_vcount(graph); al->adjs = igraph_Calloc(al->length, igraph_vector_int_t); if (al->adjs == 0) { IGRAPH_ERROR("Cannot create adjlist view", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_adjlist_destroy, al); for (i = 0; i < al->length; i++) { int j, n; IGRAPH_ALLOW_INTERRUPTION(); IGRAPH_CHECK(igraph_neighbors(graph, &tmp, i, mode)); n = igraph_vector_size(&tmp); IGRAPH_CHECK(igraph_vector_int_init(&al->adjs[i], n)); for (j = 0; j < n; j++) { VECTOR(al->adjs[i])[j] = VECTOR(tmp)[j]; } } igraph_vector_destroy(&tmp); IGRAPH_FINALLY_CLEAN(2); return 0; } /** * \function igraph_adjlist_init_empty * Initialize an empty adjacency list * * Creates a list of vectors, one for each vertex. This is useful when you * are \em constructing a graph using an adjacency list representation as * it does not require your graph to exist yet. * \param no_of_nodes The number of vertices * \param al Pointer to an uninitialized igraph_adjlist_t object. * \return Error code. * * Time complexity: O(|V|), linear in the number of vertices. */ int igraph_adjlist_init_empty(igraph_adjlist_t *al, igraph_integer_t no_of_nodes) { long int i; al->length = no_of_nodes; al->adjs = igraph_Calloc(al->length, igraph_vector_int_t); if (al->adjs == 0) { IGRAPH_ERROR("Cannot create adjlist view", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_adjlist_destroy, al); for (i = 0; i < al->length; i++) { IGRAPH_CHECK(igraph_vector_int_init(&al->adjs[i], 0)); } IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_adjlist_init_complementer * Adjacency lists for the complementer graph * * This function creates adjacency lists for the complementer * of the input graph. In the complementer graph all edges are present * which are not present in the original graph. Multiple edges in the * input graph are ignored. * \param graph The input graph. * \param al Pointer to a not yet initialized adjacency list. * \param mode Constant specifying whether outgoing * (IGRAPH_OUT), incoming (IGRAPH_IN), * or both (IGRAPH_ALL) types of neighbors (in the * complementer graph) to include in the adjacency list. It is * ignored for undirected networks. * \param loops Whether to consider loop edges. * \return Error code. * * Time complexity: O(|V|^2+|E|), quadratic in the number of vertices. */ int igraph_adjlist_init_complementer(const igraph_t *graph, igraph_adjlist_t *al, igraph_neimode_t mode, igraph_bool_t loops) { igraph_integer_t i, j, k, n; igraph_bool_t* seen; igraph_vector_t vec; if (mode != IGRAPH_IN && mode != IGRAPH_OUT && mode != IGRAPH_ALL) { IGRAPH_ERROR("Cannot create complementer adjlist view", IGRAPH_EINVMODE); } if (!igraph_is_directed(graph)) { mode = IGRAPH_ALL; } al->length = igraph_vcount(graph); al->adjs = igraph_Calloc(al->length, igraph_vector_int_t); if (al->adjs == 0) { IGRAPH_ERROR("Cannot create complementer adjlist view", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_adjlist_destroy, al); n = al->length; seen = igraph_Calloc(n, igraph_bool_t); if (seen == 0) { IGRAPH_ERROR("Cannot create complementer adjlist view", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_free, seen); IGRAPH_VECTOR_INIT_FINALLY(&vec, 0); for (i = 0; i < al->length; i++) { IGRAPH_ALLOW_INTERRUPTION(); igraph_neighbors(graph, &vec, i, mode); memset(seen, 0, sizeof(igraph_bool_t) * (unsigned) al->length); n = al->length; if (!loops) { seen[i] = 1; n--; } for (j = 0; j < igraph_vector_size(&vec); j++) { if (! seen [ (long int) VECTOR(vec)[j] ] ) { n--; seen[ (long int) VECTOR(vec)[j] ] = 1; } } IGRAPH_CHECK(igraph_vector_int_init(&al->adjs[i], n)); for (j = 0, k = 0; k < n; j++) { if (!seen[j]) { VECTOR(al->adjs[i])[k++] = j; } } } igraph_Free(seen); igraph_vector_destroy(&vec); IGRAPH_FINALLY_CLEAN(3); return 0; } /** * \function igraph_adjlist_destroy * Deallocate memory * * Free all memory allocated for an adjacency list. * \param al The adjacency list to destroy. * * Time complexity: depends on memory management. */ void igraph_adjlist_destroy(igraph_adjlist_t *al) { long int i; for (i = 0; i < al->length; i++) { if (&al->adjs[i]) { igraph_vector_int_destroy(&al->adjs[i]); } } igraph_Free(al->adjs); } /** * \function igraph_adjlist_clear * Removes all edges from an adjacency list. * * \param al The adjacency list. * Time complexity: depends on memory management, typically O(n), where n is * the total number of elements in the adjacency list. */ void igraph_adjlist_clear(igraph_adjlist_t *al) { long int i; for (i = 0; i < al->length; i++) { igraph_vector_int_clear(&al->adjs[i]); } } /** * \function igraph_adjlist_size * Number of vertices in an adjacency list. * * \param al The adjacency list. * \return The number of elements. * * Time complexity: O(1). */ igraph_integer_t igraph_adjlist_size(const igraph_adjlist_t *al) { return al->length; } /* igraph_vector_int_t *igraph_adjlist_get(igraph_adjlist_t *al, igraph_integer_t no) { */ /* return &al->adjs[(long int)no]; */ /* } */ /** * \function igraph_adjlist_sort * Sort each vector in an adjacency list. * * Sorts every vector of the adjacency list. * \param al The adjacency list. * * Time complexity: O(n log n), n is the total number of elements in * the adjacency list. */ void igraph_adjlist_sort(igraph_adjlist_t *al) { long int i; for (i = 0; i < al->length; i++) { igraph_vector_int_sort(&al->adjs[i]); } } /** * \function igraph_adjlist_simplify * Simplify * * Simplify an adjacency list, ie. remove loop and multiple edges. * \param al The adjacency list. * \return Error code. * * Time complexity: O(|V|+|E|), linear in the number of edges and * vertices. */ int igraph_adjlist_simplify(igraph_adjlist_t *al) { long int i; long int n = al->length; igraph_vector_int_t mark; igraph_vector_int_init(&mark, n); IGRAPH_FINALLY(igraph_vector_int_destroy, &mark); for (i = 0; i < n; i++) { igraph_vector_int_t *v = &al->adjs[i]; long int j, l = igraph_vector_int_size(v); VECTOR(mark)[i] = i + 1; for (j = 0; j < l; /* nothing */) { long int e = (long int) VECTOR(*v)[j]; if (VECTOR(mark)[e] != i + 1) { VECTOR(mark)[e] = i + 1; j++; } else { VECTOR(*v)[j] = igraph_vector_int_tail(v); igraph_vector_int_pop_back(v); l--; } } } igraph_vector_int_destroy(&mark); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_adjlist_remove_duplicate(const igraph_t *graph, igraph_adjlist_t *al) { long int i; long int n = al->length; IGRAPH_UNUSED(graph); for (i = 0; i < n; i++) { igraph_vector_int_t *v = &al->adjs[i]; long int j, p = 1, l = igraph_vector_int_size(v); for (j = 1; j < l; j++) { long int e = (long int) VECTOR(*v)[j]; /* Non-loop edges, and one end of loop edges are fine. */ /* We use here, that the vector is sorted and we also keep it sorted */ if (e != i || VECTOR(*v)[j - 1] != e) { VECTOR(*v)[p++] = e; } } igraph_vector_int_resize(v, p); } return 0; } #ifndef USING_R int igraph_adjlist_print(const igraph_adjlist_t *al) { long int i; long int n = al->length; for (i = 0; i < n; i++) { igraph_vector_int_t *v = &al->adjs[i]; igraph_vector_int_print(v); } return 0; } #endif int igraph_adjlist_fprint(const igraph_adjlist_t *al, FILE *outfile) { long int i; long int n = al->length; for (i = 0; i < n; i++) { igraph_vector_int_t *v = &al->adjs[i]; igraph_vector_int_fprint(v, outfile); } return 0; } #define ADJLIST_CANON_EDGE(from, to, directed) \ do { \ igraph_integer_t temp; \ if((!directed) && from < to) { \ temp = to; \ to = from; \ from = temp; \ } \ } while(0); igraph_bool_t igraph_adjlist_has_edge(igraph_adjlist_t* al, igraph_integer_t from, igraph_integer_t to, igraph_bool_t directed) { igraph_vector_int_t* fromvec; ADJLIST_CANON_EDGE(from, to, directed); fromvec = igraph_adjlist_get(al, from); return igraph_vector_int_binsearch2(fromvec, to); } int igraph_adjlist_replace_edge(igraph_adjlist_t* al, igraph_integer_t from, igraph_integer_t oldto, igraph_integer_t newto, igraph_bool_t directed) { igraph_vector_int_t *oldfromvec, *newfromvec; int err1, err2; long int oldpos, newpos; igraph_integer_t oldfrom = from, newfrom = from; ADJLIST_CANON_EDGE(oldfrom, oldto, directed); ADJLIST_CANON_EDGE(newfrom, newto, directed); oldfromvec = igraph_adjlist_get(al, oldfrom); newfromvec = igraph_adjlist_get(al, newfrom); err1 = igraph_vector_int_binsearch(oldfromvec, oldto, &oldpos); err2 = igraph_vector_int_binsearch(newfromvec, newto, &newpos); /* oldfrom -> oldto should exist; newfrom -> newto should not. */ if ((!err1) || err2) { return 1; } igraph_vector_int_remove(oldfromvec, oldpos); if (oldfromvec == newfromvec && oldpos < newpos) { --newpos; } IGRAPH_CHECK(igraph_vector_int_insert(newfromvec, newpos, newto)); return 0; } int igraph_adjedgelist_remove_duplicate(const igraph_t *graph, igraph_inclist_t *al) { IGRAPH_WARNING("igraph_adjedgelist_remove_duplicate() is deprecated, use " "igraph_inclist_remove_duplicate() instead"); return igraph_inclist_remove_duplicate(graph, al); } #ifndef USING_R int igraph_adjedgelist_print(const igraph_inclist_t *al, FILE *outfile) { IGRAPH_WARNING("igraph_adjedgelist_print() is deprecated, use " "igraph_inclist_print() instead"); return igraph_inclist_fprint(al, outfile); } #endif /** * \function igraph_adjedgelist_init * Initialize an incidence list of edges * * This function was superseded by \ref igraph_inclist_init() in igraph 0.6. * Please use \ref igraph_inclist_init() instead of this function. * * * Deprecated in version 0.6. */ int igraph_adjedgelist_init(const igraph_t *graph, igraph_inclist_t *il, igraph_neimode_t mode) { IGRAPH_WARNING("igraph_adjedgelist_init() is deprecated, use " "igraph_inclist_init() instead"); return igraph_inclist_init(graph, il, mode); } /** * \function igraph_adjedgelist_destroy * Frees all memory allocated for an incidence list. * * This function was superseded by \ref igraph_inclist_destroy() in igraph 0.6. * Please use \ref igraph_inclist_destroy() instead of this function. * * * Deprecated in version 0.6. */ void igraph_adjedgelist_destroy(igraph_inclist_t *il) { IGRAPH_WARNING("igraph_adjedgelist_destroy() is deprecated, use " "igraph_inclist_destroy() instead"); igraph_inclist_destroy(il); } int igraph_inclist_remove_duplicate(const igraph_t *graph, igraph_inclist_t *al) { long int i; long int n = al->length; for (i = 0; i < n; i++) { igraph_vector_int_t *v = &al->incs[i]; long int j, p = 1, l = igraph_vector_int_size(v); for (j = 1; j < l; j++) { long int e = (long int) VECTOR(*v)[j]; /* Non-loop edges and one end of loop edges are fine. */ /* We use here, that the vector is sorted and we also keep it sorted */ if (IGRAPH_FROM(graph, e) != IGRAPH_TO(graph, e) || VECTOR(*v)[j - 1] != e) { VECTOR(*v)[p++] = e; } } igraph_vector_int_resize(v, p); } return 0; } #ifndef USING_R int igraph_inclist_print(const igraph_inclist_t *al) { long int i; long int n = al->length; for (i = 0; i < n; i++) { igraph_vector_int_t *v = &al->incs[i]; igraph_vector_int_print(v); } return 0; } #endif int igraph_inclist_fprint(const igraph_inclist_t *al, FILE *outfile) { long int i; long int n = al->length; for (i = 0; i < n; i++) { igraph_vector_int_t *v = &al->incs[i]; igraph_vector_int_fprint(v, outfile); } return 0; } /** * \function igraph_inclist_init * Initialize an incidence list of edges * * Create a list of vectors containing the incident edges for all * vertices. The incidence list is independent of the graph after * creation, subsequent changes of the graph object do not update the * incidence list, and changes to the incidence list do not update the * graph. * \param graph The input graph. * \param il Pointer to an uninitialized incidence list. * \param mode Constant specifying whether incoming edges * (IGRAPH_IN), outgoing edges (IGRAPH_OUT) or * both (IGRAPH_ALL) to include in the incidence lists * of directed graphs. It is ignored for undirected graphs. * \return Error code. * * Time complexity: O(|V|+|E|), linear in the number of vertices and * edges. */ int igraph_inclist_init(const igraph_t *graph, igraph_inclist_t *il, igraph_neimode_t mode) { igraph_integer_t i; igraph_vector_t tmp; if (mode != IGRAPH_IN && mode != IGRAPH_OUT && mode != IGRAPH_ALL) { IGRAPH_ERROR("Cannot create incidence list view", IGRAPH_EINVMODE); } igraph_vector_init(&tmp, 0); IGRAPH_FINALLY(igraph_vector_destroy, &tmp); if (!igraph_is_directed(graph)) { mode = IGRAPH_ALL; } il->length = igraph_vcount(graph); il->incs = igraph_Calloc(il->length, igraph_vector_int_t); if (il->incs == 0) { IGRAPH_ERROR("Cannot create incidence list view", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_inclist_destroy, il); for (i = 0; i < il->length; i++) { int j, n; IGRAPH_ALLOW_INTERRUPTION(); IGRAPH_CHECK(igraph_incident(graph, &tmp, i, mode)); n = igraph_vector_size(&tmp); IGRAPH_CHECK(igraph_vector_int_init(&il->incs[i], n)); for (j = 0; j < n; j++) { VECTOR(il->incs[i])[j] = VECTOR(tmp)[j]; } } igraph_vector_destroy(&tmp); IGRAPH_FINALLY_CLEAN(2); return 0; } /** * \function igraph_inclist_init_empty * \brief Initialize an incidence list corresponding to an empty graph. * * This function essentially creates a list of empty vectors that may * be treated as an incidence list for a graph with a given number of * vertices. * * \param il Pointer to an uninitialized incidence list. * \param n The number of vertices in the incidence list. * \return Error code. * * Time complexity: O(|V|), linear in the number of vertices. */ int igraph_inclist_init_empty(igraph_inclist_t *il, igraph_integer_t n) { long int i; il->length = n; il->incs = igraph_Calloc(il->length, igraph_vector_int_t); if (il->incs == 0) { IGRAPH_ERROR("Cannot create incidence list view", IGRAPH_ENOMEM); } IGRAPH_FINALLY(igraph_inclist_destroy, il); for (i = 0; i < n; i++) { IGRAPH_CHECK(igraph_vector_int_init(&il->incs[i], 0)); } IGRAPH_FINALLY_CLEAN(1); return 0; } /** * \function igraph_inclist_destroy * Frees all memory allocated for an incidence list. * * \param eal The incidence list to destroy. * * Time complexity: depends on memory management. */ void igraph_inclist_destroy(igraph_inclist_t *il) { long int i; for (i = 0; i < il->length; i++) { /* This works if some igraph_vector_int_t's are 0, because igraph_vector_destroy can handle this. */ igraph_vector_int_destroy(&il->incs[i]); } igraph_Free(il->incs); } /** * \function igraph_inclist_clear * Removes all edges from an incidence list. * * \param il The incidence list. * Time complexity: depends on memory management, typically O(n), where n is * the total number of elements in the incidence list. */ void igraph_inclist_clear(igraph_inclist_t *il) { long int i; for (i = 0; i < il->length; i++) { igraph_vector_int_clear(&il->incs[i]); } } /** * \function igraph_lazy_adjlist_init * Constructor * * Create a lazy adjacency list for vertices. This function only * allocates some memory for storing the vectors of an adjacency list, * but the neighbor vertices are not queried, only at the \ref * igraph_lazy_adjlist_get() calls. * \param graph The input graph. * \param al Pointer to an uninitialized adjacency list object. * \param mode Constant, it gives whether incoming edges * (IGRAPH_IN), outgoing edges * (IGRPAH_OUT) or both types of edges * (IGRAPH_ALL) are considered. It is ignored for * undirected graphs. * \param simplify Constant, it gives whether to simplify the vectors * in the adjacency list (IGRAPH_SIMPLIFY) or not * (IGRAPH_DONT_SIMPLIFY). * \return Error code. * * Time complexity: O(|V|), the number of vertices, possibly, but * depends on the underlying memory management too. */ int igraph_lazy_adjlist_init(const igraph_t *graph, igraph_lazy_adjlist_t *al, igraph_neimode_t mode, igraph_lazy_adlist_simplify_t simplify) { if (mode != IGRAPH_IN && mode != IGRAPH_OUT && mode != IGRAPH_ALL) { IGRAPH_ERROR("Cannor create adjlist view", IGRAPH_EINVMODE); } if (!igraph_is_directed(graph)) { mode = IGRAPH_ALL; } al->mode = mode; al->simplify = simplify; al->graph = graph; al->length = igraph_vcount(graph); al->adjs = igraph_Calloc(al->length, igraph_vector_t*); if (al->adjs == 0) { IGRAPH_ERROR("Cannot create lazy adjlist view", IGRAPH_ENOMEM); } return 0; } /** * \function igraph_lazy_adjlist_destroy * Deallocate memory * * Free all allocated memory for a lazy adjacency list. * \param al The adjacency list to deallocate. * * Time complexity: depends on the memory management. */ void igraph_lazy_adjlist_destroy(igraph_lazy_adjlist_t *al) { igraph_lazy_adjlist_clear(al); igraph_Free(al->adjs); } /** * \function igraph_lazy_adjlist_clear * Removes all edges from a lazy adjacency list. * * \param al The lazy adjacency list. * Time complexity: depends on memory management, typically O(n), where n is * the total number of elements in the adjacency list. */ void igraph_lazy_adjlist_clear(igraph_lazy_adjlist_t *al) { long int i, n = al->length; for (i = 0; i < n; i++) { if (al->adjs[i] != 0) { igraph_vector_destroy(al->adjs[i]); igraph_Free(al->adjs[i]); } } } igraph_vector_t *igraph_lazy_adjlist_get_real(igraph_lazy_adjlist_t *al, igraph_integer_t pno) { igraph_integer_t no = pno; int ret; if (al->adjs[no] == 0) { al->adjs[no] = igraph_Calloc(1, igraph_vector_t); if (al->adjs[no] == 0) { igraph_error("Lazy adjlist failed", __FILE__, __LINE__, IGRAPH_ENOMEM); } ret = igraph_vector_init(al->adjs[no], 0); if (ret != 0) { igraph_error("", __FILE__, __LINE__, ret); } ret = igraph_neighbors(al->graph, al->adjs[no], no, al->mode); if (ret != 0) { igraph_error("", __FILE__, __LINE__, ret); } if (al->simplify == IGRAPH_SIMPLIFY) { igraph_vector_t *v = al->adjs[no]; long int i, p = 0, n = igraph_vector_size(v); for (i = 0; i < n; i++) { if (VECTOR(*v)[i] != no && (i == n - 1 || VECTOR(*v)[i + 1] != VECTOR(*v)[i])) { VECTOR(*v)[p] = VECTOR(*v)[i]; p++; } } igraph_vector_resize(v, p); } } return al->adjs[no]; } /** * \function igraph_lazy_adjedgelist_init * Initializes a lazy incidence list of edges * * This function was superseded by \ref igraph_lazy_inclist_init() in igraph 0.6. * Please use \ref igraph_lazy_inclist_init() instead of this function. * * * Deprecated in version 0.6. */ int igraph_lazy_adjedgelist_init(const igraph_t *graph, igraph_lazy_inclist_t *il, igraph_neimode_t mode) { IGRAPH_WARNING("igraph_lazy_adjedgelist_init() is deprecated, use " "igraph_lazy_inclist_init() instead"); return igraph_lazy_inclist_init(graph, il, mode); } /** * \function igraph_lazy_adjedgelist_destroy * Frees all memory allocated for an incidence list. * * This function was superseded by \ref igraph_lazy_inclist_destroy() in igraph 0.6. * Please use \ref igraph_lazy_inclist_destroy() instead of this function. * * * Deprecated in version 0.6. */ void igraph_lazy_adjedgelist_destroy(igraph_lazy_inclist_t *il) { IGRAPH_WARNING("igraph_lazy_adjedgelist_destroy() is deprecated, use " "igraph_lazy_inclist_destroy() instead"); igraph_lazy_inclist_destroy(il); } igraph_vector_t *igraph_lazy_adjedgelist_get_real(igraph_lazy_adjedgelist_t *il, igraph_integer_t pno) { IGRAPH_WARNING("igraph_lazy_adjedgelist_get_real() is deprecated, use " "igraph_lazy_inclist_get_real() instead"); return igraph_lazy_inclist_get_real(il, pno); } /** * \function igraph_lazy_inclist_init * Initializes a lazy incidence list of edges * * Create a lazy incidence list for edges. This function only * allocates some memory for storing the vectors of an incidence list, * but the incident edges are not queried, only when \ref * igraph_lazy_inclist_get() is called. * \param graph The input graph. * \param al Pointer to an uninitialized incidence list. * \param mode Constant, it gives whether incoming edges * (IGRAPH_IN), outgoing edges * (IGRPAH_OUT) or both types of edges * (IGRAPH_ALL) are considered. It is ignored for * undirected graphs. * \return Error code. * * Time complexity: O(|V|), the number of vertices, possibly. But it * also depends on the underlying memory management. */ int igraph_lazy_inclist_init(const igraph_t *graph, igraph_lazy_inclist_t *al, igraph_neimode_t mode) { if (mode != IGRAPH_IN && mode != IGRAPH_OUT && mode != IGRAPH_ALL) { IGRAPH_ERROR("Cannot create lazy incidence list view", IGRAPH_EINVMODE); } if (!igraph_is_directed(graph)) { mode = IGRAPH_ALL; } al->mode = mode; al->graph = graph; al->length = igraph_vcount(graph); al->incs = igraph_Calloc(al->length, igraph_vector_t*); if (al->incs == 0) { IGRAPH_ERROR("Cannot create lazy incidence list view", IGRAPH_ENOMEM); } return 0; } /** * \function igraph_lazy_inclist_destroy * Deallocates memory * * Frees all allocated memory for a lazy incidence list. * \param al The incidence list to deallocate. * * Time complexity: depends on memory management. */ void igraph_lazy_inclist_destroy(igraph_lazy_inclist_t *il) { igraph_lazy_inclist_clear(il); igraph_Free(il->incs); } /** * \function igraph_lazy_inclist_clear * Removes all edges from a lazy incidence list. * * \param il The lazy incidence list. * Time complexity: depends on memory management, typically O(n), where n is * the total number of elements in the incidence list. */ void igraph_lazy_inclist_clear(igraph_lazy_inclist_t *il) { long int i, n = il->length; for (i = 0; i < n; i++) { if (il->incs[i] != 0) { igraph_vector_destroy(il->incs[i]); igraph_Free(il->incs[i]); } } } igraph_vector_t *igraph_lazy_inclist_get_real(igraph_lazy_inclist_t *il, igraph_integer_t pno) { igraph_integer_t no = pno; int ret; if (il->incs[no] == 0) { il->incs[no] = igraph_Calloc(1, igraph_vector_t); if (il->incs[no] == 0) { igraph_error("Lazy incidence list query failed", __FILE__, __LINE__, IGRAPH_ENOMEM); } ret = igraph_vector_init(il->incs[no], 0); if (ret != 0) { igraph_error("", __FILE__, __LINE__, ret); } ret = igraph_incident(il->graph, il->incs[no], no, il->mode); if (ret != 0) { igraph_error("", __FILE__, __LINE__, ret); } } return il->incs[no]; } python-igraph-0.8.0/vendor/source/igraph/src/foreign-dl-header.h0000644000076500000240000000246713614300625025034 0ustar tamasstaff00000000000000/* IGraph library. Copyright (C) 2009-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_types.h" #include "igraph_types_internal.h" typedef enum { IGRAPH_DL_MATRIX, IGRAPH_DL_EDGELIST1, IGRAPH_DL_NODELIST1 } igraph_i_dl_type_t; typedef struct { void *scanner; int eof; int mode; long int n; long int from, to; igraph_vector_t edges; igraph_vector_t weights; igraph_strvector_t labels; igraph_trie_t trie; igraph_i_dl_type_t type; char errmsg[300]; } igraph_i_dl_parsedata_t; python-igraph-0.8.0/vendor/source/igraph/src/igraph_heap.c0000644000076500000240000000331713614300625024015 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2007-2012 Gabor Csardi 334 Harvard street, Cambridge, MA 02139 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "igraph_types.h" #include "igraph_heap.h" #define BASE_IGRAPH_REAL #define HEAP_TYPE_MAX #include "igraph_pmt.h" #include "heap.pmt" #include "igraph_pmt_off.h" #undef HEAP_TYPE_MAX #define HEAP_TYPE_MIN #include "igraph_pmt.h" #include "heap.pmt" #include "igraph_pmt_off.h" #undef HEAP_TYPE_MIN #undef BASE_IGRAPH_REAL #define BASE_LONG #define HEAP_TYPE_MAX #include "igraph_pmt.h" #include "heap.pmt" #include "igraph_pmt_off.h" #undef HEAP_TYPE_MAX #define HEAP_TYPE_MIN #include "igraph_pmt.h" #include "heap.pmt" #include "igraph_pmt_off.h" #undef HEAP_TYPE_MIN #undef BASE_LONG #define BASE_CHAR #define HEAP_TYPE_MAX #include "igraph_pmt.h" #include "heap.pmt" #include "igraph_pmt_off.h" #undef HEAP_TYPE_MAX #define HEAP_TYPE_MIN #include "igraph_pmt.h" #include "heap.pmt" #include "igraph_pmt_off.h" #undef HEAP_TYPE_MIN #undef BASE_CHAR python-igraph-0.8.0/vendor/source/igraph/src/scg_approximate_methods.c0000644000076500000240000001420713614300625026456 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2011-12 Gabor Csardi 334 Harvard st, Cambridge, MA, 02138 USA This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ /* * SCGlib : A C library for the spectral coarse graining of matrices * as described in the paper: Shrinking Matrices while preserving their * eigenpairs with Application to the Spectral Coarse Graining of Graphs. * Preprint available at * * Copyright (C) 2008 David Morton de Lachapelle * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 2 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA * 02110-1301 USA * * DESCRIPTION * ----------- * The intervals_method and intervals_plus_kmeans implements the * methods of sec. 5.3.2 and sec. 5.3.3 of the above reference. * They take an eigenvector 'v' as parameter and a vector 'breaks' * of length 'nb', which provide the intervals used to cut 'v'. * Then all components of 'v' that fall into the same interval are * assigned the same group label in 'gr'. The group labels are * positive consecutive integers starting from 0. * The intervals_method function is adapted from bincode of the R * base package. * The intervals_plus_kmeans is initialized with regularly-spaced * breaks, which rougly corresponds to the intervals_method. Then * kmeans minimizes iteratively the objective function until it gets * stuck in a (usually) local minimum, or until 'itermax' is reached. * So far, the breaks_computation function allows computation of * constant bins, as used in intervals_method, and of equidistant * centers as used in intervals_plus_kmeans. */ #include "igraph_error.h" #include "igraph_types.h" #include "scg_headers.h" #include "igraph_memory.h" #include "igraph_vector.h" int igraph_i_intervals_plus_kmeans(const igraph_vector_t *v, int *gr, int n, int n_interv, int maxiter) { int i; igraph_vector_t centers; IGRAPH_VECTOR_INIT_FINALLY(¢ers, n_interv); igraph_i_breaks_computation(v, ¢ers, n_interv, 2); IGRAPH_CHECK(igraph_i_kmeans_Lloyd(v, n, 1, ¢ers, n_interv, gr, maxiter)); /*renumber the groups*/ for (i = 0; i < n; i++) { gr[i] = gr[i] - 1; } igraph_vector_destroy(¢ers); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_i_intervals_method(const igraph_vector_t *v, int *gr, int n, int n_interv) { int i, lo, hi, new; const int lft = 1; const int include_border = 1; igraph_vector_t breaks; IGRAPH_VECTOR_INIT_FINALLY(&breaks, n_interv + 1); IGRAPH_CHECK(igraph_i_breaks_computation(v, &breaks, n_interv + 1, 1)); for (i = 0; i < n; i++) { lo = 0; hi = n_interv; if (VECTOR(*v)[i] < VECTOR(breaks)[lo] || VECTOR(breaks)[hi] < VECTOR(*v)[i] || (VECTOR(*v)[i] == VECTOR(breaks)[lft ? hi : lo] && !include_border)) { /* Do nothing */ } else { while (hi - lo >= 2) { new = (hi + lo) / 2; if (VECTOR(*v)[i] > VECTOR(breaks)[new] || (lft && VECTOR(*v)[i] == VECTOR(breaks)[new])) { lo = new; } else { hi = new; } } gr[i] = lo; } } igraph_vector_destroy(&breaks); IGRAPH_FINALLY_CLEAN(1); return 0; } int igraph_i_breaks_computation(const igraph_vector_t *v, igraph_vector_t *breaks, int nb, int method) { int i; igraph_real_t eps, vmin, vmax; igraph_vector_minmax(v, &vmin, &vmax); if (vmax == vmin) { IGRAPH_ERROR("There is only one (repeated) value in argument 'v' " "of bin_size_computation()", IGRAPH_EINVAL); } if (nb < 2) { IGRAPH_ERROR("'nb' in bin_size_computation() must be >= 2", IGRAPH_EINVAL); } switch (method) { case 1: /* constant bins for fixed-size intervals method */ eps = (vmax - vmin) / (igraph_real_t)(nb - 1); VECTOR(*breaks)[0] = vmin; for (i = 1; i < nb - 1; i++) { VECTOR(*breaks)[i] = VECTOR(*breaks)[i - 1] + eps; } VECTOR(*breaks)[nb - 1] = vmax; break; case 2: /* equidistant centers for kmeans */ eps = (vmax - vmin) / (igraph_real_t)nb; VECTOR(*breaks)[0] = vmin + eps / 2.; for (i = 1; i < nb; i++) { VECTOR(*breaks)[i] = VECTOR(*breaks)[i - 1] + eps; } break; /* TODO: implement logarithmic binning for power-law-like distributions */ default: IGRAPH_ERROR("Internal SCG error, this should ot happen", IGRAPH_FAILURE); } return 0; } python-igraph-0.8.0/vendor/source/igraph/src/coloring.c0000644000076500000240000001130113614300625023352 0ustar tamasstaff00000000000000 #include "igraph_coloring.h" #include "igraph_interface.h" #include "igraph_adjlist.h" #include "igraph_interrupt_internal.h" #include "igraph_types_internal.h" int igraph_i_vertex_coloring_greedy_cn(const igraph_t *graph, igraph_vector_int_t *colors) { long i, vertex, maxdeg; long vc = igraph_vcount(graph); igraph_2wheap_t cn; /* indexed heap storing number of already coloured neighbours */ igraph_vector_int_t neigh_colors; igraph_adjlist_t adjlist; IGRAPH_CHECK(igraph_vector_int_resize(colors, vc)); igraph_vector_int_fill(colors, 0); /* Nothing to do for 0 or 1 vertices. * Remember that colours are integers starting from 0, * and the 'colors' vector is already 0-initialized above. */ if (vc <= 1) { return IGRAPH_SUCCESS; } IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist, IGRAPH_ALL)); IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist); /* find maximum degree and a corresponding vertex */ { igraph_vector_t degree; IGRAPH_CHECK(igraph_vector_init(°ree, 0)); IGRAPH_FINALLY(igraph_vector_destroy, °ree); IGRAPH_CHECK(igraph_degree(graph, °ree, igraph_vss_all(), IGRAPH_ALL, 0)); vertex = igraph_vector_which_max(°ree); maxdeg = VECTOR(degree)[vertex]; igraph_vector_destroy(°ree); IGRAPH_FINALLY_CLEAN(1); } IGRAPH_CHECK(igraph_vector_int_init(&neigh_colors, 0)); IGRAPH_CHECK(igraph_vector_int_reserve(&neigh_colors, maxdeg)); IGRAPH_FINALLY(igraph_vector_int_destroy, &neigh_colors); IGRAPH_CHECK(igraph_2wheap_init(&cn, vc)); IGRAPH_FINALLY(igraph_2wheap_destroy, &cn); for (i = 0; i < vc; ++i) if (i != vertex) { igraph_2wheap_push_with_index(&cn, i, 0); /* should not fail since memory was already reserved */ } while (1) { igraph_vector_int_t *neighbors = igraph_adjlist_get(&adjlist, vertex); long neigh_count = igraph_vector_int_size(neighbors); /* colour current vertex */ { igraph_integer_t col; IGRAPH_CHECK(igraph_vector_int_resize(&neigh_colors, neigh_count)); for (i = 0; i < neigh_count; ++i) { VECTOR(neigh_colors)[i] = VECTOR(*colors)[ VECTOR(*neighbors)[i] ]; } igraph_vector_int_sort(&neigh_colors); i = 0; col = 0; do { while (i < neigh_count && VECTOR(neigh_colors)[i] == col) { i++; } col++; } while (i < neigh_count && VECTOR(neigh_colors)[i] == col); VECTOR(*colors)[vertex] = col; } /* increment number of coloured neighbours for each neighbour of vertex */ for (i = 0; i < neigh_count; ++i) { long idx = VECTOR(*neighbors)[i]; if (igraph_2wheap_has_elem(&cn, idx)) { igraph_2wheap_modify(&cn, idx, igraph_2wheap_get(&cn, idx) + 1); } } /* stop if no more vertices left to colour */ if (igraph_2wheap_empty(&cn)) { break; } igraph_2wheap_delete_max_index(&cn, &vertex); IGRAPH_ALLOW_INTERRUPTION(); } /* subtract 1 from each colour value, so that colours start at 0 */ igraph_vector_int_add_constant(colors, -1); /* free data structures */ igraph_vector_int_destroy(&neigh_colors); igraph_adjlist_destroy(&adjlist); igraph_2wheap_destroy(&cn); IGRAPH_FINALLY_CLEAN(3); return IGRAPH_SUCCESS; } /** * \function igraph_vertex_coloring_greedy * \brief Computes a vertex coloring using a greedy algorithm. * * * This function assigns a "color"---represented as a non-negative integer---to * each vertex of the graph in such a way that neighboring vertices never have * the same color. The obtained coloring is not necessarily minimal. * * * Vertices are colored one by one, choosing the smallest color index that * differs from that of already colored neighbors. * Colors are represented with non-negative integers 0, 1, 2, ... * * \param graph The input graph. * \param colors Pointer to an initialized integer vector. The vertex colors will be stored here. * \param heuristic The vertex ordering heuristic to use during greedy coloring. See \ref igraph_coloring_greedy_t * * \return Error code. * * \example examples/simple/igraph_coloring.c */ int igraph_vertex_coloring_greedy(const igraph_t *graph, igraph_vector_int_t *colors, igraph_coloring_greedy_t heuristic) { switch (heuristic) { case IGRAPH_COLORING_GREEDY_COLORED_NEIGHBORS: return igraph_i_vertex_coloring_greedy_cn(graph, colors); default: return IGRAPH_EINVAL; } } python-igraph-0.8.0/src/0000755000076500000240000000000013617375000015331 5ustar tamasstaff00000000000000python-igraph-0.8.0/src/igraph/0000755000076500000240000000000013617375000016603 5ustar tamasstaff00000000000000python-igraph-0.8.0/src/igraph/configuration.py0000644000076500000240000004047313614523316022036 0ustar tamasstaff00000000000000# vim:ts=4:sw=4:sts=4:et # -*- coding: utf-8 -*- """ Configuration framework for igraph. igraph has some parameters which usually affect the behaviour of many functions. This module provides the framework for altering and querying igraph parameters as well as saving them to and retrieving them from disk. """ __license__ = """\ Copyright (C) 2006-2012 Tamás Nepusz Pázmány Péter sétány 1/a, 1117 Budapest, Hungary This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA """ import sys if sys.version_info < (3, 2): from ConfigParser import SafeConfigParser as ConfigParser else: from configparser import ConfigParser import platform import os.path def get_platform_image_viewer(): """Returns the path of an image viewer on the given platform""" plat = platform.system() if plat == "Darwin": # Most likely Mac OS X return "open" elif plat == "Linux": # Linux has a whole lot of choices, try to find one choices = ["eog", "gthumb", "gqview", "kuickshow", "xnview", "display", "gpicview", "gwenview", "qiv", "gimv", "ristretto", "geeqie", "eom"] paths = ["/usr/bin", "/bin"] for path in paths: for choice in choices: full_path = os.path.join(path, choice) if os.path.isfile(full_path): return full_path return "" elif plat == "Windows" or plat == "Microsoft": # Thanks to Dale Hunscher # Use the built-in Windows image viewer, if available return "start" else: # Unknown system return "" class Configuration(object): """Class representing igraph configuration details. General ideas ============= The configuration of igraph is stored in the form of name-value pairs. This object provides an interface to the configuration data using the syntax known from dict: >>> c=Configuration() >>> c["general.verbose"] = True >>> print c["general.verbose"] True Configuration keys are organized into sections, and the name to be used for a given key is always in the form C{section.keyname}, like C{general.verbose} in the example above. In that case, C{general} is the name of the configuration section, and C{verbose} is the name of the key. If the name of the section is omitted, it defaults to C{general}, so C{general.verbose} can be referred to as C{verbose}: >>> c=Configuration() >>> c["verbose"] = True >>> print c["general.verbose"] True User-level configuration is stored in C{~/.igraphrc} per default on Linux and Mac OS X systems, or in C{C:\\Documents and Settings\\username\\.igraphrc} on Windows systems. However, this configuration is read only when C{igraph} is launched through its shell interface defined in L{igraph.app.shell}. This behaviour might change before version 1.0. Known configuration keys ======================== The known configuration keys are presented below, sorted by section. When referring to them in program code, don't forget to add the section name, expect in the case of section C{general}. General settings ---------------- These settings are all stored in section C{general}. - B{shells}: the list of preferred Python shells to be used with the command-line C{igraph} script. The shells in the list are tried one by one until any of them is found on the system. C{igraph} functions are then imported into the main namespace of the shell and the shell is launched. Known shells and their respective class names to be used can be found in L{igraph.app.shell}. Example: C{IPythonShell, ClassicPythonShell}. This is the default, by the way. - B{verbose}: whether L{igraph} should talk more than really necessary. For instance, if set to C{True}, some functions display progress bars. Application settings -------------------- These settings specify the external applications that are possibly used by C{igraph}. They are all stored in section C{apps}. - B{image_viewer}: image viewer application. If set to an empty string, it will be determined automatically from the platform C{igraph} runs on. On Mac OS X, it defaults to the Preview application. On Linux, it chooses a viewer from several well-known Linux viewers like C{gthumb}, C{kuickview} and so on (see the source code for the full list). On Windows, it defaults to the system's built-in image viewer. Plotting settings ----------------- These settings specify the default values used by plotting functions. They are all stored in section C{plotting}. - B{layout}: default graph layout algorithm to be used. - B{mark_groups}: whether to mark the clusters by polygons when plotting a clustering object. - B{palette}: default palette to be used for converting integer numbers to colors. See L{colors.Palette} for more information. Valid palette names are stored in C{colors.palettes}. - B{wrap_labels}: whether to try to wrap the labels of the vertices automatically if they don't fit within the vertex. Default: C{False}. Shell settings -------------- These settings specify options for external environments in which igraph is embedded (e.g., IPython and its Qt console). These settings are stored in section C{shell}. - B{ipython.inlining.Plot}: whether to show instances of the L{Plot} class inline in IPython's console if the console supports it. Default: C{True} @undocumented: _item_to_section_key, _types, _sections, _definitions, _instance """ # pylint: disable-msg=R0903 # R0903: too few public methods class Types(object): """Static class for the implementation of custom getter/setter functions for configuration keys""" def __init__(self): pass @staticmethod def setboolean(obj, section, key, value): """Sets a boolean value in the given configuration object. @param obj: a configuration object @param section: the section of the value to be set @param key: the key of the value to be set @param value: the value itself. C{0}, C{false}, C{no} and C{off} means false, C{1}, C{true}, C{yes} and C{on} means true, everything else results in a C{ValueError} being thrown. Values are case insensitive """ value = str(value).lower() if value in ("0", "false", "no", "off"): value = "false" elif value in ("1", "true", "yes", "on"): value = "true" else: raise ValueError("value cannot be coerced to boolean type") obj.set(section, key, value) @staticmethod def setint(obj, section, key, value): """Sets an integer value in the given configuration object. @param obj: a configuration object @param section: the section of the value to be set @param key: the key of the value to be set @param value: the value itself. """ obj.set(section, key, str(int(value))) @staticmethod def setfloat(obj, section, key, value): """Sets a float value in the given configuration object. Note that float values are converted to strings in the configuration object, which may lead to some precision loss. @param obj: a configuration object @param section: the section of the value to be set @param key: the key of the value to be set @param value: the value itself. """ obj.set(section, key, str(float(value))) _types = { "boolean": { "getter": ConfigParser.getboolean, "setter": Types.setboolean }, "int": { "getter": ConfigParser.getint, "setter": Types.setint }, "float": { "getter": ConfigParser.getfloat, "setter": Types.setfloat } } _sections = ("general", "apps", "plotting", "remote", "shell") _definitions = { "general.shells": { "default": "IPythonShell,ClassicPythonShell" }, "general.verbose": { "default": True, "type": "boolean" }, "apps.image_viewer": { "default": get_platform_image_viewer() }, "plotting.layout": { "default": "auto" }, "plotting.mark_groups": { "default": False, "type": "boolean" }, "plotting.palette": { "default": "gray" }, "plotting.wrap_labels": { "default": False, "type": "boolean" }, "shell.ipython.inlining.Plot": { "default": True, "type": "boolean" } } # The singleton instance we are using throughout other modules _instance = None def __init__(self, filename=None): """Creates a new configuration instance. @param filename: file or file pointer to be read. Can be omitted. """ self._config = ConfigParser() self._filename = None # Create default sections for sec in self._sections: self._config.add_section(sec) # Create default values for name, definition in self._definitions.iteritems(): if "default" in definition: self[name] = definition["default"] if filename is not None: self.load(filename) @property def filename(self): """Returns the filename associated to the object. It is usually the name of the configuration file that was used when creating the object. L{Configuration.load} always overwrites it with the filename given to it. If C{None}, the configuration was either created from scratch or it was updated from a stream without name information.""" return self._filename def _get(self, section, key): """Internal function that returns the value of a given key in a given section.""" definition = self._definitions.get("%s.%s" % (section, key), {}) getter = None if "type" in definition: getter = self._types[definition["type"]].get("getter") if getter is None: getter = self._config.__class__.get return getter(self._config, section, key) @staticmethod def _item_to_section_key(item): """Converts an item description to a section-key pair. @param item: the item to be converted @return: if C{item} contains a period (C{.}), it is splitted into two parts at the first period, then the two parts are returned, so the part before the period is the section. If C{item} does not contain a period, the section is assumed to be C{general}, and the second part of the returned pair contains C{item} unchanged""" if "." in item: section, key = item.split(".", 1) else: section, key = "general", item return section, key def __contains__(self, item): """Checks whether the given configuration item is set. @param item: the configuration key to check. @return: C{True} if the key has an associated value, C{False} otherwise. """ section, key = self._item_to_section_key(item) return self._config.has_option(section, key) def __getitem__(self, item): """Returns the given configuration item. @param item: the configuration key to retrieve. @return: the configuration value""" section, key = self._item_to_section_key(item) if key == "*": # Special case: retrieving all the keys within a section and # returning it in a dict keys = self._config.items(section) return dict((key, self._get(section, key)) for key, _ in keys) else: return self._get(section, key) def __setitem__(self, item, value): """Sets the given configuration item. @param item: the configuration key to set @param value: the new value of the configuration key """ section, key = self._item_to_section_key(item) definition = self._definitions.get("%s.%s" % (section, key), {}) setter = None if "type" in definition: setter = self._types[definition["type"]].get("setter", None) if setter is None: setter = self._config.__class__.set return setter(self._config, section, key, value) def __delitem__(self, item): """Deletes the given item from the configuration. If the item has a default value, the default value is written back instead of the current value. Without a default value, the item is really deleted. """ section, key = self._item_to_section_key(item) definition = self._definitions.get("%s.%s" % (section, key), {}) if "default" in definition: self[item] = definition["default"] else: self._config.remove_option(section, key) def has_key(self, item): """Checks if the configuration has a given key. @param item: the key being sought""" if "." in item: section, key = item.split(".", 1) else: section, key = "general", item return self._config.has_option(section, key) def load(self, stream=None): """Loads the configuration from the given file. @param stream: name of a file or a file object. The configuration will be loaded from here. Can be omitted, in this case, the user-level configuration is loaded. """ stream = stream or get_user_config_file() if isinstance(stream, basestring): stream = open(stream, "r") file_was_open = True self._config.readfp(stream) self._filename = getattr(stream, "name", None) if file_was_open: stream.close() def save(self, stream=None): """Saves the configuration. @param stream: name of a file or a file object. The configuration will be saved there. Can be omitted, in this case, the user-level configuration file will be overwritten. """ stream = stream or get_user_config_file() if not hasattr(stream, "write") or not hasattr(stream, "close"): stream = open(stream, "w") file_was_open = True self._config.write(stream) if file_was_open: stream.close() @classmethod def instance(cls): """Returns the single instance of the configuration object.""" if cls._instance is None: cfile = get_user_config_file() try: config = cls(cfile) except IOError: # No config file yet, whatever config = cls() cls._instance = config return cls._instance def get_user_config_file(): """Returns the path where the user-level configuration file is stored""" return os.path.expanduser("~/.igraphrc") def init(): """Default mechanism to initiate igraph configuration This method loads the user-specific configuration file from the user's home directory, or if it does not exist, creates a default configuration. The method is safe to be called multiple times, it will not parse the configuration file twice. @return: the L{Configuration} object loaded or created.""" return Configuration.instance() python-igraph-0.8.0/src/igraph/drawing/0000755000076500000240000000000013617375000020236 5ustar tamasstaff00000000000000python-igraph-0.8.0/src/igraph/drawing/shapes.py0000644000076500000240000004157313104627150022102 0ustar tamasstaff00000000000000# vim:ts=4:sw=4:sts=4:et # -*- coding: utf-8 -*- """ Shape drawing classes for igraph Vertex shapes in igraph are usually referred to by short names like C{"rect"} or C{"circle"}. This module contains the classes that implement the actual drawing routines for these shapes, and a resolver class that determines the appropriate shape drawer class given the short name. Classes that are derived from L{ShapeDrawer} in this module are automatically registered by L{ShapeDrawerDirectory}. If you implement a custom shape drawer, you must register it in L{ShapeDrawerDirectory} manually if you wish to refer to it by a name in the C{shape} attribute of vertices. """ from __future__ import division __all__ = ["ShapeDrawerDirectory"] __license__ = u"""\ Copyright (C) 2006-2012 Tamás Nepusz Pázmány Péter sétány 1/a, 1117 Budapest, Hungary This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA """ from math import atan2, copysign, cos, pi, sin import sys from igraph.drawing.baseclasses import AbstractCairoDrawer from igraph.drawing.utils import Point from igraph.utils import consecutive_pairs class ShapeDrawer(object): """Static class, the ancestor of all vertex shape drawer classes. Custom shapes must implement at least the C{draw_path} method of the class. The method I{must not} stroke or fill, it should just set up the current Cairo path appropriately.""" @staticmethod def draw_path(ctx, center_x, center_y, width, height=None): """Draws the path of the shape on the given Cairo context, without stroking or filling it. This method must be overridden in derived classes implementing custom shapes and declared as a static method using C{staticmethod(...)}. @param ctx: the context to draw on @param center_x: the X coordinate of the center of the object @param center_y: the Y coordinate of the center of the object @param width: the width of the object @param height: the height of the object. If C{None}, equals to the width. """ raise NotImplementedError("abstract class") # pylint: disable-msg=W0613 @staticmethod def intersection_point(center_x, center_y, source_x, source_y, \ width, height=None): """Determines where the shape centered at (center_x, center_y) intersects with a line drawn from (source_x, source_y) to (center_x, center_y). Can be overridden in derived classes. Must always be defined as a static method using C{staticmethod(...)} @param width: the width of the shape @param height: the height of the shape. If C{None}, defaults to the width @return: the intersection point (the closest to (source_x, source_y) if there are more than one) or (center_x, center_y) if there is no intersection """ return center_x, center_y class NullDrawer(ShapeDrawer): """Static drawer class which draws nothing. This class is used for graph vertices with unknown shapes""" names = ["null", "none", "empty", "hidden", ""] @staticmethod def draw_path(ctx, center_x, center_y, width, height=None): """Draws nothing.""" pass class RectangleDrawer(ShapeDrawer): """Static class which draws rectangular vertices""" names = "rectangle rect rectangular square box" @staticmethod def draw_path(ctx, center_x, center_y, width, height=None): """Draws a rectangle-shaped path on the Cairo context without stroking or filling it. @see: ShapeDrawer.draw_path""" height = height or width ctx.rectangle(center_x - width/2, center_y - height/2, width, height) # pylint: disable-msg=C0103, R0911 # R0911: too many return statements @staticmethod def intersection_point(center_x, center_y, source_x, source_y, \ width, height=None): """Determines where the rectangle centered at (center_x, center_y) having the given width and height intersects with a line drawn from (source_x, source_y) to (center_x, center_y). @see: ShapeDrawer.intersection_point""" height = height or width delta_x, delta_y = center_x-source_x, center_y-source_y if delta_x == 0 and delta_y == 0: return center_x, center_y if delta_y > 0 and delta_x <= delta_y and delta_x >= -delta_y: # this is the top edge ry = center_y - height/2 ratio = (height/2) / delta_y return center_x-ratio*delta_x, ry if delta_y < 0 and delta_x <= -delta_y and delta_x >= delta_y: # this is the bottom edge ry = center_y + height/2 ratio = (height/2) / -delta_y return center_x-ratio*delta_x, ry if delta_x > 0 and delta_y <= delta_x and delta_y >= -delta_x: # this is the left edge rx = center_x - width/2 ratio = (width/2) / delta_x return rx, center_y-ratio*delta_y if delta_x < 0 and delta_y <= -delta_x and delta_y >= delta_x: # this is the right edge rx = center_x + width/2 ratio = (width/2) / -delta_x return rx, center_y-ratio*delta_y if delta_x == 0: if delta_y > 0: return center_x, center_y - height/2 return center_x, center_y + height/2 if delta_y == 0: if delta_x > 0: return center_x - width/2, center_y return center_x + width/2, center_y class CircleDrawer(ShapeDrawer): """Static class which draws circular vertices""" names = "circle circular" @staticmethod def draw_path(ctx, center_x, center_y, width, height=None): """Draws a circular path on the Cairo context without stroking or filling it. Height is ignored, it is the width that determines the diameter of the circle. @see: ShapeDrawer.draw_path""" ctx.arc(center_x, center_y, width/2, 0, 2*pi) @staticmethod def intersection_point(center_x, center_y, source_x, source_y, \ width, height=None): """Determines where the circle centered at (center_x, center_y) intersects with a line drawn from (source_x, source_y) to (center_x, center_y). @see: ShapeDrawer.intersection_point""" height = height or width angle = atan2(center_y-source_y, center_x-source_x) return center_x-width/2 * cos(angle), \ center_y-height/2* sin(angle) class UpTriangleDrawer(ShapeDrawer): """Static class which draws upright triangles""" names = "triangle triangle-up up-triangle arrow arrow-up up-arrow" @staticmethod def draw_path(ctx, center_x, center_y, width, height=None): """Draws an upright triangle on the Cairo context without stroking or filling it. @see: ShapeDrawer.draw_path""" height = height or width ctx.move_to(center_x-width/2, center_y+height/2) ctx.line_to(center_x, center_y-height/2) ctx.line_to(center_x+width/2, center_y+height/2) ctx.close_path() @staticmethod def intersection_point(center_x, center_y, source_x, source_y, \ width, height=None): """Determines where the triangle centered at (center_x, center_y) intersects with a line drawn from (source_x, source_y) to (center_x, center_y). @see: ShapeDrawer.intersection_point""" # TODO: finish it properly height = height or width return center_x, center_y class DownTriangleDrawer(ShapeDrawer): """Static class which draws triangles pointing down""" names = "down-triangle triangle-down arrow-down down-arrow" @staticmethod def draw_path(ctx, center_x, center_y, width, height=None): """Draws a triangle on the Cairo context without stroking or filling it. @see: ShapeDrawer.draw_path""" height = height or width ctx.move_to(center_x-width/2, center_y-height/2) ctx.line_to(center_x, center_y+height/2) ctx.line_to(center_x+width/2, center_y-height/2) ctx.close_path() @staticmethod def intersection_point(center_x, center_y, source_x, source_y, \ width, height=None): """Determines where the triangle centered at (center_x, center_y) intersects with a line drawn from (source_x, source_y) to (center_x, center_y). @see: ShapeDrawer.intersection_point""" # TODO: finish it properly height = height or width return center_x, center_y class DiamondDrawer(ShapeDrawer): """Static class which draws diamonds (i.e. rhombuses)""" names = "diamond rhombus" @staticmethod def draw_path(ctx, center_x, center_y, width, height=None): """Draws a rhombus on the Cairo context without stroking or filling it. @see: ShapeDrawer.draw_path""" height = height or width ctx.move_to(center_x-width/2, center_y) ctx.line_to(center_x, center_y+height/2) ctx.line_to(center_x+width/2, center_y) ctx.line_to(center_x, center_y-height/2) ctx.close_path() @staticmethod def intersection_point(center_x, center_y, source_x, source_y, \ width, height=None): """Determines where the rhombus centered at (center_x, center_y) intersects with a line drawn from (source_x, source_y) to (center_x, center_y). @see: ShapeDrawer.intersection_point""" height = height or width if height == 0 and width == 0: return center_x, center_y delta_x, delta_y = source_x - center_x, source_y - center_y # Treat edge case when delta_x = 0 if delta_x == 0: if delta_y == 0: return center_x, center_y else: return center_x, center_y + copysign(height / 2, delta_y) width = copysign(width, delta_x) height = copysign(height, delta_y) f = height / (height + width * delta_y / delta_x) return center_x + f * width / 2, center_y + (1-f) * height / 2 ##################################################################### class PolygonDrawer(AbstractCairoDrawer): """Class that is used to draw polygons. The corner points of the polygon can be set by the C{points} property of the drawer, or passed at construction time. Most drawing methods in this class also have an extra C{points} argument that can be used to override the set of points in the C{points} property.""" def __init__(self, context, bbox=(1, 1), points = []): """Constructs a new polygon drawer that draws on the given Cairo context. @param context: the Cairo context to draw on @param bbox: ignored, leave it at its default value @param points: the list of corner points """ super(PolygonDrawer, self).__init__(context, bbox) self.points = points def draw_path(self, points=None, corner_radius=0): """Sets up a Cairo path for the outline of a polygon on the given Cairo context. @param points: the coordinates of the corners of the polygon, in clockwise or counter-clockwise order, or C{None} if we are about to use the C{points} property of the class. @param corner_radius: if zero, an ordinary polygon will be drawn. If positive, the corners of the polygon will be rounded with the given radius. """ if points is None: points = self.points self.context.new_path() if len(points) < 2: # Well, a polygon must have at least two corner points return ctx = self.context if corner_radius <= 0: # No rounded corners, this is simple ctx.move_to(*points[-1]) for point in points: ctx.line_to(*point) return # Rounded corners. First, we will take each side of the # polygon and find what the corner radius should be on # each corner. If the side is longer than 2r (where r is # equal to corner_radius), the radius allowed by that side # is r; if the side is shorter, the radius is the length # of the side / 2. For each corner, the final corner radius # is the smaller of the radii on the two sides adjacent to # the corner. points = [Point(*point) for point in points] side_vecs = [v-u for u, v in consecutive_pairs(points, circular=True)] half_side_lengths = [side.length() / 2 for side in side_vecs] corner_radii = [corner_radius] * len(points) for idx in xrange(len(corner_radii)): prev_idx = -1 if idx == 0 else idx - 1 radii = [corner_radius, half_side_lengths[prev_idx], half_side_lengths[idx]] corner_radii[idx] = min(radii) # Okay, move to the last corner, adjusted by corner_radii[-1] # towards the first corner ctx.move_to(*(points[-1].towards(points[0], corner_radii[-1]))) # Now, for each point in points, draw a line towards the # corner, stopping before it in a distance of corner_radii[idx], # then draw the corner u = points[-1] for idx, (v, w) in enumerate(consecutive_pairs(points, True)): radius = corner_radii[idx] ctx.line_to(*v.towards(u, radius)) aux1 = v.towards(u, radius / 2) aux2 = v.towards(w, radius / 2) ctx.curve_to(aux1.x, aux1.y, aux2.x, aux2.y, *v.towards(w, corner_radii[idx])) u = v def draw(self, points=None): """Draws the polygon using the current stroke of the Cairo context. @param points: the coordinates of the corners of the polygon, in clockwise or counter-clockwise order, or C{None} if we are about to use the C{points} property of the class. """ self.draw_path(points) self.context.stroke() ##################################################################### class ShapeDrawerDirectory(object): """Static class that resolves shape names to their corresponding shape drawer classes. Classes that are derived from L{ShapeDrawer} in this module are automatically registered by L{ShapeDrawerDirectory} when the module is loaded for the first time. """ known_shapes = {} @classmethod def register(cls, drawer_class): """Registers the given shape drawer class under the given names. @param drawer_class: the shape drawer class to be registered """ names = drawer_class.names if isinstance(names, (str, unicode)): names = names.split() for name in names: cls.known_shapes[name] = drawer_class @classmethod def register_namespace(cls, namespace): """Registers all L{ShapeDrawer} classes in the given namespace @param namespace: a Python dict mapping names to Python objects.""" for name, value in namespace.iteritems(): if name.startswith("__"): continue if isinstance(value, type): if issubclass(value, ShapeDrawer) and value != ShapeDrawer: cls.register(value) @classmethod def resolve(cls, shape): """Given a shape name, returns the corresponding shape drawer class @param shape: the name of the shape @return: the corresponding shape drawer class @raise ValueError: if the shape is unknown """ try: return cls.known_shapes[shape] except KeyError: raise ValueError("unknown shape: %s" % shape) @classmethod def resolve_default(cls, shape, default=NullDrawer): """Given a shape name, returns the corresponding shape drawer class or the given default shape drawer if the shape name is unknown. @param shape: the name of the shape @param default: the default shape drawer to return when the shape is unknown @return: the shape drawer class corresponding to the given name or the default shape drawer class if the name is unknown """ return cls.known_shapes.get(shape, default) ShapeDrawerDirectory.register_namespace(sys.modules[__name__].__dict__) python-igraph-0.8.0/src/igraph/drawing/edge.py0000644000076500000240000004256613104627150021526 0ustar tamasstaff00000000000000""" Drawers for various edge styles in graph plots. """ __all__ = ["AbstractEdgeDrawer", "AlphaVaryingEdgeDrawer", "ArrowEdgeDrawer", "DarkToLightEdgeDrawer", "LightToDarkEdgeDrawer", "TaperedEdgeDrawer"] __license__ = "GPL" from igraph.drawing.colors import clamp from igraph.drawing.metamagic import AttributeCollectorBase from igraph.drawing.text import TextAlignment from igraph.drawing.utils import find_cairo from math import atan2, cos, pi, sin, sqrt cairo = find_cairo() class AbstractEdgeDrawer(object): """Abstract edge drawer object from which all concrete edge drawer implementations are derived.""" def __init__(self, context, palette): """Constructs the edge drawer. @param context: a Cairo context on which the edges will be drawn. @param palette: the palette that can be used to map integer color indices to colors when drawing edges """ self.context = context self.palette = palette self.VisualEdgeBuilder = self._construct_visual_edge_builder() @staticmethod def _curvature_to_float(value): """Converts values given to the 'curved' edge style argument in plotting calls to floating point values.""" if value is None or value is False: return 0.0 if value is True: return 0.5 return float(value) def _construct_visual_edge_builder(self): """Construct the visual edge builder that will collect the visual attributes of an edge when it is being drawn.""" class VisualEdgeBuilder(AttributeCollectorBase): """Builder that collects some visual properties of an edge for drawing""" _kwds_prefix = "edge_" arrow_size = 1.0 arrow_width = 1.0 color = ("#444", self.palette.get) curved = (0.0, self._curvature_to_float) label = None label_color = ("black", self.palette.get) label_size = 12.0 font = 'sans-serif' width = 1.0 return VisualEdgeBuilder def draw_directed_edge(self, edge, src_vertex, dest_vertex): """Draws a directed edge. @param edge: the edge to be drawn. Visual properties of the edge are defined by the attributes of this object. @param src_vertex: the source vertex. Visual properties are given again as attributes. @param dest_vertex: the target vertex. Visual properties are given again as attributes. """ raise NotImplementedError() def draw_loop_edge(self, edge, vertex): """Draws a loop edge. The default implementation draws a small circle. @param edge: the edge to be drawn. Visual properties of the edge are defined by the attributes of this object. @param vertex: the vertex to which the edge is attached. Visual properties are given again as attributes. """ ctx = self.context ctx.set_source_rgba(*edge.color) ctx.set_line_width(edge.width) radius = vertex.size * 1.5 center_x = vertex.position[0] + cos(pi/4) * radius / 2. center_y = vertex.position[1] - sin(pi/4) * radius / 2. ctx.arc(center_x, center_y, radius/2., 0, pi * 2) ctx.stroke() def draw_undirected_edge(self, edge, src_vertex, dest_vertex): """Draws an undirected edge. The default implementation of this method draws undirected edges as straight lines. Loop edges are drawn as small circles. @param edge: the edge to be drawn. Visual properties of the edge are defined by the attributes of this object. @param src_vertex: the source vertex. Visual properties are given again as attributes. @param dest_vertex: the target vertex. Visual properties are given again as attributes. """ if src_vertex == dest_vertex: # TODO return self.draw_loop_edge(edge, src_vertex) ctx = self.context ctx.set_source_rgba(*edge.color) ctx.set_line_width(edge.width) ctx.move_to(*src_vertex.position) if edge.curved: (x1, y1), (x2, y2) = src_vertex.position, dest_vertex.position aux1 = (2*x1+x2) / 3.0 - edge.curved * 0.5 * (y2-y1), \ (2*y1+y2) / 3.0 + edge.curved * 0.5 * (x2-x1) aux2 = (x1+2*x2) / 3.0 - edge.curved * 0.5 * (y2-y1), \ (y1+2*y2) / 3.0 + edge.curved * 0.5 * (x2-x1) ctx.curve_to(aux1[0], aux1[1], aux2[0], aux2[1], *dest_vertex.position) else: ctx.line_to(*dest_vertex.position) ctx.stroke() def get_label_position(self, edge, src_vertex, dest_vertex): """Returns the position where the label of an edge should be drawn. The default implementation returns the midpoint of the edge and an alignment that tries to avoid overlapping the label with the edge. @param edge: the edge to be drawn. Visual properties of the edge are defined by the attributes of this object. @param src_vertex: the source vertex. Visual properties are given again as attributes. @param dest_vertex: the target vertex. Visual properties are given again as attributes. @return: a tuple containing two more tuples: the desired position of the label and the desired alignment of the label, where the position is given as C{(x, y)} and the alignment is given as C{(horizontal, vertical)}. Members of the alignment tuple are taken from constants in the L{TextAlignment} class. """ # Determine the angle of the line dx = dest_vertex.position[0] - src_vertex.position[0] dy = dest_vertex.position[1] - src_vertex.position[1] if dx != 0 or dy != 0: # Note that we use -dy because the Y axis points downwards angle = atan2(-dy, dx) % (2*pi) else: angle = None # Determine the midpoint pos = ((src_vertex.position[0] + dest_vertex.position[0]) / 2., \ (src_vertex.position[1] + dest_vertex.position[1]) / 2) # Determine the alignment based on the angle pi4 = pi / 4 if angle is None: halign, valign = TextAlignment.CENTER, TextAlignment.CENTER else: index = int((angle / pi4) % 8) halign = [TextAlignment.RIGHT, TextAlignment.RIGHT, TextAlignment.RIGHT, TextAlignment.RIGHT, TextAlignment.LEFT, TextAlignment.LEFT, TextAlignment.LEFT, TextAlignment.LEFT][index] valign = [TextAlignment.BOTTOM, TextAlignment.CENTER, TextAlignment.CENTER, TextAlignment.TOP, TextAlignment.TOP, TextAlignment.CENTER, TextAlignment.CENTER, TextAlignment.BOTTOM][index] return pos, (halign, valign) class ArrowEdgeDrawer(AbstractEdgeDrawer): """Edge drawer implementation that draws undirected edges as straight lines and directed edges as arrows. """ def draw_directed_edge(self, edge, src_vertex, dest_vertex): if src_vertex == dest_vertex: # TODO return self.draw_loop_edge(edge, src_vertex) ctx = self.context (x1, y1), (x2, y2) = src_vertex.position, dest_vertex.position (x_src, y_src), (x_dest, y_dest) = src_vertex.position, dest_vertex.position def bezier_cubic(x0,y0, x1,y1, x2,y2, x3,y3, t): """ Computes the Bezier curve from point (x0,y0) to (x3,y3) via control points (x1,y1) and (x2,y2) with parameter t. """ xt = (1.0 - t) ** 3 * x0 + 3. *t * (1.0 - t) ** 2 * x1 + 3. * t**2 * (1. - t) * x2 + t**3 * x3 yt = (1.0 - t) ** 3 * y0 + 3. *t * (1.0 - t) ** 2 * y1 + 3. * t**2 * (1. - t) * y2 + t**3 * y3 return xt,yt def euclidean_distance(x1,y1,x2,y2): """ Computes the Euclidean distance between points (x1,y1) and (x2,y2). """ return sqrt( (1.0*x1-x2) **2 + (1.0*y1-y2) **2 ) def intersect_bezier_circle(x0,y0, x1,y1, x2,y2, x3,y3, radius, max_iter=10): """ Binary search solver for finding the intersection of a Bezier curve and a circle centered at the curve's end point. Returns the x,y of the intersection point. TODO: implement safeguard to ensure convergence in ALL possible cases. """ precision = radius / 20.0 source_target_distance = euclidean_distance(x0,y0,x3,y3) radius = float(radius) t0 = 1.0 t1 = 1.0 - radius / source_target_distance xt0, yt0 = x3, y3 xt1, yt1 = bezier_cubic(x0,y0, x1,y1, x2,y2, x3,y3, t1) distance_t0 = 0 distance_t1 = euclidean_distance(x3,y3, xt1,yt1) counter = 0 while abs(distance_t1 - radius) > precision and counter < max_iter: if ((distance_t1-radius) > 0) != ((distance_t0-radius) > 0): t_new = (t0 + t1)/2.0 else: if (abs(distance_t1 - radius) < abs(distance_t0 - radius)): # If t1 gets us closer to the circumference step in the same direction t_new = t1 + (t1 - t0)/ 2.0 else: t_new = t1 - (t1 - t0) t_new = 1 if t_new > 1 else (0 if t_new < 0 else t_new) t0,t1 = t1,t_new distance_t0 = distance_t1 xt1, yt1 = bezier_cubic(x0,y0, x1,y1, x2,y2, x3,y3, t1) distance_t1 = euclidean_distance(x3,y3, xt1,yt1) counter += 1 return bezier_cubic(x0,y0, x1,y1, x2,y2, x3,y3, t1) # Draw the edge ctx.set_source_rgba(*edge.color) ctx.set_line_width(edge.width) ctx.move_to(x1, y1) if edge.curved: # Calculate the curve aux1 = (2*x1+x2) / 3.0 - edge.curved * 0.5 * (y2-y1), \ (2*y1+y2) / 3.0 + edge.curved * 0.5 * (x2-x1) aux2 = (x1+2*x2) / 3.0 - edge.curved * 0.5 * (y2-y1), \ (y1+2*y2) / 3.0 + edge.curved * 0.5 * (x2-x1) # Coordinates of the control points of the Bezier curve xc1, yc1 = aux1 xc2, yc2 = aux2 # Determine where the edge intersects the circumference of the # vertex shape: Tip of the arrow x2, y2 = intersect_bezier_circle(x_src,y_src, xc1,yc1, xc2,yc2, x_dest,y_dest, dest_vertex.size/2.0) # Calculate the arrow head coordinates angle = atan2(y_dest - y2, x_dest - x2) # navid arrow_size = 15. * edge.arrow_size arrow_width = 10. / edge.arrow_width aux_points = [ (x2 - arrow_size * cos(angle - pi/arrow_width), y2 - arrow_size * sin(angle - pi/arrow_width)), (x2 - arrow_size * cos(angle + pi/arrow_width), y2 - arrow_size * sin(angle + pi/arrow_width)), ] # Midpoint of the base of the arrow triangle x_arrow_mid , y_arrow_mid = (aux_points [0][0] + aux_points [1][0]) / 2.0, (aux_points [0][1] + aux_points [1][1]) / 2.0 # Vector representing the base of the arrow triangle x_arrow_base_vec, y_arrow_base_vec = (aux_points [0][0] - aux_points [1][0]) , (aux_points [0][1] - aux_points [1][1]) # Recalculate the curve such that it lands on the base of the arrow triangle aux1 = (2*x_src+x_arrow_mid) / 3.0 - edge.curved * 0.5 * (y_arrow_mid-y_src), \ (2*y_src+y_arrow_mid) / 3.0 + edge.curved * 0.5 * (x_arrow_mid-x_src) aux2 = (x_src+2*x_arrow_mid) / 3.0 - edge.curved * 0.5 * (y_arrow_mid-y_src), \ (y_src+2*y_arrow_mid) / 3.0 + edge.curved * 0.5 * (x_arrow_mid-x_src) # Offset the second control point (aux2) such that it falls precisely on the normal to the arrow base vector # Strictly speaking, offset_length is the offset length divided by the length of the arrow base vector. offset_length = (x_arrow_mid - aux2[0]) * x_arrow_base_vec + (y_arrow_mid - aux2[1]) * y_arrow_base_vec offset_length /= euclidean_distance(0,0, x_arrow_base_vec, y_arrow_base_vec) ** 2 aux2 = aux2[0] + x_arrow_base_vec * offset_length, \ aux2[1] + y_arrow_base_vec * offset_length # Draw tthe curve from the first vertex to the midpoint of the base of the arrow head ctx.curve_to(aux1[0], aux1[1], aux2[0], aux2[1], x_arrow_mid, y_arrow_mid) else: # Determine where the edge intersects the circumference of the # vertex shape. x2, y2 = dest_vertex.shape.intersection_point( x2, y2, x1, y1, dest_vertex.size) # Draw the arrowhead angle = atan2(y_dest - y2, x_dest - x2) arrow_size = 15. * edge.arrow_size arrow_width = 10. / edge.arrow_width aux_points = [ (x2 - arrow_size * cos(angle - pi/arrow_width), y2 - arrow_size * sin(angle - pi/arrow_width)), (x2 - arrow_size * cos(angle + pi/arrow_width), y2 - arrow_size * sin(angle + pi/arrow_width)), ] # Midpoint of the base of the arrow triangle x_arrow_mid , y_arrow_mid = (aux_points [0][0] + aux_points [1][0]) / 2.0, (aux_points [0][1] + aux_points [1][1]) / 2.0 # Draw the line ctx.line_to(x_arrow_mid, y_arrow_mid) # Draw the edge ctx.stroke() # Draw the arrow head ctx.move_to(x2, y2) ctx.line_to(*aux_points[0]) ctx.line_to(*aux_points[1]) ctx.line_to(x2, y2) ctx.fill() class TaperedEdgeDrawer(AbstractEdgeDrawer): """Edge drawer implementation that draws undirected edges as straight lines and directed edges as tapered lines that are wider at the source and narrow at the destination. """ def draw_directed_edge(self, edge, src_vertex, dest_vertex): if src_vertex == dest_vertex: # TODO return self.draw_loop_edge(edge, src_vertex) # Determine where the edge intersects the circumference of the # destination vertex. src_pos, dest_pos = src_vertex.position, dest_vertex.position dest_pos = dest_vertex.shape.intersection_point( dest_pos[0], dest_pos[1], src_pos[0], src_pos[1], dest_vertex.size ) ctx = self.context # Draw the edge ctx.set_source_rgba(*edge.color) ctx.set_line_width(edge.width) angle = atan2(dest_pos[1]-src_pos[1], dest_pos[0]-src_pos[0]) arrow_size = src_vertex.size / 4. aux_points = [ (src_pos[0] + arrow_size * cos(angle + pi/2), src_pos[1] + arrow_size * sin(angle + pi/2)), (src_pos[0] + arrow_size * cos(angle - pi/2), src_pos[1] + arrow_size * sin(angle - pi/2)) ] ctx.move_to(*dest_pos) ctx.line_to(*aux_points[0]) ctx.line_to(*aux_points[1]) ctx.line_to(*dest_pos) ctx.fill() class AlphaVaryingEdgeDrawer(AbstractEdgeDrawer): """Edge drawer implementation that draws undirected edges as straight lines and directed edges by varying the alpha value of the specified edge color between the source and the destination. """ def __init__(self, context, alpha_at_src, alpha_at_dest): super(AlphaVaryingEdgeDrawer, self).__init__(context) self.alpha_at_src = (clamp(float(alpha_at_src), 0., 1.), ) self.alpha_at_dest = (clamp(float(alpha_at_dest), 0., 1.), ) def draw_directed_edge(self, edge, src_vertex, dest_vertex): if src_vertex == dest_vertex: # TODO return self.draw_loop_edge(edge, src_vertex) src_pos, dest_pos = src_vertex.position, dest_vertex.position ctx = self.context # Set up the gradient lg = cairo.LinearGradient(src_pos[0], src_pos[1], dest_pos[0], dest_pos[1]) edge_color = edge.color[:3] + self.alpha_at_src edge_color_end = edge_color[:3] + self.alpha_at_dest lg.add_color_stop_rgba(0, *edge_color) lg.add_color_stop_rgba(1, *edge_color_end) # Draw the edge ctx.set_source(lg) ctx.set_line_width(edge.width) ctx.move_to(*src_pos) ctx.line_to(*dest_pos) ctx.stroke() class LightToDarkEdgeDrawer(AlphaVaryingEdgeDrawer): """Edge drawer implementation that draws undirected edges as straight lines and directed edges by using an alpha value of zero (total transparency) at the source and an alpha value of one (full opacity) at the destination. The alpha value is interpolated in-between. """ def __init__(self, context): super(LightToDarkEdgeDrawer, self).__init__(context, 0.0, 1.0) class DarkToLightEdgeDrawer(AlphaVaryingEdgeDrawer): """Edge drawer implementation that draws undirected edges as straight lines and directed edges by using an alpha value of one (full opacity) at the source and an alpha value of zero (total transparency) at the destination. The alpha value is interpolated in-between. """ def __init__(self, context): super(DarkToLightEdgeDrawer, self).__init__(context, 1.0, 0.0) python-igraph-0.8.0/src/igraph/drawing/baseclasses.py0000644000076500000240000001220013104627150023070 0ustar tamasstaff00000000000000""" Abstract base classes for the drawing routines. """ from igraph.compat import property from igraph.drawing.utils import BoundingBox from math import pi ##################################################################### # pylint: disable-msg=R0903 # R0903: too few public methods class AbstractDrawer(object): """Abstract class that serves as a base class for anything that draws an igraph object.""" def draw(self, *args, **kwds): """Abstract method, must be implemented in derived classes.""" raise NotImplementedError("abstract class") ##################################################################### # pylint: disable-msg=R0903 # R0903: too few public methods class AbstractCairoDrawer(AbstractDrawer): """Abstract class that serves as a base class for anything that draws on a Cairo context within a given bounding box. A subclass of L{AbstractCairoDrawer} is guaranteed to have an attribute named C{context} that represents the Cairo context to draw on, and an attribute named C{bbox} for the L{BoundingBox} of the drawing area. """ def __init__(self, context, bbox): """Constructs the drawer and associates it to the given Cairo context and the given L{BoundingBox}. @param context: the context on which we will draw @param bbox: the bounding box within which we will draw. Can be anything accepted by the constructor of L{BoundingBox} (i.e., a 2-tuple, a 4-tuple or a L{BoundingBox} object). """ self.context = context self._bbox = None self.bbox = bbox @property def bbox(self): """The bounding box of the drawing area where this drawer will draw.""" return self._bbox @bbox.setter def bbox(self, bbox): """Sets the bounding box of the drawing area where this drawer will draw.""" if not isinstance(bbox, BoundingBox): self._bbox = BoundingBox(bbox) else: self._bbox = bbox def draw(self, *args, **kwds): """Abstract method, must be implemented in derived classes.""" raise NotImplementedError("abstract class") def _mark_point(self, x, y, color=0, size=4): """Marks the given point with a small circle on the canvas. Used primarily for debugging purposes. @param x: the X coordinate of the point to mark @param y: the Y coordinate of the point to mark @param color: the color of the marker. It can be a 3-tuple (RGB components, alpha=0.5), a 4-tuple (RGBA components) or an index where zero means red, 1 means green, 2 means blue and so on. @param size: the diameter of the marker. """ if isinstance(color, int): colors = [(1, 0, 0), (0, 1, 0), (0, 0, 1), (1, 1, 0), (0, 1, 1), (1, 0, 1)] color = colors[color % len(colors)] if len(color) == 3: color += (0.5, ) ctx = self.context ctx.save() ctx.set_source_rgba(*color) ctx.arc(x, y, size / 2.0, 0, 2*pi) ctx.fill() ctx.restore() ##################################################################### class AbstractXMLRPCDrawer(AbstractDrawer): """Abstract drawer that uses a remote service via XML-RPC to draw something on a remote display. """ def __init__(self, url, service=None): """Constructs an abstract drawer using the XML-RPC service at the given URL. @param url: the URL where the XML-RPC calls for the service should be addressed to. @param service: the name of the service at the XML-RPC address. If C{None}, requests will be directed to the server proxy object constructed by C{xmlrpclib.ServerProxy}; if not C{None}, the given attribute will be looked up in the server proxy object. """ import xmlrpclib url = self._resolve_hostname(url) self.server = xmlrpclib.ServerProxy(url) if service is None: self.service = self.server else: self.service = getattr(self.server, service) @staticmethod def _resolve_hostname(url): """Parses the given URL, resolves the hostname to an IP address and returns a new URL with the resolved IP address. This speeds up things big time on Mac OS X where an IP lookup would be performed for every XML-RPC call otherwise.""" from urlparse import urlparse, urlunparse import re url_parts = urlparse(url) hostname = url_parts.netloc if re.match("[0-9.:]+$", hostname): # the hostname is already an IP address, possibly with a port return url from socket import gethostbyname if ":" in hostname: hostname = hostname[0:hostname.index(":")] hostname = gethostbyname(hostname) if url_parts.port is not None: hostname = "%s:%d" % (hostname, url_parts.port) url_parts = list(url_parts) url_parts[1] = hostname return urlunparse(url_parts) python-igraph-0.8.0/src/igraph/drawing/graph.py0000644000076500000240000011733213303054544021717 0ustar tamasstaff00000000000000""" Drawing routines to draw graphs. This module contains routines to draw graphs on: - Cairo surfaces (L{DefaultGraphDrawer}) - UbiGraph displays (L{UbiGraphDrawer}, see U{http://ubietylab.net/ubigraph}) It also contains routines to send an igraph graph directly to (U{Cytoscape}) using the (U{CytoscapeRPC plugin}), see L{CytoscapeGraphDrawer}. L{CytoscapeGraphDrawer} can also fetch the current network from Cytoscape and convert it to igraph format. """ from collections import defaultdict from itertools import izip from math import atan2, cos, pi, sin, tan from warnings import warn from igraph._igraph import convex_hull, VertexSeq from igraph.compat import property from igraph.configuration import Configuration from igraph.drawing.baseclasses import AbstractDrawer, AbstractCairoDrawer, \ AbstractXMLRPCDrawer from igraph.drawing.colors import color_to_html_format, color_name_to_rgb from igraph.drawing.edge import ArrowEdgeDrawer from igraph.drawing.text import TextAlignment, TextDrawer from igraph.drawing.metamagic import AttributeCollectorBase from igraph.drawing.shapes import PolygonDrawer from igraph.drawing.utils import find_cairo, Point from igraph.drawing.vertex import DefaultVertexDrawer from igraph.layout import Layout __all__ = ["DefaultGraphDrawer", "UbiGraphDrawer", "CytoscapeGraphDrawer"] __license__ = "GPL" cairo = find_cairo() ##################################################################### # pylint: disable-msg=R0903 # R0903: too few public methods class AbstractGraphDrawer(AbstractDrawer): """Abstract class that serves as a base class for anything that draws an igraph.Graph.""" # pylint: disable-msg=W0221 # W0221: argument number differs from overridden method # E1101: Module 'cairo' has no 'foo' member - of course it does :) def draw(self, graph, *args, **kwds): """Abstract method, must be implemented in derived classes.""" raise NotImplementedError("abstract class") def ensure_layout(self, layout, graph = None): """Helper method that ensures that I{layout} is an instance of L{Layout}. If it is not, the method will try to convert it to a L{Layout} according to the following rules: - If I{layout} is a string, it is assumed to be a name of an igraph layout, and it will be passed on to the C{layout} method of the given I{graph} if I{graph} is not C{None}. - If I{layout} is C{None}, the C{layout} method of I{graph} will be invoked with no parameters, which will call the default layout algorithm. - Otherwise, I{layout} will be passed on to the constructor of L{Layout}. This handles lists of lists, lists of tuples and such. If I{layout} is already a L{Layout} instance, it will still be copied and a copy will be returned. This is because graph drawers are allowed to transform the layout for their purposes, and we don't want the transformation to propagate back to the caller. """ if isinstance(layout, Layout): layout = Layout(layout.coords) elif isinstance(layout, str) or layout is None: layout = graph.layout(layout) else: layout = Layout(layout) return layout ##################################################################### class AbstractCairoGraphDrawer(AbstractGraphDrawer, AbstractCairoDrawer): """Abstract base class for graph drawers that draw on a Cairo canvas. """ def __init__(self, context, bbox): """Constructs the graph drawer and associates it to the given Cairo context and the given L{BoundingBox}. @param context: the context on which we will draw @param bbox: the bounding box within which we will draw. Can be anything accepted by the constructor of L{BoundingBox} (i.e., a 2-tuple, a 4-tuple or a L{BoundingBox} object). """ AbstractCairoDrawer.__init__(self, context, bbox) AbstractGraphDrawer.__init__(self) ##################################################################### class DefaultGraphDrawer(AbstractCairoGraphDrawer): """Class implementing the default visualisation of a graph. The default visualisation of a graph draws the nodes on a 2D plane according to a given L{Layout}, then draws a straight or curved edge between nodes connected by edges. This is the visualisation used when one invokes the L{plot()} function on a L{Graph} object. See L{Graph.__plot__()} for the keyword arguments understood by this drawer.""" def __init__(self, context, bbox, \ vertex_drawer_factory = DefaultVertexDrawer, edge_drawer_factory = ArrowEdgeDrawer, label_drawer_factory = TextDrawer): """Constructs the graph drawer and associates it to the given Cairo context and the given L{BoundingBox}. @param context: the context on which we will draw @param bbox: the bounding box within which we will draw. Can be anything accepted by the constructor of L{BoundingBox} (i.e., a 2-tuple, a 4-tuple or a L{BoundingBox} object). @param vertex_drawer_factory: a factory method that returns an L{AbstractCairoVertexDrawer} instance bound to a given Cairo context. The factory method must take three parameters: the Cairo context, the bounding box of the drawing area and the palette to be used for drawing colored vertices. The default vertex drawer is L{DefaultVertexDrawer}. @param edge_drawer_factory: a factory method that returns an L{AbstractEdgeDrawer} instance bound to a given Cairo context. The factory method must take two parameters: the Cairo context and the palette to be used for drawing colored edges. You can use any of the actual L{AbstractEdgeDrawer} implementations here to control the style of edges drawn by igraph. The default edge drawer is L{ArrowEdgeDrawer}. @param label_drawer_factory: a factory method that returns a L{TextDrawer} instance bound to a given Cairo context. The method must take one parameter: the Cairo context. The default label drawer is L{TextDrawer}. """ AbstractCairoGraphDrawer.__init__(self, context, bbox) self.vertex_drawer_factory = vertex_drawer_factory self.edge_drawer_factory = edge_drawer_factory self.label_drawer_factory = label_drawer_factory def _determine_edge_order(self, graph, kwds): """Returns the order in which the edge of the given graph have to be drawn, assuming that the relevant keyword arguments (C{edge_order} and C{edge_order_by}) are given in C{kwds} as a dictionary. If neither C{edge_order} nor C{edge_order_by} is present in C{kwds}, this function returns C{None} to indicate that the graph drawer is free to choose the most convenient edge ordering.""" if "edge_order" in kwds: # Edge order specified explicitly return kwds["edge_order"] if kwds.get("edge_order_by") is None: # No edge order specified return None # Order edges by the value of some attribute edge_order_by = kwds["edge_order_by"] reverse = False if isinstance(edge_order_by, tuple): edge_order_by, reverse = edge_order_by if isinstance(reverse, basestring): reverse = reverse.lower().startswith("desc") attrs = graph.es[edge_order_by] edge_order = sorted(range(len(attrs)), key=attrs.__getitem__, reverse=bool(reverse)) return edge_order def _determine_vertex_order(self, graph, kwds): """Returns the order in which the vertices of the given graph have to be drawn, assuming that the relevant keyword arguments (C{vertex_order} and C{vertex_order_by}) are given in C{kwds} as a dictionary. If neither C{vertex_order} nor C{vertex_order_by} is present in C{kwds}, this function returns C{None} to indicate that the graph drawer is free to choose the most convenient vertex ordering.""" if "vertex_order" in kwds: # Vertex order specified explicitly return kwds["vertex_order"] if kwds.get("vertex_order_by") is None: # No vertex order specified return None # Order vertices by the value of some attribute vertex_order_by = kwds["vertex_order_by"] reverse = False if isinstance(vertex_order_by, tuple): vertex_order_by, reverse = vertex_order_by if isinstance(reverse, basestring): reverse = reverse.lower().startswith("desc") attrs = graph.vs[vertex_order_by] vertex_order = sorted(range(len(attrs)), key=attrs.__getitem__, reverse=bool(reverse)) return vertex_order # pylint: disable-msg=W0142,W0221,E1101 # W0142: Used * or ** magic # W0221: argument number differs from overridden method # E1101: Module 'cairo' has no 'foo' member - of course it does :) def draw(self, graph, palette, *args, **kwds): # Some abbreviations for sake of simplicity directed = graph.is_directed() context = self.context # Calculate/get the layout of the graph layout = self.ensure_layout(kwds.get("layout", None), graph) # Determine the size of the margin on each side margin = kwds.get("margin", 0) try: margin = list(margin) except TypeError: margin = [margin] while len(margin)<4: margin.extend(margin) # Contract the drawing area by the margin and fit the layout bbox = self.bbox.contract(margin) layout.fit_into(bbox, keep_aspect_ratio=kwds.get("keep_aspect_ratio", False)) # Decide whether we need to calculate the curvature of edges # automatically -- and calculate them if needed. autocurve = kwds.get("autocurve", None) if autocurve or (autocurve is None and \ "edge_curved" not in kwds and "curved" not in graph.edge_attributes() \ and graph.ecount() < 10000): from igraph import autocurve default = kwds.get("edge_curved", 0) if default is True: default = 0.5 default = float(default) kwds["edge_curved"] = autocurve(graph, attribute=None, default=default) # Construct the vertex, edge and label drawers vertex_drawer = self.vertex_drawer_factory(context, bbox, palette, layout) edge_drawer = self.edge_drawer_factory(context, palette) label_drawer = self.label_drawer_factory(context) # Construct the visual vertex/edge builders based on the specifications # provided by the vertex_drawer and the edge_drawer vertex_builder = vertex_drawer.VisualVertexBuilder(graph.vs, kwds) edge_builder = edge_drawer.VisualEdgeBuilder(graph.es, kwds) # Determine the order in which we will draw the vertices and edges vertex_order = self._determine_vertex_order(graph, kwds) edge_order = self._determine_edge_order(graph, kwds) # Draw the highlighted groups (if any) if "mark_groups" in kwds: mark_groups = kwds["mark_groups"] # Deferred import to avoid a cycle in the import graph from igraph.clustering import VertexClustering, VertexCover # Figure out what to do with mark_groups in order to be able to # iterate over it and get memberlist-color pairs if isinstance(mark_groups, dict): # Dictionary mapping vertex indices or tuples of vertex # indices to colors group_iter = mark_groups.iteritems() elif isinstance(mark_groups, (VertexClustering, VertexCover)): # Vertex clustering group_iter = ( (group, color) for color, group in enumerate(mark_groups) ) elif hasattr(mark_groups, "__iter__"): # Lists, tuples, iterators etc group_iter = iter(mark_groups) else: # False group_iter = {}.iteritems() # We will need a polygon drawer to draw the convex hulls polygon_drawer = PolygonDrawer(context, bbox) # Iterate over color-memberlist pairs for group, color_id in group_iter: if not group or color_id is None: continue color = palette.get(color_id) if isinstance(group, VertexSeq): group = [vertex.index for vertex in group] if not hasattr(group, "__iter__"): raise TypeError("group membership list must be iterable") # Get the vertex indices that constitute the convex hull hull = [group[i] for i in convex_hull([layout[idx] for idx in group])] # Calculate the preferred rounding radius for the corners corner_radius = 1.25 * max(vertex_builder[idx].size for idx in hull) # Construct the polygon polygon = [layout[idx] for idx in hull] if len(polygon) == 2: # Expand the polygon (which is a flat line otherwise) a, b = Point(*polygon[0]), Point(*polygon[1]) c = corner_radius * (a-b).normalized() n = Point(-c[1], c[0]) polygon = [a + n, b + n, b - c, b - n, a - n, a + c] else: # Expand the polygon around its center of mass center = Point(*[sum(coords) / float(len(coords)) for coords in zip(*polygon)]) polygon = [Point(*point).towards(center, -corner_radius) for point in polygon] # Draw the hull context.set_source_rgba(color[0], color[1], color[2], color[3]*0.25) polygon_drawer.draw_path(polygon, corner_radius=corner_radius) context.fill_preserve() context.set_source_rgba(*color) context.stroke() # Construct the iterator that we will use to draw the edges es = graph.es if edge_order is None: # Default edge order edge_coord_iter = izip(es, edge_builder) else: # Specified edge order edge_coord_iter = ((es[i], edge_builder[i]) for i in edge_order) # Draw the edges if directed: drawer_method = edge_drawer.draw_directed_edge else: drawer_method = edge_drawer.draw_undirected_edge for edge, visual_edge in edge_coord_iter: src, dest = edge.tuple src_vertex, dest_vertex = vertex_builder[src], vertex_builder[dest] drawer_method(visual_edge, src_vertex, dest_vertex) # Construct the iterator that we will use to draw the vertices vs = graph.vs if vertex_order is None: # Default vertex order vertex_coord_iter = izip(vs, vertex_builder, layout) else: # Specified vertex order vertex_coord_iter = ((vs[i], vertex_builder[i], layout[i]) for i in vertex_order) # Draw the vertices drawer_method = vertex_drawer.draw context.set_line_width(1) for vertex, visual_vertex, coords in vertex_coord_iter: drawer_method(visual_vertex, vertex, coords) # Decide whether the labels have to be wrapped wrap = kwds.get("wrap_labels") if wrap is None: wrap = Configuration.instance()["plotting.wrap_labels"] wrap = bool(wrap) # Construct the iterator that we will use to draw the vertex labels if vertex_order is None: # Default vertex order vertex_coord_iter = izip(vertex_builder, layout) else: # Specified vertex order vertex_coord_iter = ((vertex_builder[i], layout[i]) for i in vertex_order) # Draw the vertex labels for vertex, coords in vertex_coord_iter: if vertex.label is None: continue # Set the font family, size, color and text context.select_font_face(vertex.font, \ cairo.FONT_SLANT_NORMAL, cairo.FONT_WEIGHT_NORMAL) context.set_font_size(vertex.label_size) context.set_source_rgba(*vertex.label_color) label_drawer.text = vertex.label if vertex.label_dist: # Label is displaced from the center of the vertex. _, yb, w, h, _, _ = label_drawer.text_extents() w, h = w/2.0, h/2.0 radius = vertex.label_dist * vertex.size / 2. # First we find the reference point that is at distance `radius' # from the vertex in the direction given by `label_angle'. # Then we place the label in a way that the line connecting the # center of the bounding box of the label with the center of the # vertex goes through the reference point and the reference # point lies exactly on the bounding box of the vertex. alpha = vertex.label_angle % (2*pi) cx = coords[0] + radius * cos(alpha) cy = coords[1] - radius * sin(alpha) # Now we have the reference point. We have to decide which side # of the label box will intersect with the line that connects # the center of the label with the center of the vertex. if w > 0: beta = atan2(h, w) % (2*pi) else: beta = pi/2. gamma = pi - beta if alpha > 2*pi-beta or alpha <= beta: # Intersection at left edge of label cx += w cy -= tan(alpha) * w elif alpha > beta and alpha <= gamma: # Intersection at bottom edge of label try: cx += h / tan(alpha) except: pass # tan(alpha) == inf cy -= h elif alpha > gamma and alpha <= gamma + 2*beta: # Intersection at right edge of label cx -= w cy += tan(alpha) * w else: # Intersection at top edge of label try: cx -= h / tan(alpha) except: pass # tan(alpha) == inf cy += h # Draw the label label_drawer.draw_at(cx-w, cy-h-yb, wrap=wrap) else: # Label is exactly in the center of the vertex cx, cy = coords half_size = vertex.size / 2. label_drawer.bbox = (cx - half_size, cy - half_size, cx + half_size, cy + half_size) label_drawer.draw(wrap=wrap) # Construct the iterator that we will use to draw the edge labels es = graph.es if edge_order is None: # Default edge order edge_coord_iter = izip(es, edge_builder) else: # Specified edge order edge_coord_iter = ((es[i], edge_builder[i]) for i in edge_order) # Draw the edge labels for edge, visual_edge in edge_coord_iter: if visual_edge.label is None: continue # Set the font family, size, color and text context.select_font_face(visual_edge.font, \ cairo.FONT_SLANT_NORMAL, cairo.FONT_WEIGHT_NORMAL) context.set_font_size(visual_edge.label_size) context.set_source_rgba(*visual_edge.label_color) label_drawer.text = visual_edge.label # Ask the edge drawer to propose an anchor point for the label src, dest = edge.tuple src_vertex, dest_vertex = vertex_builder[src], vertex_builder[dest] (x, y), (halign, valign) = \ edge_drawer.get_label_position(edge, src_vertex, dest_vertex) # Measure the text _, yb, w, h, _, _ = label_drawer.text_extents() w /= 2.0 h /= 2.0 # Place the text relative to the edge if halign == TextAlignment.RIGHT: x -= w elif halign == TextAlignment.LEFT: x += w if valign == TextAlignment.BOTTOM: y -= h - yb / 2.0 elif valign == TextAlignment.TOP: y += h # Draw the edge label label_drawer.halign = halign label_drawer.valign = valign label_drawer.bbox = (x-w, y-h, x+w, y+h) label_drawer.draw(wrap=wrap) ##################################################################### class UbiGraphDrawer(AbstractXMLRPCDrawer, AbstractGraphDrawer): """Graph drawer that draws a given graph on an UbiGraph display using the XML-RPC API of UbiGraph. The following vertex attributes are supported: C{color}, C{label}, C{shape}, C{size}. See the Ubigraph documentation for supported shape names. Sizes are relative to the default Ubigraph size. The following edge attributes are supported: C{color}, C{label}, C{width}. Edge widths are relative to the default Ubigraph width. All color specifications supported by igraph (e.g., color names, palette indices, RGB triplets, RGBA quadruplets, HTML format) are understood by the Ubigraph graph drawer. The drawer also has two attributes, C{vertex_defaults} and C{edge_defaults}. These are dictionaries that can be used to set default values for the vertex/edge attributes in Ubigraph. """ def __init__(self, url="http://localhost:20738/RPC2"): """Constructs an UbiGraph drawer using the display at the given URL.""" super(UbiGraphDrawer, self).__init__(url, "ubigraph") self.vertex_defaults = dict( color="#ff0000", shape="cube", size=1.0 ) self.edge_defaults = dict( color="#ffffff", width=1.0 ) def draw(self, graph, *args, **kwds): """Draws the given graph on an UbiGraph display. @keyword clear: whether to clear the current UbiGraph display before plotting. Default: C{True}.""" display = self.service # Clear the display and set the default visual attributes if kwds.get("clear", True): display.clear() for k, v in self.vertex_defaults.iteritems(): display.set_vertex_style_attribute(0, k, str(v)) for k, v in self.edge_defaults.iteritems(): display.set_edge_style_attribute(0, k, str(v)) # Custom color converter function def color_conv(color): return color_to_html_format(color_name_to_rgb(color)) # Construct the visual vertex/edge builders class VisualVertexBuilder(AttributeCollectorBase): """Collects some visual properties of a vertex for drawing""" _kwds_prefix = "vertex_" color = (str(self.vertex_defaults["color"]), color_conv) label = None shape = str(self.vertex_defaults["shape"]) size = float(self.vertex_defaults["size"]) class VisualEdgeBuilder(AttributeCollectorBase): """Collects some visual properties of an edge for drawing""" _kwds_prefix = "edge_" color = (str(self.edge_defaults["color"]), color_conv) label = None width = float(self.edge_defaults["width"]) vertex_builder = VisualVertexBuilder(graph.vs, kwds) edge_builder = VisualEdgeBuilder(graph.es, kwds) # Add the vertices n = graph.vcount() new_vertex = display.new_vertex vertex_ids = [new_vertex() for _ in xrange(n)] # Add the edges new_edge = display.new_edge eids = [new_edge(vertex_ids[edge.source], vertex_ids[edge.target]) \ for edge in graph.es] # Add arrowheads if needed if graph.is_directed(): display.set_edge_style_attribute(0, "arrow", "true") # Set the vertex attributes set_attr = display.set_vertex_attribute vertex_defaults = self.vertex_defaults for vertex_id, vertex in izip(vertex_ids, vertex_builder): if vertex.color != vertex_defaults["color"]: set_attr(vertex_id, "color", vertex.color) if vertex.label: set_attr(vertex_id, "label", str(vertex.label)) if vertex.shape != vertex_defaults["shape"]: set_attr(vertex_id, "shape", vertex.shape) if vertex.size != vertex_defaults["size"]: set_attr(vertex_id, "size", str(vertex.size)) # Set the edge attributes set_attr = display.set_edge_attribute edge_defaults = self.edge_defaults for edge_id, edge in izip(eids, edge_builder): if edge.color != edge_defaults["color"]: set_attr(edge_id, "color", edge.color) if edge.label: set_attr(edge_id, "label", edge.label) if edge.width != edge_defaults["width"]: set_attr(edge_id, "width", str(edge.width)) ##################################################################### class CytoscapeGraphDrawer(AbstractXMLRPCDrawer, AbstractGraphDrawer): """Graph drawer that sends/receives graphs to/from Cytoscape using CytoscapeRPC. This graph drawer cooperates with U{Cytoscape} using U{CytoscapeRPC}. You need to install the CytoscapeRPC plugin first and start the XML-RPC server on a given port (port 9000 by default) from the appropriate Plugins submenu in Cytoscape. Graph, vertex and edge attributes are transferred to Cytoscape whenever possible (i.e. when a suitable mapping exists between a Python type and a Cytoscape type). If there is no suitable Cytoscape type for a Python type, the drawer will use a string attribute on the Cytoscape side and invoke C{str()} on the Python attributes. If an attribute to be created on the Cytoscape side already exists with a different type, an underscore will be appended to the attribute name to resolve the type conflict. You can use the C{network_id} attribute of this class to figure out the network ID of the last graph drawn with this drawer. """ def __init__(self, url="http://localhost:9000/Cytoscape"): """Constructs a Cytoscape graph drawer using the XML-RPC interface of Cytoscape at the given URL.""" super(CytoscapeGraphDrawer, self).__init__(url, "Cytoscape") self.network_id = None def draw(self, graph, name="Network from igraph", create_view=True, *args, **kwds): """Sends the given graph to Cytoscape as a new network. @param name: the name of the network in Cytoscape. @param create_view: whether to create a view for the network in Cytoscape.The default is C{True}. @keyword node_ids: specifies the identifiers of the nodes to be used in Cytoscape. This must either be the name of a vertex attribute or a list specifying the identifiers, one for each node in the graph. The default is C{None}, which simply uses the vertex index for each vertex.""" from xmlrpclib import Fault cy = self.service # Create the network if not create_view: try: network_id = cy.createNetwork(name, False) except Fault: warn("CytoscapeRPC too old, cannot create network without view." " Consider upgrading CytoscapeRPC to use this feature.") network_id = cy.createNetwork(name) else: network_id = cy.createNetwork(name) self.network_id = network_id # Create the nodes if "node_ids" in kwds: node_ids = kwds["node_ids"] if isinstance(node_ids, basestring): node_ids = graph.vs[node_ids] else: node_ids = xrange(graph.vcount()) node_ids = [str(identifier) for identifier in node_ids] cy.createNodes(network_id, node_ids) # Create the edges edgelists = [[], []] for v1, v2 in graph.get_edgelist(): edgelists[0].append(node_ids[v1]) edgelists[1].append(node_ids[v2]) edge_ids = cy.createEdges(network_id, edgelists[0], edgelists[1], ["unknown"] * graph.ecount(), [graph.is_directed()] * graph.ecount(), False ) if "layout" in kwds: # Calculate/get the layout of the graph layout = self.ensure_layout(kwds["layout"], graph) size = 100 * graph.vcount() ** 0.5 layout.fit_into((size, size), keep_aspect_ratio=True) layout.translate(-size/2., -size/2.) cy.setNodesPositions(network_id, node_ids, *zip(*list(layout))) else: # Ask Cytoscape to perform the default layout so the user can # at least see something in Cytoscape while the attributes are # being transferred cy.performDefaultLayout(network_id) # Send the network attributes attr_names = set(cy.getNetworkAttributeNames()) for attr in graph.attributes(): cy_type, value = self.infer_cytoscape_type([graph[attr]]) value = value[0] if value is None: continue # Resolve type conflicts (if any) try: while attr in attr_names and \ cy.getNetworkAttributeType(attr) != cy_type: attr += "_" except Fault: # getNetworkAttributeType is not available in some older versions # so we simply pass here pass cy.addNetworkAttributes(attr, cy_type, {network_id: value}) # Send the node attributes attr_names = set(cy.getNodeAttributeNames()) for attr in graph.vertex_attributes(): cy_type, values = self.infer_cytoscape_type(graph.vs[attr]) values = dict(pair for pair in izip(node_ids, values) if pair[1] is not None) # Resolve type conflicts (if any) while attr in attr_names and \ cy.getNodeAttributeType(attr) != cy_type: attr += "_" # Send the attribute values cy.addNodeAttributes(attr, cy_type, values, True) # Send the edge attributes attr_names = set(cy.getEdgeAttributeNames()) for attr in graph.edge_attributes(): cy_type, values = self.infer_cytoscape_type(graph.es[attr]) values = dict(pair for pair in izip(edge_ids, values) if pair[1] is not None) # Resolve type conflicts (if any) while attr in attr_names and \ cy.getEdgeAttributeType(attr) != cy_type: attr += "_" # Send the attribute values cy.addEdgeAttributes(attr, cy_type, values) def fetch(self, name = None, directed = False, keep_canonical_names = False): """Fetches the network with the given name from Cytoscape. When fetching networks from Cytoscape, the C{canonicalName} attributes of vertices and edges are not converted by default. Use the C{keep_canonical_names} parameter to retrieve these attributes as well. @param name: the name of the network in Cytoscape. @param directed: whether the network is directed. @param keep_canonical_names: whether to keep the C{canonicalName} vertex/edge attributes that are added automatically by Cytoscape @return: an appropriately constructed igraph L{Graph}.""" from igraph import Graph cy = self.service # Check the version number. Anything older than 1.3 is bad. version = cy.version() if " " in version: version = version.split(" ")[0] version = tuple(map(int, version.split(".")[:2])) if version < (1, 3): raise NotImplementedError("CytoscapeGraphDrawer requires " "Cytoscape-RPC 1.3 or newer") # Find out the ID of the network we are interested in if name is None: network_id = cy.getNetworkID() else: network_id = [k for k, v in cy.getNetworkList().iteritems() if v == name] if not network_id: raise ValueError("no such network: %r" % name) elif len(network_id) > 1: raise ValueError("more than one network exists with name: %r" % name) network_id = network_id[0] # Fetch the list of all the nodes and edges vertices = cy.getNodes(network_id) edges = cy.getEdges(network_id) n, m = len(vertices), len(edges) # Fetch the graph attributes graph_attrs = cy.getNetworkAttributes(network_id) # Fetch the vertex attributes vertex_attr_names = cy.getNodeAttributeNames() vertex_attrs = {} for attr_name in vertex_attr_names: if attr_name == "canonicalName" and not keep_canonical_names: continue has_attr = cy.nodesHaveAttribute(attr_name, vertices) filtered = [idx for idx, ok in enumerate(has_attr) if ok] values = cy.getNodesAttributes(attr_name, [name for name, ok in izip(vertices, has_attr) if ok] ) attrs = [None] * n for idx, value in izip(filtered, values): attrs[idx] = value vertex_attrs[attr_name] = attrs # Fetch the edge attributes edge_attr_names = cy.getEdgeAttributeNames() edge_attrs = {} for attr_name in edge_attr_names: if attr_name == "canonicalName" and not keep_canonical_names: continue has_attr = cy.edgesHaveAttribute(attr_name, edges) filtered = [idx for idx, ok in enumerate(has_attr) if ok] values = cy.getEdgesAttributes(attr_name, [name for name, ok in izip(edges, has_attr) if ok] ) attrs = [None] * m for idx, value in izip(filtered, values): attrs[idx] = value edge_attrs[attr_name] = attrs # Create a vertex name index vertex_name_index = dict((v, k) for k, v in enumerate(vertices)) del vertices # Remap the edges list to numeric IDs edge_list = [] for edge in edges: parts = edge.split() edge_list.append((vertex_name_index[parts[0]], vertex_name_index[parts[2]])) del edges return Graph(n, edge_list, directed=directed, graph_attrs=graph_attrs, vertex_attrs=vertex_attrs, edge_attrs=edge_attrs) @staticmethod def infer_cytoscape_type(values): """Returns a Cytoscape type that can be used to represent all the values in `values` and an appropriately converted copy of `values` that is suitable for an XML-RPC call. Note that the string type in Cytoscape is used as a catch-all type; if no other type fits, attribute values will be converted to string and then posted to Cytoscape. ``None`` entries are allowed in `values`, they will be ignored on the Cytoscape side. """ types = [type(value) for value in values if value is not None] if all(t == bool for t in types): return "BOOLEAN", values if all(issubclass(t, (int, long)) for t in types): return "INTEGER", values if all(issubclass(t, float) for t in types): return "FLOATING", values return "STRING", [ str(value) if not isinstance(value, basestring) else value for value in values ] ##################################################################### class GephiGraphStreamingDrawer(AbstractGraphDrawer): """Graph drawer that sends a graph to a file-like object (e.g., socket, URL connection, file) using the Gephi graph streaming format. The Gephi graph streaming format is a simple JSON-based format that can be used to post mutations to a graph (i.e. node and edge additions, removals and updates) to a remote component. For instance, one can open up Gephi (U{http://www.gephi.org}), install the Gephi graph streaming plugin and then send a graph from igraph straight into the Gephi window by using C{GephiGraphStreamingDrawer} with the appropriate URL where Gephi is listening. The C{connection} property exposes the L{GephiConnection} that the drawer uses. The drawer also has a property called C{streamer} which exposes the underlying L{GephiGraphStreamer} that is responsible for generating the JSON objects, encoding them and writing them to a file-like object. If you want to customize the encoding process, this is the object where you can tweak things to your taste. """ def __init__(self, conn=None, *args, **kwds): """Constructs a Gephi graph streaming drawer that will post graphs to the given Gephi connection. If C{conn} is C{None}, the remaining arguments of the constructor are forwarded intact to the constructor of L{GephiConnection} in order to create a connection. This means that any of the following are valid: - C{GephiGraphStreamingDrawer()} will construct a drawer that connects to workspace 0 of the local Gephi instance on port 8080. - C{GephiGraphStreamingDrawer(workspace=2)} will connect to workspace 2 of the local Gephi instance on port 8080. - C{GephiGraphStreamingDrawer(port=1234)} will connect to workspace 0 of the local Gephi instance on port 1234. - C{GephiGraphStreamingDrawer(host="remote", port=1234, workspace=7)} will connect to workspace 7 of the Gephi instance on host C{remote}, port 1234. - C{GephiGraphStreamingDrawer(url="http://remote:1234/workspace7)} is the same as above, but with an explicit URL. """ super(GephiGraphStreamingDrawer, self).__init__() from igraph.remote.gephi import GephiGraphStreamer, GephiConnection self.connection = conn or GephiConnection(*args, **kwds) self.streamer = GephiGraphStreamer() def draw(self, graph, *args, **kwds): """Draws (i.e. sends) the given graph to the destination of the drawer using the Gephi graph streaming API. The following keyword arguments are allowed: - ``encoder`` lets one specify an instance of ``json.JSONEncoder`` that will be used to encode the JSON objects. """ self.streamer.post(graph, self.connection, encoder=kwds.get("encoder")) python-igraph-0.8.0/src/igraph/drawing/coord.py0000644000076500000240000000766113104627150021725 0ustar tamasstaff00000000000000""" Coordinate systems and related plotting routines """ from igraph.compat import property from igraph.drawing.baseclasses import AbstractCairoDrawer from igraph.drawing.utils import BoundingBox __license__ = "GPL" ##################################################################### # pylint: disable-msg=R0922 # R0922: Abstract class is only referenced 1 times class CoordinateSystem(AbstractCairoDrawer): """Class implementing a coordinate system object. Coordinate system objects are used when drawing plots which 2D or 3D coordinate system axes. This is an abstract class which must be extended in order to use it. In general, you'll only need the documentation of this class if you intend to implement an own coordinate system not present in igraph yet. """ def __init__(self, context, bbox): """Initializes the coordinate system. @param context: the context on which the coordinate system will be drawn. @param bbox: the bounding box that will contain the coordinate system. """ AbstractCairoDrawer.__init__(self, context, bbox) def draw(self): """Draws the coordinate system. This method must be overridden in derived classes. """ raise NotImplementedError("abstract class") def local_to_context(self, x, y): """Converts local coordinates to the context coordinate system (given by the bounding box). This method must be overridden in derived classes.""" raise NotImplementedError("abstract class") class DescartesCoordinateSystem(CoordinateSystem): """Class implementing a 2D Descartes coordinate system object.""" def __init__(self, context, bbox, bounds): """Initializes the coordinate system. @param context: the context on which the coordinate system will be drawn. @param bbox: the bounding box that will contain the coordinate system. @param bounds: minimum and maximum X and Y values in a 4-tuple. """ self._bounds, self._bbox = None, None self._sx, self._sy = None, None self._ox, self._oy, self._ox2, self._oy2 = None, None, None, None CoordinateSystem.__init__(self, context, bbox) self.bbox = bbox self.bounds = bounds @property def bbox(self): """Returns the bounding box of the coordinate system""" return BoundingBox(self._bbox.coords) @bbox.setter def bbox(self, bbox): """Sets the bounding box of the coordinate system""" self._bbox = bbox self._recalc_scale_factors() @property def bounds(self): """Returns the lower and upper bounds of the X and Y values""" return self._bounds.coords @bounds.setter def bounds(self, bounds): """Sets the lower and upper bounds of the X and Y values""" self._bounds = BoundingBox(bounds) self._recalc_scale_factors() def _recalc_scale_factors(self): """Recalculates some cached scale factors used within the class""" if self._bounds is None: return self._sx = self._bbox.width / self._bounds.width self._sy = self._bbox.height / self._bounds.height self._ox = self._bounds.left self._oy = self._bounds.top self._ox2 = self._bbox.left self._oy2 = self._bbox.bottom def draw(self): """Draws the coordinate system.""" # Draw the frame coords = self.bbox.coords self.context.set_source_rgb(0., 0., 0.) self.context.set_line_width(1) self.context.rectangle(coords[0], coords[1], \ coords[2]-coords[0], coords[3]-coords[1]) self.context.stroke() def local_to_context(self, x, y): """Converts local coordinates to the context coordinate system (given by the bounding box). """ return (x-self._ox)*self._sx+self._ox2, self._oy2-(y-self._oy)*self._sy python-igraph-0.8.0/src/igraph/drawing/__init__.py0000644000076500000240000004763213410676505022370 0ustar tamasstaff00000000000000""" Drawing and plotting routines for IGraph. Plotting is dependent on the C{pycairo} or C{cairocffi} libraries that provide Python bindings to the popular U{Cairo library}. This means that if you don't have U{pycairo} or U{cairocffi} installed, you won't be able to use the plotting capabilities. However, you can still use L{Graph.write_svg} to save the graph to an SVG file and view it from U{Mozilla Firefox} (free) or edit it in U{Inkscape} (free), U{Skencil} (formerly known as Sketch, also free) or Adobe Illustrator. Whenever the documentation refers to the C{pycairo} library, you can safely replace it with C{cairocffi} as the two are API-compatible. """ from __future__ import with_statement from cStringIO import StringIO from warnings import warn import os import platform import time from igraph.compat import property, BytesIO from igraph.configuration import Configuration from igraph.drawing.colors import Palette, palettes from igraph.drawing.graph import DefaultGraphDrawer from igraph.drawing.utils import BoundingBox, Point, Rectangle, find_cairo from igraph.utils import _is_running_in_ipython, named_temporary_file __all__ = ["BoundingBox", "DefaultGraphDrawer", "Plot", "Point", "Rectangle", "plot"] __license__ = "GPL" cairo = find_cairo() ##################################################################### class Plot(object): """Class representing an arbitrary plot Every plot has an associated surface object where the plotting is done. The surface is an instance of C{cairo.Surface}, a member of the C{pycairo} library. The surface itself provides a unified API to various plotting targets like SVG files, X11 windows, PostScript files, PNG files and so on. C{igraph} usually does not know on which surface it is plotting right now, since C{pycairo} takes care of the actual drawing. Everything that's supported by C{pycairo} should be supported by this class as well. Current Cairo surfaces that I'm aware of are: - C{cairo.GlitzSurface} -- OpenGL accelerated surface for the X11 Window System. - C{cairo.ImageSurface} -- memory buffer surface. Can be written to a C{PNG} image file. - C{cairo.PDFSurface} -- PDF document surface. - C{cairo.PSSurface} -- PostScript document surface. - C{cairo.SVGSurface} -- SVG (Scalable Vector Graphics) document surface. - C{cairo.Win32Surface} -- Microsoft Windows screen rendering. - C{cairo.XlibSurface} -- X11 Window System screen rendering. If you create a C{Plot} object with a string given as the target surface, the string will be treated as a filename, and its extension will decide which surface class will be used. Please note that not all surfaces might be available, depending on your C{pycairo} installation. A C{Plot} has an assigned default palette (see L{igraph.drawing.colors.Palette}) which is used for plotting objects. A C{Plot} object also has a list of objects to be plotted with their respective bounding boxes, palettes and opacities. Palettes assigned to an object override the default palette of the plot. Objects can be added by the L{Plot.add} method and removed by the L{Plot.remove} method. """ # pylint: disable-msg=E1101 # E1101: Module 'cairo' has no 'foo' member - of course it has! :) def __init__(self, target=None, bbox=None, palette=None, background=None): """Creates a new plot. @param target: the target surface to write to. It can be one of the following types: - C{None} -- an appropriate surface will be created and the object will be plotted there. - C{cairo.Surface} -- the given Cairo surface will be used. - C{string} -- a file with the given name will be created and an appropriate Cairo surface will be attached to it. @param bbox: the bounding box of the surface. It is interpreted differently with different surfaces: PDF and PS surfaces will treat it as points (1 point = 1/72 inch). Image surfaces will treat it as pixels. SVG surfaces will treat it as an abstract unit, but it will mostly be interpreted as pixels when viewing the SVG file in Firefox. @param palette: the palette primarily used on the plot if the added objects do not specify a private palette. Must be either an L{igraph.drawing.colors.Palette} object or a string referring to a valid key of C{igraph.drawing.colors.palettes} (see module L{igraph.drawing.colors}) or C{None}. In the latter case, the default palette given by the configuration key C{plotting.palette} is used. @param background: the background color. If C{None}, the background will be transparent. You can use any color specification here that is understood by L{igraph.drawing.colors.color_name_to_rgba}. """ self._filename = None self._surface_was_created = not isinstance(target, cairo.Surface) self._need_tmpfile = False # Several Windows-specific hacks will be used from now on, thanks # to Dale Hunscher for debugging and fixing all that stuff self._windows_hacks = "Windows" in platform.platform() if bbox is None: self.bbox = BoundingBox(600, 600) elif isinstance(bbox, tuple) or isinstance(bbox, list): self.bbox = BoundingBox(bbox) else: self.bbox = bbox if palette is None: config = Configuration.instance() palette = config["plotting.palette"] if not isinstance(palette, Palette): palette = palettes[palette] self._palette = palette if target is None: self._need_tmpfile = True self._surface = cairo.ImageSurface(cairo.FORMAT_ARGB32, \ int(self.bbox.width), int(self.bbox.height)) elif isinstance(target, cairo.Surface): self._surface = target else: self._filename = target _, ext = os.path.splitext(target) ext = ext.lower() if ext == ".pdf": self._surface = cairo.PDFSurface(target, self.bbox.width, \ self.bbox.height) elif ext == ".ps" or ext == ".eps": self._surface = cairo.PSSurface(target, self.bbox.width, \ self.bbox.height) elif ext == ".png": self._surface = cairo.ImageSurface(cairo.FORMAT_ARGB32, \ int(self.bbox.width), int(self.bbox.height)) elif ext == ".svg": self._surface = cairo.SVGSurface(target, self.bbox.width, \ self.bbox.height) else: raise ValueError("image format not handled by Cairo: %s" % ext) self._ctx = cairo.Context(self._surface) self._objects = [] self._is_dirty = False self.background = background def add(self, obj, bbox=None, palette=None, opacity=1.0, *args, **kwds): """Adds an object to the plot. Arguments not specified here are stored and passed to the object's plotting function when necessary. Since you are most likely interested in the arguments acceptable by graphs, see L{Graph.__plot__} for more details. @param obj: the object to be added @param bbox: the bounding box of the object. If C{None}, the object will fill the entire area of the plot. @param palette: the color palette used for drawing the object. If the object tries to get a color assigned to a positive integer, it will use this palette. If C{None}, defaults to the global palette of the plot. @param opacity: the opacity of the object being plotted, in the range 0.0-1.0 @see: Graph.__plot__ """ if opacity < 0.0 or opacity > 1.0: raise ValueError("opacity must be between 0.0 and 1.0") if bbox is None: bbox = self.bbox if not isinstance(bbox, BoundingBox): bbox = BoundingBox(bbox) self._objects.append((obj, bbox, palette, opacity, args, kwds)) self.mark_dirty() @property def background(self): """Returns the background color of the plot. C{None} means a transparent background. """ return self._background @background.setter def background(self, color): """Sets the background color of the plot. C{None} means a transparent background. You can use any color specification here that is understood by the C{get} method of the current palette or by L{igraph.colors.color_name_to_rgb}. """ if color is None: self._background = None else: self._background = self._palette.get(color) def remove(self, obj, bbox=None, idx=1): """Removes an object from the plot. If the object has been added multiple times and no bounding box was specified, it removes the instance which occurs M{idx}th in the list of identical instances of the object. @param obj: the object to be removed @param bbox: optional bounding box specification for the object. If given, only objects with exactly this bounding box will be considered. @param idx: if multiple objects match the specification given by M{obj} and M{bbox}, only the M{idx}th occurrence will be removed. @return: C{True} if the object has been removed successfully, C{False} if the object was not on the plot at all or M{idx} was larger than the count of occurrences """ for i in xrange(len(self._objects)): current_obj, current_bbox = self._objects[i][0:2] if current_obj is obj and (bbox is None or current_bbox == bbox): idx -= 1 if idx == 0: self._objects[i:(i+1)] = [] self.mark_dirty() return True return False def mark_dirty(self): """Marks the plot as dirty (should be redrawn)""" self._is_dirty = True # pylint: disable-msg=W0142 # W0142: used * or ** magic def redraw(self, context=None): """Redraws the plot""" ctx = context or self._ctx if self._background is not None: ctx.set_source_rgba(*self._background) ctx.rectangle(0, 0, self.bbox.width, self.bbox.height) ctx.fill() for obj, bbox, palette, opacity, args, kwds in self._objects: if palette is None: palette = getattr(obj, "_default_palette", self._palette) plotter = getattr(obj, "__plot__", None) if plotter is None: warn("%s does not support plotting" % (obj, )) else: if opacity < 1.0: ctx.push_group() else: ctx.save() plotter(ctx, bbox, palette, *args, **kwds) if opacity < 1.0: ctx.pop_group_to_source() ctx.paint_with_alpha(opacity) else: ctx.restore() self._is_dirty = False def save(self, fname=None): """Saves the plot. @param fname: the filename to save to. It is ignored if the surface of the plot is not an C{ImageSurface}. """ if self._is_dirty: self.redraw() if isinstance(self._surface, cairo.ImageSurface): if fname is None and self._need_tmpfile: with named_temporary_file(prefix="igraph", suffix=".png") as fname: self._surface.write_to_png(fname) return None fname = fname or self._filename if fname is None: raise ValueError("no file name is known for the surface " + \ "and none given") return self._surface.write_to_png(fname) if fname is not None: warn("filename is ignored for surfaces other than ImageSurface") self._ctx.show_page() self._surface.finish() def show(self): """Saves the plot to a temporary file and shows it.""" if not isinstance(self._surface, cairo.ImageSurface): sur = cairo.ImageSurface(cairo.FORMAT_ARGB32, int(self.bbox.width), int(self.bbox.height)) ctx = cairo.Context(sur) self.redraw(ctx) else: sur = self._surface ctx = self._ctx if self._is_dirty: self.redraw(ctx) with named_temporary_file(prefix="igraph", suffix=".png") as tmpfile: sur.write_to_png(tmpfile) config = Configuration.instance() imgviewer = config["apps.image_viewer"] if not imgviewer: # No image viewer was given and none was detected. This # should only happen on unknown platforms. plat = platform.system() raise NotImplementedError("showing plots is not implemented " + \ "on this platform: %s" % plat) else: os.system("%s %s" % (imgviewer, tmpfile)) if platform.system() == "Darwin" or self._windows_hacks: # On Mac OS X and Windows, launched applications are likely to # fork and give control back to Python immediately. # Chances are that the temporary image file gets removed # before the image viewer has a chance to open it, so # we wait here a little bit. Yes, this is quite hackish :( time.sleep(5) def _repr_svg_(self): """Returns an SVG representation of this plot as a string. This method is used by IPython to display this plot inline. """ io = BytesIO() # Create a new SVG surface and use that to get the SVG representation, # which will end up in io surface = cairo.SVGSurface(io, self.bbox.width, self.bbox.height) context = cairo.Context(surface) # Plot the graph on this context self.redraw(context) # No idea why this is needed but python crashes without context.show_page() surface.finish() # Return the raw SVG representation result = io.getvalue() if hasattr(result, "encode"): result = result.encode("utf-8") # for Python 2.x else: result = result.decode("utf-8") # for Python 3.x return result, {'isolated': True} # put it inside an iframe @property def bounding_box(self): """Returns the bounding box of the Cairo surface as a L{BoundingBox} object""" return BoundingBox(self.bbox) @property def height(self): """Returns the height of the Cairo surface on which the plot is drawn""" return self.bbox.height @property def surface(self): """Returns the Cairo surface on which the plot is drawn""" return self._surface @property def width(self): """Returns the width of the Cairo surface on which the plot is drawn""" return self.bbox.width ##################################################################### def plot(obj, target=None, bbox=(0, 0, 600, 600), *args, **kwds): """Plots the given object to the given target. Positional and keyword arguments not explicitly mentioned here will be passed down to the C{__plot__} method of the object being plotted. Since you are most likely interested in the keyword arguments available for graph plots, see L{Graph.__plot__} as well. @param obj: the object to be plotted @param target: the target where the object should be plotted. It can be one of the following types: - C{None} -- an appropriate surface will be created and the object will be plotted there. - C{cairo.Surface} -- the given Cairo surface will be used. This can refer to a PNG image, an arbitrary window, an SVG file, anything that Cairo can handle. - C{string} -- a file with the given name will be created and an appropriate Cairo surface will be attached to it. The supported image formats are: PNG, PDF, SVG and PostScript. @param bbox: the bounding box of the plot. It must be a tuple with either two or four integers, or a L{BoundingBox} object. If this is a tuple with two integers, it is interpreted as the width and height of the plot (in pixels for PNG images and on-screen plots, or in points for PDF, SVG and PostScript plots, where 72 pt = 1 inch = 2.54 cm). If this is a tuple with four integers, the first two denotes the X and Y coordinates of a corner and the latter two denoting the X and Y coordinates of the opposite corner. @keyword opacity: the opacity of the object being plotted. It can be used to overlap several plots of the same graph if you use the same layout for them -- for instance, you might plot a graph with opacity 0.5 and then plot its spanning tree over it with opacity 0.1. To achieve this, you'll need to modify the L{Plot} object returned with L{Plot.add}. @keyword palette: the palette primarily used on the plot if the added objects do not specify a private palette. Must be either an L{igraph.drawing.colors.Palette} object or a string referring to a valid key of C{igraph.drawing.colors.palettes} (see module L{igraph.drawing.colors}) or C{None}. In the latter case, the default palette given by the configuration key C{plotting.palette} is used. @keyword margin: the top, right, bottom, left margins as a 4-tuple. If it has less than 4 elements or is a single float, the elements will be re-used until the length is at least 4. The default margin is 20 on each side. @keyword inline: whether to try and show the plot object inline in the current IPython notebook. Passing ``None`` here or omitting this keyword argument will look up the preferred behaviour from the C{shell.ipython.inlining.Plot} configuration key. Note that this keyword argument has an effect only if igraph is run inside IPython and C{target} is C{None}. @return: an appropriate L{Plot} object. @see: Graph.__plot__ """ if not isinstance(bbox, BoundingBox): bbox = BoundingBox(bbox) result = Plot(target, bbox, background=kwds.get("background", "white")) if "margin" in kwds: bbox = bbox.contract(kwds["margin"]) del kwds["margin"] else: bbox = bbox.contract(20) result.add(obj, bbox, *args, **kwds) if target is None and _is_running_in_ipython(): # Get the default value of the `inline` argument from the configuration if # needed inline = kwds.get("inline") if inline is None: config = Configuration.instance() inline = config["shell.ipython.inlining.Plot"] # If we requested an inline plot, just return the result and IPython will # call its _repr_svg_ method. If we requested a non-inline plot, show the # plot in a separate window and return nothing if inline: return result else: result.show() return # We are either not in IPython or the user specified an explicit plot target, # so just show or save the result if target is None: result.show() elif isinstance(target, basestring): result.save() # Also return the plot itself return result ##################################################################### python-igraph-0.8.0/src/igraph/drawing/vertex.py0000644000076500000240000001041713614535474022142 0ustar tamasstaff00000000000000""" Drawing routines to draw the vertices of graphs. This module provides implementations of vertex drawers, i.e. drawers that the default graph drawer will use to draw vertices. """ from igraph.drawing.baseclasses import AbstractDrawer, AbstractCairoDrawer from igraph.drawing.metamagic import AttributeCollectorBase from igraph.drawing.shapes import ShapeDrawerDirectory from math import pi __all__ = ["AbstractVertexDrawer", "AbstractCairoVertexDrawer", \ "DefaultVertexDrawer"] __license__ = "GPL" class AbstractVertexDrawer(AbstractDrawer): """Abstract vertex drawer object from which all concrete vertex drawer implementations are derived.""" def __init__(self, palette, layout): """Constructs the vertex drawer and associates it to the given palette. @param palette: the palette that can be used to map integer color indices to colors when drawing vertices @param layout: the layout of the vertices in the graph being drawn """ self.layout = layout self.palette = palette def draw(self, visual_vertex, vertex, coords): """Draws the given vertex. @param visual_vertex: object specifying the visual properties of the vertex. Its structure is defined by the VisualVertexBuilder of the L{DefaultGraphDrawer}; see its source code. @param vertex: the raw igraph vertex being drawn @param coords: the X and Y coordinates of the vertex as specified by the layout algorithm, scaled into the bounding box. """ raise NotImplementedError("abstract class") class AbstractCairoVertexDrawer(AbstractVertexDrawer, AbstractCairoDrawer): """Abstract base class for vertex drawers that draw on a Cairo canvas.""" def __init__(self, context, bbox, palette, layout): """Constructs the vertex drawer and associates it to the given Cairo context and the given L{BoundingBox}. @param context: the context on which we will draw @param bbox: the bounding box within which we will draw. Can be anything accepted by the constructor of L{BoundingBox} (i.e., a 2-tuple, a 4-tuple or a L{BoundingBox} object). @param palette: the palette that can be used to map integer color indices to colors when drawing vertices @param layout: the layout of the vertices in the graph being drawn """ AbstractCairoDrawer.__init__(self, context, bbox) AbstractVertexDrawer.__init__(self, palette, layout) class DefaultVertexDrawer(AbstractCairoVertexDrawer): """The default vertex drawer implementation of igraph.""" def __init__(self, context, bbox, palette, layout): AbstractCairoVertexDrawer.__init__(self, context, bbox, palette, layout) self.VisualVertexBuilder = self._construct_visual_vertex_builder() def _construct_visual_vertex_builder(self): class VisualVertexBuilder(AttributeCollectorBase): """Collects some visual properties of a vertex for drawing""" _kwds_prefix = "vertex_" color = ("red", self.palette.get) frame_color = ("black", self.palette.get) frame_width = 1.0 label = None label_angle = -pi/2 label_dist = 0.0 label_color = ("black", self.palette.get) font = 'sans-serif' label_size = 14.0 position = dict(func=self.layout.__getitem__) shape = ("circle", ShapeDrawerDirectory.resolve_default) size = 20.0 width = None height = None return VisualVertexBuilder def draw(self, visual_vertex, vertex, coords): context = self.context width = visual_vertex.width if visual_vertex.width is not None else visual_vertex.size height = visual_vertex.height if visual_vertex.height is not None else visual_vertex.size visual_vertex.shape.draw_path(context, coords[0], coords[1], width, height) context.set_source_rgba(*visual_vertex.color) context.fill_preserve() context.set_source_rgba(*visual_vertex.frame_color) context.set_line_width(visual_vertex.frame_width) context.stroke() python-igraph-0.8.0/src/igraph/drawing/utils.py0000644000076500000240000004276313104627150021761 0ustar tamasstaff00000000000000""" Utility classes for drawing routines. """ from igraph.compat import property from itertools import izip from math import atan2, cos, sin from operator import itemgetter __all__ = ["BoundingBox", "FakeModule", "Point", "Rectangle"] __license__ = "GPL" ##################################################################### class Rectangle(object): """Class representing a rectangle.""" __slots__ = ("_left", "_top", "_right", "_bottom") def __init__(self, *args): """Creates a rectangle. The corners of the rectangle can be specified by either a tuple (four items, two for each corner, respectively), four separate numbers (X and Y coordinates for each corner) or two separate numbers (width and height, the upper left corner is assumed to be at (0,0))""" coords = None if len(args) == 1: if isinstance(args[0], Rectangle): coords = args[0].coords elif len(args[0]) >= 4: coords = tuple(args[0])[0:4] elif len(args[0]) == 2: coords = (0, 0, args[0][0], args[0][1]) elif len(args) == 4: coords = tuple(args) elif len(args) == 2: coords = (0, 0, args[0], args[1]) if coords is None: raise ValueError("invalid coordinate format") try: coords = tuple(float(coord) for coord in coords) except ValueError: raise ValueError("invalid coordinate format, numbers expected") self.coords = coords @property def coords(self): """The coordinates of the corners. The coordinates are returned as a 4-tuple in the following order: left edge, top edge, right edge, bottom edge. """ return self._left, self._top, self._right, self._bottom @coords.setter def coords(self, coords): """Sets the coordinates of the corners. @param coords: a 4-tuple with the coordinates of the corners """ self._left, self._top, self._right, self._bottom = coords if self._left > self._right: self._left, self._right = self._right, self._left if self._top > self._bottom: self._bottom, self._top = self._top, self._bottom @property def width(self): """The width of the rectangle""" return self._right - self._left @width.setter def width(self, value): """Sets the width of the rectangle by adjusting the right edge.""" self._right = self._left + value @property def height(self): """The height of the rectangle""" return self._bottom - self._top @height.setter def height(self, value): """Sets the height of the rectangle by adjusting the bottom edge.""" self._bottom = self._top + value @property def left(self): """The X coordinate of the left side of the box""" return self._left @left.setter def left(self, value): """Sets the X coordinate of the left side of the box""" self._left = float(value) self._right = max(self._left, self._right) @property def right(self): """The X coordinate of the right side of the box""" return self._right @right.setter def right(self, value): """Sets the X coordinate of the right side of the box""" self._right = float(value) self._left = min(self._left, self._right) @property def top(self): """The Y coordinate of the top edge of the box""" return self._top @top.setter def top(self, value): """Sets the Y coordinate of the top edge of the box""" self._top = value self._bottom = max(self._bottom, self._top) @property def bottom(self): """The Y coordinate of the bottom edge of the box""" return self._bottom @bottom.setter def bottom(self, value): """Sets the Y coordinate of the bottom edge of the box""" self._bottom = value self._top = min(self._bottom, self._top) @property def midx(self): """The X coordinate of the center of the box""" return (self._left + self._right) / 2.0 @midx.setter def midx(self, value): """Moves the center of the box to the given X coordinate""" dx = value - (self._left + self._right) / 2.0 self._left += dx self._right += dx @property def midy(self): """The Y coordinate of the center of the box""" return (self._top + self._bottom) / 2.0 @midy.setter def midy(self, value): """Moves the center of the box to the given Y coordinate""" dy = value - (self._top + self._bottom) / 2.0 self._top += dy self._bottom += dy @property def shape(self): """The shape of the rectangle (width, height)""" return self._right - self._left, self._bottom - self._top @shape.setter def shape(self, shape): """Sets the shape of the rectangle (width, height).""" self.width, self.height = shape def contract(self, margins): """Contracts the rectangle by the given margins. @return: a new L{Rectangle} object. """ if isinstance(margins, int) or isinstance(margins, float): margins = [float(margins)] * 4 if len(margins) != 4: raise ValueError("margins must be a 4-tuple or a single number") nx1, ny1 = self._left+margins[0], self._top+margins[1] nx2, ny2 = self._right-margins[2], self._bottom-margins[3] if nx1 > nx2: nx1 = (nx1+nx2)/2. nx2 = nx1 if ny1 > ny2: ny1 = (ny1+ny2)/2. ny2 = ny1 return self.__class__(nx1, ny1, nx2, ny2) def expand(self, margins): """Expands the rectangle by the given margins. @return: a new L{Rectangle} object. """ if isinstance(margins, int) or isinstance(margins, float): return self.contract(-float(margins)) return self.contract([-float(margin) for margin in margins]) def isdisjoint(self, other): """Returns ``True`` if the two rectangles have no intersection. Example:: >>> r1 = Rectangle(10, 10, 30, 30) >>> r2 = Rectangle(20, 20, 50, 50) >>> r3 = Rectangle(70, 70, 90, 90) >>> r1.isdisjoint(r2) False >>> r2.isdisjoint(r1) False >>> r1.isdisjoint(r3) True >>> r3.isdisjoint(r1) True """ return self._left > other._right or self._right < other._left \ or self._top > other._bottom or self._bottom < other._top def isempty(self): """Returns ``True`` if the rectangle is empty (i.e. it has zero width and height). Example:: >>> r1 = Rectangle(10, 10, 30, 30) >>> r2 = Rectangle(70, 70, 90, 90) >>> r1.isempty() False >>> r2.isempty() False >>> r1.intersection(r2).isempty() True """ return self._left == self._right and self._top == self._bottom def intersection(self, other): """Returns the intersection of this rectangle with another. Example:: >>> r1 = Rectangle(10, 10, 30, 30) >>> r2 = Rectangle(20, 20, 50, 50) >>> r3 = Rectangle(70, 70, 90, 90) >>> r1.intersection(r2) Rectangle(20.0, 20.0, 30.0, 30.0) >>> r2 & r1 Rectangle(20.0, 20.0, 30.0, 30.0) >>> r2.intersection(r1) == r1.intersection(r2) True >>> r1.intersection(r3) Rectangle(0.0, 0.0, 0.0, 0.0) """ if self.isdisjoint(other): return Rectangle(0, 0, 0, 0) return Rectangle(max(self._left, other._left), max(self._top, other._top), min(self._right, other._right), min(self._bottom, other._bottom)) __and__ = intersection def translate(self, dx, dy): """Translates the rectangle in-place. Example: >>> r = Rectangle(10, 20, 50, 70) >>> r.translate(30, -10) >>> r Rectangle(40.0, 10.0, 80.0, 60.0) @param dx: the X coordinate of the translation vector @param dy: the Y coordinate of the translation vector """ self._left += dx self._right += dx self._top += dy self._bottom += dy def union(self, other): """Returns the union of this rectangle with another. The resulting rectangle is the smallest rectangle that contains both rectangles. Example:: >>> r1 = Rectangle(10, 10, 30, 30) >>> r2 = Rectangle(20, 20, 50, 50) >>> r3 = Rectangle(70, 70, 90, 90) >>> r1.union(r2) Rectangle(10.0, 10.0, 50.0, 50.0) >>> r2 | r1 Rectangle(10.0, 10.0, 50.0, 50.0) >>> r2.union(r1) == r1.union(r2) True >>> r1.union(r3) Rectangle(10.0, 10.0, 90.0, 90.0) """ return Rectangle(min(self._left, other._left), min(self._top, other._top), max(self._right, other._right), max(self._bottom, other._bottom)) __or__ = union def __ior__(self, other): """Expands this rectangle to include itself and another completely while still being as small as possible. Example:: >>> r1 = Rectangle(10, 10, 30, 30) >>> r2 = Rectangle(20, 20, 50, 50) >>> r3 = Rectangle(70, 70, 90, 90) >>> r1 |= r2 >>> r1 Rectangle(10.0, 10.0, 50.0, 50.0) >>> r1 |= r3 >>> r1 Rectangle(10.0, 10.0, 90.0, 90.0) """ self._left = min(self._left, other._left) self._top = min(self._top, other._top) self._right = max(self._right, other._right) self._bottom = max(self._bottom, other._bottom) return self def __repr__(self): return "%s(%s, %s, %s, %s)" % (self.__class__.__name__, \ self._left, self._top, self._right, self._bottom) def __eq__(self, other): return self.coords == other.coords def __ne__(self, other): return self.coords != other.coords def __bool__(self): return self._left != self._right or self._top != self._bottom def __nonzero__(self): return self._left != self._right or self._top != self._bottom def __hash__(self): return hash(self.coords) ##################################################################### class BoundingBox(Rectangle): """Class representing a bounding box (a rectangular area) that encloses some objects.""" def __ior__(self, other): """Replaces this bounding box with the union of itself and another. Example:: >>> box1 = BoundingBox(10, 20, 50, 60) >>> box2 = BoundingBox(70, 40, 100, 90) >>> box1 |= box2 >>> print(box1) BoundingBox(10.0, 20.0, 100.0, 90.0) """ self._left = min(self._left, other._left) self._top = min(self._top, other._top) self._right = max(self._right, other._right) self._bottom = max(self._bottom, other._bottom) return self def __or__(self, other): """Takes the union of this bounding box with another. The result is a bounding box which encloses both bounding boxes. Example:: >>> box1 = BoundingBox(10, 20, 50, 60) >>> box2 = BoundingBox(70, 40, 100, 90) >>> box1 | box2 BoundingBox(10.0, 20.0, 100.0, 90.0) """ return self.__class__( min(self._left, other._left), min(self._top, other._top), max(self._right, other._right), max(self._bottom, other._bottom) ) ##################################################################### # pylint: disable-msg=R0903 # R0903: too few public methods class FakeModule(object): """Fake module that raises an exception for everything""" def __getattr__(self, _): raise TypeError("plotting not available") def __call__(self, _): raise TypeError("plotting not available") def __setattr__(self, key, value): raise TypeError("plotting not available") ##################################################################### def find_cairo(): """Tries to import the ``cairo`` Python module if it is installed, also trying ``cairocffi`` (a drop-in replacement of ``cairo``). Returns a fake module if everything fails. """ module_names = ["cairo", "cairocffi"] module = FakeModule() for module_name in module_names: try: module = __import__(module_name) break except ImportError: pass return module ##################################################################### class Point(tuple): """Class representing a point on the 2D plane.""" __slots__ = () _fields = ('x', 'y') def __new__(cls, x, y): """Creates a new point with the given coordinates""" return tuple.__new__(cls, (x, y)) # pylint: disable-msg=W0622 # W0622: redefining built-in 'len' @classmethod def _make(cls, iterable, new = tuple.__new__, len = len): """Creates a new point from a sequence or iterable""" result = new(cls, iterable) if len(result) != 2: raise TypeError('Expected 2 arguments, got %d' % len(result)) return result def __repr__(self): """Returns a nicely formatted representation of the point""" return 'Point(x=%r, y=%r)' % self def _asdict(self): """Returns a new dict which maps field names to their values""" return dict(zip(self._fields, self)) # pylint: disable-msg=W0141 # W0141: used builtin function 'map' def _replace(self, **kwds): """Returns a new point object replacing specified fields with new values""" result = self._make(map(kwds.pop, ('x', 'y'), self)) if kwds: raise ValueError('Got unexpected field names: %r' % kwds.keys()) return result def __getnewargs__(self): """Return self as a plain tuple. Used by copy and pickle.""" return tuple(self) x = property(itemgetter(0), doc="Alias for field number 0") y = property(itemgetter(1), doc="Alias for field number 1") def __add__(self, other): """Adds the coordinates of a point to another one""" return self.__class__(x = self.x + other.x, y = self.y + other.y) def __sub__(self, other): """Subtracts the coordinates of a point to another one""" return self.__class__(x = self.x - other.x, y = self.y - other.y) def __mul__(self, scalar): """Multiplies the coordinates by a scalar""" return self.__class__(x = self.x * scalar, y = self.y * scalar) __rmul__ = __mul__ def __div__(self, scalar): """Divides the coordinates by a scalar""" return self.__class__(x = self.x / scalar, y = self.y / scalar) def as_polar(self): """Returns the polar coordinate representation of the point. @return: the radius and the angle in a tuple. """ return len(self), atan2(self.y, self.x) def distance(self, other): """Returns the distance of the point from another one. Example: >>> p1 = Point(5, 7) >>> p2 = Point(8, 3) >>> p1.distance(p2) 5.0 """ dx, dy = self.x - other.x, self.y - other.y return (dx * dx + dy * dy) ** 0.5 def interpolate(self, other, ratio = 0.5): """Linearly interpolates between the coordinates of this point and another one. @param other: the other point @param ratio: the interpolation ratio between 0 and 1. Zero will return this point, 1 will return the other point. """ ratio = float(ratio) return Point(x = self.x * (1.0 - ratio) + other.x * ratio, \ y = self.y * (1.0 - ratio) + other.y * ratio) def length(self): """Returns the length of the vector pointing from the origin to this point.""" return (self.x ** 2 + self.y ** 2) ** 0.5 def normalized(self): """Normalizes the coordinates of the point s.t. its length will be 1 after normalization. Returns the normalized point.""" len = self.length() if len == 0: return Point(x = self.x, y = self.y) return Point(x = self.x / len, y = self.y / len) def sq_length(self): """Returns the squared length of the vector pointing from the origin to this point.""" return (self.x ** 2 + self.y ** 2) def towards(self, other, distance = 0): """Returns the point that is at a given distance from this point towards another one.""" if not distance: return self angle = atan2(other.y - self.y, other.x - self.x) return Point(self.x + distance * cos(angle), self.y + distance * sin(angle)) @classmethod def FromPolar(cls, radius, angle): """Constructs a point from polar coordinates. `radius` is the distance of the point from the origin; `angle` is the angle between the X axis and the vector pointing to the point from the origin. """ return cls(radius * cos(angle), radius * sin(angle)) python-igraph-0.8.0/src/igraph/drawing/text.py0000644000076500000240000003217513370304072021601 0ustar tamasstaff00000000000000""" Drawers for labels on plots. @undocumented: test """ import re from igraph.compat import property from igraph.drawing.baseclasses import AbstractCairoDrawer from warnings import warn __all__ = ["TextAlignment", "TextDrawer"] __license__ = "GPL" __docformat__ = "restructuredtext en" ##################################################################### class TextAlignment(object): """Text alignment constants.""" LEFT, CENTER, RIGHT = "left", "center", "right" TOP, BOTTOM = "top", "bottom" ##################################################################### class TextDrawer(AbstractCairoDrawer): """Class that draws text on a Cairo context. This class supports multi-line text unlike the original Cairo text drawing methods.""" LEFT, CENTER, RIGHT = "left", "center", "right" TOP, BOTTOM = "top", "bottom" def __init__(self, context, text="", halign="center", valign="center"): """Constructs a new instance that will draw the given `text` on the given Cairo `context`.""" super(TextDrawer, self).__init__(context, (0, 0)) self.text = text self.halign = halign self.valign = valign def draw(self, wrap=False): """Draws the text in the current bounding box of the drawer. Since the class itself is an instance of `AbstractCairoDrawer`, it has an attribute named ``bbox`` which will be used as a bounding box. :Parameters: wrap : boolean whether to allow re-wrapping of the text if it does not fit within the bounding box horizontally. """ ctx = self.context bbox = self.bbox text_layout = self.get_text_layout(bbox.left, bbox.top, bbox.width, wrap) if not text_layout: return _, font_descent, line_height = ctx.font_extents()[:3] yb = ctx.text_extents(text_layout[0][2])[1] total_height = len(text_layout) * line_height if self.valign == self.BOTTOM: # Bottom vertical alignment dy = bbox.height - total_height - yb + font_descent elif self.valign == self.CENTER: # Centered vertical alignment dy = (bbox.height - total_height - yb + font_descent + line_height) / 2. else: # Top vertical alignment dy = line_height for ref_x, ref_y, line in text_layout: ctx.move_to(ref_x, ref_y + dy) ctx.show_text(line) ctx.new_path() def get_text_layout(self, x = None, y = None, width = None, wrap = False): """Calculates the layout of the current text. `x` and `y` denote the coordinates where the drawing should start. If they are both ``None``, the current position of the context will be used. Vertical alignment settings are not taken into account in this method as the text is not drawn within a box. :Parameters: x : float or ``None`` The X coordinate of the reference point where the layout should start. y : float or ``None`` The Y coordinate of the reference point where the layout should start. width : float or ``None`` The width of the box in which the text will be fitted. It matters only when the text is right-aligned or centered. The text will overflow the box if any of the lines is longer than the box width and `wrap` is ``False``. wrap : boolean whether to allow re-wrapping of the text if it does not fit within the given width. :Returns: a list consisting of ``(x, y, line)`` tuples where ``x`` and ``y`` refer to reference points on the Cairo canvas and ``line`` refers to the corresponding text that should be plotted there. """ ctx = self.context if x is None or y is None: x, y = ctx.get_current_point() line_height = ctx.font_extents()[2] if wrap: if width and width > 0: iterlines = self._iterlines_wrapped(width) else: warn("ignoring wrap=True as no width was specified") else: iterlines = self._iterlines() result = [] if self.halign == self.CENTER: # Centered alignment if width is None: width = self.text_extents()[2] for line, line_width, x_bearing in iterlines: result.append((x + (width-line_width)/2. - x_bearing, y, line)) y += line_height elif self.halign == self.RIGHT: # Right alignment if width is None: width = self.text_extents()[2] x += width for line, line_width, x_bearing in iterlines: result.append((x - line_width - x_bearing, y, line)) y += line_height else: # Left alignment for line, _, x_bearing in iterlines: result.append((x-x_bearing, y, line)) y += line_height return result def draw_at(self, x = None, y = None, width = None, wrap = False): """Draws the text by setting up an appropriate path on the Cairo context and filling it. `x` and `y` denote the coordinates where the drawing should start. If they are both ``None``, the current position of the context will be used. Vertical alignment settings are not taken into account in this method as the text is not drawn within a box. :Parameters: x : float or ``None`` The X coordinate of the reference point where the drawing should start. y : float or ``None`` The Y coordinate of the reference point where the drawing should start. width : float or ``None`` The width of the box in which the text will be fitted. It matters only when the text is right-aligned or centered. The text will overflow the box if any of the lines is longer than the box width. wrap : boolean whether to allow re-wrapping of the text if it does not fit within the given width. """ ctx = self.context for ref_x, ref_y, line in self.get_text_layout(x, y, width, wrap): ctx.move_to(ref_x, ref_y) ctx.show_text(line) ctx.new_path() def _iterlines(self): """Iterates over the label line by line and returns a tuple containing the folloing for each line: the line itself, the width of the line and the X-bearing of the line.""" ctx = self.context for line in self._text.split("\n"): xb, _, line_width, _, _, _ = ctx.text_extents(line) yield (line, line_width, xb) def _iterlines_wrapped(self, width): """Iterates over the label line by line and returns a tuple containing the folloing for each line: the line itself, the width of the line and the X-bearing of the line. The difference between this method and `_iterlines()` is that this method is allowed to re-wrap the line if necessary. :Parameters: width : float or ``None`` The width of the box in which the text will be fitted. Lines will be wrapped if they are wider than this width. """ ctx = self.context for line in self._text.split("\n"): xb, _, line_width, _, _, _ = ctx.text_extents(line) if line_width <= width: yield (line, line_width, xb) continue # We have to wrap the line current_line, current_width, last_sep_width = [], 0, 0 for match in re.finditer(r"(\S+)(\s+)?", line): word, sep = match.groups() word_width = ctx.text_extents(word)[4] if sep: sep_width = ctx.text_extents(sep)[4] else: sep_width = 0 current_width += word_width if current_width >= width and current_line: yield ("".join(current_line), current_width - word_width, 0) # Starting a new line current_line, current_width = [word], word_width if sep is not None: current_line.append(sep) else: current_width += last_sep_width current_line.append(word) if sep is not None: current_line.append(sep) last_sep_width = sep_width if current_line: yield ("".join(current_line), current_width, 0) @property def text(self): """Returns the text to be drawn.""" return self._text @text.setter def text(self, text): """Sets the text that will be drawn. If `text` is ``None``, it will be mapped to an empty string; otherwise, it will be converted to a string.""" if text is None: self._text = "" else: self._text = str(text) def text_extents(self): """Returns the X-bearing, Y-bearing, width, height, X-advance and Y-advance of the text. For multi-line text, the X-bearing and Y-bearing correspond to the first line, while the X-advance is extracted from the last line. and the Y-advance is the sum of all the Y-advances. The width and height correspond to the entire bounding box of the text.""" lines = self.text.split("\n") if len(lines) <= 1: return self.context.text_extents(self.text) x_bearing, y_bearing, width, height, x_advance, y_advance = \ self.context.text_extents(lines[0]) line_height = self.context.font_extents()[2] for line in lines[1:]: _, _, w, _, x_advance, ya = self.context.text_extents(line) width = max(width, w) height += line_height y_advance += ya return x_bearing, y_bearing, width, height, x_advance, y_advance def test(): """Testing routine for L{TextDrawer}""" import math from igraph.drawing.utils import find_cairo cairo = find_cairo() text = "The quick brown fox\njumps over a\nlazy dog" width, height = (600, 1000) surface = cairo.ImageSurface(cairo.FORMAT_ARGB32, width, height) context = cairo.Context(surface) drawer = TextDrawer(context, text) context.set_source_rgb(1, 1, 1) context.set_font_size(16.) context.rectangle(0, 0, width, height) context.fill() context.set_source_rgb(0.5, 0.5, 0.5) for i in range(200, width, 200): context.move_to(i, 0) context.line_to(i, height) context.stroke() for i in range(200, height, 200): context.move_to(0, i) context.line_to(width, i) context.stroke() context.set_source_rgb(0.75, 0.75, 0.75) context.set_line_width(0.5) for i in range(100, width, 200): context.move_to(i, 0) context.line_to(i, height) context.stroke() for i in range(100, height, 200): context.move_to(0, i) context.line_to(width, i) context.stroke() def mark_point(red, green, blue): """Marks the current point on the canvas by the given color""" x, y = context.get_current_point() context.set_source_rgba(red, green, blue, 0.5) context.arc(x, y, 4, 0, 2 * math.pi) context.fill() # Testing drawer.draw_at() for i, halign in enumerate(("left", "center", "right")): # Mark the reference points context.move_to(i * 200, 40) mark_point(0, 0, 1) context.move_to(i * 200, 140) mark_point(0, 0, 1) # Draw the text context.set_source_rgb(0, 0, 0) drawer.halign = halign drawer.draw_at(i * 200, 40) drawer.draw_at(i * 200, 140, width=200) # Mark the new reference point mark_point(1, 0, 0) # Testing TextDrawer.draw() for i, halign in enumerate(("left", "center", "right")): for j, valign in enumerate(("top", "center", "bottom")): # Draw the text context.set_source_rgb(0, 0, 0) drawer.halign = halign drawer.valign = valign drawer.bbox = (i*200, j*200+200, i*200+200, j*200+400) drawer.draw() # Mark the new reference point mark_point(1, 0, 0) # Testing TextDrawer.wrap() drawer.text = "Jackdaws love my big sphinx of quartz. Yay, wrapping! " + \ "Jackdaws love my big sphinx of quartz.\n\n" + \ "Jackdaws love my big sphinx of quartz." drawer.valign = TextDrawer.TOP for i, halign in enumerate(("left", "center", "right")): context.move_to(i * 200, 840) # Mark the reference point mark_point(0, 0, 1) # Draw the text context.set_source_rgb(0, 0, 0) drawer.halign = halign drawer.draw_at(i * 200, 840, width=199, wrap=True) # Mark the new reference point mark_point(1, 0, 0) surface.write_to_png("test.png") if __name__ == "__main__": test() python-igraph-0.8.0/src/igraph/drawing/metamagic.py0000644000076500000240000003370213104627150022541 0ustar tamasstaff00000000000000"""Auxiliary classes for the default graph drawer in igraph. This module contains heavy metaclass magic. If you don't understand the logic behind these classes, probably you don't need them either. igraph's default graph drawer uses various data sources to determine the visual appearance of vertices and edges. These data sources are the following (in order of precedence): - The keyword arguments passed to the L{igraph.plot()} function (or to L{igraph.Graph.__plot__()} as a matter of fact, since L{igraph.plot()} just passes these attributes on). For instance, a keyword argument named C{vertex_label} can be used to set the labels of vertices. - The attributes of the vertices/edges being drawn. For instance, a vertex that has a C{label} attribute will use that label when drawn by the default graph drawer. - The global configuration of igraph. For instance, if the global L{igraph.config.Configuration} instance has a key called C{plotting.vertex_color}, that will be used as a default color for the vertices. - If all else fails, there is a built-in default; for instance, the default vertex color is C{"red"}. This is hard-wired in the source code. The logic above can be useful in other graph drawers as well, not only in the default one, therefore it is refactored into the classes found in this module. Different graph drawers may inspect different vertex or edge attributes, hence the classes that collect the attributes from the various data sources are generated in run-time using a metaclass called L{AttributeCollectorMeta}. You don't have to use L{AttributeCollectorMeta} directly, just implement a subclass of L{AttributeCollectorBase} and it will ensure that the appropriate metaclass is used. With L{AttributeCollectorBase}, you can use a simple declarative syntax to specify which attributes you are interested in. For example:: class VisualEdgeBuilder(AttributeCollectorBase): arrow_size = 1.0 arrow_width = 1.0 color = ("black", palette.get) width = 1.0 for edge in VisualEdgeBuilder(graph.es): print edge.color The above class is a visual edge builder -- a class that gives the visual attributes of the edges of a graph that is specified at construction time. It specifies that the attributes we are interested in are C{arrow_size}, C{arrow_width}, C{color} and C{width}; the default values are also given. For C{color}, we also specify that a method called {palette.get} should be called on every attribute value to translate color names to RGB values. For the other three attributes, C{float} will implicitly be called on all attribute values, this is inferred from the type of the default value itself. @see: AttributeCollectorMeta, AttributeCollectorBase """ from ConfigParser import NoOptionError from itertools import izip from igraph.configuration import Configuration __all__ = ["AttributeSpecification", "AttributeCollectorBase"] # pylint: disable-msg=R0903 # R0903: too few public methods class AttributeSpecification(object): """Class that describes how the value of a given attribute should be retrieved. The class contains the following members: - C{name}: the name of the attribute. This is also used when we are trying to get its value from a vertex/edge attribute of a graph. - C{alt_name}: alternative name of the attribute. This is used when we are trying to get its value from a Python dict or an L{igraph.Configuration} object. If omitted at construction time, it will be equal to C{name}. - C{default}: the default value of the attribute when none of the sources we try can provide a meaningful value. - C{transform}: optional transformation to be performed on the attribute value. If C{None} or omitted, it defaults to the type of the default value. - C{func}: when given, this function will be called with an index in order to derive the value of the attribute. """ __slots__ = ("name", "alt_name", "default", "transform", "accessor", "func") def __init__(self, name, default=None, alt_name=None, transform=None, func=None): if isinstance(default, tuple): default, transform = default self.name = name self.default = default self.alt_name = alt_name or name self.transform = transform or None self.func = func self.accessor = None if self.transform and not hasattr(self.transform, "__call__"): raise TypeError, "transform must be callable" if self.transform is None and self.default is not None: self.transform = type(self.default) class AttributeCollectorMeta(type): """Metaclass for attribute collector classes Classes that use this metaclass are intended to collect vertex/edge attributes from various sources (a Python dict, a vertex/edge sequence, default values from the igraph configuration and such) in a given order of precedence. See the module documentation for more details. This metaclass enables the user to use a simple declarative syntax to specify which attributes he is interested in. For each vertex/edge attribute, a corresponding class attribute must be defined with a value that describes the default value of that attribute if no other data source provides us with any suitable value. The default value can also be a tuple; in that case, the first element of the tuple is the actual default value, the second element is a converter function that will convert the attribute values to a format expected by the caller who uses the class being defined. There is a special class attribute called C{_kwds_prefix}; this is not used as an attribute declaration. It can contain a string which will be used to derive alternative names for the attributes when the attribute is accessed in a Python dict. This is useful in many situations; for instance, the default graph drawer would want to access the vertex colors using the C{color} vertex attribute, but when it looks at the keyword arguments passed to the original call of L{igraph.Graph.__plot__}, the C{vertex_color} keyword argument should be looked up because we also have colors for the edges. C{_kwds_prefix} will be prepended to the attribute names when they are looked up in a dict of keyword arguments. If you require a more fine-tuned behaviour, you can assign an L{AttributeSpecification} instance to a class attribute directly. @see: AttributeCollectorBase """ def __new__(mcs, name, bases, attrs): attr_specs = [] for attr, value in attrs.iteritems(): if attr.startswith("_") or hasattr(value, "__call__"): continue if isinstance(value, AttributeSpecification): attr_spec = value elif isinstance(value, dict): attr_spec = AttributeSpecification(attr, **value) else: attr_spec = AttributeSpecification(attr, value) attr_specs.append(attr_spec) prefix = attrs.get("_kwds_prefix", None) if prefix: for attr_spec in attr_specs: if attr_spec.name == attr_spec.alt_name: attr_spec.alt_name = "%s%s" % (prefix, attr_spec.name) attrs["_attributes"] = attr_specs attrs["Element"] = mcs.record_generator( "%s.Element" % name, (attr_spec.name for attr_spec in attr_specs) ) return super(AttributeCollectorMeta, mcs).__new__(mcs, \ name, bases, attrs) @classmethod def record_generator(mcs, name, slots): """Generates a simple class that has the given slots and nothing else""" class Element(object): """A simple class that holds the attributes collected by the attribute collector""" __slots__ = tuple(slots) def __init__(self, attrs=()): for attr, value in attrs: setattr(self, attr, value) Element.__name__ = name return Element class AttributeCollectorBase(object): """Base class for attribute collector subclasses. Classes that inherit this class may use a declarative syntax to specify which vertex or edge attributes they intend to collect. See L{AttributeCollectorMeta} for the details. """ __metaclass__ = AttributeCollectorMeta def __init__(self, seq, kwds = None): """Constructs a new attribute collector that uses the given vertex/edge sequence and the given dict as data sources. @param seq: an L{igraph.VertexSeq} or L{igraph.EdgeSeq} class that will be used as a data source for attributes. @param kwds: a Python dict that will be used to override the attributes collected from I{seq} if necessary. """ elt = self.__class__.Element self._cache = [elt() for _ in xrange(len(seq))] self.seq = seq self.kwds = kwds or {} for attr_spec in self._attributes: values = self._collect_attributes(attr_spec) attr_name = attr_spec.name for cache_elt, val in izip(self._cache, values): setattr(cache_elt, attr_name, val) def _collect_attributes(self, attr_spec, config=None): """Collects graph visualization attributes from various sources. This method can be used to collect the attributes required for graph visualization from various sources. Attribute value sources are: - A specific value of a Python dict belonging to a given key. This dict is given by the argument M{self.kwds} at construction time, and the name of the key is determined by the argument specification given in M{attr_spec}. - A vertex or edge sequence of a graph, given in M{self.seq} - The global configuration, given in M{config} - A default value when all other sources fail to provide the value. This is also given in M{attr_spec}. @param attr_spec: an L{AttributeSpecification} object which contains the name of the attribute when it is coming from a list of Python keyword arguments, the name of the attribute when it is coming from the graph attributes directly, the default value of the attribute and an optional callable transformation to call on the values. This can be used to ensure that the attributes are of a given type. @param config: a L{Configuration} object to be used for determining the defaults if all else fails. If C{None}, the global igraph configuration will be used @return: the collected attributes """ kwds = self.kwds seq = self.seq n = len(seq) # Special case if the attribute name is "label" if attr_spec.name == "label": if attr_spec.alt_name in kwds and kwds[attr_spec.alt_name] is None: return [None] * n # If the attribute uses an external callable to derive the attribute # values, call it and store the results if attr_spec.func is not None: func = attr_spec.func result = [func(i) for i in xrange(n)] return result # Get the configuration object if config is None: config = Configuration.instance() # Fetch the defaults from the vertex/edge sequence try: attrs = seq[attr_spec.name] except KeyError: attrs = None # Override them from the keyword arguments (if any) result = kwds.get(attr_spec.alt_name, None) if attrs: if not result: result = attrs else: if isinstance(result, str): result = [result] * n try: len(result) except TypeError: result = [result] * n result = [result[idx] or attrs[idx] \ for idx in xrange(len(result))] # Special case for string overrides, strings are not treated # as sequences here if isinstance(result, str): result = [result] * n # If the result is still not a sequence, make it one try: len(result) except TypeError: result = [result] * n # If it is not a list, ensure that it is a list if not hasattr(result, "extend"): result = list(result) # Ensure that the length is n while len(result) < n: if len(result) <= n/2: result.extend(result) else: result.extend(result[0:(n-len(result))]) # By now, the length of the result vector should be n as requested # Get the configuration defaults try: default = config["plotting.%s" % attr_spec.alt_name] except NoOptionError: default = None if default is None: default = attr_spec.default # Fill the None values with the default values for idx in xrange(len(result)): if result[idx] is None: result[idx] = default # Finally, do the transformation if attr_spec.transform is not None: transform = attr_spec.transform result = [transform(x) for x in result] return result def __getitem__(self, index): """Returns the collected attributes of the vertex/edge with the given index.""" # pylint: disable-msg=E1101 # E1101: instance has no '_attributes' member return self._cache[index] def __len__(self): return len(self.seq) python-igraph-0.8.0/src/igraph/drawing/colors.py0000644000076500000240000036213113104627150022114 0ustar tamasstaff00000000000000# vim:ts=4:sw=4:sts=4:et # -*- coding: utf-8 -*- """ Color handling functions. """ __license__ = u"""\ Copyright (C) 2006-2012 Tamás Nepusz Pázmány Péter sétány 1/a, 1117 Budapest, Hungary This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA """ from igraph.datatypes import Matrix from igraph.utils import str_to_orientation from math import ceil __all__ = ["Palette", "GradientPalette", "AdvancedGradientPalette", \ "RainbowPalette", "PrecalculatedPalette", "ClusterColoringPalette", \ "color_name_to_rgb", "color_name_to_rgba", \ "hsv_to_rgb", "hsva_to_rgba", "hsl_to_rgb", "hsla_to_rgba", \ "rgb_to_hsv", "rgba_to_hsva", "rgb_to_hsl", "rgba_to_hsla", \ "palettes", "known_colors"] class Palette(object): """Base class of color palettes. Color palettes are mappings that assign integers from the range 0..M{n-1} to colors (4-tuples). M{n} is called the size or length of the palette. C{igraph} comes with a number of predefined palettes, so this class is useful for you only if you want to define your own palette. This can be done by subclassing this class and implementing the L{Palette._get} method as necessary. Palettes can also be used as lists or dicts, for the C{__getitem__} method is overridden properly to call L{Palette.get}. """ def __init__(self, n): self._length = n self._cache = {} def clear_cache(self): """Clears the result cache. The return values of L{Palette.get} are cached. Use this method to clear the cache. """ self._cache = {} def get(self, v): """Returns the given color from the palette. Values are cached: if the specific value given has already been looked up, its value will be returned from the cache instead of calculating it again. Use L{Palette.clear_cache} to clear the cache if necessary. @note: you shouldn't override this method in subclasses, override L{_get} instead. If you override this method, lookups in the L{known_colors} dict won't work, so you won't be able to refer to colors by names or RGBA quadruplets, only by integer indices. The caching functionality will disappear as well. However, feel free to override this method if this is exactly the behaviour you want. @param v: the color to be retrieved. If it is an integer, it is passed to L{Palette._get} to be translated to an RGBA quadruplet. Otherwise it is passed to L{color_name_to_rgb()} to determine the RGBA values. @return: the color as an RGBA quadruplet""" if isinstance(v, list): v = tuple(v) try: return self._cache[v] except KeyError: pass if isinstance(v, (int, long)): if v < 0: raise IndexError("color index must be non-negative") if v >= self._length: raise IndexError("color index too large") result = self._get(v) else: result = color_name_to_rgba(v) self._cache[v] = result return result def get_many(self, colors): """Returns multiple colors from the palette. Values are cached: if the specific value given has already been looked upon, its value will be returned from the cache instead of calculating it again. Use L{Palette.clear_cache} to clear the cache if necessary. @param colors: the list of colors to be retrieved. The palette class tries to make an educated guess here: if it is not possible to interpret the value you passed here as a list of colors, the class will simply try to interpret it as a single color by forwarding the value to L{Palette.get}. @return: the colors as a list of RGBA quadruplets. The result will be a list even if you passed a single color index or color name. """ if isinstance(colors, (basestring, int, long)): # Single color name or index return [self.get(colors)] # Multiple colors return [self.get(color) for color in colors] def _get(self, v): """Override this method in a subclass to create a custom palette. You can safely assume that v is an integer in the range 0..M{n-1} where M{n} is the size of the palette. @param v: numerical index of the color to be retrieved @return: a 4-tuple containing the RGBA values""" raise NotImplementedError("abstract class") __getitem__ = get @property def length(self): """Returns the number of colors in this palette""" return self._length def __len__(self): """Returns the number of colors in this palette""" return self._length def __plot__(self, context, bbox, palette, *args, **kwds): """Plots the colors of the palette on the given Cairo context Supported keyword arguments are: - C{border_width}: line width of the border shown around the palette. If zero or negative, the border is turned off. Default is C{1}. - C{grid_width}: line width of the grid that separates palette cells. If zero or negative, the grid is turned off. The grid is also turned off if the size of a cell is less than three times the given line width. Default is C{0}. Fractional widths are also allowed. - C{orientation}: the orientation of the palette. Must be one of the following values: C{left-right}, C{bottom-top}, C{right-left} or C{top-bottom}. Possible aliases: C{horizontal} = C{left-right}, C{vertical} = C{bottom-top}, C{lr} = C{left-right}, C{rl} = C{right-left}, C{tb} = C{top-bottom}, C{bt} = C{bottom-top}. The default is C{left-right}. """ border_width = float(kwds.get("border_width", 1.)) grid_width = float(kwds.get("grid_width", 0.)) orientation = str_to_orientation(kwds.get("orientation", "lr")) # Construct a matrix and plot that indices = range(len(self)) if orientation in ("rl", "bt"): indices.reverse() if orientation in ("lr", "rl"): matrix = Matrix([indices]) else: matrix = Matrix([[i] for i in indices]) return matrix.__plot__(context, bbox, self, style="palette", square=False, grid_width=grid_width, border_width=border_width) def __repr__(self): return "<%s with %d colors>" % (self.__class__.__name__, self._length) class GradientPalette(Palette): """Base class for gradient palettes Gradient palettes contain a gradient between two given colors. Example: >>> pal = GradientPalette("red", "blue", 5) >>> pal.get(0) (1.0, 0.0, 0.0, 1.0) >>> pal.get(2) (0.5, 0.0, 0.5, 1.0) >>> pal.get(4) (0.0, 0.0, 1.0, 1.0) """ def __init__(self, color1, color2, n=256): """Creates a gradient palette. @param color1: the color where the gradient starts. @param color2: the color where the gradient ends. @param n: the number of colors in the palette. """ Palette.__init__(self, n) self._color1 = color_name_to_rgba(color1) self._color2 = color_name_to_rgba(color2) def _get(self, v): """Returns the color corresponding to the given color index. @param v: numerical index of the color to be retrieved @return: a 4-tuple containing the RGBA values""" ratio = float(v)/(len(self)-1) return tuple(self._color1[x]*(1-ratio) + \ self._color2[x]*ratio for x in range(4)) class AdvancedGradientPalette(Palette): """Advanced gradient that consists of more than two base colors. Example: >>> pal = AdvancedGradientPalette(["red", "black", "blue"], n=9) >>> pal.get(2) (0.5, 0.0, 0.0, 1.0) >>> pal.get(7) (0.0, 0.0, 0.75, 1.0) """ def __init__(self, colors, indices=None, n=256): """Creates an advanced gradient palette @param colors: the colors in the gradient. @param indices: the color indices belonging to the given colors. If C{None}, the colors are distributed equidistantly @param n: the total number of colors in the palette """ Palette.__init__(self, n) if indices is None: diff = float(n-1) / (len(colors)-1) indices = [i * diff for i in xrange(len(colors))] elif not hasattr(indices, "__iter__"): indices = [float(x) for x in indices] self._indices, self._colors = zip(*sorted(zip(indices, colors))) self._colors = [color_name_to_rgba(color) for color in self._colors] self._dists = [curr-prev for curr, prev in \ zip(self._indices[1:], self._indices)] def _get(self, v): """Returns the color corresponding to the given color index. @param v: numerical index of the color to be retrieved @return: a 4-tuple containing the RGBA values""" colors = self._colors for i in xrange(len(self._indices)-1): if self._indices[i] <= v and self._indices[i+1] >= v: dist = self._dists[i] ratio = float(v-self._indices[i])/dist return tuple([colors[i][x]*(1-ratio)+colors[i+1][x]*ratio \ for x in range(4)]) return (0., 0., 0., 1.) class RainbowPalette(Palette): """A palette that varies the hue of the colors along a scale. Colors in a rainbow palette all have the same saturation, value and alpha components, while the hue is varied between two given extremes linearly. This palette has the advantage that it wraps around nicely if the hue is varied between zero and one (which is the default). Example: >>> pal = RainbowPalette(n=120) >>> pal.get(0) (1.0, 0.0, 0.0, 1.0) >>> pal.get(20) (1.0, 1.0, 0.0, 1.0) >>> pal.get(40) (0.0, 1.0, 0.0, 1.0) >>> pal = RainbowPalette(n=120, s=1, v=0.5, alpha=0.75) >>> pal.get(60) (0.0, 0.5, 0.5, 0.75) >>> pal.get(80) (0.0, 0.0, 0.5, 0.75) >>> pal.get(100) (0.5, 0.0, 0.5, 0.75) >>> pal = RainbowPalette(n=120) >>> pal2 = RainbowPalette(n=120, start=0.5, end=0.5) >>> pal.get(60) == pal2.get(0) True >>> pal.get(90) == pal2.get(30) True This palette was modeled after the C{rainbow} command of R. """ def __init__(self, n=256, s=1, v=1, start=0, end=1, alpha=1): """Creates a rainbow palette. @param n: the number of colors in the palette. @param s: the saturation of the colors in the palette. @param v: the value component of the colors in the palette. @param start: the hue at which the rainbow begins (between 0 and 1). @param end: the hue at which the rainbow ends (between 0 and 1). @param alpha: the alpha component of the colors in the palette. """ Palette.__init__(self, n) self._s = float(clamp(s, 0, 1)) self._v = float(clamp(v, 0, 1)) self._alpha = float(clamp(alpha, 0, 1)) self._start = float(start) if end == self._start: end += 1 self._dh = (end - self._start) / n def _get(self, v): """Returns the color corresponding to the given color index. @param v: numerical index of the color to be retrieved @return: a 4-tuple containing the RGBA values""" return hsva_to_rgba(self._start + v * self._dh, self._s, self._v, self._alpha) class PrecalculatedPalette(Palette): """A palette that returns colors from a pre-calculated list of colors""" def __init__(self, l): """Creates the palette backed by the given list. The list must contain RGBA quadruplets or color names, which will be resolved first by L{color_name_to_rgba()}. Anything that is understood by L{color_name_to_rgba()} is OK here.""" Palette.__init__(self, len(l)) for idx, color in enumerate(l): if isinstance(color, basestring): color = color_name_to_rgba(color) self._cache[idx] = color def _get(self, v): """This method will only be called if the requested color index is outside the size of the palette. In that case, we throw an exception""" raise ValueError("palette index outside bounds: %s" % v) class ClusterColoringPalette(PrecalculatedPalette): """A palette suitable for coloring vertices when plotting a clustering. This palette tries to make sure that the colors are easily distinguishable. This is achieved by using a set of base colors and their lighter and darker variants, depending on the number of elements in the palette. When the desired size of the palette is less than or equal to the number of base colors (denoted by M{n}), only the bsae colors will be used. When the size of the palette is larger than M{n} but less than M{2*n}, the base colors and their lighter variants will be used. Between M{2*n} and M{3*n}, the base colors and their lighter and darker variants will be used. Above M{3*n}, more darker and lighter variants will be generated, but this makes the individual colors less and less distinguishable. """ def __init__(self, n): base_colors = ["red", "green", "blue", "yellow", \ "magenta", "cyan", "#808080"] base_colors = [color_name_to_rgba(name) for name in base_colors] num_base_colors = len(base_colors) colors = base_colors[:] blocks_to_add = ceil(float(n - num_base_colors) / num_base_colors) ratio_increment = 1.0 / (ceil(blocks_to_add / 2.0) + 1) adding_darker = True ratio = ratio_increment while len(colors) < n: if adding_darker: new_block = [darken(color, ratio) for color in base_colors] else: new_block = [lighten(color, ratio) for color in base_colors] ratio += ratio_increment colors.extend(new_block) adding_darker = not adding_darker colors = colors[0:n] PrecalculatedPalette.__init__(self, colors) def clamp(value, min_value, max_value): """Clamps the given value between min and max""" if value > max_value: return max_value if value < min_value: return min_value return value def color_name_to_rgb(color, palette=None): """Converts a color given in one of the supported color formats to R-G-B values. This is done by calling L{color_name_to_rgba} and then throwing away the alpha value. @see: color_name_to_rgba for more details about what formats are understood by this function. """ return color_name_to_rgba(color, palette)[:3] def color_name_to_rgba(color, palette=None): """Converts a color given in one of the supported color formats to R-G-B-A values. Examples: >>> color_name_to_rgba("red") (1.0, 0.0, 0.0, 1.0) >>> color_name_to_rgba("#ff8000") == (1.0, 128/255.0, 0.0, 1.0) True >>> color_name_to_rgba("#ff800080") == (1.0, 128/255.0, 0.0, 128/255.0) True >>> color_name_to_rgba("#08f") == (0.0, 136/255.0, 1.0, 1.0) True >>> color_name_to_rgba("rgb(100%, 50%, 0%)") (1.0, 0.5, 0.0, 1.0) >>> color_name_to_rgba("rgba(100%, 50%, 0%, 25%)") (1.0, 0.5, 0.0, 0.25) >>> color_name_to_rgba("hsla(120, 100%, 50%, 0.5)") (0.0, 1.0, 0.0, 0.5) >>> color_name_to_rgba("hsl(60, 100%, 50%)") (1.0, 1.0, 0.0, 1.0) >>> color_name_to_rgba("hsv(60, 100%, 100%)") (1.0, 1.0, 0.0, 1.0) @param color: the color to be converted in one of the following formats: - B{CSS3 color specification}: C{#rrggbb}, C{#rgb}, C{#rrggbbaa}, C{#rgba}, C{rgb(red, green, blue)}, C{rgba(red, green, blue, alpha)}, C{hsl(hue, saturation, lightness)}, C{hsla(hue, saturation, lightness, alpha)}, C{hsv(hue, saturation, value)} and C{hsva(hue, saturation, value, alpha)} where the components are given as hexadecimal numbers in the first four cases and as decimals or percentages (0%-100%) in the remaining cases. Red, green and blue components are between 0 and 255; hue is between 0 and 360; saturation, lightness and value is between 0 and 100; alpha is between 0 and 1. - B{Valid HTML color names}, i.e. those that are present in the HTML 4.0 specification - B{Valid X11 color names}, see U{http://en.wikipedia.org/wiki/X11_color_names} - B{Red-green-blue components} given separately in either a comma-, slash- or whitespace-separated string or a list or a tuple, in the range of 0-255. An alpha value of 255 (maximal opacity) will be assumed. - B{Red-green-blue-alpha components} given separately in either a comma-, slash- or whitespace-separated string or a list or a tuple, in the range of 0-255 - B{A single palette index} given either as a string or a number. Uses the palette given in the C{palette} parameter of the method call. @param palette: the palette to be used if a single number is passed to the method. Must be an instance of L{colors.Palette}. @return: the RGBA values corresponding to the given color in a 4-tuple. Since these colors are primarily used by Cairo routines, the tuples contain floats in the range 0.0-1.0 """ if not isinstance(color, basestring): if hasattr(color, "__iter__"): components = list(color) else: # A single index is given as a number try: components = palette.get(color) except AttributeError: raise ValueError("palette index used when no palette was given") if len(components) < 4: components += [1.] * (4 - len(components)) else: if color[0] == '#': color = color[1:] if len(color) == 3: components = [int(i, 16) * 17. / 255. for i in color] components.append(1.0) elif len(color) == 4: components = [int(i, 16) * 17. / 255. for i in color] elif len(color) == 6: components = [int(color[i:i+2], 16) / 255. for i in (0, 2, 4)] components.append(1.0) elif len(color) == 8: components = [int(color[i:i+2], 16) / 255. for i in (0, 2, 4, 6)] elif color.lower() in known_colors: components = known_colors[color.lower()] else: color_mode = "rgba" maximums = (255.0, 255.0, 255.0, 1.0) for mode in ["rgb(", "rgba(", "hsv(", "hsva(", "hsl(", "hsla("]: if color.startswith(mode) and color[-1] == ")": color = color[len(mode):-1] color_mode = mode[:-1] if mode[0] == "h": maximums = (360.0, 100.0, 100.0, 1.0) break if " " in color or "/" in color or "," in color: color = color.replace(",", " ").replace("/", " ") components = color.split() for idx, comp in enumerate(components): if comp[-1] == "%": components[idx] = float(comp[:-1])/100. else: components[idx] = float(comp)/maximums[idx] if len(components) < 4: components += [1.] * (4 - len(components)) if color_mode[:3] == "hsv": components = hsva_to_rgba(*components) elif color_mode[:3] == "hsl": components = hsla_to_rgba(*components) else: components = palette.get(int(color)) # At this point, the components are floats return tuple(clamp(val, 0., 1.) for val in components) def color_to_html_format(color): """Formats a color given as a 3-tuple or 4-tuple in HTML format. The HTML format is simply given by C{#rrggbbaa}, where C{rr} gives the red component in hexadecimal format, C{gg} gives the green component C{bb} gives the blue component and C{gg} gives the alpha level. The alpha level is optional. """ color = [int(clamp(component * 256, 0, 255)) for component in color] if len(color) == 4: return "#{0:02X}{1:02X}{2:02X}{3:02X}".format(*color) return "#{0:02X}{1:02X}{2:02X}".format(*color) def darken(color, ratio=0.5): """Creates a darker version of a color given by an RGB triplet. This is done by mixing the original color with black using the given ratio. A ratio of 1.0 will yield a completely black color, a ratio of 0.0 will yield the original color. The alpha values are left intact. """ ratio = 1.0 - ratio red, green, blue, alpha = color return (red * ratio, green * ratio, blue * ratio, alpha) def hsla_to_rgba(h, s, l, alpha = 1.0): """Converts a color given by its HSLA coordinates (hue, saturation, lightness, alpha) to RGBA coordinates. Each of the HSLA coordinates must be in the range [0, 1]. """ # This is based on the formulae found at: # http://en.wikipedia.org/wiki/HSL_and_HSV c = s*(1 - 2*abs(l - 0.5)) h1 = (h*6) % 6 x = c*(1 - abs(h1 % 2 - 1)) m = l - c/2. h1 = int(h1) if h1 < 3: if h1 < 1: return (c+m, x+m, m, alpha) elif h1 < 2: return (x+m, c+m, m, alpha) else: return (m, c+m, x+m, alpha) else: if h1 < 4: return (m, x+m, c+m, alpha) elif h1 < 5: return (x+m, m, c+m, alpha) else: return (c+m, m, x+m, alpha) def hsl_to_rgb(h, s, l): """Converts a color given by its HSL coordinates (hue, saturation, lightness) to RGB coordinates. Each of the HSL coordinates must be in the range [0, 1]. """ return hsla_to_rgba(h, s, l)[:3] def hsva_to_rgba(h, s, v, alpha = 1.0): """Converts a color given by its HSVA coordinates (hue, saturation, value, alpha) to RGB coordinates. Each of the HSVA coordinates must be in the range [0, 1]. """ # This is based on the formulae found at: # http://en.wikipedia.org/wiki/HSL_and_HSV c = v*s h1 = (h*6) % 6 x = c*(1 - abs(h1 % 2 - 1)) m = v-c h1 = int(h1) if h1 < 3: if h1 < 1: return (c+m, x+m, m, alpha) elif h1 < 2: return (x+m, c+m, m, alpha) else: return (m, c+m, x+m, alpha) else: if h1 < 4: return (m, x+m, c+m, alpha) elif h1 < 5: return (x+m, m, c+m, alpha) else: return (c+m, m, x+m, alpha) def hsv_to_rgb(h, s, v): """Converts a color given by its HSV coordinates (hue, saturation, value) to RGB coordinates. Each of the HSV coordinates must be in the range [0, 1]. """ return hsva_to_rgba(h, s, v)[:3] def rgba_to_hsla(r, g, b, alpha=1.0): """Converts a color given by its RGBA coordinates to HSLA coordinates (hue, saturation, lightness, alpha). Each of the RGBA coordinates must be in the range [0, 1]. """ alpha = float(alpha) rgb_min, rgb_max = float(min(r, g, b)), float(max(r, g, b)) if rgb_min == rgb_max: return 0.0, 0.0, rgb_min, alpha lightness = (rgb_min + rgb_max) / 2.0 d = rgb_max - rgb_min if lightness > 0.5: sat = d / (2 - rgb_max - rgb_min) else: sat = d / (rgb_max + rgb_min) d *= 6.0 if rgb_max == r: hue = (g - b) / d if g < b: hue += 1 elif rgb_max == g: hue = 1/3.0 + (b - r) / d else: hue = 2/3.0 + (r - g) / d return hue, sat, lightness, alpha def rgba_to_hsva(r, g, b, alpha=1.0): """Converts a color given by its RGBA coordinates to HSVA coordinates (hue, saturation, value, alpha). Each of the RGBA coordinates must be in the range [0, 1]. """ # This is based on the formulae found at: # http://en.literateprograms.org/RGB_to_HSV_color_space_conversion_(C) rgb_min, rgb_max = float(min(r, g, b)), float(max(r, g, b)) alpha = float(alpha) value = float(rgb_max) if value <= 0: return 0.0, 0.0, 0.0, alpha sat = 1.0 - rgb_min / value if sat <= 0: return 0.0, 0.0, value, alpha d = rgb_max - rgb_min r = (r - rgb_min) / d g = (g - rgb_min) / d b = (b - rgb_min) / d rgb_max = max(r, g, b) if rgb_max == r: hue = 0.0 + (g - b) / 6.0 if hue < 0: hue += 1 elif rgb_max == g: hue = 1/3.0 + (b - r) / 6.0 else: hue = 2/3.0 + (r - g) / 6.0 return hue, sat, value, alpha def rgb_to_hsl(r, g, b): """Converts a color given by its RGB coordinates to HSL coordinates (hue, saturation, lightness). Each of the RGB coordinates must be in the range [0, 1]. """ return rgba_to_hsla(r, g, b)[:3] def rgb_to_hsv(r, g, b): """Converts a color given by its RGB coordinates to HSV coordinates (hue, saturation, value). Each of the RGB coordinates must be in the range [0, 1]. """ return rgba_to_hsva(r, g, b)[:3] def lighten(color, ratio=0.5): """Creates a lighter version of a color given by an RGB triplet. This is done by mixing the original color with white using the given ratio. A ratio of 1.0 will yield a completely white color, a ratio of 0.0 will yield the original color. """ red, green, blue, alpha = color return (red + (1.0 - red) * ratio, green + (1.0 - green) * ratio, blue + (1.0 - blue) * ratio, alpha) known_colors = \ { 'alice blue': (0.94117647058823528, 0.97254901960784312, 1.0, 1.0), 'aliceblue': (0.94117647058823528, 0.97254901960784312, 1.0, 1.0), 'antique white': ( 0.98039215686274506, 0.92156862745098034, 0.84313725490196079, 1.0), 'antiquewhite': ( 0.98039215686274506, 0.92156862745098034, 0.84313725490196079, 1.0), 'antiquewhite1': (1.0, 0.93725490196078431, 0.85882352941176465, 1.0), 'antiquewhite2': ( 0.93333333333333335, 0.87450980392156863, 0.80000000000000004, 1.0), 'antiquewhite3': ( 0.80392156862745101, 0.75294117647058822, 0.69019607843137254, 1.0), 'antiquewhite4': ( 0.54509803921568623, 0.51372549019607838, 0.47058823529411764, 1.0), 'aqua': (0.0, 1.0, 1.0, 1.0), 'aquamarine': (0.49803921568627452, 1.0, 0.83137254901960789, 1.0), 'aquamarine1': (0.49803921568627452, 1.0, 0.83137254901960789, 1.0), 'aquamarine2': ( 0.46274509803921571, 0.93333333333333335, 0.77647058823529413, 1.0), 'aquamarine3': ( 0.40000000000000002, 0.80392156862745101, 0.66666666666666663, 1.0), 'aquamarine4': ( 0.27058823529411763, 0.54509803921568623, 0.45490196078431372, 1.0), 'azure': (0.94117647058823528, 1.0, 1.0, 1.0), 'azure1': (0.94117647058823528, 1.0, 1.0, 1.0), 'azure2': ( 0.8784313725490196, 0.93333333333333335, 0.93333333333333335, 1.0), 'azure3': ( 0.75686274509803919, 0.80392156862745101, 0.80392156862745101, 1.0), 'azure4': ( 0.51372549019607838, 0.54509803921568623, 0.54509803921568623, 1.0), 'beige': ( 0.96078431372549022, 0.96078431372549022, 0.86274509803921573, 1.0), 'bisque': (1.0, 0.89411764705882357, 0.7686274509803922, 1.0), 'bisque1': (1.0, 0.89411764705882357, 0.7686274509803922, 1.0), 'bisque2': ( 0.93333333333333335, 0.83529411764705885, 0.71764705882352942, 1.0), 'bisque3': ( 0.80392156862745101, 0.71764705882352942, 0.61960784313725492, 1.0), 'bisque4': ( 0.54509803921568623, 0.49019607843137253, 0.41960784313725491, 1.0), 'black': (0.0, 0.0, 0.0, 1.0), 'blanched almond': (1.0, 0.92156862745098034, 0.80392156862745101, 1.0), 'blanchedalmond': (1.0, 0.92156862745098034, 0.80392156862745101, 1.0), 'blue': (0.0, 0.0, 1.0, 1.0), 'blue violet': ( 0.54117647058823526, 0.16862745098039217, 0.88627450980392153, 1.0), 'blue1': (0.0, 0.0, 1.0, 1.0), 'blue2': (0.0, 0.0, 0.93333333333333335, 1.0), 'blue3': (0.0, 0.0, 0.80392156862745101, 1.0), 'blue4': (0.0, 0.0, 0.54509803921568623, 1.0), 'blueviolet': ( 0.54117647058823526, 0.16862745098039217, 0.88627450980392153, 1.0), 'brown': ( 0.6470588235294118, 0.16470588235294117, 0.16470588235294117, 1.0), 'brown1': (1.0, 0.25098039215686274, 0.25098039215686274, 1.0), 'brown2': ( 0.93333333333333335, 0.23137254901960785, 0.23137254901960785, 1.0), 'brown3': ( 0.80392156862745101, 0.20000000000000001, 0.20000000000000001, 1.0), 'brown4': ( 0.54509803921568623, 0.13725490196078433, 0.13725490196078433, 1.0), 'burlywood': ( 0.87058823529411766, 0.72156862745098038, 0.52941176470588236, 1.0), 'burlywood1': (1.0, 0.82745098039215681, 0.60784313725490191, 1.0), 'burlywood2': ( 0.93333333333333335, 0.77254901960784317, 0.56862745098039214, 1.0), 'burlywood3': ( 0.80392156862745101, 0.66666666666666663, 0.49019607843137253, 1.0), 'burlywood4': ( 0.54509803921568623, 0.45098039215686275, 0.33333333333333331, 1.0), 'cadet blue': ( 0.37254901960784315, 0.61960784313725492, 0.62745098039215685, 1.0), 'cadetblue': ( 0.37254901960784315, 0.61960784313725492, 0.62745098039215685, 1.0), 'cadetblue1': (0.59607843137254901, 0.96078431372549022, 1.0, 1.0), 'cadetblue2': ( 0.55686274509803924, 0.89803921568627454, 0.93333333333333335, 1.0), 'cadetblue3': ( 0.47843137254901963, 0.77254901960784317, 0.80392156862745101, 1.0), 'cadetblue4': ( 0.32549019607843138, 0.52549019607843139, 0.54509803921568623, 1.0), 'chartreuse': (0.49803921568627452, 1.0, 0.0, 1.0), 'chartreuse1': (0.49803921568627452, 1.0, 0.0, 1.0), 'chartreuse2': (0.46274509803921571, 0.93333333333333335, 0.0, 1.0), 'chartreuse3': (0.40000000000000002, 0.80392156862745101, 0.0, 1.0), 'chartreuse4': (0.27058823529411763, 0.54509803921568623, 0.0, 1.0), 'chocolate': ( 0.82352941176470584, 0.41176470588235292, 0.11764705882352941, 1.0), 'chocolate1': (1.0, 0.49803921568627452, 0.14117647058823529, 1.0), 'chocolate2': ( 0.93333333333333335, 0.46274509803921571, 0.12941176470588237, 1.0), 'chocolate3': ( 0.80392156862745101, 0.40000000000000002, 0.11372549019607843, 1.0), 'chocolate4': ( 0.54509803921568623, 0.27058823529411763, 0.074509803921568626, 1.0), 'coral': (1.0, 0.49803921568627452, 0.31372549019607843, 1.0), 'coral1': (1.0, 0.44705882352941179, 0.33725490196078434, 1.0), 'coral2': ( 0.93333333333333335, 0.41568627450980394, 0.31372549019607843, 1.0), 'coral3': ( 0.80392156862745101, 0.35686274509803922, 0.27058823529411763, 1.0), 'coral4': ( 0.54509803921568623, 0.24313725490196078, 0.18431372549019609, 1.0), 'cornflower blue': ( 0.39215686274509803, 0.58431372549019611, 0.92941176470588238, 1.0), 'cornflowerblue': ( 0.39215686274509803, 0.58431372549019611, 0.92941176470588238, 1.0), 'cornsilk': (1.0, 0.97254901960784312, 0.86274509803921573, 1.0), 'cornsilk1': (1.0, 0.97254901960784312, 0.86274509803921573, 1.0), 'cornsilk2': ( 0.93333333333333335, 0.90980392156862744, 0.80392156862745101, 1.0), 'cornsilk3': ( 0.80392156862745101, 0.78431372549019607, 0.69411764705882351, 1.0), 'cornsilk4': ( 0.54509803921568623, 0.53333333333333333, 0.47058823529411764, 1.0), 'crimson': ( 0.8627450980392157, 0.0784313725490196, 0.23529411764705882, 1.0), 'cyan': (0.0, 1.0, 1.0, 1.0), 'cyan1': (0.0, 1.0, 1.0, 1.0), 'cyan2': (0.0, 0.93333333333333335, 0.93333333333333335, 1.0), 'cyan3': (0.0, 0.80392156862745101, 0.80392156862745101, 1.0), 'cyan4': (0.0, 0.54509803921568623, 0.54509803921568623, 1.0), 'dark blue': (0.0, 0.0, 0.54509803921568623, 1.0), 'dark cyan': (0.0, 0.54509803921568623, 0.54509803921568623, 1.0), 'dark goldenrod': ( 0.72156862745098038, 0.52549019607843139, 0.043137254901960784, 1.0), 'dark gray': ( 0.66274509803921566, 0.66274509803921566, 0.66274509803921566, 1.0), 'dark green': (0.0, 0.39215686274509803, 0.0, 1.0), 'dark grey': ( 0.66274509803921566, 0.66274509803921566, 0.66274509803921566, 1.0), 'dark khaki': ( 0.74117647058823533, 0.71764705882352942, 0.41960784313725491, 1.0), 'dark magenta': (0.54509803921568623, 0.0, 0.54509803921568623, 1.0), 'dark olive green': ( 0.33333333333333331, 0.41960784313725491, 0.18431372549019609, 1.0), 'dark orange': (1.0, 0.5490196078431373, 0.0, 1.0), 'dark orchid': ( 0.59999999999999998, 0.19607843137254902, 0.80000000000000004, 1.0), 'dark red': (0.54509803921568623, 0.0, 0.0, 1.0), 'dark salmon': ( 0.9137254901960784, 0.58823529411764708, 0.47843137254901963, 1.0), 'dark sea green': ( 0.5607843137254902, 0.73725490196078436, 0.5607843137254902, 1.0), 'dark slate blue': ( 0.28235294117647058, 0.23921568627450981, 0.54509803921568623, 1.0), 'dark slate gray': ( 0.18431372549019609, 0.30980392156862746, 0.30980392156862746, 1.0), 'dark slate grey': ( 0.18431372549019609, 0.30980392156862746, 0.30980392156862746, 1.0), 'dark turquoise': (0.0, 0.80784313725490198, 0.81960784313725488, 1.0), 'dark violet': (0.58039215686274515, 0.0, 0.82745098039215681, 1.0), 'darkblue': (0.0, 0.0, 0.54509803921568623, 1.0), 'darkcyan': (0.0, 0.54509803921568623, 0.54509803921568623, 1.0), 'darkgoldenrod': ( 0.72156862745098038, 0.52549019607843139, 0.043137254901960784, 1.0), 'darkgoldenrod1': (1.0, 0.72549019607843135, 0.058823529411764705, 1.0), 'darkgoldenrod2': ( 0.93333333333333335, 0.67843137254901964, 0.054901960784313725, 1.0), 'darkgoldenrod3': ( 0.80392156862745101, 0.58431372549019611, 0.047058823529411764, 1.0), 'darkgoldenrod4': ( 0.54509803921568623, 0.396078431372549, 0.031372549019607843, 1.0), 'darkgray': ( 0.66274509803921566, 0.66274509803921566, 0.66274509803921566, 1.0), 'darkgreen': (0.0, 0.39215686274509803, 0.0, 1.0), 'darkgrey': ( 0.66274509803921566, 0.66274509803921566, 0.66274509803921566, 1.0), 'darkkhaki': ( 0.74117647058823533, 0.71764705882352942, 0.41960784313725491, 1.0), 'darkmagenta': (0.54509803921568623, 0.0, 0.54509803921568623, 1.0), 'darkolivegreen': ( 0.33333333333333331, 0.41960784313725491, 0.18431372549019609, 1.0), 'darkolivegreen1': (0.792156862745098, 1.0, 0.4392156862745098, 1.0), 'darkolivegreen2': ( 0.73725490196078436, 0.93333333333333335, 0.40784313725490196, 1.0), 'darkolivegreen3': ( 0.63529411764705879, 0.80392156862745101, 0.35294117647058826, 1.0), 'darkolivegreen4': ( 0.43137254901960786, 0.54509803921568623, 0.23921568627450981, 1.0), 'darkorange': (1.0, 0.5490196078431373, 0.0, 1.0), 'darkorange1': (1.0, 0.49803921568627452, 0.0, 1.0), 'darkorange2': (0.93333333333333335, 0.46274509803921571, 0.0, 1.0), 'darkorange3': (0.80392156862745101, 0.40000000000000002, 0.0, 1.0), 'darkorange4': (0.54509803921568623, 0.27058823529411763, 0.0, 1.0), 'darkorchid': ( 0.59999999999999998, 0.19607843137254902, 0.80000000000000004, 1.0), 'darkorchid1': (0.74901960784313726, 0.24313725490196078, 1.0, 1.0), 'darkorchid2': ( 0.69803921568627447, 0.22745098039215686, 0.93333333333333335, 1.0), 'darkorchid3': ( 0.60392156862745094, 0.19607843137254902, 0.80392156862745101, 1.0), 'darkorchid4': ( 0.40784313725490196, 0.13333333333333333, 0.54509803921568623, 1.0), 'darkred': (0.54509803921568623, 0.0, 0.0, 1.0), 'darksalmon': ( 0.9137254901960784, 0.58823529411764708, 0.47843137254901963, 1.0), 'darkseagreen': ( 0.5607843137254902, 0.73725490196078436, 0.5607843137254902, 1.0), 'darkseagreen1': (0.75686274509803919, 1.0, 0.75686274509803919, 1.0), 'darkseagreen2': ( 0.70588235294117652, 0.93333333333333335, 0.70588235294117652, 1.0), 'darkseagreen3': ( 0.60784313725490191, 0.80392156862745101, 0.60784313725490191, 1.0), 'darkseagreen4': ( 0.41176470588235292, 0.54509803921568623, 0.41176470588235292, 1.0), 'darkslateblue': ( 0.28235294117647058, 0.23921568627450981, 0.54509803921568623, 1.0), 'darkslategray': ( 0.18431372549019609, 0.30980392156862746, 0.30980392156862746, 1.0), 'darkslategray1': (0.59215686274509804, 1.0, 1.0, 1.0), 'darkslategray2': ( 0.55294117647058827, 0.93333333333333335, 0.93333333333333335, 1.0), 'darkslategray3': ( 0.47450980392156861, 0.80392156862745101, 0.80392156862745101, 1.0), 'darkslategray4': ( 0.32156862745098042, 0.54509803921568623, 0.54509803921568623, 1.0), 'darkslategrey': ( 0.18431372549019609, 0.30980392156862746, 0.30980392156862746, 1.0), 'darkturquoise': (0.0, 0.80784313725490198, 0.81960784313725488, 1.0), 'darkviolet': (0.58039215686274515, 0.0, 0.82745098039215681, 1.0), 'deep pink': (1.0, 0.078431372549019607, 0.57647058823529407, 1.0), 'deep sky blue': (0.0, 0.74901960784313726, 1.0, 1.0), 'deeppink': (1.0, 0.078431372549019607, 0.57647058823529407, 1.0), 'deeppink1': (1.0, 0.078431372549019607, 0.57647058823529407, 1.0), 'deeppink2': ( 0.93333333333333335, 0.070588235294117646, 0.53725490196078429, 1.0), 'deeppink3': ( 0.80392156862745101, 0.062745098039215685, 0.46274509803921571, 1.0), 'deeppink4': ( 0.54509803921568623, 0.039215686274509803, 0.31372549019607843, 1.0), 'deepskyblue': (0.0, 0.74901960784313726, 1.0, 1.0), 'deepskyblue1': (0.0, 0.74901960784313726, 1.0, 1.0), 'deepskyblue2': (0.0, 0.69803921568627447, 0.93333333333333335, 1.0), 'deepskyblue3': (0.0, 0.60392156862745094, 0.80392156862745101, 1.0), 'deepskyblue4': (0.0, 0.40784313725490196, 0.54509803921568623, 1.0), 'dim gray': ( 0.41176470588235292, 0.41176470588235292, 0.41176470588235292, 1.0), 'dim grey': ( 0.41176470588235292, 0.41176470588235292, 0.41176470588235292, 1.0), 'dimgray': ( 0.41176470588235292, 0.41176470588235292, 0.41176470588235292, 1.0), 'dimgrey': ( 0.41176470588235292, 0.41176470588235292, 0.41176470588235292, 1.0), 'dodger blue': (0.11764705882352941, 0.56470588235294117, 1.0, 1.0), 'dodgerblue': (0.11764705882352941, 0.56470588235294117, 1.0, 1.0), 'dodgerblue1': (0.11764705882352941, 0.56470588235294117, 1.0, 1.0), 'dodgerblue2': ( 0.10980392156862745, 0.52549019607843139, 0.93333333333333335, 1.0), 'dodgerblue3': ( 0.094117647058823528, 0.45490196078431372, 0.80392156862745101, 1.0), 'dodgerblue4': ( 0.062745098039215685, 0.30588235294117649, 0.54509803921568623, 1.0), 'firebrick': ( 0.69803921568627447, 0.13333333333333333, 0.13333333333333333, 1.0), 'firebrick1': (1.0, 0.18823529411764706, 0.18823529411764706, 1.0), 'firebrick2': ( 0.93333333333333335, 0.17254901960784313, 0.17254901960784313, 1.0), 'firebrick3': ( 0.80392156862745101, 0.14901960784313725, 0.14901960784313725, 1.0), 'firebrick4': ( 0.54509803921568623, 0.10196078431372549, 0.10196078431372549, 1.0), 'floral white': (1.0, 0.98039215686274506, 0.94117647058823528, 1.0), 'floralwhite': (1.0, 0.98039215686274506, 0.94117647058823528, 1.0), 'forest green': ( 0.13333333333333333, 0.54509803921568623, 0.13333333333333333, 1.0), 'forestgreen': ( 0.13333333333333333, 0.54509803921568623, 0.13333333333333333, 1.0), 'fuchsia': (1.0, 0.0, 1.0, 1.0), 'gainsboro': ( 0.86274509803921573, 0.86274509803921573, 0.86274509803921573, 1.0), 'ghost white': (0.97254901960784312, 0.97254901960784312, 1.0, 1.0), 'ghostwhite': (0.97254901960784312, 0.97254901960784312, 1.0, 1.0), 'gold': (1.0, 0.84313725490196079, 0.0, 1.0), 'gold1': (1.0, 0.84313725490196079, 0.0, 1.0), 'gold2': (0.93333333333333335, 0.78823529411764703, 0.0, 1.0), 'gold3': (0.80392156862745101, 0.67843137254901964, 0.0, 1.0), 'gold4': (0.54509803921568623, 0.45882352941176469, 0.0, 1.0), 'goldenrod': ( 0.85490196078431369, 0.6470588235294118, 0.12549019607843137, 1.0), 'goldenrod1': (1.0, 0.75686274509803919, 0.14509803921568629, 1.0), 'goldenrod2': ( 0.93333333333333335, 0.70588235294117652, 0.13333333333333333, 1.0), 'goldenrod3': ( 0.80392156862745101, 0.60784313725490191, 0.11372549019607843, 1.0), 'goldenrod4': ( 0.54509803921568623, 0.41176470588235292, 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0.078431372549019607, 0.078431372549019607, 1.0), 'grey80': ( 0.80000000000000004, 0.80000000000000004, 0.80000000000000004, 1.0), 'grey81': ( 0.81176470588235294, 0.81176470588235294, 0.81176470588235294, 1.0), 'grey82': ( 0.81960784313725488, 0.81960784313725488, 0.81960784313725488, 1.0), 'grey83': ( 0.83137254901960789, 0.83137254901960789, 0.83137254901960789, 1.0), 'grey84': ( 0.83921568627450982, 0.83921568627450982, 0.83921568627450982, 1.0), 'grey85': ( 0.85098039215686272, 0.85098039215686272, 0.85098039215686272, 1.0), 'grey86': ( 0.85882352941176465, 0.85882352941176465, 0.85882352941176465, 1.0), 'grey87': ( 0.87058823529411766, 0.87058823529411766, 0.87058823529411766, 1.0), 'grey88': ( 0.8784313725490196, 0.8784313725490196, 0.8784313725490196, 1.0), 'grey89': ( 0.8901960784313725, 0.8901960784313725, 0.8901960784313725, 1.0), 'grey9': ( 0.090196078431372548, 0.090196078431372548, 0.090196078431372548, 1.0), 'grey90': ( 0.89803921568627454, 0.89803921568627454, 0.89803921568627454, 1.0), 'grey91': ( 0.90980392156862744, 0.90980392156862744, 0.90980392156862744, 1.0), 'grey92': ( 0.92156862745098034, 0.92156862745098034, 0.92156862745098034, 1.0), 'grey93': ( 0.92941176470588238, 0.92941176470588238, 0.92941176470588238, 1.0), 'grey94': ( 0.94117647058823528, 0.94117647058823528, 0.94117647058823528, 1.0), 'grey95': ( 0.94901960784313721, 0.94901960784313721, 0.94901960784313721, 1.0), 'grey96': ( 0.96078431372549022, 0.96078431372549022, 0.96078431372549022, 1.0), 'grey97': ( 0.96862745098039216, 0.96862745098039216, 0.96862745098039216, 1.0), 'grey98': ( 0.98039215686274506, 0.98039215686274506, 0.98039215686274506, 1.0), 'grey99': ( 0.9882352941176471, 0.9882352941176471, 0.9882352941176471, 1.0), 'honeydew': (0.94117647058823528, 1.0, 0.94117647058823528, 1.0), 'honeydew1': (0.94117647058823528, 1.0, 0.94117647058823528, 1.0), 'honeydew2': ( 0.8784313725490196, 0.93333333333333335, 0.8784313725490196, 1.0), 'honeydew3': ( 0.75686274509803919, 0.80392156862745101, 0.75686274509803919, 1.0), 'honeydew4': ( 0.51372549019607838, 0.54509803921568623, 0.51372549019607838, 1.0), 'hot pink': (1.0, 0.41176470588235292, 0.70588235294117652, 1.0), 'hotpink': (1.0, 0.41176470588235292, 0.70588235294117652, 1.0), 'hotpink1': (1.0, 0.43137254901960786, 0.70588235294117652, 1.0), 'hotpink2': ( 0.93333333333333335, 0.41568627450980394, 0.65490196078431373, 1.0), 'hotpink3': ( 0.80392156862745101, 0.37647058823529411, 0.56470588235294117, 1.0), 'hotpink4': ( 0.54509803921568623, 0.22745098039215686, 0.3843137254901961, 1.0), 'indian red': ( 0.80392156862745101, 0.36078431372549019, 0.36078431372549019, 1.0), 'indianred': ( 0.80392156862745101, 0.36078431372549019, 0.36078431372549019, 1.0), 'indianred1': (1.0, 0.41568627450980394, 0.41568627450980394, 1.0), 'indianred2': ( 0.93333333333333335, 0.38823529411764707, 0.38823529411764707, 1.0), 'indianred3': ( 0.80392156862745101, 0.33333333333333331, 0.33333333333333331, 1.0), 'indianred4': ( 0.54509803921568623, 0.22745098039215686, 0.22745098039215686, 1.0), 'indigo': (0.29411764705882354, 0.0, 0.5098039215686274, 1.0), 'ivory': (1.0, 1.0, 0.94117647058823528, 1.0), 'ivory1': (1.0, 1.0, 0.94117647058823528, 1.0), 'ivory2': ( 0.93333333333333335, 0.93333333333333335, 0.8784313725490196, 1.0), 'ivory3': ( 0.80392156862745101, 0.80392156862745101, 0.75686274509803919, 1.0), 'ivory4': ( 0.54509803921568623, 0.54509803921568623, 0.51372549019607838, 1.0), 'khaki': ( 0.94117647058823528, 0.90196078431372551, 0.5490196078431373, 1.0), 'khaki1': (1.0, 0.96470588235294119, 0.5607843137254902, 1.0), 'khaki2': ( 0.93333333333333335, 0.90196078431372551, 0.52156862745098043, 1.0), 'khaki3': ( 0.80392156862745101, 0.77647058823529413, 0.45098039215686275, 1.0), 'khaki4': ( 0.54509803921568623, 0.52549019607843139, 0.30588235294117649, 1.0), 'lavender': ( 0.90196078431372551, 0.90196078431372551, 0.98039215686274506, 1.0), 'lavender blush': (1.0, 0.94117647058823528, 0.96078431372549022, 1.0), 'lavenderblush': (1.0, 0.94117647058823528, 0.96078431372549022, 1.0), 'lavenderblush1': (1.0, 0.94117647058823528, 0.96078431372549022, 1.0), 'lavenderblush2': ( 0.93333333333333335, 0.8784313725490196, 0.89803921568627454, 1.0), 'lavenderblush3': ( 0.80392156862745101, 0.75686274509803919, 0.77254901960784317, 1.0), 'lavenderblush4': ( 0.54509803921568623, 0.51372549019607838, 0.52549019607843139, 1.0), 'lawn green': (0.48627450980392156, 0.9882352941176471, 0.0, 1.0), 'lawngreen': (0.48627450980392156, 0.9882352941176471, 0.0, 1.0), 'lemon chiffon': (1.0, 0.98039215686274506, 0.80392156862745101, 1.0), 'lemonchiffon': (1.0, 0.98039215686274506, 0.80392156862745101, 1.0), 'lemonchiffon1': (1.0, 0.98039215686274506, 0.80392156862745101, 1.0), 'lemonchiffon2': ( 0.93333333333333335, 0.9137254901960784, 0.74901960784313726, 1.0), 'lemonchiffon3': ( 0.80392156862745101, 0.78823529411764703, 0.6470588235294118, 1.0), 'lemonchiffon4': ( 0.54509803921568623, 0.53725490196078429, 0.4392156862745098, 1.0), 'light blue': ( 0.67843137254901964, 0.84705882352941175, 0.90196078431372551, 1.0), 'light coral': ( 0.94117647058823528, 0.50196078431372548, 0.50196078431372548, 1.0), 'light cyan': (0.8784313725490196, 1.0, 1.0, 1.0), 'light goldenrod': ( 0.93333333333333335, 0.8666666666666667, 0.50980392156862742, 1.0), 'light goldenrod yellow': ( 0.98039215686274506, 0.98039215686274506, 0.82352941176470584, 1.0), 'light gray': ( 0.82745098039215681, 0.82745098039215681, 0.82745098039215681, 1.0), 'light green': ( 0.56470588235294117, 0.93333333333333335, 0.56470588235294117, 1.0), 'light grey': ( 0.82745098039215681, 0.82745098039215681, 0.82745098039215681, 1.0), 'light pink': (1.0, 0.71372549019607845, 0.75686274509803919, 1.0), 'light salmon': (1.0, 0.62745098039215685, 0.47843137254901963, 1.0), 'light sea green': ( 0.12549019607843137, 0.69803921568627447, 0.66666666666666663, 1.0), 'light sky blue': ( 0.52941176470588236, 0.80784313725490198, 0.98039215686274506, 1.0), 'light slate blue': (0.51764705882352946, 0.4392156862745098, 1.0, 1.0), 'light slate gray': ( 0.46666666666666667, 0.53333333333333333, 0.59999999999999998, 1.0), 'light slate grey': ( 0.46666666666666667, 0.53333333333333333, 0.59999999999999998, 1.0), 'light steel blue': ( 0.69019607843137254, 0.7686274509803922, 0.87058823529411766, 1.0), 'light yellow': (1.0, 1.0, 0.8784313725490196, 1.0), 'lightblue': ( 0.67843137254901964, 0.84705882352941175, 0.90196078431372551, 1.0), 'lightblue1': (0.74901960784313726, 0.93725490196078431, 1.0, 1.0), 'lightblue2': ( 0.69803921568627447, 0.87450980392156863, 0.93333333333333335, 1.0), 'lightblue3': ( 0.60392156862745094, 0.75294117647058822, 0.80392156862745101, 1.0), 'lightblue4': ( 0.40784313725490196, 0.51372549019607838, 0.54509803921568623, 1.0), 'lightcoral': ( 0.94117647058823528, 0.50196078431372548, 0.50196078431372548, 1.0), 'lightcyan': (0.8784313725490196, 1.0, 1.0, 1.0), 'lightcyan1': (0.8784313725490196, 1.0, 1.0, 1.0), 'lightcyan2': ( 0.81960784313725488, 0.93333333333333335, 0.93333333333333335, 1.0), 'lightcyan3': ( 0.70588235294117652, 0.80392156862745101, 0.80392156862745101, 1.0), 'lightcyan4': ( 0.47843137254901963, 0.54509803921568623, 0.54509803921568623, 1.0), 'lightgoldenrod': ( 0.93333333333333335, 0.8666666666666667, 0.50980392156862742, 1.0), 'lightgoldenrod1': (1.0, 0.92549019607843142, 0.54509803921568623, 1.0), 'lightgoldenrod2': ( 0.93333333333333335, 0.86274509803921573, 0.50980392156862742, 1.0), 'lightgoldenrod3': ( 0.80392156862745101, 0.74509803921568629, 0.4392156862745098, 1.0), 'lightgoldenrod4': ( 0.54509803921568623, 0.50588235294117645, 0.29803921568627451, 1.0), 'lightgoldenrodyellow': ( 0.98039215686274506, 0.98039215686274506, 0.82352941176470584, 1.0), 'lightgray': ( 0.82745098039215681, 0.82745098039215681, 0.82745098039215681, 1.0), 'lightgreen': ( 0.56470588235294117, 0.93333333333333335, 0.56470588235294117, 1.0), 'lightgrey': ( 0.82745098039215681, 0.82745098039215681, 0.82745098039215681, 1.0), 'lightpink': (1.0, 0.71372549019607845, 0.75686274509803919, 1.0), 'lightpink1': (1.0, 0.68235294117647061, 0.72549019607843135, 1.0), 'lightpink2': ( 0.93333333333333335, 0.63529411764705879, 0.67843137254901964, 1.0), 'lightpink3': ( 0.80392156862745101, 0.5490196078431373, 0.58431372549019611, 1.0), 'lightpink4': ( 0.54509803921568623, 0.37254901960784315, 0.396078431372549, 1.0), 'lightsalmon': (1.0, 0.62745098039215685, 0.47843137254901963, 1.0), 'lightsalmon1': (1.0, 0.62745098039215685, 0.47843137254901963, 1.0), 'lightsalmon2': ( 0.93333333333333335, 0.58431372549019611, 0.44705882352941179, 1.0), 'lightsalmon3': ( 0.80392156862745101, 0.50588235294117645, 0.3843137254901961, 1.0), 'lightsalmon4': ( 0.54509803921568623, 0.3411764705882353, 0.25882352941176473, 1.0), 'lightseagreen': ( 0.12549019607843137, 0.69803921568627447, 0.66666666666666663, 1.0), 'lightskyblue': ( 0.52941176470588236, 0.80784313725490198, 0.98039215686274506, 1.0), 'lightskyblue1': (0.69019607843137254, 0.88627450980392153, 1.0, 1.0), 'lightskyblue2': ( 0.64313725490196083, 0.82745098039215681, 0.93333333333333335, 1.0), 'lightskyblue3': ( 0.55294117647058827, 0.71372549019607845, 0.80392156862745101, 1.0), 'lightskyblue4': ( 0.37647058823529411, 0.4823529411764706, 0.54509803921568623, 1.0), 'lightslateblue': (0.51764705882352946, 0.4392156862745098, 1.0, 1.0), 'lightslategray': ( 0.46666666666666667, 0.53333333333333333, 0.59999999999999998, 1.0), 'lightslategrey': ( 0.46666666666666667, 0.53333333333333333, 0.59999999999999998, 1.0), 'lightsteelblue': ( 0.69019607843137254, 0.7686274509803922, 0.87058823529411766, 1.0), 'lightsteelblue1': (0.792156862745098, 0.88235294117647056, 1.0, 1.0), 'lightsteelblue2': ( 0.73725490196078436, 0.82352941176470584, 0.93333333333333335, 1.0), 'lightsteelblue3': ( 0.63529411764705879, 0.70980392156862748, 0.80392156862745101, 1.0), 'lightsteelblue4': ( 0.43137254901960786, 0.4823529411764706, 0.54509803921568623, 1.0), 'lightyellow': (1.0, 1.0, 0.8784313725490196, 1.0), 'lightyellow1': (1.0, 1.0, 0.8784313725490196, 1.0), 'lightyellow2': ( 0.93333333333333335, 0.93333333333333335, 0.81960784313725488, 1.0), 'lightyellow3': ( 0.80392156862745101, 0.80392156862745101, 0.70588235294117652, 1.0), 'lightyellow4': ( 0.54509803921568623, 0.54509803921568623, 0.47843137254901963, 1.0), 'lime': (0.0, 1.0, 0.0, 1.0), 'lime green': ( 0.19607843137254902, 0.80392156862745101, 0.19607843137254902, 1.0), 'limegreen': ( 0.19607843137254902, 0.80392156862745101, 0.19607843137254902, 1.0), 'linen': ( 0.98039215686274506, 0.94117647058823528, 0.90196078431372551, 1.0), 'magenta': (1.0, 0.0, 1.0, 1.0), 'magenta1': (1.0, 0.0, 1.0, 1.0), 'magenta2': (0.93333333333333335, 0.0, 0.93333333333333335, 1.0), 'magenta3': (0.80392156862745101, 0.0, 0.80392156862745101, 1.0), 'magenta4': (0.54509803921568623, 0.0, 0.54509803921568623, 1.0), 'maroon': ( 0.69019607843137254, 0.18823529411764706, 0.37647058823529411, 1.0), 'maroon1': (1.0, 0.20392156862745098, 0.70196078431372544, 1.0), 'maroon2': ( 0.93333333333333335, 0.18823529411764706, 0.65490196078431373, 1.0), 'maroon3': ( 0.80392156862745101, 0.16078431372549021, 0.56470588235294117, 1.0), 'maroon4': ( 0.54509803921568623, 0.10980392156862745, 0.3843137254901961, 1.0), 'medium aquamarine': ( 0.40000000000000002, 0.80392156862745101, 0.66666666666666663, 1.0), 'medium blue': (0.0, 0.0, 0.80392156862745101, 1.0), 'medium orchid': ( 0.72941176470588232, 0.33333333333333331, 0.82745098039215681, 1.0), 'medium purple': ( 0.57647058823529407, 0.4392156862745098, 0.85882352941176465, 1.0), 'medium sea green': ( 0.23529411764705882, 0.70196078431372544, 0.44313725490196076, 1.0), 'medium slate blue': ( 0.4823529411764706, 0.40784313725490196, 0.93333333333333335, 1.0), 'medium spring green': ( 0.0, 0.98039215686274506, 0.60392156862745094, 1.0), 'medium turquoise': ( 0.28235294117647058, 0.81960784313725488, 0.80000000000000004, 1.0), 'medium violet red': ( 0.7803921568627451, 0.082352941176470587, 0.52156862745098043, 1.0), 'mediumaquamarine': ( 0.40000000000000002, 0.80392156862745101, 0.66666666666666663, 1.0), 'mediumblue': (0.0, 0.0, 0.80392156862745101, 1.0), 'mediumorchid': ( 0.72941176470588232, 0.33333333333333331, 0.82745098039215681, 1.0), 'mediumorchid1': (0.8784313725490196, 0.40000000000000002, 1.0, 1.0), 'mediumorchid2': ( 0.81960784313725488, 0.37254901960784315, 0.93333333333333335, 1.0), 'mediumorchid3': ( 0.70588235294117652, 0.32156862745098042, 0.80392156862745101, 1.0), 'mediumorchid4': ( 0.47843137254901963, 0.21568627450980393, 0.54509803921568623, 1.0), 'mediumpurple': ( 0.57647058823529407, 0.4392156862745098, 0.85882352941176465, 1.0), 'mediumpurple1': (0.6705882352941176, 0.50980392156862742, 1.0, 1.0), 'mediumpurple2': ( 0.62352941176470589, 0.47450980392156861, 0.93333333333333335, 1.0), 'mediumpurple3': ( 0.53725490196078429, 0.40784313725490196, 0.80392156862745101, 1.0), 'mediumpurple4': ( 0.36470588235294116, 0.27843137254901962, 0.54509803921568623, 1.0), 'mediumseagreen': ( 0.23529411764705882, 0.70196078431372544, 0.44313725490196076, 1.0), 'mediumslateblue': ( 0.4823529411764706, 0.40784313725490196, 0.93333333333333335, 1.0), 'mediumspringgreen': (0.0, 0.98039215686274506, 0.60392156862745094, 1.0), 'mediumturquoise': ( 0.28235294117647058, 0.81960784313725488, 0.80000000000000004, 1.0), 'mediumvioletred': ( 0.7803921568627451, 0.082352941176470587, 0.52156862745098043, 1.0), 'midnight blue': ( 0.098039215686274508, 0.098039215686274508, 0.4392156862745098, 1.0), 'midnightblue': ( 0.098039215686274508, 0.098039215686274508, 0.4392156862745098, 1.0), 'mint cream': (0.96078431372549022, 1.0, 0.98039215686274506, 1.0), 'mintcream': (0.96078431372549022, 1.0, 0.98039215686274506, 1.0), 'misty rose': (1.0, 0.89411764705882357, 0.88235294117647056, 1.0), 'mistyrose': (1.0, 0.89411764705882357, 0.88235294117647056, 1.0), 'mistyrose1': (1.0, 0.89411764705882357, 0.88235294117647056, 1.0), 'mistyrose2': ( 0.93333333333333335, 0.83529411764705885, 0.82352941176470584, 1.0), 'mistyrose3': ( 0.80392156862745101, 0.71764705882352942, 0.70980392156862748, 1.0), 'mistyrose4': ( 0.54509803921568623, 0.49019607843137253, 0.4823529411764706, 1.0), 'moccasin': (1.0, 0.89411764705882357, 0.70980392156862748, 1.0), 'navajo white': (1.0, 0.87058823529411766, 0.67843137254901964, 1.0), 'navajowhite': (1.0, 0.87058823529411766, 0.67843137254901964, 1.0), 'navajowhite1': (1.0, 0.87058823529411766, 0.67843137254901964, 1.0), 'navajowhite2': ( 0.93333333333333335, 0.81176470588235294, 0.63137254901960782, 1.0), 'navajowhite3': ( 0.80392156862745101, 0.70196078431372544, 0.54509803921568623, 1.0), 'navajowhite4': ( 0.54509803921568623, 0.47450980392156861, 0.36862745098039218, 1.0), 'navy': (0.0, 0.0, 0.50196078431372548, 1.0), 'navy blue': (0.0, 0.0, 0.50196078431372548, 1.0), 'navyblue': (0.0, 0.0, 0.50196078431372548, 1.0), 'old lace': ( 0.99215686274509807, 0.96078431372549022, 0.90196078431372551, 1.0), 'oldlace': ( 0.99215686274509807, 0.96078431372549022, 0.90196078431372551, 1.0), 'olive': (0.5, 0.5, 0.0, 1.0), 'olive drab': ( 0.41960784313725491, 0.55686274509803924, 0.13725490196078433, 1.0), 'olivedrab': ( 0.41960784313725491, 0.55686274509803924, 0.13725490196078433, 1.0), 'olivedrab1': (0.75294117647058822, 1.0, 0.24313725490196078, 1.0), 'olivedrab2': ( 0.70196078431372544, 0.93333333333333335, 0.22745098039215686, 1.0), 'olivedrab3': ( 0.60392156862745094, 0.80392156862745101, 0.19607843137254902, 1.0), 'olivedrab4': ( 0.41176470588235292, 0.54509803921568623, 0.13333333333333333, 1.0), 'orange': (1.0, 0.6470588235294118, 0.0, 1.0), 'orange red': (1.0, 0.27058823529411763, 0.0, 1.0), 'orange1': (1.0, 0.6470588235294118, 0.0, 1.0), 'orange2': (0.93333333333333335, 0.60392156862745094, 0.0, 1.0), 'orange3': (0.80392156862745101, 0.52156862745098043, 0.0, 1.0), 'orange4': (0.54509803921568623, 0.35294117647058826, 0.0, 1.0), 'orangered': (1.0, 0.27058823529411763, 0.0, 1.0), 'orangered1': (1.0, 0.27058823529411763, 0.0, 1.0), 'orangered2': (0.93333333333333335, 0.25098039215686274, 0.0, 1.0), 'orangered3': (0.80392156862745101, 0.21568627450980393, 0.0, 1.0), 'orangered4': (0.54509803921568623, 0.14509803921568629, 0.0, 1.0), 'orchid': ( 0.85490196078431369, 0.4392156862745098, 0.83921568627450982, 1.0), 'orchid1': (1.0, 0.51372549019607838, 0.98039215686274506, 1.0), 'orchid2': ( 0.93333333333333335, 0.47843137254901963, 0.9137254901960784, 1.0), 'orchid3': ( 0.80392156862745101, 0.41176470588235292, 0.78823529411764703, 1.0), 'orchid4': ( 0.54509803921568623, 0.27843137254901962, 0.53725490196078429, 1.0), 'pale goldenrod': ( 0.93333333333333335, 0.90980392156862744, 0.66666666666666663, 1.0), 'pale green': ( 0.59607843137254901, 0.98431372549019602, 0.59607843137254901, 1.0), 'pale turquoise': ( 0.68627450980392157, 0.93333333333333335, 0.93333333333333335, 1.0), 'pale violet red': ( 0.85882352941176465, 0.4392156862745098, 0.57647058823529407, 1.0), 'palegoldenrod': ( 0.93333333333333335, 0.90980392156862744, 0.66666666666666663, 1.0), 'palegreen': ( 0.59607843137254901, 0.98431372549019602, 0.59607843137254901, 1.0), 'palegreen1': (0.60392156862745094, 1.0, 0.60392156862745094, 1.0), 'palegreen2': ( 0.56470588235294117, 0.93333333333333335, 0.56470588235294117, 1.0), 'palegreen3': ( 0.48627450980392156, 0.80392156862745101, 0.48627450980392156, 1.0), 'palegreen4': ( 0.32941176470588235, 0.54509803921568623, 0.32941176470588235, 1.0), 'paleturquoise': ( 0.68627450980392157, 0.93333333333333335, 0.93333333333333335, 1.0), 'paleturquoise1': (0.73333333333333328, 1.0, 1.0, 1.0), 'paleturquoise2': ( 0.68235294117647061, 0.93333333333333335, 0.93333333333333335, 1.0), 'paleturquoise3': ( 0.58823529411764708, 0.80392156862745101, 0.80392156862745101, 1.0), 'paleturquoise4': ( 0.40000000000000002, 0.54509803921568623, 0.54509803921568623, 1.0), 'palevioletred': ( 0.85882352941176465, 0.4392156862745098, 0.57647058823529407, 1.0), 'palevioletred1': (1.0, 0.50980392156862742, 0.6705882352941176, 1.0), 'palevioletred2': ( 0.93333333333333335, 0.47450980392156861, 0.62352941176470589, 1.0), 'palevioletred3': ( 0.80392156862745101, 0.40784313725490196, 0.53725490196078429, 1.0), 'palevioletred4': ( 0.54509803921568623, 0.27843137254901962, 0.36470588235294116, 1.0), 'papaya whip': (1.0, 0.93725490196078431, 0.83529411764705885, 1.0), 'papayawhip': (1.0, 0.93725490196078431, 0.83529411764705885, 1.0), 'peach puff': (1.0, 0.85490196078431369, 0.72549019607843135, 1.0), 'peachpuff': (1.0, 0.85490196078431369, 0.72549019607843135, 1.0), 'peachpuff1': (1.0, 0.85490196078431369, 0.72549019607843135, 1.0), 'peachpuff2': ( 0.93333333333333335, 0.79607843137254897, 0.67843137254901964, 1.0), 'peachpuff3': ( 0.80392156862745101, 0.68627450980392157, 0.58431372549019611, 1.0), 'peachpuff4': ( 0.54509803921568623, 0.46666666666666667, 0.396078431372549, 1.0), 'peru': ( 0.80392156862745101, 0.52156862745098043, 0.24705882352941178, 1.0), 'pink': (1.0, 0.75294117647058822, 0.79607843137254897, 1.0), 'pink1': (1.0, 0.70980392156862748, 0.77254901960784317, 1.0), 'pink2': ( 0.93333333333333335, 0.66274509803921566, 0.72156862745098038, 1.0), 'pink3': ( 0.80392156862745101, 0.56862745098039214, 0.61960784313725492, 1.0), 'pink4': ( 0.54509803921568623, 0.38823529411764707, 0.42352941176470588, 1.0), 'plum': (0.8666666666666667, 0.62745098039215685, 0.8666666666666667, 1.0), 'plum1': (1.0, 0.73333333333333328, 1.0, 1.0), 'plum2': ( 0.93333333333333335, 0.68235294117647061, 0.93333333333333335, 1.0), 'plum3': ( 0.80392156862745101, 0.58823529411764708, 0.80392156862745101, 1.0), 'plum4': ( 0.54509803921568623, 0.40000000000000002, 0.54509803921568623, 1.0), 'powder blue': ( 0.69019607843137254, 0.8784313725490196, 0.90196078431372551, 1.0), 'powderblue': ( 0.69019607843137254, 0.8784313725490196, 0.90196078431372551, 1.0), 'purple': ( 0.62745098039215685, 0.12549019607843137, 0.94117647058823528, 1.0), 'purple1': (0.60784313725490191, 0.18823529411764706, 1.0, 1.0), 'purple2': ( 0.56862745098039214, 0.17254901960784313, 0.93333333333333335, 1.0), 'purple3': ( 0.49019607843137253, 0.14901960784313725, 0.80392156862745101, 1.0), 'purple4': ( 0.33333333333333331, 0.10196078431372549, 0.54509803921568623, 1.0), 'rebecca purple': (0.4, 0.2, 0.6, 1.0), 'rebeccapurple': (0.4, 0.2, 0.6, 1.0), 'red': (1.0, 0.0, 0.0, 1.0), 'red1': (1.0, 0.0, 0.0, 1.0), 'red2': (0.93333333333333335, 0.0, 0.0, 1.0), 'red3': (0.80392156862745101, 0.0, 0.0, 1.0), 'red4': (0.54509803921568623, 0.0, 0.0, 1.0), 'rosy brown': ( 0.73725490196078436, 0.5607843137254902, 0.5607843137254902, 1.0), 'rosybrown': ( 0.73725490196078436, 0.5607843137254902, 0.5607843137254902, 1.0), 'rosybrown1': (1.0, 0.75686274509803919, 0.75686274509803919, 1.0), 'rosybrown2': ( 0.93333333333333335, 0.70588235294117652, 0.70588235294117652, 1.0), 'rosybrown3': ( 0.80392156862745101, 0.60784313725490191, 0.60784313725490191, 1.0), 'rosybrown4': ( 0.54509803921568623, 0.41176470588235292, 0.41176470588235292, 1.0), 'royal blue': ( 0.25490196078431371, 0.41176470588235292, 0.88235294117647056, 1.0), 'royalblue': ( 0.25490196078431371, 0.41176470588235292, 0.88235294117647056, 1.0), 'royalblue1': (0.28235294117647058, 0.46274509803921571, 1.0, 1.0), 'royalblue2': ( 0.2627450980392157, 0.43137254901960786, 0.93333333333333335, 1.0), 'royalblue3': ( 0.22745098039215686, 0.37254901960784315, 0.80392156862745101, 1.0), 'royalblue4': ( 0.15294117647058825, 0.25098039215686274, 0.54509803921568623, 1.0), 'saddle brown': ( 0.54509803921568623, 0.27058823529411763, 0.074509803921568626, 1.0), 'saddlebrown': ( 0.54509803921568623, 0.27058823529411763, 0.074509803921568626, 1.0), 'salmon': ( 0.98039215686274506, 0.50196078431372548, 0.44705882352941179, 1.0), 'salmon1': (1.0, 0.5490196078431373, 0.41176470588235292, 1.0), 'salmon2': ( 0.93333333333333335, 0.50980392156862742, 0.3843137254901961, 1.0), 'salmon3': ( 0.80392156862745101, 0.4392156862745098, 0.32941176470588235, 1.0), 'salmon4': ( 0.54509803921568623, 0.29803921568627451, 0.22352941176470589, 1.0), 'sandy brown': ( 0.95686274509803926, 0.64313725490196083, 0.37647058823529411, 1.0), 'sandybrown': ( 0.95686274509803926, 0.64313725490196083, 0.37647058823529411, 1.0), 'sea green': ( 0.1803921568627451, 0.54509803921568623, 0.3411764705882353, 1.0), 'seagreen': ( 0.1803921568627451, 0.54509803921568623, 0.3411764705882353, 1.0), 'seagreen1': (0.32941176470588235, 1.0, 0.62352941176470589, 1.0), 'seagreen2': ( 0.30588235294117649, 0.93333333333333335, 0.58039215686274515, 1.0), 'seagreen3': ( 0.2627450980392157, 0.80392156862745101, 0.50196078431372548, 1.0), 'seagreen4': ( 0.1803921568627451, 0.54509803921568623, 0.3411764705882353, 1.0), 'seashell': (1.0, 0.96078431372549022, 0.93333333333333335, 1.0), 'seashell1': (1.0, 0.96078431372549022, 0.93333333333333335, 1.0), 'seashell2': ( 0.93333333333333335, 0.89803921568627454, 0.87058823529411766, 1.0), 'seashell3': ( 0.80392156862745101, 0.77254901960784317, 0.74901960784313726, 1.0), 'seashell4': ( 0.54509803921568623, 0.52549019607843139, 0.50980392156862742, 1.0), 'sienna': ( 0.62745098039215685, 0.32156862745098042, 0.17647058823529413, 1.0), 'sienna1': (1.0, 0.50980392156862742, 0.27843137254901962, 1.0), 'sienna2': ( 0.93333333333333335, 0.47450980392156861, 0.25882352941176473, 1.0), 'sienna3': ( 0.80392156862745101, 0.40784313725490196, 0.22352941176470589, 1.0), 'sienna4': ( 0.54509803921568623, 0.27843137254901962, 0.14901960784313725, 1.0), 'silver': (0.75, 0.75, 0.75, 1.0), 'sky blue': ( 0.52941176470588236, 0.80784313725490198, 0.92156862745098034, 1.0), 'skyblue': ( 0.52941176470588236, 0.80784313725490198, 0.92156862745098034, 1.0), 'skyblue1': (0.52941176470588236, 0.80784313725490198, 1.0, 1.0), 'skyblue2': ( 0.49411764705882355, 0.75294117647058822, 0.93333333333333335, 1.0), 'skyblue3': ( 0.42352941176470588, 0.65098039215686276, 0.80392156862745101, 1.0), 'skyblue4': ( 0.29019607843137257, 0.4392156862745098, 0.54509803921568623, 1.0), 'slate blue': ( 0.41568627450980394, 0.35294117647058826, 0.80392156862745101, 1.0), 'slate gray': ( 0.4392156862745098, 0.50196078431372548, 0.56470588235294117, 1.0), 'slate grey': ( 0.4392156862745098, 0.50196078431372548, 0.56470588235294117, 1.0), 'slateblue': ( 0.41568627450980394, 0.35294117647058826, 0.80392156862745101, 1.0), 'slateblue1': (0.51372549019607838, 0.43529411764705883, 1.0, 1.0), 'slateblue2': ( 0.47843137254901963, 0.40392156862745099, 0.93333333333333335, 1.0), 'slateblue3': ( 0.41176470588235292, 0.34901960784313724, 0.80392156862745101, 1.0), 'slateblue4': ( 0.27843137254901962, 0.23529411764705882, 0.54509803921568623, 1.0), 'slategray': ( 0.4392156862745098, 0.50196078431372548, 0.56470588235294117, 1.0), 'slategray1': (0.77647058823529413, 0.88627450980392153, 1.0, 1.0), 'slategray2': ( 0.72549019607843135, 0.82745098039215681, 0.93333333333333335, 1.0), 'slategray3': ( 0.62352941176470589, 0.71372549019607845, 0.80392156862745101, 1.0), 'slategray4': ( 0.42352941176470588, 0.4823529411764706, 0.54509803921568623, 1.0), 'slategrey': ( 0.4392156862745098, 0.50196078431372548, 0.56470588235294117, 1.0), 'snow': (1.0, 0.98039215686274506, 0.98039215686274506, 1.0), 'snow1': (1.0, 0.98039215686274506, 0.98039215686274506, 1.0), 'snow2': ( 0.93333333333333335, 0.9137254901960784, 0.9137254901960784, 1.0), 'snow3': ( 0.80392156862745101, 0.78823529411764703, 0.78823529411764703, 1.0), 'snow4': ( 0.54509803921568623, 0.53725490196078429, 0.53725490196078429, 1.0), 'spring green': (0.0, 1.0, 0.49803921568627452, 1.0), 'springgreen': (0.0, 1.0, 0.49803921568627452, 1.0), 'springgreen1': (0.0, 1.0, 0.49803921568627452, 1.0), 'springgreen2': (0.0, 0.93333333333333335, 0.46274509803921571, 1.0), 'springgreen3': (0.0, 0.80392156862745101, 0.40000000000000002, 1.0), 'springgreen4': (0.0, 0.54509803921568623, 0.27058823529411763, 1.0), 'steel blue': ( 0.27450980392156865, 0.50980392156862742, 0.70588235294117652, 1.0), 'steelblue': ( 0.27450980392156865, 0.50980392156862742, 0.70588235294117652, 1.0), 'steelblue1': (0.38823529411764707, 0.72156862745098038, 1.0, 1.0), 'steelblue2': ( 0.36078431372549019, 0.67450980392156867, 0.93333333333333335, 1.0), 'steelblue3': ( 0.30980392156862746, 0.58039215686274515, 0.80392156862745101, 1.0), 'steelblue4': ( 0.21176470588235294, 0.39215686274509803, 0.54509803921568623, 1.0), 'tan': (0.82352941176470584, 0.70588235294117652, 0.5490196078431373, 1.0), 'tan1': (1.0, 0.6470588235294118, 0.30980392156862746, 1.0), 'tan2': ( 0.93333333333333335, 0.60392156862745094, 0.28627450980392155, 1.0), 'tan3': ( 0.80392156862745101, 0.52156862745098043, 0.24705882352941178, 1.0), 'tan4': ( 0.54509803921568623, 0.35294117647058826, 0.16862745098039217, 1.0), 'teal': (0.0, 0.5, 0.5, 1.0), 'thistle': ( 0.84705882352941175, 0.74901960784313726, 0.84705882352941175, 1.0), 'thistle1': (1.0, 0.88235294117647056, 1.0, 1.0), 'thistle2': ( 0.93333333333333335, 0.82352941176470584, 0.93333333333333335, 1.0), 'thistle3': ( 0.80392156862745101, 0.70980392156862748, 0.80392156862745101, 1.0), 'thistle4': ( 0.54509803921568623, 0.4823529411764706, 0.54509803921568623, 1.0), 'tomato': (1.0, 0.38823529411764707, 0.27843137254901962, 1.0), 'tomato1': (1.0, 0.38823529411764707, 0.27843137254901962, 1.0), 'tomato2': ( 0.93333333333333335, 0.36078431372549019, 0.25882352941176473, 1.0), 'tomato3': ( 0.80392156862745101, 0.30980392156862746, 0.22352941176470589, 1.0), 'tomato4': ( 0.54509803921568623, 0.21176470588235294, 0.14901960784313725, 1.0), 'turquoise': ( 0.25098039215686274, 0.8784313725490196, 0.81568627450980391, 1.0), 'turquoise1': (0.0, 0.96078431372549022, 1.0, 1.0), 'turquoise2': (0.0, 0.89803921568627454, 0.93333333333333335, 1.0), 'turquoise3': (0.0, 0.77254901960784317, 0.80392156862745101, 1.0), 'turquoise4': (0.0, 0.52549019607843139, 0.54509803921568623, 1.0), 'violet': ( 0.93333333333333335, 0.50980392156862742, 0.93333333333333335, 1.0), 'violet red': ( 0.81568627450980391, 0.12549019607843137, 0.56470588235294117, 1.0), 'violetred': ( 0.81568627450980391, 0.12549019607843137, 0.56470588235294117, 1.0), 'violetred1': (1.0, 0.24313725490196078, 0.58823529411764708, 1.0), 'violetred2': ( 0.93333333333333335, 0.22745098039215686, 0.5490196078431373, 1.0), 'violetred3': ( 0.80392156862745101, 0.19607843137254902, 0.47058823529411764, 1.0), 'violetred4': ( 0.54509803921568623, 0.13333333333333333, 0.32156862745098042, 1.0), 'web gray': ( 0.5019607843137255, 0.5019607843137255, 0.5019607843137255, 1.0), 'webgray': ( 0.5019607843137255, 0.5019607843137255, 0.5019607843137255, 1.0), 'web green': (0.0, 0.5019607843137255, 0.0, 1.0), 'webgreen': (0.0, 0.5019607843137255, 0.0, 1.0), 'webgray': ( 0.5019607843137255, 0.5019607843137255, 0.5019607843137255, 1.0), 'web grey': ( 0.5019607843137255, 0.5019607843137255, 0.5019607843137255, 1.0), 'webgrey': ( 0.5019607843137255, 0.5019607843137255, 0.5019607843137255, 1.0), 'web maroon': (0.5019607843137255, 0.0, 0.0, 1.0), 'webmaroon': (0.5019607843137255, 0.0, 0.0, 1.0), 'web purple': ( 0.4980392156862745, 0.0, 0.4980392156862745, 1.0), 'webpurple': ( 0.4980392156862745, 0.0, 0.4980392156862745, 1.0), 'wheat': ( 0.96078431372549022, 0.87058823529411766, 0.70196078431372544, 1.0), 'wheat1': (1.0, 0.90588235294117647, 0.72941176470588232, 1.0), 'wheat2': ( 0.93333333333333335, 0.84705882352941175, 0.68235294117647061, 1.0), 'wheat3': ( 0.80392156862745101, 0.72941176470588232, 0.58823529411764708, 1.0), 'wheat4': ( 0.54509803921568623, 0.49411764705882355, 0.40000000000000002, 1.0), 'white': (1.0, 1.0, 1.0, 1.0), 'white smoke': ( 0.96078431372549022, 0.96078431372549022, 0.96078431372549022, 1.0), 'whitesmoke': ( 0.96078431372549022, 0.96078431372549022, 0.96078431372549022, 1.0), 'yellow': (1.0, 1.0, 0.0, 1.0), 'yellow green': ( 0.60392156862745094, 0.80392156862745101, 0.19607843137254902, 1.0), 'yellow1': (1.0, 1.0, 0.0, 1.0), 'yellow2': (0.93333333333333335, 0.93333333333333335, 0.0, 1.0), 'yellow3': (0.80392156862745101, 0.80392156862745101, 0.0, 1.0), 'yellow4': (0.54509803921568623, 0.54509803921568623, 0.0, 1.0), 'yellowgreen': ( 0.60392156862745094, 0.80392156862745101, 0.19607843137254902, 1.0)} palettes = { "gray": GradientPalette("black", "white"), "red-blue": GradientPalette("red", "blue"), "red-purple-blue": AdvancedGradientPalette(["red", "purple", "blue"]), "red-green": GradientPalette("red", "green"), "red-yellow-green": AdvancedGradientPalette(["red", "yellow", "green"]), "red-black-green": AdvancedGradientPalette(["red", "black", "green"]), "rainbow": RainbowPalette(), "heat": AdvancedGradientPalette(["red", "yellow", "white"], indices=[0, 192, 255]), "terrain": AdvancedGradientPalette(["hsv(120, 100%, 65%)", "hsv(60, 100%, 90%)", "hsv(0, 0%, 95%)"]) } python-igraph-0.8.0/src/igraph/clustering.py0000644000076500000240000020060613303053335021334 0ustar tamasstaff00000000000000# vim:ts=4:sw=4:sts=4:et # -*- coding: utf-8 -*- """Classes related to graph clustering. @undocumented: _handle_mark_groups_arg_for_clustering, _prepare_community_comparison""" __license__ = u""" Copyright (C) 2006-2012 Tamás Nepusz Pázmány Péter sétány 1/a, 1117 Budapest, Hungary This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA """ from copy import deepcopy from itertools import izip from math import pi from cStringIO import StringIO from igraph import community_to_membership from igraph.compat import property from igraph.configuration import Configuration from igraph.datatypes import UniqueIdGenerator from igraph.drawing.colors import ClusterColoringPalette from igraph.statistics import Histogram from igraph.summary import _get_wrapper_for_width from igraph.utils import str_to_orientation class Clustering(object): """Class representing a clustering of an arbitrary ordered set. This is now used as a base for L{VertexClustering}, but it might be useful for other purposes as well. Members of an individual cluster can be accessed by the C{[]} operator: >>> cl = Clustering([0,0,0,0,1,1,1,2,2,2,2]) >>> cl[0] [0, 1, 2, 3] The membership vector can be accessed by the C{membership} property: >>> cl.membership [0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 2] The number of clusters can be retrieved by the C{len} function: >>> len(cl) 3 You can iterate over the clustering object as if it were a regular list of clusters: >>> for cluster in cl: ... print " ".join(str(idx) for idx in cluster) ... 0 1 2 3 4 5 6 7 8 9 10 If you need all the clusters at once as lists, you can simply convert the clustering object to a list: >>> cluster_list = list(cl) >>> print cluster_list [[0, 1, 2, 3], [4, 5, 6], [7, 8, 9, 10]] @undocumented: _formatted_cluster_iterator """ def __init__(self, membership, params = None): """Constructor. @param membership: the membership list -- that is, the cluster index in which each element of the set belongs to. @param params: additional parameters to be stored in this object's dictionary.""" self._membership = list(membership) if len(self._membership)>0: self._len = max(m for m in self._membership if m is not None)+1 else: self._len = 0 if params: self.__dict__.update(params) def __getitem__(self, idx): """Returns the members of the specified cluster. @param idx: the index of the cluster @return: the members of the specified cluster as a list @raise IndexError: if the index is out of bounds""" if idx < 0 or idx >= self._len: raise IndexError("cluster index out of range") return [i for i, e in enumerate(self._membership) if e == idx] def __iter__(self): """Iterates over the clusters in this clustering. This method will return a generator that generates the clusters one by one.""" clusters = [[] for _ in xrange(self._len)] for idx, cluster in enumerate(self._membership): clusters[cluster].append(idx) return iter(clusters) def __len__(self): """Returns the number of clusters. @return: the number of clusters """ return self._len def __str__(self): return self.summary(verbosity=1, width=78) def as_cover(self): """Returns a L{Cover} that contains the same clusters as this clustering.""" return Cover(self._graph, self) def compare_to(self, other, *args, **kwds): """Compares this clustering to another one using some similarity or distance metric. This is a convenience method that simply calls L{compare_communities} with the two clusterings as arguments. Any extra positional or keyword argument is also forwarded to L{compare_communities}.""" return compare_communities(self, other, *args, **kwds) @property def membership(self): """Returns the membership vector.""" return self._membership[:] @property def n(self): """Returns the number of elements covered by this clustering.""" return len(self._membership) def size(self, idx): """Returns the size of a given cluster. @param idx: the cluster in which we are interested. """ return len(self[idx]) def sizes(self, *args): """Returns the size of given clusters. The indices are given as positional arguments. If there are no positional arguments, the function will return the sizes of all clusters. """ counts = [0] * len(self) for x in self._membership: counts[x] += 1 if args: return [counts[idx] for idx in args] return counts def size_histogram(self, bin_width = 1): """Returns the histogram of cluster sizes. @param bin_width: the bin width of the histogram @return: a L{Histogram} object """ return Histogram(bin_width, self.sizes()) def summary(self, verbosity=0, width=None): """Returns the summary of the clustering. The summary includes the number of items and clusters, and also the list of members for each of the clusters if the verbosity is nonzero. @param verbosity: determines whether the cluster members should be printed. Zero verbosity prints the number of items and clusters only. @return: the summary of the clustering as a string. """ out = StringIO() print >>out, "Clustering with %d elements and %d clusters" % \ (len(self._membership), len(self)) if verbosity < 1: return out.getvalue().strip() ndigits = len(str(len(self))) wrapper = _get_wrapper_for_width(width, subsequent_indent = " " * (ndigits+3)) for idx, cluster in enumerate(self._formatted_cluster_iterator()): wrapper.initial_indent = "[%*d] " % (ndigits, idx) print >>out, "\n".join(wrapper.wrap(cluster)) return out.getvalue().strip() def _formatted_cluster_iterator(self): """Iterates over the clusters and formats them into a string to be presented in the summary.""" for cluster in self: yield ", ".join(str(member) for member in cluster) class VertexClustering(Clustering): """The clustering of the vertex set of a graph. This class extends L{Clustering} by linking it to a specific L{Graph} object and by optionally storing the modularity score of the clustering. It also provides some handy methods like getting the subgraph corresponding to a cluster and such. @note: since this class is linked to a L{Graph}, destroying the graph by the C{del} operator does not free the memory occupied by the graph if there exists a L{VertexClustering} that references the L{Graph}. @undocumented: _formatted_cluster_iterator """ # Allow None to be passed to __plot__ as the "palette" keyword argument _default_palette = None def __init__(self, graph, membership = None, modularity = None, \ params = None, modularity_params = None): """Creates a clustering object for a given graph. @param graph: the graph that will be associated to the clustering @param membership: the membership list. The length of the list must be equal to the number of vertices in the graph. If C{None}, every vertex is assumed to belong to the same cluster. @param modularity: the modularity score of the clustering. If C{None}, it will be calculated when needed. @param params: additional parameters to be stored in this object. @param modularity_params: arguments that should be passed to L{Graph.modularity} when the modularity is (re)calculated. If the original graph was weighted, you should pass a dictionary containing a C{weight} key with the appropriate value here. """ if membership is None: Clustering.__init__(self, [0]*graph.vcount(), params) else: if len(membership) != graph.vcount(): raise ValueError("membership list has invalid length") Clustering.__init__(self, membership, params) self._graph = graph self._modularity = modularity self._modularity_dirty = modularity is None if modularity_params is None: self._modularity_params = {} else: self._modularity_params = dict(modularity_params) # pylint: disable-msg=C0103 @classmethod def FromAttribute(cls, graph, attribute, intervals=None, params=None): """Creates a vertex clustering based on the value of a vertex attribute. Vertices having the same attribute will correspond to the same cluster. @param graph: the graph on which we are working @param attribute: name of the attribute on which the clustering is based. @param intervals: for numeric attributes, you can either pass a single number or a list of numbers here. A single number means that the vertices will be put in bins of that width and vertices ending up in the same bin will be in the same cluster. A list of numbers specify the bin positions explicitly; e.g., C{[10, 20, 30]} means that there will be four categories: vertices with the attribute value less than 10, between 10 and 20, between 20 and 30 and over 30. Intervals are closed from the left and open from the right. @param params: additional parameters to be stored in this object. @return: a new VertexClustering object """ from bisect import bisect def safeintdiv(x, y): """Safe integer division that handles None gracefully""" if x is None: return None return int(x / y) def safebisect(intervals, x): """Safe list bisection that handles None gracefully""" if x is None: return None return bisect(intervals, x) try: _ = iter(intervals) iterable = True except TypeError: iterable = False if intervals is None: vec = graph.vs[attribute] elif iterable: intervals = list(intervals) vec = [safebisect(intervals, x) for x in graph.vs[attribute]] else: intervals = float(intervals) vec = [safeintdiv(x, intervals) for x in graph.vs[attribute]] idgen = UniqueIdGenerator() idgen[None] = None vec = [idgen[i] for i in vec] return cls(graph, vec, None, params) def as_cover(self): """Returns a L{VertexCover} that contains the same clusters as this clustering.""" return VertexCover(self._graph, self) def cluster_graph(self, combine_vertices=None, combine_edges=None): """Returns a graph where each cluster is contracted into a single vertex. In the resulting graph, vertex M{i} represents cluster M{i} in this clustering. Vertex M{i} and M{j} will be connected if there was at least one connected vertex pair M{(a, b)} in the original graph such that vertex M{a} was in cluster M{i} and vertex M{b} was in cluster M{j}. @param combine_vertices: specifies how to derive the attributes of the vertices in the new graph from the attributes of the old ones. See L{Graph.contract_vertices()} for more details. @param combine_edges: specifies how to derive the attributes of the edges in the new graph from the attributes of the old ones. See L{Graph.simplify()} for more details. If you specify C{False} here, edges will not be combined, and the number of edges between the vertices representing the original clusters will be equal to the number of edges between the members of those clusters in the original graph. @return: the new graph. """ result = self.graph.copy() result.contract_vertices(self.membership, combine_vertices) if combine_edges != False: result.simplify(combine_edges=combine_edges) return result def crossing(self): """Returns a boolean vector where element M{i} is C{True} iff edge M{i} lies between clusters, C{False} otherwise.""" membership = self.membership return [membership[v1] != membership[v2] \ for v1, v2 in self.graph.get_edgelist()] @property def modularity(self): """Returns the modularity score""" if self._modularity_dirty: return self._recalculate_modularity_safe() return self._modularity q = modularity @property def graph(self): """Returns the graph belonging to this object""" return self._graph def recalculate_modularity(self): """Recalculates the stored modularity value. This method must be called before querying the modularity score of the clustering through the class member C{modularity} or C{q} if the graph has been modified (edges have been added or removed) since the creation of the L{VertexClustering} object. @return: the new modularity score """ self._modularity = self._graph.modularity(self._membership, **self._modularity_params) self._modularity_dirty = False return self._modularity def _recalculate_modularity_safe(self): """Recalculates the stored modularity value and swallows all exceptions raised by the modularity function (if any). @return: the new modularity score or C{None} if the modularity function could not be calculated. """ try: return self.recalculate_modularity() except: return None finally: self._modularity_dirty = False def subgraph(self, idx): """Get the subgraph belonging to a given cluster. @param idx: the cluster index @return: a copy of the subgraph @precondition: the vertex set of the graph hasn't been modified since the moment the clustering was constructed. """ return self._graph.subgraph(self[idx]) def subgraphs(self): """Gets all the subgraphs belonging to each of the clusters. @return: a list containing copies of the subgraphs @precondition: the vertex set of the graph hasn't been modified since the moment the clustering was constructed. """ return [self._graph.subgraph(cl) for cl in self] def giant(self): """Returns the giant community of the clustered graph. The giant component a community for which no larger community exists. @note: there can be multiple giant communities, this method will return the copy of an arbitrary one if there are multiple giant communities. @return: a copy of the giant community. @precondition: the vertex set of the graph hasn't been modified since the moment the clustering was constructed. """ ss = self.sizes() max_size = max(ss) return self.subgraph(ss.index(max_size)) def __plot__(self, context, bbox, palette, *args, **kwds): """Plots the clustering to the given Cairo context in the given bounding box. This is done by calling L{Graph.__plot__()} with the same arguments, but coloring the graph vertices according to the current clustering (unless overridden by the C{vertex_color} argument explicitly). This method understands all the positional and keyword arguments that are understood by L{Graph.__plot__()}, only the differences will be highlighted here: - C{mark_groups}: whether to highlight some of the vertex groups by colored polygons. Besides the values accepted by L{Graph.__plot__} (i.e., a dict mapping colors to vertex indices, a list containing lists of vertex indices, or C{False}), the following are also accepted: - C{True}: all the groups will be highlighted, the colors matching the corresponding color indices from the current palette (see the C{palette} keyword argument of L{Graph.__plot__}. - A dict mapping cluster indices or tuples of vertex indices to color names. The given clusters or vertex groups will be highlighted by the given colors. - A list of cluster indices. This is equivalent to passing a dict mapping numeric color indices from the current palette to cluster indices; therefore, the cluster referred to by element I{i} of the list will be highlighted by color I{i} from the palette. The value of the C{plotting.mark_groups} configuration key is also taken into account here; if that configuration key is C{True} and C{mark_groups} is not given explicitly, it will automatically be set to C{True}. In place of lists of vertex indices, you may also use L{VertexSeq} instances. In place of color names, you may also use color indices into the current palette. C{None} as a color name will mean that the corresponding group is ignored. - C{palette}: the palette used to resolve numeric color indices to RGBA values. By default, this is an instance of L{ClusterColoringPalette}. @see: L{Graph.__plot__()} for more supported keyword arguments. """ if "edge_color" not in kwds and "color" not in self.graph.edge_attributes(): # Set up a default edge coloring based on internal vs external edges colors = ["grey20", "grey80"] kwds["edge_color"] = [colors[is_crossing] for is_crossing in self.crossing()] if palette is None: palette = ClusterColoringPalette(len(self)) if "mark_groups" not in kwds: if Configuration.instance()["plotting.mark_groups"]: kwds["mark_groups"] = self else: kwds["mark_groups"] = _handle_mark_groups_arg_for_clustering( kwds["mark_groups"], self) if "vertex_color" not in kwds: kwds["vertex_color"] = self.membership return self._graph.__plot__(context, bbox, palette, *args, **kwds) def _formatted_cluster_iterator(self): """Iterates over the clusters and formats them into a string to be presented in the summary.""" if self._graph.is_named(): names = self._graph.vs["name"] for cluster in self: yield ", ".join(str(names[member]) for member in cluster) else: for cluster in self: yield ", ".join(str(member) for member in cluster) ############################################################################### class Dendrogram(object): """The hierarchical clustering (dendrogram) of some dataset. A hierarchical clustering means that we know not only the way the elements are separated into groups, but also the exact history of how individual elements were joined into larger subgroups. This class internally represents the hierarchy by a matrix with n rows and 2 columns -- or more precisely, a list of lists of size 2. This is exactly the same as the original format used by C{igraph}'s C core. The M{i}th row of the matrix contains the indices of the two clusters being joined in time step M{i}. The joint group will be represented by the ID M{n+i}, with M{i} starting from one. The ID of the joint group will be referenced in the upcoming steps instead of any of its individual members. So, IDs less than or equal to M{n} (where M{n} is the number of rows in the matrix) mean the original members of the dataset (with ID from 0 to M{n}), while IDs up from M{n+1} mean joint groups. As an example, take a look at the dendrogram and the internal representation of a given clustering of five nodes:: 0 -+ | 1 -+-+ | 2 ---+-+ <====> [[0, 1], [3, 4], [2, 5], [6, 7]] | 3 -+ | | | 4 -+---+--- @undocumented: _item_box_size, _plot_item, _traverse_inorder """ def __init__(self, merges): """Creates a hierarchical clustering. @param merges: the merge history either in matrix or tuple format""" self._merges = [tuple(pair) for pair in merges] self._nmerges = len(self._merges) if self._nmerges: self._nitems = max(self._merges[-1])-self._nmerges+2 else: self._nitems = 0 self._names = None @staticmethod def _convert_matrix_to_tuple_repr(merges, n=None): """Converts the matrix representation of a clustering to a tuple representation. @param merges: the matrix representation of the clustering @return: the tuple representation of the clustering """ if n is None: n = len(merges)+1 tuple_repr = range(n) idxs = range(n) for rowidx, row in enumerate(merges): i, j = row try: idxi, idxj = idxs[i], idxs[j] tuple_repr[idxi] = (tuple_repr[idxi], tuple_repr[idxj]) tuple_repr[idxj] = None except IndexError: raise ValueError("malformed matrix, subgroup referenced "+ "before being created in step %d" % rowidx) idxs.append(j) return [x for x in tuple_repr if x is not None] def _traverse_inorder(self): """Conducts an inorder traversal of the merge tree. The inorder traversal returns the nodes on the last level in the order they should be drawn so that no edges cross each other. @return: the result of the inorder traversal in a list.""" result = [] seen_nodes = set() for node_index in reversed(xrange(self._nitems+self._nmerges)): if node_index in seen_nodes: continue stack = [node_index] while stack: last = stack.pop() seen_nodes.add(last) if last < self._nitems: # 'last' is a regular node so the traversal ends here, we # can append it to the results result.append(last) else: # 'last' is a merge node, so let us proceed with the entry # where this merge node was created stack.extend(self._merges[last-self._nitems]) return result def __str__(self): return self.summary(verbosity=1) def format(self, format="newick"): """Formats the dendrogram in a foreign format. Currently only the Newick format is supported. Example: >>> d = Dendrogram([(2, 3), (0, 1), (4, 5)]) >>> d.format() '((2,3)4,(0,1)5)6;' >>> d.names = list("ABCDEFG") >>> d.format() '((C,D)E,(A,B)F)G;' """ if format == "newick": n = self._nitems + self._nmerges if self._names is None: nodes = range(n) else: nodes = list(self._names) if len(nodes) < n: nodes.extend("" for _ in xrange(n - len(nodes))) for k, (i, j) in enumerate(self._merges, self._nitems): nodes[k] = "(%s,%s)%s" % (nodes[i], nodes[j], nodes[k]) nodes[i] = nodes[j] = None return nodes[-1] + ";" raise ValueError("unsupported format: %r" % format) def summary(self, verbosity=0, max_leaf_count=40): """Returns the summary of the dendrogram. The summary includes the number of leafs and branches, and also an ASCII art representation of the dendrogram unless it is too large. @param verbosity: determines whether the ASCII representation of the dendrogram should be printed. Zero verbosity prints only the number of leafs and branches. @param max_leaf_count: the maximal number of leafs to print in the ASCII representation. If the dendrogram has more leafs than this limit, the ASCII representation will not be printed even if the verbosity is larger than or equal to 1. @return: the summary of the dendrogram as a string. """ out = StringIO() print >>out, "Dendrogram, %d elements, %d merges" % \ (self._nitems, self._nmerges) if self._nitems == 0 or verbosity < 1 or self._nitems > max_leaf_count: return out.getvalue().strip() print >>out positions = [None] * self._nitems inorder = self._traverse_inorder() distance = 2 level_distance = 2 nextp = 0 for idx, element in enumerate(inorder): positions[element] = nextp inorder[idx] = str(element) nextp += max(distance, len(inorder[idx])+1) width = max(positions)+1 # Print the nodes on the lowest level print >>out, (" " * (distance-1)).join(inorder) midx = 0 max_community_idx = self._nitems while midx < self._nmerges: char_array = [" "] * width for position in positions: if position >= 0: char_array[position] = "|" char_str = "".join(char_array) for _ in xrange(level_distance-1): print >>out, char_str # Print the lines cidx_incr = 0 while midx < self._nmerges: id1, id2 = self._merges[midx] if id1 >= max_community_idx or id2 >= max_community_idx: break midx += 1 pos1, pos2 = positions[id1], positions[id2] positions[id1], positions[id2] = -1, -1 if pos1 > pos2: pos1, pos2 = pos2, pos1 positions.append((pos1+pos2) // 2) dashes = "-" * (pos2 - pos1 - 1) char_array[pos1:(pos2+1)] = "`%s'" % dashes cidx_incr += 1 max_community_idx += cidx_incr print >>out, "".join(char_array) return out.getvalue().strip() def _item_box_size(self, context, horiz, idx): """Calculates the amount of space needed for drawing an individual vertex at the bottom of the dendrogram.""" if self._names is None or self._names[idx] is None: x_bearing, _, _, height, x_advance, _ = context.text_extents("") else: x_bearing, _, _, height, x_advance, _ = context.text_extents(str(self._names[idx])) if horiz: return x_advance - x_bearing, height return height, x_advance - x_bearing # pylint: disable-msg=R0913 def _plot_item(self, context, horiz, idx, x, y): """Plots a dendrogram item to the given Cairo context @param context: the Cairo context we are plotting on @param horiz: whether the dendrogram is horizontally oriented @param idx: the index of the item @param x: the X position of the item @param y: the Y position of the item """ if self._names is None or self._names[idx] is None: return height = self._item_box_size(context, True, idx)[1] if horiz: context.move_to(x, y+height) context.show_text(str(self._names[idx])) else: context.save() context.translate(x, y) context.rotate(-pi/2.) context.move_to(0, height) context.show_text(str(self._names[idx])) context.restore() # pylint: disable-msg=C0103,W0613 # W0613 = unused argument 'palette' def __plot__(self, context, bbox, palette, *args, **kwds): """Draws the dendrogram on the given Cairo context Supported keyword arguments are: - C{orientation}: the orientation of the dendrogram. Must be one of the following values: C{left-right}, C{bottom-top}, C{right-left} or C{top-bottom}. Individual elements are always placed at the former edge and merges are performed towards the latter edge. Possible aliases: C{horizontal} = C{left-right}, C{vertical} = C{bottom-top}, C{lr} = C{left-right}, C{rl} = C{right-left}, C{tb} = C{top-bottom}, C{bt} = C{bottom-top}. The default is C{left-right}. """ from igraph.layout import Layout if self._names is None: self._names = [str(x) for x in xrange(self._nitems)] orientation = str_to_orientation(kwds.get("orientation", "lr"), reversed_vertical=True) horiz = orientation in ("lr", "rl") # Get the font height font_height = context.font_extents()[2] # Calculate space needed for individual items at the # bottom of the dendrogram item_boxes = [self._item_box_size(context, horiz, idx) \ for idx in xrange(self._nitems)] # Small correction for cases when the right edge of the labels is # aligned with the tips of the dendrogram branches ygap = 2 if orientation == "bt" else 0 xgap = 2 if orientation == "lr" else 0 item_boxes = [(x+xgap, y+ygap) for x, y in item_boxes] # Calculate coordinates layout = Layout([(0, 0)] * self._nitems, dim=2) inorder = self._traverse_inorder() if not horiz: x, y = 0, 0 for idx, element in enumerate(inorder): layout[element] = (x, 0) x += max(font_height, item_boxes[element][0]) for id1, id2 in self._merges: y += 1 layout.append(((layout[id1][0]+layout[id2][0])/2., y)) # Mirror or rotate the layout if necessary if orientation == "bt": layout.mirror(1) else: x, y = 0, 0 for idx, element in enumerate(inorder): layout[element] = (0, y) y += max(font_height, item_boxes[element][1]) for id1, id2 in self._merges: x += 1 layout.append((x, (layout[id1][1]+layout[id2][1])/2.)) # Mirror or rotate the layout if necessary if orientation == "rl": layout.mirror(0) # Rescale layout to the bounding box maxw = max(e[0] for e in item_boxes) maxh = max(e[1] for e in item_boxes) # w, h: width and height of the area containing the dendrogram # tree without the items. # delta_x, delta_y: displacement of the dendrogram tree width, height = float(bbox.width), float(bbox.height) delta_x, delta_y = 0, 0 if horiz: width -= maxw if orientation == "lr": delta_x = maxw else: height -= maxh if orientation == "tb": delta_y = maxh if horiz: delta_y += font_height / 2. else: delta_x += font_height / 2. layout.fit_into((delta_x, delta_y, width - delta_x, height - delta_y), keep_aspect_ratio=False) context.save() context.translate(bbox.left, bbox.top) context.set_source_rgb(0., 0., 0.) context.set_line_width(1) # Draw items if horiz: sgn = 0 if orientation == "rl" else -1 for idx in xrange(self._nitems): x = layout[idx][0] + sgn * item_boxes[idx][0] y = layout[idx][1] - item_boxes[idx][1]/2. self._plot_item(context, horiz, idx, x, y) else: sgn = 1 if orientation == "bt" else 0 for idx in xrange(self._nitems): x = layout[idx][0] - item_boxes[idx][0]/2. y = layout[idx][1] + sgn * item_boxes[idx][1] self._plot_item(context, horiz, idx, x, y) # Draw dendrogram lines if not horiz: for idx, (id1, id2) in enumerate(self._merges): x0, y0 = layout[id1] x1, y1 = layout[id2] x2, y2 = layout[idx + self._nitems] context.move_to(x0, y0) context.line_to(x0, y2) context.line_to(x1, y2) context.line_to(x1, y1) context.stroke() else: for idx, (id1, id2) in enumerate(self._merges): x0, y0 = layout[id1] x1, y1 = layout[id2] x2, y2 = layout[idx + self._nitems] context.move_to(x0, y0) context.line_to(x2, y0) context.line_to(x2, y1) context.line_to(x1, y1) context.stroke() context.restore() @property def merges(self): """Returns the performed merges in matrix format""" return deepcopy(self._merges) @property def names(self): """Returns the names of the nodes in the dendrogram""" return self._names @names.setter def names(self, items): """Sets the names of the nodes in the dendrogram""" if items is None: self._names = None return items = list(items) if len(items) < self._nitems: raise ValueError("must specify at least %d names" % self._nitems) n = self._nitems + self._nmerges self._names = items[:n] if len(self._names) < n: self._names.extend("" for _ in xrange(n-len(self._names))) class VertexDendrogram(Dendrogram): """The dendrogram resulting from the hierarchical clustering of the vertex set of a graph.""" def __init__(self, graph, merges, optimal_count = None, params = None, modularity_params = None): """Creates a dendrogram object for a given graph. @param graph: the graph that will be associated to the clustering @param merges: the merges performed given in matrix form. @param optimal_count: the optimal number of clusters where the dendrogram should be cut. This is a hint usually provided by the clustering algorithm that produces the dendrogram. C{None} means that such a hint is not available; the optimal count will then be selected based on the modularity in such a case. @param params: additional parameters to be stored in this object. @param modularity_params: arguments that should be passed to L{Graph.modularity} when the modularity is (re)calculated. If the original graph was weighted, you should pass a dictionary containing a C{weight} key with the appropriate value here. """ Dendrogram.__init__(self, merges) self._graph = graph self._optimal_count = optimal_count if modularity_params is None: self._modularity_params = {} else: self._modularity_params = dict(modularity_params) def as_clustering(self, n=None): """Cuts the dendrogram at the given level and returns a corresponding L{VertexClustering} object. @param n: the desired number of clusters. Merges are replayed from the beginning until the membership vector has exactly M{n} distinct elements or until there are no more recorded merges, whichever happens first. If C{None}, the optimal count hint given by the clustering algorithm will be used If the optimal count was not given either, it will be calculated by selecting the level where the modularity is maximal. @return: a new L{VertexClustering} object. """ if n is None: n = self.optimal_count num_elts = self._graph.vcount() idgen = UniqueIdGenerator() membership = community_to_membership(self._merges, num_elts, \ num_elts - n) membership = [idgen[m] for m in membership] return VertexClustering(self._graph, membership, modularity_params=self._modularity_params) @property def optimal_count(self): """Returns the optimal number of clusters for this dendrogram. If an optimal count hint was given at construction time, this property simply returns the hint. If such a count was not given, this method calculates the optimal number of clusters by maximizing the modularity along all the possible cuts in the dendrogram. """ if self._optimal_count is not None: return self._optimal_count n = self._graph.vcount() max_q, optimal_count = 0, 1 for step in xrange(min(n-1, len(self._merges))): membs = community_to_membership(self._merges, n, step) q = self._graph.modularity(membs, **self._modularity_params) if q > max_q: optimal_count = n-step max_q = q self._optimal_count = optimal_count return optimal_count @optimal_count.setter def optimal_count(self, value): self._optimal_count = max(int(value), 1) def __plot__(self, context, bbox, palette, *args, **kwds): """Draws the vertex dendrogram on the given Cairo context See L{Dendrogram.__plot__} for the list of supported keyword arguments.""" from igraph.drawing.metamagic import AttributeCollectorBase class VisualVertexBuilder(AttributeCollectorBase): _kwds_prefix = "vertex_" label = None builder = VisualVertexBuilder(self._graph.vs, kwds) self._names = [vertex.label for vertex in builder] self._names = [name if name is not None else str(idx) for idx, name in enumerate(self._names)] result = Dendrogram.__plot__(self, context, bbox, palette, \ *args, **kwds) del self._names return result ############################################################################### class Cover(object): """Class representing a cover of an arbitrary ordered set. Covers are similar to clusterings, but each element of the set may belong to more than one cluster in a cover, and elements not belonging to any cluster are also allowed. L{Cover} instances provide a similar API as L{Clustering} instances; for instance, iterating over a L{Cover} will iterate over the clusters just like with a regular L{Clustering} instance. However, they are not derived from each other or from a common superclass, and there might be functions that exist only in one of them or the other. Clusters of an individual cover can be accessed by the C{[]} operator: >>> cl = Cover([[0,1,2,3], [2,3,4], [0,1,6]]) >>> cl[0] [0, 1, 2, 3] The membership vector can be accessed by the C{membership} property. Note that contrary to L{Clustering} instances, the membership vector will contain lists that contain the cluster indices each item belongs to: >>> cl.membership [[0, 2], [0, 2], [0, 1], [0, 1], [1], [], [2]] The number of clusters can be retrieved by the C{len} function: >>> len(cl) 3 You can iterate over the cover as if it were a regular list of clusters: >>> for cluster in cl: ... print " ".join(str(idx) for idx in cluster) ... 0 1 2 3 2 3 4 0 1 6 If you need all the clusters at once as lists, you can simply convert the cover to a list: >>> cluster_list = list(cl) >>> print cluster_list [[0, 1, 2, 3], [2, 3, 4], [0, 1, 6]] L{Clustering} objects can readily be converted to L{Cover} objects using the constructor: >>> clustering = Clustering([0, 0, 0, 0, 1, 1, 1, 2, 2, 2]) >>> cover = Cover(clustering) >>> list(clustering) == list(cover) True @undocumented: _formatted_cluster_iterator """ def __init__(self, clusters, n=0): """Constructs a cover with the given clusters. @param clusters: the clusters in this cover, as a list or iterable. Each cluster is specified by a list or tuple that contains the IDs of the items in this cluster. IDs start from zero. @param n: the total number of elements in the set that is covered by this cover. If it is less than the number of unique elements found in all the clusters, we will simply use the number of unique elements, so it is safe to leave this at zero. You only have to specify this parameter if there are some elements that are covered by none of the clusters. """ self._clusters = [list(cluster) for cluster in clusters] try: self._n = max(max(cluster)+1 for cluster in self._clusters if cluster) except ValueError: self._n = 0 self._n = max(n, self._n) def __getitem__(self, index): """Returns the cluster with the given index.""" return self._clusters[index] def __iter__(self): """Iterates over the clusters in this cover.""" return iter(self._clusters) def __len__(self): """Returns the number of clusters in this cover.""" return len(self._clusters) def __str__(self): """Returns a string representation of the cover.""" return self.summary(verbosity=1, width=78) @property def membership(self): """Returns the membership vector of this cover. The membership vector of a cover covering I{n} elements is a list of length I{n}, where element I{i} contains the cluster indices of the I{i}th item. """ result = [[] for _ in xrange(self._n)] for idx, cluster in enumerate(self): for item in cluster: result[item].append(idx) return result @property def n(self): """Returns the number of elements in the set covered by this cover.""" return self._n def size(self, idx): """Returns the size of a given cluster. @param idx: the cluster in which we are interested. """ return len(self[idx]) def sizes(self, *args): """Returns the size of given clusters. The indices are given as positional arguments. If there are no positional arguments, the function will return the sizes of all clusters. """ if args: return [len(self._clusters[idx]) for idx in args] return [len(cluster) for cluster in self] def size_histogram(self, bin_width = 1): """Returns the histogram of cluster sizes. @param bin_width: the bin width of the histogram @return: a L{Histogram} object """ return Histogram(bin_width, self.sizes()) def summary(self, verbosity=0, width=None): """Returns the summary of the cover. The summary includes the number of items and clusters, and also the list of members for each of the clusters if the verbosity is nonzero. @param verbosity: determines whether the cluster members should be printed. Zero verbosity prints the number of items and clusters only. @return: the summary of the cover as a string. """ out = StringIO() print >>out, "Cover with %d clusters" % len(self) if verbosity < 1: return out.getvalue().strip() ndigits = len(str(len(self))) wrapper = _get_wrapper_for_width(width, subsequent_indent = " " * (ndigits+3)) for idx, cluster in enumerate(self._formatted_cluster_iterator()): wrapper.initial_indent = "[%*d] " % (ndigits, idx) print >>out, "\n".join(wrapper.wrap(cluster)) return out.getvalue().strip() def _formatted_cluster_iterator(self): """Iterates over the clusters and formats them into a string to be presented in the summary.""" for cluster in self: yield ", ".join(str(member) for member in cluster) class VertexCover(Cover): """The cover of the vertex set of a graph. This class extends L{Cover} by linking it to a specific L{Graph} object. It also provides some handy methods like getting the subgraph corresponding to a cluster and such. @note: since this class is linked to a L{Graph}, destroying the graph by the C{del} operator does not free the memory occupied by the graph if there exists a L{VertexCover} that references the L{Graph}. @undocumented: _formatted_cluster_iterator """ def __init__(self, graph, clusters = None): """Creates a cover object for a given graph. @param graph: the graph that will be associated to the cover @param clusters: the list of clusters. If C{None}, it is assumed that there is only a single cluster that covers the whole graph. """ if clusters is None: clusters = [range(graph.vcount())] Cover.__init__(self, clusters, n = graph.vcount()) if self._n > graph.vcount(): raise ValueError("cluster list contains vertex ID larger than the " "number of vertices in the graph") self._graph = graph def crossing(self): """Returns a boolean vector where element M{i} is C{True} iff edge M{i} lies between clusters, C{False} otherwise.""" membership = [frozenset(cluster) for cluster in self.membership] return [membership[v1].isdisjoint(membership[v2]) \ for v1, v2 in self.graph.get_edgelist()] @property def graph(self): """Returns the graph belonging to this object""" return self._graph def subgraph(self, idx): """Get the subgraph belonging to a given cluster. @param idx: the cluster index @return: a copy of the subgraph @precondition: the vertex set of the graph hasn't been modified since the moment the cover was constructed. """ return self._graph.subgraph(self[idx]) def subgraphs(self): """Gets all the subgraphs belonging to each of the clusters. @return: a list containing copies of the subgraphs @precondition: the vertex set of the graph hasn't been modified since the moment the cover was constructed. """ return [self._graph.subgraph(cl) for cl in self] def __plot__(self, context, bbox, palette, *args, **kwds): """Plots the cover to the given Cairo context in the given bounding box. This is done by calling L{Graph.__plot__()} with the same arguments, but drawing nice colored blobs around the vertex groups. This method understands all the positional and keyword arguments that are understood by L{Graph.__plot__()}, only the differences will be highlighted here: - C{mark_groups}: whether to highlight the vertex clusters by colored polygons. Besides the values accepted by L{Graph.__plot__} (i.e., a dict mapping colors to vertex indices, a list containing lists of vertex indices, or C{False}), the following are also accepted: - C{True}: all the clusters will be highlighted, the colors matching the corresponding color indices from the current palette (see the C{palette} keyword argument of L{Graph.__plot__}. - A dict mapping cluster indices or tuples of vertex indices to color names. The given clusters or vertex groups will be highlighted by the given colors. - A list of cluster indices. This is equivalent to passing a dict mapping numeric color indices from the current palette to cluster indices; therefore, the cluster referred to by element I{i} of the list will be highlighted by color I{i} from the palette. The value of the C{plotting.mark_groups} configuration key is also taken into account here; if that configuration key is C{True} and C{mark_groups} is not given explicitly, it will automatically be set to C{True}. In place of lists of vertex indices, you may also use L{VertexSeq} instances. In place of color names, you may also use color indices into the current palette. C{None} as a color name will mean that the corresponding group is ignored. - C{palette}: the palette used to resolve numeric color indices to RGBA values. By default, this is an instance of L{ClusterColoringPalette}. @see: L{Graph.__plot__()} for more supported keyword arguments. """ if "edge_color" not in kwds and "color" not in self.graph.edge_attributes(): # Set up a default edge coloring based on internal vs external edges colors = ["grey20", "grey80"] kwds["edge_color"] = [colors[is_crossing] for is_crossing in self.crossing()] if "palette" in kwds: palette = kwds["palette"] else: palette = ClusterColoringPalette(len(self)) if "mark_groups" not in kwds: if Configuration.instance()["plotting.mark_groups"]: kwds["mark_groups"] = self else: kwds["mark_groups"] = _handle_mark_groups_arg_for_clustering( kwds["mark_groups"], self) return self._graph.__plot__(context, bbox, palette, *args, **kwds) def _formatted_cluster_iterator(self): """Iterates over the clusters and formats them into a string to be presented in the summary.""" if self._graph.is_named(): names = self._graph.vs["name"] for cluster in self: yield ", ".join(str(names[member]) for member in cluster) else: for cluster in self: yield ", ".join(str(member) for member in cluster) class CohesiveBlocks(VertexCover): """The cohesive block structure of a graph. Instances of this type are created by L{Graph.cohesive_blocks()}. See the documentation of L{Graph.cohesive_blocks()} for an explanation of what cohesive blocks are. This class provides a few more methods that make handling of cohesive block structures easier. """ def __init__(self, graph, blocks = None, cohesion = None, parent = None): """Constructs a new cohesive block structure for the given graph. If any of I{blocks}, I{cohesion} or I{parent} is C{None}, all the arguments will be ignored and L{Graph.cohesive_blocks()} will be called to calculate the cohesive blocks. Otherwise, these three variables should describe the *result* of a cohesive block structure calculation. Chances are that you never have to construct L{CohesiveBlocks} instances directly, just use L{Graph.cohesive_blocks()}. @param graph: the graph itself @param blocks: a list containing the blocks; each block is described as a list containing vertex IDs. @param cohesion: the cohesion of each block. The length of this list must be equal to the length of I{blocks}. @param parent: the parent block of each block. Negative values or C{None} mean that there is no parent block for that block. There should be only one parent block, which covers the entire graph. @see: Graph.cohesive_blocks() """ if blocks is None or cohesion is None or parent is None: blocks, cohesion, parent = graph.cohesive_blocks() VertexCover.__init__(self, graph, blocks) self._cohesion = cohesion self._parent = parent for idx, p in enumerate(self._parent): if p < 0: self._parent[idx] = None def cohesion(self, idx): """Returns the cohesion of the group with the given index.""" return self._cohesion[idx] def cohesions(self): """Returns the list of cohesion values for each group.""" return self._cohesion[:] def hierarchy(self): """Returns a new graph that describes the hierarchical relationships between the groups. The new graph will be a directed tree; an edge will point from vertex M{i} to vertex M{j} if group M{i} is a superset of group M{j}. In other words, the edges point downwards. """ from igraph import Graph edges = [pair for pair in izip(self._parent, xrange(len(self))) if pair[0] is not None] return Graph(edges, directed=True) def max_cohesion(self, idx): """Finds the maximum cohesion score among all the groups that contain the given vertex.""" result = 0 for cohesion, cluster in izip(self._cohesion, self._clusters): if idx in cluster: result = max(result, cohesion) return result def max_cohesions(self): """For each vertex in the graph, returns the maximum cohesion score among all the groups that contain the vertex.""" result = [0] * self._graph.vcount() for cohesion, cluster in izip(self._cohesion, self._clusters): for idx in cluster: result[idx] = max(result[idx], cohesion) return result def parent(self, idx): """Returns the parent group index of the group with the given index or C{None} if the given group is the root.""" return self._parent[idx] def parents(self): """Returns the list of parent group indices for each group or C{None} if the given group is the root.""" return self._parent[:] def __plot__(self, context, bbox, palette, *args, **kwds): """Plots the cohesive block structure to the given Cairo context in the given bounding box. Since a L{CohesiveBlocks} instance is also a L{VertexCover}, keyword arguments accepted by L{VertexCover.__plot__()} are also accepted here. The only difference is that the vertices are colored according to their maximal cohesions by default, and groups are marked by colored blobs except the last group which encapsulates the whole graph. See the documentation of L{VertexCover.__plot__()} for more details. """ prepare_groups = False if "mark_groups" not in kwds: if Configuration.instance()["plotting.mark_groups"]: prepare_groups = True elif kwds["mark_groups"] == True: prepare_groups = True if prepare_groups: colors = [pair for pair in enumerate(self.cohesions()) if pair[1] > 1] kwds["mark_groups"] = colors if "vertex_color" not in kwds: kwds["vertex_color"] = self.max_cohesions() return VertexCover.__plot__(self, context, bbox, palette, *args, **kwds) def _handle_mark_groups_arg_for_clustering(mark_groups, clustering): """Handles the mark_groups=... keyword argument in plotting methods of clusterings. This is an internal method, you shouldn't need to mess around with it. Its purpose is to handle the extended semantics of the mark_groups=... keyword argument in the C{__plot__} method of L{VertexClustering} and L{VertexCover} instances, namely the feature that numeric IDs are resolved to clusters automatically. """ # Handle the case of mark_groups = True, mark_groups containing a list or # tuple of cluster IDs, and and mark_groups yielding (cluster ID, color) # pairs if mark_groups is True: group_iter = ((group, color) for color, group in enumerate(clustering)) elif isinstance(mark_groups, dict): group_iter = mark_groups.iteritems() elif hasattr(mark_groups, "__getitem__") and hasattr(mark_groups, "__len__"): # Lists, tuples try: first = mark_groups[0] except: # Hmm. Maybe not a list or tuple? first = None if first is not None: # Okay. Is the first element of the list a single number? if isinstance(first, (int, long)): # Yes. Seems like we have a list of cluster indices. # Assign color indices automatically. group_iter = ((group, color) for color, group in enumerate(mark_groups)) else: # No. Seems like we have good ol' group-color pairs. group_iter = mark_groups else: group_iter = mark_groups elif hasattr(mark_groups, "__iter__"): # Iterators etc group_iter = mark_groups else: group_iter = {}.iteritems() def cluster_index_resolver(): for group, color in group_iter: if isinstance(group, (int, long)): group = clustering[group] yield group, color return cluster_index_resolver() ############################################################## def _prepare_community_comparison(comm1, comm2, remove_none=False): """Auxiliary method that takes two community structures either as membership lists or instances of L{Clustering}, and returns a tuple whose two elements are membership lists. This is used by L{compare_communities} and L{split_join_distance}. @param comm1: the first community structure as a membership list or as a L{Clustering} object. @param comm2: the second community structure as a membership list or as a L{Clustering} object. @param remove_none: whether to remove C{None} entries from the membership lists. If C{remove_none} is C{False}, a C{None} entry in either C{comm1} or C{comm2} will result in an exception. If C{remove_none} is C{True}, C{None} values are filtered away and only the remaining lists are compared. """ def _ensure_list(obj): if isinstance(obj, Clustering): return obj.membership return list(obj) vec1, vec2 = _ensure_list(comm1), _ensure_list(comm2) if len(vec1) != len(vec2): raise ValueError("the two membership vectors must be equal in length") if remove_none and (None in vec1 or None in vec2): idxs_to_remove = [i for i in xrange(len(vec1)) \ if vec1[i] is None or vec2[i] is None] idxs_to_remove.reverse() n = len(vec1) for i in idxs_to_remove: n -= 1 vec1[i], vec1[n] = vec1[n], vec1[i] vec2[i], vec2[n] = vec2[n], vec2[i] del vec1[n:] del vec2[n:] return vec1, vec2 def compare_communities(comm1, comm2, method="vi", remove_none=False): """Compares two community structures using various distance measures. @param comm1: the first community structure as a membership list or as a L{Clustering} object. @param comm2: the second community structure as a membership list or as a L{Clustering} object. @param method: the measure to use. C{"vi"} or C{"meila"} means the variation of information metric of Meila (2003), C{"nmi"} or C{"danon"} means the normalized mutual information as defined by Danon et al (2005), C{"split-join"} means the split-join distance of van Dongen (2000), C{"rand"} means the Rand index of Rand (1971), C{"adjusted_rand"} means the adjusted Rand index of Hubert and Arabie (1985). @param remove_none: whether to remove C{None} entries from the membership lists. This is handy if your L{Clustering} object was constructed using L{VertexClustering.FromAttribute} using an attribute which was not defined for all the vertices. If C{remove_none} is C{False}, a C{None} entry in either C{comm1} or C{comm2} will result in an exception. If C{remove_none} is C{True}, C{None} values are filtered away and only the remaining lists are compared. @return: the calculated measure. @newfield ref: Reference @ref: Meila M: Comparing clusterings by the variation of information. In: Scholkopf B, Warmuth MK (eds). Learning Theory and Kernel Machines: 16th Annual Conference on Computational Learning Theory and 7th Kernel Workship, COLT/Kernel 2003, Washington, DC, USA. Lecture Notes in Computer Science, vol. 2777, Springer, 2003. ISBN: 978-3-540-40720-1. @ref: Danon L, Diaz-Guilera A, Duch J, Arenas A: Comparing community structure identification. J Stat Mech P09008, 2005. @ref: van Dongen D: Performance criteria for graph clustering and Markov cluster experiments. Technical Report INS-R0012, National Research Institute for Mathematics and Computer Science in the Netherlands, Amsterdam, May 2000. @ref: Rand WM: Objective criteria for the evaluation of clustering methods. J Am Stat Assoc 66(336):846-850, 1971. @ref: Hubert L and Arabie P: Comparing partitions. Journal of Classification 2:193-218, 1985. """ import igraph._igraph vec1, vec2 = _prepare_community_comparison(comm1, comm2, remove_none) return igraph._igraph._compare_communities(vec1, vec2, method) def split_join_distance(comm1, comm2, remove_none=False): """Calculates the split-join distance between two community structures. The split-join distance is a distance measure defined on the space of partitions of a given set. It is the sum of the projection distance of one partition from the other and vice versa, where the projection number of A from B is if calculated as follows: 1. For each set in A, find the set in B with which it has the maximal overlap, and take note of the size of the overlap. 2. Take the sum of the maximal overlap sizes for each set in A. 3. Subtract the sum from M{n}, the number of elements in the partition. Note that the projection distance is asymmetric, that's why it has to be calculated in both directions and then added together. This function returns the projection distance of C{comm1} from C{comm2} and the projection distance of C{comm2} from C{comm1}, and returns them in a pair. The actual split-join distance is the sum of the two distances. The reason why it is presented this way is that one of the elements being zero then implies that one of the partitions is a subpartition of the other (and if it is close to zero, then one of the partitions is close to being a subpartition of the other). @param comm1: the first community structure as a membership list or as a L{Clustering} object. @param comm2: the second community structure as a membership list or as a L{Clustering} object. @param remove_none: whether to remove C{None} entries from the membership lists. This is handy if your L{Clustering} object was constructed using L{VertexClustering.FromAttribute} using an attribute which was not defined for all the vertices. If C{remove_none} is C{False}, a C{None} entry in either C{comm1} or C{comm2} will result in an exception. If C{remove_none} is C{True}, C{None} values are filtered away and only the remaining lists are compared. @return: the projection distance of C{comm1} from C{comm2} and vice versa in a tuple. The split-join distance is the sum of the two. @newfield ref: Reference @ref: van Dongen D: Performance criteria for graph clustering and Markov cluster experiments. Technical Report INS-R0012, National Research Institute for Mathematics and Computer Science in the Netherlands, Amsterdam, May 2000. @see: L{compare_communities()} with C{method = "split-join"} if you are not interested in the individual projection distances but only the sum of them. """ import igraph._igraph vec1, vec2 = _prepare_community_comparison(comm1, comm2, remove_none) return igraph._igraph._split_join_distance(vec1, vec2) python-igraph-0.8.0/src/igraph/version.py0000644000076500000240000000013713616240074020644 0ustar tamasstaff00000000000000__version_info__ = (0, 8, 0) __version__ = ".".join("{0}".format(x) for x in __version_info__) python-igraph-0.8.0/src/igraph/compat.py0000644000076500000240000000457313104627150020446 0ustar tamasstaff00000000000000# vim:ts=4:sw=4:sts=4:et # -*- coding: utf-8 -*- """ Compatibility methods and backported versions of newer Python features to enable igraph to run on Python 2.5. """ import sys __license__ = u"""\ Copyright (C) 2006-2012 Tamás Nepusz Pázmány Péter sétány 1/a, 1117 Budapest, Hungary This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA """ ############################################################################# # Simulating math.isnan try: from math import isnan except ImportError: def isnan(num): return num != num ############################################################################# # Providing @property.setter syntax for Python 2.5 if sys.version_info < (2, 6): _property = property class property(property): def __init__(self, fget, *args, **kwds): self.__doc__ = fget.__doc__ super(property, self).__init__(fget, *args, **kwds) def setter(self, fset): cls_ns = sys._getframe(1).f_locals for k, v in cls_ns.iteritems(): if v == self: propname = k break cls_ns[propname] = property(self.fget, fset, self.fdel, self.__doc__) return cls_ns[propname] else: if isinstance(__builtins__, dict): # This branch is for CPython property = __builtins__["property"] else: # This branch is for PyPy property = __builtins__.property ############################################################################# # Providing BytesIO for Python 2.5 try: from io import BytesIO except ImportError: # We are on Python 2.5 or earlier because Python 2.6 has a BytesIO # class already from cStringIO import StringIO BytesIO = StringIO python-igraph-0.8.0/src/igraph/app/0000755000076500000240000000000013617375000017363 5ustar tamasstaff00000000000000python-igraph-0.8.0/src/igraph/app/shell.py0000644000076500000240000004453013104627150021047 0ustar tamasstaff00000000000000"""Command-line user interface of igraph The command-line interface launches a Python shell with the igraph module automatically imported into the main namespace. This is mostly a convenience module and it is used only by the C{igraph} command line script which executes a suitable Python shell and automatically imports C{igraph}'s classes and functions in the top-level namespace. Supported Python shells are: - IDLE shell (class L{IDLEShell}) - IPython shell (class L{IPythonShell}) - Classic Python shell (class L{ClassicPythonShell}) The shells are tried in the above mentioned preference order one by one, unless the C{global.shells} configuration key is set which overrides the default order. IDLE shell is only tried in Windows unless explicitly stated by C{global.shells}, since Linux and Mac OS X users are likely to invoke igraph from the command line. """ from __future__ import print_function import re import sys # pylint: disable-msg=W0401 # W0401: wildcard import. That's exactly what we need for the shell. from igraph import __version__, set_progress_handler, set_status_handler from igraph.configuration import Configuration # pylint: disable-msg=C0103,R0903 # C0103: invalid name. Disabled because this is a third-party class. # R0903: too few public methods. class TerminalController: """ A class that can be used to portably generate formatted output to a terminal. `TerminalController` defines a set of instance variables whose values are initialized to the control sequence necessary to perform a given action. These can be simply included in normal output to the terminal: >>> term = TerminalController() >>> print 'This is '+term.GREEN+'green'+term.NORMAL This is green Alternatively, the `render()` method can used, which replaces '${action}' with the string required to perform 'action': >>> term = TerminalController() >>> print term.render('This is ${GREEN}green${NORMAL}') This is green If the terminal doesn't support a given action, then the value of the corresponding instance variable will be set to ''. As a result, the above code will still work on terminals that do not support color, except that their output will not be colored. Also, this means that you can test whether the terminal supports a given action by simply testing the truth value of the corresponding instance variable: >>> term = TerminalController() >>> if term.CLEAR_SCREEN: ... print 'This terminal supports clearning the screen.' ... Finally, if the width and height of the terminal are known, then they will be stored in the `COLS` and `LINES` attributes. @author: Edward Loper """ # Cursor movement: BOL = '' #: Move the cursor to the beginning of the line UP = '' #: Move the cursor up one line DOWN = '' #: Move the cursor down one line LEFT = '' #: Move the cursor left one char RIGHT = '' #: Move the cursor right one char # Deletion: CLEAR_SCREEN = '' #: Clear the screen and move to home position CLEAR_EOL = '' #: Clear to the end of the line. CLEAR_BOL = '' #: Clear to the beginning of the line. CLEAR_EOS = '' #: Clear to the end of the screen # Output modes: BOLD = '' #: Turn on bold mode BLINK = '' #: Turn on blink mode DIM = '' #: Turn on half-bright mode REVERSE = '' #: Turn on reverse-video mode NORMAL = '' #: Turn off all modes # Cursor display: HIDE_CURSOR = '' #: Make the cursor invisible SHOW_CURSOR = '' #: Make the cursor visible # Terminal size: COLS = None #: Width of the terminal (None for unknown) LINES = None #: Height of the terminal (None for unknown) # Foreground colors: BLACK = BLUE = GREEN = CYAN = RED = MAGENTA = YELLOW = WHITE = '' # Background colors: BG_BLACK = BG_BLUE = BG_GREEN = BG_CYAN = '' BG_RED = BG_MAGENTA = BG_YELLOW = BG_WHITE = '' _STRING_CAPABILITIES = """ BOL=cr UP=cuu1 DOWN=cud1 LEFT=cub1 RIGHT=cuf1 CLEAR_SCREEN=clear CLEAR_EOL=el CLEAR_BOL=el1 CLEAR_EOS=ed BOLD=bold BLINK=blink DIM=dim REVERSE=rev UNDERLINE=smul NORMAL=sgr0 HIDE_CURSOR=cinvis SHOW_CURSOR=cnorm""".split() _COLORS = """BLACK BLUE GREEN CYAN RED MAGENTA YELLOW WHITE""".split() _ANSICOLORS = "BLACK RED GREEN YELLOW BLUE MAGENTA CYAN WHITE".split() def __init__(self, term_stream=sys.stdout): """ Create a `TerminalController` and initialize its attributes with appropriate values for the current terminal. `term_stream` is the stream that will be used for terminal output; if this stream is not a tty, then the terminal is assumed to be a dumb terminal (i.e., have no capabilities). """ # Curses isn't available on all platforms try: import curses except ImportError: return # If the stream isn't a tty, then assume it has no capabilities. if not term_stream.isatty(): return # Check the terminal type. If we fail, then assume that the # terminal has no capabilities. try: curses.setupterm() except StandardError: return # Look up numeric capabilities. self.COLS = curses.tigetnum('cols') self.LINES = curses.tigetnum('lines') # Look up string capabilities. for capability in self._STRING_CAPABILITIES: (attrib, cap_name) = capability.split('=') setattr(self, attrib, self._tigetstr(cap_name) or '') # Colors set_fg = self._tigetstr('setf') if set_fg: for i, color in zip(range(len(self._COLORS)), self._COLORS): setattr(self, color, self._tparm(set_fg, i) or '') set_fg_ansi = self._tigetstr('setaf') if set_fg_ansi: for i, color in zip(range(len(self._ANSICOLORS)), self._ANSICOLORS): setattr(self, color, self._tparm(set_fg_ansi, i) or '') set_bg = self._tigetstr('setb') if set_bg: for i, color in zip(range(len(self._COLORS)), self._COLORS): setattr(self, 'BG_'+color, self._tparm(set_bg, i) or '') set_bg_ansi = self._tigetstr('setab') if set_bg_ansi: for i, color in zip(range(len(self._ANSICOLORS)), self._ANSICOLORS): setattr(self, 'BG_'+color, self._tparm(set_bg_ansi, i) or '') @staticmethod def _tigetstr(cap_name): """Rewrites string capabilities to remove "delays" which are not required for modern terminals""" # String capabilities can include "delays" of the form "$<2>". # For any modern terminal, we should be able to just ignore # these, so strip them out. import curses cap = curses.tigetstr(cap_name) or b'' cap = cap.decode("latin-1") return re.sub(r'\$<\d+>[/*]?', '', cap) @staticmethod def _tparm(cap_name, param): import curses cap = curses.tparm(cap_name.encode("latin-1"), param) or b'' return cap.decode("latin-1") def render(self, template): """ Replace each $-substitutions in the given template string with the corresponding terminal control string (if it's defined) or '' (if it's not). """ return re.sub('r\$\$|\${\w+}', self._render_sub, template) def _render_sub(self, match): """Helper function for L{render}""" s = match.group() if s == '$$': return s else: return getattr(self, s[2:-1]) class ProgressBar: """ A 2-line progress bar, which looks like:: Header 20% [===========----------------------------------] The progress bar is colored, if the terminal supports color output; and adjusts to the width of the terminal. """ BAR = '%3d%% ${GREEN}[${BOLD}%s%s${NORMAL}${GREEN}]${NORMAL}' HEADER = '${BOLD}${CYAN}%s${NORMAL}\n' def __init__(self, term): self.term = term if not (self.term.CLEAR_EOL and self.term.UP and self.term.BOL): raise ValueError("Terminal isn't capable enough -- you " "should use a simpler progress display.") self.width = self.term.COLS or 75 self.progress_bar = term.render(self.BAR) self.header = self.term.render(self.HEADER % "".center(self.width)) self.cleared = True #: true if we haven't drawn the bar yet. self.last_percent = 0 self.last_message = "" def update(self, percent=None, message=None): """Updates the progress bar. @param percent: the percentage to be shown. If C{None}, the previous value will be used. @param message: the message to be shown above the progress bar. If C{None}, the previous message will be used. """ if self.cleared: sys.stdout.write("\n"+self.header) self.cleared = False if message is None: message = self.last_message else: self.last_message = message if percent is None: percent = self.last_percent else: self.last_percent = percent n = int((self.width-10)*(percent/100.0)) sys.stdout.write( self.term.BOL + self.term.UP + self.term.UP + self.term.CLEAR_EOL + self.term.render(self.HEADER % message.center(self.width)) + (self.progress_bar % (percent, '='*n, '-'*(self.width-10-n))) + "\n" ) def update_message(self, message): """Updates the message of the progress bar. @param message: the message to be shown above the progress bar """ return self.update(message=message.strip()) def clear(self): """Clears the progress bar (i.e. removes it from the screen)""" if not self.cleared: sys.stdout.write(self.term.BOL + self.term.CLEAR_EOL + self.term.UP + self.term.CLEAR_EOL + self.term.UP + self.term.CLEAR_EOL) self.cleared = True self.last_percent = 0 self.last_message = "" class Shell(object): """Superclass of the embeddable shells supported by igraph""" def __init__(self): pass def __call__(self): raise NotImplementedError("abstract class") def supports_progress_bar(self): """Checks whether the shell supports progress bars. This is done by checking for the existence of an attribute called C{_progress_handler}.""" return hasattr(self, "_progress_handler") def supports_status_messages(self): """Checks whether the shell supports status messages. This is done by checking for the existence of an attribute called C{_status_handler}.""" return hasattr(self, "_status_handler") # pylint: disable-msg=E1101 def get_progress_handler(self): """Returns the progress handler (if exists) or None (if not).""" if self.supports_progress_bar(): return self._progress_handler return None # pylint: disable-msg=E1101 def get_status_handler(self): """Returns the status handler (if exists) or None (if not).""" if self.supports_status_messages(): return self._status_handler return None class IDLEShell(Shell): """IDLE embedded shell interface. This class allows igraph to be embedded in IDLE (the Tk Python IDE). @todo: no progress bar support yet. Shell/Restart Shell command should re-import igraph again.""" def __init__(self): """Constructor. Imports IDLE's embedded shell. The implementation of this method is ripped from idlelib.PyShell.main() after removing the unnecessary parts.""" Shell.__init__(self) import idlelib.PyShell idlelib.PyShell.use_subprocess = True try: sys.ps1 except AttributeError: sys.ps1 = '>>> ' root = idlelib.PyShell.Tk(className="Idle") idlelib.PyShell.fixwordbreaks(root) root.withdraw() flist = idlelib.PyShell.PyShellFileList(root) if not flist.open_shell(): raise NotImplementedError self._shell = flist.pyshell self._root = root def __call__(self): """Starts the shell""" self._shell.interp.execsource("from igraph import *") self._root.mainloop() self._root.destroy() class ConsoleProgressBarMixin(object): """Mixin class for console shells that support a progress bar.""" def __init__(self): try: self.__class__.progress_bar = ProgressBar(TerminalController()) except ValueError: # Terminal is not capable enough, disable progress handler self._disable_handlers() except TypeError: # Probably running in Python 3.x and we hit a str/bytes issue; # as a temporary solution, disable the progress handler self._disable_handlers() def _disable_handlers(self): """Disables the status and progress handlers if the terminal is not capable enough.""" try: del self.__class__._progress_handler except AttributeError: pass try: del self.__class__._status_handler except AttributeError: pass @classmethod def _progress_handler(cls, message, percentage): """Progress bar handler, called when C{igraph} reports the progress of an operation @param message: message provided by C{igraph} @param percentage: percentage provided by C{igraph} """ if percentage >= 100: cls.progress_bar.clear() else: cls.progress_bar.update(percentage, message) @classmethod def _status_handler(cls, message): """Status message handler, called when C{igraph} sends a status message to be displayed. @param message: message provided by C{igraph} """ cls.progress_bar.update_message(message) class IPythonShell(Shell, ConsoleProgressBarMixin): """IPython embedded shell interface. This class allows igraph to be embedded in IPython's interactive shell.""" def __init__(self): """Constructor. Imports IPython's embedded shell with separator lines removed.""" Shell.__init__(self) ConsoleProgressBarMixin.__init__(self) # We cannot use IPShellEmbed here because generator expressions do not # work there (e.g., set(g.degree(x) for x in [1,2,3])) where g comes # from an external context import sys from IPython import __version__ as ipython_version self.ipython_version = ipython_version try: # IPython >= 0.11 supports this try: from IPython.terminal.ipapp import TerminalIPythonApp except ImportError: from IPython.frontend.terminal.ipapp import TerminalIPythonApp self._shell = TerminalIPythonApp.instance() sys.argv.append("--nosep") except ImportError: # IPython 0.10 and earlier import IPython.Shell self._shell = IPython.Shell.start() self._shell.IP.runsource("from igraph import *") sys.argv.append("-nosep") def __call__(self): """Starts the embedded shell.""" print("igraph %s running inside " % __version__, end="") if self._shell.__class__.__name__ == "TerminalIPythonApp": self._shell.initialize() self._shell.shell.ex("from igraph import *") self._shell.start() else: self._shell.mainloop() class ClassicPythonShell(Shell, ConsoleProgressBarMixin): """Classic Python shell interface. This class allows igraph to be embedded in Python's shell.""" def __init__(self): """Constructor. Imports Python's classic shell""" Shell.__init__(self) ConsoleProgressBarMixin.__init__(self) self._shell = None def __call__(self): """Starts the embedded shell.""" if self._shell is None: from code import InteractiveConsole self._shell = InteractiveConsole() print("igraph %s running inside " % __version__, end="", file=sys.stderr) self._shell.runsource("from igraph import *") self._shell.interact() def main(): """The main entry point for igraph when invoked from the command line shell""" config = Configuration.instance() if config.filename: print("Using configuration from %s" % config.filename, file=sys.stderr) else: print("No configuration file, using defaults", file=sys.stderr) if config.has_key("shells"): parts = [part.strip() for part in config["shells"].split(",")] shell_classes = [] available_classes = dict([(k, v) for k, v in globals().iteritems() if isinstance(v, type) and issubclass(v, Shell)]) for part in parts: klass = available_classes.get(part, None) if klass is None: print("Warning: unknown shell class `%s'" % part, file=sys.stderr) continue shell_classes.append(klass) else: shell_classes = [IPythonShell, ClassicPythonShell] import platform if platform.system() == "Windows": shell_classes.insert(0, IDLEShell) shell = None for shell_class in shell_classes: # pylint: disable-msg=W0703 # W0703: catch "Exception" try: shell = shell_class() break except StandardError: # Try the next one if "Classic" in str(shell_class): raise pass if isinstance(shell, Shell): if config["verbose"]: if shell.supports_progress_bar(): set_progress_handler(shell.get_progress_handler()) if shell.supports_status_messages(): set_status_handler(shell.get_status_handler()) shell() else: print("No suitable Python shell was found.", file=sys.stderr) print("Check configuration variable `general.shells'.", file=sys.stderr) if __name__ == '__main__': sys.exit(main()) python-igraph-0.8.0/src/igraph/app/__init__.py0000644000076500000240000000004113104627150021464 0ustar tamasstaff00000000000000"""User interfaces of igraph""" python-igraph-0.8.0/src/igraph/formula.py0000644000076500000240000002133013546443130020622 0ustar tamasstaff00000000000000# vim:ts=4:sw=4:sts=4:et # -*- coding: utf-8 -*- """ Implementation of `igraph.Graph.Formula()` You should use this module directly only if you have a very strong reason to do so. In almost all cases, you are better off with calling `igraph.Graph.Formula()`. """ from cStringIO import StringIO from igraph.datatypes import UniqueIdGenerator import re import tokenize import token __all__ = ["construct_graph_from_formula"] __license__ = u"""\ Copyright (C) 2006-2012 Tamás Nepusz Pázmány Péter sétány 1/a, 1117 Budapest, Hungary This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA """ def generate_edges(formula): """Parses an edge specification from the head of the given formula part and yields the following: - startpoint(s) of the edge by vertex names - endpoint(s) of the edge by names or an empty list if the vertices are isolated - a pair of bools to denote whether we had arrowheads at the start and end vertices """ if formula == "": yield [], [""], [False, False] return name_tokens = set([token.NAME, token.NUMBER, token.STRING]) edge_chars = "<>-+" start_names, end_names, arrowheads = [], [], [False, False] parsing_vertices = True # Tokenize the formula token_gen = tokenize.generate_tokens(StringIO(formula).next) for token_info in token_gen: # Do the state transitions token_type, tok, _, _, _ = token_info if parsing_vertices: if all(ch in edge_chars for ch in tok) and token_type == token.OP: parsing_vertices = False # Check the edge we currently have if start_names and end_names: # We have a whole edge yield start_names, end_names, arrowheads start_names, end_names = end_names, [] arrowheads = [False, False] else: if any(ch not in edge_chars for ch in tok): parsing_vertices = True if parsing_vertices: # We are parsing vertex names at the moment if token_type in name_tokens: # We found a vertex name if token_type == token.STRING: end_names.append(eval(tok)) else: end_names.append(str(tok)) elif tok == ":" and token_type == token.OP: # Separating semicolon between vertex names, we just go on continue elif token_type == token.NEWLINE: # Newlines are fine pass elif token_type == token.ENDMARKER: # End markers are fine pass else: msg = "invalid token found in edge specification: %s; token_type=%r; tok=%r" % (formula, token_type, tok) raise SyntaxError(msg) else: # We are parsing an edge operator if "<" in tok: if ">" in tok: arrowheads = [True, True] else: arrowheads[0] = True elif ">" in tok: arrowheads[1] = True elif "+" in tok: if tok[0] == "+": arrowheads[0] = True if len(tok) > 1 and tok[-1] == "+": arrowheads[1] = True # The final edge yield start_names, end_names, arrowheads def construct_graph_from_formula(cls, formula = None, attr = "name", simplify = True): """Graph.Formula(formula = None, attr = "name", simplify = True) Generates a graph from a graph formula A graph formula is a simple string representation of a graph. It is very handy for creating small graphs quickly. The string consists of vertex names separated by edge operators. An edge operator is a sequence of dashes (C{-}) that may or may not start with an arrowhead (C{<} at the beginning of the sequence or C{>} at the end of the sequence). The edge operators can be arbitrarily long, i.e., you may use as many dashes to draw them as you like. This makes a total of four different edge operators: - C{-----} makes an undirected edge - C{<----} makes a directed edge pointing from the vertex on the right hand side of the operator to the vertex on the left hand side - C{---->} is the opposite of C{<----} - C{<--->} creates a mutual directed edge pair between the two vertices If you only use the undirected edge operator (C{-----}), the graph will be undirected. Otherwise it will be directed. Vertex names used in the formula will be assigned to the C{name} vertex attribute of the graph. Some simple examples: >>> from igraph import Graph >>> print Graph.Formula() # empty graph IGRAPH UN-- 0 0 -- + attr: name (v) >>> g = Graph.Formula("A-B") # undirected graph >>> g.vs["name"] ['A', 'B'] >>> print g IGRAPH UN-- 2 1 -- + attr: name (v) + edges (vertex names): A--B >>> g.get_edgelist() [(0, 1)] >>> g2 = Graph.Formula("A-----------B") >>> g2.isomorphic(g) True >>> g = Graph.Formula("A ---> B") # directed graph >>> g.vs["name"] ['A', 'B'] >>> print g IGRAPH DN-- 2 1 -- + attr: name (v) + edges (vertex names): A->B If you have may disconnected componnets, you can separate them with commas. You can also specify isolated vertices: >>> g = Graph.Formula("A--B, C--D, E--F, G--H, I, J, K") >>> print ", ".join(g.vs["name"]) A, B, C, D, E, F, G, H, I, J, K >>> g.clusters().membership [0, 0, 1, 1, 2, 2, 3, 3, 4, 5, 6] The colon (C{:}) operator can be used to specify vertex sets. If an edge operator connects two vertex sets, then every vertex from the first vertex set will be connected to every vertex in the second set: >>> g = Graph.Formula("A:B:C:D --- E:F:G") >>> g.isomorphic(Graph.Full_Bipartite(4, 3)) True Note that you have to quote vertex names if they include spaces or special characters: >>> g = Graph.Formula('"this is" +- "a silly" -+ "graph here"') >>> g.vs["name"] ['this is', 'a silly', 'graph here'] @param formula: the formula itself @param attr: name of the vertex attribute where the vertex names will be stored @param simplify: whether the simplify the constructed graph @return: the constructed graph: """ # If we have no formula, return an empty graph if formula is None: return cls(0, vertex_attrs = {attr: []}) vertex_ids, edges, directed = UniqueIdGenerator(), [], False # Loop over each part in the formula for part in re.compile(r"[,\n]").split(formula): # Strip leading and trailing whitespace in the part part = part.strip() # Parse the first vertex specification from the formula for start_names, end_names, arrowheads in generate_edges(part): start_ids = [vertex_ids[name] for name in start_names] end_ids = [vertex_ids[name] for name in end_names] if not arrowheads[0] and not arrowheads[1]: # This is an undirected edge. Do we have a directed graph? if not directed: # Nope, add the edge edges.extend((id1, id2) for id1 in start_ids \ for id2 in end_ids) else: # This is a directed edge directed = True if arrowheads[1]: edges.extend((id1, id2) for id1 in start_ids \ for id2 in end_ids) if arrowheads[0]: edges.extend((id2, id1) for id1 in start_ids \ for id2 in end_ids) # Grab the vertex names into a list vertex_attrs = {} vertex_attrs[attr] = vertex_ids.values() # Construct and return the graph result = cls(len(vertex_ids), edges, directed, vertex_attrs=vertex_attrs) if simplify: result.simplify() return result python-igraph-0.8.0/src/igraph/layout.py0000644000076500000240000004262713104627150020502 0ustar tamasstaff00000000000000# vim:ts=4:sw=4:sts=4:et # -*- coding: utf-8 -*- """ Layout-related code in the IGraph library. This package contains the implementation of the L{Layout} object. """ from itertools import izip from math import sin, cos, pi from igraph.drawing.utils import BoundingBox from igraph.statistics import RunningMean __license__ = u"""\ Copyright (C) 2006-2012 Tamás Nepusz Pázmány Péter sétány 1/a, 1117 Budapest, Hungary This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA """ class Layout(object): """Represents the layout of a graph. A layout is practically a list of coordinates in an n-dimensional space. This class is generic in the sense that it can store coordinates in any n-dimensional space. Layout objects are not associated directly with a graph. This is deliberate: there were times when I worked with almost identical copies of the same graph, the only difference was that they had different colors assigned to the vertices. It was particularly convenient for me to use the same layout for all of them, especially when I made figures for a paper. However, C{igraph} will of course refuse to draw a graph with a layout that has less coordinates than the node count of the graph. Layouts behave exactly like lists when they are accessed using the item index operator (C{[...]}). They can even be iterated through. Items returned by the index operator are only copies of the coordinates, but the stored coordinates can be modified by directly assigning to an index. >>> layout = Layout([(0, 1), (0, 2)]) >>> coords = layout[1] >>> print coords [0, 2] >>> coords = (0, 3) >>> print layout[1] [0, 2] >>> layout[1] = coords >>> print layout[1] [0, 3] """ def __init__(self, coords=None, dim=None): """Constructor. @param coords: the coordinates to be stored in the layout. @param dim: the number of dimensions. If C{None}, the number of dimensions is determined automatically from the length of the first item of the coordinate list. If there are no entries in the coordinate list, the default will be 2. Generally, this should be given if the length of the coordinate list is zero, otherwise it should be left as is. """ if coords: self._coords = [list(coord) for coord in coords] else: self._coords = [] if dim is None: if len(self._coords) == 0: self._dim = 2 else: self._dim = len(self._coords[0]) else: self._dim = int(dim) for row in self._coords: if len(row) != self._dim: raise ValueError("all items in the coordinate list "+ "must have a length of %d" % self._dim) def __len__(self): return len(self._coords) def __getitem__(self, idx): return self._coords[idx] def __setitem__(self, idx, value): if len(value) != self._dim: raise ValueError("assigned item must have %d elements" % self._dim) self._coords[idx] = list(value) def __delitem__(self, idx): del self._coords[idx] def __copy__(self): return self.__class__(self.coords, self.dim) def __repr__(self): if not self.coords: vertex_count = "no vertices" elif len(self.coords) == 1: vertex_count = "1 vertex" else: vertex_count = "%d vertices" % len(self.coords) if self.dim == 1: dim_count = "1 dimension" else: dim_count = "%d dimensions" % self.dim return "<%s with %s and %s>" % (self.__class__.__name__, vertex_count, dim_count) @property def dim(self): """Returns the number of dimensions""" return self._dim @property def coords(self): """The coordinates as a list of lists""" return [row[:] for row in self._coords] def append(self, value): """Appends a new point to the layout""" if len(value) < self._dim: raise ValueError("appended item must have %d elements" % self._dim) self._coords.append([float(coord) for coord in value[0:self._dim]]) def mirror(self, dim): """Mirrors the layout along the given dimension(s) @param dim: the list of dimensions or a single dimension """ if isinstance(dim, int): dim = [dim] else: dim = [int(x) for x in dim] for current_dim in dim: for row in self._coords: row[current_dim] *= -1 def rotate(self, angle, dim1=0, dim2=1, **kwds): """Rotates the layout by the given degrees on the plane defined by the given two dimensions. @param angle: the angle of the rotation, specified in degrees. @param dim1: the first axis of the plane of the rotation. @param dim2: the second axis of the plane of the rotation. @keyword origin: the origin of the rotation. If not specified, the origin will be the origin of the coordinate system. """ origin = list(kwds.get("origin", [0.]*self._dim)) if len(origin) != self._dim: raise ValueError("origin must have %d dimensions" % self._dim) radian = angle * pi / 180. cos_alpha, sin_alpha = cos(radian), sin(radian) for idx, row in enumerate(self._coords): x, y = row[dim1] - origin[dim1], row[dim2] - origin[dim2] row[dim1] = cos_alpha*x - sin_alpha*y + origin[dim1] row[dim2] = sin_alpha*x + cos_alpha*y + origin[dim2] def scale(self, *args, **kwds): """Scales the layout. Scaling parameters can be provided either through the C{scale} keyword argument or through plain unnamed arguments. If a single integer or float is given, it is interpreted as a uniform multiplier to be applied on all dimensions. If it is a list or tuple, its length must be equal to the number of dimensions in the layout, and each element must be an integer or float describing the scaling coefficient in one of the dimensions. @keyword scale: scaling coefficients (integer, float, list or tuple) @keyword origin: the origin of scaling (this point will stay in place). Optional, defaults to the origin of the coordinate system being used. """ origin = list(kwds.get("origin", [0.]*self._dim)) if len(origin) != self._dim: raise ValueError("origin must have %d dimensions" % self._dim) scaling = kwds.get("scale") or args if isinstance(scaling, (int, float)): scaling = [scaling] if len(scaling) == 0: raise ValueError("scaling factor must be given") elif len(scaling) == 1: if type(scaling[0]) == int or type(scaling[0]) == float: scaling = scaling*self._dim else: scaling = scaling[0] if len(scaling) != self._dim: raise ValueError("scaling factor list must have %d elements" \ % self._dim) for idx, row in enumerate(self._coords): self._coords[idx] = [(row[d]-origin[d])*scaling[d]+origin[d] \ for d in xrange(self._dim)] def translate(self, *args, **kwds): """Translates the layout. The translation vector can be provided either through the C{v} keyword argument or through plain unnamed arguments. If unnamed arguments are used, the vector can be supplied as a single list (or tuple) or just as a series of arguments. In all cases, the translation vector must have the same number of dimensions as the layout. @keyword v: the translation vector """ v = kwds.get("v") or args if len(v) == 0: raise ValueError("translation vector must be given") elif len(v) == 1 and type(v[0]) != int and type(v[0]) != float: v = v[0] if len(v) != self._dim: raise ValueError("translation vector must have %d dimensions" \ % self._dim) for idx, row in enumerate(self._coords): self._coords[idx] = [row[d]+v[d] for d in xrange(self._dim)] def to_radial(self, min_angle = 100, max_angle = 80, \ min_radius=0.0, max_radius=1.0): """Converts a planar layout to a radial one This method applies only to 2D layouts. The X coordinate of the layout is transformed to an angle, with min(x) corresponding to the parameter called I{min_angle} and max(y) corresponding to I{max_angle}. Angles are given in degrees, zero degree corresponds to the direction pointing upwards. The Y coordinate is interpreted as a radius, with min(y) belonging to the minimum and max(y) to the maximum radius given in the arguments. This is not a fully generic polar coordinate transformation, but it is fairly useful in creating radial tree layouts from ordinary top-down ones (that's why the Y coordinate belongs to the radius). It can also be used in conjunction with the Fruchterman-Reingold layout algorithm via its I{miny} and I{maxy} parameters (see L{Graph.layout_fruchterman_reingold}) to produce radial layouts where the radius belongs to some property of the vertices. @param min_angle: the angle corresponding to the minimum X value @param max_angle: the angle corresponding to the maximum X value @param min_radius: the radius corresponding to the minimum Y value @param max_radius: the radius corresponding to the maximum Y value """ if self._dim != 2: raise TypeError("implemented only for 2D layouts") bbox = self.bounding_box() while min_angle > max_angle: max_angle += 360 while min_angle > 360: min_angle -= 360 max_angle -= 360 while min_angle < 0: min_angle += 360 max_angle += 360 ratio_x = (max_angle - min_angle) / bbox.width ratio_x *= pi / 180. min_angle *= pi / 180. ratio_y = (max_radius - min_radius) / bbox.height for idx, (x, y) in enumerate(self._coords): alpha = (x-bbox.left) * ratio_x + min_angle radius = (y-bbox.top) * ratio_y + min_radius self._coords[idx] = [cos(alpha)*radius, -sin(alpha)*radius] def transform(self, function, *args, **kwds): """Performs an arbitrary transformation on the layout Additional positional and keyword arguments are passed intact to the given function. @param function: a function which receives the coordinates as a tuple and returns the transformed tuple. """ self._coords = [list(function(tuple(row), *args, **kwds)) \ for row in self._coords] def centroid(self): """Returns the centroid of the layout. The centroid of the layout is the arithmetic mean of the points in the layout. @return: the centroid as a list of floats""" centroid = [RunningMean() for _ in xrange(self._dim)] for row in self._coords: for dim in xrange(self._dim): centroid[dim].add(row[dim]) return [rm.mean for rm in centroid] def boundaries(self, border=0): """Returns the boundaries of the layout. The boundaries are the minimum and maximum coordinates along all dimensions. @param border: this value gets subtracted from the minimum bounds and gets added to the maximum bounds before returning the coordinates of the box. Defaults to zero. @return: the minimum and maximum coordinates along all dimensions, in a tuple containing two lists, one for the minimum coordinates, the other one for the maximum. @raises ValueError: if the layout contains no layout items """ if not self._coords: raise ValueError("layout contains no layout items") mins, maxs = [], [] for dim in xrange(self._dim): col = [row[dim] for row in self._coords] mins.append(min(col)-border) maxs.append(max(col)+border) return mins, maxs def bounding_box(self, border=0): """Returns the bounding box of the layout. The bounding box of the layout is the smallest box enclosing all the points in the layout. @param border: this value gets subtracted from the minimum bounds and gets added to the maximum bounds before returning the coordinates of the box. Defaults to zero. @return: the coordinates of the lower left and the upper right corner of the box. "Lower left" means the minimum coordinates and "upper right" means the maximum. These are encapsulated in a L{BoundingBox} object. """ if self._dim != 2: raise ValueError("Layout.boundary_box() supports 2D layouts only") try: (x0, y0), (x1, y1) = self.boundaries(border) return BoundingBox(x0, y0, x1, y1) except ValueError: return BoundingBox(0, 0, 0, 0) def center(self, *args, **kwds): """Centers the layout around the given point. The point itself can be supplied as multiple unnamed arguments, as a simple unnamed list or as a keyword argument. This operation moves the centroid of the layout to the given point. If no point is supplied, defaults to the origin of the coordinate system. @keyword p: the point where the centroid of the layout will be after the operation.""" center = kwds.get("p") or args if len(center) == 0: center = [0.] * self._dim elif len(center) == 1 and type(center[0]) != int \ and type(center[0]) != float: center = center[0] if len(center) != self._dim: raise ValueError("the given point must have %d dimensions" \ % self._dim) centroid = self.centroid() vec = [center[d]-centroid[d] for d in xrange(self._dim)] self.translate(vec) def copy(self): """Creates an exact copy of the layout.""" return self.__copy__() def fit_into(self, bbox, keep_aspect_ratio=True): """Fits the layout into the given bounding box. The layout will be modified in-place. @param bbox: the bounding box in which to fit the layout. If the dimension of the layout is d, it can either be a d-tuple (defining the sizes of the box), a 2d-tuple (defining the coordinates of the top left and the bottom right point of the box), or a L{BoundingBox} object (for 2D layouts only). @param keep_aspect_ratio: whether to keep the aspect ratio of the current layout. If C{False}, the layout will be rescaled to fit exactly into the bounding box. If C{True}, the original aspect ratio of the layout will be kept and it will be centered within the bounding box. """ if isinstance(bbox, BoundingBox): if self._dim != 2: raise TypeError("bounding boxes work for 2D layouts only") corner, target_sizes = [bbox.left, bbox.top], [bbox.width, bbox.height] elif len(bbox) == self._dim: corner, target_sizes = [0.] * self._dim, list(bbox) elif len(bbox) == 2 * self._dim: corner, opposite_corner = list(bbox[0:self._dim]), list(bbox[self._dim:]) for i in xrange(self._dim): if corner[i] > opposite_corner[i]: corner[i], opposite_corner[i] = opposite_corner[i], corner[i] target_sizes = [max_val-min_val \ for min_val, max_val in izip(corner, opposite_corner)] try: mins, maxs = self.boundaries() except ValueError: mins, maxs = [0.0] * self._dim, [0.0] * self._dim sizes = [max_val - min_val for min_val, max_val in izip(mins, maxs)] for i, size in enumerate(sizes): if size == 0: sizes[i] = 2 mins[i] -= 1 maxs[i] += 1 ratios = [float(target_size) / current_size \ for current_size, target_size in izip(sizes, target_sizes)] if keep_aspect_ratio: min_ratio = min(ratios) ratios = [min_ratio] * self._dim translations = [] for i in xrange(self._dim): trans = (target_sizes[i] - ratios[i] * sizes[i]) / 2. trans -= mins[i] * ratios[i] - corner[i] translations.append(trans) self.scale(*ratios) self.translate(*translations) python-igraph-0.8.0/src/igraph/cut.py0000644000076500000240000001456613104627150017761 0ustar tamasstaff00000000000000# vim:ts=4:sw=4:sts=4:et # -*- coding: utf-8 -*- """Classes representing cuts and flows on graphs.""" from igraph.clustering import VertexClustering __license__ = """\ Copyright (C) 2006-2012 Tamás Nepusz Pázmány Péter sétány 1/a, 1117 Budapest, Hungary This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA """ class Cut(VertexClustering): """A cut of a given graph. This is a simple class used to represent cuts returned by L{Graph.mincut()}, L{Graph.all_st_cuts()} and other functions that calculate cuts. A cut is a special vertex clustering with only two clusters. Besides the usual L{VertexClustering} methods, it also has the following attributes: - C{value} - the value (capacity) of the cut. It is equal to the number of edges if there are no capacities on the edges. - C{partition} - vertex IDs in the parts created after removing edges in the cut - C{cut} - edge IDs in the cut - C{es} - an edge selector restricted to the edges in the cut. You can use indexing on this object to obtain lists of vertex IDs for both sides of the partition. This class is usually not instantiated directly, everything is taken care of by the functions that return cuts. Examples: >>> from igraph import Graph >>> g = Graph.Ring(20) >>> mc = g.mincut() >>> print mc.value 2.0 >>> print min(map(len, mc)) 1 >>> mc.es["color"] = "red" """ # pylint: disable-msg=R0913 def __init__(self, graph, value=None, cut=None, partition=None, partition2=None): """Initializes the cut. This should not be called directly, everything is taken care of by the functions that return cuts. """ # Input validation if partition is None or cut is None: raise ValueError("partition and cut must be given") # Set up a membership vector, initialize parent class membership = [1] * graph.vcount() for vid in partition: membership[vid] = 0 VertexClustering.__init__(self, graph, membership) if value is None: # Value of the cut not given, count the number of edges value = len(cut) self._value = float(value) self._partition = sorted(partition) self._cut = cut def __repr__(self): return "%s(%r, %r, %r, %r)" % \ (self.__class__.__name__, self._graph, \ self._value, self._cut, self._partition) def __str__(self): return "Graph cut (%d edges, %d vs %d vertices, value=%.4f)" % \ (len(self._cut), len(self._partition), self._graph.vcount() - len(self._partition), self._value) # pylint: disable-msg=C0103 @property def es(self): """Returns an edge selector restricted to the cut""" return self._graph.es.select(self.cut) @property def partition(self): """Returns the vertex IDs partitioned according to the cut""" return list(self) @property def cut(self): """Returns the edge IDs in the cut""" return self._cut @property def value(self): """Returns the sum of edge capacities in the cut""" return self._value class Flow(Cut): """A flow of a given graph. This is a simple class used to represent flows returned by L{Graph.maxflow}. It has the following attributes: - C{graph} - the graph on which this flow is defined - C{value} - the value (capacity) of the flow - C{flow} - the flow values on each edge. For directed graphs, this is simply a list where element M{i} corresponds to the flow on edge M{i}. For undirected graphs, the direction of the flow is not constrained (since the edges are undirected), hence positive flow always means a flow from the smaller vertex ID to the larger, while negative flow means a flow from the larger vertex ID to the smaller. - C{cut} - edge IDs in the minimal cut corresponding to the flow. - C{partition} - vertex IDs in the parts created after removing edges in the cut - C{es} - an edge selector restricted to the edges in the cut. This class is usually not instantiated directly, everything is taken care of by L{Graph.maxflow}. Examples: >>> from igraph import Graph >>> g = Graph.Ring(20) >>> mf = g.maxflow(0, 10) >>> print mf.value 2.0 >>> mf.es["color"] = "red" """ # pylint: disable-msg=R0913 def __init__(self, graph, value, flow, cut, partition): """Initializes the flow. This should not be called directly, everything is taken care of by L{Graph.maxflow}. """ super(Flow, self).__init__(graph, value, cut, partition) self._flow = flow def __repr__(self): return "%s(%r, %r, %r, %r, %r)" % \ (self.__class__.__name__, self._graph, \ self._value, self._flow, self._cut, self._partition) def __str__(self): return "Graph flow (%d edges, %d vs %d vertices, value=%.4f)" % \ (len(self._cut), len(self._partition), self._graph.vcount() - len(self._partition), self._value) @property def flow(self): """Returns the flow values for each edge. For directed graphs, this is simply a list where element M{i} corresponds to the flow on edge M{i}. For undirected graphs, the direction of the flow is not constrained (since the edges are undirected), hence positive flow always means a flow from the smaller vertex ID to the larger, while negative flow means a flow from the larger vertex ID to the smaller. """ return self._flow python-igraph-0.8.0/src/igraph/__init__.py0000644000076500000240000056171413616774160020743 0ustar tamasstaff00000000000000# vim:ts=4:sw=4:sts=4:et # -*- coding: utf-8 -*- """ IGraph library. @undocumented: deprecated, _graphmethod, _add_proxy_methods, _layout_method_wrapper, _3d_version_for """ from __future__ import with_statement __license__ = u""" Copyright (C) 2006-2012 Tamás Nepusz Pázmány Péter sétány 1/a, 1117 Budapest, Hungary This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA """ # pylint: disable-msg=W0401 # W0401: wildcard import from igraph._igraph import * from igraph.clustering import * from igraph.cut import * from igraph.configuration import Configuration from igraph.drawing import * from igraph.drawing.colors import * from igraph.datatypes import * from igraph.formula import * from igraph.layout import * from igraph.matching import * from igraph.statistics import * from igraph.summary import * from igraph.utils import * from igraph.version import __version__, __version_info__ import os import math import gzip import sys import operator from collections import defaultdict from itertools import izip from shutil import copyfileobj from warnings import warn def deprecated(message): """Prints a warning message related to the deprecation of some igraph feature.""" warn(message, DeprecationWarning, stacklevel=3) # pylint: disable-msg=E1101 class Graph(GraphBase): """Generic graph. This class is built on top of L{GraphBase}, so the order of the methods in the Epydoc documentation is a little bit obscure: inherited methods come after the ones implemented directly in the subclass. L{Graph} provides many functions that L{GraphBase} does not, mostly because these functions are not speed critical and they were easier to implement in Python than in pure C. An example is the attribute handling in the constructor: the constructor of L{Graph} accepts three dictionaries corresponding to the graph, vertex and edge attributes while the constructor of L{GraphBase} does not. This extension was needed to make L{Graph} serializable through the C{pickle} module. L{Graph} also overrides some functions from L{GraphBase} to provide a more convenient interface; e.g., layout functions return a L{Layout} instance from L{Graph} instead of a list of coordinate pairs. Graphs can also be indexed by strings or pairs of vertex indices or vertex names. When a graph is indexed by a string, the operation translates to the retrieval, creation, modification or deletion of a graph attribute: >>> g = Graph.Full(3) >>> g["name"] = "Triangle graph" >>> g["name"] 'Triangle graph' >>> del g["name"] When a graph is indexed by a pair of vertex indices or names, the graph itself is treated as an adjacency matrix and the corresponding cell of the matrix is returned: >>> g = Graph.Full(3) >>> g.vs["name"] = ["A", "B", "C"] >>> g[1, 2] 1 >>> g["A", "B"] 1 >>> g["A", "B"] = 0 >>> g.ecount() 2 Assigning values different from zero or one to the adjacency matrix will be translated to one, unless the graph is weighted, in which case the numbers will be treated as weights: >>> g.is_weighted() False >>> g["A", "B"] = 2 >>> g["A", "B"] 1 >>> g.es["weight"] = 1.0 >>> g.is_weighted() True >>> g["A", "B"] = 2 >>> g["A", "B"] 2 >>> g.es["weight"] [1.0, 1.0, 2] """ # Some useful aliases omega = GraphBase.clique_number alpha = GraphBase.independence_number shell_index = GraphBase.coreness cut_vertices = GraphBase.articulation_points blocks = GraphBase.biconnected_components evcent = GraphBase.eigenvector_centrality vertex_disjoint_paths = GraphBase.vertex_connectivity edge_disjoint_paths = GraphBase.edge_connectivity cohesion = GraphBase.vertex_connectivity adhesion = GraphBase.edge_connectivity # Compatibility aliases shortest_paths_dijkstra = GraphBase.shortest_paths subgraph = GraphBase.induced_subgraph def __init__(self, *args, **kwds): """__init__(n=0, edges=None, directed=False, graph_attrs=None, vertex_attrs=None, edge_attrs=None) Constructs a graph from scratch. @keyword n: the number of vertices. Can be omitted, the default is zero. Note that if the edge list contains vertices with indexes larger than or equal to M{m}, then the number of vertices will be adjusted accordingly. @keyword edges: the edge list where every list item is a pair of integers. If any of the integers is larger than M{n-1}, the number of vertices is adjusted accordingly. C{None} means no edges. @keyword directed: whether the graph should be directed @keyword graph_attrs: the attributes of the graph as a dictionary. @keyword vertex_attrs: the attributes of the vertices as a dictionary. Every dictionary value must be an iterable with exactly M{n} items. @keyword edge_attrs: the attributes of the edges as a dictionary. Every dictionary value must be an iterable with exactly M{m} items where M{m} is the number of edges. """ # Pop the special __ptr keyword argument ptr = kwds.pop("__ptr", None) # Set up default values for the parameters. This should match the order # in *args kwd_order = ( "n", "edges", "directed", "graph_attrs", "vertex_attrs", "edge_attrs" ) params = [0, [], False, {}, {}, {}] # Is there any keyword argument in kwds that we don't know? If so, # freak out. unknown_kwds = set(kwds.keys()) unknown_kwds.difference_update(kwd_order) if unknown_kwds: raise TypeError("{0}.__init__ got an unexpected keyword argument {1!r}".format( self.__class__.__name__, unknown_kwds.pop() )) # If the first argument is a list or any other iterable, assume that # the number of vertices were omitted args = list(args) if len(args) > 0 and hasattr(args[0], "__iter__"): args.insert(0, params[0]) # Override default parameters from args params[:len(args)] = args # Override default parameters from keywords for idx, k in enumerate(kwd_order): if k in kwds: params[idx] = kwds[k] # Now, translate the params list to argument names nverts, edges, directed, graph_attrs, vertex_attrs, edge_attrs = params # When the number of vertices is None, assume that the user meant zero if nverts is None: nverts = 0 # When 'edges' is None, assume that the user meant an empty list if edges is None: edges = [] # When 'edges' is a NumPy array or matrix, convert it into a memoryview # as the lower-level C API works with memoryviews only try: from numpy import ndarray, matrix if isinstance(edges, (ndarray, matrix)): edges = numpy_to_contiguous_memoryview(edges) except ImportError: pass # Initialize the graph if ptr: GraphBase.__init__(self, __ptr=ptr) else: GraphBase.__init__(self, nverts, edges, directed) # Set the graph attributes for key, value in graph_attrs.iteritems(): if isinstance(key, (int, long)): key = str(key) self[key] = value # Set the vertex attributes for key, value in vertex_attrs.iteritems(): if isinstance(key, (int, long)): key = str(key) self.vs[key] = value # Set the edge attributes for key, value in edge_attrs.iteritems(): if isinstance(key, (int, long)): key = str(key) self.es[key] = value def add_edge(self, source, target, **kwds): """add_edge(source, target, **kwds) Adds a single edge to the graph. Keyword arguments (except the source and target arguments) will be assigned to the edge as attributes. @param source: the source vertex of the edge or its name. @param target: the target vertex of the edge or its name. @return: the newly added edge as an L{Edge} object. Use C{add_edges([(source, target)])} if you don't need the L{Edge} object and want to avoid the overhead of creating t. """ eid = self.ecount() self.add_edges([(source, target)]) edge = self.es[eid] for key, value in kwds.iteritems(): edge[key] = value return edge def add_edges(self, es): """add_edges(es) Adds some edges to the graph. @param es: the list of edges to be added. Every edge is represented with a tuple containing the vertex IDs or names of the two endpoints. Vertices are enumerated from zero. """ return GraphBase.add_edges(self, es) def add_vertex(self, name=None, **kwds): """add_vertex(name=None, **kwds) Adds a single vertex to the graph. Keyword arguments will be assigned as vertex attributes. Note that C{name} as a keyword argument is treated specially; if a graph has C{name} as a vertex attribute, it allows one to refer to vertices by their names in most places where igraph expects a vertex ID. @return: the newly added vertex as a L{Vertex} object. Use C{add_vertices(1)} if you don't need the L{Vertex} object and want to avoid the overhead of creating t. """ vid = self.vcount() self.add_vertices(1) vertex = self.vs[vid] for key, value in kwds.iteritems(): vertex[key] = value if name is not None: vertex["name"] = name return vertex def add_vertices(self, n): """add_vertices(n) Adds some vertices to the graph. @param n: the number of vertices to be added, or the name of a single vertex to be added, or a sequence of strings, each corresponding to the name of a vertex to be added. Names will be assigned to the C{name} vertex attribute. """ if isinstance(n, basestring): # Adding a single vertex with a name m = self.vcount() result = GraphBase.add_vertices(self, 1) self.vs[m]["name"] = n return result elif hasattr(n, "__iter__"): m = self.vcount() if not hasattr(n, "__len__"): names = list(n) else: names = n result = GraphBase.add_vertices(self, len(names)) self.vs[m:]["name"] = names return result return GraphBase.add_vertices(self, n) def adjacent(self, *args, **kwds): """adjacent(vertex, mode=OUT) Returns the edges a given vertex is incident on. @deprecated: replaced by L{Graph.incident()} since igraph 0.6 """ deprecated("Graph.adjacent() is deprecated since igraph 0.6, please use " "Graph.incident() instead") return self.incident(*args, **kwds) def as_directed(self, *args, **kwds): """as_directed(*args, **kwds) Returns a directed copy of this graph. Arguments are passed on to L{Graph.to_directed()} that is invoked on the copy. """ copy = self.copy() copy.to_directed(*args, **kwds) return copy def as_undirected(self, *args, **kwds): """as_undirected(*args, **kwds) Returns an undirected copy of this graph. Arguments are passed on to L{Graph.to_undirected()} that is invoked on the copy. """ copy = self.copy() copy.to_undirected(*args, **kwds) return copy def delete_edges(self, *args, **kwds): """Deletes some edges from the graph. The set of edges to be deleted is determined by the positional and keyword arguments. If any keyword argument is present, or the first positional argument is callable, an edge sequence is derived by calling L{EdgeSeq.select} with the same positional and keyword arguments. Edges in the derived edge sequence will be removed. Otherwise the first positional argument is considered as follows: - C{None} - deletes all edges - a single integer - deletes the edge with the given ID - a list of integers - deletes the edges denoted by the given IDs - a list of 2-tuples - deletes the edges denoted by the given source-target vertex pairs. When multiple edges are present between a given source-target vertex pair, only one is removed. """ if len(args) == 0 and len(kwds) == 0: raise ValueError("expected at least one argument") if len(kwds)>0 or (hasattr(args[0], "__call__") and \ not isinstance(args[0], EdgeSeq)): edge_seq = self.es(*args, **kwds) else: edge_seq = args[0] return GraphBase.delete_edges(self, edge_seq) def indegree(self, *args, **kwds): """Returns the in-degrees in a list. See L{degree} for possible arguments. """ kwds['mode'] = IN return self.degree(*args, **kwds) def outdegree(self, *args, **kwds): """Returns the out-degrees in a list. See L{degree} for possible arguments. """ kwds['mode'] = OUT return self.degree(*args, **kwds) def all_st_cuts(self, source, target): """\ Returns all the cuts between the source and target vertices in a directed graph. This function lists all edge-cuts between a source and a target vertex. Every cut is listed exactly once. @param source: the source vertex ID @param target: the target vertex ID @return: a list of L{Cut} objects. @newfield ref: Reference @ref: JS Provan and DR Shier: A paradigm for listing (s,t)-cuts in graphs. Algorithmica 15, 351--372, 1996. """ return [Cut(self, cut=cut, partition=part) for cut, part in izip(*GraphBase.all_st_cuts(self, source, target))] def all_st_mincuts(self, source, target, capacity=None): """\ Returns all the mincuts between the source and target vertices in a directed graph. This function lists all minimum edge-cuts between a source and a target vertex. @param source: the source vertex ID @param target: the target vertex ID @param capacity: the edge capacities (weights). If C{None}, all edges have equal weight. May also be an attribute name. @return: a list of L{Cut} objects. @newfield ref: Reference @ref: JS Provan and DR Shier: A paradigm for listing (s,t)-cuts in graphs. Algorithmica 15, 351--372, 1996. """ value, cuts, parts = GraphBase.all_st_mincuts(self, source, target, capacity) return [Cut(self, value, cut=cut, partition=part) for cut, part in izip(cuts, parts)] def biconnected_components(self, return_articulation_points=False): """\ Calculates the biconnected components of the graph. @param return_articulation_points: whether to return the articulation points as well @return: a L{VertexCover} object describing the biconnected components, and optionally the list of articulation points as well """ if return_articulation_points: trees, aps = GraphBase.biconnected_components(self, True) else: trees = GraphBase.biconnected_components(self, False) clusters = [] for tree in trees: cluster = set() for edge in self.es[tree]: cluster.update(edge.tuple) clusters.append(sorted(cluster)) clustering = VertexCover(self, clusters) if return_articulation_points: return clustering, aps else: return clustering blocks = biconnected_components def cohesive_blocks(self): """cohesive_blocks() Calculates the cohesive block structure of the graph. Cohesive blocking is a method of determining hierarchical subsets of graph vertices based on their structural cohesion (i.e. vertex connectivity). For a given graph G, a subset of its vertices S is said to be maximally k-cohesive if there is no superset of S with vertex connectivity greater than or equal to k. Cohesive blocking is a process through which, given a k-cohesive set of vertices, maximally l-cohesive subsets are recursively identified with l > k. Thus a hierarchy of vertex subsets is obtained in the end, with the entire graph G at its root. @return: an instance of L{CohesiveBlocks}. See the documentation of L{CohesiveBlocks} for more information. @see: L{CohesiveBlocks} """ return CohesiveBlocks(self, *GraphBase.cohesive_blocks(self)) def clusters(self, mode=STRONG): """clusters(mode=STRONG) Calculates the (strong or weak) clusters (connected components) for a given graph. @param mode: must be either C{STRONG} or C{WEAK}, depending on the clusters being sought. Optional, defaults to C{STRONG}. @return: a L{VertexClustering} object""" return VertexClustering(self, GraphBase.clusters(self, mode)) components = clusters def degree_distribution(self, bin_width = 1, *args, **kwds): """degree_distribution(bin_width=1, ...) Calculates the degree distribution of the graph. Unknown keyword arguments are directly passed to L{degree()}. @param bin_width: the bin width of the histogram @return: a histogram representing the degree distribution of the graph. """ result = Histogram(bin_width, self.degree(*args, **kwds)) return result def dyad_census(self, *args, **kwds): """dyad_census() Calculates the dyad census of the graph. Dyad census means classifying each pair of vertices of a directed graph into three categories: mutual (there is an edge from I{a} to I{b} and also from I{b} to I{a}), asymmetric (there is an edge from I{a} to I{b} or from I{b} to I{a} but not the other way round) and null (there is no connection between I{a} and I{b}). @return: a L{DyadCensus} object. @newfield ref: Reference @ref: Holland, P.W. and Leinhardt, S. (1970). A Method for Detecting Structure in Sociometric Data. American Journal of Sociology, 70, 492-513. """ return DyadCensus(GraphBase.dyad_census(self, *args, **kwds)) def get_adjacency(self, type=GET_ADJACENCY_BOTH, attribute=None, \ default=0, eids=False): """Returns the adjacency matrix of a graph. @param type: either C{GET_ADJACENCY_LOWER} (uses the lower triangle of the matrix) or C{GET_ADJACENCY_UPPER} (uses the upper triangle) or C{GET_ADJACENCY_BOTH} (uses both parts). Ignored for directed graphs. @param attribute: if C{None}, returns the ordinary adjacency matrix. When the name of a valid edge attribute is given here, the matrix returned will contain the default value at the places where there is no edge or the value of the given attribute where there is an edge. Multiple edges are not supported, the value written in the matrix in this case will be unpredictable. This parameter is ignored if I{eids} is C{True} @param default: the default value written to the cells in the case of adjacency matrices with attributes. @param eids: specifies whether the edge IDs should be returned in the adjacency matrix. Since zero is a valid edge ID, the cells in the matrix that correspond to unconnected vertex pairs will contain -1 instead of 0 if I{eids} is C{True}. If I{eids} is C{False}, the number of edges will be returned in the matrix for each vertex pair. @return: the adjacency matrix as a L{Matrix}. """ if type != GET_ADJACENCY_LOWER and type != GET_ADJACENCY_UPPER and \ type != GET_ADJACENCY_BOTH: # Maybe it was called with the first argument as the attribute name type, attribute = attribute, type if type is None: type = GET_ADJACENCY_BOTH if eids: result = Matrix(GraphBase.get_adjacency(self, type, eids)) result -= 1 return result if attribute is None: return Matrix(GraphBase.get_adjacency(self, type)) if attribute not in self.es.attribute_names(): raise ValueError("Attribute does not exist") data = [[default] * self.vcount() for _ in xrange(self.vcount())] if self.is_directed(): for edge in self.es: data[edge.source][edge.target] = edge[attribute] return Matrix(data) if type == GET_ADJACENCY_BOTH: for edge in self.es: source, target = edge.tuple data[source][target] = edge[attribute] data[target][source] = edge[attribute] elif type == GET_ADJACENCY_UPPER: for edge in self.es: data[min(edge.tuple)][max(edge.tuple)] = edge[attribute] else: for edge in self.es: data[max(edge.tuple)][min(edge.tuple)] = edge[attribute] return Matrix(data) def get_adjacency_sparse(self, attribute=None): """Returns the adjacency matrix of a graph as scipy csr matrix. @param attribute: if C{None}, returns the ordinary adjacency matrix. When the name of a valid edge attribute is given here, the matrix returned will contain the default value at the places where there is no edge or the value of the given attribute where there is an edge. @return: the adjacency matrix as a L{scipy.sparse.csr_matrix}.""" try: from scipy.sparse import csr_matrix except ImportError: raise ImportError('You should install scipy package in order to use this function') edges = self.get_edgelist() if attribute is None: weights = [1] * len(edges) else: if attribute not in self.es.attribute_names(): raise ValueError("Attribute does not exist") weights = self.es[attribute] N = self.vcount() sparse_matrix = csr_matrix((weights, zip(*edges)), shape=(N, N)) if not self.is_directed(): sparse_matrix = sparse_matrix + sparse_matrix.T di = np.diag_indices(len(edges)) sparse_matrix[di] /= 2 return sparse_matrix def get_adjlist(self, mode=OUT): """get_adjlist(mode=OUT) Returns the adjacency list representation of the graph. The adjacency list representation is a list of lists. Each item of the outer list belongs to a single vertex of the graph. The inner list contains the neighbors of the given vertex. @param mode: if L{OUT}, returns the successors of the vertex. If L{IN}, returns the predecessors of the vertex. If L{ALL}, both the predecessors and the successors will be returned. Ignored for undirected graphs. """ return [self.neighbors(idx, mode) for idx in xrange(self.vcount())] def get_adjedgelist(self, *args, **kwds): """get_adjedgelist(mode=OUT) Returns the incidence list representation of the graph. @deprecated: replaced by L{Graph.get_inclist()} since igraph 0.6 @see: Graph.get_inclist() """ deprecated("Graph.get_adjedgelist() is deprecated since igraph 0.6, " "please use Graph.get_inclist() instead") return self.get_inclist(*args, **kwds) def get_all_simple_paths(self, v, to=None, cutoff=-1, mode=OUT): """get_all_simple_paths(v, to=None, mode=OUT) Calculates all the simple paths from a given node to some other nodes (or all of them) in a graph. A path is simple if its vertices are unique, i.e. no vertex is visited more than once. Note that potentially there are exponentially many paths between two vertices of a graph, especially if your graph is lattice-like. In this case, you may run out of memory when using this function. @param v: the source for the calculated paths @param to: a vertex selector describing the destination for the calculated paths. This can be a single vertex ID, a list of vertex IDs, a single vertex name, a list of vertex names or a L{VertexSeq} object. C{None} means all the vertices. @param cutoff: maximum length of path that is considered. If negative, paths of all lengths are considered. @param mode: the directionality of the paths. L{IN} means to calculate incoming paths, L{OUT} means to calculate outgoing paths, L{ALL} means to calculate both ones. @return: all of the simple paths from the given node to every other reachable node in the graph in a list. Note that in case of mode=L{IN}, the vertices in a path are returned in reversed order! """ paths = self._get_all_simple_paths(v, to, cutoff, mode) prev = 0 result = [] for index, item in enumerate(paths): if item < 0: result.append(paths[prev:index]) prev = index+1 return result def get_inclist(self, mode=OUT): """get_inclist(mode=OUT) Returns the incidence list representation of the graph. The incidence list representation is a list of lists. Each item of the outer list belongs to a single vertex of the graph. The inner list contains the IDs of the incident edges of the given vertex. @param mode: if L{OUT}, returns the successors of the vertex. If L{IN}, returns the predecessors of the vertex. If L{ALL}, both the predecessors and the successors will be returned. Ignored for undirected graphs. """ return [self.incident(idx, mode) for idx in xrange(self.vcount())] def gomory_hu_tree(self, capacity=None, flow="flow"): """gomory_hu_tree(capacity=None, flow="flow") Calculates the Gomory-Hu tree of an undirected graph with optional edge capacities. The Gomory-Hu tree is a concise representation of the value of all the maximum flows (or minimum cuts) in a graph. The vertices of the tree correspond exactly to the vertices of the original graph in the same order. Edges of the Gomory-Hu tree are annotated by flow values. The value of the maximum flow (or minimum cut) between an arbitrary (u,v) vertex pair in the original graph is then given by the minimum flow value (i.e. edge annotation) along the shortest path between u and v in the Gomory-Hu tree. @param capacity: the edge capacities (weights). If C{None}, all edges have equal weight. May also be an attribute name. @param flow: the name of the edge attribute in the returned graph in which the flow values will be stored. @return: the Gomory-Hu tree as a L{Graph} object. """ graph, flow_values = GraphBase.gomory_hu_tree(self, capacity) graph.es[flow] = flow_values return graph def is_named(self): """is_named() Returns whether the graph is named, i.e., whether it has a "name" vertex attribute. """ return "name" in self.vertex_attributes() def is_weighted(self): """is_weighted() Returns whether the graph is weighted, i.e., whether it has a "weight" edge attribute. """ return "weight" in self.edge_attributes() def maxflow(self, source, target, capacity=None): """maxflow(source, target, capacity=None) Returns a maximum flow between the given source and target vertices in a graph. A maximum flow from I{source} to I{target} is an assignment of non-negative real numbers to the edges of the graph, satisfying two properties: 1. For each edge, the flow (i.e. the assigned number) is not more than the capacity of the edge (see the I{capacity} argument) 2. For every vertex except the source and the target, the incoming flow is the same as the outgoing flow. The value of the flow is the incoming flow of the target or the outgoing flow of the source (which are equal). The maximum flow is the maximum possible such value. @param capacity: the edge capacities (weights). If C{None}, all edges have equal weight. May also be an attribute name. @return: a L{Flow} object describing the maximum flow """ return Flow(self, *GraphBase.maxflow(self, source, target, capacity)) def mincut(self, source=None, target=None, capacity=None): """mincut(source=None, target=None, capacity=None) Calculates the minimum cut between the given source and target vertices or within the whole graph. The minimum cut is the minimum set of edges that needs to be removed to separate the source and the target (if they are given) or to disconnect the graph (if neither the source nor the target are given). The minimum is calculated using the weights (capacities) of the edges, so the cut with the minimum total capacity is calculated. For undirected graphs and no source and target, the method uses the Stoer-Wagner algorithm. For a given source and target, the method uses the push-relabel algorithm; see the references below. @param source: the source vertex ID. If C{None}, the target must also be C{None} and the calculation will be done for the entire graph (i.e. all possible vertex pairs). @param target: the target vertex ID. If C{None}, the source must also be C{None} and the calculation will be done for the entire graph (i.e. all possible vertex pairs). @param capacity: the edge capacities (weights). If C{None}, all edges have equal weight. May also be an attribute name. @return: a L{Cut} object describing the minimum cut """ return Cut(self, *GraphBase.mincut(self, source, target, capacity)) def st_mincut(self, source, target, capacity=None): """st_mincut(source, target, capacity=None) Calculates the minimum cut between the source and target vertices in a graph. @param source: the source vertex ID @param target: the target vertex ID @param capacity: the capacity of the edges. It must be a list or a valid attribute name or C{None}. In the latter case, every edge will have the same capacity. @return: the value of the minimum cut, the IDs of vertices in the first and second partition, and the IDs of edges in the cut, packed in a 4-tuple """ return Cut(self, *GraphBase.st_mincut(self, source, target, capacity)) def modularity(self, membership, weights=None): """modularity(membership, weights=None) Calculates the modularity score of the graph with respect to a given clustering. The modularity of a graph w.r.t. some division measures how good the division is, or how separated are the different vertex types from each other. It's defined as M{Q=1/(2m)*sum(Aij-ki*kj/(2m)delta(ci,cj),i,j)}. M{m} is the number of edges, M{Aij} is the element of the M{A} adjacency matrix in row M{i} and column M{j}, M{ki} is the degree of node M{i}, M{kj} is the degree of node M{j}, and M{Ci} and C{cj} are the types of the two vertices (M{i} and M{j}). M{delta(x,y)} is one iff M{x=y}, 0 otherwise. If edge weights are given, the definition of modularity is modified as follows: M{Aij} becomes the weight of the corresponding edge, M{ki} is the total weight of edges adjacent to vertex M{i}, M{kj} is the total weight of edges adjacent to vertex M{j} and M{m} is the total edge weight in the graph. @param membership: a membership list or a L{VertexClustering} object @param weights: optional edge weights or C{None} if all edges are weighed equally. Attribute names are also allowed. @return: the modularity score @newfield ref: Reference @ref: MEJ Newman and M Girvan: Finding and evaluating community structure in networks. Phys Rev E 69 026113, 2004. """ if isinstance(membership, VertexClustering): if membership.graph != self: raise ValueError("clustering object belongs to another graph") return GraphBase.modularity(self, membership.membership, weights) else: return GraphBase.modularity(self, membership, weights) def path_length_hist(self, directed=True): """path_length_hist(directed=True) Returns the path length histogram of the graph @param directed: whether to consider directed paths. Ignored for undirected graphs. @return: a L{Histogram} object. The object will also have an C{unconnected} attribute that stores the number of unconnected vertex pairs (where the second vertex can not be reached from the first one). The latter one will be of type long (and not a simple integer), since this can be I{very} large. """ data, unconn = GraphBase.path_length_hist(self, directed) hist = Histogram(bin_width=1) for i, length in enumerate(data): hist.add(i+1, length) hist.unconnected = long(unconn) return hist def pagerank(self, vertices=None, directed=True, damping=0.85, weights=None, arpack_options=None, implementation="prpack", niter=1000, eps=0.001): """Calculates the Google PageRank values of a graph. @param vertices: the indices of the vertices being queried. C{None} means all of the vertices. @param directed: whether to consider directed paths. @param damping: the damping factor. M{1-damping} is the PageRank value for nodes with no incoming links. It is also the probability of resetting the random walk to a uniform distribution in each step. @param weights: edge weights to be used. Can be a sequence or iterable or even an edge attribute name. @param arpack_options: an L{ARPACKOptions} object used to fine-tune the ARPACK eigenvector calculation. If omitted, the module-level variable called C{arpack_options} is used. This argument is ignored if not the ARPACK implementation is used, see the I{implementation} argument. @param implementation: which implementation to use to solve the PageRank eigenproblem. Possible values are: - C{"prpack"}: use the PRPACK library. This is a new implementation in igraph 0.7 - C{"arpack"}: use the ARPACK library. This implementation was used from version 0.5, until version 0.7. - C{"power"}: use a simple power method. This is the implementation that was used before igraph version 0.5. @param niter: The number of iterations to use in the power method implementation. It is ignored in the other implementations @param eps: The power method implementation will consider the calculation as complete if the difference of PageRank values between iterations change less than this value for every node. It is ignored by the other implementations. @return: a list with the Google PageRank values of the specified vertices.""" if arpack_options is None: arpack_options = _igraph.arpack_options return self.personalized_pagerank(vertices, directed, damping, None,\ None, weights, arpack_options, \ implementation, niter, eps) def spanning_tree(self, weights=None, return_tree=True): """Calculates a minimum spanning tree for a graph. @param weights: a vector containing weights for every edge in the graph. C{None} means that the graph is unweighted. @param return_tree: whether to return the minimum spanning tree (when C{return_tree} is C{True}) or to return the IDs of the edges in the minimum spanning tree instead (when C{return_tree} is C{False}). The default is C{True} for historical reasons as this argument was introduced in igraph 0.6. @return: the spanning tree as a L{Graph} object if C{return_tree} is C{True} or the IDs of the edges that constitute the spanning tree if C{return_tree} is C{False}. @newfield ref: Reference @ref: Prim, R.C.: I{Shortest connection networks and some generalizations}. Bell System Technical Journal 36:1389-1401, 1957. """ result = GraphBase._spanning_tree(self, weights) if return_tree: return self.subgraph_edges(result, delete_vertices=False) return result def transitivity_avglocal_undirected(self, mode="nan", weights=None): """Calculates the average of the vertex transitivities of the graph. In the unweighted case, the transitivity measures the probability that two neighbors of a vertex are connected. In case of the average local transitivity, this probability is calculated for each vertex and then the average is taken. Vertices with less than two neighbors require special treatment, they will either be left out from the calculation or they will be considered as having zero transitivity, depending on the I{mode} parameter. The calculation is slightly more involved for weighted graphs; in this case, weights are taken into account according to the formula of Barrat et al (see the references). Note that this measure is different from the global transitivity measure (see L{transitivity_undirected()}) as it simply takes the average local transitivity across the whole network. @param mode: defines how to treat vertices with degree less than two. If C{TRANSITIVITY_ZERO} or C{"zero"}, these vertices will have zero transitivity. If C{TRANSITIVITY_NAN} or C{"nan"}, these vertices will be excluded from the average. @param weights: edge weights to be used. Can be a sequence or iterable or even an edge attribute name. @see: L{transitivity_undirected()}, L{transitivity_local_undirected()} @newfield ref: Reference @ref: Watts DJ and Strogatz S: I{Collective dynamics of small-world networks}. Nature 393(6884):440-442, 1998. @ref: Barrat A, Barthelemy M, Pastor-Satorras R and Vespignani A: I{The architecture of complex weighted networks}. PNAS 101, 3747 (2004). U{http://arxiv.org/abs/cond-mat/0311416}. """ if weights is None: return GraphBase.transitivity_avglocal_undirected(self, mode) xs = self.transitivity_local_undirected(mode=mode, weights=weights) return sum(xs) / float(len(xs)) def triad_census(self, *args, **kwds): """triad_census() Calculates the triad census of the graph. @return: a L{TriadCensus} object. @newfield ref: Reference @ref: Davis, J.A. and Leinhardt, S. (1972). The Structure of Positive Interpersonal Relations in Small Groups. In: J. Berger (Ed.), Sociological Theories in Progress, Volume 2, 218-251. Boston: Houghton Mifflin. """ return TriadCensus(GraphBase.triad_census(self, *args, **kwds)) # Automorphisms def count_automorphisms_vf2(self, color=None, edge_color=None, node_compat_fn=None, edge_compat_fn=None): """Returns the number of automorphisms of the graph. This function simply calls C{count_isomorphisms_vf2} with the graph itself. See C{count_isomorphisms_vf2} for an explanation of the parameters. @return: the number of automorphisms of the graph @see: Graph.count_isomorphisms_vf2 """ return self.count_isomorphisms_vf2(self, color1=color, color2=color, edge_color1=edge_color, edge_color2=edge_color, node_compat_fn=node_compat_fn, edge_compat_fn=edge_compat_fn) def get_automorphisms_vf2(self, color=None, edge_color=None, node_compat_fn=None, edge_compat_fn=None): """Returns all the automorphisms of the graph This function simply calls C{get_isomorphisms_vf2} with the graph itself. See C{get_isomorphisms_vf2} for an explanation of the parameters. @return: a list of lists, each item containing a possible mapping of the graph vertices to itself according to the automorphism @see: Graph.get_isomorphisms_vf2 """ return self.get_isomorphisms_vf2(self, color1=color, color2=color, edge_color1=edge_color, edge_color2=edge_color, node_compat_fn=node_compat_fn, edge_compat_fn=edge_compat_fn) # Various clustering algorithms -- mostly wrappers around GraphBase def community_fastgreedy(self, weights=None): """Community structure based on the greedy optimization of modularity. This algorithm merges individual nodes into communities in a way that greedily maximizes the modularity score of the graph. It can be proven that if no merge can increase the current modularity score, the algorithm can be stopped since no further increase can be achieved. This algorithm is said to run almost in linear time on sparse graphs. @param weights: edge attribute name or a list containing edge weights @return: an appropriate L{VertexDendrogram} object. @newfield ref: Reference @ref: A Clauset, MEJ Newman and C Moore: Finding community structure in very large networks. Phys Rev E 70, 066111 (2004). """ merges, qs = GraphBase.community_fastgreedy(self, weights) # qs may be shorter than |V|-1 if we are left with a few separated # communities in the end; take this into account diff = self.vcount() - len(qs) qs.reverse() if qs: optimal_count = qs.index(max(qs)) + diff + 1 else: optimal_count = diff return VertexDendrogram(self, merges, optimal_count, modularity_params=dict(weights=weights)) def community_infomap(self, edge_weights=None, vertex_weights=None, trials=10): """Finds the community structure of the network according to the Infomap method of Martin Rosvall and Carl T. Bergstrom. @param edge_weights: name of an edge attribute or a list containing edge weights. @param vertex_weights: name of an vertex attribute or a list containing vertex weights. @param trials: the number of attempts to partition the network. @return: an appropriate L{VertexClustering} object with an extra attribute called C{codelength} that stores the code length determined by the algorithm. @newfield ref: Reference @ref: M. Rosvall and C. T. Bergstrom: Maps of information flow reveal community structure in complex networks, PNAS 105, 1118 (2008). U{http://dx.doi.org/10.1073/pnas.0706851105}, U{http://arxiv.org/abs/0707.0609}. @ref: M. Rosvall, D. Axelsson, and C. T. Bergstrom: The map equation, Eur. Phys. J. Special Topics 178, 13 (2009). U{http://dx.doi.org/10.1140/epjst/e2010-01179-1}, U{http://arxiv.org/abs/0906.1405}. """ membership, codelength = \ GraphBase.community_infomap(self, edge_weights, vertex_weights, trials) return VertexClustering(self, membership, \ params={"codelength": codelength}, \ modularity_params={"weights": edge_weights} ) def community_leading_eigenvector_naive(self, clusters = None, \ return_merges = False): """community_leading_eigenvector_naive(clusters=None, return_merges=False) A naive implementation of Newman's eigenvector community structure detection. This function splits the network into two components according to the leading eigenvector of the modularity matrix and then recursively takes the given number of steps by splitting the communities as individual networks. This is not the correct way, however, see the reference for explanation. Consider using the correct L{community_leading_eigenvector} method instead. @param clusters: the desired number of communities. If C{None}, the algorithm tries to do as many splits as possible. Note that the algorithm won't split a community further if the signs of the leading eigenvector are all the same, so the actual number of discovered communities can be less than the desired one. @param return_merges: whether the returned object should be a dendrogram instead of a single clustering. @return: an appropriate L{VertexClustering} or L{VertexDendrogram} object. @newfield ref: Reference @ref: MEJ Newman: Finding community structure in networks using the eigenvectors of matrices, arXiv:physics/0605087""" if clusters is None: clusters = -1 cl, merges, q = GraphBase.community_leading_eigenvector_naive(self, \ clusters, return_merges) if merges is None: return VertexClustering(self, cl, modularity = q) else: return VertexDendrogram(self, merges, safemax(cl)+1) def community_leading_eigenvector(self, clusters=None, weights=None, \ arpack_options=None): """community_leading_eigenvector(clusters=None, weights=None, arpack_options=None) Newman's leading eigenvector method for detecting community structure. This is the proper implementation of the recursive, divisive algorithm: each split is done by maximizing the modularity regarding the original network. @param clusters: the desired number of communities. If C{None}, the algorithm tries to do as many splits as possible. Note that the algorithm won't split a community further if the signs of the leading eigenvector are all the same, so the actual number of discovered communities can be less than the desired one. @param weights: name of an edge attribute or a list containing edge weights. @param arpack_options: an L{ARPACKOptions} object used to fine-tune the ARPACK eigenvector calculation. If omitted, the module-level variable called C{arpack_options} is used. @return: an appropriate L{VertexClustering} object. @newfield ref: Reference @ref: MEJ Newman: Finding community structure in networks using the eigenvectors of matrices, arXiv:physics/0605087""" if clusters is None: clusters = -1 kwds = dict(weights=weights) if arpack_options is not None: kwds["arpack_options"] = arpack_options membership, _, q = GraphBase.community_leading_eigenvector(self, clusters, **kwds) return VertexClustering(self, membership, modularity = q) def community_label_propagation(self, weights = None, initial = None, \ fixed = None): """community_label_propagation(weights=None, initial=None, fixed=None) Finds the community structure of the graph according to the label propagation method of Raghavan et al. Initially, each vertex is assigned a different label. After that, each vertex chooses the dominant label in its neighbourhood in each iteration. Ties are broken randomly and the order in which the vertices are updated is randomized before every iteration. The algorithm ends when vertices reach a consensus. Note that since ties are broken randomly, there is no guarantee that the algorithm returns the same community structure after each run. In fact, they frequently differ. See the paper of Raghavan et al on how to come up with an aggregated community structure. @param weights: name of an edge attribute or a list containing edge weights @param initial: name of a vertex attribute or a list containing the initial vertex labels. Labels are identified by integers from zero to M{n-1} where M{n} is the number of vertices. Negative numbers may also be present in this vector, they represent unlabeled vertices. @param fixed: a list of booleans for each vertex. C{True} corresponds to vertices whose labeling should not change during the algorithm. It only makes sense if initial labels are also given. Unlabeled vertices cannot be fixed. @return: an appropriate L{VertexClustering} object. @newfield ref: Reference @ref: Raghavan, U.N. and Albert, R. and Kumara, S. Near linear time algorithm to detect community structures in large-scale networks. Phys Rev E 76:036106, 2007. U{http://arxiv.org/abs/0709.2938}. """ if isinstance(fixed, basestring): fixed = [bool(o) for o in g.vs[fixed]] cl = GraphBase.community_label_propagation(self, \ weights, initial, fixed) return VertexClustering(self, cl, modularity_params=dict(weights=weights)) def community_multilevel(self, weights=None, return_levels=False): """Community structure based on the multilevel algorithm of Blondel et al. This is a bottom-up algorithm: initially every vertex belongs to a separate community, and vertices are moved between communities iteratively in a way that maximizes the vertices' local contribution to the overall modularity score. When a consensus is reached (i.e. no single move would increase the modularity score), every community in the original graph is shrank to a single vertex (while keeping the total weight of the adjacent edges) and the process continues on the next level. The algorithm stops when it is not possible to increase the modularity any more after shrinking the communities to vertices. This algorithm is said to run almost in linear time on sparse graphs. @param weights: edge attribute name or a list containing edge weights @param return_levels: if C{True}, the communities at each level are returned in a list. If C{False}, only the community structure with the best modularity is returned. @return: a list of L{VertexClustering} objects, one corresponding to each level (if C{return_levels} is C{True}), or a L{VertexClustering} corresponding to the best modularity. @newfield ref: Reference @ref: VD Blondel, J-L Guillaume, R Lambiotte and E Lefebvre: Fast unfolding of community hierarchies in large networks, J Stat Mech P10008 (2008), http://arxiv.org/abs/0803.0476 """ if self.is_directed(): raise ValueError("input graph must be undirected") if return_levels: levels, qs = GraphBase.community_multilevel(self, weights, True) result = [] for level, q in zip(levels, qs): result.append(VertexClustering(self, level, q, modularity_params=dict(weights=weights))) else: membership = GraphBase.community_multilevel(self, weights, False) result = VertexClustering(self, membership, modularity_params=dict(weights=weights)) return result def community_optimal_modularity(self, *args, **kwds): """Calculates the optimal modularity score of the graph and the corresponding community structure. This function uses the GNU Linear Programming Kit to solve a large integer optimization problem in order to find the optimal modularity score and the corresponding community structure, therefore it is unlikely to work for graphs larger than a few (less than a hundred) vertices. Consider using one of the heuristic approaches instead if you have such a large graph. @return: the calculated membership vector and the corresponding modularity in a tuple.""" membership, modularity = \ GraphBase.community_optimal_modularity(self, *args, **kwds) return VertexClustering(self, membership, modularity) def community_edge_betweenness(self, clusters=None, directed=True, weights=None): """Community structure based on the betweenness of the edges in the network. The idea is that the betweenness of the edges connecting two communities is typically high, as many of the shortest paths between nodes in separate communities go through them. So we gradually remove the edge with the highest betweenness and recalculate the betweennesses after every removal. This way sooner or later the network falls of to separate components. The result of the clustering will be represented by a dendrogram. @param clusters: the number of clusters we would like to see. This practically defines the "level" where we "cut" the dendrogram to get the membership vector of the vertices. If C{None}, the dendrogram is cut at the level which maximizes the modularity when the graph is unweighted; otherwise the dendrogram is cut at at a single cluster (because cluster count selection based on modularities does not make sense for this method if not all the weights are equal). @param directed: whether the directionality of the edges should be taken into account or not. @param weights: name of an edge attribute or a list containing edge weights. @return: a L{VertexDendrogram} object, initally cut at the maximum modularity or at the desired number of clusters. """ merges, qs = GraphBase.community_edge_betweenness(self, directed, weights) if qs is not None: qs.reverse() if clusters is None: if qs: clusters = qs.index(max(qs))+1 else: clusters = 1 return VertexDendrogram(self, merges, clusters, modularity_params=dict(weights=weights)) def community_spinglass(self, *args, **kwds): """community_spinglass(weights=None, spins=25, parupdate=False, start_temp=1, stop_temp=0.01, cool_fact=0.99, update_rule="config", gamma=1, implementation="orig", lambda_=1) Finds the community structure of the graph according to the spinglass community detection method of Reichardt & Bornholdt. @keyword weights: edge weights to be used. Can be a sequence or iterable or even an edge attribute name. @keyword spins: integer, the number of spins to use. This is the upper limit for the number of communities. It is not a problem to supply a (reasonably) big number here, in which case some spin states will be unpopulated. @keyword parupdate: whether to update the spins of the vertices in parallel (synchronously) or not @keyword start_temp: the starting temperature @keyword stop_temp: the stop temperature @keyword cool_fact: cooling factor for the simulated annealing @keyword update_rule: specifies the null model of the simulation. Possible values are C{"config"} (a random graph with the same vertex degrees as the input graph) or C{"simple"} (a random graph with the same number of edges) @keyword gamma: the gamma argument of the algorithm, specifying the balance between the importance of present and missing edges within a community. The default value of 1.0 assigns equal importance to both of them. @keyword implementation: currently igraph contains two implementations of the spinglass community detection algorithm. The faster original implementation is the default. The other implementation is able to take into account negative weights, this can be chosen by setting C{implementation} to C{"neg"} @keyword lambda_: the lambda argument of the algorithm, which specifies the balance between the importance of present and missing negatively weighted edges within a community. Smaller values of lambda lead to communities with less negative intra-connectivity. If the argument is zero, the algorithm reduces to a graph coloring algorithm, using the number of spins as colors. This argument is ignored if the original implementation is used. Note the underscore at the end of the argument name; this is due to the fact that lambda is a reserved keyword in Python. @return: an appropriate L{VertexClustering} object. @newfield ref: Reference @ref: Reichardt J and Bornholdt S: Statistical mechanics of community detection. Phys Rev E 74:016110 (2006). U{http://arxiv.org/abs/cond-mat/0603718}. @ref: Traag VA and Bruggeman J: Community detection in networks with positive and negative links. Phys Rev E 80:036115 (2009). U{http://arxiv.org/abs/0811.2329}. """ membership = GraphBase.community_spinglass(self, *args, **kwds) if "weights" in kwds: modularity_params=dict(weights=kwds["weights"]) else: modularity_params={} return VertexClustering(self, membership, modularity_params=modularity_params) def community_walktrap(self, weights=None, steps=4): """Community detection algorithm of Latapy & Pons, based on random walks. The basic idea of the algorithm is that short random walks tend to stay in the same community. The result of the clustering will be represented as a dendrogram. @param weights: name of an edge attribute or a list containing edge weights @param steps: length of random walks to perform @return: a L{VertexDendrogram} object, initially cut at the maximum modularity. @newfield ref: Reference @ref: Pascal Pons, Matthieu Latapy: Computing communities in large networks using random walks, U{http://arxiv.org/abs/physics/0512106}. """ merges, qs = GraphBase.community_walktrap(self, weights, steps) qs.reverse() if qs: optimal_count = qs.index(max(qs))+1 else: optimal_count = 1 return VertexDendrogram(self, merges, optimal_count, modularity_params=dict(weights=weights)) def k_core(self, *args): """Returns some k-cores of the graph. The method accepts an arbitrary number of arguments representing the desired indices of the M{k}-cores to be returned. The arguments can also be lists or tuples. The result is a single L{Graph} object if an only integer argument was given, otherwise the result is a list of L{Graph} objects representing the desired k-cores in the order the arguments were specified. If no argument is given, returns all M{k}-cores in increasing order of M{k}. """ if len(args) == 0: indices = xrange(self.vcount()) return_single = False else: return_single = True indices = [] for arg in args: try: indices.extend(arg) except: indices.append(arg) if len(indices)>1 or hasattr(args[0], "__iter__"): return_single = False corenesses = self.coreness() result = [] vidxs = xrange(self.vcount()) for idx in indices: core_idxs = [vidx for vidx in vidxs if corenesses[vidx] >= idx] result.append(self.subgraph(core_idxs)) if return_single: return result[0] return result def community_leiden(self, objective_function="CPM", weights=None, resolution_parameter=1.0, beta=0.01, initial_membership=None, n_iterations=2, node_weights=None): """community_leiden(objective_function=CPM, weights=None, resolution_parameter=1.0, beta=0.01, initial_membership=None, n_iterations=2, node_weights=None) Finds the community structure of the graph using the Leiden algorithm of Traag, van Eck & Waltman. @keyword objective_function: whether to use the Constant Potts Model (CPM) or modularity. Must be either C{"CPM"} or C{"modularity"}. @keyword weights: edge weights to be used. Can be a sequence or iterable or even an edge attribute name. @keyword resolution_parameter: the resolution parameter to use. Higher resolutions lead to more smaller communities, while lower resolutions lead to fewer larger communities. @keyword beta: parameter affecting the randomness in the Leiden algorithm. This affects only the refinement step of the algorithm. @keyword initial_membership: if provided, the Leiden algorithm will try to improve this provided membership. If no argument is provided, the aglorithm simply starts from the singleton partition. @keyword n_iterations: the number of iterations to iterate the Leiden algorithm. Each iteration may improve the partition further. @keyword node_weights: the node weights used in the Leiden algorithm. If this is not provided, it will be automatically determined on the basis of whether you want to use CPM or modularity. If you do provide this, please make sure that you understand what you are doing. @return: an appropriate L{VertexClustering} object. @newfield ref: Reference @ref: Traag, V. A., Waltman, L., & van Eck, N. J. (2019). From Louvain to Leiden: guaranteeing well-connected communities. Scientific reports, 9(1), 5233. doi: 10.1038/s41598-019-41695-z """ if objective_function.lower() not in ("cpm", "modularity"): raise ValueError("objective_function must be \"CPM\" or \"modularity\".") membership = GraphBase.community_leiden(self, edge_weights=weights, node_weights=node_weights, resolution_parameter=resolution_parameter, normalize_resolution=(objective_function == "modularity"), beta=beta, initial_membership=initial_membership, n_iterations=n_iterations) if weights is not None: modularity_params=dict(weights=weights) else: modularity_params={} return VertexClustering(self, membership, modularity_params=modularity_params) def layout(self, layout=None, *args, **kwds): """Returns the layout of the graph according to a layout algorithm. Parameters and keyword arguments not specified here are passed to the layout algorithm directly. See the documentation of the layout algorithms for the explanation of these parameters. Registered layout names understood by this method are: - C{auto}, C{automatic}: automatic layout (see L{Graph.layout_auto}) - C{bipartite}: bipartite layout (see L{Graph.layout_bipartite}) - C{circle}, C{circular}: circular layout (see L{Graph.layout_circle}) - C{dh}, C{davidson_harel}: Davidson-Harel layout (see L{Graph.layout_davidson_harel}) - C{drl}: DrL layout for large graphs (see L{Graph.layout_drl}) - C{drl_3d}: 3D DrL layout for large graphs (see L{Graph.layout_drl}) - C{fr}, C{fruchterman_reingold}: Fruchterman-Reingold layout (see L{Graph.layout_fruchterman_reingold}). - C{fr_3d}, C{fr3d}, C{fruchterman_reingold_3d}: 3D Fruchterman- Reingold layout (see L{Graph.layout_fruchterman_reingold}). - C{grid}: regular grid layout in 2D (see L{Graph.layout_grid}) - C{grid_3d}: regular grid layout in 3D (see L{Graph.layout_grid_3d}) - C{graphopt}: the graphopt algorithm (see L{Graph.layout_graphopt}) - C{kk}, C{kamada_kawai}: Kamada-Kawai layout (see L{Graph.layout_kamada_kawai}) - C{kk_3d}, C{kk3d}, C{kamada_kawai_3d}: 3D Kamada-Kawai layout (see L{Graph.layout_kamada_kawai}) - C{lgl}, C{large}, C{large_graph}: Large Graph Layout (see L{Graph.layout_lgl}) - C{mds}: multidimensional scaling layout (see L{Graph.layout_mds}) - C{random}: random layout (see L{Graph.layout_random}) - C{random_3d}: random 3D layout (see L{Graph.layout_random}) - C{rt}, C{tree}, C{reingold_tilford}: Reingold-Tilford tree layout (see L{Graph.layout_reingold_tilford}) - C{rt_circular}, C{reingold_tilford_circular}: circular Reingold-Tilford tree layout (see L{Graph.layout_reingold_tilford_circular}) - C{sphere}, C{spherical}, C{circle_3d}, C{circular_3d}: spherical layout (see L{Graph.layout_circle}) - C{star}: star layout (see L{Graph.layout_star}) - C{sugiyama}: Sugiyama layout (see L{Graph.layout_sugiyama}) @param layout: the layout to use. This can be one of the registered layout names or a callable which returns either a L{Layout} object or a list of lists containing the coordinates. If C{None}, uses the value of the C{plotting.layout} configuration key. @return: a L{Layout} object. """ if layout is None: layout = config["plotting.layout"] if hasattr(layout, "__call__"): method = layout else: layout = layout.lower() if layout[-3:] == "_3d": kwds["dim"] = 3 layout = layout[:-3] elif layout[-2:] == "3d": kwds["dim"] = 3 layout = layout[:-2] method = getattr(self.__class__, self._layout_mapping[layout]) if not hasattr(method, "__call__"): raise ValueError("layout method must be callable") l = method(self, *args, **kwds) if not isinstance(l, Layout): l = Layout(l) return l def layout_auto(self, *args, **kwds): """Chooses and runs a suitable layout function based on simple topological properties of the graph. This function tries to choose an appropriate layout function for the graph using the following rules: 1. If the graph has an attribute called C{layout}, it will be used. It may either be a L{Layout} instance, a list of coordinate pairs, the name of a layout function, or a callable function which generates the layout when called with the graph as a parameter. 2. Otherwise, if the graph has vertex attributes called C{x} and C{y}, these will be used as coordinates in the layout. When a 3D layout is requested (by setting C{dim} to 3), a vertex attribute named C{z} will also be needed. 3. Otherwise, if the graph is connected and has at most 100 vertices, the Kamada-Kawai layout will be used (see L{Graph.layout_kamada_kawai()}). 4. Otherwise, if the graph has at most 1000 vertices, the Fruchterman-Reingold layout will be used (see L{Graph.layout_fruchterman_reingold()}). 5. If everything else above failed, the DrL layout algorithm will be used (see L{Graph.layout_drl()}). All the arguments of this function except C{dim} are passed on to the chosen layout function (in case we have to call some layout function). @keyword dim: specifies whether we would like to obtain a 2D or a 3D layout. @return: a L{Layout} object. """ if "layout" in self.attributes(): layout = self["layout"] if isinstance(layout, Layout): # Layouts are used intact return layout if isinstance(layout, (list, tuple)): # Lists/tuples are converted to layouts return Layout(layout) if hasattr(layout, "__call__"): # Callables are called return Layout(layout(*args, **kwds)) # Try Graph.layout() return self.layout(layout, *args, **kwds) dim = kwds.get("dim", 2) vattrs = self.vertex_attributes() if "x" in vattrs and "y" in vattrs: if dim == 3 and "z" in vattrs: return Layout(zip(self.vs["x"], self.vs["y"], self.vs["z"])) else: return Layout(zip(self.vs["x"], self.vs["y"])) if self.vcount() <= 100 and self.is_connected(): algo = "kk" elif self.vcount() <= 1000: algo = "fr" else: algo = "drl" return self.layout(algo, *args, **kwds) def layout_grid_fruchterman_reingold(self, *args, **kwds): """layout_grid_fruchterman_reingold(*args, **kwds) Compatibility alias to the Fruchterman-Reingold layout with the grid option turned on. @see: Graph.layout_fruchterman_reingold() """ deprecated("Graph.layout_grid_fruchterman_reingold() is deprecated since "\ "igraph 0.8, please use Graph.layout_fruchterman_reingold(grid=True) instead") kwds["grid"] = True return self.layout_fruchterman_reingold(*args, **kwds) def layout_sugiyama(self, layers=None, weights=None, hgap=1, vgap=1, maxiter=100, return_extended_graph=False): """layout_sugiyama(layers=None, weights=None, hgap=1, vgap=1, maxiter=100, return_extended_graph=False) Places the vertices using a layered Sugiyama layout. This is a layered layout that is most suitable for directed acyclic graphs, although it works on undirected or cyclic graphs as well. Each vertex is assigned to a layer and each layer is placed on a horizontal line. Vertices within the same layer are then permuted using the barycenter heuristic that tries to minimize edge crossings. Dummy vertices will be added on edges that span more than one layer. The returned layout therefore contains more rows than the number of nodes in the original graph; the extra rows correspond to the dummy vertices. @param layers: a vector specifying a non-negative integer layer index for each vertex, or the name of a numeric vertex attribute that contains the layer indices. If C{None}, a layering will be determined automatically. For undirected graphs, a spanning tree will be extracted and vertices will be assigned to layers using a breadth first search from the node with the largest degree. For directed graphs, cycles are broken by reversing the direction of edges in an approximate feedback arc set using the heuristic of Eades, Lin and Smyth, and then using longest path layering to place the vertices in layers. @param weights: edge weights to be used. Can be a sequence or iterable or even an edge attribute name. @param hgap: minimum horizontal gap between vertices in the same layer. @param vgap: vertical gap between layers. The layer index will be multiplied by I{vgap} to obtain the Y coordinate. @param maxiter: maximum number of iterations to take in the crossing reduction step. Increase this if you feel that you are getting too many edge crossings. @param return_extended_graph: specifies that the extended graph with the added dummy vertices should also be returned. When this is C{True}, the result will be a tuple containing the layout and the extended graph. The first |V| nodes of the extended graph will correspond to the nodes of the original graph, the remaining ones are dummy nodes. Plotting the extended graph with the returned layout and hidden dummy nodes will produce a layout that is similar to the original graph, but with the added edge bends. The extended graph also contains an edge attribute called C{_original_eid} which specifies the ID of the edge in the original graph from which the edge of the extended graph was created. @return: the calculated layout, which may (and usually will) have more rows than the number of vertices; the remaining rows correspond to the dummy nodes introduced in the layering step. When C{return_extended_graph} is C{True}, it will also contain the extended graph. @newfield ref: Reference @ref: K Sugiyama, S Tagawa, M Toda: Methods for visual understanding of hierarchical system structures. IEEE Systems, Man and Cybernetics\ 11(2):109-125, 1981. @ref: P Eades, X Lin and WF Smyth: A fast effective heuristic for the feedback arc set problem. Information Processing Letters 47:319-323, 1993. """ if not return_extended_graph: return Layout(GraphBase._layout_sugiyama(self, layers, weights, hgap, vgap, maxiter, return_extended_graph)) layout, extd_graph, extd_to_orig_eids = \ GraphBase._layout_sugiyama(self, layers, weights, hgap, vgap, maxiter, return_extended_graph) extd_graph.es["_original_eid"] = extd_to_orig_eids return Layout(layout), extd_graph def maximum_bipartite_matching(self, types="type", weights=None, eps=None): """Finds a maximum matching in a bipartite graph. A maximum matching is a set of edges such that each vertex is incident on at most one matched edge and the number (or weight) of such edges in the set is as large as possible. @param types: vertex types in a list or the name of a vertex attribute holding vertex types. Types should be denoted by zeros and ones (or C{False} and C{True}) for the two sides of the bipartite graph. If omitted, it defaults to C{type}, which is the default vertex type attribute for bipartite graphs. @param weights: edge weights to be used. Can be a sequence or iterable or even an edge attribute name. @param eps: a small real number used in equality tests in the weighted bipartite matching algorithm. Two real numbers are considered equal in the algorithm if their difference is smaller than this value. This is required to avoid the accumulation of numerical errors. If you pass C{None} here, igraph will try to determine an appropriate value automatically. @return: an instance of L{Matching}.""" if eps is None: eps = -1 matches = GraphBase._maximum_bipartite_matching(self, types, weights, eps) return Matching(self, matches, types=types) ############################################# # Auxiliary I/O functions def write_adjacency(self, f, sep=" ", eol="\n", *args, **kwds): """Writes the adjacency matrix of the graph to the given file All the remaining arguments not mentioned here are passed intact to L{Graph.get_adjacency}. @param f: the name of the file to be written. @param sep: the string that separates the matrix elements in a row @param eol: the string that separates the rows of the matrix. Please note that igraph is able to read back the written adjacency matrix if and only if this is a single newline character """ if isinstance(f, basestring): f = open(f, "w") matrix = self.get_adjacency(*args, **kwds) for row in matrix: f.write(sep.join(map(str, row))) f.write(eol) f.close() @classmethod def Read_Adjacency(klass, f, sep=None, comment_char = "#", attribute=None, *args, **kwds): """Constructs a graph based on an adjacency matrix from the given file Additional positional and keyword arguments not mentioned here are passed intact to L{Graph.Adjacency}. @param f: the name of the file to be read or a file object @param sep: the string that separates the matrix elements in a row. C{None} means an arbitrary sequence of whitespace characters. @param comment_char: lines starting with this string are treated as comments. @param attribute: an edge attribute name where the edge weights are stored in the case of a weighted adjacency matrix. If C{None}, no weights are stored, values larger than 1 are considered as edge multiplicities. @return: the created graph""" if isinstance(f, basestring): f = open(f) matrix, ri, weights = [], 0, {} for line in f: line = line.strip() if len(line) == 0: continue if line.startswith(comment_char): continue row = [float(x) for x in line.split(sep)] matrix.append(row) ri += 1 f.close() if attribute is None: graph=klass.Adjacency(matrix, *args, **kwds) else: kwds["attr"] = attribute graph=klass.Weighted_Adjacency(matrix, *args, **kwds) return graph def write_dimacs(self, f, source=None, target=None, capacity="capacity"): """Writes the graph in DIMACS format to the given file. @param f: the name of the file to be written or a Python file handle. @param source: the source vertex ID. If C{None}, igraph will try to infer it from the C{source} graph attribute. @param target: the target vertex ID. If C{None}, igraph will try to infer it from the C{target} graph attribute. @param capacity: the capacities of the edges in a list or the name of an edge attribute that holds the capacities. If there is no such edge attribute, every edge will have a capacity of 1. """ if source is None: try: source = self["source"] except KeyError: raise ValueError( "source vertex must be provided in the 'source' graph " "attribute or in the 'source' argument of write_dimacs()") if target is None: try: target = self["target"] except KeyError: raise ValueError( "target vertex must be provided in the 'target' graph " "attribute or in the 'target' argument of write_dimacs()") if isinstance(capacity, basestring) and \ capacity not in self.edge_attributes(): warn("'%s' edge attribute does not exist" % capacity) capacity = [1] * self.ecount() return GraphBase.write_dimacs(self, f, source, target, capacity) def write_graphmlz(self, f, compresslevel=9): """Writes the graph to a zipped GraphML file. The library uses the gzip compression algorithm, so the resulting file can be unzipped with regular gzip uncompression (like C{gunzip} or C{zcat} from Unix command line) or the Python C{gzip} module. Uses a temporary file to store intermediate GraphML data, so make sure you have enough free space to store the unzipped GraphML file as well. @param f: the name of the file to be written. @param compresslevel: the level of compression. 1 is fastest and produces the least compression, and 9 is slowest and produces the most compression.""" from igraph.utils import named_temporary_file with named_temporary_file() as tmpfile: self.write_graphml(tmpfile) outf = gzip.GzipFile(f, "wb", compresslevel) copyfileobj(open(tmpfile, "rb"), outf) outf.close() @classmethod def Read_DIMACS(cls, f, directed=False): """Read_DIMACS(f, directed=False) Reads a graph from a file conforming to the DIMACS minimum-cost flow file format. For the exact definition of the format, see U{http://lpsolve.sourceforge.net/5.5/DIMACS.htm}. Restrictions compared to the official description of the format are as follows: - igraph's DIMACS reader requires only three fields in an arc definition, describing the edge's source and target node and its capacity. - Source vertices are identified by 's' in the FLOW field, target vertices are identified by 't'. - Node indices start from 1. Only a single source and target node is allowed. @param f: the name of the file or a Python file handle @param directed: whether the generated graph should be directed. @return: the generated graph. The indices of the source and target vertices are attached as graph attributes C{source} and C{target}, the edge capacities are stored in the C{capacity} edge attribute. """ graph, source, target, cap = super(Graph, cls).Read_DIMACS(f, directed) graph.es["capacity"] = cap graph["source"] = source graph["target"] = target return graph @classmethod def Read_GraphMLz(cls, f, *params, **kwds): """Read_GraphMLz(f, directed=True, index=0) Reads a graph from a zipped GraphML file. @param f: the name of the file @param index: if the GraphML file contains multiple graphs, specified the one that should be loaded. Graph indices start from zero, so if you want to load the first graph, specify 0 here. @return: the loaded graph object""" from igraph.utils import named_temporary_file with named_temporary_file() as tmpfile: outf = open(tmpfile, "wb") copyfileobj(gzip.GzipFile(f, "rb"), outf) outf.close() return cls.Read_GraphML(tmpfile) def write_pickle(self, fname=None, version=-1): """Saves the graph in Python pickled format @param fname: the name of the file or a stream to save to. If C{None}, saves the graph to a string and returns the string. @param version: pickle protocol version to be used. If -1, uses the highest protocol available @return: C{None} if the graph was saved successfully to the given file, or a string if C{fname} was C{None}. """ import cPickle as pickle if fname is None: return pickle.dumps(self, version) if not hasattr(fname, "write"): file_was_opened = True fname = open(fname, 'wb') else: file_was_opened=False result=pickle.dump(self, fname, version) if file_was_opened: fname.close() return result def write_picklez(self, fname=None, version=-1): """Saves the graph in Python pickled format, compressed with gzip. Saving in this format is a bit slower than saving in a Python pickle without compression, but the final file takes up much less space on the hard drive. @param fname: the name of the file or a stream to save to. @param version: pickle protocol version to be used. If -1, uses the highest protocol available @return: C{None} if the graph was saved successfully to the given file. """ import cPickle as pickle if not hasattr(fname, "write"): file_was_opened = True fname = gzip.open(fname, "wb") elif not isinstance(fname, gzip.GzipFile): file_was_opened = True fname = gzip.GzipFile(mode="wb", fileobj=fname) else: file_Was_opened = False result = pickle.dump(self, fname, version) if file_was_opened: fname.close() return result @classmethod def Read_Pickle(klass, fname=None): """Reads a graph from Python pickled format @param fname: the name of the file, a stream to read from, or a string containing the pickled data. @return: the created graph object. """ import cPickle as pickle if hasattr(fname, "read"): # Probably a file or a file-like object result = pickle.load(fname) else: fp = None try: fp = open(fname, "rb") except UnicodeDecodeError: try: # We are on Python 3.6 or above and we are passing a pickled # stream that cannot be decoded as Unicode. Try unpickling # directly. result = pickle.loads(fname) except TypeError: raise IOError('Cannot load file. If fname is a file name, that filename may be incorrect.') except IOError: try: # No file with the given name, try unpickling directly. result = pickle.loads(fname) except TypeError: raise IOError('Cannot load file. If fname is a file name, that filename may be incorrect.') if fp is not None: result = pickle.load(fp) fp.close() return result @classmethod def Read_Picklez(klass, fname, *args, **kwds): """Reads a graph from compressed Python pickled format, uncompressing it on-the-fly. @param fname: the name of the file or a stream to read from. @return: the created graph object. """ import cPickle as pickle if hasattr(fname, "read"): # Probably a file or a file-like object if isinstance(fname, gzip.GzipFile): result = pickle.load(fname) else: result = pickle.load(gzip.GzipFile(mode="rb", fileobj=fname)) else: result = pickle.load(gzip.open(fname, "rb")) return result @classmethod def Read_Picklez(klass, fname, *args, **kwds): """Reads a graph from compressed Python pickled format, uncompressing it on-the-fly. @param fname: the name of the file or a stream to read from. @return: the created graph object. """ import cPickle as pickle if hasattr(fname, "read"): # Probably a file or a file-like object if isinstance(fname, gzip.GzipFile): result = pickle.load(fname) else: result = pickle.load(gzip.GzipFile(mode="rb", fileobj=fname)) else: result = pickle.load(gzip.open(fname, "rb")) if not isinstance(result, klass): raise TypeError("unpickled object is not a %s" % klass.__name__) return result # pylint: disable-msg=C0301,C0323 # C0301: line too long. # C0323: operator not followed by a space - well, print >>f looks OK def write_svg(self, fname, layout="auto", width=None, height=None, \ labels="label", colors="color", shapes="shape", \ vertex_size=10, edge_colors="color", \ edge_stroke_widths="width", \ font_size=16, *args, **kwds): """Saves the graph as an SVG (Scalable Vector Graphics) file The file will be Inkscape (http://inkscape.org) compatible. In Inkscape, as nodes are rearranged, the edges auto-update. @param fname: the name of the file or a Python file handle @param layout: the layout of the graph. Can be either an explicitly specified layout (using a list of coordinate pairs) or the name of a layout algorithm (which should refer to a method in the L{Graph} object, but without the C{layout_} prefix. @param width: the preferred width in pixels (default: 400) @param height: the preferred height in pixels (default: 400) @param labels: the vertex labels. Either it is the name of a vertex attribute to use, or a list explicitly specifying the labels. It can also be C{None}. @param colors: the vertex colors. Either it is the name of a vertex attribute to use, or a list explicitly specifying the colors. A color can be anything acceptable in an SVG file. @param shapes: the vertex shapes. Either it is the name of a vertex attribute to use, or a list explicitly specifying the shapes as integers. Shape 0 means hidden (nothing is drawn), shape 1 is a circle, shape 2 is a rectangle and shape 3 is a rectangle that automatically sizes to the inner text. @param vertex_size: vertex size in pixels @param edge_colors: the edge colors. Either it is the name of an edge attribute to use, or a list explicitly specifying the colors. A color can be anything acceptable in an SVG file. @param edge_stroke_widths: the stroke widths of the edges. Either it is the name of an edge attribute to use, or a list explicitly specifying the stroke widths. The stroke width can be anything acceptable in an SVG file. @param font_size: font size. If it is a string, it is written into the SVG file as-is (so you can specify anything which is valid as the value of the C{font-size} style). If it is a number, it is interpreted as pixel size and converted to the proper attribute value accordingly. """ if width is None and height is None: width = 400 height = 400 elif width is None: width = height elif height is None: height = width if width <= 0 or height <= 0: raise ValueError("width and height must be positive") if isinstance(layout, str): layout = self.layout(layout, *args, **kwds) if isinstance(labels, str): try: labels = self.vs.get_attribute_values(labels) except KeyError: labels = [x+1 for x in xrange(self.vcount())] elif labels is None: labels = [""] * self.vcount() if isinstance(colors, str): try: colors = self.vs.get_attribute_values(colors) except KeyError: colors = ["red"] * self.vcount() if isinstance(shapes, str): try: shapes = self.vs.get_attribute_values(shapes) except KeyError: shapes = [1] * self.vcount() if isinstance(edge_colors, str): try: edge_colors = self.es.get_attribute_values(edge_colors) except KeyError: edge_colors = ["black"] * self.ecount() if isinstance(edge_stroke_widths, str): try: edge_stroke_widths = self.es.get_attribute_values(edge_stroke_widths) except KeyError: edge_stroke_widths = [2] * self.ecount() if not isinstance(font_size, str): font_size = "%spx" % str(font_size) else: if ";" in font_size: raise ValueError("font size can't contain a semicolon") vcount = self.vcount() labels.extend(str(i+1) for i in xrange(len(labels), vcount)) colors.extend(["red"] * (vcount - len(colors))) if isinstance(fname, basestring): f = open(fname, "w") our_file = True else: f = fname our_file = False bbox = BoundingBox(layout.bounding_box()) sizes = [width-2*vertex_size, height-2*vertex_size] w, h = bbox.width, bbox.height ratios = [] if w == 0: ratios.append(1.0) else: ratios.append(sizes[0] / w) if h == 0: ratios.append(1.0) else: ratios.append(sizes[1] / h) layout = [[(row[0] - bbox.left) * ratios[0] + vertex_size, \ (row[1] - bbox.top) * ratios[1] + vertex_size] \ for row in layout] directed = self.is_directed() print >> f, '' print >> f, '' print >> f print >> f, '> f, 'width="{0}px" height="{1}px">'.format(width, height), edge_color_dict = {} print >> f, '' for e_col in set(edge_colors): if e_col == "#000000": marker_index = "" else: marker_index = str(len(edge_color_dict)) # Print an arrow marker for each possible line color # This is a copy of Inkscape's standard Arrow 2 marker print >> f, '> f, ' inkscape:stockid="Arrow2Lend{0}"'.format(marker_index) print >> f, ' orient="auto"' print >> f, ' refY="0.0"' print >> f, ' refX="0.0"' print >> f, ' id="Arrow2Lend{0}"'.format(marker_index) print >> f, ' style="overflow:visible;">' print >> f, ' > f, ' id="pathArrow{0}"'.format(marker_index) print >> f, ' style="font-size:12.0;fill-rule:evenodd;stroke-width:0.62500000;stroke-linejoin:round;fill:{0}"'.format(e_col) print >> f, ' d="M 8.7185878,4.0337352 L -2.2072895,0.016013256 L 8.7185884,-4.0017078 C 6.9730900,-1.6296469 6.9831476,1.6157441 8.7185878,4.0337352 z "' print >> f, ' transform="scale(1.1) rotate(180) translate(1,0)" />' print >> f, '' edge_color_dict[e_col] = "Arrow2Lend{0}".format(marker_index) print >> f, '' print >> f, '' for eidx, edge in enumerate(self.es): vidxs = edge.tuple x1 = layout[vidxs[0]][0] y1 = layout[vidxs[0]][1] x2 = layout[vidxs[1]][0] y2 = layout[vidxs[1]][1] angle = math.atan2(y2 - y1, x2 - x1) x2 = x2 - vertex_size * math.cos(angle) y2 = y2 - vertex_size * math.sin(angle) print >> f, '> f, ' style="fill:none;stroke:{0};stroke-width:{2};stroke-linecap:butt;stroke-linejoin:miter;stroke-miterlimit:4;stroke-opacity:1;stroke-dasharray:none{1}"'\ .format(edge_colors[eidx], ";marker-end:url(#{0})".\ format(edge_color_dict[edge_colors[eidx]]) \ if directed else "", edge_stroke_widths[eidx]) print >> f, ' d="M {0},{1} {2},{3}"'.format(x1, y1, x2, y2) print >> f, ' id="path{0}"'.format(eidx) print >> f, ' inkscape:connector-type="polyline"' print >> f, ' inkscape:connector-curvature="0"' print >> f, ' inkscape:connection-start="#g{0}"'.format(edge.source) print >> f, ' inkscape:connection-start-point="d4"' print >> f, ' inkscape:connection-end="#g{0}"'.format(edge.target) print >> f, ' inkscape:connection-end-point="d4" />' print >> f, " " print >> f print >> f, ' ' print >> f, ' ' if any(x == 3 for x in shapes): # Only import tkFont if we really need it. Unfortunately, this will # flash up an unneccesary Tk window in some cases import tkFont import Tkinter as tk # This allows us to dynamically size the width of the nodes. # Unfortunately this works only with font sizes specified in pixels. if font_size.endswith("px"): font_size_in_pixels = int(font_size[:-2]) else: try: font_size_in_pixels = int(font_size) except: raise ValueError("font sizes must be specified in pixels " "when any of the nodes has shape=3 (i.e. " "node size determined by text size)") tk_window = tk.Tk() font = tkFont.Font(root=tk_window, font=("Sans", font_size_in_pixels, tkFont.NORMAL)) else: tk_window = None for vidx in range(self.vcount()): print >> f, ' '.\ format(vidx, layout[vidx][0], layout[vidx][1]) if shapes[vidx] == 1: # Undocumented feature: can handle two colors but only for circles c = str(colors[vidx]) if " " in c: c = c.split(" ") vs = str(vertex_size) print >> f, ' '.format(vs, c[0]) print >> f, ' '.format(vs, c[1]) print >> f, ' '\ .format(vs) else: print >> f, ' '.\ format(str(vertex_size), str(colors[vidx])) elif shapes[vidx] == 2: print >> f, ' '.\ format(vertex_size, vertex_size * 2, vidx, colors[vidx]) elif shapes[vidx] == 3: (vertex_width, vertex_height) = (font.measure(str(labels[vidx])) + 2, font.metrics("linespace") + 2) print >> f, ' '.\ format(vertex_width / 2., vertex_height / 2., vertex_width, vertex_height, vidx, colors[vidx]) print >> f, ' '.format(vertex_size / 2.,vidx, font_size) print >> f, '{2}'.format(vertex_size / 2.,vidx, str(labels[vidx])) print >> f, ' ' print >> f, '' print >> f print >> f, '' if our_file: f.close() if tk_window: tk_window.destroy() @classmethod def _identify_format(klass, filename): """_identify_format(filename) Tries to identify the format of the graph stored in the file with the given filename. It identifies most file formats based on the extension of the file (and not on syntactic evaluation). The only exception is the adjacency matrix format and the edge list format: the first few lines of the file are evaluated to decide between the two. @note: Internal function, should not be called directly. @param filename: the name of the file or a file object whose C{name} attribute is set. @return: the format of the file as a string. """ import os.path if hasattr(filename, "name") and hasattr(filename, "read"): # It is most likely a file try: filename=filename.name except: return None root, ext = os.path.splitext(filename) ext = ext.lower() if ext == ".gz": _, ext2 = os.path.splitext(root) ext2 = ext2.lower() if ext2 == ".pickle": return "picklez" elif ext2 == ".graphml": return "graphmlz" if ext in [".graphml", ".graphmlz", ".lgl", ".ncol", ".pajek", ".gml", ".dimacs", ".edgelist", ".edges", ".edge", ".net", ".pickle", ".picklez", ".dot", ".gw", ".lgr", ".dl"]: return ext[1:] if ext == ".txt" or ext == ".dat": # Most probably an adjacency matrix or an edge list f = open(filename, "r") line = f.readline() if line is None: return "edges" parts = line.strip().split() if len(parts) == 2: line = f.readline() if line is None: return "edges" parts = line.strip().split() if len(parts) == 2: line = f.readline() if line is None: # This is a 2x2 matrix, it can be a matrix or an edge # list as well and we cannot decide return None else: parts = line.strip().split() if len(parts) == 0: return None return "edges" else: # Not a matrix return None else: return "adjacency" @classmethod def Read(klass, f, format=None, *args, **kwds): """Unified reading function for graphs. This method tries to identify the format of the graph given in the first parameter and calls the corresponding reader method. The remaining arguments are passed to the reader method without any changes. @param f: the file containing the graph to be loaded @param format: the format of the file (if known in advance). C{None} means auto-detection. Possible values are: C{"ncol"} (NCOL format), C{"lgl"} (LGL format), C{"graphdb"} (GraphDB format), C{"graphml"}, C{"graphmlz"} (GraphML and gzipped GraphML format), C{"gml"} (GML format), C{"net"}, C{"pajek"} (Pajek format), C{"dimacs"} (DIMACS format), C{"edgelist"}, C{"edges"} or C{"edge"} (edge list), C{"adjacency"} (adjacency matrix), C{"dl"} (DL format used by UCINET), C{"pickle"} (Python pickled format), C{"picklez"} (gzipped Python pickled format) @raises IOError: if the file format can't be identified and none was given. """ if format is None: format = klass._identify_format(f) try: reader = klass._format_mapping[format][0] except (KeyError, IndexError): raise IOError("unknown file format: %s" % str(format)) if reader is None: raise IOError("no reader method for file format: %s" % str(format)) reader = getattr(klass, reader) return reader(f, *args, **kwds) Load = Read def write(self, f, format=None, *args, **kwds): """Unified writing function for graphs. This method tries to identify the format of the graph given in the first parameter (based on extension) and calls the corresponding writer method. The remaining arguments are passed to the writer method without any changes. @param f: the file containing the graph to be saved @param format: the format of the file (if one wants to override the format determined from the filename extension, or the filename itself is a stream). C{None} means auto-detection. Possible values are: - C{"adjacency"}: adjacency matrix format - C{"dimacs"}: DIMACS format - C{"dot"}, C{"graphviz"}: GraphViz DOT format - C{"edgelist"}, C{"edges"} or C{"edge"}: numeric edge list format - C{"gml"}: GML format - C{"graphml"} and C{"graphmlz"}: standard and gzipped GraphML format - C{"gw"}, C{"leda"}, C{"lgr"}: LEDA native format - C{"lgl"}: LGL format - C{"ncol"}: NCOL format - C{"net"}, C{"pajek"}: Pajek format - C{"pickle"}, C{"picklez"}: standard and gzipped Python pickled format - C{"svg"}: SVG format @raises IOError: if the file format can't be identified and none was given. """ if format is None: format = self._identify_format(f) try: writer = self._format_mapping[format][1] except (KeyError, IndexError): raise IOError("unknown file format: %s" % str(format)) if writer is None: raise IOError("no writer method for file format: %s" % str(format)) writer = getattr(self, writer) return writer(f, *args, **kwds) save = write ##################################################### # Constructor for dict-like representation of graphs @classmethod def DictList(klass, vertices, edges, directed=False, \ vertex_name_attr="name", edge_foreign_keys=("source", "target"), \ iterative=False): """Constructs a graph from a list-of-dictionaries representation. This representation assumes that vertices and edges are encoded in two lists, each list containing a Python dict for each vertex and each edge, respectively. A distinguished element of the vertex dicts contain a vertex ID which is used in the edge dicts to refer to source and target vertices. All the remaining elements of the dict are considered vertex and edge attributes. Note that the implementation does not assume that the objects passed to this method are indeed lists of dicts, but they should be iterable and they should yield objects that behave as dicts. So, for instance, a database query result is likely to be fit as long as it's iterable and yields dict-like objects with every iteration. @param vertices: the data source for the vertices or C{None} if there are no special attributes assigned to vertices and we should simply use the edge list of dicts to infer vertex names. @param edges: the data source for the edges. @param directed: whether the constructed graph will be directed @param vertex_name_attr: the name of the distinguished key in the dicts in the vertex data source that contains the vertex names. Ignored if C{vertices} is C{None}. @param edge_foreign_keys: the name of the attributes in the dicts in the edge data source that contain the source and target vertex names. @param iterative: whether to add the edges to the graph one by one, iteratively, or to build a large edge list first and use that to construct the graph. The latter approach is faster but it may not be suitable if your dataset is large. The default is to add the edges in a batch from an edge list. @return: the graph that was constructed """ def create_list_from_indices(l, n): result = [None] * n for i, v in l: result[i] = v return result # Construct the vertices vertex_attrs, n = {}, 0 if vertices: for idx, vertex_data in enumerate(vertices): for k, v in vertex_data.iteritems(): try: vertex_attrs[k].append((idx, v)) except KeyError: vertex_attrs[k] = [(idx, v)] n += 1 for k, v in vertex_attrs.iteritems(): vertex_attrs[k] = create_list_from_indices(v, n) else: vertex_attrs[vertex_name_attr] = [] vertex_names = vertex_attrs[vertex_name_attr] # Check for duplicates in vertex_names if len(vertex_names) != len(set(vertex_names)): raise ValueError("vertex names are not unique") # Create a reverse mapping from vertex names to indices vertex_name_map = UniqueIdGenerator(initial = vertex_names) # Construct the edges efk_src, efk_dest = edge_foreign_keys if iterative: g = klass(n, [], directed, {}, vertex_attrs) for idx, edge_data in enumerate(edges): src_name, dst_name = edge_data[efk_src], edge_data[efk_dest] v1 = vertex_name_map[src_name] if v1 == n: g.add_vertices(1) g.vs[n][vertex_name_attr] = src_name n += 1 v2 = vertex_name_map[dst_name] if v2 == n: g.add_vertices(1) g.vs[n][vertex_name_attr] = dst_name n += 1 g.add_edge(v1, v2) for k, v in edge_data.iteritems(): g.es[idx][k] = v return g else: edge_list, edge_attrs, m = [], {}, 0 for idx, edge_data in enumerate(edges): v1 = vertex_name_map[edge_data[efk_src]] v2 = vertex_name_map[edge_data[efk_dest]] edge_list.append((v1, v2)) for k, v in edge_data.iteritems(): try: edge_attrs[k].append((idx, v)) except KeyError: edge_attrs[k] = [(idx, v)] m += 1 for k, v in edge_attrs.iteritems(): edge_attrs[k] = create_list_from_indices(v, m) # It may have happened that some vertices were added during # the process if len(vertex_name_map) > n: diff = len(vertex_name_map) - n more = [None] * diff for k, v in vertex_attrs.iteritems(): v.extend(more) vertex_attrs[vertex_name_attr] = vertex_name_map.values() n = len(vertex_name_map) # Create the graph return klass(n, edge_list, directed, {}, vertex_attrs, edge_attrs) ##################################################### # Constructor for tuple-like representation of graphs @classmethod def TupleList(klass, edges, directed=False, \ vertex_name_attr="name", edge_attrs=None, weights=False): """Constructs a graph from a list-of-tuples representation. This representation assumes that the edges of the graph are encoded in a list of tuples (or lists). Each item in the list must have at least two elements, which specify the source and the target vertices of the edge. The remaining elements (if any) specify the edge attributes of that edge, where the names of the edge attributes originate from the C{edge_attrs} list. The names of the vertices will be stored in the vertex attribute given by C{vertex_name_attr}. The default parameters of this function are suitable for creating unweighted graphs from lists where each item contains the source vertex and the target vertex. If you have a weighted graph, you can use items where the third item contains the weight of the edge by setting C{edge_attrs} to C{"weight"} or C{["weight"]}. If you have even more edge attributes, add them to the end of each item in the C{edges} list and also specify the corresponding edge attribute names in C{edge_attrs} as a list. @param edges: the data source for the edges. This must be a list where each item is a tuple (or list) containing at least two items: the name of the source and the target vertex. Note that names will be assigned to the C{name} vertex attribute (or another vertex attribute if C{vertex_name_attr} is specified), even if all the vertex names in the list are in fact numbers. @param directed: whether the constructed graph will be directed @param vertex_name_attr: the name of the vertex attribute that will contain the vertex names. @param edge_attrs: the names of the edge attributes that are filled with the extra items in the edge list (starting from index 2, since the first two items are the source and target vertices). C{None} means that only the source and target vertices will be extracted from each item. If you pass a string here, it will be wrapped in a list for convenience. @param weights: alternative way to specify that the graph is weighted. If you set C{weights} to C{true} and C{edge_attrs} is not given, it will be assumed that C{edge_attrs} is C{["weight"]} and igraph will parse the third element from each item into an edge weight. If you set C{weights} to a string, it will be assumed that C{edge_attrs} contains that string only, and igraph will store the edge weights in that attribute. @return: the graph that was constructed """ if edge_attrs is None: if not weights: edge_attrs = () else: if not isinstance(weights, basestring): weights = "weight" edge_attrs = [weights] else: if weights: raise ValueError("`weights` must be False if `edge_attrs` is " "not None") if isinstance(edge_attrs, basestring): edge_attrs = [edge_attrs] # Set up a vertex ID generator idgen = UniqueIdGenerator() # Construct the edges and the edge attributes edge_list = [] edge_attributes = {} for name in edge_attrs: edge_attributes[name] = [] for item in edges: edge_list.append((idgen[item[0]], idgen[item[1]])) for index, name in enumerate(edge_attrs, 2): try: edge_attributes[name].append(item[index]) except IndexError: edge_attributes[name].append(None) # Set up the "name" vertex attribute vertex_attributes = {} vertex_attributes[vertex_name_attr] = idgen.values() n = len(idgen) # Construct the graph return klass(n, edge_list, directed, {}, vertex_attributes, edge_attributes) ################################# # Constructor for graph formulae Formula=classmethod(construct_graph_from_formula) ########################### # Vertex and edge sequence @property def vs(self): """The vertex sequence of the graph""" return VertexSeq(self) @property def es(self): """The edge sequence of the graph""" return EdgeSeq(self) ############################################# # Friendlier interface for bipartite methods @classmethod def Bipartite(klass, types, *args, **kwds): """Bipartite(types, edges, directed=False) Creates a bipartite graph with the given vertex types and edges. This is similar to the default constructor of the graph, the only difference is that it checks whether all the edges go between the two vertex classes and it assigns the type vector to a C{type} attribute afterwards. Examples: >>> g = Graph.Bipartite([0, 1, 0, 1], [(0, 1), (2, 3), (0, 3)]) >>> g.is_bipartite() True >>> g.vs["type"] [False, True, False, True] @param types: the vertex types as a boolean list. Anything that evaluates to C{False} will denote a vertex of the first kind, anything that evaluates to C{True} will denote a vertex of the second kind. @param edges: the edges as a list of tuples. @param directed: whether to create a directed graph. Bipartite networks are usually undirected, so the default is C{False} @return: the graph with a binary vertex attribute named C{"type"} that stores the vertex classes. """ result = klass._Bipartite(types, *args, **kwds) result.vs["type"] = [bool(x) for x in types] return result @classmethod def Full_Bipartite(klass, *args, **kwds): """Full_Bipartite(n1, n2, directed=False, mode=ALL) Generates a full bipartite graph (directed or undirected, with or without loops). >>> g = Graph.Full_Bipartite(2, 3) >>> g.is_bipartite() True >>> g.vs["type"] [False, False, True, True, True] @param n1: the number of vertices of the first kind. @param n2: the number of vertices of the second kind. @param directed: whether tp generate a directed graph. @param mode: if C{OUT}, then all vertices of the first kind are connected to the others; C{IN} specifies the opposite direction, C{ALL} creates mutual edges. Ignored for undirected graphs. @return: the graph with a binary vertex attribute named C{"type"} that stores the vertex classes. """ result, types = klass._Full_Bipartite(*args, **kwds) result.vs["type"] = types return result @classmethod def Random_Bipartite(klass, *args, **kwds): """Random_Bipartite(n1, n2, p=None, m=None, directed=False, neimode=ALL) Generates a random bipartite graph with the given number of vertices and edges (if m is given), or with the given number of vertices and the given connection probability (if p is given). If m is given but p is not, the generated graph will have n1 vertices of type 1, n2 vertices of type 2 and m randomly selected edges between them. If p is given but m is not, the generated graph will have n1 vertices of type 1 and n2 vertices of type 2, and each edge will exist between them with probability p. @param n1: the number of vertices of type 1. @param n2: the number of vertices of type 2. @param p: the probability of edges. If given, C{m} must be missing. @param m: the number of edges. If given, C{p} must be missing. @param directed: whether to generate a directed graph. @param neimode: if the graph is directed, specifies how the edges will be generated. If it is C{"all"}, edges will be generated in both directions (from type 1 to type 2 and vice versa) independently. If it is C{"out"} edges will always point from type 1 to type 2. If it is C{"in"}, edges will always point from type 2 to type 1. This argument is ignored for undirected graphs. """ result, types = klass._Random_Bipartite(*args, **kwds) result.vs["type"] = types return result @classmethod def GRG(klass, n, radius, torus=False): """GRG(n, radius, torus=False, return_coordinates=False) Generates a random geometric graph. The algorithm drops the vertices randomly on the 2D unit square and connects them if they are closer to each other than the given radius. The coordinates of the vertices are stored in the vertex attributes C{x} and C{y}. @param n: The number of vertices in the graph @param radius: The given radius @param torus: This should be C{True} if we want to use a torus instead of a square. """ result, xs, ys = klass._GRG(n, radius, torus) result.vs["x"] = xs result.vs["y"] = ys return result @classmethod def Incidence(klass, *args, **kwds): """Incidence(matrix, directed=False, mode=ALL, multiple=False) Creates a bipartite graph from an incidence matrix. Example: >>> g = Graph.Incidence([[0, 1, 1], [1, 1, 0]]) @param matrix: the incidence matrix. @param directed: whether to create a directed graph. @param mode: defines the direction of edges in the graph. If C{OUT}, then edges go from vertices of the first kind (corresponding to rows of the matrix) to vertices of the second kind (the columns of the matrix). If C{IN}, the opposite direction is used. C{ALL} creates mutual edges. Ignored for undirected graphs. @param multiple: defines what to do with non-zero entries in the matrix. If C{False}, non-zero entries will create an edge no matter what the value is. If C{True}, non-zero entries are rounded up to the nearest integer and this will be the number of multiple edges created. @return: the graph with a binary vertex attribute named C{"type"} that stores the vertex classes. """ result, types = klass._Incidence(*args, **kwds) result.vs["type"] = types return result def bipartite_projection(self, types="type", multiplicity=True, probe1=-1, which="both"): """Projects a bipartite graph into two one-mode graphs. Edge directions are ignored while projecting. Examples: >>> g = Graph.Full_Bipartite(10, 5) >>> g1, g2 = g.bipartite_projection() >>> g1.isomorphic(Graph.Full(10)) True >>> g2.isomorphic(Graph.Full(5)) True @param types: an igraph vector containing the vertex types, or an attribute name. Anything that evalulates to C{False} corresponds to vertices of the first kind, everything else to the second kind. @param multiplicity: if C{True}, then igraph keeps the multiplicity of the edges in the projection in an edge attribute called C{"weight"}. E.g., if there is an A-C-B and an A-D-B triplet in the bipartite graph and there is no other X (apart from X=B and X=D) for which an A-X-B triplet would exist in the bipartite graph, the multiplicity of the A-B edge in the projection will be 2. @param probe1: this argument can be used to specify the order of the projections in the resulting list. If given and non-negative, then it is considered as a vertex ID; the projection containing the vertex will be the first one in the result. @param which: this argument can be used to specify which of the two projections should be returned if only one of them is needed. Passing 0 here means that only the first projection is returned, while 1 means that only the second projection is returned. (Note that we use 0 and 1 because Python indexing is zero-based). C{False} is equivalent to 0 and C{True} is equivalent to 1. Any other value means that both projections will be returned in a tuple. @return: a tuple containing the two projected one-mode graphs if C{which} is not 1 or 2, or the projected one-mode graph specified by the C{which} argument if its value is 0, 1, C{False} or C{True}. """ superclass_meth = super(Graph, self).bipartite_projection if which == False: which = 0 elif which == True: which = 1 if which != 0 and which != 1: which = -1 if multiplicity: if which == 0: g1, w1 = superclass_meth(types, True, probe1, which) g2, w2 = None, None elif which == 1: g1, w1 = None, None g2, w2 = superclass_meth(types, True, probe1, which) else: g1, g2, w1, w2 = superclass_meth(types, True, probe1, which) if g1 is not None: g1.es["weight"] = w1 if g2 is not None: g2.es["weight"] = w2 return g1, g2 else: return g1 else: g2.es["weight"] = w2 return g2 else: return superclass_meth(types, False, probe1, which) def bipartite_projection_size(self, types="type", *args, **kwds): """bipartite_projection(types="type") Calculates the number of vertices and edges in the bipartite projections of this graph according to the specified vertex types. This is useful if you have a bipartite graph and you want to estimate the amount of memory you would need to calculate the projections themselves. @param types: an igraph vector containing the vertex types, or an attribute name. Anything that evalulates to C{False} corresponds to vertices of the first kind, everything else to the second kind. @return: a 4-tuple containing the number of vertices and edges in the first projection, followed by the number of vertices and edges in the second projection. """ return super(Graph, self).bipartite_projection_size(types, \ *args, **kwds) def get_incidence(self, types="type", *args, **kwds): """get_incidence(self, types="type") Returns the incidence matrix of a bipartite graph. The incidence matrix is an M{n} times M{m} matrix, where M{n} and M{m} are the number of vertices in the two vertex classes. @param types: an igraph vector containing the vertex types, or an attribute name. Anything that evalulates to C{False} corresponds to vertices of the first kind, everything else to the second kind. @return: the incidence matrix and two lists in a triplet. The first list defines the mapping between row indices of the matrix and the original vertex IDs. The second list is the same for the column indices. """ return super(Graph, self).get_incidence(types, *args, **kwds) ########################### # ctypes support @property def _as_parameter_(self): return self._raw_pointer() ################### # Custom operators def __iadd__(self, other): """In-place addition (disjoint union). @see: L{__add__} """ if isinstance(other, (int, basestring)): self.add_vertices(other) return self elif isinstance(other, tuple) and len(other) == 2: self.add_edges([other]) return self elif isinstance(other, list): if not other: return self if isinstance(other[0], tuple): self.add_edges(other) return self if isinstance(other[0], basestring): self.add_vertices(other) return self return NotImplemented def __add__(self, other): """Copies the graph and extends the copy depending on the type of the other object given. @param other: if it is an integer, the copy is extended by the given number of vertices. If it is a string, the copy is extended by a single vertex whose C{name} attribute will be equal to the given string. If it is a tuple with two elements, the copy is extended by a single edge. If it is a list of tuples, the copy is extended by multiple edges. If it is a L{Graph}, a disjoint union is performed. """ if isinstance(other, (int, basestring)): g = self.copy() g.add_vertices(other) elif isinstance(other, tuple) and len(other) == 2: g = self.copy() g.add_edges([other]) elif isinstance(other, list): if len(other)>0: if isinstance(other[0], tuple): g = self.copy() g.add_edges(other) elif isinstance(other[0], basestring): g = self.copy() g.add_vertices(other) elif isinstance(other[0], Graph): return self.disjoint_union(other) else: return NotImplemented else: return self.copy() elif isinstance(other, Graph): return self.disjoint_union(other) else: return NotImplemented return g def __and__(self, other): """Graph intersection operator. @param other: the other graph to take the intersection with. @return: the intersected graph. """ if isinstance(other, Graph): return self.intersection(other) else: return NotImplemented def __isub__(self, other): """In-place subtraction (difference). @see: L{__sub__}""" if isinstance(other, int): self.delete_vertices([other]) elif isinstance(other, tuple) and len(other) == 2: self.delete_edges([other]) elif isinstance(other, list): if len(other)>0: if isinstance(other[0], tuple): self.delete_edges(other) elif isinstance(other[0], (int, long, basestring)): self.delete_vertices(other) else: return NotImplemented elif isinstance(other, _igraph.Vertex): self.delete_vertices(other) elif isinstance(other, _igraph.VertexSeq): self.delete_vertices(other) elif isinstance(other, _igraph.Edge): self.delete_edges(other) elif isinstance(other, _igraph.EdgeSeq): self.delete_edges(other) else: return NotImplemented return self def __sub__(self, other): """Removes the given object(s) from the graph @param other: if it is an integer, removes the vertex with the given ID from the graph (note that the remaining vertices will get re-indexed!). If it is a tuple, removes the given edge. If it is a graph, takes the difference of the two graphs. Accepts lists of integers or lists of tuples as well, but they can't be mixed! Also accepts L{Edge} and L{EdgeSeq} objects. """ if isinstance(other, Graph): return self.difference(other) result = self.copy() if isinstance(other, (int, long, basestring)): result.delete_vertices([other]) elif isinstance(other, tuple) and len(other) == 2: result.delete_edges([other]) elif isinstance(other, list): if len(other)>0: if isinstance(other[0], tuple): result.delete_edges(other) elif isinstance(other[0], (int, long, basestring)): result.delete_vertices(other) else: return NotImplemented else: return result elif isinstance(other, _igraph.Vertex): result.delete_vertices(other) elif isinstance(other, _igraph.VertexSeq): result.delete_vertices(other) elif isinstance(other, _igraph.Edge): result.delete_edges(other) elif isinstance(other, _igraph.EdgeSeq): result.delete_edges(other) else: return NotImplemented return result def __mul__(self, other): """Copies exact replicas of the original graph an arbitrary number of times. @param other: if it is an integer, multiplies the graph by creating the given number of identical copies and taking the disjoint union of them. """ if isinstance(other, int): if other == 0: return Graph() elif other == 1: return self elif other > 1: return self.disjoint_union([self]*(other-1)) else: return NotImplemented return NotImplemented def __nonzero__(self): """Returns True if the graph has at least one vertex, False otherwise. """ return self.vcount() > 0 def __or__(self, other): """Graph union operator. @param other: the other graph to take the union with. @return: the union graph. """ if isinstance(other, Graph): return self.union(other) else: return NotImplemented def __coerce__(self, other): """Coercion rules. This method is needed to allow the graph to react to additions with lists, tuples, integers, strings, vertices, edges and so on. """ if isinstance(other, (int, tuple, list, basestring)): return self, other if isinstance(other, _igraph.Vertex): return self, other if isinstance(other, _igraph.VertexSeq): return self, other if isinstance(other, _igraph.Edge): return self, other if isinstance(other, _igraph.EdgeSeq): return self, other return NotImplemented @classmethod def _reconstruct(cls, attrs, *args, **kwds): """Reconstructs a Graph object from Python's pickled format. This method is for internal use only, it should not be called directly.""" result = cls(*args, **kwds) result.__dict__.update(attrs) return result def __reduce__(self): """Support for pickling.""" constructor = self.__class__ gattrs, vattrs, eattrs = {}, {}, {} for attr in self.attributes(): gattrs[attr] = self[attr] for attr in self.vs.attribute_names(): vattrs[attr] = self.vs[attr] for attr in self.es.attribute_names(): eattrs[attr] = self.es[attr] parameters = (self.vcount(), self.get_edgelist(), \ self.is_directed(), gattrs, vattrs, eattrs) return (constructor, parameters, self.__dict__) __iter__ = None # needed for PyPy __hash__ = None # needed for PyPy def __plot__(self, context, bbox, palette, *args, **kwds): """Plots the graph to the given Cairo context in the given bounding box The visual style of vertices and edges can be modified at three places in the following order of precedence (lower indices override higher indices): 1. Keyword arguments of this function (or of L{plot()} which is passed intact to C{Graph.__plot__()}. 2. Vertex or edge attributes, specified later in the list of keyword arguments. 3. igraph-wide plotting defaults (see L{igraph.config.Configuration}) 4. Built-in defaults. E.g., if the C{vertex_size} keyword attribute is not present, but there exists a vertex attribute named C{size}, the sizes of the vertices will be specified by that attribute. Besides the usual self-explanatory plotting parameters (C{context}, C{bbox}, C{palette}), it accepts the following keyword arguments: - C{autocurve}: whether to use curves instead of straight lines for multiple edges on the graph plot. This argument may be C{True} or C{False}; when omitted, C{True} is assumed for graphs with less than 10.000 edges and C{False} otherwise. - C{drawer_factory}: a subclass of L{AbstractCairoGraphDrawer} which will be used to draw the graph. You may also provide a function here which takes two arguments: the Cairo context to draw on and a bounding box (an instance of L{BoundingBox}). If this keyword argument is missing, igraph will use the default graph drawer which should be suitable for most purposes. It is safe to omit this keyword argument unless you need to use a specific graph drawer. - C{keep_aspect_ratio}: whether to keep the aspect ratio of the layout that igraph calculates to place the nodes. C{True} means that the layout will be scaled proportionally to fit into the bounding box where the graph is to be drawn but the aspect ratio will be kept the same (potentially leaving empty space next to, below or above the graph). C{False} means that the layout will be scaled independently along the X and Y axis in order to fill the entire bounding box. The default is C{False}. - C{layout}: the layout to be used. If not an instance of L{Layout}, it will be passed to L{Graph.layout} to calculate the layout. Note that if you want a deterministic layout that does not change with every plot, you must either use a deterministic layout function (like L{Graph.layout_circle}) or calculate the layout in advance and pass a L{Layout} object here. - C{margin}: the top, right, bottom, left margins as a 4-tuple. If it has less than 4 elements or is a single float, the elements will be re-used until the length is at least 4. - C{mark_groups}: whether to highlight some of the vertex groups by colored polygons. This argument can be one of the following: - C{False}: no groups will be highlighted - A dict mapping tuples of vertex indices to color names. The given vertex groups will be highlighted by the given colors. - A list containing pairs or an iterable yielding pairs, where the first element of each pair is a list of vertex indices and the second element is a color. - A L{VertexClustering} or L{VertexCover} instance. The vertex groups in the clustering or cover will be highlighted such that the i-th group will be colored by the i-th color from the current palette. In place of lists of vertex indices, you may also use L{VertexSeq} instances. In place of color names, you may also use color indices into the current palette. C{None} as a color name will mean that the corresponding group is ignored. - C{vertex_size}: size of the vertices. The corresponding vertex attribute is called C{size}. The default is 10. Vertex sizes are measured in the unit of the Cairo context on which igraph is drawing. - C{vertex_color}: color of the vertices. The corresponding vertex attribute is C{color}, the default is red. Colors can be specified either by common X11 color names (see the source code of L{igraph.drawing.colors} for a list of known colors), by 3-tuples of floats (ranging between 0 and 255 for the R, G and B components), by CSS-style string specifications (C{#rrggbb}) or by integer color indices of the specified palette. - C{vertex_frame_color}: color of the frame (i.e. stroke) of the vertices. The corresponding vertex attribute is C{frame_color}, the default is black. See C{vertex_color} for the possible ways of specifying a color. - C{vertex_frame_width}: the width of the frame (i.e. stroke) of the vertices. The corresponding vertex attribute is C{frame_width}. The default is 1. Vertex frame widths are measured in the unit of the Cairo context on which igraph is drawing. - C{vertex_shape}: shape of the vertices. Alternatively it can be specified by the C{shape} vertex attribute. Possibilities are: C{square}, {circle}, {triangle}, {triangle-down} or C{hidden}. See the source code of L{igraph.drawing} for a list of alternative shape names that are also accepted and mapped to these. - C{vertex_label}: labels drawn next to the vertices. The corresponding vertex attribute is C{label}. - C{vertex_label_dist}: distance of the midpoint of the vertex label from the center of the corresponding vertex. The corresponding vertex attribute is C{label_dist}. - C{vertex_label_color}: color of the label. Corresponding vertex attribute: C{label_color}. See C{vertex_color} for color specification syntax. - C{vertex_label_size}: font size of the label, specified in the unit of the Cairo context on which we are drawing. Corresponding vertex attribute: C{label_size}. - C{vertex_label_angle}: the direction of the line connecting the midpoint of the vertex with the midpoint of the label. This can be used to position the labels relative to the vertices themselves in conjunction with C{vertex_label_dist}. Corresponding vertex attribute: C{label_angle}. The default is C{-math.pi/2}. - C{vertex_order}: drawing order of the vertices. This must be a list or tuple containing vertex indices; vertices are then drawn according to this order. - C{vertex_order_by}: an alternative way to specify the drawing order of the vertices; this attribute is interpreted as the name of a vertex attribute, and vertices are drawn such that those with a smaller attribute value are drawn first. You may also reverse the order by passing a tuple here; the first element of the tuple should be the name of the attribute, the second element specifies whether the order is reversed (C{True}, C{False}, C{"asc"} and C{"desc"} are accepted values). - C{edge_color}: color of the edges. The corresponding edge attribute is C{color}, the default is red. See C{vertex_color} for color specification syntax. - C{edge_curved}: whether the edges should be curved. Positive numbers correspond to edges curved in a counter-clockwise direction, negative numbers correspond to edges curved in a clockwise direction. Zero represents straight edges. C{True} is interpreted as 0.5, C{False} is interpreted as 0. The default is 0 which makes all the edges straight. - C{edge_width}: width of the edges in the default unit of the Cairo context on which we are drawing. The corresponding edge attribute is C{width}, the default is 1. - C{edge_arrow_size}: arrow size of the edges. The corresponding edge attribute is C{arrow_size}, the default is 1. - C{edge_arrow_width}: width of the arrowhead on the edge. The corresponding edge attribute is C{arrow_width}, the default is 1. - C{edge_order}: drawing order of the edges. This must be a list or tuple containing edge indices; edges are then drawn according to this order. - C{edge_order_by}: an alternative way to specify the drawing order of the edges; this attribute is interpreted as the name of an edge attribute, and edges are drawn such that those with a smaller attribute value are drawn first. You may also reverse the order by passing a tuple here; the first element of the tuple should be the name of the attribute, the second element specifies whether the order is reversed (C{True}, C{False}, C{"asc"} and C{"desc"} are accepted values). """ drawer_factory = kwds.get("drawer_factory", DefaultGraphDrawer) if "drawer_factory" in kwds: del kwds["drawer_factory"] drawer = drawer_factory(context, bbox) drawer.draw(self, palette, *args, **kwds) def __str__(self): """Returns a string representation of the graph. Behind the scenes, this method constructs a L{GraphSummary} instance and invokes its C{__str__} method with a verbosity of 1 and attribute printing turned off. See the documentation of L{GraphSummary} for more details about the output. """ params = dict( verbosity=1, width=78, print_graph_attributes=False, print_vertex_attributes=False, print_edge_attributes=False ) return self.summary(**params) def summary(self, verbosity=0, width=None, *args, **kwds): """Returns the summary of the graph. The output of this method is similar to the output of the C{__str__} method. If I{verbosity} is zero, only the header line is returned (see C{__str__} for more details), otherwise the header line and the edge list is printed. Behind the scenes, this method constructs a L{GraphSummary} object and invokes its C{__str__} method. @param verbosity: if zero, only the header line is returned (see C{__str__} for more details), otherwise the header line and the full edge list is printed. @param width: the number of characters to use in one line. If C{None}, no limit will be enforced on the line lengths. @return: the summary of the graph. """ return str(GraphSummary(self, verbosity, width, *args, **kwds)) _format_mapping = { "ncol": ("Read_Ncol", "write_ncol"), "lgl": ("Read_Lgl", "write_lgl"), "graphdb": ("Read_GraphDB", None), "graphmlz": ("Read_GraphMLz", "write_graphmlz"), "graphml": ("Read_GraphML", "write_graphml"), "gml": ("Read_GML", "write_gml"), "dot": (None, "write_dot"), "graphviz": (None, "write_dot"), "net": ("Read_Pajek", "write_pajek"), "pajek": ("Read_Pajek", "write_pajek"), "dimacs": ("Read_DIMACS", "write_dimacs"), "adjacency": ("Read_Adjacency", "write_adjacency"), "adj": ("Read_Adjacency", "write_adjacency"), "edgelist": ("Read_Edgelist", "write_edgelist"), "edge": ("Read_Edgelist", "write_edgelist"), "edges": ("Read_Edgelist", "write_edgelist"), "pickle": ("Read_Pickle", "write_pickle"), "picklez": ("Read_Picklez", "write_picklez"), "svg": (None, "write_svg"), "gw": (None, "write_leda"), "leda": (None, "write_leda"), "lgr": (None, "write_leda"), "dl": ("Read_DL", None) } _layout_mapping = { "auto": "layout_auto", "automatic": "layout_auto", "bipartite": "layout_bipartite", "circle": "layout_circle", "circular": "layout_circle", "davidson_harel": "layout_davidson_harel", "dh": "layout_davidson_harel", "drl": "layout_drl", "fr": "layout_fruchterman_reingold", "fruchterman_reingold": "layout_fruchterman_reingold", "gfr": "layout_grid_fruchterman_reingold", "graphopt": "layout_graphopt", "grid": "layout_grid", "grid_fr": "layout_grid_fruchterman_reingold", "grid_fruchterman_reingold": "layout_grid_fruchterman_reingold", "kk": "layout_kamada_kawai", "kamada_kawai": "layout_kamada_kawai", "lgl": "layout_lgl", "large": "layout_lgl", "large_graph": "layout_lgl", "mds": "layout_mds", "random": "layout_random", "rt": "layout_reingold_tilford", "tree": "layout_reingold_tilford", "reingold_tilford": "layout_reingold_tilford", "rt_circular": "layout_reingold_tilford_circular", "reingold_tilford_circular": "layout_reingold_tilford_circular", "sphere": "layout_sphere", "spherical": "layout_sphere", "star": "layout_star", "sugiyama": "layout_sugiyama", } # After adjusting something here, don't forget to update the docstring # of Graph.layout if necessary! ############################################################## class VertexSeq(_igraph.VertexSeq): """Class representing a sequence of vertices in the graph. This class is most easily accessed by the C{vs} field of the L{Graph} object, which returns an ordered sequence of all vertices in the graph. The vertex sequence can be refined by invoking the L{VertexSeq.select()} method. L{VertexSeq.select()} can also be accessed by simply calling the L{VertexSeq} object. An alternative way to create a vertex sequence referring to a given graph is to use the constructor directly: >>> g = Graph.Full(3) >>> vs = VertexSeq(g) >>> restricted_vs = VertexSeq(g, [0, 1]) The individual vertices can be accessed by indexing the vertex sequence object. It can be used as an iterable as well, or even in a list comprehension: >>> g=Graph.Full(3) >>> for v in g.vs: ... v["value"] = v.index ** 2 ... >>> [v["value"] ** 0.5 for v in g.vs] [0.0, 1.0, 2.0] The vertex set can also be used as a dictionary where the keys are the attribute names. The values corresponding to the keys are the values of the given attribute for every vertex selected by the sequence. >>> g=Graph.Full(3) >>> for idx, v in enumerate(g.vs): ... v["weight"] = idx*(idx+1) ... >>> g.vs["weight"] [0, 2, 6] >>> g.vs.select(1,2)["weight"] = [10, 20] >>> g.vs["weight"] [0, 10, 20] If you specify a sequence that is shorter than the number of vertices in the VertexSeq, the sequence is reused: >>> g = Graph.Tree(7, 2) >>> g.vs["color"] = ["red", "green"] >>> g.vs["color"] ['red', 'green', 'red', 'green', 'red', 'green', 'red'] You can even pass a single string or integer, it will be considered as a sequence of length 1: >>> g.vs["color"] = "red" >>> g.vs["color"] ['red', 'red', 'red', 'red', 'red', 'red', 'red'] Some methods of the vertex sequences are simply proxy methods to the corresponding methods in the L{Graph} object. One such example is L{VertexSeq.degree()}: >>> g=Graph.Tree(7, 2) >>> g.vs.degree() [2, 3, 3, 1, 1, 1, 1] >>> g.vs.degree() == g.degree() True """ def attributes(self): """Returns the list of all the vertex attributes in the graph associated to this vertex sequence.""" return self.graph.vertex_attributes() def find(self, *args, **kwds): """Returns the first vertex of the vertex sequence that matches some criteria. The selection criteria are equal to the ones allowed by L{VertexSeq.select}. See L{VertexSeq.select} for more details. For instance, to find the first vertex with name C{foo} in graph C{g}: >>> g.vs.find(name="foo") #doctest:+SKIP To find an arbitrary isolated vertex: >>> g.vs.find(_degree=0) #doctest:+SKIP """ # Shortcut: if "name" is in kwds, there are no positional arguments, # and the specified name is a string, we try that first because that # attribute is indexed. Note that we cannot do this if name is an # integer, because it would then translate to g.vs.select(name), which # searches by _index_ if the argument is an integer if not args: if "name" in kwds: name = kwds.pop("name") elif "name_eq" in kwds: name = kwds.pop("name_eq") else: name = None if name is not None and isinstance(name, (str, unicode)): args = [name] if args: # Selecting first based on positional arguments, then checking # the criteria specified by the (remaining) keyword arguments vertex = _igraph.VertexSeq.find(self, *args) if not kwds: return vertex vs = self.graph.vs.select(vertex.index) else: vs = self # Selecting based on keyword arguments vs = vs.select(**kwds) if vs: return vs[0] raise ValueError("no such vertex") def select(self, *args, **kwds): """Selects a subset of the vertex sequence based on some criteria The selection criteria can be specified by the positional and the keyword arguments. Positional arguments are always processed before keyword arguments. - If the first positional argument is C{None}, an empty sequence is returned. - If the first positional argument is a callable object, the object will be called for every vertex in the sequence. If it returns C{True}, the vertex will be included, otherwise it will be excluded. - If the first positional argument is an iterable, it must return integers and they will be considered as indices of the current vertex set (NOT the whole vertex set of the graph -- the difference matters when one filters a vertex set that has already been filtered by a previous invocation of L{VertexSeq.select()}. In this case, the indices do not refer directly to the vertices of the graph but to the elements of the filtered vertex sequence. - If the first positional argument is an integer, all remaining arguments are expected to be integers. They are considered as indices of the current vertex set again. Keyword arguments can be used to filter the vertices based on their attributes. The name of the keyword specifies the name of the attribute and the filtering operator, they should be concatenated by an underscore (C{_}) character. Attribute names can also contain underscores, but operator names don't, so the operator is always the largest trailing substring of the keyword name that does not contain an underscore. Possible operators are: - C{eq}: equal to - C{ne}: not equal to - C{lt}: less than - C{gt}: greater than - C{le}: less than or equal to - C{ge}: greater than or equal to - C{in}: checks if the value of an attribute is in a given list - C{notin}: checks if the value of an attribute is not in a given list For instance, if you want to filter vertices with a numeric C{age} property larger than 200, you have to write: >>> g.vs.select(age_gt=200) #doctest: +SKIP Similarly, to filter vertices whose C{type} is in a list of predefined types: >>> list_of_types = ["HR", "Finance", "Management"] >>> g.vs.select(type_in=list_of_types) #doctest: +SKIP If the operator is omitted, it defaults to C{eq}. For instance, the following selector selects vertices whose C{cluster} property equals to 2: >>> g.vs.select(cluster=2) #doctest: +SKIP In the case of an unknown operator, it is assumed that the recognized operator is part of the attribute name and the actual operator is C{eq}. Attribute names inferred from keyword arguments are treated specially if they start with an underscore (C{_}). These are not real attributes but refer to specific properties of the vertices, e.g., its degree. The rule is as follows: if an attribute name starts with an underscore, the rest of the name is interpreted as a method of the L{Graph} object. This method is called with the vertex sequence as its first argument (all others left at default values) and vertices are filtered according to the value returned by the method. For instance, if you want to exclude isolated vertices: >>> g = Graph.Famous("zachary") >>> non_isolated = g.vs.select(_degree_gt=0) For properties that take a long time to be computed (e.g., betweenness centrality for large graphs), it is advised to calculate the values in advance and store it in a graph attribute. The same applies when you are selecting based on the same property more than once in the same C{select()} call to avoid calculating it twice unnecessarily. For instance, the following would calculate betweenness centralities twice: >>> edges = g.vs.select(_betweenness_gt=10, _betweenness_lt=30) It is advised to use this instead: >>> g.vs["bs"] = g.betweenness() >>> edges = g.vs.select(bs_gt=10, bs_lt=30) @return: the new, filtered vertex sequence""" vs = _igraph.VertexSeq.select(self, *args) operators = { "lt": operator.lt, \ "gt": operator.gt, \ "le": operator.le, \ "ge": operator.ge, \ "eq": operator.eq, \ "ne": operator.ne, \ "in": lambda a, b: a in b, \ "notin": lambda a, b: a not in b } for keyword, value in kwds.iteritems(): if "_" not in keyword or keyword.rindex("_") == 0: keyword = keyword + "_eq" attr, _, op = keyword.rpartition("_") try: func = operators[op] except KeyError: # No such operator, assume that it's part of the attribute name attr, op, func = keyword, "eq", operators["eq"] if attr[0] == '_': # Method call, not an attribute values = getattr(vs.graph, attr[1:])(vs) else: values = vs[attr] filtered_idxs=[i for i, v in enumerate(values) if func(v, value)] vs = vs.select(filtered_idxs) return vs def __call__(self, *args, **kwds): """Shorthand notation to select() This method simply passes all its arguments to L{VertexSeq.select()}. """ return self.select(*args, **kwds) ############################################################## class EdgeSeq(_igraph.EdgeSeq): """Class representing a sequence of edges in the graph. This class is most easily accessed by the C{es} field of the L{Graph} object, which returns an ordered sequence of all edges in the graph. The edge sequence can be refined by invoking the L{EdgeSeq.select()} method. L{EdgeSeq.select()} can also be accessed by simply calling the L{EdgeSeq} object. An alternative way to create an edge sequence referring to a given graph is to use the constructor directly: >>> g = Graph.Full(3) >>> es = EdgeSeq(g) >>> restricted_es = EdgeSeq(g, [0, 1]) The individual edges can be accessed by indexing the edge sequence object. It can be used as an iterable as well, or even in a list comprehension: >>> g=Graph.Full(3) >>> for e in g.es: ... print e.tuple ... (0, 1) (0, 2) (1, 2) >>> [max(e.tuple) for e in g.es] [1, 2, 2] The edge sequence can also be used as a dictionary where the keys are the attribute names. The values corresponding to the keys are the values of the given attribute of every edge in the graph: >>> g=Graph.Full(3) >>> for idx, e in enumerate(g.es): ... e["weight"] = idx*(idx+1) ... >>> g.es["weight"] [0, 2, 6] >>> g.es["weight"] = range(3) >>> g.es["weight"] [0, 1, 2] If you specify a sequence that is shorter than the number of edges in the EdgeSeq, the sequence is reused: >>> g = Graph.Tree(7, 2) >>> g.es["color"] = ["red", "green"] >>> g.es["color"] ['red', 'green', 'red', 'green', 'red', 'green'] You can even pass a single string or integer, it will be considered as a sequence of length 1: >>> g.es["color"] = "red" >>> g.es["color"] ['red', 'red', 'red', 'red', 'red', 'red'] Some methods of the edge sequences are simply proxy methods to the corresponding methods in the L{Graph} object. One such example is L{EdgeSeq.is_multiple()}: >>> g=Graph(3, [(0,1), (1,0), (1,2)]) >>> g.es.is_multiple() [False, True, False] >>> g.es.is_multiple() == g.is_multiple() True """ def attributes(self): """Returns the list of all the edge attributes in the graph associated to this edge sequence.""" return self.graph.edge_attributes() def find(self, *args, **kwds): """Returns the first edge of the edge sequence that matches some criteria. The selection criteria are equal to the ones allowed by L{VertexSeq.select}. See L{VertexSeq.select} for more details. For instance, to find the first edge with weight larger than 5 in graph C{g}: >>> g.es.find(weight_gt=5) #doctest:+SKIP """ if args: # Selecting first based on positional arguments, then checking # the criteria specified by the keyword arguments edge = _igraph.EdgeSeq.find(self, *args) if not kwds: return edge es = self.graph.es.select(edge.index) else: es = self # Selecting based on positional arguments es = es.select(**kwds) if es: return es[0] raise ValueError("no such edge") def select(self, *args, **kwds): """Selects a subset of the edge sequence based on some criteria The selection criteria can be specified by the positional and the keyword arguments. Positional arguments are always processed before keyword arguments. - If the first positional argument is C{None}, an empty sequence is returned. - If the first positional argument is a callable object, the object will be called for every edge in the sequence. If it returns C{True}, the edge will be included, otherwise it will be excluded. - If the first positional argument is an iterable, it must return integers and they will be considered as indices of the current edge set (NOT the whole edge set of the graph -- the difference matters when one filters an edge set that has already been filtered by a previous invocation of L{EdgeSeq.select()}. In this case, the indices do not refer directly to the edges of the graph but to the elements of the filtered edge sequence. - If the first positional argument is an integer, all remaining arguments are expected to be integers. They are considered as indices of the current edge set again. Keyword arguments can be used to filter the edges based on their attributes and properties. The name of the keyword specifies the name of the attribute and the filtering operator, they should be concatenated by an underscore (C{_}) character. Attribute names can also contain underscores, but operator names don't, so the operator is always the largest trailing substring of the keyword name that does not contain an underscore. Possible operators are: - C{eq}: equal to - C{ne}: not equal to - C{lt}: less than - C{gt}: greater than - C{le}: less than or equal to - C{ge}: greater than or equal to - C{in}: checks if the value of an attribute is in a given list - C{notin}: checks if the value of an attribute is not in a given list For instance, if you want to filter edges with a numeric C{weight} property larger than 50, you have to write: >>> g.es.select(weight_gt=50) #doctest: +SKIP Similarly, to filter edges whose C{type} is in a list of predefined types: >>> list_of_types = ["inhibitory", "excitatory"] >>> g.es.select(type_in=list_of_types) #doctest: +SKIP If the operator is omitted, it defaults to C{eq}. For instance, the following selector selects edges whose C{type} property is C{intracluster}: >>> g.es.select(type="intracluster") #doctest: +SKIP In the case of an unknown operator, it is assumed that the recognized operator is part of the attribute name and the actual operator is C{eq}. Keyword arguments are treated specially if they start with an underscore (C{_}). These are not real attributes but refer to specific properties of the edges, e.g., their centrality. The rules are as follows: 1. C{_source} or {_from} means the source vertex of an edge. For undirected graphs, only the C{eq} operator is supported and it is treated as {_incident} (since undirected graphs have no notion of edge directionality). 2. C{_target} or {_to} means the target vertex of an edge. For undirected graphs, only the C{eq} operator is supported and it is treated as {_incident} (since undirected graphs have no notion of edge directionality). 3. C{_within} ignores the operator and checks whether both endpoints of the edge lie within a specified set. 4. C{_between} ignores the operator and checks whether I{one} endpoint of the edge lies within a specified set and the I{other} endpoint lies within another specified set. The two sets must be given as a tuple. 5. C{_incident} ignores the operator and checks whether the edge is incident on a specific vertex or a set of vertices. 6. Otherwise, the rest of the name is interpreted as a method of the L{Graph} object. This method is called with the edge sequence as its first argument (all others left at default values) and edges are filtered according to the value returned by the method. For instance, if you want to exclude edges with a betweenness centrality less than 2: >>> g = Graph.Famous("zachary") >>> excl = g.es.select(_edge_betweenness_ge = 2) To select edges originating from vertices 2 and 4: >>> edges = g.es.select(_source_in = [2, 4]) To select edges lying entirely within the subgraph spanned by vertices 2, 3, 4 and 7: >>> edges = g.es.select(_within = [2, 3, 4, 7]) To select edges with one endpoint in the vertex set containing vertices 2, 3, 4 and 7 and the other endpoint in the vertex set containing vertices 8 and 9: >>> edges = g.es.select(_between = ([2, 3, 4, 7], [8, 9])) For properties that take a long time to be computed (e.g., betweenness centrality for large graphs), it is advised to calculate the values in advance and store it in a graph attribute. The same applies when you are selecting based on the same property more than once in the same C{select()} call to avoid calculating it twice unnecessarily. For instance, the following would calculate betweenness centralities twice: >>> edges = g.es.select(_edge_betweenness_gt=10, # doctest:+SKIP ... _edge_betweenness_lt=30) It is advised to use this instead: >>> g.es["bs"] = g.edge_betweenness() >>> edges = g.es.select(bs_gt=10, bs_lt=30) @return: the new, filtered edge sequence """ es = _igraph.EdgeSeq.select(self, *args) is_directed = self.graph.is_directed() def _ensure_set(value): if isinstance(value, VertexSeq): value = set(v.index for v in value) elif not isinstance(value, (set, frozenset)): value = set(value) return value operators = { "lt": operator.lt, \ "gt": operator.gt, \ "le": operator.le, \ "ge": operator.ge, \ "eq": operator.eq, \ "ne": operator.ne, \ "in": lambda a, b: a in b, \ "notin": lambda a, b: a not in b } # TODO(ntamas): some keyword arguments should be prioritized over # others; for instance, we have optimized code paths for _source and # _target in directed and undirected graphs if es.is_all() is True; # these should be executed first. This matters only if there are # multiple keyword arguments and es.is_all() is True. for keyword, value in kwds.iteritems(): if "_" not in keyword or keyword.rindex("_") == 0: keyword = keyword + "_eq" pos = keyword.rindex("_") attr, op = keyword[0:pos], keyword[pos+1:] try: func = operators[op] except KeyError: # No such operator, assume that it's part of the attribute name attr, op, func = keyword, "eq", operators["eq"] if attr[0] == '_': if attr in ("_source", "_from", "_target", "_to") and not is_directed: if op not in ("eq", "in"): raise RuntimeError("unsupported for undirected graphs") # translate to _incident to avoid confusion attr = "_incident" if func == operators["eq"]: if hasattr(value, "__iter__") and not isinstance(value, (str, unicode)): value = set(value) else: value = set([value]) if attr in ("_source", "_from"): if es.is_all() and op == "eq": # shortcut here: use .incident() as it is much faster filtered_idxs = sorted(es.graph.incident(value, mode="out")) func = None # TODO(ntamas): there are more possibilities; we could # optimize "ne", "in" and "notin" in similar ways else: values = [e.source for e in es] if op == "in" or op == "notin": value = _ensure_set(value) elif attr in ("_target", "_to"): if es.is_all() and op == "eq": # shortcut here: use .incident() as it is much faster filtered_idxs = sorted(es.graph.incident(value, mode="in")) func = None # TODO(ntamas): there are more possibilities; we could # optimize "ne", "in" and "notin" in similar ways else: values = [e.target for e in es] if op == "in" or op == "notin": value = _ensure_set(value) elif attr == "_incident": func = None # ignoring function, filtering here value = _ensure_set(value) # Fetch all the edges that are incident on at least one of # the vertices specified candidates = set() for v in value: candidates.update(es.graph.incident(v)) if not es.is_all(): # Find those that are in the current edge sequence filtered_idxs = [i for i, e in enumerate(es) if e.index in candidates] else: # We are done, the filtered indexes are in the candidates set filtered_idxs = sorted(candidates) elif attr == "_within": func = None # ignoring function, filtering here value = _ensure_set(value) # Fetch all the edges that are incident on at least one of # the vertices specified candidates = set() for v in value: candidates.update(es.graph.incident(v)) if not es.is_all(): # Find those where both endpoints are OK filtered_idxs = [i for i, e in enumerate(es) if e.index in candidates and e.source in value and e.target in value] else: # Optimized version when the edge sequence contains all the edges # exactly once in increasing order of edge IDs filtered_idxs = [i for i in candidates if es[i].source in value and es[i].target in value] elif attr == "_between": if len(value) != 2: raise ValueError("_between selector requires two vertex ID lists") func = None # ignoring function, filtering here set1 = _ensure_set(value[0]) set2 = _ensure_set(value[1]) # Fetch all the edges that are incident on at least one of # the vertices specified candidates = set() for v in set1: candidates.update(es.graph.incident(v)) for v in set2: candidates.update(es.graph.incident(v)) if not es.is_all(): # Find those where both endpoints are OK filtered_idxs = [i for i, e in enumerate(es) if (e.source in set1 and e.target in set2) or (e.target in set1 and e.source in set2)] else: # Optimized version when the edge sequence contains all the edges # exactly once in increasing order of edge IDs filtered_idxs = [i for i in candidates if (es[i].source in set1 and es[i].target in set2) or (es[i].target in set1 and es[i].source in set2)] else: # Method call, not an attribute values = getattr(es.graph, attr[1:])(es) else: values = es[attr] # If we have a function to apply on the values, do that; otherwise # we assume that filtered_idxs has already been calculated. if func is not None: filtered_idxs = [i for i, v in enumerate(values) if func(v, value)] es = es.select(filtered_idxs) return es def __call__(self, *args, **kwds): """Shorthand notation to select() This method simply passes all its arguments to L{EdgeSeq.select()}. """ return self.select(*args, **kwds) ############################################################## # Additional methods of VertexSeq and EdgeSeq that call Graph methods def _graphmethod(func=None, name=None): """Auxiliary decorator This decorator allows some methods of L{VertexSeq} and L{EdgeSeq} to call their respective counterparts in L{Graph} to avoid code duplication. @param func: the function being decorated. This function will be called on the results of the original L{Graph} method. If C{None}, defaults to the identity function. @param name: the name of the corresponding method in L{Graph}. If C{None}, it defaults to the name of the decorated function. @return: the decorated function """ if name is None: name = func.__name__ method = getattr(Graph, name) if hasattr(func, "__call__"): def decorated(*args, **kwds): self = args[0].graph return func(args[0], method(self, *args, **kwds)) else: def decorated(*args, **kwds): self = args[0].graph return method(self, *args, **kwds) decorated.__name__ = name decorated.__doc__ = """Proxy method to L{Graph.%(name)s()} This method calls the C{%(name)s()} method of the L{Graph} class restricted to this sequence, and returns the result. @see: Graph.%(name)s() for details. """ % { "name": name } return decorated def _add_proxy_methods(): # Proxy methods for VertexSeq and EdgeSeq that forward their arguments to # the corresponding Graph method are constructed here. Proxy methods for # Vertex and Edge are added in the C source code. Make sure that you update # the C source whenever you add a proxy method here if that makes sense for # an individual vertex or edge decorated_methods = {} decorated_methods[VertexSeq] = \ ["degree", "betweenness", "bibcoupling", "closeness", "cocitation", "constraint", "diversity", "eccentricity", "get_shortest_paths", "maxdegree", "pagerank", "personalized_pagerank", "shortest_paths", "similarity_dice", "similarity_jaccard", "subgraph", "indegree", "outdegree", "isoclass", "delete_vertices", "is_separator", "is_minimal_separator"] decorated_methods[EdgeSeq] = \ ["count_multiple", "delete_edges", "is_loop", "is_multiple", "is_mutual", "subgraph_edges"] rename_methods = {} rename_methods[VertexSeq] = { "delete_vertices": "delete" } rename_methods[EdgeSeq] = { "delete_edges": "delete", "subgraph_edges": "subgraph" } for klass, methods in decorated_methods.iteritems(): for method in methods: new_method_name = rename_methods[klass].get(method, method) setattr(klass, new_method_name, _graphmethod(None, method)) setattr(EdgeSeq, "edge_betweenness", _graphmethod( \ lambda self, result: [result[i] for i in self.indices], "edge_betweenness")) _add_proxy_methods() ############################################################## # Making sure that layout methods always return a Layout def _layout_method_wrapper(func): """Wraps an existing layout method to ensure that it returns a Layout instead of a list of lists. @param func: the method to wrap. Must be a method of the Graph object. @return: a new method """ def result(*args, **kwds): layout = func(*args, **kwds) if not isinstance(layout, Layout): layout = Layout(layout) return layout result.__name__ = func.__name__ result.__doc__ = func.__doc__ return result for name in dir(Graph): if not name.startswith("layout_"): continue if name in ("layout_auto", "layout_sugiyama"): continue setattr(Graph, name, _layout_method_wrapper(getattr(Graph, name))) ############################################################## # Adding aliases for the 3D versions of the layout methods def _3d_version_for(func): """Creates an alias for the 3D version of the given layout algoritm. This function is a decorator that creates a method which calls I{func} after attaching C{dim=3} to the list of keyword arguments. @param func: must be a method of the Graph object. @return: a new method """ def result(*args, **kwds): kwds["dim"] = 3 return func(*args, **kwds) result.__name__ = "%s_3d" % func.__name__ result.__doc__ = """Alias for L{%s()} with dim=3.\n\n@see: Graph.%s()""" \ % (func.__name__, func.__name__) return result Graph.layout_fruchterman_reingold_3d=_3d_version_for(Graph.layout_fruchterman_reingold) Graph.layout_kamada_kawai_3d=_3d_version_for(Graph.layout_kamada_kawai) Graph.layout_random_3d=_3d_version_for(Graph.layout_random) Graph.layout_grid_3d=_3d_version_for(Graph.layout_grid) Graph.layout_sphere=_3d_version_for(Graph.layout_circle) ############################################################## def autocurve(graph, attribute="curved", default=0): """Calculates curvature values for each of the edges in the graph to make sure that multiple edges are shown properly on a graph plot. This function checks the multiplicity of each edge in the graph and assigns curvature values (numbers between -1 and 1, corresponding to CCW (-1), straight (0) and CW (1) curved edges) to them. The assigned values are either stored in an edge attribute or returned as a list, depending on the value of the I{attribute} argument. @param graph: the graph on which the calculation will be run @param attribute: the name of the edge attribute to save the curvature values to. The default value is C{curved}, which is the name of the edge attribute the default graph plotter checks to decide whether an edge should be curved on the plot or not. If I{attribute} is C{None}, the result will not be stored. @param default: the default curvature for single edges. Zero means that single edges will be straight. If you want single edges to be curved as well, try passing 0.5 or -0.5 here. @return: the list of curvature values if I{attribute} is C{None}, otherwise C{None}. """ # The following loop could be re-written in C if it turns out to be a # bottleneck. Unfortunately we cannot use Graph.count_multiple() here # because we have to ignore edge directions. multiplicities = defaultdict(list) for edge in graph.es: u, v = edge.tuple if u > v: multiplicities[v, u].append(edge.index) else: multiplicities[u, v].append(edge.index) result = [default] * graph.ecount() for pair, eids in multiplicities.iteritems(): # Is it a single edge? if len(eids) < 2: continue if len(eids) % 2 == 1: # Odd number of edges; the last will be straight result[eids.pop()] = 0 # Arrange the remaining edges curve = 2.0 / (len(eids) + 2) dcurve, sign = curve, 1 for idx, eid in enumerate(eids): edge = graph.es[eid] if edge.source > edge.target: result[eid] = -sign*curve else: result[eid] = sign*curve if idx % 2 == 1: curve += dcurve sign *= -1 if attribute is None: return result graph.es[attribute] = result def get_include(): """Returns the folder that contains the C API headers of the Python interface of igraph.""" import igraph paths = [ # The following path works if python-igraph is installed already os.path.join(sys.prefix, "include", "python{0}.{1}".format(*sys.version_info), "python-igraph"), # Fallback for cases when python-igraph is not installed but # imported directly from the source tree os.path.join(os.path.dirname(igraph.__file__), "..", "src") ] for path in paths: if os.path.exists(os.path.join(path, "igraphmodule_api.h")): return os.path.abspath(path) raise ValueError("cannot find the header files of python-igraph") def read(filename, *args, **kwds): """Loads a graph from the given filename. This is just a convenience function, calls L{Graph.Read} directly. All arguments are passed unchanged to L{Graph.Read} @param filename: the name of the file to be loaded """ return Graph.Read(filename, *args, **kwds) load=read def write(graph, filename, *args, **kwds): """Saves a graph to the given file. This is just a convenience function, calls L{Graph.write} directly. All arguments are passed unchanged to L{Graph.write} @param graph: the graph to be saved @param filename: the name of the file to be written """ return graph.write(filename, *args, **kwds) save=write def summary(obj, stream=None, *args, **kwds): """Prints a summary of object o to a given stream Positional and keyword arguments not explicitly mentioned here are passed on to the underlying C{summary()} method of the object if it has any. @param obj: the object about which a human-readable summary is requested. @param stream: the stream to be used. If C{None}, the standard output will be used. """ if stream is None: stream = sys.stdout if hasattr(obj, "summary"): stream.write(obj.summary(*args, **kwds)) else: stream.write(str(obj)) stream.write("\n") config = configuration.init() del construct_graph_from_formula python-igraph-0.8.0/src/igraph/matching.py0000644000076500000240000001530113104627150020744 0ustar tamasstaff00000000000000# vim:ts=4:sw=4:sts=4:et # -*- coding: utf-8 -*- """Classes representing matchings on graphs.""" from igraph.clustering import VertexClustering from igraph._igraph import Vertex __license__ = u"""\ Copyright (C) 2006-2012 Tamás Nepusz Pázmány Péter sétány 1/a, 1117 Budapest, Hungary This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA """ class Matching(object): """A matching of vertices in a graph. A matching of an undirected graph is a set of edges such that each vertex is incident on at most one matched edge. When each vertex is incident on I{exactly} one matched edge, the matching called I{perfect}. This class is used in C{igraph} to represent non-perfect and perfect matchings in undirected graphs. This class is usually not instantiated directly, everything is taken care of by the functions that return matchings. Examples: >>> from igraph import Graph >>> g = Graph.Famous("noperfectmatching") >>> matching = g.maximum_matching() """ def __init__(self, graph, matching, types=None): """Initializes the matching. @param graph: the graph the matching belongs to @param matching: a numeric vector where element I{i} corresponds to vertex I{i} of the graph. Element I{i} is -1 or if the corresponding vertex is unmatched, otherwise it contains the index of the vertex to which vertex I{i} is matched. @param types: the types of the vertices if the graph is bipartite. It must either be the name of a vertex attribute (which will be retrieved for all vertices) or a list. Elements in the list will be converted to boolean values C{True} or C{False}, and this will determine which part of the bipartite graph a given vertex belongs to. @raise ValueError: if the matching vector supplied does not describe a valid matching of the graph. """ self._graph = graph self._matching = None self._num_matched = 0 self._types = None if isinstance(types, basestring): types = graph.vs[types] self.types = types self.matching = matching def __len__(self): return self._num_matched def __repr__(self): if self._types is not None: return "%s(%r,%r,types=%r)" % \ (self.__class__.__name__, self._graph, self._matching, self._types) else: return "%s(%r,%r)" % \ (self.__class__.__name__, self._graph, self._matching) def __str__(self): if self._types is not None: return "Bipartite graph matching (%d matched vertex pairs)" % len(self) else: return "Graph matching (%d matched vertex pairs)" % len(self) def edges(self): """Returns an edge sequence that contains the edges in the matching. If there are multiple edges between a pair of matched vertices, only one of them will be returned. """ get_eid = self._graph.get_eid eidxs = [get_eid(u, v, directed=False) \ for u, v in enumerate(self._matching) if v != -1 and u <= v] return self._graph.es[eidxs] @property def graph(self): """Returns the graph corresponding to the matching.""" return self._graph def is_maximal(self): """Returns whether the matching is maximal. A matching is maximal when it is not possible to extend it any more with extra edges; in other words, unmatched vertices in the graph must be adjacent to matched vertices only. """ return self._graph._is_maximal_matching(self._matching, types=self._types) def is_matched(self, vertex): """Returns whether the given vertex is matched to another one.""" if isinstance(vertex, Vertex): vertex = vertex.index return self._matching[vertex] >= 0 def match_of(self, vertex): """Returns the vertex a given vertex is matched to. @param vertex: the vertex we are interested in; either an integer index or an instance of L{Vertex}. @return: the index of the vertex matched to the given vertex, either as an integer index (if I{vertex} was integer) or as an instance of L{Vertex}. When the vertex is unmatched, returns C{None}. """ if isinstance(vertex, Vertex): matched = self._matching[vertex.index] if matched < 0: return None return self._graph.vs[matched] matched = self._matching[vertex] if matched < 0: return None return matched @property def matching(self): """Returns the matching vector where element I{i} contains the ID of the vertex that vertex I{i} is matched to. The matching vector will contain C{-1} for unmatched vertices. """ return self._matching @matching.setter def matching(self, value): """Sets the matching vector. @param value: the matching vector which must contain the ID of the vertex matching vertex I{i} at the I{i}th position, or C{-1} if the vertex is unmatched. @raise ValueError: if the matching vector supplied does not describe a valid matching of the graph. """ if not self.graph._is_matching(value, types=self._types): raise ValueError("not a valid matching") self._matching = list(value) self._num_matched = sum(1 for i in self._matching if i >= 0) // 2 @property def types(self): """Returns the type vector if the graph is bipartite. Element I{i} of the type vector will be C{False} or C{True} depending on which side of the bipartite graph vertex I{i} belongs to. For non-bipartite graphs, this property returns C{None}. """ return self._types @types.setter def types(self, value): types = [bool(x) for x in value] if len(types) < self._graph.vcount(): raise ValueError("type vector too short") self._types = types python-igraph-0.8.0/src/igraph/summary.py0000644000076500000240000003467713607102615020672 0ustar tamasstaff00000000000000# vim:ts=4:sw=4:sts=4:et # -*- coding: utf-8 -*- """Summary representation of a graph. @undocumented: _get_wrapper_for_width, FakeWrapper """ from igraph.statistics import median from itertools import islice from math import ceil from texttable import Texttable from textwrap import TextWrapper __all__ = ["GraphSummary"] __license__ = u"""\ Copyright (C) 2006-2012 Tamás Nepusz Pázmány Péter sétány 1/a, 1117 Budapest, Hungary This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA """ class FakeWrapper(object): """Object whose interface is compatible with C{textwrap.TextWrapper} but does no wrapping.""" def __init__(self, *args, **kwds): pass def fill(self, text): return [text] def wrap(self, text): return [text] def _get_wrapper_for_width(width, *args, **kwds): """Returns a text wrapper that wraps text for the given width. @param width: the maximal width of each line that the text wrapper produces. C{None} means that no wrapping will be performed. """ if width is None: return FakeWrapper(*args, **kwds) return TextWrapper(width=width, *args, **kwds) class GraphSummary(object): """Summary representation of a graph. The summary representation includes a header line and the list of edges. The header line consists of C{IGRAPH}, followed by a four-character long code, the number of vertices, the number of edges, two dashes (C{--}) and the name of the graph (i.e. the contents of the C{name} attribute, if any). For instance, a header line may look like this:: IGRAPH U--- 4 5 -- The four-character code describes some basic properties of the graph. The first character is C{U} if the graph is undirected, C{D} if it is directed. The second letter is C{N} if the graph has a vertex attribute called C{name}, or a dash otherwise. The third letter is C{W} if the graph is weighted (i.e. it has an edge attribute called C{weight}), or a dash otherwise. The fourth letter is C{B} if the graph has a vertex attribute called C{type}; this is usually used for bipartite graphs. Edges may be presented as an ordinary edge list or an adjacency list. By default, this depends on the number of edges; however, you can control it with the appropriate constructor arguments. @undocumented: _construct_edgelist_adjlist, _construct_edgelist_compressed, _construct_edgelist_edgelist, _construct_graph_attributes, _construct_vertex_attributes, _construct_header, _edge_attribute_iterator, _infer_column_alignment, _new_table, _vertex_attribute_iterator """ def __init__(self, graph, verbosity=0, width=78, edge_list_format="auto", max_rows=99999, print_graph_attributes=False, print_vertex_attributes=False, print_edge_attributes=False, full=False): """Constructs a summary representation of a graph. @param verbosity: the verbosity of the summary. If zero, only the header line will be returned. If one, the header line and the list of edges will both be returned. @param width: the maximal width of each line in the summary. C{None} means that no limit will be enforced. @param max_rows: the maximal number of rows to print in a single table (e.g., vertex attribute table or edge attribute table) @param edge_list_format: format of the edge list in the summary. Supported formats are: C{compressed}, C{adjlist}, C{edgelist}, C{auto}, which selects automatically from the other three based on some simple criteria. @param print_graph_attributes: whether to print graph attributes if there are any. @param print_vertex_attributes: whether to print vertex attributes if there are any. @param print_edge_attributes: whether to print edge attributes if there are any. @param full: False has no effect; True turns on the attribute printing for graph, vertex and edge attributes with verbosity 1. """ if full: print_graph_attributes = True print_vertex_attributes = True print_edge_attributes = True verbosity = max(verbosity, 1) self._graph = graph self.edge_list_format = edge_list_format.lower() self.max_rows = int(max_rows) self.print_graph_attributes = print_graph_attributes self.print_vertex_attributes = print_vertex_attributes self.print_edge_attributes = print_edge_attributes self.verbosity = verbosity self.width = width self.wrapper = _get_wrapper_for_width(self.width, break_on_hyphens=False) if self._graph.is_named(): self._edges_header = "+ edges (vertex names):" else: self._edges_header = "+ edges:" self._arrow = ["--", "->"][self._graph.is_directed()] self._arrow_format = "%%s%s%%s" % self._arrow def _construct_edgelist_adjlist(self): """Constructs the part in the summary that prints the edge list in an adjacency list format.""" result = [self._edges_header] arrow = self._arrow_format if self._graph.vcount() == 0: return if self._graph.is_named(): names = self._graph.vs["name"] maxlen = max(len(name) for name in names) format_str = "%%%ds %s %%s" % (maxlen, self._arrow) for v1, name in enumerate(names): neis = self._graph.successors(v1) neis = ", ".join(str(names[v2]) for v2 in neis) result.append(format_str % (name, neis)) else: maxlen = len(str(self._graph.vcount())) num_format = "%%%dd" % maxlen format_str = "%s %s %%s" % (num_format, self._arrow) for v1 in xrange(self._graph.vcount()): neis = self._graph.successors(v1) neis = " ".join(num_format % v2 for v2 in neis) result.append(format_str % (v1, neis)) # Try to wrap into multiple columns if that works with the given width if self.width is not None: maxlen = max(len(line) for line in result[1:]) colcount = int(self.width + 3) / int(maxlen + 3) if colcount > 1: # Rewrap to multiple columns nrows = len(result) - 1 colheight = int(ceil(nrows / float(colcount))) newrows = [[] for _ in xrange(colheight)] for i, row in enumerate(result[1:]): newrows[i % colheight].append(row.ljust(maxlen)) result[1:] = [" ".join(row) for row in newrows] return result def _construct_edgelist_compressed(self): """Constructs the part in the summary that prints the edge list in a compressed format suitable for graphs with mostly small degrees.""" result = [self._edges_header] arrow = self._arrow_format if self._graph.is_named(): names = self._graph.vs["name"] edges = ", ".join(arrow % (names[edge.source], names[edge.target]) for edge in self._graph.es) else: edges = " ".join(arrow % edge.tuple for edge in self._graph.es) result.append(edges) return result def _construct_edgelist_edgelist(self): """Constructs the part in the summary that prints the edge list in a full edge list format.""" attrs = sorted(self._graph.edge_attributes()) table = self._new_table(headers=["", "edge"] + attrs) table.add_rows(islice(self._edge_attribute_iterator(attrs), 0, self.max_rows), header=False) table.set_cols_align(["l", "l"] + self._infer_column_alignment(edge_attrs=attrs)) result = [self._edges_header] result.extend(table.draw().split("\n")) return result def _construct_graph_attributes(self): """Constructs the part in the summary that lists the graph attributes.""" attrs = self._graph.attributes() if not attrs: return [] result = ["+ graph attributes:"] attrs.sort() for attr in attrs: result.append("[[%s]]" % (attr, )) result.append(str(self._graph[attr])) return result def _construct_vertex_attributes(self): """Constructs the part in the summary that lists the vertex attributes.""" attrs = sorted(self._graph.vertex_attributes()) if not attrs or (len(attrs) == 1 and "name" in attrs): return [] table = self._new_table(headers=[""] + attrs) table.add_rows(islice(self._vertex_attribute_iterator(attrs), 0, self.max_rows), header=False) table.set_cols_align(["l"] + self._infer_column_alignment(vertex_attrs=attrs)) result = ["+ vertex attributes:"] result.extend(table.draw().split("\n")) return result def _construct_header(self): """Constructs the header part of the summary.""" graph = self._graph params = dict( directed="UD"[graph.is_directed()], named="-N"[graph.is_named()], weighted="-W"[graph.is_weighted()], typed="-T"["type" in graph.vertex_attributes()], vcount=graph.vcount(), ecount=graph.ecount(), ) if "name" in graph.attributes(): params["name"] = graph["name"] else: params["name"] = "" result = ["IGRAPH %(directed)s%(named)s%(weighted)s%(typed)s "\ "%(vcount)d %(ecount)d -- %(name)s" % params] attrs = ["%s (g)" % (name, ) for name in sorted(graph.attributes())] attrs.extend("%s (v)" % (name, ) for name in sorted(graph.vertex_attributes())) attrs.extend("%s (e)" % (name, ) for name in sorted(graph.edge_attributes())) if attrs: result.append("+ attr: %s" % ", ".join(attrs)) if self.wrapper is not None: self.wrapper.subsequent_indent = ' ' result[-1:] = self.wrapper.wrap(result[-1]) self.wrapper.subsequent_indent = '' return result def _edge_attribute_iterator(self, attribute_order): """Returns an iterator that yields the rows of the edge attribute table in the summary. `attribute_order` must be a list containing the names of the attributes to be presented in this table.""" arrow = self._arrow_format if self._graph.is_named(): names = self._graph.vs["name"] for edge in self._graph.es: formatted_edge = arrow % (names[edge.source], names[edge.target]) yield ["[%d]" % edge.index, formatted_edge] + \ [edge[attr] for attr in attribute_order] else: for edge in self._graph.es: formatted_edge = arrow % edge.tuple yield ["[%d]" % edge.index, formatted_edge] + \ [edge[attr] for attr in attribute_order] def _infer_column_alignment(self, vertex_attrs=None, edge_attrs=None): """Infers the preferred alignment for the given vertex and edge attributes in the tables by peeking into the attribute values of the first 100 vertices or edges. Numeric attributes will be aligned right, everything else will be aligned left.""" values = [] if vertex_attrs is not None: vs = self._graph.vs[:100] values.extend(vs[attr] for attr in vertex_attrs) if edge_attrs is not None: es = self._graph.es[:100] values.extend(es[attr] for attr in edge_attrs) result = [] for vs in values: is_numeric = True try: [float(x) for x in vs] except ValueError: is_numeric = False if is_numeric: result.append("r") else: result.append("l") return result def _new_table(self, headers=None): """Constructs a new table to pretty-print vertex and edge attributes""" table = Texttable(max_width=0) table.set_deco(0) if headers is not None: table.header(headers) return table def _vertex_attribute_iterator(self, attribute_order): """Returns an iterator that yields the rows of the vertex attribute table in the summary. `attribute_order` must be a list containing the names of the attributes to be presented in this table.""" for vertex in self._graph.vs: yield ["[%d]" % vertex.index] + [vertex[attr] for attr in attribute_order] def __str__(self): """Returns the summary representation as a string.""" output = self._construct_header() if self.print_graph_attributes: output.extend(self._construct_graph_attributes()) if self.print_vertex_attributes: output.extend(self._construct_vertex_attributes()) if self.verbosity <= 0: return "\n".join(output) if self._graph.ecount() > 0: # Add the edge list if self.edge_list_format == "auto": if (self.print_edge_attributes and self._graph.edge_attributes()): format = "edgelist" elif median(self._graph.degree(mode="out")) < 3: format = "compressed" else: format = "adjlist" else: format = self.edge_list_format method_name = "_construct_edgelist_%s" % format if hasattr(self, method_name): output.extend(getattr(self, method_name)()) if self.wrapper is not None: return "\n".join("\n".join(self.wrapper.wrap(line)) for line in output) return "\n".join(output) python-igraph-0.8.0/src/igraph/datatypes.py0000644000076500000240000006752413104627150021166 0ustar tamasstaff00000000000000# vim:ts=4:sw=4:sts=4:et # -*- coding: utf-8 -*- """Additional auxiliary data types""" from itertools import islice __license__ = """\ Copyright (C) 2006-2012 Tamás Nepusz Pázmány Péter sétány 1/a, 1117 Budapest, Hungary This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA """ class Matrix(object): """Simple matrix data type. Of course there are much more advanced matrix data types for Python (for instance, the C{ndarray} data type of Numeric Python) and this implementation does not want to compete with them. The only role of this data type is to provide a convenient interface for the matrices returned by the C{Graph} object (for instance, allow indexing with tuples in the case of adjacency matrices and so on). """ def __init__(self, data=None): """Initializes a matrix. @param data: the elements of the matrix as a list of lists, or C{None} to create a 0x0 matrix. """ self._nrow, self._ncol, self._data = 0, 0, [] self.data = data # pylint: disable-msg=C0103 @classmethod def Fill(cls, value, *args): """Creates a matrix filled with the given value @param value: the value to be used @keyword shape: the shape of the matrix. Can be a single integer, two integers or a tuple. If a single integer is given here, the matrix is assumed to be square-shaped. """ if len(args) < 1: raise TypeError("expected an integer or a tuple") if len(args) == 1: if hasattr(args[0], "__len__"): height, width = int(args[0][0]), int(args[0][1]) else: height, width = int(args[0]), int(args[0]) else: height, width = int(args[0]), int(args[1]) mtrx = [[value]*width for _ in xrange(height)] return cls(mtrx) # pylint: disable-msg=C0103 @classmethod def Zero(cls, *args): """Creates a matrix filled with zeros. @keyword shape: the shape of the matrix. Can be a single integer, two integers or a tuple. If a single integer is given here, the matrix is assumed to be square-shaped. """ result = cls.Fill(0, *args) return result # pylint: disable-msg=C0103 @classmethod def Identity(cls, *args): """Creates an identity matrix. @keyword shape: the shape of the matrix. Can be a single integer, two integers or a tuple. If a single integer is given here, the matrix is assumed to be square-shaped. """ # pylint: disable-msg=W0212 result = cls.Fill(0, *args) for i in xrange(min(result.shape)): result._data[i][i] = 1 return result def _set_data(self, data=None): """Sets the data stored in the matrix""" if data is not None: self._data = [list(row) for row in data] self._nrow = len(self._data) if self._nrow > 0: self._ncol = max(len(row) for row in self._data) else: self._ncol = 0 for row in self._data: if len(row) < self._ncol: row.extend([0]*(self._ncol-len(row))) def _get_data(self): """Returns the data stored in the matrix as a list of lists""" return [list(row) for row in self._data] data = property(_get_data, _set_data) @property def shape(self): """Returns the shape of the matrix as a tuple""" return self._nrow, self._ncol def __add__(self, other): """Adds the given value to the matrix. @param other: either a scalar or a matrix. Scalars will be added to each element of the matrix. Matrices will be added together elementwise. @return: the result matrix """ if isinstance(other, Matrix): if self.shape != other.shape: raise ValueError("matrix shapes do not match") return self.__class__([ [a+b for a, b in izip(row_a, row_b)] for row_a, row_b in izip(self, other) ]) else: return self.__class__([ [item+other for item in row] for row in self]) def __eq__(self, other): """Checks whether a given matrix is equal to another one""" return isinstance(other, Matrix) and \ self._nrow == other._nrow and \ self._ncol == other._ncol and \ self._data == other._data def __getitem__(self, i): """Returns a single item, a row or a column of the matrix @param i: if a single integer, returns the M{i}th row as a list. If a slice, returns the corresponding rows as another L{Matrix} object. If a 2-tuple, the first element of the tuple is used to select a row and the second is used to select a column. """ if isinstance(i, int): return list(self._data[i]) elif isinstance(i, slice): return self.__class__(self._data[i]) elif isinstance(i, tuple): try: first = i[0] except IndexError: first = slice(None) try: second = i[1] except IndexError: second = slice(None) if type(first) == slice and type(second) == slice: return self.__class__(row[second] for row in self._data[first]) elif type(first) == slice: return [row[second] for row in self._data[first]] else: return self._data[first][second] else: raise IndexError("invalid matrix index") def __hash__(self): """Returns a hash value for a matrix.""" return hash(self._nrow, self._ncol, self._data) def __iadd__(self, other): """In-place addition of a matrix or scalar.""" if isinstance(other, Matrix): if self.shape != other.shape: raise ValueError("matrix shapes do not match") for row_a, row_b in izip(self._data, other): for i in xrange(len(row_a)): row_a[i] += row_b[i] else: for row in self._data: for i in xrange(len(row)): row[i] += other return self def __isub__(self, other): """In-place subtraction of a matrix or scalar.""" if isinstance(other, Matrix): if self.shape != other.shape: raise ValueError("matrix shapes do not match") for row_a, row_b in izip(self._data, other): for i in xrange(len(row_a)): row_a[i] -= row_b[i] else: for row in self._data: for i in xrange(len(row)): row[i] -= other return self def __ne__(self, other): """Checks whether a given matrix is not equal to another one""" return not self == other def __setitem__(self, i, value): """Sets a single item, a row or a column of the matrix @param i: if a single integer, sets the M{i}th row as a list. If a slice, sets the corresponding rows from another L{Matrix} object. If a 2-tuple, the first element of the tuple is used to select a row and the second is used to select a column. @param value: the new value """ if isinstance(i, int): # Setting a row if len(value) != len(self._data[i]): raise ValueError("new value must have %d items" % self._ncol) self._data[i] = list(value) elif isinstance(i, slice): # Setting multiple rows if len(value) != len(self._data[i]): raise ValueError("new value must have %d items" % self._ncol) if any(len(row) != self._ncol for row in value): raise ValueError("rows of new value must have %d items" % \ self._ncol) self._data[i] = [list(row) for row in value] elif isinstance(i, tuple): try: first = i[0] except IndexError: first = slice(None) try: second = i[1] except IndexError: second = slice(None) if type(first) == slice and type(second) == slice: # Setting a submatrix # TODO raise NotImplementedError elif type(first) == slice: # Setting a submatrix raise NotImplementedError else: # Setting a single element self._data[first][second] = value else: raise IndexError("invalid matrix index") def __sub__(self, other): """Subtracts the given value from the matrix. @param other: either a scalar or a matrix. Scalars will be subtracted from each element of the matrix. Matrices will be subtracted together elementwise. @return: the result matrix """ if isinstance(other, Matrix): if self.shape != other.shape: raise ValueError("matrix shapes do not match") return self.__class__([ [a-b for a, b in izip(row_a, row_b)] for row_a, row_b in izip(self, other) ]) else: return self.__class__([ [item-other for item in row] for row in self]) def __repr__(self): class_name = self.__class__.__name__ rows = ("[%s]" % ", ".join(repr(item) for item in row) for row in self) return "%s([%s])" % (class_name, ", ".join(rows)) def __str__(self): rows = ("[%s]" % ", ".join(repr(item) for item in row) for row in self) return "[%s]" % "\n ".join(rows) def __iter__(self): """Support for iteration. This is actually implemented as a generator, so there is no need for a separate iterator class. The generator returns I{copies} of the rows in the matrix as lists to avoid messing around with the internals. Feel free to do anything with the copies, the changes won't be reflected in the original matrix.""" return (list(row) for row in self._data) def __plot__(self, context, bbox, palette, **kwds): """Plots the matrix to the given Cairo context in the given box Besides the usual self-explanatory plotting parameters (C{context}, C{bbox}, C{palette}), it accepts the following keyword arguments: - C{style}: the style of the plot. C{boolean} is useful for plotting matrices with boolean (C{True}/C{False} or 0/1) values: C{False} will be shown with a white box and C{True} with a black box. C{palette} uses the given palette to represent numbers by colors, the minimum will be assigned to palette color index 0 and the maximum will be assigned to the length of the palette. C{None} draws transparent cell backgrounds only. The default style is C{boolean} (but it may change in the future). C{None} values in the matrix are treated specially in both cases: nothing is drawn in the cell corresponding to C{None}. - C{square}: whether the cells of the matrix should be square or not. Default is C{True}. - C{grid_width}: line width of the grid shown on the matrix. If zero or negative, the grid is turned off. The grid is also turned off if the size of a cell is less than three times the given line width. Default is C{1}. Fractional widths are also allowed. - C{border_width}: line width of the border drawn around the matrix. If zero or negative, the border is turned off. Default is C{1}. - C{row_names}: the names of the rows - C{col_names}: the names of the columns. - C{values}: values to be displayed in the cells. If C{None} or C{False}, no values are displayed. If C{True}, the values come from the matrix being plotted. If it is another matrix, the values of that matrix are shown in the cells. In this case, the shape of the value matrix must match the shape of the matrix being plotted. - C{value_format}: a format string or a callable that specifies how the values should be plotted. If it is a callable, it must be a function that expects a single value and returns a string. Example: C{"%#.2f"} for floating-point numbers with always exactly two digits after the decimal point. See the Python documentation of the C{%} operator for details on the format string. If the format string is not given, it defaults to the C{str} function. If only the row names or the column names are given and the matrix is square-shaped, the same names are used for both column and row names. """ # pylint: disable-msg=W0142 # pylint: disable-msg=C0103 grid_width = float(kwds.get("grid_width", 1.)) border_width = float(kwds.get("border_width", 1.)) style = kwds.get("style", "boolean") row_names = kwds.get("row_names") col_names = kwds.get("col_names", row_names) values = kwds.get("values") value_format = kwds.get("value_format", str) # Validations if style not in ("boolean", "palette", "none", None): raise ValueError("invalid style") if style == "none": style = None if row_names is None and col_names is not None: row_names = col_names if row_names is not None: row_names = [str(name) for name in islice(row_names, self._nrow)] if len(row_names) < self._nrow: row_names.extend([""]*(self._nrow-len(row_names))) if col_names is not None: col_names = [str(name) for name in islice(col_names, self._ncol)] if len(col_names) < self._ncol: col_names.extend([""]*(self._ncol-len(col_names))) if values == False: values = None if values == True: values = self if isinstance(values, list): values = Matrix(list) if values is not None and not isinstance(values, Matrix): raise TypeError("values must be None, False, True or a matrix") if values is not None and values.shape != self.shape: raise ValueError("values must be a matrix of size %s" % self.shape) # Calculate text extents if needed if row_names is not None or col_names is not None: te = context.text_extents space_width = te(" ")[4] max_row_name_width = max([te(s)[4] for s in row_names])+space_width max_col_name_width = max([te(s)[4] for s in col_names])+space_width else: max_row_name_width, max_col_name_width = 0, 0 # Calculate sizes total_width = float(bbox.width)-max_row_name_width total_height = float(bbox.height)-max_col_name_width dx = total_width / self.shape[1] dy = total_height / self.shape[0] if kwds.get("square", True): dx, dy = min(dx, dy), min(dx, dy) total_width, total_height = dx*self.shape[1], dy*self.shape[0] ox = bbox.left + (bbox.width - total_width - max_row_name_width) / 2.0 oy = bbox.top + (bbox.height - total_height - max_col_name_width) / 2.0 ox += max_row_name_width oy += max_col_name_width # Determine rescaling factors for the palette if needed if style == "palette": mi, ma = self.min(), self.max() color_offset = mi color_ratio = (len(palette)-1) / float(ma-mi) # Validate grid width if dx < 3*grid_width or dy < 3*grid_width: grid_width = 0. if grid_width > 0: context.set_line_width(grid_width) else: # When the grid width is zero, we will still stroke the # rectangles, but with the same color as the fill color # of the cell - otherwise we would get thin white lines # between the cells as a drawing artifact context.set_line_width(1) # Draw row names (if any) context.set_source_rgb(0., 0., 0.) if row_names is not None: x, y = ox, oy for heading in row_names: _, _, _, h, xa, _ = context.text_extents(heading) context.move_to(x-xa-space_width, y + (dy+h)/2.) context.show_text(heading) y += dy # Draw column names (if any) if col_names is not None: context.save() context.translate(ox, oy) context.rotate(-1.5707963285) # pi/2 x, y = 0., 0. for heading in col_names: _, _, _, h, _, _ = context.text_extents(heading) context.move_to(x+space_width, y + (dx+h)/2.) context.show_text(heading) y += dx context.restore() # Draw matrix x, y = ox, oy if style is None: fill = lambda: None else: fill = context.fill_preserve for row in self: for item in row: if item is None: x += dx continue if style == "boolean": if item: context.set_source_rgb(0., 0., 0.) else: context.set_source_rgb(1., 1., 1.) elif style == "palette": cidx = int((item-color_offset)*color_ratio) if cidx < 0: cidx = 0 context.set_source_rgba(*palette.get(cidx)) context.rectangle(x, y, dx, dy) if grid_width > 0: fill() context.set_source_rgb(0.5, 0.5, 0.5) context.stroke() else: fill() context.stroke() x += dx x, y = ox, y+dy # Draw cell values if values is not None: x, y = ox, oy context.set_source_rgb(0., 0., 0.) for row in values.data: if hasattr(value_format, "__call__"): values = [value_format(item) for item in row] else: values = [value_format % item for item in row] for item in values: th, tw = context.text_extents(item)[3:5] context.move_to(x+(dx-tw)/2., y+(dy+th)/2.) context.show_text(item) x += dx x, y = ox, y+dy # Draw borders if border_width > 0: context.set_line_width(border_width) context.set_source_rgb(0., 0., 0.) context.rectangle(ox, oy, dx*self.shape[1], dy*self.shape[0]) context.stroke() def min(self, dim=None): """Returns the minimum of the matrix along the given dimension @param dim: the dimension. 0 means determining the column minimums, 1 means determining the row minimums. If C{None}, the global minimum is returned. """ if dim == 1: return [min(row) for row in self._data] if dim == 0: return [min(row[idx] for row in self._data) \ for idx in xrange(self._ncol)] return min(min(row) for row in self._data) def max(self, dim=None): """Returns the maximum of the matrix along the given dimension @param dim: the dimension. 0 means determining the column maximums, 1 means determining the row maximums. If C{None}, the global maximum is returned. """ if dim == 1: return [max(row) for row in self._data] if dim == 0: return [max(row[idx] for row in self._data) \ for idx in xrange(self._ncol)] return max(max(row) for row in self._data) class DyadCensus(tuple): """Dyad census of a graph. This is a pretty simple class - basically it is a tuple, but it allows the user to refer to its individual items by the names C{mutual} (or C{mut}), C{asymmetric} (or C{asy} or C{asym} or C{asymm}) and C{null}. Examples: >>> from igraph import Graph >>> g=Graph.Erdos_Renyi(100, 0.2, directed=True) >>> dc=g.dyad_census() >>> print dc.mutual #doctest:+SKIP 179 >>> print dc["asym"] #doctest:+SKIP 1609 >>> print tuple(dc), list(dc) #doctest:+SKIP (179, 1609, 3162) [179, 1609, 3162] >>> print sorted(dc.as_dict().items()) #doctest:+ELLIPSIS [('asymmetric', ...), ('mutual', ...), ('null', ...)] @undocumented: _remap """ _remap = {"mutual": 0, "mut": 0, "sym": 0, "symm": 0, "asy": 1, "asym": 1, "asymm": 1, "asymmetric": 1, "null": 2} def __getitem__(self, idx): return tuple.__getitem__(self, self._remap.get(idx, idx)) def __getattr__(self, attr): if attr in self._remap: return tuple.__getitem__(self, self._remap[attr]) raise AttributeError("no such attribute: %s" % attr) def __repr__(self): return "DyadCensus((%d, %d, %d))" % self def __str__(self): return "%d mutual, %d asymmetric, %d null dyads" % self def as_dict(self): """Converts the dyad census to a dict using the known dyad names.""" return {"mutual": self[0], "asymmetric": self[1], "null": self[2]} class TriadCensus(tuple): """Triad census of a graph. This is a pretty simple class - basically it is a tuple, but it allows the user to refer to its individual items by the following triad names: - C{003} -- the empty graph - C{012} -- a graph with a single directed edge (C{A --> B, C}) - C{102} -- a graph with a single mutual edge (C{A <-> B, C}) - C{021D} -- the binary out-tree (C{A <-- B --> C}) - C{021U} -- the binary in-tree (C{A --> B <-- C}) - C{021C} -- the directed line (C{A --> B --> C}) - C{111D} -- C{A <-> B <-- C} - C{111U} -- C{A <-> B --> C} - C{030T} -- C{A --> B <-- C, A --> C} - C{030C} -- C{A <-- B <-- C, A --> C} - C{201} -- C{A <-> B <-> C} - C{120D} -- C{A <-- B --> C, A <-> C} - C{120U} -- C{A --> B <-- C, A <-> C} - C{120C} -- C{A --> B --> C, A <-> C} - C{210C} -- C{A --> B <-> C, A <-> C} - C{300} -- the complete graph (C{A <-> B <-> C, A <-> C}) Attribute and item accessors are provided. Due to the syntax of Python, attribute names are not allowed to start with a number, therefore the triad names must be prepended with a lowercase C{t} when accessing them as attributes. This is not necessary with the item accessor syntax. Examples: >>> from igraph import Graph >>> g=Graph.Erdos_Renyi(100, 0.2, directed=True) >>> tc=g.triad_census() >>> print tc.t003 #doctest:+SKIP 39864 >>> print tc["030C"] #doctest:+SKIP 1206 """ _remap = {"003": 0, "012": 1, "102": 2, "021D": 3, "021U": 4, "021C": 5, \ "111D": 6, "111U": 7, "030T": 8, "030C": 9, "201": 10, "120D": 11, \ "120U": 12, "120C": 13, "210": 14, "300": 15} def __getitem__(self, idx): if isinstance(idx, basestring): idx = idx.upper() return tuple.__getitem__(self, self._remap.get(idx, idx)) def __getattr__(self, attr): if isinstance(attr, basestring) and attr[0] == 't' \ and attr[1:].upper() in self._remap: return tuple.__getitem__(self, self._remap[attr[1:].upper()]) raise AttributeError("no such attribute: %s" % attr) def __repr__(self): return "TriadCensus((%s))" % ", ".join(str(item) for item in self) def __str__(self): maxidx = len(self) maxcount = max(self) numwidth = len(str(maxcount)) captionwidth = max(len(key) for key in self._remap) colcount = 4 rowcount = maxidx / colcount if rowcount * colcount < maxidx: rowcount += 1 invmap = dict((v, k) for k, v in self._remap.iteritems()) result, row, idx = [], [], 0 for _ in xrange(rowcount): for _ in xrange(colcount): if idx >= maxidx: break row.append("%-*s: %*d" % (captionwidth, invmap.get(idx, ""), numwidth, self[idx])) idx += 1 result.append(" | ".join(row)) row = [] return "\n".join(result) class UniqueIdGenerator(object): """A dictionary-like class that can be used to assign unique IDs to names (say, vertex names). Usage: >>> gen = UniqueIdGenerator() >>> gen["A"] 0 >>> gen["B"] 1 >>> gen["C"] 2 >>> gen["A"] # Retrieving already existing ID 0 >>> gen.add("D") # Synonym of gen["D"] 3 >>> len(gen) # Number of already used IDs 4 >>> "C" in gen True >>> "E" in gen False """ def __init__(self, id_generator=None, initial=None): """Creates a new unique ID generator. `id_generator` specifies how do we assign new IDs to elements that do not have an ID yet. If it is `None`, elements will be assigned integer identifiers starting from 0. If it is an integer, elements will be assigned identifiers starting from the given integer. If it is an iterator or generator, its `next` method will be called every time a new ID is needed.""" if id_generator is None: id_generator = 0 if isinstance(id_generator, int): import itertools self._generator = itertools.count(id_generator) else: self._generator = id_generator self._ids = {} if initial: for value in initial: self.add(value) def __contains__(self, item): """Checks whether `item` already has an ID or not.""" return item in self._ids def __getitem__(self, item): """Retrieves the ID corresponding to `item`. Generates a new ID for `item` if it is the first time we request an ID for it.""" try: return self._ids[item] except KeyError: self._ids[item] = self._generator.next() return self._ids[item] def __setitem__(self, item, value): """Overrides the ID for `item`.""" self._ids[item] = value def __len__(self): """"Returns the number of items""" return len(self._ids) def reverse_dict(self): """Returns the reverse mapping, i.e., the one that maps from generated IDs to their corresponding objects""" return dict((v, k) for k, v in self._ids.iteritems()) def values(self): """Returns the values stored so far. If the generator generates items according to the standard sorting order, the values returned will be exactly in the order they were added. This holds for integer IDs for instance (but for many other ID generators as well).""" return sorted(self._ids.keys(), key = self._ids.__getitem__) add = __getitem__ python-igraph-0.8.0/src/igraph/utils.py0000644000076500000240000003133013576365502020327 0ustar tamasstaff00000000000000# vim:ts=4:sw=4:sts=4:et # -*- coding: utf-8 -*- """Utility functions that cannot be categorised anywhere else. @undocumented: _is_running_in_ipython """ from contextlib import contextmanager try: from collections.abc import MutableMapping except ImportError: from collections import MutableMapping from ctypes import c_double, sizeof from itertools import chain import os import tempfile __all__ = ( "dbl_epsilon", "multidict", "named_temporary_file", "numpy_to_contiguous_memoryview", "rescale", "safemin", "safemax" ) __docformat__ = "restructuredtext en" __license__ = u"""\ Copyright (C) 2006-2012 Tamás Nepusz Pázmány Péter sétány 1/a, 1117 Budapest, Hungary This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA """ def _is_running_in_ipython(): """Internal function that determines whether igraph is running inside IPython or not.""" try: from IPython import get_ipython return get_ipython() is not None except ImportError: return False @contextmanager def named_temporary_file(*args, **kwds): """Context manager that creates a named temporary file and returns its name. All parameters are passed on to ``tempfile.mkstemp``, see its documentation for more info. """ handle, tmpfile = tempfile.mkstemp(*args, **kwds) os.close(handle) try: yield tmpfile finally: os.unlink(tmpfile) def numpy_to_contiguous_memoryview(obj): """Converts a NumPy array or matrix into a contiguous memoryview object that is suitable to be forwarded to the Graph constructor. This is used internally to allow us to use a NumPy array or matrix directly when constructing a Graph. """ # Deferred import to prevent a hard dependency on NumPy from numpy import float32, float64, require size = sizeof(c_double) if size == 8: dtype = float64 elif size == 4: dtype = float32 else: raise TypeError("size of C double (%d bytes) is not supported" % size) return memoryview(require(obj, dtype=dtype, requirements="AC")) def rescale(values, out_range=(0., 1.), in_range=None, clamp=False, scale=None): """Rescales a list of numbers into a given range. `out_range` gives the range of the output values; by default, the minimum of the original numbers in the list will be mapped to the first element in the output range and the maximum will be mapped to the second element. Elements between the minimum and maximum values in the input list will be interpolated linearly between the first and second values of the output range. `in_range` may be used to override which numbers are mapped to the first and second values of the output range. This must also be a tuple, where the first element will be mapped to the first element of the output range and the second element to the second. If `clamp` is ``True``, elements which are outside the given `out_range` after rescaling are clamped to the output range to ensure that no number will be outside `out_range` in the result. If `scale` is not ``None``, it will be called for every element of `values` and the rescaling will take place on the results instead. This can be used, for instance, to transform the logarithm of the original values instead of the actual values. A typical use-case is to map a range of values to color identifiers on a logarithmic scale. Scaling also applies to the `in_range` parameter if present. Examples: >>> rescale(range(5), (0, 8)) [0.0, 2.0, 4.0, 6.0, 8.0] >>> rescale(range(5), (2, 10)) [2.0, 4.0, 6.0, 8.0, 10.0] >>> rescale(range(5), (0, 4), (1, 3)) [-2.0, 0.0, 2.0, 4.0, 6.0] >>> rescale(range(5), (0, 4), (1, 3), clamp=True) [0.0, 0.0, 2.0, 4.0, 4.0] >>> rescale([0]*5, (1, 3)) [2.0, 2.0, 2.0, 2.0, 2.0] >>> from math import log10 >>> rescale([1, 10, 100, 1000, 10000], (0, 8), scale=log10) [0.0, 2.0, 4.0, 6.0, 8.0] >>> rescale([1, 10, 100, 1000, 10000], (0, 4), (10, 1000), scale=log10) [-2.0, 0.0, 2.0, 4.0, 6.0] """ if scale is not None: values = [scale(value) for value in values] if in_range is None: mi, ma = min(values), max(values) else: mi, ma = in_range if scale is not None: mi, ma = scale(mi), scale(ma) ratio = float(ma - mi) if not ratio: return [(out_range[0] + out_range[1]) / 2.] * len(values) min_out, max_out = map(float, out_range) ratio = (max_out - min_out) / ratio result = [(x - mi) * ratio + min_out for x in values] if clamp: return [max(min(x, max_out), min_out) for x in result] else: return result def str_to_orientation( value, reversed_horizontal=False, reversed_vertical=False ): """Tries to interpret a string as an orientation value. The following basic values are understood: ``left-right``, ``bottom-top``, ``right-left``, ``top-bottom``. Possible aliases are: - ``horizontal``, ``horiz``, ``h`` and ``lr`` for ``left-right`` - ``vertical``, ``vert``, ``v`` and ``tb`` for top-bottom. - ``lr`` for ``left-right``. - ``rl`` for ``right-left``. ``reversed_horizontal`` reverses the meaning of ``horizontal``, ``horiz`` and ``h`` to ``rl`` (instead of ``lr``); similarly, ``reversed_vertical`` reverses the meaning of ``vertical``, ``vert`` and ``v`` to ``bt`` (instead of ``tb``). Returns one of ``lr``, ``rl``, ``tb`` or ``bt``, or throws ``ValueError`` if the string cannot be interpreted as an orientation. """ aliases = { "left-right": "lr", "right-left": "rl", "top-bottom": "tb", "bottom-top": "bt", "top-down": "tb", "bottom-up": "bt", "top-bottom": "tb", "bottom-top": "bt", "td": "tb", "bu": "bt" } dir = ["lr", "rl"][reversed_horizontal] aliases.update(horizontal=dir, horiz=dir, h=dir) dir = ["tb", "bt"][reversed_vertical] aliases.update(vertical=dir, vert=dir, v=dir) result = aliases.get(value, value) if result not in ("lr", "rl", "tb", "bt"): raise ValueError("unknown orientation: %s" % result) return result def consecutive_pairs(iterable, circular=False): """Returns consecutive pairs of items from the given iterable. When `circular` is ``True``, the pair consisting of the last and first elements is also returned. Example: >>> list(consecutive_pairs(range(5))) [(0, 1), (1, 2), (2, 3), (3, 4)] >>> list(consecutive_pairs(range(5), circular=True)) [(0, 1), (1, 2), (2, 3), (3, 4), (4, 0)] >>> list(consecutive_pairs([])) [] >>> list(consecutive_pairs([], circular=True)) [] >>> list(consecutive_pairs([0])) [] >>> list(consecutive_pairs([0], circular=True)) [(0, 0)] """ it = iter(iterable) try: prev = it.next() except StopIteration: return first = prev for item in it: yield prev, item prev = item if circular: try: yield item, first except UnboundLocalError: yield first, first class multidict(MutableMapping): """A dictionary-like object that is customized to deal with multiple values for the same key. Each value in this dictionary will be a list. Methods which emulate the methods of a standard Python `dict` object will return or manipulate the first items of the lists only. Special methods are provided to deal with keys having multiple values. """ def __init__(self, *args, **kwds): self._dict = {} if len(args) > 1: raise ValueError( "%r expected at most 1 argument, got %d" % (self.__class__.__name__, len(args)) ) if args: args = args[0] self.update(args) self.update(kwds) def __contains__(self, key): """Returns whether there are any items associated to the given `key`.""" try: return len(self._dict[key]) > 0 except KeyError: return False def __delitem__(self, key): """Removes all the items associated to the given `key`.""" del self._dict[key] def __getitem__(self, key): """Returns an arbitrary item associated to the given key. Raises ``KeyError`` if no such key exists. Example: >>> d = multidict([("spam", "eggs"), ("spam", "bacon")]) >>> d["spam"] 'eggs' """ try: return self._dict[key][0] except IndexError: raise KeyError(key) def __iter__(self): """Iterates over the keys of the multidict.""" return iter(self._dict) def __len__(self): """Returns the number of distinct keys in this multidict.""" return len(self._dict) def __setitem__(self, key, value): """Sets the item associated to the given `key`. Any values associated to the key will be erased and replaced by `value`. Example: >>> d = multidict([("spam", "eggs"), ("spam", "bacon")]) >>> d["spam"] = "ham" >>> d["spam"] 'ham' """ self._dict[key] = [value] def add(self, key, value): """Adds `value` to the list of items associated to `key`. Example: >>> d = multidict() >>> d.add("spam", "ham") >>> d["spam"] 'ham' >>> d.add("spam", "eggs") >>> d.getlist("spam") ['ham', 'eggs'] """ try: self._dict[key].append(value) except KeyError: self._dict[key] = [value] def clear(self): """Removes all the items from the multidict.""" self._dict.clear() def get(self, key, default=None): """Returns an arbitrary item associated to the given `key`. If `key` does not exist or has zero associated items, `default` will be returned.""" try: items = self._dict[key] return items[0] except (KeyError, IndexError): return default def getlist(self, key): """Returns the list of values for the given `key`. An empty list will be returned if there is no such key.""" try: return self._dict[key] except KeyError: return [] def iterlists(self): """Iterates over ``(key, values)`` pairs where ``values`` is the list of values associated with ``key``.""" return self._dict.iteritems() def lists(self): """Returns a list of ``(key, values)`` pairs where ``values`` is the list of values associated with ``key``.""" return self._dict.items() def update(self, arg, **kwds): if hasattr(arg, "keys") and callable(arg.keys): for key in arg.keys(): self.add(key, arg[key]) else: for key, value in arg: self.add(key, value) for key, value in kwds.iteritems(): self.add(key, value) def safemax(iterable, default=0): """Safer variant of ``max()`` that returns a default value if the iterable is empty. Example: >>> safemax([-5, 6, 4]) 6 >>> safemax([]) 0 >>> safemax((), 2) 2 """ it = iter(iterable) try: first = it.next() except StopIteration: return default else: return max(chain([first], it)) def safemin(iterable, default=0): """Safer variant of ``min()`` that returns a default value if the iterable is empty. Example: >>> safemin([-5, 6, 4]) -5 >>> safemin([]) 0 >>> safemin((), 2) 2 """ it = iter(iterable) try: first = it.next() except StopIteration: return default else: return min(chain([first], it)) def dbl_epsilon(): """Approximates the machine epsilon value for doubles.""" epsilon = 1.0 while 1.0 + epsilon / 2.0 != 1.0: epsilon /= 2 return epsilon dbl_epsilon = dbl_epsilon() python-igraph-0.8.0/src/igraph/statistics.py0000644000076500000240000005536013104627150021355 0ustar tamasstaff00000000000000# vim:ts=4:sw=4:sts=4:et # -*- coding: utf-8 -*- """ Statistics related stuff in igraph """ __license__ = u"""\ Copyright (C) 2006-2012 Tamas Nepusz Pázmány Péter sétány 1/a, 1117 Budapest, Hungary This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA """ import math __all__ = ["FittedPowerLaw", "Histogram", "RunningMean", "mean", "median", \ "percentile", "quantile", "power_law_fit"] class FittedPowerLaw(object): """Result of fitting a power-law to a vector of samples Example: >>> result = power_law_fit([1, 2, 3, 4, 5, 6]) >>> result # doctest:+ELLIPSIS FittedPowerLaw(continuous=False, alpha=2.425828..., xmin=3.0, L=-7.54633..., D=0.2138..., p=0.99311...) >>> print result # doctest:+ELLIPSIS Fitted power-law distribution on discrete data Exponent (alpha) = 2.425828 Cutoff (xmin) = 3.000000 Log-likelihood = -7.546337 H0: data was drawn from the fitted distribution KS test statistic = 0.213817 p-value = 0.993111 H0 could not be rejected at significance level 0.05 >>> result.alpha # doctest:+ELLIPSIS 2.425828... >>> result.xmin 3.0 >>> result.continuous False """ def __init__(self, continuous, alpha, xmin, L, D, p): self.continuous = continuous self.xmin = xmin self.alpha = alpha self.L = L self.D = D self.p = p def __repr__(self): return "%s(continuous=%r, alpha=%r, xmin=%r, L=%r, D=%r, p=%r)" % \ (self.__class__.__name__, self.continuous, self.alpha, \ self.xmin, self.L, self.D, self.p) def __str__(self): return self.summary(significance=0.05) def summary(self, significance=0.05): """Returns the summary of the power law fit. @param significance: the significance level of the Kolmogorov-Smirnov test used to decide whether the input data could have come from the fitted distribution @return: the summary as a string """ result = ["Fitted power-law distribution on %s data" % \ ("discrete", "continuous")[bool(self.continuous)]] result.append("") result.append("Exponent (alpha) = %f" % self.alpha) result.append("Cutoff (xmin) = %f" % self.xmin) result.append("") result.append("Log-likelihood = %f" % self.L) result.append("") result.append("H0: data was drawn from the fitted distribution") result.append("") result.append("KS test statistic = %f" % self.D) result.append("p-value = %f" % self.p) result.append("") if self.p < significance: result.append("H0 rejected at significance level %g" \ % significance) else: result.append("H0 could not be rejected at significance "\ "level %g" % significance) return "\n".join(result) class Histogram(object): """Generic histogram class for real numbers Example: >>> h = Histogram(5) # Initializing, bin width = 5 >>> h << [2,3,2,7,8,5,5,0,7,9] # Adding more items >>> print h N = 10, mean +- sd: 4.8000 +- 2.9740 [ 0, 5): **** (4) [ 5, 10): ****** (6) """ def __init__(self, bin_width = 1, data = None): """Initializes the histogram with the given data set. @param bin_width: the bin width of the histogram. @param data: the data set to be used. Must contain real numbers. """ self._bin_width = float(bin_width) self._bins = None self._min, self._max = None, None self._running_mean = RunningMean() self.clear() if data: self.add_many(data) def _get_bin(self, num, create = False): """Returns the bin index corresponding to the given number. @param num: the number for which the bin is being sought @param create: whether to create a new bin if no bin exists yet. @return: the index of the bin or C{None} if no bin exists yet and {create} is C{False}.""" if len(self._bins) == 0: if not create: result = None else: self._min = int(num/self._bin_width)*self._bin_width self._max = self._min+self._bin_width self._bins = [0] result = 0 return result if num >= self._min: binidx = int((num-self._min)/self._bin_width) if binidx < len(self._bins): return binidx if not create: return None extra_bins = binidx-len(self._bins)+1 self._bins.extend([0]*extra_bins) self._max = self._min + len(self._bins)*self._bin_width return binidx if not create: return None extra_bins = int(math.ceil((self._min-num)/self._bin_width)) self._bins[0:0] = [0]*extra_bins self._min -= extra_bins*self._bin_width self._max = self._min + len(self._bins)*self._bin_width return 0 @property def n(self): """Returns the number of elements in the histogram""" return len(self._running_mean) @property def mean(self): """Returns the mean of the elements in the histogram""" return self._running_mean.mean # pylint: disable-msg=C0103 @property def sd(self): """Returns the standard deviation of the elements in the histogram""" return self._running_mean.sd @property def var(self): """Returns the variance of the elements in the histogram""" return self._running_mean.var def add(self, num, repeat=1): """Adds a single number to the histogram. @param num: the number to be added @param repeat: number of repeated additions """ num = float(num) binidx = self._get_bin(num, True) self._bins[binidx] += repeat self._running_mean.add(num, repeat) def add_many(self, data): """Adds a single number or the elements of an iterable to the histogram. @param data: the data to be added""" try: iterator = iter(data) except TypeError: iterator = iter([data]) for x in iterator: self.add(x) __lshift__ = add_many def clear(self): """Clears the collected data""" self._bins = [] self._min, self._max = None, None self._running_mean = RunningMean() def bins(self): """Generator returning the bins of the histogram in increasing order @return: a tuple with the following elements: left bound, right bound, number of elements in the bin""" x = self._min for elem in self._bins: yield (x, x+self._bin_width, elem) x += self._bin_width def __plot__(self, context, bbox, _, **kwds): """Plotting support""" from igraph.drawing.coord import DescartesCoordinateSystem coord_system = DescartesCoordinateSystem(context, bbox, \ (kwds.get("min", self._min), 0, \ kwds.get("max", self._max), kwds.get("max_value", max(self._bins)) )) # Draw the boxes context.set_line_width(1) context.set_source_rgb(1., 0., 0.) x = self._min for value in self._bins: top_left_x, top_left_y = coord_system.local_to_context(x, value) x += self._bin_width bottom_right_x, bottom_right_y = coord_system.local_to_context(x, 0) context.rectangle(top_left_x, top_left_y, \ bottom_right_x - top_left_x, \ bottom_right_y - top_left_y) context.fill() # Draw the axes coord_system.draw() def to_string(self, max_width=78, show_bars=True, show_counts=True): """Returns the string representation of the histogram. @param max_width: the maximal width of each line of the string This value may not be obeyed if it is too small. @param show_bars: specify whether the histogram bars should be shown @param show_counts: specify whether the histogram counts should be shown. If both I{show_bars} and I{show_counts} are C{False}, only a general descriptive statistics (number of elements, mean and standard deviation) is shown. """ if self._min is None or self._max is None: return "N = 0" # Determine how many decimal digits should we use if int(self._min) == self._min and int(self._bin_width) == self._bin_width: number_format = "%d" else: number_format = "%.3f" num_length = max(len(number_format % self._min), \ len(number_format % self._max)) number_format = "%" + str(num_length) + number_format[1:] format_string = "[%s, %s): %%s" % (number_format, number_format) # Calculate the scale of the bars on the histogram if show_bars: maxval = max(self._bins) if show_counts: maxval_length = len(str(maxval)) scale = maxval // (max_width-2*num_length-maxval_length-9) else: scale = maxval // (max_width-2*num_length-6) scale = max(scale, 1) result = ["N = %d, mean +- sd: %.4f +- %.4f" % \ (self.n, self.mean, self.sd)] if show_bars: # Print the bars if scale > 1: result.append("Each * represents %d items" % scale) if show_counts: format_string += " (%d)" for left, right, cnt in self.bins(): result.append(format_string % (left, right, '*'*(cnt//scale), cnt)) else: for left, right, cnt in self.bins(): result.append(format_string % (left, right, '*'*(cnt//scale))) elif show_counts: # Print the counts only for left, right, cnt in self.bins(): result.append(format_string % (left, right, cnt)) return "\n".join(result) def __str__(self): return self.to_string() class RunningMean(object): """Running mean calculator. This class can be used to calculate the mean of elements from a list, tuple, iterable or any other data source. The mean is calculated on the fly without explicitly summing the values, so it can be used for data sets with arbitrary item count. Also capable of returning the standard deviation (also calculated on the fly) """ # pylint: disable-msg=C0103 def __init__(self, items=None, n=0.0, mean=0.0, sd=0.0): """RunningMean(items=None, n=0.0, mean=0.0, sd=0.0) Initializes the running mean calculator. There are two possible ways to initialize the calculator. First, one can provide an iterable of items; alternatively, one can specify the number of items, the mean and the standard deviation if we want to continue an interrupted calculation. @param items: the items that are used to initialize the running mean calcuator. If C{items} is given, C{n}, C{mean} and C{sd} must be zeros. @param n: the initial number of elements already processed. If this is given, C{items} must be C{None}. @param mean: the initial mean. If this is given, C{items} must be C{None}. @param sd: the initial standard deviation. If this is given, C{items} must be C{None}.""" if items is not None: if n != 0 or mean != 0 or sd != 0: raise ValueError("n, mean and sd must be zeros if items is not None") self.clear() self.add_many(items) else: self._nitems = float(n) self._mean = float(mean) if n > 1: self._sqdiff = float(sd) ** 2 * float(n-1) self._sd = float(sd) else: self._sqdiff = 0.0 self._sd = 0.0 def add(self, value, repeat=1): """RunningMean.add(value, repeat=1) Adds the given value to the elements from which we calculate the mean and the standard deviation. @param value: the element to be added @param repeat: number of repeated additions """ repeat = int(repeat) self._nitems += repeat delta = value - self._mean self._mean += (repeat*delta / self._nitems) self._sqdiff += (repeat*delta) * (value - self._mean) if self._nitems > 1: self._sd = (self._sqdiff / (self._nitems-1)) ** 0.5 def add_many(self, values): """RunningMean.add(values) Adds the values in the given iterable to the elements from which we calculate the mean. Can also accept a single number. The left shift (C{<<}) operator is aliased to this function, so you can use it to add elements as well: >>> rm=RunningMean() >>> rm << [1,2,3,4] >>> rm.result # doctest:+ELLIPSIS (2.5, 1.290994...) @param values: the element(s) to be added @type values: iterable""" try: iterator = iter(values) except TypeError: iterator = iter([values]) for value in iterator: self.add(value) def clear(self): """Resets the running mean calculator.""" self._nitems, self._mean = 0.0, 0.0 self._sqdiff, self._sd = 0.0, 0.0 @property def result(self): """Returns the current mean and standard deviation as a tuple""" return self._mean, self._sd @property def mean(self): """Returns the current mean""" return self._mean @property def sd(self): """Returns the current standard deviation""" return self._sd @property def var(self): """Returns the current variation""" return self._sd ** 2 def __repr__(self): return "%s(n=%r, mean=%r, sd=%r)" % \ (self.__class__.__name__, int(self._nitems), self._mean, self._sd) def __str__(self): return "Running mean (N=%d, %f +- %f)" % \ (self._nitems, self._mean, self._sd) __lshift__ = add_many def __float__(self): return float(self._mean) def __int__(self): return int(self._mean) def __long__(self): return long(self._mean) def __complex__(self): return complex(self._mean) def __len__(self): return int(self._nitems) def mean(xs): """Returns the mean of an iterable. Example: >>> mean([1, 4, 7, 11]) 5.75 @param xs: an iterable yielding numbers. @return: the mean of the numbers provided by the iterable. @see: RunningMean() if you also need the variance or the standard deviation """ return RunningMean(xs).mean def median(xs, sort=True): """Returns the median of an unsorted or sorted numeric vector. @param xs: the vector itself. @param sort: whether to sort the vector. If you know that the vector is sorted already, pass C{False} here. @return: the median, which will always be a float, even if the vector contained integers originally. """ if sort: xs = sorted(xs) mid = int(len(xs) / 2) if 2 * mid == len(xs): return float(xs[mid-1] + xs[mid]) / 2 else: return float(xs[mid]) def percentile(xs, p=(25, 50, 75), sort=True): """Returns the pth percentile of an unsorted or sorted numeric vector. This is equivalent to calling quantile(xs, p/100.0); see L{quantile} for more details on the calculation. Example: >>> round(percentile([15, 20, 40, 35, 50], 40), 2) 26.0 >>> for perc in percentile([15, 20, 40, 35, 50], (0, 25, 50, 75, 100)): ... print "%.2f" % perc ... 15.00 17.50 35.00 45.00 50.00 @param xs: the vector itself. @param p: the percentile we are looking for. It may also be a list if you want to calculate multiple quantiles with a single call. The default value calculates the 25th, 50th and 75th percentile. @param sort: whether to sort the vector. If you know that the vector is sorted already, pass C{False} here. @return: the pth percentile, which will always be a float, even if the vector contained integers originally. If p is a list, the result will also be a list containing the percentiles for each item in the list. """ if hasattr(p, "__iter__"): return quantile(xs, (x/100.0 for x in p), sort) return quantile(xs, p/100.0, sort) def power_law_fit(data, xmin=None, method="auto", return_alpha_only=False): """Fitting a power-law distribution to empirical data @param data: the data to fit, a list containing integer values @param xmin: the lower bound for fitting the power-law. If C{None}, the optimal xmin value will be estimated as well. Zero means that the smallest possible xmin value will be used. @param method: the fitting method to use. The following methods are implemented so far: - C{continuous}, C{hill}: exact maximum likelihood estimation when the input data comes from a continuous scale. This is known as the Hill estimator. The statistical error of this estimator is M{(alpha-1) / sqrt(n)}, where alpha is the estimated exponent and M{n} is the number of data points above M{xmin}. The estimator is known to exhibit a small finite sample-size bias of order M{O(n^-1)}, which is small when M{n > 100}. igraph will try to compensate for the finite sample size if n is small. - C{discrete}: exact maximum likelihood estimation when the input comes from a discrete scale (see Clauset et al among the references). - C{auto}: exact maximum likelihood estimation where the continuous method is used if the input vector contains at least one fractional value and the discrete method is used if the input vector contains integers only. @return: a L{FittedPowerLaw} object. The fitted C{xmin} value and the power-law exponent can be queried from the C{xmin} and C{alpha} properties of the returned object. @newfield ref: Reference @ref: MEJ Newman: Power laws, Pareto distributions and Zipf's law. Contemporary Physics 46, 323-351 (2005) @ref: A Clauset, CR Shalizi, MEJ Newman: Power-law distributions in empirical data. E-print (2007). arXiv:0706.1062""" from igraph._igraph import _power_law_fit if xmin is None or xmin < 0: xmin = -1 method = method.lower() if method not in ("continuous", "hill", "discrete", "auto"): raise ValueError("unknown method: %s" % method) force_continuous = method in ("continuous", "hill") fit = FittedPowerLaw(*_power_law_fit(data, xmin, force_continuous)) if return_alpha_only: from igraph import deprecated deprecated("The return_alpha_only keyword argument of power_law_fit is "\ "deprecated from igraph 0.7 and will be removed in igraph 0.8") return fit.alpha else: return fit def quantile(xs, q=(0.25, 0.5, 0.75), sort=True): """Returns the qth quantile of an unsorted or sorted numeric vector. There are a number of different ways to calculate the sample quantile. The method implemented by igraph is the one recommended by NIST. First we calculate a rank n as q(N+1), where N is the number of items in xs, then we split n into its integer component k and decimal component d. If k <= 1, we return the first element; if k >= N, we return the last element, otherwise we return the linear interpolation between xs[k-1] and xs[k] using a factor d. Example: >>> round(quantile([15, 20, 40, 35, 50], 0.4), 2) 26.0 @param xs: the vector itself. @param q: the quantile we are looking for. It may also be a list if you want to calculate multiple quantiles with a single call. The default value calculates the 25th, 50th and 75th percentile. @param sort: whether to sort the vector. If you know that the vector is sorted already, pass C{False} here. @return: the qth quantile, which will always be a float, even if the vector contained integers originally. If q is a list, the result will also be a list containing the quantiles for each item in the list. """ if not xs: raise ValueError("xs must not be empty") if sort: xs = sorted(xs) if hasattr(q, "__iter__"): qs = q return_single = False else: qs = [q] return_single = True result = [] for q in qs: if q < 0 or q > 1: raise ValueError("q must be between 0 and 1") n = float(q) * (len(xs)+1) k, d = int(n), n-int(n) if k >= len(xs): result.append(xs[-1]) elif k < 1: result.append(xs[0]) else: result.append((1-d) * xs[k-1] + d * xs[k]) if return_single: result = result[0] return result def sd(xs): """Returns the standard deviation of an iterable. Example: >>> sd([1, 4, 7, 11]) #doctest:+ELLIPSIS 4.2720... @param xs: an iterable yielding numbers. @return: the standard deviation of the numbers provided by the iterable. @see: RunningMean() if you also need the mean """ return RunningMean(xs).sd def var(xs): """Returns the variance of an iterable. Example: >>> var([1, 4, 8, 11]) #doctest:+ELLIPSIS 19.333333... @param xs: an iterable yielding numbers. @return: the variance of the numbers provided by the iterable. @see: RunningMean() if you also need the mean """ return RunningMean(xs).var python-igraph-0.8.0/src/igraph/remote/0000755000076500000240000000000013617375000020076 5ustar tamasstaff00000000000000python-igraph-0.8.0/src/igraph/remote/__init__.py0000644000076500000240000000010613104627150022201 0ustar tamasstaff00000000000000"""Classes that help igraph communicate with remote applications.""" python-igraph-0.8.0/src/igraph/remote/gephi.py0000644000076500000240000002630513104627150021547 0ustar tamasstaff00000000000000# vim:ts=4:sw=4:sts=4:et # -*- coding: utf-8 -*- """Classes that help igraph communicate with Gephi (http://www.gephi.org).""" from igraph.compat import property import urllib2 try: # JSON is optional so we don't blow up with Python < 2.6 import json except ImportError: try: # Try with simplejson for Python < 2.6 import simplejson as json except ImportError: # No simplejson either from igraph.drawing.utils import FakeModule json = FakeModule() __all__ = ["GephiConnection", "GephiGraphStreamer", "GephiGraphStreamingAPIFormat"] __docformat__ = "restructuredtext en" __license__ = u"""\ Copyright (C) 2006-2012 Tamás Nepusz Pázmány Péter sétány 1/a, 1117 Budapest, Hungary This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA """ class GephiConnection(object): """Object that represents a connection to a Gephi master server.""" def __init__(self, url=None, host="127.0.0.1", port=8080, workspace=1): """Constructs a connection to a Gephi master server. The connection object can be constructed either by specifying the `url` directly, or by specifying the `host`, `port` and `workspace` arguments. The latter three are evaluated only if `url` is None; otherwise the `url` will take precedence. The `url` argument does not have to include the operation (e.g., ``?operation=updateGraph``); the connection will take care of it. E.g., if you wish to connect to workspace 2 in a local Gephi instance on port 7341, the correct form to use for the `url` is as follows:: http://localhost:7341/workspace0 """ self._pending_operations = [] self._autoflush_threshold = 1024 self.url = url or self._construct_default_url(host, port, workspace) def __del__(self): try: self.close() except urllib2.URLError: # Happens when Gephi is closed before the connection is destroyed pass def _construct_default_url(self, host, port, workspace): return "http://%s:%d/workspace%d" % (host, port, workspace) def close(self): """Flushes all the pending operations to the Gephi master server in a single request.""" self.flush() def flush(self): """Flushes all the pending operations to the Gephi master server in a single request.""" data = b"".join(self._pending_operations) self._pending_operations = [] conn = urllib2.urlopen(self._update_url, data=data) return conn.read() @property def url(self): """The URL of the Gephi workspace where the data will be sent.""" return self._url_root @url.setter def url(self, value): self._url_root = value self._get_url = self._url_root + "?operation=getGraph" self._update_url = self._url_root + "?operation=updateGraph" def write(self, data): """Sends the given raw data to the Gephi streaming master server in an HTTP POST request.""" self._pending_operations.append(data) if len(self._pending_operations) >= self._autoflush_threshold: self.flush() def __repr__(self): return "%s(url=%r)" % (self.__class__.__name__, self.url) class GephiGraphStreamingAPIFormat(object): """Object that implements the Gephi graph streaming API format and returns Python objects corresponding to the events defined in the API. """ def get_add_node_event(self, identifier, attributes={}): """Generates a Python object corresponding to the event that adds a node with the given identifier and attributes in the Gephi graph streaming API. Example:: >>> api = GephiGraphStreamingAPIFormat() >>> api.get_add_node_event("spam") {'an': {'spam': {}}} >>> api.get_add_node_event("spam", dict(ham="eggs")) {'an': {'spam': {'ham': 'eggs'}}} """ return {"an": {identifier: attributes}} def get_add_edge_event(self, identifier, source, target, directed, attributes={}): """Generates a Python object corresponding to the event that adds an edge with the given source, target, directednessr and attributes in the Gephi graph streaming API. """ result = dict(attributes) result["source"] = source result["target"] = target result["directed"] = bool(directed) return {"ae": {identifier: result}} def get_change_node_event(self, identifier, attributes): """Generates a Python object corresponding to the event that changes the attributes of some node in the Gephi graph streaming API. The given attributes are merged into the existing ones; use C{None} as the attribute value to delete a given attribute. Example:: >>> api = GephiGraphStreamingAPIFormat() >>> api.get_change_node_event("spam", dict(ham="eggs")) {'cn': {'spam': {'ham': 'eggs'}}} >>> api.get_change_node_event("spam", dict(ham=None)) {'cn': {'spam': {'ham': None}}} """ return {"cn": {identifier: attributes}} def get_change_edge_event(self, identifier, attributes): """Generates a Python object corresponding to the event that changes the attributes of some edge in the Gephi graph streaming API. The given attributes are merged into the existing ones; use C{None} as the attribute value to delete a given attribute. Example:: >>> api = GephiGraphStreamingAPIFormat() >>> api.get_change_edge_event("spam", dict(ham="eggs")) {'ce': {'spam': {'ham': 'eggs'}}} >>> api.get_change_edge_event("spam", dict(ham=None)) {'ce': {'spam': {'ham': None}}} """ return {"ce": {identifier: attributes}} def get_delete_node_event(self, identifier): """Generates a Python object corresponding to the event that deletes a node with the given identifier in the Gephi graph streaming API. Example:: >>> api = GephiGraphStreamingAPIFormat() >>> api.get_delete_node_event("spam") {'dn': {'spam': {}}} """ return {"dn": {identifier: {}}} def get_delete_edge_event(self, identifier): """Generates a Python object corresponding to the event that deletes an edge with the given identifier in the Gephi graph streaming API. Example:: >>> api = GephiGraphStreamingAPIFormat() >>> api.get_delete_edge_event("spam:ham") {'de': {'spam:ham': {}}} """ return {"de": {identifier: {}}} class GephiGraphStreamer(object): """Class that produces JSON event objects that stream an igraph graph to Gephi using the Gephi Graph Streaming API. The Gephi graph streaming format is a simple JSON-based format that can be used to post mutations to a graph (i.e. node and edge additions, removals and updates) to a remote component. For instance, one can open up Gephi (http://www.gephi.org}), install the Gephi graph streaming plugin and then send a graph from igraph straight into the Gephi window by using `GephiGraphStreamer` with the appropriate URL where Gephi is listening. Example:: >>> from cStringIO import StringIO >>> from igraph import Graph >>> buf = StringIO() >>> streamer = GephiGraphStreamer() >>> graph = Graph.Formula("A --> B, B --> C") >>> streamer.post(graph, buf) >>> print buf.getvalue() # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE {"an": {"igraph:...:v:0": {"name": "A"}}} {"an": {"igraph:...:v:1": {"name": "B"}}} {"an": {"igraph:...:v:2": {"name": "C"}}} {"ae": {"igraph:...:e:0:1": {...}}} {"ae": {"igraph:...:e:1:2": {...}}} """ def __init__(self, encoder=None): """Constructs a Gephi graph streamer that will post graphs to a given file-like object or a Gephi connection. `encoder` must either be ``None`` or an instance of ``json.JSONEncoder`` and it must contain the JSON encoder to be used when posting JSON objects. """ self.encoder = encoder or json.JSONEncoder(ensure_ascii=True) self.format = GephiGraphStreamingAPIFormat() def iterjsonobj(self, graph): """Iterates over the JSON objects that build up the graph using the Gephi graph streaming API. The objects returned from this function are Python objects; they must be formatted with ``json.dumps`` before sending them to the destination.""" # Construct a unique ID prefix id_prefix = "igraph:%s" % (hex(id(graph)), ) # Add the vertices add_node = self.format.get_add_node_event for vertex in graph.vs: yield add_node("%s:v:%d" % (id_prefix, vertex.index), vertex.attributes()) # Add the edges add_edge = self.format.get_add_edge_event directed = graph.is_directed() for edge in graph.es: yield add_edge("%s:e:%d:%d" % (id_prefix, edge.source, edge.target), "%s:v:%d" % (id_prefix, edge.source), "%s:v:%d" % (id_prefix, edge.target), directed, edge.attributes()) def post(self, graph, destination, encoder=None): """Posts the given graph to the destination of the streamer using the given JSON encoder. When `encoder` is ``None``, it falls back to the default JSON encoder of the streamer in the `encoder` property. `destination` must be a file-like object or an instance of `GephiConnection`. """ encoder = encoder or self.encoder for jsonobj in self.iterjsonobj(graph): self.send_event(jsonobj, destination, encoder=encoder, flush=False) destination.flush() def send_event(self, event, destination, encoder=None, flush=True): """Sends a single JSON event to the given destination using the given JSON encoder. When `encoder` is ``None``, it falls back to the default JSON encoder of the streamer in the `encoder` property. `destination` must be a file-like object or an instance of `GephiConnection`. The method flushes the destination after sending the event. If you want to avoid this (e.g., because you are sending many events), set `flush` to ``False``. """ encoder = encoder or self.encoder destination.write(encoder.encode(event).encode("utf-8")) destination.write(b"\r\n") if flush: destination.flush() python-igraph-0.8.0/src/_igraph/0000755000076500000240000000000013617375000016742 5ustar tamasstaff00000000000000python-igraph-0.8.0/src/_igraph/edgeobject.c0000644000076500000240000005545313104627150021212 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim: set ts=2 sw=2 sts=2 et: */ /* IGraph library. Copyright (C) 2006-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "attributes.h" #include "edgeobject.h" #include "error.h" #include "graphobject.h" #include "pyhelpers.h" #include "py2compat.h" #include "vertexobject.h" /** * \ingroup python_interface * \defgroup python_interface_edge Edge object */ PyTypeObject igraphmodule_EdgeType; /** * \ingroup python_interface_edge * \brief Checks whether the given Python object is an edge */ int igraphmodule_Edge_Check(PyObject* obj) { if (!obj) return 0; return PyObject_IsInstance(obj, (PyObject*)(&igraphmodule_EdgeType)); } /** * \ingroup python_interface_edge * \brief Checks whether the index in the given edge object is a valid one. * \return nonzero if the edge object is valid. Raises an appropriate Python * exception and returns zero if the edge object is invalid. */ int igraphmodule_Edge_Validate(PyObject* obj) { igraph_integer_t n; igraphmodule_EdgeObject *self; igraphmodule_GraphObject *graph; if (!igraphmodule_Edge_Check(obj)) { PyErr_SetString(PyExc_TypeError, "object is not an Edge"); return 0; } self = (igraphmodule_EdgeObject*)obj; graph = self->gref; if (graph == 0) { PyErr_SetString(PyExc_ValueError, "Edge object refers to a null graph"); return 0; } if (self->idx < 0) { PyErr_SetString(PyExc_ValueError, "Edge object refers to a negative edge index"); return 0; } n = igraph_ecount(&graph->g); if (self->idx >= n) { PyErr_SetString(PyExc_ValueError, "Edge object refers to a nonexistent edge"); return 0; } return 1; } /** * \ingroup python_interface_edge * \brief Allocates a new Python edge object * \param gref weak reference of the \c igraph.Graph being referenced by the edge * \param idx the index of the edge * * \warning \c igraph references its edges by indices, so if * you delete some edges from the graph, the edge indices will * change. Since the \c igraph.Edge objects do not follow these * changes, your existing edge objects will point to elsewhere * (or they might even get invalidated). */ PyObject* igraphmodule_Edge_New(igraphmodule_GraphObject *gref, igraph_integer_t idx) { igraphmodule_EdgeObject* self; self=PyObject_New(igraphmodule_EdgeObject, &igraphmodule_EdgeType); if (self) { RC_ALLOC("Edge", self); Py_INCREF(gref); self->gref=gref; self->idx=idx; self->hash=-1; } return (PyObject*)self; } /** * \ingroup python_interface_edge * \brief Clears the edge's subobject (before deallocation) */ int igraphmodule_Edge_clear(igraphmodule_EdgeObject *self) { PyObject *tmp; tmp=(PyObject*)self->gref; self->gref=NULL; Py_XDECREF(tmp); return 0; } /** * \ingroup python_interface_edge * \brief Deallocates a Python representation of a given edge object */ void igraphmodule_Edge_dealloc(igraphmodule_EdgeObject* self) { igraphmodule_Edge_clear(self); RC_DEALLOC("Edge", self); PyObject_Del((PyObject*)self); } /** \ingroup python_interface_edge * \brief Formats an \c igraph.Edge object as a string * * \return the formatted textual representation as a \c PyObject */ PyObject* igraphmodule_Edge_repr(igraphmodule_EdgeObject *self) { PyObject *s; PyObject *attrs; #ifndef IGRAPH_PYTHON3 PyObject *grepr, *drepr; #endif attrs = igraphmodule_Edge_attributes(self); if (attrs == 0) return NULL; #ifdef IGRAPH_PYTHON3 s = PyUnicode_FromFormat("igraph.Edge(%R, %ld, %R)", (PyObject*)self->gref, (long int)self->idx, attrs); Py_DECREF(attrs); #else grepr=PyObject_Repr((PyObject*)self->gref); drepr=PyObject_Repr(attrs); Py_DECREF(attrs); if (!grepr || !drepr) { Py_XDECREF(grepr); Py_XDECREF(drepr); return NULL; } s=PyString_FromFormat("igraph.Edge(%s, %ld, %s)", PyString_AsString(grepr), (long int)self->idx, PyString_AsString(drepr)); Py_DECREF(grepr); Py_DECREF(drepr); #endif return s; } /** \ingroup python_interface_edge * \brief Returns the hash code of the edge */ Py_hash_t igraphmodule_Edge_hash(igraphmodule_EdgeObject* self) { Py_hash_t hash_graph; Py_hash_t hash_index; Py_hash_t result; PyObject* index_o; if (self->hash != -1) return self->hash; index_o = PyInt_FromLong((long int)self->idx); if (index_o == 0) return -1; hash_index = PyObject_Hash(index_o); Py_DECREF(index_o); if (hash_index == -1) return -1; /* Graph objects are unhashable from Python so we cannot call PyObject_Hash * directly. */ hash_graph = igraphmodule_Py_HashPointer(self->gref); if (hash_graph == -1) return -1; result = hash_graph ^ hash_index; if (result == -1) result = 590923713U; self->hash = result; return result; } /** \ingroup python_interface_edge * \brief Rich comparison of an edge with another */ PyObject* igraphmodule_Edge_richcompare(igraphmodule_EdgeObject *a, PyObject *b, int op) { igraphmodule_EdgeObject* self = a; igraphmodule_EdgeObject* other; if (!igraphmodule_Edge_Check(b)) Py_RETURN_NOTIMPLEMENTED; other = (igraphmodule_EdgeObject*)b; if (self->gref != other->gref) Py_RETURN_FALSE; switch (op) { case Py_EQ: Py_RETURN(self->idx == other->idx); case Py_NE: Py_RETURN(self->idx != other->idx); case Py_LE: Py_RETURN(self->idx <= other->idx); case Py_LT: Py_RETURN(self->idx < other->idx); case Py_GE: Py_RETURN(self->idx >= other->idx); case Py_GT: Py_RETURN(self->idx > other->idx); default: Py_RETURN_NOTIMPLEMENTED; } } /** \ingroup python_interface_edge * \brief Returns the number of edge attributes */ Py_ssize_t igraphmodule_Edge_attribute_count(igraphmodule_EdgeObject* self) { igraphmodule_GraphObject *o = self->gref; if (!o) return 0; if (!((PyObject**)o->g.attr)[1]) return 0; return PyDict_Size(((PyObject**)o->g.attr)[1]); } /** \ingroup python_interface_edge * \brief Returns the list of attribute names */ PyObject* igraphmodule_Edge_attribute_names(igraphmodule_EdgeObject* self) { if (!self->gref) return NULL; return igraphmodule_Graph_edge_attributes(self->gref); } /** \ingroup python_interface_edge * \brief Returns a dict with attribute names and values */ PyObject* igraphmodule_Edge_attributes(igraphmodule_EdgeObject* self) { igraphmodule_GraphObject *o = self->gref; PyObject *names, *dict; long int i, n; if (!igraphmodule_Edge_Validate((PyObject*)self)) return 0; dict=PyDict_New(); if (!dict) return NULL; names=igraphmodule_Graph_edge_attributes(o); if (!names) { Py_DECREF(dict); return NULL; } n = PyList_Size(names); for (i=0; ig.attr)[ATTRHASH_IDX_EDGE], name); if (dictit) { PyObject *value = PyList_GetItem(dictit, self->idx); if (value) { /* no need to Py_INCREF, PyDict_SetItem will do that */ PyDict_SetItem(dict, name, value); } } } } Py_DECREF(names); return dict; } /** * \ingroup python_interface_edge * \brief Updates some attributes of an edge * * \param self the edge object * \param args positional arguments * \param kwds keyword arguments */ PyObject* igraphmodule_Edge_update_attributes(PyObject* self, PyObject* args, PyObject* kwds) { return igraphmodule_Vertex_update_attributes(self, args, kwds); } /** \ingroup python_interface_edge * \brief Returns the corresponding value to a given attribute of the edge * \param self the edge object * \param s the attribute name to be queried */ PyObject* igraphmodule_Edge_get_attribute(igraphmodule_EdgeObject* self, PyObject* s) { igraphmodule_GraphObject *o = self->gref; PyObject* result; if (!igraphmodule_Edge_Validate((PyObject*)self)) return 0; if (!igraphmodule_attribute_name_check(s)) return 0; result=PyDict_GetItem(((PyObject**)o->g.attr)[2], s); if (result) { /* result is a list, so get the element with index self->idx */ if (!PyList_Check(result)) { PyErr_SetString(igraphmodule_InternalError, "Edge attribute dict member is not a list"); return NULL; } result=PyList_GetItem(result, self->idx); Py_INCREF(result); return result; } /* result is NULL, check whether there was an error */ if (!PyErr_Occurred()) PyErr_SetString(PyExc_KeyError, "Attribute does not exist"); return NULL; } /** \ingroup python_interface_edge * \brief Sets the corresponding value of a given attribute of the edge * \param self the edge object * \param k the attribute name to be set * \param v the value to be set * \return 0 if everything's ok, -1 in case of error */ int igraphmodule_Edge_set_attribute(igraphmodule_EdgeObject* self, PyObject* k, PyObject* v) { igraphmodule_GraphObject *o=self->gref; PyObject* result; int r; if (!igraphmodule_Edge_Validate((PyObject*)self)) return -1; if (!igraphmodule_attribute_name_check(k)) return -1; if (v==NULL) // we are deleting attribute return PyDict_DelItem(((PyObject**)o->g.attr)[2], k); result=PyDict_GetItem(((PyObject**)o->g.attr)[2], k); if (result) { /* result is a list, so set the element with index self->idx */ if (!PyList_Check(result)) { PyErr_SetString(igraphmodule_InternalError, "Vertex attribute dict member is not a list"); return -1; } /* we actually don't own a reference here to v, so we must increase * its reference count, because PyList_SetItem will "steal" a reference! * It took me 1.5 hours between London and Manchester to figure it out */ Py_INCREF(v); r=PyList_SetItem(result, self->idx, v); if (r == -1) { Py_DECREF(v); } return r; } /* result is NULL, check whether there was an error */ if (!PyErr_Occurred()) { /* no, there wasn't, so we must simply add the attribute */ int n=(int)igraph_ecount(&o->g), i; result=PyList_New(n); for (i=0; iidx) { Py_INCREF(Py_None); if (PyList_SetItem(result, i, Py_None) == -1) { Py_DECREF(Py_None); Py_DECREF(result); return -1; } } else { /* Same game with the reference count here */ Py_INCREF(v); if (PyList_SetItem(result, i, v) == -1) { Py_DECREF(v); Py_DECREF(result); return -1; } } } if (PyDict_SetItem(((PyObject**)o->g.attr)[2], k, result) == -1) { Py_DECREF(result); /* TODO: is it needed here? maybe not! */ return -1; } Py_DECREF(result); /* compensating for PyDict_SetItem */ return 0; } return -1; } /** * \ingroup python_interface_edge * Returns the source vertex index of an edge */ PyObject* igraphmodule_Edge_get_from(igraphmodule_EdgeObject* self, void* closure) { igraphmodule_GraphObject *o = self->gref; igraph_integer_t from, to; if (!igraphmodule_Edge_Validate((PyObject*)self)) return NULL; if (igraph_edge(&o->g, self->idx, &from, &to)) { igraphmodule_handle_igraph_error(); return NULL; } return PyInt_FromLong((long int)from); } /** * \ingroup python_interface_edge * Returns the source vertex index of an edge */ PyObject* igraphmodule_Edge_get_source_vertex(igraphmodule_EdgeObject* self, void* closure) { igraphmodule_GraphObject *o = self->gref; igraph_integer_t from, to; if (!igraphmodule_Edge_Validate((PyObject*)self)) return NULL; if (igraph_edge(&o->g, self->idx, &from, &to)) { igraphmodule_handle_igraph_error(); return NULL; } return igraphmodule_Vertex_New(o, from); } /** * \ingroup python_interface_edge * Returns the target vertex index of an edge */ PyObject* igraphmodule_Edge_get_to(igraphmodule_EdgeObject* self, void* closure) { igraphmodule_GraphObject *o = self->gref; igraph_integer_t from, to; if (!igraphmodule_Edge_Validate((PyObject*)self)) return NULL; if (igraph_edge(&o->g, self->idx, &from, &to)) { igraphmodule_handle_igraph_error(); return NULL; } return PyInt_FromLong((long)to); } /** * \ingroup python_interface_edge * Returns the target vertex of an edge */ PyObject* igraphmodule_Edge_get_target_vertex(igraphmodule_EdgeObject* self, void* closure) { igraphmodule_GraphObject *o = self->gref; igraph_integer_t from, to; if (!igraphmodule_Edge_Validate((PyObject*)self)) return NULL; if (igraph_edge(&o->g, self->idx, &from, &to)) { igraphmodule_handle_igraph_error(); return NULL; } return igraphmodule_Vertex_New(o, to); } /** * \ingroup python_interface_edge * Returns the edge index */ PyObject* igraphmodule_Edge_get_index(igraphmodule_EdgeObject* self, void* closure) { return PyInt_FromLong((long int)self->idx); } /** * \ingroup python_interface_edge * Returns the edge index as an igraph_integer_t */ igraph_integer_t igraphmodule_Edge_get_index_igraph_integer(igraphmodule_EdgeObject* self) { return self->idx; } /** * \ingroup python_interface_edge * Returns the edge index as an ordinary C long */ long igraphmodule_Edge_get_index_long(igraphmodule_EdgeObject* self) { return (long)self->idx; } /** * \ingroup python_interface_edge * Returns the source and target vertex index of an edge */ PyObject* igraphmodule_Edge_get_tuple(igraphmodule_EdgeObject* self, void* closure) { igraphmodule_GraphObject *o = self->gref; igraph_integer_t from, to; if (!igraphmodule_Edge_Validate((PyObject*)self)) return NULL; if (igraph_edge(&o->g, self->idx, &from, &to)) { igraphmodule_handle_igraph_error(); return NULL; } return Py_BuildValue("(ii)", (long)from, (long)to); } /** * \ingroup python_interface_edge * Returns the source and target vertex of an edge */ PyObject* igraphmodule_Edge_get_vertex_tuple(igraphmodule_EdgeObject* self, void* closure) { igraphmodule_GraphObject *o = self->gref; igraph_integer_t from, to; PyObject *from_o, *to_o; if (!igraphmodule_Edge_Validate((PyObject*)self)) return NULL; if (igraph_edge(&o->g, self->idx, &from, &to)) { igraphmodule_handle_igraph_error(); return NULL; } from_o = igraphmodule_Vertex_New(o, from); if (!from_o) { return NULL; } to_o = igraphmodule_Vertex_New(o, to); if (!to_o) { Py_DECREF(from_o); return NULL; } return Py_BuildValue("(NN)", from_o, to_o); /* steals references */ } /** \ingroup python_interface_edge * Returns the graph where the edge belongs */ PyObject* igraphmodule_Edge_get_graph(igraphmodule_EdgeObject* self, void* closure) { Py_INCREF(self->gref); return (PyObject*)self->gref; } #define GRAPH_PROXY_METHOD(FUNC, METHODNAME) \ PyObject* igraphmodule_Edge_##FUNC(igraphmodule_EdgeObject* self, PyObject* args, PyObject* kwds) { \ PyObject *new_args, *item, *result; \ long int i, num_args = args ? PyTuple_Size(args)+1 : 1; \ \ /* Prepend ourselves to args */ \ new_args = PyTuple_New(num_args); \ Py_INCREF(self); PyTuple_SET_ITEM(new_args, 0, (PyObject*)self); \ for (i = 1; i < num_args; i++) { \ item = PyTuple_GET_ITEM(args, i-1); \ Py_INCREF(item); PyTuple_SET_ITEM(new_args, i, item); \ } \ \ /* Get the method instance */ \ item = PyObject_GetAttrString((PyObject*)(self->gref), METHODNAME); \ result = PyObject_Call(item, new_args, kwds); \ Py_DECREF(item); \ Py_DECREF(new_args); \ return result; \ } GRAPH_PROXY_METHOD(count_multiple, "count_multiple"); GRAPH_PROXY_METHOD(delete, "delete_edges"); GRAPH_PROXY_METHOD(is_loop, "is_loop"); GRAPH_PROXY_METHOD(is_multiple, "is_multiple"); GRAPH_PROXY_METHOD(is_mutual, "is_mutual"); #undef GRAPH_PROXY_METHOD #define GRAPH_PROXY_METHOD_SPEC(FUNC, METHODNAME) \ {METHODNAME, (PyCFunction)igraphmodule_Edge_##FUNC, METH_VARARGS | METH_KEYWORDS, \ "Proxy method to L{Graph." METHODNAME "()}\n\n" \ "This method calls the " METHODNAME " method of the L{Graph} class " \ "with this edge as the first argument, and returns the result.\n\n"\ "@see: Graph." METHODNAME "() for details."} #define GRAPH_PROXY_METHOD_SPEC_2(FUNC, METHODNAME, METHODNAME_IN_GRAPH) \ {METHODNAME, (PyCFunction)igraphmodule_Edge_##FUNC, METH_VARARGS | METH_KEYWORDS, \ "Proxy method to L{Graph." METHODNAME_IN_GRAPH "()}\n\n" \ "This method calls the " METHODNAME_IN_GRAPH " method of the L{Graph} class " \ "with this edge as the first argument, and returns the result.\n\n"\ "@see: Graph." METHODNAME_IN_GRAPH "() for details."} /** * \ingroup python_interface_edge * Method table for the \c igraph.Edge object */ PyMethodDef igraphmodule_Edge_methods[] = { {"attributes", (PyCFunction)igraphmodule_Edge_attributes, METH_NOARGS, "attributes() -> dict\n\n" "Returns a dict of attribute names and values for the edge\n" }, {"attribute_names", (PyCFunction)igraphmodule_Edge_attribute_names, METH_NOARGS, "attribute_names() -> list\n\n" "Returns the list of edge attribute names\n" }, {"update_attributes", (PyCFunction)igraphmodule_Edge_update_attributes, METH_VARARGS | METH_KEYWORDS, "update_attributes(E, **F) -> None\n\n" "Updates the attributes of the edge from dict/iterable E and F.\n\n" "If E has a C{keys()} method, it does: C{for k in E: self[k] = E[k]}.\n" "If E lacks a C{keys()} method, it does: C{for (k, v) in E: self[k] = v}.\n" "In either case, this is followed by: C{for k in F: self[k] = F[k]}.\n\n" "This method thus behaves similarly to the C{update()} method of Python\n" "dictionaries." }, GRAPH_PROXY_METHOD_SPEC(count_multiple, "count_multiple"), GRAPH_PROXY_METHOD_SPEC_2(delete, "delete", "delete_edges"), GRAPH_PROXY_METHOD_SPEC(is_loop, "is_loop"), GRAPH_PROXY_METHOD_SPEC(is_multiple, "is_multiple"), GRAPH_PROXY_METHOD_SPEC(is_mutual, "is_mutual"), {NULL} }; #undef GRAPH_PROXY_METHOD_SPEC #undef GRAPH_PROXY_METHOD_SPEC_2 /** * \ingroup python_interface_edge * Getter/setter table for the \c igraph.Edge object */ PyGetSetDef igraphmodule_Edge_getseters[] = { {"source", (getter)igraphmodule_Edge_get_from, NULL, "Source vertex index of this edge", NULL }, {"source_vertex", (getter)igraphmodule_Edge_get_source_vertex, NULL, "Source vertex of this edge", NULL }, {"target", (getter)igraphmodule_Edge_get_to, NULL, "Target vertex index of this edge", NULL }, {"target_vertex", (getter)igraphmodule_Edge_get_target_vertex, NULL, "Target vertex of this edge", NULL }, {"tuple", (getter)igraphmodule_Edge_get_tuple, NULL, "Source and target vertex index of this edge as a tuple", NULL }, {"vertex_tuple", (getter)igraphmodule_Edge_get_vertex_tuple, NULL, "Source and target vertex of this edge as a tuple", NULL }, {"index", (getter)igraphmodule_Edge_get_index, NULL, "Index of this edge", NULL, }, {"graph", (getter)igraphmodule_Edge_get_graph, NULL, "The graph the edge belongs to", NULL, }, {NULL} }; /** \ingroup python_interface_edge * This structure is the collection of functions necessary to implement * the edge as a mapping (i.e. to allow the retrieval and setting of * igraph attributes in Python as if it were of a Python mapping type) */ PyMappingMethods igraphmodule_Edge_as_mapping = { // returns the number of edge attributes (lenfunc)igraphmodule_Edge_attribute_count, // returns an attribute by name (binaryfunc)igraphmodule_Edge_get_attribute, // sets an attribute by name (objobjargproc)igraphmodule_Edge_set_attribute }; /** \ingroup python_interface_edge * Python type object referencing the methods Python calls when it performs various operations on * an edge of a graph */ PyTypeObject igraphmodule_EdgeType = { PyVarObject_HEAD_INIT(0, 0) "igraph.Edge", // tp_name sizeof(igraphmodule_EdgeObject), // tp_basicsize 0, // tp_itemsize (destructor)igraphmodule_Edge_dealloc, // tp_dealloc 0, // tp_print 0, // tp_getattr 0, // tp_setattr 0, /* tp_compare (2.x) / tp_reserved (3.x) */ (reprfunc)igraphmodule_Edge_repr, // tp_repr 0, // tp_as_number 0, // tp_as_sequence &igraphmodule_Edge_as_mapping, // tp_as_mapping (hashfunc)igraphmodule_Edge_hash, /* tp_hash */ 0, // tp_call 0, // tp_str 0, // tp_getattro 0, // tp_setattro 0, // tp_as_buffer Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE, // tp_flags "Class representing a single edge in a graph.\n\n" "The edge is referenced by its index, so if the underlying graph\n" "changes, the semantics of the edge object might change as well\n" "(if the edge indices are altered in the original graph).\n\n" "The attributes of the edge can be accessed by using the edge\n" "as a hash:\n\n" " >>> e[\"weight\"] = 2 #doctest: +SKIP\n" " >>> print e[\"weight\"] #doctest: +SKIP\n" " 2\n", // tp_doc 0, // tp_traverse 0, // tp_clear (richcmpfunc)igraphmodule_Edge_richcompare, /* tp_richcompare */ 0, // tp_weaklistoffset 0, // tp_iter 0, // tp_iternext igraphmodule_Edge_methods, // tp_methods 0, // tp_members igraphmodule_Edge_getseters, // tp_getset }; python-igraph-0.8.0/src/_igraph/error.h0000644000076500000240000000306713104627150020247 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef PYTHON_ERROR_H #define PYTHON_ERROR_H #include #include /** \defgroup python_interface_errors Error handling * \ingroup python_interface */ PyObject* igraphmodule_handle_igraph_error(void); void igraphmodule_igraph_warning_hook(const char *reason, const char *file, int line, int igraph_errno); void igraphmodule_igraph_error_hook(const char *reason, const char *file, int line, int igraph_errno); extern PyObject* igraphmodule_InternalError; #define IGRAPH_PYCHECK(a) do { \ int igraph_i_pyret=(a); \ if (IGRAPH_UNLIKELY(igraph_i_pyret != 0)) {\ igraphmodule_handle_igraph_error(); \ IGRAPH_FINALLY_FREE(); \ return 0; \ } } while (0) #endif python-igraph-0.8.0/src/_igraph/common.c0000644000076500000240000000467513104627150020407 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "common.h" #include "structmember.h" /** * \ingroup python_interface * \brief Handler function for all unimplemented \c igraph.Graph methods * * This function is called whenever an unimplemented \c igraph.Graph method * is called ("unimplemented" meaning that there is a method name in the * method table of \c igraph.Graph , but there isn't any working implementation * either because the underlying \c igraph API might be subject to change * or because the calling format from Python is not decided yet (or maybe * because of laziness or lack of time ;)) * * All of the parameters are ignored, they are here just to make the * function satisfy the requirements of \c PyCFunction, thus allowing it * to be included in a method table. * * \return NULL */ PyObject* igraphmodule_unimplemented(PyObject* self, PyObject* args, PyObject* kwds) { PyErr_SetString(PyExc_NotImplementedError, "This method is unimplemented."); return NULL; } /** * \ingroup python_interface * \brief Resolves a weak reference to an \c igraph.Graph * \return the \c igraph.Graph object or NULL if the weak reference is dead. * Sets an exception in the latter case. */ PyObject* igraphmodule_resolve_graph_weakref(PyObject* ref) { PyObject *o; #ifndef PYPY_VERSION /* PyWeakref_Check is not implemented in PyPy yet */ if (!PyWeakref_Check(ref)) { PyErr_SetString(PyExc_TypeError, "weak reference expected"); return NULL; } #endif /* PYPY_VERSION */ o=PyWeakref_GetObject(ref); if (o == Py_None) { PyErr_SetString(PyExc_TypeError, "underlying graph has already been destroyed"); return NULL; } return o; } python-igraph-0.8.0/src/_igraph/py2compat.c0000644000076500000240000000617213104627150021027 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim: set ts=2 sw=2 sts=2 et: */ /* IGraph library. Copyright (C) 2006-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "py2compat.h" /* Common utility functions that are useful both in Python 2.x and 3.x */ int PyFile_Close(PyObject* fileObj) { PyObject *result; result = PyObject_CallMethod(fileObj, "close", 0); if (result) { Py_DECREF(result); return 0; } else { /* Exception raised already */ return 1; } } #ifdef IGRAPH_PYTHON3 /* Python 3.x functions */ PyObject* PyFile_FromObject(PyObject* filename, const char* mode) { PyObject *ioModule, *fileObj; ioModule = PyImport_ImportModule("io"); if (ioModule == 0) return 0; fileObj = PyObject_CallMethod(ioModule, "open", "Os", filename, mode); Py_DECREF(ioModule); return fileObj; } char* PyString_CopyAsString(PyObject* string) { PyObject* bytes; char* result; if (PyBytes_Check(string)) { bytes = string; Py_INCREF(bytes); } else { bytes = PyUnicode_AsUTF8String(string); } if (bytes == 0) return 0; result = strdup(PyBytes_AS_STRING(bytes)); Py_DECREF(bytes); if (result == 0) PyErr_NoMemory(); return result; } int PyString_IsEqualToUTF8String(PyObject* py_string, const char* c_string) { PyObject* c_string_conv; int result; if (!PyUnicode_Check(py_string)) return 0; c_string_conv = PyUnicode_FromString(c_string); if (c_string_conv == 0) return 0; result = (PyUnicode_Compare(py_string, c_string_conv) == 0); Py_DECREF(c_string_conv); return result; } #else /* Python 2.x functions */ char* PyString_CopyAsString(PyObject* string) { char* result; if (!PyBaseString_Check(string)) { PyErr_SetString(PyExc_TypeError, "string or unicode object expected"); return 0; } result = PyString_AsString(string); if (result == 0) return 0; result = strdup(result); if (result == 0) PyErr_NoMemory(); return result; } int PyString_IsEqualToASCIIString(PyObject* py_string, const char* c_string) { PyObject* c_string_conv; int result; if (PyString_Check(py_string)) { return strcmp(PyString_AS_STRING(py_string), c_string) == 0; } if (!PyUnicode_Check(py_string)) return 0; c_string_conv = PyUnicode_DecodeASCII(c_string, strlen(c_string), "strict"); if (c_string_conv == 0) return 0; result = (PyUnicode_Compare(py_string, c_string_conv) == 0); Py_DECREF(c_string_conv); return result; } #endif python-igraph-0.8.0/src/_igraph/graphobject.c0000644000076500000240000222452213616774160021420 0ustar tamasstaff00000000000000/* vim:set ts=4 sw=2 sts=2 et: */ /* IGraph library. Copyright (C) 2006-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "attributes.h" #include "arpackobject.h" #include "bfsiter.h" #include "common.h" #include "convert.h" #include "edgeseqobject.h" #include "error.h" #include "filehandle.h" #include "graphobject.h" #include "indexing.h" #include "memory.h" #include "py2compat.h" #include "pyhelpers.h" #include "vertexseqobject.h" #include PyTypeObject igraphmodule_GraphType; #define CREATE_GRAPH_FROM_TYPE(py_graph, c_graph, py_type) { \ py_graph = (igraphmodule_GraphObject*) igraphmodule_Graph_subclass_from_igraph_t( \ py_type, &c_graph \ ); \ } #define CREATE_GRAPH(py_graph, c_graph) { \ py_graph = (igraphmodule_GraphObject*) igraphmodule_Graph_subclass_from_igraph_t( \ Py_TYPE(self), &c_graph \ ); \ } /********************************************************************** * Basic implementation of igraph.Graph * **********************************************************************/ /** \defgroup python_interface_graph Graph object * \ingroup python_interface */ /** * \ingroup python_interface_internal * \brief Initializes the internal structures in an \c igraph.Graph object's * C representation. * * This function must be called whenever we create a new Graph object with * \c tp_alloc */ void igraphmodule_Graph_init_internal(igraphmodule_GraphObject * self) { if (!self) return; self->destructor = NULL; self->weakreflist = NULL; } /** * \ingroup python_interface_graph * \brief Creates a new igraph object in Python * * This function is called whenever a new \c igraph.Graph object is created in * Python. An optional \c n parameter can be passed from Python, * representing the number of vertices in the graph. If it is omitted, * the default value is 0. * * Example call from Python: \verbatim g = igraph.Graph(5); \endverbatim * * In fact, the parameters are processed by \c igraphmodule_Graph_init * * \return the new \c igraph.Graph object or NULL if an error occurred. * * \sa igraphmodule_Graph_init * \sa igraph_empty */ PyObject *igraphmodule_Graph_new(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; self = (igraphmodule_GraphObject *) type->tp_alloc(type, 0); RC_ALLOC("Graph", self); igraphmodule_Graph_init_internal(self); return (PyObject *) self; } /** * \ingroup python_interface_graph * \brief Clears the graph object's subobject (before deallocation) */ int igraphmodule_Graph_clear(igraphmodule_GraphObject * self) { PyObject *tmp; PyObject_GC_UnTrack(self); tmp = self->destructor; self->destructor = NULL; Py_XDECREF(tmp); return 0; } /** * \ingroup python_interface_graph * \brief Support for cyclic garbage collection in Python * * This is necessary because the \c igraph.Graph object contains several * other \c PyObject pointers and they might point back to itself. */ int igraphmodule_Graph_traverse(igraphmodule_GraphObject * self, visitproc visit, void *arg) { int vret, i; RC_TRAVERSE("Graph", self); if (self->destructor) { vret = visit(self->destructor, arg); if (vret != 0) return vret; } if (self->g.attr) { for (i = 0; i < 3; i++) { vret = visit(((PyObject **) (self->g.attr))[i], arg); if (vret != 0) return vret; } } return 0; } /** * \ingroup python_interface_graph * \brief Deallocates a Python representation of a given igraph object */ void igraphmodule_Graph_dealloc(igraphmodule_GraphObject * self) { PyObject *r; /* Clear weak references */ if (self->weakreflist != NULL) PyObject_ClearWeakRefs((PyObject *) self); igraph_destroy(&self->g); if (self->destructor != NULL && PyCallable_Check(self->destructor)) { r = PyObject_CallObject(self->destructor, NULL); if (r) { Py_DECREF(r); } } igraphmodule_Graph_clear(self); RC_DEALLOC("Graph", self); Py_TYPE(self)->tp_free((PyObject*)self); } /** * \ingroup python_interface_graph * \brief Initializes a new \c igraph object in Python * * This function is called whenever a new \c igraph.Graph object is initialized in * Python (note that initializing is not equal to creating: an object might * be created but not initialized when it is being recovered from a serialized * state). * * Throws \c AssertionError in Python if \c vcount is less than or equal to zero. * \return the new \c igraph.Graph object or NULL if an error occurred. * * \sa igraphmodule_Graph_new * \sa igraph_empty * \sa igraph_create */ int igraphmodule_Graph_init(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "n", "edges", "directed", "__ptr", NULL }; long int n = 0; PyObject *edges = NULL, *dir = Py_False, *ptr_o = 0; void* ptr = 0; igraph_vector_t edges_vector; igraph_bool_t edges_vector_owned = 0; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|lOOO!", kwlist, &n, &edges, &dir, &PyCapsule_Type, &ptr_o)) return -1; /* Safety check: if ptr is not null, it means that we have been explicitly * given a pointer to an igraph_t for which we must take ownership. * This means that n should be zero and edges should not be specified */ if (ptr_o && (n != 0 || edges != NULL)) { PyErr_SetString(PyExc_ValueError, "neither n nor edges should be given " "in the call to Graph.__init__() when the graph is " "pre-initialized with a C pointer"); return -1; } if (ptr_o) { /* We must take ownership of an igraph graph */ ptr = PyCapsule_GetPointer(ptr_o, "__igraph_t"); if (ptr == 0) { PyErr_SetString(PyExc_ValueError, "pointer should not be null"); } else { self->g = *(igraph_t*)ptr; } } else if (edges) { /* Caller specified an edge list, so we use igraph_create */ /* We have to convert the Python list to a igraph_vector_t */ if (igraphmodule_PyObject_to_edgelist(edges, &edges_vector, 0, &edges_vector_owned)) { igraphmodule_handle_igraph_error(); return -1; } if (igraph_create (&self->g, &edges_vector, (igraph_integer_t) n, PyObject_IsTrue(dir))) { igraphmodule_handle_igraph_error(); if (edges_vector_owned) { igraph_vector_destroy(&edges_vector); } return -1; } if (edges_vector_owned) { igraph_vector_destroy(&edges_vector); } } else { /* No edge list was specified, and no previously initialized graph object * was fed into our object, so let's use igraph_empty */ if (igraph_empty(&self->g, (igraph_integer_t) n, PyObject_IsTrue(dir))) { igraphmodule_handle_igraph_error(); return -1; } } return 0; } /** \ingroup python_interface_graph * \brief Creates an \c igraph.Graph subtype from an existing \c igraph_t * * The newly created instance (which will be a subtype of )\c igraph.Graph) * will take ownership of the given \c igraph_t. This function is not * accessible from Python. */ PyObject* igraphmodule_Graph_subclass_from_igraph_t( PyTypeObject* type, igraph_t *graph ) { PyObject* result; PyObject* capsule; PyObject* args; PyObject* kwds; if (!PyType_IsSubtype(type, &igraphmodule_GraphType)) { PyErr_SetString(PyExc_TypeError, "igraph.GraphBase expected"); return 0; } capsule = PyCapsule_New(graph, "__igraph_t", 0); if (capsule == 0) { return 0; } args = PyTuple_New(0); if (args == 0) { Py_DECREF(capsule); return 0; } kwds = PyDict_New(); if (kwds == 0) { Py_DECREF(args); Py_DECREF(capsule); return 0; } if (PyDict_SetItemString(kwds, "__ptr", capsule)) { Py_DECREF(kwds); Py_DECREF(args); Py_DECREF(capsule); return 0; } /* kwds now holds a reference to the capsule so we can release it */ Py_DECREF(capsule); /* Call the type */ result = PyObject_Call((PyObject*) type, args, kwds); /* Release args and kwds */ Py_DECREF(args); Py_DECREF(kwds); return result; } /** \ingroup python_interface_graph * \brief Creates an \c igraph.Graph object from an existing \c igraph_t * * The newly created \c igraph.Graph object will take ownership of the * given \c igraph_t. This function is not accessible from Python the * normal way, but it is exposed via the C API of the Python module. * See \c api.h for more details. */ PyObject* igraphmodule_Graph_from_igraph_t(igraph_t *graph) { return igraphmodule_Graph_subclass_from_igraph_t( &igraphmodule_GraphType, graph ); } /** \ingroup python_interface_graph * \brief Formats an \c igraph.Graph object in a human-readable format. * * This function is rather simple now, it returns the number of vertices * and edges in a string. * * \return the formatted textual representation as a \c PyObject */ PyObject *igraphmodule_Graph_str(igraphmodule_GraphObject * self) { if (igraph_is_directed(&self->g)) return PyString_FromFormat("Directed graph (|V| = %ld, |E| = %ld)", (long)igraph_vcount(&self->g), (long)igraph_ecount(&self->g)); else return PyString_FromFormat("Undirected graph (|V| = %ld, |E| = %ld)", (long)igraph_vcount(&self->g), (long)igraph_ecount(&self->g)); } /** \ingroup python_interface_copy * \brief Creates a copy of the graph * \return the copy of the graph */ PyObject *igraphmodule_Graph_copy(igraphmodule_GraphObject * self) { igraphmodule_GraphObject *result; igraph_t g; if (igraph_copy(&g, &self->g)) { igraphmodule_handle_igraph_error(); return NULL; } CREATE_GRAPH(result, g); return (PyObject *) result; } /********************************************************************** * The most basic igraph interface * **********************************************************************/ /** \ingroup python_interface_graph * \brief Returns the number of vertices in an \c igraph.Graph object. * \return the number of vertices as a \c PyObject * \sa igraph_vcount */ PyObject *igraphmodule_Graph_vcount(igraphmodule_GraphObject * self) { PyObject *result; result = Py_BuildValue("l", (long)igraph_vcount(&self->g)); return result; } /** \ingroup python_interface_graph * \brief Returns the number of edges in an \c igraph.Graph object. * \return the number of edges as a \c PyObject * \sa igraph_ecount */ PyObject *igraphmodule_Graph_ecount(igraphmodule_GraphObject * self) { PyObject *result; result = Py_BuildValue("l", (long)igraph_ecount(&self->g)); return result; } /** \ingroup python_interface_graph * \brief Checks whether an \c igraph.Graph object is a DAG. * \return \c True if the graph is directed, \c False otherwise. * \sa igraph_is_dag */ PyObject *igraphmodule_Graph_is_dag(igraphmodule_GraphObject * self) { igraph_bool_t res; if (igraph_is_dag(&self->g, &res)) { igraphmodule_handle_igraph_error(); return NULL; } if (res) Py_RETURN_TRUE; Py_RETURN_FALSE; } /** \ingroup python_interface_graph * \brief Checks whether an \c igraph.Graph object is directed. * \return \c True if the graph is directed, \c False otherwise. * \sa igraph_is_directed */ PyObject *igraphmodule_Graph_is_directed(igraphmodule_GraphObject * self) { if (igraph_is_directed(&self->g)) Py_RETURN_TRUE; Py_RETURN_FALSE; } /** * \ingroup python_interface_graph * \brief Checks whether a matching is valid in the context of an \c igraph.Graph * object. * \sa igraph_is_matching */ PyObject *igraphmodule_Graph_is_matching(igraphmodule_GraphObject* self, PyObject* args, PyObject* kwds) { static char* kwlist[] = { "matching", "types", NULL }; PyObject *matching_o, *types_o = Py_None; igraph_vector_long_t* matching = 0; igraph_vector_bool_t* types = 0; igraph_bool_t result; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|O", kwlist, &matching_o, &types_o)) return NULL; if (igraphmodule_attrib_to_vector_long_t(matching_o, self, &matching, ATTRIBUTE_TYPE_VERTEX)) return NULL; if (igraphmodule_attrib_to_vector_bool_t(types_o, self, &types, ATTRIBUTE_TYPE_VERTEX)) { if (matching != 0) { igraph_vector_long_destroy(matching); free(matching); } return NULL; } if (igraph_is_matching(&self->g, types, matching, &result)) { if (matching != 0) { igraph_vector_long_destroy(matching); free(matching); } if (types != 0) { igraph_vector_bool_destroy(types); free(types); } igraphmodule_handle_igraph_error(); return NULL; } if (matching != 0) { igraph_vector_long_destroy(matching); free(matching); } if (types != 0) { igraph_vector_bool_destroy(types); free(types); } if (result) Py_RETURN_TRUE; Py_RETURN_FALSE; } /** * \ingroup python_interface_graph * \brief Checks whether a matching is valid and maximal in the context of an * \c igraph.Graph object. * \sa igraph_is_maximal_matching */ PyObject *igraphmodule_Graph_is_maximal_matching(igraphmodule_GraphObject* self, PyObject* args, PyObject* kwds) { static char* kwlist[] = { "matching", "types", NULL }; PyObject *matching_o, *types_o = Py_None; igraph_vector_long_t* matching = 0; igraph_vector_bool_t* types = 0; igraph_bool_t result; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|O", kwlist, &matching_o, &types_o)) return NULL; if (igraphmodule_attrib_to_vector_long_t(matching_o, self, &matching, ATTRIBUTE_TYPE_VERTEX)) return NULL; if (igraphmodule_attrib_to_vector_bool_t(types_o, self, &types, ATTRIBUTE_TYPE_VERTEX)) { if (matching != 0) { igraph_vector_long_destroy(matching); free(matching); } return NULL; } if (igraph_is_maximal_matching(&self->g, types, matching, &result)) { if (matching != 0) { igraph_vector_long_destroy(matching); free(matching); } if (types != 0) { igraph_vector_bool_destroy(types); free(types); } igraphmodule_handle_igraph_error(); return NULL; } if (matching != 0) { igraph_vector_long_destroy(matching); free(matching); } if (types != 0) { igraph_vector_bool_destroy(types); free(types); } if (result) Py_RETURN_TRUE; Py_RETURN_FALSE; } /** \ingroup python_interface_graph * \brief Checks whether an \c igraph.Graph object is simple. * \return \c True if the graph is simple, \c False otherwise. * \sa igraph_is_simple */ PyObject *igraphmodule_Graph_is_simple(igraphmodule_GraphObject *self) { igraph_bool_t res; if (igraph_is_simple(&self->g, &res)) { igraphmodule_handle_igraph_error(); return NULL; } if (res) Py_RETURN_TRUE; Py_RETURN_FALSE; } /** \ingroup python_interface_graph * \brief Adds vertices to an \c igraph.Graph * \return the extended \c igraph.Graph object * \sa igraph_add_vertices */ PyObject *igraphmodule_Graph_add_vertices(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { long n; if (!PyArg_ParseTuple(args, "l", &n)) return NULL; if (igraph_add_vertices(&self->g, (igraph_integer_t) n, 0)) { igraphmodule_handle_igraph_error(); return NULL; } Py_RETURN_NONE; } /** \ingroup python_interface_graph * \brief Removes vertices from an \c igraph.Graph * \return the modified \c igraph.Graph object * * \todo Need more error checking on vertex IDs. (igraph fails when an * invalid vertex ID is given) * \sa igraph_delete_vertices */ PyObject *igraphmodule_Graph_delete_vertices(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { PyObject *list; igraph_vs_t vs; if (!PyArg_ParseTuple(args, "O", &list)) return NULL; if (igraphmodule_PyObject_to_vs_t(list, &vs, &self->g, 0, 0)) return NULL; if (igraph_delete_vertices(&self->g, vs)) { igraphmodule_handle_igraph_error(); igraph_vs_destroy(&vs); return NULL; } igraph_vs_destroy(&vs); Py_RETURN_NONE; } /** \ingroup python_interface_graph * \brief Adds edges to an \c igraph.Graph * \return the extended \c igraph.Graph object * * \todo Need more error checking on vertex IDs. (igraph fails when an * invalid vertex ID is given) * \sa igraph_add_edges */ PyObject *igraphmodule_Graph_add_edges(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { PyObject *list; igraph_vector_t v; igraph_bool_t v_owned = 0; if (!PyArg_ParseTuple(args, "O", &list)) return NULL; if (igraphmodule_PyObject_to_edgelist(list, &v, &self->g, &v_owned)) return NULL; /* do the hard work :) */ if (igraph_add_edges(&self->g, &v, 0)) { igraphmodule_handle_igraph_error(); if (v_owned) { igraph_vector_destroy(&v); } return NULL; } if (v_owned) { igraph_vector_destroy(&v); } Py_RETURN_NONE; } /** \ingroup python_interface_graph * \brief Deletes edges from an \c igraph.Graph * \return the extended \c igraph.Graph object * * \todo Need more error checking on vertex IDs. (igraph fails when an * invalid vertex ID is given) * \sa igraph_delete_edges */ PyObject *igraphmodule_Graph_delete_edges(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { PyObject *list; igraph_es_t es; static char *kwlist[] = { "edges", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O", kwlist, &list)) return NULL; if (igraphmodule_PyObject_to_es_t(list, &es, &self->g, 0)) { /* something bad happened during conversion, return immediately */ return NULL; } if (igraph_delete_edges(&self->g, es)) { igraphmodule_handle_igraph_error(); igraph_es_destroy(&es); return NULL; } igraph_es_destroy(&es); Py_RETURN_NONE; } /********************************************************************** * tructural properties * **********************************************************************/ /** \ingroup python_interface_graph * \brief The degree of some vertices in an \c igraph.Graph * \return the degree list as a Python object * \sa igraph_degree */ PyObject *igraphmodule_Graph_degree(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { PyObject *list = Py_None; PyObject *loops = Py_True; PyObject *dtype_o = Py_None; PyObject *dmode_o = Py_None; igraph_neimode_t dmode = IGRAPH_ALL; igraph_vector_t result; igraph_vs_t vs; igraph_bool_t return_single = 0; static char *kwlist[] = { "vertices", "mode", "loops", "type", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOOO", kwlist, &list, &dmode_o, &loops, &dtype_o)) return NULL; if (dmode_o == Py_None && dtype_o != Py_None) { dmode_o = dtype_o; PY_IGRAPH_DEPRECATED("type=... keyword argument is deprecated since igraph 0.6, use mode=... instead"); } if (igraphmodule_PyObject_to_neimode_t(dmode_o, &dmode)) return NULL; if (igraphmodule_PyObject_to_vs_t(list, &vs, &self->g, &return_single, 0)) { return NULL; } if (igraph_vector_init(&result, 0)) { igraph_vs_destroy(&vs); return NULL; } if (igraph_degree(&self->g, &result, vs, dmode, PyObject_IsTrue(loops))) { igraphmodule_handle_igraph_error(); igraph_vs_destroy(&vs); igraph_vector_destroy(&result); return NULL; } if (!return_single) list = igraphmodule_vector_t_to_PyList(&result, IGRAPHMODULE_TYPE_INT); else list = PyInt_FromLong((long int)VECTOR(result)[0]); igraph_vector_destroy(&result); igraph_vs_destroy(&vs); return list; } /** * \ingroup python_interface_graph * \brief Structural diversity index of some vertices in an \c igraph.Graph * \sa igraph_diversity */ PyObject *igraphmodule_Graph_diversity(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { PyObject *list = Py_None; PyObject *weights_o = Py_None; igraph_vector_t result, *weights = 0; igraph_vs_t vs; igraph_bool_t return_single = 0; igraph_integer_t no_of_nodes; static char *kwlist[] = { "vertices", "weights", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OO", kwlist, &list, &weights_o)) return NULL; if (igraphmodule_PyObject_to_vs_t(list, &vs, &self->g, &return_single, 0)) { igraphmodule_handle_igraph_error(); return NULL; } if (igraph_vector_init(&result, 0)) { igraph_vs_destroy(&vs); return NULL; } if (igraphmodule_attrib_to_vector_t(weights_o, self, &weights, ATTRIBUTE_TYPE_EDGE)) { igraph_vs_destroy(&vs); igraph_vector_destroy(&result); return NULL; } if (weights == 0) { /* Handle this case here because igraph_diversity bails out when no weights * are given. */ if (igraph_vs_size(&self->g, &vs, &no_of_nodes)) { igraphmodule_handle_igraph_error(); igraph_vs_destroy(&vs); igraph_vector_destroy(&result); return NULL; } if (igraph_vector_resize(&result, no_of_nodes)) { igraphmodule_handle_igraph_error(); igraph_vs_destroy(&vs); igraph_vector_destroy(&result); return NULL; } igraph_vector_fill(&result, 1.0); } else { if (igraph_diversity(&self->g, weights, &result, vs)) { igraphmodule_handle_igraph_error(); igraph_vs_destroy(&vs); igraph_vector_destroy(&result); igraph_vector_destroy(weights); free(weights); return NULL; } igraph_vector_destroy(weights); free(weights); } if (!return_single) list = igraphmodule_vector_t_to_PyList(&result, IGRAPHMODULE_TYPE_FLOAT); else list = PyFloat_FromDouble(VECTOR(result)[0]); igraph_vector_destroy(&result); igraph_vs_destroy(&vs); return list; } /** \ingroup python_interface_graph * \brief The strength (weighted degree) of some vertices in an \c igraph.Graph * \return the strength list as a Python object * \sa igraph_strength */ PyObject *igraphmodule_Graph_strength(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { PyObject *list = Py_None; PyObject *loops = Py_True; PyObject *dtype_o = Py_None; PyObject *dmode_o = Py_None; PyObject *weights_o = Py_None; igraph_neimode_t dmode = IGRAPH_ALL; igraph_vector_t result, *weights = 0; igraph_vs_t vs; igraph_bool_t return_single = 0; static char *kwlist[] = { "vertices", "mode", "loops", "weights", "type", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOOOO", kwlist, &list, &dmode_o, &loops, &weights_o, &dtype_o)) return NULL; if (dmode_o == Py_None && dtype_o != Py_None) { dmode_o = dtype_o; PY_IGRAPH_DEPRECATED("type=... keyword argument is deprecated since igraph 0.6, use mode=... instead"); } if (igraphmodule_PyObject_to_neimode_t(dmode_o, &dmode)) return NULL; if (igraphmodule_PyObject_to_vs_t(list, &vs, &self->g, &return_single, 0)) { igraphmodule_handle_igraph_error(); return NULL; } if (igraph_vector_init(&result, 0)) { igraph_vs_destroy(&vs); return NULL; } if (igraphmodule_attrib_to_vector_t(weights_o, self, &weights, ATTRIBUTE_TYPE_EDGE)) { igraph_vs_destroy(&vs); igraph_vector_destroy(&result); return NULL; } if (igraph_strength(&self->g, &result, vs, dmode, PyObject_IsTrue(loops), weights)) { igraphmodule_handle_igraph_error(); igraph_vs_destroy(&vs); igraph_vector_destroy(&result); if (weights) { igraph_vector_destroy(weights); free(weights); } return NULL; } if (weights) { igraph_vector_destroy(weights); free(weights); } if (!return_single) list = igraphmodule_vector_t_to_PyList(&result, IGRAPHMODULE_TYPE_FLOAT); else list = PyFloat_FromDouble(VECTOR(result)[0]); igraph_vector_destroy(&result); igraph_vs_destroy(&vs); return list; } /** \ingroup python_interface_graph * \brief Calculates the graph density * \return the density * \sa igraph_density */ PyObject *igraphmodule_Graph_density(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { char *kwlist[] = { "loops", NULL }; igraph_real_t result; PyObject *loops = Py_False; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O", kwlist, &loops)) return NULL; if (igraph_density(&self->g, &result, PyObject_IsTrue(loops))) { igraphmodule_handle_igraph_error(); return NULL; } return Py_BuildValue("d", (double)result); } /** \ingroup python_interface_graph * \brief The maximum degree of some vertices in an \c igraph.Graph * \return the maxium degree as a Python object * \sa igraph_maxdegree */ PyObject *igraphmodule_Graph_maxdegree(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { PyObject *list = Py_None; igraph_neimode_t dmode = IGRAPH_ALL; PyObject *dtype_o = Py_None; PyObject *dmode_o = Py_None; PyObject *loops = Py_False; igraph_integer_t result; igraph_vs_t vs; igraph_bool_t return_single = 0; static char *kwlist[] = { "vertices", "mode", "loops", "type", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOOO", kwlist, &list, &dmode_o, &loops, &dtype_o)) return NULL; if (dmode_o == Py_None && dtype_o != Py_None) { dmode_o = dtype_o; PY_IGRAPH_DEPRECATED("type=... keyword argument is deprecated since igraph 0.6, use mode=... instead"); } if (igraphmodule_PyObject_to_neimode_t(dmode_o, &dmode)) return NULL; if (igraphmodule_PyObject_to_vs_t(list, &vs, &self->g, &return_single, 0)) { igraphmodule_handle_igraph_error(); return NULL; } if (igraph_maxdegree(&self->g, &result, vs, dmode, PyObject_IsTrue(loops))) { igraphmodule_handle_igraph_error(); igraph_vs_destroy(&vs); return NULL; } igraph_vs_destroy(&vs); return PyInt_FromLong((long)result); } /** \ingroup python_interface_graph * \brief Checks whether an edge is a loop edge * \return a boolean or a list of booleans * \sa igraph_is_loop */ PyObject *igraphmodule_Graph_is_loop(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { PyObject *list = Py_None; igraph_vector_bool_t result; igraph_es_t es; igraph_bool_t return_single = 0; static char *kwlist[] = { "edges", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O", kwlist, &list)) return NULL; if (igraphmodule_PyObject_to_es_t(list, &es, &self->g, &return_single)) { igraphmodule_handle_igraph_error(); return NULL; } if (igraph_vector_bool_init(&result, 0)) { igraphmodule_handle_igraph_error(); igraph_es_destroy(&es); return NULL; } if (igraph_is_loop(&self->g, &result, es)) { igraphmodule_handle_igraph_error(); igraph_es_destroy(&es); igraph_vector_bool_destroy(&result); return NULL; } if (!return_single) list = igraphmodule_vector_bool_t_to_PyList(&result); else { list = (VECTOR(result)[0]) ? Py_True : Py_False; Py_INCREF(list); } igraph_vector_bool_destroy(&result); igraph_es_destroy(&es); return list; } /** \ingroup python_interface_graph * \brief Checks whether an edge is a multiple edge * \return a boolean or a list of booleans * \sa igraph_is_multiple */ PyObject *igraphmodule_Graph_is_multiple(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { PyObject *list = Py_None; igraph_vector_bool_t result; igraph_es_t es; igraph_bool_t return_single = 0; static char *kwlist[] = { "edges", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O", kwlist, &list)) return NULL; if (igraphmodule_PyObject_to_es_t(list, &es, &self->g, &return_single)) { igraphmodule_handle_igraph_error(); return NULL; } if (igraph_vector_bool_init(&result, 0)) { igraphmodule_handle_igraph_error(); igraph_es_destroy(&es); return NULL; } if (igraph_is_multiple(&self->g, &result, es)) { igraphmodule_handle_igraph_error(); igraph_es_destroy(&es); igraph_vector_bool_destroy(&result); return NULL; } if (!return_single) list = igraphmodule_vector_bool_t_to_PyList(&result); else { list = (VECTOR(result)[0]) ? Py_True : Py_False; Py_INCREF(list); } igraph_vector_bool_destroy(&result); igraph_es_destroy(&es); return list; } /** \ingroup python_interface_graph * \brief Checks whether an edge is mutual * \return a boolean or a list of booleans * \sa igraph_is_mutual */ PyObject *igraphmodule_Graph_is_mutual(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { PyObject *list = Py_None; igraph_vector_bool_t result; igraph_es_t es; igraph_bool_t return_single = 0; static char *kwlist[] = { "edges", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O", kwlist, &list)) return NULL; if (igraphmodule_PyObject_to_es_t(list, &es, &self->g, &return_single)) { igraphmodule_handle_igraph_error(); return NULL; } if (igraph_vector_bool_init(&result, 0)) { igraphmodule_handle_igraph_error(); igraph_es_destroy(&es); return NULL; } if (igraph_is_mutual(&self->g, &result, es)) { igraphmodule_handle_igraph_error(); igraph_es_destroy(&es); igraph_vector_bool_destroy(&result); return NULL; } if (!return_single) list = igraphmodule_vector_bool_t_to_PyList(&result); else { list = (VECTOR(result)[0]) ? Py_True : Py_False; Py_INCREF(list); } igraph_vector_bool_destroy(&result); igraph_es_destroy(&es); return list; } /** \ingroup python_interface_graph * \brief Checks whether an \c igraph.Graph object has multiple edges. * \return \c True if the graph has multiple edges, \c False otherwise. * \sa igraph_has_multiple */ PyObject *igraphmodule_Graph_has_multiple(igraphmodule_GraphObject *self) { igraph_bool_t res; if (igraph_has_multiple(&self->g, &res)) { igraphmodule_handle_igraph_error(); return NULL; } if (res) Py_RETURN_TRUE; Py_RETURN_FALSE; } /** \ingroup python_interface_graph * \brief Checks the multiplicity of the edges * \return the edge multiplicities as a Python list * \sa igraph_count_multiple */ PyObject *igraphmodule_Graph_count_multiple(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { PyObject *list = Py_None; igraph_vector_t result; igraph_es_t es; igraph_bool_t return_single = 0; static char *kwlist[] = { "edges", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O", kwlist, &list)) return NULL; if (igraphmodule_PyObject_to_es_t(list, &es, &self->g, &return_single)) { igraphmodule_handle_igraph_error(); return NULL; } if (igraph_vector_init(&result, 0)) { igraph_es_destroy(&es); return NULL; } if (igraph_count_multiple(&self->g, &result, es)) { igraphmodule_handle_igraph_error(); igraph_es_destroy(&es); igraph_vector_destroy(&result); return NULL; } if (!return_single) list = igraphmodule_vector_t_to_PyList(&result, IGRAPHMODULE_TYPE_INT); else list = PyInt_FromLong((long int)VECTOR(result)[0]); igraph_vector_destroy(&result); igraph_es_destroy(&es); return list; } /** \ingroup python_interface_graph * \brief The neighbors of a given vertex in an \c igraph.Graph * This method accepts a single vertex ID as a parameter, and returns the * neighbors of the given vertex in the form of an integer list. A * second argument may be passed as well, meaning the type of neighbors to * be returned (\c OUT for successors, \c IN for predecessors or \c ALL * for both of them). This argument is ignored for undirected graphs. * * \return the neighbor list as a Python list object * \sa igraph_neighbors */ PyObject *igraphmodule_Graph_neighbors(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { PyObject *list, *dtype_o=Py_None, *dmode_o=Py_None, *index_o; igraph_neimode_t dmode = IGRAPH_ALL; igraph_integer_t idx; igraph_vector_t result; static char *kwlist[] = { "vertex", "mode", "type", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|OO", kwlist, &index_o, &dmode_o, &dtype_o)) return NULL; if (dmode_o == Py_None && dtype_o != Py_None) { dmode_o = dtype_o; PY_IGRAPH_DEPRECATED("type=... keyword argument is deprecated since igraph 0.6, use mode=... instead"); } if (igraphmodule_PyObject_to_neimode_t(dmode_o, &dmode)) return NULL; if (igraphmodule_PyObject_to_vid(index_o, &idx, &self->g)) return NULL; if (igraph_vector_init(&result, 1)) return igraphmodule_handle_igraph_error(); if (igraph_neighbors(&self->g, &result, idx, dmode)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&result); return NULL; } list = igraphmodule_vector_t_to_PyList(&result, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&result); return list; } /** \ingroup python_interface_graph * \brief The incident edges of a given vertex in an \c igraph.Graph * This method accepts a single vertex ID as a parameter, and returns the * IDs of the incident edges of the given vertex in the form of an integer list. * A second argument may be passed as well, meaning the type of neighbors to * be returned (\c OUT for successors, \c IN for predecessors or \c ALL * for both of them). This argument is ignored for undirected graphs. * * \return the adjacency list as a Python list object * \sa igraph_incident */ PyObject *igraphmodule_Graph_incident(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { PyObject *list, *dmode_o = Py_None, *dtype_o = Py_None, *index_o; igraph_neimode_t dmode = IGRAPH_OUT; igraph_integer_t idx; igraph_vector_t result; static char *kwlist[] = { "vertex", "mode", "type", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|OO", kwlist, &index_o, &dmode_o, &dtype_o)) return NULL; if (dmode_o == Py_None && dtype_o != Py_None) { dmode_o = dtype_o; PY_IGRAPH_DEPRECATED("type=... keyword argument is deprecated since igraph 0.6, use mode=... instead"); } if (igraphmodule_PyObject_to_neimode_t(dmode_o, &dmode)) return NULL; if (igraphmodule_PyObject_to_vid(index_o, &idx, &self->g)) return NULL; igraph_vector_init(&result, 1); if (igraph_incident(&self->g, &result, idx, dmode)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&result); return NULL; } list = igraphmodule_vector_t_to_PyList(&result, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&result); return list; } /** \ingroup python_interface_graph * \brief Calculates the graph reciprocity * \return the reciprocity * \sa igraph_reciprocity */ PyObject *igraphmodule_Graph_reciprocity(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { char *kwlist[] = { "ignore_loops", "mode", NULL }; igraph_real_t result; igraph_reciprocity_t mode = IGRAPH_RECIPROCITY_DEFAULT; PyObject *ignore_loops = Py_True, *mode_o = Py_None; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OO", kwlist, &ignore_loops, &mode_o)) return NULL; if (igraphmodule_PyObject_to_reciprocity_t(mode_o, &mode)) return NULL; if (igraph_reciprocity(&self->g, &result, PyObject_IsTrue(ignore_loops), mode)) { igraphmodule_handle_igraph_error(); return NULL; } return Py_BuildValue("d", (double)result); } /** \ingroup python_interface_graph * \brief The successors of a given vertex in an \c igraph.Graph * This method accepts a single vertex ID as a parameter, and returns the * successors of the given vertex in the form of an integer list. It * is equivalent to calling \c igraph.Graph.neighbors with \c type=OUT * * \return the successor list as a Python list object * \sa igraph_neighbors */ PyObject *igraphmodule_Graph_successors(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { PyObject *list, *index_o; igraph_integer_t idx; igraph_vector_t result; static char *kwlist[] = { "vertex", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O", kwlist, &index_o)) return NULL; if (igraphmodule_PyObject_to_vid(index_o, &idx, &self->g)) return NULL; igraph_vector_init(&result, 1); if (igraph_neighbors(&self->g, &result, idx, IGRAPH_OUT)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&result); return NULL; } list = igraphmodule_vector_t_to_PyList(&result, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&result); return list; } /** \ingroup python_interface_graph * \brief The predecessors of a given vertex in an \c igraph.Graph * This method accepts a single vertex ID as a parameter, and returns the * predecessors of the given vertex in the form of an integer list. It * is equivalent to calling \c igraph.Graph.neighbors with \c type=IN * * \return the predecessor list as a Python list object * \sa igraph_neighbors */ PyObject *igraphmodule_Graph_predecessors(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { PyObject *list, *index_o; igraph_integer_t idx; igraph_vector_t result; static char *kwlist[] = { "vertex", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O", kwlist, &index_o)) return NULL; if (igraphmodule_PyObject_to_vid(index_o, &idx, &self->g)) return NULL; igraph_vector_init(&result, 1); if (igraph_neighbors(&self->g, &result, idx, IGRAPH_IN)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&result); return NULL; } list = igraphmodule_vector_t_to_PyList(&result, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&result); return list; } /** \ingroup python_interface_graph * \brief Decides whether a graph is connected. * \return Py_True if the graph is connected, Py_False otherwise * \sa igraph_is_connected */ PyObject *igraphmodule_Graph_is_connected(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { char *kwlist[] = { "mode", NULL }; PyObject *mode_o = Py_None; igraph_connectedness_t mode = IGRAPH_STRONG; igraph_bool_t res; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O", kwlist, &mode_o)) return NULL; if (igraphmodule_PyObject_to_connectedness_t(mode_o, &mode)) return NULL; if (igraph_is_connected(&self->g, &res, mode)) { igraphmodule_handle_igraph_error(); return NULL; } if (res) Py_RETURN_TRUE; Py_RETURN_FALSE; } /** \ingroup python_interface_graph * \brief Decides whether there is an edge from a given vertex to an other one. * \return Py_True if the vertices are directly connected, Py_False otherwise * \sa igraph_are_connected */ PyObject *igraphmodule_Graph_are_connected(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "v1", "v2", NULL }; PyObject *v1, *v2; igraph_integer_t idx1, idx2; igraph_bool_t res; if (!PyArg_ParseTupleAndKeywords(args, kwds, "OO", kwlist, &v1, &v2)) return NULL; if (igraphmodule_PyObject_to_vid(v1, &idx1, &self->g)) return NULL; if (igraphmodule_PyObject_to_vid(v2, &idx2, &self->g)) return NULL; if (igraph_are_connected(&self->g, idx1, idx2, &res)) return igraphmodule_handle_igraph_error(); if (res) Py_RETURN_TRUE; Py_RETURN_FALSE; } /** \ingroup python_interface_graph * \brief Returns the ID of an arbitrary edge between the given two vertices * \sa igraph_get_eid */ PyObject *igraphmodule_Graph_get_eid(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "v1", "v2", "directed", "error", NULL }; PyObject *v1, *v2; PyObject *directed = Py_True; PyObject *error = Py_True; igraph_integer_t idx1, idx2; igraph_integer_t result; if (!PyArg_ParseTupleAndKeywords(args, kwds, "OO|OO", kwlist, &v1, &v2, &directed, &error)) return NULL; if (igraphmodule_PyObject_to_vid(v1, &idx1, &self->g)) return NULL; if (igraphmodule_PyObject_to_vid(v2, &idx2, &self->g)) return NULL; if (igraph_get_eid(&self->g, &result, idx1, idx2, PyObject_IsTrue(directed), PyObject_IsTrue(error))) return igraphmodule_handle_igraph_error(); return Py_BuildValue("l", (long)result); } /** \ingroup python_interface_graph * \brief Returns the IDs of some edges between some vertices * \sa igraph_get_eids */ PyObject *igraphmodule_Graph_get_eids(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "pairs", "path", "directed", "error", NULL }; PyObject *pairs_o = Py_None, *path_o = Py_None; PyObject *directed = Py_True; PyObject *error = Py_True; PyObject *result = NULL; igraph_vector_t pairs, path, res; igraph_bool_t pairs_owned = 0; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOOO", kwlist, &pairs_o, &path_o, &directed, &error)) return NULL; if (igraph_vector_init(&res, 0)) return igraphmodule_handle_igraph_error(); if (pairs_o != Py_None) { if (igraphmodule_PyObject_to_edgelist(pairs_o, &pairs, &self->g, &pairs_owned)) { igraph_vector_destroy(&res); return NULL; } } if (path_o != Py_None) { if (igraphmodule_PyObject_to_vector_t(path_o, &path, 1)) { igraph_vector_destroy(&res); if (pairs_owned) { igraph_vector_destroy(&pairs); } return NULL; } } if (igraph_get_eids(&self->g, &res, pairs_o == Py_None ? 0 : &pairs, path_o == Py_None ? 0 : &path, PyObject_IsTrue(directed), PyObject_IsTrue(error))) { if (pairs_owned) { igraph_vector_destroy(&pairs); } if (path_o != Py_None) { igraph_vector_destroy(&path); } igraph_vector_destroy(&res); return igraphmodule_handle_igraph_error(); } if (pairs_owned) { igraph_vector_destroy(&pairs); } if (path_o != Py_None) { igraph_vector_destroy(&path); } result = igraphmodule_vector_t_to_PyList(&res, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&res); return result; } /** \ingroup python_interface_graph * \brief Calculates the diameter of an \c igraph.Graph * This method accepts two optional parameters: the first one is * a boolean meaning whether to consider directed paths (and is * ignored for undirected graphs). The second one is only meaningful * in unconnected graphs: it is \c True if the longest geodesic * within a component should be returned and \c False if the number of * vertices should be returned. They both have a default value of \c False. * * \return the diameter as a Python integer * \sa igraph_diameter */ PyObject *igraphmodule_Graph_diameter(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { PyObject *dir = Py_True, *vcount_if_unconnected = Py_True; PyObject *weights_o = Py_None; igraph_vector_t *weights = 0; static char *kwlist[] = { "directed", "unconn", "weights", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOO", kwlist, &dir, &vcount_if_unconnected, &weights_o)) return NULL; if (igraphmodule_attrib_to_vector_t(weights_o, self, &weights, ATTRIBUTE_TYPE_EDGE)) return NULL; if (weights) { igraph_real_t i; if (igraph_diameter_dijkstra(&self->g, weights, &i, 0, 0, 0, PyObject_IsTrue(dir), PyObject_IsTrue(vcount_if_unconnected))) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(weights); free(weights); return NULL; } igraph_vector_destroy(weights); free(weights); return PyFloat_FromDouble((double)i); } else { igraph_integer_t i; if (igraph_diameter(&self->g, &i, 0, 0, 0, PyObject_IsTrue(dir), PyObject_IsTrue(vcount_if_unconnected))) { igraphmodule_handle_igraph_error(); return NULL; } return PyInt_FromLong((long)i); } } /** \ingroup python_interface_graph * \brief Returns a path of the actual diameter of the graph * \sa igraph_diameter */ PyObject *igraphmodule_Graph_get_diameter(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { PyObject *dir = Py_True, *vcount_if_unconnected = Py_True, *result; PyObject *weights_o = Py_None; igraph_vector_t *weights = 0; igraph_vector_t res; static char *kwlist[] = { "directed", "unconn", "weights", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOO", kwlist, &dir, &vcount_if_unconnected, &weights_o)) return NULL; if (igraphmodule_attrib_to_vector_t(weights_o, self, &weights, ATTRIBUTE_TYPE_EDGE)) return NULL; igraph_vector_init(&res, 0); if (weights) { if (igraph_diameter_dijkstra(&self->g, weights, 0, 0, 0, &res, PyObject_IsTrue(dir), PyObject_IsTrue(vcount_if_unconnected))) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(weights); free(weights); igraph_vector_destroy(&res); return NULL; } igraph_vector_destroy(weights); free(weights); } else { if (igraph_diameter(&self->g, 0, 0, 0, &res, PyObject_IsTrue(dir), PyObject_IsTrue(vcount_if_unconnected))) { igraphmodule_handle_igraph_error(); return NULL; } } result = igraphmodule_vector_t_to_PyList(&res, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&res); return result; } /** \ingroup python_interface_graph * \brief Returns the farthest points and their distances in the graph * \sa igraph_distance */ PyObject *igraphmodule_Graph_farthest_points(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { PyObject *dir = Py_True, *vcount_if_unconnected = Py_True; PyObject *weights_o = Py_None; igraph_vector_t *weights = 0; igraph_integer_t from, to, len; igraph_real_t len_real; static char *kwlist[] = { "directed", "unconn", "weights", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOO", kwlist, &dir, &vcount_if_unconnected, &weights_o)) return NULL; if (igraphmodule_attrib_to_vector_t(weights_o, self, &weights, ATTRIBUTE_TYPE_EDGE)) return NULL; if (weights) { if (igraph_diameter_dijkstra(&self->g, weights, &len_real, &from, &to, 0, PyObject_IsTrue(dir), PyObject_IsTrue(vcount_if_unconnected))) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(weights); free(weights); return NULL; } igraph_vector_destroy(weights); free(weights); if (from >= 0) return Py_BuildValue("lld", (long)from, (long)to, (double)len_real); return Py_BuildValue("OOd", Py_None, Py_None, (double)len_real); } else { if (igraph_diameter(&self->g, &len, &from, &to, 0, PyObject_IsTrue(dir), PyObject_IsTrue(vcount_if_unconnected))) { igraphmodule_handle_igraph_error(); return NULL; } if (from >= 0) return Py_BuildValue("lll", (long)from, (long)to, (long)len); return Py_BuildValue("OOl", Py_None, Py_None, (long)len); } } /** * \ingroup python_interface_graph * \brief Calculates the girth of an \c igraph.Graph */ PyObject *igraphmodule_Graph_girth(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { PyObject *sc = Py_False; static char *kwlist[] = { "return_shortest_circle", NULL }; igraph_integer_t girth; igraph_vector_t vids; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O", kwlist, &sc)) return NULL; igraph_vector_init(&vids, 0); if (igraph_girth(&self->g, &girth, &vids)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&vids); return NULL; } if (PyObject_IsTrue(sc)) { PyObject* o; o=igraphmodule_vector_t_to_PyList(&vids, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&vids); return o; } return PyInt_FromLong((long)girth); } /** * \ingroup python_interface_graph * \brief Calculates the convergence degree of the edges in a graph */ PyObject *igraphmodule_Graph_convergence_degree(igraphmodule_GraphObject *self) { igraph_vector_t result; PyObject *o; igraph_vector_init(&result, 0); if (igraph_convergence_degree(&self->g, &result, 0, 0)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&result); return NULL; } o=igraphmodule_vector_t_to_PyList(&result, IGRAPHMODULE_TYPE_FLOAT); igraph_vector_destroy(&result); return o; } /** * \ingroup python_interface_graph * \brief Calculates the sizes of the convergence fields in a graph */ PyObject *igraphmodule_Graph_convergence_field_size(igraphmodule_GraphObject *self) { igraph_vector_t ins, outs; PyObject *o1, *o2; igraph_vector_init(&ins, 0); igraph_vector_init(&outs, 0); if (igraph_convergence_degree(&self->g, 0, &ins, &outs)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&ins); igraph_vector_destroy(&outs); return NULL; } o1=igraphmodule_vector_t_to_PyList(&ins, IGRAPHMODULE_TYPE_INT); o2=igraphmodule_vector_t_to_PyList(&outs, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&ins); igraph_vector_destroy(&outs); return Py_BuildValue("NN", o1, o2); } /** * \ingroup python_interface_graph * \brief Calculates the average nearest neighbor degree of the vertices * of a \c igraph.Graph */ PyObject *igraphmodule_Graph_knn(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = { "vids", "weights", NULL }; PyObject *vids_obj = Py_None, *weights_obj = Py_None; PyObject *knn_obj, *knnk_obj; igraph_vector_t *weights = 0; igraph_vector_t knn, knnk; igraph_vs_t vids; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OO", kwlist, &vids_obj, &weights_obj)) { return NULL; } if (igraph_vector_init(&knn, 0)) { igraphmodule_handle_igraph_error(); return NULL; } if (igraph_vector_init(&knnk, 0)) { igraph_vector_destroy(&knn); igraphmodule_handle_igraph_error(); return NULL; } if (igraphmodule_PyObject_to_vs_t(vids_obj, &vids, &self->g, 0, 0)) { igraph_vector_destroy(&knn); igraph_vector_destroy(&knnk); igraphmodule_handle_igraph_error(); return NULL; } if (igraphmodule_attrib_to_vector_t(weights_obj, self, &weights, ATTRIBUTE_TYPE_EDGE)) { igraph_vs_destroy(&vids); igraph_vector_destroy(&knn); igraph_vector_destroy(&knnk); return NULL; } if (igraph_avg_nearest_neighbor_degree(&self->g, vids, IGRAPH_ALL, IGRAPH_ALL, &knn, &knnk, weights)) { igraphmodule_handle_igraph_error(); igraph_vs_destroy(&vids); igraph_vector_destroy(&knn); igraph_vector_destroy(&knnk); if (weights) { igraph_vector_destroy(weights); free(weights); } return NULL; } igraph_vs_destroy(&vids); if (weights) { igraph_vector_destroy(weights); free(weights); } knn_obj = igraphmodule_vector_t_to_PyList(&knn, IGRAPHMODULE_TYPE_FLOAT); igraph_vector_destroy(&knn); if (!knn_obj) { igraph_vector_destroy(&knnk); return NULL; } knnk_obj = igraphmodule_vector_t_to_PyList(&knnk, IGRAPHMODULE_TYPE_FLOAT); igraph_vector_destroy(&knnk); if (!knnk_obj) { Py_DECREF(knn_obj); return NULL; } return Py_BuildValue("NN", knn_obj, knnk_obj); } /** \ingroup python_interface_graph * \brief Calculates the radius of an \c igraph.Graph * * \return the radius as a Python integer * \sa igraph_radius */ PyObject *igraphmodule_Graph_radius(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { PyObject *mode_o = Py_None; igraph_neimode_t mode = IGRAPH_OUT; igraph_real_t radius; static char *kwlist[] = { "mode", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O", kwlist, &mode_o)) return NULL; if (igraphmodule_PyObject_to_neimode_t(mode_o, &mode)) return NULL; if (igraph_radius(&self->g, &radius, mode)) { igraphmodule_handle_igraph_error(); return NULL; } return PyFloat_FromDouble((double)radius); } /** \ingroup python_interface_graph * \brief Converts a tree graph into a Prufer sequence * \return the Prufer sequence as a Python object * \sa igraph_to_prufer */ PyObject *igraphmodule_Graph_to_prufer(igraphmodule_GraphObject * self) { igraph_vector_int_t result; PyObject *list; if (igraph_vector_int_init(&result, 0)) { return NULL; } if (igraph_to_prufer(&self->g, &result)) { igraphmodule_handle_igraph_error(); igraph_vector_int_destroy(&result); return NULL; } list = igraphmodule_vector_int_t_to_PyList(&result); igraph_vector_int_destroy(&result); return list; } /********************************************************************** * Deterministic and non-deterministic graph generators * **********************************************************************/ /** \ingroup python_interface_graph * \brief Generates a graph from its adjacency matrix * \return a reference to the newly generated Python igraph object * \sa igraph_adjacency */ PyObject *igraphmodule_Graph_Adjacency(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; igraph_t g; igraph_matrix_t m; PyObject *matrix, *mode_o = Py_None; igraph_adjacency_t mode = IGRAPH_ADJ_DIRECTED; static char *kwlist[] = { "matrix", "mode", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O!|O", kwlist, &PyList_Type, &matrix, &mode_o)) return NULL; if (igraphmodule_PyObject_to_adjacency_t(mode_o, &mode)) return NULL; if (igraphmodule_PyList_to_matrix_t(matrix, &m)) { PyErr_SetString(PyExc_TypeError, "Error while converting adjacency matrix"); return NULL; } if (igraph_adjacency(&g, &m, mode)) { igraphmodule_handle_igraph_error(); igraph_matrix_destroy(&m); return NULL; } igraph_matrix_destroy(&m); CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Generates a graph from the Graph Atlas * \return a reference to the newly generated Python igraph object * \sa igraph_atlas */ PyObject *igraphmodule_Graph_Atlas(PyTypeObject * type, PyObject * args) { long n; igraphmodule_GraphObject *self; igraph_t g; if (!PyArg_ParseTuple(args, "l", &n)) return NULL; if (igraph_atlas(&g, (igraph_integer_t) n)) { igraphmodule_handle_igraph_error(); return NULL; } CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Generates a graph based on the Barabasi-Albert model * This is intended to be a class method in Python, so the first argument * is the type object and not the Python igraph object (because we have * to allocate that in this method). * * \return a reference to the newly generated Python igraph object * \sa igraph_barabasi_game */ PyObject *igraphmodule_Graph_Barabasi(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; igraph_t g; long n, m = 1; float power = 1.0f, zero_appeal = 1.0f; igraph_vector_t outseq; igraph_t *start_from = 0; igraph_barabasi_algorithm_t algo = IGRAPH_BARABASI_PSUMTREE; PyObject *m_obj = 0, *outpref = Py_False, *directed = Py_False; PyObject *implementation_o = Py_None; PyObject *start_from_o = Py_None; static char *kwlist[] = { "n", "m", "outpref", "directed", "power", "zero_appeal", "implementation", "start_from", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "l|OOOffOO", kwlist, &n, &m_obj, &outpref, &directed, &power, &zero_appeal, &implementation_o, &start_from_o)) return NULL; if (igraphmodule_PyObject_to_barabasi_algorithm_t(implementation_o, &algo)) return NULL; if (igraphmodule_PyObject_to_igraph_t(start_from_o, &start_from)) return NULL; if (n < 0) { PyErr_SetString(PyExc_ValueError, "Number of vertices must be positive."); return NULL; } if (m_obj == 0) { igraph_vector_init(&outseq, 0); m = 1; } else if (m_obj != 0) { /* let's check whether we have a constant out-degree or a list */ if (PyInt_Check(m_obj)) { m = PyInt_AsLong(m_obj); igraph_vector_init(&outseq, 0); } else if (PyList_Check(m_obj)) { if (igraphmodule_PyObject_to_vector_t(m_obj, &outseq, 1)) { /* something bad happened during conversion */ return NULL; } } else { PyErr_SetString(PyExc_TypeError, "m must be an integer or a list of integers"); return NULL; } } if (igraph_barabasi_game(&g, (igraph_integer_t) n, (igraph_real_t) power, (igraph_integer_t) m, &outseq, PyObject_IsTrue(outpref), (igraph_real_t) zero_appeal, PyObject_IsTrue(directed), algo, start_from)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&outseq); return NULL; } igraph_vector_destroy(&outseq); CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Generates a bipartite graph * \return a reference to the newly generated Python igraph object * \sa igraph_barabasi_game */ PyObject *igraphmodule_Graph_Bipartite(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; igraph_t g; igraph_vector_bool_t types; igraph_vector_t edges; igraph_bool_t edges_owned = 0; PyObject *types_o, *edges_o, *directed = Py_False; static char *kwlist[] = { "types", "edges", "directed", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "OO|O", kwlist, &types_o, &edges_o, &directed)) return NULL; if (igraphmodule_PyObject_to_vector_bool_t(types_o, &types)) return NULL; if (igraphmodule_PyObject_to_edgelist(edges_o, &edges, 0, &edges_owned)) { igraph_vector_bool_destroy(&types); return NULL; } if (igraph_create_bipartite(&g, &types, &edges, PyObject_IsTrue(directed))) { igraphmodule_handle_igraph_error(); if (edges_owned) { igraph_vector_destroy(&edges); } igraph_vector_bool_destroy(&types); return NULL; } if (edges_owned) { igraph_vector_destroy(&edges); } igraph_vector_bool_destroy(&types); CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Generates a De Bruijn graph * \sa igraph_kautz */ PyObject *igraphmodule_Graph_De_Bruijn(PyTypeObject *type, PyObject *args, PyObject *kwds) { long int m, n; igraphmodule_GraphObject *self; igraph_t g; static char *kwlist[] = {"m", "n", NULL}; if (!PyArg_ParseTupleAndKeywords(args, kwds, "ll", kwlist, &m, &n)) return NULL; if (igraph_de_bruijn(&g, (igraph_integer_t) m, (igraph_integer_t) n)) { igraphmodule_handle_igraph_error(); return NULL; } CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject*)self; } /** \ingroup python_interface_graph * \brief Generates a random graph with a given degree sequence * This is intended to be a class method in Python, so the first argument * is the type object and not the Python igraph object (because we have * to allocate that in this method). * * \return a reference to the newly generated Python igraph object * \sa igraph_degree_sequence_game */ PyObject *igraphmodule_Graph_Degree_Sequence(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; igraph_t g; igraph_vector_t outseq, inseq; igraph_degseq_t meth = IGRAPH_DEGSEQ_SIMPLE; igraph_bool_t has_inseq = 0; PyObject *outdeg = NULL, *indeg = NULL, *method = NULL; static char *kwlist[] = { "out", "in", "method", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O!|O!O", kwlist, &PyList_Type, &outdeg, &PyList_Type, &indeg, &method)) return NULL; if (igraphmodule_PyObject_to_degseq_t(method, &meth)) return NULL; if (igraphmodule_PyObject_to_vector_t(outdeg, &outseq, 1)) return NULL; if (indeg) { if (igraphmodule_PyObject_to_vector_t(indeg, &inseq, 1)) { igraph_vector_destroy(&outseq); return NULL; } has_inseq=1; } if (igraph_degree_sequence_game(&g, &outseq, has_inseq ? &inseq : 0, meth)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&outseq); if (has_inseq) igraph_vector_destroy(&inseq); return NULL; } igraph_vector_destroy(&outseq); if (has_inseq) igraph_vector_destroy(&inseq); CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Generates a graph based on the Erdos-Renyi model * \return a reference to the newly generated Python igraph object * \sa igraph_erdos_renyi_game */ PyObject *igraphmodule_Graph_Erdos_Renyi(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; igraph_t g; long n, m = -1; double p = -1.0; igraph_erdos_renyi_t t; PyObject *loops = Py_False, *directed = Py_False; static char *kwlist[] = { "n", "p", "m", "directed", "loops", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "l|dlOO", kwlist, &n, &p, &m, &directed, &loops)) return NULL; if (m == -1 && p == -1.0) { /* no density parameters were given, throw exception */ PyErr_SetString(PyExc_TypeError, "Either m or p must be given."); return NULL; } if (m != -1 && p != -1.0) { /* both density parameters were given, throw exception */ PyErr_SetString(PyExc_TypeError, "Only one must be given from m and p."); return NULL; } t = (m == -1) ? IGRAPH_ERDOS_RENYI_GNP : IGRAPH_ERDOS_RENYI_GNM; if (igraph_erdos_renyi_game(&g, t, (igraph_integer_t) n, (igraph_real_t) (m == -1 ? p : m), PyObject_IsTrue(directed), PyObject_IsTrue(loops))) { igraphmodule_handle_igraph_error(); return NULL; } CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Generates a graph based on a simple growing model with vertex types * \return a reference to the newly generated Python igraph object * \sa igraph_establishment_game */ PyObject *igraphmodule_Graph_Establishment(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; igraph_t g; long n, types, k; PyObject *type_dist, *pref_matrix; PyObject *directed = Py_False; igraph_matrix_t pm; igraph_vector_t td; char *kwlist[] = { "n", "k", "type_dist", "pref_matrix", "directed", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "llO!O!|O", kwlist, &n, &k, &PyList_Type, &type_dist, &PyList_Type, &pref_matrix, &directed)) return NULL; if (n <= 0 || k <= 0) { PyErr_SetString(PyExc_ValueError, "Number of vertices and the amount of connection trials per step must be positive."); return NULL; } types = PyList_Size(type_dist); if (igraphmodule_PyList_to_matrix_t(pref_matrix, &pm)) { PyErr_SetString(PyExc_TypeError, "Error while converting preference matrix"); return NULL; } if (igraph_matrix_nrow(&pm) != igraph_matrix_ncol(&pm) || igraph_matrix_nrow(&pm) != types) { PyErr_SetString(PyExc_ValueError, "Preference matrix must have exactly the same rows and columns as the number of types"); igraph_matrix_destroy(&pm); return NULL; } if (igraphmodule_PyObject_to_vector_t(type_dist, &td, 1)) { PyErr_SetString(PyExc_ValueError, "Error while converting type distribution vector"); igraph_matrix_destroy(&pm); return NULL; } if (igraph_establishment_game(&g, (igraph_integer_t) n, (igraph_integer_t) types, (igraph_integer_t) k, &td, &pm, PyObject_IsTrue(directed))) { igraphmodule_handle_igraph_error(); igraph_matrix_destroy(&pm); igraph_vector_destroy(&td); return NULL; } igraph_matrix_destroy(&pm); igraph_vector_destroy(&td); CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Generates a famous graph by name * \return a reference to the newly generated Python igraph object * \sa igraph_famous */ PyObject *igraphmodule_Graph_Famous(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; igraph_t g; const char* name; static char *kwlist[] = { "name", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "s", kwlist, &name)) return NULL; if (igraph_famous(&g, name)) { igraphmodule_handle_igraph_error(); return NULL; } CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Generates a graph based on the forest fire model * \return a reference to the newly generated Python igraph object * \sa igraph_forest_fire_game */ PyObject *igraphmodule_Graph_Forest_Fire(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; igraph_t g; long n, ambs=1; double fw_prob, bw_factor=0.0; PyObject *directed = Py_False; static char *kwlist[] = {"n", "fw_prob", "bw_factor", "ambs", "directed", NULL}; if (!PyArg_ParseTupleAndKeywords(args, kwds, "ld|dlO", kwlist, &n, &fw_prob, &bw_factor, &ambs, &directed)) return NULL; if (igraph_forest_fire_game(&g, (igraph_integer_t)n, (igraph_real_t)fw_prob, (igraph_real_t)bw_factor, (igraph_integer_t)ambs, (igraph_bool_t)(PyObject_IsTrue(directed)))) { igraphmodule_handle_igraph_error(); return NULL; } CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Generates a full graph * \return a reference to the newly generated Python igraph object * \sa igraph_full */ PyObject *igraphmodule_Graph_Full(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; igraph_t g; long n; PyObject *loops = Py_False, *directed = Py_False; char *kwlist[] = { "n", "directed", "loops", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "l|OO", kwlist, &n, &directed, &loops)) return NULL; if (n < 0) { PyErr_SetString(PyExc_ValueError, "Number of vertices must be positive."); return NULL; } if (igraph_full(&g, (igraph_integer_t) n, PyObject_IsTrue(directed), PyObject_IsTrue(loops))) { igraphmodule_handle_igraph_error(); return NULL; } CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Generates a full bipartite graph * \sa igraph_full_bipartite */ PyObject *igraphmodule_Graph_Full_Bipartite(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; igraph_t g; igraph_vector_bool_t vertex_types; igraph_neimode_t mode = IGRAPH_ALL; long int n1, n2; PyObject *mode_o = Py_None, *directed = Py_False, *vertex_types_o = 0; static char *kwlist[] = { "n1", "n2", "directed", "mode", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "ll|OO", kwlist, &n1, &n2, &directed, &mode_o)) return NULL; if (n1 < 0 || n2 < 0) { PyErr_SetString(PyExc_ValueError, "Number of vertices must be positive."); return NULL; } if (igraphmodule_PyObject_to_neimode_t(mode_o, &mode)) return NULL; if (igraph_vector_bool_init(&vertex_types, n1+n2)) { igraphmodule_handle_igraph_error(); return NULL; } if (igraph_full_bipartite(&g, &vertex_types, (igraph_integer_t) n1, (igraph_integer_t) n2, PyObject_IsTrue(directed), mode)) { igraph_vector_bool_destroy(&vertex_types); igraphmodule_handle_igraph_error(); return NULL; } CREATE_GRAPH_FROM_TYPE(self, g, type); vertex_types_o = igraphmodule_vector_bool_t_to_PyList(&vertex_types); igraph_vector_bool_destroy(&vertex_types); if (vertex_types_o == 0) return NULL; return Py_BuildValue("NN", (PyObject *) self, vertex_types_o); } /** \ingroup python_interface_graph * \brief Generates a full citation graph * \return a reference to the newly generated Python igraph object * \sa igraph_full */ PyObject *igraphmodule_Graph_Full_Citation(PyTypeObject *type, PyObject *args, PyObject *kwds) { igraphmodule_GraphObject *self; igraph_t g; long n; PyObject *directed = Py_False; char *kwlist[] = { "n", "directed", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "l|O", kwlist, &n, &directed)) return NULL; if (igraph_full_citation(&g, (igraph_integer_t) n, (igraph_bool_t) PyObject_IsTrue(directed))) { igraphmodule_handle_igraph_error(); return NULL; } CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Generates a graph based on the geometric random model * \return a reference to the newly generated Python igraph object * \sa igraph_grg_game */ PyObject *igraphmodule_Graph_GRG(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; igraph_t g; long n; double r; PyObject *torus = Py_False; PyObject *o_xs, *o_ys; igraph_vector_t xs, ys; static char *kwlist[] = { "n", "radius", "torus", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "ld|O", kwlist, &n, &r, &torus)) return NULL; if (igraph_vector_init(&xs, 0)) { igraphmodule_handle_igraph_error(); return NULL; } else if (igraph_vector_init(&ys, 0)) { igraph_vector_destroy(&xs); igraphmodule_handle_igraph_error(); return NULL; } if (igraph_grg_game(&g, (igraph_integer_t) n, (igraph_real_t) r, PyObject_IsTrue(torus), &xs, &ys)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&xs); igraph_vector_destroy(&ys); return NULL; } o_xs = igraphmodule_vector_t_to_PyList(&xs, IGRAPHMODULE_TYPE_FLOAT); igraph_vector_destroy(&xs); if (!o_xs) { igraph_destroy(&g); igraph_vector_destroy(&ys); return NULL; } o_ys = igraphmodule_vector_t_to_PyList(&ys, IGRAPHMODULE_TYPE_FLOAT); igraph_vector_destroy(&ys); if (!o_ys) { igraph_destroy(&g); Py_DECREF(o_xs); return NULL; } CREATE_GRAPH_FROM_TYPE(self, g, type); return Py_BuildValue("NNN", (PyObject*)self, o_xs, o_ys); } /** \ingroup python_interface_graph * \brief Generates a growing random graph * \return a reference to the newly generated Python igraph object * \sa igraph_growing_random_game */ PyObject *igraphmodule_Graph_Growing_Random(PyTypeObject * type, PyObject * args, PyObject * kwds) { long n, m; PyObject *directed = NULL, *citation = NULL; igraphmodule_GraphObject *self; igraph_t g; static char *kwlist[] = { "n", "m", "directed", "citation", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "ll|O!O!", kwlist, &n, &m, &PyBool_Type, &directed, &PyBool_Type, &citation)) return NULL; if (n < 0) { PyErr_SetString(PyExc_ValueError, "Number of vertices must be positive."); return NULL; } if (m < 0) { PyErr_SetString(PyExc_ValueError, "Number of new edges per iteration must be positive."); return NULL; } if (igraph_growing_random_game(&g, (igraph_integer_t) n, (igraph_integer_t) m, (directed == Py_True), (citation == Py_True))) { igraphmodule_handle_igraph_error(); return NULL; } CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Generates a bipartite graph from an incidence matrix * \return a reference to the newly generated Python igraph object * \sa igraph_incidence */ PyObject *igraphmodule_Graph_Incidence(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; igraph_matrix_t matrix; igraph_vector_bool_t vertex_types; igraph_t g; PyObject *matrix_o, *vertex_types_o; PyObject *mode_o = Py_None, *directed = Py_False, *multiple = Py_False; igraph_neimode_t mode = IGRAPH_OUT; static char *kwlist[] = { "matrix", "directed", "mode", "multiple", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O!|OOO", kwlist, &PyList_Type, &matrix_o, &directed, &mode_o, &multiple)) return NULL; if (igraphmodule_PyObject_to_neimode_t(mode_o, &mode)) return NULL; if (igraph_vector_bool_init(&vertex_types, 0)) { igraphmodule_handle_igraph_error(); return NULL; } if (igraphmodule_PyList_to_matrix_t(matrix_o, &matrix)) { igraph_vector_bool_destroy(&vertex_types); PyErr_SetString(PyExc_TypeError, "Error while converting incidence matrix"); return NULL; } if (igraph_incidence(&g, &vertex_types, &matrix, PyObject_IsTrue(directed), mode, PyObject_IsTrue(multiple))) { igraphmodule_handle_igraph_error(); igraph_matrix_destroy(&matrix); igraph_vector_bool_destroy(&vertex_types); return NULL; } igraph_matrix_destroy(&matrix); CREATE_GRAPH_FROM_TYPE(self, g, type); vertex_types_o = igraphmodule_vector_bool_t_to_PyList(&vertex_types); igraph_vector_bool_destroy(&vertex_types); if (vertex_types_o == 0) return NULL; return Py_BuildValue("NN", (PyObject *) self, vertex_types_o); } /** \ingroup python_interface_graph * \brief Generates a graph with a given isomorphy class * This is intended to be a class method in Python, so the first argument * is the type object and not the Python igraph object (because we have * to allocate that in this method). * * \return a reference to the newly generated Python igraph object * \sa igraph_isoclass_create */ PyObject *igraphmodule_Graph_Isoclass(PyTypeObject * type, PyObject * args, PyObject * kwds) { long int n, isoclass; PyObject *directed = Py_False; igraphmodule_GraphObject *self; igraph_t g; static char *kwlist[] = { "n", "class", "directed", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "ll|O", kwlist, &n, &isoclass, &directed)) return NULL; if (n < 3 || n > 4) { PyErr_SetString(PyExc_ValueError, "Only graphs with 3 or 4 vertices are supported"); return NULL; } if (igraph_isoclass_create(&g, (igraph_integer_t) n, (igraph_integer_t) isoclass, PyObject_IsTrue(directed))) { igraphmodule_handle_igraph_error(); return NULL; } CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Generates a Kautz graph * \sa igraph_kautz */ PyObject *igraphmodule_Graph_Kautz(PyTypeObject *type, PyObject *args, PyObject *kwds) { long int m, n; igraphmodule_GraphObject *self; igraph_t g; static char *kwlist[] = {"m", "n", NULL}; if (!PyArg_ParseTupleAndKeywords(args, kwds, "ll", kwlist, &m, &n)) return NULL; if (igraph_kautz(&g, (igraph_integer_t) m, (igraph_integer_t) n)) { igraphmodule_handle_igraph_error(); return NULL; } CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject*)self; } /** \ingroup python_interface_graph * \brief Generates a k-regular random graph * \return a reference to the newly generated Python igraph object * \sa igraph_k_regular_game */ PyObject *igraphmodule_Graph_K_Regular(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; igraph_t g; long int n, k; PyObject *directed_o = Py_False, *multiple_o = Py_False; static char *kwlist[] = { "n", "k", "directed", "multiple", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "ll|OO", kwlist, &n, &k, &directed_o, &multiple_o)) return NULL; if (igraph_k_regular_game(&g, (igraph_integer_t) n, (igraph_integer_t) k, PyObject_IsTrue(directed_o), PyObject_IsTrue(multiple_o))) { igraphmodule_handle_igraph_error(); return NULL; } CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject*)self; } /** \ingroup python_interface_graph * \brief Generates a regular lattice * \return a reference to the newly generated Python igraph object * \sa igraph_lattice */ PyObject *igraphmodule_Graph_Lattice(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraph_vector_t dimvector; long int nei = 1; igraph_bool_t directed; igraph_bool_t mutual; igraph_bool_t circular; PyObject *o_directed = Py_False, *o_mutual = Py_True, *o_circular = Py_True; PyObject *o_dimvector = Py_None; igraphmodule_GraphObject *self; igraph_t g; static char *kwlist[] = { "dim", "nei", "directed", "mutual", "circular", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O!|lOOO", kwlist, &PyList_Type, &o_dimvector, &nei, &o_directed, &o_mutual, &o_circular)) return NULL; directed = PyObject_IsTrue(o_directed); mutual = PyObject_IsTrue(o_mutual); circular = PyObject_IsTrue(o_circular); if (igraphmodule_PyObject_to_vector_t(o_dimvector, &dimvector, 1)) return NULL; if (igraph_lattice(&g, &dimvector, (igraph_integer_t) nei, directed, mutual, circular)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&dimvector); return NULL; } igraph_vector_destroy(&dimvector); CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Generates a 3-regular Hamiltonian graph from LCF notation * \return a reference to the newly generated Python igraph object * \sa igraph_lattice */ PyObject *igraphmodule_Graph_LCF(PyTypeObject *type, PyObject *args, PyObject *kwds) { igraph_vector_t shifts; long int repeats, n; PyObject *o_shifts; igraphmodule_GraphObject *self; igraph_t g; static char *kwlist[] = { "n", "shifts", "repeats", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "lOl", kwlist, &n, &o_shifts, &repeats)) return NULL; if (igraphmodule_PyObject_to_vector_t(o_shifts, &shifts, 0)) return NULL; if (igraph_lcf_vector(&g, (igraph_integer_t) n, &shifts, (igraph_integer_t) repeats)) { igraph_vector_destroy(&shifts); igraphmodule_handle_igraph_error(); return NULL; } igraph_vector_destroy(&shifts); CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Generates a graph based on vertex types and connection preferences * \return a reference to the newly generated Python igraph object * \sa igraph_preference_game */ PyObject *igraphmodule_Graph_Preference(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; igraph_t g; long n, types; PyObject *type_dist, *pref_matrix; PyObject *directed = Py_False; PyObject *loops = Py_False; igraph_matrix_t pm; igraph_vector_t td; igraph_vector_t type_vec; PyObject *type_vec_o; PyObject *attribute_key = Py_None; igraph_bool_t store_attribs; char *kwlist[] = { "n", "type_dist", "pref_matrix", "attribute", "directed", "loops", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "lO!O!|OOO", kwlist, &n, &PyList_Type, &type_dist, &PyList_Type, &pref_matrix, &attribute_key, &directed, &loops)) return NULL; types = PyList_Size(type_dist); if (igraphmodule_PyList_to_matrix_t(pref_matrix, &pm)) return NULL; if (igraphmodule_PyObject_float_to_vector_t(type_dist, &td)) { igraph_matrix_destroy(&pm); return NULL; } store_attribs = (attribute_key && attribute_key != Py_None); if (store_attribs && igraph_vector_init(&type_vec, (igraph_integer_t) n)) { igraph_matrix_destroy(&pm); igraph_vector_destroy(&td); igraphmodule_handle_igraph_error(); return NULL; } if (igraph_preference_game(&g, (igraph_integer_t) n, (igraph_integer_t) types, &td, 0, &pm, store_attribs ? &type_vec : 0, PyObject_IsTrue(directed), PyObject_IsTrue(loops))) { igraphmodule_handle_igraph_error(); igraph_matrix_destroy(&pm); igraph_vector_destroy(&td); if (store_attribs) igraph_vector_destroy(&type_vec); return NULL; } CREATE_GRAPH_FROM_TYPE(self, g, type); if (store_attribs) { type_vec_o = igraphmodule_vector_t_to_PyList(&type_vec, IGRAPHMODULE_TYPE_INT); if (type_vec_o == 0) { igraph_matrix_destroy(&pm); igraph_vector_destroy(&td); igraph_vector_destroy(&type_vec); Py_DECREF(self); return NULL; } if (attribute_key != Py_None && attribute_key != 0) { if (PyDict_SetItem(ATTR_STRUCT_DICT(&self->g)[ATTRHASH_IDX_VERTEX], attribute_key, type_vec_o) == -1) { Py_DECREF(type_vec_o); igraph_matrix_destroy(&pm); igraph_vector_destroy(&td); igraph_vector_destroy(&type_vec); Py_DECREF(self); return NULL; } } Py_DECREF(type_vec_o); igraph_vector_destroy(&type_vec); } igraph_matrix_destroy(&pm); igraph_vector_destroy(&td); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Generates a graph based on asymmetric vertex types and connection preferences * \return a reference to the newly generated Python igraph object * \sa igraph_asymmetric_preference_game */ PyObject *igraphmodule_Graph_Asymmetric_Preference(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; igraph_t g; long n, types; PyObject *type_dist_matrix, *pref_matrix; PyObject *loops = Py_False; igraph_matrix_t pm; igraph_matrix_t td; igraph_vector_t in_type_vec, out_type_vec; PyObject *type_vec_o; PyObject *attribute_key = Py_None; igraph_bool_t store_attribs; char *kwlist[] = { "n", "type_dist_matrix", "pref_matrix", "attribute", "loops", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "lO!O!|OO", kwlist, &n, &PyList_Type, &type_dist_matrix, &PyList_Type, &pref_matrix, &attribute_key, &loops)) return NULL; types = PyList_Size(type_dist_matrix); if (igraphmodule_PyList_to_matrix_t(pref_matrix, &pm)) return NULL; if (igraphmodule_PyList_to_matrix_t(type_dist_matrix, &td)) { igraph_matrix_destroy(&pm); return NULL; } store_attribs = (attribute_key && attribute_key != Py_None); if (store_attribs) { if (igraph_vector_init(&in_type_vec, (igraph_integer_t) n)) { igraph_matrix_destroy(&pm); igraph_matrix_destroy(&td); igraphmodule_handle_igraph_error(); return NULL; } if (igraph_vector_init(&out_type_vec, (igraph_integer_t) n)) { igraph_matrix_destroy(&pm); igraph_matrix_destroy(&td); igraph_vector_destroy(&in_type_vec); igraphmodule_handle_igraph_error(); return NULL; } } if (igraph_asymmetric_preference_game(&g, (igraph_integer_t) n, (igraph_integer_t) types, &td, &pm, store_attribs ? &in_type_vec : 0, store_attribs ? &out_type_vec : 0, PyObject_IsTrue(loops))) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&in_type_vec); igraph_vector_destroy(&out_type_vec); igraph_matrix_destroy(&pm); igraph_matrix_destroy(&td); return NULL; } CREATE_GRAPH_FROM_TYPE(self, g, type); if (store_attribs) { type_vec_o = igraphmodule_vector_t_pair_to_PyList(&in_type_vec, &out_type_vec); if (type_vec_o == NULL) { igraph_matrix_destroy(&pm); igraph_matrix_destroy(&td); igraph_vector_destroy(&in_type_vec); igraph_vector_destroy(&out_type_vec); Py_DECREF(self); return NULL; } if (attribute_key != Py_None && attribute_key != 0) { if (PyDict_SetItem(ATTR_STRUCT_DICT(&self->g)[ATTRHASH_IDX_VERTEX], attribute_key, type_vec_o) == -1) { Py_DECREF(type_vec_o); igraph_matrix_destroy(&pm); igraph_matrix_destroy(&td); igraph_vector_destroy(&in_type_vec); igraph_vector_destroy(&out_type_vec); Py_DECREF(self); return NULL; } } Py_DECREF(type_vec_o); igraph_vector_destroy(&in_type_vec); igraph_vector_destroy(&out_type_vec); } igraph_matrix_destroy(&pm); igraph_matrix_destroy(&td); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Generates a bipartite graph based on the Erdos-Renyi model * \return a reference to the newly generated Python igraph object * \sa igraph_bipartite_game */ PyObject *igraphmodule_Graph_Random_Bipartite(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; igraph_t g; long int n1, n2, m = -1; double p = -1.0; igraph_erdos_renyi_t t; igraph_neimode_t neimode = IGRAPH_ALL; PyObject *directed_o = Py_False, *neimode_o = NULL; igraph_vector_bool_t vertex_types; PyObject *vertex_types_o; static char *kwlist[] = { "n1", "n2", "p", "m", "directed", "neimode", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "ll|dlOO", kwlist, &n1, &n2, &p, &m, &directed_o, &neimode_o)) return NULL; if (m == -1 && p == -1.0) { /* no density parameters were given, throw exception */ PyErr_SetString(PyExc_TypeError, "Either m or p must be given."); return NULL; } if (m != -1 && p != -1.0) { /* both density parameters were given, throw exception */ PyErr_SetString(PyExc_TypeError, "Only one must be given from m and p."); return NULL; } t = (m == -1) ? IGRAPH_ERDOS_RENYI_GNP : IGRAPH_ERDOS_RENYI_GNM; if (igraphmodule_PyObject_to_neimode_t(neimode_o, &neimode)) return NULL; if (igraph_vector_bool_init(&vertex_types, n1+n2)) { igraphmodule_handle_igraph_error(); return NULL; } if (igraph_bipartite_game(&g, &vertex_types, t, (igraph_integer_t) n1, (igraph_integer_t) n2, (igraph_real_t) p, (igraph_integer_t) m, PyObject_IsTrue(directed_o), neimode)) { igraph_vector_bool_destroy(&vertex_types); igraphmodule_handle_igraph_error(); return NULL; } CREATE_GRAPH_FROM_TYPE(self, g, type); vertex_types_o = igraphmodule_vector_bool_t_to_PyList(&vertex_types); igraph_vector_bool_destroy(&vertex_types); if (vertex_types_o == 0) return NULL; return Py_BuildValue("NN", (PyObject *) self, vertex_types_o); } /** \ingroup python_interface_graph * \brief Generates a graph based on sort of a "windowed" Barabasi-Albert model * \return a reference to the newly generated Python igraph object * \sa igraph_recent_degree_game */ PyObject *igraphmodule_Graph_Recent_Degree(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; igraph_t g; long n, m = 0, window = 0; float power = 0.0f, zero_appeal = 0.0f; igraph_vector_t outseq; PyObject *m_obj, *outpref = Py_False, *directed = Py_False; char *kwlist[] = { "n", "m", "window", "outpref", "directed", "power", "zero_appeal", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "lOl|OOff", kwlist, &n, &m_obj, &window, &outpref, &directed, &power, &zero_appeal)) return NULL; if (n < 0) { PyErr_SetString(PyExc_ValueError, "Number of vertices must be positive."); return NULL; } // let's check whether we have a constant out-degree or a list if (PyInt_Check(m_obj)) { m = PyInt_AsLong(m_obj); igraph_vector_init(&outseq, 0); } else if (PyList_Check(m_obj)) { if (igraphmodule_PyObject_to_vector_t(m_obj, &outseq, 1)) { // something bad happened during conversion return NULL; } } if (igraph_recent_degree_game(&g, (igraph_integer_t) n, (igraph_real_t) power, (igraph_integer_t) window, (igraph_integer_t) m, &outseq, PyObject_IsTrue(outpref), (igraph_real_t) zero_appeal, PyObject_IsTrue(directed))) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&outseq); return NULL; } igraph_vector_destroy(&outseq); CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Generates a ring-shaped graph * \return a reference to the newly generated Python igraph object * \sa igraph_ring */ PyObject *igraphmodule_Graph_Ring(PyTypeObject * type, PyObject * args, PyObject * kwds) { long n; PyObject *directed = Py_False, *mutual = Py_False, *circular = Py_True; igraphmodule_GraphObject *self; igraph_t g; static char *kwlist[] = { "n", "directed", "mutual", "circular", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "l|O!O!O!", kwlist, &n, &PyBool_Type, &directed, &PyBool_Type, &mutual, &PyBool_Type, &circular)) return NULL; if (n < 0) { PyErr_SetString(PyExc_ValueError, "Number of vertices must be positive."); return NULL; } if (igraph_ring(&g, (igraph_integer_t) n, (directed == Py_True), (mutual == Py_True), (circular == Py_True))) { igraphmodule_handle_igraph_error(); return NULL; } CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Generates a graph based on a stochastic blockmodel * \return a reference to the newly generated Python igraph object * \sa igraph_sbm_game */ PyObject *igraphmodule_Graph_SBM(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; igraph_t g; long int n; PyObject *block_sizes_o, *pref_matrix_o; PyObject *directed_o = Py_False; PyObject *loops_o = Py_False; igraph_matrix_t pref_matrix; igraph_vector_int_t block_sizes; static char *kwlist[] = { "n", "pref_matrix", "block_sizes", "directed", "loops", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "lO!O!|OO", kwlist, &n, &PyList_Type, &pref_matrix_o, &PyList_Type, &block_sizes_o, &directed_o, &loops_o)) return NULL; if (igraphmodule_PyList_to_matrix_t(pref_matrix_o, &pref_matrix)) return NULL; if (igraphmodule_PyObject_to_vector_int_t(block_sizes_o, &block_sizes)) { igraph_matrix_destroy(&pref_matrix); return NULL; } if (igraph_sbm_game(&g, (igraph_integer_t) n, &pref_matrix, &block_sizes, PyObject_IsTrue(directed_o), PyObject_IsTrue(loops_o))) { igraphmodule_handle_igraph_error(); igraph_matrix_destroy(&pref_matrix); igraph_vector_int_destroy(&block_sizes); return NULL; } igraph_matrix_destroy(&pref_matrix); igraph_vector_int_destroy(&block_sizes); CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Generates a star graph * \return a reference to the newly generated Python igraph object * \sa igraph_star */ PyObject *igraphmodule_Graph_Star(PyTypeObject * type, PyObject * args, PyObject * kwds) { long n, center = 0; igraph_star_mode_t mode = IGRAPH_STAR_UNDIRECTED; PyObject* mode_o = Py_None; igraphmodule_GraphObject *self; igraph_t g; static char *kwlist[] = { "n", "mode", "center", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "l|Ol", kwlist, &n, &mode_o, ¢er)) return NULL; if (n < 0) { PyErr_SetString(PyExc_ValueError, "Number of vertices must be positive."); return NULL; } if (center >= n || center < 0) { PyErr_SetString(PyExc_ValueError, "Central vertex ID should be between 0 and n-1"); return NULL; } if (igraphmodule_PyObject_to_star_mode_t(mode_o, &mode)) { PyErr_SetString(PyExc_ValueError, "Mode should be either \"in\", \"out\", \"mutual\" or \"undirected\""); return NULL; } if (igraph_star(&g, (igraph_integer_t) n, mode, (igraph_integer_t) center)) { igraphmodule_handle_igraph_error(); return NULL; } CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Generates a non-growing random graph with edge probabilities * proportional to node fitnesses. * \return a reference to the newly generated Python igraph object * \sa igraph_static_fitness_game */ PyObject *igraphmodule_Graph_Static_Fitness(PyTypeObject *type, PyObject* args, PyObject* kwds) { igraphmodule_GraphObject *self; igraph_t g; long int m; PyObject *fitness_out_o = Py_None, *fitness_in_o = Py_None; PyObject *fitness_o = Py_None; PyObject *multiple = Py_False, *loops = Py_False; igraph_vector_t fitness_out, fitness_in; static char *kwlist[] = { "m", "fitness_out", "fitness_in", "loops", "multiple", "fitness", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "l|OOOOO", kwlist, &m, &fitness_out_o, &fitness_in_o, &loops, &multiple, &fitness_o)) return NULL; /* This trickery allows us to use "fitness" or "fitness_out" as * keyword argument, with "fitness_out" taking precedence over * "fitness" */ if (fitness_out_o == Py_None) fitness_out_o = fitness_o; if (fitness_out_o == Py_None) { PyErr_SetString(PyExc_TypeError, "Required argument 'fitness_out' (pos 2) not found"); return NULL; } if (igraphmodule_PyObject_float_to_vector_t(fitness_out_o, &fitness_out)) return NULL; if (fitness_in_o != Py_None) { if (igraphmodule_PyObject_float_to_vector_t(fitness_in_o, &fitness_in)) { igraph_vector_destroy(&fitness_out); return NULL; } } if (igraph_static_fitness_game(&g, (igraph_integer_t) m, &fitness_out, fitness_in_o == Py_None ? 0 : &fitness_in, PyObject_IsTrue(loops), PyObject_IsTrue(multiple))) { igraph_vector_destroy(&fitness_out); if (fitness_in_o != Py_None) igraph_vector_destroy(&fitness_in); igraphmodule_handle_igraph_error(); return NULL; } igraph_vector_destroy(&fitness_out); if (fitness_in_o != Py_None) igraph_vector_destroy(&fitness_in); CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Generates a non-growing random graph with prescribed power-law * degree distributions. * \return a reference to the newly generated Python igraph object * \sa igraph_static_power_law_game */ PyObject *igraphmodule_Graph_Static_Power_Law(PyTypeObject *type, PyObject* args, PyObject* kwds) { igraphmodule_GraphObject *self; igraph_t g; long int n, m; float exponent_out = -1.0f, exponent_in = -1.0f, exponent = -1.0f; PyObject *multiple = Py_False, *loops = Py_False; PyObject *finite_size_correction = Py_True; static char *kwlist[] = { "n", "m", "exponent_out", "exponent_in", "loops", "multiple", "finite_size_correction", "exponent", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "ll|ffOOOf", kwlist, &n, &m, &exponent_out, &exponent_in, &loops, &multiple, &finite_size_correction, &exponent)) return NULL; /* This trickery allows us to use "exponent" or "exponent_out" as * keyword argument, with "exponent_out" taking precedence over * "exponent" */ if (exponent_out == -1.0) exponent_out = exponent; if (exponent_out == -1.0) { PyErr_SetString(PyExc_TypeError, "Required argument 'exponent_out' (pos 3) not found"); return NULL; } if (igraph_static_power_law_game(&g, (igraph_integer_t) n, (igraph_integer_t) m, exponent_out, exponent_in, PyObject_IsTrue(loops), PyObject_IsTrue(multiple), PyObject_IsTrue(finite_size_correction))) { igraphmodule_handle_igraph_error(); return NULL; } CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Generates a tree graph where almost all vertices have an equal number of children * \return a reference to the newly generated Python igraph object * \sa igraph_tree */ PyObject *igraphmodule_Graph_Tree(PyTypeObject * type, PyObject * args, PyObject * kwds) { long int n, children; PyObject *tree_mode_o = Py_None, *tree_type_o = Py_None; igraph_tree_mode_t mode = IGRAPH_TREE_UNDIRECTED; igraphmodule_GraphObject *self; igraph_t g; static char *kwlist[] = { "n", "children", "mode", "type", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "ll|OO", kwlist, &n, &children, &tree_mode_o, &tree_type_o)) return NULL; if (n < 0) { PyErr_SetString(PyExc_ValueError, "Number of vertices must be positive."); return NULL; } if (tree_mode_o == Py_None && tree_type_o != Py_None) { tree_mode_o = tree_type_o; PY_IGRAPH_DEPRECATED("type=... keyword argument is deprecated since igraph 0.6, use mode=... instead"); } if (igraphmodule_PyObject_to_tree_mode_t(tree_mode_o, &mode)) { return NULL; } if (igraph_tree(&g, (igraph_integer_t) n, (igraph_integer_t) children, mode)) { igraphmodule_handle_igraph_error(); return NULL; } CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Generates a graph based on the Watts-Strogatz model * \return a reference to the newly generated Python igraph object * \sa igraph_watts_strogatz_game */ PyObject *igraphmodule_Graph_Watts_Strogatz(PyTypeObject * type, PyObject * args, PyObject * kwds) { long int nei = 1, dim, size; double p; PyObject* loops = Py_False; PyObject* multiple = Py_False; igraphmodule_GraphObject *self; igraph_t g; static char *kwlist[] = { "dim", "size", "nei", "p", "loops", "multiple", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "llld|OO", kwlist, &dim, &size, &nei, &p, &loops, &multiple)) return NULL; if (igraph_watts_strogatz_game(&g, (igraph_integer_t) dim, (igraph_integer_t) size, (igraph_integer_t) nei, p, PyObject_IsTrue(loops), PyObject_IsTrue(multiple))) { igraphmodule_handle_igraph_error(); return NULL; } CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Generates a graph from its weighted adjacency matrix * \return a reference to the newly generated Python igraph object * \sa igraph_weighted_adjacency */ PyObject *igraphmodule_Graph_Weighted_Adjacency(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; igraph_t g; igraph_matrix_t m; PyObject *matrix, *mode_o = Py_None, *attr_o = Py_None, *s = 0; PyObject *loops = Py_True; char* attr = 0; igraph_adjacency_t mode = IGRAPH_ADJ_DIRECTED; static char *kwlist[] = { "matrix", "mode", "attr", "loops", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O!|OOO", kwlist, &PyList_Type, &matrix, &mode_o, &attr_o, &loops)) return NULL; if (igraphmodule_PyObject_to_adjacency_t(mode_o, &mode)) return NULL; if (attr_o != Py_None) { s = PyObject_Str(attr_o); if (s) { attr = PyString_CopyAsString(s); if (attr == 0) return NULL; } else return NULL; } if (igraphmodule_PyList_to_matrix_t(matrix, &m)) { if (attr != 0) free(attr); PyErr_SetString(PyExc_TypeError, "Error while converting adjacency matrix"); return NULL; } if (igraph_weighted_adjacency(&g, &m, mode, attr ? attr : "weight", PyObject_IsTrue(loops))) { igraphmodule_handle_igraph_error(); if (attr != 0) free(attr); igraph_matrix_destroy(&m); return NULL; } if (attr != 0) free(attr); igraph_matrix_destroy(&m); CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /********************************************************************** * Advanced structural properties of graphs * **********************************************************************/ /** \ingroup python_interface_graph * \brief Calculates the articulation points of a graph. * \return the list of articulation points in a PyObject * \sa igraph_articulation_points */ PyObject *igraphmodule_Graph_articulation_points(igraphmodule_GraphObject *self) { igraph_vector_t res; PyObject *o; if (igraph_vector_init(&res, 0)) { igraphmodule_handle_igraph_error(); return NULL; } if (igraph_articulation_points(&self->g, &res)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&res); return NULL; } igraph_vector_sort(&res); o = igraphmodule_vector_t_to_PyList(&res, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&res); return o; } /** \ingroup python_interface_graph * \brief Calculates the nominal assortativity coefficient * \sa igraph_assortativity_nominal */ PyObject *igraphmodule_Graph_assortativity_nominal(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = { "types", "directed", NULL }; PyObject *types_o = Py_None, *directed = Py_True; igraph_real_t res; int ret; igraph_vector_t *types = 0; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|O", kwlist, &types_o, &directed)) return NULL; if (igraphmodule_attrib_to_vector_t(types_o, self, &types, ATTRIBUTE_TYPE_VERTEX)) return NULL; ret = igraph_assortativity_nominal(&self->g, types, &res, PyObject_IsTrue(directed)); if (types) { igraph_vector_destroy(types); free(types); } if (ret) { igraphmodule_handle_igraph_error(); return NULL; } return Py_BuildValue("d", (double)(res)); } /** \ingroup python_interface_graph * \brief Calculates the assortativity coefficient * \sa igraph_assortativity */ PyObject *igraphmodule_Graph_assortativity(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = { "types1", "types2", "directed", NULL }; PyObject *types1_o = Py_None, *types2_o = Py_None, *directed = Py_True; igraph_real_t res; int ret; igraph_vector_t *types1 = 0, *types2 = 0; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|OO", kwlist, &types1_o, &types2_o, &directed)) return NULL; if (igraphmodule_attrib_to_vector_t(types1_o, self, &types1, ATTRIBUTE_TYPE_VERTEX)) return NULL; if (igraphmodule_attrib_to_vector_t(types2_o, self, &types2, ATTRIBUTE_TYPE_VERTEX)) { if (types1) { igraph_vector_destroy(types1); free(types1); } return NULL; } ret = igraph_assortativity(&self->g, types1, types2, &res, PyObject_IsTrue(directed)); if (types1) { igraph_vector_destroy(types1); free(types1); } if (types2) { igraph_vector_destroy(types2); free(types2); } if (ret) { igraphmodule_handle_igraph_error(); return NULL; } return Py_BuildValue("d", (double)(res)); } /** \ingroup python_interface_graph * \brief Calculates the assortativity coefficient for degrees * \sa igraph_assortativity_degree */ PyObject *igraphmodule_Graph_assortativity_degree(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = { "directed", NULL }; PyObject *directed = Py_True; igraph_real_t res; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O", kwlist, &directed)) return NULL; if (igraph_assortativity_degree(&self->g, &res, PyObject_IsTrue(directed))) { igraphmodule_handle_igraph_error(); return NULL; } return Py_BuildValue("d", (double)(res)); } /** \ingroup python_interface_graph * \brief Calculates Kleinberg's authority scores of the vertices in the graph * \sa igraph_authority_score */ PyObject *igraphmodule_Graph_authority_score( igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = { "weights", "scale", "arpack_options", "return_eigenvalue", NULL }; PyObject *scale_o = Py_True, *weights_o = Py_None; PyObject *arpack_options_o = igraphmodule_arpack_options_default; igraphmodule_ARPACKOptionsObject *arpack_options; PyObject *return_eigenvalue = Py_False; PyObject *res_o; igraph_real_t value; igraph_vector_t res, *weights = 0; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOO!O", kwlist, &weights_o, &scale_o, &igraphmodule_ARPACKOptionsType, &arpack_options_o, &return_eigenvalue)) return NULL; if (igraph_vector_init(&res, 0)) return igraphmodule_handle_igraph_error(); if (igraphmodule_attrib_to_vector_t(weights_o, self, &weights, ATTRIBUTE_TYPE_EDGE)) return NULL; arpack_options = (igraphmodule_ARPACKOptionsObject*)arpack_options_o; if (igraph_authority_score(&self->g, &res, &value, PyObject_IsTrue(scale_o), weights, igraphmodule_ARPACKOptions_get(arpack_options))) { igraphmodule_handle_igraph_error(); if (weights) { igraph_vector_destroy(weights); free(weights); } igraph_vector_destroy(&res); return NULL; } if (weights) { igraph_vector_destroy(weights); free(weights); } res_o = igraphmodule_vector_t_to_PyList(&res, IGRAPHMODULE_TYPE_FLOAT); igraph_vector_destroy(&res); if (res_o == NULL) return igraphmodule_handle_igraph_error(); if (PyObject_IsTrue(return_eigenvalue)) { PyObject *ev_o = PyFloat_FromDouble((double)value); if (ev_o == NULL) { Py_DECREF(res_o); return igraphmodule_handle_igraph_error(); } return Py_BuildValue("NN", res_o, ev_o); } return res_o; } /** \ingroup python_interface_graph * \brief Calculates the average path length in a graph. * \return the average path length as a PyObject * \sa igraph_average_path_length */ PyObject *igraphmodule_Graph_average_path_length(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { char *kwlist[] = { "directed", "unconn", NULL }; PyObject *directed = Py_True, *unconn = Py_True; igraph_real_t res; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O!O!", kwlist, &PyBool_Type, &directed, &PyBool_Type, &unconn)) return NULL; if (igraph_average_path_length(&self->g, &res, (directed == Py_True), (unconn == Py_True))) { igraphmodule_handle_igraph_error(); return NULL; } return PyFloat_FromDouble(res); } /** \ingroup python_interface_graph * \brief Calculates the betweennesses of some vertices in a graph. * \return the betweennesses as a list (or a single float) * \sa igraph_betweenness */ PyObject *igraphmodule_Graph_betweenness(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "vertices", "directed", "cutoff", "weights", "nobigint", NULL }; PyObject *directed = Py_True; PyObject *vobj = Py_None, *list; PyObject *cutoff = Py_None; PyObject *weights_o = Py_None; PyObject *nobigint = Py_True; igraph_vector_t res, *weights = 0; igraph_bool_t return_single = 0; igraph_vs_t vs; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOOOO", kwlist, &vobj, &directed, &cutoff, &weights_o, &nobigint)) { return NULL; } if (igraphmodule_attrib_to_vector_t(weights_o, self, &weights, ATTRIBUTE_TYPE_EDGE)) return NULL; if (igraphmodule_PyObject_to_vs_t(vobj, &vs, &self->g, &return_single, 0)) { if (weights) { igraph_vector_destroy(weights); free(weights); } igraphmodule_handle_igraph_error(); return NULL; } if (igraph_vector_init(&res, 0)) { igraph_vs_destroy(&vs); if (weights) { igraph_vector_destroy(weights); free(weights); } return igraphmodule_handle_igraph_error(); } if (cutoff == Py_None) { if (igraph_betweenness(&self->g, &res, vs, PyObject_IsTrue(directed), weights, PyObject_IsTrue(nobigint))) { igraph_vs_destroy(&vs); igraph_vector_destroy(&res); if (weights) { igraph_vector_destroy(weights); free(weights); } igraphmodule_handle_igraph_error(); return NULL; } } else if (PyNumber_Check(cutoff)) { PyObject *cutoff_num = PyNumber_Float(cutoff); if (cutoff_num == NULL) { igraph_vs_destroy(&vs); igraph_vector_destroy(&res); if (weights) { igraph_vector_destroy(weights); free(weights); } return NULL; } if (igraph_betweenness_estimate(&self->g, &res, vs, PyObject_IsTrue(directed), (igraph_real_t)PyFloat_AsDouble(cutoff_num), weights, PyObject_IsTrue(nobigint))) { igraph_vs_destroy(&vs); igraph_vector_destroy(&res); if (weights) { igraph_vector_destroy(weights); free(weights); } Py_DECREF(cutoff_num); igraphmodule_handle_igraph_error(); return NULL; } Py_DECREF(cutoff_num); } else { PyErr_SetString(PyExc_TypeError, "cutoff value must be None or integer"); igraph_vs_destroy(&vs); igraph_vector_destroy(&res); if (weights) { igraph_vector_destroy(weights); free(weights); } return NULL; } if (!return_single) list = igraphmodule_vector_t_to_PyList(&res, IGRAPHMODULE_TYPE_FLOAT); else list = PyFloat_FromDouble(VECTOR(res)[0]); igraph_vector_destroy(&res); igraph_vs_destroy(&vs); if (weights) { igraph_vector_destroy(weights); free(weights); } return list; } /** \ingroup python_interface_graph * \brief Calculates the bibliographic coupling of some vertices in a graph. * \return the bibliographic coupling values in a matrix * \sa igraph_bibcoupling */ PyObject *igraphmodule_Graph_bibcoupling(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { char *kwlist[] = { "vertices", NULL }; PyObject *vobj = NULL, *list; igraph_matrix_t res; igraph_vs_t vs; igraph_bool_t return_single = 0; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O", kwlist, &vobj)) return NULL; if (igraphmodule_PyObject_to_vs_t(vobj, &vs, &self->g, &return_single, 0)) { igraphmodule_handle_igraph_error(); return NULL; } if (igraph_matrix_init(&res, 1, igraph_vcount(&self->g))) { igraph_vs_destroy(&vs); igraphmodule_handle_igraph_error(); return NULL; } if (igraph_bibcoupling(&self->g, &res, vs)) { igraph_vs_destroy(&vs); igraphmodule_handle_igraph_error(); return NULL; } /* TODO: Return a single list instead of a matrix if only one vertex was given */ list = igraphmodule_matrix_t_to_PyList(&res, IGRAPHMODULE_TYPE_INT); igraph_matrix_destroy(&res); igraph_vs_destroy(&vs); return list; } /** \ingroup python_interface_graph * \brief Calculates the biconnected components of a graph. * \return the list of spanning trees of biconnected components in a PyObject * \sa igraph_biconnected_components */ PyObject *igraphmodule_Graph_biconnected_components(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { igraph_vector_ptr_t components; igraph_vector_t points; igraph_bool_t return_articulation_points; igraph_integer_t no; PyObject *result, *aps=Py_False; static char* kwlist[] = {"return_articulation_points", NULL}; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O", kwlist, &aps)) return NULL; return_articulation_points = PyObject_IsTrue(aps); if (igraph_vector_ptr_init(&components, 0)) { igraphmodule_handle_igraph_error(); return NULL; } if (return_articulation_points) { if (igraph_vector_init(&points, 0)) { igraphmodule_handle_igraph_error(); igraph_vector_ptr_destroy(&components); return NULL; } } if (igraph_biconnected_components(&self->g, &no, &components, 0, 0, return_articulation_points ? &points : 0)) { igraphmodule_handle_igraph_error(); igraph_vector_ptr_destroy(&components); if (return_articulation_points) igraph_vector_destroy(&points); return NULL; } result = igraphmodule_vector_ptr_t_to_PyList(&components, IGRAPHMODULE_TYPE_INT); IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(&components, igraph_vector_destroy); igraph_vector_ptr_destroy_all(&components); if (return_articulation_points) { PyObject *result2; igraph_vector_sort(&points); result2 = igraphmodule_vector_t_to_PyList(&points, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&points); return Py_BuildValue("NN", result, result2); /* references stolen */ } return result; } /** \ingroup python_interface_graph * \brief Returns the one-mode projections of a bipartite graph * \return the two projections as new igraph objects * \sa igraph_bipartite_projection */ PyObject *igraphmodule_Graph_bipartite_projection(igraphmodule_GraphObject * self, PyObject* args, PyObject* kwds) { PyObject *types_o = Py_None, *multiplicity_o = Py_True, *mul1 = 0, *mul2 = 0; igraphmodule_GraphObject *result1 = 0, *result2 = 0; igraph_vector_bool_t* types = 0; igraph_vector_t multiplicities[2]; igraph_t g1, g2; igraph_t *p_g1 = &g1, *p_g2 = &g2; long int probe1 = -1; long int which = -1; static char* kwlist[] = {"types", "multiplicity", "probe1", "which", NULL}; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|Oll", kwlist, &types_o, &multiplicity_o, &probe1, &which)) return NULL; if (igraphmodule_attrib_to_vector_bool_t(types_o, self, &types, ATTRIBUTE_TYPE_VERTEX)) return NULL; if (which == 0) { p_g2 = 0; } else if (which == 1) { p_g1 = 0; } if (PyObject_IsTrue(multiplicity_o)) { if (igraph_vector_init(&multiplicities[0], 0)) { if (types) { igraph_vector_bool_destroy(types); free(types); } igraphmodule_handle_igraph_error(); return NULL; } if (igraph_vector_init(&multiplicities[1], 0)) { igraph_vector_destroy(&multiplicities[0]); if (types) { igraph_vector_bool_destroy(types); free(types); } igraphmodule_handle_igraph_error(); return NULL; } if (igraph_bipartite_projection(&self->g, types, p_g1, p_g2, p_g1 ? &multiplicities[0] : 0, p_g2 ? &multiplicities[1] : 0, (igraph_integer_t) probe1)) { igraph_vector_destroy(&multiplicities[0]); igraph_vector_destroy(&multiplicities[1]); if (types) { igraph_vector_bool_destroy(types); free(types); } igraphmodule_handle_igraph_error(); return NULL; } } else { if (igraph_bipartite_projection(&self->g, types, p_g1, p_g2, 0, 0, (igraph_integer_t) probe1)) { if (types) { igraph_vector_bool_destroy(types); free(types); } igraphmodule_handle_igraph_error(); return NULL; } } if (types) { igraph_vector_bool_destroy(types); free(types); } if (p_g1) { CREATE_GRAPH(result1, g1); } if (p_g2) { CREATE_GRAPH(result2, g2); } if (PyObject_IsTrue(multiplicity_o)) { if (p_g1) { mul1 = igraphmodule_vector_t_to_PyList(&multiplicities[0], IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&multiplicities[0]); if (mul1 == NULL) { igraph_vector_destroy(&multiplicities[1]); return NULL; } } else { igraph_vector_destroy(&multiplicities[0]); } if (p_g2) { mul2 = igraphmodule_vector_t_to_PyList(&multiplicities[1], IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&multiplicities[1]); if (mul2 == NULL) return NULL; } else { igraph_vector_destroy(&multiplicities[1]); } if (p_g1 && p_g2) { return Py_BuildValue("NNNN", result1, result2, mul1, mul2); } else if (p_g1) { return Py_BuildValue("NN", result1, mul1); } else { return Py_BuildValue("NN", result2, mul2); } } else { if (p_g1 && p_g2) { return Py_BuildValue("NN", result1, result2); } else if (p_g1) { return (PyObject*)result1; } else { return (PyObject*)result2; } } } /** \ingroup python_interface_graph * \brief Returns the sizes of the two one-mode projections of a bipartite graph * \return the two one-mode projections as new igraph objects * \sa igraph_bipartite_projection_size */ PyObject *igraphmodule_Graph_bipartite_projection_size(igraphmodule_GraphObject * self, PyObject* args, PyObject* kwds) { PyObject *types_o = Py_None; igraph_vector_bool_t* types = 0; igraph_integer_t vcount1, vcount2, ecount1, ecount2; static char* kwlist[] = {"types", NULL}; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O", kwlist, &types_o)) return NULL; if (igraphmodule_attrib_to_vector_bool_t(types_o, self, &types, ATTRIBUTE_TYPE_VERTEX)) return NULL; if (igraph_bipartite_projection_size(&self->g, types, &vcount1, &ecount1, &vcount2, &ecount2)) { if (types) { igraph_vector_bool_destroy(types); free(types); } igraphmodule_handle_igraph_error(); return NULL; } if (types) { igraph_vector_bool_destroy(types); free(types); } return Py_BuildValue("llll", (long)vcount1, (long)ecount1, (long)vcount2, (long)ecount2); } /** \ingroup python_interface_graph * \brief Calculates the closeness centrality of some vertices in a graph. * \return the closeness centralities as a list (or a single float) * \sa igraph_betweenness */ PyObject *igraphmodule_Graph_closeness(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "vertices", "mode", "cutoff", "weights", "normalized", NULL }; PyObject *vobj = Py_None, *list = NULL, *cutoff = Py_None, *mode_o = Py_None, *weights_o = Py_None, *normalized_o = Py_True; igraph_vector_t res, *weights = 0; igraph_neimode_t mode = IGRAPH_ALL; int return_single = 0; igraph_vs_t vs; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOOOO", kwlist, &vobj, &mode_o, &cutoff, &weights_o, &normalized_o)) return NULL; if (igraphmodule_PyObject_to_neimode_t(mode_o, &mode)) return NULL; if (igraphmodule_PyObject_to_vs_t(vobj, &vs, &self->g, &return_single, 0)) { igraphmodule_handle_igraph_error(); return NULL; } if (igraph_vector_init(&res, 0)) { igraph_vs_destroy(&vs); return igraphmodule_handle_igraph_error(); } if (igraphmodule_attrib_to_vector_t(weights_o, self, &weights, ATTRIBUTE_TYPE_EDGE)) { igraph_vs_destroy(&vs); igraph_vector_destroy(&res); return NULL; } if (cutoff == Py_None) { if (igraph_closeness(&self->g, &res, vs, mode, weights, PyObject_IsTrue(normalized_o))) { igraph_vs_destroy(&vs); igraph_vector_destroy(&res); if (weights) { igraph_vector_destroy(weights); free(weights); } igraphmodule_handle_igraph_error(); return NULL; } } else if (PyNumber_Check(cutoff)) { PyObject *cutoff_num = PyNumber_Float(cutoff); if (cutoff_num == NULL) { igraph_vs_destroy(&vs); igraph_vector_destroy(&res); return NULL; } if (igraph_closeness_estimate(&self->g, &res, vs, mode, (igraph_real_t)PyFloat_AsDouble(cutoff_num), weights, PyObject_IsTrue(normalized_o))) { igraph_vs_destroy(&vs); igraph_vector_destroy(&res); if (weights) { igraph_vector_destroy(weights); free(weights); } igraphmodule_handle_igraph_error(); Py_DECREF(cutoff_num); return NULL; } Py_DECREF(cutoff_num); } if (weights) { igraph_vector_destroy(weights); free(weights); } if (!return_single) list = igraphmodule_vector_t_to_PyList(&res, IGRAPHMODULE_TYPE_FLOAT); else list = PyFloat_FromDouble(VECTOR(res)[0]); igraph_vector_destroy(&res); igraph_vs_destroy(&vs); return list; } /** \ingroup python_interface_graph * \brief Calculates the (weakly or strongly) connected components in a graph. * \return a list containing the cluster ID for every vertex in the graph * \sa igraph_clusters */ PyObject *igraphmodule_Graph_clusters(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "mode", NULL }; igraph_connectedness_t mode = IGRAPH_STRONG; igraph_vector_t res1, res2; igraph_integer_t no; PyObject *list, *mode_o = Py_None; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O", kwlist, &mode_o)) return NULL; if (igraphmodule_PyObject_to_connectedness_t(mode_o, &mode)) return NULL; igraph_vector_init(&res1, igraph_vcount(&self->g)); igraph_vector_init(&res2, 10); if (igraph_clusters(&self->g, &res1, &res2, &no, mode)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&res1); igraph_vector_destroy(&res2); return NULL; } list = igraphmodule_vector_t_to_PyList(&res1, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&res1); igraph_vector_destroy(&res2); return list; } /** \ingroup python_interface_graph * \brief Calculates Burt's constraint scores for a given graph * \sa igraph_constraint */ PyObject *igraphmodule_Graph_constraint(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "vertices", "weights", NULL }; PyObject *vids_obj = Py_None, *weight_obj = Py_None, *list; igraph_vector_t result, weights; igraph_vs_t vids; igraph_bool_t return_single = 0; if (!PyArg_ParseTupleAndKeywords (args, kwds, "|OO", kwlist, &vids_obj, &weight_obj)) return NULL; if (igraph_vector_init(&result, 0)) { igraphmodule_handle_igraph_error(); return NULL; } if (igraphmodule_PyObject_to_attribute_values(weight_obj, &weights, self, ATTRHASH_IDX_EDGE, 1.0)) { igraph_vector_destroy(&result); return NULL; } if (igraphmodule_PyObject_to_vs_t(vids_obj, &vids, &self->g, &return_single, 0)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&result); igraph_vector_destroy(&weights); return NULL; } if (igraph_constraint(&self->g, &result, vids, &weights)) { igraphmodule_handle_igraph_error(); igraph_vs_destroy(&vids); igraph_vector_destroy(&result); igraph_vector_destroy(&weights); return NULL; } if (!return_single) list = igraphmodule_vector_t_to_PyList(&result, IGRAPHMODULE_TYPE_FLOAT); else list = PyFloat_FromDouble((double)VECTOR(result)[0]); igraph_vs_destroy(&vids); igraph_vector_destroy(&result); igraph_vector_destroy(&weights); return list; } /** \ingroup python_interface_graph * \brief Calculates the cocitation scores of some vertices in a graph. * \return the cocitation scores in a matrix * \sa igraph_cocitation */ PyObject *igraphmodule_Graph_cocitation(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { char *kwlist[] = { "vertices", NULL }; PyObject *vobj = NULL, *list = NULL; igraph_matrix_t res; int return_single = 0; igraph_vs_t vs; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O", kwlist, &vobj)) return NULL; if (igraphmodule_PyObject_to_vs_t(vobj, &vs, &self->g, &return_single, 0)) { igraphmodule_handle_igraph_error(); return NULL; } if (igraph_matrix_init(&res, 1, igraph_vcount(&self->g))) { igraph_vs_destroy(&vs); return igraphmodule_handle_igraph_error(); } if (igraph_cocitation(&self->g, &res, vs)) { igraph_matrix_destroy(&res); igraph_vs_destroy(&vs); igraphmodule_handle_igraph_error(); return NULL; } /* TODO: Return a single list instead of a matrix if only one vertex was given */ list = igraphmodule_matrix_t_to_PyList(&res, IGRAPHMODULE_TYPE_INT); igraph_matrix_destroy(&res); igraph_vs_destroy(&vs); return list; } /** \ingroup python_interface_graph * \brief Replaces multiple vertices with a single one. * \return None. * \sa igraph_contract_vertices */ PyObject *igraphmodule_Graph_contract_vertices(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char* kwlist[] = {"mapping", "combine_attrs", NULL }; PyObject *mapping_o, *combination_o = Py_None; igraph_vector_t mapping; igraph_attribute_combination_t combination; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|O", kwlist, &mapping_o, &combination_o)) return NULL; if (igraphmodule_PyObject_to_attribute_combination_t( combination_o, &combination)) return NULL; if (igraphmodule_PyObject_to_vector_t(mapping_o, &mapping, 1)) { igraph_attribute_combination_destroy(&combination); return NULL; } if (igraph_contract_vertices(&self->g, &mapping, &combination)) { igraph_attribute_combination_destroy(&combination); igraph_vector_destroy(&mapping); return NULL; } igraph_attribute_combination_destroy(&combination); igraph_vector_destroy(&mapping); Py_RETURN_NONE; } /** \ingroup python_interface_graph * \brief Decomposes a graph into components. * \return a list of graph objects, each containing a copy of a component in the original graph. * \sa igraph_components */ PyObject *igraphmodule_Graph_decompose(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { char *kwlist[] = { "mode", "maxcompno", "minelements", NULL }; igraph_connectedness_t mode = IGRAPH_STRONG; PyObject *list, *mode_o = Py_None; igraphmodule_GraphObject *o; long maxcompno = -1, minelements = -1, n, i; igraph_vector_ptr_t components; igraph_t *g; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|Oll", kwlist, &mode_o, &maxcompno, &minelements)) return NULL; if (igraphmodule_PyObject_to_connectedness_t(mode_o, &mode)) return NULL; igraph_vector_ptr_init(&components, 3); if (igraph_decompose(&self->g, &components, mode, maxcompno, minelements)) { igraph_vector_ptr_destroy(&components); igraphmodule_handle_igraph_error(); return NULL; } /* We have to create a Python igraph object for every graph returned */ n = igraph_vector_ptr_size(&components); list = PyList_New(n); for (i = 0; i < n; i++) { g = (igraph_t *) VECTOR(components)[i]; CREATE_GRAPH(o, *g); PyList_SET_ITEM(list, i, (PyObject *) o); /* reference has been transferred by PyList_SET_ITEM, no need to DECREF * * we mustn't call igraph_destroy here, because it would free the vertices * and the edges as well, but we need them in o->g. So just call free */ free(g); } igraph_vector_ptr_destroy(&components); return list; } /** \ingroup python_interface_graph * \brief Calculates the eccentricities of some vertices in a graph. * \return the eccentricities as a list (or a single float) * \sa igraph_eccentricity */ PyObject *igraphmodule_Graph_eccentricity(igraphmodule_GraphObject* self, PyObject* args, PyObject* kwds) { static char *kwlist[] = { "vertices", "mode", NULL }; PyObject *vobj = Py_None, *list = NULL, *mode_o = Py_None; igraph_vector_t res; igraph_neimode_t mode = IGRAPH_OUT; int return_single = 0; igraph_vs_t vs; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OO", kwlist, &vobj, &mode_o)) return NULL; if (igraphmodule_PyObject_to_neimode_t(mode_o, &mode)) return NULL; if (igraphmodule_PyObject_to_vs_t(vobj, &vs, &self->g, &return_single, 0)) { igraphmodule_handle_igraph_error(); return NULL; } if (igraph_vector_init(&res, 0)) { igraph_vs_destroy(&vs); return igraphmodule_handle_igraph_error(); } if (igraph_eccentricity(&self->g, &res, vs, mode)) { igraph_vs_destroy(&vs); igraph_vector_destroy(&res); igraphmodule_handle_igraph_error(); return NULL; } if (!return_single) list = igraphmodule_vector_t_to_PyList(&res, IGRAPHMODULE_TYPE_FLOAT); else list = PyFloat_FromDouble(VECTOR(res)[0]); igraph_vector_destroy(&res); igraph_vs_destroy(&vs); return list; } PyObject* igraphmodule_Graph_eigen_adjacency(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = { "algorithm", "which", "arpack_options", NULL }; PyObject *algorithm_o = Py_None, *which_o = Py_None; PyObject *arpack_options_o = igraphmodule_arpack_options_default; igraph_eigen_algorithm_t algorithm; igraph_eigen_which_t which; igraphmodule_ARPACKOptionsObject *arpack_options; igraph_vector_t values; igraph_matrix_t vectors; PyObject *values_o, *vectors_o; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOO!", kwlist, &algorithm_o, &which_o, &igraphmodule_ARPACKOptionsType, &arpack_options)) { return NULL; } if (igraphmodule_PyObject_to_eigen_algorithm_t(algorithm_o, &algorithm)) { return NULL; } if (igraphmodule_PyObject_to_eigen_which_t(which_o, &which)) { return NULL; } if (igraph_vector_init(&values, 0)) { return NULL; } if (igraph_matrix_init(&vectors, 0, 0)) { igraph_vector_destroy(&values); return igraphmodule_handle_igraph_error(); } arpack_options = (igraphmodule_ARPACKOptionsObject*)arpack_options_o; if (igraph_eigen_adjacency(&self->g, algorithm, &which, igraphmodule_ARPACKOptions_get(arpack_options), /*storage=*/ 0, &values, &vectors, /*cmplxvalues=*/ 0, /*cmplxvectors=*/ 0)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&values); igraph_matrix_destroy(&vectors); return NULL; } values_o = igraphmodule_vector_t_to_PyList(&values, IGRAPHMODULE_TYPE_FLOAT); igraph_vector_destroy(&values); vectors_o = igraphmodule_matrix_t_to_PyList(&vectors, IGRAPHMODULE_TYPE_FLOAT); igraph_matrix_destroy(&vectors); return Py_BuildValue("NN", values_o, vectors_o); } /** \ingroup python_interface_graph * \brief Calculates the edge betweennesses in the graph * \return a list containing the edge betweenness for every edge * \sa igraph_edge_betweenness */ PyObject *igraphmodule_Graph_edge_betweenness(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "directed", "cutoff", "weights", NULL }; igraph_vector_t res, *weights = 0; PyObject *list, *directed = Py_True, *cutoff = Py_None; PyObject *weights_o = Py_None; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOO", kwlist, &directed, &cutoff, &weights_o)) return NULL; if (igraphmodule_attrib_to_vector_t(weights_o, self, &weights, ATTRIBUTE_TYPE_EDGE)) return NULL; igraph_vector_init(&res, igraph_ecount(&self->g)); if (cutoff == Py_None) { if (igraph_edge_betweenness(&self->g, &res, PyObject_IsTrue(directed), weights)) { igraphmodule_handle_igraph_error(); if (weights) { igraph_vector_destroy(weights); free(weights); } igraph_vector_destroy(&res); return NULL; } } else if (PyNumber_Check(cutoff)) { PyObject *cutoff_num = PyNumber_Float(cutoff); if (!cutoff_num) { if (weights) { igraph_vector_destroy(weights); free(weights); } igraph_vector_destroy(&res); return NULL; } if (igraph_edge_betweenness_estimate(&self->g, &res, PyObject_IsTrue(directed), (igraph_real_t)PyFloat_AsDouble(cutoff_num), weights)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&res); if (weights) { igraph_vector_destroy(weights); free(weights); } Py_DECREF(cutoff_num); return NULL; } Py_DECREF(cutoff_num); } else { PyErr_SetString(PyExc_TypeError, "cutoff value must be None or integer"); igraph_vector_destroy(&res); return NULL; } if (weights) { igraph_vector_destroy(weights); free(weights); } list = igraphmodule_vector_t_to_PyList(&res, IGRAPHMODULE_TYPE_FLOAT); igraph_vector_destroy(&res); return list; } /** \ingroup python_interface_graph * \brief Calculates the edge connectivity of the graph * \return the edge connectivity * \sa igraph_edge_connectivity, igraph_st_edge_connectivity */ PyObject *igraphmodule_Graph_edge_connectivity(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = { "source", "target", "checks", NULL }; PyObject *checks = Py_True; long int source = -1, target = -1, result; igraph_integer_t res; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|llO", kwlist, &source, &target, &checks)) return NULL; if (source < 0 && target < 0) { if (igraph_edge_connectivity(&self->g, &res, PyObject_IsTrue(checks))) { igraphmodule_handle_igraph_error(); return NULL; } } else if (source >= 0 && target >= 0) { if (igraph_st_edge_connectivity(&self->g, &res, (igraph_integer_t) source, (igraph_integer_t) target)) { igraphmodule_handle_igraph_error(); return NULL; } } else { PyErr_SetString(PyExc_ValueError, "if source or target is given, the other one must also be specified"); return NULL; } result = res; return Py_BuildValue("l", result); } /** \ingroup python_interface_graph * \brief Calculates the eigenvector centralities of the vertices in the graph * \sa igraph_eigenvector_centrality */ PyObject *igraphmodule_Graph_eigenvector_centrality( igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = { "directed", "scale", "weights", "arpack_options", "return_eigenvalue", NULL }; PyObject *directed_o = Py_True; PyObject *scale_o = Py_True; PyObject *weights_o = Py_None; PyObject *arpack_options_o = igraphmodule_arpack_options_default; igraphmodule_ARPACKOptionsObject *arpack_options; PyObject *return_eigenvalue = Py_False; PyObject *res_o; igraph_real_t value; igraph_vector_t *weights=0, res; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOOO!O", kwlist, &directed_o, &scale_o, &weights_o, &igraphmodule_ARPACKOptionsType, &arpack_options, &return_eigenvalue)) return NULL; if (igraphmodule_attrib_to_vector_t(weights_o, self, &weights, ATTRIBUTE_TYPE_EDGE)) return NULL; if (igraph_vector_init(&res, 0)) { if (weights) { igraph_vector_destroy(weights); free(weights); } return igraphmodule_handle_igraph_error(); } arpack_options = (igraphmodule_ARPACKOptionsObject*)arpack_options_o; if (igraph_eigenvector_centrality(&self->g, &res, &value, PyObject_IsTrue(directed_o), PyObject_IsTrue(scale_o), weights, igraphmodule_ARPACKOptions_get(arpack_options))) { igraphmodule_handle_igraph_error(); if (weights) { igraph_vector_destroy(weights); free(weights); } igraph_vector_destroy(&res); return NULL; } if (weights) { igraph_vector_destroy(weights); free(weights); } res_o = igraphmodule_vector_t_to_PyList(&res, IGRAPHMODULE_TYPE_FLOAT); igraph_vector_destroy(&res); if (res_o == NULL) return igraphmodule_handle_igraph_error(); if (PyObject_IsTrue(return_eigenvalue)) { PyObject *ev_o = PyFloat_FromDouble((double)value); if (ev_o == NULL) { Py_DECREF(res_o); return igraphmodule_handle_igraph_error(); } return Py_BuildValue("NN", res_o, ev_o); } return res_o; } /** \ingroup python_interface_graph * \brief Calculates a feedback arc set for a graph * \return a list containing the indices in the chosen feedback arc set * \sa igraph_feedback_arc_set */ PyObject *igraphmodule_Graph_feedback_arc_set( igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = { "weights", "method", NULL }; igraph_vector_t* weights = 0; igraph_vector_t result; igraph_fas_algorithm_t algo = IGRAPH_FAS_APPROX_EADES; PyObject *weights_o = Py_None, *result_o = NULL, *algo_o = NULL; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OO", kwlist, &weights_o, &algo_o)) return NULL; if (igraphmodule_PyObject_to_fas_algorithm_t(algo_o, &algo)) return NULL; if (igraphmodule_attrib_to_vector_t(weights_o, self, &weights, ATTRIBUTE_TYPE_EDGE)) return NULL; if (igraph_vector_init(&result, 0)) { if (weights) { igraph_vector_destroy(weights); free(weights); } } if (igraph_feedback_arc_set(&self->g, &result, weights, algo)) { if (weights) { igraph_vector_destroy(weights); free(weights); } igraph_vector_destroy(&result); return NULL; } if (weights) { igraph_vector_destroy(weights); free(weights); } result_o = igraphmodule_vector_t_to_PyList(&result, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&result); return result_o; } /** \ingroup python_interface_graph * \brief Calculates the shortest paths from/to a given node in the graph * \return a list containing shortest paths from/to the given node * \sa igraph_get_shortest_paths */ PyObject *igraphmodule_Graph_get_shortest_paths(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "v", "to", "weights", "mode", "output", NULL }; igraph_vector_t *res, *weights=0; igraph_neimode_t mode = IGRAPH_OUT; long int i, j; igraph_integer_t from, no_of_target_nodes; igraph_vs_t to; PyObject *list, *item, *mode_o=Py_None, *weights_o=Py_None, *output_o=Py_None, *from_o = Py_None, *to_o=Py_None; igraph_vector_ptr_t *ptrvec=0; igraph_bool_t use_edges = 0; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|OOOO!", kwlist, &from_o, &to_o, &weights_o, &mode_o, &PyString_Type, &output_o)) return NULL; if (output_o == 0 || output_o == Py_None || PyString_IsEqualToASCIIString(output_o, "vpath")) { use_edges = 0; } else if (PyString_IsEqualToASCIIString(output_o, "epath")) { use_edges = 1; } else { PyErr_SetString(PyExc_ValueError, "output argument must be \"vpath\" or \"epath\""); return NULL; } if (igraphmodule_PyObject_to_vid(from_o, &from, &self->g)) return NULL; if (igraphmodule_PyObject_to_neimode_t(mode_o, &mode)) return NULL; if (igraphmodule_attrib_to_vector_t(weights_o, self, &weights, ATTRIBUTE_TYPE_EDGE)) return NULL; if (igraphmodule_PyObject_to_vs_t(to_o, &to, &self->g, 0, 0)) { if (weights) { igraph_vector_destroy(weights); free(weights); } return NULL; } if (igraph_vs_size(&self->g, &to, &no_of_target_nodes)) { if (weights) { igraph_vector_destroy(weights); free(weights); } igraph_vs_destroy(&to); igraphmodule_handle_igraph_error(); return NULL; } ptrvec = (igraph_vector_ptr_t *) calloc(1, sizeof(igraph_vector_ptr_t)); if (!ptrvec) { PyErr_SetString(PyExc_MemoryError, ""); if (weights) { igraph_vector_destroy(weights); free(weights); } igraph_vs_destroy(&to); return NULL; } if (igraph_vector_ptr_init(ptrvec, no_of_target_nodes)) { PyErr_SetString(PyExc_MemoryError, ""); free(ptrvec); if (weights) { igraph_vector_destroy(weights); free(weights); } igraph_vs_destroy(&to); return NULL; } res = (igraph_vector_t *) calloc(no_of_target_nodes, sizeof(igraph_vector_t)); if (!res) { PyErr_SetString(PyExc_MemoryError, ""); igraph_vector_ptr_destroy(ptrvec); free(ptrvec); if (weights) { igraph_vector_destroy(weights); free(weights); } igraph_vs_destroy(&to); return NULL; } for (i = 0; i < no_of_target_nodes; i++) { VECTOR(*ptrvec)[i] = &res[i]; igraph_vector_init(&res[i], 0); } if (igraph_get_shortest_paths_dijkstra(&self->g, use_edges ? 0 : ptrvec, use_edges ? ptrvec : 0, from, to, weights, mode, 0, 0)) { igraphmodule_handle_igraph_error(); for (j = 0; j < no_of_target_nodes; j++) igraph_vector_destroy(&res[j]); free(res); igraph_vector_ptr_destroy(ptrvec); free(ptrvec); if (weights) { igraph_vector_destroy(weights); free(weights); } igraph_vs_destroy(&to); return NULL; } igraph_vector_ptr_destroy(ptrvec); free(ptrvec); if (weights) { igraph_vector_destroy(weights); free(weights); } igraph_vs_destroy(&to); list = PyList_New(no_of_target_nodes); if (!list) { for (j = 0; j < no_of_target_nodes; j++) igraph_vector_destroy(&res[j]); free(res); return NULL; } for (i = 0; i < no_of_target_nodes; i++) { item = igraphmodule_vector_t_to_PyList(&res[i], IGRAPHMODULE_TYPE_INT); if (!item || PyList_SetItem(list, i, item)) { if (item) { Py_DECREF(item); } Py_DECREF(list); for (j = 0; j < no_of_target_nodes; j++) igraph_vector_destroy(&res[j]); free(res); return NULL; } } for (j = 0; j < no_of_target_nodes; j++) igraph_vector_destroy(&res[j]); free(res); return list; } /** \ingroup python_interface_graph * \brief Calculates all of the shortest paths from/to a given node in the graph * \return a list containing shortest paths from/to the given node * \sa igraph_get_shortest_paths */ PyObject *igraphmodule_Graph_get_all_shortest_paths(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "v", "to", "weights", "mode", NULL }; igraph_vector_ptr_t res; igraph_vector_t *weights = 0; igraph_neimode_t mode = IGRAPH_OUT; long int i, j; igraph_integer_t from; igraph_vs_t to; PyObject *list, *item, *from_o, *mode_o=Py_None, *to_o=Py_None, *weights_o=Py_None; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|OOO", kwlist, &from_o, &to_o, &weights_o, &mode_o)) return NULL; if (igraphmodule_PyObject_to_neimode_t(mode_o, &mode)) return NULL; if (igraphmodule_PyObject_to_vid(from_o, &from, &self->g)) return NULL; if (igraphmodule_PyObject_to_vs_t(to_o, &to, &self->g, 0, 0)) return NULL; if (igraphmodule_attrib_to_vector_t(weights_o, self, &weights, ATTRIBUTE_TYPE_EDGE)) { igraph_vs_destroy(&to); return NULL; } if (igraph_vector_ptr_init(&res, 1)) { igraphmodule_handle_igraph_error(); igraph_vs_destroy(&to); if (weights) { igraph_vector_destroy(weights); free(weights); } return NULL; } if (igraph_get_all_shortest_paths_dijkstra(&self->g, &res, NULL, from, to, weights, mode)) { igraphmodule_handle_igraph_error(); igraph_vector_ptr_destroy(&res); igraph_vs_destroy(&to); if (weights) { igraph_vector_destroy(weights); free(weights); } return NULL; } igraph_vs_destroy(&to); if (weights) { igraph_vector_destroy(weights); free(weights); } IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(&res, igraph_vector_destroy); j = igraph_vector_ptr_size(&res); list = PyList_New(j); if (!list) { igraph_vector_ptr_destroy_all(&res); return NULL; } for (i = 0; i < j; i++) { item = igraphmodule_vector_t_to_PyList((igraph_vector_t *) igraph_vector_ptr_e(&res, i), IGRAPHMODULE_TYPE_INT); if (!item) { Py_DECREF(list); igraph_vector_ptr_destroy_all(&res); return NULL; } if (PyList_SetItem(list, i, item)) { Py_DECREF(list); Py_DECREF(item); igraph_vector_ptr_destroy_all(&res); return NULL; } } igraph_vector_ptr_destroy_all(&res); return list; } /** \ingroup python_interface_graph * \brief Calculates all the simple paths from a single source to other nodes * in the graph. * * \return a list containing all simple paths from the given node to the given * nodes * \sa igraph_get_all_simple_paths */ PyObject *igraphmodule_Graph_get_all_simple_paths(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "v", "to", "cutoff", "mode", NULL }; igraph_vector_int_t res; igraph_neimode_t mode = IGRAPH_OUT; igraph_integer_t from; igraph_vs_t to; igraph_integer_t cutoff; PyObject *list, *from_o, *mode_o=Py_None, *to_o=Py_None, *cutoff_o=Py_None; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|OOO", kwlist, &from_o, &to_o, &cutoff_o, &mode_o)) return NULL; if (igraphmodule_PyObject_to_neimode_t(mode_o, &mode)) return NULL; if (PyInt_AsInt(cutoff_o, &cutoff)) return NULL; if (igraphmodule_PyObject_to_vid(from_o, &from, &self->g)) return NULL; if (igraphmodule_PyObject_to_vs_t(to_o, &to, &self->g, 0, 0)) return NULL; if (igraph_vector_int_init(&res, 0)) { igraphmodule_handle_igraph_error(); igraph_vs_destroy(&to); return NULL; } if (igraph_get_all_simple_paths(&self->g, &res, from, to, cutoff, mode)) { igraphmodule_handle_igraph_error(); igraph_vector_int_destroy(&res); igraph_vs_destroy(&to); return NULL; } igraph_vs_destroy(&to); list = igraphmodule_vector_int_t_to_PyList(&res); return list; } /** \ingroup python_interface_graph * \brief Calculates Kleinberg's hub scores of the vertices in the graph * \sa igraph_hub_score */ PyObject *igraphmodule_Graph_hub_score( igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = { "weights", "scale", "arpack_options", "return_eigenvalue", NULL }; PyObject *scale_o = Py_True, *weights_o = Py_None; PyObject *arpack_options_o = igraphmodule_arpack_options_default; igraphmodule_ARPACKOptionsObject *arpack_options; PyObject *return_eigenvalue = Py_False; PyObject *res_o; igraph_real_t value; igraph_vector_t res, *weights = 0; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOO!O", kwlist, &weights_o, &scale_o, &igraphmodule_ARPACKOptionsType, &arpack_options, &return_eigenvalue)) return NULL; if (igraph_vector_init(&res, 0)) return igraphmodule_handle_igraph_error(); if (igraphmodule_attrib_to_vector_t(weights_o, self, &weights, ATTRIBUTE_TYPE_EDGE)) return NULL; arpack_options = (igraphmodule_ARPACKOptionsObject*)arpack_options_o; if (igraph_hub_score(&self->g, &res, &value, PyObject_IsTrue(scale_o), weights, igraphmodule_ARPACKOptions_get(arpack_options))) { igraphmodule_handle_igraph_error(); if (weights) { igraph_vector_destroy(weights); free(weights); } igraph_vector_destroy(&res); return NULL; } if (weights) { igraph_vector_destroy(weights); free(weights); } res_o = igraphmodule_vector_t_to_PyList(&res, IGRAPHMODULE_TYPE_FLOAT); igraph_vector_destroy(&res); if (res_o == NULL) return igraphmodule_handle_igraph_error(); if (PyObject_IsTrue(return_eigenvalue)) { PyObject *ev_o = PyFloat_FromDouble((double)value); if (ev_o == NULL) { Py_DECREF(res_o); return igraphmodule_handle_igraph_error(); } return Py_BuildValue("NN", res_o, ev_o); } return res_o; } /** \ingroup python_interface_graph * \brief Returns the line graph of the graph * \return the line graph as a new igraph object * \sa igraph_linegraph */ PyObject *igraphmodule_Graph_linegraph(igraphmodule_GraphObject * self) { igraph_t lg; igraphmodule_GraphObject *result; if (igraph_linegraph(&self->g, &lg)) { igraphmodule_handle_igraph_error(); return NULL; } CREATE_GRAPH(result, lg); return (PyObject *) result; } /** * \ingroup python_interface_graph * \brief Returns the k-neighborhood of some vertices in the * graph. * \sa igraph_neighborhood */ PyObject *igraphmodule_Graph_neighborhood(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = { "vertices", "order", "mode", "mindist", NULL }; PyObject *vobj = Py_None; PyObject *mode_o = 0; PyObject *result; long int order = 1; int mindist = 0; igraph_neimode_t mode = IGRAPH_ALL; igraph_bool_t return_single = 0; igraph_vs_t vs; igraph_vector_ptr_t res; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OlOi", kwlist, &vobj, &order, &mode_o, &mindist)) return NULL; if (igraphmodule_PyObject_to_neimode_t(mode_o, &mode)) return NULL; if (igraphmodule_PyObject_to_vs_t(vobj, &vs, &self->g, &return_single, 0)) { return igraphmodule_handle_igraph_error(); } if (igraph_vector_ptr_init(&res, 0)) { igraph_vs_destroy(&vs); return igraphmodule_handle_igraph_error(); } if (igraph_neighborhood(&self->g, &res, vs, (igraph_integer_t) order, mode, mindist)) { igraph_vs_destroy(&vs); return igraphmodule_handle_igraph_error(); } igraph_vs_destroy(&vs); if (!return_single) result = igraphmodule_vector_ptr_t_to_PyList(&res, IGRAPHMODULE_TYPE_INT); else result = igraphmodule_vector_t_to_PyList((igraph_vector_t*)VECTOR(res)[0], IGRAPHMODULE_TYPE_INT); IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(&res, igraph_vector_destroy); igraph_vector_ptr_destroy_all(&res); return result; } /** * \ingroup python_interface_graph * \brief Returns the size of the k-neighborhood of some vertices in the * graph. * \sa igraph_neighborhood_size */ PyObject *igraphmodule_Graph_neighborhood_size(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = { "vertices", "order", "mode", "mindist", NULL }; PyObject *vobj = Py_None; PyObject *mode_o = 0; PyObject *result; long int order = 1; int mindist = 0; igraph_neimode_t mode = IGRAPH_ALL; igraph_bool_t return_single = 0; igraph_vs_t vs; igraph_vector_t res; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OlOi", kwlist, &vobj, &order, &mode_o, &mindist)) return NULL; if (igraphmodule_PyObject_to_neimode_t(mode_o, &mode)) return NULL; if (igraphmodule_PyObject_to_vs_t(vobj, &vs, &self->g, &return_single, 0)) { return igraphmodule_handle_igraph_error(); } if (igraph_vector_init(&res, 0)) { igraph_vs_destroy(&vs); return igraphmodule_handle_igraph_error(); } if (igraph_neighborhood_size(&self->g, &res, vs, (igraph_integer_t) order, mode, mindist)) { igraph_vs_destroy(&vs); return igraphmodule_handle_igraph_error(); } igraph_vs_destroy(&vs); if (!return_single) result = igraphmodule_vector_t_to_PyList(&res, IGRAPHMODULE_TYPE_INT); else result = PyInt_FromLong((long)VECTOR(res)[0]); igraph_vector_destroy(&res); return result; } /** \ingroup python_interface_graph * \brief Calculates the Google personalized PageRank value of some vertices in the graph. * \return the personalized PageRank values * \sa igraph_personalized_pagerank */ PyObject *igraphmodule_Graph_personalized_pagerank(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = { "vertices", "directed", "damping", "reset", "reset_vertices", "weights", "arpack_options", "implementation", "niter", "eps", NULL }; PyObject *directed = Py_True; PyObject *vobj = Py_None, *wobj = Py_None, *robj = Py_None, *rvsobj = Py_None; PyObject *list; PyObject *arpack_options_o = igraphmodule_arpack_options_default; igraphmodule_ARPACKOptionsObject *arpack_options; double damping = 0.85; igraph_vector_t res; igraph_vector_t *reset = 0; igraph_vector_t weights; igraph_bool_t return_single = 0; igraph_vs_t vs, reset_vs; igraph_pagerank_algo_t algo=IGRAPH_PAGERANK_ALGO_PRPACK; PyObject *algo_o = Py_None; long niter=1000; float eps=0.001f; igraph_pagerank_power_options_t popts; void *opts; int retval; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOdOOOO!Olf", kwlist, &vobj, &directed, &damping, &robj, &rvsobj, &wobj, &igraphmodule_ARPACKOptionsType, &arpack_options_o, &algo_o, &niter, &eps)) return NULL; if (robj != Py_None && rvsobj != Py_None) { PyErr_SetString(PyExc_ValueError, "only reset or reset_vs can be defined, not both"); return NULL; } if (igraphmodule_PyObject_to_vs_t(vobj, &vs, &self->g, &return_single, 0)) { igraphmodule_handle_igraph_error(); return NULL; } arpack_options = (igraphmodule_ARPACKOptionsObject*)arpack_options_o; if (robj != Py_None) { if (igraphmodule_attrib_to_vector_t(robj, self, &reset, ATTRIBUTE_TYPE_VERTEX)) { igraph_vs_destroy(&vs); igraphmodule_handle_igraph_error(); return NULL; } } else if (rvsobj != Py_None) { if (igraphmodule_PyObject_to_vs_t(rvsobj, &reset_vs, &self->g, 0, 0)) { igraph_vs_destroy(&vs); igraphmodule_handle_igraph_error(); return NULL; } } if (igraphmodule_PyObject_to_attribute_values(wobj, &weights, self, ATTRHASH_IDX_EDGE, 1.0)) { igraph_vs_destroy(&vs); if (rvsobj != Py_None) igraph_vs_destroy(&reset_vs); if (reset) { igraph_vector_destroy(reset); free(reset); } return NULL; } if (igraph_vector_init(&res, 0)) { igraph_vs_destroy(&vs); if (rvsobj != Py_None) igraph_vs_destroy(&reset_vs); if (reset) { igraph_vector_destroy(reset); free(reset); } igraph_vector_destroy(&weights); return igraphmodule_handle_igraph_error(); } if (igraphmodule_PyObject_to_pagerank_algo_t(algo_o, &algo)) return NULL; popts.niter = (igraph_integer_t) niter; popts.eps = eps; if (algo == IGRAPH_PAGERANK_ALGO_POWER) { opts = &popts; } else if (algo == IGRAPH_PAGERANK_ALGO_ARPACK) { opts = igraphmodule_ARPACKOptions_get(arpack_options); } else { opts = 0; } if (rvsobj != Py_None) retval = igraph_personalized_pagerank_vs(&self->g, algo, &res, 0, vs, PyObject_IsTrue(directed), damping, reset_vs, &weights, opts); else retval = igraph_personalized_pagerank(&self->g, algo, &res, 0, vs, PyObject_IsTrue(directed), damping, reset, &weights, opts); if (retval) { igraphmodule_handle_igraph_error(); igraph_vs_destroy(&vs); if (rvsobj != Py_None) igraph_vs_destroy(&reset_vs); if (reset) { igraph_vector_destroy(reset); free(reset); } igraph_vector_destroy(&weights); igraph_vector_destroy(&res); return NULL; } if (!return_single) list = igraphmodule_vector_t_to_PyList(&res, IGRAPHMODULE_TYPE_FLOAT); else list = PyFloat_FromDouble(VECTOR(res)[0]); igraph_vector_destroy(&res); igraph_vs_destroy(&vs); if (rvsobj != Py_None) igraph_vs_destroy(&reset_vs); igraph_vector_destroy(&weights); if (reset) { igraph_vector_destroy(reset); free(reset); } return list; } /** \ingroup python_interface_graph * \brief Calculates the path length histogram of the graph * \sa igraph_path_length_hist */ PyObject *igraphmodule_Graph_path_length_hist(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = { "directed", NULL }; PyObject *directed = Py_True, *result; igraph_real_t unconn; igraph_vector_t res; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O", kwlist, &directed)) return NULL; if (igraph_vector_init(&res, 0)) return igraphmodule_handle_igraph_error(); if (igraph_path_length_hist(&self->g, &res, &unconn, PyObject_IsTrue(directed))) { igraph_vector_destroy(&res); return igraphmodule_handle_igraph_error(); } result=igraphmodule_vector_t_to_PyList(&res, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&res); return Py_BuildValue("Nd", result, (double)unconn); } /** \ingroup python_interface_graph * \brief Permutes the vertices of the graph * \return the new graph as a new igraph object * \sa igraph_permute_vertices */ PyObject *igraphmodule_Graph_permute_vertices(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = { "permutation", NULL }; igraph_t pg; igraph_vector_t perm; igraphmodule_GraphObject *result; PyObject *list; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O!", kwlist, &PyList_Type, &list)) return NULL; if (igraphmodule_PyObject_to_vector_t(list, &perm, 1)) return NULL; if (igraph_permute_vertices(&self->g, &pg, &perm)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&perm); return NULL; } igraph_vector_destroy(&perm); CREATE_GRAPH(result, pg); return (PyObject *) result; } /** \ingroup python_interface_graph * \brief Rewires a graph while preserving degree distribution * \return the rewired graph * \sa igraph_rewire */ PyObject *igraphmodule_Graph_rewire(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "n", "mode", NULL }; long int n = 1000; PyObject *mode_o = Py_None; igraph_rewiring_t mode = IGRAPH_REWIRING_SIMPLE; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|lO", kwlist, &n, &mode_o)) return NULL; if (igraphmodule_PyObject_to_rewiring_t(mode_o, &mode)) return NULL; if (igraph_rewire(&self->g, (igraph_integer_t) n, mode)) { igraphmodule_handle_igraph_error(); return NULL; } Py_RETURN_NONE; } /** \ingroup python_interface_graph * \brief Rewires the edges of a graph wth constant probability * \return the rewired graph * \sa igraph_rewire_edges */ PyObject *igraphmodule_Graph_rewire_edges(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "prob", "loops", "multiple", NULL }; double prob; PyObject *loops_o = Py_False, *multiple_o = Py_False; if (!PyArg_ParseTupleAndKeywords(args, kwds, "d|OO", kwlist, &prob, &loops_o, &multiple_o)) return NULL; if (igraph_rewire_edges(&self->g, prob, PyObject_IsTrue(loops_o), PyObject_IsTrue(multiple_o))) { igraphmodule_handle_igraph_error(); return NULL; } Py_RETURN_NONE; } /** \ingroup python_interface_graph * \brief Calculates shortest paths in a graph. * \return the shortest path lengths for the given vertices * \sa igraph_shortest_paths, igraph_shortest_paths_dijkstra, * igraph_shortest_paths_bellman_ford, igraph_shortest_paths_johnson */ PyObject *igraphmodule_Graph_shortest_paths(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "source", "target", "weights", "mode", NULL }; PyObject *from_o = NULL, *to_o = NULL, *mode_o = NULL, *weights_o = Py_None; PyObject *list = NULL; igraph_matrix_t res; igraph_vector_t *weights=0; igraph_neimode_t mode = IGRAPH_OUT; int return_single_from = 0, return_single_to = 0, e = 0; igraph_vs_t from_vs, to_vs; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOOO", kwlist, &from_o, &to_o, &weights_o, &mode_o)) return NULL; if (igraphmodule_PyObject_to_neimode_t(mode_o, &mode)) return 0; if (igraphmodule_PyObject_to_vs_t(from_o, &from_vs, &self->g, &return_single_from, 0)) { igraphmodule_handle_igraph_error(); return NULL; } if (igraphmodule_PyObject_to_vs_t(to_o, &to_vs, &self->g, &return_single_to, 0)) { igraph_vs_destroy(&from_vs); igraphmodule_handle_igraph_error(); return NULL; } if (igraphmodule_attrib_to_vector_t(weights_o, self, &weights, ATTRIBUTE_TYPE_EDGE)) { igraph_vs_destroy(&from_vs); igraph_vs_destroy(&to_vs); return NULL; } if (igraph_matrix_init(&res, 1, igraph_vcount(&self->g))) { if (weights) { igraph_vector_destroy(weights); free(weights); } igraph_vs_destroy(&from_vs); igraph_vs_destroy(&to_vs); return igraphmodule_handle_igraph_error(); } /* Select the most suitable algorithm */ if (weights) { if (igraph_vector_min(weights) > 0) { /* Only positive weights, use Dijkstra's algorithm */ e = igraph_shortest_paths_dijkstra(&self->g, &res, from_vs, to_vs, weights, mode); } else { /* There are negative weights. For a small number of sources, use Bellman-Ford. * Otherwise, use Johnson's algorithm */ igraph_integer_t vs_size; e = igraph_vs_size(&self->g, &from_vs, &vs_size); if (!e) { if (vs_size <= 100 || mode != IGRAPH_OUT) { e = igraph_shortest_paths_bellman_ford(&self->g, &res, from_vs, to_vs, weights, mode); } else { e = igraph_shortest_paths_johnson(&self->g, &res, from_vs, to_vs, weights); } } } } else { /* No weights, use a simple BFS */ e = igraph_shortest_paths(&self->g, &res, from_vs, to_vs, mode); } if (e) { if (weights) igraph_vector_destroy(weights); igraph_matrix_destroy(&res); igraph_vs_destroy(&from_vs); igraph_vs_destroy(&to_vs); igraphmodule_handle_igraph_error(); return NULL; } if (weights) { igraph_vector_destroy(weights); list = igraphmodule_matrix_t_to_PyList(&res, IGRAPHMODULE_TYPE_FLOAT); } else { list = igraphmodule_matrix_t_to_PyList(&res, IGRAPHMODULE_TYPE_INT); } if (weights) { igraph_vector_destroy(weights); free(weights); } igraph_matrix_destroy(&res); igraph_vs_destroy(&from_vs); igraph_vs_destroy(&to_vs); return list; } /** \ingroup python_interface_graph * \brief Calculates the Jaccard similarities of some vertices in a graph. * \return the similarity scores in a matrix * \sa igraph_similarity_jaccard */ PyObject *igraphmodule_Graph_similarity_jaccard(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "vertices", "pairs", "mode", "loops", NULL }; PyObject *vertices_o = Py_None, *pairs_o = Py_None; PyObject *list = NULL, *loops = Py_True, *mode_o = Py_None; igraph_neimode_t mode = IGRAPH_ALL; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOOO", kwlist, &vertices_o, &pairs_o, &mode_o, &loops)) return NULL; if (igraphmodule_PyObject_to_neimode_t(mode_o, &mode)) return NULL; if (vertices_o != Py_None && pairs_o != Py_None) { PyErr_SetString(PyExc_ValueError, "at most one of `vertices` and `pairs` " "must be given"); return NULL; } if (pairs_o == Py_None) { /* Case #1: vertices, returning matrix */ igraph_matrix_t res; igraph_vs_t vs; int return_single = 0; if (igraphmodule_PyObject_to_vs_t(vertices_o, &vs, &self->g, &return_single, 0)) return NULL; if (igraph_matrix_init(&res, 0, 0)) { igraph_vs_destroy(&vs); return igraphmodule_handle_igraph_error(); } if (igraph_similarity_jaccard(&self->g, &res, vs, mode, PyObject_IsTrue(loops))) { igraph_matrix_destroy(&res); igraph_vs_destroy(&vs); igraphmodule_handle_igraph_error(); return NULL; } igraph_vs_destroy(&vs); list = igraphmodule_matrix_t_to_PyList(&res, IGRAPHMODULE_TYPE_FLOAT); igraph_matrix_destroy(&res); } else { /* Case #2: vertex pairs or edges, returning list */ igraph_vector_t edges; igraph_vector_t res; igraph_bool_t edges_owned; if (igraphmodule_PyObject_to_edgelist(pairs_o, &edges, 0, &edges_owned)) return NULL; if (igraph_vector_init(&res, igraph_vector_size(&edges) / 2)) { igraph_vector_destroy(&edges); igraphmodule_handle_igraph_error(); return NULL; } if (igraph_similarity_jaccard_pairs(&self->g, &res, &edges, mode, PyObject_IsTrue(loops))) { igraph_vector_destroy(&res); if (edges_owned) { igraph_vector_destroy(&edges); } igraphmodule_handle_igraph_error(); return NULL; } if (edges_owned) { igraph_vector_destroy(&edges); } list = igraphmodule_vector_t_to_PyList(&res, IGRAPHMODULE_TYPE_FLOAT); igraph_vector_destroy(&res); } return list; } /** \ingroup python_interface_graph * \brief Calculates the Dice similarities of some vertices in a graph. * \return the similarity scores in a matrix * \sa igraph_similarity_dice */ PyObject *igraphmodule_Graph_similarity_dice(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "vertices", "pairs", "mode", "loops", NULL }; PyObject *vertices_o = Py_None, *pairs_o = Py_None; PyObject *list = NULL, *loops = Py_True, *mode_o = Py_None; igraph_neimode_t mode = IGRAPH_ALL; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOOO", kwlist, &vertices_o, &pairs_o, &mode_o, &loops)) return NULL; if (igraphmodule_PyObject_to_neimode_t(mode_o, &mode)) return NULL; if (vertices_o != Py_None && pairs_o != Py_None) { PyErr_SetString(PyExc_ValueError, "at most one of `vertices` and `pairs` " "must be given"); return NULL; } if (pairs_o == Py_None) { /* Case #1: vertices, returning matrix */ igraph_matrix_t res; igraph_vs_t vs; int return_single = 0; if (igraphmodule_PyObject_to_vs_t(vertices_o, &vs, &self->g, &return_single, 0)) return NULL; if (igraph_matrix_init(&res, 0, 0)) { igraph_vs_destroy(&vs); return igraphmodule_handle_igraph_error(); } if (igraph_similarity_dice(&self->g, &res, vs, mode, PyObject_IsTrue(loops))) { igraph_matrix_destroy(&res); igraph_vs_destroy(&vs); igraphmodule_handle_igraph_error(); return NULL; } igraph_vs_destroy(&vs); list = igraphmodule_matrix_t_to_PyList(&res, IGRAPHMODULE_TYPE_FLOAT); igraph_matrix_destroy(&res); } else { /* Case #2: vertex pairs or edges, returning list */ igraph_vector_t edges; igraph_vector_t res; igraph_bool_t edges_owned; if (igraphmodule_PyObject_to_edgelist(pairs_o, &edges, 0, &edges_owned)) return NULL; if (igraph_vector_init(&res, igraph_vector_size(&edges) / 2)) { if (edges_owned) { igraph_vector_destroy(&edges); } igraphmodule_handle_igraph_error(); return NULL; } if (igraph_similarity_dice_pairs(&self->g, &res, &edges, mode, PyObject_IsTrue(loops))) { igraph_vector_destroy(&res); if (edges_owned) { igraph_vector_destroy(&edges); } igraphmodule_handle_igraph_error(); return NULL; } if (edges_owned) { igraph_vector_destroy(&edges); } list = igraphmodule_vector_t_to_PyList(&res, IGRAPHMODULE_TYPE_FLOAT); igraph_vector_destroy(&res); } return list; } /** \ingroup python_interface_graph * \brief Calculates the inverse log-weighted similarities of some vertices in * a graph. * \return the similarity scores in a matrix * \sa igraph_similarity_inverse_log_weighted */ PyObject *igraphmodule_Graph_similarity_inverse_log_weighted( igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "vertices", "mode", NULL }; PyObject *vobj = NULL, *list = NULL, *mode_o = Py_None; igraph_matrix_t res; igraph_neimode_t mode = IGRAPH_ALL; int return_single = 0; igraph_vs_t vs; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OO", kwlist, &vobj, &mode_o)) return NULL; if (igraphmodule_PyObject_to_neimode_t(mode_o, &mode)) return NULL; if (igraphmodule_PyObject_to_vs_t(vobj, &vs, &self->g, &return_single, 0)) return NULL; if (igraph_matrix_init(&res, 0, 0)) { igraph_vs_destroy(&vs); return igraphmodule_handle_igraph_error(); } if (igraph_similarity_inverse_log_weighted(&self->g,&res,vs,mode)) { igraph_matrix_destroy(&res); igraph_vs_destroy(&vs); igraphmodule_handle_igraph_error(); return NULL; } list = igraphmodule_matrix_t_to_PyList(&res, IGRAPHMODULE_TYPE_FLOAT); igraph_matrix_destroy(&res); igraph_vs_destroy(&vs); return list; } /** \ingroup python_interface_graph * \brief Calculates a spanning tree for a graph * \return the spanning tree or a list of edges participating in the spanning tree * \sa igraph_minimum_spanning_tree_unweighted * \sa igraph_minimum_spanning_tree_unweighted * \sa igraph_minimum_spanning_tree_prim */ PyObject *igraphmodule_Graph_spanning_tree(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "weights", NULL }; igraph_vector_t* ws = 0; igraph_vector_t res; PyObject *weights_o = Py_None, *result = NULL; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O", kwlist, &weights_o)) return NULL; if (igraph_vector_init(&res, 0)) { igraphmodule_handle_igraph_error(); return NULL; } if (igraphmodule_attrib_to_vector_t(weights_o, self, &ws, ATTRIBUTE_TYPE_EDGE)) { igraph_vector_destroy(&res); return NULL; } if (igraph_minimum_spanning_tree(&self->g, &res, ws)) { if (ws != 0) { igraph_vector_destroy(ws); free(ws); } igraph_vector_destroy(&res); igraphmodule_handle_igraph_error(); return NULL; } if (ws != 0) { igraph_vector_destroy(ws); free(ws); } result = igraphmodule_vector_t_to_PyList(&res, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&res); return result; } /** \ingroup python_interface_graph * \brief Simplifies a graph by removing loops and/or multiple edges * \return the simplified graph. * \sa igraph_simplify */ PyObject *igraphmodule_Graph_simplify(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "multiple", "loops", "combine_edges", NULL }; PyObject *multiple = Py_True, *loops = Py_True, *comb_o = Py_None; igraph_attribute_combination_t comb; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOO", kwlist, &multiple, &loops, &comb_o)) return NULL; if (igraphmodule_PyObject_to_attribute_combination_t(comb_o, &comb)) return NULL; if (igraph_simplify(&self->g, PyObject_IsTrue(multiple), PyObject_IsTrue(loops), &comb)) { igraph_attribute_combination_destroy(&comb); igraphmodule_handle_igraph_error(); return NULL; } igraph_attribute_combination_destroy(&comb); Py_INCREF(self); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Calculates the vertex indices within the same component as a given vertex * \return the vertex indices in a list * \sa igraph_subcomponent */ PyObject *igraphmodule_Graph_subcomponent(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "v", "mode", NULL }; igraph_vector_t res; igraph_neimode_t mode = IGRAPH_ALL; igraph_integer_t from; PyObject *list = NULL, *mode_o = Py_None, *from_o = Py_None; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|O", kwlist, &from_o, &mode_o)) return NULL; if (igraphmodule_PyObject_to_neimode_t(mode_o, &mode)) return NULL; if (igraphmodule_PyObject_to_vid(from_o, &from, &self->g)) return NULL; igraph_vector_init(&res, 0); if (igraph_subcomponent(&self->g, &res, from, mode)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&res); return NULL; } list = igraphmodule_vector_t_to_PyList(&res, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&res); return list; } /** \ingroup python_interface_graph * \brief Returns an induced subgraph of the graph based on the given vertices * \return the subgraph as a new igraph object * \sa igraph_induced_subgraph */ PyObject *igraphmodule_Graph_induced_subgraph(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "vertices", "implementation", NULL }; igraph_vs_t vs; igraph_t sg; igraphmodule_GraphObject *result; PyObject *list, *impl_o = Py_None; igraph_subgraph_implementation_t impl = IGRAPH_SUBGRAPH_AUTO; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|O", kwlist, &list, &impl_o)) return NULL; if (igraphmodule_PyObject_to_subgraph_implementation_t(impl_o, &impl)) return NULL; if (igraphmodule_PyObject_to_vs_t(list, &vs, &self->g, 0, 0)) return NULL; if (igraph_induced_subgraph(&self->g, &sg, vs, impl)) { igraphmodule_handle_igraph_error(); igraph_vs_destroy(&vs); return NULL; } igraph_vs_destroy(&vs); CREATE_GRAPH(result, sg); return (PyObject *) result; } /** \ingroup python_interface_graph * \brief Returns a subgraph of the graph based on the given edges * \return the subgraph as a new igraph object * \sa igraph_subgraph_edges */ PyObject *igraphmodule_Graph_subgraph_edges(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "edges", "delete_vertices", NULL }; igraph_es_t es; igraph_t sg; igraphmodule_GraphObject *result; PyObject *list, *delete_vertices = Py_True; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|O", kwlist, &list, &delete_vertices)) return NULL; if (igraphmodule_PyObject_to_es_t(list, &es, &self->g, 0)) return NULL; if (igraph_subgraph_edges(&self->g, &sg, es, PyObject_IsTrue(delete_vertices))) { igraphmodule_handle_igraph_error(); igraph_es_destroy(&es); return NULL; } CREATE_GRAPH(result, sg); igraph_es_destroy(&es); return (PyObject *) result; } /** \ingroup python_interface_graph * \brief Calculates the graph transitivity (a.k.a. clustering coefficient) * \return the clustering coefficient * \sa igraph_transitivity_undirected */ PyObject *igraphmodule_Graph_transitivity_undirected(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "mode", NULL }; igraph_real_t res; PyObject *r, *mode_o = Py_None; igraph_transitivity_mode_t mode = IGRAPH_TRANSITIVITY_NAN; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O", kwlist, &mode_o)) return NULL; if (igraphmodule_PyObject_to_transitivity_mode_t(mode_o, &mode)) return NULL; if (igraph_transitivity_undirected(&self->g, &res, mode)) { igraphmodule_handle_igraph_error(); return NULL; } r = Py_BuildValue("d", (double)(res)); return r; } /** \ingroup python_interface_graph * \brief Calculates the average of vertex transitivities over the graph * \sa igraph_transitivity_avglocal_undirected */ PyObject *igraphmodule_Graph_transitivity_avglocal_undirected(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "mode", NULL }; igraph_real_t res; PyObject *r, *mode_o = Py_None; igraph_transitivity_mode_t mode = IGRAPH_TRANSITIVITY_NAN; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O", kwlist, &mode_o)) return NULL; if (igraphmodule_PyObject_to_transitivity_mode_t(mode_o, &mode)) return NULL; if (igraph_transitivity_avglocal_undirected(&self->g, &res, mode)) { igraphmodule_handle_igraph_error(); return NULL; } r = Py_BuildValue("d", (double)(res)); return r; } /** \ingroup python_interface_graph * \brief Calculates the local transitivity of given vertices * \return the transitivities in a list * \sa igraph_transitivity_local_undirected */ PyObject *igraphmodule_Graph_transitivity_local_undirected(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "vertices", "mode", "weights", NULL }; PyObject *vobj = NULL, *mode_o = Py_None, *list = NULL; PyObject *weights_o = Py_None; igraph_vector_t result; igraph_vector_t *weights = 0; igraph_bool_t return_single = 0; igraph_vs_t vs; igraph_transitivity_mode_t mode = IGRAPH_TRANSITIVITY_NAN; int retval; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOO", kwlist, &vobj, &mode_o, &weights_o)) return NULL; if (igraphmodule_PyObject_to_transitivity_mode_t(mode_o, &mode)) return NULL; if (igraphmodule_PyObject_to_vs_t(vobj, &vs, &self->g, &return_single, 0)) { igraphmodule_handle_igraph_error(); return NULL; } if (igraph_vector_init(&result, 0)) { igraph_vs_destroy(&vs); return igraphmodule_handle_igraph_error(); } if (igraphmodule_attrib_to_vector_t(weights_o, self, &weights, ATTRIBUTE_TYPE_EDGE)) { igraph_vs_destroy(&vs); igraph_vector_destroy(&result); return NULL; } if (weights == 0) { retval = igraph_transitivity_local_undirected(&self->g, &result, vs, mode); } else { retval = igraph_transitivity_barrat(&self->g, &result, vs, weights, mode); } igraph_vs_destroy(&vs); if (weights) { igraph_vector_destroy(weights); free(weights); } if (retval) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&result); return NULL; } if (!return_single) list = igraphmodule_vector_t_to_PyList(&result, IGRAPHMODULE_TYPE_FLOAT); else list = PyFloat_FromDouble(VECTOR(result)[0]); igraph_vector_destroy(&result); return list; } /** \ingroup python_interface_graph * \brief Calculates a possible topological sorting * \return a possible topological sorting as a list * \sa igraph_topological_sorting */ PyObject *igraphmodule_Graph_topological_sorting(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "mode", "warnings", NULL }; PyObject *list, *mode_o=Py_None; PyObject *warnings_o=Py_True; igraph_neimode_t mode = IGRAPH_OUT; igraph_vector_t result; igraph_warning_handler_t* old_handler = 0; int retval; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OO", kwlist, &mode_o, &warnings_o)) return NULL; if (igraphmodule_PyObject_to_neimode_t(mode_o, &mode)) return NULL; if (igraph_vector_init(&result, 0)) return igraphmodule_handle_igraph_error(); if (!PyObject_IsTrue(warnings_o)) { /* Turn off the warnings temporarily */ old_handler = igraph_set_warning_handler(igraph_warning_handler_ignore); } retval = igraph_topological_sorting(&self->g, &result, mode); if (!PyObject_IsTrue(warnings_o)) { /* Restore the warning handler */ igraph_set_warning_handler(old_handler); } if (retval) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&result); return NULL; } list = igraphmodule_vector_t_to_PyList(&result, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&result); return list; } /** \ingroup python_interface_graph * \brief Calculates the vertex connectivity of the graph * \return the vertex connectivity * \sa igraph_vertex_connectivity, igraph_st_vertex_connectivity */ PyObject *igraphmodule_Graph_vertex_connectivity(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = { "source", "target", "checks", "neighbors", NULL }; PyObject *checks = Py_True, *neis = Py_None; long int source = -1, target = -1, result; igraph_integer_t res; igraph_vconn_nei_t neighbors = IGRAPH_VCONN_NEI_ERROR; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|llOO", kwlist, &source, &target, &checks, &neis)) return NULL; if (source < 0 && target < 0) { if (igraph_vertex_connectivity(&self->g, &res, PyObject_IsTrue(checks))) { igraphmodule_handle_igraph_error(); return NULL; } } else if (source >= 0 && target >= 0) { if (igraphmodule_PyObject_to_vconn_nei_t(neis, &neighbors)) return NULL; if (igraph_st_vertex_connectivity(&self->g, &res, (igraph_integer_t) source, (igraph_integer_t) target, neighbors)) { igraphmodule_handle_igraph_error(); return NULL; } } else { PyErr_SetString(PyExc_ValueError, "if source or target is given, the other one must also be specified"); return NULL; } if (!IGRAPH_FINITE(res)) return Py_BuildValue("d", (double)res); result = (long)res; return Py_BuildValue("l", result); } /********************************************************************** * Bipartite graphs * **********************************************************************/ /** \ingroup python_interface_graph * \brief Checks whether a graph is bipartite * \return a boolean or a (boolean, list of booleans) pair * \sa igraph_is_bipartite */ PyObject *igraphmodule_Graph_is_bipartite(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { PyObject *types_o, *return_types_o = Py_False; igraph_vector_bool_t types; igraph_bool_t return_types = 0, result; static char *kwlist[] = { "return_types", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O", kwlist, &return_types_o)) return NULL; return_types = PyObject_IsTrue(return_types_o); if (return_types) { if (igraph_vector_bool_init(&types, igraph_vcount(&self->g))) { igraphmodule_handle_igraph_error(); return NULL; } if (igraph_is_bipartite(&self->g, &result, &types)) { igraph_vector_bool_destroy(&types); igraphmodule_handle_igraph_error(); return NULL; } if (result) { types_o = igraphmodule_vector_bool_t_to_PyList(&types); if (!types_o) { igraph_vector_bool_destroy(&types); return NULL; } igraph_vector_bool_destroy(&types); // reference to types_o will be stolen by Py_BuildValue return Py_BuildValue("ON", Py_True, types_o); } else { igraph_vector_bool_destroy(&types); return Py_BuildValue("OO", Py_False, Py_None); } } else { if (igraph_is_bipartite(&self->g, &result, 0)) { igraphmodule_handle_igraph_error(); return NULL; } if (result) Py_RETURN_TRUE; else Py_RETURN_FALSE; } } /********************************************************************** * Motifs, dyad and triad census * **********************************************************************/ /** \ingroup python_interface_graph * \brief Calculates the dyad census of the graph * \return the dyad census as a 3-tuple * \sa igraph_dyad_census */ PyObject *igraphmodule_Graph_dyad_census(igraphmodule_GraphObject *self) { igraph_integer_t mut, asym, nul; PyObject *list; if (igraph_dyad_census(&self->g, &mut, &asym, &nul)) { return igraphmodule_handle_igraph_error(); } list = Py_BuildValue("lll", (long)mut, (long)asym, (long)nul); return list; } typedef struct { PyObject* func; PyObject* graph; } igraphmodule_i_Graph_motifs_randesu_callback_data_t; igraph_bool_t igraphmodule_i_Graph_motifs_randesu_callback(const igraph_t *graph, igraph_vector_t *vids, int isoclass, void* extra) { igraphmodule_i_Graph_motifs_randesu_callback_data_t* data = (igraphmodule_i_Graph_motifs_randesu_callback_data_t*)extra; PyObject* vector; PyObject* result; igraph_bool_t retval; vector = igraphmodule_vector_t_to_PyList(vids, IGRAPHMODULE_TYPE_INT); if (vector == NULL) { /* Error in conversion, return 1 */ return 1; } result = PyObject_CallFunction(data->func, "OOi", data->graph, vector, isoclass); Py_DECREF(vector); if (result == NULL) { /* Error in callback, return 1 */ return 1; } retval = PyObject_IsTrue(result); Py_DECREF(result); return retval; } /** \ingroup python_interface_graph * \brief Counts the motifs of the graph sorted by isomorphism classes * \return the number of motifs found for each isomorphism class * \sa igraph_motifs_randesu */ PyObject *igraphmodule_Graph_motifs_randesu(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { igraph_vector_t result, cut_prob; long int size=3; PyObject* cut_prob_list=Py_None; PyObject* callback=Py_None; PyObject *list; static char* kwlist[] = {"size", "cut_prob", "callback", NULL}; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|lOO", kwlist, &size, &cut_prob_list, &callback)) return NULL; if (cut_prob_list == Py_None) { if (igraph_vector_init(&cut_prob, size)) { return igraphmodule_handle_igraph_error(); } igraph_vector_fill(&cut_prob, 0); } else { if (igraphmodule_PyObject_float_to_vector_t(cut_prob_list, &cut_prob)) return NULL; } if (callback == Py_None) { if (igraph_vector_init(&result, 1)) { igraph_vector_destroy(&cut_prob); return igraphmodule_handle_igraph_error(); } if (igraph_motifs_randesu(&self->g, &result, (igraph_integer_t) size, &cut_prob)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&result); igraph_vector_destroy(&cut_prob); return NULL; } igraph_vector_destroy(&cut_prob); list = igraphmodule_vector_t_to_PyList(&result, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&result); return list; } else if (PyCallable_Check(callback)) { igraphmodule_i_Graph_motifs_randesu_callback_data_t data; data.graph = (PyObject*)self; data.func = callback; if (igraph_motifs_randesu_callback(&self->g, (igraph_integer_t) size, &cut_prob, igraphmodule_i_Graph_motifs_randesu_callback, &data)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&cut_prob); return NULL; } igraph_vector_destroy(&cut_prob); /* Don't let exceptions from the callback function go unnoticed */ if (PyErr_Occurred()) return NULL; Py_RETURN_NONE; } else { PyErr_SetString(PyExc_TypeError, "callback must be callable or None"); return NULL; } } /** \ingroup python_interface_graph * \brief Counts the total number of motifs of the graph * \return the total number of motifs * \sa igraph_motifs_randesu */ PyObject *igraphmodule_Graph_motifs_randesu_no(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { igraph_vector_t cut_prob; igraph_integer_t result; long int size=3; PyObject* cut_prob_list=Py_None; static char* kwlist[] = {"size", "cut_prob", NULL}; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|lO", kwlist, &size, &cut_prob_list)) return NULL; if (cut_prob_list == Py_None) { if (igraph_vector_init(&cut_prob, size)) { return igraphmodule_handle_igraph_error(); } igraph_vector_fill(&cut_prob, 0); } else { if (igraphmodule_PyObject_float_to_vector_t(cut_prob_list, &cut_prob)) { return NULL; } } if (igraph_motifs_randesu_no(&self->g, &result, (igraph_integer_t) size, &cut_prob)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&cut_prob); return NULL; } igraph_vector_destroy(&cut_prob); return PyInt_FromLong((long)result); } /** \ingroup python_interface_graph * \brief Estimates the total number of motifs of the graph * \return the estimated total number of motifs * \sa igraph_motifs_randesu_estimate */ PyObject *igraphmodule_Graph_motifs_randesu_estimate(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { igraph_vector_t cut_prob; igraph_integer_t result; long size=3; PyObject* cut_prob_list=Py_None; PyObject *sample=Py_None; static char* kwlist[] = {"size", "cut_prob", "sample", NULL}; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|lOO", kwlist, &size, &cut_prob_list, &sample)) return NULL; if (sample == Py_None) { PyErr_SetString(PyExc_TypeError, "sample size must be given"); return NULL; } if (cut_prob_list == Py_None) { if (igraph_vector_init(&cut_prob, size)) { return igraphmodule_handle_igraph_error(); } igraph_vector_fill(&cut_prob, 0); } else { if (igraphmodule_PyObject_float_to_vector_t(cut_prob_list, &cut_prob)) { return NULL; } } if (PyInt_Check(sample)) { /* samples chosen randomly */ long int ns = PyInt_AsLong(sample); if (igraph_motifs_randesu_estimate(&self->g, &result, (igraph_integer_t) size, &cut_prob, (igraph_integer_t) ns, 0)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&cut_prob); return NULL; } } else { /* samples given in advance */ igraph_vector_t samp; if (igraphmodule_PyObject_to_vector_t(sample, &samp, 1)) { igraph_vector_destroy(&cut_prob); return NULL; } if (igraph_motifs_randesu_estimate(&self->g, &result, (igraph_integer_t) size, &cut_prob, 0, &samp)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&cut_prob); return NULL; } } igraph_vector_destroy(&cut_prob); return PyInt_FromLong((long)result); } /** \ingroup python_interface_graph * \brief Calculates the triad census of the graph * \return the triad census as a list * \sa igraph_triad_census */ PyObject *igraphmodule_Graph_triad_census(igraphmodule_GraphObject *self) { igraph_vector_t result; PyObject *list; if (igraph_vector_init(&result, 16)) { return igraphmodule_handle_igraph_error(); } if (igraph_triad_census(&self->g, &result)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&result); return NULL; } list = igraphmodule_vector_t_to_PyTuple(&result); igraph_vector_destroy(&result); return list; } /********************************************************************** * Graph layout algorithms * **********************************************************************/ /** \ingroup python_interface_graph * \brief Places the vertices of a graph uniformly on a circle. * \return the calculated coordinates as a Python list of lists * \sa igraph_layout_circle */ PyObject *igraphmodule_Graph_layout_circle(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { igraph_matrix_t m; int ret; long dim = 2; PyObject *result; PyObject *order_o = Py_None; igraph_vs_t order; static char *kwlist[] = { "dim", "order", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|lO", kwlist, &dim, &order_o)) return NULL; if (dim != 2 && dim != 3) { PyErr_SetString(PyExc_ValueError, "number of dimensions must be either 2 or 3"); return NULL; } if (dim != 2 && order_o != Py_None) { PyErr_SetString(PyExc_NotImplementedError, "vertex ordering is supported "\ "for 2 dimensions only"); return NULL; } if (igraphmodule_PyObject_to_vs_t(order_o, &order, &self->g, 0, 0)) { return NULL; } if (igraph_matrix_init(&m, 1, 1)) { igraphmodule_handle_igraph_error(); igraph_vs_destroy(&order); return NULL; } if (dim == 2) ret = igraph_layout_circle(&self->g, &m, order); else ret = igraph_layout_sphere(&self->g, &m); igraph_vs_destroy(&order); if (ret) { igraph_matrix_destroy(&m); igraphmodule_handle_igraph_error(); return NULL; } result = igraphmodule_matrix_t_to_PyList(&m, IGRAPHMODULE_TYPE_FLOAT); igraph_matrix_destroy(&m); return (PyObject *) result; } /** \ingroup python_interface_graph * \brief Places the vertices of a graph randomly. * \return the calculated coordinates as a Python list of lists * \sa igraph_layout_random */ PyObject *igraphmodule_Graph_layout_random(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { igraph_matrix_t m; int ret; long dim = 2; PyObject *result; static char *kwlist[] = { "dim", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|l", kwlist, &dim)) return NULL; if (dim != 2 && dim != 3) { PyErr_SetString(PyExc_ValueError, "number of dimensions must be either 2 or 3"); return NULL; } if (igraph_matrix_init(&m, 1, 1)) { igraphmodule_handle_igraph_error(); return NULL; } if (dim == 2) ret = igraph_layout_random(&self->g, &m); else ret = igraph_layout_random_3d(&self->g, &m); if (ret) { igraph_matrix_destroy(&m); igraphmodule_handle_igraph_error(); return NULL; } result = igraphmodule_matrix_t_to_PyList(&m, IGRAPHMODULE_TYPE_FLOAT); igraph_matrix_destroy(&m); return (PyObject *) result; } /** \ingroup python_interface_graph * \brief Places the vertices on a grid * \sa igraph_layout_grid, igraph_layout_grid_3d */ PyObject *igraphmodule_Graph_layout_grid(igraphmodule_GraphObject* self, PyObject *args, PyObject *kwds) { static char *kwlist[] = { "width", "height", "dim", NULL }; igraph_matrix_t m; PyObject *result; long int width = 0, height = 0, dim = 2; int ret; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|lll", kwlist, &width, &height, &dim)) return NULL; if (dim == 2 && height > 0) { PyErr_SetString(PyExc_ValueError, "height must not be given if dim=2"); return NULL; } if (dim != 2 && dim != 3) { PyErr_SetString(PyExc_ValueError, "number of dimensions must be either 2 or 3"); return NULL; } if (igraph_matrix_init(&m, 1, 1)) { igraphmodule_handle_igraph_error(); return NULL; } if (dim == 2) ret = igraph_layout_grid(&self->g, &m, width); else ret = igraph_layout_grid_3d(&self->g, &m, width, height); if (ret != IGRAPH_SUCCESS) { igraphmodule_handle_igraph_error(); igraph_matrix_destroy(&m); return NULL; } result = igraphmodule_matrix_t_to_PyList(&m, IGRAPHMODULE_TYPE_FLOAT); igraph_matrix_destroy(&m); return (PyObject *) result; } /** \ingroup python_interface_graph * \brief Places the vertices in a star-like layout * \sa igraph_layout_star */ PyObject *igraphmodule_Graph_layout_star(igraphmodule_GraphObject* self, PyObject *args, PyObject *kwds) { static char *kwlist[] = { "center", "order", NULL }; igraph_matrix_t m; PyObject *result, *order_o = Py_None, *center_o = Py_None; igraph_integer_t center = 0; igraph_vector_t* order = 0; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OO", kwlist, ¢er_o, &order_o)) return NULL; if (igraph_matrix_init(&m, 1, 1)) { igraphmodule_handle_igraph_error(); return NULL; } if (igraphmodule_PyObject_to_vid(center_o, ¢er, &self->g)) return NULL; if (order_o != Py_None) { order = (igraph_vector_t*)calloc(1, sizeof(igraph_vector_t)); if (!order) { igraph_matrix_destroy(&m); PyErr_NoMemory(); return NULL; } if (igraphmodule_PyObject_to_vector_t(order_o, order, 1)) { igraph_matrix_destroy(&m); free(order); igraphmodule_handle_igraph_error(); return NULL; } } if (igraph_layout_star(&self->g, &m, center, order)) { if (order) { igraph_vector_destroy(order); free(order); } igraph_matrix_destroy(&m); igraphmodule_handle_igraph_error(); return NULL; } result = igraphmodule_matrix_t_to_PyList(&m, IGRAPHMODULE_TYPE_FLOAT); igraph_matrix_destroy(&m); return (PyObject *) result; } /** \ingroup python_interface_graph * \brief Places the vertices on a plane according to the Kamada-Kawai algorithm. * \return the calculated coordinates as a Python list of lists * \sa igraph_layout_kamada_kawai */ PyObject *igraphmodule_Graph_layout_kamada_kawai(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "maxiter", "epsilon", "kkconst", "seed", "minx", "maxx", "miny", "maxy", "minz", "maxz", "dim", NULL }; igraph_matrix_t m; igraph_bool_t use_seed=0; int ret; long int niter = 1000, dim = 2; double kkconst, epsilon = 0.0; PyObject *result, *seed_o=Py_None; PyObject *minx_o=Py_None, *maxx_o=Py_None; PyObject *miny_o=Py_None, *maxy_o=Py_None; PyObject *minz_o=Py_None, *maxz_o=Py_None; igraph_vector_t *minx=0, *maxx=0; igraph_vector_t *miny=0, *maxy=0; igraph_vector_t *minz=0, *maxz=0; #define DESTROY_VECTORS { \ if (minx) { igraph_vector_destroy(minx); free(minx); } \ if (maxx) { igraph_vector_destroy(maxx); free(maxx); } \ if (miny) { igraph_vector_destroy(miny); free(miny); } \ if (maxy) { igraph_vector_destroy(maxy); free(maxy); } \ if (minz) { igraph_vector_destroy(minz); free(minz); } \ if (maxz) { igraph_vector_destroy(maxz); free(maxz); } \ } kkconst = igraph_vcount(&self->g); if (!PyArg_ParseTupleAndKeywords(args, kwds, "|lddOOOOOOOl", kwlist, &niter, &epsilon, &kkconst, &seed_o, &minx_o, &maxx_o, &miny_o, &maxy_o, &minz_o, &maxz_o, &dim)) return NULL; if (dim != 2 && dim != 3) { PyErr_SetString(PyExc_ValueError, "number of dimensions must be either 2 or 3"); return NULL; } if (seed_o == 0 || seed_o == Py_None) { if (igraph_matrix_init(&m, 1, 1)) { igraphmodule_handle_igraph_error(); return NULL; } } else { use_seed=1; if (igraphmodule_PyList_to_matrix_t(seed_o, &m)) return NULL; } /* Convert minimum and maximum x-y-z values */ if (igraphmodule_attrib_to_vector_t(minx_o, self, &minx, ATTRIBUTE_TYPE_EDGE)) { igraph_matrix_destroy(&m); DESTROY_VECTORS; igraphmodule_handle_igraph_error(); return NULL; } if (igraphmodule_attrib_to_vector_t(maxx_o, self, &maxx, ATTRIBUTE_TYPE_EDGE)) { igraph_matrix_destroy(&m); DESTROY_VECTORS; igraphmodule_handle_igraph_error(); return NULL; } if (igraphmodule_attrib_to_vector_t(miny_o, self, &miny, ATTRIBUTE_TYPE_EDGE)) { igraph_matrix_destroy(&m); DESTROY_VECTORS; igraphmodule_handle_igraph_error(); return NULL; } if (igraphmodule_attrib_to_vector_t(maxy_o, self, &maxy, ATTRIBUTE_TYPE_EDGE)) { igraph_matrix_destroy(&m); DESTROY_VECTORS; igraphmodule_handle_igraph_error(); return NULL; } if (dim > 2) { if (igraphmodule_attrib_to_vector_t(minz_o, self, &minz, ATTRIBUTE_TYPE_EDGE)) { igraph_matrix_destroy(&m); DESTROY_VECTORS; igraphmodule_handle_igraph_error(); return NULL; } if (igraphmodule_attrib_to_vector_t(maxz_o, self, &maxz, ATTRIBUTE_TYPE_EDGE)) { igraph_matrix_destroy(&m); DESTROY_VECTORS; igraphmodule_handle_igraph_error(); return NULL; } } if (dim == 2) ret = igraph_layout_kamada_kawai (&self->g, &m, use_seed, (igraph_integer_t) niter, epsilon, kkconst, /*weights=*/ 0, /*bounds*/ minx, maxx, miny, maxy); else ret = igraph_layout_kamada_kawai_3d (&self->g, &m, use_seed, (igraph_integer_t) niter, epsilon, kkconst, /*weights=*/ 0, /*bounds*/ minx, maxx, miny, maxy, minz, maxz); DESTROY_VECTORS; #undef DESTROY_VECTORS if (ret) { igraph_matrix_destroy(&m); igraphmodule_handle_igraph_error(); return NULL; } result = igraphmodule_matrix_t_to_PyList(&m, IGRAPHMODULE_TYPE_FLOAT); igraph_matrix_destroy(&m); return (PyObject *) result; } /** \ingroup python_interface_graph * \brief Places the vertices on a plane according to the Davidson-Harel algorithm. * \return the calculated coordinates as a Python list of lists * \sa igraph_layout_davidson_harel */ PyObject* igraphmodule_Graph_layout_davidson_harel(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = { "seed", "maxiter", "fineiter", "cool_fact", "weight_node_dist", "weight_border", "weight_edge_lengths", "weight_edge_crossings", "weight_node_edge_dist", NULL }; igraph_matrix_t m; igraph_bool_t use_seed=0; long int maxiter=10; long int fineiter=-1; double cool_fact=0.75; double weight_node_dist=1.0; double weight_border=0.0; double weight_edge_lengths=-1; double weight_edge_crossings=-1; double weight_node_edge_dist=-1; igraph_real_t density; PyObject *result; PyObject *seed_o=Py_None; int retval; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|Olldddddd", kwlist, &seed_o, &maxiter, &fineiter, &cool_fact, &weight_node_dist, &weight_border, &weight_edge_lengths, &weight_edge_crossings, &weight_node_edge_dist)) return NULL; /* Provide default parameters based on the properties of the graph */ if (fineiter < 0) { fineiter = log(igraph_vcount(&self->g)) / log(2); if (fineiter > 10) { fineiter = 10; } } if (weight_edge_lengths < 0 || weight_edge_crossings < 0 || weight_node_edge_dist < 0) { if (igraph_density(&self->g, &density, 0)) { igraphmodule_handle_igraph_error(); return NULL; } if (weight_edge_lengths < 0) { weight_edge_lengths = density / 10.0; } if (weight_edge_crossings < 0) { weight_edge_crossings = 1.0 - sqrt(density); if (weight_edge_crossings < 0) { weight_edge_crossings = 0; } } if (weight_node_edge_dist < 0) { weight_node_edge_dist = 0.2 * (1 - density); if (weight_node_edge_dist < 0) { weight_node_edge_dist = 0; } } } /* Allocate result matrix if needed */ if (seed_o == 0 || seed_o == Py_None) { if (igraph_matrix_init(&m, 1, 1)) { igraphmodule_handle_igraph_error(); return NULL; } } else { if (igraphmodule_PyList_to_matrix_t(seed_o, &m)) { return NULL; } use_seed=1; } retval = igraph_layout_davidson_harel(&self->g, &m, use_seed, (igraph_integer_t) maxiter, (igraph_integer_t) fineiter, cool_fact, weight_node_dist, weight_border, weight_edge_lengths, weight_edge_crossings, weight_node_edge_dist); if (retval) { igraph_matrix_destroy(&m); igraphmodule_handle_igraph_error(); return NULL; } result = igraphmodule_matrix_t_to_PyList(&m, IGRAPHMODULE_TYPE_FLOAT); igraph_matrix_destroy(&m); return (PyObject *) result; } /** \ingroup python_interface_graph * \brief Places the vertices on a plane according to the DrL algorithm. * \return the calculated coordinates as a Python list of lists * \sa igraph_layout_drl */ PyObject* igraphmodule_Graph_layout_drl(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = { "weights", "seed", "fixed", "options", "dim", NULL }; igraph_matrix_t m; igraph_bool_t use_seed=0; igraph_vector_t *weights=0; igraph_vector_bool_t *fixed=0; igraph_layout_drl_options_t options; PyObject *result; PyObject *wobj=Py_None, *fixed_o=Py_None, *seed_o=Py_None, *options_o=Py_None; long dim = 2; int retval; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOOOl", kwlist, &wobj, &seed_o, &fixed_o, &options_o, &dim)) return NULL; if (dim != 2 && dim != 3) { PyErr_SetString(PyExc_ValueError, "number of dimensions must be either 2 or 3"); return NULL; } if (igraphmodule_PyObject_to_drl_options_t(options_o, &options)) return NULL; if (fixed_o != 0 && fixed_o != Py_None) { fixed = (igraph_vector_bool_t*)malloc(sizeof(igraph_vector_bool_t)); if (!fixed) { PyErr_NoMemory(); return NULL; } if (igraphmodule_PyObject_to_vector_bool_t(fixed_o, fixed)) { free(fixed); return NULL; } } if (seed_o == 0 || seed_o == Py_None) { if (igraph_matrix_init(&m, 1, 1)) { igraphmodule_handle_igraph_error(); if (fixed) { igraph_vector_bool_destroy(fixed); free(fixed); } return NULL; } } else { if (igraphmodule_PyList_to_matrix_t(seed_o, &m)) { if (fixed) { igraph_vector_bool_destroy(fixed); free(fixed); } return NULL; } use_seed=1; } /* Convert the weight parameter to a vector */ if (igraphmodule_attrib_to_vector_t(wobj, self, &weights, ATTRIBUTE_TYPE_EDGE)) { igraph_matrix_destroy(&m); if (fixed) { igraph_vector_bool_destroy(fixed); free(fixed); } igraphmodule_handle_igraph_error(); return NULL; } if (dim == 2) { retval = igraph_layout_drl(&self->g, &m, use_seed, &options, weights, fixed); } else { retval = igraph_layout_drl_3d(&self->g, &m, use_seed, &options, weights, fixed); } if (retval) { igraph_matrix_destroy(&m); if (weights) { igraph_vector_destroy(weights); free(weights); } if (fixed) { igraph_vector_bool_destroy(fixed); free(fixed); } igraphmodule_handle_igraph_error(); return NULL; } if (weights) { igraph_vector_destroy(weights); free(weights); } if (fixed) { igraph_vector_bool_destroy(fixed); free(fixed); } result = igraphmodule_matrix_t_to_PyList(&m, IGRAPHMODULE_TYPE_FLOAT); igraph_matrix_destroy(&m); return (PyObject *) result; } /** \ingroup python_interface_graph * \brief Places the vertices on a plane according to the Fruchterman-Reingold algorithm. * \return the calculated coordinates as a Python list of lists * \sa igraph_layout_fruchterman_reingold */ PyObject *igraphmodule_Graph_layout_fruchterman_reingold(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "weights", "niter", "start_temp", "seed", "minx", "maxx", "miny", "maxy", "minz", "maxz", "dim", "grid", NULL }; igraph_matrix_t m; igraph_bool_t use_seed=0; igraph_vector_t *weights=0; igraph_vector_t *minx=0, *maxx=0; igraph_vector_t *miny=0, *maxy=0; igraph_vector_t *minz=0, *maxz=0; igraph_layout_grid_t grid = IGRAPH_LAYOUT_AUTOGRID; int ret; long int niter = 500, dim = 2; double start_temp; PyObject *result; PyObject *wobj=Py_None, *seed_o=Py_None; PyObject *minx_o=Py_None, *maxx_o=Py_None; PyObject *miny_o=Py_None, *maxy_o=Py_None; PyObject *minz_o=Py_None, *maxz_o=Py_None; PyObject *grid_o=Py_None; #define DESTROY_VECTORS { \ if (weights) { igraph_vector_destroy(weights); free(weights); } \ if (minx) { igraph_vector_destroy(minx); free(minx); } \ if (maxx) { igraph_vector_destroy(maxx); free(maxx); } \ if (miny) { igraph_vector_destroy(miny); free(miny); } \ if (maxy) { igraph_vector_destroy(maxy); free(maxy); } \ if (minz) { igraph_vector_destroy(minz); free(minz); } \ if (maxz) { igraph_vector_destroy(maxz); free(maxz); } \ } start_temp = sqrt(igraph_vcount(&self->g)) / 10.0; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OldOOOOOOOlO", kwlist, &wobj, &niter, &start_temp, &seed_o, &minx_o, &maxx_o, &miny_o, &maxy_o, &minz_o, &maxz_o, &dim, &grid_o)) return NULL; if (dim != 2 && dim != 3) { PyErr_SetString(PyExc_ValueError, "number of dimensions must be either 2 or 3"); return NULL; } if (igraphmodule_PyObject_to_layout_grid_t(grid_o, &grid)) { return NULL; } if (seed_o == 0 || seed_o == Py_None) { if (igraph_matrix_init(&m, 1, 1)) { igraphmodule_handle_igraph_error(); return NULL; } } else { if (igraphmodule_PyList_to_matrix_t(seed_o, &m)) return NULL; use_seed=1; } /* Convert the weight parameter to a vector */ if (igraphmodule_attrib_to_vector_t(wobj, self, &weights, ATTRIBUTE_TYPE_EDGE)) { igraph_matrix_destroy(&m); igraphmodule_handle_igraph_error(); return NULL; } /* Convert minimum and maximum x-y-z values */ if (igraphmodule_attrib_to_vector_t(minx_o, self, &minx, ATTRIBUTE_TYPE_EDGE)) { igraph_matrix_destroy(&m); DESTROY_VECTORS; igraphmodule_handle_igraph_error(); return NULL; } if (igraphmodule_attrib_to_vector_t(maxx_o, self, &maxx, ATTRIBUTE_TYPE_EDGE)) { igraph_matrix_destroy(&m); DESTROY_VECTORS; igraphmodule_handle_igraph_error(); return NULL; } if (igraphmodule_attrib_to_vector_t(miny_o, self, &miny, ATTRIBUTE_TYPE_EDGE)) { igraph_matrix_destroy(&m); DESTROY_VECTORS; igraphmodule_handle_igraph_error(); return NULL; } if (igraphmodule_attrib_to_vector_t(maxy_o, self, &maxy, ATTRIBUTE_TYPE_EDGE)) { igraph_matrix_destroy(&m); DESTROY_VECTORS; igraphmodule_handle_igraph_error(); return NULL; } if (dim > 2) { if (igraphmodule_attrib_to_vector_t(minz_o, self, &minz, ATTRIBUTE_TYPE_EDGE)) { igraph_matrix_destroy(&m); DESTROY_VECTORS; igraphmodule_handle_igraph_error(); return NULL; } if (igraphmodule_attrib_to_vector_t(maxz_o, self, &maxz, ATTRIBUTE_TYPE_EDGE)) { igraph_matrix_destroy(&m); DESTROY_VECTORS; igraphmodule_handle_igraph_error(); return NULL; } } if (dim == 2) { ret = igraph_layout_fruchterman_reingold (&self->g, &m, use_seed, (igraph_integer_t) niter, start_temp, grid, weights, minx, maxx, miny, maxy); } else { ret = igraph_layout_fruchterman_reingold_3d (&self->g, &m, use_seed, (igraph_integer_t) niter, start_temp, weights, minx, maxx, miny, maxy, minz, maxz); } DESTROY_VECTORS; if (ret) { igraph_matrix_destroy(&m); igraphmodule_handle_igraph_error(); return NULL; } #undef DESTROY_VECTORS result = igraphmodule_matrix_t_to_PyList(&m, IGRAPHMODULE_TYPE_FLOAT); igraph_matrix_destroy(&m); return (PyObject *) result; } /** \ingroup python_interface_graph * \brief Places the vertices on a plane according to the layout algorithm in * graphopt 0.4.1 * \return the calculated coordinates as a Python list of lists * \sa igraph_layout_graphopt */ PyObject *igraphmodule_Graph_layout_graphopt(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = { "niter", "node_charge", "node_mass", "spring_length", "spring_constant", "max_sa_movement", "seed", NULL }; igraph_matrix_t m; long int niter = 500; double node_charge = 0.001, node_mass = 30; long spring_length = 0; double spring_constant = 1, max_sa_movement = 5; PyObject *result, *seed_o = Py_None; igraph_bool_t use_seed=0; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|lddlddO", kwlist, &niter, &node_charge, &node_mass, &spring_length, &spring_constant, &max_sa_movement, &seed_o)) return NULL; if (seed_o == 0 || seed_o == Py_None) { if (igraph_matrix_init(&m, 1, 1)) { igraphmodule_handle_igraph_error(); return NULL; } } else { use_seed=1; if (igraphmodule_PyList_to_matrix_t(seed_o, &m)) return NULL; } if (igraph_layout_graphopt(&self->g, &m, (igraph_integer_t) niter, node_charge, node_mass, spring_length, spring_constant, max_sa_movement, use_seed)) { igraph_matrix_destroy(&m); igraphmodule_handle_igraph_error(); return NULL; } result = igraphmodule_matrix_t_to_PyList(&m, IGRAPHMODULE_TYPE_FLOAT); igraph_matrix_destroy(&m); return (PyObject *) result; } /** \ingroup python_interface_graph * \brief Places the vertices of a graph according to the Large Graph Layout * \return the calculated coordinates as a Python list of lists * \sa igraph_layout_lgl */ PyObject *igraphmodule_Graph_layout_lgl(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "maxiter", "maxdelta", "area", "coolexp", "repulserad", "cellsize", "root", NULL }; igraph_matrix_t m; PyObject *result, *root_o = Py_None; long int maxiter = 150; igraph_integer_t proot = -1; double maxdelta, area, coolexp, repulserad, cellsize; maxdelta = igraph_vcount(&self->g); area = -1; coolexp = 1.5; repulserad = -1; cellsize = -1; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|ldddddO", kwlist, &maxiter, &maxdelta, &area, &coolexp, &repulserad, &cellsize, &root_o)) return NULL; if (area <= 0) area = igraph_vcount(&self->g)*igraph_vcount(&self->g); if (repulserad <= 0) repulserad = area*igraph_vcount(&self->g); if (cellsize <= 0) cellsize = sqrt(sqrt(area)); if (igraphmodule_PyObject_to_vid(root_o, &proot, &self->g)) return NULL; if (igraph_matrix_init(&m, 1, 1)) { igraphmodule_handle_igraph_error(); return NULL; } if (igraph_layout_lgl(&self->g, &m, (igraph_integer_t) maxiter, maxdelta, area, coolexp, repulserad, cellsize, proot)) { igraph_matrix_destroy(&m); igraphmodule_handle_igraph_error(); return NULL; } result = igraphmodule_matrix_t_to_PyList(&m, IGRAPHMODULE_TYPE_FLOAT); igraph_matrix_destroy(&m); return (PyObject *) result; } /** \ingroup python_interface_graph * \brief Places the vertices of a graph using multidimensional scaling * \return the calculated coordinates as a Python list of lists * \sa igraph_layout_mds */ PyObject *igraphmodule_Graph_layout_mds(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "dist", "dim", "arpack_options", NULL }; igraph_matrix_t m; igraph_matrix_t *dist = 0; long int dim = 2; igraphmodule_ARPACKOptionsObject *arpack_options; PyObject *dist_o = Py_None; PyObject *arpack_options_o = igraphmodule_arpack_options_default; PyObject *result; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OlO!", kwlist, &dist_o, &dim, &igraphmodule_ARPACKOptionsType, &arpack_options_o)) return NULL; if (dist_o != Py_None) { dist = (igraph_matrix_t*)malloc(sizeof(igraph_matrix_t)); if (!dist) { PyErr_NoMemory(); return NULL; } if (igraphmodule_PyList_to_matrix_t(dist_o, dist)) { free(dist); return NULL; } } if (igraph_matrix_init(&m, 1, 1)) { if (dist) { igraph_matrix_destroy(dist); free(dist); } igraphmodule_handle_igraph_error(); return NULL; } arpack_options = (igraphmodule_ARPACKOptionsObject*)arpack_options_o; if (igraph_layout_mds(&self->g, &m, dist, dim, igraphmodule_ARPACKOptions_get(arpack_options))) { if (dist) { igraph_matrix_destroy(dist); free(dist); } igraph_matrix_destroy(&m); igraphmodule_handle_igraph_error(); return NULL; } if (dist) { igraph_matrix_destroy(dist); free(dist); } result = igraphmodule_matrix_t_to_PyList(&m, IGRAPHMODULE_TYPE_FLOAT); igraph_matrix_destroy(&m); return (PyObject *) result; } /** \ingroup python_interface_graph * \brief Places the vertices of a graph according to the Reingold-Tilford * tree layout algorithm * \return the calculated coordinates as a Python list of lists * \sa igraph_layout_reingold_tilford */ PyObject *igraphmodule_Graph_layout_reingold_tilford(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "mode", "root", "rootlevel", NULL }; igraph_matrix_t m; igraph_vector_t roots, *roots_p = 0; igraph_vector_t rootlevels, *rootlevels_p = 0; PyObject *roots_o=Py_None, *rootlevels_o=Py_None, *mode_o=Py_None; igraph_neimode_t mode = IGRAPH_OUT; PyObject *result; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOO", kwlist, &mode_o, &roots_o, &rootlevels_o)) return NULL; if (igraphmodule_PyObject_to_neimode_t(mode_o, &mode)) return NULL; if (roots_o != Py_None) { roots_p = &roots; if (igraphmodule_PyObject_to_vector_t(roots_o, roots_p, 1)) return 0; } if (rootlevels_o != Py_None) { rootlevels_p = &rootlevels; if (igraphmodule_PyObject_to_vector_t(rootlevels_o, rootlevels_p, 1)) { if (roots_p) igraph_vector_destroy(roots_p); return 0; } } if (igraph_matrix_init(&m, 1, 1)) { if (roots_p) igraph_vector_destroy(roots_p); if (rootlevels_p) igraph_vector_destroy(rootlevels_p); igraphmodule_handle_igraph_error(); return NULL; } if (igraph_layout_reingold_tilford(&self->g, &m, mode, roots_p, rootlevels_p)) { igraph_matrix_destroy(&m); if (roots_p) igraph_vector_destroy(roots_p); if (rootlevels_p) igraph_vector_destroy(rootlevels_p); igraphmodule_handle_igraph_error(); return NULL; } if (roots_p) igraph_vector_destroy(roots_p); if (rootlevels_p) igraph_vector_destroy(rootlevels_p); result = igraphmodule_matrix_t_to_PyList(&m, IGRAPHMODULE_TYPE_FLOAT); igraph_matrix_destroy(&m); return (PyObject *) result; } /** \ingroup python_interface_graph * \brief Places the vertices of a graph according to the Reingold-Tilford * tree layout algorithm in a polar coordinate system * \return the calculated coordinates as a Python list of lists * \sa igraph_layout_reingold_tilford */ PyObject *igraphmodule_Graph_layout_reingold_tilford_circular( igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "mode", "root", "rootlevel", NULL }; igraph_matrix_t m; igraph_vector_t roots, *roots_p = 0; igraph_vector_t rootlevels, *rootlevels_p = 0; PyObject *roots_o=Py_None, *rootlevels_o=Py_None, *mode_o=Py_None; igraph_neimode_t mode = IGRAPH_OUT; PyObject *result; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOO", kwlist, &mode_o, &roots_o, &rootlevels_o)) return NULL; if (igraphmodule_PyObject_to_neimode_t(mode_o, &mode)) return NULL; if (roots_o != Py_None) { roots_p = &roots; if (igraphmodule_PyObject_to_vector_t(roots_o, roots_p, 1)) return 0; } if (rootlevels_o != Py_None) { rootlevels_p = &rootlevels; if (igraphmodule_PyObject_to_vector_t(rootlevels_o, rootlevels_p, 1)) { if (roots_p) igraph_vector_destroy(roots_p); return 0; } } if (igraph_matrix_init(&m, 1, 1)) { if (roots_p) igraph_vector_destroy(roots_p); if (rootlevels_p) igraph_vector_destroy(rootlevels_p); igraphmodule_handle_igraph_error(); return NULL; } if (igraph_layout_reingold_tilford_circular(&self->g, &m, mode, roots_p, rootlevels_p)) { igraph_matrix_destroy(&m); if (roots_p) igraph_vector_destroy(roots_p); if (rootlevels_p) igraph_vector_destroy(rootlevels_p); igraphmodule_handle_igraph_error(); return NULL; } if (roots_p) igraph_vector_destroy(roots_p); if (rootlevels_p) igraph_vector_destroy(rootlevels_p); result = igraphmodule_matrix_t_to_PyList(&m, IGRAPHMODULE_TYPE_FLOAT); igraph_matrix_destroy(&m); return (PyObject *) result; } /** \ingroup python_interface_graph * \brief Places the vertices of a graph according to the Sugiyama layout. * \return the calculated coordinates as a Python list of lists * \sa igraph_layout_sugiyama */ PyObject *igraphmodule_Graph_layout_sugiyama( igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "layers", "weights", "hgap", "vgap", "maxiter", "return_extended_graph", NULL }; igraph_matrix_t m; igraph_t extd_graph; igraph_vector_t extd_to_orig_eids; igraph_vector_t *weights = 0, *layers = 0; double hgap = 1, vgap = 1; long int maxiter = 100; PyObject *layers_o = Py_None, *weights_o = Py_None, *extd_to_orig_eids_o = Py_None; PyObject *return_extended_graph = Py_False; PyObject *result; igraphmodule_GraphObject *graph_o; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOddlO", kwlist, &layers_o, &weights_o, &hgap, &vgap, &maxiter, &return_extended_graph)) return NULL; if (igraph_vector_init(&extd_to_orig_eids, 0)) { igraphmodule_handle_igraph_error(); return NULL; } if (igraph_matrix_init(&m, 1, 1)) { igraph_vector_destroy(&extd_to_orig_eids); igraphmodule_handle_igraph_error(); return NULL; } if (igraphmodule_attrib_to_vector_t(layers_o, self, &layers, ATTRIBUTE_TYPE_VERTEX)) { igraph_vector_destroy(&extd_to_orig_eids); igraph_matrix_destroy(&m); return NULL; } if (igraphmodule_attrib_to_vector_t(weights_o, self, &weights, ATTRIBUTE_TYPE_EDGE)) { if (layers != 0) { igraph_vector_destroy(layers); free(layers); } igraph_vector_destroy(&extd_to_orig_eids); igraph_matrix_destroy(&m); return NULL; } if (igraph_layout_sugiyama(&self->g, &m, (PyObject_IsTrue(return_extended_graph) ? &extd_graph : 0), (PyObject_IsTrue(return_extended_graph) ? &extd_to_orig_eids : 0), layers, hgap, vgap, maxiter, weights)) { if (layers != 0) { igraph_vector_destroy(layers); free(layers); } if (weights != 0) { igraph_vector_destroy(weights); free(weights); } igraph_vector_destroy(&extd_to_orig_eids); igraph_matrix_destroy(&m); igraphmodule_handle_igraph_error(); return NULL; } if (layers != 0) { igraph_vector_destroy(layers); free(layers); } if (weights != 0) { igraph_vector_destroy(weights); free(weights); } result = igraphmodule_matrix_t_to_PyList(&m, IGRAPHMODULE_TYPE_FLOAT); igraph_matrix_destroy(&m); if (PyObject_IsTrue(return_extended_graph)) { CREATE_GRAPH(graph_o, extd_graph); extd_to_orig_eids_o = igraphmodule_vector_t_to_PyList(&extd_to_orig_eids, IGRAPHMODULE_TYPE_INT); result = Py_BuildValue("NNN", result, graph_o, extd_to_orig_eids_o); } igraph_vector_destroy(&extd_to_orig_eids); return (PyObject *) result; } /** \ingroup python_interface_graph * \brief Places the vertices of a bipartite graph according to a simple two-layer * Sugiyama layout. * \return the calculated coordinates as a Python list of lists * \sa igraph_layout_bipartite */ PyObject *igraphmodule_Graph_layout_bipartite( igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "types", "hgap", "vgap", "maxiter", NULL }; igraph_matrix_t m; igraph_vector_bool_t *types = 0; double hgap = 1, vgap = 1; long int maxiter = 100; PyObject *types_o = Py_None; PyObject *result; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|Oddl", kwlist, &types_o, &hgap, &vgap, &maxiter)) return NULL; if (igraph_matrix_init(&m, 1, 1)) { igraphmodule_handle_igraph_error(); return NULL; } if (types_o == Py_None) { types_o = PyString_FromString("type"); } else { Py_INCREF(types_o); } if (igraphmodule_attrib_to_vector_bool_t(types_o, self, &types, ATTRIBUTE_TYPE_VERTEX)) { igraph_matrix_destroy(&m); Py_DECREF(types_o); return NULL; } Py_DECREF(types_o); if (igraph_layout_bipartite(&self->g, types, &m, hgap, vgap, maxiter)) { if (types != 0) { igraph_vector_bool_destroy(types); free(types); } igraph_matrix_destroy(&m); igraphmodule_handle_igraph_error(); return NULL; } if (types != 0) { igraph_vector_bool_destroy(types); free(types); } result = igraphmodule_matrix_t_to_PyList(&m, IGRAPHMODULE_TYPE_FLOAT); igraph_matrix_destroy(&m); return (PyObject *) result; } /********************************************************************** * Conversion between various graph representations * **********************************************************************/ /** \ingroup python_interface_graph * \brief Returns the adjacency matrix of a graph. * \return the adjacency matrix as a Python list of lists * \sa igraph_get_adjacency */ PyObject *igraphmodule_Graph_get_adjacency(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "type", "eids", NULL }; igraph_get_adjacency_t t = IGRAPH_GET_ADJACENCY_BOTH; igraph_matrix_t m; PyObject *result, *eids = Py_False; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|iO", kwlist, &t, &eids)) return NULL; if (t != IGRAPH_GET_ADJACENCY_UPPER && t != IGRAPH_GET_ADJACENCY_LOWER && t != IGRAPH_GET_ADJACENCY_BOTH) { PyErr_SetString(PyExc_ValueError, "type must be either GET_ADJACENCY_LOWER or GET_ADJACENCY_UPPER or GET_ADJACENCY_BOTH"); return NULL; } if (igraph_matrix_init (&m, igraph_vcount(&self->g), igraph_vcount(&self->g))) { igraphmodule_handle_igraph_error(); return NULL; } if (igraph_get_adjacency(&self->g, &m, t, PyObject_IsTrue(eids))) { igraphmodule_handle_igraph_error(); igraph_matrix_destroy(&m); return NULL; } result = igraphmodule_matrix_t_to_PyList(&m, IGRAPHMODULE_TYPE_INT); igraph_matrix_destroy(&m); return result; } /** \ingroup python_interface_graph * \brief Returns the incidence matrix of a bipartite graph. * \return the incidence matrix as a Python list of lists * \sa igraph_get_incidence */ PyObject *igraphmodule_Graph_get_incidence(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "types", NULL }; igraph_matrix_t matrix; igraph_vector_t row_ids, col_ids; igraph_vector_bool_t *types; PyObject *matrix_o, *row_ids_o, *col_ids_o, *types_o; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O", kwlist, &types_o)) return NULL; if (igraph_vector_init(&row_ids, 0)) return NULL; if (igraph_vector_init(&col_ids, 0)) { igraph_vector_destroy(&row_ids); return NULL; } if (igraphmodule_attrib_to_vector_bool_t(types_o, self, &types, ATTRIBUTE_TYPE_VERTEX)) { igraph_vector_destroy(&row_ids); igraph_vector_destroy(&col_ids); return NULL; } if (igraph_matrix_init(&matrix, 1, 1)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&row_ids); igraph_vector_destroy(&col_ids); if (types) { igraph_vector_bool_destroy(types); free(types); } return NULL; } if (igraph_get_incidence(&self->g, types, &matrix, &row_ids, &col_ids)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&row_ids); igraph_vector_destroy(&col_ids); if (types) { igraph_vector_bool_destroy(types); free(types); } igraph_matrix_destroy(&matrix); return NULL; } if (types) { igraph_vector_bool_destroy(types); free(types); } matrix_o = igraphmodule_matrix_t_to_PyList(&matrix, IGRAPHMODULE_TYPE_INT); igraph_matrix_destroy(&matrix); row_ids_o = igraphmodule_vector_t_to_PyList(&row_ids, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&row_ids); col_ids_o = igraphmodule_vector_t_to_PyList(&col_ids, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&col_ids); return Py_BuildValue("NNN", matrix_o, row_ids_o, col_ids_o); } /** \ingroup python_interface_graph * \brief Returns the Laplacian matrix of a graph. * \return the Laplacian matrix as a Python list of lists * \sa igraph_laplacian */ PyObject *igraphmodule_Graph_laplacian(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "weights", "normalized", NULL }; igraph_matrix_t m; PyObject *result; PyObject *weights_o = Py_None; PyObject *normalized = Py_False; igraph_vector_t *weights = 0; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OO", kwlist, &weights_o, &normalized)) return NULL; if (igraphmodule_attrib_to_vector_t(weights_o, self, &weights, ATTRIBUTE_TYPE_EDGE)) return NULL; if (igraph_matrix_init (&m, igraph_vcount(&self->g), igraph_vcount(&self->g))) { igraphmodule_handle_igraph_error(); if (weights) { igraph_vector_destroy(weights); free(weights); } return NULL; } if (igraph_laplacian(&self->g, &m, /*sparseres=*/ 0, PyObject_IsTrue(normalized), weights)) { igraphmodule_handle_igraph_error(); if (weights) { igraph_vector_destroy(weights); free(weights); } igraph_matrix_destroy(&m); return NULL; } if (PyObject_IsTrue(normalized) || weights) { result = igraphmodule_matrix_t_to_PyList(&m, IGRAPHMODULE_TYPE_FLOAT); } else { result = igraphmodule_matrix_t_to_PyList(&m, IGRAPHMODULE_TYPE_INT); } if (weights) { igraph_vector_destroy(weights); free(weights); } igraph_matrix_destroy(&m); return result; } /** \ingroup python_interface_graph * \brief Returns the list of edges in a graph. * \return the list of edges, every edge is represented by a pair * \sa igraph_get_edgelist */ PyObject *igraphmodule_Graph_get_edgelist(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { igraph_vector_t edgelist; PyObject *result; igraph_vector_init(&edgelist, igraph_ecount(&self->g)); if (igraph_get_edgelist(&self->g, &edgelist, 0)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&edgelist); return NULL; } result = igraphmodule_vector_t_to_PyList_pairs(&edgelist); igraph_vector_destroy(&edgelist); return (PyObject *) result; } /** \ingroup python_interface_graph * \function igraphmodule_Graph_to_undirected * \brief Converts a directed graph to an undirected one. * \return The undirected graph. * \sa igraph_to_undirected */ PyObject *igraphmodule_Graph_to_undirected(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { PyObject *mode_o = Py_None, *comb_o = Py_None; igraph_to_undirected_t mode = IGRAPH_TO_UNDIRECTED_COLLAPSE; igraph_attribute_combination_t comb; static char *kwlist[] = { "mode", "combine_edges", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OO", kwlist, &mode_o, &comb_o)) return NULL; if (igraphmodule_PyObject_to_to_undirected_t(mode_o, &mode)) return NULL; if (igraphmodule_PyObject_to_attribute_combination_t(comb_o, &comb)) return NULL; if (igraph_to_undirected(&self->g, mode, &comb)) { igraph_attribute_combination_destroy(&comb); igraphmodule_handle_igraph_error(); return NULL; } igraph_attribute_combination_destroy(&comb); Py_RETURN_NONE; } /** \ingroup python_interface_graph * \function igraphmodule_Graph_to_directed * \brief Converts an undirected graph to a directed one. * \return The directed graph. * \sa igraph_to_directed */ PyObject *igraphmodule_Graph_to_directed(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { PyObject *mutual = Py_True; igraph_to_directed_t mode = IGRAPH_TO_DIRECTED_MUTUAL; static char *kwlist[] = { "mutual", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O", kwlist, &mutual)) return NULL; mode = (PyObject_IsTrue(mutual) ? IGRAPH_TO_DIRECTED_MUTUAL : IGRAPH_TO_DIRECTED_ARBITRARY); if (igraph_to_directed(&self->g, mode)) { igraphmodule_handle_igraph_error(); return NULL; } Py_RETURN_NONE; } /********************************************************************** * Reading/writing foreing graph formats * **********************************************************************/ /** \ingroup python_interface_graph * \brief Reads a DIMACS file and creates a graph from it. * \return the graph * \sa igraph_read_graph_dimacs */ PyObject *igraphmodule_Graph_Read_DIMACS(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; igraphmodule_filehandle_t fobj; igraph_integer_t source = 0, target = 0; igraph_vector_t capacity; igraph_t g; PyObject *fname = NULL, *directed = Py_False, *capacity_obj; static char *kwlist[] = { "f", "directed", NULL }; if (!PyArg_ParseTupleAndKeywords (args, kwds, "O|O", kwlist, &fname, &directed)) return NULL; if (igraphmodule_filehandle_init(&fobj, fname, "r")) return NULL; if (igraph_vector_init(&capacity, 0)) { igraphmodule_handle_igraph_error(); igraphmodule_filehandle_destroy(&fobj); return NULL; } if (igraph_read_graph_dimacs(&g, igraphmodule_filehandle_get(&fobj), 0, 0, &source, &target, &capacity, PyObject_IsTrue(directed))) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&capacity); igraphmodule_filehandle_destroy(&fobj); return NULL; } igraphmodule_filehandle_destroy(&fobj); capacity_obj = igraphmodule_vector_t_to_PyList(&capacity, IGRAPHMODULE_TYPE_FLOAT); igraph_vector_destroy(&capacity); if (!capacity_obj) return NULL; CREATE_GRAPH_FROM_TYPE(self, g, type); return Py_BuildValue("NiiN", (PyObject *) self, (long)source, (long)target, capacity_obj); } /** \ingroup python_interface_graph * \brief Reads an UCINET DL file and creates a graph from it. * \return the graph * \sa igraph_read_graph_dl */ PyObject *igraphmodule_Graph_Read_DL(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; igraph_t g; igraphmodule_filehandle_t fobj; PyObject *fname = NULL, *directed = Py_True; static char *kwlist[] = { "f", "directed", NULL }; if (!PyArg_ParseTupleAndKeywords (args, kwds, "O|O", kwlist, &fname, &directed)) return NULL; if (igraphmodule_filehandle_init(&fobj, fname, "r")) return NULL; if (igraph_read_graph_dl(&g, igraphmodule_filehandle_get(&fobj), PyObject_IsTrue(directed))) { igraphmodule_handle_igraph_error(); igraphmodule_filehandle_destroy(&fobj); return NULL; } igraphmodule_filehandle_destroy(&fobj); CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject*)self; } /** \ingroup python_interface_graph * \brief Reads an edge list from a file and creates a graph from it. * \return the graph * \sa igraph_read_graph_edgelist */ PyObject *igraphmodule_Graph_Read_Edgelist(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; PyObject *directed = Py_True, *fname = NULL; igraphmodule_filehandle_t fobj; igraph_t g; static char *kwlist[] = { "f", "directed", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|O", kwlist, &fname, &directed)) return NULL; if (igraphmodule_filehandle_init(&fobj, fname, "r")) return NULL; if (igraph_read_graph_edgelist(&g, igraphmodule_filehandle_get(&fobj), 0, PyObject_IsTrue(directed))) { igraphmodule_handle_igraph_error(); igraphmodule_filehandle_destroy(&fobj); return NULL; } igraphmodule_filehandle_destroy(&fobj); CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Reads an edge list from an NCOL file and creates a graph from it. * \return the graph * \sa igraph_read_graph_ncol */ PyObject *igraphmodule_Graph_Read_Ncol(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; PyObject *names = Py_True, *weights = Py_None, *directed = Py_True; PyObject *fname = NULL; igraphmodule_filehandle_t fobj; igraph_add_weights_t add_weights = IGRAPH_ADD_WEIGHTS_IF_PRESENT; igraph_t g; static char *kwlist[] = { "f", "names", "weights", "directed", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|OOO", kwlist, &fname, &names, &weights, &directed)) return NULL; if (igraphmodule_PyObject_to_add_weights_t(weights, &add_weights)) return NULL; if (igraphmodule_filehandle_init(&fobj, fname, "r")) return NULL; if (igraph_read_graph_ncol(&g, igraphmodule_filehandle_get(&fobj), 0, PyObject_IsTrue(names), add_weights, PyObject_IsTrue(directed))) { igraphmodule_handle_igraph_error(); igraphmodule_filehandle_destroy(&fobj); return NULL; } igraphmodule_filehandle_destroy(&fobj); CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Reads an edge list from an LGL file and creates a graph from it. * \return the graph * \sa igraph_read_graph_lgl */ PyObject *igraphmodule_Graph_Read_Lgl(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; PyObject *names = Py_True, *weights = Py_None, *directed = Py_True; PyObject *fname = NULL; igraphmodule_filehandle_t fobj; igraph_add_weights_t add_weights = IGRAPH_ADD_WEIGHTS_IF_PRESENT; igraph_t g; static char *kwlist[] = { "f", "names", "weights", "directed", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|OOO", kwlist, &fname, &names, &weights, &directed)) return NULL; if (igraphmodule_PyObject_to_add_weights_t(weights, &add_weights)) return NULL; if (kwds && PyDict_Check(kwds) && \ PyDict_GetItemString(kwds, "directed") == NULL) { if (PyErr_Occurred()) return NULL; } if (igraphmodule_filehandle_init(&fobj, fname, "r")) return NULL; if (igraph_read_graph_lgl(&g, igraphmodule_filehandle_get(&fobj), PyObject_IsTrue(names), add_weights, PyObject_IsTrue(directed))) { igraphmodule_handle_igraph_error(); igraphmodule_filehandle_destroy(&fobj); return NULL; } igraphmodule_filehandle_destroy(&fobj); CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Reads an edge list from a Pajek file and creates a graph from it. * \return the graph * \sa igraph_read_graph_pajek */ PyObject *igraphmodule_Graph_Read_Pajek(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; PyObject *fname = NULL; igraphmodule_filehandle_t fobj; igraph_t g; static char *kwlist[] = { "f", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O", kwlist, &fname)) return NULL; if (igraphmodule_filehandle_init(&fobj, fname, "r")) return NULL; if (igraph_read_graph_pajek(&g, igraphmodule_filehandle_get(&fobj))) { igraphmodule_handle_igraph_error(); igraphmodule_filehandle_destroy(&fobj); return NULL; } igraphmodule_filehandle_destroy(&fobj); CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Reads a GML file and creates a graph from it. * \return the graph * \sa igraph_read_graph_gml */ PyObject *igraphmodule_Graph_Read_GML(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; PyObject *fname = NULL; igraphmodule_filehandle_t fobj; igraph_t g; static char *kwlist[] = { "f", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O", kwlist, &fname)) return NULL; if (igraphmodule_filehandle_init(&fobj, fname, "r")) return NULL; if (igraph_read_graph_gml(&g, igraphmodule_filehandle_get(&fobj))) { igraphmodule_handle_igraph_error(); igraphmodule_filehandle_destroy(&fobj); return NULL; } igraphmodule_filehandle_destroy(&fobj); CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Reads a GraphDB file and creates a graph from it. * \return the graph * \sa igraph_read_graph_graphdb */ PyObject *igraphmodule_Graph_Read_GraphDB(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; PyObject *fname = NULL, *directed_o = Py_False; igraph_t g; igraphmodule_filehandle_t fobj; static char *kwlist[] = { "f", "directed", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|O", kwlist, &fname, &directed_o)) return NULL; if (igraphmodule_filehandle_init(&fobj, fname, "r")) return NULL; if (igraph_read_graph_graphdb(&g, igraphmodule_filehandle_get(&fobj), PyObject_IsTrue(directed_o))) { igraphmodule_handle_igraph_error(); igraphmodule_filehandle_destroy(&fobj); return NULL; } igraphmodule_filehandle_destroy(&fobj); CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Reads a GraphML file and creates a graph from it. * \return the graph * \sa igraph_read_graph_graphml */ PyObject *igraphmodule_Graph_Read_GraphML(PyTypeObject * type, PyObject * args, PyObject * kwds) { igraphmodule_GraphObject *self; PyObject *fname = NULL; long int index = 0; igraph_t g; igraphmodule_filehandle_t fobj; static char *kwlist[] = { "f", "index", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|l", kwlist, &fname, &index)) return NULL; if (igraphmodule_filehandle_init(&fobj, fname, "r")) return NULL; if (igraph_read_graph_graphml(&g, igraphmodule_filehandle_get(&fobj), (igraph_integer_t) index)) { igraphmodule_handle_igraph_error(); igraphmodule_filehandle_destroy(&fobj); return NULL; } igraphmodule_filehandle_destroy(&fobj); CREATE_GRAPH_FROM_TYPE(self, g, type); return (PyObject *) self; } /** \ingroup python_interface_graph * \brief Writes the graph as a DIMACS file * \return none * \sa igraph_write_graph_dimacs */ PyObject *igraphmodule_Graph_write_dimacs(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { long source = 0, target = 0; PyObject *capacity_obj = Py_None, *fname = NULL; igraphmodule_filehandle_t fobj; igraph_vector_t* capacity = 0; static char *kwlist[] = { "f", "source", "target", "capacity", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "Oll|O", kwlist, &fname, &source, &target, &capacity_obj)) return NULL; if (igraphmodule_filehandle_init(&fobj, fname, "w")) return NULL; if (capacity_obj == Py_None) { capacity_obj = PyString_FromString("capacity"); } else { Py_INCREF(capacity_obj); } if (igraphmodule_attrib_to_vector_t(capacity_obj, self, &capacity, ATTRIBUTE_TYPE_EDGE)) { igraphmodule_filehandle_destroy(&fobj); Py_DECREF(capacity_obj); return NULL; } Py_DECREF(capacity_obj); if (igraph_write_graph_dimacs(&self->g, igraphmodule_filehandle_get(&fobj), source, target, capacity)) { igraphmodule_handle_igraph_error(); if (capacity) { igraph_vector_destroy(capacity); free(capacity); } igraphmodule_filehandle_destroy(&fobj); return NULL; } if (capacity) { igraph_vector_destroy(capacity); free(capacity); } igraphmodule_filehandle_destroy(&fobj); Py_RETURN_NONE; } /** \ingroup python_interface_graph * \brief Writes the graph as a DOT (GraphViz) file * \return none * \sa igraph_write_graph_dot */ PyObject *igraphmodule_Graph_write_dot(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { PyObject *fname = NULL; igraphmodule_filehandle_t fobj; static char *kwlist[] = { "f", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O", kwlist, &fname)) return NULL; if (igraphmodule_filehandle_init(&fobj, fname, "w")) return NULL; if (igraph_write_graph_dot(&self->g, igraphmodule_filehandle_get(&fobj))) { igraphmodule_handle_igraph_error(); igraphmodule_filehandle_destroy(&fobj); return NULL; } igraphmodule_filehandle_destroy(&fobj); Py_RETURN_NONE; } /** \ingroup python_interface_graph * \brief Writes the edge list to a file * \return none * \sa igraph_write_graph_edgelist */ PyObject *igraphmodule_Graph_write_edgelist(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { PyObject *fname = NULL; igraphmodule_filehandle_t fobj; static char *kwlist[] = { "f", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O", kwlist, &fname)) return NULL; if (igraphmodule_filehandle_init(&fobj, fname, "w")) return NULL; if (igraph_write_graph_edgelist(&self->g, igraphmodule_filehandle_get(&fobj))) { igraphmodule_handle_igraph_error(); igraphmodule_filehandle_destroy(&fobj); return NULL; } igraphmodule_filehandle_destroy(&fobj); Py_RETURN_NONE; } /** \ingroup python_interface_graph * \brief Writes the graph as a GML file * \return none * \sa igraph_write_graph_gml */ PyObject *igraphmodule_Graph_write_gml(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { PyObject *ids = Py_None, *fname = NULL; PyObject *creator = Py_None; igraph_vector_t idvec, *idvecptr=0; char *creator_str=0; igraphmodule_filehandle_t fobj; static char *kwlist[] = { "f", "creator", "ids", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|OO", kwlist, &fname, &creator, &ids)) return NULL; if (igraphmodule_filehandle_init(&fobj, fname, "w")) return NULL; if (PyList_Check(ids)) { idvecptr = &idvec; if (igraphmodule_PyObject_to_vector_t(ids, idvecptr, 0)) { igraphmodule_filehandle_destroy(&fobj); return NULL; } } if (creator != Py_None) { PyObject* o = PyObject_Str(creator); if (o == 0) { if (idvecptr) igraph_vector_destroy(idvecptr); igraphmodule_filehandle_destroy(&fobj); } creator_str = PyString_CopyAsString(o); Py_DECREF(o); if (creator_str == 0) { if (idvecptr) igraph_vector_destroy(idvecptr); igraphmodule_filehandle_destroy(&fobj); } } if (igraph_write_graph_gml(&self->g, igraphmodule_filehandle_get(&fobj), idvecptr, creator_str)) { if (idvecptr) { igraph_vector_destroy(idvecptr); } if (creator_str) free(creator_str); igraphmodule_filehandle_destroy(&fobj); igraphmodule_handle_igraph_error(); return NULL; } if (idvecptr) { igraph_vector_destroy(idvecptr); } if (creator_str) free(creator_str); igraphmodule_filehandle_destroy(&fobj); Py_RETURN_NONE; } /** \ingroup python_interface_graph * \brief Writes the edge list to a file in .ncol format * \return none * \sa igraph_write_graph_ncol */ PyObject *igraphmodule_Graph_write_ncol(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { PyObject *fname = NULL; char *names = "name"; char *weights = "weight"; igraphmodule_filehandle_t fobj; static char *kwlist[] = { "f", "names", "weights", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|zz", kwlist, &fname, &names, &weights)) return NULL; if (igraphmodule_filehandle_init(&fobj, fname, "w")) return NULL; if (igraph_write_graph_ncol(&self->g, igraphmodule_filehandle_get(&fobj), names, weights)) { igraphmodule_handle_igraph_error(); igraphmodule_filehandle_destroy(&fobj); return NULL; } igraphmodule_filehandle_destroy(&fobj); Py_RETURN_NONE; } /** \ingroup python_interface_graph * \brief Writes the edge list to a file in .lgl format * \return none * \sa igraph_write_graph_lgl */ PyObject *igraphmodule_Graph_write_lgl(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { PyObject *fname = NULL; char *names = "name"; char *weights = "weight"; PyObject *isolates = Py_True; igraphmodule_filehandle_t fobj; static char *kwlist[] = { "f", "names", "weights", "isolates", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|zzO", kwlist, &fname, &names, &weights, &isolates)) return NULL; if (igraphmodule_filehandle_init(&fobj, fname, "w")) return NULL; if (igraph_write_graph_lgl(&self->g, igraphmodule_filehandle_get(&fobj), names, weights, PyObject_IsTrue(isolates))) { igraphmodule_handle_igraph_error(); igraphmodule_filehandle_destroy(&fobj); return NULL; } igraphmodule_filehandle_destroy(&fobj); Py_RETURN_NONE; } /** \ingroup python_interface_graph * \brief Writes the graph as a Pajek .net file * \return none * \sa igraph_write_graph_pajek */ PyObject *igraphmodule_Graph_write_pajek(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { PyObject *fname = NULL; static char *kwlist[] = { "f", NULL }; igraphmodule_filehandle_t fobj; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O", kwlist, &fname)) return NULL; if (igraphmodule_filehandle_init(&fobj, fname, "w")) return NULL; if (igraph_write_graph_pajek(&self->g, igraphmodule_filehandle_get(&fobj))) { igraphmodule_handle_igraph_error(); igraphmodule_filehandle_destroy(&fobj); return NULL; } igraphmodule_filehandle_destroy(&fobj); Py_RETURN_NONE; } /** \ingroup python_interface_graph * \brief Writes the graph to a GraphML file * \return none * \sa igraph_write_graph_graphml */ PyObject *igraphmodule_Graph_write_graphml(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { PyObject *fname = NULL; static char *kwlist[] = { "f", NULL }; igraphmodule_filehandle_t fobj; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O", kwlist, &fname)) return NULL; if (igraphmodule_filehandle_init(&fobj, fname, "w")) return NULL; if (igraph_write_graph_graphml(&self->g, igraphmodule_filehandle_get(&fobj), /*prefixattr=*/ 1)) { igraphmodule_handle_igraph_error(); igraphmodule_filehandle_destroy(&fobj); return NULL; } igraphmodule_filehandle_destroy(&fobj); Py_RETURN_NONE; } /** \ingroup python_interface_graph * \brief Writes the edge list to a file in LEDA native format * \return none * \sa igraph_write_graph_leda */ PyObject *igraphmodule_Graph_write_leda(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { PyObject *fname = NULL; char *vertex_attr_name = "name"; char *edge_attr_name = "weight"; igraphmodule_filehandle_t fobj; static char *kwlist[] = { "f", "names", "weights", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|zz", kwlist, &fname, &vertex_attr_name, &edge_attr_name)) return NULL; if (igraphmodule_filehandle_init(&fobj, fname, "w")) return NULL; if (igraph_write_graph_leda(&self->g, igraphmodule_filehandle_get(&fobj), vertex_attr_name, edge_attr_name)) { igraphmodule_handle_igraph_error(); igraphmodule_filehandle_destroy(&fobj); return NULL; } igraphmodule_filehandle_destroy(&fobj); Py_RETURN_NONE; } /********************************************************************** * Routines related to graph isomorphism * **********************************************************************/ /** * \ingroup python_interface_graph * \brief Calculates the canonical permutation of a graph using BLISS * \sa igraph_canonical_permutation */ PyObject *igraphmodule_Graph_canonical_permutation( igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = { "sh", "color", NULL }; PyObject *sh_o = Py_None; PyObject *color_o = Py_None; PyObject *list; igraph_bliss_sh_t sh = IGRAPH_BLISS_FM; igraph_vector_t labeling; igraph_vector_int_t *color = 0; int retval; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OO", kwlist, &sh_o, &color_o)) return NULL; if (igraphmodule_PyObject_to_bliss_sh_t(sh_o, &sh)) return NULL; if (igraph_vector_init(&labeling, 0)) { igraphmodule_handle_igraph_error(); return NULL; } if (igraphmodule_attrib_to_vector_int_t(color_o, self, &color, ATTRIBUTE_TYPE_VERTEX)) return NULL; retval = igraph_canonical_permutation(&self->g, color, &labeling, sh, 0); if (color) { igraph_vector_int_destroy(color); free(color); } if (retval) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&labeling); return NULL; } list = igraphmodule_vector_t_to_PyList(&labeling, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&labeling); return list; } /** \ingroup python_interface_graph * \brief Calculates the isomorphy class of a graph or its subgraph * \sa igraph_isoclass, igraph_isoclass_subgraph */ PyObject *igraphmodule_Graph_isoclass(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { Py_ssize_t n; igraph_integer_t isoclass = 0; PyObject *vids = 0; char *kwlist[] = { "vertices", NULL }; if (!PyArg_ParseTupleAndKeywords (args, kwds, "|O!", kwlist, &PyList_Type, &vids)) return NULL; n = vids ? PyList_Size(vids) : igraph_vcount(&self->g); if (n < 3 || n > 4) { PyErr_SetString(PyExc_ValueError, "Graph or subgraph must have 3 or 4 vertices."); return NULL; } if (vids) { igraph_vector_t vidsvec; if (igraphmodule_PyObject_to_vector_t(vids, &vidsvec, 1)) { PyErr_SetString(PyExc_ValueError, "Error while converting PyList to igraph_vector_t"); return NULL; } if (igraph_isoclass_subgraph(&self->g, &vidsvec, &isoclass)) { igraphmodule_handle_igraph_error(); return NULL; } } else { if (igraph_isoclass(&self->g, &isoclass)) { igraphmodule_handle_igraph_error(); return NULL; } } return PyInt_FromLong((long)isoclass); } /** \ingroup python_interface_graph * \brief Determines whether the graph is isomorphic to another graph. * * \sa igraph_isomorphic */ PyObject *igraphmodule_Graph_isomorphic(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { igraph_bool_t result = 0; PyObject *o = Py_None; igraphmodule_GraphObject *other; static char *kwlist[] = { "other", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O!", kwlist, &igraphmodule_GraphType, &o)) return NULL; if (o == Py_None) other = self; else other = (igraphmodule_GraphObject *) o; if (igraph_isomorphic(&self->g, &other->g, &result)) { igraphmodule_handle_igraph_error(); return NULL; } if (result) Py_RETURN_TRUE; Py_RETURN_FALSE; } /** \ingroup python_interface_graph * \brief Determines whether the graph is isomorphic to another graph, * using the BLISS isomorphism algorithm * * The actual code is almost the same as igraphmodule_Graph_isomorphic_vf2. * Be sure to correct bugs in both interfaces if applicable! * * \sa igraph_isomorphic_bliss */ PyObject *igraphmodule_Graph_isomorphic_bliss(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { igraph_bool_t result = 0; PyObject *o=Py_None, *return1=Py_False, *return2=Py_False; PyObject *sho1=Py_None, *sho2=Py_None; PyObject *color1_o=Py_None, *color2_o=Py_None; igraphmodule_GraphObject *other; igraph_vector_t mapping_12, mapping_21, *map12=0, *map21=0; igraph_bliss_sh_t sh1=IGRAPH_BLISS_FM, sh2=IGRAPH_BLISS_FM; igraph_vector_int_t *color1=0, *color2=0; int retval; static char *kwlist[] = { "other", "return_mapping_12", "return_mapping_21", "sh1", "sh2", "color1", "color2", NULL }; /* TODO: convert igraph_bliss_info_t when needed */ if (!PyArg_ParseTupleAndKeywords (args, kwds, "|O!OOOOOO", kwlist, &igraphmodule_GraphType, &o, &return1, &return2, &sho1, &sho2, &color1_o, &color2_o)) return NULL; if (igraphmodule_PyObject_to_bliss_sh_t(sho1, &sh1)) return NULL; sh2 = sh1; if (igraphmodule_PyObject_to_bliss_sh_t(sho2, &sh2)) return NULL; if (sho2 != Py_None && sh2 != sh1) { PY_IGRAPH_WARN("sh2 is ignored in isomorphic_bliss() and is always assumed to " "be equal to sh1"); } sh2 = sh1; if (igraphmodule_attrib_to_vector_int_t(color1_o, self, &color1, ATTRIBUTE_TYPE_VERTEX)) return NULL; if (igraphmodule_attrib_to_vector_int_t(color2_o, self, &color2, ATTRIBUTE_TYPE_VERTEX)) return NULL; if (o == Py_None) other = self; else other = (igraphmodule_GraphObject *) o; if (PyObject_IsTrue(return1)) { igraph_vector_init(&mapping_12, 0); map12 = &mapping_12; } if (PyObject_IsTrue(return2)) { igraph_vector_init(&mapping_21, 0); map21 = &mapping_21; } retval = igraph_isomorphic_bliss(&self->g, &other->g, color1, color2, &result, map12, map21, sh1, 0, 0); if (color1) { igraph_vector_int_destroy(color1); free(color1); } if (color2) { igraph_vector_int_destroy(color2); free(color2); } if (retval) { igraphmodule_handle_igraph_error(); return NULL; } if (!map12 && !map21) { if (result) Py_RETURN_TRUE; Py_RETURN_FALSE; } else { PyObject *iso, *m1, *m2; iso = result ? Py_True : Py_False; Py_INCREF(iso); if (map12) { m1 = igraphmodule_vector_t_to_PyList(map12, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(map12); if (!m1) { Py_DECREF(iso); if (map21) igraph_vector_destroy(map21); return NULL; } } else { m1 = Py_None; Py_INCREF(m1); } if (map21) { m2 = igraphmodule_vector_t_to_PyList(map21, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(map21); if (!m2) { Py_DECREF(iso); Py_DECREF(m1); return NULL; } } else { m2 = Py_None; Py_INCREF(m2); } return Py_BuildValue("NNN", iso, m1, m2); } } typedef struct { PyObject* node_compat_fn; PyObject* edge_compat_fn; PyObject* callback_fn; PyObject* graph1; PyObject* graph2; } igraphmodule_i_Graph_isomorphic_vf2_callback_data_t; igraph_bool_t igraphmodule_i_Graph_isomorphic_vf2_callback_fn( const igraph_vector_t *map12, const igraph_vector_t *map21, void* extra) { igraphmodule_i_Graph_isomorphic_vf2_callback_data_t* data = (igraphmodule_i_Graph_isomorphic_vf2_callback_data_t*)extra; igraph_bool_t retval; PyObject *map12_o, *map21_o; PyObject *result; map12_o = igraphmodule_vector_t_to_PyList(map12, IGRAPHMODULE_TYPE_INT); if (map12_o == NULL) { /* Error in conversion, return 0 to stop the search */ PyErr_WriteUnraisable(data->callback_fn); return 0; } map21_o = igraphmodule_vector_t_to_PyList(map21, IGRAPHMODULE_TYPE_INT); if (map21_o == NULL) { /* Error in conversion, return 0 to stop the search */ PyErr_WriteUnraisable(data->callback_fn); Py_DECREF(map21_o); return 0; } result = PyObject_CallFunction(data->callback_fn, "OOOO", data->graph1, data->graph2, map12_o, map21_o); Py_DECREF(map12_o); Py_DECREF(map21_o); if (result == NULL) { /* Error in callback, return 0 */ PyErr_WriteUnraisable(data->callback_fn); return 0; } retval = PyObject_IsTrue(result); Py_DECREF(result); return retval; } igraph_bool_t igraphmodule_i_Graph_isomorphic_vf2_node_compat_fn( const igraph_t *graph1, const igraph_t *graph2, const igraph_integer_t cand1, const igraph_integer_t cand2, void* extra) { igraphmodule_i_Graph_isomorphic_vf2_callback_data_t* data = (igraphmodule_i_Graph_isomorphic_vf2_callback_data_t*)extra; igraph_bool_t retval; PyObject *result; result = PyObject_CallFunction(data->node_compat_fn, "OOll", data->graph1, data->graph2, (long)cand1, (long)cand2); if (result == NULL) { /* Error in callback, return 0 */ PyErr_WriteUnraisable(data->node_compat_fn); return 0; } retval = PyObject_IsTrue(result); Py_DECREF(result); return retval; } igraph_bool_t igraphmodule_i_Graph_isomorphic_vf2_edge_compat_fn( const igraph_t *graph1, const igraph_t *graph2, const igraph_integer_t cand1, const igraph_integer_t cand2, void* extra) { igraphmodule_i_Graph_isomorphic_vf2_callback_data_t* data = (igraphmodule_i_Graph_isomorphic_vf2_callback_data_t*)extra; igraph_bool_t retval; PyObject *result; result = PyObject_CallFunction(data->edge_compat_fn, "OOll", data->graph1, data->graph2, (long)cand1, (long)cand2); if (result == NULL) { /* Error in callback, return 0 */ PyErr_WriteUnraisable(data->edge_compat_fn); return 0; } retval = PyObject_IsTrue(result); Py_DECREF(result); return retval; } /** \ingroup python_interface_graph * \brief Determines whether the graph is isomorphic to another graph, * using the VF2 isomorphism algorithm * * The actual code is almost the same as igraphmodule_Graph_subisomorphic. * Be sure to correct bugs in both interfaces if applicable! * * \sa igraph_isomorphic_vf2 */ PyObject *igraphmodule_Graph_isomorphic_vf2(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { igraph_bool_t result = 0; PyObject *o=Py_None, *return1=Py_False, *return2=Py_False; PyObject *color1_o=Py_None, *color2_o=Py_None; PyObject *edge_color1_o=Py_None, *edge_color2_o=Py_None; PyObject *callback_fn=Py_None; PyObject *node_compat_fn=Py_None, *edge_compat_fn=Py_None; igraphmodule_GraphObject *other; igraph_vector_t mapping_12, mapping_21; igraph_vector_t *map12=0, *map21=0; igraph_vector_int_t *color1=0, *color2=0; igraph_vector_int_t *edge_color1=0, *edge_color2=0; igraphmodule_i_Graph_isomorphic_vf2_callback_data_t callback_data; int retval; static char *kwlist[] = { "other", "color1", "color2", "edge_color1", "edge_color2", "return_mapping_12", "return_mapping_21", "callback", "node_compat_fn", "edge_compat_fn", NULL }; if (!PyArg_ParseTupleAndKeywords (args, kwds, "|O!OOOOOOOOO", kwlist, &igraphmodule_GraphType, &o, &color1_o, &color2_o, &edge_color1_o, &edge_color2_o, &return1, &return2, &callback_fn, &node_compat_fn, &edge_compat_fn)) return NULL; if (o == Py_None) other=self; else other=(igraphmodule_GraphObject*)o; if (callback_fn != Py_None && !PyCallable_Check(callback_fn)) { PyErr_SetString(PyExc_TypeError, "callback must be None or callable"); return NULL; } if (node_compat_fn != Py_None && !PyCallable_Check(node_compat_fn)) { PyErr_SetString(PyExc_TypeError, "node_compat_fn must be None or callable"); return NULL; } if (edge_compat_fn != Py_None && !PyCallable_Check(edge_compat_fn)) { PyErr_SetString(PyExc_TypeError, "edge_compat_fn must be None or callable"); return NULL; } if (igraphmodule_attrib_to_vector_int_t(color1_o, self, &color1, ATTRIBUTE_TYPE_VERTEX)) return NULL; if (igraphmodule_attrib_to_vector_int_t(color2_o, other, &color2, ATTRIBUTE_TYPE_VERTEX)) { if (color1) { igraph_vector_int_destroy(color1); free(color1); } return NULL; } if (igraphmodule_attrib_to_vector_int_t(edge_color1_o, self, &edge_color1, ATTRIBUTE_TYPE_EDGE)) { if (color1) { igraph_vector_int_destroy(color1); free(color1); } if (color2) { igraph_vector_int_destroy(color2); free(color2); } return NULL; } if (igraphmodule_attrib_to_vector_int_t(edge_color2_o, other, &edge_color2, ATTRIBUTE_TYPE_EDGE)) { if (color1) { igraph_vector_int_destroy(color1); free(color1); } if (color2) { igraph_vector_int_destroy(color2); free(color2); } if (edge_color1) { igraph_vector_int_destroy(edge_color1); free(edge_color1); } return NULL; } if (PyObject_IsTrue(return1)) { igraph_vector_init(&mapping_12, 0); map12 = &mapping_12; } if (PyObject_IsTrue(return2)) { igraph_vector_init(&mapping_21, 0); map21 = &mapping_21; } callback_data.graph1 = (PyObject*)self; callback_data.graph2 = (PyObject*)other; callback_data.callback_fn = callback_fn == Py_None ? 0 : callback_fn; callback_data.node_compat_fn = node_compat_fn == Py_None ? 0 : node_compat_fn; callback_data.edge_compat_fn = edge_compat_fn == Py_None ? 0 : edge_compat_fn; if (callback_data.callback_fn == 0) { retval = igraph_isomorphic_vf2(&self->g, &other->g, color1, color2, edge_color1, edge_color2, &result, map12, map21, node_compat_fn == Py_None ? 0 : igraphmodule_i_Graph_isomorphic_vf2_node_compat_fn, edge_compat_fn == Py_None ? 0 : igraphmodule_i_Graph_isomorphic_vf2_edge_compat_fn, &callback_data); } else { retval = igraph_isomorphic_function_vf2(&self->g, &other->g, color1, color2, edge_color1, edge_color2, map12, map21, igraphmodule_i_Graph_isomorphic_vf2_callback_fn, node_compat_fn == Py_None ? 0 : igraphmodule_i_Graph_isomorphic_vf2_node_compat_fn, edge_compat_fn == Py_None ? 0 : igraphmodule_i_Graph_isomorphic_vf2_edge_compat_fn, &callback_data); } if (color1) { igraph_vector_int_destroy(color1); free(color1); } if (color2) { igraph_vector_int_destroy(color2); free(color2); } if (edge_color1) { igraph_vector_int_destroy(edge_color1); free(edge_color1); } if (edge_color2) { igraph_vector_int_destroy(edge_color2); free(edge_color2); } if (retval) { igraphmodule_handle_igraph_error(); return NULL; } if (!map12 && !map21) { if (result) Py_RETURN_TRUE; Py_RETURN_FALSE; } else { PyObject *m1, *m2; if (map12) { m1 = igraphmodule_vector_t_to_PyList(map12, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(map12); if (!m1) { if (map21) igraph_vector_destroy(map21); return NULL; } } else { m1 = Py_None; Py_INCREF(m1); } if (map21) { m2 = igraphmodule_vector_t_to_PyList(map21, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(map21); if (!m2) { Py_DECREF(m1); return NULL; } } else { m2 = Py_None; Py_INCREF(m2); } return Py_BuildValue("ONN", result ? Py_True : Py_False, m1, m2); } } /** \ingroup python_interface_graph * \brief Counts the number of isomorphisms of two given graphs * * The actual code is almost the same as igraphmodule_Graph_count_subisomorphisms. * Make sure you correct bugs in both interfaces if applicable! * * \sa igraph_count_isomorphisms_vf2 */ PyObject *igraphmodule_Graph_count_isomorphisms_vf2(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { igraph_integer_t result = 0; PyObject *o = Py_None; PyObject *color1_o=Py_None, *color2_o=Py_None; PyObject *edge_color1_o=Py_None, *edge_color2_o=Py_None; PyObject *node_compat_fn=Py_None, *edge_compat_fn=Py_None; igraphmodule_GraphObject *other; igraph_vector_int_t *color1=0, *color2=0; igraph_vector_int_t *edge_color1=0, *edge_color2=0; igraphmodule_i_Graph_isomorphic_vf2_callback_data_t callback_data; static char *kwlist[] = { "other", "color1", "color2", "edge_color1", "edge_color2", "node_compat_fn", "edge_compat_fn", NULL }; if (!PyArg_ParseTupleAndKeywords (args, kwds, "|O!OOOOOO", kwlist, &igraphmodule_GraphType, &o, &color1_o, &color2_o, &edge_color1_o, &edge_color2_o, &node_compat_fn, &edge_compat_fn)) return NULL; if (o == Py_None) other=self; else other=(igraphmodule_GraphObject*)o; if (node_compat_fn != Py_None && !PyCallable_Check(node_compat_fn)) { PyErr_SetString(PyExc_TypeError, "node_compat_fn must be None or callable"); return NULL; } if (edge_compat_fn != Py_None && !PyCallable_Check(edge_compat_fn)) { PyErr_SetString(PyExc_TypeError, "edge_compat_fn must be None or callable"); return NULL; } if (igraphmodule_attrib_to_vector_int_t(color1_o, self, &color1, ATTRIBUTE_TYPE_VERTEX)) return NULL; if (igraphmodule_attrib_to_vector_int_t(color2_o, other, &color2, ATTRIBUTE_TYPE_VERTEX)) { if (color1) { igraph_vector_int_destroy(color1); free(color1); } return NULL; } if (igraphmodule_attrib_to_vector_int_t(edge_color1_o, self, &edge_color1, ATTRIBUTE_TYPE_EDGE)) { if (color1) { igraph_vector_int_destroy(color1); free(color1); } if (color2) { igraph_vector_int_destroy(color2); free(color2); } return NULL; } if (igraphmodule_attrib_to_vector_int_t(edge_color2_o, other, &edge_color2, ATTRIBUTE_TYPE_EDGE)) { if (color1) { igraph_vector_int_destroy(color1); free(color1); } if (color2) { igraph_vector_int_destroy(color2); free(color2); } if (edge_color1) { igraph_vector_int_destroy(edge_color1); free(edge_color1); } return NULL; } callback_data.graph1 = (PyObject*)self; callback_data.graph2 = (PyObject*)other; callback_data.callback_fn = 0; callback_data.node_compat_fn = node_compat_fn == Py_None ? 0 : node_compat_fn; callback_data.edge_compat_fn = edge_compat_fn == Py_None ? 0 : edge_compat_fn; if (igraph_count_isomorphisms_vf2(&self->g, &other->g, color1, color2, edge_color1, edge_color2, &result, node_compat_fn == Py_None ? 0 : igraphmodule_i_Graph_isomorphic_vf2_node_compat_fn, edge_compat_fn == Py_None ? 0 : igraphmodule_i_Graph_isomorphic_vf2_edge_compat_fn, &callback_data)) { if (color1) { igraph_vector_int_destroy(color1); free(color1); } if (color2) { igraph_vector_int_destroy(color2); free(color2); } if (edge_color1) { igraph_vector_int_destroy(edge_color1); free(edge_color1); } if (edge_color2) { igraph_vector_int_destroy(edge_color2); free(edge_color2); } igraphmodule_handle_igraph_error(); return NULL; } if (color1) { igraph_vector_int_destroy(color1); free(color1); } if (color2) { igraph_vector_int_destroy(color2); free(color2); } if (edge_color1) { igraph_vector_int_destroy(edge_color1); free(edge_color1); } if (edge_color2) { igraph_vector_int_destroy(edge_color2); free(edge_color2); } return Py_BuildValue("l", (long)result); } /** \ingroup python_interface_graph * \brief Returns all isomorphisms of two given graphs * * The actual code is almost the same as igraphmodule_Graph_get_subisomorphisms. * Make sure you correct bugs in both interfaces if applicable! * * \sa igraph_get_isomorphisms_vf2 */ PyObject *igraphmodule_Graph_get_isomorphisms_vf2(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { igraph_vector_ptr_t result; PyObject *o = Py_None; PyObject *color1_o = Py_None, *color2_o = Py_None; PyObject *edge_color1_o=Py_None, *edge_color2_o=Py_None; PyObject *node_compat_fn=Py_None, *edge_compat_fn=Py_None; PyObject *res; igraphmodule_GraphObject *other; igraph_vector_int_t *color1=0, *color2=0; igraph_vector_int_t *edge_color1=0, *edge_color2=0; igraphmodule_i_Graph_isomorphic_vf2_callback_data_t callback_data; static char *kwlist[] = { "other", "color1", "color2", "edge_color1", "edge_color2", "node_compat_fn", "edge_compat_fn", NULL }; if (!PyArg_ParseTupleAndKeywords (args, kwds, "|O!OOOOOO", kwlist, &igraphmodule_GraphType, &o, &color1_o, &color2_o, &edge_color1_o, &edge_color2_o, &node_compat_fn, &edge_compat_fn)) return NULL; if (o == Py_None) other=self; else other=(igraphmodule_GraphObject*)o; if (node_compat_fn != Py_None && !PyCallable_Check(node_compat_fn)) { PyErr_SetString(PyExc_TypeError, "node_compat_fn must be None or callable"); return NULL; } if (edge_compat_fn != Py_None && !PyCallable_Check(edge_compat_fn)) { PyErr_SetString(PyExc_TypeError, "edge_compat_fn must be None or callable"); return NULL; } if (igraphmodule_attrib_to_vector_int_t(color1_o, self, &color1, ATTRIBUTE_TYPE_VERTEX)) return NULL; if (igraphmodule_attrib_to_vector_int_t(color2_o, other, &color2, ATTRIBUTE_TYPE_VERTEX)) { if (color1) { igraph_vector_int_destroy(color1); free(color1); } return NULL; } if (igraphmodule_attrib_to_vector_int_t(edge_color1_o, self, &edge_color1, ATTRIBUTE_TYPE_EDGE)) { if (color1) { igraph_vector_int_destroy(color1); free(color1); } if (color2) { igraph_vector_int_destroy(color2); free(color2); } return NULL; } if (igraphmodule_attrib_to_vector_int_t(edge_color2_o, other, &edge_color2, ATTRIBUTE_TYPE_EDGE)) { if (color1) { igraph_vector_int_destroy(color1); free(color1); } if (color2) { igraph_vector_int_destroy(color2); free(color2); } if (edge_color1) { igraph_vector_int_destroy(edge_color1); free(edge_color1); } return NULL; } if (igraph_vector_ptr_init(&result, 0)) { if (color1) { igraph_vector_int_destroy(color1); free(color1); } if (color2) { igraph_vector_int_destroy(color2); free(color2); } if (edge_color1) { igraph_vector_int_destroy(edge_color1); free(edge_color1); } if (edge_color2) { igraph_vector_int_destroy(edge_color2); free(edge_color2); } return igraphmodule_handle_igraph_error(); } callback_data.graph1 = (PyObject*)self; callback_data.graph2 = (PyObject*)other; callback_data.callback_fn = 0; callback_data.node_compat_fn = node_compat_fn == Py_None ? 0 : node_compat_fn; callback_data.edge_compat_fn = edge_compat_fn == Py_None ? 0 : edge_compat_fn; if (igraph_get_isomorphisms_vf2(&self->g, &other->g, color1, color2, edge_color1, edge_color2, &result, node_compat_fn == Py_None ? 0 : igraphmodule_i_Graph_isomorphic_vf2_node_compat_fn, edge_compat_fn == Py_None ? 0 : igraphmodule_i_Graph_isomorphic_vf2_edge_compat_fn, &callback_data)) { igraphmodule_handle_igraph_error(); if (color1) { igraph_vector_int_destroy(color1); free(color1); } if (color2) { igraph_vector_int_destroy(color2); free(color2); } if (edge_color1) { igraph_vector_int_destroy(edge_color1); free(edge_color1); } if (edge_color2) { igraph_vector_int_destroy(edge_color2); free(edge_color2); } igraph_vector_ptr_destroy(&result); return NULL; } if (color1) { igraph_vector_int_destroy(color1); free(color1); } if (color2) { igraph_vector_int_destroy(color2); free(color2); } if (edge_color1) { igraph_vector_int_destroy(edge_color1); free(edge_color1); } if (edge_color2) { igraph_vector_int_destroy(edge_color2); free(edge_color2); } res = igraphmodule_vector_ptr_t_to_PyList(&result, IGRAPHMODULE_TYPE_INT); IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(&result, igraph_vector_destroy); igraph_vector_ptr_destroy_all(&result); return res; } /** \ingroup python_interface_graph * \brief Determines whether a subgraph of the graph is isomorphic to another graph * using the VF2 algorithm. * * \sa igraph_subisomorphic_vf2 */ PyObject *igraphmodule_Graph_subisomorphic_vf2(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { igraph_bool_t result = 0; PyObject *o, *return1=Py_False, *return2=Py_False; PyObject *color1_o=Py_None, *color2_o=Py_None; PyObject *edge_color1_o=Py_None, *edge_color2_o=Py_None; PyObject *callback_fn=Py_None; PyObject *node_compat_fn=Py_None, *edge_compat_fn=Py_None; igraphmodule_GraphObject *other; igraph_vector_t mapping_12, mapping_21, *map12=0, *map21=0; igraph_vector_int_t *color1=0, *color2=0; igraph_vector_int_t *edge_color1=0, *edge_color2=0; igraphmodule_i_Graph_isomorphic_vf2_callback_data_t callback_data; int retval; static char *kwlist[] = { "other", "color1", "color2", "edge_color1", "edge_color2", "return_mapping_12", "return_mapping_21", "callback", "node_compat_fn", "edge_compat_fn", NULL }; if (!PyArg_ParseTupleAndKeywords (args, kwds, "O!|OOOOOOOOO", kwlist, &igraphmodule_GraphType, &o, &color1_o, &color2_o, &edge_color1_o, &edge_color2_o, &return1, &return2, &callback_fn, &node_compat_fn, &edge_compat_fn)) return NULL; other=(igraphmodule_GraphObject*)o; if (callback_fn != Py_None && !PyCallable_Check(callback_fn)) { PyErr_SetString(PyExc_TypeError, "callback must be None or callable"); return NULL; } if (node_compat_fn != Py_None && !PyCallable_Check(node_compat_fn)) { PyErr_SetString(PyExc_TypeError, "node_compat_fn must be None or callable"); return NULL; } if (edge_compat_fn != Py_None && !PyCallable_Check(edge_compat_fn)) { PyErr_SetString(PyExc_TypeError, "edge_compat_fn must be None or callable"); return NULL; } if (igraphmodule_attrib_to_vector_int_t(color1_o, self, &color1, ATTRIBUTE_TYPE_VERTEX)) return NULL; if (igraphmodule_attrib_to_vector_int_t(color2_o, other, &color2, ATTRIBUTE_TYPE_VERTEX)) { if (color1) { igraph_vector_int_destroy(color1); free(color1); } return NULL; } if (igraphmodule_attrib_to_vector_int_t(edge_color1_o, self, &edge_color1, ATTRIBUTE_TYPE_EDGE)) { if (color1) { igraph_vector_int_destroy(color1); free(color1); } if (color2) { igraph_vector_int_destroy(color2); free(color2); } return NULL; } if (igraphmodule_attrib_to_vector_int_t(edge_color2_o, other, &edge_color2, ATTRIBUTE_TYPE_EDGE)) { if (color1) { igraph_vector_int_destroy(color1); free(color1); } if (color2) { igraph_vector_int_destroy(color2); free(color2); } if (edge_color1) { igraph_vector_int_destroy(edge_color1); free(edge_color1); } return NULL; } if (PyObject_IsTrue(return1)) { igraph_vector_init(&mapping_12, 0); map12 = &mapping_12; } if (PyObject_IsTrue(return2)) { igraph_vector_init(&mapping_21, 0); map21 = &mapping_21; } callback_data.graph1 = (PyObject*)self; callback_data.graph2 = (PyObject*)other; callback_data.callback_fn = callback_fn == Py_None ? 0 : callback_fn; callback_data.node_compat_fn = node_compat_fn == Py_None ? 0 : node_compat_fn; callback_data.edge_compat_fn = edge_compat_fn == Py_None ? 0 : edge_compat_fn; if (callback_data.callback_fn == 0) { retval = igraph_subisomorphic_vf2(&self->g, &other->g, color1, color2, edge_color1, edge_color2, &result, map12, map21, node_compat_fn == Py_None ? 0 : igraphmodule_i_Graph_isomorphic_vf2_node_compat_fn, edge_compat_fn == Py_None ? 0 : igraphmodule_i_Graph_isomorphic_vf2_edge_compat_fn, &callback_data); } else { retval = igraph_subisomorphic_function_vf2(&self->g, &other->g, color1, color2, edge_color1, edge_color2, map12, map21, igraphmodule_i_Graph_isomorphic_vf2_callback_fn, node_compat_fn == Py_None ? 0 : igraphmodule_i_Graph_isomorphic_vf2_node_compat_fn, edge_compat_fn == Py_None ? 0 : igraphmodule_i_Graph_isomorphic_vf2_edge_compat_fn, &callback_data); } if (color1) { igraph_vector_int_destroy(color1); free(color1); } if (color2) { igraph_vector_int_destroy(color2); free(color2); } if (edge_color1) { igraph_vector_int_destroy(edge_color1); free(edge_color1); } if (edge_color2) { igraph_vector_int_destroy(edge_color2); free(edge_color2); } if (retval) { igraphmodule_handle_igraph_error(); return NULL; } if (!map12 && !map21) { if (result) Py_RETURN_TRUE; Py_RETURN_FALSE; } else { PyObject *m1, *m2; if (map12) { m1 = igraphmodule_vector_t_to_PyList(map12, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(map12); if (!m1) { if (map21) igraph_vector_destroy(map21); return NULL; } } else { m1 = Py_None; Py_INCREF(m1); } if (map21) { m2 = igraphmodule_vector_t_to_PyList(map21, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(map21); if (!m2) { Py_DECREF(m1); return NULL; } } else { m2 = Py_None; Py_INCREF(m2); } return Py_BuildValue("ONN", result ? Py_True : Py_False, m1, m2); } } /** \ingroup python_interface_graph * \brief Counts the number of subisomorphisms of two given graphs * * The actual code is almost the same as igraphmodule_Graph_count_isomorphisms. * Make sure you correct bugs in both interfaces if applicable! * * \sa igraph_count_subisomorphisms_vf2 */ PyObject *igraphmodule_Graph_count_subisomorphisms_vf2(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { igraph_integer_t result = 0; PyObject *o = Py_None; PyObject *color1_o = Py_None, *color2_o = Py_None; PyObject *edge_color1_o=Py_None, *edge_color2_o=Py_None; PyObject *node_compat_fn=Py_None, *edge_compat_fn=Py_None; igraph_vector_int_t *color1=0, *color2=0; igraph_vector_int_t *edge_color1=0, *edge_color2=0; igraphmodule_GraphObject *other; igraphmodule_i_Graph_isomorphic_vf2_callback_data_t callback_data; static char *kwlist[] = { "other", "color1", "color2", "edge_color1", "edge_color2", "node_compat_fn", "edge_compat_fn", NULL }; if (!PyArg_ParseTupleAndKeywords (args, kwds, "O!|OOOOOO", kwlist, &igraphmodule_GraphType, &o, &color1_o, &color2_o, &edge_color1_o, &edge_color2_o, &node_compat_fn, &edge_compat_fn)) return NULL; other=(igraphmodule_GraphObject*)o; if (node_compat_fn != Py_None && !PyCallable_Check(node_compat_fn)) { PyErr_SetString(PyExc_TypeError, "node_compat_fn must be None or callable"); return NULL; } if (edge_compat_fn != Py_None && !PyCallable_Check(edge_compat_fn)) { PyErr_SetString(PyExc_TypeError, "edge_compat_fn must be None or callable"); return NULL; } if (igraphmodule_attrib_to_vector_int_t(color1_o, self, &color1, ATTRIBUTE_TYPE_VERTEX)) return NULL; if (igraphmodule_attrib_to_vector_int_t(color2_o, other, &color2, ATTRIBUTE_TYPE_VERTEX)) { if (color1) { igraph_vector_int_destroy(color1); free(color1); } return NULL; } if (igraphmodule_attrib_to_vector_int_t(edge_color1_o, self, &edge_color1, ATTRIBUTE_TYPE_EDGE)) { if (color1) { igraph_vector_int_destroy(color1); free(color1); } if (color2) { igraph_vector_int_destroy(color2); free(color2); } return NULL; } if (igraphmodule_attrib_to_vector_int_t(edge_color2_o, other, &edge_color2, ATTRIBUTE_TYPE_EDGE)) { if (color1) { igraph_vector_int_destroy(color1); free(color1); } if (color2) { igraph_vector_int_destroy(color2); free(color2); } if (edge_color1) { igraph_vector_int_destroy(edge_color1); free(edge_color1); } return NULL; } callback_data.graph1 = (PyObject*)self; callback_data.graph2 = (PyObject*)other; callback_data.callback_fn = 0; callback_data.node_compat_fn = node_compat_fn == Py_None ? 0 : node_compat_fn; callback_data.edge_compat_fn = edge_compat_fn == Py_None ? 0 : edge_compat_fn; if (igraph_count_subisomorphisms_vf2(&self->g, &other->g, color1, color2, edge_color1, edge_color2, &result, node_compat_fn == Py_None ? 0 : igraphmodule_i_Graph_isomorphic_vf2_node_compat_fn, edge_compat_fn == Py_None ? 0 : igraphmodule_i_Graph_isomorphic_vf2_edge_compat_fn, &callback_data)) { igraphmodule_handle_igraph_error(); if (color1) { igraph_vector_int_destroy(color1); free(color1); } if (color2) { igraph_vector_int_destroy(color2); free(color2); } if (edge_color1) { igraph_vector_int_destroy(edge_color1); free(edge_color1); } if (edge_color2) { igraph_vector_int_destroy(edge_color2); free(edge_color2); } return NULL; } if (color1) { igraph_vector_int_destroy(color1); free(color1); } if (color2) { igraph_vector_int_destroy(color2); free(color2); } if (edge_color1) { igraph_vector_int_destroy(edge_color1); free(edge_color1); } if (edge_color2) { igraph_vector_int_destroy(edge_color2); free(edge_color2); } return Py_BuildValue("l", (long)result); } /** \ingroup python_interface_graph * \brief Returns all subisomorphisms of two given graphs * * The actual code is almost the same as igraphmodule_Graph_get_isomorphisms. * Make sure you correct bugs in both interfaces if applicable! * * \sa igraph_get_isomorphisms_vf2 */ PyObject *igraphmodule_Graph_get_subisomorphisms_vf2(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { igraph_vector_ptr_t result; PyObject *o; PyObject *color1_o=Py_None, *color2_o=Py_None; PyObject *edge_color1_o=Py_None, *edge_color2_o=Py_None; PyObject *node_compat_fn=Py_None, *edge_compat_fn=Py_None; PyObject *res; igraphmodule_GraphObject *other; igraph_vector_int_t *color1=0, *color2=0; igraph_vector_int_t *edge_color1=0, *edge_color2=0; igraphmodule_i_Graph_isomorphic_vf2_callback_data_t callback_data; static char *kwlist[] = { "other", "color1", "color2", "edge_color1", "edge_color2", "node_compat_fn", "edge_compat_fn", NULL }; if (!PyArg_ParseTupleAndKeywords (args, kwds, "O!|OOOOOO", kwlist, &igraphmodule_GraphType, &o, &color1_o, &color2_o, &edge_color1_o, &edge_color2_o, &node_compat_fn, &edge_compat_fn)) return NULL; if (igraph_vector_ptr_init(&result, 0)) { return igraphmodule_handle_igraph_error(); } other=(igraphmodule_GraphObject*)o; if (node_compat_fn != Py_None && !PyCallable_Check(node_compat_fn)) { PyErr_SetString(PyExc_TypeError, "node_compat_fn must be None or callable"); return NULL; } if (edge_compat_fn != Py_None && !PyCallable_Check(edge_compat_fn)) { PyErr_SetString(PyExc_TypeError, "edge_compat_fn must be None or callable"); return NULL; } if (igraphmodule_attrib_to_vector_int_t(color1_o, self, &color1, ATTRIBUTE_TYPE_VERTEX)) return NULL; if (igraphmodule_attrib_to_vector_int_t(color2_o, other, &color2, ATTRIBUTE_TYPE_VERTEX)) { if (color1) { igraph_vector_int_destroy(color1); free(color1); } return NULL; } if (igraphmodule_attrib_to_vector_int_t(edge_color1_o, self, &edge_color1, ATTRIBUTE_TYPE_EDGE)) { if (color1) { igraph_vector_int_destroy(color1); free(color1); } if (color2) { igraph_vector_int_destroy(color2); free(color2); } return NULL; } if (igraphmodule_attrib_to_vector_int_t(edge_color2_o, other, &edge_color2, ATTRIBUTE_TYPE_EDGE)) { if (color1) { igraph_vector_int_destroy(color1); free(color1); } if (color2) { igraph_vector_int_destroy(color2); free(color2); } if (edge_color1) { igraph_vector_int_destroy(edge_color1); free(edge_color1); } return NULL; } callback_data.graph1 = (PyObject*)self; callback_data.graph2 = (PyObject*)other; callback_data.callback_fn = 0; callback_data.node_compat_fn = node_compat_fn == Py_None ? 0 : node_compat_fn; callback_data.edge_compat_fn = edge_compat_fn == Py_None ? 0 : edge_compat_fn; if (igraph_get_subisomorphisms_vf2(&self->g, &other->g, color1, color2, edge_color1, edge_color2, &result, node_compat_fn == Py_None ? 0 : igraphmodule_i_Graph_isomorphic_vf2_node_compat_fn, edge_compat_fn == Py_None ? 0 : igraphmodule_i_Graph_isomorphic_vf2_edge_compat_fn, &callback_data)) { igraphmodule_handle_igraph_error(); if (color1) { igraph_vector_int_destroy(color1); free(color1); } if (color2) { igraph_vector_int_destroy(color2); free(color2); } if (edge_color1) { igraph_vector_int_destroy(edge_color1); free(edge_color1); } if (edge_color2) { igraph_vector_int_destroy(edge_color2); free(edge_color2); } igraph_vector_ptr_destroy(&result); return NULL; } if (color1) { igraph_vector_int_destroy(color1); free(color1); } if (color2) { igraph_vector_int_destroy(color2); free(color2); } if (edge_color1) { igraph_vector_int_destroy(edge_color1); free(edge_color1); } if (edge_color2) { igraph_vector_int_destroy(edge_color2); free(edge_color2); } res = igraphmodule_vector_ptr_t_to_PyList(&result, IGRAPHMODULE_TYPE_INT); IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(&result, igraph_vector_destroy); igraph_vector_ptr_destroy_all(&result); return res; } /** \ingroup python_interface_graph * \brief Determines whether a subgraph of the graph is isomorphic to another graph * using the LAD algorithm. * * \sa igraph_subisomorphic_lad */ PyObject *igraphmodule_Graph_subisomorphic_lad(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { igraph_bool_t result = 0; PyObject *o, *return_mapping=Py_False, *domains_o=Py_None, *induced=Py_False; float time_limit = 0; igraphmodule_GraphObject *other; igraph_vector_ptr_t domains; igraph_vector_ptr_t* p_domains = 0; igraph_vector_t mapping, *map=0; static char *kwlist[] = { "pattern", "domains", "induced", "time_limit", "return_mapping", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O!|OOfO", kwlist, &igraphmodule_GraphType, &o, &domains_o, &induced, &time_limit, &return_mapping)) return NULL; other=(igraphmodule_GraphObject*)o; if (domains_o != Py_None) { if (igraphmodule_PyObject_to_vector_ptr_t(domains_o, &domains, 1)) return NULL; p_domains = &domains; } if (PyObject_IsTrue(return_mapping)) { if (igraph_vector_init(&mapping, 0)) { if (p_domains) igraph_vector_ptr_destroy_all(p_domains); igraphmodule_handle_igraph_error(); return NULL; } map = &mapping; } if (igraph_subisomorphic_lad(&other->g, &self->g, p_domains, &result, map, 0, PyObject_IsTrue(induced), (int)time_limit)) { if (p_domains) igraph_vector_ptr_destroy_all(p_domains); igraphmodule_handle_igraph_error(); return NULL; } if (p_domains) igraph_vector_ptr_destroy_all(p_domains); if (!map) { if (result) Py_RETURN_TRUE; Py_RETURN_FALSE; } else { PyObject *m = igraphmodule_vector_t_to_PyList(map, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(map); if (!m) return NULL; return Py_BuildValue("ON", result ? Py_True : Py_False, m); } } /** \ingroup python_interface_graph * \brief Finds all the subisomorphisms of a graph to another graph using the LAD * algorithm * * \sa igraph_subisomorphic_lad */ PyObject *igraphmodule_Graph_get_subisomorphisms_lad( igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { PyObject *o, *domains_o=Py_None, *induced=Py_False, *result; float time_limit = 0; igraphmodule_GraphObject *other; igraph_vector_ptr_t domains; igraph_vector_ptr_t* p_domains = 0; igraph_vector_ptr_t mappings; static char *kwlist[] = { "pattern", "domains", "induced", "time_limit", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O!|OOf", kwlist, &igraphmodule_GraphType, &o, &domains_o, &induced, &time_limit)) return NULL; other=(igraphmodule_GraphObject*)o; if (domains_o != Py_None) { if (igraphmodule_PyObject_to_vector_ptr_t(domains_o, &domains, 1)) return NULL; p_domains = &domains; } if (igraph_vector_ptr_init(&mappings, 0)) { igraphmodule_handle_igraph_error(); if (p_domains) igraph_vector_ptr_destroy_all(p_domains); return NULL; } if (igraph_subisomorphic_lad(&other->g, &self->g, p_domains, 0, 0, &mappings, PyObject_IsTrue(induced), (int)time_limit)) { igraphmodule_handle_igraph_error(); igraph_vector_ptr_destroy_all(&mappings); if (p_domains) igraph_vector_ptr_destroy_all(p_domains); return NULL; } if (p_domains) igraph_vector_ptr_destroy_all(p_domains); result = igraphmodule_vector_ptr_t_to_PyList(&mappings, IGRAPHMODULE_TYPE_INT); igraph_vector_ptr_destroy_all(&mappings); return result; } /********************************************************************** * Graph attribute handling * **********************************************************************/ /** \ingroup python_interface_graph * \brief Returns the number of graph attributes */ Py_ssize_t igraphmodule_Graph_attribute_count(igraphmodule_GraphObject * self) { return PyDict_Size(((PyObject **) self->g.attr)[ATTRHASH_IDX_GRAPH]); } /** \ingroup python_interface_graph * \brief Handles the subscript operator on the graph. * * When the subscript is a string, returns the corresponding value of the * given attribute in the graph. When the subscript is a tuple of length * 2, retrieves the adjacency matrix representation of the graph between * some vertices. */ PyObject *igraphmodule_Graph_mp_subscript(igraphmodule_GraphObject * self, PyObject * s) { PyObject *result = 0; if (PyTuple_Check(s) && PyTuple_Size(s) >= 2) { /* Adjacency matrix representation */ PyObject *ri = PyTuple_GET_ITEM(s, 0); PyObject *ci = PyTuple_GET_ITEM(s, 1); PyObject *attr; if (PyTuple_Size(s) == 2) { attr = 0; } else if (PyTuple_Size(s) == 3) { attr = PyTuple_GET_ITEM(s, 2); } else { PyErr_SetString(PyExc_TypeError, "adjacency matrix indexing must use at most three arguments"); return 0; } return igraphmodule_Graph_adjmatrix_get_index(&self->g, ri, ci, attr); } /* Ordinary attribute retrieval */ result = PyDict_GetItem(ATTR_STRUCT_DICT(&self->g)[ATTRHASH_IDX_GRAPH], s); if (result) { Py_INCREF(result); return result; } /* result is NULL, check whether there was an error */ if (!PyErr_Occurred()) PyErr_SetString(PyExc_KeyError, "Attribute does not exist"); return NULL; } /** \ingroup python_interface_graph * \brief Handles the subscript assignment operator on the graph. * * If k is a string, sets the value of the corresponding attribute of the graph. * If k is a tuple of length 2, sets part of the adjacency matrix. * * \return 0 if everything's ok, -1 in case of error */ int igraphmodule_Graph_mp_assign_subscript(igraphmodule_GraphObject * self, PyObject * k, PyObject * v) { PyObject* dict = ATTR_STRUCT_DICT(&self->g)[ATTRHASH_IDX_GRAPH]; if (PyTuple_Check(k) && PyTuple_Size(k) >= 2) { /* Adjacency matrix representation */ PyObject *ri, *ci, *attr; if (v == NULL) { PyErr_SetString(PyExc_NotImplementedError, "cannot delete parts " "of the adjacency matrix of a graph"); return -1; } ri = PyTuple_GET_ITEM(k, 0); ci = PyTuple_GET_ITEM(k, 1); if (PyTuple_Size(k) == 2) { attr = 0; } else if (PyTuple_Size(k) == 3) { attr = PyTuple_GET_ITEM(k, 2); } else { PyErr_SetString(PyExc_TypeError, "adjacency matrix indexing must use at most three arguments"); return 0; } return igraphmodule_Graph_adjmatrix_set_index(&self->g, ri, ci, attr, v); } /* Ordinary attribute setting/deletion */ if (v == NULL) return PyDict_DelItem(dict, k); if (PyDict_SetItem(dict, k, v) == -1) return -1; return 0; } /** \ingroup python_interface_graph * \brief Returns the attribute list of the graph */ PyObject *igraphmodule_Graph_attributes(igraphmodule_GraphObject * self) { return PyDict_Keys(ATTR_STRUCT_DICT(&self->g)[ATTRHASH_IDX_GRAPH]); } /** \ingroup python_interface_graph * \brief Returns the attribute list of the graph's vertices */ PyObject *igraphmodule_Graph_vertex_attributes(igraphmodule_GraphObject * self) { return PyDict_Keys(ATTR_STRUCT_DICT(&self->g)[ATTRHASH_IDX_VERTEX]); } /** \ingroup python_interface_graph * \brief Returns the attribute list of the graph's edges */ PyObject *igraphmodule_Graph_edge_attributes(igraphmodule_GraphObject * self) { return PyDict_Keys(ATTR_STRUCT_DICT(&self->g)[ATTRHASH_IDX_EDGE]); } /********************************************************************** * Graph operations (union, intersection etc) * **********************************************************************/ /** \ingroup python_interface_graph * \brief Creates the disjoint union of two graphs (operator version) */ PyObject *igraphmodule_Graph_disjoint_union(igraphmodule_GraphObject * self, PyObject * other) { PyObject *it; igraphmodule_GraphObject *o, *result; igraph_t g; /* Did we receive an iterable? */ it = PyObject_GetIter(other); if (it) { /* Get all elements, store the graphs in an igraph_vector_ptr */ igraph_vector_ptr_t gs; if (igraph_vector_ptr_init(&gs, 0)) { Py_DECREF(it); return igraphmodule_handle_igraph_error(); } if (igraph_vector_ptr_push_back(&gs, &self->g)) { Py_DECREF(it); igraph_vector_ptr_destroy(&gs); return igraphmodule_handle_igraph_error(); } if (igraphmodule_append_PyIter_of_graphs_to_vector_ptr_t(it, &gs)) { igraph_vector_ptr_destroy(&gs); Py_DECREF(it); return NULL; } Py_DECREF(it); /* Create disjoint union */ if (igraph_disjoint_union_many(&g, &gs)) { igraph_vector_ptr_destroy(&gs); return igraphmodule_handle_igraph_error(); } igraph_vector_ptr_destroy(&gs); } else { PyErr_Clear(); if (!PyObject_TypeCheck(other, &igraphmodule_GraphType)) { Py_INCREF(Py_NotImplemented); return Py_NotImplemented; } o = (igraphmodule_GraphObject *) other; if (igraph_disjoint_union(&g, &self->g, &o->g)) { igraphmodule_handle_igraph_error(); return NULL; } } /* this is correct as long as attributes are not copied by the * operator. if they are copied, the initialization should not empty * the attribute hashes */ CREATE_GRAPH(result, g); return (PyObject *) result; } /** \ingroup python_interface_graph * \brief Creates the union of two graphs (operator version) */ PyObject *igraphmodule_Graph_union(igraphmodule_GraphObject * self, PyObject * other) { PyObject *it; igraphmodule_GraphObject *o, *result; igraph_t g; /* Did we receive an iterable? */ it = PyObject_GetIter(other); if (it) { /* Get all elements, store the graphs in an igraph_vector_ptr */ igraph_vector_ptr_t gs; if (igraph_vector_ptr_init(&gs, 0)) { Py_DECREF(it); return igraphmodule_handle_igraph_error(); } if (igraph_vector_ptr_push_back(&gs, &self->g)) { Py_DECREF(it); igraph_vector_ptr_destroy(&gs); return igraphmodule_handle_igraph_error(); } if (igraphmodule_append_PyIter_of_graphs_to_vector_ptr_t(it, &gs)) { Py_DECREF(it); igraph_vector_ptr_destroy(&gs); return NULL; } Py_DECREF(it); /* Create union */ if (igraph_union_many(&g, &gs, /*edgemaps=*/ 0)) { igraph_vector_ptr_destroy(&gs); igraphmodule_handle_igraph_error(); return NULL; } igraph_vector_ptr_destroy(&gs); } else { PyErr_Clear(); if (!PyObject_TypeCheck(other, &igraphmodule_GraphType)) { Py_INCREF(Py_NotImplemented); return Py_NotImplemented; } o = (igraphmodule_GraphObject *) other; if (igraph_union(&g, &self->g, &o->g, /*edge_map1=*/ 0, /*edge_map2=*/ 0)) { igraphmodule_handle_igraph_error(); return NULL; } } /* this is correct as long as attributes are not copied by the * operator. if they are copied, the initialization should not empty * the attribute hashes */ CREATE_GRAPH(result, g); return (PyObject *) result; } /** \ingroup python_interface_graph * \brief Creates the intersection of two graphs (operator version) */ PyObject *igraphmodule_Graph_intersection(igraphmodule_GraphObject * self, PyObject * other) { PyObject *it; igraphmodule_GraphObject *o, *result; igraph_t g; /* Did we receive an iterable? */ it = PyObject_GetIter(other); if (it) { /* Get all elements, store the graphs in an igraph_vector_ptr */ igraph_vector_ptr_t gs; if (igraph_vector_ptr_init(&gs, 0)) { Py_DECREF(it); return igraphmodule_handle_igraph_error(); } if (igraph_vector_ptr_push_back(&gs, &self->g)) { Py_DECREF(it); igraph_vector_ptr_destroy(&gs); return igraphmodule_handle_igraph_error(); } if (igraphmodule_append_PyIter_of_graphs_to_vector_ptr_t(it, &gs)) { Py_DECREF(it); igraph_vector_ptr_destroy(&gs); return NULL; } Py_DECREF(it); /* Create union */ if (igraph_intersection_many(&g, &gs, /*edgemaps=*/ 0)) { igraph_vector_ptr_destroy(&gs); igraphmodule_handle_igraph_error(); return NULL; } igraph_vector_ptr_destroy(&gs); } else { PyErr_Clear(); if (!PyObject_TypeCheck(other, &igraphmodule_GraphType)) { Py_INCREF(Py_NotImplemented); return Py_NotImplemented; } o = (igraphmodule_GraphObject *) other; if (igraph_intersection(&g, &self->g, &o->g, /*edge_map1=*/ 0, /*edge_map2=*/ 0)) { igraphmodule_handle_igraph_error(); return NULL; } } /* this is correct as long as attributes are not copied by the * operator. if they are copied, the initialization should not empty * the attribute hashes */ CREATE_GRAPH(result, g); return (PyObject *) result; } /** \ingroup python_interface_graph * \brief Creates the difference of two graphs (operator version) */ PyObject *igraphmodule_Graph_difference(igraphmodule_GraphObject * self, PyObject * other) { igraphmodule_GraphObject *o, *result; igraph_t g; if (!PyObject_TypeCheck(other, &igraphmodule_GraphType)) { Py_INCREF(Py_NotImplemented); return Py_NotImplemented; } o = (igraphmodule_GraphObject *) other; if (igraph_difference(&g, &self->g, &o->g)) { igraphmodule_handle_igraph_error(); return NULL; } /* this is correct as long as attributes are not copied by the * operator. if they are copied, the initialization should not empty * the attribute hashes */ CREATE_GRAPH(result, g); return (PyObject *) result; } /** \ingroup python_interface_graph * \brief Creates the complementer of a graph */ PyObject *igraphmodule_Graph_complementer(igraphmodule_GraphObject * self, PyObject * args) { igraphmodule_GraphObject *result; PyObject *o = Py_True; igraph_t g; if (!PyArg_ParseTuple(args, "|O", &o)) return NULL; if (igraph_complementer(&g, &self->g, PyObject_IsTrue(o))) { igraphmodule_handle_igraph_error(); return NULL; } /* this is correct as long as attributes are not copied by the * operator. if they are copied, the initialization should not empty * the attribute hashes */ CREATE_GRAPH(result, g); return (PyObject *) result; } /** \ingroup python_interface_graph * \brief Creates the complementer of a graph (operator version) */ PyObject *igraphmodule_Graph_complementer_op(igraphmodule_GraphObject * self) { igraphmodule_GraphObject *result; igraph_t g; if (igraph_complementer(&g, &self->g, 0)) { igraphmodule_handle_igraph_error(); return NULL; } /* this is correct as long as attributes are not copied by the * operator. if they are copied, the initialization should not empty * the attribute hashes */ CREATE_GRAPH(result, g); return (PyObject *) result; } /** \ingroup python_interface_graph * \brief Creates the composition of two graphs */ PyObject *igraphmodule_Graph_compose(igraphmodule_GraphObject * self, PyObject * other) { igraphmodule_GraphObject *o, *result; igraph_t g; if (!PyObject_TypeCheck(other, &igraphmodule_GraphType)) { Py_INCREF(Py_NotImplemented); return Py_NotImplemented; } o = (igraphmodule_GraphObject *) other; if (igraph_compose(&g, &self->g, &o->g, /*edge_map1=*/ 0, /*edge_map2=*/ 0)) { igraphmodule_handle_igraph_error(); return NULL; } /* this is correct as long as attributes are not copied by the * operator. if they are copied, the initialization should not empty * the attribute hashes */ CREATE_GRAPH(result, g); return (PyObject *) result; } /********************************************************************** * Graph traversal algorithms * **********************************************************************/ /** \ingroup python_interface_graph * \brief Conducts a breadth first search (BFS) on the graph */ PyObject *igraphmodule_Graph_bfs(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "vid", "mode", NULL }; long vid; PyObject *l1, *l2, *l3, *result, *mode_o=Py_None; igraph_neimode_t mode = IGRAPH_OUT; igraph_vector_t vids; igraph_vector_t layers; igraph_vector_t parents; if (!PyArg_ParseTupleAndKeywords(args, kwds, "l|O", kwlist, &vid, &mode_o)) return NULL; if (igraphmodule_PyObject_to_neimode_t(mode_o, &mode)) return NULL; if (igraph_vector_init(&vids, igraph_vcount(&self->g))) return igraphmodule_handle_igraph_error(); if (igraph_vector_init(&layers, igraph_vcount(&self->g))) { igraph_vector_destroy(&vids); return igraphmodule_handle_igraph_error(); } if (igraph_vector_init(&parents, igraph_vcount(&self->g))) { igraph_vector_destroy(&vids); igraph_vector_destroy(&parents); return igraphmodule_handle_igraph_error(); } if (igraph_i_bfs (&self->g, (igraph_integer_t) vid, mode, &vids, &layers, &parents)) { igraphmodule_handle_igraph_error(); return NULL; } l1 = igraphmodule_vector_t_to_PyList(&vids, IGRAPHMODULE_TYPE_INT); l2 = igraphmodule_vector_t_to_PyList(&layers, IGRAPHMODULE_TYPE_INT); l3 = igraphmodule_vector_t_to_PyList(&parents, IGRAPHMODULE_TYPE_INT); if (l1 && l2 && l3) { result = Py_BuildValue("NNN", l1, l2, l3); /* references stolen */ } else { if (l1) { Py_DECREF(l1); } if (l2) { Py_DECREF(l2); } if (l3) { Py_DECREF(l3); } result = NULL; } igraph_vector_destroy(&vids); igraph_vector_destroy(&layers); igraph_vector_destroy(&parents); return result; } /** \ingroup python_interface_graph * \brief Constructs a breadth first search (BFS) iterator of the graph */ PyObject *igraphmodule_Graph_bfsiter(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { char *kwlist[] = { "vid", "mode", "advanced", NULL }; PyObject *root, *adv = Py_False, *mode_o = Py_None; igraph_neimode_t mode = IGRAPH_OUT; if (!PyArg_ParseTupleAndKeywords (args, kwds, "O|OO", kwlist, &root, &mode_o, &adv)) return NULL; if (igraphmodule_PyObject_to_neimode_t(mode_o, &mode)) return NULL; return igraphmodule_BFSIter_new(self, root, mode, PyObject_IsTrue(adv)); } /** \ingroup python_interface_graph * \brief Unfolds a graph into a tree using BFS */ PyObject *igraphmodule_Graph_unfold_tree(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "roots", "mode", NULL }; igraphmodule_GraphObject *result_o; PyObject *mapping_o, *mode_o=Py_None, *roots_o=Py_None; igraph_neimode_t mode = IGRAPH_OUT; igraph_vs_t vs; igraph_vector_t mapping, vids; igraph_t result; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|O", kwlist, &roots_o, &mode_o)) return NULL; if (igraphmodule_PyObject_to_neimode_t(mode_o, &mode)) return NULL; if (igraphmodule_PyObject_to_vs_t(roots_o, &vs, &self->g, 0, 0)) return NULL; if (igraph_vector_init(&mapping, igraph_vcount(&self->g))) { igraph_vs_destroy(&vs); return igraphmodule_handle_igraph_error(); } if (igraph_vector_init(&vids, 0)) { igraph_vs_destroy(&vs); igraph_vector_destroy(&mapping); return igraphmodule_handle_igraph_error(); } if (igraph_vs_as_vector(&self->g, vs, &vids)) { igraph_vs_destroy(&vs); igraph_vector_destroy(&vids); igraph_vector_destroy(&mapping); return igraphmodule_handle_igraph_error(); } igraph_vs_destroy(&vs); if (igraph_unfold_tree(&self->g, &result, mode, &vids, &mapping)) { igraph_vector_destroy(&vids); igraph_vector_destroy(&mapping); igraphmodule_handle_igraph_error(); return NULL; } igraph_vector_destroy(&vids); mapping_o = igraphmodule_vector_t_to_PyList(&mapping, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&mapping); if (!mapping_o) { igraph_destroy(&result); return NULL; } CREATE_GRAPH(result_o, result); return Py_BuildValue("NN", result_o, mapping_o); } /********************************************************************** * Dominator * **********************************************************************/ /** \ingroup python_interface_graph * \brief Calculates the dominator tree for the graph */ PyObject *igraphmodule_Graph_dominator(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "vid", "mode", NULL }; PyObject *list = Py_None; PyObject *mode_o = Py_None; long int root = -1; igraph_vector_t dom; igraph_neimode_t mode = IGRAPH_OUT; int res ; if (!PyArg_ParseTupleAndKeywords(args, kwds, "l|O", kwlist, &root, &mode_o)) { return NULL; } if (igraphmodule_PyObject_to_neimode_t(mode_o, &mode)) { return NULL; } if (mode == IGRAPH_ALL) { mode = IGRAPH_OUT; } if (igraph_vector_init(&dom, 0)) { return NULL; } res = igraph_dominator_tree(&self->g, root, &dom, NULL, NULL, mode); if(res) { igraph_vector_destroy(&dom); return NULL; } list = igraphmodule_vector_t_to_PyList(&dom, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&dom); return list; } /********************************************************************** * Maximum flows * **********************************************************************/ /** \ingroup python_interface_graph * \brief Calculates the value of the maximum flow in the graph */ PyObject *igraphmodule_Graph_maxflow_value(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "source", "target", "capacity", NULL }; PyObject *capacity_object = Py_None; igraph_vector_t capacity_vector; igraph_real_t result; long int vid1 = -1, vid2 = -1; igraph_integer_t v1, v2; igraph_maxflow_stats_t stats; if (!PyArg_ParseTupleAndKeywords(args, kwds, "ll|O", kwlist, &vid1, &vid2, &capacity_object)) return NULL; v1 = (igraph_integer_t) vid1; v2 = (igraph_integer_t) vid2; if (igraphmodule_PyObject_to_attribute_values(capacity_object, &capacity_vector, self, ATTRHASH_IDX_EDGE, 1.0)) return igraphmodule_handle_igraph_error(); if (igraph_maxflow_value(&self->g, &result, v1, v2, &capacity_vector, &stats)) { igraph_vector_destroy(&capacity_vector); return igraphmodule_handle_igraph_error(); } igraph_vector_destroy(&capacity_vector); return Py_BuildValue("d", (double)result); } /** \ingroup python_interface_graph * \brief Calculates the maximum flow of the graph */ PyObject *igraphmodule_Graph_maxflow(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "source", "target", "capacity", NULL }; PyObject *capacity_object = Py_None, *flow_o, *cut_o, *partition_o; igraph_vector_t capacity_vector; igraph_real_t result; long int vid1 = -1, vid2 = -1; igraph_integer_t v1, v2; igraph_vector_t flow, cut, partition; igraph_maxflow_stats_t stats; if (!PyArg_ParseTupleAndKeywords(args, kwds, "ll|O", kwlist, &vid1, &vid2, &capacity_object)) return NULL; v1 = (igraph_integer_t) vid1; v2 = (igraph_integer_t) vid2; if (igraphmodule_PyObject_to_attribute_values(capacity_object, &capacity_vector, self, ATTRHASH_IDX_EDGE, 1.0)) return igraphmodule_handle_igraph_error(); if (igraph_vector_init(&flow, 0)) { igraph_vector_destroy(&capacity_vector); return igraphmodule_handle_igraph_error(); } if (igraph_vector_init(&cut, 0)) { igraph_vector_destroy(&capacity_vector); igraph_vector_destroy(&flow); return igraphmodule_handle_igraph_error(); } if (igraph_vector_init(&partition, 0)) { igraph_vector_destroy(&capacity_vector); igraph_vector_destroy(&flow); igraph_vector_destroy(&cut); return igraphmodule_handle_igraph_error(); } if (igraph_maxflow(&self->g, &result, &flow, &cut, &partition, 0, v1, v2, &capacity_vector, &stats)) { igraph_vector_destroy(&capacity_vector); igraph_vector_destroy(&flow); igraph_vector_destroy(&cut); igraph_vector_destroy(&partition); return igraphmodule_handle_igraph_error(); } igraph_vector_destroy(&capacity_vector); flow_o = igraphmodule_vector_t_to_PyList(&flow, IGRAPHMODULE_TYPE_FLOAT); igraph_vector_destroy(&flow); if (flow_o == NULL) { igraph_vector_destroy(&cut); igraph_vector_destroy(&partition); return NULL; } cut_o = igraphmodule_vector_t_to_PyList(&cut, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&cut); if (cut_o == NULL) { igraph_vector_destroy(&partition); return NULL; } partition_o = igraphmodule_vector_t_to_PyList(&partition, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&partition); if (partition_o == NULL) return NULL; return Py_BuildValue("dNNN", (double)result, flow_o, cut_o, partition_o); } /********************************************************************** * Minimum cuts (edge separators) * **********************************************************************/ /** \ingroup python_interface_graph * \brief Calculates all s-t cuts in a graph */ PyObject *igraphmodule_Graph_all_st_cuts(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "source", "target", NULL }; igraph_integer_t source, target; igraph_vector_ptr_t cuts, partition1s; PyObject *source_o, *target_o; PyObject *cuts_o, *partition1s_o; if (!PyArg_ParseTupleAndKeywords(args, kwds, "OO", kwlist, &source_o, &target_o)) return NULL; if (igraphmodule_PyObject_to_vid(source_o, &source, &self->g)) return NULL; if (igraphmodule_PyObject_to_vid(target_o, &target, &self->g)) return NULL; if (igraph_vector_ptr_init(&partition1s, 0)) { return igraphmodule_handle_igraph_error(); } if (igraph_vector_ptr_init(&cuts, 0)) { igraph_vector_ptr_destroy(&partition1s); return igraphmodule_handle_igraph_error(); } if (igraph_all_st_cuts(&self->g, &cuts, &partition1s, source, target)) { igraph_vector_ptr_destroy(&cuts); igraph_vector_ptr_destroy(&partition1s); return igraphmodule_handle_igraph_error(); } IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(&cuts, igraph_vector_destroy); IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(&partition1s, igraph_vector_destroy); cuts_o = igraphmodule_vector_ptr_t_to_PyList(&cuts, IGRAPHMODULE_TYPE_INT); igraph_vector_ptr_destroy_all(&cuts); if (cuts_o == NULL) { igraph_vector_ptr_destroy_all(&partition1s); return NULL; } partition1s_o = igraphmodule_vector_ptr_t_to_PyList(&partition1s, IGRAPHMODULE_TYPE_INT); igraph_vector_ptr_destroy_all(&partition1s); if (partition1s_o == NULL) return NULL; return Py_BuildValue("NN", cuts_o, partition1s_o); } /** \ingroup python_interface_graph * \brief Calculates all minimum s-t cuts in a graph */ PyObject *igraphmodule_Graph_all_st_mincuts(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "source", "target", "capacity", NULL }; igraph_integer_t source, target; igraph_real_t value; igraph_vector_ptr_t cuts, partition1s; igraph_vector_t capacity_vector; PyObject *source_o, *target_o, *capacity_o = Py_None; PyObject *cuts_o, *partition1s_o; if (!PyArg_ParseTupleAndKeywords(args, kwds, "OOO", kwlist, &source_o, &target_o, &capacity_o)) return NULL; if (igraphmodule_PyObject_to_vid(source_o, &source, &self->g)) return NULL; if (igraphmodule_PyObject_to_vid(target_o, &target, &self->g)) return NULL; if (igraph_vector_ptr_init(&partition1s, 0)) { return igraphmodule_handle_igraph_error(); } if (igraph_vector_ptr_init(&cuts, 0)) { igraph_vector_ptr_destroy(&partition1s); return igraphmodule_handle_igraph_error(); } if (igraphmodule_PyObject_to_attribute_values(capacity_o, &capacity_vector, self, ATTRHASH_IDX_EDGE, 1.0)) { igraph_vector_ptr_destroy(&cuts); igraph_vector_ptr_destroy(&partition1s); return igraphmodule_handle_igraph_error(); } if (igraph_all_st_mincuts(&self->g, &value, &cuts, &partition1s, source, target, &capacity_vector)) { igraph_vector_ptr_destroy(&cuts); igraph_vector_ptr_destroy(&partition1s); igraph_vector_destroy(&capacity_vector); return igraphmodule_handle_igraph_error(); } igraph_vector_destroy(&capacity_vector); IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(&cuts, igraph_vector_destroy); IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(&partition1s, igraph_vector_destroy); cuts_o = igraphmodule_vector_ptr_t_to_PyList(&cuts, IGRAPHMODULE_TYPE_INT); igraph_vector_ptr_destroy_all(&cuts); if (cuts_o == NULL) { igraph_vector_ptr_destroy_all(&partition1s); return NULL; } partition1s_o = igraphmodule_vector_ptr_t_to_PyList(&partition1s, IGRAPHMODULE_TYPE_INT); igraph_vector_ptr_destroy_all(&partition1s); if (partition1s_o == NULL) return NULL; return Py_BuildValue("dNN", (double)value, cuts_o, partition1s_o); } /** \ingroup python_interface_graph * \brief Calculates the value of the minimum cut in the graph */ PyObject *igraphmodule_Graph_mincut_value(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "source", "target", "capacity", NULL }; PyObject *capacity_object = Py_None; igraph_vector_t capacity_vector; igraph_real_t result, mincut; igraph_integer_t v1, v2; long vid1 = -1, vid2 = -1; long n; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|llO", kwlist, &vid1, &vid2, &capacity_object)) return NULL; if (igraphmodule_PyObject_to_attribute_values(capacity_object, &capacity_vector, self, ATTRHASH_IDX_EDGE, 1.0)) return igraphmodule_handle_igraph_error(); v1 = (igraph_integer_t) vid1; v2 = (igraph_integer_t) vid2; if (v1 == -1 && v2 == -1) { if (igraph_mincut_value(&self->g, &result, &capacity_vector)) { igraph_vector_destroy(&capacity_vector); return igraphmodule_handle_igraph_error(); } } else if (v1 == -1) { n = igraph_vcount(&self->g); result = -1; for (v1 = 0; v1 < n; v1++) { if (v2 == v1) continue; if (igraph_st_mincut_value(&self->g, &mincut, v1, v2, &capacity_vector)) { igraph_vector_destroy(&capacity_vector); return igraphmodule_handle_igraph_error(); } if (result < 0 || result > mincut) result = mincut; } if (result < 0) result = 0.0; } else if (v2 == -1) { n = igraph_vcount(&self->g); result = -1; for (v2 = 0; v2 < n; v2++) { if (v2 == v1) continue; if (igraph_st_mincut_value(&self->g, &mincut, v1, v2, &capacity_vector)) { igraph_vector_destroy(&capacity_vector); return igraphmodule_handle_igraph_error(); } if (result < 0.0 || result > mincut) result = mincut; } if (result < 0) result = 0.0; } else { if (igraph_st_mincut_value(&self->g, &result, v1, v2, &capacity_vector)) { igraph_vector_destroy(&capacity_vector); return igraphmodule_handle_igraph_error(); } } igraph_vector_destroy(&capacity_vector); return Py_BuildValue("d", (double)result); } /** \ingroup python_interface_graph * \brief Calculates a minimum cut in a graph */ PyObject *igraphmodule_Graph_mincut(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "source", "target", "capacity", NULL }; PyObject *capacity_object = Py_None, *cut_o, *part_o, *part2_o, *result; PyObject *source_o = Py_None, *target_o = Py_None; int retval; igraph_vector_t capacity_vector; igraph_real_t value; igraph_vector_t partition, partition2, cut; igraph_integer_t source = -1, target = -1; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOO", kwlist, &source_o, &target_o, &capacity_object)) return NULL; if (source_o != Py_None && igraphmodule_PyObject_to_vid(source_o, &source, &self->g)) return NULL; if (target_o != Py_None && igraphmodule_PyObject_to_vid(target_o, &target, &self->g)) return NULL; if (igraphmodule_PyObject_to_attribute_values(capacity_object, &capacity_vector, self, ATTRHASH_IDX_EDGE, 1.0)) return igraphmodule_handle_igraph_error(); if (igraph_vector_init(&partition, 0)) { igraph_vector_destroy(&capacity_vector); return igraphmodule_handle_igraph_error(); } if (igraph_vector_init(&partition2, 0)) { igraph_vector_destroy(&partition); igraph_vector_destroy(&capacity_vector); return igraphmodule_handle_igraph_error(); } if (igraph_vector_init(&cut, 0)) { igraph_vector_destroy(&partition); igraph_vector_destroy(&partition2); igraph_vector_destroy(&capacity_vector); return igraphmodule_handle_igraph_error(); } if (source == -1 && target == -1) { retval = igraph_mincut(&self->g, &value, &partition, &partition2, &cut, &capacity_vector); } else if (source == -1 || target == -1) { retval = IGRAPH_UNIMPLEMENTED; PyErr_SetString(PyExc_ValueError, "if you specify one of 'source' and 'target', " "you must specify the other one as well"); } else { retval = igraph_st_mincut(&self->g, &value, &cut, &partition, &partition2, source, target, &capacity_vector); } if (retval) { igraph_vector_destroy(&cut); igraph_vector_destroy(&partition); igraph_vector_destroy(&partition2); igraph_vector_destroy(&capacity_vector); if (!PyErr_Occurred()) igraphmodule_handle_igraph_error(); return NULL; } igraph_vector_destroy(&capacity_vector); cut_o=igraphmodule_vector_t_to_PyList(&cut, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&cut); if (!cut_o) { igraph_vector_destroy(&partition); igraph_vector_destroy(&partition2); return 0; } part_o=igraphmodule_vector_t_to_PyList(&partition, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&partition); if (!part_o) { Py_DECREF(cut_o); igraph_vector_destroy(&partition2); return 0; } part2_o=igraphmodule_vector_t_to_PyList(&partition2, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&partition2); if (!part2_o) { Py_DECREF(part_o); Py_DECREF(cut_o); return 0; } result = Py_BuildValue("dNNN", (double)value, cut_o, part_o, part2_o); return result; } /** \ingroup python_interface_graph * \brief Calculates the Gomory-Hu tree of an undirected graph */ PyObject *igraphmodule_Graph_gomory_hu_tree(igraphmodule_GraphObject * self, PyObject *args, PyObject *kwds) { static char* kwlist[] = { "capacity", NULL }; igraph_vector_t capacity_vector; igraph_vector_t flow_vector; igraph_t tree; PyObject *capacity_o = Py_None; PyObject *flow_o; igraphmodule_GraphObject *tree_o; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O", kwlist, &capacity_o)) return NULL; if (igraphmodule_PyObject_to_attribute_values(capacity_o, &capacity_vector, self, ATTRHASH_IDX_EDGE, 1.0)) return igraphmodule_handle_igraph_error(); if (igraph_vector_init(&flow_vector, 0)) { igraph_vector_destroy(&capacity_vector); return igraphmodule_handle_igraph_error(); } if (igraph_gomory_hu_tree(&self->g, &tree, &flow_vector, &capacity_vector)) { igraph_vector_destroy(&flow_vector); igraph_vector_destroy(&capacity_vector); return igraphmodule_handle_igraph_error(); } igraph_vector_destroy(&capacity_vector); flow_o = igraphmodule_vector_t_to_PyList(&flow_vector, IGRAPHMODULE_TYPE_FLOAT); igraph_vector_destroy(&flow_vector); if (!flow_o) { igraph_destroy(&tree); return 0; } CREATE_GRAPH(tree_o, tree); if (!tree_o) { igraph_destroy(&tree); return 0; } return Py_BuildValue("NN", tree_o, flow_o); } /** \ingroup python_interface_graph * \brief Calculates a minimum s-t cut in a graph */ PyObject *igraphmodule_Graph_st_mincut(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "source", "target", "capacity", NULL }; igraph_integer_t source, target; PyObject *cut_o, *part_o, *part2_o, *result; PyObject *source_o, *target_o, *capacity_o = Py_None; igraph_vector_t capacity_vector; igraph_real_t value; igraph_vector_t partition, partition2, cut; if (!PyArg_ParseTupleAndKeywords(args, kwds, "OOO", kwlist, &source_o, &target_o, &capacity_o)) return NULL; if (igraphmodule_PyObject_to_vid(source_o, &source, &self->g)) return NULL; if (igraphmodule_PyObject_to_vid(target_o, &target, &self->g)) return NULL; if (igraphmodule_PyObject_to_attribute_values(capacity_o, &capacity_vector, self, ATTRHASH_IDX_EDGE, 1.0)) return igraphmodule_handle_igraph_error(); if (igraph_vector_init(&partition, 0)) { igraph_vector_destroy(&capacity_vector); return igraphmodule_handle_igraph_error(); } if (igraph_vector_init(&partition2, 0)) { igraph_vector_destroy(&partition); igraph_vector_destroy(&capacity_vector); return igraphmodule_handle_igraph_error(); } if (igraph_vector_init(&cut, 0)) { igraph_vector_destroy(&partition); igraph_vector_destroy(&partition2); igraph_vector_destroy(&capacity_vector); return igraphmodule_handle_igraph_error(); } if (igraph_st_mincut(&self->g, &value, &cut, &partition, &partition2, source, target, &capacity_vector)) { igraph_vector_destroy(&cut); igraph_vector_destroy(&partition); igraph_vector_destroy(&partition2); igraph_vector_destroy(&capacity_vector); return igraphmodule_handle_igraph_error(); } igraph_vector_destroy(&capacity_vector); cut_o=igraphmodule_vector_t_to_PyList(&cut, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&cut); if (!cut_o) { igraph_vector_destroy(&partition); igraph_vector_destroy(&partition2); return NULL; } part_o=igraphmodule_vector_t_to_PyList(&partition, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&partition); if (!part_o) { Py_DECREF(cut_o); igraph_vector_destroy(&partition2); return NULL; } part2_o=igraphmodule_vector_t_to_PyList(&partition2, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&partition2); if (!part2_o) { Py_DECREF(part_o); Py_DECREF(cut_o); return NULL; } result = Py_BuildValue("dNNN", (double)value, cut_o, part_o, part2_o); return result; } /********************************************************************** * Vertex separators * **********************************************************************/ /** \ingroup python_interface_graph * \brief Returns all minimal s-t separators of a graph */ PyObject *igraphmodule_Graph_all_minimal_st_separators( igraphmodule_GraphObject * self) { PyObject* result_o; igraph_vector_ptr_t result; if (igraph_vector_ptr_init(&result, 0)) { igraphmodule_handle_igraph_error(); return NULL; } if (igraph_all_minimal_st_separators(&self->g, &result)) { igraphmodule_handle_igraph_error(); igraph_vector_ptr_destroy(&result); return NULL; } result_o = igraphmodule_vector_ptr_t_to_PyList(&result, IGRAPHMODULE_TYPE_INT); IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(&result, igraph_vector_destroy); igraph_vector_ptr_destroy_all(&result); return result_o; } /** \ingroup python_interface_graph * \brief Checks whether a given vertex set is a vertex separator */ PyObject *igraphmodule_Graph_is_separator(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { PyObject* list = Py_None; igraph_bool_t result; igraph_vs_t vs; static char *kwlist[] = { "vertices", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O", kwlist, &list)) return NULL; if (igraphmodule_PyObject_to_vs_t(list, &vs, &self->g, 0, 0)) { return NULL; } if (igraph_is_separator(&self->g, vs, &result)) { igraphmodule_handle_igraph_error(); igraph_vs_destroy(&vs); return NULL; } igraph_vs_destroy(&vs); if (result) Py_RETURN_TRUE; else Py_RETURN_FALSE; } /** \ingroup python_interface_graph * \brief Checks whether a given vertex set is a minimal vertex separator */ PyObject *igraphmodule_Graph_is_minimal_separator(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { PyObject* list = Py_None; igraph_bool_t result; igraph_vs_t vs; static char *kwlist[] = { "vertices", NULL }; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O", kwlist, &list)) return NULL; if (igraphmodule_PyObject_to_vs_t(list, &vs, &self->g, 0, 0)) { return NULL; } if (igraph_is_minimal_separator(&self->g, vs, &result)) { igraphmodule_handle_igraph_error(); igraph_vs_destroy(&vs); return NULL; } igraph_vs_destroy(&vs); if (result) Py_RETURN_TRUE; else Py_RETURN_FALSE; } /** \ingroup python_interface_graph * \brief Returns the minimum size separators of the graph */ PyObject *igraphmodule_Graph_minimum_size_separators( igraphmodule_GraphObject * self) { PyObject* result_o; igraph_vector_ptr_t result; if (igraph_vector_ptr_init(&result, 0)) { igraphmodule_handle_igraph_error(); return NULL; } if (igraph_minimum_size_separators(&self->g, &result)) { igraphmodule_handle_igraph_error(); igraph_vector_ptr_destroy(&result); return NULL; } result_o = igraphmodule_vector_ptr_t_to_PyList(&result, IGRAPHMODULE_TYPE_INT); IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(&result, igraph_vector_destroy); igraph_vector_ptr_destroy_all(&result); return result_o; } /********************************************************************** * Cohesive blocks * **********************************************************************/ /** \ingroup python_interface_graph * \brief Calculates the cohesive block structure of a graph */ PyObject *igraphmodule_Graph_cohesive_blocks(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { PyObject *blocks_o, *cohesion_o, *parents_o, *result_o; igraph_vector_ptr_t blocks; igraph_vector_t cohesion, parents; if (igraph_vector_ptr_init(&blocks, 0)) { igraphmodule_handle_igraph_error(); return NULL; } if (igraph_vector_init(&cohesion, 0)) { igraph_vector_ptr_destroy(&blocks); igraphmodule_handle_igraph_error(); return NULL; } if (igraph_vector_init(&parents, 0)) { igraph_vector_ptr_destroy(&blocks); igraph_vector_destroy(&cohesion); igraphmodule_handle_igraph_error(); return NULL; } if (igraph_cohesive_blocks(&self->g, &blocks, &cohesion, &parents, 0)) { igraph_vector_ptr_destroy(&blocks); igraph_vector_destroy(&cohesion); igraph_vector_destroy(&parents); igraphmodule_handle_igraph_error(); return NULL; } blocks_o = igraphmodule_vector_ptr_t_to_PyList(&blocks, IGRAPHMODULE_TYPE_INT); IGRAPH_VECTOR_PTR_SET_ITEM_DESTRUCTOR(&blocks, igraph_vector_destroy); igraph_vector_ptr_destroy_all(&blocks); if (blocks_o == NULL) { igraph_vector_destroy(&parents); igraph_vector_destroy(&cohesion); return NULL; } cohesion_o = igraphmodule_vector_t_to_PyList(&cohesion, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&cohesion); if (cohesion_o == NULL) { Py_DECREF(blocks_o); igraph_vector_destroy(&parents); return NULL; } parents_o = igraphmodule_vector_t_to_PyList(&parents, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&parents); if (parents_o == NULL) { Py_DECREF(blocks_o); Py_DECREF(cohesion_o); return NULL; } result_o = Py_BuildValue("NNN", blocks_o, cohesion_o, parents_o); if (result_o == NULL) { Py_DECREF(parents_o); Py_DECREF(blocks_o); Py_DECREF(cohesion_o); return NULL; } return result_o; } /********************************************************************** * Cliques and independent sets * **********************************************************************/ /** \ingroup python_interface_graph * \brief Find all or some cliques in a graph */ PyObject *igraphmodule_Graph_cliques(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "min", "max", NULL }; PyObject *list, *item; long int min_size = 0, max_size = 0; long int i, j, n; igraph_vector_ptr_t result; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|ll", kwlist, &min_size, &max_size)) return NULL; if (igraph_vector_ptr_init(&result, 0)) { PyErr_SetString(PyExc_MemoryError, ""); return NULL; } if (igraph_cliques(&self->g, &result, (igraph_integer_t) min_size, (igraph_integer_t) max_size)) { igraph_vector_ptr_destroy(&result); return igraphmodule_handle_igraph_error(); } n = (long)igraph_vector_ptr_size(&result); list = PyList_New(n); if (!list) return NULL; for (i = 0; i < n; i++) { igraph_vector_t *vec = (igraph_vector_t *) VECTOR(result)[i]; item = igraphmodule_vector_t_to_PyTuple(vec); if (!item) { for (j = i; j < n; j++) igraph_vector_destroy((igraph_vector_t *) VECTOR(result)[j]); igraph_vector_ptr_destroy_all(&result); Py_DECREF(list); return NULL; } else { PyList_SET_ITEM(list, i, item); } igraph_vector_destroy(vec); } igraph_vector_ptr_destroy_all(&result); return list; } /** \ingroup python_interface_graph * \brief Find all largest cliques in a graph */ PyObject *igraphmodule_Graph_largest_cliques(igraphmodule_GraphObject * self) { PyObject *list, *item; long int i, j, n; igraph_vector_ptr_t result; if (igraph_vector_ptr_init(&result, 0)) { PyErr_SetString(PyExc_MemoryError, ""); return NULL; } if (igraph_largest_cliques(&self->g, &result)) { igraph_vector_ptr_destroy(&result); return igraphmodule_handle_igraph_error(); } n = (long)igraph_vector_ptr_size(&result); list = PyList_New(n); if (!list) return NULL; for (i = 0; i < n; i++) { igraph_vector_t *vec = (igraph_vector_t *) VECTOR(result)[i]; item = igraphmodule_vector_t_to_PyTuple(vec); if (!item) { for (j = i; j < n; j++) igraph_vector_destroy((igraph_vector_t *) VECTOR(result)[j]); igraph_vector_ptr_destroy_all(&result); Py_DECREF(list); return NULL; } else { PyList_SET_ITEM(list, i, item); } igraph_vector_destroy(vec); } igraph_vector_ptr_destroy_all(&result); return list; } /** \ingroup python_interface_graph * \brief Finds a maximum matching in a bipartite graph */ PyObject *igraphmodule_Graph_maximum_bipartite_matching(igraphmodule_GraphObject* self, PyObject* args, PyObject* kwds) { static char* kwlist[] = { "types", "weights", "eps", NULL }; PyObject *types_o = Py_None, *weights_o = Py_None, *result_o; igraph_vector_bool_t* types = 0; igraph_vector_t* weights = 0; igraph_vector_long_t result; double eps = -1; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|Od", kwlist, &types_o, &weights_o, &eps)) return NULL; if (eps < 0) eps = DBL_EPSILON * 1000; if (igraphmodule_attrib_to_vector_bool_t(types_o, self, &types, ATTRIBUTE_TYPE_VERTEX)) return NULL; if (igraphmodule_attrib_to_vector_t(weights_o, self, &weights, ATTRIBUTE_TYPE_EDGE)) { if (types != 0) { igraph_vector_bool_destroy(types); free(types); } return NULL; } if (igraph_vector_long_init(&result, 0)) { if (types != 0) { igraph_vector_bool_destroy(types); free(types); } if (weights != 0) { igraph_vector_destroy(weights); free(weights); } igraphmodule_handle_igraph_error(); return NULL; } if (igraph_maximum_bipartite_matching(&self->g, types, 0, 0, &result, weights, eps)) { if (types != 0) { igraph_vector_bool_destroy(types); free(types); } if (weights != 0) { igraph_vector_destroy(weights); free(weights); } igraph_vector_long_destroy(&result); igraphmodule_handle_igraph_error(); return NULL; } if (types != 0) { igraph_vector_bool_destroy(types); free(types); } if (weights != 0) { igraph_vector_destroy(weights); free(weights); } result_o = igraphmodule_vector_long_t_to_PyList(&result); igraph_vector_long_destroy(&result); return result_o; } /** \ingroup python_interface_graph * \brief Find all maximal cliques in a graph */ PyObject *igraphmodule_Graph_maximal_cliques(igraphmodule_GraphObject * self, PyObject* args, PyObject* kwds) { static char* kwlist[] = { "min", "max", "file", NULL }; PyObject *list, *item, *file = Py_None; long int i = 0, j = 0; igraph_integer_t min, max; Py_ssize_t n; igraph_vector_ptr_t result; igraphmodule_filehandle_t filehandle; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|llO", kwlist, &i, &j, &file)) return NULL; min = (igraph_integer_t) i; max = (igraph_integer_t) j; if (file == Py_None) { if (igraph_vector_ptr_init(&result, 0)) { PyErr_SetString(PyExc_MemoryError, ""); return NULL; } if (igraph_maximal_cliques(&self->g, &result, min, max)) { igraph_vector_ptr_destroy(&result); return igraphmodule_handle_igraph_error(); } n = (Py_ssize_t)igraph_vector_ptr_size(&result); list = PyList_New(n); if (!list) return NULL; for (i = 0; i < n; i++) { igraph_vector_t *vec = (igraph_vector_t *) VECTOR(result)[i]; item = igraphmodule_vector_t_to_PyTuple(vec); if (!item) { for (j = i; j < n; j++) igraph_vector_destroy((igraph_vector_t *) VECTOR(result)[j]); igraph_vector_ptr_destroy_all(&result); Py_DECREF(list); return NULL; } else { PyList_SET_ITEM(list, i, item); } igraph_vector_destroy(vec); } igraph_vector_ptr_destroy_all(&result); return list; } else { if (igraphmodule_filehandle_init(&filehandle, file, "w")) { return igraphmodule_handle_igraph_error(); } if (igraph_maximal_cliques_file(&self->g, igraphmodule_filehandle_get(&filehandle), min, max)) { igraphmodule_filehandle_destroy(&filehandle); return igraphmodule_handle_igraph_error(); } igraphmodule_filehandle_destroy(&filehandle); Py_RETURN_NONE; } } /** \ingroup python_interface_graph * \brief Returns the clique number of the graph */ PyObject *igraphmodule_Graph_clique_number(igraphmodule_GraphObject * self) { PyObject *result; igraph_integer_t i; if (igraph_clique_number(&self->g, &i)) return igraphmodule_handle_igraph_error(); result = PyInt_FromLong((long)i); return result; } /** \ingroup python_interface_graph * \brief Find all or some independent vertex sets in a graph */ PyObject *igraphmodule_Graph_independent_vertex_sets(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "min", "max", NULL }; PyObject *list, *item; long int min_size = 0, max_size = 0; long int i, j, n; igraph_vector_ptr_t result; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|ll", kwlist, &min_size, &max_size)) return NULL; if (igraph_vector_ptr_init(&result, 0)) { PyErr_SetString(PyExc_MemoryError, ""); return NULL; } if (igraph_independent_vertex_sets(&self->g, &result, (igraph_integer_t) min_size, (igraph_integer_t) max_size)) { igraph_vector_ptr_destroy(&result); return igraphmodule_handle_igraph_error(); } n = (long)igraph_vector_ptr_size(&result); list = PyList_New(n); if (!list) return NULL; for (i = 0; i < n; i++) { igraph_vector_t *vec = (igraph_vector_t *) VECTOR(result)[i]; item = igraphmodule_vector_t_to_PyTuple(vec); if (!item) { for (j = i; j < n; j++) igraph_vector_destroy((igraph_vector_t *) VECTOR(result)[j]); igraph_vector_ptr_destroy_all(&result); Py_DECREF(list); return NULL; } else { PyList_SET_ITEM(list, i, item); } igraph_vector_destroy(vec); } igraph_vector_ptr_destroy_all(&result); return list; } /** \ingroup python_interface_graph * \brief Find all largest independent_vertex_sets in a graph */ PyObject *igraphmodule_Graph_largest_independent_vertex_sets(igraphmodule_GraphObject * self) { PyObject *list, *item; long int i, j, n; igraph_vector_ptr_t result; if (igraph_vector_ptr_init(&result, 0)) { PyErr_SetString(PyExc_MemoryError, ""); return NULL; } if (igraph_largest_independent_vertex_sets(&self->g, &result)) { igraph_vector_ptr_destroy(&result); return igraphmodule_handle_igraph_error(); } n = (long)igraph_vector_ptr_size(&result); list = PyList_New(n); if (!list) return NULL; for (i = 0; i < n; i++) { igraph_vector_t *vec = (igraph_vector_t *) VECTOR(result)[i]; item = igraphmodule_vector_t_to_PyTuple(vec); if (!item) { for (j = i; j < n; j++) igraph_vector_destroy((igraph_vector_t *) VECTOR(result)[j]); igraph_vector_ptr_destroy_all(&result); Py_DECREF(list); return NULL; } else { PyList_SET_ITEM(list, i, item); } igraph_vector_destroy(vec); } igraph_vector_ptr_destroy_all(&result); return list; } /** \ingroup python_interface_graph * \brief Find all maximal independent vertex sets in a graph */ PyObject *igraphmodule_Graph_maximal_independent_vertex_sets(igraphmodule_GraphObject * self) { PyObject *list, *item; long int i, j, n; igraph_vector_ptr_t result; if (igraph_vector_ptr_init(&result, 0)) { PyErr_SetString(PyExc_MemoryError, ""); return NULL; } if (igraph_maximal_independent_vertex_sets(&self->g, &result)) { igraph_vector_ptr_destroy(&result); return igraphmodule_handle_igraph_error(); } n = (long)igraph_vector_ptr_size(&result); list = PyList_New(n); if (!list) return NULL; for (i = 0; i < n; i++) { igraph_vector_t *vec = (igraph_vector_t *) VECTOR(result)[i]; item = igraphmodule_vector_t_to_PyTuple(vec); if (!item) { for (j = i; j < n; j++) igraph_vector_destroy((igraph_vector_t *) VECTOR(result)[j]); igraph_vector_ptr_destroy_all(&result); Py_DECREF(list); return NULL; } else { PyList_SET_ITEM(list, i, item); } igraph_vector_destroy(vec); } igraph_vector_ptr_destroy_all(&result); return list; } /** \ingroup python_interface_graph * \brief Returns the independence number of the graph */ PyObject *igraphmodule_Graph_independence_number(igraphmodule_GraphObject * self) { PyObject *result; igraph_integer_t i; if (igraph_independence_number(&self->g, &i)) return igraphmodule_handle_igraph_error(); result = PyInt_FromLong((long)i); return result; } /********************************************************************** * K-core decomposition * **********************************************************************/ /** \ingroup python_interface_graph * \brief Returns the corenesses of the graph vertices * \return a new PyCObject */ PyObject *igraphmodule_Graph_coreness(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "mode", NULL }; igraph_neimode_t mode = IGRAPH_ALL; igraph_vector_t result; PyObject *o, *mode_o = Py_None; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O", kwlist, &mode_o)) return NULL; if (igraphmodule_PyObject_to_neimode_t(mode_o, &mode)) return NULL; if (igraph_vector_init(&result, igraph_vcount(&self->g))) return igraphmodule_handle_igraph_error(); if (igraph_coreness(&self->g, &result, mode)) { igraph_vector_destroy(&result); return igraphmodule_handle_igraph_error(); } o = igraphmodule_vector_t_to_PyList(&result, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&result); return o; } /********************************************************************** * Community structure detection and related routines * **********************************************************************/ /** * Modularity calculation */ PyObject *igraphmodule_Graph_modularity(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = {"membership", "weights", 0}; igraph_vector_t membership; igraph_vector_t *weights=0; igraph_real_t modularity; PyObject *mvec, *wvec=Py_None; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|O", kwlist, &mvec, &wvec)) return NULL; if (igraphmodule_PyObject_to_vector_t(mvec, &membership, 1)) return NULL; if (igraphmodule_attrib_to_vector_t(wvec, self, &weights, ATTRIBUTE_TYPE_EDGE)){ igraph_vector_destroy(&membership); return NULL; } if (igraph_modularity(&self->g, &membership, &modularity, weights)) { igraph_vector_destroy(&membership); if (weights) { igraph_vector_destroy(weights); free(weights); } return NULL; } igraph_vector_destroy(&membership); if (weights) { igraph_vector_destroy(weights); free(weights); } return Py_BuildValue("d", (double)modularity); } /** * Newman's edge betweenness method */ PyObject *igraphmodule_Graph_community_edge_betweenness(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = { "directed", "weights", NULL }; PyObject *directed = Py_True; PyObject *weights_o = Py_None; PyObject *res, *qs, *ms; igraph_matrix_t merges; igraph_vector_t q; igraph_vector_t *weights = 0; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OO", kwlist, &directed, &weights_o)) return NULL; if (igraphmodule_attrib_to_vector_t(weights_o, self, &weights, ATTRIBUTE_TYPE_EDGE)) return NULL; if (igraph_matrix_init(&merges, 0, 0)) { if (weights != 0) { igraph_vector_destroy(weights); free(weights); } return igraphmodule_handle_igraph_error(); } if (igraph_vector_init(&q, 0)) { igraph_matrix_destroy(&merges); if (weights != 0) { igraph_vector_destroy(weights); free(weights); } return igraphmodule_handle_igraph_error(); } if (igraph_community_edge_betweenness(&self->g, /* removed_edges = */ 0, /* edge_betweenness = */ 0, /* merges = */ &merges, /* bridges = */ 0, /* modularity = */ weights ? 0 : &q, /* membership = */ 0, PyObject_IsTrue(directed), weights)) { igraphmodule_handle_igraph_error(); if (weights != 0) { igraph_vector_destroy(weights); free(weights); } igraph_matrix_destroy(&merges); igraph_vector_destroy(&q); return NULL; } if (weights != 0) { igraph_vector_destroy(weights); free(weights); } if (weights == 0) { /* Calculate modularity vector only in the unweighted case as we don't * calculate modularities for the weighted case */ qs=igraphmodule_vector_t_to_PyList(&q, IGRAPHMODULE_TYPE_FLOAT); igraph_vector_destroy(&q); if (!qs) { igraph_matrix_destroy(&merges); return NULL; } } else { qs = Py_None; Py_INCREF(qs); } ms=igraphmodule_matrix_t_to_PyList(&merges, IGRAPHMODULE_TYPE_INT); igraph_matrix_destroy(&merges); if (ms == NULL) { Py_DECREF(qs); return NULL; } res=Py_BuildValue("NN", ms, qs); /* steals references */ return res; } /** * Newman's leading eigenvector method, precise implementation */ PyObject *igraphmodule_Graph_community_leading_eigenvector(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = { "n", "weights", "arpack_options", NULL }; long int n=-1; PyObject *cl, *res, *merges, *weights_obj = Py_None; igraph_vector_t members; igraph_vector_t *weights = 0; igraph_matrix_t m; igraph_real_t q; igraphmodule_ARPACKOptionsObject *arpack_options; PyObject *arpack_options_o = igraphmodule_arpack_options_default; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|lOO!", kwlist, &n, &weights_obj, &igraphmodule_ARPACKOptionsType, &arpack_options_o)) { return NULL; } if (igraph_vector_init(&members, 0)) return igraphmodule_handle_igraph_error(); if (igraph_matrix_init(&m, 0, 0)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&members); return 0; } if (n<0) n = igraph_vcount(&self->g); else n -= 1; if (igraphmodule_attrib_to_vector_t(weights_obj, self, &weights, ATTRIBUTE_TYPE_EDGE)) { igraph_matrix_destroy(&m); igraph_vector_destroy(&members); return NULL; } arpack_options = (igraphmodule_ARPACKOptionsObject*)arpack_options_o; if (igraph_community_leading_eigenvector(&self->g, weights, &m, &members, (igraph_integer_t) n, igraphmodule_ARPACKOptions_get(arpack_options), &q, 0, 0, 0, 0, 0, 0)){ igraph_matrix_destroy(&m); igraph_vector_destroy(&members); if (weights != 0) { igraph_vector_destroy(weights); free(weights); } return igraphmodule_handle_igraph_error(); } if (weights != 0) { igraph_vector_destroy(weights); free(weights); } cl = igraphmodule_vector_t_to_PyList(&members, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&members); if (cl == 0) { igraph_matrix_destroy(&m); return 0; } merges = igraphmodule_matrix_t_to_PyList(&m, IGRAPHMODULE_TYPE_INT); igraph_matrix_destroy(&m); if (merges == 0) return 0; res=Py_BuildValue("NNd", cl, merges, (double)q); return res; } /** * Clauset et al's greedy modularity optimization algorithm */ PyObject *igraphmodule_Graph_community_fastgreedy(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "weights", NULL }; PyObject *ms, *qs, *res, *weights = Py_None; igraph_matrix_t merges; igraph_vector_t q, *ws=0; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O", kwlist, &weights)) { return NULL; } if (igraphmodule_attrib_to_vector_t(weights, self, &ws, ATTRIBUTE_TYPE_EDGE)) return NULL; igraph_matrix_init(&merges, 0, 0); igraph_vector_init(&q, 0); if (igraph_community_fastgreedy(&self->g, ws, &merges, &q, 0)) { if (ws) { igraph_vector_destroy(ws); free(ws); } igraph_vector_destroy(&q); igraph_matrix_destroy(&merges); return igraphmodule_handle_igraph_error(); } if (ws) { igraph_vector_destroy(ws); free(ws); } qs=igraphmodule_vector_t_to_PyList(&q, IGRAPHMODULE_TYPE_FLOAT); igraph_vector_destroy(&q); if (!qs) { igraph_matrix_destroy(&merges); return NULL; } ms=igraphmodule_matrix_t_to_PyList(&merges, IGRAPHMODULE_TYPE_INT); igraph_matrix_destroy(&merges); if (ms == NULL) { Py_DECREF(qs); return NULL; } res=Py_BuildValue("NN", ms, qs); /* steals references */ return res; } /** * Infomap community detection algorithm of Martin Rosvall and Carl T. Bergstrom, */ PyObject *igraphmodule_Graph_community_infomap(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "edge_weights", "vertex_weights", "trials", NULL }; PyObject *e_weights = Py_None, *v_weights = Py_None; unsigned int nb_trials = 10; igraph_vector_t *e_ws = 0, *v_ws = 0; igraph_vector_t membership; PyObject *res = Py_False; igraph_real_t codelength; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOI", kwlist, &e_weights, &v_weights, &nb_trials)) { return NULL; } if (igraph_vector_init(&membership, igraph_vcount(&self->g))) { igraphmodule_handle_igraph_error(); return NULL; } if (igraphmodule_attrib_to_vector_t(e_weights, self, &e_ws, ATTRIBUTE_TYPE_EDGE)) { igraph_vector_destroy(&membership); return NULL; } if (igraphmodule_attrib_to_vector_t(v_weights, self, &v_ws, ATTRIBUTE_TYPE_VERTEX)){ igraph_vector_destroy(&membership); if (e_ws) { igraph_vector_destroy(e_ws); free(e_ws); } return NULL; } if (igraph_community_infomap(/*in */ &self->g, /*e_weight=*/ e_ws, /*v_weight=*/ v_ws, /*nb_trials=*/nb_trials, /*out*/ &membership, &codelength)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&membership); if (e_ws) { igraph_vector_destroy(e_ws); free(e_ws); } if (v_ws) { igraph_vector_destroy(v_ws); free(v_ws); } return NULL; } if (e_ws) { igraph_vector_destroy(e_ws); free(e_ws); } if (v_ws) { igraph_vector_destroy(v_ws); free(v_ws); } res = igraphmodule_vector_t_to_PyList(&membership, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&membership); if (!res) return NULL; return Py_BuildValue("Nd", res, (double)codelength); } /** * The label propagation algorithm of Raghavan et al */ PyObject *igraphmodule_Graph_community_label_propagation( igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = { "weights", "initial", "fixed", NULL }; PyObject *weights_o = Py_None, *initial_o = Py_None, *fixed_o = Py_None; PyObject *result; igraph_vector_t membership, *ws = 0, *initial = 0; igraph_vector_bool_t fixed; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOO", kwlist, &weights_o, &initial_o, &fixed_o)) { return NULL; } if (fixed_o != Py_None) { if (igraphmodule_PyObject_to_vector_bool_t(fixed_o, &fixed)) return NULL; } if (igraphmodule_attrib_to_vector_t(weights_o, self, &ws, ATTRIBUTE_TYPE_EDGE)) { if (fixed_o != Py_None) igraph_vector_bool_destroy(&fixed); return NULL; } if (igraphmodule_attrib_to_vector_t(initial_o, self, &initial, ATTRIBUTE_TYPE_VERTEX)){ if (fixed_o != Py_None) igraph_vector_bool_destroy(&fixed); if (ws) { igraph_vector_destroy(ws); free(ws); } return NULL; } igraph_vector_init(&membership, igraph_vcount(&self->g)); if (igraph_community_label_propagation(&self->g, &membership, ws, initial, (fixed_o != Py_None ? &fixed : 0), 0)) { if (fixed_o != Py_None) igraph_vector_bool_destroy(&fixed); if (ws) { igraph_vector_destroy(ws); free(ws); } if (initial) { igraph_vector_destroy(initial); free(initial); } igraph_vector_destroy(&membership); return igraphmodule_handle_igraph_error(); } if (fixed_o != Py_None) igraph_vector_bool_destroy(&fixed); if (ws) { igraph_vector_destroy(ws); free(ws); } if (initial) { igraph_vector_destroy(initial); free(initial); } result=igraphmodule_vector_t_to_PyList(&membership, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&membership); return result; } /** * Multilevel algorithm of Blondel et al */ PyObject *igraphmodule_Graph_community_multilevel(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = { "weights", "return_levels", NULL }; PyObject *return_levels = Py_False; PyObject *mss, *qs, *res, *weights = Py_None; igraph_matrix_t memberships; igraph_vector_t membership, modularity; igraph_vector_t *ws; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OO", kwlist, &weights, &return_levels)) { return NULL; } if (igraphmodule_attrib_to_vector_t(weights, self, &ws, ATTRIBUTE_TYPE_EDGE)) return NULL; igraph_matrix_init(&memberships, 0, 0); igraph_vector_init(&membership, 0); igraph_vector_init(&modularity, 0); if (igraph_community_multilevel(&self->g, ws, &membership, &memberships, &modularity)) { if (ws) { igraph_vector_destroy(ws); free(ws); } igraph_vector_destroy(&membership); igraph_vector_destroy(&modularity); igraph_matrix_destroy(&memberships); return igraphmodule_handle_igraph_error(); } if (ws) { igraph_vector_destroy(ws); free(ws); } qs=igraphmodule_vector_t_to_PyList(&modularity, IGRAPHMODULE_TYPE_FLOAT); igraph_vector_destroy(&modularity); if (!qs) { igraph_vector_destroy(&membership); igraph_matrix_destroy(&memberships); return NULL; } if (PyObject_IsTrue(return_levels)) { mss=igraphmodule_matrix_t_to_PyList(&memberships, IGRAPHMODULE_TYPE_INT); if (!mss) { res = mss; } else { res=Py_BuildValue("NN", mss, qs); /* steals references */ } } else { res=igraphmodule_vector_t_to_PyList(&membership, IGRAPHMODULE_TYPE_INT); } igraph_vector_destroy(&membership); igraph_matrix_destroy(&memberships); return res; } /** * Optimal modularity by integer programming */ PyObject *igraphmodule_Graph_community_optimal_modularity( igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = {"weights", NULL}; PyObject *weights_o = Py_None; igraph_real_t modularity; igraph_vector_t membership; igraph_vector_t* weights = 0; PyObject *res; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O", kwlist, &weights_o)) return NULL; if (igraph_vector_init(&membership, igraph_vcount(&self->g))) { igraphmodule_handle_igraph_error(); return NULL; } if (igraphmodule_attrib_to_vector_t(weights_o, self, &weights, ATTRIBUTE_TYPE_EDGE)) { igraph_vector_destroy(&membership); return NULL; } if (igraph_community_optimal_modularity(&self->g, &modularity, &membership, weights)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&membership); if (weights != 0) { igraph_vector_destroy(weights); free(weights); } return NULL; } if (weights != 0) { igraph_vector_destroy(weights); free(weights); } res = igraphmodule_vector_t_to_PyList(&membership, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&membership); if (!res) return NULL; return Py_BuildValue("Nd", res, (double)modularity); } /** * Spinglass community detection method of Reichardt & Bornholdt */ PyObject *igraphmodule_Graph_community_spinglass(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = {"weights", "spins", "parupdate", "start_temp", "stop_temp", "cool_fact", "update_rule", "gamma", "implementation", "lambda_", NULL}; PyObject *weights_o = Py_None; PyObject *parupdate_o = Py_False; PyObject *update_rule_o = Py_None; PyObject *impl_o = Py_None; PyObject *res; long int spins = 25; double start_temp = 1.0; double stop_temp = 0.01; double cool_fact = 0.99; igraph_spinglass_implementation_t impl = IGRAPH_SPINCOMM_IMP_ORIG; igraph_spincomm_update_t update_rule = IGRAPH_SPINCOMM_UPDATE_CONFIG; double gamma = 1; double lambda = 1; igraph_vector_t *weights = 0, membership; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OlOdddOdOd", kwlist, &weights_o, &spins, &parupdate_o, &start_temp, &stop_temp, &cool_fact, &update_rule_o, &gamma, &impl_o, &lambda)) return NULL; if (igraphmodule_PyObject_to_spincomm_update_t(update_rule_o, &update_rule)) { return NULL; } if (igraphmodule_PyObject_to_spinglass_implementation_t(impl_o, &impl)) { return NULL; } if (igraph_vector_init(&membership, igraph_vcount(&self->g))) { igraphmodule_handle_igraph_error(); return NULL; } if (igraphmodule_attrib_to_vector_t(weights_o, self, &weights, ATTRIBUTE_TYPE_EDGE)) { igraph_vector_destroy(&membership); return NULL; } if (igraph_community_spinglass(&self->g, weights, 0, 0, &membership, 0, (igraph_integer_t) spins, PyObject_IsTrue(parupdate_o), start_temp, stop_temp, cool_fact, update_rule, gamma, impl, lambda)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&membership); if (weights != 0) { igraph_vector_destroy(weights); free(weights); } return NULL; } if (weights != 0) { igraph_vector_destroy(weights); free(weights); } res = igraphmodule_vector_t_to_PyList(&membership, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&membership); return res; } /** * Walktrap community detection of Latapy & Pons */ PyObject *igraphmodule_Graph_community_walktrap(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "weights", "steps", NULL }; PyObject *ms, *qs, *res, *weights = Py_None; igraph_matrix_t merges; int steps=4; igraph_vector_t q, *ws=0; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|Oi", kwlist, &weights, &steps)) return NULL; if (igraphmodule_attrib_to_vector_t(weights, self, &ws, ATTRIBUTE_TYPE_EDGE)) return NULL; igraph_matrix_init(&merges, 0, 0); igraph_vector_init(&q, 0); if (igraph_community_walktrap(&self->g, ws, steps, &merges, &q, 0)) { if (ws) { igraph_vector_destroy(ws); free(ws); } igraph_vector_destroy(&q); igraph_matrix_destroy(&merges); return igraphmodule_handle_igraph_error(); } if (ws) { igraph_vector_destroy(ws); free(ws); } qs = igraphmodule_vector_t_to_PyList(&q, IGRAPHMODULE_TYPE_FLOAT); igraph_vector_destroy(&q); if (!qs) { igraph_matrix_destroy(&merges); return NULL; } ms = igraphmodule_matrix_t_to_PyList(&merges, IGRAPHMODULE_TYPE_INT); igraph_matrix_destroy(&merges); if (ms == NULL) { Py_DECREF(qs); return NULL; } res=Py_BuildValue("NN", ms, qs); /* steals references */ return res; } /** * Leiden community detection method of Traag, Waltman & van Eck */ PyObject *igraphmodule_Graph_community_leiden(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = {"edge_weights", "node_weights", "resolution_parameter", "normalize_resolution", "beta", "initial_membership", "n_iterations", NULL}; PyObject *edge_weights_o = Py_None; PyObject *node_weights_o = Py_None; PyObject *initial_membership_o = Py_None; PyObject *res; int error = 0, i; long int n_iterations = 2; double resolution_parameter = 1.0; double beta = 0.01; igraph_vector_t *edge_weights = NULL, *node_weights = NULL, *membership; igraph_bool_t start = 1; igraph_bool_t normalize_resolution = 0; igraph_integer_t nb_clusters = 0; igraph_real_t quality = 0.0, prev_quality = -IGRAPH_INFINITY; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOdidOl", kwlist, &edge_weights_o, &node_weights_o, &resolution_parameter, &normalize_resolution, &beta, &initial_membership_o, &n_iterations)) return NULL; /* Get edge weights */ if (igraphmodule_attrib_to_vector_t(edge_weights_o, self, &edge_weights, ATTRIBUTE_TYPE_EDGE)) { igraphmodule_handle_igraph_error(); error = -1; } /* Get node weights */ if (!error && igraphmodule_attrib_to_vector_t(node_weights_o, self, &node_weights, ATTRIBUTE_TYPE_VERTEX)) { igraphmodule_handle_igraph_error(); error = -1; } /* Get initial membership */ if (!error && igraphmodule_attrib_to_vector_t(initial_membership_o, self, &membership, ATTRIBUTE_TYPE_VERTEX)) { igraphmodule_handle_igraph_error(); error = -1; } if (!error && membership == 0) { start = 0; membership = (igraph_vector_t*)calloc(1, sizeof(igraph_vector_t)); if (membership==0) { PyErr_NoMemory(); error = -1; } else { igraph_vector_init(membership, 0); } } if (normalize_resolution) { /* If we need to normalize the resolution parameter, * we will need to have node weights. */ if (node_weights == 0) { node_weights = (igraph_vector_t*)calloc(1, sizeof(igraph_vector_t)); if (node_weights==0) { PyErr_NoMemory(); error = -1; } else { igraph_vector_init(node_weights, 0); if (igraph_strength(&self->g, node_weights, igraph_vss_all(), IGRAPH_ALL, 0, edge_weights)) { igraphmodule_handle_igraph_error(); error = -1; } } } resolution_parameter /= igraph_vector_sum(node_weights); } /* Run actual Leiden algorithm for several iterations. */ if (!error) { if (n_iterations > 0) { for (i = 0; !error && i < n_iterations; i++) { error = igraph_community_leiden(&self->g, edge_weights, node_weights, resolution_parameter, beta, start, membership, &nb_clusters, &quality); start = 1; } } else { while (!error && prev_quality < quality) { error = igraph_community_leiden(&self->g, edge_weights, node_weights, resolution_parameter, beta, start, membership, &nb_clusters, &quality); start = 1; prev_quality = quality; } } } if (edge_weights != 0) { igraph_vector_destroy(edge_weights); free(edge_weights); } if (node_weights != 0) { igraph_vector_destroy(node_weights); free(node_weights); } if (!error) { res = igraphmodule_vector_t_to_PyList(membership, IGRAPHMODULE_TYPE_INT); } if (membership != 0) { igraph_vector_destroy(membership); free(membership); } if (!error) { return res; } else { return NULL; } } /********************************************************************** * Random walks * **********************************************************************/ /** * Simple random walk of a given length */ PyObject *igraphmodule_Graph_random_walk(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { static char *kwlist[] = { "start", "steps", "mode", "stuck", NULL }; PyObject *start_o, *mode_o = Py_None, *stuck_o = Py_None, *res; igraph_integer_t start; int steps=10; igraph_neimode_t mode = IGRAPH_OUT; igraph_random_walk_stuck_t stuck = IGRAPH_RANDOM_WALK_STUCK_RETURN; igraph_vector_t walk; if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OiOO", kwlist, &start_o, &steps, &mode_o, &stuck_o)) return NULL; if (igraphmodule_PyObject_to_vid(start_o, &start, &self->g)) return NULL; if (igraphmodule_PyObject_to_neimode_t(mode_o, &mode)) return NULL; if (igraphmodule_PyObject_to_random_walk_stuck_t(stuck_o, &stuck)) return NULL; if (igraph_vector_init(&walk, steps)) return igraphmodule_handle_igraph_error(); if (igraph_random_walk(&self->g, &walk, start, mode, steps, stuck)) { igraph_vector_destroy(&walk); return igraphmodule_handle_igraph_error(); } res = igraphmodule_vector_t_to_PyList(&walk, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&walk); return res; } /********************************************************************** * Special internal methods that you won't need to mess around with * **********************************************************************/ /** \defgroup python_interface_internal Internal functions * \ingroup python_interface */ #ifdef IGRAPH_PYTHON3 PyObject *igraphmodule_Graph___graph_as_capsule__(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { return PyCapsule_New((void *)&self->g, 0, 0); } #else /** \ingroup python_interface_internal * \brief Returns the encapsulated igraph graph as a PyCObject * \return a new PyCObject */ PyObject *igraphmodule_Graph___graph_as_cobject__(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { return PyCObject_FromVoidPtr((void *)&self->g, 0); } #endif /** \ingroup python_interface_internal * \brief Returns the pointer of the encapsulated igraph graph as an ordinary * Python integer. This allows us to use igraph graphs with the Python ctypes * module without any additional conversions. */ PyObject *igraphmodule_Graph__raw_pointer(igraphmodule_GraphObject *self) { return PyInt_FromLong((long int)&self->g); } /** \ingroup python_interface_internal * \brief Registers a destructor to be called when the object is destroyed * \return the previous destructor (if any) * Unimplemented. */ PyObject *igraphmodule_Graph___register_destructor__(igraphmodule_GraphObject * self, PyObject * args, PyObject * kwds) { char *kwlist[] = { "destructor", NULL }; PyObject *destructor = NULL, *result; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O", kwlist, &destructor)) return NULL; if (!PyCallable_Check(destructor)) { PyErr_SetString(PyExc_TypeError, "The destructor must be callable!"); return NULL; } result = self->destructor; self->destructor = destructor; Py_INCREF(self->destructor); if (!result) Py_RETURN_NONE; return result; } /** \ingroup python_interface * \brief Member list of the \c igraph.Graph object type */ #define OFF(x) offsetof(igraphmodule_GraphObject, x) /** \ingroup python_interface * \brief Method list of the \c igraph.Graph object type */ struct PyMethodDef igraphmodule_Graph_methods[] = { //////////////////////////// // BASIC IGRAPH INTERFACE // //////////////////////////// // interface to igraph_vcount {"vcount", (PyCFunction) igraphmodule_Graph_vcount, METH_NOARGS, "vcount()\n\n" "Counts the number of vertices.\n" "@return: the number of vertices in the graph.\n" "@rtype: integer"}, // interface to igraph_ecount {"ecount", (PyCFunction) igraphmodule_Graph_ecount, METH_NOARGS, "ecount()\n\n" "Counts the number of edges.\n" "@return: the number of edges in the graph.\n" "@rtype: integer"}, // interface to igraph_is_dag {"is_dag", (PyCFunction) igraphmodule_Graph_is_dag, METH_NOARGS, "is_dag()\n\n" "Checks whether the graph is a DAG (directed acyclic graph).\n\n" "A DAG is a directed graph with no directed cycles.\n\n" "@return: C{True} if it is a DAG, C{False} otherwise.\n" "@rtype: boolean"}, // interface to igraph_is_directed {"is_directed", (PyCFunction) igraphmodule_Graph_is_directed, METH_NOARGS, "is_directed()\n\n" "Checks whether the graph is directed.\n" "@return: C{True} if it is directed, C{False} otherwise.\n" "@rtype: boolean"}, // interface to igraph_is_simple {"is_simple", (PyCFunction) igraphmodule_Graph_is_simple, METH_NOARGS, "is_simple()\n\n" "Checks whether the graph is simple (no loop or multiple edges).\n\n" "@return: C{True} if it is simple, C{False} otherwise.\n" "@rtype: boolean"}, /* interface to igraph_add_vertices */ {"add_vertices", (PyCFunction) igraphmodule_Graph_add_vertices, METH_VARARGS, "add_vertices(n)\n\n" "Adds vertices to the graph.\n\n" "@param n: the number of vertices to be added\n"}, /* interface to igraph_delete_vertices */ {"delete_vertices", (PyCFunction) igraphmodule_Graph_delete_vertices, METH_VARARGS, "delete_vertices(vs)\n\n" "Deletes vertices and all its edges from the graph.\n\n" "@param vs: a single vertex ID or the list of vertex IDs\n" " to be deleted.\n"}, /* interface to igraph_add_edges */ {"add_edges", (PyCFunction) igraphmodule_Graph_add_edges, METH_VARARGS, "add_edges(es)\n\n" "Adds edges to the graph.\n\n" "@param es: the list of edges to be added. Every edge is\n" " represented with a tuple, containing the vertex IDs of the\n" " two endpoints. Vertices are enumerated from zero.\n"}, /* interface to igraph_delete_edges */ {"delete_edges", (PyCFunction) igraphmodule_Graph_delete_edges, METH_VARARGS | METH_KEYWORDS, "delete_edges(es)\n\n" "Removes edges from the graph.\n\n" "All vertices will be kept, even if they lose all their edges.\n" "Nonexistent edges will be silently ignored.\n\n" "@param es: the list of edges to be removed. Edges are identifed by\n" " edge IDs. L{EdgeSeq} objects are also accepted here.\n"}, /* interface to igraph_degree */ {"degree", (PyCFunction) igraphmodule_Graph_degree, METH_VARARGS | METH_KEYWORDS, "degree(vertices, mode=ALL, loops=True)\n\n" "Returns some vertex degrees from the graph.\n\n" "This method accepts a single vertex ID or a list of vertex IDs as a\n" "parameter, and returns the degree of the given vertices (in the\n" "form of a single integer or a list, depending on the input\n" "parameter).\n" "\n" "@param vertices: a single vertex ID or a list of vertex IDs\n" "@param mode: the type of degree to be returned (L{OUT} for\n" " out-degrees, L{IN} IN for in-degrees or L{ALL} for the sum of\n" " them).\n" "@param loops: whether self-loops should be counted.\n"}, /* interface to igraph_strength */ {"strength", (PyCFunction) igraphmodule_Graph_strength, METH_VARARGS | METH_KEYWORDS, "strength(vertices, mode=ALL, loops=True, weights=None)\n\n" "Returns the strength (weighted degree) of some vertices from the graph\n\n" "This method accepts a single vertex ID or a list of vertex IDs as a\n" "parameter, and returns the strength (that is, the sum of the weights\n" "of all incident edges) of the given vertices (in the\n" "form of a single integer or a list, depending on the input\n" "parameter).\n" "\n" "@param vertices: a single vertex ID or a list of vertex IDs\n" "@param mode: the type of degree to be returned (L{OUT} for\n" " out-degrees, L{IN} IN for in-degrees or L{ALL} for the sum of\n" " them).\n" "@param loops: whether self-loops should be counted.\n" "@param weights: edge weights to be used. Can be a sequence or iterable or\n" " even an edge attribute name. ``None`` means to treat the graph as\n" " unweighted, falling back to ordinary degree calculations.\n" }, /* interface to igraph_is_loop */ {"is_loop", (PyCFunction) igraphmodule_Graph_is_loop, METH_VARARGS | METH_KEYWORDS, "is_loop(edges=None)\n\n" "Checks whether a specific set of edges contain loop edges\n\n" "@param edges: edge indices which we want to check. If C{None}, all\n" " edges are checked.\n" "@return: a list of booleans, one for every edge given\n"}, /* interface to igraph_is_multiple */ {"is_multiple", (PyCFunction) igraphmodule_Graph_is_multiple, METH_VARARGS | METH_KEYWORDS, "is_multiple(edges=None)\n\n" "Checks whether an edge is a multiple edge.\n\n" "Also works for a set of edges -- in this case, every edge is checked\n" "one by one. Note that if there are multiple edges going between a\n" "pair of vertices, there is always one of them that is I{not}\n" "reported as multiple (only the others). This allows one to easily\n" "detect the edges that have to be deleted in order to make the graph\n" "free of multiple edges.\n\n" "@param edges: edge indices which we want to check. If C{None}, all\n" " edges are checked.\n" "@return: a list of booleans, one for every edge given\n"}, /* interface to igraph_has_multiple */ {"has_multiple", (PyCFunction) igraphmodule_Graph_has_multiple, METH_NOARGS, "has_multiple()\n\n" "Checks whether the graph has multiple edges.\n\n" "@return: C{True} if the graph has at least one multiple edge,\n" " C{False} otherwise.\n" "@rtype: boolean"}, /* interface to igraph_is_mutual */ {"is_mutual", (PyCFunction) igraphmodule_Graph_is_mutual, METH_VARARGS | METH_KEYWORDS, "is_mutual(edges=None)\n\n" "Checks whether an edge has an opposite pair.\n\n" "Also works for a set of edges -- in this case, every edge is checked\n" "one by one. The result will be a list of booleans (or a single boolean\n" "if only an edge index is supplied), every boolean corresponding to an\n" "edge in the edge set supplied. C{True} is returned for a given edge\n" "M{a} --> M{b} if there exists another edge M{b} --> M{a} in the\n" "original graph (not the given edge set!). All edges in an undirected\n" "graph are mutual. In case there are multiple edges between M{a}\n" "and M{b}, it is enough to have at least one edge in either direction\n" "to report all edges between them as mutual, so the multiplicity\n" "of edges do not matter.\n\n" "@param edges: edge indices which we want to check. If C{None}, all\n" " edges are checked.\n" "@return: a list of booleans, one for every edge given\n"}, /* interface to igraph_count_multiple */ {"count_multiple", (PyCFunction) igraphmodule_Graph_count_multiple, METH_VARARGS | METH_KEYWORDS, "count_multiple(edges=None)\n\n" "Counts the multiplicities of the given edges.\n\n" "@param edges: edge indices for which we want to count their\n" " multiplicity. If C{None}, all edges are counted.\n" "@return: the multiplicities of the given edges as a list.\n"}, /* interface to igraph_neighbors */ {"neighbors", (PyCFunction) igraphmodule_Graph_neighbors, METH_VARARGS | METH_KEYWORDS, "neighbors(vertex, mode=ALL)\n\n" "Returns adjacent vertices to a given vertex.\n\n" "@param vertex: a vertex ID\n" "@param mode: whether to return only successors (L{OUT}),\n" " predecessors (L{IN}) or both (L{ALL}). Ignored for undirected\n" " graphs."}, {"successors", (PyCFunction) igraphmodule_Graph_successors, METH_VARARGS | METH_KEYWORDS, "successors(vertex)\n\n" "Returns the successors of a given vertex.\n\n" "Equivalent to calling the L{Graph.neighbors} method with type=L{OUT}."}, {"predecessors", (PyCFunction) igraphmodule_Graph_predecessors, METH_VARARGS | METH_KEYWORDS, "predecessors(vertex)\n\n" "Returns the predecessors of a given vertex.\n\n" "Equivalent to calling the L{Graph.neighbors} method with type=L{IN}."}, /* interface to igraph_get_eid */ {"get_eid", (PyCFunction) igraphmodule_Graph_get_eid, METH_VARARGS | METH_KEYWORDS, "get_eid(v1, v2, directed=True, error=True)\n\n" "Returns the edge ID of an arbitrary edge between vertices v1 and v2\n\n" "@param v1: the ID or name of the first vertex\n" "@param v2: the ID or name of the second vertex\n" "@param directed: whether edge directions should be considered in\n" " directed graphs. The default is C{True}. Ignored for undirected\n" " graphs.\n" "@param error: if C{True}, an exception will be raised when the\n" " given edge does not exist. If C{False}, -1 will be returned in\n" " that case.\n" "@return: the edge ID of an arbitrary edge between vertices v1 and v2\n"}, /* interface to igraph_get_eids */ {"get_eids", (PyCFunction) igraphmodule_Graph_get_eids, METH_VARARGS | METH_KEYWORDS, "get_eids(pairs=None, path=None, directed=True, error=True)\n\n" "Returns the edge IDs of some edges between some vertices.\n\n" "This method can operate in two different modes, depending on which\n" "of the keyword arguments C{pairs} and C{path} are given.\n\n" "The method does not consider multiple edges; if there are multiple\n" "edges between a pair of vertices, only the ID of one of the edges\n" "is returned.\n\n" "@param pairs: a list of integer pairs. Each integer pair is considered\n" " as a source-target vertex pair; the corresponding edge is looked up\n" " in the graph and the edge ID is returned for each pair.\n" "@param path: a list of vertex IDs. The list is considered as a\n" " continuous path from the first vertex to the last, passing\n" " through the intermediate vertices. The corresponding edge IDs\n" " between the first and the second, the second and the third and\n" " so on are looked up in the graph and the edge IDs are returned.\n" " If both C{path} and C{pairs} are given, the two lists are\n" " concatenated.\n" "@param directed: whether edge directions should be considered in\n" " directed graphs. The default is C{True}. Ignored for undirected\n" " graphs.\n" "@param error: if C{True}, an exception will be raised if a given\n" " edge does not exist. If C{False}, -1 will be returned in\n" " that case.\n" "@return: the edge IDs in a list\n"}, /* interface to igraph_incident */ {"incident", (PyCFunction) igraphmodule_Graph_incident, METH_VARARGS | METH_KEYWORDS, "incident(vertex, mode=OUT)\n\n" "Returns the edges a given vertex is incident on.\n\n" "@param vertex: a vertex ID\n" "@param mode: whether to return only successors (L{OUT}),\n" " predecessors (L{IN}) or both (L{ALL}). Ignored for undirected\n" " graphs."}, ////////////////////// // GRAPH GENERATORS // ////////////////////// /* interface to igraph_adjacency */ {"Adjacency", (PyCFunction) igraphmodule_Graph_Adjacency, METH_CLASS | METH_VARARGS | METH_KEYWORDS, "Adjacency(matrix, mode=ADJ_DIRECTED)\n\n" "Generates a graph from its adjacency matrix.\n\n" "@param matrix: the adjacency matrix\n" "@param mode: the mode to be used. Possible values are:\n" "\n" " - C{ADJ_DIRECTED} - the graph will be directed and a matrix\n" " element gives the number of edges between two vertex.\n" " - C{ADJ_UNDIRECTED} - alias to C{ADJ_MAX} for convenience.\n" " - C{ADJ_MAX} - undirected graph will be created and the number of\n" " edges between vertex M{i} and M{j} is M{max(A(i,j), A(j,i))}\n" " - C{ADJ_MIN} - like C{ADJ_MAX}, but with M{min(A(i,j), A(j,i))}\n" " - C{ADJ_PLUS} - like C{ADJ_MAX}, but with M{A(i,j) + A(j,i)}\n" " - C{ADJ_UPPER} - undirected graph with the upper right triangle of\n" " the matrix (including the diagonal)\n" " - C{ADJ_LOWER} - undirected graph with the lower left triangle of\n" " the matrix (including the diagonal)\n" "\n" " These values can also be given as strings without the C{ADJ} prefix.\n" }, /* interface to igraph_asymmetric_preference_game */ {"Asymmetric_Preference", (PyCFunction) igraphmodule_Graph_Asymmetric_Preference, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "Asymmetric_Preference(n, type_dist_matrix, pref_matrix, attribute=None, loops=False)\n\n" "Generates a graph based on asymmetric vertex types and connection probabilities.\n\n" "This is the asymmetric variant of L{Graph.Preference}.\n" "A given number of vertices are generated. Every vertex is assigned to an\n" "\"incoming\" and an \"outgoing\" vertex type according to the given joint\n" "type probabilities. Finally, every vertex pair is evaluated and a\n" "directed edge is created between them with a probability depending on\n" "the \"outgoing\" type of the source vertex and the \"incoming\" type of\n" "the target vertex.\n\n" "@param n: the number of vertices in the graph\n" "@param type_dist_matrix: matrix giving the joint distribution of vertex\n" " types\n" "@param pref_matrix: matrix giving the connection probabilities for\n" " different vertex types.\n" "@param attribute: the vertex attribute name used to store the vertex\n" " types. If C{None}, vertex types are not stored.\n" "@param loops: whether loop edges are allowed.\n"}, // interface to igraph_atlas {"Atlas", (PyCFunction) igraphmodule_Graph_Atlas, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "Atlas(idx)\n\n" "Generates a graph from the Graph Atlas.\n\n" "@param idx: The index of the graph to be generated.\n" " Indices start from zero, graphs are listed:\n\n" " 1. in increasing order of number of vertices;\n" " 2. for a fixed number of vertices, in increasing order of the\n" " number of edges;\n" " 3. for fixed numbers of vertices and edges, in increasing order\n" " of the degree sequence, for example 111223 < 112222;\n" " 4. for fixed degree sequence, in increasing number of automorphisms.\n\n" "@newfield ref: Reference\n" "@ref: I{An Atlas of Graphs} by Ronald C. Read and Robin J. Wilson,\n" " Oxford University Press, 1998."}, // interface to igraph_barabasi_game {"Barabasi", (PyCFunction) igraphmodule_Graph_Barabasi, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "Barabasi(n, m, outpref=False, directed=False, power=1,\n" " zero_appeal=1, implementation=\"psumtree\", start_from=None)\n\n" "Generates a graph based on the Barabasi-Albert model.\n\n" "@param n: the number of vertices\n" "@param m: either the number of outgoing edges generated for\n" " each vertex or a list containing the number of outgoing\n" " edges for each vertex explicitly.\n" "@param outpref: C{True} if the out-degree of a given vertex\n" " should also increase its citation probability (as well as\n" " its in-degree), but it defaults to C{False}.\n" "@param directed: C{True} if the generated graph should be\n" " directed (default: C{False}).\n" "@param power: the power constant of the nonlinear model.\n" " It can be omitted, and in this case the usual linear model\n" " will be used.\n" "@param zero_appeal: the attractivity of vertices with degree\n" " zero.\n\n" "@param implementation: the algorithm to use to generate the\n" " network. Possible values are:\n\n" " - C{\"bag\"}: the algorithm that was the default in\n" " igraph before 0.6. It works by putting the ids of the\n" " vertices into a bag (multiset) exactly as many times\n" " as their in-degree, plus once more. The required number\n" " of cited vertices are then drawn from the bag with\n" " replacement. It works only for I{power}=1 and\n" " I{zero_appeal}=1.\n\n" " - C{\"psumtree\"}: this algorithm uses a partial prefix-sum\n" " tree to generate the graph. It does not generate multiple\n" " edges and it works for any values of I{power} and\n" " I{zero_appeal}.\n\n" " - C{\"psumtree_multiple\"}: similar to C{\"psumtree\"}, but\n" " it will generate multiple edges as well. igraph before\n" " 0.6 used this algorithm for I{power}s other than 1.\n\n" "@param start_from: if given and not C{None}, this must be another\n" " L{Graph} object. igraph will use this graph as a starting\n" " point for the preferential attachment model.\n\n" "@newfield ref: Reference\n" "@ref: Barabasi, A-L and Albert, R. 1999. Emergence of scaling\n" " in random networks. Science, 286 509-512."}, /* interface to igraph_create_bipartite */ {"_Bipartite", (PyCFunction) igraphmodule_Graph_Bipartite, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "_Bipartite(types, edges, directed=False)\n\n" "Internal function, undocumented.\n\n" "@see: Graph.Bipartite()\n\n"}, /* interface to igraph_de_bruijn */ {"De_Bruijn", (PyCFunction) igraphmodule_Graph_De_Bruijn, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "De_Bruijn(m, n)\n\n" "Generates a de Bruijn graph with parameters (m, n)\n\n" "A de Bruijn graph represents relationships between strings. An alphabet\n" "of M{m} letters are used and strings of length M{n} are considered.\n" "A vertex corresponds to every possible string and there is a directed edge\n" "from vertex M{v} to vertex M{w} if the string of M{v} can be transformed into\n" "the string of M{w} by removing its first letter and appending a letter to it.\n" "\n" "Please note that the graph will have M{m^n} vertices and even more edges,\n" "so probably you don't want to supply too big numbers for M{m} and M{n}.\n\n" "@param m: the size of the alphabet\n" "@param n: the length of the strings\n" }, // interface to igraph_establishment_game {"Establishment", (PyCFunction) igraphmodule_Graph_Establishment, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "Establishment(n, k, type_dist, pref_matrix, directed=False)\n\n" "Generates a graph based on a simple growing model with vertex types.\n\n" "A single vertex is added at each time step. This new vertex tries to\n" "connect to k vertices in the graph. The probability that such a\n" "connection is realized depends on the types of the vertices involved.\n" "\n" "@param n: the number of vertices in the graph\n" "@param k: the number of connections tried in each step\n" "@param type_dist: list giving the distribution of vertex types\n" "@param pref_matrix: matrix (list of lists) giving the connection\n" " probabilities for different vertex types\n" "@param directed: whether to generate a directed graph.\n"}, // interface to igraph_erdos_renyi_game {"Erdos_Renyi", (PyCFunction) igraphmodule_Graph_Erdos_Renyi, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "Erdos_Renyi(n, p, m, directed=False, loops=False)\n\n" "Generates a graph based on the Erdos-Renyi model.\n\n" "@param n: the number of vertices.\n" "@param p: the probability of edges. If given, C{m} must be missing.\n" "@param m: the number of edges. If given, C{p} must be missing.\n" "@param directed: whether to generate a directed graph.\n" "@param loops: whether self-loops are allowed.\n"}, /* interface to igraph_famous */ {"Famous", (PyCFunction) igraphmodule_Graph_Famous, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "Famous(name)\n\n" "Generates a famous graph based on its name.\n\n" "Several famous graphs are known to C{igraph} including (but not limited to)\n" "the Chvatal graph, the Petersen graph or the Tutte graph. This method\n" "generates one of them based on its name (case insensitive). See the\n" "documentation of the C interface of C{igraph} for the names available:\n" "U{http://igraph.org/doc/c}.\n\n" "@param name: the name of the graph to be generated.\n" }, /* interface to igraph_forest_fire_game */ {"Forest_Fire", (PyCFunction) igraphmodule_Graph_Forest_Fire, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "Forest_Fire(n, fw_prob, bw_factor=0.0, ambs=1, directed=False)\n\n" "Generates a graph based on the forest fire model\n\n" "The forest fire model is a growing graph model. In every time step, a new\n" "vertex is added to the graph. The new vertex chooses an ambassador (or\n" "more than one if M{ambs>1}) and starts a simulated forest fire at its\n" "ambassador(s). The fire spreads through the edges. The spreading probability\n" "along an edge is given by M{fw_prob}. The fire may also spread backwards\n" "on an edge by probability M{fw_prob * bw_factor}. When the fire ended, the\n" "newly added vertex connects to the vertices ``burned'' in the previous\n" "fire.\n\n" "@param n: the number of vertices in the graph\n" "@param fw_prob: forward burning probability\n" "@param bw_factor: ratio of backward and forward burning probability\n" "@param ambs: number of ambassadors chosen in each step\n" "@param directed: whether the graph will be directed\n" }, /* interface to igraph_full_citation */ {"Full_Citation", (PyCFunction) igraphmodule_Graph_Full_Citation, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "Full_Citation(n, directed=False)\n\n" "Generates a full citation graph\n\n" "A full citation graph is a graph where the vertices are indexed from 0 to\n" "M{n-1} and vertex M{i} has a directed edge towards all vertices with an\n" "index less than M{i}.\n\n" "@param n: the number of vertices.\n" "@param directed: whether to generate a directed graph.\n"}, /* interface to igraph_full */ {"Full", (PyCFunction) igraphmodule_Graph_Full, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "Full(n, directed=False, loops=False)\n\n" "Generates a full graph (directed or undirected, with or without loops).\n\n" "@param n: the number of vertices.\n" "@param directed: whether to generate a directed graph.\n" "@param loops: whether self-loops are allowed.\n"}, /* interface to igraph_full_bipartite */ {"_Full_Bipartite", (PyCFunction) igraphmodule_Graph_Full_Bipartite, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "_Full_Bipartite(n1, n2, directed=False, loops=False)\n\n" "Internal function, undocumented.\n\n" "@see: Graph.Full_Bipartite()\n\n"}, /* interface to igraph_grg_game */ {"_GRG", (PyCFunction) igraphmodule_Graph_GRG, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "_GRG(n, radius, torus=False)\n\n" "Internal function, undocumented.\n\n" "@see: Graph.GRG()\n\n"}, /* interface to igraph_growing_random_game */ {"Growing_Random", (PyCFunction) igraphmodule_Graph_Growing_Random, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "Growing_Random(n, m, directed=False, citation=False)\n\n" "Generates a growing random graph.\n\n" "@param n: The number of vertices in the graph\n" "@param m: The number of edges to add in each step (after adding a new vertex)\n" "@param directed: whether the graph should be directed.\n" "@param citation: whether the new edges should originate from the most\n" " recently added vertex.\n"}, /* interface to igraph_incidence */ {"_Incidence", (PyCFunction) igraphmodule_Graph_Incidence, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "_Incidence(matrix, directed=False, mode=ALL, multiple=False)\n\n" "Internal function, undocumented.\n\n" "@see: Graph.Incidence()\n\n"}, /* interface to igraph_kautz */ {"Kautz", (PyCFunction) igraphmodule_Graph_Kautz, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "Kautz(m, n)\n\n" "Generates a Kautz graph with parameters (m, n)\n\n" "A Kautz graph is a labeled graph, vertices are labeled by strings\n" "of length M{n+1} above an alphabet with M{m+1} letters, with\n" "the restriction that every two consecutive letters in the string\n" "must be different. There is a directed edge from a vertex M{v} to\n" "another vertex M{w} if it is possible to transform the string of\n" "M{v} into the string of M{w} by removing the first letter and\n" "appending a letter to it.\n\n" "@param m: the size of the alphabet minus one\n" "@param n: the length of the strings minus one\n" }, /* interface to igraph_k_regular */ {"K_Regular", (PyCFunction) igraphmodule_Graph_K_Regular, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "K_Regular(n, k, directed=False, multiple=False)\n\n" "Generates a k-regular random graph\n\n" "A k-regular random graph is a random graph where each vertex has degree k.\n" "If the graph is directed, both the in-degree and the out-degree of each vertex\n" "will be k.\n\n" "@param n: The number of vertices in the graph\n\n" "@param k: The degree of each vertex if the graph is undirected, or the in-degree\n" " and out-degree of each vertex if the graph is directed\n" "@param directed: whether the graph should be directed.\n" "@param multiple: whether it is allowed to create multiple edges.\n" }, /* interface to igraph_preference_game */ {"Preference", (PyCFunction) igraphmodule_Graph_Preference, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "Preference(n, type_dist, pref_matrix, attribute=None, directed=False, loops=False)\n\n" "Generates a graph based on vertex types and connection probabilities.\n\n" "This is practically the nongrowing variant of L{Graph.Establishment}.\n" "A given number of vertices are generated. Every vertex is assigned to a\n" "vertex type according to the given type probabilities. Finally, every\n" "vertex pair is evaluated and an edge is created between them with a\n" "probability depending on the types of the vertices involved.\n\n" "@param n: the number of vertices in the graph\n" "@param type_dist: list giving the distribution of vertex types\n" "@param pref_matrix: matrix giving the connection probabilities for\n" " different vertex types.\n" "@param attribute: the vertex attribute name used to store the vertex\n" " types. If C{None}, vertex types are not stored.\n" "@param directed: whether to generate a directed graph.\n" "@param loops: whether loop edges are allowed.\n"}, /* interface to igraph_bipartite_game */ {"_Random_Bipartite", (PyCFunction) igraphmodule_Graph_Random_Bipartite, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "_Random_Bipartite(n1, n2, p=None, m=None, directed=False, neimode=\"all\")\n\n" "Internal function, undocumented.\n\n" "@see: Graph.Random_Bipartite()\n\n"}, /* interface to igraph_recent_degree_game */ {"Recent_Degree", (PyCFunction) igraphmodule_Graph_Recent_Degree, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "Recent_Degree(n, m, window, outpref=False, directed=False, power=1)\n\n" "Generates a graph based on a stochastic model where the probability\n" "of an edge gaining a new node is proportional to the edges gained in\n" "a given time window.\n\n" "@param n: the number of vertices\n" "@param m: either the number of outgoing edges generated for\n" " each vertex or a list containing the number of outgoing\n" " edges for each vertex explicitly.\n" "@param window: size of the window in time steps\n" "@param outpref: C{True} if the out-degree of a given vertex\n" " should also increase its citation probability (as well as\n" " its in-degree), but it defaults to C{False}.\n" "@param directed: C{True} if the generated graph should be\n" " directed (default: C{False}).\n" "@param power: the power constant of the nonlinear model.\n" " It can be omitted, and in this case the usual linear model\n" " will be used.\n"}, /* interface to igraph_sbm_game */ {"SBM", (PyCFunction) igraphmodule_Graph_SBM, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "SBM(n, pref_matrix, block_sizes, directed=False, loops=False)\n\n" "Generates a graph based on a stochastic blockmodel.\n\n" "A given number of vertices are generated. Every vertex is assigned to a\n" "vertex type according to the given block sizes. Vertices of the same\n" "type will be assigned consecutive vertex IDs. Finally, every\n" "vertex pair is evaluated and an edge is created between them with a\n" "probability depending on the types of the vertices involved. The\n" "probabilities are taken from the preference matrix.\n\n" "@param n: the number of vertices in the graph\n" "@param pref_matrix: matrix giving the connection probabilities for\n" " different vertex types.\n" "@param block_sizes: list giving the number of vertices in each block; must\n" " sum up to I{n}.\n" "@param directed: whether to generate a directed graph.\n" "@param loops: whether loop edges are allowed.\n"}, // interface to igraph_star {"Star", (PyCFunction) igraphmodule_Graph_Star, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "Star(n, mode=\"undirected\", center=0)\n\n" "Generates a star graph.\n\n" "@param n: the number of vertices in the graph\n" "@param mode: Gives the type of the star graph to create. Should be\n" " either \"in\", \"out\", \"mutual\" or \"undirected\"\n" "@param center: Vertex ID for the central vertex in the star.\n"}, // interface to igraph_lattice {"Lattice", (PyCFunction) igraphmodule_Graph_Lattice, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "Lattice(dim, nei=1, directed=False, mutual=True, circular=True)\n\n" "Generates a regular lattice.\n\n" "@param dim: list with the dimensions of the lattice\n" "@param nei: value giving the distance (number of steps) within which\n" " two vertices will be connected.\n" "@param directed: whether to create a directed graph.\n" "@param mutual: whether to create all connections as mutual\n" " in case of a directed graph.\n" "@param circular: whether the generated lattice is periodic.\n"}, /* interface to igraph_lcf */ {"LCF", (PyCFunction) igraphmodule_Graph_LCF, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "LCF(n, shifts, repeats)\n\n" "Generates a graph from LCF notation.\n\n" "LCF is short for Lederberg-Coxeter-Frucht, it is a concise notation\n" "for 3-regular Hamiltonian graphs. It consists of three parameters,\n" "the number of vertices in the graph, a list of shifts giving\n" "additional edges to a cycle backbone and another integer giving how\n" "many times the shifts should be performed. See\n" "U{http://mathworld.wolfram.com/LCFNotation.html} for details.\n\n" "@param n: the number of vertices\n" "@param shifts: the shifts in a list or tuple\n" "@param repeats: the number of repeats\n" }, // interface to igraph_ring {"Ring", (PyCFunction) igraphmodule_Graph_Ring, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "Ring(n, directed=False, mutual=False, circular=True)\n\n" "Generates a ring graph.\n\n" "@param n: the number of vertices in the ring\n" "@param directed: whether to create a directed ring.\n" "@param mutual: whether to create mutual edges in a directed ring.\n" "@param circular: whether to create a closed ring.\n"}, /* interface to igraph_static_fitness_game */ {"Static_Fitness", (PyCFunction) igraphmodule_Graph_Static_Fitness, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "Static_Fitness(m, fitness_out, fitness_in=None, loops=False, multiple=False)\n\n" "Generates a non-growing graph with edge probabilities proportional to node\n" "fitnesses.\n\n" "The algorithm randomly selects vertex pairs and connects them until the given\n" "number of edges are created. Each vertex is selected with a probability\n" "proportional to its fitness; for directed graphs, a vertex is selected as a\n" "source proportional to its out-fitness and as a target proportional to its\n" "in-fitness.\n\n" "@param m: the number of edges in the graph\n" "@param fitness_out: a numeric vector with non-negative entries, one for each\n" " vertex. These values represent the fitness scores (out-fitness scores for\n" " directed graphs). I{fitness} is an alias of this keyword argument.\n" "@param fitness_in: a numeric vector with non-negative entries, one for each\n" " vertex. These values represent the in-fitness scores for directed graphs.\n" " For undirected graphs, this argument must be C{None}.\n" "@param loops: whether loop edges are allowed.\n" "@param multiple: whether multiple edges are allowed.\n" "@return: a directed or undirected graph with the prescribed power-law\n" " degree distributions.\n" }, /* interface to igraph_static_power_law_game */ {"Static_Power_Law", (PyCFunction) igraphmodule_Graph_Static_Power_Law, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "Static_Power_Law(n, m, exponent_out, exponent_in=-1, loops=False,\n" " multiple=False, finite_size_correction=True)\n\n" "Generates a non-growing graph with prescribed power-law degree distributions.\n\n" "@param n: the number of vertices in the graph\n" "@param m: the number of edges in the graph\n" "@param exponent_out: the exponent of the out-degree distribution, which\n" " must be between 2 and infinity (inclusive). When I{exponent_in} is\n" " not given or negative, the graph will be undirected and this parameter\n" " specifies the degree distribution. I{exponent} is an alias to this\n" " keyword argument.\n" "@param exponent_in: the exponent of the in-degree distribution, which\n" " must be between 2 and infinity (inclusive) It can also be negative, in\n" " which case an undirected graph will be generated.\n" "@param loops: whether loop edges are allowed.\n" "@param multiple: whether multiple edges are allowed.\n" "@param finite_size_correction: whether to apply a finite-size correction\n" " to the generated fitness values for exponents less than 3. See the\n" " paper of Cho et al for more details.\n" "@return: a directed or undirected graph with the prescribed power-law\n" " degree distributions.\n" "\n" "@newfield ref: Reference\n" "@ref: Goh K-I, Kahng B, Kim D: Universal behaviour of load distribution\n" " in scale-free networks. Phys Rev Lett 87(27):278701, 2001.\n" "@ref: Cho YS, Kim JS, Park J, Kahng B, Kim D: Percolation transitions in\n" " scale-free networks under the Achlioptas process. Phys Rev Lett\n" " 103:135702, 2009.\n" }, // interface to igraph_tree {"Tree", (PyCFunction) igraphmodule_Graph_Tree, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "Tree(n, children, type=TREE_UNDIRECTED)\n\n" "Generates a tree in which almost all vertices have the same number of children.\n\n" "@param n: the number of vertices in the graph\n" "@param children: the number of children of a vertex in the graph\n" "@param type: determines whether the tree should be directed, and if\n" " this is the case, also its orientation. Must be one of\n" " C{TREE_IN}, C{TREE_OUT} and C{TREE_UNDIRECTED}.\n"}, /* interface to igraph_degree_sequence_game */ {"Degree_Sequence", (PyCFunction) igraphmodule_Graph_Degree_Sequence, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "Degree_Sequence(out, in=None, method=\"simple\")\n\n" "Generates a graph with a given degree sequence.\n\n" "@param out: the out-degree sequence for a directed graph. If the\n" " in-degree sequence is omitted, the generated graph\n" " will be undirected, so this will be the in-degree\n" " sequence as well\n" "@param in: the in-degree sequence for a directed graph.\n" " If omitted, the generated graph will be undirected.\n" "@param method: the generation method to be used. One of the following:\n" " \n" " - C{\"simple\"} -- simple generator that sometimes generates\n" " loop edges and multiple edges. The generated graph is not\n" " guaranteed to be connected.\n" " - C{\"no_multiple\"} -- similar to C{\"simple\"} but avoids the\n" " generation of multiple and loop edges at the expense of increased\n" " time complexity. The method will re-start the generation every time\n" " it gets stuck in a configuration where it is not possible to insert\n" " any more edges without creating loops or multiple edges, and there\n" " is no upper bound on the number of iterations, but it will succeed\n" " eventually if the input degree sequence is graphical and throw an\n" " exception if the input degree sequence is not graphical.\n" " - C{\"vl\"} -- a more sophisticated generator that can sample\n" " undirected, connected simple graphs uniformly. It uses\n" " Monte-Carlo methods to randomize the graphs.\n" " This generator should be favoured if undirected and connected\n" " graphs are to be generated and execution time is not a concern.\n" " igraph uses the original implementation of Fabien Viger; see the\n" " following URL and the paper cited on it for the details of the\n" " algorithm: U{http://www-rp.lip6.fr/~latapy/FV/generation.html}.\n" }, /* interface to igraph_isoclass_create */ {"Isoclass", (PyCFunction) igraphmodule_Graph_Isoclass, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "Isoclass(n, class, directed=False)\n\n" "Generates a graph with a given isomorphy class.\n\n" "@param n: the number of vertices in the graph (3 or 4)\n" "@param class: the isomorphy class\n" "@param directed: whether the graph should be directed.\n"}, /* interface to igraph_watts_strogatz_game */ {"Watts_Strogatz", (PyCFunction) igraphmodule_Graph_Watts_Strogatz, METH_VARARGS | METH_CLASS | METH_KEYWORDS, "Watts_Strogatz(dim, size, nei, p, loops=False, multiple=False)\n\n" "@param dim: the dimension of the lattice\n" "@param size: the size of the lattice along all dimensions\n" "@param nei: value giving the distance (number of steps) within which\n" " two vertices will be connected.\n" "@param p: rewiring probability\n\n" "@param loops: specifies whether loop edges are allowed\n" "@param multiple: specifies whether multiple edges are allowed\n" "@see: L{Lattice()}, L{rewire()}, L{rewire_edges()} if more flexibility is\n" " needed\n" "@newfield ref: Reference\n" "@ref: Duncan J Watts and Steven H Strogatz: I{Collective dynamics of\n" " small world networks}, Nature 393, 440-442, 1998\n"}, /* interface to igraph_weighted_adjacency */ {"Weighted_Adjacency", (PyCFunction) igraphmodule_Graph_Weighted_Adjacency, METH_CLASS | METH_VARARGS | METH_KEYWORDS, "Weighted_Adjacency(matrix, mode=ADJ_DIRECTED, attr=\"weight\", loops=True)\n\n" "Generates a graph from its adjacency matrix.\n\n" "@param matrix: the adjacency matrix\n" "@param mode: the mode to be used. Possible values are:\n" "\n" " - C{ADJ_DIRECTED} - the graph will be directed and a matrix\n" " element gives the number of edges between two vertex.\n" " - C{ADJ_UNDIRECTED} - alias to C{ADJ_MAX} for convenience.\n" " - C{ADJ_MAX} - undirected graph will be created and the number of\n" " edges between vertex M{i} and M{j} is M{max(A(i,j), A(j,i))}\n" " - C{ADJ_MIN} - like C{ADJ_MAX}, but with M{min(A(i,j), A(j,i))}\n" " - C{ADJ_PLUS} - like C{ADJ_MAX}, but with M{A(i,j) + A(j,i)}\n" " - C{ADJ_UPPER} - undirected graph with the upper right triangle of\n" " the matrix (including the diagonal)\n" " - C{ADJ_LOWER} - undirected graph with the lower left triangle of\n" " the matrix (including the diagonal)\n" "\n" " These values can also be given as strings without the C{ADJ} prefix.\n" "@param attr: the name of the edge attribute that stores the edge\n" " weights.\n" "@param loops: whether to include loop edges. When C{False}, the diagonal\n" " of the adjacency matrix will be ignored.\n" }, ///////////////////////////////////// // STRUCTURAL PROPERTIES OF GRAPHS // ///////////////////////////////////// // interface to igraph_are_connected {"are_connected", (PyCFunction) igraphmodule_Graph_are_connected, METH_VARARGS | METH_KEYWORDS, "are_connected(v1, v2)\n\n" "Decides whether two given vertices are directly connected.\n\n" "@param v1: the ID or name of the first vertex\n" "@param v2: the ID or name of the second vertex\n" "@return: C{True} if there exists an edge from v1 to v2, C{False}\n" " otherwise.\n"}, /* interface to igraph_articulation_points */ {"articulation_points", (PyCFunction)igraphmodule_Graph_articulation_points, METH_NOARGS, "articulation_points()\n\n" "Returns the list of articulation points in the graph.\n\n" "A vertex is an articulation point if its removal increases the number of\n" "connected components in the graph.\n" }, /* interface to igraph_assortativity */ {"assortativity", (PyCFunction)igraphmodule_Graph_assortativity, METH_VARARGS | METH_KEYWORDS, "assortativity(types1, types2=None, directed=True)\n\n" "Returns the assortativity of the graph based on numeric properties\n" "of the vertices.\n\n" "This coefficient is basically the correlation between the actual\n" "connectivity patterns of the vertices and the pattern expected from the\n" "disribution of the vertex types.\n\n" "See equation (21) in Newman MEJ: Mixing patterns in networks, Phys Rev E\n" "67:026126 (2003) for the proper definition. The actual calculation is\n" "performed using equation (26) in the same paper for directed graphs, and\n" "equation (4) in Newman MEJ: Assortative mixing in networks, Phys Rev Lett\n" "89:208701 (2002) for undirected graphs.\n\n" "@param types1: vertex types in a list or the name of a vertex attribute\n" " holding vertex types. Types are ideally denoted by numeric values.\n" "@param types2: in directed assortativity calculations, each vertex can\n" " have an out-type and an in-type. In this case, I{types1} contains the\n" " out-types and this parameter contains the in-types in a list or the\n" " name of a vertex attribute. If C{None}, it is assumed to be equal\n" " to I{types1}.\n\n" "@param directed: whether to consider edge directions or not.\n" "@return: the assortativity coefficient\n\n" "@newfield ref: Reference\n" "@ref: Newman MEJ: Mixing patterns in networks, Phys Rev E 67:026126, 2003.\n" "@ref: Newman MEJ: Assortative mixing in networks, Phys Rev Lett 89:208701,\n" " 2002.\n" "@see: L{assortativity_degree()} when the types are the vertex degrees\n" }, /* interface to igraph_assortativity_degree */ {"assortativity_degree", (PyCFunction)igraphmodule_Graph_assortativity_degree, METH_VARARGS | METH_KEYWORDS, "assortativity_degree(directed=True)\n\n" "Returns the assortativity of a graph based on vertex degrees.\n\n" "See L{assortativity()} for the details. L{assortativity_degree()} simply\n" "calls L{assortativity()} with the vertex degrees as types.\n\n" "@param directed: whether to consider edge directions for directed graphs\n" " or not. This argument is ignored for undirected graphs.\n" "@return: the assortativity coefficient\n\n" "@see: L{assortativity()}\n" }, /* interface to igraph_assortativity_nominal */ {"assortativity_nominal", (PyCFunction)igraphmodule_Graph_assortativity_nominal, METH_VARARGS | METH_KEYWORDS, "assortativity_nominal(types, directed=True)\n\n" "Returns the assortativity of the graph based on vertex categories.\n\n" "Assuming that the vertices belong to different categories, this\n" "function calculates the assortativity coefficient, which specifies\n" "the extent to which the connections stay within categories. The\n" "assortativity coefficient is one if all the connections stay within\n" "categories and minus one if all the connections join vertices of\n" "different categories. For a randomly connected network, it is\n" "asymptotically zero.\n\n" "See equation (2) in Newman MEJ: Mixing patterns in networks, Phys Rev E\n" "67:026126 (2003) for the proper definition.\n\n" "@param types: vertex types in a list or the name of a vertex attribute\n" " holding vertex types. Types should be denoted by numeric values.\n" "@param directed: whether to consider edge directions or not.\n" "@return: the assortativity coefficient\n\n" "@newfield ref: Reference\n" "@ref: Newman MEJ: Mixing patterns in networks, Phys Rev E 67:026126, 2003.\n" }, /* interface to igraph_average_path_length */ {"average_path_length", (PyCFunction) igraphmodule_Graph_average_path_length, METH_VARARGS | METH_KEYWORDS, "average_path_length(directed=True, unconn=True)\n\n" "Calculates the average path length in a graph.\n\n" "@param directed: whether to consider directed paths in case of a\n" " directed graph. Ignored for undirected graphs.\n" "@param unconn: what to do when the graph is unconnected. If C{True},\n" " the average of the geodesic lengths in the components is\n" " calculated. Otherwise for all unconnected vertex pairs,\n" " a path length equal to the number of vertices is used.\n" "@return: the average path length in the graph\n"}, /* interface to igraph_authority_score */ {"authority_score", (PyCFunction)igraphmodule_Graph_authority_score, METH_VARARGS | METH_KEYWORDS, "authority_score(weights=None, scale=True, arpack_options=None, return_eigenvalue=False)\n\n" "Calculates Kleinberg's authority score for the vertices of the graph\n\n" "@param weights: edge weights to be used. Can be a sequence or iterable or\n" " even an edge attribute name.\n" "@param scale: whether to normalize the scores so that the largest one\n" " is 1.\n" "@param arpack_options: an L{ARPACKOptions} object used to fine-tune\n" " the ARPACK eigenvector calculation. If omitted, the module-level\n" " variable called C{arpack_options} is used.\n" "@param return_eigenvalue: whether to return the largest eigenvalue\n" "@return: the authority scores in a list and optionally the largest eigenvalue\n" " as a second member of a tuple\n\n" "@see: hub_score()\n" }, /* interface to igraph_betweenness[_estimate] */ {"betweenness", (PyCFunction) igraphmodule_Graph_betweenness, METH_VARARGS | METH_KEYWORDS, "betweenness(vertices=None, directed=True, cutoff=None, weights=None, nobigint=True)\n\n" "Calculates or estimates the betweenness of vertices in a graph.\n\n" "Keyword arguments:\n" "@param vertices: the vertices for which the betweennesses must be returned.\n" " If C{None}, assumes all of the vertices in the graph.\n" "@param directed: whether to consider directed paths.\n" "@param cutoff: if it is an integer, only paths less than or equal to this\n" " length are considered, effectively resulting in an estimation of the\n" " betweenness for the given vertices. If C{None}, the exact betweenness is\n" " returned.\n" "@param weights: edge weights to be used. Can be a sequence or iterable or\n" " even an edge attribute name.\n" "@param nobigint: if C{True}, igraph uses the longest available integer\n" " type on the current platform to count shortest paths. For some large\n" " networks that have a specific structure, the counters may overflow.\n" " To prevent this, use C{nobigint=False}, which forces igraph to use\n" " arbitrary precision integers at the expense of increased computation\n" " time.\n" "@return: the (possibly estimated) betweenness of the given vertices in a list\n"}, /* interface to biconnected_components */ {"biconnected_components", (PyCFunction) igraphmodule_Graph_biconnected_components, METH_VARARGS | METH_KEYWORDS, "biconnected_components(return_articulation_points=True)\n\n" "Calculates the biconnected components of the graph.\n\n" "Components containing a single vertex only are not considered as being\n" "biconnected.\n\n" "@param return_articulation_points: whether to return the articulation\n" " points as well\n" "@return: a list of lists containing edge indices making up spanning trees\n" " of the biconnected components (one spanning tree for each component)\n" " and optionally the list of articulation points" }, /* interface to igraph_bipartite_projection */ {"bipartite_projection", (PyCFunction) igraphmodule_Graph_bipartite_projection, METH_VARARGS | METH_KEYWORDS, "bipartite_projection(types, multiplicity=True, probe1=-1, which=-1)\n\n" "Internal function, undocumented.\n\n" "@see: Graph.bipartite_projection()\n"}, /* interface to igraph_bipartite_projection_size */ {"bipartite_projection_size", (PyCFunction) igraphmodule_Graph_bipartite_projection_size, METH_VARARGS | METH_KEYWORDS, "bipartite_projection_size(types)\n\n" "Internal function, undocumented.\n\n" "@see: Graph.bipartite_projection_size()\n"}, /* interface to igraph_closeness */ {"closeness", (PyCFunction) igraphmodule_Graph_closeness, METH_VARARGS | METH_KEYWORDS, "closeness(vertices=None, mode=ALL, cutoff=None, weights=None,\n" " normalized=True)\n\n" "Calculates the closeness centralities of given vertices in a graph.\n\n" "The closeness centerality of a vertex measures how easily other\n" "vertices can be reached from it (or the other way: how easily it\n" "can be reached from the other vertices). It is defined as the\n" "number of the number of vertices minus one divided by the sum of\n" "the lengths of all geodesics from/to the given vertex.\n\n" "If the graph is not connected, and there is no path between two\n" "vertices, the number of vertices is used instead the length of\n" "the geodesic. This is always longer than the longest possible\n" "geodesic.\n\n" "@param vertices: the vertices for which the closenesses must\n" " be returned. If C{None}, uses all of the vertices in the graph.\n" "@param mode: must be one of L{IN}, L{OUT} and L{ALL}. L{IN} means\n" " that the length of the incoming paths, L{OUT} means that the\n" " length of the outgoing paths must be calculated. L{ALL} means\n" " that both of them must be calculated.\n" "@param cutoff: if it is an integer, only paths less than or equal to this\n" " length are considered, effectively resulting in an estimation of the\n" " closeness for the given vertices (which is always an underestimation of the\n" " real closeness, since some vertex pairs will appear as disconnected even\n" " though they are connected).. If C{None}, the exact closeness is\n" " returned.\n" "@param weights: edge weights to be used. Can be a sequence or iterable or\n" " even an edge attribute name.\n" "@param normalized: Whether to normalize the raw closeness scores by\n" " multiplying by the number of vertices minus one.\n" "@return: the calculated closenesses in a list\n"}, /* interface to igraph_clusters */ {"clusters", (PyCFunction) igraphmodule_Graph_clusters, METH_VARARGS | METH_KEYWORDS, "clusters(mode=STRONG)\n\n" "Calculates the (strong or weak) clusters for a given graph.\n\n" "@attention: this function has a more convenient interface in class\n" " L{Graph} which wraps the result in a L{VertexClustering} object.\n" " It is advised to use that.\n" "@param mode: must be either C{STRONG} or C{WEAK}, depending on\n" " the clusters being sought. Optional, defaults to C{STRONG}.\n" "@return: the component index for every node in the graph.\n"}, {"copy", (PyCFunction) igraphmodule_Graph_copy, METH_NOARGS, "copy()\n\n" "Creates a copy of the graph.\n\n" "Attributes are copied by reference; in other words, if you use\n" "mutable Python objects as attribute values, these objects will still\n" "be shared between the old and new graph. You can use `deepcopy()`\n" "from the `copy` module if you need a truly deep copy of the graph.\n" }, {"decompose", (PyCFunction) igraphmodule_Graph_decompose, METH_VARARGS | METH_KEYWORDS, "decompose(mode=STRONG, maxcompno=None, minelements=1)\n\n" "Decomposes the graph into subgraphs.\n\n" "@param mode: must be either STRONG or WEAK, depending on the\n" " clusters being sought.\n" "@param maxcompno: maximum number of components to return.\n" " C{None} means all possible components.\n" "@param minelements: minimum number of vertices in a component.\n" " By setting this to 2, isolated vertices are not returned\n" " as separate components.\n" "@return: a list of the subgraphs. Every returned subgraph is a\n" " copy of the original.\n"}, /* interface to igraph_contract_vertices */ {"contract_vertices", (PyCFunction) igraphmodule_Graph_contract_vertices, METH_VARARGS | METH_KEYWORDS, "contract_vertices(mapping, combine_attrs=None)\n\n" "Contracts some vertices in the graph, i.e. replaces groups of vertices\n" "with single vertices. Edges are not affected.\n\n" "@param mapping: numeric vector which gives the mapping between old and\n" " new vertex IDs. Vertices having the same new vertex ID in this vector\n" " will be remapped into a single new vertex. It is safe to pass the\n" " membership vector of a L{VertexClustering} object here.\n" "@param combine_attrs: specifies how to combine the attributes of\n" " the vertices being collapsed into a single one. If it is C{None},\n" " all the attributes will be lost. If it is a function, the\n" " attributes of the vertices will be collected and passed on to\n" " that function which will return the new attribute value that has to\n" " be assigned to the single collapsed vertex. It can also be one of\n" " the following string constants which define built-in collapsing\n" " functions: C{sum}, C{prod}, C{mean}, C{median}, C{max}, C{min},\n" " C{first}, C{last}, C{random}. You can also specify different\n" " combination functions for different attributes by passing a dict\n" " here which maps attribute names to functions. See\n" " L{Graph.simplify()} for more details.\n" "@return: C{None}.\n" "@see: L{Graph.simplify()}\n" }, /* interface to igraph_constraint */ {"constraint", (PyCFunction) igraphmodule_Graph_constraint, METH_VARARGS | METH_KEYWORDS, "constraint(vertices=None, weights=None)\n\n" "Calculates Burt's constraint scores for given vertices in a graph.\n\n" "Burt's constraint is higher if ego has less, or mutually stronger\n" "related (i.e. more redundant) contacts. Burt's measure of\n" "constraint, C[i], of vertex i's ego network V[i], is defined for\n" "directed and valued graphs as follows:\n\n" "C[i] = sum( sum( (p[i,q] p[q,j])^2, q in V[i], q != i,j ), j in V[], j != i)\n\n" "for a graph of order (ie. number od vertices) N, where proportional\n" "tie strengths are defined as follows:\n\n" "p[i,j]=(a[i,j]+a[j,i]) / sum(a[i,k]+a[k,i], k in V[i], k != i),\n" "a[i,j] are elements of A and the latter being the graph adjacency matrix.\n\n" "For isolated vertices, constraint is undefined.\n\n" "@param vertices: the vertices to be analysed or C{None} for all vertices.\n" "@param weights: weights associated to the edges. Can be an attribute name\n" " as well. If C{None}, every edge will have the same weight.\n" "@return: constraint scores for all given vertices in a matrix."}, /* interface to igraph_density */ {"density", (PyCFunction) igraphmodule_Graph_density, METH_VARARGS | METH_KEYWORDS, "density(loops=False)\n\n" "Calculates the density of the graph.\n\n" "@param loops: whether to take loops into consideration. If C{True},\n" " the algorithm assumes that there might be some loops in the graph\n" " and calculates the density accordingly. If C{False}, the algorithm\n" " assumes that there can't be any loops.\n" "@return: the reciprocity of the graph."}, /* interfaces to igraph_diameter */ {"diameter", (PyCFunction) igraphmodule_Graph_diameter, METH_VARARGS | METH_KEYWORDS, "diameter(directed=True, unconn=True, weights=None)\n\n" "Calculates the diameter of the graph.\n\n" "@param directed: whether to consider directed paths.\n" "@param unconn: if C{True} and the graph is unconnected, the\n" " longest geodesic within a component will be returned. If\n" " C{False} and the graph is unconnected, the result is the\n" " number of vertices if there are no weights or infinity\n" " if there are weights.\n" "@param weights: edge weights to be used. Can be a sequence or iterable or\n" " even an edge attribute name.\n" "@return: the diameter"}, {"get_diameter", (PyCFunction) igraphmodule_Graph_get_diameter, METH_VARARGS | METH_KEYWORDS, "get_diameter(directed=True, unconn=True, weights=None)\n\n" "Returns a path with the actual diameter of the graph.\n\n" "If there are many shortest paths with the length of the diameter,\n" "it returns the first one it founds.\n\n" "@param directed: whether to consider directed paths.\n" "@param unconn: if C{True} and the graph is unconnected, the\n" " longest geodesic within a component will be returned. If\n" " C{False} and the graph is unconnected, the result is the\n" " number of vertices if there are no weights or infinity\n" " if there are weights.\n" "@param weights: edge weights to be used. Can be a sequence or iterable or\n" " even an edge attribute name.\n" "@return: the vertices in the path in order."}, {"farthest_points", (PyCFunction) igraphmodule_Graph_farthest_points, METH_VARARGS | METH_KEYWORDS, "farthest_points(directed=True, unconn=True, weights=None)\n\n" "Returns two vertex IDs whose distance equals the actual diameter\n" "of the graph.\n\n" "If there are many shortest paths with the length of the diameter,\n" "it returns the first one it found.\n\n" "@param directed: whether to consider directed paths.\n" "@param unconn: if C{True} and the graph is unconnected, the\n" " longest geodesic within a component will be returned. If\n" " C{False} and the graph is unconnected, the result contains the\n" " number of vertices if there are no weights or infinity\n" " if there are weights.\n" "@param weights: edge weights to be used. Can be a sequence or iterable or\n" " even an edge attribute name.\n" "@return: a triplet containing the two vertex IDs and their distance.\n" " The IDs are C{None} if the graph is unconnected and C{unconn}\n" " is C{False}."}, /* interface to igraph_diversity */ {"diversity", (PyCFunction) igraphmodule_Graph_diversity, METH_VARARGS | METH_KEYWORDS, "diversity(vertices=None, weights=None)\n\n" "Calculates the structural diversity index of the vertices.\n\n" "The structural diversity index of a vertex is simply the (normalized)\n" "Shannon entropy of the weights of the edges incident on the vertex.\n\n" "The measure is defined for undirected graphs only; edge directions are\n" "ignored.\n\n" "@param vertices: the vertices for which the diversity indices must\n" " be returned. If C{None}, uses all of the vertices in the graph.\n" "@param weights: edge weights to be used. Can be a sequence or iterable or\n" " even an edge attribute name.\n" "@return: the calculated diversity indices in a list, or a single number if\n" " a single vertex was supplied.\n" "@newfield ref: Reference\n" "@ref: Eagle N, Macy M and Claxton R: Network diversity and economic\n" " development, Science 328, 1029--1031, 2010." }, /* interface to igraph_eccentricity */ {"eccentricity", (PyCFunction) igraphmodule_Graph_eccentricity, METH_VARARGS | METH_KEYWORDS, "eccentricity(vertices=None, mode=ALL)\n\n" "Calculates the eccentricities of given vertices in a graph.\n\n" "The eccentricity of a vertex is calculated by measuring the\n" "shortest distance from (or to) the vertex, to (or from) all other\n" "vertices in the graph, and taking the maximum.\n\n" "@param vertices: the vertices for which the eccentricity scores must\n" " be returned. If C{None}, uses all of the vertices in the graph.\n" "@param mode: must be one of L{IN}, L{OUT} and L{ALL}. L{IN} means\n" " that edge directions are followed; C{OUT} means that edge directions\n" " are followed the opposite direction; C{ALL} means that directions are\n" " ignored. The argument has no effect for undirected graphs.\n" "@return: the calculated eccentricities in a list, or a single number if\n" " a single vertex was supplied.\n"}, /* interface to igraph_edge_betweenness[_estimate] */ {"edge_betweenness", (PyCFunction) igraphmodule_Graph_edge_betweenness, METH_VARARGS | METH_KEYWORDS, "edge_betweenness(directed=True, cutoff=None, weights=None)\n\n" "Calculates or estimates the edge betweennesses in a graph.\n\n" "@param directed: whether to consider directed paths.\n" "@param cutoff: if it is an integer, only paths less than or equal to this\n" " length are considered, effectively resulting in an estimation of the\n" " betweenness values. If C{None}, the exact betweennesses are\n" " returned.\n" "@param weights: edge weights to be used. Can be a sequence or iterable or\n" " even an edge attribute name.\n" "@return: a list with the (exact or estimated) edge betweennesses of all\n" " edges.\n"}, {"eigen_adjacency", (PyCFunction) igraphmodule_Graph_eigen_adjacency, METH_VARARGS | METH_KEYWORDS, "" }, /* interface to igraph_[st_]edge_connectivity */ {"edge_connectivity", (PyCFunction) igraphmodule_Graph_edge_connectivity, METH_VARARGS | METH_KEYWORDS, "edge_connectivity(source=-1, target=-1, checks=True)\n\n" "Calculates the edge connectivity of the graph or between some vertices.\n\n" "The edge connectivity between two given vertices is the number of edges\n" "that have to be removed in order to disconnect the two vertices into two\n" "separate components. This is also the number of edge disjoint directed\n" "paths between the vertices. The edge connectivity of the graph is the minimal\n" "edge connectivity over all vertex pairs.\n\n" "This method calculates the edge connectivity of a given vertex pair if both\n" "the source and target vertices are given. If none of them is given (or they\n" "are both negative), the overall edge connectivity is returned.\n\n" "@param source: the source vertex involved in the calculation.\n" "@param target: the target vertex involved in the calculation.\n" "@param checks: if the whole graph connectivity is calculated and this is\n" " C{True}, igraph performs some basic checks before calculation. If the\n" " graph is not strongly connected, then the connectivity is obviously\n" " zero. If the minimum degree is one, then the connectivity is\n" " also one. These simple checks are much faster than checking the entire\n" " graph, therefore it is advised to set this to C{True}. The parameter\n" " is ignored if the connectivity between two given vertices is computed.\n" "@return: the edge connectivity\n" }, /* interface to igraph_eigenvector_centrality */ {"eigenvector_centrality", (PyCFunction) igraphmodule_Graph_eigenvector_centrality, METH_VARARGS | METH_KEYWORDS, "eigenvector_centrality(directed=True, scale=True, weights=None, return_eigenvalue=False, arpack_options=None)\n\n" "Calculates the eigenvector centralities of the vertices in a graph.\n\n" "@param directed: whether to consider edge directions in a directed\n" " graph. Ignored for undirected graphs.\n" "@param scale: whether to normalize the centralities so the largest\n" " one will always be 1.\n" "@param weights: edge weights given as a list or an edge attribute. If\n" " C{None}, all edges have equal weight.\n" "@param return_eigenvalue: whether to return the actual largest\n" " eigenvalue along with the centralities\n" "@param arpack_options: an L{ARPACKOptions} object that can be used\n" " to fine-tune the calculation. If it is omitted, the module-level\n" " variable called C{arpack_options} is used.\n" "@return: the eigenvector centralities in a list and optionally the\n" " largest eigenvalue (as a second member of a tuple)" }, /* interface to igraph_feedback_arc_set */ {"feedback_arc_set", (PyCFunction) igraphmodule_Graph_feedback_arc_set, METH_VARARGS | METH_KEYWORDS, "feedback_arc_set(weights=None, method=\"eades\")\n\n" "Calculates an approximately or exactly minimal feedback arc set.\n\n" "A feedback arc set is a set of edges whose removal makes the graph acyclic.\n" "Since this is always possible by removing all the edges, we are in general\n" "interested in removing the smallest possible number of edges, or an edge set\n" "with as small total weight as possible. This method calculates one such edge\n" "set. Note that the task is trivial for an undirected graph as it is enough\n" "to find a spanning tree and then remove all the edges not in the spanning\n" "tree. Of course it is more complicated for directed graphs.\n\n" "@param weights: edge weights to be used. Can be a sequence or iterable or\n" " even an edge attribute name. When given, the algorithm will strive to\n" " remove lightweight edges in order to minimize the total weight of the\n" " feedback arc set.\n" "@param method: the algorithm to use. C{\"eades\"} uses the greedy cycle\n" " breaking heuristic of Eades, Lin and Smyth, which is linear in the number\n" " of edges but not necessarily optimal; however, it guarantees that the\n" " number of edges to be removed is smaller than |E|/2 - |V|/6. C{\"ip\"} uses\n" " an integer programming formulation which is guaranteed to yield an optimal\n" " result, but is too slow for large graphs.\n" "@return: the IDs of the edges to be removed, in a list.\n\n" "@newfield ref: Reference\n" "@ref: Eades P, Lin X and Smyth WF: A fast and effective heuristic for the\n" " feedback arc set problem. In: Proc Inf Process Lett 319-323, 1993.\n" }, // interface to igraph_get_shortest_paths {"get_shortest_paths", (PyCFunction) igraphmodule_Graph_get_shortest_paths, METH_VARARGS | METH_KEYWORDS, "get_shortest_paths(v, to=None, weights=None, mode=OUT, output=\"vpath\")\n\n" "Calculates the shortest paths from/to a given node in a graph.\n\n" "@param v: the source/destination for the calculated paths\n" "@param to: a vertex selector describing the destination/source for\n" " the calculated paths. This can be a single vertex ID, a list of\n" " vertex IDs, a single vertex name, a list of vertex names or a\n" " L{VertexSeq} object. C{None} means all the vertices.\n" "@param weights: edge weights in a list or the name of an edge attribute\n" " holding edge weights. If C{None}, all edges are assumed to have\n" " equal weight.\n" "@param mode: the directionality of the paths. L{IN} means to\n" " calculate incoming paths, L{OUT} means to calculate outgoing\n" " paths, L{ALL} means to calculate both ones.\n" "@param output: determines what should be returned. If this is\n" " C{\"vpath\"}, a list of vertex IDs will be returned, one path\n" " for each target vertex. For unconnected graphs, some of the list\n" " elements may be empty. Note that in case of mode=L{IN}, the vertices\n" " in a path are returned in reversed order. If C{output=\"epath\"},\n" " edge IDs are returned instead of vertex IDs.\n" "@return: see the documentation of the C{output} parameter.\n"}, /* interface to igraph_get_all_shortest_paths */ {"get_all_shortest_paths", (PyCFunction) igraphmodule_Graph_get_all_shortest_paths, METH_VARARGS | METH_KEYWORDS, "get_all_shortest_paths(v, to=None, weights=None, mode=OUT)\n\n" "Calculates all of the shortest paths from/to a given node in a graph.\n\n" "@param v: the source for the calculated paths\n" "@param to: a vertex selector describing the destination for\n" " the calculated paths. This can be a single vertex ID, a list of\n" " vertex IDs, a single vertex name, a list of vertex names or a\n" " L{VertexSeq} object. C{None} means all the vertices.\n" "@param weights: edge weights in a list or the name of an edge attribute\n" " holding edge weights. If C{None}, all edges are assumed to have\n" " equal weight.\n" "@param mode: the directionality of the paths. L{IN} means to\n" " calculate incoming paths, L{OUT} means to calculate outgoing\n" " paths, L{ALL} means to calculate both ones.\n" "@return: all of the shortest path from the given node to every other\n" " reachable node in the graph in a list. Note that in case of mode=L{IN},\n" " the vertices in a path are returned in reversed order!"}, /* interface to igraph_get_all_simple_paths */ {"_get_all_simple_paths", (PyCFunction) igraphmodule_Graph_get_all_simple_paths, METH_VARARGS | METH_KEYWORDS, "_get_all_simple_paths(v, to=None, cutoff=-1, mode=OUT)\n\n" "Internal function, undocumented.\n\n" "@see: Graph.get_all_simple_paths()\n\n" }, /* interface to igraph_girth */ {"girth", (PyCFunction)igraphmodule_Graph_girth, METH_VARARGS | METH_KEYWORDS, "girth(return_shortest_circle=False)\n\n" "Returns the girth of the graph.\n\n" "The girth of a graph is the length of the shortest circle in it.\n\n" "@param return_shortest_circle: whether to return one of the shortest\n" " circles found in the graph.\n" "@return: the length of the shortest circle or (if C{return_shortest_circle})\n" " is true, the shortest circle itself as a list\n" }, /* interface to igraph_convergence_degree */ {"convergence_degree", (PyCFunction)igraphmodule_Graph_convergence_degree, METH_NOARGS, "convergence_degree()\n\n" "Undocumented (yet)." }, /* interface to igraph_convergence_field_size */ {"convergence_field_size", (PyCFunction)igraphmodule_Graph_convergence_field_size, METH_NOARGS, "convergence_field_size()\n\n" "Undocumented (yet)." }, /* interface to igraph_hub_score */ {"hub_score", (PyCFunction)igraphmodule_Graph_hub_score, METH_VARARGS | METH_KEYWORDS, "hub_score(weights=None, scale=True, arpack_options=None, return_eigenvalue=False)\n\n" "Calculates Kleinberg's hub score for the vertices of the graph\n\n" "@param weights: edge weights to be used. Can be a sequence or iterable or\n" " even an edge attribute name.\n" "@param scale: whether to normalize the scores so that the largest one\n" " is 1.\n" "@param arpack_options: an L{ARPACKOptions} object used to fine-tune\n" " the ARPACK eigenvector calculation. If omitted, the module-level\n" " variable called C{arpack_options} is used.\n" "@param return_eigenvalue: whether to return the largest eigenvalue\n" "@return: the hub scores in a list and optionally the largest eigenvalue\n" " as a second member of a tuple\n\n" "@see: authority_score()\n" }, /* interface to igraph_induced_subgraph */ {"induced_subgraph", (PyCFunction) igraphmodule_Graph_induced_subgraph, METH_VARARGS | METH_KEYWORDS, "induced_subgraph(vertices, implementation=\"auto\")\n\n" "Returns a subgraph spanned by the given vertices.\n\n" "@param vertices: a list containing the vertex IDs which\n" " should be included in the result.\n" "@param implementation: the implementation to use when constructing\n" " the new subgraph. igraph includes two implementations at the\n" " moment. C{\"copy_and_delete\"} copies the original graph and\n" " removes those vertices that are not in the given set. This is more\n" " efficient if the size of the subgraph is comparable to the original\n" " graph. The other implementation (C{\"create_from_scratch\"})\n" " constructs the result graph from scratch and then copies the\n" " attributes accordingly. This is a better solution if the subgraph\n" " is relatively small, compared to the original graph. C{\"auto\"}\n" " selects between the two implementations automatically, based on\n" " the ratio of the size of the subgraph and the size of the original\n" " graph.\n" "@return: the subgraph\n"}, /* interface to igraph_is_bipartite */ {"is_bipartite", (PyCFunction) igraphmodule_Graph_is_bipartite, METH_VARARGS | METH_KEYWORDS, "is_bipartite(return_types=False)\n\n" "Decides whether the graph is bipartite or not.\n\n" "Vertices of a bipartite graph can be partitioned into two groups A\n" "and B in a way that all edges go between the two groups.\n\n" "@param return_types: if C{False}, the method will simply\n" " return C{True} or C{False} depending on whether the graph is\n" " bipartite or not. If C{True}, the actual group assignments\n" " are also returned as a list of boolean values. (Note that\n" " the group assignment is not unique, especially if the graph\n" " consists of multiple components, since the assignments of\n" " components are independent from each other).\n" "@return: C{True} if the graph is bipartite, C{False} if not.\n" " If C{return_types} is C{True}, the group assignment is also\n" " returned.\n" }, /* interface to igraph_avg_nearest_neighbor_degree */ {"knn", (PyCFunction) igraphmodule_Graph_knn, METH_VARARGS | METH_KEYWORDS, "knn(vids=None, weights=None)\n\n" "Calculates the average degree of the neighbors for each vertex, and\n" "the same quantity as the function of vertex degree.\n\n" "@param vids: the vertices for which the calculation is performed.\n" " C{None} means all vertices.\n" "@param weights: edge weights to be used. Can be a sequence or iterable or\n" " even an edge attribute name. If this is given, the vertex strength\n" " will be used instead of the vertex degree in the calculations, but\n" " the \"ordinary\" vertex degree will be used for the second (degree-\n" " dependent) list in the result.\n" "@return: two lists in a tuple. The first list contains the average\n" " degree of neighbors for each vertex, the second contains the average\n" " degree of neighbors as a function of vertex degree. The zeroth element\n" " of this list corresponds to vertices of degree 1.\n" }, /* interface to igraph_is_connected */ {"is_connected", (PyCFunction) igraphmodule_Graph_is_connected, METH_VARARGS | METH_KEYWORDS, "is_connected(mode=STRONG)\n\n" "Decides whether the graph is connected.\n\n" "@param mode: whether we should calculate strong or weak connectivity.\n" "@return: C{True} if the graph is connected, C{False} otherwise.\n"}, /* interface to igraph_linegraph */ {"linegraph", (PyCFunction) igraphmodule_Graph_linegraph, METH_VARARGS | METH_KEYWORDS, "linegraph()\n\n" "Returns the line graph of the graph.\n\n" "The line graph M{L(G)} of an undirected graph is defined as follows:\n" "M{L(G)} has one vertex for each edge in G and two vertices in M{L(G)}\n" "are connected iff their corresponding edges in the original graph\n" "share an end point.\n\n" "The line graph of a directed graph is slightly different: two vertices\n" "are connected by a directed edge iff the target of the first vertex's\n" "corresponding edge is the same as the source of the second vertex's\n" "corresponding edge.\n" }, /* interface to igraph_maxdegree */ {"maxdegree", (PyCFunction) igraphmodule_Graph_maxdegree, METH_VARARGS | METH_KEYWORDS, "maxdegree(vertices=None, mode=ALL, loops=False)\n\n" "Returns the maximum degree of a vertex set in the graph.\n\n" "This method accepts a single vertex ID or a list of vertex IDs as a\n" "parameter, and returns the degree of the given vertices (in the\n" "form of a single integer or a list, depending on the input\n" "parameter).\n" "\n" "@param vertices: a single vertex ID or a list of vertex IDs, or\n" " C{None} meaning all the vertices in the graph.\n" "@param mode: the type of degree to be returned (L{OUT} for\n" " out-degrees, L{IN} IN for in-degrees or L{ALL} for the sum of\n" " them).\n" "@param loops: whether self-loops should be counted.\n"}, /* interface to igraph_neighborhood */ {"neighborhood", (PyCFunction) igraphmodule_Graph_neighborhood, METH_VARARGS | METH_KEYWORDS, "neighborhood(vertices=None, order=1, mode=ALL, mindist=0)\n\n" "For each vertex specified by I{vertices}, returns the\n" "vertices reachable from that vertex in at most I{order} steps. If\n" "I{mindist} is larger than zero, vertices that are reachable in less\n" "than I{mindist} steps are excluded.\n\n" "@param vertices: a single vertex ID or a list of vertex IDs, or\n" " C{None} meaning all the vertices in the graph.\n" "@param order: the order of the neighborhood, i.e. the maximum number of\n" " steps to take from the seed vertex.\n" "@param mode: specifies how to take into account the direction of\n" " the edges if a directed graph is analyzed. C{\"out\"} means that\n" " only the outgoing edges are followed, so all vertices reachable\n" " from the source vertex in at most I{order} steps are counted.\n" " C{\"in\"} means that only the incoming edges are followed (in\n" " reverse direction of course), so all vertices from which the source\n" " vertex is reachable in at most I{order} steps are counted. C{\"all\"}\n" " treats directed edges as undirected.\n" "@param mindist: the minimum distance required to include a vertex in the\n" " result. If this is one, the seed vertex is not included. If this is two,\n" " the direct neighbors of the seed vertex are not included either, and so on.\n" "@return: a single list specifying the neighborhood if I{vertices}\n" " was an integer specifying a single vertex index, or a list of lists\n" " if I{vertices} was a list or C{None}.\n" }, /* interface to igraph_neighborhood_size */ {"neighborhood_size", (PyCFunction) igraphmodule_Graph_neighborhood_size, METH_VARARGS | METH_KEYWORDS, "neighborhood_size(vertices=None, order=1, mode=ALL, mindist=0)\n\n" "For each vertex specified by I{vertices}, returns the number of\n" "vertices reachable from that vertex in at most I{order} steps. If\n" "I{mindist} is larger than zero, vertices that are reachable in less\n" "than I{mindist} steps are excluded.\n\n" "@param vertices: a single vertex ID or a list of vertex IDs, or\n" " C{None} meaning all the vertices in the graph.\n" "@param order: the order of the neighborhood, i.e. the maximum number of\n" " steps to take from the seed vertex.\n" "@param mode: specifies how to take into account the direction of\n" " the edges if a directed graph is analyzed. C{\"out\"} means that\n" " only the outgoing edges are followed, so all vertices reachable\n" " from the source vertex in at most I{order} steps are counted.\n" " C{\"in\"} means that only the incoming edges are followed (in\n" " reverse direction of course), so all vertices from which the source\n" " vertex is reachable in at most I{order} steps are counted. C{\"all\"}\n" " treats directed edges as undirected.\n" "@param mindist: the minimum distance required to include a vertex in the\n" " result. If this is one, the seed vertex is not counted. If this is two,\n" " the direct neighbors of the seed vertex are not counted either, and so on.\n" "@return: a single number specifying the neighborhood size if I{vertices}\n" " was an integer specifying a single vertex index, or a list of sizes\n" " if I{vertices} was a list or C{None}.\n" }, /* interface to igraph_personalized_pagerank */ {"personalized_pagerank", (PyCFunction) igraphmodule_Graph_personalized_pagerank, METH_VARARGS | METH_KEYWORDS, "personalized_pagerank(vertices=None, directed=True, damping=0.85,\n" " reset=None, reset_vertices=None, weights=None, \n" " arpack_options=None, implementation=\"prpack\", niter=1000,\n" " eps=0.001)\n\n" "Calculates the personalized PageRank values of a graph.\n\n" "The personalized PageRank calculation is similar to the PageRank\n" "calculation, but the random walk is reset to a non-uniform distribution\n" "over the vertices in every step with probability M{1-damping} instead of a\n" "uniform distribution.\n\n" "@param vertices: the indices of the vertices being queried.\n" " C{None} means all of the vertices.\n" "@param directed: whether to consider directed paths.\n" "@param damping: the damping factor.\n" " M{1-damping} is the PageRank value for vertices with no\n" " incoming links.\n" "@param reset: the distribution over the vertices to be used when resetting\n" " the random walk. Can be a sequence, an iterable or a vertex attribute\n" " name as long as they return a list of floats whose length is equal to\n" " the number of vertices. If C{None}, a uniform distribution is assumed,\n" " which makes the method equivalent to the original PageRank algorithm.\n" "@param reset_vertices: an alternative way to specify the distribution\n" " over the vertices to be used when resetting the random walk. Simply\n" " supply a list of vertex IDs here, or a L{VertexSeq} or a L{Vertex}.\n" " Resetting will take place using a uniform distribution over the specified\n" " vertices.\n" "@param weights: edge weights to be used. Can be a sequence or iterable or\n" " even an edge attribute name.\n" "@param arpack_options: an L{ARPACKOptions} object used to fine-tune\n" " the ARPACK eigenvector calculation. If omitted, the module-level\n" " variable called C{arpack_options} is used. This argument is\n" " ignored if not the ARPACK implementation is used, see the \n" " I{implementation} argument.\n" "@param implementation: which implementation to use to solve the \n" " PageRank eigenproblem. Possible values are:\n\n" " - C{\"prpack\"}: use the PRPACK library. This is a new \n" " implementation in igraph 0.7\n\n" " - C{\"arpack\"}: use the ARPACK library. This implementation\n" " was used from version 0.5, until version 0.7.\n\n" " - C{\"power\"}: use a simple power method. This is the\n" " implementation that was used before igraph version 0.5.\n\n" "@param niter: The number of iterations to use in the power method\n" " implementation. It is ignored in the other implementations.\n" "@param eps: The power method implementation will consider the\n" " calculation as complete if the difference of PageRank values between\n" " iterations change less than this value for every node. It is \n" " ignored by the other implementations.\n" "@return: a list with the personalized PageRank values of the specified\n" " vertices.\n"}, /* interface to igraph_path_length_hist */ {"path_length_hist", (PyCFunction) igraphmodule_Graph_path_length_hist, METH_VARARGS | METH_KEYWORDS, "path_length_hist(directed=True)\n\n" "Calculates the path length histogram of the graph\n" "@attention: this function is wrapped in a more convenient syntax in the\n" " derived class L{Graph}. It is advised to use that instead of this version.\n\n" "@param directed: whether to consider directed paths\n" "@return: a tuple. The first item of the tuple is a list of path lengths,\n" " the M{i}th element of the list contains the number of paths with length\n" " M{i+1}. The second item contains the number of unconnected vertex pairs\n" " as a float (since it might not fit into an integer)\n" }, /* interface to igraph_permute_vertices */ {"permute_vertices", (PyCFunction) igraphmodule_Graph_permute_vertices, METH_VARARGS | METH_KEYWORDS, "permute_vertices(permutation)\n\n" "Permutes the vertices of the graph according to the given permutation\n" "and returns the new graph.\n\n" "Vertex M{k} of the original graph will become vertex M{permutation[k]}\n" "in the new graph. No validity checks are performed on the permutation\n" "vector.\n\n" "@return: the new graph\n" }, /* interfaces to igraph_radius */ {"radius", (PyCFunction) igraphmodule_Graph_radius, METH_VARARGS | METH_KEYWORDS, "radius(mode=OUT)\n\n" "Calculates the radius of the graph.\n\n" "The radius of a graph is defined as the minimum eccentricity of\n" "its vertices (see L{eccentricity()}).\n" "@param mode: what kind of paths to consider for the calculation\n" " in case of directed graphs. C{OUT} considers paths that follow\n" " edge directions, C{IN} considers paths that follow the opposite\n" " edge directions, C{ALL} ignores edge directions. The argument is\n" " ignored for undirected graphs.\n" "@return: the radius\n" "@see: L{Graph.eccentricity()}" }, /* interface to igraph_reciprocity */ {"reciprocity", (PyCFunction) igraphmodule_Graph_reciprocity, METH_VARARGS | METH_KEYWORDS, "reciprocity(ignore_loops=True, mode=\"default\")\n\n" "Reciprocity defines the proportion of mutual connections in a\n" "directed graph. It is most commonly defined as the probability\n" "that the opposite counterpart of a directed edge is also included\n" "in the graph. This measure is calculated if C{mode} is C{\"default\"}.\n" "\n" "Prior to igraph 0.6, another measure was implemented, defined as\n" "the probability of mutual connection between a vertex pair if we\n" "know that there is a (possibly non-mutual) connection between them.\n" "In other words, (unordered) vertex pairs are classified into three\n" "groups: (1) disconnected, (2) non-reciprocally connected and (3)\n" "reciprocally connected. The result is the size of group (3), divided\n" "by the sum of sizes of groups (2) and (3). This measure is calculated\n" "if C{mode} is C{\"ratio\"}.\n" "\n" "@param ignore_loops: whether loop edges should be ignored.\n" "@param mode: the algorithm to use to calculate the reciprocity; see\n" " above for more details.\n" "@return: the reciprocity of the graph\n" }, /* interface to igraph_rewire */ {"rewire", (PyCFunction) igraphmodule_Graph_rewire, METH_VARARGS | METH_KEYWORDS, "rewire(n=1000, mode=\"simple\")\n\n" "Randomly rewires the graph while preserving the degree distribution.\n\n" "Please note that the rewiring is done \"in-place\", so the original\n" "graph will be modified. If you want to preserve the original graph,\n" "use the L{copy} method before.\n\n" "@param n: the number of rewiring trials.\n" "@param mode: the rewiring algorithm to use. It can either be C{\"simple\"} or\n" " C{\"loops\"}; the former does not create or destroy loop edges while the\n" " latter does.\n"}, /* interface to igraph_rewire_edges */ {"rewire_edges", (PyCFunction) igraphmodule_Graph_rewire_edges, METH_VARARGS | METH_KEYWORDS, "rewire_edges(prob, loops=False, multiple=False)\n\n" "Rewires the edges of a graph with constant probability.\n\n" "Each endpoint of each edge of the graph will be rewired with a constant\n" "probability, given in the first argument.\n\n" "Please note that the rewiring is done \"in-place\", so the original\n" "graph will be modified. If you want to preserve the original graph,\n" "use the L{copy} method before.\n\n" "@param prob: rewiring probability\n" "@param loops: whether the algorithm is allowed to create loop edges\n" "@param multiple: whether the algorithm is allowed to create multiple\n" " edges.\n"}, /* interface to igraph_shortest_paths */ {"shortest_paths", (PyCFunction) igraphmodule_Graph_shortest_paths, METH_VARARGS | METH_KEYWORDS, "shortest_paths(source=None, target=None, weights=None, mode=OUT)\n\n" "Calculates shortest path lengths for given vertices in a graph.\n\n" "The algorithm used for the calculations is selected automatically:\n" "a simple BFS is used for unweighted graphs, Dijkstra's algorithm is\n" "used when all the weights are positive. Otherwise, the Bellman-Ford\n" "algorithm is used if the number of requested source vertices is larger\n" "than 100 and Johnson's algorithm is used otherwise.\n\n" "@param source: a list containing the source vertex IDs which should be\n" " included in the result. If C{None}, all vertices will be considered.\n" "@param target: a list containing the target vertex IDs which should be\n" " included in the result. If C{None}, all vertices will be considered.\n" "@param weights: a list containing the edge weights. It can also be\n" " an attribute name (edge weights are retrieved from the given\n" " attribute) or C{None} (all edges have equal weight).\n" "@param mode: the type of shortest paths to be used for the\n" " calculation in directed graphs. L{OUT} means only outgoing,\n" " L{IN} means only incoming paths. L{ALL} means to consider\n" " the directed graph as an undirected one.\n" "@return: the shortest path lengths for given vertices in a matrix\n"}, /* interface to igraph_simplify */ {"simplify", (PyCFunction) igraphmodule_Graph_simplify, METH_VARARGS | METH_KEYWORDS, "simplify(multiple=True, loops=True, combine_edges=None)\n\n" "Simplifies a graph by removing self-loops and/or multiple edges.\n\n" "\n" "For example, suppose you have a graph with an edge attribute named\n" "C{weight}. C{graph.simplify(combine_edges=max)} will take the\n" "maximum of the weights of multiple edges and assign that weight to\n" "the collapsed edge. C{graph.simplify(combine_edges=sum)} will\n" "take the sum of the weights. You can also write\n" "C{graph.simplify(combine_edges=dict(weight=\"sum\"))} or\n" "C{graph.simplify(combine_edges=dict(weight=sum))}, since\n" "C{sum} is recognised both as a Python built-in function and as\n" "a string constant.\n\n" "@param multiple: whether to remove multiple edges.\n" "@param loops: whether to remove loops.\n" "@param combine_edges: specifies how to combine the attributes of\n" " multiple edges between the same pair of vertices into a single\n" " attribute. If it is C{None}, only one of the edges will be kept\n" " and all the attributes will be lost. If it is a function, the\n" " attributes of multiple edges will be collected and passed on to\n" " that function which will return the new attribute value that has to\n" " be assigned to the single collapsed edge. It can also be one of\n" " the following string constants:\n\n" " - C{\"ignore\"}: all the edge attributes will be ignored.\n\n" " - C{\"sum\"}: the sum of the edge attribute values will be used for\n" " the new edge.\n\n" " - C{\"product\"}: the product of the edge attribute values will be used for\n" " the new edge.\n" " - C{\"mean\"}: the mean of the edge attribute values will be used for\n" " the new edge.\n\n" " - C{\"median\"}: the median of the edge attribute values will be used for\n" " the new edge.\n\n" " - C{\"min\"}: the minimum of the edge attribute values will be used for\n" " the new edge.\n\n" " - C{\"max\"}: the maximum of the edge attribute values will be used for\n" " the new edge.\n\n" " - C{\"first\"}: the attribute value of the first edge in the collapsed set\n" " will be used for the new edge.\n\n" " - C{\"last\"}: the attribute value of the last edge in the collapsed set\n" " will be used for the new edge.\n\n" " - C{\"random\"}: a randomly selected value will be used for the new edge\n\n" " - C{\"concat\"}: the attribute values will be concatenated for the new\n" " edge.\n\n" " You can also use a dict mapping edge attribute names to functions or\n" " the above string constants if you want to make the behaviour of the\n" " simplification process depend on the name of the attribute.\n" " C{None} is a special key in this dict, its value will be used for all\n" " the attributes not specified explicitly in the dictionary.\n" }, /* interface to igraph_minimum_spanning_tree */ {"_spanning_tree", (PyCFunction) igraphmodule_Graph_spanning_tree, METH_VARARGS | METH_KEYWORDS, "_spanning_tree(weights=None)\n\n" "Internal function, undocumented.\n\n" "@see: Graph.spanning_tree()"}, // interface to igraph_subcomponent {"subcomponent", (PyCFunction) igraphmodule_Graph_subcomponent, METH_VARARGS | METH_KEYWORDS, "subcomponent(v, mode=ALL)\n\n" "Determines the indices of vertices which are in the same component as a given vertex.\n\n" "@param v: the index of the vertex used as the source/destination\n" "@param mode: if equals to L{IN}, returns the vertex IDs from\n" " where the given vertex can be reached. If equals to L{OUT},\n" " returns the vertex IDs which are reachable from the given\n" " vertex. If equals to L{ALL}, returns all vertices within the\n" " same component as the given vertex, ignoring edge directions.\n" " Note that this is not equal to calculating the union of the \n" " results of L{IN} and L{OUT}.\n" "@return: the indices of vertices which are in the same component as a given vertex.\n"}, /* interface to igraph_subgraph_edges */ {"subgraph_edges", (PyCFunction) igraphmodule_Graph_subgraph_edges, METH_VARARGS | METH_KEYWORDS, "subgraph_edges(edges, delete_vertices=True)\n\n" "Returns a subgraph spanned by the given edges.\n\n" "@param edges: a list containing the edge IDs which should\n" " be included in the result.\n" "@param delete_vertices: if C{True}, vertices not incident on\n" " any of the specified edges will be deleted from the result.\n" " If C{False}, all vertices will be kept.\n" "@return: the subgraph\n"}, /* interface to igraph_topological_sorting */ {"topological_sorting", (PyCFunction) igraphmodule_Graph_topological_sorting, METH_VARARGS | METH_KEYWORDS, "topological_sorting(mode=OUT)\n\n" "Calculates a possible topological sorting of the graph.\n\n" "Returns a partial sorting and issues a warning if the graph is not\n" "a directed acyclic graph.\n\n" "@param mode: if L{OUT}, vertices are returned according to the\n" " forward topological order -- all vertices come before their\n" " successors. If L{IN}, all vertices come before their ancestors.\n" "@return: a possible topological ordering as a list"}, /* interface to to_prufer */ {"to_prufer", (PyCFunction) igraphmodule_Graph_to_prufer, METH_NOARGS, "to_prufer()\n\n" "Converts a tree graph into a Prufer sequence.\n\n" "@return: the Prufer sequence as a list" }, // interface to igraph_transitivity_undirected {"transitivity_undirected", (PyCFunction) igraphmodule_Graph_transitivity_undirected, METH_VARARGS | METH_KEYWORDS, "transitivity_undirected(mode=\"nan\")\n\n" "Calculates the global transitivity (clustering coefficient) of the\n" "graph.\n\n" "The transitivity measures the probability that two neighbors of a\n" "vertex are connected. More precisely, this is the ratio of the\n" "triangles and connected triplets in the graph. The result is a\n" "single real number. Directed graphs are considered as undirected\n" "ones.\n\n" "Note that this measure is different from the local transitivity\n" "measure (see L{transitivity_local_undirected()}) as it calculates\n" "a single value for the whole graph.\n\n" "@param mode: if C{TRANSITIVITY_ZERO} or C{\"zero\"}, the result will\n" " be zero if the graph does not have any triplets. If C{\"nan\"} or\n" " C{TRANSITIVITY_NAN}, the result will be C{NaN} (not a number).\n" "@return: the transitivity\n" "@see: L{transitivity_local_undirected()}, L{transitivity_avglocal_undirected()}\n" "@newfield ref: Reference\n" "@ref: S. Wasserman and K. Faust: I{Social Network Analysis: Methods and\n" " Applications}. Cambridge: Cambridge University Press, 1994." }, /* interface to igraph_transitivity_local_undirected and * igraph_transitivity_barrat */ {"transitivity_local_undirected", (PyCFunction) igraphmodule_Graph_transitivity_local_undirected, METH_VARARGS | METH_KEYWORDS, "transitivity_local_undirected(vertices=None, mode=\"nan\", weights=None)\n\n" "Calculates the local transitivity (clustering coefficient) of the\n" "given vertices in the graph.\n\n" "The transitivity measures the probability that two neighbors of a\n" "vertex are connected. In case of the local transitivity, this\n" "probability is calculated separately for each vertex.\n\n" "Note that this measure is different from the global transitivity\n" "measure (see L{transitivity_undirected()}) as it calculates\n" "a transitivity value for each vertex individually.\n\n" "The traditional local transitivity measure applies for unweighted graphs\n" "only. When the C{weights} argument is given, this function calculates\n" "the weighted local transitivity proposed by Barrat et al (see references).\n\n" "@param vertices: a list containing the vertex IDs which should be\n" " included in the result. C{None} means all of the vertices.\n" "@param mode: defines how to treat vertices with degree less than two.\n" " If C{TRANSITIVITT_ZERO} or C{\"zero\"}, these vertices will have\n" " zero transitivity. If C{TRANSITIVITY_NAN} or C{\"nan\"}, these\n" " vertices will have C{NaN} (not a number) as their transitivity.\n" "@param weights: edge weights to be used. Can be a sequence or iterable or\n" " even an edge attribute name.\n" "@return: the transitivities for the given vertices in a list\n" "@see: L{transitivity_undirected()}, L{transitivity_avglocal_undirected()}\n" "@newfield ref: Reference\n" "@ref: Watts DJ and Strogatz S: I{Collective dynamics of small-world\n" " networks}. Nature 393(6884):440-442, 1998.\n" "@ref: Barrat A, Barthelemy M, Pastor-Satorras R and Vespignani A:\n" " I{The architecture of complex weighted networks}. PNAS 101, 3747 (2004).\n" " U{http://arxiv.org/abs/cond-mat/0311416}." }, /* interface to igraph_transitivity_avglocal_undirected */ {"transitivity_avglocal_undirected", (PyCFunction) igraphmodule_Graph_transitivity_avglocal_undirected, METH_VARARGS | METH_KEYWORDS, "transitivity_avglocal_undirected(mode=\"nan\")\n\n" "Calculates the average of the vertex transitivities of the graph.\n\n" "The transitivity measures the probability that two neighbors of a\n" "vertex are connected. In case of the average local transitivity,\n" "this probability is calculated for each vertex and then the average\n" "is taken. Vertices with less than two neighbors require special\n" "treatment, they will either be left out from the calculation or\n" "they will be considered as having zero transitivity, depending on\n" "the I{mode} parameter.\n\n" "Note that this measure is different from the global transitivity measure\n" "(see L{transitivity_undirected()}) as it simply takes the average local\n" "transitivity across the whole network.\n\n" "@param mode: defines how to treat vertices with degree less than two.\n" " If C{TRANSITIVITT_ZERO} or C{\"zero\"}, these vertices will have\n" " zero transitivity. If C{TRANSITIVITY_NAN} or C{\"nan\"}, these\n" " vertices will be excluded from the average.\n" "@see: L{transitivity_undirected()}, L{transitivity_local_undirected()}\n" "@newfield ref: Reference\n" "@ref: D. J. Watts and S. Strogatz: I{Collective dynamics of small-world\n" " networks}. Nature 393(6884):440-442, 1998." }, /* interface to igraph_unfold_tree */ {"unfold_tree", (PyCFunction) igraphmodule_Graph_unfold_tree, METH_VARARGS | METH_KEYWORDS, "unfold_tree(sources=None, mode=OUT)\n\n" "Unfolds the graph using a BFS to a tree by duplicating vertices as necessary.\n\n" "@param sources: the source vertices to start the unfolding from. It should be a\n" " list of vertex indices, preferably one vertex from each connected component.\n" " You can use L{Graph.topological_sorting()} to determine a suitable set. A single\n" " vertex index is also accepted.\n" "@param mode: which edges to follow during the BFS. C{OUT} follows outgoing edges,\n" " C{IN} follows incoming edges, C{ALL} follows both. Ignored for undirected\n" " graphs.\n" "@return: the unfolded tree graph and a mapping from the new vertex indices to the\n" " old ones.\n" }, /* interface to igraph_[st_]vertex_connectivity */ {"vertex_connectivity", (PyCFunction) igraphmodule_Graph_vertex_connectivity, METH_VARARGS | METH_KEYWORDS, "vertex_connectivity(source=-1, target=-1, checks=True, neighbors=\"error\")\n\n" "Calculates the vertex connectivity of the graph or between some vertices.\n\n" "The vertex connectivity between two given vertices is the number of vertices\n" "that have to be removed in order to disconnect the two vertices into two\n" "separate components. This is also the number of vertex disjoint directed\n" "paths between the vertices (apart from the source and target vertices of\n" "course). The vertex connectivity of the graph is the minimal vertex\n" "connectivity over all vertex pairs.\n\n" "This method calculates the vertex connectivity of a given vertex pair if both\n" "the source and target vertices are given. If none of them is given (or they\n" "are both negative), the overall vertex connectivity is returned.\n\n" "@param source: the source vertex involved in the calculation.\n" "@param target: the target vertex involved in the calculation.\n" "@param checks: if the whole graph connectivity is calculated and this is\n" " C{True}, igraph performs some basic checks before calculation. If the\n" " graph is not strongly connected, then the connectivity is obviously\n" " zero. If the minimum degree is one, then the connectivity is\n" " also one. These simple checks are much faster than checking the entire\n" " graph, therefore it is advised to set this to C{True}. The parameter\n" " is ignored if the connectivity between two given vertices is computed.\n" "@param neighbors: tells igraph what to do when the two vertices are\n" " connected. C{\"error\"} raises an exception, C{\"infinity\"} returns\n" " infinity, C{\"ignore\"} ignores the edge.\n" "@return: the vertex connectivity\n" }, /***********************/ /* SIMILARITY MEASURES */ /***********************/ /* interface to igraph_bibcoupling */ {"bibcoupling", (PyCFunction) igraphmodule_Graph_bibcoupling, METH_VARARGS | METH_KEYWORDS, "bibcoupling(vertices=None)\n\n" "Calculates bibliographic coupling scores for given vertices in a graph.\n\n" "@param vertices: the vertices to be analysed. If C{None}, all vertices\n" " will be considered.\n" "@return: bibliographic coupling scores for all given vertices in a matrix."}, /* interface to igraph_cocitation */ {"cocitation", (PyCFunction) igraphmodule_Graph_cocitation, METH_VARARGS | METH_KEYWORDS, "cocitation(vertices=None)\n\n" "Calculates cocitation scores for given vertices in a graph.\n\n" "@param vertices: the vertices to be analysed. If C{None}, all vertices\n" " will be considered.\n" "@return: cocitation scores for all given vertices in a matrix."}, /* interface to igraph_similarity_dice */ {"similarity_dice", (PyCFunction) igraphmodule_Graph_similarity_dice, METH_VARARGS | METH_KEYWORDS, "similarity_dice(vertices=None, pairs=None, mode=IGRAPH_ALL, loops=True)\n\n" "Dice similarity coefficient of vertices.\n\n" "The Dice similarity coefficient of two vertices is twice the number of\n" "their common neighbors divided by the sum of their degrees. This\n" "coefficient is very similar to the Jaccard coefficient, but usually\n" "gives higher similarities than its counterpart.\n\n" "@param vertices: the vertices to be analysed. If C{None} and I{pairs} is also\n" " C{None}, all vertices will be considered.\n" "@param pairs: the vertex pairs to be analysed. If this is given, I{vertices}\n" " must be C{None}, and the similarity values will be calculated only for the\n" " given pairs. Vertex pairs must be specified as tuples of vertex IDs.\n" "@param mode: which neighbors should be considered for directed graphs.\n" " Can be L{ALL}, L{IN} or L{OUT}, ignored for undirected graphs.\n" "@param loops: whether vertices should be considered adjacent to\n" " themselves. Setting this to C{True} assumes a loop edge for all vertices\n" " even if none is present in the graph. Setting this to C{False} may\n" " result in strange results: nonadjacent vertices may have larger\n" " similarities compared to the case when an edge is added between them --\n" " however, this might be exactly the result you want to get.\n" "@return: the pairwise similarity coefficients for the vertices specified,\n" " in the form of a matrix if C{pairs} is C{None} or in the form of a list\n" " if C{pairs} is not C{None}.\n" }, /* interface to igraph_similarity_inverse_log_weighted */ {"similarity_inverse_log_weighted", (PyCFunction) igraphmodule_Graph_similarity_inverse_log_weighted, METH_VARARGS | METH_KEYWORDS, "similarity_inverse_log_weighted(vertices=None, mode=IGRAPH_ALL)\n\n" "Inverse log-weighted similarity coefficient of vertices.\n\n" "Each vertex is assigned a weight which is 1 / log(degree). The\n" "log-weighted similarity of two vertices is the sum of the weights\n" "of their common neighbors.\n\n" "@param vertices: the vertices to be analysed. If C{None}, all vertices\n" " will be considered.\n" "@param mode: which neighbors should be considered for directed graphs.\n" " Can be L{ALL}, L{IN} or L{OUT}, ignored for undirected graphs.\n" " L{IN} means that the weights are determined by the out-degrees, L{OUT}\n" " means that the weights are determined by the in-degrees.\n" "@return: the pairwise similarity coefficients for the vertices specified,\n" " in the form of a matrix (list of lists).\n" }, /* interface to igraph_similarity_jaccard */ {"similarity_jaccard", (PyCFunction) igraphmodule_Graph_similarity_jaccard, METH_VARARGS | METH_KEYWORDS, "similarity_jaccard(vertices=None, pairs=None, mode=IGRAPH_ALL, loops=True)\n\n" "Jaccard similarity coefficient of vertices.\n\n" "The Jaccard similarity coefficient of two vertices is the number of their\n" "common neighbors divided by the number of vertices that are adjacent to\n" "at least one of them.\n\n" "@param vertices: the vertices to be analysed. If C{None} and I{pairs} is also\n" " C{None}, all vertices will be considered.\n" "@param pairs: the vertex pairs to be analysed. If this is given, I{vertices}\n" " must be C{None}, and the similarity values will be calculated only for the\n" " given pairs. Vertex pairs must be specified as tuples of vertex IDs.\n" "@param mode: which neighbors should be considered for directed graphs.\n" " Can be L{ALL}, L{IN} or L{OUT}, ignored for undirected graphs.\n" "@param loops: whether vertices should be considered adjacent to\n" " themselves. Setting this to C{True} assumes a loop edge for all vertices\n" " even if none is present in the graph. Setting this to C{False} may\n" " result in strange results: nonadjacent vertices may have larger\n" " similarities compared to the case when an edge is added between them --\n" " however, this might be exactly the result you want to get.\n" "@return: the pairwise similarity coefficients for the vertices specified,\n" " in the form of a matrix if C{pairs} is C{None} or in the form of a list\n" " if C{pairs} is not C{None}.\n" }, /******************/ /* MOTIF COUNTING */ /******************/ {"motifs_randesu", (PyCFunction) igraphmodule_Graph_motifs_randesu, METH_VARARGS | METH_KEYWORDS, "motifs_randesu(size=3, cut_prob=None, callback=None)\n\n" "Counts the number of motifs in the graph\n\n" "Motifs are small subgraphs of a given structure in a graph. It is\n" "argued that the motif profile (ie. the number of different motifs in\n" "the graph) is characteristic for different types of networks and\n" "network function is related to the motifs in the graph.\n\n" "This function is able to find the different motifs of size three\n" "and four (ie. the number of different subgraphs with three and four\n" "vertices) in the network.\n\n" "In a big network the total number of motifs can be very large, so\n" "it takes a lot of time to find all of them. In such cases, a sampling\n" "method can be used. This function is capable of doing sampling via\n" "the I{cut_prob} argument. This argument gives the probability that\n" "a branch of the motif search tree will not be explored.\n\n" "@newfield ref: Reference\n" "@ref: S. Wernicke and F. Rasche: FANMOD: a tool for fast network\n" " motif detection, Bioinformatics 22(9), 1152--1153, 2006.\n\n" "@param size: the size of the motifs (3 or 4).\n" "@param cut_prob: the cut probabilities for different levels of the search\n" " tree. This must be a list of length I{size} or C{None} to find all\n" " motifs.\n" "@param callback: C{None} or a callable that will be called for every motif\n" " found in the graph. The callable must accept three parameters: the graph\n" " itself, the list of vertices in the motif and the isomorphy class of the\n" " motif (see L{Graph.isoclass()}). The search will stop when the callback\n" " returns an object with a non-zero truth value or raises an exception.\n" "@return: the list of motifs if I{callback} is C{None}, or C{None} otherwise\n" "@see: Graph.motifs_randesu_no()\n" }, {"motifs_randesu_no", (PyCFunction) igraphmodule_Graph_motifs_randesu_no, METH_VARARGS | METH_KEYWORDS, "motifs_randesu_no(size=3, cut_prob=None)\n\n" "Counts the total number of motifs in the graph\n\n" "Motifs are small subgraphs of a given structure in a graph.\n" "This function counts the total number of motifs in a graph without\n" "assigning isomorphism classes to them.\n\n" "@newfield ref: Reference\n" "@ref: S. Wernicke and F. Rasche: FANMOD: a tool for fast network\n" " motif detection, Bioinformatics 22(9), 1152--1153, 2006.\n\n" "@param size: the size of the motifs (3 or 4).\n" "@param cut_prob: the cut probabilities for different levels of the search\n" " tree. This must be a list of length I{size} or C{None} to find all\n" " motifs.\n" "@see: Graph.motifs_randesu()\n" }, {"motifs_randesu_estimate", (PyCFunction) igraphmodule_Graph_motifs_randesu_estimate, METH_VARARGS | METH_KEYWORDS, "motifs_randesu_estimate(size=3, cut_prob=None, sample)\n\n" "Counts the total number of motifs in the graph\n\n" "Motifs are small subgraphs of a given structure in a graph.\n" "This function estimates the total number of motifs in a graph without\n" "assigning isomorphism classes to them by extrapolating from a random\n" "sample of vertices.\n\n" "@newfield ref: Reference\n" "@ref: S. Wernicke and F. Rasche: FANMOD: a tool for fast network\n" " motif detection, Bioinformatics 22(9), 1152--1153, 2006.\n\n" "@param size: the size of the motifs (3 or 4).\n" "@param cut_prob: the cut probabilities for different levels of the search\n" " tree. This must be a list of length I{size} or C{None} to find all\n" " motifs.\n" "@param sample: the size of the sample or the vertex IDs of the vertices\n" " to be used for sampling.\n" "@see: Graph.motifs_randesu()\n" }, {"dyad_census", (PyCFunction) igraphmodule_Graph_dyad_census, METH_NOARGS, "dyad_census()\n\n" "Dyad census, as defined by Holland and Leinhardt\n\n" "Dyad census means classifying each pair of vertices of a directed\n" "graph into three categories: mutual, there is an edge from I{a} to\n" "I{b} and also from I{b} to I{a}; asymmetric, there is an edge\n" "either from I{a} to I{b} or from I{b} to I{a} but not the other way\n" "and null, no edges between I{a} and I{b}.\n\n" "@attention: this function has a more convenient interface in class\n" " L{Graph} which wraps the result in a L{DyadCensus} object.\n" " It is advised to use that.\n\n" "@return: the number of mutual, asymmetric and null connections in a\n" " 3-tuple." }, {"triad_census", (PyCFunction) igraphmodule_Graph_triad_census, METH_NOARGS, "triad_census()\n\n" "Triad census, as defined by Davis and Leinhardt\n\n" "Calculating the triad census means classifying every triplets of\n" "vertices in a directed graph. A triplet can be in one of 16 states,\n" "these are listed in the documentation of the C interface of igraph.\n" "\n" "@attention: this function has a more convenient interface in class\n" " L{Graph} which wraps the result in a L{TriadCensus} object.\n" " It is advised to use that. The name of the triplet classes are\n" " also documented there.\n\n" }, /********************/ /* LAYOUT FUNCTIONS */ /********************/ /* interface to igraph_layout_bipartite */ {"layout_bipartite", (PyCFunction) igraphmodule_Graph_layout_bipartite, METH_VARARGS | METH_KEYWORDS, "layout_bipartite(types=\"type\", hgap=1, vgap=1, maxiter=100)\n\n" "Place the vertices of a bipartite graph in two layers.\n\n" "The layout is created by placing the vertices in two rows, according\n" "to their types. The positions of the vertices within the rows are\n" "then optimized to minimize the number of edge crossings using the\n" "heuristic used by the Sugiyama layout algorithm.\n\n" "@param types: an igraph vector containing the vertex types, or an\n" " attribute name. Anything that evalulates to C{False} corresponds to\n" " vertices of the first kind, everything else to the second kind.\n" "@param hgap: minimum horizontal gap between vertices in the same layer.\n" "@param vgap: vertical gap between the two layers.\n" "@param maxiter: maximum number of iterations to take in the crossing\n" " reduction step. Increase this if you feel that you are getting too many\n" " edge crossings.\n" "@return: the calculated layout."}, /* interface to igraph_layout_circle */ {"layout_circle", (PyCFunction) igraphmodule_Graph_layout_circle, METH_VARARGS | METH_KEYWORDS, "layout_circle(dim=2, order=None)\n\n" "Places the vertices of the graph uniformly on a circle or a sphere.\n\n" "@param dim: the desired number of dimensions for the layout. dim=2\n" " means a 2D layout, dim=3 means a 3D layout.\n" "@param order: the order in which the vertices are placed along the\n" " circle. Not supported when I{dim} is not equal to 2.\n" "@return: the calculated layout."}, /* interface to igraph_layout_grid */ {"layout_grid", (PyCFunction) igraphmodule_Graph_layout_grid, METH_VARARGS | METH_KEYWORDS, "layout_grid(width=0, height=0, dim=2)\n\n" "Places the vertices of a graph in a 2D or 3D grid.\n\n" "@param width: the number of vertices in a single row of the layout.\n" " Zero or negative numbers mean that the width should be determined\n" " automatically.\n" "@param height: the number of vertices in a single column of the layout.\n" " Zero or negative numbers mean that the height should be determined\n" " automatically. It must not be given if the number of dimensions is 2.\n" "@param dim: the desired number of dimensions for the layout. dim=2\n" " means a 2D layout, dim=3 means a 3D layout.\n" "@return: the calculated layout."}, /* interface to igraph_layout_star */ {"layout_star", (PyCFunction) igraphmodule_Graph_layout_star, METH_VARARGS | METH_KEYWORDS, "layout_star(center=0, order=None)\n\n" "Calculates a star-like layout for the graph.\n\n" "@param center: the ID of the vertex to put in the center\n" "@param order: a numeric vector giving the order of the vertices\n" " (including the center vertex!). If it is C{None}, the vertices\n" " will be placed in increasing vertex ID order.\n" "@return: the calculated layout." }, /* interface to igraph_layout_kamada_kawai */ {"layout_kamada_kawai", (PyCFunction) igraphmodule_Graph_layout_kamada_kawai, METH_VARARGS | METH_KEYWORDS, "layout_kamada_kawai(maxiter=1000, seed=None, maxiter=1000, epsilon=0, \n" " kkconst=None, minx=None, maxx=None, miny=None, maxy=None, \n" " minz=None, maxz=None, dim=2)\n\n" "Places the vertices on a plane according to the Kamada-Kawai algorithm.\n\n" "This is a force directed layout, see Kamada, T. and Kawai, S.:\n" "An Algorithm for Drawing General Undirected Graphs.\n" "Information Processing Letters, 31/1, 7--15, 1989.\n\n" "@param maxiter: the maximum number of iterations to perform.\n" "@param seed: if C{None}, uses a random starting layout for the\n" " algorithm. If a matrix (list of lists), uses the given matrix\n" " as the starting position.\n" "@param epsilon: quit if the energy of the system changes less than\n" " epsilon. See the original paper for details.\n" "@param kkconst: the Kamada-Kawai vertex attraction constant.\n" " C{None} means the square of the number of vertices.\n" "@param minx: if not C{None}, it must be a vector with exactly as many\n" " elements as there are vertices in the graph. Each element is a\n" " minimum constraint on the X value of the vertex in the layout.\n" "@param maxx: similar to I{minx}, but with maximum constraints\n" "@param miny: similar to I{minx}, but with the Y coordinates\n" "@param maxy: similar to I{maxx}, but with the Y coordinates\n" "@param minz: similar to I{minx}, but with the Z coordinates. Use only\n" " for 3D layouts (C{dim}=3).\n" "@param maxz: similar to I{maxx}, but with the Z coordinates. Use only\n" " for 3D layouts (C{dim}=3).\n" "@param dim: the desired number of dimensions for the layout. dim=2\n" " means a 2D layout, dim=3 means a 3D layout.\n" "@return: the calculated layout." }, /* interface to igraph_layout_davidson_harel */ {"layout_davidson_harel", (PyCFunction) igraphmodule_Graph_layout_davidson_harel, METH_VARARGS | METH_KEYWORDS, "layout_davidson_harel(seed=None, maxiter=10, fineiter=-1, cool_fact=0.75,\n" " weight_node_dist=1.0, weight_border=0.0, weight_edge_lengths=-1,\n" " weight_edge_crossings=-1, weight_node_edge_dist=-1)\n\n" "Places the vertices on a 2D plane according to the Davidson-Harel layout\n" "algorithm.\n\n" "The algorithm uses simulated annealing and a sophisticated energy function,\n" "which is unfortunately hard to parameterize for different graphs. The\n" "original publication did not disclose any parameter values, and the ones\n" "below were determined by experimentation.\n\n" "The algorithm consists of two phases: an annealing phase and a fine-tuning\n" "phase. There is no simulated annealing in the second phase.\n\n" "@param seed: if C{None}, uses a random starting layout for the algorithm.\n" " If a matrix (list of lists), uses the given matrix as the starting\n" " position.\n" "@param maxiter: Number of iterations to perform in the annealing phase.\n" "@param fineiter: Number of iterations to perform in the fine-tuning phase.\n" " Negative numbers set up a reasonable default from the base-2 logarithm\n" " of the vertex count, bounded by 10 from above.\n" "@param cool_fact: Cooling factor of the simulated annealing phase.\n" "@param weight_node_dist: Weight for the node-node distances in the energy\n" " function.\n" "@param weight_border: Weight for the distance from the border component of\n" " the energy function. Zero means that vertices are allowed to sit on the\n" " border of the area designated for the layout.\n" "@param weight_edge_lengths: Weight for the edge length component of the\n" " energy function. Negative numbers are replaced by the density of the\n" " graph divided by 10.\n" "@param weight_edge_crossings: Weight for the edge crossing component of the\n" " energy function. Negative numbers are replaced by one minus the square\n" " root of the density of the graph.\n" "@param weight_node_edge_dist: Weight for the node-edge distance component\n" " of the energy function. Negative numbers are replaced by 0.2 minus\n" " 0.2 times the density of the graph.\n" "@return: the calculated layout." }, /* interface to igraph_layout_drl */ {"layout_drl", (PyCFunction) igraphmodule_Graph_layout_drl, METH_VARARGS | METH_KEYWORDS, "layout_drl(weights=None, fixed=None, seed=None, options=None, dim=2)\n\n" "Places the vertices on a 2D plane or in the 3D space ccording to the DrL\n" "layout algorithm.\n\n" "This is an algorithm suitable for quite large graphs, but it can be\n" "surprisingly slow for small ones (where the simpler force-based layouts\n" "like C{layout_kamada_kawai()} or C{layout_fruchterman_reingold()} are\n" "more useful.\n\n" "@param weights: edge weights to be used. Can be a sequence or iterable or\n" " even an edge attribute name.\n" "@param seed: if C{None}, uses a random starting layout for the\n" " algorithm. If a matrix (list of lists), uses the given matrix\n" " as the starting position.\n" "@param fixed: if a seed is given, you can specify some vertices to be\n" " kept fixed at their original position in the seed by passing an\n" " appropriate list here. The list must have exactly as many items as\n" " the number of vertices in the graph. Items of the list that evaluate\n" " to C{True} denote vertices that will not be moved.\n" "@param options: if you give a string argument here, you can select from\n" " five default preset parameterisations: C{default}, C{coarsen} for a\n" " coarser layout, C{coarsest} for an even coarser layout, C{refine} for\n" " refining an existing layout and C{final} for finalizing a layout. If\n" " you supply an object that is not a string, the DrL layout parameters\n" " are retrieved from the respective keys of the object (so it should\n" " be a dict or something else that supports the mapping protocol).\n" " The following keys can be used:\n" " \n" " - C{edge_cut}: edge cutting is done in the late stages of the\n" " algorithm in order to achieve less dense layouts. Edges are\n" " cut if there is a lot of stress on them (a large value in the\n" " objective function sum). The edge cutting parameter is a value\n" " between 0 and 1 with 0 representing no edge cutting and 1\n" " representing maximal edge cutting.\n\n" " - C{init_iterations}: number of iterations in the initialization\n" " phase\n\n" " - C{init_temperature}: start temperature during initialization\n\n" " - C{init_attraction}: attraction during initialization\n\n" " - C{init_damping_mult}: damping multiplier during initialization\n\n" " - C{liquid_iterations}, C{liquid_temperature}, C{liquid_attraction},\n" " C{liquid_damping_mult}: same parameters for the liquid phase\n\n" " - C{expansion_iterations}, C{expansion_temperature},\n" " C{expansion_attraction}, C{expansion_damping_mult}:\n" " parameters for the expansion phase\n\n" " - C{cooldown_...}: parameters for the cooldown phase\n\n" " - C{crunch_...}: parameters for the crunch phase\n\n" " - C{simmer_...}: parameters for the simmer phase\n\n" " \n" " Instead of a mapping, you can also use an arbitrary Python object\n" " here: if the object does not support the mapping protocol, an\n" " attribute of the object with the same name is looked up instead. If\n" " a parameter cannot be found either as a key or an attribute, the\n" " default from the C{default} preset will be used.\n\n" "@param dim: the desired number of dimensions for the layout. dim=2\n" " means a 2D layout, dim=3 means a 3D layout.\n" "@return: the calculated layout." }, /* interface to igraph_layout_fruchterman_reingold */ {"layout_fruchterman_reingold", (PyCFunction) igraphmodule_Graph_layout_fruchterman_reingold, METH_VARARGS | METH_KEYWORDS, "layout_fruchterman_reingold(weights=None, niter=500, seed=None, \n" " start_temp=None, minx=None, maxx=None, miny=None, \n" " maxy=None, minz=None, maxz=None, grid=\"auto\")\n\n" "Places the vertices on a 2D plane according to the\n" "Fruchterman-Reingold algorithm.\n\n" "This is a force directed layout, see Fruchterman, T. M. J. and Reingold, E. M.:\n" "Graph Drawing by Force-directed Placement.\n" "Software -- Practice and Experience, 21/11, 1129--1164, 1991\n\n" "@param weights: edge weights to be used. Can be a sequence or iterable or\n" " even an edge attribute name.\n" "@param niter: the number of iterations to perform. The default\n" " is 500.\n" "@param start_temp: Real scalar, the start temperature. This is the \n" " maximum amount of movement alloved along one axis, within one step,\n" " for a vertex. Currently it is decreased linearly to zero during\n" " the iteration. The default is the square root of the number of \n" " vertices divided by 10.\n" "@param minx: if not C{None}, it must be a vector with exactly as many\n" " elements as there are vertices in the graph. Each element is a\n" " minimum constraint on the X value of the vertex in the layout.\n" "@param maxx: similar to I{minx}, but with maximum constraints\n" "@param miny: similar to I{minx}, but with the Y coordinates\n" "@param maxy: similar to I{maxx}, but with the Y coordinates\n" "@param minz: similar to I{minx}, but with the Z coordinates. Use only\n" " for 3D layouts (C{dim}=3).\n" "@param maxz: similar to I{maxx}, but with the Z coordinates. Use only\n" " for 3D layouts (C{dim}=3).\n" "@param seed: if C{None}, uses a random starting layout for the\n" " algorithm. If a matrix (list of lists), uses the given matrix\n" " as the starting position.\n" "@param grid: whether to use a faster, but less accurate grid-based\n" " implementation of the algorithm. C{\"auto\"} decides based on the number\n" " of vertices in the graph; a grid will be used if there are at least 1000\n" " vertices. C{\"grid\"} is equivalent to C{True}, C{\"nogrid\"} is equivalent\n" " to C{False}.\n" "@return: the calculated layout." }, /* interface to igraph_layout_graphopt */ {"layout_graphopt", (PyCFunction) igraphmodule_Graph_layout_graphopt, METH_VARARGS | METH_KEYWORDS, "layout_graphopt(niter=500, node_charge=0.001, node_mass=30, spring_length=0, spring_constant=1, max_sa_movement=5, seed=None)\n\n" "This is a port of the graphopt layout algorithm by Michael Schmuhl.\n" "graphopt version 0.4.1 was rewritten in C and the support for layers\n" "was removed.\n\n" "graphopt uses physical analogies for defining attracting and repelling\n" "forces among the vertices and then the physical system is simulated\n" "until it reaches an equilibrium or the maximal number of iterations is\n" "reached.\n\n" "See U{http://www.schmuhl.org/graphopt/} for the original graphopt.\n\n" "@param niter: the number of iterations to perform. Should be a couple\n" " of hundred in general.\n\n" "@param node_charge: the charge of the vertices, used to calculate electric\n" " repulsion.\n" "@param node_mass: the mass of the vertices, used for the spring forces\n" "@param spring_length: the length of the springs\n" "@param spring_constant: the spring constant\n" "@param max_sa_movement: the maximum amount of movement allowed in a single\n" " step along a single axis.\n" "@param seed: a matrix containing a seed layout from which the algorithm\n" " will be started. If C{None}, a random layout will be used.\n" "@return: the calculated layout." }, /* interface to igraph_layout_lgl */ {"layout_lgl", (PyCFunction) igraphmodule_Graph_layout_lgl, METH_VARARGS | METH_KEYWORDS, "layout_lgl(maxiter=150, maxdelta=-1, area=-1, coolexp=1.5, repulserad=-1, cellsize=-1, root=None)\n\n" "Places the vertices on a 2D plane according to the Large Graph Layout.\n\n" "@param maxiter: the number of iterations to perform.\n" "@param maxdelta: the maximum distance to move a vertex in\n" " an iteration. If negative, defaults to the number of vertices.\n" "@param area: the area of the square on which the vertices\n" " will be placed. If negative, defaults to the number of vertices\n" " squared.\n" "@param coolexp: the cooling exponent of the simulated annealing.\n" "@param repulserad: determines the radius at which vertex-vertex\n" " repulsion cancels out attraction of adjacent vertices.\n" " If negative, defaults to M{area} times the number of vertices.\n" "@param cellsize: the size of the grid cells. When calculating the\n" " repulsion forces, only vertices in the same or neighboring\n" " grid cells are taken into account. Defaults to the fourth\n" " root of M{area}.\n" "@param root: the root vertex, this is placed first, its neighbors\n" " in the first iteration, second neighbors in the second,\n" " etc. C{None} means that a random vertex will be chosen.\n" "@return: the calculated layout." }, /* interface to igraph_layout_mds */ {"layout_mds", (PyCFunction) igraphmodule_Graph_layout_mds, METH_VARARGS | METH_KEYWORDS, "layout_mds(dist=None, dim=2, arpack_options=None)\n" "Places the vertices in an Euclidean space with the given number of\n" "dimensions using multidimensional scaling.\n\n" "This layout requires a distance matrix, where the intersection of\n" "row M{i} and column M{j} specifies the desired distance between\n" "vertex M{i} and vertex M{j}. The algorithm will try to place the\n" "vertices in a way that approximates the distance relations\n" "prescribed in the distance matrix. igraph uses the classical\n" "multidimensional scaling by Torgerson (see reference below).\n\n" "For unconnected graphs, the method will decompose the graph into\n" "weakly connected components and then lay out the components\n" "individually using the appropriate parts of the distance matrix.\n\n" "@param dist: the distance matrix. It must be symmetric and the\n" " symmetry is not checked -- results are unspecified when a\n" " non-symmetric distance matrix is used. If this parameter is\n" " C{None}, the shortest path lengths will be used as distances.\n" " Directed graphs are treated as undirected when calculating\n" " the shortest path lengths to ensure symmetry.\n" "@param dim: the number of dimensions. For 2D layouts, supply\n" " 2 here; for 3D layouts, supply 3.\n" "@param arpack_options: an L{ARPACKOptions} object used to fine-tune\n" " the ARPACK eigenvector calculation. If omitted, the module-level\n" " variable called C{arpack_options} is used.\n" "@return: the calculated layout.\n\n" "@newfield ref: Reference\n" "@ref: Cox & Cox: Multidimensional Scaling (1994), Chapman and\n" " Hall, London.\n" }, /* interface to igraph_layout_reingold_tilford */ {"layout_reingold_tilford", (PyCFunction) igraphmodule_Graph_layout_reingold_tilford, METH_VARARGS | METH_KEYWORDS, "layout_reingold_tilford(mode=\"out\", root=None, rootlevel=None)\n" "Places the vertices on a 2D plane according to the Reingold-Tilford\n" "layout algorithm.\n\n" "This is a tree layout. If the given graph is not a tree, a breadth-first\n" "search is executed first to obtain a possible spanning tree.\n\n" "@param mode: specifies which edges to consider when builing the tree.\n" " If it is C{OUT} then only the outgoing, if it is C{IN} then only the\n" " incoming edges of a parent are considered. If it is C{ALL} then all\n" " edges are used (this was the behaviour in igraph 0.5 and before).\n" " This parameter also influences how the root vertices are calculated\n" " if they are not given. See the I{root} parameter.\n" "@param root: the index of the root vertex or root vertices.\n" " if this is a non-empty vector then the supplied vertex IDs are\n" " used as the roots of the trees (or a single tree if the graph is\n" " connected. If this is C{None} or an empty list, the root vertices\n" " are automatically calculated based on topological sorting,\n" " performed with the opposite of the I{mode} argument.\n" "@param rootlevel: this argument is useful when drawing forests which are\n" " not trees. It specifies the level of the root vertices for every tree\n" " in the forest.\n" "@return: the calculated layout.\n\n" "@see: layout_reingold_tilford_circular\n" "@newfield ref: Reference\n" "@ref: EM Reingold, JS Tilford: I{Tidier Drawings of Trees.}\n" "IEEE Transactions on Software Engineering 7:22, 223-228, 1981."}, /* interface to igraph_layout_reingold_tilford_circular */ {"layout_reingold_tilford_circular", (PyCFunction) igraphmodule_Graph_layout_reingold_tilford_circular, METH_VARARGS | METH_KEYWORDS, "layout_reingold_tilford_circular(mode=\"out\", root=None, rootlevel=None)\n" "Circular Reingold-Tilford layout for trees.\n\n" "This layout is similar to the Reingold-Tilford layout, but the vertices\n" "are placed in a circular way, with the root vertex in the center.\n\n" "See L{layout_reingold_tilford} for the explanation of the parameters.\n\n" "@return: the calculated layout.\n\n" "@see: layout_reingold_tilford\n" "@newfield ref: Reference\n" "@ref: EM Reingold, JS Tilford: I{Tidier Drawings of Trees.}\n" "IEEE Transactions on Software Engineering 7:22, 223-228, 1981."}, /* interface to igraph_layout_random */ {"layout_random", (PyCFunction) igraphmodule_Graph_layout_random, METH_VARARGS | METH_KEYWORDS, "layout_random(dim=2)\n" "Places the vertices of the graph randomly.\n\n" "@param dim: the desired number of dimensions for the layout. dim=2\n" " means a 2D layout, dim=3 means a 3D layout.\n" "@return: the coordinate pairs in a list."}, /* interface to igraph_layout_sugiyama */ {"_layout_sugiyama", (PyCFunction) igraphmodule_Graph_layout_sugiyama, METH_VARARGS | METH_KEYWORDS, "Internal function, undocumented.\n\n" "@see: Graph.layout_sugiyama()\n\n"}, //////////////////////////// // VISITOR-LIKE FUNCTIONS // //////////////////////////// {"bfs", (PyCFunction) igraphmodule_Graph_bfs, METH_VARARGS | METH_KEYWORDS, "bfs(vid, mode=OUT)\n\n" "Conducts a breadth first search (BFS) on the graph.\n\n" "@param vid: the root vertex ID\n" "@param mode: either L{IN} or L{OUT} or L{ALL}, ignored\n" " for undirected graphs.\n" "@return: a tuple with the following items:\n" " - The vertex IDs visited (in order)\n" " - The start indices of the layers in the vertex list\n" " - The parent of every vertex in the BFS\n"}, {"bfsiter", (PyCFunction) igraphmodule_Graph_bfsiter, METH_VARARGS | METH_KEYWORDS, "bfsiter(vid, mode=OUT, advanced=False)\n\n" "Constructs a breadth first search (BFS) iterator of the graph.\n\n" "@param vid: the root vertex ID\n" "@param mode: either L{IN} or L{OUT} or L{ALL}.\n" "@param advanced: if C{False}, the iterator returns the next\n" " vertex in BFS order in every step. If C{True}, the iterator\n" " returns the distance of the vertex from the root and the\n" " parent of the vertex in the BFS tree as well.\n" "@return: the BFS iterator as an L{igraph.BFSIter} object.\n"}, ///////////////// // CONVERSIONS // ///////////////// // interface to igraph_get_adjacency {"get_adjacency", (PyCFunction) igraphmodule_Graph_get_adjacency, METH_VARARGS | METH_KEYWORDS, "get_adjacency(type=GET_ADJACENCY_BOTH, eids=False)\n\n" "Returns the adjacency matrix of a graph.\n\n" "@param type: either C{GET_ADJACENCY_LOWER} (uses the\n" " lower triangle of the matrix) or C{GET_ADJACENCY_UPPER}\n" " (uses the upper triangle) or C{GET_ADJACENCY_BOTH}\n" " (uses both parts). Ignored for directed graphs.\n" "@param eids: if C{True}, the result matrix will contain\n" " zeros for non-edges and the ID of the edge plus one\n" " for edges in the appropriate cell. If C{False}, the\n" " result matrix will contain the number of edges for\n" " each vertex pair.\n" "@return: the adjacency matrix.\n"}, // interface to igraph_get_edgelist {"get_edgelist", (PyCFunction) igraphmodule_Graph_get_edgelist, METH_NOARGS, "get_edgelist()\n\n" "Returns the edge list of a graph."}, /* interface to igraph_get_incidence */ {"get_incidence", (PyCFunction) igraphmodule_Graph_get_incidence, METH_VARARGS | METH_KEYWORDS, "get_incidence(types)\n\n" "Internal function, undocumented.\n\n" "@see: Graph.get_incidence()\n\n"}, // interface to igraph_to_directed {"to_directed", (PyCFunction) igraphmodule_Graph_to_directed, METH_VARARGS | METH_KEYWORDS, "to_directed(mutual=True)\n\n" "Converts an undirected graph to directed.\n\n" "@param mutual: C{True} if mutual directed edges should be\n" " created for every undirected edge. If C{False}, a directed\n" " edge with arbitrary direction is created.\n"}, // interface to igraph_to_undirected {"to_undirected", (PyCFunction) igraphmodule_Graph_to_undirected, METH_VARARGS | METH_KEYWORDS, "to_undirected(mode=\"collapse\", combine_edges=None)\n\n" "Converts a directed graph to undirected.\n\n" "@param mode: specifies what to do with multiple directed edges\n" " going between the same vertex pair. C{True} or C{\"collapse\"}\n" " means that only a single edge should be created from multiple\n" " directed edges. C{False} or C{\"each\"} means that every edge\n" " will be kept (with the arrowheads removed). C{\"mutual\"}\n" " creates one undirected edge for each mutual directed edge pair.\n" "@param combine_edges: specifies how to combine the attributes of\n" " multiple edges between the same pair of vertices into a single\n" " attribute. See L{Graph.simplify()} for more details.\n" }, /* interface to igraph_laplacian */ {"laplacian", (PyCFunction) igraphmodule_Graph_laplacian, METH_VARARGS | METH_KEYWORDS, "laplacian(weights=None, normalized=False)\n\n" "Returns the Laplacian matrix of a graph.\n\n" "The Laplacian matrix is similar to the adjacency matrix, but the edges\n" "are denoted with -1 and the diagonal contains the node degrees.\n\n" "Normalized Laplacian matrices have 1 or 0 in their diagonals (0 for vertices\n" "with no edges), edges are denoted by 1 / sqrt(d_i * d_j) where d_i is the\n" "degree of node i.\n\n" "Multiple edges and self-loops are silently ignored. Although it is\n" "possible to calculate the Laplacian matrix of a directed graph, it does\n" "not make much sense.\n\n" "@param weights: edge weights to be used. Can be a sequence or iterable or\n" " even an edge attribute name. When edge weights are used, the degree\n" " of a node is considered to be the weight of its incident edges.\n" "@param normalized: whether to return the normalized Laplacian matrix.\n" "@return: the Laplacian matrix.\n"}, /////////////////////////////// // LOADING AND SAVING GRAPHS // /////////////////////////////// // interface to igraph_read_graph_dimacs {"Read_DIMACS", (PyCFunction) igraphmodule_Graph_Read_DIMACS, METH_VARARGS | METH_KEYWORDS | METH_CLASS, "Read_DIMACS(f, directed=False)\n\n" "Reads a graph from a file conforming to the DIMACS minimum-cost flow file format.\n\n" "For the exact description of the format, see\n" "U{http://lpsolve.sourceforge.net/5.5/DIMACS.htm}\n\n" "Restrictions compared to the official description of the format:\n\n" " - igraph's DIMACS reader requires only three fields in an arc definition,\n" " describing the edge's source and target node and its capacity.\n" " - Source vertices are identified by 's' in the FLOW field, target vertices are\n" " identified by 't'.\n" " - Node indices start from 1. Only a single source and target node is allowed.\n\n" "@param f: the name of the file or a Python file handle\n" "@param directed: whether the generated graph should be directed.\n" "@return: the generated graph, the source and the target of the flow and the edge\n" " capacities in a tuple\n"}, /* interface to igraph_read_graph_dl */ {"Read_DL", (PyCFunction) igraphmodule_Graph_Read_DL, METH_VARARGS | METH_KEYWORDS | METH_CLASS, "Read_DL(f, directed=True)\n\n" "Reads an UCINET DL file and creates a graph based on it.\n\n" "@param f: the name of the file or a Python file handle\n" "@param directed: whether the generated graph should be directed.\n"}, /* interface to igraph_read_graph_edgelist */ {"Read_Edgelist", (PyCFunction) igraphmodule_Graph_Read_Edgelist, METH_VARARGS | METH_KEYWORDS | METH_CLASS, "Read_Edgelist(f, directed=True)\n\n" "Reads an edge list from a file and creates a graph based on it.\n\n" "Please note that the vertex indices are zero-based.\n\n" "@param f: the name of the file or a Python file handle\n" "@param directed: whether the generated graph should be directed.\n"}, /* interface to igraph_read_graph_graphdb */ {"Read_GraphDB", (PyCFunction) igraphmodule_Graph_Read_GraphDB, METH_VARARGS | METH_KEYWORDS | METH_CLASS, "Read_GraphDB(f, directed=False)\n\n" "Reads a GraphDB format file and creates a graph based on it.\n\n" "GraphDB is a binary format, used in the graph database for\n" "isomorphism testing (see U{http://amalfi.dis.unina.it/graph/}).\n\n" "@param f: the name of the file or a Python file handle\n" "@param directed: whether the generated graph should be directed.\n"}, /* interface to igraph_read_graph_graphml */ {"Read_GraphML", (PyCFunction) igraphmodule_Graph_Read_GraphML, METH_VARARGS | METH_KEYWORDS | METH_CLASS, "Read_GraphML(f, directed=True, index=0)\n\n" "Reads a GraphML format file and creates a graph based on it.\n\n" "@param f: the name of the file or a Python file handle\n" "@param index: if the GraphML file contains multiple graphs,\n" " specifies the one that should be loaded. Graph indices\n" " start from zero, so if you want to load the first graph,\n" " specify 0 here.\n"}, /* interface to igraph_read_graph_gml */ {"Read_GML", (PyCFunction) igraphmodule_Graph_Read_GML, METH_VARARGS | METH_KEYWORDS | METH_CLASS, "Read_GML(f)\n\n" "Reads a GML file and creates a graph based on it.\n\n" "@param f: the name of the file or a Python file handle\n" }, /* interface to igraph_read_graph_ncol */ {"Read_Ncol", (PyCFunction) igraphmodule_Graph_Read_Ncol, METH_VARARGS | METH_KEYWORDS | METH_CLASS, "Read_Ncol(f, names=True, weights=\"if_present\", directed=True)\n\n" "Reads an .ncol file used by LGL.\n\n" "It is also useful for creating graphs from \"named\" (and\n" "optionally weighted) edge lists.\n\n" "This format is used by the Large Graph Layout program. See the\n" "U{documentation of LGL }\n" "regarding the exact format description.\n\n" "LGL originally cannot deal with graphs containing multiple or loop\n" "edges, but this condition is not checked here, as igraph is happy\n" "with these.\n\n" "@param f: the name of the file or a Python file handle\n" "@param names: If C{True}, the vertex names are added as a\n" " vertex attribute called 'name'.\n" "@param weights: If True, the edge weights are added as an\n" " edge attribute called 'weight', even if there are no\n" " weights in the file. If False, the edge weights are never\n" " added, even if they are present. C{\"auto\"} or C{\"if_present\"}\n" " means that weights are added if there is at least one weighted\n" " edge in the input file, but they are not added otherwise.\n" "@param directed: whether the graph being created should be\n" " directed\n" }, /* interface to igraph_read_graph_lgl */ {"Read_Lgl", (PyCFunction) igraphmodule_Graph_Read_Lgl, METH_VARARGS | METH_KEYWORDS | METH_CLASS, "Read_Lgl(f, names=True, weights=\"if_present\", directed=True)\n\n" "Reads an .lgl file used by LGL.\n\n" "It is also useful for creating graphs from \"named\" (and\n" "optionally weighted) edge lists.\n\n" "This format is used by the Large Graph Layout program. See the\n" "U{documentation of LGL }\n" "regarding the exact format description.\n\n" "LGL originally cannot deal with graphs containing multiple or loop\n" "edges, but this condition is not checked here, as igraph is happy\n" "with these.\n\n" "@param f: the name of the file or a Python file handle\n" "@param names: If C{True}, the vertex names are added as a\n" " vertex attribute called 'name'.\n" "@param weights: If True, the edge weights are added as an\n" " edge attribute called 'weight', even if there are no\n" " weights in the file. If False, the edge weights are never\n" " added, even if they are present. C{\"auto\"} or C{\"if_present\"}\n" " means that weights are added if there is at least one weighted\n" " edge in the input file, but they are not added otherwise.\n" "@param directed: whether the graph being created should be\n" " directed\n" }, /* interface to igraph_read_graph_pajek */ {"Read_Pajek", (PyCFunction) igraphmodule_Graph_Read_Pajek, METH_VARARGS | METH_KEYWORDS | METH_CLASS, "Read_Pajek(f)\n\n" "Reads a Pajek format file and creates a graph based on it.\n\n" "@param f: the name of the file or a Python file handle\n"}, /* interface to igraph_write_graph_dimacs */ {"write_dimacs", (PyCFunction) igraphmodule_Graph_write_dimacs, METH_VARARGS | METH_KEYWORDS, "write_dimacs(f, source, target, capacity=None)\n\n" "Writes the graph in DIMACS format to the given file.\n\n" "@param f: the name of the file to be written or a Python file handle\n" "@param source: the source vertex ID\n" "@param target: the target vertex ID\n" "@param capacity: the capacities of the edges in a list. If it is not a\n" " list, the corresponding edge attribute will be used to retrieve\n" " capacities."}, /* interface to igraph_write_graph_dot */ {"write_dot", (PyCFunction) igraphmodule_Graph_write_dot, METH_VARARGS | METH_KEYWORDS, "write_dot(f)\n\n" "Writes the graph in DOT format to the given file.\n\n" "DOT is the format used by the U{GraphViz }\n" "software package.\n\n" "@param f: the name of the file to be written or a Python file handle\n" }, /* interface to igraph_write_graph_edgelist */ {"write_edgelist", (PyCFunction) igraphmodule_Graph_write_edgelist, METH_VARARGS | METH_KEYWORDS, "write_edgelist(f)\n\n" "Writes the edge list of a graph to a file.\n\n" "Directed edges are written in (from, to) order.\n\n" "@param f: the name of the file to be written or a Python file handle\n"}, /* interface to igraph_write_graph_gml */ {"write_gml", (PyCFunction) igraphmodule_Graph_write_gml, METH_VARARGS | METH_KEYWORDS, "write_gml(f, creator=None, ids=None)\n\n" "Writes the graph in GML format to the given file.\n\n" "@param f: the name of the file to be written or a Python file handle\n" "@param creator: optional creator information to be written to the file.\n" " If C{None}, the current date and time is added.\n" "@param ids: optional numeric vertex IDs to use in the file. This must\n" " be a list of integers or C{None}. If C{None}, the C{id} attribute of\n" " the vertices are used, or if they don't exist, numeric vertex IDs\n" " will be generated automatically."}, /* interface to igraph_write_graph_ncol */ {"write_ncol", (PyCFunction) igraphmodule_Graph_write_ncol, METH_VARARGS | METH_KEYWORDS, "write_ncol(f, names=\"name\", weights=\"weights\")\n\n" "Writes the edge list of a graph to a file in .ncol format.\n\n" "Note that multiple edges and/or loops break the LGL software,\n" "but igraph does not check for this condition. Unless you know\n" "that the graph does not have multiple edges and/or loops, it\n" "is wise to call L{simplify()} before saving.\n\n" "@param f: the name of the file to be written or a Python file handle\n" "@param names: the name of the vertex attribute containing the name\n" " of the vertices. If you don't want to store vertex names,\n" " supply C{None} here.\n" "@param weights: the name of the edge attribute containing the weight\n" " of the vertices. If you don't want to store weights,\n" " supply C{None} here.\n"}, /* interface to igraph_write_graph_lgl */ {"write_lgl", (PyCFunction) igraphmodule_Graph_write_lgl, METH_VARARGS | METH_KEYWORDS, "write_lgl(f, names=\"name\", weights=\"weights\", isolates=True)\n\n" "Writes the edge list of a graph to a file in .lgl format.\n\n" "Note that multiple edges and/or loops break the LGL software,\n" "but igraph does not check for this condition. Unless you know\n" "that the graph does not have multiple edges and/or loops, it\n" "is wise to call L{simplify()} before saving.\n\n" "@param f: the name of the file to be written or a Python file handle\n" "@param names: the name of the vertex attribute containing the name\n" " of the vertices. If you don't want to store vertex names,\n" " supply C{None} here.\n" "@param weights: the name of the edge attribute containing the weight\n" " of the vertices. If you don't want to store weights,\n" " supply C{None} here.\n" "@param isolates: whether to include isolated vertices in the output.\n"}, /* interface to igraph_write_graph_pajek */ {"write_pajek", (PyCFunction) igraphmodule_Graph_write_pajek, METH_VARARGS | METH_KEYWORDS, "write_pajek(f)\n\n" "Writes the graph in Pajek format to the given file.\n\n" "@param f: the name of the file to be written or a Python file handle\n" }, /* interface to igraph_write_graph_edgelist */ {"write_graphml", (PyCFunction) igraphmodule_Graph_write_graphml, METH_VARARGS | METH_KEYWORDS, "write_graphml(f)\n\n" "Writes the graph to a GraphML file.\n\n" "@param f: the name of the file to be written or a Python file handle\n" }, /* interface to igraph_write_graph_leda */ {"write_leda", (PyCFunction) igraphmodule_Graph_write_leda, METH_VARARGS | METH_KEYWORDS, "write_leda(f, names=\"name\", weights=\"weights\")\n\n" "Writes the graph to a file in LEDA native format.\n\n" "The LEDA format supports at most one attribute per vertex and edge. You can\n" "specify which vertex and edge attribute you want to use. Note that the\n" "name of the attribute is not saved in the LEDA file.\n\n" "@param f: the name of the file to be written or a Python file handle\n" "@param names: the name of the vertex attribute to be stored along with\n" " the vertices. It is usually used to store the vertex names (hence the\n" " name of the keyword argument), but you may also use a numeric attribute.\n" " If you don't want to store any vertex attributes, supply C{None} here.\n" "@param weights: the name of the edge attribute to be stored along with\n" " the edges. It is usually used to store the edge weights (hence the\n" " name of the keyword argument), but you may also use a string attribute.\n" " If you don't want to store any edge attributes, supply C{None} here.\n"}, /***************/ /* ISOMORPHISM */ /***************/ {"canonical_permutation", (PyCFunction) igraphmodule_Graph_canonical_permutation, METH_VARARGS | METH_KEYWORDS, "canonical_permutation(sh=\"fm\")\n\n" "Calculates the canonical permutation of a graph using the BLISS isomorphism\n" "algorithm.\n\n" "Passing the permutation returned here to L{Graph.permute_vertices()} will\n" "transform the graph into its canonical form.\n\n" "See U{http://www.tcs.hut.fi/Software/bliss/index.html} for more information\n" "about the BLISS algorithm and canonical permutations.\n\n" "@param sh: splitting heuristics for graph as a case-insensitive string,\n" " with the following possible values:\n\n" " - C{\"f\"}: first non-singleton cell\n\n" " - C{\"fl\"}: first largest non-singleton cell\n\n" " - C{\"fs\"}: first smallest non-singleton cell\n\n" " - C{\"fm\"}: first maximally non-trivially connected non-singleton\n" " cell\n\n" " - C{\"flm\"}: largest maximally non-trivially connected\n" " non-singleton cell\n\n" " - C{\"fsm\"}: smallest maximally non-trivially connected\n" " non-singleton cell\n\n" "@param color: optional vector storing a coloring of the vertices\n " "with respect to which the isomorphism is computed." "If C{None}, all vertices have the same color.\n" "@return: a permutation vector containing vertex IDs. Vertex 0 in the original\n" " graph will be mapped to an ID contained in the first element of this\n" " vector; vertex 1 will be mapped to the second and so on.\n" }, {"isoclass", (PyCFunction) igraphmodule_Graph_isoclass, METH_VARARGS | METH_KEYWORDS, "isoclass(vertices)\n\n" "Returns the isomorphy class of the graph or its subgraph.\n\n" "Isomorphy class calculations are implemented only for graphs with\n" "3 or 4 vertices.\n\n" "@param vertices: a list of vertices if we want to calculate the\n" " isomorphy class for only a subset of vertices. C{None} means to\n" " use the full graph.\n" "@return: the isomorphy class of the (sub)graph\n\n"}, {"isomorphic", (PyCFunction) igraphmodule_Graph_isomorphic, METH_VARARGS | METH_KEYWORDS, "isomorphic(other)\n\n" "Checks whether the graph is isomorphic to another graph.\n\n" "The algorithm being used is selected using a simple heuristic:\n\n" " - If one graph is directed and the other undirected, an exception\n" " is thrown.\n\n" " - If the two graphs does not have the same number of vertices and\n" " edges, it returns with C{False}\n\n" " - If the graphs have three or four vertices, then an O(1) algorithm\n" " is used with precomputed data.\n\n" " - Otherwise if the graphs are directed, then the VF2 isomorphism\n" " algorithm is used (see L{Graph.isomorphic_vf2}).\n\n" " - Otherwise the BLISS isomorphism algorithm is used, see\n" " L{Graph.isomorphic_bliss}.\n\n" "@return: C{True} if the graphs are isomorphic, C{False} otherwise.\n" }, {"isomorphic_bliss", (PyCFunction) igraphmodule_Graph_isomorphic_bliss, METH_VARARGS | METH_KEYWORDS, "isomorphic_bliss(other, return_mapping_12=False, return_mapping_21=False,\n" " sh1=\"fm\", sh2=None)\n\n" "Checks whether the graph is isomorphic to another graph, using the\n" "BLISS isomorphism algorithm.\n\n" "See U{http://www.tcs.hut.fi/Software/bliss/index.html} for more information\n" "about the BLISS algorithm.\n\n" "@param other: the other graph with which we want to compare the graph.\n" "@param color1: optional vector storing the coloring of the vertices of\n" " the first graph. If C{None}, all vertices have the same color.\n" "@param color2: optional vector storing the coloring of the vertices of\n" " the second graph. If C{None}, all vertices have the same color.\n" "@param return_mapping_12: if C{True}, calculates the mapping which maps\n" " the vertices of the first graph to the second.\n" "@param return_mapping_21: if C{True}, calculates the mapping which maps\n" " the vertices of the second graph to the first.\n" "@param sh1: splitting heuristics for the first graph as a\n" " case-insensitive string, with the following possible values:\n\n" " - C{\"f\"}: first non-singleton cell\n\n" " - C{\"fl\"}: first largest non-singleton cell\n\n" " - C{\"fs\"}: first smallest non-singleton cell\n\n" " - C{\"fm\"}: first maximally non-trivially connected non-singleton\n" " cell\n\n" " - C{\"flm\"}: largest maximally non-trivially connected\n" " non-singleton cell\n\n" " - C{\"fsm\"}: smallest maximally non-trivially connected\n" " non-singleton cell\n\n" "@param sh2: splitting heuristics to be used for the second graph.\n" " This must be the same as C{sh1}; alternatively, it can be C{None},\n" " in which case it will automatically use the same value as C{sh1}.\n" " Currently it is present for backwards compatibility only.\n" "@return: if no mapping is calculated, the result is C{True} if the graphs\n" " are isomorphic, C{False} otherwise. If any or both mappings are\n" " calculated, the result is a 3-tuple, the first element being the\n" " above mentioned boolean, the second element being the 1 -> 2 mapping\n" " and the third element being the 2 -> 1 mapping. If the corresponding\n" " mapping was not calculated, C{None} is returned in the appropriate\n" " element of the 3-tuple.\n"}, {"isomorphic_vf2", (PyCFunction) igraphmodule_Graph_isomorphic_vf2, METH_VARARGS | METH_KEYWORDS, "isomorphic_vf2(other=None, color1=None, color2=None, edge_color1=None,\n" " edge_color2=None, return_mapping_12=False, return_mapping_21=False,\n" " node_compat_fn=None, edge_compat_fn=None, callback=None)\n\n" "Checks whether the graph is isomorphic to another graph, using the\n" "VF2 isomorphism algorithm.\n\n" "Vertex and edge colors may be used to restrict the isomorphisms, as only\n" "vertices and edges with the same color will be allowed to match each other.\n\n" "@param other: the other graph with which we want to compare the graph.\n" " If C{None}, the automorphjisms of the graph will be tested.\n" "@param color1: optional vector storing the coloring of the vertices of\n" " the first graph. If C{None}, all vertices have the same color.\n" "@param color2: optional vector storing the coloring of the vertices of\n" " the second graph. If C{None}, all vertices have the same color.\n" "@param edge_color1: optional vector storing the coloring of the edges of\n" " the first graph. If C{None}, all edges have the same color.\n" "@param edge_color2: optional vector storing the coloring of the edges of\n" " the second graph. If C{None}, all edges have the same color.\n" "@param return_mapping_12: if C{True}, calculates the mapping which maps\n" " the vertices of the first graph to the second.\n" "@param return_mapping_21: if C{True}, calculates the mapping which maps\n" " the vertices of the second graph to the first.\n" "@param callback: if not C{None}, the isomorphism search will not stop at\n" " the first match; it will call this callback function instead for every\n" " isomorphism found. The callback function must accept four arguments:\n" " the first graph, the second graph, a mapping from the nodes of the\n" " first graph to the second, and a mapping from the nodes of the second\n" " graph to the first. The function must return C{True} if the search\n" " should continue or C{False} otherwise.\n" "@param node_compat_fn: a function that receives the two graphs and two\n" " node indices (one from the first graph, one from the second graph) and\n" " returns C{True} if the nodes given by the two indices are compatible\n" " (i.e. they could be matched to each other) or C{False} otherwise. This\n" " can be used to restrict the set of isomorphisms based on node-specific\n" " criteria that are too complicated to be represented by node color\n" " vectors (i.e. the C{color1} and C{color2} parameters). C{None} means\n" " that every node is compatible with every other node.\n" "@param edge_compat_fn: a function that receives the two graphs and two\n" " edge indices (one from the first graph, one from the second graph) and\n" " returns C{True} if the edges given by the two indices are compatible\n" " (i.e. they could be matched to each other) or C{False} otherwise. This\n" " can be used to restrict the set of isomorphisms based on edge-specific\n" " criteria that are too complicated to be represented by edge color\n" " vectors (i.e. the C{edge_color1} and C{edge_color2} parameters). C{None}\n" " means that every edge is compatible with every other node.\n" "@return: if no mapping is calculated, the result is C{True} if the graphs\n" " are isomorphic, C{False} otherwise. If any or both mappings are\n" " calculated, the result is a 3-tuple, the first element being the\n" " above mentioned boolean, the second element being the 1 -> 2 mapping\n" " and the third element being the 2 -> 1 mapping. If the corresponding\n" " mapping was not calculated, C{None} is returned in the appropriate\n" " element of the 3-tuple.\n"}, {"count_isomorphisms_vf2", (PyCFunction) igraphmodule_Graph_count_isomorphisms_vf2, METH_VARARGS | METH_KEYWORDS, "count_isomorphisms_vf2(other=None, color1=None, color2=None, edge_color1=None,\n" " edge_color2=None, node_compat_fn=None, edge_compat_fn=None)\n\n" "Determines the number of isomorphisms between the graph and another one\n\n" "Vertex and edge colors may be used to restrict the isomorphisms, as only\n" "vertices and edges with the same color will be allowed to match each other.\n\n" "@param other: the other graph. If C{None}, the number of automorphisms\n" " will be returned.\n" "@param color1: optional vector storing the coloring of the vertices of\n" " the first graph. If C{None}, all vertices have the same color.\n" "@param color2: optional vector storing the coloring of the vertices of\n" " the second graph. If C{None}, all vertices have the same color.\n" "@param edge_color1: optional vector storing the coloring of the edges of\n" " the first graph. If C{None}, all edges have the same color.\n" "@param edge_color2: optional vector storing the coloring of the edges of\n" " the second graph. If C{None}, all edges have the same color.\n" "@param node_compat_fn: a function that receives the two graphs and two\n" " node indices (one from the first graph, one from the second graph) and\n" " returns C{True} if the nodes given by the two indices are compatible\n" " (i.e. they could be matched to each other) or C{False} otherwise. This\n" " can be used to restrict the set of isomorphisms based on node-specific\n" " criteria that are too complicated to be represented by node color\n" " vectors (i.e. the C{color1} and C{color2} parameters). C{None} means\n" " that every node is compatible with every other node.\n" "@param edge_compat_fn: a function that receives the two graphs and two\n" " edge indices (one from the first graph, one from the second graph) and\n" " returns C{True} if the edges given by the two indices are compatible\n" " (i.e. they could be matched to each other) or C{False} otherwise. This\n" " can be used to restrict the set of isomorphisms based on edge-specific\n" " criteria that are too complicated to be represented by edge color\n" " vectors (i.e. the C{edge_color1} and C{edge_color2} parameters). C{None}\n" " means that every edge is compatible with every other node.\n" "@return: the number of isomorphisms between the two given graphs (or the\n" " number of automorphisms if C{other} is C{None}.\n"}, {"get_isomorphisms_vf2", (PyCFunction) igraphmodule_Graph_get_isomorphisms_vf2, METH_VARARGS | METH_KEYWORDS, "get_isomorphisms_vf2(other=None, color1=None, color2=None, edge_color1=None,\n" " edge_color2=None, node_compat_fn=None, edge_compat_fn=None)\n\n" "Returns all isomorphisms between the graph and another one\n\n" "Vertex and edge colors may be used to restrict the isomorphisms, as only\n" "vertices and edges with the same color will be allowed to match each other.\n\n" "@param other: the other graph. If C{None}, the automorphisms\n" " will be returned.\n" "@param color1: optional vector storing the coloring of the vertices of\n" " the first graph. If C{None}, all vertices have the same color.\n" "@param color2: optional vector storing the coloring of the vertices of\n" " the second graph. If C{None}, all vertices have the same color.\n" "@param edge_color1: optional vector storing the coloring of the edges of\n" " the first graph. If C{None}, all edges have the same color.\n" "@param edge_color2: optional vector storing the coloring of the edges of\n" " the second graph. If C{None}, all edges have the same color.\n" "@param node_compat_fn: a function that receives the two graphs and two\n" " node indices (one from the first graph, one from the second graph) and\n" " returns C{True} if the nodes given by the two indices are compatible\n" " (i.e. they could be matched to each other) or C{False} otherwise. This\n" " can be used to restrict the set of isomorphisms based on node-specific\n" " criteria that are too complicated to be represented by node color\n" " vectors (i.e. the C{color1} and C{color2} parameters). C{None} means\n" " that every node is compatible with every other node.\n" "@param edge_compat_fn: a function that receives the two graphs and two\n" " edge indices (one from the first graph, one from the second graph) and\n" " returns C{True} if the edges given by the two indices are compatible\n" " (i.e. they could be matched to each other) or C{False} otherwise. This\n" " can be used to restrict the set of isomorphisms based on edge-specific\n" " criteria that are too complicated to be represented by edge color\n" " vectors (i.e. the C{edge_color1} and C{edge_color2} parameters). C{None}\n" " means that every edge is compatible with every other node.\n" "@return: a list of lists, each item of the list containing the mapping\n" " from vertices of the second graph to the vertices of the first one\n"}, {"subisomorphic_vf2", (PyCFunction) igraphmodule_Graph_subisomorphic_vf2, METH_VARARGS | METH_KEYWORDS, "subisomorphic_vf2(other, color1=None, color2=None, edge_color1=None,\n" " edge_color2=None, return_mapping_12=False, return_mapping_21=False,\n" " callback=None, node_compat_fn=None, edge_compat_fn=None)\n\n" "Checks whether a subgraph of the graph is isomorphic to another graph.\n\n" "Vertex and edge colors may be used to restrict the isomorphisms, as only\n" "vertices and edges with the same color will be allowed to match each other.\n\n" "@param other: the other graph with which we want to compare the graph.\n" "@param color1: optional vector storing the coloring of the vertices of\n" " the first graph. If C{None}, all vertices have the same color.\n" "@param color2: optional vector storing the coloring of the vertices of\n" " the second graph. If C{None}, all vertices have the same color.\n" "@param edge_color1: optional vector storing the coloring of the edges of\n" " the first graph. If C{None}, all edges have the same color.\n" "@param edge_color2: optional vector storing the coloring of the edges of\n" " the second graph. If C{None}, all edges have the same color.\n" "@param return_mapping_12: if C{True}, calculates the mapping which maps\n" " the vertices of the first graph to the second. The mapping can contain\n" " -1 if a given node is not mapped.\n" "@param return_mapping_21: if C{True}, calculates the mapping which maps\n" " the vertices of the second graph to the first. The mapping can contain\n" " -1 if a given node is not mapped.\n" "@param callback: if not C{None}, the subisomorphism search will not stop at\n" " the first match; it will call this callback function instead for every\n" " subisomorphism found. The callback function must accept four arguments:\n" " the first graph, the second graph, a mapping from the nodes of the\n" " first graph to the second, and a mapping from the nodes of the second\n" " graph to the first. The function must return C{True} if the search\n" " should continue or C{False} otherwise.\n" "@param node_compat_fn: a function that receives the two graphs and two\n" " node indices (one from the first graph, one from the second graph) and\n" " returns C{True} if the nodes given by the two indices are compatible\n" " (i.e. they could be matched to each other) or C{False} otherwise. This\n" " can be used to restrict the set of isomorphisms based on node-specific\n" " criteria that are too complicated to be represented by node color\n" " vectors (i.e. the C{color1} and C{color2} parameters). C{None} means\n" " that every node is compatible with every other node.\n" "@param edge_compat_fn: a function that receives the two graphs and two\n" " edge indices (one from the first graph, one from the second graph) and\n" " returns C{True} if the edges given by the two indices are compatible\n" " (i.e. they could be matched to each other) or C{False} otherwise. This\n" " can be used to restrict the set of isomorphisms based on edge-specific\n" " criteria that are too complicated to be represented by edge color\n" " vectors (i.e. the C{edge_color1} and C{edge_color2} parameters). C{None}\n" " means that every edge is compatible with every other node.\n" "@return: if no mapping is calculated, the result is C{True} if the graph\n" " contains a subgraph that's isomorphic to the given one, C{False}\n" " otherwise. If any or both mappings are calculated, the result is a\n" " 3-tuple, the first element being the above mentioned boolean, the\n" " second element being the 1 -> 2 mapping and the third element being\n" " the 2 -> 1 mapping. If the corresponding mapping was not calculated,\n" " C{None} is returned in the appropriate element of the 3-tuple.\n"}, {"count_subisomorphisms_vf2", (PyCFunction) igraphmodule_Graph_count_subisomorphisms_vf2, METH_VARARGS | METH_KEYWORDS, "count_subisomorphisms_vf2(other, color1=None, color2=None,\n" " edge_color1=None, edge_color2=None, node_compat_fn=None,\n" " edge_compat_fn=None)\n\n" "Determines the number of subisomorphisms between the graph and another one\n\n" "Vertex and edge colors may be used to restrict the isomorphisms, as only\n" "vertices and edges with the same color will be allowed to match each other.\n\n" "@param other: the other graph.\n" "@param color1: optional vector storing the coloring of the vertices of\n" " the first graph. If C{None}, all vertices have the same color.\n" "@param color2: optional vector storing the coloring of the vertices of\n" " the second graph. If C{None}, all vertices have the same color.\n" "@param edge_color1: optional vector storing the coloring of the edges of\n" " the first graph. If C{None}, all edges have the same color.\n" "@param edge_color2: optional vector storing the coloring of the edges of\n" " the second graph. If C{None}, all edges have the same color.\n" "@param node_compat_fn: a function that receives the two graphs and two\n" " node indices (one from the first graph, one from the second graph) and\n" " returns C{True} if the nodes given by the two indices are compatible\n" " (i.e. they could be matched to each other) or C{False} otherwise. This\n" " can be used to restrict the set of isomorphisms based on node-specific\n" " criteria that are too complicated to be represented by node color\n" " vectors (i.e. the C{color1} and C{color2} parameters). C{None} means\n" " that every node is compatible with every other node.\n" "@param edge_compat_fn: a function that receives the two graphs and two\n" " edge indices (one from the first graph, one from the second graph) and\n" " returns C{True} if the edges given by the two indices are compatible\n" " (i.e. they could be matched to each other) or C{False} otherwise. This\n" " can be used to restrict the set of isomorphisms based on edge-specific\n" " criteria that are too complicated to be represented by edge color\n" " vectors (i.e. the C{edge_color1} and C{edge_color2} parameters). C{None}\n" " means that every edge is compatible with every other node.\n" "@return: the number of subisomorphisms between the two given graphs\n"}, {"get_subisomorphisms_vf2", (PyCFunction) igraphmodule_Graph_get_subisomorphisms_vf2, METH_VARARGS | METH_KEYWORDS, "get_subisomorphisms_vf2(other, color1=None, color2=None,\n" " edge_color1=None, edge_color2=None, node_compat_fn=None,\n" " edge_compat_fn=None)\n\n" "Returns all subisomorphisms between the graph and another one\n\n" "Vertex and edge colors may be used to restrict the isomorphisms, as only\n" "vertices and edges with the same color will be allowed to match each other.\n\n" "@param other: the other graph.\n" "@param color1: optional vector storing the coloring of the vertices of\n" " the first graph. If C{None}, all vertices have the same color.\n" "@param color2: optional vector storing the coloring of the vertices of\n" " the second graph. If C{None}, all vertices have the same color.\n" "@param edge_color1: optional vector storing the coloring of the edges of\n" " the first graph. If C{None}, all edges have the same color.\n" "@param edge_color2: optional vector storing the coloring of the edges of\n" " the second graph. If C{None}, all edges have the same color.\n" "@param node_compat_fn: a function that receives the two graphs and two\n" " node indices (one from the first graph, one from the second graph) and\n" " returns C{True} if the nodes given by the two indices are compatible\n" " (i.e. they could be matched to each other) or C{False} otherwise. This\n" " can be used to restrict the set of isomorphisms based on node-specific\n" " criteria that are too complicated to be represented by node color\n" " vectors (i.e. the C{color1} and C{color2} parameters). C{None} means\n" " that every node is compatible with every other node.\n" "@param edge_compat_fn: a function that receives the two graphs and two\n" " edge indices (one from the first graph, one from the second graph) and\n" " returns C{True} if the edges given by the two indices are compatible\n" " (i.e. they could be matched to each other) or C{False} otherwise. This\n" " can be used to restrict the set of isomorphisms based on edge-specific\n" " criteria that are too complicated to be represented by edge color\n" " vectors (i.e. the C{edge_color1} and C{edge_color2} parameters). C{None}\n" " means that every edge is compatible with every other node.\n" "@return: a list of lists, each item of the list containing the mapping\n" " from vertices of the second graph to the vertices of the first one\n"}, {"subisomorphic_lad", (PyCFunction) igraphmodule_Graph_subisomorphic_lad, METH_VARARGS | METH_KEYWORDS, "subisomorphic_lad(other, domains=None, induced=False, time_limit=0, \n" " return_mapping=False)\n\n" "Checks whether a subgraph of the graph is isomorphic to another graph.\n\n" "The optional C{domains} argument may be used to restrict vertices that\n" "may match each other. You can also specify whether you are interested\n" "in induced subgraphs only or not.\n\n" "@param other: the pattern graph we are looking for in the graph.\n" "@param domains: a list of lists, one sublist belonging to each vertex in\n" " the template graph. Sublist M{i} contains the indices of the vertices in\n" " the original graph that may match vertex M{i} in the template graph.\n" " C{None} means that every vertex may match every other vertex.\n" "@param induced: whether to consider induced subgraphs only.\n" "@param time_limit: an optimal time limit in seconds. Only the integral\n" " part of this number is taken into account. If the time limit is\n" " exceeded, the method will throw an exception.\n" "@param return_mapping: when C{True}, the function will return a tuple,\n" " where the first element is a boolean denoting whether a subisomorphism\n" " has been found or not, and the second element describes the mapping\n" " of the vertices from the template graph to the original graph. When\n" " C{False}, only the boolean is returned.\n" "@return: if no mapping is calculated, the result is C{True} if the graph\n" " contains a subgraph that is isomorphic to the given template, C{False}\n" " otherwise. If the mapping is calculated, the result is a tuple, the first\n" " element being the above mentioned boolean, and the second element being\n" " the mapping from the target to the original graph.\n"}, {"get_subisomorphisms_lad", (PyCFunction) igraphmodule_Graph_get_subisomorphisms_lad, METH_VARARGS | METH_KEYWORDS, "get_subisomorphisms_lad(other, domains=None, induced=False, time_limit=0)\n\n" "Returns all subisomorphisms between the graph and another one using the LAD\n" "algorithm.\n\n" "The optional C{domains} argument may be used to restrict vertices that\n" "may match each other. You can also specify whether you are interested\n" "in induced subgraphs only or not.\n\n" "@param other: the pattern graph we are looking for in the graph.\n" "@param domains: a list of lists, one sublist belonging to each vertex in\n" " the template graph. Sublist M{i} contains the indices of the vertices in\n" " the original graph that may match vertex M{i} in the template graph.\n" " C{None} means that every vertex may match every other vertex.\n" "@param induced: whether to consider induced subgraphs only.\n" "@param time_limit: an optimal time limit in seconds. Only the integral\n" " part of this number is taken into account. If the time limit is\n" " exceeded, the method will throw an exception.\n" "@return: a list of lists, each item of the list containing the mapping\n" " from vertices of the second graph to the vertices of the first one\n"}, //////////////////////// // ATTRIBUTE HANDLING // //////////////////////// {"attributes", (PyCFunction) igraphmodule_Graph_attributes, METH_NOARGS, "attributes()\n\n" "@return: the attribute name list of the graph\n"}, {"vertex_attributes", (PyCFunction) igraphmodule_Graph_vertex_attributes, METH_NOARGS, "vertex_attributes()\n\n" "@return: the attribute name list of the graph's vertices\n"}, {"edge_attributes", (PyCFunction) igraphmodule_Graph_edge_attributes, METH_NOARGS, "edge_attributes()\n\n" "@return: the attribute name list of the graph's edges\n"}, /////////////// // OPERATORS // /////////////// {"complementer", (PyCFunction) igraphmodule_Graph_complementer, METH_VARARGS, "complementer(loops=False)\n\n" "Returns the complementer of the graph\n\n" "@param loops: whether to include loop edges in the complementer.\n" "@return: the complementer of the graph\n"}, {"compose", (PyCFunction) igraphmodule_Graph_compose, METH_O, "compose(other)\n\nReturns the composition of two graphs."}, {"difference", (PyCFunction) igraphmodule_Graph_difference, METH_O, "difference(other)\n\nSubtracts the given graph from the original"}, {"disjoint_union", (PyCFunction) igraphmodule_Graph_disjoint_union, METH_O, "disjoint_union(graphs)\n\n" "Creates the disjoint union of two (or more) graphs.\n\n" "@param graphs: the list of graphs to be united with the current one.\n"}, {"intersection", (PyCFunction) igraphmodule_Graph_intersection, METH_O, "intersection(graphs)\n\n" "Creates the intersection of two (or more) graphs.\n\n" "@param graphs: the list of graphs to be intersected with\n" " the current one.\n"}, {"union", (PyCFunction) igraphmodule_Graph_union, METH_O, "union(graphs)\n\n" "Creates the union of two (or more) graphs.\n\n" "@param graphs: the list of graphs to be united with\n" " the current one.\n"}, /**********************/ /* DOMINATORS */ /**********************/ {"dominator", (PyCFunction) igraphmodule_Graph_dominator, METH_VARARGS | METH_KEYWORDS, "dominator(vid, mode=)\n\n" "Returns the dominator tree from the given root node" "@param vid: the root vertex ID\n" "@param mode: either L{IN} or L{OUT}\n" "@return: a list containing the dominator tree for the current graph." }, /*****************/ /* MAXIMUM FLOWS */ /*****************/ {"maxflow_value", (PyCFunction) igraphmodule_Graph_maxflow_value, METH_VARARGS | METH_KEYWORDS, "maxflow_value(source, target, capacity=None)\n\n" "Returns the value of the maximum flow between the source and target vertices.\n\n" "@param source: the source vertex ID\n" "@param target: the target vertex ID\n" "@param capacity: the capacity of the edges. It must be a list or a valid\n" " attribute name or C{None}. In the latter case, every edge will have the\n" " same capacity.\n" "@return: the value of the maximum flow between the given vertices\n"}, {"maxflow", (PyCFunction) igraphmodule_Graph_maxflow, METH_VARARGS | METH_KEYWORDS, "maxflow(source, target, capacity=None)\n\n" "Returns the maximum flow between the source and target vertices.\n\n" "@attention: this function has a more convenient interface in class\n" " L{Graph} which wraps the result in a L{Flow} object. It is advised\n" " to use that.\n" "@param source: the source vertex ID\n" "@param target: the target vertex ID\n" "@param capacity: the capacity of the edges. It must be a list or a valid\n" " attribute name or C{None}. In the latter case, every edge will have the\n" " same capacity.\n" "@return: a tuple containing the following: the value of the maximum flow\n" " between the given vertices, the flow value on all the edges, the edge\n" " IDs that are part of the corresponding minimum cut, and the vertex IDs\n" " on one side of the cut. For directed graphs, the flow value vector gives\n" " the flow value on each edge. For undirected graphs, the flow value is\n" " positive if the flow goes from the smaller vertex ID to the bigger one\n" " and negative if the flow goes from the bigger vertex ID to the smaller." }, /**********************/ /* CUTS, MINIMUM CUTS */ /**********************/ {"all_st_cuts", (PyCFunction) igraphmodule_Graph_all_st_cuts, METH_VARARGS | METH_KEYWORDS, "all_st_cuts(source, target)\n\n" "Returns all the cuts between the source and target vertices in a\n" "directed graph.\n\n" "This function lists all edge-cuts between a source and a target vertex.\n" "Every cut is listed exactly once.\n\n" "@param source: the source vertex ID\n" "@param target: the target vertex ID\n" "@attention: this function has a more convenient interface in class\n" " L{Graph} which wraps the result in a list of L{Cut} objects. It is\n" " advised to use that.\n" "@return: a tuple where the first element is a list of lists of edge IDs\n" " representing a cut and the second element is a list of lists of vertex\n" " IDs representing the sets of vertices that were separated by the cuts.\n" }, {"all_st_mincuts", (PyCFunction) igraphmodule_Graph_all_st_mincuts, METH_VARARGS | METH_KEYWORDS, "all_st_mincuts(source, target)\n\n" "Returns all minimum cuts between the source and target vertices in a\n" "directed graph.\n\n" "@param source: the source vertex ID\n" "@param target: the target vertex ID\n" "@attention: this function has a more convenient interface in class\n" " L{Graph} which wraps the result in a list of L{Cut} objects. It is\n" " advised to use that.\n" }, {"mincut_value", (PyCFunction) igraphmodule_Graph_mincut_value, METH_VARARGS | METH_KEYWORDS, "mincut_value(source=-1, target=-1, capacity=None)\n\n" "Returns the minimum cut between the source and target vertices or within\n" "the whole graph.\n\n" "@param source: the source vertex ID. If negative, the calculation is\n" " done for every vertex except the target and the minimum is returned.\n" "@param target: the target vertex ID. If negative, the calculation is\n" " done for every vertex except the source and the minimum is returned.\n" "@param capacity: the capacity of the edges. It must be a list or a valid\n" " attribute name or C{None}. In the latter case, every edge will have the\n" " same capacity.\n" "@return: the value of the minimum cut between the given vertices\n"}, {"mincut", (PyCFunction) igraphmodule_Graph_mincut, METH_VARARGS | METH_KEYWORDS, "mincut(source=None, target=None, capacity=None)\n\n" "Calculates the minimum cut between the source and target vertices or\n" "within the whole graph.\n\n" "The minimum cut is the minimum set of edges that needs to be removed\n" "to separate the source and the target (if they are given) or to disconnect\n" "the graph (if the source and target are not given). The minimum is\n" "calculated using the weights (capacities) of the edges, so the cut with\n" "the minimum total capacity is calculated.\n" "For undirected graphs and no source and target, the method uses the Stoer-Wagner\n" "algorithm. For a given source and target, the method uses the push-relabel\n" "algorithm; see the references below.\n\n" "@attention: this function has a more convenient interface in class\n" " L{Graph} which wraps the result in a L{Cut} object. It is advised\n" " to use that.\n" "@param source: the source vertex ID. If C{None}, target must also be\n" " {None} and the calculation will be done for the entire graph (i.e. all\n" " possible vertex pairs).\n" "@param target: the target vertex ID. If C{None}, source must also be\n" " {None} and the calculation will be done for the entire graph (i.e. all\n" " possible vertex pairs).\n" "@param capacity: the capacity of the edges. It must be a list or a valid\n" " attribute name or C{None}. In the latter case, every edge will have the\n" " same capacity.\n" "@return: the value of the minimum cut, the IDs of vertices in the\n" " first and second partition, and the IDs of edges in the cut,\n" " packed in a 4-tuple\n\n" "@newfield ref: Reference\n" "@ref: M. Stoer, F. Wagner: A simple min-cut algorithm. Journal of\n" " the ACM 44(4):585-591, 1997.\n" "@ref: A. V. Goldberg, R. E. Tarjan: A new approach to the maximum-flow problem.\n" " Journal of the ACM 35(4):921-940, 1988.\n" }, {"st_mincut", (PyCFunction) igraphmodule_Graph_st_mincut, METH_VARARGS | METH_KEYWORDS, "st_mincut(source, target, capacity=None)\n\n" "Calculates the minimum cut between the source and target vertices in a\n" "graph.\n\n" "@param source: the source vertex ID\n" "@param target: the target vertex ID\n" "@param capacity: the capacity of the edges. It must be a list or a valid\n" " attribute name or C{None}. In the latter case, every edge will have the\n" " same capacity.\n" "@return: the value of the minimum cut, the IDs of vertices in the\n" " first and second partition, and the IDs of edges in the cut,\n" " packed in a 4-tuple\n\n" "@attention: this function has a more convenient interface in class\n" " L{Graph} which wraps the result in a list of L{Cut} objects. It is\n" " advised to use that.\n" }, {"gomory_hu_tree", (PyCFunction) igraphmodule_Graph_gomory_hu_tree, METH_VARARGS | METH_KEYWORDS, "gomory_hu_tree(capacity=None)\n\n" "Internal function, undocumented.\n\n" "@see: Graph.gomory_hu_tree()\n\n" }, /*********************/ /* VERTEX SEPARATORS */ /*********************/ {"all_minimal_st_separators", (PyCFunction) igraphmodule_Graph_all_minimal_st_separators, METH_NOARGS, "all_minimal_st_separators()\n\n" "Returns a list containing all the minimal s-t separators of a graph.\n\n" "A minimal separator is a set of vertices whose removal disconnects the graph,\n" "while the removal of any subset of the set keeps the graph connected.\n\n" "@return: a list where each item lists the vertex indices of a given\n" " minimal s-t separator.\n" "@newfield ref: Reference\n" "@ref: Anne Berry, Jean-Paul Bordat and Olivier Cogis: Generating all the\n" " minimal separators of a graph. In: Peter Widmayer, Gabriele Neyer and\n" " Stephan Eidenbenz (eds.): Graph-theoretic concepts in computer science,\n" " 1665, 167--172, 1999. Springer.\n"}, {"is_minimal_separator", (PyCFunction) igraphmodule_Graph_is_minimal_separator, METH_VARARGS | METH_KEYWORDS, "is_minimal_separator(vertices)\n\n" "Decides whether the given vertex set is a minimal separator.\n\n" "A minimal separator is a set of vertices whose removal disconnects the graph,\n" "while the removal of any subset of the set keeps the graph connected.\n\n" "@param vertices: a single vertex ID or a list of vertex IDs\n" "@return: C{True} is the given vertex set is a minimal separator, C{False}\n" " otherwise.\n"}, {"is_separator", (PyCFunction) igraphmodule_Graph_is_separator, METH_VARARGS | METH_KEYWORDS, "is_separator(vertices)\n\n" "Decides whether the removal of the given vertices disconnects the graph.\n\n" "@param vertices: a single vertex ID or a list of vertex IDs\n" "@return: C{True} is the given vertex set is a separator, C{False} if not.\n"}, {"minimum_size_separators", (PyCFunction) igraphmodule_Graph_minimum_size_separators, METH_NOARGS, "minimum_size_separators()\n\n" "Returns a list containing all separator vertex sets of minimum size.\n\n" "A vertex set is a separator if its removal disconnects the graph. This method\n" "lists all the separators for which no smaller separator set exists in the\n" "given graph.\n\n" "@return: a list where each item lists the vertex indices of a given\n" " separator of minimum size.\n" "@newfield ref: Reference\n" "@ref: Arkady Kanevsky: Finding all minimum-size separating vertex sets\n" " in a graph. Networks 23:533--541, 1993.\n"}, /*******************/ /* COHESIVE BLOCKS */ /*******************/ {"cohesive_blocks", (PyCFunction) igraphmodule_Graph_cohesive_blocks, METH_NOARGS, "cohesive_blocks()\n\n" "Calculates the cohesive block structure of the graph.\n\n" "@attention: this function has a more convenient interface in class\n" " L{Graph} which wraps the result in a L{CohesiveBlocks} object.\n" " It is advised to use that.\n" }, /********************************/ /* CLIQUES AND INDEPENDENT SETS */ /********************************/ {"cliques", (PyCFunction) igraphmodule_Graph_cliques, METH_VARARGS | METH_KEYWORDS, "cliques(min=0, max=0)\n\n" "Returns some or all cliques of the graph as a list of tuples.\n\n" "A clique is a complete subgraph -- a set of vertices where an edge\n" "is present between any two of them (excluding loops)\n\n" "@param min: the minimum size of cliques to be returned. If zero or\n" " negative, no lower bound will be used.\n" "@param max: the maximum size of cliques to be returned. If zero or\n" " negative, no upper bound will be used."}, {"largest_cliques", (PyCFunction) igraphmodule_Graph_largest_cliques, METH_NOARGS, "largest_cliques()\n\n" "Returns the largest cliques of the graph as a list of tuples.\n\n" "Quite intuitively a clique is considered largest if there is no clique\n" "with more vertices in the whole graph. All largest cliques are maximal\n" "(i.e. nonextendable) but not all maximal cliques are largest.\n\n" "@see: L{clique_number()} for the size of the largest cliques or\n" " L{maximal_cliques()} for the maximal cliques"}, {"maximal_cliques", (PyCFunction) igraphmodule_Graph_maximal_cliques, METH_VARARGS | METH_KEYWORDS, "maximal_cliques(min=0, max=0, file=None)\n\n" "Returns the maximal cliques of the graph as a list of tuples.\n\n" "A maximal clique is a clique which can't be extended by adding any other\n" "vertex to it. A maximal clique is not necessarily one of the largest\n" "cliques in the graph.\n\n" "@param min: the minimum size of maximal cliques to be returned. If zero\n" " or negative, no lower bound will be used.\n\n" "@param max: the maximum size of maximal cliques to be returned. If zero\n" " or negative, no upper bound will be used. If nonzero, the size of every\n" " maximal clique found will be compared to this value and a clique will\n" " be returned only if its size is smaller than this limit.\n\n" "@param file: a file object or the name of the file to write the results\n" " to. When this argument is C{None}, the maximal cliques will be returned\n" " as a list of lists.\n" "@return: the maximal cliques of the graph as a list of lists, or C{None}\n" " if the C{file} argument was given." "@see: L{largest_cliques()} for the largest cliques."}, {"clique_number", (PyCFunction) igraphmodule_Graph_clique_number, METH_NOARGS, "clique_number()\n\n" "Returns the clique number of the graph.\n\n" "The clique number of the graph is the size of the largest clique.\n\n" "@see: L{largest_cliques()} for the largest cliques."}, {"independent_vertex_sets", (PyCFunction) igraphmodule_Graph_independent_vertex_sets, METH_VARARGS | METH_KEYWORDS, "independent_vertex_sets(min=0, max=0)\n\n" "Returns some or all independent vertex sets of the graph as a list of tuples.\n\n" "Two vertices are independent if there is no edge between them. Members\n" "of an independent vertex set are mutually independent.\n\n" "@param min: the minimum size of sets to be returned. If zero or\n" " negative, no lower bound will be used.\n" "@param max: the maximum size of sets to be returned. If zero or\n" " negative, no upper bound will be used."}, {"largest_independent_vertex_sets", (PyCFunction) igraphmodule_Graph_largest_independent_vertex_sets, METH_NOARGS, "largest_independent_vertex_sets()\n\n" "Returns the largest independent vertex sets of the graph as a list of tuples.\n\n" "Quite intuitively an independent vertex set is considered largest if\n" "there is no other set with more vertices in the whole graph. All largest\n" "sets are maximal (i.e. nonextendable) but not all maximal sets\n" "are largest.\n\n" "@see: L{independence_number()} for the size of the largest independent\n" " vertex sets or L{maximal_independent_vertex_sets()} for the maximal\n" " (nonextendable) independent vertex sets"}, {"maximal_independent_vertex_sets", (PyCFunction) igraphmodule_Graph_maximal_independent_vertex_sets, METH_NOARGS, "maximal_independent_vertex_sets()\n\n" "Returns the maximal independent vertex sets of the graph as a list of tuples.\n\n" "A maximal independent vertex set is an independent vertex set\n" "which can't be extended by adding any other vertex to it. A maximal\n" "independent vertex set is not necessarily one of the largest\n" "independent vertex sets in the graph.\n\n" "@see: L{largest_independent_vertex_sets()} for the largest independent\n" " vertex sets\n\n" "@newfield ref: Reference\n" "@ref: S. Tsukiyama, M. Ide, H. Ariyoshi and I. Shirawaka: I{A new\n" " algorithm for generating all the maximal independent sets}.\n" " SIAM J Computing, 6:505--517, 1977."}, {"independence_number", (PyCFunction) igraphmodule_Graph_independence_number, METH_NOARGS, "independence_number()\n\n" "Returns the independence number of the graph.\n\n" "The independence number of the graph is the size of the largest\n" "independent vertex set.\n\n" "@see: L{largest_independent_vertex_sets()} for the largest independent\n" " vertex sets"}, /*********************************/ /* COMMUNITIES AND DECOMPOSITION */ /*********************************/ {"modularity", (PyCFunction) igraphmodule_Graph_modularity, METH_VARARGS | METH_KEYWORDS, "modularity(membership, weights=None)\n\n" "Calculates the modularity of the graph with respect to some vertex types.\n\n" "The modularity of a graph w.r.t. some division measures how good the\n" "division is, or how separated are the different vertex types from each\n" "other. It is defined as M{Q=1/(2m) * sum(Aij-ki*kj/(2m)delta(ci,cj),i,j)}.\n" "M{m} is the number of edges, M{Aij} is the element of the M{A} adjacency\n" "matrix in row M{i} and column M{j}, M{ki} is the degree of node M{i},\n" "M{kj} is the degree of node M{j}, and M{Ci} and C{cj} are the types of\n" "the two vertices (M{i} and M{j}). M{delta(x,y)} is one iff M{x=y}, 0\n" "otherwise.\n\n" "If edge weights are given, the definition of modularity is modified as\n" "follows: M{Aij} becomes the weight of the corresponding edge, M{ki}\n" "is the total weight of edges incident on vertex M{i}, M{kj} is the\n" "total weight of edges incident on vertex M{j} and M{m} is the total\n" "edge weight in the graph.\n\n" "@attention: method overridden in L{Graph} to allow L{VertexClustering}\n" " objects as a parameter. This method is not strictly necessary, since\n" " the L{VertexClustering} class provides a variable called C{modularity}.\n" "@param membership: the membership vector, e.g. the vertex type index for\n" " each vertex.\n" "@param weights: optional edge weights or C{None} if all edges are weighed\n" " equally.\n" "@return: the modularity score. Score larger than 0.3 usually indicates\n" " strong community structure.\n" "@newfield ref: Reference\n" "@ref: MEJ Newman and M Girvan: Finding and evaluating community structure\n" " in networks. Phys Rev E 69 026113, 2004.\n" }, {"coreness", (PyCFunction) igraphmodule_Graph_coreness, METH_VARARGS | METH_KEYWORDS, "coreness(mode=ALL)\n\n" "Finds the coreness (shell index) of the vertices of the network.\n\n" "The M{k}-core of a graph is a maximal subgraph in which each vertex\n" "has at least degree k. (Degree here means the degree in the\n" "subgraph of course). The coreness of a vertex is M{k} if it\n" "is a member of the M{k}-core but not a member of the M{k+1}-core.\n\n" "@param mode: whether to compute the in-corenesses (L{IN}), the\n" " out-corenesses (L{OUT}) or the undirected corenesses (L{ALL}).\n" " Ignored and assumed to be L{ALL} for undirected graphs.\n" "@return: the corenesses for each vertex.\n\n" "@newfield ref: Reference\n" "@ref: Vladimir Batagelj, Matjaz Zaversnik: I{An M{O(m)} Algorithm\n" " for Core Decomposition of Networks.}"}, {"community_fastgreedy", (PyCFunction) igraphmodule_Graph_community_fastgreedy, METH_VARARGS | METH_KEYWORDS, "community_fastgreedy(weights=None)\n\n" "Finds the community structure of the graph according to the algorithm of\n" "Clauset et al based on the greedy optimization of modularity.\n\n" "This is a bottom-up algorithm: initially every vertex belongs to a separate\n" "community, and communities are merged one by one. In every step, the two\n" "communities being merged are the ones which result in the maximal increase\n" "in modularity.\n\n" "@attention: this function is wrapped in a more convenient syntax in the\n" " derived class L{Graph}. It is advised to use that instead of this version.\n\n" "@param weights: name of an edge attribute or a list containing\n" " edge weights\n" "@return: a tuple with the following elements:\n" " 1. The list of merges\n" " 2. The modularity scores before each merge\n" "\n" "@newfield ref: Reference\n" "@ref: A. Clauset, M. E. J. Newman and C. Moore: I{Finding community\n" " structure in very large networks.} Phys Rev E 70, 066111 (2004).\n" "@see: modularity()\n" }, {"community_infomap", (PyCFunction) igraphmodule_Graph_community_infomap, METH_VARARGS | METH_KEYWORDS, "community_infomap(edge_weights=None, vertex_weights=None, trials=10)\n\n" "Finds the community structure of the network according to the Infomap\n" "method of Martin Rosvall and Carl T. Bergstrom.\n\n" "See U{http://www.mapequation.org} for a visualization of the algorithm\n" "or one of the references provided below.\n\n" "@param edge_weights: name of an edge attribute or a list containing\n" " edge weights.\n" "@param vertex_weights: name of an vertex attribute or a list containing\n" " vertex weights.\n" "@param trials: the number of attempts to partition the network.\n" "@return: the calculated membership vector and the corresponding\n" " codelength in a tuple.\n" "\n" "@newfield ref: Reference\n" "@ref: M. Rosvall and C. T. Bergstrom: I{Maps of information flow reveal\n" " community structure in complex networks}. PNAS 105, 1118 (2008).\n" " U{http://arxiv.org/abs/0707.0609}\n" "@ref: M. Rosvall, D. Axelsson and C. T. Bergstrom: I{The map equation}.\n" " Eur Phys J Special Topics 178, 13 (2009). U{http://arxiv.org/abs/0906.1405}\n" }, {"community_label_propagation", (PyCFunction) igraphmodule_Graph_community_label_propagation, METH_VARARGS | METH_KEYWORDS, "community_label_propagation(weights=None, initial=None, fixed=None)\n\n" "Finds the community structure of the graph according to the label\n" "propagation method of Raghavan et al.\n\n" "Initially, each vertex is assigned a different label. After that,\n" "each vertex chooses the dominant label in its neighbourhood in each\n" "iteration. Ties are broken randomly and the order in which the\n" "vertices are updated is randomized before every iteration. The algorithm\n" "ends when vertices reach a consensus.\n\n" "Note that since ties are broken randomly, there is no guarantee that\n" "the algorithm returns the same community structure after each run.\n" "In fact, they frequently differ. See the paper of Raghavan et al\n" "on how to come up with an aggregated community structure.\n\n" "@param weights: name of an edge attribute or a list containing\n" " edge weights\n" "@param initial: name of a vertex attribute or a list containing\n" " the initial vertex labels. Labels are identified by integers from\n" " zero to M{n-1} where M{n} is the number of vertices. Negative\n" " numbers may also be present in this vector, they represent unlabeled\n" " vertices.\n" "@param fixed: a list of booleans for each vertex. C{True} corresponds\n" " to vertices whose labeling should not change during the algorithm.\n" " It only makes sense if initial labels are also given. Unlabeled\n" " vertices cannot be fixed. Note that vertex attribute names are not\n" " accepted here.\n" "@return: the resulting membership vector\n" "\n" "@newfield ref: Reference\n" "@ref: Raghavan, U.N. and Albert, R. and Kumara, S. Near linear\n" " time algorithm to detect community structures in large-scale\n" " networks. Phys Rev E 76:036106, 2007. U{http://arxiv.org/abs/0709.2938}.\n" }, {"community_leading_eigenvector", (PyCFunction) igraphmodule_Graph_community_leading_eigenvector, METH_VARARGS | METH_KEYWORDS, "community_leading_eigenvector(n=-1, arpack_options=None, weights=None)\n\n" "A proper implementation of Newman's eigenvector community structure\n" "detection. Each split is done by maximizing the modularity regarding\n" "the original network. See the reference for details.\n\n" "@attention: this function is wrapped in a more convenient syntax in the\n" " derived class L{Graph}. It is advised to use that instead of this version.\n\n" "@param n: the desired number of communities. If negative, the algorithm\n" " tries to do as many splits as possible. Note that the algorithm\n" " won't split a community further if the signs of the leading eigenvector\n" " are all the same.\n" "@param arpack_options: an L{ARPACKOptions} object used to fine-tune\n" " the ARPACK eigenvector calculation. If omitted, the module-level\n" " variable called C{arpack_options} is used.\n" "@param weights: name of an edge attribute or a list containing\n" " edge weights\n" "@return: a tuple where the first element is the membership vector of the\n" " clustering and the second element is the merge matrix.\n\n" "@newfield ref: Reference\n" "@ref: MEJ Newman: Finding community structure in networks using the\n" " eigenvectors of matrices, arXiv:physics/0605087\n" }, {"community_multilevel", (PyCFunction) igraphmodule_Graph_community_multilevel, METH_VARARGS | METH_KEYWORDS, "community_multilevel(weights=None, return_levels=True)\n\n" "Finds the community structure of the graph according to the multilevel\n" "algorithm of Blondel et al. This is a bottom-up algorithm: initially\n" "every vertex belongs to a separate community, and vertices are moved\n" "between communities iteratively in a way that maximizes the vertices'\n" "local contribution to the overall modularity score. When a consensus is\n" "reached (i.e. no single move would increase the modularity score), every\n" "community in the original graph is shrank to a single vertex (while\n" "keeping the total weight of the incident edges) and the process continues\n" "on the next level. The algorithm stops when it is not possible to increase\n" "the modularity any more after shrinking the communities to vertices.\n\n" "@attention: this function is wrapped in a more convenient syntax in the\n" " derived class L{Graph}. It is advised to use that instead of this version.\n\n" "@param weights: name of an edge attribute or a list containing\n" " edge weights\n" "@param return_levels: if C{True}, returns the multilevel result. If\n" " C{False}, only the best level (corresponding to the best modularity)\n" " is returned.\n" "@return: either a single list describing the community membership of each\n" " vertex (if C{return_levels} is C{False}), or a list of community membership\n" " vectors, one corresponding to each level and a list of corresponding\n" " modularities (if C{return_levels} is C{True}).\n" "\n" "@newfield ref: Reference\n" "@ref: VD Blondel, J-L Guillaume, R Lambiotte and E Lefebvre: Fast\n" " unfolding of community hierarchies in large networks. J Stat Mech\n" " P10008 (2008), http://arxiv.org/abs/0803.0476\n" "@see: modularity()\n" }, {"community_edge_betweenness", (PyCFunction)igraphmodule_Graph_community_edge_betweenness, METH_VARARGS | METH_KEYWORDS, "community_edge_betweenness(directed=True, weights=None)\n\n" "Community structure detection based on the betweenness of the edges in\n" "the network. This algorithm was invented by M Girvan and MEJ Newman,\n" "see: M Girvan and MEJ Newman: Community structure in social and biological\n" "networks, Proc. Nat. Acad. Sci. USA 99, 7821-7826 (2002).\n\n" "The idea is that the betweenness of the edges connecting two communities\n" "is typically high. So we gradually remove the edge with the highest\n" "betweenness from the network and recalculate edge betweenness after every\n" "removal, as long as all edges are removed.\n\n" "@attention: this function is wrapped in a more convenient syntax in the\n" " derived class L{Graph}. It is advised to use that instead of this version.\n\n" "@param directed: whether to take into account the directedness of the edges\n" " when we calculate the betweenness values.\n" "@param weights: name of an edge attribute or a list containing\n" " edge weights.\n\n" "@return: a tuple with the merge matrix that describes the dendrogram\n" " and the modularity scores before each merge. The modularity scores\n" " use the weights if the original graph was weighted.\n" }, {"community_optimal_modularity", (PyCFunction) igraphmodule_Graph_community_optimal_modularity, METH_VARARGS | METH_KEYWORDS, "community_optimal_modularity(weights=None)\n\n" "Calculates the optimal modularity score of the graph and the\n" "corresponding community structure.\n\n" "This function uses the GNU Linear Programming Kit to solve a large\n" "integer optimization problem in order to find the optimal modularity\n" "score and the corresponding community structure, therefore it is\n" "unlikely to work for graphs larger than a few (less than a hundred)\n" "vertices. Consider using one of the heuristic approaches instead if\n" "you have such a large graph.\n\n" "@param weights: name of an edge attribute or a list containing\n" " edge weights.\n\n" "@return: the calculated membership vector and the corresponding\n" " modularity in a tuple.\n" }, {"community_spinglass", (PyCFunction) igraphmodule_Graph_community_spinglass, METH_VARARGS | METH_KEYWORDS, "community_spinglass(weights=None, spins=25, parupdate=False, " "start_temp=1, stop_temp=0.01, cool_fact=0.99, update_rule=\"config\", " "gamma=1, implementation=\"orig\", lambda=1)\n\n" "Finds the community structure of the graph according to the spinglass\n" "community detection method of Reichardt & Bornholdt.\n\n" "@param weights: edge weights to be used. Can be a sequence or iterable or\n" " even an edge attribute name.\n" "@param spins: integer, the number of spins to use. This is the upper limit\n" " for the number of communities. It is not a problem to supply a\n" " (reasonably) big number here, in which case some spin states will be\n" " unpopulated.\n" "@param parupdate: whether to update the spins of the vertices in parallel\n" " (synchronously) or not\n" "@param start_temp: the starting temperature\n" "@param stop_temp: the stop temperature\n" "@param cool_fact: cooling factor for the simulated annealing\n" "@param update_rule: specifies the null model of the simulation. Possible\n" " values are C{\"config\"} (a random graph with the same vertex degrees\n" " as the input graph) or C{\"simple\"} (a random graph with the same number\n" " of edges)\n" "@param gamma: the gamma argument of the algorithm, specifying the balance\n" " between the importance of present and missing edges within a community.\n" " The default value of 1.0 assigns equal importance to both of them.\n" "@param implementation: currently igraph contains two implementations for\n" " the spinglass community detection algorithm. The faster original\n" " implementation is the default. The other implementation is able to take\n" " into account negative weights, this can be chosen by setting\n" " C{implementation} to C{\"neg\"}.\n" "@param lambda: the lambda argument of the algorithm, which specifies the\n" " balance between the importance of present and missing negatively\n" " weighted edges within a community. Smaller values of lambda lead\n" " to communities with less negative intra-connectivity. If the argument\n" " is zero, the algorithm reduces to a graph coloring algorithm, using\n" " the number of spins as colors. This argument is ignored if the\n" " original implementation is used.\n" "@return: the community membership vector.\n" }, {"community_leiden", (PyCFunction) igraphmodule_Graph_community_leiden, METH_VARARGS | METH_KEYWORDS, "community_leiden(edge_weights=None, node_weights=None, \n" " resolution_parameter=1.0, normalize_resolution=False, beta=0.01, \n" " initial_membership=None, n_iterations=2)\n\n" " Finds the community structure of the graph using the\n" " Leiden algorithm of Traag, van Eck & Waltman \n\n" " @param edge_weights: edge weights to be used. Can be a sequence or\n" " iterable or even an edge attribute name.\n" " @param node_weights: the node weights used in the Leiden algorithm.\n" " @param resolution_parameter: the resolution parameter to use.\n" " Higher resolutions lead to more smaller communities, while \n" " lower resolutions lead to fewer larger communities.\n" " @param normalize_resolution: if set to true, the resolution parameter\n" " will be divided by the sum of the node weights. If this is not\n" " supplied, it will default to the node degree, or weighted degree\n" " in case edge_weights are supplied.\n" " @param node_weights: the node weights used in the Leiden algorithm.\n" " @param beta: parameter affecting the randomness in the Leiden \n" " algorithm. This affects only the refinement step of the algorithm.\n" " @param initial_membership: if provided, the Leiden algorithm\n" " will try to improve this provided membership. If no argument is\n" " provided, the aglorithm simply starts from the singleton partition.\n" " @param n_iterations: the number of iterations to iterate the Leiden\n" " algorithm. Each iteration may improve the partition further.\n" " @return: the community membership vector.\n" }, {"community_walktrap", (PyCFunction) igraphmodule_Graph_community_walktrap, METH_VARARGS | METH_KEYWORDS, "community_walktrap(weights=None, steps=None)\n\n" "Finds the community structure of the graph according to the random walk\n" "method of Latapy & Pons.\n\n" "The basic idea of the algorithm is that short random walks tend to stay\n" "in the same community. The method provides a dendrogram.\n\n" "@attention: this function is wrapped in a more convenient syntax in the\n" " derived class L{Graph}. It is advised to use that instead of this version.\n\n" "@param weights: name of an edge attribute or a list containing\n" " edge weights\n" "@return: a tuple with the list of merges and the modularity scores corresponding\n" " to each merge\n" "\n" "@newfield ref: Reference\n" "@ref: Pascal Pons, Matthieu Latapy: Computing communities in large networks\n" " using random walks, U{http://arxiv.org/abs/physics/0512106}.\n" "@see: modularity()\n" }, /*************/ /* MATCHINGS */ /*************/ {"_is_matching", (PyCFunction)igraphmodule_Graph_is_matching, METH_VARARGS | METH_KEYWORDS, "_is_matching(matching, types=None)\n\n" "Internal function, undocumented.\n\n" }, {"_is_maximal_matching", (PyCFunction)igraphmodule_Graph_is_maximal_matching, METH_VARARGS | METH_KEYWORDS, "_is_maximal_matching(matching, types=None)\n\n" "Internal function, undocumented.\n\n" "Use L{Matching.is_maximal} instead.\n" }, {"_maximum_bipartite_matching", (PyCFunction)igraphmodule_Graph_maximum_bipartite_matching, METH_VARARGS | METH_KEYWORDS, "_maximum_bipartite_matching(types, weights=None)\n\n" "Internal function, undocumented.\n\n" "@see: L{Graph.maximum_bipartite_matching}\n" }, /****************/ /* RANDOM WALKS */ /****************/ {"random_walk", (PyCFunction)igraphmodule_Graph_random_walk, METH_VARARGS | METH_KEYWORDS, "random_walk(start, steps, mode=\"out\", stuck=\"return\")\n\n" "Performs a random walk of a given length from a given node.\n\n" "@param start: the starting vertex of the walk\n" "@param steps: the number of steps that the random walk should take\n" "@param mode: whether to follow outbound edges only (L{OUT}),\n" " inbound edges only (L{IN}) or both (L{ALL}). Ignored for undirected\n" " graphs." "@param stuck: what to do when the random walk gets stuck. C{\"return\"}\n" " returns a partial random walk; C{\"error\"} throws an exception.\n" "@return: a random walk that starts from the given vertex and has at most\n" " the given length (shorter if the random walk got stuck)\n" }, /**********************/ /* INTERNAL FUNCTIONS */ /**********************/ #ifdef IGRAPH_PYTHON3 {"__graph_as_capsule", (PyCFunction) igraphmodule_Graph___graph_as_capsule__, METH_VARARGS | METH_KEYWORDS, "__graph_as_capsule()\n\n" "Returns the igraph graph encapsulated by the Python object as\n" "a PyCapsule\n\n." "A PyCapsule is practically a regular C pointer, wrapped in a\n" "Python object. This function should not be used directly by igraph\n" "users, it is useful only in the case when the underlying igraph object\n" "must be passed to other C code through Python.\n\n"}, #else {"__graph_as_cobject", (PyCFunction) igraphmodule_Graph___graph_as_cobject__, METH_VARARGS | METH_KEYWORDS, "__graph_as_cobject()\n\n" "Returns the igraph graph encapsulated by the Python object as\n" "a PyCObject\n\n." "A PyCObject is practically a regular C pointer, wrapped in a\n" "Python object. This function should not be used directly by igraph\n" "users, it is useful only in the case when the underlying igraph object\n" "must be passed to other C code through Python.\n\n"}, #endif {"_raw_pointer", (PyCFunction) igraphmodule_Graph__raw_pointer, METH_NOARGS, "_raw_pointer()\n\n" "Returns the memory address of the igraph graph encapsulated by the Python\n" "object as an ordinary Python integer.\n\n" "This function should not be used directly by igraph users, it is useful\n" "only if you want to access some unwrapped function in the C core of igraph\n" "using the ctypes module.\n\n"}, {"__register_destructor", (PyCFunction) igraphmodule_Graph___register_destructor__, METH_VARARGS | METH_KEYWORDS, "__register_destructor(destructor)\n\n" "Registers a destructor to be called when the object is freed by\n" "Python. This function should not be used directly by igraph users."}, {NULL} }; /** \ingroup python_interface_graph * This structure is the collection of functions necessary to implement * the graph as a mapping (i.e. to allow the retrieval and setting of * igraph attributes in Python as if it were of a Python mapping type) */ PyMappingMethods igraphmodule_Graph_as_mapping = { /* __len__ function intentionally left unimplemented */ 0, /* returns an attribute by name or returns part of the adjacency matrix */ (binaryfunc) igraphmodule_Graph_mp_subscript, /* sets an attribute by name or sets part of the adjacency matrix */ (objobjargproc) igraphmodule_Graph_mp_assign_subscript }; /** \ingroup python_interface * \brief Collection of methods to allow numeric operators to be used on the graph */ PyNumberMethods igraphmodule_Graph_as_number = { 0, /* nb_add */ 0, /*nb_subtract */ 0, /*nb_multiply */ #ifndef IGRAPH_PYTHON3 0, /*nb_divide */ #endif 0, /*nb_remainder */ 0, /*nb_divmod */ 0, /*nb_power */ 0, /*nb_negative */ 0, /*nb_positive */ 0, /*nb_absolute */ 0, /*nb_nonzero (2.x) / nb_bool (3.x) */ (unaryfunc) igraphmodule_Graph_complementer_op, /*nb_invert */ 0, /*nb_lshift */ 0, /*nb_rshift */ (binaryfunc) igraphmodule_Graph_intersection, /*nb_and */ 0, /*nb_xor */ (binaryfunc) igraphmodule_Graph_union, /*nb_or */ #ifndef IGRAPH_PYTHON3 0, /*nb_coerce */ #endif 0, /*nb_int */ 0, /*nb_long (2.x) / nb_reserved (3.x)*/ 0, /*nb_float */ #ifndef IGRAPH_PYTHON3 0, /*nb_oct */ 0, /*nb_hex */ #endif 0, /*nb_inplace_add */ 0, /*nb_inplace_subtract */ 0, /*nb_inplace_multiply */ #ifndef IGRAPH_PYTHON3 0, /*nb_inplace_divide */ #endif 0, /*nb_inplace_remainder */ 0, /*nb_inplace_power */ 0, /*nb_inplace_lshift */ 0, /*nb_inplace_rshift */ 0, /*nb_inplace_and */ 0, /*nb_inplace_xor */ 0, /*nb_inplace_or */ #ifdef IGRAPH_PYTHON3 0, /*nb_floor_divide */ 0, /*nb_true_divide */ 0, /*nb_inplace_floor_divide */ 0, /*nb_inplace_true_divide */ 0, /*nb_index */ #endif }; /** \ingroup python_interface_graph * Python type object referencing the methods Python calls when it performs various operations on an igraph (creating, printing and so on) */ PyTypeObject igraphmodule_GraphType = { PyVarObject_HEAD_INIT(0, 0) "igraph.Graph", /* tp_name */ sizeof(igraphmodule_GraphObject), /* tp_basicsize */ 0, /* tp_itemsize */ (destructor) igraphmodule_Graph_dealloc, /* tp_dealloc */ 0, /* tp_print */ 0, /* tp_getattr */ 0, /* tp_setattr */ 0, /* tp_compare (2.x) / tp_reserved (3.x) */ 0, /* tp_repr */ &igraphmodule_Graph_as_number, /* tp_as_number */ 0, /* tp_as_sequence */ &igraphmodule_Graph_as_mapping, /* tp_as_mapping */ #ifndef PYPY_VERSION (hashfunc) PyObject_HashNotImplemented, /* tp_hash */ #else /* PyObject_HashNotImplemented raises an exception but it is not handled * properly by PyPy so we don't use it */ 0, /* tp_hash */ #endif 0, /* tp_call */ (reprfunc) igraphmodule_Graph_str, /* tp_str */ 0, /* tp_getattro */ 0, /* tp_setattro */ 0, /* tp_as_buffer */ Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE | Py_TPFLAGS_HAVE_GC, /* tp_flags */ "Low-level representation of a graph.\n\n" "Don't use it directly, use L{igraph.Graph} instead.\n\n" "@undocumented: _Bipartite, _Full_Bipartite, _GRG, _Incidence, _is_matching,\n" " _is_maximal_matching, _layout_sugiyama, _maximum_bipartite_matching,\n" " _spanning_tree\n" "@deffield ref: Reference", /* tp_doc */ (traverseproc) igraphmodule_Graph_traverse, /* tp_traverse */ (inquiry) igraphmodule_Graph_clear, /* tp_clear */ 0, /* tp_richcompare */ offsetof(igraphmodule_GraphObject, weakreflist), /* tp_weaklistoffset */ 0, /* tp_iter */ 0, /* tp_iternext */ igraphmodule_Graph_methods, /* tp_methods */ 0, /* tp_members */ 0, /* tp_getset */ 0, /* tp_base */ 0, /* tp_dict */ 0, /* tp_descr_get */ 0, /* tp_descr_set */ 0, /* tp_dictoffset */ (initproc) igraphmodule_Graph_init, /* tp_init */ 0, /* tp_alloc */ igraphmodule_Graph_new, /* tp_new */ 0, /* tp_free */ }; #undef CREATE_GRAPH python-igraph-0.8.0/src/_igraph/indexing.c0000644000076500000240000004115313104627150020714 0ustar tamasstaff00000000000000/* vim:set ts=4 sw=2 sts=2 et: */ /* IGraph library - Python interface. Copyright (C) 2006-2011 Tamas Nepusz 5 Avenue Road, Staines, Middlesex, TW18 3AW, United Kingdom This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "attributes.h" #include "convert.h" #include "error.h" #include "indexing.h" #include "platform.h" #include "py2compat.h" #include "pyhelpers.h" /***************************************************************************/ static PyObject* igraphmodule_i_Graph_adjmatrix_indexing_get_value_for_vertex_pair( igraph_t* graph, igraph_integer_t from, igraph_integer_t to, PyObject* values) { igraph_integer_t eid; PyObject* result; /* Retrieving a single edge */ igraph_get_eid(graph, &eid, from, to, /* directed = */1, /* error = */0); if (eid >= 0) { /* Edge found, get the value of the attribute */ if (values == 0) { return PyInt_FromLong(1L); } else { result = PyList_GetItem(values, eid); Py_XINCREF(result); return result; } } else { /* No such edge, return zero */ return PyInt_FromLong(0L); } } static PyObject* igraphmodule_i_Graph_adjmatrix_get_index_row(igraph_t* graph, igraph_integer_t from, igraph_vs_t* to, igraph_neimode_t neimode, PyObject* values); PyObject* igraphmodule_Graph_adjmatrix_get_index(igraph_t* graph, PyObject* row_index, PyObject* column_index, PyObject* attr_name) { PyObject *result = 0, *values; igraph_vs_t vs1, vs2; igraph_integer_t vid1 = -1, vid2 = -1; char* attr; if (igraphmodule_PyObject_to_vs_t(row_index, &vs1, graph, 0, &vid1)) return NULL; if (igraphmodule_PyObject_to_vs_t(column_index, &vs2, graph, 0, &vid2)) return NULL; if (attr_name == 0) { /* Using the "weight" attribute by default */ values = igraphmodule_get_edge_attribute_values(graph, "weight"); } else { /* Specifying the name of the attribute */ attr = igraphmodule_PyObject_ConvertToCString(attr_name); values = igraphmodule_get_edge_attribute_values(graph, attr); free(attr); } if (vid1 >= 0 && vid2 >= 0) { /* Retrieving an edge between vid1 and vid2 */ result = igraphmodule_i_Graph_adjmatrix_indexing_get_value_for_vertex_pair( graph, vid1, vid2, values); } else if (vid1 >= 0) { /* Retrieving the successors of vid1 */ result = igraphmodule_i_Graph_adjmatrix_get_index_row( graph, vid1, &vs2, IGRAPH_OUT, values); } else if (vid2 >= 0) { /* Retrieving the predecessors of vid2 */ result = igraphmodule_i_Graph_adjmatrix_get_index_row( graph, vid2, &vs1, IGRAPH_IN, values); } else { /* Retrieving a submatrix */ igraph_vit_t vit; PyObject *item; if (igraph_vit_create(graph, vs1, &vit)) { igraphmodule_handle_igraph_error(); result = 0; } else { result = PyList_New(0); if (result != 0) { while (!IGRAPH_VIT_END(vit)) { vid1 = IGRAPH_VIT_GET(vit); item = igraphmodule_i_Graph_adjmatrix_get_index_row(graph, vid1, &vs2, IGRAPH_OUT, values); if (item == 0) { Py_DECREF(result); result = 0; break; } if (PyList_Append(result, item)) { /* error while appending */ Py_DECREF(item); Py_DECREF(result); result = 0; break; } Py_DECREF(item); IGRAPH_VIT_NEXT(vit); } } igraph_vit_destroy(&vit); } } igraph_vs_destroy(&vs1); igraph_vs_destroy(&vs2); return result; } static PyObject* igraphmodule_i_Graph_adjmatrix_get_index_row(igraph_t* graph, igraph_integer_t from, igraph_vs_t* to, igraph_neimode_t neimode, PyObject* values) { igraph_vector_t eids; igraph_integer_t eid; igraph_vit_t vit; PyObject *result = 0, *item; long int i, n; igraph_integer_t v; if (igraph_vs_is_all(to)) { /* Simple case: all edges */ IGRAPH_PYCHECK(igraph_vector_init(&eids, 0)); IGRAPH_FINALLY(igraph_vector_destroy, &eids); IGRAPH_PYCHECK(igraph_incident(graph, &eids, from, neimode)); n = igraph_vector_size(&eids); result = igraphmodule_PyList_Zeroes(igraph_vcount(graph)); if (result == 0) { IGRAPH_FINALLY_FREE(); return 0; } for (i = 0; i < n; i++) { eid = (igraph_integer_t)VECTOR(eids)[i]; v = IGRAPH_OTHER(graph, eid, from); if (values) item = PyList_GetItem(values, eid); else item = PyInt_FromLong(1); Py_INCREF(item); PyList_SetItem(result, v, item); /* reference stolen here */ } IGRAPH_FINALLY_CLEAN(1); igraph_vector_destroy(&eids); return result; } /* More complicated case: only some vertices */ IGRAPH_PYCHECK(igraph_vit_create(graph, *to, &vit)); IGRAPH_FINALLY(igraph_vit_destroy, &vit); result = PyList_New(0); if (result == 0) { IGRAPH_FINALLY_FREE(); return 0; } while (!IGRAPH_VIT_END(vit)) { v = IGRAPH_VIT_GET(vit); if (neimode == IGRAPH_OUT) { item = igraphmodule_i_Graph_adjmatrix_indexing_get_value_for_vertex_pair( graph, from, v, values); } else { item = igraphmodule_i_Graph_adjmatrix_indexing_get_value_for_vertex_pair( graph, v, from, values); } if (item == 0) { IGRAPH_FINALLY_FREE(); Py_DECREF(result); return 0; } if (PyList_Append(result, item)) { /* error while appending */ Py_DECREF(item); Py_DECREF(result); result = 0; break; } Py_DECREF(item); IGRAPH_VIT_NEXT(vit); } igraph_vit_destroy(&vit); IGRAPH_FINALLY_CLEAN(1); return result; } /***************************************************************************/ /** * Determines whether the given Python value means that the user would like * to delete the edge the value is being assigned to in the adjacency matrix * assignment syntax. */ static INLINE igraph_bool_t deleting_edge(PyObject* value) { return value == Py_None || value == Py_False || (PyInt_Check(value) && PyInt_AsLong(value) == 0); } /** * Structure to hold data related to newly added/removed edges during an * adjacency matrix assignment. */ typedef struct { igraph_vector_t to_add; PyObject* to_add_values; igraph_vector_t to_delete; } igraphmodule_i_Graph_adjmatrix_set_index_data_t; int igraphmodule_i_Graph_adjmatrix_set_index_data_init( igraphmodule_i_Graph_adjmatrix_set_index_data_t* data) { if (igraph_vector_init(&data->to_add, 0)) { igraphmodule_handle_igraph_error(); return -1; } if (igraph_vector_init(&data->to_delete, 0)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&data->to_delete); return -1; } data->to_add_values = PyList_New(0); if (data->to_add_values == 0) { igraph_vector_destroy(&data->to_add); igraph_vector_destroy(&data->to_delete); return -1; } return 0; } void igraphmodule_i_Graph_adjmatrix_set_index_data_destroy( igraphmodule_i_Graph_adjmatrix_set_index_data_t* data) { igraph_vector_destroy(&data->to_add); igraph_vector_destroy(&data->to_delete); Py_DECREF(data->to_add_values); } static int igraphmodule_i_Graph_adjmatrix_set_index_row(igraph_t* graph, igraph_integer_t from, igraph_vs_t* to, igraph_neimode_t neimode, PyObject* values, PyObject* new_value, igraphmodule_i_Graph_adjmatrix_set_index_data_t* data) { PyObject *iter = 0, *item; igraph_vit_t vit; igraph_integer_t v, v1, v2, eid; igraph_bool_t deleting, ok = 1; /* Check whether new_value is an iterable (and not a string). If not, * every assignment will use the same value (that is, new_value) */ if (!PyBaseString_Check(new_value)) { iter = PyObject_GetIter(new_value); if (PyErr_Occurred()) { /* Object is not an iterable. Clear the exception */ iter = 0; PyErr_Clear(); } } if (igraph_vit_create(graph, *to, &vit)) { Py_XDECREF(iter); igraphmodule_handle_igraph_error(); return -1; } v1 = from; v2 = from; /* The two branches of the next `if' are almost the same; make sure * you make changes to both branches if appropriate! */ if (iter != 0) { /* The new value is an iterable, so it must have exactly as many elements * as the number of vertices in the graph. If it has less, we simply * skip the rest (with a warning) */ while (!IGRAPH_VIT_END(vit) && (item = PyIter_Next(iter)) != 0) { v = IGRAPH_VIT_GET(vit); /* Get the ID of the edge between from and v */ if (neimode == IGRAPH_OUT) { v2 = v; } else { v1 = v; } igraph_get_eid(graph, &eid, v1, v2, /* directed = */1, /* error = */0); if (deleting_edge(item)) { /* Deleting edges if eid != -1 */ if (eid != -1) { if (igraph_vector_push_back(&data->to_delete, eid)) { igraphmodule_handle_igraph_error(); igraph_vector_clear(&data->to_delete); ok = 0; break; } } } else { if (eid == -1) { /* Adding edges */ if (igraph_vector_push_back(&data->to_add, v1) || igraph_vector_push_back(&data->to_add, v2)) { igraphmodule_handle_igraph_error(); igraph_vector_clear(&data->to_add); ok = 0; break; } if (values != 0) { Py_INCREF(new_value); if (PyList_Append(data->to_add_values, new_value)) { Py_DECREF(new_value); igraph_vector_clear(&data->to_add); ok = 0; break; } } } else if (values != 0) { /* Setting attribute */ Py_INCREF(item); if (PyList_SetItem(values, eid, item)) { Py_DECREF(item); igraph_vector_clear(&data->to_add); } } } Py_DECREF(item); IGRAPH_VIT_NEXT(vit); } if (!IGRAPH_VIT_END(vit)) { PyErr_WarnEx(PyExc_RuntimeWarning, "iterable was shorter than the number of vertices in the vertex " "sequence", 1); } } else { /* The new value is not an iterable; setting the same value for * more than one edge */ deleting = deleting_edge(new_value); while (!IGRAPH_VIT_END(vit)) { v = IGRAPH_VIT_GET(vit); /* Get the ID of the edge between from and v */ if (neimode == IGRAPH_OUT) { v2 = v; } else { v1 = v; } igraph_get_eid(graph, &eid, v1, v2, /* directed = */1, /* error = */0); if (deleting) { /* Deleting edges if eid != -1 */ if (eid != -1) { if (igraph_vector_push_back(&data->to_delete, eid)) { igraphmodule_handle_igraph_error(); igraph_vector_clear(&data->to_delete); ok = 0; break; } } } else { if (eid == -1) { /* Adding edges */ if (igraph_vector_push_back(&data->to_add, v1) || igraph_vector_push_back(&data->to_add, v2)) { igraphmodule_handle_igraph_error(); igraph_vector_clear(&data->to_add); ok = 0; break; } if (values != 0) { Py_INCREF(new_value); if (PyList_Append(data->to_add_values, new_value)) { Py_DECREF(new_value); igraph_vector_clear(&data->to_add); ok = 0; break; } } } else if (values != 0) { /* Setting attribute */ Py_INCREF(new_value); if (PyList_SetItem(values, eid, new_value)) { Py_DECREF(new_value); igraph_vector_clear(&data->to_add); } } } IGRAPH_VIT_NEXT(vit); } } Py_XDECREF(iter); igraph_vit_destroy(&vit); return ok ? 0 : -1; } int igraphmodule_Graph_adjmatrix_set_index(igraph_t* graph, PyObject* row_index, PyObject* column_index, PyObject* attr_name, PyObject* new_value) { PyObject *values; igraph_vs_t vs1, vs2; igraph_vit_t vit; igraph_integer_t vid1 = -1, vid2 = -1, eid = -1; igraph_bool_t ok = 1; igraphmodule_i_Graph_adjmatrix_set_index_data_t data; char* attr; if (igraphmodule_PyObject_to_vs_t(row_index, &vs1, graph, 0, &vid1)) return -1; if (igraphmodule_PyObject_to_vs_t(column_index, &vs2, graph, 0, &vid2)) return -1; if (attr_name == 0) { /* Using the "weight" attribute by default */ values = igraphmodule_get_edge_attribute_values(graph, "weight"); } else { /* Specifying the name of the attribute */ attr = igraphmodule_PyObject_ConvertToCString(attr_name); values = igraphmodule_create_or_get_edge_attribute_values(graph, attr); free(attr); } if (vid1 >= 0 && vid2 >= 0) { /* Setting an edge between vid1 and vid2 */ igraph_get_eid(graph, &eid, vid1, vid2, /* directed = */1, /* error = */0); if (deleting_edge(new_value)) { if (eid != -1) { /* Deleting the edge between vid1 and vid2 if it is there */ if (igraph_delete_edges(graph, igraph_ess_1(eid))) { igraphmodule_handle_igraph_error(); ok = 0; } } } else { /* Adding the edge between vid1 and vid2 if it is not there */ if (eid == -1) { eid = igraph_ecount(graph); if (igraph_add_edge(graph, vid1, vid2)) { igraphmodule_handle_igraph_error(); ok = 0; } } if (ok && values != 0) { /* Set the attribute value */ Py_INCREF(new_value); PyList_SetItem(values, eid, new_value); /* reference stolen here */ } } } else { /* In all the non-trivial cases, we do the modifications in three phases; * in the first phase, we modify the attribute values of edges that are to * stay (but possibly with a different attribute value) and collect the * list of edges to be added (and their attribute values) and the list of * edge to be deleted. In the second phase, we do the deletions in one * batch. Finally, we add the edges to be added. */ igraphmodule_i_Graph_adjmatrix_set_index_data_init(&data); /* First phase */ if (vid1 >= 0) { /* vs1 is a single vertex, vs2 is not */ ok = (igraphmodule_i_Graph_adjmatrix_set_index_row( graph, vid1, &vs2, IGRAPH_OUT, values, new_value, &data) == 0); } else if (vid2 >= 0) { /* vs2 is a single vertex, vs1 is not */ ok = (igraphmodule_i_Graph_adjmatrix_set_index_row( graph, vid2, &vs1, IGRAPH_IN, values, new_value, &data) == 0); } else { /* Complete submatrix */ if (igraph_vit_create(graph, vs1, &vit)) { igraphmodule_handle_igraph_error(); ok = 0; } else { while (!IGRAPH_VIT_END(vit)) { vid1 = IGRAPH_VIT_GET(vit); if (igraphmodule_i_Graph_adjmatrix_set_index_row( graph, vid1, &vs2, IGRAPH_OUT, values, new_value, &data) == 0) { ok = 0; break; } IGRAPH_VIT_NEXT(vit); } igraph_vit_destroy(&vit); } } if (ok) { /* Second phase: do the deletions in one batch */ if (igraph_delete_edges(graph, igraph_ess_vector(&data.to_delete))) { igraphmodule_handle_igraph_error(); ok = 0; } } if (ok) { /* Third phase: add the new edges in one batch */ if (!igraph_vector_empty(&data.to_add)) { eid = igraph_ecount(graph); igraph_add_edges(graph, &data.to_add, 0); if (values != 0) { PyList_SetSlice(values, eid, eid+PyList_Size(data.to_add_values), data.to_add_values); if (PyList_Size(values) != igraph_ecount(graph)) { PyErr_SetString(PyExc_ValueError, "hmmm, attribute value list " "length mismatch, this is most likely a bug."); ok = 0; } } } } igraphmodule_i_Graph_adjmatrix_set_index_data_destroy(&data); } igraph_vs_destroy(&vs1); igraph_vs_destroy(&vs2); return ok ? 0 : -1; } python-igraph-0.8.0/src/_igraph/igraphmodule.c0000644000076500000240000007514513616240152021600 0ustar tamasstaff00000000000000/* vim:set ts=2 sw=2 sts=2 et: */ /* IGraph library. Copyright (C) 2006-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include #include #include "arpackobject.h" #include "attributes.h" #include "bfsiter.h" #include "common.h" #include "convert.h" #include "edgeobject.h" #include "edgeseqobject.h" #include "error.h" #include "graphobject.h" #include "py2compat.h" #include "random.h" #include "vertexobject.h" #include "vertexseqobject.h" #define IGRAPH_MODULE #include "igraphmodule_api.h" extern double igraph_i_fdiv(double, double); /** * \defgroup python_interface Python module implementation * \brief Functions implementing a Python interface to \a igraph * * These functions provide a way to access \a igraph functions from Python. * It should be of interest of \a igraph developers only. Classes, functions * and methods exposed to Python are still to be documented. Until it is done, * just type the following to get help about \a igraph functions in Python * (assuming you have \c igraph.so somewhere in your Python library path): * * \verbatim import igraph help(igraph) help(igraph.Graph) \endverbatim * * Most of the functions provided here share the same calling conventions * (which are determined by the Python/C API). Since the role of the * arguments are the same across many functions, I won't explain them * everywhere, just give a quick overview of the common argument names here. * * \param self the Python igraph.Graph object the method is working on * \param args pointer to the Python tuple containing the arguments * \param kwds pointer to the Python hash containing the keyword parameters * \param type the type object of a Python igraph.Graph object. Used usually * in constructors and class methods. * * Any arguments not documented here should be mentioned at the documentation * of the appropriate method. * * The functions which implement a Python method always return a pointer to * a \c PyObject. According to Python conventions, this is \c NULL if and * only if an exception was thrown by the method (or any of the functions * it has called). When I explain the return value of a function which * provides interface to an \a igraph function, I won't cover the case of * returning a \c NULL value, because this is the same for every such method. * The conclusion is that a method can return \c NULL even if I don't state * it explicitly. * * Also please take into consideration that I'm documenting the C calls * with the abovementioned parameters here, and \em not the Python methods * which are presented to the user using the Python interface of \a igraph. * If you are looking for the documentation of the classes, methods and * functions exposed to Python, please use the \c help calls from Python * or use \c pydoc to generate a formatted version. * * \section weakrefs The usage of weak references in the Python interface * * Many classes implemented in the Python interface (e.g. VertexSeq, Vertex...) * use weak references to keep track of the graph they are referencing to. * The use of weak references is twofold: * * -# If we assign a VertexSeq or a Vertex of a given graph to a local * variable and then destroy the graph, real references keep the graph * alive and do not return the memory back to Python. * -# If we use real references, a Graph object will hold a reference * to its VertexSeq (because we don't want to allocate a new VertexSeq * object for the same graph every time it is requested), and the * VertexSeq will also hold a reference to the Graph. This is a circular * reference. Python does not reclaim the memory occupied by the Graph * back when the Graph is destroyed, because the VertexSeq is holding a * reference to it. Similarly, VertexSeq doesn't get freed because the * Graph is holding a reference to it. These situations can only be * resolved by the Python garbage collector which is invoked at regular * intervals. Unfortunately, the garbage collector refuses to break * circular references and free the objects participating in the circle * when any of the objects has a \c __del__ method. In this case, * \c igraph.Graph has one (which frees the underlying \c igraph_t * graph), therefore our graphs never get freed when we use real * references. */ /** * Whether the module was initialized already */ static igraph_bool_t igraphmodule_initialized = 0; /** * Module-specific global variables */ struct module_state { PyObject* progress_handler; PyObject* status_handler; }; static struct module_state _state = { 0, 0 }; #define GETSTATE(m) (&_state) #ifdef IGRAPH_PYTHON3 static int igraphmodule_traverse(PyObject *m, visitproc visit, void* arg) { Py_VISIT(GETSTATE(m)->progress_handler); Py_VISIT(GETSTATE(m)->status_handler); return 0; } static int igraphmodule_clear(PyObject *m) { Py_CLEAR(GETSTATE(m)->progress_handler); Py_CLEAR(GETSTATE(m)->status_handler); return 0; } #endif static int igraphmodule_igraph_interrupt_hook(void* data) { if (PyErr_CheckSignals()) { IGRAPH_FINALLY_FREE(); return IGRAPH_INTERRUPTED; } return IGRAPH_SUCCESS; } int igraphmodule_igraph_progress_hook(const char* message, igraph_real_t percent, void* data) { PyObject* progress_handler = GETSTATE(0)->progress_handler; if (progress_handler) { PyObject *result; if (PyCallable_Check(progress_handler)) { result=PyObject_CallFunction(progress_handler, "sd", message, (double)percent); if (result) Py_DECREF(result); else return IGRAPH_INTERRUPTED; } } return IGRAPH_SUCCESS; } int igraphmodule_igraph_status_hook(const char* message, void*data) { PyObject* status_handler = GETSTATE(0)->status_handler; if (status_handler) { PyObject *result; if (PyCallable_Check(status_handler)) { result = PyObject_CallFunction(status_handler, "s", message); if (result) Py_DECREF(result); else return IGRAPH_INTERRUPTED; } } return IGRAPH_SUCCESS; } PyObject* igraphmodule_set_progress_handler(PyObject* self, PyObject* o) { PyObject* progress_handler; if (!PyCallable_Check(o) && o != Py_None) { PyErr_SetString(PyExc_TypeError, "Progress handler must be callable."); return NULL; } progress_handler = GETSTATE(self)->progress_handler; if (o == progress_handler) Py_RETURN_NONE; Py_XDECREF(progress_handler); if (o == Py_None) o = 0; Py_XINCREF(o); GETSTATE(self)->progress_handler=o; Py_RETURN_NONE; } PyObject* igraphmodule_set_status_handler(PyObject* self, PyObject* o) { PyObject* status_handler; if (!PyCallable_Check(o) && o != Py_None) { PyErr_SetString(PyExc_TypeError, "Status handler must be callable."); return NULL; } status_handler = GETSTATE(self)->status_handler; if (o == status_handler) Py_RETURN_NONE; Py_XDECREF(status_handler); if (o == Py_None) o = 0; Py_INCREF(o); GETSTATE(self)->status_handler = o; Py_RETURN_NONE; } PyObject* igraphmodule_convex_hull(PyObject* self, PyObject* args, PyObject* kwds) { static char* kwlist[] = {"vs", "coords", NULL}; PyObject *vs, *o, *o1=0, *o2=0, *coords = Py_False; igraph_matrix_t mtrx; igraph_vector_t result; igraph_matrix_t resmat; long no_of_nodes, i; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O!|O", kwlist, &PyList_Type, &vs, &coords)) return NULL; no_of_nodes=PyList_Size(vs); if (igraph_matrix_init(&mtrx, no_of_nodes, 2)) { igraphmodule_handle_igraph_error(); return NULL; } for (i=0; i= 2) { o1=PyList_GetItem(o, 0); o2=PyList_GetItem(o, 1); if (PyList_Size(o) > 2) PyErr_Warn(PyExc_Warning, "vertex with more than 2 coordinates found, considering only the first 2"); } else { PyErr_SetString(PyExc_TypeError, "vertex with less than 2 coordinates found"); igraph_matrix_destroy(&mtrx); return NULL; } } else if (PyTuple_Check(o)) { if (PyTuple_Size(o) >= 2) { o1=PyTuple_GetItem(o, 0); o2=PyTuple_GetItem(o, 1); if (PyTuple_Size(o) > 2) PyErr_Warn(PyExc_Warning, "vertex with more than 2 coordinates found, considering only the first 2"); } else { PyErr_SetString(PyExc_TypeError, "vertex with less than 2 coordinates found"); igraph_matrix_destroy(&mtrx); return NULL; } } if (!PyNumber_Check(o1) || !PyNumber_Check(o2)) { PyErr_SetString(PyExc_TypeError, "vertex coordinates must be numeric"); igraph_matrix_destroy(&mtrx); return NULL; } /* o, o1 and o2 were borrowed, but now o1 and o2 are actual references! */ o1=PyNumber_Float(o1); o2=PyNumber_Float(o2); if (!o1 || !o2) { PyErr_SetString(PyExc_TypeError, "vertex coordinate conversion to float failed"); Py_XDECREF(o1); Py_XDECREF(o2); igraph_matrix_destroy(&mtrx); return NULL; } MATRIX(mtrx, i, 0)=(igraph_real_t)PyFloat_AsDouble(o1); MATRIX(mtrx, i, 1)=(igraph_real_t)PyFloat_AsDouble(o2); Py_DECREF(o1); Py_DECREF(o2); } if (!PyObject_IsTrue(coords)) { if (igraph_vector_init(&result, 0)) { igraphmodule_handle_igraph_error(); igraph_matrix_destroy(&mtrx); return NULL; } if (igraph_convex_hull(&mtrx, &result, 0)) { igraphmodule_handle_igraph_error(); igraph_matrix_destroy(&mtrx); igraph_vector_destroy(&result); return NULL; } o=igraphmodule_vector_t_to_PyList(&result, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&result); } else { if (igraph_matrix_init(&resmat, 0, 0)) { igraphmodule_handle_igraph_error(); igraph_matrix_destroy(&mtrx); return NULL; } if (igraph_convex_hull(&mtrx, 0, &resmat)) { igraphmodule_handle_igraph_error(); igraph_matrix_destroy(&mtrx); igraph_matrix_destroy(&resmat); return NULL; } o=igraphmodule_matrix_t_to_PyList(&resmat, IGRAPHMODULE_TYPE_FLOAT); igraph_matrix_destroy(&resmat); } igraph_matrix_destroy(&mtrx); return o; } PyObject* igraphmodule_community_to_membership(PyObject *self, PyObject *args, PyObject *kwds) { static char* kwlist[] = { "merges", "nodes", "steps", "return_csize", NULL }; PyObject *merges_o, *return_csize = Py_False, *result_o; igraph_matrix_t merges; igraph_vector_t result, csize, *csize_p = 0; long int nodes, steps; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O!ll|O", kwlist, &PyList_Type, &merges_o, &nodes, &steps, &return_csize)) return NULL; if (igraphmodule_PyList_to_matrix_t(merges_o, &merges)) return NULL; if (igraph_vector_init(&result, nodes)) { igraphmodule_handle_igraph_error(); igraph_matrix_destroy(&merges); return NULL; } if (PyObject_IsTrue(return_csize)) { igraph_vector_init(&csize, 0); csize_p = &csize; } if (igraph_community_to_membership(&merges, (igraph_integer_t)nodes, (igraph_integer_t)steps, &result, csize_p)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&result); if (csize_p) igraph_vector_destroy(csize_p); igraph_matrix_destroy(&merges); return NULL; } igraph_matrix_destroy(&merges); result_o = igraphmodule_vector_t_to_PyList(&result, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&result); if (csize_p) { PyObject* csize_o = igraphmodule_vector_t_to_PyList(csize_p, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(csize_p); if (csize_o) return Py_BuildValue("NN", result_o, csize_o); Py_DECREF(result_o); return NULL; } return result_o; } PyObject* igraphmodule_compare_communities(PyObject *self, PyObject *args, PyObject *kwds) { static char* kwlist[] = { "comm1", "comm2", "method", NULL }; PyObject *comm1_o, *comm2_o, *method_o = Py_None; igraph_vector_t comm1, comm2; igraph_community_comparison_t method = IGRAPH_COMMCMP_VI; igraph_real_t result; if (!PyArg_ParseTupleAndKeywords(args, kwds, "OO|O", kwlist, &comm1_o, &comm2_o, &method_o)) return NULL; if (igraphmodule_PyObject_to_community_comparison_t(method_o, &method)) return NULL; if (igraphmodule_PyObject_to_vector_t(comm1_o, &comm1, 0)) return NULL; if (igraphmodule_PyObject_to_vector_t(comm2_o, &comm2, 0)) { igraph_vector_destroy(&comm1); return NULL; } if (igraph_compare_communities(&comm1, &comm2, &result, method)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&comm1); igraph_vector_destroy(&comm2); return NULL; } igraph_vector_destroy(&comm1); igraph_vector_destroy(&comm2); return PyFloat_FromDouble((double)result); } PyObject* igraphmodule_is_degree_sequence(PyObject *self, PyObject *args, PyObject *kwds) { static char* kwlist[] = { "out_deg", "in_deg", NULL }; PyObject *out_deg_o = 0, *in_deg_o = 0; igraph_vector_t out_deg, in_deg; igraph_bool_t is_directed, result; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|O", kwlist, &out_deg_o, &in_deg_o)) return NULL; is_directed = (in_deg_o != 0 && in_deg_o != Py_None); if (igraphmodule_PyObject_to_vector_t(out_deg_o, &out_deg, 0)) return NULL; if (is_directed && igraphmodule_PyObject_to_vector_t(in_deg_o, &in_deg, 0)) { igraph_vector_destroy(&out_deg); return NULL; } if (igraph_is_degree_sequence(&out_deg, is_directed ? &in_deg : 0, &result)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&out_deg); if (is_directed) igraph_vector_destroy(&in_deg); return NULL; } igraph_vector_destroy(&out_deg); if (is_directed) igraph_vector_destroy(&in_deg); if (result) Py_RETURN_TRUE; else Py_RETURN_FALSE; } PyObject* igraphmodule_is_graphical_degree_sequence(PyObject *self, PyObject *args, PyObject *kwds) { static char* kwlist[] = { "out_deg", "in_deg", NULL }; PyObject *out_deg_o = 0, *in_deg_o = 0; igraph_vector_t out_deg, in_deg; igraph_bool_t is_directed, result; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|O", kwlist, &out_deg_o, &in_deg_o)) return NULL; is_directed = (in_deg_o != 0 && in_deg_o != Py_None); if (igraphmodule_PyObject_to_vector_t(out_deg_o, &out_deg, 0)) return NULL; if (is_directed && igraphmodule_PyObject_to_vector_t(in_deg_o, &in_deg, 0)) { igraph_vector_destroy(&out_deg); return NULL; } if (igraph_is_graphical_degree_sequence(&out_deg, is_directed ? &in_deg : 0, &result)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&out_deg); if (is_directed) igraph_vector_destroy(&in_deg); return NULL; } igraph_vector_destroy(&out_deg); if (is_directed) igraph_vector_destroy(&in_deg); if (result) Py_RETURN_TRUE; else Py_RETURN_FALSE; } PyObject* igraphmodule_power_law_fit(PyObject *self, PyObject *args, PyObject *kwds) { static char* kwlist[] = { "data", "xmin", "force_continuous", NULL }; PyObject *data_o, *force_continuous_o = Py_False; igraph_vector_t data; igraph_plfit_result_t result; double xmin = -1; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|dO", kwlist, &data_o, &xmin, &force_continuous_o)) return NULL; if (igraphmodule_PyObject_float_to_vector_t(data_o, &data)) return NULL; if (igraph_power_law_fit(&data, &result, xmin, PyObject_IsTrue(force_continuous_o))) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&data); return NULL; } igraph_vector_destroy(&data); return Py_BuildValue("Oddddd", result.continuous ? Py_True : Py_False, result.alpha, result.xmin, result.L, result.D, result.p); } PyObject* igraphmodule_split_join_distance(PyObject *self, PyObject *args, PyObject *kwds) { static char* kwlist[] = { "comm1", "comm2", NULL }; PyObject *comm1_o, *comm2_o; igraph_vector_t comm1, comm2; igraph_integer_t distance12, distance21; if (!PyArg_ParseTupleAndKeywords(args, kwds, "OO", kwlist, &comm1_o, &comm2_o)) return NULL; if (igraphmodule_PyObject_to_vector_t(comm1_o, &comm1, 0)) return NULL; if (igraphmodule_PyObject_to_vector_t(comm2_o, &comm2, 0)) { igraph_vector_destroy(&comm1); return NULL; } if (igraph_split_join_distance(&comm1, &comm2, &distance12, &distance21)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&comm1); igraph_vector_destroy(&comm2); return NULL; } igraph_vector_destroy(&comm1); igraph_vector_destroy(&comm2); return Py_BuildValue("ll", (long)distance12, (long)distance21); } /** \ingroup python_interface * \brief Method table for the igraph Python module */ static PyMethodDef igraphmodule_methods[] = { {"community_to_membership", (PyCFunction)igraphmodule_community_to_membership, METH_VARARGS | METH_KEYWORDS, "community_to_membership(merges, nodes, steps, return_csize=False)" }, {"_compare_communities", (PyCFunction)igraphmodule_compare_communities, METH_VARARGS | METH_KEYWORDS, "_compare_communities(comm1, comm2, method=\"vi\")" }, {"_power_law_fit", (PyCFunction)igraphmodule_power_law_fit, METH_VARARGS | METH_KEYWORDS, "_power_law_fit(data, xmin=-1, force_continuous=False)" }, {"convex_hull", (PyCFunction)igraphmodule_convex_hull, METH_VARARGS | METH_KEYWORDS, "convex_hull(vs, coords=False)\n\n" "Calculates the convex hull of a given point set.\n\n" "@param vs: the point set as a list of lists\n" "@param coords: if C{True}, the function returns the\n" " coordinates of the corners of the convex hull polygon,\n" " otherwise returns the corner indices.\n" "@return: either the hull's corner coordinates or the point\n" " indices corresponding to them, depending on the C{coords}\n" " parameter." }, {"is_degree_sequence", (PyCFunction)igraphmodule_is_degree_sequence, METH_VARARGS | METH_KEYWORDS, "is_degree_sequence(out_deg, in_deg=None)\n\n" "Returns whether a list of degrees can be a degree sequence of some graph.\n\n" "Note that it is not required for the graph to be simple; in other words,\n" "this function may return C{True} for degree sequences that can be realized\n" "using one or more multiple or loop edges only.\n\n" "In particular, this function checks whether\n\n" " - all the degrees are non-negative\n" " - for undirected graphs, the sum of degrees are even\n" " - for directed graphs, the two degree sequences are of the same length and\n" " equal sums\n\n" "@param out_deg: the list of degrees. For directed graphs, this list must\n" " contain the out-degrees of the vertices.\n" "@param in_deg: the list of in-degrees for directed graphs. This parameter\n" " must be C{None} for undirected graphs.\n" "@return: C{True} if there exists some graph that can realize the given degree\n" " sequence, C{False} otherwise." "@see: L{is_graphical_degree_sequence()} if you do not want to allow multiple\n" " or loop edges.\n" }, {"is_graphical_degree_sequence", (PyCFunction)igraphmodule_is_graphical_degree_sequence, METH_VARARGS | METH_KEYWORDS, "is_graphical_degree_sequence(out_deg, in_deg=None)\n\n" "Returns whether a list of degrees can be a degree sequence of some simple graph.\n\n" "Note that it is required for the graph to be simple; in other words,\n" "this function will return C{False} for degree sequences that cannot be realized\n" "without using one or more multiple or loop edges.\n\n" "@param out_deg: the list of degrees. For directed graphs, this list must\n" " contain the out-degrees of the vertices.\n" "@param in_deg: the list of in-degrees for directed graphs. This parameter\n" " must be C{None} for undirected graphs.\n" "@return: C{True} if there exists some simple graph that can realize the given\n" " degree sequence, C{False} otherwise.\n" "@see: L{is_degree_sequence()} if you want to allow multiple or loop edges.\n" }, {"set_progress_handler", igraphmodule_set_progress_handler, METH_O, "set_progress_handler(handler)\n\n" "Sets the handler to be called when igraph is performing a long operation.\n" "@param handler: the progress handler function. It must accept two\n" " arguments, the first is the message informing the user about\n" " what igraph is doing right now, the second is the actual\n" " progress information (a percentage).\n" }, {"set_random_number_generator", igraph_rng_Python_set_generator, METH_O, "set_random_number_generator(generator)\n\n" "Sets the random number generator used by igraph.\n" "@param generator: the generator to be used. It must be a Python object\n" " with at least three attributes: C{random}, C{randint} and C{gauss}.\n" " Each of them must be callable and their signature and behaviour\n" " must be identical to C{random.random}, C{random.randint} and\n" " C{random.gauss}. By default, igraph uses the C{random} module for\n" " random number generation, but you can supply your alternative\n" " implementation here. If the given generator is C{None}, igraph\n" " reverts to the default Mersenne twister generator implemented in the\n" " C layer, which might be slightly faster than calling back to Python\n" " for random numbers, but you cannot set its seed or save its state.\n" }, {"set_status_handler", igraphmodule_set_status_handler, METH_O, "set_status_handler(handler)\n\n" "Sets the handler to be called when igraph tries to display a status\n" "message.\n\n" "This is used to communicate the progress of some calculations where\n" "no reasonable progress percentage can be given (so it is not possible\n" "to use the progress handler).\n\n" "@param handler: the status handler function. It must accept a single\n" " argument, the message that informs the user about what igraph is\n" " doing right now.\n" }, {"_split_join_distance", (PyCFunction)igraphmodule_split_join_distance, METH_VARARGS | METH_KEYWORDS, "_split_join_distance(comm1, comm2)" }, {NULL, NULL, 0, NULL} }; #define MODULE_DOCS \ "Low-level Python interface for the igraph library. " \ "Should not be used directly.\n\n" \ "@undocumented: community_to_membership, _compare_communities, _power_law_fit, " \ "_split_join_distance" /** * Module definition table (only for Python 3.x) */ #ifdef IGRAPH_PYTHON3 static struct PyModuleDef moduledef = { PyModuleDef_HEAD_INIT, "igraph._igraph", /* m_name */ MODULE_DOCS, /* m_doc */ sizeof(struct module_state), /* m_size */ igraphmodule_methods, /* m_methods */ 0, /* m_reload */ igraphmodule_traverse, /* m_traverse */ igraphmodule_clear, /* m_clear */ 0 /* m_free */ }; #endif /****************** Exported API functions *******************/ /** * \brief Constructs a new Python Graph object from an existing igraph_t * * The newly created Graph object will take ownership of igraph_t and * it will destroy it when the Python object is destructed. * * Returns a null pointer in case of an error and sets the appropriate * Python exception. */ PyObject* PyIGraph_FromCGraph(igraph_t* g) { return igraphmodule_Graph_from_igraph_t(g); } /** * \brief Extracts the pointer to the \c igraph_t held by a Graph instance * * The ownership of the \c igraph_t object remains with the Graph instance, * so make sure you don't call \c igraph_destroy() on the extracted pointer. * * Returns a null pointer in case of an error and sets the appropriate * Python exception. */ igraph_t* PyIGraph_ToCGraph(PyObject* graph) { igraph_t *result = 0; if (graph == Py_None) { PyErr_SetString(PyExc_TypeError, "expected Graph, got None"); return 0; } if (igraphmodule_PyObject_to_igraph_t(graph, &result)) return 0; if (result == 0) PyErr_SetString(PyExc_ValueError, "null pointer stored inside a Graph " "object. Probably a bug."); return result; } extern PyObject* igraphmodule_InternalError; extern PyObject* igraphmodule_arpack_options_default; #ifdef IGRAPH_PYTHON3 # define INITERROR return NULL PyObject* PyInit__igraph(void) #else # define INITERROR return # ifndef PyMODINIT_FUNC # define PyMODINIT_FUNC void # endif PyMODINIT_FUNC init_igraph(void) #endif { PyObject* m; static void *PyIGraph_API[PyIGraph_API_pointers]; PyObject *c_api_object; /* Check if the module is already initialized (possibly in another Python * interpreter. If so, bail out as we don't support this. */ if (igraphmodule_initialized) { PyErr_SetString(PyExc_RuntimeError, "igraph module is already initialized " "in a different Python interpreter"); INITERROR; } /* Initialize VertexSeq, EdgeSeq */ if (PyType_Ready(&igraphmodule_VertexSeqType) < 0) INITERROR; if (PyType_Ready(&igraphmodule_EdgeSeqType) < 0) INITERROR; /* Initialize Vertex, Edge */ igraphmodule_VertexType.tp_clear = (inquiry)igraphmodule_Vertex_clear; if (PyType_Ready(&igraphmodule_VertexType) < 0) INITERROR; igraphmodule_EdgeType.tp_clear = (inquiry)igraphmodule_Edge_clear; if (PyType_Ready(&igraphmodule_EdgeType) < 0) INITERROR; /* Initialize Graph, BFSIter, ARPACKOptions etc */ if (PyType_Ready(&igraphmodule_GraphType) < 0) INITERROR; if (PyType_Ready(&igraphmodule_BFSIterType) < 0) INITERROR; if (PyType_Ready(&igraphmodule_ARPACKOptionsType) < 0) INITERROR; /* Initialize the core module */ #ifdef IGRAPH_PYTHON3 m = PyModule_Create(&moduledef); #else m = Py_InitModule3("igraph._igraph", igraphmodule_methods, MODULE_DOCS); #endif if (m == NULL) INITERROR; /* Initialize random number generator */ igraphmodule_init_rng(m); /* Add the types to the core module */ PyModule_AddObject(m, "GraphBase", (PyObject*)&igraphmodule_GraphType); PyModule_AddObject(m, "BFSIter", (PyObject*)&igraphmodule_BFSIterType); PyModule_AddObject(m, "ARPACKOptions", (PyObject*)&igraphmodule_ARPACKOptionsType); PyModule_AddObject(m, "Edge", (PyObject*)&igraphmodule_EdgeType); PyModule_AddObject(m, "EdgeSeq", (PyObject*)&igraphmodule_EdgeSeqType); PyModule_AddObject(m, "Vertex", (PyObject*)&igraphmodule_VertexType); PyModule_AddObject(m, "VertexSeq", (PyObject*)&igraphmodule_VertexSeqType); /* Internal error exception type */ igraphmodule_InternalError = PyErr_NewException("igraph._igraph.InternalError", PyExc_Exception, NULL); PyModule_AddObject(m, "InternalError", igraphmodule_InternalError); /* ARPACK default options variable */ igraphmodule_arpack_options_default = igraphmodule_ARPACKOptions_new(); PyModule_AddObject(m, "arpack_options", igraphmodule_arpack_options_default); /* Useful constants */ PyModule_AddIntConstant(m, "OUT", IGRAPH_OUT); PyModule_AddIntConstant(m, "IN", IGRAPH_IN); PyModule_AddIntConstant(m, "ALL", IGRAPH_ALL); PyModule_AddIntConstant(m, "STAR_OUT", IGRAPH_STAR_OUT); PyModule_AddIntConstant(m, "STAR_IN", IGRAPH_STAR_IN); PyModule_AddIntConstant(m, "STAR_MUTUAL", IGRAPH_STAR_MUTUAL); PyModule_AddIntConstant(m, "STAR_UNDIRECTED", IGRAPH_STAR_UNDIRECTED); PyModule_AddIntConstant(m, "TREE_OUT", IGRAPH_TREE_OUT); PyModule_AddIntConstant(m, "TREE_IN", IGRAPH_TREE_IN); PyModule_AddIntConstant(m, "TREE_UNDIRECTED", IGRAPH_TREE_UNDIRECTED); PyModule_AddIntConstant(m, "STRONG", IGRAPH_STRONG); PyModule_AddIntConstant(m, "WEAK", IGRAPH_WEAK); PyModule_AddIntConstant(m, "GET_ADJACENCY_UPPER", IGRAPH_GET_ADJACENCY_UPPER); PyModule_AddIntConstant(m, "GET_ADJACENCY_LOWER", IGRAPH_GET_ADJACENCY_LOWER); PyModule_AddIntConstant(m, "GET_ADJACENCY_BOTH", IGRAPH_GET_ADJACENCY_BOTH); PyModule_AddIntConstant(m, "REWIRING_SIMPLE", IGRAPH_REWIRING_SIMPLE); PyModule_AddIntConstant(m, "REWIRING_SIMPLE_LOOPS", IGRAPH_REWIRING_SIMPLE_LOOPS); PyModule_AddIntConstant(m, "ADJ_DIRECTED", IGRAPH_ADJ_DIRECTED); PyModule_AddIntConstant(m, "ADJ_UNDIRECTED", IGRAPH_ADJ_UNDIRECTED); PyModule_AddIntConstant(m, "ADJ_MAX", IGRAPH_ADJ_MAX); PyModule_AddIntConstant(m, "ADJ_MIN", IGRAPH_ADJ_MIN); PyModule_AddIntConstant(m, "ADJ_PLUS", IGRAPH_ADJ_PLUS); PyModule_AddIntConstant(m, "ADJ_UPPER", IGRAPH_ADJ_UPPER); PyModule_AddIntConstant(m, "ADJ_LOWER", IGRAPH_ADJ_LOWER); PyModule_AddIntConstant(m, "BLISS_F", IGRAPH_BLISS_F); PyModule_AddIntConstant(m, "BLISS_FL", IGRAPH_BLISS_FL); PyModule_AddIntConstant(m, "BLISS_FS", IGRAPH_BLISS_FS); PyModule_AddIntConstant(m, "BLISS_FM", IGRAPH_BLISS_FM); PyModule_AddIntConstant(m, "BLISS_FLM", IGRAPH_BLISS_FLM); PyModule_AddIntConstant(m, "BLISS_FSM", IGRAPH_BLISS_FSM); PyModule_AddIntConstant(m, "TRANSITIVITY_NAN", IGRAPH_TRANSITIVITY_NAN); PyModule_AddIntConstant(m, "TRANSITIVITY_ZERO", IGRAPH_TRANSITIVITY_ZERO); /* More useful constants */ { const char* version; igraph_version(&version, 0, 0, 0); PyModule_AddStringConstant(m, "__igraph_version__", version); } PyModule_AddStringConstant(m, "__build_date__", __DATE__); /* initialize error, progress, warning and interruption handler */ igraph_set_error_handler(igraphmodule_igraph_error_hook); igraph_set_progress_handler(igraphmodule_igraph_progress_hook); igraph_set_status_handler(igraphmodule_igraph_status_hook); igraph_set_warning_handler(igraphmodule_igraph_warning_hook); igraph_set_interruption_handler(igraphmodule_igraph_interrupt_hook); /* initialize attribute handlers */ igraphmodule_initialize_attribute_handler(); /* Initialize the C API pointer array */ PyIGraph_API[PyIGraph_FromCGraph_NUM] = (void *)PyIGraph_FromCGraph; PyIGraph_API[PyIGraph_ToCGraph_NUM] = (void *)PyIGraph_ToCGraph; /* Create a CObject containing the API pointer array's address */ #ifdef IGRAPH_PYTHON3 c_api_object = PyCapsule_New((void*)PyIGraph_API, "igraph._igraph._C_API", 0); #else c_api_object = PyCObject_FromVoidPtr((void*)PyIGraph_API, 0); #endif if (c_api_object != 0) { PyModule_AddObject(m, "_C_API", c_api_object); } igraphmodule_initialized = 1; #ifdef IGRAPH_PYTHON3 return m; #endif } python-igraph-0.8.0/src/_igraph/bfsiter.c0000644000076500000240000002057513104627150020552 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "bfsiter.h" #include "common.h" #include "error.h" #include "py2compat.h" #include "vertexobject.h" /** * \ingroup python_interface * \defgroup python_interface_bfsiter BFS iterator object */ PyTypeObject igraphmodule_BFSIterType; /** * \ingroup python_interface_bfsiter * \brief Allocate a new BFS iterator object for a given graph and a given root * \param g the graph object being referenced * \param vid the root vertex index * \param advanced whether the iterator should be advanced (returning distance and parent as well) * \return the allocated PyObject */ PyObject* igraphmodule_BFSIter_new(igraphmodule_GraphObject *g, PyObject *root, igraph_neimode_t mode, igraph_bool_t advanced) { igraphmodule_BFSIterObject* o; long int no_of_nodes, r; o=PyObject_GC_New(igraphmodule_BFSIterObject, &igraphmodule_BFSIterType); Py_INCREF(g); o->gref=g; o->graph=&g->g; if (!PyInt_Check(root) && !PyObject_IsInstance(root, (PyObject*)&igraphmodule_VertexType)) { PyErr_SetString(PyExc_TypeError, "root must be integer or igraph.Vertex"); return NULL; } no_of_nodes=igraph_vcount(&g->g); o->visited=(char*)calloc(no_of_nodes, sizeof(char)); if (o->visited == 0) { PyErr_SetString(PyExc_MemoryError, "out of memory"); return NULL; } if (igraph_dqueue_init(&o->queue, 100)) { PyErr_SetString(PyExc_MemoryError, "out of memory"); return NULL; } if (igraph_vector_init(&o->neis, 0)) { PyErr_SetString(PyExc_MemoryError, "out of memory"); igraph_dqueue_destroy(&o->queue); return NULL; } if (PyInt_Check(root)) { r=PyInt_AsLong(root); } else { r=((igraphmodule_VertexObject*)root)->idx; } if (igraph_dqueue_push(&o->queue, r) || igraph_dqueue_push(&o->queue, 0) || igraph_dqueue_push(&o->queue, -1)) { igraph_dqueue_destroy(&o->queue); igraph_vector_destroy(&o->neis); PyErr_SetString(PyExc_MemoryError, "out of memory"); return NULL; } o->visited[r]=1; if (!igraph_is_directed(&g->g)) mode=IGRAPH_ALL; o->mode=mode; o->advanced=advanced; PyObject_GC_Track(o); RC_ALLOC("BFSIter", o); return (PyObject*)o; } /** * \ingroup python_interface_bfsiter * \brief Support for cyclic garbage collection in Python * * This is necessary because the \c igraph.BFSIter object contains several * other \c PyObject pointers and they might point back to itself. */ int igraphmodule_BFSIter_traverse(igraphmodule_BFSIterObject *self, visitproc visit, void *arg) { int vret; RC_TRAVERSE("BFSIter", self); if (self->gref) { vret=visit((PyObject*)self->gref, arg); if (vret != 0) return vret; } return 0; } /** * \ingroup python_interface_bfsiter * \brief Clears the iterator's subobject (before deallocation) */ int igraphmodule_BFSIter_clear(igraphmodule_BFSIterObject *self) { PyObject *tmp; PyObject_GC_UnTrack(self); tmp=(PyObject*)self->gref; self->gref=NULL; Py_XDECREF(tmp); igraph_dqueue_destroy(&self->queue); igraph_vector_destroy(&self->neis); free(self->visited); self->visited=0; return 0; } /** * \ingroup python_interface_bfsiter * \brief Deallocates a Python representation of a given BFS iterator object */ void igraphmodule_BFSIter_dealloc(igraphmodule_BFSIterObject* self) { igraphmodule_BFSIter_clear(self); RC_DEALLOC("BFSIter", self); PyObject_GC_Del(self); } PyObject* igraphmodule_BFSIter_iter(igraphmodule_BFSIterObject* self) { Py_INCREF(self); return (PyObject*)self; } PyObject* igraphmodule_BFSIter_iternext(igraphmodule_BFSIterObject* self) { if (!igraph_dqueue_empty(&self->queue)) { igraph_integer_t vid = (igraph_integer_t)igraph_dqueue_pop(&self->queue); igraph_integer_t dist = (igraph_integer_t)igraph_dqueue_pop(&self->queue); igraph_integer_t parent = (igraph_integer_t)igraph_dqueue_pop(&self->queue); long int i; if (igraph_neighbors(self->graph, &self->neis, vid, self->mode)) { igraphmodule_handle_igraph_error(); return NULL; } for (i=0; ineis); i++) { igraph_integer_t neighbor = (igraph_integer_t)VECTOR(self->neis)[i]; if (self->visited[neighbor]==0) { self->visited[neighbor]=1; if (igraph_dqueue_push(&self->queue, neighbor) || igraph_dqueue_push(&self->queue, dist+1) || igraph_dqueue_push(&self->queue, vid)) { igraphmodule_handle_igraph_error(); return NULL; } } } if (self->advanced) { PyObject *vertexobj, *parentobj; vertexobj = igraphmodule_Vertex_New(self->gref, vid); if (!vertexobj) return NULL; if (parent >= 0) { parentobj = igraphmodule_Vertex_New(self->gref, parent); if (!parentobj) return NULL; } else { Py_INCREF(Py_None); parentobj=Py_None; } return Py_BuildValue("NlN", vertexobj, (long int)dist, parentobj); } else { return igraphmodule_Vertex_New(self->gref, vid); } } else { return NULL; } } /** * \ingroup python_interface_bfsiter * Method table for the \c igraph.BFSIter object */ PyMethodDef igraphmodule_BFSIter_methods[] = { {NULL} }; /** \ingroup python_interface_bfsiter * Python type object referencing the methods Python calls when it performs various operations on * a BFS iterator of a graph */ PyTypeObject igraphmodule_BFSIterType = { PyVarObject_HEAD_INIT(0, 0) "igraph.BFSIter", // tp_name sizeof(igraphmodule_BFSIterObject), // tp_basicsize 0, // tp_itemsize (destructor)igraphmodule_BFSIter_dealloc, // tp_dealloc 0, // tp_print 0, // tp_getattr 0, // tp_setattr 0, /* tp_compare (2.x) / tp_reserved (3.x) */ 0, // tp_repr 0, // tp_as_number 0, // tp_as_sequence 0, // tp_as_mapping 0, // tp_hash 0, // tp_call 0, // tp_str 0, // tp_getattro 0, // tp_setattro 0, // tp_as_buffer Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE | Py_TPFLAGS_HAVE_GC, // tp_flags "igraph BFS iterator object", // tp_doc (traverseproc) igraphmodule_BFSIter_traverse, /* tp_traverse */ (inquiry) igraphmodule_BFSIter_clear, /* tp_clear */ 0, // tp_richcompare 0, // tp_weaklistoffset (getiterfunc)igraphmodule_BFSIter_iter, /* tp_iter */ (iternextfunc)igraphmodule_BFSIter_iternext, /* tp_iternext */ 0, /* tp_methods */ 0, /* tp_members */ 0, /* tp_getset */ 0, /* tp_base */ 0, /* tp_dict */ 0, /* tp_descr_get */ 0, /* tp_descr_set */ 0, /* tp_dictoffset */ 0, /* tp_init */ 0, /* tp_alloc */ 0, /* tp_new */ 0, /* tp_free */ }; python-igraph-0.8.0/src/_igraph/convert.c0000644000076500000240000026145313576370547020620 0ustar tamasstaff00000000000000/* vim:set ts=2 sw=2 sts=2 et: */ /* IGraph library. Copyright (C) 2006-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ /************************ Miscellaneous functions *************************/ #include #include #include "attributes.h" #include "graphobject.h" #include "vertexseqobject.h" #include "vertexobject.h" #include "edgeseqobject.h" #include "edgeobject.h" #include "convert.h" #include "error.h" #include "memory.h" #include "py2compat.h" #if defined(_MSC_VER) #define strcasecmp _stricmp #endif /** * \brief Converts a Python integer to a C int * * This is similar to PyInt_AsLong, but it checks for overflow first and throws * an exception if necessary. * * Returns -1 if there was an error, 0 otherwise. */ int PyInt_AsInt(PyObject* obj, int* result) { long dummy = PyInt_AsLong(obj); if (dummy < INT_MIN) { PyErr_SetString(PyExc_OverflowError, "integer too small for conversion to C int"); return -1; } if (dummy > INT_MAX) { PyErr_SetString(PyExc_OverflowError, "integer too large for conversion to C int"); return -1; } *result = (int)dummy; return 0; } /** * \brief Converts a Python long to a C int * * This is similar to PyLong_AsLong, but it checks for overflow first and * throws an exception if necessary. * * Returns -1 if there was an error, 0 otherwise. */ int PyLong_AsInt(PyObject* obj, int* result) { long dummy = PyLong_AsLong(obj); if (dummy < INT_MIN) { PyErr_SetString(PyExc_OverflowError, "long integer too small for conversion to C int"); return -1; } if (dummy > INT_MAX) { PyErr_SetString(PyExc_OverflowError, "long integer too large for conversion to C int"); return -1; } *result = (int)dummy; return 0; } /** * \ingroup python_interface_conversion * \brief Converts a Python object to a corresponding igraph enum. * * The numeric value is returned as an integer that must be converted * explicitly to the corresponding igraph enum type. This is to allow one * to use the same common conversion routine for multiple enum types. * * \param o a Python object to be converted * \param translation the translation table between strings and the * enum values. Strings are treated as case-insensitive, but it is * assumed that the translation table keys are lowercase. The last * entry of the table must contain NULL values. * \param result the result is returned here. The default value must be * passed in before calling this function, since this value is * returned untouched if the given Python object is Py_None. * \return 0 if everything is OK, 1 otherwise. An appropriate exception * is raised in this case. */ int igraphmodule_PyObject_to_enum(PyObject *o, igraphmodule_enum_translation_table_entry_t* table, int *result) { char *s, *s2; int i, best, best_result, best_unique; if (o == 0 || o == Py_None) return 0; if (PyInt_Check(o)) return PyInt_AsInt(o, result); if (PyLong_Check(o)) return PyLong_AsInt(o, result); s = PyString_CopyAsString(o); if (s == 0) { PyErr_SetString(PyExc_TypeError, "int, long or string expected"); return -1; } /* Convert string to lowercase */ for (s2=s; *s2; s2++) *s2 = tolower(*s2); best = 0; best_unique = 0; best_result = -1; /* Search for matches */ while (table->name != 0) { if (strcmp(s, table->name) == 0) { *result = table->value; free(s); return 0; } for (i=0; s[i] == table->name[i]; i++); if (i > best) { best = i; best_unique = 1; best_result = table->value; } else if (i == best) best_unique = 0; table++; } free(s); if (best_unique) { *result = best_result; return 0; } PyErr_SetObject(PyExc_ValueError, o); return -1; } /** * \ingroup python_interface_conversion * \brief Converts a Python object to an igraph \c igraph_neimode_t */ int igraphmodule_PyObject_to_neimode_t(PyObject *o, igraph_neimode_t *result) { static igraphmodule_enum_translation_table_entry_t neimode_tt[] = { {"in", IGRAPH_IN}, {"out", IGRAPH_OUT}, {"all", IGRAPH_ALL}, {0,0} }; return igraphmodule_PyObject_to_enum(o, neimode_tt, (int*)result); } /** * \ingroup python_interface_conversion * \brief Converts a Python object to an igraph \c igraph_add_weights_t */ int igraphmodule_PyObject_to_add_weights_t(PyObject *o, igraph_add_weights_t *result) { static igraphmodule_enum_translation_table_entry_t add_weights_tt[] = { {"true", IGRAPH_ADD_WEIGHTS_YES}, {"yes", IGRAPH_ADD_WEIGHTS_YES}, {"false", IGRAPH_ADD_WEIGHTS_NO}, {"no", IGRAPH_ADD_WEIGHTS_NO}, {"auto", IGRAPH_ADD_WEIGHTS_IF_PRESENT}, {"if_present", IGRAPH_ADD_WEIGHTS_IF_PRESENT}, {0,0} }; if (o == Py_True) { *result = IGRAPH_ADD_WEIGHTS_YES; return 0; } if (o == Py_False) { *result = IGRAPH_ADD_WEIGHTS_NO; return 0; } return igraphmodule_PyObject_to_enum(o, add_weights_tt, (int*)result); } /** * \ingroup python_interface_conversion * \brief Converts a Python object to an igraph \c igraph_adjacency_t */ int igraphmodule_PyObject_to_adjacency_t(PyObject *o, igraph_adjacency_t *result) { static igraphmodule_enum_translation_table_entry_t adjacency_tt[] = { {"directed", IGRAPH_ADJ_DIRECTED}, {"undirected", IGRAPH_ADJ_UNDIRECTED}, {"upper", IGRAPH_ADJ_UPPER}, {"lower", IGRAPH_ADJ_LOWER}, {"minimum", IGRAPH_ADJ_MIN}, {"maximum", IGRAPH_ADJ_MAX}, {"plus", IGRAPH_ADJ_PLUS}, {0,0} }; return igraphmodule_PyObject_to_enum(o, adjacency_tt, (int*)result); } int igraphmodule_PyObject_to_attribute_combination_type_t(PyObject* o, igraph_attribute_combination_type_t *result) { static igraphmodule_enum_translation_table_entry_t attribute_combination_type_tt[] = { {"ignore", IGRAPH_ATTRIBUTE_COMBINE_IGNORE}, {"sum", IGRAPH_ATTRIBUTE_COMBINE_SUM}, {"product", IGRAPH_ATTRIBUTE_COMBINE_PROD}, {"min", IGRAPH_ATTRIBUTE_COMBINE_MIN}, {"max", IGRAPH_ATTRIBUTE_COMBINE_MAX}, {"random", IGRAPH_ATTRIBUTE_COMBINE_RANDOM}, {"first", IGRAPH_ATTRIBUTE_COMBINE_FIRST}, {"last", IGRAPH_ATTRIBUTE_COMBINE_LAST}, {"mean", IGRAPH_ATTRIBUTE_COMBINE_MEAN}, {"median", IGRAPH_ATTRIBUTE_COMBINE_MEDIAN}, {"concatenate", IGRAPH_ATTRIBUTE_COMBINE_CONCAT}, {0, 0} }; if (o == Py_None) { *result = IGRAPH_ATTRIBUTE_COMBINE_IGNORE; return 0; } if (PyCallable_Check(o)) { *result = IGRAPH_ATTRIBUTE_COMBINE_FUNCTION; return 0; } return igraphmodule_PyObject_to_enum(o, attribute_combination_type_tt, (int*)result); } int igraphmodule_PyObject_to_eigen_algorithm_t(PyObject *object, igraph_eigen_algorithm_t *a) { static igraphmodule_enum_translation_table_entry_t eigen_algorithm_tt[] = { {"auto", IGRAPH_EIGEN_AUTO}, {"lapack", IGRAPH_EIGEN_LAPACK}, {"arpack", IGRAPH_EIGEN_ARPACK}, {"comp_auto", IGRAPH_EIGEN_COMP_AUTO}, {"comp_lapack", IGRAPH_EIGEN_COMP_LAPACK}, {"comp_arpack", IGRAPH_EIGEN_COMP_ARPACK}, {0,0} }; if (object == Py_None) { *a = IGRAPH_EIGEN_ARPACK; return 0; } else { return igraphmodule_PyObject_to_enum(object, eigen_algorithm_tt, (int*)a); } } int igraphmodule_PyObject_to_eigen_which_t(PyObject *object, igraph_eigen_which_t *w) { PyObject *key, *value; Py_ssize_t pos = 0; static igraphmodule_enum_translation_table_entry_t eigen_which_position_tt[] = { { "LM", IGRAPH_EIGEN_LM}, { "SM", IGRAPH_EIGEN_SM}, { "LA", IGRAPH_EIGEN_LA}, { "SA", IGRAPH_EIGEN_SA}, { "BE", IGRAPH_EIGEN_BE}, { "LR", IGRAPH_EIGEN_LR}, { "SR", IGRAPH_EIGEN_SR}, { "LI", IGRAPH_EIGEN_LI}, { "SI", IGRAPH_EIGEN_SI}, { "ALL", IGRAPH_EIGEN_ALL}, { "INTERVAL", IGRAPH_EIGEN_INTERVAL}, { "SELECT", IGRAPH_EIGEN_SELECT} }; static igraphmodule_enum_translation_table_entry_t lapack_dgeevc_balance_tt[] = { { "none", IGRAPH_LAPACK_DGEEVX_BALANCE_NONE }, { "perm", IGRAPH_LAPACK_DGEEVX_BALANCE_PERM }, { "scale", IGRAPH_LAPACK_DGEEVX_BALANCE_SCALE }, { "both", IGRAPH_LAPACK_DGEEVX_BALANCE_BOTH } }; w->pos = IGRAPH_EIGEN_LM; w->howmany = 1; w->il = w->iu = -1; w->vl = IGRAPH_NEGINFINITY; w->vu = IGRAPH_INFINITY; w->vestimate = 0; w->balance = IGRAPH_LAPACK_DGEEVX_BALANCE_NONE; if (object != Py_None && !PyDict_Check(object)) { PyErr_SetString(PyExc_TypeError, "Python dictionary expected"); return -1; } if (object != Py_None) { while (PyDict_Next(object, &pos, &key, &value)) { char *kv; #ifdef IGRAPH_PYTHON3 PyObject *temp_bytes; if (!PyUnicode_Check(key)) { PyErr_SetString(PyExc_TypeError, "Dict key must be string"); return -1; } temp_bytes = PyUnicode_AsEncodedString(key, "ascii", "ignore"); if (temp_bytes == 0) { /* Exception set already by PyUnicode_AsEncodedString */ return -1; } kv = strdup(PyBytes_AS_STRING(temp_bytes)); Py_DECREF(temp_bytes); #else if (!PyString_Check(key)) { PyErr_SetString(PyExc_TypeError, "Dict key must be string"); return -1; } kv=PyString_AsString(key); #endif if (!strcasecmp(kv, "pos")) { igraphmodule_PyObject_to_enum(value, eigen_which_position_tt, (int*) &w->pos); } else if (!strcasecmp(kv, "howmany")) { w->howmany = (int) PyInt_AsLong(value); } else if (!strcasecmp(kv, "il")) { w->il = (int) PyInt_AsLong(value); } else if (!strcasecmp(kv, "iu")) { w->iu = (int) PyInt_AsLong(value); } else if (!strcasecmp(kv, "vl")) { w->vl = PyFloat_AsDouble(value); } else if (!strcasecmp(kv, "vu")) { w->vu = PyFloat_AsDouble(value); } else if (!strcasecmp(kv, "vestimate")) { w->vestimate = (int) PyInt_AsLong(value); } else if (!strcasecmp(kv, "balance")) { igraphmodule_PyObject_to_enum(value, lapack_dgeevc_balance_tt, (int*) &w->balance); } else { PyErr_SetString(PyExc_TypeError, "Unknown eigen parameter"); #ifdef IGRAPH_PYTHON3 if (kv != 0) { free(kv); } #endif return -1; } #ifdef IGRAPH_PYTHON3 if (kv != 0) { free(kv); } #endif } } return 0; } /** * \ingroup python_interface_conversion * \brief Converts a Python object to an igraph \c igraph_barabasi_algorithm_t */ int igraphmodule_PyObject_to_barabasi_algorithm_t(PyObject *o, igraph_barabasi_algorithm_t *result) { static igraphmodule_enum_translation_table_entry_t barabasi_algorithm_tt[] = { {"bag", IGRAPH_BARABASI_BAG}, {"psumtree", IGRAPH_BARABASI_PSUMTREE}, {"psumtree_multiple", IGRAPH_BARABASI_PSUMTREE_MULTIPLE}, {0,0} }; return igraphmodule_PyObject_to_enum(o, barabasi_algorithm_tt, (int*)result); } /** * \ingroup python_interface_conversion * \brief Converts a Python object to an igraph \c igraph_connectedness_t */ int igraphmodule_PyObject_to_connectedness_t(PyObject *o, igraph_connectedness_t *result) { static igraphmodule_enum_translation_table_entry_t connectedness_tt[] = { {"weak", IGRAPH_WEAK}, {"strong", IGRAPH_STRONG}, {0,0} }; return igraphmodule_PyObject_to_enum(o, connectedness_tt, (int*)result); } /** * \ingroup python_interface_conversion * \brief Converts a Python object to an igraph \c igraph_vconn_nei_t */ int igraphmodule_PyObject_to_vconn_nei_t(PyObject *o, igraph_vconn_nei_t *result) { static igraphmodule_enum_translation_table_entry_t vconn_nei_tt[] = { {"error", IGRAPH_VCONN_NEI_ERROR}, {"negative", IGRAPH_VCONN_NEI_NEGATIVE}, {"number_of_nodes", IGRAPH_VCONN_NEI_NUMBER_OF_NODES}, {"nodes", IGRAPH_VCONN_NEI_NUMBER_OF_NODES}, {"ignore", IGRAPH_VCONN_NEI_IGNORE}, {0,0} }; return igraphmodule_PyObject_to_enum(o, vconn_nei_tt, (int*)result); } /** * \ingroup python_interface_conversion * \brief Converts a Python object to an igraph \c igraph_bliss_sh_t */ int igraphmodule_PyObject_to_bliss_sh_t(PyObject *o, igraph_bliss_sh_t *result) { static igraphmodule_enum_translation_table_entry_t bliss_sh_tt[] = { {"f", IGRAPH_BLISS_F}, {"fl", IGRAPH_BLISS_FL}, {"fs", IGRAPH_BLISS_FS}, {"fm", IGRAPH_BLISS_FM}, {"flm", IGRAPH_BLISS_FLM}, {"fsm", IGRAPH_BLISS_FSM}, {0,0} }; return igraphmodule_PyObject_to_enum(o, bliss_sh_tt, (int*)result); } /** * \ingroup python_interface_conversion * \brief Converts a Python object to an igraph \c igraph_community_comparison_t */ int igraphmodule_PyObject_to_community_comparison_t(PyObject *o, igraph_community_comparison_t *result) { static igraphmodule_enum_translation_table_entry_t commcmp_tt[] = { {"vi", IGRAPH_COMMCMP_VI}, {"meila", IGRAPH_COMMCMP_VI}, {"nmi", IGRAPH_COMMCMP_NMI}, {"danon", IGRAPH_COMMCMP_NMI}, {"split-join", IGRAPH_COMMCMP_SPLIT_JOIN}, {"rand", IGRAPH_COMMCMP_RAND}, {"adjusted_rand", IGRAPH_COMMCMP_ADJUSTED_RAND}, {0,0} }; return igraphmodule_PyObject_to_enum(o, commcmp_tt, (int*)result); } /** * \ingroup python_interface_conversion * \brief Converts a Python object to an igraph \c igraph_degseq_t */ int igraphmodule_PyObject_to_degseq_t(PyObject *o, igraph_degseq_t *result) { static igraphmodule_enum_translation_table_entry_t degseq_tt[] = { {"simple", IGRAPH_DEGSEQ_SIMPLE}, {"no_multiple", IGRAPH_DEGSEQ_SIMPLE_NO_MULTIPLE}, {"vl", IGRAPH_DEGSEQ_VL}, {"viger-latapy", IGRAPH_DEGSEQ_VL}, {0,0} }; return igraphmodule_PyObject_to_enum(o, degseq_tt, (int*)result); } /** * \ingroup python_interface_conversion * \brief Converts a Python object to an igraph \c igraph_fas_algorithm_t */ int igraphmodule_PyObject_to_fas_algorithm_t(PyObject *o, igraph_fas_algorithm_t *result) { static igraphmodule_enum_translation_table_entry_t fas_algorithm_tt[] = { {"approx_eades", IGRAPH_FAS_APPROX_EADES}, {"eades", IGRAPH_FAS_APPROX_EADES}, {"exact", IGRAPH_FAS_EXACT_IP}, {"exact_ip", IGRAPH_FAS_EXACT_IP}, {"ip", IGRAPH_FAS_EXACT_IP}, {0,0} }; return igraphmodule_PyObject_to_enum(o, fas_algorithm_tt, (int*)result); } /** * \brief Converts a Python object to an igraph \c igraph_layout_grid_t */ int igraphmodule_PyObject_to_layout_grid_t(PyObject *o, igraph_layout_grid_t *result) { static igraphmodule_enum_translation_table_entry_t layout_grid_tt[] = { {"auto", IGRAPH_LAYOUT_AUTOGRID}, {"grid", IGRAPH_LAYOUT_GRID}, {"nogrid", IGRAPH_LAYOUT_NOGRID}, {0,0} }; if (o == Py_True) { *result = IGRAPH_LAYOUT_GRID; return 0; } else if (o == Py_False) { *result = IGRAPH_LAYOUT_NOGRID; return 0; } else { return igraphmodule_PyObject_to_enum(o, layout_grid_tt, (int*)result); } } /** * \ingroup python_interface_conversion * \brief Converts a Python object to an igraph \c igraph_random_walk_stuck_t */ int igraphmodule_PyObject_to_random_walk_stuck_t(PyObject *o, igraph_random_walk_stuck_t *result) { static igraphmodule_enum_translation_table_entry_t random_walk_stuck_tt[] = { {"return", IGRAPH_RANDOM_WALK_STUCK_RETURN}, {"error", IGRAPH_RANDOM_WALK_STUCK_ERROR}, {0,0} }; return igraphmodule_PyObject_to_enum(o, random_walk_stuck_tt, (int*)result); } /** * \brief Converts a Python object to an igraph \c igraph_reciprocity_t */ int igraphmodule_PyObject_to_reciprocity_t(PyObject *o, igraph_reciprocity_t *result) { static igraphmodule_enum_translation_table_entry_t reciprocity_tt[] = { {"default", IGRAPH_RECIPROCITY_DEFAULT}, {"ratio", IGRAPH_RECIPROCITY_RATIO}, {0,0} }; return igraphmodule_PyObject_to_enum(o, reciprocity_tt, (int*)result); } /** * \brief Converts a Python object to an igraph \c igraph_rewiring_t */ int igraphmodule_PyObject_to_rewiring_t(PyObject *o, igraph_rewiring_t *result) { static igraphmodule_enum_translation_table_entry_t rewiring_tt[] = { {"simple", IGRAPH_REWIRING_SIMPLE}, {"simple_loops", IGRAPH_REWIRING_SIMPLE_LOOPS}, {"loops", IGRAPH_REWIRING_SIMPLE_LOOPS}, {0,0} }; return igraphmodule_PyObject_to_enum(o, rewiring_tt, (int*)result); } /** * \brief Converts a Python object to an igraph \c igraph_spinglass_implementation_t */ int igraphmodule_PyObject_to_spinglass_implementation_t(PyObject *o, igraph_spinglass_implementation_t *result) { static igraphmodule_enum_translation_table_entry_t spinglass_implementation_tt[] = { {"original", IGRAPH_SPINCOMM_IMP_ORIG}, {"negative", IGRAPH_SPINCOMM_IMP_NEG}, {0,0} }; return igraphmodule_PyObject_to_enum(o, spinglass_implementation_tt, (int*)result); } /** * \brief Converts a Python object to an igraph \c igraph_spincomm_update_t */ int igraphmodule_PyObject_to_spincomm_update_t(PyObject *o, igraph_spincomm_update_t *result) { static igraphmodule_enum_translation_table_entry_t spincomm_update_tt[] = { {"simple", IGRAPH_SPINCOMM_UPDATE_SIMPLE}, {"config", IGRAPH_SPINCOMM_UPDATE_CONFIG}, {0,0} }; return igraphmodule_PyObject_to_enum(o, spincomm_update_tt, (int*)result); } /** * \ingroup python_interface_conversion * \brief Converts a Python object to an igraph \c igraph_star_mode_t */ int igraphmodule_PyObject_to_star_mode_t(PyObject *o, igraph_star_mode_t *result) { static igraphmodule_enum_translation_table_entry_t star_mode_tt[] = { {"in", IGRAPH_STAR_IN}, {"out", IGRAPH_STAR_OUT}, {"mutual", IGRAPH_STAR_MUTUAL}, {"undirected", IGRAPH_STAR_UNDIRECTED}, {0,0} }; return igraphmodule_PyObject_to_enum(o, star_mode_tt, (int*)result); } /** * \ingroup python_interface_conversion * \brief Converts a Python object to an igraph \c igraph_subgraph_implementation_t */ int igraphmodule_PyObject_to_subgraph_implementation_t(PyObject *o, igraph_subgraph_implementation_t *result) { static igraphmodule_enum_translation_table_entry_t subgraph_impl_tt[] = { {"auto", IGRAPH_SUBGRAPH_AUTO}, {"copy_and_delete", IGRAPH_SUBGRAPH_COPY_AND_DELETE}, {"old", IGRAPH_SUBGRAPH_COPY_AND_DELETE}, {"create_from_scratch", IGRAPH_SUBGRAPH_CREATE_FROM_SCRATCH}, {"new", IGRAPH_SUBGRAPH_CREATE_FROM_SCRATCH}, {0,0} }; return igraphmodule_PyObject_to_enum(o, subgraph_impl_tt, (int*)result); } /** * \ingroup python_interface_conversion * \brief Converts a Python object to an igraph \c igraph_to_undirected_t */ int igraphmodule_PyObject_to_to_undirected_t(PyObject *o, igraph_to_undirected_t *result) { static igraphmodule_enum_translation_table_entry_t to_undirected_tt[] = { {"each", IGRAPH_TO_UNDIRECTED_EACH}, {"collapse", IGRAPH_TO_UNDIRECTED_COLLAPSE}, {"mutual", IGRAPH_TO_UNDIRECTED_MUTUAL}, {0,0} }; if (o == Py_True) { *result = IGRAPH_TO_UNDIRECTED_COLLAPSE; return 0; } else if (o == Py_False) { *result = IGRAPH_TO_UNDIRECTED_EACH; return 0; } return igraphmodule_PyObject_to_enum(o, to_undirected_tt, (int*)result); } /** * \ingroup python_interface_conversion * \brief Converts a Python object to an \c igraph_transitivity_mode_t */ int igraphmodule_PyObject_to_transitivity_mode_t(PyObject *o, igraph_transitivity_mode_t *result) { static igraphmodule_enum_translation_table_entry_t transitivity_mode_tt[] = { {"zero", IGRAPH_TRANSITIVITY_ZERO}, {"0", IGRAPH_TRANSITIVITY_ZERO}, {"nan", IGRAPH_TRANSITIVITY_NAN}, {0,0} }; return igraphmodule_PyObject_to_enum(o, transitivity_mode_tt, (int*)result); } /** * \ingroup python_interface_conversion * \brief Converts a Python object to an igraph \c igraph_tree_mode_t */ int igraphmodule_PyObject_to_tree_mode_t(PyObject *o, igraph_tree_mode_t *result) { static igraphmodule_enum_translation_table_entry_t tree_mode_tt[] = { {"in", IGRAPH_TREE_IN}, {"out", IGRAPH_TREE_OUT}, {"all", IGRAPH_TREE_UNDIRECTED}, {"undirected", IGRAPH_TREE_UNDIRECTED}, {"tree_in", IGRAPH_TREE_IN}, {"tree_out", IGRAPH_TREE_OUT}, {"tree_all", IGRAPH_TREE_UNDIRECTED}, {0,0} }; return igraphmodule_PyObject_to_enum(o, tree_mode_tt, (int*)result); } /** * \brief Extracts a pointer to the internal \c igraph_t from a graph object * * Raises suitable Python exceptions when needed. * * \param object the Python object to be converted. If it is Py_None, the * result pointer is untouched (so it should be null by default). * \param result the pointer is stored here * * \return 0 if everything was OK, 1 otherwise */ int igraphmodule_PyObject_to_igraph_t(PyObject *o, igraph_t **result) { if (o == Py_None) return 0; if (!PyObject_TypeCheck(o, &igraphmodule_GraphType)) { PyErr_Format(PyExc_TypeError, "expected graph object, got %s", o->ob_type->tp_name); return 1; } *result = &((igraphmodule_GraphObject*)o)->g; return 0; } /** * \brief Converts a Python object to an igraph \c igraph_integer_t * * Raises suitable Python exceptions when needed. * * \param object the Python object to be converted * \param v the result is returned here * \return 0 if everything was OK, 1 otherwise */ int igraphmodule_PyObject_to_integer_t(PyObject *object, igraph_integer_t *v) { int retval, num; if (object == NULL) { } else if (PyLong_Check(object)) { retval = PyLong_AsInt(object, &num); if (retval) return retval; *v = num; return 0; #ifdef IGRAPH_PYTHON3 } else if (PyNumber_Check(object)) { PyObject *i = PyNumber_Int(object); if (i == NULL) return 1; retval = PyInt_AsInt(i, &num); Py_DECREF(i); if (retval) return retval; *v = num; return 0; } #else } else if (PyInt_Check(object)) { retval = PyInt_AsInt(object, &num); if (retval) return retval; *v = num; return 0; } else if (PyNumber_Check(object)) { PyObject *i = PyNumber_Int(object); if (i == NULL) return 1; retval = PyInt_AsInt(i, &num); Py_DECREF(i); if (retval) return retval; *v = num; return 0; } #endif PyErr_BadArgument(); return 1; } /** * \brief Converts a Python object to an igraph \c igraph_real_t * * Raises suitable Python exceptions when needed. * * \param object the Python object to be converted * \param v the result is returned here * \return 0 if everything was OK, 1 otherwise */ int igraphmodule_PyObject_to_real_t(PyObject *object, igraph_real_t *v) { #ifdef PYPY_VERSION /* PyFloatObject is not defined in pypy, but PyFloat_AS_DOUBLE() is * supported on PyObject: /pypy/module/cpyext/floatobject.py. Also, * don't worry, the typedef is local to this function. */ typedef PyObject PyFloatObject; #endif /* PYPY_VERSION */ if (object == NULL) { } else if (PyLong_Check(object)) { double d = PyLong_AsDouble(object); *v=(igraph_real_t)d; return 0; #ifndef IGRAPH_PYTHON3 } else if (PyInt_Check(object)) { long l = PyInt_AS_LONG((PyIntObject*)object); *v=(igraph_real_t)l; return 0; #endif } else if (PyFloat_Check(object)) { double d = PyFloat_AS_DOUBLE((PyFloatObject*)object); *v=(igraph_real_t)d; return 0; } else if (PyNumber_Check(object)) { PyObject *i = PyNumber_Float(object); double d; if (i == NULL) return 1; d = PyFloat_AS_DOUBLE((PyFloatObject*)i); Py_DECREF(i); *v = (igraph_real_t)d; return 0; } PyErr_BadArgument(); return 1; } /** * \ingroup python_interface_conversion * \brief Converts a Python object to an igraph \c igraph_vector_t * The incoming \c igraph_vector_t should be uninitialized. Raises suitable * Python exceptions when needed. * * \param list the Python list to be converted * \param v the \c igraph_vector_t containing the result * \param need_non_negative if true, checks whether all elements are non-negative * \return 0 if everything was OK, 1 otherwise */ int igraphmodule_PyObject_to_vector_t(PyObject *list, igraph_vector_t *v, igraph_bool_t need_non_negative) { PyObject *item, *it; Py_ssize_t size_hint; int ok; igraph_integer_t number; if (PyBaseString_Check(list)) { /* It is highly unlikely that a string (although it is a sequence) will * provide us with integers */ PyErr_SetString(PyExc_TypeError, "expected a sequence or an iterable containing integers"); return 1; } /* if the list is a sequence, we can pre-allocate the vector to its length */ if (PySequence_Check(list)) { size_hint = PySequence_Size(list); if (size_hint < 0) { /* should not happen but let's try to recover */ size_hint = 0; } } else { size_hint = 0; } /* initialize the result vector */ if (igraph_vector_init(v, 0)) { igraphmodule_handle_igraph_error(); return 1; } /* if we have a size hint, allocate the required space */ if (size_hint > 0) { if (igraph_vector_reserve(v, size_hint)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(v); return 1; } } /* try to use an iterator first */ it = PyObject_GetIter(list); if (it) { while ((item = PyIter_Next(it)) != 0) { ok = 1; if (igraphmodule_PyObject_to_integer_t(item, &number)) { PyErr_SetString(PyExc_ValueError, "iterable must yield integers"); ok=0; } else { if (need_non_negative && number < 0) { PyErr_SetString(PyExc_ValueError, "iterable must yield non-negative integers"); ok=0; } } Py_DECREF(item); if (!ok) { igraph_vector_destroy(v); Py_DECREF(it); return 1; } if (igraph_vector_push_back(v, number)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(v); Py_DECREF(it); return 1; } } Py_DECREF(it); } else { /* list is not iterable; maybe it's a single number? */ PyErr_Clear(); if (igraphmodule_PyObject_to_integer_t(list, &number)) { PyErr_SetString(PyExc_TypeError, "sequence or iterable expected"); igraph_vector_destroy(v); return 1; } else { if (need_non_negative && number < 0) { PyErr_SetString(PyExc_ValueError, "non-negative integers expected"); igraph_vector_destroy(v); return 1; } igraph_vector_push_back(v, number); } } return 0; } /** * \ingroup python_interface_conversion * \brief Converts a Python list of floats to an igraph \c igraph_vector_t * The incoming \c igraph_vector_t should be uninitialized. Raises suitable * Python exceptions when needed. * * \param list the Python list to be converted * \param v the \c igraph_vector_t containing the result * \return 0 if everything was OK, 1 otherwise */ int igraphmodule_PyObject_float_to_vector_t(PyObject *list, igraph_vector_t *v) { PyObject *item, *it; Py_ssize_t size_hint; int ok; igraph_real_t number; if (PyBaseString_Check(list)) { /* It is highly unlikely that a string (although it is a sequence) will * provide us with numbers */ PyErr_SetString(PyExc_TypeError, "expected a sequence or an iterable containing numbers"); return 1; } /* if the list is a sequence, we can pre-allocate the vector to its length */ if (PySequence_Check(list)) { size_hint = PySequence_Size(list); if (size_hint < 0) { /* should not happen but let's try to recover */ size_hint = 0; } } else { size_hint = 0; } /* initialize the result vector */ if (igraph_vector_init(v, 0)) { igraphmodule_handle_igraph_error(); return 1; } /* if we have a size hint, allocate the required space */ if (size_hint > 0) { if (igraph_vector_reserve(v, size_hint)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(v); return 1; } } /* try to use an iterator first */ it = PyObject_GetIter(list); if (it) { while ((item = PyIter_Next(it)) != 0) { ok = 1; if (igraphmodule_PyObject_to_real_t(item, &number)) { PyErr_SetString(PyExc_ValueError, "iterable must yield numbers"); ok=0; } Py_DECREF(item); if (!ok) { igraph_vector_destroy(v); Py_DECREF(it); return 1; } if (igraph_vector_push_back(v, number)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(v); Py_DECREF(it); return 1; } } Py_DECREF(it); } else { /* list is not iterable; maybe it's a single number? */ PyErr_Clear(); if (igraphmodule_PyObject_to_real_t(list, &number)) { PyErr_SetString(PyExc_TypeError, "sequence or iterable expected"); igraph_vector_destroy(v); return 1; } else { igraph_vector_push_back(v, number); } } return 0; } /** * \ingroup python_interface_conversion * \brief Converts a Python list of ints to an igraph \c igraph_vector_int_t * The incoming \c igraph_vector_int_t should be uninitialized. * Raises suitable Python exceptions when needed. * * This function is almost identical to * \ref igraphmodule_PyObject_to_vector_t . Make sure you fix bugs * in both cases (if any). * * \param list the Python list to be converted * \param v the \c igraph_vector_int_t containing the result * \return 0 if everything was OK, 1 otherwise */ int igraphmodule_PyObject_to_vector_int_t(PyObject *list, igraph_vector_int_t *v) { PyObject *item; int value=0; Py_ssize_t i, j, k; int ok, retval; if (PyBaseString_Check(list)) { /* It is highly unlikely that a string (although it is a sequence) will * provide us with integers or integer pairs */ PyErr_SetString(PyExc_TypeError, "expected a sequence or an iterable containing integers"); return 1; } if (!PySequence_Check(list)) { /* try to use an iterator */ PyObject *it = PyObject_GetIter(list); if (it) { PyObject *item; igraph_vector_int_init(v, 0); while ((item = PyIter_Next(it)) != 0) { ok = 1; if (!PyNumber_Check(item)) { PyErr_SetString(PyExc_TypeError, "iterable must return numbers"); ok=0; } else { PyObject *item2 = PyNumber_Int(item); if (item2 == 0) { PyErr_SetString(PyExc_TypeError, "can't convert a list item to integer"); ok = 0; } else { ok = (PyInt_AsInt(item, &value) == 0); Py_DECREF(item2); } } if (ok == 0) { igraph_vector_int_destroy(v); Py_DECREF(item); Py_DECREF(it); return 1; } if (igraph_vector_int_push_back(v, value)) { igraphmodule_handle_igraph_error(); igraph_vector_int_destroy(v); Py_DECREF(item); Py_DECREF(it); return 1; } Py_DECREF(item); } Py_DECREF(it); return 0; } else { PyErr_SetString(PyExc_TypeError, "sequence or iterable expected"); return 1; } return 0; } j=PySequence_Size(list); igraph_vector_int_init(v, j); for (i=0, k=0; i>=1; list=PyList_New(n); /* populate the list with data */ for (i=0, j=0; iitemsize != sizeof(igraph_real_t)) { PyErr_SetString( PyExc_TypeError, "item size of buffer must match the size of igraph_real_t" ); return 1; } if (buffer->ndim != 2) { PyErr_SetString(PyExc_TypeError, "edge list buffers must be two-dimensional"); return 1; } if (buffer->shape[1] != 2) { PyErr_SetString(PyExc_TypeError, "edge list buffers must have two columns"); return 1; } if (buffer->strides[0] != 2 * buffer->itemsize || buffer->strides[1] != buffer->itemsize) { PyErr_SetString(PyExc_TypeError, "edge list buffers must be contiguous"); return 1; } igraph_vector_view(v, buffer->buf, buffer->len / buffer->itemsize); if (list_is_owned) { *list_is_owned = 0; } return 0; } it = PyObject_GetIter(list); if (!it) return 1; igraph_vector_init(v, 0); if (list_is_owned) { *list_is_owned = 1; } while ((item = PyIter_Next(it)) != 0) { ok = 1; if (!PySequence_Check(item) || PySequence_Size(item) != 2) { PyErr_SetString(PyExc_TypeError, "iterable must return pairs of integers or strings"); ok=0; } else { i1 = PySequence_ITEM(item, 0); if (i1 == 0) { i2 = 0; } else { i2 = PySequence_ITEM(item, 1); } ok = (i1 != 0 && i2 != 0); ok = ok && !igraphmodule_PyObject_to_vid(i1, &idx1, graph); ok = ok && !igraphmodule_PyObject_to_vid(i2, &idx2, graph); Py_XDECREF(i1); Py_XDECREF(i2); /* PySequence_ITEM returned new ref */ } Py_DECREF(item); if (ok) { if (igraph_vector_push_back(v, idx1)) { igraphmodule_handle_igraph_error(); ok = 0; } if (ok && igraph_vector_push_back(v, idx2)) { igraphmodule_handle_igraph_error(); ok = 0; } } if (!ok) { igraph_vector_destroy(v); Py_DECREF(it); return 1; } } Py_DECREF(it); return 0; } /** * \ingroup python_interface_conversion * \brief Converts an attribute name or a sequence to a vector_t * * This function is useful for the interface of igraph C calls accepting * edge or vertex weights. The function checks the given Python object. If * it is None, returns a null pointer instead of an \c igraph_vector_t. * If it is a sequence, it converts the sequence to a newly allocated * \c igraph_vector_t and return a pointer to it. Otherwise it interprets the * object as an attribute name and returns the attribute values corresponding * to the name as an \c igraph_vector_t, or returns a null pointer if the attribute * does not exist. * * Note that if the function returned a pointer to an \c igraph_vector_t, * it is the caller's responsibility to destroy the object and free its * pointer after having finished using it. * * \param o the Python object being converted. * \param self a Python Graph object being used when attributes are queried * \param vptr the pointer to the allocated vector is returned here. * \param attr_type the type of the attribute being handled * \return 0 if everything was OK, nonzero otherwise. */ int igraphmodule_attrib_to_vector_t(PyObject *o, igraphmodule_GraphObject *self, igraph_vector_t **vptr, int attr_type) { igraph_vector_t *result; *vptr = 0; if (attr_type != ATTRIBUTE_TYPE_EDGE && attr_type != ATTRIBUTE_TYPE_VERTEX) return 1; if (o == Py_None) return 0; if (PyString_Check(o)) { /* Check whether the attribute exists and is numeric */ igraph_attribute_type_t at; igraph_attribute_elemtype_t et; long int n; char *name = PyString_CopyAsString(o); if (attr_type == ATTRIBUTE_TYPE_VERTEX) { et = IGRAPH_ATTRIBUTE_VERTEX; n = igraph_vcount(&self->g); } else { et = IGRAPH_ATTRIBUTE_EDGE; n = igraph_ecount(&self->g); } if (igraphmodule_i_attribute_get_type(&self->g, &at, et, name)) { /* exception was set by igraphmodule_i_attribute_get_type */ free(name); return 1; } if (at != IGRAPH_ATTRIBUTE_NUMERIC) { PyErr_SetString(PyExc_ValueError, "attribute values must be numeric"); free(name); return 1; } /* Now that the attribute type has been checked, allocate the target * vector */ result = (igraph_vector_t*)calloc(1, sizeof(igraph_vector_t)); if (result==0) { PyErr_NoMemory(); free(name); return 1; } igraph_vector_init(result, n); if (attr_type == ATTRIBUTE_TYPE_VERTEX) { if (igraphmodule_i_get_numeric_vertex_attr(&self->g, name, igraph_vss_all(), result)) { /* exception has already been set, so return */ igraph_vector_destroy(result); free(name); free(result); return 1; } } else { if (igraphmodule_i_get_numeric_edge_attr(&self->g, name, igraph_ess_all(IGRAPH_EDGEORDER_ID), result)) { /* exception has already been set, so return */ igraph_vector_destroy(result); free(name); free(result); return 1; } } free(name); *vptr = result; } else if (PySequence_Check(o)) { result = (igraph_vector_t*)calloc(1, sizeof(igraph_vector_t)); if (result==0) { PyErr_NoMemory(); return 1; } if (igraphmodule_PyObject_float_to_vector_t(o, result)) { igraph_vector_destroy(result); free(result); return 1; } *vptr = result; } else { PyErr_SetString(PyExc_TypeError, "unhandled type"); return 1; } return 0; } /** * \ingroup python_interface_conversion * \brief Converts an attribute name or a sequence to a vector_int_t * * Similar to igraphmodule_attrib_to_vector_t and * igraphmodule_attrib_to_vector_long_t. Make sure you fix bugs * in all three places (if any). * * Note that if the function returned a pointer to an \c igraph_vector_int_t, * it is the caller's responsibility to destroy the object and free its * pointer after having finished using it. * * \param o the Python object being converted. * \param self a Python Graph object being used when attributes are queried * \param vptr the pointer to the allocated vector is returned here. * \param attr_type the type of the attribute being handled * \return 0 if everything was OK, nonzero otherwise. */ int igraphmodule_attrib_to_vector_int_t(PyObject *o, igraphmodule_GraphObject *self, igraph_vector_int_t **vptr, int attr_type) { igraph_vector_int_t *result; *vptr = 0; if (attr_type != ATTRIBUTE_TYPE_EDGE && attr_type != ATTRIBUTE_TYPE_VERTEX) return 1; if (o == Py_None) return 0; if (PyString_Check(o)) { igraph_vector_t* dummy = 0; long int i, n; if (igraphmodule_attrib_to_vector_t(o, self, &dummy, attr_type)) return 1; if (dummy == 0) return 0; n = igraph_vector_size(dummy); result = (igraph_vector_int_t*)calloc(1, sizeof(igraph_vector_int_t)); igraph_vector_int_init(result, n); if (result==0) { igraph_vector_destroy(dummy); free(dummy); PyErr_NoMemory(); return 1; } for (i=0; ig); } else { et = IGRAPH_ATTRIBUTE_EDGE; n = igraph_ecount(&self->g); } if (igraphmodule_i_attribute_get_type(&self->g, &at, et, name)) { /* exception was set by igraphmodule_i_attribute_get_type */ free(name); return 1; } if (at == IGRAPH_ATTRIBUTE_BOOLEAN) { /* The attribute is a real Boolean attribute. Allocate the target * vector */ result = (igraph_vector_bool_t*)calloc(1, sizeof(igraph_vector_bool_t)); if (result==0) { PyErr_NoMemory(); free(name); return 1; } igraph_vector_bool_init(result, n); if (attr_type == ATTRIBUTE_TYPE_VERTEX) { if (igraphmodule_i_get_boolean_vertex_attr(&self->g, name, igraph_vss_all(), result)) { /* exception has already been set, so return */ igraph_vector_bool_destroy(result); free(name); free(result); return 1; } } else { if (igraphmodule_i_get_boolean_edge_attr(&self->g, name, igraph_ess_all(IGRAPH_EDGEORDER_ID), result)) { /* exception has already been set, so return */ igraph_vector_bool_destroy(result); free(name); free(result); return 1; } } free(name); *vptr = result; } else if (at == IGRAPH_ATTRIBUTE_NUMERIC) { /* The attribute is a numeric attribute, so we fall back to * attrib_to_vector_t and then convert the result */ igraph_vector_t *dummy = 0; free(name); if (igraphmodule_attrib_to_vector_t(o, self, &dummy, attr_type)) { return 1; } if (dummy == 0) { return 0; } n = igraph_vector_size(dummy); result = (igraph_vector_bool_t*)calloc(1, sizeof(igraph_vector_bool_t)); igraph_vector_bool_init(result, n); if (result==0) { igraph_vector_destroy(dummy); free(dummy); PyErr_NoMemory(); return 1; } for (i=0; inc) nc=n; } igraph_matrix_init(m, nr, nc); for (i=0; ig); Py_DECREF(t); } return 0; } /** * \ingroup python_interface_conversion * \brief Tries to interpret a Python object as a single vertex ID * * \param o the Python object * \param vid the vertex ID will be stored here * \param graph the graph that will be used to interpret vertex names * if a string was given in o. It may also be a null pointer * if we don't need name lookups. * \return 0 if everything was OK, 1 otherwise */ int igraphmodule_PyObject_to_vid(PyObject *o, igraph_integer_t *vid, igraph_t *graph) { int retval, tmp; if (o == Py_None || o == 0) { *vid = 0; } else if (PyInt_Check(o)) { /* Single vertex ID */ if (PyInt_AsInt(o, &tmp)) return 1; *vid = tmp; } else if (PyLong_Check(o)) { /* Single vertex ID */ if (PyLong_AsInt(o, &tmp)) return 1; *vid = tmp; } else if (graph != 0 && PyBaseString_Check(o)) { /* Single vertex ID from vertex name */ if (igraphmodule_get_vertex_id_by_name(graph, o, vid)) return 1; } else if (PyObject_IsInstance(o, (PyObject*)&igraphmodule_VertexType)) { /* Single vertex ID from Vertex object */ igraphmodule_VertexObject *vo = (igraphmodule_VertexObject*)o; *vid = igraphmodule_Vertex_get_index_igraph_integer(vo); } else if (PyIndex_Check(o)) { /* Other numeric type that can be converted to an index */ PyObject* num = PyNumber_Index(o); if (num) { if (PyInt_Check(num)) { retval = PyInt_AsInt(num, &tmp); if (retval) { Py_DECREF(num); return 1; } *vid = tmp; } else if (PyLong_Check(num)) { retval = PyLong_AsInt(num, &tmp); if (retval) { Py_DECREF(num); return 1; } *vid = tmp; } else { PyErr_SetString(PyExc_TypeError, "PyNumber_Index returned invalid type"); Py_DECREF(num); return 1; } Py_DECREF(num); } else return 1; } else { PyErr_SetString(PyExc_TypeError, "only numbers, strings or igraph.Vertex objects can be converted to vertex IDs"); return 1; } if (*vid < 0) { PyErr_Format(PyExc_ValueError, "vertex IDs must be positive, got: %ld", (long)(*vid)); return 1; } return 0; } /** * \ingroup python_interface_conversion * \brief Tries to interpret a Python object as a vertex selector * * \param o the Python object * \param vs the \c igraph_vs_t which will contain the result * \param graph an \c igraph_t object which will be used to interpret vertex * names (if the supplied Python object contains strings) * \param return_single will be 1 if the selector selected only a single vertex, * 0 otherwise * \param single_vid if the selector selected only a single vertex, the ID * of the selected vertex will also be returned here. * * \return 0 if everything was OK, 1 otherwise */ int igraphmodule_PyObject_to_vs_t(PyObject *o, igraph_vs_t *vs, igraph_t *graph, igraph_bool_t *return_single, igraph_integer_t *single_vid) { igraph_integer_t vid; igraph_vector_t vector; if (o == 0 || o == Py_None) { /* Returns a vertex sequence for all vertices */ if (return_single) *return_single = 0; igraph_vs_all(vs); return 0; } if (PyObject_IsInstance(o, (PyObject*)&igraphmodule_VertexSeqType)) { /* Returns a vertex sequence from a VertexSeq object */ igraphmodule_VertexSeqObject *vso = (igraphmodule_VertexSeqObject*)o; if (igraph_vs_copy(vs, &vso->vs)) { igraphmodule_handle_igraph_error(); return 1; } if (return_single) *return_single = 0; return 0; } if (PySlice_Check(o) && graph != 0) { /* Returns a vertex sequence from a slice */ Py_ssize_t no_of_vertices = igraph_vcount(graph); Py_ssize_t start, stop, step, slicelength, i; /* Casting to void* because Python 2.x expects PySliceObject* * but Python 3.x expects PyObject* */ if (PySlice_GetIndicesEx((void*)o, no_of_vertices, &start, &stop, &step, &slicelength)) return 1; if (start == 0 && slicelength == no_of_vertices) { igraph_vs_all(vs); } else { IGRAPH_CHECK(igraph_vector_init(&vector, slicelength)); IGRAPH_FINALLY(igraph_vector_destroy, &vector); for (i = 0; i < slicelength; i++, start += step) { VECTOR(vector)[i] = start; } IGRAPH_CHECK(igraph_vs_vector_copy(vs, &vector)); igraph_vector_destroy(&vector); IGRAPH_FINALLY_CLEAN(1); } if (return_single) *return_single = 0; return 0; } if (igraphmodule_PyObject_to_vid(o, &vid, graph)) { /* Object cannot be converted to a single vertex ID, * assume it is a sequence or iterable */ PyObject *iterator; PyObject *item; if (PyBaseString_Check(o)) { /* Special case: strings and unicode objects are sequences, but they * will not yield valid vertex IDs */ return 1; } /* Clear the exception set by igraphmodule_PyObject_to_vid */ PyErr_Clear(); iterator = PyObject_GetIter(o); if (iterator == NULL) { PyErr_SetString(PyExc_TypeError, "conversion to vertex sequence failed"); return 1; } IGRAPH_CHECK(igraph_vector_init(&vector, 0)); IGRAPH_FINALLY(igraph_vector_destroy, &vector); IGRAPH_CHECK(igraph_vector_reserve(&vector, 20)); while ((item = PyIter_Next(iterator))) { vid = -1; if (igraphmodule_PyObject_to_vid(item, &vid, graph)) break; Py_DECREF(item); igraph_vector_push_back(&vector, vid); } Py_DECREF(iterator); if (PyErr_Occurred()) { igraph_vector_destroy(&vector); IGRAPH_FINALLY_CLEAN(1); return 1; } IGRAPH_CHECK(igraph_vs_vector_copy(vs, &vector)); igraph_vector_destroy(&vector); IGRAPH_FINALLY_CLEAN(1); if (return_single) *return_single = 0; return 0; } /* The object can be converted into a single vertex ID */ if (return_single) *return_single = 1; if (single_vid) *single_vid = vid; igraph_vs_1(vs, vid); return 0; } /** * \ingroup python_interface_conversion * \brief Tries to interpret a Python object as a single edge ID * * \param o the Python object * \param eid the edge ID will be stored here * \param graph the graph that will be used to interpret vertex names and * indices if o is a tuple. It may also be a null pointer * if we don't want to handle tuples. * \return 0 if everything was OK, 1 otherwise */ int igraphmodule_PyObject_to_eid(PyObject *o, igraph_integer_t *eid, igraph_t *graph) { int retval, tmp; igraph_integer_t vid1, vid2; if (o == Py_None || o == 0) { *eid = 0; } else if (PyInt_Check(o)) { /* Single edge ID */ if (PyInt_AsInt(o, &tmp)) return 1; *eid = tmp; } else if (PyLong_Check(o)) { /* Single edge ID */ if (PyLong_AsInt(o, &tmp)) return 1; *eid = tmp; } else if (PyObject_IsInstance(o, (PyObject*)&igraphmodule_EdgeType)) { /* Single edge ID from Edge object */ igraphmodule_EdgeObject *eo = (igraphmodule_EdgeObject*)o; *eid = igraphmodule_Edge_get_index_igraph_integer(eo); } else if (PyIndex_Check(o)) { /* Other numeric type that can be converted to an index */ PyObject* num = PyNumber_Index(o); if (num) { if (PyInt_Check(num)) { retval = PyInt_AsInt(num, &tmp); if (retval) { Py_DECREF(num); return 1; } *eid = tmp; } else if (PyLong_Check(num)) { retval = PyLong_AsInt(num, &tmp); if (retval) { Py_DECREF(num); return 1; } *eid = tmp; } else { PyErr_SetString(PyExc_TypeError, "PyNumber_Index returned invalid type"); Py_DECREF(num); return 1; } Py_DECREF(num); } else return 1; } else if (graph != 0 && PyTuple_Check(o)) { PyObject *o1, *o2; o1 = PyTuple_GetItem(o, 0); if (!o1) return 1; o2 = PyTuple_GetItem(o, 1); if (!o2) return 1; if (igraphmodule_PyObject_to_vid(o1, &vid1, graph)) return 1; if (igraphmodule_PyObject_to_vid(o2, &vid2, graph)) return 1; igraph_get_eid(graph, eid, vid1, vid2, 1, 0); if (*eid < 0) { PyErr_Format(PyExc_ValueError, "no edge from vertex #%ld to #%ld", (long int)vid1, (long int)vid2); return 1; } } else { PyErr_SetString(PyExc_TypeError, "only numbers, igraph.Edge objects or tuples of vertex IDs can be " "converted to edge IDs"); return 1; } if (*eid < 0) { PyErr_Format(PyExc_ValueError, "edge IDs must be positive, got: %ld", (long)(*eid)); return 1; } return 0; } /** * \ingroup python_interface_conversion * \brief Tries to interpret a Python object as an edge selector * * \param o the Python object * \param vs the \c igraph_es_t which will contain the result * \param graph an \c igraph_t object which will be used to interpret vertex * names and tuples (if the supplied Python object contains them) * \param return_single will be 1 if the selector selected only a single edge, * 0 otherwise * \return 0 if everything was OK, 1 otherwise */ int igraphmodule_PyObject_to_es_t(PyObject *o, igraph_es_t *es, igraph_t *graph, igraph_bool_t *return_single) { igraph_integer_t eid; igraph_vector_t vector; if (o == 0 || o == Py_None) { /* Returns an edge sequence for all edges */ if (return_single) *return_single = 0; igraph_es_all(es, IGRAPH_EDGEORDER_ID); return 0; } if (PyObject_IsInstance(o, (PyObject*)&igraphmodule_EdgeSeqType)) { /* Returns an edge sequence from an EdgeSeq object */ igraphmodule_EdgeSeqObject *eso = (igraphmodule_EdgeSeqObject*)o; if (igraph_es_copy(es, &eso->es)) { igraphmodule_handle_igraph_error(); return 1; } if (return_single) *return_single = 0; return 0; } if (igraphmodule_PyObject_to_eid(o, &eid, graph)) { /* Object cannot be converted to a single edge ID, * assume it is a sequence or iterable */ PyObject *iterator; PyObject *item; /* Clear the exception set by igraphmodule_PyObject_to_eid */ PyErr_Clear(); iterator = PyObject_GetIter(o); if (iterator == NULL) { PyErr_SetString(PyExc_TypeError, "conversion to edge sequence failed"); return 1; } IGRAPH_CHECK(igraph_vector_init(&vector, 0)); IGRAPH_FINALLY(igraph_vector_destroy, &vector); IGRAPH_CHECK(igraph_vector_reserve(&vector, 20)); while ((item = PyIter_Next(iterator))) { eid = -1; if (igraphmodule_PyObject_to_eid(item, &eid, graph)) break; Py_DECREF(item); igraph_vector_push_back(&vector, eid); } Py_DECREF(iterator); if (PyErr_Occurred()) { igraph_vector_destroy(&vector); IGRAPH_FINALLY_CLEAN(1); return 1; } if (igraph_vector_size(&vector) > 0) { igraph_es_vector_copy(es, &vector); } else { igraph_es_none(es); } igraph_vector_destroy(&vector); IGRAPH_FINALLY_CLEAN(1); if (return_single) *return_single = 0; return 0; } /* The object can be converted into a single edge ID */ if (return_single) *return_single = 1; /* if (single_eid) *single_eid = eid; */ igraph_es_1(es, eid); return 0; } /** * \ingroup python_interface_conversion * \brief Tries to interpret a Python object as a numeric attribute value list * * \param o the Python object * \param v the \c igraph_vector_t which will contain the result * \param g a \c igraphmodule_GraphObject object or \c NULL - used when the * provided Python object is not a list and we're trying to interpret it as * an attribute name. * \param type the attribute type (graph = 0, vertex = 1, edge = 2) to be used * \param def default value if the attribute name supplied is \c None * if \c o is not a list. * \return 0 if everything was OK, 1 otherwise * * If the Python object is not a list, tries to interpret it as an attribute * name. */ int igraphmodule_PyObject_to_attribute_values(PyObject *o, igraph_vector_t *v, igraphmodule_GraphObject* g, int type, igraph_real_t def) { PyObject* list = o; long i, n; if (o==NULL) return 1; if (o == Py_None) { if (type == ATTRHASH_IDX_VERTEX) n=igraph_vcount(&g->g); else if (type == ATTRHASH_IDX_EDGE) n=igraph_ecount(&g->g); else n=1; if (igraph_vector_init(v, n)) return 1; for (i=0; ig.attr)[type], o); if (!list) { if (!PyErr_Occurred()) PyErr_SetString(PyExc_KeyError, "Attribute does not exist"); return 1; } } n=PyList_Size(list); if (igraph_vector_init(v, n)) return 1; for (i=0; iOPTION); \ Py_XDECREF(o1); \ } \ o1 = PyObject_GetAttrString(obj, #OPTION); \ igraphmodule_PyObject_to_##TYPE##_t(o1, &options->OPTION); \ Py_XDECREF(o1); \ } while (0) #define CONVERT_DRL_OPTION_BLOCK(NAME) do { \ CONVERT_DRL_OPTION(NAME##_iterations, integer); \ CONVERT_DRL_OPTION(NAME##_temperature, real); \ CONVERT_DRL_OPTION(NAME##_attraction, real); \ CONVERT_DRL_OPTION(NAME##_damping_mult, real); \ } while (0) if (!retval) { CONVERT_DRL_OPTION(edge_cut, real); CONVERT_DRL_OPTION_BLOCK(init); CONVERT_DRL_OPTION_BLOCK(liquid); CONVERT_DRL_OPTION_BLOCK(expansion); CONVERT_DRL_OPTION_BLOCK(cooldown); CONVERT_DRL_OPTION_BLOCK(crunch); CONVERT_DRL_OPTION_BLOCK(simmer); PyErr_Clear(); } #undef CONVERT_DRL_OPTION #undef CONVERT_DRL_OPTION_BLOCK } if (retval) { igraphmodule_handle_igraph_error(); return 1; } return 0; } int igraphmodule_i_PyObject_pair_to_attribute_combination_record_t( PyObject* name, PyObject* value, igraph_attribute_combination_record_t *result) { if (igraphmodule_PyObject_to_attribute_combination_type_t(value, &result->type)) return 1; if (result->type == IGRAPH_ATTRIBUTE_COMBINE_FUNCTION) { result->func = (void*) value; } else { result->func = 0; } if (name == Py_None) result->name = 0; else if (!PyString_Check(name)) { PyErr_SetString(PyExc_TypeError, "keys must be strings or None in attribute combination specification dicts"); return 1; } else { #ifdef IGRAPH_PYTHON3 result->name = PyString_CopyAsString(name); #else result->name = PyString_AS_STRING(name); #endif } return 0; } /** * \brief Converts a Python object to an \c igraph_attribute_combination_t * * Raises suitable Python exceptions when needed. * * An \c igraph_attribute_combination_t specifies how the attributes of multiple * vertices/edges should be combined when they are collapsed into a single vertex * or edge (e.g., when simplifying a graph). For each attribute, one can specify * a Python callable object to call or one of a list of recognised strings which * map to simple functions. The recognised strings are as follows: * * - \c "ignore" - the attribute will be ignored * - \c "sum" - the attribute values will be added * - \c "prod" - the product of the attribute values will be taken * - \c "min" - the minimum attribute value will be used * - \c "max" - the maximum attribute value will be used * - \c "random" - a random value will be selected * - \c "first" - the first value encountered will be selected * - \c "last" - the last value encountered will be selected * - \c "mean" - the mean of the attributes will be selected * - \c "median" - the median of the attributes will be selected * - \c "concat" - the attribute values will be concatenated * * The Python object being converted must either be a string, a callable or a dict. * If a string is given, it is considered as an \c igraph_attribute_combination_t * object that combines all attributes according to the function given by that * string. If a callable is given, it is considered as an * \c igraph_attribute_combination_t that combines all attributes by calling the * callable and taking its return value. If a dict is given, its key-value pairs * are iterated, the keys specify the attribute names (a key of None means all * explicitly not specified attributes), the values specify the functions to * call for those attributes. * * \param object the Python object to be converted * \param result the result is returned here. It must be an uninitialized * \c igraph_attribute_combination_t object, it will be initialized accordingly. * It is the responsibility of the caller to * \return 0 if everything was OK, 1 otherwise */ int igraphmodule_PyObject_to_attribute_combination_t(PyObject* object, igraph_attribute_combination_t *result) { igraph_attribute_combination_record_t rec; if (igraph_attribute_combination_init(result)) { igraphmodule_handle_igraph_error(); return 1; } if (object == Py_None) { return 0; } if (PyDict_Check(object)) { /* a full-fledged dict was passed */ PyObject *key, *value; Py_ssize_t pos = 0; while (PyDict_Next(object, &pos, &key, &value)) { if (igraphmodule_i_PyObject_pair_to_attribute_combination_record_t(key, value, &rec)) { igraph_attribute_combination_destroy(result); return 1; } igraph_attribute_combination_add(result, rec.name, rec.type, rec.func); #ifdef IGRAPH_PYTHON3 free((char*)rec.name); /* was allocated in pair_to_attribute_combination_record_t above */ #endif } } else { /* assume it is a string or callable */ if (igraphmodule_i_PyObject_pair_to_attribute_combination_record_t(Py_None, object, &rec)) { igraph_attribute_combination_destroy(result); return 1; } igraph_attribute_combination_add(result, 0, rec.type, rec.func); #ifdef IGRAPH_PYTHON3 free((char*)rec.name); /* was allocated in pair_to_attribute_combination_record_t above */ #endif } return 0; } /** * \ingroup python_interface_conversion * \brief Converts a Python object to an igraph \c igraph_pagerank_algo_t */ int igraphmodule_PyObject_to_pagerank_algo_t(PyObject *o, igraph_pagerank_algo_t *result) { static igraphmodule_enum_translation_table_entry_t pagerank_algo_tt[] = { {"prpack", IGRAPH_PAGERANK_ALGO_PRPACK}, {"arpack", IGRAPH_PAGERANK_ALGO_ARPACK}, {"power", IGRAPH_PAGERANK_ALGO_POWER}, {0,0} }; return igraphmodule_PyObject_to_enum(o, pagerank_algo_tt, (int*)result); } python-igraph-0.8.0/src/_igraph/vertexobject.c0000644000076500000240000007100113104627150021606 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim: set ts=2 sw=2 sts=2 et: */ /* IGraph library. Copyright (C) 2006-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "attributes.h" #include "convert.h" #include "edgeobject.h" #include "error.h" #include "graphobject.h" #include "pyhelpers.h" #include "vertexobject.h" /** * \ingroup python_interface * \defgroup python_interface_vertex Vertex object */ PyTypeObject igraphmodule_VertexType; /** * \ingroup python_interface_vertex * \brief Checks whether the given Python object is a vertex */ int igraphmodule_Vertex_Check(PyObject* obj) { if (!obj) return 0; return PyObject_IsInstance(obj, (PyObject*)(&igraphmodule_VertexType)); } /** * \ingroup python_interface_vertex * \brief Checks whether the index in the given vertex object is a valid one. * \return nonzero if the vertex object is valid. Raises an appropriate Python * exception and returns zero if the vertex object is invalid. */ int igraphmodule_Vertex_Validate(PyObject* obj) { igraph_integer_t n; igraphmodule_VertexObject *self; igraphmodule_GraphObject *graph; if (!igraphmodule_Vertex_Check(obj)) { PyErr_SetString(PyExc_TypeError, "object is not a Vertex"); return 0; } self = (igraphmodule_VertexObject*)obj; graph = self->gref; if (graph == 0) { PyErr_SetString(PyExc_ValueError, "Vertex object refers to a null graph"); return 0; } if (self->idx < 0) { PyErr_SetString(PyExc_ValueError, "Vertex object refers to a negative vertex index"); return 0; } n = igraph_vcount(&graph->g); if (self->idx >= n) { PyErr_SetString(PyExc_ValueError, "Vertex object refers to a nonexistent vertex"); return 0; } return 1; } /** * \ingroup python_interface_vertex * \brief Allocates a new Python vertex object * \param gref the \c igraph.Graph being referenced by the vertex * \param idx the index of the vertex * * \warning \c igraph references its vertices by indices, so if * you delete some vertices from the graph, the vertex indices will * change. Since the \c igraph.Vertex objects do not follow these * changes, your existing vertex objects will point to elsewhere * (or they might even get invalidated). */ PyObject* igraphmodule_Vertex_New(igraphmodule_GraphObject *gref, igraph_integer_t idx) { igraphmodule_VertexObject* self; self=PyObject_New(igraphmodule_VertexObject, &igraphmodule_VertexType); if (self) { RC_ALLOC("Vertex", self); Py_INCREF(gref); self->gref=gref; self->idx=idx; self->hash=-1; } return (PyObject*)self; } /** * \ingroup python_interface_vertex * \brief Clears the vertex's subobject (before deallocation) */ int igraphmodule_Vertex_clear(igraphmodule_VertexObject *self) { PyObject *tmp; tmp=(PyObject*)self->gref; self->gref=NULL; Py_XDECREF(tmp); return 0; } /** * \ingroup python_interface_vertex * \brief Deallocates a Python representation of a given vertex object */ void igraphmodule_Vertex_dealloc(igraphmodule_VertexObject* self) { igraphmodule_Vertex_clear(self); RC_DEALLOC("Vertex", self); PyObject_Del((PyObject*)self); } /** \ingroup python_interface_vertex * \brief Formats an \c igraph.Vertex object to a string * * \return the formatted textual representation as a \c PyObject */ PyObject* igraphmodule_Vertex_repr(igraphmodule_VertexObject *self) { PyObject *s; PyObject *attrs; #ifndef IGRAPH_PYTHON3 PyObject *grepr, *drepr; #endif attrs = igraphmodule_Vertex_attributes(self); if (attrs == 0) return NULL; #ifdef IGRAPH_PYTHON3 s = PyUnicode_FromFormat("igraph.Vertex(%R, %ld, %R)", (PyObject*)self->gref, (long int)self->idx, attrs); Py_DECREF(attrs); #else grepr=PyObject_Repr((PyObject*)self->gref); drepr=PyObject_Repr(igraphmodule_Vertex_attributes(self)); Py_DECREF(attrs); if (!grepr || !drepr) { Py_XDECREF(grepr); Py_XDECREF(drepr); return NULL; } s=PyString_FromFormat("igraph.Vertex(%s,%ld,%s)", PyString_AsString(grepr), (long int)self->idx, PyString_AsString(drepr)); Py_DECREF(grepr); Py_DECREF(drepr); #endif return s; } /** \ingroup python_interface_vertex * \brief Returns the hash code of the vertex */ Py_hash_t igraphmodule_Vertex_hash(igraphmodule_VertexObject* self) { Py_hash_t hash_graph; Py_hash_t hash_index; Py_hash_t result; PyObject* index_o; if (self->hash != -1) return self->hash; index_o = PyInt_FromLong((long int)self->idx); if (index_o == 0) return -1; hash_index = PyObject_Hash(index_o); Py_DECREF(index_o); if (hash_index == -1) return -1; /* Graph objects are unhashable from Python so we cannot call PyObject_Hash * directly. */ hash_graph = igraphmodule_Py_HashPointer(self->gref); if (hash_graph == -1) return -1; result = hash_graph ^ hash_index; if (result == -1) result = 590923713U; self->hash = result; return result; } /** \ingroup python_interface_vertex * \brief Rich comparison of a vertex with another */ PyObject* igraphmodule_Vertex_richcompare(igraphmodule_VertexObject *a, PyObject *b, int op) { igraphmodule_VertexObject* self = a; igraphmodule_VertexObject* other; if (!igraphmodule_Vertex_Check(b)) Py_RETURN_NOTIMPLEMENTED; other = (igraphmodule_VertexObject*)b; if (self->gref != other->gref) Py_RETURN_FALSE; switch (op) { case Py_EQ: Py_RETURN(self->idx == other->idx); case Py_NE: Py_RETURN(self->idx != other->idx); case Py_LE: Py_RETURN(self->idx <= other->idx); case Py_LT: Py_RETURN(self->idx < other->idx); case Py_GE: Py_RETURN(self->idx >= other->idx); case Py_GT: Py_RETURN(self->idx > other->idx); default: Py_RETURN_NOTIMPLEMENTED; } } /** \ingroup python_interface_vertex * \brief Returns the number of vertex attributes */ Py_ssize_t igraphmodule_Vertex_attribute_count(igraphmodule_VertexObject* self) { igraphmodule_GraphObject *o = self->gref; if (!o) return 0; if (!((PyObject**)o->g.attr)[1]) return 0; return PyDict_Size(((PyObject**)o->g.attr)[1]); } /** \ingroup python_interface_vertex * \brief Returns the list of attribute names */ PyObject* igraphmodule_Vertex_attribute_names(igraphmodule_VertexObject* self) { if (!self->gref) return NULL; return igraphmodule_Graph_vertex_attributes(self->gref); } /** \ingroup python_interface_vertex * \brief Returns a dict with attribue names and values */ PyObject* igraphmodule_Vertex_attributes(igraphmodule_VertexObject* self) { igraphmodule_GraphObject *o = self->gref; PyObject *names, *dict; long i, n; if (!igraphmodule_Vertex_Validate((PyObject*)self)) return 0; dict=PyDict_New(); if (!dict) return NULL; names=igraphmodule_Graph_vertex_attributes(o); if (!names) { Py_DECREF(dict); return NULL; } n=PyList_Size(names); for (i=0; ig.attr)[ATTRHASH_IDX_VERTEX], name); if (dictit) { PyObject *value = PyList_GetItem(dictit, self->idx); if (value) { /* No need to Py_INCREF, PyDict_SetItem will do that */ PyDict_SetItem(dict, name, value); } } } } Py_DECREF(names); return dict; } /** * \ingroup python_interface_vertex * \brief Updates some attributes of a vertex * * Incidentally, this method is re-used intact in edgeobject.c for edges. * * \param self the vertex object * \param args positional arguments * \param kwds keyword arguments */ PyObject* igraphmodule_Vertex_update_attributes(PyObject* self, PyObject* args, PyObject* kwds) { PyObject* items[] = { Py_None, kwds, 0 }; PyObject** pObj; PyObject *key, *value, *it, *item, *keys; igraph_bool_t ok = 1; if (!PyArg_ParseTuple(args, "|O", &items[0])) return NULL; pObj = items; for (pObj = items; ok && *pObj != 0; pObj++) { PyObject* obj = *pObj; PyObject* keys_func; if (obj == Py_None) continue; keys_func = PyObject_GetAttrString(obj, "keys"); if (keys_func == 0) PyErr_Clear(); if (keys_func != 0 && PyCallable_Check(keys_func)) { /* Object has a "keys" method, so we iterate over the keys */ keys = PyObject_CallObject(keys_func, 0); if (keys == 0) { ok = 0; } else { /* Iterate over the keys */ it = PyObject_GetIter(keys); if (it == 0) { ok = 0; } else { while (ok && ((key = PyIter_Next(it)) != 0)) { value = PyObject_GetItem(obj, key); if (value == 0) { ok = 0; } else { PyObject_SetItem((PyObject*)self, key, value); Py_DECREF(value); } Py_DECREF(key); } Py_DECREF(it); if (PyErr_Occurred()) ok = 0; } Py_DECREF(keys); } } else { /* Object does not have a "keys" method; assume that it * yields tuples when treated as an iterator */ it = PyObject_GetIter(obj); if (!it) { ok = 0; } else { while (ok && ((item = PyIter_Next(it)) != 0)) { if (!PySequence_Check(item) || PyBaseString_Check(item)) { PyErr_SetString(PyExc_TypeError, "cannot convert update sequence element to a sequence"); ok = 0; } else { key = PySequence_GetItem(item, 0); if (key == 0) { ok = 0; } else { value = PySequence_GetItem(item, 1); if (value == 0) { ok = 0; } else { PyObject_SetItem((PyObject*)self, key, value); Py_DECREF(value); } Py_DECREF(key); } } Py_DECREF(item); } Py_DECREF(it); if (PyErr_Occurred()) ok = 0; } } if (keys_func != 0) { Py_DECREF(keys_func); } } if (ok) Py_RETURN_NONE; return 0; } /** * \ingroup python_interface_vertex * \brief Returns the inbound and outbound edges of a vertex * * \param self the vertex object * \param args positional arguments * \param kwds keyword arguments */ PyObject* igraphmodule_Vertex_all_edges(PyObject* self) { return PyObject_CallMethod(self, "incident", "i", (int) IGRAPH_ALL); } /** * \ingroup python_interface_vertex * \brief Returns the inbound edges of a vertex * * \param self the vertex object * \param args positional arguments * \param kwds keyword arguments */ PyObject* igraphmodule_Vertex_in_edges(PyObject* self) { return PyObject_CallMethod(self, "incident", "i", (int) IGRAPH_IN); } /** * \ingroup python_interface_vertex * \brief Returns the outbound edges of a vertex * * \param self the vertex object * \param args positional arguments * \param kwds keyword arguments */ PyObject* igraphmodule_Vertex_out_edges(PyObject* self) { return PyObject_CallMethod(self, "incident", "i", (int) IGRAPH_OUT); } /** \ingroup python_interface_vertex * \brief Returns the corresponding value to a given attribute of the vertex * \param self the vertex object * \param s the attribute name to be queried */ PyObject* igraphmodule_Vertex_get_attribute(igraphmodule_VertexObject* self, PyObject* s) { igraphmodule_GraphObject *o = self->gref; PyObject* result; if (!igraphmodule_Vertex_Validate((PyObject*)self)) return 0; if (!igraphmodule_attribute_name_check(s)) return 0; result=PyDict_GetItem(((PyObject**)o->g.attr)[ATTRHASH_IDX_VERTEX], s); if (result) { /* result is a list, so get the element with index self->idx */ if (!PyList_Check(result)) { PyErr_SetString(igraphmodule_InternalError, "Vertex attribute dict member is not a list"); return NULL; } result=PyList_GetItem(result, self->idx); Py_INCREF(result); return result; } /* result is NULL, check whether there was an error */ if (!PyErr_Occurred()) PyErr_SetString(PyExc_KeyError, "Attribute does not exist"); return NULL; } /** \ingroup python_interface_vertex * \brief Sets the corresponding value of a given attribute of the vertex * \param self the vertex object * \param k the attribute name to be set * \param v the value to be set * \return 0 if everything's ok, -1 in case of error */ int igraphmodule_Vertex_set_attribute(igraphmodule_VertexObject* self, PyObject* k, PyObject* v) { igraphmodule_GraphObject *o=self->gref; PyObject* result; int r; if (!igraphmodule_Vertex_Validate((PyObject*)self)) return -1; if (!igraphmodule_attribute_name_check(k)) return -1; if (PyString_IsEqualToASCIIString(k, "name")) igraphmodule_invalidate_vertex_name_index(&o->g); if (v==NULL) // we are deleting attribute return PyDict_DelItem(((PyObject**)o->g.attr)[ATTRHASH_IDX_VERTEX], k); result=PyDict_GetItem(((PyObject**)o->g.attr)[ATTRHASH_IDX_VERTEX], k); if (result) { /* result is a list, so set the element with index self->idx */ if (!PyList_Check(result)) { PyErr_SetString(igraphmodule_InternalError, "Vertex attribute dict member is not a list"); return -1; } /* we actually don't own a reference here to v, so we must increase * its reference count, because PyList_SetItem will "steal" a reference! * It took me 1.5 hours between London and Manchester to figure it out */ Py_INCREF(v); r=PyList_SetItem(result, self->idx, v); if (r == -1) { Py_DECREF(v); } return r; } /* result is NULL, check whether there was an error */ if (!PyErr_Occurred()) { /* no, there wasn't, so we must simply add the attribute */ int n=(int)igraph_vcount(&o->g), i; result=PyList_New(n); for (i=0; iidx) { Py_INCREF(Py_None); if (PyList_SetItem(result, i, Py_None) == -1) { Py_DECREF(Py_None); Py_DECREF(result); return -1; } } else { /* Same game with the reference count here */ Py_INCREF(v); if (PyList_SetItem(result, i, v) == -1) { Py_DECREF(v); Py_DECREF(result); return -1; } } } if (PyDict_SetItem(((PyObject**)o->g.attr)[1], k, result) == -1) { Py_DECREF(result); return -1; } Py_DECREF(result); /* compensating for PyDict_SetItem */ return 0; } return -1; } /** * \ingroup python_interface_vertex * Returns the vertex index */ PyObject* igraphmodule_Vertex_get_index(igraphmodule_VertexObject* self, void* closure) { return PyInt_FromLong((long int)self->idx); } /** * \ingroup python_interface_vertex * Returns the vertex index as an igraph_integer_t */ igraph_integer_t igraphmodule_Vertex_get_index_igraph_integer(igraphmodule_VertexObject* self) { return self->idx; } /** * \ingroup python_interface_vertex * Returns the vertex index as an ordinary C long */ long igraphmodule_Vertex_get_index_long(igraphmodule_VertexObject* self) { return (long)self->idx; } /** * \ingroup python_interface_vertexseq * Returns the graph where the vertex belongs */ PyObject* igraphmodule_Vertex_get_graph(igraphmodule_VertexObject* self, void* closure) { Py_INCREF(self->gref); return (PyObject*)self->gref; } /**************************************************************************/ /* Implementing proxy method in Vertex that just forward the call to the * appropriate Graph method. * * These methods may also execute a postprocessing function on the result * of the Graph method; for instance, this mechanism is used to turn the * result of Graph.neighbors() (which is a list of vertex indices) into a * list of Vertex objects. */ /* Dummy postprocessing function that does nothing. */ static PyObject* _identity(igraphmodule_VertexObject* vertex, PyObject* obj) { Py_INCREF(obj); return obj; } /* Postprocessing function that converts a Python list of integers into a * list of edges in-place. */ static PyObject* _convert_to_edge_list(igraphmodule_VertexObject* vertex, PyObject* obj) { Py_ssize_t i, n; if (!PyList_Check(obj)) { PyErr_SetString(PyExc_TypeError, "_convert_to_edge_list expected list of integers"); return NULL; } n = PyList_Size(obj); for (i = 0; i < n; i++) { PyObject* idx = PyList_GET_ITEM(obj, i); PyObject* v; int idx_int; if (!PyInt_Check(idx)) { PyErr_SetString(PyExc_TypeError, "_convert_to_edge_list expected list of integers"); return NULL; } if (PyInt_AsInt(idx, &idx_int)) return NULL; v = igraphmodule_Edge_New(vertex->gref, idx_int); PyList_SetItem(obj, i, v); /* reference to v stolen, reference to idx discarded */ } Py_INCREF(obj); return obj; } /* Postprocessing function that converts a Python list of integers into a * list of vertices in-place. */ static PyObject* _convert_to_vertex_list(igraphmodule_VertexObject* vertex, PyObject* obj) { Py_ssize_t i, n; if (!PyList_Check(obj)) { PyErr_SetString(PyExc_TypeError, "_convert_to_vertex_list expected list of integers"); return NULL; } n = PyList_Size(obj); for (i = 0; i < n; i++) { PyObject* idx = PyList_GET_ITEM(obj, i); PyObject* v; int idx_int; if (!PyInt_Check(idx)) { PyErr_SetString(PyExc_TypeError, "_convert_to_vertex_list expected list of integers"); return NULL; } if (PyInt_AsInt(idx, &idx_int)) return NULL; v = igraphmodule_Vertex_New(vertex->gref, idx_int); PyList_SetItem(obj, i, v); /* reference to v stolen, reference to idx discarded */ } Py_INCREF(obj); return obj; } #define GRAPH_PROXY_METHOD_PP(FUNC, METHODNAME, POSTPROCESS) \ PyObject* igraphmodule_Vertex_##FUNC(igraphmodule_VertexObject* self, PyObject* args, PyObject* kwds) { \ PyObject *new_args, *item, *result; \ long int i, num_args = args ? PyTuple_Size(args)+1 : 1; \ \ /* Prepend ourselves to args */ \ new_args = PyTuple_New(num_args); \ Py_INCREF(self); PyTuple_SET_ITEM(new_args, 0, (PyObject*)self); \ for (i = 1; i < num_args; i++) { \ item = PyTuple_GET_ITEM(args, i-1); \ Py_INCREF(item); PyTuple_SET_ITEM(new_args, i, item); \ } \ \ /* Get the method instance */ \ item = PyObject_GetAttrString((PyObject*)(self->gref), METHODNAME); \ result = PyObject_Call(item, new_args, kwds); \ Py_DECREF(item); \ Py_DECREF(new_args); \ \ /* Optional postprocessing */ \ if (result) { \ PyObject* pp_result = POSTPROCESS(self, result); \ Py_DECREF(result); \ return pp_result; \ } \ return NULL; \ } #define GRAPH_PROXY_METHOD(FUNC, METHODNAME) \ GRAPH_PROXY_METHOD_PP(FUNC, METHODNAME, _identity) GRAPH_PROXY_METHOD(betweenness, "betweenness"); GRAPH_PROXY_METHOD(closeness, "closeness"); GRAPH_PROXY_METHOD(constraint, "constraint"); GRAPH_PROXY_METHOD(degree, "degree"); GRAPH_PROXY_METHOD(delete, "delete_vertices"); GRAPH_PROXY_METHOD(diversity, "diversity"); GRAPH_PROXY_METHOD(eccentricity, "eccentricity"); GRAPH_PROXY_METHOD(get_shortest_paths, "get_shortest_paths"); GRAPH_PROXY_METHOD_PP(incident, "incident", _convert_to_edge_list); GRAPH_PROXY_METHOD(indegree, "indegree"); GRAPH_PROXY_METHOD(is_minimal_separator, "is_minimal_separator"); GRAPH_PROXY_METHOD(is_separator, "is_separator"); GRAPH_PROXY_METHOD_PP(neighbors, "neighbors", _convert_to_vertex_list); GRAPH_PROXY_METHOD(outdegree, "outdegree"); GRAPH_PROXY_METHOD(pagerank, "pagerank"); GRAPH_PROXY_METHOD_PP(predecessors, "predecessors", _convert_to_vertex_list); GRAPH_PROXY_METHOD(personalized_pagerank, "personalized_pagerank"); GRAPH_PROXY_METHOD(shortest_paths, "shortest_paths"); GRAPH_PROXY_METHOD(strength, "strength"); GRAPH_PROXY_METHOD_PP(successors, "successors", _convert_to_vertex_list); #undef GRAPH_PROXY_METHOD #define GRAPH_PROXY_METHOD_SPEC(FUNC, METHODNAME) \ {METHODNAME, (PyCFunction)igraphmodule_Vertex_##FUNC, METH_VARARGS | METH_KEYWORDS, \ "Proxy method to L{Graph." METHODNAME "()}\n\n" \ "This method calls the " METHODNAME " method of the L{Graph} class " \ "with this vertex as the first argument, and returns the result.\n\n"\ "@see: Graph." METHODNAME "() for details."} #define GRAPH_PROXY_METHOD_SPEC_2(FUNC, METHODNAME, METHODNAME_IN_GRAPH) \ {METHODNAME, (PyCFunction)igraphmodule_Vertex_##FUNC, METH_VARARGS | METH_KEYWORDS, \ "Proxy method to L{Graph." METHODNAME_IN_GRAPH "()}\n\n" \ "This method calls the " METHODNAME_IN_GRAPH " method of the L{Graph} class " \ "with this vertex as the first argument, and returns the result.\n\n"\ "@see: Graph." METHODNAME_IN_GRAPH "() for details."} /** * \ingroup python_interface_vertex * Method table for the \c igraph.Vertex object */ PyMethodDef igraphmodule_Vertex_methods[] = { {"attributes", (PyCFunction)igraphmodule_Vertex_attributes, METH_NOARGS, "attributes() -> dict\n\n" "Returns a dict of attribute names and values for the vertex\n" }, {"attribute_names", (PyCFunction)igraphmodule_Vertex_attribute_names, METH_NOARGS, "attribute_names() -> list\n\n" "Returns the list of vertex attribute names\n" }, {"update_attributes", (PyCFunction)igraphmodule_Vertex_update_attributes, METH_VARARGS | METH_KEYWORDS, "update_attributes(E, **F) -> None\n\n" "Updates the attributes of the vertex from dict/iterable E and F.\n\n" "If E has a C{keys()} method, it does: C{for k in E: self[k] = E[k]}.\n" "If E lacks a C{keys()} method, it does: C{for (k, v) in E: self[k] = v}.\n" "In either case, this is followed by: C{for k in F: self[k] = F[k]}.\n\n" "This method thus behaves similarly to the C{update()} method of Python\n" "dictionaries." }, {"all_edges", (PyCFunction)igraphmodule_Vertex_all_edges, METH_NOARGS, "Proxy method to L{Graph.incident(..., mode=\"all\")}\n\n" \ "This method calls the incident() method of the L{Graph} class " \ "with this vertex as the first argument and \"all\" as the mode " \ "argument, and returns the result.\n\n"\ "@see: Graph.incident() for details."}, {"in_edges", (PyCFunction)igraphmodule_Vertex_in_edges, METH_NOARGS, "Proxy method to L{Graph.incident(..., mode=\"in\")}\n\n" \ "This method calls the incident() method of the L{Graph} class " \ "with this vertex as the first argument and \"in\" as the mode " \ "argument, and returns the result.\n\n"\ "@see: Graph.incident() for details."}, {"out_edges", (PyCFunction)igraphmodule_Vertex_out_edges, METH_NOARGS, "Proxy method to L{Graph.incident(..., mode=\"out\")}\n\n" \ "This method calls the incident() method of the L{Graph} class " \ "with this vertex as the first argument and \"out\" as the mode " \ "argument, and returns the result.\n\n"\ "@see: Graph.incident() for details."}, GRAPH_PROXY_METHOD_SPEC(betweenness, "betweenness"), GRAPH_PROXY_METHOD_SPEC(closeness, "closeness"), GRAPH_PROXY_METHOD_SPEC(constraint, "constraint"), GRAPH_PROXY_METHOD_SPEC(degree, "degree"), GRAPH_PROXY_METHOD_SPEC_2(delete, "delete", "delete_vertices"), GRAPH_PROXY_METHOD_SPEC(diversity, "diversity"), GRAPH_PROXY_METHOD_SPEC(eccentricity, "eccentricity"), GRAPH_PROXY_METHOD_SPEC(get_shortest_paths, "get_shortest_paths"), GRAPH_PROXY_METHOD_SPEC(incident, "incident"), GRAPH_PROXY_METHOD_SPEC(indegree, "indegree"), GRAPH_PROXY_METHOD_SPEC(is_minimal_separator, "is_minimal_separator"), GRAPH_PROXY_METHOD_SPEC(is_separator, "is_separator"), GRAPH_PROXY_METHOD_SPEC(neighbors, "neighbors"), GRAPH_PROXY_METHOD_SPEC(outdegree, "outdegree"), GRAPH_PROXY_METHOD_SPEC(pagerank, "pagerank"), GRAPH_PROXY_METHOD_SPEC(predecessors, "predecessors"), GRAPH_PROXY_METHOD_SPEC(personalized_pagerank, "personalized_pagerank"), GRAPH_PROXY_METHOD_SPEC(shortest_paths, "shortest_paths"), GRAPH_PROXY_METHOD_SPEC(strength, "strength"), GRAPH_PROXY_METHOD_SPEC(successors, "successors"), {NULL} }; #undef GRAPH_PROXY_METHOD_SPEC #undef GRAPH_PROXY_METHOD_SPEC_2 /** \ingroup python_interface_vertex * This structure is the collection of functions necessary to implement * the vertex as a mapping (i.e. to allow the retrieval and setting of * igraph attributes in Python as if it were of a Python mapping type) */ PyMappingMethods igraphmodule_Vertex_as_mapping = { // returns the number of vertex attributes (lenfunc)igraphmodule_Vertex_attribute_count, // returns an attribute by name (binaryfunc)igraphmodule_Vertex_get_attribute, // sets an attribute by name (objobjargproc)igraphmodule_Vertex_set_attribute }; /** * \ingroup python_interface_vertex * Getter/setter table for the \c igraph.Vertex object */ PyGetSetDef igraphmodule_Vertex_getseters[] = { {"index", (getter)igraphmodule_Vertex_get_index, NULL, "Index of the vertex", NULL }, {"graph", (getter)igraphmodule_Vertex_get_graph, NULL, "The graph the vertex belongs to", NULL }, {NULL} }; /** \ingroup python_interface_vertex * Python type object referencing the methods Python calls when it performs various operations on * a vertex of a graph */ PyTypeObject igraphmodule_VertexType = { PyVarObject_HEAD_INIT(0, 0) "igraph.Vertex", /* tp_name */ sizeof(igraphmodule_VertexObject), /* tp_basicsize */ 0, /* tp_itemsize */ (destructor)igraphmodule_Vertex_dealloc, /* tp_dealloc */ 0, /* tp_print */ 0, /* tp_getattr */ 0, /* tp_setattr */ 0, /* tp_compare (2.x) / tp_reserved (3.x) */ (reprfunc)igraphmodule_Vertex_repr, /* tp_repr */ 0, /* tp_as_number */ 0, /* tp_as_sequence */ &igraphmodule_Vertex_as_mapping, /* tp_as_mapping */ (hashfunc)igraphmodule_Vertex_hash, /* tp_hash */ 0, /* tp_call */ 0, /* tp_str */ 0, /* tp_getattro */ 0, /* tp_setattro */ 0, /* tp_as_buffer */ Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE, /* tp_flags */ "Class representing a single vertex in a graph.\n\n" "The vertex is referenced by its index, so if the underlying graph\n" "changes, the semantics of the vertex object might change as well\n" "(if the vertex indices are altered in the original graph).\n\n" "The attributes of the vertex can be accessed by using the vertex\n" "as a hash:\n\n" " >>> v[\"color\"] = \"red\" #doctest: +SKIP\n" " >>> print v[\"color\"] #doctest: +SKIP\n" " red\n", /* tp_doc */ 0, /* tp_traverse */ 0, /* tp_clear */ (richcmpfunc)igraphmodule_Vertex_richcompare, /* tp_richcompare */ 0, /* tp_weaklistoffset */ 0, /* tp_iter */ 0, /* tp_iternext */ igraphmodule_Vertex_methods, /* tp_methods */ 0, /* tp_members */ igraphmodule_Vertex_getseters, /* tp_getset */ }; python-igraph-0.8.0/src/_igraph/pyhelpers.h0000644000076500000240000000273413104627150021131 0ustar tamasstaff00000000000000/* vim:set ts=4 sw=2 sts=2 et: */ /* IGraph library - Python interface. Copyright (C) 2006-2011 Tamas Nepusz 5 Avenue Road, Staines, Middlesex, TW18 3AW, United Kingdom This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef PYTHON_HELPERS_H #define PYTHON_HELPERS_H #include PyObject* igraphmodule_PyList_NewFill(Py_ssize_t len, PyObject* item); PyObject* igraphmodule_PyList_Zeroes(Py_ssize_t len); char* igraphmodule_PyObject_ConvertToCString(PyObject* string); PyObject* igraphmodule_PyRange_create(Py_ssize_t start, Py_ssize_t stop, Py_ssize_t step); long igraphmodule_Py_HashPointer(void *p); #define PY_IGRAPH_DEPRECATED(msg) \ PyErr_WarnEx(PyExc_DeprecationWarning, (msg), 1) #define PY_IGRAPH_WARN(msg) \ PyErr_WarnEx(PyExc_RuntimeWarning, (msg), 1) #endif python-igraph-0.8.0/src/_igraph/random.c0000644000076500000240000001345413104627150020372 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=2 sw=2 sts=2 et: */ /* IGraph library. Copyright (C) 2006-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "py2compat.h" #include "random.h" #include #include /** * \ingroup python_interface_rng * \brief Internal data structure for storing references to the * functions used from Python's random number generator. */ typedef struct { PyObject* randint_func; PyObject* random_func; PyObject* gauss_func; } igraph_i_rng_Python_state_t; static igraph_i_rng_Python_state_t igraph_rng_Python_state = {0, 0, 0}; static igraph_rng_t igraph_rng_Python = {0, 0, 0}; int igraph_rng_Python_init(void **state) { IGRAPH_ERROR("Python RNG error, unsupported function called", IGRAPH_EINTERNAL); return 0; } void igraph_rng_Python_destroy(void *state) { igraph_error("Python RNG error, unsupported function called", __FILE__, __LINE__, IGRAPH_EINTERNAL); } /** * \ingroup python_interface_rng * \brief Sets the random number generator used by igraph. */ PyObject* igraph_rng_Python_set_generator(PyObject* self, PyObject* object) { igraph_i_rng_Python_state_t new_state, old_state; PyObject* func; if (object == Py_None) { /* Reverting to the default igraph random number generator instead * of the Python-based one */ igraph_rng_set_default(igraph_rng_default()); Py_RETURN_NONE; } #define GET_FUNC(name) {\ func = PyObject_GetAttrString(object, name); \ if (func == 0) \ return NULL; \ if (!PyCallable_Check(func)) {\ PyErr_SetString(PyExc_TypeError, name "attribute must be callable"); \ return NULL; \ } \ } GET_FUNC("randint"); new_state.randint_func = func; GET_FUNC("random"); new_state.random_func = func; GET_FUNC("gauss"); new_state.gauss_func = func; old_state = igraph_rng_Python_state; igraph_rng_Python_state = new_state; Py_XDECREF(old_state.randint_func); Py_XDECREF(old_state.random_func); Py_XDECREF(old_state.gauss_func); igraph_rng_set_default(&igraph_rng_Python); Py_RETURN_NONE; } /** * \ingroup python_interface_rng * \brief Sets the seed of the random generator. */ int igraph_rng_Python_seed(void *state, unsigned long int seed) { IGRAPH_ERROR("Python RNG error, unsupported function called", IGRAPH_EINTERNAL); return 0; } /** * \ingroup python_interface_rng * \brief Generates an unsigned long integer using the Python random number generator. */ unsigned long int igraph_rng_Python_get(void *state) { PyObject* result = PyObject_CallFunction(igraph_rng_Python_state.randint_func, "kk", 0, LONG_MAX); unsigned long int retval; if (result == 0) { PyErr_WriteUnraisable(PyErr_Occurred()); PyErr_Clear(); /* Fallback to the C random generator */ return rand() * LONG_MAX; } retval = PyInt_AsLong(result); Py_DECREF(result); return retval; } /** * \ingroup python_interface_rng * \brief Generates a real number between 0 and 1 using the Python random number generator. */ igraph_real_t igraph_rng_Python_get_real(void *state) { PyObject* result = PyObject_CallFunction(igraph_rng_Python_state.random_func, NULL); double retval; if (result == 0) { PyErr_WriteUnraisable(PyErr_Occurred()); PyErr_Clear(); /* Fallback to the C random generator */ return rand(); } retval = PyFloat_AsDouble(result); Py_DECREF(result); return retval; } /** * \ingroup python_interface_rng * \brief Generates a real number distributed according to the normal distribution * around zero with unit variance. */ igraph_real_t igraph_rng_Python_get_norm(void *state) { PyObject* result = PyObject_CallFunction(igraph_rng_Python_state.gauss_func, "dd", 0.0, 1.0); double retval; if (result == 0) { PyErr_WriteUnraisable(PyErr_Occurred()); PyErr_Clear(); /* Fallback to the C random generator */ return 0; } retval = PyFloat_AsDouble(result); Py_DECREF(result); return retval; } /** * \ingroup python_interface_rng * \brief Specification table for Python's random number generator. * This tells igraph which functions to call to obtain random numbers. */ igraph_rng_type_t igraph_rngtype_Python = { /* name= */ "Python random generator", /* min= */ 0, /* max= */ LONG_MAX, /* init= */ igraph_rng_Python_init, /* destroy= */ igraph_rng_Python_destroy, /* seed= */ igraph_rng_Python_seed, /* get= */ igraph_rng_Python_get, /* get_real */ igraph_rng_Python_get_real, /* get_norm= */ igraph_rng_Python_get_norm, /* get_geom= */ 0, /* get_binom= */ 0 }; void igraphmodule_init_rng(PyObject* igraph_module) { PyObject* random_module; if (igraph_rng_Python.state != 0) return; random_module = PyImport_ImportModule("random"); if (random_module == 0) { PyErr_WriteUnraisable(PyErr_Occurred()); PyErr_Clear(); return; } igraph_rng_Python.type = &igraph_rngtype_Python; igraph_rng_Python.state = &igraph_rng_Python_state; if (igraph_rng_Python_set_generator(igraph_module, random_module) == 0) { PyErr_WriteUnraisable(PyErr_Occurred()); PyErr_Clear(); return; } Py_DECREF(random_module); } python-igraph-0.8.0/src/_igraph/attributes.h0000644000076500000240000000743513104627150021307 0ustar tamasstaff00000000000000/* vim:set ts=2 sw=2 sts=2 et: */ /* IGraph library. Copyright (C) 2006-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef PY_IGRAPH_ATTRIBUTES_H #define PY_IGRAPH_ATTRIBUTES_H #include #include #include #include #include #include #define ATTRHASH_IDX_GRAPH 0 #define ATTRHASH_IDX_VERTEX 1 #define ATTRHASH_IDX_EDGE 2 typedef struct { PyObject* attrs[3]; PyObject* vertex_name_index; } igraphmodule_i_attribute_struct; #define ATTR_STRUCT(graph) ((igraphmodule_i_attribute_struct*)((graph)->attr)) #define ATTR_STRUCT_DICT(graph) ((igraphmodule_i_attribute_struct*)((graph)->attr))->attrs #define ATTR_NAME_INDEX(graph) ((igraphmodule_i_attribute_struct*)((graph)->attr))->vertex_name_index int igraphmodule_i_attribute_get_type(const igraph_t *graph, igraph_attribute_type_t *type, igraph_attribute_elemtype_t elemtype, const char *name); int igraphmodule_i_get_numeric_graph_attr(const igraph_t *graph, const char *name, igraph_vector_t *value); int igraphmodule_i_get_numeric_vertex_attr(const igraph_t *graph, const char *name, igraph_vs_t vs, igraph_vector_t *value); int igraphmodule_i_get_numeric_edge_attr(const igraph_t *graph, const char *name, igraph_es_t es, igraph_vector_t *value); int igraphmodule_i_get_string_graph_attr(const igraph_t *graph, const char *name, igraph_strvector_t *value); int igraphmodule_i_get_string_vertex_attr(const igraph_t *graph, const char *name, igraph_vs_t vs, igraph_strvector_t *value); int igraphmodule_i_get_string_edge_attr(const igraph_t *graph, const char *name, igraph_es_t es, igraph_strvector_t *value); int igraphmodule_i_get_boolean_graph_attr(const igraph_t *graph, const char *name, igraph_vector_bool_t *value); int igraphmodule_i_get_boolean_vertex_attr(const igraph_t *graph, const char *name, igraph_vs_t vs, igraph_vector_bool_t *value); int igraphmodule_i_get_boolean_edge_attr(const igraph_t *graph, const char *name, igraph_es_t es, igraph_vector_bool_t *value); int igraphmodule_attribute_name_check(PyObject* obj); void igraphmodule_initialize_attribute_handler(void); void igraphmodule_index_vertex_names(igraph_t *graph, igraph_bool_t force); void igraphmodule_invalidate_vertex_name_index(igraph_t *graph); int igraphmodule_get_vertex_id_by_name(igraph_t *graph, PyObject* o, igraph_integer_t* id); PyObject* igraphmodule_create_edge_attribute(const igraph_t* graph, const char* name); PyObject* igraphmodule_create_or_get_edge_attribute_values(const igraph_t* graph, const char* name); PyObject* igraphmodule_get_edge_attribute_values(const igraph_t* graph, const char* name); igraph_bool_t igraphmodule_has_graph_attribute(const igraph_t *graph, const char* name); igraph_bool_t igraphmodule_has_vertex_attribute(const igraph_t *graph, const char* name); igraph_bool_t igraphmodule_has_edge_attribute(const igraph_t *graph, const char* name); #endif python-igraph-0.8.0/src/_igraph/filehandle.h0000644000076500000240000000277413104627150021215 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef PYTHON_FILEHANDLE_H #define PYTHON_FILEHANDLE_H #include #include /** * \defgroup python_interface_filehandle File handle object */ /** * \ingroup python_interface_filehandle * \brief A structure encapsulating a Python object and a \c FILE* pointer * created out of it. */ typedef struct { PyObject* object; FILE* fp; unsigned short int need_close; } igraphmodule_filehandle_t; int igraphmodule_filehandle_init(igraphmodule_filehandle_t* handle, PyObject* object, char* mode); FILE* igraphmodule_filehandle_get(const igraphmodule_filehandle_t* handle); void igraphmodule_filehandle_destroy(igraphmodule_filehandle_t* handle); #endif python-igraph-0.8.0/src/_igraph/vertexseqobject.h0000644000076500000240000000371313104627150022331 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef PYTHON_VERTEXSEQOBJECT_H #define PYTHON_VERTEXSEQOBJECT_H #include #include "graphobject.h" /** * \ingroup python_interface_vertexseq * \brief A structure representing the vertex sequence of a graph */ typedef struct { PyObject_HEAD igraphmodule_GraphObject* gref; igraph_vs_t vs; PyObject* weakreflist; } igraphmodule_VertexSeqObject; PyObject* igraphmodule_VertexSeq_new(PyTypeObject *subtype, PyObject* args, PyObject* kwds); int igraphmodule_VertexSeq_init(igraphmodule_VertexSeqObject* self, PyObject* args, PyObject* kwds); void igraphmodule_VertexSeq_dealloc(igraphmodule_VertexSeqObject* self); int igraphmodule_VertexSeq_sq_length(igraphmodule_VertexSeqObject *self); PyObject* igraphmodule_VertexSeq_find(igraphmodule_VertexSeqObject *self, PyObject *args); PyObject* igraphmodule_VertexSeq_select(igraphmodule_VertexSeqObject *self, PyObject *args); int igraphmodule_VertexSeq_to_vector_t(igraphmodule_VertexSeqObject *self, igraph_vector_t *v); PyObject* igraphmodule_VertexSeq_get_graph(igraphmodule_VertexSeqObject *self, void* closure); extern PyTypeObject igraphmodule_VertexSeqType; #endif python-igraph-0.8.0/src/_igraph/arpackobject.h0000644000076500000240000000353713104627150021550 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef PYTHON_ARPACKOBJECT_H #define PYTHON_ARPACKOBJECT_H #include #include #include "graphobject.h" /** * \ingroup python_interface * \defgroup python_interface_arpack ARPACK parameters object */ extern PyTypeObject igraphmodule_ARPACKOptionsType; /** * \ingroup python_interface_arpack * \brief A structure representing ARPACK parameters */ typedef struct { PyObject_HEAD igraph_arpack_options_t params; igraph_arpack_options_t params_out; } igraphmodule_ARPACKOptionsObject; extern PyObject* igraphmodule_arpack_options_default; void igraphmodule_ARPACKOptions_dealloc(igraphmodule_ARPACKOptionsObject* self); PyObject* igraphmodule_ARPACKOptions_new(void); PyObject* igraphmodule_ARPACKOptions_str(igraphmodule_ARPACKOptionsObject *self); #define igraphmodule_ARPACKOptions_CheckExact(ob) ((ob)->ob_type == &igraphmodule_ARPACKOptionsType) igraph_arpack_options_t *igraphmodule_ARPACKOptions_get(igraphmodule_ARPACKOptionsObject *self); int igraphmodule_ARPACKOptions_Check(PyObject *ob); #endif python-igraph-0.8.0/src/_igraph/edgeseqobject.c0000644000076500000240000007622313104627150021721 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim: set ts=2 sts=2 sw=2 et: */ /* IGraph library. Copyright (C) 2006-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "attributes.h" #include "common.h" #include "convert.h" #include "edgeseqobject.h" #include "edgeobject.h" #include "error.h" #include "py2compat.h" #include "pyhelpers.h" #define GET_GRAPH(obj) (((igraphmodule_GraphObject*)obj->gref)->g) /** * \ingroup python_interface * \defgroup python_interface_edgeseq Edge sequence object */ PyTypeObject igraphmodule_EdgeSeqType; /** * \ingroup python_interface_edgeseq * \brief Allocate a new edge sequence object for a given graph * \param g the graph object being referenced * \return the allocated PyObject */ PyObject* igraphmodule_EdgeSeq_new(PyTypeObject *subtype, PyObject *args, PyObject *kwds) { igraphmodule_EdgeSeqObject* o; o=(igraphmodule_EdgeSeqObject*)PyType_GenericNew(subtype, args, kwds); if (o == NULL) return NULL; igraph_es_all(&o->es, IGRAPH_EDGEORDER_ID); o->gref=0; o->weakreflist=0; RC_ALLOC("EdgeSeq", o); return (PyObject*)o; } /** * \ingroup python_interface_edgeseq * \brief Copies an edge sequence object * \return the copied PyObject */ igraphmodule_EdgeSeqObject* igraphmodule_EdgeSeq_copy(igraphmodule_EdgeSeqObject* o) { igraphmodule_EdgeSeqObject *copy; copy=(igraphmodule_EdgeSeqObject*)PyType_GenericNew(Py_TYPE(o), 0, 0); if (copy == NULL) return NULL; if (igraph_es_type(&o->es) == IGRAPH_ES_VECTOR) { igraph_vector_t v; if (igraph_vector_copy(&v, o->es.data.vecptr)) { igraphmodule_handle_igraph_error(); return 0; } if (igraph_es_vector_copy(©->es, &v)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&v); return 0; } igraph_vector_destroy(&v); } else { copy->es = o->es; } copy->gref = o->gref; if (o->gref) Py_INCREF(o->gref); RC_ALLOC("EdgeSeq(copy)", copy); return copy; } /** * \ingroup python_interface_edgeseq * \brief Initialize a new edge sequence object for a given graph * \return the initialized PyObject */ int igraphmodule_EdgeSeq_init(igraphmodule_EdgeSeqObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = { "graph", "edges", NULL }; PyObject *g, *esobj=Py_None; igraph_es_t es; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O!|O", kwlist, &igraphmodule_GraphType, &g, &esobj)) return -1; if (esobj == Py_None) { /* If es is None, we are selecting all the edges */ igraph_es_all(&es, IGRAPH_EDGEORDER_ID); } else if (PyInt_Check(esobj)) { /* We selected a single edge */ long int idx = PyInt_AsLong(esobj); if (idx < 0 || idx >= igraph_ecount(&((igraphmodule_GraphObject*)g)->g)) { PyErr_SetString(PyExc_ValueError, "edge index out of range"); return -1; } igraph_es_1(&es, (igraph_integer_t)idx); } else { /* We selected multiple edges */ igraph_vector_t v; igraph_integer_t n = igraph_ecount(&((igraphmodule_GraphObject*)g)->g); if (igraphmodule_PyObject_to_vector_t(esobj, &v, 1)) return -1; if (!igraph_vector_isininterval(&v, 0, n-1)) { igraph_vector_destroy(&v); PyErr_SetString(PyExc_ValueError, "edge index out of range"); return -1; } if (igraph_es_vector_copy(&es, &v)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&v); return -1; } igraph_vector_destroy(&v); } self->es = es; Py_INCREF(g); self->gref = (igraphmodule_GraphObject*)g; return 0; } /** * \ingroup python_interface_edgeseq * \brief Deallocates a Python representation of a given edge sequence object */ void igraphmodule_EdgeSeq_dealloc(igraphmodule_EdgeSeqObject* self) { if (self->weakreflist != NULL) PyObject_ClearWeakRefs((PyObject *)self); if (self->gref) { igraph_es_destroy(&self->es); Py_DECREF(self->gref); self->gref=0; } Py_TYPE(self)->tp_free((PyObject*)self); RC_DEALLOC("EdgeSeq", self); } /** * \ingroup python_interface_edgeseq * \brief Returns the length of the sequence (i.e. the number of edges in the graph) */ int igraphmodule_EdgeSeq_sq_length(igraphmodule_EdgeSeqObject* self) { igraph_t *g; igraph_integer_t result; g=&GET_GRAPH(self); if (igraph_es_size(g, &self->es, &result)) { igraphmodule_handle_igraph_error(); return -1; } return (int)result; } /** * \ingroup python_interface_edgeseq * \brief Returns the item at the given index in the sequence */ PyObject* igraphmodule_EdgeSeq_sq_item(igraphmodule_EdgeSeqObject* self, Py_ssize_t i) { igraph_t *g; igraph_integer_t idx = -1; if (!self->gref) return NULL; g=&GET_GRAPH(self); switch (igraph_es_type(&self->es)) { case IGRAPH_ES_ALL: if (i < 0) { i = igraph_ecount(g) + i; } if (i >= 0 && i < igraph_ecount(g)) { idx = (igraph_integer_t)i; } break; case IGRAPH_ES_VECTOR: case IGRAPH_ES_VECTORPTR: if (i < 0) { i = igraph_vector_size(self->es.data.vecptr) + i; } if (i >= 0 && i < igraph_vector_size(self->es.data.vecptr)) { idx = (igraph_integer_t)VECTOR(*self->es.data.vecptr)[i]; } break; case IGRAPH_ES_1: if (i == 0 || i == -1) { idx = self->es.data.eid; } break; case IGRAPH_ES_SEQ: if (i < 0) { i = self->es.data.seq.to - self->es.data.seq.from + i; } if (i >= 0 && i < self->es.data.seq.to - self->es.data.seq.from) { idx = self->es.data.seq.from + (igraph_integer_t)i; } break; /* TODO: IGRAPH_ES_PAIRS, IGRAPH_ES_ADJ, IGRAPH_ES_PATH, IGRAPH_ES_MULTIPATH - someday :) They are unused yet in the Python interface */ } if (idx < 0) { PyErr_SetString(PyExc_IndexError, "edge index out of range"); return NULL; } return igraphmodule_Edge_New(self->gref, idx); } /** \ingroup python_interface_edgeseq * \brief Returns the list of attribute names */ PyObject* igraphmodule_EdgeSeq_attribute_names(igraphmodule_EdgeSeqObject* self) { return igraphmodule_Graph_edge_attributes(self->gref); } /** \ingroup python_interface_edgeseq * \brief Returns the list of values for a given attribute */ PyObject* igraphmodule_EdgeSeq_get_attribute_values(igraphmodule_EdgeSeqObject* self, PyObject* o) { igraphmodule_GraphObject *gr = self->gref; PyObject *result=0, *values, *item; long int i, n; if (!igraphmodule_attribute_name_check(o)) return 0; PyErr_Clear(); values=PyDict_GetItem(ATTR_STRUCT_DICT(&gr->g)[ATTRHASH_IDX_EDGE], o); if (!values) { PyErr_SetString(PyExc_KeyError, "Attribute does not exist"); return NULL; } else if (PyErr_Occurred()) return NULL; switch (igraph_es_type(&self->es)) { case IGRAPH_ES_NONE: n = 0; result = PyList_New(0); break; case IGRAPH_ES_ALL: n = PyList_Size(values); result = PyList_New(n); if (!result) return 0; for (i=0; ies.data.vecptr); result = PyList_New(n); if (!result) return 0; for (i=0; ies.data.vecptr)[i]); Py_INCREF(item); PyList_SET_ITEM(result, i, item); } break; case IGRAPH_ES_SEQ: n = self->es.data.seq.to - self->es.data.seq.from; result = PyList_New(n); if (!result) return 0; for (i=0; ies.data.seq.from+i); Py_INCREF(item); PyList_SET_ITEM(result, i, item); } break; default: PyErr_SetString(PyExc_RuntimeError, "invalid edge selector"); } return result; } PyObject* igraphmodule_EdgeSeq_is_all(igraphmodule_EdgeSeqObject* self) { if (igraph_es_is_all(&self->es)) Py_RETURN_TRUE; Py_RETURN_FALSE; } PyObject* igraphmodule_EdgeSeq_get_attribute_values_mapping(igraphmodule_EdgeSeqObject *self, PyObject *o) { Py_ssize_t index; /* Handle integer indices according to the sequence protocol */ if (PyIndex_Check(o)) { index = PyNumber_AsSsize_t(o, 0); return igraphmodule_EdgeSeq_sq_item(self, index); } /* Handle strings according to the mapping protocol */ if (PyBaseString_Check(o)) return igraphmodule_EdgeSeq_get_attribute_values(self, o); /* Handle iterables and slices by calling the select() method */ if (PySlice_Check(o) || PyObject_HasAttrString(o, "__iter__")) { PyObject *result, *args; args = Py_BuildValue("(O)", o); if (!args) return NULL; result = igraphmodule_EdgeSeq_select(self, args); Py_DECREF(args); return result; } /* Handle everything else according to the mapping protocol */ return igraphmodule_EdgeSeq_get_attribute_values(self, o); } /** \ingroup python_interface_edgeseq * \brief Sets the list of values for a given attribute */ int igraphmodule_EdgeSeq_set_attribute_values_mapping(igraphmodule_EdgeSeqObject* self, PyObject* attrname, PyObject* values) { PyObject *dict, *list, *item; igraphmodule_GraphObject *gr; igraph_vector_t es; long i, j, n, no_of_edges; gr = self->gref; dict = ATTR_STRUCT_DICT(&gr->g)[ATTRHASH_IDX_EDGE]; if (!igraphmodule_attribute_name_check(attrname)) return -1; if (values == 0) { if (igraph_es_type(&self->es) == IGRAPH_ES_ALL) return PyDict_DelItem(dict, attrname); PyErr_SetString(PyExc_TypeError, "can't delete attribute from an edge sequence not representing the whole graph"); return -1; } if (PyString_Check(values) || !PySequence_Check(values)) { /* If values is a string or not a sequence, we construct a list with a * single element (the value itself) and then call ourselves again */ int result; PyObject *newList = PyList_New(1); if (newList == 0) return -1; Py_INCREF(values); PyList_SET_ITEM(newList, 0, values); /* reference stolen here */ result = igraphmodule_EdgeSeq_set_attribute_values_mapping(self, attrname, newList); Py_DECREF(newList); return result; } n=PySequence_Size(values); if (n<0) return -1; if (igraph_es_type(&self->es) == IGRAPH_ES_ALL) { no_of_edges = (long)igraph_ecount(&gr->g); if (n == 0 && no_of_edges > 0) { PyErr_SetString(PyExc_ValueError, "sequence must not be empty"); return -1; } /* Check if we already have attributes with the given name */ list = PyDict_GetItem(dict, attrname); if (list != 0) { /* Yes, we have. Modify its items to the items found in values */ for (i=0, j=0; ig, self->es, &es)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&es); return -1; } no_of_edges = (long)igraph_vector_size(&es); if (n == 0 && no_of_edges > 0) { PyErr_SetString(PyExc_ValueError, "sequence must not be empty"); igraph_vector_destroy(&es); return -1; } /* Check if we already have attributes with the given name */ list = PyDict_GetItem(dict, attrname); if (list != 0) { /* Yes, we have. Modify its items to the items found in values */ for (i=0, j=0; ig); list = PyList_New(n2); if (list == 0) { igraph_vector_destroy(&es); return -1; } for (i=0; igref; result=igraphmodule_EdgeSeq_copy(self); if (result == 0) return NULL; /* First, filter by positional arguments */ n = PyTuple_Size(args); for (i=0; ies); igraph_es_none(&result->es); /* We can simply bail out here */ return (PyObject*)result; } else if (PyCallable_Check(item)) { /* Call the callable for every edge in the current sequence to * determine what's up */ igraph_bool_t was_excluded = 0; igraph_vector_t v; if (igraph_vector_init(&v, 0)) { igraphmodule_handle_igraph_error(); return 0; } m = PySequence_Size((PyObject*)result); for (j=0; jes); if (igraph_es_vector_copy(&result->es, &v)) { Py_DECREF(result); igraph_vector_destroy(&v); igraphmodule_handle_igraph_error(); return NULL; } } igraph_vector_destroy(&v); } else if (PyInt_Check(item)) { /* Integers are treated specially: from now on, all remaining items * in the argument list must be integers and they will be used together * to restrict the edge set. Integers are interpreted as indices on the * edge set and NOT on the original, untouched edge sequence of the * graph */ igraph_vector_t v, v2; if (igraph_vector_init(&v, 0)) { igraphmodule_handle_igraph_error(); return 0; } if (igraph_vector_init(&v2, 0)) { igraph_vector_destroy(&v); igraphmodule_handle_igraph_error(); return 0; } if (igraph_es_as_vector(&gr->g, self->es, &v2)) { igraph_vector_destroy(&v); igraph_vector_destroy(&v2); igraphmodule_handle_igraph_error(); return 0; } m = igraph_vector_size(&v2); for (; i= m || idx < 0) { PyErr_SetString(PyExc_ValueError, "edge index out of range"); igraph_vector_destroy(&v); igraph_vector_destroy(&v2); return NULL; } if (igraph_vector_push_back(&v, VECTOR(v2)[idx])) { Py_DECREF(result); igraphmodule_handle_igraph_error(); igraph_vector_destroy(&v); igraph_vector_destroy(&v2); return NULL; } } igraph_vector_destroy(&v2); igraph_es_destroy(&result->es); if (igraph_es_vector_copy(&result->es, &v)) { Py_DECREF(result); igraphmodule_handle_igraph_error(); igraph_vector_destroy(&v); return NULL; } igraph_vector_destroy(&v); } else { /* Iterators and everything that was not handled directly */ PyObject *iter, *item2; igraph_vector_t v, v2; /* Allocate stuff */ if (igraph_vector_init(&v, 0)) { igraphmodule_handle_igraph_error(); return 0; } if (igraph_vector_init(&v2, 0)) { igraph_vector_destroy(&v); igraphmodule_handle_igraph_error(); return 0; } if (igraph_es_as_vector(&gr->g, self->es, &v2)) { igraph_vector_destroy(&v); igraph_vector_destroy(&v2); igraphmodule_handle_igraph_error(); return 0; } m = igraph_vector_size(&v2); /* Create an appropriate iterator */ if (PySlice_Check(item)) { /* Create an iterator from the slice (which is not iterable by default )*/ Py_ssize_t start, stop, step, sl; PyObject* range; igraph_bool_t ok; /* Casting to void* because Python 2.x expects PySliceObject* * but Python 3.x expects PyObject* */ ok = (PySlice_GetIndicesEx((void*)item, igraph_vector_size(&v2), &start, &stop, &step, &sl) == 0); if (ok) { range = igraphmodule_PyRange_create(start, stop, step); ok = (range != 0); } if (ok) { iter = PyObject_GetIter(range); Py_DECREF(range); ok = (iter != 0); } if (!ok) { igraph_vector_destroy(&v); igraph_vector_destroy(&v2); PyErr_SetString(PyExc_TypeError, "error while converting slice to iterator"); Py_DECREF(result); return 0; } } else { /* Simply create the iterator corresponding to the object */ iter = PyObject_GetIter(item); } /* Did we manage to get an iterator? */ if (iter == 0) { igraph_vector_destroy(&v); igraph_vector_destroy(&v2); PyErr_SetString(PyExc_TypeError, "invalid edge filter among positional arguments"); Py_DECREF(result); return 0; } /* Do the iteration */ while ((item2=PyIter_Next(iter)) != 0) { if (PyInt_Check(item2)) { long idx = PyInt_AsLong(item2); Py_DECREF(item2); if (idx >= m || idx < 0) { PyErr_SetString(PyExc_ValueError, "edge index out of range"); Py_DECREF(result); Py_DECREF(iter); igraph_vector_destroy(&v); igraph_vector_destroy(&v2); return NULL; } if (igraph_vector_push_back(&v, VECTOR(v2)[idx])) { Py_DECREF(result); Py_DECREF(iter); igraphmodule_handle_igraph_error(); igraph_vector_destroy(&v); igraph_vector_destroy(&v2); return NULL; } } else { /* We simply ignore elements that we don't know */ Py_DECREF(item2); } } /* Deallocate stuff */ igraph_vector_destroy(&v2); Py_DECREF(iter); if (PyErr_Occurred()) { igraph_vector_destroy(&v); Py_DECREF(result); return 0; } igraph_es_destroy(&result->es); if (igraph_es_vector_copy(&result->es, &v)) { Py_DECREF(result); igraphmodule_handle_igraph_error(); igraph_vector_destroy(&v); return NULL; } igraph_vector_destroy(&v); } } return (PyObject*)result; } /** * \ingroup python_interface_edgeseq * Method table for the \c igraph.EdgeSeq object */ PyMethodDef igraphmodule_EdgeSeq_methods[] = { {"attribute_names", (PyCFunction)igraphmodule_EdgeSeq_attribute_names, METH_NOARGS, "attribute_names() -> list\n\n" "Returns the attribute name list of the graph's edges\n" }, {"find", (PyCFunction)igraphmodule_EdgeSeq_find, METH_VARARGS, "find(condition) -> Edge\n\n" "For internal use only.\n" }, {"get_attribute_values", (PyCFunction)igraphmodule_EdgeSeq_get_attribute_values, METH_O, "get_attribute_values(attrname) -> list\n\n" "Returns the value of a given edge attribute for all edges.\n\n" "@param attrname: the name of the attribute\n" }, {"is_all", (PyCFunction)igraphmodule_EdgeSeq_is_all, METH_NOARGS, "is_all() -> bool\n\n" "Returns whether the edge sequence contains all the edges exactly once, in\n" "the order of their edge IDs.\n\n" "This is used for optimizations in some of the edge selector routines.\n" }, {"set_attribute_values", (PyCFunction)igraphmodule_EdgeSeq_set_attribute_values, METH_VARARGS | METH_KEYWORDS, "set_attribute_values(attrname, values) -> list\n" "Sets the value of a given edge attribute for all vertices\n" "@param attrname: the name of the attribute\n" "@param values: the new attribute values in a list\n" }, {"select", (PyCFunction)igraphmodule_EdgeSeq_select, METH_VARARGS, "select(...) -> VertexSeq\n\n" "For internal use only.\n" }, {NULL} }; /** * \ingroup python_interface_edgeseq * This is the collection of functions necessary to implement the * edge sequence as a real sequence (e.g. allowing to reference * edges by indices) */ static PySequenceMethods igraphmodule_EdgeSeq_as_sequence = { (lenfunc)igraphmodule_EdgeSeq_sq_length, 0, /* sq_concat */ 0, /* sq_repeat */ (ssizeargfunc)igraphmodule_EdgeSeq_sq_item, /* sq_item */ 0, /* sq_slice */ 0, /* sq_ass_item */ 0, /* sq_ass_slice */ 0, /* sq_contains */ 0, /* sq_inplace_concat */ 0, /* sq_inplace_repeat */ }; /** * \ingroup python_interface_edgeseq * This is the collection of functions necessary to implement the * edge sequence as a mapping (which maps attribute names to values) */ static PyMappingMethods igraphmodule_EdgeSeq_as_mapping = { /* returns the number of edge attributes */ (lenfunc) 0, /* returns the values of an attribute by name */ (binaryfunc) igraphmodule_EdgeSeq_get_attribute_values_mapping, /* sets the values of an attribute by name */ (objobjargproc) igraphmodule_EdgeSeq_set_attribute_values_mapping, }; /** * \ingroup python_interface_edgeseq * Returns the graph where the edge sequence belongs */ PyObject* igraphmodule_EdgeSeq_get_graph(igraphmodule_EdgeSeqObject* self, void* closure) { Py_INCREF(self->gref); return (PyObject*)self->gref; } /** * \ingroup python_interface_edgeseq * Returns the indices of the edges in this edge sequence */ PyObject* igraphmodule_EdgeSeq_get_indices(igraphmodule_EdgeSeqObject* self, void* closure) { igraphmodule_GraphObject *gr = self->gref; igraph_vector_t es; PyObject *result; if (igraph_vector_init(&es, 0)) { igraphmodule_handle_igraph_error(); return 0; } if (igraph_es_as_vector(&gr->g, self->es, &es)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&es); return 0; } result = igraphmodule_vector_t_to_PyList(&es, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&es); return result; } /** * \ingroup python_interface_edgeseq * Getter/setter table for the \c igraph.EdgeSeq object */ PyGetSetDef igraphmodule_EdgeSeq_getseters[] = { {"graph", (getter)igraphmodule_EdgeSeq_get_graph, NULL, "The graph the edge sequence belongs to", NULL}, {"indices", (getter)igraphmodule_EdgeSeq_get_indices, NULL, "The edge indices in this edge sequence", NULL, }, {NULL} }; /** \ingroup python_interface_edgeseq * Python type object referencing the methods Python calls when it performs various operations on * an edge sequence of a graph */ PyTypeObject igraphmodule_EdgeSeqType = { PyVarObject_HEAD_INIT(0, 0) "igraph.core.EdgeSeq", /* tp_name */ sizeof(igraphmodule_EdgeSeqObject), /* tp_basicsize */ 0, /* tp_itemsize */ (destructor)igraphmodule_EdgeSeq_dealloc, /* tp_dealloc */ 0, /* tp_print */ 0, /* tp_getattr */ 0, /* tp_setattr */ 0, /* tp_compare (2.x) / tp_reserved (3.x) */ 0, /* tp_repr */ 0, /* tp_as_number */ &igraphmodule_EdgeSeq_as_sequence, /* tp_as_sequence */ &igraphmodule_EdgeSeq_as_mapping, /* tp_as_mapping */ 0, /* tp_hash */ 0, /* tp_call */ 0, /* tp_str */ 0, /* tp_getattro */ 0, /* tp_setattro */ 0, /* tp_as_buffer */ Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE, /* tp_flags */ "Low-level representation of an edge sequence.\n\n" /* tp_doc */ "Don't use it directly, use L{igraph.EdgeSeq} instead.\n\n" "@deffield ref: Reference", 0, /* tp_traverse */ 0, /* tp_clear */ 0, /* tp_richcompare */ offsetof(igraphmodule_EdgeSeqObject, weakreflist), /* tp_weaklistoffset */ 0, /* tp_iter */ 0, /* tp_iternext */ igraphmodule_EdgeSeq_methods, /* tp_methods */ 0, /* tp_members */ igraphmodule_EdgeSeq_getseters, /* tp_getset */ 0, /* tp_base */ 0, /* tp_dict */ 0, /* tp_descr_get */ 0, /* tp_descr_set */ 0, /* tp_dictoffset */ (initproc) igraphmodule_EdgeSeq_init, /* tp_init */ 0, /* tp_alloc */ (newfunc) igraphmodule_EdgeSeq_new, /* tp_new */ 0, /* tp_free */ 0, /* tp_is_gc */ 0, /* tp_bases */ 0, /* tp_mro */ 0, /* tp_cache */ 0, /* tp_subclasses */ 0, /* tp_weakreflist */ }; python-igraph-0.8.0/src/_igraph/py2compat.h0000644000076500000240000000502513576370542021045 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim: set ts=2 sw=2 sts=2 et: */ /* IGraph library. Copyright (C) 2006-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef PY_IGRAPH_PY2COMPAT_H #define PY_IGRAPH_PY2COMPAT_H #include /* Common utility functions */ int PyFile_Close(PyObject* fileObj); /* Compatibility hacks */ #ifndef Py_hash_t # define Py_hash_t long #endif #if PY_MAJOR_VERSION >= 3 /* Python 3.x-specific part follows here */ #define IGRAPH_PYTHON3 #define PyBaseString_Check(o) (PyUnicode_Check(o) || PyBytes_Check(o)) PyObject* PyFile_FromObject(PyObject* filename, const char* mode); #ifndef PYPY_VERSION typedef PyLongObject PyIntObject; #endif /* PYPY_VERSION */ #define PyInt_AsLong PyLong_AsLong #define PyInt_Check PyLong_Check #define PyInt_FromLong PyLong_FromLong #define PyNumber_Int PyNumber_Long #define PyString_AS_STRING PyUnicode_AS_UNICODE #define PyString_Check PyUnicode_Check #define PyString_FromFormat PyUnicode_FromFormat #define PyString_FromString PyUnicode_FromString #define PyString_Type PyUnicode_Type #define PyString_IsEqualToASCIIString(uni, string) \ (PyUnicode_CompareWithASCIIString(uni, string) == 0) #ifndef PyVarObject_HEAD_INIT #define PyVarObject_HEAD_INIT(type, size) \ PyObject_HEAD_INIT(type) size, #endif int PyString_IsEqualToUTF8String(PyObject* py_string, const char* c_string); #else /* Python 2.x-specific part follows here */ #define PyBaseString_Check(o) (PyString_Check(o) || PyUnicode_Check(o)) int PyString_IsEqualToASCIIString(PyObject* py_string, const char* c_string); #ifndef Py_TYPE # define Py_TYPE(o) ((o)->ob_type) #endif #ifndef PyVarObject_HEAD_INIT # define PyVarObject_HEAD_INIT(type, size) PyObject_HEAD_INIT(type) size, #endif #endif char* PyString_CopyAsString(PyObject* string); #endif python-igraph-0.8.0/src/_igraph/igraphmodule_api.h0000644000076500000240000000500613104627150022422 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim:set ts=2 sw=2 sts=2 et: */ /* IGraph library. Copyright (C) 2006-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef Py_IGRAPHMODULE_H #define Py_IGRAPHMODULE_H #ifdef __cplusplus extern "C" { #endif /* C API functions */ #define PyIGraph_FromCGraph_NUM 0 #define PyIGraph_FromCGraph_RETURN PyObject* #define PyIGraph_FromCGraph_PROTO (igraph_t *graph) #define PyIGraph_ToCGraph_NUM 1 #define PyIGraph_ToCGraph_RETURN igraph_t* #define PyIGraph_ToCGraph_PROTO (PyObject *graph) /* Total number of C API pointers */ #define PyIGraph_API_pointers 2 #ifdef IGRAPH_MODULE /* This section is used when compiling igraphmodule.c */ static PyIGraph_FromCGraph_RETURN PyIGraph_FromCGraph PyIGraph_FromCGraph_PROTO; static PyIGraph_ToCGraph_RETURN PyIGraph_ToCGraph PyIGraph_ToCGraph_PROTO; #else /* This section is used in modules that use igraph's API */ static void** PyIGraph_API; # define PyIGraph_FromCGraph \ (*(PyIGraph_FromCGraph_RETURN (*)PyIGraph_FromCGraph_PROTO) \ PyIGraph_API[PyIGraph_FromCGraph_NUM]) # define PyIGraph_ToCGraph \ (*(PyIGraph_ToCGraph_RETURN (*)PyIGraph_ToCGraph_PROTO) \ PyIGraph_API[PyIGraph_ToCGraph_NUM]) /* Return -1 and set exception on error, 0 on success */ static int import_igraph(void) { PyObject *c_api_object; PyObject *module; module = PyImport_ImportModule("igraph._igraph"); if (module == 0) return -1; c_api_object = PyObject_GetAttrString(module, "_C_API"); if (c_api_object == 0) { Py_DECREF(module); return -1; } if (PyCObject_Check(c_api_object)) PyIGraph_API = (void**)PyCObject_AsVoidPtr(c_api_object); Py_DECREF(c_api_object); Py_DECREF(module); return 0; } #endif #ifdef __cplusplus } #endif #endif /* !defined(Py_IGRAPHMODULE_H) */ python-igraph-0.8.0/src/_igraph/common.h0000644000076500000240000000504413104627150020403 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef PYTHON_COMMON_H #define PYTHON_COMMON_H #include #ifdef RC_DEBUG # define RC_ALLOC(T, P) fprintf(stderr, "[ alloc ] " T " @ %p\n", P) # define RC_DECREF(T, P) fprintf(stderr, "[ ref - ] " T " @ %p (was: %d)\n", P, (int)P->ob_refcnt); # define RC_INCREF(T, P) fprintf(stderr, "[ ref + ] " T " @ %p (was: %d)\n", P, (int)P->ob_refcnt); # define RC_PRINT(P) fprintf(stderr, "[refcntr] %s @ %p = %d\n", ((PyTypeObject*)P->ob_type)->tp_name, P, (int)P->ob_refcnt); # define RC_DEALLOC(T, P) fprintf(stderr, "[dealloc] " T " @ %p\n", P); # define RC_TRAVERSE(T, P) #else # define RC_ALLOC(T, P) # define RC_DECREF(T, P) # define RC_INCREF(T, P) # define RC_PRINT(P) # define RC_DEALLOC(T, P) # define RC_TRAVERSE(T, P) #endif /* Compatibility stuff for Python 2.3 */ #ifndef Py_RETURN_TRUE #define Py_RETURN_TRUE { Py_INCREF(Py_True); return Py_True; } #endif #ifndef Py_RETURN_FALSE #define Py_RETURN_FALSE { Py_INCREF(Py_False); return Py_False; } #endif #ifndef Py_RETURN_NONE #define Py_RETURN_NONE { Py_INCREF(Py_None); return Py_None; } #endif #ifndef Py_RETURN_NOTIMPLEMENTED #define Py_RETURN_NOTIMPLEMENTED { Py_INCREF(Py_NotImplemented); return Py_NotImplemented; } #endif #ifndef Py_RETURN #define Py_RETURN(x) { if (x) { Py_RETURN_TRUE; } else { Py_RETURN_FALSE; } } #endif /* Compatibility stuff for Python 2.4 */ #if (PY_MAJOR_VERSION <= 2) & (PY_MINOR_VERSION <= 4) #define lenfunc inquiry #define ssizeargfunc intargfunc #define ssizessizeargfunc intintargfunc #define Py_ssize_t int #endif #define ATTRIBUTE_TYPE_VERTEX 1 #define ATTRIBUTE_TYPE_EDGE 2 PyObject* igraphmodule_unimplemented(PyObject* self, PyObject* args, PyObject* kwds); PyObject* igraphmodule_resolve_graph_weakref(PyObject* ref); #endif python-igraph-0.8.0/src/_igraph/edgeobject.h0000644000076500000240000000375113104627150021211 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef PYTHON_EDGEOBJECT_H #define PYTHON_EDGEOBJECT_H #include #include "graphobject.h" #include "py2compat.h" /** * \ingroup python_interface_edge * \brief A structure representing an edge of a graph */ typedef struct { PyObject_HEAD igraphmodule_GraphObject* gref; igraph_integer_t idx; Py_hash_t hash; } igraphmodule_EdgeObject; int igraphmodule_Edge_clear(igraphmodule_EdgeObject *self); void igraphmodule_Edge_dealloc(igraphmodule_EdgeObject* self); int igraphmodule_Edge_Check(PyObject *obj); int igraphmodule_Edge_Validate(PyObject *obj); PyObject* igraphmodule_Edge_New(igraphmodule_GraphObject *gref, igraph_integer_t idx); PyObject* igraphmodule_Edge_repr(igraphmodule_EdgeObject *self); PyObject* igraphmodule_Edge_attributes(igraphmodule_EdgeObject* self); PyObject* igraphmodule_Edge_attribute_names(igraphmodule_EdgeObject* self); igraph_integer_t igraphmodule_Edge_get_index_igraph_integer(igraphmodule_EdgeObject* self); long igraphmodule_Edge_get_index_long(igraphmodule_EdgeObject* self); PyObject* igraphmodule_Edge_update_attributes(PyObject* self, PyObject* args, PyObject* kwds); extern PyTypeObject igraphmodule_EdgeType; #endif python-igraph-0.8.0/src/_igraph/error.c0000644000076500000240000000534113614535600020243 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "error.h" #include /** \ingroup python_interface_errors * \brief Exception type to be returned when an internal \c igraph error occurs. */ PyObject* igraphmodule_InternalError; /** * \ingroup python_interface_errors * \brief Generic error handler for internal \c igraph errors. * * Since now \c igraph supports error handler functions, a special * function called \c igraphmodule_igraph_error_hook is responsible * for providing a meaningful error message. If it fails (or it isn't * even called), this function will provide a default error message. * * \return Always returns \c NULL, and all callers are advised to pass this * \c NULL value to their callers until it is propagated to the Python * interpreter. */ PyObject* igraphmodule_handle_igraph_error() { if (!PyErr_Occurred()) { PyErr_SetString(igraphmodule_InternalError, "Internal igraph error. Please contact the author!"); } return NULL; } /** * \ingroup python_interface_errors * \brief Warning hook for \c igraph */ void igraphmodule_igraph_warning_hook(const char *reason, const char *file, int line, int igraph_errno) { char buf[4096]; snprintf(buf, sizeof(buf), "%s at %s:%i", reason, file, line); PyErr_Warn(PyExc_RuntimeWarning, buf); } /** * \ingroup python_interface_errors * \brief Error hook for \c igraph */ void igraphmodule_igraph_error_hook(const char *reason, const char *file, int line, int igraph_errno) { char buf[4096]; PyObject *exc = igraphmodule_InternalError; if (igraph_errno == IGRAPH_UNIMPLEMENTED) exc = PyExc_NotImplementedError; if (igraph_errno == IGRAPH_ENOMEM) exc = PyExc_MemoryError; snprintf(buf, sizeof(buf), "Error at %s:%i: %s, %s", file, line, reason, igraph_strerror(igraph_errno)); IGRAPH_FINALLY_FREE(); /* make sure we are not masking already thrown exceptions */ if (!PyErr_Occurred()) PyErr_SetString(exc, buf); } python-igraph-0.8.0/src/_igraph/bfsiter.h0000644000076500000240000000323513104627150020551 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef PYTHON_BFSITER_H #define PYTHON_BFSITER_H #include #include "graphobject.h" /** * \ingroup python_interface_bfsiter * \brief A structure representing a BFS iterator of a graph */ typedef struct { PyObject_HEAD igraphmodule_GraphObject* gref; igraph_dqueue_t queue; igraph_vector_t neis; igraph_t *graph; char *visited; igraph_neimode_t mode; igraph_bool_t advanced; } igraphmodule_BFSIterObject; PyObject* igraphmodule_BFSIter_new(igraphmodule_GraphObject *g, PyObject *o, igraph_neimode_t mode, igraph_bool_t advanced); int igraphmodule_BFSIter_traverse(igraphmodule_BFSIterObject *self, visitproc visit, void *arg); int igraphmodule_BFSIter_clear(igraphmodule_BFSIterObject *self); void igraphmodule_BFSIter_dealloc(igraphmodule_BFSIterObject* self); extern PyTypeObject igraphmodule_BFSIterType; #endif python-igraph-0.8.0/src/_igraph/indexing.h0000644000076500000240000000250013104627150020712 0ustar tamasstaff00000000000000/* vim:set ts=4 sw=2 sts=2 et: */ /* IGraph library - Python interface. Copyright (C) 2006-2011 Tamas Nepusz 5 Avenue Road, Staines, Middlesex, TW18 3AW, United Kingdom This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef PYTHON_INDEXING_H #define PYTHON_INDEXING_H #include #include PyObject* igraphmodule_Graph_adjmatrix_get_index(igraph_t* graph, PyObject* row_index, PyObject* column_index, PyObject* attr_name); int igraphmodule_Graph_adjmatrix_set_index(igraph_t* graph, PyObject* row_index, PyObject* column_index, PyObject* attr_name, PyObject* value); #endif python-igraph-0.8.0/src/_igraph/graphobject.h0000644000076500000240000004206313616774160021421 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef PYTHON_GRAPHOBJECT_H #define PYTHON_GRAPHOBJECT_H #include #include #include "structmember.h" #include "common.h" extern PyTypeObject igraphmodule_GraphType; /** * \ingroup python_interface * \brief A structure containing all the fields required to access an igraph from Python */ typedef struct { PyObject_HEAD // The graph object igraph_t g; // Python object to be called upon destruction PyObject* destructor; // Python object representing the sequence of vertices PyObject* vseq; // Python object representing the sequence of edges PyObject* eseq; // Python object of the weak reference list PyObject* weakreflist; } igraphmodule_GraphObject; void igraphmodule_Graph_init_internal(igraphmodule_GraphObject *self); PyObject* igraphmodule_Graph_new(PyTypeObject *type, PyObject *args, PyObject *kwds); int igraphmodule_Graph_clear(igraphmodule_GraphObject *self); int igraphmodule_Graph_traverse(igraphmodule_GraphObject *self, visitproc visit, void *arg); void igraphmodule_Graph_dealloc(igraphmodule_GraphObject* self); int igraphmodule_Graph_init(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_from_igraph_t(igraph_t *graph); PyObject* igraphmodule_Graph_str(igraphmodule_GraphObject *self); PyObject* igraphmodule_Graph_vcount(igraphmodule_GraphObject *self); PyObject* igraphmodule_Graph_ecount(igraphmodule_GraphObject *self); PyObject* igraphmodule_Graph_is_dag(igraphmodule_GraphObject *self); PyObject* igraphmodule_Graph_is_directed(igraphmodule_GraphObject *self); PyObject* igraphmodule_Graph_is_simple(igraphmodule_GraphObject *self); PyObject* igraphmodule_Graph_add_vertices(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_delete_vertices(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_add_edges(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_delete_edges(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_degree(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_is_loop(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_count_multiple(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_neighbors(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_successors(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_predecessors(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_get_eid(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_Adjacency(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_Asymmetric_Preference(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_Atlas(PyTypeObject *type, PyObject *args); PyObject* igraphmodule_Graph_Barabasi(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_Degree_Sequence(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_Establishment(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_Erdos_Renyi(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_Famous(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_Forest_Fire(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_Full_Citation(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_Full(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_GRG(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_Growing_Random(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_Isoclass(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_Lattice(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_LCF(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_Preference(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_Recent_Degree(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_Ring(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_SBM(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_Star(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_Tree(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_Watts_Strogatz(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_is_connected(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_are_connected(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_adjacency_spectral_embedding(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_articulation_points(igraphmodule_GraphObject *self); PyObject* igraphmodule_Graph_average_path_length(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_betweenness(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_bibcoupling(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_closeness(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_clusters(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_cocitation(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_constraint(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_copy(igraphmodule_GraphObject *self); PyObject* igraphmodule_Graph_decompose(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_density(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_diameter(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_edge_betweenness(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_eigen_adjacency(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_get_shortest_paths(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_get_all_shortest_paths(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_maxdegree(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_pagerank(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_path_length_hist(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_reciprocity(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_rewire(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_shortest_paths(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_spanning_tree(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_simplify(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_subcomponent(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_subgraph(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_transitivity_undirected(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_transitivity_local_undirected(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_scan1(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_layout_circle(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_layout_sphere(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_layout_random(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_layout_random_3d(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_layout_kamada_kawai(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_layout_kamada_kawai_3d(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_layout_drl(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_layout_fruchterman_reingold(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_layout_fruchterman_reingold_3d(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_layout_grid_fruchterman_reingold(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_layout_lgl(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_layout_reingold_tilford(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_get_adjacency(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_get_edgelist(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_to_undirected(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_to_directed(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_laplacian(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_Read_DIMACS(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_Read_Edgelist(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_Read_GML(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_Read_Ncol(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_Read_Lgl(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_Read_Pajek(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_Read_GraphML(PyTypeObject *type, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_write_dimacs(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_write_dot(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_write_edgelist(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_write_ncol(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_write_lgl(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_write_gml(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_write_graphml(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_isoclass(igraphmodule_GraphObject* self, PyObject* args, PyObject* kwds); PyObject* igraphmodule_Graph_isomorphic(igraphmodule_GraphObject* self, PyObject* args, PyObject* kwds); PyObject* igraphmodule_Graph_count_isomorphisms(igraphmodule_GraphObject* self, PyObject* args, PyObject* kwds); PyObject* igraphmodule_Graph_get_isomorphisms(igraphmodule_GraphObject* self, PyObject* args, PyObject* kwds); PyObject* igraphmodule_Graph_subisomorphic(igraphmodule_GraphObject* self, PyObject* args, PyObject* kwds); PyObject* igraphmodule_Graph_count_subisomorphisms(igraphmodule_GraphObject* self, PyObject* args, PyObject* kwds); PyObject* igraphmodule_Graph_get_subisomorphisms(igraphmodule_GraphObject* self, PyObject* args, PyObject* kwds); Py_ssize_t igraphmodule_Graph_attribute_count(igraphmodule_GraphObject* self); PyObject* igraphmodule_Graph_get_attribute(igraphmodule_GraphObject* self, PyObject* s); int igraphmodule_Graph_set_attribute(igraphmodule_GraphObject* self, PyObject* k, PyObject* v); PyObject* igraphmodule_Graph_attributes(igraphmodule_GraphObject* self); PyObject* igraphmodule_Graph_vertex_attributes(igraphmodule_GraphObject* self); PyObject* igraphmodule_Graph_edge_attributes(igraphmodule_GraphObject* self); PyObject* igraphmodule_Graph_get_vertices(igraphmodule_GraphObject* self, void* closure); PyObject* igraphmodule_Graph_get_edges(igraphmodule_GraphObject* self, void* closure); PyObject* igraphmodule_Graph_complementer(igraphmodule_GraphObject* self, PyObject* args); PyObject* igraphmodule_Graph_complementer_op(igraphmodule_GraphObject* self); PyObject* igraphmodule_Graph_compose(igraphmodule_GraphObject* self, PyObject* other); PyObject* igraphmodule_Graph_difference(igraphmodule_GraphObject* self, PyObject* other); PyObject* igraphmodule_Graph_disjoint_union(igraphmodule_GraphObject* self, PyObject* other); PyObject* igraphmodule_Graph_intersection(igraphmodule_GraphObject* self, PyObject* other); PyObject* igraphmodule_Graph_union(igraphmodule_GraphObject* self, PyObject* other); PyObject* igraphmodule_Graph_bfs(igraphmodule_GraphObject* self, PyObject* args, PyObject* kwds); PyObject* igraphmodule_Graph_bfsiter(igraphmodule_GraphObject* self, PyObject* args, PyObject* kwds); PyObject* igraphmodule_Graph_maxflow(igraphmodule_GraphObject* self, PyObject* args, PyObject* kwds); PyObject* igraphmodule_Graph_maxflow_value(igraphmodule_GraphObject* self, PyObject* args, PyObject* kwds); PyObject* igraphmodule_Graph_mincut(igraphmodule_GraphObject* self, PyObject* args, PyObject* kwds); PyObject* igraphmodule_Graph_mincut_value(igraphmodule_GraphObject* self, PyObject* args, PyObject* kwds); PyObject* igraphmodule_Graph_cliques(igraphmodule_GraphObject* self, PyObject* args, PyObject* kwds); PyObject* igraphmodule_Graph_maximal_cliques(igraphmodule_GraphObject* self, PyObject* args, PyObject* kwds); PyObject* igraphmodule_Graph_largest_cliques(igraphmodule_GraphObject* self); PyObject* igraphmodule_Graph_clique_number(igraphmodule_GraphObject* self); PyObject* igraphmodule_Graph_independent_sets(igraphmodule_GraphObject* self, PyObject* args, PyObject* kwds); PyObject* igraphmodule_Graph_maximal_independent_sets(igraphmodule_GraphObject* self); PyObject* igraphmodule_Graph_largest_independent_sets(igraphmodule_GraphObject* self); PyObject* igraphmodule_Graph_independence_number(igraphmodule_GraphObject* self); PyObject* igraphmodule_Graph_community_edge_betweenness(igraphmodule_GraphObject* self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_community_fastgreedy(igraphmodule_GraphObject* self, PyObject *args, PyObject *kwds); PyObject *igraphmodule_Graph_community_infomap(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_community_label_propagation(igraphmodule_GraphObject* self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_community_leading_eigenvector(igraphmodule_GraphObject* self, PyObject *args, PyObject *kwds); PyObject *igraphmodule_Graph_community_multilevel(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject *igraphmodule_Graph_community_optimal_modularity(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_community_spinglass(igraphmodule_GraphObject* self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_community_walktrap(igraphmodule_GraphObject* self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_modularity(igraphmodule_GraphObject* self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph_leiden(igraphmodule_GraphObject* self, PyObject *args, PyObject *kwds); PyObject *igraphmodule_Graph_is_bipartite(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph___graph_as_cobject__(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); PyObject* igraphmodule_Graph___register_destructor__(igraphmodule_GraphObject *self, PyObject *args, PyObject *kwds); #endif python-igraph-0.8.0/src/_igraph/vertexobject.h0000644000076500000240000000403013104627150021611 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef PYTHON_VERTEXOBJECT_H #define PYTHON_VERTEXOBJECT_H #include #include "graphobject.h" #include "py2compat.h" /** * \ingroup python_interface_vertex * \brief A structure representing a vertex of a graph */ typedef struct { PyObject_HEAD igraphmodule_GraphObject* gref; igraph_integer_t idx; Py_hash_t hash; } igraphmodule_VertexObject; int igraphmodule_Vertex_clear(igraphmodule_VertexObject *self); void igraphmodule_Vertex_dealloc(igraphmodule_VertexObject* self); int igraphmodule_Vertex_Check(PyObject *obj); int igraphmodule_Vertex_Validate(PyObject *obj); PyObject* igraphmodule_Vertex_New(igraphmodule_GraphObject *gref, igraph_integer_t idx); PyObject* igraphmodule_Vertex_repr(igraphmodule_VertexObject *self); PyObject* igraphmodule_Vertex_attributes(igraphmodule_VertexObject* self); PyObject* igraphmodule_Vertex_attribute_names(igraphmodule_VertexObject* self); igraph_integer_t igraphmodule_Vertex_get_index_igraph_integer(igraphmodule_VertexObject* self); long igraphmodule_Vertex_get_index_long(igraphmodule_VertexObject* self); PyObject* igraphmodule_Vertex_update_attributes(PyObject* self, PyObject* args, PyObject* kwds); extern PyTypeObject igraphmodule_VertexType; #endif python-igraph-0.8.0/src/_igraph/convert.h0000644000076500000240000001663213441432071020600 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ /************************ Miscellaneous functions *************************/ /** \defgroup python_interface_conversion Converting between Python and igraph data types * \ingroup python_interface */ #ifndef PYTHON_CONVERT_H #define PYTHON_CONVERT_H #include #include #include #include "graphobject.h" typedef enum { IGRAPHMODULE_TYPE_INT=0, IGRAPHMODULE_TYPE_FLOAT } igraphmodule_conv_t; typedef struct { const char* name; int value; } igraphmodule_enum_translation_table_entry_t; int PyInt_AsInt(PyObject* obj, int* result); int PyLong_AsInt(PyObject* obj, int* result); /* Conversion from PyObject to enum types */ int igraphmodule_PyObject_to_enum(PyObject *o, igraphmodule_enum_translation_table_entry_t *table, int *result); int igraphmodule_PyObject_to_add_weights_t(PyObject *o, igraph_add_weights_t *result); int igraphmodule_PyObject_to_adjacency_t(PyObject *o, igraph_adjacency_t *result); int igraphmodule_PyObject_to_attribute_combination_type_t(PyObject* o, igraph_attribute_combination_type_t *type); int igraphmodule_PyObject_to_barabasi_algorithm_t(PyObject *o, igraph_barabasi_algorithm_t *result); int igraphmodule_PyObject_to_bliss_sh_t(PyObject *o, igraph_bliss_sh_t *result); int igraphmodule_PyObject_to_community_comparison_t(PyObject *obj, igraph_community_comparison_t *result); int igraphmodule_PyObject_to_connectedness_t(PyObject *o, igraph_connectedness_t *result); int igraphmodule_PyObject_to_degseq_t(PyObject *o, igraph_degseq_t *result); int igraphmodule_PyObject_to_fas_algorithm_t(PyObject *o, igraph_fas_algorithm_t *result); int igraphmodule_PyObject_to_layout_grid_t(PyObject *o, igraph_layout_grid_t *result); int igraphmodule_PyObject_to_neimode_t(PyObject *o, igraph_neimode_t *result); int igraphmodule_PyObject_to_pagerank_algo_t(PyObject *o, igraph_pagerank_algo_t *result); int igraphmodule_PyObject_to_random_walk_stuck_t(PyObject *o, igraph_random_walk_stuck_t *result); int igraphmodule_PyObject_to_reciprocity_t(PyObject *o, igraph_reciprocity_t *result); int igraphmodule_PyObject_to_rewiring_t(PyObject *o, igraph_rewiring_t *result); int igraphmodule_PyObject_to_spinglass_implementation_t(PyObject *o, igraph_spinglass_implementation_t *result); int igraphmodule_PyObject_to_spincomm_update_t(PyObject *o, igraph_spincomm_update_t *result); int igraphmodule_PyObject_to_star_mode_t(PyObject *o, igraph_star_mode_t *result); int igraphmodule_PyObject_to_subgraph_implementation_t(PyObject *o, igraph_subgraph_implementation_t *result); int igraphmodule_PyObject_to_to_undirected_t(PyObject *o, igraph_to_undirected_t *result); int igraphmodule_PyObject_to_transitivity_mode_t(PyObject *o, igraph_transitivity_mode_t *result); int igraphmodule_PyObject_to_tree_mode_t(PyObject *o, igraph_tree_mode_t *result); int igraphmodule_PyObject_to_vconn_nei_t(PyObject *o, igraph_vconn_nei_t *result); /* Conversion from PyObject to igraph types */ int igraphmodule_PyObject_to_integer_t(PyObject *object, igraph_integer_t *v); int igraphmodule_PyObject_to_real_t(PyObject *object, igraph_real_t *v); int igraphmodule_PyObject_to_igraph_t(PyObject *o, igraph_t **result); int igraphmodule_PyObject_to_vector_t(PyObject *list, igraph_vector_t *v, igraph_bool_t need_non_negative); int igraphmodule_PyObject_float_to_vector_t(PyObject *list, igraph_vector_t *v); int igraphmodule_PyObject_to_vector_int_t(PyObject *list, igraph_vector_int_t *v); int igraphmodule_PyObject_to_vector_long_t(PyObject *list, igraph_vector_long_t *v); int igraphmodule_PyObject_to_vector_bool_t(PyObject *list, igraph_vector_bool_t *v); int igraphmodule_PyObject_to_vector_ptr_t(PyObject *list, igraph_vector_ptr_t *v, igraph_bool_t need_non_negative); int igraphmodule_PyObject_to_edgelist( PyObject *list, igraph_vector_t *v, igraph_t *graph, igraph_bool_t *list_is_owned ); int igraphmodule_PyList_to_matrix_t(PyObject *o, igraph_matrix_t *m); PyObject* igraphmodule_strvector_t_to_PyList(igraph_strvector_t *v); int igraphmodule_PyList_to_strvector_t(PyObject* v, igraph_strvector_t *result); int igraphmodule_append_PyIter_of_graphs_to_vector_ptr_t(PyObject *it, igraph_vector_ptr_t *v); int igraphmodule_PyObject_to_vid(PyObject *o, igraph_integer_t *vid, igraph_t *graph); int igraphmodule_PyObject_to_vs_t(PyObject *o, igraph_vs_t *vs, igraph_t *graph, igraph_bool_t *return_single, igraph_integer_t *single_vid); int igraphmodule_PyObject_to_eid(PyObject *o, igraph_integer_t *eid, igraph_t *graph); int igraphmodule_PyObject_to_es_t(PyObject *o, igraph_es_t *es, igraph_t *graph, igraph_bool_t *return_single); int igraphmodule_PyObject_to_attribute_values(PyObject *o, igraph_vector_t *v, igraphmodule_GraphObject* g, int type, igraph_real_t def); int igraphmodule_PyObject_to_drl_options_t(PyObject *obj, igraph_layout_drl_options_t *options); int igraphmodule_PyObject_to_attribute_combination_t(PyObject* object, igraph_attribute_combination_t *type); int igraphmodule_PyObject_to_eigen_algorithm_t(PyObject *object, igraph_eigen_algorithm_t *a); int igraphmodule_PyObject_to_eigen_which_t(PyObject *object, igraph_eigen_which_t *w); /* Conversion from attributes to igraph types */ int igraphmodule_attrib_to_vector_t(PyObject *o, igraphmodule_GraphObject *self, igraph_vector_t **vptr, int attr_type); int igraphmodule_attrib_to_vector_int_t(PyObject *o, igraphmodule_GraphObject *self, igraph_vector_int_t **vptr, int attr_type); int igraphmodule_attrib_to_vector_long_t(PyObject *o, igraphmodule_GraphObject *self, igraph_vector_long_t **vptr, int attr_type); int igraphmodule_attrib_to_vector_bool_t(PyObject *o, igraphmodule_GraphObject *self, igraph_vector_bool_t **vptr, int attr_type); /* Conversion from igraph types to PyObjects */ PyObject* igraphmodule_vector_bool_t_to_PyList(const igraph_vector_bool_t *v); PyObject* igraphmodule_vector_t_to_PyList(const igraph_vector_t *v, igraphmodule_conv_t type); PyObject* igraphmodule_vector_t_to_PyTuple(const igraph_vector_t *v); PyObject* igraphmodule_vector_t_pair_to_PyList(const igraph_vector_t *v1, const igraph_vector_t *v2); PyObject* igraphmodule_vector_t_to_PyList_pairs(const igraph_vector_t *v); PyObject* igraphmodule_vector_ptr_t_to_PyList(const igraph_vector_ptr_t *v, igraphmodule_conv_t type); PyObject* igraphmodule_vector_int_t_to_PyList(const igraph_vector_int_t *v); PyObject* igraphmodule_vector_long_t_to_PyList(const igraph_vector_long_t *v); PyObject* igraphmodule_matrix_t_to_PyList(const igraph_matrix_t *m, igraphmodule_conv_t type); #endif python-igraph-0.8.0/src/_igraph/edgeseqobject.h0000644000076500000240000000363413104627150021722 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef PYTHON_EDGESEQOBJECT_H #define PYTHON_EDGESEQOBJECT_H #include #include "graphobject.h" /** * \ingroup python_interface_edgeseq * \brief A structure representing the edge sequence of a graph */ typedef struct { PyObject_HEAD igraphmodule_GraphObject* gref; igraph_es_t es; PyObject* weakreflist; } igraphmodule_EdgeSeqObject; PyObject* igraphmodule_EdgeSeq_new(PyTypeObject *subtype, PyObject *args, PyObject *kwds); igraphmodule_EdgeSeqObject* igraphmodule_EdgeSeq_copy( igraphmodule_EdgeSeqObject *o); int igraphmodule_EdgeSeq_init(igraphmodule_EdgeSeqObject *self, PyObject *args, PyObject *kwds); void igraphmodule_EdgeSeq_dealloc(igraphmodule_EdgeSeqObject* self); int igraphmodule_EdgeSeq_sq_length(igraphmodule_EdgeSeqObject *self); PyObject* igraphmodule_EdgeSeq_find(igraphmodule_EdgeSeqObject *self, PyObject *args); PyObject* igraphmodule_EdgeSeq_select(igraphmodule_EdgeSeqObject *self, PyObject *args); PyObject* igraphmodule_EdgeSeq_get_graph(igraphmodule_EdgeSeqObject *self, void* closure); extern PyTypeObject igraphmodule_EdgeSeqType; #endif python-igraph-0.8.0/src/_igraph/vertexseqobject.c0000644000076500000240000010364413104627150022330 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim: set ts=2 sts=2 sw=2 et: */ /* IGraph library. Copyright (C) 2006-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include "attributes.h" #include "common.h" #include "convert.h" #include "error.h" #include "py2compat.h" #include "pyhelpers.h" #include "vertexseqobject.h" #include "vertexobject.h" #define GET_GRAPH(obj) (((igraphmodule_GraphObject*)obj->gref)->g) /** * \ingroup python_interface * \defgroup python_interface_vertexseq Vertex sequence object */ PyTypeObject igraphmodule_VertexSeqType; /** * \ingroup python_interface_vertexseq * \brief Allocate a new vertex sequence object for a given graph * \return the allocated PyObject */ PyObject* igraphmodule_VertexSeq_new(PyTypeObject *subtype, PyObject *args, PyObject *kwds) { igraphmodule_VertexSeqObject *o; o=(igraphmodule_VertexSeqObject*)PyType_GenericNew(subtype, args, kwds); if (o == NULL) return NULL; igraph_vs_all(&o->vs); o->gref=0; o->weakreflist=0; RC_ALLOC("VertexSeq", o); return (PyObject*)o; } /** * \ingroup python_interface_vertexseq * \brief Copies a vertex sequence object * \return the copied PyObject */ igraphmodule_VertexSeqObject* igraphmodule_VertexSeq_copy(igraphmodule_VertexSeqObject* o) { igraphmodule_VertexSeqObject *copy; copy=(igraphmodule_VertexSeqObject*)PyType_GenericNew(Py_TYPE(o), 0, 0); if (copy == NULL) return NULL; if (igraph_vs_type(&o->vs) == IGRAPH_VS_VECTOR) { igraph_vector_t v; if (igraph_vector_copy(&v, o->vs.data.vecptr)) { igraphmodule_handle_igraph_error(); return 0; } if (igraph_vs_vector_copy(©->vs, &v)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&v); return 0; } igraph_vector_destroy(&v); } else { copy->vs = o->vs; } copy->gref = o->gref; if (o->gref) Py_INCREF(o->gref); RC_ALLOC("VertexSeq(copy)", copy); return copy; } /** * \ingroup python_interface_vertexseq * \brief Initialize a new vertex sequence object for a given graph * \return the initialized PyObject */ int igraphmodule_VertexSeq_init(igraphmodule_VertexSeqObject *self, PyObject *args, PyObject *kwds) { static char *kwlist[] = { "graph", "vertices", NULL }; PyObject *g, *vsobj=Py_None; igraph_vs_t vs; if (!PyArg_ParseTupleAndKeywords(args, kwds, "O!|O", kwlist, &igraphmodule_GraphType, &g, &vsobj)) return -1; if (vsobj == Py_None) { /* If vs is None, we are selecting all the vertices */ igraph_vs_all(&vs); } else if (PyInt_Check(vsobj)) { /* We selected a single vertex */ long int idx = PyInt_AsLong(vsobj); if (idx < 0 || idx >= igraph_vcount(&((igraphmodule_GraphObject*)g)->g)) { PyErr_SetString(PyExc_ValueError, "vertex index out of range"); return -1; } igraph_vs_1(&vs, (igraph_integer_t)idx); } else { igraph_vector_t v; igraph_integer_t n = igraph_vcount(&((igraphmodule_GraphObject*)g)->g); if (igraphmodule_PyObject_to_vector_t(vsobj, &v, 1)) return -1; if (!igraph_vector_isininterval(&v, 0, n-1)) { igraph_vector_destroy(&v); PyErr_SetString(PyExc_ValueError, "vertex index out of range"); return -1; } if (igraph_vs_vector_copy(&vs, &v)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&v); return -1; } igraph_vector_destroy(&v); } self->vs = vs; Py_INCREF(g); self->gref = (igraphmodule_GraphObject*)g; return 0; } /** * \ingroup python_interface_vertexseq * \brief Deallocates a Python representation of a given vertex sequence object */ void igraphmodule_VertexSeq_dealloc(igraphmodule_VertexSeqObject* self) { if (self->weakreflist != NULL) PyObject_ClearWeakRefs((PyObject *) self); if (self->gref) { igraph_vs_destroy(&self->vs); Py_DECREF(self->gref); self->gref=0; } Py_TYPE(self)->tp_free((PyObject*)self); RC_DEALLOC("VertexSeq", self); } /** * \ingroup python_interface_vertexseq * \brief Returns the length of the sequence */ int igraphmodule_VertexSeq_sq_length(igraphmodule_VertexSeqObject* self) { igraph_t *g; igraph_integer_t result; if (!self->gref) return -1; g=&GET_GRAPH(self); if (igraph_vs_size(g, &self->vs, &result)) { igraphmodule_handle_igraph_error(); return -1; } return (int)result; } /** * \ingroup python_interface_vertexseq * \brief Returns the item at the given index in the sequence */ PyObject* igraphmodule_VertexSeq_sq_item(igraphmodule_VertexSeqObject* self, Py_ssize_t i) { igraph_t *g; igraph_integer_t idx = -1; if (!self->gref) return NULL; g=&GET_GRAPH(self); switch (igraph_vs_type(&self->vs)) { case IGRAPH_VS_ALL: if (i < 0) { i = igraph_vcount(g) + i; } if (i >= 0 && i < igraph_vcount(g)) { idx = (igraph_integer_t)i; } break; case IGRAPH_VS_VECTOR: case IGRAPH_VS_VECTORPTR: if (i < 0) { i = igraph_vector_size(self->vs.data.vecptr) + i; } if (i >= 0 && i < igraph_vector_size(self->vs.data.vecptr)) { idx = (igraph_integer_t)VECTOR(*self->vs.data.vecptr)[i]; } break; case IGRAPH_VS_1: if (i == 0 || i == -1) { idx = self->vs.data.vid; } break; case IGRAPH_VS_SEQ: if (i < 0) { i = self->vs.data.seq.to - self->vs.data.seq.from + i; } if (i >= 0 && i < self->vs.data.seq.to - self->vs.data.seq.from) { idx = self->vs.data.seq.from + (igraph_integer_t)i; } break; /* TODO: IGRAPH_VS_ADJ, IGRAPH_VS_NONADJ - someday :) They are unused yet in the Python interface */ } if (idx < 0) { PyErr_SetString(PyExc_IndexError, "vertex index out of range"); return NULL; } return igraphmodule_Vertex_New(self->gref, idx); } /** \ingroup python_interface_vertexseq * \brief Returns the list of attribute names */ PyObject* igraphmodule_VertexSeq_attribute_names(igraphmodule_VertexSeqObject* self) { return igraphmodule_Graph_vertex_attributes(self->gref); } /** \ingroup python_interface_vertexseq * \brief Returns the list of values for a given attribute */ PyObject* igraphmodule_VertexSeq_get_attribute_values(igraphmodule_VertexSeqObject* self, PyObject* o) { igraphmodule_GraphObject *gr = self->gref; PyObject *result=0, *values, *item; long int i, n; if (!igraphmodule_attribute_name_check(o)) return 0; PyErr_Clear(); values=PyDict_GetItem(ATTR_STRUCT_DICT(&gr->g)[ATTRHASH_IDX_VERTEX], o); if (!values) { PyErr_SetString(PyExc_KeyError, "Attribute does not exist"); return NULL; } else if (PyErr_Occurred()) return NULL; switch (igraph_vs_type(&self->vs)) { case IGRAPH_VS_NONE: n = 0; result = PyList_New(0); break; case IGRAPH_VS_ALL: n = PyList_Size(values); result = PyList_New(n); if (!result) return 0; for (i=0; ivs.data.vecptr); result = PyList_New(n); if (!result) return 0; for (i=0; ivs.data.vecptr)[i]); Py_INCREF(item); PyList_SET_ITEM(result, i, item); } break; case IGRAPH_VS_SEQ: n = self->vs.data.seq.to - self->vs.data.seq.from; result = PyList_New(n); if (!result) return 0; for (i=0; ivs.data.seq.from+i); Py_INCREF(item); PyList_SET_ITEM(result, i, item); } break; default: PyErr_SetString(PyExc_RuntimeError, "invalid vertex selector"); } return result; } PyObject* igraphmodule_VertexSeq_get_attribute_values_mapping(igraphmodule_VertexSeqObject *self, PyObject *o) { long int index; /* Handle integer indices according to the sequence protocol */ if (PyIndex_Check(o)) { index = PyNumber_AsSsize_t(o, 0); return igraphmodule_VertexSeq_sq_item(self, index); } /* Handle strings according to the mapping protocol */ if (PyBaseString_Check(o)) return igraphmodule_VertexSeq_get_attribute_values(self, o); /* Handle iterables and slices by calling the select() method */ if (PySlice_Check(o) || PyObject_HasAttrString(o, "__iter__")) { PyObject *result, *args; args = Py_BuildValue("(O)", o); if (!args) return NULL; result = igraphmodule_VertexSeq_select(self, args); Py_DECREF(args); return result; } /* Handle everything else according to the mapping protocol */ return igraphmodule_VertexSeq_get_attribute_values(self, o); } /** \ingroup python_interface_vertexseq * \brief Sets the list of values for a given attribute */ int igraphmodule_VertexSeq_set_attribute_values_mapping(igraphmodule_VertexSeqObject* self, PyObject* attrname, PyObject* values) { PyObject *dict, *list, *item; igraphmodule_GraphObject *gr; igraph_vector_t vs; long i, j, n, no_of_nodes; gr = self->gref; dict = ATTR_STRUCT_DICT(&gr->g)[ATTRHASH_IDX_VERTEX]; if (!igraphmodule_attribute_name_check(attrname)) return -1; if (PyString_IsEqualToASCIIString(attrname, "name")) igraphmodule_invalidate_vertex_name_index(&gr->g); if (values == 0) { if (igraph_vs_type(&self->vs) == IGRAPH_VS_ALL) return PyDict_DelItem(dict, attrname); PyErr_SetString(PyExc_TypeError, "can't delete attribute from a vertex sequence not representing the whole graph"); return -1; } if (PyString_Check(values) || !PySequence_Check(values)) { /* If values is a string or not a sequence, we construct a list with a * single element (the value itself) and then call ourselves again */ int result; PyObject *newList = PyList_New(1); if (newList == 0) return -1; Py_INCREF(values); PyList_SET_ITEM(newList, 0, values); /* reference stolen here */ result = igraphmodule_VertexSeq_set_attribute_values_mapping(self, attrname, newList); Py_DECREF(newList); return result; } n=PySequence_Size(values); if (n<0) return -1; if (igraph_vs_type(&self->vs) == IGRAPH_VS_ALL) { no_of_nodes = (long)igraph_vcount(&gr->g); if (n == 0 && no_of_nodes > 0) { PyErr_SetString(PyExc_ValueError, "sequence must not be empty"); return -1; } /* Check if we already have attributes with the given name */ list = PyDict_GetItem(dict, attrname); if (list != 0) { /* Yes, we have. Modify its items to the items found in values */ for (i=0, j=0; ig, self->vs, &vs)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&vs); return -1; } no_of_nodes = (long)igraph_vector_size(&vs); if (n == 0 && no_of_nodes > 0) { PyErr_SetString(PyExc_ValueError, "sequence must not be empty"); igraph_vector_destroy(&vs); return -1; } /* Check if we already have attributes with the given name */ list = PyDict_GetItem(dict, attrname); if (list != 0) { /* Yes, we have. Modify its items to the items found in values */ for (i=0, j=0; ig); list = PyList_New(n2); if (list == 0) { igraph_vector_destroy(&vs); return -1; } for (i=0; igref->g, item, &i)) return NULL; /* We now have the ID of the vertex in the graph. If the vertex sequence * itself represents the full vertex sequence of the graph, we can return * here. If not, we have to check whether the vertex sequence contains this * ID or not. */ if (igraph_vs_is_all(&self->vs)) return PySequence_GetItem((PyObject*)self, i); if (igraph_vit_create(&self->gref->g, self->vs, &vit)) { igraphmodule_handle_igraph_error(); return NULL; } for (n = 0; !IGRAPH_VIT_END(vit); IGRAPH_VIT_NEXT(vit), n++) { if (IGRAPH_VIT_GET(vit) == i) { igraph_vit_destroy(&vit); return PySequence_GetItem((PyObject*)self, n); } } igraph_vit_destroy(&vit); PyErr_SetString(PyExc_ValueError, "vertex with the given name exists but not in the current sequence"); return NULL; } PyErr_SetString(PyExc_IndexError, "no such vertex"); return NULL; } /** * \ingroup python_interface_vertexseq * \brief Selects a subset of the vertex sequence based on some criteria */ PyObject* igraphmodule_VertexSeq_select(igraphmodule_VertexSeqObject *self, PyObject *args) { igraphmodule_VertexSeqObject *result; igraphmodule_GraphObject *gr; long i, j, n, m; gr=self->gref; result=igraphmodule_VertexSeq_copy(self); if (result==0) return NULL; /* First, filter by positional arguments */ n = PyTuple_Size(args); for (i=0; ivs); igraph_vs_none(&result->vs); /* We can simply bail out here */ return (PyObject*)result; } else if (PyCallable_Check(item)) { /* Call the callable for every vertex in the current sequence to * determine what's up */ igraph_bool_t was_excluded = 0; igraph_vector_t v; if (igraph_vector_init(&v, 0)) { igraphmodule_handle_igraph_error(); return 0; } m = PySequence_Size((PyObject*)result); for (j=0; jvs); if (igraph_vs_vector_copy(&result->vs, &v)) { Py_DECREF(result); igraph_vector_destroy(&v); igraphmodule_handle_igraph_error(); return NULL; } } igraph_vector_destroy(&v); } else if (PyInt_Check(item)) { /* Integers are treated specially: from now on, all remaining items * in the argument list must be integers and they will be used together * to restrict the vertex set. Integers are interpreted as indices on the * vertex set and NOT on the original, untouched vertex sequence of the * graph */ igraph_vector_t v, v2; if (igraph_vector_init(&v, 0)) { igraphmodule_handle_igraph_error(); return 0; } if (igraph_vector_init(&v2, 0)) { igraph_vector_destroy(&v); igraphmodule_handle_igraph_error(); return 0; } if (igraph_vs_as_vector(&gr->g, self->vs, &v2)) { igraph_vector_destroy(&v); igraph_vector_destroy(&v2); igraphmodule_handle_igraph_error(); return 0; } m = igraph_vector_size(&v2); for (; i= m || idx < 0) { PyErr_SetString(PyExc_ValueError, "vertex index out of range"); igraph_vector_destroy(&v); igraph_vector_destroy(&v2); return NULL; } if (igraph_vector_push_back(&v, VECTOR(v2)[idx])) { Py_DECREF(result); igraphmodule_handle_igraph_error(); igraph_vector_destroy(&v); igraph_vector_destroy(&v2); return NULL; } } igraph_vector_destroy(&v2); igraph_vs_destroy(&result->vs); if (igraph_vs_vector_copy(&result->vs, &v)) { Py_DECREF(result); igraphmodule_handle_igraph_error(); igraph_vector_destroy(&v); return NULL; } igraph_vector_destroy(&v); } else { /* Iterators, slices and everything that was not handled directly */ PyObject *iter=0, *item2; igraph_vector_t v, v2; /* Allocate stuff */ if (igraph_vector_init(&v, 0)) { igraphmodule_handle_igraph_error(); Py_DECREF(result); return 0; } if (igraph_vector_init(&v2, 0)) { igraph_vector_destroy(&v); Py_DECREF(result); igraphmodule_handle_igraph_error(); return 0; } if (igraph_vs_as_vector(&gr->g, self->vs, &v2)) { igraph_vector_destroy(&v); igraph_vector_destroy(&v2); Py_DECREF(result); igraphmodule_handle_igraph_error(); return 0; } m = igraph_vector_size(&v2); /* Create an appropriate iterator */ if (PySlice_Check(item)) { /* Create an iterator from the slice (which is not iterable by default) */ Py_ssize_t start, stop, step, sl; PyObject* range; igraph_bool_t ok; /* Casting to void* because Python 2.x expects PySliceObject* * but Python 3.x expects PyObject* */ ok = (PySlice_GetIndicesEx((void*)item, igraph_vector_size(&v2), &start, &stop, &step, &sl) == 0); if (ok) { range = igraphmodule_PyRange_create(start, stop, step); ok = (range != 0); } if (ok) { iter = PyObject_GetIter(range); Py_DECREF(range); ok = (iter != 0); } if (!ok) { igraph_vector_destroy(&v); igraph_vector_destroy(&v2); PyErr_SetString(PyExc_TypeError, "error while converting slice to iterator"); Py_DECREF(result); return 0; } } else { /* Simply create the iterator corresponding to the object */ iter = PyObject_GetIter(item); } /* Did we manage to get an iterator? */ if (iter == 0) { igraph_vector_destroy(&v); igraph_vector_destroy(&v2); PyErr_SetString(PyExc_TypeError, "invalid vertex filter among positional arguments"); Py_DECREF(result); return 0; } /* Do the iteration */ while ((item2=PyIter_Next(iter)) != 0) { if (PyInt_Check(item2)) { long idx = PyInt_AsLong(item2); Py_DECREF(item2); if (idx >= m || idx < 0) { PyErr_SetString(PyExc_ValueError, "vertex index out of range"); Py_DECREF(result); Py_DECREF(iter); igraph_vector_destroy(&v); igraph_vector_destroy(&v2); return NULL; } if (igraph_vector_push_back(&v, VECTOR(v2)[idx])) { Py_DECREF(result); Py_DECREF(iter); igraphmodule_handle_igraph_error(); igraph_vector_destroy(&v); igraph_vector_destroy(&v2); return NULL; } } else { /* We simply ignore elements that we don't know */ Py_DECREF(item2); } } /* Deallocate stuff */ igraph_vector_destroy(&v2); Py_DECREF(iter); if (PyErr_Occurred()) { igraph_vector_destroy(&v); Py_DECREF(result); return 0; } igraph_vs_destroy(&result->vs); if (igraph_vs_vector_copy(&result->vs, &v)) { Py_DECREF(result); igraphmodule_handle_igraph_error(); igraph_vector_destroy(&v); return NULL; } igraph_vector_destroy(&v); } } return (PyObject*)result; } /** * \ingroup python_interface_vertexseq * Converts a vertex sequence to an igraph vector containing the corresponding * vertex indices. The vector MUST be initialized and will be resized if needed. * \return 0 if everything was ok, 1 otherwise */ int igraphmodule_VertexSeq_to_vector_t(igraphmodule_VertexSeqObject *self, igraph_vector_t *v) { return igraph_vs_as_vector(&self->gref->g, self->vs, v); } /** * \ingroup python_interface_vertexseq * Returns the graph where the vertex sequence belongs */ PyObject* igraphmodule_VertexSeq_get_graph(igraphmodule_VertexSeqObject* self, void* closure) { Py_INCREF(self->gref); return (PyObject*)self->gref; } /** * \ingroup python_interface_vertexseq * Returns the indices of the vertices in this vertex sequence */ PyObject* igraphmodule_VertexSeq_get_indices(igraphmodule_VertexSeqObject* self, void* closure) { igraphmodule_GraphObject *gr = self->gref; igraph_vector_t vs; PyObject *result; if (igraph_vector_init(&vs, 0)) { igraphmodule_handle_igraph_error(); return 0; } if (igraph_vs_as_vector(&gr->g, self->vs, &vs)) { igraphmodule_handle_igraph_error(); igraph_vector_destroy(&vs); return 0; } result = igraphmodule_vector_t_to_PyList(&vs, IGRAPHMODULE_TYPE_INT); igraph_vector_destroy(&vs); return result; } /** * \ingroup python_interface_vertexseq * Returns the internal dictionary mapping vertex names to vertex IDs. */ PyObject* igraphmodule_VertexSeq__name_index(igraphmodule_VertexSeqObject* self, void* closure) { igraphmodule_GraphObject *gr = self->gref; PyObject* result = ATTR_NAME_INDEX(&gr->g); if (result == 0) Py_RETURN_NONE; Py_INCREF(result); return result; } /** * \ingroup python_interface_vertexseq * Re-creates the dictionary that maps vertex names to vertex IDs. */ PyObject* igraphmodule_VertexSeq__reindex_names(igraphmodule_VertexSeqObject* self) { igraphmodule_index_vertex_names(&self->gref->g, 1); Py_RETURN_NONE; } /** * \ingroup python_interface_vertexseq * Method table for the \c igraph.VertexSeq object */ PyMethodDef igraphmodule_VertexSeq_methods[] = { {"attribute_names", (PyCFunction)igraphmodule_VertexSeq_attribute_names, METH_NOARGS, "attribute_names() -> list\n\n" "Returns the attribute name list of the graph's vertices\n" }, {"find", (PyCFunction)igraphmodule_VertexSeq_find, METH_VARARGS, "find(condition) -> Vertex\n\n" "For internal use only.\n" }, {"get_attribute_values", (PyCFunction)igraphmodule_VertexSeq_get_attribute_values, METH_O, "get_attribute_values(attrname) -> list\n" "Returns the value of a given vertex attribute for all vertices in a list.\n\n" "The values stored in the list are exactly the same objects that are stored\n" "in the vertex attribute, meaning that in the case of mutable objects,\n" "the modification of the list element does affect the attribute stored in\n" "the vertex. In the case of immutable objects, modification of the list\n" "does not affect the attribute values.\n\n" "@param attrname: the name of the attribute\n" }, {"set_attribute_values", (PyCFunction)igraphmodule_VertexSeq_set_attribute_values, METH_VARARGS | METH_KEYWORDS, "set_attribute_values(attrname, values) -> list\n" "Sets the value of a given vertex attribute for all vertices\n\n" "@param attrname: the name of the attribute\n" "@param values: the new attribute values in a list\n" }, {"select", (PyCFunction)igraphmodule_VertexSeq_select, METH_VARARGS, "select(...) -> VertexSeq\n\n" "For internal use only.\n" }, {"_reindex_names", (PyCFunction)igraphmodule_VertexSeq__reindex_names, METH_NOARGS, "Re-creates the dictionary that maps vertex names to IDs.\n\n" "For internal use only.\n" }, {NULL} }; /** * \ingroup python_interface_vertexseq * This is the collection of functions necessary to implement the * vertex sequence as a real sequence (e.g. allowing to reference * vertices by indices) */ static PySequenceMethods igraphmodule_VertexSeq_as_sequence = { (lenfunc)igraphmodule_VertexSeq_sq_length, 0, /* sq_concat */ 0, /* sq_repeat */ (ssizeargfunc)igraphmodule_VertexSeq_sq_item, /* sq_item */ 0, /* sq_slice */ 0, /* sq_ass_item */ 0, /* sq_ass_slice */ 0, /* sq_contains */ 0, /* sq_inplace_concat */ 0, /* sq_inplace_repeat */ }; /** * \ingroup python_interface_vertexseq * This is the collection of functions necessary to implement the * vertex sequence as a mapping (which maps attribute names to values) */ static PyMappingMethods igraphmodule_VertexSeq_as_mapping = { /* this must be null, otherwise it f.cks up sq_length when inherited */ (lenfunc) 0, /* returns the values of an attribute by name */ (binaryfunc) igraphmodule_VertexSeq_get_attribute_values_mapping, /* sets the values of an attribute by name */ (objobjargproc) igraphmodule_VertexSeq_set_attribute_values_mapping, }; /** * \ingroup python_interface_vertexseq * Getter/setter table for the \c igraph.VertexSeq object */ PyGetSetDef igraphmodule_VertexSeq_getseters[] = { {"graph", (getter)igraphmodule_VertexSeq_get_graph, NULL, "The graph the vertex sequence belongs to", NULL, }, {"indices", (getter)igraphmodule_VertexSeq_get_indices, NULL, "The vertex indices in this vertex sequence", NULL, }, {"_name_index", (getter)igraphmodule_VertexSeq__name_index, NULL, "The internal index mapping vertex names to IDs", NULL }, {NULL} }; /** \ingroup python_interface_vertexseq * Python type object referencing the methods Python calls when it performs various operations on * a vertex sequence of a graph */ PyTypeObject igraphmodule_VertexSeqType = { PyVarObject_HEAD_INIT(0, 0) "igraph.core.VertexSeq", /* tp_name */ sizeof(igraphmodule_VertexSeqObject), /* tp_basicsize */ 0, /* tp_itemsize */ (destructor)igraphmodule_VertexSeq_dealloc, /* tp_dealloc */ 0, /* tp_print */ 0, /* tp_getattr */ 0, /* tp_setattr */ 0, /* tp_compare (2.x) / tp_reserved (3.x) */ 0, /* tp_repr */ 0, /* tp_as_number */ &igraphmodule_VertexSeq_as_sequence, /* tp_as_sequence */ &igraphmodule_VertexSeq_as_mapping, /* tp_as_mapping */ 0, /* tp_hash */ 0, /* tp_call */ 0, /* tp_str */ 0, /* tp_getattro */ 0, /* tp_setattro */ 0, /* tp_as_buffer */ Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE, /* tp_flags */ "Low-level representation of a vertex sequence.\n\n" /* tp_doc */ "Don't use it directly, use L{igraph.VertexSeq} instead.\n\n" "@deffield ref: Reference", 0, /* tp_traverse */ 0, /* tp_clear */ 0, /* tp_richcompare */ offsetof(igraphmodule_VertexSeqObject, weakreflist), /* tp_weaklistoffset */ 0, /* tp_iter */ 0, /* tp_iternext */ igraphmodule_VertexSeq_methods, /* tp_methods */ 0, /* tp_members */ igraphmodule_VertexSeq_getseters, /* tp_getset */ 0, /* tp_base */ 0, /* tp_dict */ 0, /* tp_descr_get */ 0, /* tp_descr_set */ 0, /* tp_dictoffset */ (initproc) igraphmodule_VertexSeq_init, /* tp_init */ 0, /* tp_alloc */ (newfunc) igraphmodule_VertexSeq_new, /* tp_new */ 0, /* tp_free */ 0, /* tp_is_gc */ 0, /* tp_bases */ 0, /* tp_mro */ 0, /* tp_cache */ 0, /* tp_subclasses */ 0, /* tp_weakreflist */ }; python-igraph-0.8.0/src/_igraph/platform.h0000644000076500000240000000177413104627150020745 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* vim: set ts=2 sw=2 sts=2 et: */ /* IGraph library. Copyright (C) 2006-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef PYTHON_PLATFORM_H #define PYTHON_PLATFORM_H #ifdef _MSC_VER # define INLINE __forceinline #else # define INLINE inline #endif #endif python-igraph-0.8.0/src/_igraph/arpackobject.c0000644000076500000240000002575313104627150021547 0ustar tamasstaff00000000000000/* vim:set ts=4 sw=2 sts=2 et: */ /* IGraph library. Copyright (C) 2007-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "arpackobject.h" #include "graphobject.h" #include "error.h" #include "py2compat.h" PyObject* igraphmodule_arpack_options_default; /** * \ingroup python_interface_arpack * \brief Checks if the object is an ARPACK parameter object */ int igraphmodule_ARPACKOptions_Check(PyObject *ob) { if (ob) return PyType_IsSubtype(ob->ob_type, &igraphmodule_ARPACKOptionsType); return 0; } /** * \ingroup python_interface_arpack * \brief Allocates a new ARPACK parameters object */ PyObject* igraphmodule_ARPACKOptions_new() { igraphmodule_ARPACKOptionsObject* self; self=PyObject_New(igraphmodule_ARPACKOptionsObject, &igraphmodule_ARPACKOptionsType); if (self) { igraph_arpack_options_init(&self->params); igraph_arpack_options_init(&self->params_out); } return (PyObject*)self; } /** * \ingroup python_interface_arpack * \brief Deallocates a Python representation of a given ARPACK parameters object */ void igraphmodule_ARPACKOptions_dealloc( igraphmodule_ARPACKOptionsObject* self) { /*igraph_arpack_options_destroy(&self->params);*/ PyObject_Del((PyObject*)self); } /** \ingroup python_interface_arpack * \brief Returns one of the attributes of a given ARPACK parameters object */ PyObject* igraphmodule_ARPACKOptions_getattr( igraphmodule_ARPACKOptionsObject* self, char* attrname) { PyObject *result = NULL; if (strcmp(attrname, "bmat") == 0) { char buf[2] = { self->params_out.bmat[0], 0 }; result=PyString_FromString(buf); } else if (strcmp(attrname, "n") == 0) { result=PyInt_FromLong(self->params_out.n); } else if (strcmp(attrname, "which") == 0) { char buf[3] = { self->params.which[0], self->params.which[1], 0 }; result=PyString_FromString(buf); } else if (strcmp(attrname, "nev") == 0) { result=PyInt_FromLong(self->params.nev); } else if (strcmp(attrname, "tol") == 0) { result=PyFloat_FromDouble((double)self->params.tol); } else if (strcmp(attrname, "ncv") == 0) { result=PyInt_FromLong(self->params.ncv); } else if (strcmp(attrname, "ldv") == 0) { result=PyInt_FromLong(self->params.ldv); } else if (strcmp(attrname, "ishift") == 0) { result=PyInt_FromLong(self->params.ishift); } else if (strcmp(attrname, "maxiter") == 0 || strcmp(attrname, "mxiter") == 0) { result=PyInt_FromLong(self->params.mxiter); } else if (strcmp(attrname, "nb") == 0) { result=PyInt_FromLong(self->params.nb); } else if (strcmp(attrname, "mode") == 0) { result=PyInt_FromLong(self->params.mode); } else if (strcmp(attrname, "start") == 0) { result=PyInt_FromLong(self->params.start); } else if (strcmp(attrname, "sigma") == 0) { result=PyFloat_FromDouble((double)self->params.sigma); } else if (strcmp(attrname, "info") == 0) { result=PyInt_FromLong(self->params_out.info); } else if (strcmp(attrname, "iter") == 0) { result=PyInt_FromLong(self->params_out.iparam[2]); } else if (strcmp(attrname, "nconv") == 0) { result=PyInt_FromLong(self->params_out.iparam[4]); } else if (strcmp(attrname, "numop") == 0) { result=PyInt_FromLong(self->params_out.iparam[8]); } else if (strcmp(attrname, "numopb") == 0) { result=PyInt_FromLong(self->params_out.iparam[9]); } else if (strcmp(attrname, "numreo") == 0) { result=PyInt_FromLong(self->params_out.iparam[10]); } else { PyErr_SetString(PyExc_AttributeError, attrname); } return result; } /** \ingroup python_interface_arpack * \brief Sets one of the attributes of a given ARPACK parameters object */ int igraphmodule_ARPACKOptions_setattr( igraphmodule_ARPACKOptionsObject* self, char* attrname, PyObject* value) { if (value == 0) { PyErr_SetString(PyExc_TypeError, "attribute can not be deleted"); return -1; } if (strcmp(attrname, "maxiter") == 0 || strcmp(attrname, "mxiter") == 0) { if (PyInt_Check(value)) { long int n=PyInt_AsLong(value); if (n>0) self->params.mxiter=(igraph_integer_t)n; else { PyErr_SetString(PyExc_ValueError, "maxiter must be positive"); return -1; } } else { PyErr_SetString(PyExc_ValueError, "integer expected"); return -1; } } else if (strcmp(attrname, "tol") == 0) { if (PyInt_Check(value)) { self->params.tol = (igraph_real_t) PyInt_AsLong(value); } else if (PyFloat_Check(value)) { self->params.tol = (igraph_real_t) PyFloat_AsDouble(value); } else { PyErr_SetString(PyExc_ValueError, "integer or float expected"); return -1; } } else { PyErr_SetString(PyExc_AttributeError, attrname); return -1; } return 0; } /** \ingroup python_interface_arpack */ igraph_arpack_options_t *igraphmodule_ARPACKOptions_get( igraphmodule_ARPACKOptionsObject *self) { self->params_out = self->params; self->params_out.iparam[0] = self->params.ishift; self->params_out.iparam[2] = self->params.mxiter; self->params_out.iparam[3] = self->params.nb; self->params_out.iparam[6] = self->params.mode; self->params_out.lworkl = 0; self->params_out.info = self->params.start; return &self->params_out; } /** \ingroup python_interface_arpack * \brief Formats an \c igraph.ARPACKOptions object in a * human-consumable format. * * \return the formatted textual representation as a \c PyObject */ PyObject* igraphmodule_ARPACKOptions_str( igraphmodule_ARPACKOptionsObject *self) { PyObject *s; s=PyString_FromFormat("ARPACK parameters"); return s; } /** * \ingroup python_interface_arpack * Method table for the \c igraph.ARPACKOptions object */ PyMethodDef igraphmodule_ARPACKOptions_methods[] = { /*{"attributes", (PyCFunction)igraphmodule_Edge_attributes, METH_NOARGS, "attributes() -> list\n\n" "Returns the attribute list of the graph's edges\n" },*/ {NULL} }; /** * \ingroup python_interface_edge * Getter/setter table for the \c igraph.ARPACKOptions object */ PyGetSetDef igraphmodule_ARPACKOptions_getseters[] = { /*{"tuple", (getter)igraphmodule_Edge_get_tuple, NULL, "Source and target node index of this edge as a tuple", NULL },*/ {NULL} }; /** \ingroup python_interface_edge * Python type object referencing the methods Python calls when it performs * various operations on an ARPACK parameters object */ PyTypeObject igraphmodule_ARPACKOptionsType = { PyVarObject_HEAD_INIT(0, 0) "igraph.ARPACKOptions", /* tp_name */ sizeof(igraphmodule_ARPACKOptionsObject), /* tp_basicsize */ 0, /* tp_itemsize */ (destructor)igraphmodule_ARPACKOptions_dealloc, /* tp_dealloc */ 0, /* tp_print */ (getattrfunc)igraphmodule_ARPACKOptions_getattr, /* tp_getattr */ (setattrfunc)igraphmodule_ARPACKOptions_setattr, /* tp_setattr */ 0, /* tp_compare (2.x) / tp_reserved (3.x) */ 0, /* tp_repr */ 0, /* tp_as_number */ 0, /* tp_as_sequence */ 0, /* tp_as_mapping */ 0, /* tp_hash */ 0, /* tp_call */ (reprfunc)igraphmodule_ARPACKOptions_str, /* tp_str */ 0, /* tp_getattro */ 0, /* tp_setattro */ 0, /* tp_as_buffer */ Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE, /* tp_flags */ "Class representing the parameters of the ARPACK module.\n\n" "ARPACK is a Fortran implementation of the implicitly restarted\n" "Arnoldi method, an algorithm for calculating some of the\n" "eigenvalues and eigenvectors of a given matrix. igraph uses this\n" "package occasionally, and this class can be used to fine-tune the\n" "behaviour of ARPACK in such cases.\n\n" "The class has several attributes which are not documented here,\n" "since they are usually of marginal use to the ordinary user.\n" "See the source code of the original ARPACK Fortran package\n" "(especially the file C{dsaupd.f}) for a detailed explanation of the\n" "parameters. Only the most basic attributes are explained here. Most\n" "of them are read only unless stated otherwise.\n\n" " - C{bmat}: type of the eigenproblem solved. C{'I'} means standard\n" " eigenproblem (A*x = lambda*x), C{'G'} means generalized\n" " eigenproblem (A*x = lambda*B*x).\n\n" " - C{n}: dimension of the eigenproblem\n\n" " - C{tol}: precision. If less than or equal to zero, the standard\n" " machine precision is used as computed by the LAPACK utility\n" " called C{dlamch}. This can be modified.\n\n" " - C{mxiter}: maximum number of update iterations to take. This\n" " can be modified. You can also use C{maxiter}.\n\n" " - C{iter}: actual number of update iterations taken\n\n" " - C{numop}: total number of OP*x operations\n\n" " - C{numopb}: total number of B*x operations if C{bmat} is C{'G'}\n\n" " - C{numreo}: total number of steps of re-orthogonalization\n\n" "", /* tp_doc */ 0, /* tp_traverse */ 0, /* tp_clear */ 0, /* tp_richcompare */ 0, /* tp_weaklistoffset */ 0, /* tp_iter */ 0, /* tp_iternext */ igraphmodule_ARPACKOptions_methods, /* tp_methods */ 0, /* tp_members */ igraphmodule_ARPACKOptions_getseters, /* tp_getset */ 0, /* tp_base */ 0, /* tp_dict */ 0, /* tp_descr_get */ 0, /* tp_descr_set */ 0, /* tp_dictoffset */ 0, /* tp_init */ 0, /* tp_alloc */ (newfunc)igraphmodule_ARPACKOptions_new, /* tp_new */ 0, /* tp_free */ }; python-igraph-0.8.0/src/_igraph/random.h0000644000076500000240000000201113104627150020362 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2006-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef PYTHON_RANDOM_H #define PYTHON_RANDOM_H #include void igraphmodule_init_rng(PyObject*); PyObject* igraph_rng_Python_set_generator(PyObject* self, PyObject* object); #endif python-igraph-0.8.0/src/_igraph/attributes.c0000644000076500000240000016577313616232155021321 0ustar tamasstaff00000000000000/* vim:set ts=2 sw=2 sts=2 et: */ /* IGraph library. Copyright (C) 2006-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include #include "attributes.h" #include "common.h" #include "convert.h" #include "py2compat.h" #include "pyhelpers.h" int igraphmodule_i_attribute_struct_init(igraphmodule_i_attribute_struct *attrs) { int i; for (i=0; i<3; i++) { attrs->attrs[i] = PyDict_New(); if (PyErr_Occurred()) return 1; RC_ALLOC("dict", attrs->attrs[i]); } attrs->vertex_name_index = 0; return 0; } void igraphmodule_i_attribute_struct_destroy(igraphmodule_i_attribute_struct *attrs) { int i; for (i=0; i<3; i++) { if (attrs->attrs[i]) { RC_DEALLOC("dict", attrs->attrs[i]); Py_DECREF(attrs->attrs[i]); } } if (attrs->vertex_name_index) { RC_DEALLOC("dict", attrs->vertex_name_index); Py_DECREF(attrs->vertex_name_index); } } int igraphmodule_i_attribute_struct_index_vertex_names( igraphmodule_i_attribute_struct *attrs, igraph_bool_t force) { Py_ssize_t n = 0; PyObject *name_list, *key, *value; if (attrs->vertex_name_index && !force) return 0; if (attrs->vertex_name_index == 0) { attrs->vertex_name_index = PyDict_New(); if (attrs->vertex_name_index == 0) { return 1; } } else PyDict_Clear(attrs->vertex_name_index); name_list = PyDict_GetItemString(attrs->attrs[1], "name"); if (name_list == 0) return 0; /* no name attribute */ n = PyList_Size(name_list) - 1; while (n >= 0) { key = PyList_GET_ITEM(name_list, n); /* we don't own a reference to key */ value = PyInt_FromLong(n); /* we do own a reference to value */ if (value == 0) return 1; if (PyDict_SetItem(attrs->vertex_name_index, key, value)) { /* probably unhashable vertex name. If the error is a TypeError, convert * it to a more readable error message */ if (PyErr_Occurred() && PyErr_ExceptionMatches(PyExc_TypeError)) { PyErr_Format( PyExc_RuntimeError, "error while indexing vertex names; did you accidentally try to " "use a non-hashable object as a vertex name earlier? " "Check the name of vertex %R (%R)", value, key ); } return 1; } /* PyDict_SetItem did an INCREF for both the key and a value, therefore we * have to drop our reference on value */ Py_DECREF(value); n--; } return 0; } void igraphmodule_i_attribute_struct_invalidate_vertex_name_index( igraphmodule_i_attribute_struct *attrs) { if (attrs->vertex_name_index == 0) return; Py_DECREF(attrs->vertex_name_index); attrs->vertex_name_index = 0; } void igraphmodule_invalidate_vertex_name_index(igraph_t *graph) { igraphmodule_i_attribute_struct_invalidate_vertex_name_index(ATTR_STRUCT(graph)); } void igraphmodule_index_vertex_names(igraph_t *graph, igraph_bool_t force) { igraphmodule_i_attribute_struct_index_vertex_names(ATTR_STRUCT(graph), force); } int igraphmodule_PyObject_matches_attribute_record(PyObject* object, igraph_attribute_record_t* record) { #ifndef IGRAPH_PYTHON3 int result; #endif if (record == 0) { return 0; } if (PyString_Check(object)) { return PyString_IsEqualToASCIIString(object, record->name); } #ifndef IGRAPH_PYTHON3 /* On Python 2.x, we need to handle Unicode strings as well because * the user might use 'from __future__ import unicode_literals', which * would turn some igraph attribute names into Unicode strings */ if (PyUnicode_Check(object)) { PyObject* ascii = PyUnicode_AsASCIIString(object); if (ascii == 0) { return 0; } result = PyString_IsEqualToASCIIString(ascii, record->name); Py_DECREF(ascii); return result; } #endif return 0; } int igraphmodule_get_vertex_id_by_name(igraph_t *graph, PyObject* o, igraph_integer_t* vid) { igraphmodule_i_attribute_struct* attrs = ATTR_STRUCT(graph); PyObject* o_vid = NULL; int tmp; if (graph) { attrs = ATTR_STRUCT(graph); if (igraphmodule_i_attribute_struct_index_vertex_names(attrs, 0)) return 1; o_vid = PyDict_GetItem(attrs->vertex_name_index, o); } if (o_vid == NULL) { #ifdef IGRAPH_PYTHON3 PyErr_Format(PyExc_ValueError, "no such vertex: %R", o); #else PyObject* s = PyObject_Repr(o); if (s) { PyErr_Format(PyExc_ValueError, "no such vertex: %s", PyString_AS_STRING(s)); Py_DECREF(s); } else { PyErr_Format(PyExc_ValueError, "no such vertex: %p", o); } #endif return 1; } if (!PyInt_Check(o_vid)) { PyErr_SetString(PyExc_ValueError, "non-numeric vertex ID assigned to vertex name. This is most likely a bug."); return 1; } if (PyInt_AsInt(o_vid, &tmp)) return 1; *vid = tmp; return 0; } /** * \brief Checks whether the given graph has the given graph attribute. * * \param graph the graph * \param name the name of the attribute being searched for */ igraph_bool_t igraphmodule_has_graph_attribute(const igraph_t *graph, const char* name) { PyObject *dict = ATTR_STRUCT_DICT(graph)[ATTRHASH_IDX_GRAPH]; return name != 0 && dict != 0 && PyDict_GetItemString(dict, name) != 0; } /** * \brief Checks whether the given graph has the given vertex attribute. * * \param graph the graph * \param name the name of the attribute being searched for */ igraph_bool_t igraphmodule_has_vertex_attribute(const igraph_t *graph, const char* name) { PyObject *dict = ATTR_STRUCT_DICT(graph)[ATTRHASH_IDX_VERTEX]; return name != 0 && dict != 0 && PyDict_GetItemString(dict, name) != 0; } /** * \brief Checks whether the given graph has the given edge attribute. * * \param graph the graph * \param name the name of the attribute being searched for */ igraph_bool_t igraphmodule_has_edge_attribute(const igraph_t *graph, const char* name) { PyObject *dict = ATTR_STRUCT_DICT(graph)[ATTRHASH_IDX_EDGE]; return name != 0 && dict != 0 && PyDict_GetItemString(dict, name) != 0; } /** * \brief Creates a new edge attribute and sets the values to None. * * This returns the actual list that we use to store the edge attributes, so * be careful when modifying it - any modification will propagate back to the * graph itself. You have been warned. * * \param graph the graph * \param name the name of the attribute being created * \returns a Python list of the values or \c NULL if the given * attribute exists already (no exception set). The returned * reference is borrowed. */ PyObject* igraphmodule_create_edge_attribute(const igraph_t* graph, const char* name) { PyObject *dict = ATTR_STRUCT_DICT(graph)[ATTRHASH_IDX_EDGE]; PyObject *values; Py_ssize_t i, n; if (dict == 0) { dict = ATTR_STRUCT_DICT(graph)[ATTRHASH_IDX_EDGE] = PyDict_New(); } if (PyDict_GetItemString(dict, name)) return 0; n = igraph_ecount(graph); values = PyList_New(n); if (values == 0) return 0; for (i = 0; i < n; i++) { Py_INCREF(Py_None); PyList_SET_ITEM(values, i, Py_None); /* reference stolen */ } if (PyDict_SetItemString(dict, name, values)) { Py_DECREF(values); return 0; } Py_DECREF(values); return values; } /** * \brief Returns the values of the given edge attribute for all edges in the * given graph. * * This returns the actual list that we use to store the edge attributes, so * be careful when modifying it - any modification will propagate back to the * graph itself. You have been warned. * * \param graph the graph * \param name the name of the attribute being searched for * \returns a Python list or \c NULL if there is no such attribute * (no exception set). The returned reference is borrowed. */ PyObject* igraphmodule_get_edge_attribute_values(const igraph_t* graph, const char* name) { PyObject *dict = ATTR_STRUCT_DICT(graph)[ATTRHASH_IDX_EDGE]; if (dict == 0) return 0; return PyDict_GetItemString(dict, name); } /** * \brief Returns the values of the given edge attribute for all edges in the * given graph, optionally creating it if it does not exist. * * This returns the actual list that we use to store the edge attributes, so * be careful when modifying it - any modification will propagate back to the * graph itself. You have been warned. * * \param graph the graph * \param name the name of the attribute being searched for * \returns a Python list (borrowed reference) */ PyObject* igraphmodule_create_or_get_edge_attribute_values(const igraph_t* graph, const char* name) { PyObject *dict = ATTR_STRUCT_DICT(graph)[ATTRHASH_IDX_EDGE], *result; if (dict == 0) return 0; result = PyDict_GetItemString(dict, name); if (result != 0) return result; return igraphmodule_create_edge_attribute(graph, name); } /* Attribute handlers for the Python interface */ /* Initialization */ static int igraphmodule_i_attribute_init(igraph_t *graph, igraph_vector_ptr_t *attr) { igraphmodule_i_attribute_struct* attrs; long int i, n; attrs=(igraphmodule_i_attribute_struct*)calloc(1, sizeof(igraphmodule_i_attribute_struct)); if (!attrs) IGRAPH_ERROR("not enough memory to allocate attribute hashes", IGRAPH_ENOMEM); if (igraphmodule_i_attribute_struct_init(attrs)) { PyErr_PrintEx(0); free(attrs); IGRAPH_ERROR("not enough memory to allocate attribute hashes", IGRAPH_ENOMEM); } graph->attr=(void*)attrs; /* See if we have graph attributes */ if (attr) { PyObject *dict=attrs->attrs[0], *value; char *s; n = igraph_vector_ptr_size(attr); for (i=0; itype) { case IGRAPH_ATTRIBUTE_NUMERIC: value=PyFloat_FromDouble((double)VECTOR(*(igraph_vector_t*)attr_rec->value)[0]); break; case IGRAPH_ATTRIBUTE_STRING: igraph_strvector_get((igraph_strvector_t*)attr_rec->value, 0, &s); if (s == 0) value=PyString_FromString(""); else value=PyString_FromString(s); break; case IGRAPH_ATTRIBUTE_BOOLEAN: value=VECTOR(*(igraph_vector_bool_t*)attr_rec->value)[0] ? Py_True : Py_False; Py_INCREF(value); break; default: IGRAPH_WARNING("unsupported attribute type (not string, numeric or Boolean)"); value=0; break; } if (value) { if (PyDict_SetItemString(dict, attr_rec->name, value)) { Py_DECREF(value); igraphmodule_i_attribute_struct_destroy(attrs); free(graph->attr); graph->attr = 0; IGRAPH_ERROR("failed to add attributes to graph attribute hash", IGRAPH_FAILURE); } Py_DECREF(value); value=0; } } } return IGRAPH_SUCCESS; } /* Destruction */ static void igraphmodule_i_attribute_destroy(igraph_t *graph) { igraphmodule_i_attribute_struct* attrs; /* printf("Destroying attribute table\n"); */ if (graph->attr) { attrs=(igraphmodule_i_attribute_struct*)graph->attr; igraphmodule_i_attribute_struct_destroy(attrs); free(attrs); } } /* Copying */ static int igraphmodule_i_attribute_copy(igraph_t *to, const igraph_t *from, igraph_bool_t ga, igraph_bool_t va, igraph_bool_t ea) { igraphmodule_i_attribute_struct *fromattrs, *toattrs; PyObject *key, *value, *newval, *o=NULL; igraph_bool_t copy_attrs[3] = { ga, va, ea }; int i, j; Py_ssize_t pos = 0; if (from->attr) { fromattrs=ATTR_STRUCT(from); /* what to do with the original value of toattrs? */ toattrs=(igraphmodule_i_attribute_struct*)calloc(1, sizeof(igraphmodule_i_attribute_struct)); if (!toattrs) IGRAPH_ERROR("not enough memory to allocate attribute hashes", IGRAPH_ENOMEM); if (igraphmodule_i_attribute_struct_init(toattrs)) { PyErr_PrintEx(0); free(toattrs); IGRAPH_ERROR("not enough memory to allocate attribute hashes", IGRAPH_ENOMEM); } to->attr=toattrs; for (i=0; i<3; i++) { if (!copy_attrs[i]) continue; if (!PyDict_Check(fromattrs->attrs[i])) { toattrs->attrs[i]=fromattrs->attrs[i]; Py_XINCREF(fromattrs->attrs[i]); continue; } pos = 0; while (PyDict_Next(fromattrs->attrs[i], &pos, &key, &value)) { /* value is only borrowed, so copy it */ if (i>0) { newval=PyList_New(PyList_GET_SIZE(value)); for (j=0; jattrs[i], key, newval); Py_DECREF(newval); /* compensate for PyDict_SetItem */ } } } return IGRAPH_SUCCESS; } /* Adding vertices */ static int igraphmodule_i_attribute_add_vertices(igraph_t *graph, long int nv, igraph_vector_ptr_t *attr) { /* Extend the end of every value in the vertex hash with nv pieces of None */ PyObject *key, *value, *dict; long int i, j, k, l; igraph_attribute_record_t *attr_rec; igraph_bool_t *added_attrs=0; Py_ssize_t pos = 0; if (!graph->attr) return IGRAPH_SUCCESS; if (nv<0) return IGRAPH_SUCCESS; if (attr) { added_attrs = (igraph_bool_t*)calloc((size_t)igraph_vector_ptr_size(attr), sizeof(igraph_bool_t)); if (!added_attrs) IGRAPH_ERROR("can't add vertex attributes", IGRAPH_ENOMEM); IGRAPH_FINALLY(free, added_attrs); } dict=ATTR_STRUCT_DICT(graph)[ATTRHASH_IDX_VERTEX]; if (!PyDict_Check(dict)) IGRAPH_ERROR("vertex attribute hash type mismatch", IGRAPH_EINVAL); while (PyDict_Next(dict, &pos, &key, &value)) { if (!PyList_Check(value)) IGRAPH_ERROR("vertex attribute hash member is not a list", IGRAPH_EINVAL); /* Check if we have specific values for the given attribute */ attr_rec=0; if (attr) { j=igraph_vector_ptr_size(attr); for (i=0; itype) { case IGRAPH_ATTRIBUTE_NUMERIC: o=PyFloat_FromDouble((double)VECTOR(*(igraph_vector_t*)attr_rec->value)[i]); break; case IGRAPH_ATTRIBUTE_STRING: igraph_strvector_get((igraph_strvector_t*)attr_rec->value, i, &s); o=PyString_FromString(s); break; case IGRAPH_ATTRIBUTE_BOOLEAN: o=VECTOR(*(igraph_vector_bool_t*)attr_rec->value)[i] ? Py_True : Py_False; Py_INCREF(o); break; default: IGRAPH_WARNING("unsupported attribute type (not string, numeric or Boolean)"); o=0; break; } if (o) { if (PyList_Append(value, o) == -1) IGRAPH_ERROR("can't extend a vertex attribute hash member", IGRAPH_FAILURE); else Py_DECREF(o); } } /* Invalidate the vertex name index if needed */ if (!strcmp(attr_rec->name, "name")) igraphmodule_i_attribute_struct_invalidate_vertex_name_index(ATTR_STRUCT(graph)); } else { for (i=0; itype) { case IGRAPH_ATTRIBUTE_NUMERIC: o=PyFloat_FromDouble((double)VECTOR(*(igraph_vector_t*)attr_rec->value)[i]); break; case IGRAPH_ATTRIBUTE_STRING: igraph_strvector_get((igraph_strvector_t*)attr_rec->value, i, &s); o=PyString_FromString(s); break; case IGRAPH_ATTRIBUTE_BOOLEAN: o=VECTOR(*(igraph_vector_bool_t*)attr_rec->value)[i] ? Py_True : Py_False; Py_INCREF(o); break; default: IGRAPH_WARNING("unsupported attribute type (not string, numeric or Boolean)"); o=0; break; } if (o) PyList_SET_ITEM(value, i+j, o); } /* Invalidate the vertex name index if needed */ if (!strcmp(attr_rec->name, "name")) igraphmodule_i_attribute_struct_invalidate_vertex_name_index(ATTR_STRUCT(graph)); PyDict_SetItemString(dict, attr_rec->name, value); Py_DECREF(value); /* compensate for PyDict_SetItemString */ } free(added_attrs); IGRAPH_FINALLY_CLEAN(1); } return IGRAPH_SUCCESS; } /* Permuting vertices */ static int igraphmodule_i_attribute_permute_vertices(const igraph_t *graph, igraph_t *newgraph, const igraph_vector_t *idx) { long int n, i; PyObject *key, *value, *dict, *newdict, *newlist, *o; Py_ssize_t pos=0; dict=ATTR_STRUCT_DICT(graph)[ATTRHASH_IDX_VERTEX]; if (!PyDict_Check(dict)) return 1; newdict=PyDict_New(); if (!newdict) return 1; n=igraph_vector_size(idx); pos=0; while (PyDict_Next(dict, &pos, &key, &value)) { newlist=PyList_New(n); for (i=0; iattr) return IGRAPH_SUCCESS; if (ne<0) return IGRAPH_SUCCESS; if (attr) { added_attrs = (igraph_bool_t*)calloc((size_t)igraph_vector_ptr_size(attr), sizeof(igraph_bool_t)); if (!added_attrs) IGRAPH_ERROR("can't add vertex attributes", IGRAPH_ENOMEM); IGRAPH_FINALLY(free, added_attrs); } dict=ATTR_STRUCT_DICT(graph)[ATTRHASH_IDX_EDGE]; if (!PyDict_Check(dict)) IGRAPH_ERROR("edge attribute hash type mismatch", IGRAPH_EINVAL); while (PyDict_Next(dict, &pos, &key, &value)) { if (!PyList_Check(value)) IGRAPH_ERROR("edge attribute hash member is not a list", IGRAPH_EINVAL); /* Check if we have specific values for the given attribute */ attr_rec=0; if (attr) { j=igraph_vector_ptr_size(attr); for (i=0; itype) { case IGRAPH_ATTRIBUTE_NUMERIC: o=PyFloat_FromDouble((double)VECTOR(*(igraph_vector_t*)attr_rec->value)[i]); break; case IGRAPH_ATTRIBUTE_STRING: igraph_strvector_get((igraph_strvector_t*)attr_rec->value, i, &s); o=PyString_FromString(s); break; case IGRAPH_ATTRIBUTE_BOOLEAN: o=VECTOR(*(igraph_vector_bool_t*)attr_rec->value)[i] ? Py_True : Py_False; Py_INCREF(o); break; default: IGRAPH_WARNING("unsupported attribute type (not string, numeric or Boolean)"); o=0; break; } if (o) { if (PyList_Append(value, o) == -1) IGRAPH_ERROR("can't extend an edge attribute hash member", IGRAPH_FAILURE); else Py_DECREF(o); } } } else { for (i=0; itype) { case IGRAPH_ATTRIBUTE_NUMERIC: o=PyFloat_FromDouble((double)VECTOR(*(igraph_vector_t*)attr_rec->value)[i]); break; case IGRAPH_ATTRIBUTE_STRING: igraph_strvector_get((igraph_strvector_t*)attr_rec->value, i, &s); o=PyString_FromString(s); break; case IGRAPH_ATTRIBUTE_BOOLEAN: o=VECTOR(*(igraph_vector_bool_t*)attr_rec->value)[i] ? Py_True : Py_False; Py_INCREF(o); break; default: IGRAPH_WARNING("unsupported attribute type (not string, numeric or Boolean)"); o=0; break; } if (o) PyList_SET_ITEM(value, i+j, o); } PyDict_SetItemString(dict, attr_rec->name, value); Py_DECREF(value); /* compensate for PyDict_SetItemString */ } free(added_attrs); IGRAPH_FINALLY_CLEAN(1); } return IGRAPH_SUCCESS; } /* Deleting edges, currently unused */ /* static void igraphmodule_i_attribute_delete_edges(igraph_t *graph, const igraph_vector_t *idx) { long int n, i, ndeleted=0; PyObject *key, *value, *dict, *o; Py_ssize_t pos=0; dict=ATTR_STRUCT_DICT(graph)[ATTRHASH_IDX_EDGE]; if (!PyDict_Check(dict)) return; n=igraph_vector_size(idx); for (i=0; iname != 0) { free((char*)ptr->name); ptr++; } free(records); } /* Auxiliary function for the common parts of * igraphmodule_i_attribute_combine_vertices and * igraphmodule_i_attribute_combine_edges */ static int igraphmodule_i_attribute_combine_dicts(PyObject *dict, PyObject *newdict, const igraph_vector_ptr_t *merges, const igraph_attribute_combination_t *comb) { PyObject *key, *value; Py_ssize_t pos; igraph_attribute_combination_record_t* todo; Py_ssize_t i, n; if (!PyDict_Check(dict) || !PyDict_Check(newdict)) return 1; /* Allocate memory for the attribute_combination_records */ n = PyDict_Size(dict); todo = (igraph_attribute_combination_record_t*)calloc( n+1, sizeof(igraph_attribute_combination_record_t) ); if (todo == 0) { IGRAPH_ERROR("cannot allocate memory for attribute combination", IGRAPH_ENOMEM); } for (i = 0; i < n+1; i++) todo[i].name = 0; /* sentinel elements */ IGRAPH_FINALLY(igraphmodule_i_free_attribute_combination_records, todo); /* Collect what to do for each attribute in the source dict */ pos = 0; i = 0; while (PyDict_Next(dict, &pos, &key, &value)) { todo[i].name = PyString_CopyAsString(key); if (todo[i].name == 0) IGRAPH_ERROR("PyString_CopyAsString failed", IGRAPH_FAILURE); igraph_attribute_combination_query(comb, todo[i].name, &todo[i].type, &todo[i].func); i++; } /* Combine the attributes. Here we make use of the fact that PyDict_Next * will iterate over the dict in the same order */ pos = 0; i = 0; while (PyDict_Next(dict, &pos, &key, &value)) { PyObject *empty_str; PyObject *func; PyObject *newvalue; /* Safety check */ if (!PyString_IsEqualToASCIIString(key, todo[i].name)) { IGRAPH_ERROR("PyDict_Next iteration order not consistent. " "This should never happen. Please report the bug to the igraph " "developers!", IGRAPH_FAILURE); } newvalue = 0; switch (todo[i].type) { case IGRAPH_ATTRIBUTE_COMBINE_DEFAULT: case IGRAPH_ATTRIBUTE_COMBINE_IGNORE: break; case IGRAPH_ATTRIBUTE_COMBINE_FUNCTION: func = (PyObject*)todo[i].func; newvalue = igraphmodule_i_ac_func(value, merges, func); break; case IGRAPH_ATTRIBUTE_COMBINE_SUM: newvalue = igraphmodule_i_ac_sum(value, merges); break; case IGRAPH_ATTRIBUTE_COMBINE_PROD: newvalue = igraphmodule_i_ac_prod(value, merges); break; case IGRAPH_ATTRIBUTE_COMBINE_MIN: newvalue = igraphmodule_i_ac_builtin_func(value, merges, "min"); break; case IGRAPH_ATTRIBUTE_COMBINE_MAX: newvalue = igraphmodule_i_ac_builtin_func(value, merges, "max"); break; case IGRAPH_ATTRIBUTE_COMBINE_RANDOM: newvalue = igraphmodule_i_ac_random(value, merges); break; case IGRAPH_ATTRIBUTE_COMBINE_FIRST: newvalue = igraphmodule_i_ac_first(value, merges); break; case IGRAPH_ATTRIBUTE_COMBINE_LAST: newvalue = igraphmodule_i_ac_last(value, merges); break; case IGRAPH_ATTRIBUTE_COMBINE_MEAN: newvalue = igraphmodule_i_ac_mean(value, merges); break; case IGRAPH_ATTRIBUTE_COMBINE_MEDIAN: newvalue = igraphmodule_i_ac_median(value, merges); break; case IGRAPH_ATTRIBUTE_COMBINE_CONCAT: empty_str = PyString_FromString(""); func = PyObject_GetAttrString(empty_str, "join"); newvalue = igraphmodule_i_ac_func(value, merges, func); Py_DECREF(func); Py_DECREF(empty_str); break; default: IGRAPH_ERROR("Unsupported combination type. " "This should never happen. Please report the bug to the igraph " "developers!", IGRAPH_FAILURE); } if (newvalue) { if (PyDict_SetItem(newdict, key, newvalue)) { Py_DECREF(newvalue); /* PyDict_SetItem does not steal reference */ IGRAPH_ERROR("PyDict_SetItem failed when combining attributes.", IGRAPH_FAILURE); } Py_DECREF(newvalue); /* PyDict_SetItem does not steal reference */ } else { /* We can arrive here for two reasons: first, if the attribute is to * be ignored explicitly; second, if there was an error. */ if (PyErr_Occurred()) { IGRAPH_ERROR("Unexpected failure when combining attributes", IGRAPH_FAILURE); } } i++; } igraphmodule_i_free_attribute_combination_records(todo); IGRAPH_FINALLY_CLEAN(1); return 0; } /* Combining vertices */ static int igraphmodule_i_attribute_combine_vertices(const igraph_t *graph, igraph_t *newgraph, const igraph_vector_ptr_t *merges, const igraph_attribute_combination_t *comb) { PyObject *dict, *newdict; int result; /* Get the attribute dicts */ dict=ATTR_STRUCT_DICT(graph)[ATTRHASH_IDX_VERTEX]; newdict=ATTR_STRUCT_DICT(newgraph)[ATTRHASH_IDX_VERTEX]; /* Combine the attribute dicts */ result = igraphmodule_i_attribute_combine_dicts(dict, newdict, merges, comb); /* Invalidate vertex name index */ igraphmodule_i_attribute_struct_invalidate_vertex_name_index(ATTR_STRUCT(graph)); return result; } /* Combining edges */ static int igraphmodule_i_attribute_combine_edges(const igraph_t *graph, igraph_t *newgraph, const igraph_vector_ptr_t *merges, const igraph_attribute_combination_t *comb) { PyObject *dict, *newdict; /* Get the attribute dicts */ dict=ATTR_STRUCT_DICT(graph)[ATTRHASH_IDX_EDGE]; newdict=ATTR_STRUCT_DICT(newgraph)[ATTRHASH_IDX_EDGE]; return igraphmodule_i_attribute_combine_dicts(dict, newdict, merges, comb); } /* Getting attribute names and types */ static int igraphmodule_i_attribute_get_info(const igraph_t *graph, igraph_strvector_t *gnames, igraph_vector_t *gtypes, igraph_strvector_t *vnames, igraph_vector_t *vtypes, igraph_strvector_t *enames, igraph_vector_t *etypes) { igraph_strvector_t *names[3] = { gnames, vnames, enames }; igraph_vector_t *types[3] = { gtypes, vtypes, etypes }; int retval; long int i, j, k, l, m; for (i=0; i<3; i++) { igraph_strvector_t *n = names[i]; igraph_vector_t *t = types[i]; PyObject *dict = ATTR_STRUCT_DICT(graph)[i]; PyObject *keys; PyObject *values; PyObject *o=0; keys=PyDict_Keys(dict); if (!keys) IGRAPH_ERROR("Internal error in PyDict_Keys", IGRAPH_FAILURE); if (n) { retval = igraphmodule_PyList_to_strvector_t(keys, n); if (retval) return retval; } if (t) { k=PyList_Size(keys); igraph_vector_resize(t, k); for (j=0; j0) { for (i=0; iob_type) : 0; if (type_str != 0) { PyErr_Format(PyExc_TypeError, "igraph supports string attribute names only, got %s", PyString_AS_STRING(type_str)); Py_DECREF(type_str); } else { PyErr_Format(PyExc_TypeError, "igraph supports string attribute names only"); } return 0; } python-igraph-0.8.0/src/_igraph/filehandle.c0000644000076500000240000003050113250445624021203 0ustar tamasstaff00000000000000/* -*- mode: C -*- */ /* IGraph library. Copyright (C) 2010-2012 Tamas Nepusz This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "filehandle.h" #include "py2compat.h" #include "pyhelpers.h" #ifndef PYPY_VERSION # ifndef IGRAPH_PYTHON3 static int igraphmodule_i_filehandle_init_cpython_2(igraphmodule_filehandle_t* handle, PyObject* object, char* mode) { FILE* fp; PyObject* fileno_method; PyObject* fileno_result; int fileno = -1; if (object == 0) { PyErr_SetString(PyExc_TypeError, "trying to convert a null object " "to a file handle"); return 1; } handle->object = 0; handle->need_close = 0; if (PyBaseString_Check(object)) { /* We have received a string; we need to open the file denoted by this * string now and mark that we opened the file ourselves (so we need * to close it when igraphmodule_filehandle_destroy is invoked). */ handle->object = PyFile_FromString(PyString_AsString(object), mode); if (handle->object == 0) { /* Could not open the file; just return an error code because an * exception was raised already */ return 1; } /* Remember that we need to close the file ourselves */ handle->need_close = 1; /* Get a FILE* object from the file */ fp = PyFile_AsFile(handle->object); } else if (PyFile_Check(object)) { /* This is a file-like object; store a reference for it and * we will handle it later */ handle->object = object; Py_INCREF(handle->object); /* Get a FILE* object from the file */ fp = PyFile_AsFile(handle->object); } else { /* Check whether the object has a fileno() method. If so, we convert * that to a file descriptor and then fdopen() it */ fileno_method = PyObject_GetAttrString(object, "fileno"); if (fileno_method != 0) { if (PyCallable_Check(fileno_method)) { fileno_result = PyObject_CallObject(fileno_method, 0); Py_DECREF(fileno_method); if (fileno_result != 0) { if (PyInt_Check(fileno_result)) { fileno = (int)PyInt_AsLong(fileno_result); Py_DECREF(fileno_result); } else { Py_DECREF(fileno_result); PyErr_SetString(PyExc_TypeError, "fileno() method of file-like object should return " "an integer"); return 1; } } else { /* Exception set already by PyObject_CallObject() */ return 1; } } else { Py_DECREF(fileno_method); PyErr_SetString(PyExc_TypeError, "fileno() attribute of file-like object must be callable"); return 1; } } else { PyErr_SetString(PyExc_TypeError, "expected filename or file-like object"); return 1; } if (fileno > 0) { fp = fdopen(fileno, mode); } else { PyErr_SetString(PyExc_ValueError, "fileno() method returned invalid " "file descriptor"); return 1; } } handle->fp = fp; if (handle->fp == 0) { igraphmodule_filehandle_destroy(handle); /* This already called Py_DECREF(handle->object), no need to call it */ PyErr_SetString(PyExc_RuntimeError, "PyFile_AsFile() failed unexpectedly"); return 1; } return 0; } # else /* IGRAPH_PYTHON3 */ static int igraphmodule_i_filehandle_init_cpython_3(igraphmodule_filehandle_t* handle, PyObject* object, char* mode) { int fp; if (object == 0 || PyLong_Check(object)) { PyErr_SetString(PyExc_TypeError, "string or file-like object expected"); return 1; } handle->need_close = 0; handle->object = 0; if (PyBaseString_Check(object)) { /* We have received a string; we need to open the file denoted by this * string now and mark that we opened the file ourselves (so we need * to close it when igraphmodule_filehandle_destroy is invoked). */ handle->object = PyFile_FromObject(object, mode); if (handle->object == 0) { /* Could not open the file; just return an error code because an * exception was raised already */ return 1; } /* Remember that we need to close the file ourselves */ handle->need_close = 1; } else { /* This is probably a file-like object; store a reference for it and * we will handle it later */ handle->object = object; Py_INCREF(handle->object); } /* At this stage, handle->object is something we can handle. * We have to call PyObject_AsFileDescriptor instead * and then fdopen() it to get the corresponding FILE* object. */ fp = PyObject_AsFileDescriptor(handle->object); if (fp == -1) { igraphmodule_filehandle_destroy(handle); /* This already called Py_DECREF(handle->object), no need to call it */ return 1; } handle->fp = fdopen(fp, mode); if (handle->fp == 0) { igraphmodule_filehandle_destroy(handle); /* This already called Py_DECREF(handle->object), no need to call it */ PyErr_SetString(PyExc_RuntimeError, "fdopen() failed unexpectedly"); return 1; } return 0; } # endif /* IGRAPH_PYTHON3 */ #endif /* PYPY_VERSION */ #ifdef PYPY_VERSION # ifndef IGRAPH_PYTHON3 static int igraphmodule_i_filehandle_init_pypy_2(igraphmodule_filehandle_t* handle, PyObject* object, char* mode) { int fp; PyObject* fpobj; char* fname; if (object == 0) { PyErr_SetString(PyExc_TypeError, "trying to convert a null object " "to a file handle"); return 1; } handle->need_close = 0; handle->object = 0; if (PyBaseString_Check(object)) { /* We have received a string; we need to open the file denoted by this * string now and mark that we opened the file ourselves (so we need * to close it when igraphmodule_filehandle_destroy is invoked). */ handle->object = PyFile_FromString(PyString_AsString(object), mode); if (handle->object == 0) { /* Could not open the file; just return an error code because an * exception was raised already */ return 1; } /* Remember that we need to close the file ourselves */ handle->need_close = 1; } else { /* This is probably a file-like object; store a reference for it and * we will handle it later */ handle->object = object; Py_INCREF(handle->object); } /* PyPy does not have PyFile_AsFile, so we will try to access the file * descriptor instead by calling its fileno() method and then opening the * file handle with fdopen */ fpobj = PyObject_CallMethod(handle->object, "fileno", 0); if (fpobj == 0 || !PyInt_Check(fpobj)) { if (fpobj != 0) { Py_DECREF(fpobj); } igraphmodule_filehandle_destroy(handle); /* This already called Py_DECREF(handle->object), no need to call it. * Also, an exception was raised by PyObject_CallMethod so no need to * raise one ourselves */ return 1; } fp = (int)PyInt_AsLong(fpobj); Py_DECREF(fpobj); handle->fp = fdopen(fp, mode); if (handle->fp == 0) { igraphmodule_filehandle_destroy(handle); /* This already called Py_DECREF(handle->object), no need to call it */ PyErr_SetString(PyExc_RuntimeError, "fdopen() failed unexpectedly"); return 1; } return 0; } # else /* IGRAPH_PYTHON3 */ static int igraphmodule_i_filehandle_init_pypy_3(igraphmodule_filehandle_t* handle, PyObject* object, char* mode) { int fp; if (object == 0 || PyLong_Check(object)) { PyErr_SetString(PyExc_TypeError, "string or file-like object expected"); return 1; } handle->need_close = 0; if (PyBaseString_Check(object)) { /* We have received a string; we need to open the file denoted by this * string now and mark that we opened the file ourselves (so we need * to close it when igraphmodule_filehandle_destroy is invoked). */ handle->object = PyFile_FromObject(object, mode); if (handle->object == 0) { /* Could not open the file; just return an error code because an * exception was raised already */ return 1; } /* Remember that we need to close the file ourselves */ handle->need_close = 1; } else { /* This is probably a file-like object; store a reference for it and * we will handle it later */ handle->object = object; Py_INCREF(handle->object); } /* At this stage, handle->object is something we can handle. * We have to call PyObject_AsFileDescriptor instead * and then fdopen() it to get the corresponding FILE* object. */ fp = PyObject_AsFileDescriptor(handle->object); if (fp == -1) { igraphmodule_filehandle_destroy(handle); /* This already called Py_DECREF(handle->object), no need to call it */ return 1; } handle->fp = fdopen(fp, mode); if (handle->fp == 0) { igraphmodule_filehandle_destroy(handle); /* This already called Py_DECREF(handle->object), no need to call it */ PyErr_SetString(PyExc_RuntimeError, "fdopen() failed unexpectedly"); return 1; } return 0; } # endif /* IGRAPH_PYTHON3 */ #endif /** * \ingroup python_interface_filehandle * \brief Constructs a new file handle object from a Python object. * * \return 0 if everything was OK, 1 otherwise. An appropriate Python * exception is raised in this case. */ int igraphmodule_filehandle_init(igraphmodule_filehandle_t* handle, PyObject* object, char* mode) { #ifdef PYPY_VERSION # ifdef IGRAPH_PYTHON3 return igraphmodule_i_filehandle_init_pypy_3(handle, object, mode); # else return igraphmodule_i_filehandle_init_pypy_2(handle, object, mode); # endif #else # ifdef IGRAPH_PYTHON3 return igraphmodule_i_filehandle_init_cpython_3(handle, object, mode); # else return igraphmodule_i_filehandle_init_cpython_2(handle, object, mode); # endif #endif } /** * \ingroup python_interface_filehandle * \brief Destroys the file handle object. */ void igraphmodule_filehandle_destroy(igraphmodule_filehandle_t* handle) { PyObject *exc_type = 0, *exc_value = 0, *exc_traceback = 0; if (handle->fp != 0) { fflush(handle->fp); if (handle->need_close && !handle->object) { fclose(handle->fp); } } handle->fp = 0; if (handle->object != 0) { /* PyFile_Close might mess up the stored exception, so let's * store the current exception state and restore it */ PyErr_Fetch(&exc_type, &exc_value, &exc_traceback); if (handle->need_close) { if (PyFile_Close(handle->object)) { PyErr_WriteUnraisable(Py_None); } } Py_DECREF(handle->object); PyErr_Restore(exc_type, exc_value, exc_traceback); exc_type = exc_value = exc_traceback = 0; handle->object = 0; } handle->need_close = 0; } /** * \ingroup python_interface_filehandle * \brief Returns the file encapsulated by the given \c igraphmodule_filehandle_t. */ FILE* igraphmodule_filehandle_get(const igraphmodule_filehandle_t* handle) { return handle->fp; } python-igraph-0.8.0/src/_igraph/pyhelpers.c0000644000076500000240000000734113104627150021123 0ustar tamasstaff00000000000000/* vim:set ts=4 sw=2 sts=2 et: */ /* IGraph library - Python interface. Copyright (C) 2006-2011 Tamas Nepusz 5 Avenue Road, Staines, Middlesex, TW18 3AW, United Kingdom This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "py2compat.h" #include "pyhelpers.h" /** * Creates a Python list and fills it with a pre-defined item. * * \param len the length of the list to be created * \param item the item with which the list will be filled */ PyObject* igraphmodule_PyList_NewFill(Py_ssize_t len, PyObject* item) { Py_ssize_t i; PyObject* result = PyList_New(len); if (result == 0) return 0; for (i = 0; i < len; i++) { Py_INCREF(item); PyList_SET_ITEM(result, i, item); /* reference to item stolen */ } return result; } /** * Creates a Python list and fills it with zeroes. * * \param len the length of the list to be created */ PyObject* igraphmodule_PyList_Zeroes(Py_ssize_t len) { PyObject* zero = PyInt_FromLong(0); PyObject* result; if (zero == 0) return 0; result = igraphmodule_PyList_NewFill(len, zero); Py_DECREF(zero); return result; } /** * Converts a Python object to its string representation and returns it as * a C string. * * It is the responsibility of the caller to release the C string. */ char* igraphmodule_PyObject_ConvertToCString(PyObject* string) { char* result; if (string == 0) return 0; if (!PyBaseString_Check(string)) { string = PyObject_Str(string); if (string == 0) return 0; } else { Py_INCREF(string); } result = PyString_CopyAsString(string); Py_DECREF(string); return result; } /** * Creates a Python range object with the given start and stop indices and step * size. * * The function returns a new reference. It is the responsibility of the caller * to release it. Returns \c NULL in case of an error. */ PyObject* igraphmodule_PyRange_create(Py_ssize_t start, Py_ssize_t stop, Py_ssize_t step) { static PyObject* builtin_module = 0; static PyObject* range_func = 0; PyObject* result; if (builtin_module == 0) { #ifdef IGRAPH_PYTHON3 builtin_module = PyImport_ImportModule("builtins"); #else builtin_module = PyImport_ImportModule("__builtin__"); #endif if (builtin_module == 0) { return 0; } } if (range_func == 0) { #ifdef IGRAPH_PYTHON3 range_func = PyObject_GetAttrString(builtin_module, "range"); #else range_func = PyObject_GetAttrString(builtin_module, "xrange"); #endif if (range_func == 0) { return 0; } } result = PyObject_CallFunction(range_func, "lll", start, stop, step); return result; } /** * Generates a hash value for a plain C pointer. * * This function is a copy of \c _Py_HashPointer from \c Objects/object.c in * the source code of Python's C implementation. */ long igraphmodule_Py_HashPointer(void *p) { long x; size_t y = (size_t)p; /* bottom 3 or 4 bits are likely to be 0; rotate y by 4 to avoid * excessive hash collisions for dicts and sets */ y = (y >> 4) | (y << (8 * sizeof(p) - 4)); x = (long)y; if (x == -1) x = -2; return x; }